20220128 14523300 1.0 FALSE RoadPly_2021 389883.226500 407854.039500 124954.519000 147486.885000 1 002 Projected GCS_North_American_1983 Linear Unit: Meter (1.000000) NAD_1983_StatePlane_Maryland_FIPS_1900 <ProjectedCoordinateSystem xsi:type='typens:ProjectedCoordinateSystem' xmlns:xsi='http://www.w3.org/2001/XMLSchema-instance' xmlns:xs='http://www.w3.org/2001/XMLSchema' xmlns:typens='http://www.esri.com/schemas/ArcGIS/3.0.0'><WKT>PROJCS[&quot;NAD_1983_StatePlane_Maryland_FIPS_1900&quot;,GEOGCS[&quot;GCS_North_American_1983&quot;,DATUM[&quot;D_North_American_1983&quot;,SPHEROID[&quot;GRS_1980&quot;,6378137.0,298.257222101]],PRIMEM[&quot;Greenwich&quot;,0.0],UNIT[&quot;Degree&quot;,0.0174532925199433]],PROJECTION[&quot;Lambert_Conformal_Conic&quot;],PARAMETER[&quot;False_Easting&quot;,400000.0],PARAMETER[&quot;False_Northing&quot;,0.0],PARAMETER[&quot;Central_Meridian&quot;,-77.0],PARAMETER[&quot;Standard_Parallel_1&quot;,38.3],PARAMETER[&quot;Standard_Parallel_2&quot;,39.45],PARAMETER[&quot;Latitude_Of_Origin&quot;,37.66666666666666],UNIT[&quot;Meter&quot;,1.0],AUTHORITY[&quot;EPSG&quot;,26985]]</WKT><XOrigin>-36747100</XOrigin><YOrigin>-29091500</YOrigin><XYScale>10000</XYScale><ZOrigin>0</ZOrigin><ZScale>1</ZScale><MOrigin>0</MOrigin><MScale>1</MScale><XYTolerance>0.001</XYTolerance><ZTolerance>0.001</ZTolerance><MTolerance>0.001</MTolerance><HighPrecision>true</HighPrecision><WKID>26985</WKID><LatestWKID>26985</LatestWKID></ProjectedCoordinateSystem> 20231011 16533400 20231011 16533400 FGDC FGDC CSDGM Metadata 5000 150000000 /9j/4AAQSkZJRgABAQEAYABgAAD/2wBDAAMCAgMCAgMDAwMEAwMEBQgFBQQEBQoHBwYIDAoMDAsK CwsNDhIQDQ4RDgsLEBYQERMUFRUVDA8XGBYUGBIUFRT/2wBDAQMEBAUEBQkFBQkUDQsNFBQUFBQU FBQUFBQUFBQUFBQUFBQUFBQUFBQUFBQUFBQUFBQUFBQUFBQUFBQUFBQUFBT/wAARCAGQAlgDASIA AhEBAxEB/8QAHwAAAQUBAQEBAQEAAAAAAAAAAAECAwQFBgcICQoL/8QAtRAAAgEDAwIEAwUFBAQA AAF9AQIDAAQRBRIhMUEGE1FhByJxFDKBkaEII0KxwRVS0fAkM2JyggkKFhcYGRolJicoKSo0NTY3 ODk6Q0RFRkdISUpTVFVWV1hZWmNkZWZnaGlqc3R1dnd4eXqDhIWGh4iJipKTlJWWl5iZmqKjpKWm p6ipqrKztLW2t7i5usLDxMXGx8jJytLT1NXW19jZ2uHi4+Tl5ufo6erx8vP09fb3+Pn6/8QAHwEA AwEBAQEBAQEBAQAAAAAAAAECAwQFBgcICQoL/8QAtREAAgECBAQDBAcFBAQAAQJ3AAECAxEEBSEx BhJBUQdhcRMiMoEIFEKRobHBCSMzUvAVYnLRChYkNOEl8RcYGRomJygpKjU2Nzg5OkNERUZHSElK U1RVVldYWVpjZGVmZ2hpanN0dXZ3eHl6goOEhYaHiImKkpOUlZaXmJmaoqOkpaanqKmqsrO0tba3 uLm6wsPExcbHyMnK0tPU1dbX2Nna4uPk5ebn6Onq8vP09fb3+Pn6/9oADAMBAAIRAxEAPwDzrUdc i034pXbPJIunS2sLSzpJgRBMs5YZ7lwB+NYUvxJ0pLjXNWvr24naE21vEVG4soDKTyegZs88ACuJ 8SeJBqGs6hc30wmZbWG3V4uA23JBPrgfLj2Fcjpd9FpMk93hBdX0cgWLJKIOd8bZz/s8GuyFS8Eo nfUpcsm5GF4mubzxp4gvtR0mC6vwzee+0gttVAGB78bSfp0rJEz2LfZb57y1bYz7GXB24BUnrx0P FaSXlxot7d/2fcS2zKAENnhVdnUNtPoAe9YF5b6lJeI8kpdZIxHHuXa6KDkp+HOMVxS9932ZPK47 amjo17bjVkS5u5YrOR/nkFu4wuM5xnPPTirlveiXUIF3SWkHl7HklkLcjgkAdvaoP+EPvrhpXunN za/fRjGC4booznp0zV3w34HmjvJLG9unhRod6XUhURRHeBu5++eSqoOp5PAqbNvQ09nNatCaPq11 a3UVxaXRjuITujljc7gQeCDmva/APxOv/wCzhY61rXlzzD7PYXcyZmVXbZIjyEnKkN8u4cEGvCPs MzXQVFhsvKYxlPNAfIOD17nriuh/sS2hk08W/iKG4ubwBWjmBijhYjne7cZHI+lOnzU3dC0mrM+5 dcu4/D3hbUoI7qS4hgRI1mWTzkmO9RuDgnaOccHPGaq6xNfaNY3t5cTSW9ncKvmLCxEluBkIWyeQ f7vXnjNeVeFfEdn/AMK/8PeF7K+tr27tgjX0kPz2calnkzvwA7jYCcDrjkim6j4yF9cTSCW5uLW4 Y4mYHczLjDOAcDByB0xnNenKvFK5jTw8pHVza5JdNLFbCYyuqF57jOWZGxtz34PTqcY5o0/ULmy0 6W2V3+3wbbeGONP3mxs7txJ68gLx6dDXL+GfiLa6P9oW5hivJFJmV9m4N0whznoRu6Hk1NoK28kO qXt7f+fDb39tGkkeRvDMGfjoCoZeTxx7VjCspWtubzoSinfY7u8urnTLyOx1G3ZUlhBZbOTZIuCE 25GQDkck+9J4T0Vrplms9Ta1jt7goJFlcmVucqV64U/ePfI9Kzvi9cQ6Pp6XMUrRvLE7okw3s8is jBVIxljnvwQKm8B6k3hfT7OXUrVo7yYZimChy0mSzAkH5Tz9etbO3PZ7GKUuS63PddD1aTU7MO4Z WHBO1gOOMc85rR8xv7x/Ouf0bxbp+rWccqXglDDmUjALdDk/X1rXt7uK6TfDIsi9NynIr0otW0PJ lFp6os+YfU/nR5h9ai301plTknvj6VRNix5hP8R/Ok3e5qJZA2cHJHpS7vSgRKHI7mneafUmoc0A +px9eKAsTeYfU07zT/eP51kx65ZyTGMS7WV2jcNxsYAHn6g8HvV5ZBIu5CHXjke9LRjcWtyx5h9T +dL5h/vVBuNLk8UWET+YfWl8w+pqvupd1FgJzIR3/WjzD/eqAtupOaLAWfM/2v1o3H14qvTt340W Am3n3o3H1qLfSb6AJtzev60bj1yah30u+gCbcfX9aAzetQ76XfQBLvb1NG4+uKi30b6QybzD6/rR vPqah30u6gCXzG9T+dL5h9TUO+jdQBL5h9T+dHmH1NRbqbJMkWC7bQe/akBP5h9T+dHmH1qpNeJF sJZdpODz2Pf86m3cUDsS+YfU0eYfWot1GaAJfMPrS+YeoJ/Ood1G6kMm8w+po8w+vNQ7qXNAEvmN 6k1geI/GEehso3I5jkRpVZwP3RHJB7HO0c9M1X8QeMl8O6pax3EEgtXbZJIV9eFZSD0zwQeleA+M PEE9v4nuFhsZ1tLhn2rhJGuIwMPtUnnrnK88cisZy5VodNKnzas7zwx8WPE+pa9bxzvFPaxTyCeJ I1j3qFLdT0A6D1xjqaz/ABJ46XTL7R4luJVJujLaJMCx/dhsE+ud+ME9hXmn9qW2k+DtV1a3eS9d Z2SePaBJbblKswUjcqsCp9crnpXFR+LLm4utKu7iyl1uH7NOAG3EMoUBhx0wOa4uZxjZ6npcicuZ Kx7Ja/GTUvEXjC8uPMXTk+zCCeF3YxSKT91h2znIPBzxmoJPGmnaD4mt9StkdNJvrWaCKKSYtAzA fekyT8w24xxnIzXBeA9SiFpq09xPYxaabZpZftO5yiBlKAg85UKAAemPfNdFD4T09V3/ANm72l+Z mkU/N3BxnaPw49K1pxlJbmVSUU9vItWfxGn1bX7i1tXMD3HlnCxZNuvlDcq9+xHHADetZ2oeJ9I1 BprC6uV/tvTxJFa3UO/NncMQxlGCCCoTGegBOOTXc/CnwfY33xC0SKTRre4iaRy8ckIYFQjE5B6j pX0DJ8LvCzZ3eC9GJYYYnTo8sPfjmuHE1nh5KDV76no4WisRHnTtbQ+MfAPx+1X4f61O0n/E2fUf 315BPdNt3Oy7WGWYKyrzxyd/PSvoU/tC+F/7UsrTfPCLiaSJpJiB5aqQA5x2JJ468e9ehN8K/CP/ AEJGic88adH/AIVG3wr8I9f+EI0bPr9gT/CvNhjK1O9np6Ho1MDQq2clqcP4m+NOk6Zoct7pUy37 qSmWbasbYyCwPYj3zkjivGLX48San4ohvo5g8Ux2mC4Cxup2ksRjqSBjHTI96+nG+FvhDZ5f/CF6 PsJ3FPsa7SfXHr71GfhX4P6f8IToo/7cVrqeYSe8TmjlcI7SPm2z+IVv4uvr1bOOaLDrKRcsArxo MLwT8rA8E9MV0un6pdaXq1leSXMltNb6f5kcM+WYrtz520HDgsSdvXGD2xXr2q/C3wYlqYx4N0eF 5QVWT7Lt59+eRk9PevIda8K+Dp/J0PVvDdtoOs2zSNFMYJMRENtCuc8x5xhuB8wHUcuOPvvFjeWd po3dA+Jmo+LbXWNPiuYY9XgjaaCLqW6soDd+FOOPrRb/ABUu7yD+0ImZ7Y2UrOCDlHjQNkDuWyw9 OK8r+IvhGD4eapp39peGLHTW2vbvqlokrWt1GSHVxyP3yrvIUYLAEVB488F2mj6hYWWkaPEbbV/M FhewzMHwojkkUqrfMdrbQerb8HOK1WP29053llr+9sfQfhfxdda1a2ct5ALQ3Rby1GecNtA+uc59 8+ldO0NweRHKR2IU14Ja+F9D0vxN9hk0WFrO2EKzyNPLJKzMnyxqA4Bc91H3d1eq+G/BnhjXLSc/ 8I5GPIlaIGOS4C7QcAcSYyMEHHHFL+0ox3gx/wBkSk9Jo6FoLn/nnL/3yagaG57xy/8AfJqBvhf4 Zz/yAMf9vFz/APHKib4Y+GhnGhsv0urn/wCOUv7Uh/Iw/sep/Oix5dxuHyS9fQ0VS/4Vn4ZWZE/s iRXY5UfbLkZx/wBtKKP7Th/KyHlNRfbX4n51XN7FY68Vmkhuofs8cpYDcGwThc/w88nueBWdrm3W Llb21QpAFYOA5Vh/tN7Zx9Rx2rP1KQzXEkvCu27LZAPB4x+FR29xIbYKH4YEPlucen0ojLSxEo82 5p6SqW7B5PlbZtbd/CR049P6Grl1cQzTW0nlRt5RLKQOQ3rn/PSuZtvPZTGz74+QAw6e596vwyPD GEB4XhvcVMmlojWC01R0tvqkiJIdnmRuMHdwQM9amk1gSbTFHltpxJIo4GecZ7+4rAtZGmfjGzj7 w4P19Ksxn5inyuR69uetYts7FZkutNe6tFc3xliF2+B5UNsAkvReAB8nGT6fiax5o5/JtIvsLKyk 5LfNvJPBI7ADt+ddPZTmOEZlEi/88/TPbNTLOkbOwzuHock8cZo53K7ZhLDw3QvhiSTQ7VlXMLux LtjDMMY59F9h6V1+k3vnRqbm6WXDNknIYrt+UnHUZrGssTQyqFzvRd0eOVGfvD2q3p8c1pb6pIqr 50Nu8hYH/lmGG4Be5GcjtiuSV1pc6oRSjYv28MupSRJboPJhkCMMhQqvyGDEdiOfpXSaSslxa6mp mieCSaCznU48sM20l/bIHX6DpXEae8kcmoxwM0iC3Z5GY7Y0OeHP03fqKv6LrEcK6iIpJY40WMgu cHyOAZGx0OenccAVrRrapdLE1aXuto6f4tX0dxqmmRW9/JeaQlyIIPObkMqqZFIHLcFQD3BrS/t+ 5iaO8uz5QwwtbeNiVCgAAgc4J55PX6VzniTxFpWsr4b/AHZWZd9zczLFs5Z1UIcdT8ucnjoK5p9c mWa7aJ5lgmk3gKMcA/LtGPTqOlem5Le+5wQg7Wa0R6lY/Ee4vLk21wn2bTYDxEJNoxwFQemRuz9T Xq3hHx5Yafbzol1H5MMW8MZFyBjJRUzkhc43HtXySNRlwVVZgRk7XGGOBg9azo7iTzhLKBbynkNv UHae+QemKUcRKmOeHhU02Pr7Vvj/AKZaQTy2btd3GwmONVIHmdAp9ujH2rD8K/Gq+1zw2raqsa6u pMUskQ2JKpJ2Oq9j0z2FfOum6qNsgmKB3yA27OT26Vr6DrtnHdRLMFlVSCV5Ctg8GojiqspXbKeE ope6fWOl+NZYbVIpXXzpI/MEnYscYOfStPT/AB1bQ20d5ezrHA4PQ54HVseleCWniX7Sohs2hjkm Eab7q4w4LZxx/noBWRdeN7u+gtJ72O1tmtXktoLa1dpDIUJTqw5X5Tk9Oa9L21rHmPDptpnus3xE nh0q5a0P2q+AkmSN5MxsDnaAeu04HuM18xfEL45eJPilZ2FpZ6fcaRf2t75t1a20/mKsij5ZI364 4PJ9SCK2Ly4W80ua3u5I76xeRgkJiIVwAGwe6FT+ePevItON4dOW8t7qNrZmEJkVwHbJyDgY7dqx q1W1YuFGKlc9e0/46attZLkNe3e1d5djGzEHg5Hfgkn1rpPhn8Z9YuNevru61iCaKe6w1k4Ki0Ud o8nBU8dsk56CvCtL+2X0K24idrmZjGXX5sLk/Nu9hxmneF7g2OoIJY9zxF13dMHpnn0J6VzRqSTT TOpxjLRrc+6PEHxT02z+H934hh33AgTcbdSFYtnG3J714n8Kf2hrVvFd5N4p1aeSCaZpluCm1Isj aibP4VxyfcV5ZrXii9v9KfTYrnyrFcfuVOFVuPu++ea4ZXi0XUoDFcyyxrLsudqDe+ecjPBYHFVV xM3JSi7WMVhoQi01e5+hmi/ErRPEWpfY9PuhcOSQMAg4wDnB+tdSoLdBmvjDwb40t/B9pa38139s 1GRxIQ8pD4zn5lAxkAc85GcV6FrH7QdhrAtnivmSWNvM2xKypzwFJzg7TySeMV1U8ZG1qjVzlqYN tp01ofREl5FFMsTttdug9fpU2a8DsPHuoXuvWskWp2Wo3Soiusc4bfnl1RhjBJxk44xivcbO8W7t Y5V3fMOQ6lWHsRXbTqqpexx1KLppNlvdS7qi3Uu6tjnsP3Uuaj3Uu6gLEsYLuFzjJxmvAbf9rK31 Tx9p2jaZ4cafQLi5NnJqk0zLMJA2GZEC42gc4b5jz0r1LxN48Xw9b6i1nplxrN7YxGY2kJ2M4Clj jucAZ464PevzkvvH2o3Hja58VLLKNQlu2uXt5BsPPGDtxzt4LDBPJ6muHE1nTtys6adNfaR+o0RF yqPbsLmKRBJHJHyroRkMPYjmmSXEcIzLKsS5xuc4FfnHJ+0V4tuvDNppC6pPbWVvPNPJ5JK+c7tl ckchI8BQg4rpl/aY8V6p4TOh6tqqX16rb7a8ukBMjEfKjsMEYI4PoeelR9eitGioYfmklc+rPE3x 90bw7cXEK2slyYH2yN5qoNvOWB7Yx34rzux/bE0Bbe+u4J59alilSP8As9lEBdWbBkiZuCFHbvmv jTVNZk1uSW9ndZbqRyZgD9455P8AnrUX2WSxPnWzYbcHKj+EgA5X05rhli6jejsdSjTS5YxP1Q0P xHYeIbOKeynRy0au0O4b4yQMqw9QTg+4rS3elfE37OHxw0jwjNMNbvoojNzI5Qk7cYIL9yDlq+qN e15vsFtf2d4fs0t1bKDHMmHjc54UjI3A9+K9OjiFUhd7o5alDlkuXZnY7tvU4+vFRG+txkG4iBxn lx+dZem6haStLCzf6XH85hldTJjGTwMYwePrVO+1bRtNvhPewrZhYcF54Ao+Zxg4x68ZrolJJXMY 0+Z2OiF1FxiWP/vsVy/j3WLe10aaSPUY4byEb44/M+V2HQMB2z37Vxvjb4y39jBaTeGNJgvII5GN 5PeyRqAuPkjRd2RI3UZ9Mc5rw7xh8ftc8YWpQ+HrONowRJtUhlYHByAflODgjOO9RKrFaG9PDyep 3qfFi4uriC2VmUQvGDKGywJBO36DkZ9xXRp8cL43tt5dusdmzt5iSMA0aqOQe+c4x65r5v0nxFHr 3jApbvJBbXvlSyK0mwxlIyWG7uScgk9ce9dPqXiCwuHsZluXnNvCQQItnyZGzJ7jAC46kCuV1Ha6 Z1KnHms0fXHhfxnZeJLUPHKPMxkqevXGfbJ6Cuh3fnXyj8K/EUk/iq1Syz9jwHWSQ8AHJPOcdT+g r6giui0cbCRHDj5S7AFq66cuZanDVp8stC7uqhceItLs1mabUbWPyZRbyK0q7kkJUbSuc5+ZfzqO XUEiYCeaONScHDgD8Sa81+Iviy1k06SMaXZzGO5glkn3xs2UnTHYs2cdCeAfaic1FNip03NpHq9t qFteSTx29zDcPAQsohcPsJGQCRx0INStMI0Z2OFUZNeQap8b9MgS5+y2Hlm2dSY4njA3sSDtx2Hf NZVv+0NZ3DPG8MpuHfYkAx++H+yc8AY60ueJfsZb2Ow+JHiCyuPB832qRYZN6qWYthQW4cMvQj1/ OvAo9MtI7yPTRdyxLbZuLO9Xcg3HLHZITkFsMBnAbkYOcV22r+LDqUNgGeMzTsS0UV6qvLHnBEow VTHYnnjGO9eceKPCNrq2nXVxoVzqFtYymMNJdziSIyfMcFducfKcL2zmsZ+8zaHuqxieItRbQ9W1 IPf3F9p+sokhv4SUt7hmGzzSnRMHC7O2MiuT8L3DpeLpF3PPZNbzyrFJZ5Zg+5QckcDcgC89eTUd 94tnu9F07w7rkL3o066McEcb7iIpFK/vVHXll+cHIx7isLRvtOialf2sll9thvisaNJFJu2hiBLF J0BADKc9cc1yvubpvY7rxNqWt6nZ2ltBpqanHaqs66nYkMby3kb/AFDxgj5M+oyCpJ4Oa6a48C+L tV1bT0i1K6ttOmSY7bO/QpGFAKIx3fe6rx2xmpfBUF5eXFzHfWENrp1zY3M2WtCLcjyyFgjnHJK8 E9uW9a0tU8HWek+NvCE+m2McEGqWrzPDCyGOK4FqgfaAc4cpv3EDOc9TRzOLvf8Ar7y+VNaxf9fI zPCPw/12w+IFj9r1XWbeBUjeOZb4q5cmQMuVbIGAK9B0HWNW1n9r7xR4Bl1i/Xwtp9nJNDaw3Uiy K628LDMm7J+Z2PvmsbwrpcmnfFaRZYhC62dvGwyMg7pWwcexB/GpfAOl3Kf8FBPiNq7vGLQ211AF Eo37vs8GPk6gY79O1cmNhHkUnudeBlJVOVLS6PoD/hXtoWONU1tTjPGqTf414X8QNY8Q+Gf2qPhn 4J0/X9QPhfW7yxjvreW5keVhJKwkHmZyFKjGB719KLcfvCCe39a+Tvilbyy/8FDfhNdh/wDRo5NL