{"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"name":"python","version":"3.10.13","mimetype":"text/x-python","codemirror_mode":{"name":"ipython","version":3},"pygments_lexer":"ipython3","nbconvert_exporter":"python","file_extension":".py"},"kaggle":{"accelerator":"none","dataSources":[{"sourceId":59093,"databundleVersionId":7469972,"sourceType":"competition"},{"sourceId":1735965,"sourceType":"datasetVersion","datasetId":1030338},{"sourceId":7680946,"sourceType":"datasetVersion","datasetId":4476546}],"dockerImageVersionId":30646,"isInternetEnabled":true,"language":"python","sourceType":"notebook","isGpuEnabled":false}},"nbformat_minor":4,"nbformat":4,"cells":[{"cell_type":"markdown","source":"# Process EEG signals\n## The Temple University Hospital Seizure Detection Corpus\n\nI learned about the existence of the TUH EEG Corpus but could not access it [here][1]. Luckily, the portion of data we desire is hosted on Kaggle [here][2]. I located the [manuscript][3] describing the dataset, and worked out the rest.\n\nFrom the [manuscript][3], we learn how this data is organized (see image below). However, the Kaggle dataset is separated into 3 directories: `01_tcp_ar`, `02_tcp_le`, and `03_tcp_ar_a`. Using ChatGPT, I've determined TCP stands for transverse chain placement, and the remaining characters indicate the signal reference: average reference (ar), linked ears reference (le), and adjusted avereage reference (ar_a). Assuming duplicated signals do not exist, but need to verify.\n\nThe annotations are stored in the `.tse` and `.tse_bi` files, appear to be slightly different. The class codes for all seizures in the `.tse_bi` files are \"SEIZ\", where `.tse` contains more detailed information on seizure type:\n\n![image.png](attachment:86b17c77-2dfc-4043-8fa0-b83623fbf872.png)\n\nNote that two of the seizure types are clinically determined. We might want to avoid using these seizures when training models with EEG data.\n\nEKG signal not always present, check `seizure.csv` for details. EKG units may differ from competition dataset. Need to compare...\n\nSome competition spectrograms are missing considerable information. (For an example, see `/kaggle/input/hms-harmful-brain-activity-classification/train_spectrograms/9661509.parquet`. More information is contained in [this notebook][4] and [this discussion][5]) This gives reason to include all seizures, regardless if 10 minutes of data exists, as long as there is a full 50-second EEG signal.\n\nThe dataset can be accessed [here][6]. An example of usage with EfficientNet can be found [here][7]. Please let me know your thoughts in this [discussion][8].\n\nHuge thanks to Chris Deotte for his work on converting EEG signals to spectrograms!\n\n[1]: https://isip.piconepress.com/projects/tuh_eeg/html/downloads.shtml\n[2]: https://www.kaggle.com/datasets/psyryuvok/the-tuh-eeg-seizure-corpus-tusz-v152\n[3]: https://isip.piconepress.com/publications/book_sections/2018/frontiers_neuroscience/tuh_eeg/\n[4]: https://www.kaggle.com/code/seanbearden/missing-data-in-spectrograms\n[5]: https://www.kaggle.com/competitions/hms-harmful-brain-activity-classification/discussion/478233\n[6]: https://www.kaggle.com/datasets/seanbearden/hms-hba-tuh-tusz-seizures\n[7]: https://www.kaggle.com/code/seanbearden/effnetb0-2-pop-model-train-twice-lb-0-39\n[8]: https://www.kaggle.com/competitions/hms-harmful-brain-activity-classification/discussion/479244","metadata":{},"attachments":{"86b17c77-2dfc-4043-8fa0-b83623fbf872.png":{"image/png":"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"}}},{"cell_type":"markdown","source":"![tusz_data_explain.png](attachment:6201c59a-6d9b-4256-950a-80d853255876.png)\n\n*Figure 1: Directory and file structure of the TUH-EEG database. Data is organized by patient (orange) and then by session (yellow). Each session contains one or more signal (edf) and physican report (txt) files. To accommodate filesystem management issues, patients are grouped into sets of about 100 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2Zx+KzDcH1/ds0gQS5WMpp+uuj+6vm7X7d9eXIYhN54vLLnZSQ5jjre/GR0HtsO/n24WxPdHIrnnXXmuRnq5jqtfvQw7ftvnWp0z7eF4P1aE9HKhuQOCa+x96eyE3GooCPxx2oJZe3Px4cCQGu2S9uY4dOgQzacpwh133EHEzknOmPxOnz5dNMquD2YiFL6+xk+rXbt2Bfvzuoq+Htd9paX9zCb4hTgtaa563vwAoP5FkqN8ZOluZq7F6jzdKsQHy4+kG9o9mpqP2wY6P6n2bBEIUMQGvSQTsQ8hH6eaECZQJrJWVkb4s7mn2afS5SrTRk3rerfqBMUl8kJh0in6TOrEmttkS64tNV5rXlh6+UXl7bBY8A6f1p2RRy4SeinKTiPXiQ5alikonEh1oXCTUDM5EoNwnVAz6NcUGAp2w1CFoyx4+AQY3l/cnmvfbTRJzSvMae3jbcVqpc/1BeLciPq4fboPPH3pGqoB8TAHG/rlvkqywnhHEBdpwDdecceZqIeM/JvO5WuC/PJktaL8eDE5LWTEYjoGB258PEpRAQ2sifwUly3KI71A5/l2j0X1cvOPfiL6FTJimSDlhtqIeLMo5J+sF6Ugja6p9vqss3rbFHAOrDl/G46xSGAQY8irTiK6c+Wej0ySg5vRtcN/DUj+/WwTlryxGhOeGIULpvWFvdCOFR+sF8+I2uhmVkIOjm44gbjtpw3V+4f5ouOgdtQukJ9VgJgLQg37OREVQ89PHccooVCJjCCzetdWopBUbTQI+PIX8VrorcawevToIVwZ/vnH/adDbrtXr16w0guYXR78/JxkYfPmzcISXAv9a7RV9ogOQAqFb+HJaOzny9bp5MwCDGrnHLn4sytEqA/WHM/AkBjHA2LTiWx0a1Z/FjX+fF5TVsS6OnleoVE0Wc1HhAEzR5H/Iz1UC08dRmD/Swxd8OvaH9lrfkbEVfeLfEGC6a4yBYVpegFUJuWbV7Q0b+Qf2EQz62/T8niCmUIuC0W5WURaHC/AzGVfI4CiSejFm3yI83aspMk5Dteh/IObHIRWZ701BUcI8mo9c4wm5zjIFodGCxpu/CTvc05vZC3/FqGX3iiayNu7Dp5hUVS2/q4V/bE2tG3FlofClC0IuuATQ9fS/iD/6aOfOSaV0R5TEA2arBk0kCGfyOLINByRwBx9saFcTSaY9ObT5LWQi9fCK7ir26q9IgfDemYZ+a07fNIdIc+KiPh2dKt/Nmaao0dR+LUXDIdmS1mLgL6vG/LqMqFZcOuy0Qq0xaT39q+moV3fVpr2loWOL7daRiU32F/43882o9e4rsKCqy8e2joY3Ud3ElZffb5+2zfQGwkHkvRZ4JBlycfSyNJdG3TG0JRMSARKRcBT3fPdd99hxYoVmDlzJjjsGMfo5VBlbO1VL1L242WrMLtE5OXRi4U+Hd97773CBYLz+Y+FR3NcB/+pwrr811Tkql7NkEV+vgt2JIpD/nRjPAL4UxD5Butl5DlheGaJw5/wdKYFf5H+K+OML7ciJnLk/6BGdGB7PKdrRSj6BpnAaqXq2qqUIzh4kv+rGirMQlEYrAnHaSLblYYmg4ddLaI/qL6/iZ88SRPXLjIQX79OfeFNE+OSv36ZLLpFSPn+DWERDjx/jFaXKSCYSMt1OPn8FJFnJZJtObgFYeNv13R4I/TSm5C16kdtIJH242wEDprg+ERarGkKDIFXVCuK1fqeyCmI20+T4vYgdMz1xRqOn8jpjyF53nPCR7ioIA+Jcx9Ai/vmGnSY8Ct28qdXw5jRL6fphBr1mkBKoYlgebufRh6FuRJC17RAgX71k8s8vUPh0/Zqios8VajZMvfAlrmLJhveYkSJ7wl2i+A/9Z0t3CSMauWlLMe+QN7OJ+na/JWs96F0PpMolN1c5B2YbSga2I/cIGiCnY1j/BbZkL35Tppsd7NBRyRon0Po6DgkGqdd7181VJrIL7631bySNZadw8dcVHxNaZgYv1qJflD9ir6NKmDlFdKd/Nq7I3f3c+KY8o98IO4d75bjjH3kftBxa+2JPqq4GFWrnaqA32m126hCBd4+Xlj9yUY69fTuJSML+8seXHGUHwk0maz4nFey3o+vX4Bti/bgQ/LTdZWrX7kMf725Gqd2nRFtchtJFJXhnSu+wBd3LBTqE54ejT1LD+GXF/8WFmi2Qn9203fwor7q+8R8gfvJfeeblPcxQdbruLYv0xKB6iDgQRcdXWoO2bdvn5iklpycLMKPMZG96aabwP69HTp0EEocsaF///5ISnKM5K677jpBeL/++msMHDgQ69evB0d+iImJUas1/OqaM+RXNJGQbUWLx1dCeddJRCpatq71DifnofPMtfD2NaOIHs6nnx6CZhTdQS9MZs97ezP2JOTCThbir2/ujennRetV8OLfx/HMz4cdeXy6eLRM/6e/NgKhNRznMJ5CZLEVM/reOYY+NPREUX4ueCEJdhuw52ai3VurKAZqnxLdzl7/O+Jfug4eZCllgtvuzeUlfHrZbeHY7f0EDhwqrcPHO0SIMX1lis2K2AeG04S2OBQV5KLlo/M0y65eL/XHt5H8xfMifFrQwPFoOeNT/W6xrRTk49g9g1CURbP2c9LRdtbfNKN/YAm9M3PuRdbK74Uvcdj4O9D8jlcNOjmbl+LkkxPpeMgPkq439gtWKGpFx892w7vVOQbdqiRSfwxF+KTTjcLVoSg/gRZP6EUWcXYTocmB5MrBCzn49XwG/hT+Sy+KvYCieQwXJFQppAm9A+fRtTFWr4Kc7TMorN3HdN/RwFBQaHaRCaPYv0cMeuUlstZR/OX4P8T5cdTD1RWJ8F8c01cvBXELiPDeJcKrmcj1Inj4n3ROnW5g7LqR9ue5xTycH+PMyD3oy8Ns+La/Vqsqc8WlIo6v1h7pmML6IpRcQRxlNNVyN9J+O4fwZBcutT2ay9ByPIIHzdfK8gTCwsTllOb+OPQ8KRJF2Nidmk5FN/g8Zvx1AV1z/nR+UmhAuE5Y6fXlLcfnI3cbf8VxtsdMKmzCIcKucq4M+nrdbT/UZibeOPmUu131mpcRn4XZ4z+Dhd4hDPnwOwcirGUwFlBEheguzfDI8tvp2mF8Ki4bvtmORc8sxXkUpeGa18YbC1IbByhs2ld3/UTRGNj3nMmrgjEPXIT+V/eGL8WcZzmyLhaf3PCdaJt1prwxHuwfnJ2ci2vfnYQ+E7rj4Mqj+ORG0tENKvg113NMZ9zwodF4YeyETJ3tCCw8YcHf8QX4oIZ9fA3EVwWRXRnYoltW2LGMjAyxGptapq5+GxPxVTE5Tr69MS6WXnWf47UAnCY3CPYLrm+Jf+1Weln4Ivr/3q3vrlSpfeFry+4OZQkRDVt6koj1W5aa3v2gND22HptCyNWCyGZpwpPe2EprCnS6VLjTLUxhv+Sy+24nf2MOpebpV/d+to2J+DK+HCbMgxZtYGLJUR6YBJclTCQ9fDm4PpPbBiLEAIosZ+h8G/3V66d36tOqqq1XvTxHclCjc1S19Zoo93Db/+H1E0/WRFW1UgcvBxwQUbfuT3n0pdKL3PbKWmwiJyUXgQ15Uk6tnA1ZaXURqC3i6/Ztzf67eh9ed53nJYilVAyB0kgvl1bH4A2B9Ir+kKuD+ORUsUNrcFrCx7e8XhGxYfeI8kT1uS1LzyvcGG7JnS77H5vorzwpj/RyeZ5YJ6ViCAjSy6p0vssjvazWMMgl90QnZKVrOP1Sn1a6/lVqs+rlGwLp5UPVWyUrdeh1pFzXpJcPyz/Et9yjk6S3XIikQh0i4Jb41mH7sqmGhgDHpiULmRSJgESgYgiwNZndKZzD2JLlOFyiVxD77led/JWstfo5vCAGyNWjTKGBgyOaRPX7zq4Lii2Hmiu9LgdW55TZpfraye4CbBho6ATYFZ9ssrhasiyu2SXSUR0iSuTJDInA2YaAJL5n2xmt7vFwVAd1clR165LlJQJNAAFeGKMweTVRudJdJJjMBfaZRXyvdMJXH1BZT/5IKwcaQ1KV6AeFrwvo+TT13elfXEKnghnWM0to8uAewqp0HHiSGi+x3CCFTnFjJL5H1sQiduupMgk7H9cVtAiGFInA2Y6AJL5n+xmu7PHRi9lDWnwri5rUb8II+LSeSPGfJzZKBPy68KSwuhPfDjfWXWO10BJbfIuIIJY+xKmFRmugyr6TeoD/pEgEJAKOJYskDhIBDQFHHF+ehCJFIiARkAhIBPQICFcHaRjQQyK3JQKNDoHGNnBtdAA3ug43wji+jQ5j2WGJgESgUSIgiK+94Xb9wKqjeH/KV/j5ub9RaLGV2tHfX1qOdyd/gbIWueBwZm9TiLQ/Z60stZ64bacoXNkCfPvAr6W2x/F7Fz6xGB9e+w0Or40tta4j62Px/tSv8dNTS2HNo7BsbiQnLQ/zKYQahz9LPJzsRgNIPppKx/+X6Puqj4yrcLotUAOZ3A5jtfzdtaXWlhqXjt9mLsNSin8spX4RkMS3FvGPS7OgLcXx9bhrCWL+tw4JtISjOxn+3jbSWQr/x1fiu+IFL/R6yw+nodPL6+Fx/zJ43LcMEz/fBRt9bqsNYYsvx8BsbMJLCMc9NAr7L/HDkRt7wHJkh9tD4AUlDk9th/3jAnHqBccCFK6K1tNHRBzf/WMDcey2vig4fdhVRaRPPX8NDowPwaGrW1Os0fludVIXzsHBK6OF3pl37nWrw7F242Zc4uj7DV2Rt3+jW70EKn9gQhgOTm6OpHnPltDhhTROPDkBBydGCL24R8agMOlECT2Z4YIAWfCy1lyD1J+agePUFsR976IAWBNXInP5SKQsiia95sjecBPpVO0+ydvzIrXTGWm/tEHa711hiS25QAB3wBL3Le3vLPqVtYauVddFIKjf+QffRta/V1JdbWnRlmUl+s0Z7FebvfEWpC85D7m7nnGrU9HMghPfI3v9dUin+MH5Rz5yW8yWtgU5W+4R8Xf5+Koj3AbHBU77ozst/73bbVVFlmTk7phB52eEOMbanJzLke7UhZrcdqYeMzd8ux3fPfg7+lHc3dy0XEFsXbvDJJQJb9rJTLG0McfU3fLjLlc1rHh/PZa+sQoX3dwfxzbEYd7tP5bQOUOrsn0w7Rt0GdYRIc2D8Mqw98GT6PRSkGPF6xd/BJO3l1gBjhe3OPTvMb2K2N5KC2V8edci9L28uyC9cybOK6GTT2HTZo34ABFtwtBhQBu8fdlndBw8qdQp+/85gtmXfw7fQB8MmNIba+Ztxdf3/uxUqIWtn55ego3f7cTQWwZgK62Wx7GPXYUHBl/c+RMd+3EwbtWR7b/sxXcP/16dKrSyfC2c2FGOj7+mffZsSOJbi+ey/fNrcNsFLaG8dymm9m2OVi/SJBiXFdfGfLgdefQwUt67BH/f3hdTP9iOMzqCzEHBR7+6AZN7RUF5ezSKZo/G6qMZePAX92Ss2ofDFt/iFfiqXVcdVsAE1bt1Z3Rbmo/mt72E43fTghC0mIVeeFW0+NdvRZtX/kS3P3PoRZqM07SYhaucfPYqBF4wDt0W5yDwwgk4RYtCuErCB49QkP44dP09E22pvsT3HiSCcdyglrNpCVK+fAEdP98r9PK2rxCrrxmUKHH8roHwimgp+h5991uIu2+oWA5Zr5e54jvkbFyCLgvPoOOnu5H+y/u0lPJmpwpdJ0z8TQGh6PJLKrr+lg4PHz863tudOnLLLQI52x+GUpCKiMlJCLrwW+Ruf5Bi5yYadHM23Q5zizGIvCKB9BJhzz5Ei0v816BTkQSvPmY5/gVCRv6F8IknafndN6i9h2gxtCxDcV5COXfrfbSYxheiX4o1FTk7nzLq0ApqtqxDtMrczXSu6flQSnQGW+YBig89iEL4nUec0P3g21BxGQl71kFaznmMYxGTUj7520jHM6AtfGJuKEnWy6jb3a6i3Fj4tJ8O2IhQlTIgLyJsPEy0IA2twFdicOCu0mrkqVEdqlFFrRTl98Sqjzbi8ucuxgVT++DaOZNgK7AJIqZvkElXEllEp8+eSAtN9MLdC6/HwieXCL9lvd5fb/+Lu368HudNPhf3/HQD9i87TItOGJ+n397/Ky57bIQgx+PoNyjSH1t/Mg5Otv+yh0I5emES9WvQtf1w1ctj8cOMP8ViF/r2Vn2wAeMeHYGB0+kd+OYEeHp5YsPX2/QqtHzyJrQ+twUue3wERt51IS68/jz89j9eKMUp3Uaeg5l7H8alDw/Dhdedh7EzhuHYxqoP/hnX3PR8MOlmsWQb7x+eELjp253474JrxYDj4WV3YO28LShwsVhPe+tyPLj4FiLsbSu9kIjz6BxbuWT1zs8oO0KH68p33E/OcxVrXiHyyEDX1EQS31o644t2JyMo0IxHR7YXLTw2oh2tqlmEuLR8Q4v/EImdNd4RumdwTAhGE0F+8FcnqeUH7cGXh+PVyxw6PBf6tQkd8c6qqt/Mhg64JMRqX1W0ZLlUVWdJWzoRkawURE57VLQZNGg8fNp0QebKHwx9YGuvd9tutKqVY5JH9D1vE+n4h1ZLc1oNLESOracOotktM0XZZje9IAg066lSZMlFxh8fo80LP4ks34694Nt1ADKWfK6qiF9eQjl4xBR4BTtCBEVQ/7LXkPVB9wLnVeZstFJc5LWPizKB/S+Fb6d+tOrYZ4a6Uhe8hoipM2i1MF94hTVDs5tfxOnXbnHq0HXS7q0VaPn4fC0v6tonaXncVVq6KW7YiKBajs1DwcmfiRPlw5q8xgADh9YqoJW/gi5yLLNqjugPU+i5VOYLg17IqH/g3/0xLc+7zdWwZ+zR0hXd4GWHQ8dsoAFKe1HEp9VlYlU560nHtaTWk7vjIVpt73JBWDkvkFZjKzhmvCY8TD4I6v8erTJHdXia1aIlfv273k/k+Fa6dkLo2iuxu1IZ/hTdwTeGBouepcel5lXj/LvNoGOMqVTd7pQDer9EEwevoF2ld9wruCv8z30OXiF0X+vuLXf1VTuP7jMmEQ1NeHnflONp6D7K8Z7g/sX0b0NLBh80dHXzD7vQeWgHseAE7+DV3TgObxxFfFBl95IDCCYLblSMM2Z4r8u64e+3nfcOk6+sxGx0ush5ji+8/nxs+8l4T+z9+xC6j3b2qW2floIU8kIbeonfn4je47tpWZ2HxGDXYmPf/5m7Dpc8OFTTGXXPYOz7+7Ag+FqmywZPRPSrQJxhl2IiGbvlJJ7t+7awMrM1+9m+bwmrdh4RYVXYyh7dNQpBUYEiy9PkgY6D2mHNpzqjhKpMv9W5dtj9g11TYrefRiZhv5HaXvflVqydvxU5qU5LO1vLXzh/Np6nv7RTGYgj/Sd7vC7ynun9luhNwqFkUZ4J+v6VR0Q9XNfevw7penv2bno1ykNreM+dEjDuOpODyABveNONwBLi54WoYB/8G5uJc6L8RV6e1UYvTwuGd3Su6DWgbQh+35ci9qv/dC7WV9NfbknEheeEqsma/SVXB+HuULO11kBtfNIdWLpWxsSXV0czR7d37KJjMLfuRETBuERq3t51CBl6pVZcLBhB1m07LRVsCnTgmbPuVwT0G6Xp8AaT2pwtf5N1bqTIt8YfpUUFgsiqRUSiWEJG/wfpC98GiCirwnoho69Vk/DrNpCWjj3DTz8tNJQ9M0UQax+yVguhF6t3265ExowvEMuhrVTXf7S6/HsPQ/Lnz4gV4Tx9HNcTL8GsF17C2JtwqClR7BaxdGxN1Ve79SjIXD2R4utm0kBnOq3Utw05m28j6K2IvCpTa9pO1lAPn3CyMDkw5B0+7aaRVXYeEd0Zmp6JltzViz1rH5VzDGj0+eVte3h6U7lITY3j/ypkXTZHDdHyeKMwcTWRuWe1PBOTOrr+bTnH4EXLF0upHwTMvl746p6fYSKLZF0KW0Bv/OiqUsORpcZl0HOFrl1/b61bYa1DkHQsTUvzBpPjjgPbanlcr4lWXcvLcJK51NgMhEQ7iJyqGNE+DLGbTqpJ4c/LYwx2KVAluksUeOlkvWTQe7DP5Q5DA+czCS2ir542+sqpCrtdsGVVX1coEXK9pVZYMInERneOUovB7GumPy9yr8hDWKtgLZ83mPAteW0Vkul4b/jA+cw3KJWT+Og/3+L69yfjnMHtiVzbsen7nfiL/HPtNMhQJelIKiLbOd/fnM9uHynkz1vTwlbn+L0JZKHNJ/wLkRKbLrDkQU8ODSQCIwJEk7d8fg1+J0v4MTpfoS1DEN46FO3Pa02DmUCMf9zxDksgy3/ycSpPxrjspBwaCDmoYD59be5BS0VXRGYvmwJv3XOzImVUnSJy27pj6KfwMjmvV3VfXfw2TuLrY0ILciOw041QRDcM/YiBPl+OPMKjpMjnG9O5v1iPURUFeIML8o/6W7zNu8rUAX594HxM6OG8CbmIXngJ4jA/kz4LHWnZ4v2JOVrengQa9dJDRy/RQWZk5Nv0WYbtxftTsfpQGmKfM74oDUrVSZCrA1tG0//4vDq11GhZc1QLdP4xvtQ6raeP0lKzxge1OaoNbLQEsF7YsurV3PnQZ1cAPveK1fnQt548RJ+EW+iLCYttIZFYVezZ5EbgRRY29ocuFu/odmCiq5ci0tOvEMeW36L8XHHJqRSe/XI9XJYfNke2guWok7TbMpLIKkjLFPtSf4uF0/QWpBisOWR8c5I2dT8vyZz+y1w0v5vIeA1J0AWfI31pf8f94rjLiu8dcRNRK3wf8V1ImBb/qmlxjxXvF3eom/10h1IoPWNdWj1q3ep+IrC+nf6LwPPnuj069vu0k09o6Jj1hFu00GGrZ/aGGw36RdYUgpFXnlLPCK2O598WRdlHDHr6hDVxBX0V+JkGIqv12VXazt58J7yiLqIV+c7RyivkwkAPILLQOi1uvNOTCHoRLd0LSXw1rOp6Y8wDQ5F5xkju6qIPniYi2s5LtEST2UnZ8Ak0kghOF+ZbDbpMkPxCnc8LXoiD6+ZP3qrkkH+wt5+xLj8iuFnJuaoK2FeYb0WT2TkAYMuxnkCzcj4tmqG3uDLBYqsnEy5VsrjvZCTSizel9ZPzCnIKYKJ+ehQbkoQu4cHE3ZpboC8qti1E4Lz9zYLUHSUf5aiOlR+k2guLkJGQTefbgS378Lbp1QIB4U78ssj9wzfISf65cW43U/eeL9G5KmaEtAjG5c9cjLVfbBGTBC8rJrGu1XH/prwxQfg2f37LD8Jy72U2YSrlqcKDEf5jf+sLpvUlP+0O6q4K/7YJ7wkzfXWqrHjR4P/vfe/TE915DVS2jurqN07iSxfk4lt7w0I3j4ksZHTvwpNvYP6lpwNv83NC3eZ8oaflUZr1CT1RhsgeLdRbXK44n/fTH9k/y3zglHYCvKis7t4WaoV0w3tzx4pFWINdzj1PWtOpqKrid19iLsbN3YpZV3ZBu7Dyl4k0FK5ggq29QUMmoZXuk3kFi9abmofJTA9TpwWBO6IU2egh6XJ5U9qwOAc/uen0GhYVIEKr2IwvC65bEN3iI2R3EEHyitP8w/XqdcQuuq4Uu7Nfoo98wemFCbROh3e59t3Dk45DEEVdQUEAqevUhqswMT9G90fw8GvIl3Sq6+4qp73bXAFPJmi8kIHAgO4wuv/UbfGr5VO/xD4eHKg6FCNaK6vmsZ7jz4FrcTm+O4VuWUsdlH4oHuZgGiwEIWvddOEKwOTXK6QbQkcsMRYSizIw2XaKohAJoIezO7HnxJKv9U20wMIcGhBVb+JWDvnw8kSw8MsOGJoSmHIOLeSgFx4ElOXSoNeV27WDwIXX9audiqtZa2RMBJFMIwFkdwLfYON7IrxNKLKIzKmi+n7qySlbCI9vPqWqiN9s+pQeGeO0bHr5eInbu5Asoarw5/fg6CA1KX6DowKQleQkzFYi4uwOYCIipgq7VLj6zrI7gY/Omuwf6id8VNnS6e1X7NZDt63daoe/joiqdbbs3pz8iccJf+bXRn2I7hd3QnAzY99U3dJ+p701AX++uhJ/vrxCtG2nL7TnXXku2vVt5SAOVDCqXTjYbUAveWSZDW/j/Bqo31cT22wxd30duKv32ncm4Y1LPqboFyl4Ys1d7lToGUNDbFei4l6zRO7kfk+XyKtoxp+7Z1dUtVb0XJhBrbRR85XSS79Pq8pdxDXfibJrbBXig2yaXKCXw/RJ5oGL2mhZ57agTxM254ODdyRkWxFCn29c5UhyHnq8sh7PX34OHiF/4VoTJmsuxK/W2qqhir1bExmzWgy12RLiSnzmN0e1hi3xpKanFLCfGRErb6cllX2D2a1BL/asVPh0OFfLMgWFE0ZEjnRkuzAhFmYXVwNTYBh9Yk/UynE9nmSZ1lNfbk9x7XvSSZjCmmvlTMHUXmEh2B/YVOxeodjoJUf3gYef0dLNE/qO3toL/n1GIPreOVodNbHhYfIF+8A2BuG+hl2yBfmH3ie/3pXkTpBEvtzHiTh6kRV4I7mqOKz6nuR2oBRZ6PlPWBYfWFEu4S+WFzYeqS19F7JWTyBsZ8Gn3RTjzkqmcrb8H/kd/4CwsbvoJepyv3twmhZKoElbelFoaWRTYIw+S25LBAQCQUQwfcjSyJ/4mbiyJB1Nowlnjs/fIoP+adm9GfYtO4JLHhoqsvgTfmF+oeajypktujVD4qtGd7sTO+LRabDz2mMLLQ/QmFyznzDL4TWxaOZiWY1oH44ja2MxcFofoZNFllCTF7mi6d5xbKFkkpscm4Yo0mfhCXgBLsYd9js+uPoY+k3sKXRS49KEf6/rMYqdxf9wf9gCe3p3IoJHVY4ztDu/DR5dcacgvTxASD+Tifeu/BLs79yF/KRZWvdugY0LdhS35vjhvnce6sTKsLMCiSxyPWCf3ZbdnO8AfTEeONis9P4pR/589R9x/jsMiAD7/f7fLzeWKMEWfx5MNDUhs4qU2kDggrbBFJ3B6vjCSw2k0qekrFwbLqQJbKqYiGQG0EzYP/c7HzJrj2eCJ7nphf2FO81ch7lXdcUzYxw3nH5/jW6z9c1oAKvR6mujMq/QKDHpy3rmmKN6IoTW+CPw7TbA0Bz77mb/u1DLK0w5TdsKTRZzPmCCR01D3o4Vmg5v5O5cKaynaqZ3u6406z+PrHVOUpv+6wcIdrGuerfrjlwdic7bswZekS0dFs7iypjIegYEUwitfWr1KDhxgPyBXfp+/ijwZDlVcjYshneHnmSYdFp0eNLdUbb0DrkCrZ/+RlVtkr+KNZ2iLtwNv673IeSiRQi9eC0irognwtsSltivNExMob1o4JFBvtJOkmk5+jF82k7XdHijMGU9MleNhX/vl+BbTHodbhgGtQolcrY9QKHHliBs3B4aCEW5LePd5ipyp/hF21eYuomu8TB4+jsHztpOudHkEfCkd0lkh3Bs/p4GUiTsM3uQYvoOuck4UO1HURrYz1cNO7Zt0W5BQlv1cD4DeVKcP5FOjuPLwhbDkzvPYPS9g0Wa/+HP+x0GtcU/763T8rZRSLILigmumsnhyfS+upvJTza8XSjYgquX1j2jseErR3ucv5smtg27Y6BeBZc/Oxp/vfGvlrfwyaUYfZ/R5e/fTzYJ0qwq7aXJb2wh7TSkvZpVoV+OiPHShe/i8LpYQZzZbSS6E71n+EuuLj5yT/KHZaw5jBrLsU0nRIi1geQ+oInufcquIcJtRd2p28dZp3adwctD5uKdSV/Q5DMjoVaLsO/2qd0JalJEnFjxwXoxoFEzl81ZI6z2t301TSxDza4M7145X/RV1eFfdk9hX2BVeIDDkTKqagVW62novy6mhobe3cbTv9GdwxFI/rsP/3YYdw9ujZeWx6JDlB/ahjqJCh/NtD7N8H8/H0KHCH/sScjBWorZ+8ctvbUDPUmT33pTDOAhXSNospwZ87ecgZVu5Ns+2wXlw0s1vZraEJ/OK/IdpaYarIF6TOQ763tOHyR9+hSa3/oScigCQ1FeNoIGTzTUHnzRZKR88wp9qv4T3u26If61WxE67jYiH06fLXN4NPx7Dhb7oq57Cslfv0yz2ClqQ4zDysAVsjtI1PXP4sTjl4lQZhwzuJBCmYWQa4FeIq66HyceG4f8CbcTYaEJD1+/gsjpj1EFHpoa5/Okt6RPnkTzu95E3p61sKWeQcgoI/GKmPYYTr8w1THBjtwqkr94DjHvb9LqUQqt5N7QB6aQSAQOvExEtGBSHE+RH7osStL0msoGR2soTFxO5Pcu+He5l9xQgmHPO0U+1vE0+LhQg4FdL/y6PUp+7eNpwPAjDWY20aDmDEUFmaTpKBRKi2PXmskX18MrkCy1C8lKTGGAdj6B8MuLB1uadtkbHMO3IO4bBNIM8cKkVaRMFpfEf8hHnXwHez6hFQ449zmkUszgAor24BXaExxOzbfTXdp+3uCJerY0igFOFmPe5hBrhSnhZK3uRP7Azgl0tsy9IhwYW725PXav4KgMXhS9orLCZbktAolC7sWJAQG3xW2qYs86QNbqdOrPQZElSDtFnfAK05EBVbmcXy5LjdEf9TuDnnl2shjSRENP8sNWpaiA/LnJJ9uWtZ9AIQtm6nra5en4OiGs56rmWfxLjxT+tP3eVV8idsspIqrxGEBhzTiKgl4iyNWh/zW9wJ//2/RuSdEcTuP+P27Wq4jta169DPMo5u7BVcdwmGLPcjQFJn16uXbORIrR+zFmT/hMuFlEEfHuM6G7XoUiOnRCByLEL/SfjQiaBJZ2IgOPLL/DoMOJKW+Mx1wiZqf3JCB+XyL6TuwuQn/pFXtQXWs+24zXRn4I9gFmP+PhdwzSq+DMwWT88eoKMVEumCbopVJ7TNjZNaMywsfKhHnBA7+JSWHNO0fiyDqHrzBPdtPLhCdHCX9ajnBxYMVRTHl9vH43X7oitjAvYMF+wyzP9H4Tbfu2xK3zphp0+bjY+s0uHIFkFHMn3Ud1QuueLfBox1cQ2iII6TShkAcO58xsL9SFe8OhFITShD/VZYSjefD2s9Tuc9sf0Mj3iLsvFH3nSB459EWaByRdhsVQn43n2l0/GnMezSWh4UojEnYFaPH4Sijvjmnwvc6li5cXrkijyWoxNII+/LjxJlUPYMqXe/AThT/ja23t3eehP1mLVdl6KhsXkV+v0dNRQXuqb+8M44hYLVOd35QFs5C/fxPaPP9jdaqpl7JxRDILju0WRDZmLoWMCgor0Y8CWpziBC0WwVEgAvqNRqvH5pXQ4Vvi2G19KNoDuSaQK0GHj7a5nUB2auZ0Ij+riQx5oe2rS8hK2LVEXdkbFyPhrTuZpSBs0r0Ucm1GCR3OOPH0FSg4SITE2wftabTOBNxV0ha9gxQKa0bf3hB1w3MII0KtShG5bcTeexF9zk83PLQ8fQMo7q/DCqTqNoVfJkOZy4bCM7AjnUcmYI7HXOB575DP79gSEGStneIghESUQoYvJpcC55cVe34islaMEufQWZB88cnHN5isyZWRnG0PoTD+dzpHJq2YQjOcgwZ8DHOzYVoebxSmbED2umvF+TRHj6LQZR8a9hdZEpCxbBg9N+grjU78z32RrsWrtBw+NnvGTkoXv8zo+jaF9KS+/+DM07TL3shYOoDcfJw+onxde0WPRpBukiEvllFIYeMc/eI2yY3EtzlCR60su3I3e9MXkxGAibboO/s22ig02y2G0HKWE98hjxbm0OOgEAEOvZgmNlYh8oabbjSqrKPr49CK4t36ukx20x8ET/46sfM0Ol/kvM71+9XtvcsOofOQDgbXBHWf+ntyVzxZiP3EwhJqnusvRw5IpcUmOLpAWXJsYxyFB2suLJGl6SUdTaEJbYVoTRPNSpNTRKDZb7gDWa95AlxVhCe2hZLPMk++Sz+VheadIktMZFPr5cgK+8jqy6SU5wbVidAjLYXcQyJ1Yeeq2i5/AfAiQ52fi094Vesrr9y938TgzSn7aXKc0RDoWm7hCQv+ji/ABwNDXHdVKy2Jb7Xgq1hhJsABLtEbXEvm0+jVT+fw77q/rtKp372OvL3rKUat0yWgrtquiXaYALqLcmCom178THw5Jm5Zwq4DTBzLEvbP9TB703u59IermNQmJsiRXhlSVJBPfTd+AnRVZ8suPVlLTtxzVZRpIkzku8bxbfl8E3niuLdliWLPJx2+JuroxVVWZ7R91HcOI2cq+7rQ1OWGREAiIBFo4AjUN/GtnP2/gYPZULtXHunlfjcE0ivwI1LFVpzGKuWSXj4wMq2XR3pZrTzSK6oqhzwLHQ57pgt9xnnupDzSy2UEyXZXWOaVRIBJLwuf73JIr1BrkOSS+y5JrziP8h+JQDUQ4C95PJGv7IEtfQ0hA5Q+6kQ1mpRFGygCkvg20BNTb91igkYPCCkSAYlAxRCwkRsB+5iW90L1aTO5HJ2KtVeTWlbyL+bJfWUKhXbzaTmODq/0rxplltft5EmC7GddJlY08Na7auiKy02JQJURyKD4y7PHf+4Mh+amJl4HgH2CeelkKWcvApL4nr3ntkpHxn5yVZ2tXqUGZSGJQGNHgNxYlCJynRGRwd0fDDksuN9R37nsDiJ8aMvqSA26fpCPrtNn132b9RnY3n2PZO7ZgEAYrWL27Jb7yj0ULY52uZpSobEiIIlvYz1ztdVvafGtLWRlvWcpAl7h/WiFvn6N8ui8W1xSp/02N7uoTtuTjUkE9Ai4RqbQ75PbTQeB6n+7ajpYNYkj9eBl44oar49vkzhJ8iAlAhIBiYBEQCIgEagSApL4Vgm2ihfKppVxEikEG0d2KE0KaMnA5JxCZFDYs9Lcay0U/y811yrqYv1aExG/r4F+li3noJPnv4BDV7XEqRenilXO3KkXpichbsalODStPdJ+ec+divgoHf/Wf3FgYgTiZ91Ms+rp86wbSVs0F4emtkPsQ6MoxmiSGw3AcnQXjpPP2JEbu1MsWApjVYqkfPsK9b0VTj57lQij5k4td8dKUc+x2/uJeL8ldMg3MnPFAsQ+MBIHJ0YikWIDK3IQUwImmSERkAhIBCQCTRcBSXxr8dxviM1E+NOrEf3sagQ+sQrbKSavqzCJjXr2XzR7ahXC6O+5pcdcVfDrnmSEP0P1PL8W0aTT6sW1giSXUKyJDIov2hh9fE9SHNzcbcspZu1uWqq4M47dXDI4vy0tAccpPm/oJdejwzvrkEqLWaR8R3FxXeTUkxNhSzmFTl8cEItJnHyGJyUZJWPJPMciEm+voiVwb8DxOwcQ+U02KBXE7kPs/UPR7JaZaDvzF5yhxSQy/1lg0OHEqRenI3vtr+j4yQ6xEMdRN33P270GpylucKvH56PZba/gxKNjKe5sgqGulO/fRPrP76P5Ha9SLODVtErdT6JNg5JMSAQkAhIBiYBEoAkjIIlvLZ18C8XlHfTGJvx607lQ3hyNz6d0Q7+3NyOP8vUy7L1tuLRLBJS3RyP+2YvwwpJj2EbBsvXC9t1ld/RF4awRKHxrNHki0Mpt39MqRbUhJorq0MishPbsdFp0YyNaPPABBeaPQLObXoAHxcPNXverAaHstb+Ilc14VTReOrjVU98g7cfZNKvdoulxXTlbltICHj/BREsht311MS1hvAracsjFmkkfPy72maPbCyLtSYtlZK//TauHN1J/fAuBF4xDQJ8RRMY7IWL640hbONsQNYNjBeft/hfR//eOaI9Xi+OV6DKXf2Os6/s3EDLmevh1OR+B/ccgfNLdiH/jdoNO5JSH0X72Klqmtz98aLnkyKkzkLvrX4OOTEgEJAISAYmARKApIyCJby2d/R92JSGcVle7mEgty7S+tBY6re5yKCnP0OLG4xl4YnQ7kdci2BuTaAnjp4j86mVSzyhc2N6xcokXrQpzx0D6JJ5ZoFepsW1ewrWhTkAv7SBtmcmCvHq36aKpmFt0JEK5RkvzRjYtVRx00RVaHluGaV1Kg+U046/58OtxIa3GVhwDlrT9ew9F5tL5Wjm25PIiEj669sIuvxOZZAXWi+XwNkF81byAfqNoedo4wtfpqmLPyaClXzPJ0usMn8PLKee5ENasNT8j4uoH1KoQPPpa5O/bIBbi0DJdNvKpfT9aylmKREAiIBGQCEgEJAIOBBp1VAc7WT5LSAUi71RApUS1rhkc8qSseg4l5yPMzwtMVFl8aNnENhH+2HgiC31aBYm8dA6mTUsv9mnpSHMmbzNpdid8tAcSc/HKijj8c2ctERoidEV5WcgjCyoKLOTfWkhLlFqFn6ti4236ozzYyB+Z84vT/AuxTfmFrMP7yDdWlHeW09cl9Lke1uEVyfiX/Gl5W/wW121u3hYxtIxvaVIYfxygZYM9ePGNYvFu0V64Kahp/rWlxMN76JValqcvr4VOwZOs+VpeIS1pbG7WRkvzhhdZfq0JsVoeLwvs4eUNsHW8WHxanUNWYeqHTuzZGTBHttJyvMKagS28fB7Va6cw/ijV49L35u0MFuai3CxaxMAErzAaPBULL3bhQRE4ivJzKNi6cUUydvmIf/tueFM97V5bqhaRvxIBiYBEQCIgEWjyCDRO4utDROGOJU72ICZkFZ9LlVG4y2MVNV/VE3nF/6h54rc4oea56P11ex9c3Dmcc93KabLIRgY4rYas1J4swPsSczT9PWdyack24ymICjQjkya5uZMR5Baxivx9R/ZqhhHnhBsIlDv9quRxHF8meYlz7oVCxMqDSRlZP9VfQdJMnOZ93rSP+l+s49hXrM9lmJwJXWcdxNKK6+JyxdtUHmoboi6ql0kl76f6PX0DyzwUe342rWhmXH6Y21ZcfG55OWMPHya7xcJtMAu1O91P7Hlu6iKSW5SVopYShF+sBqZeS7SH61UsznPLykzyPXSkVJBll4ly9rwcWkXOSFx5VTnF6rTo27nfjJFeihcTcDfxzqd9DzS78TkkfjgDCe8/jOj/vq4vKbclAhIBiYBEQCLQZBFweZs2EhwsZBX88NIKdZZ5DS9VyNESitTf4jw2GPM+8WvIK9alPK2M0GWe5NBvHkgWvzIkyMcEjuigl0xLIZFhZzkmuShwfvZm3TwrrVpE1mF3svKufjiemo/JX+xGH/If3vHQAHdq1csjq6lvTA+0e2N59eqpw9JsbVWIsOrFlnwKXhEt9FnC+spWX1UUsmgLAkskWRX2xbUc3KomxS/7/ZqjY7Q8U2AYkWW6BskXWh0XFVJ75ugOmg5vmAJDYc90Emaux8M3QCvDOj7UXom+p54h624z3i3EHB4NpaBAWNDFQINz2epO166nX8lBgRfph4ycSr6+F+DIfzog4pqHYHbBwlGz/FciIBGQCEgEJAJNCwH3DKuhY6CyjQr0k1U9yTJnIpcDM8Wo9SZS6Ut/ftZZ2CsAAEAASURBVLQed4C3CYFkPQ729UII/YX6mRHub0YEWWqjiNg2o7/oIB+0CPZBqxAftA71QZtQX7Qjy62vuWzoWpN+DoUwY8KtyqHkPPSMDlCT6NqMtknBogtPdirTIlwkNCWXjZgIP/xxSy/sJN9gtirXtPDnc3dWxJpupybrYxcAD7O307WBMLWeOgzvtl0NzfiSv2uObsKbiIrA10aAw3+alQN6Dyf/2lWGcpYj2+Hfc7CWx64Q7LLAbgaqZK3+Ef69hqhJ8csuGnpfXfb59QqJdH51IC1TaKSwFgvf3+LSBScOwEyEWC/ebTsj69+FWlY+kXOPgCCyhjuvJ21n8YZ3yxh4kiXaNfqDq55MSwQkAhIBiYBEoKkgUDZ7ayoo1MJxjjgnDKczCmAr9kM+mWGBpVDBwHZOksXNNm8RiIU6n94VRzIwkSazlSUpueQKQfU2Y4txTQv7yTayqA5s4WRLasbfXwo0rPHHBPENHnaVAZ3g4degIHYv2J2BJfmrmfChSWUmJqPF4n/uYFqFqwU4Ri9L+h+fCJ/joCGTijWIrFLUhaDBE3H65RtFno0stPk7V4tIC5oSbYSMvg5Zq37QstIWvYuA88cQ8XXedqaAUBHNIX3xZ0KPLccFRLRDL7lBK8cbkdMeQ/JnT4uBEqcT596P6Hvf4U0h7Bd94onLkX9gk5qFhLkPwJOs036dnBPntJ1yQyIgEZAISAQkAk0Qgcbp6tAITtT5bYIxmCIxDHtvKx4c2hb/Wx6L4eeECuuxvvsPD2+Dm7/bj0K7grVkxT1KrgxPjWqnqRxJyUOn59Zg1LlRuIR8ilNoMtyslScwc3JnYcHWFGtoQ1h89WbqGqq3Vqshq23M3A04ftcFyPjzMxRSDN42L/5Ck9Kc7gLcPocCi6KYukemtIVncLiw9Ma8u65E11o9/S3i7h+G9N8/RCGR6PbvrCmhE33fXBy/50IcufYc2LLT0OzWl0T8YL1iyKipsMTuwcHLI4iY+4swY9H3vKVXEdbfmNmrcezuQciiGL9MfFs/8z25JrQ06HEoM560xgtmKAX5CKZJekEDnO4+7ALh130g4h6+2OFXTRZwT/8gtH3ld0M9MiERkAhIBCQCEoGmjIAH+bjqPsY3fCgSaBW0Fo+vhPIuWc4auDCw//l6L3aeycGgdsH4+Opubnv81qoTmL81QbhWfHJNV3Kp8DX4ga4+loEP1p3C3sQ8cs/wxPR+0bhncGu3dVU3k2PdpiyYhZh31la3qnopX3DyIPRhxtx1gl05CpNPwlvnt+tOz3JsF3w79HK3S8vj+L4cuUE/iU3bWbwh3CLIysyW6bKk4NQh8vntXJYKuS2cERP5TBQ3uDSxUsg0dvExU1QHKRIBiYBEQCIgEWhICNz7TQzenLKfjHfGSemufVx4woK/4wvwwUDjl3JXvcqmpcW3sohVQp/Jx9fX9ii3xAPD2oL/SpOhHULBf3Ui5OPb2Fwd9LiUR3pZlyMklEd6Wa880ss63i068E+Zwn64ZfniqoXLI72sx24Y5QmHMZMiEZAISAQkAhIBiUBJBJzOhiX3yZymiAATX90CC00RAnnMEgGJgERAIiARkAicnQhI4nt2ntcqHxUvAtHIvF+qfKyyoERAIiARkAhIBCQCTQsBSXyb1vku/2g54kDjcvsu/5ikhkRAIiARkAhIBCQCEgFCQBJfeRkYEOCoDtLVwQCJTEgEJAISAYmAREAicJYgICe3nSUnssYOg+P4SotvjcF5NlVUpNiRY0k7mw5JHotEQCIgEZAI1CECvuaSq43WYfOiKUl86xpxl/