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block;\nwidth: 100%;\noverflow: auto;\nword-break: normal;\nword-break: keep-all;\n}\ntable th {\nfont-weight: bold;\n}\ntable th,\ntable td {\npadding: 6px 13px;\nborder: 1px solid #ddd;\n}\ntable tr {\nbackground-color: #fff;\nborder-top: 1px solid #ccc;\n}\ntable tr:nth-child(2n) {\nbackground-color: #f8f8f8;\n}\nimg {\nmax-width: 100%;\nbox-sizing: content-box;\nbackground-color: #fff;\n}\ncode {\npadding: 0;\npadding-top: 0.2em;\npadding-bottom: 0.2em;\nmargin: 0;\nfont-size: 85%;\nbackground-color: rgba(0,0,0,0.04);\nborder-radius: 3px;\n}\ncode:before,\ncode:after {\nletter-spacing: -0.2em;\ncontent: \"\\00a0\";\n}\npre\u003ecode {\npadding: 0;\nmargin: 0;\nfont-size: 100%;\nword-break: normal;\nwhite-space: pre;\nbackground: transparent;\nborder: 0;\n}\n.highlight {\nmargin-bottom: 16px;\n}\n.highlight pre,\npre {\npadding: 16px;\noverflow: auto;\nfont-size: 85%;\nline-height: 1.45;\nbackground-color: #f7f7f7;\nborder-radius: 3px;\n}\n.highlight pre {\nmargin-bottom: 0;\nword-break: normal;\n}\npre {\nword-wrap: normal;\n}\npre code {\ndisplay: inline;\nmax-width: initial;\npadding: 0;\nmargin: 0;\noverflow: initial;\nline-height: inherit;\nword-wrap: normal;\nbackground-color: transparent;\nborder: 0;\n}\npre code:before,\npre code:after {\ncontent: normal;\n}\nkbd {\ndisplay: inline-block;\npadding: 3px 5px;\nfont-size: 11px;\nline-height: 10px;\ncolor: #555;\nvertical-align: middle;\nbackground-color: #fcfcfc;\nborder: solid 1px #ccc;\nborder-bottom-color: #bbb;\nborder-radius: 3px;\nbox-shadow: inset 0 -1px 0 #bbb;\n}\n.pl-c {\ncolor: #969896;\n}\n.pl-c1,\n.pl-s .pl-v {\ncolor: #0086b3;\n}\n.pl-e,\n.pl-en {\ncolor: #795da3;\n}\n.pl-s .pl-s1,\n.pl-smi {\ncolor: #333;\n}\n.pl-ent {\ncolor: #63a35c;\n}\n.pl-k {\ncolor: #a71d5d;\n}\n.pl-pds,\n.pl-s,\n.pl-s .pl-pse .pl-s1,\n.pl-sr,\n.pl-sr .pl-cce,\n.pl-sr .pl-sra,\n.pl-sr .pl-sre {\ncolor: #183691;\n}\n.pl-v {\ncolor: #ed6a43;\n}\n.pl-id {\ncolor: #b52a1d;\n}\n.pl-ii {\nbackground-color: #b52a1d;\ncolor: #f8f8f8;\n}\n.pl-sr .pl-cce {\ncolor: #63a35c;\nfont-weight: bold;\n}\n.pl-ml {\ncolor: #693a17;\n}\n.pl-mh,\n.pl-mh .pl-en,\n.pl-ms {\ncolor: #1d3e81;\nfont-weight: bold;\n}\n.pl-mq {\ncolor: #008080;\n}\n.pl-mi {\ncolor: #333;\nfont-style: italic;\n}\n.pl-mb {\ncolor: #333;\nfont-weight: bold;\n}\n.pl-md {\nbackground-color: #ffecec;\ncolor: #bd2c00;\n}\n.pl-mi1 {\nbackground-color: #eaffea;\ncolor: #55a532;\n}\n.pl-mdr {\ncolor: #795da3;\nfont-weight: bold;\n}\n.pl-mo {\ncolor: #1d3e81;\n}\nkbd {\ndisplay: inline-block;\npadding: 3px 5px;\nfont: 11px Consolas, \"Liberation Mono\", Menlo, Courier, monospace;\nline-height: 10px;\ncolor: #555;\nvertical-align: middle;\nbackground-color: #fcfcfc;\nborder: solid 1px #ccc;\nborder-bottom-color: #bbb;\nborder-radius: 3px;\nbox-shadow: inset 0 -1px 0 #bbb;\n}\n.task-list-item {\nlist-style-type: none;\n}\n.task-list-item+.task-list-item {\nmargin-top: 3px;\n}\n.task-list-item input {\nmargin: 0 0.35em 0.25em 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fED/sW9U/9JpK9hrx79oT/khXxA/7FvVP/SaSvDwX+8U/Vfmd9f8Ahy9GflD+wZ4A8F/EH4heItP8baNaa1bWujedDFeRiVEkNxEu4A8ZwSM+hr9k/CHgTwd4A0+XSvBWj2mi2c8xuJYLOIRI8pVULkDqxVVGfQCvyc/4Jt/8lO8U/wDYBH/pTFX7H19DxfWqfX5U+Z8tlpfTbsebk0I/V1K2uoUUVzXjTxLB4M8Ha74wuYXuYdC0y81KSGMhXkSzheYopPALBMAnjNfLQi5SUY7s9ZtJXZ0tFfmp/wAPKfBP/Qmar/4FQ/4Uf8PKfBP/AEJmq/8AgVD/AIV7f+rOZ/8APp/ev8zh/tTC/wA/5/5H6V0VwHwt8f2nxS8AaN4+sLSSxt9YheZLeZg7xhJHjwSvB5XPFd/Xi1Kcqc3Cas1oztjJSSktmc74p8JeGfG2kPoPi7TLbVtOkdJGtrqMSRF4zlSVPGQelfkr/wAFAfhp4A+Hf/CB/wDCDaBY6H/aH9sfavsUKxed5P2Ly9+Ou3e2PTca/Yyvyr/4Kaf803/7jv8A7YV9FwpWqLMadNSfLrpfT4X0PNzeEfqspW10/NH2J+yH/wAm4eB/+vKb/wBKZq+kK+b/ANkP/k3DwP8A9eU3/pTNX0hXkZn/AL5V/wAUvzZ24X+BD0X5BRRXzV+0P+0pon7PP/CP/wBsaNdav/b/ANt8v7NKkflfY/I3bt4Od3njGPQ1hhsNVxFRUaKvJ9PxLq1YU4uc3ZI+laK/NT/h5T4J/wChM1X/AMCof8K7H4fft8eEviD430TwRZ+FdRtJ9bvYrKOeS4iZI2lbAZgBkge1epPhzMYRc5UnZea/zOWOZ4Zuyn+Z99UUUV4h3Hmfir4NfCrxxqx13xf4V0vV9QMaxG5u7dZJDGmdq7jzgZ4r8WfB2mafov7bMOj6Tbx2ljYfEG6tra3iG2OKGG/kSNFA6KqgADsBX75V+Deg/wDJ9kv/AGUi+/8ATjLX2nC9apKniISk2lB2V/U8PNoRUqTS15j95KKKK+LPcCiivz68af8ABQPwh4L8Y674OufCepXM2haneabJNHcwqkj2czwl1BGQGK5APNduCy7EYuTjh48zRhXxNOik6jtc/QWivzU/4eU+Cf8AoTNV/wDAqH/CvqH9nv8AaJ0b9oOw1q/0fSLnSV0aaCF1uZUkMhnV2BGwDGNnf1roxWR47D03WrU7RXW6/wAzOlj6FSXJCV2fRVQ3FvBd28trcossMyNHIjDKsjDDAj0IOKmoryjrPgH9rb4H/CHwf+z54r8R+F/COk6Xqdp/Z3kXdtbLHLH5moW0b7WHI3IzKfYmvxVr9/v22v8Ak2Lxn/3C/wD052lfgDX6vwZWqVMFKVSTb5nu79InyGeQjGulFW0/VhRRRX1p4x6x8Kvjb8SPg1qn9peBdWktopGDXFhNmWyucf8APWEnBOON67XA6MK/Xf4HftvfDj4nfZ9C8XlPCfiKTCCO5k/0C5c8fubhsBWY9Ek2nJAVnNfhhRXi5pkGExyvUVpd1v8APud+EzGth3aLuux/VQCCMjkGivwK+B/7YXxP+Dpg0e6mPiTw3Hhf7NvpDvgQdraf5mix2Uhox2UE5r9gfg7+0V8MPjbZqfCeoiHVETfPpF5iK9ix1ITJEqD+/GWUcZweK/M814dxWBvKS5od1+vb8vM+pweZUa+idpdn/Wp7pRRRXgnoBRRRQAUUUUAf/9f9/KKKq3t9ZabaTahqNxFa2tuhkmnndY4o0UZLM7EKoA6knAppX0QFquR8a+PfB3w60STxF421a20iwj4824fBdsZ2RoMvI5HRUBY+lfCXxv8A2/8Awv4Z+0eH/g/BH4g1Jco2qzhl06FumYl+V7gj1+WPoQzjivym8dfETxr8S9bfxF451e51a+fIVp2+SJSc7Io1wkSZ/hRQPavrsp4RxGItUxPuR/F/Lp8/uPGxmc0qXu0vef4H3n8b/wDgoF4h177R4f8Ag1bvolgco2sXSq19KOhMMfzJAD2Y7nxgjYa/OXUdR1DV76fU9Wupr28uXMk1xcSNLLK7dWd2JZifUnNUqK/RsBlmGwcOTDxt59X6s+YxGKq15c1R3Ciiiu85wooooAKKKKACv3D/AOCe/wDyQKT/ALD19/6Lgr8PK/cP/gnv/wAkCk/7D19/6Lgr5TjL/kXf9vL9T2Mj/wB5+TPuWiiivyY+wPgH/go5/wAkQ0T/ALGq0/8ASK+r8Va/ar/go5/yRDRP+xqtP/SK+r8Va/W+Dv8AkXL1Z8dnf+8v0R7don7N3xy8SaPZ+IND8Hahe6dfwpcW1xGEKSxOMqy5fOCPavFJYpIZHhmUpJGxVlYYKsDggjsQa/o6/Zv/AOSCeAf+wBY/+ihX87fiL/kYNT/6/Lj/ANGNW+SZzVxtatSqRSUHZW9X/kZ4/AwoU4Ti/i/4B+hv/BNj/kffGH/YIg/9Hiv2Cr8ff+CbH/I++MP+wRB/6PFfsFXwfF3/ACM5+i/I+hyb/dY/P8wrx79oT/khXxA/7FvVP/SaSvYa8e/aE/5IV8QP+xb1T/0mkrw8F/vFP1X5nfX/AIcvRn5o/wDBNv8A5Kd4p/7AI/8ASmKv2Pr8cP8Agm3/AMlO8U/9gEf+lMVfsfXu8X/8jKXovyPPyb/dV8wryv46/wDJEfiF/wBirrf/AKRTV6pXlfx1/wCSI/EL/sVdb/8ASKavBwf8eHqvzPRrfw5ejP5q6KKK/ez87P6GP2RP+TcPA/8A15Tf+lM1fSFfN/7In/JuHgf/AK8pv/SmavpCvwnM/wDfKv8Ail+bP0HC/wACHovyCvyr/wCCmn/NN/8AuO/+2FfqpX5V/wDBTT/mm/8A3Hf/AGwr0+Ff+RpS/wC3v/SWcmb/AO6T+X5o+xP2Q/8Ak3DwP/15Tf8ApTNX0hXzf+yH/wAm4eB/+vKb/wBKZq+kK8zM/wDfKv8Ail+bOvC/wIei/IK/Kz/gpp0+G/8A3Hf/AGwr9U6/Kz/gpp0+G/8A3Hf/AGwr0+Ff+RpS/wC3v/SWcmb/AO6T+X5o/Kqvb/2a/wDkvvgH/sPWf/oYrxCvb/2a/wDkvvgH/sPWf/oYr9Zx/wDu1T/C/wAj4/D/AMWPqj+jmiiivwU/Qgr8G9B/5Psl/wCykX3/AKcZa/eSvwb0H/k+yX/spF9/6cZa+w4U+HE/4H+p42b70v8AEfvJRRRXx57IV/Nb8dv+S3/EL/sata/9LZq/pSr+a347f8lv+IX/AGNWtf8ApbNX3XAv8er6L8zwM/8A4cPU8pr9bv8Agml/yLvjr/r907/0XNX5I1+t3/BNL/kXfHX/AF+6d/6Lmr6fiz/kWVPl+aPKyf8A3uPz/I/Tqiiivx4+0PlX9tr/AJNi8Z/9wv8A9OdpX4A1+/37bX/JsXjP/uF/+nO0r8Aa/U+CP9xn/jf5RPks+/3hen6sKKKK+xPECiiigAq3YX99pd5DqOmXEtpd2ziSGeB2jljdeQyOpDKw7EHNVKKGr6MD9I/gd/wUA8R+Hvs/h74yQSa5p4wi6vbKov4R0BmT5UnUd2G2TqTvPFfqv4K8e+DviLocXiPwTq1tq+ny8ebbtko2M7JEOHjcd1cBh6V/MLXa+A/iL42+GWuJ4i8DavcaTergM0Lfu5VBzsljbKSp/supHfrXyGbcI4fEXqYb3Jfg/l0+X3HtYPOalP3avvL8f+Cf050V+dXwO/b88KeKvs/h/wCLsMfhzVGwi6nFk6bO3TMgOXtifUlo+pLKOK/Q20u7W/tor2xmjuLedFkimiYPHIjDIZWUkMCOQQcGvzjHZdiMHPkxEbfk/Rn0+HxNOtHmpu5YooorhNz/0P1P+PP7XPw6+CMs+gNv13xTGin+yrU7FgMih0NzMQViDKQQoDvgg7QCDX49fGL9oz4ofG27b/hK9SMGlK+6DSLLMNlFj7pKZJlcf35CxHOMDiuu/bTOf2mvGn+/p3/pvta+W6/XuHskwtDD08Qo3nJJ3fS6vp2/PzPjMyx1apUlSbtFNqwUUUV9MeUFFFFABRRRQAUUUUAFFFFABX7h/wDBPf8A5IFJ/wBh6+/9FwV+HlfuH/wT3/5IFJ/2Hr7/ANFwV8pxl/yLv+3l+p7GR/7z8mfctFFFfkx9gfAP/BRz/kiGif8AY1Wn/pFfVyX7B/ww+G3i/wCDN/q/i3wpout3w1+6hFxqOnwXcqxJBbFUDyoxCgsTgHGST3r65+P/AMENN+Png2z8Hapqk+kxWepxamJoIllZmihmhCEMQMETE59qn+AvwV034D+CpvBel6lPqsU2oTagZ7iNYmDTJGhUKpIwBGD+NfTRzSlDJ1hYSaqc1+u3qeW8JJ4320l7tj13TdM03RtPt9J0e0gsbG0jWK3traNYYYY1GFREQBVUDoAABXy3+0J8H/hLpfwX8c63pvgrw7aajBo17PFdwaVax3EcwQkSLIsYZXB53A5zX1lXHfEHwfb/ABA8Ea54Jurh7SHW7GayeeNQ7xrMpUsFOASPQ14uDxMqVeM+ZpXTf3ndXpKdNxt00Pyu/wCCbH/I++MP+wRB/wCjxX7BV8pfs9/sraJ+z9req63pevXWrvqtqlq0dxAkQQI+/cCrHJ7V9W138Q42lisdKtQd4u35HNltCdGgqdTfUK8e/aE/5IV8QP8AsW9U/wDSaSvYa8e/aE/5IV8QP+xb1T/0mkrzsF/vFP1X5nVX/hy9Gfmj/wAE2/8Akp3in/sAj/0pir9j6/HD/gm3/wAlO8U/9gEf+lMVfsfXu8X/APIyl6L8jz8m/wB1XzCvK/jr/wAkR+IX/Yq63/6RTV6pXlfx1/5Ij8Qv+xV1v/0imrwcH/Hh6r8z0a38OXoz+auiiiv3s/Oz+hj9kT/k3DwP/wBeU3/pTNX0hXzf+yJ/ybh4H/68pv8A0pmr6Qr8JzP/AHyr/il+bP0HC/wIei/IK/Kv/gpp/wA03/7jv/thX6qV+Vf/AAU0/wCab/8Acd/9sK9PhX/kaUv+3v8A0lnJm/8Auk/l+aPsT9kP/k3DwP8A9eU3/pTNX0hXzf8Ash/8m4eB/wDrym/9KZq+kK8zM/8AfKv+KX5s68L/AAIei/IK5TxP4E8D+Nvs3/CZ+HtK177F5n2b+07KG88nzdu/y/ORtm/Yu7GM7RnoK6uiuOE5RfNF2Zs4pqzPKf8AhRHwP/6J54V/8Etl/wDGqvaZ8HPhFouoW+raP4H8OWF9aSLLb3NtpNpDNFIvIZHSIMrDsQQRXpFFbPF12rOb+9kKjT/lX3BRRRXOaBX4N6D/AMn2S/8AZSL7/wBOMtfoP8ev2zrL4G+Pn8Cz+E5dYdLOC7+0pfrbgifd8uwwSdNvXdzX5n/CnxMvjX9rfRPGSW5tF17xodTFuX8wwi8ummCF8Lu278ZwM4zgV95w3l+Io4etXqRtGUNHda7nz+Z4mnOpTpxeqlqf0G0UUV8GfQBXml/8F/g7qt9canqfgXw1eXl5K89xcT6RaSyzTSsWeSR2iLM7MSWYkkk5Nel0VpTqzhrBtehMoRl8SPKf+FEfA/8A6J54V/8ABLZf/Gq67wz4I8GeCo54fB2gaZoUd0ytOumWcNmsrICFLiFF3FQTjOcZrqKKqeIqzXLOTa9WJUoJ3SQVheKLqey8M6ve2rmOa3sLmWNx1V0jYqR9CK3a5vxn/wAifrv/AGDbv/0S1RTXvoc/hZ/PF4s/aG+NHjnw/deFvFviu81LSr3y/tFrKsQSTypFlTO1AfldFYc9RXjFFFfvlKhTpLlpRSXkrH55OpKbvN3CiiitSAooooAKKKKACiiigAr3/wCDP7SvxQ+CNykXhu/+2aMX3TaPfFpbN8n5igzuhc/3oyMnG4MOK8AorHEYelXg6daKafRl06s6cuaDsz9/fgv+198KPi9bpZzXieG9eVC0um6lKqBtoyxgnO2OZQMnHyvgElAOa+gv+E58E/8AQwaX/wCBsP8A8XX8wFFfG4jgfDzm5Uqjiu1r/ie5Tz6oo2nG7+4//9Gr+2ic/tM+NP8Arpp//pvtq+Xa+oP2zjn9pjxr/wBdbD/0gtq+X6/dcq/3Kj/hj+SPgMZ/Hn6v8wooorvOYKKKKACiiigAooooAKKKKACv3D/4J7/8kCk/7D19/wCi4K/Dyv3D/wCCe/8AyQKT/sPX3/ouCvlOMv8AkXf9vL9T2Mj/AN5+TPuWiiivyY+wCiiigAooooAKKKKACvHv2hP+SFfED/sW9U/9JpK9hrx79oT/AJIV8QP+xb1T/wBJpK6sF/vFP1X5mVf+HL0Z+aP/AATb/wCSneKf+wCP/SmKv2Pr8cP+Cbf/ACU7xT/2AR/6UxV+x9e7xf8A8jKXovyPPyb/AHVfMK8r+Ov/ACRH4hf9irrf/pFNXqleV/HX/kiPxC/7FXW//SKavBwf8eHqvzPRrfw5ejP5q6KKK/ez87P6GP2RP+TcPA//AF5Tf+lM1fSFfN/7In/JuHgf/rym/wDSmavpCvwnM/8AfKv+KX5s/QcL/Ah6L8gr8q/+Cmn/ADTf/uO/+2FfqpX5V/8ABTT/AJpv/wBx3/2wr0+Ff+RpS/7e/wDSWcmb/wC6T+X5o+xP2Q/+TcPA/wD15Tf+lM1fSFfN/wCyH/ybh4H/AOvKb/0pmr6QrzMz/wB8q/4pfmzrwv8AAh6L8grivGHxI8BfD77J/wAJxr+n6H9v8z7L9unSDzvJ2+Zs3EZ271zjpuFdrX5Wf8FNOnw3/wC47/7YVrk2BjjMZDDTdk77eSb/AEIxuIdCjKrFXt/mfdH/AA0h8BP+h/0D/wAD4v8AGj/hpD4Cf9D/AKB/4Hxf41/OFRX3X+o2G/5+S/D/ACPA/t+r/Kj+j3/hpD4Cf9D/AKB/4Hxf40f8NIfAT/of9A/8D4v8a/nCoo/1Gw3/AD8l+H+Qf2/V/lR9cftseLvDHjb43S654R1S11jTzpdlELmzlWWIum/cu5SRkZ5Febfs1/8AJffAP/Yesv8A0YK8Qr2/9mv/AJL74B/7D1l/6MFfSTwyw+XyoRd1GLX4HlxqupiVUfV/qf0c0UUV+HH3oV5Fqfx++CmjaldaPqvjfQ7S9sZ5La5t5b2NZIZoWKOjqTkMrAgg9CK9dr+a347f8lv+IX/Y1a1/6WzV9Fw9k1PMak4VJNWV9Dzcyx0sNGMoq9z95/8AhpD4Cf8AQ/6B/wCB8X+Nd14Q+IXgb4gRXM/gnXbDXI7NkS4axnWYRNICVDFScEgHH0r+Yiv1u/4Jpf8AIu+Ov+v3Tv8A0XNXrZ1wrQwWEliITbatvbq0jjwOb1K9ZUpRSufp1WH4ntLi/wDDWrWNonmT3NjcxRJkDc7xsqjJwBknvW5RXxEXZpnutXVj+c7xn+zN8cfh94bvPF/jDwvLp2kWHlfaLlrq1kEfnSJCnyxzO53SOq8KevPHNeEV+/37bX/JsXjP/uF/+nO0r8Aa/ZeHc1q5hhpVqqSak1p6J9W+58TmeEhh6qhB6Wvr8wooor3jzgooooAKKKKACiiigAooooAKKKKAP//Spftmf8nL+Nf+u1j/AOkNvXzBX07+2Uc/tLeNf+u9l/6Q29fMVfuuVf7lR/wx/JHwGM/jz9X+YUUUV3nMFFFFABRRRQAUUUUAFFFFABX7h/8ABPf/AJIFJ/2Hr7/0XBX4eV+4f/BPf/kgUn/Yevv/AEXBXynGX/Iu/wC3l+p7GR/7z8mfctFFFfkx9gFFFfG/7TH7V1x+z34g0fQ4fDKa6NVs3uzK18bXy9khTbtEEu7OM5yK6sHg62KqqjQV5P5fmZVq8KUOeo7I+KP2jfjZ8W/DX7Tet+F9A8W6tYaRBqGmRxWUFy6QokttbM4Cg4AZmYn3Jr9n6/mw+KPxTk+JfxZ1D4pyaaNPe/ubS4NkJvOCfZYootvm7Ezu8rOdoxnviv1D+Cn7dN38XPidonw7l8GR6WusPcKbtdSM5i8i3ln/ANX9mj3Z8vH3hjOfavtM/wAjrvCUJUqa9yPvbLZL79n3PDy/H0/bVFOXxPTfuz9DKKKK+BPoQrx79oT/AJIV8QP+xb1T/wBJpK9hrx79oT/khXxA/wCxb1T/ANJpK6sF/vFP1X5mVf8Ahy9Gfmj/AME2/wDkp3in/sAj/wBKYq/Y+vxw/wCCbf8AyU7xT/2AR/6UxV+x9e7xf/yMpei/I8/Jv91XzCvK/jr/AMkR+IX/AGKut/8ApFNXqlc74w8N2vjLwlrfhC+lkgttc06702aWLHmJHdxNCzJuBG4BiRkEZr57DzUKsZy2TR6VSLcGkfy80V+yX/Dtz4Xf9DRr/wD5Lf8Axmj/AIdufC7/AKGjX/8AyW/+M1+r/wCt+W/zP7mfIf2Liuy+8+hv2RP+TcPA/wD15Tf+lM1fSFcN8NPAWmfC/wAC6R4C0a4nurPR4WhimuSpmfc7SEtsVV+8xxgdPXqe5r8sx1WNXE1KkNnJtfNn1tCDjSjF7pIK/Kv/AIKaf803/wC47/7YV+qlflX/AMFNP+ab/wDcd/8AbCvX4V/5GlL/ALe/9JZxZv8A7pP5fmj7E/ZD/wCTcPA//XlN/wClM1fSFfN/7If/ACbh4H/68pv/AEpmr6QrzMz/AN8q/wCKX5s68L/Ah6L8gr8rP+CmnT4b/wDcd/8AbCv1Tr8rP+CmnT4b/wDcd/8AbCvT4V/5GlL/ALe/9JZyZv8A7pP5fmj8qqKKK/Yz4kKKKKACvb/2a/8AkvvgH/sPWX/owV4hXt/7Nf8AyX3wD/2HrL/0YK5cf/u1T/C/yNsP/Fj6o/o5ooor8FP0IK/mt+O3/Jb/AIhf9jVrX/pbNX9KVfzW/Hb/AJLf8Qv+xq1r/wBLZq+64F/j1fRfmeBn/wDDh6nlNfrd/wAE0v8AkXfHX/X7p3/ouavyRr9bv+CaX/Iu+Ov+v3Tv/Rc1fT8Wf8iyp8vzR5WT/wC9x+f5H6dUUUV+PH2h8q/ttf8AJsXjP/uF/wDpztK/AGv3+/ba/wCTYvGf/cL/APTnaV+ANfqfBH+4z/xv8onyWff7wvT9WFFFFfYniBRRRQAUUUUAFFFFABRRRQAUUUUAf//Tzv2yP+TlfG3/AF8Wf/pFb18yV9M/tjHP7Snjb/r5tP8A0jgr5mr91yr/AHKj/hj+SPz/ABn8efq/zCiiiu85wooooAKKKKACiiigAooooAK/cP8A4J7/APJApP8AsPX3/ouCvw8r9w/+Ce//ACQKT/sPX3/ouCvlOMv+Rd/28v1PYyP/AHn5M+5aKKK/Jj7A43xx8QfBnw20mLXfHOrQaPYT3C2kc9xu2tO6O6oNoY5Kxsfwr8dP27fiX4E+JnjLwzqHgTWbfWbez0yWGeS33YjkaYsFO5V5I5r6/wD+Cjn/ACRDRP8AsarT/wBIr6vxVr9G4Pyim4Rx93zaq3TsfM51jJczw9tNAr3/APZb8V+HvBHx58KeKPFd6mnaVZS3f2i5kDFI/NtJ4kJ2gnBd1HTjPPFeAUV9xiKCrUpUZbSTX3qx4FKo4TU10dz+l7wL8Yfhl8TLq6svAfiG01meyjWW4jty25Ec7QxDKvGRjivSq/H3/gmx/wAj74w/7BEH/o8V+wVfi+d5fDBYuWHpttK2/mj7nAYmVeiqklqFePftCf8AJCviB/2Leqf+k0lew149+0J/yQr4gf8AYt6p/wCk0lceC/3in6r8zev/AA5ejPyZ/YV+JPgb4afEDxBqfjvWINGtbvR/IhluA215RPG20bVbnaCefSv2U8D/ABD8FfErS5ta8C6vb6xZW9wbWWa33bUmVVcodwU52up6Y5r+Yqv2e/4Jv/8AJHvEP/Yyzf8ApJa197xhlFPklj7vm0VunY+eyXGT5lh7aan6FUUUV+cH0wUUUUAFFFFAHL+MPGvhXwBoj+I/GWpQ6VpsciRPcz52B5DhR8oJyT7V+SP7fHxX+HfxP/4QX/hAddtta/s3+1/tf2fd+58/7H5e7cq/e8tsY9K+yP29v+TdtR/7CWn/APo2vwlr9B4PyilNLHtvmi2rdNrfqfOZ1jJRbw9tGl+f/AP6GP2Q/wDk3DwP/wBeU3/pTNX0hXzf+yH/AMm4eB/+vKb/ANKZq+kK+MzP/fKv+KX5s9zC/wACHovyCvys/wCCmnT4b/8Acd/9sK/VOvys/wCCmnT4b/8Acd/9sK9PhX/kaUv+3v8A0lnJm/8Auk/l+aPyqooor9jPiQooooAK9v8A2a/+S++Af+w9Zf8AowV4hXt/7Nf/ACX3wD/2HrL/ANGCuXH/AO7VP8L/ACNsP/Fj6o/o5ooor8FP0IK/mt+O3/Jb/iF/2NWtf+ls1f0pV/Nb8dv+S3/EL/sata/9LZq+64F/j1fRfmeBn/8ADh6nlNfrd/wTS/5F3x1/1+6d/wCi5q/JGv1u/wCCaX/Iu+Ov+v3Tv/Rc1fT8Wf8AIsqfL80eVk/+9x+f5H6dUUUV+PH2h8q/ttf8mxeM/wDuF/8ApztK/AGv3+/ba/5Ni8Z/9wv/ANOdpX4A1+p8Ef7jP/G/yifJZ9/vC9P1YUUUV9ieIFFFFABRRRQAUUUUAFFFFABRRRQB/9TK/bEOf2k/G3/Xza/+kcFfNFfSv7YRz+0l43/6+rb/ANJIK+aq/dsr/wByo/4Y/kj8/wAX/Hn6v8woooruOcKKKKACiiigAooooAKKKKACu48PfE34k+EbA6V4T8Wa5otkZGlNtp2pXNrCZGADPsikVdxAAJxk4FcPRUTpxmrTV0VGTi7pnqv/AAvb43/9FD8V/wDg7vf/AI9R/wAL2+N//RQ/Ff8A4O73/wCPV5VUsUE052wxtIR2UFv5Vl9UofyL7kX7ap/M/vOw8SfEn4i+MbKPTfF/inWtcs4pRPHb6lqNxdxJKqsodUmkZQ4VmAYDOCR3NcVVz+ztQ/59pv8Av23+FINPvyARbTEHoRG3+FawjCCtBJIiTk3dlSip5ba5gAM8Txg9N6lc/mKgqyTpPDXjLxf4MuZbzwfrmpaFcXCeVLLpt3NaSSRg52s0LIWXIzg8Zrsf+F7fG/8A6KH4r/8AB3e//Hq8qorGeHpTfNKKb9C41ZxVkz1X/he3xv8A+ih+K/8Awd3v/wAeqnqHxl+L+r2FxpereOfEl7ZXcTw3FtcavdywzROMMjo8pVlYHBBBBHWvNwCTgck1aGn35GRbTEH/AKZt/hU/VaC15F9yK9rUfVlSuz8N/Eb4heDbSWw8IeKNZ0O2mk86WHTdQuLSN5MBd7LDIoLYAGSM4AFcv9gv87fs02euPLb/AAoNhfqMtbTADuY2/wAK1nGE1yzSaIi5J3R6V/wvb43/APRQ/Ff/AIO73/49R/wvb43/APRQ/Ff/AIO73/49Xm39nah/z7Tf9+2/wqCWGaA7Zo2jPowKn9ax+q4f+Rfci/a1f5meof8AC9vjf/0UPxX/AODu9/8Aj1H/AAvb43/9FD8V/wDg7vf/AI9XlVFP6pQ/kX3IPbVP5n956r/wvb43/wDRQ/Ff/g7vf/j1H/C9vjf/ANFD8V/+Du9/+PV5VRR9UofyL7kHtqn8z+87vX/ij8TfFenNpHinxdrusWDOrta6hqVzdQF05VjHLIykg9DjIrhKKK1hTjBWgrIiUnJ3kz0LR/i58V/D2mwaNoHjTxDpmn2oKwWlnqt1bwRAksQkccqqoLEk4A5Oa0/+F7fG/wD6KH4r/wDB3e//AB6vKqKzeFot3cF9yKVaa0Un956r/wAL2+N//RQ/Ff8A4O73/wCPVynibx1438am2PjLxDquvfY9/wBm/tO9nvPJ83bv8vznfZv2ruxjO0Z6CuVopww9KL5oxSfohOrNqzbCiiitiAooooAKu6bqWo6Nf2+q6RdT2N7aSLLb3NtI0M0MiHKujoQysDyCCCKpUUmk1Zgmeq/8L2+N/wD0UPxX/wCDu9/+PUf8L2+N/wD0UPxX/wCDu9/+PV5VRWH1Sh/IvuRr7ap/M/vPVf8Ahe3xv/6KH4r/APB3e/8Ax6vNL6+vdUvbjUtSuJbu8u5XnuLid2klmlkYs7u7EszsxJZiSSTk1VorSnRpw1hFL0RMqkpfEwrrvDPj/wAeeC454fB3iTV9CjumVp10y+ns1lZMhS4hdAxUE4JzjNc4LC/YArbTEHoRG3+FRy21zAAZ4njB6b1K5/MU5RjNcsldCTcdUenf8L2+N/8A0UPxX/4O73/49R/wvb43/wDRQ/Ff/g7vf/j1eVUVl9UofyL7kX7ap/M/vPQNb+LHxT8TaXNoniTxl4g1XTrnZ51nfapdXNvJ5bB13xySMjbXUMMjggEcgV5/RSgEnA5JrWFOEFaCt6ESk5ayYlFWxp9+QCLaYg9D5bf4UfYL7O37NNnrjY3+FVdCsypRVs2F+oJa2mAHUmNv8KqU7isFFFFABRRRQAUUUUAFFFFAH//Vx/2wDn9pHxv/ANfdv/6Sw18119JftenP7SHjf/r8g/8ASaGvm2v3bK/9zo/4Y/kj8/xf8efq/wAwoooruOcKKKKACiiigAooooAKKKKACivcf2efhDbfG/4k2/gO71OTSYprS5uTcxwidgYFyF2lkHOeua+/P+HaXh//AKHu9/8ABdH/APH68jHZ7gsHU9liJWdr7N/kjtw+X160eemrr1PySr77/wCCdf8AyWrU/wDsA3H/AKOhr0PwH/wT40Txh4UsvEU/jS6tnujODElgjKvkzPFwTMDzsz+Nes/DP9lzUfgB8U9KbwV4ujuLvxDpmpxSS6jpXmpDHatbP8scd3ESzl8ZLYAHQ548fNs+wOIw1XC05+801s+m/TyO3B5fXp1YVZR09UfojXm3wa/5JD4I/wCxd0v/ANJY6r/2D8YP+hw0T/wnpf8A5Z15/wDCfRfipL8LfB8mn+K9It7VtC00wxS6FLK8cZto9qtINRQOwGAWCqCecDpX5zGjD2MvfW679n5H0zm+de69n28vM+Pv+Cl/3fAP11T/ANtq/Kmv0u/4KFWPi+yj8EjxXq9lqpc6j5Bs9Pew8sDyN27ddXO/PGMbcYPXPH5o1+rcMJLLaaTvv+bPkM1d8VJ+n5IKK/VLw1/wTo0HXvDmla5J43u4W1Gyt7to10+MhDPGrlQfOGQM4zXyh+1B+zxY/s96zoel2Oty60usWs1wzy2625jMLquAFd85z7YrfC59gsTW+r0Z3lr0fT5EVsur0oe0mtPVHzLZ/wDH3B/10T+Yr+o3Rf8AkD2P/XtD/wCgCv5cbP8A4+4P+uifzFf0f6VofxdbS7No/F2iIht4iq/8I/McDaMDP9p84r5rjiCkqN5JfFvfy7Jnp5DJrnsr7fqa+nf8lh8Qf9i1oX/pXq1L8Zf+SSeNP+wBqX/pO9ebWGi/FQ/FTXIk8VaOLoeH9FaSY6FKUaI3WphFEf8AaIKsrByzbjuDAALtJZfivovxUi+GHi2XUPFWj3FquiagZoY9ClieSMQPuVZDqLhCRwGKtg84PSvjVSj9Yh76+z37LyPcc37OXuvr28/M+ka/E3/goj/yW6w/7AVt/wCjZq/WH+wfjB/0OGif+E9L/wDLOvj74m/stah8fPivqp8aeL0t7zQdI0sJNp2l+VHLHdyXZw0cl1KQyGLqGwQegxk+lw5iKGExbr1ZrlSeyfWy7HLmdOpWo+zhHVvy/wAz8aaK/T7x7/wT30Twd4P1TxPB40urmTT4fNET6eiq/wAwGCRMSOtdf/w7S8P/APQ93v8A4Lo//j9fePinLVFT59H5Ppby8z57+yMVe3L+KPySor279oT4SW3wS+JV14CtNSk1WK3tra4FzJEIWPnpuI2hnHHrmvEa9yhXhWpxq03o1dHBUpyhJwlugooorUgKKKKACiiigAooooAKKKKACiiigAoor9MPhd+wHovxC+Hnh/xvceMrqyk1qxivGt0sEdYjKM7QxmBbHrgZ9K4MfmWHwUFPESsnps3+R0YfC1K7caavY/M+iv0/1X/gnxoeneMNA8ML40u3TWYNQmaY2CAx/YhCQAvnYO7zeeRjFdd/w7S8P/8AQ93v/guj/wDj9ebLinLUk3Pfyfp28jqWUYp3Sj+KPuz4J/8AJHPA3/Yu6X/6Sx1+f3/BS/8A1XgD/e1T+VtX178JdD+KbfC3wg2neKtHt7U6Fp3kRSaFLK8cf2dNqtINRQOwGAWCrk84HSvhr/goXY+L7KHwQPFer2Wql21LyDZ6e9h5eBb7t266ud+eMY24weuePisipxWcpqSestNez8j3cwk3gmrdF28vM/M+iiv1R8Mf8E6dB8QeGtJ16TxvdwtqVjbXbRrp8bBDPGshUHzhkDdjNfo2YZphsEovEytfbRv8j5nDYSrXbVJXsfldU9r/AMfMX/XRf5iv04f/AIJ76Inj2Hwf/wAJpdGKXSJdT8/+z03Bop44dm3zsYIfOfatbxF/wTr0Lw54f1PxDF42u5n0uzuLxY209ArtbxtIFJE+QCVxmvPfE+XXS59/J/5HSspxOr5dvNH6f6H/AMgTT/8Ar1h/9AFcVp//ACWDXv8AsWtE/wDSvVK53w5pXxdvPD2l3cfizRYknsreRY/7AlbYHjUhc/2kM4zjOOa5mx0X4qH4p63EvirRxdDw/o7PMdClKNEbrUgiCP8AtEFWVgxLFjuBAAXaS35ZCjFe099befdeR9a5v3fdf4dn5nofxr/5I545/wCxc1X/ANJZK/mlr+hT4uaJ8U4/hV4xfUfFWkXFqug6kZ4otClhkkjFtJuVZDqLhGIyAxVgDzg9K+WP+HaXh/8A6Hu9/wDBdH/8fr6vhnNMJgKM1iJ/E9LJ9F6eZ5Ga4StiJx9nHZeX+Z+SVFfQ37SfwRs/gL45tfCFlq0usJcafHemeWEQEGR3TbtVn6bM5z36evzzX6FhsRTr0o1qTvF7HzdWlKnNwnugooorYzCiut8BeGo/GXjbQvCU07WqazqFtYtOq7zGLiQJuCkjO3OcZGfWv1A/4dpeH/8Aoe73/wAF0f8A8fry8fnOEwUlHESs35N/kdeHwNaum6SvY/JKivYfjz8MLb4OfFHVvh5aX76nFpqWrC6kjELP9ot45jlAzAbd+OpzjNePV30a0KtONWD0auvRnPUg4ScJbo//1sP9rs5/aP8AHH/X7D/6TQ18319HftcnP7R3jj/r+i/9J4q+ca/dss/3Ol/hj+SPz/F/x5+r/MKKKK7jnCiiigAooooAKKKKACiiigD65/Yk8RaH4W+Otpq/iK9h0+zTTb5DNM21dzoAo+pr9mv+F4/CT/oadP8A+/h/wr8f/wBgX/k4ey/7Beof+gCv3Vr8u4xlSWPXOm3yrZ26vyZ9bkil9X0fV/1ufLvwe+Mfwu074daTaX3iWxhmU3TMjSEMA9zKy5GOMqQcU7xB8Y/hfN8UPB99F4ksWt7ax1tZZBIdqGUWmwE46ttOB7H0r0r4I/8AJMdI/wB+9/8ASuaneJf+SteCP+wfr38rOvElKj9aqe6/t9V2f907kp+yjqunT08xP+F4/CT/AKGnT/8Av4f8K8++E3xl+F2nfC3wfYX3iWxhuLbQdNimjdyGSRLaMMpGOCCMGvpavNvg1/ySHwR/2Lul/wDpLHXNGVD2Mvde66rs/wC6atT51qtn09PM/Nz9vbxDo/xLk8F23w/uP+Ehmsl1J7iPT0e4eJH+zgMyqpIBPGcYzX52P4H8axo0knh/VERAWZmspgAB1JOzgCv6MNR/5LP4f/7FjXf/AEs0qu517/kBaj/16T/+gNX0+A4oeCw9PDwpXXm+7fkeViMpVepKpKVn6eXqeK+BPjR8KrPwR4etLnxPp8c0GlWUciGTlXSBAw6diK/PL9vLXNM+Jni/woPh9K3iE2Om3RuRp8b3Bi8yZdu7apxnBr9TvhR/yS3wd/2ANL/9JY6yoP8Akt17/wBirZ/+ltxXlYDHU8JjJYiEG3G+7+X8vmdmIoSrUVTk9Hbp/wAE/nZj8F+MbWRLq60HU4YYWEkkklnMqIi8szEoAABySeAK/oV0n42/CaLS7OKTxTp4ZLeJSPNzyFAPIFdJ8W/+SVeM/wDsXtV/9JZa6/Rf+QPY/wDXtD/6AK3znO45hThOrTtZvZ+nkzPA4B4aUowle9unr5nz3YfGX4XJ8Vdd1BvEtiLaXw/osKSlztaSK61NnUHHVQ6k/wC8KX4r/GT4Xal8MPFun2PiWwmubnRNQiijWT5nd4HCqOOpJwK9L07/AJLD4g/7FrQv/SvVqX4y/wDJJPGn/YA1L/0nevNUqP1iHuv7PVdl/dOpqfsparr09fMp/wDC8fhJ/wBDTp//AH8P+Feb6J8YvhfD8UvFmoy+JbBba50rQ44pPM+V3he/3gcdV3rn6ivp2vLPD/8AyV/xn/2B/D3/AKHqNY0ZUOSfuvbuu6/ulzU+aOq37eT8zzP4w/GL4Xan8M/ENhY+JtPlnmtCEQS43HcpxkgDtXaf8NH/AAH/AOh70T/wLSq/7TP/ACQDx7/2BLr/ANBr+cqvpMjyLD5lh223Hlb6p7peS7Hl5hmFTC1Ekk7r/M+rP2zvFnhvxp8dNQ13wnqNvqunvYWMa3Ns/mRM6RAMAw4ODwfevlOiiv0jCYdYejChF3UUl9x8xWqupUdR9QoooroMgooooAKs2lneahcJaWEElzPIcJFChkdj6BVBJ/Kq1fS37H//ACcb4M/6+pv/AERJXPiq3saM61r8qb+5GtGnz1Iw7ux4p/wgnjj/AKF3Vv8AwCn/APiKih8F+MbhWa30LU5QjtGxSzmYB0OGU4TgqRgjqDX9QVeXfCX/AJAOsf8AY0+JP/TrdV8LHjebg5+xWluve/l5HvvIY8yXP+B/OdJ4K8ZRPHHLoOpo0zFI1azmBdwpbaoKcnapOB2BPQGpf+EE8cf9C7q3/gFP/wDEV/Rn47/5Gb4ef9jLP/6ZdVr0qifG84xi/YrVd/Nrt5DWQxba5/w/4J/K5PBPazPb3MbxSxsVeN1KsrDqCDyCPQ1FXqvxz/5LN44/7GDUf/Sh68qr76jU56cZ90mfOTjyycewV++X7P3xd+Gei/BPwXpWqeI7G3u7XR7aOaF5PmRwvKnAPI7jtX4G1/Rx+zV/yQPwH/2BLX/0GvkONXBYanzpv3ujt09Ge1kV/ay5exx/iL4x/C+f4neDr6LxJYtb21nrQmkEh2oZFtQgJx1bBwPY+lel/wDC8fhJ/wBDTp//AH8P+FHif/krPgb/AK8td/8AQLWvVa/Pq0qHJT917d1/M/7p9JBT5parft5LzPmn4TfGX4W6f8LvCNhfeJbGG4t9D06KWN3IZHS3QMpGOCCMGvir9vfxFo3xLbwVa/D+4/4SGayGpyXEeno9w8SN9mAZlVSQCeM9M1+kXwa/5JH4K/7F/TP/AEmjo1D/AJLBoH/Yta5/6V6VXo4PG08Lj3XhBtx5uumz8jmr0JVcOqbejt09PM/nJfwN42jRpJPD+qqqglmNlMAAOpJ2V+/vgH4z/Cuy8C+HLO68TWEc0Gk2MUiGTlXSBAwPHYivbtc/5Auof9es3/oBrk/hN/ySvwZ/2L+l/wDpLHXTm+exzGjF1aduV9H3Xp5GWCwDw02oSvddu3zPIZfjF8Lz8X7XVB4l0/7Kvhu5tzJ5vAlN3AwXGM8qCemOK3PH3xq+FV14F8R21v4msJJZtJvo40VyWZmgcAAY5JNddN/yW60/7FW6/wDS2Cui+Iv/ACT7xP8A9gbUP/Sd68pyo89P3X06rv8A4TstPllqvu/4J554U+NXwptvC2jW0/ifT0ki0+1R18zoyxKCOB2Nc9Y/GX4Wr8VNb1BvEtiLaTw/o8KSFztaSO61JmUHHVQ6k/UV7l4M/wCRP0L/ALBtp/6JWua0/wD5LBr3/YtaJ/6V6pUqVC9T3Xt3Xdf3R2n7uq+7yfmeYfFv4yfC7UvhX4x0+w8S2M9zc6DqUMMSOSzyPbyKqgY5JJwK9D/4Xj8JP+hp0/8A7+H/AAqz8af+SP8Ajj/sXdU/9JZK9MqJSoexj7r3fVdl/dGlPneq2XT18z8R/wBt27i+JHxcs9T8ALL4gtbbRbaKaXTonuFjkMsxCuUU7SRyAe1fGdz4N8X2cLXN5oepQQpjdJLaTIgyQBklABknH1r+i/wz/wAla8cf9eOg/wDoN3R8bP8Akmmq/wDXWx/9LIK+twPFLwypYONK6tFXv3s+3meNiMpVVyrOWuvTt8z+df8A4QTxx/0Lurf+AU//AMRUEfg3xfLNLbxaHqTywbfNjW0mLR7xldwCZXI5Geor+oSvKPCH/JTviB/v6P8A+khranxvOUZP2K0V9/NLt5kSyGKaXPv5f8E/Bn4UeHvEHhv4n+Etd8QaXfabp1jrenzXN3dW0sUMMazplndlCqPqa/ej/hePwk/6GnT/APv4f8Kl+MP/ACJSf9hzw7/6eLKvUK8DOc4hmChWq07WutH6Ps+56OCwTw3NCEr7Pb18z+fT9sXXtH8S/tCeJNZ0G7jvbGePTxHPEco2yygVsHjowI+or5ir60/bh/5OX8U/9ctM/wDSG3r5Lr9Qym31Kjbblj+SPk8Z/vE793+Z/9fn/wBrc5/aN8cf9f8AH/6Iir5zr6W/alsL7Vv2mvGOmaZBJdXd1qkUMEEKl5JJHhiCqqjksTwAOSa86/4Ul8Yv+hJ1/wD8F0//AMRX7lgK1OGEoqckvdju/JHwOIpylWnyrq/zPLqK1tb0HWvDWoyaP4hsbjTb6EKZLa6jaKZA4DLuRgGGVIIyOQc1k16KaaujmaadmFFFFMQUUUUAfph8Af2J/AXxb+FOi+PtY1vVbO71L7R5kNv5PlKYZnjG3dGTyFBOT1rufEP/AAT++G+jav4Y06HxDrMia7qsthMzeRmNI9PvLwMuI/vb7ZV5yME98V6t+yL8TfB/hz4AeGdI1ae9juYftZcRabe3CYe5lYYkhgeNuD2Y4PB5BFeq+Mvi74FufEfgWaG4vylpr880pOk6gpCHSNSjGA1sCx3OvC5OMnGASPy/F5nmscZVhCUuVOVtO17dD6yjhMI6EJSSvp+h8/8A/Dt/4X/9DLrn/kv/APGq/J34ieHbTwh488Q+FbCSSW20jU7qyiklwZGSCRkBbAAyQOcACv6If+F0/D3/AJ+tR/8ABPqX/wAi1+GfxL+G3xE8YfEfxV4m8MeF9Z1LS9Q1vUZba6g0+4ZJE+0SA4+TIIIIIOCCCCARivX4YzHGVKk/r0naytfTU481wtGMI+wWvlqec/DL4m+KvhH4ri8ZeDZYYtShhlgUzxCaMpMMMCp/Q19Kf8N9/tDf8/mlf+C9P/iq+cpfg78V7eaC3n8H63HLcsyQI1hMGlZVLkICmWIVSxA7AntVn/hSXxi/6EnX/wDwXT//ABFfSYnD5dXl7Suoyfd2PLpVMTTXLTukez+Gv22vjt4V0W30HS7zTfstsZCnm2KM/wC9dpGycj+Jj26Ut5+238dr7XdN8RT3em/a9KiuobcixQJtu/L8zcM8n90uPTmvDrT4O/Fe/t1urHwfrdxC+dskVhM6HaSDghCDggg+9K3wc+LCXMdk/g/W1uJkeSOI2EwkdIiodlXZkqpdQxHALDPUVn9RyvmcuSF9e3zK+sYu1ru3zPoz/hvv9ob/AJ/NK/8ABen/AMVWP4f/AG4Pjx4Z0HTvDml3emCz0u0hsrcPYoziK3QRpubPJ2qMnvXif/CkvjF/0JOv/wDgun/+Iqva/Bz4sX1rDe2Xg/W7i3uI1lhmisJnjkjcBlZWCEMrA5BBwRU/2flNrckLfIf1nGXveX4nucv7b3x2m8QWviZ7rTPt1nZ3NjEwsV2+TdyQSSAru5O63TB7c+taVz+3n+0Dd28trNd6UY5kaNwLBRlWGDzu9DXy34k8DeMvBywP4s0PUNHF0WEBvraS380pjds3gbtu4Zx0yK5Wto5Rl80pRpRa6aIh43ExdnNn9Evw/wDBPjkeA/DYs/H2oW1v/ZFj5UI0/TnEcfkJtTc1uWbaOMk5PesQ+EPG8fxfFsvjvUPtNx4bLvc/YNPz5cF2Akez7Pt6ysd3XtW94E+MPgK08D+HrWe51BZIdKso3A0jUWAZYEBwVtiDyOoJBrn5Pi54GPxhg1Hz9Q+zjw1NCW/snUM+YbyJsbfs27oOuMe9flqjifaVP3ff7C/yPrn7Llj73br/AME2viJ4K8c/8K/8TfbPH2oXNv8A2Pf+bCdP05BLH9nfchZbcMu4cZByO1bPh3wj8QLvw/pl0PiDqEYms7eQINN00hd0anGTbc4zWT8QPjD4DvPAfiS0t7m/Ms+kX8aA6RqKgs8DgZZrYADJ6kgDvWj4X+MngG38NaTBLc6gHjsbZGH9j6icMsag8i1IPPpWXLivY/w+v8i7ehX7rn+Lp3f+ZzVh4R8dN8VtdtV8eX6zp4e0WRrj+z9P3Oj3WphUK/Z9oCFWIIGTvOcgDD/iv4P8c2/ww8W3F348v7uGPRNQaSBtP09FlUQOShZLcMAw4yCCO1MsPi54GT4r67qLXF/5E3h7RYEI0nUC2+K61NmBQW24DEi4JAB5AJIOHfFf4u+BdR+GHi2wtLi/aa40TUIow2k6hGpZ4HAyz2yqoz3JAHc1qo4n28P3f8v2V2XkQ/Zezl73fr6+Z6B/whPxB/6KJqP/AILNN/8Akavzy/aR+N/xb/Z5+LU1h4c16PVZtZ0ewkurnUbG33EW8lyI1VYVjRQPMbJwSc9eBX6G/wDC6fh7/wA/Wo/+CfUv/kWvyv8A2zNK134tfFyDVvh1o2ra5bWmjWsU7QaddK0btLORuSSJXAbBwcYODgnBx6PDtFzxXLi6a5LO94pLpbWyOXM58tG9GXvX6Nv9Ty7xd+2j8b/G/hjU/COv3Omyadq1tJa3Kx2SxuY5Bg7WDZB9DXybXomo/CP4paRYT6pqvhLWrOztY2lnnnsZo440UZLMzIAAB1Jrzuv0rB0MNSi1hUkvK36Hy9epVm71W7+YUUUV2GAUUV2vh/4cfEDxXYnU/DHhzVNWs1kaIz2VpLPGJFAJUsikBgCCR1wRUTqRgrzdkOMXJ2SOKorvdY+FnxL8PadNrGveFtX06xtwDLc3VlNFEm4hRudlAGWIAyepxXBUQqQmrwd/QcouOkkfov8As1/sc+B/jX8L7fxzrms6pY3ct5c2zRWvleViBgARvQnJB55r3WL9jjwv8GPFHhXxh4O8TaumqPrltYRSypbSLELpZFZwjRFWIAIAIxzV39iT4keEvDHwKtNK1ma8juV1K+ciHTr25TazjGJIYJEP0DZHevbviV8W/A18fCn2a4v2+z+JtOnkzpOoLiNPMyRuthk89BknsK/Ncfj8yeOqUU5ezu1a2lvuPqcNhsL7CM2lzWXXqemf8IT8Qf8Aoomo/wDgs03/AORq83+GXhHxzPpmtLa+O7+1SHxJrkbKun6e++QXspeTLW5ILuSxA4GcDAwK9I/4XT8Pf+frUf8AwT6l/wDItebfDL4t+BrDTtdS6uL9TN4k1qdNuk6g4Mct5IynK2xAODyDyDwQDXgQjivZS/d9vsLz8j0X7LnXvd+r/wAyz4z8H+OovEPgVJvHl/M8viCZInOn6ephcaRqTbwFtwGJVWTDZGGJxkAj0D/hCfiD/wBFE1H/AMFmm/8AyNXn/jP4u+BbnxD4FmhuL8raeIJppc6TqCkIdI1KPgNbAsdzrwuTjJxgEj0D/hdPw9/5+tR/8E+pf/ItKrHFcsP3fT+Rd35BH2V3734vsvM+KNF/Yg8E/FSG98feIvEerrqWrarqrXPkrbqjSQ308JYKIsDd5e4gcAnjisXW/wBgT4b6V4s8NeHY9f1l4tca+EkjGDdH9lh80bR5eDuPBz2r6q+E/wAW/A+m+C47S8uL9ZRqWsOQuk6g4xJqNy68pbEZ2sMjOQeDggio/FXxa8D3HxD8D30VxfmG0k1TzSdK1BSPMtdq4U2wZueu0HHfFeuszzWNaUFKXKua2nZO3Q4/qmEcFJpXduvpc8L/AOHb/wAL/wDoZdc/8l//AI1Xt3wX8D+MYvhlodppPjrULGys45rO2txYafL5cVrPJCg3vblmO1ASTzXqP/C6fh7/AM/Wo/8Agn1L/wCRa80+EHxc8Dad8PdNtLu4v0lSW9LAaTqDgbruZhytsR0I78dDzXHWxeZYig/bpys1a8b9H5G0KGGp1F7Oy0ez9B+u+D/G/wDwtHwlazeO9QkmbTNcmhn/ALP08NF5bWKMu0W+1g4k5yMjaMd8+kf8IT8Qf+iiaj/4LNN/+Rq831v4t+B5vin4U1CO4vzBbaTrsch/snUAwaaTTymFNtuIOw5IBA4yRkZ9I/4XT8Pf+frUf/BPqX/yLXLVjiuWFqfT+Rd35G0PZXl73Xu+y8zz/wCFHg/x1cfC/wAI3Fp48v7SGTQ9PeOBdP091iRrdCEDPbliFHALEk9zTNQ8KfECL4raFbReOriS4k8Pa04nuNMsm2RpdaYGQJGkQ+cspLEkjbgdTT/hP8XfAun/AAv8I2F1cX6zW+h6fFIF0nUJFDJboDhktmVhkcFSQexpl/8AFzwM/wAV9C1Jbi/+zxeHtagYnStQDb5brTGUBDbbyMI2SAQOASCRnZxxPt5/u9Pe+yuz8jNey9nH3u3X/gnZat4U+JqaVePL47EiLbylk/se2XcoU5GQ/GR3rl/hj4W+JE3w28JzWnjgW8D6HprRQ/2RbyeWhtoyqbi2W2jjJ5PWup1f4y+AJtKvYY7nUC8lvKqj+x9RGSUIHJtcCuX+GXxf8CWHw28J2Nzc34mt9D02KQLpOoOodLaNThltirDI4IJB6g4rFRxXsX+76r7C7PyNH7LnXvdO7/zKC+FfHtx8XGtbjxvcJd23hxZEurfTbNCYri7IaNo5ElU4aFWDDB5IORjG5488G+PIfA/iKW48f6hPEmk3zPEdO05RIogclSy2+RuHGRyKwY/i34GHxfuNSNxf/Z28NwQBv7J1Dd5i3crEFfs24DDDBIweQDkHG749+MPgK78DeIrWC51AyTaTfRoDpGoqCzQOBktbADk9SQBWjjifaU/3fb7K/wAif3XLL3u/X/gl3wp4M8eyeFtHkh+IGoxRtp9qyRjTtObYpiXC5Nvk4HGTzXOWHhHx03xX1y0Hjy/WePw9o0jXH9n6fudHutSCoV+z7QEKkggZO45yAMdF4T+MfgG38LaNbzXOoCSLT7VGA0jUThliUHkWpB59K5uw+LngZPizrmotcX/kS+HdFgUjSdQLb4rrU2YFBbbgMSLgkAHkAkg4Sjib1P3fT+Rd15D/AHXu+9+Pl6jvi14Q8c23ws8YXF348v7uCLQdSeS3fT9PRZUW3kJQsluGUMOCVII7HNehf8IT8Qf+iiaj/wCCzTf/AJGrz34tfF3wLqPws8YafaXF+09zoOpRRh9K1CNS728gGXe2VVGTyWIA6k4r0L/hdPw9/wCfrUf/AAT6l/8AItZyjivYx/d9X9hdl5DXsud+90XV+fmecaH4P8b/APC0fFlrD47v45l0vQ5prj+z9PLS+Y98qqVNvtUII+MDJ3HOeMN+L/hHxvafDbXby98d6heRW1us/kNYafGHeKRHTLJb7gA4B464xT9F+LXgeH4peKtRkuL8QXOkaFHERpWoFi0Mmob8oLbcoG8YJAB5wTg4Z8Yfi14H1P4Y+I7CyuL9pprJlQNpWoRqTkHlntlUfiRXRFYn6zD3NPd+yuy8jN+z9lL3u/X18z0n/hCfiD/0UTUf/BZpv/yNXmvhLwh43n8d+OhF471CK4gvNOglmFhp7ecosYZEJU2+FK+YV+XqMZ5r0r/hdPw9/wCfrUf/AAT6l/8AItea+D/i34HtvHHjy7muL8RXmoae8JGk6gxITTrdDkC2JUhlPDAHGD0IJwoxxXJO9Pp/Iu68jSfsrx97r3fZ+ZL8VPCHji38JJJd+PL+6j/tnQV8ttP09BufVbRVfK24OUYhwOhK4IIJFei/8IT8Qf8Aoomo/wDgs03/AORq86+Knxb8Daj4SS2tLi/aT+2dBkw2k6gg2w6raSNy1sBnapwM5Y8AEkA+i/8AC6fh7/z9aj/4J9S/+RaJRxXsY/u+r+wuy8gXsud+90XV+fmfiV+2LY6jpv7QniSz1XUpNWuo49P33k0UULybrOEjKQqkY2gheFGcZPOa+Ya+nv2xdb07xF+0J4k1jSmke1ni0/Y0sMtu52WcKnMcypIvIPVRkcjjmvmGv13K7/U6XMteWP5HxeMt7edu7/M//9DtfHZz+3qP+xy0v/0KCv3Hr8KviRFLcftzTwW9xJaSyeLtPRLiEIZImJhAdBIsiFlPI3Ky5HII4r9iP+EF8W/9FF8Rf+Aui/8Aysr7HiSmpU8LeSXuLv5dkzxcsk1OrZX95n4qftu/8nKeKv8Ac0//ANIoK+T6/a7U/wBkHwJ8YPHvjTxB4817Xr3U7DVrbTxcxyWcDSxLpdhOpdIrRY9wM5XKqo2gZBOSeO8cfsGfB3wzptheWOo69I91rOkac4luYCBFf3sNtIRi3B3BJCV7BsZBHFfSYDiTBUaNLDSb5lGK202R5mJyuvOpOqlo23v5n5BUV+1//Dur4I/9BTxH/wCBVv8A/ItcV4P/AGDfg94gvPE1veajryLo2ty6bAY7mAFokt7eYF825