Upu53B5G6fSvJo025ant4yXLTvFdUaP7MHivX/jFqnxDXX9d1T7PouoLb2SWt08W1GeXgkH5sBFF ep+OF03wFpqXN1q/iS5nmIW3tYNSkzIcgZJ6KBu6+xwDXjH7CdtPYXHxUknkXdNqsO0B93Rp8/zr rvjja6nqHiL7VZ6pdQW9kGVrVrU4MwAPB/ijKkYYcD5uppVad6jUdjTCz/cRlNXf/BO58Paj4G8c 6boVrpus+LJvF8kV1LqWk32rubQxRhgQjgAfMdhV8/LyT6V5NfR/8JcusadpviHVrMW0Jkt49Z1B 5p7SZdqsVYfLLEThQTxx83OK8Hjv7q08SeJmjV7G7Fndwyxm6YARumHQueuc5wRz0x1r1D4A+IPD E3hHRtLGi/2bqcF+1rPqEF5Mp+zTKfMxK7E87U+TG0dRzWPsp0/ek3oRCzqaO6dzQ8aeE9T1b4ey alHrt1q1tbAy3WkXFzIfJjjkAMiIc+WVO5toOCMgVyHw2tZvFXiax1LVvE+pXlhodjNqkj2NykU9 lbxwPvMKnJkmVISAo2jBTJzwfcPEnheyuNYvNBvZL/w7r12s72OpaffN5N5GFG+SIOTu+TKvC/3W yR8vNfCtrDND4H1F48q66gkRkaQr5amN90eR/CwHK9DtGa6KcJVYtKVv+CYYv93KLS/pH03o8Mvi Ozh1fw9qWvGxWeR7KKaVi9lEzMwupDjLHlVx94nngGut1bU9c+HPgnVbyPxPr9gLW3WZf32/yVBw DsGAcsTxkE5pPhrJaaF8I9LljtHljXSxMskjshkusKAmOAI13D5jyxZiAcZrh/ip4m/tnwj47Tzp Y1jtgBFLJtLONp3dMfNu3Y6AbR61nyuUuW+h2aQp362/Q9z+EeneIfiv8L4fEGm/FnWo5/tN/Mby TTyBeQwxoRFsaT9ztYOobndnOO1dv/wiuoMFP/CW+I1Bxx9uzj/x2vgi41K+t/hD8ELW21OS1SXx HqjSeXcsiSKbm2G3APzjjv0z71+jHiXWbLR5Li6u7hbe18/Z5xUlRubC5wOBmuetSnTn8V09vl/m LAz9opc62t+KPD/iR/wnVjMlt4Z8S3g8Q2kwm2azqscULWmwl5UkfC9AAVJyD0orhP26LWSTw7oD ESRGTVY/MYsoTHltwpzyT1xj60V20aLnBSb/AK+883HVpU63LHY+VNZKTagwV2K5xIY1AUH09sY5 NKs0EapzKFxkKQuDVi9js3nl8xZXYSbsBsY9uKaEteDsdlxx8wGDXdfTU5uRp6D7URM5JDhW5PT1 q3tjRW8wF93yruIOT2FURLGMmKJmRecbsHFSzXULRtJ5LKQMhxJjntj3rNlp2L1pcQTSgMrhd2Ww 3p26Vf8AMtlkIaPIIyCWOevFYdlqVvHJKWgKbQOfM4Jp7axCszy+S3opLE/jiocZNmkakUtTo7WV VVkjiDyNzjc2Oa0beSOVvJmRGXBPzcYNcxZ3iNKvlQruC5LbmIPt1/Gta3v2umk3wxjsnBOSPQ5r KcX1N6c+x0VqxhlVXEbLGMeXk5wfU5rTRw9vcsChVImCkgg4OAVOOoPTnjj3rmI7p5GDxxxEgckJ 17fjWvHftHby7tq4TcflyCf/ANVRGV3ZnRy6XSNax064bQ725hELl2jiEmflj2hmcsO5AUH0Bxms G51hbNXtNOmlkZ/me4lQKJT/AHsEZYDnGfr71vTK+maU9hJvlvpLovLHDIrRMNibQShw5ySQB3HP SsLWo72znCzahDZO2Va1tYVmnJ9DzhW9i1FovVEybsUI7W6kUyGSVpGB27izfmOhyeaqLDqahjtZ f4vM3EjGOP8AIrf12bTLW/NlpOuSa/ZRokhv2haDdIygvGVOMFDlcjg4JBxXDTajqct6LdpvOVXZ Tj7o54wPTmqpybk0RPlUU+jNSS2nmjCBVNxIRlzwMDOWP6VNDo9xCIoiYjF8p3MygFT3/Qms/wC3 RWs0drHGWlLZLSZVT6gk9a0bzR2uJEUPuwolRWIKnnA6emK6pbWZyKOt0Xo1aG1be8RLAoqnO0D1 9zipbez/AH2+O6yGQbJOSNvbmsW5tboYt5rtZpZmyWdtxXIzg9h3rQt43s1UC8ibYQDyVXGMDtyP pWUrrodFOMW9WbF0t3NbxLHGb+4dxlioKqQMhSO4xz+FJJ8QLmC6so2t7HTXitGUC3j8/bliV4Y9 yOccEdDVrQ7VprqBvtE1tcGRECQRs8gVvvSKMgE7QeK0vH2h2zeCvt1rB9uhgnkS2mhT99bL5rYY kDLK38SMAAemCOemnOUmmjlr01BM52HxnLrV5J58kD3MrBjHbxeWpGMH5enIA49qq+ILqTxF4onm t7K3ttPWUeQvG1QByTtx37D1ri4vtEepBHlWFkYCRVbHykZPXk81LNqW12IUAmMWzRrnb5a9gPfq fWrdXdM4ktOxos0UN7boqXDFX8x3jR227vmBOB8uOmela/gjR9U8Wea1ibeZYt+6S6vYod21c7VL sNzAdhUVn8QvEng3RdJGga3eaIl010J1tGCiUbwMNx0wf1rO8LyQjS9P822WSFtRkXy8A4/drjGe +efwpc2l0bxWqubumvZ6pFcXs2tw2KRGRLfz7OWVZ5Au7aNv3CeBubgVyLaodWumVLeF3VfnUEkJ jnJIPYmtzwzrVtfQ2SNZW5jOoOB5ybixFsWzjOOoHBHapNR8Taj4+U3V3LaTTafYK05s4IrbESsO CFUB8Fx156+lRuxv3upesGNlYlbpZIyByqDJckjgfU46V6H8L7XTLi6nsNcD2d1dJ5GxuVRfQsvT oDnklvarXhz9lf4m+I9A0rWLHSbSfTtRgS6tZpdUhVjEygqSpOQeenaur0P9lH4nW1xPLf6Np5G0 RyxrqcT5G7G4c/e9/alDmUk7BOzja5r+G/g3YzaabuySP+1bO5YMHlwJEz8pKD7rAc5HrXuHh1ri z0uGG4jl3rx+8kDH8zXG/C34J+OPDMl5b37Wa2NxButYbmcNKJecfMAflwO/rXpVh4B1WS1gfzbO JpIlcr9txztGeMeua9mlUox6pM8mrGrLpdDFuD18mbHsmR+ho+2IPvFk/wB5G/wrtbT4a6S9rB5m t3kd49urtEvlsolLYKg45Xbkg1B4s8DWWgaFLf2GsXN28c4j2TqqrsZgEPA6kc+xqo4ylKSir6+T MXhpxV3+ZyP26HPEq/jkVHeX3k2NxLBPCsyRs0bSOAoYDjPtmoDd3G07UE30OK7bT/hydQ0mzvJb 2GI3MQkMLW5YpntnPP1rpnUjTXvPcxjBy2R8PfHTU5fBvh631FfEFxoOpSXiXcd5bNJMsFwp3heP 4G5z2AwOa+XNa1W61u+n1O+uk1S5umMsk6EYkJ6E4x+WOK/W3VvgEdWjuba416zlt5EdCk2mCXgk EggnB4GM9eetfJHxy/YitPg14Rv/ABxB4zN7pdvqMEH9jR2Bjk2zuV+WVnIyueMjtjNeTWqU5tcs vzO6NOfVHy3Z6Tqt1pt1PcxiBWkCLbsgWMAgDOAeByPzJqf+zdRsbZppYbVDCzK/mTx4+UcjIPzZ HTHtU63lpBrl2kM01tYBtiec4klZQcAEjhv5U6Wy0ZrG2LNNLDHMxaO3t40ZyQN4GW4A4561yzSv qaRt0Zyt1FDHJIFkMb/eEQyNvcAVbS+32T/utvljcGbK78dPwqfUrmCRFmFrHLAsYiWR+GCj2HX8 earSaleX1vaLK63lpaIYbZJmY+QhOSoHYc5xRJJi67kVipdkYpMq5DFYyPmBPTpxxXttr421W+nt JPtMxtVttkUTXOPL2q20gA9c+vrmvFp5rX92GhmlbAKrGTsGPfP610ul+IIr69jMNjZ6YLe1eNls YzGJBsbLOSTlz68ZpKPU6KL5XY73T/iV4i03UFuotTuRclg43zZPAxk5znn1qz8R/jHqHi/4bxpc mSS5TU/IaSJ+JSId5+nJ+6O9eTrrS21uyiM7SOsb459M1Q13VhbeA7O28qaOC41KeXcjNklYkUnd j3HSqipXsjqnKEVzMzde8ZatrGnwWlxcNHZwS+YrKNzucYG8fxEY4J6c+tX9P1+8S1ZDcNItyu15 JMksMfp/9aoPF2j6bY6Hov2PTXiu3nvGeWFyTOgMW0Z/i25PHUBu9Z9isEMIV7mVpCo+R2Pyj8s1 0qPU81ybbuzp9D1iTTb6EvPJBHuwwjG449a7VvFQuLW1is0mjgsYhJOzz7QxLjJVfc4Pt0rzB5YV 6eaRj5fnx9K6Dw7eRSabrCiCT5Y41EjSAK5MgJB7j8KNdi00ehH4mXkM1vdaTYQaVDAyx28kMREO 4dQc8Mf4gPXrXSXnxa1S+vrKXXtV1C9smhjuJYbOcQSOxTqrYIH0xXJeBfEuqt4Z1vTP7QlTw9Ha zTT6Yl2TakkHBKYOSWH3hyMVrt4q0K31HToNU8BaPq8V9Z28Mf2TUbixNs5xiQBSwc89G4IFHvan RGUNGbtx8Ude0m4urSDUp7qyV/lhvysjlMBhuIGM8449M09tW1TW9Fk1iE2n2a2crLapfoLmEZGJ vJY72Rcjlc9a4bULl7jXtZN5YrbGLZ5JSZsSEBc8DplfWpNK1KwkvLtLeDLraS7MMzMigruwT3bk UpSdmNcrewy+vpGmAMrSc7mfP3t3OcfjWVcasFYhpGWdv4lOKXUL6zgdZIY43ibcImlkIZTn7rEc AjpxVDQvGUVvdBb7w1Y6hp0hJuElmdZWTuqyDleQPmAzzWiuYymjTTxI6x+U1g1zLJlTOkroAMdO KyNf1WfTZbS3ht3keaNJgqzy7SxH3WQNgnjuM4HavStF8ZeANUs41svhve26Xt4lsstvrjSi2nEY IdVdOV5J2n04IrzS48Q63fXlhDYaNpyS36Lt1O4kP7lnB3BiQcDGRnHesJXuW37umpyWtapc3Ucl yHkDxou+JCdoUHkA9Sv+FdD4bn8S2Nwkiz6tLpd+gljtLd5CjREkcbeFzgkd6raLb3MNvqf2pdOW eKNRhLiJRECxBZnORxxjPUnFe9/s06f9q+GuqXWtw2FxMXnkTzyHljVYlClQp2hOSfXkGtaUPbS5 EYVJKjFTdzNsIY7WaDUl1K5hkjimmge9umEViArK5aJ8ZyOuOw4HStnT5dBk1LwneP4r0d2topoZ pGaRnOyFQP4RhFGPvdAR1zXpHws0/S9Rm0KOeysbi5uIIG/0jY6u7YXLdc8j0r1LwzZ2Unw3+Cxt dM0a7W61NI5HuooUMmI7gHeoUnB28hjjhc1M4yoqFnuv8jaEoVnK62f+Z4n4d0uPT/GyXXno9rJB AqssTIvWQ53EYPUcD1rC+Gshk/b0+KEqsBEtpc4kWZSQMQAfLnPOK+7Lex08PMp0/STBu3QyRrC3 BAG1lHQjnn0pseg+Hob6W/i0jQ4tQkB828jtoEncHGd8gG45wOp7ClUqOrGzKpU1RmpLoeYLdHzM C4kPHTAPevFbz4a698QP2ptL8a6XPYtofhO4s4b83ExiuhJGjlhEuNpxu4ya+lfiBJZafoN46w2k OI2O6MJvxjnb71xfgXxdo2m+H45l0jfJNciOZdis7SYOGb+8e+e/TtWcKHJHnbOqriPbNU0jyz4E /s7+OvASa9Ldy6Jc/b78XQOn3TlDGA3Jbb947unPesf4k+DPEXhvxZdwas0hSQRzhGuyY9jEhWHO SmOB9CDX2P8AakudNBzGEaPG1WG1eOgxwPwqLWdI0XULqG5vdNsb64SOOOOaeAO6gchQx9+QKzlT Td+5pTrOC5eiPyY1i6sk8ceM0WeGS3t47gfMNquMqoIj/h5PH4e9dv8ABHVE+waZORNBDaXDFzb/ AH02hydvBOSCdxxxjivs79pDwb4a034I/ErVrPwvotjrH9jSsb6HT4hO3zJwz7e5x9a+SPg34o1u 98Ksyi0hvEuH8tbfToFwvknJ2BBuO44J96xxEOWGhVCperr1PaPEXiS08T+B7uK9AOoxzNcxXlrH vkhCg7LiFtvGOh7MGYHivg9NRuE8KXxZ2W0ub1A8WMq8ixOwYN0BAcjb6NX19deN9ch8HpeDWILl dNR4r22jgWKYW7KyrtKgADJwc9eR6V88/CHwT4R8catfaT4y8dQfD3w/Fbfaob+ezNzA04G0jywQ c7AeRkk7RjnNYU5KjCUpbLtr/wAE0x0udxa8z2+fxJBp/wAN/DWn6RC2rTzW9lcvbsxRo7poxGkY J4O5tzEf7NWviB4NHgn9nTxPda3LMdWubRYgCQkaSvIrNtzkvk5Oc5OBjAGKyvBb6bY+JNT8QaxO tnpHh77NaWulzTq6RnyEPnnBx5mHyevlliBkg1p+LNesPilaz6z4zubzTPh9DbmO2sLYK1w8WQfN G7I82Q7cHGUB5A5rFvld+i1/4B2c14NvezS/zPnmbxCl/wCEPh/pMdvLbJoV7cXS3LOp3iWeN8gd tuzue9fWPiz4meHvG2nz2WsancaVbrCMsq7o2nUb/LVgQGDE5IbmvjzxAtla6hMunCUaau7yBcOr uFyMBmUAE9OgrPutSuLe1e1SR2TGcbiRuI6j0rqnBVbM4qNb2N1a9zrPGXji+8SWdnptxqP9p6da XQe1SR2eSNMEA/N0BzkjPBOOlFecwyMtzACPm3jpnj2orW3LojinF1HzPU7y4tQ0lycgnJRFUHue 1ZF1b7LgRrJgR4J2jv8A410eoyJFcbQR5yk7inQN2rBnhBlYk5GS2fVqiLujrqLWz3J7WGK4dmAO 89VwTn/IrQXw3thLF/Nkwu2GJcrg5JBOeGHHHvWJb6jItwgiC7lwC5PAPTOO/pWto7T2t9atKWKE fNycZPIHuf8AGk7oI8suhnappctvJHIkU0iSYVPLUNznHTuSaJtKv7eRoHsrlLhOTGQPu+v6fpXo nh28i03xNo161uZ0s5xKbcdMgEAjHPGc/wDAaseINfj1L4iapcRW99PYzW/ks0UTIztgs5I7DLY2 5zge9XGfMrmdSjZ37nmtrb3FrHvkspljc5+f5c5GQenfFaVrC1pbiZIGCKQg+c43E8getddoeh67 fX01jq2kyJFeGO6F1uIWGJAdy8A4z8vB9BVPWNFuptYkbTtOulgIWP5k2IshJyVA7AY+maUot6jh 7qMyHUds3mRDaxzn+79T/wDWrbe+SSJyBGjhQGOPxHfnmsKHw/fR2tzetZXZt7Uqk03ybIi2Qu7n vtOPXFTwhGTymQoicq2MlfSuGceXVdDtpzbR0tnqk6W8ccMEaS+UQZkA3BST0PbPc9fpWTeWarb7 mnYg8rHEodgf7vtn35qSOOaE4SVJhsBJ2AAccjnqKp6lqzafpvmXcsEUeTGjSblAY9PnVev+yTWy 95XQqjSWpnHVpLaRlgMULbQGSRS7MxPHtg+1ZGpaozSkw71kQKXZASRnjbx6HNb+ky6VqWmvdGa3 dfmSZ47pwYj6rlcEd8t1rktctY7HWAlrObtmVG2wAqWYj16Ekc4GetaRWt2cMp+7ozrNL0Wa5t4r hiJZ1KvGzMQwbGcDPseeK1rfTH09IpbYRyeQWkMauo4b+FfUA9vepfhrrkWpeGNT04s3kWqtcRvN JgxuxAOC3JPy4x+QrIvpnkv7Ix7mafE5j2lsAgYGQOvPT605K2vQ6IuLW12Wby5L6g9w0EtqrBmi UDGOn3h+lXP7VJw0Fr57zcIc7ijdMAYJyc4xUcoilt0t7iE+f94bwSwU559x1qNdNk3rNB5scKxy yowRgMRn52HH8JHbnIqOZW16GqhLmfLrf8DpNL1KXw7OxudLkivopVufJukeCQOE2gnIDYHUDvW7 L8Wrq1094bzw7Y3v9q28ktw0M0luzB3YGI7eCnHQ/WuX0hm8Xa4bVLhtS1CQIp86ZnmZiCEBZzkj Ix14rZk8GXP2ywsZpLWxu0nex8m5dm3So5ym5ARxuAyTjn606dSMWm9CK8Jy0jr/AJl3x78BLbwt DY3s+qmeyvYUltYfORjECobYCwDkAkDcSRXlup+EYfNmmhWfyogokZQuAp4z17np3r6K+M3jCLRP hP4RsrpfJ1u+tttvuCvuSJcyjI5UYAyCMmvLPhH8NW+y2d9carp6RamYDHBDKqPGpc7t+7OOG7V3 R5W7WPKlHl2PPtYsVsfD+mKk80kcQuJEbAz806Agj2/rWp4LsoL7Q2kvJpIzYy3d6BGq728tYxgg +ob68VNNpFvY/D63uFime4XW76zPkzKhZBOGG3KkZJwQO/Y1D4D1awksruKHT7qGRYL1U+0XCnoI gzNlOGJxgnpzUqOuoKXYd4P0vSrf7DMWu/LGoubefdH5cpa2I3cdAB17g9RVjwfo1n/wg3iq8Rry FW+yaW/nyQ/N5zo6upHBB28djmtLwbf291LZbRfQSDUzBIJpEUB/sMspDDZjGU+8Bz16cVd+EC6l 410O5sfOvbeSXVdNsI41mh2lJQ771Yx7OiHBIxjI4zSuld3LScmorVn3J8P/ABF4k0Pwf4Z0KDR9 Oms9PtodPhvpryRdzBUC+ZhcKW4x26iteP4geKplu5X8OabAm2SXEl7L+9Ebtu8v5cEgqcqecYr5 IHxL1HR/itH8MpNKu8za1/ZR1CfUpPNZfMC7nSNthYKeQtUL/wCNWp2OrXejzaDHNHa3k1kJ49Yu BGrxyMpPlkkqxx0JzzkUoe/tqE4qPxH2fb+OfFimxc+HdNS72Q+XbNeyg7XDbCTt5BH8Q4z6UyT4 ieJbazsBbeH9MvLma3kK2/2qZZFWOMO4Zdmd+08Ade1fJmvfFfU9JsdF1IaFdX1xcWtjJFbjVZ9y /aIGkG3GSBlQFA/nX0Xpvw70iSaxi1PxVJp2q3dlFMqreIXAeFX2bTcb0YA4G7CsBx6U5RaeoRcZ LQ7Oz+IniKSayB0PQ3zbRztdRXczQxozOq7/AJN3VSCexxkda5347eOPFOhfDea5Tw0ZLVNXtbeR 9E825nds/d2kAbCSoz78Vlr8NfDukR2qX3jL+yRdIJA11elHJ3MMyAy7mVsZDLlcnBx1Od460HT/ AAv4C1TVtE8UwatbWsq23kx3YI3/ACksw8wg8HHAyDjPWpjJXT9PzJnFcyS8/wAjyjW/ixrdlHdR i7u7IhZrm7j2K8tuBMsSwxqxwRuLDdnAwQecV7D4d/aj1bR/AOnSnwJe3enWFqsLaguqwKH2fKXK 4OPm4wCeeK+efFGsR3/h1rZUcm60p70NK4MiqLpPlIxwcsc/gMd6tXWm+LpPDcVqviHSr+xWxigE X25f3KSxM/lrFjmRVVlJGSC3HPNdUXGon7eVmr2t87ferHymZZk8Di5UYqTjyJq3Lvre94vTT8D6 Oh/ay1i+tdKurb4d3M8epwfabdhrMGHjJKnI/gOQflbmvOPj/wDHM/GH4ZXvg298K6hoa6hIuo29 1Hew3XmNaZmaIKo6sPlyehNePL8FtQ+2LbDXtDKTOscckV8HD5RXzgdAAy8nvkdQak0f4f6n4W8Y 6VEzRatPfWN1cW9vo1wJrhwI5kCAAHbKxQlVOTyK5OWC6nz1DPswnWp0qiaUpJP4erSe0U/+HPAY dH0W8uLWWKXU4YZFiAeVYW+aXGyFFU5d8noOntW9rXg2PR76HQr+4vrHUrLVH08pNbKkjONoPynB AGeSe/FdN4f1vVPiBa6do+gaJdarcaSt7rNxfLdxRvBbRRo8zNuQFHi2glevIK7q5/VPiNP4ggtP EEzalqL3V4nmand3BlnjkIQgTSGM/MexJ+bH4VcXzb6f8P8A195+h25ZWWqt539DsY/2b9F1K4lu LXVlEqbzKrarFFNFhsZdTF8p6cAnr3qpN+z3o0k9tMdXuEjuA8ZuWvogkTom7bJ+5+XPADdCSBWj