Y45Bmtgoxf9yYjmWL0DqSwZz2j6/HCYB/fRraAhQuk9ZpUiuzI3fwX7DnpIm6vdyvjCmz12rlqNv7X3vfwz4GPqRaOVyJFIiARkAhIBCQClUVAQbBf2Yt0VbbGyupL4ltZxGpYnylEnzc3YedpWk2MllWm9Yvx7rTuuLuW4vSW130PD+nqUB5GZe2Pe2AErCcP0bn0RFFuFlrM+BQhI6aUVaTR7Ptj15uYM+0oPHQrzzWazsuOSgQkAhIBiYBEgBCQPr71fBm8+Pdx7DyV5SC93BdfLzzx59H66xWTb+nqUCX8k7+ciYK4/YL0cgWeAcFInvdclepqqIWsdktD7Zrsl0RAIiARkAhIBMpFQBLfciGqXYV1sUR6TcbTkEUuD/UnHiiy5NVf84245fz9G+DhZTYcgS090ZCWCYmAREAiIBGQCEgE6g8BI+Oqv3402ZYv6xYBFBYZjj882NuQrsuEb0wPtH76m7ps8qxpK3DAWChWo0XUHFU7S0ufNaDJA5EISAQkAhIBiUAdIiCJbx2C7a6pe4a0xsXdI8lvsnivXcGHV3Z1p1oneZ7+wfDrdkGdtHW2NRI+6W749x5Gc78cJ1OxFSL6rjfOtsOUxyMRkAhIBCQCEoFGi4Cc3NYATt3S2/vgSGoe8sny2zLYB5EBxs/lDaCLsgsVRKDNCwthTYgly28BvMKjYQoKq2BJqSYRkAhIBCQCEgGJQG0jIIlvbSNcgfrZQNgp0r8CmlKlwSNAEQ+8W3Ro8N2UHZQISAQkAhIBiUBTRKDRuTqIgAPkDiBFIiARkAhIBCQCEgGJgERAIlAZBBod8Y0MNGPrkxdW5hilrkRAIiARkAhIBCQCEgGJgESg8cXxNVOc2X6tg+SpkwhIBCQCEgGJgERAIiARkAhUCoFGZ/Gt1NE1EuWFu5IR9ey/8Lj3b1z68Q4k5VgbSc9lN10RyF7zM47c0A0Hxofg9MvXw56d7qoi0xIBiYBEQCIgEZAI1BMCkvjWE/Bqs1tOZuOqj7YjhRet8DFh6cE0DHl3m7pb/jYiBPIPbiayex0tVZwJT98A5G5dhlPPX9OIjkB2VSIgEZAISAQkAmc3ApL41vP5fXl5LBFeY3CNw0m59dwr2XxVEEhZMIsIb6ChqOXoTkNaJiQCEgGJgERAIiARqD8EJPGtP+xFy8G+Jvo1RqnwNKmrWdRz52TzlULARIt/uJ5LD6/6W4WvUp2XyhIBiYBEQCIgEWgCCEjiW88n+eVx5zhW+lK5L4Vqu6QLLWMspdEhEHXzi9RnGrSImHv0Y7Mi8IKxje44ZIclAhIBiYBEQCJwtiIgiW89n9noYG/EPzMEA9oGwc/LEy+M64A/b+1dz72SzVcFAXNES8R8uBU+HXrBw8cXUTc+j5YPf1yVqmQZiYBEQCIgEZAISARqAQGjc2ktNCCrLB+BFkR+N97Xv3xFqdHgETBHtkS715Y2+H7KDkoEJAISAYmARKApIiAtvk3xrMtjlghIBCQCEgGJgERAItAEEZDEtwmedHnIEgGJgERAIiARkAhIBJoiApL4NsWzLo9ZIiARkAhIBCQCEgGJQANGwMujdiJcSR/fej7pHMzBXqSA4/keT7Ngap/mGNMlvJ57JZuvGgIKRXIoROrCObClxiN46JXw7zm4alXJUhIBiYBEoJYRsFIUoaF/pXEsGikSgQaJwI0d/Wq8X5L41jiklatQodBXMf9bh1PpFsDTA5+vPoknx5+DmWM7VK4iqV3vCCh2O47dcT5s6Ynw8PRExm8fotltLyN88v/Ve99kByQCEgGJgB6BPJuCS5enY8NYGT5Tj4vcPvsRkK4O9XyOH/39iEZ6RVf8vPDW6hP13CvZfFUQSPrkSdjSEoj08qIkHvAMCBHW36rUJctIBCQCEoHaRICMvQgyeyCHCLAUiUBTQkAS33o+2/sS84SlV9+NPItNn5TbjQSBghP74WEyfkQpyklvJL2X3ZQISASaEgJ2+trILg7SzaEpnXV5rIyAJL71fB3857xoQEd0+SHULMSnnnslm68KAiGjpqHIkqsr6gFzdIwuLTclAhIBiUDDQIAtvjx3SBLfhnE+ZC/qDgFJfOsOa7ctTevbHLcObQtvEz1+aJJbkK8Xvr+up1tdmdmwEQgZOQ2hY64XVl+lyA5P/yC0fOijht1p2TuJgESgSSIgiG+TPHJ50E0dAQ+aXCUdfBrAVVBITyE+Ecx/TTTJTUrjRUCxk6sKf0ZkX1+a5Ha2yL3fxOD1a/bCx8v/bDkkeRwSgSaLwJl8O+7ckIUFQ0Phxy8eKRKBJoKA0SGxiRx0QzxMs3zwNMTTUqU+ufr5VqkSWUgiIBGQCNQiAtLVoRbBlVU3aATOHnNUg4ZZdk4iIBGQCEgEJAINBwHp6tBwzoXsSd0iIIlv3eItW5MISAQkAhIBiUC9IyCjOtT7KZAdqCcEJPGtJ+BlsxIBiYBEQCIgEagvBOxFxVEdpHtvfZ0C2W49ISCJbz0BL5uVCEgEJAISAYlAfSHgcHWQrLe+8Jft1h8CkvjWH/ayZYmAREAiIBGQCNQLAs7JbZL81ssJkI3WGwKS+NYb9LJhiYBEQCIgEZAI1A8C0se3fnCXrdY/ApL41v85kD2QCEgEJAISAYlAnSKgRXWQBt86xV02Vv8IyDi+9X8OZA8kAg0agYMJa+Hp4Qkvkxn7z6ymbRM6NR8IP3NQg+637JxEQCJQNgK8VpKXJL5lgyT3nnUIyJXbzrpTKg9IIlCzCHy36Qlsjv2ZiK8PraptJ8IbjOcnrqnZRmRtEgGJQJ0gkFVYhIVxFqQUKNiYUojrO/qiha8J/SPNddK+bEQiUN8ISFeH+j4Dsn2JQANHYMqAl4j0eotesuX36vOfb+A9lt2TCEgESkMg2OyJ9UR4/02ywlqk4KND+bDREutSJAJNBQFJfJvKmZbHKRGoBgIju94Ghf7z9PBCj5Yjq1GTLCoRkAjUNwKTWvsQ6XX0IsLHA4OiHAPb+u6XbF8iUBcISOJbFyjLNiQCjRyBizpdB5u9ADdcOBseHtIpsJGfTtn9Jo7AuNa+aObrAb6TX+0nffWb+OXQ5A6/Wj6+Vls+2YCKh41NDjp5wBKBpoOAiSy9G479iH7txsPk2YjnxNIXXRNN0vPyLN/CNXllOnJt8hNw07nKm9aRmmlmG49h2d2BXuRSJAJnHQJ8fX8yKASt/U2GY6vWG+yxhX1hK7KKT6CGWmVCIiAROOsQYPvQ91ueatTvSLOnD85tPRo3DX633PNzJr8IS0aHS/JbLlJSoTEiYKV4Znn0F+otP/w2xvMn+1w2AmYivTety4TFXlKvWsS3kD59vjP9eMlaZY5EQCIgEWiACPyy4xUkZ8dWqGdsBAvxsiH+nwXw8TaTfzNg1z5wKfAIb48OfQZVqC6pJBGQCEgEJAINA4FqEV8+hAJbHny8/BvG0cheSAQkAhKBMhCwFxWWsdfNLms+Yj/6LyLCw5GQBwrl5okRbSmmMbl4bYm6TBJfN5DJLImAREAi0JARkN84GvLZkX2TCEgE6hcBchLz8Q9AoZcvTN7eiGkeAi9vGujTn8lcvp+wofPKfvy6OQ4fPX4bVsfmGnaxk+XTEyfg0im34PCJbRg9djxueuoDcsBMwth+gzH+liex6IMvkOhSSiYlAhIBiYBEoHIISOJbObyktkRAItCUEKDJbcHkAzmwpTcu6+SLc4KLHcbI7cGki27xzZzH8e4fOwzIKEoR5syaib93nEbCll/w3Ke/4Mz+v/Hlklh0bRFg0GXHaY+APvj+u08Rak/G4/N/xdNDTPjg583oPeZe/PDBi/DMPYPP3n4FSw4UYOM3n2P+Hxuw5MOX8NDMd3Fk1yokWGz44aMliD+xG1vXLMOjTzxDdukCvPHck9hxKhlfP/cqTp1ON7YrUxIBiYBEoIkhIIlvEzvhTflwlVoK0p6QkFBhWGurDxXugFSsHAK0nmtmQRE2nbYg36ogm7bXn7AgPdeG1Hx11kQuglt0wbZ33qGFAJzVZx/8HskeITh84B98seAAnruiL0J6nIfp4yajmQ/pFaXi49nv4GiaVRTKz4zDdwuWkjXZm6YRFiE0IoqWk7Xj2I4V+HLhUmRkWzDpzvuxdNZ9+G3xblx8QQT+Tj0fjw8GVmw+hD9/X4ZfD27HT18twcHEZIy76hqsf/8p5HoFYdnKZVi5Jh7RrcKcHZRbEgGJgESgCSJQq8S3qKgIhw4dwuLFi5GYmAi73Y6kpCScPn0ap06dgsVi0SBPTk4WefHx8eK3sLAQGRkZ4DRLTk6OyD9z5oxIcx1qPSdPnhR5/E9ubi42bNiAtWvX4tixY+A+5Ofni7Ksz31g4XzuA+epbYgdpfyTnZ0t9FNSUpCamirKcZ+4PbUe7kdWVpaogevfv38/fvjhB2zfvh15eXmibdZV9fmX62BhLNasWSN0rVbHi5CPVT1Gxo/rVPvNZZlEMeliHc6vCeFzdcUVV2Dq1Km48sorsXXrVq3aJ554Aueffz4OHjyo5TX0Dcbez88PzZs3dxt/lrHjuLQ///xzlQ9l8uTJ5Zb98MMPERoa6rYPJ06cMNwLpVXG14W/vz9++umn0lQqnX/11Ve77ZO7ivi+YqwY0yYjdI91p+D+MeFmbI234EhqIQa29aV5DR6I8CsOkZO+C2uPZiAs1E9MgGNsVn39EdLa9qXz1QyDBwxFeOE+LPp5OaxUn634GQTPCNx2373oGO5wmfD0NCEgzIysHBtW/7oIH/y4AxMvOQ+d+l+K26eOJb/iTCxd9Bt8z5mCyOBgBESGwnpkOeYvTsSEKVdjw8J5mP/QYBxtOQJjB5yLg4vnI7JnTwRHtMaofl0REtxMxG1tMudOHqhEQCIgEXCHAJGnKss9X7dXLIW5bssTwVRatGihEJFSiIAqnp6eCpE3Ze/evcqwYcOUpUuXKpmZmVrZAwcOKMuXL1fatGkj9hFZVYgMKz4+PsrXX3+tEAlWbrvtNoVe+qLMqlWrlCeffFJ5/fXXFd5mSUtLE20SMVN+++030Sa3kZ6errz//vtK7969lWXLlgldIhGi3EUXXaSsW7dO5JX1DxFf5dxzz1WI3CpHjhxRoqOjFSKtCpFgUSfvW7lypThGrue+++5T3nzzTXEMnTp1Ev3ZtGmTyJs5c6YyZswYcZwPP/ywQuRZCQoKUvbs2SPqYn0Wbqd///7Kxo0blTvuuEN5/PHHRf67776r3HLLLWJ73rx5ChFShYivSFf3H26LBicKH+8111yj7Nq1S1RJpEf5+OOPxXarVq0Uxq+xCGMzcODAUrv7/PPPKwsWLCh1f03tuPTSS91WdcMNN4hz7HanS+Zbb71V432l54LC92tF5M4771T4Om6ssnDrC8rHq++oUPcv+DNFUfIzlP03BCj5j7ZW9t3eTMmZ0UrJfqSVYnkkWln3prMeS36eYsnNUO6ZNkW5bOwtyv4Mm8J3ZH5erpJnsSpFdquSV1Cg2OlatBXSArFuxGrJV3Jy88S5yKNngtVG54T0C4v17YWFSh7Vx2fKZi0UNRQW5Iv6OVEo8qh+O5WxWkjXInS4D/kF1uL9Ikv+IxGQCEgEznoELluephzOKvm8ZathlaUs4rtixQqNqHEDTOqYvLJce+214tfdPz169DBkn3feeUq7du1EWSZ8ZEHW9i9atMhAWvmlHBcXp+2fPXs2PfzzRPrpp59WbDabcvHFF2v7eWPatGmGdFmJcePGabt79uypbfPGyJEjDelLLrlEa5uJJJP4v/76S9m3b5/4ZRLP8t///ld54403BLlXK3jllVc0Mj927Fg120DemjVrphTQi7RPnz7aft74888/BUE/fvy4Ib+yCa6bcVdlypQpyuHDh0WS+86kvzRhItmyZUuFLN7ijwcvPOBgDHr16qXweRo8eLDy6quviiq43gEDBih333230r17d3rRO17qDz74oHLBBRcojzzyiEJWVeXyyy8vrUmFLOCijoceekhhgvnNN98YdF2J79tvv6107NhR1N+vXz+FLPMGfX2CB2V87pn48/ngAZSKxTPPPFPiHNAXBKVt27bKMBrgse6IESNEdUOGDBF942uQLMAij7HiQRRZ0pXhw4eXS2rnzJmjdO3aVQxK+BrkQRPL999/LzC6+eabtfuLBy18jDzI4utx1qxZQpf/4QEVX7PcP5X48gCV6+TzwP1RBzqMPw/s+Bzx/bhlyxatHv0GfbVQyKqtzJ07V2RzmuvhQSDft3wueaA3atQo5Y8//hB/ERERCn1dENcD46Ve7y+88II4Hh4U3H///aI+HtCS9V7cw6NHj1b4XFdWKk18iWae2rNRSTywRUk6uEVJoF/H32Yl6eSxyjYv9SUCEgGJgESgjhCoc+L78ssvK+vXr3d7eNOnT9fymWAxIVXFlfjyi5Mtxc8++6wgC/zyU2XhwoUKuTSoSaVbt24a2dQyizeYiJCbgsL106dlbTe/dFVhK2dZwpZYJmxMothCqxeV3Kh5TA7at28vXvZslWYLKR8n/y5ZskS59dZbhSoTcyaV5LKgFhUk8amnnhLpyMhIYd2lT/UaGeYdbKUODw8vQfC4bsYhNjZWq68qG1yeBxqqDBo0SBtUsIWZXDrUXW5/GW+22rNFnFwnhA4f86effirI/+7duwXhYnLEwhZltl4zKWLyrgqTb/11VJplOyQkRHxZUMt5eXlppJDzXIkvnxtVmNSpXxLUPNdfJpF9+/Z1zRZpJnZ6ufDCCzUL/DvvvKO89957Yje3owqTQFXYeq9a1tW80n65PnXAwCRStb4y1vwV5ddffzUQce6LKkxcWXgQqB4vnx8mviwTJkwQxJu/yuzcuVPx9vYWln++B1UJCwtTyP1FTZb45S8oPMDlLxRcNw9YWLgu/vLCwudQbVPtX2BgoNgXExMjLJ58LzI5/vLLL4Wuet7J1UK79vic658dooJy/qk88S2nQrlbIiARkAhIBBokAqUR31rz8SXyBSIs9H4rW7799lsQgS1TKSoqCmQxFD67ZSmSdcutryR9xqZlSk0gS6D4JYtqiWrorIGITYl8fQa9lIUfLh9X69at9btKbLM/J1ldhb8xvfBB1mfRttlsNuiy/ynXS1ZFLZ/9d4kkiTRZ2ECWN3AdRNY0HSKiIGsvyGKt5fEGWfdApBJEGA35lU289NJLws9XLdelSxfhK81p9okm1xV1l9tfIvsgixwee+wxfPLJJ0Ln6NGjIHcUEKERft8fffQRzePxxvjx40GuKbjuuutAFmHNT5oLMc5EWrU22MfUVdhvm32tyXqo7aIBA1R/cC2zeIN9lIcOHaplEyEEESgt7W6D/cRffPFFd7s0v3F1J7nXaNchWXO1uvXXDA34VHWwPzsRPS1d1gYfK7kDCRUaiGnt0EBMnBMiryVwUOvjsizsS87XFQtff6rweWWfcRp4gEi0OG9EyKH3YSZLcZn+5GSdBVnTQW5LIBIOIrSiehrwgSz/YpvPIZ93xlTtEw3ixD6+b/ja4uuXz+d//vMf0UfVF57L0qBG6PJ+vm+lSAQkAhIBiYBEoKIIlM1eKlqLGz36FAn6VC0IDr/U6ZOlmOhGlhvxwuPJbDxhiwkdv7yYePDEMP7lCWTqC40JAk9yI/9ZkKVLa4nz+I+JlEoayGUATAbok60gnfxyZ0LExIuJ5ebNm0GWLEFGuSLex5PKuA7uC7+cyxLWZeG+MVlRhfvBZbk+VbhtJqAsPMHP19dXbPPxcXs82U3Vp0//oE+8ok4ma+TLC550xDpMDvhlz6RRT3K5LLep9klUTv+QXzGYXJPFWc2q9C9jPn/+fJBFTStLn+RB/qXi/PDkKvV4NAWXDe4/T4xjDFRSQxZfMemQrwv63C8IMOPB+NFnd3GOySKsEUW+RhhnxkGdNOjSjEjyoGbGjBkCN85g0kauIOCBEBMrnlCp1sO4MYnnSXx8jHwsn332WZlkjnEm66U4b1yXem1yW+q5VCc9ch4TP2574sSJIGsuZwnhc6mK/vrhgc8///wjSCe5GYjJj6qe6y/XoZJmJoN8/tX7hwdLZF3G6tWrNR19m+r1Te4ZYgIj3wvcHgvfl3zO+LohS7IYGJAr0f+zdx/wllXV/cDXdGZght7BGdoAIiAIKBoUjb1h7EaDaOwRrEjUv4o1sSTRRGNDwcSoGBXsBZAioYj0Ir13gaFNY8r5r+/GfTnvzr1v3rx5AwPe9fm8d8/ZZ59d1l57799ee5+1IjXTYRFkYXL44YdHHtfpgNXusrkHksXPYxVh8ZNHKUq0t7/97SXMjYVoHi8pgLbWpQLgyheLXTxMDXfpA7Xs6qqsSNx2W5TAVfmvWRL3JM8X3rcozjnt9Lj+7uEXS7UoC+bdG3TcixYP8wFq1uunvzqrvtL3d9GCbH99Yv7cLMfI8u8kluU/6sendW5X5uLu686M8/54y5/dV3cvPhbHKadfMKLk84xyjt9zs8/Pix8eeXxYmj2obTpsKZsco+flOLsw5i3smhuWLo5f/GpkY+yibP9FZZOjnVnl2dL82HEYuWi/8iBe33rZafG29344FqVLY3Tu75dVYuW59fjwwQfHpXc8MBc+iEV8SLK67vzfxZy7H1BatAtxzYUnx73zxogX2Ve//OkPxPGXrJj5wSYd9Bx/wlCziu0y3jd/XizI+X3uvTl+LFzB8aOd0Apc57cHQ2M3i+PMU0/Jfj40eDR3t958dVx8w8iURu30Jxya1A5Yketfnv+FeOZO/xATxw/VYkqDRueQQw4p2sr8OK1MiLkNWsATLZOJnuYJ6GFBILc04wc/+EHRYtIW0b4CqyY3EzltbZ7/LJpQ7+d2bQBGtKrHHHNMAY40QHnkoEy40v7kJz9ZwCUtFtBLy5cfuRVNEq1qngON/ACvaKfEzzOWoYy9SJmAiDwCUMAzYKUctGQmZ4Cbpky9t9566xI3jyMUsCDNAw88sCQLTNAYA4N+AT5aLqCWhlRdAQOaMgCCNQJAliZUfrSV8lJ/gAkQASKrJpSmzJf/AEi3drlXvXqF4em2225bQE99DgSrO/D74x//uJS5Puv3mx/Kxbe+9a0OSAbM8PCzn/1s5Id78ba3vS3ySETk+dPCJ9YN8nhFkQMLpzzeErNnzy4g9Zxzzint0y+vPCJRgCOwBSTjIc0h2QDY7EAAuxYhub1egJ84Fl7kNLf3I8+Y9kw+j4+UHQeg184DHmv/3/3ud6W8uf1f5Nmz5z0vvXll++eZ4MizuEW2aYDrAs4izX1dAALh5E67A+Hakga6tme7QBYJ5ND7ZFk74CMtv/fIi7xpXS32yJgFnXLLry7yaNjJhvrrV3n8p7QRGRQXD/UP6dBYi6N/0rRqM22RR37aRRtyTf7yrHGxWJLnskt/ww+LIIsC7SI9Oz20wGQ9P5gsv/hqUaVfkBO8Jss0z/g8I60ZeEef9qtM+sFI6Y83nRTzF90Tu898/nJfOezy+fGG7R7wSvm1f/pw3HwXkDYnjvnlGbF5jkf/d+wvY+Otto2pE/9s4aEr1dO/+h/x07MvjYuvvSvuXTw9/nTRiXH2FTfHuEWLU5Z+E1tnPzvmZz+M+VM3S1k9P7bZ4NY46aJ7Yvas3hYYLvv9r+ITH/xw3LRoXPzptkUx55pzY26Mjyuuuys2nnp3/OQXJ6esbxe/POp7sXDtreOq434S1y6cGFeefXzccM/UXBSeF3vtNCGOO/XimL3NzK7Stm7nXx/PffZr4ul/96o498Tfxt3jJsSV19wS4+65Pn557O9ivUn3xI+Pvz6mjbs4DvvVBTFz85kx7r67okm5+nlaSPnDFffEThvcG7898+bYbutNY9l9mojF990eh3ziG3FfAt+582+MX/zmsvjDL78Td63/qLj3j6fHHZM3iPk3XBSX3DA3tthk/VbhHrj87396R5w2bpu4/H/fE7+/c+uYd8nJWe+ZyZeL46TT/xCbbDQ93vHBL8e2aYf55N9fGNttv02c8osfx3mZ5rYbLU1+nR5bzd4mzcY9kGa9WrpkUfziqG/Gp//tyFgrzcCde9q5sd1Os+MPx/w4rp+/dvzupAvTocld8buzb8o6bt6zjrdedmZ85SenxuVX3x3bb7gwfn3S2bHlxgvj3R/6Vtz7pwvjlCuvi2bxpLjy3N/H1Xctic2n3BHfP+q4mLHRJnHCr34R0zadFWtPXXZ+rWX0e9wPjorpm28Ta64xIS4548S46IZx2R7rtKMsc33KMb+Iu5auGxut/4B8tyNdcfG5sfU+L4nbLjgxLrxlYcy58uLYaN0E+8edH5ttOj1uuXtpzLv8ith0/N1x2/StYqsN79/Zaafh+r6774hf/OTXMXunHXryp8afe8t18cvf/iF22H7rDFoSx/zoJzF9qx1izeF8y6ad7BOO/m786ORz4rGP2zV6c2lpXHPxVTFjvelx05/uielr3q+AqvnW38t/f0wcc2qOMcn3X//8lzH70TvG+af8Oi6/bY2Y96cr45Lrb4xbLr0g5t5+WZx46qUxY/Ot4rYLj4/TLro9+9Gm8evcub742itj1sbrxTV3Lo0N1+my0/3njM4++Zg4/YIrYouN14yjjjotHvOYreOEn/wwlq6/Zdr4/n1cfN1NcflFF8XiG/8vfnzW5HjBE9aLE0+5LtZec3ycd/YZsXDCtLg7++GEKeNzrL4+fnvCKbH+Zhtlu58R89ZYL36XY8mxZ94Uz9z3sbVqrd+lccHJP4/P/suX4p5FiWXSROPdN14UN941L6646c7YcNKd8Yvjz4vtZm8WPz36xxGTJqZn3vFxX7bNZVdeH6ef9YeYmfPxKf/7vbh14vqx+QbTW2n/+XLpwvjaxw6LTTa4Pf7xq8fHJnefE789b06sOWVeHH/SGTF7+9lx8rE/iWNPOid232HdzO/K2GSzNVOZkmNZmodckHP3tDV7yeSSOOyL347t99o1zv7JYbHGuhvEcb8+JcZPmxiXpW3ya889Je6ZMD02XW/GkDJ956oF8ezNp8R6ya82jcvV9ahx94Hf2So+9/ILBy6L2xwdXBfzasAZIEWDOFoA/nBmpXrTLlvMAHgA3IAeeg786KyPxx1zb4g37POV5RbmCb+8PU57zgOA6yv/701x2vWL42nP2jXOO2tJTvYLYsEaa8WcidvFJ972nJ7p3X3eUfHe/zkrXvyCF8alV5wTa8zYOTa589Q4/sQz4n0HPSt+e+cusdaVv41/OvHOeMnjt43br7g+XvTXe8Rez3tmmkbrgcZSx/qDL342nvW218Vn3/mZuHf9x8WFl18fT39yTkJn/zGmzF4zQfWEmBM7x+O3uStuWufJ8fInbREn/PBbafbsrNhp931i/hUXxtQNIl707k/EzjN6w4U//uKwuOW+uXHlvEfFCT+9MG5IWd73rzaOKamZfc1rnhv//LUfxbh714m/f/Pe8acE1tddMzF23fi2ODcB6x5PfV2ceeLRcdaPzo8Zj5oXB7z/S7HNZstOkksW3RkvfukbY/paM+MpT988LrlsRsyaMS+23XlmHH3CuXHHVffE5tuvkwvgg2Odyb3L+asf/lfceOrpEY/dNebedEvEhn8VZ516nO2AeMv+T4kLliYIvurGeO1TN4z/+OaRsf6eu2Za28XE60+JG864JCZuNSEe9eR/iJc+aXbP9suDXXHYf50VS87+aTztNS+MHxz7+5iy5p4x9+pjIjbZJeZde0O8+BXPjN2f+PghDk1qYvNuuzoO+tgX4iUHvCnOzN2YSduuHU9+yUvj7P+7NfbaLjVh664TJx/1w5iw0dMibj4xrrlkbuz/D8+Kww4/MzbYe594wdN2jN1mblGTG/J73z3Xxmc+9q/x/Pd+Jh670YT4wec/GPO2e1Hs//wHjoYNeSFvFi24O474p3+M7V783th3VyCzN11w6q/ipnEbx3Gn3Bxb335G/HH6xvGxAx4fR+TCdb2nHRDnn3pl3B33xN/vMC3u3WW/eMqOG/VOKEPn/emaeOcnvxHvfv/7YoeNewNkL99x+e/jff95bHziU4fEhuPvjc9+5BPx5JcfFE/cbcueac+bc0V6QFwznr5lLviOuz3bYe+e8Y496qvx2J13i4sWbxFP3mGznnEW3POn+PTnvx6P2nBcPPHJT4+fpyJi0txNYvLc38fZF0+NDbaaGtvtsVPcfe3FsddTXhzH/OLYePWzt4vDvv7fsf6jtosdn/2W7MffiaNPHB+H/MtBsdGk3gvh+XdcnQq5L8a0u+5OO9t7xn8de3Wm+9yUh9/E5pttEWvHDbHTDuvFJqkQOu+qSXFZAtvnPmV6fPc3l8RTXvuBuP3o/4371r46pu74wthh5jZx6vE/iYsXT45tJq+dJgwnxO1r7x1nn3BevOsdL+1Zz9zbi58deWQ8fb9nx8c/8tWYue2G8cdcmG+x8fi47vx7Yr2d0873GmvH1JmPjeftNCUXuZfH5DTFeHZ+kvOG/Z8Q3z3t9njKM54dz9plk5g+7f6ja90Z/f7XX4ur75uddbkjbr/q3Lh96eZxz/yb4wXPfELaG/9DbLjunrH41jPj4vNui6c9c1accNHU2HWvteO8O9ePv1p/zVTk7NWdZN4vja8denD85orbcqt+YY5bG8WE7WfEVdesFbttPT92eMIL47zjj413f+SQIe8+/7dz4vN7zohtpw9tj6EweMgrg5sBB0bHAVpD2+g0qXULe3QpPXzfcuaWhpZWeAB6H77t2C75lE0fG0cc8c3Y/6k7xIJ5eewplUdPe8nfxvtf/9ftaK3rJn575fh4/4F/F//3P7+M8bndPX5SU7byp818cmya2o8rfn1k3LvFU2OrBIG333JXvOz1z4vv/9ePytGIVkJDLhfn0ZumSRcXEyalBnLH2HHWDrElTfgGk+JvX/3OeO7znxFP3HZ8/OrEq+Pe+QvjipN+GDdM2S12WndJ3DV3SczYbLM46J3/GDv1Ab2R3t6++53vx7wZW8elF54U2+y+R8ye+ejYau1pMW3DjWLBffNiw/WmlqMbkydOjhvTscZtN18fl116Sbp1zolz8d1xXe7kbbTtlnHQh/81Zm3SG+ykAbZ4/us/EN/+n8/FtlPHxYIs65r33BtzlqY2dqdnxH9+/f2x43Y79QW9mDL/3vvi9f/0qXjVM7bP9xfFwnnzY+mUibHFDnvHzNSETV20NO697Y447Lsnxitf+ty48+Z7soxNjMtdyqkbTopXvu6D8YLHbzOEv9039+URlUnjl8TC+Qticu4y3LdwXizKRcn81JT9zRufG8d9738jLch1v1bu59xzZxz8jnfElcedHJNmbhxvesu7Y4/UgN+dR6cmpWXmmxcsjKWT1onZO+4am6y/XjTjZ6QTlCY2fPRjYr8dF8ep59/cM12Bk9faIl51wN/E9//p43Hf0vHxnFfsH9eddHSccWvvrXjvTFpjRrz47/aPn/7Hl3JR07vM4uWBk3RNOCE2y7ZbtN7asd7kufGpz/wkd3/2ivmL14vnzLwoXvA3r4vJTR5O6bU+uz+RTOa++NanPxcveOkrYvthQG+z+N740r8fGQe87tWxSWquv5cAe/0nvigev8vmNaVlfqetu008e7dNYuIGs/uCXi/t/bi9491fPyF237o36BXn5O9/LrbY8/mx7riFuTs3LyZPXSOW3jc/8jBVrLXlDrH9tjvETtluKTkxPrWTa0y6Pb5x5FXx1N23zJ2L+Xkcb0Ha6F4jttvmqrj8yv5b71877Ovx9De8J/vI3Jg/977MZ3KOJSkDUybHprlbN3v29rFVlnONDJ8+fd2YkvxbMP++mLTBzvGYR8+Mxz9jcmzwlPfGXddfHLde9YcEzy+KiQmit31sHh2buFaOG/PjmtzFHI6W5G6TJhs3YXzM2mG72Gb2o2PT3E2buuH02P/A98XrX/7keNqmc+PUqyfFzuteHlN2fEvMevTesd2jNo0ZWfd7s7zDHc+ZvdUeceqZZ8SOmy6NP0x7YUwfvzA2nLVzbLrlpjlkTo2JS5fE1TdeHxNynElTjzH78TPjF0dfFM+87bhY8qiN+xQ9Ob/eY+Kr//2teMer94mJ05fGs1/+7nj7G/eJJVOnxxpZl0nr5dgzQhpofEfIqEG0AQcGHHj4c2BlNL5zEqys6wPKnKRvuHlubLDh2nHOWWfnoL5DbL1p70F3wR3XxVkXXhfb7bZ7DvST4tPvPyBunrRz/Nv73xjrrT857pm7NK744wUxbYOt8/jQlLjjmsti4mbbx7YbD92ya3P+zttujekJkm67+baYOG2dWJiTxxoT07XytMVxxrmX5VGoWXHFpdfGjnvuFdef8/uYtPHMuO9Pl8f4dbeOGWtMi7Um3BkXXvmn2H2vPWKNXqqPPCd4fW5vb7HpWnHHTdfHogRmi/M88dprT4hvf/lLsce+z8qjV9vmVuv89AS3Xpx/7oUxY+r4uGvRlNh1h5l5tv/seNR2u8aUhTfEJdfMid3ye4cpk5bNKK0Rx5x7FsV6M6bGvXfeFnfPi9h4nSVx+c3zY2Jq4G4ft25skxPh+ussqy2u/Lh7zh0xY938MDLb5J77JsZNl6aWeeudY0IuDtadPinmLpkYt19zfkxIzfzNt6c2Oc+Nf/R9b4l5mz45DvtQOv0489LY9jGPjQ3W6r0FngnHbbfPzzIuiT+cdVXs/vjd4poL8iz2utvmEYSlcfv1V+b15rH9lr0n7MUL5saZ51wQm83eOdZPPfw5l94Yu+zxuPjTFefH2pvNjquvujS2zIXIGlPXSaB1d1z868/Hx755cbz58/8aG8+9NXbNI39rTFyWd7X+fpcsWhgLlk7M7WRarSZuvfGu2Giz4Y86pO435tyePEoNWy+68KTvxye+d1oeLdw3XvHCJ8am60yOJfNujstuWZTgbsc4+bsfTQ3k/4tPvvZV8bQPHxZ/Pbt3fovzTPrcpRNi7WmTe2XTCbsvj4AtTtmcVjSlS+OuexfE2mv12vLuvDLyC/J87d2xxawHdm+GvtzEDRdflGf2m9hl963i/LP+GLvvuUfccPn5sXDS5tlnxuWxqnEFjM7LoxuX567MDrs9Pu699sy4LY+L7JRHHc77w9kxfcutY9vN144bb5qX2tvcUulB11xyYXp8HBe7PmbT3A29MR7/hJ3ij2edEetvt3MuIhbHhPybPDlhaS6sFi6eEuMX3BKX3pC7S49aN6ZNXzt3c+6JZvKa+W3JPbHBmk2cdcHl+QH4zFhrxvSYnp35rLPPiw3z2MvMze7/WLhHEeLuO+fE9LVnxK233JFpTov7ElhPHGdxtzDO+eP1MWu7mXHDNTfEY3bZOY458t/jaX/3nph3612x3toTs48mry67MNbccvsc83q3ebNkYdw8Z0Gsv9a4uHPR1Ji0MI9ATZyU7Tklv0+IuOayC2KN9beKTddaEBdcOT/22G3ruOXa22LG2uNiyZR1Y601ep9vueO2ObH2BuvGgrtuz/bIumY7rbvF1nHXBUfH1Qu2jb/a90mxSS7I29RP4zsAvm0uDa4HHBhw4BHNgZUBvmPBmHR0kVrDaXnOeSxSG6QxGg4syO8M1lgjJ8jhNJWjSXgM3lmyaEF+CDc51ug6kzgGSa9wEoty8TBp8vCAdVF+PDwpNcMDGnBgdeRAP+DbG1o/CDXwcZuPf9LRQd/cfNjmY6BqFaBvxMGDhwUHfGDlYzKkTXt9wPVQV0T5lHPNNdfsfJS3vDL5SMwHmgMaWw44MuPD2He9613DJlytujheMuaUQGT+4ge2hMns1fmRp48y2/Lrgz3WZGbNmjWkCFxi+0C1mmCDthalhq5XXNZJWHXxgV8leaRTnmLCrp2fuD5ANH52f6bhbLkPBmu4snGnzpxeDZO+9Hxc7OPadjgrKj7SfaDM98fVHsrWjuujTf3FB43tcHFZ5miX2bEnZfOhbDsuyyjarvtbAB+7Mt3XToMlE/WRX5vwwofK+FLJe3inrdokP/3bx5GVatzu/IRrE2m3y+zDah9TK0slcbW3DzXbcV374LbNZ3Erj+r79ff2228M5hjbaVTrPd3WdFib6Y7LAop28SFoO41efNYmymY8bsftx2f188Frm8/35EJCnm0rQOqibNqVLFVS7179xzch2r+7Xfvx2Ufl3bLfq37D83ko78SVH352Uz8+q7c6tnnHwo9+ol9U6sdn/Y8c+nC9kvfURf9pp+vDcMfn2uOc5+RT327np1zasNvkIz5rj3Z+0vQRdPf4oK9Ks52fMuKFtm6PD+SNHClzm4SR2bYM1DSUrU3GHflVE5j1mTlZ39E+bcLnNo88Vz99m3xOfqBrtl8r18M8WibumAbo9NV0UU3Yh0DdlG5z/yLOiaYDh2HNWHXzZSzu08lAmfjGIq2RpEGomThj4soAujqSQTm9o0U6EBlx8Qw8f4nE0kLb/vRY88BAb0BuE6scrIW0ycCYXvHaQWN3PSlPpeWkVP8M4umcp0zSNcyvyStdkXfi1Wfpxa6AkHrfjlsnvPrM5MCyTb33Kz9mHA3k7XBxjzjiiPK8O5ylD+/VcPmkp8AhYTXtdAC0TLg+YCKr79e4TNq10xVu8gFQu8PVo7vMJmMffXbHZakEAGjn55p1kTpJ12fa31+9r7/qZz6p937lw6xeN5/Tq2gpd3dcpiBN5t3hrP90l5l1HmCmOy7TiN1xgePueotzdFq/aL/vGvhjRaY7DeOlcaY7PktC3XHx0jcW3eEs3FgkttMAeiihuuOyHmRx1o7rmlUk43g7XNn0yXaYa+kCSe1w+VSTm+3ws846q5jsbIe57sdnZi+7y8yqDvDUTkMcabTDXOMzi0jtNFz34qf4LAK14wrDZ5ZqusP1k26Zw+cTTzxxmbj4BsS3y0euusvmuX7Jok47Ltli5787P/3yhBNO6Jmf/tpOA8+k0V0PMqB+7biuyZGxuR1unGa3vR3mWv2A+O5wtvy789Ov5dkdl8Uj7dUOd9/dJtKDL6p8TpjywGKie0JYZRpfk4DVCJugGoXxfwMhQPHtb3+7dGJmrJCCaoyzzz67/FrdMtmlcltttVWkd6oyIRx00EHDfij0s5/9rKyIDBAahr3YShrFH/u66SY4xDVxp1exYuqKaah0JxwvetGLyn19r/0r3eqIQr2YV1Kv9ERXBMfky1QUstIhTITVqkS9CSmhTnesZeClyWI2zMrKQMVEk2urG1qifsRMG5urR+TEx6GAOlRiLird6cZLXvKSYhJKuDy9YzWE58xXWVmrrz/5MYNFcEzqBxxwQEnO4ML+spWg92kymJYyITG5xbwcPnIwkS5/iwUDmhFkEDKIaD82XK3GTCpMb7VXaSXyMP+YN0vXx8ExA9Nf0tM5THRWnT6gU26DKbNxbPjS8HB8QKZMWvjOkQZbxOqNX7S02kTn0VnYATbJMqNn1S+8TUzT0T7Kf1Zq9V760vu/mmXKTvqVaJ7YB0bp4a7kqcOSOQMMW9P6hfJ0r3hrGiYck6J20y5sODPHhgeIqTJlZvJNO+sfBgfm4ti+5RQGr9PVcJFDkz9Q4N5qGLCXN1mz6yI/9nzVw6CW7o/TzM5jIj3SlX6Et8zF4Rm5Jw/6F5n1jralXaptLw2WLMgHfvYzEch8m7ZUB2brDIbp2ryYQsNHfbINaIExeZpMyWw1g6a98VRbIAs6bbmqSJ26tQ/yqk5B2vniY6+ysGPci7RfN3FU05ax+lzbdZNyGZe6SVv0ol710K+M2d1E9rupale6w9Wju8z40Gtco2XVR7pJvbvLRzPZna73jGnmi27qft9z8qvc3WRB3ittstlN6tfWeNXn+mk3mfd61Vvf7ibl7fUxrP7Vqy69wvCyl9ayF5/xTHg34XMvfuJzd73bfb+djnS7Nbie43N3uWlIpdNN3fHq8158ll8vue3Vp6TbvRMg7VldOzY1v15t0o/PvdLAS/NnN/WqH/72Kpt+2R2fvPbq2/hOzruJtl46bTJ/9kqDDHQrJ73Xi8/G4l7jQ3d5a769+GncMo53E751p+O+VxpDd9e6U2rdZ0ajprf/z6xmwaK5Pd9/4xvf2OTkXdyU5sqoXOfkWuKmlqhJu7ZNAt1ynxqb4to0G6W4t01wVVylepgAo7hSTYDV5GRR4vf7x9VqVq24iOVGNif8EpX75LRz2uTKqkkQ1nBTnCunJkFqcWubE39x8ZsTd5MN3TP5nOgb5eMilnvdFPriOjVXd00KanFDnJN0x02u/BJUNgmimhSI4r5V2rlt0HELmxNBk6CmSaBSXBvvu+++pa6HHnpozzLUwNSQlHriSYKfJldU5VE6wWgSlBbXwgk2mrS5W9zDpjA0CVgaZZVnrgSbBN1NDjZNAuEm7bQ20kQJQpoEHMXdsDgJdko419A52BSepTanqWXMyam8o63TDm6J699H0sV0grPSFl/5ylc64S68k6B0SFivmwQNxZ1zgugmO1upT64gG/UhQ7mSb3LhUF7NlWnhifJyiZ0ahOLONu3BNgliS5wPfvCDRe4SQBV30gLxPweZIe6OxU8btuUd/3Ih0SRYL/cJGps009Z5Jh+ufivlyr5Jm7WlbMLStm7zpje9qbiqzoGo8Bmvc2Dq616bnCS4KrzPAbPIcZV9LrO5jE4tS+kbCfaaXNA0OXiVuqgbF9G5AChFykGjyGZqG4rs5fZXo29oP+VOe8DlF18TsDdcUyfoLHmQIZSL0OJKWpo5iZcw7a0sZF46uQAp4Wkvu6ThJhcWHTkpD7v+4UNOgqUfkQd9RVuoQ2osmtSeNWm/uvOW/JWXu+e0D1zasj7U7/EiF7tNLrpr8DK/A5fFQ1mSC5ShAY+wO+7AcwH5CKvVA9VJ75cP3DwCr1LRVMa3R2DVSpWMo+auRyqlsnHI3Ppg17Ofy2IIe9Q0HPBNzU0DcKb2pQGCU1vWpEazkxcwVIFvDTSZdVNqHwuAEZ5azu7HQ+4BwD322KOEmbwrKAKg0qB+k1rA8gvgolxhFMCb2q8CEAGKfpTasjIR1+epiWzSw1oBIKl5LcG5tdPUa0AgVyQF0KeGuzxPjXEBEfvvv3+T7nkLaDBZo9SONqnNKtfL+5fa5Eb+CPAy+KWWvFP3+n6egSrlU85KQBJQgQDlPHJSH5VfoAjwRYBHBb4mj9QolvD2P4uISqkVrJeNdgNGcmVWgErnQV6MBPgCQgBXJWDIAkmZyVYlADW3LsutRQ3K7bwmtbvl2uIDEEQAaSXgqRKZSacd9bYA5TbwtehRFwsTspxa/E5cFzXfGqjsFlUodxDKrwEc/8igP0B+uEnL4g8BhuQmNcbl3uKjTVXG0yFEY4GAKt+kn9qqTp6pYWoAd30vt8Ob1OI3qWVtUvPapEa7AFntVvuJfoHkqT+h1J50roHpdPxSwus/8qXNLfwsdIHZ4QiQ1bb4SxYr2PaOBSlZaZOFpwVfN6XGohPUaxypDwfAt3Li/t8B8B3Kj4fb3XBjyMOtLr3KOwC+vbjy8AlbXYHvKjvqYHvB2TRb5dTgCQiHbMlT0dsCalMvtbp4dfupe4ul/a5r6u+6PVPfEW7L2Fa2rRTPc7AQXLxPpTaueCOzNds+MlAitP7ZirEFXsn2MLW6OtTtFdc1X9vQ8nR8wba2rdnUppVf56QchbAdUbd31K1X/Wt+7V951Dxd13vnpispqzRta9j+59ULyc/ZJKS83W3gILszk8hRkLrVLI9e24Pt9+u1Yw62xLJ7lr+n9PCIVuOWjHr8sy1qi18a2tW97XVl8KGO9JFr2zeotr20lRfZEksNd7Gnqw0q2d5x5lC66tsuT+Vpjev8Ei979YgGOXEmrVLNq97bCnK2iTfA2qb4aouc5zth+kQvftY01LlSuzzdZ15ruR1BwRNHFrgkRvJQf8dz5Ck/YY7gSBNv23InjLc2si7ccZJKbd7WsomDh21yRMGRJbLtXFsu8JY5NtKOzwOdYzKOUOiLjodUqnWr937lKd1uasdtX3fHG9wPODDgwIADAw78hXNgZdYOw2l8pZvnOYtmkpapam5oml73utc1eUa0aMNoYivR5r3hDW8oW++OQuQkX44XWPXZ2s0zJ43r0F39AABAAElEQVTrfkSzaguZdion97ItSwucHws0eT60sdW93377lS1iadguz7NQ5RhCikHjSMZwRDtFI5pnjTuaKXWx3YscExAH0UA5ppFuV5s8+1fyojVVR2WwJbtvahDrEQPaLhpB2+LpUrccVygJ9fhH+5dne4uWmnYuz9gWrZmjHY4t0HbSFNLi5fnpsvVP66nceS6ws/Vw5JFHFs0k7bMjE8qHz7SI8qApTxe8ZZteuyRwKlq8PKNcSuWYAK0gXrv2nMY7QVbJ3zs0fwk4G1vg+YV10Zjalqcpzo8Zh92GTABXZIi2nYbWDkHlE+181Z4qzKG5dU/DnudWm1xwlHrmWdBSznQiUTSKVWspsG7rO7agPP/8z/9cykLulJnWVFvQjtPkkw/y4+8Vr3hFSRd/1ZEm1c6GbdVKjg54p60dJhvqTWvs6ILjI72IxhjPEngWLT6tu2MnNLWOsji+kWfLyzEAZahE3hwVaJO4dkrURZ60pWQnF6TlaAAeOkKgXLbc1DsXamWngqwmsC39qGpeEng2uXArWdh5ICNvectbSh/Qt+3s5KKsyKB2c8RmOFL+BNIlH/yqpH3zw9bSNsqei5fyiPZdnuk6ufQ1Gv08x13S0L54lIu7IRr8mqbf0Wp8//ltz2j++g0fab79g182a2z4uOb1r3px87EfnN58/UOvbl732ft3SEo+dxzb7PHklzUHvuZ5zU8vvL7ZYPbezRe/85PmZ194a3PAB/6t+eFx57SL85BfDzS+D3kTrFQBBhrflWLfQ/7y4KjDqm2CB/2og+oAUiYqfwDJQ03O+HZTBbsm7ZEQIFmpfV3D6m99Vo8V1HC/ntV82+GugcaVpV55SlN7jJRq+Ucav1e8sWrzXuk4zrAitLwt95GklR+njSRaJw6Q3k3OANvaX1myKOxFjoN0k7Z0FGak5GjFilAvmV2R9qkLkl5l71cOgHw0NFrg+5mDntds/binNf/2/d80a2zxzOaQt724+eTRVzbNmZ9v/u4zRzdL593WnHzK6c2S245rnv6y9zb/9uG3NKdec2ez6cztmte++1+b337z3c2ef/3C5su/OHc0xV5l7wyA7ypj7YOS8AD4PihsXmWZDIDvKmNtSbgf8H3gc/RUt4w12Tq1pezP1udDTfWr83Y56heOvb78bMer13Wb1337uj6vv/WZr+e7ybOab/czW7krS73ylKb2GCnV8o80fq94Y9XmvdKxZb8i1Osr5xV5X9xeX54Pl4ajEd1kG97xipUlxxF6Ufs4R32uLevRmBo23G89OjJcnPazXjK7Iu1Tv3buVfZ2Pu3revSiHbYqr+ffMydedPB/xFufvWPct2BKvP9LP4gP7LdV/OnW29Nz2oIYN3Xd2HXnx8T49Ig1Y+ON4tY/nhbnXHJD3LvWTvHFf3lXLLnz9njDx78eb3nOLquymIO0BxwYcGDAgQEHlsOBlUdZy8lg8HjAgQEHBhx4OHIAuD7jdyfEnvvsG6895IuxZL1ZMWX6tDjux5+K6TEuli6aHxdOeEq88fHpaGfJ+JjOxeqUPeMjb98pdtzytfHbky+PY795SJx12tmx26s+Fo9Ot7QDGnBgwIEBBwYceGg5MHIV4ENbzkHuAw4MODDgwIPKAR8DvuY1ry4fAc7cfreYc+399qQ3WW9ianZzB2XS1NjpsbvEzK22if/49Kfu/+hu0nqxy/ZbxKRpG8W+T3lcftj367jk/D/EV7/57dhs7d6afk4FRkM+/hyOfGCZ+30lil8f1FZiOxl17+z4KJYt717EDnUlNsFRHp/qOBnJIy/1cfllo7lNylA/wOVVarTkY1Q2tXuRjz89q/Xurp932BdfWcpvAiLPnfdMRt541esjzJ4vtAIrX2uQNLrD6jO/3Tyvz3zAnEfe6u2Y/mpzzhj6UR5N6/foQQlnO18bdPcrYT7sHY7IVlqFGS5Kedb9UW99IY+VFfvo9X51+81jdsUJxmjL1R4DahrChnNkVHc483uOZZwP1TSUq/bZGjaSX/LvY3q23fkdGCk9rIEvRo2GWSNlziDegANtDhjUBvLW5sj9zmfw5RFJeUTkpptuLg521A+QNMBytIE4AnGMi9MYVj44WmkTj0yOgeTHjAWEAAxt+WFtA7DJj/fKa23AWcGDCba+U93Wsm6C55x5ALNADjJ5SEO6vCVxxlPBl2f5IW6JJ4zzkPyIs1g0qeBJXhzMeDc/1Cxx82PIAm6V4Vvf+laxwOHBAX92cpMfYharKpyHVIdE5cX8511WPSopJ0s46EMf+lBJVz14qeomjkzyw9pOcFvGWNRRn25SpzTrV0CZtkLqWvkHCLKsUq2VmLA5a0E87HUDxcpnz6WBT9pQu5psOcBpU82HJR9OX1jF6SZOlPJD3BIsvfqOANdtfrm3eBDGOxqeVVJ/POkGct4Rnt+sFOc5tf4cEAHq2jZtrNdkyq96sFrTTcpHvtplFIeXUc5wqjzmR9LlVYsZFozImXw5H0IcHrXluQTmP054ON9B6lPl0H1N23Wl7nLU8O5fDoRmpSMKssyZTyXe81g4QspXeZffNJQwbZMfQpcycQKF2nLnHQs35eDAqP2sRM5/eOBYHR63nwvP87w1Ws9fdW4vTtuRyKp8yX4b0FsUkUmUH5AX75H9FkrkVj+tDpa8I83KV2Ws441+QVbapD4sUtX49Zn+y1sdL2/qaEyoZOHJoZA4+gP+8j7XJulpC/2tF+F7d98UZhxO3w3F0ZL+VmVG/bvL2J3uKge+tBJppaB4gurXqN2FGuk9oTbpPFjUFuSR5NnuyOITPKau+jXwSNIcyzi1w7TT5AmOabeVIWbsqge7lUlnRd/tVZ8VTWO4+Fxqc8O5OhN3p84WA2gPBvEKZ9AZCXX3h5G881DGuTsH0N/+9riiIdRnnVvWf5leIwfAGTlPCxnFsyF3tUj48ekWF1BMKyAljPfCV7/61WWgFmCS5VWQ50EgykTKo6MJDnDyDQCvkECSyYTXyrQoE7QmtLWApzKZZNMOdcnDOe60qlLyZxbORMSrJPON+nU9cw6IA0FAKEAkXxMeb5DKaxIDYnksA3BMXkCobwfSCkikRY1iCpInQeDlP//zP4sbYXHU3aSEgAcgKe2JF8+CadmnTIryFUe9hPFEqN5ImbmYNVHKz0SP0tpKMQ+ojLwgKr/JEiCshFe0dQAP0J0WPoqrYNc0lMAgb4Bp/aUAFO1oDuG9EvAFMLlaBtLMW2nxpdQPiDEm8pSHP9qcl0SLmrSRXrMP7p/d49tVV11VeOJhWrPp9BGmBrVDWoMJZh7xq4IsfK7mLb2nL6eVnkjrP2VxxExgJWCCzAARxiVxkV9n5pWRmUCg1oJDGx9++OFFbsgwU5ueM3OJL8CUetNkVwIUyZFy0eiRaeRemeriSJ30bd5afUciPXyVLw+Y5Em78diqH5Bh5cRz9TNuA2R14ehXGyqvPmcXQnvLx0KgvaDoBmfKmU5vivwA4ORVPzN3pwWpUm5xtCVwZ6HkVzuQE2mTD/1t36wjWa8kHtn1fQX50GcQ+a+kL+O9OvJYSa6ZtTT3a/O0CFSjlgWqXaWqEdV/0uJTR3sKyFaSBx55rl5kDRlTaLi1E17rk+S4vSMCrIuD18x/ptWm8i4+K6dFD7CYVnSKt1uYSh/r/qbFQsYYQ+bIeeW9b3CAZrKDh22NuT4CoJIl9SFD4gjzDtI+xjreR1F7EaY99BcLKqCbDCF9VzzvGaMoIMQ1ThgDle8Pp50a48Y/YBa0vPjnf+MSGd+/F9YOHeH1gd/ZKj738gtjysQ829aHCBGh1aF9vDKWNjZ1NoLV70OxPkUadTCG6sxsnS6PDOzKVVe6Nb4PhwihhnowSTMbsNpkcrNab39UpI4Euu3uuf3OSK8NGtq9Uq/867Ox+mWztg6eY5VmOx2DA/ldkQ+32u8/WNcm/HTW0dPt5ViVoban/udvJB8PGgPGevG7ovX50Vkfjzvm3hBv2Ocry331r465Kz6x5OT4ly99pUwCxjJ9BXCwXQ5wAnbAKwAGkJowTYoWHiY5boxNuvVDX9pGoIO2FRhI83FlojYRmACMF2kergA0k6wJmtwZN0wiwKLxw+QqTSCZO2kgMM3PlUnCRKv90wRgsakMWJqk2XmmFfEuwFn7J4ChPOKnqbiiDTY2AEMmHL/AlIkPMAQCASYgUn/AlzSVV1xWyxcQM0mpj7HSM/HEB4jIp3eQj4otGBxRMKEbj7hKpbU2iZn0TIjAhnfYRwdUlUcbmAO4TKe1AyBM7uoAoOIfIOKjZhM+oKl9AEiLNWMwUCBcfFolz/EabytIqAuGCmjxSTspB0ANsHAPa0InE+x8ywOYAvpp2JSPHXcg2qIHSJEGUCxP4E/70kiqgz9bt7T2afWkLESMzZ4DJd4BMNRVOWhOgQGASNp4ZaEEdAJdeENO2fu22AEa5AfckD3jNRBGnsmt9lJ+7wOP6kMrK098kx7tHSBE9tU7TSKW8Zd8AENk1yJG3fEXwCd/ymr8MMeoj3Yi1xRk/vBd+bSDBSYQjE/km4bP+EurSPYt4owrFiLaz44HHjufjy+AkbKyb+65OTlNiBZ51xfJE1viZIycmiPT1GqRW3J/QC4w1UX7kCU7CXioTOopX+mw065c+AcAaj/toZx44wgFV+6AqXKRGTIof2OAPLizJ9N2LiwA7SKx+24BLQ1yYyGL/3ivjZXReERGlcm9Z3CKPoI3yq0cyk3W9TWy4Bn30doPbyykLDi1h35qTMAP6QC72kMb65vGEsAVyNZ2aUazyCg+aSOyaqFhHCSTT33qU0ub6wMW4uYBuy/kTH2MAxZO6kIuyYZxzuKM3Bkb8Bb4117KrN8rj+fkGChWdn3xhMQeW2yycVz5sk/Fvz1uemw7fcLQ8T4FcNQ0nB3fFPBiZzWZ2/EElYNUyYudWR6l2ONMRpewXCUWN62zZs0qdkQFst+ZDV7sw7Irm5Nrsanq2aFpt5Vt3uzkbgvxRMX2KA9iXJ1Wk0/y5V2L/VJufLMB6ys9f9lt9T5bvDkplDjc7/LClQJd3NCmgPZ8V2CC3lI+dm25rM3O2InLbS27p7yqpXB0wpmlUfds+I63tM7D1kUOCI002Nple1X86kI3V7KljtJhHzknu2IrNjUnJQW2UVMwSnh22mKzNQekYnMV/1F2suIOVhrSV5fRUA6k5X12YXOVXpLghle7Zycr9o2VxbW6aBf2kNmdzYGyxE9tT7H3LB7bueqTK8biAlobZacrdptz8ir2W3nkw2s8zw5X0vCMa11p5GDTMatHBtgjFt52cSuMzPFWloNkxwQcm8M5kBc3zJUfypMdstjxZUsZ/xEbyqn1bnJganJFXqOv0G8OKqXc6pQAqbxLjpWNRzT2el+btnhr+/D6x+sZ2Wf/mM3kfpSDU+Gd8omfg2WJyr5wDn6l/NJSBs/IWE60TU5Ixc0129QI3/TB6t2vBOY/doCrjOZgVYJTi9DkxNBpn9RWNlyM438OsCVODo7F5rXyrSpaEXNme/3ifg+H/cqSA/6QRznANwkyi03onBiGPKs3ZJzN7LbM1Wd+6xjZDmtfpyax48WvHT4SnhnLEpy1Xyv3CcCG2KBuR2DrOyfNdlDnOiecznW9yEm3SU1ex1a48Fonfb2SvlMpwVXp12y7s4ldKRfg5TIXG6U/Joipj4b8snHNVnwv0lfIWoL94oa7O44xsZYrFxhl7DE2slXtbzgyJ/AGyT62fqA/tanadBdG/rspwUTx1mnsSM1bsflNLngUNbZ1k75k3MtFSbFdnQCqjNfi4ScviupgvKh1MvYqZx0n9OcqK8ZjZK7GQ/bmuR9nq94Ylhq04l2Sh0bzLBvddVz1njyNc7mwc7sMpYa0UUby1SbjSoLqEoQHCRAbcdVNG7NVjqSvHORAHsa0BEPFFCi79Gx245c53582SMBX3q3/EsAN4aU8Kkk/F+3lNgFlDR7yq6zaLgFvSTuPm3SeJ3hr2Cone2QA5cKw89yFd/HeHC0tfSYXACUOPGKezoVJsT2fi9ciqx7qR+rreZWjBHvlPf8SxJZ0hfUyAwn7JNIreIB9f3NiNzHxqV1zV6A8MjZceuml5Vq7ajtzMIxAJqsX0poO/ieQrredX/U1DuoPZLvKYidCXuiT6p9gvh1croXBe+YR/GzLF/v7/ajdtsagQ97z7qafOTMofNQ0HPCVqA6m8qh2PEL+kY98pFMZnY1AqJw/1yYHjYLxlbEmYgOwjoDEzZVMw2lFJR1EYxNork11DsSxgE6rDATVBD8cSbsODvJF3iWYgJX0a336pUMYAXVx/VUCInLFWcJyNVU6gglUnSsBi8OlD5QSHE5BlBWwNblUQC8sV9JF6FwrRyXXVRANoDqO8tX64lPlG4BeFyb1/ZH+WvAok7zkg1ITVsrqWsc2GaHclihx1Fn7WxSg1Lp0yqozVDfC2l2dxZWHOnqXbKiH+ghDeFUHN3Vxj1772tcWsC0+EKm9DJqcpFTKVXEnHWGpgek4UnBv4sgtuxJHnuos39Q6F2cm4gCJJpDREuBucq5yTgZN5ojzDC6r2cHNVXPhh3D8M0Esj0ySymaiQ6llKGAfTy3K1B8ZRC1SUysyxM2yupLd1ACUeP5ZYCpvJYs/ZMAnn95pt48Fn0UP0i/VZ1XSigDfxy8H+PZbXKhj7U/ddQHygMmVoX5pLy9NYCO3HIdEA/LQaNMckljecHeuT4yG8I3Tktpfaxpkn5xWwFDD66+xsB/wNfZL9/jjj1/Gvbb3e9Vb/JGQeMYdaXB8Y7xsU6+0289rPjWe8Ux79AID3hPfeMBBD7Dq2ngwWjIXVqL40JfJBzCqj1aSr7HCwrdN4rSBcPuZa0oUY343GQsqGDbmVr6Z3wGmNhlb5I0qv1xXGQMMkby6gVl5kP8qf+t9r9+RxOn1njDgu122dryabv1tP0stepMa8TLu9nournEceO+mfvFrPH0ld1zKLRzVj6SjvZH2rSBau7X7YWrXO89qWnhOedGPzCPa6coEz92EXxZ7vYhcW6BV++7tOP343I7j+n7+LOkLfCcO1f+O7Z3torq9TqWNnAlLhnXCbalRS9tGo6K2Vead7Bwlfn3P1pythGRICRdH+t1ElW6bg3rexx/IuaDsUOXaNg51+XBke1I5/Gbjl6jK4Y8afiQ2RMVRxu64OViUdIWntqtsF6Rglq1i21eIKt9WhTNuvUi6/rzvF9+cW0ptSYkuzLaH8z+uUw46ybiv5Fo52mVMYS3n98TJRUfni+36zkh/8Q6vbOE484WUT92yI5RtHdtoSFvvv//+hb+227RzdsDyri1VPEO2V1AKddkSFbeStlEfMtGWC9sltpYRPtiO9itN23bi2sK0vWbbyvYi3mXnK1uu3fyq+SmDYxXkrfLRlqq2VBb1QdK2bSXtFaHDc/tZP8lJoWwV2g5C8rUVh7QPOVFWfK38aJ9LKxG7/tnq0u9s/9luVT6Ug0o5l6bdchFRttyE22a21YQvCTIK/9S5/olTyTZmal7KNrXn+I3XVcYqr2p8fLJNaEtcG9j+Wl0IP9/79rfG57745Z5Fsr3Xi3rxpcZzzGBlqS3fK5JW7T+93hltmt1p2bpNrVF38Iju8c3Wrq3pNhnHhiN9w7GIfqS/75tb+b2oV72VYyQknr6OfOhIftvUK+3285pPjUfejJdbbbVVO1rnWnxb2r6hQK7bY3sn4ggvHGOpZKu5ny17+doW99cmfdqxlH5Ux8Du59q3trGx3rY7SqVQ59xw9zvuK79cG7/U3RlmJK9UHpXr7n+Vv93h7fuRxGnHb18b243Lxs1uqunW3/ZzmCYXzyWo13MPUnFY/trvue4Xv8aDCeoRRkcA+5F0jPXIO5Uqlqj3sEY39WvfGg8/6txdw+qvtjR39qJ6tIhsdFNbBrqfte+Xx59lkWP77ZW8BmhMpqgywOSZRx1KGFCZq9sy2ebKoABSB9Od36gduv4SrDZJD0jLFXcnbUxpx6tMcmjbOTjnZwyQ3Ye22+kCXICajwGcvQEqKun4wLQ8nKMb7jypQQwoUUZn/pzvqVTr5Nefyd4ZnNwWKednfFQxXBm9o241HTwmqAAN3iHnaJxFQ6lpK+UGOH0oUMl5J+evnLdxLqyWp7YZ3tY8vOM8lsFOnZZHtR1qG9T4uS1eBjdlqmTict5J+fAVuMqtlfLrDJeFivNqQCTS9mSrylQ7HQsAZ5SdFUR5XKV8oCANA72zUpV36odqvVOzUMCec065Ci6AsPKrypu6uzbhkSnnGJFzeN4HLqRXeYSXlRfiKcOsWbNcDkv6A/CbRz9K+1Q+Sq+2jzzkZWBTZqDbQIqX7Ty7M7L4tBhwPstE227j+p7fmmdNW7/IYyOlXaSpDZQBH10jZ7mkid/OujnTZgCUll/lw1Ny4D1nBJ3xNPjWBUpJKP+lJqWAaOcCHwrSxldccflDkfXDNk9tb0IfLTkTW8HkaNN4qN4D3FaW6pnPlU1nJO8PB1pH8v5YxNHWIxkPe+VlTGkvErrBWq93VkUYBUov0Lsq8hppmubU3N0dafS/vHg56Y2ahjvqQFXtXEii93K2L4W7c9brI3nUIRumhDuziqjzbRU792FrK9F+OR9p6zkn4ZKWLWRb3LZHEoCVbVnnv1w7X2crXHzHHGy5yvuqq64q6Xtu61Z+r81t7uEoJ+wmgWfZdnP+JTtUJ7pte8+cKVKO4ci5pZwIylla28SOFSi/8yvqkpq0Jg9xlyRs6YiLL46D9KME0CUN56SlY4vNdp57xwpscyeY6JwLlY4tFdv5ziE5I+q8KrLdlJrxJjVu5X1hzjXX4ymOZeBvpezg5axtve/365yW9stD/43zRdoELyqRBUdZKmm3BEpNrpzLmd66fWbLQxlSO1DK7uyvspMT52+1+3F5bKSSrRoy53k9V00OtR+eOANGNlAuTMqZWLJFTpz/tWXqvLE6O3tazxSSmRygS7h8c5DruB22Nat8zuI6EoDIhzIgR0ts8SsHEvf43HZdHjlrpe7qY2s8B/mSZw705YyzckvbcyRNZUutTZO7J+VZgtKe2Qh37hlPEiSXujp64oiLeju7lgvUkoajB9K1pah+6uLst3NpZNUzZVBn22GIXNb+rV0r2X4Tnzy0t6ZtqTkL1k35JXM5zpMLje5Ho75fkaMOzzj5vma/Zz295HX3nNuaq3MsueHmObkFd21z1TU3NvctXtRck2HX3dJyE71kQXP9NVc311x3Y7M4t/NuvOG65qprr2/m3XNn2ba88U/3b9uOugJj/GI96jDGya42yRkb9ZVHKjkq9Eim9lGHR2I9HS9xxOyRSo7t9Drq8GDV9yE54ztc5VJrtczjXmHLRFrJAB/v1I9zhktquMFyVZVzrNIdruzD1Xm4Z8oGENaPEoaLO9wzoKr7oD2g7wOKfjQW9RmLNPqVb6Tt5hwdwD3S+P3y6xe+qtLtl99w4StSFh9P9PuAarg8RvNstMD3k2/at3n3d85t5tx6bTNxy5c0P/3Kwc3TDv5Wgtlbm1ftvmXzm6v/PJ7d8Ztmv3/4YvOzL/1D88+/vrBZe49XNpY8x37hDc03Tr05z2Yu+0HYaOoxVu8MgO9YcfKhSWcAfB8avo9VrgPgO1ac7J1OP+C7So86DKc/t03RTb3CuuOM9j41jnHAAQeUrdcEWstNZrgzIquqnGOV7nBlX27F+0RQtvxqsnPOtk+0YYOZ0XGO2dGPenbaC442MPlTz2t1JzIW9RmLNLrLVe9H2m62QpnDGWn8mv5If1dVuiPNvx1vJGXR7rn7Uo6JOPqwOtPESVPist8fGxfecEdMWXhpHHHK7fGpA18RcdtJ8bMbHxVbLrogPviRT8XdiybFjWf8b/zHT66Ot+y7bUyce1Mce/x5MS6PdJx5/M/iwuvvXJ2rOSjbgAMDDgw48IjnwLKnsR+hVXbO19+ARs+Blf3wKDV7PTP3YeNfAvmgY7gPjP4SeNCuYx6PKB/wtcNW1+umWRqP2ee5sce2M2LSjN3iB9/6Rsy/5aKYtser4t//67ux1rrbxSc/+oGIOcfGo5/19/G8NX4e7/3sD2Pq5Kkxecq4PM88Lvb86xfE7ttstLpWcVCuAQcGHBhwYJVxwPcg9XuPVZbJCBP+iwG+I+THINqAAwMODDjQ4UAe2SjXh3zpN3/+CHBczLnsWyVs6saPzrD7XQp3NNzrPj2O+JjHfxcvy//NB155v4b/icNbkikJjvG/3PxbZbsLY1VU/F2VuzFjVc5BOmPPAfKJOn1njLLwMawdJLtJY522Iq6qco9R9VfbZDjF4Hkuv/MYUsaVGadG2xYP2VGHITUf3Aw4MODAgAOrGQccxXj9619XPFg5opMf3qalj/M6pcxz48UrFjesPDF1E6sZ+cFg8ZyUH+l0P17l96xqVGsb/TKrE0e/5zWcmTqWS1aU0v7uMq+kvdpOGLORjjn1Kmc1c9WJ/OcLJi1ZGkG8krUpP4wt3sJqmCNV1XpLDetljadtvafGa/8C6Kym8BYmD7tfNFgPNY0W2OFhJUfMqhyoJwtDY0V4zS1uL2Kukbey4Wg09eMZkPlF1pEq8UJHhoGvfsQcHatIyzPHx8IQs3urI7GE06svsVaFeD/LD/471p9WpA5kZEVlQ/vZ6eThkBwwwdm20sOcJl5yZ9wOb5eLtap+xEwtax7VupI8ajpLF91vaajXuwPg24srg7ABBwYc+IvnANN9P/nJT4t7Xq4zmdPjnrSSSZQNT3aTPeMzvpLBl31kEzCzd0zIIW5I28SEn4k0rWoUM2+AB0DdTczA1cnWxM4knD+TgomugjATCQL4uD6tZ+k95z4WcSHq2BEby2lho4T5l96rOtfdF8wzAqhpPaT7UbkHRGteAkySzP4xU5dOEYpdbjxJD2HFBa7JFxhx3IU977S+UABlTZzpybScEyeccMKQdD3Hy7TaUqJyoVzBLz4wzciUI7u9AKoz9epbiVvW9OpUTO1Z2FRibpIpxDrJplOd+qj8MpHoGxE2tN/85jeXX/bh2yDDu0x1qlttDy+TGfzh0hjAlnbNZ0gmPW5oLtMT4zKmG0W9Om2UKwMTkOqLv3iO3xYNFmTKjcgvG/bik0ffWSBmLLks1hZkD3EtPRwBUY6nkTWuqZVR2hZ5ZD6tMpXXheOF8ikHudU+CB/IlLLiWTq9WQYgW7Bwt0tGlLe9YFFX/ATa09NbSdM/+aT1mGJ2k3aRuUQmTJmF5LJX2x2R7nTJunJqCzKJyBIQhSdMN5JhPKmLAouetG5TTDKSq36U3t3Ke4D9ipL+VeW5+108A2x7EXlifpX9fPLdTdwIM9GaTo+K+Vhl6zXO1Pe0sXfaRNalzVRlfhTbGdOYOU3HV8VtujFGm1Ziixfv06BAsSusrfTpSuQBeKU4wPNe9N///d9FrtrPmA7l1ti4yCSeMYHp07QYVkzHAtL6zfgJvSFu79B2DoPrAQcGHBhw4C+QA86jpSnASDfl5aNM4CJNBhYASWsJOBl02VHmaMRkYrI2UQJRwBmHFcJMvgzsm7CBIhOqP4NzesUreXAUwq42rQxbzCYfWigTIfvh8vZcnrRXDMCn6bgyEfnwlP1cQBbgMcmxRQ1c0FTLy4SOABFAj51vkwfAmmYHi1YGIFZ2k5d35GnCV2bAG0hxXT8QVrd0LV9AeHoRK3UXRtNDu2Oikz+gQRsDILl/zWteUyZL/KEZT7OEHecyafqxOCpKr5mFpyZrky5+440yp/m78j5gBbjJM131lrQBLCDH+yZ3vPE+u9iAAVva2syCQxy8Berl+8QnPrE4Q6Dd1sbep63iYMX7nJYA5BwkcQADsIlTgQJeCgcwTc7AA4BmUWTRA3SyLY6X+FiBs8md3KhH/WMHHoj3rnKrK5KfuOzHpsm/AlS1Ga0XLSc5ZQ9YfsKAAXVRt3S7XmRRHnUhoq7ysPgCaIFMoFb7y8uv+ACluktHWYAfYBGQ4bQGuGGHH//lKzwtAZVycvCh3bS/BYkFozTVX98BprSBMLzUFhYp2o7tf3Vg5xuwVyZl1984eLBAZT/ce+TNH62tuBZ3wLC82fytIIo8qjPQRZYsIvUrQBowPiAXOf4sdJRXGupugUB2yZp2Vl7tWPkkT32Jc4dqS55s63PK5PiFsovv3fqea/KiX+pvlffS9uceuAWqgUQLGeW0o2Ingrwpk7HEYkRb4a3ykBX9WLvgF7mwIFUn+Xpe5QoPjT14aMFGXpRL39NOnlswWCxYnOoTFjvGCw6cyBBwDsTqC8YTu134YQcqzVyWcDsOtMfkTdvy58DGvnpUeau8VTYLAmOe+uBfeukr/DB+yuvQQw8t7SlNdXcvXq1bqWDr37h8cH+tW4EjvTzwO1vF515+YUyZOG2krwziDTgw4MCAAw8ZB3501sfjjrk3xBv2+cpyy/DMUxbH3AMfF4d85OPFe10dkDnlAMZMHiYlk4MBmYbVB7QmHo4YnvGMZxRvV4ZYwIODGhMfrZLJALCmleKh0cQLVBmwTV60W7wlAYu0xrwZiWPiNdE4Jwe40SQCboCPyYEGxR/AoUxApfLQVCmzdIEowAg45fEPGDGRpO3pMjkDyGmbuWw/iguQmwRNtMpKa2bSBwYBFpom5QOGeVoERIADdWHJBN9MssoIlAFaJjU8UgZ84LDFxEgDpz7AO22d878AFUAASOM3zSLgJF1gBUhSd3VVvnqG0MQLHDlOATBLK21Ql7y9R0uEV8ItGAAciwkggSMOAIHGUTiwIR3X+IG8a0GjHLxeAdHAKMChLK73zfpafEivnmVWZ8AXIPKxK76rDwAjDJA3eZMZMgFQmMRpUAELQMQ7QJ04QL6yAiNkx7EcAFSdgW7POIkhT7Tf+E17qD0BVG0DZOMXvgCbwC1LSOQNP/FemurO06K0DkhgSDYBeffqJz55B2iAJ3WvBJR4BhDzxqccyi89BBzS1NkFkT/Z0bY0hoA1+VF/fLLYQkCrdAAmfLOgsVDVJgivkXvXgCZNedpr74R5ph0BPsBMGYEpYA//gTa7Ovoz8CoPcWgYgUH8pmEHRjlmAvb0P/y3yPIn3GIJwMMn/V4f8gx/jSH6kzLqt+oqHrCub6qbRRQ5xVdxtCu+07jqFxYXZIOsALnCtJe+pk8Zeyx25UF2jR9AqnHLc+MLYKuPSEfbyQfPPNfP1ZecaA8AWDrax7PKY22hjRxxwEP9ovYZ6ZNj4B4f5aF+Fvjqb3FhTONBVX0AZLwzHlhsWZgIIxvGC/2gUm1f2njOO3bafnYcOn/H+Pwe02Pb6RNqtPt/swFHTcM5sBh1ooMXBxwYcGDAgVXEgRW14/s3z3nGkJLkpNIk8GsSiA0Jd5OTYpMTd3Fuk5PiMs8FJHho2O7kaKSXYfeccJucdIqt59SiNDmID0knAVFPW9o5uQ2JV29ysiiOT3JSalKTV8pXn/lN8DPEmYx4tVzqgnISKs5dyk3+Ewcpa9smd05qTYLrhqOZnExLnBX5l4C7SdDQ5AQ/5LUEZk0CrMKLPBYx5Jkbdc8JeplwAcqDcpIsvyv6Tx0PP/zwvq+pvzbNybtJQNCJlyCiONtJDWwnrH2RoKQ42UktXsOWck76TWrQijOD1Nw3CbKaBFTtV8p1Au+SH6c7CQA6ZUuw3iS4bXJxVeSnvpgawSbBYr3t/JKFfjxL0Foc2SRAbeSXRx+aBEmdd+tFlYN6v7K/qY0tjn9SO9tJihObytcEWeV57mQ07PGPJfWrCx6lVrg4eurOT7kSgJfgXFw2CWSL46waz3igD7dlj0OHBHxFnjnV4jAqwWSTQL9JLXR5VZ/Ns89NbuM3CXKbPEZQ2jAXVB0nYDWP+lv7bL2vv9JIcNvom92kX+XCrJRbXcRptzPZR7k4KvUg021KwN2+7VzjZZouLfUydihDm4wPiAMw42ml3KUql+z650Kk8MhvpQTRxSFWLt5r0HJ/+9nxtXIZNQ2A76hZN3hxwIEBBx4CDqwo8K2e22pRDeoGbBNaNwFgqbFoDj300M5k3R0HCOEFD1jqN9l2vzNW9/JrTzTSza3q5SafWs8CLpcbMSOYDPMow0iiPihx2p7bViW/U4M66voALal97rwP0KZWvHPffaENLY5QdWChbt5LDWpfcNSdznD3Fh9tMAUAPxjUDcbbntvUUd9DD6bjFYBrJKTstV3EB1T91TLXNPIYSblUH6CUR1Vtl1rdEp4a1iHv5O5Ac1WC4VVFdUxo83dl86IYwAt1asvRSNI1juYuVKPt+4HrkaQjTj/gO3Go/ndwN+DAgAMDDgw40I8DttNsTToC0E22iZ17s43sg5xe5JyvYwQPhT1nZXd8oE3ClkfOpY6U1MtZvNWRRlLX0ZbbUY/Rku1sf5V8EOSvH2nDXu043Dv90uoX7vhCm9ofQbbDx/raMZl+pP3qMRbHOx4scvxhJKTs7fLb6kf1t6bh2AtSH0dTHFnRdo7SIEccaj3dOwKwKqnKUpu/K5ufo1TIMYkVJeOo4xCrksavysQHaQ84MODAgAN/aRyo59n61fuhAL39yjLW4c4xDmjAgQEHRs6B1HCOPPIg5phwYKDxHRM2DhIZcGDAgUcyB0748TfjmLNuiK0fu0/cfskZMWfppHj3u94ZG1LsNrfEJz/whZgwfc149YEHx8+/8bmYE+vGq5726Dj86JNj89l7xpte+cxHMnsGdRtwYMCBAQceNhwYaHwfNk01KOiAAwMOPFQcOPWX/xN3bPZXsd8znhgHHvTWaM76aRx/5dxi9imW3BxH/d8d8ZbXzIzPH31+/NfPT4n9XnlATL/tlJiz4e7xiuc96aEq9iDfAQcGHBhwYMCBLg4MgG8XQwa3Aw4MODDgwLIcaGLG+pvE+mtOjqnT1orNNxsfZ55+Rhz0jnfGNTenA4mrfhmP3fPg+H9/+7hYtHhcbLpJqoKXLI211t0w1k5N8IAGHBhwYMCBAQdWDw4MgO/q0Q6DUgw4MODAasyBjbbYJjZdZ41YeM918fdveXucPm/7+IdX7hvfOOzrMXPz/Fjt6a+L80//frzipe+KWRtPjkPe8+G4efxm5Z3VuFqDog04MODAgAN/cRxYrc/4pjWK8uXjcK2SpjiK0enh4vR6NpK0fZHoC8M29XsvTZYUo9XtuIPr3hxIMyflq9Vu/vp6nPvS+tVr77dXv1AehXjrWV2JMXEeyBiNX92IoX5G3TkA4EhhdaW//39f7xTtG1/5YufaRTNuu/jO4YeWsN8ctU/5rf92qheD3wEHBhwYcGDAgdWCA6tM48sDD/MYPLNUsMh7EI8lwpkI8ecaAPLLAwuzMO95z3s67/CwwtyG5/4q8TjD60f1/mNiZ0aIFxjxuD+sxKsI80LC5QlYuWYShamRGl79b/OWxLwIs0PKjKqHGHF5yPHLmwvPJby78OLEDAlvI2NBaVOveOxJA9MlOcBAnjy4PFzJ16vMOe22226lnfCsTbwjtc3BtJ+N9TWPMt0me4bLI43YF1nuFYf3q7EkHne0NXeuiPy6H+3Xv6wM8Az1YBD3osra7t/6ZT9KRw7FExf3viMhHoR4lnqoyALXYrtND4xK7dAHrrl/fbDJ+DFcvsbk4Wh5z4d7d7hnadh+uMcr/UzfsbDuVX480XZ+e5F3+j3rFf/BCEv7rsNmY85Z3Wg4uVuZsmofeGIk1Kv9R/LeWMThuW80ZE56uNPy5FX9Hsq2qfxdZb2Gazuu6Nh05I6SjTpasfQCEya79BRS3ONxB0iryk0eF3/80gNAdYCkEeLmLo3CdxjG7SZXjDoYd4vAFKExwdNucdfX1sCZ9D03IRsUuRVFfI2n0eniv1p5uPPjTpNLUnkCtcK4zFQ2QI1LPe4muVT89Kc/HR//+MeLG8X0TlJcCra1ldJsA/DK9JH8GtD4QVefo446qpQLX/whtv2AYW4TK3FJyiagOrAzyiUhd6X8mH/9618v7iS5F+ROFHmXO0DuFiuZGLg25PJPm3GLWAkQY65Indvh9fnyfrnjxPs0aF38bJMDZOGTRu8LoKmdQrnJxqxZs+JLX/pScVFoccNFpsWAdiNjXGlqD8QFJF/kfH9LE5ER9bFAwgftj8ikuvpVrkrpVSvSc1JpX3xE2ja9BRXZFZ8v+0rkltvWNj3pSU+KE088sbhk5FZxRQn4T8P0pXzkWx9II+dlYSgtizGuWfmfR1enC05uIdWTq0v9wTXii14/5Ia1kvf1EUS++X/nDpNLTrJPtixQLV5XlLib1CZ4yy0l16L6EiJnZFa7ViLn3E9276xYfFpscmvJDSqSTnqTKv1NO3A5W8mCkKzw996ua30+Fr8mNO56P/rRjxYXujVN/a7fhMyFL3/yw/UXfXM0pA9o+15E/vWVXsTtLtefxhULlDZ5z0KLAiE9Rg3hpXpWIl/Gt0rpjamMl1zi6mOnnnpqp91rHAsg7fTWt761BpWxqnPz5wv16men1fvK1YssTvX9Aw44oLh17o5jvKes4Dq6m5R/r732Cm51K+GFMadN3MNWSq9o9bLzm44GOtfdF9zdrgiZf7RFJWNQJfOjMUZYP0DYbp/63or+Gk96kfmwH5mre5E+3S4TN7UrQlzhmn+XR+SDK95eBF/0oyrDXIKjfn1LOfqRhZN5aKRkrPeOBRtlHrfH/Ui+VTnXKw7ZS+93vR6VsLoo7BthJR/ccMMNxS6xcVIfVt7uhRmZTW+GfXOCd7rJ2KpP9yP9tN/42++dif0erGw4JpusGXQHOoCoupomYOmerwyUniOg1B9BMIkbZA3OwkyKfiuZePhCr8RPewVMJlU+xgmvTgaIpnvDGrXEAwRQO83aQNICzqrm0fa7Cfjggw8ukypAaGD3Lg0cEAEQApwatD05AGTqAISOxnanPIAbafBPX8srP/wz+AEagJoBEABTX/zW+fnepl21Fa9DMUJusBaPcJoY0zViAbL8dZts8IbvcT7uLR7UUVw+wYGxdCFZNN4089p3RYix7pe97GWhgwDwFkFI+zriwBe8DkMLD3gpN5AMGGlPPthNXtIQR/mANZMZSi9NxX83IKEDWfAAW8CH+pAb6ZMLvNFhgCm/lWj58RR42nvvvYsPcRO2hZOJiJwAoxW0A+V2ANoE7AJI6fGq+G1Pt6SFf+04y7vWf6QLmAK+te3JUbp2jHRPWtqCr3f58Q9v0tdW4vI7j8iyXRP8sOhBFi7AroWD9gRihOGp9ywsyAVf7KMh/NIXTI4WCXhGtowBBsP0XlYGyApoa99t5wWQaWtEhqWJ7zQKFjParb6nnEcccUQByPqmBSoZGwvCT/nIHwgC5PHTGGORRZ7kKdxiZOuttw5jhjKqs4UiDbW+CgySC++kV6Lie95EABDpm/iCb+TGGAl8nnzyyWUMkAZQRu4saKWvrWjAyYQxatNNNy0yoH+YANdZZ52ye6YOFmNAg10y/c6kTlFggemPrKWr2rLwmZULCAATQNYPLfyN3XiuDwOI8qrHU9RfPzVGWKgYg6Wv39GQc86gHsaedEscwKMFClCn7ProCbmg0S+NMcAW4GIsUiZ5kyHvKbsFjwUdPgNP6da18OsDH/hAMXyfLk+LPKS71CJ/eGSMMYaQH+1HcWHRiif6kMWivIFn8wWe6VN4oV5kEJ8ocoQZ9/UzfU4fsshTZ2koH35qK3WUlnEF4DYWAEbSsfBQVmO1XU35kQNx8YMcaCNtZuxLb4ElnHMDc4L0jf3GTbyQPvCjTOYxc4f+p7zGSf3JPPXVr361pKsvaitlNN9pU7Jp7PFnTrBIoWSyO2b8M0YceeSRpe2f9axnFYWUulNcyEuaO+ywQ5E34xSlgbKrtz6Cj+ZSC21y//a3v73IqfFGn7d7pr3kZ9w3n2kzC2ljeHX0oG21Cxk1R4mnn6ab7bD4Ukd1FQf/PU9vYmXcVE/5SteYQq6M9eTVvGA+ceyKfGhjMq2/GVcoDLQLnurr6qgM5i+kHdUZ38h+utwtdfGrj1As1HLp4+IZy7/73e8WmVAOY7V+Ji7lCxnHV/1Q+sY77YU/6qBvqS+Z9q6wAxIo6q/k3oKDzOOxe31O3RC+wAYwgzlOv9Le4skX/+qc6Vc74oH34TS8xUOKCLwyRjlSZ7yx++1avfUp76jfjBkzSp2NLdJTH31AnbQ7bENmtDlAS8Fo/MM3/VW97bIbL4yj6qxt/JEF5ZHOhuuuHeOmPqnUs/vfuBSW4fe8ut9o3R/4na3icy+/MKZMnNYKvf9SQ+nYBNHAZ5IwCWOkjmYyN2EbIDSmyjriACTqdIQtfUWXxDBX5WlOkHRoLV/4wheW+/oPk0w+BgX5qxqGVjJ4iqOx20SIr/6z5sSEoeNUjZgyGOgxE9g2+GlwkxLtoF+C79ozg03VtslDPdV3NERgT8gBUGMbDAz6eErA8MQghNTLxAyUGxR1OHEqAXzCCZ6OJg2DDv4ZVA1oBA0glh9ArCMQLh0KiCC4BqtKBMzRlBUlbULQrW61s0GkkjyVy+CmDgZ0HcmgLh7ZUU8aRYDBhGkgVS+dy4KALOEHraX2In8GMWlrBxMbMlnXQbbmr07qaeI1AdHS1cHegACsGzS7yaDW1vp6X7sbuAyI8qpa9u53+92bTA1Qdjf0BRMkebDgAKgMUvhPnrUn0lbAbHeXNiEB89oeGTDwxyQN4POyY+GEX+Tf4GQwBDpGo7GmWTfxAgcGdXw1qClz1TBqp6uzz9XJVp5tDS5wZ1GsP9Ny4KEBU3uSgbrzoT5k10DtObkHsMiHd7vpR2d9PO6Ye0O8YZ/7Nd7dz9v3zzltafxq7wkdgKF/WTDgn3PJ5Fc9tIdJAkDDP21kwUI2jRuOWRlzLIT9mXS1q4loVo49AK/JV50tBkyyxszZs2eXdgE0tJ00gB/g+YgE+iZHANzYqY0t4LSrsuErEKQv4D3grc8BeNIySSi7SQNvySngJT7gZfL0nvT1Q2nLDwlXRvXVJ/FcOxs3vOd9oEm/1cbGLbIAiJNX5D3v62/yBOKkYYzBP2MwvumDJj18sXumL5BZbYGHwMxJJ51Uxmj1Mi4qn3ENINA3gSR9Ak+AdWVQFv1J2sCLdiKnQBzAoEwmb+OPXTHji7He2ESuTNj4h6cWjeYZeQIY0paGhYn0PTePaD9zCXBFdowT++YiU33JjWcW+9IAeL0nHzJC5vQH8m9sNG+qD5CC7xb55AUYNdcCZcpqPFd3ecgfDy0U8BPv9FWgC+l/3gdixNX38dvcC/SYg/RT8y/+45V4eGT3EA+UAR+BOjygYQWALGTUCw+1qbY1Zyo/WSQnFCnkoYJrC0VjhnzMX2RfPyc3xi5jpLRhBqCfHBrT1d1YYJ4ht2SSvJFfZQLMzdnSIgPmbGUiGzWutMiN9sF7PDHO4AcwqrzKpB20mb5Orswz+C1fPLIwEWb81h+AYjJjjIIjtJX0vS8+uTOuG8elZ0FLBozN22+/fZF9vDVPknu819/M8eYL9/iljQFh4wg5tMAxZlr8KJMFNt7CXORc2xobjJsUR+pmDDO36EPaFt/1UXMj3huH8U1/0A54NitlldzBDNJUX/GNI5RE2la+FjFkgDxTiKif9JX9iBzbyIZ5Xlxzq/FGe0nT3GS8VBb5yV+f8L785I8f73vPu+LfJj0hPr/H9Nh2+oQi451/2Uijprf/z6xmwaL7/U53J5IDWJODfCc4BbXJTlDuc5DrhB9wwAHlOhuiScEu135zoO7ESeTfZEU6955nI5b7rGyTA2GTA1eTGqYmt6078XKSLb7La0A2zJD7Gp7CVy+bnMCabKiOb/oESsWftggJXkq8FCSLhSYbpckBp8nOVMJTGJtcaZRr/7KRmhTcnnl2Ig1zkYN/k4NfiZEC3KQglusUmCY7Q7nODtxkZ2lyYCr32eGLf/By0/qX2r7Cw5zkSmhOnqXc+JegrkktRAnP7e3OW6mdKXVPAW/wLgeF8iyFrNOWArJzNDnYdHjWSaDrIifWJjtmJzQniiF+5XMgL3koE57myq7EzcGnEZaTQbnPwbzJM6FNDkKdtPA5NXLlPkFekwN8uc7O0eQgVK5zgG8SuJTrHGyaHADLdQ7Upew5mDXZAUuYumZH6/A1J6YmB6vyLCetUp5yk/8SyJRLZUQ5IReeuM4O3ORA57JQLqiKzNQy1fDu3xwkOrJM1nOCKmUk02S9krKgBOgNOdZmOfjXx6WcCcKbHKg6YeS2xlFWMoyqfJMz7ZQLi8476pFanZ6y1Yn054scsLqDmhyMmhyUSriyktkEKeXeb056Q97Js8KdZ+rsHZRau0ZbIO2G5znxd/qJ8MoT1930wzM/1nz9pDd3B/e8f8bJ9zV/85z7yyFCTn494z0cAnPh2LOYORH2DH8wA3PyK+2bE27PbBMoNuaT0VBqGTv9fzTvL+8dY2EC0p7RPNMfV4TIdAKuEb9iXh0LMi7lgqmTlLlnRSiB0ZAxsb5rPtVne1F7rs4FWGd8aMc1DibY7jmHmiMSrDWpsW8S6DW549d+tXOd4K5zPZYX5t5c0PRN0hgPk3QTec5FTwk2rvbij/A6p3e/7964l4vJXo86YbnzU+ZR426v/pO7Dk3FA52XWhe5cGzIBVIec8WKEpnKReOKvlbi51HPvu8l+O37TB+q8vu84+5oLrt78TJxrU5GTcMB31xdNblyKczSyIAT4GJyBRpzBVr+XGtEz4E2oBiQqMAgVydNroTKRAmQVkoVd5lMgaXUrDU6jrQS/TeAGpDj3jMTIZDlHmisgpZq+JK2cOXJFW9JPlfCTa7ym1wBNgA5AtrEq4A7Vy4NQA4MKJeJW1mAp0oGA+/kCrEGjfgXT3I7sLxP+HLF0wGCFhD4BOikVrbTiXLlV+LjV2o/h+QF0OZqvDM4AeXaI7UTjYFBOXOFWQYZPMzVY5Or0I6wG6TEB0albVCvBIBWQFnDev2mhqvwG8/koY1Qamo6siBc+hZNyqSzabPU+jWpyWmAWrwhWzpjpdRglPLlyr7J1WcBrQal1E6UtlRG9THoVDIparNcNTYAADkB+rRnbqsU+crVfIlOpvDVM8DOoJQr08I/5SQ/qc0ocf0CayhXziUO3iI8rINJCejzz0IntSlNavKa1Bp1FlT4IC/tQD4NAMKUQblMBq5Tu11S1qeUAe+Uy0CEf6klbMhLajFK/MMPP7z8plaihJGJ1Pg0uRov6YifmuE+pX0gOLenSzraoc1r/LPQILO5/d/pg/oVvlYe6pNIv8NrsuKd1ASVcIOatvROanpKXzdW5FZuI0/ynNqNErfXvxUFvvs9a/l17pXP6hZWx9Pucq0OwLe7TGN5Dwz1q/tY5jOWaZHxkdJYAd8VyXOkZRuLeOb5foBLmS2agTdj91VXXdUzy/Y41DPCQxjYD/iORZGGUwCMJH39xlyB8Lpej+TdGmdlgG9NY2V++wHfVXLUIQta1N45ma0UjSSdbNyytbVSGfV5ORu+qNf7PC7Btils92TnKttJw8Ud62cpjJ3jBr141Q5LoS1bAbZRRkK2tupRiuHi246xfZVAuGyPDBe3pjkWvFrRdl/R+MPVY7hnbZ53x7NFm6C1bIV1P2vfD5dGjef8U4LretvzdyTp9HyxR6CtQ9v5tsBWhtoyu6LpLK8+ZNxW4XC0Ikcdnvl/i2Lax58bR//qmOGSfFg/q2f7H9aVGKbwvrmwLb48uRgmidX6kW3p9gfOq3VhR1E4W+iOcphjHonkGJBjPvUY0SOtjo5QqZsjFw8FPf+3c+Lze85Y5qjD8LPEKEua2ttRvjn0tZGk4zzXqiJnSpZHQC8CaB5saoPYXrxqhxn42/GXV9aRgF5pSNNZ0JEAoprmWPBqRdt9ReMvjz/9nrd53h3HmUBn+ZZHw6VR310elJPFmgAAQABJREFU6BVvJOnU9Jb360zWSNp4eemsiAx2p7W8+qxqcLN06ZJ0xtbbFFauZvJcX312/xk/auzyTie8u0aD+wEHBhxYHgcseAc04MBYcmCVAN+xLOAgrdWbAwDYiphvWb1rs2pLR2uxoh+5rdoSjTx1VkX+kukL73tJ7LzP8+J9/8Gc1d2x5aP3iDs7OPePscusHeOlz983Trh6Tjxn373ipX//zjjnp1+IPfZ9Xrznn474S2bdoO4DDgw4MODAasWB1Qr4DlZ2q5VsDAoz4MCAA3/mwML582LNDbbIr9pnxzve8+lYd9NtYq0cPc8+O22rzl8Y4zfYOT58yEvi4qvT9NKScfnl+C6x0YwlMW2DzfJr9R0HfBxwYMCBAQcGHFhNOLBaAV9bmcxu9CLmyZhrckZwQAMODDgw4MCDyYEFc++Kp7/xo/E3sxfE/Pyu4PaLTorDjj69mO1ZkGPS0nk3xWc/9J+x5XrjUxO8frz/H98YU+bdGU/b/+DY/7l7P5hFHeQ14MCAAwMODDgwDAdWGfD1MVF+lV3OGabJsmGKMPQRO4G9iA07tu98RDWgAQcGHBhw4MHkwN7P/tvYe8uJMWGdneJr//6Z+MePfCz+/kWPT9vRz4s1pm8ef/emN8f/HHtq/PyLX44XP3ePeOfb3h23bbxvPGHmmg9mMQd5DTgw4MCAA6slB9it9oH76kCrDPj6mIhRcKDXb5uOT+P2aZKoGPhnPBwxos74NEPhlRx98PW6L3MZiWaEelV/wFLzHvwOODDgwIADdqHSRGE84+VvjxfsunGHIQe+5Y1RP6udc9fUeOPrXhDjpqRh9699Mj70wY/HN//zX2ObnfeJL37wzcUJhUF/QAMO/KVxgNUj1lZWJXHmMKD7OcC5xqrmdzev5cdxTC8yfjIAAAdyNMLBxlgS+eLsY0VplQFfBeEVhZcXnoV8+Y/SKHHxLsSDDK8nhx56aAn3xbhnbU9evKhwT8dzGa82H0lXjINzwIVdg38DDgw4sIo5YNC+5JL73efywsdjWjcdnp4AP5EetpiV6p5wmO1761vfViyfMMnUj9L+aMdLZb84q0u4nbyxJOM54LIqd/K0Y5uYqRwtcbnMfBgPfCvCC/Nd2rIebbZ93+uuW9+IrQfAAtnsRyuqlQN6mLXsRTx/8fzWTfpK2kEv3vV46xot8e7GBTIPYL1IO/F45wNs8apiDQ8qtfvt8upu1zkdKhVPZPX91eFXP+KxFs7ixbEXVXl1bJQnueGIpzQL/m4y3qUd+uJhrT7jTc0RVR42eU+kxKxEUQnw8lapXDyqtSntuBdzdY6x9uuX7fZpv+ta2/IImPb4i0t5Xu3Q8o7ErlLgC+VzmZgOI4o7TI2DcUw6pWH6SG9iQwa8NO4/RKPLnaGjD3w0c2XY7/xvqeng34ADAw4MODCGHEjT7cVNKFfp7FGmE5jifrdmweWrI1hcD6fjkCGLdnG4QgWY2bDsZ8fyU5/6VHEb+pnPfCbSk9KwgKTm69dOWJvYiEbGWO5xl0eUDJVMcty7ci/bj0xKb3vb20pde8VpT3bt51yItgGfSYwb0krcrNrR685bmfCP8qOb1LGGAz4VzNR43PHKw8TNDB+Xr8h73LdSpFSgpt3apB7sVXPR2k3pCSvSY2RxUc2VOQDRJsBC3t0ETKUjhvKNCner3eXtjt++x6+qHGqH12u7qWzBchGLADouXruBIP6SV8Cd+/X0KFaT6LyLP1xbL89NOa1dBVH4xT2uuZ5b9ErSYsGGXFowum7LpTIw72hBAEgBQOnMob7e+QXs0zFPcVXbCfzzhbS589bGdpGVRbnwmEtdbpL1E33PjrG2I1OANoDIUg1Z4LYbffazny3ufLmbR2SkPtPeX/7yl4sLapiGe+d+IJnMt/uDMnTvepcM8p/61V1ssohvlWqfrvfyg6XIGNfeFhWUh+SJS2Vl/MAHPlAUizS/xivxLEwAdvgJH7hOxus2+K95+MVD7oC/973vFWVkfcadMZDLLjZ5JiviArvcERtTuGPmTrhNypnOuIrrb4C7Pk/HJMXFNdfcFJz6fC8iK7Bgt2ZfvSkNpAnwprOMsigxVrP//P6D39vhbXe6q8SBhUx0tNe+9rWls7mnjlZBwsg+rgEIYSRf3ZWsDggVov31HkEkIOmNqnTY9O5Vnuss0qrHJUrg4N+AAwMODDjQhwMr4sDiWacsjvve88T4wlcPK6ml98eyCDe4p9e7eMc73hFAMXDC73y6Ti0gxVgFYLzwhS8sk457IMnADuixZy3MpGHCsqg34aVb6jJZAZl2yw466KCiGDAhnnPOOQXIGT+BZHkCq1XTLAwwBSLSe16Z6GiZZ82aVSY/+ZoMaF1MMunhrpTPpKxsNK4mr5NOOqk4CzApVbDumEZ6OSygId2CF+CXLsIjXbaWegM8NDkmOJoXZTPZysv4nV72ygIhvQB2wMUrX/nKMkHjiTRpq5QfX4GEdDka6Y420nV1AXbKme7gi9MW9Qai1EE+6cK+aPTMBSZ2GjmA2HE678kfIDCfiC9MnkwxSgMYopXUhtpG3fHOe+qjrdTRwgQIBUCkIz182GyzzUrbmqDTO2bhA+Clfb0LKAE3wCkNlXwBgfSOWAC8PPGKuUOAXpuRAeUBzMyb+AO4pBfDojBSfkAn3RsHkMPBjDaWjnfNkQAjxVG6Cy8aagsAgBcwVscXv/jFBbSSLWDWIk0ZzbPpQbHUnd1t9ZCXcqSn0KKlJZOAFTCi3bQ5QJQeTyM9ShZQ5Zo2jmwDuepAHmibgVM8p5nDT3wCYO0Q175hhxeP05Nn7LLLLqWOZEh6yoQ3niP1BsDS/Xrst99+hS/AG75Lr5IFkf5Lay+d2o7qovxkR39UTvXCUzKlvOzP6/PSw2OgE44BRrWVtretD+gDmpR8rtMLZfz85z8Pij1Yxa+8AWvxHOHceuutSxsBbUClBQENKvlT3qtzEQdYWpD5dsqCWTn0WSDbjrlFAF5KO90ZlzqSScdO9Xl1JvsW6wA9eUrvqaVtyCTMpp3gL2WXl3hkS/5kBE/wXpmMh9///vdLueSJJ8YRuE9ZtIl+iJ/KjLyr/6YX1aIFBlbJ6v9n707gbbuKOvGvkEQUZGoVgkDzAlHToIiQyCTJYwgBwiRqaKQxkQYZoyANiooJgb8f7IYmTeP0R5oog+KAgqDYDeTJYDMIiE0cOo2JIjQihkHDECK761tJnay77z7n3fG9m7Dr87n3nLP3GmtNv1Wrqpa+ac4zB+o32kWawC0AbpOiPCTH+rNxEjeaZj3VqUj7mnvl8Tu/9RvtWZ86tp13wvoLLHYN+Bqgdixx33My/h73uEdW2qRmUBm4BrrvOhYJsAFht6SRVFQHMClpPBOiBhNGw+jQbjxBGDzTzIGZAzMHDsaBzQBfN7dd95xT26/9zuszWQuNCdekTooZ13QvjtS8AyBNyhZAm3Jgy+SNzFdAHklcXBOdUkULO4AENCCfJm5pCQ9IWkzMhX77I1224AIkFjRpek56YyEyT4rjucXDwgEAKgvgYv5URosLKQlBgzIAEdIBACyG8lBWYFN9vDdfW7gsUhY0UjY8sCDe8573bOedd17O1xb0M0MCCOjIW9lKmmUBtMhaSAEkoA/4IWXdH6AD2LZQWjyBCPW0CFtorRUAm7rgkXfqLG11lZaFWzwgGA9+7Md+LOsNyJx11lkJVLWJ+MrlE5hxJC4Ncf35DjiRjpGU2kwAIeqPxPMdqLHYSxvIxFe/n/rUp+YmBJDEc+ub9lIuJG9ATfto3/e///0J7oBScQEOgIo01dqpTbUXMAQIaCsSSECaNLXKg5faV1/SVwEzmyObg7o1UlrCA97AJx6qrz8AStmsuaeddlqCSH3Omqt9rLmAm/RJ2mx48B1P1Y+QCpDzXrpj0q9sELV98VIY5VEuQMgGQ38DdgErfUHf8w5QJMXUtn4X0MMPf8YPEKpvqE+NvyqHfLyrvP0WTzrVNuLb1Cm/vqruftuICV/lxV9l1T7GDOBuI3zqqacmGNXuNlbSwyN54JfyG6f6mb5iLsH3O93pTtm3AVljyFgARkmi9X1xbLKkhYrn6qkO+Fek3OpYc4S8qs7aRnjxzg91E3kZQzZ7ccV3jutKz6fy2Fy5gU1chIfq4z2qMeW7dI03gNb4t3nV3gj/tJGNq76kXBXXc+BXH3HKr39qfydCCMA1xwK25iRhxioN0teOyvfly7/YHv6uyydvbpPplukpr9o3fOFLl62LH8xZ92z8IBpp/Gjd70pnKmy9WxdpfjBzYObAzIElHPjt9507vPRtj1/ydu3jU95x+fDQU++75mEsHkNMuENIgNY89yMm4SFAwRDga4gFbd17Dw4cODDEwj/EQj75fjcerpor49hxXZYhsMhnIYRY965/EBKYIYDTEAtnPg6gNpxyyilDgMAhjkX7oBv+HtLlSd5uOIFRwFjIh6n1YxRsWMajACpDAONx8HW/x/H1E+0cm4ohQNq68B4EmBoCMA0BnoYQ3mSY2BBMhl32MKSUy17l8wALQ4D2lWGmXoaEf4iNzBAbkiHA8xBXW08F2/VnIfwaAnhlPgHIh9gUDSEVHeKoftfz3mwGsYk5aBRjK4R/i3AhCc62N18EkFw8P5xfxn15K2X57d/+7SE2ZNlvNsKXPg/zaEiEhwD7OTb6d5v9ftpbLh0u+uwV66IdlVB6h//VrmhVsrVTWBWm0pkKW+9WxZ/fzRyYOTBzYCc5QJLQ68f2aZM0kIaSRpCikOKMyfGzo0P6hoeKVs2VyjmmUiVzrL2KGC33RCJEJYA0jgR3K+RUz9+hpmU8IsHbCI3j6yeOtelBkmpNEek3lY+enJTuJJGAOznYLDE2KiKB2wtEckrlYK8SCe3BqMZWhSOFJWGn6rBXaNyXt1IuajT+qG5slsyjTkBId3drLtgV4LvZis7hZw7MHJg5cG3hAJ3YVYsH/bZrMzkiPv7446/NVdxQ3RwznxM6wTPNHJg5sHkO7BboVZIrFTQ2X6Y5xsyBmQMzB76iOHD5P4c+3j98sn35i5e1T3zy0nalttuVLPjyv8RtbqHTV3TZZy5tn/rnL7QvRdi///gn2uV94Ao0f84cmDkwc2DmwCHnwAx8DznL5wxnDswcuKZx4INvPK+d+sAfaq98dbhKCmOTFz7z0e2uj7z6GPxZ33NS+8mX/Fy71e0f0375ef+u3e7hT29veteF7fr/+sT20le8tv3952bke01r87m8MwdmDlw7OTCrOlw723Wu1cyBmQM7yIGX/KcXtLN++e/aw7/5ykTPesj+9pgn3q+97Q9+q11xzInt+je6STv6pjdvtz3p5u0m1//T9vmP/Vn7l6Ou177ua65o7/3Qhe3J15tlDDvYHHNSMwdmDswc2DIH5tl4y6ybI84cmDnwlcKBB4eLol99wQvb//6Lv2wv/IWXtn/3Aw9s/+X5/6Xd+R73ad/5rbdun/r0P7Vvu8Px7X2/+UvtLy7+SDv+/o9p33XcjdunjvqW9tu/8l/bTeaZ9iulq8z1nDkwc2CPc2CW+O7xBpqLN3Ng5sDh58BDnvWydtPff1378w//TbvPt+9rF33s69rb//sz2/Wve2XZnvIz/7V93bfcsb3z9/5ju+yoG7UTPvaR9reXfrH94a89fzakOPzNN5fgWsKBcLW18B17LanSXI3DwIEZ+B4Gps9ZzhyYOXDN48BdH/jQRaHvuPh25Zfb3v7KJze+232venPiKMQ176cLEzjN5wx/TAAIp/4uRdjLNOUKU3nrKleXBozJpRO3uMUtxo/zd/gnTQf8Lo0Yk8sIuC6rCwbG7zf72wVQXOLxDjEmbtK4k6tLF+q9SwC01yqvIhV2r326HS78BeeFFePy44XLH1xW5UKOqfZx25/25PbscBDXZNpjWZ87HGU6nHm6FGOKuFB0ycrhpPkA7nByf8575sDMgZkDO8wB/i83SuHZfTKo53HZRoIQtzaN6RGPeETeQOeq5Clyc90y4usXkBnThz70oUzTNazbJTdeAbduXeuBiNutXEPrClm3wfX1d/3uXe5yl7w1zO1oPbmlCtB0Ja4b2txw15Nb3tzY5VYyt6H16fbh+utV++euoHX7W5EbT93w57awsa9lN9nxkQpYuFWsJzfMubaab9gifqf5lx6TW6/4S3Xznhvx+jK//e1vb9/+7d+e1xi79c0VusL25Pat8tfsJj63rm6E9KvxjVvi2Uy4ktiNcD1pP+3hym3tBviOCSjmH1ubbpXcoLaKep6Ow7nJkB/fN7zhDeNX+Vu7u+ltTHgOLGsDfN4qjfvIZtOxaXBLo1v6pkh7GVMHI/U0xi6++OK8NVBb82ldZOPitkdtPdUnbTrdXui2uClaBqanwq56NgPfVdyZ380cmDnwFc2BHjQVI1wV628ZAR7eLwOgFjsTu0V+ilxRun///rzO1gUKgIBr3V3RKu4y8OQdv7EA3/Of//w1SVtwACmgrCcXArgC+CUveUn/OBdw1/UCHEBNDwpczADwAl0nnXRSXrtakV3I4Lpb17i6snhMrjAFLpWzJ/xwTS+H96ScPYgCGIBCC6Ir7MfkaliAz3W2/vAKuAbeXHvrCtWixz/+8XlFszDA64Mf/OB8JW8XbwBW0rj3ve+dC7eX4rv6F6hyOYmrVvft27eot2tVpeM6YeHi9rpmAVdu+QFFD3rQg/KK4rjtbgHcAEcbBLwHZNXNBScunFAOQMi11k95ylOyDNoBH77zO78zr4Il3VSWuH0vwbyrp0lMgQqA39WuroAFWJXDnzZ1eYrvj3nMY1Jij/ck2S972cuKTZnOBz/4wWyPj3/849nvpEWqif70T/80+WtTdK973avFDWstbiRrz3ve87Kv3PWud20PechD8spjmxwnBAAPnru+Vjl6wrvTTz89r0N+8pOfnFcBe0/yS4rus/5sPGw0ipxMAL02JUCWttws4cXrXve63GgAZB/4wAfWJGE88yvrCukxAXr6jDFG2m4TMSbtpu740BPJp/bVXq57jpv4+tf53XXIRVMbBvmbI1xJ7upw/WBM3iu7sTmmt7zlLdm/3vrWtyaPlaMn/ctG14bDHNSTfv7DP/zDea2wNnVFuPZ+05velOXRD0p6bzwY38a+tnYltmu5i971rne1t73tbXmFt3DjjZa50NzoSu8pEG5OMl8ZUwfbRBwRk+X0lr9Ks+LzrFcf215w+oXtumG9PNPMgZkDMwf2Ogde+/7ntksv+2h77D1/8aBFPfWPr2hfeNpd2gt/7pdSakgiCMxa0IE/IADIAUAcbwNIJutv+qZval//9V+f4BAQBJaEBaIt8AAJadqjH/3o9prXvKZ94zd+Yy4WBb6OO+64lLS+8pWvTBBocbSoAJI3v/nNFwsscCmORZVEEugB3uKa3lxA5GVRJX2xmCmTsgln8bDgAYgWE8f0ngOKJFveWSyV2/G5Rel+97tfw4O4gjS/W3C9e8UrXpFhLTZAyAMe8ICU6AEAwBowBzyR5J5wwgm5iOLjm9/85va4xz0uASKwBzwqIwD13ve+NwGShZOk7/u+7/sSpKkT4A9AuPnMTVjeW/Qt6oDPE57whMyfJA0QBVjEIRXDW8BRvbzXXqRtJEnAoHCWRG0V1y5nHxHvZje7WZZdvhZyYWxw7njHO6bUU/mQd/oBnmo33wF94W51q1tlOwEL8sVLPJaW9kPiWPxtKBz961d1C5wyx1XCWZYCQKS/vhfvSrrmxjYgRdn1M3WVD3BGPUW5fOov6iofEvcLLrggQS3wVCDNO/Hx6OlPf3ry0CUs+r40AVNlkCbQAyiRVONrXOGd/KEWYywol/6ln8iv1GhsrMQRXnlIqfVvmwOA+7GPfWyq3eCRNH7/938/+7Lw2hio02/kD6DZEBgr+h4+k2jiv/raWN33vvdNnsvfeFQf4xDgxX+XsFCnEA6Yt5lwM6E2p0qBF94DbsZUXGOe9ccz0nFjUD2El6+NFD5RUXnoQx+afRLQNobkpf3wEoDGG/xWNuNWne5+97vnd5soY0jdhNffxME7GwLta9MkDxJoadkAahvvlcHYUgd1xhdA35hRFrw1TvfHxttGovpqlU/bakvxlct3eauf8gC35gP9XXz8UU8b8Re96EUtrpzOcaufKrvNbMVVTnOZNlIO41k9fNcm8jHejRUbBOnrI+qmj1AJMm6QzcI9737X9gs3OLmdd8IN23E3ODKfL/5FYbdMT3nVvuELX5q+h3zLic4RZw7MHJg5sEsc+O33nTu89G2P31DqAXyHb/xXNxp+4Ad+YDjjjDOGmPyHmOjXxI3FYojFI5/94A/+4Jp3AQaGWFCGAFpDgKohJF5DAL41YfwISd8QAHKIRXOQ3mYoFqkhpJdDLIZDLHprogbYHM4888whJL1rnoeUd4iFfAgp1hCSmTXvYuEZnvGMZ6x55keA/XwWoHbduwAWmUcAhHXvYuEcQho7hIRu3bsAykNIp4fzzz9/CMC57n0AmCEkkfm+fxmL6xCL+BASqiGARP9q3feQ5CVPlT+kk+veX9MfBDjY0SoEuB5C2rajaa5KLDZgQ4DDySCx0RsC8E6OGRFCZWWIo/khgN9k/DiRGOLa7SEk2Wve/+7v/u4QAH8IwDSEhHAI8LXmff0I0JZ9L8BwPVrzaXz7m6IApkNsaoY4uVj3OiSXQ6iIDAHahgMHDgyxeV0XZiMPAiAOsYmYDBpgfohN0uS4E0EZAvgOsQFbx198CZWd5P0jH/nIyfQ3+lA5QtI9mBvNcWMy38UJxPArv/Ir41fJo9hEZPvh15ie+MQn5tiODc8gnzE99+xnD6e95dLhos+ubyMofcs0A98ts26OOHNg5sBh4MBmgO8p77h8eNj9T1lZSmA1jnmHkEgMcWQ9GbYWx/qcDLSNhyHVm1xUKkllHFNIMxNoA5YboZA85eK1LOyyBVj4Sy65ZAjp9bqoyh1Ho0NIbNe9qwdA7pjUp+oU0p/x6zW/Q/K26c3EmgT2+I+QfO3xEm69eCEFHn7kR35kmOoDUgXQbJ5WEbAFzI9Jv7/1rW892LStIhuzrZDxUH10HN8GLKSb+R4IB7APB03xpcphrjI+8Xg7FKcOw8UXXzy5sT1YuvgXKjVDXAE/GdTYD737ATifmgfe9553DQ+64FOTwPdqreOFDHj+MnNg5sDMgZkDOBAz7kpGOK5jLEW3zLHdFDm2RPU5FWY7zxyVriJlHFMdCY6fL/tNRaDXqxyHW2VJHwCj+RuTco91kcdhHP2Pqa/PlMeDcfj59zWTA1Qx9LsAQJMVoIJx5zvfefJdPSxVivpdn3Sq/R2MGHxthVaNByoSU14ptpLPduKUWsxUGuaqg80rU/GmnplDqStsloxzKmHLyNin4kI9amoeuNOJd2nDW6c9S8zAdxlX5+czB2YOzBzYAAfo346NdTYQbQ4yc2DmwEE4sAz0HiTa/PorhAN0nbdCs1eHrXBtIs7BJEMTUXblEQMIxh4bJRbFy1yHbCQNExOl+J2oP+mP8o9J2juVxzjtr+TfxVe8PZQkv40saAwnplwXHcqy9nn95Xv/Z3vHO9/Trvjy0C792F+3D3/issXrT/ztRe0dYZzxkU9/sX36Hz7a3v3Ot7cP/vXH24UffF878EfvbJ/54mrJ8SKh+cvMgZkDMwdmDuwqB3YN+LLcdEzA8o6lMCs/Cx4XPqHonJVy1CAMVyEnnnhiWj87umCFG3obLRSeMy6raO9DH2bBDJaYrCVvc5vbtNAByefcwciHyxzWgUWsF1lFWuhZojqaDJ2QfM3SlPWj90Aga+Pjjz8+y0DMLu8w9siw0hHXXyjNV/Jpkaks3/3d353PuL1h6Rm6LY2rHWlwZ7NTpH7KoDysh3sK3ZyFK5j++bLvrFhZ/vZU9e2fLfvOpRELy53wvfme9wSoiPKPSfm4MmHRuhPEkrV4qK/5Y13PnQ+LWe88w2NWsSiMIbKf7As3RjvZljtRn62mwXKXxTKXSaHLtdVkNh1Pf+HO5mBkQ8Zt0l6glz79Ie2lb//HOKI8ph11xUXtwfc4of3Yq96zKNoLf/SJ7fO3ukX71pveq/3aL/54e9br/rp9/fWPand55E+1r7/lvvbV89naglfzl5kDMwdmDhxODuzadMxtBvc2YbGbbi+4baE3wtcaQMn3G/c53IBwFcJnINcfgDAABNRxScG/3cvDZQvpD9ci3GpwfcKdEOfZwCwXF1yjAGyACjcYXLkcc8wxjZ9BbjD4eaQzIj2/6QcBOXwL0s8TXnmA4Ec96lEtlOrTfRD3LfIFMLn04YJHnpyVo7D2Tpc8XBzxiclXJh92HFkD9oAl5+TKV2RB53pFXlshfLKxsEkA1rnh+aVf+qUE2fwx4ueYuAvSJv64IOKaCADhSgT/ipQNwMRHrn0AfO3GxQh/lcrNJUnp7NmQAIir9P8qbfnRxVE+/OGuB2+5keE+h9sd7dITXiovP4IF0LWpvkGPijuk0h8CaLlEUTYbp2XEBYqNjnrwe6iuHHfjq/4A5NrIcGfEzRO3TDZVNjJold6X9uZehhsm4Fm72xw4Cldf/YfPSeWrcnPRxH0Ul0nc8ACkU2RTYDNo86hs9MSUX3/Ut40T/g2NEZtN4fFcG+Grvq9P4o88tTX+e1dlwcMD4XTcxg04lbY8bd4846rHWBJGOuqKn9wzhZVtFpsLHmOJ2yDtw62P8pkPbFLlyT3NKhJOHV0aUMS3K8f+xrX3xt6UDmiF38nPd//J+9oDnvCgduy+oZ151zu3Y0/8jvbXH/6L9rpfu6gNtzq53fBG12u/+h9/pj3wZ85txxzxG+1TF/5V+9hn7tu+evjn9o6YN25z7PfsZHHmtGYOzByYOTBzYIsc2DWJr/IAWZTL/fmOgCiSUU6vUQEdUjZkkbRgUlhGFkyAoUCb+Jwk181A3pNaAS2IwjalbMCCg2RAQJha2IXxm785oIafOAS4Aqik0iS+N7jBDbJswAiggqRR5QDgADIArBzR8+XIzx2QqF7AFBAvjnoVyRNY3Mhxb8XpP9VRWfgwtAFwHKw+8uHbkjPuIsCFFBxo5V+PUUsptQO1nNcDkkXAJwf4JOF4WI7kgRBgG2AEuPvj8f57pTP1KR/gC++0kY3KjW9842wPRgx8H+Jpkbz4aASygCs85EMUCOMbU31tkJB24CBcGwBeQO0q0j6AnzbHSzcuIXnoF0972tPSH6lyacf+tGGVg3RtCiTbTPD1yFm7cgHp2gAYRvyOIicCnOnr0/xeOv1YRsoG3AKgfDGeeeaZ6Thef+ZjUlp8qBpf+r121jY2GvLwm79DZdQO6s/no80Ckjb/rtodSNVXpA3o61PAu/HgnbjnnHNOfgdA+XS0SdF3tNXJ4T/TqUqlwSct0K39tNmUZL+vt36snJzZFzF2URf9WL/mj/VQ0TOe9ez2sh99fPvd17+p/fyBd7b7fNst201uvq899JE/1B72XeEnNg6Qzjr7Be3Ac89o777kM+2GX310btRueON97Qcf9T3telcP/0NV5DmfmQMzB2YO7AkOHMoTxY1UeNckvqsyBzQAKWACkAUySYB7qmNtiyen3SRIFnsEQPUWhwDgFBghESudUQtlTwCBhbQnkkfSsp6AduB1isrBeA9q1U0jW7RJU9XNQt0TkM7RdB+vf7/Z78oIMOIDAA9EFSkHyTJgiACTktaSTovTE8k3aTDH9j3hFVAMYJOyaZdVlqt93PpOeg7QAEEki9q02pEEXT2KgEAAFphDQLq62ORwxI2n+o6+4A8IBPYATmoR6uVEgOR2GZWkU7r7QoWhSDnKStSn0wYAHZEIk4Tv378/N1YVpz5tCpTVxg1o1BeUU7mkRU1CuwPU6qIM+rXNEPDqtGIZiSdd/CN1BciVC9Dl6B2//AHGVH1I/0mEfdqQ9US9wRgD/Iv0yxpjTmb0XwRgype0tcjNOvIAhI0PgJuknJWtkxT1UG+nJEBx+MLNtsQHJyq10aj0xp/aT/8ksS6y0cFTajX6jVMYALo2chVuJz8juwSw33L/J7TX3/vyxr5cm53xk/+tPbpdjWbPOf+17TpHHtU+8o+XRIgjsq8ecZ2j2l+9/fx29E4WaE7rsHLA/Gfu049n2jsc0CbG5TIyD1ubZzq0HDBf+3NBhrWYoG4v0NUz9y6VxuKn4kX1nbqDhZ9UDNXzCiceAkIs3I5SMQ85/iR1KqKfSToojT4dx++AFnDgBhJEGgu4AW3S6HciJJqVRn2KU2Wp7/Xbog/MFKiWtvTkWeWw8Fug+8UZEADStkoAUIFmIEwZCsCO+S2PHrgDRlW2yr/qU78BwZ6oGAA/4ppgfK/8hVO3/ncft/9Okm+DQ7XgwIEDqXLSv1eu4hOe9lJB/KpyAr6kqAD+JZdcklJVG5k+vLYAlFaR9gMAtVcBQPk6SqdCYjNF4k26XJJY4B8f9u/fvzRpt2XZaLhtiMTSYLfhoK9qI6aP1CmCtgNaSU+B5jr5WJY4PmvzopKQm/RJ7/FEv6d2g4S/yU1uUsHXfI77QfXjCtRfU2sD15O4Fb/arPqAjZP28WfTADRLuxamvvx9muPv1d79c3nW88q3f7/T3y2WNhna/6jgcdXhOtc5sh11navntSMD9Pp11FFHZx8W7uijrhN/V85jO12uOb1DzwHj1GmF9WiKnGCZ26fIRtGtXTXPTIXZqWfmxK2QOZQaYL/BHaczdR2vMAQl1BXHZG12yrSbZHPspI+ArNTh+vzw/TnPeU6uFf3zQ/Wd0AFvN0v41q/dG4lPZc4p6RRZcwmUCOy2QtaaKeBKBZDdlhNNfa/HVOZrz7l6dNpJ4LcXaNeALxBikOv4jlNZ7Gt890EDg45XLc4aAzlexlRAQ0cFEOhGkkq5X96EQ3plMQUo6KxqYPeO0zsFhqWtozhGZsTmyNmi7widjjFdRaDJMbYFzdEuUENy5hgWEEeADakhCVZ/fzkAa5BRLVBGpFPLq45yHSErO4nmeeedlyoNGr9AgTjAljKMAaZ3GyHA5vzQnSZ9dKyMT4iuMgAFJCofIzsgAc8YAdL7BPaAEDqSyqEjqr+6FfAR1iSOb/hio8BIkTTPBGMBEAf5NKloD1eqkrKuIm1mcpVOESmzNnN1orTUj1RaW9nQOEp3jE4iKZx6kfgaTI7U8dtkDaBoU9JF0uVlUhmbICcO9KLxQFvrf4CpMuir+KhvGcT6nzzxlEQU70pSXXXoP6nY6I/AM8mnSYFqi0VD+QFDfDcGLJTArqsdy7CyT2vqu3JIk2RZP/BJDYEU1fWQZ4b0W1uZkPBbvdRTHgi/jE36uZ4bo0gc7SxNuvd0cY1j9RdX2+jfiLS+wDW9ZRtJiztdbRJZfVF6dJ2RNsWDJz3pSak7rM8at8soLoXIPqkO2sImVbsZM+pjjOprdKp3i4zbiy76P9nHbMD1qZ7MZ3Sl+w1X/9538wdQYMO4ipYBplVxlr07mP70snjXxucWa+04RcZjCV7qvQ0qoYzxW/Ohd/qdOV6/txaVIKXi6Z/Gtf49Jhs9GyFqP/rRVFuPy9Gn4XreMQF4tent35mPqSpZG6b6nPFC7alOVCuuuRBwNI/2QqV6bz0znqXf26vY2Fo7CASM8b4e1j/1Nq+NSRrm91e96lX5ytrNRsCcMy43AYa5rT/9qfRcR0ySaN4jcLAW96RsTqPMd+bjPu0xSCasKOFan0Z9d8JlfpSmubMn/YZ6HT715KpuYBToG+cnnL6JR4RBRfqLuRYvS32s3vmkLkbAYX3Gf4Q3BDYEhPqF9uj9ilvvOARgt0FwRVBG0LeMzGnqWH3VWDEmrLH45JQVztBf9AvrLqzldBm4LoJ7nKTDENq2yidv6qrWB/hwJ8jaTJDkauRxO6xLPwb3lmknbm6LRt5y/qFnuPTKvqlEY9BPPR4CyE0+38zDVWlEJ5q8WWQz6e9U2Jgktnx1pytQe4rFoP+54e8xSWw4rDbGvzEFQJ28kScmkHHQHfsdg3UIwLWh9Ko/jMsz5mGAp0zPLUUboQDVS6/oFH+c30bSHIeJXfv40ZrfG2l35ZgKFxuMNWkd6h+bvbnt4Q88ddH/YuHM4uqP/tz65Nax2FwMsQnIG8LqXWwuhgAsQwD8ISb4IdRG8r327sPERiKvNI4NQ/Kr3sWGK/t3LDB5TXLF0wdDsj8E4F6kU3HwOxa7ITaSeTNUPa/PWPTzpitzrmfCB5DLcsmvwtWnPD0Xr3/m+dSzCuNT/cdx67130qg6eS69eu531b/i+Kw4wtXzWOTzZq+p8gdIG2LBTf6JU3n4Hsa1ed1tGJPmGiI9fHFTGIrNbd44V2UMFYchBCP5zr8AUkPNTcIEKM7wsZkdAhSvqVsAnrxSFb+Nc1cto6qD527/U94ArUNsCLP+AXAG4z1OybIfFc9joz6E8CDrEAKATEv9XY8dQCh/63cXxLW8VX6f3gVYyvxdB42UQbovf/nLF79jg5c8rfKJ21/7q5xIvAA9i/XE2A5peOYZgGmIU7EMh3dhnLwoD765bha5DlyfDlCZv82vAagW7Y8vsakfAkzlLV4hGMtbCtUXL42/2AgveOl7CAWyDPgegHgxrqw7+CW/AGyDtg/j2/xufNYztzCqs7+Qjg4B+oYAaAsexGlitpX3eODmtbA9GEJwN8QmfQjgtchTf8LbALE5LlWy+BrgP+eOk08+eQi7lSEEIFlv7RSbiOSHvhQqm5me/AIIr7nCO8B+5hmqaRleX1ImYc1PIcAaAvTmlebGir4fQpzEPCF0XIzTi+N2tTidzCuc8VZfFzdOQ7M95KPc0jXHxCZpiBPK7J9VH+/M+9pS22h3c6O2qzCuT5dvCAwX6xj+SV984y5U9YbYmOVv8fQXc1psBgZjospSaVqvXH0dwrTsG/pQ3Qa57MriI3BrHRre4IOzXn1se8HpF7brHrX6SHmDyc3BdpED1D00tV31wW5L2sVizElvgwMkAXStSTgYh+6EC7ltFOcaGfW1739uu/Syj7bH3vMXD1r+U//4inb50+/eXvz/vyzDklKRYJBcU/1wQuRkhCSJJI1UykkFNRaSfQaipDCxkLTf+q3fSokL6b4TBs+cWvC4QYJIokLy41TGyRfpoJOFWMTyRIAEg6SfJM+JFwm8P3YS0iZxp5pD4sEYkfSNR41Y5HPck94oJ0kSCSLptSNP0jhpC0cy5rTHPEGNhAcPKkO+mzdIl5wGqKuyCis9dSV9J+0nbRKedPROd7pTGl+KI52iAAKZRyyOKYnj4YUXHTYZyu7I3AldLGypv05q5uSJlMpJnXKTvJKeOq0IAJNJ41V5MCFNIqFSVypWeCQ/UilpM5AlnXLyIj0nfyWZLHsCpzUkZ6RVJKK+q7c+EItt2jtoL9Jfpxd09PFOO8mbrr06kNr5XuV0GiIN6bFhIEGj+08lSJtSvSIdxAcndk6wnLKRyLKFoCNfEjtzgHp5r4ykawEgMp4TK/1TGupCWok/8nYS5NRRfykPRviESOy0MduBAFJ5ckrC6LSQhJIEc9++fXnqgoeMwQtG4LuTVieAJKBlGyFP7axe2lg8p2YBavKUV9s7oZOfseCTFJWUUjsbK+Kqr3oI6/SJFJGEXnhUbeOkxWmok7BSjfLOqaGxh/fqbkxrN2HKhsBplFNpdSLF1+e8K5Utz7U3Q2Dth7fqg+/4Y5xpf/XTJsIF4Mz6kLZ7ZoxrzwCKOf7V32mj8ayfqJO5Q/8xNvnmN8b1I3Y8lZd6G3vaQ7n81QmHd+qnbuYd9fe+PvXbc+I0zVjQr9idqJc/ZXAKar0xr2gzfb/iW4tKlVAZi+RtHJLAm3Oo7znhrdNXbUhybtwYh8ooTW3pZMy8JE/qRMqE53hifOpL+qbykXArtzlLGyi7dREpA17+zm/+Rvubf/uz7T/f6WvbcTcYqZxFplumnZD4bjnzOeKmOGD3ZSc40zWXAzFJ5O47JrqUCl1za3L4Sr5Zie93P+CURWFJQkoiGIv6EBPu4h1JSkldSHEvCGnbmEirSItC9SglOwFi1wQJVa6UDIs/plDTSikLSVoRCQkJSADPlCgGIK5XKYUK8DwEsMtnARyHWMDyO6lKSS9jMU0JmPLHgpoSIHMFSR5JIyJlCuPLlCyRdKJYwAZSwzPOOGMI4DaEUfDgFAbFwrSQWAVATAlcvoh/obc4BCAbAhgNAaxTYhSLWL4m2XEiQhqLSPvOPvvslEIFABoCmGa+2oDU0WeAjgzrX4CalHSTCJFyIRJOkrWeSL56Im0PMDnEAptS33pHWkXi50+ZeyIdVm7SM20zJrwPAcNAyhiqQmtek/45PRDGSUHfj9YEnPgxDhubiolQVz8imSN9k19PJHyhRjYEuMgy9O98JwklwdWupI49kYCS6hkDY8Kr8ACTUr3xO/0qgNb48crfJHd4vVkyLraz3sWmY9GHN5u38AHUhthsZfv38UnOSaGL9Lkal5454ZkiJ4jGzDWJ8D/0e/MkZLPlNm8Yz+aI2OxMRiehj03Y5DsPv/DPnx1Oe+ulw0WfXX9iDG1vmWbgu2XWzRFnDswcOAwc2Czwfeip911TytBRyyNck/KYAOOQZOSxLmCxjCzKgAWQ0BOABhRvlsQrQNrHtegAw6F73z/OY8c4McijW6C1yIYK6HRMHlK7epyfIdUZpgA5IF8Uuo/5FWDtFyTgSznC20fypsL7xIdVAMXiBkD0hM+hq5jqHv1z3wFrwKsI8LVBWEWAh+PWMQH3jr2pg0xR6BTmUe7UO3wBqNXZpmK3qDYNy9K3AaByM7URWxbHc5vskE4OAOAU4c0y0ld2ivQlG6JrGgH5+uLBCPCd6nsHi3dNeU9FwXy3WTJ+qO7Y1G+Hlqk6zMB3O1yd484cmDlwjeLAdoEvQBDHoCkFXVZx0ooeEE6FWwbGpL8VWhZv2XN50L0bS5HoFtJJXgVslpUPCLMxAFbHREo4RavKNxV+s882AnxXpWkjQPdyq2Qzsaytt5pmH+9gwFc/JLXdSTDa57/b36+pwHejfJmB72pObXd+WAZ8d82rA12LUBhPHQ/6WKuIDhd9HLoau0k3v/nN11hP7mZe0o5G27EsTg7vBXGEt630WMOzoowd2Mp06FjR3QtJzJpwMUhTb3Aj9YrFP61O+YMdUyxGeYPZ+Plu/d5IeXcjbzp2+E2ParNEZ49elXFBx2urFNPKVqOui7fR/rMu4rXoAf0x+mb0z5YRPd/Sf1sWhp7dFJV+3tS7Vc+WxVv2XFp04sZjg/4oneNVXkuWlcN8T69Pnx0TPdApWlW+qfCH+hkPLbyVbJVcYLOsrbea5mbi6Ye85pSe62bizmFnDhxuDuzW/HDUblaMixKK/JT0GScsI0rcJuDYna67VGJZnK0850+O4vShIArfDGAYe+wEcUdiEt4OucGNUjkjFYYpU6TclPXxivI5hXZkc8LAgGI6Rf44yl05oTMeoJCv/Rkk1A1cDCS4waLcrwzLyjFVtq0+M+kfDAB6v5ODjGsVGwzGGYwENkuU9Y0b/bU3JNhsOowEuP7i0m67tJH+s9089mr8t7z2l9rb//Kz7cib3Lbd+YafaRd/4uPtiGNPak962JUg7w9f+ZL2oU+HH+obfmu7xy3/vr32f3603f0+92/v/YPfat94q9u0h4axyzHXm3artZfqbLxzZbcVYhBTBlxbib9X41wb67RXeT2Xa+bAoeDAtNhhB3NmkTkm4MlOmM89Vo3IrphEkTXz4x//+HXSxj4Nln/8mCI+6QoQklACWCS7JAwFtoQjPWMdW9IzgJTlJCtpYIwlaoEjZSLRYdUaxhV5g5Q0poivPb7xWNny1ccPMQL2WDezdGZJWsSXMMtMgA+YRcAJS1X5edf7UQwjjrwJi5Wq9JB6smZl8YgXVW5gEziRLnBaCxirTFIY/h2BqFUkD3myZO4Jn1gr79+/P33rHiwdPmpJjkipATjEalr9tDGfv6xdVxEJI+8F2gdgtzEikdq3b18CcX4KWTED1zZOrtXVDm4OY3mM6uIJn/Xdc6CUNS8LfGUBeklnWeKz9lVX+bJ8XUbydCGHjRuflHwbotCny75HassanuXyKuIdgLU5K1WW/EXKMQbjeMDSWPvoLyyUEet08Vlm85GsD8mfVTurff3QRrTCagdW1voMqRB+2PSQxrMq10Z1ArOs/4jPGhnPtyMVy0Lt8X/v/R+vaZcfe0p7888+qX3baY9u33nMEe2P/uBA++LnP9cuj4OdA2/4g3bfH3pMe+4Tf6q9/91vau/97E3aXY+/RXvx77673e1e+9vNrgGgd483wVy8mQMzB2YO7AwHAjRtmTZi3EaHjN/BnljV0j2i1M3wAcVRflq/0i3jbzeAXR9l3XcWyCiA7BAAK7/zW8cKGPEnF0Anv/tHxykW6bRwrYf0hxhxBIBJo4vy0RpgKK2LGVEEIKngk598arLWRnzP8cEnPXp+4cIjLXZZ1RYpL2MOz2JTUI+dRw/0wSjyByjJ5wFK0ncdngSwGMKN0iI8vTFpsTzuLX2lw8qYJay0hItNRvq3w5MAtqmHt0hoyZfYOKzR8wtgt6inOo8Nc5YkM4RroAXP43KRVFgXlmV5SFKWRcvn2qEsxRmY4ANDkZCCLuIFEM/v2roMdViGl69gFsl4ol36dghQu0iDhTIDIFbjjIRi45AWz/ha1u+LwN0XvjT5rVQmvObzEPnNGpXFteerjFvCgfvCMEn9Auiuac9w4bLwzakPq3vpSwagTb+f8gjwmrySl/qwFjfOWBGHK6JMU7iil7/85dkv9KFqS34Qyz+ssgSgz7481X8Y/TDkKqIHKb+9TlvV8f3Zp9x/uNejnzW8/k8uubKKF//+8G/ueq/hwBt+ffjvf3LxcO5jHjo86oyHDP/uRW8dXvuzZw4P+88Hhs9/7rLhhnf6t8Onvnj5sDXN3d3npv57babt6vjudd4cTMd3r5f/YOXbjI4v3fKayw6W7l55P+v47m5LLNPx3VVVhyloTn80XOOkZI0eGX9riLSJ5NYzfjJLOjWVhmclCeNjr3SoSALdJsJvnOPl/njXcXeF69Mk2ZIWKVpYYqZPPGUg7UN8Ea4ifvlIIeXnzzWD0iONlZ/PInUkeVU+R9mkpiTP/PM5YpQnKZ86IVJLeqLKw8+jG2MQlQP+K0lfSUX5y4yNQ74jwVQe9ZUOf4RuEyJ5J5mkhxdgOMNu5p+4AaoySkwuWbcAUulbr66zDRDVDsRNfOqHlI/PwlIvUYaSIgawyvJkwCX/8DIcg6fEFC8f+MAHptSblJtUlSoFaSlySiAsSTtVDlJ0VHmTYhaRmJNs4wteaBd9ThvgH5+D+pJ20T5TJB6pKsm7tMSTF9+T0iJFFcbzVcTfISmt8us3q/qbcmoDPMVrbewYlpTYiQHJK8KXIvnrP30/9A4/8U4di0iNnaAgcXxXx3H/iakqfTs6tXHTkd/6oFt+PLs20jff4W7tprd9VHvwnW/ZXvLC57bPfuaz7Zln/+d28v3vmNX9h2/7zvbIx/1Ye/GTH93+5ttv3475u7e0N7znJu30U+7Srv9VIbm/NjJlrtPMgR3mgPmG79da3/vkQ4iWp5nnnHPOwj9wvbfO8U3s5HZKx7zC7danUzGnhW6iMxePiX9mp3ROYqfozLht00m4uh9OckoIm1zbaVdVHSzSFmtHwgWaqDNoZMfLGFwgzCJOr5TqAMBzsM5LHUG6Fmv6p8ixtOP92PnllYyAELIw159yVJ7i13flFIbBB9BCD5Xj8ZCMZRrL/nEUD2zJEyApsA1QANLyA8Y5xfYdOAJMgMIx1WBXDuQo3vXIjrfxLSSW+Vx8x/YcYHPqrB49AdT1zCAMqUDy1XE2J9FTG4A+vu/KACAWyUu7IMfaQCLAJhwg7A8PC/RyHB7WxGkIRN8VGfQmL0T3lRrAKuKon2GGa2E57S4H8xzz2yRpu+onVEiUkYqFzUC1A1CKtAXQ7TpXZRcXH7UZQz7XYVd/UKdqg+LjuJz6KyOnOuLXNvouR+FIW/srVYRx/PpNpYbagXLoR/SqgU5UeUsHb6su+CK8iwNcIWkccThvEymOMnH0jfRlwNhzoJxuNpKe9pV2EVWJUr+xeZAmED/uP8JT61FnajzKwsF9OSmv9K5Nnw973E+3M+9926jSke0pT392+4lz/1M78yrQq57f/9SfaMdd/8j24vNf3Z76tJ9sv/DCc9v3nnyH9tLnP7UdfQ1lhP7sumqb1DHpP55PvRuHPZy/a04dl8H4r+tYx+9W/bbZrzVjVbivtHfWqO2SORpwLGFYpacNrV2emy9rbqv3hADWasIO6+RuEaFdrcHjPMyrVB4J7Kb6B6GVsVTrSsW3jlBHI5gxh1pHx1Tr7vh5/7tfq/vnG/1ufaCuR6VyGR1sLRvHwwuXTYzHoL5iTbdWTxF10WUCp6nwW3oWDbFlWqXqEA04hPRyiIbN4/UAW3nUHA00BKAb/HZ87bg/gEeGCSAE8Q0B1g7qtNoxsrRdgUeFIUBMXtEXFtVDgM7BUbbrI5Gj+WB+lke+jvFj4h4CuOVxLpUGaZXqQYCBLBOn3wFEVvLHMXKA2SHA1BD6tWuOtR0nyy/0UIcAnHls7OhNHUM/M8PHLjGPxQPU5OfZoarhfR1hhdQty45HIdFLp85UMmL3OIQ0L3koj1ikMp5y+B2AcFFuvJFmSDEH+fVH1ItAV33hQFtYbeez3B3FwMirVT1z3eAqisUw+YmnysLnZpHjKM/jxpV6tPSTmol6ahcO+PWdIsfy1CWKXKMovLRDfzoveqh3fIoqB7UBbYKoXVQd4zajVAWgmqJ+MdFkeHUWzxWayyik0BknpN7pHko4/FYOf9Lj4mkZxSQ5xC0/GU7bUbmQL3UVcas99S3kcgD93Tuf1IIQNZ8AzBl+3Gdjk5XhqavoJ1SPjIcqXzmo1+/5d1Vn46ecqS/rPy4REFZZ+E5V7r1OW1V12Gy9qNscLtpMO6xSdTBHUUcLffc185p6uUhDnzdXT+VHhWarRA1up8hVssbYmPgqplI2VXaXUkyR8eH6XBdTjImaD5U3nztJU+WTvjUrgODiGt3t5CkPqnHWxDF557n5KDx2jF/nb/MHtSj8GdOy8o/D+W1NN25KjdEzqg4BiHPd81t6Y/UzbvlCCux1rvX5ZZP/+CuGP+Q31V/k63pl87H5kH/anvhsRta+Urmr99wf8qUsXZer9PTGN74xL4cpPrv2uCd1CyHDQK1tGS/1hbCXymhx6rw03LL4IrpymzogFb2pcNZtZYfrxqTvlEoR3+HCWDviFD3XZP20CA9c6AKHmDt6NU1hQviTqnlTY8x78fWHZaQP9uVfpupgB7JlWgV8t5zoDkTsK76d5HSEkIJtKImpwbKhiBsItJtpbyD7NUF2oixTE+SaTEY/xu1pcMfR+ijUlT/HYScDdQ93oj47kcZmyz21SHXV2tbX3Ux7WwXbgciHAvhawG2a6YxPEf3oVbQd0BhHxXkb2qr0+75Gnx0IHC/k4ofRaCYT6kvrbu+yEQX0gKF+AyqCDaoNu83+ZgmAsJFatdk8WJoEKjbnb37zm3OzPw4fx7kJkIAOC21P6hNqZHnbXM8nc1aoiSUIZMvB5qInYIdePVsD6W6W3II3vuEtVNrSrsMmvyd8D9WlvF2vbhKs9wQkQFBtZuv5qs84Hctb5Mb9DgiyAQ7VssEGf+rSFnmFkXL2IWGAoCICGjeYsRvoyW17ZdvTPy9Aqw1q81HAt28n9jPGWJFy1ZqiL9qwjcnzusVw/E7/V0bphsH7EKpd6y4miZPMBSAG1mz6i1zcQqBQ5OKP3p6Cb+wi80K/KeYnmqClqARe9TuulU6gxxZJ2/aEv/jkBkjjWAlxQzUAAEAASURBVN8DGMeCD3Hwkf0KQR1bn/7SDDin+pG66Yd937fJVX99yo2OPXknf+Mt1EbT1sTGtepsXulvV3Tpi/FpjZFvzTHS1IZxepj2X3FqOwjbkzFn3XeLpL7al1E4m3j115+NEbQM+F55DhwzzbWJxqL1zdYtmJoeIBwtrxL99+mG5Kv/uaPfdzPtzRZ0J8pSR/YbzbtvTx4nqJU4lnfsVHqtlVYftp6t+tyJ+uxEGpstd0hrV1VrW+92M+1tFewwRI4JOvWZ9Vk6erHJyeN9x7JUR+jlU0kq0heo55QXlFgoFsd22tiRLC8bVHGoCfCMIU3v6s+RKe8sIUVJVSaqXHFqlWor9LJj8cz4vNc4Nqxjzlg4UkecOg+1n5Dsp4pLzP9pOxCnY6me5EiYOhR7AipJdLl5NKGnrSza3/GrZ46Vqd44avYOxYKTKjB09uVP3SsWzlSfkWaccKTut6NpqjOl0uYdzyexCKeKElUoaXlOF50bRce6VJq4O+QxBc8DkORv5WK3EIAsVZfExW/P8JGdAx3RWPRSTcdzXl8uifg1RpX5x3/8x/PP8XKpBeG9euItXu8LHX9zDU84+BeLfnoSUid8P//889PTDH54HxKzfKZML3rRi5I/VV5HxMrECw2+UvPidchxrvqpK119eehL+gg1I3Xh7YWKGB1Rfc1nAKD0lKNObD3wlApGAIr0sqI9eDTS96jc8awjbfVSdn06jI7TTkBbUMWjMkV9jucj5fKcvqm21L+0Udygl/nGSVOG0eb6I/U94wNPqCtqB/2LzirVLXXR1x17SwsP2ZrwSuN4XxtRBQxpavY37XJB2HBQp1LWMPpOuw2f1ZfxRv+xVlPJkab+yd6Etyh9iVoEHumDeG/N0KfiVHjh3UkcKmbGqz4Qm6XkJR7rN+pFdU48fEbCec5bEdsJdTIOqCl4R+UrQF3a/KiHsSOusgtnTOkT/uALdkKeiUt1UV/Wn/CFOiC+0V3maYgqJu9F1Ah4PNK+xq26+ZNHgOEsM1VE40r5rZX4or7y05ee8YxnZNnpR5uPlAG/jAN9Qlh9GE/ODPVU5aNyyGsQ/lJbZIdE3ZCHLL/jJDX7b6mm6Evis+vCT+1AF1t/NF/RjdZ22lkf0D+pICl3nM5mfxYO3wLoZ78w9+o/+rt3yFiHC/QnfQ1ff/hJoUp5xHXz/fjfEcEoO+wt0VmvPra94PQL23WPut6W4s+RZg7MHJg5cCg58Nr3P7ddetlH22PvebWLwWX5P+BdX25vu8eR7WH/9vsToPBFbjE2qVqcLTgWawsYPW1kcTCB0/82gdPRPztcIpq4LZbAlN8WbKCHTnxIVPO9xfKcc85J0CGtOFJNvXR5Ai8mdMAQWAVKLZJsGhjVWLBC0piLPb1uwMViDYAAA74DZIxX6CoyyrSAWJiBHXVgE8Fw1nd63dJVRosf95HeWaC4wKNTj+QbN70lcAAqgTpLCkNU8SyMgAb3jcoHlEubez3ARZy4CjnTxwfAz2LpuTwsuIAuI0p5Kz8AD0ACBsCQctokhFQvwQfgpwz4ALhyq6j+AAr7AEDTwq+t5AXQWdAZEAMcQKF3+K+ueAAY0alXJ++AHHVjSEx/U/7KjIAMevghfUqeMQ7VbjYjFuj9Yd/B5aI8hZEP8Kh8ymPxtrAru/wAEHkDcNLCW8+UQ5riAmF4quzqDrwol3oqq/5D/xW/ABVGtOqkTwMZ0gNMgCl2M4CNOhSwUC9l0Z8BzVDPSqB097vfPeN6rzwAo/6t/NoZGNNuwA0wxMYE/20Q9EvAWJ9XV5sO4woJe3HozRpD+jAQy8C6CJ9cjoQv2hsYlA/S7njxiEc8IsukHwF53gPyNgvyVF59kn2HsvRQyHd9Rh7KC6wZF0XGMoN49df2yiY9ZE4wZm1S5MtAXXgkn5Di5oZB3dXr2NjYlD97cW2M2cXoB8ZokTSMeTxRR2QeGZOy6yc2Q/iJDzYjeI70DZsROsf6HqCsH1X98RvQZr+hHWwypFF9TrvanBobbIj0i4prPtA/5GGzBIz6ft5552Ud9fe+zNrGOFBPG3VgVn9F2hbv9UFlMA7xFZ8BZ89snuStL9s8nnHGGVkem5nvf8T3tWd84lbtvBNv2I67wUhQFJG2THtV1WHLFZojzhyYOXCt5sDmVR3uk0dqjkod8/mLRXfBo1hM1hz/heRsnS664zlHqY5rHTP2FJP8EEBhCACb6gH9MXmAhTXHon08+aIAUXlEqEyOGosCJOcxdYCp1AMNgFuvhgDA+d3RqWPHogBD+TUWlDw2rOc+HS8WjY+SHVlWXPrysUBW0LzemWqB4+tY4Ne8CwPVDFflWUSKL7HYDY6M0VgFgAoDfXVtEkB1COCc4UJ6lJ/9vwAlyV/hHYlrv/4YWthYYIfwqpLRiq9+xGKddikhCRuoIozJ8TJbiimVFjyhExrgceh5Lw15OF6nIjBFAdDWPRZHW45pqlwVBs/LBqCe1edUHt4FME5biGXvhXEcHoBtTVt6jtjV6IelqnDl0+X/8ZB6S9mS9CFDMp9tho9j0r/Zqjhin7KhoJNKRYQawpgC5OVRe2xG03Zk/L7/rd+s4kWA4T744jv1EP1X/cYUm9KBLmwAyIGqQ692UGH7MVTPNvuJR+O+3qcREvp0G4tXY1K2AP1r5pQKY64J8F0/V35SdQjwvFBFGQemtki9AZ9CKr7m9cUXX7zQlw5Au+adH/q+NlTPANBr3muX/+/cc5aqOkDLW6atAN9+YtlyxteQiCbv8aS300XfCj+3Emenyz2nd/g5ACismhi3U0JgZ9misJ10txt388D3an/iwIp69WQsFXCjcxdHkP3r/A6g0f8MCeG6dx5Y/Laq00q3kLEif95AdE8hLUldVQtYTxYjZWJ0yuimCMA7O0A4QBYSmHqcnwAN39iMQkOiueadHyE5GkJiug4M4U9IfDJd/OmJQVFIe4Y42u8fL77rnyH1WqMj6GVIjNIIhy4fgLGKAE9lYGgj/NQir65Tz8WzWbFBWEY2CYeTAJSdJHXWxlslICRORDYcHcCb4r0E+DgPNZlJYOs9o0vtulmQCMjim03LqvkPL4C2rZAyAXP66hQZfwjgnwK+U3F245m+D3yOiR4yXfet1r/SK+Bbv6c+zQOhmrPulTnRvBkqD8PFAYLHZD7Vd5TVHNqTtee55/z03gG+ChfHA+kJwUS6F8ngZYm5XbIriqOnNclokDj2WvMsjqDSoANQ3ggZuKz/D3YBxKq0LAiMEQ4l4Ucc0WZd46hiZda8F+jwJlE7O38mCws1ows7fZ09juQWUjF8BQIs9BuVOKwsxFUvpSvPD33oQ2kEFEdrk4v/RtI61GEYdCybWAGc3kiHtCeOYLN9NrKjF2ZZuDhSXlw+cqjrvCq/7QDfqXQtjiSJv/ALPz+Q9h5qkr/5ahWNNyAWY1b4Pqe8Ong+BhNxDJ5Sql6qvCrPeqd8NgPG6ZjkQdqzjEg4SaWWkfjjBW8clsRXGcb1GYdb9ZuUeK/STgPfvVRP7UZiO97QVRkBtjJiqmeb/ZTH4SRr/7L5+XCWa6fy3gjw1QahXjGZZahRDXg0ReIxynMyMN5UC/+Hb/y94UEXfGq46LNXrIt+peJJalTs7L+YbFNnqXTg6KSUngsdFvolUZpFpr7T84gJKnVCxEOe0/mISqZ+FD0qeiQB/jI8fQ86Skh875BPcemFoJjMU39KuqXPIzydK+8oiUtbnFjMU7+Fnp58qtyZUPePThZ9GPGkW7+lJX/xws1UF6OlkntYALc4EsznwlD8pg9DDxApX9UjH4z+0amh/0JfbiPU87DKSoeHknssmplE8UlYz+jVaDPh8d6z4hWdHfXFG7zznM6VcisbEl8c7UPJ3iel/7CITp077byKGHXEYpuGMYxvYmeeyu50hOhDUYqnx0gfjY4VPUG/YyHMPCjy0xvbCZIfnTgGKvSI9As6j/olfqmftsMPbY8X+qT640fpY6mzPoeKV54Jh//GjD/pVV8WzndtIIz0hBdO22gLacjfb5/C6U/KxtiATifdKH2q2kca+pD4RS6foFtGd1J+RdpSO0uvyu0dvUJp0lPVvn3a9Emr3pWONJRb2aq/aVdlUEfh9aW9SPiBz9c58qh25HWOaIGm2pdb1Dm+u3zkI2G8cuc7n9C+HFPaEcOX2xUR9ojrhD5ofP+XeKjOwaIdJ3zv23Aqg5pL651+wghJX52iqef0dI3HkGJNRVn6TPnojfobk75Dt3AZ4VkccS57nX2vrqtfGihe6Ler5tNVcb1zYc5Mh54D+o6+q/2myDzpbzskj5kOLwe0wbJ5n/HkMhKPn3l67Axox3Rbzz46fnrl711zRRD6RanwDTRQjLaoWvSKxp05JHhpicrimOUiEIEYYTDmCFccOcEfCAMIFPo9qQwfu/GsvImNtSFLU8Ak/MTmgswimsEFownGCAARpX8LmQXLhE7B2ycgE9K9FlKNtFB0GQGDh2XEGnLfvn0JvoRhCcm6EdgFnpWN9W5RSAyzPgwolAegKwIuTPIWgpDE1eOVnz04WRYQn/eHMQVjA4r6wCce4hewSHmcsQNFcUTpnVU54xEK+0AcQI+3DBUAmtvd7nbZPpTYQwcqDW2kQ9m9SL0ZAQFXjIC2QvKXDr7p4AVkgaZwg5JALyQeCUgoyFOUR8oEEO8Uyc/AtEkBGvwhfa3KZDOnjCGFaGeGQQ6gyehGHRgJIHxgJEHRvy660OcYZjAs0mf1AZezqA/jBsS4R3+3yWLZyyBC27H85wjccwYv8tfn1B/hDQMNhh6MEBi4FDHoEWeZE/EK51MaNhysvvUDpEzAv/Lqyz1AYZUunDFQVOPqgjCmUlfWvUhfZ5CDR3i2V+nFz/ye9qBHn9W+436PbmaxH334Xdu//+V3L4r7quc+ub3ijX/Q7n7qT7ZXv/hH2kmPekZ7/Tv+rH3rCae0l7z01e1jn7t6I7GIdJi+WDAY9GyWTr7qdsjNxpvDzxyYOTBzYDc4wFjVWjlFt/3m45dumnZN4msxJOFhqQwosBy0ALNonCLgCzC1MJL8WDQBSBKsAmUmXkDz/HCbQioFiJHCuDkqROoJKkkyuXKx8F4cVqEAJatj+QJw3vljbQngAhGACukCiZ5yAO1c3ljoV5H4ygrEKEsBXgAEuZ2OJXQRnqgLEAGE9gSIsrpFpIrA+E4QiRoXIYAiAraBMaAZ0FAOHQdgEkYZbRy4+eGqhYQWaMYXoIs1MumcTQxrYsDUZgWVVIfklUTbBkY7sdYlncavzRDQLi2uYFjQ2lQgfAa8Kj/Azx8LVq5fuHohKVAPu8GdIK5eWDkDwCU9ClWMxfWUJKiAPvdqNld4ChjqcwWaSeb0DbxXXkAdYGTdzhOAk4AiPGM5jVjQGjvqpA28szEEGg18/ZWVv76P3yxekY2dDaeNQ4HofBH/9HkSvNpg1vOpT26JbHiE57LGmOIJQL8n5R1vbEjHhe03t4CWvmgTwZIc+FIGYF//smky5gF57bbX6PIvXNa+4TZ3aH/zgV9sf/TLZ7d