pytorch-tabular-pss3e17.ipynb

{"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"name":"python","version":"3.10.10","mimetype":"text/x-python","codemirror_mode":{"name":"ipython","version":3},"pygments_lexer":"ipython3","nbconvert_exporter":"python","file_extension":".py"}},"nbformat_minor":4,"nbformat":4,"cells":[{"source":"<a href=\"https://www.kaggle.com/code/averma111/pytorch-tabular-pss3e17?scriptVersionId=134762243\" target=\"_blank\"><img align=\"left\" alt=\"Kaggle\" title=\"Open in Kaggle\" src=\"https://kaggle.com/static/images/open-in-kaggle.svg\"></a>","metadata":{},"cell_type":"markdown"},{"cell_type":"markdown","source":"<div style=\"color:white;\n           display:fill;\n           border-radius:5px;\n           background-color:#4270c5;\n           font-size:110%;\n           font-family:sans-serif;\n           letter-spacing:0.2px\">\n\n<p style=\"padding: 30px;\n              color:white;\">\nBINARY CLASSIFICATION OF MACHINE FAILURES\n</p>\n</div>","metadata":{}},{"cell_type":"markdown","source":"![image.png](attachment:3a970f42-6caa-45f7-b74d-4de31a4b3bf8.png)","metadata":{},"attachments":{"3a970f42-6caa-45f7-b74d-4de31a4b3bf8.png":{"image/png":"iVBORw0KGgoAAAANSUhEUgAAA8oAAAEQCAYAAABoVY1UAAAAAXNSR0IArs4c6QAAAARnQU1BAACxjwv8YQUAAAAJcEhZcwAADsMAAA7DAcdvqGQAANurSURBVHhe7J0NXFRV/v8/u7TjmqNsw2pQBqigBtiG9BPxL2miFkbBsuFPf/LTH25ubKblptViD2I+ZSItiAvhysrKxmqxUiQlYRIuiglYIqmQAmmwsUyhk8SsNP9zH4a5M8zMvTMMqO333WvynnvuPQ/fp3POfeJHBgYIgiAIgiAIgiAIguD5sfgvQRAEQRAEQRAEQRAMWigTBEEQBEEQBEEQhARaKBMEQRAEQRAEQRCEBFooEwRBEARBEARBEIQEWigTBEEQBEEQBEEQhARaKBMEQRAEQRAEQRCEBFooEwRBEARBEARBEIQEWigTBEEQBEEQBEEQhARaKBMEQRAEQRAEQRCEBFooEwRBEARBEARBEIQEWigTBEEQBEEQBEEQhARaKBMEQRAEQRAEQRCEBFooEwRBEARBEARBEIQEWigTBEEQBEEQBEEQhARaKBMEQRAEQRAEQRCEBEULZb1OB12HjZ9ObzzItN2PcG3Rd4uJGxjdmWLkp6cju6gB/So1Ob10a1FbWgPtD0CmzqJvrkT1GZ2YssJAyejiYeQX1MHYEj3zr/6w9f4qVw5ZOV8LOpl/9H/Yso22EgU7DkMrJonrEDkb6W5FdR6L5el5qG4T992gXPPxlZN1p7h9TdChpaISTddZmHKYbj2bnzkQ2AZk/jYAsnW03/2Ey8fYrku49HWXmLBO19fsGPuHKIerz15hV9tQzeZEbVfFtKvh+2vl962YL0dbDT6sEYPx1S7+3K7+aqs1erXfVYqxAte/Hl114YvDR9CgVE5W6Go6goqz/djeGxBFC+UDz8YgMsbG79lifpKnLUrq2e4/Wvm2ZNeISVn0aKlhgXkgZ6HaBlTXtNpf/J7JQeLyQlz2m4QgHzVU4u6+o0VTRQ1aJBMNWb00FGLTuo040CCmf/BYykiHIzuSsSrvmGmBerEG1Q0SiQ2IjLQoeW0L9P4BUPPpGmTHJOFAHyfevfrCl+uID3H0tivH6S3n64HarBisLWoVU5b0Q/ywjA+aYPi2bcCu8ms/ufuh0dv2ncO+jehQlrwYW894IijADx6C896gODq+uh5O1pFZ17ABHceQm5yM/MobfKXcVoy1MVmoFZNyyM0TXOJLAyFbB/vtClwzxtqn7Z2n8YuQB7DtpLjDkqbd+J+QEDz1jmuu1PH1PfU2bJZ27m08u+T32HdOTLsYob8hvX/pyoTa8PffY/Ezb4Ofsv3rbTwV8jT2/YvPGhB6tz8Io0IWMpu4JB7hQk6kmnR1qQwZiUuw47DSei6h4XANvuhZF1/ChxlLsHhHGdsijChaKEdlfIDyD4XfH6PZjuhXe9LlGdHQCIddh2hRtWM1ivrJma1yrhhP7qi0vxi4rEOTXyR+FRmKsAme4k5X0ISi1Tmo6hCTShiXgN0f7sG8cWL6B4+ljNSYtnY/StfOEBeobOpbmYMni5rEFGMgZFS3F9ktcZg2QUy7iF59cQon7KoXveV8/dMP8aNXfFBh4qxIFL1del1dQPgh4Brbl0OHy+16hD0ch7CIUPgMFncTNybuM/Ds+/vxbMQNfcXD5bjEl36gsh2YOMNxAdsKjsDavb5Tb/8J1eL2gDD21yg59x6WjBXT/cH0DTh2rh7npb/ngsVM+/j95j2cL/k1/MT0NcGi/Z9sC8CeX/0ehV+L+f3BsNnYVFuLTfcPE3fI8Tn2LNyOip42DcMDm2txevNstkUYcVvDELcV8dXRXLyL2Vg82UvcI9D5WTHyz49GlN957E1NQca7n6L7Z4G4c6T5zEFbkYedmduRd/AMOgePxp132Ama3WxB+eFe5GzbjHc/7sTP7hyNy4cK0BG8EJNuE49prURBTi7y0t/GJ9pODL1jPEYM4TKaUZaejw8+acCF9g60tKkwLshLuHtr8xwB3fmDKMrYjlf/WoYLHWr4BY7EYMklBVt90NXsxa6Ccnzy+UXo2xqgHxEK31v4rB5aDqQj/72anmNaVExGXsI9Zduy4fpyALqRg/DJ7hSk7dcjdLo/zCTbUYOC7Ddx9LMGtF5pQ+O3XggZ4y6vF/68w+geH4gRP2Xp7lbU7stD5h9eQ8mJDnTf6o8xP7dzz7ujASW7M5GzlZNlN34+xh8eXDki3CPmBZmvY+u+4+j83gu+ozVQibLk5XVyEMZdrUT2hmS8zev4LnhdqUHRrm3IeKMSnUP9zeV7cigmXK3ATtaXXBs2ZLNOGzLidfK5aTvvwAl81vgvdF/QYhAnly4LGdmrg8vr1c6L6NaMxlgv27Po+oJ1OOgTjyX3DBf3tOLjXSfws1+GQvdOKjI2W5evPflb7ctPuXJLgIgo3FTGlZuHw61u8L3THz+zpmY7Miu55IObT+QhLaUIzCDhy/mQHd+Sylko9zP8LLAbR3cwm/7TQVzQazBqrJeZr5nBPeL6Rg7y/5zO4kEHrgz1MclUYXna44XYnfEar5ObRo7H0IZ8fOIei1l3WsYhO/GDb0cWsrfnouxMB4aOZjYrPb2jGUfeykAWJ9vzLN+f5TMZ2IwPt/wb2lcLcfmBSIy1bAZDz2xt5z/+jQnjh8ON38O1LRf1Q4MxZriwR19XiJ2HOjEuUFmMM8qBiwec/Y7114hlW4HF4fr385D7xxQxDo9E+zs78NkQSXyTscOSS/64tbkAmVuFWD7YdzTucJcYnD2Zirq9efRXOJj6B7x6diSiJzI/sWMP1m2fz5IdgxTbCN+ut/EPo43UfYvbQkfhR2JcG/WvYr6/TbfFIuhWdrxduxFj/GgPXNizEZuymP26+WCCvwpfle7Fjm3bUfK5G24ba+H/UkQ95f85S+gbRmLMaHe7epUdX+VsnWFTnlZ88pyV8VSKtfmFXX3ZsQHrdtMpyNnfCxcKxLjaeROL36MwlDdHwbeaRN9UFMuV+EcPTupZZpw1xRyuP+4Y56PD4YIO/OL/QjFCPMReGcZ5wvwHx5vPKxhWfYkfE635pD0bNJdtn+MCh5J+W2JHDo6O3dbjjMIxVk6nEq7UvYPsn4zFrDc/BRY+iPHS5nQdQcZvPoVbUCt+OuHXiA4QA/3VNlS88Tp2bN+EPZVX8O0tdyCIG4gktB3ejT/8YQsyD5zBt0PG4RfeQj5fX/0YzL3zHHI2rMeGv3+Kqx6B+MUd4vmXapC7vRTdgUwfgy7gvdS3cWm8F84XbMGGF/bi4++HwG+ML6SqxKU6FO7ajj+sZfmXv8cI/3EYMUjMs8BY/5LoQJi3WELrEeRm70TmJq68K3D3DuTHWY5Lx3dj24fdCLrLC4N0rN4/fQ6/Xz+MIDXX1j+h4bYw+P1MOFboy0lowsaAzUzwxfupKPzmDgyp+hPWrn8HmBoBP67cPrZ/0B3j4F6bhA/V/4cH/Ac5X09rDf6W/So2/vF9NN7kh5Chddj2sUasy1r/bJTH9/sv+PBYHS5c/RoNXXdgit8wvl07Phe2eXg7SkfKltfx3qlvMWzsXTCFYAW65x7TL3gdr2zahMLqK+geGYjxHjeJmTcGtqakznExD1vzdQh6MAFPzBqKkhcXI+O48ZFCPWq3x2NBjhZjWf6iGd6oT1+MJ/ObxXxLdKhl+YvztQh6ZBliw1QoeWEDPpLe1arLQvz8FNQPn4xFSQmYjFI8uTQdtfwjomr4hgTAhynUY9wkhIwTJ5B2zxHyExP3oD0kAeuTHoHXmRQsT68RH5W03wfVCGa04zxY1T4ICpkEX87rLBg6mmuL6ZixI7hWWZT7YADacxYjvqfedtQWFCJjzRac9YzAooeDe9+VU7HJLuuvB8vxCWB1jJYcYU8vnc04yibvjXz/tShbvRibTmgQtXIDloTpULAiCUUX+SN701qM5+cvR5E+GLGPP4LJbgexfP4GVIu3xrRFqxD3QiVUYY/giUcmQ3UkCdErCnse79KfL0duYRoyCvUIYzqe7FaIJ59dhbUphzHo7oexiGtrcmJPW4Xjt2BtagN8jfJ/bTGeKTA9FmleZzD0hcsRt/mwIEcbMmpni4zcunZ+m9MP9zg8RgQgJMQPHpx6zGSktF9bkCrKfN6EFuT/LpHVIR7QCy0aT+kQNs7y+qcWH72ShBK3ybx8gzoLkbiE2arx1iMv/yRUq4X8yepKJM9djhJRHFb7InLktRRUaSLYeXMR1JqD+GdN7TfDjsyK0tdg60lPzFoYLSzwZHxLKmdBpvuQmrIbl8cxXcfdDW3+KizfYUNI3XXInR/PP+I6+dEkLAoDPnouEdk1Uju2X15LAWcLNfCYwfmYNxpTk5FbL2b2wkb86GSDS/xiZGsDELUwAbNur8e2xYkoOM+fJLRzCdO1NhiLNiQhluVv5WTAdGYzPgz2g39AHepPi32xQOWuRz2blJw1vvPG7GsXiwebDpwSdwBnD2ThSCenJYaMHnQHVgtyeHAl1j8+GZeZXJ6X+JA5QhxOLGC23BOH1yC3qBC1oiot7TBIX2gWB3hbydmIbcc0mMbKmOZejueXbESZ0eDkZMrrdjc2bX4T+hDmc9M9Ze3Buu3Lj0EO2YjoGz02EuKNoWw37//5G7D1b3peZmG3s50WfYwK0CJ70VyT/YoxPndzJs56c/brx2Ib08uqLcht82JyE/x0cZINP2V7y1bP5fU09pHlLC75oSkrEc8X2ter3fFVTi9y8jT6ZPIWNI5ifVoYwY+ncSxWtih6f1OmfEUxwcJujHLeaIx/M6A+tAXx6w6KT3QI+Ubblo/lCvzDDCf0LBPn2eoOGWLMEcbhYiS/UgqzJ01lfNQetsdES9nK2aC5bPscF5T02xIZWTo6djs9xjqjj5Fx+N9FZcjdf0HcIXDpwG7kTv9fLPwvcQfHVbZ4ipyClz4ZjulLNzL9dOH9//1fpNSY3mWtTo/GzE11GDnnt1j6yzG4sOkBLMj7XMxnNPwJL/25AxN/+VskPTgMhUvmYsNx8fwrDTiUXob6K1yCLYTS92LbCxtxZNhs/O+qBzCs8AnMSjpgeny39R389r7f4ciQaSw/HhO79uJ/7ktGhbPv0tZtx6wpyagbMQ1PrFuK6d0H8D//k4pqsXldjWXYVtpg5e4719bt5t+S4PtS3fOYeVvNduzZmMRkNxLRv4lDILdedGH7L3UJrXKqngt7sXjm71Ez4mEsZef4NSTjqSyJziz7x5f3v9jTNZEvbzreM5U3aDiC/isQIzAMfhMnI2yUsDDm2rXN+H53Vw22xTyAlK8CMfc3v8XcX7QhZSZL99iRnO4v4b2n78Ozx4Zj7ksZeHr6JRazn8DfzE34+sfgICdTIwxTU6vFlIn2t5YZpi7YaWi8Ku5gNO5aYDq2fb9h9ez1horLQpJH3Fd1RUxLadpjSLQ8/txuQ+L0CMO2j8V0V7uh8Vy7mOBoMry1INLwek/zWgzvPC45nkPmHL4frxwVEhxX2g1ftncJ20r68HGaYerj+wzSGnpheUzLPsOq6SsNB6QnXS43bJ2dYHiriUtUG7axfm/6QFqxNbjjlhneaRGTDFm98HUbz+HOf8zwzgU+h+dyS5OhS3KulLMZ0Ya4jFNiiqPLcHZfmuGdatbOq6ys2dGGXZ+KWRxXmawTIg1bPxLkKbRtt6GRTzGuHmX1s3MkRZ5MizQk7OKFIBxvzSaM8r96yrArmsnsnJDFY9wnFMHoLSNLm+brkdq4VEaK+2Uu85OpkYa4TKmspHBtMu+3UeeJYt8FLhsqXo40JL4h7OPLNJM/p9sEw4wN5UwTAr36IpZrZktXmK1ZyMQcGzJ7obSnHh4Z3zKTMy/TBYY3TgtJHuYXM6IzDWfFpBlXuwzt9U2Gdgs7npGmsDyuj5w/SW2D97EIw6q3bHW8d/y4vH+lYcbLJvly8PuMMufbscVQ1dNO1u4L7SYfshEfONnYbodgX8Z2cDpdlZpmWNUjK87GF5j6pkAPy/dI6mpvMXxpLQZzWIvD3D5JHObigLmdivt67NTSVgS5Jr8vFKpMpha6lbMHRi/bl4vfLrIRa/7P71u5n3mwia4P1xtmJOwxfMmnBL/c+qFJCl/uecww9dlS0zlfcXJg7behq66mesOXkgq48qcuszEWKRhfZfUiJ09ebywufig5wCJWWmIWI+TKdyYmWIt//HFJhkPfcAkhX+prdmO5Av8wx3E9y8X5L99g2xZ64vKnTk8znBTTcj7K99POvKWXL1mVrZwNmsu2r3FBSb8tkZOlrL6t0Es21mzMYoyV04clX+191OC7kdXxaYYhPDzDUPtvMcPwhWFXbKDhxfLvDFUb/QwJe78Sdv/7O8NXDQ2Gr3qOMxjq//ywYdxWsZ3atw2Jox437NMKSZ6WDw2vp31oaGabfH0P7zDUW5zPt4GjZY8hYdSjhny+P9WG9aP8DM9+8B2fxcPnrzAUdwjJ2rTphtg/NwgJEX7f7i/ElDl8/eGPGl7cutWwpef3F0OVWJ7hu68M9Q1iX3kaDLseDjRsEZvHn89iK3+Elbaul/omn7/RUCUmOTn6rvrQIOmNc+031m+k8S+snjjDLnHC63g93xn+sSbQIv87w8HnAyV1mfePOzc8TWq73xlqC7Ya8quNguSON8pGgG+XqGe+H0vfNhiP5vjuwzWGcbF/4e1EXvdc/v8a8iVi6mj5wvCdxK5uBFx7R9ldg6GS57yGqjXiFqD/tAZlozzYv5WorhB/p7Usow6NVi5668/VozZ4Mibwt0hERoVjFnd13ohKAx9vNbQNNaguLUR++k6UtOntf21Q5hzN+ED4FCfjyZRCHKlrhs5NAy+NcJnQ0T4oRX/6FI5MmIoQk7gA9d2YGNyM2tOmS4xqd6kwHMCOXszxQVBoM1JXrkZ+cQ2aWvVQe3pDZfXZvWacrACipgeIaQ4V/KOXISqYtbO5DlWIwETpO7du3pgQqmJylXwVi/WJuwvD48bJ2RsaSfNuu90P9VrJpflxgRhnaRPDj6GWu8rcXIND3d5Ai0Q/lU24rG5G0znrd+scRnG/zGV+m7cfWjp7X980Yd5vATXC7mH96UGNCZOCUXuiATom/7PHgVlhUvkzDd4TCo/KU5B7Y8rMlgYPEe6WOormFvPzHPZHDWuHuMkx0hshHXqr72BxtqHx84a6rQG1FQdRtCMd+eVai7LtlNfahJODQzFhFJ8joJ6EyeHitiL0OFlVgyCNnrXBZGNn21jOqSa0cIcM90fQ8GKsXpqCotI6tDD31dyuseFDSmH9mK5BWRV3W0OHk8e0mBwdjcmacpzk7P48s3uEm/omowffgFDU7liJtTnFqG1ohd7dEzaeLLQeh71DJXFYiAO+qhaTz7FfY6eald0sPMnBYWYrnvD1Zz3RcbFNgUx5LHSryB7MkY3fLrERETP/1+NMXR3CpoYKd/xFVEyu086fwFnJXVyV2iSlQVw89LzFdM5wbxahW9Fu41sBKhZjPJg+6lm/SrivcL99ArAhD/nxVV4vysZDPwQFSiphsZKzZbNYaQPZ8p2JCSJm8Y+NcT64jMvGp8ossRPL5f3DOsr1LBfn9WhkfjZt0t1msdgnPALMxUQU+qjD9JatIzbI43RcUNJvSxSOmQ6P3daxPcb2QR8THsajw7djz1GxPXVvY0fb45g72eIZ4JsGYfiYMRj2r89RffgQ/vZ6Kna8+znEm5no+qQa7z0UjfukrwZ4TseSZdNxh5iExzC4S56QdR9i82F2nmHukjZ4+jHPv4wO/o7z56j6oAv+N32FisNHen4NHcOYP1u76ytyyxhM/K/JCOv5BWK4sYpBw+HnMwxtn9egonQvslP/hMLPu9Blz9YcQeMOU2+cbP+xVCSwcTqK+0VNwfgH92LEtq1Y6CPmczhUzwU0VA/Hff81RjyeYxCmRMSJ25Zw5QFzI6T2PgiBv1yB/w5W8gZyF2o/OYT7Iiabva88aGIYHqipxinJ175s657p8KFqvJT4O2S/U4OG1i4M8xyJQTfWk9cD93eUdR1sZOtkgarqGKp6flr4xLIgJR4jhT+eDSbSIMjCMFSSCZ3+eDoWz4nB6pyDqGITRp+pMzFNuq6wguw5AY9h9xtbEOXZgJK0lYi7f07Po0OO9kEpfLkjPdmwI4UtINkOYdAYKDSYtn4Pdi6bBFT9FcmJMYiYL3nU14x2tLepobYxwcY3WjR5e/aSi1rj6dSg08MI8fHSHphNuOtwmXNKrk439jPTTwNUodHwcXfRQrm/+sUNj72CPLMJi4mImg3iuHyZHc3J3xtelmMXy/eytdjsZ5zxR8XoapA9fw6in81hC0Y2pRk1FfeGOlA4pze15RfmVRhkvkMGHXRfsX5ePCWxL/br8MbCUPHRbLcALHxjN9KiPdF0MA2r5s5B5Cqlj5raxucetlorr0FTxzGUneYWxdyCA6it10FbUwnd7PCeCaKcHtSz16Mwcxkmdtcg/4VERM6JR/Zx63FGPg5zdsj+3yyRB/s1qkKx0G+I/UkfjwKZWsMJe5CN3y6xEWsIffTxtLgSph7C6rWzQHOE7laUrGK2Fr8FRaxflzWTMHva3WJmb+T1Kq8XZeOhJ5hIzeAu1CqJlbLl9zUmuAB5OfYVuTgv6GmoysJIWbrnAnSffVQhDtqgfeTsT0m/Lblexsy+6GMkYv5vGnLzhUdbT7FF4vDHHkag5cLj2xqkRAVh0tIMvPfx52y9Mh33z5woZgKXvr7AVjcstonp/uUSW9AOwlcNR3HkY9OvYch0PDHe3bbcPcZgytQwyS8Yd4gN7jqeiqi7pyBx+/s4wrrnFz4bD/xCyHM9Trb/F4/jlT//BX/lfn95D5+cKMSmOSPFTGvI1cPlD8MwC6UNGmRLi9aPV84lXGLhzc/T+N0ckZuHYkTPQliOYXggpQJFz4UBx3bgqdgQjI9KRXUf/nzVtWDAFsoab3+ougMwe9kyLLH4TZNewRfhjz9ucWesswH1PReidTjyZiFue2o3/rj+aSx5NBphwd5Q2Z10KDxneABmLXgaL2buQXFmHL58LR1lHY73QSka/0B4VZyA+atwzWj8VAX/Ua78KrYS1PCZEo15z7+Knfv2YJ1/IdbmWXtBxx9jg1uFK/xSjH9zdHQgpjWY3y1hwx4azzQgbJT0kpqDnJbeZWJwNlEXgLFckfwdRO59td76ieXucruCfumXB7xub0CTWcc4WN/qzYfNpjM1UI33hoaXfwOqT5kvcPT19aie4A3jt3gGDmf8UTm6ijeRO3IZ9u5aj6XLEhAVEYzbVA5cROJs42IdGs30xvmYuKkINqHyV6FrXHQv+1qybAZMnx/yhH/kAixdn4nd72RiUUs6skvttVWHdjYgCU9U2CAgHFG6SlQVHkXZ9En8ophbPNceK0XFsQZMm2S8aqxMD2rvUEQ9moR1b+xD8TN+yF2XZxF/BPjYxMVh6UJfW4OjPXHYB77jdPCa9Fhvmcyz8i2FXiiVqTnO2INs/HaJjVhDA99ANcpOWMTR5gZUqfzh64oQf6YQ2fXRyHwrDStYf2IjQ+Fj5U6qEfnxVV4vysbDOrRwtt2DeHddQayUK7/PMcEFyPtHX5GL84KejrDxRwqfL2733UcV4qAN2kfO/pT025LrZczsmz6GzY7HwkN/wb66I9iTFYCFVhZfl8r+gm2+G1H+1lYkrfg1/pv5xh2DTIFt+DiWLqtDg/RvC/N/b7g/LheMhF/YBdwx7XE8vWKF+W9BsBNfV76ED/+yHXds/BBvpTyHp38Th/vuuQODFLn+MIy0/MsiTAb2e+1k+9kCdsQtbKEq/uTvosrVw+XXofqM+R9uajh7RNyyZAwCI+pwpM78eHzLFsCK1DwcfhNH4j3Lcavpc1TcHAB/xePWMPhNjcOSlzNQVFGFPwZsx1O2P9hzXTJgC2XcFY2lqjxk7DV9OEVXmY74mHTUWruEdlcEFqlY4DUe361DdVYminrmkmp4eKrYBNO0UNMe2o0CKx+e0mmNHiR3jh61KXMQn14JnTjw6dq10Kk8hb+PqbQPHVq0O3IHaVwk5mkkfWW07N2CDH00pt8l7lAMa6/ZRM8BLhbiyTnLUWRsRrcWLe2A7/BezwQz1Ah7YAaO5OSh2lhf20Gkzo9HwRm27T4JsyJqkJ0jkWVlFjLKQ/FguLXyFHJRIn/eJtJQFBqDMO6i1/AI/DLiMDKyTHWieS+eYX0qMbMLBTLSfm0qQ0q/9MsbvkzPZ8+bzSgZKhRlZZnky/qSkafHIjboGeVftiPHlN9RiezthzErKpxNIyTY6otDyMlMuT86A3fHXsVWkz1+1XYYBTb/tq0VhofjwVBzvbXsZQvYNmHbHqb4AQRFLcCgvC0SH2E2+NpcRIsf3tNXpiByfrpJJ7p2tOtU8NBIpj+94kMzmk6rEeRvz34CMHF6A9P/YUTdHSjsGjcJ0yqykFozFWHiLnk9tKIocQ6eKTDFmvY2duztvZ+S4AlgE1XvQiRvLkZTqw661joUbMxDY88EWINpsTNQtF1ip93NKFrO6rD5ISlz5GRqDcX2ILV9ufjdBxuRw392HDwK2PjV00cmo9Q86GMjECTu6hNMHr6d7fiX0VR1DSgqOCwmrCA7virQi6LxsBUZqXt7nqhwKFbKlN/nmOAKZP2jr8jH+aCIaKiktsXlZx2W3OXuu4/yyI0jjtqgDHL2J99vSxwYMx3FoTG2j/oYFIa5j7Vhw9wl+FtcPB7o9WV1tjQZMQKDWr7CV8aFcNsh/GW3ZHEy9n7+Ee6UN41fVepCQ+4T+MULxo8wuZLheGBBPP62PhUVxsKvXsDfloRg8d+d+arTMIzwGoSv2kyBuY2NcX+x9TemzWCLzYmD8F7hAbRxsvm6DrmbNqFKyLSBq9tvC7l6huO+Xz6E91K3m/Kb9iIlTfoxLynD2PHx+DBNcjyzg5cio5F7VkzzfIVLpumCGYGzf43hGan4m/GKKtceJq+upffD9HyCHS7sxYK7mZ32nN+GL/4F+A0X71JfPIzslDzUK7rIce0YuIWymzdiX3kJQaWJCL8/BtFzZiJ6Yz2iXk5AkLXIxj3CmLqSTS7Y8XO44+eiYNQyrJB8GDgobiV8Dyxn+XMRP2cOVp4MRJTZ6yeemJ0QjTMpMQiPyeLvmNg/R4Wgx7Yg6nQyIh+ai8UxcxC5rh6xW1gbuXdWlPQhOA4venFfppuJtQcUat+sXFbn/TOxuMgH6zIeg79D7zYGI/YpL+xKnInw54xf8XSA26Px3NMaFCyZg+j5cxE5MxFFI5KwItr6pSPV9OXYGduK5LkzEclkGR6fhsvztmAef8WODUpPpWFeRzqiZ7I+8bJqRWza7zGtLyNSQBzubU1CBG8TMVh9OhKZzxv/Nq95ndFMf+GJxfB6Kknyzpi8jDSzE7Cwfgvrf4yVr132T7+CJs1AdVWdRXv8sOIpbxRwjxdyfVlSCI+n07BQtFde/vPasc0o/7kb0R6bhudmmxpivy9KUWZX8v7YBzi/8illfjUH8b+ag4jlNfCPdKRwNjl5XvRt3nbmYHXr/+DFSDHbKr3jB0YtwPq1gShhsoiIiWFynYvkc5HYkhDMT9BUoY8hLfIUVjN9xc+PYcck42z0Fiy5hzuZYS0+tNajFpEIk/k73UFTWWP1wZgYLAYbt0BMnKKHPvxeBEke9bSvB09EvSDE1YiYeJY/E/GFGqxLsvX38D0xKzWTLVgOInllIpav2QfVo2swT/IOppkdMplEsLjx7oiVWBGl8JKzjEytosAeetm+bPx2xkYUIu0jK5eXkU8S0h51kYN4RmDJvGasZXYX/Sumg7lZGBoeIWZaQcH4KqsXRWN6AJZMb8Vq1mcuhkUmn0LUFoWxUq78PscEVyDvH31FNs4HPIZX+XFb9L/5b2LsUwkIEXJ5+uqjisYRR21QDjn7U9BvS5SMmY7izBjbV30EPvxrBF4Zjidiw6w/Pn13PF4b9zaixoZg1qwQjE+oQcD86WIm46YxWJi5DX57ozEqKAS/CArCr94dg50vPWT7DmkfGDT9ORQ9dgkbpvjjF1OmYPzYaOzx3Ijkh+w9imybifFb4V/A2h7yAGaFBCGhJgBzJd2zzSBM+fVWTKn5HSaN9ceomRlwX/Acpoi5tnB1+20hV8+wORvxVlwdfnt3ECZNYXpdegFLNsfzedbgy/u/r/AUV15ICEbdl4SOx3ZgSc9d9WD8b8pIbItisnjSykWSMfHIzA7G27H+GM/O59szZhv+ukRhnB0Zh02bh+MvD7L2Rj2AX4x9gPUnA8kxwkJZf+4j5BcVospFN1T6ix9xX/QStwcO7vHcbhXUkg9a2EOv00GvUnOvAllFLt8asufItdHBPiiGK5ctxmy++zsQdOuh0+mh4t7XU7JQlztez/qk77ustAXLEV0agcIMNqnnyuy2Iycuv5PVafaH/FyMi/rF01mDjPl/xdidr2KWlTFb38EWVbbk66i++hln/FExrpC5i3yM04l+sI1+OqCTlvzFWIs1+OM8175fqShuuimQA3enxKwPzSiIT0T70/uxhHu4wYgL7NCuTK3hrD0oie/9FIft+nJf4XXAincg7inxV1m9WJNnayGemV+Ke99IQ9Rwx9tlhj19uTIOO4NS/+grcv6lxP9c4KOyOGGDcrgq1vYwEHJQQn+3o4t7zHYQhtl7UZV7FJctj4fZ/IPFLoR7vPtyFwYNVfIosjxdly6ha1Bf3sN1EBe33yZy9fD5bOF8i8KOu6DdXV+zZbSz5w+U3PqJgbujLIULeA4MalwQsXe4XL41ZM+Ra6ODfVAMV+61XCRzuLFJh7sDgVvueG4S5mpZcWXakxOX35+LZA5X9mtwMOYndKGo0PrLbSp78nVUX/2MM/6oGFfI3EU+xunEZlOU6kRXiYICPyyMcv1HiBTFTTk56OuQGz8XqaWtwteE2cSuqTAL+W1TETJeOKQHF9ihXZlaw1l7UBLf+ykO2/XlvsLrwDF5KPFXWb3IydOJdplhr3xXxmFHccQ/+oqcfynxPxf4qCx91bUVXBJrpQyEHJTQ3+3gFpFyq8ghA7RI5riJLdoVva+rjEHDBnCRzOHi9ttErh4+34GOu6Ddg/py/kDJrZ+4NneUCcIJtMVrsPJYKLa8FNm394kIglCM/kwxsjOyUHBSBz1U8AmOwNKnnkbYwH5gmLjRaCvGKysqMTl1DaZZfDj1hwT5B0EQxA8XWigTBEEQBEEQxHVG9q43xC2C+OGwZNF8cev6hxbKBEEQBEEQBEEQBCHh2ryjTBAEQRAEQRAEQRDXKbRQJgiCIAiCIAiCIAgJtFAmCIIgCIIgCIIgCAm0UCYIgiAIgiAIgiAICbRQJgiCIAiCIAiCIAgJtFAmCIIgCIIgCIIgCAnKFsrdeug6dL1/Or14wA8Ivq+mfumbK1F9RiemXIEOLRWVaDIWydXXD3J0fbtvMDqZfXaK2z8E+slOCBG9i+OZGDP13WKacDn660G+3VrUltZAq7Qdjh4vg0My4GzcOHZLf66Kk3Ixt7sV1XnpyE7PQ3WbuI9QxvUSTxy137YaHKnRiom+47DP07h5w6E7U4z8dBYnihqgWHNyscfFdngjIrsmGGgZceNRf8zRXT2XYyhbKNdkITImpvfv2WK4RqxaNFXUoOV6WNi0FWNtTBZq+YQOR3YkY1XeMbYlj/5iDaobZCTScQy5ycnIrxRL5GTbZzlays+xdv8Qqc1i9plVI6YGmn6wZ5fYiR4tNZVo6u9YqG1AdU2r8kFuwOmtH21RUh/ka0WufBxJwgFaELiE3rG1BtlsDMq+Vi5upKEQm9ZtxIEGMS2Ho8fbxTEZ8DYuHb+NPxfFSfsxV4ey5MXYesYTQQF+8FCLuwcARePydcV1HE8ctN+moo14ZmMhmsR033DC5x0cNwfeVq6juW+fcNHc4kwOEpcX4rLfJAT5qKESd5thZX4hN99zrR3eAPSSkeWaoLe+BlpG/HjU57HH1XM56zjw6HU0/vjhByiX/jKioRFz+0YTilbnoKpDTF43qDFt7X6Urp3BtuTRVebgySIZM3OfgWff349nI1w5U7CUn2PtJlzN9WrPWlTtWI2ic2KyvzhXjCd3VF7HF2lcrZ8Bkut/MIpi67VgXAJ2f7gH88aJaTkcPd7VBCxDoeU4/lSwmNmf6HC5XY+wh+MQFhEKn8Hi7gHgurUdm1zH8cRB+/VJ2IPyPQnwEdPXOwNvK9frXMFRXGSzl3Vo8ovEryJDETbBU9xpgRPzixvNDvtMLxlZrgl66+vGlNHA+I/bGoa4bZsvjyGnBIj6v1CMEHf1oqMBJbszkbP1bXyi7cbPx/jD46diHoN7nKJg15+RnXsQ5zp+hDtGj8JQ7nJRRw0Kst/E0c8a0HqlDY3feiFkjDtaDqQj/3NhW0CH2vwsfDYkFL63sFTNXuw6OQij/lWMzK2b0XRbLIJuZYdxj3e9kYXs7bkoO9OBoaPvgpe91WJHM468lYGszazdne4Y56PD4YIO/ELsq2U7dOcPoihjO179axkudKjhFzgSg38sHJd34AQ+a/wXui9oMWh8IEb8tBll6QegGzkIn+xOQdp+PUKnD8Kx9Fw0jRD6wcv2hDtiJ3WgJPUPeHXfcXR+7wXf0RqoxMsYdmXxY6XyY65RkYedmduRd/AMOgePxp13GAUjttPfCxcKUpHBy+Im1gZRRyLa44XYnfEaMt79lG/jWH8N3MS8XrRWoiAnF3npnD10Yugd4zFiiJDFta3kkg9uPpGHtJQiMKHAl8uTsaFe2NH1V0dz8S5mY/FkL2GHnF2w/Np9ecj8w2soOdGB7lv9Mebnks4rbZsNexbyHOyflL7ayS2cjvPxwScNuNDegZY2FcYFefW6Yiv41VBMuFqBnakpyD14Ed2a0RjrJZnZ2pElf35BOT75/CL0bQ3QG+3cCnxMyHwdWy37omW2s6MKNwWOh4fYQG15DnYfY/O0QLHNduyLx1Ybbein87Ni5J8fjfkPjkdnBaurdihCmH33wLfpJG4KZjozM3obctWdQclb5+Ezyx9Ne5jv/+E9nObiixgvjNiUgTXkbFTW5/xx6/l8vLo+C2XNbvC90x83tx5EYfp2ZL5/HjeNHG9enpzPyCGjI1ux1BKu7b1jays+3sUGpYgo3FTGxaw8HG4V+vQzqVE76nP2judt5zPcPPorHOR88OxIRI+5wPYdRjffJvE4rt9Zf0QmG+suuPlgwk0nsPP9bwS74MswHq8s7tocOyHKYPZCTLqNP9QuUhu3tU61PUYI2LPXXjHXCN/nt/EPo4/UfYvbQkfhR86O4Q7YpXXbEfLk+mqC05NkzOYQbeFnrB9DxV12x0fFbR7AeMJhx96tzrF+KrVf4TiTHC/yMeTm6iwWawJxp5dKKKNML441Cuy9W4f69/OQ/+csQS8YiTGj3UU5KrD31hoU5W5Dxp9E3xvSgFw2bvbYvJ3ybdqK3TYxeuaQLAadZ7r1Z7qVjkW2ZGxjLLKG7RggoHRu1nt8t2L7dvsr6rDXnFZ+bsFjxw/4+ct7NT1zhxaVYENSbM0vhNgzHTE/KuNtNf+jNrPxzNwOGXI6s0DOr+zFEkfHXkU6Ythqky0Z8fLl54cdVmOM3lJGdurg6OlXcwEv83c/7sRg39G4w91cZ7bgx6OOYMTfwsZHJ/opN5eL8juPvaxczie6f8ZsaaTzV2fthVDltBbj+flJqFZPRuzjjyBIX4jl8zegWrycoTuwGtHc4xQBj+CJ5Y/ApzkT8UmF4G+Nq5hThwTAA2r4BExCyGhBSO11hcita+e3BXRoLC9ErbhLf74cufkbsPVvegQ9sgxht7OdnTXIjV+MbG0AohYmYNbt9di2OBEF54VzeqGrQcaSRORqg/l2T3YrRvIrpfiXmM1h1o66LCQm7kF7SALWJz0CrzMpWJ5ewz/eMHS08KgIRgQgJMRPnOC3o7agEBlrtuCsZwQWPRzMeinsM/aDp6MUqS8UA2FMPo8E43LBciSK5XLYlYUi+elRuz0eC3K0GPtgAhY9GID2nMWI76lDaFPuxhRUaSKYLGZAfWgL4tcdZDUJcDqM21wDjwdXYv3jk/k2Pl/QKuZawOQUPz8F9cMnY1FSAiajFE8uTUet+HgE17ai9DXYetITsxZGYyzXZBkb6oWo620N3qyMBESNarWtawu7iArQInvRXGTXGCWsRdnqxdh0QoOolRuwJEyHghVJKLooZjvSNhv6sCxjsroSyXOXo8SGCK3SFzth7fFl7eJM1GMca9c46wMZ71eFW5Car0MQs5V5E1qQ/zvmI3XiATKyVI3wY2V7sOp8EBQyCb7Wx31oi1Yh7oVKqMS+6AuXM/s6LPRFEwjfzhwk54mV6g5j17pyeNzD+Q9Dxr7s2oYt/UjQ/EyPkqxS1EvehWs5kIUM3VD49BKaPbk2Iz91Ny6PexiLeJ9KNtOXXRn0QsZGlfjcjo3IPuPD9DYXvqfTsThpFVJz2uE14xFez7sSWXlGe3Q0lloipyM7sdQS67FV4Mhrxpg1F0GtOYh/VhxXOByNKXI+2tmMowW7sWnzm9CHMJ1N9xT3laPR2K+LhXhmEev37SzeL3wYvg1bsDZ1H3LLm4W+mR2vLO7aHDtdisUYMcMb9emL8WR+s5jvqL1KEH2ux0dCvPnFpVNjuIN2ad125MZDS6yM2bweT7EcAbvjo0NtHqh4wpCxd+v6Mbf3FtbPuNfqWQzh5OiNxtRkpBYW4uh5wYL5Moy2L2vvXIybi8QCHcY+spz1wQ9NWYl4vlDhIMn73kacYmX3+F5uvZjJYb9867Yi06buOuSKc8hFG5IQy3S7lYtzRge2F4MUjEUccjHAkbmZcXxfm9oAX6Ofv7YYz/QcL6cDQYfmc1plcwtLP7CcO3Dyl84dxo7oXYrd+UVFOrYd02Aas1XL8czMDuV0ZgHvVysKhZj/yGTgoNSv5GOJo2OvvI7ENtnwdVsyMs0PrevL3Fct65gM1ZEkRDM5GO2O71fOxh6ZT3Mvx/NLNqLMkcGpPseBflq0wZ7/XMzDVnEO+8SsoSh5cTEyjht75gQGJXycZpg6PcGQnJZmeF3yO3ROyD6bEW1I3NUkJET4fW+I+640GRqbLgvbHFfKDVunLzMc+EpMG6oN21j6nRYxyTiZGmGYmlotpjhaDO88HmHY9rGQan9rmWHqgp2GxqtCmuPy/pWGGS+XG7rENAe/b4P5PiNfvpHQ6/jGXQmsr2mGk2Ja2g6+zleO8ts8V9oNX7abzubzzdrM9SvCsOkDSd/FfcZ+GGX7lihLnstMPrPZPlF8crKQlV/LPsOq6SsNB9qFJI9ZHVbayZ+TZDj0jZDkylu+R1JBe4vhyyvitiVd7YbGc9LKmgxvLYg0vC42h2/bC6Vmcpe1IQs4vU5dud8glWz7RzsNuz4Qju+lN4tjuz5cb5iRsMfwJZ/i+v+Y4Z0LfILnckuToUu0LUfbZl0fkYa4jFNiSoCzNVu22QuX2IllujfW/Ipve6bQdnlZMri2Pr7PILUAM66eMuyKtuiLcZ9RpMa+nbtsOJkWZy5/GfuSsw1r+uH71dNmoTyTnFg6IdKw9SNbmrIiV95/FhjeOC2mOc7tNiQYY4sSGZhh30YV+Zw01l3YY1gu8W8mAcOBZRGGrR8KRzgaS3sh0x5e3nZiqSX88XKxVRxXjHp11G9lfdSaTvl9xjq7DFUbIi3qFPb12JbZ8Vb6YBF37Y+dwvn2/FkKL8PoZYatZuP4HsNJrq72/YbVs9cbKsycRthXxcV5BfbaO/5I6e0jfHscHMOdsctetsPL2N54aIkVOfNlmM8TbI2Pjrd5IOKJvL1b04+Z/XK2yMdoIYuH3xdhWPWWIAu+jJ64Km/vXU31hi8l2dzYMnWZ+fnW7d2a7102VLws8T2G/fKt2ArD7jl8+7cYqnpk1GVov9DuwNyB65P5WNQLmfmzPduzhO+fpZ8zO0o0+jlDiQ7M57QcVmzWAr7uvs4dOKwcw8ceszllF9O9DTuU0ZkZvA9FG3Z9KqY5rpwyHODiJtcRviz7scTRsVdWR0p83ZaMemzbRjw2nnOV6Xm2Rb+vms+DestcKDP5fUvbsI58P+XbYM1/+HIt4lbjrgV2xiZ5HLij7MFW72zVLvkJVyqacbIC8FW1oLqisufX2KlGbYN4dWKwN3w8gZY6llech+zthahiu7v6+gVHdw2G9jxfosfJqhoEafSolbTjbBvLOdWEFvEoE3o0svZNm3S32dUvn/AI+IvblmjGB8KnOBlPphTiSF0zdG4aeGmsXjszQ+1u/UphD+6hmDBK3OZQ342Jwc2oPW3jEpeD6E+fwpEJUxEifaHcSh1m7fRkOsNlXBavHPsGhKJ2x0qszSlmem2F3t0T0qdxzVBp4OOthrahBtWlhchP34mSNr351yo1t5hdKZe1ITMEXc+aFQ6pZDXhCVgY4S2mjOhxpq4OYVNDzY5VBU/GtPMncJZ/t8EHQaHNSF25GvnFNWhq1UPN+q/ibcvRtlmjGWePA7PCAsS0gM89ofCoPAXFb0T1s530YOZXwG3efmjp7GJbSmSpgOYaHOpmemoxybO6sgmX1c1oOidKVD0VS572QnZSIjaVR+B3CyR6tWtfjtiGLbwRFuWJgsPihyaaK1GijUbUFHlfN0fDfErc5Bisxs/FTUUyMMOejTKU+Jx6iMnn3FQYBE949LSPxbLRrDla7lqto7HUCjLtcTaWWmIWswZL+uew3yr1UQudmtGKxlMqhN0jtTMVgsKmitvWsRd3XT52incZTOO4cOdM/2kNykZ5sH9Nsqo+zWxBX4dG7gK/w/aqEIfGcBfYJUPpeOgItsdH17RZwJXxRKG9W4wFZrQ24eRgizFp8CRMDhe3bWDP3lVsrPFgbatn7S/hvpD+9glAka1b8z01Qqaa+54z5ds9Z7g/goYXY/XSFBSV1qGFmY/mdo0L5w4MmRjg0NyMY1wgxkkHx1HhmDX8GGrFJxyUyEh2TtsLF80d7GE2p1RhqK0m2tWZBZxfIRJhE8Q0x+AAzFoWhyBWvuJYonjsFbGno/6KxVKa65iNRWCitN9u3pgQqmLjteRLfmYy94QvWzzpdA7EUKb/CWb9DEbYYGM/FbbBGhZxa6haqiDHcWCh7I2gKaGYKPn58HW3o50F/fbmY6iqMv0aVaFY6DeEDwYthasQ+VA8UgtYnlaDkEhmWNypLkUH3VfMcC+eMmtHVYc3FoZaexREOH6oyiKHpY3vHPUi4DHsfmMLojwbUJK2EnH3z1H+WJA9hrMBUNwUUGMok61DBmcHXQdr40hP5o5SHKtDPXs9CjOXYWJ3DfJfSETknHhkH7d+rv54OhbPicHqnIOoYgbvM3UmpknHr17I25A5NnRnFeFYH08LR2GBy6NngNZg2vo92LlsElD1VyQnxiBivvFRHEfbZg2uDG94Wb7gz5zZq0MPbgmqiH62E3mUyFIB32jR5MZ+EnlWVTVAFRoNH3eTRNWBd2NCKxv477kbPpKgZ9++HLEN23hNj0ZIcTGqWZ9aKorRPjsc/rYmjM6gUAYm7NmoMz5nD0GGymNpb2Tb01+xtAdH/dYVPsqVoYbaYpKqGjxI3HIcl4+d7n4IMRvHg/lJNT9GdLLFk0RWVVVa+MSyhRN3nsP26gxydtd3u+RwxXhoie3x0TVtlsVh/bjA3rk61ZZfJmaLAGc71d2KklVzEBm/BUWs/Zc1kzB72t1iphwKfM+Z8uXOcQvAwjd2Iy3aE00H07BqLjt2VSFa+IWlozHIOnIxwJG5Gc8I7mFVKSqo3HW4fIVt9kkH9hD8oM9zB1dgV2cWWLVxE/0RS3js6WggYjFXhzdbzItJI2qNp3jTxEVohlj0UwPNcEk/B6INCrhJ/LcP+MB3HHOCSY9hyXRr5lSHgpx6zN+yDwuNVwY6D6NM3LTFUCaMnofhjdi1ARbg/VXoco/GkoVKZojC8dlnGrBiuumqqr6+HtW2l8pssRKAWQu4H9s+k4PFiekom74e02zeZVBAQz24d35MVwGb0fipCv6zmAwYjsvCHI1/ILxyTqAeoZK75dI6lF3XVnuHIupR7seqL12DiHV5mL7vMYs78DocebMQtz21B+sijeGjWebPH8jZkCUa+AaqkV1nrjv+76d1Ww6W4rEn6rA0VHJscwOqVP6YJoiYoYbPFBZo2G8e14cXY7A2LwJ7HnO0bdbwx9jgBpSd0iHqdlNY4G1tQiAUfIdHoJ/tRB6lspRhpDdCOi5j8qPLEGYxsTHBBuxXcoBlSYjK34jsyt2sTk52cvbliG3YwTMcs+7KQtnxOvgU6THvZUlZrkCRDCyxZaPeTvicPRyNpZYojAH9EUt7cNRvXeGjXBnMbk9rETvK2G+gvqqc/d9PSDhEHUqcGDudQePtD1W3BrOXLWCSswJbVDlur44ib3ftfbJLAfnx0BIPeN1uMUp2915M2hof++ZLCnE4nrjA3kcHYtrFYpzVMpsxmnt3HWor2L/OmPuZQmTXRyPzLTanEC9K6g+VChuycP7eiiP1OuZ7pv40neGeChIb40z5is7xhH/kAv63tLsB+YsSkV0agRdnu2LuoCwGKJubiZzmnmSYavLzzgbU1wUgiNvRJx3Yw0VzB5dhS2cm2+GxZuMM7u95gy2gHY8lCrGnIwxALOb63VCKsx1x8OoZj/VoZOulsAlWRwjn+LQBTUx2Zv1sEPupGqA2KMAFH/PSYFrsDBRtz0K18fGJ7mYULZ+DZ/g7BBpobtej/Svj1RUdmvbuQZGYMqGFTvL4hdeoAKgOFaOMK6Jbi/rcFGSYvitilaCoBRiUtwVFxuO6dah+bS6ibXykIygiGqqCTNPxHZXIzjps4+qRHrUpcxCfXskm3MIeXTtrs8rT/G9Car/uyVeM6jCr11Ruy94tyNBHY/pdQlqZLMzlZ8a4SMzTsAC413SSZR32aUVRItNngen89ja2Iru999UebjLv4alCe6tpxaY9tBsFxo8OWUXOhnrjPzsOHoUS3elYsFsRg02HLFeK4rFSPXNlp+ZBHxuBIC59sRBPzlkuydeipR3wHc5FRsfbJiDVhxphD8xA2Y4cUxmcrW0/jFlR4awGAV1Dpf2/4egSO2H1aJ2/0ikrSyMdWrTb8oPhEfhlxGFkSPqC5r14humgRLQT3YF0bNKxQSx6Bub9PgJHUnLED0HJ25cy27DjLzwahM0K5j86l6+KRpj08UIbOCRXBTIww66NOuNz9lESS23bq1x7FMZSSxyKrY76rTIftQ8r47+j0fjaGuQeb2b2pUNL6QZsO+TsJFnp2ClykcWHlDywtYLj3BWNpao8ZEjGCF1lOuJj0lHLKdxRe3USObtzdIzvQWo7Do+HnmySr0LZeweh5crQ1qHgNRaPhEyG/fHR2Tb3azxxhb27T0VsbBM2rWGyaGYLQu5LwpvTcMBpc2dy7mzHv3rMvQFFBYfFhBwsXkeFmveH9T87XxKflJYvtRWZc/SVKYicn26qU9eOdp0KHhoukCmNQfbGIrkY4MjcTOSixM85W8xKQ1FoDMKGs3SfdMAOt2OziucOSrA3v5DBvs4scJ+EWRGnsCvX5FdaFtPjF+UJryf0eW5tA3s6UurrCmRkU198v2uQnSMZoyuzkFEeigfDlY2GnF03Vcj8be22PJPsLPupuA1yc7m+45KvXqumL8fOee3YNncmImNiEDEzEe+OWIkVUdwVFU/MToxDYwrbH8MGh/vnIts9HLHCqSLBiH3KC7sSZyL8OeELiKopi/FicB3Wzmf7ZsZjl/sjWCp3lXLUAqxfG4gSVk4Ea0fkzLlIPheJLQnB1he/AY/h1ac1KFgitnv+mxj7VIKNR9tUCHpsC6JOJyPyoblYHDMHkevqEbslAUHilTfN7AQsrN/C6o0xfSVYCX4JeGLUm4ibE4PoOTMRX6DBi6mmK3rysugtPzPcvBH7yksIKk1E+P2s3ffPxOIiH6zLMNVhH09EvbCSBblEJtd4xHNtLNRgXZL1v6MdFLcSvgeWI3zOXHbsHKw8GYgomRty9m3ICpyuf++DdzldszoiHlqOstFr8LvZVloktQvuWK5snySkPSo26vZoPMfbwRxEz5/L9JeIohFJWBEt1O1w26zZs7QM1obwuRvRHpuG5yTtPVuwGrt6vsRthT7bCfPFhGicYb4YHpMF6fdAFSMnS47gOLzotReLZ87E2gPWAjGbpD2Vhnkd6YieyWTOfCk8sRheTyVhFvdlVe1BbE2px6KVC/hHrlXBCfjdPaXYlCVOluXsS9Y2ZPxFRB0eiSg26fBlE0eLP3hjgTNylZGBJTI26ozP2UVBLLVnr/bbIx9LLXEmtjrqt0p8VA5V8DJkbgpF444kLF+aiIwzEXjpaZmXNm2iZOw0oT/3EfKLClHlzMLVbIwQ4kv0xnpEvcx0wivcQXt1Fjm7U2CXlvSyHYfHQxUmLlyJkFNbWN9ZzIjPwdBHpPMEmfHR4TYPQDxh9N3emR8/vhN/CG3gvyWxfGk66mdswO+miNmO4hmBJfOasZa1PfpXzObnZmFoeISYKY969u+RGXkKq7nz2S/i2VbMezpSzGUoKL+Xrcicowp9DGlinfHzOT9NxtnoLVhyj5gvG4PkxiK5GODY3IwnIA73tiaxsZHz8xisPh2JzOdnMAtiOK0DBTYr9QNuXLY2d1CC7PzCPnI6M0fwq9jWjbxfRTL5xqV/i3mvLBBiRZ/n1jawpyMlvi4rIzl9mdfB9Tt6Yyti036PaUrDQ3c9/zeOT9p7si1yJeYp7Kf1Niiby/WVH3Ff9BK3+063HjqdHirumX4rRmJ8XMHqS/MuhqtLP1gNta3RU4pMu3vRyT3GqWJdUVK4A3DtYEbl8nKlcG1nBqj4EVQL9DomVzdl5/PHqhTqwIijumA4Yld2j5Wr24m29cJmGa0oWpII7Yp9WCg3bgyEnSjAJf7MPRLdyXxJ4d/ek6LEvvrUxs7DSI0pRNAbr2KW0sHBGRyRgYwNOuVzMliPpcrsVbY9/RVLpTjqt331c+7qt+Q8/aENiCgIRGGancmrDC7xNaXI6aQPPusI1u3OhFy+Ivo4HloiNz66pM1yOKqfvti7ha2zynFk3Rz8fcIebI520tr59jBzd9a+5M53pnxFZdqRoVy+AuRigJztcWgLliO6NAKFGSwWcXZi63UkZ2TkAAMaz2zhqE44eentxEUXxRLFOuIYiFgs129bXNyLJ5dq8YStVwCkKOmnM21wEa75O8pG3DiF2TY6lZ08V8PVpVimMu3uBTfQ9YfCuHb0tyFwbe+DI3NBRen5/LGOdsdRXTAcsSu7x8rV7UTbemGrjO4mNDVHYOI4MW2PgbATBbjEn7lFlJNBXol9OddGFpRbW1GfvwdF06OVX0F1FkdkIGODTvmcDFZjqUJ7lW1Pf8VSKY76bR/8XFu8GpEr8lAvPm6m19YgP+cggqYEO71I5nCJrylFTid98FlHsGp3EuTyFdHH8dASufHRJW2Ww1H9OG3v3N/cnYNncuvYJJcl2cJDezwHuaXemBzcB2vn29MHIcmd70z5isq0I0O5fAXIxQA52+sFZye2jndGRg4woPHMFo7qhJOXPed1cSzhsacjjoGIxXL9tsWFZtROnyS/SOZQ0s9+D5y2ce1CmSAI59D7YFraApuPnhIDiO4Edq1ciW0NochcNtXmI53/0ZC9WkUz+2msD67D1viZCL9vJiIXp6Nx9qt4Na4fP+REENcEDaY9/RImntmCOO6R9JkxSNjejFlb0xBL5n59MlgD/xE0ol3X/EB0pB85A5kLgsXUjY1rH70mCIIgCIIgCIIgiBscuqNMEARBEARBEARBEBJooUwQBEEQBEEQBEEQEmihTBAEQRAEQRAEQRASaKFMEARBEARBEARBEBJooUwQBEEQBEEQBEEQEmihTBAEQRAEQRAEQRASaKFMEARBEARBEARBEBJ+OAvlbj10HTrou8X0tYJvh15MAPrmSlSf0YkpRncrqvPSkZ2eh+o2cR9DW5HH9qUjv0Ir7iGuCXoddDpRf9eLTf0QkMrVlXSycjvF7f6iW4va0hpoyQ4ErpE89NdFfHew7y6WlT0Z9Bprrgk6tFRUoklpM9pqcKSmH8e8/i6fEODisNLwfi3HVRvzL4IgCFsoXCjr0VLDBr/rebxpK8bamCQcuNbBj29HFmr5hA5HdiRjVd4xtiWky5IXY+sZTwQF+MFDze+ErnQN4l6rh0dAIMZ6iTuJa4K2KAmRzxaDN/UBtSktmipq0NLfi75rhJlcnUXbgOqaVhaNTNRmxSAyq0ZM9RMNhdi0biMONIjp/yisxP4BkIf+Yg2qG6SV1iA7JgbZ/axqWRztu0tlZU8GlmON4/SWuRN0HENucjLyK5W1oqloI57ZWIgmMe1q+rt8QoCLw2uLWsWUDNdsrmZ9/kUQBGEPhQtlLap2rEbROTFJKESNaWv3o3TtDLbFocPldj3CHo5DWEQofAbzO6Hv0EI/JRqxETMwcZRK2En8h9GEotU5qOoQk0RvzhXjyR2VTi8EnGZcAnZ/uAfzxonp/yisxP4BkIeuMgdPFl2HyxtH+z5gtmM51jiOS2TuPgPPvr8fz0Yoa4VPwh6U70mAj5h2Nf1dPnEjYX3+RRAEYQ+3NQxx2yZl6Vn44JMGXGjvQEubCuOCvMAv57jHWN7IQvb2XJSd6cDQ0XdB7oYo94jxzsztyDt4Bp2DR+POO4QT9A3FyCv4J0b8whtD+eW7HvWF21Fy0QtjR7vjqwPpKLnkj1ubC5C5dTPe/bgD3bf6Y8zPxYWl7gxK3joPn0ciMdbYho4GlOzORM7Wt/GJths/H+MPj58KWbqavdh1chBG/auYL6/ptlgE3coyHO1TRzOOvJWBrM2sjk53jPPR4XBBB37xf6EYwbJbWLvzP/dCyM/PoSD7bfzDKMe6b3Fb6HA05WehoPwEPmv8F7ov1EE3IhS+t3DlurjtHTWs/s/ws8BuHN2RgrQ/HcQFvQajxnphsORyiS39GLGb3yOLPBw+z+r3Z/UPEfMs6dah/v085P85SygLIzGG6dlNzOb6UrsvD5l/eA0lJyx0LUXP5LS9HN/fNR4ePxF28TKvHYoJ44cL5XXWoSTzEDoDAzGCK8KObDs/K0b++dGY/+B4DLZmU1Jc1QdeN2/i6GcNaL3ShsZvmb2McRfzbLfVGrrzB1GUsR2v/rUMFzrU8Asc6ZB+dWeKUZD5OrbuO47O773gO1oDlZXLaXp23M5//NskYzSzOJGL+qHBGDNc2KOvK8TOQ50YF+iFblGuUX7nsTc1BRnvforunwXizpHmsxVb7eNtvqAcn3x+Efq2BuhFP/nqaC7exXTE/KiM94X8j9pw08jx5nK24xc2fUkKr5/D6B7P7OenXD8PQOfvhQsFqcjg/f4mJqdRGCpVrYze7MnZWpt8v+T2MZu+WoGdTH65NvTnfNzIYXaczsfVK0N9MNaL0wvX1/zesd8ZebRWoiDrj8jMZXHHzQcTbjqBne9/YxpLJHD+m3fAGBO1GMTX04qPd5UAEVG4qYyrh8WYVjf43umPnzkg917YO16MmTeP/goHU/+AV8+ORPSYC5K+i8fZ65sTsuJtY9efkc3KO9fxI9zRky/KYPZCTLqNP9SMnrGGix1i2+XivRHrMhfbO3IQPtnNytivR+h0fwy2G/e4c3LRJPonV675uN2Jwb6jcYe70GHeJsv0Elk5MkZd5H395uosVgeLJV6WlmS9/JvHd+PjjI1Y/+ZxIQZ5dbI4ncvi9N9Q3cHG8J6YaUVfDvmUtZjD9ufk4OxQJh8NlxbQVeZh14mbMWGshpejXBzWHi/E7ozX+DjK5Y/1F86zxNi+cVcrkb0hGW8z+f/sTtaWKzUo2rUNGW9UonOov2PjPMNYf66og6EN+fjEPRaz7jQdZ7MMu+OqvMyN2Czfpt9azr+YX/HHOxgzf+qoHTHs+YxCu5e1CRmdEQThHBI3s41vSAB8mM95jJuEkHFswOF2dtYgN34xsrUBiFqYgKgALbIXzUV2ja0XVfSo3R6PBTlajH0wAYtmeKM+fTGezG/mc1WjgqGp2YDsUvHRr/N7sXX7ZfiEevP1tbNJd1HOGiS/q8LkR5YhNkSHguWLkXHcxv2l1mI8Pz8J1erJiH38EUxWVyJ57nKUiE8H6c+XIzd/A7b+TY8gVl7Y7WynRZ9m3V6PbYsTUXBeOKcXuhpkLElErjZYqMOtGMmvlOJfYjYH1+7cunbWQTaYSeUY4s2CtIrfDuJ2jghg+ybBl1sfWbQ9SF+I5fM3oFrsqlNt72zG0YJ9SE3ZjcvjHsaiuLuhzV+F5TvqxANE/aTXw2sG08+DfmiR6EdOf+iuQ64oi0UbkhDL6t+6NB21VtWjRdnquUgs0GHsI8vxxCN+aMpKxPOFxke3uPzF2HRCg6iVG7AkjOl6RRKKLorZUlRqdJ3OwoFTYpoNtEdymcy3l+Ks8R2oU6XYVKnHUG7ckJGtclzZB8E2PKCGTwCzjdHiACdjw72oy0Ji4h60hyRgfdIj8DqTguXpNUxzHDL6Y2iLViHuhUqowh5h/QmGvnA54jYfFs83R+WuR71UxswmdxUUYpNJETh7IAtHOrleiVzMw9Z8HYJY/U/MGoqSFzn/NZYuEx9G+LHY4wGofRBk9BMjFenYdkyDacwX5k1owa5EJmejjGT8wqovWcL7Tjka+cfi21HL+pm7MQVVmgimlxlQH9qC+HUHTXe6eb0tR5HeGBcOmtmYuZwnQ3UkCdErCpnFCFhrE7+vcAvWpjbA1yif1xbjmQKJMTgT8zi/nR/PP444+dEkLAoDPnouUYzjahux30F5XCzEM4tSUH97BBYtfBi+DVw/9iG3vNmqbQ0dLY2JfvCQrH+OvGasZy6CWnMQ/6xJbg77tpx/8f3cjU2b34Q+hOlquqdF3xlyfXNQVroDqxG9vBCXA1h9yx+BT3Mm4pMkfbRDz1jDwddrL96bY13mQnsz1mzBWU/Wv4eDmUXIxT3hnFqxGcK4vbHHP6e5l+P5JRtRJnaIt0kzWdlvc0sBi0mvGccobzSmJiO1sBBHz1tXsrXyM14rRBfne1OBgudW4vnVKTgy+G4WHzh9JCOxJ2aK+lqThBI30aY6C5G4xDSuWfUpu3MjTwzVlyLjgFQPzTiQlQeduzDXkYvDnI3Eba6Bx4Mrsf7xybjMZPK8NA5IEOJGGjIK9Qhj7ZvsVognn12FtSmHMehuJmMuDicn2o7DDwagPWcx4ntkIuqAq1+ig9x6MZNHfqyxjbzMZcvn9Wzht1bnXwxnYqbDdiTjMwrsnrcJNkbw/WFjBg5KbaIv8iYIQhaDIloM7zweYdj2sZhktL+1zDB15X7DZTHN0fXhesOMhD2GL8W0Ge37DatnrzdUSE8Q91VdEdPndhsS+WNaDAeWRRq2fmg6+GRqhGFqwm5D41VxB8OsvpZ9hlXTlxneaeGz2PGRhriMU0JCpHFXgmHGhnJDF9vm279gp1l5l/evNMx4Wcg3wu8Tz7HkyzdYeRbHc3VMnZ5mOCmm+XanVoup3nLk4NvSc4zBcDYj2pC4q0lMCfD73hD2OdV2Xj4LDG+c5rMEPk4zzIjONJzltjldTF9pONDO5wi0lBveyCwV5CunP778LYaqnjZ1GdovtBu6JG2U0tVUb/hSUhany6nL9hmE6qsN26Y/ZnjnAp/gudzSZLMsXg9G+XHteDzNsO3xaMMuUf1nM6MNCaI8Fcn2cbEdFjZliSv7IBxvXpecDVvCt/2Vo2KKcaXd8GW7eKSc/q6eMuyKTjC8dU7I4jHuMxeXSJPhrYTIHlvm6l6VmmZYZbQnA3fugp7yrNls464FJruXax8Hs9ce3Yjw/vVCqUQeXYaKlyMMq94SBCnnF9ba1QszO+D0FGHY9IGkoXx+kuHQN0KSsydzvXUZzu5LM7xTzc65ys6fzWzzUzGL46ogy60fCa201iZ+n6V8xHhplI8zMc9wlflpfZOh3UIvM9LsxCyH5NFlqNoQaeFzwj5LXUrh2yqJiVbruVJu2CrxGTnftkTWv/h+WMRMs74r6JtDsmJcaTI0NvXu44GvuIRwvuX4YcRsrLHWdmm8t4IimTPk456pjb39U7Cn5PeFAvg6zWRlp82cLGZbxCh+n8nfLbFWvvT8qlciDHGZEhuoZvUtYPMMIcH3xVy/l1l8YTq3Mxbz++zNjZr2ML9lcwTjOXxaeRzmZLp8j6S/7S2GL40x0gKhfcb+MK4eZX0yjY0cJ9Mie8ZHQUYW84DLoty5Q6zpgM+X6EAulvN1mPzWHHmZKyvfwo54escyp2Kmw3Yk4zPW2iu1e17/FmPGlVOGA2l7DCe5MuXkQRBEn1B0R7k3epypq0PY1FCz96FUwZMx7fwJnLXynqX+0xqUjfJg/1aiukL8ndayjDo0Gi+GjlqA38WeQMaSldh680osmS4tnSs/AD6S54tUofciymp9zTh7HJgVFiCmBXzuCYVH5SnThz3cNRjaU54eJ6tqEKTRo9bYPvY728ZyTjWhRTzKhB6NDc2YNulu4S6LiE94BPzFbedoxskKwFfVYpIT+zV2qlHL6jNe1XWu7RqopXfiRnojpEOPLrbJ6yc0EmEaIYvHcyrmPTYDXmxTVn/D/RE0vBirl6agqLQOLTpW2+0aqKw9D8ZQefvBg/W1npVTwn2F8u0TQM9XMH0QFNqM1JWrkV9cg6ZWPdSe3jbL8gqNgM+hY+Auaus+PYZ/hUYjNlyDQ8e5K6pMnuXA9Hu8hW0lslWIK/vQG4U2LEEzPhA+xcl4MqUQR+qaoXPTwEsjWKes/pprcKibyahFkl/ZhMvqZjSdsyYZZjvTNSir4q5663DymBaTo6MxWVOOk9zd2vOsPIRjwij+YAEzmwWGqk3Gpig+2EJzi8QHVcKTAzwK/cKiXUpQu0tiE9OrDy7jMn/XULCxqOlSvangH70MUcHsnOY6VCECEyeIWRxu3pgQqmI6k3zxyVqbxgVinDQkjgrHrOHHUMvfHXcm5jHcVND4eUPd1sBkdBBFO9KRX651+Iu0tuXRisZTKoTx/mdEhaCwqeK2Y5jVM3iIRO+O+rZS/7KImWY41zfbsmIMZmlP5oZ1rP3FecjeXsjsBehyUB8CtuO9I5i1l2E/7lnBzD894csGSJ3O+h1gu21ubcLJwaHmMWXwJEwOF7cVwcYkydseKtYw3+GSQc+L1XdRyzRiRMV8VapfNUKmTkXtiQbTExMWY7Hs3Mg7FLNuL0aZ+FG2lopitEfHYCL/toN8HPYNCEXtjpVYm1PMbLsVendP8G9K2ILpj797ysH8nYvdGkmXb7vdD/Va4REA/elTODJhKkKk8wD13ZgY3Iza06zH1nSgNtdBn2I5j32ZKyvfnt8acTJm8jhmR/I+Y8fuOZsAm5tJx4zBAZi1LA5BzMj6Lm+CIOzh5EJZB91XLKB4SqMpQz2EBQPJoC9B18E8tpMFpqpjqOr5aeETy4KSeAyHz92h0Le2YkJIgNlAw+HjLj2SwU+UrNXXjvY2b3hxLwlLYQHPy+ZEQeiT/uIpSfvYr8MbC0PFRw7NEI4fykVIKSzdMyg5Bdd29v9mSRvYr1EVioV+Q2ws5hxte294/ahVNo+V1Z9bABa+sRtp0Z5oOpiGVXPnIHJVIVqsTaC6W1GyiuXHb0ERK+eyZhJmT7tbzOTQYNr6Pdi5bBJQ9VckJ8YgYr6tx7gZo4IxHdwCTYeqg6f4RTG3eAZbeOhaa3BUxwYZ/mM6zsjWBq7uQy+csOGAx7D7jS2I8mxASdpKxN0/p+fxLln9faNFkxv7meU3QBUazfzOumR87mGzo/IaNHUcQ9lpblHMBvfpQG29DtqaSuhmhyu+aKQ0PjhG3/3CcTi9qaG2NXHl5Ozt2atPao0nWjplljAjJI+x8zB/ddfh8hVu25mYx9DVIHv+HEQ/m4OyKjY1HDUV94ZKJ6l9xbo8VIMHiVuuwlHfdlJeZri+by2FqxD5UDxSC1j7tRqERLJFi5h3XSAb9/oRznfUagu/VWFQ/ziyiAYePxM3RVRqNsJfvmx3LLY/N/LG9Cg/FJRwj84248gBLaLCxcWagjisnr0ehZnLMLG7BvkvJCJyTjyybb2C5iB8HB7pyXothS202Q7+4oYCHfQ9ltuXuevGClfEAAX01WesytxE/4ydBEEYcXKhrIFvoBplJyzed2puQJXKH76eYlqCxtsfqu4AzF62DEssftOMVyc7a7ArpRKzfr8M6h0ber3PWd9scWfgfJ2N+vwxNrgB1afMBw99fT2qJ3jDyndQGCw4+qvQNS66V/uWLBPuqpojHH/kjPnf/eDrELedwwe+43TwmvRY73bM494Rs4ajbe+Nxj8QXsdPoUm6sJX8TWhF+oMn/CMXYOn6TOx+JxOLWtKRXWplAD9TiOz6aGS+lYYV7PzYyFA2CRDzelDDZ0o05j3/Knbu24N1/oVYm2dhbz0EICxSh6PlhaiuicBEblHMLZ5PH8WhCjZoTJ8Ef/6KsDOytYHL+2CJMzbMGB6AWQuexouZe1CcGYcvX0tHWYcC/fFXsLn3VHvnx3J3Qq0REI4oXSWqCo+ijJMx28UtnmuPlaLiWAOmTTK/Um8PZfblKH33C8fh9NYqXNGXYvw7o6MDMa3B8ikYPRpZHAkbJfNt3tMWT7Z0NqC+LgBj+dOcsxddxZvIHbkMe3etx9JlCYiKCMZtKis+6zTW5VFfVS5uuQpHfdtJ/zLD1X2rQ0lOPeZv2YfNz7N2L4jExFHX2VRXUdzrJzjfuch8Ryru7jrUVojb/UIrmprMZh1oqquEarw3iy7WUDY30kyPRNihj1B7shxFWsndQoVxWO0diqhHk7DujX0ofsYPuevy+Ceq+go/D6g4YVFWMxo/VcF/FGs8176LdWg0i19cvrjJ6Hssty9z140VrogBCuirz1ize4bxb6r3z9hJEIQRhxbKOq0poPjPjoNHQSaKjN8L6G5GUWoe9LERCBJ3mXFXNJaq8pCx1/SBAV1lOuJj0lErxsT63I3Iv2s5Fs2OxhOPAxmvWHzEpDQN2ca/z2i3PjXCHpiBsh05qDYG9I5KZG8/jFlR4TYGOCAoagEG5W2R9EmH6tfmIlryIQspQRHRUEllwNWRddjmlT9laDAtdgaKtmeZ2s71dfkcPNPzwZTeONr2XoyLxDwNC+gFxgJ0aMpdich1pWyLIaM/fWUKIuenm9qsa0e7TgUPjZVFlsYTvp3t+JfRnHQNKCo4LCYYFwvx5Jzlkr5o0dJu8WiTBf4hEajKy0NReDDG8oviAEycfhipWTWICgnkj3FWtlbphz5wH/3Q9UxAHLVhPWpT5iA+vRI68WKHrp2Vp/IU/l6knP8Nj8AvIw4jI8t0Ppr34hnWhxJrHyDj4WTcgIy8w4i6W5TxuEmYVpGF1JqpCDOKXQkK4gNPhxbt1p5SsEGf/cJhBL0dyckz6a3tIFLnx6PgDNt2n4RZETXIzpHoqTILGeWheDDcnm0wLkrkw/UjKw1FoTEIG87tcC7mcXeyVe2tJpm2HUaBlb+HKo39jsHa9d/RaHxtDXKPNzP71qGldAO2HVIQJbVfm2xRFkd92zl5mdOHvllFA83terR/1RNU0LR3D4rE1IAgJ3O5uNefuE9FbGwTNq3JQW2zjsm7GUc2p+FA3wZcWQqkNsViYkaeHosigsUdvVE0N9KEY1bwYWx9eS8GzYtkSzYR2TjciqJEZtM94zTQ3sZmSbf3fkrFKYzzAEkcbtm7BRn6aEy/iyWGh+PBUPP41bI3HdltwjaP0lhuB7syd0H5Aq6IAQroq8/wY8Yp7Mo1yVzL4kz8ojzh8XBZeehQn5eC7EMOznEIguBRuFD2xOyEaJxJiUF4TJZwtXHUAqxfG4iSxJmImDMHETMT8a5PEtIetXEXyc0bsa+8hKDSRITfH4PoOTMRvbEeUS8nIIgb6OqykFzgjxcfn8ovNDVRSVjanYVN0q85RsZh7JtzERETg0hWX4HHSrxqoz7V9OXYOa8d2+bORCRrX/jcjWiPTcNzs+2EP2mf+DrmIvlcJLYkBFtf/AY8hlef1qBgCauDHR8x/02MfSqhz4/KmbWdK5eT7YiVWBFl5Va9EUfbbgmvnyT4FHH6mYNIpqPEQz7Y/EwkG06M+bb1pwp9DGmRp7A6hi3W5rM2xyTjbPQWLLmHL90czwgsmdeMtezY6F+xY+dmYWh4hJjJuD0az/FyZfnz5/K6LhqRhBXRdvofzCZRbOkjfWd87N1ToddPxeR7TBJwSrbWcHkfghH7lBd2Mf2FPyd8BdcxG1Yh6LEtiDqdjMiH5mIxa1fkunrEbmH64S4cyPkfN2l4Kg3zOtIRPZO1mZ0fnlgMr6eSMMval6BFgqZGsjV6MCYGizJ2C8TEKXrow+9FkL335iyRbR8jOA4veu3F4pkzsfaAwoVbX/3CCXi9xbYi2ai3+DRcnrcF8/i7RuZyjuT72YrYtN9jmtzMLCAO97YmsXjLyScGq09HIvP5GYJ/MpyKeZxMfUqZTJnf/orF8eU18I+UxlQrsd9BVMHLkLkpFI07krB8aSIyzkTgpaftv1iqmZ2AhfVbmL5ikKvwIQxHfdspeVngTN9sw2SdGIdGJuuImLmIvn8ust3DWVwbGBTJXC7u9Sssxj2+E38IbUB2UiKTdzrqZ2zA76aI2f3EvDhvFHCvJ3AxcUkhPJ5Ow0J7D8somhuxOPDgVLS0aTBrivn7uPbjsCeiXljJFuKJzEbiEc/iR3yhBuuSol2zsDOLw9w8YCYWF/lgXcZj4lNZGkx7Xhxn+Dg0B6tb/wcvsmGgByWxXAa7MndB+UZcEQNk6bPPCDYR27qxZ8yIS/8W815ZIOhEVh5anCwtRv7BOuGmB0EQDvEj7ote4rbTcI+AgHuHgg+kCuAeQ+xWsVOUR7Xa12bit3gV5U8FC+e7qblXauXhHh/W6aFypH0M/rGWwf1bhywD0XZrcPJlwdnme5b29OdIm/ljmemIf1OzF/0lVw5XlT0QfXC0DDn/ksvXs/xOlm+rT/2NXPucpM9+4ShyeuPkrFfWT23BckSXRqAwg02IufO67finMzbnQFucgrsTImmL/tAGRBQEojDNRRN8KY72v68+2g99c3hMHWh4mdmJe/2FhayZpHBk3Rz8fcIebI52tSXVIOO+VcCrH2DpPc7ppE96lInDeqYAPTcPcuSCpCMomQfYy+dwOJY7KHNXjRV9jQFKcIXPyMXpfho7CeI/GSffUTZH5e5gcOEmq31xZEcmu27cQON48OP61N91yDIQbbcGJ197g589/TnSZv5YOw3tL7lyuKrsgeiDo2XI+ZdcvorlD/QEWIpc+5ykz37hKHJ64+TsTIO48+z5pzM252xbFKAtXo3IFXmoF9+j0WtrkJ9zEEFTgl2/SOZwtP998NH+6pvDY+pAw8tsoGME9/do5+CZ3Dq2GGBJtvDQHs9Bbqk3Jgf3iyWZ4YxO+qRHmTjMLer6bZHMoWQeIFd/H2O5rPxcNVb0IQYoxhU+Ixen+2nsJIj/ZFyyUB4Q1J7wV7v6S6kEQRA3AIM18B9xY06ANLOfxvrgOmyNn4nw+2YicnE6Gme/ilfjXPl17WvDD7lv1x8aTHv6JUw8swVxM5m8Z8YgYXszZm1NQ2y/iHsQPLh3f2naMYCQzAmCuL5wyaPXBEEQBEEQBEEQBPFD4ca5o0wQBEEQBEEQBEEQAwAtlAmCIAiCIAiCIAhCAi2UCYIgCIIgCIIgCEICLZQJgiAIgiAIgiAIQgItlAmCIAiCIAiCIAhCAi2UCYIgCIIgCIIgCEICLZQJgiAIgiAIgiAIQgItlAmCIAiCIAiCIAhCAi2UCYIgCIIgCIIgCEICLZQJgiAIgiAIgiAIQgItlAmCIAiCIAiCIAhCAi2UCYIgCIIgCIIgCEICLZQJgiAIgiAIgiAIQgItlAmCIAiCIAiCIAhCAi2UCYIgCIIgCIIgCEICLZQJgiAIgiAIgiAIQgItlAmCIAiCIAiCIAhCAi2UCYIgCIIgCIIgCEICLZQJgiAIgiAIgiAIQgItlAmCIAiCIAiCIAhCAi2UCYIgCIIgCIIgCEICLZQJgiAIgiAIgiAIQgItlAmCIAiCIAiCIAhCAi2UCYIgCIIgCIIgCEICLZQJgiAIgiAIgiAIQgItlAmCIAiCIAiCIAhCAi2UCYIgCIIgCIIgCEICLZQJgiAIgiAIgiAIQgItlAmCIAiCIAiCIAhCgssXyl/sT8aC6IV4af8FcQ9BEARBEARBEARB3Dj8yMAQt21zfBNGzf2TmLDOkj31SLqnBhtGz0U2tyP4JXz0VjzuQBv+tngKnjvE9k3fgGM74zCcyycIgiAIgiAIgiCI6xAX31EOQPTz0zHccwyi46ezRTJBEARBEARBEARB3Fg4fEd5YXYVnp7Ib5oxaOgwDLpJTJhBd5QJgiAIgiAIgiCIGweH7ygPch+GYbf0/gmL5Da8lxSNqGj2SzrAUjK01eBvm5YiakoQRo0OwazopdjwTh0uXRXzjVyqQyF33KwQdpw/xk+JxoKn/4SKVjGfIAiCIAiCIAiCIFyEyz/m1dFah1Mn2a+1Q9xjgwt7sfi+uXju9QPs2C624xIaTh5A9pPR+JV0kf31ATx3XzSe4o77/BK/q4vVUfH3TVgwcwn+Rt8MIwiCIAiCIAiCIFyIwwvlqjdSkZJq8XvfwdXq1c+R+2QSPrzCtsfEY+eHVTh9sgofZcfDj+1qePN32HaYWzwDbYf24m9fc1sjsSS3CufP1eN8RQYWjmS7rhzCS7truEyCIAiCIAiCIAiCcAkOL5Sr/74d29ItfjWyD1mbc/Z97ODXt4OwZONLuM9nGAYNGYY7Ip5D0gJufxdy3z/C/s/o5v4n0PXtJXRxj2V7zkZySS2/aD79XLCQSRAEQRAEQRAEQRAuwOGF8sRfPo4nlln8gh37PFfbmRp8wW91IXuuP//esfALwuI8PgO42AbuQevhUx/GfTdzOy4g97f3YfzYIEyKWoinXt2LD8VHsQmCIAiCIAiCIAjCVTi8UA6ZvwJPr7D43c89B+0APXeJB2F4QAACJ1j5eboLh3g+hJ0f5CLpl8EYzi+Yu9BWdwSFO5OxeNYULH6TXlImCIIgCIIgCIIgXIfLP+alhOG3jzFuYeHmQhQVWvltmG36M1KeYViSsgfHautx+kQFSrIfx0Rx0fxh2ts4xR9EEARBEARBEARBEH3nmiyUMXEaFoqPU29L3YsvjH8O6tIRbJgl/PmnqHWHcIn99+G6aEwK8seoezeh4ltg0LDh8Jv2MB4wrrUJgiAIgiAIgiAIwoVcm4XyoDA88fJ0DGKbXaVJuPfuKYiKfgC/uHshsj9n+1q78EDsdAxj/015cDrcua9jX/gTFoRyx7FF9L3R2HCSLwj3rYhDILdJEARBEARBEARBEC7g2iyUGcN/mY3yvBW4z5Mtl6+04dTJz/mPdw0Ljsem9wrxRIBw3KDgFfir2XHc32juwiDP6ViS/R52/tKxD4kRBEEQBEEQBEEQhD1+ZGCI29eOby/hkp79e/MwDONuM9vCeJyKHTdE2EUQBEEQBEEQBEEQruT6WCgTBEEQBEEQBEEQxHXCNXv0miAIgiAIgiAIgiCuR2ihTBAEQRAEQRAEQRASaKFMEARBEARBEARBEBJooUwQBEEQBEEQBEEQEmihTBAEQRAEQRAEQRASaKFMEARBEARBEARBEBJooUwQBEEQBEEQBEEQEmihTBAEQRAEQRAEQRASaKFMEARBEARBEARBEBJooUwQBEEQBEEQBEEQEmihTBAEQRAEQRAEQRASaKFMEARBEARBEARBEBJooUwQBEEQBEEQBEEQEmihTBAEQRAEQRAEQRASaKFMEARBEARBEARBEBJooUwQBEEQBEEQBEEQEmihTBAEQRAEQRAEQRASaKFMEARBEARBEARBEBJooUwQBEEQBEEQBEEQEmihTBAEQRAEQRAEQRASaKFMEARBEARBEARBEBJooUwQBEEQBEEQBEEQEmihTBAEQRAEQRAEQRASaKFMEARBEARBEARBEBJooUwQBEEQBEEQBEEQEmihTBAEQRAEQRAEQRASaKFMEARBEARBEARBEBJ+ZGCI2wRB3GB0d38P/b//je7vv8f37Ef8cPnxj38MN/ZT/eQncHOja5wEQRAEQRD9CS2UCeIGpfO7Lvz76lUxRfwn8ZObbsLgnw4SUwRBEARBEISroYUyQdyAXOn8Dle7u8UU8Z/ITW5uuHnwT8UUQRAEQRAE4Uro+T2CuMHg7iTTIpngbICzBYIgCIIgCML10EKZIG4guHeS6XFrwghnC5xNEARBEARBEK7lhlso60/m4PnEDSi7KO74D0DfoYP+eryB2K1FbWkNtArbpm+uRPUZnZgaILr10On0YuLGh/tw1zXh63P49Ng5fCsmbwi+Oo6iLS9g2W9+g9+/vAefXRL395Xv/onPjh1n8hB/574WM64NtmzC1f7WX3FIf7IQBYdawXuprL/q0FJRiaYBDiNS9A3FyC2sE9r7Q+PiYeQX1DEpOwinNxn7cMgeO3XQdYrbztBWgyM1WjFxDblRxx+p/B0c5/sXBf6vZ213gcyv23kXQ6/rY9uuF512NKBkRzqy04vRpFRlLtJvX3F0fHXpeOyEDPpsM9cbA2jDA7NQ7mxFLQtu1RUNjg/AFpw9tBdlZw7i3ePXwSDYD+gv1qC6Qdq3GmTHxCC7Rky6BD1aathg01cRNhRi07qNONAgpu2iw5EdyViVd6zPNuAQNVmIfLYYSrvaW/79jRZNFTVoUTgp5L5ubclnf4zGgw+l4OPvxB24gKIn2L6V++GyJVxjCVtslqBZTNrj28Mb8ctfbcOn13Is++4o/vjbV3Bo2L1Y8eKLWHL/aKjFLOWcQ8Gvo/H7ff8U0yL6f+LzE1U4wX7v57yM37//hZhxbbBmE331t4GJQ4zuOuS/cBhD7/KEikvL+WvHMeQmJyO/ckCjiBkqv0CoC7egSMYZBj6W2EJpvNei5LUt0PsHOO4rbcVYG5OEA21iuheO2WNtVgwis5w3tqaijXhmYyGaxPQ1w8HxRxmOjRnOYCZ/h8b5fqaX//eWhbYoyWGZD1i8cwmtOPBsH9t2Xei0AflLlqOg0w8hAT4Yyg8AlrhGv67H0fHVtfNfx2XgqM24aI3gCNoGVNeIF8yVMIA2PDAL5Y5K5K5ejSdXF6NR3OUsQY/vxM6tO/FilEbc88NCV5mDJ4v6e3jXomrHahSdE5POMi4Buz/cg3njxLRd1Ji2dj9K185wYsEycAyM/KU0oWh1Dqo6xKQMtv8E1Ec4flwMMU0VeP8azhCHhC1GyoY43GV14Bsgao+jyCMOT/5mFkaPHInRk+7BHcPEPMWMxv0vvoLHZ9wqpkWG3YWo3zyGhewXdZe47xpi3Sb65m8D5Qe60jxk3xONaUrDufsMPPv+fjwbcS2jiDemR6mRX1Qnpq0z8LHEFgrjfd1eZLfEYdoEMe1SBjb++yTsQfmeBPiI6R8Wjo0Zfcahcb6f6eX/rpHF9eOrA8R1odPLaG/zw4NxkZgYEQDrQ8AA27piHI1nN8b814SL1giOcK4YT+6oVH4hYQBt2G0NQ9zuHzpqULCzAIcb2pgAOqG/3AyMCIXvj9n+7Ddx+LwKt/3kBHI3JOMfg2YjzJfNrlsrUZCTi7z0PJbfBr2HP8b8XJh1t3yQgwM1Z9AyKBB3eqnQciAd+fuPQTciEIOq92LHtu0oqe3AUP+74DWEP8U6rTUoys9B7laujg6ovEbjjltMM3vdmWIU7PozsrfvxceSfO6xu7y893CsgenprpHCXZDuBpRl5KHkWB1+5BMMLyc9getL3oET+KzxX+i+oMWg8YEY8dNWfLyrBIiIwk1lqcjYzNrb6gbfO/3xM+lCpLsV1W9ksfbmouwM6/9o1n+r7WhGWXo+PvikARfaO9DSpsK4IC/oa/Zi18lBGPWvYmRu3Yym22IRxK0P+HJzkP/ndLz7cQeuDPXBWK/BQlGcbrMPo5tvJ1fuAej8vXChgGvn2/ik8yb4jh7Vc6WQ19XnXggZ4w4dX99QTLhagZ2pKcg9eBHdmtGmsjm6dah/Pw+5f0xhdXfiZ3eORPs7O/DZEGY/t4jHWMLpNXcbMv50EBfcfDBhSANyT7hj/oPjwZdspz/W5W//HJ6OZhx5KwNZnG6YrVjaHm9Lma9j677j6Pzei8lEAxV3iYqX35s4+lkDWq+0ofFbQTbcIyX1n7RhqJc73IQieujS937M9l/H89GgH4nazhGIDhuJL9/7A07r78CX8EXsbH+x33r8s/4f+Mf+w/j8GxWG3vZzqC0L7/4nzpV/hA8/qofup8Nw+88lBtRahb9+CMz+7zH47viHKK1oZLHfE8N7jJCV/2kNzjV9iX+2XIK+6yaob79F8A8RfcunOMXs7dYhl3Duw/348FQ7Bt3ig1ss/FTfchrl772F2hYVBv/8Vrg78FeQ+Do++wKfVe5HxT/VuPPWH+PSRdamrsG49RaTzrg6qg+9j8qz32DQMC/cMlQiDO4x85Of45/svK+/1aN78M8xXJovgZP9AczAgv+SLqYFWXzxvfS8r/HFsXp853Er1DeJu7hHuKu/ws1MTt+eKUFpwVGcN9wK79vUJr3rmU6YrN6p+hIqM3mbM0jVe7/U3zh05w+iKGM7Xv1rGS50qOEXOBKDrVwq7VMc4h6l252JnK3M/7Xd+PkYf3jY/DC3DkeyU+A29SnMGCMW8uUx5DB/jZ3UgZLUP+BVS5/h41cumrgxhMUARXGkZzzh2tSJoXeMxwjR5oTzzePe2G+KsfN9rSm+c/AxvhBaMb4P/qkWxSl1GPM/oRihWIYsQzaefoabR3+Fg1zfz45E9MTh7BwFcdCm3K3He2tWVF+wDgd94rHkHlYnWDtz9qLRKxh3iGGAl9W7X2PURG8hprBjjuzIw4Wf34M73M6g5K3z8Jnlj6Y9KUj7w3s43emOcRIbs7RHe2PWV0dz8S6mI+ZHZbxe8j9qw00jx/fMA+Tg21qmF/oqyvVngd04uoO1jRsb9BqMGutl1f6NaCvysDNzO/IOnkHn4NG40ygIBteXkks+uPlEHtJSioDQ6fDlbEpu/GHYLlccQ0cOwie7WTv361mxYvw2YmvM4PMc8T2GHb8Q5D8biyd7iXUax3kh39SHi7xebq7OYvIQ5mSKfFKCtiIHhY1eCPIR5cDX9x6+Yb5mFI22PAd7Gzzwi9EdJv8X55CWsuj8rBj550cjyu889rL6M979FN0/Y20bab3+gYt3DDs2b8//mz7ci5xtm0X/H43LhwrQEbwQk24Tz7VTrrUYF/RTc50K9uyPW5sL+GO4egb7sjmvu6SznL1k/RGZuaJt33SCxclvbMYTDpu2zsai7N3v4hOj7r6wEpds2LpS/drzX2s46pff9Ipn9uO0NP4p8hE7Y4VRBtK4YoYSm7Hp/3bGDDsxg0NujmFLxrw8CsrxyecXoW9rgF4c3+1iLS4dL8TujNd4m+DmDWP9Nb3m0M5gZ5gwce78eSxd/hTC75vJ/8ulFdPZjKPFdWjhE80oKShEbbu4n23nlv4VGc+mIL+mFS1aHVuwpSN+/mqkFhxGI5tIVR3Iw9rEuVh7QHgGoL2OncPOO3peuO5gTJdkbUT8uhwU1LDAVZSDJ5ems4UDf0hvLhbimUWr8EreQZRdFI5/ZvFcPFPYymfrDqxGdCJzwAOncJlvA5e/GNk1eqhuH4r2IlbnjjdxxPhYwplSZHB9qVTBw1Pc5wRDR08SBosRAQgJ8YOHJGoceS0FVZoIxD4+F0GtOYh/lk3axDx01iA3nrVPG4CohQmYdXs9ti1ORIFVNanhGxIArhqPcZMQMk5wAP35cuTmb8DWv+kR9MgyhN3OdnbXIXd+PLae8cTkR5OwKAz46LlEXg48vA7L0cjLuR21nAw2Gts5A+pDW5hODvZcIeJ1VccpX6yvcAtS83UIejAB8ya0IP93iSyfz2boUJu+GIkFLJ+1JzZMhZIX1iCXyZ63H2vwet2IU6z+RQsfhm/DFqzNrRczGTL9sSp/ORlw+UtYu7XBWLQhCbFM9ls52xM7rS1ahbgXKqEKewRPPBIMfeFyxG0+LDxeomKOzHThwXTiE8B0MVoIGtrijVjMZLHLgUerPKZOw32H/4HT351GxTu3IGzaaDGHwRbAh5IXYFnWx/j3LWxRdjQLifOfxaGvxHyOrz5C2qNPIPXQOei+O4dDm59A4pajFu8kn8Pf1m1C0YkvoGvaj5eeWIrcnuerv8Xnxa8jewf7bXvF6mPa3x7Pw++3b8Wrv3sdH577Gl9X78bTvzVvxz/feRb/vTwLn33N5HAiB08nPIv3heChiH+3neMfif7sC6aAb9mCWXxE+kSjqSf/3P8C4lkdx7+7BUO+/ge2P7EAa/ZLHq9uOSL0g/02v/Iy/nbc0QfYv8aJXMvzvsCBl/NwQvqe9KUq/O3lLPxpw2+wbPNevH+8DEUn/2maLLTsx5r5TyD7BCvn60+Ru/L/sOYdi8fA7SD1N9QxnSfuQXtIAtYnPQKvMylYnl5j9TEnp+NQazGen5+EavVklv8IgvSFWD5/A6ptXiKux9kaTwT5C3bfQ0cpUl8oBkSfuVywHIk9bRXijDEGyMYR1u/4+SmoHz4Zi5ISMBmlZmODtbin8hyEFml8Z+gr9mBtjRpexvg+islGX4mzNh6/diqW8PF0NzZtfhP6ENb36VxlCuKgXblbj/e90aLxlA5h4/zEtCdbYO7F3yuEMZFJACffzUJu3h707GKTpr/nsUZw62qeZuSn7sblcQ9jER//kyV6s7BHccza1uCNWWzMihrV2nvMqkjHtmMaTGP95vS6KzEJRca6ZeD1Wt4s1M3LdR9SU8S2xd0Nbf4qLN9h64kAPWq3x2NBjhZjmU0tejAA7TmLEW/Rl6L0Ndh60pO1PxpjOROWG38sy53hjXqm2yfzjUYk2HbGmi0468nKeDi4990nG2OGpQ1MVlciee5ylNiSl4xfmGE2zrOwxPwx7rV6eM3gZOONxtRkpBaa5mTyY7s5GpUO2fmVPXFEX1PM5n95EttrRUV+HtrdOH+Q+L8tWXBczMNWsf4nZg1FyYuLkWF84sqCAYt3FvO0qAAtshfNVeT/i/O1Ev/fgI+kd1hl5n/WYpylTnl7ztnY42/T3Mvx/JKNKDN2lrdtZi+3S2w7dZ/Jx3oh40Pu3kzWEt1Zi0tO61fOzyyR83frfmkWzxTEaenxsj4iN1bYRYHN2PV/G2OGXMywO8ewrxPVCD9Wjwer2gdBIZPgK157sIuFDXPrtrjNNfB4cCXWPz6Znzc8X6BwwJCD+zvKcjy+7EnD1OkRPT8u7RAt+wyr+HPTDCfFXaZ9kYZVe+oNl690Gbq6ugxn30kzvJ6WZnjn08vCcUe3CPUu22doZ8mTqUIbVr3Vwmcb0zOW7TE0drEd7eWGbdHCvm0f84dY0G44sNJYb5Ow6/ROQyJXR3Sm4SyXv0w4f+s/hGxD/X6+Ta+/zx3fZajaEMnnJ78vtLFx1wI+nfiGWF4faH9rmWFqarWY4qg2bGNlb/pAlAfHlXLD1unLDO8IIjBc3r/SMOPlctYyE/y+Deb7TLQY3nncXD58vQt2Ghqvijs4rnYZ2uubDO2SfVxfZ6SJ7eN1aGyHlXby+UmGQ98ISV5XYt+s1XcyNdIQl3lKSDTtMSTOXm+okBTH72N1WNeroJfEXVIdXDZUvMx09bhgO7L9YfSSvyIZbDFU9eSz4y+0G7q49NVThl3RCYa3zgk5PMZ9Pc3k5GbSJc/VdsPZ6ibDZUmdRjou63r9jm6OMKz462nDBy9FGjZt3mT41WPMFz5KMUzl/uWO+fyQISfl74bab4znaNmxEYaF2ad70uVrIw2/eu24mGa/1g8Mm2Y/bHj9uJjmypu+2vBBq5hmv5rXHjZMfekDQ5vxHOOPPzbFcNRif+Nflxqmzs+StOMLQ+EKFk/+8rmQ/my3YcnsZw3FzaZzarMXGWastVKHzI+vy9h/s9/nhvLMFEPxJ6Z9bcXJrF07DbVmx3G/zw17HuNkK7bPyo+T/dTNFRb7rZ1XwXx2qWHP55LjPt9jWMHikPXyTxvyFkUani/8wrSvdieTT7KhvE16nPCzRi9/e+Uov81zpd3wZbv16MDhTBw6mxFt4X/iPltx0SI+8HycxmzHwmcus3pmG31GaIcxBsjGka52Q+M53vtFmgxvLYg0vC52zdr5nA9XvGwaY3pii1k/esdQS5yLJQsMb5wWkjwK4qC83OXbKsg12rBLFBtH10frDTN6YifLj9xi2PZKZM+4d/n9JMNU47hjre3ndhsSJGO+1B658Wnqyv0sQpto/2inYdcHQpv5Y18oFcrmsdSJfXjZG9turW3Mzmbw470V+ONXGg5IzcbMBq23T3b8ad9vWG2pS3Ff1RUuYcXHrMIdZz5m8DafIVEeo3FXgu05gIxfSHUlyEOsj/N5Tg5S/+T3mXQj65OW8Oeb+sMduy11i2HGs6WCfXxTakiezuQmkZHJlnvLwlr9/BzNLJ6Z08tXremij/GOr8PC5rs+ZD6WsMfwJZdQ6v/Mr6T+Lzf/syYPM50yetuzEDMEX7dm2+I82GjblijwIWu6640T+pX1Mwtk22rFFhhmPqIgTkuPt9YHMx+RGSv4823JXoHNyPm/Uf9mY4aSsdTWHEOJTrix31afrGHFhpfvkRpKi+FLa/p2AkV3lD89WStuCVim+0YkFsb5QT1YBZVKBf+oZVi0IBK+l8tRkJ6O1JxS4TCZL5uFTA+HD3fZQzMVYVOEfVbpOIEjx7mNqfhllDe/i3vW/Q/79qF4VwL8ocHYYOFtiYJ1c/H8unQU1Hti9oJlWDKbO16FibMi+SssJcdOQI9WnKzkrlp4Y9YUsTwLtAXL+bvxpl86HJWg2l1yNW3wEMnVNz1OVtUgSKMXP5gm/M62sZxTTeKdfIW4a2D2hKmbCho/b6jbGljZB1G0Ix355Vq7X84za6enN3xwGZeNV5wssajvNm8/tHQKfxdWf64etcGTMUFSHLxDMYu7GmqVVjSeUiHsHqkO1AiZOlXcZjjRH9lzhvsjaHgxVi9NQVFpHVp0zARv10DF9au5Boe6WXtaTHqprmzCZXUzms7ZuTLopoF/MKvToWdGfoJfTJ6Mov0lGPNAGMyeWhlxD2J/PQ3qpk/FLzV/ii8uAee+Nl4uPo0Th/X4fxPHi2nGkMn4dW42fmm8wcSjgVrymM0tI+5gYtc69iXsYbdI+nULbvVi8aRFuEv6dc0RfOZxC/T1pi9Kf83q1B//DBf4I1zBrbhrwWO455ZzPV+uPn3hG6ajr2Hzxme/MhP//ZDFO9AcX32K4023QPPvz3tk8SkT0y36KnzmxKt0mvGB8ClOxpMphThS1wwdszEvTa9r+LLYjkPNOFkB+KpaTLbOfo2datQ22LrrwOEJD8urx+6hmDBK3OZQ342Jwc2oPW1DQ3biCFQa+HiroW2oQXVpIfLTd6KkTW/u85Zxj/UqZNoMVJWKd7k6j6HsUCBi+fjfBxTFH+ZjEnnIx0Fn5W4Nb2iEoY9Hdc+9iKo7hpPcnYgzTAZTQrEobCrK+HGPjTvHKjFr0t0SGzBvOwar8XNx0xxhzJo1K5y/M2NEE56AhRESGWukr26oMFR6sMNYtG2kN0I69LD2V8j1p0/hyISpCJHIwqoNmrVPfvzRf1qDslEe7F+TnqpPMwvT16FRcuPDzMcU0YyzbE4zKyxATAv43BMKj8pT1j9opsQvrNHahJODLfxz8CRMDhe3jdjzSUv48+tQ/SknW/bvoamYuDAUUTVHcZLNHfTs35JQ5gPWn5y2jkX9Q9VSZSrHdfFOjzN1dQibGmpm8yrm29POn8DZnrt9Cvx/VLjE/xXO/3rFOCuY2bMnfP0BnY7TiTXbViGIxQJbKPYhZ7GjX6V+ZkRpW+35pePzVYY9H3FmrioibzMMZ/xf5hx7cwxHdeIMvgGhqN2xEmtzipkPtkLv7gkvR2KGHRQtlO+aECRuCVimXUlTXiIif5WI3yZnoaiyGc48y2zldT0TndzD1BxDMVQiRBVzArX4PobPwkz84dEZmOauxxFmEKmbVyH+V3PwvPG5r+AILOKCWXkNzl6sxEfc4xKjIhFmYx6lidqAYm4h3vN7DK6ToA66r5i9XTyFqqpjpl+HNxaG2nrMTiG6GmTPn4PoZ3NQVsWG21FTcW9oHyeLCtF1MFmrVRbtZ2mbht+O9jamQ4t81WDJC67O9EfuHLcALHxjN9KiPdF0MA2r5s5B5KpCtHDB4xstmtzYT6qXqgaoQqPhw2zL1aju+X+Iwl34fyEWL3d8dxoFv1uAF/9SZfb1SCn/1g+B2uJdYNUQNjGQG1xdjdvXaDY+Ls39Lo3Ef08bA8n6vI/ocS5vBeJX5uHjf14R912v/ATaJoksTnyNOx6ahjvsvQNni4DHsPuNLYjybEBJ2krE3c/imfiqiWvg/I/9v1lq68fQqArFQr8hViaORqwMzsPZZFHcFFBjKJvECJM2x9AfT8fiOTFYnXMQVedZbJ86E9MUhDDVlEjENhTiEBuC9Mc/QtFdMxDm3FzbhBPxRz4OOit3a7CjpboYzCaLoWxCU6NHfXkxgtiiWM0tno+zxVf3KVSXB7PJs+3Jo22EMWuo3YH62sHLfKQnW7JIkbNB+fGHL7eTLWoleqqq0sInli1oxWOcg6vbG14jxKQRNhH3snUxwEm/4Mc0tbqXPQ7qkypVmDApVLjxUFeOovFskq/hFs/HUM/advbEYUybxmxPPPr6wFG/E2zex9MiiKiHMN3bvpkg7//9OP/rQd62LXHOh1yDo37mirbK68lB+jD3VtIWZ/xf9hw7cwxHdeIM6tnrUZi5DBO7a5D/AltHzolH9nHX2JqihfLTK57sWRxz/3Lp/qEGB3IbWJCZis1v7cPO3a9ixcOBYl4f4P7mmDEQefojiL9iV4rqk/wepsBKZMfHY3F8Dn+nV69TwTd0Lpbu3IfSD/Zjz1PB3F6UFYt3GNjiKGw2C9v6Ury74zCOsF1hUeHw4vKsoeIW4dKfa8KXABsM/VXoGheNJcuWWfxm2G6TAnQVbyJ35DLs3bUeS5clICoiGLep+jfIGdH4B8KLn5CJOzi0NThq81PwPvAd14raevP2NZ0xvejrTH+UneMJ/8gFWLo+E7vfycSilnRkl7Jj+LsW3DsmlnpZhtjgfhj2fzoZv85/AdMt1sn64+/iT51xeOalBNw/7R7cNeke3GlmGBrc6vUttFrp8M59kOo4vnDZ35dSALcod5uA+8UvSpt+98LKPVfn+K4a7+d/i4UvvoCFD93Ly+KucSPFTFdxCzSOX98zR4zMd86xlMVjmOLsp3yHB2DWgqfxYuYeFGfG4cvX0lHmsq+Jcv6ng9ekx3rZ+pJ5Vt615HD3YPGpCV+yCacZDfU97x0JNKPxUxX8RzkqVB2OvFmI257ajT+ufxpLHo1GWLA3VDYmpWa4BWN2tBYlFXWoKjuIqAcjLPqghfYim3w4cCHJmfgjHwedkLtVmC5ub0CT2SNIaoTMCEXRib2oKvfGxLtYadzieXw5ThYeQ5mfxV0YxWjgG6jGkTqLYC4dp68hvMwrTkD6drG8DcqPPxpvf6i6AzDbUk/sN016h9Zh/DE2uAHVp8zr1tfXo3qCN4zf7jHRB78YHYhpF0/gLD8REumuQ22FuO0k6tAIzCqvQVFlOXwncX+ejFs8B+LQ8UJUH/LDZPEpv+sHR/1OsPmyExYvajc3oErlD18bZsXbDOf/YpqnswH1Pa7Tf/M/E5x9tQp3ACXUV5WLW71xzodcg6N+5oq2Oj5ftU9f5t7yNuOM/ys8x8Yco/9inzlq71BEPZqEdW/sQ/Ezfshdl2ehV+dQtFAePWoUMtJeQ/mHH/D/cmmHGDxUDBzlyE9hgjvPJ6wwCIP4qx51OHqAuz1fiIzXxEevnaXzMFIfikHknMUo4N8bD8C0WO4yiA7ZzyYilXu8e0Uyci+2oimQBQQ2ATqycS6ilyRi1ca9OFLJFsLcFR2GaiT3WQEB//BIFoR0KDrEDYQBuHeKC51f+zV0lndZ7BAUtQCD8iR/17Nbh+rXWB8kHx+xhk5r3/HUbLavam9Fu7EtbYdRoPRrKn0lgAV+70Ikby5GUyubQLXWoWBjHhqlj8+ZoUFYVCjKduSg2jj5b96L7HxTcFfcH4n85c7RV6Ygcn66qU5dO9p1KnhomKUMj8AvIw4jI6vSpE/WpmfmLEfJRTHNo4VOumDh/+649b+T+eMf23dZ1ZDeF2FUQ9i0o/0LtIofkvq2fg/+9oGwLTAS/++h8SjatxdfiM9Rf1u/F39MLsZA/oXgW6b9ElEtefjjPtOD1t9+ytJ7z9m1Y4f4yc1Qqb7GF8aPe106h6J8M2G4ABW8R4/Ex2VH8E9R7//cl4ciYVMZP5+GB6d9hT+l7+spA5c+RcGWPfjCQhhyNsFd9KhNmYP4dJMd6tqZzak84dF7RmfCoTikYXF1Boq2Z5l8obsZRcvn9HwksReD/eDvV4cmsxGdoTqMbInPtOzdggx9NKY7/Ke41PDwVKG91RQDtId2o8DM92zjPz0S7QVrkFE+A9NCLfyqoxWNHcEYK/lmnlUciCVWkY2DyuVuP957w5fJ9+x583PUd01CSHEeshGKCfwQp2YLGA2LaYXwCA9mtTuH/+w4eBRmmsYsXQPyV8Rg0yHzybhtuL+v2k9/53NcJOZpCpG919g4JTYoP/7grmgsVeUhQ1KurjId8THpqHU4wEnHDDXCHphhXndHJbK3H8asqHArOuqDX7hPRWxsEzatyUFtM7NH7i8+bE7Dgb5e+3cPwES/YmTkgy2KhbkUZ3s/z8vCLk04QuxOryzGT2fp53jH23yBxOa541PzoI+NsP2E4V0RWKSS2CI3t8tiZUjk7ez8TznMvv47Go2vrUHu8WYmax1aSjdg2yE7SnfKh2zhoH4d9TNXtNXh+ap9+jT3lrUZ5f5vGjPkzpGZYyjVSYfW1GcG//fNFf1t5VYUJTLfExZ5PO1trK23s/rFdF9QtFDuMyy4Lnqcu8qmRVlRId79VDJ4mBGAec/HIWiwFgXpq/Fk8l6o4uIQJuY6hUojvAOn8uqZFPosSMMfFwZA092AgoJCFJzhJkXLsHPZVDbFZQHw+S1YOkGNlvIsPLN6A1LLdQiKMOaLTAhHlNEJ7okE/4FCF6CZnYCF9VsQOTPG5lciezFqAdavDURJ4kxExMSwc+ci+VwktiQEm9prhidmJ0TjTEoMwmOybF9xCY7Diz6lWDyTOcCv5iBieQ38I83fg+o/PDErNZM510Ekr0zE8jX7oHp0DebZeedDPfv3yIw8hdUxcxDNfhHPtmLe05FiLkNBf3rJX+YcVehjSBPrjJ8fw+SfjLPRW7DkHi6XDTBPpWFeRzqi2flcm8ITi+H1VJLkfZFgxD7lhV1Md+HPiV8I15Yje/VBtFhRnpvsosgKd81F0r1nsGFBNB58KBoJf/w37rp3CPDVNz3vF98y50VsCT6Op+fFYS7zufg1n+Kul3+HKXKf6O/hn3h/pVD+gy/uZ+n9WMlts9+flH69e8hk/PYPv8Gt76/Ag7/6H8THcW39GvfcN9qGHTuB212IXTENdWn/I7T11+nQB0/DrfgKXxu/SF2TJeQ99Buksdjw8eu/EdIr94O/wf7VfqwR+8Z2sa6+IB6fhc+4fMat9y/Dr7/Pw+IYbn8cdqjCECXmKWMI/mtFKp4cXoJlMUwfC+JYW7Pw9eRZuMNCGPI2oULQY1sQdToZkQ/NZW2ag8h19YjdkoAgG3dEnYlDqunLsXNeO7bNnYlIFociZibi3RErsSLKVnD0ZGHUs/ddFr8EPDHqTcTNiUH0nJmIL9DgxdTH4O/EawBBcSvhe2A5wufMRfycOVh5MhBRSkNYAJtAqbRoiYzERMtH6OpPoeyeqQixMxFyNJZYRz4OystdWbwPmjQD1VV1Qgwy4hmKe/30/KLY+CCDJjgUPnoNZvXlNRxuzPq9D97lxiyml4iHlqNs9Br8brbCpXd3Pf/3Vbl3WF2OmzdiX3kJQaWJCL+f+cr9M7G4yAfrMuzboOz4Y1auYNvRG+sR9TLzQ4cCXO8xw8wGmDzD525Ee2wanrMhT+f9gsWSx3fiD6ENyE5i9rg0HfUzNuB39r4LowhPTInwg35wuOn9Z89gTB6uh8/0UDt3Rq2Mn04wIPFOOk/jbJ473icJaY/aETz3alfqSrbAZjbDx8O5KBi1DCuk3w5xeP7nOKrgZcjcFIrGHUlM54nIOBOBl562fDFdgpM+1Bsn9Ouon7mkrY7PV+3Sl7m3ApuR9//eY4b9c2TmGEp0wvXZay/r80ysPSBour0iC0+WNCmwY09EvSD0OSImnrWPzRsKNViXFO30xVwpP+K+6CVu9z/d3PtoKvvvEIvoO/RQueoRZa5eJupej8mx/Tody+HeubHmEHL51yH6Dh0bbNTcKwqug3skTq+C2qWFKoC7smQm92YUxCei/en9WMI9DW8LXm9s4mLLfpzpj9w5crbCP1bIzldi05UpCP97MIo39f7j9N3d3+PbTidnh6yN3/5bhSF2/84jO+Y7tkyzcmd6QPnuW3z74yHoz2boLzF9DevnfrJ+6H/Sx3e9ZXQyZPBguLkpvIDSyeyQxeB+9WU5X5DSWohnElux5C0rkxKuHGbqrmirngUEPfcKjENFsXizeDl0K/Zh4QRxF48e1RtjUDZ1H1aEO9E2R+OP0jjoiNyt0VmDjPl/xdidr2KWK2YXCuHGLCYMx9p8cS+eXKrFE/uY3Yi7+gXOX1gUtnw/0y68HuyMPxz95YcO2oBTftHLHvU4sm4O/j5hDzZHD6DhXC844XfO2LwSXfXL/M+Ihd71hzYgoiAQhWkyixFnfMhVOOpnfWmrs/NVe/Rx7i1nM874v+w5cjJ3QCfVm2ei6O59eJF71VUhfPvcXGtvA3NH2YibskUyh8sWyRxcvdYCEtvPvTNsM1jJ5V+H8B8lc6HoeDincHmhMujrkBs/F6mlrcLHfthg1FSYhfy2qQiRfJzZKrze7LTXmf7InSNnK9z5Cm26pbkeYfx7Wr3hFkQ/uekmMeUgrI12F8kc3DHXepHM8dP+XSRz9PsimYP1o8/xw45OOFtQvEjm4CZR/e3Lcr4gxTMSCyPKUXRIuIJsBleOi9rKTWKVF8UmvlodWg7sRj4WYJbZIplxsRD59QsQO8XJtjkSfxyJg47I3RqDgzE/oQtFhU6+WOck3JjlcJsvNKN2+qT+XSRzcP7i6ISL14OMfvvLDx20Acf8gkOLstVz8ExuHZvssiSzR+3xHOSWel+H7xEPEE74nTM2r0RX/TL/Y2iLVyNyRR7qxYdB9doa5OccRNAUBa9fOONDrsJRP3O2rX2Zr9qjj3NvOZtx3P8VnCMnc8U6acWX9QHCtzEcgG+fi+1tYO8oE4QD6M8UIzsjCwUndfwTAT7BEVj61NM2vy7+Q0HXUIPLnsHwshMfrnR+h6vdXEQm/lO5yc0NNw925hPYhH0aULB0DYoGBWPJ0yzeOPv4nIv4T42D9tBfrEGTKhj+w8UdxMDRVon817Kwq6IZOmaPmlHBWLTs9/3zgUri+qBbi+rcFGTvrURtJ1uMuHtjWtwy/I77cJmzF+Z+YFCcdjVaNNXo4MV9NEzcc62ghTJB3KB0fteFf1+9KqaI/yS4O8mDf2r7z3MQBEEQBEEQfYMWygRxA8O9s6z/97/R/f33+J79iB8u3NetuQ93qX7yE8cetyYIgiAIgiAchhbKBEEQBEEQBEEQBCGBbksQBEEQBEEQBEEQhARaKBMEQRAEQRAEQRCEBFooEwRBEARBEARBEIQEWigTBEEQBEEQBEEQhARaKBMEQRAEQRAEQRCEhB/QQlmHlopKNOnEpCvo1kPXoYO+W0y7gk4ddJ3i9vVOf/T/eqZbi9rSGmjt9FffXInqMy4yMm0lCnYchlZMEgRBEARBEARxfXDjLJS1DaiuaYVeTPai4xhyk5ORX+nsIkaPlhq20JauWtqKsTYmCQfaxLQLqM2KQWRWjZjqG/qLNahu6MdlVj/0/7qmoRCb1m3EgQYxzZawTRU1aOm5sKHDkR3JWJV3jG25AE0wfNs2YFe5TasmCIIgCIIgCOIacOMslM8V48kdlbYXKO4z8Oz7+/FshFrc4ShaVO1YjaJzYvIGQFeZgyeLmsQU0WfGJWD3h3swb5yYRhOKVuegqkNMQo1pa/ejdO0MtuUKVJg4KxJFb5e6ZuFNEARBEARBEIRLcFvDELf7DV3NXuw6ORQTrlZgZ2oKcg9eRLdmNMZ6DRaPENBW5GFn5nbkHTyDzsGjcecdwnKEP7+gHJ98fhH6tgboR4TC9xY+S0IzytJz0STmKa1TgDs3Hx980oAL7R1oaVNhXJAXVLozKHnrPHxm+aNpTwrS/vAeTne6Y1zgSAyWXGLQnSlGQebr2LrvODq/94LvaA1UNi5BfHU0F+9iNhZP9hJ2tFaiICcXeelv4xNtJ4beMR4jhghZHNrjhdid8Roy3v2UL3usvwZubH/LgXTkHTiBzxr/he4LWgwaH4gRPxXOscSWXHm6W1H9Rhayt+ei7EwHho6+C17GbGP/H4nEWLaPqzP/cy+EjHE3HoDa/Cx8NkSQOZdfcskft57Px6vrs1DW7AbfO/1xc+tBFKZvR+b753HTyPEY83OVcLZDOrJ2vJX+cHQ0oGR3JnK2cjLtxs/H+MNDIhvd+YMoytiOV/9ahgsdavgZ9dlRg4Lsw+jmZNnFbb+Jo581oPVKGxq/FfrdSwb25Mfb1QHo/L1woSAVGZtZezpvYvYxCkMFEQC3/BvaVwtx+QFBxgRBEARBEARBXHsG5I6y/nw5cgu3IDVfh6AHEzBvQgvyf5eI3DrxAOhRuz0eC3K0GMvyFz0YgPacxYhPr+EftVaN8EPIOA9A7YOgkEnwNa7TzGhHbUEhatuFlHydUtTwDQmAD1uoeIybxOpii2Qxh1vs5KfuxuVxD2PR4zOgPpSMRLFdHNqiVYh7oRKqsEfwxCPB0BcuR9zmw7YfEZdSl4X4+SmoHz4Zi5ISMBmleHJpOmrFR311B1azsmrg8eBKrH98Mi4XLMfzBa183tDRkxDENXhEAEJC/OBharAEUa7p9fCawcnVDy3pi/FkfrOQ3VmD3PjFyNYGIGphAqICtMheNBfZNdZb315XyOQnCphHh8Zyk8y5/KIdG5F9xoeVNxe+p9OxOGkVUnPaWf2P8DrYlZiEIqELDurIdPza1Ab4cnYywxv1ry3GM6JMeFqL8fz8JFSrJyP28UcwWV2J5LnLUWI8hMk8MXEP2kMSsD7pEXidScFyoz47m3G0oByNnPxVXhjLbMKD2YZPALOJ0cIq1kwGsvITbDJ3YwqqNBGsPZz9bEH8uoOmO8iD/eAfUIf604oshiAIgiAIgiCIgcAwALS/tcwwdcFOQ+NVcQfjZGqkIS7zlJBo2WdYNX2l4UC7kOS5XG7YOjvB8FaTmP44zTD18X0G6SHmVBu2TY8wbPtYSMnW2YsWwzuPm87n4du1wPDGaTHNcW63IWF6muEkt331lGFXNGvjOT5HwLjP2G4LTqZGGKamVguJrnZD4zlpj5oMby2INLwuZnPHLt/TIiQ42lsMX14Rtxl8H41lWaN9v2G1pVxbyg1vZJYavmSb/Pkr9xsuCzk8XR+uN8xI2MPnC/1fZnhHbIJZ23nMZcbnv1xu6BKSBsOFPYbl05MMh74R00x7B5ZFGLZ+KBzhqI7442evN1RIG8z0kcj2VYly4c/PMD+/cVeCYcYGoV18Ga8cFTI4rrQbvmwXW2zRX8GmpGlzGcjKT7TJTR9IjuDrkMpEKHPVW5JKCIIgCIIgCIK4pgzcO8ruGgzlnhkWuc3bDy2dXfy2/vQpHJkwFSEaPimgvhsTg5tRe7oPb2/aqVM5Gqild7AHq/FzcRPNNTjU7Q20VKK6QvxVNuGyuhlN5xTcIVRp4OOthrahBtWlhchP34mSNn3PV6Z9A0JRu2Ml1uYUo7ahFXp3T9h4Ktkq+k9rUBYaiTCpXD2nYt5jM+AFPc7U1SFsaqjZ+7aq4MmYdv4Ezva8l+sg6iGmu/FuKgyCJzx65KeB12gmLq3kA2SO6mhcIMZJGzwqHLOGH0PteS7RjLPHgVlhAXyWEZ97QuFReQrc29ya8YHwKU7GkymFOFLXDJ0ba5PG6u14GZTLT+0uOcLTGz64jMs3ypfPCYIgCIIgCOI/kIFbKNtB19EKjPRkyygpagxlO3S66/gzR99o0eTGflXHUNXza4AqNBo+7vILZf3xdCyeE4PVOQdRxRZ6PlNnYhpbdxtRz16PwsxlmNhdg/wXEhE5Jx7Zx5XLg5erWiV5jFyKDrqvWJ2e5lLnFroe1/NCbgT3MLQU1j93HS5f4bbb0d7mDa8RfIYJthj36tCDX34HPIbdb2xBlGcDStJWIu7+OXi+UPLotmJuUPkRBEEQBEEQBCHLdbFQ1vgHwqviBOrFtEAzGj9VwX+Up5i+DhnpjZAOT0x+dBmWLDP/xQabL+d6o8ORNwtx21O78cf1T2PJo9EIC/aGymKBpfYORdSjSVj3xj4UP+OH3HV5FnKyDS/X46fQJP27wPzfRuYW8Rr4BqpRdsLiheDmBlSp/OFrRexDNVZ2DvSrtaeb0CJu8nQ2oL4uAGN9uIQ/xgY3oPqU+cUEfX09qid44zYxjeEBmLXgabyYuQfFmXH48rV0lDl8B91x+VlHh3Zune7mzF1tgiAIgiAIgiD6g+tioYxxkZinKUT2XvEjU4yWvVuQoY/G9LvEHRwdWrRLF339gE7rwB3s4RH4ZcRhZGRVQmdsV/NePDNnOUouimmbqOHhqWKLJNNjyNpDu1HQc14rihLn4JkCk0za29ixt3vCQ0zzaL821W2JUa49ZejQlLsSkeuEP0fkPzsOHgWZKDJmdzejKDUP+tgIBIm7pHiNCoDqUDHKuIVdtxb1uSnIMDVvYLiYhwyjnXTrUJ2VhqLQGIQN53aoEfbADJTtyEG1ceHbUYns7YcxKyqcLW31qE2Zg/h0k7507VroVEymNq9rsHwbi2hH5WedZjSdViPI3+LONEEQBEEQBEEQ14zrY6Hs5o3YV15CUGkiwu+fg8j7Z2JxkQ/WZTwGf+P7q8FxeNFrLxbPnIm1B/rjcWxPzE6IxpmUGITHZCm8a8sWZk+lYV5HOqJnzkF0zByEJxbD66kkzLpdPMQOQXEr4XtgOcLnzEX8nDlYeTIQUT2v13oi6oWVbCGWiIiYeJY/E/GFGqxLiu55RF0zOwEL67cgcmaM9S9F83JNgk+RUa4xSDzkg83PRAqPL49agPVrA1GSOBMRrP6ImYl41ycJaY+av+NrRDVlMV4MrsPa+TMRPjMeu9wfwVI/MXOgCIjDva1JrL0xiOYeWz8dicznTX/XWDV9OXbOa8e2uTMRyfoUPncj2mPT8NxsTmoqBD22BVGnkxH50FwsZvqKXFeP2C0JCJK8J20iGLFPeWEXk0/4c5IvVRtxUH5Waa1HLSIR1vO3mwmCIAiCIAiCuNb8iPuil7h9fdCpYwsSNdQOfLTqukDP2t2pgtrd8Udo9Tod9CrWZxun8vlufZSJjFz1HWwZqFZDZXXBeH2gLViO6NIIFGZEQ8PJu9uOTLhHzHV6qGz1iZNHN9OXLaE7iLPya8lfjLVYgz/Ok7ycThAEQRAEQRDENeX6uKMsZfANuEjm4Ba6TiySObjFnL31Gp/fV5nIyFXlfn0vknvBydueTNy4ixZ2+sTJw0WLZA6n5KerREGBHxZG0SKZIAiCIAiCIK4nrr+FMkHYYrAG/iNct7i95qhDsXRPEsLkvvtGEARBEARBEMSAcv09ek0QBEEQBEEQBEEQ1xC6o0wQBEEQBEEQBEEQEmihTBAEQRAEQRAEQRASaKFMEARBEARBEARBEBJooUwQBEEQBEEQBEEQEmihTBAEQRAEQRAEQRASaKFMEARBEARBEARBEBJooUwQBEEQBEEQBEEQEmihTBAEQRAEQRAEQRASaKFMEARBEARBEARBEBJooUwQBEEQBEEQBEEQEn5kYIjbBEEQBEH8QOnu/h76f/8b3d9/j+/Zj/jh8uMf/xhu7Kf6yU/g5kb3RAiCIJyBFsoEQRAE8QOn87su/PvqVTFF/Cfxk5tuwuCfDhJTBEEQhFJooUwQBEEQP2CudH6Hq93dYor4T+QmNzfcPPinYoogCIJQAj2PQxAEQRA/ULg7ybRIJjgb4GyBIAiCUA4tlAmCIAjiBwj3TjI9bk0Y4WyBswmCIAhCGbRQvt7Q66DT6cXED4xuPXQdP9C+XefodTro7d1UaqvBkRqtmOgPdGipqESTTky6lP4s+zrDwof0/7+984GLqsr7/6eHGpccMyEVykBNtBDdRf2JthAsKC1Kz7AUPvrIyx7cXCkDs9RKqk1TKxUpCINw5ZEHNlaSlQ0lQUyEQIw/poh/QBT8A8kySoyRU3R/59y5A3eGmWH4o23b9/163dfMuefec77n+/2eM+c799x7G0pRceYWN/xnNCZpW3vw857g+rXYViNfk+umQ42q/Eqob/fF29Za5G2PQ1JcDuqNROcP7vpJuFaH40frcENK/iy4WobsLa8j4k9/wqtv7cKpb6T9/eW7r3HqaBnTh7TVXZMyfhp+Mp8gCIL4GXJ7AuX2JlSxyUVFcS2bZgwcmlpeZimqLv88JnHdUaO+uBKN7VKSoc5eg4CXc1jOAKKuRUVlEwZOS1o0VrLJYm+FbM7BuqBEVEnJHhlwuXuij+36l6cJuS8HIalSSpqgPvttrH47C/VSut8Y2671KFLWrkV66S0I6vpV9s/M5gZ9SIOS7WuxKu2oleNq9/GmO7dpTLolVCIpaA1ym6VkX6hMtNxWI18z0E1tFt5Z/zZya8Ws7n3gllCL9CWRyGwfh6muzhiikHZL8KdbG3PqQxXmPhGNL7+TduASsp9n+1buw4CFcBfyWLCZhwYpaYkbRW/jD09+gOM/5c/4d0fw4bPv4tA9j2HFG29gyeNjoZSyrKcOmX9U4dU9X0tpCe3XOHesHMfYtj/5Lby6/6KU8dNgyicIgiAI09yeQLm1FClRUVgelYML0q6B4EI2LzMKKaU/18imHtlRyShvlZK3irocLN9eOoB/UqhRvj0K2XVS8lYx4HL3xG1q178gzmG7ULgrDM5Sut8Y226oL17evw8v+/V++tkj/Sr752xzJbzX7UP+Ol8rJ/XWjDe3aUz6uWLJ1yaEIfXzXZg/QUrflvGrDS3N4zA3JABT/FxhJ+3VY/4VUIdRViZFpvXF2D9g/5D1nsEzFyN6YwgmGwX5t5WqMmTbh2D5n2Zj7KhRGDt9Gh68R8qzmrF4/I138ZzvSCktcc9kBP5pKRaxLXCytO8nhF4LRhAEYT02bzKk77eG1kpk7shEUW0zmzC0Q9vWAIzwwOhhLK9Dg/rPM5D2l21I2Hsc7T86YvRYOyhk4bu6OA2pO/8P8R/loU7djiH3P4wRbI7SmBuHtNwzqGMTuo72dlxvtcUEN0eY/K01rueGEvePd4Stvp6OJlR8nIz0/41D0v7Tsnw1KlK2I/vwUWjsmczSLERTmoadfy9ARbM9Jo23g41ud+/gekn6BEdO1aLp22ZcuOGIqQ8NRfupHKSfH4vAceeRERONeCZvx70T8cgoW+lEHVwvOxK2Ie3gGbTbjsUjD5qeKmsqM7AzsxBfnbsMbXMttHrd87wzOchM+Ahb95R11z3TSdWeNCS8/x7yjrWiY6QLHrqPa7cBBXHpOPBVLS61tKKxWWFe760NKNkdj8RN/8BX7UMxwVmDosxW/Pp/PDBCOkSUYef/IinlILPlHXhw7BjxqohZuZkta/anMVsl6tqOUXho7NAuG5iVW4IvU0xNQPJWJpO6A/c95AJ78UGg5tqlQWNlA74fYdflL50wv0lOxtkhXb7BEf3j2N2dvmFJz9yP08/pbK9Dg6r0RJwarGuvqIcTgzDmnzlI2LoJ9fcHw81oHiYi+nAikraloOBMK4aMnQzHTpfQ4Oy+TLS6B2PkV8mIjd7e7RixngKtgS0t+gfDXL5p23H9pqCefx/MbLAtB+0ukzFC5tb1OXH4rNkZbpIvW+vjOttJZUu+rS7LQmr8e2L/4bKNdzHVTy34skV9GiH25VO4d2IHjmyPRuxfuC8rMW7iqE6f4XbO+8YZdx9LY/rPBjx8mB74ueb8UaKHPtTNf8zJbWa8MeA2jUk6vedC4+KIS5kxiOdtM2q7Wb+3aJcmfLnzGO79gwc0n5ouV6SpFJnJKUiL4/nsN+VB9pvCbcG5chTJx4YieHor8mLex+Zuvm/oa3rdLJj7MGxF/RWh4+GJuPtU9z5w/9Uc7NivxoTJo7rGy45aFMRnQe3sbta/zOr1/EEkpe7FV3p7Xew+Ft/Udl9m+8+ydNRqR6GqfQRUM0fhymfv47T2QVzBaAT7u0C0aocWX9d8gS/2FeHcdQX73b0PSuMO1PE16goP4/PDNdD86h48cJ+sAU3l+OvngP9/PYTvyj5HfvEFQOmA4ffqpWPlH69EXf0VfN34DbQ374TygWEGsmsbj+Mk65MjB3+Dus/34fOTLRg0zBnD9LaS0DaeRuFnu1HVqIDtfSMxtBdvQRLrOHURp0r3ofhrJR4Z+R/45jKT6aYtRg7r8m9eR8Wh/Sg9ex2D7nHEsCEyZfBl5ifO4Wt23rUbWnTY3ofh8nwZXPe58MXC/ycfxHW6uPij/LxruHi0Bt/Zj4TyTmkXX8JdcRV3Mz3dOJOH/MwjOC+MhNP9yq6xTctswnT1afkVKAz0bcgghen9BEEQhCGyaa956s6fx7LIF+D1u1niJ09bTXsDjuRUo1FMNCAvMwtVLfw7CwjiFiN0PQtQ+b2RdUVsYhMO1YosNEr3eNUkzoMqKhkpxfzv7nrkpsXh2acjkdcEtFRnIU9a19V4IgcphQ1mlrjJ6imuRU3lQcTHrYJqQRybKLDsjmqkLAjF8u1ZyBWrYXKw/BAmhxp2cFRUIoXJHJ9bLZbGyyv/O5OJ7dMonQx+2HuFgk3ep7rCHko4u07H1LGyScblNGxN18Btbhienz0EeW8sRrz+33/WyqptoViYrMZ4lv+0rxNqWPuWp5te5KYYMQ5TJ9izSQoLQKZOx2hpbqzOZm18vRSKmU/h+afcoc2KRMimIkmHahRELcY7x+wQuHIjlszUIHPFGmRf5nlKjGZyOzNx7ScwuScYTsw60VQifkk4UtTuCH7uKcywycHad/PxTymbo8mNgioyC22uTIbIp+DckIDQNVzv5uTmcs1DeKYG45+KZHKPQ31iOF7LYg4hYkluRlMOXluwBhXKGaJMbtosRC7YiArxko+Zdp1Iw+IXw/FOtqlVCw4Yos2X+QanAbmJadAM1fmGoZ5nQFGyRvRxfWncj1OqxQ4hocGFQn0fYdY+X4iU9I3Y+jct3J6KwMwHdPsNaGc+GroYSWpXBC4KQ6CrGklPz0NSpWGPqE9Zi621TuIxsx+owVbWl/S6EeuR9SHL/iHls3Zop+rahYNd+aZt14Iqfd9XOEBxmfVH+UqQ9iJkvlcJxSgHluidjxuUzeB+FbKpEvZzV2LDczPQlhmJ1zL1PiLHjM2t1GcnfIzL3IOYtVtwYcx/4ulFfnA8Ey3qRz+WcTtnx72JrSccMHuRCuN5d7fojwwr+pCB/0hyf8BsPJvLPaYJHywORyYfri2NN3pu05ikt1fKm2uQZyO1vT0L4UvYmCy13aTfW2UXNQ6/a75cVCcidEE0aobPwNNrwjAD+Vi+TPot0NOaj5jXcwDJ97n/hMdVSr5v6GsGiH5QiAusLFN9QOEwCI3bP0GJzO21xbuwrlIJR+723TDS61xXtCSz3zK9LGyMmSq3l7mx2AT2nt74XdEXOP3daRR/OgwzvcdKOQwWAB9auxARiV/i+2EsKDuSiPAFL+PQVSmfc/UwYp95HjGH6qD5rg6HNj2P8C1HjO5JrsPf1r+D7GMXoanfhz8/vwwpneurb+BczkdI2s62D941uUz7RlkaXt22FZtf/Aif113DtYpUvPSsoRxff/oy/isyEaeuMcsfS8ZLYS9jv26yYRXfN9eJS6JPXWQOcoMFzNIS6WMXulry9b7XEcrqKPtuGAZf+wLbnl+IN/fJllc3lujawbZN776Fv5X1dgH7NRxLMT7vInLfSsMx+X3S35Tjb28l4i8b/4SITRnYX1aA7BNfd9m8cR/eXPA8ko6xcq4dR8rK/8GbnxotAycIgiB6B3+Pck88F7Fc8PTx69x4ulc07hFWiefGCiekXcLxBCGE7fON2CNc+YHvaBNOxISwYwKErYdvsnSF8JE/PydM2F3P89kRR1KFj2Jjhd0VbWL6RIxOnlW7G8W0SaR6PENihfLrLP1Dm1D8VoB43tr9rJyKWMGX54ftEq6IJ7QIJ1JjWT27hBP8+PpdQjjPVyUIZ3n2t4XCVp723yCUf8t39IcK4QOfCOFTmfgtuyMEz4U7hAuiTnRc2LlQ8Iyp0CVa9glRrO5inQp0SPvMyvNlrOD53B7WMokfTgo7VUyvdVKao98n6prLtVT49JKYI9LWWC/c7JSpUfj0OT/hgy+lpAmufBwm+L5VKHBL6rmwM8zQB76tFy7Uyxoi6jZCyL0qpY3lZtysrxGuyE65+fkGwZP5kO4Yy3KfjVcJ4TslZ5IQ932s32eqXW3ClYqTQovMHgbUpQph/qxN+nzuL3pb/MDk8VcJO4/rskR+qBd2h+l9XPJhvW1FDGUw5Q/GiMes3Mck7YLrxbfTp3VlmrKH70bdPrEMva578g/xu1G7vj0p5PI+oxeim+24bbradfMwk0+WL6b18vbaxw3L5jqN3CXvVI3CFbN9tbvNe9anEeL4xmz6uewMU3Z+Pd9A/z35ozV9SO4/bftWdpO75fAOYecBfR1cT4bjTXe6HzPwY5LOXoZt143L+rabqrNnu/RcrnCzRbhQJx9RmJ0WBggf6bsg91v+myP3/TY2LvnLx0aj/qn3Y9EPZLrr1gduMlnkv1c3hfKNMtmMEctbKeTKxTWQhWPZpq1tmm7bkU1+woq/nhYO/DlAeGfTO8KTS3cJFw5HC578kx9z7pCQHP13oeq6/hw1O9ZPWJR0ujNduC5AePK9MinNtqYDwjv+/yl8VCaleXk+UcKBJinNtsr3/lPw/PMBoVl/jn4Tj40Wjhjtv/DXZYLngkSZHBeFrBVs/vF/53TpU6nCEv+XhZyGrnOqkp4WfNeZqKOHTaxL336D7ZxQmBAt5HzVta85Zy2Ta4dQZXAc384Ju5Zy3Urymdi47j03FRvtN3VeMfstXCbsOic77twuYQUbZ0yXf1pIezpAeC3rYte+qh1MP2uFwmb5cbqNIAiCsA6rrigfP2H4+CXjdF+oKc4RrzLboxbZ2/gTO5NR0syvYGiRfewk+3TBeA/+X2kD4iMXY110Mg5p3BG4NALB7iauhphBX49LoApT+JUtGyVmrt6FnD178KIPK2fsRPjzas4nI3xxFOK3F6LNPQRPPxcCN368kxfmurLP1kKc4FdmTlYim30ofB6Dm+HKQ4lKxP9ulnj1Xb+tNnk1ywJD7SBfuTVE2bWuV3u8EgVj7Nmn7kFm4nZazTKqccHaahoqcajDCWiUlVFajzZlA+rr+D/+znDzaEDMyiik51SivkkLpYMTFKZXk5lAiwu1DfCe/huDKxzOXn7MqjJsneDswMSoZvXnpCFpWxbK2e6bFp4aq3Aax3ymgdm1FHlpzG/+cQzoPN6S3A04UQyMVjR2tZltF9qVqGKyyq9JGaKEo7sr7My1fYwXAh/IQYH0oKxG5m8tqiBM4b7RUM3a44cpk3R5IjZOmMT8uqRa/8QfKzDyB0O0OFNdjZmeHkzSLhTuM+B9/hjOyu417WaPaR6wLz3Z/QFePfkHz0cAZsrbZeuK2RGsz1jZNRXTHkNgbT6KRZ/VoqqoCDND/ODIU/308dGuHqjavhLrknOYbZugHeoAR5N91RTW69OQcXCbKDuD2Xmqj52hne3kS0t78kcr+1AnWpwor8Ts2V4Gctt5hWGRH7NlfxnwMUnB+oVcLiWmenqi6pjsgY8GdVprFza+TzMsd9J0965yFXZwdlJCXVuJivwspMftQF4z07Z8zBnqgUljpO8c5W8wxb0BVac7JesjCkz19kV5fqluRUn7URQcmohgf9P20Z4+iZJJnpgqv/F4wGS5C7+eMQPZ+/Lw0O9nQrpjQceIaQj+ozeU9celJzUfx8VvgLpr+kvhp3GsSIvfTnlYSjMGz8AfU5Lwh3FSWsQOStky6WEjHgSa1L17EvY9w2RLvodhJBsgjjfqrpJeqyzBKfth0NZ0PVH6GqtTW3YKl8QjBoKRmLxwKaYNq+t8cvXpS9fZ2Hity09vK7PwX0+YuPfm6nGU1Q+D3ffnOnVxnKlpmLYcp37C+88JgiB+7lgVKE+e5CZ902Gc7gs323U/My1s0l1SWqrb6rVwecABzrb8JiMlvFfH4o0QD7jZNCEvOw3vro/EvCdCkWJuCaQJ9PXcp5RNNxVKKIeyje8a6osVsS9h0aNOGNJUinQWfK1eFoqA0ERpOZ4DfALd2WcTjlQ2sQl9DpuyKRDoOd1gAtuFO5awIJwH4vrtjUCT6+r6hKaVzTzbG3C2/CjKOzc1nINZ0CMd0yPX1ai3YZtBGbVQeKjgPJTr1g7eG3ZhR8R0oPyvWBseBD++VN3qmYEGmqtsMm18HxRLD5G+chqzViGA2TMmk9WvtsPUADYplPJM0sH8YNUcZpstyGYyt9lNh7/3b6RMjiW5W9DSzP1N3uajuKDwwKJxg5lN+4oT849xyMzjy44bUJKrRqAX/2eFwfXs5NDNLko7BzS235RS/UWna2cH+WyawWao9mhDm2xJqT3zeQNYIOLYqkU3SXryD56vVJrxfyux9cTsgFrsPdTQGTB4e+ja0F8fV/pvQFZCBKZ0VCL99XAEzAlFUpm1zmu9Pg1xAFOJATyYNG/nnvzRuj7UhZnjbwN9s5cd7O+VvkoolKxlbW1m+qK1dnGAnbjUvwsl83N9udqyOCyeE4So5IMoP8/K85wFb+M4dTgL8KSvOpQYworQaKweAM2ieDQAwbVZ4G6vLTuM7Mm+mGnUJD2iXkex9khpHQMoy7TfIhCT8dupBmEy8N1pZL64EG/8X7nZJ6R/rx0MpdG9wIrBg3vxZ+oAYXMNDfrl0nz7ZhT+y/shGN3G3A+0qEtbgdCVafjy62+lff+q3AV1vUwXx67hwSe88aD8/nyCIAiiV1gVKL+0YnlncMw/ebq/3D9GF0w4q97EjtRU3RYfiy3xCYhdyPL4+yw7HODmE4YNu/eh8MAuvB/MAk5tE5IK+BVn88jfpcmvLnFKSirZVEtHY+YqLA4Nxbs5/KoHO9ZhInzCNiJ13wEU7t6ARQ/wajKgr0bp4Qtv9llSksAm9my6pQjA7EfNT0gVPAiXbwM4d7VzcoGiwxX+ERFYYrR5y6+CWGKUE6a2OmDGM93L6Lpar4TzoyrMf20zduzZhfUuWViXJr8X1xIsAHNRoOSM4VVTbU0NKqTvQDXykmuwYMsebHqN1b0wAFPG9BAGnclCUo0KCbtjsYLLGuDBAjcprxNzcjtj9AQNHKcv7dbmJfPdjSbGvcPOJwAzDx1G1YlCZGtD4K2/0jqWBX+1xlchtbjA9DJzjO750kNY0NyNXkXtdhg9UYmCY0a2aahFucIFo2XFl58xvAtQtMckJ9wvpTvpyT94uy6zdukvMEn09h22bn4qtOSWoqb0MDLdmQ6liGAgfFzp5IHAZ9Zg/cd7kLN6HFLWp6FGyrOM9fo0pBqNBldPpSugkp2705M/WtOH5Ojk7rZSgb/n12xwPzD0zV5NqDd66W99dSkUDzuxlpjCWrvUoqbGqNwzlVK5GpR8koX7X0jFhxtewpJnVJjp7gSFsX5qa8T7jLtowIXjCriMMWt867Fxh79KjbziapQXHETgXD+zY4+dy0Q4Fh8z8tsBlOVXM/DH9NfhYxQna8v24i/tIVj95zA87j0Nk6dPwyN8qUcndhjpeANqtVzP/IFUZbg4YO+XsgIelNtMwuPSE6W7tsdg6nmHfeK7CuxPv4FFb7yORU88Jupi8oRRUuZAMQymfgZ6hTSTe2SOsS6W4tEBe5UBQRDELw+rAuWxY8YgPvY9FH5+QPzk6V5hO0SaDBQiPToOBefZT63fPASzALImZQ1eS85BRU4yXlsyD6qgeUgSHxJTi8wlQZi3LBKr4lh+aSnKj+tm5m4OuoBqkK2u1PKcBCSl6wLhxvTF8AsKQoD0YCEl/wefB6plcYh8JRpJ0VGISqxEzWU22ZjIpmS1aQgPWozFy9YgKaeU1XMUFeJ7OJ3gyB8ry7HzAJsvsDKKkM2CHkWAJ9wG7J9zNTRml3OaYLIKyxRpiM/oCno0pXEIDYpDleH80JBWNVr0QcxwP/zBrwjxiaXQ6Pc1ZGD1nEjk8Yc7Xc7CcvY9W19FhxqNLcDo4YZTWI3a/FUNHgQpMhO6ymgtRVJikewqpB3sHtCi5aq+DA3qM3aJy9oNkMvNZhOj21vwz85TapGdWSQlGBbltoN3sC+ytyWiQq/vjgZkR87B6s6HgekwbJca9cU9vGfXzguz3Yuw9a0MDAr06nrF0tDpmO1XiaTkLj1rShMRX+iBuV46XTqOcYXiUA4KuAhM3pqUaMQbxrM94uIfAnu5rnm7YtKgDfaDfO1HfXqcoT22FWE2k7dbYNKTf4jtOomdKV356vyNCH06zXAZt9x2ppjkhUB1BtYyOYLnenYFDH31cZEmZIczm2Z2ndvSzIz3QPcr+3LkNrdWn4Y0IT4mo/PhXcZ27k7P/thzHzJElDtLdjzrH+krgvDOIbnzWjPe3J4xKVPeduZf8WlaPO3HV++Yxjq7KJCdaK5cJewdFGhp6tKH+lAqMvUP+9OjKGJ67vLtxowtiNeq4NOXV/uY6AMuPgFoyXyT+YcvvMXbi8wwIQDz7bKQJNNrb2X5j/+w/BOvGNy9fsVgJRQtF9EkPUjqRs0u/O2A7ruOUfjtEw8je08GLkrrqG/UZODDtTm4nW8IHub9BwQ2puHDPV0LrW8cZ+mMut7912iJu+6GQnENF/UP9/qmDtnpBsoYABRwGjsKXxaU4GvJV77ek9b9t9AS93ljrvdV/CVuT2cZ+OY4MrfswkUjZfTkEwRBEEQXt2fEHOqJp5/jV0nUKMjOwl4e8Co9sSLpJQQ7aVDAgoPlm9JQoHFC8OoErPBiP942rlgUs4blA1WZLD8qGikNCswM2YANIbq1ci4hKzGfTXy0tUVISS4S39E8xE735E9HOzvdhLKzHhaUl+YgJbsUNTbjsOSdLeI+uC7F5ld9WeBbi5RNUUyOLJy1de3KF7HDzNm6K9N8smVpMtc73BH8giN2hs+C1ysHO694W8SG6ejdP8MtPxxejwdBNWcWVG/XIPCtMLiZm3O5h+ANxwwsnjUL63J5LUrMfCEW81vjoJo1B6qgOfAKz4HjC2swmz9d9gEVXnnJDplLWN6CeQiYFY7sEWuwQqX/29sB/mEqnIkOgldQoukrdVyvYhmzEBDEl0B/gvEvhMmWVrMywkNwgZXhFzQPqsfnIWmoF4KlXBFjuR38sGR+A9YxeVVPsvPmJWKIl590MKMHuRU+kdgxvwUfzJNkYvl7R6zEis6l8Sba1VEjvlf2hMWrckyfv/dEfbMT5vp0Og3DUM8Boq2aEBz7Kryl+Enx6GK84V6NdQuYD8wKxc6hT2GZwX1+VjBmITasm4g85kd+c+bo2uW8BrHPSEvAJYJf+m80vszk4G0PWouzAVvwir+pQK4H/5Dyg5ve7mxXSNwNzH93IVz0fyB18zlTuGL2fCXqWz3hPU3mvH3x8U4cEPj6ShZQhbM2hiKUnRuaZYf1a1Td/xAQMWFzK/VpCBszfJoQxY7n+gpYexKBW7rsbIoe/bHHPmQEl/tVZ+zVy/1EJArGvokXO21szXhzm8Ykxnw2jmcukPxrSRbsX4rFIksqtsou47DiBfPlurHfjNG5kfCaM4/5xhysPDERgcZ1jgvD82M+QcgcXVtCM+3wRszSLt+2FnN9wJUFwAo1GgMCdM8yMIeBXplPPT4Li7OdsT7eells+hIUTZ6HNY+dwcaFKsx9QoWwD7/H5McGA1evd95fPGzOG9jiXoaX5odgXkgIQt88jslvvYhHja5Om+dr7F+pK3/uG/tYeh9W8u9s+4v0vIceGTwDz77/J4zcvwJzn/xvhIZwWa9h2u/Gmv0zqdfYTEbwCm9Ux/63TtY/xkHr7o2RuIpr+idSVybq8p74E2LPAF9+9CddeuU+iBfYr+7Dm1Lb2C7W1Nel4xNxiuczRj4egT/+mIbFQXx/CLYrZiJQyrOOwfh/K2KwfHgeIoKYPRaGMFkTcW3GbDxopIw++QRBEMQvlDv4E72k77eeDv7QFAW/zc6Qdg00WgWUQ838vEnLBxX8vkhTE4R2LWArO1fL0qbu1eP1sPqVZtZCazUa8PuPzeX/y9FDe6xC1K0Z3fPl7xqmEXN6twYryuBLdvkNnlbXIZbJTjHnLz3V2Zt2Xc7A8mVqPL+HTU6lXabQFm5EwD/ckbU5gIWRJuB65j5+i33LGl1yP4et4THqzEiojgYh5x1fQ/kt+QfnVrerHz4u9mcbJZRWP8irO1b5ZlMWVi/Ix2MfxyJweA++aYqB9FeJXvepgcIqe/EHHq4CNh/Asml9k9UqP7dwjOgb/FkVlsTkeme/OwPv2w3IXBwJzYo9WCR/IJ4luF5Zz+ytL3d0/Igb7Rb/5TMPa/+N7xUYbOkeV37MdyxMM3Fl+rby3Q3c+I/BuJViaL9hffCeW9xO1g7tXf2817sHmwy2tYWNDQXLBEEQ1nB7R0sbE0Eyh03aLU4spYdvmf3xkAfJHHMPtOH1WJj08InoLZvw3wp6aI9ViLo1Uwazl0W9W4MVZfB7untVh1imhXb3VGdv2nWpAVU+080HyRo11E3VyEwvQuB/mr/fUNTzbfAta3TZLeBqb8CJ6gY4jnHoLr8l/+Dc6nb1w8fF/tyPIJkz4L5pioH0V4leyz1Q9MFefZHVKj+3cIzoGz2JyfU+oL7NAm+1Bo25qUjHQsy2NkjmcL32wZd5QHTXnXdKqV7C2m8xSObwY37qIJnzq1sbJHNueZDMYe3od7+1YBPuCxQkEwRBWA+NmARhAe0oXyQsNL/UXlOZjJUrY3H20S1Yxm8Z+BlSlbYGmQjDZv4QPaL3sImp/QOWXuFFGDKI6csB9kZPTf73pwG5r4cj6rNBWPFWiPgqtNuB7a8G4U4bcs5fOtwHuC8QBEEQ1nN7l14TBEEQBHHbaf/uJr7/4QcpRfyS4FeSKUgmCILoPRQoEwRBEMQvAH7Psvb779Hx44/4kW3Evy/86db8wV2Ku+6i5dYEQRB9hAJlgiAIgiAIgiAIgpBBfzMSBEEQBEEQBEEQhAwKlAmCIAiCIAiCIAhCBgXKBEEQBEEQBEEQBCGDAmWCIAiCIAiCIAiCkEGBMkEQBEEQBEEQBEHIoECZIAiCIAiCIAiCIGRQoEwQBEEQBEEQBEEQMihQJgiCIAiCIAiCIAgZFCgTBEEQBEEQBEEQhAwKlAmCIAiCIAiCIAhCBgXKBEEQBEEQBEEQBCGDAmWCIAiCIAiCIAiCkEGBMkEQBEEQBEEQBEHI+OUGyh1aaFo1bNNKO35i2rksbBtgcRpzN2L5i8mo0Ug7+oOmGukvhiMmt0naQfys4D7WLn2/3WgHum4NGotLUd9vvx6ociyjLk5DUlwc0ovVLGVUZ3/s0qFGVX4l1B1SeiD4Kf3kZ4LmTA7SmT2TsmvxL/ILQhAEQRDEAPPLDZSbc7AuKAgBQYmoknb9lFQlclmCsC57IINQNonOPoiKygwcqpF29YeafCRV1iIzu5SVTPzcEH0ssVJK3V7U2WsGtu7Wo0hZuxbppf2McAeqHAto8t9EyHs1sHediPGOym519ssutVl4Z/3byK2V0r1FXcvGhyaDYO+n9JOfHBP66MaZZIRHZqFt3HS4OSuhkHb/9GjRWFmKehqcCYIgCGJAoKXX/9bYYfZbO/Bh/A4scZd29Qf3CGTEb0bqWypWMkH8hAz1xcv79+FlPxZ49oeBKscC2lY1tI+qEOzniyljWFg1kHVOCEPq57swf4KU7i11OVi+vRS3+IL6zwdr9NGmQf24ADwZ4IGZkxyknf8KqFG+PQrZdVKSIAiCIIh+YfMmQ/p+S+FL1TJ3/i+StmXgy/OtUDiOxYPDuv6L78r/DKcvN2OQ82Twiy+cxtw4pO87Cs2IibjjSDJio/+GitahmDBxFGxqcrAjJhopBy/jzlEP46H7eJkaVKUnIutzdo79RHxfGoeYtX/HV+26c2z53wOaM8jbfRSX8DAC/8cDI8Sa2FSjLAtZO/6CrX8twKVWJcbpj++JjiZUfJyM9P+NQ9L+02i/ocT94x11554/iKTUbFScV2CCm6N4BUJTmYGdnxxk7XDE1IeG4uqRFOw9AzzoEYip17KRELMNeec6YD/6YYwYLNbQNz3sSUdJVTU7xwOjh7FdluTktNYiLzUZaR9tQ2bJebRjFB50HgqF1I7U/eU4d6WrHWhtQMnu7UjexuQ91opv73bE+Pv1AYDeDg0Y5OKIqzkpSHifydzUwep0wb1d5u+GoR3uwEjnMbj3V1Imgy9lTd35f4j/KA916nYMuZ/pSalFfc52ZHxWgnq44JFRtrqDa3OQlPYZKqqBMe7Mnrq9faOpFJnJKUiL+we+4vU+2GUfU2iYzrLjt2GzKX+S2WLvl0x3Q5wx3lGSrrUSmUmncPfDHfgy/m1s+KQMHfdOxCOO7cymkh4l24vlScffO7EDR7ZHI/YvB1FnVJ/oY/DH4hmOuh0MrscdCduQdvAM2m3H4pEHLQRvoq3jkbgpDUWsDw9xYX1UbHsDCuJSUK/3MY5eHo8xGMKS7adykN7qjtBhxyQ/Na6Pl5ELzVh7XNr1Nt5JPIhLNs6Y5KLA1fwMbP+A9wcb0W/sRT/oXqdFXfdKdt4HEpC8ldu4A/c9pK+T53XX8yWtHcbI+1AnOv/PLDyGUxf+iY5L+n5oWGc3u4h+kcjGwhQUnGGyju0aC7shylOEjocnYsSvJB2yvnYpMwbxm5j87Xdi9FhmAxN9TRyDMgvx1bnL0DbXQmsgjw+C7ihAwtZNSD/cLBtTJHojo4RFX7NUnr4vjL2KgzHvY/PZUVBNade1ddQgfJXK7LBPCw8fF7Fvi78lCR9h654ytP/oyNpvpxu/9Jixrzl9yBHH4M8qO49pVPA+qdOLpfbx8/K+ccbdx9LYuJ0NJiwGfcH3uWDk+XRs3pCIggYbjH7EBXc3HURW3DYk7D/fXe9mxx9u+3Qc+KoWl1pa0dgsG6MJgiAIgugTVgXKdefP47U/r8U7m7agvKICjzw8AcOGGc0gLKDJjYLqlQwcudAKJftRP3eiCP/IzEXHr1WY6mgDdVYkgl/7h5SvwVdHS/CP3dm4c3oIfj0cqP80Chv3nGFzqfOI35WLmpYmnKo4iJLzdfhy29+w96IajRerUZB7Hg/N9cNoWzWOfvg2th0+g6tVxUjaW476Nt05mcW28Jk7Efd+2z1QbsyMxIL1e3Hksgb2P1zG4S/ykJ7TiukBLN/SjKOjGikLlmBD0Rlc1CoxpPUMPiv4DJmVQ/FEwMOwPZeNF2Kz2KT1Ycyby9LsFE1JIl7dWYSv7D3FCbI+ULbV1CDzb3n4skmNuuqj2Jt1RmpT//QwwnMRpo/sQU71Qayb/zKSjzXg+l22sLlSjb15mSjSTEKghyNsjNuhLkLM0hWILWKTsx8UuH7uKA58lomD19nxrE3MslL9rdDWZyA2sxx1XOYTJciukurUadCATjucb4K65TKqKgqRmVmGB2cH4CE296xJnIcFsSX4qkkLe9tWfPVFAf7+Kc8PhJsmF69u+wxfXHfCPH8XcaJYk7EK6zJO4NspoZj/66G6SvpCdSJCF6fhzseCsOApL9hdzMDquFpMDWT+cZd0jBx2/OKIfIwIDsezT07A9bxN2HpinE43ks+k3uGD4EVP4tF7L+Pva9/DBTddn8D1o0hen8P8oAmjvH8PP7vz2LExHRVnTqBtnDd8PBzQsmcTYs+7QsXLk44/UlMImynzEeAxCh2lcViVpYC//8MYwgIFw4BMi6ptTyM8xx6B8wIx80Hgy4S1yPjBCwFuJnTE5X06EntHqPDssicxvjUfm6NPYLzYN+qw95U4XOU+dr90vChPLcZLfUsMlMuOob74DvwmRKovfi3+YeOH2Y/wgIKXkYzDzJcVUwPhxwLRw9HROHi8HjVD3eA7cyIUx7bj1WwFgsQ+ZFRnT7q2VvamHLy2KBrq/xeEwFm/gWP7IWyOysQQyff0djnSWIMRUwLhM9EWJ3e+jZ3XpyF4GhusjOj4ntny2jEUCI9ise8k3D9qFO61NazTwC7tlUzW5ci6LxALAh6Fs1CKhHXp6Hg0EI+YGnJFeQ5hqCoA45WSDuuqcdM1AH5e3Efew7oyRzw5a0z3oOlHLe785hw+uzgKIaqZeEiUTZKnuBotd3rAf5YPHvlVJZLWZkPxe14HO6+3Mup9LQPwfjIEPq4KnIp7A2l6XzMqb/w9tUh6JRqNBn0hAwfPX8CDv30KAVOd4WjXKLZ17/Ey2Lg/wew8GaNYZN2avQrz37uK6UEq+P/6XjTuWos3TjpjnpcTG48Yon3XouohFRY8MRWO6r14ZV0ZXFVecLzTtD7k3CEAg9ovdB4z+oFRGHFPh2FfYko6lxyFmHpX3bjJzuNj985Pj6PiR3eonvDAQ86OaPmM7TtQi/pB0xDgNxHaQ8xW+cfQfMYObrNmws1Y7xbHnw7c0aHF1a9K0OGxCH6uo+DI9CG2mSAIgiCIviFYwXMRywVPH7/Ojaetp0XIjdCdt/ULaVfNPuGj2Fjho/31LNEolO9g32N3CMWXdNlXdi0Vj/eNrRDTJ2J05/uu2Se0/CAIbV9sEUJEWSKE3byIH2qEj8N0x6zd38Z2NAqfPqdLh7x7RGhj5wjXjwgfqCQ5Pr/JDtkjrBLLiBVO8Epa9glRPB3C0rwIxpXdEYIv2xf+Ma/EAhWx4nGeYbuEK+KOFuFEKm/TLuHEdZb8Mlas1/O5PSxHRwsrW9wXY9jGzvp/qBc+jQgQ94UknDQ4pi96+OBLluxBzpY9kkwbj4i5vLxD3E6x+brjjdpxIkYn30LWBqZRmY5DhI9P8x1d9S+M0dnhZt0uSe8RwqeN/Bgj9HbwZ/mS2i/sCBPL0OmhQvjIn58fpmszo+1IquhPuytYm78tFLaK+WuEQ1z3Qr2we6Hh8X3mZotwoU5vQQ4vO0D4SGfCbog2Zv7XybctwpUWUVNMtzeFlpp60Y56Luxc2OnzOv9cKOyu0yU55e92+YIIt+fCVOEC/y4eH8B8W3JeDvOh3WFs32FdnaL/SP4m6tl/g1AsO1y/r/xbKS1HLH+LUN4pL5P/UotwU0xXCB8w+4g+pkc8XupbDFEXxvXVpQrhnfXpyhD7poQ4DrycL3SecpWXycqQHa+v06KueyE79+mQeJmOGRd2hgm+Gwt1Pi7ZReffEqxf+KoShLNS0hhRNr3eRYzr7LJL276Vgu9bUl0S4j59/caI8uj7kq7cdw7IlCzm6/uCCXiflo1LHFGe1/Nl9d0Uit/yE1bt1nXYXsso9umVQq68ksZC4eME3bgi6mflvi47M25+vkHw1Y9TpnRuqq0/nBR2qlg/l/WZzn1S3z8brzKy703h7J5Y4VM+dnBM6KMbxseI8hm1r42PQ131dteptE+ux0u7hEgDW+l+Ozv7RI/jj268NeiHBEEQBEH0mW6LBU1x/ITh466M05axw3h33R2tmevn4bX1cciscYD/wggs8Xdiex0wJSwCT6s8MOh0FtLjopGU2SAerzV6kuvUqe6wswGUY8dhtLjHBeN5ETbj4DZZ3AGNxvDuMm9fDyj53+pDPeAfwP+WB0rOdH/yjaasCAX8i20TSpLjxCfUZrPD7NmuquJKyw+vGjsR/vxyzflkhC+OQvz2QrS5h+Dp50Jg6uKcJaaEsHO4mDZO8A/2FPc1nqwxqL8vehDpQU67h93hzI/LXYvQFzciKb0G9gELsSTCF12LdfVUo+IQf+SNA4JV7rqrVUzH3j78ixoVJw0fSjbTU2cHxRgvPDZO2mmCTjt4zYPoHgznRQnI2bMHOxa5shRrqwevrQHxkYuxLjoZhzTuCFwagWB3pjhbT8wO4PmlqKhk8jVV4shllhwTgJlSecZUvTcLXr+TbcuyTNtbYQdnJyXUtZWoyOe+ugN5zdpufqrH7uGJcM5Zi+XRWSipboDGxg6OdqKmmK0UsBvnBGVzLfOvg8jeHof0QrVRWXZQyK5oKdipo4fL7g53dMLUy2q0SUmA2X+izsdFmA9N9bFjdXf3d+3xShSMsWefTE/F0naatVpbjQumnic33AVuw3MQtSwa2fnVaGTuZfcAk683l6zcZ2CSTDyMccdM26OoOi+lGQqlpB/GIKYjOAxD5ynDnZh/NqGlVUrLsKhrq2VvwNkyYPZM7mddOE/zgH3pSdRLaW4Xpbxfj2J6btXippTsO1qcKK+Em52W+USXXc42s5yT9WiUjuoJ5VCZkh24ztrQ1tunWNsNk12BVmBIZ5G9l1H0NQ/W/+QPNnDwxPylfFzR4kx1tW58kLI4CuYr3ueP4WynrY10LmHQ1oZKHOpgnbyxS66K0nq0KRtQX8fHqgacKAYCfeT2VcBFFYFAPnb0Ee3pkyiZ5Imp8vYpf4Mp7g2oOi0bhw10KqEc3LWP+fsgNp7ad7aT+fBY1hy1NBr1cvwhCIIgCKJ/WBUoT57kJn3TYZzuCR7ovP+ML7yHalHCfuBjNq1C6JNz8Jr4hGc1SlgA7fd0JJvkpiH3pBqDhnebTgwISjvdg1ca27tPabUaKdxorkFJaaluO66G8gEHuNj3IM9QX6yIfQmLHnXCkKZSpKfFYfWyUASEJqKqlxPUQbLJu0LJ7+5kDNREqCc5J4Qh9p0wFnDaoe3kQaRsj8azS+YhYFWOicDxJtrESaxhMGcVFtTZaQejCSSfECvFepTwXh2LN0I84GbThLzsNLy7PhLznghFCg+MGW5+KjGwzz52Eo3F+Sjh+/w9TAT7OtyW7hED8c7t3QDWqu5oy+KweE4QopIPopwFd86es+BtJvgWcV2K1I+3INChFnmxKxHyOPP5LCkK1VQiacEcqF5ORkE5C8HGeOIxD0uFWYMDlEbz/SFKO5P+rmllcrSzwLD8KMo7NzWcg1lQKB1jgI0rFn2ciliVA+oPxmLVvDnML7LQ2BvftBtsEAxx37EbrkHbt1KyP1jStdWyt6Cl2QmOfK24nKEsYBmQQLgnNNBcZX52+aTMJmxrdcIij3+V+017L6Poa0qFGfl15Tk7GPU41v/texvgX1ej3oZtcrnKa6HwUMGZ/fbo7KsfRwYOsX2jHIzGDCWGsB0m/7DsI70efwiCIAiC6BdWBcovrVjeGRzzT57uDVqNAqM95mHZjj3IP7APu17gj2DWoiCnFOrmQvw9n4VhDyxE6qe7sCNhAxZ5DdyTRKtqdVeneUBedVR3ZW3mGPG6qQF2Y3T3s2JaOBJSU7GDbwmx2BKfgNiX/EwGTp1oNdA6TIRP2Eak7juAwt2sDQ+w3U0ZKDgpHcNpVaNNmpy3se+mKK/uei9n/YlS3Rdn40lYH+lJznYNFM4eCHxpB7L2H0B+agS82W5NWQ6KpZijCxe4efDPapw8qZ8MssDruO6bo10vJObvbZUaza8MigHtoaOokXSlLWYTxNBQLN5eDfH91x0OcPMJw4bd+1B4YBfeD2b+om1Ckl7Zrl4IHMp2HcpCSgk7B66Y62NhRmnLJs88ENdvsquaXWhQ8kkW7n8hFR9ueAlLnlFhprsTFD1N5Ie7YvbCl/BGwi7kJITgyntxKGhlpRV/gpRREcjYuQHLIsIQ6OeO+xX9nVRXo9HATtLVOlP+7sT8vcMV/hERWGK0eY+RDuqGA1wCFmLZhgTWVxPwdGMckvK5zPZwZH5kALNTt8DyeK3sqiyjvRY1ta4Y3128vmFG1zrMyS7HBePda1HR6c86tDU1qJjkBP3t17cOFpC7KHBzgqqbTUyv6vgp6L2Mdi6sT5edRL38jwnxPfa809th9EQlCo7xfiqjoRblCheM7s1PgXhl3wEznjGWS1ptItq3SbdyQo5s/OkLYvuKj8HwDXwNuHBcAZcxA/Vb1sfxhyAIgiCIPmNVoDx2zBjEx76Hws8PiJ88bT1qlLw9D6ol4Vj1dgZKSotQwq+gMRSj7KFUDNFdZWquRMGhUlTkJyM+ua8vBe3O2eQ1eC06DvGvROKdMrZD4YG5XiaCuMkqLOPNKtyC5ZuyxCvf8StCoQoKwqqe3m1cm4bwoMVYvGwNkljwX1F6FBXNPEO6OsUmUrN58jI7bnEU1kUGISrLTFBUuBHhr0QjaX04wlN4vUrM9x2IdzsxepBTU/g2VAvCsXjFRmTml6K8sBIXeLbCAfd3W/aoxMw/BOiu3G5aifjMLKS/sgbxfBnt8BAEell5/ashA8/OCULAExtRIV7VDsB8bofWDEQu24ikuI1YtT4LNZfVmDSBr9muReaSIMxbFolVcTmsDUzO47qJr5uDdC3UxhUz/ZlXtRYhm9vc1Q+P9nu+qoS9gwItTV2TbPWhVGTyZd0m0aIqeg5C40pZYK/bo2lRQ8N0ac9E46sbFC1NaNEHD81FyOz3O7SbEB+T0XmlVFOaiPhCC/6uSEN8hv6PJH58HEKD4lBlImjQlkYjYEEcKvSBp6YFLRoF7O1473VgwY4CBZ8dhJrXra5G5nvJ3d9P3pyGJH19HRpUJMYi2yMIM7s/A6uXWNa1ZdnlMJ/+vS8Ktid3HdtaiqRtRZgd6DUwf1b1gFvgQgxK24JsvVm4nt5j42dcZecfaANOq7rLD62g1zLyPm2X1XlLDTMA6lNWImB9PvvGhkf/ENhnJsjKa0B2TBq0wX7o1dql4X74g18R4hO7/ICPL6vnRCJP7Kc6+5Ykp3XZt/kgYhaEIvOMlOb0Uh+d7ZP1pcaMLYjXquAj3QrTf6wffzRqM78tBEEQBEH0CqsC5f5hB+/XtmDZJCUaCxOxOmojYgo1cPOLwI4ITyiG+mLJCx7sqGoWHEZheXQ1vMMCpHP7T/AzizGkLAfppU3Q2o7Dsi2vwtvUjNfGCcExm5mcCpzNicPq9XFIb1Bg5qLN2BzSw/o216XY/Kov3GxqkbKJtYEF2mdtXbHknS0I5qfyNr7qCRcWO2oaSlHCJlB/jvDTnWvE1IUr4X89Hyn5tWyir8TspVuwZJqVQWdP9CCn0v9VJCxyhR0LMGOYLVYnFqHFyRcvx0ZiionligqPl/C+VF56XBzimY4VE0LwfvxSuFh776rSHuLbVYba615h02kHJbRnDiIl8yAqOhwQGBGLZTz45stoY9aI8lZlRmN5VDRSuJ1CNmCDzE4uPrognuM9QEGOW8hKjM6NhNeceQidMwcrT0xEoOHtrDIUcGO2Czy9FgFPzMPioDksMKhB8JYwpi+W7R6CN5zzsXgWC/CenAO/yEq4BJgtzEqYLX2aEMVkU/H61p5EoCV/f/fPcMsPh9fjQVDNmQXV2zUIfIvJZ8LdFB5LERtwElGs3NAFQfALWouzKu6bYi6mLFqJqSe3QDVrFrxCkzHkqTBMFc+UEbAS85vWwG8Ory8IUacDkPCaLwsB+otlXVuW3RCFTyR2zG/BB/NmIYDp0Wve22gJjsUr/rcjTGaMWYgN6yYiL3wWkzMIAbPmYW1dALaESc8BGGi4HzpmMD+chXW5VgZYvZVR9LU1cM7mvsZsw/wt/JAzNq0O0NleXh7Tud+scOx1XoPYZ3rbH1gg/EIs5rfGMT/U9QGv8Bw4vrAGs6UVD6J9g5uwVm/f0Fi0zd+C+ZN0+X3Sh0Ff4u2bhcXZzljfm3HQCnoefxzgH6bCmeggeAUlGl3hJgiCIAiit9zBn+glfb/18OV2Gi0USmX3B+nwvHY21TG57LW3NCF7WSjerQbmbz6AZWxCrBXrtbJsrUaURS4nf+DTs1m674ao8OHnEZ1XPrQaDVhN/W9HOyuHBcq9elhSL+hJTm2rrn5r7+cTj+dLmPvSbGZ7Lku3top24PcnmynUhJ1uB6LuuG6sbStf2tlhRte8DdoB8JemLKxekI/HPo5F4HDez1hfMqc3YyzJZ4ylPmwtvM0d1vtWr7DUlt7IPhDt7Cf96lO3iV7LyO3DAlpztuflMeP1X+c9jR23yr49tG8g6PX4QxAEQRBEn7i9gfJto3ug3F8ac+OQLV+e18lEBP7L3D9I/GKRB8oDd4s/QRAEQRAEQfwi+TcNlNUoWBuJnTWA/8upXcvqCOLfleYcvLuiFDNi3oR3v+/5JQiCIAiCIIhfNv+mgTJBEARBEARBEARB9I3b8DAvgiAIgiAIgiAIgvj5QIEyQRAEQRAEQRAEQcigQJkgCIIgCIIgCIIgZFCgTBAEQRAEQRAEQRAyKFAmCIIgCIIgCIIgCBkUKBMEQRAEQRAEQR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"}}},{"cell_type":"markdown","source":"<div style=\"color:white;\n           display:fill;\n           border-radius:5px;\n           background-color:#4270c5;\n           font-size:110%;\n           font-family:sans-serif;\n           letter-spacing:0.2px\">\n\n<p style=\"padding: 30px;\n              color:white;\">\nINSTALLATION OF PYTORCH-TABULAR LIBRARIES\n</p>\n</div>","metadata":{}},{"cell_type":"code","source":"%%capture\n!pip install pytorch_tabular[all]","metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","execution":{"iopub.status.busy":"2023-06-25T01:36:22.514794Z","iopub.execute_input":"2023-06-25T01:36:22.515254Z","iopub.status.idle":"2023-06-25T01:36:34.094107Z","shell.execute_reply.started":"2023-06-25T01:36:22.515224Z","shell.execute_reply":"2023-06-25T01:36:34.092293Z"},"trusted":true},"execution_count":70,"outputs":[]},{"cell_type":"markdown","source":"<div style=\"color:white;\n           display:fill;\n           border-radius:5px;\n           background-color:#4270c5;\n           font-size:110%;\n           font-family:sans-serif;\n           letter-spacing:0.2px\">\n\n<p style=\"padding: 30px;\n              color:white;\">\nREQUIRED LIBRARIES\n</p>\n</div>","metadata":{}},{"cell_type":"code","source":"import numpy as np \nimport pandas as pd \nimport os\nimport datetime\nimport seaborn as sns\nfrom tqdm.notebook import tqdm\n    \nfrom sklearn.model_selection import train_test_split\nfrom sklearn.preprocessing import LabelEncoder,StandardScaler\nfrom imblearn.over_sampling import SMOTE,SMOTENC\nfrom sklearn.metrics import confusion_matrix, classification_report, roc_curve, roc_auc_score\n\n\nfrom pytorch_tabular import TabularModel\nfrom pytorch_tabular.models import CategoryEmbeddingModelConfig\nfrom pytorch_tabular.config import DataConfig, OptimizerConfig, TrainerConfig, ExperimentConfig\nfrom pytorch_tabular.models.common.heads import LinearHeadConfig\nfrom pytorch_tabular.utils import get_balanced_sampler, get_class_weighted_cross_entropy\n\n\nimport matplotlib.pyplot as plt\n%matplotlib inline\nplt.style.use('fivethirtyeight')\nimport plotly.express as px\n\nimport warnings\nwarnings.filterwarnings('ignore')\nimport itertools","metadata":{"execution":{"iopub.status.busy":"2023-06-25T01:36:34.09666Z","iopub.execute_input":"2023-06-25T01:36:34.09707Z","iopub.status.idle":"2023-06-25T01:36:34.111232Z","shell.execute_reply.started":"2023-06-25T01:36:34.097038Z","shell.execute_reply":"2023-06-25T01:36:34.109418Z"},"trusted":true},"execution_count":71,"outputs":[]},{"cell_type":"markdown","source":"<div style=\"color:white;\n           display:fill;\n           border-radius:5px;\n           background-color:#4270c5;\n           font-size:110%;\n           font-family:sans-serif;\n           letter-spacing:0.2px\">\n\n<p style=\"padding: 30px;\n              color:white;\">\nUTILITY CLASS\n</p>\n</div>","metadata":{}},{"cell_type":"code","source":"class Utils:\n    \n    def print_metrics(self,y_true, y_pred, tag):\n        if isinstance(y_true, pd.DataFrame) or isinstance(y_true, pd.Series):\n            y_true = y_true.values\n        if isinstance(y_pred, pd.DataFrame) or isinstance(y_pred, pd.Series):\n            y_pred = y_pred.values\n        if y_true.ndim>1:\n            y_true=y_true.ravel()\n        if y_pred.ndim>1:\n            y_pred=y_pred.ravel()\n        val_acc = accuracy_score(y_true, y_pred)\n        val_f1 = f1_score(y_true, y_pred)\n        print(f\"{tag} Acc: {val_acc} | {tag} F1: {val_f1}\")\n        return val_acc, val_fi\n    \n    \n","metadata":{"execution":{"iopub.status.busy":"2023-06-25T01:36:34.113145Z","iopub.execute_input":"2023-06-25T01:36:34.113564Z","iopub.status.idle":"2023-06-25T01:36:34.127245Z","shell.execute_reply.started":"2023-06-25T01:36:34.113526Z","shell.execute_reply":"2023-06-25T01:36:34.125703Z"},"trusted":true},"execution_count":72,"outputs":[]},{"cell_type":"markdown","source":"<div style=\"color:white;\n           display:fill;\n           border-radius:5px;\n           background-color:#4270c5;\n           font-size:110%;\n           font-family:sans-serif;\n           letter-spacing:0.2px\">\n\n<p style=\"padding: 30px;\n              color:white;\">\nDATA PREPARATIONS\n</p>\n</div>","metadata":{}},{"cell_type":"code","source":"class Datapreparation(object):\n    \n    def __init__(self,root_path):\n        self.root_path = root_path\n        \n    def get_dataframe(self,filename):\n        return pd.read_csv(os.path.join(self.root_path,filename))\n    \n    def summary(self,text, df):\n        summary = pd.DataFrame(df.dtypes, columns=['dtypes'])\n        summary['null'] = df.isnull().sum()\n        summary['unique'] = df.nunique()\n        summary['min'] = df.min()\n        summary['median'] = df.median()\n        summary['max'] = df.max()\n        summary['mean'] = df.mean()\n        summary['std'] = df.std()\n        summary['duplicate'] = df.duplicated().sum()\n        return summary\n    \n    def rename_column(self,df):\n        updated_df=df.rename(columns=\n                             {\"Product ID\": \"Product_ID\", \n                              \"Air temperature [K]\": \"Air_temperature\",\n                             \"Process temperature [K]\":\"Process_temperature\",\n                             \"Rotational speed [rpm]\":\"Rotational_speed\",\n                             \"Torque [Nm]\":\"Torque\",\n                             \"Tool wear [min]\":\"Tool_wear\",\n                             \"Machine failure\":\"Machine_failure\"}\n                            )\n        return updated_df\n    \n    def set_label(self,df):\n        self.label = 'Machine_failure'\n        return df[self.label]\n    \n    def set_feature(self,df):\n        encoder = LabelEncoder()\n        df['Type'] = encoder.fit_transform(df['Type'])\n        return df\n    \n    \n    def reduce_oversampling(self,X,y):\n        smote_nc = SMOTENC(categorical_features=[0, 6, 7, 8, 9, 10], random_state=42)\n        return smote_nc.fit_resample(X,y)\n\n    \n    \n    def random_split_data(self,X,y):\n        return train_test_split(X, y,test_size=0.20,random_state=42)\n\n \n    def standardization_data(self,X_data):\n        scaler = StandardScaler()\n        std_X_data = scaler.fit_transform(X_data)\n        return std_X_data\n    \n\n    \ndata = Datapreparation('/kaggle/input/playground-series-s3e17')\ntrain=data.get_dataframe('train.csv')\ntrain = data.rename_column(train)\n","metadata":{"execution":{"iopub.status.busy":"2023-06-25T01:36:34.129278Z","iopub.execute_input":"2023-06-25T01:36:34.130082Z","iopub.status.idle":"2023-06-25T01:36:34.249045Z","shell.execute_reply.started":"2023-06-25T01:36:34.130057Z","shell.execute_reply":"2023-06-25T01:36:34.247493Z"},"trusted":true},"execution_count":73,"outputs":[]},{"cell_type":"markdown","source":"<div style=\"color:white;\n           display:fill;\n           border-radius:5px;\n           background-color:#4270c5;\n           font-size:110%;\n           font-family:sans-serif;\n           letter-spacing:0.2px\">\n\n<p style=\"padding: 30px;\n              color:white;\">\nTRAIN DATA SUMMARY \n</p>\n</div>","metadata":{}},{"cell_type":"code","source":"data.summary('train',train)","metadata":{"execution":{"iopub.status.busy":"2023-06-25T01:36:34.251825Z","iopub.execute_input":"2023-06-25T01:36:34.252616Z","iopub.status.idle":"2023-06-25T01:36:36.318029Z","shell.execute_reply.started":"2023-06-25T01:36:34.252592Z","shell.execute_reply":"2023-06-25T01:36:36.317222Z"},"trusted":true},"execution_count":74,"outputs":[{"execution_count":74,"output_type":"execute_result","data":{"text/plain":"                      dtypes  null  unique     min   median     max  \\\nid                     int64     0  136429       0  68214.0  136428   \nProduct_ID            object     0    9976  H29424      NaN  M24859   \nType                  object     0       3       H      NaN       M   \nAir_temperature      float64     0      95   295.3    300.0   304.4   \nProcess_temperature  float64     0      81   305.8    310.0   313.8   \nRotational_speed       int64     0     952    1181   1493.0    2886   \nTorque               float64     0     611     3.8     40.4    76.6   \nTool_wear              int64     0     246       0    106.0     253   \nMachine_failure        int64     0       2       0      0.0       1   \nTWF                    int64     0       2       0      0.0       1   \nHDF                    int64     0       2       0      0.0       1   \nPWF                    int64     0       2       0      0.0       1   \nOSF                    int64     0       2       0      0.0       1   \nRNF                    int64     0       2       0      0.0       1   \n\n                             mean           std  duplicate  \nid                   68214.000000  39383.804275          0  \nProduct_ID                    NaN           NaN          0  \nType                          NaN           NaN          0  \nAir_temperature        299.862776      1.862247          0  \nProcess_temperature    309.941070      1.385173          0  \nRotational_speed      1520.331110    138.736632          0  \nTorque                  40.348643      8.502229          0  \nTool_wear              104.408901     63.965040          0  \nMachine_failure          0.015744      0.124486          0  \nTWF                      0.001554      0.039389          0  \nHDF                      0.005160      0.071649          0  \nPWF                      0.002397      0.048899          0  \nOSF                      0.003958      0.062789          0  \nRNF                      0.002258      0.047461          0  ","text/html":"<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>dtypes</th>\n      <th>null</th>\n      <th>unique</th>\n      <th>min</th>\n      <th>median</th>\n      <th>max</th>\n      <th>mean</th>\n      <th>std</th>\n      <th>duplicate</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>id</th>\n      <td>int64</td>\n      <td>0</td>\n      <td>136429</td>\n      <td>0</td>\n      <td>68214.0</td>\n      <td>136428</td>\n      <td>68214.000000</td>\n      <td>39383.804275</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>Product_ID</th>\n      <td>object</td>\n      <td>0</td>\n      <td>9976</td>\n      <td>H29424</td>\n      <td>NaN</td>\n      <td>M24859</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>Type</th>\n      <td>object</td>\n      <td>0</td>\n      <td>3</td>\n      <td>H</td>\n      <td>NaN</td>\n      <td>M</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>Air_temperature</th>\n      <td>float64</td>\n      <td>0</td>\n      <td>95</td>\n      <td>295.3</td>\n      <td>300.0</td>\n      <td>304.4</td>\n      <td>299.862776</td>\n      <td>1.862247</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>Process_temperature</th>\n      <td>float64</td>\n      <td>0</td>\n      <td>81</td>\n      <td>305.8</td>\n      <td>310.0</td>\n      <td>313.8</td>\n      <td>309.941070</td>\n      <td>1.385173</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>Rotational_speed</th>\n      <td>int64</td>\n      <td>0</td>\n      <td>952</td>\n      <td>1181</td>\n      <td>1493.0</td>\n      <td>2886</td>\n      <td>1520.331110</td>\n      <td>138.736632</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>Torque</th>\n      <td>float64</td>\n      <td>0</td>\n      <td>611</td>\n      <td>3.8</td>\n      <td>40.4</td>\n      <td>76.6</td>\n      <td>40.348643</td>\n      <td>8.502229</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>Tool_wear</th>\n      <td>int64</td>\n      <td>0</td>\n      <td>246</td>\n      <td>0</td>\n      <td>106.0</td>\n      <td>253</td>\n      <td>104.408901</td>\n      <td>63.965040</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>Machine_failure</th>\n      <td>int64</td>\n      <td>0</td>\n      <td>2</td>\n      <td>0</td>\n      <td>0.0</td>\n      <td>1</td>\n      <td>0.015744</td>\n      <td>0.124486</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>TWF</th>\n      <td>int64</td>\n      <td>0</td>\n      <td>2</td>\n      <td>0</td>\n      <td>0.0</td>\n      <td>1</td>\n      <td>0.001554</td>\n      <td>0.039389</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>HDF</th>\n      <td>int64</td>\n      <td>0</td>\n      <td>2</td>\n      <td>0</td>\n      <td>0.0</td>\n      <td>1</td>\n      <td>0.005160</td>\n      <td>0.071649</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>PWF</th>\n      <td>int64</td>\n      <td>0</td>\n      <td>2</td>\n      <td>0</td>\n      <td>0.0</td>\n      <td>1</td>\n      <td>0.002397</td>\n      <td>0.048899</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>OSF</th>\n      <td>int64</td>\n      <td>0</td>\n      <td>2</td>\n      <td>0</td>\n      <td>0.0</td>\n      <td>1</td>\n      <td>0.003958</td>\n      <td>0.062789</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>RNF</th>\n      <td>int64</td>\n      <td>0</td>\n      <td>2</td>\n      <td>0</td>\n      <td>0.0</td>\n      <td>1</td>\n      <td>0.002258</td>\n      <td>0.047461</td>\n      <td>0</td>\n    </tr>\n  </tbody>\n</table>\n</div>"},"metadata":{}}]},{"cell_type":"markdown","source":"<div style=\"color:white;\n           display:fill;\n           border-radius:5px;\n           background-color:#4270c5;\n           font-size:110%;\n           font-family:sans-serif;\n           letter-spacing:0.2px\">\n\n<p style=\"padding: 30px;\n              color:white;\">\nEXPLORATORY DATA ANALYSIS\n</p>\n</div>","metadata":{}},{"cell_type":"code","source":"class EDA:\n    \n    def plot_numerical_distributions(self,dataframe, columns_to_plot, num_rows, num_cols):\n        fig, axes = plt.subplots(num_rows, num_cols, figsize=(18, 10))\n        axes = axes.flatten()\n        for i, column in enumerate(columns_to_plot):\n            sns.histplot(data=dataframe, x=column, hue='Type', kde=True, multiple='stack', ax=axes[i])\n            axes[i].set_title(f\"Distribution Plot: {column}\")\n            axes[i].set_xlabel(column)\n            axes[i].legend(title='Type', labels=['L', 'M', 'H'])\n\n        if len(columns_to_plot) < num_rows * num_cols:\n            for j in range(len(columns_to_plot), num_rows * num_cols):\n                fig.delaxes(axes[j])\n        fig.suptitle(\"Distribution Plots for Numerical Features\", fontsize=24, fontweight='bold', y=1.10)\n        fig.tight_layout()\n        plt.show()\n        \n        \n    def plot_machine_reasons(self,trian):\n        reason_columns = ['TWF', 'HDF', 'PWF', 'OSF', 'RNF']\n        failures_data = train[train['Machine_failure'] == 1]\n        reason_counts = failures_data[reason_columns].sum()\n       # Create a colormap\n        cmap = plt.get_cmap('rainbow')\n        colors = cmap(np.linspace(0, 1, len(reason_columns)))\n       # Plot the reason counts\n        plt.figure(figsize=(8, 6))\n        bars = plt.bar(reason_columns, reason_counts, color=colors)\n       # Add count labels on top of each bar\n        for bar in bars:\n            height = bar.get_height()\n            plt.text(bar.get_x() + bar.get_width() / 2, height, str(int(height)), ha='center', va='bottom')\n\n        plt.xlabel('Reasons for Machine Failures')\n        plt.ylabel('Count')\n        plt.title('Reasons for Machine Failures (Machine_failure = 1)')\n        plt.show()\n        \n    def plot_outliers(self,train,numerical_columns):\n        plt.figure(figsize=(10,6))\n        for i, column in enumerate(numerical_columns):\n            plt.subplot(2, 3, i+1)\n            sns.boxplot(data=train[column])\n            plt.title(f'Boxplot: {column}')\n            plt.xlabel(column)\n        plt.tight_layout()\n        plt.show()\n        \n        \n    def plot_roc(self,fpr,tpr):\n        plt.rcParams['agg.path.chunksize'] = 100000\n        # Plot the ROC curve\n        plt.figure(figsize=(6, 4))\n        plt.plot(fpr, tpr,marker='.')\n        plt.plot([0, 1], [0, 1], color='red', linestyle='--', label='Random')\n        plt.xlabel('False Positive Rate')\n        plt.ylabel('True Positive Rate')\n        plt.title('Receiver Operating Characteristic (ROC) Curve')\n        plt.legend(loc='lower right')\n        plt.show()","metadata":{"execution":{"iopub.status.busy":"2023-06-25T01:36:36.319519Z","iopub.execute_input":"2023-06-25T01:36:36.31997Z","iopub.status.idle":"2023-06-25T01:36:36.333415Z","shell.execute_reply.started":"2023-06-25T01:36:36.319946Z","shell.execute_reply":"2023-06-25T01:36:36.332342Z"},"trusted":true},"execution_count":75,"outputs":[]},{"cell_type":"code","source":"eda = EDA()","metadata":{"execution":{"iopub.status.busy":"2023-06-25T01:36:36.335254Z","iopub.execute_input":"2023-06-25T01:36:36.335599Z","iopub.status.idle":"2023-06-25T01:36:36.350632Z","shell.execute_reply.started":"2023-06-25T01:36:36.33557Z","shell.execute_reply":"2023-06-25T01:36:36.349676Z"},"trusted":true},"execution_count":76,"outputs":[]},{"cell_type":"markdown","source":"<div style=\"color:white;\n           display:fill;\n           border-radius:5px;\n           background-color:#4270c5;\n           font-size:110%;\n           font-family:sans-serif;\n           letter-spacing:0.2px\">\n\n<p style=\"padding: 30px;\n              color:white;\">\nDISTRIBUTION PLOTS\n</p>\n</div>","metadata":{}},{"cell_type":"code","source":"num_rows = 2\nnum_cols = 3\ncolumns_to_plot = ['Air_temperature', 'Process_temperature', 'Rotational_speed', \n                             'Torque', 'Tool_wear']\neda.plot_numerical_distributions(train, columns_to_plot, num_rows, num_cols)","metadata":{"execution":{"iopub.status.busy":"2023-06-25T01:36:36.352105Z","iopub.execute_input":"2023-06-25T01:36:36.352494Z","iopub.status.idle":"2023-06-25T01:36:44.668488Z","shell.execute_reply.started":"2023-06-25T01:36:36.352469Z","shell.execute_reply":"2023-06-25T01:36:44.667558Z"},"trusted":true},"execution_count":77,"outputs":[{"output_type":"display_data","data":{"text/plain":"<Figure size 1800x1000 with 5 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FpMCX375pbHbrKFDh1r8WDd//nxly5bNbHr27NntLnOmTJn0ySefqGLFinJyctL169e1cePGOO8uLiIiQsmTJ1f37t3VoEEDpUiRQgcPHtS0adOM46FENmLECDVr1kzOzvEfzr377rvaunWrpFcJAkutHDp37qwuXbqYTc+VK1eM9hkREaH+/ftbPPY0adKoV69eql69upIlS6aDBw9q+vTpZsu+ePFCAwYMkKenp1mCwRYXFxf16dNH77//vp49e6bff//dYkJw3759unfvXrSup7gyffp0q61aoxqbyJaXL19qwIABFj8gZsqUSX379lW5cuUUHBys3bt3a+7cuWa1//38/DR8+HBj4iqurh9LlQhy5MihTz/9VMWKFVO6dOkUGBioO3fuyNvbW4cPH9a5c+di/TE0ps8aw3Vx5swZ/fHHHxa3XaxYMfXu3VsFChTQw4cPtXz5cm3fvt1sucOHD2vOnDnq06dPtMqeJk0a9ejRQ9WrV5eLi4v+++8/bdu2TSlSpIjWduxRokQJtWjRQmvXrjVOu3r1qpYtW2Z1PClHljFjRg0ZMkSlS5eWt7e3fv75Z7NKBWFhYTp37pykV79lv379lC1bNm3btk1z5swx2+aVK1f0zz//mI11+u+//2rMmDEWy/HBBx+oZcuWyp07tx4/fqy///5bS5cuNUu0f/XVV2rYsKHeeeedaB1nXL/j+vfvr8ePH1ucV6hQIXXq1EklS5aUi4uLHjx4oCNHjmjdunVWE3/JkiVTkSJFVLZsWZUqVUqurq7KmDGjMmbMqOTJk+vZs2f677//tHv3brN7JyIiQpMnT9aMGTNidCzxwd7n8+tjbMb3NZIxY0aVKVNG5cqVU86cOY3nOG3atAoJCZGfn5/Onz+vxYsXm7XA27Rpk65du2bszjF79uzGZ/6ZM2f09ddfm+2vfv36FpNYlmK2xOLs7KzOnTurTp06ypgxo27fvq09e/YYx18MDg5W3759LVZ6KVasmD766CMVLlxYoaGhOnXqlGbNmmV2byxevFitWrVS3bp1jdNevnypo0ePmm2zcOHC6tmzpwoWLKjUqVPr6dOnunnzpry9vXXo0CH9+++/cXwGAACAIyGRBwAALLL2MeXhw4cx3qal2v9p0qTR5s2brXYTKL36+Ll69WolT57cOK1gwYIqWLCgJClDhgwW1ytTpozJh7DoKliwoDZv3myWqOnVq1eMt2nLjBkz1KZNG+N/16lTR/Xq1VOTJk3MWrXcvn1bW7duVdOmTeOlLJFlzJhRVatWlWQ9kZsrVy7jMnFhx44dFrsFTJEihTZs2KAKFSoYp9WtW1eNGzdWo0aNzD6onTlzRjt27FDDhg3t2q+zs7PWrl1rcix16tRR7dq1dfXqVZNlIyIidOLECTVu3Dg6hxZjISEhunbtmpYvX64///zT4jLJkiVTo0aNYryPhQsXWuz60dXVVXv27FH+/PmN0z788EPVqFHD4jhUmzdv1oULF1SiRIk4u34sPT9mz56tatWqWV3n4cOHWr9+vdzd3W1u25bYPmvGjx9vseu6ChUqaOPGjUqdOrVxWqtWrTR06FDNnDnTbPmJEyeqV69eJs9BW7JkyaLNmzeraNGiJtO7d+9u1/ox8c0332j9+vUmydNx48apffv2CVLpIK6kSJFC69evV5kyZSS9SpS4uLhY7dY4X7582r59uzJmzCjpVZLiwYMHxjFeIzt+/LhZIm/cuHEWE86jRo3SF198YTKtVatWatCggVni+9mzZ5o6daq+/fZbu48zrt9xnp6e8vLysjiva9eumjBhgtl10KZNG40ePVp//fWXyb1gMGPGDLuu+V69eqldu3basWOHyfS9e/dG4wgcV3xeI4UKFdKNGzeirPDSpk0bNW3aVHXq1DGZHhERob179xoTealSpTI+z61185glS5Y4jRniWurUqbV69Wqz90vkSglLlizRzZs3zdZt0qSJ5s2bZ3KtN27cWJ06ddIHH3xglsz77bffTBJ5jx8/tvjOWLt2rc3KUbdv39aaNWusvqcAAEDSRteaAADAovTp01uc/vTp0xhv09XV1WxacHBwlK38ChUqpK+//jpeWpHY8scffyRYa6uqVauaJPEiT2/durXFdd6UD5SWGGrzv65z584mSTyDChUqWGzRJb0aZ89eXbp0Mfu4mD59eqvJMUsf8eKSq6ur8X9Zs2ZV5cqVNWHCBKvdXnbp0kX58uWL8f6snff+/fubJPEMmjVrZvIBMjJLLctiw9LzI6oWCJkzZ1bPnj1VsmTJOC2LvUJCQrR7926L80aPHm0xcfHDDz9YPFZfX1+dOHHC7n2PHDnSLIkX34oWLWr2vLpx44aWLFmSoOWIrVatWhmTeAa2EsZDhgwxJvEMrFUe+O+//0z+OzQ01Cz5JL16772eoDFo0qSJxfsxqjH4XhfX77iNGzdanF62bFlNnDjRajI3RYoU6t27t8UKRIYk3oULFzR27Fi1b99eZcuWVd68eZU1a1aTZ6Sl8+jr66s7d+7E4qgSX3xfI8mSJZOTk5MCAwO1du1a9e3bV/Xq1VORIkWUI0cOZcqUyXiOX0/iGdgaIzIpGjhwoM17XpLFcXiTJUumsWPHWrzW8+XLZzaWqPSqxXXkSnIZM2a0mFSN6n2XM2dO9evXL1F6CQAAAPEv6VSLBAAACSogIMDi9NjU9C1cuLAyZ85s8sEiNDRUNWrUUKVKlVS8eHEVKFBAhQsXVtGiRWOVkIitwoULq3r16gm2P1utuho3bqwVK1aYTY/u+G9JyZEjRyxO9/DwsLpOkyZNNHfuXLu3ZUmrVq0sTs+ZM6fF6dbuk8RQtmxZ/fzzz7HaRkzPu6Vk1eHDh2NVltdVrlxZmzZtMpk2aNAgzZw5U++9954KFSqkQoUKqXDhwipSpEiCJ/4tOXfunMUxHrNmzapKlSpZXCdNmjSqW7euVq9ebTbv8OHDqlixYpT7zZAhg9UKAPHt66+/1po1a0xaEY8bN04dO3ZMlPLEhKUknK2P45aWt9YK9PVnxrlz5yw+R65cuWIxoWvLxYsX5e/vb9d68fGOO3TokMXpn376qd0tSV93//59DR482GLSxF4PHz5Ujhw5Yrx+YkuIa2TZsmUaMWJEjMc2jE1vDY6oW7duUS5j6R0XHh4e7YojERER8vLyMib50qRJo9KlS5v1StC6dWtjF7OFChVSwYIFVaRIERUqVCjOu3sHAACOh0QeAACw6P79+xanZ86cOcbbTJYsmQYPHqz/+7//M5keFhYmLy8vsy65smTJolq1aqlTp05WW/3EF0utvuJToUKFoj0vph/ckgJL3TtKrz4+W2NtnrVr2RJrH+AMY+K8zlq3YQmtXbt2+vXXX622pLXH06dPLY675+TkZPP6tHbeXx9HKbYGDRqkbdu2mZ3zixcv6uLFiybT0qRJo8qVK6t169Zq27atUqVKFadlsZe169jW+ZRif05Lly6tlClT2rVsXCtUqJDatm2rZcuWGafdvHlTCxcutHn/OhJLv0/atGktLpshQwaLLcmsJZJfv36tXSMxERERoXv37tmV3ImPd5y1Z609yWdLHj9+rEaNGsVqbF7JsSpcWBu793WRE8fxfY3MmDHD4jh20eFI5zi2cufOHWWrtmfPnsWqh4rXvf4bf/XVV/roo4/Mljt58qRZJa6MGTOqWrVqat++vZo1a0ZSDwCANxRveAAAYObly5c6d+6cxXmGMVBiqm/fvho+fLhdH5n9/Py0evVq48f4Fy9exGrf0eHm5pZg+5KsJ4ok6x+Q4+Ij0utj7zkKa8cWk/MUnQ+M1j6Ax7Q1SXzKly+funfvrr1792rmzJnRbpnxOmvnPFWqVDaPPy7Ouz3Kly+vhQsXKmvWrFEu+/z5c+3du1dffPGFqlWrZja+YUKxdk6tnbOo5tt7ThP6+fW6r7/+2qxrufHjxys4ODhe92tpDLGYsNTy3Fq3kLEdjyqu75PXx9+yJj6ukSdPnlicHtNzNHr06Fgn8aS4uy7iQpkyZVS1atUo/xe58kF8XiO3bt3SDz/8EOttOso5jouYxp57I77v26ZNm+qPP/5QunTpolz3yZMn2rp1q7p376569erJz88vTssGAAAcA4k8AABgZsuWLVbH4KpVq1astz906FCdPXtWI0eOVJ06dZQpU6Yo19m5c6dGjBgR633bK6Fb8Dx//tzqPEutpCTr4xhaYu33tPbhNbFZO7aYnKfofES2lrCyNF5NQti6davJ/3bv3q2jR4/qxo0bOnXqlH7//XeVLVs2TvZl7ZwHBQXZ/DgaF+fdXo0aNdLp06c1bdo0tWzZ0mqXp5FdvXpVH330UaJ8aLZ2Tq2ds6jm23tOE6sFokH+/PnVoUMHk2m3b9/W/Pnz42T71lrC+vv7x8n2o3O/x/bZ8PrYerFlbyvh+LhGrB1LTJIeoaGhWrlypcV59evX16ZNm3T16lU9fvxY/v7+8vf3N7vm3hTxeY2sXbvWYiWp9OnTa8yYMTp16pTu3btnPMenTp2K07LEhK1rPC5iGnvujYS4b7t27apz585p/Pjx+vDDD+1qyXnixAl9/vnncVo2AADgGOhaEwAAmAgJCdHEiRMtzkudOrXef//9ONmPm5ub+vXrp379+kl61fruxo0bun79uo4ePaolS5aYfcxevHixfv7550T/SB0frly5YnWetdZEllomWWs1EhgYaLHFlrWWl4kte/bsFluWXL582erYiZcvX7Y4PbFbJ8VG1apVE2xf6dOnV9q0ac3uu4iICF25ckVFixa1uJ61827PR8eYSJMmjTp27Ggcc+3Zs2e6fv26fHx8dObMGS1dulQ3b940WefChQvy8vJK0HEvJevjqtm636WEP6fx4auvvtLy5ctNKhFs3LgxWtuw9TyzxFGfZ7ZYez69//77Zt1Q26NEiRKxLVKMubm5WRwr7fjx49HuVvX69esWE7MFCxbUkiVLLHZd+qZ2Nx2f14i1xNzYsWPVqVMns+kJfY6TJ09uVpHEVkWIhHoGpE2bVunSpTMbAzVDhgxavnx5tLeXK1cui9NdXV318ccf6+OPP5b0qrLCjRs3dOPGDZ08eVKLFi0yu+d27NihmzdvKnfu3NEuBwAAcFwk8gAAgInhw4fr7NmzFud9/PHHcV4L2SBLlizKkiWLKlSooLZt2+rdd981JvkMXrx4ocuXL6tUqVIm0621onKUrp7ssWXLFrPjjTzPEkstsax1w3Tz5k2zRF5gYKC2b98erXJaO9dx3UVn5cqVzcY9k6TNmzerfv36FtfZtGmT1W3BPpUrV9aePXvMpm/evNlqIs/aea9SpYrZtPi4ftKlS6fSpUurdOnSatKkiTp16qQyZcqYLXf27NkET+SVKlXK4sfeBw8e6OjRo6pUqZLZOs+fP9fu3bstbs/SOXVUefPmVefOnTVv3jzjtIiIiGhtw9bzzJI1a9ZEa/uOoFSpUkqfPr1ZN6ze3t4qW7asXFxc7N5WaGio1eRnQqhWrZouXLhgNn3WrFlq3759tMbuevTokcXpJUuWtJjEe/jwodk4u2+K+LxGrJ1nS89Qyfrz3prYPvPTpUtn1souICBAT548MYtHb926paNHj0arfLFRpUoV7dq1y6xsqVOntnr+LInOfevq6qoyZcqoTJkyatGiherUqaPmzZubLXf27FkSeQAAvGHoWhMAAEiS7t69q+7du2vWrFkW57u6umrAgAGx3s+QIUN05MiRKD/oWqtxbakLKGvjSV2/fj36BUwkXl5eWrVqldn0I0eOWJwuSR988IHZNGsfbpYtW2Y27bvvvot2V3TWzvWNGzeitZ2oNGrUyOL0xYsX6/jx42bTjx8/rkWLFllcp2HDhnFatjeZtfP+xx9/WLyfNmzYYDXp1KBBA7Npsbl+Jk6cqA0bNigoKMjmcq8nzQwScoxNgxQpUqhu3boW5w0fPtximX788UeL92W2bNlUrly5uC5ivPryyy/tGg/VGmvPszVr1piNt7d27Vrt3bs3xvtKLM7OzhYrJ/j5+WnAgAFWu0U2CAgI0MqVK9WoUSOtWLEivopplyZNmlicfuLECX355ZdWkzdhYWGaM2eO7t+/b5xm7Vlx4sQJs/ggODhYffv2tdn1clIWn9eItfO8b98+s2kHDhzQtGnTolHy2McM9sY0YWFhGjJkSIKO+9u4cWOL0/v27StfX1+b64aGhsrT01M9e/bUkCFDzOb/8MMP2rt3b5THE51YGQAAJG20yAMA4C1z4cIFOTs7Kzw8XE+ePNGtW7d04MABbd++3eoH8uTJk2vu3LkWu3KMrkWLFmnOnDnKkiWLatasqZIlS6pAgQLKmDGjnJ2d9fjxY3l5eemvv/6yuL67u7vZNGsfeoYNG6aBAwcqV65cxtrO2bJlU8GCBWN9HPHhs88+0+HDh9WgQQM5Ozvr0KFDmjZtmsUPOTlz5rSYdKlYsaLFFnxTpkxRUFCQPDw8FBAQoMWLF2vHjh3RLqO1c71+/XoVKVJE5cuXV5o0aYzTY9o1ZIMGDVS6dGmz1qEhISFq1qyZevXqpffff19OTk46dOiQpk+fbvFjZqlSpUjkRUOXLl3022+/mXxQl15151W3bl19/vnnKl++vIKDg7Vr1y7NnTvX4nYaNWqkkiVLmk2PzfVz4MAB/fjjj0qTJo2qVaumMmXKqFChQsqcObNSp06tp0+f6vz585o9e7bFfVh6diSEwYMHa8OGDWaVF44fP646deqod+/eyp8/vx49eqRly5ZZbSU7YMAAq61bHFWuXLnUtWtXq79JVCpWrGhx+rFjx9S2bVt99tlnSp48uXbu3Gn1nZEUfPXVV1q3bp1ZK/Lly5fL09NTXbp0UdGiRZUtWzYFBQXp0aNH8vb21okTJ3T48GFjUrNLly6JUXyj2rVrq2rVqhZbxv311186cOCAOnXqpBIlSsjFxUUPHz7UiRMntHbtWt26dUv16tUzLl+wYEG5uLjo5cuXJtu5deuWGjdurN69eytnzpzy8fHRrFmzrPYk8KaIr2ukRIkSFlvZff/997pz546qV68uJycn7d69W3PnzjVLoEclT548FqcfPXpU3377rWrUqGEy9me5cuVMuk+vWLGixe4yhw0bJj8/P73//vu6d++e5syZk6Ct8SSpc+fOmjBhgm7dumUy/fz58ypTpozatm2rihUrKkeOHJJevUevXLmiM2fOaP/+/caWhoZuoiPbvHmzfv/9d2XIkEE1atRQ6dKlVahQIbm6usrFxUX+/v46efKk1cp3ifW+AwAA8YdEHgAAb5mvv/46WssnS5ZMEydOtNj6Kzb8/Py0Zs2aaHWFVqpUKYvjiFSqVEkzZ840m/7vv/+qT58+JtM6duwY7RrlCSU0NFSzZ8+266P3yJEjLXbF1KpVK40cOdJit6L2btuWEiVKWOziKyQkRKNHjzZbProt/gycnJw0adIkeXh4mNUsf/78uX7//Xf9/vvvNrfh4uKiSZMmycnJKUZleBulTp1aEydOVJcuXcyuoUePHmnUqFFRbiNz5swaM2aMxXlxcf08f/5cu3btMuvSzBZbLePi23vvvae+fftq8uTJZvMuXryogQMHRrmNSpUq6ZNPPomH0sW/wYMHa9GiRWYJGXtUqFBB+fPnt9ga1NPTU56ennFRxERXvHhxDR06VL/88ovZvHv37um3335LhFLFzKRJk9SgQQOL9+6lS5f0ww8/2LWd1KlTy8PDQ6tXrzabd/r0aX3++edm0y09W94U8XWNtG7dWr/99pvZ8z4oKEh//PGH/vjjD5Pp0T3HmTJlUqFChSyOCzp58mSz5+Lp06eVN29e43+3bdvWYoWR8PBwjRs3TuPGjbO7LHEtVapUmjx5stq0aaPQ0FCTec+fP9f8+fM1f/78WO0jICBAmzdv1ubNm+1eJ3PmzFYrQQAAgKSLrjUBAIBV2bJl07Jly9S1a9fELoqcnZ01duxYi/MaN26sLFmyJHCJ4lbv3r3tHiOla9euatWqlcV5efPm1ccff2zXdlxcXNSiRQt7iyhJSpkypTp06BCtdWKqXLlymj17tkkLLXulTp1aM2fOVPny5eOhZG+2xo0b67fffovRWFvvvPOOFi9erHz58lmcn5DXT2TDhg2LkxbFMfXTTz+pffv2MVq3ZMmSWrRokUkrlaQkR44c6tatW4zWdXJy0o8//mj38olxbcWVb775xqziSVJUpEgRLV++PE7utxEjRtg9Lm/Lli2tdu35poiPa6Ro0aJ2VxJInTq1xQoJUYnp/S+9Gnfxww8/tGtZV1fXBG+BX7t2bU2fPl2pU6dO0P3a8ssvv1gcRxIAACRtJPIAAICZzJkza8iQITp69KjFca5iw1KLuqjkyZNHq1evVvXq1S3OT5MmjWbNmmV1LJakoEmTJlqwYIEyZ85sdRknJyf16dMnypZoo0aNkoeHh81l8ubNqzVr1lgcdycqI0aMUNmyZaO9Xkx4eHhoz5490eqis1KlStq1a5eaNWsWjyV7s/Xs2VMbN2602D2mNfXr15enp6eqVKlic7mYXj85cuSIduvK9OnTa/To0Ro8eHC09xeXkiVLphkzZmjSpElyc3Oza51UqVKpV69e2rVrl7JlyxbPJYxfgwcPjvGH7mbNmun777+3+dunS5dOEyZM0LBhw2JaRIcwZswYLVq0KNrdP2fKlEk9evSw+o5MaJUrV9bBgwfVunXraHUH+/pvnC9fPi1fvjzKijqdOnXS1KlTY1TWpCY+rpHRo0db7N4xMjc3Ny1fvlxlypSJ1n4lqU+fPrGKJadPn67KlSvbXKZUqVLaunVrjMoXW23atNGePXuiff+lTJlSHh4e6ty5s9m8mMTKWbJk0Zw5c9S2bdtorwsAABwfXWsCAPAWSp48uVKmTCkXFxe5uroqS5Ysyps3r4oUKaLKlSurWrVq8Vab959//tHly5fl5eWlU6dOydvbWzdv3tTjx4/1/PlzpUyZUmnTplWePHlUqlQp1atXT40bN46yPB988IEOHTqk2bNny9PTUz4+Pnr69KnFLiYdVePGjVWxYkXNmzdPW7Zs0Y0bN/T8+XO5ubnp/fffV8+ePVWhQoUot5MqVSotXrxY69at09KlS3XixAn5+/vL1dVVRYsWVfPmzdWlSxelTp3aYpd1UcmQIYO2bdumpUuXauPGjTp37pweP34c7bFz7FWsWDFt3bpVx48f16ZNm3T48GH5+Pjo8ePHkl7Vws+dO7eqVKkiDw+PKBNJsE/VqlV18OBB/f3339q2bZuOHDmiO3fuyN/fX8mSJVOmTJmUP39+Va1aVS1atFCpUqXs2m5Mr58///xT3333nQ4cOKCTJ0/q/Pnz8vHxka+vr54/fy4nJyelSZNG7u7uKlasmGrVqqXmzZvrnXfeiYvTESe6deumDh06aN26dfL09NSJEyfk6+urgIAApUmTRpkyZVLx4sVVvXp1tWvXzu6kn6Nzc3NTz549NWXKlBitP2jQIGPLl0OHDsnX11cuLi7KmzevGjZsqJ49e8rd3V0+Pj5xXPKE16RJE3l4eGjXrl3avXu3jh07ZrzvQkNDlS5dOrm5ualw4cIqXbq0atasqQoVKsSoBW18ypYtm+bMmaMffvhBa9eu1eHDh3XhwgU9fvxYgYGBcnV1VbZs2ZQ3b17Vrl1b9erVszieWpUqVXT06FFNnz5dW7du1fXr1xUWFiY3NzdVqFBBXbp0Ue3atRP+ABNRXF8jzs7OmjZtmrEby2PHjunhw4fKmDGj8ubNqyZNmqhr167KnDlzjO4xZ2dnLVu2TGvXrtXKlSt19uxZPXz40O7udl1dXbVlyxYtXrxYq1at0rlz5/T06VNlzpxZpUuXVqtWrdSuXTslT55c69ati3b54kLx4sW1efNmnTlzRhs3btSxY8d05coVPXnyRM+fP1fatGmN3YyWKFFC1atXV/Xq1ZU+fXqL21u7dq1u3rypgwcP6uTJk/L2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g1iUjwMAAAAAAEWtUIm8m1kLrm3btjd9PYvFomeffVZr1qxR//799frrr9vt9/PzkyQlJCQ4PT4pKckuzvo654y7/MTn5xr5eerflUt84eZ5eHhU2J+tyS1DbmajTG4GeXrmvf6aye3aFDFrnMVi0We/xyvz+hqQkv7m76Y6/h5257Rey2gyyuhmkNFkkNHNYLetqPebjNdmCpqMpmK/VlHur+njpp+v2N90zrJIv6e7qVFV6hxdryJ/hlF6SnpMhZuXabZo6S/OHzqhfFzRKK21tlxxjS9XbBMAAAAAoGQVKpH34IMPymDI/2wOg8GgS5cu3dS1zGaznnnmGa1cuVL9+vXT4sWLZTTa/8fVuqZdbGys03NY17ezxllff/fdd7ZZGPmJz+0aFotFsbGxCg4Olo+PT0HfIlCh/eeXFP2S4LwUZ5daeScFkbea3s5v8h29kkkiD3ARJTmmAlxdaa215YprfLlimwAAAAAAJatQibxatWrletMpJSXFdoPJw8PDIUlWEDmTeA899JDeeecd27p4OdWrV0/BwcHat2+fkpOT7ZJpaWlp2rNnj4KDgxUeHm7b3rZtW3333Xfavn27Bg4caHe+7du322Ks2rVrZ9s3fvx4u/gffvhBCQkJ6tq1602/V6AiOh6fqb9/53yW60N1K+kWH8fPO/IvqJLz/jt6hVKDgKsoqTEVAAAAAAAAypZC1WI5dOiQDh486PTXiRMndPLkSf3973+Xm5ubhg4dqoMHDxb4GmazWWPHjtXKlSvVu3dvLVmyxGkST7r2dPqQIUN09epVzZs3z27fggULFB8fryFDhtjdKBs0aJDc3Nw0f/58u3KZx44d0+rVq1W3bl116NDBtj0iIkJt2rTRzp07tXnzZtv2zMxMzZo1S5I0dOjQAr9PoKLKyLZo5I4rSnVSNiqoklH/vNu/FFpVvvh7GOTp5NueRB7gOkpiTIXilZZl0brYVL20P0HDvr6kYV9f0ryfEvVtXFqupREBAAAAAABupFAz8m4kICBAkyZNUnh4uEaMGKHbb79dDzzwQIHOMXfuXH344Yfy9fVVRESE/vnPfzrEREZG6o477pAkjRs3Ths3blRUVJQOHjyopk2b6vDhw9qyZYsaN26scePG2R0bERGhKVOmaNasWWrbtq169eqllJQUrVu3TpmZmYqKipKbm303LViwQN26ddPgwYPVu3dvBQcHa+vWrTpy5IiGDh1ql/gDkLe5PyXq50vOE0qL2ldRNS9m4xWWwWBQYCWT/ki2Xyfv6BXnpUwBuJ6iGFOheJgtFv1wIVO7zqYr47p1Xj//LU2SVM3TqLGNfPVQXdbfBAAAAAAABVOsiTyrhx56SFOnTtXChQsLfNPp999/lyRdvXpVr732mtOY0NBQWyLPx8dHX3zxhebOnav169dr165dCgoK0pgxY/TCCy84Xbtu0qRJCg0N1eLFi7V06VK5u7urVatWmjp1qpo3b+4QX79+fW3fvl0zZ87U1q1blZycrPDwcM2dO1cjR44s0PsDKrKTSVl691iK031PNvBR51u44VlUAisZHRJ5fyRnKz7drABn0/UAuKTCjKlQ9BIyzPr0ZKrOpZrzjLuUbtaMHxL1r0NJalvTU7dXcSvQmogAAAAAAKDiKpFEniSFhITo8OHDBT5u8eLFWrx4cYGO8ff31+zZszV79ux8H9O/f3/1798/3/ERERFatmxZgdoF4C9pWRatjUmVs2JjgV5GzWhJSc2iFOjlPFl3LD5TrYM8S7g1AArjZsdUKFppWRZ9FJOiK+n5L5t5JcOiL35P04lEN3Wv5SUvN5J5AIrW1UxzruV8PU0G+brzABcAAABQ1pRIIs9sNis2NlbZ2dk3DgZQIfz3VJriMxxvMhgN0iP1KqkSNzeLVG6JvCOXSeQBZQljKtdgtli0/lRqgZJ4OUXHZ+lsSrIeDvdW1Vy+nwFXRaLItaVnW7TkWLLTfU828JGvewk3CAAAAEChFXsiLzMzU9OnT1dCQoJatmxZ3JcDUAZ8ejJFB3JZF69DTQ+F+LAuXlELrOS8T1knDyg7GFO5jp1nMnQyKfdkqodRyrZc+5Wb+AyLPvg1WX3rVlIt3xIrkgEUGokiAAAAAChZhbpr8PTTT+e6z2Kx6MKFCzp48KAuXLggg8GgMWPGFOZyAMqBi2nZmrg3wem+upVNurOGRwm3qGLwNBkU4GFwmAV59IrzhCqAksWYquw4Hp+l/53PcLovxNuoxe2r6J4QL2VkW7TnXLrm/5yknWedx6dlSx/FpKpveKXibDIAAAAAACjDCpXI+/DDD2UwGGSx5F1WyMfHRy+99JL69OlTmMsBKAem7kvQ5XSzw3Y/D4MeDq8kg4GSmsUlqJJJ8Rn2M/COxmfKYrHQ70ApY0xVdiw8ctXpdl83gz7uWk23V732QIqHyaB7Q7x0b4iXPv8tVc/tueK0FGeWRVoXm6qeYV6KDPMu1rYDAAAAAICyp1CJvBdeeCHXfQaDQd7e3qpXr546dOggX1/fwlwKQDmw7c80rYlNdbpvQesAnU/NVoKTdfNQNGp6G/XLdZMhEzMs+v1qtsIqU9YNKE2MqcqG86nZ2vRHusN2k0HqU7eSgrydlzHuVaeSWtXw0MCtl/STk9LSWRZpxLfx+vw+k1rVYN3SiiSv9eakvMuzAgAAAAAqhkLduZ0yZUpRtQNAOZecadb4PfFO9z0Y6qV+4d5adCSpZBtVwdTM5Qbz4cuZJPKAUlYSY6r4+HjNnj1bBw4c0KlTpxQfH69q1aopIiJCI0aMUM+ePR1m5yYmJurVV1/V+vXrdf78edWoUUM9e/bUlClT5Ofn5/Q6a9eu1eLFixUdHS13d3e1atVKU6dOVbNmzZzGx8TEaObMmdq5c6eSk5MVHh6uxx57TCNGjJDRaCzyfiiM3bmUyGxe3f2G67sGe5u0olNVPbT5ko4nOK5Pmppt0aPbLmvrg4Gqw3dyhZHXenOS9MTfmKUJAAAAABWda90dAVBuzT6QpN+vZjts9/Mw6J+tA0q+QRVQsLfzr/yDl1knD6gILl++rJUrV8rb21uRkZEaO3asunTpoujoaA0bNkzPPfecXXxycrIiIyO1aNEi3XrrrRozZozq16+vRYsWKTIyUsnJjsmH+fPna+TIkTp//rwef/xx9enTR/v27VP37t21c+dOh/jo6Gh17NhRGzZsUOfOnTVq1ChJ0uTJkzV+/Phi6YebdSE122kCzt0o3ZXP9V0ruRnUq46XGlVxnqi7mGbWw1suKd5JCWoAAAAAAFAxFenjvmazWadPn9bVq1fl6+ur2rVru9yT1ABK3oGLGVp81PmaQjNa+Cs4l5liKFrVvYzydjMoJcu+TtchEnmAyymOMVVYWJhOnTolNzf74V9SUpK6du2qZcuW6amnnlKDBg0kSVFRUTp06JDGjRunGTNm2OJnz56tefPmKSoqSlOnTrVtj4mJ0Zw5cxQREaFt27bJ399fkjRq1Ch17txZzz77rPbv3293/QkTJigxMVFr1qxRt27dJEnTpk1Tv379tGzZMvXt21cdOnQo1PsuKj87KYkpSc2qu8vHPf8/G6PBoPtDvWRWmo5ecUwM/pqQpce/uayPu1aTycj6pShbDJIupTk+uGXlaTLItwCfl4oqr5Kr9CEAAABQ8RTJ/wB++uknDRkyRKGhoWrWrJnat2+vZs2aKTQ0VMOGDdNPP/1UFJcBUAZlmi16Zne8zE7uRdSpbNIwSkaVGKPBoIZOZoGQyANcR3GOqUwmk0MST5IqV66sTp06SZJiY2MlSRaLRR988IF8fX01efJku/gJEyYoICBAK1askMXy15f7ypUrlZWVpYkTJ9qSeJLUoEEDDRgwQCdPntSOHTts20+cOKE9e/aoffv2tiSeJLm7u2v69OmSpOXLl9/0+y1KZotF0fGFm42Xk9FgUGSolyL8nD/I8nVcul79iXLTKHsyzddKheb2K6/1AG/kaqZZl9Kynf66mlm+ZrFaS64WdR8CAAAAKJsKncj74IMP1K1bN23YsEHJycmyWCy2X8nJyVq/fr26deumFStWFEV7AZQxS6OTddhJoshkkHrX8ZLRwGyDktS4quMN59NXs3WFMm5AqSutMVVaWpp27Nghg8Gg+vXrS7o2u+7MmTO666675OPjYxfv5eWlNm3aKC4uzpb4k6Rdu3ZJki0pmJN12+7du/MV36JFC/n7+9vFl6bfr2YrOcvx5vnf/N3k7fbXcNo6Gym3XznvvxsNBvUIq6SgSs6H4//8OUmbTqcV9VsByiySWwAAAAAqqkKV1jx48KDGjx+v7OxstW7dWs8884xuv/121axZU2fPntWxY8f05ptvas+ePRo/frzuuOMO3XHHHUXVdgAu7nJatuYcSHS6r2OIp2pUoqRmSbujmrvT7YcuZ6pDsGcJtwaAVUmOqeLj47V48WKZzWZdvHhRW7Zs0R9//KEXXnhB9erVk3QtkSdJ4eHhTs+RMy7na19fXwUFBeUZb5XXNQwGg8LDw3XgwAGlpKTI2zvv2dtpaUWT8MrIyJBkUna2fWnAI5cynMb/zc+orKy/ZuplmC369xHn/+5J0siGfnbxRkm9Qz20MiZNVx0n/OmpHZf19f0BqpnLGqdlybW+/ev3vJjNbnb9ZL/PUmQ/b1e4bl7XlCSLdMM2FaRvi0Jebc6rvdeOvfl+LK6fT27ntX4P5NWvJd2m/Jy3LHx+SvrvbEVRUv3q5eVVrOcHAACAo0Il8hYuXKjs7Gw9/fTTmjVrlt2+sLAwhYWF6b777tNLL72kN998UwsXLtSSJUsK1WAAZcecn5IUn+H4hHT9ADd1CC54KTIUXuOqJPIAV1SSY6qEhATNnTvX9md3d3fNnDlTY8eOtW1LTLyWjMpZIjOnypUr28VZXwcGBhYoPr/XuFEiLy4uziH5drO8q4co+Wqy7c/ZFul4gpuuzbf7SyWjRQHZyUpM+GubxVxZiQm5J/Jy29+pqkFfXnDT9ZP+rmRY9NS3FxXVMF3lZbm8c+fO3TDGu3pIrv2Yke6p0xfjirpZpXbdvK4p5f136vo25advi0Jebb7RZ6Aw/VhcP5+8fwbeefZrabTpRuctS5+fkvo7W9EUZ7+aTKZcH/IBAABA8SlUIm/37t3y9/fXyy+/nGfctGnTtGzZMpcpjwSg+EXHZ2ppdLLTfXPvCtCR/8/encdXUZ+LH//MnH3JyUYSEiBAiAgKiqiogIigUJeKK+60tlV7tT+p1quWW3tr5WKxVcu1ldb20qq4i7buAqKygyLIviXsgRCyneTs58z8/oiJHM4kZF+f9+vFi8N8vzPzPZPJYc488zzfcnkCtyMMTTWjKiTMWbixnmwTIUT7aM9rqv79+1NRUUEsFuPgwYO8/fbbPP7446xZs4Z//vOfhvPodXY5OTmtsp1wOExVDFxuFyZTTdb4Lm+MsJ74GXlqipmUlPgAo6IqeJI99W6/vnYP8Ms+Zh5fnzgv3uoKE4uCvfjJYEcT303nEg6HKS4uJisrC6u14Yd5qjRzvcfRarOR3q9fWwyxQ/bb0D6h4XOqdkxNObatoaExn+x3wOGwY+0z0LDNpoKV+rP52urnU992ax8OaOi4tveYGrPdrvD7097nbE8hx1UIIYQQovtq0Z2akpIShg8fjsVinOFRy2q1kp+fz+bNm1uyOyFEF6EAT26owmi6kity7VyUY5NAXgdxmlUGJ5vZXhF/o2yTwTyGQoj20xHXVCaTif79+3P//fdjMpn49a9/zQsvvMCPf/xjPJ6am7GVlZWG61ZV1QScavvVvj4+464x/Ruzj9rMvIa0apmvQAyTyVQX0NxdZfz5OCzdhtkcXyJagQYDoQ21/+BUJ5vKo/xrbyChbeYGP5P7uzklueHzoyuwWq0n/Xn5grF6j5OqKm1W1q0j9tvQPqHhc+bEMTXm2LaGhsZ8st+BiKYzb4ffsO2uoS48DYy/rX4+J/sZNHRc23tMuq5z0B+jMgxFvhgOs8LAJDP5yWbcFrVNx9TcMTe03/Y6Z3saOa5CCCGEEN1PiwJ5bre70WUbjh49isvlasnuhBBdRDCm886exBuRFhUeP9e4hJpoP8PTLAmBvJ0VUYJRHbu5m9RuE6KL6ehrqosvvhiA5cuX8+Mf/7huTrvCwkLD/rXz29X2q329du3aumyAxvSvbx+6rlNYWEh2dnaHXj/qus6+qsSSnclWhZxWnrdOURSeGZ3C2qMhivxaXFswBvetqOCDy3qhKvI5LURPUxqMsaksypbyCE9+U53QblJgYh8bPxriYmQ98yELIYQQQgghuq4W3YE444wzKCoq4sMPP2yw30cffcTBgwc544wzWrI7IUQXseRQCINkPO4c6iLP0/VKtnU3ZxjMkxfVYVuFZOUJ0VE6+prqyJEjwHeZNIMGDSI7O5s1a9bg88WXSQ4Gg6xcuZLs7Oy4eXLGjBkDwJIlSxK2X7ustg/A2LFj6+2/bt06Kisr4/p3hGNBDd+JE9cBgzxmlDYIqKXaVJ67MNWwbVVxmH/sMC5ZLURnUhnWWF0c4s0CPy/u9PG3bT5e3Olj8cEgiw4GiZxY31vUqyKk8e+9Af6+3c+ao2GqI8bHLqbDwoMhblpcxuUfHeNAdf0lSoUQQgghhBBdT4sCebfddhu6rnPXXXfx5z//mUAgPgMnGAwyd+5c7r77bhRF4fbbb2/RYIUQnZ8/qrH6aGLZTJMCPzv95OXRRNsbXs+T2l+VSLlTITpKe1xTbdy40bCMZXl5Ob/97W8BuOSSSwDq9lFdXc2TTz4Z1//pp5+moqKC22+/PS6Ydeutt2I2m3nqqafi9rNt2zZee+01Bg4cyLhx4+qW5+fnM3r0aJYtW8bChQvrlkciEWbOnAnAtGnTmvw+W9O+6sRsPID+bpPh8tYwPsfO3UONsxB/85WXg3KDXjRSdUSjNBgz/FMd0U6+gSY64o9xx+fl/GWrjy8OhymsinHYr1EW0jjs11h3LMLPVlQyd4uPtUfDEtBrQDims/RwiL9v9yVUUTiZ3d4Yr+wO8MmBIGGjOvdCCCGEEEKILqdFqTHXX3897733Hu+++y6PPvooTzzxBP379ycrK4vi4mL27duH3+9H13WmTJnCdddd11rjFkJ0UutKIhjdGxqRbiHH1XY3PkXjndXLigIJWZNrjoa5c2hHjEgI0R7XVK+88govvfQSY8eOJTc3F6fTyYEDB1i4cCHV1dVcddVV3HDDDXX9p0+fzkcffcScOXPYuHEjI0aMYPPmzSxatIjhw4czffr0uO3n5+fzyCOPMHPmTMaMGcOUKVPw+/0sWLCASCTCnDlzEuZPevrpp5k0aRK33XYbV199NdnZ2SxevJgtW7Ywbdq0uMBfR9hblXgDXVUg19222eWPnu3howNB9p8QSKyK6PzqSy//vDitTfcvuodQTOf5bcZZnHcNdeFupQqM4ZjOsiMh1pVEDCsynCgQ0/msKMRXJWEu62dnoFRriLOxNMxdS8ubHMA70YbSCId8Ma4b6CDZ1rqlgIUQQgghhBDtq8XfmubNm8fvf/97nnvuOaqqqti6dStbt26ta09KSuLee+/lwQcfbOmuhBCdnKbrbCwzLs84NtvazqMR9Um2qgxNNbO1PP4G0ZqjYebv9OGNaHgsKrcNlnlNhWhPbX1NNWXKFLxeL1999RWrVq3C7/eTmprK+eefz0033cR1110Xl2Hncrl4//33mT17Nu+++y7Lly8nKyuLe+65h4cffthw7roHH3yQ3Nxc5s6dy7x587BYLIwaNYoZM2YwcuTIhP5DhgxhyZIlPP744yxevBifz0deXh6zZ8/mzjvvbNb7bC0xXeeAQUbesFRzm88n6rao/HF0CtcuLE1o+9feAF8UBbkox96mYxCiMarCGm8UBjgWbHqGX1VE543CAOdlWrmwd+e4TtR1nVCsJtjoD2usL42SbNNw2lWSrQppNpVUm9ompXUjms4zG6t4ckMVBhV9m6UkqPHCTj/XDrTTt40fQBBCCCGEEEK0nRZfzZtMJh555BHuu+8+Vq1axa5du6iursbtdjN48GDOP/98nE5na4xVCNHJ7auKGc7dke8xkeWQbLzO5LxMa0Ig70B1jAO+KKAArV9ySwjRsLa+prrgggu44IILmrROcnIys2bNYtasWY1eZ+rUqUydOrXR/fPz83nhhReaNK72cNgXI2zwUTg6y9Yu+5/Qx87N+U5e3e1PaHt4TSXLptiwqG0bUBSiIaXBGG8UBPDWM29bY605GuaQL8aN+U7S7e13vVjsj7G2JMzq4hCLDoYoDWp4I1pcZYn5BaGE9dxmhUHJZoakmDk91cLRQIwMe8uCexuOhfn5ygo2lDY8X7FJge/1s6EqCslWlVBM57A/xjelEarq+TkEYjqvFwS4aoCj2eMTQgghhBBCdKxWeyzP6XQyceJEJk6c2FqbFEJ0MfVl441I7xxPWYvvjMq08Y8diTeH91fH2rxknBCiYXJN1TnUNz/e+VlWtrWw5F1jPX6uhw/3B6gMx9+g314R5fltPu493d0u4xAdpyyksa08wmF/jNKQhoqC26KQYlO5tK+tXQNfxyvyxXirMECggTnYFCDDrmI1KZSFNPwNpJkd9MW49pNS3pyUzpCUVqr5eYKIpvNFUYiFB4N8eihIgdf4d/xkqqM635RG+KY0AtTMZ+oyKwz0mBjkMTPA3fis3ZJAjD98U8XftvtoaMpABTgz3cKY3lbuG+Zm3nHXcHkeMxdkWVlXEmHp4ZBhNl9Uh3f2BDg/08pdp8nnhhBCCCGEEF1Nk+/W3nrrraxYsYL7778/YW4UI3/84x/54x//yPjx4/nnP//ZnDEKIbqAqKazuSzxxqbDBAOSWn6TSXIOWtf5mcbB1f1VEsgTor3INVXntrcq8Sa/WYGRvSztFsjrZTcx4ywPD6+pTGh7Yr2XiTlWMhwmbCYFt6X958CqjmiE6gnkdNSYugtfRGNVcZinN1YZzj0M8HlRiFEZVn6Qb+WcdjzUXxSFeK3AX++4TAqMyrQyspel7hzQdZ391TG2V0TrzTo74Isx6f0S5o1P45K+rVc69uuSMC/t8vHvvUHKQm1TccAXrbkO3lwWRQH6uExous5l/RyclmqJC+zFNJ2vSsK8vSfAizv9DQZDoSYYekWunSxn/dfTqqJwbqaV/GQznxeF2FmZ+BmlAw+tqSSs6fxsWFJz36oQQgghhBCiAzTpbu369ev58MMPOf3007nvvvsatc59993HW2+9xbvvvsuGDRsYMWJEc8YphOjklh0O4TN4BPj0NAumVij95bYodfO3ZUuZzhYbkGTCZVYSfmb7qqOMpX3KxgnRk8k1VecW03WO+BMDeX1cNUGz9vTjIS5e2OlLKIdcHdH5yRflXNHfwV1DXbjbJompQaGYzvPbfIZtHTWm7mDDsTCfFYUMS7ueaG1JmLUlYU5z25jtiHBhv7adO/H1Aj/3Liuvdw63UzwmLsqxk26PjywqikL/JDO/OTuJn62o5LOiEEbxK29EZ+riUv7n3GR+epqr2eUqQzGdf+0N8PzWatYda7hcZWvTqckw/P031fz+m2rMCvRzm0ixqfgjOgd9McNr5hMp1GQAj86yYm7ktXSqTeXVianctLicXV7jBw5+9aWX0qDGr8/2tMlcf0IIIYQQQojW16RnN998800UReHBBx9s9EW/qqr853/+J7qu8/rrrzdrkEKIzu/tPQHD5Wektd5dPG9EozKsUx2V+dtaquaGWmJAtMivEWmotpMQolXINVXndiyoGwYq+rnb/0ESs6rw5Pkphm2by6Mc9DWvPKDofGK6zsIDQT452Lgg3vG2Vpv4/mIvv1xTUW+WZEv9aXMVdy+tP4jXx2Xi5YlpCUG84ymKwtkZVqYNdpJsNf7s03T45dpK7vi8nMomHogiX4z/+drL8DePcPfS8nYP4hmJ6rCnKsb6YxF2VEYbFcQb5DFx2ylOxmXbGh3Eq+W2qFw90M5Z6fVfgz+zqZrpKyuIyTWfEEIIIYQQXUKTMvJWrVqFzWZj8uTJTdrJpEmTsNlsrFq1qknrCSG6hoim896+xEBekqVmvpDqjr+HIgz0d5sSMjw0HY74Y/Sq5yZcbVakx6Jy22BXewxTiG5Jrqk6tyMB4+BBdgOl7drS2N42vt/fznv7ggltnx4M8puzpUxeVxfRdN7eEzAs6doUc7f6WHo4xP+NTyOjgYBaU+i6zn9/5eV/N1fX2yffY+aqAXaSrY3bZ6bDxLTBTt7eE+RQPcHof+0NsO5YmJnnJnNV//ozDXVdZ3VxiDcKA7y/L2iY6XcyFhV62VVSbSoei4rLomBBY1KOBbdVBZOF8pBGcSBGgTfKtvKoYfnKlrKqcP8ZSfxgsJMXdibOZdxYqqJwaV8bDrPCyuKwYZ8Xd/opD2k8Py4NRyPn9BNCCCGEEEJ0jCYF8vbs2UNubi4Oh6NJO3E4HAwYMIA9e/Y0aT0hRNfwTWmEinDiXZMR6RZMigLoMsddJ5RbT2bJvuoYw+rJpKzNigTJihSiJeSaqnM77O9cgTyAR0Yk8fGBYMK8ZEcCGv/aE+TaPONzSeaq6/xims6/GhHEs6pgURX8UZ2GYlVbyqOMf/covzzLg67rLSqfGNF07ltRwau76w8qDU+z8L1+NtQm7sdpVrlpkINPDgTZXG4cFDtQHeMHn5VxToaF7/d3UBqM4baohGM65WGNvVUxdlZGKQ027bok3aYysY+NC7NtnJpiZvHBYMJxikajTO5jJd1hwm5PDCSWhzQWHgjwl60+CrxRvJGWZbddmWvnN+d4yE+2UBpseaatoihcmF0TzPv0UMiwz3v7glzy/lFeuDiN/GSphSuEEEIIIURn1aRAns/nIympeU/8ut1uAgHj0ntCiK5t2WHjmwNnpH/3ESNz3HU+OS4TZoWEElmF9cypIoRoPXJN1bkZZeSl2pQOzVrp7TQxOsvKF4cTs2t+v7GKIn8Mq8H8fTJXXecW03Q+2B+ksIEg3qkpZsZkWellV1EUhUBUZ1tFhB0VUfZXG68XjMF/f+VlkMfEZf3suJoRzC0LxvjRF+V8XmR8nQdwfqaVcdnWZgcLzarC5bl20u1hw3O71lclEb4qaVmJB49V4bqBDq7Lc3JBprVuDufSYIxPmzH+VJvKJX3tFFbF0HWd0pBGoTdGoTfKAV+MxlStdJsVruhvZ/rwJE5LbZtf1HMyrDhMCh/uDxo+hlUT+C3hlyM93DnEZfg5IoQQQgghhOhYTQrkpaSkUFZW1qwdlZWV4fF4mrWuEKJzW34k8QaPSYG8JDOh4+4Y1GZzJVkkm6szsKgKeR4TOyvjbwIe9mtUn5jyIYRoVXJN1Xn5IjqlocQ78B2ZjVfrnAyrYRb80YDGmqNhLsy2ddDIRHM9s6mabRXGD9BYVHjq/GQOnZAh6jArjOxlZc7oFF4vCDB7g5f6ErgKvDH+scPPZf3sDEpu/Fe/b0rDTFtSxr56AoUAE/vYOCfD2uht1kdRFM7PsnH7YBcPra6kLNS61yBDUszcNdTN1EGONstOVRSFXnYTvewmRmVaCcV0RvaysKcqxpbyCOXBmmtgs1ozl2A/t4kxvW2M7W3D1g6Bs9PTLNjNCu/vCxieK9VRnf9aW8m87dX8aIibawc64j7zdF3nWFBjZ2WUXZVRdlZG2FURZU9VjLCmY1HBY1WxqDDAbSY3yfRtVQ4hhBBCCCFEa2hSIC83N5cNGzZQWlpKenp6o9c7duwYe/fuZcSIEU0dnxCik4toOqsN5t7o6zJhNSmEGvM4sugwp6ZYEgJ5QJvM+yKE+I5cU3Vem+sJqnSGQJ5ZVbg4x8Y7exPnylt7NMyZ6RY8jZyjTHS8D/YFmLvVZ9jmMClMHeRgcj8783YYl7W0mRTuPyOJi7MUfvJ5Obv9xj97X1TnrT0BTvGYubiPjVRb/edIIKrz5Iaa+fDqm2vOosL3+tlbPYPs4hwby6ZkcucXZfXO69ZYqgKX9bNz11B3izIGm8tmUhjT28ZVAzr+c6PWII+ZFy9O486l5d+WSU9U4I3xX2sr+a+1laTbVLKcKlENjgZihmX049VcT649GiHJojChj41Tk83tfuyFEEIIIYTojpr0TX/s2LHous68efOatJN58+ah6zrjxo1r0npCiM5vw7EIvhNrMwJ5ns5z40LU79R6ns7fUc+NbCFE65Brqs5rU7lxBlJnCOQBnJJspp8rcSxRHb6op9S16HwKKqP8x7JywzarClMHOejdyHNuSLKZf44IctepifO4HW+XN8rftvl4Z0+ARQeDdfOwRTSdDcfCzPzay7A3jvDMpvqDeC6zwt/GpbZZGcg+LhPvX9aLuRemku1selC6l13lF2e4+eb6LF6emM5FObZOG0iqjmiUBmOGf+o7/i11doaVJVdmcnrqyZ/nLQ1pbC2PsrMy2oggXryqiM6/9wZ5szAgVR6EEEIIIYRoBU36dvTDH/4QVVV5+umnWbVqVaPWWblyJU8//TRms5lp06Y1a5BCiM5rmUFZTYA8T5MSfkU7MLqNlWZXGWwQzNtVGSUq2ZRCtBm5puq8jAJ5qgJZjs6R6aYoChP7GJfQ3FoepchXfylE0Tn4Ihq3f1aKN5L4/6xJgevyGh/Eq2VT4bcjXbx1aTqZDZyrOjVZ9z9dVsGgV4/Q65+HyHqxiPHvlfCHb6oobaCsZR+niQ8u69XmJVxVReHmfCdfXZvF7POSOTej4aChRa3J5vvruFS2TO3No2cn08/d+a9DQzGd57f5DP/oettdgw1KNrP4ykymDXa22T5q7amK8couP8V++VwSQgghhBCiJZp0R2LgwIH89Kc/JRgMcvXVVzN79ux653cpKyvjd7/7Hddeey3hcJg777yTvLy8Vhm0EKLzWG7w9L9ZwTBbQHQst0Vh/k4fz22p4p3C78p0Teqb+AR/MFZTpk0I0TbkmqrzMiqtmWlXMaudJ6sny2lieJpxoGJJUbBNgwAdTYF6s5hKg7FOn/2j6zr3r6pga7lx5vvEPjZyWxCEuqSvnZVXZzK5X8PZebWiOjTmuZ0Lsqx8dlUGI3q1fE68xnJZVO4+zc2iKzPZdEMWfxqTwoQcG+dnWhnb28rl/ezcku/gvmFu/n5RKjcOcrbLfHPdgcOs8L9jUnn/sl4MS2ub7Mpa5WGdW5eUcUSCeUIIIYQQQjRbk78l/va3v2Xv3r188MEHzJ49mz/84Q8MGTKEAQMG4HK58Pl87N27l+3btxOLxdB1ncsvv5yZM2c2e5Cvv/46q1atYsOGDWzdupVwOMyf//xnbr311oS+TzzxBLNnzzbcjs1mo7i42LDtzTffZO7cuWzfvh2LxcKoUaOYMWMGZ511lmH/goICHn/8cZYtW4bP5yMvL48f/vCH/OQnP0FVO8cT20K0tYims9og2NM/qWZ+PNH5eCMalWGdJMt3Nzov7WvnT1uqE/p+fCDI6N5t+9S9ED1ZR1xTiYaVBDSOBBKjGtmd8OGUcdk2tldEOTFudcinsb0iytA2Kn3Y0SKaXu+ccQB3DXXh7sRv/f+2+3ijIGDYNizVzIj0lg++l93EaxPTeG5LNY9/7SXYgviJWYGfn5HEQ2cmdei1XT+3mctyFQ7Uk3FaG+A1YjMpuC3y/czI2N42vvh+Bm/tCfDSTh/LjzT+Ia4Mu0p+splUm0ogqvNVSZgqgyxTqMnMu3bhMT69MhOHWb4jCCGEEEII0VRNDuSpqsr8+fN59tln+eMf/0hZWRmbN29m8+bNKIoS9wRwamoqP//5z7nvvvtaNMiZM2dy4MAB0tPTycrK4sCBAydd5+abbyY3Nzdumdls/HafeuopHn/8cfr27csdd9yBz+fj7bffZvLkySxYsIALL7wwrv/27duZNGkSgUCAa665huzsbBYtWsRDDz3Eli1bmDNnTvPfrBBdyNclYfwG8+OdUs+8ayeSr/GdwwVZVpIsSsLNl3f2BvjNOR7UTjq3jBBdXUdcU4mGba1nftDejs4XyHNbVM7PtLLM4Mb750Uh8pPNWDpRFqGAL4+G+eXaSsO2TLvKpH72VpvPTVEUbsp3UhzQWHY4xDelEZqaq3heppWnL0jh9DbO2GoNDQV4O3twt6OZVIUbBzm5cZCTA9VRPisKsaMiyu7KmnmwraqC06wwyGPmlBQzg5PNnJJsIdUWHxwt9ke5f1UlXxSFDOfP3loe5fGvK5k1KqWd3pkQQgghhBDdR7Prtvy///f/+PGPf8yiRYtYtWoVRUVFVFVV4Xa7ycnJYfTo0VxyySW4XK4WD/LZZ58lLy+P3NxcnnnmGR577LGTrnPLLbckBOCMFBQU8MQTT5Cfn8+nn35KcnIyAHfffTcTJ07kvvvu48svv4wLAj7wwAN4vV7eeOMNJk2aBMCvfvUrrr/+el544QWuu+46xo0b18x3K0TXUd9Tu6c0cn682lKP3ohGdie8SdpTWE0Kl/a18/ae+AyBA9Ux1h4Nc36WZOUJ0Zba85pKNGxrhXFGT0NzjnWkczOtbCiNJDyI4Y3UZMdcIJ/fnUZJIMYPPitNyKCEmvntrh7oaJPAq8OsMKmfnQuyrKwvjbCxNGIYZKllUuB7/ezcc7qb0VnWVgssis6hocxFgFSbyrTBxv/XVEc0QrGac0fT9YTtKIrC8DQLgzwmXt0d4Fgw8WSfu8XH5bkOzklp9lsQQgghhBCiR2rRLOBOp5MpU6YwZcqU1hqPofHjx7fZtl9++WWi0Si/+MUv6oJ4AEOHDuWmm25i3rx5LF26lAkTJgCwe/duVq5cyYUXXlgXxAOwWCw8+uijfPHFF7z44osSyBM9wvIjifPjmRQY6DE1uoyTUalH0f6uG+hICOQBvFkYkECeEO2gva6pRMOMAnkK0MveOQN5FlVhfI6N9/YFE9pWF4cZ3gUyqXqCqKbz4y/KKfIbX+tc2d+RkN3U2pKsKuOybVzY28qxoEaex0yRP0YkBhrQ26FyToaVkRlWkq2d83wXLdeS0rShmM7z23z1rvujU50AOM0qNw1y8OruAKWh+HNeB+5ZVs6S7yUbbEEIIYQQQghRnxYF8jqzVatW8fXXX6OqKoMHD2b8+PHYbIk3o5cvXw5QF6g73oQJE5g3bx4rVqyoa2+o/9lnn01ycjIrVqxozbciRKcUjumsMZgfL8dpwqIqBGP1P+19MvLsd/u7tK+dFKtCRfiE8pp7AvzuvGQpzyaE6BG2GZTWTLOpmDvxZ+DQFDMHqi1sKI3ELQ9rNSU2HzgjqYNG1jIVIY2DvhhH/DGOBjR8UQ1fROfZzdXoOthMkGJTSbOp5DhN9HOb8HTSANQv11Sy9HDiw08A957uatf52xRFIcNh4uZ8J+l2qYYg2obLonL1QDv/3OHnxK8E+6tjPLc9wM0pHTI0IYQQQgghuqRuG8ibNWtW3L979+7N3Llzufjii+OWFxQU4Ha7ycrKStjGoEGD6voc3x8gLy8vob+iKOTl5bF+/Xr8fj9Op7PBMQaDiU9Pi64rHA7H/d3drS2JGM6P19epoMU0tKiGpqpoUY1oVEOLmRNe19futJt5cZuXyrBGjsuEFo01e1ut2R7TajI1YloMLap06Fha0n78ax0IhULous6V/azML4i/0VgW0vhkbxWX5NSU14pFY0SjGjFVrVuvu+hpv8M9TSQSwW63d/QwRCcW0XR2ehMz8jI6aVnNWoqi8MsRbm78tDyhbUt5lDVHw1ye6+iAkTXdlrIIbxX6eX9fkF1e4/kK0Wr+3wnEoCIcY29VjK+pCWKm2VR8EY1bTnFxWmrnyEb8+7Zq/rbdOItpQo6N6cPc/F8DGVJCdFW97CbGZdv4rCgxiP3X7QEuOxv6dcC4hBBCCCGE6Iq6XSBv+PDhzJ07lzFjxpCZmUlRURELFizg6aef5uabb2bRokUMHz68rr/X6yUjI8NwW0lJSXV9ju8PxJXhrG+dkwXyioqKiMUaWX9QdBnFxcUdPYR28dEBM2BNWJ5OkOpqjeqIhhJWqY5oeP0RqrElvG6ovSqiUeqPoIZP3re92gPfTmwT8Ac7fCwtaT/+tabpFBWVE41GuchtYT6JNz7nby3n1FgYs9lMVZUFbzCKyW6uW6+76Sm/wz2NyWSq+z9aCCO7K6OEDSofdtb58Y43opeV01LNbC1P/Ez+76+8XNrX3mkzqyvDGq/v9vPCTh9bDMbfFGUhjT9t8fGnLT6GpJi5eoCD6/IcnJLcMUG99/YFeHhNpWFbX5eJv12U2s4jEqJ9nZthYVdllIO++O+8vii8eNDC7xOfjRVCCCGEEEIY6HaBvCuvvDLu33l5efznf/4nmZmZTJ8+nT/84Q+88MILHTS6eDk5OR09BNGKwuEwxcXFZGVlYbUmBri6m827vEB8GS+zAoMy3LjdFvSwhtuqooc1IhYNt9uc8Ppk7U3p2x7t0WAE/BEcTjt6VOnUY23scdWBnBwHuq7TF/BsLcMbic+yW1puJi07E7dFJckbIGbTSLKqdet1Fz3td7iniUQiJ+8kerQt5cbnSEYXKT84PsdmGIzcVRnlz5ur+XknK7G5uSzC/22v5o2CAD6DDP+W2l4R5XcbqvjdhirOSLNwfZ6DawY66Odun68/Cw8E+dHnZQllBQEcJoX5E9JIt5sobeykwkJ0QYqiMKGPjRd3JmadvnHYzIMBjf6SLC+EEEIIIcRJdbtAXn1uvvlmfvGLX7BmzZq45R6PJy7j7nhVVVV1fY7vD1BZafx0be06jXnqX0p8dU9Wq7Xb/2xDMZ2vjiU+Nd/PbcJutaCaVFSzgmpSUM0KZk2tW3b865O1N6Vve7Sb1JqbuSbV1OFjaa3jCsTNH3pmuoVlR+JLS/qj8NlRnevzbJjMYcyaismsGM472h30hN9hIUSiLWX1BPK6QEYeQJJFZWxvG0sMytg9scHL5bl2Bqd0bLlJTYeFh8L8ZUcVK4vbr4zxxrIIG8si/PorL+dkWJjU186kvnbOTLegKK2fqfjOHj8/XVZOxCDDE+Av41IZ0avzPjBSHdEINTDXcQumQRY9ULbTxKV9bSw6GP/ZFNIU/rQ1wO/HNFzFRgghhBBCCNGDAnlWqxW3243fH/804KBBg1i7dm1dFsbxaufDq50r7/jXhYWFCfvQdZ3CwkKys7NxuVyt/RaE6DS+PhYmYHAXJ8/TYz5Sui2jQB7Am4UBrs+TGy1CiO5rq0FGnlUFj6VzlqQ0cnaGhU1lEUqC8RGkUAzuXV7Ox5dnYGqnEpsK1GWbhWI6/9oT4e/b3BRWVzV5W26zQrpdxWVROC3FzNaKKNURnbKgRnUTs/m+KonwVUmEWeur6O1QmdjXztjeNsb0tuIyt+zYxDSd2d9U8eSG+t/jjLOSmDKgc89ZGIrpPL/NeF4/gB+dKtcDomnuH+5m8cEQJ/62vrYnxK9HaSRZusYDE0IIIYQQQnSUHnPXvaCggIqKCoYNGxa3fMyYMaxdu5YlS5Zw8803x7UtWbKkrk+tsWPH1rXdf//9cf3XrVtHZWUll156aVu8BSE6jWWHE5/2B8hL6hrlx0T9sp0q6TaV0lD8TeBPDwal/JcQolszmp8t02Fqk4wtI8cHvow0JgtKVRQm97Mzf1diGbsvSyL8eUs19w1vnxKbEU3nr9t8bDgWYc3RcJPKZ9pNkOs2k59sZoDbRJL1u5v8PzrVybwd372/yrDG/uoYuyqjFHqjTcoWOxLQeHmXn5e/PV59XCqpVpW+bhO5bjMpVqXRP/8vj4Z5cHUF35TWX8b37qEu/vPMzlXiVIj2cGqKhevyHLxVGIhbXhXReaPAz4+HuDtoZEIIIYQQQnQN3SqQV1VVxb59+xKCdRUVFfzsZz8D4Prrr49ru/XWW3n22Wd56qmnuPzyy0lOTgZg27ZtvPbaawwcOJBx48bV9c/Pz2f06NEsW7aMhQsXMmnSJKBm7p2ZM2cCMG3atDZ7j0J0BssNMrbspprSmr7E+6CiC1EUhdNSzQlZeVEd/r032EGjEkKItlUR0jjoSwyitWdZzYimxwWoTtTYLKg+LhPnZFj4qiQxoPTbdV4uyLJxbmbblnWMajov7/Lz/FZfkzLmzs+0cvtgJ2N7W3lld+DkKwDJVpXhaSrD0yyEYjq5bhMLD4b49FCw3tKW9Tnk0zjk09hcHgVC2E2Q5TCR5VDp7VA5q5eVTIcJh1khFNPZVxVlfWmEtwr9hsf7eD8c7OR35yW3W2BYiM7mZ6e7EwJ5AH/f5uNHp7rkd0MIIYQQQogGdIlA3osvvsiqVasA2Lp1KwAvvfQSy5cvB+CKK67gyiuvpKysjLFjx3LWWWdx2mmnkZGRQVFREYsXL6asrIyLL76Ye+65J27b+fn5PPLII8ycOZMxY8YwZcoU/H4/CxYsIBKJMGfOHMzm+MP09NNPM2nSJG677TauvvpqsrOzWbx4MVu2bGHatGlxgT8huptQTGft0cSMvFGZNsyqAglFc0RXMzS1vvKafr7fX+aOE0J0P5VhjUl9bWwui1Dk/y76k2nvmuXexmXbKKiMUh6O/z85qsMdn5ex9KoM0uytn0Wv6TqbyiKsOBKmKtK46wGXWWHqIAc/GuJmeFrNHH7NzQC3mRSmDKjZVkVI4919ARYUBlh2JITWjMuTYAz2VcfYVx1jbYnx/NiNcfdQF09IEE/0cCN6WTk3w8KXJwS9t1VEWX4kzIXZ3XPuZSGEEEIIIVpDlwjkrVq1ildffTVu2erVq1m9ejUAubm5XHnllaSmpnLnnXfy5Zdf8vHHH1NZWYnT6eT0009n6tSpTJs2DZMp8abFgw8+SG5uLnPnzmXevHlYLBZGjRrFjBkzGDlyZEL/IUOGsGTJEh5//HEWL16Mz+cjLy+P2bNnc+edd7bNQRCik/iqJIzR/bWxvdv26X7RflJtKv1cJg6ckJ2yqjjMuGwrNQXghBCi++ifZOaNS3sRDAYpqIwwZ1uQsrBCblKXuFROYFEVLs+187JBVttBX4yffFHO65emY2nF+fL2VUVZcijE0WDj0uBynCr3DkvitlOcJFtbP2CaYlOZNtjFtMEuiv0x/r03wCcHgyw7HCLcxEy95jIr8IcLUvjhqTJ3thAAdw5182VJecLyP2+p4rRU489bm0nBLXPoCSGEEEKIHq5L3J2YO3cuc+fOPWk/j8fD73//+2btY+rUqUydOrXR/fPz83nhhReatS8hurLlR4znxxvb28aG0sQsLtE1nZluSQjkAWwpi3L6txkTQgjRHaVYax5mGJjcJS6T69XXbWZ0lpWVxYn/Ny8pCvGz5eXMvTAVtYVZYmUhjc8PhdjlbVxt7Qy7wvlZNn5/fjK9ne1zjLOcJu46zc1dp7nxRTS+OBxi4YEgnxWF2FfdNvO/npJs5n/HpHBBlmQZCVFrygAH/7W2kpITAv4LD4T446YqnObEgN1dQ1245dJTCCGEEEL0cF37DoUQot0tP5wYyHOYFM7OsEogrxsZnmbm/f2Jy7eURySQJ4QQXcSY3lZ0ajKqT/R6QYBUm8qsUcnNCuYdC8Z4fJ2Xl3b5G1W2MtuhMMIdYWimG4vF0qrZgE3hsqhcnuvg8lwHAAero6wsDrPiSIilh0PsqWpZYM9pVrjnNBc/GuLCZlIoDcYko0iIb9lMCj8Y7OIPG6vilmvAjoooZ/WSCh9CCCGEEEIYkUCeEKLRglGdtSWJNwNHZVqxmaTcYneS4zKRl2Si8IQbmnurYvgiGsnW1p9bSQghROtSFYU/XpDMlE9KORJIrCf5l60+jgY0/jw2FYe5cf+P+6Mac7f4+OOmqkbNg9fboTI220auQ6fKG+5088T1dZuZ6jYzdZCT0mCMpzdWcaA6xhF/jOKAxtGARiB28vd5ZrqF3g6VISkWTKrCCzv9dW2SUSTEd249xZkQyAPYXBaRQJ4QQgghhBD1kECeEKLRvjoWJiTz43UrDd1OHZJiTgjk6cCuyig5LgnkCSFEV9DLYeK1S9K58qNjVEcTA1Jv7wmwqzLKM6NTOCej/v/PvWGNV3b7mbOpisP+k08yNyDJxFnpFk5JNqMoCtFo40pvdjS3RWVoqsrQ1JrIm67rVEV0zsmw4o/qHA1oRHUdm6qQZFUYmmLh9DQLUU3n+W2+Dh696EwUoNRoYulvNSI+3G0cfyw8VoWz0i2sL43E9Snya5SHNFJtkr0qhBBCCCHEiSSQJ4RoNKOymgAXZsv8L12V26Iwf6cPb0Qj2xEfnDs9zcKHBxJ/5jsqo1yUIz9zIYToKkb0sjJ/Yho3LColYhCD21QW4ZL3S/h+fzvX5zk5M91Cqk2lJBBjc1mUTw4GeX9foFEZeHYTjOltY87oZF7aFWiDd9O+FEXBY1UYn2Mj3V7/QywNBWxEzxTRdObt8Nfb/qNTne04msZpKPjYksDjiccirZ5nBraURxjbW64xhRBCCCGEOJEE8oQQjfZ5kfH8eCOlDE6X5o1oVIZ1kizxd3dTbSp9nCqHTsi82F8Vw2+Q1SGEEKLzGp9j5+8XpfHjz8uo7yP8vX1B3tsXbNb2FWBkLwtjettwmJUOmwNPNE5bBWxE19ZQ8LE1A4+nJptYcjiMfkJtiK1lEcZkWTtdCV4hhBBCCCE6mgTyhBCNUhHSDOfHOz/LilXmx+u2Tk+zcMgfH8DVgJ0VXaNEmhBCiO9MGeAgdXIvbl9SSmW49aI1g5PNXJRtI80uJfG6ivYK2AhhxGFWyLXr7AvGf4coD+sUBzR6O6WEuxBCCCGEEMeTb9tCCEPzd/qYv/O7uV4+LwqhGdzzu6SvvR1HJdrbsFTj5z12VEYMlwshhOjcxmXbWHxlBoOTW/483zkZFm47xck1Ax0SxBNCNEm+y3iuzZ2V8rCYEEIIIYQQJ5Jv3EIIQ96Ihve4iXQWHTIutXVJH5nHojvr5TAxyJP4VPTOiihRo8iuEEKITu+UZAvLpmTy6EgPjmZk1V+QZeXViWm8NjGNPi7JnDmZ2jKWRn+kjKXoqXLtOmaDj58dUvVBCCGEEEKIBFJaUwhxUrqu8+nBxEBeP7epVZ7oF53b5H52ntvii1sWiMHao2FG95ZArhBCdEU2k8Ivzkzipnwn/7e9mgWFAfZVG8+ZBjX/53+vr51bT3Ey4tu5ceubY03EkzKWQiQyqzAwSWWXNz4zryykcSwYo5ddHhIQQgghhBCiltyBF0Kc1ObyKEcCieVvLu1jl8noe4DJfRMDeQALDwYlkCeEEF1cH5eJX5+dzKMjPWwqi7CtIkqxP0Z5SCPdrtLPbWZIipnByWb5P18I0apO8ZgSAnlQU/mhV28J5AkhhBBCCFFLAnlCiJNabJCNBzCxj435O314IxrZDvmy3V1dkGUjyaJQFYmv//XJgSC/OSe5g0YlhBCiNSmKwhnpVs5It3b0UIQQPURekgmLGiFyQixvR2VUHhYTQgghhBDiODJHnhDipBYaBPIsKozLseGNaFSGdaqjxhPWi67PalK4OCfxZsq2iij7qmQeEyGEEEII0XQ2k8IFWYkPDxwNaFSE5LuFEEIIIYQQtSSQJ4Ro0BF/jNXF4YTlNVla8hHSU0zuZzdcbhTkFUII0Xko1MxlV9+f6hNTYYQQoh1N6mt8jbnbKw+LCSGEEEIIUUtKawohGvTvvQF0g+WT+kq5m57k0npusiw8EOTOoe52Ho0QQojGimg683b4622/a6gLt6UdByREO6sNZtcnZnShK9rNxBwbvzJYXuCNck6GlPoVQgghhBACJCNPCHES7+wJGC6/eoCjnUciOlKmw8TZvRLv9C49EsIn2RxCdAlFRUU899xzXHPNNQwbNoyMjAwGDx7M7bffzldffWW4jtfrZcaMGQwbNozMzEyGDRvGjBkz8Hq99e7nzTffZMKECeTk5NC/f39uuOEG1q9fX2//goICfvjDHzJo0CB69+7N6NGjef7559E0+WwRQrRcRNN5fpuv3j+6LpG8jpRmV8lxJt6WOFAdIyxRViGEEEIIIQAJ5AkhGlAR0lh9NLGsZn+3ib5uSejtaSYZlNcMxWDp4VAHjEYI0VTPP/88M2bMYO/evYwfP56f/exnnH/++Xz44YdMmjSJd955J66/z+fjiiuu4LnnnuOUU07hnnvuYciQITz33HNcccUV+Hy+hH089dRT3HnnnRw9epQ77riDa665hjVr1jB58mSWLVuW0H/79u1cfPHFfPDBB0ycOJG7774bgIceeoj777+/bQ6EEEKITmWQJ/F7RUyHvTIXsxBCCCGEEICU1hRCNGBzWcRw+fA0qcHVE03ua+eJ9VUJyz85EOSyXMnQFKKzGzlyJB9++CGjR4+OW75y5UqmTJnCAw88wOWXX47NVlM6ec6cOWzatInp06fz2GOP1fWfNWsWTz75JHPmzGHGjBl1ywsKCnjiiSfIz8/n008/JTk5GYC7776biRMnct999/Hll19iNn93+fnAAw/g9Xp54403mDRpEgC/+tWvuP7663nhhRe47rrrGDduXJsdEyG6stqSkZpmxtkrhyrNjO+4EpJdLZlJSmD2XIM8ZpYdSXx4sLCq/vNBCCGEEEKInkQy8oQQ9dpYTyBvWJo8A9ATnZluIcmiJCxfeDAoZamE6AKuuuqqhCAewOjRo7nwwgspLy9n69atAOi6zksvvYTb7eahhx6K6//AAw+QkpLC/Pnz4373X375ZaLRKL/4xS/qgngAQ4cO5aabbmLPnj0sXbq0bvnu3btZuXIlF154YV0QD8BisfDoo48C8OKLL7bOmxeiG6otGfmXLV7+uK6Ev2zxdumSkVICs+fKdKi4Da4xC7xR+bkLIYQQQgiBBPKEEPUoC2kc9CXOT5TrNuGxykdHT6QoCqemJAZxi/wam+oJ+gohugaLpSbT2mQyATXZdYcPH+a8887D5XLF9bXb7YwePZqioiIKCwvrli9fvhyACRMmJGy/dtmKFSsa1f/ss88mOTk5rr8QQojuSVEU8pISrzGrIzrbKqS8phBCCCGEEJJWI4QwtKnUODAzxCCQI3qOISlmvipJPDc+ORDkjHRrB4xICNFSBw4c4PPPPycrK4vTTz8dqAnkAeTl5RmuM2jQoLp+x792u91kZWU12L9WQ/tQFIW8vDzWr1+P3+/H6XQ2+B6CwWCD7Y0VDocBE7FY/eXcdCAaNb6x3FBbR617su1qmt7s46dp5kbvt/aY1v7d0H6bst3Eddvm/Zxsu80dc2v83E88ti3db2c8j1uybnO3W3s8az4XjLXkXO3JP5/jz9natgFuhY1liesuORTk3NR6dyuOU3uuNnTOtga7PXHebCGEEEII0bbkjrwQwpBRWU0VDDOyRM8xyGPGpCTOU/PhgSD/OcLTMYMSQjRbJBLh7rvvJhQK8dhjj9Vl5Hm9XoC4EpnHS0pKiutX+zojI6NJ/Ru7j5MF8oqKihoMvjWFs1cOvmpfve26loS30tvkto5a92TbDYdsHDhWVG97Q5y9cpq839pj29B+m7PdWm31fk623eaOuTV/7ieet211znS1dVuyXXBSXFxc77otOVfl51NzzupaCt5KL2kaqJjRiC+x+dmhILckl9S7X5GooXO2pUwmU70P+QghhBBCiLYjd+SFEAl2V0Y47E8sq5nnMeE0S1nNnsxmUsh1m9hTFX/DfP2xCAeqo/Rzy38rQnQVmqZx7733snLlSn7wgx9w0003dfSQmi0nJ6dVthMOh6mKgcvtqgtqnkhRFTzJxg8uNNTWUeuebLtWm430fv3qbW9IlWZu9H5jsRi+al/dsW1ov03Z7ona6v2cbLvNHXNr/NxPPLYt3W9nPI9bsm5zt1v7cEBWVhZWq3HVgZacqz3553P8OXt8W7+KEPtOKO3/TVkMZ2Yf0m3yHeRkwuEwxcXFDZ6zQgghhBCia5I7rkKIBG/vCRguPyPd0s4jEZ3R4GRzQiAP4IP9QX56mrsDRiSEaCpd17nvvvt44403mDp1Ks8880xcu8dTc1O1srLScP2qqqq4frWvj8+4a0z/xuyjNjOvIa1a5isQw2QyYTYbXyYr0Ky2jlr3ZNtVVaXZx88XjDV5v7XH1qQq+DC+rtCVzvd+Trbd5hyLk7U1dd0Tz9u2Ome62rot2S6A1Wqt92ff3J/7ydq72jFu7romkymuLT9FY58vFNdHB1Ycg6mDpJxjYzV0zgohhBBCiK5JAnlCiATvGATyLCqclmohkpioJ7oxxWBZfrKZhQdDnFBdk/f2BSSQJ0QXoGka/+///T9efvllrr/+eubOnYuqxmc61M5pV1hYaLiN2vntavvVvl67dm1dNkBj+te3D13XKSwsJDs7G5fL1dS3KLqAiKYzb4ffsO1HpzZcSlWI9mKzWqjSVHxB49K9J5YaFy0zyGPm00OhhOULDwaZOkg+F4QQQgghRM8lgTwhRJxt5RG2VSROVD8hx4bTrFAZ1g2DO6J7clsU5u/04Y1oZDtM3y5TyXWb2Fcdf1NrVXGYY8EYvezG5eiEEB3v+CDetddey1//+lfDEpKDBg0iOzubNWvW4PP54oJpwWCQlStXkp2dHTdPzpgxY1i7di1Llizh5ptvjtvekiVL6vrUGjt2bF3b/fffH9d/3bp1VFZWcumll7b8TQshRDNFdIW/b/XWm2kmQefWlWpTSbUplIfiI6SLDwaJajpmVb6FCCGEEEKInkkKzQsh4tRXVvOagd/dqKgN7rxTaPwkvehevBGNyrBOdfS7dMzTUxNvaGk6fLQ/2J5DE0I0gaZp/OxnP+Pll1/m6quv5vnnn69/HjhF4fbbb6e6uponn3wyru3pp5+moqKC22+/HUX57qbqrbfeitls5qmnnoorl7lt2zZee+01Bg4cyLhx4+qW5+fnM3r0aJYtW8bChQvrlkciEWbOnAnAtGnTWuW9C9FSClAajNX7RzKzhGgdgzyJ15gVYZ0vS8IdMBohhBBCCCE6B8nIE0LU0XXdsKymzQSX59qZv8tXt8wb0ZDcvKbzWFRcZoWqiHGJpq7itDQLHx5ILH303r4Atw+WMnhCdEazZ8/mlVdewe12k5+fz+9///uEPldccQVnnHEGANOnT+ejjz5izpw5bNy4kREjRrB582YWLVrE8OHDmT59ety6+fn5PPLII8ycOZMxY8YwZcoU/H4/CxYsIBKJMGfOnISslqeffppJkyZx2223cfXVV5Odnc3ixYvZsmUL06ZNiwv8ibZRG6AyYjMpuC3d57m/6ohGqIGIW0PBuIZKgYJkZgnRWgZ5zHxVEklYvuhgkAuybB0wIiGEEEIIITqeBPKEEHU2lUXY7U0sqznIY+bTg5Jp1VLVEZ17I5sA+JNlWAePpmXSbCrD0yxsKou/0bLkUIiSQIwMh5TXFKKz2b9/PwDV1dX84Q9/MOyTm5tbF8hzuVy8//77zJ49m3fffZfly5eTlZXFPffcw8MPP2w4d92DDz5Ibm4uc+fOZd68eVgsFkaNGsWMGTMYOXJkQv8hQ4awZMkSHn/8cRYvXozP5yMvL4/Zs2dz5513tuK7F/VpKEB111AXbks7D6iFGgpMxnT4v+0+wzaQYJwQnUE/lwmrCuET5uVeeDDEr8/umDEJIYQQQgjR0SSQJ4SoY5SNBzWBvOPLKorm0QHVW1bzj/QOHUqrmDLAkRDIi+rwVmGA/zjd3UGjEkLUZ+7cucydO7dJ6yQnJzNr1ixmzZrV6HWmTp3K1KlTG90/Pz+fF154oUnjEqI+DQUmJVAnROdnUhUGJJnZWRn/cOHmsgiH/TGynfKwmBBCCCGE6Hm6T60cIUSL6LpuOD+eRYV8g7kqhLghz2G4/LWCmhuo83f6mL+z/swHIYQQnZvMCyeE6AgDPcbBusVSIUQIIYQQQvRQcndeCAHA+mMR9lUnlqI6NcWM1SRz4YlE/ZPMjOltZcWRcNzyb0ojbC2P4I1IFqcQoutxW03cc5oL6pkHtmvPcNo0Mi+cEKIj5CWZgcS5mBcfCspczEIIIYQQokfqEhl5r7/+Oj//+c8ZP348mZmZpKSk8PLLL9fb3+v1MmPGDIYNG0ZmZibDhg1jxowZeL3eetd58803mTBhAjk5OfTv358bbriB9evX19u/oKCAH/7whwwaNIjevXszevRonn/+eTRNblyLrunfe43Lap6R1sUmxxHt6qZBxjdxX9td/41fIYTozGz+CjI+fJHshS8b/jHpcq0nhBBtyWNV6WVPvFXxWVGIqCapwEIIIYQQoufpEoG8mTNn8s9//pMDBw6QlZXVYF+fz8cVV1zBc889xymnnMI999zDkCFDeO6557jiiivw+RLLvD311FPceeedHD16lDvuuINrrrmGNWvWMHnyZJYtW5bQf/v27Vx88cV88MEHTJw4kbvvvhuAhx56iPvvv7913rQQ7WT+Th9/3uzlFYPAi1WtycgToj5TBjiwGPxP8kaBn5jcaBFCCCGEEM2Ql5RYXtMb1ll7NGzQWwghhBBCiO6tSwTynn32WTZu3EhBQQE/+tGPGuw7Z84cNm3axPTp03nnnXf4zW9+w1tvvcVDDz3Epk2bmDNnTlz/goICnnjiCfLz81mxYgX/8z//wx//+Ec++eQTzGYz9913H9Fo/ETbDzzwAF6vl5dffpnnn3+exx57jC+++IKLLrqIF154gaVLl7b6MRCirXgjGgXeGCXBxAyD01MtWFQpqynq57GqDDUI9h4JaGwpjxqsIYQQQgghRMPy6pmje/EhmSdPCCGEEEL0PF0ikDd+/Hhyc3NP2k/XdV566SXcbjcPPfRQXNsDDzxASkoK8+fPR9e/yxJ5+eWXiUaj/OIXvyA5Oblu+dChQ7npppvYs2dPXGBu9+7drFy5kgsvvJBJkybVLbdYLDz66KMAvPjii81+r0J0hB2VxgGXM9MlG0+c3NkZVsPlq4rliWkhhBBCCNF0fV0mrAZ3KxYfTJw7TwghhBBCiO6uSwTyGqugoIDDhw9z3nnn4XLFT4Jtt9sZPXo0RUVFFBYW1i1fvnw5ABMmTEjYXu2yFStWNKr/2WefTXJyclx/IbqCnRWJgTyTUpORJ8TJDPKYSLMlZm7uq45R5IvFLZu/08dzW6qYvzOxzLEQQgghhBAAJlWhvzvxocKNZRGK/TGDNYQQQgghhOi+ul0gDyAvL8+wfdCgQXH9al+73W7Duffq61/fPhRFIS8vj8OHD+P3J843JkRnVBrUDMtqnpJsxm6WsprH81hV0p0WkixyXI6nKgojezUuK88b0agM63gjieecEEIIIYQQtfI8ifPkgZTXFEIIIYQQPU+3qpvn9XoB4kpkHi8pKSmuX+3rjIyMJvVv7D6cTmeD4w0G5QtIdxIOh+P+7goURWFzqXF5mqHJKlpMQ4tqRKMaWsyc8FpT1TZtb899nazdG4V7Ipvwlx7Cae3Dny3Dm74tVSUarQlgadFYlz6uMVUlFKo5d2LRGEM8CssOQ+iE+Nw3pREOVgboZVNQFIXYt++7dv3jSx13tK74OywaLxKJYLfbO3oYQgghhGikmnnyEr+rfLA/yPf62bGZFNyWbvVsshBCCCGEEIa6VSCvqykqKiIWk7Ig3U1xcXFHD6HRzGYzm0otQHyGmQmdPqYQ1dVRqiMaXn+EamwJr5Ww2qbt7bmvk7UD+EsPoRUfwg9Up+c1eVsWpwWfr6akZLXd16WPq8lupqioHICqKguhYJRhHjPrKuLPpagOz3xVwk9zQ5jNZqqqLHiD0br1o1Hj+Rk7Ulf6HRaNZzKZ6h62EUIIIUTn57Gq5HtM7PbGf2f+9FCQv2yt5qenuXHLTABCCCGEEKIH6FaBPI/HA0BlZaVhe1VVVVy/2tfHZ9w1pn9j9tGYm4U5OTkn7SO6jnA4THFxMVlZWVitxmUGO5vDAY2iYHnC8guyrGSlWHFbVfSwRsSi4XabE163dXt77utk7QBOv51qwOmw43a5mr4tq4orWDN/Z7PW70THNcmqkpPjACDJGyBm0/hemsrXFT5OzLF747CZh8/tRbLNVNe3dv3OlpHX1X6HReNFIpGOHoIQQgghmmhcto3d3vhpK0IxEuZhFkIIIYQQojvrVoG82jntCgsLDdtr57er7Vf7eu3atXU3bxvTv7596LpOYWEh2dnZuFyuk45XSnx1T1artcv8bBcWVhsuv3qgk7Cmo5oUVLOCWVNRTWrC67Zub899nawdQFFNdX+rZlPTt2VWMJtryv80a/1OdFxNZgWbzQaAyRzGrKn0dqkMTTWztTw+y64qojN/b4wHznDW9T1+/c6mK/0OCyGEEEJ0Zxf2tjJvR+L884VVEsgTQgghhBA9R7cqKD9o0CCys7NZs2ZNXfm6WsFgkJUrV5KdnU1eXl7d8jFjxgCwZMmShO3VLqvtAzB27Nh6+69bt47Kysq4/kJ0Zu/tCxguv6K/o51H0j48FpVkq4Lb3PYffe25r46g1LN8fLZxcO65LdX4o5phmxBCCCGEEEbOybBiNA1eobfzlWcXQgghhBCirXSrO8yKonD77bdTXV3Nk08+Gdf29NNPU1FRwe23346ifHcL+tZbb8VsNvPUU0/Flcvctm0br732GgMHDmTcuHF1y/Pz8xk9ejTLli1j4cKFdcsjkQgzZ84EYNq0aW31FoVoNceCMVYWhxOWn5dpJdtp6oARta3qiM40/0buK13Kdd5vus2+OorbojB/p493CuOfkO7rNjEgKfH8ORbUeGln4tPUQgghhBBC1MdqUujvTry2LA5oHAtIVp4QQgghhOgZukRpzRdffJFVq1YBsHXrVgBeeuklli9fDsAVV1zBlVdeCcD06dP56KOPmDNnDhs3bmTEiBFs3ryZRYsWMXz4cKZPnx637fz8fB555BFmzpzJmDFjmDJlCn6/nwULFhCJRJgzZw5mc/xhevrpp5k0aRK33XYbV199NdnZ2SxevJgtW7Ywbdq0uMCfEJ3Vh/uDaAbTk32/f/csKagDqrcMtfRozYL07rGvjuSNaOgGuXkXZFrZW5WY7fns5mruGupsj6EJIYQQQohuIs9jZrc3MWi39EiYU1NlXmMhhBBCCNH9dYlA3qpVq3j11Vfjlq1evZrVq1cDkJubWxfIc7lcvP/++8yePZt3332X5cuXk5WVxT333MPDDz9sOHfdgw8+SG5uLnPnzmXevHlYLBZGjRrFjBkzGDlyZEL/IUOGsGTJEh5//HEWL16Mz+cjLy+P2bNnc+edd7bBERCi9b2717isZkVYS8iyEu3HY1FxmRWqIl33CeN+32bl7T1h7pKDvhjflEbIT7Z00MiEEEIIIURXk5dkBkIJy78oCnHnUHf7D0gIIYQQQoh21iUCeXPnzmXu3LmN7p+cnMysWbOYNWtWo9eZOnUqU6dObXT//Px8XnjhhUb3F6IzqQhpfHE48ctwjlPFpChUy1xmHaI6onNvZBMAf7IM6+DRNJ+iKEzqa+P5bYkB4S8Oh8nzmKl/lj0hhBBCCCG+k2xTSbOplIXiv6MsPxIipumYVLmuFEIIIYQQ3Vu3miNPCNE4nxwMEjGI1Z2eJplSbUbXUbSGs+zqSnJ6y9pnTG3o9FQzvR2J/8UcC2rsrIx2wIiEEEIIIURXledJnCevIqyz7ljinN9CCCGEEEJ0N10iI08I0brqK6t5eqp8JLQmpaIM854d3Fj+CVlHdmEPB9BVFaw2ru3zORvzzqdi2AVUWZI6eqitTlUULsqx8XpB4rm2ujjMqAwJGgshhBBCiMbJ85j5qiSSsHzRwRCjMm0dMCIhhBBCCCHaj9y1F6KH8UU0Pj0UTFje26GS6TBRGdY7YFRdm8eiAhpus0p1KMypO1ZgXfMy6tEiAPof11fRNAgGyC/4kvyCL4l+9le+PGcKC0deD1Znh4y/rQxLM7PooEJZKP6cKg5o7KrsunMACiGEEEKI9tXPZcKiklBVZPGhIP810tMxgxJCCCGEEKKdSCBPiB5m8aEQQYMYypnpkiHVHLXz2qmVpSjHivGuXErGsX2NXt8cDXPB6jc5fdOnLJ70U0hrw8G2M5OiMC7bxr/2JgaOPzeYo1EIIYQQQggjZlUh122iwBv/RWb9sQglgRgZjsTSm0IIIYQQQnQXMkeeED3Me/uMy2qOkEBes+iAeft6rO/8E9u7LzUpiHc8j6+Ma9+ZhfnLpaAZTGDYRY3sZTGcK29vVYxVxRLME0IIIYQQjZOXZPwc8qKDiQ+NCSGEEEII0Z1IIE+IHiQQ1fnkQOIX3RSrQh9Xz/048FhU3Oamv/9+h7dz42v/hfWjN1DLj7XKWMwb12BZuABryN8q2+toZlXhZ8Pchm1/3FTdzqMRQgghhBBdVZ7HOJD34X4J5AkhhBBCiO6t5965F6IH+mh/gKpI4hx4g5PNKIrSASPqeNURnWn+jVzn/aZxK2gapr07ufG1/+Knrz9E//0bT7pK2GJnV+4Ivjr7+0SHnImWltFgf9OhvUx941EcwSqgJtCYbFWaFWzsDH54qotUW+L59cmBIAWV0Q4YkRBCCCGE6GpSbCq97InXw0uKQgSiMs+3EEIIIYTovmSOPCG6ofk7fXgjGh6Lym2DXXXLXy8wzvI6NaXnltXUAdVbVvOP9MR2RYuRVnqI7MM7sW3/BOe+XaixKP0bs21XEtEzzuO5UXdSojhItioMK10KwKuxfoxb/DcGHdxkuG7O4Z385M0ZLLjpce6wHkL1lqF50viTZVjz3mgHcltU7hrqZvaGqoS2v2yr5vfnp7T/oIQQQgghRJdzSrKZY8Fw3DJ/VOfzoiCX5To6aFRCCCGEEEK0LQnkCdENeSMalWEd+G6utZJAjMWHEuck62VXyXZ2zUyvE3ksKqDhNqtURWLGnSJh1H27GLPtIPaKo6T5y7AGj4GucZv6Lnosho0YuhbDEvLjqS5D1Zs2Z12VOx37mWejp2ehZfQmbHNCOP4p4ZLMgcy7biaX7lrE2E/+gjmWmJnWu3QfU19/FHXylai+b8tQGgQbu4KfDHHxzMYqwiccyld2+fmvszyk2LrHOSiEEEIIIdrOKclmVhWHE5Z/uF8CeUIIIYQQovuSQJ4QPcRbhQFiBhVnRqRbukVZzeqIzr2RTYaZa2oswpDty7F+9QbK0UMous4Yg23ktHAMut3BZxfcwvqzLufeytWopUfR+S7AWPM3xy2DA+dezivpA7n67f/B4ytL2GbGsX1oH79J9LyJLRxdx8pwmLhhkJOXd8VnhfqiOvN3+fjZsKQOGpkQQgghhOgqejtU3BaF6hOmC/joQJCYpmNSu/73GiGEEEIIIU4kgTwheoj6ymqe1at7lNWsLZGplh6tWZBeUxbz9K8+5KwVb5BUnRgka7V9W6zE8k8jes5FfJV9SUL7DyrWogT9aJ40CPjB4Yxb9qfsYfzthif48TuPklJ5NGF9tfQo5lWLCF95S5u9h/bw09PcCYE8gOe3+bjndDdqNwgoCyGEEEKItqMoCqd4zKwvjcQtPxbU+LIkzPlZtg4amRBCCCGEEG1HapkJ0QNsK4+w4YQvuwAXZFlJ7aYlDXsf3sV/vPYg4z75S5sF8Y6lZLPk4h8TuvFutFPPBKs1oY8CqOXHUEuPonrLUE5YpnjL8FhUYpk5vDft92jJqYb7UsuPYV24AEs40ORxeiwqyVYFt7ljf9bD0ywMTDIlLN9fHeOzosSyr0IIIYQQQpwoP9n4eeQP9wfbeSRCCCGEEEK0D8nIE6IH+McOn+HymwY58UWbNv9bp6frmDau4bavljd5brvGiNqdaAOH8NaIG9iaORSPzcTo0qVQ7W32No/PzgtffBXWT/+FWlWZ0E8tPsS1b8/kk5v+G0gMGhppqORoRxjT28qeqsRg5As7fEzsY++AEQkhhBBCiK6kv9uEVSVh7uUP9gd47BxPt5g2QAghhBBCiONJIE+Ibs4X0XjNoKymw6QwZYCDV3YbB/m6pHAI85rPUI8caFT3qGqmOikdj0kHVQVdB3R0q40D1nSCqplYSi/KXL041iuXSZZSvEeKSMobzMGsYehhg0kHm0gBlPJjKP7qmn873YQvu5HQx++Q7C1J6N9//0a+99b/8ObV/wWcvCyqUcnRjnRqitlwXpMP9wc5GoiR6UjM2BNCCCGEEKKWSVXI85jZXhGNW17gjbGzMsqpKd1j6gAhhBBCCCFqSSBPiG5uwZ4AXoOA05npFj471H3Kz7irSrF+8CpqWWLw63haUjKxoWfx0unXUejph8dm4r7SpQAoAT+Kv5pYeiYf9x6PN6KR7TBxOBAD4NLiz9v6bdRISub1G/+HG1/9JcnVpQnNuYVfM+Xfs3nx8oeBrjUPiElRGJ5mYVVxOG55VIdXd/uZPjypg0YmhBBCCCG6ilOSEwN5AB/sD0ogTwghhBBCdDvdc3IsIUSd+spqntXLQnUXKavpsagNzu9LKnhNAACBGElEQVTWz1vE7a881GAQryy1D+FLryU6YQqx4edyLGMAulL/Nn9QsZb7SpdynfebFo29uSpSs5l37eNUu1IM2/ML1jL1o6dQtFj7DqwVnJFmwajg0Qs7fOh6y7MchRBCCCFE9zbIY8ZicCn/4f6mzycthBBCCCFEZyeBPCG6sYPVMdYfiyQs7+820dfVNX79qyM60/wb6w2oWYoPctOLD5JUedSwXVcUVoy+mX/c8Sxa7iBoxJwZCqCWH0MtPYrqLWv0WHVqgo4eo7sKTVC7nUjvfnxw6yx0u8Ow37DdK5n476dQY4lPI3dmKTaVfE9iCc3CqhgrTsjUE0IIIYQQ4kQ2k8L5mYlzRn9VEuGwv+s96CaEEEIIIURDusadfCFEs6ysJyhyQZa1y0wCXzfH2wkBNY9FJddfzE2v/xeKv8p4XZudyPduYMXYW4iZm1dip6nBuR9UrGWafyMEEuclbIrajMDvuyoJX3wVuiXxRgXAKVuXct2C32ILtWx/7e1cgxsvAK/v7lrvQwghhBBCdIxL+toNl3+8v/tMHyCEEEIIIQRIIE+Ibssb1thYlpiNZ1XhnIyuPW9EdUTnB8VLufOVB3FXJc4hB6B5UolcdAVaTv8W76+xwbm6TD5vmWHpyMZKyAhM7UV09KX1BvMG7l3PT996hKzqhucH7EzOzbDgMicepX/vDRCISnlNIYQQQgjRsIl9jOeKfm+flNcUQgghhBDdi7mjByCEaBvrSsJoBvGQM9It2EwKYaPGDlaT9abhNqtUReovieOsLsP2xl9RqysN27XMHCIXXoYSi9Zl1DWXAijlx9AdTnQ67pjpqb0IT74e5ZO3sUYSnzLOLNnLNX+9lzeu+iVlp5zVASM0Vl9A06wqDE8zs/pofLDZG9H5aH+Aa/OcbT84IYQQQvR4FlXhrsFGmV06sRY9miXaWrbTxFm9LAlTCXxxOERpMEa6PbGUuxBCCCGEEF2RBPKE6IaCMZ0NpYnZeCpwToZxVldHq47o3BvZhOotQ/Ok8SfLMMN+Ln8FNy74Faq3wrBdS8sg/L0bUKJR8FcDNRl1utXe4nKXHU3P6sPb1/2a6xf8FotBME8J+rnhzf9mzcU/YNnZ13TACBO5LQrzd/rwRjSyHfE3U87qZU0I5AG8VuCXQJ4QQggh2oUei5G98OWE5dFolOLv3d4BIxJNcVV/R0IgL6bDe/uC/PBUVweNSgghhBBCiNYlpTWF6Ia+PBomrCUuH5ZmJtnaOX7tPRYVt/m7sdTNhVdbTtKAPeDlR28/Sq/SA4btWlom0QsugeNKUBqVu6zN0ku2Ks3M1lNauH7zHcgdzis3P4HmSjJsV3WNC5b8g6vefdIw2NcRvBGNyrBOdTT+pOzrUsl0JB6/Tw+FOBqoPyNTCCGEEEIIgGsGOgyXv71HymsKIYQQQojuQzLyhOhmglGd5UfChm1jexvPI9HearPvgHoz7xKEgtz43qNkHdtn2KylZRC5+PsosWijNveDirUoQT+aJ60mU8/RlAwwPXH9dlTcO5/wlbdg/ej1ejMTh+xYzk+PHeDda2e069iaQlEURmVYeH9/KG55TIe3CgPcc7q7g0YmhBCiJ6q/xCLI4yVCdE4DksyM7GXh6xOy8pYfqXkwLNMh5TWFEEIIIUTX1zlSc4QQrealXT6qIolzuY3OstLX3Tm+yNZl39WTeZcgHML6yVtkHS00bNaSUwl/byrYjG++naguS+/b7L/mzH7S0vWbozaT0GNRwe0hOu5yYgMG19u/d+k+pr34AOoB4+PWGZxbT6nX13Z37TKoQnRGr7/+Oj//+c8ZP348mZmZpKSk8PLLieXkanm9XmbMmMGwYcPIzMxk2LBhzJgxA6/XW+86b775JhMmTCAnJ4f+/ftzww03sH79+nr7FxQU8MMf/pBBgwbRu3dvRo8ezfPPP4+mGaSVC9HGakssGv0x6XJOCtFZXTMgMStP0+HfeyUrTwghhBBCdA+SkSdENxKO6czZVG3Y9sAZSeysTJyPrDXVlJnUcJtVqiKt8+y6JRzAunABaslhw3bNk0pkwpSajLouPgdeY8TN92e2EJlwFfrXKzBtWI1CYgDXHvKhL1xAbOgItAsu6YARNyzNrjIwycSeqvjzZWNZhK3lEU5LtXTQyITofmbOnMmBAwdIT08nKyuLAweMyxQD+Hw+rrjiCjZt2sTFF1/M9ddfz+bNm3nuuedYtmwZH3/8MS5X/NxDTz31FI8//jh9+/bljjvuwOfz8fbbbzN58mQWLFjAhRdeGNd/+/btTJo0iUAgwDXXXEN2djaLFi3ioYceYsuWLcyZM6dNjkNHkowvIYRofVcPdPDoV4kPmby9J8CdQ6XCgxBCCCGE6PokkCdEN/Lqbj8HfYm3As/qZWFiH1ubBvJqy2Wq3jI0T1rjS2Y2wO0r56b3HkctPmTYrjvdhC+/EUXtHJmGbU0BlPJj6A7nd1mAikLstJHoTjfmdctQQonz4imAedsGlIAP07UXAJ0rODaylyUhkAfw+m4/j52b3AEjEqJ7evbZZ8nLyyM3N5dnnnmGxx57rN6+c+bMYdOmTUyfPj2u36xZs3jyySeZM2cOM2Z8V7q3oKCAJ554gvz8fD799FOSk2t+d++++24mTpzIfffdx5dffonZ/N2l5wMPPIDX6+WNN95g0qRJAPzqV7/i+uuv54UXXuC6665j3LhxrX0YOlRtxpeRw5NubefRCCFE99DPbWZUhpW1JfHTC6wqDrO/OkquW257CCGEEEKIrk1KawrRTQSjOr//psqw7T/PTEJR2rYAZF25zG/LTbZUxtE9/PS1B8k+stt4fy4PkbGTwZXU4n11B3pmDuEpt1OcObDePqa9u7j6X09girZtZmZTnZ5mwWxwer5R6CemJWYZCiGaZ/z48eTm5p60n67rvPTSS7jdbh566KG4tgceeICUlBTmz5+Prn/3+/nyyy8TjUb5xS9+URfEAxg6dCg33XQTe/bsYenSpXXLd+/ezcqVK7nwwgvrgngAFouFRx99FIAXX3yx2e9ViO6iNovT6E97lfYWoiu4ZmBieU2ANwukvKYQQgghhOj6JJAnRDfx9+3Vhtl4w9IsXNavcXPHdQq6hmnjWm5/6QFSq0oMu1S50wlfPhWcUirneFpSCu/98A/sHDa+3j6DCr/ilg+eQO1EwTy7SeGU5MQnpQ/7NZYeDnXAiITo2QoKCjh8+DDnnXdeQvlMu93O6NGjKSoqorDwu/k3ly9fDsCECRMStle7bMWKFY3qf/bZZ5OcnBzXvzOxqUhgRbQbmbdPiMa5Ls+ByeBD+PUCf9yDJ0IIIYQQQnRFUmNCiG6gMqzx1EbjbLyH2iEbr1XoOurBPZhXL0GtrD+jr8qZwus3zuQ2ClFKj7bjALuGW30b0S+ZRMQaxbx+BYrBjYshe75C+eB/+fdl90Mnue08LM3CtopowvJXC/xc3KcLBaKF6AYKCgoAyMvLM2wfNGhQXb/jX7vdbrKyshrs35h9KIpCXl4e69evx+/343Q6W/BuWp87VEXaZ+8atkl5TCF6ls4472VnHFN7yHSYmJBjY9Gh+IfAdlZG2VAa4axe1g4amRBCCCGEEC0ngTwhuoFnN1VTHkoM2PR1qXy/f+cOgtgDVQzZvJTztizEerSwwb5lqX34x5RfE0vPgdKG+/ZEx8+hpw05k6jDhfnLL1DCifPmnbr5MyakZrNtwm1URTr+ts6AJBNJFoWqSPx5/P6+INURDbdFEsiFaC9erxcgrkTm8ZKSkuL61b7OyMhoUv/G7qMxgbxgMPFzrjnC4TBWIBZr+HMxGk188KCG3kDbydobXldvYL/NbWvPdWuPae3fnfH9dMafT2PGdOKxbesx1QSKbIZtsZOs2xE/2+Ye4/qOa9yasSgZHxqXAS65fFrH/E53wJiauu7xx7Yl29U0Pe7z/9pcS0IgD+DlHVUMdbsSlnc34XA47u+2Yrd37u+XQgghhBDdkQTyhOji9lZF+dMW42y8yf3snTIbz1VdjmnbBtS9O7n3yNOYtJMHkrSsvsyfOpsyUxLGt33FifSM3oQvm4r1w9dRIok3Nc5Z9grDnRHmnDmtA0YXT1UUzsmw8FlR/I0Hf1TnvX1Bbs7vXBk5QojOpaio6KTBt8bql5JEdbWv3na3plFZ6TVs0zQdbz1tNe3OZq+ra0n1tje3rSPW9X17bDvj++mMP5+mjMl3wnnbVmOKRZzYX/+zYVvwxns71fnWmO02dIwh8bg2dt2ucM605n6b+3mgaynN3m44ZOPAsaK6fw8DXCYHvlj8958FewL8uFcZ5h7yXFhxcXGbbdtkMtWbsS+EEEIIIdqOBPKE6MJ0Xefh1RUEDe5dDkwyMcjTeX7FTdEwp21ZwWnfLGTgwc0oNG6uCh2F2BnnEh05lqDDA2GZ46Ip9F5ZRCZcheXTf6EYzItnXbSAfqlnUdl7WAeMLt6oTGtCIA/gtd1+CeQJ0Y48Hg8AlZWVhu1VVVVx/WpfH59x15j+jdlHbWbeyeTk5DSq38mEw2EI+XG7XZhMJsM+mqqSnOwxbAurCp562gBUVWn2ukoD7c1ta891Y7EYvmofrm+PbWd8P53x59OYMZ14bDvDmOrTET/b5r6fWCxGEBKOa2PWhc59zrT2mJq67vHnbEu2a7XZSO/XL27ZlUeqeX1P/ANs5RGF7aYsLuvbvctrhsNhiouLycrKwmrt3u9VCCGEEKKn6Tx3+VvR8OHDOXDggGHbHXfcwTPPPBO3zOv18rvf/Y53332Xo0ePkpmZyVVXXcUjjzwSd9PpeG+++SZz585l+/btWCwWRo0axYwZMzjrrLNa/f0IUZ8P9wf55GBippUCXJRt6xSzn5miYS786l0uWvcOjkD9T9saKU3uzSeXT+daZ/1z5omT09MziY4aj3nV4oQ58xRN45p3/ocjN/4eXLl4LCqg4Tar7V5ys6/LRG+HypGAFrd86eEQh3wx+riMb6IJIVpX7Zx2hYXGJYxr57er7Vf7eu3atXU3EBvTv7596LpOYWEh2dnZuFyNK4XWqmW+Qn5MJhNms/FlchjqbQOlgbaTtTe8rtLAfpvb1hHr1h7bzvh+OuPPpyljOvG87Qxjas39WlWFe05zG7bFWrDdk425oc+Drn7OtOZ+m/t50JLtqqqS8Pl/66lKQiAP4NU9Ya7Jrz9g2J1YrVYpfymEEEII0c10y0Ae1Dzp/R//8R8Jy08MtPl8Pq644go2bdrExRdfzPXXX8/mzZt57rnnWLZsGR9//HHCTaSnnnqKxx9/nL59+3LHHXfg8/l4++23mTx5MgsWLODCCy9s0/cmeq75O2tK+9w22IU3rPHwGuNMhlGZFrKcJtwWhfk7fXgjGtmO9g+C5G1fwfmL/k6yt6RJ6+kOJ4vHTGPZ0EtxO6xQurSNRthz6Jk5REdfimXFwoQ2e8jHtH//lldv/wM/shxA9ZahedL4k6X9s/TO6mXhowPxN1904M0CPz8/o3GZOUKIlhk0aBDZ2dmsWbMGn88Xdx0UDAZZuXIl2dnZcaW1xowZw9q1a1myZAk333xz3PaWLFlS16fW2LFj69ruv//+uP7r1q2jsrKSSy+9tNXfW1tT/VX0KivGGazCFIsSsdgIWR1UunsRtjo6enhdRs0cbMY3oTt+VlfRUfRYjOyFLxu2HZ50azuPpp3oOo5QNUm+cpKqS0nylZO838/4I35MsSimWASTFkVHIWq2EjVZSNrvQi3cDjY7utVW87fNAVbjeQ27m7G9rfR3m9hXHf9psfhQiIPVUfq6u+0tECGEEEII0Y1126vY5ORkfvnLX56035w5c9i0aRPTp0/nscceq1s+a9YsnnzySebMmcOMGTPqlhcUFPDEE0+Qn5/Pp59+SnJyzWxdd999NxMnTuS+++7jyy+/PMlTkkI0jzfyXabSL9dWctCXeDurl11lUl87Ye27dSrDOkkWLaFvm4lGmPTJnxjxzSdNWk3LzEHrM4DoGaNYnzWRmJTRbFWxIWeyLprE+WsWJLSlVx5hyr9moV4yGbXi2wzI9HYeIHBmuoWPD4QSCq++tMvHfcPdqJ1wzkchuhtFUbj99tt58sknefLJJ+Ouj55++mkqKiq466674uZgvfXWW3n22Wd56qmnuPzyy+uuj7Zt28Zrr73GwIEDGTduXF3//Px8Ro8ezbJly1i4cCGTJk0CIBKJMHPmTACmTev4+TtPKhJBLdqLcrQItayEfv96gfvr6eqzJ2HqNxCTHkVP6YWW2gucbpDPtQQ9MmDTBiQg2nkpuoatuoJ7nSWYKsswVZbW/O0tw1RZhvndMh6rKMXkLTMsjd6cxxx0VaXP6iX8Kr030V7ZRHplE/32dTSrD7rV3i3OC1VRuH2wi5lfx1cC0XR4Zbefh0b0jKw8IYQQQgjRvfToaJOu67z00ku43W4eeuihuLYHHniA559/nvnz5/PLX/6y7mbVyy+/TDQa5Re/+EXdTSqAoUOHctNNNzFv3jyWLl3KhAkT2vW9iJ7lg30BXt7lN2z77TkeKsIa4Y4KggV8WJd+xIiyo43qfrj3KXwzaDQHho7mdn03aulRMFvaeJA919Jx03CVHWH4rhUJbf0ObiW2HGKnn9MBI6vhsaoMSDKxpyr+VlKBN8aSQyEu6StlgoRorhdffJFVq1YBsHXrVgBeeuklli9fDsAVV1zBlVdeCcD06dP56KOPmDNnDhs3bmTEiBFs3ryZRYsWMXz4cKZPnx637fz8fB555BFmzpzJmDFjmDJlCn6/nwULFhCJRJgzZ07CQ05PP/00kyZN4rbbbuPqq68mOzubxYsXs2XLFqZNmxYX+Ot0fFWYdmxEPbQXJRZt1CquYBXs2hi3TLfa0Hr1Rs/Ixnz0EOhpEtjrYRoKtgHYFIMHsXQdYlFUbzmeaj9+xYzP4Dxst4CoFoNwCCUUwrZjA6cVlKFqNeOuLekdM5kIWRzYLKlklqqErA6qHSnEutM1XywKoSBKOAShIK41ixlTWIIr4MUVqMQV8NZk1vnKcPsrMGntGzZTNA1z8UHMxQcT2nQAp5tA3ulMtuVwNC2XkvR+HE3rS9jauHmKO1Pg+JZ8J7PWe9FO+Dr00i4/D56ZJA+GCSGEEEKILqfbBvLC4TCvvPIKhw8fJiUlhVGjRjF8+PC4PgUFBRw+fJiJEycmlM+02+2MHj2aDz/8kMLCwrq5XGpvdhkF6iZMmMC8efNYsWKFBPJEm6kKa0xfWWHYNra3lZvznczdWt2+g/qW4q3AsuxjFH/D+y/rlUtSXh6xgafyUv8rqQzrJFsVKN3dTiPtwRSVtyb/nDTfMfoU7UhoNu3eim6xofXKMli5fQxPsyQE8gD+urVaAnlCtMCqVat49dVX45atXr2a1atXA5Cbm1sXyHO5XLz//vvMnj2bd999l+XLl5OVlcU999zDww8/bDh33YMPPkhubi5z585l3rx5cXMIjxw5MqH/kCFDWLJkCY8//jiLFy/G5/ORl5fH7NmzufPOO9vgCLSCSATruy9h+exdFK3lme5KOISpaB8U7aPPN6t5MCmDwn5nUNDvDApzz6TKldYKgxadmWGwTdeh2oviLUfL6otp4xqUai+Kvwoikbrgcb/3X+Hh41aLqSYiZht+uxu/w0N6egombxlYbeg2W83fVjtYbVgOFuKpthFTTeiKig7oioolFsZSXEaf4lKs4QD2kB9X0IszUPPHFfCSsdiH+VABSihYE8A7LmOs92fvcrIQ4fGPAfjtSVQ5U6hypZGZncH3YklUuVKpcqZS7UrBZ/fgd3jw2z1AK18D6DrmWAS1Ogz+aohFa95LNAqRMKZQCM/n/+big5U4oiHsYT+2sB9bOIAt5McWCZCpBzB7y2p+LicE5nqtWszlrTviNqMA+Ktxbl7DiY9QlCdlUJLWj7QhgxlmyqUocxBlyb0THjroiExaBSgNJl4z2kwwPtvGkqL4cu0HquXBMCGEEEII0TV120BecXEx99xzT9yySy65hL/+9a+kp9fUiysoKACIm+PleLXBu4KCgrjXbrebrKzEm9zH9xGiLWi6zusFAY4FE28eJlkUJvWx8689gQ4YGaSVHsT6wasNBvG0rD5Ezx6LffCZxI4eAkfjnvAVrStqtvHONf/FvS/8DKXam9Bu3rYeLbsfpHdMNszgFDMphxUqTsgqXXQoxO7KCPnJ3ejpfSHa0dy5c5k7d26j+ycnJzNr1ixmzZrV6HWmTp3K1KlTG90/Pz+fF154odH9O5JSUYb5y89RfFVtto/UqhLO3vopZ2/9FICjaf1qgnr9hqP2OReQz79uKRZDqShFKTuKWnoUpexoTVZXE5m0GKawH3vYT5r3KBTX3zdnxcK4IOCJ7mmgrTU5g1U4g1VklR2AA9DQTOOazYFiMtXM+2a2gGoCk4qumkgvOsgNlVFUXUP59o+qaai6RrY1yt2VfizRENZIEGskhCVa87eqNxyQt32ziu+17lvuclKrSkitKoF9X1M7A6rmcBHqfyrBwWcSOuUMQv0HG2ePtrGIpjNvh3GVkhSbcdbd37b7JJAnhBBCCCG6nG4ZyLvtttsYM2YMQ4cOxWq1smPHDmbPns2iRYu4+eab+eSTT1AUBa+35gb28SUyj5eUlARQ16/2dUZGRqP7NyQYDDb6PYnOLxwOx/3d2hRF4dODQQoNMpUAbhhoQ9VjeEM6WlQjGtXQYuYGX2uq2irtdm8ZN7z163qDeLrJTOj8S4jl9EcJVKOVl6JHY+hRDS0aq9mmqhKNaqjRaM22T1gO1NtX+XZbSjSGctwypZXb9W+zL3QtRrSN99VW7bXHsNrmITDhGhwfvYoSSTxnLV98SHbGBXgHnt4u59Dxy/SYxpgsCx8cSBzX3M1e/ufsxEyg1tDWv8OiY0UiEex2uXEnmkfdtwvTN6tbJQuvKTLLDpBZdoALvvkA/QOFe3sNoLDvGezpN5w9fU4nZKv5POyoknadqZReV+L0V5J7eDv9i7aR9d4OLHu2tfu51RWpoZqH1YyuN92H9jKigXVz22ZIPZYa8OHY/jWO7V8DNdf6sfzTwWpDy84FZ9tcqzXFII+ZLIdKcSD+d2vhgSB7q6IMSOqWt0KEEEIIIUQ31S2vXh9+OP750nPOOYfXX3+dK664glWrVrFw4UImT57cQaP7TlFREbGY3OboboqLG3j8uQXWV1n47LCZb4vfxBng0MizhKj26ShhleqIhtcfoRpbg69P1rcx7cFAkB+8O5Nkb4nhuKPuZMpOHYmePQDF7yPm9aLak1ACPnQNqu0+vP4IFqcFn8+HVlnTfuJyqL9v7baUQPz2T9xXy9trbiD5A8F22FfbtB9/DKusDkLnXULyio9Q9fjsNyUW5fp3Hue1ax7lcEpum55DRu1nuqx8rEDshLlNXt4d4IaUMtKtLf+dqk9b/Q6LjmUymeoeuBGiKdSdmzBv/fqk/bSkFHxnjuZzc198Dg8xkwVzNIwrUEmKt4Ss0v3kle7G1MyMPkXXySnZQ07JHsau/zeaolKUOYjCvsOxhUeSunczWG0J67VVSTvomFJ6XYkai5JSVYJjazkXfr2NvsW76FO8qya7SQgDOoDNjtYrGyUaRrc5wO5EtzvQ7TWviy+9mX8eVIiZzMRUC5rJhKLrmGIRzNEwP8xVyFzyZk3p01AQJRxACQZryodaraiH9qEEjbPYmkuJRTHv+KbmH5vWoqVloOXmo/UZAJY2vGhrgKoo3Jzv5I+b4gO/OvB/2308fq7xw7xCCCGEEEJ0Rt0ykGdEVVVuueUWVq1axZo1a5g8eTIejweAyspKw3WqqmputNT2q31dX8adUf+G5OTkNHr8ovMLh8MUFxeTlZWF1dq6X1jLQhq/XlcJJD6tnWxVuLy/k6QkC4Q13FYVPawRsWi43eYGX5+s70nbLTDlk2cZeKzQcNyx9N6Exn4PdyyC5nKhqKAoWt1r3eHC7XLVbNOq4gq6UJM9aK7E5aCQk5qE26XhOaFv7bZO3P6J+2ppu45GtbcCp8OO2sb7apt2d8IxZNBQFlv7MmnJ8wk/P0fYz43v/Y6XbnyCSHLvtjmH6mnPcps5My3A16XRuDEFNYU3ytOYdU7rP+ndlr/DouNFIpGTdxLieLqOafs3mGpvTht1QUHrn4+WNwQ9OY2ySbeyemf9FRfuOsVG9r/+ivptGUWl5Aiqt7xZw1N1jb7Fu+hbvAvWvV0znqRktLRM9LQMtLRMcDfumrTb0nUs0RCugBdnsApHLMQZu0pwhKoxR8OYYxHMsWhNACQWIW2dhunAzm/n/lJq/lYUUFVSAiEuKdfQav5TjduNqsVI/ybCdUcqsYX9OEI+UrzFpFQdqyvdKFf9PVvEZMXn9OBzpFDlSsXrSmNwbgbuQ7vrAnS63QE2B6gq4YuvwvrZu4bbiqVnESiN/5zRFdBUExGLnViqHZKS0ZNqAlXHPxNVt91YDPzVKL4qFJ8XpaoSpaoCPRDA5G95+WC1rAS1rAR905douYMwjxgPpLd4u0110yAHf95STeSEr1Av7fTxy7OScJrVdh+TEEIIIYQQzdFjAnlA3dx4fn/NE4i1c9oVFhoHIWrnuqvtV/t67dq1dTd7T9a/IVLiq3uyWq2t+rPVdZ3/XFHGkUBiEM+swM35DpKsJlSTimpWUE0KqlnBrKl1y+p7fbK+J2u/YNkLDNm10nDcWq/eRC6bijkWQ/FXo5lVFLMJxWyue62bVVSzqWabZgWzWUX9tv3E5TpwR9U6lKAfzZOGGgnW9a3d1onbP3FfLW2PqTVf9hXVhLmN99UW7TGzknAMcTjZcM73cZcVMXrD+wk/R6e/kpsW/Dd/uWE2anImKQ4TqlnDYzPh02ItPocaah+TbUsI5AG8VBDkvjOT26wkUmv/DgshuiZ11+YGg3haWgaxERege1LrltlU6i01CdTMIeVKQnMlQZ8BNQtDAdSSIwRsLsKb15NeeaTZY1aqKjFVVcK+XQDoFhuZ2zdymas/h3sN5EjGQErS+hIzdcG59nQdolFMpUfoU1yC89vgXO3froAXR6CK7I98/Ky0vK7NEosP4t/YzN0n79rMxSfpM7KZ2z4ZXVHAmYTuTqrJ0DJbwGzGO/RcVpdqmMMB9GovbhPYo8Fv33sV2bEqzBXHDEtoN1fQ6sCUlIwpFgGbvWa+Ouu3f9vsREaOxbxjIzVPPEFdJQktBtEIscFnYN64BsIhlGAAQgGUYAAlFECPRlFbOVOsNcVUE0Grk5DVScjqIGR1kpnqxlZxtOZnYrGi2+xgtaHb7By7cAovH3PgcyQTttgTAsB3DbbjrCejtc2ZTHXBvuMDfYcvvYVXNhwhs2w/maU1pX0zS/fTu2QvjrCvybtRYlFMe3aQ89iPuGHwOJacfzOlqe0X1s5wmLh6gIM3C+PnEK8I67xZEOAHp3Z8CVAhhBBCCCEao0cF8tatWwdAbm7NLAmDBg0iOzubNWvW4PP5cLm+u5APBoOsXLmS7Oxs8vLy6paPGTOGtWvXsmTJEm6++ea47S9ZsqSujxCt5R87/Hyw3/jp/v8+x4NJgcqwbtjels745hNGrnzLsE1LSiEy7vKaEl+B1rkhowBK+bG6eVGMp68XDTE6hrVnzofjfkxaoJwhO1YkrJfsLeGOt3/NG7f+jh9ZDqB6y9A8afzJMqxNx5vtNDE8zcymsvhgXkSDWV97ef6itDbdvxCi5zId2ttgOc1Y/mnETju7JlhxHHeoirR6smigJhsmgc2B1ncgZZNu5fmdQVIqixl04BsGHdhI3oGNJPkrmvs2UCIhHDs2MJYNdcuiqpmStH4Up+dSltKbpLL+5AbTKPdk4XOmoKmmZu+vsUyxCCZvOenlx3CEfDgDVTiD3rqgXNo6P+aCTRAO1QR8wsGavzWNvh+8wj0n2b6zzd9B29EVFT0lDT0tEy09k/Cl12HZtDbhXAPwTrqJ5TuDRKNRvJVePMkezObvvt7dNdheU/pU0yASgtB3x9KbP4Iv95Wj6BoqOug6iq4TU02M7JfC5xVmQhYHIZsDn92D3+HBb/cQM1u+266B2JnnYyo7Wu/7i559Yb1ZqIcn3co/tlSQ5CsnyVeOK1AZF7A9y+rHuWdrzXuJRlG0WE1mmRZDM1sIaGrN8VOUmjl4lZp/JzltHNWshC12whYbYbOdiMX27b/tnNnbhXvvVjCZwWxBN1vAYiGqqBybcAP/OAAxp4eoyWIYjKvvWIQHDqU80sXmRFcUql2pVLtSKex35neLdY3/SKsg8/1/fJtRXIJSXtLouR0VXWfEji8YvnMZXw2bxMejbqZxs8q33F1D3QmBPIA/banm9sFOVEW+VQghhBBCiM6v2wXytm/fTu/evUlJSYlbvmrVKv785z9js9n4/ve/D4CiKNx+++08+eSTPPnkkzz22GN1/Z9++mkqKiq46667UI67uL/11lt59tlneeqpp7j88stJTq4pWbJt2zZee+01Bg4cyLhx49r+jYoeYXtFhBlrKwzbJvaxce/pbv6ytdqwvS312bOBSxfNNWzTLVYik68Dq2Q0dQU64LGogJmlV/8np8w/hOnQ3oR+meUHmfr6r1AvvRzV/+0T2e1QIWlSXzvbyquJnhCrfqMwwC2nBBmfI+eZEKJ1mfdsx/rNKsM2HQjdeDdqqO1uzlckZ7EueRLrhk0CXSej/CB5BzYysWILzi1fooRDLdq+WYuSfWwP2cf21CxYA3d/26ah4Hd6qHKmUu1MIauXh2uDlroMpJjJjI6CrijoKHj2WFB3b65ZORb7NrAShViM9CNF3FgawBYJYg9VYw/5sAWqcEb8WKM1GWIPtOiddA8xhxvFk4yWnoWeloGe2qsmoPQtPTPHMIjXJKpaU7LR5qh7gKd67OUsyzQ+j/NPdbJhR8dkxkUsdspSsilLyU5oyx1sx9rAnIzP11PW9kenOpnXwPsZUE9mnB6NEs3IwVfqjwuQdrRGZf62Ml1RiWbkoPcZQKw2mzgWRSk7hnrsCEpJUc3DYnrDDxeadI3zNn3M8J3LeWfEdWw65/utPtbjKcDAJJVhaWY2n/Bg2K7KKB/tD3JFf0ebjkEIIYQQQojW0Hm+kbSSd955h//93/9l3Lhx5ObmYrPZ2LZtG0uWLEFVVZ555hn69etX13/69Ol89NFHzJkzh40bNzJixAg2b97MokWLGD58ONOnT4/bfn5+Po888ggzZ85kzJgxTJkyBb/fz4IFC4hEIsyZM6dTfdETXVcwqvPjz8sIxhLbMuwqz41N7ZAnSDNK9zN5wROYtMSB6apK9LyL0ZPTUBqRifddEEn79u+Gl4u28YOKtXXlNiNjJqEsfge1rCShX2bJXrQPXyd6/sR2G1u6XWXaYBfzdiSWc/qPZeWsvDqLVJucI0KI1qFUluF58RnDLBMdhdjIMURHT6p37qrWH5BCSVo/StL6cebg68j+ZD6Kt7xmbr1jR1COHUGJtt78jyo6bn8lbv+380fvh7ObuS333p2c0Woj6x6iqpniXgM4mJXPod6ncKD3qVx9Xj7Zi1/t6KHFsahKuweKuqO2Crg1K/O3LZjM6Bm9iWX0hqEjiIy8ENtbz6PuL0CtKG1wVWeomlvXvMDug+sw934YSG6TIUY0nXk7/AxMSgzkAfzv5moJ5AkhhBBCiC6h20WcLrzwQnbu3Mk333zDypUrCQaDZGZmcu2113LPPfdw9tnxtyNcLhfvv/8+s2fP5t1332X58uVkZWVxzz338PDDD8eV26z14IMPkpuby9y5c5k3bx4Wi4VRo0YxY8YMRo5sq9kxRE/zm3WVbClP/MIJcP1ABwv2+Ml2tH35q+M5feXc8u/fYgsZz5ERGTsZ0jKbtM3jg0jHl+FMWO7oyoWyOq+EcptmC9HzJ2JetRi1/FhCf7WiFMvyjwldeWu7ZOQBPDQiidcK/PhPSMs77Ne4f2UF/xifWpc5PX+nD2+kJgB822CZ90QI0QRajKT/exK1qtKwOXbGKLTcxs2D3GYUBT05DT05DS3/NNA1FG8FsV69saz+FLWsBMVX1bFj7MJ0kxm+LTNZW2qy0esqSk0mneXb0ox2J7rTje5KovyCy3jDn87R9FyiZmv8ii3NtmsDeixWb7lIaLtAUUsCXw2ta/BMXLvoNAG3dqInp6LlDUXLG4pSWYZasA31YGGD5TfzD21Gm3kXZ47/Kd8MPdkslM03JMXM0sNKwnQEa46GWV0c4vwsW5vtWwghhBBCiNbQ7QJ5Y8eOZezYsU1aJzk5mVmzZjFr1qxGrzN16lSmTp3a1OEJAZw82LDoYJC/bDUOlo3PttIvyURlWCfJ0n5PRFuDPq588zekeY3nPVkx+ibOPqUfamn986KcqL557xqay020A6uN8PduIPDRv0itOJzQrFR7sX74Kkm3nAvpTQvcNpUC9Haa+M3ZHh5ak3hz/V97AwzZYOaRszwAeCPatzdpJFtACNE0lo9ex7pjg2FbbNBpaHlD2ndAjaGo6MlpRMd+DzUSrglYBAMoZSWoZUdRKsvQA35M1cbBye5EVxSw2IikZVKkuvE7PPgcHvz2pG/nd0tidH4G75Za8duTiFhsRE0WoiYLMZOFmMnMnac6EwNY3wb1jkyYyj92+lF0g2xNReGHp6XUm1nnP/siiuop+yi+05LAV0PrHp50a4vHJppGT04jNnIMsaFnYdq5EXV/AUrM+AFFNRRg6ifPcHnlFspuvBfdFp8h1xqBWFVRODfDyuJDiaWJn95YxRuXSiBPCCGEEEJ0bt0ukCdEV1BfsGH+Th9VYY1nNhvPe9fboXLVALthuc22ZI6G+d7bj5N1tNCwfcOpF7FizC2cXbasfQcm2ozudPP+7b9jysu/xFNWlNCueiu45ZVH+PDmx6hK7ttm43BbFObv9BHRNIammNlWkXgT6Hcbqsh0mPjREMnAE0I0X3TMZJQNq7Hu3Bi3XMvqQ2xYcwtMdgC7Az0nl1hOLgCHL72FVzccJvvoHnof20N2yR6ySveRVnEESyzcwYM1pqsqWKzoVlvNnLtWW81rm53o0JGYDuyua6v52wYWKygKhyfdyt/qCZqNONXJ/qbO/aYoNZmQVhthawOPFXXCzLqGNJTBJqUze65WPy8cTmJnnk/w9uk4/vYE6uED9XZ1r16Ic9tXRM+fAI7vrulaKxA7PM3C8iOhhO9RCw+GWFcS5uwMq/GKQgghhBBCdAISyBOiE6kMx3hpV4CjgcQvyhYVbsx3YFEVgrH2y08zR4Lc9u7/0Gf/ZsP2g32G8s6l/w9XB8zXJ9rW9Voh+nU/oHTBS6SXHUxoT/Ye5ZoXH+Ktax+lMqPtMlW8EQ1vBKYMsHNkm4/yUOL5/4tVFdjbt9KsEKKb0VPS8f78CZxv/x3H4ndqssEdLqJnjwWlawVp4igKVa40qgamsXPgdwFJRddI8pVzm6ec1Zv24qkuJclfjstfQZKvAlegklQtSMzvxxYJNGmXuqqCzQ6aDiYTutWGbrYQ1hUsTieKzUbV0HNZWm0naHMRtLnwOZLx25PwOTz8YFga2YteMdx25OKrUNprjsJurKEMtu5W8lE0XludF3p6FtHzJqAUH8S8YTVKwLjyiFpZhuXzD4iefzF6akaz92fEalIY2cvKyuLEBxh+t97Lm5N6ter+hBBCCCGEaE0SyBOiE1lzNMJ2g4wjgGsG2Mlq5znxzOEg1y14nP77Nxq2a6kZLJ76KC6LDY+lC9/kFAlqy5vqDiev3jyL6197lN6l+xL62QNV3Pj6r3j9ew9SdeboNh2Tx6ry/Lg0blpcyomxbB24d3kFVw+wMzjF0qbjEEJ0YyYT/u/diFpVie2bVUTPHVeTEdYOWjI/WPO36wRTP87JH5bQ4geqFJX/21FTTtISCWLSYjVzx1ETCLw9z0bW5wsAHVQTmEw1fysK4YuvwnpcQCAajVJZ6SU52YPZbKZy0q2sqa/cpDwc1Cjf/Wx1NM2Jqip8V6hcMutE56Nn9SUy4SrUjWsxHygw7KOEApiXfUJs5Bi0vgNbdf/nZlj5qiRM+IRfjUWHQnx5NMy5mZKVJ4QQQgghOicJ5AnRSeyoiPDhfuMbWvkeE2N7W6k2jvG1CaevgqveeZysop2G7brTTXjStdwY3oHi9aN50iDQxHJVokvwu1L5v+tmcuc7j5JZsjeh3RINc8sHv2N59KesPuOyNhuHAlza186cMSn8bHlFQrsOvLM3yKV9dC7uI3OdCCGaT8vIJnLpdTWBqXbSkvnBWrpd60nmFtMVlbDVmdCueexgdyQsF+2j9md7YpC0lmTWiU7JYiV85vlUuZJJ2b0RJZr4BUfRYpi/Wkq0uhIuvaXVdm03K5yTYZyVN2u9l3cmS1aeEEIIIYTonCSQJ0QnEIzq/OSLcqIGFTPdFoXLcu0oikJNqKJ11WTSabjNKlWRmkkjkssOcdmr/01qxRHj8TqSUL53Pbg9qOXHUPw1c/rJ8/Pdj07NOeJNSeGD23/HD+Y/gHrUYM48XWPcx8/hOVzIOxf+BGj9DJba+fK8EY2r+tt5d59x4HvRoRAWE9xzelKrj0EI0YO0YxBPtJ6GMhBbMsVwW2VMirYnP7vOKZjRh2B2X2xb16EWHzLsY97+DWmvPYty1o/R1db5TD43w8q6kjChE37snxWFWHIoyIQ+7ZOFLYQQQgghRFNIIE+IDqbrOvevqmBTWcSw/fqBDpzmtilbWR3RuTeyCdVbhuZJ40+WYQzat57rPnoSW9B47grd7kC/7g7QWnI7THQlP6hYixKsyboMj/8+1mUfoh4+YNh3xDcfk3F4N5/d8EuqXJmtPhZvRKMyrHN+poXTUi38bkOVYb8P94d4dlMV/2+4BPOEEKInaSgDsTbDsLW3Cw1nvzUUSJIgUttrq2xX0XK6Kwn//U/gfPoRwwfFAJKWvc/U4kremvxzYqaWl0+vzcpbYZCV9+iXlVyUbcOkyuOJQgghhBCic5FAnhAd7C9bfby627gk5U9Pc5HrNlEZbv1MPKjJtlK9ZailR0HXOXvvv7n4s3mouvFNJd3hJHrBJSg2G0rA3wb5gaKzqZ0rry7r0mwmOmo86s5NmLdtMFynz9HdXP9/03n/igcoGTIqrs0oA7Q5kqwqHqvCpL42Fh4MGfZ59CsvZlXhP053N3s/Qggh2kZPCm41FEiSIJLo8RwuoudPxLT5K0yF2wy7nLFzGaeY/JTc9Wt023flfJt7JXluppVtFRHKQvHfZraUR3m1wM9tp7iauWUhhBBCCCHahgTyhOhAOyuivLTLOIh3WqqZ35ydzLwd1W0/kFgM87KPmbhrc71dylOycV56BUrEOHNQ9CCKSuSCS9CT07CsXmLYxR6s5voFv2XD+dfy6ejbALNhBmhLeCMaZ/WyYlLgowPGwbxfrq3EaoIfD5FgnhBCdCYdEdySEotCdFKqSuyMUehJyZg2rkHREx8XdGxbR9/f/oToBRPBWjMXcnOzbG0mhfuGufnNusTKDjPXebmqvwOPtW0qogghhBBCCNEcEsgTooMc8cd4dbefmEFam8ei8M/xadjN7VDWxV+NecUnqGUl9XYpyj6VhTf+NzdVrUcpPdr2YxKdnqIoaHlDCdudWJZ/jBKNGvYbsfptcgq+5tXJvyCUM+C7DFCA9NYZy7hsG+Nz7Dy8ptKw/RerKrGoCtMGy9PVQgjRFN0t8CUlFoXo3LSBp6LbnZi//ALFoIy/Wl6CefknREdfCnaHwRYa76Z8J/N3Bdjtjb+GPRLQeGK9lyfOS2nR9oUQQgghhGhNEsgTogOUhTTeKgwQNrj/pQB/uyiNwSktnwPiZHof3oXt3y/VlU00Ej1lGGmjL2Gqsg8CxtmDoufSBg0l4krCsvRDlCrjQFpmyV7uefUBll70AxiQ0upjcFsUFBRuz3fw0u6AYZ/pKyowK3CLlEoSQohGk8CXEKK96dn9iI6+BPPqJSjRxEogqrccy/KPiYye1KL9WFSFx87xcOuSsoS2v27zcVO+kzPTrS3ahxBCCCGEEK1FAnlCtLMiX4z/2+7DFzWeYe7SvjYm96v/6ffWcvrmT5m08DmUaOJE71Azf170nHFopwxDrSwHswWZ9l0Y0ZPTiFx0Baat6+ud28QSizBxyd+J5eQSGz7KsE9LeCMao7KslIU1PtifWGZTB+5dXoE/qvOToVJmUwghhBAn5zAp3HOaC+q5Cu5qWaldhd6rN9GxkzGvWowSCia0K9VeLMs+wjzmSiCt2fu5PNfO+BwbnxfFXztqOjywsoKFV2RgUuUbkBBCCCGE6HgSyBOiHZUEYlz9yTHKQ8ZBvLN7Wbgou22f/DRFI4z78G+cvv7jevvoFivR0ZcSyz8NRbLwRGOYLYTHX8FXp4zngsV/xxwznkvRVLQfteQIkQu/B+njWn0YY3rb8EVJuCEDNcG8B1dX8vGBIFP627n9VAnoCSGEEKJ+rqAXz6f/wmw2/tosWaltR09JJ3LhZZi/Xm44BYAS8JH19ANkXvVbjqbnNmsfiqLwh/OTGf2vowmVUtYdi/DnLdXcNzypWdsWQgghhBCiNckMzkK0k4qQxjULS9lZaTyX2MQ+Nq4eYEdR2u6pzyTvUe5685GGg3iuJMLfvxWtz4A2G0dP9v/bu+/4Ksq8//+vmTklnUASQu8gghS7gCBFFMWOa2PV++euq9h27W29t7miq66uim756n2vK9ZbXbGsCCqCAqJYaNJC7+k9OefMXL8/ThIScxIgBEjg/Xw8ziM5c10zc801c86Zmc9c12XiEzFxCYe6GAeGZXFCn/a4503GS+/QcLZwiMAnMxj78T+w3difh/1xcvsA47sEG0yfvbWSf6wspTRc/yl6n893QD+DIiIiIrKXklIov+VBTFJKzGRfYR4/f+NeOu1c2+RV9Gnj51eDYwfrHvymiGV5sR9OExERERE5mBTIEzkIisMeF8/KafBC8Nh0P/87pt0B7bql25qvuPqfv6LLzjUN5vE6dCF82kRM2/QDVo4jWnkZ5UenU9Hz8BynzQLs/BwsYwidczmRo4cSu+1p1AmLZ3DOK/9NfFnssfX2x9hOQe4a2vAT1EvyIox/P5slubu7lrUsi//kxvH3leW8tLq02cskIiIiIvvGtE0nfOoEvJS2MdMTK4r52Zu/ptu2FU1ex22DkumV7NSbHvLgurl5VLqNndGKiIiIiBx4CuSJHGBFIY9LZuXydXbsIN6Atj7eOiOdZH/zfRxT/DZtAhZJPht/qJzzP36Wia//joTy4gbniQw8nvDocyHQcEsm2T8WYEL5mFD+oS7Kgef4cI8dQfisSylKbjgw3HnjEq568VY67cpq1tUn+S26JTpM6Nrw8bwiP8LYd7N5cHERJVWt8woqXApCHkUxWuuJiIiIyCEQF0/k1DPxGnjYMC5Uxv/31m/ovfHbpi3eZzFtZNuYIyEuz49w36Lmf+hMRERERGRfaIw8kQMov9Jj0kc5fJMTO4iXHmfz7zPTaRvcHcTb3zZ5JWHDjeGl2EV5kJtN5Scf0KZoV4P5jc+PO3QYkSEnazw8aXZup27837XPcMp/nmXAD3Nj5mlTlM0vXrubOef+km/7Nd+4eUVhjyFpAdoGbF7NKo/ZOjBi4LElxfxzdSk3DYin0ov9w1jdQu+n/Q7P1pQispsvLg7vzIsINZTBqPtdEZGDLhAkMvwMfF9+gp2zo35ypJKrZvyBV8++ix96n7LPix+WGeSXg5J4cmlJvbTnV5ZyYkaAy/ocpt3ji4iIiEiLp0CeSDOqPb7WhuIIl8/O5YeC2GOApfgtrjkqgfbxdbtxSfJbvLS6lKKwR8f4+l287IkBnK3r8H/+Efa2jcQ1kje3XReSRo/H8tT6aK8kJOGkpEJ8AoQrDnVpWo3LK3/AGn4yld0yCcx+C8t16+XxuyHG//tREodt5IOTrqA5G4wP7xAg6Fi8vq6cskjsrpGyKzx+800pfgsGtA0xunPd9auFnsiRI2QqCe34AJ8v9mlyIP3sg1wiEREBwO8nMmwcvkVzsHdurZfscyNc/t7DzBh3A18fc8Y+L/7eY1P4aEsFK/LrX7/dOr+Ao9v6GJIWaFLRRURERET2h7rWFGkm1eNrvbqukgU7Kxn3bnaDQbxkv8VlfRJIDcb+CBaFPQpDhpLIvgUPApWlnDbnfwn83wvY2zY2mnflUSP415WPazy8vVVeRsWANMoHpVDZS0/j7q3qcfPs3F2YLj0Ij5+EiW+4VdvwBa9z2fuP4As1b6C0X6qPO4ck0SG+8Z+9sLH4Ps/lL0tLOfc/2byzoZyIp3FRRERERFoEx0fk5DF4nbrHTjYeF85+htPnvwSm4XM4C8itcOu8SsIejw9rQ7xTv+V1uWu4dFYum0tiX9+JiIiIiBxIapEn0ozyy13m5FZw+5fFNNDwh04JNpf0jifoNF8c3XHDDFz8McfPnU5iWeNjOBjHR3jYOOaMupk4y4L6vce0WtUBIhOXELOb0D2lN8YCTGUe4dJtmMSGA3mGCK4pwFi5GH8unrcZzy7AJBRhHBd3g4sxEYr8QIqH5SVgOTZ2XADb64RjJWCZDjg4+93Naktk2mUQHn0OznfzcbZvjpnnmLULyHzxbv7vwvshrX2zrTs9zuaGgYn8Z3MlX+4Msacw+bwdIebtyKNTgs2Atn5OzPA3W1lEREREpIlsh8gJowjt2kHSwlkxs4xZ9DrF5OKcdAOur/45XNgzvLAq9vXA1JNT+NX8+tdUO8o9fjIrlw/PzmjwgUwRERERkQNBgTyRZrK11OWNbbChLPZ4eABpQZtfHZNEBCgMmf0O1NhuhEFLPuaUL16jbXHD4+BV8zK7EBl8Im63Plxd+BUmEAeHy7h45WWUH9cdE3KwAokk5OfsW3oDjDFAGI9yTEURTngnXmElFXYRJq4IzwXjlOAlleBFKsFfCS7Rb1cf4AFO1QugMvrHg2h00CuIto0OAt666Dwu4HNwElNx3C74rLb47EQwGYdHcC8YR2jCJfgXf45vyZcxs2TszOKqF2/j4wvuYGWXIc22ap9tMapjkBPS/XyTG+aLHQ2OglVjW5nHtrJKPt1WSVaxy38fl0KXJP18ioiIiBwytk3uT29nWbmfU77/IGaW5EUf81/bdjH9nHupiEva60Wf2z2eH/Ij/O2H0nppKwsiTPooh7fOTKdNQME8ERERETk4dCdSZD8ZY/jXmjLuX1RIcbjhMMsx7fxM7BYk3m9RHI4212vqeHi2G+HY5XMY/9VrtCmoP9j7j5UHE/ls9P/H6M5x2HnZWICVn4OJT2jWwND+tHjbXxZgQvlQuYsfN4Y0eBgq8YrXYCp2gJNAyCqEQDGetxljl2JcD+OUQUI5XsQCXzkmuQLPDYG/qgudLZAAmHKoqA7OGQ5MJ8WWi+vLxTW5hHxAMlhuPI6ThuN1igb3rPjo9h3Cem8qy7ZxjzkBk5KKb/6smOM0JpYVcO7LD5A2/FI+PP4SoPnGJOmX6qNfm+jrs22VrCuuP27fj7kGXs8q5/2NFdw1NJkbBibhtw+L0KqIiIhI62PbvDv6OkrjUhj35asxs/TaspQbX76Vl8+5h+3te+/1oh88qQ2rCyN8uq2yXtrinDCTPsrhzTMUzBMRERGRg0OBPJH9sKUkwq/mFzB7a/0LvNomdovjb6Pa8uLq+k91Vo+Hl+zf83h4aV4FQ776iL4L/02bouw95jeWxXdDJvCfky7Hl9qW0blz9zhPkzWxxVtzMPGJGFOBV7YFyjZiCldS4uzCSyrAREIYf9X+2bB7nrIft5irDshVX4tbVa8WxFBOxN5CxNtCpQ9IATucAm17QLt22MkOifl7Dki1JO5RgzFxCfjnfoAVqv85sjCMmP8qPdd8yRfn/YritF7Ntu7iiKF9vMPPj05keGaQv68o4vV1FURM4zu+NGL4zddFvLOhnP93Wjt6peinVEREROSQsCw+GXYF+SmZXPjxMzhe/XPhdkU7ue61u5kx9nq+GXj6Xi3Wb1v8c0w7zvogm+X59cfF+zo7zDn/yeGN8Wl0SNj7BzJFRERERJpCdx9FmuDFVSV8vK2SmZsrqGgkbmJbcNeQZO4amoxtNT0qlFyax7EL3+fkb9/FqqzYq3m89p0JnXoGXx59Mb6wR4r/wD4t2liLuOZmjMGjANe/iXDoWyLx+ZjKbKg15Jp3hDwc61lFULAk+v+uORT6bJxIBo6dhs+fjG0C2HGp2LTcFnumfSfCp03E99Vn2AW5MfN0yl7PpBduZcng8Xx40uWQmN6sZRiaHuCJk5NJNxV8X+Zjab5LXmXjR/I3OWFGvbOLPw9P5ZLeDY+bKCIiIiIH1rcDx1GUnMYV7z1MXKj++a7fDTFp1lN0276S90b/gmg/G7FZQG7VRd7fR7Xl4lm5bC+r/9Dl0rwwp7+Xzf+dkUb/VI2lLCIiIiIHjgJ5IvtoSW6IR78vYXNp4y2fOiXY/OO0dozoEGzyutK3r2Xkl+/Q/4d5+Lz6T4LG4rXLIDL4ZEhNw7RN5+qCRVgVZXgp7VrteHgeFUS8XXj2VtyE7UTcfIy/AqqvlxtvENkiWCaIZSVi4oJg+8F4YMLRMfjcMoiUNNOKPFx24jo7CSUA7pfgxGO1aY+V0JP4ggA+q+EbF4esm87EZCrPnUzg85k461fFzGIbj6Hfz2TA8k9ZNWQ8C489j8Kkjs1ajDgHTkj3c0bXeI5KDfCPlaV8tLmiweB0ScTwi7n5LMsL85vjU3DU1aaIiEjr4vMRGndezCRrzx1mSAuS1W0of7/kYa769+9JLYndO8iJyz6iy47VRH5xN9A5Zp6wZ3hh1e7z4HO7x/PK2rKa4RFq21Lqcvq72Uwb2Zbze8Q3y3aIiIiIiPyYAnkie6kk7DH122L+uqIEdw9Nzi7rHc/DJ6eSGrT3eQw8y3Ppt2oBQ7+aQY9tK/a6fF7bdNxjTsDtewxWRTlWWUnNWHhWWTRI1JJCDF5cPCboRINFdjGescAqwfjycL0teHYeXkIBbqQU4y/a3QVmS+u5xo4DJ4hlByDQFssORv8G24IVwE7oDHYAvDBWoC2mfCs4CbuDd8H24JZhQgVg+TEVOzCRUkz5NkzFTvD2rgVmo9xyTNlGTNlGSqu75Iyk4DjpOF5nfFYbfMQd0u5RAaxAkMgp4zCJyTjLv8Eyse+eBSIhBi1+n0GL32dDpwFsGnQaS/oMh9S2zVaWlIDNjjKX0zoGGNcxwGvrylmcE24w/1PLSlhVGOH509qSdIBbv4qIiLQWBgNEMFYYY4VxS9cQ9u3AEAHLw+ABHlgekV0f4QVqP8wT7efcqjqDjeR8gvGvqzXdBhPtFz1StATL2RmdVjW9+n+vMhvPKqs3vWbZXoRQzgf1yh6JRIhrf84BGQpZDpyd6T346+WPcdn7f2rwWqpjzgbMwzcx7sSLmXPSJbhO463p2gZtLu+T0GAwryRiuPrTPG4YmMh/H9eGOF9LuuoSERERkcOBAnkie1Ac9nhhZSlPLyshp6Lxx3KTHLigR5BnRrWrmba3Y+AFKko4cfFHHP/te6QU7trr8nmp6bh9B+IOOhGrohz2owvPpjIYPErwSvMxZZvBWkeZXYhxwxinBJNUgYkYjC8MyWFM2AXLhVKirer8gEv0G6n2uHUHNWhnRQNuti/ags3ygeVAIBXL8oM/BYNFaWkpSWl9sB0fmAhWXMd6Qbk6gTosCBdCpKTRLkct2wfBDCx/Ys38JlwMTjymdCOmfAsmXIQp2xmtu/3kUYRnFxH21kXrPMXGMe0wmztj+RKwkvthDkXU1LLw+gzE7dUf/2cfYBfmNZq9x7YV9Ni2glM/+htbeg7hhz7D+bbbCZCYsd9Fqf7sdkm0mdQrnhMz/HyyLcTqwtitY2duruDcD3N4/fQ0MvYycC8irZ/Bw1gVeFYFkaIlGP8GjBXCWGHAxVgRDC5YHt6GbYTjq/uBrvV7bWy8LUW4wY2Ag2UcLOOr+t+HhYNb/AMROw8Lf3RadbrCDNKMDAbjhfGsSqIBODcahMMFK4KxIoRzPsULrKoJztW8iOCtWkx50q6qaREgXPdJslUfQmIDK9+yGBpr0LRpcbS3gVjWzqMyqYG05R9QntLQBtvwzb+JDpZsgWVHX1WBvorchVgpRViWUxM4jAYWo/97G7YQjt8GxqoVIIx+Jr0tJUTi1lavqPZKAXA35xOJW18vzQDepmzCcRtjFjmatqGBDbLwNucTidsA2FimVtDS2Li7ApjAWqj6DrGqvmMwDhY+vFAunlWJZfyt+rulOLEdz096kNtXTCf14zdj5rE8l7FfvsaArIW8Of6XbMvs0+gy2wZtJvdJ4PV15eRVxr6ue3Z5KXO2VvLXUW0ZnBbY7+0QEREREammQJ5IDDvKXL7ODvHexnLe3VhBaWTPo76dmO5jRGqEnumBPbbCi45X55Hks/Ht3MzIr2ZwwoqP8Yf3vvXV5i4DWTr8YsYmlWLnZR+0AJ7BwzW7cO1NRNw8PF8ObkohWBHYsjtfyCF6X6L2PQCLg9cs0I7D8idBIB1/SRyWFUc4IwHLC0GwPfEbwtjlEYhrQ9mAdLB8WF553YDcj4JzbqgYt3IrVjADi1DzdYfZAMuywJ+Cldwb4jOj5V4bwiOXsvRsTOn6aEu+UOPBrr1bmYdr5UBBVSu8nAUU+QI4bkd8djo+JwXbtDtou89kdCQ84RLsVd/jW7IIy2s8eGkbj27rvqXbum85E8ju0JvVvU7iu+4nQs++jc67t9vULdnHp+e24f5Fhfzv6tjdjn6bE+bM97N584x0eqboJ1bkcBHtBrkcEyogtP1dwvGL8OzS6MsqA6vqPGHtrMaGXYK8DdDQvd1dWUTiGpl3zVwqkmMVzoElH1Ce7O2+OW98WET/epuyicRtrTOdWv+7JWtw7QLAqRukwMK45dGWU7VbLx3OGuliEbPv2x4NybiYSDGeVRYNihGBqr/GconkLcD412Esl5rAb63/3Q1bqOheCcYF40ZbsJmq16pvqUjMweBhJbmUOnbVj5qJrn35Z5QnlVQdn6YqXFT1/5L/UJZcGX1vmZpUcOG716GhwBfApgUNB9xKaXm9JzTG8sBruI92EynCNNZYK28zboOf6ZXQWA/72WuINJSek9XwvI2lAWRnNbzcLd8TaixYuuw/u4OexhcN6Bk/lgnA2lWE4/Nr3lsmgG3isLwglonDhAujx+JBDAAGbfhFv4a/OPMGTOE/wd5cNOtpguHymHk65Gxkyqt38M2AsXw8bDJFSWkNLq9N0OanfRP4Ykdlgz01rCiIMObdbKYMSOKeY5PVU4OIiIiINAvdZZQjXnnE8H1uiK+zQ3ydHebr7BBb9jD+XW3tghbjOsdxansf2/OLgcZb4ZWEDTdWfo/vh29w1izHWb9yr9dlAK9HP8LHjyQjtR2jU+Jg54Ht/tCjFNe3hbC7BtfZipuSA64bvUlT9fDyIedLwUrohBVMx3ISsJJ6YWF2B+J88Rg7Dqd8a800J87FMqWY+EQsu/Xccaro3wbszOi2xHeAYHtMuABTugnjVmAqszHl25olyGisEBGzkYizEZIA9zMcf3t8SRnYvjB+4rEavWO9nxwH9/hT8br1wffN5zhb1u/1rBk7ssjYkcWI+a9QktSOrF4nsvWok1jZZTA/vvuV5Ld4aXUp8baHbVs09Om3gES/zZMj2nJS+wA3f1EQs5vddcUu49/P5o3xaRybrqexRVoj41bghfIxFTmYUC4mlA9eCIg2IG8wGHcoWC5EivEaulecs7Hhm/oAqz+LHSAE+P7flLWp9d5UB/kALPju35SmNPCt+d07lKbUasFswGprKMaKPnz03YyadKtm2VUnFUtnUpZe9d6qWqdV9X753GhwqqZ7xaolVM1vVi2mIrGgKsWqm7Z2NaGEnfWmV+f1snbgVm6JvresaAAXA8bDDnYiFL+pJihW3R9BNCjn4q34gvKkgmgrtKppNQOsLXmz4cDYhs/3EPzdw29f1dWc5Yt2aFBHZTGmoVOcSEW0V0qRhlS1wDRUBcCKchoOWkL0c5tSNS60CWKbOGwvHttLxMtJwvJtx/YSsL0EmusCIqmymHafzmgwffsZk1nW71R2pnfnsvf/RIfc2K0cbeNxwvLZDF41l/nHno/V7acNljHeZ/HS2Hb8ZnERr2fFDg66Bp5ZXsKb68u479gUruiToHGURURERGS/KJAnR5zisMecbZXM3VbJV9khluWF2YsGd/XYFozvHGR4hwBlsXvaq6dt3lYGLZ1N/NIPa8at2xvG58c9ajBu76MxGR2xysuwcqPdbzbnJaEhgutkE/a24DpbiURyMP6SaNeXP25dd6gYB8ekYdK6YvkSsVL6R1uu1e7O0omP/l89S2VuNL2W8qOSMBEHK9AWqsetawVibYtlB7Cqgnq4ZRg7HiqzMWWbMJGy6Hh7lbuiT/PvFw+XHbjODqhYSrkf7EhbfE4GPn8qtgni4Gv+2G5SCu4JowifeBq+ld/hrFq6xxZ6dWYvyWPIkpkMWTKT8b4AWV0Hs7P/ySzvcSKFwWg3uEVhD9du/IugOuBX3dr25/0T+NeacspifIHkVHic858c/nFaW87u1tij7yLSkhi3ErP0DqjMbjCof0Szoi3ManiRhk9Efpxm/Sirt7vLRVOVXiPccAspoOHgFEBpXsNXOEXbcRtrXZW7YXd5fsQtXd94EKMir/FyiRwJLDBWJYZKPIp2T9+0glDtLlU9P1ZSkHIrGbaUY/y7sL1kHC8Zy8Q1W+vf3S32+lJ5/DQKPnyFNjNfwfIaHod59Fdv4P7wEWOOmciiwRMoTUitl8+2oGeyjwldg8zaUtng+Onbyzxu/qKAactLuGNIMhf2iFdAT0RERESaRIE8OewZY1hbFGHm5gpmbalk/s5Kwo0PV7dHvZIdxnYOMiTNXzXgeeyrN8tzab9zPUPXfM2QDV+RuW3VPq0nP7UjSf2PxqRl4nXoglUeuzu/pjCEiJh83GAunrOdiFeI59sFfhN9pLsFBO0sLw6bFEzbTKy4TBK2JOGU+SEhhdL2KVC5C3yJdYJ2e8tU5u5x3LrWKtolZxJWYrfdwb1wEeDg37wNN7KFiJ2LRx4NHbt7yyOfkJ0fHbPGXYTli8dJSMV2O+KzkrBNJxyCzXM7pl0G7rEj8Hr0g/xc8jZvpcPWvW/RCuCPhOi//mv6r/+a04Ct7Xuzq/dQ1nfoT3GHXtGuoxpRu7Vt92QfP+2bwFvry2OOn1kaMVzxcR53DEnm3qHJunEj0gpYTpAW8QMoInI4s8NYwTARSmDXdiK1n1EzPhwvGduNBvZMXhq2nRcN8tFYJL6+ei32gj4io87G+eYL7KL8BudzSgo5feHLnPbVG3zf/zTmH3seO9N71Ms3JC1ApwSH9zZVsKu84QvMlQURfv5ZPn/8pohr+idyeZ8E0uMU+RcRERGRvadAnhyWyiOGL3ZUMnNLBbO2VLChuHmeq++a6HBBjzj6tfFRHDEk+WwqSktJz8uma8UuOu/YTOdIMfGF2SQW7KTLrnX7NO5dtS09hvDlceeRc9SJXL1rHnZV67t9ZYyHRzHG2YXrZePZuXgJOUQixRh/0e6H6qND9jV/N5lOAjjxWHYAfAk1LcIsX1UfXr4ELCc+2kOnPxUixYCHldCNhE2J2OFKTHwiZR2iF7rOliIsDs/g24FmWTYEM3CP7oaJlOMLtMUr3YAJF0MoB690c7TVXrhozwtrhLHKifjLwWwn5CN6jPnBSo7DjqRiO4k4wSCW1wHbCmKb9tjY+3boBeNxBx5Hm+NPpTJ7O9bWjfhWLMbO3/duZjvvyqLzriyOrXof9gXIT+1EWfsubGvTiZ0JGfjad6CkTSZeWnuKfzTwT9ugzW2DEpm2opStpbFv4Dz2fTGfbavgz8PbMqjdvt2AEpFDIKk3VO5s3mVaTvRl+6Mt0Uz1L1nVX+MRo2NEkdbB8kWPbcuPFZcOkbLoe9uPZflr/sf246SdhFewDGwfWE50PLWq7lOdDuNwd31G9ITUVH1Odj8w57QfibvzM6q7O412feqCMThpx+PmfLl7/MCqsQSN8fAl9sdZvQRjVX/OPExN61KD27kLbvmmmnmq5zeei+1PhfxsLMuA5UW7U2X3/ybgA7eipkz79oDUj89+ar23narlxZrNabyXBWNo1d8nVgTXycd18gkDbFhOZdWlg+Ul4LgpOF4yjpeCV7wCzyrfp1Z8JjWNyOiJlEUgceZr+N3YY90B+N0wJyyfzQnLZ7Opw1EsOWoUS/udSu3+cDPiHa7qm8AXO0N8uSuE18ghsL7Y5YGvivj94iLO7R7P1f0SGNkxiH2QxjoXERERkdZLgTw5LLieYUlemM+2VTJ3eyULdoYob6iPk32UEWdzcVeHDgVbOapwA10Wb+OEnB+w87OxSouxKpqnlZxxfLjd+xIZchJpnXowsaIMr2I5NNIKzxiDoQLj5BLxCjB2Lq5bjnHy8ZIL8dyyaAs7P9Hreafq1Zz8qVj+FKz4jli+RLADWAndAQ/Ll7S7u8uqlmF1/q/dHWbt9EA7KvrHYyLldbq+NPHRPnmq/8q+q90S0bL9WAldINgOO75TdLy9yuyq8fbKMBU7MOXbm6FLTjB2RbRbThvCcYC3IvoL5AJ+GzslEcuk4dhxOIEAlleEQxyW8ce8LWMBVn4OVqgSr/9gwt37YDwXJ+sHnE1ZWDk7sNy97PO2Fn8kRPucDZCzgR4x0ksS25KXnEFZ+25sbt+brHa9cXr04uf9E3ljXTkr8mOv86vsMKNn7OInveK5YWASg9Na0gBbIlJHYh/Inb+HTBb4EqO/e76kaFfPTgJO+xG4+cuiLfvsQE0Az6q6SevrPJHI1vdjLtHpdBaRLTOi37leJPrXRDBV7512Q3BzvsR4ETDhqjwR8CJYce3xSjfVTDdV0zGRqsBEwzeqpaWyosePL6Gqm1KbOmMFWjZWIBXCRRgDEdfD5/NFH9yp6sfUisvEVGSze6zBquViYcd3BWNq5a9erg/LlxANytlBcOKif6telh2EYDKRvM/Bqg7W7W7F2tgxDuDLGE4kFLsllB2fiedr+BzPTuiCF0itXUM1nLZDMWVbY87nT59AYFmoweWGepxHKOeDetMjkQhxnS9q9HzC+HyEd+xu8WVqBfN8nc4msu0/dUpr1QrYNFZXTU2rTg9veY9oYNJQO7DpZI7G3T6r6rslAp5b9T0RwXgR7JR+eAVLwAtjvHB0bFAvhPHCWLYPEyqIPoxwiB6rM3YZEbuMCDuiE9YspiIFLOOvasGXguOmYHspOF5K9PszFtuh8JzJ/L3DGE5f8BJDf5iDvYdt6rZjFd12rOLsuc9T0W8IJ3c6mbXdhpKb2hHHthjVMciAtj6W5UX4clfDxxtA2IO31pfz1vpyMuJszugax4SucYzpFCTJr1bhIiIiIlKfAnn74ZtvvmHq1KksWrSIcDhM//79mTJlCj/5yU8OddEOa8YYNpa4fJ8bZkluiO9yw3ydHaIwtP8XlDaGXk4FA8LZDC1ez2l5yzk1dxlOSWEzlDw2E58YDeAdNzz6JGl8AnZ+Tq0x9CK4dhERrwxj5+wO1CUV4rql4A/XDdQdyLHs7CBWMA0roTtWsG30L179QJwvoUndXdYWq+vLeuPaSbOzfIlYiV13d8lpBaJj7ZVtxISKMOVbwWt87KJ95+FZxeAW4zpAPOAtiR7XLli+BJzEJCw3A8dOxPEFsIwPhx8F+RKT8foeg+ncA69NW5z1q7E3rsHO3oZVVtosJU0qzSepNB92rKY/sxkPeJZNblpXzu06gHvanclsNyPmvK6BV7PKeTWrnH5tfIzvEsdJ7QMMbuena5KDT11vyhGsRZ1TJfWp+94OYAXaYQXaYgVS8XU5Dzf/eyyr/pMxTrvjMeU7mrRay7KxbD/gr/PQTfU3g5N2UlVQpr7Gbuz7O5wPoXLwKjFeRfSvWwleBcatwBDGzV9YdcO76qZ/VYseO7kPXtGq3S2Nqv6aqhaFdmJXvNLNVWuqex5mJ3TFK9tc8954HqFwmIDfj2XbtdKrWyXubnllx3fEqwnKVE030f+tuAxMxc6a9z9uuWX5Uuu1yKoJaOBhlZdEt4Hd80RbWBmM40SDntUtJmsFzbCDVfvcjr6vDtLagWhAywliwvm1grdOTaszu83ReMVZ0SBZ1bToy4cvc1S0JZlVa7rtA2wsy9qrgE4kEqG8qIiUlBR8Pl+99MbmbSwtWguVGFMZffCmKibiS5+IVZQUc96WyPj8hMad10h6w5fErh0mtPXdOvVam6/zxDrvawc1LdtX5/3BFA0YOvUa/dlxGXiBNtE8MebzdZ5IQ2HLmuPCmOjnxK3EuBXRFoleBVZiN7z8JdFpXiUmUha9HmiGB8L2xFhhXF8eLnl1E76bSUVSYlWAL7kqwJeE7SWC8ShMyeDNM29l/rHnc+bn/0vfTd/tcV228UhY9S3nrfoWgPzkDLK6DWFdl0FszezLvaP7sDDH5XeLi1hTuOeHyrIrPKavKWP6mjKCDpyUEeDk9kFOah/gxPYB2gYV2BMRERERBfKabN68eUyaNIlAIMBFF11ESkoK7777Ltdeey2bNm3i9ttvP9RFbPWMMWwr81hZEGZlQYSV+WFWFURYWRimqBmCdgAZbiknlG1iRMEPjMhZxvHF60nwGn+CsjkY28br2I3IwOPx2iVjQrm4wZ2YcB6eW4nnFGISC3Ej5Rh/6cEL1NVhQTADO5iOFWiDldwvehPLLa3Voi5uvwN2++JwHteupbJsH1Z8B/AnRVvsRUqhfBvGLcdU7MQr3woNPFnfXIxVRsRXBmYXYQdIBNzPwQd2ciK22w7bTsL20rAtJ3r/07EwXdpjt2uHadcBe+tG7F1bsTeswc6PfSO8qWzjkZGzkYycjfyH//C3TuO4tc9VhO2Gf2JXF0ZYXVjCtOXR944FHRMcuiY5dEl0SI+zSQlEX8l+ixS/TcCBOMci4FjRv3bd90HHIuhA0LY0Hp+0Ki3unCq+CyT2xonLwAqmgz+lTisaO7F7tGvAVsI4ESJ5HzWY7us8EROJ3TXx3rT82dtAUSQSobKoiGBVsOlAtkZqLKhpRRpunfjj1lXNtd7G0uzkvnhFqxtcruw/40QI76jf4q7aj4Nx0jjLssAKRB9y8CfXTPd1nkjEDtbJa4wBrxKn3XFEts3EuKUQKcMLl+BWFuFQHm31d6AYF88pwnOKCP+od/PgVx9wUyADE8zAdMrA/PRYsrcdRdLCJcSv/GGvV9G2OLum+00A7/UEOnTryxld+/Fy26H8pawL6yv37rZLpQvzdoSYt2N3nfRJ8TGgrY+j2/oZ0NbP0ak+uif7CDo61xMRERE5kiiQ1wSRSIRbbrkFy7J4//33GTJkCAB33303Z5xxBlOnTuWCCy6gd+/eh7ikLZ8xhuwKj00lLpuKI2wqcVlbFGFVQTRoVxRu3pCNbTyGFa7m7LzvOCv3OwaVbm72YeEaYmyLcGaAym5+Kno4eMEcsD4ADASpH6g72A9f+lOrWhy0wUrqg+VPxvK3qdPd5cEM2knLZFkWBNpgBfuCW4bjJFR1x7kBEy7BVOzEhHIP7E2ZmsKAZ5XimdLoZ8cj+qtWa2w+2gBuADszAB2CWMck4BR3xb/TI7C1FN+OYuxQ8z0pbgHXb/uYISUbufroG1gXn7lX87kGtpS6bCltnrL4LKoCe1XBPcciaFukBCzaBW3axTm0C9qkxdnR90GbdnE2abX+9ysYKAdBSzynsiwH2p6A3UgrHWmdFNARObgsywInDjupJ3Zi15rpJhKhrKoVabDTWMKb3oJIESZchAkXR8dwjhQd0NZ8lolgVW6Hyu010zyg6GQo7R8g4QeXuCwXex97arcryohb/T1xq7/nJt5gChb/zjiR5zqfwZzUo/e5nGuLIqwtijBj4+5x1y2gY4JNtyQf3ZIcuiVH/2b4XSIlFk6ZS2e/UbBPRERE5DCiOxRNMHfuXNavX8/kyZNrbjgBJCcnc+edd3LNNdcwffp0/vu///uglWnzrhz+tWgdEWNFX0DEWLjGit7btgwByyOIh982BKreV//1Wx4+PHyWwYfBweBY0ffGgGssXMAzFh4m+t5Ex6ZzPYPnGVwPPOPhehD2LCo8iwrPptyzqTDRV7nnkGuC5BJHrokjlzhC1oE9DNNDRUzI+56zc79jfP4S2kYOfDDKOOAmWrjJFuE0i3CGTTjTxvgtiO6dA16GBlk+rGB6tHvKuI7RgJ0TxIrvXH+8OpG9EO2Os/vu7jjDxeBLxJRvxYRLIZSLCeVHu1oKF0bHYjmoQnhWCCgBG9w2EGoDpf0A48MpdPDnGZxCD1+RwSk0+IoM1n7cOxpWtJbvv7qbh7pfwGNdz2m0dd6BEDEQiRhKI01/GCLFCtPODpNiRwhaHnGWR8DyiLM9gpaJvrcNcbYhaHkEbROdbht8VcM4WURv4lV1TlczzYbqIZywLLM7HQsLg2VBemIc4045fv8rQ1q0lnhOJSIiB4/lT8aOSwfS60w3xoBbht3maCLbZ0G4sCrQVwRu+QEtk9vGpvgUm5JjfcStd4lb7xLY1bRzKgfDpOxFTMpexNr4TF7oMJp/dhzFzlrjPe4rA2wr89hWFmLhrh+nxsN3BUAByYRJsyu5pFOE+8YPbPL6REREROTQUyCvCT7//HMAxo4dWy+tetoXX3xxUMuUvSWL54u6HdR17rVGWpYlN5zUZH4T4bji9YwsWMWYgmUMLdmIU90ZY7wfQ5v9XofngJtsRYN1CRam6q+bGH2ZAFXjqhwKFvgSsZx4CKZh2XHR8VviO2M5fvAiWHEZ0QtgJz76N1IKth9MAOxgrf9jTTuY6S2pLP5oF0K+eLAD0apuyWU9hPVqOXEQaBv9W/sYC6ZHx0sJ52HwRQN8biUmlAfhIoxbHg0kH2RuRvRVhzFYleCUGpwyg1NqsEujf51ig69kzzdz4oDf53zEz4q/4f91GsPL7YdT6sQfkG04MIIUE6S49iRDzRhJB9qxFRsZd8rBWZccOi3xnArLAidYNU5ZzAzR77x9TjtU87aQMjlO9De0pm5b+fY027zNsNx6ddsCytSi5m3ich0nmtbivg9aYh3v47y1j9kG5rMAnDic1MGY8p110owXxkSKceJ7YMq24lXuwKvYiancxY/H69wfxg/lg6Ivu8wQt8kluMnFn9+0dfSmgj/mfMhvc2cxt01/ZrUbxEdtB7Mt2K7ZylxX9FzO5CwDFMgTERERac2sgoICDTe1j66++mreeecd5syZw9ChQ+ul9+7dG8uyWLt27cEvnIiIiEgroXMqEREREREREZHGHexRuA4LRUVFAKSkpMRMT05OrskjIiIiIrHpnEpEREREREREpHEK5ImIiIiIiIiIiIiIiIi0QArkNUH1U+MNPSFeXFzc4JPlIiIiIhKlcyoRERERERERkcYpkNcEvXv3BiArK6teWkFBAbm5uTV5RERERCQ2nVOJiIiIiIiIiDROgbwmGDFiBACffPJJvbTqadV5RERERCQ2nVOJiIiIiIiIiDTOKigoMIe6EK1NJBLhhBNOYPv27cyaNYvBgwcD0e6fzjjjDNasWcPChQvp06fPIS6piIiISMulcyoRERERERERkcapRV4T+Hw+nnrqKTzP4+yzz+aXv/wlv/71rzn11FP54YcfuOeee3TD6TCybds2nn32WS688EKOOeYYMjIy6NevH1deeSVff/11zHmKioq47777OOaYY2jfvj3HHHMM9913X4NjAEnL8pe//IXU1FRSU1P56quvYubRPm6d3n33XS644AJ69uxJhw4dGDx4MD/72c/YsmVLnXzav62LMYYZM2ZwzjnncNRRR9GxY0dOOOEEfvWrX7Fhw4Z6+bV/W46WdE71zTff8JOf/ITu3bvTqVMnxo4dyxtvvHFQ1t3aDRo0qOZ388evW2+9tV5+fQbreu211/jVr37F6NGjad++PampqUyfPr3B/E2pvzfeeIOxY8fSqVMnunfvzk9+8hO+/fbbA7E5Lcq+1O3UqVMbPI4zMzMbXMeRWLcH6/roSKvbfa1XHbMiIiIiRw61yNsPixcvZurUqSxatIhwOEz//v2ZMmUKl1xyyaEumjSj3/72tzz55JP07NmTESNGkJGRQVZWFu+//z7GGJ5//nkuvPDCmvylpaVMmDCBpUuXMmbMGIYMGcKyZcuYPXs2gwYN4sMPPyQxMfEQbpE0ZtWqVYwaNQqfz0dpaSmzZs3ixBNPrJNH+7j1McZw66238r//+7/07NmTcePGkZSUxPbt2/niiy/4xz/+wbBhwwDt39bo/vvvZ9q0aXTo0IGzzz6b5ORkli1bxieffEJSUhIzZ85kwIABgPZvS3Woz6nmzZvHpEmTCAQCXHTRRaSkpPDuu++yceNGHnjgAW6//faDUo7WatCgQRQWFjJlypR6acceeywTJkyoea/PYH2DBg1i8+bNpKWlkZCQwObNm5k2bRqTJ0+ul7cp9ff444/zhz/8gS5dunD++edTWlrKW2+9RUVFBW+++SYjR448WJt60O1L3U6dOpVHHnmEyy+/nG7dutVJ8/l83HnnnfXmOVLr9mBcHx2Jdbuv9apjVkREROTIoUCeyB7MmDGD9PR0hg8fXmf6/PnzOf/880lKSmLlypUEg0EAHnroIf70pz/xy1/+kt/97nc1+aun33XXXdx3330HdRtk77iuy/jx47Esi969e/P666/HDORpH7c+f/3rX7nnnnu49tprefjhh3Ecp056JBLB5/MB2r+tzc6dOzn66KPp0qULn3/+OSkpKTVpzz77LPfddx+TJ09m2rRpgPav1BeJRDjxxBPZtm0bH330EUOGDAHqdu/55Zdf0rt370Nc0pZr0KBBACxdunSPefUZrG/OnDn06tWLbt268cQTT/C73/2uwWDTvtZfVlYWJ598Mj169ODjjz+mTZs2APzwww+MGzeOzMxMvvrqq5rfwMPNvtRtdVDk3Xff3atgxpFctwf6+uhIrdt9rVcdsyIiIiJHDnWtKbIH5513Xr2LKYDhw4czcuRI8vPzWbFiBRBt9fOvf/2LpKQk7rrrrjr5b7vtNlJTU3nppZcwRvHzlujJJ59k2bJlPPPMM/UCPdW0j1uf8vJyHnnkEXr06MHUqVNj7tvqGxbav63Ppk2b8DyPU045pU4QD+DMM88EICcnB9D+ldjmzp3L+vXrufjii2uCeADJycnceeedRCKRRrs5lL2nz2Bso0ePrteaJpam1N/06dOJRCLcfvvtNTftAY4++mguu+wy1q9fz9y5c5tvY1qYva3bpjiS6/ZAXx8dqXW7L/XaFEdqvYqIiIgcDhTIE9kPfr8foCYwkJWVxfbt2zn55JPrdQ8TFxfH8OHD2bZtG+vWrTvoZZXGrVixgkceeYQ77riDo48+usF82setz6effkp+fj4TJ07EdV1mzJjBE088wQsvvFBvP2n/tj69e/cmEAiwcOFCiouL66R99NFHADVPqWv/Siyff/45AGPHjq2XVj3tiy++OKhlao1CoRAvv/wyjz/+OM8//3zM1nn6DO6fptSfju99t2DBAv7yl7/w9NNPM3PmTCorK2PmU93G1hzXR6rb+n5cr7XpmBURERE5/KnPBJEm2rx5M3PmzCEzM5OBAwcC0QtVgF69esWcp7pbrqysLHXR1YJEIhFuuOEG+vXrx6233tpoXu3j1ufbb78Foq3uTj31VNasWVOTZts2N9xwAw8++CCg/dsatWvXjgceeIAHHniAk08+mbPOOoukpCRWrFjBnDlz+K//+i+uu+46QPtXYqs+LmLt89TUVNLS0mrySMN27tzJDTfcUGfa6aefzt/+9jfS0tIAfQb3V1PqLysri6SkJDIzMxvNL7s99NBDdd536NCB5557jjFjxtSZrrqtr7muj1S3dcWq19p0zIqIiIgc/tQiT6QJwuEw1113HZWVlfzud7+reTKyqKgIoE5XJbUlJyfXySctw+OPP17TpWb1064N0T5ufaq7VXzmmWdITk7mk08+YcuWLXzwwQf06dOHZ555hueffx7Q/m2tbr75Zv7xj39QVFTE888/z1/+8hdmzZrFcccdxyWXXFLzudb+lViq9/ePu2atlpycrGNiD37605/y3nvvkZWVxebNm5k9ezbjx49n9uzZXH755TVd5ukzuH+aUn9FRUWNHts/zn8kGzRoEM899xxLlixhx44dfPPNN9x///0UFhZy+eWX12tlqrqtqzmvj1S3uzVUr6BjVkRERORIokCeyD7yPI8bb7yR+fPnc/XVV3PZZZcd6iLJfli6dCmPPfYYN998M0OHDj3UxZEDwPM8AAKBANOnT+e4444jKSmJ4cOH889//hPbtnnmmWcOcSllfzz66KPccMMN3HrrrSxfvpytW7fy4YcfEolEOPfcc5kxY8ahLqLIYe3uu+/m1FNPJS0tjeTkZE444QRee+01hg0bxqJFi2q6uRVpyc455xwuv/xyunXrRlxcHL169eLOO+/k4YcfpqKigscee+xQF7HF0vXRgbGnetUxKyIiInLkUCBPZB8YY7jlllt4/fXXueSSS3jiiSfqpFc/4VhYWBhz/urxmxp6ElIOvilTptCzZ0/uueeevcqvfdz6VO+LoUOH0rFjxzppRx99ND169GD9+vUUFBRo/7ZCn332GX/84x+59tpruf322+ncuTOJiYmccsopvPbaa8THx3PfffcB+vxKbNX7u6FWCMXFxTommsC2ba644goAvvzyS0Cfwf3VlPpLSUlp9Nj+cX6p7/LLL8fn89Ucx9VUt1EH4vpIdbvnem2MjlkRERGRw48CeSJ7yfM8brrpJl566SUuvvhinnvuOWy77keoemyB2oO119bYODxyaCxbtozVq1eTmZlJampqzeuVV14BYPz48aSmpvLee+8B2setUd++fYGGu3Sqnl5RUaH92wpVt/QZOXJkvbT09HQGDBjAli1byM3N1f6VmBobF6igoKDOsSP7pnpsvLKyMkC/ofurKfXXu3dvSkpK2Llz517ll/oCgQBJSUk1x3E11e2Buz460ut2b+q1MTpmRURERA4/CuSJ7AXP87j55puZPn06F110EX/729/qjE9QrXfv3nTs2JEvv/yS0tLSOmkVFRXMnz+fjh07NjjYuxx8V155ZcxX9UXsWWedxZVXXkm3bt0A7ePWqDrAs3r16npp4XCYdevWkZiYSHp6uvZvKxQKhYDdYyH+WPX0QCCg/SsxjRgxAoBPPvmkXlr1tOo8sm8WL14MoN/QZtKU+tPxvf+ysrIoKCioOY6rHel1eyCvj47kut3bem2MjlkRERGRw48CeSJ7UP1E5PTp07ngggv4+9//3uDFlGVZXHnllZSUlPCnP/2pTtqf//xnCgoKuPLKK7Es62AUXfbC008/HfN10kknAXDbbbfx9NNPM3jwYED7uDXq2bMnY8eOZd26dbz44ot10p544gkKCwuZOHEiPp9P+7cVOuWUUwB49tln63Xb9fLLL7Nu3TqGDh1KcnKy9q/EdNppp9GjRw/+7//+jyVLltRMLy4u5tFHH8Xn89V0ESn1rVy5koKCgnrTFyxYwLRp0wgGg5x77rmAfkP3V1Pqb/Lkyfh8Ph5//PE635E//PADr776Kj179mTUqFEHbRtaquLiYpYtW1ZvekFBATfddBMAF198cZ20I7luD/T10ZFat/tSrzpmRURERI4sVkFBgTnUhRBpyaZOncojjzxCUlIS119/fcyLqYkTJ9YEekpLS5kwYQJLly5lzJgxDB06lGXLljFr1iwGDRrEhx9+SGJi4sHeDNlHU6ZM4ZVXXmHWrFmceOKJddK0j1uf9evXc8YZZ5Cdnc2ZZ55J3759WbJkCXPnzqVr167Mnj2bzMxMQPu3tXFdl/PPP5/PP/+c9PR0zjrrLFJTU1m2bBmffvopwWCQf//73wwbNgzQ/pXY5s6dy6RJkwgGg0yaNInk5GTeffddNm7cyK9//WvuuOOOQ13EFmvq1Kk89dRTjBo1im7duhEMBvnhhx/45JNPsG2bJ554gquuuqomvz6D9b344ossWLAAgBUrVvD9999zyimn0LNnTyB6nnnOOecATau/xx57jAcffJAuXbpw/vnnU1ZWxptvvkl5eTlvvvnmYX3jfm/rduPGjQwZMoRjjz2WAQMGkJGRwbZt25g9ezZ5eXmMGTOG1157jUAgUGf5R2rdHozroyOxbvelXnXMioiIiBxZFMgT2YPqgE5jpk2bxuTJk2veFxYW8sgjjzBjxgx27txJZmYm5513HnfffXeD43RJy9JYIA+0j1ujLVu28NBDD/Hxxx+Tl5dHZmYmZ511FnfddRcZGRl18mr/ti6VlZX89a9/5a233mLNmjWEQiHat2/PiBEjuPXWWxkwYECd/Nq/EsvixYuZOnUqixYtIhwO079/f6ZMmcIll1xyqIvWon3++ec8//zzfP/992RnZ1NRUUH79u055ZRTuOGGGzj++OPrzaPPYF17Ote8++67uffee2veN6X+Xn/9dZ577jlWrlyJ3+/npJNO4r777uO4445r9u1pSfa2bouKivjDH/7AV199xebNmyksLCQhIYGBAwdyySWXcNVVVzXYMupIrNuDdX10pNXtvtSrjlkRERGRI4sCeSIiIiIiIiIiIiIiIiItkMbIExEREREREREREREREWmBFMgTERERERERERERERERaYEUyBMRERERERERERERERFpgRTIExEREREREREREREREWmBFMgTERERERERERERERERaYEUyBMRERERERERERERERFpgRTIExEREREREREREREREWmBFMgTERERERERERERERERaYEUyBMRERERERERERERERFpgRTIExERERERkX0yaNAgUlNTmTdv3qEuioiIiIiIyGHNd6gLICISS2pqapPmmzZtGpMnT27ewoiIiIgcRDoPEhERERERkWoK5IlIi3TKKafEnL5w4UIAevfuTUZGRr309u3bH9ByiYiIiBxoOg8SERERERGRagrkiUiL9OGHH8acXv2E+m233aYnzkVEROSwpPMgERERERERqaYx8kRERERERERERERERERaIAXyROSwMnv2bC677DL69u1LRkYG/fr1Y/LkycydOzdm/nnz5pGamsqgQYMAePXVV5kwYQLdu3cnNTWVJUuW1OTdsGED1113Hf369SMzM5Pjjz+eBx98kPLycqZMmUJqaipTp06ts/zp06eTmprKxIkTGyzzxIkTSU1NZfr06THTs7Oz+d3vfsfw4cPp0qULHTt2ZNiwYfzxj3+ksLBwX6tIREREDlP7eh5UbdWqVdx4440MGjSI9u3b0717d84++2xefPFFXNc9YOUdOHAgqampfPvtt/XSRowYQWpqKkcddVS9tI0bN5KamkrXrl2JRCL10hcsWMA111zDgAEDaN++PT169OCCCy7gnXfeiVmOUCjEjBkzuPHGGxk+fDg9evQgMzOTQYMGcf3117NixYqY81WXo7ql5MyZM7nwwgvp1asXqampvPfee/tQGyIiIiIiIrEpkCcih417772Xiy++uKY7qkGDBuG6Lu+//z7nnXdevSDbj911111cf/31rF+/nt69e9cZZ+a7775j1KhRvPbaaxQUFNTcVHrsscc499xzCYfDB2SbFi5cyMknn8wTTzzBmjVr6NChA127dmXNmjU8+uijjB07lq1btx6QdYuIiEjr0dTzoLfffpuRI0cyffp08vLyGDBgAG3atGH+/PnccsstXHrppVRUVByQMp966qkAfPbZZ3Wm5+bm1gTPdu7cycqVK+ukV+cfNmwYPl/d0SJ++9vfctZZZ/HWW29RUlLCUUcdRTAYZM6cOVx99dXcdttt9cqxdu1arrrqKl555RVyc3Pp1q0bvXr1Ij8/n1dffZUxY8Ywc+bMRrfl6aef5tJLL+X777+nR48edOnSZd8qQ0REREREpAEK5InIYeHll1/mueeew3Ec/vznP7Nq1So++eQTVq9ezR/+8Acsy+KRRx5p8Mnobdu28eKLL/L888/XzLty5Ur69+9PZWUl11xzDUVFRYwcOZLly5czd+5cFi9ezMyZM1m/fn2DT3jvj61bt3L55ZeTl5fHddddx5o1a/j6669ZtGgRy5cvZ/z48WRlZfGLX/yi2dctIiIirUdTz4NWr17NlClTCIVCXHXVVaxevZo5c+awZMkS3n77bVJSUpg9eza//e1vD0i5R40aBVCvxeC8efMwxtC5c+cG0wFGjhxZZ/rzzz/Pk08+SVpaGv/zP//Dpk2bmDdvHqtWreLtt98mIyODF154oV4vCOnp6fztb38jKyuLVatWMXfuXBYsWEBWVhaPPvookUiEG264gbKysga35fe//z1Tp05lzZo1fPLJJyxbtozTTz+9aRUjIiIiIiJSiwJ5InJYePTRRwG45ppruOaaa7Dt6Neb4zjcfPPN/OQnPwHgkUceiTm/67rcc889TJo0qWaabdsEAgHefvtt1q1bR3x8PP/zP/9DRkZGTZ6TTz6Zhx9++IC0yPvzn/9Mfn4+kyZN4pFHHqnptgkgMzOTF154gU6dOvHFF1/w1VdfNfv6RUREpHVo6nnQU089RUVFBQMGDOAvf/kLiYmJNWljxozhwQcfBOCFF14gOzu72ctdHYhbuHAhoVCoZnp14O6OO+6o875arEBeWVkZDz30EAB///vfufDCC+vMM2bMGB5//HEAnnzyyTpp7du359JLL6Vt27Z1pgeDQa699lomTZpEbm5uo63yrrzySqZMmYLjODXT4uLiGswvIiIiIiKytxTIE5FWb/Xq1axfvx6Am266KWaeW265BYClS5eyffv2mHkmT54cc/qsWbMAuPjii0lPT6+XftFFF9GhQ4d9LveeVLfy+6//+q+Y6cnJyYwePRqof4NLREREjgz7cx5UfY5z4403YllWvfkuv/xyMjIyCIVCzJkzp5lLDt26daNHjx6UlZXVeShp7ty5xMfHc8UVV9CxY0e++OILPM8DouP57dixg9TUVAYPHlwzz7x588jNzaVr166MGzcu5vrOOuss/H4/a9asiXk++Nlnn3H//fdz6aWXcvbZZzNhwgQmTJjA/PnzAfj+++8b3Jaf/vSnTaoDERERERGRPfHtOYuISMu2Zs0aAJKSkujevXvMPP3798dxHFzXZfXq1XTs2LFOelpaWp2WdrWtXr0aoGZcvB9zHIc+ffqwY8eOpm5CPdu3bycnJweIjvXi9/tj5tu8eTMQ7RpUREREjjxNPQ8qLCxk586dAAwcODDmfH6/n759+5KdnV1zPtTcRo4cyYYNG5g7dy4jRoxg+/btrF27ltGjRxMMBhk5ciSvv/46S5YsYejQoTUPL40YMaKm5SHAsmXLACgqKmLChAkNrq86YLlt27aa88GSkhKuvPJKPv3000bLmpeX12BaQ+eJIiIiIiIi+0uBPBFp9UpKSoBot0gN8fl8pKWlsWvXrpr8tSUkJOzX8htLa4qCgoKa/xcvXrzH/I2N2SIiIiKHr6aeB9U+H2ps3upeB2KdPzWHUaNG8a9//Yu5c+dy77338tlnn9VMB2oCefPmzasTyKtOr1Z97lRYWMjChQv3uN7a504PPPAAn376KWlpafzmN79h5MiRdOjQgfj4eAD++Mc/8uijjzbalXrtbklFRERERESakwJ5ItLqJSUlATQ6dkskEiE3N7dO/n1d/q5duxrM01Ba9VPfxpgG540VhKt9M2jDhg11xscTERERqdbU86Da50O7du2iU6dOMeet7nFgX8+f9lb1OHeLFy+mrKysZvy76kDdaaedBkS7zrzpppv44osv6sxXrfrcaeLEiUyfPn2v1x+JRHjjjTcAeO655zjjjDPq5cnPz9+XTRIREREREWlWGiNPRFq9fv36AVBcXMymTZti5lm1ahWu69bJv6/LX7VqVcx013VZu3ZtzLTqm0qN3VzLysqqN61z5860adMGgEWLFu1TeUVEROTI0dTzoDZt2pCZmQnAihUrYs4XiURqznEOVNeRHTp0oF+/foRCIRYsWMC8efNISUnh2GOPBaLj6HXv3p0FCxbw3XffkZeXR0ZGBgMGDKiznOr3X3/9dc14ensjJyenprXhsGHDYub58ssvm7JpIiIiIiIizUKBPBFp9fr27UuvXr0AmDZtWsw8Tz/9NACDBw+uNz7enpx++ukAvPnmmzVPs9f29ttvNzg+XnW5Nm7cGLPV3uuvv05RUVG96Y7jcN555wHwxBNP1Nx8ExEREaltf86DqlufPfvsszF7D3j11VfZtWsXwWCwpmXcgVDduu7FF19k06ZNDBs2DMdxatJHjRpFcXExTz75JACnnnpqvWWMGTOGNm3asHPnTv75z3/u9bqru88EYp7PzZkzh6VLl+718kRERERERJqbAnkicli44447AHj++ed58cUXa25GeZ7Hs88+y2uvvQbAXXfdtc/LvvDCC+nRowdlZWX87Gc/Iycnpybtq6++4t5778Xv98ecd+DAgXTr1o1QKMSdd95ZpxvNzz77rNF577rrLtq1a8eCBQuYPHkyGzZsqJPuui7z58/npptuYtu2bfu8XSIiInJ4aOp50M0330xcXBzLli3j9ttvr3ee8utf/xqAa665hoyMjANW/upuNGfMmFHn/d6mAyQnJ/PAAw8AcPfddzNt2jTKy8vr5CkoKODVV1+tyQfRlonHHHMMAPfcc0+dcYrnzp3Lz372M+Li4vZn80RERERERPaLAnkicli44ooruP7664lEItxyyy0cddRRjB07ln79+nHfffdhjOGuu+7inHPO2edlx8XF8cILL5CSksKcOXMYMGAAp512GieccALjx4+ne/funH/++THntW2bhx56CNu2eeedd+jXrx+nnXYaxxxzDOeffz5nnXUWJ510Usx5u3btyhtvvEHHjh358MMPGTp0KMceeyzjx49n+PDhdOnShbPPPpuXXnqJcDi8z9slIiIih4emngf169eP5557jkAgwAsvvEC/fv0YM2YMQ4cO5fzzz6egoIBx48bxm9/85oCW/9RTT8WyrJoAZEOBvOr0H4+PV+3nP/859913H+FwmPvvv5+ePXsycuRIxo0bx5AhQ+jZsyfXX38933zzTZ35fv/73+M4Dh9//DEDBw5k1KhRDBkyhPPOO49OnTpx7bXXNvcmi4iIiIiI7DUF8kTksPHwww/zxhtvcOaZZ+J5HkuWLMGyLM4++2zeeecd7rvvviYv+7jjjuOzzz7jkksuISUlhZUrV+J5Hrfffjvvvvtug63qAM455xzefPNNRowYAcCaNWtIT0/nqaee4plnnml0vccffzwLFy7kN7/5DSeddBJ5eXl89913FBYWcswxx3DLLbcwc+ZMunXr1uRtExERkdavqedBF154IXPnzuWKK64gNTWV5cuXk5eXx7Bhw3jqqad4/fXXD3iLtLS0tJox7tLS0mpayFXLzMykf//+AHTq1Ik+ffo0uKy77rqLuXPnctVVV9GpUyfWrl3LypUr8fv9nH766fzpT3/i73//e515xo4dy7vvvsvo0aOxLIs1a9YQDAa54447mDlzJgkJCc28xSIiIiIiInvPKigoqD8YgoiI7JMpU6bwyiuvcPfdd3Pvvfce6uKIiIiIiIiIiIiIyGFALfJEREREREREREREREREWiAF8kRERERERERERERERERaIN+hLoCIiIiIiIi0bldffTU7d+7c6/yPPPIIQ4YMOYAlEhEREREROTwokCciIiIiIiL75ZtvvmHz5s17nb+oqOgAlkZEREREROTwYRUUFJhDXQgRERERERERERERERERqUtj5ImIiIiIiIiIiIiIiIi0QArkiYiIiIiIiIiIiIiIiLRACuSJiIiIiIiIiIiIiIiItEAK5ImIiIiIiIiIiIiIiIi0QArkiYiIiIiIiIiIiIiIiLRACuSJiIiIiIiIiIiIiIiItEAK5ImIiIiIiIiIiIiIiIi0QArkiYiIiIiIiIiIiIiIiLRACuSJiIiIiIiIiIiIiIiItED/P0bPHLMwd+07AAAAAElFTkSuQmCC"},"metadata":{}}]},{"cell_type":"markdown","source":"<div