a/tC6Vo63l9a6fqmlhp3jurmExp9qlDNhUUP8x5JOPu5Oa6TRfihL4zj1HR9M8K61rn9nJ9rufs4 8yGG3ADuWjD/ADEkggfeJHArGrU9gueo0kur0/E+aWBz2q/3dWLf9f3O17nlvij4R6H4da0ibUry 7gZRO88qo0aKRyS4KhlyPlwATnpW3qHhfwfdLY/8I9cXtn5enY1FriFGjNy7bAkQDbl+V1O1iSDk 5wRWlrnxA0TXNNsEutM1NLa5t47m0kjNokFrAm6P50fd0IbJc5yeM9K7n4L2fhr4leE9estIurS9 8UX10lhodtqy28OoS4I3G124jCFgMmRWIIHTiipJpKfb9dOvbc+8wc3Qw3sasU5ySu99Vu49r+mv Y+fdE8HabfXNvCur3OnvJI0cZmtkbzgud7KA/QAEZPB6DvWf4w8K6XceB9FU6lfwyNcXE8Vm9lvm m86RUTgP8vK4Cn5sEHAr16yt4bfxDeX1vpfiTW9R0S4mS9Wy06yeSF7cET9AD5cZG0kYyegwaseK NB0S20nTjZy64Wl0V9T3Wmm6fLJMJpQGiJbjzMsTlOoPrXZCScrJnBWS5dVoea/EDwLb6HH4W0OX VZo9RSS7mKR6dvKh1gZgx3gLsA+Zs4688VnR+BbDVLrRooPE8c9vqCSSC7XTXCQxo5QyM5fOCVOB gluMda9Z8beHtLm0Oy+yabqdpDNBJeXEM2lWHnXMKrCFzHJIrBtynKD+7zwFrF8ByeGfE194I0QX Y0uFrqYWr63osMEStISd7mN2McSgHL4OOcA5qlJ8ilZpeaOeUFGbV0/n6HBeFPhrpnizXIbVfEcz 2CX9tZ3F0ulOgLSyKipGxYjzDuGARx1OK+0pP+Canhizh1Oyi8b+ITHc7UJlsYGZNr5GMYzyK+ev h/4O1m+1Jb+2aGfw5p8kEct9b6Mi2zfOxgXzYyRGXdNyk/M3Ga9D/wCFgA/D8XcfjjxN/wAJR5Pm GP7dIIVkzjy8HO445yMClKlXlJqLStr02+f9bHBWzTB4RJVrbN6tq9nsrJ3dmt7a3PZvhb+yzYfB DXXutG1zWNRkUCCT7foiTQSIOSODjnn5scV67DpMUNpdxSadaSSxlZPN/s9EOJPnA2lflIBx+FfE p+M2pKiFNY8YpJhd4GtfKeAGxlSRzkj6gGvRYbfU/EXwFvPG9zeXF2zah9jtriRpZNVib7VGqMZE YK67CVYYxyT2rm5Zt6szy/P8JmFR0aEGmlc+WviUr2/xU+IMkQWIyavcr8vIIEjcf7NZvg+M6h4g ufLLoP7JuQZGzjcApJwPpVvxtbQ2viS7+13+pNLqE++JRpbMzNwpQNu+Yk5OerA5re+HH9haTJ4k tJrxNW1C40+WKC5a1kR9IaILJMqBX2SF0ZUYHOOxzXTOWj0PUjrJHmt1cPbRySXBjnthjzbdxgHt hh2buGyOKyzHtTzrNGmiWQ7YW4mT2x3HPUV3ng/4d+K/Fc01loGr6hrd7pdk+oXGm2+gs89pZj70 kibuByPlJLfMvHIr07wTZ6D4o0ObR7iF7/VG0tLyw1Xc8KW7ROHkd4v40kiJTAOQeRSdXoldhGKk 7nnPguzhaHwfM1ojSya3OWkx8/yxRkCvO/FFpeXWkWP2S2hlit7RVBePEq4JJKkHuD09q9dt9esd S17wg+h6bLpmmTa5qJispJ3kZAsCHO9hlh6ZrxPRvFWp2JtJVVrtdySJHKuWUgj5T6g+hrjjUlH3 kjsqSg1ySNHwJf6dBZ3C3umz6jDJbtDdLGhTzwzqYxnPG0Bst719C/s02Mq/AHW2VfLvBd30kER4 P/Hvs2fQj+QrwrR9JtdaHj7ULmVonk06bUbGONzBsvBNGSigcEAPJhB2HtXo3wT+MVl8NfhRNo1/ Z3F5rUlzO6Im3ylV0AUu+T3ByoGRXrYSrTjPnk7I8jExlKKilr/wTpv2c9O1eb4teFNRmsbq50q4 u7ZkuHhyA2YxuVgMYO3aOccVxtx4B8V3fi7WNWtNA1l7C/S8trSSK0laO5lfIVYnA2s5KMAAc5Bx 0r2r4P8Ax6l0nXPC8WoaXBBoFsbUrLaNh4I1xnIztPQsceuK7TwZ8fPDNt8NfBHh83Oopqui+Izq TxJaM6Lai5uXDIwOHYo4AA6nI7V59eph5RUYy+G6fTX/AIJ61OjWj71SNlKzT3uv6Z8sab8EviDc 2pSPw14it5pSWZL2znQAY4UNtPfmuN8L/DPXrrxpFoeozro+oyPKI/7YungiLIpJG4jrkADjr1xX 6lx/Gi28W6GmseFW1YNpesQxz2uoQtp7zHyJZRFmXja21cseMjmvyz8MaZr9n8ZIJfEiS2uqSTXV zLHqLFm3GGRye+QcgkA96UYwiueGqZz1L3SLfgeS90+wFzia+jXVbaZbtVeWNFQ5Kk5wAT9AcV9O 6X4/tNT8UGDTn3Qs3mxXJLBUzH+8YANlWAbapPTA6V8maJ4s1SWOLzZQ6G38l1hHloqdQNowD1PW r02ufYnS4X5GUZUJke/r606LUVKK6u5tH3kpvpp/X3n6R+C/iFpujeF9Qhm/s6yi0mGS4dH3NIU3 YVuvOcHP0NfE/wC0h8RovjF8XrnxNZpc29h/Z9vZxxrMyoRECrEbDhuxyK8xXxHeXscscssjPcRi OSR5Sz7cg8c9v6n1rr/Cvh+78Ravp2hWZtorm7YQxNd3IggRuvmvI3yoOoJbjnFZYjEwpRu3Y7qN ByvKS2Kfg3xHc+E9H8W2a+dLDq2myWTpcyPIgVnRgJQxO5QVB2+pB7V1Ph+11e38MReMtQ8mTSpz c2sHkEIVmiESszKuDhVdcdjj1rl9QtLmwM5mi8u3EEluZpRlJFBGeDz6YapNI8Sak3hPXdKnnC6V Y2k1xa6epxGs0jxB3UZ5JVAD9BWEKyqwvF3/AOHCcVCdrWH6l4pvYZjazSFDGJIZjniaNznJHcHI P5VylvCmx4pI1nQFcKyjHsR+BrS1JTPYrfObd4DI0cSeePOAADEMn3sDdwx4PIHQ1npJFcZYHy/L XJ+bO8e2fTrWt9NAU7tM3NP1m5g029tIJVjS8CidSgLXHzAj5iM9cZAxkAA8Crvj7xIPFOlxm7n8 28gCxwrklixxljnjaAMADgfjXORybHRSXHmfIFChsen0NVpI42CtC5wh2kEEE+34c1zw+K9zrnPm hYz/ALsaKRuVOC2OT7mqQkfDOdwxztPXJrXljDNH8ysihsbsrwO361mXFkY43VZ4m39SSc/SuqLv uedUjZ3Rgsnl6hjf8+5Tt2YAXOc0VoNcQeZGhZZ3k2/dwdoB4xxwKKshM/WJ/wBn/wAAySc+BdOk JJOTeof6U1/2dfh4wA/4V5pbbRwDdp/hXTsugNMCG8MAdwWcd/rSNbaC7HL+Gen/AD0cf1rpUY9E cbqTerk/6+Zzsf7PHw5bR3h/4V1o3mfbo/lVkMm3YSf3vYcD5aswfADwLDGI4/AlqkSuXCLeIQG4 +YA9DwPyrorW30hvD86RtorW39poZPLmYW+8Rn7xznfjHFLHZ6ID08OsPQ3Mn+Nc9H4p+v6I6K0m ow1+z/mYK/BHwf5eR4KQAZI23yD+VMX4EeCLqzv2n8FRnc8OFa9ZnJLclWDALx1zXRR2OieX8i+H lHUbbqTH86u6ba6V/Y+rRwjSdjXVsZ/s9y/lcElfMbOVPXAHWnXbULruvzQsO7zs+z/I4+P9nL4f W6TJH4DaMTKY5B9vLbg2N3Vu+ByOafJ+zp4Ak0s6a/gdvsDSeabdbsBd2c54bOc12C2ejkDNvopP tfSD+tSJYaTnIttLz/s6g+a05Y9jL2k9rv8Ar5nAW/7Lnwxs9PvLC3+HgjtLxopLmFbkbZWiJMTH 5uqlmxj1NRw/ss/C1bO4QfDuFW+0QqmZmaYqQ24KQ+AvAznmvQpNK0lo2DW1hg+mpvTrLSdN+x6i kUcAV7u2aVYtRYgkK2Nz9V46L3rCtFRV0t2vzS/I3ozlKVm3on/n37nncn7JvwxlUj/hBrqIdMR3 BI/9Dr42/bm+Hmg/CvxN4T0nw1pF1pmm6hpc11dwTTNJvlFw6BsFiAQqgDFfot/Y2nYz9nj/APBq wr5N/bR8Irr3jDwbDDJb26WukXBSE3BmfDXTkvuwePc4A6UVeWEU7df0ZNPnqNxT+8+IPBXgnRtQ 1PS08RtqGlaLJOGvbm1xcTRxdciHePM7DGQcEntXrS+IPhz4R+NOsXUUF74y8M31pbRw61Npwgmi uiqedKsLt8jJyo29dvvWLofhrStc8QwafFrEUzNJmb7Pbu8qRA/OyR4y5Cg4UdSOoBzVjRY/BdxH 4qml1rxA8+nzLHoGm/8ACPMBqCszAvdMSRbsFCttUty2ATiriry99Wa9evoccoOElOnUbXVK1tOu ut9e5k/DrSvCkieMX1rUL7RmttIu10aKOB7v7fdMdiRyH/ljlcHf255450NJuNKluNHlbRtSu7uO yRMLNgR/3lfI5PA596Lv+wLbU5PsEusGz3cNN5IYqevAHr616z8OPGE974i8OWfhf4T+GfFFjp9p Kt+NaneK51WQjAluZVygCHouAMmsp07+9Ujyrq9P1sdNGUqMpOnNzb2j29P6Z5ndarFq19GLPw/r UJMIgi8ma2k3BSSAoYgtgk/nWzo+l2eqaTHZz2V8NSWC6hikuwqTxQzEtKAgkCMcFiMjP5V7r4N+ MHiPUTNZwJ4Q8DX02syabZaZbeHN1xZEKzlixiKrCpAjVuXJO5sDmtzxn8NfhdqXi7R7+bx1rni+ XW4NmsaX4S/faptwp+zFYyFEhmUdFU4jIx6xUlh1JQpXT8/+B/wT3oYLGRputjFaLvZdbrW1n123 s9dNdD5n1nw5Z/DvxBatpd7eyXV7BbyieaJEjKEkhc9d+OQOARk9RXS6X4g0mz1zSNNhnSKKOT7Y k02UEnKjGDk5JDNz6dea7fx18Gby8t9Xv9Pu4vDcHhP/AEltBu50aexjaUJa75SoM6fMz5TIj2lW zXLx/DO7+Iml32ippcPju+TcmoeLdHiX7NbszkJKkw2rtfDbThVGefSufkjGUadWfzt2XXovW+qs 1dMpUqsoynShbyutr+bv2vpp1PL9YudS1bxUsupBZbW0WdLLofLj2N91exbPJPJrl4NPfyrQJbeX HdfLEysqmQ9wO+a99f4Uar4fuLjSY7bw9Y+Cgtrsvta1RbfU4bVo8zPIMDI3nDMFJQAYByTXM6B4 D8AeNdcuLbQ/F2i6FqEMixaFp+vTXGbpyQFZZVQqELDHzYJJXrzW0pQjtLbfy+6/+d+hxLC1p3tC /wCP5pdNe1tb7manhrU5PhHb79IhuIhqUuy1vQHD5RfmZePYhs44xUvhy1v7jS1a50Wzjla0vImb 7IFG4LDtRjnvk5z12jnivRda0lvA/h5dB8QSQ2t1b3RivZC7XMMd0Ylf5CvJTJXG3pUGlXtlb6DD LBr11LY+aySMumtJDJckpsfazDLJgD8a35pKcY+Xdf8ADv7jBUqfJOTeqbS0fbva34nL+BvCfiSz j0FdR0S0srT+1WK7LVUGxtPmMbA57nIHP3SRwKqfD3S9T0f4U+JbspZafNb6lpElisdqsYR2y0jG PJ5wflY9Ovevf9L+K2n+GdYu7S50pr/VtLv4ILxbyzhPkXLByGi+bCOx3HcM7Rx0NcXpPxi8D6bf apq1/pUviQ317BezQ6pDAIp2UMANsY3MQWznI29vSsMI6tSjzYlqMn0TTX33HilSo1UsOuaK73X6 HCeGfGniS98X6LdXU8e46g089wtsjTFwy4kD4yHZv4vasTS/ilqN5rD3uoLYTJNcNNcWzQxxtNgl 2JYD65btuNd5rXxC+HXiu9tfL8CweEfs16L2OXTNRmt4+DwjQBX80AgZPBGa85a28LaLr3k6f8Pr +d7WL7PBd/24WimGCVwoj+YsWK5PfrXTTlGCanLUwkuflcLf16lpvjLrOreGJb2DUDObfUorcLHA sq2tusLsqgjOFUYAbtgV1Gk+NB4q17Vr5dQg1Cwku1tba4miRZjaogJ5I3/3VGemDitfw7B4h0GD V1tPhTqdk+qWLeezGXaW2BRbqEjXYx6+YBtG31rG1qSRby5ufEPge8aedmmlkvdSvFDN3YkAD/Cu iMqkqkk4JRXr/wDI2+5+pjKMY003PV+n+Z7/AOBfhrqXxl+KXiTTtHvYYm0y3ktbODULEuFUACJ4 5mTBRe6lgfmyM81o+IfhTc6Hrd94Hv2+2Wkto2230ySG6uBOdiO8kJZUEhIyEI5XaSc1w2lftQan 8PLKObTPD1smpRzx7Lf7VKsywsUEi7sfM7KAOeik4xk1pXfxyg0P4u2OuavoMllqkumRGy16zmCX od2IWB1f5WVfuiZuW9TXC5VFNU7au9t+n9dWO2spqXuq34/edx8dv2a7b4e/C3UNVk8QaW9/ZaXD bXfzBJVLSxfKsQBYEkbjk4A9eteEa1qGhfaLe4j8L+D4p5/Kj8mPUlfhlSIF1xtUblLseMbiTX0F q3xMN54Ji1jxXrGr+H7e5kuILT+0tNtpJL+RZAZSCseZEUsAWz145ry7xd428OaVpemix13Tb67+ 3W8b21tpIguJbeRgXuSWUj92pB2bQTXPTqSjzRmm7dlJ/ilb8zwMyyWeYV4141YxuktVHo3rrtv5 eZxNpcaJeXEyHwv4Nl+zySW7SPq3lGV2hOHByAyrkEEDAZa6PwiTpfxM8EDSPDWjy6pDLdTJF4a1 dWe/kKOYojLkiFhgKG991O0v4oaVq1jpC7Pt1+shU2cVmnA8xgiSK0QLsVKnjAHSqurJrXxG1PWr DwxZQ6a1naSmRrrUljVCX+UbFTbIcqVKMcKD6Vu25+6k7v1X5nmU+GKkKkarrRtFp/CujTtp3ta/ 6XPJ/CHw5+I03iy90vw9pdu+uXUUo1Cw0zRmhmkhZgJSX6Sx8srMMqSp5Ndv428Dv4Z0t/BHwztr HxE3iC+tYoreaGMFp98ioqIuI3+WIHLjIzx2rtdS+L1v8O/+EJOqeObXRfFFvp7aabjw7qL3k62a Q+YqHEP7mPzX8sRjuGYEAZrmdd1bw54t8Fy3nhjXJdXurO0hn1bVrvzQ0N/JKdhhCCNmTgxkYwCw yw6nkrV3VaqU3otlZ69rt+mnqfqOEwbw/LPEwvBuzaav1TSW+q72PmnxLq+o6devpWp+H9Fk1axa S1ubY6ckjxMkhVhgHAwc5PfOa6Dwr8SviX4OmlvdB0htFmu7R7czWWnohlhcD5WAbnOBgkbhjgiv ojUPBkGieJvDsV/revRaPBbWUl1N4fWC9triFkDzOS8e5WLOU8s7sAA5Pel4I8A+FP8AhKZbG7ku dGu9TsZ7rw5q1vcRtKhkLfZ5JEcFUOwMp/iDjGM8V3z9hXw6WK1jJJtNXTXo7pnnxo1K2JlDCRt7 zitdfL8P6ueG+GrvbFo9v4i8HxSabLE/7m00th5Mu7EQkJPy45Jznrmuwhmks7+0ubXTU0rTLiHc l7bWh82JPMHIZOVGVY+/B7V9MfCzxP42j1iTVIPDV34sjvPKh1ez8T2tvp0MabCsawArtZg0Z81z xmRcDk12Fn9n+Mt9BoWhabZ/DnWvDFyJLi2g0eC+SaNJiRFK4YbP3gKtHtBIXrg4ojWp1YtKdmv1 TWnbXq1ZnNmWBx2Ax1LDKnzU5bz/AJUrNtrd6X0TTXS+z+BdJ17UtOk1m0t9GW1tbqC4MkkcNxCZ 0YYILbsneMbuea6//hZ2rWfguzhTSrdLVLZrS0jigCouwgbQ3JAIJ6cqQOp6e+fFL4Ito/h+4utE 1u28dapHeXl5e3lpeR2siRfeMTW8TspCMWIZSNiqQelbHhjUvBnib4H6Vd+E7VGm8J6jJD4iutQ0 pZHeNlDSyyiSQBkwSVdSCzoBxzneUaDUXK3NF3V1d3s9uz1tfs35nm1/r9PEQo4eHNTq6OV7JR5k m2tXJKzdtNursn8m+I7q01bwbYlNJtpr63t55mh1mKTyI4lnjBjikL7pGZX3bOpK8Z5q/wCGtWsP CPiRNW0myx/advKxu72CRrie1PLybN5EZAUfKCcAYFek618WdIt9Nii0/VLNRbQlGutQ0eWK4unU n94FjYpHvGPkzwQcnpXZeGvEfgL/AIRvxNca/aQv4nvrBRpc9tdzyW8LAklR8m5VbI9ehGcV0crq U5Rdm+l9jhzHE1MtcKsIOWqT5d/l/X3K54rdab418VfDzy7+W60rwa/l3cNrpMT29rdhWDbmjDDf gElSQeTxX0dffBn9lnWtDS7tNV0vTA91cW26O7KyO0xaFGdS5+WFmEiYwPkGRjNcz4U/afk0X4TW vhOw8J+Mdf1Da0cJt42IUmQN5Y4ysaBQAOcLj1rV8N/EzxPq2pXFvceHvFmjWsdvvjur6CTY0hO0 IiohOVXnJ4A4xX5ZxfhcyzarQlgVXhyc13CXLe9laSktdFo+mttdvuMpweEp0X9YxEE3bon+Tf8A W/Q85+DPw9+FnhS++K2n6nrtpr13pOs2lvoOqS6v5Nzc242mWSLy5FDrjcGKggAHmvX/AAb4/wDD +m/FHxr8O/C032vR7LWEudMNgHv7e2glt4pJpDNkhMzZVRuOSXHGK5GT4qaPaX3iEX1q8Vr4dt83 Fw1upIGMsojeLcMkjPGDmup0HxTon9u6tdaTP4d0bW7WztLiWzvykb6hHt82FYVQgT8FsooyCWBr nyLD5rDNZ4nH+0UJQtaU04c1oK/KtE3yN7KzlLvrpjqWCoUUsPWjN36Jp/j/AF+J5X8aviVc6h40 1PwbN4bbV9GNpB5+pTSPbm3kkh4MZAwkgXvnkGvN/AEWl+Hbe6t20S/063isLq4F15jyqiAKr7JS gU/LgjIyDXafFL42aL8QNNttO1HVLzQorGN08zRINpuG3lldt8J+6CVXZjC4HNYvxKstP0r4neMr fSdZjsPDx8PrcRaSbV0eFpLa3LTuwGxmYncwH944Ffqqr0fZ21vtt/wD5NqXPzXVr91+n/Dnlfhj xOPBdxeXWl6R4gsGnicNPHrLbnibJ+cqgLBwdzKxx0znFdR8F7pf7a8XahZQ3EQj0K9aR725WY7x GNuAFHAyPbsBXnOrXUEN9N/Y7Q+Ujb1kQFd+R8zAEnAPPFdV8EtUjjk+IEEMIhu28NXEsY5+Yenu OnNRHk5k4rfyRpHTS+xmeAd8dr8NVadZP+Jpq0nU/Ptt0OfoP615XY6XKtrb3Ktbo6xB2YFsjPbH cn+tepfDfeNM+F80kQRhc+IJOBjGLde34V5pot4r28GGODGMsR/Fj1rCWhnKfX+uhG+LjTWtnld4 FzNGehzjlh7/AOFQ6aIo1KyN++Ubw7RFQ3bPvmr9vJb294ZXtYSmSv2eblJB3P8As5rT8UXljq12 k9ho9voNrHEqiztp5JIlYA5cFyWyTzjOB29KyTe1i/db3Oy0eZfDmsWVrdXC2kEmnRXand+6IkTI LehA/AVD4WvI7zxJbXFnKZliVjDK0h25QOwOz+6SMgd+T3rnvHV8Zr7RI0fYJNA08Njkv+6Ix9MZ rqvB8tjNa6PA8iwyhZDujzvkjZWDKuBhSBkgnjisK9PlqSklq/u2f9f8E9nB4hOMaU9lf8baeh7r cfHaLX/hj4ri1PXLrWNR1ktqItYbWRERFgeOWKIr8y7TIGAJyAcZNfOXhe1ht/FmmaclpbyDS7W5 XzoYXhZm+yvv8xW6tngnAzgV7FpvxK8OTxzadoWi2lvYCyZ3uIGNrfXBEZVgWYbMhTy2ecnjmvLP DUka+KJIoN81mNNu5IxcEGZP9GkOMg/ewVya9CNCFCmqVNWjGyVtvQ8tz9pNS7/5nF6MYrSxKxxJ HG6BS6v1OOh+h7VVuZtr7WVFI59QeK6/R/Cdo3gj+15Nes4NTW/W0/sOZtk0kBjL/ag33fLVhsbv