/OvoG7Z+vGNoH3v1HrX397dvnP3dF+46Yn972tte34UtfbJ/+p6F9Q4yff/zcZS3MX9pNrrdrMoa9xqq5PDMHZg7MHNjTHNi12djiDiCUdIyUMBSlF8yw8PlDwKujbRIoVxYCTeKThtXxqXCkr1x/cMkCzIkvD65XAFhxSqpsgZW398AzACQt4IFLFWTR5x4EAYPKgYQHTDZCwAepGd+GQGQvrZ0CFTYDwNCYSBMr/DKx/zjORn4DqUB9EfcfJYUm5UZ4JRziuxGI5/LFMWLxAYipI1WAuKja1+/KB0gEwBD+ky6Wakc+jH/V9vV76lMYwI76gnYjuUc2BsCtY1cnBY5mbUAAPjwk5ac+UnzUL4C/at+pvFY9Uw4gXj/jJkV6RfodcA64AXBIGQqkK7dy6Pv6mLT82dhoiwpfID4fxD8SWuoS+A4Uawv56iee68s2HrWhkWbVt/q0tLQfqf0USU+8KarneGbDyU0RYC5/wBdJ21iZoj5tafjdj2XflQuvyhUYNQpjfi/Sl750efvsF67TDrzvA+0Nb/5wuyTmoA+8/tXtetf/2vY11z06+taX20V//PvtRrf+hvaFAPjfdJ/vb9/xr0NN5Wu+qT3rKWe26x0xfVy7F+s6l2k5B6rvLw8xvzkcHDBvEAoQtM00c+BgHNg14CtjixtJHT97JIYkoAgIcZxLkkX/UDjgyyJPDSEs+RLcArr8Njo65bwYUHOEzWcbp8jAlUUT4CQtBniAYunVMSsQ5miVlJj/RxOXo1vE32KFI1UsSRkgBWzJW16r9NBI7NSRtI9UjXQZSY8kDshVT/VFJHB8B5IuCyueegMGwgIJwPGqCVZ4/AA6pDMFpDOzq/ID9EmTlcOGgdTZkXyBDDyQJwKapK/NSBnxCPHDWN+pdOArMtGQ5CGf0jEBkQJrG212zjnnpBNt5cQTgIeOrrZfRviBh+qpzemqkhoX2FJ+fYAvROV19E+qCIjzrakPFAAMw7gEkvQat0KkyPL1Z4NQvJIWSbnNDv4W8Je3spAIU9UhZaeqQx0CWCVpp+4AyEtPnyUhDSOHNcUDtIFjKhUIsKXeAPCTlOqv6o+0jTZCPqsv629OW/CQSgVpMd7KSzjPtYl+p1081/eMUf0fAAa09RHlAFRrzNTYC6PDlFzzkem9uPqICx58xw98Mu7k47uNCem4MlRfojpT4yQrsof+fe8Tn9vOftL3tmO+9sj24l9/ZXv5r7yqvfy8Z7dv+dY7t+NveaN2+lnPak99xs+2551+m3bLez2ufe+/+nD7ows/3l71wrNCFxhNbzD2UBXnomyAA04LrVFT1J/YTL0/VM/Mh7tB5o1laVNVWvZuJ8pinSmB1Tg9p23U86y/5vrDQdYpOKPW1MNRhjnPjXNg14CvQUDaZfEnQbQ4kroCDQCq405H074ji2z4B2z79+/PRbwkSYCdxVfHoidYSswWWXG9B2pJ29w+AwAAqySwFlfkN11TkkdAgJTQAgwI19GzfEmcEOmzI343njiGBhaWkToY9HSZOV8uCai6kD4D8UBAvxOVvyNdPHBk7P2B0Ls1gNWHekSBi6l88VYcUkPABQhcRnhH5QMoA3zrKJn0luI4kAOM4Y90gXIGA9oMKCHpFIa+qroBr9RI1AdQoRICtAGHNiDaUThScG0mDTygdwo4igfQ6RviLJssgTAbCu0tHEDlyF0d6EgDi6g2SRyJ2/y87nWvS7WXHkSeGUfqVGjweyukLPLRJupE6lsScukBstQbiiwQykeybpEsI0Rl0lbajP4t3Xf9lQ47Sbs+0294tIF3+nWRtLSFvky9QZ8zVoBan8YXFYcCk9QGbEIYrQGebgLS99XFRA28ahPtqv95Xio3npPY46vxawPIoK02OiTY+g2AS3WIyoM+oc2L174jBkJAg7azCS71GEC+TgeoSOw1Pd+jjz4qy33g3X/R7nzc1Scdt/qWE9tJx9+0mqXd4W4ntZt+VWv3fMDp7f73uW/7gcc8tp12129pD7/vXduuTbKL3Nd/WTau1odc/WSvbkRWl3p7b81nTpTGPDQ3Ov1YNt/aqBuHy8iYZBeyFRqXpdKok5n67WQJACx7h3ref5rPjO2ezCNOXG3ia+3t31t7zStsOcxvPam3ecUGe0wEQ/1c3L8n/OiJsMUNYtaJntTRHGR9thbXqW6FMbeb55xGFZ6od4fq07pEyGNtG5M5Ee7oBSbjMHv9tzZnxMwpwRTpGzXXj99PGcsKsxH7knFaO/Y7BtSWaZUf3xgotp15f3SAtC3nMUecObAXORATQbpaCj3c9CVZZYzJLd1a8asaG5x6PH/uEQ5sxp3Z/f74S8Ntb3HMELetDWGMt8bnrerEBiId/k9VLcDD1OMdeRY67kvTiQ17+iddGmD0IjZQoydX/4zN2xCLVrocU9drIk1dfqAeAdaG8UUcnhu/AV6HUM1b46ovNt550UWAsiFOzNb5f+U+UZrcA8amWFJryEUhAc6G2CAPATrXvPMjTmjSXWJsCNe8C1uGSbeV5pbY0A9xkrQmvL4am5X06+xzTC4NCYHPoJ/0FIAyXYMFqB/iJKp/ld+5k0QuWIlNdH73L04sc3xwTcrFZmycF+/0Lb6TQxK+xlcsXgZAHMIwOH3FihACkwwXm+90D1iJhBpZ8pM/ZRQCrnVjLk6QKvgQ4Hng/7mnECple64aNy7liJPKIexv+qhrvnObFaeXQ0ie11xiI1DczpZhtVecZK6JJw5/uPrImELIkJfbhMrcGteSwrl8JDYOeVnIOF4A7bwgpZ6rWwDJLFuA/3q85pPP6xAGJp8DpK5550ecSE5e+OGdPsGPufbuybyAb/qt/hgqf2v6AF/MXGRyM4pHwpsbY3M2hE1K9vk+Pd/DCHvyUpgKFxuJ+rrmE49DGJPzVfmiPu0tl066M9s1YQQ9zHAunFIvEtSZZg5cmzhACuG0gKSD1LOIOgKpCSPAOp2od/PnNYwDsXUnxWE0yCMGyXZPpPoM/Jy+jMlJiP5Buh+z80KS79TCiQEi3XeSMSYSrVjI8l0sFClFrzCka9RkpqRoJHn0zc27wkzRWCJGSuakwV9Pykyvm5SKRH4sZRPWSRdJl3zHxAiSMSgJ3mZIffft25enbcqwHXLsTWXNScaYSEQZyPbGx8I4kVBvJxu9G7M6xTG+2av0HlLEkwdeOqExJ/RU7cxg2MkR1aIxOb1zGmfuKDUlkucATXn62BtaOyVyekKyW3YX0nMa5STNSQwJHKl1Tzz1iPcTP/ETqXZV75wIkkjyrsJWQjo9UeGoEyRSYW2OnE46qTI+8MQ82EvxSDrxiaEv49iSduvb8AEJsZMr5Jn5Un1InPGBSp55Vt9z8oSoq40Nv5W5yAlqL3U1vpySGbvae4qMCfViZ6F98HdMbDicjFItc6LZ9xuS6jJEpp5JvatI2tQ42SaVjUq986l+5gP9lGqh8Po9yTYpu9NsKmZOn4ucIjrhdBLIqB+R2CuHucg15qifW7Q9qbi2p3anvfpTS21lzPbPMpH4RwJPvc7V307RS9VHOfVPJ49O+Jzu68PKqg9rTzY6TijNh/hGbbVO4tWrVEMrLyeh7IEqj3ruU7/URozGp+YG9afyYs6uU9Y+fv/9iEhgy7PLWa8+tr3g9AvbdY+6uuP1ic/fZw7MHJg5sJc48Nr3P7ddetlH22PveaWLuVVlO/WPr2ifftId27Of9/xUFbLoOrqlx2chtjDxVML4kJpHqalY4Bg30qcXxmIAGNH1togAGdwGUh9BFmuqQECm41zAi1609MSjemRx2b9/f6rIUN2xsAA2FpEyggRIHHVbaKh3hZQl0zTFS9tRPV15ainUziy61FfkD4zxhw3YqRsAow6ASOnuA8DS8p5+vbCAPzsF4EeZkXKrN/124FP6BVzkCWTTd7dYApSeSUueFnAqPmUoui9AsPQsvMCShd2iLy8Le6WrbhZ89UTaiEqZtLkCtGhLB7B2zO8dV4Q2ChZni7J3yssDkPgAn7Ij7SA+IY689QVqDwx91SEkrWnDokzeAVL9ES9VI23oPcAnLjUypP/gMX7Jg7oWvuMFMApQOurXZ6jWaXtAQnl5CAJW8As41Z7UlrQTMAWQ4Qk+qOsTnvCELD9AZWNCBQ4YVv6CAtqByhqwx3bCc/1M2aSDL0960pOyj1GfqnZXl5CupgqhPBneGi/iScM7tgmAHpUQbQeQ4hOeUaMAej0H6NhocL8JYBs76o70H+U6M8aBtgTq1BM/lO+CUH2gesiGwFgCuo07wAmfgXXhAFJl1CbUrKo/Ad02bMav/qav6D/6UfVX+VOD1C8AamPHO2RcysO4Zawvbf1bGbQJFTekTwObbGKq/1EzEx5AtGEA+tXLnIJ3ygvoUzeUH8CqvjZdwiMbDMDZvACM4pHxUXG0BfVB6qLSRFTP2KVoS2UEktVfHtLQb2yqtCVeA6YM4G0GAFH8RD6BYbzXZ/RVILs2aPS0qZgi5ajxh1f4oe2Nb/1PWtrRJ/Uim31qct4ByOa3Slc/soHTJsWv73nYQ9p/+aq7tRedcIN23A2unJsy46syj/y3RqtUHbaW4tZjRQMtIvffFw+38CUWpi3E2nqU2O3lMdXWU7g65nZ5EINpW7cdXV2Sa++37fL42suZvVuzzag6nPKOy4cHn3LvvFUoFq08CnREHItRHgu73jeknYOj1lhQM5x31Fwc3XoXk3CG9zzAZf7Wb1y16V0stnkVsOuDqRY4DjUPIMeRniHHq+FqMH8rSyxAOVcEEFvc3BaLUYb13nF0LFiLI9lYzPOoUoA6GlYOR/DScvwegDnjB3DK42ZH5dLyOyQt+U4cR9eOlKtujsdjAcsb0oQXz5G/7+rsWNb3SktdHVfGZiHrGoAoj0MDTGd55RcLc6aJP458Hem72jSAyBAgJI/cFSgW+VRNcEyrjNpHfo5Ylc8Nldoj9O3zaJjKiiNX6gjKEwBtcCQvH2UKgJn1rXZUF+kEsMkbxKoejvQD3CfvQsKV/Kt3+kIswJm+MkpTHeq9vPCLagTVBMf++Frvhe2P06sfBbBN3ktTWM+pIEgvwN3gfaXhMySPQ4DFbI8AqKIt3uNxgJlU36AaoL4VV1lC6pnXQWs/JK96T80igN9APULfqec+Q9KcbR4bueRXH++CWFMCJGV6FUe/w9v6XZ8CBbhJFYWQoq6Jo+zK7D1VAW1e8XxqU/WNE4k8Vq8yaLMAndnO+qf+gv+oj+97nMzk8zCUTr72/PFe2wUIy1to9f8+fpy25Jh0pK/vKa/30ghJcR77a2NXAscmJ69krvjaTJ2oLvR5uuEwNn6pZuN51UldqSCM20HhtWFsBpMXflce4kojAHu2VwDZHA+eKasxRmUhNhY51gJwLuJKw28qJ9quT7fSVxYkH/Xrx7++VWUX3piLjWeOf7yqcWD8x+Ysf4cUfgjAn+NQXGWMk7R8psz4L27Pg9iQDM959k/urSuLkytL/qmQa34N/M0SHZwQk28qmgVoijSIQbLTpNHoiE1RGJutvKJzKk7/zPWAJvh9+/b1j5d+j51pDoCpALGTywlk6t387GoOhNuxIXbWVz9Y8Q0YCqnDihDTr8LIb7CQzLR9DmwW+D701PuuyTQMAnOhCYne4rmFKiRL+Rs4G+vBLQIe5Avd0pCyLA1lQerJRA9kAU4h9coFpN6bZ8JwMW0slC+khvVqiCPV/A4cArFF9DEtLIAe4NZTSIESvMWRey7U/TvfQzKTj8SlS2gBLzKfFwG9RRZm4aQJiI6JDigCsnsCCiyWwLy8LJbIQhxH0ak7WuGBKiQNi/DJJ5+c+pb13icgbC4MSW/q2tY78ymeh9RqKB3TegdwhLQu+4J4VYZ6DwwDTeKFRLUer/kEygGg7RDwt4yUyfoWUtMhpGnLgm36OR3WOKZeo7dbiai3OREYmyJgdKMEGNENHevsig/w0JkOKflkctZvY2BMIVlOIGjDpA2NnykyRvTbKT3pPnxIo/uf+V3Zwkg3yzilQ2/zVf3W2AQkN0IFKDcSdhxm3D/rvc2bDdOY4sQjdWWXxZsar+M0/DaG6N4ejGwE8a0nur5IHx+vm8qlL/mUvo1MT3j14he9cDjtrdM6vsTNW6aDSXxlrnOZTIuBOqMK6tT9c4Xw3F+IrYcQ9S8tlzDSkb50Km0TX0kmPO9JHDuw8fNawOyai0zetQDUM5+eq4+/Pt8+TH1XJmEqfD2/+OKLc+BJq8+z+FJ1EV4ZpFGfVfbiW5XHZ5H8SER6ko843vVhGTkY2N73+Qo3NciqPjWhSEu61c592n3+vlfYqkP9rrS0j11avRen6q1svguDlLf42pc7X078k6a2r35TQYonVdfKQ9iqk7DiVVxpjfO0gI1JOPWpMosDoDCeUP6eV/KSp/x78twznyb5mbbPge0CX1IaG1RGPj0x1iAlimP6/vGmvjthKmnvZiKSeJTkqo9nQSUJHZPwFl5AG2Au8pzE2cbc+OrJ7zgWT+lo33crTKhz5JxN+jY1d5PIAJCEEz3ZSJDsTJG0SLmF6cl4ACiAZpvJVQT4TpW3j0O6xNBmTOpMgqlNpjYz+GRTuoy8v/JEd1mI7T9fBXwr9WWClnq/lU/AaDwPVjrW750igGgZODWP1vqxU/n16UyB2v79qu/PfOYzc50vifmysJsBvsvS2MvPNwp8p+oQKlm59tmYTvU184a+7dRjiv7qzz80POiCT00at+0q8AWsQt8jj1TszpEdhskg9Ltyt1Y7adIGksrQOUng5ihlGbEwJGEgHSFyLwkn4Bt6QXl0sn///jxikobOZQfmmCFccgzhkiMlDKGHM4SeT+5QTbBlkQoMWtzCSGFNEUKfbQjjheGMsLRUB5KHZRQ6ULljIlERVtlM1KHwnTvwMHxJ8X7Ft1iEDs5CAqOh7ZwdP4ZuXQIfRx2kJPKX1iWXXJLHESQZRQDUGPiqh4n97LPPXkixSbPVHV+Uqd8xkQ4dE9aRPQglvbCI6Gx2wnbUFgQ8wUf1DX24Ksa6Tzx17OZ4BYnLwpjUxC489ICGl8fRrHYALlAYMWS9SYlIGEJnKJ9rd0efyoNnq8hRLoksYBIu7tKqWnhl9WdBk55dozbXr1he4wm+Gbj6DV5ph9DzGk4OqVFPY+BLeuTkwYDUFo4G7fJD72kI3cpB29dCC9jiJ2Bggdf/EcAS+kvZ1sIvk2z05Zi/H5wD2wW+y3IIvcNUf7AYHw7aqARG2QA6c5IxaXz0pL/rgzZtmyVzvfE03sBJJ1wdDmFYsy5JR/RTi1oFJHE112yVNgJ8V6XNWp3Ucau0nbJvJM+NAN+NpLNXw6wCvnu1zMpFRcmabpO2imbgu5w71mTrp03WMnKiMfaisQj7pcsPj6oDPTOAhS5RGG0sdt4AUBEgadIO5ex6lO4sgIVVBEAUOfayKwAub33rW+djKhNALgIcegL2igpM1e/+U7pFQAx3LUUmQyB0GdGtMakDdY4Ji0gX7AanCAgMa+PFKxuHi0NCrG6kMSZxgAjwd6SKHJX1xylTwNcxgSNA0gsLXu2SHWeOJTuVeRjgLBYwvAT6iixGJYHsXQLZbKwi+aMwmkkdqQKtgJ+jSPWwUejzAkDxoAgYDeX/XLD1kTAKWLlIA6xFNgrArckojJLqcR6jkNyQSNGlIrHQL4TT5kBN32cB5r5/joFvGAgM9JIsmiZuPEfqBsz3BAzY2ZoAtb+wdDvxSFsiG5u+vH38+fvmOLAd4PuRv/xfw8X/9ypAeMXnh7//x6vB4RWXf2748EV/Pvz5RX8XBQo3ZxdfNHzgT/9s+NQnPzFc+GcfGP7yb/5hcwXdxdCAZh0/6qM9eWcTvAqM9uH776THNnh7ibYLfEn9SMb3Ks3Ad6+2zMbKNQPf5XwiRNiuis4hd2fGEtMFBNxVcMUSYGth9VgXRcQin1Z8cRycFrt+o9BnvPLLiv/cgxSxqA4wlj9ZASLWqnFEkt97q1MP+vwD3GSYg/2TflkQChvS07ToXRYvjrXTUpOFLOtGbohQgJlJ10DeRUP7WFB0ieSb8rPaLMtPAfAMhWRmYVGZD0b/YgFLi1hulLgfkk7VWX7KM0XyLkvNkOAsLJCFZd0ZEtuM1lsu4/kqYlXKYtSnsoT0P4Mrh7opi7KxMC0KyXMLiX79TGvUkNCmJTOH2axm+3ZZBLzqSxxzLh7Fpigt2mODlJb19UL6+gpeyd+nNIvH0qhb4MSJjdTKW+eEVxdtE4C5hfFOZhUS9IXVeT6If8YJy1hW5LEBzMsjWMTiebnpcRFG3zeUi2XrTIeOA29/2Y+1H37Oa9ozvuse7W8+97H2vXf81+27f/p3FgX4v+99Tbvd/X66nXvaCWHV/cb2zSfeu33kby9pzznzbu3ZL39z+9g/fHYR9nB/Ma77+bMvj3dcMtXY798d7DsL8bGbr4PF2evvY1OeXiv2ejnn8s0cuLZxAO7hNWc36ErneLuQMoDFnQaQwb0OsGQxRxZuwMpibsHnsgSI4UaEHz1uVOIYbmWpQncmAWVICtNvorgFNkQEIgq4mMi5rkHcmwBORSEFTJcq/DqWO5CQMKZboDimSoAhXa4z3EzGbQY3IIBaSGErmXWf4ZA6XQbxOcgFhziIKyPuVwDpc8Lth/KjUODP2748LzdHgFJIiPN9qGHkYoSfblDhwzHUHfJ63gL9woornjoIi7jgCclu+qXE8yo3t0HcnHB/wsUIwCYfPBFOWgAuoAegxe40QSG3QQAnwiMAD+G5Dc4y4g4mpKXZviH9TJc8wrr1TDm4cQE61Q1xz4T3/KX6Q3z/cQfEvQ33RtpFmGXEDYurspUzVETSLQtXTiEpzzyV1+1hofOYfU599U38svgXD0NCli5r9AF9SDmEC2l48lNZ8Q1x7aRt9Cdl475GWMBbvfEypEgt1EYyLX3PAN8XANyGigsYPhq1s82BvlRum6TPlYwb1+Q906HhwCte8er26HAr9dM/fff2xvcO7fsf9/B29HWv2774v/+wnfkDP9L+/l++th35+Yvb/7n1Se2E29+y3fgGX9Uu+dvL2g2/Lm6r/MePti9c56sOTUHnXGYOfIVywBprDZpp5sDBOHBELMiOV7dEB/PjqyMCGBZwQBbARUAMB//AWagL5HfgjKQPQI4j83TCDjiMpbVV0NA5TZBA8hV6IAlm5SUfEmMgBIgJfcyUnIUuSF7bCsTxl1hAQnh+90j0+I9TjjhyzvfAO2DEVyWpm/TC20RK8QAvkrllxIEyQAjkCMuvXxGQG4Yb6eCZb0d58IspP2CL1DH0X9N3I/92pNihx5JgBwADkkKpO4Ep3oYRS/qNtBngyxEPgX4gG5+BsvLLCdzKg58+TU8Ca7IQDhAGgtWT30HlIrHk3088gF36+EvKbrPCRylflqGSsPi+SmJP+h/Hj1lfJwLqjLQBx9f4rB1IO0NHKiX36uK38Eh9LgjfhTZW6gEAryK81deUudoBsJW+9sfP0KdOX4l4r74ApzbAH3wBXkMNIgG0/qbt+ZPEV7yyUcDX2jzJ0yYp1GqSX9oRaXegOHSZs1/o39pN/9T3OO/GS20T6hRZPvXmB9QGgSTaBidUXtJn4ap6z+/Wc2Azfnzv984vtes994Htd9/0P9qbf/6p7aXvu2k7+n/+Rjv7HW9pL3/Kg9uvXXpSu/D3zm1fuuyL7VMf+s12p6f+r/aAr/61duLp/6H91Atf1t74Kz/Xfuc/Pqbd9Mlvbj9x2nHrC7MHnvAVW9dL74Hi7HgRQg0pfX7WfL/dDIxPghn+a/cChQpe+iHeC2XZjTIQHJ0Z/nrN9YiQItzDLbBEn6d5nF9j68fhILjBHB3qdeuyt4bxe0vw01OoseX6Zb4npDGvX5so1KZyrVt2wrTbdX3QWz/VzjvxhtcOP770XGMApM5kSAijz8w0c2D3OED3mLEfI7eQ4O5eRnPKu86B7ej4XvKh9w0X/R23W58f/vyDFw5/9RcfGr5wlUOVK77wT8Pf/t8wwrriM+Fp4MPDxX/9v4d3v+dPhk9+/O+GT3/u8l2v11YzGOv49unEpi7tM/pn4+9sD/YSBcBYcxXxdnV8+7oxzA2BRvoPnVp36EaP3S718Vd9x8cpo8BQFVxjT1BpxIY9DZ+nvE0wqGOXcKgpTse2nWVvOyGxMm5jaO07rzghUFuXD0MyvMCv3ST9KwRCCzuZPi92TFzbhZBoYc9U7xlu97ZF9ZyOLzzDZok9ydgGRDhrzlTfqDR26pNtSzkb2Kk02TeVPcFOpbmZdA65ju9uInkSxrCCTykvKdtMMwd2kwNunqGiEEZ3KU3fzbzmtPcuB259+zu1425BmvPV7d/c4Xbtm4+/fbvuVcpiR173a9utjrlxa0feMCQ4cWvUzW7R7vjt39a+Lj5v9DVHH9JKxcKwI/lRZwoPOHnSMU7QaY/boUhynAxNkVOirZDrgp20LFNhciqzrI5Un8J7S17LKm8nMWNSXidAbiybIlJdp4c9yTPAS54GOdFyCtinraxO8pzMUWHaDKmLm9io6/XkREme1J7GRAoaxtepmta/w3OSR9ffbpScwjkBm+JpqbGRso6pwju1dWpApbDCV1h8wbuNkNvQnJBSJ+vJGk+dzykbNTinfWPCe+pjTi593w1SXyeSrvwlve0Jf5wEuvGN2uBY5UKZnexRF+zJiZ+TVDeyUaEjGe5Je2p/qni7SdrIDXJ1AruVvIwHapb4pD85iXWi2mM09RnXcSt5TcWR90Zp13R8N1qArYRz9Bz+elONYSvx5zgzBzbDAYsc9RvXgm5nYthMnnPYazYHqFgxjDrUZNEBADZKVIiA2DHRtWes5ojZojgGsdTWqAoBqeo6JupsgJCFb7NEFQrQcUw6RQDE1OJJVYqKER146kQAEMAxVnOgVgUYUocbE0ATJzt5lWr/zuINUCPtGt5lUiWswoQbuFSHcmUqu4Axv4TDE0fhY36rJ5UMG2tgtogRMP1+dhfsFIr8ZkhsPhKnJ/YFrpQFIl3Vi/QJgJLawJjY3bzyla9MFa0x2Gd/o67UsNgT9EbH0tFOyqAPAB1Us4TtybXMbDum+MGWoSeqkerP+ByY7glPGTqjcZ+iflebJCpreFV2Mn0a2/3OJkd7UIuk4teTvuTKXYbK7InGIMxvKoj6tbFVpF8ZX+yA9NPeiFoYPHIlMPuQsuWpuP2ntgU89aONbjT6+PgbHobyWm19eUzaj4qdzdiY1Mcm0oaLKinQy2aHoSsj9rIpEo9NE2N/Tg+M4zEpA6HmVsjGMbxXLWzJVqVxjQS+qyo0v5s5MHNg5sBOcYBEhmHkZokun0m+4vaLXaX1Qz/0Q/V1zWcZjvYPAbp+wS9D4T6M73TIAdFwgTh+NfkbyCPhJHHqCWikn45I88YgkZ6r+gE24aZwneSRAWq4XUwgM5YC9vmMv8d1r5kvADSWJFvQPQ/3f5PABk/CnVoaHit7XOqRNgDjPCyOQIw/C3NP7AcIVujOhtvJxSsgUHpFAF/vWYVNB3CCSGOB/p6AXbYlJHfjd+KyPYhj8rQZAHbYGLBjwWObk3D7mZJE5QW6Q/0qk2cYqy0AH7wBGtgcAPzhZz7DkOQBw2xB4ig7nwHDCL/D5WZKHRnW9vSe97wn39cmQ5wCpJ4BOcAwsEdqCbD2UnCAXj8gAWcLUaSPMpBW3vJ2BLwWWGRbUZJRwBBgVHbCB2Rj10ug9VX1Q8oIaI+l54BbGUhnwNE/9hh0g9lixK1za+pRQdWPdJxhszFWPPS+/84uph+fB8KrjzZANixlsO63uhlb5RGJRNnvIqCRHY8+Yw5Qj3BhV6/z06kAuxD9jh0LO50p0q8YkNvgjEGnjaKNBd45tRiTZ9oSwDUWepIehwEM/vUFdRFGfzbG4l6ADK6vCGPDrE8/+9nP7pNJOx/zCZsWc0pP5k99vB+T/XugG9lYOi06GO2qcdvBMp/fzxyYOTBz4FByYDPGbaf+cRzdPe0u7eOf/ueUflqESOG48LNIW/wtBryEhD/rBVAjNTQBU8kCoIRjMEkaBQRaAEzwFvvw15xHpHhgkQc2gFHGjxYyIIZRJdAHPMmH8anFHkAjhQSaLLwWG+Uh9Qt91DSkIX1BADzgrA4WV+EBE4u5cloIgTmLH8kTMGYRZKijrowrnbKV5I5UlWQNOLUoMrpkTFtABTADboANpyQkxN4BY+Iqu0VMXsriD58qX+Vw5G3xxAPSXAsmQE/aBuA6ci5XhsLgHSDhhAa4sBgzGBLHQosH+AIkADnyBCJI1PAF77QT8ADAqQPplDxIRYGPMlxSF/xjuIyHyqZviOcdo0F1BsCBgRe84AWZlnYto1XxtClQ61hYefBKmbQJkFLgX70AHGnjq9++A9/Kp+7AFhCsr3gHwAHA3gO1pLGMokmMGYLJW9nUV96eh55sSuP0UWWJm02zjfCPVNAGCfC0odMnSECBEvG1pXbhOhOdE6BHG3sPjOknxg5jbWlTkwFYSAaVS3vpz9JhRA6EqieDNuCcgbG0lEUfYmCoP5JQ4r3+A3RpI96h9Gf56HOkscrPG44xVGTMANH6lD6JhLeJAZ6liZfe1zj2Wz8lnTVG8Fid6oRHHQFd41C/BOK1pbFog8AgGziWDr4oU/0mUSVB1yf0Vyp2cYFTlkvb2HgwiNfupP3mAnHj8qMMrz7CAee14cQDRnPGhDkIL/Cp0iUtZ2Rn86BM+oH6eV/SYxuxfeF1SJvZCJvXtI/yiMtzF76r+znR7sYF/jsp0N+BWacONgzyMN6UyZyh/+lPxggwrGzywxf9Ex+MJ33WRkm/Vl/1QvqEsVtzqff4+JAHPqC94DontBedcINrh3FbDLKZZg7MHJg5sGkObMa4Lbw6DLe9xc0W1xOfH7cWBujIi2lk7HIaFFKz/Kx/IZlYd6tjgKt87Ur1WIDy4hkPxsY4AYAqmbzlMo6TFwYnsaAMsRjn+1j48vbD0LNdhD9w4MDiel/fXSBUFIvOcO655y4u9YnFYnDxistwkDKF1KeCD7Fwr7kYJryVLN4FwFpz1bEX4ZFk8V5ela7vsbjnO1fPxjo1BADLy39cFhMgI/9i8V13sY9nARSyXLHoLdKXf4ClhXP7AD95AY4LecYU0rKBkR6Ko+LkpboWuWjGrYgBlvMq8ViQ61UaU/kdG5S8bnzx4qovrq1maOWW0QA149d5OyM+BmjOC236AAyapm6y68Ns5PtWL7AIfdLkYZ9HgI+8KTL0n1deRBJgLOuM72MKEDkESMzLiBii9STdAIP9oyFAY17tG64m1zz3w9hgbKWPyLMnfcnFWCjUVvpX+Z3RmLIEEMwLgipAAOa8zKl+azthxqRtArTlY3wJSec4yGAsBzCc7BuhIpQGbgEgB3n2FJuBxU+XIcWGdPHbF0Zm6qbvqPsyis3WulfGNX7gTxE+BFCtn/kZJxt54ZcfIUle8y42W3nRUwD9fM5gs24OVV/fXTwWG+402PNsGRkjLuDSlrEpXBesrjAP4LpmDBl3DONQSJRzLPqOH7Epyvz9RgHw11z8JZ+QzMebLx+em9uyVPO/mQMzB2YO7BEObBb4nnyXE9ZYaFtY3A9vwQrJVtYqpGl5215VERAWrqeQoOVPk3ZPFo2QcuQj15OHZGTxWlhXeBdNAY2Q0uTiK4yrsiuMxQDItIiGpG0IqcrgKnKLQhyX53XnFuBaXMQPqZmPIaTJQ0gQ83v9AxAviZsPUUhjFt/rvQWsACWADbQifAipV34PCc6aBdmiGBKzvBnN1cn42pP0LO5x3D95bXFcEpSLZUiwB1feTxFABXiEBGwA9oCYMQG2oRM6fpzXzmoTQL0HEn1AlvghPV7X3sJoWzy3YZmiaqupdxt9tlXgCxjYPI0J2FHm2riM3/utPfShKSBjs+X6ejyPo/Wp6GueAZ0hOZ30QqH/u8k0JMxr4vgBGIUqyBAnFUNICte9x3sb0JBIr7nZFM/dyln9M4w318X1oDY7xrK+E1LYdeFsesQHzMbEA5C8whhv3VgxXyDX1CtfqHHk7/oXpxsJFmvOqOcb/dTHjW3j0FgN/eEB0O1J/UNVJW/NneKBGxiNeWTz0Y8PY1qZQ9o76d2iz8cV6OaNkCL3jxffw3AveajP9HOm77VJInDo8xfZvBanD5mOsvSbfA/jlGr4mXPPWQp8Zx1fsvKZZg7MHJg5MOJAzJ95nOnotcgxHdUCx3E8CCA6p9QRioQXridHwo7u6zi13jmuc2ToaNTxoGNB+SIGL3Qbi/py1LNY3NJfdEhlshwVxvG240jHyI4P6ZdSTXBsSHXB0TKPDb4XOUKlQuEImzpAT44cA/zlI4Zhpc9aYagTOGKlm+dI0nF0EdUPx6aOUh3vFzlGpyfqaNzxM772hC+xaOYR9djoRzhHpXRWpTPWF6x0HDUHgM6yOVadSofaSekzVzyfwp8Z6ibapPzI9u99x1dHx+P29k7b4nkAHT/XUbXVuheH4AEVkCn/51QLqBvwTLCM6B7XEfQ4DK8KjtP1gbHh3Tis3/opdRiqHWNSDl4SAsSOX2U8Y0PblO/0PhDeM76jgkI1pAjP6ekaL47p5T9F+oT4+gs9aCoNY/LMPEAVY0ziU1MICWX2o/49NR598uLwLDL26yscL0LUirbqX1uZeYigSkVtiorLeN6hkiBvBoXG2ZioLnhnTjDu+/Ghr1PZ0QfU/2AUIHbS77J41HqoiNAD7seQ7/hLDcU4p/bQE3UtqkjmLyodpYJUYcxz73//B9oR11k7D9d7k+yW6Smv2jd84UuzX9MtM3COOHNg5sAh5cBmJL6nvOPy4aGn3ndD5SO1DQCWUot3hoRwM+S4Nxb/zURZE5ZkJgzl1jzrf4QuZ/8zJasl3R1LlcKwKP2Jkpj0RL2gpKoBBvtXi++el5Ro8fCqL45bpyj08aYeL56RvC1TCfCOFHcVlbSQ6sdWieRwr9JWJb57tT7jcpHqk9720sAKo++EHmn93NRngLYhQNsQm7JNxdtMYNLMqfZxgkD9JYz7UrJOYrkbZMyOx3GfTwDvPFEiuV5GpOPbIRLfrfrxVb7Q5V2jAjEuSxh6DtTBpujjH/3IEBdYDBd9dr2KxZXawQsYPH+ZOTBzYObAzIEpDvyPV5/fvnjM3dqD7n2L9hv/7dfb9Y+7YzvtpBMy6E/9hye333vTW9srf/0P26MfeVJ7w++8pn3iM19qd7nDse19H/yLdqPj7t4ees/bTSXb9l9lrT75cgMPGc5M+XqtqOMbJhmTMNaaIoYqcUSbRkX9e9bYpJcMtpa5VSL1JjGcIoYuU6Qsq4jk7HnPe95kEO/4v11FJEckToxqtkqk5jMdHg7EkXwahU1J3PnNDXWILRWMNJRUcCMSyy1lEJFIJHspZqXjJMeJC2mn8bZbZMyuon1hrMYoLEDj0mDlLWFpgF18YXwzwFzWRuYp/WOZd5ybfeMt2/CX0x55rj7D28UKzEnPHJg5MHPgmsyB//qUONL+/PHtr3/537cLPvzJ9l0PPL395jMe2P7uqkp98sI3taf93P9pn/zVp7bX/d4ftB/80ee02x57XHvF85/Q3nLJv7R9t/iGXa1+WThvJBOL8f9j707gbLuqOvHvDJgwi1EQac0DUVRmJEgEQhgCoQmCiooiEhAUG6eAggqYKIRRUHAAjP4TBHFqRcU2LSKJTK3djdKmFTVq+CuIiiKGQRnC6fVdYV12nXfurVv1qurVe++sz6fq3nvOPntYe+21f3vtfdZaBlCBgWX3HF9Y5R912XPr1GlVminwUOl3q8zK3+eq8vt08/e95YB+Ia9FPJMASusQULgMUK3z/Dpp1G3ZcRZeF/YDOZYydYyj6nY4ZR//AO9lus392BHI4xhV33U/Z+C7LqfmdDMHZg4csxz40z/9i3bHM+7e7nXmrdtV/xDutX7jwvamj5zRbvqet7Tv+vant3+85vrtX//q19sz/+5z2jn3uV07OVz7DMPx7aTrXr+d0MLdU5wtPBKJW6GenOtzbvZYJW6kWJBn2nsOcMfn3OwUuOXOjY9ZLuYOF3GXtsx66hzqLDdb75llZ7ArJ4uXfvFT1zf7PDK18Watmu/PHJg5MHNgBznwtAuf1171xG9s3/e8v29ff7u/aF/7hJ9uj3zMA9vfnHhae/FPPKvd7Dofbbe48yPa8+7/0fbkCy5qx3/i38Nv6R+3j33ko+12p9+v3enAKTtYm73JyjasYA9xBnlvCjwCShFAgg/RmT7FAYDOtvNuEasj/61enDw3XjYcW/n5OvaSoyAZXs7cTVLWVFu9KOdlPvVDYwDs5S2gfHwhB1SFAABAAElEQVQ9E8c/L5CJtBeeMurSEfXpBcQjCdjPwPeIEq+5sjMHZg7sJQdMuqJ5tc+7d/uZV72w/eaf//d23Ruf0d73kX9oT33cN7Rbn3LtW803v9sj2hWveVJ7/I/9fnteeGj4ozde1r7gC2/dfviVf9CedPa1jvH3ot4mVlGodoJ4Y2Dx9Wb61Jv1wpKKZhaupQ4qTj388RCxVRJudyo06lbz2en06uRt+2Vnfln81okatdP1Gudne3inZKDy1o/OpZKJMQlS4O1/QR7GBAytC+bwlyeFMZEjRwYEQXCO3Fv+PbEAl1cIZ9DXLa/PY93vyhlHhfOsoBO8Rzi3K2QxC29PPFfw6tJ7Uan7wLTw4Dw92Lofk8AfvDOsonh5czLi2qpnpu6R4SnSBxYWrOq+jynctmWkQZ5iBNUo4jGi0oebtbq8K5/ldWadzGfguw6X5jQzB2YOHJMccBZQhKhXXHJxe+7znt9Oug6VeXxYnU661hXT///OjDp03HHHx5nBE+LeCXkU4BnP+MH2d/ECzT3vdUa62jKpjcmLGatomQWFeyXbvlNkEvUil4lwHRLpiduzqZeEyk0UV0iiOY1JpCUTvol+TBYMXFsJrzsGAeO0498AlrKn+MPaNgXCKw8842Ks+LPsfKB6T724I39hf0UcG1v2AH1unLxoFQ75q8jFJ5dtttyFVh0/W4mAgGX3lvX3FP/w4AMf+MACVFT+8gCyWA+5nRuTNrDgjwGOl5xEQFtGXIcBNH1oa+WHv95c3Ah5axHUgxvtFKLZ3xT1LgDdF6rbWAufrpm8+EGWwkd1yhKL6hhgC4EsehniAowrrzGFP+cEluPr/W9jAThd1j9c9gHdXk7r+SAPrsnw0DEgIZd72RWxzMLAs15468k2vShpxiu3iNXmSiOfCMySoLMAJV7kYrwSxSdQ6iVXZS8bHyzOL37xi3PMdo/mV20WbVL7pwj4JjvcGOqPnkSj4xoP8PeyqYUyEMqtGheGFjTqRG9ZvDjfrK1TiwCuAUXhW9YH46NXfT3Imb4Pbxb95cnvM/CdZMt8cebAzIFjnQM14bJm8GjAd2RPvBsASCauMbF0UPomgwPx9jR/u4jvTH5EgRn5TZ1JBDJM/vzTIiDOW+gonOVn2FOWISBrTEBbBA5I/6bje+PfJlX+XIUDFaK2J2E/hf5FfHiOLbDKAHLCJVNOpkKv9mRrVx4RgGCDBajSTIE59/gcBSr47+RHdEzAhf6YmjSlVa5t7wjAkEADQBi/YKTdQB4ejkGCM6Re4uNbtD9LaiIGbnjIAH75Yu231YGviKKXvp2XbVkDPhYRQMqYgFGA/ZJLLtlwy+KCT9UeUEqgngD4O8PPcU/4Axxq2/gsNsDE1zIAZ2u+SFoLAX0VruPqcn4CYvhl4SZkM1koy5oQwhZap59+eoIzdQJcivQjuTFGlFlgjUVWe/0u8Ks/LQq8aMVnq4UFoIX0n/rWWU5pgKsiFudapDluoE69PJMFIJ1MTZFygVPn142FqV0K/e88qZfB9AeQXCSUcYFS15TfL7iANX2C1KOXfW1SpuMb+tPv3mKNT3gqzLE2C9MNnLpufOgfoFm7+YsmQ8bdmLz457rwyY7r0CM94S854E97Sq/we0x3qVu4LFw8qu36nSVYeG+yrRz9aozpdzoG0MUXdQS+jRehr4uMQ89akFn8jBdtwj3Ly/NjXSQP+ojfZ8ezpnYlqpz6PL6+7IdPwoQhmDtWSAam62U2P1z1xfTxanmrdaFEvCRxtBClYGDps75/TNalJI+Wtq7TDoBp2XbosucvvvjidCRuRb1qxWoykT9Q0vN6Wb6H4zolNSaW05/7uZ8bX97Xv3PCvfpDCwtHROjaYBEBeG3tmcx6CxBgG+GAE3hQ+LZvASVkK5bzeAADwLU1ClAV1QQTkZPSegFMCaTAegq0RFSnBLUCNtTLPvUsIG5yBHjGDt+lAeRMTkXaw8oGGADoPZhgNawABJzDA7g9ASbqcq973SvBXJ+vdGWBE7ACcOrJGVkuiKbkVzmCedAlY7dpAI7JvoBrn6fvLMXaCFyy5tqSFiDDhNuToxQArMlZO3sCWARvAFR6N2rqit/6Dt3ylrfcME7pOnzyPIskANKTuQvAAWLGFmHjnUVdfclNgSjPSO/4RLUHD5AxBiziE6trkSMO5fqrt9Ljm/yBHvMsoIC0C5+1mQ7iIqzANIBmAadPgBEEdAI06sYVHTnAC2ADaOsXJHQ/AAOQAL91/EIADGDQIk1fAm8WgHYq6Lbzzjsvwe7NbnazLNO1Ar0usAgC+EXGFECK1JfVk4USKDNm9DfeG69TOxsskcAZPlvAGbPVB1WGcXkgFrBFyim5Npff8Y53rFsJ6Mpq7aL+rT7Rjl6/mzvpi6KyDPutbwBc/KND6An9DXiaXyxESq+6b8eBNdV47ol+IkcXXHBB8iL86uYCrR9/MI26KT9CsR80Ni288DmiqW3Q48YxSz+yMIgQ4cln+k4QE8+wwpMLwJW1HBkD6ls4yNxgd0ja0iklo9Kz5gpmIhAQmcO3IvJDzpSp/fhbdao0488TghkXjC+u+/vSK17cHnDbJ7YTj7/OQY9QKEzdBESlCNe5oUysuggJBWJlZVBpMCVjNSJqyZlnnpnC6zyNlYRBG7Hgc2C4ZuA6a0V5WaVYQVCmBFFZVqI6CuMMVMr9tNNOy5U8U7hBZ5DpGEzzXX1s2VEOJjERYQxWeVptIZOPVaHO0hbCpqOswBy8F8nJAPK9H6jFHIKmU3UMxcWiY9VDECkRwmG1pE0mDlaHMelweeODdqo3H5n4hCfqy5KkHIoPkAKSKG0WCithvGG1mCL1sfI3EKzw1IsFhJCaWORhYFEi+gnfDUj1EHlK2crz57uFDEUmX8JO6VECrDZW/OouD6tGilE6fJ5q+1R9N7tmC46StA1kVU2ODMbdJP1P2ZYVYp2yRK+iXMkP4ELZT5F+M2QpEUpoWbqpZ/fqGiXlzFpPZIAlgYwcTnrHe97Y/v1jH2h3OfWcTavxyr+9pn3eO36nff2jvinHDPnxkg1ZN34BHBOucRvx7lNugQj6BeCjWyxy/ZHnxzzmManAgVIyqJ8pcluFJjR/dAIdCcABlixRAJpJDhCnf+RrfJoQWTeNNZOb8ST6GVBCNwKAQAydAizQaYA6cHXzm988J3fggp42LlhLPQ+wGN+u0Sf0lberfaqjT9Y4kyRLkfYBSfxu0s2ep9vpHnWhR+kKbQKwvTAHRBgfdBaQYQJnSWPRUm/toVdZE7WVJdhvkx/e0RmsU84X02cmXZOe8aOOgJxtVaCCLlQnQMiWN/1tjOo3sop/2kSP4TXZ1Q78xBs84MZNhC55aC8dRl/RjeoPUN7vfvdLa5S8WHfJurq7rz62rC0mTP7KMdfRy/rEfX2ib+hCfW1hQk/iza1udassT9muyUsabTHHAkKMMuaE4onxRlfQw+RHnfBBmkvCsuw5fVHygOfkhr4055JjCzS631yibCDX/KCP/NYXdU8/mOfJgcVGhDZe9Lt7LM4A2KMe9aicj/EGWAFkAB9YQF7Skkv6DY/M3/rbdWX6NP+Z67UVf4wl+blv7nRNn/h+Zsie+ugPfCIX0knPQmi+IXv6Un5wgcWXxQvrPR6Zcz2Hx8qXlux4Fj/Ico0FPAa8bf9boJqzjVXPWezCAf6MB/63LRpLrugY8yy5JSN2mtTVHxkwH8sHD/HL8QTyROa1xx/wTpbwhL4y9oF597QPOLUgxB/zCT7SDcazNMaDaxZzxj1Zob/oA23zR16l0T688FzV0ziB8fDDQg32wic6Uzr1p8P0MT7DaI5IwIH6Sxr9xSptnFm8kCmyRpbNebAXGTDulQNDwWLkk24Rse+Lbv357dIPXL+d/Tkntc846fiN+j46YNu0KnJbdIQT0Iu8Q6Et4r/HoMnrMRCG6OD8HlaNRYSPUEhDNH4QszoausgjOnQIhZu/AzAtrgfjF999CQU0hELZcC0G2OJ3CGFGAwlFmdeCUfkZnbtI40sI/OJ3CEnGvq4LYku7FiA1I4eIeR9CNoRCqiQHfcYkltFa6oZY5KHM82cMzvyMCTTjaodSrWQbPkN4FnyNgZj3QnCGGERDgPZFWm2LySt/x+SRdRPXPIRkwPdlJA57rJbyNl6LSIUCtGZsd30Sg2cI5ZxxwPG6KCwBWaYY4b4XiUcegjjEIBiqzvonhDwj8uBBDPJKPoSCWnwPxTSE0p6M3LNItMaXmPw2pNLXAUSGGJCTseD7xAE2hphQ81JM5ENYRYZQivnbJ1kMBZQy62KAn5QJ8cVDkQ2hbDOtyFexiMq/GOh5LSabISaWISbEISbyRXzyWIwNMRlkTPlQJMNzn/vcTF//pA/lkT/JnTEVE1rWjWwWxcSX/FRugM+8HEplCEWff6FIk79uBPBO+RVxyHgMIFTZrP0ZE98QinOIRVPyN7av8tkAD8kjsqgv8BEFQMo6a68xEBNLXt+tf4cauQ3P8TImpxwTVc+wiA0BnPKnsWI8rkvGNB0kQhm+FZGNAJT1c/JTXxqzsd05GGc9xQSTei4A6BAAM3WA+wFoFvIblrDFIzF55/dY3C5kpW4GiBroJhTgeJjSTyWjolIZ70XGfZxtzLrE5FqXh7Bm5biSnuyWrFSCAJ55zVzSPxdAYogF9RBWwkwaIHUIQDsESKlHF5/kPF4MGsIIMsQiIfVtTOiL+3G+Oecd4yQW3UMsEhb3wqAy4CHSdnqvJ7oxQG5GFgtg1t8azAc13sxnsfDecJ+upvO0LYwBG+6pU0zgB0Wl084wcAxhIFqkl7ao9EH99hngaIjw04t21L0AHEMAzvq54dO85z59RL7GZF6oeXt8jxxqe4DW1Cf9fXIeILu/tPgei4PF9/oSi5MhwNAQgKYuLT7xIsDXEAaGIQDS4vpmXwJE51gzPs2HAd4mHyEzsUjLfgsQm3p4nJB+JlfkeEzKIadhDBvfSrlwL4BsRklUj57wfCrPPs2q73CFupt3yKj5aExkxXgQRa6fbysduaIb6LQwsqSc1j2fseA66Fp/v74bo/JYRvgfu1pDPyalDXCd5foeOxGJHXwvwtcA6/kT/+innuCLiy96+fDg33vfZOS2TyHT/qk1v28F+KpITaQAcaD1hfJVXBxlGGKbaIjVyBDbOjmpx3bfQnmMq0T5UlaAi0mnJ0AEGOhJeQTAJGHyRbG6zE8TA6LwiwhGrOjq5xBWgBzQdcHgjlVXKq+a1E3aQNoyipXhhjykE+YUmUxjRZN/eWHFP+ATAVsotijzE7AymCi6WAktgC9wGpaL5DklvIpidTfEinegdDxTeZtUwoqVoFt7EfBmUIwpVntDWFoXl2PFlpOS0IV4HRagweIjLOuZJiweuYioB/qBSDmHha1ubfuTXPUUFvtBWxF+rQIqlDXFHOftcsKPrcXFwgowAQLILJCOyJmJOFbTOYBds9gATCg1z4QlY4MsjJV7WF0WE7lnwyIsmwX1wNdFE2lYE/I+4IrCwjOENWAIa0IqbnwVUhagMiH6jFV6ghLpLeJi+zGv6SuT2HbIpDcmMmMiRWH1yQnL91jRJ08oOuMjLBEu7xodKvCtitFh6lxkHNAxeD0FwCrd1Cd5oLh7QDOVbtk1/U42l02WwJV+LdIXtXDrQxYbz0BPWLIPAnlk3D16byoMq7wBOXWw6DYxFik/dvRyIVQLnron1LJJ1iRWuqbuAZX4DHQCzz3RzxajFk7GgnpNkfzpcWnCajQJkgDU4kMPbtXb2GMs8Dyw0hNwD4Cba8jumMLKlkAbSAur/vh2hoCmh8bAR0JjcUx4V7q/7i3ri7rvs/Rsf833MoyMr2/2G5BhNBjzw3P6KaxxCVZq0bBZfsvu05XmxKkw2PrGYkhZ+mddMj5jKz+xQ5zB32BwGedhcbuKgF71myL6G49iR+ig2+TdGIvz0rsWsphup0/gnWWk/4whBsUx0RHmkRp/4/vr/mYAM5dsh8wj6kif6O+eCp/5tKgvLFdppD/nQQ8czrnsMIcstt3jYDyyBWCLJgZ8bsPZXmPGtvVkm8jWQSiV3BaypTZFthLPj4POzrsw+W9G8rb9ZlvAtglSZk9M/MvINgNTflGAmzTV+x1CklsPthNWUQCsbHOlsWUQCjV/2poJhZJbA3V/2Wd/nkiaOs+Hd7a3bA/Y0gkhyCxsMdjmsiVhmyCUU/bBVP4hSHn8wNGAmHAWeXvO9qc8bPvY+rP9YUtsTNqpLkW2TPBP3mHZyi1V2ye23KbIdk+RIzD9Wbu6fqiftpZs+SB1sl1im2+K1NM2sC1oWz/abovOVo8zY44d2FbSfwivbBO6FpNe9oetWu2vl5xsVdZ48EwMcB8LiklucYzBc5uRPrG9hfQLcsxEXdQd2Va2teUsom1Z22UBaPK6LWjbR85GuW67zLZzWGLz2a38C6WTW3fa35NjLYjMB6jO78al/tVGf7YP9zsZV/qVDiqyVYeH+tT53K0QmbIduF3Sp7Yu9fUUOXfqqEmRoxq2NsdEjm0704+2ZHuyhejIAh3oDOUUOSP8zjha4agAHV+kfPyxhUlOeyILxhce2LrviU6MXYDUMeS1J221VerspvOvpUf7NL6TKUcDbLHbMrWtOiZnTUtX2v4vUh/j21ERxxHG9SPPjgLQk9KMyXEK9TbejPcxqZe+6PVdpXEsZkx4N9b94zRTv5fpWUdAtkMHQl/ahh/zQ170PL2hXf342E45trHN8Y4DjYlM8ZAQi448/jO+v+w3Xtv6p1/x0zheRnDJKqrjQlNpHEk499xzJ+WCTDvCQD+Ty90gMjc+dz8uR/85mjKee6QzzwdoTiwGTxwOMkc7++14qv7uyfg39sxp5o8xlpP+l3/pl9vX/O+N82rlsVHT1NUd/AQKASbKsN5SpozCypHnhGJ7LEvzAgcwrMMQBevMhpfaKBbPOCMKFKPqLArHwCDIKFY6+b0+XcNAipWicjbJgCqSD6WnPkXKMiBixZl/rqun8yjSesZZM4yXRlpggeJfNvnIw+RG4J0TQs5wOdeC1F8+zsesQ+oAYPRU17Sv6um+6/jhTIzFhgG3jLSH0JhInR9yxgkBKHhkgjG58Suo7gRTfsoggCYi/RSrtHzOmSJ8c5ZJffGH8olVb57fkwi/3aPEvBRQAMk9ky0A1QNp17dC6q1+Nbl5tsqs7yU/U/k666W+zuGaCPEIOYtFRikGZ7LqurwARrx2dgyoBiq1zxlycuOsZliZMx9t92eBop7I2TaKxzUTSU2O6o1KRiu9suue79pKJp1ztwgid/rOgs2Cy5gEGIwvL1gh5ZmwwnqWL7AA9kUUJEWvnpuRc1rO62s3paU8zxV/1Jk8IXKGv8C5ceyc834nMjw1qVuAviDOoT7oQdd6Y9jLdqzSO+N6SDsFWqQzpp35HC9ayAWZ7Rdr43wBZ7IK/IwJyJhaWAI2eLmsPhabsVs4zi5/A450FJBRi75xQuOA3mP0mAK9lX6Kf+pEJp0fnHLZRs/ih7OIU/UH/o0tdTO/jQnIrnE9vjeV3zjN4fzdz6HjeujnqfExTrfOb/3X6+3+GedmY6e0v7T2d3OcPu8XOms//MmEnh8DssqDLvDOz5RcMQx5j8iZ2an7lcdefBrnQO4Uqd/hAr3q470lfKp5bVxH88wlYUBbJgPXvWEA9mttf+NH4/oh0KqjDsznzuDYwo+VT57vUhTTunOetin82YZHvttit03unFtMjnncISbI3CJ21reOHrgf4Gix/essinONzgUHmMxtPMcZ6swak70y1SVeusvy/HOuxHlN9zwXwDPvxUop68OEHmB1cZbS1ofztM5cOvcTYCzT2UJ2TMIZyakzPYsC44ttGeltgTiLg5xhsfWIB3VuJW8s+YcnAazyGW0KoJV19F1bbEva2sdrZWiHLW/5a+eqLRx9gHfKQM4s2ypTXuUhnzrDa6s8VrB5rvOCOHpS5ByYbWt1qm0IddJO2zwoAGDmY8vJuc+YZA7aMrTNWf1YeW/l0zks9VWu4zG1pakutV3n3vgowbiMAHDZ347rVNttm4X1K3mq7/HHdq3+jQGZWZB9bbPtZ7uT7JC5AAh539aqPjEOPFcy7iZZktZREf2CbJ+SyRpDzkeTaWXjo3Pk+o8MI1u1zvEqVxuQbSznil03jsgLsl0c1qG8HlaRDcc/yJCjNOuQs3zGvvyd+UV4oH3GDFnSZsdLbMlpi6Mfylb/3aTtHnW49NU/Njzlh543vPo33zT8xI+/ZHjKd37r8Ot//MnzyJ949/DU7zhveMFzLhj+8p8+NLzwWc8YXvSyVwxXve3S4WnPfO7wc6+5bDebdEh513g4pEx2+eGtHh3pq2Mr3FxyKDQ+XjDOKybm8aU9+73OUYc9q8wuFOScdX+kaBeKOKxZOo5QR9QOa0V2qfBDOeqgSlNHhLZS1T0/47uVys1pZw7MHNjfHIjV//6u4Jq12y7wfd4T47zYd71g+IMr/yVLus/d7z286+PDtWfPPv5/htPO+LbhH//qlcMP/PL/Hc44897DK379jcPfv+H5w8O+88LhzW+/cs3a7X2yIwH4HgpXdgL4Hkr5u/3sDHx3m8O7m/8MfHeXv8uA764fdTjYxjxfmTkwc+BI44Bz4ccyXXPNx9qt7nzvdtvPvXH744u+td3qKx7XbnHN1eln8yMfvqYd94E/b9/81U9t3/ifb9s+csJN2sMeeq92vU98tH3Bl57R7vKFB29zH8u8nNs+c2DmwMyBw8mBGfgeTu7PZc8cOEI44LzXsUy3vdv92+lf/Dnt+ide0375jz7SnvotEab3026UZ0xPusFntbO+8hvab77h0vbjF7yk3f/0L2kXX/Tz7V9vfMd211vfPM5Nn3wss25u+8yBmQMzB/YVBza+KrevqjZXZubAzIGZA/uDA1/xmO9fVOQ5L71k8T2/HPef2rOe8bj8+lMv2Og14EBc9WLpTr3sk4Ucwf+8aBrn3dMh/RHcjLnqh4EDsSmeL8oKKrKfyYuUXk72Qv1WiEcmHlqWvWy2Tl5eJPZC2uF6ac5Ly17Y3O8vZ84W33WkaZ+m4cptppkDMwf2jgM8Upig1iUuvHj28NxekzJXeStRn6kJkgcObu0A1J0mnkYiUMUhZcud4DLirYQHBd6EtkL6SYSwzYinEq459wst8yqwX+q3k/Xwdj8vMJd/0hXiTua91bzIyzLibWQMenlsAtxXkXaVN6RV6abucRnK8xHvPTwBLSNefnaLeM8C3IHfnSa828l8dw34Cud5qIOS2y/+D5e5s9lp5q6bHx+n3IAsm1T4Ro238NNNE5998RZ7uooSmpRLN+66XPdZSlyIw3gbP0OGcn21DnE7tV0yMfBNyS3NVhQ5xW/y4qprpoM5wGWXcI6sfOuSkNuH6wwtmQR+NlPK67ZlWTqTlrCpXBD1pN38KfPZuhmZGPim5Douov2kP1n+kfeShNQWdntdisASGdZzGVie4rtrLDeodAyXgVwH9lT3+mu+m/iEYg0vKxvcNI7T8Sndu3Gs+1wI8pHbu7NzT70AS8Tfb7yxnd/9Mylddtll6S7Pb/5r48U5X5OqnfQHl2f1u+73n0A3N2bjupEhLhO5hRRGd0zcBUakqnSBxGfvFPGty13bmLj8A/jxbRkpnytCbv/CY04uDsZpw4tKhldex+3f+Nnxb/0I6I37QTpuPM0fU2AgvLwk+C9XmVP5livF8b3x73JBOL6ub8a+i7miFFq2ZHf8zDq/f+mXfmmp+ypzZHjYaBHcY2VWAOAyo9CqBSheagO3d/p6iriD5BKV676eAE8uT4Ve5gJP3/TEjWV4F5p0B2ks6DN4hy/wsUvHqrOF6LhcZbhvLudCjStBfBqTMoDqKdnv0/I/v1VSPteedDlrb9Vfmf6Kl8YG/dnrjSqLXuAWEFX6ume80UfG/hRFQJKl96bSu3bishuHeh3yN5kRlIjilcqqzgn6zUE6v6KcaJdZHGMor3DhlD4jBQko59v8jb4z/Me6x0E/ITXpSWOg8enGz6QJgm9HA0Sce/HcdYZBqkyO2AFRAzrCHaYDZAKF6ZS1VYvOp3AEfXAN0xGwKH+/xYxeRp4NF1k5QPgvtjqkcJUnyAXfcwaP+hAWHc0RcymjVXkrU/pLL700fcP2deCXFT8F/wj3VtnWSm/SpEjDjVryHb+sTPmnJZxFwLQ8EOfaQIm0CF8IubYU4aO89Qe+l69O7bJA4JdZH4Vbs3pk8tNg8Qzwb9LjHxfhGZngTJxC0q/Kotz0lf4pn5LkSj/rH+AT6S++hNUNyCOTvgN72qrvtfdAOGUnX3wxh3utlC3lyF9aPqa1n4zxC2rynSKyZrFGprVD2nI6b9Wv3/AbCMQb7WABo7BsceG1RZU0+K9OZL7ymCrTNUAb8FBnSle5lCm+ApvGj8ADZYkga2Re0JYCvj6nSFpjAdCycFNvfWLRZgvfGCfnq8ArfuC3mPY98XVqHJf/7v7e+Hu4QMu2kXP58Q9NXhCZJw/aYIyT852gD3/4Q+nHVV7kC+DSvxGZKWWDzOo3/c7XrbGJx/qCg30+O/WJcVZ6RF76twInkDH6wDWASb8JOOHPGNK2iECWZeBXTex4YOxFJMHkPX+x+sXEQoZcV67JGD/whzFCHckIYFxjl/xXvfSjMUFeBSrgJ5c8GT9AGNmno/i01m/yE2hIu4FddbWY5svZfRNxuKBMvuGJvOgEzxhPdIq/cHeXwAMwBsojZHHWU1uMcX5R6ReLCX/GpOuexQu8ol/JO3CEb+QBKMFbY4ls2Apm3aVz5QHM0wnaAXQbE2RevxmDeEeH0yP+wkVhY9ihK4xxeSqf73mA2Lyj7cZsAUf1ABZZ3PDXHBYuMLP+ylO2OmoLkp/xCUTpI3UAKqWRF6DBpz0dHtFLs1/5pMUr7abDyAJ9qb3k07P0AR/s5qhwf5htdK/GThYe//hdJu/0lH7S32Sz+gJf6ATp6B511DdAiv5XvvZrh3Fh7uELnJwLjkRv4BdMIF/GLYtZskGO/akXnVP9x0BgUUY2y7Jf9a1P/NOnxqn+Ie/FM6Da2IEp9AE+hqvN7FP9oe7GsrHheW3wpw7kgb5TrjaQTToVb40Tc7r2GW8MV/Liw1xZZFT71J98uK7N6masGysMSWQQf40z8y7eeJahCWAlU/zk6zvyoF3+yKxrxoy8lEG+a2GMj8Yd0mYgHD4pgE9/608BmNw3B3mmJ9f1l/o5aiLvktlf+IVfyPaTQ/JIrxlbgkoYH3AdntAN4h8Yo3hGn5OPii2AJ/xlkyVyhXzqI4GN8EPb/KkjPKZPi8+Avf7SLmPtBidHG467Frv0bcnvwbht0yo/vlHwEMwbQkgy7HAwLEOhKozvU/5ZxTcXpxlFhdPPKp+xMSgGYWyRUJChLNK377nhEzUGWV6PCSCvhdKA2jKEbDAzfQbzORoMzDCusZLIcJ58iPK1y1eofGKAZLjjAErpT5QPVP70QgGkX9oQpPSv67MoGJ++X7VJmdFRdeugT/5Vo1PSj2lEN8uQzBKFwOZ34UFDKWZoUDG1YxAdlMeyC+rOP14sLjYk4cs4lF+Gzw3ByHshnMOpESZY7G7+YEOAN/gKxscQ/EU+/PbKW/8Jayu8I+L31h8+xQS3CLMZSn8QWtozylY3pJ36Q3jf8kGbNyb+4VMokPRbGwM9eSxZKIJByFFhSfGcv9lQFMl7IXpjMC18y4YSTl+wAXTTpzNeIH1K9mIwpEzxT4v4F+aTV9/EAB0uu+yyRd7u8zUcCjv9T/Mtq++1R9hWPFpFYqAL9ywU6oEDBxa+eUOZD2LAi+OOhyicdGfaAEjp9/hlL3tZXlemPuNzWR4xaef1Zf9e9apXDXxeBrhMXkkXC8JB/+Cje7Hlno/zHYwn2hIgIflZ/TaVP15zm2Rs8oWM5GEMhPUzw3+SjXUoAPJByYyjmHAOuj6+YLyQ31ispO9q/PQsnRDWjqxfTIyLMODj5/3eqjuzh5x13yyLXiCHochTR8QEN8QEnv6f8fHREaJayOqYELJ/3cej8mEdID2fkw8KsLvQZTExZN8LvU6m9Yl20VeeQ9oeQCZ1Jn0RoCiv+0fm9QUeBPhIP80B2hb36VDjhwzhDx/PZF8ZEWwmxyjZ9oeX2qCeygwQNYSVJsMw06FFnvXHb7Ux5rsyPUsvxYI1k/LnLFQ1HaFs+UonjGmAhSEWk/lsALT0N175SxdgI3UZOY6FYc4DrvtDwjBfHD7QA8ykjinf1e6TZ76iPacMeZlT1NO9ADHD+eefP9CTAWqzrZ6jR4Q2jsk4rwfAyZC53E7py+KNtAEMB32BT/jQhxmmz/nW5q87wGaGXRXS2XxHpxmXAeCST7EIyHT6VP7yC/CTPq3Vt9oa4CfLxD/jTjplap/8EHmp0ODu08PSKlv4dzrF3Munt/aHESN5iCfSa5c/Mnl5hCw3f9Ad6i3vWPhk/uZwPtzlQzecGb7c/S65c58ONM+pg3LpKKSf6Fb1CoCYOlbeeK69rtFV+owfcP2j/kjd1CnAYPZjX+cA10OAv8wjwHLOVeYMacgoHYWvxpl8EJ7Kn44sH/rSI31rbjB2+HzHL/2jfBQgPcOvm+vli/CxeKAOAW4XIb6VaTyZQ41lYerhC3NQP3781lfm1ABzyQ8yhJStPG4I6Rc+6I1vJH91D+CYYYh9l685h8z5Lo12GI+xC5V/5p4qn17Cf23wvD/P0G3moVjMJH6qMa/P+JYvkh4FGB7Itf5TX/NxlW8chXU884XPyBS+KcdYD/Ccukh6OlDfV9vwxbiBTfh+JzfSFMGK9DF9+EW3/vzhIZe9f7jy6vA7OSIrhm3TZsBX4SqMDE6VRrEFk4MCYwBUE1msuPKef0BXxXcW8xrD+3jdYSHKzqsHCGcR0KGjewJ6eoqVSf4U2KKCOYh1rzMRgS+A/eiY0FBYR4bYZsjv/plgqpMXF7svAJ9JRZsJWJG6GCQUjs5GFIFBjihnZRG0zchg7YkwU1gIjynxWGnmAqDShYUqJ5D6PQa+BpoBhwwAYIfy194ibTJRSQd8eMYfBUdoEaUAZMbWY9ahnp36JMDFi7CIDrGlkc9QGvKlqAQtKXAVOwWLbAxUBHRbSEkrGAXZMyEiCymAuYiCBlqK9LXBRKkAVkWeo0wNRvmFFSDbA5SuIhNF9YN0sarNwU9pFK/wrZS5tgEvPcVqNoGAdgGFlMcqCmtXAiYAPSyLi6Q90CzQSvFSWKgAbPF/8WD3JawF2f/yxgc8QXhVPAYwakLoHj3oa1+fuknBjYEvRWns+cMfCxHjTflApTFOf3gW0SEmB/24irYCfB/41o8P1zu+5aJHnpRsT2F5zonMZOjPItHC2hj2uyfjxQRBdyFAoOe576VPjLeiPo1r2lltrjQ+yXBsleZY7a/Xdzrt3ve+d04KAFuVZQLdjOgmxoJ1iXwYY4hMAORl4OjzCEvwQlYFqalnKg0e4iU9o91jMmkCD4A2sDAlf8AVEA68jImOHZcpzZjn4+f638a0sWweG5M5wALbvAE49TzUtjI46G8A+fwAJALWAAL+xmQevCwW6HSkcYuATn1J3+CzhROdW3TVVVclj4BY/JZW2dqoT/CMXqMzer1GRxSAA6zIj7nAOOzTFc/rs8olA2RSG8fyqg70Ri3ktMeCv3SJ+tG55kh6D4Ds515lAKkAaxkEtAfQLtwAd5h/jUkYohYKnvXb+KOzzHFFyu1JnvKBR/C7xkyl8dvcXn1R1/tPi2X178m8QofpMwtDi7AxyRs4tKAg52OCV8xhU/LrmnbBQoC2OaSCFMkH8MRzckum6IMi94wX440cCQBFThim6AE80VcwAEzmHv5MkYW0ucPcNMZk6qcsOruAe+VhXAK20lhY9UTO9H1ETFz0fX/fd3JE3777b985LPPju2tHHWKCSjN2maxjEKUZPcBZmsiDsflp65O5uz9nasvMtgmKhuaZrQAMeYbF9omXF+p8UbTzoDNF0aH5bP2LgVdf85OJHNmCqXu2R2zXIvWxDYHK5B+dm+nzYvyLQZLp6vfUZyiiDHMbHZHblsL/qq8wl84p2v6w1eFYAr6EFSa3IHyfitU+LiOAx/hSbkO4aEsihDTrb0umKAb7QS9+VB9JYwsoFFYmD6WZ2wbaasulKJRabkHoG9uKIaTJj1COLQZSJrN9bVtP+xxT8H0Z2V4KQc0tVVsutlIQXoUiz3ao16mnnprX+7pU3bXV8Qjt03cxMLMt+UD8szVSJC/9WaQ9+hw/lVkUSi+vkV08dAYrlFxu1S07s+lZecmzSL7qZzvKNiB+kudqj/R9uZ7T7lgA5VnxAMiLMNeVZ/8ZCia3jUJB5vaSrbqikl+/S176thcv6149V5/qrR76D18rfeWn7qi/nheW/Jsqp8Za/wiZCeWfl/DGthnyfJ1Ts61WZFtTSGlb0LaBbbsdKpHvO93pDu0x3/YduTXnqIYznkXCcPdkC9c2XgCE/nJ+D4tcykAszHKr1hGI4p0EvtfvAGmL5+taXaixUb/r05ECf7aKp4hOoeOUu1Wiiy+++OK1H6NX/SF9ZyvSFuaYbJ/b7gwLTQuAk1uZfRpjm07Wz46XjMkxCWc5Y6JPnTElW+phW9c5wDGNj93U/THP6/rUJ3nQDturY9Iuf4hODcCzSKJtNU/pb1vAdIu2ILpiTGQ8rKZ5OcDM4raxZ2s5wMVBR8roY1vMUyQkLPKcMPOOj9DDjsjguzkEOaYif0ctxlQ8r8+6X/1PJsekvv7MHcoeE944QhCGjNTjtrNt3fekT/3RzQGQUp97r8Y4Q/Seo10BqlIXF9/cI4v+AjTn9r5rqOaSa39dOybl0+vQuudTG5Ydeat0U3qILi1ZgA0Kg9QzlTe573Vcf598kLswRvSX87trtvz1PX1DrnqiS8NAkEdVyFE/N7rn+BhZCGNlYhT3wyi4wGSOsSK6yBxpPp0ibcQ7R7zGRx3l4Qy6Yz7jMOjGJflx5Ek9eyJn2ubYyTJSHzgx6colL+iGYto2rbL4QtxRcIZPZelgnWHFYoUUPpVVzFaUFbNVodUwy44VWjA+VypWjLXloZIxQebxAd+lDwCclqgQQJcGxxasgqxOy3zu+iWxpaYsKxn3Q5hczq1LxyLUhTXL1pmVlvJZc6wchF0VfhdJw2LHyqhttoymyGrJVk+cRRkC4KbVgnXZSpkl1MreddtAVi/Ksfq0Qo0zRFnXqXzrmm001kLWWm2zMkJW7qylKMBPbmf6ru3CA8fklas81j6WYDyykrOatg1lNWUFZvvFqs6K0DY3YomI8165Na8vy6qgL4WyteXGIssCIZ9QImmpcYzBcZRVxAodk1iGFmbFZuVBeMaSYtXIAuFYgPrFoEjrltV2gMf8zqLBoukYAXkrq6c2x2DJviVbRSxMeKJvbfWUxZX1nXwoKybA3AW4LKws1R51YTlbRqwGZU1QD3x70pOelMnxgWXHStx1xxKQlbO26g/boywEZNJ4wFvWKrxfRbZnyZTxwjqvrSwFZMS4MMbw2K6G76wAQiKzSJFlW7VTFMA35UGdWfDxkszK23OsFTGBpBzpm2VEJlgPtIXMltWI1YbVQF76apX1hDVHOtY9VopQcGk1YlFynQyTw9oFmKrLViy+Z735o8NDH3j/zMbWKj4eKhnfrED7hdax+O52XWunbTfKYQElw0cr0bc7RdUPdKDxuh+IbjD2pogeoasdkzRn071HGjlCU3zf6bqzqE5ZhHe6nFX52a0pK3yfzhxE99eRxP6e73YbzCuHSsssvlbk26ZVwLfPVAN7sn0wZb4HOsfbAv1zU98ptVjZTN3acM1AZu4fDw5l2lZZl66KraPdIpN+nffZ6TK0cd1BAEhMpSWsU9sa8rZt1ZM+Bq4tdrZCFhxxWH/xiAHQb/0ubiz5Anwpex2Sd1jBDko6llcypm+0fyvtkc94ArEdHbsbB5VJLuu4S920IFq3LZ6ZakvlNfW5lbGmL48G2i7wPVqh034AvrspVzPw3U3u7n7eDACbzc/05JFKuwl89wNPlgHfvarbMuB7YlhKdp16U7rCmL9tU43J1sHUdso4nd+2NMMKmFsctsk2IyZyTqXHpEx/65Ltg90i2w5hCdyV7G0drUu2nqe2UGprbpyPvMf56+OwDI+TLv3tmMRl8Sa8IwJhEVuks93Wb/0ubiz5spWtXHmHRfSgnMbyautT3/jbCo3z8eyyrWjbbHW8p8pYtoVU98efU20Zp+l/rzvWPLOVvuzLOFq+/+h5D2l/ePLZ7bFnn9bOe9aPty+/yXvbl5/3yvbNp4ce+8Sftrvc8TvauQ8/0K5/v6e31/zwE9ojvuvp7fTj/7D94O+f2B73Ffdt9/nyT269HS0Mmdsxc2CfcGCrenKfVHuuxmHkwJ4A391onzMjsT19EFjYjbLmPHefA1zBhIV0g8un3S91LmHmwHocuCbOZf/re/+hnXjjONf2F3/Wrgh3xF97w2vCvdBr2tn3O7V94riT2k1v9Z/aCSdfr139Hx9q7/vnq9t1Tw0XV+/9x/aR4651zbNeSXOqmQMzB2YOzBzYTQ5c+2bKbpawi3mPLWS7WNSc9S5zgJXZIfiZZg7sRw587CMfbnd9yDe3e35eOLa/x9e3J5/zxe2nX39l+Py8T7ve9U9oJ93wBu1PXvPa9rFrPto+dMJntm949Dnt0z7yoXa3h3xTO/v0a18G2Y/tmuu0dQ7EcbStPzQ/MXPgGOcAn+dTL/IdDrYcsRbfw8GsucyZAzMHjk0OnPt9L20fv/HN2smfcXK79Kn/2t79kQe0//pld2jHJTtOahe9/NntDl90i/bmt1zRfuZFT29/8sa3tC897fHt20+a9rJwbHJxa63mrcSb4Y6p7ReKF6ryqF68VLvwNLJu3XgpWeYhYN085nQzB1ZxgIwxIm3FM8mq/Na5F2esM+hGvNQ9mdxRUt4p4rxvs2jcytHSyQxHF3mtWObtZpR08fOwWHxF1eL6p3dhtqhR94ULKW5H4gWh7urOfNVZ8QZ8Rs85lBxFsgovCYeSxfzsJzngjGq5UnMp/PllBDbudQ6VwsfwoWax68+Hp4y13NjtekXmAhYcqAnkFrf6knbqKVx0Hdduc6fT230/CXqdSf+N33hdu8PtviDiYF6v3fPeXxbn9E9r9z3jHu3Trvvp7dU/85OTLpsWBcxflnKAm8Stgt54GTRdn3FzxroUL3AeBALCs9DSMlfdCC8+GUnS3MWN2Vjvi6zl+jLiUs3cxz3h0UbxslK6fBy3iwvIeDt/fHlXf8fLyBlhbTcKiReQ083WbuR9qHly8Roeo5biKq5CuRbk4o31dTsU3nTSRWH/rHdluMbjdk6kQS7miujP8NSUbhRFcDTH9QSHicoG68UL3v2ttb5z0eh9JK5jwztGut77lOtUzn6m6bAAXyEV+XFzpnMV8cXmpZ+afFal3eo9fuLUYSuDkr9AZ1F74h9zu0LU57OV76wNjgVQvHwae2HKSu9IIP4hwzvCZFX5OebTtyjc6mT4TWEa16GxP8D+mXg7uP+5L7/z48yitBsLvX3Z4H1eKbrnd3/3dY0lI1zSLcKn99XmlzkiB2XY0P66716+/dIvvWuG8gXA9oo+pfj3qsTl5YzbbaIaT3B8x8ab+xsyERqWT1ZhWMcU3nkWvsh7n9TSyUd/uc6vs7C/fMYX0SkAtbDXPQFLFt0W2UKmmqR7MpnzBcufLKstv7d9voAf4KFsIaJ7co+PWWWa+/iZ3gqxfC8j1j1gvyc+TrV7TIC7OYOPcDzcDvVtrufDbVaLYAsJqFjfegpXmWlgEtZ2L0g/XX755e2CCy5Y6NHw9JMvwwNoY3kc10lfkYUpwmdzlJeC+YxfRvg8lvFlabd6Xf3wetzn4XUnfVrzIx5uMSezJb/wTriNzMXhVutoTIZL2PQ/7QV0mEN9ItBIyhO8xg91eL5alE+HWgzWi+HhEjNDnVcCmIo/5nDDusH3fd33qZxlfcLXsPFK3skY38A1hn8rFqLLsOOuAl9BGnhBYG0bOxzu38Rk+QVaOH4PX7AZS7oaKh2vDbxAaGCReNAEUPCHzSzHBp9481YXnPuXc2MKjJDKuxQsSwEvAjqLwuEl4Mwzz2zhiy4dPosHT7GV5wGKJ3ySpjNuzqKRWNicLAvEYZVvRWI1tFOkg+XHaTqeaJ/J10RhxYUo2vBnmoLK2TXrKWfbETFmUY3wI5yOoiMUabbVDcEBOLA2cXiB0GqNBw3Osq3WTAj4Y9Fg8FGkgkbwYFDKLXypNk6oxdTGv5qI8c4AVXeDrwAwoKf/rVbXOQMkXjsPE6ztlC4SXIDS4xDdX02IgjqEr+H29Kc/PdPVP4E1eNDgsFusc8RBvLZxOi9/K+RlpJ5kL6IAZVu1l3UDRajibDeZV7Y/CiIi9uV4sDqlRIr0yd3vfveM5c7CZbDqq/AxnP3CEg4QI7wiW5Q4Txg1ySpbOWQuIoxlWv/0iTb5C1/Ai+tTXygYTt8tPoADZAwYwxVgwHbVsUQfDCMEuQ/f0hmcogcUxhylDxSz/OrjIn0afpJTn3kXIdz91a0Nn+SHDgGKlsl+LYTIchELCX3DAqVcf2ReH1pc0gueWza5ea4n+m2K5FvlT92va6Wv67dPVqDwId5fauGTNeXURYDXWDBRmZCrHPrC+GCdGltntc94NafgfURxXOhiedJPdJEAQPQiHVltBYDoM/0msAKZrj6jH+kDdQIQ6Ka+PwTk6T3XmDtq7CkXn41ZgVcAE2UU0ZPKq61gk7MJe4qKB3XvTW96UwPWS7fUdZ/qF64eEzjgv2fxURvJwute97pFcmXiqfnv0Y9+9CIAlAS2oUuGetCyeDi+4Ls6W5wzWPX97XlHUuhNcle7duHzvAE6+KkPIlLZYsECQAviY7HgXvhGzyAe1R992b5r29Q9gYTMM0i9LCrIBz2mrfrMPBY+7ltEK1ssOqr+6lrf5c+oJL+psiJceYtw0CnD2tWPx6xA/JMXMBf+aetSfpqblvG2EtIZq4yB+gAWCd/GOc/TOa7BNebOc889Nw2F8IgFYN8GsmAsmHctDAQkWVWWOvU811aYB2+MI7jGbrw5E44wj8II5jjgFxmL5AUOwX8ENxTf1NFz9JX6LzNwkRHGPTikSN0sQowt86HxJeAF7KL/yeqb3/Lm9olh+rRAxmetzLb6+R2vvmX7ka/903ZSbPFNEYGG9A1a4AroKaIcROOpCDUALyABNJhcIoBCgjXKgoKnQAkyRYAMHJM8gTLxAFuriFAASZQVQRE1BoMoCoqXcrEFZZI3aAiICYugm5xEeyOYygUOMZrSJWSUrJW8NkVoxHSRpT2UqQ4zGHR4rwxX1XWzezoVMCE0hMcEw/Ik+o9IKCLtiHojDZ4azO4RPhHNLAIsFvDAc1bBFgMGAtBFkLTN4sLgYlUWgYa1A0CVv7YaWAaidjm3YxuPMvM8sG9yJqD6D4jT//hDyLnH8lcrQUo8wlbnoMLbnggzDx5F+lHfG1g/+7M/2yK4Qi5MADuKF7+1GThUR5OAPGzTFAHrfluRkgODVbQa+Vr8AKL638CSZoosmlhPAHr94BkyD8gAztoK/FCu5EQ5FnfqR5bxEO9NXmTYxMBKiBeUp+csomyhumeg6zMKghIDavGY/KqrMkz6gBpe6n/pLE70g3QmqWVk8lamvgQKyBLlJg8Tp7rJ3/g5Us8q/tofPbO970Pvbo+718uWsWFxPUIWt/d96+3bMy58XsqRNuszfYUPdJTjUmSMLBg/xhi5Ey2LTtHXdIedIRNEkQUOYGeCJDvGp7FqUaevyJ0FuUWiiYr+tJUXIZFTTwFZFkQWOeoDsNGzACGdyaIHFJBneZFN9SQLyjb+6V7ySvYBBHKrzhY+ZEF6MmPxCphYLNK3FtXGszqoo/rTiRZFJRvGJNnxW/3pDTJML9IlJil1oB+5mQTKlEeHmBiNZTKtHhZ92oGvFpMVDQ1v3WekMD/4bTyQXUSX0QdVP3qT7sNfRG/hG4uTfNULkFAnCz56wPiWzthSN2UU4SVd5HlgAGCnD7XZ93Iv6HtF6FRf9SIfZEff4HtZws0jZIDM4Il5jd4w99jlo1PsVsoPj/WN/MimfqMTWf38Bk4ANETvmAPVk8EIQMF3wMXWN30JvNJF5NSYL+Avf4CSVY4Vnbxotz7CD4s6/CdX+hoPGSXwz6d+c88YwQu6jz7XD8CUOkYgjuSjNjAiFOE9PcSwoY/oP0DWfKU/XSdb6mTOMuea49UBqbcFjTaoAz6SK3wi/xY0dDUjgjmfHJM/dTX3M7yZj8wV8jI+8NYuL7kiT+QWmSfgA4tI4wO/yAIrOL3rHCre+lQXRP8be/SJulss0DHaSS7Ii/LkA0Tqb3oYJgHktflAYBb6Hp5SF2OaDDCEkFmyax53n25XNrkjH+Z/pBw8I1eMJMqj38icMvCavOKV553VdY382AWv9iifroMB6EOyqn+MX6QfzGfmX8+qo3FCFhgf4Yf+vK58LTjIEL4am3SO8YlfrNslp1lA/POMsfkFtzrQXnXzc9qP3vWG7dY3HM3hUdFt06oAFgE2hhg8GXErFNUQg2pDzO5YjW+IER1KfxHBJBqSEaJULEDlIghAKP2sazApI7WI6CLCVgj2pm0QzW1MIWCL6FkiU4USzCQhKEMo9wymEQN38ViAkSEmgsVvX2IVN3BCjUKxDwFG8nsIXLY3wF3+1r6dohisGTc9lMgQCiyjpck7Bv8QApbFKB/hVQDk/F7/QmENoayHUGIZAS8Ge0YOCyWWSUIRVdLF5zsjioooYgGMMmCIfMXYDqHNPEKpZh4ip6EINZifMYCGGMT53T9lx2Bf/O6/xKDK/PtrvsekvbiE37GyHB772McOAaiHUE6LezGIFt/HX8hikf6NAV8/8zMUWH6GohtiUOX3mCAW3zck/uSPWIQNATwWt+QRvojzdwD/Dc+KUFOyIQHe4Sc+CY6BBMeIQZuRpkJ5Z/Q212PgZ1/hpTr1ZKyIhR4LiOSJfgjFuJBTMo5/AVKGUCz9owd9J7/4RC5CcS0iHOJ3KNNMH0pxCOV40LNHyoWtBrB42NnXRm6r9pE/7Y8dhEW0v7qnP40LFGC0LudnWEo2/NZvY12iz+kb+tI4IVul8zwck3VGGwwLyIa8BI8JYDMEGNlwPUBO/qbXRAw0XmIyyj95BVBO/UqfoJhYhgCNWSa5FKFPpMIAM0NMtENYXDJypXsx2WUkvgDCGaUSX0S+RHR/RV/MC/GPTGrzMiJfsaDLSIAxoW1IRr/ip7KmiN4KUJTjZHyfbgswnLp53CfShpElI06On/M7FpoZaKnvg3G6AKUZ7bOPQBUAInVhpe3v1bUwAmTkzvotImgsVCGoIXasci4cz1kByFI28MO8hwKs5efUvwCNGXnT3DYObqMMZU7xNIwjmR2+1rinr3qii2LBkTzqr/suIiU9QcbGRCZjwZd6svLu04iuGqAsL0krgIX81BfR3dLAD2SqiDwGkKufm37SuQFkM512BqDawCOyrp4BwjJyHNmuua0yr7nHmCK7Im8aY8h8GYuU7M8A24vImBdccEE9np/6MgBgfhd5MwBoRrLUr+eff372r3xjQb3AGRsyiB9TfNb3+CS6qfE7ReaVMDRm5NJY4GUU3QCpQyy8BjKgH+gzc4jAWlshuot+wxe8GJM55rJPzpX9PXpKoKgiz8aiIX8KbkWWw7CTPKo0qz6XBbCwQtg2rQK+oqSF1THz1gnCzOpUhJkYQyHXtbAoJKNiFZWhQWM1lmljW2aRpgBZrBYXSsPgWAf4UhQGeZUnc4NHZBFkgFGCRcLLxkonJ4e6ZnKRdoDy+wAAQABJREFUj4FiAJpoTBaxss0kBK3ADeBA0ceKKe/FiriyyQEVq97FJLm4seYXgCu2LjI1wRZeuAhfhUsm1AivAc+wHOWEpM0UFmUMNCM8iRVsfvfPIEM9r+QDdAlzi/8oVlVDWA0W7aDMS5kV0KcghZYuCitQPqcv9B1eyhsBvrFizmt+1/VY4fuZFKveISyzyVsDB0Aoks5iIFa3uahSf3n4DEtYJlMeUu9q38WhZEw6CPAtIKregP4y0g/AtvTAfKzcF4MW8DVRVRlheRrIMlIn8kH2hDUOq3WGrQY0YkWc7SdLcY4snzdBxQsA2WYAt0JcXhVgg4IOy1nWu+pKERc4lX/RGDTX9foUIhkYAsDDMrFQOIBvKaPYmj4oSl89fyR8bhX4VsjiahtQQ0ZMRmMCsMheWDwSiPX3XcffmkCA1dIVfTrfTYCIDh3TGICM72/1t8lkiuKYzwZgMU5jHNE7QsCX7iCzdKQx6Pt+IMBXXQEx4HgrpM/oFPPXMgprdC4qelBvfNNTxiGZ8DlFJn/GmzjOsQB2QtHT0VMgXR7ypguKNgtZHGeRF7qvnqlPeU2RucJzYfXM+jEEAGFjovdKz4zv+b0s/6m0dY2+pPcsOiwkLaDMGWMyD41pO+WN85j6rS9qzuvvW+ABYRYr5iTGJvNxEZ0JyPULOQulvwnMUBTHQHIOYOATnhnRv3SDxfJVoePNi1PgtvI4lM8Ct5WH9kwB1bq/7qf5Dug1x/Xt7Z+vuXh8LazXC+NY7HhMRktdt6/3HPgS4DjbkUIBZMX2Qq4+dSRB6f80HDA0uACG2NZLkGalIl1sj6Vy8D3OUCWfzjzzzLwXW7AJrAySZcTiNS4PSDCBAabAmfuxpbDIArAdW2ncBLKlpRBZWCtfHeE7i121m5VEniw0QBRFgoBnK6t1Oy8f6v5VmYCX78BSgR7AsRYNHlEGQaLIYhtpiO2KvAZ4aoPnYxthESb4QIR/rvx99mTVbUHQk4Fb6ePcUE78FLdrymRB8h0vEGUJIOIT/hJ+K/fKw2dsOWba4nXdo0RMMLHdk89bgbsHOCJAAS/kXRMHsFnP+8QLZLKJbZ9MXwuq2M7KtFa8Fg7SWyQsI/y3MlYfyqlATV/eqaeeunic0qt7BW4onjgGk9fVw/0CRBZHfpMXn8gkaiET22ppHdTfKLadsj3SAfkWIchvafWxfllFJnjAGv8sBD2rPJ+xfZ6A13eT9ZFKhwp8tZtsTQFQ45z1BiCcAll0Si1ITWT0x+GmZSGL19VN5K9Py9hhMbjMyrTX7WXJomOmJtl16qJtffvGzyy7DxQxQtBJtZAeP+s3YGB3seYG15bl6d6YNgO+0tMfWyU7R3YCAHc6lD7YSzJ3wBDqbnE/plV9Mk67E7+XlaeOxrXPdYixzLxH77NS06dAIrA7pipzu7I7zu9w/F4FfJfVBz/MfQAzfHcotOfAd6uVNfi3OhGUYGy1rHXSAyNlvVwn/X5JY1uirHNVp97iWtfqs7dU1LVVnyxee0G72bd9/Q9FqQC6LD6Hg5bVe9n1w1HH/VjmTgBf7arjMOM2slCYzJbpDuAY2GRF3ysZH9ex/70M+PZptvLdBA701/btVp7djbQFfHcj783ytGisBe5mabd7fx3gu528WXJrbpiydm4nz+08Y/ekjDrbeX4/PgPwxrsbCYBZ16d2dvZjvbdTp+0AX+XUrseUAWEr9VgGfPdFAAsH5R0M91KGw/D18kJMICspLFMr72/nZqwu82C4w+ZhnckXNLaTz14/E1aFxVv7Dud7IQI5gM7bgxdSHI6PIyUbquYA/VbI4fi9oN3o26l6O2y/HYoVfr68EBavlBMvVOwlLav3sut7Wbejsawr/udb29XXHN8+/tFr2i0/+wbtyne/r936zl/eTr3JSdncf7jqz9ufv/M97ayvflT7+CO/pv3B//yj9q5/u6ad8IG/bf/0vv9op93rjPbpJx2XL8PQdWHxPRrZlC9YeZllppYvLIV174hkRRhLFvX2YuTholgcLl5GPFx12OlyvcAVRr58cY63BW2caSMHvODppUkv7e0GbQ317EYNIk9v6nnjdz9QbP/n27T7oS5bqYM3Ib2hOiZv23o7eKad5YAFgzezZzo2OPCZt7hl+96H3Ln9wKv+R/ut339z++JP+6t21vkXtb9806uTAS8475vbF3/nhe2cUx7Ynvu08MZw9QPbz33vbdrtz/q+9pbXvaJdp3upuNwpHhucm1s5c2DmwJgDDGtorww84/L3+28GnN0Cvdq+PXPXfufaXL+ZAzMHZg7sIAdufoubt1t8zmeHa55btv/yLY9q//b+D4e/1Du2F/7A49qzXnF5uEi6Sfv5cOvzmJde2D7rBjds//5Pf9Pe/x9DO/m617S3/98/ix2tnd+d2sHmzVnNHDhiOBBb3UdMXeeK7k8O7Drw5csv3hTcn63fRq0ENeAL8HBSvG2cRzCE+htTnLFLH4zj61v9HS/8pX/ieDt7q49umt4RknBHlj5ut7rNw9dy+enctKAlCWwzc6R/qGTLip/T/UT8YvIly8/hTDvLgQ998Op4e7W1C5/19PZ37/3n9o6//rf25Gf/THv6o88M35kfbN99wfntV89/bHvrO97Vrv7gh9rfvvu97V+GU9o3fdXZ7eQjFPcerSDjSGgXv6p8n68ix2aOFTJX8JkcL8gfK03eUjuPBJneUoN2MfGuA9/w+bgyvN8utm1XsrZNyTnz4SROvi8OZ9vxxu1B1eAoOt4m3nDdeSIBLbZCHE9zwL0bR1DCjU9GUuMgfLOtHiCuJ9Ga4oWR/tKWv3OIHofmt/zc+IF403lldLdx+r34LaiAIAHOHs+0sxz4+d/7y3bSv/5L+57zntK+7rwXtje84tmLAl7wa69vX3GXO7e/f/f/ac956W+2P37lD7Yz7nyb9tErfqXtZ8y77Ix/uDRaBCVYNLL7Ev5HmzTLCGibovAMkwFYVi14w+PM1KNrXeOkP15oW5rWuODcf6x34s38DBqz9MFP3qATLdz3ghgx4sWyyaI46A+fsBlIYDLBEXoxvGEsrbk2x8tSmwarWprBDt0gu6tkNF7G44LnoNJcX0UCKG3XqCaa21imV5V1rN/bVeCrI4XGE/GkCCgLt035EptD8yK5oHgbPdMCXOEuKKOSuO5FCYrMeUqRvkSvQiyRfotwEm9K5zUCyZIoGlgPmCgQEW/CfVm+XCJiSZGX6URGEeVqlTKWXthS0ZVEHCkSeYRVO3ykZtSRur7sM3zbZZhOkUtEDUKi5Ij+JtqZyHWAmYGjbgQ63H3li2vhrWGRrbaMXzSLt0MzGo+IPkXhNiUjtIgQI3qPaCfIS274YIISDSbeNK1Hsh3hLi4P4NdgMtABKv0TruMmB/Yig/gisky4+MpIUqLcIHXQP/gdb23mi3eVfybo/qm3KDYmVzzT/2QExdvGufhwfrm3iIiKA/iL0qbPV5E6iMZjYSbSTFG4qcqoMqIa9eBYSFnnssLFWkYxq/QsLngjYhZZQOSINR6PhesU3UeUKnxmITYGREkKv72ZHu9F4QNaveiJnDUXmYflVlhXgEG7jRl5kP1+J0U6CwlyX5GSMqP5345x4IQTTmwPiqiOJ13/Ru0p3/OkDfm6lwD3+JPa9U4+qb3/g//ebnJDY/TEHAsbEq/xoyZOY9nClX4gAz3Z+bEzM0VetrRAXKXT3Au3URkdrvSwvOyIiLZo/NE/YzI2RSsEfnuy20DPIqHTS5YrjWhYojSJtkSPjkkUKVG7Hvawh2X47jEIon/pIONkamGnPQwTIrl5OWaK7PQY7+F1Y4MOKzBbu0nhsWWhbyofel60LuOxXh6ue3QA3SZanoh8O0H4BQiJAjYm/NdGdRmTuoRXhpyXxvf89txm+nHqufG1cD96UNhbsrFd8o5KuC/LKGLjPOhPRhhGn2UyjV/mmN0miyR6fUxeVDNWRWIb88E8K/LZ1Hg11sOnfcqOeWCrpCx96l2e8OqUUdq2mkelL71Tv7fy6VkY44jYbYzKbptWBbCQaQzAjDbCdUdPwcz0fcdvKP+g3KaI7MZvIJ+HnH/7QyLO8IUrghBH/Xzmcf8RijXvczIeICADFnDlxHl6DOqBY3aRQxAn/uUbNUJCZiQYZfItXL5X5S+KySpS1mURNKH8xkobIR4zKha/jSK9bOZ+g+N69dMWbUZc0vCTKCqJaD3qws0JNzL8qipDm9VXHYoqOlv9rvaXr1rXpRfsQqAHAUMqSEco0yEsBvmo+/oB8QHLxRF3NgHcsk36UUS4ckTNuTiXLMtIpB3O2flH5tKHr2T1jwGaQSv4+sQHPFhG0vIhyZ8fn6e+ax8iPwJGaAu/xIhvWa6kkLpX4JC8MPGP+zwRYchLBfSQjHzpH/lXxDsuy0S6k5aruAhhuchR+aL6cFsUAz6v8z1IztQjgOgiihVfnXxHc2ml/TF5D6L68O+Lx1xgyVvgC9fxGZEH/ETc+wgaoKywbmUwCzzWP/o3FgopM9ox08EcOBR3Zvw8GytIfy/zz0o/8G8tSAoH/CL6CdbSk74X5ck4LKLr+GPmAkiwEWNMv3OOj8Z+mEWOEqxmTLEblHrXmC4ZUt8xBVBLWTGe6EpjDklbLhHJMkf0PQXgyTGibcZnET/fl4fvdREC1V1gn96tmwho5ByN9Yd2Vzn4YGwL+FFkLBk/AhzhpSh3Y5JHud7i45s/ZeM2gFImDWC+CMyg7e4V6SNjkg9iARNi8Zz+2Ou+8kq/8Nlq7EmP5G++Mmb1PZ/Zxct6vj6NUXMPohP1oefGUcfMhfStdvOP3pM5xjPKPTf87VYfS2MO0g/4ay4pnVnP07n0jQA1m5F20jV8gpv3qr2e44+Wn2LlS8flGF/8fNTWPDGV/6rAJnzEk30RUovMi3SdqJLGH+r1fqXDC3MlfatvlpVTedRzU5+rXIzRr9pNvvq5WD8J2nRxjD3jAh7oyRimO/hE7knkNn6Kze3mHdHk+JjvSX+ak0WCEzRqTPqYDPCVTw7NU1MUhpS8XONhnAZOK8w0vrfO71g8ZqCyaruxKqBNLw+wQY+f+nz7QB/9dX1Grsc6tE+z7PthcWfG8sT6OqYIkrB4Y88K2sreSqesABEOdLHatnoKn7rp6qzyYemycgrFmOZ992PybyyiMRFkeqsO1kSu0Wyts4SFMki3aQFkclUkj1COabFjubOaXEWsndrTWynF8WbdY2lkJQ2hTSv1VD4hoGm5YanlLsbWhzqw3oo/rXxlsObZ1glfn3lMROxsxJIpljvL3hR5E5JVsndpJT/8cb1/m1yZdT6MpblIf0TknPyJX6zCMZDSOmKbjxuvGDiL/qvn+s8Y/HmUQRn+nIVl9WdF5VpNn7LUryIWWZZw3irwoSd5sLD747oNhbJKi2h5sGBRt8qWzxSFksnVsXsssFVGTM7ZF6zV+kd7WWZZqMUsR721iZUrlF5a0llxkd0IViX9YCchFnh5nYzoOxbgIvVmzTZWQvllevz2OxRrJuv7h+ywiilLXSPSWlq9I7DLon/tGoQiqCLmz0PgwPHHf+qggvFSfUyuWKDIKCsmIisR1CRlISbGtH7GJJ395JPFv8iuluNHAShyTMek02JSzHj03iOIhXrKYYDA3PnxnH51xp08KT8mudR5ZNNvuimiMeYZeGU99KEPbZ4PcJLjjzVMueppByMmoLSu2l0gewFoc5dDG8sNF+ssSxxLFh1CX9p5oKtYmdTp1FNPTb7QF7FY3uAyUR2NdzqA3iDXiAyz8MaiP38bMyy9qPhJz9KPeMTNZFlS5cdyG6As9SXestAaS9qE6GJtVNfS1+pXljpzTQD8FgvkTG8c00nyZHWkd2JBm7wzluRjFwuRA1vuVf8wTKRujsBFeZ8OpTPkrU52iWKRnbuVxqz8tEk59AMe+876ztKO8MNRBoTn8vEsImNkRbvMG46rkIuzzjor5w66Db/NIfpH/vLTT3YCzIUBlJpjY/Skt+c9Y2e1eMUCGVHvml20ANm5Cyk/9YvFS+7WsazrFzu45l+yp+3a4hheBCJqEYyqmSPNQeptblN38mU+K6K3zft2CuxukAV6T33oPHJs9xjZWZNvTyztAapy5804oH9jUbaYC8m8/sJ7Vn18K8JnOt0OhXFkPOCP77V7qn01PliWL7/88hwXeI6UbzfCWEPGR+lvv8kXnICXrhfWMD9fEnjEfddY8B3FUQdyJq2dYWPPjgIeaVvv8cBOCJ486EEPSkszORnvxkTwp2yfPiJnY8ITeaxysxgLnxyP410GvCUn5ju6Ql+aE+3462M6Etkl8R02M2/TOUUBbnNM2HlxhLAnmEoZ8oP57PROkfFNfuyY0xt4u4xOXHZjJ66rLLBH2HwW0KIAezIwMJVi1qE+dTgwIo96Tj4GgoZjLIFBJn/KkFBRbBpOMdm2RhSg7SLC41gEMGzbCjCiTA1Gg5kv3FWkDfVXdfFJKSL3SnFM5RNWgOwMxw2Am1L6xR+fPW/kRYgKgFHuOr9IeuQZQuc3fhXVdYDLwEUF2igVigiZaA1yhAexQktgbvAfiEWKRQn+mAgoFUrSYmUZET6K3UDCExNGtRWvqo3qu4pf8q96Gyz4YHKqdrtfz1OsBoXBr0zyUW2SbkwmYJMk8EFWLC4snIBq9bWd5b6yKHCKIyyvKTMGpwUWcsSBfJkoKWeu+cISn1s+FK9jCc4dIn1TfVRnK/lX1sdhkc96W2iYrMgkRR5WmzzyUMdaPF/8q762iLL1CZwALUAXXhSZrGztmjxnWp8DZOvd7/77FhbMhQw4dkRO9LcJymKoAG0twiy0yQg5RCZURwYAJOABOCCnPk1wJk0gA4ANi1ymUbb+RI76IH2vr41h45C8uSaPmrzpT0exlFME0JBFMq9uZMGRGfkaJyVH7hvvxlKVKQ9jVv2822DCt51a99UTgLII1Z667jn3gD8TPn7QI3Xf2DTWAHF6whh0hEGbioBji1I6QJ2MM+1F6gPYK1d7LRyMJRM3EIHoCu0BeIw3C/8qX93MO3ScSdL4sThXF/pQ3wFHylF3YLyezczjn/riPUAZVuLFfe0EROlJIOGdcVwropdm35r8lSE/AE/99Z366Xt1lp+2V3nqSi/TEWQFL/BVv6hjzX1hkc7t9Oo/8yZwQVeRP/1r3rHwdsRLv+MPeVZf+l17gWHfGTrMrQhvpFM3fFbPmvcALQYOgJCeImNhzc5+kBfgrm7mLjyx+LewM66AZKAHj7WPzvMZOw35Sec78gX8aCvdhx/mH/OofnLNvE/nyUe76W+AXz2lL13u+CC+A5Gum6f0D0DGeOBZgIlseNbYMZYAbXJlviCH5BfQgiecwyZbxlj1mbGMD67jCzlxz2/Anx5BYd3OfsBff+pkDqFXLA4sco1V8xMZcE1/mhfoIHUwP/mTv+f1a9VDexhWXNNGGIh8WKz4bTwBq/QGTBBRX3Oc18JXHeV5xRVXJK/0pz4m+/rDvEwmyYJrjjWaP2tsk2tyZCHqnqOr+Kr+eKB8Yw++oF/IB/k0nrXPUUZl4625DV6TzvjRD+pMRtURZtTPZEK5T/u+p7Tjbn6OJhxMUfC2adVRB1tcUXhuS0epGQbV1k4IQ16LFWhuo7jHxB3Cl1vLMTiHWO3l1oktAPf9BbAbbE8V2apxPTo2Y3uH8srIbzEx5HWxvN1XZgDdITo8/8Rsr+2OULIZIlk9hZxV3iqqutSnrbf6Hh2fW1zqGRPWZDYxQIcKS+uYwoEIDxyTRh55iIGWRz1i0A1XXXVV5hvANLfdbJmGMh1qq0K41CpXeTFIsjzHP/x2z2cIyKIeoRTyWkzSuT3uRky+mfbc2K7yTAyO5BeehnDnVqHrMaHl9ry6uRdCt2lkJttsIYx5TCUAV9YjFEdeq7qvE46w+jkEPLeKhL/2fExOQ0wO+d12cQh7hpNWv1BKB22lLhgRX2wlycO2kDqGYhliEZTtjxV83nMcIyaNRchEMkROyJetJ2RrLixc+b3CVNu6UpeYOIaYRDKym