style=\"color:white;\n           display:fill;\n           border-radius:5px;\n           background-color:#4270c5;\n           font-size:110%;\n           font-family:sans-serif;\n           letter-spacing:0.2px\">\n\n<p style=\"padding: 30px;\n              color:white;\">\nREASONS FOR THE MACHINE FAILURES\n</p>\n</div>","metadata":{}},{"cell_type":"code","source":"eda.plot_machine_reasons(train)","metadata":{"execution":{"iopub.status.busy":"2023-06-25T01:36:44.669684Z","iopub.execute_input":"2023-06-25T01:36:44.670788Z","iopub.status.idle":"2023-06-25T01:36:44.888944Z","shell.execute_reply.started":"2023-06-25T01:36:44.670762Z","shell.execute_reply":"2023-06-25T01:36:44.887217Z"},"trusted":true},"execution_count":78,"outputs":[{"output_type":"display_data","data":{"text/plain":"<Figure size 800x600 with 1 Axes>","image/png":"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"},"metadata":{}}]},{"cell_type":"markdown","source":"<div style=\"color:white;\n           display:fill;\n           border-radius:5px;\n           background-color:#4270c5;\n           font-size:110%;\n           font-family:sans-serif;\n           letter-spacing:0.2px\">\n\n<p style=\"padding: 30px;\n              color:white;\">\nOUTLIERS\n</p>\n</div>","metadata":{}},{"cell_type":"code","source":"eda.plot_outliers(train,columns_to_plot)","metadata":{"execution":{"iopub.status.busy":"2023-06-25T01:36:44.893391Z","iopub.execute_input":"2023-06-25T01:36:44.893698Z","iopub.status.idle":"2023-06-25T01:36:45.524585Z","shell.execute_reply.started":"2023-06-25T01:36:44.893675Z","shell.execute_reply":"2023-06-25T01:36:45.52332Z"},"trusted":true},"execution_count":79,"outputs":[{"output_type":"display_data","data":{"text/plain":"<Figure size 1000x600 with 5 Axes>","image/png":"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"},"metadata":{}}]},{"cell_type":"markdown","source":"<div style=\"color:white;\n           display:fill;\n           border-radius:5px;\n           background-color:#4270c5;\n           font-size:110%;\n           font-family:sans-serif;\n           letter-spacing:0.2px\">\n\n<p style=\"padding: 30px;\n              color:white;\">\ntRAIN DATASET NORMALIZATION\n</p>\n</div>","metadata":{}},{"cell_type":"code","source":"train_updated = data.set_feature(train)\ntrain_updated.drop(columns=['id','Product_ID'],axis=1,inplace=True)\ntrain_updated.head()","metadata":{"execution":{"iopub.status.busy":"2023-06-25T01:36:45.525497Z","iopub.execute_input":"2023-06-25T01:36:45.525736Z","iopub.status.idle":"2023-06-25T01:36:45.573059Z","shell.execute_reply.started":"2023-06-25T01:36:45.525712Z","shell.execute_reply":"2023-06-25T01:36:45.572366Z"},"trusted":true},"execution_count":80,"outputs":[{"execution_count":80,"output_type":"execute_result","data":{"text/plain":"   Type  Air_temperature  Process_temperature  Rotational_speed  Torque  \\\n0     1            300.6                309.6              1596    36.1   \n1     2            302.6                312.1              1759    29.1   \n2     1            299.3                308.5              1805    26.5   \n3     1            301.0                310.9              1524    44.3   \n4     2            298.0                309.0              1641    35.4   \n\n   Tool_wear  Machine_failure  TWF  HDF  PWF  OSF  RNF  \n0        140                0    0    0    0    0    0  \n1        200                0    0    0    0    0    0  \n2         25                0    0    0    0    0    0  \n3        197                0    0    0    0    0    0  \n4         34                0    0    0    0    0    0  ","text/html":"<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>Type</th>\n      <th>Air_temperature</th>\n      <th>Process_temperature</th>\n      <th>Rotational_speed</th>\n      <th>Torque</th>\n      <th>Tool_wear</th>\n      <th>Machine_failure</th>\n      <th>TWF</th>\n      <th>HDF</th>\n      <th>PWF</th>\n      <th>OSF</th>\n      <th>RNF</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>1</td>\n      <td>300.6</td>\n      <td>309.6</td>\n      <td>1596</td>\n      <td>36.1</td>\n      <td>140</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>2</td>\n      <td>302.6</td>\n      <td>312.1</td>\n      <td>1759</td>\n      <td>29.1</td>\n      <td>200</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>1</td>\n      <td>299.3</td>\n      <td>308.5</td>\n      <td>1805</td>\n      <td>26.5</td>\n      <td>25</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>1</td>\n      <td>301.0</td>\n      <td>310.9</td>\n      <td>1524</td>\n      <td>44.3</td>\n      <td>197</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>2</td>\n      <td>298.0</td>\n      <td>309.0</td>\n      <td>1641</td>\n      <td>35.4</td>\n      <td>34</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n    </tr>\n  </tbody>\n</table>\n</div>"},"metadata":{}}]},{"cell_type":"code","source":"y = data.set_label(train)\nX_resampled,y_resampled = data.reduce_oversampling(train_updated,y)\nX_train,X_val,y_train,y_val = data.random_split_data(X_resampled,y_resampled)\nprint(X_train.shape,X_val.shape,y_train.shape,y_val.shape)","metadata":{"execution":{"iopub.status.busy":"2023-06-25T01:36:45.574276Z","iopub.execute_input":"2023-06-25T01:36:45.574754Z","iopub.status.idle":"2023-06-25T01:36:56.696218Z","shell.execute_reply.started":"2023-06-25T01:36:45.574731Z","shell.execute_reply":"2023-06-25T01:36:56.695272Z"},"trusted":true},"execution_count":81,"outputs":[{"name":"stdout","text":"(214849, 12) (53713, 12) (214849,) (53713,)\n","output_type":"stream"}]},{"cell_type":"code","source":"num_col_names = ['Air_temperature','Process_temperature','Rotational_speed','Torque','Tool_wear']\ncat_col_names = ['Type','TWF','HDF','PWF','OSF','RNF']","metadata":{"execution":{"iopub.status.busy":"2023-06-25T01:36:56.713358Z","iopub.execute_input":"2023-06-25T01:36:56.714426Z","iopub.status.idle":"2023-06-25T01:36:56.723157Z","shell.execute_reply.started":"2023-06-25T01:36:56.714395Z","shell.execute_reply":"2023-06-25T01:36:56.722365Z"},"trusted":true},"execution_count":83,"outputs":[]},{"cell_type":"code","source":"std_X_train = data.standardization_data(X_train)\nstd_X_val = data.standardization_data(X_val)\nprint(std_X_train[0],std_X_val[0])","metadata":{"execution":{"iopub.status.busy":"2023-06-25T01:36:56.724351Z","iopub.execute_input":"2023-06-25T01:36:56.724869Z","iopub.status.idle":"2023-06-25T01:36:56.774629Z","shell.execute_reply.started":"2023-06-25T01:36:56.724841Z","shell.execute_reply":"2023-06-25T01:36:56.773085Z"},"trusted":true},"execution_count":84,"outputs":[{"name":"stdout","text":"[-0.27822181 -1.72018222 -1.32389097 -0.96206009  0.92759186  1.13736702\n  0.99979057 -0.17967389 -0.45829591 -0.21741065  2.99836435 -0.03358039] [-0.27148309  0.01838727 -0.65203409  0.17594555  0.52073436 -1.61905775\n -0.99916256 -0.17846828 -0.45322008 -0.21394658 -0.33487232 -0.03507513]\n","output_type":"stream"}]},{"cell_type":"markdown","source":"<div style=\"color:white;\n           display:fill;\n           border-radius:5px;\n           background-color:#4270c5;\n           font-size:110%;\n           font-family:sans-serif;\n           letter-spacing:0.2px\">\n\n<p style=\"padding: 30px;\n              color:white;\">\nPYTORCH TABULAR CONFIG CLASS\n</p>\n</div>","metadata":{}},{"cell_type":"code","source":"class Configs:\n    \n    \"\"\"Data Configuration\"\"\"\n    data_config = DataConfig(\n    target=['Machine_failure'], \n    continuous_cols=num_col_names,\n    categorical_cols=cat_col_names,\n    )\n    \n    \"\"\"Trainer Configuration\"\"\"\n    trainer_config = TrainerConfig(\n    auto_lr_find=True, # Runs the LRFinder to automatically derive a learning rate\n    batch_size=256,\n    max_epochs=10,\n    early_stopping=\"valid_loss\", # Monitor valid_loss for early stopping\n    early_stopping_mode = \"min\", # Set the mode as min because for val_loss, lower is better\n    early_stopping_patience=5, # No. of epochs of degradation training will wait before terminating\n    checkpoints=\"valid_loss\", # Save best checkpoint monitoring val_loss\n    load_best=True, # After training, load the best checkpoint\n#     accelerator=\"cpu\"\n    )\n    \n    \"\"\"Optimizer Configuration\"\"\"\n    optimizer_config = OptimizerConfig()\n    \n    head_config = LinearHeadConfig(\n    layers=\"\", # No additional layer in head, just a mapping layer to output_dim\n    dropout=0.1,\n    initialization=\"kaiming\"\n    ).__dict__ \n    \n    \"\"\"Model Configuration\"\"\"\n    model_config = CategoryEmbeddingModelConfig(\n    task=\"classification\",\n    layers=\"8-4-4\",  # Number of nodes in each layer\n    activation=\"LeakyReLU\", # Activation between each layers\n    head = \"LinearHead\", #Linear Head\n    head_config = head_config, # Linear Head Config\n    learning_rate = 1e-3,\n    metrics=[\"f1_score\",\"accuracy\"], \n    metrics_params=[{\"num_classes\":2},{}],\n    metrics_prob_input=[True, False]\n)\n    \nconfig = Configs()","metadata":{"execution":{"iopub.status.busy":"2023-06-25T01:36:56.776364Z","iopub.execute_input":"2023-06-25T01:36:56.776838Z","iopub.status.idle":"2023-06-25T01:36:56.785695Z","shell.execute_reply.started":"2023-06-25T01:36:56.776781Z","shell.execute_reply":"2023-06-25T01:36:56.78465Z"},"trusted":true},"execution_count":85,"outputs":[]},{"cell_type":"markdown","source":"<div style=\"color:white;\n           display:fill;\n           border-radius:5px;\n           background-color:#4270c5;\n           font-size:110%;\n           font-family:sans-serif;\n           letter-spacing:0.2px\">\n\n<p style=\"padding: 30px;\n              color:white;\">\nPYTORCH TABULAR TRAINER CLASS\n</p>\n</div>","metadata":{}},{"cell_type":"code","source":"class Trainer:\n    \n    \"\"\"Training Configuration\"\"\"\n    tabular_model = TabularModel(\n    data_config=config.data_config,\n    model_config=config.model_config,\n    optimizer_config=config.optimizer_config,\n    trainer_config=config.trainer_config,\n)","metadata":{"execution":{"iopub.status.busy":"2023-06-25T01:36:56.786918Z","iopub.execute_input":"2023-06-25T01:36:56.787213Z","iopub.status.idle":"2023-06-25T01:36:56.848483Z","shell.execute_reply.started":"2023-06-25T01:36:56.787188Z","shell.execute_reply":"2023-06-25T01:36:56.847221Z"},"trusted":true},"execution_count":86,"outputs":[{"name":"stderr","text":"2023-06-25 01:36:56,820 - {pytorch_tabular.tabular_model:105} - INFO - Experiment Tracking is turned off\n","output_type":"stream"}]},{"cell_type":"markdown","source":"<div style=\"color:white;\n           display:fill;\n           border-radius:5px;\n           background-color:#4270c5;\n           font-size:110%;\n           font-family:sans-serif;\n           letter-spacing:0.2px\">\n\n<p style=\"padding: 30px;\n              color:white;\">\nMODEL TRAINING\n</p>\n</div>","metadata":{}},{"cell_type":"code","source":"trainer = Trainer()\ntrainer.tabular_model.fit(train=X_train, validation=X_val)\n","metadata":{"execution":{"iopub.status.busy":"2023-06-25T01:36:56.850004Z","iopub.execute_input":"2023-06-25T01:36:56.850252Z","iopub.status.idle":"2023-06-25T01:41:22.192024Z","shell.execute_reply.started":"2023-06-25T01:36:56.850231Z","shell.execute_reply":"2023-06-25T01:41:22.190642Z"},"trusted":true},"execution_count":87,"outputs":[{"name":"stderr","text":"2023-06-25 01:36:56,854 - {pytorch_tabular.tabular_model:473} - INFO - Preparing the DataLoaders\n2023-06-25 01:36:56,857 - {pytorch_tabular.tabular_datamodule:290} - INFO - Setting up the datamodule for classification task\n2023-06-25 01:36:57,120 - {pytorch_tabular.tabular_model:521} - INFO - Preparing the Model: CategoryEmbeddingModel\n2023-06-25 01:36:57,168 - {pytorch_tabular.tabular_model:268} - INFO - Preparing the Trainer\n2023-06-25 01:36:57,234 - {pytorch_tabular.tabular_model:573} - INFO - Auto LR Find Started\n","output_type":"stream"},{"output_type":"display_data","data":{"text/plain":"Finding best initial lr:   0%|          | 0/100 [00:00<?, ?it/s]","application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"298d1094a31e4878b573b875bfa304c1"}},"metadata":{}},{"name":"stderr","text":"2023-06-25 01:36:59,357 - {pytorch_tabular.tabular_model:575} - INFO - Suggested LR: 0.8317637711026709. For plot and detailed analysis, use `find_learning_rate` method.\n2023-06-25 01:36:59,358 - {pytorch_tabular.tabular_model:582} - INFO - Training Started\n","output_type":"stream"},{"output_type":"display_data","data":{"text/plain":"┏━━━┳━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━┓\n┃\u001b[1;35m \u001b[0m\u001b[1;35m \u001b[0m\u001b[1;35m \u001b[0m┃\u001b[1;35m \u001b[0m\u001b[1;35mName            \u001b[0m\u001b[1;35m \u001b[0m┃\u001b[1;35m \u001b[0m\u001b[1;35mType                     \u001b[0m\u001b[1;35m \u001b[0m┃\u001b[1;35m \u001b[0m\u001b[1;35mParams\u001b[0m\u001b[1;35m \u001b[0m┃\n┡━━━╇━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━┩\n│\u001b[2m \u001b[0m\u001b[2m0\u001b[0m\u001b[2m \u001b[0m│ _backbone        │ CategoryEmbeddingBackbone │    200 │\n│\u001b[2m \u001b[0m\u001b[2m1\u001b[0m\u001b[2m \u001b[0m│ _embedding_layer │ Embedding1dLayer          │     48 │\n│\u001b[2m \u001b[0m\u001b[2m2\u001b[0m\u001b[2m \u001b[0m│ head             │ LinearHead                │     10 │\n│\u001b[2m \u001b[0m\u001b[2m3\u001b[0m\u001b[2m \u001b[0m│ loss             │ CrossEntropyLoss          │      0 │\n└───┴──────────────────┴───────────────────────────┴────────┘\n","text/html":"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">┏━━━┳━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━┓\n┃<span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">   </span>┃<span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\"> Name             </span>┃<span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\"> Type                      </span>┃<span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\"> Params </span>┃\n┡━━━╇━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━┩\n│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 0 </span>│ _backbone        │ CategoryEmbeddingBackbone │    200 │\n│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 1 </span>│ _embedding_layer │ Embedding1dLayer          │     48 │\n│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 2 </span>│ head             │ LinearHead                │     10 │\n│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 3 </span>│ loss             │ CrossEntropyLoss          │      0 │\n└───┴──────────────────┴───────────────────────────┴────────┘\n</pre>\n"},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"\u001b[1mTrainable params\u001b[0m: 258                                                                                              \n\u001b[1mNon-trainable params\u001b[0m: 0                                                                                            \n\u001b[1mTotal params\u001b[0m: 258                                                                                                  \n\u001b[1mTotal estimated model params size (MB)\u001b[0m: 0                                                                          \n","text/html":"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">Trainable params</span>: 258                                                                                              \n<span style=\"font-weight: bold\">Non-trainable params</span>: 0                                                                                            \n<span style=\"font-weight: bold\">Total params</span>: 258                                                                                                  \n<span style=\"font-weight: bold\">Total estimated model params size (MB)</span>: 0                                                                          \n</pre>\n"},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"Output()","application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"0f1aae9c99754c4d9d2463884d6d8a6f"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"","text/html":"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"\n","text/html":"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n</pre>\n"},"metadata":{}},{"name":"stderr","text":"2023-06-25 01:41:22,168 - {pytorch_tabular.tabular_model:584} - INFO - Training the model completed\n2023-06-25 01:41:22,169 - {pytorch_tabular.tabular_model:1258} - INFO - Loading the best model\n","output_type":"stream"},{"execution_count":87,"output_type":"execute_result","data":{"text/plain":"<pytorch_lightning.trainer.trainer.Trainer at 0x7bdde060ea70>"},"metadata":{}}]},{"cell_type":"markdown","source":"<div style=\"color:white;\n           display:fill;\n           border-radius:5px;\n           background-color:#4270c5;\n           font-size:110%;\n           font-family:sans-serif;\n           letter-spacing:0.2px\">\n\n<p style=\"padding: 30px;\n              color:white;\">\nTEST DATA PREPARATION\n</p>\n</div>","metadata":{}},{"cell_type":"code","source":"test=data.get_dataframe('test.csv')\ntest = data.rename_column(test)\ntest.head()","metadata":{"execution":{"iopub.status.busy":"2023-06-25T01:41:22.193672Z","iopub.execute_input":"2023-06-25T01:41:22.194051Z","iopub.status.idle":"2023-06-25T01:41:22.284524Z","shell.execute_reply.started":"2023-06-25T01:41:22.19402Z","shell.execute_reply":"2023-06-25T01:41:22.283325Z"},"trusted":true},"execution_count":88,"outputs":[{"execution_count":88,"output_type":"execute_result","data":{"text/plain":"       id Product_ID Type  Air_temperature  Process_temperature  \\\n0  136429     L50896    L            302.3                311.5   \n1  136430     L53866    L            301.7                311.0   \n2  136431     L50498    L            301.3                310.4   \n3  136432     M21232    M            300.1                309.6   \n4  136433     M19751    M            303.4                312.3   \n\n   Rotational_speed  Torque  Tool_wear  TWF  HDF  PWF  OSF  RNF  \n0              1499    38.0         60    0    0    0    0    0  \n1              1713    28.8         17    0    0    0    0    0  \n2              1525    37.7         96    0    0    0    0    0  \n3              1479    47.6          5    0    0    0    0    0  \n4              1515    41.3        114    0    0    0    0    0  ","text/html":"<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>id</th>\n      <th>Product_ID</th>\n      <th>Type</th>\n      <th>Air_temperature</th>\n      <th>Process_temperature</th>\n      <th>Rotational_speed</th>\n      <th>Torque</th>\n      <th>Tool_wear</th>\n      <th>TWF</th>\n      <th>HDF</th>\n      <th>PWF</th>\n      <th>OSF</th>\n      <th>RNF</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>136429</td>\n      <td>L50896</td>\n      <td>L</td>\n      <td>302.3</td>\n      <td>311.5</td>\n      <td>1499</td>\n      <td>38.0</td>\n      <td>60</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>136430</td>\n      <td>L53866</td>\n      <td>L</td>\n      <td>301.7</td>\n      <td>311.0</td>\n      <td>1713</td>\n      <td>28.8</td>\n      <td>17</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>136431</td>\n      <td>L50498</td>\n      <td>L</td>\n      <td>301.3</td>\n      <td>310.4</td>\n      <td>1525</td>\n      <td>37.7</td>\n      <td>96</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>136432</td>\n      <td>M21232</td>\n      <td>M</td>\n      <td>300.1</td>\n      <td>309.6</td>\n      <td>1479</td>\n      <td>47.6</td>\n      <td>5</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>136433</td>\n      <td>M19751</td>\n      <td>M</td>\n      <td>303.4</td>\n      <td>312.3</td>\n      <td>1515</td>\n      <td>41.3</td>\n      <td>114</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n    </tr>\n  </tbody>\n</table>\n</div>"},"metadata":{}}]},{"cell_type":"markdown","source":"<div style=\"color:white;\n           display:fill;\n           border-radius:5px;\n           background-color:#4270c5;\n           font-size:110%;\n           font-family:sans-serif;\n           letter-spacing:0.2px\">\n\n<p style=\"padding: 30px;\n              color:white;\">\nTEST DATA SUMMARY\n</p>\n</div>","metadata":{}},{"cell_type":"code","source":"data.summary('test',test)","metadata":{"execution":{"iopub.status.busy":"2023-06-25T01:41:22.285775Z","iopub.execute_input":"2023-06-25T01:41:22.286035Z","iopub.status.idle":"2023-06-25T01:41:23.322531Z","shell.execute_reply.started":"2023-06-25T01:41:22.286014Z","shell.execute_reply":"2023-06-25T01:41:23.321641Z"},"trusted":true},"execution_count":89,"outputs":[{"execution_count":89,"output_type":"execute_result","data":{"text/plain":"                      dtypes  null  unique     min    median     max  \\\nid                     int64     0   90954  136429  181905.5  227382   \nProduct_ID            object     0    9909  H29424       NaN  M24859   \nType                  object     0       3       H       NaN       M   \nAir_temperature      float64     0      92   295.3     300.0   304.4   \nProcess_temperature  float64     0      84   305.7     310.0   313.8   \nRotational_speed       int64     0     946    1168    1493.0    2886   \nTorque               float64     0     595     3.8      40.5    76.6   \nTool_wear              int64     0     246       0     106.0     253   \nTWF                    int64     0       2       0       0.0       1   \nHDF                    int64     0       2       0       0.0       1   \nPWF                    int64     0       2       0       0.0       1   \nOSF                    int64     0       2       0       0.0       1   \nRNF                    int64     0       2       0       0.0       1   \n\n                              mean           std  duplicate  \nid                   181905.500000  26256.302529          0  \nProduct_ID                     NaN           NaN          0  \nType                           NaN           NaN          0  \nAir_temperature         299.859493      1.857562          0  \nProcess_temperature     309.939375      1.385296          0  \nRotational_speed       1520.528179    139.970419          0  \nTorque                   40.335191      8.504683          0  \nTool_wear               104.293962     63.871092          0  \nTWF                       0.001473      0.038355          0  \nHDF                       0.005343      0.072903          0  \nPWF                       0.002353      0.048449          0  \nOSF                       0.003870      0.062090          0  \nRNF                       0.002309      0.047995          0  ","text/html":"<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>dtypes</th>\n      <th>null</th>\n      <th>unique</th>\n      <th>min</th>\n      <th>median</th>\n      <th>max</th>\n      <th>mean</th>\n      <th>std</th>\n      <th>duplicate</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>id</th>\n      <td>int64</td>\n      <td>0</td>\n      <td>90954</td>\n      <td>136429</td>\n      <td>181905.5</td>\n      <td>227382</td>\n      <td>181905.500000</td>\n      <td>26256.302529</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>Product_ID</th>\n      <td>object</td>\n      <td>0</td>\n      <td>9909</td>\n      <td>H29424</td>\n      <td>NaN</td>\n      <td>M24859</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>Type</th>\n      <td>object</td>\n      <td>0</td>\n      <td>3</td>\n      <td>H</td>\n      <td>NaN</td>\n      <td>M</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>Air_temperature</th>\n      <td>float64</td>\n      <td>0</td>\n      <td>92</td>\n      <td>295.3</td>\n      <td>300.0</td>\n      <td>304.4</td>\n      <td>299.859493</td>\n      <td>1.857562</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>Process_temperature</th>\n      <td>float64</td>\n      <td>0</td>\n      <td>84</td>\n      <td>305.7</td>\n      <td>310.0</td>\n      <td>313.8</td>\n      <td>309.939375</td>\n      <td>1.385296</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>Rotational_speed</th>\n      <td>int64</td>\n      <td>0</td>\n      <td>946</td>\n      <td>1168</td>\n      <td>1493.0</td>\n      <td>2886</td>\n      <td>1520.528179</td>\n      <td>139.970419</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>Torque</th>\n      <td>float64</td>\n      <td>0</td>\n      <td>595</td>\n      <td>3.8</td>\n      <td>40.5</td>\n      <td>76.6</td>\n      <td>40.335191</td>\n      <td>8.504683</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>Tool_wear</th>\n      <td>int64</td>\n      <td>0</td>\n      <td>246</td>\n      <td>0</td>\n      <td>106.0</td>\n      <td>253</td>\n      <td>104.293962</td>\n      <td>63.871092</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>TWF</th>\n      <td>int64</td>\n      <td>0</td>\n      <td>2</td>\n      <td>0</td>\n      <td>0.0</td>\n      <td>1</td>\n      <td>0.001473</td>\n      <td>0.038355</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>HDF</th>\n      <td>int64</td>\n      <td>0</td>\n      <td>2</td>\n      <td>0</td>\n      <td>0.0</td>\n      <td>1</td>\n      <td>0.005343</td>\n      <td>0.072903</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>PWF</th>\n      <td>int64</td>\n      <td>0</td>\n      <td>2</td>\n      <td>0</td>\n      <td>0.0</td>\n      <td>1</td>\n      <td>0.002353</td>\n      <td>0.048449</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>OSF</th>\n      <td>int64</td>\n      <td>0</td>\n      <td>2</td>\n      <td>0</td>\n      <td>0.0</td>\n      <td>1</td>\n      <td>0.003870</td>\n      <td>0.062090</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>RNF</th>\n      <td>int64</td>\n      <td>0</td>\n      <td>2</td>\n      <td>0</td>\n      <td>0.0</td>\n      <td>1</td>\n      <td>0.002309</td>\n      <td>0.047995</td>\n      <td>0</td>\n    </tr>\n  </tbody>\n</table>\n</div>"},"metadata":{}}]},{"cell_type":"markdown","source":"<div style=\"color:white;\n           display:fill;\n           border-radius:5px;\n           background-color:#4270c5;\n           font-size:110%;\n           font-family:sans-serif;\n           letter-spacing:0.2px\">\n\n<p style=\"padding: 30px;\n              color:white;\">\nTEST DATA NORMALIZATION\n</p>\n</div>","metadata":{}},{"cell_type":"code","source":"test_updated = data.set_feature(test)\ntest_updated.drop(columns=['Product_ID'],axis=1,inplace=True)\ntest_updated","metadata":{"execution":{"iopub.status.busy":"2023-06-25T01:41:23.323749Z","iopub.execute_input":"2023-06-25T01:41:23.324025Z","iopub.status.idle":"2023-06-25T01:41:23.36526Z","shell.execute_reply.started":"2023-06-25T01:41:23.324004Z","shell.execute_reply":"2023-06-25T01:41:23.364343Z"},"trusted":true},"execution_count":90,"outputs":[{"execution_count":90,"output_type":"execute_result","data":{"text/plain":"           id  Type  Air_temperature  Process_temperature  Rotational_speed  \\\n0      136429     1            302.3                311.5              1499   \n1      136430     1            301.7                311.0              1713   \n2      136431     1            301.3                310.4              1525   \n3      136432     2            300.1                309.6              1479   \n4      136433     2            303.4                312.3              1515   \n...       ...   ...              ...                  ...               ...   \n90949  227378     1            302.3                311.4              1484   \n90950  227379     1            297.9                309.8              1542   \n90951  227380     1            295.6                306.2              1501   \n90952  227381     1            298.1                307.8              1534   \n90953  227382     1            303.5                312.8              1534   \n\n       Torque  Tool_wear  TWF  HDF  PWF  OSF  RNF  \n0        38.0         60    0    0    0    0    0  \n1        28.8         17    0    0    0    0    0  \n2        37.7         96    0    0    0    0    0  \n3        47.6          5    0    0    0    0    0  \n4        41.3        114    0    0    0    0    0  \n...       ...        ...  ...  ...  ...  ...  ...  \n90949    40.4         15    0    0    0    0    0  \n90950    33.8         31    0    0    0    0    0  \n90951    41.4        187    0    0    0    0    0  \n90952    40.3         69    0    0    0    0    0  \n90953    36.1         92    0    0    0    0    0  \n\n[90954 rows x 12 columns]","text/html":"<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>id</th>\n      <th>Type</th>\n      <th>Air_temperature</th>\n      <th>Process_temperature</th>\n      <th>Rotational_speed</th>\n      <th>Torque</th>\n      <th>Tool_wear</th>\n      <th>TWF</th>\n      <th>HDF</th>\n      <th>PWF</th>\n      <th>OSF</th>\n      <th>RNF</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>136429</td>\n      <td>1</td>\n      <td>302.3</td>\n      <td>311.5</td>\n      <td>1499</td>\n      <td>38.0</td>\n      <td>60</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>136430</td>\n      <td>1</td>\n      <td>301.7</td>\n      <td>311.0</td>\n      <td>1713</td>\n      <td>28.8</td>\n      <td>17</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>136431</td>\n      <td>1</td>\n      <td>301.3</td>\n      <td>310.4</td>\n      <td>1525</td>\n      <td>37.7</td>\n      <td>96</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>136432</td>\n      <td>2</td>\n      <td>300.1</td>\n      <td>309.6</td>\n      <td>1479</td>\n      <td>47.6</td>\n      <td>5</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>136433</td>\n      <td>2</td>\n      <td>303.4</td>\n      <td>312.3</td>\n      <td>1515</td>\n      <td>41.3</td>\n      <td>114</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>...