uIrF0/SnSQS/uriKXHmoJUc8kj7vbkCuaE0uaSO2MXJxg3YpWSStCreQoSRgI5CApP8Auj1+tdTp 6gQ2Mmoxapf21xNtdLVUby0UAMwTGWJzwvHQ1AbGyWEy2tuouAAuTknYCflPpg9DUzTW66VC7NeW u/PyxHCo4J27W7985rhrc9ZJQ0O6VGNFu76HT6t8StBvvA9poln4Os7PWbXU5ZrnxRPM8l5fwkOq QyoflUKGBwOMoowDknndBitZvDfih4j86WKovnAKyZkXjPTJHeuSA23D25vvKtn8xizIWEjDnBA5 yT36Zre0cyx+CPGIWRd4WBUbcCMlwG+YdOP8K6qeGjRh7nl+Z5sZrm5ZLuJPHFHJBLFEJxLbo5yR lTjnn6D+dUokYMj26iOLbvTcQW5OcGlV5ZNOs55JY5po4nVFXHCq5xwAPX9MV0/w10HwJ408P+Nd T8WeNn8I6tptks2gafFYtcLrFzhv3RZRiMAqg7HEhbOFNbN6O45SirGB5Nwq+eltM1pgZkjQtGN3 A3ehyDVW6ldS4O4PG+Cp/hx2Pv8A41bXxhqmmWstlZancWUcysGt0XCMSfmQnHORXOXOqSSWwhku E8sMX+ZcHJPb9OKfJ1K9pZWNBpEkkWQNg9dp5Un39+lJJZyN/rLcsW+UbQWCnr+f1qjp18PNjhXY jqCQCdzYxnOPXP8AOta1vnbcweRi3Le656YrLmfNY15YtXOY1K1uLq/t1EbJGzYQK57Hue1FdDqd 5LeahF9sWUogEYkeF84zkYwOfrRXbFNpHl1JR5tj9Vl+JnhCZmI8SxnB/i0RP6rUr/Ebwo+N3ii0 JIwM6NGT9OlfJj+M/BkkpbyPFSjOcCdP/i6pav4+8MQPCLK315VMcuTcyJu8zadhGH+6D1Fd/Icv tIdz6wtfjB4dOoHS/t9uNN3reDWX01UjL7CPLEG3kj++ea1/+Fm+DFyx8Waavru0Qf8AxNfEsnj6 z+w2l/B/a39oq6me0aRRaXKEfOB8xaNh1VhnuCMV00fxC8D3SFkPjBSDhkEkXyn0+/WcaSi3Zbs1 lWjJRTlsj6zHxO8FCPH/AAlekHA+7/YgH/stVIfi54V+3/2PHqFjc2148c7aguniKCJkJ+RoyP3j Y5zkYz3r5bXx74MXknxg5x/FJF/8XVHWviZ4djtWXTx4iVmGc3jRk7h2GH4X1pzoqas/ImnWjCV0 +/5H2I/xI8CttB8UaCRn+LSSP6U5fiH4GZgB4n8PM3/YLYf0r4m/4WdaeTY3qHV5riPYt3ZMVS2u EJw207iY3HUMAQeQRjmupf4leArtc2x8Woo4OVhyp9MeZT9myfaQ2ufWS+OfBc3KeIPDr5/6hzVR g+InheHUJdFMmk/YbmSO8/tVbbZaLIoIEbR/eZ8dGzgZr5T/AOE48HM243vjMf7qQf8AxdUbv4i+ HrbWIWgm8RS2LWsqSLdpEG87chjYAPjAG4H61nKlzWi0awrRhdqR9n6b4g8H+IBO+m6v4Z1BYX8u QxWr5RvQgkV4Z8cvEvinS/jl8OrPwZpeheIrZLT7XJptwwgtLyRbmUiKQtn5QBk5zyO1Uvh9+0L4 G8EC5S2HiWUvJtkuE0+1JnUE7SwMpAPPQHFee/tDfGjw7481rS73RLbVLa9g097a4vL2OKJpAZWd VCRsQuNx+YHJzyK48VTqezXJG7/4DOjD1KXO1Odlb9UdVH4r8Y6f4N8Wf8I34E0k3urWw/tzUrmJ Le40ycyAstjsJ8xCfMGMDjYc8EV4bqHia9toNWh8+Y3WpZa7bcQseTyg/vN6t74Hc1UsPiZqOl3D iG5mkgktzDIshz19P8c5rLi1uzuJkN68xTcC+xRkj061OHp1OZuqvz/zHVqUkv3cv62JfB/hC78Z a3b2NrC3lM4ViB0Gep9K+gdO8VaF4J/svRbC9hi8K6lNEl7ZsIzqcpt2ZbtkAYLDG5KCMXHJCll6 nPhd98RE05pY/DkDWaSk+ZPMcSNk5I46CsPQ/EkWm+PrfxZqOj2erXTTO11pkjMLCVCm1QIsHDL9 7cSfm7VNenPEv95F8q6f1/XTzPUy7FYfB3cZLnbWr6d319Led7nqlx4q8SDU7Ox8PypFfz6tc3Nj rov5BerLMojZZbh5THt2nBz/AHjliK7j4cXGg+C/DOpnxp8OIdeSxulOuatcahaqLK5RytqYZVky 6ODgBAMNkktn5fGdB8ZaHB40bW7jSv7NjAeRPstnHdKsgjKoDBIyxurFstu6YG0VsfEL4keHvE+g vpNsdUa3JjSH7Rp9nDMhSDaj+dFg7UkziHbghyS24c51aUqb9lRi7O2ur6976en/AAx6WHx1GvTl XxVRc95NJO1r2ei7t6XvorncfG7xVpHjbT9G0nwx4JuPh7ovh3Tp7p7eUBGuZHk3rllYl4lLFgG6 lj6VqaLr03w5ks/D0L22i6B4iu2s9T1u/u4JLSOzjAdXaMoA0iONysSF+bbjOTXhcXjCD7Lrpure Ke+1CxkjWS3t1tYY28tVjjESkqArKXLjkkkY5zTNc+K3iy38Q6Rc6HfxtZWkMbNa6jEJIJ5cAkSw nKSIG5Ct9aiFGrGKtF3Xf8/l0OSOPw8aj9pPmi1bzXZK90tdXv5Pv758ffFnhj4hatY2dtZ6Pe+H tAZZtV8Sab5XmaveTgqUj2AjesYIZScAKxAxgV41qy3Gl263tnHBKttdm3uL60hdgkpG+JXb7qkq pKgYJ2k84q34g+K134u0eOPWlt7O/gjUx2uj2MVtaM+G3Ssi4+dsgZweB6cVnaL8T7nTfgL4m8A/ ZbNJdY1u2uzeeTumWAFWmG/Iy4McflsRlQZBkbq8/HLH4eFP6nDm96KktPhcleV7fZWtuq69/Krz weLmqmJ96Sulq1a++2/l2NS61XUfFPwVg1BopLzUZtRnkkESFnIjVQzkDk4UZJ9Bms3Tb4af4dsb BJkvQRdXxmQlQ3lSxEqB7j+Kur+HHxI0X4c3Ghrpi6g0Wmavc3EU00UbuY5IivI3BS3zHjpiqPjr xP4R1zTdP1C1jvrPXLe1nsjCLWJbedJWBZmKvkONo+bHI4x3r1adKrOUarhZcsbd768ya8vdtre9 9FbWZ4iEXKlz3V36PbYTQNcXxLrHi3XoLJ7W31bWrG4W3clwgYTDG4gbunX3ryaHxRNafJHA08aq u1VG0LxyPSvSdJ+KV3qGgWGna5JJdf2QlnY2DQxIAlpC8xWJsY5US4DHJY5ya5Xw9pNk11bx6lNd 2OnIMvJaQJJO3HACswA+pP4VjGjWlCKlDXX89AxNek6n7qenc674W6Dpnje31p9TsbmQ2ixlFE7I Ru3ZLAHkcV7/APD74S+FlvrLV1tLmGfTnV4YWmYx+ZjIkI747Dp3rgtA+I3gHw3oZ0yw0rVlhG5y 0kcbSSuRjc7+Zk/ToOwrWj/aN8N6HaFbW01RZGAOwxxncQuOvmcV61PDxhBKUbtHF7Zc1+bQ9t8S eILHSLOaS5vY0Cje/mOBgepyeK+ZfiH8YD4tnfT9HDSWYYA3UwOzAOQI0PUZAJLdSBxxXJ+NviZr HjS6SbVoIzYSNutraORivHd8EZbpyat+Hb/wlpevWqeI7rUbDT5FLzyaXaRzXEOVOBHvlCsQ2OW+ uO1b8zTuyXOElZPQsv4L1TSrTRtW16x1e10nWXb7HqsSBkl2H946ggtKBxnbzzXsXhz4YQaPHY+L fFPh3Sl1G+0yJvDnhrxBYs9z4hvEGUXhgGQZjzyFYSDaODWH4Z+L/gH7DcWfjDxF4617TIbOe20m w8q2KwmUMFlQmQeVKPlfcoOCWBDDrzNn8dX0ORjfQ6n45KMo06+8QSL9p0pExhbd0yMsRk4CgYAA rzsTPFSfsqa36/1+JvR+q255yaa6f1/XofT+ofDLWP2hPDOheJtT0jUtH8bWtk/2rwfcXqx2VrDC wXy4GZP3KHAOwZ69T1ryDxX4EHh+VPjPD8KtNudE/tL7JbeD4bp54r6UxsGkA2iRdjqZGLEqx4qv Y/HrwVDN4H1f+z/Fln4l024l/tFvtRkt54yzOhUeauW+YAhxj5R1xW9J+1F4JhbT9auLLxLLr2nw yWtlM7RiFIpT+83L5p3OcKobHAz61wRp4nC0ml77fa+l3t/wTrVXD1ppt8qWmvXzPLINP1Lwxd3W qarb3Fj4w1LdcmzmjKvpySgsXcHpK4b5R/Cpz1Irvf2ZZWPiTxBGYvMc2MKKH6DM0navNPF3x0i8 TXTPc2dxqsYJSNr4Zmjj7Ksobdgdgcgdqm+E/wAaNK8G69cNJaXz2V5AyToqRvIjIS0exty8Zdgw I7DFejhoVeZTqxs/+A/6/VkVq9HlcIS0/wCCrnNsCnjKb+x44JL2eVLZWtQoMjFQhQMRwM5HUd81 uXXhjXPBFrqMOt6FHpUWoWUiqzSxlJjFJFMVzExG7lW5ySCMZyK1tJ8S/DbQ/iNo3imxg8SpBa3A e70q4ignhuIzGY3UMZAwyrHg5FdJ8f8A43fDvxh8NbDw14D8Kap4eEWpreTL9lt44hFHEIYolMbl iFjSNfmBzg81rKE4uFNRvok36GMcRT5nNy6tmR4s8d+FV+Ikt6PCPhbXPEcl3pi2WqeGtUiggaWV FVw0bAMroMrlcKG5YjNO0/WNB0XwbZ6z4gi1ufT/AAhrl5osklgrTXsTSOLlJlkjcYMMiyrkMQPP VvmOK8W0Hxdb6foreD7rT4/+ESmu47qe8jsoX1S3AYtKIpJARhtxO1uCQo4Fdld/FC18N6LDpPhJ 9ck0m6eb7Q98lvazSQbh5UbCHKyL8ucEDBJGWFczo1mlG2q/r+l8z6Z47L5tOU2n8V132s7212ba 0tolfU7DxX8XPhv8QNJ+xeB5fFeqapJepI2m65LLEjxPlZmlYttfBKOF+9uUt610vwx8ea03j6TV LTxtD4dXxNayaN4guPsW8TSpD+5ljLIQspUKcjJyGYnLV45oXxGn+HSD/hGJLjTV1bSzBqlrJEqx h33KWj2vh8IdoZgOP4RWfaeLNM0ubTLpTNcz6cv2iO3vYFe3luS25kcqwbyiAAQd3Rh0NZPDVJSm 2vR9/wCnY0jmGEaoQnPms9b9nZ/8Otr9N7+maP8AH7w/pd7pF0ms6hq2rW0sGnW2htpn2G1unjJx PczQoGZWZyM8l/4gFJNO+FsfiS28Yy6VoPiC20GHxIklpqOm6hcfZbKeRFkdbSRiu1TubCYJwkgB zXNeH/ih4Z0/WtVv7/w5Y2kdxdw31nb6bZR3QtRnc0Sq7qFjyFAAxxuz1wOS17x1FqtrbeVG8V3H JJdxsMBIp2fchxkhgoC4DDjp0rSdBylJRhuuu33fn1/AyeY0Z+znUmk09LLp33tvra68z1nR/Aul a9p97d3cfgvRZba3UW9tFrwvG1GZQ4m8kbFGAU4GfbPevJdT1Lyb44tozEzM0UsTugZAcFAM8bTw e4/KvVda+OPhrxC1/Fe3t8lveNDFJND4YslY2ropvEdBNuZzJGhRw46scD7tc34L+J3hexj1bwvr Gn3mq+DtSEksSFEFzZ3aK32e6iYOCrE4WRd2GVj1KiqwlKVCcqnK1dLS7drb2b/rQ584xUMVQhCU 4ycW9Ukm77X0WyX4mB4Q+KGreC9WNxZBmsJH3Taf5zYbtuRzyjgdG/A5FfTXhX4jW3jDTrOeO8aW O6YxwzTDa7SAZMMi5+WUenRhyK+TZW02/XzvsF5YSMv3EuElVW9MkKSPfrVvwv4s1bwNdXE+lSLK lwmy4tbpAYpAOVY8/eXsw5GTXtXW6R8hzJaXPp3x54STxdJNot0rW39pabPE91FEDL8pUrn+8FI6 ema+YrP4Y698M/ix4cs9UtA9m1w8lveRgmKVRG5JjJ6Ed1PINekeH/2oLt9Qt77WNPa+uLGCaOBY 1C+Z5gUHcxbtjg4rf1D9qbRdahhhuPCM02nMwdpZJULRyDOdinPVcruBB+Y/SuGrT9o22tTb91Ll fNt/mfI2s6lZ317e3GmTXU9jNhoknQrMAVHBXpkH0r1f4vS7viX47iaRkZfDMETAcFP9HtBz/nvX Tf8ACafDfQ9QutZ8I6PrnhTxB9mmtY53ig1C3EUqFJAIpGGCUYhTk7Tz7Vj+I/EXhHUvFninVJLW +vo9e0VNJMNzCqyWZEMS+bHJ5jBmBiBGV6GuL2VXnkpR030Zoo0I0041Peb27f1c+d9S8PzTTb49 QCNjaVVhg4/z+Nen/APRr281Dx2t/eRwpP4fa2S5zxbqzqhb6BefwrmT4PsY/l8+5mUd5IQOfqDX U/D27s/CaeJA6SONQ0/7LF5ZyQfMDfNkjAwOozW6jUlpa3nbYwp1IxknKzROmgw+FL3wBptubjy7 QeJSGvMeaf8ARFbc23jnqPbGcHNYf7KHwW0T48Xmu6drfi0+ERpNgl1AyiJvtZZypGJGA+X5Tx61 3+kzeDYfAllBd2+qzeI9PbU7i01OAosX+mq6S2kiFjuUBg4lGGDLjbg1534J8C6J4dsLu+cXcupy RC1ihZVeFFY5eRiTktwu0AAetcVHnnT5JJ3jZXa3dk7rfR+fW51OpSnVc1ZR1dr7Lt8jzMefNq93 bKPMhs2dZfKBI3hyq8/wgkZJPQZpiahbvMYo5mnPzIsyqSr9efr7fSvQdI8LxaBa6/F/pDS6pp9x atJINwV5GRvM4xnAUjHoxrntD8H6h4Z1GG+sNVVbi2KywM8QIEgP8QOeMZ6c10ezm5OPLY5VKMdU zpYfDMev3Xh1pZb2MDRbNGa10ya8KAIxGVjHfpjNbNloeo+HPFtzpUkbT2+j3Riubi2jZrdcqSjF sfITkYVsHPHWtrQ/jV4q8E+H9F0fQ0sUt7C2Cs0/mEvK2fMHB+4eg7461xS6hqeo+MZtYvboJ9ru Wubi2tSUhZipGfL6cHpnpiuifNytKGrv+RvGdNSi+baxo/Dnx1qUza7YQpbzre6ZNbyiSzR2lUlP uFh8pz/EMGm+GdHsYdc1Fba4KKNGvd0bvkJmFhuJHT/AcVgeDdF/4R24llX5i9uIwyuSVbzI2OPb Cn8wPetXRsW7a28g/wBKksby3tXToBLGV2v6AHDd8ZIrhjSq899bGsK9NU0pO5zd1LFDYB0naUqA F2nk9iVH8I/WptF0q1vI31P7ZJHcW5QGNSdmDkZb1/xqOy8P3ESgSSRMe+0H8s1oQ6cY1EUqx+Tj ayr6Zzg8c81qozpJ2jcar05O7drCyLDexXCyrMYIY/MEoYq7beAT7ZPQ+uKzp4b+1sVlttQa5jQi R1ki2lGz0HqAfTrVjWvD8moIY47k28TnLAAEtjoD9O3pWvCv/EgltpVWV3Ma4YZUqoIwT1681nGl OKTin5nTUxkKmjfzOH1S71uxvJlv7YzWyqGhEcYjWQnkE8ZPfIHet3wvMtx8N/FLtbMPPmtFMTZ/ v9eewrqteuE1BtPZfMYJa+RMsjfKwLFiAOeMnOeDUQ8lvDutWyoUnu2gZGA4GxgSCc56CtZRnJaR 7fmjGFSnB/H3/I4+9mea1iSCWSJmikVpFHKgvyB+QrovAirf2E6XOy4mkuGZk2gH7gGdo9SKZdWj PZ6fBiNvIiYPnjflmIGfQZFU7bQUMZMl3LDPnAaDso6HPHOamNOcd4hKtTvdSOr1jwvdXlssUMlv FBGxKebw3QdSB2rkdX0O9t44w0ceXuEWKMR7S0pPykMeoPXtXQ6b4i1ezikFybW7KnEZ5V2HOc4H Hbsc81Hr2qXmp3NqkK28NtHNHPFLJuZ8qpxnnH3zg+3PtWqpzfQj6xTtuc//AMIzqceoW1vLptx9 pkjYqu8BuMbm3D+Gui0P4eeKb61l1GHw9LPp9kDLd3CRnZEAdockfw5Iy1FjrepnVIrq/it4zDGy f6NIzE5xnOR04rpLjxisMx+zT3dsJIRHKscjASKQMqw3YKk9jxS9g5X5kX9bjFaSLOlX2r27J/xM VCcDy9gzGc+4orDbXI2bflgFIz09frRV/V32Mni49zWt5luA37pFdThlZ8EGqurAqsbbVXac/K2e +P60+eHy3R0ljDL0fbnaPQ+q/wAqhurj7VbyhvLSRYzlQPcHg9/rXqHhlmzUNZxjYrDcRgtx0pk1 u8LiVAqvnGS+QR6N/Q1Lp/8Ax4wnMYyxPI46fzqz17w/98mkin0IreZbhWxCFZThkaTBU1X1BTsU bQuTxhs0TW5jZJI3jDKeGwTgeh9V/lUctwLhQCqRyKTlAOnHX39jTES6bGfIYGPcOnL0TQyW0nnR LtPAOX4Yejf0Pan2K4Rh+67dfpVoj2h/KkA2CcXCkrG4Knays/Kn0NQX+fLQlSp3EYLZ7Uye3eGQ TRGMMDj1GPQ+o/lTJrxZoFJRUdXw0Y7cY/H60Ai3pisIPuOfm/vYrP15lF1Hvyv7vncc/wARrQsf lhI2x9e7Vg+KT/p0PCj91/D0+8aTGnYqyNCehAqH90cDqfp0qvzUtttaQhsk44CjJNLlDmFkhQYK gn1pvlkn7pFWpN0LDzYWViMjdwcetXFsZ/L8xoZ41xnOzjH1NPlkHMjOAP8ADIQRRHCz4bdlc+tW 5bbyeZI507ZaLA/OmCSNf45B+C1NmO4q6dLICyI0oP8Adp39j3TsMQsowB8/FRifB4uGx2C8H9Kc 1vLwxeYA/wB7qfpmnyvqLmXQkOg3UmS2xfQl80v9k+UrLLcIoPJK81VkgO7EkkgHo3FL5cMUfDyc nPODSAueTHHZou9mhE2N68HGByKe0tjHhpFeZxxlgTSSeRFYxRtLwzFsH7wqNV0+TOS5z/t8H9OK oNizHdLcMRDDtAAXacDOTnt9Kj/tC6mcLGkaMxwB1OfxqQ2KwKyrbSSI+D8smenTmpLeH7NJ5gtZ N+OFzuP59qeoepC1rfthpH4yMhW/wpP7JKyZdmfc2P3YyeaurZ3GtRyKw+yQxYdsg5JGf0qG10O0 1C42w3xLYzgRkDjvk0XEMuLGys7gLGs1xJtOWVsKD0wf8KvDTP7SMLiEQIqANuO3OO9TXVnBJdSx fa8zl920rwvGSePrVyS3nulMN5tMKqNjR8Fj/Tj+dYSkl6mlmU/tVvtZHhitZF/d7OvHrmlha+n2 W+61ZFbIT5s/nioNXlaO6RpbaOI46sAdwz1NXHs7jUGjbDWW5cKI5MDHrgVSslcnVjdRuh57Rvci SRANwC42n0pl5DYzQql7cbXAGzuuR1OPxqG+0t1aNGkWZlXDyZwW9zTBYQXEhecrHIw45OcVD0Vy lqZU2mJ/aLQx3QeNWUGYMcc1fW1Sx1TyklEoVWO8d+BTG0TT4rgR/aCq+p71BeRRabcD7JLuAHXr 17VpGV2hWSNpWPTOKVWb+9isL+1rhcEqpB6cdaeuuyrx5MR+ua1J0J9aV22vhWyPbsf8DUVtet9n Ubfs8kalFKxFxJzznFRT6o94oRoExnPy5z0p0NwfsU0EjLDEFAUs5U4zk9OvOOPepNIvsSXCwyrH IshblVjjkQqcd+ewzUdpu+2fM62+4lWkbnr2/GqqyqtvHJI8ISZSAgY7uvp25p7W0dwvCySRjqQD jI9fem0EZ6pmxPGY7Zkee1i3RZKxqfnwePpWTc5WYkou7gj5h6VVuLqOGNYQNv2cllDLklj1HToB 601o5Y4bNIVRPODOWkIJ6459ABU3VxybZNO/mNPOl1+5YrkqMc+gHbnNXdHmtGaQK3708dMYXvWX a6lLayO8U6EEEf6nhvwq5a3V9e3EcTTKUkPzFVAxgcGrbe1jPSTumdG2BjAXHbB7VR1KWVbdhGm4 NwxzyPoKpRrqcPmoGjVozgR7c7v8KWXUr20k8uZUD4yQR/hSsBUjvJY2ZfLyhGCuP84rSspPMsMs