+MJtsaq3frG1hXCc1vS6o2/objzun+OY6hfTNz5rGsBeFJmlSEfzyFb6/InJ2GJyyMVZBKRNXWdaRi2ctTh7P9xTfIUj0O5Lo4GFR/1AYqJf4gJbeUxp5i0BjJlTNdzlc9OfpLjrVDJ4WbPxIQ0OJq2VaLzHOXqt68rD3wQaj5AV46/ul6f2uKIQVja6tKGT887ArWKjEFb444e7QYFiNhytsv6yBZxAL08IjaVaQCMnCfND0V4i3ZCpgKApE4hp+oxJmWYq82bWyEyMEWi+wVoT/3k6ETfBuNF2GK60zEQbe/JnBTgLC+5H6Cqv53HEBxxrGOCl8VRjSLHSGLBlz8dpVhFcMWy/vJcgPoc01N5hHV1iAVGHi3peeCohD4MsJnyr449aRt9Tu7Dwtvfyu/kxPyqHbFoOui+csk8grNiAbAhjWNwjgYGUBzMyT0P1NNc15OjLmGIWRx1cXTBPBwLlDzqQgbxaYocbYB5wnC04bajOuZ/x4ccjerJvTo2Y96MhcrituMiYRhKzPO0pz0t5zrXyCv5UX/HjGCzb/i6rxnOuexfhyuv/vji+foCcW+bVgHfbWe6iw8WEBgXsez6ON1e/6YYTAzrUD+w1km/3TSA2n6m3ajfZrxddd/EC6RvRqvy2M1nN8v7aLu/FeD7gLd8bLjP6XfLiY+SNVlN0TrnqekY4Hm/0brA91DqTbZNnlOEp2Edm7qV18LKuBJ4LH3wkzfCYrdZkiP6fgHfnWhEWN3y3Hot7Hciz0PJo4xkwN9YrxtPDEKMO72xoC+P0SuszEPsUPSX85y5eTWslwcBsg0Jd+AH+R2/yxI7fPkOj3uAYViUt1xSWEE3nIEfZ8AgAzwCqFPkHRbtZ1jqz+BKC3cwxAGcQDOgPj5TH5beIY7T5Nnbcd/05cVOTi4+xjyIHYjBotF7DhbVYwJivduz2fgFuNVlit7/z+8dHvyG900C31096hAWqH1FzN9TtOz6VNq9uhYdmWeKYmLIrQ3bOqvqydS/FxTWr70oZttl7Eb9NuPt1H1bao7v2LazNbgZTeWx2TN1/1CerTzmz4M5YAzaRra1Z7tuGdkm3IyMXVuYxyKRT0d3pih2vfJ84NQ915y1P1QK4L0463moeR3NzzsK4c92/n4g3oMcBbEtP9brxpPzyrbN65z2uM7eKXGe1RGGnrTRUQpnam3B7yZNya9jJkUBGnObvn6v++m4wiWfPOo59YwjSbwSOeY4RY5SOIZX7/P0aRzP8S6RMevogPnL8b2eHDtwzMIRFHpyFdGf4z5yxMWxGn0xRbGbmUddHZFZRfUe0VSaG58S+naYdus5jQSncpmv7SkHTBb1MsWeFjwXtiMc8BLBTDMHZg7MHJg5sD0OAI2AkXOpUzQGtFNpnC+eIoDai2JHMm1m8KgXtqfaaCExBXorbTka8G7LKqp0q9Isu7cM9C5Lv5PXZ+C7k9yc85o5MHPgqOTAT1/49PYX7/9YvDhxfHv2cy9sf/o7F7d3fMb92zfd49Rs7xt/9aL2K294e7vno57Sbj9c0V72qv/WbnnfR7WP/tlvtyvf9eH21Of/SPuCGx9/VPJmbtTMgZkDMweOJA7MmvhI6q25rjMHZg4cFg487mnPau/+37/avvOCZ7eTr/5f4Y3g+9uv/eHfLOrym6/8+fY15/9w+8bTv6698Xd/sb31w6e2s+96q3bhxZe3r/qGR7TPveGsahfMOoK/8LRRnnGO4GbMVZ85cExzYNbGx3T3z42fOTBzYB0OUJTXu9712w1udFx7+FlPbne+z5e1f/nbK9uLLvjO9oJfeEv7zJveqP3A139l+7ZX/GT7zJPDp+4pn9VufL2T2onXv2G7SbjlOWFvjuCv05Q5zTY54Dwm37XOnG6H4oWshQuw7Tw/PzNzYL9ygGyvIu7n+JKOl9ZWJduzezPw3TNWzwXNHJg5cCRz4LgTjm+f+Hhrv/q2N7V7f/Hntk8/9bbtSRe8pH3v198j/Ip+vD3n1b/TLn/Svdt/fdt72jv++8Xtp38r/Mle95T2pXf8wnadGfgeyV2fdefH20s3fLROEZ/DfI4uI+Fc+Xzmm/RYos1efjqWeHE0thWo9RLcMtL/gmx4EY6v3f1AM/DdD71wlNWBgudY2uF7b8VX9JujrJlzc44BDgA6PKpQ2t/7gl9snx2uyY+LaG5ffd5Ptdeed48FB5716t9u97rZdduf/PMH2y/+0qXt7694Y/v+R96nvf5lT2p/GQ76Zzo8HFgVxGaqRn0Ajf4+zxCCP4Rbuwxaw+MAC3ARS5Y35QWjmSIeXgBnwNgb90cj8ZQgGEJPPAsIVnC4SfCNCsZxKHURpEbktP1KglyF3+HJ6gm0cagkwMTYuqtMsi9QDC9UAnUVwQAiF1rwuU8eegKKKyJff323v8/Ad7c5fIzlTzGIYiTKDBJ5h+ITyWemmQNHEgcoZYpbJC+TyS9n5LtPmW5NAqJPiSZ0kCXjuOPbS3/qJzMKoshTe0n7eWJelw+AorC/29kaFanKZCuiG+8qFi89iWAoStZ4AtffIquJtCgqnN9F6iFKF/dZXCiZyEWqKyILXEcJW8wV1Ji0RwRFhgBRQ3eDgHPAGgh55zvfOVmEyJDKXxaaVkS1ZTxn2ZsyYoQv1YwsxstCRRuswoX1FlHNGOn5Wff7z2WATRrziIiuUyS62aoxpk2itYrYdqh08cUXJ7ATintZeyyORDQbkzYse0Za95fxfpyX36KdFTl3zr3ZIx7xiEn3aObfck1mx0G47q2ShZujPuSgSH1FzRNpkAeN8B+c4Lfui4Jnh4QMcI8mUl0ReRW9TQhtEePG47HS1WdhivrtUxRKUfHC93QaJ0TLMxZ73vTp6/tGjVBX58+ZA9vkAAU/RcIazjRz4EjiAJc/v/3bv9MikmRaJca+aFkAKWyApg8lro3CfgMJD3/4w9MPpvNtUyS8NIBm0luHTJzSC+PLstJPFn6b5AGEKWBjMu4nLeXVRGwCGZO8hdGdujdOaxIbkwmowjj396rM/lr/HXiiL0xiY/+tyuGGqUKZy6vPTxuFVI7IVRlKWf/0AFWYaaHaTfyAQD3LeqvPgFfhXiOy1eKeugEWni2yuBeCtQgo4D5KSGmAfUwmZqAYkYllwPQZz3jG+NFFPTxT/T3Fb6F/gS7gwznkcRp15DuVT+o+pHUVCNQJIT0lO/iFl2RrHPrcNjaXY0Lxkr8iYDSCKGSYXta+iIxat/Kz+gVI8Ry/uyyzY7Jw4TPWfeF7exkGuj2L5/e85z1bRM7MoyQR0SyziUicKb9cg/Jba7z1VP1f13pgVtfq02JJG4BoIYSFIh8Ti6dx3+80WDgLUS6Mb79LMH6Wz+Ep3vfp6BxjStl83NqhEHb8qU99avY76yuQ2ZM2ApgR2TXrFVE8G+A+BufjRUufh/LonYjyluXUQl/Z5557bibVT2Sw9IV+FfqavDMguM+/vQUkAmQtMh/5yEc2Oyhja3Amin94YmzJa0zGLJkWPplM80EtJHY/VsfP+D0D3ymuzNe2zQETByEf07HqvH/Mh/n3kcMBwOEBD7jvIgAJR+4RYnzRAEo+wk3nsR7O8HtyPOLKK6/MS5y9Tyli14AhAKEHDH0+rGCOWRSZ6CIaUlpJnClleSwyobz2ta/NCd5EOCbpWWXEuC8yLpXt+tii4jfwGdGlKvnSzzPPPPOge6ymLFBj4ny/J5M1yxFwog0AwB3ucIf29re/vY39iN7//vdPa2yEKc9JFrACSIoAZhYoFGFqE/QWeDZ5R7SqFlGjEvRqV23Ny4+lFiDgcP/000/PIy6Vb4RFzcm3fgMTfZ8DACbniHjVIqT7hu1eYPXBD35wPdoEMBgDHG0FaPTD2PJJ5vS5uheoAPCkLV+oQLH2SKf9Eda+4WsRoBKhcRMURpjnDeBRGoAPWAM85TMGhECqfIHcHtg72nHaaae1CHecfAOCLDoQ+YkQ62kh55OXNb3fBsdru4HkUp+TbYC1L9tcoo34CvDKWx2Q8cmCHSHD0yevfrXoMQbIDQAkGMN3f/d3Z3pBFMYWVdv/AKHxip8RKSzzyAdG/4B/bUDK1gc96Td88Ce/ImXYhcCn8TGXap9FGBl461vfWo/lp8UVsE4+tdXYsfCweGFJvctd7pLAURsBa7yyQLDQKkD6oz/6oynzFkPKoW+0td+ZAFKNrWWW4AhtvPD7C3A7zmjnwIL+bne726LO+rfGGyMYoNv3OYBaCxd1vu9975u7IAI9LfOrrAw8mPJLTCbpGQE2HLVh/TVWLUzudLsvacfHexlTdEII2gVTN9a5dukVL24PuO0T24nHX2ed5HOaY4ADp5xySg5eK7Eig5NFbAoQV5r5c+bAXnDgHe95Y/v3j32g3eXUczYt7pXvGtpHf/vl7e73PCMtjBZ1T3jCE9KaxnphQgHQACqgwUTy6eHBgaI3KVDULJMAkvFwm9vcJn+7xnLDQnH7298+LWksvraFAYUIwZqTGRAnrck6QoumNY6VRh0AM2XJG6CJ0KI5oVD+LDdAkknM1jxLmLxsKXI4DwQBpCYbwBv4UFfbmCZWVjRbo36zbgEtrKQmXkCRhdv2MpBlggEWWF0AaBZPIIllCLBncZPGOT6TrcUCC8/LX/7ynOgANlZlFh911R5lsVqysppkTZSs7gAui+Sd7nSntFYBaEAhEODICasgUCkffeJ5ABPQAwZ+8Ad/MC1CeOrPpIsnwDMrL756zj1g1TVgCT8ABn2Nt+7rB0DLwsPZ0QgdnPkBpqyf6kYXyg940d/kx2/ADnDAa20HEIEZMgWcXHTRRSlPd73rXXPC1w/AhPrhu0WNfnRsIsJlJ1AD1gEA5Wu3vFh4Dxw4kGXq4/POOy/rrQ2AMQuu76xuN73pTROcq5+64Jd8tFX98FCZ2qosQEzf+Q34+JRW/+EV+cMTgEQb3QOstI98kBVlaAP+s7BLg5/aKDIbvitXXbWN3LK0472xRo7IiciJQKdtdbsByvYJaJ4ZCzL1lzdwpw8ijG9aXiPccZbBSg4oq49PVm0AFUgDiiM0by4mybS24xkZI2/yNQ7xRp8bV37Xey6OAABj5Ehejt4InoHP8rHYcQTDOAES9TNAC7RboDq2ggcWqMo2HukRcyrAXzwga/oAb403oJx1WZ3w4NRTT80yKT0LcfUB0Fn58cOCRzsdk3LPAvSxj31szuX4DbjTFdqLh2TYeDQWLQJc96fPWG7pD32s3o4G0Ynu+06e1YGuIHeu61uyo+146ThG5akcVmp6kCzgkUWdHYanPOUpKSv4Wel94sdXf9VXtjd85JR29udEEJSTRgA4GrBt+vafPzD8x8cOjrO87QznB48aDojFHRPrrsdCP2oYNjdkTzjwq2/74eGiN37rWmWd9eaPDg994P03pI3JfgjLyhAT3BCgY8O9mNQXv2MyXXz3JaxZQ0xgi7j0odiHmJA3pImjFEOEYR0CLOT1mLg23A/Fv+F3/TDW4gzlEBN7XRoCCAwBrIYAtENYnhfXfYmJbIiF6BBAaAgwurinbWENGgIgOtw6BHhf3Bt/iW3PrGtYgoawdubtAJ/5qR6XXHLJ4hF8evzjHz/EBJvXYqJc3AtgMATQWvz2JSbvDb9joh/Cirrh2vjHMt4EIB/C+jXEEYIhrJPjx4YA1UO8iDto+5jCupd1wd8AwePbQ0zuQ4D/IRYeQ2xxL+4HaB4CuCx+B7gYAvwtfvsS1u0hFkOLa30/BNgfwsKVdZOg59figU9+CcA4xBb++HL+DvCVMhdgZAgwuiFNWEaHABFDWKKHAImDOhcFIMt7VW6cGx7UqSeyEUA25ay/7nsA7uxTsjEmchlAZnx58VuZAWaHWBgN2hagcIit+8X9+hJgciVfKt2qz1hsDv6mKADmEIu1IRaUQyxaBjwcyxie3fGOdxwCxGUWsVBYZGV8B3Ae4ojD4povAZYH91AsAodYfA2xOMvf9S+A48qxV+k2+yTbm9Hzn//8gZwUxaJziEXoEIuirKexGUcV6vZan/pQHuQggPcGOZeB9geI3iBzlXEcExlikb/oW7rLtSJ6i+zG4rAurfx88O+9b7jy6o161AOQ+7ZpBr7bZt384MyBmQOHgQOHCnyBurBMHAQENCUsuENYLgaTSQ+EqplxPjAnSnlQ3ibTnsKCPIQFpL90SN+B080oLDkbksRW8hAWnwR6QMpmBFQWxZbkENuXCRQA6J2i2DLddlZhjU7AEpaxyYlWxoDGFIXlccAPE/gyAtBMxv0iBUCKM635iOth+T4IIIYFbIgt+yGs8gnwwrq3rIiV11cBAP0XVrshrLMpm+OMwuI5LCtX3ciyxVPsGIwfXfkbyI8t6Hx+ZcIlN/W3OqNHP/rRQxxdWJJy9y4Db2H53fEC6AUyg2LnJEGdBfHRRrWQtDDsF3jrtJNOqsU6OeoXFOs836dZBnxH9t9Nd//mBDMHZg7MHDhmOeAMne1lW3ZjsiVvO9Kxh/5cW6WzJWzL0BEJ24HjPJx5sz28U+R841bJ1qWtaVut2rIZeZmkyBall3gcR9jJY022lQ+VnAW0fT5Fto6nyFld29ur3EDpT1vLda5RPo4ZOJrhKIhtYtuuY16SEVvQztYGQD3o7OlUfaauxSQ/dTmvKdMxFcfMHKkZk6102+tT5ExygM4819ufT55KO75mq9wWvKMH2yH9XfWq4wrbyedQniG/jiTsNDl64oiDse44hmMa5OVoo1PjaMV2ie5xfAqFkSCPjmw3r2XPTWuCZann6zMHZg7MHDjGOeDcmol9TM7d/vWVf9Hue/+z4kWTA+Pb+dv5Q+fSlk12zjIeqQToODfpz/nCI52AU2cgV1H/olefztlWL2E5N+ps7RRZCDmH66xjWImnkhzyNQDr9a9//WQ+zlQuI+d/nelGzlceLsKXsL4eruJ3pVzn4cMi2pzh7l+C25XCjsBMLTqMHWfCnf/eDZqB725wdc5z5sDMgaOKAz9x/lPbb7zpre1zv+hu7SG3+Hi7+I/e2+5yz/u1C8671jJx8Q89sf23v3x/u/ntv7Z9xef9Rfv2p/yv9uBHfXv7/Ve9sH3mzT6//cALf6Td5tNPSEvoTlpD9yuTl1lX92t9d7pe+thLY16A8+IdED1FLH5o2UJo6pmtXLNIG7vw2srz0i6r+1bz2Yn0QDDeHsljSJ/4m2k5B1j6vaC3W/189NnYl/NyvrOHHPCmqLdbveV6tK3Y95CNc1H7hAPf/kPPa597vavbc37ihe3qP3t7e9c/Xd2+6B5nL2r3l3/2N+3JL/7J9qoff2X7x7+/ql35ng+2W3/ezdvb/uyv2/E3vEH77BudsEg7fzk2OMBqynLFc8HhJEc2jhbi8o6HjJmObg44OsSFHQ8Su0Ez8N0Nrh7DeXIDxCUNV0pcq3CNw2UJNyczzRw4kjkwfCJeBo5d1we9/PXtj/6/b2nf9/hvan/6tre0P7nqX9pJJ1+nveYlF7Q7fdWD2nU/8R/tyx/9tPZVX3Zq+/CNvri98DnntxvNmvZI7vpt17387G47g2PsQefnl51bdjyA32Dn48fEuMJdmGeXPT9+Zjd+cym2XRL4giu7mXafA7M63n0eH1MliO7SRzTSeH71+H2caebAkcyBe5710Ha9OBz2axc9u33Xj722/dQlv9Bu+6X3aHe45Sntdl92RvuW7w8/sh99Q/ubE2/TbvLnv9IuuvRP2iO/8v7tRtc9sR0c0mX/c0LEqWUgAtDYrXOph8IZQRB2k/gUFRhjLwjvGRKmyHXGhKNtN42v5WVt5t/Xy58CFIzJljjLuhfxdmt7vC9zSvb5wuZnVuCa8bgRzOHJT35yn8XiO+umFwn5rzZ/bofGc+528tCmzc60byVfPNiLvthKnSrtDHyLE/PnjnBgmdLioHqmmQNHMge++bxnNpvWTzjv/Pbin7yo/ec733TRnIf/l+9pt46X2H/45T/fvvdJ39de8qLntsefc1p76flPaEfiixQmLS/emAjHk7hGh1umDKggLPFO05RHjHXLEKhByFZvg29GU+3a7BnnZafAtbwKhG4n36lyBZDgGWKK9AvvB2Prp5cKBSOYCkk8lY/06ovnVf9KJyhAee3gvWJclr6v+olcx8Ax1fapa1VG/+kYg5DEY6sp8CQATF13Pnb8UpgdRt5EvDC4bA7qy9rud8EmBLwIv9QbshBERj1FjePlYyzDALsgHeeee+6G55ztFrDGIrOCmmxIED+AZgEhlvGRV5BloHqc17LfQK9xg8/bJbLEi4l6kg1Ba8beTOS9ztjcbh3WfW4Gvutyak63FgeETZwig2CmmQNHAwdMQlMWn2obd2AsOIDLdkjoUtRPdCbb8AO84dpU3p4xEa5LzuGH3+GDkptsuRUySUVwjIPKFZ1LPYENk92YRFMTaWyrhHfACwA7dTwKGGNVGwML5aiPKF3O1goljRciRE0RCxmwMUXLzpAClPpdCNUI6rDhUR4QRMITYe8QgqFuyBPQJEeilY3pRS96UZ51dX7XIqRINDGgWPhXUfKQaFz4MkUiYIkuxrVWv4jRp6yvgD4Lq2MG3HAVAaFkQDhtEfm8jCSS2LhfRCMU7rYIONKHU6Tv8ZArOGOsJ2WXiyxeUfrQvmRU5ENeVfCLPIsEuIz6cTVOg39A7BQAdE+9Dhw40CJwxYZH9QFXfmRKHcaLCBEEuQr01+sOYFn9RWdD5NUCoojBSDQ5Z8W1cYq8SCrCG2DtnZrtAEtjx5jdrutAfOEyEG+MW+PBS5F2eutFVwsSIZ+NzykXgWQU+JcXedsqOSazLs3Ad11OzenW4oCQq5QpNz7IQLg8wj/uhk/EtSo0J5o5cCgcOG7jwyY0oTudX19GwhW/5CUvyfCiy7YuTQ4mtKlJivsrFiKTohCePAMIUSqkqGsmWeDBROHMY08mDmF4I5pXf3npd6CG1U743h4QsBjauvWSKj+3YxBqOxcQVzcgbEyOBNh2dmaxJnIT3xOf+MQMPzsFDoUxxtuIXpfAQsjgIoCKb1dg3OQp/zEJ1xuBQTKkrxdj+LDlyqv3mICvQi775OoLL7UbkANaWb2EPZam5wewwqqmXz3n3YUe5FlsAD6AB+vnmF9VV/LT5+s6wAdERnS5SpYhpoVrBrYAbj6ii2z58wXNfZzr5E0eCBBVVyCEVZSMaIv+VWdlP/OZz0xgAXzgMSAJWPZ8ct60rK/yJsc9eJYWSONvlX4XMvvCCy9M/lg0GR8ADJ7waqHd2iG9hU1EA0s+VZuEwrYYcSb6kksuybC2dY/MRyCRduaZZ9alDQsP8lV1Y3ixSOQiru8foYEtCCwixmOOrKsjkC+kMPA6XlzpX2OxrL0VarcqBNjWONCPPBIUsegK342AwR7A4iNZrgWahUyBYOmN8zPOOCPrLhy5MdIvHPSnhanQ3RH5Md0skpsx4R854Jc6IqdtuK1tZALPuBBjeR+TOiuDzipeVxrP82BirFkEkX/tAnqNeWUjPIELpJNXT+QD79WN/hL2uyeyqmxhlqeI/Frg0R/Gw2ZHP04IBXTBVEbrXLv0ihe3B9z2ie3E4zd3dL5OfnOao4MDJhwTHNEySRwI8DvTzIH9wIF3vOeN7f+1d/8x31Z1HcAvfEAUUOKnLlQeQQGHwgAnW8vJREINcyMt8w9KZTNRkDnS5lY6oWyNXLY5WzplQa0t5tzCBmgizTWHP8oac2n+KLNaGqWpEAin9+s8ni/X97qv73M/9/3cz+/zefbc3+u6zo/rnM855/q8P5/z43P/Q/87nH/qZesW5+ZvPjL86PYPDhdf+uIKMIAZlkiC3kYaVi5CjnMAQpaVDBBhOYm3qyrcHVfFEmFMEAbixSNUFbSmAeXFCkSYAF8sVYQM6xbLE3/3AIuxJH/XhAZrIEFufSBgKgxAMd5Y2VjrCANjjyVP3oQSQen8VsITwHZOJscT8fBVQRMLsLKwHjlTWHk9s66VsPceABN4IKTxhBOGc845p4JygguPWL1Y4KxbpAwDNOrCUmrz6+23315BkbKxanknsA6IKR8LFiEHfLPAEnzKyYrMmkuIOl9WeZSB4HamLsEKRBCAQAYesiBqFzyIp7kKXoBo8ZWVoFVOAllZgDBlideyOlULxLGIsVTZZU4oA0vy9x8QBdbwXD21L+ckrvFD+fQBbRZ3vNW6Kk8AQTuYPgdu9CVnu8pffYBevGJJpfSoG6DOmmuqXT9hCWSlAzwADX3PNb5+/vOfr0oEgEwhoKRwZoE3yqst1B+/ATdKkPfjFfD06le/utZPvb1bH2TpBKzbOlthLMacVmhnVmZtIh/T/voiReK8886rwEQ/AXAAaXxSNsBW/1KuuI+uzzwHmNTDGNImyoBvygfIajN9AEiNu/AKsvBEGhZhQJCFWV8FSimFV199dQWhFAH5KAM+M8xQqowH4/FTGZeUCGNb2+lD8UZYx6V3aH+gDu+MK+mMb3l6RgHSr4wfeV1wwQW1XPhM0dS3xNXH8dTyDfniBd4D8MCgPOIFsNbD+dhve9vbap+xnMI41C/0HbxRJ85S9GP8N/7laWwpP0XGPZ7om/qlMhiL+rWx5rn6iKsdhfulmCnLRVE+vKttJGQZNxb1I/1YPvqNdlEH3yf1VX+zQ+qibVmB9V39Rxxg1fdQ3wW+jT99RnkpJOqkn1E+kPGlH+oPyidv/KBgUMDw82k/+eTho98+fHjxKUcOxx85sfHmQ7hp6i6LN826nrBzoHNgH3Bgoy6LX/myl5QIlBJhWvK9LVnfWUsd61UJwKrX3A9nlmNRm3ykF9cuIrRLLLP1WQRVCfip1/5wX/r2t7+9utWNQFn4qBcWwFdixSixXrhdogj9es81bgBOCYgpXNDGulSfxwpTyxvrVQlwKgEHJQK4xLJVIthKAGF9V4DmIt9Y4ep1LFAlAmXx3EUE0uI+Vq81LngD7EsEaH3nN77xjUXce+65p8hXXQISS0DIIizT2vU6lsESIFrjLAJzEYBUuA0OsC4BOougCPKSjUyL+4DEIq+A4sWzdsHdrnwioEssRiXgpwXVX+0SIV8iVJeeu4l1t7Y9HsZCvCZcfQNcSoBHCcBZhEcAl4C9olwR7CUKSgl4q+6BA94L98mxHpcA3MqzgOOaVhkDCKq744CJRX4uuG1V51i7S0DjIiwgqV4HpM26hh3HFTHAubrKDuBe5NEu9KkAhnqrj0xJ2wVM1v6qHwWYTaOUKBcloK+6Og4IXhM+faBNuKjVR6dkXMSSXN1GBzwtBeufAbEloLQE6CyFuQlgK1FEKt+41dZWjaLULdxX68urKKC4BISVAOEyxy9lj3W7jtFpHsZlgFm57bbbaj8ah2dmYXGrL0zHNxfGUYBLFOviezGlAL2SpYPVPbj8pxQFqPKsPee22jeikXbDuwDg2obNhXILN1ajYLfb6j74kksuWdwHMFe37MYs3o+/IYtIP75QloDkEmV1Kch49k2NElcCbIt2UJ5G+ru0KKB48b3Bb67fo0DVfiNcW/u+jSlAvDx4/w/KKpfFLACbpg58N826nrBzoHNgH3BgI8D30r/5UXn8YUMBVrJusGSqsRA6jRrA9RGOJaJkLWOJ1aPE0tKiLH6zSagCr1hRF8/aBTABfMW60R6t+0uookzzVmAJNANOY5IfgBXr3vhxrQtQhoCORq4JIYCh5d/CgD8AVd0I3SkBqEBYrGBLQYRZLGAVcMYqthRGYBJqQNa4HC2S8gOtmXptj+qvsgG5BCOQjefeD3RNCaCKta+C51irKr/GcZQv61urcjJ+7hovstSjxFpWhfQ0PFbFCmqmwAuwAPpifa/AJcsSFoBfGCBGeE+BI2BJoaKUzFEswmsUkgbI8WSa31weO3sGjFDuskSlgom5uMAgoL8zUo5dLU8s7BU8UbamRGEEEvXhubrF+ll5STmco1ibSyyVaxQiwO6uu+6qSeJhby7p4tk73vGOxfXcRWZNqiIxDQPI9bdYjNf03ywjqWm0HVAa6/FScv047qRrXxiDwaVIuZmOixYOpOt7wDdl2Hdhyj9g25jOkqU6Bltav+KqV5bK1PFO+chsxThK0W6+eRSSnZVRuHc05W4pk9zE2l6/T3N5yN/3RFnG5Rc3syUlFug6/rKeuI63cd7Sves3f6MD3zFT+nXnQOfAocmBjQDfSz79YHnpCx8V8mPQO+YeMMjCwGrIIjf3ESd8Ms1chc04rWtWw90lgGkVTQE1sNzA+RhwZqlELeNcPVkUCUogfQqwV73XcwIr0+Ilu9nXgClWcgA260Bns2DZBW7xdI4yHVqyHrgK4TmeSwMUA76Zdq3xpvkon/eMLdHjOAQ8ELGKdmbtYonyf09SA75b9Q7W6jkr4zj/qXIzDtvKa4DQrIqxNUfaNVP6c0H1Gcsk4JklCmviUCIyHb9uXdck3MAD1nbAdkoAJYUsywrqLIzZmq0mFl4A22zJHFFMgP4suViyBre4vhGssGZyWJ83S4DvRr4X4/cA8GZAWH9Xke9HllUtzQiJq37XXfvm8rK7/qd85XuPWpJbPt3i2zjRf7eUAwYOrXc8RbmlL+iZdQ5sggMbBb4vv/RFu/QWlqmsaV0Z19IDAmC6hGBlgr0UMAa+673S9CegtwpkrkoPPE6nU8dxgdc5AkopE6umzFkfWad3RtlMVYM3K3wlZrHdX2mrge/+Vk/1A8bnSP/wfzPEqro7gG4z7xynufXWW+vyJ+NvTwDf8btWXQPFxo+Zi1Wk77PYbpZ2B/h6JxyxirS92RZLQ+bo4QcfWGnxPdxC4U6dA1vJARsoLMJPx6wL1+2GtpC9U+fAwcqBtuliVf1s3LDZ40Amm1s2QzaixOK7Mmk7K3YawUYfG2f8zpENSTZcrUe+Q7vDexuIOu0bDtiAZTPUHK3qF3Nxp89sfnJKwL4iGzTR9DzivVmerC+ePWd3XAab1tpxZOPne+t6errD+L3aP+vAx4+Wrh9zxJG5n/cfMNnqtpSu33QObJgDjrKxs5KwQZlyqOcqZpPLhvPqCToH9hcO3HN3TnL4qbOGmz7y8eErd75/+PV3/95w75e+tSjeDa/9ueH6P/rgcN4Fvzr88e+9YbjkzX8wfPberw5Pv+Cy4eN3f3a474Ed42GR4BC6IKCcfrCKdgZgdhYmv/XCV71zI8/3xjs2Up5DLW6seYdalfdKfY1JfXtn/Xtfgt49yYQOfPckdw/BvLO0YbbWjrnp1DlwoHLgeS+4aHjq8Y8bLrv8kuH6G353+Nrf/93wvo/eNdz7uU8PX/zad3JE0MPDMTn26/HPOG14bAT1Vz539/CfMTb88LvfHP7iE58cjnhs/9QeqG0/Lnc2BdXjoMbP+vX+w4EOkvefttifS9K/xvtz6xyAZeMvfU6D7A4sDsDG7EVe4kD2zQ+PxPj01ON+YvilKy4f7vjIh4ezn/vTw7mnnTg8+NBjhlOOK8O/fvPLw//98P7h/J9/0/CiZz95eOCJzxrec/3bhif0L+0SLw/UGw4EnHE8R8597bRnOADQmj2co2xMrOceO4d3leFlLt2eeNZmOvdE3vtDnqsUizmHMtPyrmq/aby9cd8/x3uDy4fQOxy4nl2WSzXmwSnnAC496zedAwcaB2780O3D8Vlu+lu3fno465TThs988mOLKlx74/uGy174yuGvP3Tt8Pwr3jm862dOHP79uw8N//CX7xv25kaKJpja76KAm7jIprR6yP0mkh7QSXLixWz5s1GnOvrIjvw14dnwVx0e7GzNIWcJ9j8AanuSOCzYarLWlocuTiA2QoBgNihtJMlsXG3CKYJfTiHGxIkBZyA8jvEgN0c5iaI6nDHafl4AABB8SURBVJgL2+izVa7IOWihGM2RcuHhgUq+JxyPXHfddWuqwHGEtfg8H/LmOCXLJbj5hguyqXAavE/uO/DdJ2w/uF/64XiU4g3G5oHsWh1yyPbBXeFeu4OWAzbW8JLFc9ctf/bnO0DsEUcPzzrn3OGkJzyuemNS+ZNPedpw1LZh2H7Ws4fTtj89npmeM3zitluHX3vzVdUz1N5iEFDF29RWgB9gjheqHGO2qeIDJNm9vuG0XI965xTgbDijJLCpcCMEqPE4xwPeWHlgrbJci5c0nqsI8jHx3sbjFK9f+DYlefFOxbseoLAnCTjxDZ4j4CSOTNaAUW5yeRHjrW+OuN21yY/HtSnpczwVcqM8pZyDWz22TZ+7n/KJV7U54GoGEejybh7PpgCSQqLPGKtzSgtLPNfJY1fAc+XxjIfAVcRNdxyl1A1pUwunPSxXXnll3czNLfLYupkzg+vmSt5M50jfUIcc37UmOEcRVu9pawLyYNw/eZ8zE2Gz3PjdLZ1nXBtrY0rCKprytsXjcQ7g500txx22x/U3513XvmHDHo9vPOohY4myhB82/+Y88erSmjfDPUF4aLMr7LEedeC7Hod6+KY4wKUh96s5HH5T6XuizoF9zQEuSLld5YIToJkjrm+5gp0SQUHAcDHM5WmO1ZpGqQBo1ZpRQmNu2lZehP973/veJcHXMs+Zt9UVLUG4K9SWJc0JI+9QDoCD9XeO4sluzQyPeEANAM716JyVZyo8x3l7F5AyBwQARyCMBW8VqQve5Zi0mo92nJJyabspEc6smnGMsQQg8CFHolV3yNwp6xdjUt6TTjqpAiPun6eET8AS4Dl3Aoi6cis8F6Y8lIgx4S8+tfYTRlEAMri8BYC8c0zxUlcVIgB2GhbnKxUYcU2rz06J1fb9739/dcs7NmRoR4CXNTuOTapr4ZYWAHJ6gjKxhk5BVRzCVJfS4ue85upyl0vjaV21X+tD2nS6pAS44moXkTsNeNUH+UPh4PKWq+dVpL25OLYxew44Spdzb6vLayeUxGnCUlbcK1OOueT9etxKj5U2vAa81RefpwRQ+g5wyX3LLbcsgoFe/HjKU55S27QF+N7oK2YX1F0bcCtu7FPIphvJAeScyVvdXzttSfmby+GWp/7kG0VRmSN1AHq5hh6fcqLd49im9n1uidVPfYwXSq88zfZyXc01MVfSOb+7fvvi/a/ee5++TIHSx+aUF2MHwI7zkbni1fHOJbjN9VxxzylQ44Rrvwjj0H7dOdA50DlwiHLAxzvuioeLLrqociAeq5aEro88IHPCCSdUgThmEwHNwoJYguKFahxchSvrEUEbd5tLYQTn6aefXv3Pmx7MWaaLcAKC4CC4pkcEAjY59L/GPe644xZp2oX6TMHeW9/61ipA4wxgyZJDWAIYgBWhPQVK8nQcEoAdL3CDI8vGRAirR9z+LuUrzlve8pbhjDPOGEdfXJ9//vnVin7FFVdUy+Qi4McXLEosSxSAOQKaLLeypCBnDlcwMxakBGjcCQ/HHntszWcMUIBp4IWA1yaOYWxEKAMh6JhjjhnignhhOcMrQNtzFvILL7xwMRMgPiDFCAD8AYLxBDewEI8JOGOJBc6A+0asyCyN8XpXQURrhzhlGOJcYKBgNYpThgoO3AMdLI1jiiOR4YYbbqhWTUBtTOoO8NqjMQWe4sW9bI2ufE0h05/0c8fRKf+55567NNMATLIga2vrb5s1Fc+BJ4rRNddcU/Nt1sS46R30yTHpgw2MAtcNBIuDVxSORsbU2BpLSWlW7Jz5OsQjWotaf+UFnDnuDuhUH5bDKeGz9AAm0k+bYqb940BmeOYzn1nD4lRhAFobNcBvqQagOCYnKwCljg0DaLUDvuIn66Wxrq/rL8A7HsvbtT5sDEpHOTj55JPrLCulbkxNiRQXANUe8Q5YAWqLpy6+RcbsHOkv3qFs+p7vENIXmrImPA5Fhg984AN1xsF3Kx4vK9AWVzvecccdtQzGMQs1MKuurOGOLjN+GMvGY1Z9vROvtNWc5TznEVdgbakJQ8WqeigHOiyNVnZcbvzv1X/69OHGX7h3OPLwozaeuKfoHOgc6BzYyxz4yBeuH+77wbeGK5//h+u+OS6Lh++98bzhnb9zY7WuEv6sXa961auqEAA0LwooNrXm48ySYokBAURo+UC3zyvBxRoBxGzfvn0AollAWJkIXICVtcXHnSAx1c4KRKAScK6f97znVWBmzbx1c4QRIWda25Q+IckaLIyAYykCoFnDCAICHYg13ckqCUz4JXxYST4V4PX617++PgfqzzzzzOHoo4+u1iv5ATgsLuISRITwqaeeWkFA3IrWcgAwBBwLHsBBkKsXqyAeAV9+WdDjWWoAuJU9HrpqWYBGwFAdgOYm5AA+7wQQ4g2tTn2zrrF4qRtwYCkC/hHwyk1Is+DGbevwpCc9qSofeMZqZbMtMAuMOp8YgFIvvAaMgRVA551pRwId/wFN0+nqR/Cz6OMRPlJyCHl5spBrWwBc+7OmsXTpK8rEMgUwvOAFL6j34uALga//WOZBQQFclY+Co1yeAyyuWZ8taVC/1j/UWb/Bc3my+rK2qouy6kv4qwwAID7jvXz9sjiqC4VB2Sh02sXaWcDw7LPPrrwAquUrf6ATiPE+aYVZAw3csjxT+rSld8pHOv2QoqS+LJT6g3vKnPa0TlR/MzYoIe7jyKTe4z1e6tNAsjBt2zZPC9e/taW+yspqeYo20G/MFiifdlRGCg7lFu/0HWVVPoqNJS+WWOgbwox77esd+KmdWTPjcruOfTwUBvBLgy+AtO+Bugnz/aDMeL8lL+pvTAJ93s166huBl74RTYH1DP/0XX1O/fXLxnN93vfJO/BHPwey9UHvMq7VX7i0n8pYx5Ozzjqr9m1AmjVYfurjW6Pcvh/GFqUIuGz9Wx3jHa72EeMQyVs/0Ed9P3wv1Acv9aMWx6/yAeDeRyECdLWnPqZcyqDvqCMF3LdMXZTTd8CyGGm1vbrgvXb0fuUwdo4/9gnD3Re+Yfj95z5xeMYTttX3L/4k4qbpTX+yvTzw0A82nb4n7BzoHOgc2Jsc2KjntstfeulS8bjxbMTtaaNYrhZugAMq1rgBzUe6xDJTo0dollgTW9L6GwFePZSN8xxHiACf9QzHq1WAS43Kd/2Ysha1BECUTMuXgK6SJQA1mBtgZVDmAIFFkpY+QGmNq9UI3ur2N5bYElBWItwW6VxEEJZYbuoz7pPH+XpXwEQNi8Cqv+2Psql7hFqJsGyP62/WbVZPd/KLJXIRFmBXIpBLFIYSJaFEOJYA4xJL3yJOu1BeLo95f8PbgIMWVH95r8LDCM3qXW7sYjjTpQs3x1ddddVSOjwKuKrP8DVgdik8lqnFfUBfiXK0uHehTI2yMWipvwRsl4CjEsFfAupbtOpWOSBgyZOW+mdqeyl9SxCwUgLGa7rMTLTH9TfTzEUdlIt3vCm1vqoMmX5eCs5Sgurta/pcpACOElBT3cyO+0DLQD8MeGq3O/0NoKl84t53SvqafmM8ar8pCW/jYhwWMFYCqkqUx5J1yeWmm24aBy+ueXUzjpV3FeFpgF2JYrcmSkB9fTbuBx4E6NZy6zMB5NV7W6zJa9LvzoMoZYvkUbYX19OLKO7VdXIA75JbYOMQj6LMlsw4FeNwSsberlBAav3W7ErccRz9KIpLfRQFaxxU8OsVr3hF8TwW5JJZmqXwdnPNG99QLrvrv7vL4saQ/ts50DlwaHJgo8B36rI4VqISS2YFjZkmXTAxU4VVCANlsVSuAYaLiCsuAOPXvOY1JVPhK2LMPwaqCP+bb765gr9xrFhSSqaUK0AkyBopYywf9XkDpMIIY8IkFrM1ADEWzzIGhS2v8a96IyCZwGsUC07JFHl1LxrLd3tcf2PRrYJ1zMsWATCLVajEkr0EpFv4xRdfXLJsogKpTM+3x0u/2ZhYQXcseiWWxaWwdhOr3axwJnwB6li8SqyXLXr9xfdY0eo18D7OW1vGCraIn6nmNaA+lr8KVikFU3AkIVC3K7Sey+Lt27fXOgDBUwK8ADHtM6VM11cA25SZcTh+xMI4frS45hoaKMn60xKr5+J5u+ACd1cJH7O0YaFQjdMJi/W6APAbIekakALAgfg50r5A/85Im8ciPRsFv4FqwGxKseBXRUnbU3qaAjWNtzfujXl9fI4oVZSY3SHfl824C8+65cob786s0GwfpQRm1qh8faQcTsv6s391Xwe+U6b0+86BzoFDiwO7C3wJxEwhFhbYKWWKsT7Kutdp0C7dZ/q7ZNnBLsUdRwJcCNCNULMK5dSVpWSsnMDk1DK6FGnFTabIKwDP0otCQRhTpjLXWLmFs5ZlOnkcdekaP3I6zNKzdqPeWVrRbmd/gUpt5v2riCIgzpTwKFPhBUid1kdc1vRMYZe59hafZRw1gFxvRn9YkYGjVaB9FHXl5XrAl9WU8gDgTAkInKu3eMIA3DlQLHwM9N2PyWwAZWAriLURCNoXtIo347Lg0xxliUpVLudALf40hXNfA9+5srdnq9q+he/K72aBr/5l/GRpw6aAcyvbKuB7+GLNQ7/oHOgc6BzoHNgpB6wfs95s7jxL62utQ7PjejNkvaSNGRsl60nbBp5dTWvd3xxZ/2iD16rwuTTtmXW7sVTWdYjWRI7JWkUbzqaUaf3po6V7/LBpa47Uu202mgtvzyIEF2sl27Pxr7WVc2QtZKxyde3ktD7iO8LLWtK2QWuch/jW09rUZkPWHOHHZvg8l9eqZzbFOVbSetkpWT+5ioRZm7mKbORbRdZu+r8VFPBZ121uRV4bzcNYX49W8dB6YP1jju9byZ/1yrc74cbXviL9y1rmzPrUdcRbXY75Eb/LbynD17/zheGx247c5RQ9YudA50DnwL7iwPce+PZQ8m/XKILv4UePzfq3L//t8MiJzxqecvyRw4k5xOCr//Jfw+lPO2FHVvffN/zjl/5puPNjdw6nnfnU4Yuf+8yw7bFHDSccs234j/t+ODzx5O2J++ju8117/56PtS3e6MZkk41NIpshG6D832pyasRm6bBHfpQNMusDmLn8gZrXv+619SzyuXAbauZAb4trM9DrfvmK4Rff/dvt0dLvVoDeafstvSA3yugUjAOVHlMeHo5Yjc/362pRkNcj7Xf4Ybv6PVovt/0vfNvwyHDE5obfcPnLX1ZP6HBSx1bTbp3q8J47Lx++8/1/3uoy9fw6BzoHOgf2CAcejiC96IxfGV7ynGvXzf9FH79vOOqIfLpjdUKHsZBFUMWAWHcO+55ngryGDbl5zGE7JPQjibPjegfEPkxg4i3i7kixX/xl1WIRPVgJ6M0qht2rnobezSx2rwCrUx/s7Xco1E/nOliHYG0/g2eT44fRfXd4Q+d9z8ypDrsFfFcPxx7SOdA50DlwYHPga99/eHh4kx/sA7vmvfSdA50DnQMHBwe2H71tzaxBB74HR9v2WnQOdA50DnQOdA50DnQOdA6sw4EDdPXMOrXqwZ0DnQOdA50DnQOdA50DnQOdAxMOdOA7YUi/7RzoHOgc6BzoHOgc6BzoHDg4OdCB78HZrr1WnQOdA50DnQOdA50DnQOdA50DnQOdA50DnQOdA50DnQOdA50DhyIH/h/fdGre8U4aagAAAABJRU5ErkJggg=="}}},{"cell_type":"markdown","source":"![Picture1.png](attachment:33602920-7854-49a8-85d4-58911acf5b70.png)\n![Picture2.png](attachment:d7896f4a-a3bb-4b84-aab1-025ee4a84e4f.png)\n![Picture3.png](attachment:a59c8a5d-70cc-4c5d-a62d-edb19ea23f61.png)\n![Picture4.png](attachment:23915d78-4ae1-4458-9fa6-9b8ff8dbc598.png)\n\n*Figure 2: Metrics describing the TUH-EEG corpus. [1st] histogram showing number of sessions per patient; [2nd] histogram showing number of sessions recorded per calendar year; [3rd] histogram of patient ages; [4th] histogram showing number of EEG-only channels (purple) and total channels 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"},"d7896f4a-a3bb-4b84-aab1-025ee4a84e4f.png":{"image/png":"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"},"a59c8a5d-70cc-4c5d-a62d-edb19ea23f61.png":{"image/png":"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"},"23915d78-4ae1-4458-9fa6-9b8ff8dbc598.png":{"image/png":"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"}}},{"cell_type":"code","source":"! pip install pyedflib","metadata":{"execution":{"iopub.status.busy":"2024-02-23T16:47:08.139519Z","iopub.execute_input":"2024-02-23T16:47:08.139954Z","iopub.status.idle":"2024-02-23T16:47:26.722808Z","shell.execute_reply.started":"2024-02-23T16:47:08.139919Z","shell.execute_reply":"2024-02-23T16:47:26.721714Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"import os\nimport pyedflib\nfrom pathlib import Path\nimport pandas as pd\nimport numpy as np\n\nSAVE_DIRS = ['eeg_raw', 'eeg_10min_spec', 'eeg_50sec_spec']\n\nfor directory in SAVE_DIRS:\n    if not os.path.exists(directory):\n        Path(directory).mkdir(parents=True, exist_ok=True)\n        \nDATA_DIRS = ['train', 'dev']\nREF_DIRS = {'01_tcp_ar': 'REF', '02_tcp_le': 'LE', '03_tcp_ar_a': 'REF'}\nFREQUENCY = 200\n\nSAVE_SEIZURES = True\n\nSAVE_EEG_RAW = True\nSAVE_SPEC_10MIN = True\nSAVE_SPEC_50S = False\nSAVE_SPEC_50S_NPY = False\nSAVE_SPEC_10MIN_NPY = False\n","metadata":{"execution":{"iopub.status.busy":"2024-02-23T16:47:26.726347Z","iopub.execute_input":"2024-02-23T16:47:26.726785Z","iopub.status.idle":"2024-02-23T16:47:27.217530Z","shell.execute_reply.started":"2024-02-23T16:47:26.726745Z","shell.execute_reply":"2024-02-23T16:47:27.216534Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"## Load Data","metadata":{}},{"cell_type":"code","source":"# used for column arrangement \nspec_comp = pd.read_parquet('/kaggle/input/hms-harmful-brain-activity-classification/train_spectrograms/9661509.parquet')","metadata":{"execution":{"iopub.status.busy":"2024-02-23T16:47:27.226585Z","iopub.execute_input":"2024-02-23T16:47:27.226859Z","iopub.status.idle":"2024-02-23T16:47:27.447683Z","shell.execute_reply.started":"2024-02-23T16:47:27.226832Z","shell.execute_reply":"2024-02-23T16:47:27.446300Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"import os\n\ndata_dict = {}\nfor directory in DATA_DIRS:\n    for dirname, _, filenames in os.walk(f'/kaggle/input/the-tuh-eeg-seizure-corpus-tusz-v152/edf/{directory}'):\n        for filename in filenames:\n            if filename.split('.')[-1] == 'edf':\n                dir_split = dirname.split('/')\n                fn = filename.split('.')[0]\n\n                with open(os.path.join(dirname, f'{fn}.tse'), 'r') as file:\n                    for i, line in enumerate(file):\n                        # events start on 3rd line.