control motor using face camera <br /> <img alt="" height="240" 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ym2G8lhKSpXwzhv9yLHRYptfSrVO2y5vnKOkVWNGVMWF9o0UlvJ3+jQZywx3txi9SrzLjXfc5r7EyJUkNeOqtlsmNoEq715WBTx+hDV25pSifN24oTYf7Xd9lPNFcLZNmOysc8zOiLqtuMDkTZXbTdxjHKXqBzekNPXWvd2uUk/yf1RkZZVkYj4HIcWJDOEGDsOzWhRr1e2pmmbp2YCoNw/SVUgLWUCIN/Uwi6xhtuNahOksBVZqG+I6vvrma7tI3fcccK9DcXecyeW3FwoR4PmrVC8kzYPpNmW1WhYU7N+b0V3W/Uv44kTriK1w+ytVJ/tWw9lVS0stp/baZTaYk38yVf//DM1jxypfyKaz86j0R4mVHM3WoalrBzKWbsXOy5Sc+tTSnbYciCZx2hFxzL8x7/aSv5GBz5jqfHmNxHKqeuiuT8hQgV5mauazYbtl15787Ao49HgMEqet2uqDxe13a5TbVRNApgryJtjJ6oczs+gR0SDv+MDkTYnro74MdZ3Keda697uNGqeosSu1lZFI8210BxVjSVTHugWzAzVTADk8z8rlgBU13/YJdaAuyHeYqr3zbC55obC+wsXZE25h/0kNxfKIhg+2uWwdpJvfLG2rEhDqUb9/qrvdnViZf9yP1MnXEXE69VfqT5bt955FB3ndholtlhVIPkBID4afU36GXYsjNtmD5Oq0UnbsBSVwzDO2r3ocZEaW59WosOWA8k8RieKeFs2mNRW8jfarDmNoq+L2ETbmxUruuccoYJsomo2GiY3wWpvHhZFXA9RrjmI2s6beJJHbrfrVLPcWqqs3yHJIouUYNgjCoOfC9Q5vxDRgqkZO8ZQYPlDiLysanOh0NzcNFL7IyMtq6KR5lpojqou5HGomQCcddaLpPunfEBVIE2ZALgJEsLboNoVm6g8yGXm+krMTvo3gmqXWM0d669wW0U8Vhg219zDUO3aI+tmYL39sN2Tyh1Oo+q4zFt29Qnk9qDaRO2TgBXOFSn009j/SEOpagemVmPTLij7l/sZTrjaARWRh9lbqT4p7vZYDEi33H0U4tyal8+gjqW3mlu03Rv8XlVb50/EUNOUq7HtqqkO+0nuhu2/bViKyg0v0rZ78eMiDXIIUtGNBvkD6TjG5i6ZtYQ7wAGktkKL9qwawhCNbnTQMxZ/XcTOtL1ZseSeB7grWhWOhRdbDzm5CVazeXRRdFsboi4mTu8USp63sA+q0NmkkrmO7micCmpeeyMa+Ii6PhBpc7yV5qE1Cywzeruutc7tTiPaH3eCBGFX3bI/e2rnaxHxOQ4tROb1qt8NEa+XuTQMJ+64ozYU97mnhhq3UULb9mr91UwASJQD8DzAW//jb6tVrCWeAeDFsEusQXfDvcuo99bUGfBvMf6NhvOHkEVMJ9ocjygiHK/fBzNYfVCWnaKfDY39jzSUih1vT4muzEaj+yP3M3XCVUQeZm+l+mzdeudR6HPb7K23ElusKlR5LJfFp6/fN/s5VH1qDrBvjU4io6txbmt1uncvcVy1OgNJdNhyIDnHWK3yMq2ccZlaaiv5Gx3yjHWPt3CWImeM1dyfEKGCbKJqNhomN8Fqbx4WfaHWW2Nb06njvFHZfbJUke4mQdRWDzManGkDNIg6PhBpc3wyW45R7VLOtTbrD2K5PzLSskpG+EOcaBmW0HxkLgHCXxfypXRBc1nJBM+OKDO09MtXa5uu1l/RBKBTS5oAVNd/2CXWsLth31P0s4mpM2D36sQdb993wo0nWjx6R/WuNJWix1UFxbubGdO1N/r4h1azw0bDmqI70E+yq7BRe6pD/5HXt7kD9UjtMHsr1Wf71nOOQjZv9tZbnT1TxH7cVKhdsvtcDfJB9q3ZSThFXrGTUzcH7btHBXc8nvDqN7c+pWSHLQeSdYxNmc8Y/sCYVmor+Rsd8IxRV+718LS8yo0z5tTcnxChQnihZTy6SEptgqXq28EWFnOH6CCi3tz58jRHDh9LiOQ0CdJBMwCqzzVWtOEUohPY9oFIm8s5RrFLWdda53anUfMUJXa1tqolAi1aZuTwWPKvjh0/wvI1X9+WV7a9Wn/JBEA++cORbdu2qwhrKRMAKoeLn8r+stfVBpB5l6zN44TNRTdk3pV8vkgy+yl8yTSKbk4GRbmWd5p9qPafVrX4PNNQvKvO6u+EiK7MtefKbz9sTjRfdabs3AlVzhlyVK5/HvRUqs/WrXcfBQ8k+aKo3npLddXouXrFWeGDU9S0r/ugtibWSXJYysqhLILR3Usel6jjVk2veofJA8k8Rqur7/CLZs+rHqaS2kr+Rhs1eyv5ushNiLJ9casrdxZ/BSi+CZaun34XCtVCObat3so6b/xWY64GE8ls4qSCOXWml9klt7dmkfqnRXmBcLm+XXmMtVWmefU6mpc1cRl2bHca1Xe1FmlZ1RKBFi/z6WyudP/qjCoBePe7b1KRUI00uwTAXKOMvfCaEdlwUrX3L/cq7FJYHOyMGwlvZxU219xDU0HdVpEWcDpFj6sWrG3afuYx/h2TdzjUj++/f/O11D5dojvQT3LTsk9+17bULr+cITfrfcvfevQorMSLUp3waUW70bafNALVtvSbnQnSPoeLSHXYT4lOIsOSVKvsh3HH7qWPq6oj106nRofxA2lZRT24IKHHzzBvESS1n/kbVQ37K2+81d+sIu85zf0JESq0vOHTouuJqPZkgre11LtQc+cT2+qlzPPm4vYNp7WJ2yvC16n1Q201yYZTqfZC6w9E2lx4b48fY32XanWM0pdh63ankd5VEZG7ymcvGmkcBbQQRe6G1F5KHlH1oRheu+brKNu2VOuvVAJAUn8OKFQjTZMAQBAEQRAEQdAyidy5y818cij8us8t9ZeAk84+RNqr9VdLAqAUqpGQAEAQBEEQBEHQJDKTh3LKcWFCAgBBEARBEARBM5d5eKz20ODChAQAgiAIgiAIgmYk8UWgMm7/k2QCkC8kABAEQRAEQRA0SiEBgCAIgiAIgqAVEln5flL9sJAAQBAEQRAEQdAKCQkABEEQBEEQBK2QkABAEARBEARB0AoJCQAEQbPS2WefO3apI4IgCIKgJdDKJQBPetKTzj33PBWEJtXqnEYMmGlEBnrjxmePV9EEYOmHBMZ8+cJr1K6Szw9eO6gQZSUAcrCOfeDi2htEq3MaMWCmERKAwSU3PaPdwJgvX3iN2lXy+cFrBxUizABAfdR5Gk899fSnPe10+9OV64u6fm9FN1EvT6UVGzADnDEpJACLlrkQvNSqpNIHOHFXi1PLroZVmVLNh1XPDc14EMq96pRqS1IVSPlrm1KVpVTNSiVfpL32TR04S9Vpl2rLUnWg1dIECUB5l5MaykGqWk3t197jX/899XOmestHv3Xtl5646D9/VsUXItoT0jOe8SwSF1p2rP00nnbaM/79v6e1xoI/73nPP//8LVu2vJREBVocxJcH0baam6BNP+tZz37hC8+eflv5b9a/+qunqcgIdfo557z49NPPaMR7CgnAja972jf/aHtTqtqkyt6B0/m66HxjlEof4OkXXnjxRF1liHoLUqumUcuumlWZytirsPOdNaNyOzNp85bXSEitCuqsk3uKEj3UmtNbiqhm3mHk2kQPUvGdaW+Yd5FSD0Fq1USarJ+J3kC89EnI3JbQ9D1Ay6aZzAD8ylkXk3e86sjP2FNSgRYpqKpNp9Of8YyN5PCk86NFCrYP685rj3z/B694RnD/X6nz/ve/P9ScXr/67LN75wB8bkls2dm18yL97N1h6Kq9n9bTeDq5f3pFTj/dpAH86khRkHz59NaceuBMQ/VPouCzn/0cKkyfA2S+WV9/7zUbX/JcFRyhzIcEXUr02jVW9RESgGMHLj78/z6bL6ug6ROAbI0gAeixhxlq2VXthFqUsVdq/+lnkKyWktuZ7PpO7a9RV4eddXJPUaIH3dznANr9kxI9SMV3pr1h3kU65WsXNNkYnugNxEufhB47OXUP0LJp+O8AnHbe64P1l6IgrVKV++r0jRufFay/FAVpVcvIbr/22P1TQeYAp592Bn9sD5UDbHrVO5qn6Pn/6Q5VrV2hYXAVYZELk+YAobnqUFVjtZ5G92543nn0CpnCi1507rOe9WwSFThib9KrVn1E/aQ2EYbHlG9zmW/W73/wP+/+6o1nvfksFW/T1UdPOo6+/bTG2vnJJGPPfe7zXvzil7zkJb/Jnw0vfenLnvnMTY2aE6ueANzwmcfdARMP3fUqsUqJaj505ytVcAHqlwDIO/0pqSb5kpvOGJl97HX6AI2HsF1lSjVnqTotUg1Zqk5SaYtTq5Yh1VxJm8gJT7izZaI+b5QVqmm1v0ZdHTbrKMkmRr/xGy+g+vRTxa1UW5Lrn3TWWS+qVzaSaYCNqOasWpMuqbaZ79u9X7uw3U6phkYZ+6Y6qanrvLFqTVjhnOf1AC2/Bp4B+JWzLo66fxatGmIewNz7j7p/Fq1qmQdov/aC7w+ZADt+zgE4ASBC/X6i8xCmRKhAZ+YtH/0WlZVFIIUmTYWzqvx6KJBUk3Zxk213/UVQSyetp9G9jbKe85zn2teCb/mfzgadXqNBZgB4GFCfoX8SbTFsnWSDum2+8j5ITALAuuz3XkGL3Y8DXXTHieD7L7pj3zVUuPbI4yf2vVzUSSq/ZqdOJ6NPp1F9NpAoJfBnVTWZQI0EINh6mwx89gaxVgoJwDRyFwJLXAUpqeYtB2g8BP/sVLRnq9r7Q0otzdWGouJq6U5YritRrRnpVG8Tyeq5D+2vkW/u3hXrHTYjnTr9pS99GdWnn3lNXP9s9MPtf1YIch0bVM1ZtQOhRIIXSSGpEBVU28z37d6v3VRjOGPf3KE1FVZ17aTuIRpptIJWSwN/B4DtLOs3tn2AzCj9DBHSpLelYzr9hS88W15mZPhOO+3p0vZRhdTgbr/2gvs//7lPCTMAQSENUPFJRefhjJftoAKfrnBO2McHtbuEcEpVK1JYpZq0K7RSUtVYradRvznK53Ce9axnc3CIdx+3ITvnYyK0leYTQVNuKO+DpEoASFmPA1199OSJOy6u3fhfQAJw+unPCB/t9LG6adOvcdne/qfzxtKt8pVOAJ698dL9D5387PXPDGulkAB0qHUHstwJK/r6pg/QeAj+2an0yJnKPOVvnX82mku5rkS1ZqRT7nB8E7XYqZ770P4a+eZOdEX7XXLK2YRQ5drzmrj6jYa1xa4Oq52kt6YXv/glT3/6GfRBTz+pzDlAqNBom/m+3fu1m2oMZ+ybO7SmwqqundQ9RCONVtBqaeAZgHD7P+r+SVRBNZlc7r6vlMoBqEJqcOe9Lxi9//3v5/v9AZ4KoIKqOankDECQdPCsdpcQTqlqRQqrVJN2PffyW0JDKVWN1Xoaa2+O6in8WSQA1GcINr8VMOWGMgeMTABIGY8DkYmnFOASueg4ei1F3n7YLfEim/4jR064IONW9Rd/HtNZ8g/9m4vrjDOeSWV61ahMcfnyTaq2BGDjq+48cfIzv2PLJhlgOCWwNa93Qf+wkGwuyr7tQ3ftHzxtGOkMgBz/7YpeHekDNB7CNsmUas5SdVqkGrJUnaQyLE7TSzUjLXIbEmcysthopdRzH9pfI27+3Oc+jxN7upBJdLHTIn1KZm5CyByIr5/bxJv7yvSHQojbgmoYVO0k/WT3TwXOAUKcC422nRep2QFS39cuVOiUamiU8ZniDo0ONkgcbFvnXrqHesMg2QRaOQ38HQC2jOz+m2oxlKTXv/4N+wS0qCp4uas0jGypkAOkBnfntUf+nnY1FIJMBmBzgDe96U2yvlTmIZzxsh2cKfGi3IpUu0vgk9ku1USKK/CGuEA5STQHUA1ZradRvr+oZ0iyHgF6yUvOe6OAFlUFFjtU6o0fAZLxsHWvqpVUzoYy3qyNVALA6noc6JJ968a5HjHP/5Ci9/VDUCYM0ZpO2dcRyX1IbNr0ayFi/wSQOWl0KdEq+yBQqF9TztnLSwBE/LrPWrtPEXL0+y+jiPH3vDaaAJianEVc9hFKBGT/ubr88m3uZFloMazqlwD85b5q7f6dz5C+PyhUmFRy04ndkCO/6WmaUs1bDtAMmGiTKST3UK2aRjm76sa/qNaMtMjsOf8MheZio5VSz31of424+QtecBbtAy+y6A2TH+3jxfZNCFE104QLjbUpceV2qSZS1U7ST/pw58VQPuOMZ/JitJ+ui3SQ1y6oathYFVHGZ4o79mBswuFn79X0PUDLr4FnANgy9ksASNu3v5k/g6mgVgm5i02O7KBZJwCErNxU3iHUJLci1e4S+GS2SzWR4gq8IS7Qz2gOoBqyMt7CtMiXh2e3Or8EvHnzFraVVFCrpMKXgNU8Q746N5R5pMr6s15z4FW0quP7AObLAJwD1G199RXhkACEtW0JAClzED7zmZvo8+ClL31ZOHXyHJJ7oLX0M0Sa6jx7XQmAXaxu/1vMFwNqNa8/2sgTQpnacp4gg25xAr3lLW/lM0YFGe+XALzgtddzhk8/N73qHb+7/TRp/VmqycxUWRP++Ge1m4D0AZpO2tvmiXrolGoyqXJ21Z0TUa0ZaZGzieEMRxcbrZR67kP7a+SbG5Hp54i44z7RYZJMP6JPtTYlrtwu1USq2kn6OfgMQPTFUouNVlLhEFqkmjhlfKa4QwvGho89dbAxTd8DtPwa+DsA/LFH6v0IEFmWLusceQTouc99Ho3vQR4BIotPex4KSp0JACnjEJ5+4hNvVD031e4S1ImNSjWR4gpyc51NpDLewmqS7j/zz4CSp0zZShb1IB/4mSYHaNlQ5pEq67/7qze+5G0R7xjVxR8+YR/mEba++orwJfvWJ04ASDmDkJ/4p1On4qycBIDUfvbaEgDj++0DP6EQrxmbKBg6ASCR9Vfun9QvAaB3uY2bL6drin5S+cznPVVaf5ZqMqmyr77K0/DHP6vdBKQP0HRi27ZLtWrK7VVKmZ20q/MwuU69WjPSIrchsc+RxUYrpZ770P4a+ebO/Z911ovC4zf2TXKiwyS5JlxorI1qyEeA6CjOO+98zgHoJ5Wn/g6A2QHSFK9d/zHc8toF8aEF705qOVihqoegCXuAVkgDzwDwt1pZ0RwgfOF1Cs3wS8Ck6ROATq3/t1crNxBEicF/eMHpvC1aVA2l5FlNSTWRUjWDVLWUOk+j0OnyHwLQS0OuvVGnv6g3mVrYZ9mHfIPLPFLp/q+/95pfu6jr75xefYd38OZBIPtsj7D14SvCJhPokwDkyX3M8EP/SvwnQe0f/tOr8pVOAKjsvwBgy/W/CioiVXogvjNw3Wf90z5VP70fAWpRvwSArqPwjrHj0z+kiLzGWbL+LFV5Gn6tWe3XSItB4bayK6X2nr36myehjt3gn41WUq4HUa0Z6ZR0jc3FTvXch/bXiJuT1yej/NKXvozeFUlUoHy+XwJQ9+5qbVOufqNhbbGrQ1Phuc99HjcJ8xgkOqjOo8h7357mtes/hnNeOy401bVvumE00mgFragG/g7A2P8MKGkOCcDhdxlzn9KXb/113haVVUMpdW6jUk2kVM0gVS2lvLdXI+X++92kbxf1ObscIPNIg/t/zYFXPevMX8/4r8Bk4t0zL+G7vO6Lv2bRfT3g5ImjRyIzALKmi/TS6S9+8UvoI4F+hteFC/S5y58W0dwgX40EwO62oe7Ujcv3+EeAPvMZF/N5Avt+y2c/W+USPljCl4BPPdX8pOtIzgDICp3iJ5EkqoLcdMbIrDwNv6Cs9guk3aCorpTae/aiOp1STZrq2A3+2Wgl5XoQ1cLW2xtKTWMiSZF9aEQian+NVIeiEP3DoJ1azJ8BlZV5MS3VNvN9e5rXLmy6RaqJU85rx4WmWrq10g2jkUarmtz7jkBVgJZGA88AkEb9j8BIZPHZ5dNPNuJSvGoa0fvvq18SeSRA6rcvNn9vlAqqrZQ6vVGpJlKqZpCqllLe2+vT5cvEXz4LRnNomT95UR8DqkJPZR4pWf+JHvspQ+afAPCnwkte8pv2q8Cnk+Pnh39IPM/eaDWB6gnAjBV5lGhaTZQAsPuXs6D0psd/8Hdxkp5GSdWs1G5Q6p1EpVq1a1LHHCS3GJHfVdVKynmjrmrtmsZEkpr7kLVX7a+Rak7vuuz7W+rUxZUr0RsFHVT9rwMHqbYk1z8p6t2D+yfZiGrOqtx/uB8hlW5olPe+PeVrFzRZw7zXrkWqlVR15lu7Uq2gFdXA3wFg/cpZF9OnYEgDqECLQ9z7lzLzAC984dnBX1KBFlvu/bPy3heMZpQAsP5y33nS8St948DFtC0qqFZSwWS0SDWRUjWDVLWUck4jfeQ8//kv5FfnOe7fgek6g6r6F2C03aEyjcwBk/XYT5GiD1e+vadEn7veN+gm+ZpnAnD90ZPuDwcNp0lnANj9D/GgY4ey3437eJp2gzL0hUy9BalV0yhnV6XfUqvypU2kkKymJKvlSDVve41aWnl11tE+MqVED7p5SAOk9WclejAfH1SZG6omrFRDVt77dr/XrqnJGrZfX/nHGNP0PUArpOFnAOaocMkpqWo15b0vGJHXj6Kq9dONr3uadPxN3f22TfRTtRpQ0vRLqWopZZ5GehN/0YvOlX+nf9aibdEWh3L/pPwBk/HYT6E644xn0gdtSANe8pLftNM1uloPzT4BMF8M8Ax8+5/UIwFg98+zAT00yV9xzVH5CcCMlLOrzi1Nd0TUNkitapE2ai2K9pz/vtRLubuXOOpac+/+3SqVAyR6MPI3IFqkmwTlnZ+srgZX+/WVeXISmr6Hwd+CoHI18HcAyteM3zdXRZOcxrm+t1oNucXVGTD1z1q9tp/mOQMwC02UAATT39v9s7a3/hVXuemMkdnnNW0xKJN2tTjl7Gqo015tFpKbzpFqPuv3JbX1dqm2JFWBlL92GJX8vp1xfUmpOu1SbVmqTrfa34KgpdGoZwD6qOT3hRFpdU4jBsw0WqkEYEDR5+4CP3ox5ssXXqN2lXx+RvHaLfYtCJqPkABAfbQ6pxEDZhohARijMObLF16jdpV8fvDaQYVo5RIACILmJjLQY5c6IgiCIAhaAiEBgCAIgiAIgqAVEhIACIIgCIIgCFohIQGAIAiCIAiCoBUSEgAIgiAIgiAIWiEhAYAgCIIgCIKgFRISAAiCIAiCIAhaISEBgCAIgiAIgqAVEhIACIIgCIIgCFohIQGAIAiCIAiCoBXShuc//1wlVcPrRZdsu/Ss2uLrXn7+Ob9WRSLacO1fQKsg9bpDEARBEJQj5cEgaBZSo46UmQBsP/DAx6/bEuw+LX71i0fv++qxe27Zdmm9Zk3KJkLLKvW6QxAEQRCUo4TvgqDBFB1j2QnAsbu3ufJrbz388dtuesv5VD7NxOs1a1I2EVpWqdcdgiAIgqAcJXwXBA2m6BibNAE48+zzr/9YlQwgAYCM1OsOQRAEQVCOEr4LggZTdIxlJgCvuP7Axz59+OO33XjgyLF7btnOXwZwyUCjciVlE6FllXrdIQiCIAjKUcJ3QdBgio6x/C8Bb9l+0617D9x6nXP/pBddQuXTQoWIlE2EllXqdYcgCIIgKEdp3wVBwyg6xvITANKZZ59/weauv/wjVbeJf7v2/z3xxLf/th78i2f96f964on/deveWtDptr/7TmqVke3Q850/+2ajwnzEu8H72XeXOo40pk8+bjfy+Ouva6waQtvu+d6xH/2cfnYGSfXX/dojj588efTaevDpF3/4xMmTJ/a9vBZ0uuiOE6lVRrZDz4k7LmlUmEZ9O+/YZwiCIAjqVqvvglZIzoh41NppFB1jmQmAfdrngWOOBz5+XV4aULeJZI7/13d+qmyudM+TynTYq+Gwot0ILlzukj20RsIzqOSmu0XeXUXaddWRR6jJK//wYV6kAi1SMFQIqr/uZKlPEHVzzD67n2M2Hc7MasvO7U42UhcIgiAImpEivmvbAWe3jh24IvmcxZv3P3D0pi0qGNP57zlyLK9mRLQVtyvE/u1qbUrZ+wYJBdNv/X9bAvCBD3yQKtDPziAr6u3zvwR8dP9Nbznf/Nmfj1+3RX4PuE11m2jM8dq3/1ftvvgnH3/i24/39fHSbS9Q0oXXd8nc15/VHXqriRMAKbU2qpADtLh/Uv11N5b6yJETtbvpVx89efRoXx8/twSA7+sffXvrg20QBEEQNJS07zJ+3fv+899zU9Jzt5vsoSx4v36QAPRRMP3G/nfNANx5511U513vupEXqUCLFAwVpKLePj8BYMfPhbDYobpNZHMsPes3bzUTApVpfv237FMthLtxHlbZwpf5oZfwaE3VsJLx3I61T3HQVKPEwz4tY5t8ytWhCvYBJEPscR3aPV7JXanFIOozkQDYJq5ytWNcWfUmGvqa3/mzv/NBu1YfPscnSwCi5XZxDtDi/kn1150tNf0MTvqSfesccVb77Yft6Cbc7fawyhb2HeWVPoWoGlYyTt1x5BoOmmqUeFCnbz/NNrnG1aEK9gEkQ+MhH9U57arvsNoEH4hZxdgKoqGveeKOO3zQrtUH0uxT7rOt4KS2pRYhCIKgEsV3YRXRm7JB2ndtO3Ds6Hs2y0hcq5sAnHvueUWVm+oxDEhUJxRCuUUhB2h3/6Sot++RANxzy7ZbP90/ATAuv/LEP/27Z2nTXNWsF3xWYJ59Z9drgx5vo6XhrtqKnOGJJ/6BNuqeoXfxqs8gY9BrWYGZrIg+z0N9diYAIv7Jx023urdQwewhH4L4doQJNg6f490JANt3lgyGcrv4uX9S89H/oPrr7pwxufzKSZ+442I25TUfHyKy4LOCq8k9B5dsrwaLN9+ic/dkkQmKnMH47oupuenHx6s+g6im3KuQAIj41UdNczOJIZ8OChXMtnhnxPcc7A5EDqTep61WpQdOZh9qQb1pCIIgqFAp89dp+xq+i9zzsSM3XVALmmkBh38OJ5hs6ba5bHpwHHhzrUKqn5vcQ0d6u7XOSRfcdNjXcYmKrbDddeubd29x//6j7gGnqgLPe9TXmvqj1KTDgETVQiGU28U5ANHi/klRb5+ZALzi+gM3vNwVbn+/eRZIrk2qbhO9x3W+P2QCwfs6U24JxlcVUkErY/orQxzpP6tsVe/KR+opgRO1bUkA7KJtW0FWXvfmG1Lcnpx6b7JbVe5OAILYxweptVGFJ3/Cs0CqAqv+unub63x/yARq9peHrLDLqpAKWhnTX/n4SP9Z5WiEzLddrG7VW8h/24jw5b6hP8x6b7GNNvvUW7eqH52PNPMECIIgqERl2jJWzHcZn00Ix+zLxi6ztw4mW7jt7mC0H84T+LsHynbbtY5g0KnAP30FnrKI71t8i5FUYdsBG5Rr2zTNPftZlJuaaBiQqGYohHK7QprRnmBEvX1mAtBTdZsYnKu1xZ8KTtfHK8/tfXPVRLneZtCq6sFo4ATAih8Z4jv0XtQ2kQCETrp78w2pZjEJgPqbP2pRqv66B1NrzfQ1wR9LH8wG17vtqok0xNGgVd0iD5kAhJ6bLtyKHyWqbY5qTpAAqD7rW2d1bxqCIAgqWuT5Mm1f0nfZW+PGPZtC5cuvuIsttTTZ3kO3Bzv6UeVUxH1H2dn6egXdZ+cW7TFWqPmK8St/GFgbr1F1lMKTPyQqhO8DNBUdY9mPAFGGV1P/R4BM2d7p9/e/fZyC/HCOscvK+CrX2wyGVd6dV5472jZVDoXGI0Be5NrrcWoSTQCoHFIFU27tLTSsWtUfAZLdyvJkCYCKtChq91M5QP11F6bW3un3t659nILsmI3T5ZqhiTTE0WBY5a1wZZejbVPlZoHLwWGbcvSmOxlxG5c9uFb1R4Bkt1XNep/Rao1HgLz8pnUcgiAIGqkSvsto841HjSceTQJgJi4mTwCqClaxLdY1zX36WZSHVafvZ/G9/3DjXy0qRcdYZgJw5tlbLtjs9Lorb7p1735+IqhDdZsonSvZ66ZpNp7b8A+Pr/WbASAZ38806+eUVdD1ZRx59XiS8txUTR6Lq6T/tmm1Y/YRIN2b2K5fpb8EXO2VLE+QAMxO9dddmlrysuFmds3gGk4cPdJvBoBkfD/TrJ9TlgXXkejKqtqEfVynemypkW/4VfpLwK43UVZ9pqqZsqtlUgu9aQiCIGhJpH3XtvdIPx2einGGu3LMwSgH283WnIPSRodyez+q3BKhhvyTF/0TO5E+zdquLaoHfuTaVRR90qtIU1G735IDRL19v0eA+v0VoGXVzFx4NYmRUpkJwAqrmo6AIAiCoG41fJfxxA5+NJ9k3DMjrbMv21vyhgMHQvCKuzhCPYia7f1EzLfYGfMd3zeHLwGb2Qn/JWD7nV2D8/oTbFFWWMJHgHooJwGYVFFv3yMBeNEl227af+QDr9HxiJRNXFKRC39C3+8fQuaPovIzUVG5iQIkAAXJ/HnT6vsAEARBENShDN9Vslbdrw+uAhOAM88+/3VX3njgyAP3ferArddtv/QsXSEiZROhDPnnoAxFmPscqdd9xeSfaDLg9j8EQRA0gdK+axRCAjACRcdYZgLw2lsPHz1y5OO3Zf8BUJayidCySr3uEARBEATlKOG7xiIkACNQdIxlJgCvuP7Axz5NCcCNbzlfr2qTsokQBEEQBEErK2WTSAnfBUGDKTrGJvkOwGlbtt90+8eO3PPRu269bhseAYIgCIIgCJpAyiaR2nwXBA2h6Bjr9SXg7TftP5r1JWDq7d8BAAAAAKw8UYuV4bsgaCpFx9hECcCZZ59/webzz/k1HU+KenOjHgAAAABghYlarFbfBUEDKDrGMhMAsv7Xfyz8LdgHPn5dXhpAvblRDwAAAACwwkQtVsJ3QdBgio6xzARg+4FjR/ebPwFEhY9ft+X6j+X9IzDqzY16AAAAAIAVJmqxEr4LggZTdIzlJwDs+LmQ+5+AqTc36gEAAAAAVpioxUr4LggaTNEx1iMBuOeWbbd+GgkAAAAAAEA2UYuV8F1Loic96UnnnnueCkIz0m/91quj5egYy0wAXnH9gRte7gq3vz/734FRb27UAwAAAACsMFGLlfBdSyIkAPPUvn37gu+X5egYy0wAeop6c6MeAAAAAGCFiVqsYX1XaUICME+R6d++/c3NcnSMZT8C9MCxYzXhESAAAAAAgFyiFivhu6I6XUitytT0PTz9/RYuf+UrXwnxqDoTAOqKOmFCt0svd8AxVM2JFBy/KkfHWGYCcObZWy7Y7PS6K2+6de9+fiKoQ9SbG/UAAAAAACtM1GIlfJfU6c94xsYXvvDs88/fsmXLS0lUoEUKNmqmNH0PTsGvs1nvNKw5MwDc5/zd/6Tb5foBitDPT3ziE696VfW0/ZTibgdXdIz1ewQIfwUIAAAAAGACohar03dt3PisYNylKEircu7lT98Dix3w9u1vJlGBF1UdpcxHgFr6OfXU/pMVncrPAZT7JyjoSl/5yo033igrt8g1iMFrZeWhFB1jfb8DgC8BAwAAAABkE7VY7b7rGc/YGPXuLFrVeRd/+h5Ywf0/4xnPInEO0GlYJ00Arr322s9//vPcMxVoMdQZRNxzk84c4MILL7777rtdbQsFX/WqV3/iE5/gxSnnAbhD/jm4omMMXwIGAAAAAJg5UYvV7rte+MKzg1l/znOee9ppT6efIUKiCqqJkuyB1OyksweScv8yB2i3zvlfAt606TnBTJP1v/fee7lMQVo71DwA99mkMwEgf881w05yPOw272eLuFUUXht+Dq7oGCslAbjiiivwEz/xEz/xEz/xEz+X9WfUYrX6rtPDzfuo+ydRhdZneKoeglRXXT3E3T+rMwfITwCuvfZa6oqs/yWXXMqdU4FnAwafBwi68cYb2/c/KLh8cvyqScgNQiQqrhOF14afgys6xjADAAAAAAAwc6IWq9V3nS4te1O8tj0B4DqqISvkAC09tLh/VnsOkJ8AsNdn908F7pwWqUyrVGXW61//hn0CWlQVlPhYwq6qxXZRTYKf81FNLrzwYl4rg01xHT6uIA7y2vBzcEXHWGYC0PwzoEF3NypXot7cqO+C82