CpJOFYc/lVX+2GfO+CN6VdSi3BhCyMOhR8UuWwrkflwPGQvy8duKfeW+64dt5yQvy59hTGksWbJS Zf8AZVxipPOsriQlpZI2bqWAI/8ArUcrC5VkvGtfkFww45GcimyahNLbyENvKc4YdvUGrU1nAzcg ycfxgYI9iDTJrNI7WYRdWXG3PH4UJMbKX9vmSEpLCM/MQy8YJGOlEepIbcx/aHQ5XGR6Zz/Ss2S3 ki+/Gy++KjquVEXNqO/myds5Zc5A3E/1qDbufLHIz+NZdPWaSP7rkfrS5X3GaSw+Yp3BThTg++aY sYBJC4btg1WW+lHXa31FPF6rEGSIn/cbFTZhoW4Y0VSSrZzjAPP1psMb7pSSxPlMOVp0F5ZMCDJJ DwPvjOT+FW4ja7sJcK4YEFi3TijUeljM8raORz/umopH2/8ALNsewrYRYJMncUXJA3EcipYYYGk5 LGNRlj5gAPPb0o+QGNbGOR8SFoxjhthP8qsyRqtviF/NAPPy4+vWtdobRcBYi3OP+PgUrJaY2+Wu Dn/lvR1K6WMCbcQnBwF9KasjRxOuOGxk+lbscNqwJaONTnAH2nt/WhobSRtrRwlOob7Sev5UWJ1M PeeAV5ApNy8dB+FbkyWjYYR2xYdmnal22QBJW0OPV2NKwamIs23nA46Gk+XDDA2NyB6GtpUsCBuF kG/2S5FN22Afn7Fsxwdr9aLeYamNJhlGRlgMH39DS3UYEzZU4AH8hWvItiFyv2M885jc/wBadI9m shDtbdP4oWJz780/mBhKE8t+DnIorY+0WW3rb7s8j7N97n68UUX8ybFz7PJ3Df8AfNI1m57N+K1p fZx/db/v5R9nH91v+/lWBmR29wSC3CkleB83HtT2t5R3f/vmtBbf5FGG++x+/wC3rS/Z/Z/++xST KZlGG57D8waVbS4b5iq7chTwc/h7VqfZ/Zv++xSrDiFh8wJcH7wJ6UNsEZiwTkHqDn+6aPJuf8hq 0xb4zw//AH2KXyP+un/fQpiOz+AvwdHxq8fL4bufEdv4Xja1kuP7QvIt8YKY+UguvJz69q+nNR/4 JgrpHlfb/i1pFl5q/uzcab5e8D0zOMjkfnXxh5J/6af99CvuH/gpipZfhWBu/wCPG6+71/5YVhNy 5kk9y42sct4i/wCCbvizS/D1xqfhDxho/jXywWa1gjMEj4BysZ3urN04LL1/P428RaVLHrQiuVli uIV8uS3MJDqysQQwPQg8YPpX13/wTmsvFH/C+o59KF0PDy2c41l8HyCnlt5SsRxv83YQDzgPjvXm f7V2saXqH7RXju40UpLYyag372Ija8gULKQR1zIHOe+c0RlLm5XqOytc8It/D7Ng/ZT9Z3x+grVs 9JNnIshdExzsjQAfnXvfwO/ZB8ffHPSf7cs/sfh7wzlsatqjFVl2khvKUAswBBBY4XgjOQRXZ+MP +Cd/jjT9Bl1fwvr+i+OIoVYyW+nylZyRzhAcqxx23A+gNNyV7Nit1R8maoZGuAYoVmbHDuMheKoQ 2erQx+WuoZT/AJ5sWK/Tmut0PwnqPiLxVY+G7K33a5eXS2cNnK6xMZi20IS5AU54+YjmvqjTP+Cb /id0ittW8ceGNI1qYDZp3mvNJyOAeF5+gI9zVNxjuxWbPiqbT7+6ULPOJlHRd5AH4VW/streQMfK yvYyA/pXrPxx+A/i/wCA3ihNE8VQxkXCGW0vLNy1tdIDglGIByD1VgCMjjBBOR8LfhD4j+MXiqLw 94V0z7fqDL5rnISOGMEAySMeFUEjn1IAyTiq921+gtTJ+CfgHw94++Kuj6P4v8RReFfD12ZjdasX RVg2wyOnL/KNzqi8/wB6vc/2zf2bdN/Z9svA8uj+I5/Edrrq3UhN7EigCIQFGQp1yJj+QrvJv+Ca Xie3t/syeOvC7eI/K3jSi8i5bGcBtu7Hvsrd/wCCniz+HvC/wUsp4gbiCzv4ZFX5gGVLIHB+tY8y lNcrKtZO58G3011qIjN1IshT7vlgACoY4YEwGikY/wC9ivff2cf2X/Fn7Q1nfavavZ6H4XsJPKuN X1N2jj3ABmVAASxAIJ6AZHNdp4+/4J7eMbPQZNe8E67ovxCsYmIlt9Fm3TqQRwg5V8dwGDexrTmh F2YrSaufKeoaHIbVbuMqsZ6Rs+Wwe/0pul+H5by4KM6RYXJYtkVvXkaadZ3NhcWzW9/CxjnSRcNG wbDAgehGDWXHHJNJJ9mZVlThl2BeP84qU20ytLm9DpMdvaqJbjbu435znjqCay7fRUlu2jDvs3ff 8wdPUUlrp1zc2wjvZnBByoR84H9KdDoUaSZV3B/vZ5/OnGVkJxJtY0vbHEltK+5T8zZ+8uPu5qnY 6d5O5mWVJMEmVpcAD6Yq61ilhukMzDIwWkfgD09qLc2moP5Juzgg5WM/eHvx0pbq49jGh1K3jih3 QtLMmR9o5ywNbFndtdIsiAFQduOePasy4sYYLpkjJe2B++DkY98dK3pdPt7WOOWBnO7glW4bA70p KLFFszptPnmKG5ujLIV2ltoIXn+HPQ1JNa3MbAC6M0bABQ/DL/8AWp8sg69h70qyFlD4+YjAzTUX oNtAqrErZOQOSx6mqDLM25mZQzcnk8DsKtz/AHVQHGeSajOzcMuoHua0tfQSdjHv3n0+6iM1u0kT jIySCw9vSmWsMupee6QNDCnO7lgOeh79KgRb2a4M8TYO8hWaUA8HrzVmGC+iukLK22R/ndZNw56k 4qdTb3HoSSaXIY41MqYXOOvc1EdNdhxLHW66qV+8DyelQrGM1rc5jJ/s2VWBEsakcgjIqW60l77E jSplvv4P8Xr9DWnsx2qSMovDBQjcNx+tIDCXYlwv7iNo7MMGZs4cgZx9c9KgkW8y7/bto5c7pGBH fGOxravswqwkSIhCCcjj2Pv606G1sr5RL5Tz5BM8cLFQFHTIPqfSo0W5pdtGHHfRPboJrvzZVJO5 geh7dOeaZDHJCy3hRLmORjGoY5U//Xq80LW4Mt2JoA74SOBUARR0zn/PFC3VjuVpDduq87ZEjYH3 4PBq+W60M+Zp6ktjp8E1uPljil7ybST78GoVkS63IrgjJj+YqpPGcgdauX8mIZLqK5kYOgQRKhyM nr/9al0fTZNSaeS9nfzWTYpX7xHqSOlZyqcq1LUFIrWcGoNCBFNKsR6o5wePwqX+z52hAmCtNnmY Nnd9R/hVi+0ezsod3n3DTRn5liky/tntRPq0cTMSjumchkIPBqovm1SFLTqZ01kbeFnk25Vgu2Mg kk1EuI2H7pgTx+8AxVy6aeeWGe1QSrjJVzgr7EU241W9ZQfsqsUGAuA39Krma6E2TtqWIfNWPHkQ 7h06EEfXFTb0b7yCFvRgMfnToG3Qxs3BZckdwakZgF6g1RJSutPM2CDs94+M1EFeJQjr5iLwPWrZ 2q2Ufyj/ALJ4/I0nmMeCFk94zz+VUrE6lPy4G4DNG3p0H5VDNpYm/hSTPTjB/Or+2ObIVhn+6etR NalDlSy/SiwX7mPNpCryN8X+8MiqradMPubZR/snn8q6HzZE4Ybh+VMbyJR8yYP5VNh3OZdWjOHU of8AaGKbXStZiRTsk49GGRVWbSeMm3GM/eiOKQGJRV2TTgPuyFD6SD+tQvYzKMhRIPVDmgDqPDfw p8eeKtNj1LQPB3iLWNOkZlS707S554WIOCA6IQSD1rVX4F/FUfe+G3i1x3DaFdf/ABFfoF+zX8SN V+D/APwTbvPGGjQ282q6TLdywR3qM0RJvAh3AEE8MehFeC/8PWvi9/0CPCf/AIAz/wDx+ufmlJuy NbJLU+e1+BnxPHJ+GXi8f7uh3X/xupB8CfiY/wDzTbxeD76Fdf8AxuvvP4D/ALUnx/8Aj94F8W+K dIk8AaZaeHAxngvdPvDJLiJpPl2zEdFxz3pvwp/ao+P3xa+CvjD4lafJ4AstM8NfafPs7rT7wzTe TAszbCsxXkMAMnqKm77Dsj4P/wCFB/E3A/4tx4t/8Ed0f/adIfgD8Tef+LceLv8AwR3X/wAbr6B/ 4etfF7/oEeE//AGf/wCP06H/AIKsfF1nCtpHhPnp/oU/X/v/AEWn2F7p8/w/AH4m+YM/DnxZjB5O h3Xp/wBc6YfgH8T2hGfhx4tzu/6AV16f9c6+jP8Ah6b8XcAjSPChHP8Ay5T/APx+vbvE/wC1B8fP C/7O+kfF+eTwFNo2pGIR6fHYXf2hN7soyTLt4K+tTzSK5UfAX/Cgvihz/wAW48W/+CO6/wDjdH/C gvijjP8Awrnxd/4I7r/43X378Rv2ofj18Nfgb4T+J95L4CvNL8RfZxDY2+n3Yni86F5V3EzbTgIQ cHqa8R/4emfF7GP7I8Kg/wDXjP8A/H6FKT2Fyo+U/FXw+8V+CbeJ/EnhrWfD63TEQtqthLbCUqPm 2l1G7GRnHTIrDu+LqXnjP9BX6J/8FTtSl1T4e/CO+mCrLdfapnCA4DNFbsce2TX54Xi7p7huysBV xd1cTVir3oqRdhA3Bt2f4aKomx2W6D/npb+/zdKFMMh2o8Dn0Vs1gw2M26TCxShht6Z/Opfsl0cL t2R5OViTZwRjHH51tdCVzb2osKAmMDe3ViB0oVYm6NCT7OaprDBDpsCywPKFc4RmAOcYyfqKkW+W BcQ6eEP1A/pU3LsWvJHon5mhYR5LDC/fB6n0qBdYl282jA+z8fyqRr+RrNpijIwcLgEA4pXYIf5A XrtH/AiKTy0/vIP+2hqmbpjz9mkJP94iqN5HPc3AdIflxjDDp+VXp1J9Db8pexU/SQ1+o/7V37TO p/s+2vgaDT/D2k64NUs5HdtTDZj8sRAbcHvv/Svzq/Zx+C+pfHLxz/wiWnXVrpd3JBLdC4utxj2o BkfKCc8+lffP/BQD4Gar4y+H2meK7XULKG28HabO9zbzBy8+7yvuYGP4D1x1rnqOLlFM0jezNL4b /Gq+/bA+B3jTQ/Dsz+AvGtjDgx6ZKPLmDqxTDlNyK5Vkbady8Hdzg/mvoejjVvE+laPM5tpLu7it GBBLIWkCHI9s96+gv+Cc/j6Tw3+0Tb6XcSulvr9hPY7MAJ5igTIfr+7ZR/v+9Uf22fgLL+z78Rbb xLa6tHLZ+J9SvtQsoYoyr2RSSOTaT/FzMMY7LRG0JOKB6q56h/wUe8c3fg248HfCvQM6X4ZtdIjv XtYDsjlHmPFEjAfeCCEnB4ywPUDHz7+yd8Udd+Gvx08KS6dfTLaapqFvp1/ZqcRXEMsgQhl6Eru3 KexHua+rfHnhbQ/+Chnw08OeIfC2t2GkfEbRbcw32kXrkZDcsjYBYLuBZJApGGIIBzt5/wCBv7F0 vwL8V2fxG+LviDRNF0bQJPtdvbLc7/MuF5jZmKgfKQGVV3MWUDFKMoqHK9ws73R5z+2x8NLqx/a2 +x+DbKdtZ16K21KC204ES/amLKzpj7pLRFy2eCScik/4YC+Je6LUNc8U+EtB1SfFwYdX1qRboMTn JZY2BOe4Y8967L4S/tLeHPHP7dVz401xo9N0a9tpNJ0ee8KqLYBVWJ3Y/dLgSZ9DNjOKp/Fz9hH4 qeK/il4g1y41XR77Rb6+kvH1zU9Q8tEt2ct86kFl2KQMAFQFwDinzONot2C19UdF/wAFHLXUrP8A Z6+Dx1i6h1HXoTHDeX9u/mJNKbRfNdHxyrOu7OOeDVL9j++m+En7EPxQ+JOnhf8AhJJp5oobkxgt GsaRxxdeu15ZH9OR1rv/ANsb4JHxf+yD4Jm0DXrC60fwXpVveC9+YJf262qRo8WMgBhhhk4weteJ fsE/F7wdfeB/GXwS8bagmmWPiYyS2V5cSKkZkkjWJ4w54D/JGyZ4JU9yAYT/AHdvMLe8fJ+seKbt ZpdXmuLi51G5lLi8upGaZ3zky7icls9yc19of8FOJmuvBPwLnneee4k0++ctnLOxjsSSzE9axtc/ 4Jt/EO314rNr3hweHbcZfW7ido1SEHLSNGVO045xnGf4sc17x+3P8Ar34i/CDwzr+k61ZJp3gjR7 y5leZGLXcZigKmPAIBIgJ5P8QpuScotMpXS1PHP2YPHvgD4rfsx3PwP8S+Jh4D1r7W8trdXUipHe hpvNXBZgHIY7ShIJwpB9I7r9nv42/sd2+teI/AGsRXOgzW4N5f6TDFckQqNwkkt5kbAXk7kDYGSS Bmuf8Bfso/Dn9oT4HQjwF4nd/i9aWsMl7ZanO8NuW3HegUxDI2/xIWAOASM17b+yl8MfH/7Jmj+K Nd+L/iqz03wKlgYoNDkvhcBrjepDxgnaGKhkCKSXMg44FTLS9n8gvdn5ra1PdaxrN7qErfbZ7yaS eW5XK72ZizEqowuSScYxVzRLWz8gzSzeXJkr5cbnLZ4/WrsunDdfGSJrK1uJzNBbRsSUJJwu7uAC B71V/wCEYZcNEwg2kE7e/tW7l0ISLsbMvH9acrPu4H61BJvj+9gZ96a1reXduXtuAM5zwT7U+VBz D9Q0e51OEsJyEB37CBgYHQHv3rItbG6XKw3QjCjBw6j5fSoY9SvOY/MdlxtOG7+tac2gz/YFlmmV eh3BRkZp6RRPxMBojWkYMs2RPjC5x83Yn2qWPS5othF1H5KggRbieT35quLOWOSNt25V7s1WHkZU 6jceAPelbqUI0Ikk2EqVXltvf2qZcMxbPHb6dzUSgRoEBO5upA/M06SRDHsBwW4wf7taECBhIS+O v+RTGjBJ/wAKlDJt++o/GlQx7h++j6/3qSeg3uY2tR3JgRfPiikUb/JViWbPAIP9KyWtb5URz5iJ IQFZmbBzSXEcl3fzpCFby3K794Xucc1MsM5tn8922R8mPzQcZ6cVOpouTqdFa281rbRQTSRzFQcu hzjHAHSnq208HH4Vztnq7Wqv5cPXg7jz9av2uuCeQJIuwnv2q0nbUyk43901GkLY+Yf980ZzjLr/ AN80iTKyj5uD0p4ZWUEt9eKTGEiieHaXQsg6MCcr/wDW/lWNdTSafOZFmAR1KFYwR+OfxrbEm0hk cAg5Hy1R1GBZlIDSLG/I2DOCO34VIzM1jT2mW3CTxOiLwo4K/UVXbRWEYaSe2hXgknOeegIq7AqK zfuY7l8Bf9IGMcdc1tw2dtdKV8lQnB2sNwzj3PTP8605lYjlbfkVNPkW2s0R7uE7FVdyoRx2ye9T SW88syTQXZWPGMqvDVJJHpSlopI4NqnkAHrT2eyVY/IcL8uNuSByfT196znFS3RtFSsQx3SwXyre zDCKTuk6e3HU1ojV9NCZF1bAfiDWbJZo03nMhEq8bwxDfnSfZU3bg0gb13mpS5VZEvXUtXM8F75b W8kcoVSC0ZzjnpVZlPc5qK2t1sJJXi3I0py53H5qsPMnlu8su1V5LMenuatXENjU7sg0k24q2xQ8 nYMdoqMX1p0F3Cf+BU3ULhBpskysJF/hdDkEjt9aeotCG907UbqSN7RljTHTcM+/OKjj0PWxIm6W EqDn53B/pVbR9dmhV/8AR1nj/hy4Uj8av33iI28JdbQ4xwwkDAH3Gad2JpX0J5YGVikyLuHBB5x9 DUflvH/q5P8AgMnI/Olsbz7dapO7DfJyQBipTs7GmmxNIhLbVzKhT/aX5l/OmtCsgypBHtU/C9Gx UbQRnkZRv7yHBqrk2RVa1KnK5B9qA8qcEbhVhvMTGMSj6YNMFxEzbWzG391ximLYheZG4dcf7wzU bWcEnKHYeoK1ce3Dcjmq72eDkcGlYLn6AeBYD/w6v8SR58wn7T97/r+Wvzom09M/PC8R9UPH61+j ngJWj/4Ja+IhnLf6R1/6/lr8/PPHRlI/UVhT3l6mknsfeH/BOG3EP7OnxqCvv3I+OMf8ub1W/Y0i eH/gn/8AHNXXacar/wCm6Otv/gnmsbfs+/GTaFwyyZ2/9ej1V/Y+tRD+wf8AGxIz97+1CM+p0+Os Zby9UaLofm1n8aAeh9K17qwZFzNAG45aPg8D29816r+zX+yz4g/aS8bDTNJd7HRLRw2p6vNETHax 56Ds0jc7V78k4AJrpdkrsxR5MrAcEdetfof8Xf8AlFz4J2nHzWf/AKPkrb8XfCn9i34W6xN4c8Ry s2saeqxXZF1qM7BwOfMaHKB/VRjBOMDpXKftYfH34Ka1+yxB8Ofhprv2oWN3bfZNP+zXQ2xI7M37 yVBnr3Oea5G+ZqyOgs/tWEp/wTu+CpzjD6V/6QzV+e5ky3bFfpV4a+O37NXj39m/4feBPiVr/wBq bRdPszNY/Z76Mw3UcBjPzwoM43OOCQc15p8XLP8AY2T4ZeJT4HmY+LhZP/Zg3an/AK/+H/WfJ/31 xRF20sD1Os/4KbNt+FvwX9DFOOuP+WFvX58XjN5865+Ut6elfoH/AMFOV3fC74Kc4Plzf+iLavz7 vPmmcZwck9cdzV0/hE9xnlDzMAniio/MYuDRVkaHd+ZFBwCFH91RUbXrY+Rcf7xqDb+Apyx1qohz DJUNwwaXMmOmelSCM+9PVM8DJ+gpkl1DC2xmLyddiDJ/+tVaInVjgu3vTZ4Yzjz2CAc4Y4/Sozcz yfcQQL+bfnUaxANuIZn/ALxOTQBM12vSJGf/AGn4H5UwyTSZ3Snb/dUYFAU/7VL93+9QA1VC9P60 jRhsEkcU7zD6sKTd7mgBMf7X6mj3z+tLu/2v0pNoJ+8SfpTETWd5Pp9zHc2lxJbXEZyk0MhR1PqC ORVvVdf1XxFJG+qaneam8QIRry5eUoD1ALE4qiQqdTuPoBUbtu9h6AcUrAPO1ehyfrxVu+17WNS0 ZdIuNYvZdKXG2ye4cwjByMJnbwfas78KXlegpgVf7FgPB2/985qSPQ7YZO8HIxjYKm3N6U9XP8Rx 7Zosuor9iLVvFOtSaPBo/wDaWpPpkQAFlNdO0KgH5QE3beOtc9G020Ax5Ockk9fbrWtrniCGa0az NsqyI+DN9O/41jLHCtqszSxuSf8AVhjurOL01Ka1Nvw9f3un3CMst1GybnhkhkKvHJjgqwOR3rR1 jWte1qa2m1S+n1iWEHabueSUxg8kKXY9/T0qlY+JI7fT1to4VDDgzdvc8+lajMGgUg5XGR71m2zS KMxtfu7zVLaCVfLOfnXABCnr/Kr13qG6Tar8fWomjUuZNi78Y3Y5qG6kgtU3zSqo6Dj7x74+lUo9 yWyOS6Rusn61DeeIIxbmyiTbJwTMG9ulMOrWXGNzZPGE61ZttQ0u42oWKSMcEtGMfnVSV0SnqYcd wfKZWWMyH/lr5nP5Vtxa6F04wOokdyAGznHI4FXfssAb7oH/AAEVOtnbeXwpLdQQBWbsWinuDc0+ 3/eOXxwOF/rRNC2AqA/McDNTeX5MQVfoD7+tbIhjo13Et1z8q/T/APXUDIJJXbgjO0fQVZkkWGFi v8IwufXtVaEpEgBdeB3IH40PsOPcR4x6D8qgaGM9UX8qmluIh/y1T/voVVkuohn96v50yRTZwN1g jJ/3RSebbQOsE0KtGpLbV+U8j1/KoGvUHSdRWfeKt1KJDdLu6HIPNJq5SZpwLbMx8yGNl7YkAP41 PG0EeQIISvPJlAIrnV08zOEjuIyW6DkU17ffGEE6jHTGalpvQadtTpAP7v3e1Sox5APvVC1uF2oj SZ2gDgGrP2qBP4xkVorkNlje39/FPjLyZj3Kd3K5/vVUN1C33ZFz78VE2oRRsQSyup9O9FguSu0y kEBfxqCzOoQyPvuAIfmbgDng8Ul5qqLsfawWTJBA4yDgj8/51Sv9V8yzaNVJJI7Vm0zWNty409rd XkL20rWgAVPnXcCTxk89Ks3Sw/b4mnvBOFCkx20Q24z0yDwa5eFjIwBPl49ifxrVOntNA9w1zlVO cSLgt7ipszq9pC9zdhkW43vHLIVLfIGUcL6H3odjH05FZ1jMtrAE8+JgTu9CKtyakrKzOFfHUxkc ++KpJ9TmlKLk3HYl3ecu0MVJ4yOoqT+zRNp01pJM7bzhmKjd2IrMnujEzoUII47VWHiBobXH777Q q4Ck/I3uaLE3saH/AAiSbcfbJMehQVowaOtjpMsKyebtfzMsuDWHH4mH2PczOLrafk8vKk545z0x Viz8VQtbEzO63BBXyAvyk9iD2oepKHtHGPvQp/3wKTyoO0Sj/gIqKTW4pcAQFG6cHrVeS+2OQ0bI w6g1Yi6rJCu0IFX0ApxmD49az/7VTGGiY/lTP7QQ5+RgPWgRoTTLAgZ3AHf2+tQf2lB/z0/Q1ALd LxGh+0qA4yjTPwcfw57GpLTQXnVVjue3GCCKnmit2Nxl2J47tJPuOHx1HenmZJFw65H+1zVax0kC +EYuQZlyPLc4z7ZqKS/CyMpiwQSMbulNSTdkJxaV2XVjC8wyFD/dblf/AK1Kbxof+PmIxr/fHK/n VBb4f3P1qaPUpo+IwvPUOcg1TdhJXdj9DfAsiN/wS78RMnzr/pH4/wCnLX58yahEvDQkEdjX3/8A D6by/wDgln4hcgLg3HTp/wAfy18hD4J/Ea4hU/8ACuPEyk4PmRaRcgEfTZiuH2kVe66nfTpt7M+u v+CdtxDcfs+/GUxo0YAk3ZOf+XR65H9jn9o/4Y/C34K+KPBnxBkvJU1m/maW2htHlSW2kt442Usp BGdrj1r1P9iHwZrngz4C/FmHW9C1TQpZopHjj1O0eBnAtXBKh1GQK5f9iPwD8ONY/Z48Z+MfHHhH Ttd/sW/uZZJprQSzCCK2ikKoGP8AvEDI5NT7SMm7rczdNpXT2Gf8LD/Yn6Hwpd/+A97/APHab8Qf 2yvBvhP4dWfw9/Z10a40681SZojcRWjpJAZCBmIEl5JnJwGOdoAxzjF0/tA/sjEZ/wCFVykf9gS3 /wDj1XdA/aw/Zf8AAmqJrfhz4aXdhrVqrG2uLfR7eORWKkYD+aduc4z71rbybMfmil4G/Zd+Gf7P vwrn8a/tCul/q+quoXT2mlZoC3PlKImDSynJLnkDB9Cxyf8AhN/2G+MeE7j/AL8X3/x2vlb49/Gj xd+0d4+/tjWXVlL+RpmkQ7jHaxsRiOMD7zE4y2MsfbAHrul/sZ+Efhl4bsNa+PPxDj8D3F9H5tv4 d01PtF/s9WwGwfXCMB0LZ4qnHrN6+Qubtselt44/YcGT/wAIhd/UW98f/atch8WPG37IF78N/EkH gzwzc2viuSzddNme3vFCT4+U5eQqPxFUNM/ZJ+Dvxkhktvg98XZrvxGqF4tG8S2/kyXOASQjeXGe norY74HNfLvjDwjd+AvE2o+Hdd8/S9Y0+Uw3NpdQnKMPpkEEYII4IIIyDTjTjLZsXM10PuP/AIKb Y/4Vh8E8jPyTf+ibavzzuMefNnn52x+dfdH/AAUC+JnhP4i/Df4QQeGdf07XriztZbieKynDvApi gUeYAcocqw2tg/KeOK+HJoAztuVkYncaVOL5Qk9SuqrwM4+tFWIbW1eQB5pYU/vFQ3P9BRV8rFc6 9VLZwOPXtUMl7DGcLunf0UcfnWRcX4uj+8ucqDwm0gD9KdHeRxjCuh+rkf0rXUC/LJJdLiQlU/55 x8Ckjjjj4UED8Kqf2ow6NB+Mp/wo/tSfsbX/AL+0AaIC/wC1Tvl9cVmnVLtujW34ODTDf37dDB+G 3/GgRq8djimH/f8A51lNeakf7v8AwEJ/jTBdakf4N3/AVpgbAx/f/Q0vP97j6VjrNqEjBfJGf9pM Ae5PYUkmoCPasZWSbvMoO0f7oJ5+poFc28FeWfaPfrTWm4wDgfUZNco9xcSMcs59+aTfLx87En3q 7E8x07SqvVgPxqNrqEdZU/76qnonl3Ed3bXjiKNlBDEYZjngfTPNULi1NrcPEwIKn+IYOO2R2qOt iulza+2QL/y2T86Y2oWy/wDLVT+dYqqWZVVdzE4AHUmmSt5LOhIDqcHnOPWgZ0DXkKtt3hn7hRn8 M1HtSXc2XGOTXNeYzHAY47AGmxsGYAuw55bdSEdAdHgWRrgtK7Mem3j86mW2ttvEcm70AAqPRNXj hsJbeUM5EgZFUbmwRzgVpQTAlSybT/dYYI9q5pXubx2M6bTIpIwxt5cqc/eGKs3GoeVGqiA5xjBc VrNOi254rD1JmhmCsQjFc7B1XPY+9KMmxtWHXl5IsKCBY2dhjcSdob29RWbrFrcSXZyVZIx5e4cA 46n8T/SnNefMmTnaQQK0X8VWf9ktbNb5m6NkZGc5zWt2jN2Zzot5RjBxjpz0p8djNINqkE9eKuWW pTNumVINq5GGq9pvjSK3kaSa2UuRtXyxjFaOS6Ecvcia4u4thebJZeVA6U7+0byYpAs7DccDBxUa 3p1ea5uMbckYQfw01VMMLyY/eSN5Mf8A7Mf6Vk2amhp+bi5abJaOIbELE8+/+fWtL7xBJ6VBbQrb QrGvQdT6n1qZa1irIzbKOrsSILcdJWyfp0rFumWa4kbHGePoOBWrqEgbVAB/yyjJ/HBNYvWkviKf wjo1h/jD/wDAMf1qRxa7RsM+7/aC4qv+NLuqyB+2L+84/Af402ZY0YbJfNHrtK4/Ok3D1ppxQIlt IWuZkjVN7OdqrnGTT/LG4gjnOKgil8twwYqQcgjqKtwtDI3zXG0nrkVL0KWpoabHE9v5aSqDLlXS XjDfwsD+mPes1tNuEuJYzHtlU4KM33vcetUb+RYZHVWD4PVTwfQ1AuoybSHd2B9WzSi2ncJWaszZ /se4eVUwiuy7gpfBPqAD3qW40maCxjnIyBw3qv19KybjWGuFRHkeRVwVJ+8Pxqxa6l5ytCGaPcOe eG+tDkwSiWbeP7TaXFuw5H72Fs/xgfMv4r+oqnC27HepWXy3DBhuU5FRzKI5cr9xvmX6GmBKY2bh Fyx6CretWt42mwQLEZViUhmiGVAznr+IqrDcGJlcEqVOcr1FLHqFyLuVLa8KRE5wV/DpUy5vslLl +0ZCW8x48pyc44H6Uv2e4D4EUgPTGDXV6LYsqzNcFJgRg+4Pr9CBVrVo7O2n+0TPsDAfMCeGHBBF X5E6X8jItrOeTTt8iMk8IIdJOCyg9R9O9Upow3VAfwro59a0i6jVZbnzFU5Gc5HFQ+doki/Lcqp/ 2iRUR5re9a421fQ5lraPP+rAoWBFIO3kdK072FIZmRZBInVHHRl7GqDcVaE9ApjSk46nAx60M1dJ Z2ot4rVAqt5kQkLUdbC6NnNsXTG6NhuGRx1FRtNtU8EH6V0LeILFGZDv4OOE4zSvq1nGsbzFSkq5 XEZz1xzVWRJykl3mQMiCP1UEkZq1/bT7Qpgh/wB7bg1umHT9aSRLVQtwq7gQuKwPLHdRUOJWo0am 4feECn1WtaOK31Abo99tJjLbvnjJ+vUfrWcsStwqAn6Vb8uaO0dlhYKBhivKnPQ5pFJNojaHaxG5 W91bIqOSNmQjcQPaqSxvsKtGxz0buKTyphxhsVRmfo54AR1/4JQ+JFDZbNzg9P8Al/WrkH7S37Y6 QRqvwdtGUKAG/sa5546/6+q/w7x/w6k8QGRSRi4yAcE/6eteOR/8FKPjGI1RNX0uLaAAJNIjYY+q n+lcnLzN2XU3vax634o/aP8A2u7/AMM6xa6l8Ira1sJrOaO4nXR7gGOMoQ7ZM/GASfwpf2LGkX9g j42GUl2B1Tluf+YdHXqX7Kn7QHjD9oL4G/FO/wDF13Y3dxp8E0Fu1jbiEBWtnYhgO+a8v/Y3R4/2 CfjcHUq2NU6/9g6Ol0at1Q7+Z8D295tPAH0Vyv6N/jVr7cF/1isg/wBtCB+Y4rn979mpyT3Ef3HZ f904rsMD6p/4J9aXpvin9oSO91S2S4t/DumXOtImNwaSPYqED1Uybh7qK674V6Z4Z+NCfFT49fF+ 2ufEumaHIhTRoXI8x5DiOMkEERoDGoAIHJJzjnwr9j/4xp8Efj5oev6oVOh3e7TdTLD7tvLgF/or BHPqFNev+MvGXiL9gj46+LNAtdFsvFPw98TRC5j0y/G62vrJy2wZwRvQs8ZOCCByCCMYyvd23KVr Gx488I/Drx98BT8Z/hZoV14A1Xw5q0Vpe6fFdMyby0eySJyeGUyRkFdv8WRkA1X/AGzo9N+Jfg/4 NfEa+sI08Q+IdFmh1GVV2ea9u0YDYH+1JJ+G0dBXI69+0R4h/amvvCfwd8A+CdL8BeHrzUFZNJ0s ZRpOS00rBV+RF3OQFH3STnAxZ/bs+KGkaf4z8NfC/wAMIl3o/wAPtP8A7La6Z8NJdME84cdceWgP +3vqdeZFaWPAP+Ef0+JjtgKg943IP5Gsm90+W1nH2eViOv73g/SoP+Ewl3BTaqvv5hxVv+0FusM5 wfQEGtrNvViuktigyyiTfJbrIemFHGPXjvRWjujJA3c0U7eZNzI3Qc5gcfSX/wCtQGtv7kw+jr/h UrXC7vmt7f8ABCP6037RB3tI/wDgLMP61QDP9F/6eB/3yaXy7U/8tZh9UB/rTvNtu9r/AN8zH/Ck 8y07wTD/AHZQf5igA8m3/wCflh9YT/Q0fZ4P+fpfxiYUbrP0uV/FTSf6I3SS4X6op/rQA1rWL/n4 h/HI/pTWtVRSwmgYAdFfn8sVLFZw3UyxRXDl26bouPck54FVZY9krBJPNUHAcDAPvQSWWuf9G8iM FEbmQk5Mh7A+w9Kn0pYWvIxPKsUZ+87dv/r1nKjswA6ngc4prq6spwsu1sledpx2+lUI6PxLb2dt DAlmzSSscn5sgrWfbafMt1Aj4iVzhpG6D1qrqur3urXUUxRYvKG2ONPurVaSe7mYeaWfHbNUpu6F yq1jttQj0/TFjkt/3tzkCJc5DMehrlrlX+0yiV/MlDHe/qe9OvdWvL68tZzEsK24AjjX7q/54/Ko I/mmUyuQpbLtjJ9zWer1ZSslZApaNgykqw6FeDWvpnhxtSs9ybB3LMOh7D8v51kySI0zMilI8/Kp OcD61ZtvFFzp4eCNwseMj5cnJrOV+haKU1tGlwYyUB3be9SWtnFNOIgy5LbQcHHWmxXBvbgKqxKT yXap/tUljcYVYZNozlRmq5tAtqdLDof9husnnoryK0QYLyCR1z+FUIpGbDs29m5LHv71lar4hutR jWGRiSe23FXBMqooB4AAFYO73NVoWLq6GzAP5VQm2spyST61JFdRxySM6eZmNlUejHv+FRsv7sf4 0JWBlMw5PHWoo9FnkJKAvuPGBWnDbgsMio7vWJ7ObyoH8tYycFeue9aLV2IempWXw/e4x5D4zjp3 9Klj8OXTL9zH4Uja5fNHuN055LYz39aSPXLyMBhOxGcYzT5WTzIvafpMun28m88tTbwMtnCxOSkr f0NWlvjcW4Yd/eqcreZazqf4Sr/0rHW92baWsjd3BlDDowyKcrVR0mbztPj5yVJU/hVrJrqRgPkh SbG5ckdG7j8ay7rRCuWgOR/drUDflTqVhXOTmhaNtrqVb0NR811Vxax3S4kUZ9R1rGu9JaAkg7l7 Gj1KtfYzsUbRTnjKsQeD6HrScimSN8sUjIG60+koEQPZo9M+wL/eNWqTmgZWFiP7xp8dqI2DA81P RSAKBukjKDkr8y/TuKnt7Xz0LF9uKFihjcMLleD6VVg2KZ8xlI7EYqr5citnDZAxmtjyYN/FwAvY d6RoxGeGV17Mp4NS0ytBuhtJcXnlSu4i25bnB/Ct3UNJj1SQWz3TLJEP7vLDsT+FY1vdJaTI7HCn 5c+ldhaKHjPGTuyD6Gp1itAVm9Tnl8DD+G8OP9yj/hBTnJvP/HK6gRsy4pdpIA9OlHMFjltQ0RdN sEAmE7IdpOMFQeRWOy4ru9RhgmtZfNxGWTa0uOmOh/A1xkidRkNg4yp4P0pRb6lO3QrLGJSsTfcL ZJHX866axkLW4ixgxbgueoz2/Oua8xYZFZuFzzitnS2R8OEdJFIG5TlGGMHj9abdhJJmafDt5uOY uc56irFxodxJb2qbDmNCp9jmt7zG9aqXUlz9oiMQYwYO8LjOe3WncnlRT0PS7jT9SWR0whXBbtWf qUIh1C5QD5Q5x/Ot2B5mjlE3mY3fL03bfb3rHvLczTXDxTfaTGcspBD7f72O/vilza2K5dLmczeV 844KnNXtP1GdrzbbI2x+qoeOevFZ8ysyEAdaLScW6jKkOvp1pSsEZNbHQzaaysJZbSTaOH25A+uP WqV0tvHOBDJIhHOOuaWHUJNoH2mSRJF5UkjH0/w71Hcadcbo7lF3I2QGU9COx9KaaS1YOMuh+nX7 L/gmy+MP7Ab+CJdet9Fk1SW6hN06q5hxd7wfLLLnO31HWvOv+HVdj/0WCy/8FS//ACRXwNax3vmC aASBgSNwP5g0y3s5r24wihZC3K8Lz6VlyON2pWQ7uWlj9R/hh+xz4t+DvhnXfD/hX456VZaXrYIv YpvD0MzPlChwzTkr8pPSjwL+xv4u+G/w717wN4f+Oel2nhvXPO+3W8nh6GR382IRPtdp9y5RQOOn WvzVihNvGg8hcrw3ygNVxbiPaCQqD+9jA/8ArVPLLv8AgO9uh9s/8OtLVvvfGCxkH+3o6H/24qvq H/BLnTrPT7m4Pxb0xDFGz7ptPEUYwM/M32g7R6nBxXxn5h9aPMbt/Or5Z/zC93scvNCkUjoRJ8pI 3Bdyn3HtX2b4fVf2v/2SJ9AZvtfxL+GUfn2LMD5t7p2MGPnkkKu3jPzRx/36+WfMeu7+CHxk1X4G /EbTfFmmQrdNb7o7izZ9i3UDDDxlsHGeCDg4Kg4OKuSbV1uJWPZv2cdNg/Zh/Z78RfHLU4o28Va4 jaN4Rt5cE/NkNOAe2VJ/3YiP+WlfGt9JcaheT3d28lxczyNLLNLlmd2OWYk9SSSa+gv2kf2iLr9o bWNHdtDt/Dug6RbfZ7HRYJRLFCScu4OxBk4UYCjAUCvEL6OG1+Y2nH96MlV/nRG61luD10RiBSvS j3KqT6kVofaYmO3yCox1LZNRt5b5AjUe+Mf1quZE2ZWWYr0Lr/utn+dFT+XHx8v15NFF0KzG/aoe 9lF/wF2H9aPPtD1syP8AdnP+FNY2J48y4T6op/rUeLPnF1J/wKH/AOvTGTeZZf8APCdf92UH+YpC 1i3/AD9L/wB8Gq7C2PS9H4xMKTy4W6XsP4qw/pRcCcizPSedfrED/I0qwW0jBVumLE4A8g5J9ODV fyExkXdv+Lkf0qwH/sqPeWVrqRf3ZQ5Ean+L6ntQInuNlgj2kUgeRuJ5V/8AQB7etVABVXzhThcC qQi0qhu9WYrdG5JrPWcVPHdVtGxlK5ea3j9c0sdqpaq5uhikW8ArW8TPUtTwqo61SfC570SXQbqe O+OtMvL5bm4aRV2JgKi+gH9azk0XG4mB3qFrWNpN5Y5ppnpvnVzuxsiTy0HvU0KoDnOKp+cKXzve p5UUpNFuSGKSZZMnIFTecu0CqHne9J51LlQ+ZmgshSNmC5RjtLFc8+gNP84HAqib4tapb4wquZN3 ckjFKsw9aTSHzM2LZw0ijOMnk/Tms++0e6tcS3EbIrdGPr1qM33kLvXqK19X8aWl9prQIjh3GPmA wKle6N6nPNEvHzYNT2ti91IkUWZGJ4VahtIftCl16ZxWnoXiC10mR2ZGbIwSoGa0cjNRLEml3Gnr HDN8pJLDnOagj5aVD/EjD8uak1PX11a+jZAURVwA3Wqq3Q+1Re7Y/OspG0ehe8OyZ+0R544YVscd 65jR7rytQdP7ykfka3PtHvWyZkXRinBgv0/lVMXHvS/affimIt5o4OQRkHqCMg1U+1Y46+lH2mgC O80tJlGwZ/2c8j/dP9DWLNaGEMSeAcHg8fX0reNwcdcGo5Cs33j8w6OByPb6e1TtsVfuc79DRVy9 0/Zlkwo9f4f/AK38qzXLRsQw2n0NHMLlJsikzUPme9Hme9O4iep7OG3nm8u4laEMPkdeze/tVFZl 706S5WNdwwcdQelS2Ubt5YzLC4YoZAPvRjG8djxwR7isRdLmHqR64q1Z600JQRylNpyA/I57fSro 1INMWhCRxnny85APepUntbQpxT1uZX9lytgdPTirEOlzwoxIyp/nWw2ppJHtcLn170yLUpI1KsY5 Im+9G3Q/4U3JpXSHGKbOeuELfUHNC6peRrjzJOOmDipbiZWncqNqk5AJzj8ajaQL1wOn3un4+1D1 J2Jv+Ek1HnbIwH54qRfE1+QweQkH04qXWby30+6CLCAQQSO3SqX9uW558il7NWuPm1sSrrl7OjQS TNJE/wDf6ihWG0jLb88emP8AGom1q2aNlEO1ux9D/hR9ojk2yR/Krfw+h7iq5bILruMu8tGQO9Vo dSubYbY5mQdODWrczW9xHG6IIpekkar8p/2h6fSqElvG3ai5NhF16+H/AC8MfrTv+Egvl/5bn8hV Z7dB2NS2NmGmRjGXTPIzQCTbsblk2qXEaSfaUUMMgMBTn0eeaQyNPGZCckg4qvqlndFIRCNseMjn FZ/2C/8A9r/vqlzR7lcr7GjcaTcWsLScMq9l549apeaPY0tnb6nBcRsu4/N93d19qfdWO26lRCUl ++sLcbl9vcelHNF6C5WU3leNiVPA7Uy3vX2uhkkCN1VW9Pan7w1QtCjcjimJNotx6tPbsfKuWG7r kVG140sxlZyWPUjjNQeWi9RmnoI16KKA63Nyz14jAn3TRnpIf9Yn/wAUPatby1mVZY3Vkfo68q3s ff261ySuF6dKuadfy2sp8tvkf78bcq/1Hr7jmla2wb6s6JZTH8uP+A/4VOsiSAlTnHB9qx5tWibh UY8ZK9Sv49/rVy3V7qDzYJElKjoD849iKfNbcajcu8UnFZf9tLHKI51MTZx8wxVz7QCMg1VxNWZN xRux6VXaf3pPPHrRcRBeaUkmXgxG/df4T/hWQWe3fa6srf3WBzW4Zh61BcJFdIBIM46N3FS49h3Z lecMjnBop0+nSRZaJ/NUc4PDUVnqh3Z0LfC3VyeJ7L/v4/8A8RULfCjWT/y8WP8A38f/AOIr1miv nfr9fufuX+qOV9pfeeRt8JdaP/LzY/8Afx//AIik/wCFSa3/AM/Vj/38f/4ivXaKX1+t3D/VHK/5 ZfeeT2/wn1dJg0s9i6Lzt8x/mPYH5OlJL8K9dmkaR7uxZ2OSfMf/AOIr1min9fr9w/1Ryv8All95 5J/wqfW/+fmx/wC/j/8AxFH/AAqfW/8An5sf+/j/APxFet0Uf2hX7i/1Qyv+WX3nkn/Cp9b/AOfm x/7+P/8AEU5fhTrY/wCXmx/7+P8A/EV69Z2c2oXkFrbRtNcTusUcajlmY4AHuSaW9s59NvJ7S5ia C5gkaKWJxhkdTgg+4INP+0K/f8Bf6o5Ve1n/AOBHkn/Crda/5+bH/v4//wARSf8ACrda/wCfmx/7 +P8A/EV6tVu60m8sbOyu7i3khtr1GktpWGFlVXKMV9QGVh9Qaf8AaOI7/gL/AFQylbp/+BHj3/Cq 9Zx/x82P/fx//iKYfhRrXa5sf+/j/wDxFes1atdLu760vbq3t5JreyRZLmRRlYlZ1QFvQFmUfUil /aFfuN8I5VHdP/wI8b/4VPrX/PzY/wDfx/8A4im/8Kl1v/n5sf8Av4//AMRXrlFL+0K/cr/VDK+0 vvPIv+FS63/z82OP+uj/APxFL/wqbW/+fmx/7+P/APEV65RR9fr9w/1QyvtL7zyT/hU+t/8APzY/ 9/H/APiKP+FTa3/z82P/AH8f/wCIr1uij+0K/cP9UMr/AJZfeeSf8Kn1v/n5sf8Av4//AMRS/wDC qNb/AOfmx/7+P/8AEV61RS+v1+4f6o5X2l955HN8JtckiZBdWHP/AE0f/wCIqr/wprXNvN3Yf9/H /wDiK9mopfXq3cf+qOV9pfeeQQ/CbxDbx7EvbADOf9Y//wARUS/BvW883djj/ro//wARXslFH16t 