\n                        if i >= 2:\n\n                            info = line.strip().split()\n                            data_dict[f'{fn}_{i-2}'] = {\n                                'path': os.path.join(dirname, filename),\n                                'reference_type': dir_split[6],\n                                'group': dir_split[7],\n                                'patient_id': dir_split[8],\n                                'session': dir_split[9],\n                                'start_time': float(info[0]),\n                                'stop_time': float(info[1]),\n                                'class_code': info[2],\n#                                 'unkown_feature': float(info[3]),\n                                'directory': directory\n                            }","metadata":{"execution":{"iopub.status.busy":"2024-02-23T16:47:27.452263Z","iopub.execute_input":"2024-02-23T16:47:27.452653Z","iopub.status.idle":"2024-02-23T16:48:28.042604Z","shell.execute_reply.started":"2024-02-23T16:47:27.452622Z","shell.execute_reply":"2024-02-23T16:48:28.041475Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"## EDA","metadata":{}},{"cell_type":"code","source":"df = pd.DataFrame(data_dict).T\ndf['event_time'] = df['stop_time']-df['start_time']\ndf['EKG'] = False\ndf['processed'] = False\ndf.index.name = 'id'\ndf.reset_index(inplace=True)\ndf['missing_data'] = 0.0\n\nprint(f\"There are {df['patient_id'].nunique()} patient ids.\")\nprint(f\"There are {df['session'].nunique()} recording sessions.\")\nprint(f\"There are {df[df['class_code']!='bckg']['session'].nunique()} sessions with seizure events.\")\nprint(f\"{(df['class_code']!='bckg').sum()} events have been labeled seizures.\")\nprint(f\"{(df['class_code']=='bckg').sum()} events have been labeled baseline/non-interesting events.\")\n\ndf.head()","metadata":{"execution":{"iopub.status.busy":"2024-02-23T16:48:28.043795Z","iopub.execute_input":"2024-02-23T16:48:28.044831Z","iopub.status.idle":"2024-02-23T16:48:28.618894Z","shell.execute_reply.started":"2024-02-23T16:48:28.044796Z","shell.execute_reply":"2024-02-23T16:48:28.617603Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"df.class_code.value_counts().plot(kind='bar', title='All Event Labels');","metadata":{"execution":{"iopub.status.busy":"2024-02-23T16:48:28.620500Z","iopub.execute_input":"2024-02-23T16:48:28.620925Z","iopub.status.idle":"2024-02-23T16:48:28.942447Z","shell.execute_reply.started":"2024-02-23T16:48:28.620883Z","shell.execute_reply":"2024-02-23T16:48:28.941421Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"if SAVE_SEIZURES:\n    # save seizures only\n    df = df[df['class_code'] != 'bckg']\n    df.class_code.value_counts().plot(kind='bar', title='All Non-Background Labels (Seizures)');\nelse:\n    # save non-seizures\n    df = df[df['class_code'] == 'bckg']","metadata":{"execution":{"iopub.status.busy":"2024-02-23T16:48:28.943654Z","iopub.execute_input":"2024-02-23T16:48:28.943961Z","iopub.status.idle":"2024-02-23T16:48:29.243493Z","shell.execute_reply.started":"2024-02-23T16:48:28.943933Z","shell.execute_reply":"2024-02-23T16:48:29.242338Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"df['event_time'].plot.hist(bins=100, title='Length of Recorded Seizures', xlabel='Seconds');","metadata":{"execution":{"iopub.status.busy":"2024-02-23T16:48:29.246605Z","iopub.execute_input":"2024-02-23T16:48:29.246952Z","iopub.status.idle":"2024-02-23T16:48:29.683787Z","shell.execute_reply.started":"2024-02-23T16:48:29.246921Z","shell.execute_reply":"2024-02-23T16:48:29.682560Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"The dataset contains very long recordings of seizures, but most are under 10 minutes.","metadata":{}},{"cell_type":"markdown","source":"## Functions","metadata":{}},{"cell_type":"code","source":"INCLUDED_CHANNELS = [\n    'EEG FP1',\n    'EEG F3',\n    'EEG C3',\n    'EEG P3',\n    'EEG F7',\n    'EEG T3',\n    'EEG T5',\n    'EEG O1',\n    'EEG FZ',\n    'EEG CZ',\n    'EEG PZ',\n    'EEG FP2',\n    'EEG F4',\n    'EEG C4',\n    'EEG P4',\n    'EEG F8',\n    'EEG T4',\n    'EEG T6',\n    'EEG O2',\n#     'EEG EKG1'\n]","metadata":{"execution":{"iopub.status.busy":"2024-02-22T20:51:11.009198Z","iopub.execute_input":"2024-02-22T20:51:11.009563Z","iopub.status.idle":"2024-02-22T20:51:11.016440Z","shell.execute_reply.started":"2024-02-22T20:51:11.009505Z","shell.execute_reply":"2024-02-22T20:51:11.015326Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"def get_signals(edf, orderedChannels):\n    samples = edf.getNSamples()[0]\n    signals = np.zeros((len(orderedChannels), samples))\n    for idx, ch in enumerate(orderedChannels):\n        sig = edf.readSignal(ch)\n        signals[idx, :] = sig\n    return signals","metadata":{"execution":{"iopub.status.busy":"2024-02-22T20:51:11.018075Z","iopub.execute_input":"2024-02-22T20:51:11.018471Z","iopub.status.idle":"2024-02-22T20:51:11.026003Z","shell.execute_reply.started":"2024-02-22T20:51:11.018433Z","shell.execute_reply":"2024-02-22T20:51:11.024847Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"def get_channels(file_name, labels_object, channel_names):\n    labels = list(labels_object)\n    for i in range(len(labels)):\n        labels[i] = labels[i].split(\"-\")[0]\n\n    ordered_channels = []\n    for ch in channel_names:\n        ordered_channels.append(labels.index(ch))\n    return ordered_channels","metadata":{"execution":{"iopub.status.busy":"2024-02-22T20:51:11.027527Z","iopub.execute_input":"2024-02-22T20:51:11.028149Z","iopub.status.idle":"2024-02-22T20:51:11.037032Z","shell.execute_reply.started":"2024-02-22T20:51:11.028112Z","shell.execute_reply":"2024-02-22T20:51:11.035983Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"from scipy.signal import resample\n\ndef resample_signal(signals, to_freq, window_size):\n    num = int(to_freq * window_size)\n    resampled = resample(signals, num=num, axis=1)\n    return resampled","metadata":{"execution":{"iopub.status.busy":"2024-02-22T20:51:11.038546Z","iopub.execute_input":"2024-02-22T20:51:11.039338Z","iopub.status.idle":"2024-02-22T20:51:11.735452Z","shell.execute_reply.started":"2024-02-22T20:51:11.039310Z","shell.execute_reply":"2024-02-22T20:51:11.734018Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"import librosa\nimport pywt\nimport matplotlib.pyplot as plt\nUSE_WAVELET = None\n\nNAMES = ['LL','LP','RP','RR']\n\nFEATS = [['Fp1','F7','T3','T5','O1'],\n         ['Fp1','F3','C3','P3','O1'],\n         ['Fp2','F8','T4','T6','O2'],\n         ['Fp2','F4','C4','P4','O2']]\n\ndef spectrogram_from_eeg(eeg, display=False, offset=None):\n    \n    # LOAD MIDDLE 50 SECONDS OF EEG SERIES\n#     eeg = pd.read_parquet(parquet_path)\n\n    if offset is None:\n        middle = (len(eeg)-10_000)//2\n        eeg = eeg.iloc[middle:middle+10_000]\n    else:\n        eeg = eeg.iloc[offset:offset+10_000]\n    \n    # VARIABLE TO HOLD SPECTROGRAM\n    img = np.zeros((128,256,4),dtype='float32')\n    \n    if display: plt.figure(figsize=(10,7))\n    signals = []\n    for k in range(4):\n        COLS = FEATS[k]\n        \n        for kk in range(4):\n        \n            # COMPUTE PAIR DIFFERENCES\n            x = eeg[COLS[kk]].values - eeg[COLS[kk+1]].values\n\n            # FILL NANS\n            m = np.nanmean(x)\n            if np.isnan(x).mean() < 1: \n                x = np.nan_to_num(x,nan=m)\n            else: x[:] = 0\n\n            # DENOISE\n            if USE_WAVELET:\n                x = denoise(x, wavelet=USE_WAVELET)\n            signals.append(x)\n\n            # RAW SPECTROGRAM\n            mel_spec = librosa.feature.melspectrogram(y=x, sr=200, hop_length=len(x)//256, \n                  n_fft=1024, n_mels=128, fmin=0, fmax=20, win_length=128)\n\n            # LOG TRANSFORM\n            width = (mel_spec.shape[1]//32)*32\n            mel_spec_db = librosa.power_to_db(mel_spec, ref=np.max).astype(np.float32)[:,:width]\n\n            # STANDARDIZE TO -1 TO 1\n            mel_spec_db = (mel_spec_db+40)/40 \n            img[:,:,k] += mel_spec_db\n                \n        # AVERAGE THE 4 MONTAGE DIFFERENCES\n        img[:,:,k] /= 4.0\n        \n        if display:\n            plt.subplot(2,2,k+1)\n            plt.imshow(img[:,:,k],aspect='auto',origin='lower')\n            # plt.title(f'EEG {eeg_id} - Spectrogram {NAMES[k]}')\n            \n    if display: \n        plt.show()\n        plt.figure(figsize=(10,5))\n        offset = 0\n        for k in range(4):\n            if k>0: offset -= signals[3-k].min()\n            plt.plot(range(10_000),signals[k]+offset,label=NAMES[3-k])\n            offset += signals[3-k].max()\n        plt.legend()\n        # plt.title(f'EEG {eeg_id} Signals')\n        plt.show()\n        print(); print('#'*25); print()\n        \n    return img\n","metadata":{"execution":{"iopub.status.busy":"2024-02-22T20:51:11.737126Z","iopub.execute_input":"2024-02-22T20:51:11.737458Z","iopub.status.idle":"2024-02-22T20:51:11.844478Z","shell.execute_reply.started":"2024-02-22T20:51:11.737426Z","shell.execute_reply":"2024-02-22T20:51:11.843181Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"from scipy.signal import spectrogram\nfrom math import ceil\nfrom functools import reduce\n\n# ordered to align with competition spectrogram columns\nNAMES_10MIN = ['LL','RL','LP','RP']\n\nFEATS_10MIN = [['Fp1','F7','T3','T5','O1'],\n         ['Fp2','F8','T4','T6','O2'],\n         ['Fp1','F3','C3','P3','O1'],\n         ['Fp2','F4','C4','P4','O2'],\n]\n\ndef spectrogram_from_eeg_10min(eeg_df, sr, display=False, offset=None):\n    eeg = eeg_df.copy()\n    \n    if display: plt.figure(figsize=(10,7))\n    signals = []\n    dfs = []\n    for k in range(4):\n        REGION = NAMES_10MIN[k]\n        COLS = FEATS_10MIN[k]\n        vals = []\n        for kk in range(4):\n        \n            # COMPUTE PAIR DIFFERENCES\n            x = eeg[COLS[kk]].values - eeg[COLS[kk+1]].values\n\n            # FILL NANS\n            m = np.nanmean(x)\n            if np.isnan(x).mean() < 1: \n                x = np.nan_to_num(x,nan=m)\n            else: x[:] = 0\n\n            # DENOISE\n            if USE_WAVELET:\n                x = denoise(x, wavelet=USE_WAVELET)\n            signals.append(x)\n\n            frequencies, times, Sxx = spectrogram(x, fs=sr, window='hann', nperseg=400, noverlap=0, nfft=1024, detrend=False, scaling='density', mode='magnitude')\n            freq_idx = [i for i, fr in enumerate(frequencies) if 0.5 < fr < 20]\n            \n            vals.append(Sxx[freq_idx, :].T)\n\n        times_series = [int(t) for t in times]\n        col_names = [f'{REGION}_{round(fr, 2)}' for fr in frequencies[freq_idx]]\n        # Convert the list of arrays into a single multidimensional NumPy array\n        stacked_arrays = np.stack(vals)\n        # Compute the element-wise average\n        elementwise_mean = np.mean(stacked_arrays, axis=0)\n\n        df_spec = pd.DataFrame(times_series, columns=['time'])\n        df_spec.loc[:, col_names] = elementwise_mean\n        dfs.append(df_spec)\n        if display:\n            plt.subplot(2,2,k+1)\n            sig = df_spec[col_names].fillna(0).T.values\n            sig = np.clip(sig, np.exp(-4.0), np.exp(8.0))\n            # Compute the logarithm of the array\n            sig = np.log(sig)\n            # Normalize the array\n            sig -= np.mean(sig)\n            sig /= (np.std(sig) + 1e-6)\n            sig -= sig.min()\n            sig /= sig.max() + 1e-4\n            plt.imshow(sig,aspect='auto',origin='lower')\n            \n    if display: \n        plt.show()\n\n    merged_df = reduce(lambda left, right: pd.merge(left, right, on='time', how='inner'), dfs)\n    # not all rounded frequencies used to generate column names are in agreement with competition data.\n    merged_df.columns = spec_comp.columns\n    return merged_df\n","metadata":{"execution":{"iopub.status.busy":"2024-02-22T20:51:11.846289Z","iopub.execute_input":"2024-02-22T20:51:11.846854Z","iopub.status.idle":"2024-02-22T20:51:11.866478Z","shell.execute_reply.started":"2024-02-22T20:51:11.846821Z","shell.execute_reply":"2024-02-22T20:51:11.865554Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"## Process Data\n* Only want 20 channels, 19 if EKG if not available.\n* Resampled at 200 Hz\n* Save 50 second sample and spectrogram\n* Save 10 minute spectrogram","metadata":{}},{"cell_type":"code","source":"eeg_specs_50s = {}\neeg_specs_10min = {}\n\n# loop over each file path\nfor edf_fn, dfs in df.groupby('path'):\n    with pyedflib.EdfReader(edf_fn) as f:\n        # assuming all sample frequencies the same...Not true for all signals, but appears to be true for signals of interest.\n        sample_freq = f.getSampleFrequency(0)\n        total_recording_len = f.readSignal(0).shape[0]\n        total_recording_seconds = total_recording_len/sample_freq\n        # use to verify all 20 signals in session\n        signal_labels = f.getSignalLabels()\n        \n        # EKG not always present\n        if f\"EEG EKG1-{REF_DIRS[dfs.iloc[0]['reference_type']]}\" in signal_labels:            \n            orderedChannels = get_channels(edf_fn, signal_labels, INCLUDED_CHANNELS + ['EEG EKG1'])\n        else:\n            orderedChannels = get_channels(edf_fn, signal_labels, INCLUDED_CHANNELS)\n\n        signals_ = get_signals(f, orderedChannels)\n        \n    # loop over all labeled seizures\n    for idx, row in dfs.iterrows():  \n        signals = np.copy(signals_)\n        start = row['start_time']\n        end = row['stop_time']\n        VERIFY_SIGNAL_LABELS = [f\"{ch}-{REF_DIRS[row['reference_type']]}\" for ch in INCLUDED_CHANNELS]\n        if len([l for l in VERIFY_SIGNAL_LABELS if l not in signal_labels]) > 0:\n            continue\n        # First try to center on mean time of seizure\n        seizure_mean_time = start + (end - start)/2\n\n        # need to make sure the 10 min and 50 sec are aligned.\n        if total_recording_seconds >= 50:\n            # might need to verify that shifting 50 second signal does not violate boundaries\n            print(row['id'])\n            \n            spec_cutoff = 300\n            sig_cutoff = 25\n            if seizure_mean_time < sig_cutoff:\n                # move middle to sig_cutoff, and check that seizure has not ended.\n                if end > sig_cutoff:\n                    df.loc[idx, 'processed'] = True\n                    eeg_start_idx = 0\n                    eeg_stop_idx = round(2 * sig_cutoff * sample_freq)\n                    spec_start_idx = -(spec_cutoff - sig_cutoff)\n                    spec_stop_idx = round((sig_cutoff + spec_cutoff)* sample_freq)\n                else:\n                    continue\n            elif seizure_mean_time + sig_cutoff > total_recording_seconds:\n                # move middle to total_recording_seconds - sig_cutoff, and check that seizure has started.\n                if start > total_recording_seconds-sig_cutoff:\n                    df.loc[idx, 'processed'] = True\n                    eeg_stop_idx = total_recording_len\n                    eeg_start_idx = eeg_stop_idx - round(2 * sig_cutoff * sample_freq)\n                    spec_stop_idx = total_recording_len + (spec_cutoff - sig_cutoff)\n                    spec_start_idx = spec_stop_idx - round((spec_cutoff + sig_cutoff) * sample_freq)\n                else:\n                    continue\n            else:\n                df.loc[idx, 'processed'] = True\n                eeg_start_idx = round((seizure_mean_time - sig_cutoff) * sample_freq)\n                eeg_stop_idx = round((seizure_mean_time + sig_cutoff) * sample_freq)\n                spec_start_idx = round((seizure_mean_time - spec_cutoff) * sample_freq)\n                spec_stop_idx = round((seizure_mean_time + spec_cutoff) * sample_freq)\n            \n            while (spec_stop_idx-spec_start_idx)/sample_freq < 600:\n                spec_stop_idx += 1\n            while (spec_stop_idx-spec_start_idx)/sample_freq > 600:\n                spec_stop_idx -= 1\n            while (eeg_stop_idx-eeg_start_idx)/sample_freq < 50:\n                eeg_stop_idx += 1\n            while (eeg_stop_idx-eeg_start_idx)/sample_freq > 50:\n                eeg_stop_idx -= 1\n\n                # create 10 min\n            spec_start_idx_missing = None\n            spec_stop_idx_missing = None\n\n            if spec_start_idx < 0:\n                spec_start_idx_missing = -spec_start_idx\n                spec_start_idx = 0\n            if spec_stop_idx > signals.shape[1]:\n                spec_stop_idx_missing = spec_stop_idx - signals.shape[1]\n                spec_stop_idx = signals.shape[1]\n\n            desired_shape = (signals.shape[0], round(2 * spec_cutoff * sample_freq))\n            result = np.full(desired_shape, 0.0)\n            \n            spec_array = np.array(signals[:, spec_start_idx:spec_stop_idx])\n\n            df.loc[idx, 'missing_data'] = 1 - spec_array.shape[1]/desired_shape[1]\n\n            if spec_start_idx_missing is not None:\n                result[:, spec_start_idx_missing:spec_start_idx_missing + spec_array.shape[1]] = spec_array\n            elif (spec_start_idx_missing is None) & (spec_stop_idx_missing is not None):\n                result[:, :spec_array.shape[1]] = spec_array\n            else:\n                result = spec_array\n            \n            # resample so frequency is 200 Hz\n            eeg_array = np.array(signals[:, eeg_start_idx:eeg_stop_idx])\n            eeg_raw_arr = resample_signal(\n                eeg_array,\n                to_freq=FREQUENCY,\n                window_size=int(eeg_array.shape[1] / sample_freq),\n            )\n            assert eeg_raw_arr.shape[1] == 10000      \n            \n            spec_eeg_arr = resample_signal(\n                result,\n                to_freq=FREQUENCY,\n                window_size=int(result.shape[1] / sample_freq),\n            )\n            assert spec_eeg_arr.shape[1] == FREQUENCY * 600\n            \n            col_names = [col.split()[1] for col in INCLUDED_CHANNELS]\n            col_names = [s[0] + s[1:].lower() for s in col_names]\n            if f\"EEG EKG1-{REF_DIRS[row['reference_type']]}\" in signal_labels:\n                df.loc[idx, 'EKG'] = True\n                spec_eeg_df = pd.DataFrame(spec_eeg_arr, index=col_names + ['EKG']).T\n                eeg_df = pd.DataFrame(eeg_raw_arr, index=col_names + ['EKG']).T\n            else:\n                spec_eeg_df = pd.DataFrame(spec_eeg_arr, index=col_names).T\n                spec_eeg_df['EKG'] = np.nan\n                eeg_df = pd.DataFrame(eeg_raw_arr, index=col_names).T\n                eeg_df['EKG'] = np.nan\n\n            # Save data and generate spectrograms if needed\n            if SAVE_SPEC_10MIN | SAVE_SPEC_10MIN_NPY:\n                spec_1 = spectrogram_from_eeg_10min(spec_eeg_df, FREQUENCY, display=False)\n                if SAVE_SPEC_10MIN:\n                    spec_1.to_parquet(os.path.join(SAVE_DIRS[1], f\"{row['id']}.parquet\"))\n                if SAVE_SPEC_10MIN_NPY:\n                    eeg_specs_10min[row['id']] = spec_1.iloc[:, 1:].values\n                \n            if SAVE_EEG_RAW:    \n                eeg_df.to_parquet(os.path.join(SAVE_DIRS[0], f\"{row['id']}.parquet\"))\n                \n            if SAVE_SPEC_50S | SAVE_SPEC_50S_NPY:\n                spec_50s = spectrogram_from_eeg(eeg_df)\n                if SAVE_SPEC_50S:\n                    np.save(os.path.join(save_dir[2], row['id']),spec_50s)\n                if SAVE_SPEC_50S_NPY:\n                    eeg_specs_50s[row['id']] = spec_50s\n        else:\n            # signal not 50 seconds\n            continue\n            \nif SAVE_SPEC_10MIN_NPY:\n    np.save('eeg_specs_10min', eeg_specs_10min)\n    \nif SAVE_SPEC_50S_NPY:\n    np.save('eeg_specs_50s', eeg_specs_50s)","metadata":{"execution":{"iopub.status.busy":"2024-02-22T20:51:37.436156Z","iopub.execute_input":"2024-02-22T20:51:37.436550Z","iopub.status.idle":"2024-02-22T20:51:37.791818Z","shell.execute_reply.started":"2024-02-22T20:51:37.436489Z","shell.execute_reply":"2024-02-22T20:51:37.790421Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"# ! cp /kaggle/input/hms-hba-tuh-tusz-seizures/eeg_10min_spec/kaggle/working/eeg_10min_spec/* /kaggle/working/eeg_10min_spec/\n# ! cp /kaggle/input/hms-hba-tuh-tusz-seizures/eeg_raw/kaggle/working/eeg_raw/* /kaggle/working/eeg_raw/\n# ! cp /kaggle/input/hms-hba-tuh-tusz-seizures/seizures.csv /kaggle/working/","metadata":{"execution":{"iopub.status.busy":"2024-02-22T18:00:03.627978Z","iopub.execute_input":"2024-02-22T18:00:03.628786Z","iopub.status.idle":"2024-02-22T18:00:06.731169Z","shell.execute_reply.started":"2024-02-22T18:00:03.628729Z","shell.execute_reply":"2024-02-22T18:00:06.728570Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"! tar -cvf /kaggle/working/eeg_raw.tar -C /kaggle/working/eeg_raw .\n!cd /kaggle/working\n!rm -rf eeg_raw","metadata":{},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"! tar -cvf /kaggle/working/eeg_10min_spec.tar -C /kaggle/working/eeg_10min_spec . \n\n!cd /kaggle/working\n!rm -rf eeg_10min_spec","metadata":{},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"if SAVE_SEIZURES:\n    df.to_csv('seizures.csv', index=False)\nelse:\n    df.to_csv('background.csv', index=False)","metadata":{"execution":{"iopub.status.busy":"2024-02-22T00:59:41.448747Z","iopub.status.idle":"2024-02-22T00:59:41.449334Z","shell.execute_reply.started":"2024-02-22T00:59:41.448996Z","shell.execute_reply":"2024-02-22T00:59:41.449017Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"# Spectrograms","metadata":{}},{"cell_type":"code","source":"spec_1 = spectrogram_from_eeg_10min(spec_eeg_df, FREQUENCY, display=True)","metadata":{"execution":{"iopub.status.busy":"2024-02-22T20:51:41.624145Z","iopub.execute_input":"2024-02-22T20:51:41.624558Z","iopub.status.idle":"2024-02-22T20:51:42.682348Z","shell.execute_reply.started":"2024-02-22T20:51:41.624502Z","shell.execute_reply":"2024-02-22T20:51:42.681504Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"import tensorflow as tf\nddff = spec_comp.fillna(0)\nsig = ddff.iloc[:300, 1:101].T.values\nsig\n# Log spectrogram \nsig = tf.clip_by_value(sig, tf.math.exp(-4.0), tf.math.exp(8.0)) # avoid 0 in log\nsig = tf.math.log(sig)\n\n# Normalize spectrogram\nsig -= tf.math.reduce_mean(sig)\nsig /= tf.math.reduce_std(sig) + 1e-6\n\n# Plot the spectrogram\ntimes = ddff.iloc[:300]['time']\nfrequencies = [float(c.split('_')[-1]) for c in ddff.columns if c[:2] == 'LL']\nimg = sig.numpy() #ddff.iloc[:300, 1:101].T\nimg -= img.min()\nimg /= img.max() + 1e-4\nplt.figure(figsize=(10, 4))\nplt.pcolormesh(times, frequencies, img, shading='gouraud')\nplt.ylabel('Frequency [Hz]')\nplt.xlabel('Time [sec]')\nplt.title('Linear-frequency power spectrogram')\n# plt.colorbar(format='%+2.0f dB')\nplt.tight_layout()\nplt.show()","metadata":{"execution":{"iopub.status.busy":"2024-02-22T20:51:42.683799Z","iopub.execute_input":"2024-02-22T20:51:42.684318Z","iopub.status.idle":"2024-02-22T20:51:57.893140Z","shell.execute_reply.started":"2024-02-22T20:51:42.684291Z","shell.execute_reply":"2024-02-22T20:51:57.891902Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"","metadata":{},"execution_count":null,"outputs":[]}]}