y26VhxgYA47nojxdl7Tkm9PIyeTYlNLT7z8haK/Xrxp+wb8HfDv9g/Y9R19xqet2enTeZcwHENxv3FcWww3y8E5HtXc/wDDur4Gf9BPxL/4GW3/AMiUS4uy9RUrvXyBZLiW7afeel/sU/8AJt3hT/t9/wDSuavYfHP/ACNHw8/7GS4/9Mmq15D8EPhhfeH/AAPJ4d8O+NNf0zTNI1nW9PtbaKLSpQsVpqFxCpLz6dLIzME3MS2NxOABgDd8Z+DfEkXiPwHHJ471+ZpvEE6I7waOGhYaPqbb026aoLEKU+cMu1jxu2sv57ilCeNqzU1q5vr1T8j6Si5RoQi1tbt5H0VXl3wd/wCRJb/sOeIv/TveVY/4QbxR/wBFD8Sf+A+if/KqvNvhL4P8R3ngmK5i8da/aCTUtYYxQwaQU3/2lc72/eaa7ZdssRuwCSFAXAHHGlH2EvfW679peRs5v2i93o+3l5ne+Nv+Sg/Dr/sJal/6bLmvVa+avGHg7xHF468BQv461+Z5tQ1BUleDSA8JXTrhiyBdNVSWA2nerDBOADgj0z/hBvFH/RQ/En/gPon/AMqqK1KPJT99bef8z8ghN80vde/l2XmUvgj/AMkx0j/fvf8A0rmqTXv+SweDv+wL4h/9G6ZXnXwc8G+I7n4c6VND471+1Rmu8RRQaQUXF1MDgyaa7cnk5Y8njAwB85/tieL/AIk/AuTwb4t8K+MdRvtSuDqdiJNStNMkWKCQWzuEWGxhGXZEyWDEbeMZOe+hgnXx8qNOa5pOS69n5HPUr+zw6nJOyt28vM/SOvNvg1/ySHwR/wBi7pf/AKSx1+K3/Dcf7S//AENEP/gssf8A5Hr9ZvhF4O8SXfwp8G3UPjvX7SObQNMkW3hg0gxxBraMhEMmmvIVXoNzs2OpJ5OuY5DWwFH/AGicfeata/RPy8yMNmFPET/dp6Ly/wAz45/4KX/d8A/XVP8A22r8qa/db4q/s9aP8XfiFoHhL4h+KNf1aztdG1PUbd/+JfbSxSpcWcRANvYxKVZZDkMpOQMEcg8bqn/BPP4H2emXd3FqXiTfBBLIubu2I3IpIz/onqK+mybiDB4LB08PVbb12WmrfoeXjstrV68qkFp/wD7T+Hf/ACT/AMM/9gew/wDSdK5uT/kt9v8A9irP/wClsVfizZ/toftF6LZwaNp3iaKO1sI0tYEOm2TFYoQEQEmAk4UDk8mvrT9kX4ifFL4/eNvEOreMvGF9aXmi6VBbW8um2emxEw3Exd1dZbKZT80YIIAPvivFxfDWJwsKmJqyjy2ffr8juo5pSqyjSgnf5dPmfol8Sf8AknXir/sC6j/6TyVqeEf+RU0X/sH2v/opa8o+IPgvxLD4B8SzSePvEM6R6Pfs0Ulvo4SQCByVYppithuh2sDjoQea0fC3gnxNJ4Y0h0+IHiKNWsLYhFt9GKqDEvA3aWTgdOST6mvn/ZR9h8a38+3oelzvn+F7eX+Ztab/AMll8Rf9izoH/pZq9SfGX/kknjT/ALAGpf8ApO9fnX+1h8Wfiz8AfilYxeDPF13dS61oFq11calZadLIVt7q7ESKIrOKMKpkc52biWOSQFA+Vta/bL/aG8Q6Pe6Dq/iSKex1G3ltbmL+zrNN8MylHXcsAYZUkZBBHY19FhOGMViPZ4qnKPLp1fSy7eR5lfNaVPmoyTvr26/M/oGryzw//wAlf8Z/9gfw9/6HqNfjB/w3H+0v/wBDRD/4LLH/AOR6+0v2O/FvxI+OX/CYeMPFPjHUbHU4H02xaTTbTTI1lhiWd4w6zWMwBQyPgrtznnOBjDFcM4nBYedavKNrJaX7ryLpZpSr1Iwpp3+XZ+Z9W/tM/wDJAPHv/YEuv/Qa/nKr9+f2iPCHiGy+B3ja7ufHGu38UWj3LPbXEGkrFKAv3XMOnRSAH/ZdT71+A1fTcExUcNUs7+959l3SPLz1t1Y3XQKKK7f4aeHbDxf8QvDfhXVGkSz1fVLSynaFgsixzyqjFCQwDAHgkEZ6g19jUmoRc3sjw4xcmkjiK/bb/gnb/wAkJ1D/ALGS8/8ASe1pn/Dur4Gf9BPxL/4GW3/yJXf/AAU+C6fD+Hxd4J8FeL/EGk6TpHiERwxIumTs7T6bp9w7u9xp8rFi0pX5SqhVHGck/AZ9nuEx+DdGi2mmnqn/AMHufSZfl9bD1lOa020J/wBtr/k2/wAT/wC/Y/8ApVFX4DV+4n7YPhbXdM/Z/wDEd5feMda1eFGsw1peQ6YkL5uIwCxtrCCX5TyNsg5HORwfw7r1ODIpYGSTv7z/ACXexyZ4711ddP1Z+6n7An/JvNn/ANhXUP8A0Na99+KvXwd/2Nmmf+1K+T/2H/DGuar8B7S7sPF2s6NEdTvlFrZQ6a8IIYZYG6sbiXLd8uR6AV7j8R/BniNLzwZbzeO9fuFufE9qgMkGkAxMlvcyrImzTV+YNGBhty4JyucEfGY+nH+1Kr518Uu/n5HuYaT+qwVui7H0tXlfwm/5BniL/sate/8AS2Wrf/CDeKP+ih+JP/AfRP8A5VV5p8MPBviO407Xmi8d6/bBPEutxlYoNIIdku5AZD5mmudzn5mAIXJ+VVGBXlwpR9jP31uu/n5HXKb517r69v8AM9L8df8AIzfDz/sZZ/8A0y6rXpNfOvjTwb4ki8ReBI5PHevzNN4hmRHeDRw0LDSNTbem3TVBYhSmHDLtY8btrL6D/wAIN4o/6KH4k/8AAfRP/lVSq0o8kPfW3n3fkEJu8vde/l2XmVfgz/yIUX/YV1z/ANOl3UfjD/kp3w//AOumsf8ApJXC/CjwZ4in8HloPHev2saaxrsQiig0gr+61S7TdmTTXbc5Xc3ONxO0KuFEfi/wb4jg8eeAg3jrX5Zbi91GBZng0gPCpsJ5GKBdNVSWMYB3q3GcYPNdLpR+s1PfX2+/Z+Rkpv2UdO3buj6Vryr4J/8AJNNL/wCu1/8A+lk9XP8AhBvFH/RQ/En/AID6J/8AKqvMvg74N8R3Hw802aHx3r9qhlvgIooNHKLi7mBIMmmu3JGTljyeMDAHPGlH2EvfW679peRo5v2i917Pt5eZ6Hr/APyWDwb/ANgbxD/6M02vU6+bNc8G+I0+KvhK2bx3r7ySaTrrLcNBpHmRhH08MigaaEKvuBbcrH5RtK/Nu9K/4QbxR/0UPxJ/4D6J/wDKqitSjyQ99bef8z8hwm7y917+XZeYfBr/AJJH4K/7F/TP/SaOotS/5LN4e/7FjXv/AEs0muD+E3g3xHc/C3whcQ+O/EFpHLoenOsEUGjmOJWt0IRDJpjuVXoNzM2OpJ5qPUPBviNfi1oVsfHevtI/h3WpFuDBpHmoqXelgxqBpoj2uWBYshbKLtZRuDbulH6xU99fa79n5Gam/Zx93t2Petc/5Auof9es3/oBrk/hN/ySvwZ/2L+l/wDpLHWJrHgjxOmkXzN8QfETgW0xKm30XDAIeDjSwcH2INcx8MPBniS4+GvhK4h8eeILWOXQ9NdYIrfRzHErW0ZCKZNMdyqjgbmZsDkk81gqUfYP31uu/Z+Rbm/aL3Xt5f5nXRf8luuv+xVtv/S2eui+Iv8AyT7xP/2BtQ/9J3rx1/BviOP4xxWy+O9f8y48MySPceRpHmbYLxAiY/s3y9uZWOdm7P8AFjit7x94K8Sw+BfEc0nj7xDOiaTfM0UlvowSQCByVYppitg9DtYHHQg81q6UfaU3zrZd/wDIlTfLL3X17f5nqXgz/kT9C/7Btp/6JWuV07/ks3iH/sWNC/8ASzVqw/CXgnxNJ4U0WRPiB4iiVtPtSEW30YqoMS8DdpZbA6DJJ9TXN2Hg3xG3xa122HjvX1kTw5osjXAg0jzXV7vUwI2B00x7UKkqVQNl23Mw2hZjSjep7628+68h87tH3X+Hb1PQvjT/AMkf8cf9i7qn/pLJXplfOvxa8GeI7f4WeMJ5/Hev3cUehak7280GkLHKq28hKOY9NSQKw4O1lbHQg816D/wg3ij/AKKH4k/8B9E/+VVZypR9jH31u+/ZeRSm+d+69l28/MraB/yWDxj/ANgXw9/6N1OmfHD/AJJL4n/68W/9CWuC0Twd4jf4q+LLZfHWvpJHpGhM1wsGkeZKHk1DarA6aYwqbSV2op+Y7i3y7WfGLwb4jt/hxrDT+O9fu4pBbwSQzQaQqOk9xFG2THpqOMBiRhhz7cV0xpR+tU/fX2O/ZeRk5v2Uvd79u7PpWvKvBH/JQfiL/wBhPTf/AE2WtXP+EG8Uf9FD8Sf+A+if/KqvMvCfg7xG3xD8dWkXjvX4jHNpcskqwaQXmeSzVcvu01lG1UVQEVRgZOTk1z0aUeSp7628/wCZeRpOb5o+69/Ls/M9G+MP/IlJ/wBhzw7/AOniyr1CvkX9pHSfF3g/4L+IvFdt441u+uNH+w30EF3b6T5DT295BJEXEOnROQjgNgOASMHIyD+Y/wDw3H+0v/0NEP8A4LLH/wCR69bL+H6+Ow/Nh5Rsm979l5HHicxp4eraonql28/Mb+3D/wAnL+Kf+uWmf+kNvXyXXYePPHnif4l+KLvxl4yulvdWvViWedYo4Q4hjWJPkiVUGEUDgDOMnmuPr9UwFCVHDU6M94pL7kfI4ioqlWU1s22f/9HpfiNdR2X7clxezLI0cHi6wkZYY3mkKo0JISONWd244VVLMeACa/Yr/hbPhz/oGeJ//CY1j/5Dr8e/HPP7dzf9jnp//oyGv3Rr7HiV01TwvOm/cXW3byZ4uVqXNVs/tM+cfBnxO0C28ReO5X07xEy3XiCGVBH4d1WRlUaRpseJFW0JjbKE7XCttKtjaykw/E74m6DfaLpUcWn+IUMfiPw/MTN4d1WEFYtSt3YAvaKC5AIVAdzthVBYgH0rwJ/yM3xD/wCxlg/9MulVB8Wv+QDo/wD2NPhv/wBOtrXiRlS+sw91/Z6+S8jvan7OWvfp/wAEk/4Wz4c/6Bnif/wmNY/+Q680+HnxN0G01Hxq8mn+IXFz4lmmXyvDuqylVNnaLhwloSj5U/I2Gxg4wQT9MV5V8Mv+Qn48/wCxrn/9IrKsKUqPs5+6+nXz9DSanzR1/D/gnnfxK+J2g3f/AAivlad4iXyfEunTN5vh3VYsqnmZC77Vdznsq5Y9hXpP/C2vD/8A0CfFH/hNat/8iVF8U/8AmUP+xr0z/wBqV6rRUlR9lD3X16/8AUVPmev4f8E+avhj8TtDsdE1OKTTPEUhk8ReIJgYfD2pyqBLqdy4UlLVgHAIDLncjZVgGBAl8ZfE/Q7jxH4EmTS/Eai18QTyuJPD2pxsynR9TjxGrWwMjZcEqgLBQzY2qxHoHwl/5AGr/wDY0eJf/TtdVP45/wCRo+Hf/YyXH/pk1Wt5So/WJ+6/tdfJ+RCU/Zx17dCD/hbXh/8A6BPij/wmtW/+RK83+EvxN0PT/BEFrLpniKVlv9WbdB4f1OaMiTULlxh0tWXIBwwzlTlTggivpivK/gv/AMk/t/8AsJaz/wCnK6rGMqPsJe69118peRbU/aLXo+np5nnPi/4m6HceOPAd0mmeIlW11DUGZZPD+ppI4fT7hB5aNahpCCckKCQuWPAJHpX/AAtrw/8A9AnxR/4TWrf/ACJUXjb/AJKD8Ov+wlqX/psua9VorSo8lP3Xt3/vPyCCneWvXt5LzPhr4a/tZfAfwj4MsvDniLxE1lqVlLdpcW72V1vidrmVtrYiOGAYZHY8V86/tb+P/D37TFv4W8PfA37Z4t1HSZb66vLaysrjzIoZFhVXIeNcruGMjODjPUV+efj7/kevEf8A2Fr7/wBHvX2d/wAE6/8AktWp/wDYBuP/AEdDX6DVyXD4CMs0pNucU5WbVtflfr3Pm4Y6piGsJO1np56fM+bv+GcPj1/0IHiD/wAAJf8A4mv2s+EfxO0PT/hV4NsJtL8RySW2gaZEzweHtTmiZktowSkkdqyOpI4ZSVI5BIr6SrzT4Mf8kf8AA/8A2Lulf+ksdfK5pn0swor28Lcr6Pun3v2PXwmXrDT/AHct11PNLv4naG3xc0rUBpniLYnhzU4Sh8P6mJiz3diwIiNrvKAKQWAKqcAkFhns9a+K+gS6PfxDSvEyl7aZct4b1VVGUIySbTAHqa0r3/ktWj/9itq3/pbp9d3r3/IC1H/r0n/9AavKqSo/u/de3fzfkdkVP3tfw8vU/lzuf+PiX/fb+dfcn7D3xh+Hnwh1vxVefEDVP7Mi1G1tIrY+TLNvaN5CwxEj4wCOuOtfDlz/AMfMv++386gr9mx2Dhi8PLD1G7Pt958PQryo1FUjuj92PGv7Yf7PeteDde0fTfE/nXl/pl5bW8Ys7ob5ZoXRFyYgBliBkkCvZfDXxT0O18OaVay6T4n3w2VvG23w3qrDKxqDgi0wRnuK/nLs/wDj7g/66J/MV/Ubov8AyB7H/r2h/wDQBX5xxFlGGy6FOMLvmb3a6W8j6fLcbVxMpOVla39bn4s/t/8AiOz8TfE/w/e2VtqFqkegpEV1GwuNPlJFzO2VjuY4nZcH7wBXORnIOPg+v0P/AOCkP/JWvDf/AGLqf+ldzX54V93w/b+zqXLtb9T5/Mr/AFmd+4V+i/7D/wAdPhh8IdA8VWfxA1j+zJtSvLSS2XyJpt6RRuGP7pHxgsOuK/OiiurMcBTxlB4eq2k7beWphhsRKhUVSG6P2p+OX7WPwG8Y/CDxd4X8PeJftOpanpVxb2sJtLlPMlZeF3NEFGfcgV+K1FFY5VlFHL6cqdFtpu+v/DI0xmMniZKU0tOwV6b8FrqOy+Lvgy8mWRkg1ywlZYY3mkKpMhISOMM7tgcKoLE8AE15lXq3wL/5LR4G/wCxg03/ANKErsxf8Cfo/wAjCj/Ej6o/oC/4W14f/wCgT4o/8JrVv/kSvPvBfxP0O28Q+OpX0vxGwuvEMMyCPw9qcjKo0jTY8SKtqTG+UJ2uA20q2NrKT9I15p4D/wCRl+If/YzQ/wDpl0qvxKlKjyT917d/NeR97NTvHXr28n5nzh+1X4ug8c/BLWfCnh7R/EMmp6lPYQWsVxoWo2qyytdRBUEk1ukYZjwoLDccAZJAr8m/+GcPj1/0IHiD/wAAJf8A4mv3s+Lf/IC0X/safDf/AKdLavUq9zLeIZ5fhlCjBNNt6vyXax5+Ky2OIq81SWyW3zPgj9jvxJ/wrv4Or4S8U6J4hg1Sx1a/W5hg0LULoROXHys8Nu6Bh3XOR3r1z4h/E7Q7vUfBTppniNBbeJYZm83w9qcZZRZ3a4QNagu+WGFXLYycYBI9F+FXTxf/ANjXqn846X4m/wDIT8B/9jXB/wCkV7XBWr06uNnUlF3d3v3T8jpp05QoKCeit08yX/hbXh//AKBPij/wmtW/+RK82+GPxO0Oy07XVk0zxG5l8S63MPJ8P6nKAsl5IwDFLVgrgH5lPzKeGAORX0zXlfwm/wCQZ4i/7GrXv/S2WuOEqPsZe69119fI2kp86179P+CcH4z+J+h3PiHwLMml+I1Fr4gmlcSeHtTjZlOkalHiNWtQZGy4O1AWChmxtViPQP8AhbXh/wD6BPij/wAJrVv/AJEqbx3/AMjN8PP+xln/APTLqtelUqsqPJD3Xt3835Dgp3lr17eS8z5q+FnxO0Ow8JyW8umeIpD/AG1r0m6Dw9qcyYl1W7cDclqw3AMAy53K2VYBgQIvGHxN0O48b+A7pNM8RKtrqN+7LJ4f1NJHD6dcp+7RrUNIQSCQoJC5YjAJHpXwf/5EuT/sO+I//Txe1F43/wCSgfDn/sKal/6a7quhypfWanuv7fXyfkZJT9lHXt09CX/hbXh//oE+KP8AwmtW/wDkSvM/g/8AE/Q7H4e6bay6X4jdllvSWh8PanMnzXczcPHbMpIzg4JwcjqK+nK8q+Cf/JNNL/67X/8A6WT1hGVH2Evde66+UvI0an7Ra9H09PM881v4naHL8U/Cl8NM8RKlvpOuxsjeH9TWVjLJp5GyM2u91Gw7mUELxuILLn0j/hbXh/8A6BPij/wmtW/+RKZr/wDyWDwb/wBgbxD/AOjNNr1OitKjyQ917d/7z8ggp3lr17eS8z5v+E/xP0Ow+F/hGyl0vxHI9voenRs0Hh7U5oiyW6AlJI7Zkdc9GUlSOQSKZf8AxO0N/ixoWoDTPEeyLw7rULIfD2piYtJdaYwKxm13sgCEMwBVSVDEFlz6V8Gv+SR+Cv8AsX9M/wDSaOotS/5LN4e/7FjXv/SzSa2cqX1ip7r+118n5GaU/Zx17dP+CZmr/FfQJdJvYxpXiZd9vKuW8N6qFGUPJJtOB71zHwx+KOh2Xw28J2cul+JHeDQ9NiZofD2qSxsUtowSkiWrI6nHDKSCOQSK901z/kC6h/16zf8AoBrk/hN/ySvwZ/2L+l/+ksdYqVH2D917rr5PyNGp+0WvTt/wTyaX4naGfjBa6h/ZniPYPDVzDs/4R7U/OybuBt3l/Zd5TjBbG0HjOSK3fHvxT0K58C+I7aPSvEqtLpN8imTw7qkaAtA4BZ3tQqj1LEADknFdRN/yW60/7FW6/wDS2Cui+Iv/ACT7xP8A9gbUP/Sd61cqPPT919Ovn6E2nyy1/A4Hwn8VdBg8LaNA2leJmMen2qFk8Oaq6ErEoyrC1II9CDg1zdh8TtDT4sa7qB0zxHsl8O6LCEHh7UzMDHdamxLRi13qhDgKxAViGCklWx7h4M/5E/Qv+wbaf+iVrldO/wCSzeIf+xY0L/0s1apjKjep7r27+a8h2n7uv4eT8zz34sfE/Q7/AOF3i+xi0vxHG9xoWoxK8/h7U4YlL28gBeSS1VEUE8sxCgckgV6B/wALa8P/APQJ8Uf+E1q3/wAiVP8AGX/kkXjb/sXtU/8ASaSvSazlKj7GPuvd9fJeQ0p8716Lp6+Z80aL8TdDi+Kfiq/OmeImS40jQo1RfD+ptKpik1DJeMWu9FO8bWYANg7SSrYZ8XvidoeofD7UrSLTPEUTPJZkNP4e1OGMbbqFjl3tVUZA4yeTgDkgV6RoH/JYPGP/AGBfD3/o3U6Z8bP+Saar/wBdbH/0sgrojKl9ap+6/sdfJeRm1P2Ute/T1Jf+FteH/wDoE+KP/Ca1b/5ErzPwr8TtDh+Ivji7bTPEZW5bStqp4f1N5F2WuDvRbYsmT93cBuHIyOa+nK8o8If8lO+IH+/o/wD6SGsKMqPJU917d/7y8jSanzR169vJ+Z4d+0345svFnwM8U+G9G0fxE19qMNrb26z6BqNtG0r3UO1TJNbJGpY8DLDJIA5IFfkT/wAM4fHr/oQPEH/gBL/8TX71/Gf/AJEGb/sJ6J/6c7WvU69rLOIJZfhuWjC6lJ7vyXaxw4rLliat6ktktvmfy5+I/DPiDwfq82geKdPuNK1K3CGW1uozFMgkUOu5WwRuUgj2INYdfWn7cP8Aycv4p/65aZ/6Q29fJdfqGCruvh6daSs5JP70fJ4imqdWUF0bR//Syf2jdb1Lw5+1B4t8QaPL5F/p2uLc20u0NsliWNkbDAg4IBwQRVn/AIbK/aO/6G+b/wABrf8A+NVz/wC1R/ycN47/AOwq/wD6AteAV+34TB0K2FpOtBS91bpPoj4OtXqQrTUJNav8z6Osv2tPj9p1zf3dl4plim1S4W7u2FvAfNmWGK3DHMZAxFDGuBgfLnGSSfRfhr+0N8afiv8AEjwl4C8X+KrqXS9T1zThN5EVvFKrRXCSxujiLKsropB9vSviyvTvgv4m0jwX8WPCfizX5Gi07SdVtru6dEMjLFE4ZiFXJJx2FPFZbhlSlKnSjzWdtFe9tLaBSxVXnSlN2vrqf0Cf8Kuuv+h28V/+BsH/AMjV5v8AD34cT3OoeM1Pi7xLGYfEs0RaK8iQyYtLQ7nxBgvg4zgZAHfk8p/w3l+zn/0FtQ/8F0/+FbPwj+MGn6/aeJfFHhbw7r+uaRrWv3F3Z3llbQ+WyC3t4WUrNPG6srxMCCvoRkEGvy76tj6VKbqwcdt0l18z6z2uHnJKEr+juX/iV8OrqzfwkY/F/iV2m8TWEQMt3DLs3LL86q9uV3jHBIOPSvTP+Faat/0P3iv/AL+2H/yDXmfxJ+It1cP4Tebwf4ltUg8TWExaW1gO/aso2Isdw7M5zwAOxr0v/ha8P/Qp+K//AAUSf41jUWJ9nCy79i4ulzP/AIJ538Mvh9ql3ompyJ428S2wTxF4gi2wyWIVjHqdypc7rJiXkI3Oc43E4AGAJfGXw81OHxH4Eibxv4mmNx4gnjV5JbLdCRo+pvvj22QG4hSh3BhtZuM4Ig+GPxMis9E1SM+GPE02/wAR+IJd0Olu6gS6ncvtJDcOudrL1DAipvGXxNin8R+BJR4Y8TJ9m8QTylZNLkVpM6PqabYwT8zDfuIH8IY9q1ksT9Ynpp73RdmSnT9mte3c9B/4Vpq3/Q/eK/8Av7Yf/INeb/Cb4f6pe+CILhPG3iW1Bv8AVl8qCSxEYKahcqSA1kxyxG5ucbicADAHo/8AwteH/oU/Ff8A4KJP8a82+EvxLisPBENs3hnxLOV1DVm3waY8kZ36hctwwPUZwR2IIPIrGKxPsZadV0XZlt0+da9H38hfF/w/1SDxx4Etm8beJJTc6hqCiWSSxMkJTT7ht0ZFkACwG05DAqTxnBHpP/CtNW/6H7xX/wB/bD/5BrzXxf8AEqK48b+BLseGvEsf2XUL9jHJpjrJJv065X92pPzlc5YDoOa9J/4WvD/0Kfiv/wAFEn+NOssTyQsunZd2EHSvLXr59kfI/wAPv2Kvgv448KWvivxH/a9xqWozXktzKL0JvcXMq7sCPAJA5x3rrdB/Zj8C/Cf4o+H4Ph1qet6HJrenasl3PDcwyyslsbVkVTPBIqjLnOFyeOa7/wCD3xLjsfh3pVq/hfxNKyNd5eDTGljO65lPDqxBxnBweDxTvEHxMjl+J/g+8HhjxMogsdaUxtpjrI/mC05RC2WC7fmI6ZGetd9XF5jKtUpym3H3tL6bO2hzRo4ZQjJJX0/Q9L/4Vpq3/Q/eK/8Av7Yf/INeefCb4ay33ws8H3v/AAl3ia38/QdNk8mC+RIo99tGdqL5Jwq5wBk4Fehf8LXh/wChT8V/+CiT/GvPvhL8TYrH4WeDrJvDHiaYwaDpsZkg0t5In2W0Y3I4OGU4yCOorz4rFeylp1XRdmdL9lzr0ffyILv4bSj4u6VZf8Jd4mO/w5qcvnG+TzV2Xdiu0N5PCNuyRjkgeldprXwvmi0a/kHjLxUxS2mbDX8bKcIeoMGCPauMu/iZEfi7pN9/wjHiYBPDmpxeUdLfziWu7FtwTOSg24LdASB3FdrrHxShm0i+h/4RbxSm+2mXc+kyBVyhGSc8AdzV1PrXuenl3ZMfZe9/wex8x+Bv2GfgV4j8E+H/ABDqcWrG81TSrK9uCl9tUy3EKSPgbDgbmOB2r4p/bK+BngX4H+IPDen+Blu1h1WzuJrgXc/nnfFIqqVO1ccHmv1N+GfxPitPhv4UtD4X8TymHRNOjMkOlyPG+y3jG5GBwynGQR1Ffnd/wUE8Tr4m8UeEJl0rU9LEFhdrjU7U2rSFpUOUViSQO5xjn64+kyPF4+eZqFabcPe0b02djy8woYeOFcoRV9D890do3WROGUgj6ivpaP8AbB/aKhjWKLxfOqIAqqLe3AAHAA/dV8z0V99XwtGtb20FK3dXPnadapD4JNeh3vxC+J3jj4qarb61481N9VvbW3FrFK6IhWEMzhcIqj7zsc4zzXBUUVpTpxhFQgrJdiZScnzSd2FFFFWSdD4R0u21zxXoui3u4W+oaja2suw4by5pVRtpwcHB4OK/a3/h3/8As+f88dY/8Dz/APG6/F3wFMbbxz4duBG8xi1axfy4gDI+2dDtUEgFj0AyOa/om/4WvD/0Kfiv/wAFEn+NfEcW4nGUp01hZNaO9nbse9k1KjOMvapPY+QfDP7D/wADdV8V+L9Iu4tWNvot9Z29qFvcEJNYwXDbjs+Y75G/DArS8XfsafB74d6XbeMfCjaxaatp+raR9mn+27zG02oW8JYAx43BXOM9Dg17F4P+JkcHjbx7cHwx4mcXOpWDhY9Mdnj26dbJiRQ2UJxkA9VIIp3xZ+Jkd74Le3Xwx4mhP9qaK+6bTHjT93qVq+NxbGWxhR3Ygd6+c+vZm68IupKz5b6+Suep9XwqptqKvr09T0f/AIVXL/0Oniz/AMGCf/Ga8/8ABfw0kn8QeOox4u8Tx/Z/EEUZaO/QNJnSdNfdIfJ5b5tuePlUDtk+g/8AC14f+hT8V/8Agok/xr5yH7WXwo+GvjTxrpPjddX0q+vtZt76O2m0+QSrA2l2EKl1BO0loWwD2we9cOGpY2opxhFt26JPqjoqzoRs5Oyv+jPRfif8NpbPRtJf/hLfE0/meJNAi2zXyOo83Ubdd4/cjDpncp7MB1HFej/8Krl/6HTxZ/4ME/8AjNfJ3j/9tn4D+IdL06102/1BpLXXNGv5A9jIv7myvoZ5SD6iNGIHc8V3P/De/wCzv/0ENT/8F8ldEsBmnsopUpXu/s+nkZLEYTnfvrp19Trvh18Npbi78YwDxd4mhW08S3MS+VexoX3W9tKWf9z8zlpDk+mKb8SfhtNZS+EpV8XeJpXbxNYwqZb6N/L85Jo2ZP3PD7WIB7ZrN+D3xo0HXrTxP4m8PaL4g1XS9Z8Q3F3aXVnpskkbR/Z7aIg8gqyvGwIP16EGtP4l/EuO7PhTb4X8TR+T4m06Y+bpjx7gnmfKm5huc54UcmpccUsTaS/LsUnRdK6/rU9L/wCFVy/9Dp4s/wDBgn/xmvOPhh8NJLvR9XmHi3xNAR4k1+IiG+RQ3k6jPHvb9ycuwUFj3Oeg4HpH/C14f+hT8V/+CiT/ABrzn4Y/EyOz0XVY28MeJpt/iPX5g0OmPIoEupXD7SQ3DrnaynlWBFc0frXspeq7eZo/Zc6+ffyJfGfw1kg8Q+BIv+Eu8TyfaPEE0W6S+QtFjSNSfdGfJG1js255+VmHfNegf8Krl/6HTxZ/4ME/+M15/wCM/ibFceIvAko8MeJo/s/iCaUrJpcitJnSNSTbGCfmb592B/CGPavQf+Frw/8AQp+K/wDwUSf40qv1rlhbt5d2OPsrv/g9kec/Cz4bS3vhKSf/AIS3xNB/xOdeTZDfIiHy9Vu03Y8k/M+3c3qxJwOlQ+K/hvNH8QfA1ifF3iaRZ59TkDvexmSN4rNgDG3k/LlXYH1Bqf4WfEuKx8JyW58M+JZ/+J1r774NLkkT95qt2+Mg/eXdtYdmBHaofFXxKin+IXge8HhnxKgtpNUzG+mOssnmWpH7tScvt/ix0Bz0rof1n6xPt73bszJey9lH5d/I9K/4VXL/ANDp4s/8GCf/ABmvM/g98NZbz4eaZP8A8Jd4nhzJershvkRBsu5lyB5PU4yfUkmvTf8Aha8P/Qp+K/8AwUSf415p8IPiYlj8PdNtX8L+JpWSW9JaDTGljO67mbh1YqcZwcHg5FYR+texl6rt2kaP2XOvR9/Idr/w7vLT4neELe28Y+JVe6sdaQzvdW80qIn2RyqGW2dVDEDd8uTgcjnPpX/CtNW/6H7xX/39sP8A5BrzPxF8TI5fid4Nux4Y8TKILTWgY20x1kfzFtuUQtlgMfNjpkZ616X/AMLXh/6FPxX/AOCiT/GissVyQ06dl3YQdK8vXz7I4D4T/DzU7v4X+EbqPxv4mtVm0PTnWCCWyEUQa3QhE32TNtXoNzE46knmkv8A4cXjfFTQ7S48Z+Jpi3h/WZFmNzbRSptutNBRWitY/kfcCwIPKrjHOT4T/E2Ky+F3hGzbwv4mmMGh6fGZIdLeSJ9tug3IwOGU9QR1FF98TYm+KeiXv/CMeJgI/D+sxeUdLcSnfdaa25UzkqNuGPQEgdxWslifbz0/m6LzITp+zj8u512sfC6aPSb2QeMvFTFbaVsNfxkHCHqDBgj2rmPhj8NJbv4beE7seLvE8HnaHpsnlQ36LHHvtoztRfJOFGcAZOBXU6t8U4ZtKvIv+EV8Upvt5V3PpMgVcqRknPAHeuX+GPxOis/ht4TtD4X8TzGDQ9NjMkOlyPG+y2jG5GBwynGQe4rJfWvYvvdduzLfsudenmZi/DaaT4wSWLeLvE2IPDUcqS/bY/NHnXbq67/JzsPlKceozW74++GMsHgXxHP/AMJh4pk8vSb59kl+hRtsDnDDyRkHofasWP4lxj4vXGof8Ix4lKt4bgh8oaY/nArdytuKbs7DnAbpkEHHGdzx78UIrnwN4it18LeKIzLpN8gaTSnRFLQOMsxbCqO5PAFaP617SHy7Er2XLL59y34T+GEs/hbRpz4x8Up5mn2rbUv41Rd0SnCjyeAOwrnrH4ZyH4q63a/8Jd4nBTw9o8hmF8nmtvutSAVm8nlV25UdizevHReE/ilFB4V0aE+FfFLmPT7VSyaVIynbEoypDYIPYjrXP2PxNiX4qa1ef8Iv4mIk8P6PF5Y0tzKpS61E7mTdkK27CnoSCO1SvrV6np5d0P8Ade7/AMHsN+LXw2lsfhZ4wvf+Eu8T3HkaFqUvlT3yPFJst5DtdfJGVOMEZGRXoP8AwquX/odPFn/gwT/4zXn3xb+JsV98K/GNkPDHiaAz6DqUfmz6XJHEm62kG52JwqjqT2Fehf8AC14f+hT8V/8Agok/xqJfWvZR9X27Ipey536Lv5nmnh/4bzT/ABQ8YWreLvEym2sNEUSrfRiV1f7Y2128n5gpJ2+m40nxf+G01j8PdSuR4u8TTlJLIbJ72OSM7rqEcqYecZyPfFO8PfEuKH4neMLw+GfEri4stFURppjmWPyxdD503ZUNn5SevOOhpfi98So9Q+H2p2i+GfEsBZ7Mh7jTHij+S6hbBZmwC2MDPGSBXRH6z9Zp9vd7dkZP2XspfPv5npH/AAquX/odPFn/AIME/wDjNeZeFfhrLL8RfHNr/wAJd4mTyH0o+Yl8gkk32ufnbyeduML6CvTv+Frw/wDQp+K//BRJ/jXzdd/tT/DH4Z/FDxhH46h1jR5tUXS5reC4sHEpjityhZkBJUZ6Zxkc9KjC0sbUU4wjd26Jd0VVnQi4uTsr/oze/aS8Iaj4O+CniTxVp3i3xHcXekrZ3cEd3eRzQGWK7gZC6eSNwVgDjpkV+Xf/AA2L+0b/ANDjcf8Afi3/APjVfdPxt/ar+E3xl+GGtfC7wBLqF94i8SC2stOtns2hWWdrmIhS7kKucHknFfBX/DI37Rn/AEJN9/38g/8AjtfYZBQpU8O45pGKld250k7WW1zxcxqTlUTwjbVtbX8zxnxn408S/EHxFc+LPF962oareCMT3DqqlxEixpwoCjCKBwB0rlq6bxh4O8S+AdfuPC3i6xfTdVtBG01tIVLIJUEiZKlhyjA9e9czX2dLk5F7O3LbS21vI8KfNzPm3P/T5H9qX/k4Xx3/ANhaT/0Fa8Br3z9qM5/aE8d/9heX+S14HX7xl3+60v8ACvyPz7E/xp+r/MKKKK7DAK/df9gf/k3ew/7Cmof+jBX4UV6f4V+NPxY8D6Sug+EPFeqaTpySPKttazskQeTliFHAJPWvFz7K54/DewptJ3T1+Z35di44er7SSvof0BfFT/WeDP8AsbNO/wDQJq9Xr8J/gH8Tvid8WfjL4T8HeOfGGuX+mTXrT7BeyRsksMMjRujqQVZT0NfsF/wqay/6GfxX/wCDu5/+Kr81zbKvqLhQrT1tfRd38j6jB4v26lUhHQm+Ev8AyANX/wCxo8S/+na6qfxz/wAjR8O/+xkuP/TJqteW/DL4Y2d7omqSN4i8SwlPEXiCHEOsXEat5Wp3KBiA2C7AZZurMSTyTUvjL4YWdv4j8CQjxH4mcXPiCeItJrFwzRgaPqcm6Mlvkb5NpI52ll6E1yyhS+sT97+bp5PzNVKfs46dup9LV5X8F/8Akn9v/wBhLWf/AE5XVN/4VNZf9DP4r/8AB3c//FV5v8JvhlZ3/giG6PiHxLAW1DVl8uDWLiOMbNQuVyFDYycZJ7kk96xjTpexl7/VdPKXmW5T9otOj6+h6T42/wCSg/Dr/sJal/6bLmvVa+YPF/wzs7fxv4EtB4h8SyC61C/UySavcNJHs0+4bMbFsoTjDEdRxXpP/CprL/oZ/Ff/AIO7n/4qitTpclP3+nb+8/MISneWnXv5IPgj/wAkx0j/AH73/wBK5qd4l/5K14I/7B+vfys68x+D/wAMbO++Hel3R8Q+JoN7XY8uDWLlIxtuZRwu7jOMn1OTT/EHwxs4vid4Qs/+Eh8SuJ7HWm8xtYuDKnli04Rt2VDbvmHfA9K6JQpfWqnvfz9PJ+ZmpT9lHTt19D6frzT4Mf8AJH/A/wD2Lulf+ksdVP8AhU1l/wBDP4r/APB3c/8AxVcD8JfhfpF/8LPB99JrHiSJ7jQdNlZINf1CGJS9tGSEjScKijPCqAAOAMVzRhR9jL3nuunk/M1cp8606Pr6Hod7/wAlq0f/ALFbVv8A0t0+u717/kBaj/16T/8AoDV+Y37bN74j+C1/4P1f4e+JNfsb7UIdStp7ifVbq7kMKtbPsUzyPtUsASFxkgZ6CvhWT9pT49zRvDL471t0dSrK10xBU8EEehFfR4LhirjaFPEUppRt1vfRv1PMr5rChUlTnF3/AOAfv18KP+SW+Dv+wBpf/pLHX5j/APBSr/kbvBP/AGDrz/0alfG1j+0X8c9MsbfTdP8AG+s29raRJBBDHcsEjijUKiqOwVQAB6VxXjL4h+OPiHc213441y91uazRo4HvJTKY0Y5IXPQE9a97KuGK+ExyxU5prXTXrc8/GZrCth/YqLvocZRRRX2h4QUUUUAFFFFAHZ/Dn/koXhf/ALDOn/8ApQlf061/K/aXVzY3UN7ZyvBcW8iyxSodrpIhDKykcgggEGva/wDhpj4//wDQ+65/4FNXy3EWQVcxnCVOSXLffzPXyzMYYZSUle5+8Pgj/kfviL/2FdO/9NdpTvjL/wAiI/8A2FtC/wDTraV+Btt+0L8b7O7vL+18bazFcag6SXUi3LBpnjRY1ZvUhFVQfQAUaj+0N8b9XtTY6n421i5gMkUpjkuWK74XWWNseqOqsPQgV4i4NxHto1PaLTl79Ev8ju/tulyOPK9b/if0iV+BP7b/APycr4p/656b/wCkUFcB/wANMfH/AP6H3XP/AAKavu/9lv4M+BP2jPAOpfEj4x2914j8Rya1NZPfz3cyyPBb29t5atsdQdoYgHrjA7VpgcteRSljcTLmi1y2jvq13t2Jr4pZglQpKz31Pydor9ufiB+x/wDALQLLRptM8OvG95r2lWEpa8uGzBdXKRyAZk4JUkZ6jtzXe/8ADEX7OH/QtSf+B1z/APHK9N8Z4FRUuWWvkv8AM5Vkde7V1+P+Rzv7An/JvNn/ANhXUP8A0Na99+KvXwd/2Nmmf+1K/Gr4x+OfG/wJ+KXiX4afCfxDqnh3w3pl4ptbC2u5DHG0sMbOfmYnLMSTz1rT+AnxQ+JnxX+MvhPwd488W63qWlT3zTND9umhZZYYZGjdHiZXVlPIINeNieH6lWc8zU1yO87dbNX9L/M7qWYxgo4Vx95aeV9j92a8u+Ev/IB1j/safEn/AKdbqm/8Kl0X/oN+Kv8Awo9S/wDkivxd+LXxg+K/w4+KnjDwb4N8Ya1p+k6frl+sEAvZJCC8zM7M7sWZnYlmZiSWJJ5NeDlOU/X+ejQnro9V/wAP3PQxmM+r2qVFptoftX47/wCRm+Hn/Yyz/wDpl1WvSq/D39mn4k/En4u/HHwv4R8feLdc1HTd19dKi380Ekc0VjchXSSJldGwzKSCMqxB4Jr9b/8AhUui/wDQb8Vf+FHqX/yRU5vlawU4UK09bX0Xm/NDweL9vF1ILS/X0Q/4P/8AIlyf9h3xH/6eL2oPGH/JTvh//wBdNY/9JK8/+Fvwx0i/8JyXEmr+JIj/AGzr0e2DXtQiTEWq3aA7UnA3ELlm6sxLMSSTUXi/4Y6Pa+OPAkCav4jb7Xf6hC8j69qDyIi6fcSYjczkpuZF3FcEgYPGawcaX1mp7z+308n5mic/ZR07dfQ+nK8q+Cf/ACTTS/8Artf/APpZPTv+FS6L/wBBvxV/4Uepf/JFebfB/wCGOj6j8NNAv5NX8SQyXNsZXWDX9Qij3u7MxCLOFG5iScdyTWEYUfYS957rp5S8zRuftFp0fX08j0fxP/yVnwN/15a7/wCgWteq18x+IfhjpEPxM8HWQ1fxGy3NprLF317UGlQxrbY2OZ9yA5+YA4bjPQY9J/4VLov/AEG/FX/hR6l/8kUVoUeSn7z27f3n5hBzvLTr38l5Fr4Nf8kj8Ff9i/pn/pNHRqH/ACWDQP8AsWtc/wDSvSq82+FHwv0i/wDhf4RvpNY8SRPcaHp8rJBr+oQxKXt0JCRpOFRRnhVAAHAGKZf/AAx0hPivoWnDWPEhSXw9rUzOdf1AzBorrTFCrIZ9yoQ5LKCAxCk5KrjaUKX1ip7z+109fMzTn7OOnbqfQOuf8gXUP+vWb/0A1yfwm/5JX4M/7F/S/wD0ljrnNX+FGixaVey/214obZbyttfxFqRU4QnBH2jkHuK5f4ZfC7R734beE7yTWPEsbT6Hp0rJDr+oRRKXtoyQiJOFRRnhVAAHA4rFQo+wfvPddPJ+Zo3P2i06d/TyO3i/5Lddf9irbf8ApbPXRfEX/kn3if8A7A2of+k714rJ8MdHT4vwaeur+JAsvhueZ5P7f1DzmMV3EqKZPP3bBvYhc4ySetanxK+GGk6f8OvFV/BrXiZpLbRNRmRZfEGoyRlo7eRgGRpyrLkcqQQRwa1cKTq0/efTp/wSOaajLTv1PZPBn/In6F/2DbT/ANErXNaf/wAlg17/ALFrRP8A0r1SsLRPhLoX9jWHl6x4niX7LDtSPxDqSoo2DAUfaOAOgHpXH2Hwx0h/ivrmnHWPEgSLw9o0yuNf1ASlpbrU1IaQT7mQBAVUkhSWIwWbMRjRftHzPbt5rzKbn7un4+T8j0r40/8AJH/HH/Yu6p/6SyV6ZXzX8WvhhpGn/CzxhfR6x4kle30LUpVSfXtQmiYpbyEB43nKupxyrAgjgjFeg/8ACpdF/wCg34q/8KPUv/kiolCj7GPvPd9PJeY058706Lr6+Q3wz/yVrxx/146D/wCg3dHxs/5Jpqv/AF1sf/SyCvOPD/wy0ib4m+MLE6v4jVbay0Vg6a9qCyuZBdZ8yQT7nA2/KCcLzjqc5nx6+HWm6F8G/F+t2eseI3ubDS5rmAXGvahPGJYcOjGN5yrbWAYZBGQK6oQpPF01zP7HTyXmZOU/Yy079fU+r6/Cj9vj/k4i/wD+wZp//os15D/w0x8f/wDofdc/8Cmr7d/ZV+FXhD9pTwxrnjn41R3fibXbfUls0vbi8nWT7OkKFUOxwCFJOOO9fVYLKpZHN47Ey5o2tZb6td7HkV8Wselh6Ss99fI+A/gb/wAll8Ef9h/Tv/R6V/SpXw546/ZP+CHgbQU8U+FtFnsNUstS0kW9zFf3IkiM1/bxMynzMq2xzhhgg8ggjNfSH/CpdF/6Dfir/wAKPUv/AJIryOIszw2YOnWhdJXWqXk+/mdmW4WrhlKErPZ/1ofi9+3D/wAnL+Kf+uWmf+kNvXyXX0/+2NpEGhftCeJNKtp7q5jhi0/Et7cy3dw2+zhY75pmeRsE4GScDAHAFfMFfpGU2+pUbfyx/I+Yxn+8Tv3f5n//1ON/ahOf2g/Hn/YYm/kK8Fr3j9p85/aC8ef9hmf+leD1+85f/utP/CvyPz7E/wAafq/zCiiiuswCiiigD6J/ZQvbjTvj94TvbWxuNSlinmK2tqYlmlzBIMIZ5IYsgHPzOvA45wD+63/Cd+Iv+if+Jf8Av7pH/wAs6/Dn9jz/AJON8G/9fM//AKTy1/QfX5nxpOMcZBOKfu+fd9mfVZFFug7Pr+iPnD4YeM9ettD1RIvA/iC5DeI/EMheKTSgFaTU7lih36ih3RklWwCu4HaWXBMvjPxpr0viPwHI/gfxBCYfEE7ojyaVumY6PqabE26iw3AMX+cqu1Tzu2q3dfCX/kAav/2NHiX/ANO11U/jn/kaPh3/ANjJcf8Apk1WvnZVYfWJ+4vtd+z8z01B+zj73bt3D/hO/EX/AET/AMS/9/dI/wDlnXmvwj8Z69a+B4IYvBHiC6Uahq582GTSghLahcsQPM1FGypO08YyDgkYJ+k68r+C/wDyT+3/AOwlrP8A6crqsI1Yewl7i3XftLzLcH7Re90fby8jz/xh4z16Xxz4CmfwR4giaDUNQKRPJpW+Ytp1wpCbdRZcqDuO8qMA4JOAfS/+E78Rf9E/8S/9/dI/+WdU/G3/ACUH4df9hLUv/TZc16rRWqw5KfuLbz/mfmEIPml73Xy7LyPmn4OeNNetvhzpUEXgfxBdKrXeJYZNK2Nm6mPG/UUbjODkDkccc07xD4z15/ih4OuG8D+IEeKx1sLC0mleZKHFpkpjUSmEwN25lPIwDzjvvgj/AMkx0j/fvf8A0rmp3iX/AJK14I/7B+vfys66JVYfWqnuL7ffs/MzUH7KPvdu3dFv/hO/EX/RP/Ev/f3SP/lnXnvwk8aa9a/CvwdbReB/EF2kWgaYizwyaUI5VW2jAdPM1FH2sORuVWx1APFfRdeafBj/AJI/4H/7F3Sv/SWOueNWHsZe4t137PzNXB86957Pt5eR+an/AAUO13UdaTwQb/QNS0LyjqIQag9mxm3eRnZ9kubnG3Azu29RjPOPzNr9Vv8Agpf93wD9dU/9tq/Kmv1bhdp5bTaVt/zZ8fmytipfL8kFFFFe+ecFFFFABRRRQAUUUUAFFFFAHtfw1/Z5+LXxc0i413wDoy6lZWs5tpZDdW8G2UKG27ZZEY/KwOQMV2Os/seftBaBYnUtW8NpBbCaCDf9vtG/eXMqQRDCyk/NJIq56DOTgZNff3/BOL/klPiH/sOt/wCiIq+vPjL/AMiI/wD2FtC/9OtpXwOO4oxdHMJYWEY8qaWzv+Z9Fh8po1MOqzbvb+uh+LP/AAxF+0p/0Kqf+DGy/wDj1foH+yFp3jr4Q/D7W/AXiHwZq17qdh4gme5Onz6a8MTT2dnKiFpr6ElvLZWO0FcMBnIIH3rXmngP/kZfiH/2M0P/AKZdKrwcZxJiMdQlSrxjZWel+6XfzPRoZXTw9RTpt326f5Hm3xP8Z69cWGgCTwR4gtgniXRZAZZNKw7JdoRGuzUXO5zwucLnqQOa9L/4TvxF/wBE/wDEv/f3SP8A5Z1U+LP/ACDvDn/Y1aF/6WR16pXjTqw9jD3F17+Xmd0YPnfvdu3+R+J/xk/Z6+NHxp+LPi3x14M8Ly/2fPqRtil3eWUU0c1vFGkiOouHXII6qzA9jS/Bv9nz40fBX4s+E/HXjPwtMdPh1EWqx2l5YyzyTXMUiRoqtcIvJPVmUADrX6s/Crp4v/7GvVP5x0nxV6+Dv+xs0z/2pX0n+suJt9R5Y8luXre1vU8z+y6V/b3fNe/Tv6F7/hO/EX/RP/Ev/f3SP/lnX5A/Eb9mn44fFn4j+LvHvhPwu503Ute1Lyxc3tlFMjw3DxSI6i4YBkdGU4YqcZBIwa/cevLvhL/yAdY/7GnxJ/6dbqvKyvN54JTrUIK+i1v5+fkdWLwca9oVG7b9P8j8uP2f/gH8Zvgh8afCnjLxn4Vne0kmvbGGGyvLGWeWeWwunCqGuY0GEjdiWdRhSBliAf1P/wCE78Rf9E/8S/8Af3SP/lnR46/5Gb4ef9jLP/6ZdVr0mpzXNZ4ycK9eCvbz7vzKwmEjQi6cJO1/LsvI+cPhX4z1618JSRReCPEF0v8AbWvv5kMmlBMvqt2xT59RRtyElG427gdpZcMYvGPjPXpfHHgGZ/BGvxNBqWoMkTyaVvmLabcqVTbqLLlQdx3lRgHBJwD6J8H/APkS5P8AsO+I/wD08XtReN/+SgfDn/sKal/6a7qsnVh9ZqLkX2+/Z+ZSi/ZR17dvIuf8J34i/wCif+Jf+/ukf/LOvM/g340161+GHh23i8D+ILpEswBNDLpXluNzcrv1FGx9VB9q+la8q+B//JJvDH/Xkv8A6E1YRqw9hL3Fuu/aXmaOD9oveez7eXkef+I/GevSfE/wZcN4H8QRvFaa0FhaTSvMlDrbZKY1EphMfNuZTyMA849M/wCE78Rf9E/8S/8Af3SP/lnVPxP/AMlZ8Df9eWu/+gWteq0q1WHJT9xbef8AM/MIQfNL3nv5dl5Hzr8JvGmvWvwu8IW0XgfxBdJFoenIs8MuleXKFt0AdN+oo+1uo3KrY6gHimah4z15vizoN0fA/iBZE8O63GLcyaV5rq93pZLrjUSm1CoDZYNll2gjcV9E+DX/ACSPwV/2L+mf+k0dRal/yWbw9/2LGvf+lmk1u6sfrFT3F9rv2fmQoP2cfe7dinrHjnxC+kXyHwD4jQNbSgs0ukYGUPJxqROB7CuX+GHjXX7b4a+EreLwN4huUi0PTUWaKTShHKFtowHTfqKPtbqNyq2OoB4r27XP+QLqH/XrN/6Aa5P4Tf8AJK/Bn/Yv6X/6Sx1gqsPYP3Fuu/Z+Zbg/aL3unkeVzeM9e/4XFaXX/CD+IN48M3Mf2fzNK80qbyA7/wDkI7NoPH3t2e2Oa0/id411+5+G3iy3l8DeIbZJdD1JGmlk0oxxBraQF32ai77V6narNjoCeK62b/kt1p/2Kt1/6WwVq/Fj/klnjL/sX9U/9JZK3VWHtKXuLp37+pDg+Sfvd+xh6L458Qro9io8A+JGAtoRkS6Rg4QcjOp1xlh4z15fi1rt0PA/iBnfw7osbW4k0rzUVLvUyHbOohNrliFwxbKNuCjaW960P/kCaf8A9esP/oArhdO/5LN4h/7FjQv/AEs1asqdWH7z3Ft5915luD933vy7PyOB+LnjTXrr4VeMbaXwP4gtEl0HUkaeaTSjFErW0gLv5eou+1Rydqs2OgJ4r0P/AITvxF/0T/xL/wB/dI/+WdM+NP8AyR/xx/2Luqf+kslemVMqsPYx9xbvv2XmNQfO/eey7efkfNXh3xnr0fxQ8ZXC+CPEEjy2WiBoFk0rzIggusF86iEw+fl2sx4OccZyf2g/GOuX3wS8a2lx4K16wjl0e5Vrm4k0swxAr95xFqEkmB/sox9q9W8M/wDJWvHH/XjoP/oN3WL+0p/yQTx3/wBgS6/9BrrpVYfXKS5F9jv2XmYyi/Yy1/m7eZ/ONX6EfsjftR/Dj4GeCtW8O+MrfVZrq+1H7XE1hbxyxiPy1TDF5oyGyvoRjvX570V+u4/AUsZRdCtt5HxeHxE6E/aQ3P2D+If7d/wW8U+F5NG02015Z2vNOuAZbSFU2Wl5BcPyLgnJSM445OOnWu2/4eIfAj/ny8R/+AUH/wAlV+I1FeI+EMvcVCzsvPvb/I7/AO2sTe+n3Huv7SXxI8P/ABa+MOtePfC6XMem6ilmsS3aLHMDb20ULblVnUfMhxhjxj6V4VRRX0eHoxo0o0obRSS+R5lSo5zc5bs//9Xif2nTn9oHx5/2Grj+YrwmvdP2mzn9oDx7/wBhu5/nXhdfvOX/AO60/wDCvyPz3E/xp+r/ADCiiiusxCiiigD6I/ZR0u11r4++FNLvWnWC4nmVzbXE1pLgQSH5ZoHjlTpyVYZHHQkV+6X/AAqLwf8A89/EH/hS6z/8m1+AnwG8f6T8LvitoPjvXIZ7iy0qSWSWO2CtK2+J0AUMyjqwzk9K/T//AIeN/CT/AKAOu/8AfEH/AMdr4PinA4+viYywsW1y9H1uz6HKcRh4UmqrV79T3f4Y/C7wtfaHqks8+uAx+I/EEKiPxBq0S7IdTuUXIjvFBYgfMxG52yzEsSTL4y+FvhW28R+BIY5tcK3XiCeKTf4g1aRgo0fU5PkZrwmNtyD5kKsVyudrMDzXwR+JfinxH4GbxJ4X8FXeoaXrGsa1qNrO9/Z27GO71C4mCtG8m4Mm/ae2QcZGDW74y8XePn8R+BJLrwHdxmHxBO8UcepWMjzOdH1Ndi5lVVIVmclmAwpAyxAPytRYlYmac/5vtLs/M9eLpOlFqPbp/wAA9I/4VF4P/wCe/iD/AMKXWf8A5Nrzb4S/C/wtqHgeC6uZ9cEjX+rKfK8QatCuI9QuUHyR3arnAGTjLHLHJJJ9D/4Tjx5/0TnV/wDwYaV/8m15v8JvGPjO18EQQ2ngPVLyIX+rMJkvtMQEtqFyzLh7tWyjEqeMEjIJGCcI/WfYy9/qvtrs/M0fsude70fR+XkSeMPhf4Wt/HPgO1jn1zy7vUNQWTf4g1Z2wmn3DjY7XZaM5HJQgkZByCQfSv8AhUXg/wD57+IP/Cl1n/5Nry/xb4x8ZT+O/Apk8B6rDPb3eozxQte6YTOosZYnCst2VUr5it8xGRnHPFelf8Jx48/6Jzq//gw0r/5NorfWeSFp9P513fmEPZXl7vXs+y8jzj4O/C3wrf8Aw60q6uJtcDu12CIvEGrQp8tzKowkd4qDgdhyeTzXyp+3Rb3fwmsfBmteANY1zS766uNRgkuDrWoXMnlbICVU3FxLsBP3tuN2BnOBWp4N/bo+HXw88Pw+C9c0PWW1DSp7uG58kQMgkNxIzKG83naWxnoccV80ftb/ALTHg/4+6X4bsfC+n39k+jXF1LMb0RgMJ1jVdux26bDnOO1fTZZluPWZKpWi/Z3e70tZ26nlYvFYf6q4wa5rL16Hzz/wvj41/wDQ9+If/Blcf/HKrWfxt+MGn2kFhYeNNdtra2jSGGGLUJ0jjjjAVURVcBVUAAADAFeX0V9/9Uobci+5f5Hzvt6n8z+867xP4+8b+Nlt08Ya9qOtC0LmAX9zJceUZMbtnmM23dtGcdcDPSuRooraEIwXLFWRnKTbuwoooqhBRRRQAUUUUAFFFFAHT+CbC01XxloOl6hH5treanZ288ZJXfHLMiuuQQRlSRkEGv3p/wCGOv2a/wDoSbb/AMC7z/4/X4OeAZJIfHfhyWKJp3TVrFliQqGkInQhQWKqCegyQPUgV/RP/wAJx48/6Jzq/wD4MNK/+Ta+F4wrYmFSl7Co46P7XL280fQZLClKM/aRvt0v+jPJ/hx8Ffh54f8AGPjbw34ftNQ0rS7KfTXgtLDWNStYlee1DSMVhuk3MxHJbJ7dK3Pir8MvC9l4Rjmhl1os2taBERJr2qyrtm1W0jb5Xu2XO1jtbGVOGUhgCKHhTxj40j+IXjmePwFqksssul+ZCt9pgaHbaALuZrsKSw5G0nA64PAn+KXjHxpc+FIorrwFqlpH/bWgP5j32mONyaraMqYS7Y5kYBFOMAsCxC5I+UcsS8TBup/L9pdl5nsJUlSklHv09fI9P/4VP4S/57a7/wCFFq//AMm1554K+GXhe58Q+O4pZta223iGGKPZr2qoSp0jTX+dluwXbLn5nLNtwudqqB3H/CcePP8AonOr/wDgw0r/AOTa8+8F+MfGsXiDx08PgHVJ2m8QwvKi32mAwONJ01fLYtdgFiqh8oWXDAZ3BgOal9Z5J+/0/nXdeZrP2d17v4Ps/If8UPhl4YstH0eaCbWt7eJNAhPma9qsoCzahBG+A92wDbWOGGGU8qQQDXpP/Cp/CX/PbXf/AAotX/8Ak2vLvid4x8Z3GjaSl14D1S0C+I9AkRnvtMcPImo27LH8l2xBkI2gkbQSNxAyR6N/wnHjz/onOr/+DDSv/k2nP6z7KPv9X9teXmJez537vbo/PyPPvhz8MvC9ze+M4ZJtaCWvia5iiCa9qseFNtayHO27G5i7sSzZY564AwnxG+GPhe3v/BUMcutFLrxNbxSB9e1WT5Ra3Ug277s7GDIpDLhhjGcEgwfD3xj4zg1Dxm1t4D1W5MviSaSULe6YphkNpaAxtuuwGIAByuVwRznICfELxj4zn1HwU1x4C1S3MXiWGSMNfaYxmcWd2BGu27IBIJOWIXAPOcA9H+0e3+Pp/Mv5fUj937P4fw8/Q9V/4VP4S/57a7/4UWr/APybXm/ww+Gfhi90XVpJ5taBj8SeIIV8vXtViGyLUrhFyEu1BbA+ZiNzHLMSxJPe/wDCcePP+ic6v/4MNK/+Ta86+GXjHxnb6LqqW3gLVLpW8R6/IzJfaYoR31K4Zo/nu1JMZJUkDaSCVJXBPPH6z7KXv9V9tefmaP2fOvd79H5eR4Z+2zoq/DT4V6V4r8Fanren6tD4ht4ork61qNw0ay2t2r7BPcyKrMuV3ABtpIzgkH8vP+F8fGv/AKHvxD/4Mrj/AOOV+rH7WOjfEr4y+BtC+H2l+DbrSb7UPEET20t/f2Bhd7eyvJWTMFxKwJjRmBIC/LjOSAfhj/hgz9oz/oE6f/4MYP8AGvt+H8ThKeDSxs4813u03b8TwcxpV5Vm6CdvK6P0a/Zh8EaP4r+BfhbxLrt3rU+o6lHd3N1KmuanAJJpLucu5SG6RAzHliFGWJJ5JJ6/xj8M/DFv458A20c2tbLnUdQSTdr2qu2F065cbWa7LIcqMlSCRkE4JB+SfhZ+1/4J+A3gXTvg94x0XVZdb8KNdWF81p5MkHnrcSswRjKNwG7Gcc4q/wCIf29/hdrHiXwtrkOja0keg3l1cTIyQ7pFuLOe3AXEuMhpATnHGe/B8KrluZyxVSpTjLkfNbXSzva2vpY74YrCqlGMmrq1/wALn3n/AMKn8Jf89td/8KLV/wD5Nr8EvEnxa+KfhbxJq/hvw94w12w0zTNQu7W0todRuBHDDFM6oi/vOgAx61+ln/Dxv4Sf9AHXf++IP/jtfj94o1SLXPEura1bqyRahfXN0it95VmkZwD7gGvb4Xy7FU5VPr0HbS3Nr39TgzbFUpKPsJa67H3Z+xrrnib4ufF2bTPiJ4g1zWILDR7qe236tewSRSNJCrFZIZ45AGHDDdg4GQcDH6o/8Ki8H/8APfxB/wCFLrP/AMm1+Hv7K/xm8OfA34gXni7xNa3d3bT6bLZpHZqjP5kkkbAneygKAh75zX6Df8PG/hJ/0Add/wC+IP8A47XFxFlmPni74SD5LLbRfob5bisPGjatJc1+p778I/hl4Y1D4V+D764m1oS3GhadK4i17VYYwz28ZO2OO7VEX0VQFA4AApNQ+GfhhfizoNgJta8mTw7rczZ17VS4eO70tRtkN3vVSHO5QwVjgsCVUit8I/GXjS3+Ffg+3tPAWqXkEehackdxHfaYiTItvGA6rJdq4DDkBlDY6gHii/8AGPjRvixoVyfAWqLOnh3Wo1tjfaZvdHutMLSBhd7AEKgEFgxLjaCAxHzr+sfWJ+//ADfaXZ+Z6a9n7OPu9un/AADsPFHwu8L2vhnV7qC411ZIbC5kQ/8ACQ6ucMsTEHBvCDyO/FZvw++FfhObwF4amaXWlL6PYMVj1/Vo0BMCHCol4FUegUAAcAYq34k8YeO7vw7qlofh5q0YmsriMub/AEohd8bDJAvMnGc8V8j+GP8AgoH8LPDvhrSfD91omtyTaZY21nI6JBtZ7eNY2K5lzgleKrD4XH16TVFuTT6Sv08mKpWw9OadTTTqv+AfSMvwy8Lj4x2tj52teU3hm5lP/E/1XfuF5Av3/te8DB5XO0nkjIFbvxA+FfhOHwH4klWXWmKaRfsFk1/VpEOIHOGR7xlYHuGBBHBBFeHfDP8AaRsvjN8TLjxD8PPCmr6iukaE9ndwvLZW7obm5jkRwZrhFYHy2BAJINe0+PfGnjibwL4jil+H2qwI+k3ytK9/pZWMGBwWIW7ZiAOTgE+gJp1aWMpVoQqSs1a6cknv2uEJ0ZQlKKuten/ANjwr8L/C934X0e6nuNdaWawtZHP/AAkOrjLNEpJwLwAcnsMVzlj8MfC7fFXW7Iza15aeHtHlBGvaqHLPdakpy4u97KAo2qSVUkkAFmzseFPGvjiPwto8cPw91aaNNPtVSQX+lqHURLhgDeAjI5wea56x8ZeNR8U9buR4B1Rpn8P6OjW4vtM3oi3WpEOWN3sw5YgAMWypyANpOC+s3qe/0/mXdeZf7v3fd/B9vQs/Fr4Y+F7L4WeMLyCbWjJBoWpSIJde1WVCy28hAaOS7ZHX1VgVI4IIr0L/AIVP4S/57a7/AOFFq/8A8m15p8WfGfjSf4W+L4bzwFqlnBJoWorJcSX2mOkKG3kBdlju2chRyQqliBwCeK8J/wCHjfwk/wCgDrv/AHxB/wDHa2o4PMK9FewvKzd7Sv0VtmROvh6c/wB5ZadV6nzb+2br/if4S/FyDTPh54g1zR4L7R7We5CatezPLIskyqWkmmdyFH3RuwMnA5OfmHQPiv8AFDxbr+l+F/Evi7XNR0nVr61s720n1C4aKe3nlVJI3Hmcqykg11f7VHxn8OfHL4gWfi3wza3dnbQaZFZvHeKiyeZHJIxI2MwKkOO+c54rxDwLI8Xjfw9LHG0zpqtkyxoVDORMhCgsVUE9BkgepFfpOXYPkwMPbQ99LW+9/U+XxVfmxEvZy92/yP3m/wCGOv2a/wDoSbb/AMC7z/4/X5I/tg+AvCXw3+NN54Y8E6cml6XHYWUy26PJIA8qZc5kZ25PvX7Zf8Jx48/6Jzq//gw0r/5Nr8Yv22dR1PVfjvfXer6TPotwdOsV+y3EsM0gUR8MWt5JI/m7AMT618pwpXxc8a1WqOS5XpzX6rpdnr5xToqheEbO/a36HyRRRRX6OfMBRRRQB//W4b9pn/kv/j3/ALDl1/6FXhle4/tLnPx+8e/9h27/APQ68Or95wH+60/8K/I/PcR/Fl6sKKKK6zEKKKKACiiigD9/v2Kf+TbvCn/b7/6VzV7D45/5Gj4d/wDYyXH/AKZNVr+cnT/HPjbSbOPT9K8QapZ2sORHBb3s0USZJJ2orhRkkngdanl+IXj6d4ZZvEuryPbuZIWa/nYxuVZCykv8rbHZcjnDEdCa+FxHB9Spialf2q95ye3e/wDmfQU86jGlGny7W69j+nivK/gv/wAk/t/+wlrP/pyuq/nh/wCFl/Eb/oatb/8ABjcf/HK/aP8AZh+F/gPxT8CPCfiHxFpSahqV/b3E1zdTyytJLIbmbLMd/JNeFmvDyy/Dc1WpdSktl5PzR6GEzL6zVtCNrJ9fTyPePF3/ACVDwB9dZ/8ASVa9Xr5g8XfCD4d2fjrwJbWOk/ZUvb7UYrj7Pc3ELSRrYTyBS0cqtgOinr2r0r/hSnw5/wCfC7/8Gl//APJNeFWjQ5KfvPbsv5n/AHjvg6l5aLfv5LyP52fH3/I9eI/+wtff+j3rkq6XxnbQ2XjDXbO2XZDBqd5FGpJbCJM4AySScAdSc1zVfuFL4F6HwU/iYUUUVoSFFFFABRRRQAUUUUAFFFFABRRRQB2fw5/5KF4X/wCwzp//AKUJX9OtfzB+AraG88c+HbS4UtFPq1jG4BKkq86AjIII4PUHNf0T/wDCkPhV/wBC9b/99y//ABdfnvG6pupS521o9lft5o+lyFy5Z8q7CeDv+SmfEH/rrpH/AKRip/jB/wAiZF/2HvDn/p4sq8r8J/Bz4aTfEPx1aS6FC0NtLpXlIZJcJ5loC2Pn7nrUvxZ+Dvw00/wW11ZaFDDKNU0VA6vKCFk1O1Rh9/urEfjXyqjR+s0/ef2Oi7L+8etefspaLr1835H09XmngP8A5GX4h/8AYzQ/+mXSqq/8KQ+FX/QvW/8A33L/APF1554K+DfwzufEPjuGfQYHS18QwwwgvL8kZ0jTZNo+f++7H8a56UaHJP3nt2Xdf3jWbqXjot+/k/I9G+Lf/IC0X/safDf/AKdLavUq+X/if8HfhpZafoLWmhwxGbxLosEm2SUbo5LtAyn5+hFel/8ACkPhV/0L1v8A99y//F0ThQ9jH3nu+i8v7wJ1Od6Lp19fIPhl/wAhLx3/ANjXcf8ApHZ0fE3/AJCfgP8A7GuD/wBIr2vMvhp8Hfhrff8ACVNeaHDMYfE2owRl5JTtij8sIo+foo4ApPiX8HfhpYt4Ta00OGIzeJ9PhcrJKC0cglDqfn6MOD7V08tH6zbme1tl2/xGd6ns9l9/n6H1HXl3wl/5AOsf9jT4k/8ATrdVH/wpD4Vf9C9b/wDfcv8A8XXnHww+Dvw0v9F1aW70KCVo/EniCBSzy8Rw6lcIij5+iqoFc0I0PYy957rovP8AvGjdTnWi69fTyPU/HX/IzfDz/sZZ/wD0y6rXpNfNHjT4N/DK28ReBIYNBgRLrxDNDMA8vzoNI1OQA/P/AH0U/hXoX/CkPhV/0L1v/wB9y/8AxdFWNDkh7z27Lu/7wQdS8tFv38l5H4A/HP8A5LN44/7GDUf/AEoevKq/fP4a/s8/BLXvDM2p614O0u+u31nXomnniMkjJBql3FGCxOTtjRVGewr5c/bs+D/wx+Hnw70PVfBHhuw0a7uNW8iWW0j2M8Rhdtp55GVBr9Iy/iahOvDAqDvtfS2nz8j5fE5VUjTeIbVt/vPyvooor6w8cKKKKAP6Wfgn/wAkc8Df9i7pf/pLHS6l/wAlm8Pf9ixr3/pZpNeZ/CH4O/DTU/hT4N1G/wBCgmubrQdNmmkZ5cvI9vGzMcP3Jov/AIOfDNPizoWnroUAt5fDutTPHvlwZIrvTFRvv9QJGH41+JSjR+s1Pef2ui7P+8feJz9nHRdOv/APobXP+QLqH/XrN/6Aa/lyuv8Aj5l/66N/M1/R1rPwT+FsekX0kfh+BWW2mZWEkoIIQ4I+ev5xbn/j5l/32/ma+x4IVNKtyNv4d1bv5s8TPnL3OZd/0P0t/wCCan/I1eN/+wfY/wDo2Sv1C+Iv/JPvE/8A2BtQ/wDSd6/JX/gn14M8M+MfE3jCDxLYpfR21jZvErs6qrNI4JwrDJwO/Tt1Nfof8Tfg18MrH4beLL200GCOe30PUZYnDy5V0tpGUj5+xGa8fiONJ5s+aTv7vTyXmvyO3LHNYNWXfr/wD2nwZ/yJ+hf9g20/9ErXNaf/AMlg17/sWtE/9K9Urn9E+CPwrfRrBm8PW5JtYSSXlySUH+3X5k/tyW3/AAq34naLZfDue68PQX2gxS3KWF1NCJnS5uApfD87QTjPTNedlmAp4zESw9ObTknuvO/fyOrFYiVCmqklovP/AIB+qPxr/wCSOeOf+xc1X/0lkr+aWuwufiF4+vLeW0u/EurzwTo0csUl/O6OjjDKylyCCDgg8EVx9fo2QZLLLqc4SlzXd9rHzGY45YmSklawV1/w+/5H3w1/2GLD/wBHpX3/APsD/Cn4c/EbQ/GFz458P2Wty2V3Yx27Xce8xK6SlgvPGSBn6V9V/HT4AfBjwr8H/FviXw34R03TNV0zTJrqzvLaMxzQTxAMkiOpBVlIyCK5sbxLQpYp4GUXfRX0trbz8zXD5XOdJV01bf7j7Pr8KP2+P+TiL/8A7Bmn/wDos18yf8LL+I3/AENWt/8AgxuP/jlczqeraprV22oaxeXF/dOAGnuZWmkYKMAF3JY4HA5rHI+GZ4DEOvKpfRrb0Lx+axxFL2ajbUz6KKK+uPGCiiigD//X4L9pT/kvvj7/ALD15/6Ga8Qr239pI5+Pnj7/ALD17/6MNeJV+9YD/dqf+FfkfnuI/iy9WFFFFdRiFFFFABRRRQAUUUUAFfpL8F/26/Dvws+GGg+AL3wpe382jwSRPcxXccaSb5XkyFZCRw+Ovavzaorhx+W4fGwVPEK6Tvvb8jow2KqUJOVN6n6j69/wUF8Max4j8Na6nhC/jXQbq6uHjN3ETKLi1ltwAdnBUyBuQcgV1/8Aw8q8J/8AQk6j/wCBsX/xuvyJory5cK5a0k4beb9e/mdazfFK7UvwR9yab+xd8XPipZp8StEuNHgsPE7PqtvFNdSebHHdsZAj4hxuXdg44yKo3n7CPxhsde03w5Pe6N9r1WG6mt8XEhTbZ+X5m4+Vwf3q4455/H9Zv2bv+SDeBP8AsCWn/oFbHiX/AJK14I/7B+vfys6+TlxTjoV50Va0ea2nZO35HsLKcO6am73duvc/J7/h3h8cP+f3Qv8AwKk/+M18IzxG3nkgY5MbshI9VOK/qjr+WTUv+Qjdf9d5P/QjX0PC+c4nHur9Yt7trWVt7/5Hm5tgaWHUfZ9b/oUqKKK+tPGCiiigAooooAKKKKACiiigDb8NasugeI9K114jMum3tvdmMHaXEEivtBwcZ24ziv1b/wCHlXhP/oSdR/8AA2L/AON1+RNFeZmGT4XGuLxEb221a/I68Nja1BNUnufqLon/AAUF8NaV4q8SeIZPB99JHrj2TRxi8jDR/ZYBEdx8vB3HkYp/jj/goN4Z8WeHm0WDwff27m80+63veRMMWV3DclcBOrCIqPQnNflvRXH/AKsZdzqfJqrdX026m/8Aa2Js4834Lqfrt/w8q8J/9CTqP/gbF/8AG69k+A3xk8WfE3TfFXj3wd4L8/TtY8QFwtxqsUEkUlvp1hbshBibd/qgwYf3sdq/CWv22/4J2/8AJCdQ/wCxkvP/AEnta8DP8lwWBwbrUIatpat/5+R6OXY6viKyhUlpvsj1P4m+JPiVNYaCLzwZBbBPEmivGf7Yjk3yLdoUj4h+XeeN3QV6T/wlXxV/6EOD/wAHkP8A8Yp3xZ/5B3hz/satC/8ASyOvVK+JnWh7GP7tbv8Am8vM92MHzv3n07f5Hy98NvEnxKh/4Sn7H4MguQ/iXUXk/wCJxHH5crbN0fMJ3bT/ABDg0nxK8SfEuY+FftXgu3t9nibT3j/4nMb+ZIPM2x8QfLu/vHgV6Z8Kuni//sa9U/nHSfFXr4O/7GzTP/aldKrQ+tW5F+Pb1M+R+y+J/h/kL/wlXxV/6EOD/wAHkP8A8Yrzn4Y+JPiXDouqrZ+C4LlG8R6+7MdYijKyNqVwZEwYTnY5K7ujAZ4zgfTleXfCX/kA6x/2NPiT/wBOt1XNCtD2Mv3a3X83n5mjg+de8+vby8jzrxn4l+JkniHwK0/gqCJ4/EEzQp/bMTebJ/ZGpKUJEPyYQs245+7jvkegf8JV8Vf+hDg/8HkP/wAYq746/wCRm+Hn/Yyz/wDpl1WvSaVWtDkh+7W397u/MIQd5e89/LsvI/L2x/bn0f4UTar4B1vwfeXF9petayZ3gvYvL33OoXFwVUmPJCeZtz3xnivnr9p39rPRPj94Q03w1pvh+70iWw1AXhlnnSZXXy3TbhVUg/NmvnP45/8AJZvHH/Ywaj/6UPXlVfquByHBQlDFxh7++73fkfI4jMK7UqLfu7bIKKKK+gPNCiiigD9SvAn/AAUI8MeD/BOgeE5/B9/cyaNplpYPMl5EqyNbRLGWAKEgNtzjPFLdf8FCPDFx4303xaPB9+I7DStR05oftcW5mvZ7OUOG2YAUWpBGOdw9K/LSivn3wxlzk58mrv1fXfqel/a2Jso823kj9a77/gpD4UvLG4sx4L1FPPiePd9tiON6kZxs7Zr8mJnEkzyDozEjPuajoruy/KcNgub6tG199W9vU58TjKte3tXex9Ufst/tD6b+z5rOvalqejT6wmsW0ECrBMsJjMLs2TuVsg7vwxX1b4t/4KGeGPFfhXWfC8Hg6/gk1jT7qwSV7yJlja6iaIMQEyQpbJFflVU9r/x8xf8AXRf5isMVkOCxFb6xVjeWnV9DSjmNenD2UHp6H9HOj+KPimmkWKp4Gt3UW0IDDW4gGAQc4MGefevyu/b91HxFqXxM8PzeJNHTRp10JVSFLtbzen2mc796ogHJIxjtmv2l0P8A5Amn/wDXrD/6AK/Hz/gpD/yVfw1/2Lyf+lVxXwfCtWLzJJQS0ff9Wz6DN4tYV3fbt/kfnpbwtcTx26nBldUBPYscV92/8O8Pjh/z+6F/4FSf/Ga+GtM/5CVp/wBd4/8A0IV/U1X1HFGc4nAOl9Xt7173V9rf5nlZTgaWIUvadLfqfnV+yv8ADr4p/AO98Y+DJdEsfEF3K2mXkz2+pC3SJZEnCL+8hyxO0njpXsHx/wDEXxGuvgr40t9V8HQ2FpJo90JrldXjnMS7fvCMQqW+mRXsHhn/AJK144/68dB/9Bu6xf2lP+SCeO/+wJdf+g18RPGuvmEKtSCcm4NvXsvOx70aHs8PKEW7K/bz8j+cavpP4M/sufEL45aBeeIvB9zpsVvZXRtJVvJnjfeEV8gLGwIIb1r5sr9l/wDgnD/ySzxH/wBhz/2hHX6TxBj6uDwbr0d01ufL5bh4Vq6pz2Pif4h/sVfFf4aeDNU8c+ILvSX0/SY1lnW3uJHlId1jG1TEoPzMO44r5Ar+hX9r/wD5Nv8AG/8A16W//pVDX89Vc/DOZ18dhpVa9rqVtPRGma4Snh6ijT2sFFFFfRnmH//Q8+/aQOfj34+/7D99/wCjTXile1ftHHPx68f/APYwX/8A6NavFa/esD/u1P8Awr8j89xH8WXqwooorqMQooooAKKKKACiiigAooooAKKKKAL8eq6pCgihvLhEXoqysAPoAa+1/wBhTRNJ8cfFy/03xjaRa1axaLcSxw3y/aESQSwjcofOGwSMjtXwzX3B+wTP4jt/i7qT+GLKyv7s6LOGiv7ySyiEfmxZYSRW10xYHAC7ACCTuGMHyc8TWAquOjt6fiduXu+Igntc/Xf/AIUj8If+hP0f/wABI/8ACvPPhN8HPhNqfws8H6lqPg3Qrq7utB02aeeXT4Hkllkto2Z3YoSzMSSSeSa9J/tP4xf9C34a/wDChvP/AJT1578JNR+KyfCvwcmneH/D01qug6YIJJtduopXjFtHtZ410qRUYjBKh2APG49T+TxnifYy/edV9pdn5n2DjS517vR9PTyKt/8AB34Tp8WND0tPBuhLZzeHdZuJIBp1uI3liutNVHZdmCyLI4UnkBmx1NdjrXwS+DsOjX80Xgjw+jpbTMrDTbfIIQkEfu+1crf6j8VT8WtDd/D/AIeF2PDmsiOIa5dGJojd6ZvZpP7KDKysECqEIYFiWXaA3WeI9Z+Llt4e1S4ufDfhwRRWVw8mzX7tn2LGxO0HSFBOOgJH1FXKWJ/d2qdP5l3fmSlS973fw8vQ5r4Z/Bn4Sah8OPCl/feDNBuLm50TTppppdOt2eSSS3jZmZihJZiSSTyTX52f8FBvBvhLwb4n8IW/hLRbDRormwu3mSwto7dZGWVACwjVdxA6Z6V+kHw5u/izafD3wxa2ugeHZoYdG0+OOSTXbuN3RbdArMg0lwpIGSAzAHjJ618q/tLfA34qftC/ETQdEYeH9BudK0W5ugRqN1eRyxvcIhy32CEqwJHG0gjuOletk2JnSzH2lep7i5vtX6Ppc48dSU8Ly04+87dD8faK++Nd/wCCevxW0DRNQ1268QeHpIdNtZ7uRI5LouyQIXYLm2AyQvGSBmp9N/4J2/FnU9OtdSh8Q+HUju4I51VpLvcFkUMAcWxGQDzX3v8ArBl1ub2qt8z57+zcTe3Iz4Aor2v45fAzxL8BfEdj4Z8UX1jf3N/ZC/R7BpGjWMyPGAxljjO7MZPAxjHPp4pXp0K9OtTVWk7xezOSpTlCThNWaCiiitSAooooAKKKKACrkGo6hap5VtdTQpnO2ORlGT3wCKp0UNXA9w+ALNr/AMa/BOja6zahYXetWkVxa3RM0MqM4yro+VYH0Ir96f8AhSfwe/6EnQP/AAW2/wD8RX4E/s9vfx/G/wAEPpUMNxeLrVoYIriVoInk3jAeRY5WRSepEbEehr9+v7T+MX/Qt+Gv/ChvP/lPX53xk6qxFP2Urad7dT6bJOR05cyvr2ueY/Dz4RfCu91Dxol54Q0SZbXxLPBAH0+BhHELS0YIuU4XczHA7knvSfEP4RfCuy1HwUlp4Q0SFbrxLDBOE0+BRLEbO7Yo2E5XcqnB7gHtUnw71H4qrqHjQ2fh/wAPyM3iacziXXLqMJL9ktMqhGlPvXbghiFOSRt4yU+Imo/FVtR8FG78P+Ho2XxNAYBHrt1IHl+x3eFcnSk2Lt3HcAxyANvJI+d5sR7f4+n8y/l9T07U/Z/D17eZ6R/wpP4Pf9CToH/gtt//AIivOfhj8IvhXqGi6rLfeENEuHi8R+IIEaTT4GKxQ6lcRxoCU+6iKFUdlAA4Felf2n8Yv+hb8Nf+FDef/KevOPhhqPxVTRdWFj4f8PSofEniAuZdcuoiJTqVwZFAXSnBVXyFbILKAxVSdo54yxPspfvOq+0vPzNGqXOvd79PTyPnD9u3wD4I8FfBvT9Y8H6Dp2iXzeILWE3On2sdtMYnt7osm+NVbaSoJGcHAr8i/wC2tY/5/rn/AL/P/jX65ft63nj64+C1inijSNHsLQeILQrLYarPeymX7Pc4Uxy2FqoUjJLbyQQBtOcj8eq/SOFFJ4BOo7u763/E+XziyxHu6aLyHySSTO0srM7scszHJJ9yaZX2l8M/2HviT8UfA2k+PtE1vQ7Wy1eN5YYrp7kTII5HjIYJA65yhIwx4rjvjj+yl44+A3h6y8SeKNV0q+t767+xxpYPO0ivsL5YSwxjbhT0JOe1epDN8HKt9XjUXPe1vNHJLBV1D2jjofL1FFFekcoUUUUAFFFFABRRRQAVPa/8fMX++v8AOoKkhcRypIeQrBvyNDBH9IejfBf4Qy6RYyyeC9BZ3toWYnTrfJJQEn7lchZ/B74US/FPWtNl8HaE9rF4f0eeOFtPgMaSy3Woq7qpTAZlRAxHUKM9Bj45sP8AgpPa2Vjb2f8AwgEjeREkW7+1gM7FAz/x698ViW//AAUPtYPGF/4r/wCEGkb7dptjp/kf2oBs+xzXUu/d9m53/acYwMbc5OePyqOR5yue8XqtPeXdeZ9e8wwWmq+59vQ+3/iv8HPhNpnwv8Xajp3g3Qra6tdD1GaCaLTrdJIpEt5GV0YICrKRkEcg16H/AMKT+D3/AEJOgf8Agtt//iK/N3xl/wAFD7Txb4Q1vwr/AMINJa/2xp11Yef/AGoJPK+0xNHv2/Zl3bd2cZGemRXS/wDDzC1/6J9J/wCDYf8AyLSlkecumlZ3u/tLy8/UazDA8zd1b0fn5HhX7dejaT4J+Lthpng2zg0O0k0W3leDToxaxtIZZgWZYgoLYAGTzivih9W1WRGjkvbh1YYZWlcgg9iCa9w/aN+N8Xx78bWvjCLSG0X7PYR2Jt2uBc58t3ffvEcfXfjG3t19PEdG0ufXNYsdFtWRJtQuYbWNpCQivM4RS2ATgE84BOK/Q8rozo4OnDEL3ktep81jKkZ15Ons3oZtW7e/vrRSlrcywqeojdlB/Iiv0C/4dv8Axd/6GPw3/wB/bv8A+Ra53Sf2A/ilq+ta3olvr2gJNoU8FvO7yXWx2uII7hSmLcnASQA5A5zxjk4rP8ukm/arT+uxf9nYpfYZ82/B+efWPit4P0rV5HvbK71uwintrhjLDLG86BkdGJVlI4IIINfv5/wo74M/9CN4e/8ABZb/APxuvyo1H9kP4j/s9xQ/GvXdT0TVbDwfd2epzWVpNcLPOI7iMBEZ7YKpJI5PQc4PSvXv+HmFr/0T6T/wbD/5Fr5rPKeIzKUKuVvmirp2dtfnY9TASp4VOGL0b2urnyD+2NoWi+Gv2hPEmi+HrC302wt4tP8AKtbSJYYY99nC7bUQBRuZiTgckk18w1678dPihH8ZPibqvxEj046UNTS1X7I03nmP7PBHD/rNibt2zd90YzjnGa8ir7LL6c6eFpwq/EopP1tqeJiZRlWlKGzbP//R87/aMOfjz4//AOxh1D/0c1eL17N+0Uc/Hjx//wBjFqP/AKPevGa/esD/ALtT/wAK/I/PcR/Fl6sKKKK6jEKKKKACiiigAooooAKKKKACiiigAr72/wCCeM8Nv8Z9UlnkWNBoNxlnYKOZoO5r4Jr7j/YG8PaB4l+L2paf4j0yz1W1XRJ5VgvbeO4iEiyxAMEkVl3AEgHGcE15GfW/s+rzbWO3Lr/WYW7n7a/2tpX/AD+W/wD39X/GvNvg1qemx/CLwSkl3ArL4d0oEGRQQRax8EZrX/4VH8KP+hL8Pf8Agqtf/jVeefCP4XfDPUPhV4Nvr/wjoVzc3OgaZLNNNpttJJJI9tGzO7NGSzMSSSTkmvyGKo+xlq910XZ+Z9m3PnWi2f6eR1Go6npv/C5PD8n2uDYPDOuLu8xcZN5pRxnPWuo8Z6ppj+D9dRLuBmbTbwACVSSTC/A5rym7+F/w0X4v6Tp6+EtCFrJ4b1OZ4Bptt5TSpd2Kq5Ty9pZVZgDjIDEdzXa658JvhXHouoSR+DfD6strMVYaXagghDgg+X1rSSop09Xt2Xd+Ylzvm0X9L0Nf4fappieAvDSPdwKy6RYAgyqCCIE4PNc3JqmmH42wOLuDaPCswJ81cAm9iwM574NY/wAMfhZ8Mb34beE7y88IaDPcT6HpssssumWzySSPbRlmZjGSzMTkk8k1lw/C74Zn4x3dgfCOhG2XwzazLD/Ztt5Yka8nUuF8vG4gAE4zgAVSjRVSpq+vRd/UV58sdF0/rY9L+JOq6Wfh34pAvLck6LqGB5q/8+8nvWr4T1TTE8LaMj3cCsun2oIMqggiJeDzXnnxC+FfwwtPAPiW6tfB+gwzQ6PfyRyR6ZbK6OsDlWVhGCCCMgjkGtLwt8J/hZN4Y0iabwb4fkkksLZmZtLtSzMYlJJJjyST1NZWo+w3e/ZdvUq8+fZbf10Py/8A+CjVzbXXxY8ONbSpKB4djBKMGAP2q49K/Pev6KNM+Gnw4T4r69Yp4V0RbaPw9osqQjTrcRrJJdamruF8vAZgignGSFGegpnxl+HPw9sfhH40vLLwvo1vcQaBqUkUsWn26SRulvIVZWWMFWB5BHINfZZdxRSwtOlg1TbtZXvbfXb5niYrKZ1Zyr81t/wP52qKKK/Qj5oKKKKACiiigAooooA9r/Zwmht/jx4EnuHWKOPXLNndyFVVDjJJPAAr+iD/AISjwz/0F7H/AMCY/wD4qv52v2d7Kz1H45+BrHUIIrq2n1u0SWGZBJHIpcZVlYEEH0Ir+gr/AIVl8Nv+hT0P/wAFtt/8br83419n9Zp89/h6ep9PkXN7KXL3OK+G3iLw/DqPjgzanZp5niid03XEY3KbOzAYZbkHHWk+JPiPw/NqfgUxanZv5fimF323EZ2qLK9yThuAPWsX4YfDr4fXA8WfaPDGjS+X4o1ONN+n27bUUphRmPhR2A4FJ8T/AIdfD63PhL7P4Y0aLzfFGmxvs0+3XcjeZlTiPlT3B4r5y1H6za77dOx6v7z2fT+me2f8JR4Z/wCgvY/+BMf/AMVXmXwp8R+H4dC1cTanZoW8TeI3UNcRjKtqlyQRluQR0Peuy/4Vl8Nv+hT0P/wW23/xuvNfhZ8O/h/d6Jq8l14Y0aZ18S+IYlaSwt2ISLUrlEUExn5VUBVHQAADiuaCoexlq9128/M0ftOdbdf0Pnv/AIKEa1o+ofA/T4LC/trmQeI7NikMySNtFtdZOFJOOa/F2v2R/b98HeEPD/wTsL3QdD03TbhvEVpG01paQwSFDb3RKlo0U7SQDjOMgV+N1fpvCPL/AGeuTa7Plc5v9Z17I/f39kfX9Cs/2dPBVtd6jaQTJa3G6OSdEdc3UxGQTkcV4T/wUS1fSdR+Fvh+PT723umTWwWWGVJCB5EnJCk4r2H9k7wF4G1b9nrwbqOq+HdJvLqa1uDJPcWMEsrkXUwBZ2QscAAcnpXhv/BQbwh4T8PfDLQLrQNF07TJ5NZEbyWdpFA7J5Mh2lo1UkZAOOmRXyOB9l/bujd+eX5s9nEc/wBQ125V+h+RNFFFfqp8gFFFFABRRRQAUUUUAFFFFABRRRQAUVd00BtRtVYAgzRgg9CNwr+mL/hV/wANP+hS0L/wW23/AMbrwM7z6OW8nNDm5r9bbW/zPRwGXvE81pWsfzIV13gBlTx34bdyFVdXsSSeAAJ0r98vDnw5+HsnxT8aWsnhfRmhhstEaONtPtyiF1utxVfLwC2BnHXAzSfGj4cfDyz+FniS6tPC+iwTRWTMkken26OrBl5DCMEH6V48uMacpqj7J+9br3S/zO1ZJJLn5tr9Ox7Z/wAJR4Z/6C9j/wCBMf8A8VXl3grxH4fTx78QpX1OzVJNS07YxuIwG26Zag4O7nB4Ndt/wrL4bf8AQp6H/wCC22/+N15d4T+HXw+l+JPju3k8MaM8ULaR5aNp9uVTdakttBjwMnk46mvgqKoclTV7eX8y8z6GftOaO2/6M579rfxBoN3+zp41t7XUrOaV7S3CpHPGzMftUPQA5NfgDX9Efxf+HXw+tPAs01r4Y0aGT+0tHXfHp9ujbX1K1VhkRg4ZSQR3BIr0z/hV/wANP+hS0L/wW23/AMbr6PJeIKOXYZxUHLmk+y6I83HZdPE1btpWX+Z/MhRX1L+2dpWmaL+0V4m03R7OCwtIo9O8u3tolhiTdZQMdqIAoySScDknNfLVfpOExCr0IVkrcyT+9Hy1an7OpKn2dj//0vN/2hzn47/ED/sY9S/9KHrxuvYv2hf+S7fED/sZNT/9KHrx2v3vBf7vT9F+R+e4j+LL1YUUUV0mIUUUUAFFFFABRRRQAUUUUAFFFFABX25+wd/wlH/C29R/4RI2Avf7Fn3HURKYfL82LOBFht2cY7YzXxHX3V/wT+1fSdF+MepXWsXtvYQtoc6LJcypChczQkKGcgZwCce1eTnt/qFWyvodmX/7zC/c/Wjb8cP+enhT/vi9/wDiq8/+E0/xjX4WeD106x8MtajQdNEDTXt4spj+zR7S4W2ZQxGMgEgHoTXtP/Cf+BP+hj0n/wADoP8A4uvLPhH8S/hxZfCrwbZ3nirRILiDQNMjlil1G3R43S2jDKymQFWBGCDyDX5LF1HRl+76ro+zPsmoqa97o+voYl7N8YV+LWjs9j4a+2P4c1YRqL288nyUu9P3lj9m3B9zJtABBG7JGBnrPEd/8abXw9qlzc6d4XaGGyuJJBHfXm8osbEhc2uM46Z4zVC4+IPgK8+MGh3Vp4l0ieCLw1rUckkd/A6I73ellVZg5ALBWIB5IBx0Ndd4x8c+CZvCOuQw+INKeR9Nu1VVvYSzMYmAAAfJJNaS57006fTs+78yUlaVpf1Y4n4dn4z23w/8M21nY+GHt4tHsEiaW9vBIY1t0ClgLUgMR1wSM1ircfGKL4wyZsfDRvLnw0mB9tvPJWG3u3zk/ZdxdmmGBjAAPrx6L8P/AB14Ii8B+G45PEOlI6aRYqytewggiBAQRv4IrnJPHHgo/GqCceINL8seFpkL/bYdu43sRAzvxnAPFNSn7Sp+7XXoxWXLH3uxB8Qp/jQfAPiUXVj4XWE6Pf8AmNHe3jOE8h9xUG2AJx0BIGe9afhi4+NX/CNaT9nsPC/lfYbby999ebtvlrjdi1xnHXFafxG8deCZfh94nii8Q6U7vo2oKqrewlmY27gAAPySak8K/FH4ZxeGNHil8XaEjpYWqsralbAqREoIIMnBFZ++6GlLr2fYr3VP4uh8dfG79pfx5+z58UjJ4h8PaRqV1r2gWCqtleTiKKK0ur7BLSQqxZmmPGMAKOTnjw7xn/wUI1zxj4R1vwnN4OtLZNZ0+5sGmW9dmjFzG0ZYKYwCV3Zxnmuf/wCCg/iHQPEnxS8PXnh3U7PVII9ASN5bK4juEVxdXB2lo2YBsEHBOcEV8EV+h5RkmDrYWliK1L37efTbqfN43H14VZU4S935BRRRX1h4wUUUUAFFFFABRRRQB7F+z62or8bvBLaQkEl6Natfs63LskJk3jbvZFdgueuFJr98ftHxw/6B/hT/AMDr3/5Fr8E/2dbu1sfjp4FvL6aO3gh1yzaSWVgiIocZLM2AB7mv6FP+E/8AAn/Qx6T/AOB0H/xdfnXGbl9Yp2hfTs+59NkaXspXdtTwz4bXHxgx4o/s+w8NH/ipdR87zr27H77Kb9m21+50xnn1pvxLn+MRbwn9usfDKgeJtP8AK8q8vDmXEmwNuthhM9SMn0HcbXw2+Ivw+05vFkWoeJ9GtXk8UalKizahbxlo38sqwDSAlWHQ9DUfxO+JXw5uj4T+y+KtEm8nxRp0snl6jbtsjXzNztiQ4UZ5J4FfPLn+s/w/wfY9P3fZ/F+R2/2j44f9A/wp/wCB17/8i15x8MZ/jCNF1UafY+GmT/hI/EG8zXt4recdSuPMAC2xGwPkKSclcEgE4Hr/APwtT4X/APQ4aD/4M7b/AOO1wPwo8deCI9B1bzPEOlL5niXxDKmb2Ebo5NTuXRh8/KspDKehBBHFc0faexlel1XR+Zo+XnXvd+q8j5P/AG8ZfiQ/wZsB4ttdDgsv+EgtCradc3M0xl+z3WAVlgjULjOTnOccen5BV+zH/BQHxR4Z1n4JafaaPq9jfTjxFZuYra5jmcKLe6BbajE4BI596/Gev0nhJv6grq2rPl85/wB43voj73+E/wC3VrHwq+Hmi/D+18J21/Fo8UkS3Ml28bSeZK8pJURkDBfHXtXD/tCftaaj8fvC1h4avvDsGkCwvheLNFctNuxGyFSrIv8AeznPavkCivRhkmChX+sxp+/e97vd/M5pY+vKn7Jy93boFFFFeqcYUUUUAFFFFABRRRQAUUUUAFFFFAF3Tt39oWuzBbzo8Z4Gdwr+kb7R8cP+gf4U/wDA69/+Ra/m501guo2rMQAJoySegAYV/Td/wn/gT/oY9J/8DoP/AIuvg+NnK9G0b/F+h9FkSVp3dtv1PDfD1x8YP+FneMDBYeGvtf2PRftAe9u/KC4uvL2EWu4nruyPTHej4wXHxg/4Vl4iGq2HhoWn2JvNNve3ZlC5HKh7UKTnsSPrW1ofxC8A2PxU8Z3F74l0e3iuLHRBE8t/AiybBd7tpZwG25GcdMjNRfGb4k/Dq/8Ahd4ks7HxTotxPLZMqRRajbu7HcOAqyEk/QV8pHn+s0/3f8vR9keu+X2Uve7/AKna/aPjh/0D/Cn/AIHXv/yLXmXhWf4xD4ieOTBY+GTcl9K88PeXgjA+y/JsItiTxndkDngetey/8LU+F/8A0OGg/wDgztv/AI7XnHg3x94Ek+I/jy6j8R6S0Ez6R5cgvoCj7bUhtrB8HB4OOhrCl7TkqXpdOz/mRpPl5o+917+TMT4tT/GI+CZRqFj4ZWD+0dHyYby8Z939o22wANbKMFsAnPAyQCeD6V9o+OH/AED/AAp/4HXv/wAi1zHxh8ceCrjwJNFb6/pcr/2lozbUvYWOF1K1ZjgN0ABJ9AK9P/4T/wACf9DHpP8A4HQf/F0pOfsI/u1u+j7R8wSXtH73RfqfhD+2I2vP+0J4kbxLHaRagY9P81LF3ktwPsUG3a0iI5+XGcqOc/WvmKvqj9tLULDVf2jfE99plzDeW0kem7JoJFljbbZQA4ZSQcEYPvXyvX7BlX+5Ubq3ux/JHxeM/jz9X+Z//9P6M/ae/Yo8eXfijXfid8OZf+Ehi1e8uNRu9L2iO+gkncyP5IztnQEnCjbJ0AVzzX5n3dpdWFzLZX0MlvcQOY5YZVKSRupwVZWAIIPUEZFf1QV4D8Zv2a/hf8brV5PEun/ZNZCbYdYsgIrxMDChzgrMg/uyA4GdpU819zk/GEqSVHGK8Vpdbr1XX8/U8DG5Kptzouz7H86tFfU/xv8A2R/ih8GGn1VoP7f8NxkkatYIxESdjcw8vAfU5aPtvzxXyxX6HhsXRxFNVKElJeR81VozpS5aiswoooroMwooooAKKKKACiiigAooooAKKKKACv6RvgzoWhzfCHwRNNp1o8j+HdKZmaBCzE2seSSVySa/m5r+hL4R2vxfb4VeDW03U/DaWh0DTDAs+nXbyrF9mj2B2W8VWYLjJCgE9AOlfE8axvRpe9bV/ke9kTtOel9DrNY8M+G7r4weH7W50mxlg/4RrW5PLe2jZN63elgNtK4yASAeuCfWt3xj4J8GQ+Edcmi0HTEdNNu2Vls4QysImIIIXIINea3lr8XH+LWjxyat4cjvU8Oas0ci6XdvD5LXen71ZDfq28sqFWDgABgQcgjpfF1h8Yh4T1o3Ou+GWhGnXXmCPRbxXKeU2QpOpkA46EgjPaviOVp017Rbefd+R7901L3fy7G34B8FeDZ/AvhyefQdMkkk0mxd3ezhZmZoEJJJXJJPU1z0ng7wj/wua3s/7D03yP8AhGJ5fK+yQ7N/2yIbtu3G7HGeuKi8CWnxkPgjw8bTVPDKwf2VZeUJNNvC4TyE27iL0AtjrgAZrASy+Ls/xhkDav4bivLbw0mGGlXckTRXF22QV+3owcNCOd2MHp3qkpe0qP2i69X/AJCbXLH3e3Y7X4q+C/B1t8L/ABhcW+haZFLFoGpujpZwqysttIQQQuQQeQRXfaRoGgvpNk76baMzW8RJMCEklBkk7a8k+I+mfF6X4eeKIr/XPDb2r6LqCzrDo92khjNvIGCM2pOqsVzglWAPJB6V+dFp/wAFGvijaWsNqvhnQGEMaRgkXWSEAGf9d7V04PKsXjaNsPJSs9dbbrzt2Ma+MpUJ3qq112IP+Ci9lZ2PxX8ORWMEVujeHkYrEgQE/argZwoHPFfnzXt/x2+OniD49+JLDxN4j0+z064sLEWCR2XmbGQSPLuPmM53ZkI4OMYrxCv1DKMNUw+Dp0avxJanyeNqxqV5Thswooor0jlCiiigAooooAKKKKACiiigD9xP2DtJ0q+/Z9spr2yt7iQapfrvliV2wHHGSCcV738SNE0WDU/Avk2FrH5niiFH2wou5DZXuVOByD6V+P3wY/bI8c/BTwTH4G0HRNJv7SK5muVmuxP5u6cgkHy5VXAI44rtPEH7f3xI8Qz6NcXPh3Q4m0XUk1KEILnDyJFLDtbM33SspPGDkD3B/OMZw7mFTHVK0F7rbtr3ufT0Mzw0aEYSeqS6H7Pf8I74f/6Bln/4Dx//ABNfzs/tGxRw/Hjx5DCixxprt6qqoAVQJDgADgAV9V/8PIvil/0LGgfldf8Ax6vhbx54vvfH3jPWfGupQxW91rd5LezRQbvKR5m3ELuJbA7ZJNenwxk2MwVac8StGrb36nLmuOo16cY0nrfscnRRRX2h4QUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFAH6xf8E3dO06/8OeODfWsNzsvbDb5savtzHNnG4HGcV9u/GrRNFtvhV4mnt7C1ikWxfa6QorDJA4IGelfit8Bf2nfFn7P9jrFh4b0rTtRTWZoJpWvvNyhgVlAXy3Tg7znOa9d8W/t/fEfxh4b1DwzfeHdEhg1GEwvJF9o3qCQcjdKRnjuK/P8zyDHVsyeJpr3Lp79kr6H0mEzHDwwqpSetn0P2d/4R3w//wBAyz/8B4//AImvw5/bwtra0/aCvoLSJIIl0ywwkahFGYyTgDA5Nel/8PIvil/0LGgfldf/AB6vj/4y/FnWvjV43m8da9Z2tjdzW8FuYbPf5QWBdoP7xmbJ781rw3kWNweLdXEL3bNb37EZpmFCtR5Kb1v2PKqK9E+HHwo8f/FnWRongPR59SmUjzpVGy3t1P8AFNM2EjHpk5PRQTxX6zfBD9gvwN4H+z698Tni8Va0mHFptI0u3cdvLYBrgj1kAQ/888jNfR5nnmFwK/eyvLst/wDgfM8vC4CtiH7i079D83fg9+y98WvjSv27w5p62GkYb/ia6mWgtHYZ+WMhWeUkjBMaMqn7xFe+/wDDuP4yf9B3w5/3/uv/AJFr9noYYbaFLe3jWKKJQiIgCqqqMAADgADgAVLXwWI40xspt0kox7Wv+J9FTyOgo2nds//U/fyiiigBGVWUqwBBGCDyCDXw18cP2Gfh58R/tGu+BPL8Ja++XKwx/wDEtuX6/vIFx5RJ/jiwOpKMa+5qK68Hj6+Eqe0w8rP+t11Ma+Hp1o8tRXR/NP8AE/4N/ET4Pav/AGT470iWy3sRb3a/vLS5A7wzL8rccleHX+JQa8vr+o7xD4c0DxbpFxoHibT7bVNOul2zW11GssbjtwwOCOoI5B5HNfmF8cf+CfDL9o8RfA+53Dl20C+l5+ltcufySY/9tOgr9FynjCjWtTxa5Zd+j/y/LzPmcZks4e9R1Xbr/wAE/K6itnX/AA9rvhXVrjQvEun3OmajattmtruJopUPurAHB6g9CORxWNX2cZJq62PEaadmFFFFMQUUUUAFFFFABRRRQAV/Q38Ifiz8K9O+FHgzT9Q8ZeH7W6ttA0yGeCbVLWOWKSO2jVkdGkDKykEEEZB4NfzyV/S38Ff+SO+Bv+xc0n/0ljr4jjdwVGlzq+r626ejPeyG/PO3Y87u/ix8LG+L2laivjLw+bSPw3qcLzjVLXyllku7FlQv5m0MyoxAzkhSR0NdN4w+L/wluPCWt29v428Oyyy6ddoiJq1ozMzRMAABLkkngAVuaj/yWfw//wBixrv/AKWaVXU+Nf8AkTde/wCwZef+iXr4VypXpe69u67vyPoUp2lr+Hl6nmPgP4vfCe18DeHba58a+HYZodJsY5I5NVtFdHWBAysplyCDwQeQa52L4t/CpfjHd37eM/DwtW8M2sKznVLXyzIt5OxQN5m0sFYEjOQCDXs3w8/5EDwz/wBgew/9EJX5cf8ABSr/AJG7wT/2Drz/ANGpXfleEo4vGvDarmvrdPz2suxzYutOjQVXR2t/W59+/EL4v/Ca88AeJrS08beHZ559Hv44oo9VtHd3eBwqqolJLEnAA5Jr+dGiiv0fJclhl0ZRhJy5rb+R8xjsfLEtOStYKKKK9s4AooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKUAsQqjJPAAr7c+CH7D3xI+Jn2fXPGQfwl4fkw4a5jzf3KHn91bnBQEfxy7eoKq4rkxmOoYWn7SvKy/rbubUcPUrS5aauz430TQta8S6pb6J4esbjUtQunCQW1rG0ssjHsqKCT/Sv0u+B//BPi8u/s/iH43XJtYeHXQrGQGZh6XNwhIQeqREnB/wBYp4r9DPhX8Efht8GtL/s7wLpMdtLIoW4v5v3t7c4/56zEbiM87F2oD0UV6zX55m3GNareng1yx79f+B+Z9Lg8khD3q2r7dP8AgnPeFvCfhnwTo0Hh7wlpltpOnW4xHb2sYjTPdjjlmOPmZiWY8kk10NFFfFyk5Nyk7s9xJJWQUUUVIz//1f38ooooAKKKKACiiigDyv4pfBf4c/GPSf7L8d6THduilbe9j/dXtsT3imA3AZ5KnKMfvKa/Iz44/sOfEX4a/aNd8ECTxb4ej3OTBH/xMbZBz+9gXPmAD+OLPQlkQV+49Fe1lefYvAu1N3j2e3y7HDi8uo4hXkrPufysEFSVYYI4IPakr9/Pjf8AshfC/wCMon1ZIB4d8SSZYarYRgCZz3uYMqk2e7ZWTp8+Bivx9+Mn7N/xQ+CN2zeKNP8AtOks+2DWLLdLZSZ+6GbAMTn+5IFJOdu4c1+l5VxFhcdaKfLPs/07/n5Hy2MyytQ1ese6PBaKKK9884KKKKACiiigAr+hX4R6N8VJfhV4Nl07xTo1vavoGmNBDLoUs0kcZto9qtINSQOwGAWCKCedo6D+eqv6D/hH8Yvhvpvwq8G6de6ykdxa6BpkMqeROdskdtGrDIjIOCOxIr4zjNVHRp+zjfV9L9PRnuZG488uZ2072HX2jfFKT4taPbyeKtJW6Tw5qzxzx6HIqiJrvTw6NG2oPklgpDBhjBGDkEdV4j8MfFefw9qkE/jPTGiksrhHUaCQSrRsCAft/HHeuJ1L41/Cu2+LOk6ve+JLOzsk8O6nbGe6LWyedJd2LqgMqrklUY4HYGur1j9oP4IXOk3tvD440RpJbaVEX7ZHyzIQB17mviZQxX7tqn0/kXd+R7ylR968vx8vU/L/AEz/AIKAfF/QNNtNCs9L0JoNOgjtImeCcsUgUIpYiYDOF5rwD43/AB88X/HrUdL1PxdbWNtLpMEkEIsUdFKysGJbe7knI9q8UuCDcSEHILsQfxqGv1jD5Tg6NT21KmlLufH1MZWnHknK6CiiivROUKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKK7nwB8NfHPxQ1tfD/AIE0i41W7ODJ5S4ihUnG+aVsRxL7uQOwyeKipUjCLnN2S6sqMXJ2irs4avfvg1+zX8UfjbcpL4a0/wCyaOH2zaxfBorNMH5ghwWmcf3Yw2DjcVHNfoz8D/2BPCHhP7Pr/wAWpovEuqrh102LI0yBvR8gPckf7QVOoKN1r9CbW1tbG2isrKGO3t4EWOKKJQkcaKMBVVQAABwABgV8Rm3GVOF6eCXM/wCZ7fJdfy9T3sHkcpe9X0XY+XPgj+yH8Lvg0INWa3/4SHxJHhv7Vv41PlOO9tB8yQ47N80nX58cV9V0UV+e4rF1sTU9pXk2/M+kpUYUo8tNWQUUUVzmgUUUUAFFFFAH/9b9/KKKKACiiigAooooAKKKKACq15ZWeo2k1hqEEV1bXCNHNDMgkjkRhgqysCGUjqCMGrNFCdtUB+cnxx/YB8MeJvtHiH4Pzx+H9SbMjaVOSdOmbriJuXtyfTDR9AAg5r8pPHHw+8Z/DbXJPDvjjSbnSL6PJCTr8kig43xSDKSpnoyEr71/TtXHeOPh94M+JOhyeHfHGk22r2EmSEnX5o2PG+KRcPG/+0hDe9fX5TxdiMPaniffj+K+fX5/eeNjMmp1fepe6/wP5iKK/Rz44/sAeJ/DX2jxB8Hp5PEGmrl20qcqNRhXqRE3ypcAdh8snQAOea/O29srzTbuaw1GCW1urdzHNDMhjkjdTgqysAVYHqCMiv0fAZlh8ZDnw8r/AJr1R8xiMLVoS5aisVaKKK7jnCv6W/gr/wAkd8Df9i5pP/pLHX80lf0IfCPwh47ufhV4NuLTx5fWkEugaY8VuunWDrEjW0ZVAzwFmCjgFiSe/NfEcbQUqNK8ktXvft5JnvZC2pzsr6HyL/wUv+74B+uqf+21flTX6Wf8FCNF8QaPH4JGveIbjXjKdR8oz21tbeSF8jOPs8abt2RndnGOO9fmnXscMRSy2mk77/m+5xZq74qT9PyQUUUV755wUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAVf0vStT1zUINJ0W0nv766cRwW1tG0s0rnoqIgLMfYCvrz4IfsVfE34rfZ9b8Qo3hTw5JhxdXkZ+13CHn9xbkqxDDo7lVwcru6V+vHwk+Anwy+Cun/ZfBWlqt46bLjU7nE19ceu6UgbVOPuIFTPO3NfMZtxThcJeFP359lsvV/wCR6uDymrW96WkT87fgh/wT61nV/s/iD403LaVZnEi6LZuGu5B1AnmG5IQe6pufBxlGFfqd4P8ABPhL4f6JF4d8GaVbaRp0PKw2ybQzYwWduWkc45dyWPc11NFfm2ZZxisdK9eWnZbL+vM+owuCpUFamte/UKKKK8s6wooooAKKKKACiiigAooooA//1/38ooooAKKKKACiiigAooooAKKKKACiiigArwb4yfs4fC/422jN4o08W2rqm2DWLLEV7HgfKGbBEqD+5IGAGdu0817zRW1DEVaE1Uoyaa6oipTjUjyzV0fgJ8cP2Qvih8GjPq8cB8ReG4yWGqWEZJhT1uYMs8Pu2Wj/ANvPFfKVf1TkBgQRkHgg18QfHH9hz4dfEr7RrvgkR+EvEL5cm3j/AOJfcv1/ewLjy2Y9Xix3LI5r7/KeM07U8crf3l+q/wAvuPncZkbXvYf7v8j8N6/d34V/tSfAHQvhl4S0TVvGVnbX2n6Hp1rcwtHOTHNDbxo6kiIglWBHBIr8dvil8F/iN8HNW/srx3pMlokjFbe9j/e2VyB3imA2k45KnDqPvKK8rr6TMssw2a0oNz91apxa/wCCeXhcVVwk5JR18z9Lv2zvGPh/9oCfwnZfBeeXxfcaQmoS30WmW08rwRymBUZlMYO0kEZ6Zr4eb4LfF5FLv4L14KoySdPnwAP+AV9jf8E3f+Sq+Jv+xeb/ANKoK/X/AF7/AJAWo/8AXpP/AOgNXzeIzmWTTWXUYc0Y9W9ddenqepSwKx0XiZuzfbyP5biCpKsMEHBFJU9z/wAfMv8Avt/OoK+/PnAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKK7DwR4A8Z/EjW4/DvgjSLnV7+TBMcC5WNScb5XOEjTPVnZVHrX6q/BD/gn94c8P/Z/EHxjuE13UBh10i2ZlsIm64mf5XnI7gbE6ghxzXlZlnOFwMb1pa9lv/XqdmFwNbEP3Fp36H51fB/8AZ5+J/wAbL0J4Q00x6aj7J9WvMw2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width=\"90\" alt align=\"left\" hspace=\"10px\"\u003e\nwopr: An R package to query the \u003cbr\u003e WorldPop Open Population Repository\n\u003c/h1\u003e\n\n\u003cbr\u003e\n\n\u003cp\u003eWorldPop, University of Southampton\u003c/p\u003e\n\u003cp\u003e10 June 2021\u003c/p\u003e\n\u003ch2 id=\"introduction\"\u003eIntroduction\u003c/h2\u003e\n\u003cp\u003e\u003cem\u003ewopr\u003c/em\u003e is an R package that provides API access to the\n\u003ca href=\"https://wopr.worldpop.org\" target=\"_blank\"\u003eWorldPop Open\nPopulation Repository\u003c/a\u003e. This gives users the ability to:\u003c/p\u003e\n\u003col style=\"list-style-type: decimal\"\u003e\n\u003cli\u003eDownload WorldPop population data sets directly from the R\nconsole,\u003c/li\u003e\n\u003cli\u003eSubmit spatial queries (points or polygons) to the WorldPop server\nto retrieve population estimates within user-defined geographic\nareas,\u003c/li\u003e\n\u003cli\u003eGet estimates of population sizes for specific demographic groups\n(i.e. age and sex), and\u003c/li\u003e\n\u003cli\u003eGet probabilistic estimates of uncertainty for all population\nestimates.\u003c/li\u003e\n\u003cli\u003eRun the\n\u003ca href=\"https://apps.worldpop.org/woprVision\" target=\"_blank\"\u003ewoprVision\u003c/a\u003e\nweb application locally from the R console.\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003eCode for the \u003cem\u003ewopr\u003c/em\u003e package is openly available on GitHub:\n\u003ca href=\"https://github.com/wpgp/wopr\" target=\"_blank\"\u003e\u003ca href=\"https://github.com/wpgp/wopr\"\u003ehttps://github.com/wpgp/wopr\u003c/a\u003e\u003c/a\u003e.\u003c/p\u003e\n\u003ch2 id=\"installation\"\u003eInstallation\u003c/h2\u003e\n\u003cp\u003eFirst, start a new R session. Then, install the \u003cem\u003ewopr\u003c/em\u003e R\npackage from WorldPop on GitHub:\u003c/p\u003e\n\u003cdiv class=\"sourceCode\" id=\"cb1\"\u003e\u003cpre class=\"sourceCode r\"\u003e\u003ccode class=\"sourceCode r\"\u003e\u003cspan id=\"cb1-1\"\u003e\u003ca href=\"#cb1-1\" aria-hidden=\"true\" tabindex=\"-1\"\u003e\u003c/a\u003edevtools\u003cspan class=\"sc\"\u003e::\u003c/span\u003e\u003cspan class=\"fu\"\u003einstall_github\u003c/span\u003e(\u003cspan class=\"st\"\u003e\u0026#39;wpgp/wopr\u0026#39;\u003c/span\u003e)\u003c/span\u003e\n\u003cspan id=\"cb1-2\"\u003e\u003ca href=\"#cb1-2\" aria-hidden=\"true\" tabindex=\"-1\"\u003e\u003c/a\u003e\u003cspan class=\"fu\"\u003elibrary\u003c/span\u003e(wopr)\u003c/span\u003e\u003c/code\u003e\u003c/pre\u003e\u003c/div\u003e\n\u003cp\u003eYou may be prompted to update some of your existing R packages. This\nis not required unless the \u003cem\u003ewopr\u003c/em\u003e installation fails. You can\navoid checking for package updates by adding the argument\n\u003ccode\u003eupgrade=\u0026#39;never\u0026#39;\u003c/code\u003e. If needed, you can update individual\npackages that may be responsible for any \u003cem\u003ewopr\u003c/em\u003e installation\nerrors using \u003ccode\u003einstall.packages(\u0026#39;package_name\u0026#39;)\u003c/code\u003e. Or, you can\nuse \u003ccode\u003edevtools::install_github(\u0026#39;wpgp/wopr\u0026#39;, upgrade=\u0026#39;ask\u0026#39;)\u003c/code\u003e to\nupdate all of the packages that \u003cem\u003ewopr\u003c/em\u003e depends on. In R Studio,\nyou can also update all of your R packages by clicking “Tools \u0026gt; Check\nfor Package Updates”.\u003c/p\u003e\n\u003cp\u003eNote: When updating multiple packages, it may be necessary to restart\nyour R session before each installation to ensure that packages being\nupdated are not currently loaded in your R environment.\u003c/p\u003e\n\u003ch2 id=\"usage\"\u003eUsage\u003c/h2\u003e\n\u003cp\u003eDemo code is provided in \u003ccode\u003edemo/wopr_demo.R\u003c/code\u003e that follows\nthe examples in this README.\u003c/p\u003e\n\u003cp\u003eYou can list vignettes that are available using:\n\u003ccode\u003evignette(package=\u0026#39;wopr\u0026#39;)\u003c/code\u003e\u003c/p\u003e\n\u003cp\u003eThe\n\u003ca href=\"https://apps.worldpop.org/woprVision\" target=\"_blank\"\u003ewoprVision\nweb application\u003c/a\u003e is an interactive web map that allows you to query\npopulation estimates from the\n\u003ca href=\"https://wopr.worldpop.org\" target=\"_blank\"\u003eWorldPop Open\nPopulation Repository\u003c/a\u003e. See the vignette for woprVision with:\n\u003ccode\u003evignette(\u0026#39;woprVision\u0026#39;, package=\u0026#39;wopr\u0026#39;)\u003c/code\u003e\u003c/p\u003e\n\u003cp\u003eIf you are intersted in developing your own front end applications\nthat query the WOPR API, please read the vignette that describes the API\nbackend for developers:\n\u003ccode\u003evignette(\u0026#39;woprAPI\u0026#39;, package=\u0026#39;wopr\u0026#39;)\u003c/code\u003e\u003c/p\u003e\n\u003ch3 id=\"woprvision\"\u003ewoprVision\u003c/h3\u003e\n\u003cp\u003ewoprVision is an R shiny application that allows you to browse an\ninteractive map to get population estimates for specific locations and\ndemographic groups. woprVision is available on the web at\n\u003ca href=\"https://apps.worldpop.org/woprVision\" target=\"_blank\"\u003e\u003ca href=\"https://apps.worldpop.org/woprVision\"\u003ehttps://apps.worldpop.org/woprVision\u003c/a\u003e\u003c/a\u003e.