3D/VHK/5X955Bb/CPXIZi32qx2/9dHz/AOgVN/wqrW9yn7VY8HP+sf8A+Ir1mij69WD/AFRyztL7 zymL4Wa1FfCYXNjt3E48x84P/AK0h8PtW/5+LT/vtv8A4mvRKKax9ZdRf6o5X/K/vPPP+Ff6r/z3 tP8Avtv/AImlPgDVe09p/wB9v/8AE16FRT+v1+4f6o5X2l9554fh/qvUT2mcY5d//iaUeAdVxzPa n/gbf/E16FRR9fr9w/1Ryv8All9559/wgOq/897T/vtv/iaQeAdV7z2n/fbf/E16FRR9fr9w/wBU cr/ll9559/wgOqf897X/AL7b/wCJqrcfDLUZVIE1p/ul2x+B28V6XRS+vVh/6o5WukvvPJ2+E+sb vkurIr/tO+f/AECmf8Kn1r/n5sf+/j//ABFet0UfX6/cX+qOV/yy+88jb4S60f8Al5sf+/j/APxF Rv8ACHW2Uj7XY/8Afx//AIivYKKPr9buH+qOV9pfeeN/8Kd13gC7sOP+mj//ABFKvwh19f8Al8sP +/kn/wARXsdFH1+sH+qOV9pfeePr8JNfXn7bY/8Afx//AIipW+E+tsqn7XZB+/7x8f8AoFet0UfX q3cf+qOV9pfeeTL8KdaHW5sf+/j/APxFP/4VTq8gw9zZnHTDv+X3K9Woo+v1u4v9Ucr7S+88hvPh Jrl1NvN3YkdBukfP/oFQ/wDCndb/AOfqw/7+P/8AEV7JRT/tCv3D/VDK+0vvPHP+FO63/wA/Vh/3 8f8A+Iqza/CfWoEKm5sSM/8APR//AIivWqKP7Qr9w/1Qyv8All955R/wqvWv+fmx/wC/j/8AxFO/ 4VZrP/PzY/8Afx//AIivVaKX16t3H/qllnaX3nk7fCnWW/5ebH/v4/8A8RU0fwv1mNAPtNmCPSR/ /ia9SopPHVmP/VLLF0l95wjeCdVe3CNLaB+p2u2D/wCO01fAuqf89rX/AL7b/wCJrvaKzWLqx2Y/ 9U8s/lf3nBr4J1ZWBEtmR3Bdv/iaq618OtT1Pyys1mHXqWdv/ia9GoprGVU73B8J5Y/sv7zyT/hU 2tf8/Nj/AN/H/wDiKX/hU+tf8/Nj/wB/H/8AiK9aorT6/W7kf6o5X/LL7zyQ/CfWv+fmx/7+P/8A EUf8Km1r/n5sf+/j/wDxFet0UfX63cP9Ucr7S+88l/4VPrX/AD82P/fx/wD4ipYvhXrMfS6syP7p d+D7fLXqtFH16sUuEssWyl955RN8KtaeRXS7s0YcgiR//iKfH8NfEMTbkvbFGxyVdxn/AMcr1Sih 4+s97fcJcJZYtlL7zyef4XeILpt0t9ZyHp80jn/2Sr1r8O9bgRUa5smQdfnfP4fLXpVFH1+t5B/q jlnaX3nnv/CAaqf+W9r/AN9t/wDE0n/Cv9U/572v/fbf/E16HRR9frdxf6o5X2f3nnf/AAr/AFX/ AJ72n/fbf/E0n/CvdV/572n/AH23/wATXotFP6/X7h/qjlfaX3nnY+H2qj/lvaf99t/8TRXolFH9 oV+4f6o5X/LL7wooorzT7QKKKKACiiigAooooA9H/Z/8baX4B+JVhq+uQWVxpFurTTLd2YuX3Ipe PyQfuyl1UK2QATk8Zp37QXjjSviF8SLzWdCt7O10m5RJ4o7azW3k3uoeXz8fflEhcFskHAI4xX0p +w98LPB/jn4V6vfeIPDWm6xeR61LCk95brI6xiCAhQT2yzH8TX0R/wAM8fDL/oRNC/8AAJP8K74U Zzpqz0PzzGZ9g8FmM5Spyc4rl6W739T8nredrW4imQKXjYOodQy5BzyDwR7Gvon47fGPwh4y+Fug 6D4fsNGttX00xwXslrpIhVgyeZIbN/8AlnEJi4YYBbII4zn7Y/4Z4+GX/QiaF/4BJ/hR/wAM8fDL /oRNC/8AAJP8KuOGnFNJ7nHX4owOIq06s6Urwd1qvxPyar6M+BHxi8I+Dfhfr+heIrDRbjVNSMlv ZSXOkiYKFQyRm8YD95F5wjCjBKkMTwBj7Z/4Z4+GX/QiaF/4BJ/hR/wzx8Mv+hE0L/wCT/CiOGnB 3TDF8UYLGU/ZVKUrXT0a6H5PXE7XVxLM4UPIxdtihVyTngDgD2Fe2/s2/BHwj8aprvTdY8UXOj68 JD9ksbeIMZogm5nyRgY571i/tUeH9M8K/HrxTpej2EGmabbm28q1tUCRpm1iY4A6ZYk/Umul/Yd/ 5OE0n/r0uv8A0Ua5IRSqcr11PsMbiJVMrliqEnB8vMtu17dTqtU/Z3+CWnaxeaLN8XpLHVrad7WV Lq3ULFKjFWViQBwQR94D3rzT41/s2eI/gzHBqUs0GueGrlgLfWbH/VkkZAdcnYT25IPY9q5n43f8 lo8ff9jBqH/pTJX0h+xlrD/FLwH42+FuvyNe6SbMTWYlyxtw5KsF9AH8t1HY5PetEo1JOFrM86pU xeXYeGNdZ1Iac0ZJbO2sWktr7M+dvgj4F0X4kfEbTtB8Qa2ugabcBy10WVSzBSVjVm+UFj3P88Vl fE3wzpvg3x9reiaRqqa3ptlcGKC+jIIlXAPUcEgkqSOMg16b+zv8HfAnxR1q58N+KPEWpaT4qa5e GysLGPcsyRxs8hLmNlBGxurDOOK871/wC0Hxf1HwRpMjTumuyaNaSXBG5yLgwoWIGMnjOBWTj7i0 PXhiYyxtSPO0oxXutWW/xJ9e3Y4+ivqvxJ8HfgL8L9cTwf4t8T+IpvEgSP7XfWaKsFszqGXK7GwM ENj5uDya4rxl8AfDPwn+J2n6Z4y8WeZ4P1CGae31LSUMlwqqPkEibGAJYgfLuBHPHSh0pImlnGHr WUYy1TcfdfvJfy9/zPKPFHgHxD4JtdLn13Sp9LTVITcWguMK8kYIG7bncvUfeAzWBX3h+1VoPwt1 Cx8Jt4q8S6tpl1Do7DSo7S3LrcJhdpkPltgk7fTrXjP7M/wF+H3xv0+ex1LxLqtn4shElw+m2cYC C2VkUSb2iK53OBjdn2q5UWp8kWceFzuE8F9bxEGkt7Rdt3t5aavoz51r1b9nf4V+Gvix4p1DTvE3 iVfDlvb2bTwneiNMwIBAZ/lwoySOpH0Jru/FXwX+DPhPwx4otJPiBeXvjjRreQfZY5I47aS6CsRC oMRL4I2thuvHByAz9mz4CfDr43aYbK+8T6ta+L4kluZ9NtIwI0t1dUDh2iKnJdeAxPPSlGm1NJ2f zNMVmdKeDqVYOcEtObld1fW9n08z591qyg03Wb+0trpL+2t7iSKK6j+7MqsQHHsQAfxqnWt4T8L6 j428SadoWkwfaNRv5lghj6DJ7k9gBkk9gDX0lrHwV+BfwnuBoHjvxnrF/wCJ9i/ahpEeIrQsMg4E bc4IOCScYO0ZxWcYOWvQ9DEY+lhJRpSvKbV7RV3bvZbI+V639T8A+IdF8K6d4kv9Kns9E1GQxWl1 NhROQM5VSdxGP4sY969h+Iv7OPhvwBc+H/Ev/CaQap8NtWvYbf7Za5a/iR0dy2wIVYARnnrkgbBX u/xU8PfCa6+Avw7tdd8U6xZeFYc/2VfW9sWmuPkP318s44z/AAitY0XrfoeXXzunF0XQi5Rm7P3X 0T0/xX6dj4Ioq1qsdpDql4lhK89iszrbyyDDPGGO0kYHJGOwr1T4BfAJ/i8+ratquqL4f8IaKnma hqbgEjALFEzxkKCSx4UY4OQKwjFydke7iMTSwtJ16ztFf1t3PIaK+ndN+HH7O/jrVofDPh/xb4i0 vWpnEFnqGoRK1vcynhQQUXqegOzJIA6gV5NrHwvg+G/xdHhTx/dTabpkE2Lm/sULloCpKSxjacg8 duOQeQat02tTko5lSrOUOWUZJXs4tNrul1+R6d4R+Bvw78H/AAl0Xxz8UtW1VDrjH7BpukgbtnJV j8pJOBuzkABgOTXjvxTs/BNn4mVPAN9qd/obW6uz6qgWVJiW3IMKuVA28465619kfGbw/wDCa8+D fwzt/EfinWNP8OQWuNIvLW2Ly3KeUgzIvlnadu09B1r4NvFhS8nW2dpLcSMI3YYLLngn3xWlaKha KSPJyWtPGueIqSne70atG12lbTdW1133PQPgr8CvEXxw16Sy0dY7WxtsNealcZ8q3U9PdmODhR+O BzXst58D/wBnfw3ef2NrXxU1KXWkYxySWSqbdXHBBKwSKuD2L1qeJtUk+Cv7FPhmz0U/ZdU8YSb7 y7jAVzHKrO/OOvliOP6E18gUPlppK12VS+s5rOpUVV06cW4xUbXdtG22n12R738X/wBk3WfBOmw+ IvCN2fHHhK4TzUvdOj8ySJME7nVNwKYB+deOOcV4JXdeEfjh448C+F7/AMOaJr0tpol8HE1m0MUq kOu19pdWKZHXaR69a6T4BfAJ/i8+ratquqL4f8IaKnmahqbgEjALFEzxkKCSx4UY4OQKhpTaUEd9 OrWwFGc8wqJxjtJLVrzVt+mm55DW94ETw/J4u0tfFT3Efh4y/wCmtaf60Jg/d4POcV7/AKb8OP2d /HWrQ+GfD/i3xFpetTOILPUNQiVre5lPCggovU9AdmSQB1Arwv4mfDnVvhT401Dw3rKKLu1b5ZY8 7Jozyki+xH5cg8ik4OPvbo1o46ljHKhaUJW2a5Xba6/rQ9U/af8AhD4N+HPh/wCH+s+DGv3sfElr Nebr+XcxjCW7xEDA2nEpyK8Cr6f/AGsv+SL/ALPv/Yvn/wBJrKqen/s9/D7xF+z7qnjzQ/EurX+r 6Vp6PfWjII4Ybzy0aSL5ogWUF+qkg+prSdPmm1H+tDzMBmCw+BpTxMnJylKN9/ttK7Pmyivav2a/ hP4F+L+sT6F4k8Q6jpWvzyY02zsY8i4VY3kkJYxsq4CdyM+9cN8SPB+n+B/iprfhtLmZ9M0/UGtf tEuDJ5YbBY4GM49BWPI+VS6HtRxtKWIlhVfmir7Pbuu5x1FfWut/srfC1/hzp3jnSPiJe23heS4P najqUH34VMiOsUXlo5lMiBQCOgY4PFO8O/s3/CT41eHdTi+GfijVl8R6dEGMerABJCful18sEKSC NyH5c8g8CtfYy2PL/t7Ccrm1LlTs3yu0Xt73Y+SKmsfIN5bi6LC28xfNKddmfmx74zX0z4b+EXwF 03Wk8KeIvHmpar4lmkFq93pieVYwzHjYjlGBwxxuJK8c45FeV/tCfBmb4HfEKTQftTX1jNAt3ZXL qFZ4mLLhgONwZWBx1wDgZxUSpyiuY66GZ0MTW9hFSTaurpq67q56d8Yfg38M7D4C2vxA8ByatLHc 6gtrG2oS8FQXV/k2g9Ur5mr7W8D+G/Dfif8AYn0CDxb4gPhvQbfVJrm4u0j3yPtnmAjjXnLMTxgH oeDXK6P8A/g58ZrK8074aeLdTtfFVrCZYrTWh8lwB3I2KeehKk7c5K1tOnzWcbao8PA5pHCRq08Q 5yUJyXM02kk7K7PnLwDoOn+KPGui6Rquppo2nXl0kM9/JjbChPLc8D0yeBnniuk+PPw90P4Y/ES5 0Lw9rq6/p8cMcn2jejtG7A5jYp8pIwDx2YVsfBv4Y+E/EPxAv/CXxB1jUPDWqLdJp1nBaRF2luzL 5ZiY+W4XnHJwPesP49fDux+FHxY13wrp1zcXdlYeR5c10VMjb4I5DnaAOrkdOgFY8toXse3HEKpj 1SjN6Rva3uvVaqXW17aHAUV9F+H/AAX+ztoenWH/AAkXjfW9b1K5hjkm/s+1aKG3LAHBHlscrnB+ Y9Dxniue/aM+Adh8JY9A1vw3q8mu+EteiMlndTbTIh2qwDMoAYMrAggDoRjjkdNpXHTzSjUrKg4y i5Xs5RaTt2ueK0UUVkeuFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRR RQAUUUUAFFFFAH0h+zbp/wAcbvwPfv8ADPULa00Iai4nSb7Nk3HlRbj+9UnGzy+nHH1r1j+xf2tv +gzYflY//G65r9jn9oDwH8KPhrquleKNbbTdQn1eS6jiFnPNmMwwqGzGjDqjDHXiveP+Gz/g9/0N jf8Agsu//jVelTUORXnb5n5bmdXHRxlRU8FGcb6N027/AD6nln9i/tbf9Bmw/Kx/+N0f2L+1t/0G bD8rH/43Xqf/AA2f8Hv+hsb/AMFl3/8AGqP+Gz/g9/0Njf8Agsu//jVa8tP/AJ+P7zzPbZj/ANC6 P/gpnln9i/tbf9Bmw/Kx/wDjdH9i/tbf9Bmw/Kx/+N16n/w2f8Hv+hsb/wAFl3/8ao/4bP8Ag9/0 Njf+Cy7/APjVHLT/AOfj+8PbZj/0Lo/+Cmfn78bofFtv8UNaj8dTR3HipfJ+2SReXtP7mPy8eWAv +r2dB+teh/sO/wDJwmk/9el1/wCijXIftKeMtH+IHxs8Sa/oF2b7Sbw25guDE8e7bbxI3yuAwwys OR2ra/Z9/aA0r4G/bLibwRbeItWkl3Qak12LeW3QptZFPlOcH6iuCLjGrdvS5+h4iFevlHs4U/fl BLlVo2bXna1uxxvxu/5LR4+/7GDUP/SmSvpT9k3Rz8E/hT4w+KviNTZ29zaiLToJV2vcKuSpXPXz HKKvrtJ6EGuUu/2uPA9xqs+rf8KN0F9Ylma5a8uLqOVjMzFjI2bYEtkk5znPNeWfGT9oLxX8bLuL +2Z47XSrdt1vpVmCkEZ5AYgklmwcbifXAGcVSlCm3NO7OOpQxuYUIYKpS9nDTmbabaXRJX3tuzov 2O55Lr9prwnNKxeWRr13Y9STZzkmuZ+JNxqdn+0R4tutFSZ9WtvE97cWv2eMyOJEundSFAOcFc/h W78APj3o/wAEWuLq58DWviTWDMZbXU5LoQTWqmMoyKfKc4IJ7jqaXx5+0VHrXxI0jxt4S8J2XgvW rJpppZI3S5+1TS53Syfu0ycM3XPXNTePs0r63OqVPFf2jOpGj7jhyptqzau9Ve9ne2x6jffG74X/ ABku4bD4weC7rw54mVEgfW7HehTjhnHDqMNwrLIBmvHP2ivgp/wo/wAcx6Vb3x1PSr22W8srl8bz GWKlXxxuBXqOCCDx0Ho91+0t8M/GV9b+IfGnwpj1LxfEF826tLxo4Ll1AAZ0yAeABhw+AMZNeR/G r4xar8bPGR13UoI7KOOFba0soSSlvECSFz3JLEk45z2AAFVJRlHV3f8AW5y5bh8TRxEVCnKnTs+a LkpRv05NW7b9lboezfty/wDNMv8AsB//ABFRf8E9f+S0a1/2L83/AKU21Ubj9pTwN468I+G7P4ie AbjxFreg24toLq1v2t0nUBRl9pBGdoyORnJGM4rO+Bv7T2h/BGwultPh3b6hqc002NUOoCKcW7sr CAt5DFgCg5zyRnAquaHtVO+hy/V8Z/ZM8AqLc1dbxs7tu61/Ox4l4oYt4m1dmJLG8mJJ6n5zX0Z/ wT1/5LRrX/Yvzf8ApTbV418YviBo3xK8VQ6tonhK18HW62ywy2VpKJFll3uzTEhE+YhwOn8I59PR fgP+0/o/wP0JYI/h7a6rrZ8xJNaW+FvPJE7BvLP7ljtBVf4uwrOm4xqXb0R62ZU8TicslRp0nzyV rXWnzvb7mRfsQ3FnB+0HpH2oqJXtblLYt/z0MR6e+3ePxrzT4xWuo2fxW8XxasrrqA1W5aXzOpJk Ygj2III9iKveOPida6x8QrXxT4Q0CDwGbQRNb2mnyK6xyoc+YCEUEk9ivbvXss37VngLxzDb3/xC +FtrrXiWCNYzf2siqs+BwWBwQM/wksB29KFyuPJfZkVFiqGKWNjRclOKTimrxabfezWutmfNd7oO p6bp9lfXen3VtZXyl7W5mhZY51BIJRiMNggjj0r6W+Pn/Jpfwb/H/wBFtXlfxt+Pmq/GafT7ZrC3 0Hw7pi7bDRrI/uoeMZJwNxxwMAADoBk57Hwp+0P4T1D4T6T4G+Ivg+48SWujSl7C6srswOF+bCtg g8BivBwRjIyMkjyrminuGKji6kcPiJ0vehK7imm7NNdbJvVX1Pn6vrXwSkmofsC+LoNFybyHUWkv 0hOHKCWFnJ9vKCk/7Kmvl/xVqGmar4k1G80bTG0bS55me309pzN5CHom8gE49/1613HwN+PetfA/ WLqaygi1TR75Ql9pNy2I5wM4IODtYZIzgggkEHjE05KMnfZ6HXmWHq4rDwlSj78ZRmovrbWze36X PPNJtry81Szt9PWR7+WZI7dYThzIWAQL75xivpT9v6e3f4paBDlX1OHRIhdunqZZCoPv1PTowplp +0l8LPB+oyeIPCPwjisvFLfNFNd3Za3t3xjciDIXH+wEJ9RXi7fEy51z4ox+M/FllF4nle7W5u7G chIrhRgCL7rBV2gKODgCq92MXFO9zmisRisXDFSpOCpxlZNq8m7aaNq2m7e57n+0t/ybV8D/APrx H/oiKvlmvprx7+174a8deBZfDUvwnsLeKGyltNMlbUFkGnM8ZRZIk+zjBX5SACPujkV8y0qzi5Xi 7muTU69HDuniKfK+aT3Tvdt9G+59gahpM/x6/Yv0EaIhvNf8HT7J7GEbpWjjVkwq9STE0bj12MBk 18fspViCMEcEGu3+Evxh8R/BnxH/AGt4fuVXzAEubOcFoLlB0VxkHjJwQQRnrya91uP2pvhT4kuP 7W8RfByzuNeclpZIzE8crf3mJUbs/wC0D+NU+Wok27M5accXlc6kKdL2lOTclZpNX1aadtL7M8k8 B/s+a946+GviTxstzbaTpGkIXSTUNyJd7QTII2APK4A6YLNtzkHHsnglJNQ/YF8XQaLk3kOotJfp CcOUEsLOT7eUFJ/2VNeWfGz9prXvjFY2+jRWVv4a8LWxBi0ewbKsR93zGwN23sAAo64yM1lfA349 618D9YuprKCLVNHvlCX2k3LYjnAzgg4O1hkjOCCCQQeMEZQjKy2ta4sRh8fi8P7SolzxnGcYX6R+ y5dW++1zzzSba8vNUs7fT1ke/lmSO3WE4cyFgEC++cYr6U/b+nt3+KWgQ5V9Th0SIXbp6mWQqD79 T06MKZaftJfCzwfqMniDwj8I4rLxS3zRTXd2Wt7d8Y3IgyFx/sBCfUV43F8UJ9X+KieNfF2nw+K5 JLnz7uwuCEinXbtEfKsFUDAHBwFFL3Yxcb3uapYnFYqGKlRcFTjKybV5N200bVtN29z2j9rL/ki/ 7Pv/AGL5/wDSayrT+AqNL+xr8W1RS7CaZiFGTgQREn6YB/Kue+KH7Wfh74leBf8AhHX+FtjYta2j Wml3bX6y/wBnKQo/dL5AxwijAI+6PSuM/Z//AGitQ+Btxqds2mQ69oGqKBd6bM+zLAEblbDAcEgg ggjHpWnND2l76NfoebHB4yWWKi6VpwnzJNrX3+bdNpb21Ln7Gf8Aycn4P/7fP/SOeuc/aO/5Lv45 /wCwrN/OvV9L/a+8LeCfEUF/4N+Emj6PHuJupfNUXMqFT8kbiP8AdDJGeGBAxgZyPKfjL8WNM+K3 xCt/E9r4Ut/D6eWgu7OO4Ewu5RI7tK7eWvLBgpyD90c9qiXKqfKnd3PQw8cXUzF4qpRcYuHLq4vV Nvoz2nxT/wAo9fB//YVk/wDSu6rN/wCCerH/AIXNrQzx/YExx/2821T6v+2Z4X1TwO3hQfCDT4dF RXNvZ/2irQwSNuPmLH9nxkM7N9Sa5P4A/tNaT8C9FkiTwDbaxrUjSB9ZF8LeZoWKHyj+5Y7QUB6/ hWnNDni+bY8t4XHSwGKoewalUlJpc0dpO/fp/wAMeMeJWK+JdVIOCLuUgj/fNfT3/BRL/konhf8A 7BTf+jnryu6+M3hS7+LyeL3+GmmnRfsxik8Nm4UwySEEGUv5ON2Tn7nbrXSfHr9qTSvjj4d+xy+A LbStXRkEOsNfC4mijDbjGv7lSAc+tZpxUJK+56VSni6mMwtb2L5YJ82sdOZJd9bW1t8jpdc/5R/+ H/8AsON/6OnrzH9lWz1C8/aA8G/2cshliuzLKyZ+WEI3mEnsCuR+OO9dP8P/ANqbT/CPwl0/wFqv