PJMwEAAAAAxgZ5mH/zb/4Nm5lAvxkANugLTwCUbVWiCikbnZ8AUCf33ntv6DB0zomBqhxE6Qe7fyqoVUoT2X0pfvqI2hLnnXe+XMW9TTQDEI6LxUFeG34OrugYy04Ajn38OvdnQK//WK08TAIgoYvnrLPO+sxnPvODH/zgCQAAAACA8fCLX/ziO3/30//77PN+6f/6v5yzsUQtVsJ3sWbyCNBzn/s82VXnI0DkSpVhZWRQNQmaKAEgr6+2QmX+MoCqLEXWP9P9R1E1U+LK8pu+3Oek3wGgI7r2S0+wwpHy2vBzcEXHWH4CEP7upy6LalrUmxv1XYQZAHL/H/jABx555JEP33sMgiAIgiBojHrw8X/5w4f+NuQAvWYAivgSMLlS9uXBsDIyqJoE9XsEKKj9EaB8TZ8AyO8AcISbc5yQuUFUXE0eHYmDvFZWHlbRMVZKAhA466yzyP3vu/cbEARBEARB49WXHvv5v7volc7fjPbPgJI3VYaVkUHVJKicLwFzDpD/B/uVwnM+5PjZ6/Mik7OHXDOcNBYHea2sPKyiYywzAdiy/aa3nB8Wq38C8KJLtl/qyxFRb27Ud8EzAM985jM/85nP7Fv7BgRBEARB0Nj1qb/7Z/4+QL8ZgKc97fSp/43XtD2QN1WGlZFB1SQoMwHg5+zD3XQJBUOFKcU5AP1U8UzxnwxiaNGVPJ3dunoxVM3BFR1jmQnAa289/IHXJBeTot6svc+FEoAf/OAHdxx+EIIgCIIgaOz6xN/93FmcXjMAVqc/4xkbX/jCs4OJpwIt2jv3mbZ4qh7IoUqvH5BB1SQofwaAde2M/xHYlHqV/89f/MdAAzlJhasaQ9UcXNExlj8DcODIA/fcsu3NV2y79dMPHN0vJwTSot7cqO8izAD8y7/8y0eOHIcgCIIgCBq7PvrjfyZvwz4narESvisqMutBalWm+vTgXGorqknQRAlA9Db/UP8CbJUVHWOZCYDVadsPHCPu3lY9AtQh6s3a+1zoInniiSfuOroOQRAEQRA0dv2XH7kEgIharDbfNX5NOgMAzULRMZY9A3CjnQHY/uYrtt/6aTMVcOlZuk5E1BsP+k7CDAAlAPs/sw5BEARBEDR23fnDAWcAxickACUoOsayvwNw9AOvCTf+T7OL1dqkqDdr73PhBODAZx+CIAiCIAgau25/5OeYAVBBaM6KjrFJHgGaXNQbD/pO5AyAunggCIIgCJq/PvSJL7/lnfte9ds3Dy7qljqf51bu/ugfv+p5m8/+pScNLuqWOuetNBUSgNWcAYBKUHSMtScA2w88cOxYXOFfAbSJerP2PhdOAP7L577ZqY0bniCpIARBEARBQ+mNb/vgZ/702Hcf/dngom6p83lu5YJTnvXZOz7yz8f/YnBRt9Q5b6Wp3/3+Sn8HACpB0THWngCcefaWCzYbvfmm/be//6artpryrr1HD9y4fYbfAfivf/ytTnECoIIQBEEQBA2l1/yn95KN/tP1Hw8u6pY6n+dWzv6lJ/3TN77+d3945+Cibqlz3kpT7//eSn8HACpB0TGW+QiQ/O+/zcWkqDdr73NBAgBBEARBhWjrjv/8Nz/+2ZeO/3hwUbfU+Ty3Qh79Z/d/9ccf3ffox6yoYMUR+mkKLLsYKjz60TtIriGVua3ohLrNSQCIqMVK+C4IGkzRMZafAHz8uvPP+TVTPvPs86//2NAJgJwB+IMvfLtTnACoIARBEARBQ+m1zpr/aHBRt9R5zlbe88H/cuHLL0+J1qr6UnIr5NEf/59f/tF/va2m33eF26+9PvR5+7XXUbweuT7UVPrhf72NuqXOeStN7f7b7hkACJq11KgjZSYAL7pk+62fPvbVLx6+56N3ffqLx4b/R2AMJwD/7Yt/FRWb/mZ5ct151oZnvOoPVDCtP7juyd31J+wzS7E+b75kA/Gr190qgxAEQRA0tF67830P//hnXzz+48FF3VLnOVsh//2LNLRW1ZeSWyGP/o9f/dIj+z/4yF1GP9hvxGUS9UP2g6Hy3quvURFq+ANq5eubflh3fZC6pc55K029+2+6ZwBIGzc+G4J6iMdPp9SoI2UmAFanURrw5iu2v+7lW3gqoFvUGw/6TuQMwMfu++uo2PQ3y5PrrrM3nPHq/6aCU2o+fVJkw9nvlREIgiAImoled+Ut5KG/cPzHg+uvf/xP1HnOVsh8s9ePQmtVfSnqNmyFPPo/fPnz3//w+763z+rDtxiZglm87aqrqav/n0eVaS3V+b5tyD+/t4/a3sJl6pY656009TsPZ80AKFcHQZni8dMpNepIkyQAk4t6s/Y+F04APv6lh6Ni0y+lKmTrrhdtOOM1H1XBKTWfPmexFQiCIAiKyFrzf/rC8UcHFycAYSt/bWYAHo0qJABUkApBVV9KboUTgO/etvu7v7ebfv6tFRfMz9/b/Xu7rqLe/rUORShuWnHN33P1g6ghJwC8laau+WvMAEAzFI+fTqlRR8r+DoD+M6BBdzcqV6LeeNB3ImcA/vBPH05JJQCpVTJe6eO/c4p5embDKW/9HWOjP26C12yxIWLLXbaaddhvvZRjp7z1C1XQ1g+KN3xf2IRo6IMvet/DH3rrGbYYKjT7ie+nFfXm4OaRtn/6hdec6mK0ORPxvW3YcOk1rg4EQRAEdev1u97/1ROPfPi//0VUV/6/t7EXj4rWqvpS1C11nrMV6urvLFRoDzYlt0Ie/dt33Hr07FNb9K7Nvxl6JqhMEVWnKeqWOuetNHXld/4JMwDQNLr22uuPHv3Mt7/9V1/84n3vfvd7Nm06U67l8dMpNepImQlA+HugTZ3TqFyJerP2PhdOAA5++bs9xNZfFuo6cM6GDefcYsp7jAs/Y+vH1VqOmGobthwwwVsoDbj02trapuoNT71hDwVrDWWQjPt9plVVIajWT8Z+RoP3bT3Vb0KvMhutr4IgCIKgNnVac/rITpFjzTO38n0LFaRCUNWXklvpTADY/XO3AYp05gCcAPBWmnrrX7kEgIhaLLZe0tJBUNAf/dGnTtb5kz/5U5kD8PjplBp1pIkeATrz7PMv2Oz+FlCWqDce9J3IGYA/+rO/bdcTGzYEhSD7/mbZ6Q9veAoZcbdobPFr/9CW338Z+XILR8SqqiyDXhM3TJRVP6n9jEaabTdcdl1VmSOCLQeqVRAEQRDUKnLPX3vokTv+x19GReb4r9PQWlVfirqlzmtbOfSXUXVvpdEk6GsP/TBshROAz71k42fP2/i588xPLnzuvGd+7iXPfPd/2CI3pMq0luqYtla2ycYgTgB4K01d8e1eMwCXXLPPcc0lalVPXXr1vve+6RwVFMraYlcnQedccXNmzYhoKxVXX6LWppS9b5PonDe9d9/Vl/rFl7zpZrdX+26+4hxRraFhdubaa68nx//DH/5w166rzztvy1ve8tbvfve7FPnABz4U6vD46ZQadaTsGYDzr//YA8ccD4Q/Cdoh6s3a+1w4AfjUV77XIun+WRxn098sO33iHU952jtuc4t3n7th4+s+YYMbLrveRL70uqfZSFglq9WCVn0axsrNfqL76RbrkWhbF/FqRiAIgiAoT2+46v1f/+YP71x7ICpyxt9MQ2tVfSnqljqXW7lr7YGoOrei6kt9/Zs/Clshj/5Xd33oixf+RkPPo59yK1S+6eILVaTepCbqljrnrTT1hm9OPgNg3LN34edc8aZcB9yuVkuau8V2XzuUBe/Xz1BbF6LTEoy+OUUiG3FnKbXRYXbm6NHPkN0n9x8ir3nN6yjyjW98I0R4/HRKjTpS9ncAjt1zy/ZLzzqN/xbQrZ+e5f8BuOer328ROX5ZDots+qVCNav/cu6GDed+wJRv37Fxw4aNr/+j79/zgVdueNo7b6e1f/TOp3DEVOOCLMugVZ+GsXK8n8Z+miYs0Umk7Z+8/mkbnrLjT+r1VQSCIAiCsvTGt916/1///R984VtRXbP7I+SMU6K1qr4UdUudz3Mr5NEf/v0Pf/nV5/3pq3+T9OXXnGf0aqfdl10a+qTyl1/9m82IETcxP+2ibUvdUue8laZec2LyGYBLrum6wdxDrZY0d4vtvnYoC96vn6G2XumcN7335je9xJbNvf/YXERqo8PszMMPP0x2/8Uv/k0ZpAgRFnn8dEqNOlJ+AiAd/2z/E/B//9ojOWL3HxaV+w/xSh98JT8I88s73vniDRvf8EkKfvkNT7Ohp73yxU/jyO/7VbIsg6weDaPlZj/R/QySncTamgqOF3/QRj75zl92gQ0b/sPv+34gCIIgqEOXv+0DD/7tY3/0Z98dXNQtdT7PrZBH/9uDd39t+yVf2/4KIV40P79+hQq+4msmIuuHypd87QorG6duqXPeSlOv9AkAEbVYbL2Cn7Mi+7jPW08vewfa4m7VXxIelHHPqBjTefXV7/UVqudVrHO1lvQS14nuvGOLwfsGXxsKoWx6cJj9ERVS/bzJPXQU2xnpns2BuDouUbEV9LF0b7E6Ofpk1tc60XZlh3IVi1p5/CH7TsTOGFFX9eb2QKrFhD73uT8mr79t25tD5MILX06Rhx76Zojw+Pnwh++0eYGDFjkepEYdKT8BmN9/Av4f//OH7WLrzwpB9v3NMgRBEARBPfSmt3/woR+cVMFBRN1S51yez1bIoz9y78H7r3rDQHqjlSlTt9R52KjSy9d/NvEMgJGz7w3nbbxj3TGHVcaP+lXCNFfVaLW9zW8e92/a2eYWfdnY37AJVcgJRvth0xzdGbvWwasowq46LPpjie9bfIuRVMGdTLk2iIJ+x6if+AyJ6Cq1CaOeCcDHPvZxcvMPP/zwq161lRbJ/R8/vk6Rj3zkrlCHxw/pD/7gY9b8n6RCCAapUUfK/g7AFjL9933qrgP7zX8Cto8D6ToRUW/W3ufCCcChv/hRi4L1V3E2/c0yBEEQBEE9tO2aD33rR/905NjfDS7qljqf51bIoz/6+bUH3/HbD97w28ff8dvH6ecNpmz0jreauFn1VtJxt2jKrsBlXmubyObULXXOW2nqZcddAkBELRZbr+DnajL+1XpZW6iorDMTPK43naZ+3XFqqyrtqVBti1UPl1zNljo0jPYWC3b0o8qpiDtYZ+vrFXSfnVu0x1ih5isqUdD3U+9TSDaMldW2qkPo1nveczMbegXlAM997vNDNR4/LLL+UfdPUqOOlJkAWM3rPwHf+5c/Sim4fyVaxaafq8kyBEEQBEE9tONdH/nC17/17R//8+CibqnzeW7lpU/9tT++4yM//fP7Bhd1S53zVpra8mC/GQAn91domga0irzEP6kiDGjEsKasqlZ0iwUnAGbiotZn5xY7To4MhmphK0qyYapMaswAdEm6/8997o/vv/9+Kjz00Dc/8pG7pPsn8fjplBp1pEkSgMlFvVl7nwsnAGv3/xiCIAiCoMXq9z97fMe77rji2t8dXNQtdT7PrXzkwNoFpzzr7F960uCibqlz3kpT531j8u8AXHKF947Gd8afUbHPkCSegZENff02e5rcorO8lWMODYUhNta8uQOh3N6PKrdEqCH/5EV/dJE+zdquLbacnCA6RhGsZSCm58ZfAUqVSdQV70aWfvd3f4+tP0FltVaJx0+n1KgjZX8HoPbff0kz/A7AkQcehSAIgiAIGrtefKzHDIBxqA5+2odkvKzHBI0FN9x8zdXNGYB6J9a2tthTjngiW4w1tIbYcPU1IXgJ92J6EDXb+2nfGePULw3JjJmd8F8Ctl+3NXhTnr/F5sls7oOR+CtAVrKV/0pA/JATHVay+ZsOWk3k/kk8fjqlRh0p/zsA4V//vu7Km27du/+Gl+s6EVFv1t7nwgnA0WN/B0EQBEEQNHa96IEpvgMAxdVlr4cSOf74d3+nlX8wKaL9++9m908FtSoqHj+dUqOO1O8RoOH/DKicAfjMN/4egiAIgiBo7DrLJwD9vgMAxTSvBCB8I6IRn060/21PBJH1z3T/JB4/nVKjjjRRAnDm2edfsJn/GOhpalVc1Ju197ls2LAhmgDc8+W/gSAIgiAIKlnKvZCef//PyNuwyYlaLLZeytVBrZpfAlC+ePx0So06UvYjQOdf/7EHjjkeCP8ToEPUGw/6TngGAAkABEEQBEEjlXIvpJAAYAYAmoV4/HRKjTpS9peAjx3df9Nbzj/N/kcw8z8BZvKfgJEAQBAEQRA0Uin3QsIMADRT8fjplBp1pPwEgB0/F2b1HQAkABAEQRAEjVTKvZAyZwAgaKZSo47UIwG455Ztt34aMwAQBEEQBEFCyr2QcmYAVASChlV0jGUmAK+4/gD/3U8q3P5+8yyQXJsU9caDvhPMAEAQBEEQNGop90LKmQFQEQgaVtExlpkA9BT1Zu19LkgAIAiCIAgaqZR7IeXMADz5yadA0OwUHXjZjwDV/g0wqczvAOw/l7rwPOWtX7zn47/zlA1nvP7jvIoLg+mGLXYTIXLLpRu27BdbnKNo057aLrVrIbvq1Hw5Wl6g4V87CIIgCBpcyr2QcmYAlF2DoGEVHXiZCcCc/hMwXSRTJwBzNJHs+P0i5QPn3iLWzk3G/YdD++LrT23PAQox083dmO9rB0EQBEFDS7kXEmYAoGH1G79x1qSKDrx+jwAV+1eA5msizR30S29wi9R/KM9TxvHXEo/aXjVViJlu7sZ8XzsIgiAIGlrKvZAwAwANK2XucxQdeBvUcq4K/U/ALbZSrDIWmZnSsgvzXc0GJDckpgjqdcQ0wsSK2H3aK3HIt7h9sNMCFPGYjUZ3tb6Tb3UPF/lZBXPIzHTTHWLTzYh+gcIqW6gdEbeFIAiCoMVLuRcSZgCgYaXMfY4GTQDylJ8AzOI7ANah1r1jrWBc+5Qm8va3nsE9xMx9Y0MhSaDFU13D0ENPkVc+9XdurwVDWkI7sGEDrzWWurFXtV31+1+ryXkCP2VkvXj9qacpZDvXNPbQvUC1/WwcEQRBEAQVIeVeSAPOAHw5G9UQWiYpc5+johMAhi6Smc8AVHeXLVPaWee/w013UnpDrjJlC/Y2tm7YS2YrrTMAvnOfosig3NWqk66ag9x6r+1bLdI8b1XlWquFfekCgiAIgmJS7oU04AyAc/cZqIbQMkmZ+xwVnQDM7DsADe8YcczTyLpt5+Y50rIhtub7z3XW/9IbqE7VsJ+on7oPrrYrz0aoJoPxXW1LAGyF2996Br1S05nvWoe1SOS8hcqyVePAIQiCIGihUu6FVNAMwM61k461K09prHXatfb4+t6XqmBMW/aun8yrGdGuteN7t5h9oM2dPHl4l6qw5bb1k22dx3ay2h/bp2f99gtq1SZQrZ+1XWpti8LR1WQOKhypeS1aXoU2KXOfo6ITAGYeCYApDPn4OLth0WHbhswDP+Lhn3O3TPsMklF4PsdIblSU41lBbVedme6o6TTtk0uNDtXO1DuPrYrkCRAEQRC0SCn3Qhp2BuCpTz21U/EEwPhj7zi37N2btLPtCUD72nzJBGCdqPfJzjtnN6L7M9xOhn4m8+uxBIDO/zoHL9h7nHKetbXHB04A9u3bpyJBRScA85sBoKDxjp7pn2g3vcmNtm5IVtYNp5DJARziprjZk3O3mPxExm/YYpdrj9bIXQ27JNaGcrWhKc237LwR0ectrDKF5hFBEARBUAlS7oU07AyA8vpRxRMAsrDOgLar3T0P561FArC2tl67T0+7avxxzm5E92e4naz6majPSAKw5bb6MZoOh0wAyP0zKs4qOgFg6CKZLgGApJome+xaviOCIAiClkfKvZBmNwPwlFN+mfTLv/yrMkiKJwDGcTaehzHTAg7/iEtwuk37a3pwmEdZRIVUP3vdQ0fp53BCz8ENX7D3OEe4c7GVqhxacfdqf2QTpyvvdRXF40b2TrzF7XN1FLwzoh+ZPulqpEZXWnxQMkKdNxMAu8Vdrn9/0kyQciS3uS17lbknOe/vUWtJRScAA80AQFJIACAIgiBoflLuhTTgDMDWrVvJ8bPLp8LNN998zz33yCArkQCQnE8VHl16X+WeQyEnGO3Hu+2252dcJ2TQqx6M1ZadR7fYvtY6aEvdkYc65lQ0bsn7rnau2VWinyptaFZrdtUUtVJnoBnhoHn0yWQa9TMpkoGTytw7119H1Sk6AWCQAAwqJAAQBEEQND8p90IacAaAHD/BN/6pQEafoVV5CYCVvYFtbLEpVB7UW3CymMF3eqfbHuzoR5WVRCfW+E64G+1rhUwSwthV9X02sqelQk4pyMrNas2uIqKuVJ1mhIPVnkfOpN2WdPbO78eQ1YpOADADAEEQBEHQqKXcC2nY7wAQnAZQ4Q1veCNHaNUECUD4czR157rgBIAfktkVvikb4tF+Mtd6VXvoH8VpuvZmRPRTPcGf1bAp6qrZebOV3HMzsdCZAGSq6ASAQQIAQRAEQdBIpdwLadjvAATTTwX2+gSt6k4Adu6VzjI84mItpnSxwW4GA8q3zzkoHWoot/ejykpilb1JL5514Xj7bkS3IoNW1FA/VxNOQqhGrZqRaOeqWrOrpqhOfZdMP9EEwHeVPJP6EaAcFZ0AYAYAgiAIgqBRS7kX0rAzAP0TAOsdHeGJduMymabTdY7cIP4mz5X8bVr5hExnP7WyklxFLjl44vbdqNbG9qe5OePRDetra5URp2o2GL4nUB1F4wB52qTKIjzuTDa6aijvrwCZLdrv+8quartBW1fmPkfxBICiSqpGq15x/V03NIKVqDdr73NBAgBBEARB0Eil3Atp2BkAIvoIEBcCshVUhChtcE83taju9RNS5j5H0YE3ZQKw/cCxuxvBStQbD/pO5AzAZ7/x91J0/agLDIIgCIIgqDSRY1EeZsAZALb+oezMPuz+SOS+etGIC61kAsCkEoDHAQAAAADKpiUBIKIWi4LK4WWKcgD+M6AqDo1WJSYA2w88cOxYVLOYAXjw76XocrrpppvctQUAAAAAUB7kVUwCUPcwA84AQBBJOvttaWS16MDLTADOPHvLBZsjuv5js5gBqF88SAAAAAAAUDjtCQARtVgUVA4Pgloknb0z+zFktejAK/I7APWLBwkAAAAAAAoHMwDQHCSdvTP7MWS16MCbKAE48+zzL9h8/jm/VkW2bL/pLaKCFvVm7X0uqQTAXVsAAAAAAKWCGQBo1pLO3pn9GLJadOBlPwJ0/vUfM0/8Wx74+HW1NCAp6o0HfSdyBuBzD/69FGYAAAAAAFA4PAOgPAxmAKBhJZ29M/sxZLXowMv+EvCxe27ZfulZpz39aae96JLtt3762N3bdJ2IqDdr73PxCcBPpJAAAAAAAKBwRAJQeZiFzwDc/I0bM6UaQmVKOntn9mPIatGBl58ASMevFpOi3njQd1KfAaiuHBISAAAAAAAUjk8Aah5m4TMA5Ozl/wlOKZEA7HL/41b8Eyv3z3erf/rbkP3fvfV/fKvivlum46/jt6veVfp/8S6NpLN3Zj+GrBYdePkJQHjsxz4ONNMZgOM/kaLLyV1bAAAAAAClYhKAuoeZxQzAOedM0GSYBKCy+81IQzIBsGVnylUC0P2fcXPE+7N2pelKlpdW0tk7sx9DVosOvOzvAJi/+Hnfp+46sP+uT3+RHwfSdSKi3njQdyJnAP74+E+C6OLBDAAAAAAACodnAKSHIQ0+A3DRRRf/6Ec/UsEWhQTgDW94I//nYCrQIhXCT1JLArC+vl439C6QkwDwdEHjrvyMEgDeXPf/0hq1pLN3Zj+GrBYdeJkJgJV5+v/NV2x/3cu3ZH0DmES9WXufSzMBICEBAACAefLJ5cUdIQAzoD0BIKIWi4LK4bWI3P/f//3fk8lV8RZxAsDuf+PGZ1H5eb/+fJMHCNoTgJOH1+xP86DOltvWyWDvDT5beH2zir2+D/qHhSzUvGUGYMte05gJcRF06UekmkgAeG14oCizz7FJOntn9mPIatGBN0kCEPkzoB2i3njQd5KaASAhAQAAgHlCRvl7ywgSADBTZj0DQO7/Jz/5CZtXtapFnACQy3/pS19GhSD2/fyT1JoA7LJWnkz2BXuPh8XuBICCtRkAlQB4avMDoQ479dosgdsZU668fqqrWOVIn+OTdPbO7MeQ1aIDL/sRoBn/GVCGE4DPH/+JFF1O7toCAIAMrgXZuFNWBwkAAP0gx6I8zFAzANL9E2pti6IJAC1KOhMA9uVre42BJpM9TAKgjHj93jz3xp042eY1qgTAJye8V4nKkT5HKOnsndmPIatFB17+l4Bn+2dA5QzA59d/IjXSGQD36QoycKcMgIGgQUXvJKCT1NWHBACAHvAMgPIwg8wAKPdPqAot4gTgbW+7mox+eASIc4Dwk9SRANiCffbfPGwzeALA1cwqX6fqze9Mwr6HBMCbfttttHKzzzFKOntn9mPIatGBl58AzPbPgDJLlgDwRyxoBwkAGBxcfZkgAQBgQNoTACJqsSioHJ7SOeec+6Mf/chYW4Gq0yJOAEicAxCXXfZKjkh1JQDOo4tylQDICioBqHnuZAJQ3byvjHvzcR03RWC9vultr73ZLxIA14/dXLQyHgESyk8AZvtnQOUMwBfWfyKFBGC5QQIABgdXXyZIAAAYEE4AlIcZ8DsA/RQSgHZ1JgBs39nKVwmA99xm2f5tIJUAeINuO0kmAK6JWSv/4lD9oSAVMe11AhD6sYuRyrE+xybp7J3ZjyGrRQde9ncAZvxnQBmfAPxUii4nd21Nyv27N23afb9bmDewIJksYQJAA4+GsmXrQRcbgOnG88Gtw+wP91PDdioO2m9Fhpqbbl87Hbj6MhkwAfjSOza613LDhsvudsHSQAIAZo1NAGoeZqjvAPTWdAkAVJyks3dmP4asFh14mQmA1Sz/DKicAfjiiZ+SvuDVfwZgOsNkmKIHWJBMli4BIIfsB43xuK3ONjXAovGJKmtor4b12LUOzYFW+2ByBLNO7lhzJ9vXKjor1KldfYcvt6Z0w4bLD08VWUaGSgCM+9/4ji+5pbsvm2kOQBurtjUZSADATOEZADYw7GRIJcwAZEo1hMqUdPbO7MeQ1aIDb5IEYHJRb9be50IXCX0mhcuGNfYE4MwzP/gdLk3Kdz5o2vJPF1pCli0BmH7UEdFOUj3nbHGQvaohE4BE77VwIwNpX6uYcP9FAmCMPHt4KtkrqV9kORkoAZjCkveghATAJLkDXFE0rm2WaWi9AJaC1FWcc3XrOrV3DPNqMIs+iSEBkFr4DAC0ZJLO3pn9GLJadOBlfwfggWPH4rq7UbkS9caDvhM5A3DfiZ9K5ScA1btA/QZkLL51q33j3bT7IL8D83tLvSbVsyX93lR760mxyARgVDnDsiUAZng1rUH9E0qMQFNVLpr1iYFnqnHl3bt9d3qU+iW3bCqHngmzcX05GOq7R6h+IoirwO5SpJaMN+tE11LBbdd2buJi/1397guwSgCa/r1fZEkZJgFIOXIzL8DY+QBb7R2XiVAzUmsVOjVTCsxld/vVvXKAoRIAMwRpYNZHdEVztMcwg72qZq7BjmE9DfISy9i3mZDadM4uVXWoZAdA5P0np6PZwgmA8jALnwGAlkzS2TuzH0NWiw68/O8AXLA5rnMalStRb9be50IXCX0m3ffQT6XocnLXVj78PtB8NwjxYI8qn5SoqeLZIAHIZOkSAMIMLAuPHrPoP6zoY56zTjHwzHo3zlxVjtsGFVVl31uIVK19s6qyjYg1FS5oKtV2T477aEODcOGpOqbjQKNGZK0JcaeuZH7ZVVSI70accPXRpaCe4ekXWVZmmQAYp86e3pWsda9cPjVpRvyvesTXMZnAxnfcHd1cFgMlADQcaXQeTGYAWcN1wjE9JfPdWpzUPuTsm64j3n/ixYVhEoC6h8EMADSspLN3Zj+GrBYdeKU8AlSbAXjop18Syp8BMO8R1k0Y6M0ivGW0xJsFV69ec3J0AmA8BROcxWH/lLELVcscoSY+AfigX+UaN3oLgTM/eNgVR5IDLGMC4GnYaYcaeLIClekjrNmEiFaWESrYV95jM42wSrZyFRKDvNlPbTWTlwBE40x0uyHC5RBp76qBTADOvPxyd23Ya6VfZFmZYQIgg1zOjPBpd8Tsvmw1IcMkADQazdj3g1IOTlMWk3scsUv6/r5sJVH1bTUx4xeL1FqFTukKddTmCW3zyI5Fux3WUftNV3tWHZGcAvWVOcBH5Nt6qh2Ta3StucMzANLAkDADAA0r6eyd2Y8hq0UHXimPADF0kdBnkrp4shMAekfw1z6/Dbg3g1RcvFt01pycegJg/DkbCV+qIpEHDowB8ff+TUVfkyOR3qgHG+BlV20cLHMCwJ9SzVGkBp6s0IwEOitTQX1ay1WuVcYgb/YTwR6aKze7sCTCjuh2Q4TLIdLeVQOZAPhry10r/SLLyjAJQNSSR819TiTc7mdkHaYZyWaQBIAGIw99Nyrl4ORyFaGSu06qEiNbVTTqm1++HTdpRvyveiRszV7y+l5AVcGVzC/V7dA0u+WI2LQpmpKoGurU2lbvP3KNrjV32hMAImqxKKgcHgS1SDp7Z/ZjyGrRgZeZALzi+v23v/+mq7aaZ3527T164Ebzt4CGfARIzgD8yTf/QWqSBMC9IziT494MUnHxbtFZc3JqCQC5COcnrKNQkYAxG55Qp72tK9Mv10gEx8GSJQA0ZMIgcqOoFrMh9WEs1rsix22kIlQOq3SESvWOwqqqTmOQy1bVuK/3Y4t1RD9cy/VP0Cq7rtpojMjaamOuFOq0d9UgXH2UGutrpV9kSRkoATCevPFXgCov70rSuHO5GfF1XcQ185EiHgEyY7OChqUcnFyOjltZJtQi06yfGXF7w4h3mEBo1dKJinB5QEK3VHC7GjuBdOXLCobmEVXvP6p1rdbc4QRAeRjMAEDDSjp7Z/ZjyGrRgZc9AzDH/wSsLh66nNy11UXtTUO8raTi1btFqqa1MuG2iKdmfVJMngCIeQBZp72tLLuHiDADsGB40FjCOKliJqQGnvm5yY08jkcHXlWZ64R+ZOWwIVspVBatqOiqEC5Y371axDfTUIXa7slu3Qqx0QjRtaEXXlXVUcdY23STKgEw1wTfwaergkv9IsvJUAkAYXy6Rzh4C/t1WlR2vxkxpfCV37BOfgk4LPqkYBIGSABoTFajzw5Q6U15xIZxWw3getmglw3N+pkRdUXIOkyIhCbNTlSEywPiuqXr1/ee2jT97Dgi8SYQLy6MlgSAiFosCiqHN5QuuuhiFZlGL3/5Jffccw//L+GrrrpKrYXmJunsndmPIatFB15+AjC//wT8p9/8B6nsGYCyqCUAwkb4kjQW5DaoUvAcPkBVwk+Ou3LV1pXML65kaxxGAjAq9GcbmBaRANirifGXV8/IMjJgAjAKpk8A1MVqF3fXHCj7V1eJSm5dVfKYSNUXtaT1jfr0K9ThcjPi67qIa+YjvE85jwDpbofGdVs37BSp9iXsViPk2gZEJ9UqXWn+8AyA8jALnAF49NFHh8oByP2z9SduvvlmtbYh/99/Df5f8M5a5l/8zmtbC5V09s7sx5DVogMvMwF40SXbb/30sa9+8fA9HzX/Cfjo/pvecr6uExH1Zu19LnSR0GfSn37rH6SWIgFgq26prHmwGM5jhCoGqmbNfPx+f6O3eoB7HodzQQJQwMfWslFLAEAaJAATwo7VLRisPd1NPxgzl0frqRphHaqpYIld42ElIfyuhevLNwcuNyOmxFsMzWSEe/a7FJpQwa5NbsiUqJX32dPjuw1bNlBELod9UEckd89Q2zF1qAvEJQB1D7PAGQBy34888sggOUC49y/df3oegBIA58W33GZs+ZZT5NoBVW1odSSdvTP7MWS16MDLTACs5vWfgL/8rX+QGnsCANpBAgAGB1dfJkgAABgQTgCUh1ngDAAlAGQEB8kB2P0TIQGgAi2GCnVJXz5Tj44EIImsFh14kyQA5uGfCza7B4GyRL1Ze58LJwB/9u1/kKLLyV1bowIWJBMkAGBwcPVlggQAgGEhx6I8zGJnAOgnecHpcwB2/wxZf3b/hKrmFU0ATGFtbf3kybUrT+Endhxru0TNXS6+fvsFrreqpm1Y9SM4vKu2Ud3kgr3H/bLb1oglnT17/SiyWnTgZSYA9rn/B445HgjfB+gQ9caDvhM5A/Bn335MCjMAyw0SADA4uPoyQQIAwIDwDIDyMIudAeDC+953C+UAZ5yxMayaVGz3Fffcc4+q5lV5cfEIEAWDrTdl58WrZ/dN0FWuBb2t37lmm6t+/Nqq3Giyc81mCFxt9JLO3pn9GLJadODlfwn4nlu2X3rWafwg0K2fnuVfAfrzbz8mhQRguUECAAYHV18mLQnAsuKOEIAZwAmA8jALnwG46KKLyf2TI5SrJtJHP/pRZ/nrvPzll6iaXsaje/gePAe9Lzf+PsRPufJeTgakm/fB6l6+Rd3pj5abTWykmlIYuaSzZ68fRVaLDrz8BGC2fwZUzgB85a8ek0ICsNwgAQCDQ4MKZOJOGQBgajgBUB5msTMAw7r/z372s1y455570u6fVLPykWB3AmAe2vEJQFXTKmb6ZTnSxMjMReARIKH8BGC2fwaUSSUA7toaFe7TFWTgThkAAAAwZloSACJqsSioHN5QIr87oPu/ufuvfwZJXx4NUtl78cqvm6C7Tx8NOql+muVmEyfKAZZgHkA6e/b6UWS16MDL/g7AFjL9933qrgP7zZ8BtY8D6ToRUW886DuRMwBf/c4/So10BgAAAAAAqwPPACgPs8AZgMcee4yMoApOJOf9J3P/JOnLE0Fj8Zmagw/f7q1u1Vc1m48AmdmDSFw12bnmyrGZgdFJOnv2+lFktejAy0wArGb5Z0AZTgC+9p1/lEICAAAAAIDC4QRAeZgFzgCQC1SRSdXL/fdWNG2AtKSzZ68fRVaLDrzMBOC1tx7+wGuSi0lRbzzoO5EzAF//63+UQgIAAAAAgMLhBEB5mAXOAIxNSACyJJ29M/sxZLXowMtMALZsv+nAkQfuuWXbm6/YduunH5jtfwL+nw//oxRdTu7aAgAAAAAoFXIsysMscAZgbEICkCXp7J3ZjyGrRQfeRI8AbT9g/gvA3dtOa6xKiHrjQd+JnAH4nw8/LoUZAAAAAAAUDs8AKA+DGQBoWEln78x+DFktOvCyZwButDMA5jsAt37aTAUM/CVghhOAv/ibx6WQAAAAAACgcDgBUB4GMwDQsJLO3pn9GLJadOBlfwfg6AdeE278n2YXq7VJUW886DuRMwB/+TePSyEBAAAAAEDhcAKgPAxmAKBhJZ29M/sxZLXowNuglodVfgLAcAJw/3cfl6LLyV1bAAAAAAClQo5FeRjMAEDDSjp7Z/ZjyGpFJwByBuCB756UwgwAAAAAAAqHZwCUh8EMADSspLN3Zj+GrFZ0AsBwAnDsb09KIQEAAAAAQOFwAqA8zAJnAC666GIVgZZA0tk7sx9DVis6AZAzAOriQQIAAJiIa0eLOwAwX9zZB9PhzuYK054AzH8G4NFHH11QDrBr7XH3r3eJ6n/6NsX/o3d975bx/4PeuUk6e2f2Y8hqRScADCcA3/jeSSm6nNy1BQAAGZAXoXeS0VGOhfrk8uKOsM5IB0xRIAFgyLEoD7PAGQCy1o888siwOQD/b2CJqmAl/qK/sfhrV8b9vckT2tIDKCbp7J3ZjyGrFZ0AyBmAB793UgozAGAFoU9TkIk7ZQIKsikZF9FjWQhklL+3jCABmB3ljN4FwjMAysMscAaAEgAygv1yAOfuLak4I9d6yX/p1fLvvVpWQUlJZ89eP4qsVnQCwHACcPz7P5PKTwDs/Z2icTtah943QSbulE2IO/sF43ZUQAfLH6ugneioGOnZ6z3CB4fGpLPMy0X0WiNwuU1POaN3gXACoDzMYmcA6Cd5wR45gHP3llSckWu96jMA4QmfLXvXzRM/xNqVp5jb/8z67Rc01rpO1tYoZhdja/futU8QhR6MLth7nGN+bkE3bFQYm6SzZ68fRVYrOgGQMwDr3/+Z1EQJgHubLxJ89kxJ7w+YMQ4MjIpMoqNipGev9wgfnMIvmd7gTXh2lDN6FwgnAMrDLHYGgAvve98tlAOcccbGsKpTzt1bwqKKM6GJUGXuTx7eJYJVVmAtu4jE1wZnH1/rOq+eMjLmXiQDsYZUudqlUUo6e2f2Y8hqRScAjEsAfvAzKbqc3LXVxRh9HoHPnkx6f8CMcWBgVGQSHRUjPXu9R/jgFH7J9AZvwrOjnNG7WEwCUPcwC58BuOiii8n9kyOUqzrl3L0lFWfkWi9vu83dd7bm8k68xbhw4c6nWRvdHKvZ0EbqScLIJJ09e/0oslrRCYCcATjxyM+kMAMAmN4fMGMcGBgVmURHxUjPXu8RPjiFXzK9wZvw7Chn9C4QngFg6/LQI//EhcXOAPRz/yTn7i2pOCPXelXufMtt685tN925tvh913YkAKqhEe0VnRw8AqRDAyo/AWA4AaDLRgoJAGB6f8CMcWBgVGQSHRUjPXu9R/jgTHvJfOkdG+nd3HPZ3S78vbsvc6ENG9/xJRdTlQmuX9UNVB31BG/Cs6Oc0btAOAFQHmaxMwD93H+LnOsXqApWMXduCunnc6Zdy+XoI0Dx+/1VZjI2SWfPXj+KrFZ0AiBnAL75yD8Z/dD+nF0CQJ861WeQ/QgSH0mzAJ89U9L7A6Z9YMzCZ0xEdGBgVGQSHRUjPXu9R/jgTPZe2kS+u4ayudL8pWXecX2N2ltxY9E0G+yCxJtwP772ta+5kkAFyxm9C4QTAOdhvBY4A/DYY4+REVTBuUi6c3u7nb8HbO7He/RjPNOsVWVXq/ElYNuQ//OAITIzMApJZ89eP4qsVnQCwNBFQu8jxvoL0eXkrq0uJvvQEh8z7oOp43NoWvDZMyW9P2DyBkaezxh6VBDRgYFRkUl0VIz07PUe4YMz2Xtpk9plwldW48oJF5xeo67EvAszD7wJ94CM0m/91m/RqXPLFlqkIK1yy0gAPCYBqHuYBc4AkAtUEWgJJJ09e/0oslrRCYCcAfjWD/9JatYzAPR71vf+GXz2TEnvD5i8gTGkz5iI6MDAqMgkOipGevZ6j/DBmey9tIn09Fw277P16ytEZGVCLSIBKACVA1BBuX+inNG7QHgGQHmYBc4AQEsp6eyd2Y8hqxWdADCcAHz7R/9E+pbXbBMA+nAJny4cMT8vu4wfSq0vbnzH3eZJob7PCuGzZ0p6f8DkDYy6z6DX3bzU/tXOHhVmQHkybUt0YGBUZBIdFSM9e71H+OBM9l7apLp8iHAFqfdNf8XVKhPqukECUAQhByCa7p8oZ/QuEE4AgofhwgJnAKCllHT2zuzHkNWKTgDkDMC3f/TPUjNMAOynDeE+XvgjysTFJ5ZcTH6SZUG753a0Dj57Mun9AZM3MKTPEK9xcxioxdSoaEYSRAcGRkUm0VEx0rPXe4QPzmTvpU2il4Py8SFSq9yshwSgFDgHiLp/opzRu0B8AlDzMJgBgIaVdPbO7MeQ1YpOABi6SOh95K9+/M9/9aNKdDm5a6uLyT60zAeN/dihzxf++OHPofBpFF2UhQnBZ8+U9P6AyRsYwmfQS2wzQ4+9y585KmRbjnQRHRgYFZlER8VIz17vET44k72XNgmXQ0UjFC44tUYbfiQABUHWP+r+iXJG72Ihx2Ksi7AxmAGAhpV09s7sx5DVik4A5AyAuXKEZjgD4D51jGUzRY6EeHSx1nAy8NkzJb0/YPIGhkoA6p5DvfrNweAK1Akvi1VdRAcGRkUm0VEx0rPXe4QPzmTvpU2ig58ujtollrpSlONHAjAOyhm9C4RnAJSHwQwANKyks3dmP4asVnQCwHAC8J0f/7PU7BMA/2nEd3lDnAtqURYmBJ89U9L7AyZvYEifQa+xX+CievXVYlUQnVCRV3URHRgYFZlER8VIz17vET44k72XNgnXhYIuCodYrSvTsrT8SADGQTmjd4FwAqA8DGYAoGElnb0z+zFktaITADkDoC6eeSQA/JnDn0ohzgW1KAsTgs+eKen9AZM3MJTPCFbFvtjZo4J+u3YEr+oiOjAwKjKJjoqRnr3eI3xwJnsvHQ94E54d5YzeBdKeAGAGABpE0tk7sx9DVis6AWDoIqH3kb9+9J+l6HJy11YXhX9o4bNnSnp/wIxxYGBUZBIdFSM9e71H+OAUfsn0Bm/Cs6Oc0btYyLEoD7McMwDXv/JXvnnwiqhUTWjWks7emf0YslrRCYCcAVAXz6xmAOYOPnumpPcHzBgHBkZFJtFRMdKz13uED07hl0xv8CY8O8oZvQuEZwCUh1mOGYAH7nrZPb+z6alPPVUpmQBM+Q93zb/vFf8GOFfVvwEm3H8Cjop3j/8/sVpVvKSzd2Y/hqxWdALATJ8AFI7b0Tr47Mmk9weMO/sF43ZUgFGRSXRUUHCkuANYNDQmnWVeLqLXGkFn3o0n0JdyRu8CaU8AiHElAPI2f4tUKyNj373v37J3b4sRH1iUAPi0wVj8VO5h8oS29KBsSWfvzH4MWa3oBKA+A/BzK7pyTCE/ARgp+OzJZKU+YDAqMoHtmAUrmACA6XFnc4XxCQB7GKfxzgAoo5+SamVE5nsxN9dFAlArK7WsGoGks3dmP4asVnQCwHACoL5AQ5eTu7aWFHrfZCsD2lmpDxj7eQqycKcMDAcZ5WXFHSEAs4Eci/IwqzgDYG+xr99+QS1opgUYvjFvXPjaGsXW19fF/XiXPEiPfsHe474lV9NdBYlWMgmp1Tf7xrg9TO6YXYyt3bvXPeAkjrFzJxsV+ko6e2f2Y8hqRScAcgbgoUf+SWoVZgBAJu6UAQAAAIXBMwDKw6ziDICR87ve7NasufXNxog7A01m/fAubnjlvdwk1Df91HOJZldylbXYhO8wsWkfia8NW4yvdZ1XTxll7KQ4xiklnb0z+zFktaITAIYTgD//q8eCvvJXjy19AgAAAACAscMJgPIwKzkD4GXvghtDX90OtxgrLCyyKfv768f5tr1faxryKq9IV2FtrFX7pqdZO9FO2kg9Segp6eyd2Y8hqxWdAMgZgM9+4+8/+2AlJAAAAAAAKBxOAJSHWdUZAKctt617+1u3yDUnbaqROeaftbVxb626Cqr6rLpq3/Q0ayffSXM28AhQlFQC4K4tAAAAAIBSaUkAiFVJAHbu9RY5PBtDXjn9kAyJHPP62trxYJrD2ujTNalb6bLPUG7WV9WmWcvlCXZSJDk9JZ29M/sxZLWiEwDMAAAAAABgvGAGwMvYX4d5bMYGzU1xj36WhmQ8dFVZ+2zXzt07111xNa5Z9Wlut/P3gNs33X+tKrta8Z00XxhgIjMDE0k6e2f2Y8hqRScADBIAAAAAAIyR9gSAWJkEAJqhpLN3Zj+GrFZ0AoAZAAAAAACMlyWbAYDKlHT2zuzHkNWKTgCYVALgri0AAAAAgFJZphkAqExJZ+/MfgxZregEADMAAAAAABgvmAGA5iDp7J3ZjyGrFZ0AMEgAAAAAADBG2hMAAgkANL2ks3dmP4asVnQCgBkAAAAAAIwXzABAc5B09s7sx5DVik4AmFQC4K4tAAAAAIBSwQwANGtJZ+/MfgxZregEADMAAAAAABgvmAGA5iDp7J3ZjyGrFZ0AMEgAAAAAADBG2hMAYs4JwEUXXawivXX9K39F/fn/IFUTmrWks3dmP4asVnQCgBkAAAAAAIyX0mYAHn300aFygAfuetk9v7PpqU89VSmRAFT/Fpdw/xkXGkjS2TuzH0NWKzoBYFIJgLu2AAAAAABKpagZADLfjzzySO8cQN7mb5FqZUUJwPrel9ryzjVKAa48Ra6FppJ09s7sx5DVik4AMAMAAAAAgPFS2gwAJQBkBHvnAMrop6RaWYkEoFaGBpB09uz1o8hqRScADBIAAAAAAIyR9gSAmH8CQD/JC/bLAZTRT0m1sqrPAKzv3cIzAFv2rptnggieE7hg73G/zI8JVRXCg0PRXMIU1taobmc/iQpjlnT27PWjyGpFJwCYAQAAAADAeClwBoAL73vfLZQDnHHGxrAqR8rop6RaWZFBZ7998uThXSJYZQXrt19gcoNqLVeQDr7y+rEE4KTpwQSNufdlVS21oXFLOntn9mPIakUnAEwqAXDXFgAAAABAqRQ4A3DRRReT+ydHKFflSBn9lFQrK2/BjY/3XwAQd/cN5MhtpPLusvKTT7nyXk4GUgmAD9Zb+YiguaGRSzp79vpRZLWiEwDMAAAAAABgvBQ4A9Db/ZOU0U9JtbKqDPqW29ad8246dSuqQPtpvP6QCUDrhurx0Uk6e/b6UWS1ohMABgkAAAAAAMZIewJAzD8B6O3+Scrop6RaWaVce/w2vE8STAXxCBCbePOEjwuaPyjUSADijwC1b0jHxyXp7NnrR5HVik4AMAMAAAAAgPFS2gzAY489RkZQBfOljH5KqpWVNOj21jt/D9jYes/hXdbQM/6GfVWhal5VO7wmcglRwTp+RuQPnuiGxizp7NnrR5HVik4AmFQC4K4tAAAAAIBSKWoGgFygikwkZfRTUq2gWUs6e/b6UWS1ohMAzAAAAAAAYLyUNgMALaWks3dmP4asVnQCwCABAAAAAMAYaU8ACCQA0PSSzt6Z/RiyWtEJAGYAAAAAADBeMAMAzUHS2TuzH0NWKzoBYFIJgLu2AAAAAABKBTMA0Kwlnb0z+zFktaITAMwAAAAAAGC8YAYAmoOks3dmP4asVnQCwCABAAAAAMAYaU8ACCQA0PSSzt6Z/RiyWtEJQOcMAMMXGIMygzKDMoMygzKDMoMygzIzu/LSzAB8ORvVEJq1pLN3Zj+GrFZ0AsCkEgC6rgAAAAAASqaoGYCLLrpYRfLl3H0GqiE0a0ln78x+DFmt6ASgfQbAXVgAAAAAAKVS1AzAo48+2jsHcO4+A9VQ6sp77T/irSLqP/hCfSSdvTP7MWS1ohMApl8CcP/uTdSQ2XrQBWfNrDZK/W7afb9bAAAAAMBoKGoG4OTJk4888ki/HICc/VOfemqn2hKALXvX19fWjkvHP2UCgPzBSDp7Z/ZjyGpFJwC9ZwCMEa8c88Gtc8kBem40x9wjAQAAAADGSVEzAJQAkBHslwM0EwBzt78OB1XDoC23ra/ffgH/9EEkAANIOnv2+lFktaITAGbyBGAhfrnvRpEAAAAAAMtLaTMA9JO8YI8cIPh7hsucCbBCUDX0umAv3/s38wB7t5zCQevgd+1dpz07ebJKDKiOjRBru0RN5/W5TD9dnfpjRSTalltjm6vFZZN09uz1o8hqRScAPWcAEnbZ3JP3mHvzptrWrfaZnU27D/LDO64drTJLPlDV3LpVdRJIefSqK1vdVtvtO9l60K+mtmIrISxb8Y5wNLopAAAAAJRGaTMAXHjf+26hHOCMMzaGVZ1Sdp+9voKDqqFT5ft9JmDi1sRz3Jh+jpugc+q1oEoAVDDI2H0xyXDKk3euNTKEpZJ09s7sx5DVik4AGLpIognAX8cwl5q3y0m4gnHTwVb7gvkt2quaElHLoBYdpiXnCa5kfrmIaxIamlVVSbcyayiFseFqvcEdOQAAAADKo8AZgIsuupjcPzlCuapT7O87lUoA5JM/VPaOvObgr7zX+n5j+teudFMEPpifANSb+0g9JVguSWfPXj+KrFZ0AtA+A0AXlbPACmeXGxjf7FHOWxZkNYOdHggdqk44SIROJDIYOk9FmoVQdhH6pTcLAAAAgGJpTwAWMgPQz/2TmgkARRQcVA2tyKmbJ3AE7NGlgzd37meSAFiZrAOPAHkVnQAwdJFMlgDUHHTg4NbgnGuuuuG86ae4v24IFZqd2KJFLxtkjMstkWYhlGXEPctU30MAAAAAlEeBMwD93D8p+HuGy5wJsEJQNTTaueae83ER7/VtYuDuzVfG3QSdU6+CoYntre25oMYjQF717x8vj6SzZ68fRVYrOgHoOQNgbbO4T24M89aD/vkZDkhXrQumtavKxVDBtKx3wmWLqVtFeKNVV65UdeU3FyLVKle3KoWabgNVVQAAAAAUS2kzAI899hgZQRXMlLL77PUVHFQNSVfeqx25fwrIuPa1NfeN3+r2vH1oxyJu8Bvfbzm8Fny/+ccCJuK6EsmAjXOfoWFsZmAJJJ09e/0oslrRCQDTIwEgjFv2VGY6wH5a2enKVxv77uvV/LbuxAYDci1vtArpTYQyb0umGclWKgwAAACAkiltBoBcoIrki/19p6IJADRTSWfPXj+KrFZ0AtB7BgAAAAAAYOGUNgMwjcwd/jxUQ2jWks7emf0YslrRCQCDBAAAAAAAY6S0GQBoKSWdvTP7MWS1ohMAzAAAAAAAYLws0wwAVKyks3dmP4asVnQCwCABAAAAAMAYwQwANAdJZ+/MfgxZregEADMAAAAAABgvmAGA5iDp7J3ZjyGrFZ0AMEgAAAAAADBGMAMAzUHS2TuzH0NWKzoBwAwAAAAAAMbLss4AuD/3U+eqq65S1aD5SDp7Z/ZjyGpFJwAMEgAAwGSY/64x9X/LCP93w+P+uccckP8VRJKKS3QdOhfVjod/cTLHgymJnBPYpF8rACzLOgNAdr/55/+Jm2++WdWE5iDp7J3ZjyGrFZ0AYAYAANAD43m3bk16tkw/p6rN0wWmtpWzD1UdKlmvH8x+bdXcDqYkmsedcyZW9WyBQVjiGYBoAkCUmwPw/wNe37vF/Jth8Q+Gxy/p7J3ZjyGrFZ0AMHSRIAEAAGRDfo0s78FkBpDp53S12q302ZLaw5w9b9nteHGVyHzpFf1aAWBZ1hkAUioBIFTNMrRr7fGTa7tUcEkknb0z+zFktaITAMwAAAAmhuya8bbetUn3Zspbt/J9cQ5SxC5FnomRDQle1L25yG7/aM0wBttvhXoJ+GPy+x/6pyAH+JB8W0+1J3KNrrUiNE9gOBFU4HDkxLpTq18Ow4pmUiCfZZoBOPvssz/60Y9ymQrPec5zVQ7AKjgBWKq7/lLS2TuzH0NWKzoBYOgiQQIAAMiEbBs7MmftgsMLoSpCJWffqlLAhCR2ddVW9BbsoFw7Dc1+GtsyRVMSVUOdWlskAAI6bHUC3YlwS1VcRMwpVCfLtQKgm2WaAbjzzjuDuacCLZ5yyi8r909KJQBX3msewDEc3mUj1pHv2rtuY+u3X5AOSl2w97hdd9LfzjfP8zj8DX7byV77wI/rxNz+ry/6ZMA3X79973gzBOnsndmPIasVnQBgBgAAMCHGt1WQS5Nejcsh0lzFZaYWoQVvC1WTZoTL0xD6oYI7ktix0B7JCoZNuw+qfUACIIieQIo0T00zwgV3nt2cAACdLNMMADn7YO65fMopT1HunxTqJBTMtzXl63u3nMIuvCUYZNx/PSsw9UUmIDrhNMM89792JfVWbVeWq+ZbbqNEQG1uNJLO3pn9GLJa0QkAQxcJEgAAQBZk0ZzdJaxxk4aYnZz0c2oVlxkVYSPdbNLeST9cP+LOc2pb9NP7e4esY6gSgERxlYiewPCzGZeR5sthiwC0s0wzAGz6JZMlAPwdXEMw35XhvvJeNuLRoJex+Ozm45FYJ9LrN4LUnJONWs3xSTp7Z/ZjyGpFJwCYAQAATIQyZnZxd8320uqqEpXcuqoUUH05z1w30bXemk364vqJbctHfLERcm0DopNqla60KjTOlj8T1QpfqkdMncbLwWUAWlmmGYAbbriBfT9Di08h/5+ZAFRO/YK9x5uO3Nzab3j3EPRCApCQdPbO7MeQ1YpOABgkAACAPBq+zLq43fSD2USwkyOsmTMVLE0/R6tqQecIQwvXm6xWlYVZ7IHvp9oWwdtyC3KH+XB8SO6PobYnoeo0ezdimicwnK6wKpy9KsLDptbaV5vuhQYrwDLNAJBuvvlmdv9UeErsCwCkeAKwc63xYA8Zbv88T+XjU0Fu0vkIkKovy6mga45HgEiYAQAAAAAAmJZlmgFgcQJABeX7g+IJgPXu9vGftTUxA7C25r7B6+/0J4PCu/NK6fuZpr+X5WiwejAJXwImYQYAAAAAAGBalmwGgBQSgFBuEiq3Sjry9uBcVE0gjE/S2TuzH0NWKzoBwAwAAAAAAMbLEs8ATK2yEgDzV0qr7wOMTNLZO7MfQ1YrOgFgkAAAAAAAYIws9wzAdCohAfAPJhnGevufJJ29M/sxZLWiEwDMAAAAAABgvCzfDABUoKSzd2Y/hqxWdALAIAEAAAAAwBhZvhkAqEBJZ+/MfgxZregEADMAAAAAABgvmAGA5iDp7J3ZjyGrFZ0AMEgAAAAAADBGMAMAzUHS2TuzH0NWKzoBwAwAAAAAAMYLZgCgOUg6e2f2Y8hqRScADBIAAAAAAIyR0mYALrroYhWBlkDS2TuzH0NWKzoBwAwAAAAAAMZLaTMAjz766IJygF3hP/gS5p/4mn+8NdBf/PT/zZdYv/0CH4/9RdH+G23sv64wG+XtsHT2zuzHkNWKTgAYJAAAAAAAGCOlzQCQeX3kkUemzAFe/v4Lb/7GjayXvmszRagQfiY0sz/wb9x/6Nn8XX+fA0y/RdmDKJstlvVPA6Szd2Y/hqxWdAKAGQAAAAAAjJfSZgAoASAjOE0OwO7/+s+9naw/lV/0H1/ImUCQqu81owTAOP7a/Xhzy5zd+cwSgFkdS39JZ89eP4qsVnQCwCABAAAAAMAYKXAGgH6SF+ydA5DFf9ef3/DUZzxDBcPPhJqmWUSMazes3763GfS32239ve5pH3ebv7L7QZQScA+2/q7Qc2NaQPfPbX1oF9V05ZOHd9Ua7lw7ub53Czfp6ETVEbmKD4pDjh2g3+6W20IfvD+1TUtnz14/iqxWdAKAGQAAAAAAjJcCZwC48L733UI5wBlnbAyrMkUu/z9+fLuKSMlVQsJP6zv0ZhU7Y2tzhRv2htu6YdsDe9/wEA6Z4ODFncKcgK3Pa41XVt02+zcNve1miTrcG8P7oCq0dSIzgbD16CE3DlBuwvXWiO9cugSAQQIAAAAAgDFS5gzARRddTO6fHKFclSmy+APPANRMvAiy22bUPfhatXDrnUUWnKvVtnjlvSErSPQf6aprizmd1CNuNyjYPOTo5mrBcBR609LZs9ePIqsVnQBgBgAAAAAA46XAGYBp3D/pP358Oxn98B2A897+YlUhoZqRrUWibrjppGs9hHK43+9VNZT15bRAov/cLZp79u4ef04n9chUCcDOtWryod6tdPbs9aPIakUnAAwSAAAAAACMkQJnAKZx/6SnPuMZnAOwBkgATMGZePU8TOsDOcIWV1ZYthLlyi6HhrImq/MRoGY5sxN52z7sRvSQo5sIhcrxcw9hQ9LZs9ePIqsVnQBMNAPwBgDAaHGXMQAALBelzQA89thjZARVcC4yhjVgnWuwtmziOR79EnD6ESDu3DcnnNX2ddbWXB8+Lhrq/nmtC3D9K++1C3rr1rVX3y7wJDoRdSL7rL8E7CqEsiu4PWEam5bOnr1+FFmt6ASAyU8AXAkAMCpw8QIAlpXSZgDIBapIWTKmVt7nHlzkp2fa/+Qa4pCls2evH0VWKzoBmHQGwJUAAKNimov34FZ6h6iz9aBbB0CK+3dv2rT7frcwCb0bglWltBmAwmXuc1cPx89AO8Vf8CxDgxyydPbO7MeQ1YpOABi6SJAAALDEDHHxUiKQYfxT7g2ubtXo8YpzEwwVMCGlzQAUKfPcvGdmt+fdAzPiIZxFauBDls7emf0YslrRCQBmAABYBeaXAADA9PbxSADAhGAGAJqDpLN3Zj+GrFZ0AsAgAQBguRk4ATAWbevWTfTOsXWreEDIrBY3cXf7VW1x7s0FNmxwzg/JxviJvdbycTKOhBffvPJikGAYgHx6zwBAUL6ks3dmP4asRq3UqCNhBgAAMD86L1662Ju4dY56AuCteoV0b6aCr90et33VI0ncboHF4V4JgVtRx6yIvNYCF/GDikcBB5uV67htgJXEDYI6FO83AwBB+ZLO3pn9GLIatVKjjoQZAADA/MhJAFwpST0BCBbNWDdPcG+qQmdcRrgMyiM6SJIjJ/rKUsGNlXDP3xdDNdkQAEFqsFF8OWYA1DMnnVLNoZlKOntn9mPIatRKjToSZgAAAPNjZgkABb1Zk+5NericuIxwGZRHdJAkR07klW2MFlskaIWZLeAghgFIkBpsFF+OGQDy9F/OBgnAnCWdvTP7MWQ1aqVGHQkzAACA+THLBMAH2d01PZyMNOPml+9CrgXlER0kyZETea1jo8WlBLbGQVsNwwAkSA02ii/NDIBz9xkgAZizpLN3Zj+GrEat1KgjYQYAADA/ZpYAmCK9gTiCe5MeTkaacS649uFZELEtUAzRQZIcObHXWr7U/FqHiFnialVDDANQIzXYKI4ZAKtbv/r/PfHEV29V8Tf94Q+feOKHn9hWCzpd/slHUquMbIeeRw6+pVFhhSSdvTP7MWQ1aqVGHQkzAACA+TFEAjB74PfKJjpIihg5YDVIDTaKlzwD8MpXvlZFUuIE4KlPPbVT6QTgh488ogw9m/gWl98i02Gvhkso6eyd2Y8hq1ErNepImAEAAMyPghMAcv0Bd+MXlEl0kCxu5ICVIzXYKF7sDMC2bW/98Y9/rIIpRRMAc7e/DgdTCcBXv/rD2q36m7/+xFe/3tfHIwGoJJ29M/sxZDVqpUYdCTMAAID5MY4ZAFA20UGCkQPmRmqwUbzMGQBy/z/5yU9Onjyp4imFBMD6fAOXORNghWAqAfjENvr59fe+gCNv+cQPOOJ8/Hu/QnbP4p4UCqts4RNf55U+hagaVjJPDTm++j4OmmqUeDzxBG3XNvnPrg5VsA8gGWJPENHu8UruSi2WJensndmPIatRKzXqSJgBAADMDyQAYHqigwQjB8yN1GCjeIEzAOT+f/rTn5L775EASFFEwcF0AmBcvjPQZNYf+eSbIj4+RGTBZwU3UxrAKYQNemyfJlJ17p4sMkGRM5DZp41yPz5e9Rlk7H5jskJ/gaEcSWfvzH4MWY1aqVFHwgwAAGB+IAEA0xMdJBg5YG6kBhvFS5sBkO6fUGtTiiYAUbUnAN73h0zAx6mONeWWZgLg68SDVsb0Vz4+0n9W2arelY9EJwqKkHT2zuzHkNWolRp1JMwAAADmBxIAMD3RQYKRA+ZGarBRvKgZAOX+CVUhpaFmANyTP//ZpQFVvPLc/GiQbBI16zJoNdMEwIofGXKTDCVJOntn9mPIatRKjToSZgAAAPMDCQCYnuggwcgBcyM12ChezgzAK1/52h//+MfO+HtUnZRCAmB9voHLnAmwQrA1Aag/fhPiFOSUwJhvrhmaRM26DIZV8hEgdvDRtqlyKDQeAfKiHKDAeQDp7J3ZjyGrUSs16kiYAQAAzI/pEwDqAawC7vWOER0knSMHgKFIDTaKFzUD0FvDzQCQyF6H++s1z2145OtfdX8ttOnLU0Ev4/uZZv2csgq6vkxSUT2eFJkZWLiks3dmP4asRq3UqCNhBgAAMD86L95OG4fLfxVAAgBKJjXYKF7ODMA0iiYAUSUSAGiGks7emf0Yshq1UqOOhBkAAMD8QAIAckACAEomNdgovkwzAJkgAZizpLN3Zj+GrEat1KgjYQYAADA/kACAHJAAgJJJDTaKL80MwERSzaGZSjp7Z/ZjyGrUSo06EmYAAADzAwkAyAEJACiZ1GCj+HLMAEAlSzp7Z/ZjyGrUSo06EmYAAADzAwkAyAEJACiZ1GCj+HLMAEAlSzp7Z/ZjyGrUSo06EmYAAADzAwkAyAEJACiZ1GCjeL8ZAPVEDQS1SDp7Z/ZjyGpFJwAMEgAAlhskACAHJACgZFKDjeL9ZgCUw4OgFkln78x+DFmt6AQAMwAArAJIAEAOSABAyaQGG8UxA0A6/6YjV33hCfqp4tAgks7emf0YslrRCQCDBACA5QYJAMhhZgnA/bs30efMhg1bD7qAD23afb9bBge3qlPUC+4l67xOULUMUoON4kswA3DRRRerSA/JHID/WujNN98sK0C9JZ29M/sxZLWiEwDMAACwCiABADnMPAEQdnPpEgB3jP0NfHcCkLOJ0bn6CUgNNoovwQzAo48+2jsHINOvRDnAU0755bwcYNfa4ydPHt6l4ltuWz95cn3vS2tBpy1711OrjGyHnvXbL2hUmEZ9O+/Y525JZ+/MfgxZregEgKGLBAkAAEsMEgCQwxwSgOBNOYQEoAIJQBepwUbxJZgBIDv7yCOP9MsBlPsnyQSAaM0ByFKvE3VzzD67n2M2HU5jtVslO7c72UhdZiTp7J3ZjyGrFZ0AYAYAgFUACQDIYS4JgHOnHDLF+koLW1z2soJNm0RN0UsNZY9dJ+yI/YLsh0lsMTjp5obq25HrzRpdP9Y/xVLdxppPsgmz22FjtFDfsDuoqqovcxfFkhpsFF+CGQCy22Qfe+cArPAIELn/pz71VGf/LaqmkLHUa2vrtbvpO9dOHl7r6+PnlgDwff21K08Ja2co6ezZ60eR1YpOABi6SJAAALDEIAEAOcw6Adh60BXIdHLJWVFBqFrZ5ZrbFQsNuxqPVz5XOt6KxBabcdfQVdJblxvnKr5G1brWf7rbVPNJNsHwelm3qimL4yA12Ci+HDMA9JMcZO8cQLl/qc4EYO9L6Wdw0hfsPc4RZ7WvvJf2zuJut4dVtrB3jVf6FKJqWMk4dcfaLg6aapR4UODKU2yTXa4OVbAPIBkaD/mozmlXfYfVJvhAzCq3bCqIhr7m+u17fdCu1QdS61M6e/b6UWS1ohMAzAAAsAogAQA5zD4BoHLNoTr36dYLTNWaQU0uxNtK6jV4bcYWqyUuhG7VokMcI1fQhI7q/Te7TTbP3wTju64dbNie68PvzQhIDTaKL8cMABfe975bKAc444yNYdVEarp/UkYCYFx+5aTX925hU17z8SEiCz4r2EnumZ23DXq8+ZY2vWorcgbzwNEWam768fGqzyCqKfcqJAAivnPNNDeTGPLpoFDBbIt3RnzPwe5A5ECqPqWzd2Y/hqxWdALA0EWCBACAJQYJAMhhLglAzbwa9+kWvTHlxcrkOoMaX0i2rSENcNVx1xbD0sHa3qe2Uh2jK/luBLX+6yel6jbdPH8THlXBNSPMVmt7MwZSg43iSzMDcNFFF5P7Jx8pV2WKXL7y/UE5CYD3/SETqNlfa+aJYJdVIRW0Mqa/8vGR/rPK0QhPVshb9Ray8jYiJhB8Q3+Y9d5iG633KZ09e/0oslrRCQBmAABYBZAAgBzmlAAIl2rcZ8wVNw1qfCHZtk4wvlwzb4vVkqvC8dRWXNyGuaXvyC3Rmnr/yW5TzSfaRNV7bTtVBVEaCanBRvHlmAGYxv2Tpk0A2EzvCv5Y+uDwUI2yyzHfXAtaVT0YDZkAhJ7rmwjiR4lqm6OaEyQAVZ/S2bPXjyKrFZ0AMHSRIAEAYIlBAgBymFsCoPyrW5BUPrjhW+sLibaaWvNkq3otudRs0NhKqBLbL65d759IdhttPukmfIWtBzOrus2USmqwUXw5ZgCmcf+kqRMAd6dfPJZj4xRkx2wMsbLLMd9cC4ZV7qkb4aqjbVPlZoHLvltbFvf7K1EOYOOyB9eq/giQ7LaqGfqUzp69fhRZregEADMAAKwCSABADjNLABbOkP5W+mYwT1KDjeJLMAPw2GOPkX1UwYk0QAJg7vGHe94hbp6zN6yvrfWbASAZ38806+eUZcF1JLqyqjZhHwGqHltq5Bt+lf4SsOtNlEWf0tmz148iqxWdADB0kSABAGCJQQIAcljKBMA/WzOF/Q9dBAq/Vb6kpAYbxZdgBoC8o4pMqr4JwAqrmo7olnT27PWjyGpFJwCYAQBgFUACAHJYygQALA2pwUbxJZgBmF7k8ltQlSGS+fOm1fcBOiSdvTP7MWS1ohMABgkAAMsNEgCQAxIAUDKpwUbxJZgBgOYl/0STIff2P0k6e2f2Y8hqRScAmAEAYBVAAgByQAIASiY12CiOGQBo1pLO3pn9GLJa0QkAgwQAgOUGCQDIAQkAKJnUYKM4ZgCgWUs6e2f2Y8hqRScAmAEAYBVAAgByQAIASiY12CiOGQBo1pLO3pn9GLJa0QkAgwQAgOUGCQDIAQkAKJnUYKM4ZgCgWUs6e2f2Y8hqRScAmAEAYBVAAgByQAIASiY12CiOGQDS+TcdueoLT9BPFYcGkXT2zuzHkNWKTgAYJAAALDdIAEAOSABAyaQGG8UxA8CSOQD/9c+bb75ZVoB6Szp7Z/ZjyGpFJwCYAQBgFUACAHJAAgBKJjXYKL7iMwBk+pUoB3jKKb+clwPY/617eJeKb7ltXf+r3SDz/7MSq4zkP+s9uX77BY0Ko5R09s7sx5DVik4AGCQAACw3SABADkgAQMmkBhvFV3wGQLl/kkwAiNYcgPz6OlE39GziW1x+i0yHvRoWLensndmPIasVnQBgBgCAVQAJAMgBCQAomdRgo/iKzwAEhUeAyP0/9amnOvtvUTWFjF9fW1uv3arfuXby8FpfH48EwKnoBIBBAgDAcoMEAOSABACUTGqwUXzFZwBYyv1LdSYAe19KP8O/xb1g73GOOB9/5b38OE94UiissoW9a7zSpxBVw0rmqSHH2i4OmmqUeNh/x2ub7HJ1qIJ9AMnQeIJItpLd8s5X/+V3bZcpu+aUz6zv3ZL9T3+jks7emf0YslrRCQBmAABYBZAAgByQAICSSQ02imMGIKjp/kkZCYBx+c6ak6s2drnp40NEFnxWQCbbuXAb9Ng+TaTq3D1ZZIIiZzAPHBmPbvoRxt31GaRa+T3cuWaCZuJCfpmBKnB2oTrpI+nsM1V0AsAgAQBguUECAHJAAgBKJjXYKI4ZABK5fOX7g3ISAO/7QyZQs9fs5v23AsIqUScetDKmv7Lgkf6zyo1IdfvfQtbfRnx6YGX33OUe00mZ+xwVnQBgBgCAVQAJAMgBCQAomdRgozhmAEjTJgD85M8ulwZU8cq+86NBsok06NGg1QwTgMitfX58yJl+JADtIAEAYLlBAgByQAIASiY12CiOGQDS1AmAs8v6ARsKckpgDDfXDE2kQY8GwyrvwivXHm2bKjcLXK7f7/eiHMDGqQJti3/qOpNKmfscFZ0AYAYAgFUACQDIAQkAKJnUYKM4ZgBIAyQA5h5/8Moh7r9Zu7621m8GgGR8P9Osn1NuFqyqbu0jQNWjSnQU1ZeAzZyAm9boL2Xuc1R0AsAgAQBguUECAHJAAgBKJjXYKI4ZAFLfBADKkjL3OSo6AcAMAACrABIAkAMSAFAyqcFGccwAkMjlt6AqQ5NKmfscFZ0AMEgAAFhukACAHGaXABzc+gR9zrA27f6Ziz7+860+uGHrz11ME+r860EXyWeatqA4UoON4qkEgFmRBACaqZS5z1HRCQBmAABYBZAAgBxmlwAY7v+XTc6OP7FV+PH7d//r7vtdOY5r2MvEH/xXJABLQ2qwUbyZALCxYZAAQNNLmfscFZ0AMEgAAFhukACAHGadAGzd+q8+B/hFMP2zTQCmaQsKIzXYKI4EAJq1lLnPUdEJAGYAAFgFkACAHGaeAOz+mb8lX5lyJAAgk9RgozgSAGjWUuY+R0UnAAwSAACWGyQAIId5JADG8f/C5QCb/oWcfz0B+NnuTZweuLUGb+J3+4biCaJYfcKnGZvcnAMlAOL7Bram+1qCbAXKJjXYKI4EgPUrv/Krp5zyFBIV1CpoSilzn6OiEwDMAACwCiABADnMJwEgqu8Eb/25SADYzfPdeuvX2Z27BIC/Pcw+np8gStR3dUzcJxuijnj66OBuuP8xkRpsFEcCQGL3/9Af/jYJOcDgUuY+R0UnAAwSAACWGyQAIIe5JQDyzv2mTT4B4Nv2zsS7CuZmf/0xHk4eTDKQqO9MP/9ZIfUIEDfhVQf/VX4XGZRParBRvJkAjO6vAF100cUqMpGC+3/863tIyAEGlzL3OSo6AcAMAACrABIAkMMcEwCC78eT3C15Z9zrht4Y/UQCkKrflgC4amaLuP0/OlKDjeKpBIB9zigSgEcffbR3DqDcfzMHoJ/pZGDX2uPu3+cS/K9zJ5FsLv5Hb5D5Z72xeEqT1lf/G3hmUuY+R0UnAAwSAACWGyQAIIf5JgDBnftncrJmAES8fQaA4zoBCK1+sbsKgXGQGmwUb0kAiFEkAGSfH3nkkR45QNT9ywSAK4RkoKEpDXTVfMttxrpvOUWunYOQAAjlJwCYAQBgFUACAHKYdwJAGDseHspnE89mXTzTX8sT5LP+7fVtnO2+TADczIOMgHGQGmwUX4IZAEoAtm3b1iMHSLl/WYcWQz4g41aDJQBz8+J1IQEQyk8AGCQAACw3SABADrNLAMR/AtbOu/5XgMJzQcHlW0O/9efe1qseYvUJ5/sp+AtuZb9A7Lh/9y/kIhgLqcFG8eWYAaCfPXKAaAIQFecAqnnMQJvI2tr6yZNrV55i1+7aSwvE2i57m9/iHxaSzUO50YMP7t27Vm9OumDvcY6Z/lUnYdOh/pX32mXi8K76RmcrZe5zVHQCgBkAAFYBJAAgh9klAGVx8F9EygFGQ2qwUXw5ZgC48L733UI5wBlnbAyr2qUeAaICx6lMP2VukE4A2FAbvAWX/t48228e7NlpvLuLmzKZe67g/Ld4BEj1EAy9d+1Vc+P+RTLQqM8dRr4YIKupVTORMvc5KjoBYJAAALDcIAEAOSx3AmBnIX6x+/6fb+XvB4OxkRpsFF+aGYCLLrqY3P+2bdvkqk6FHIAtPj/noxIAuaqupoGWkc4yFWzqYGBP31KzETTOPrSqr6rVNzf+bXLi8hBLpNrspMx9jopOADADAMAqgAQA5LDcCYD7cjCe/h8tqcFG8eWYAejn/lmcA0iLzwkAiRMDKpx66tM4UlfTQMtIZ7nZXAWjNX05NwEwEwUmAajqU6RZbYZS5j5HRScADBIAAJYbJAAgh+VOAMDYSQ02ii/HDEBv988i6y9v8IcEgMQ5wMxmAFRzFYzWDOWOR4DcquD7d641HgqS3c5Q0tnvSyOrFZ0AYAYAgFUACQDIAQkAKJnUYKP4EswAPPbYY9O4/6b4yR8pzgFUtZiBlpHOcrO5CkZrqrJ9oif2JWD7TeKwiuS/MUxrFjoD4Px+HVWn6ASAQQIAwHKDBADkgAQAlExqsFF8CWYAhnX/QWT6uxKAYjUnZ58pZe5JzvV71FpS0QkAZgAAWAWQAIAckACAkkkNNoovwQzA4OJvBYQEIP0IULEqPQEgOe8fc/+kohMABgkAAMsNEgCQAxIAUDKpwUbxJZgBmIVCDjBC908aQQJASrl/UtEJAGYAAFgFkACAHJAAgJJJDTaKYwYgJc4BRuj+i5My9zkqOgFgkAAAsNwgAQA5IAEAJZMabBTHDAA0aylzn6OiEwDMAACwCiABADkgAQAlkxpsFMcMADRrKXOfo6ITAAYJAADLDRIAkAMSAFAyqcFGccwAQLOWMvc5KjoBwAwAAKsAEgCQAxIAUDKpwUZxzABAs5Yy9zkqOgFgkAAAsNwgAQA5IAEAJZMabBQvagbgoosuVhFoCaTMfY6KTgAwAwDAKoAEAOSABACUTGqwUbzfDICyaxDUIjV+clR0AsAgAQBguUECAHJAAgBKJjXYKN5vBkA5PAhqkRo/OSo6AcAMAACrABIAkAMSAFAyqcFGccwAQLOWGj85KjoBYJAAALDcIAEAOSABACWTGmwUxwwANGup8ZOjohMAzAAAsAogAQA5IAEAJZMabBSfxQzAvn37VIS0DZSBel2mV/TlllLjJ0dFJwAMEgAAlhskACAHJACgZFKDjeKDzwCQHUQCUDLqdZleqVc8SI2fHBWdAGAGAIBVAAkAyAEJACiZ1GCj+LAzAOwFCRUnOfsJFo16XaaXe8nTOYAaPzkqOgFgkAAAsNwgAQA5IAEAJZMabBQfcAbA2UCLWkVy9hMsGvW6TC/3klvUKpYaPzkqOgHADAAAqwASAJADEgBQMqnBRvGhZgCcAfSotSRnP8GiUa/L9HIvuUetJanxk6OiEwAGCQAAyw0SAJADEgBQMqnBRnHMAKwa6nWZXu4lt6hVLDV+clR0AoAZAABWASQAIAckAKBkUoON4kPNALCcDUQCUDDqdZle7iVPuH+SGj85KjoBYJAAALDcIAEAOSABACWTGmwUH3AGgJXygs5+gkWjXpfplXrFg9T4yVHRCQBmAABYBZAAgByQAICSSQ02ig87A8BCAlAy6nWZXu3un6TGT46KTgAYJAAALDdIAEAOSABAyaQGG8UHnwGAICU1fnJUdAKAGQAAVgEkACCHmSYAB7fSR82GrQepeP/uTaZcY9Pu+7leDW4UWZdckUJsHoyU1GCj+CxmACBISo2fHBWdADB0kSABAGCJQQIAcphzAlC5cV4X8fMT+/wk3QlAY69AYaQGG8UxAwDNWmr85KjoBAAzAACsAkgAQA4LSwCS7hsJAKhIDTaKYwYAmrXU+MlR0QkAQxcJEgAAlhgkACCHBSYACfvNjSSuQi0zcG09IV9QcYJaN4O2Txneujteh+jOI8DMSA02ivebAXjyk09ZGtHhQAVKjToSZgAAAPMDCQDIodwEQDaz/r5KALxz55aiTi1HcB2p7mubje8BkVwB5ktqsFG83wyA8tCjVvQYoQKFGQAAwPxAAgByKDUBCLf0q0Vdqtr5NbvrcVnNbUtg4vU9iNcBiyQ12CiOGQAkAGMRZgAAAPMDCQDIYYEJQNz/C5+vFkOp0dCt2bq1Hg+b50JYEeJyF5J1wCJJDTaKYwYACcBYhBkAAMD8QAIAclhUAuCWK6MfqDlxV83W4hWm6BvrOrK2rFS1rMd92RSTdcAiSQ02imMGAAnAWIQZAADA/EACAHKYcwJQw7lthUsAKny1qEV3hK4arXnzzbCKUwftdZALLITUYKP4YDMA539+w+3/2+rz//aUxlqnt/+fex/+pTNVMKbn3Pl/3J5Xc2ohARiLMAMAAJgfSABADjNNAACYktRgo/gwMwDGr3vf/5w7f2lzfW2l9gQgOz0YVM1jvOKuY4ojN12g6kynN+9/wPVM7N+u1s5OF9x02G302NH3bDYR2pOjN22RdSYTnavaydl24NiBNz/t/PccOTZVt1FhBgAAMD+QAIAckACAkkkNNooPMwNw/uc33Hjn/6OCEY0jAfCa1hynNbue0zKmXCQb57/nJlOeek/Y8ftFygdml89gBgAAMD+QAIAckACAkkkNNooPMwNgvPv//j+2vqwWNNMC/FDQ//4/3ZxAsPjS63PZ9OAeItr59lqFVD+vcQ8d6e1OqNVIAMy9/5g1n3pPTF5x4IrTeJF6C+XhhRkAAMD8QAIAckACAEomNdgoPswMgNHLfundyqP7cvVAf7D1wt93B6P9cJ7A3z1o+dZBt3ITAHsH3eI8bvWkkLsFbutvd9XIbW++8agtNp8gUrbbuHNXZ9sB+3BOrasBHkCq2XSpak8ah1M9L2QzB7UYJFKLajZAHGD9vIkpgnqd/dU0QkqYAQAAzA8kACAHJACgZFKDjeIDzQB42bv1xq+bQuXL/+0ONvGdXr8R7OhHlfsoLwEQ5W0H6o48rKKCf7aerHAw7qaszLet6eBVFKEC//QVuCtjoMNu9BV1coQf+leiDanOfaT+bI9eFKI8h480Zu5F/3zeQj+0eMQ1DD20CzMAAID5gQQA5IAEAJRMarBRfLgZAKf/5zUPm3vzS5YAVLexLd7CukVn0KWZTpVTEddb5O74IA/Wm/1XSQhLbEgdjj3kyperRSmXXVxw0+Gwz77b5nlzlemg7BSHbtgmzAAAAOYHEgCQAxIAUDKpwUbxYWYAzr/TW3DzIJB9KJ98OZt1aeKDWTfV3FrzDA8Ho7a+vR9RDmubBVMtqewEoG6gq0jwr9K1p8qpSEsCIJ6x6a9UJ35DkcMx4qeYQkO16GWbODfPkWa3Qdz/m/c763/gis2p2QktzAAAAOYHEgCQAxIAUDKpwUbxgWYAjE3nr+S6R/NJxn9zsGnrxf8N2Pn5EPy3O0IPomZ7P/NJAEy5fv+b/Lp+REfVj5ZbImSU+Scv+s0FD91SqPpJq5ZgmLa1vwIUORwn9XxO9HEdTgxEPBygOBBRWT78s3+/eqQqKcwAAADmBxIAkAMSAFAyqcFG8WFmAMasvASAnbHHPAJk7qkbjh7YfySY3VA/VQ4R29Zy5KY3U1fBEIcvAe/f775D7Fz7lAkASR4C2/1q3xqHUz0RZDehFmW3JNOzPEZxyHKj/OiUrKwbtgkzAACA+YEEAOSABACUTGqwUXygGYARK50ALFDNnAHCDAAAYI4gAQA5IAEAJZMabBTHDAASgLEIMwAAgPmBBADkgAQAlExqsFEcMwBIAMYizAAAAOYHEgCQAxIAUDKpwUZxzAAUmQBAEWEGAAAwP5AAgByQAICSSQ02imMGAAnAWIQZAADA/EACAHJAAgBKJjXYKN5vBmDJpA4QKlOYAQAAzA8kACAHJACgZFKDjeL9ZgAgaNZSo46EGQAAwPxAAgByQAIASiY12CiOGQCoTKlRR8IMAABgfiABADkgAQAlkxpsFMcMAFSm1KgjYQYAADA/kACAHJAAgJJJDTaKYwYAKlNq1JEwAwAAmB9IAEAOSABAyaQGG8UxAwCVKTXqSJgBAADMDyQAIAckAKBkUoON4pgBgMqUGnUkzAAAAOYHEgCQAxIAUDKpwUZxzABAZUqNOhJmAAAA8wMJAMgBCQDI4v7dvyDbELRp98/citmSGmwU7zcDoCIQNKyKTgAwAwDAKoAEAOSABABkcP+/bDK+/xe776eFn2+tyrMmNdgo3m8GQEUgaFgVnQAwSAAAWG6QAIAckACAbtzt/60/58WDW+c2CZAabBTHDABUoIpOADADAMAqgAQA5IAEAHSjHL/KB2ZJarBRHDMAUIEqOgFgkAAAsNwgAQA5IAEA3YwtASCQAEALUdEJAGYAAFgFkACAHJAAgG4wAwAtl07WUWunUdEJAIMEAIDlBgkAyAEJAOhmaWcA3rz/gWOeozdtkatmpvPfc2Ru24ISCqa/MwH4wAc+SBXoZ2eQVXQCgBkAAFYBJAAgByQAoJuxfQk4ewaAEgDnxTffePTY0fdsrq0dUNWGoBIUTL+x/10zAHfeeRfVede7buRFKtAiBUMFqaITAAYJAADLDRIAkAMSAJDByP4MKDFpAjBjjz5k5+eee97Klpvim/GK6L15KaoTCqHcopADtLt/UtEJAGYAAFgFkACAHJAAgCzcJIDXXG7/E6nBRvFhZwBE2RT27z967NiBK07jJ3Yc+7eLmttd/MhNF7jeqpq2YdWP4MCbaxvVTS646bBb9tuCuqVygE73T6JqoRDK7eIcgGhx/6SiEwAGCQAAyw0SAJADEgBQMqnBRvFhZwDEI0AUDLbelJ0Xr57dN0FXuRb0tn7bAdtc9ePXVuVGk20HbIbA1To0zX30sZebynTnQVQzFEK5XSHNaE8wik4AMAMAwCqABADkgAQAlExqsFF8oBkAd8fd34PnoPflxt+H+NOvuIuTAenmfbC6l29Rd/qj5WYTG6mmFKBJRNY/3/03UXWUwpM/nGmE7wM0VXQCwCABAGC5QQIAckACAEomNdgoPuwMQDzYnQCYh3Z8AlDVtIqZflmONDEycxGtjwBNc+987OVh1en7WXzvP9z4V4tKRScAmAEAYBVAAgByQAIASiY12Cg+0AxA8OXRIJW9F6/8ugm6+/TRoJPqp1luNnGiHADzAHNQTgIQtfstOUDRCQCDBACA5QYJAMgBCQAomdRgo/g8ZgBIxuIzNQcfvt1b3aqvajYfATKzB5G4arLtgCvHZgagwZWTAEyqohMAzAAAsAogAQA5IAEAJZMabBQfYgagn6JpAzQ+rVwCwCABAGC5QQIAckACAEomNdgoPsQMQD8hAYCSKjoBwAwAAKsAEgCQAxIAUDKpwUZxzABABaroBIBBAgDAcoMEAOSABACUTGqwUXxxMwAQlFTRCQBmAABYBZAAgByQAICSSQ02ii9uBgCCkio6AWCQAACw3CABADkgAQAlkxpsFMcMAFSgik4AMAMAwCqABADkgAQAlExqsFG83wzAxo3PhqAZ6clPPqXoBIBBAgDAcoMEAOSABACUTGqwUbzfDIBybBA0oEpPADADAMAqgAQA5IAEAJRMarBRHDMAUGnCDAAAYPEMkgCAVcC93jGig6Rz5AAwFKnBRnHMAEClCTMAAIDF03nxwsaBTqKDBCMHzI3UYKM4ZgCg0oQZAADA4kECAKYnOkgwcsDcSA02imMGACpNmAEAACweJABgeqKDBCMHzI3UYKM4ZgCg0oQZAADA4kECAKYnOkgwcsDcSA02ig83A3DdkZOCI9c1KnTpFXesu8aW9TtesXGTrnPNUbNm32U6ntKw9e1ay9Frmvs2M11z5OSRa8Lm6Dyf2PcKv0i7RKfanDoRbFO9+QCqve4TnOq0MAMAAFg8SADA9EQHCUYOmBupwUbx4WYArBGMuvZMcQLAPbDVbmYRwxr6plrqm93zvv8Vd+yrHHmLBnLb7PK5bM9S2MNX7DsxoeeeRQIwbIeYAQAAFAASADA90UGCkQPmRmqwUXzgGYChEgAu95hGmFItCQCtmvjoBjLHdDb8psnxH9l3x7o7M5ftW5+0fyQACeUnAJgBAGAVQAIApic6SJrBT64S7pgbuNVgCtypFKTepig+wxkANvGOo9c4f3/CB08cOXLCFdnOygQgGHHVSYjbQtVb2K6oH6pVhSNHa/Vl52q7fAg1mQMUq8h8iydzqKHpwQSZI9fYE8LIAzTwTIK1zte4IHVF5t4WmzsQjD4XqGHoQXRlKtjCPntyZD9+0+v77qj8ujh8PhDxrFHo0FYz+y8PjeuwRM2gRs9UrVahVZgBAAAsHiQAYHqig6QZJOv2vdUgalKZ1TkJM2LABICYOAHwGNvnXGDdblqf7ZxuZSttHeEaDTXT7DupG3rZW7VFtvK8V+n6NZNdr1ZbVZMzwc7UUmXeyWCdRcRKmmNRvuao3YQ9Y7y3crumrL9j4K35dUds/WuO2K6qzYXObZ8crPoxQd5ne+xVTXcg5rzVO6Q9pOTK7g81cWemdmhBdoset5PNnmMJgGvjCXHMAAAAFg8SADA90UHSDCIBIJAATMmACcAwMwAhwovWREoLTta2lgDIHpqdGFNbOXXVW66zF3viyhZdLSXbxDtd77B5D+0q0ZwqsP2tbchgti7WJstetGPUhH96U+6sea1JrB/adHVWRVCkGS7B8DVNgnENl/3kgz60oMbeRntOzAC4syHcPwkzAACAxYMEAExPdJA0g0gACCQAUzJgAkCMMQFw955Z9frOv/o9sZuur5XV0jIbihtxv9bthjDHZqPqvr60zqmyFzVfv+OafSfc0dHikTvEFwBCk1g/tq0/qyIYsen+ESNTn8r2wS3xikTOcHNv4z3HEwASdagimAEAACweJABgeqKDpBlEAkAgAZiSAROA0c0ARHpQ9e0q72Krp4+qHloSgGvu8DbXNHR1aIvrR49URtyJOrQVlB1XPau1zbIMVnvr6xDBZ0ebyKBz7fZIddCeN9eV2XPx8M+RI/y0EvXm1Dg0uUVWtOdkAtAUZgAAAIsHCQCYnuggaQYH8b53X0afS4bL7naRCF96x0ZXq7XazEACMDsGTACIkSUAob4lVKvqB2zDECTLa37K+rz1muwBMtzcyux/WKy24vy0PTpfQeybjUjrHC3LoD1McXJq2403EeVwpPEvAVdbsUFZQfdQ+wazWVXbSadIz9UZ6xRmAAAAiwcJAJie6CBpBgfwvmT/N77jS66U8vZVJZsJXHY3/fSB+YAEYHYMmABMOANQttqc/VQiI15/JAaaVpgBAAAsHiQAYHqig6QZHNT7pk19cw0SgCViwASAQALQoVfUHpGHBhFmAAAAiwcJAJie6CBpBof0vnxr3y0ozDph+M2igUN+yT0cZHKDyy5zocEeF0ICMDsGTAAwA9Aq9VA+NJgwAwAAWDxIAMD0RAdJMziU92UP3+rWg823rt+4fE4ITJwbupL51Vg3NUgAZseACQCxPAkANB5hBgAAsHiQAIDpiQ6SZnBQ75tn1/nrAFQ33P53bt+XVWSgDKCkBKDlyxIZyPNTBgMmAEs1AwCNR5gBAAAsHiQAYHqig6QZHNb75llTa39DVWX3qdyMcHk6ykgA6HjoM5zITgCaZ2C4czIUAyYABBIAaP7CDAAAYPGsTgJwLZgOdx5jRAdJMzi99zWW1rlZUaxTW6FmAMRKVxK1aw2no4wEgMEMAGYAoLKEGQAAwOJZqQSA3s1APwpJAAjys4z3pRGDG+r4m98csGVj8y3c3hjcjbXIEIwjATCnwh8zl+/2dj+cJUJHZBNmigRjcgZMAAgkAND8hRkAAMDiQQIAcignARgYcrHD+f7AOBIAu66y91TLnQ23JGqI09SoI2rPgwETgJYZALJoEDQ7FZ0AMEgAAFhukACAHJAATMRYEgDh5u1Z4N/ynIQIuYEKMVcQ6nB59gyYABAtCYAKQtBQKj0BwAwAAKsAEgCQw9ImALNhNAkAm3f55A/bfWXu6afqpFmHy7NnwASgfQaAyxv3PTG9Qs/DSm2ln1Sf0ByEGQAAwOIZMgG4f/emDZt23++WzKJYWjhVAvCdD55Jb22eyw+78IDQFs784HfcQhOzA2J9R+0iQAIwEeNJAIx7p6vAGXhn5Su/b0r1iC/W67RtYWAGTACInAQgxPtpdia75H2DWoQZAADA4hk6AdhQpQAlJwDBcM/GfGckABuqFAAJwNJRagIQSwa8x3dlLpqgxXxFmldSWxeqKtcD82HABCBzBiDE+2lwk/2kJz2JCyXvG9QizAAAABbPwAnApt27t27YerBaLD0BeOLw5bOYAzh8eVundgc+GDaMBGDpKCkBWDYGTACIOScAJp9KEOp0qj0BcN0l0JXTR+caxFA1pZAA5AgzAACAxTN4AnB/8P2+cHArvZE4TG5g4lu3msmCDZt2H7SzBm7aQNc0UMwXp6NjBoAKbst22cQvv9yELv+gX+MaVTWtgbc9kJsXIUeoqO29bfId/hkWbS4SMP2YOO8D9XCYO2vsg+57RiABmAgkALNjwARg0hmA++pEI02pBMBVrdPuqpU6EwDXaZ33vOc9xrzXN9SeAFx++eWused//I//oXpQykwA6HOniaqzxMIMAABg8XRevKlP1gjC8XujX58B4Aj9ZMMvC9GabmEYagmA9c6WugcPRVOHI36KwESo4H7VAy7i2tpio6HAV3M1aq0sHDEN7QpZML9FA1GcKUgAJgIJwOwYMAEgeiQA5IC5EOLtiiYAbMfpJy+2u2qlnASAfkp4K80cIJUAcDWy+9yQocXnPOc5snlTOQkAfehceeWVH/rQh26z3HDDDcb+W1TNZRVmAAAAi6fz4k19skaoXPvBrVQIi8boe1S8WXD1xHcJBiI+A8AYhy2xN9xdHbeuWgptudyMcFk1lFTVDl8ue3AtLCouC7KagdfNFiQAE4EEYHYMmAD0mAFgZ0xQmSOSEAlNSNEE4OKLL6Yy/eRFKvPaQGjSVO8EgOAcoKqcTgDU7f8c90/qTADoE4fcP1t/4p3vfKcx/h5VeVmFGQAAwOLpvHhTn6wRgo/n4tatdvHg1uDluYK0+7VCo6YtDkVXAhC/SR+wz+dcfljGudyMcNnjGroli6hmipdfbhepooy2JwD1DmcPEoCJQAIwOwZMAIhJEwAi+OkQb1czAeAHae6++w/oJ99lZ2NNPy//iydIvJjSNAkAQYtV5UQPhLz9n+n+STkJQLj3L90/zwOoyssqzAAAABZP58Wb+mSNUHPt9nl+Z+vF8/wUaUsA6jW5PBBtCYAJeU/NxVDHLMbdtyuFmhyS5VpDjlpqAZsgmEX3QJCLUSRU0wX6Vd9bW5wpSAAmAgnA7BgwAZjFdwBCIaiZAFx99dXWYxuoTBEq8FqZAPDPplIJANVnuMMoYVuuSSIBkLf/890/qT0BME7/DW9g90+EBIAKtEgFVX9ZhRkAAMDi6bx4U5+sEeq37WmJTbwpBCiifX9V0DVNNyIrmI7WBICwRtxg14k6xmNXKxrLsrd6z7phoFnNLob6BoqEas2C2tvZgwRgIpAAzI4BEwBiogSgn5oJAPlpfvqfflKZChRnQgLAhIZSzQTA1fbwDEMU3ha3kj1UEUu4/R/cv0Q1kZooASDI+rP7J2iVqr+swgwAAGDxdF68qU/W0VElAGBykABMBBKA2TFgAjDpDEBT7JIDISLrNBOAJmysid4JAH+dgAr08zWveY1tHYHrcCvZQxWp3/5XcGqhmkhNmgAEPvShD9EqVX9ZhRkAAMDi6bx4U5+sowMJwDQgAZgIJACzY8AEgJgyAciRSgBSXL7vL8xPnwDwYmgoFU0AyJ2/853vpAL9pDIVovAqbiV7cIuWcPtfEWYDZBOllgTAeH/xBQDFlVdeSWtVk2UVZgAAAIun8+JNfbKODiQA0zBUArA6uGNu4FaDKXCnUpB6m6J4UTMAZjGBsf77/oITAC5QUDYMaiYAZ511Fm10qAQgwF0xOe6flEoAjPdPuH8KrpT7J2EGAACweDov3tQn6+hAAjANgyQAAMyI1GCj+IAzAM4Le0K8XU2T7dp7rNk2t/yd+/c5AAVlw6DUDIDEdhmBV3Er2YMS1eEvJzCZ7p8UTQCM96+7f0otOBhQTZZbmAEAACyezot3aWwcEoBpQAIASiY12Cg+4AwAu2G20USIt6uZADD8PWB+qp6RMwAckQ2DoglA+JcCxDTfAWBRnXD7P9/9k1oSAOf9V/Vv/0thBgAAsHg6L96lsXFkYcE0uPMYIzpIlmbkgPJJDTaKDzsDYEy0hcockYSaUtEEILj/4K05bnKAVvdPaiYApmz/sQD1SfZ67969dnfiyJ6jCQBVCLf/J3L/pM4EILh/VWelhBkAAMDi6bx4YeNAJ9FBgpED5kZqsFG8wBkA5f6JsCoQ6jfVmQBwDy1UrRIJAN/+n9T9k1oSAImqsGrCDAAAYPF0XrywcaCT6CDByAFzIzXYKD7sDICkJRKakJoJANcJ1By5JSxGlUoA2LXzfxkL8XY1EwC7fbOHPdw/KZoAkKztd6hVKyjMAAAAFk/nxQsbBzqJDhKMHDA3UoON4gPOAPRTMwFoIit0KpUASEK8XakEIKDWdiqVAEBSmAEAACweJABgeqKDBCNH4r5IAYbDnVlLarBRfMAZgH6avgelaALQT7PbN6hFmAEAACweJABgeqKDBCNHQoaVPkzBUAySACxkBmB6IQEYuzADAABYPEgAwPREBwlGjgQJwLDMcwZgeoWeB5FMAKZX6HYQIQHIEWYAAACLBwkAmJ7oIMHIkSABGJa5zQBA0ODCDAAAYPEgAQDTEx0kGDkSJADDMrcZAAgaXJgBAAAsHiQAYHqig2TikXP/7k2bdt/fLCtaVhWMTAAOX04frZbLD7sQmJBZzwCoCAQNq6ITAIYuErrSkAAAsKwgAQDTEx0kE4wc9vTNn251nbEnAN/54JlnfvA79RKYlFnPAKgIBKX0G79x1qSiVkUnAJgBAGAVQAIApic6SCYeOdLZL3ECcPjycONfFMFkFDUD8OQnn7KCWtkDV1LmPkd06opOABgkAAAsN0gAwPREB0ly5BgHv3XrJvp4IbYedJHIDMDurVyHK3m4gikdNOtt2ZYcprKp4zaxaffB3a5gG9Eqs+QDVc2tW1UnBuq4tvHehARA3vbHFECUr33ta64kUMGiZgCUI1wRreyBKylznyM6dUUnAJgBAGAVQAKQySdXG3cWEkQHSXLkGAsu3DgZbOPCGwlAcOEcsUWDWyRrLqOeqrldKwvmt/sVqSkRtYYCCUAmJ0+e/K3f+i0acm7ZQosUpFVuGTMABWhlD1xJmfsc0akrOgFgkAAAsNwgAciELMj3VpXhE4Bgr43/3noweHH1M9QJZYIW6ZOJkLfmQ5CQzVVBVjPY6YHQueqEgwOBBCAflQM03T+BGYCFa2UPXEmZ+xzRqSs6AcAMAACrABKATJAAtBAdJMmRE0x5KKd+yjpcJmjRzRqEFEDMBqjmqiAbMaFCsxNbHIqQAOA7ADmEHIBoun9ibjMAtOkUoU7dEe485NYbHtyzub52eVQ/cHvUh3aKiNHmPcdPnjy+Z/MpT96850Eu1CsMqR32xJsz3ljF4gqGQzvUqn6yHSpznyM6dUUnAAwSAACWGyQAmZARcXZ49aBjd2chQXSQJEeOcOGuyIa7+dPW0XY8LFLB9SOe1GcbL+vUClUbVwwVmp1weSCqBKC67Y8JgDbIWpH1j7p/Ym4zALR1bfusKB7q1FeRFe7tdKdpO2/VD9zs+YMPqp3nXGg+R2S2dWhHKDc2ajIQ7/s379njak4h36Ey90H79u1TkSA6dUUnAJgBAGAVQAKQCRKAFqKDJDlyjOfe5B62ke68+bOqL+y4WKQid2ELHtm8WTDuPtRr9uapKvusYDqqBAD/ByAb4x5j7p+Y5wxA8HyqHOqEoNU0Jn6atvNW/cDNnh86dLw247Hj0MlDh+Z1RPLUxU4j7UzL5EAP+Q6VuWeR+2dUnEWnrugEgKGLhK40JAAALCtIADJBAtBCdJAkR47w3KuDTADA9CxkBqB/AmDuFjtqd6n3uIdSrG+miKfxLE2Bqh84HzX9DE/X0DFzhM9GKPAqf6DmbJhVlDy4J3Mi50rVb9ahHhwPhnNK1E6jqVPLT558ingmiGvanay9KBRsbN3JdajMPcl5f49aS6JTV3QCgBkAAFYBJACZIAFoITpIkiMHCQCYmjnPALD/C3Ak1BGm0PnCQLCnwrkGQ+x9p/Gh7JutAVXJQ6mqH7jbc3PTPxypcdDhiELBnIK6ETenwkdMWZ8r06m28rHzyQVVljK1/YsiFeqbnvWLorcuZTpU5t65/jqqDp26ohMABgkAAMsNEoBMkAC0EB0kGDkSJADDMqYZAOMSw33xYJGjhrXRtmDVD9zvOR2s8fLNwxQVxNmotaVy9FyZoMgZJjifMdneXA5AjR31nTQ15Q6rjKUm6eyd348hq9GpKzoBwAwAAKsAEoBMkAC0EB0kGDkSJADDMucZAJYqhzohaNVwnxMY1kbbglU/8LDndLTH9+xwaUDk0Opno942da6M7B8UsosTnM+4TFeHdop+7D7LnTTBWifV1n0nQdLZZ4pOXdEJAIMEAIDlBglAJkgAWogOEowcCRKAYVnIDIDUBAmAiXjvWJnOqNdsti1X9QMXe25vq4tHetShmVNQv6Euj5rKzXPlRC7cNozWUZ2EsteOPT7id4D2k7MUE1A7qcpGfus+4jtU5j5HdOqKTgAwAwDAKoAEIJMeCcDdl9E7qOWyu11onCABmB4kAMMyzxmAFKFOZQqNYu7TWEwm6i+rsjXPZG9TD50XpPqBy8Ohow3GPcTV8ToaN+9j58qdFMJ323E+o6ex2qiP+14ePHSoZQaguXUn16Ey9zmiU1d0AsDQRUJXGhIAAJYVJACZTJoAfOkdG73vF8XeUB8b3/Elt+CJBtvp0QQJwBCQYQXD4s6sJTXYKD7lDECOhClcIa3sgSspc58jOnVFJwCYAQBgFUACkEmPGYBAL9edwaz61SABAIWTGmwUn3IGIEfKEa6IVvbAlZS5zxGduqITAAYJAADLDRKATKZIAMinx2YAjH2/7LKN9C572d2mCuMdfRWxMe/1Q3jjO+52RbfWdXVZeO7IP3kkmnzJbnTinAEJACic1GCjOGYAZqSVPXAlZe5zRKeu6AQAMwAArAJIADLpnQAY/x313NUK4cpd0ayrHiCiiIvffRmHeb0Lyq4E7U0mAQkAKJzUYKM4ZgBmpJU9cCVl7nNEp67oBIBBAgDAcoMEIJN+CUDUmTuCFzeVJPbmfmjF1VxlV9WtlD3I+rYXQ0uTSSg/AaA9BHPDnfSSSA02imMGYEZa2QNXUuY+R3Tqik4AMAMAwCqABCAT8j3ODmdjrHeL2w5e3NSrPyIkbTqXZcT9faH6DIBbS2t8vfYmk9Dp+aKDZJ4jp8erA/qxTAnAUDMA0CpLmfscUauiEwAGCQAAyw0SgEwmtpjGcddtvaLy4lTyVV2xHqFq4afz93Y5TBTwWlPbP/DDxZYmk4AEAASWKQEgBkkA1C3hFdHKHriSMvc5olNXdAKAGQAAVgEkAJlMajHtHfcK67qFOycq106E6j5kjLuHYr5yCPsOidp9fdmOK9WaiJr5IAEAgWVKAPAdgGnEB87vLf2QvY1XytzniE5d0QkAQ68QEgAAlhgkAJkszGLWs4aFgAQABJYpASCQAPQWH7h18j2RvY1XytzniE5d0QkAZgAAWAWQAGQyX4sp5w8mv2M/NKuYANRmUtpSMD8L4xaz6DUPUwjLlABgBmAa8YGb0d8X2dt4pcx9jujUFZ0AMPQKIQEAYIlBApDJfBOAsljRBKDy6CYbSFh8P0EzkadHAjA0qcFG8bnPAOw8dLLiwT2b62sn0uY9D7p+bEdqbRBt8fiezSo4c/GBWyffE9lbTJmHP73cCdwhXzlLzsunzH2O6NQVnQBgBgCAVQAJQCZIAFqIDpJ5jpwZJwBpyx7iSAAWSmqwUXzuMwAD2XHrfg/tqBb3hLLWMiYAExx+VBOdE1V5srbK3OeITl3RCQBDrxASAACWGCQAmSABaCE6SOY5cmaeAPg7/fLZrMvuDksbN/IDQ7ZJvQ535f/lM3dWdW7rdrSi9e6/PrtGtMos+YDov/l/oAdnmRIAotQEwPjfyv52aPkSgIkOPyokAA3lJwCYAQBgFUACkAkSgBaig2SeI2f2CYBedoEQbqw3hDreujtcZfL8zTaNVrJgfrtfkZoSUWtYlikBmN8MgHiYxftaU+3QoeMmUKsQFm2hqURXboudGxpOfODWyfdE9lZTj8Pf4x7fsQ/tUMRzaGf6VNd7SCUAVX1qbhbcc0E7Dp188Ditks5+WxpZjU5d0QkAQ68QEgAAlhgkAJkgAWghOkjmOXJmnwCQWbe31I3b9rD55mqyfqpOIFSQd+lTrVRBVjM0/m+0i7vpgcFZpgSAmE0CUGEtpok4r2kMJJtLE/SPmAvHueOQCVI188tGakp1VfXZuqEhxQfOY60fsreaJj58ipLRt6ac1rua/pTWzkCqh1BZLYoyvzQmQpvgn6aCdPbO7MeQ1ejUFZ0AYAYAgFUACUAmSABaiA6SeY6cmScAblHcsw92nANV/XSdAEWM93e/LBk9h7h6uidUaHZii8OyTAnAnGYAjNFks2hEHtUaUFHNVBCQl603qdTeVeeGBhUfuHXyPZG91dTv8E0wlKPBzFOk6guqNIMbmsrS2TuzH0NWo1NXdALA0CuEBACAJQYJQCZIAFqIDpJ5jpwZJwDBdPt5AC6yHedqNReeqBOQrVzljJ5doWrjiqFCsxMuD8oyJQBEMQmA8rsckhGr9q46NzSo+MCtk++J7K2uXodvgqEcDWaeomR9J2q23AkAZgAAWAWQAGRCvmeVcWchQXSQzHPk0B46fzoUxltXeFtdD5PDrplvwlRM1/GIiK1sFpKtmgW3La7X7M3jg8PSORgWQmqwUXzxMwAm4v1iZShlNVNBP6VTc5mmof0zOO1ddW5oSPGB81jrh+xNq8/hy3I0yOXOU6Tr118ailAr/mkWpbN3Zj+GrEanrugEgKFXCAkAAEsMEgAwPdFBMs+RM3wCABIsUwJAzCUBYK/JRF2prED+1D5nooLhmfj2rjo3NJz4wK2T74nsLaIehy/KNoPgk5k61dEeGotyNw7toQXOBzbvOc57JZ29M/sxZDU6dUUnAJgBAGAVQAIApic6SOY5cpAAzA3MADTljeNqiQ/cOvmeyN7GK+nsndmPIavRqSs6AWDoFUICAMASgwQATE90kMxz5CABmBuYAWhKOcIVER+4dfI9kb2NV9LZO7MfQ1ajU1d0AoAZAABWASQAYHqig2SeI4dcKZgb7qSXRGqwURwzADMSH7h18j2RvY1X0tk7sx9DVqNTV3QCwNArhAQAgCUGCQCYnuggwcgBcyM12CiOGYAZiQ/cOvmeyN7GK+nsndmPIavRqSs6AcAMAACrABIAMD3RQYKRA+ZGarBRHDMAM9LKHriSdPbO7MeQ1ejUFZ0AMEgAAFhukACA6YkOEowcMDdSg43ic5gBgFZZ0tk7sx9DVqNWRScAmAEAYBVAAgCmJzpIMHLA3EgNNopjBmBGWtkDV5LO3pn9GLIanbqiEwAmPwEAAIwUdxkngI0DnUQHCUYOmBupwUbxOcwAKEe4IlrZA1eSzt6Z/RiyGp26ohOAiWYAAADLCl3sAHTihovArQBgLrhhV4fimAGYkVb2wJWks3dmP4asRqeu6ASAQQIAAAAAgDHSngAQSAB6a2UPXEk6e2f2Y8hqdOqKTgAwAwAAAACA8bKIGYCdh05WPLhnc31tP9X6PLRDrc0R9XB8z2YVjGlH2NShHWpVXfrAVcPNex7M3GJ837J3eNGSzt6Z/RiyGp26ohMABgkAAAAAAMbIImYAZuFcRZ/GWHdY85jy9kp2vnnPHpNpJBvWDjzSMF/RTcziNM5E0tlnik5d0QkAZgAAAAAAMF4WNAMwuHOVffbrP6/VjkN2zkIGkw1rBx5pmK/oJvod5gKkzH2O6NQVnQAwSAAAAAAAMEZKmQEwN8gd/gEeU+3QoeP2gRnbZIerQxU276G4wT9BJPokq31oZ163VYUH9+ypeqha8T17tSfysSWz6Di0h5rJp4/qB64acsRsMRyLwe65eFaID8TW9IcfOWS9w2VJmfsc0akrOgHADAAAAAAAxsuCZgAqrGM2EWedjZdlX2uCwuzygnuS3sVNOXj0QDDBWd1yBevCQwVvrHccsjVlE5Kz297r1+pXuUfkS8Dphm5R2fdQweyAO/zagahC2GFbLkbK3OeITl3RCQCDBAAAAAAAY6SIGQBjaivva1y0sciyWmdZBINF7uyWKrCrNvJx00pgDL3copetFttPl5DQYuPAreINw+5ZmcSG4QrRmj4Y2WFXsxApc58jOnVFJwCYAQAAAADAeFnQDEBlZ42MhR0uAXDdZXRLFeIJQNWqtqoWtJMGjfSAgtQl/aRy48CdIg3NznnjXu0AlbiC3ASvFsHIDpclZe5zRKeu6ASAaUkAAAAAAABKZvEzACbCplbaWVmtsyyCpocQ7OzWVag/AiQf+OGIb7Jjj29rerTVZId2Qw8eOvRgIwFoa0gF4eApGeC0pH4gbpciByLWFill7nNEp67oBKB9BsAl1wAAAAAApbL4GQCS8bVMWCWrdZapEAhrO7utHrZJfAmYn6hRW/T4e/auD7loy/UDbzZ03fpdsBgj7zdvEwm7XVPTfgvZ4FIauVd6h7lCKVLmPkd06opOAJhUAnDttddSnNYCAAAAAJQGuRTyKnOfAVhykaFnj75qB56SMvc5olNXdALQPgOABAAAAAAAxdKZAMxmBmCptbn6XsFqHXhaytzniE5d0QkAw5cQEgAAAAAAjIjOBIBAApAtfhAnPCyEBMBJmfsc0akrOgHADAAAAAAARkpnAoAZgGm0sgeupMx9jujUFZ0AMHwJIQEAAAAAwIjoTAAIJAC9tbIHrqTMfY7o1BWdAGAGAAAAAAAjpTMBGGoGAFplKXOfI2pVdALA8CWEBAAAAAAAI6IzASAGSQDULeEV0coeuJIy9zmiU1d0AoAZAAAAAACMlM4EAN8BmEYre+BKytzniE5d0QkAw5cQEgAAAAAAjIjOBIBAAtBbK3vgSsrc54hOXdEJAGYAAAAAADBSOhMAzABMo5U9cCVl7nNEp67oBIDhSwgJAAAAAABGRGcCQMwgAdh56GQF/9Nc+zf0q7+g3xA1aVlr/vmuwvwzrka1zn6cuDv//7x6q37g9qgP7axHMnZm/FLmPkd06opOADADAAAAAICR0pkAzGYGQBhfY7UP7aitjSrqlZvBTkud47mpjk9LsuonVT9w09WDD4aeXaR35yOSMvc5olNXdALA8CWEBAAAAAAAI6IzASBmmwDkmuBotWaws7eczck6OfWTqh+47WrHngeriYWpOh+RlLnPEZ26ohMAzAAAAAAAYKR0JgDzmAFwhlgEzeNA/AzOHh/07tnFN9uIp3qupm6pfT9E2x39qtqhHaJbu3VP7dGdXNUP3G3aHbGImHJkV5dHytzniE5d0QkAw5cQEgAAAAAAjIjOBICYTQLgiXh3s5ZN8OY9x0+KoEsVqqeGhIHWnXDZm+nqCwatTXYc8qmF7ETVn0D1Aw9dRQvNXV0eKXOfIzp1RScAmAEAAAAAwEjpTABmOwNgzG74AoAIujkBEawKqaBapTo3992tw240MdUEJiGJbquP6gcuujJ7IzYU39XlkTL3OaJTV3QCwPAlhAQAAAAAACOiMwEgZpgA2Hv8+nmYBSQAVTWr6Lb6qH7gsiveqo8gAWiITl3RCQBmAAAAAAAwUjoTgJl/B6Aqy4JzwPVHgFqaBKlq3klXDjvaJDyUHyLNbfVR/cDrXZldIjhi9qGxq8sjZe5zRKeu6ASA4UsICQAAAAAARkRnAkDMOAGwLt8YcBHcQX7YoL8E7JpUZVex+0vAsm2F8/1VteYjQM1NTKD6gdf3rZbeRHd1eaTMfY7o1BWdAGAGAAAAAAAjpTMBmM0MQLZGfju8/4Evl5S5zxGduqITAIYvISQAAAAAABgRnQkAscAEwNx9r74PMD71PvAlkzL3OaJTV3QCgBkAAAAAAIyUzgRgETMAtSdyRv00/IQHvrRS5j5HdOqKTgAYvoSQAAAAAABgRHQmAMTcE4Dl0coeuJIy9zmiU1d0AoAZAAAAAACMlM4EYMHfARi5VvbAlZS5zxGduqITAIYvISQAAAAAABgRnQkAMUgCAK2ylLnPEbUqOgHADAAAAAAARkpnAoAZgGm0sgeupMx9jujUFZ0AMHwJIQEAAAAAwIjoTAAIJAC9tbIHrqTMfY7o1BWdAGAGAAAAAAAjpTMBwAzANFrZA1dS5j5HdOqKTgAYvoSQAAAAAABgRHQmAAQSgN5a2QNXUuY+R3Tqik4AMAMAAAAAgJHSmQDMZgZg5yH3Z/4Nh3bYoPnr/8f3bJbVpKhJy1r7L8PqmH8g1qjW2Y8Td6f/B1leW6H6gdeOeqrdG5uUuc8RnbqiEwCGLyEkAAAAAAAYEZ0JADGbBMDbXGO1c/7bV9QZN4OdBjrHYVMdn5bU6ue0ral+4JmbnmwTo5Ay9zmiU1d0AoAZAAAAAACMlM4EYGYzAJO66mi1ZrCzt5zNyTqpcpbqBz7pppdHytzniE5d0QkAw5cQEgAAAAAAjIjOBICYbQKw45B/0kYEzeNA/JzMHh+0a3eE+GYb8RzaGelZ9EPE7uh7VdUO7RDd2q17zCYibatHj0wF05HfkFH9wDubyzpyn2zl2k665mORMvc5olNXdAKAGQAAAAAAjJTOBGDm3wGIeHezll3v5j3HT4qgSxWqp4ZCkyAZqfqx7jn0k26y45BPLWQn0bKSX0X7Vh1R23cAZJ4geo73U9u028mwagRS5j5HdOqKTgAYvoSQAAAAAABgRHQmAMRsEgBrZ/mOeTPo5gREUDrgeFCtUp2be+3WczeaVHfWLcZ2R7elyl7VPXxeRXVcckJr6wee2dwW7F5VRj+yk6KT4qXMfY7o1BWdAGAGAAAAAAAjpTMBmPV3ADbvOe5trvC+804AqmpW0W2pslXVlkpuFR8R/aRy/cBzmtfq2AkQu9uRnRyTlLnPEZ26ohMAhi8hJAAAAAAAGBGdCQAx0wRAlGXBul79CFBLkyBVzfUjDHS0ibjX7iLNbamyFWUVnKuY/v0qKj946NCDGQlApLmu4xMkiqudHJOUuc8RnbqiEwDMAAAAAABgpHQmALOeASAZl2+8rQj6B2P0l4Bdk6rsKka+SGBljDUj21Y4S11V465qnYhNNNv6ltbx15rYXaofeH3fjJrNfR1/BkwKw5X1ToZORiBl7nNEp67oBIDhSwgJAAAAAABGRGcCQMwgAciWcb3je/SF3DvPPPQ/8OWSMvc5olNXdAKAGQAAAAAAjJTOBGA2MwC5MvfBzZ12HS9alLT4fe594EsmZe5zRKeu6ASA4UsICQAAAAAARkRnAkDMPQGoPewyqtv/vOfVcz4THvjSSpn7HNGpKzoBwAwAAAAAAEZKZwKw2BmAsWtlD1xJmfsc0akrOgFg+BJCAgAAAACAEdGZABBIAHprZQ9cSZn7HNGpKzoBwAwAAAAAAEZKZwIw1AwAtMpS5j5H1KroBIDhSwgJAAAAAABGRGcCQCABmEbqXvhqSpn7HNGpKzoBwAwAAAAAAEZKZwKAGYAppazwakqZ+xzRqSs6AWD4EkICAAAAAIAR0ZkAEEgAppGywqspZe5zRKeu6AQAMwAAAAAAGCmdCQBmAKaUssKrKWXuc0SnrugEgOFLCAkAAAAAAEZEZwJADJ4AvG2N/8Z/xfrei1WdpZGywqzNe47TUfN/C86S+Y9o9l+iqbgU/xOCQzt1fAql9tPuzgT/o02Z+xzRqSs6AcAMAAAAAABGSmcCMMsZgKvXyPlfqIIpTVS5ICkrzBp1AsDBjp2pS5n7HNGpKzoBYPgSQgIAAAAAgBHRmQAQSACmkbLCrIkTgBzNNwGYaOeVuc8RnbqiEwDMAAAAAABgpHQmAPObAbjw9nXylYbDb3vaxXvXaZ19Luhth0+ur/tVJ0+uXe2bj0PSB7N1DhgPza6d4Sdq+PGaB4+7uAjWbro3G3JENVTBk8cPHfL7wKlCs5/oftq4XkU9xJrLIO+zMvc5olNXdALA8CWEBAAAAAAAI6IzASDmkgCI8tsOW+tPEcoE+KeqPCYF6+ycvbXdrihvogeL7xIAY6are+3NBCAorHJev96wEbQ7wNHjezbH+uEdSO2n7FwEo7vh1+5U5j5HdOqKTgAwAwAAAACAkdKZAMxpBqC6/W/h2/xvO2yKb2tUHpWCRZZmuuah1f1y4b+5Wgiagu8t0pAXbUNtx1Vvbmd8AlDvJ7mfXjpYby634rTjkDL3OaJTV3QCwPAlhAQAAAAAACOiMwEg5pUA8J1+oRVIADho7HKw7K5eRwIQadgrAWj2w5HMBKDZvNmEIsrc54hOXdEJQM4MAAAAAABAmRQxA2DKtCD/GChFluoRIOG/3T3zQzu4YIx4tdYZ8PYEINawTwIQ6UdU47UtCUB6N0zJN9m8R5n7HNGpKzoBYFoSAAAAAACAkln8DABJPgW0dnv4EvCFpnT7heG/B4z5S8Ds7QPGQ/vQgw96A82RjgQg1lB4/ewEINZPdD/DdmsJQLy526iFI9LZ70sjq9GpKzoBkDMAdP1AEARBEASNXb/8wCOznwFYCbFpXnFJZ09yfr+OqkOnrugEgEECAEEQBEHQ0igkAAQSgGmkrPBqSpl7knP9HrWWRKeu6AQAMwAQBEEQBC2ZMAMwlJQVXk0pc89y3j/m/kl06opOABgkABAEQRAELY0wAzCUlBVeTSlzH5Ry/yQ6dUUnAJgBgCAIgiBoyYQZgKGkrPBqSpn7HNGpKzoBYJAAQBAEQRC0NMIMADSglLnPEbUqOgEIMwB0qUAQBM1O9D4jUWshCIKGlXuv2bBhkARA3RJeEa3sgSspc58jOnVFJwCMu0QAAGBmPFHHRQEAYDa495onnkAC0Fsre+BKytzniE5d0QkAzwAAAMBMkR/GDEXcOgAAGBokAINoZQ9cSZn7HNGpKzoBIDgHwE/8xE/8nN3PVALQ3go/8RM/8bPfTyQAg2hlD1xJmfsc0akrPQEAAIBZk0oAAABgFgyeAEDQpEICAABYdZAAAADmSU4CoO7yQtCwQgIAAADm81jiogAAMBvce036rwApuwZBwwoJAAAAAADAYkACAC1ESAAAAAAAABYDEgBoIUICAAAAAACwGJAAQAsREgAAAAAAgMWABABaiJAAAAAAAAAsBiQA0EKEBAAAAAAAYDEgAYAWIiQAAAAAAACLAQkAtBAhAQAAAAAAWAzZCcDmPQ+e1Dy4Z7OuBkFZQgIAAAAAALAYshMAp817jjvn31jVoR2HqOGhHY04tJJCAgAAAAAAsBjmlgBY/48EAHJCAgAAAAAAsBimTQDkk0H2iSCucPLQzlCZyuz+HXYVtOJCAgAAAAAAsBimSwB22sd6rKHnTMCUuXR8z2a71mYFVAEzAJAUEgAAAAAAgMUwVQJQu7FvkcmAgdIA1xAJACSFBAAAAAAAYDFMkwDUZwOEkABAXUICAAAAAACwGKZJALzRP7SD1+7YY+2+fwRoh/3tHwHihkgAINZiEoDf+I2zIAiCIAiCVlxTJQCk6mY/Ye73851+OUXgv/VrvxJQLUIrLSQAEARBEARBi9GkCQAEDSIkABAEQRAEQYsREgBoIUICAEEQBEEQtBghAYAWohITgH379qkIaRsAAAAAwIJQtiRTUUsjhQQAWoiKSwDoUkECAAAAAICiULYkUylXE4QEAFqIykoA+DohVJzkrj8AAAAAgLmjbEmmnK1J5wBIAKCFqKAEwF0iFrWK5K4/AAAAAIC5o2xJppytsahVLCQA0EJUSgLgLg6PWkty1x8AAAAAwNxRtiRTztZ41FoSEgBoISolASC5i8OiVpHc9QcAAAAAMHeULcmUszUWtYqFBABaiApKAEjuEkECAAAAAICSULYkU87WJNw/KT8B4H/xK7H/7nfnIfsPgFXl8cn8S+PpD2SSsxHfYn4PxZ75rB0rKwEgpa4Td/0BAAAAAMwdZUsylXI1QfkJgJeyd5Pa0InqF+Jx83ej3w7LVu095NccVhNtK6tycQkACQkAAAAAAIpC2ZJMtbt/EhKADOXvRr8dlq3ae8ivOawm2lZW5RITAAiCIAiCoFXQMAnAjj0PVg8F2bh5voU5tMPV5MqeQzsb1cyC62HHoZMPHverfGWv6mEkF5e9NBflVnwk0qo6rnr/7ftsu/KRB/fsUd6XuvJbFOeN6rueKaL6t8Hm+XQ9eFpqNnevkjrk6Jmx3dJxWPxTXh6/3UOHjrv+Uz0gAYAgCIIgCCpTQyQA7BOta3emU9TZcajhYkPzZjWKUA/8U1Vuyq81Lttac5ZaNNW8NzVulTs0pfSOqYhcJcrVPrv+N+8hW1zvJOwMVaaUxm6RqvmG0f6b5zOos6aooM989JCbZ8Z26/c50q2t4PtJ9RAqJ4UEAIIgCIIgaDEaIgGQ1tCWjRcUaDvu60erGdPpPWXKSto6lmpzlbWNLFY2mpqazutBK7Et1X/7PlPEbKzRCcuv3XHI3q03ZQqpbmWrVLkZiZWbuxfamlX1Q65H3JmJbyKx3e4ekkICAEEQBEEQtBjNLAFQ9jooaR+drPluSwCqVlSq1tq776GhWIya1Mimmzsf+m/dZ4q0JACuk532bjyVD+2o6ofKslWq3IzEys3dC2quqkdWIgGAIAiCIAiCSMomkSio7JqQsndRa0gF9bRJkKrffCiFDCX/5MWGlSSbyQbauM/aWv9ojVo0W3GJQWVYTamxadtbpH+5G6a3RkPXv8069A6b3RAP/xw6FJ7MCd2q/qPlZiRapoLavaDoITfPTKrb1HZbepA1taIDDwkABEEQBEHQPKRsEomCyq4JKVen7KAvGzvoqT0CZO4TV8FatT3BoRonbUr1yk6+zYNkpe3mXCXCGlC1SKq2ovbcUb9v3ei/bZ9txG+x+SVgX98HZVmcLtF/4nx6ddds7l4lquYQrp2JbrQqJ7bb3kO9Zl3RgYcEAIIgCIIgaB5SNolEQWXXIGhYRQfezBOAfwcAAAAAsPIgAYAWIiQAAAAAAACLAQkAtBAhAQAAAAAAWAxIAKCFCAkAAAAAAMBiQAIALURIAAAAAAAAFgMSAGghQgIAAAAAALAYkABACxESAAAAAACAxYAEAFqIkAAAAAAAACwGJADQQoQEAID/f3vnARfF8cVxqYKioog1KtwZu8ZYI9HE3nuJaGJijz1GjTUiWGKJsaAJtoCaaBI0tr+mGAuoGBElEBsWBBVNbBF7Igj/tzt7e7Nv945DDg7w/T7fD+zOvJmd2zL3e3d7dyQSiUQi2UaUABA2gRIAEolEIpFIJNuIEgDCJlACQCKRSCQSiWQbUQJA2ARKAEgkEolEIpFsI0oACJtACQCJRCKRSCSSbUQJAGETKAEgkUgkEolEso0oASBsAiUAJBKJRCKRSLYRJQCETaAEgEQikUgkEsk2ogSAsAmUAJBIJBKJRCLZRpQAEDaBEgASiUQikUgk24gSAMImUAJAIpFIJBKJZBtRAkDYBEoASCQSiUQikWwjSgAIm0AJQH7WEwskhZJyUNKuV0qqI4mSdopSUh2JRCLlI1ECQNgESgDys8AztTQrMlU2kfq40IFAol1EIpFeElECQNgESgDys5iLSr53XxMyVbYS7HZ2aJjYqlRHEsX2ibSDaBeRSKT8K0oACJtACUB+Fm+hNEWmKocl+tgnBw4cGDp0qHQMWraEZShhVVLcSyy2H2gXkUikl0SUABA2gRKA/CxmmCyX1IyUbYKdvG7dOl9f372/7mVvwsBfWIYSKKdDAKJdRCKRXipRAkDYBNskAARBEARBEASAbBKAAggiO0BnHZC9CQBBEARBEARBELkKSgAIgiAIgiAI4iWCEgCCIAiCIAiCeImgBIAgCIIgCIIgXiIoASAIgiAIgiCIlwhKAAiCIAiCIAjiJaJAgeknCIIgCIIgCIJ4WcDrBEEQBEEQBEHkY/A6QRAEQRAEQRD5GLxOEARBEARBEEQ+Bq8TBEEQBEEQBJGPwesEQRAEQRAEQeRj8DpBEARBEARBEPkY5XrinrR0WXu28VWWA538u+QrVEgQBEEQBEEQRC5Auc559x+T09OTh8zgay2EEgCCIAiCIAiCyK0o13nv/sI+nhIAgiAIgiAIgsitKNeV7wDcvdmQlX9586J0W5D0nsCQOGk9/Xyi1NYQczHiptjJuSV3uJuI+N4IgiAIgiAIgrAVynVIAEQXD5KdvTIruBhxzlDOVwkNmd1vePjf9HSxEEy/oRNIGF70EwUEQRAEQRAEQVgP5brB0Asv5xs+AGB8+V8U8/TCJwSYDPF35Bf4+ayAdZK4x1hLEARBEARBEITtUK7L3l14IV96sZ9PBhjGknNL7phJAKROjF0RBEEQBEEQBGFblOtG784tw0K6wsHLN/QLmYAxBt8CxALuJO9hSYLcnCAIgiAIgiAIW6Fc5xMA0cobjb5Bwi1Awgd8Bd3lzL3hpiDDh4ClToSPCxs/TkAQBEEQBEEQhE3B69aGPv5LEARBEARBELkIvG5dFJ8NIAiCIAiCIAjC1uB1q8FuE6K7/wmCIAiCIAgiN4HXCYIgCIIgCILIx+B1giAIgiAIgiDyMXidIAiCIAiCIIh8DF4nCIIgCIIgCCIfU8DeKVdRn0Qi5VkVsHfOHA5ZoSDxgjjKuJjDgQOVyDE8cq0xwLAhNIA8AzrlnOs3fCNXgS8oDP/0qi4hrAW/w+Vltpqt8NsyACcqKjEH6tAUqIlmQz5GSeaGZIC77nCV5fCdMFCAGVBD86C2uZLhH45UlKgOoY2RfASJRMqDUkwuloDm0MyBvBphMbIvl727JmpDj1YRcq0xwLAhNIA8AzrlKAEgNOH3LVvOmV0tb4sDTlRUYg7UoSlQvGZDOUZF5obEwa47VJgpWA88KMAMqKF5UNtciTIBcKIEgEQiWU3c5GIZaA61PsjPEUpk766J2tCjVYRcawzI5QmA+jyRS7RB/tvm4AsKwz+9qksIa2GrHcuOqRI4UVGJOVCHWQH1zJG5IXGw6w4VaoBGImPogUfR0CyooXlQW23Q8BDqGLmh5fDNMWICwJUoVnIBko8gkUh5UKrJKCPQHGp9ZGNHaCF7d03Uhh6tIuRaY0DeSgDkVZMg/21z8AWF4Z9e1SVEXkc+0BxwoqISc6AOswjq3EDmhvQCoGHIiLXc9cs1sQC+oXlQQ5Og4SHUMXJDy+GbYygBIJFI2SXVZJQRaBq1PbI1fDmQvbsmakOPVhFyrTqAr9JGNbacAB13edUkyH/bHHxBYfinV3UJkdeRDzQHnKioxByowyyCOjeQuSGZAW0uQ8RW3PXLdWUBfEPzoIYmQcNDqGPkhpbDN8dQAkAikbJLqskoI9A0antka/hygGw6gjfoqESO4ZFr1QF8lTaqseUE6uMul2iD/LfNwRcUhn96VZcQeR35QHPAiYpKzIE6zCKocwOZG5IZ0OYyxNCQXb/yqoWwVhaC2mqDhodQx8gNLYdvjqEEgEQiZZdUk1FGoDnU9shG8OUA2XQEb9BRiRzDI9eqA/gqbVRjswIZHll1rVyiDfLfNgdfUBj+6VVdokZuaAmobS7B/NjkwZuJyUPwD8cAnKioxByowyyCOjeQuSGZAW1OBoVZCe7CzxhDK/+AOemiQrds1SpBIxeA8kuX4j08ywCwwIKhldxnZsCd81ACQCKRskuqycgC2NTJz6S2RDaCLwfIpiN4g45K5BgeuVYdwFdpoxqbFcjwyKpr5RJtkP+2OYpLSQP+6VVdokZuaAmobe7B/NhYbW4ev+WwA6EETlRUYg7UYdZB/YtkbkhmQNuSQWFWgrvwM0ZsUq1G7WvXkuAvcPPmzb6+76oX0OCh/P79+ywBgOVhw0dAYV/f/hAMq8bBZAzbD4rOEZQAkEik7JJyPrIMNnXKf3MpancoW8a8DLLpmcdLXzUs/FBi4hX4m5ycvCxwBZS4e5SWAtDmsh3D0XF0cSleukTlWmVee7Nc/ebl6r1dqlZjd+/qTkVKaARnBuS/tWicKQa8PzAhIfH69RtfB4fA03OnLt3e8GmKYsyAnkCzSKFCBSt7F+razmV5gMuudc6HQ+3/t9ph8gcOFctALXfNSijavgh2Anb2zo7Ork6uhV3cPdp26+7r5+cZEFCAo1xAQL9p0173aeroVsy5UBF7x4K4H8JS0BFEoEh+9YVR98zDai0HNQfECxMXyvBteSyJ4VBOAkZQmPhif1TUCVYVumUrAFb+9OkzYO5hW1Alvq7Pb114+X/nrv/JMYxqNWqJiUQtucQCYKOoBJOvEoBmzZoNHjx41qxZgYGBq0XBAqxCIVRJQSQSKackz4MvCD+35h4qvVmg6UdG6vQp4O7N+ci8DGflXwDw+mD6x0+Y1LxV2x07d8Hf9Ru+gWQgJjZ24OBh2fa6vimk4+Xq+UrjD2e2X7mna2jsO79d7xd+t//B271/Tuy86UTrz7dU6/qBfUE3Pj5TqOw+Aht08wweMgzc/5mwCxsnb4vaFXvvTvLFi5d+3bt3ytTpb7dohYI1QU+gL4CDe4Widdt4te4/YPyg0E1vxISVuRVld3Wn3Q+f2s/o4/BhW4dV4+23+duXKgbB6IJV9JNpRPcPODq51KxVp3Gnzu7dulccPaaKv7+LMgEoFBBQdeZMz8FDinfp2rh9h4qVdJQDvCjoCCJQmLyaFcx3xWotBzUHxAsTF2YKvn8TKCcBIyjMYPpZFUsGwNaDuYc0QPb0UM5e74etQ3n4oUN8ksDwD5gtJBLGQVoCbBSVYPJJAtCkSZOxY8cGBQUFBwfv3r07PDw8UhQswCoUQhUEQJjUgEQiZb/kedBi2IXPlfATK1u2Fa4egt3/KLLA5HMa9PyyQOlaSgOaF5HvwFGi8voSyqqw8EPg/uvWbwSmH/6yQsgEAEgMuvfso9pctiIctVLVGvTaENFyW3ydXdca7L7eau/Njvtvdzpwu/Xem433XPfZmbDoWMKIkL1FyumMBzozqBw/Aht0M4D7v3Xr1s2EO/4tlw73mjoaTG6LJftDIpJv3n/y5AnsQBSvifzU+QI4lPAq3mZko083TArdvv/wVw+T16XcbZ6013HPvGLtejYvX0lfzNHJ1d7J3cXpyzH2jas4oubWwbWwU0Xvxn19282Y4e7nZ+fvb6d0/wyh0M+v5MyZ7aZMqdquvV25CgVcCuOuiFwKTOaoxIqIFyYuzCyGZxxTKCcBIyhMKwGA/sHfwxVtuK0fzL2UAMi5AZ8AQHOIzLz7B2CjqASTHxKA1q1bL168OCQkJCIi4unTp+LnJRSCQqiCAAiDYKkZiUTKZsnzoMXI1z4q5+An3BwDzP3A7dj0q2k4WGVDrcmSKa8+Pdn0UPSom3FjUuPHMlL+bPE0uuniKZWLF3dF8ZlH6ftlOJevgKv10lcF3w+rkAYIr/cbAthNQZAYiO8DDF22fIX/7Lmq7VqZmqVdp7YrU63rwPYbY19bHeO15mStzQda7DrY4Kekt/beemvv7Xo//1Vl9zXdj/H1g2M2R/2582jYgO5NSwg7UHXozZ57KsePMFrzjp27fjxhUsvWbflCGXbnD7j/+V2+HFZxCs+4mv5xR4UPAqImmnBXUGZwdnOr0/bNRTvH/R4fembfnbub0p8tSr/++oN9xbd922/OgbDuuy/Unf9L8baj7IuUhviezRyaVrdyAmDn4Ozo7ALu375//yJTprj7+zsoTb8ax4AA91mzXCdOsuvdx6l8RXofgJAuUlz4AigvfIRyEjCCwrQSAN7cwyrLARhSsJghqN8BgJwByuUSC4CNohJMdiUAXrrKzVu2HjhoCIx7+44dBw+GMS+OwjJE8hGmBYZ++fLloaGhd+7cgf7T0tJOnDgRGBg4TRQswCoUQhUEQBgEUw5AIuWM5HnQYvjLH1Up4afd7Abcv6kX/tU0/QiZUSuy+fMaKbHNhh77Oerq/rTkMEbK6fZQ+DS20/4tI0LXDhdYPTR09eDvVw/8fvX73we9931Q/++DfNcv6VarRnnUoQqDp0cwN6+Gq+3es8+ywBXuHqWFNEAsqVu/EWQC4PjFuV8hlgw0b9lGNQDrsKl72UPv1v5w5pK+84O6LP7Sf+34qB2NPtz6Rbnt8bpdSd67kjy2X3EOveSxJrb6qujRO86GHv3l/Omf145v6VWxkOLQZ3TWqRw/QjDlTd9q/sWSpefPX0hJSYmMPA5eX/brDPnOH/+WS5H7Z5zY/SfsNNRKE+UVZBF2hUuWaDm82/Y/lickRZwLffhwc/rDfukxJa5tL/vNL4FLLl6bef3ZqEspviceNVh/yqNXgEOJSm/Xc6xRycoJALh/4c6fvr7g/pHRzxD3Tz5p3KMn3QtEsIuUTTKWS9WJjGoGYKjmAQkUpvUZANnlA1KtuFytRq379+9LAxIl3xfEQNmCBcBGUQnGCglA3XoNmrdoDUY/ZP0GMPpQIg1fS3xDS5B8hAk1adJk8eLFYOsfP34MncfExPTr10+q4wSFUAUBEAbB0ITuBSKRckDyPGgxwlUvThUZSIrnJ99swtWjwIgDCosPyUD/byU0E4Mq7ZAftRYsAXgQ0+bfP9uknDIQ+1bqmS5pV2en/xWU/tdX6TdWpl9fnnZ9aVrS4rRrC9Kuznt+JeB54qcp8VN6dqyJOlTBmX7LEe2+/+y56zd8A3+Tk5PDwg9JxykjqQZgBYq4OB/s6BXdQR83subFyTUuLap2I6RSxJbGrsExBb674PTDJccfLsGCXciZosuOl5kX3nLZ4St/X35y+9vzf2z7YoK34ugbz0zt803l+BGCKd+563///fffvb+Sty/49cGdh6CPJ0ySLfvIUWNu377N7vwZVglbf0Y2JgCOrkV9BnTbdSboVnJ0fOiz//6X/vT99KNOV0JLB/68eenl28vupC5OTp/xd/qohNReUY9qro4p2WNG9VfdShSzcgLg5Fq4cafOwp0//v7I32dIyVmzhHuBGja2c3JB3RL5j1Zt2hV190CFBoSrks0tlkvViYxqBsgkffu9y769x/CdP/3BKsvOHjw9JANg65HXl98BGDZ8BPvgL/xlzeUYC4ABoBJMVhMAaf9x0iyUxbe1BMlHmNDYsWNDQkLYa/979ux54403pAqVoAoCIAyCoQk0lCpIJFK2iZ8KLUO46pUTBQoQEAPEZZUhsz5NPzI6+04LhXcDqrQ1eE0xPYBCOYABCQPnR61I6Nrhoss3w8r0G4Hp15elJX2Rdm1h2tXP0q7OAff/PGHq84RJvTvXQB1i2Ov6apDj5xBe4w9cYbnjR8IDsAbe7q4HW3lfHaa7NlafNEl/Y773reAK4TPqN1nyXc01P3l8ecjh69NOa2NdvowuuuRYydlhFafuXbLnVOrdb9L++Tr6QLfK3k7SoedOOQlWzqFy/AjBlMPDDNt4bNSrM8DKB74fkhiblHzv/sJFnzdv2Xr8xxPhKUnzzh+e7EsACr5Ss93XB1b8fT8yYfezp9+kP+7772G7HYsrNhww0r3liHI9Jr8xbe2o/efnXv9v+t/pwy6kdDyc/OqSCPc3+lr9tXaX4h7u3bp7+PkVmTevyPz5xRYuZBRdsKDwZ585zpnDvL7znDmwCoVygNv8+UXmzvWYNq2IT9OCbkVRt4R5hGsQT7m5goGDhpgaVdXqNX2avoUKDQhXJTTMlFSdaKKaDSxCeJmfbUV+/R5MPythL/+bSQBggX1aAASZgxxgLfJwAtCsWbOgoKCIiAjoNiYmxoz7Z4IA9j4ANIGGGX4vkO+01aun+crLhsUXVNuRC9kXE4nKYmc5I3HIC0e2lVZNSQjLE4/HhEyOXzgB8vQjywVSzYYmEacHQXDVs78GcCQgBnBNVLbMaoC/Z6/x9/9W+KofcP9g7o03+hvC1B8PyJ43ATJIAG58mX5jhcH9L0q7Nj/typznV2Y+T5z6/PInz+PH9+5UHXWIQb5fRuX7ZaRj8KLCA7AGH9QqfvF976tD9VdH669N1N+Yrbu5uuIfA7yi+teM+qT5kAkzii6NLPb578X9D5ac/lu5yb+WGbvrLf9d16/9kn5rzqOEru1aOEqHVXXiGY+4AZXjRwimHB7m6pGbZDc/qf68PSsO3ruTDE//4P7Vd/74t1o6Qj+dL8m+BMD7vVlzzl79Pe67/x5/m363TfoB+9WTPUtVKGtXUHTSjoXsi5UtWq9rvy1Rc2+lTrye1v/PJ2/9crvs6GBHj4p8P1mnrfidP2UXLHhv48Z5+/atPH58ZVQUsPjQoY+2bKm9fLnd7Nng/psHBX2ybduSI0dYbWBkpN9PP70TElJm7tyag4d06NIVdUuYR7gGszkBEG4IbyHdEG6hi2XuH42qS7ceZcpVgAWngoXad+xs4k0A4apkbUGqWgVSkKWPXTUbWITYFuYKeTk3kYcTgMGDBwcHBz99+jQtLU3zzh+1IAyCIaOChtBcKjUhLgHIov9n5p/rwXdapruDIWTsxa0qGDUo463mwQRAsTPzegKTq6WcCs0hTg6wIFz1yolCESYgzu/MfqFl61Onj+DmOy0UltknAYRX91Vh/LsEjE6LkCu1CuYSAMn9L09LWpKW9Lno/uc+v+L/PHGa6P4/To0f27tTNdRh1oH9b0ph4Yd27NzlP3suu91fKlUK9ZZ1Crs4b2pf7soAfeJg/dWR+msf669/qvt7RcULH+turB73+8419eb8r1RAWMnJv3iM2eE+LLTE8C3Fh3xfYei6348Fpv81Nv2fcf16ONrBMUVnnYmzUeX4EYIph4fJJwDA6Kozt3++N+W/FPWdP580/OxSVOLHdefIJUA2JQAOHl7tv/p196lt/z7Zlf50ZPphh/0rvItVrIrC7FyLVx86L+DKE79baUMuPOsUkVxtxYlCVZsXsLfmmwDv+vk1X7CgW3Dw1iNHjsTFHUxMZBy6dOngyZNjQkMhB2iwcuWC3bsjYmIOxcez2rCEhKNnzmwOC+u0Zk37efMG+Pmhbl8ewDQDqNA84iVoFJQwj64J39BCwPoz39+8ZWsA1ZqCuX/2ly+vUMkbfD+4f1iuWfs1gK/lER9NJoSamwXPAArY04FGCeokt5CHE4BZs2bt3r0b+jxx4oRUZIEgGJpAQ2guFZmQMQHImv8XDGbWvXuOJwBsg8adYFKUAJBMSjEVmkWcHGBBuOqVE4UiTCAnEwCw/sz9u3tJbwW0mqEIYFRpq3D/wMDtyJhaBdMJwFeC+78RKN76D+5/oeHW/xnPE6Y8vzwhNX5c6qVRvTtVRR1mHdj/TAavP6x5q7awisIAFoaEYrKOvkShIz0qJvjqEgfqr3yovzZOnzRF/9fnXjdXVQgZ806NcT+UG7+n3Md7So/eXnzo96791rn0XFmwx8ouAZuPHpqZdrVf2oON2+eVKOQC1hadeNpno8rxIwRTDg+TJQDTmy76vNfq4V5Tma1f2ncdf+fPh17TAtosS4i5BvETXs+JBKBw3c6z9h25nbw1/dnMtOiCl7fpW3wy37lCbafSVURelfHsPGF2/IPP/kkfnZDa8+Sj17+54N5qZAEna37zZqV584Zv3PjjkSMn4uOn/fZbvbVr66xeDfTduvXA+fP7oqM37t27ad++Y+fO/RoX1+OHHxoHB/uEhDRdv351ZGTs5cvfHjzYbdWqsrOtf5tEnoDZZVCmcgCI11xW8wIJAPtoKPxF5WYQH4Eg9ihgQS5n+UPdeg2Y7y9TroLpu4CM/Vgo1NwseAZQAM8F6hKhEHWSW8jDCUBgYGB4eDj0uXz5cqnIAkEraAINYUEqMiFN7ytaR1+wjExCvWAgjWsqZWChja1BxjjmSoW2UDpN/CeJxfDNsJeV67iMQTvejAwemXUpFYpigxLEOuIj2Gbww7V8p3HDNDFKLoILYWOQ66QKtOuF6oUjR+Kdqd0WZNgFIJMxIH5/CA8SP/qXWng2NI04OcCCcNUrJwpFmEBOJgDCV/qIC+ob/TNE5U21kLeFyrUxkQCIH/y9IX/wV7z1/8psg/ufmBr/UerFUakXhvfuWAV1mHVg/zOhQn6VwcKQUEzWqVva7VQf7/g+uoT39IlD9VdH6RPH6U+PePW3gPq+EyYUHbip6ODvig7aXLjvGtfeXzl1/sKhzRzHt2eMX/7D41vBqVe6P0/euH9+w2KFXNiZJmA8FTXORuS/NYGHyRKAxe+suZV4d+UHG3hzzxihn/7t1O3/3EhmuyVnEgCP9h9FnFz9/NGn6adL3Pqh1Hd/bPc///eEY+fHR5wbf+QsYxxw+OykqKtL76QuSk4fd+25759PGm+7VvLdRQUKFkEdZoUi8+fP27fvSFwcuP8aQUF2YOXFm/5Lf/HFe9u374qNvXb9+uVr176OjOy1ZUv5Zcv6bN067pdfvAMDIQeYe/Bg2Nmz72/ZInxUQNVzvkd+yVxeQAGmgGCw1LAAf2EZFpKTk1lz+AvLLAzIbAIAzaGJl64yW5W/E9J8P2wM6tXxH0/cvmMnLHh4lnm7RStYKORWrEu3HqxWDTRkQuUIKSijMC3wPCAhTBeqEjyH5CKymgBkN5KP0BI4rsjISDh4YJClIgsEwdAEGkJzqciEkH1kEt2e5P8kP8ivqc2fZi8GKdvwa8LywoXTjEaTc6OgtiPlKtxKHpCwZUMTE/GmZdycEG8MF8cldeU7UlwwBvBb5CWU892Z2Gl832IbjVFm7oEbHwVIiJHCVeUabRVR5mLkZXHFgn37MgnPhqYRZ2FYEK565YysCGMIAWxize4EgOHqgc29Jai8qRb8hlCVBloJAHP/K9LkW/+Z+7/iJ3zw9/Kk5/HjUy+OTr34YeqFIb07VkYdZh3Y/0yokF9lsDAkFJN1qpUodLST18Weusv9dYmDhDcBDvtUXvr2W690nunW4wv7XkEOfVbb917l0HGxQ5vPHJrPcPKZ6NpwzISA0Wm3Oj5PavAwafLWxU3dCrsKZxo7LsZTUeNsRP5bE3iYcgIAy/8++m9p33W8vwfWjfn+6cN/xV0iKGcSgEbDJj6+szLtau30TQW2/jp7/aPH36alf5tuAJbT0jempm9ISQ/+N33V4/SF99LHJ6X1O/W0yc6/Sg35qkDBYqjDrFBs4cKVx48fTExs+PXXuhUr3ggObiJSa9WqCsuWfRUV9V9Kyj9Pnoz++WfPxYvfDAkJPXPmeFJSv23byi1d+taGDdBwxJ49jnPnom7zPWCs4dwQXTuckPwqjlSTmHiFOX74K3x7L9ccdZKhd+dhr/0z9w9/WVtLbgGCjWquupfwlJdl329JAmChUHMLUEwCZmEfAEDNcwt5+B0A8Fq2SQCMhao12QvK0uxFkqqB0aMKS4o6zc6ZjFXKVsbelDLTlUF8iKIbjT6lImhiqluhythItSa14rcJMjV6TsYWQrCxsbEp1yffn2JTptrixhn0LwrWMxr0yyXVbGgScXKABeGqV04UijCGECCZ5hxJANR3+FiCypuqUG0IB2D4BOCvpM3nrm0/fWVbbOLW6ITQqMvfRcZv+v3ixogL6w+f//pQ3Krwc1+GnQ28dN4v9eKI1AtDU85/0LujHnWYdWD/M6FCfpXBwpBQTNZ5raTbiY7ecV10l9/RXX5Pf7aPLvJt/QHfuo26jHVpO9eh/YJiXed6vfNp8c5+zs2nuzYYXfi1oUVqDJj96dv/nX8tNbFO8tnqx1ZXci8qnmnsoBhPRY2zEflvTeBh8gmA5nf+rBy44Z/ryewna0A5kAAUdCm4Y2fnf/8ek7Lf6eC3b3119frG5+mfJyUHnLsacDoR8AdOJc6KTZwZkzg9OuGTEwkjjyb4Hrjcbte514JOeLzzWQFna74DICQAUVHg431CQsb98stvly+zu/xXHD9eb+1aqHqWmnrv6dORP/302po1ITExSQ8ewOrBhISuP/zQbP16iISqly0BUDp1OCHVheaoW68B+H4Ihr/srQBAs7l/wBz5S2zMwxw/7/4tvwsItqu5qkoAhEdq0wSAYZwHTIOa5C7oFiCT0jRzSsdnbk2SGUuoUSV3wdtVUarOhQhZUpWyldq1ylKPk5eyoXJV6oYbm1i9EEpNPEw8dhNrsKCSZo9aD0Qo03zgcveKCMUQMm5rMkZZDFIVvOxSzYYmEScHWBCueuVEoQgTyMlbgBjqz/hagsqbcqg2gUHxEnwC4Hf+hu/pJ51jn7SIftw46lHtyEdVfn9YMeJh6cMPS4Q/KBL2wPXgA+cD9/v8fkRw/3EDU86927uDDnWYdWD/Z0Wot6xTtXjhg628TrXXXeihi++ri+ulu/iO7sqH+pNjai0Z2MZ/SKetM5pELKv941Kfym1HutUZUrRy35qNe5z58a3/Tr2acsH1aWShTeM9CrlIZ5qA8VTUOBuR/9YEHqacAJj6ta8RumkLe6y6fv5vtltyIAF4u+krl8/VevpnxZOb68w9+HPQk5Tg/9Lqzgh1rdzEuUJdA687v/K6sPCKTB2Gg4e3dT8ELCcADdeta7p+/fA9e8DQA91DQ3UrVvAJwCvLlr2/Y0d4YuKFO3f8wsJqBAW9GRLyEiYAKqcOJ6SpKnNApLwsN0TNLU8AoBVz/HwmAMAy9Aliq5qgWnmVvwWoVZt28Ehf+BYgqUIpFGMxiqnABKhJ7iIPJwB+fn459CFgTgrraHZNEmcosTQ2IHehcpKKzoWWxlVjlbKVcdOm4rUltFNJ0UKKYJsSNyMkACY7VW7QxJowRtXuxhKCjK2NPZl64HKMMsDYEGSyLRdlIkYYjmLMyjhSfkwAND8ELICdqFlQWzUoXoJPAEaeu9f9zyet/3jsc+Lx68cfVf39oXfEw3JHHpY89KBY2INCYYL7dzhwv/mR6JS4QSlxA1LO9e3dwRt1mHVg/zOhQn6VwcKQUEzWKVKw4Kp65U+20J3tpLvUS8gBLvfTJX6gvzJSf2Vc5cTxlS+P0oV1fNWvi0+lRh8UrzWwhFf30UPrPt5X/GmU68PDxf/ZUnrYm0UcnORv7gPkU1HjbET+WxN4mCwBmNxoPv+dP6uGfsvfCzS80tSPavnHHY2H+OxOAOwdnWZOqXLlD7e/9hZZvOuLKWeSlj9MXfvkuc/8rQ4lvFCwFvIeQOUvTvUFC1YfOnT40iXfrVvLLV3qNHcuuHnAfdEin+DgTdHRd5OTb9y581lYWN01a8ouXTrxt98gK6gZFATpwaAdOw5dvDhpxw6vOXMK2DkZUW0lPyHfr29AcTigir+J3wTCQRQuQ8PRlPs0NGflwi/acq1Mwkw/W5Zf+4e/sImDYWEZ3gUEYUziGIwDgwXxDQrnuvUa1qxdFxZs9yFgHmnnmAU1yV3k4QQgB78G1CiFdTS7ZpDgCbVNIec1JRn9o8pJ8p0rK7luTFSYjNeURr1WE9y78M9EvxbtNK1tYEmbksS1MFkhbQB9OFcxBJNtuSgTMYoNCYIm/HZIqtnQJOLkAAvCVa+cKBRhAjmfADQcbEwANL8GVAA7UdOoW/ElDDlYAZcAfDXo9D/tY540Pfm4/vFHNY890h19WP7IQ8/DD93DH7iFPSh48IHjgfv2+++/deSk6P77pZzt3atDJdRh1oH9z4QK+VUGC0NCMVZhQmXPIz66P1rp4jrrLvXWXfbVXeonvBUQ1qHqFp8aS2vWbVq5vWeVviUrv1NK38vLu83vwRWTd3om7y51+5tXzkyr0KhcYekoSKecfCpqnI3If2sCD5MlADITXp+7Lzgi5Vnq3ev3+O8FAibVnxfz65nxdWbLJYDVE4DixV22byiWdOQHhVAAABIASURBVMjuYEjd98NiPrpwb/7dZ18+Sp0QdcWz9bACTm58sF3h0mXbDKn+4ec1xwdV/2jdqyNXl+wy1alcbeu+AzBs5szV330XfvLkgfPn39u+3ePzz9nvfDUJDv4uNjbi9Onw48cPRUX9Hhe3Pjq6wbp1NYKC6q1dq1+x4tMDByIuXdp37Bg8Aw2aMePlSQBUwAmJSixCuAyFBXVzViL8tTABAK8vm345E4D+wf2zZUsA9w9N2F9+DBUq6cSvAS0Mq5AG2OhrQIWf72WtQrdsFQcmwArBW/b1fVcuhJ0m/9QX10TqB/bP/fv32Q/9coVSE+VWpHhUwgpRJ9xIMv7ZYOsnAHZm934Be8dMIfkILeXkD4HJUlhHs2uchJ4UVYbfARAr5G3wdlLpOEFCqKEAB8qdK1vJYabi+XJZJgvFno2/YCAUicvygjEKydxu4tbw3uA+Ai2JH5u4McOacQyC+DC2hYXKvSlsiduQibbc0EzFCEvGTYkPQIrj+nmZpZwu2LTIlxgRpwdBbFkslKZRjMH0i+GCcABgdNLWoHQtYwIAsC8G1cTVQ/yZMFV55gAXKy/ICCXGBODGl/3+vPt29OOGUY9qRT7acWrz7rjvd579dvuZDT+eDt5yap2T6P4L7L//ZnjUv6d9U870fna6W6/2FZR9WgHpGAhHRFHIrzJYGBKKsQo1ihbaU7fS700qx7bRxXURc4B+uoQB+l1daw6q3/RV7w6lK3QqVb5D2QqdO7zefM2AOv9s9r4ZVPGvz72SZnqvaFWtZgkxARBOJMUpqgny3yqELwOFh8knAHPbrzh35NKtv2+tWr3m/PkL6u8FmlB37odcSgBYPQGoUKFg+Ban61vtBg16s/mPf37w5z9Trz9dfD915YPUQbuiPFt84OChE9IAF3enV14r22XCwN2np1x9Nib+Wd+oBz67/irfb5F9kdKoTyMvZMEbNX2r9ccTxn3//b7o6F2xsV+Jv/MFbIqOBve/8Kefen79dd/16zeEhx87e3ZjdDSrXX3ixIHTp389cWL4+vVvDxzYsIkPshBmwWN4OREuQ9F6gps089cQj/YhYCi0cwTX3lz8lh5hQXy9H9oy9y9c7aLE+Axg7h8Fd+nao0y5V2BB+CGwDqZ+CEyAtbVcqLkS7mnF3hn8/cRJk2GhWo3aN2/e7NvvXZgrok6cEEy5ctLw8Cxz+vQZiIfIa9eSwKMDQhPf/lB16VL82bPnWDnXpLTYpD8gbsVJbgILqk5KqzsB98+nB6aRjp2YAEjLAqq4DJD2H6ccSwBAY8eODQkJuXPnDvS8Z88eMzkAVEEAhEEwNIGGUoVpKVyiQZwpBJlbU0p0irK4ML4CFSs3bggUS42toI1xu8pWwhpXoY7nAmRBpaoMJHYAXRs7kqOEInmjQnPVblPumAzWZGmMwtQDUY5BXONao1VBhm6ENibbckMzGWPsCsS+KJTFKWJeXimnC8X8aAZxooAFFq+Cf9UfVcmwWisy4oAiB+j/jfDJYD4AkoRWM6TfCuDLXwRwsfKCjFBiSACEb/3vGXO3yYnHr0UKN//cjp3yPNFP+M2vBPE3vy6NdThw305MAN7YH/kwuuez0z2enercq/0ryj6tABwLpvUbvvGfPad7zz7sN79QGMDCkFCMVbB3cJ6u8wx7XR/5pl7IAToL9wJd9tXFD9DHvvvqynavv9fA54NGb3zZpf6pEVVuf+Z1b7HX1Yn6K2P1m3vUWdCwcilX6ISdSIrTUhPkv1VICUDk9j9GV/0UrPzaMd/dv/Xw3r17n0ye+oZP0wHvD/r77781vxeIx+oJwKs6x+M/2l9eb/dK2Qqv+m3tGP7X0HMP/G4++yL5+bK7/40Ni6s79etSvWZVeG9+ywU7JkQmTb6WMjLxee+Yp/X23PaYsqdQ7U6oQwXqBIAv4ZGb2Ds5uhX16NqtyaJFs3/8cdvJkwcSEtiHgH86e3blr7++HRTkPGeO27x5fUNC1u3f/4vhl8L2x8d/d/TojB9+qD9nTtEmPvbOLshCmEUxgJcTMGwAKjQN2oEMuVyw+ywSFtjd/3DeskxAuNpFsYAMMbwDgMuBqtVrmrn/R83Bg2Fs00ywigLMwj2tcPD+Pjr6D1gVy40NoSr80CFYgNyJvagPgDuXDbrs6dkqALY+PFxoIiOnBLA/tTupLnZSXegE/oojMZ2ZG5GOXVYTAKDu6w3Y2z0h6zewPSvtZi0pNmYBko8woSZNmixevDg0NPTx48fQeUxMjOa9QFDIXvuHMAiGJtBQqiPleylzjGxVDm4qb4ifKAxTJ1+ijThVZCCDRc4p2E8CqwHHz0w/D2qbaUQDKi3ICCViAiD+5tf15Z3+uFPv+KPqvz/yPvrwauT4lMvg/sXf/Lo0LvXiKPbyf4F99xv+9vvtY53B/T/7s32v9uWUfVoB6XhoyfBLwHNy8peAGW6Ozmv0r4S9XvmYjz6mle5cJ93FHrr4d3SX++sTBugTB+oTh+ivjtD/9bHu1lTvq6P0CUP18e/pDnf07lWxmLTzLTtXkf/W5NtNm//555/kWw/2Bx99eO/RpUvxw4aPkGv79X/vzJmz6nuBeLIlAQi12/GpXREHZ7fXulZZ+FuHsL+HnH/0yY1ns++mLvwnddHtZwuS/p179enMaymTbqQNS3ze88+njX657TFrf6E3B1v3+38YToXcGrfv0G369DoLF1ZfuZL9ChhQ66uvdEuXFvnsswIBAXazZ3ssWFB52bJaQUFSwKpVVQMD6y5c2PWTT6rWa2DnVBBZCLPgMRAZgXYgQy5XJABsQbjGDQtMbDUrtGrTzszL/5ocDJNygEy6f5PI9h38/dmz5+7fvw+dw6UtZgJCAHh09rYJ79f5ZECdAIhNpP3GkGOUnRiTASkBEDuBcuVIzGQC0rGzQgKgCSR/kBVADgdj2r5jh5yBKTZmAZKPMK3WrVsvX74cbD17HyAtLe3EiROBgYHTRMECrLLvVoMACINgaCI1JuV/5eBL8cL7F8b3CUgg5bRgqalSwlopkfxxzmL5b4GhhpkGLKy8ICOUfPlZv9RrgewXf1ufvM1u/X/lyMOEiDFPzk+UfvPrkvCbX8z9iwnA0WsH2/wb2z45skW7ZqWVfVoBcV5/caHerISwr6oXKvy1V4UDtfURjSufbK471U53rouYBvTRxfvqLr8rfjJ4kD7hfR1Y//O9dFt8yjf3dLN3ED/+CwhnGjoVNUD+W5PGTd4cNHjonp9+fvLkybqvgzt06oICOnbqGhYebuo3wgCrJwDlSjvuXWv//VT7wvaOdk6FXKq18poW2nzf9V6nHg6N/3dsUsrHfz0ff+P56KS0wVee94171jryUZ3dtz2n73Fp0KeAawnUm1WwdyxYsZKuarv2rhMnsZ8As5zC4z+u2ryFZ6myyD9kBB4DkRFoBzLkcj4y1wE5gLXcPyDfbAOe3nDrv7HQcNtPbVhWeneTCQBaZcgdKjsxmQDIt/4bGsrHSJvsSgBMw23MAiQfYVZg6BcvXhwSEhIREfH06VP2vMILCqEKAiCM3P/LI8GQi3fmSOvZIGkTksj9YymvfUtNlRLWSgmzaDmPhTkAapVpJAurNrVubm6ensU9SwrU/DWRfe9nmcMPS5Qo6lGymKdnMc+SRRlyAuC4/KcSxQt7lihcskQh54KoTysQExsrzbMvJNSblRD2lZ2DcyPXIpsrVvytpv5IQ31k08rRLYU04Gwn3fluwpeEXuwlENddF9POe2PtSjpX7se/AOFMQ6eiBsh/m+HNZm/3ecf3DZ+mqJzRpWv3uLjzmvcCLey5+maC8PIWaqIJGp4pQGv97c+E2Hm6wPMs5DwuzhXrVRwV9Pqm062O3+8S+7j7qSc9Tv/bOfZpy8gnDfbfq7Quruyobws16F2gYFG+H+sCOYBduQp2vfu4f/JJyVmzHFVGH+EUEABh4P4LdOtuJ7zyqjAPFoAHQGQE2oEMuZyPzLewO/g1Pb28DAtygNK7m0wAwL7LYQDairITkwkANxK2LB8jbfJDAgBq0qTJ2LFjg4KCgoODd+/eHR4eHikKFmAVCqEKAujOHxIpJ6W89i01VUpYKw7ZouUAaNNA7T748wA8Pb8UbhZCnWQaycKqTW3m4XvIRpq3bDN+wqT1G77JbD6A+rEe0h7wdHCe7FkqVF9pX23doQaVj72pj3pbB5lATGuB6Fa6zQ2rfKSr7OPGvvdG3m/scPPnoTbIf2cF/l6gEfrp05t9/s3kbZdjrj18+BDKN2z8BsVrgoZnhlp6x63+dl+NsW/TwKGTj0Orho7Fy5Z1q9/Ts4+/bvaOKsvDqgXHei85XG7mzlK+C4o07udYpgbqIVtwKexUvmLjHj3bTZlSfNo0x5kzweUj328H1t/f337GjJLTprWdOLFq8xaC+8/c3f8M1daJDEA7kCGX85H5E8Ot/8Yv2FEnAIYY4T0BFMD7eD4BQN1qbcVo7hWdUAIgq1mzZoMHD541a1ZgYCB7SRYWYBUKM/zOHxKJZHUpr31LTZUS1opDtmiSS9OCj8kOStcSfhyAp0pb4SuAUNgLIvtXDUebSfgecg4L84HExCuoofUw7gQneJos6Nq3qPtnZcus8Sq/s6rX99UqBOrL+FX0HFKmuE/RwiWFG8dVZ46wik5FDZD/ziIdO3UJCxPuBYr57dzf8bcvnL/4dXDIhyNGNW/RGkWaAg3PPO6FHZtUd2xRy6FRNcfyJRyF25/snexc3B1K6pzL1XQqXxtMv6Onzs6tlLBLVc2tAX7GB+wdnStW8q7asHERnzdrDh7S2M/PTZkAFAsIaDxjRsV3+ro1blK1XoPM3/kjgwZDZAjagQy5nI/Mn/AmmwHmm/9uH7D7sMw+/suAVQiAMDlSbih7d6EJ9/Ff9VYs6USuYl8QBJ1wx0ibfJUAkEikXCXltW+pqVLCWnHIFk1yaVrwMXkP2b9qO9rMwPdgM9T5ACxDIQqzKmg/ODvYO7vYOxdycC7i6Ozm6OTq4FzQ3smBnWAsBp05wip/HmqD/HfWadO2fUTE0fj4y5/O9Gvdpr2pW4ZMgYaX68HP+AzIAeycChZ0K9qhS9f3Zs4spUwAygcEDJg2rUHjJnBIM/mpXwQaDJEhaAcy5Co5LN8SumUrm8GY2Cvx4LmfPHkCq8y1QyGkAXITALw4ixdNuVTIe3exibFKcysZdgKgkSgPkwaUAJBIpOyS6vK3HIMhsy2yHcxRNPzri6J2w6wkP8E/OhWax1E+vpq1gFCOTkgeYwDy3zaHG2SeAD/j5yxoMESGoB2IQMEvI+DFDd8KiqtM8QJNLAYdIAwlACQSKbukuvwzBbNZNgX5whwiI1ObCdQWmZXkJ/hHp0TzOMqFMnwtQyhHZyOPMQD5b5vDDTJPgJ/xcxY0GCJD0A5EoGDC5qADhKEEgEQiZZdUl3+mYDYr14ANoqrQapg1tdaBN9B5BfQQLEB9mOQSHrlWRihHZyOPMQD5byvQwAJQEw5ukHkC/Iyfs6DBEBmCdiACBRM2Bx0gDCUAJBIpu6S6/DMFs1m5CYVBVJZYkxcyu5mDN9Z5BfQQLIA/TPKyGr4JQyhHZyOPMQD576yCjL4pUCsObpB5AvyMn7OgwRAZgnYgAgUTNgcdIAwlACQSKbukuvwzBbNZuQmFQVSWWJMXMrvWgTfcuQ00VAvgD5O8rIZvwhDK0dnIYwxA/jurIKNvCtSKgxtkngA/4+csaDBEhqAdiEDBhM1BBwhDCQCJRMouqS7/TMFsVq4BG0RVodV4IbNrHXjDndtAQ7UA9WGSS3jkWhmhHJ2NPMYA5L+zCjL6pkCtOLhB5gnwM37OggZDZAjagQgUTNgcdIAw2ZYA2JmA35gFSD6CRCLlQeFpIXMwm5W9TP71rk3AjpMDRVqXdh8teX/lAU3QMFT+2+YohoceV47BnZnCWYpqbY7h2pFAtdbF3LmkHAYP6iTHQNZCBI/NQuwMSCUKh5PHUDwQGZOPCO1ABArOHxifLDICNcwu5NPPeOD448WDDxCGEgASiZRdwtNC5kDTa7aAXEKOgewsD4q0LpQAZBHuzBTOUlRrcwzXjgSqtS6UAEglCoeTl8APREbrEYlhaAcijMH5BeMzhQWgttmFfNSMB44/Xjz4AGEUCYC94/8BZ2BtcbW+s48AAAAASUVORK5CYII=" width="320" /><br /> using System;<br /> using System.Collections.Generic;<br /> using System.Drawing;<br /> using System.Windows.Forms;<br /> using Emgu.CV;<br /> using Emgu.CV.Structure;<br /> using Emgu.CV.CvEnum;<br /> using System.IO;<br /> using System.Diagnostics;<br /> using System.Media;<br /> using System.Net.Sockets;<br /> using DirectShowLib;<br /> using System.IO.Ports;<br /> <br /> <br /> namespace MultiFaceRec<br /> {<br /> public partial class FrmPrincipal : Form<br /> {<br /> //Declararation of all variables, vectors and haarcascades<br /> Image<Bgr, Byte> currentFrame;<br /> Capture grabber;<br /> HaarCascade face;<br /> HaarCascade eye;<br /> MCvFont font = new MCvFont(FONT.CV_FONT_HERSHEY_TRIPLEX, 0.5d, 0.5d);<br /> Image<Gray, byte> result, TrainedFace = null;<br /> Image<Gray, byte> gray = null;<br /> List<Image<Gray, byte>> trainingImages = new List<Image<Gray, byte>>();<br /> List<string> labels= new List<string>();<br /> List<string> NamePersons = new List<string>();<br /> int ContTrain, NumLabels, t;<br /> string name, names = null;<br /> bool CapturingProcess = false; <br /> TcpClient _tcpClient = null;<br /> bool CapRunning = false;<br /> private int _CameraIndex;<br /> bool CamAuto = false;<br /> bool ConnectAuto = false;<br /> string revision = "3.7.14";<br /> <br /> <br /> <br /> public FrmPrincipal()<br /> {<br /> InitializeComponent();<br /> //Load haarcascades for face detection<br /> face = new HaarCascade("haarcascade_frontalface_default.xml");<br /> //eye = new HaarCascade("haarcascade_eye.xml");<br /> try<br /> {<br /> //Load of previus trainned faces and labels for each image<br /> string Labelsinfo = File.ReadAllText(Application.StartupPath + "/TrainedFaces/TrainedLabels.txt");<br /> string[] Labels = Labelsinfo.Split('%');<br /> NumLabels = Convert.ToInt16(Labels[0]);<br /> ContTrain = NumLabels;<br /> string LoadFaces;<br /> <br /> for (int tf = 1; tf < NumLabels+1; tf++)<br /> {<br /> LoadFaces = "face" + tf + ".bmp";<br /> trainingImages.Add(new Image<Gray, byte>(Application.StartupPath + "/TrainedFaces/" + LoadFaces));<br /> labels.Add(Labels[tf]);<br /> }<br /> }<br /> catch(Exception e)<br /> {<br /> //MessageBox.Show(e.ToString());<br /> MessageBox.Show("No faces have been trained. Please add at least a face (train with the Add face Button).", "EZ-Face Notice", MessageBoxButtons.OK, MessageBoxIcon.Exclamation);<br /> }<br /> }<br /> <br /> <br /> <br /> private void button1_Click(object sender, EventArgs e)<br /> {<br /> //Set the camera number to the one selected via combo box<br /> //This method is no longer used, DirectShow to display device name is now used<br /> //int CamNumber = -1;<br /> //CamNumber = int.Parse(cbCamIndex.Text);<br /> <br /> //This is for reading faces from a video file, for testing only at this time<br /> //String sFileName = @"c:\test.mp4"; //this work with new opencv_ffmpeg290.dll in the bin folder<br /> //grabber = new Capture(sFileName); //this works, but crashes the app once movie stops<br /> <br /> //Initialize the capture device<br /> grabber = new Capture(_CameraIndex);<br /> grabber.QueryFrame();<br /> //Initialize the FrameGraber event<br /> Application.Idle += new EventHandler(FrameGrabber);<br /> button1.Enabled = false;<br /> CapturingProcess = true;<br /> btn_stop_capture.Enabled = true;<br /> groupBox1.Enabled = true;<br /> CapRunning = true;<br /> }<br /> <br /> <br /> private void button2_Click(object sender, System.EventArgs e)<br /> {<br /> try<br /> {<br /> //Trained face counter<br /> ContTrain = ContTrain + 1;<br /> <br /> //Get a gray frame from capture device<br /> gray = grabber.QueryGrayFrame().Resize(320, 240, Emgu.CV.CvEnum.INTER.CV_INTER_CUBIC);<br /> <br /> //Face Detector<br /> MCvAvgComp[][] facesDetected = gray.DetectHaarCascade(<br /> face,<br /> 1.2,<br /> 10,<br /> Emgu.CV.CvEnum.HAAR_DETECTION_TYPE.DO_CANNY_PRUNING,<br /> new Size(20, 20));<br /> <br /> //Action for each element detected<br /> foreach (MCvAvgComp f in facesDetected[0])<br /> {<br /> TrainedFace = currentFrame.Copy(f.rect).Convert<Gray, byte>();<br /> break;<br /> }<br /> <br /> //resize face detected image for force to compare the same size with the <br /> //test image with cubic interpolation type method<br /> TrainedFace = result.Resize(100, 100, Emgu.CV.CvEnum.INTER.CV_INTER_CUBIC);<br /> trainingImages.Add(TrainedFace);<br /> labels.Add(textBox1.Text);<br /> <br /> //Show face added in gray scale<br /> imageBox1.Image = TrainedFace;<br /> <br /> //Write the number of triained faces in a file text for further load<br /> File.WriteAllText(Application.StartupPath + "/TrainedFaces/TrainedLabels.txt", trainingImages.ToArray().Length.ToString() + "%");<br /> <br /> //Write the labels of triained faces in a file text for further load<br /> for (int i = 1; i < trainingImages.ToArray().Length + 1; i++)<br /> {<br /> trainingImages.ToArray()[i - 1].Save(Application.StartupPath + "/TrainedFaces/face" + i + ".bmp");<br /> File.AppendAllText(Application.StartupPath + "/TrainedFaces/TrainedLabels.txt", labels.ToArray()[i - 1] + "%");<br /> }<br /> <br /> MessageBox.Show(textBox1.Text + "´s face detected and added.", "Training OK", MessageBoxButtons.OK, MessageBoxIcon.Information);<br /> }<br /> catch<br /> {<br /> MessageBox.Show("Enable the face detection first.", "Training Fail", MessageBoxButtons.OK, MessageBoxIcon.Exclamation);<br /> }<br /> }<br /> <br /> <br /> void FrameGrabber(object sender, EventArgs e)<br /> {<br /> label3.Text = "0";<br /> //label4.Text = "";<br /> NamePersons.Add("");<br /> <br /> //This is where the app most often encounters critical errors<br /> //Get the current frame form capture device<br /> currentFrame = grabber.QueryFrame().Resize(320, 240, Emgu.CV.CvEnum.INTER.CV_INTER_CUBIC);<br /> <br /> //Convert it to Grayscale<br /> gray = currentFrame.Convert<Gray, Byte>();<br /> <br /> //Face Detector<br /> MCvAvgComp[][] facesDetected = gray.DetectHaarCascade(<br /> face,<br /> 1.2,<br /> 10,<br /> Emgu.CV.CvEnum.HAAR_DETECTION_TYPE.DO_CANNY_PRUNING,<br /> new Size(20, 20));<br /> <br /> //Action for each element detected<br /> foreach (MCvAvgComp f in facesDetected[0])<br /> {<br /> t = t + 1;<br /> result = currentFrame.Copy(f.rect).Convert<Gray, byte>().Resize(100, 100, Emgu.CV.CvEnum.INTER.CV_INTER_CUBIC);<br /> //draw the face detected in the 0th (gray) channel with blue color<br /> currentFrame.Draw(f.rect, new Bgr(Color.Red), 2);<br /> <br /> <br /> if (trainingImages.ToArray().Length != 0)<br /> {<br /> //TermCriteria for face recognition with numbers of trained images like maxIteration<br /> MCvTermCriteria termCrit = new MCvTermCriteria(ContTrain, 0.001);<br /> <br /> //Eigen face recognizer<br /> EigenObjectRecognizer recognizer = new EigenObjectRecognizer(<br /> trainingImages.ToArray(),<br /> labels.ToArray(),<br /> 3000,<br /> ref termCrit);<br /> <br /> name = recognizer.Recognize(result);<br /> <br /> //Draw the label for each face detected and recognized<br /> currentFrame.Draw(name, ref font, new Point(f.rect.X - 2, f.rect.Y - 2), new Bgr(Color.LightGreen));<br /> <br /> }<br /> <br /> NamePersons[t-1] = name;<br /> NamePersons.Add("");<br /> <br /> <br /> //Set the number of faces detected on the scene<br /> label3.Text = facesDetected[0].Length.ToString();<br /> <br /> /*<br /> //Set the region of interest on the faces<br /> <br /> gray.ROI = f.rect;<br /> MCvAvgComp[][] eyesDetected = gray.DetectHaarCascade(<br /> eye,<br /> 1.1,<br /> 10,<br /> Emgu.CV.CvEnum.HAAR_DETECTION_TYPE.DO_CANNY_PRUNING,<br /> new Size(20, 20));<br /> gray.ROI = Rectangle.Empty;<br /> <br /> foreach (MCvAvgComp ey in eyesDetected[0])<br /> {<br /> Rectangle eyeRect = ey.rect;<br /> eyeRect.Offset(f.rect.X, f.rect.Y);<br /> currentFrame.Draw(eyeRect, new Bgr(Color.Blue), 2);<br /> }<br /> */<br /> <br /> }<br /> t = 0;<br /> <br /> //Names concatenation of persons recognized<br /> for (int nnn = 0; nnn < facesDetected[0].Length; nnn++)<br /> {<br /> names = names + NamePersons[nnn] + ", ";<br /> }<br /> //Show the faces procesed and recognized<br /> imageBoxFrameGrabber.Image = currentFrame;<br /> label4.Text = names;<br /> //This logs the faces recognized<br /> if (String.IsNullOrEmpty(names))<br /> {<br /> textBox2.Text = "off";<br /> string m = comboBox1.Text.ToString();<br /> string s = textBox2.Text.ToString();<br /> sErial(m, s);<br /> }<br /> else<br /> {<br /> File.AppendAllText(Application.StartupPath + "/RecognitionLog/facelog.txt",<br /> names + DateTime.Now.ToString() + Environment.NewLine);<br /> textBox2.Text = "on";<br /> string m = comboBox1.Text.ToString();<br /> string s = textBox2.Text.ToString();<br /> sErial(m, s);<br /> }<br /> <br /> //<br /> //This sends the name automatically - this needs to be enabled or disabled<br /> //<br /> tbX.Text = "\"" + names + "\"";<br /> btnSetX.PerformClick(); //sends the informations to EZ-Builder<br /> //btngetX.PerformClick(); //gets the information from EZ-Builder - this works by only until recognition stops<br /> //This clears the name value for the next face to be recognized<br /> names = "";<br /> //Clear the list(vector) of names<br /> NamePersons.Clear();<br /> <br /> }<br /> <br /> private void FrmPrincipal_Load(object sender, EventArgs e)<br /> {<br /> this.Text = "EZ-Face " + revision;<br /> //cbCamIndex.Items.AddRange(Camera.GetVideoCaptureDevices());<br /> tbLog.Visible = false;<br /> groupBox1.Enabled = false;<br /> loadUserSettingsToolStripMenuItem.PerformClick();<br /> timer1.Start();<br /> timer2.Start();<br /> if (File.Exists(Application.StartupPath + "/RecognitionLog/facelog.txt"))<br /> {<br /> var fileName = (Application.StartupPath + "/RecognitionLog/facelog.txt");<br /> FileInfo fi = new FileInfo(fileName);<br /> var size = fi.Length;<br /> lb_facename_file.Text = "Face Log File size: " + size;<br /> }<br /> if (CamAuto == true)<br /> {<br /> lb_autorun.Text = "Enabled";<br /> button1.PerformClick();<br /> }<br /> else<br /> {<br /> lb_autorun.Text = "Disabled";<br /> }<br /> if (ConnectAuto == true)<br /> {<br /> lb_autoconnect.Text = "Enabled";<br /> btnConnect.PerformClick();<br /> }<br /> else<br /> {<br /> lb_autoconnect.Text = "Disabled";<br /> }<br /> <br /> <br /> <br /> }<br /> <br /> private void Log(object txt, params object[] vals)<br /> {<br /> tbLog.AppendText(string.Format(txt.ToString(), vals));<br /> tbLog.AppendText(Environment.NewLine);<br /> }<br /> <br /> private void btnConnect_Click(object sender, EventArgs e)<br /> {<br /> tbLog.Visible = true;<br /> try<br /> {<br /> if (_tcpClient != null)<br /> disconnect();<br /> else<br /> connect();<br /> }<br /> catch (Exception ex)<br /> {<br /> Log("Error performing connection action: {0}", ex);<br /> }<br /> }<br /> <br /> private void disconnect()<br /> {<br /> if (_tcpClient != null)<br /> _tcpClient.Close();<br /> _tcpClient = null;<br /> btnConnect.Text = "Connect";<br /> Log("Disconnected");<br /> tbLog.Visible = false;<br /> }<br /> <br /> private void connect()<br /> {<br /> int port = Convert.ToInt32(tbPort.Text);<br /> Log("Attempting Connection to {0}:{1}", tbAddress.Text, port);<br /> _tcpClient = new TcpClient();<br /> IAsyncResult ar = _tcpClient.BeginConnect(tbAddress.Text, port, null, null);<br /> System.Threading.WaitHandle wh = ar.AsyncWaitHandle;<br /> <br /> try<br /> {<br /> if (!ar.AsyncWaitHandle.WaitOne(TimeSpan.FromSeconds(3), false))<br /> {<br /> _tcpClient.Close();<br /> throw new TimeoutException();<br /> }<br /> <br /> _tcpClient.EndConnect(ar);<br /> }<br /> finally<br /> {<br /> wh.Close();<br /> }<br /> <br /> _tcpClient.NoDelay = true;<br /> _tcpClient.ReceiveTimeout = 2000;<br /> _tcpClient.SendTimeout = 2000;<br /> btnConnect.Text = "Disconnect";<br /> Log("Connected");<br /> Log(readResponseLine());<br /> }<br /> <br /> private string sendCommand(string cmd)<br /> {<br /> try<br /> {<br /> Log("Sending: {0}", cmd);<br /> clearInputBuffer();<br /> _tcpClient.Client.Send(System.Text.Encoding.ASCII.GetBytes(cmd + Environment.NewLine));<br /> return readResponseLine(); //original exampled used this: Log(readResponseLine());<br /> }<br /> catch (Exception ex)<br /> {<br /> Log("Command Error: {0}", ex);<br /> disconnect();<br /> }<br /> return string.Empty;<br /> }<br /> <br /> /// <summary><br /> /// Clears any data in the tcp incoming buffer by reading the buffer into an empty byte array.<br /> /// </summary><br /> private void clearInputBuffer()<br /> {<br /> if (_tcpClient.Available > 0)<br /> _tcpClient.GetStream().Read(new byte[_tcpClient.Available], 0, _tcpClient.Available);<br /> }<br /> <br /> /// <summary><br /> /// Blocks and waits for a string of data to be sent. The string is terminated with a \r\n<br /> /// </summary><br /> private string readResponseLine()<br /> {<br /> string str = string.Empty;<br /> do<br /> {<br /> <br /> byte[] tmpBuffer = new byte[1024];<br /> _tcpClient.GetStream().Read(tmpBuffer, 0, tmpBuffer.Length);<br /> str += System.Text.Encoding.ASCII.GetString(tmpBuffer);<br /> } while (!str.Contains(Environment.NewLine));<br /> <br /> // Return only the first line if multiple lines were received<br /> return str.Substring(0, str.IndexOf(Environment.NewLine));<br /> }<br /> <br /> <br /> private void btnSetX_Click(object sender, EventArgs e)<br /> {<br /> sendCommand(string.Format("$FaceName = {0}", tbX.Text));<br /> <br /> <br /> }<br /> void sErial(string Port_name, string data_Send)<br /> {<br /> SerialPort sp = new SerialPort(Port_name, 9600, Parity.None, 8, StopBits.One);<br /> sp.Open();<br /> <br /> sp.Write(data_Send);<br /> sp.Close();<br /> }<br /> private void btn_stop_capture_Click(object sender, EventArgs e)<br /> {<br /> {<br /> if (CapturingProcess == true)<br /> {<br /> Application.Idle -= FrameGrabber;<br /> grabber.Dispose();<br /> //Application.Exit(); //this closes the application<br /> //CapturingProcess = false;<br /> //playorpause.Text = "Play";<br /> }<br /> else<br /> {<br /> Application.Idle += FrameGrabber;<br /> //CapturingProcess = true;<br /> //playorpause.Text = "Pause";<br /> }<br /> } <br /> button1.Enabled = true;<br /> btn_stop_capture.Enabled = false;<br /> groupBox1.Enabled = false;<br /> imageBoxFrameGrabber.Image = null; //sets the image to blank<br /> imageBox1.Image = null; //sets image to blank<br /> }<br /> <br /> <br /> <br /> private void deleteLearnedFacesToolStripMenuItem_Click(object sender, EventArgs e)<br /> {<br /> DialogResult d = MessageBox.Show("Are you sure you want to delete all learned faces?", "Question", MessageBoxButtons.YesNo, MessageBoxIcon.Question);<br /> <br /> if (d == DialogResult.Yes)<br /> {<br /> <br /> if (CapRunning = true)<br /> {<br /> btn_stop_capture.PerformClick();<br /> }<br /> Array.ForEach(Directory.GetFiles(Application.StartupPath + "/TrainedFaces"), File.Delete);<br /> button1.Enabled = false;<br /> DialogResult b = MessageBox.Show("You must close EZ-Face and re-open it for changes to take effect.", "EZ-Face Notice", MessageBoxButtons.OK, MessageBoxIcon.Asterisk);<br /> if (b == DialogResult.OK)<br /> {<br /> Application.Exit();<br /> }<br /> }<br /> else if (d == DialogResult.No)<br /> {<br /> //Do nothing<br /> }<br /> }<br /> <br /> private void aboutToolStripMenuItem1_Click(object sender, EventArgs e)<br /> {<br /> var aboutForm = new About();<br /> aboutForm.revision = revision;<br /> aboutForm.Show();<br /> }<br /> <br /> private void j2RScientificComToolStripMenuItem_Click(object sender, EventArgs e)<br /> {<br /> System.Diagnostics.Process.Start("http://www.J2RScientific.com");<br /> }<br /> <br /> private void instructionsToolStripMenuItem_Click(object sender, EventArgs e)<br /> {<br /> if (File.Exists(@"C:\BotBrain\EZ-Face\Resources\ReadMe.txt"))<br /> {<br /> System.Diagnostics.Process.Start(@"C:\BotBrain\EZ-Face\Resources\ReadMe.txt");<br /> }<br /> else<br /> {<br /> MessageBox.Show("I'm sorry. The ReadMe.txt file could not be found.", "EZ-Face Notice", MessageBoxButtons.OK, MessageBoxIcon.Asterisk);<br /> }<br /> <br /> }<br /> <br /> private void deleteLogOfDetectedFacesToolStripMenuItem_Click(object sender, EventArgs e)<br /> {<br /> DialogResult f = MessageBox.Show("Are you sure you want to delete facelog.txt file?", "Question", MessageBoxButtons.YesNo, MessageBoxIcon.Question);<br /> if (f == DialogResult.Yes)<br /> {<br /> if (File.Exists(Application.StartupPath + "/RecognitionLog/facelog.txt"))<br /> {<br /> File.Delete(Application.StartupPath + "/RecognitionLog/facelog.txt");<br /> }<br /> }<br /> <br /> }<br /> <br /> private void viewSavedFacesToolStripMenuItem_Click(object sender, EventArgs e)<br /> {<br /> Process.Start(Application.StartupPath + "/TrainedFaces");<br /> }<br /> <br /> private void viewLogOfDetectedFacesToolStripMenuItem_Click(object sender, EventArgs e)<br /> {<br /> if (File.Exists(Application.StartupPath + "/RecognitionLog/facelog.txt"))<br /> {<br /> System.Diagnostics.Process.Start(Application.StartupPath + "/RecognitionLog/facelog.txt");<br /> }<br /> else<br /> {<br /> MessageBox.Show("I'm sorry. The facelog.txt file could not be found.", "EZ-Face Notice", MessageBoxButtons.OK, MessageBoxIcon.Asterisk);<br /> }<br /> }<br /> <br /> private void saveSettingsToolStripMenuItem_Click(object sender, EventArgs e)<br /> {<br /> string httpAddress = tbAddress.Text;<br /> string portAddress = tbPort.Text;<br /> if (File.Exists(Application.StartupPath + "/Settings/user_settings.txt")) <br /> {<br /> File.Delete(Application.StartupPath + "/Settings/user_settings.txt");<br /> }<br /> File.AppendAllText(Application.StartupPath + "/Settings/user_settings.txt", httpAddress.ToString() + Environment.NewLine);<br /> File.AppendAllText(Application.StartupPath + "/Settings/user_settings.txt", portAddress.ToString() + Environment.NewLine);<br /> File.AppendAllText(Application.StartupPath + "/Settings/user_settings.txt", _CameraIndex.ToString() + Environment.NewLine);<br /> File.AppendAllText(Application.StartupPath + "/Settings/user_settings.txt", CamAuto.ToString() + Environment.NewLine);<br /> File.AppendAllText(Application.StartupPath + "/Settings/user_settings.txt", ConnectAuto.ToString() + Environment.NewLine);<br /> MessageBox.Show("Your user settings were saved.", "EZ-Face Notice", MessageBoxButtons.OK, MessageBoxIcon.Asterisk);<br /> }<br /> <br /> private void loadUserSettingsToolStripMenuItem_Click(object sender, EventArgs e)<br /> {<br /> if (File.Exists(Application.StartupPath + "/Settings/user_settings.txt"))<br /> {<br /> string[] lines = System.IO.File.ReadAllLines(Application.StartupPath + "/Settings/user_settings.txt");<br /> for (int i = 0; i < lines.Length; i++)<br /> {<br /> string line = lines[i];<br /> tbAddress.Text = lines[0];<br /> tbPort.Text = lines[1];<br /> // _CameraIndex = lines[2];<br /> //int _CameraIndex = Int32.Parse(lines[2]);<br /> _CameraIndex = Int32.Parse(lines[2]);<br /> CamAuto = bool.Parse(lines[3]);<br /> ConnectAuto = bool.Parse(lines[4]);<br /> }<br /> }<br /> else<br /> {<br /> MessageBox.Show("I'm sorry. The user_settings.txt file could not be found.", "EZ-Face Notice", MessageBoxButtons.OK, MessageBoxIcon.Asterisk);<br /> }<br /> }<br /> <br /> private void timer1_Tick(object sender, EventArgs e)<br /> {<br /> if (File.Exists(Application.StartupPath + "/RecognitionLog/facelog.txt"))<br /> {<br /> var fileName = (Application.StartupPath + "/RecognitionLog/facelog.txt");<br /> FileInfo fi = new FileInfo(fileName);<br /> var size = fi.Length;<br /> lb_facename_file.Text = "Face Log File size: " + size;<br /> <br /> if (size > 1000000) //if file is greater then 1mb it will be deleted<br /> {<br /> File.Delete(Application.StartupPath + "/RecognitionLog/facelog.txt");<br /> }<br /> }<br /> <br /> <br /> }<br /> <br /> private void cbCamIndex_SelectedIndexChanged(object sender, EventArgs e)<br /> {<br /> //-> Get the selected item in the combobox<br /> KeyValuePair<int, string> SelectedItem = (KeyValuePair<int, string>)cbCamIndex.SelectedItem;<br /> //-> Assign selected cam index to defined var<br /> _CameraIndex = SelectedItem.Key;<br /> }<br /> <br /> private void btn_refresh_camerlist_Click(object sender, EventArgs e)<br /> {<br /> //-> Create a List to store for ComboCameras<br /> List<KeyValuePair<int, string>> ListCamerasData = new List<KeyValuePair<int, string>>();<br /> //-> Find systems cameras with DirectShow.Net dll <br /> DsDevice[] _SystemCamereas = DsDevice.GetDevicesOfCat(FilterCategory.VideoInputDevice);<br /> int _DeviceIndex = 0;<br /> foreach (DirectShowLib.DsDevice _Camera in _SystemCamereas)<br /> {<br /> ListCamerasData.Add(new KeyValuePair<int, string>(_DeviceIndex, _Camera.Name));<br /> _DeviceIndex++;<br /> }<br /> //-> clear the combobox<br /> cbCamIndex.DataSource = null;<br /> cbCamIndex.Items.Clear();<br /> //-> bind the combobox<br /> cbCamIndex.DataSource = new BindingSource(ListCamerasData, null);<br /> cbCamIndex.DisplayMember = "Value";<br /> cbCamIndex.ValueMember = "Key";<br /> //DirectShowLib-2005 must be added as a reference in the bin folder<br /> }<br /> <br /> private void setCameraToAutoRunToolStripMenuItem_Click(object sender, EventArgs e)<br /> {<br /> CamAuto = true;<br /> lb_autorun.Text = "Enabled";<br /> MessageBox.Show("Remember, please make sure all user settings are set to the correct values - then use the File/Save User Settings feature.", "EZ-Face Notice", MessageBoxButtons.OK, MessageBoxIcon.Asterisk);<br /> }<br /> <br /> private void removeCameraAutoRunToolStripMenuItem_Click(object sender, EventArgs e)<br /> {<br /> CamAuto = false;<br /> lb_autorun.Text = "Disabled";<br /> MessageBox.Show("Remember, please make sure all user settings are set to the correct values - then use the File/Save User Settings feature.", "EZ-Face Notice", MessageBoxButtons.OK, MessageBoxIcon.Asterisk);<br /> }<br /> <br /> private void btngetX_Click(object sender, EventArgs e)<br /> {<br /> string retVal = sendCommand("print($EZfaceCMD)");<br /> tb_getX.Text = retVal;<br /> Log(retVal);<br /> if (retVal == "EZfaceSTOP")<br /> {<br /> if (button1.Enabled == false)<br /> { <br /> btn_stop_capture.PerformClick();<br /> }<br /> }<br /> if (retVal == "EZfaceSTART")<br /> { <br /> if (btn_stop_capture.Enabled == false)<br /> {<br /> button1.PerformClick();<br /> }<br /> }<br /> if (retVal == "EZfaceCLOSE")<br /> {<br /> Application.Exit();<br /> }<br /> }<br /> <br /> private void setAutoConnectToolStripMenuItem_Click(object sender, EventArgs e)<br /> {<br /> ConnectAuto = true;<br /> lb_autoconnect.Text = "Enabled";<br /> MessageBox.Show("This settings enables auto communication connection upon the application running. Remember, please make sure all user settings are set to the correct values - then use the File/Save User Settings feature.", "EZ-Face Notice", MessageBoxButtons.OK, MessageBoxIcon.Asterisk);<br /> }<br /> <br /> private void removeAutoConnectToolStripMenuItem_Click(object sender, EventArgs e)<br /> {<br /> ConnectAuto = false;<br /> lb_autoconnect.Text = "Disabled";<br /> MessageBox.Show("This settings disables auto communication connection upon the application running. Remember, please make sure all user settings are set to the correct values - then use the File/Save User Settings feature.", "EZ-Face Notice", MessageBoxButtons.OK, MessageBoxIcon.Asterisk);<br /> <br /> }<br /> <br /> private void timer2_Tick(object sender, EventArgs e)<br /> {<br /> btngetX.PerformClick();<br /> }<br /> <br /> private void tbPort_TextChanged(object sender, EventArgs e)<br /> {<br /> <br /> }<br /> <br /> private void tbX_TextChanged(object sender, EventArgs e)<br /> {<br /> <br /> }<br /> <br /> private void button3_Click(object sender, EventArgs e)<br /> {<br /> string[] ports = SerialPort.GetPortNames();<br /> foreach (string port in ports)<br /> {<br /> comboBox1.Items.Add(port);<br /> }<br /> }<br /> <br /> private void label3_Click(object sender, EventArgs e)<br /> {<br /> <br /> }<br /> <br /> }<br /> } control motor using face camera using System; using System.Collections.Generic; using System.Drawing; using System.Windows.Forms; using Emgu.CV; using Emgu.CV.Struct... 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