\nYou can also run woprVision locally from your R console using:\u003c/p\u003e\n\u003cdiv class=\"sourceCode\" id=\"cb2\"\u003e\u003cpre class=\"sourceCode r\"\u003e\u003ccode class=\"sourceCode r\"\u003e\u003cspan id=\"cb2-1\"\u003e\u003ca href=\"#cb2-1\" aria-hidden=\"true\" tabindex=\"-1\"\u003e\u003c/a\u003ewopr\u003cspan class=\"sc\"\u003e::\u003c/span\u003e\u003cspan class=\"fu\"\u003ewoprVision\u003c/span\u003e()\u003c/span\u003e\u003c/code\u003e\u003c/pre\u003e\u003c/div\u003e\n\u003cp\u003eWe suggest installing Michael Harper’s fix to the leaflet.extras draw\ntoolbar:\u003c/p\u003e\n\u003cdiv class=\"sourceCode\" id=\"cb3\"\u003e\u003cpre class=\"sourceCode r\"\u003e\u003ccode class=\"sourceCode r\"\u003e\u003cspan id=\"cb3-1\"\u003e\u003ca href=\"#cb3-1\" aria-hidden=\"true\" tabindex=\"-1\"\u003e\u003c/a\u003edevtools\u003cspan class=\"sc\"\u003e::\u003c/span\u003e\u003cspan class=\"fu\"\u003einstall_github\u003c/span\u003e(\u003cspan class=\"st\"\u003e\u0026quot;dr-harper/leaflet.extras\u0026quot;\u003c/span\u003e)\u003c/span\u003e\u003c/code\u003e\u003c/pre\u003e\u003c/div\u003e\n\u003cp\u003eThis is not required, but it fixes a bug that prevents the draw\ntoolbar from being removed from the map when it is inactive.\u003c/p\u003e\n\u003ch3 id=\"data-download\"\u003eData Download\u003c/h3\u003e\n\u003cp\u003eOne way to access data from WOPR is to simply download the files\ndirectly to your computer from the R console. This can be done with\nthree easy steps:\u003c/p\u003e\n\u003cdiv class=\"sourceCode\" id=\"cb4\"\u003e\u003cpre class=\"sourceCode r\"\u003e\u003ccode class=\"sourceCode r\"\u003e\u003cspan id=\"cb4-1\"\u003e\u003ca href=\"#cb4-1\" aria-hidden=\"true\" tabindex=\"-1\"\u003e\u003c/a\u003e\u003cspan class=\"co\"\u003e# Retrieve the WOPR data catalogue\u003c/span\u003e\u003c/span\u003e\n\u003cspan id=\"cb4-2\"\u003e\u003ca href=\"#cb4-2\" aria-hidden=\"true\" tabindex=\"-1\"\u003e\u003c/a\u003ecatalogue \u003cspan class=\"ot\"\u003e\u0026lt;-\u003c/span\u003e \u003cspan class=\"fu\"\u003egetCatalogue\u003c/span\u003e()\u003c/span\u003e\n\u003cspan id=\"cb4-3\"\u003e\u003ca href=\"#cb4-3\" aria-hidden=\"true\" tabindex=\"-1\"\u003e\u003c/a\u003e\u003c/span\u003e\n\u003cspan id=\"cb4-4\"\u003e\u003ca href=\"#cb4-4\" aria-hidden=\"true\" tabindex=\"-1\"\u003e\u003c/a\u003e\u003cspan class=\"co\"\u003e# Select files from the catalogue by subsetting the data frame\u003c/span\u003e\u003c/span\u003e\n\u003cspan id=\"cb4-5\"\u003e\u003ca href=\"#cb4-5\" aria-hidden=\"true\" tabindex=\"-1\"\u003e\u003c/a\u003eselection \u003cspan class=\"ot\"\u003e\u0026lt;-\u003c/span\u003e \u003cspan class=\"fu\"\u003esubset\u003c/span\u003e(catalogue,\u003c/span\u003e\n\u003cspan id=\"cb4-6\"\u003e\u003ca href=\"#cb4-6\" aria-hidden=\"true\" tabindex=\"-1\"\u003e\u003c/a\u003e                    country \u003cspan class=\"sc\"\u003e==\u003c/span\u003e \u003cspan class=\"st\"\u003e\u0026#39;NGA\u0026#39;\u003c/span\u003e \u003cspan class=\"sc\"\u003e\u0026amp;\u003c/span\u003e\u003c/span\u003e\n\u003cspan id=\"cb4-7\"\u003e\u003ca href=\"#cb4-7\" aria-hidden=\"true\" tabindex=\"-1\"\u003e\u003c/a\u003e                      category \u003cspan class=\"sc\"\u003e==\u003c/span\u003e \u003cspan class=\"st\"\u003e\u0026#39;Population\u0026#39;\u003c/span\u003e \u003cspan class=\"sc\"\u003e\u0026amp;\u003c/span\u003e \u003c/span\u003e\n\u003cspan id=\"cb4-8\"\u003e\u003ca href=\"#cb4-8\" aria-hidden=\"true\" tabindex=\"-1\"\u003e\u003c/a\u003e                      version \u003cspan class=\"sc\"\u003e==\u003c/span\u003e \u003cspan class=\"st\"\u003e\u0026#39;v1.2\u0026#39;\u003c/span\u003e)\u003c/span\u003e\n\u003cspan id=\"cb4-9\"\u003e\u003ca href=\"#cb4-9\" aria-hidden=\"true\" tabindex=\"-1\"\u003e\u003c/a\u003e\u003c/span\u003e\n\u003cspan id=\"cb4-10\"\u003e\u003ca href=\"#cb4-10\" aria-hidden=\"true\" tabindex=\"-1\"\u003e\u003c/a\u003e\u003cspan class=\"co\"\u003e# Download selected files\u003c/span\u003e\u003c/span\u003e\n\u003cspan id=\"cb4-11\"\u003e\u003ca href=\"#cb4-11\" aria-hidden=\"true\" tabindex=\"-1\"\u003e\u003c/a\u003e\u003cspan class=\"fu\"\u003edownloadData\u003c/span\u003e(selection)\u003c/span\u003e\u003c/code\u003e\u003c/pre\u003e\u003c/div\u003e\n\u003cp\u003eNote: \u003ccode\u003e\u0026#39;NGA\u0026#39;\u003c/code\u003e refers to Nigeria. WOPR uses\n\u003ca href=\"https://en.wikipedia.org/wiki/ISO_3166-1_alpha-3\" target=\"_blank\"\u003eISO\ncountry codes\u003c/a\u003e to abbreviate country names.\u003c/p\u003e\n\u003cp\u003eBy default, \u003ccode\u003edownloadData()\u003c/code\u003e will not download files\nlarger than 100 MB unless you change the \u003ccode\u003emaxsize\u003c/code\u003e argument\n(see \u003ccode\u003e?downloadData\u003c/code\u003e). Using the default settings, a folder\nnamed \u003ccode\u003e./wopr\u003c/code\u003e will be created in your R working directory\nfor downloaded files. A spreadsheet listing all WOPR files currently\nsaved to your hard drive can be found in\n\u003ccode\u003e./wopr/wopr_catalogue.csv\u003c/code\u003e. To list the files that have been\ndownloaded to your working directory from within the R console, use\n\u003ccode\u003elist.files(\u0026#39;wopr\u0026#39;, recursive=T)\u003c/code\u003e. In multiple calls to\ndownloadData(), files that you have previously downloaded will be\noverwritten if your local files do not match the server files (based on\nan md5sums check). This allows you to keep up-to-date local copies of\nevery file.\u003c/p\u003e\n\u003cp\u003eYou can download the entire WOPR data catalogue using:\n\u003ccode\u003edownloadData(getCatalogue(), maxsize=Inf)\u003c/code\u003e. Note: Some files\nin the WOPR data catalogue are very large (e.g. 140 GB), so please\nensure that you have enough disk space. If disk space is limited, you\ncan restrict the maximum file size that you woud like to download using\nthe \u003ccode\u003emaxsize\u003c/code\u003e argument (default = 100 MB).\u003c/p\u003e\n\u003ch3 id=\"spatial-query\"\u003eSpatial Query\u003c/h3\u003e\n\u003cp\u003ePopulation estimates can also be obtained from WOPR using spatial\nqueries (geographic points or polygons) for user-defined geographic\narea(s) and demographic group(s).\u003c/p\u003e\n\u003cp\u003eSpatial queries must be submitted using objects of class\n\u003ccode\u003esf\u003c/code\u003e. You can explore this functionality using example data\nfrom Nigeria that are included with the \u003ccode\u003ewopr\u003c/code\u003e package. Plot\nthe example data using:\u003c/p\u003e\n\u003cdiv class=\"sourceCode\" id=\"cb5\"\u003e\u003cpre class=\"sourceCode r\"\u003e\u003ccode class=\"sourceCode r\"\u003e\u003cspan id=\"cb5-1\"\u003e\u003ca href=\"#cb5-1\" aria-hidden=\"true\" tabindex=\"-1\"\u003e\u003c/a\u003e\u003cspan class=\"fu\"\u003edata\u003c/span\u003e(wopr_points)\u003c/span\u003e\n\u003cspan id=\"cb5-2\"\u003e\u003ca href=\"#cb5-2\" aria-hidden=\"true\" tabindex=\"-1\"\u003e\u003c/a\u003e\u003cspan class=\"fu\"\u003eplot\u003c/span\u003e(wopr_points, \u003cspan class=\"at\"\u003epch=\u003c/span\u003e\u003cspan class=\"dv\"\u003e16\u003c/span\u003e)\u003c/span\u003e\n\u003cspan id=\"cb5-3\"\u003e\u003ca href=\"#cb5-3\" aria-hidden=\"true\" tabindex=\"-1\"\u003e\u003c/a\u003e\u003c/span\u003e\n\u003cspan id=\"cb5-4\"\u003e\u003ca href=\"#cb5-4\" aria-hidden=\"true\" tabindex=\"-1\"\u003e\u003c/a\u003e\u003cspan class=\"fu\"\u003edata\u003c/span\u003e(wopr_polys)\u003c/span\u003e\n\u003cspan id=\"cb5-5\"\u003e\u003ca href=\"#cb5-5\" aria-hidden=\"true\" tabindex=\"-1\"\u003e\u003c/a\u003e\u003cspan class=\"fu\"\u003eplot\u003c/span\u003e(wopr_polys)\u003c/span\u003e\u003c/code\u003e\u003c/pre\u003e\u003c/div\u003e\n\u003cp\u003eNote: ESRI shapefiles (and other file types) can be read into R as\n\u003ccode\u003esf\u003c/code\u003e objects using:\u003c/p\u003e\n\u003cdiv class=\"sourceCode\" id=\"cb6\"\u003e\u003cpre class=\"sourceCode r\"\u003e\u003ccode class=\"sourceCode r\"\u003e\u003cspan id=\"cb6-1\"\u003e\u003ca href=\"#cb6-1\" aria-hidden=\"true\" tabindex=\"-1\"\u003e\u003c/a\u003esf_feature \u003cspan class=\"ot\"\u003e\u0026lt;-\u003c/span\u003e sf\u003cspan class=\"sc\"\u003e::\u003c/span\u003e\u003cspan class=\"fu\"\u003est_read\u003c/span\u003e(\u003cspan class=\"st\"\u003e\u0026#39;shapefile.shp\u0026#39;\u003c/span\u003e)\u003c/span\u003e\u003c/code\u003e\u003c/pre\u003e\u003c/div\u003e\n\u003cp\u003eTo submit a spatial query, you must first identify which WOPR\ndatabases support spatial queries:\u003c/p\u003e\n\u003cdiv class=\"sourceCode\" id=\"cb7\"\u003e\u003cpre class=\"sourceCode r\"\u003e\u003ccode class=\"sourceCode r\"\u003e\u003cspan id=\"cb7-1\"\u003e\u003ca href=\"#cb7-1\" aria-hidden=\"true\" tabindex=\"-1\"\u003e\u003c/a\u003e\u003cspan class=\"fu\"\u003egetCatalogue\u003c/span\u003e(\u003cspan class=\"at\"\u003espatial_query=\u003c/span\u003eT)\u003c/span\u003e\u003c/code\u003e\u003c/pre\u003e\u003c/div\u003e\n\u003cp\u003eThis will return a \u003ccode\u003edata.frame\u003c/code\u003e:\u003c/p\u003e\n\u003cdiv style=\"width:200px\"\u003e\n\n\u003ctable\u003e\n\u003cthead\u003e\n\u003ctr class=\"header\"\u003e\n\u003cth\u003ecountry\u003c/th\u003e\n\u003cth\u003eversion\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr class=\"odd\"\u003e\n\u003ctd\u003eNGA\u003c/td\u003e\n\u003ctd\u003ev1.2\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr class=\"even\"\u003e\n\u003ctd\u003eNGA\u003c/td\u003e\n\u003ctd\u003ev1.1\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr class=\"odd\"\u003e\n\u003ctd\u003eCOD\u003c/td\u003e\n\u003ctd\u003ev1.0\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\n\u003cp\u003eThese results indicate that there are currently two WOPR databases\nfor Nigeria (NGA) that support spatial queries and one database for\nDemocratic Republic of Congo (COD).\u003c/p\u003e\n\u003ch4 id=\"query-total-population-at-a-single-point\"\u003eQuery total population\nat a single point\u003c/h4\u003e\n\u003cp\u003eTo get the total population for a single point location from the NGA\nv1.2 population estimates use:\u003c/p\u003e\n\u003cdiv class=\"sourceCode\" id=\"cb8\"\u003e\u003cpre class=\"sourceCode r\"\u003e\u003ccode class=\"sourceCode r\"\u003e\u003cspan id=\"cb8-1\"\u003e\u003ca href=\"#cb8-1\" aria-hidden=\"true\" tabindex=\"-1\"\u003e\u003c/a\u003eN \u003cspan class=\"ot\"\u003e\u0026lt;-\u003c/span\u003e \u003cspan class=\"fu\"\u003egetPop\u003c/span\u003e(\u003cspan class=\"at\"\u003efeature=\u003c/span\u003ewopr_points[\u003cspan class=\"dv\"\u003e1\u003c/span\u003e,], \u003c/span\u003e\n\u003cspan id=\"cb8-2\"\u003e\u003ca href=\"#cb8-2\" aria-hidden=\"true\" tabindex=\"-1\"\u003e\u003c/a\u003e            \u003cspan class=\"at\"\u003ecountry=\u003c/span\u003e\u003cspan class=\"st\"\u003e\u0026#39;NGA\u0026#39;\u003c/span\u003e, \u003c/span\u003e\n\u003cspan id=\"cb8-3\"\u003e\u003ca href=\"#cb8-3\" aria-hidden=\"true\" tabindex=\"-1\"\u003e\u003c/a\u003e            \u003cspan class=\"at\"\u003eversion=\u003c/span\u003e\u003cspan class=\"st\"\u003e\u0026#39;v1.2\u0026#39;\u003c/span\u003e)\u003c/span\u003e\u003c/code\u003e\u003c/pre\u003e\u003c/div\u003e\n\u003cp\u003eNotice that the population estimate is returned as a vector of\nsamples from the Bayesian posterior distribution:\u003c/p\u003e\n\u003cdiv class=\"sourceCode\" id=\"cb9\"\u003e\u003cpre class=\"sourceCode r\"\u003e\u003ccode class=\"sourceCode r\"\u003e\u003cspan id=\"cb9-1\"\u003e\u003ca href=\"#cb9-1\" aria-hidden=\"true\" tabindex=\"-1\"\u003e\u003c/a\u003e\u003cspan class=\"fu\"\u003eprint\u003c/span\u003e(N)\u003c/span\u003e\n\u003cspan id=\"cb9-2\"\u003e\u003ca href=\"#cb9-2\" aria-hidden=\"true\" tabindex=\"-1\"\u003e\u003c/a\u003e\u003cspan class=\"fu\"\u003ehist\u003c/span\u003e(N)\u003c/span\u003e\u003c/code\u003e\u003c/pre\u003e\u003c/div\u003e\n\u003cp\u003eThis can be summarized using:\u003c/p\u003e\n\u003cdiv class=\"sourceCode\" id=\"cb10\"\u003e\u003cpre class=\"sourceCode r\"\u003e\u003ccode class=\"sourceCode r\"\u003e\u003cspan id=\"cb10-1\"\u003e\u003ca href=\"#cb10-1\" aria-hidden=\"true\" tabindex=\"-1\"\u003e\u003c/a\u003e\u003cspan class=\"fu\"\u003esummaryPop\u003c/span\u003e(N, \u003cspan class=\"at\"\u003econfidence=\u003c/span\u003e\u003cspan class=\"fl\"\u003e0.95\u003c/span\u003e, \u003cspan class=\"at\"\u003etails=\u003c/span\u003e\u003cspan class=\"dv\"\u003e2\u003c/span\u003e, \u003cspan class=\"at\"\u003eabovethresh=\u003c/span\u003e\u003cspan class=\"fl\"\u003e1e5\u003c/span\u003e, \u003cspan class=\"at\"\u003ebelowthresh=\u003c/span\u003e\u003cspan class=\"fl\"\u003e5e4\u003c/span\u003e)\u003c/span\u003e\u003c/code\u003e\u003c/pre\u003e\u003c/div\u003e\n\u003cp\u003eThe \u003ccode\u003econfidence\u003c/code\u003e argument controls the width of the\nconfidence intervals. The \u003ccode\u003etails\u003c/code\u003e argument controls whether\nthe confidence intervals are calculated as one-tailed or two-tailed\nprobabilities. If \u003ccode\u003econfidence=0.95\u003c/code\u003e and \u003ccode\u003etails=2\u003c/code\u003e,\nthen there is a 95% probability that the true population falls within\nthe confidence intervals, given the model structure and the data used to\nfit the model. If \u003ccode\u003econfidence=0.95\u003c/code\u003e and \u003ccode\u003etails=1\u003c/code\u003e,\nthen there is a 95% chance that the true population exceeds the lower\nconfidence interval and a 95% chance that the true population is less\nthan the upper confidence interval.