</th>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n    </tr>\n    <tr>\n      <th>90949</th>\n      <td>227378</td>\n      <td>1</td>\n      <td>302.3</td>\n      <td>311.4</td>\n      <td>1484</td>\n      <td>40.4</td>\n      <td>15</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>90950</th>\n      <td>227379</td>\n      <td>1</td>\n      <td>297.9</td>\n      <td>309.8</td>\n      <td>1542</td>\n      <td>33.8</td>\n      <td>31</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>90951</th>\n      <td>227380</td>\n      <td>1</td>\n      <td>295.6</td>\n      <td>306.2</td>\n      <td>1501</td>\n      <td>41.4</td>\n      <td>187</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>90952</th>\n      <td>227381</td>\n      <td>1</td>\n      <td>298.1</td>\n      <td>307.8</td>\n      <td>1534</td>\n      <td>40.3</td>\n      <td>69</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>90953</th>\n      <td>227382</td>\n      <td>1</td>\n      <td>303.5</td>\n      <td>312.8</td>\n      <td>1534</td>\n      <td>36.1</td>\n      <td>92</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n    </tr>\n  </tbody>\n</table>\n<p>90954 rows × 12 columns</p>\n</div>"},"metadata":{}}]},{"cell_type":"markdown","source":"<div style=\"color:white;\n           display:fill;\n           border-radius:5px;\n           background-color:#4270c5;\n           font-size:110%;\n           font-family:sans-serif;\n           letter-spacing:0.2px\">\n\n<p style=\"padding: 30px;\n              color:white;\">\nBASELINE MODEL EVALUATION\n</p>\n</div>","metadata":{}},{"cell_type":"code","source":"result = trainer.tabular_model.evaluate(test_updated)\nresult\n","metadata":{"execution":{"iopub.status.busy":"2023-06-25T01:41:23.366249Z","iopub.execute_input":"2023-06-25T01:41:23.366489Z","iopub.status.idle":"2023-06-25T01:41:29.840068Z","shell.execute_reply.started":"2023-06-25T01:41:23.366461Z","shell.execute_reply":"2023-06-25T01:41:29.83925Z"},"trusted":true},"execution_count":91,"outputs":[{"output_type":"display_data","data":{"text/plain":"Output()","application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"046dc2f354d14b4899cfe2d1cd3a540a"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"┏━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━┓\n┃\u001b[1m \u001b[0m\u001b[1m       Test metric       \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1m      DataLoader 0       \u001b[0m\u001b[1m \u001b[0m┃\n┡━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━┩\n│\u001b[36m \u001b[0m\u001b[36m      test_accuracy      \u001b[0m\u001b[36m \u001b[0m│\u001b[35m \u001b[0m\u001b[35m   0.8429975509643555    \u001b[0m\u001b[35m \u001b[0m│\n│\u001b[36m \u001b[0m\u001b[36m      test_f1_score      \u001b[0m\u001b[36m \u001b[0m│\u001b[35m \u001b[0m\u001b[35m   0.8429975509643555    \u001b[0m\u001b[35m \u001b[0m│\n│\u001b[36m \u001b[0m\u001b[36m        test_loss        \u001b[0m\u001b[36m \u001b[0m│\u001b[35m \u001b[0m\u001b[35m   6.5214691162109375    \u001b[0m\u001b[35m \u001b[0m│\n└───────────────────────────┴───────────────────────────┘\n","text/html":"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">┏━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━┓\n┃<span style=\"font-weight: bold\">        Test metric        </span>┃<span style=\"font-weight: bold\">       DataLoader 0        </span>┃\n┡━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━┩\n│<span style=\"color: #008080; text-decoration-color: #008080\">       test_accuracy       </span>│<span style=\"color: #800080; text-decoration-color: #800080\">    0.8429975509643555     </span>│\n│<span style=\"color: #008080; text-decoration-color: #008080\">       test_f1_score       </span>│<span style=\"color: #800080; text-decoration-color: #800080\">    0.8429975509643555     </span>│\n│<span style=\"color: #008080; text-decoration-color: #008080\">         test_loss         </span>│<span style=\"color: #800080; text-decoration-color: #800080\">    6.5214691162109375     </span>│\n└───────────────────────────┴───────────────────────────┘\n</pre>\n"},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"","text/html":"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"\n","text/html":"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n</pre>\n"},"metadata":{}},{"execution_count":91,"output_type":"execute_result","data":{"text/plain":"[{'test_loss': 6.5214691162109375,\n  'test_f1_score': 0.8429975509643555,\n  'test_accuracy': 0.8429975509643555}]"},"metadata":{}}]},{"cell_type":"code","source":"results =[]\n\nresult = {k: float(v) for k,v in result[0].items()}\nresult[\"Mode\"] = \"Normal\"\nresults.append(result)\n","metadata":{"execution":{"iopub.status.busy":"2023-06-25T01:41:29.841193Z","iopub.execute_input":"2023-06-25T01:41:29.841437Z","iopub.status.idle":"2023-06-25T01:41:29.847969Z","shell.execute_reply.started":"2023-06-25T01:41:29.841414Z","shell.execute_reply":"2023-06-25T01:41:29.845771Z"},"trusted":true},"execution_count":92,"outputs":[]},{"cell_type":"markdown","source":"<div style=\"color:white;\n           display:fill;\n           border-radius:5px;\n           background-color:#4270c5;\n           font-size:110%;\n           font-family:sans-serif;\n           letter-spacing:0.2px\">\n\n<p style=\"padding: 30px;\n              color:white;\">\nBALANCED SAMPLER CLASS\n</p>\n</div>","metadata":{}},{"cell_type":"code","source":"class Balancedsampler:\n    \n    tabular_model = TabularModel(\n    data_config=config.data_config,\n    model_config=config.model_config,\n    optimizer_config=config.optimizer_config,\n    trainer_config=config.trainer_config,\n    )\nsampler = get_balanced_sampler(train['Machine_failure'].values.ravel())\n\n\nbal = Balancedsampler()","metadata":{"execution":{"iopub.status.busy":"2023-06-25T01:41:29.84994Z","iopub.execute_input":"2023-06-25T01:41:29.850295Z","iopub.status.idle":"2023-06-25T01:41:30.845023Z","shell.execute_reply.started":"2023-06-25T01:41:29.850268Z","shell.execute_reply":"2023-06-25T01:41:30.843897Z"},"trusted":true},"execution_count":93,"outputs":[{"name":"stderr","text":"2023-06-25 01:41:29,876 - {pytorch_tabular.tabular_model:105} - INFO - Experiment Tracking is turned off\n","output_type":"stream"}]},{"cell_type":"markdown","source":"<div style=\"color:white;\n           display:fill;\n           border-radius:5px;\n           background-color:#4270c5;\n           font-size:110%;\n           font-family:sans-serif;\n           letter-spacing:0.2px\">\n\n<p style=\"padding: 30px;\n              color:white;\">\nTRAINING BALANCED SAMPLER MODEL\n</p>\n</div>","metadata":{}},{"cell_type":"code","source":"bal.tabular_model.fit(train=X_train, validation=X_val, train_sampler=sampler)","metadata":{"execution":{"iopub.status.busy":"2023-06-25T01:41:30.846401Z","iopub.execute_input":"2023-06-25T01:41:30.846748Z","iopub.status.idle":"2023-06-25T01:43:26.856706Z","shell.execute_reply.started":"2023-06-25T01:41:30.84672Z","shell.execute_reply":"2023-06-25T01:43:26.855043Z"},"trusted":true},"execution_count":94,"outputs":[{"name":"stderr","text":"2023-06-25 01:41:30,850 - {pytorch_tabular.tabular_model:473} - INFO - Preparing the DataLoaders\n2023-06-25 01:41:30,853 - {pytorch_tabular.tabular_datamodule:290} - INFO - Setting up the datamodule for classification task\n2023-06-25 01:41:31,111 - {pytorch_tabular.tabular_model:521} - INFO - Preparing the Model: CategoryEmbeddingModel\n2023-06-25 01:41:31,157 - {pytorch_tabular.tabular_model:268} - INFO - Preparing the Trainer\n2023-06-25 01:41:31,227 - {pytorch_tabular.tabular_model:573} - INFO - Auto LR Find Started\n","output_type":"stream"},{"output_type":"display_data","data":{"text/plain":"Finding best initial lr:   0%|          | 0/100 [00:00<?, ?it/s]","application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"937e732cd379416f825580452748b9ae"}},"metadata":{}},{"name":"stderr","text":"2023-06-25 01:41:33,441 - {pytorch_tabular.tabular_model:575} - INFO - Suggested LR: 0.15848931924611143. For plot and detailed analysis, use `find_learning_rate` method.\n2023-06-25 01:41:33,442 - {pytorch_tabular.tabular_model:582} - INFO - Training Started\n","output_type":"stream"},{"output_type":"display_data","data":{"text/plain":"┏━━━┳━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━┓\n┃\u001b[1;35m \u001b[0m\u001b[1;35m \u001b[0m\u001b[1;35m \u001b[0m┃\u001b[1;35m \u001b[0m\u001b[1;35mName            \u001b[0m\u001b[1;35m \u001b[0m┃\u001b[1;35m \u001b[0m\u001b[1;35mType                     \u001b[0m\u001b[1;35m \u001b[0m┃\u001b[1;35m \u001b[0m\u001b[1;35mParams\u001b[0m\u001b[1;35m \u001b[0m┃\n┡━━━╇━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━┩\n│\u001b[2m \u001b[0m\u001b[2m0\u001b[0m\u001b[2m \u001b[0m│ _backbone        │ CategoryEmbeddingBackbone │    200 │\n│\u001b[2m \u001b[0m\u001b[2m1\u001b[0m\u001b[2m \u001b[0m│ _embedding_layer │ Embedding1dLayer          │     48 │\n│\u001b[2m \u001b[0m\u001b[2m2\u001b[0m\u001b[2m \u001b[0m│ head             │ LinearHead                │     10 │\n│\u001b[2m \u001b[0m\u001b[2m3\u001b[0m\u001b[2m \u001b[0m│ loss             │ CrossEntropyLoss          │      0 │\n└───┴──────────────────┴───────────────────────────┴────────┘\n","text/html":"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">┏━━━┳━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━┓\n┃<span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">   </span>┃<span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\"> Name             </span>┃<span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\"> Type                      </span>┃<span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\"> Params </span>┃\n┡━━━╇━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━┩\n│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 0 </span>│ _backbone        │ CategoryEmbeddingBackbone │    200 │\n│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 1 </span>│ _embedding_layer │ Embedding1dLayer          │     48 │\n│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 2 </span>│ head             │ LinearHead                │     10 │\n│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 3 </span>│ loss             │ CrossEntropyLoss          │      0 │\n└───┴──────────────────┴───────────────────────────┴────────┘\n</pre>\n"},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"\u001b[1mTrainable params\u001b[0m: 258                                                                                              \n\u001b[1mNon-trainable params\u001b[0m: 0                                                                                            \n\u001b[1mTotal params\u001b[0m: 258                                                                                                  \n\u001b[1mTotal estimated model params size (MB)\u001b[0m: 0                                                                          \n","text/html":"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">Trainable params</span>: 258                                                                                              \n<span style=\"font-weight: bold\">Non-trainable params</span>: 0                                                                                            \n<span style=\"font-weight: bold\">Total params</span>: 258                                                                                                  \n<span style=\"font-weight: bold\">Total estimated model params size (MB)</span>: 0                                                                          \n</pre>\n"},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"Output()","application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"af38e1b2d10443aba4c5c15e631d7902"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"","text/html":"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"\n","text/html":"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n</pre>\n"},"metadata":{}},{"name":"stderr","text":"2023-06-25 01:43:26,834 - {pytorch_tabular.tabular_model:584} - INFO - Training the model completed\n2023-06-25 01:43:26,835 - {pytorch_tabular.tabular_model:1258} - INFO - Loading the best model\n","output_type":"stream"},{"execution_count":94,"output_type":"execute_result","data":{"text/plain":"<pytorch_lightning.trainer.trainer.Trainer at 0x7bddde12cb50>"},"metadata":{}}]},{"cell_type":"markdown","source":"<div style=\"color:white;\n           display:fill;\n           border-radius:5px;\n           background-color:#4270c5;\n           font-size:110%;\n           font-family:sans-serif;\n           letter-spacing:0.2px\">\n\n<p style=\"padding: 30px;\n              color:white;\">\nBALANCED SAMPLER MODEL EVALUATION\n</p>\n</div>","metadata":{}},{"cell_type":"code","source":"result = trainer.tabular_model.evaluate(test_updated)\n","metadata":{"execution":{"iopub.status.busy":"2023-06-25T01:43:26.86081Z","iopub.execute_input":"2023-06-25T01:43:26.86114Z","iopub.status.idle":"2023-06-25T01:43:33.581027Z","shell.execute_reply.started":"2023-06-25T01:43:26.861113Z","shell.execute_reply":"2023-06-25T01:43:33.579786Z"},"trusted":true},"execution_count":95,"outputs":[{"output_type":"display_data","data":{"text/plain":"Output()","application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"8d590a60c0954f69af1af30ce2e0fa95"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"┏━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━┓\n┃\u001b[1m \u001b[0m\u001b[1m       Test metric       \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1m      DataLoader 0       \u001b[0m\u001b[1m \u001b[0m┃\n┡━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━┩\n│\u001b[36m \u001b[0m\u001b[36m      test_accuracy      \u001b[0m\u001b[36m \u001b[0m│\u001b[35m \u001b[0m\u001b[35m   0.8429975509643555    \u001b[0m\u001b[35m \u001b[0m│\n│\u001b[36m \u001b[0m\u001b[36m      test_f1_score      \u001b[0m\u001b[36m \u001b[0m│\u001b[35m \u001b[0m\u001b[35m   0.8429975509643555    \u001b[0m\u001b[35m \u001b[0m│\n│\u001b[36m \u001b[0m\u001b[36m        test_loss        \u001b[0m\u001b[36m \u001b[0m│\u001b[35m \u001b[0m\u001b[35m   6.5214691162109375    \u001b[0m\u001b[35m \u001b[0m│\n└───────────────────────────┴───────────────────────────┘\n","text/html":"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">┏━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━┓\n┃<span style=\"font-weight: bold\">        Test metric        </span>┃<span style=\"font-weight: bold\">       DataLoader 0        </span>┃\n┡━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━┩\n│<span style=\"color: #008080; text-decoration-color: #008080\">       test_accuracy       </span>│<span style=\"color: #800080; text-decoration-color: #800080\">    0.8429975509643555     </span>│\n│<span style=\"color: #008080; text-decoration-color: #008080\">       test_f1_score       </span>│<span style=\"color: #800080; text-decoration-color: #800080\">    0.8429975509643555     </span>│\n│<span style=\"color: #008080; text-decoration-color: #008080\">         test_loss         </span>│<span style=\"color: #800080; text-decoration-color: #800080\">    6.5214691162109375     </span>│\n└───────────────────────────┴───────────────────────────┘\n</pre>\n"},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"","text/html":"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"\n","text/html":"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n</pre>\n"},"metadata":{}}]},{"cell_type":"code","source":"result = {k: float(v) for k,v in result[0].items()}\nresult[\"Mode\"] = \"Balanced Sampler\"\n\nresults.append(result)\n","metadata":{"execution":{"iopub.status.busy":"2023-06-25T01:43:33.582469Z","iopub.execute_input":"2023-06-25T01:43:33.582818Z","iopub.status.idle":"2023-06-25T01:43:33.587978Z","shell.execute_reply.started":"2023-06-25T01:43:33.582777Z","shell.execute_reply":"2023-06-25T01:43:33.587021Z"},"trusted":true},"execution_count":96,"outputs":[]},{"cell_type":"markdown","source":"<div style=\"color:white;\n           display:fill;\n           border-radius:5px;\n           background-color:#4270c5;\n           font-size:110%;\n           font-family:sans-serif;\n           letter-spacing:0.2px\">\n\n<p style=\"padding: 30px;\n              color:white;\">\nWEIGHTED SAMPLER MODEL CLASS\n</p>\n</div>","metadata":{}},{"cell_type":"code","source":"class Weightedsampler:\n    \n    tabular_model = TabularModel(\n    data_config=config.data_config,\n    model_config=config.model_config,\n    optimizer_config=config.optimizer_config,\n    trainer_config=config.trainer_config,\n)\nweighted_loss = get_class_weighted_cross_entropy(train[\"Machine_failure\"].values.ravel(), mu=0.1)\n\n\nws = Weightedsampler()","metadata":{"execution":{"iopub.status.busy":"2023-06-25T01:43:33.59295Z","iopub.execute_input":"2023-06-25T01:43:33.59336Z","iopub.status.idle":"2023-06-25T01:43:33.655013Z","shell.execute_reply.started":"2023-06-25T01:43:33.593329Z","shell.execute_reply":"2023-06-25T01:43:33.653612Z"},"trusted":true},"execution_count":97,"outputs":[{"name":"stderr","text":"2023-06-25 01:43:33,620 - {pytorch_tabular.tabular_model:105} - INFO - Experiment Tracking is turned off\n","output_type":"stream"}]},{"cell_type":"markdown","source":"<div style=\"color:white;\n           display:fill;\n           border-radius:5px;\n           background-color:#4270c5;\n           font-size:110%;\n           font-family:sans-serif;\n           letter-spacing:0.2px\">\n\n<p style=\"padding: 30px;\n              color:white;\">\nWEIGHTED SAMPLER MODEL TRAINING\n</p>\n</div>","metadata":{}},{"cell_type":"code","source":"ws.tabular_model.fit(train=X_train, validation=X_val, loss=weighted_loss)","metadata":{"execution":{"iopub.status.busy":"2023-06-25T01:43:33.656508Z","iopub.execute_input":"2023-06-25T01:43:33.65699Z","iopub.status.idle":"2023-06-25T01:48:02.383642Z","shell.execute_reply.started":"2023-06-25T01:43:33.656951Z","shell.execute_reply":"2023-06-25T01:48:02.382357Z"},"trusted":true},"execution_count":98,"outputs":[{"name":"stderr","text":"2023-06-25 01:43:33,661 - {pytorch_tabular.tabular_model:473} - INFO - Preparing the DataLoaders\n2023-06-25 01:43:33,666 - {pytorch_tabular.tabular_datamodule:290} - INFO - Setting up the datamodule for classification task\n2023-06-25 01:43:33,928 - {pytorch_tabular.tabular_model:521} - INFO - Preparing the Model: CategoryEmbeddingModel\n2023-06-25 01:43:33,976 - {pytorch_tabular.tabular_model:268} - INFO - Preparing the Trainer\n2023-06-25 01:43:34,047 - {pytorch_tabular.tabular_model:573} - INFO - Auto LR Find Started\n","output_type":"stream"},{"output_type":"display_data","data":{"text/plain":"Finding best initial lr:   0%|          | 0/100 [00:00<?, ?it/s]","application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"25296a17557d4595879caa83dad83008"}},"metadata":{}},{"name":"stderr","text":"2023-06-25 01:43:36,061 - {pytorch_tabular.tabular_model:575} - INFO - Suggested LR: 0.07585775750291836. For plot and detailed analysis, use `find_learning_rate` method.\n2023-06-25 01:43:36,062 - {pytorch_tabular.tabular_model:582} - INFO - Training Started\n","output_type":"stream"},{"output_type":"display_data","data":{"text/plain":"┏━━━┳━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━┓\n┃\u001b[1;35m \u001b[0m\u001b[1;35m \u001b[0m\u001b[1;35m \u001b[0m┃\u001b[1;35m \u001b[0m\u001b[1;35mName            \u001b[0m\u001b[1;35m \u001b[0m┃\u001b[1;35m \u001b[0m\u001b[1;35mType                     \u001b[0m\u001b[1;35m \u001b[0m┃\u001b[1;35m \u001b[0m\u001b[1;35mParams\u001b[0m\u001b[1;35m \u001b[0m┃\n┡━━━╇━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━┩\n│\u001b[2m \u001b[0m\u001b[2m0\u001b[0m\u001b[2m \u001b[0m│ custom_loss      │ CrossEntropyLoss          │      0 │\n│\u001b[2m \u001b[0m\u001b[2m1\u001b[0m\u001b[2m \u001b[0m│ _backbone        │ CategoryEmbeddingBackbone │    200 │\n│\u001b[2m \u001b[0m\u001b[2m2\u001b[0m\u001b[2m \u001b[0m│ _embedding_layer │ Embedding1dLayer          │     48 │\n│\u001b[2m \u001b[0m\u001b[2m3\u001b[0m\u001b[2m \u001b[0m│ head             │ LinearHead                │     10 │\n└───┴──────────────────┴───────────────────────────┴────────┘\n","text/html":"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">┏━━━┳━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━┓\n┃<span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">   </span>┃<span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\"> Name             </span>┃<span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\"> Type                      </span>┃<span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\"> Params </span>┃\n┡━━━╇━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━┩\n│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 0 </span>│ custom_loss      │ CrossEntropyLoss          │      0 │\n│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 1 </span>│ _backbone        │ CategoryEmbeddingBackbone │    200 │\n│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 2 </span>│ _embedding_layer │ Embedding1dLayer          │     48 │\n│<span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 3 </span>│ head             │ LinearHead                │     10 │\n└───┴──────────────────┴───────────────────────────┴────────┘\n</pre>\n"},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"\u001b[1mTrainable params\u001b[0m: 258                                                                                              \n\u001b[1mNon-trainable params\u001b[0m: 0                                                                                            \n\u001b[1mTotal params\u001b[0m: 258                                                                                                  \n\u001b[1mTotal estimated model params size (MB)\u001b[0m: 0                                                                          \n","text/html":"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">Trainable params</span>: 258                                                                                              \n<span style=\"font-weight: bold\">Non-trainable params</span>: 0                                                                                            \n<span style=\"font-weight: bold\">Total params</span>: 258                                                                                                  \n<span style=\"font-weight: bold\">Total estimated model params size (MB)</span>: 0                                                                          \n</pre>\n"},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"Output()","application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"2209d7bc34774ae3a0ad6e5ee1a0e332"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"","text/html":"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"\n","text/html":"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n</pre>\n"},"metadata":{}},{"name":"stderr","text":"2023-06-25 01:48:02,361 - {pytorch_tabular.tabular_model:584} - INFO - Training the model completed\n2023-06-25 01:48:02,362 - {pytorch_tabular.tabular_model:1258} - INFO - Loading the best model\n","output_type":"stream"},{"execution_count":98,"output_type":"execute_result","data":{"text/plain":"<pytorch_lightning.trainer.trainer.Trainer at 0x7bddde24f5b0>"},"metadata":{}}]},{"cell_type":"markdown","source":"<div style=\"color:white;\n           display:fill;\n           border-radius:5px;\n           background-color:#4270c5;\n           font-size:110%;\n           font-family:sans-serif;\n           letter-spacing:0.2px\">\n\n<p style=\"padding: 30px;\n              color:white;\">\nWEIGHTED SAMPLER MODEL EVALUATION\n</p>\n</div>","metadata":{}},{"cell_type":"code","source":"result = trainer.tabular_model.evaluate(test_updated)\n","metadata":{"execution":{"iopub.status.busy":"2023-06-25T01:48:02.385455Z","iopub.execute_input":"2023-06-25T01:48:02.385941Z","iopub.status.idle":"2023-06-25T01:48:09.293832Z","shell.execute_reply.started":"2023-06-25T01:48:02.385904Z","shell.execute_reply":"2023-06-25T01:48:09.292843Z"},"trusted":true},"execution_count":99,"outputs":[{"output_type":"display_data","data":{"text/plain":"Output()","application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"65bd69eab0ed4e9081af0c09a4291a3a"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"┏━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━┓\n┃\u001b[1m \u001b[0m\u001b[1m       Test metric       \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1m      DataLoader 0       \u001b[0m\u001b[1m \u001b[0m┃\n┡━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━┩\n│\u001b[36m \u001b[0m\u001b[36m      test_accuracy      \u001b[0m\u001b[36m \u001b[0m│\u001b[35m \u001b[0m\u001b[35m   0.8429975509643555    \u001b[0m\u001b[35m \u001b[0m│\n│\u001b[36m \u001b[0m\u001b[36m      test_f1_score      \u001b[0m\u001b[36m \u001b[0m│\u001b[35m \u001b[0m\u001b[35m   0.8429975509643555    \u001b[0m\u001b[35m \u001b[0m│\n│\u001b[36m \u001b[0m\u001b[36m        test_loss        \u001b[0m\u001b[36m \u001b[0m│\u001b[35m \u001b[0m\u001b[35m   6.5214691162109375    \u001b[0m\u001b[35m \u001b[0m│\n└───────────────────────────┴───────────────────────────┘\n","text/html":"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">┏━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━┓\n┃<span style=\"font-weight: bold\">        Test metric        </span>┃<span style=\"font-weight: bold\">       DataLoader 0        </span>┃\n┡━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━┩\n│<span style=\"color: #008080; text-decoration-color: #008080\">       test_accuracy       </span>│<span style=\"color: #800080; text-decoration-color: #800080\">    0.8429975509643555     </span>│\n│<span style=\"color: #008080; text-decoration-color: #008080\">       test_f1_score       </span>│<span style=\"color: #800080; text-decoration-color: #800080\">    0.8429975509643555     </span>│\n│<span style=\"color: #008080; text-decoration-color: #008080\">         test_loss         </span>│<span style=\"color: #800080; text-decoration-color: #800080\">    6.5214691162109375     </span>│\n└───────────────────────────┴───────────────────────────┘\n</pre>\n"},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"","text/html":"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"\n","text/html":"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n</pre>\n"},"metadata":{}}]},{"cell_type":"code","source":"result = {k: float(v) for k,v in result[0].items()}\nresult[\"Mode\"] = \"Class Weights\"\n\nresults.append(result)\n","metadata":{"execution":{"iopub.status.busy":"2023-06-25T01:48:09.294958Z","iopub.execute_input":"2023-06-25T01:48:09.295199Z","iopub.status.idle":"2023-06-25T01:48:09.300555Z","shell.execute_reply.started":"2023-06-25T01:48:09.295179Z","shell.execute_reply":"2023-06-25T01:48:09.299548Z"},"trusted":true},"execution_count":100,"outputs":[]},{"cell_type":"markdown","source":"<div style=\"color:white;\n           display:fill;\n           border-radius:5px;\n           background-color:#4270c5;\n           font-size:110%;\n           font-family:sans-serif;\n           letter-spacing:0.2px\">\n\n<p style=\"padding: 30px;\n              color:white;\">\nMODELS STATISTICS\n</p>\n</div>","metadata":{}},{"cell_type":"code","source":"res_df = pd.DataFrame(results).T\nres_df.columns = res_df.iloc[-1]\nres_df = res_df.iloc[:-1].astype(float)\nres_df.style.highlight_min(color=\"lightgreen\",axis=1)\n","metadata":{"execution":{"iopub.status.busy":"2023-06-25T01:48:09.302004Z","iopub.execute_input":"2023-06-25T01:48:09.302338Z","iopub.status.idle":"2023-06-25T01:48:09.326032Z","shell.execute_reply.started":"2023-06-25T01:48:09.302309Z","shell.execute_reply":"2023-06-25T01:48:09.324329Z"},"trusted":true},"execution_count":101,"outputs":[{"execution_count":101,"output_type":"execute_result","data":{"text/plain":"<pandas.io.formats.style.Styler at 0x7bdde051c940>","text/html":"<style type=\"text/css\">\n#T_e2a54_row0_col0, #T_e2a54_row0_col1, #T_e2a54_row0_col2, #T_e2a54_row1_col0, #T_e2a54_row1_col1, #T_e2a54_row1_col2, #T_e2a54_row2_col0, #T_e2a54_row2_col1, #T_e2a54_row2_col2 {\n  background-color: lightgreen;\n}\n</style>\n<table id=\"T_e2a54\">\n  <thead>\n    <tr>\n      <th class=\"index_name level0\" >Mode</th>\n      <th id=\"T_e2a54_level0_col0\" class=\"col_heading level0 col0\" >Normal</th>\n      <th id=\"T_e2a54_level0_col1\" class=\"col_heading level0 col1\" >Balanced Sampler</th>\n      <th id=\"T_e2a54_level0_col2\" class=\"col_heading level0 col2\" >Class Weights</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th id=\"T_e2a54_level0_row0\" class=\"row_heading level0 row0\" >test_loss</th>\n      <td id=\"T_e2a54_row0_col0\" class=\"data row0 col0\" >6.521469</td>\n      <td id=\"T_e2a54_row0_col1\" class=\"data row0 col1\" >6.521469</td>\n      <td id=\"T_e2a54_row0_col2\" class=\"data row0 col2\" >6.521469</td>\n    </tr>\n    <tr>\n      <th id=\"T_e2a54_level0_row1\" class=\"row_heading level0 row1\" >test_f1_score</th>\n      <td id=\"T_e2a54_row1_col0\" class=\"data row1 col0\" >0.842998</td>\n      <td id=\"T_e2a54_row1_col1\" class=\"data row1 col1\" >0.842998</td>\n      <td id=\"T_e2a54_row1_col2\" class=\"data row1 col2\" >0.842998</td>\n    </tr>\n    <tr>\n      <th id=\"T_e2a54_level0_row2\" class=\"row_heading level0 row2\" >test_accuracy</th>\n      <td id=\"T_e2a54_row2_col0\" class=\"data row2 col0\" >0.842998</td>\n      <td id=\"T_e2a54_row2_col1\" class=\"data row2 col1\" >0.842998</td>\n      <td id=\"T_e2a54_row2_col2\" class=\"data row2 col2\" >0.842998</td>\n    </tr>\n  </tbody>\n</table>\n"},"metadata":{}}]},{"cell_type":"code","source":"","metadata":{},"execution_count":null,"outputs":[]}]}