\u003c/p\u003e\n\u003cp\u003eThe \u003ccode\u003eabovethresh\u003c/code\u003e argument defines the threshold used to\ncalculate the probability that the population will exceed this\nthreshold. For example, if \u003ccode\u003eabovethresh=1e5\u003c/code\u003e, then the\n\u003ccode\u003eabovethresh\u003c/code\u003e result from \u003ccode\u003esummaryPop()\u003c/code\u003e is the\nprobability that the population exceeds 100,000 people. The\n\u003ccode\u003ebelowthresh\u003c/code\u003e argument is similar except it will return the\nprobability that the population is less than this threshold.\u003c/p\u003e\n\u003ch4 id=\"query-total-population-within-a-single-polygon\"\u003eQuery total\npopulation within a single polygon\u003c/h4\u003e\n\u003cp\u003eTo query WOPR using a single polygon works exactly the same as a\npoint-based query:\u003c/p\u003e\n\u003cdiv class=\"sourceCode\" id=\"cb11\"\u003e\u003cpre class=\"sourceCode r\"\u003e\u003ccode class=\"sourceCode r\"\u003e\u003cspan id=\"cb11-1\"\u003e\u003ca href=\"#cb11-1\" aria-hidden=\"true\" tabindex=\"-1\"\u003e\u003c/a\u003eN \u003cspan class=\"ot\"\u003e\u0026lt;-\u003c/span\u003e \u003cspan class=\"fu\"\u003egetPop\u003c/span\u003e(\u003cspan class=\"at\"\u003efeature=\u003c/span\u003ewopr_polygons[\u003cspan class=\"dv\"\u003e1\u003c/span\u003e,], \u003c/span\u003e\n\u003cspan id=\"cb11-2\"\u003e\u003ca href=\"#cb11-2\" aria-hidden=\"true\" tabindex=\"-1\"\u003e\u003c/a\u003e            \u003cspan class=\"at\"\u003ecountry=\u003c/span\u003e\u003cspan class=\"st\"\u003e\u0026#39;NGA\u0026#39;\u003c/span\u003e, \u003c/span\u003e\n\u003cspan id=\"cb11-3\"\u003e\u003ca href=\"#cb11-3\" aria-hidden=\"true\" tabindex=\"-1\"\u003e\u003c/a\u003e            \u003cspan class=\"at\"\u003eversion=\u003c/span\u003e\u003cspan class=\"st\"\u003e\u0026#39;v1.2\u0026#39;\u003c/span\u003e)\u003c/span\u003e\n\u003cspan id=\"cb11-4\"\u003e\u003ca href=\"#cb11-4\" aria-hidden=\"true\" tabindex=\"-1\"\u003e\u003c/a\u003e\u003c/span\u003e\n\u003cspan id=\"cb11-5\"\u003e\u003ca href=\"#cb11-5\" aria-hidden=\"true\" tabindex=\"-1\"\u003e\u003c/a\u003e\u003cspan class=\"fu\"\u003esummaryPop\u003c/span\u003e(N, \u003cspan class=\"at\"\u003econfidence=\u003c/span\u003e\u003cspan class=\"fl\"\u003e0.95\u003c/span\u003e, \u003cspan class=\"at\"\u003etails=\u003c/span\u003e\u003cspan class=\"dv\"\u003e2\u003c/span\u003e, \u003cspan class=\"at\"\u003eabovethresh=\u003c/span\u003e\u003cspan class=\"fl\"\u003e1e2\u003c/span\u003e, \u003cspan class=\"at\"\u003ebelowthresh=\u003c/span\u003e\u003cspan class=\"dv\"\u003e50\u003c/span\u003e)\u003c/span\u003e\u003c/code\u003e\u003c/pre\u003e\u003c/div\u003e\n\u003ch4 id=\"query-population-for-specific-demographic-groups\"\u003eQuery\npopulation for specific demographic groups\u003c/h4\u003e\n\u003cp\u003eTo query population estimates for specific demographic groups, you\ncan use the \u003ccode\u003eagesex_select\u003c/code\u003e argument (see\n\u003ccode\u003e?getPop\u003c/code\u003e). This argument accepts a character vector of\nage-sex groups. \u003ccode\u003e\u0026#39;f0\u0026#39;\u003c/code\u003e represents females less than one year\nold; \u003ccode\u003e\u0026#39;f1\u0026#39;\u003c/code\u003e represents females from age one to four;\n\u003ccode\u003e\u0026#39;f5\u0026#39;\u003c/code\u003e represents females from five to nine;\n\u003ccode\u003e\u0026#39;f10\u0026#39;\u003c/code\u003e represents females from 10 to 14; and so on.\n\u003ccode\u003e\u0026#39;m0\u0026#39;\u003c/code\u003e represents males less than one, etc.\u003c/p\u003e\n\u003cp\u003eQuery the population of children under the age of five within a\nsingle polygon:\u003c/p\u003e\n\u003cdiv class=\"sourceCode\" id=\"cb12\"\u003e\u003cpre class=\"sourceCode r\"\u003e\u003ccode class=\"sourceCode r\"\u003e\u003cspan id=\"cb12-1\"\u003e\u003ca href=\"#cb12-1\" aria-hidden=\"true\" tabindex=\"-1\"\u003e\u003c/a\u003eN \u003cspan class=\"ot\"\u003e\u0026lt;-\u003c/span\u003e \u003cspan class=\"fu\"\u003egetPop\u003c/span\u003e(\u003cspan class=\"at\"\u003efeature=\u003c/span\u003ewopr_polygons[\u003cspan class=\"dv\"\u003e1\u003c/span\u003e,], \u003c/span\u003e\n\u003cspan id=\"cb12-2\"\u003e\u003ca href=\"#cb12-2\" aria-hidden=\"true\" tabindex=\"-1\"\u003e\u003c/a\u003e            \u003cspan class=\"at\"\u003ecountry=\u003c/span\u003e\u003cspan class=\"st\"\u003e\u0026#39;NGA\u0026#39;\u003c/span\u003e, \u003c/span\u003e\n\u003cspan id=\"cb12-3\"\u003e\u003ca href=\"#cb12-3\" aria-hidden=\"true\" tabindex=\"-1\"\u003e\u003c/a\u003e            \u003cspan class=\"at\"\u003eversion=\u003c/span\u003e\u003cspan class=\"st\"\u003e\u0026#39;v1.2\u0026#39;\u003c/span\u003e,\u003c/span\u003e\n\u003cspan id=\"cb12-4\"\u003e\u003ca href=\"#cb12-4\" aria-hidden=\"true\" tabindex=\"-1\"\u003e\u003c/a\u003e            \u003cspan class=\"at\"\u003eagesex_select=\u003c/span\u003e\u003cspan class=\"fu\"\u003ec\u003c/span\u003e(\u003cspan class=\"st\"\u003e\u0026#39;f0\u0026#39;\u003c/span\u003e,\u003cspan class=\"st\"\u003e\u0026#39;f1\u0026#39;\u003c/span\u003e,\u003cspan class=\"st\"\u003e\u0026#39;m0\u0026#39;\u003c/span\u003e,\u003cspan class=\"st\"\u003e\u0026#39;m1\u0026#39;\u003c/span\u003e))\u003c/span\u003e\n\u003cspan id=\"cb12-5\"\u003e\u003ca href=\"#cb12-5\" aria-hidden=\"true\" tabindex=\"-1\"\u003e\u003c/a\u003e\u003c/span\u003e\n\u003cspan id=\"cb12-6\"\u003e\u003ca href=\"#cb12-6\" aria-hidden=\"true\" tabindex=\"-1\"\u003e\u003c/a\u003e\u003cspan class=\"fu\"\u003esummaryPop\u003c/span\u003e(N, \u003cspan class=\"at\"\u003econfidence=\u003c/span\u003e\u003cspan class=\"fl\"\u003e0.95\u003c/span\u003e, \u003cspan class=\"at\"\u003etails=\u003c/span\u003e\u003cspan class=\"dv\"\u003e2\u003c/span\u003e, \u003cspan class=\"at\"\u003eabovethresh=\u003c/span\u003e\u003cspan class=\"dv\"\u003e10\u003c/span\u003e, \u003cspan class=\"at\"\u003ebelowthresh=\u003c/span\u003e\u003cspan class=\"dv\"\u003e1\u003c/span\u003e)\u003c/span\u003e\u003c/code\u003e\u003c/pre\u003e\u003c/div\u003e\n\u003cp\u003eIf the \u003ccode\u003eagesex\u003c/code\u003e argument is not included, the\n\u003ccode\u003egetPop()\u003c/code\u003e function will return estimates of the\n\u003cem\u003etotal\u003c/em\u003e population (as above).\u003c/p\u003e\n\u003ch4 id=\"query-multiple-point-or-polygon-features\"\u003eQuery multiple point\nor polygon features\u003c/h4\u003e\n\u003cp\u003eWe can query multiple point or polygon features using the\n\u003ccode\u003ewoprize()\u003c/code\u003e function:\u003c/p\u003e\n\u003cdiv class=\"sourceCode\" id=\"cb13\"\u003e\u003cpre class=\"sourceCode r\"\u003e\u003ccode class=\"sourceCode r\"\u003e\u003cspan id=\"cb13-1\"\u003e\u003ca href=\"#cb13-1\" aria-hidden=\"true\" tabindex=\"-1\"\u003e\u003c/a\u003eN_table \u003cspan class=\"ot\"\u003e\u0026lt;-\u003c/span\u003e \u003cspan class=\"fu\"\u003ewoprize\u003c/span\u003e(\u003cspan class=\"at\"\u003efeatures=\u003c/span\u003ewopr_polys, \u003c/span\u003e\n\u003cspan id=\"cb13-2\"\u003e\u003ca href=\"#cb13-2\" aria-hidden=\"true\" tabindex=\"-1\"\u003e\u003c/a\u003e                   \u003cspan class=\"at\"\u003ecountry=\u003c/span\u003e\u003cspan class=\"st\"\u003e\u0026#39;NGA\u0026#39;\u003c/span\u003e, \u003c/span\u003e\n\u003cspan id=\"cb13-3\"\u003e\u003ca href=\"#cb13-3\" aria-hidden=\"true\" tabindex=\"-1\"\u003e\u003c/a\u003e                   \u003cspan class=\"at\"\u003eversion=\u003c/span\u003e\u003cspan class=\"st\"\u003e\u0026#39;1.2\u0026#39;\u003c/span\u003e,\u003c/span\u003e\n\u003cspan id=\"cb13-4\"\u003e\u003ca href=\"#cb13-4\" aria-hidden=\"true\" tabindex=\"-1\"\u003e\u003c/a\u003e                   \u003cspan class=\"at\"\u003eagesex_select=\u003c/span\u003e\u003cspan class=\"fu\"\u003ec\u003c/span\u003e(\u003cspan class=\"st\"\u003e\u0026#39;m0\u0026#39;\u003c/span\u003e,\u003cspan class=\"st\"\u003e\u0026#39;m1\u0026#39;\u003c/span\u003e,\u003cspan class=\"st\"\u003e\u0026#39;f0\u0026#39;\u003c/span\u003e,\u003cspan class=\"st\"\u003e\u0026#39;f1\u0026#39;\u003c/span\u003e),\u003c/span\u003e\n\u003cspan id=\"cb13-5\"\u003e\u003ca href=\"#cb13-5\" aria-hidden=\"true\" tabindex=\"-1\"\u003e\u003c/a\u003e                   \u003cspan class=\"at\"\u003econfidence=\u003c/span\u003e\u003cspan class=\"fl\"\u003e0.95\u003c/span\u003e,\u003c/span\u003e\n\u003cspan id=\"cb13-6\"\u003e\u003ca href=\"#cb13-6\" aria-hidden=\"true\" tabindex=\"-1\"\u003e\u003c/a\u003e                   \u003cspan class=\"at\"\u003etails=\u003c/span\u003e\u003cspan class=\"dv\"\u003e2\u003c/span\u003e,\u003c/span\u003e\n\u003cspan id=\"cb13-7\"\u003e\u003ca href=\"#cb13-7\" aria-hidden=\"true\" tabindex=\"-1\"\u003e\u003c/a\u003e                   \u003cspan class=\"at\"\u003eabovethresh=\u003c/span\u003e\u003cspan class=\"fl\"\u003e2e4\u003c/span\u003e,\u003c/span\u003e\n\u003cspan id=\"cb13-8\"\u003e\u003ca href=\"#cb13-8\" aria-hidden=\"true\" tabindex=\"-1\"\u003e\u003c/a\u003e                   \u003cspan class=\"at\"\u003ebelowthresh=\u003c/span\u003e\u003cspan class=\"fl\"\u003e1e4\u003c/span\u003e\u003c/span\u003e\n\u003cspan id=\"cb13-9\"\u003e\u003ca href=\"#cb13-9\" aria-hidden=\"true\" tabindex=\"-1\"\u003e\u003c/a\u003e                   )\u003c/span\u003e\u003c/code\u003e\u003c/pre\u003e\u003c/div\u003e\n\u003cp\u003eYou can save these results in a number of ways:\u003c/p\u003e\n\u003cdiv class=\"sourceCode\" id=\"cb14\"\u003e\u003cpre class=\"sourceCode r\"\u003e\u003ccode class=\"sourceCode r\"\u003e\u003cspan id=\"cb14-1\"\u003e\u003ca href=\"#cb14-1\" aria-hidden=\"true\" tabindex=\"-1\"\u003e\u003c/a\u003e\u003cspan class=\"co\"\u003e# save results as shapefile\u003c/span\u003e\u003c/span\u003e\n\u003cspan id=\"cb14-2\"\u003e\u003ca href=\"#cb14-2\" aria-hidden=\"true\" tabindex=\"-1\"\u003e\u003c/a\u003esf\u003cspan class=\"sc\"\u003e::\u003c/span\u003e\u003cspan class=\"fu\"\u003est_write\u003c/span\u003e(N_table, \u003cspan class=\"st\"\u003e\u0026#39;example_shapefile.shp\u0026#39;\u003c/span\u003e)\u003c/span\u003e\n\u003cspan id=\"cb14-3\"\u003e\u003ca href=\"#cb14-3\" aria-hidden=\"true\" tabindex=\"-1\"\u003e\u003c/a\u003e\u003c/span\u003e\n\u003cspan id=\"cb14-4\"\u003e\u003ca href=\"#cb14-4\" aria-hidden=\"true\" tabindex=\"-1\"\u003e\u003c/a\u003e\u003cspan class=\"co\"\u003e# save results as csv\u003c/span\u003e\u003c/span\u003e\n\u003cspan id=\"cb14-5\"\u003e\u003ca href=\"#cb14-5\" aria-hidden=\"true\" tabindex=\"-1\"\u003e\u003c/a\u003e\u003cspan class=\"fu\"\u003ewrite.csv\u003c/span\u003e(sf\u003cspan class=\"sc\"\u003e::\u003c/span\u003e\u003cspan class=\"fu\"\u003est_drop_geometry\u003c/span\u003e(N_table), \u003cspan class=\"at\"\u003efile=\u003c/span\u003e\u003cspan class=\"st\"\u003e\u0026#39;example_spreadsheet.csv\u0026#39;\u003c/span\u003e, \u003cspan class=\"at\"\u003erow.names=\u003c/span\u003eF)\u003c/span\u003e\n\u003cspan id=\"cb14-6\"\u003e\u003ca href=\"#cb14-6\" aria-hidden=\"true\" tabindex=\"-1\"\u003e\u003c/a\u003e\u003c/span\u003e\n\u003cspan id=\"cb14-7\"\u003e\u003ca href=\"#cb14-7\" aria-hidden=\"true\" tabindex=\"-1\"\u003e\u003c/a\u003e\u003cspan class=\"co\"\u003e# save image of mapped results\u003c/span\u003e\u003c/span\u003e\n\u003cspan id=\"cb14-8\"\u003e\u003ca href=\"#cb14-8\" aria-hidden=\"true\" tabindex=\"-1\"\u003e\u003c/a\u003e\u003cspan class=\"fu\"\u003ejpeg\u003c/span\u003e(\u003cspan class=\"st\"\u003e\u0026#39;example_map.jpg\u0026#39;\u003c/span\u003e)\u003c/span\u003e\n\u003cspan id=\"cb14-9\"\u003e\u003ca href=\"#cb14-9\" aria-hidden=\"true\" tabindex=\"-1\"\u003e\u003c/a\u003etmap\u003cspan class=\"sc\"\u003e::\u003c/span\u003e\u003cspan class=\"fu\"\u003etm_shape\u003c/span\u003e(N_table) \u003cspan class=\"sc\"\u003e+\u003c/span\u003e tmap\u003cspan class=\"sc\"\u003e::\u003c/span\u003e\u003cspan class=\"fu\"\u003etm_fill\u003c/span\u003e(\u003cspan class=\"st\"\u003e\u0026#39;mean\u0026#39;\u003c/span\u003e, \u003cspan class=\"at\"\u003epalette=\u003c/span\u003e\u003cspan class=\"st\"\u003e\u0026#39;Reds\u0026#39;\u003c/span\u003e, \u003cspan class=\"at\"\u003elegend.reverse=\u003c/span\u003eT)\u003c/span\u003e\n\u003cspan id=\"cb14-10\"\u003e\u003ca href=\"#cb14-10\" aria-hidden=\"true\" tabindex=\"-1\"\u003e\u003c/a\u003e\u003cspan class=\"fu\"\u003edev.off\u003c/span\u003e()\u003c/span\u003e\u003c/code\u003e\u003c/pre\u003e\u003c/div\u003e\n\u003ch2 id=\"contributing\"\u003eContributing\u003c/h2\u003e\n\u003cp\u003eThe WorldPop Open Population Repository (WOPR) was developed by the\nWorldPop Research Group within the Department of Geography and\nEnvironmental Science at the University of Southampton. Funding was\nprovided by the Bill and Melinda Gates Foundation and the United Kingdom\nForeign, Commonwealth \u0026amp; Development Office (OPP1182408, OPP1182425,\nINV-002697). Professor Andy Tatem provides oversight of the WorldPop\nResearch Group. The wopr R package was developed by Doug Leasure. Maksym\nBondarenko and Niko Ves developed the API backend server. Edith Darin\nadded multi-lingual functionality to the Shiny app and the French\ntranslation. Natalia Tejedor Garavito proofread the Spanish translation.\nGianluca Boo created the WOPR logo. Population data have been\ncontributed to WOPR by many different researchers within the WorldPop\nResearch Group.\u003c/p\u003e\n\u003ch2 id=\"suggested-citation\"\u003eSuggested Citation\u003c/h2\u003e\n\u003cp\u003eLeasure DR, Bondarenko M, Darin E, Tatem AJ. 2021. wopr: An R package\nto query the WorldPop Open Population Repository, version 1.3.3.\nWorldPop, University of Southampton. doi: 10.5258/SOTON/WP00716. \u003ca href=\"https://github.com/wpgp/wopr\"\u003ehttps://github.com/wpgp/wopr\u003c/a\u003e\u003c/p\u003e\n\u003ch2 id=\"license\"\u003eLicense\u003c/h2\u003e\n\u003cp\u003eGNU General Public License v3.0 (GNU GPLv3)]\u003c/p\u003e\n\n\u003c/body\u003e\n\u003c/html\u003e\n","funding_links":[],"readme_doi_urls":[],"works":{},"citation_counts":{},"total_citations":0,"keywords_from_contributors":[],"project_url":"https://ost.ecosyste.ms/api/v1/projects/20897","html_url":"https://ost.ecosyste.ms/projects/20897"}