gGy8UadBPJLO19d4WVWkZ8KnlHYwLDDZPTpzxoXX7V2h+ENIvrT4YfD2x8GX97F5UuryTefcICei ZXt1GWIz/DxVXg3GXNtY5VSxtOnicNGhf2kptSvG1pdXrfztYr+M7201D9ua2lsmV4B4t0+MlCCP MWWFZOn+2rVnftZaTca9+1Z4h0y0Cm6vZ9PtogxwC72tuq5/EiuW+Cnxe0v4W+JrzW9a8JW/jK8k aOa2kvLgRyW06vv81XMbndnHPB4zW/8AG79orT/ixqWnaxpfgq28KeI7W7S7k1iK6W4nnKKFjDHy kPy7Vxkn7o4qXKMoO71budNPD4qhjKahTvCFPk5rrfR3te/S2x23jzwP8Ff2f7618M+JtK1zxr4l Fuk97cW9ybaCMsMgKAw+uOeCMnsNf9qa50i8/Zs+FU2g2c2n6PJKzWtrcyeZJGnlnCs3c1g69+0/ 8PfiHDaat44+FketeLbWERC5t75oIJyOm8DnHswfHas34jftZ6f8SPhf/wAIle/DvT7WeGIJZXtv dAR2RBGDFD5Xy/KNuA/TvWjlC0kmtdtDy6WGx8quHqVac3KErybkrapq8VfbXsn01PnaiiiuI+9C iiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACivijyVN0xKMw3k7Qpx1rqPD9wv8A b+lKsBjTzlAyp78c17f9mu6XN+H/AAT8u/14Vm/q/wD5N/8Aan1fRVr4P+A9KsLKTXdd+xQTBSLO TUHG3apO5vLHzPjoFGAcnOelS/HRYr7T1sZIZL/VHiXzTcxhf7NgJHlqkK/LC74H3vmA4wM1x1ML 7NtOWx2w4udRJrD7/wB7/wC1KFFeCX3hhI2cNESelZv9hpvwqYFKOGjLaX4f8EJcXSjvh/8Ayb/7 U+jaK8Ds9ETjjnPHFX20WPyyCM1f1T+9+Av9b3/0D/8Ak3/2p7bRXgD+Gy0jfLiuzsIYP+Fdv4Zt LKaO7vL8Xl/esy7JUUYjjUdeOM54NN4SMVdz/D/gkx4vlJ2+r/8Ak3/2p6ZRXn3hv4SvqTO7KURc YBHb/wCvWhqnwhEPIH6Vy8lLm5ef8Dp/1oqWv9X/APJv/tTsaK87h+GYBJ28D2q7a/DeN+i/Mc9F olCnH7f4f8EUeKakv+Yf/wAm/wDtTt6K8+1D4drEBtXr7Vz2oeDUtQS+cnpzVQpQqbS/AUuKpx/5 h/8Ayb/7U9iorwSTQYo/7xPtTl0mNsYRj7Gun6mv5vw/4Jh/rg/+gf8A8m/+1PeaK8PXR41QERYH 1q/cXl3JoNvozyg6ZbTNcRW+ANsjfebOMms/qv8Ae/Av/W5/8+P/ACb/AO1PYaK+fdQjba6xrn3W sCTQL253eVAzE9gDWiwTerkYy4z5dsP/AOTf/an1DRXyfY/D3xFH5jJYTFWyS201XXRdX0wzxzRS KHGOV6YNZPC62UhrjK++H/8AJv8A7U+uKK+ZLXxBqGFQxjAG3n6Yq5p9rcSCPCscHjiolh5I1XF8 X/y4/wDJv/tT6Por5h8QeEbrVJi8lux2LtyR0Ga6DTNHePSbRGXG1Npz7VosI+VO5P8Argrtew/8 m/8AtT36ivnq/wBL2LkAVP4Pmj0fxFZzTDNtI3kTr6xv8p/oacsHKMHJO7XQqHF6lNRlQsn15v8A 7U9+or511bTbj4Y+Pt8X3tPuQy8cSQE5/Iqf0r6807SYdSsYLq2TdBOiyI3qCM1tTwKqwU4z0fl/ wTKfGMqc3CWG1X97/wC1ONorv18MsORGKmXwuduCMH2zWv8AZn9/8P8Agmf+uv8A1D/+Tf8A2p51 RXpA8Kj+6f8Avmnf8Imo48v9Kf8AZn9/8P8Agk/67f8AUP8A+Tf/AGp5rRXpDeFsHG3J9qT/AIRf nG360/7Lf8/4f8EX+u3/AFD/APk//wBqecUV33/CLSQ3nKZjuDw3YSAf+zD9VqUeFmxxHgg+lT/Z v9/8P+CX/rr/ANQ//k//ANqeeUV6J/wi7bSdo9uKjbwudwXHLdsUf2Z/f/D/AIIv9df+of8A8m/+ 1PP6K77/AIRcrkFRke1Nk8MsvIUfiKP7Nf8AP+H/AAQ/11/6h/8Ayb/7U4Oiu2bw7ICQV5+lVL/w nHqVlcWN3EXtriMxyADnae/1HX8KX9mv+f8AD/gh/rr/ANQ//k3/ANqcpRXidzYnwP4s1Pw1rq7d LvCILkjO1CeYrhD+Rz9fSuO1jS7nw7q1zpt4MT27Y3Do6n7rj2I5rBYJ87puWu681/wH+nc2lxla mqiw9+j97Z/+A9V+vY+naK+bdKsRrGnXNla6VqOpawn72KS1l3RRQj726LH6g96wRJ+VbrLW1fm/ D/gnO+N7f8w//k3/ANqfWFFfJrTbecVTutY/s0x3K5YwurlQcHAPb3pvLba8/wCH/BBcb3/5h/8A yb/7U+vqK8v+GfjHTF3gzoqmUOBnj5hkEexr3bR/E+i6imxbuAuo5UsM49ap5Ykr8/4f8EqPGjlf /Ztv7/8A9qczRXpNvfadKgU3Ubjtls1YE2nqOLiEf8CrP+z/AO/+H/BNP9cn/wBA/wD5N/8Aanl1 FemfbtKhkAe5hUt0O4V88/HtY7/xRCqsnyrnKHrxwal4C32/w/4Jf+uD/wCgf/yb/wC1O6oryXQN WtrXwnqfhvXLWfUNJlzdWElsV87T7vtIm7jY3R179a85vLry2KuBuHUr0qY4Hm2l+H/BInxnyb4f /wAm/wDtT6gor5YF8jZDDBqG4ug0ThTz2zWn9mv+b8P+CY/67r/oH/8AJv8A7U+raK+RbW+juo2v LNmhntiDcQg/NEQeHX1Q/oevFe3/AAn8cWjNbSyXqwzRtu+Xgo395P6iqjlvMnaevp/wRvjblaTw 2n+L/wC1PS6K77QJNPvLhrk38MssxzIzjIf611reG7Sa3EsF1D5a8lCwyv09q5pYPkdnI3XGPNth /wDyb/7U8Uor1+Tw/bYz9ph+ma5jxEsuhf6Za3SrLGDhlbpx3pfU7p8stfP+mbR4tv8AFQsv8X/2 pw9FeU+MJNA8bapfNdXdv4e8VIGla8nO2w1X2cgfuZ/9rGx++DXmvkFv4cGt1l7a1l+Byy40Sdlh /wDyb/7U+oKK+XGtd3aqt1YERtgdqby5r7X4f8ElcbXf+7/+Tf8A2p9W0V8labr0FrbstwfMtMmK VTyVz39mHr3Fex/Df4nx/wDCO6p4eulivNKuRh4LlyWgfPy3ER9emR/9euOthalNJwXNrr007/1Y 9OhxXSrJqVPlfS8t/nb7u56lRXkUem6ZrGoSWc+yC9t3HlXS4KzpkYVsd+eG/OitI4RS+1+H/BOW XFzW2Hv/ANvf/ant2i/COLxFqX2aw0+zuJTkkRgYUZ6sew9zXsnhX9kXUoWtL2w8JLq12SGivr/F vYQejgH55MeuMHtXsn7Hfw98HfCDwv8AY9a1a11vxGiK93dIrSq0pySBwchff1r2v4g/GrTdN0m4 XT0WViMG5uiY4VHc+p+gFe7jcyqxjKOHj73Rd3+CS8z8to4PX3ldfgfCnjbwnpnw10u91PUrZdY8 RLKYc7fLgibPDF+pUHlYo+TjLkDivCvFOrzaXFaabO2yS5KzS7xh2DEndIvUse2frgV3HxZ+M0vj v4lNJLK8qWMkgSe4QCNcjG5Iu7em76nNeLah4gTxz4suH02LNhpqt5tw7Ftz5UElv4nP/wBavLrO dRXqWv1tsvTbr1sj06KjCyiP1TyiABhTGCDls559O34elYyxw7iWYDPWukvGjZmDBQvXoKzm8tgC FUf8BpUY6GlUghaErwe+MelXY0j7ZOPY1LbWpk5H1zitqx0sOV3EjufpW9SUYoypxcijpOipeTMD JHCVG798SN3P3V4OT/hXpOheDbHbOGmWWRPkj8tCyyMTgEccjvVLQ9GWQsQ6qq9WyOmK9v8AAnhj +x/LaWaRJZ0SSQTdF7qvqOOT9a8HF4nlWh7GHoXeqK/hrwLb2NssKRbsDLMScZxyTxRq3hWJMgj5 iew7ete46PDC0axLcxsTzz0H19qbe6ajzFBe2/y87d3AP5V8r9clz3Z7HsY2seAr8PC6bjbx47ck fj0q4Ph7GsOAYyWyw2jJ64OfQV67ffZfMKi9iwuR3A/lWLLqEMcpiSQSKBjcinB9e1W8VUmEaMUe U6p4BSG3yTlwdoXZxjHUH1z2/HNcN4g8Hx20bDZnJwMjGfevfNWvLe7UDcwUcnIJ7cAV514p8tif kPQ43ZzXpYWtNtXOWvSjY8L1Dw4kDMQo4PTFY0+mq/IyMc/KK77VFctJkbDkjGBXN3Csqn5s8emK +ppybWp4M4pM5ia3KDp+f+FR38kd0qRRWMcBULmRZHcsQOSQeOTzx0xxWrMHmmVASzuwVVXqWJwA Pck4q1rXhrVvCutSabrOnXGk6jGiu9peR7ZFVhlSRnuK6I9znlsZvhfwkt/JtcBjx1HNfQHw0+D9 hdSRtJCrDg+1eW+BW/evkHLEHgfrX0f8O79reaP5yynAwV/zzXHiqkknYyhTTO9s/hJpSWHlfZo9 pGQCo9OTXivxM+CelrJK6QKp6YxX0xb6yU08jd1XByM+4+hFeW+ONUecMwDbTzwB+ZFePSqy5tDX 2fc+UZPhDBFdFVhU/N6V3vgz4K200kJeAEdOV710dxGGnJwBu5GR/Su08K6gbeRdjqzKc4x2+ld1 StPl0CMFcoX/AOz/AGElixWBFcjH3TgmvEfGXwu/sUSKicKx4xX2iuqGTS93lM6D0Ocn0rxn4ixJ eNMREMdRzmscPiJ81mNx6nx/rWjm3R8rtxXMNZltykHHQ1694wsQZGVYxjPOFrz26s3jlYFSPwr6 SnNSRzSi0a/j7Rz4s+H+g+JwFa4t1Ol35zyWX/VsfqP5169+ynr0mveELrRLk77nS5MK7HLGM8rn 2x/KuC+E8Meuf234Pu2At9ctSYCT9y5jGUI9yP5VQ+AOvXHw7+MEKXymG2vlbT7kHgLKCSg/76BX 8axwcvYyqYd/Z1X+GWq+53XyR04yPtFTxK+1o/8AEtPxVn82fX0eibWPPXmrcej/ACnjPqDjNbSJ HIFbG0sAdpPrUixxg4JUnpjivZiebJIyV0lVUcY/Dg07+yVzgLkEc4FdDFCjKCVX8GFOazQ85B56 bqswtqcy2jJtxjI9xUbaKrADGcdPUV1nklcHCnns1DQocEkKPqKqwjj7rw/HeQukhaPdxuHVSOQR 9CM1Ba2by2+ZIwsyExzKpyAw7jHYjBHsa7V4IiuQwZc45NULu1jtbqK5Q7Y5SsM208Kf4HP0J2k+ jCpaLXY57+zhk8YyeMdKc2lHkLFyeRkHH41vvZIGLszFzwV39Pwpdqqo2sCR/CxIz60huJz/APZK j7q5x1zTW0heCVwScCt/91J827vzu4x+GKPtNs67llVsnA4PPpjihhaxzkmgo3VD+dRN4fQ9Uxz6 11Y8ny8l19+aaVi4y65qSrHzv+0Z8GX8YeGV1mwTfqGlRN50KJlprfqce6HJx6E+lfN1voc3jrwr NZYL+JfD8Rkg7td2g+9H7snUe1foynkxuGVoyc9D0PsfUV8h/HT4f3nwd+IGmeKNBj8vS7mcyWpj HyI45e3b8M49VIPauPE0pTjzU/iWq9f8nszrw8oRlap8L0fp3Xmt0fNVi4guIZXe4S2LATG1kMch j/iAPY49eKn1jTrWPUpW0621C30yQ7rYakgExX1JAw31Feg/FLwraW93beI9Fjx4b14GaNMf8e0/ WSFvQg5I/Gsea8OteF0l1jxZLNfaUy2mnaHeRSP/AKOcZMUv3UA/uHnjitMPWjWpqcev4Pqn5o5s Rh5UKjpy6dejXRrya1OGm01iOhNZ19orzREbSQ1dstvu7UhtQHYbeDXTa5zcqPIpLDVtKmcW5mVC MBoz1APFNj1XXbW6W4S5uo514DKxBr1mbT4+4z9BVSTTIG/hFcsqPmbx2OEh+IHi2HhdRuvxqwvx N8YdBqNzn6V1y6ZAv8AqRdLg/uDNR7J9x81upxNx488WXke2TULhgpziun8PeJNS1WzjfUZXkmiG xWfrj3rT/smE8hACKcNNWEhlHynrWioidSW1x02sT+XsXt0rNj0u61cyvBHv8td75YDaPxPNbK2S 7eRxUTWSRt5gXeB95f6/WqUeV6EN825zzafIw4JPpxVSawmbI3bTXaLboy7lwy+1EmnpIuQAGHSt TLlR5fJo99a3v2u2fy5lOcr/AJ5B9KhtBrGk3Bkt8jJ+6Pu16edPik4YYaqlxpCrnaMHrispU9bo 0T0szM0b4t+MNHjCJCko/wBoH/Guntf2l/GljFtfToZE+rZrnm09lztH4Uq2TMcY/OsnTvuzRScd jp1/as8TFSraTHu7fvGpsH7Suu6hN9nu9KjVX4zvY1zo0lGb5oxn6VJ/YsZA+TPPFT7HW5r7eXct ahfDVpmuPL8tZOdo7VVaQwL8x3ejVajhMMezGVHQ1FNZtICCMqe1b8tjnbuFvMs3ysCG96ddRbYG PbFMvp7+48hbm7mu4oE8uEStu8tf7o9BR53mwtG/foaog80hhmvdTuobcks+flzw3tW9oOh3sBgu nLRqThGDcAjqPY+1R/ZX0PWDP5bMjHO4DNdJb+JlhtZY2hWSKZcsrD+L1Ho3vXlV6kqbsjrgrnVe H9KnmuY5vPb5GBOwcqM9fpRXDaf40v8ASr6B4pZAyuMEDqM9KK5PaS6I31R7J8Pf2xNR8IxxaTD5 v2ZWIluppS80hz1OeAPpXoHiP9saPVdJZWmAKKTulbOPw9a+L30cPcSblcjeeg96bqWm+RCFhhc8 ZLMMmtuaLlpudPPVjBpnrXi7WtS1DwxqGtxStZRXLoFAGJZAwPzD+6Dzz19KzPg34iuW0/8AswHb axszNt43FiDyfwrO0+8vtY0qGK4Riqxog3DA+UY4H866nwrpi6cvyJsHU7VxzWns5STMVJKSZ2TS yTZAJIJ5qzb229gev1qtbbtwPIzx0rUtEc465rVR5Il35maWn2u5lABx9a93/Z78C6fqut6j4k8Q 2yz+FvC9sb+9EyZjlkwfLiPY56kH/Z9a8Y0to4VMszYjX+E4BY/4V02l+LJbLTJNNj1KaPTrlxJc WqSFYZWHQumcMRgdfSuaVKpU95I6FOENGz0Kzmg1fVLrUmtILJr+dpFt4YQiRAnIRFHHAwOOOCa9 d8M2cQjiY/M2dzsTxmvnrSPGNtHfo5mXKAKmQPlXHOK9a8F+Po7y4LwMjiLaiALnLscIuPXqfwrw sRlmIqadPyS3fyR69HGUtkezW8kXlkqFQBemevpx6fWqF9LCmdy7mx95v15rF8TfEK003UbLw9aS C5vIFRZFRcs9w+AE6Z4yOKT4neJ9P0rxBbaHaNEz6barBPcRkZlm+87Ej72CcA9cCvl5YKrTSlJb nqRrRk2o9B15qCKuGQPjryM4xXNyajH9ozvTHOVxn/PFYWoa4VG9pSxHT1OaxLXXEXzZCwKhCBuX dyf5Y7e9aQoOxTqI6681KMxs+VOV+VVIFec+JL9XVmLRsc/e3fpVi/1QrAdx+ZhnH1/rXD69qmWK K+5cYJxj869nC0LM8+vU0MbWLjBABUsx7VzV5cbRy4/Kr19N5k+NzcVgXkh5y2fWvpqceh4VSRq+ Eo7W78ZaBFeXMVrZNqNuZp5m2xxoJFZmZuwwK7n49a1a+Mvjd4n1HTbuG+09pIre2urdg8ciJGoy p7jOea8nRgckgsPSt3w7D+8BOEXqflrpfuxscUpXZ0PgLTpHklU4UgjGDxXvXg/SpLeSJ/PDDdwM 8j6j37fSvJPAtqkWoRsJU2lflxksOT29K9o0W+WGZ1CjbFH5s0hBwF7AnsTggV4+JcpOyNaZ6N0s 9pkdDj5eRywPQ1514wiKq7jcdp2gjPArds9W+2+Add1h8iS3msILbG792Z3c+uPuqB3PeuW1PUEv IPFAeVGWxizFkgHf5oTI+b68DNY0cBiLvTZ/5f5lyq0+5x13HKxJVdvOSScflV7SRPFPEWdirj5T uHOD19vxqlJCF0WKbzMySXBQN3wFBPf1NaGn2UlvpMeouGeMRzznAP3Y2VP5tXbUwdeK1XkZxqQk 7JnaQX11HZtumKk8j5ycj2HYiuI8U30s2/zHGen+fWumg12DUFktUXy5YFUNtYnJ/vEdia5fxMgK ODk46gjOPQ151JOM7SWptPVaHkHiaEuzkHocdOtcPqCL1H1r0jXrf962R19a4bVbbCscEV7dPTVG HNdcrMfTL+fR9UtL+A4ntZUnRl/2TnH4jI/Guk+OOjL/AMJQur6YwjtNYhj1GF16LJxn6Ybafxrm fu/w5Oa7uGL/AIS74S3SLzf+G5fOUd2tm649hz+VaVLU6tOv/wBuv0e342+9l0v3lGpQ/wC3l6rf 8L/cj6f+E/jCPx14B0vVAQsrQqsikjhxww+oIP6V1WACMKM59vzr5q/ZN8TR29/rvhmWaNQ6HVLU l/lIUATRr2z91sfWvpVoNwDBox+PNenGT27HnxtJDo2VP4M/7IIqzG6cfKw/EGqix7euDT1z2A/O t1JicUW1VcH/ADik+UHnNVLmYwKu6JpEJAzGNxBzgcdas/ZdxJ+0RjHbmr1M9BnnReZyzIfUrj9a e22SNo2PmI4KlQRyD1FRSIF4JTHZiajSN0bD7XH4UwFgkKq8Um5p4SFZjj5x/C/4jr7g0kWI/l8w FegDDp+NNvICirdD/lkCJVTq0WcnHuv3vzptxHMm3yys+7G3kBSPXP0pi9SVtvYBhnPymkOzglcD PrTUWXkEKPwpGZ1zmEMP96gYkiRFeqj8ajWOJE3DBI68k5p6yO3Bhb8qilcr/Bj6ikMaqxSNgjjP UVm+LPCdh468M6hoGoFltbxMCQcmGQcpIv8Aun8wSK0N/wBAKjtdStrqSQQ3CyvGcOFONvsc1O5R 8cW+iv4R1bWfAHi2NoNMvZhBJL1WyvBjy5kboVbKnPoR71wNqNW+F/jae1n0/SbrUI82bxazbLPa OshAWXDdBjBD/wAPPpX1z+0P4Bg8VeGG1pCsctlEI9QlWFppXtgflZVX7xRjz/sk+lfPmsaNJ8QN Dn0uUvL4x8Ow5heWMxyahZ4yUZSfvr2/D1ryKn+x1fbfYl8Xk+kv0l8n0Z6cF9cpKl9uPw+a3cf1 j811R514k8M3/grXJ9H1T7KL2ILITY3SXUDK3KlJUJVh+ORjms5+ehrU+z6PeeDbRNH8M6vFrVi7 SapqsMpmsZIjnbmILmBh3JODg1jqRkfN8rDivWTPFY/7y/SoZBt/Cn/dYg9OtI65z6Uw5irJgD3o ifHv6UsmOo696r7tvUcVOwXNCOQHPIPrUvDLgj5TWdHNnvVqOQtjntVE3JUYI2w8Dt7VKyj05qv9 7g9akjk5Ct1oaGmNhlWzukLxq8e4MI3JCvg8qxHIB9RyK9Q8VeA9H13wg/jjwBHcnR7QKmveH7mX z7vRJD/y03dZbZuofqO/t5fMNylWAK9+9avgnxtrnw/8QLqmh6g9hqCxNCJdquksTDDRSIwKup/u sDUrTQCgcSqGByeoIpvEgCsPmqSWczXEsuyOPzHLlIUCICTkhVHCj0A6U1l8zBz83b3qgImhXnIw e9V3jCt04q2rFiQx596Y8eW6kUmhcxXEoXgqGH61YSRG6VVkTbnHWofMZWyMg1OxVzUKK3UYFRNH 5bcLlaqpeHjd+dWFm3e9O47MR41boMfSqNxaFQXRdwHWPP8AKr+Ocqce1N+96Z9KVidTo9a+FLN4 J/4TLwzqCeLPDUG1NU8uExXmjyn+G6gySEP8MykofauOtbOxnwrFY89+orpPBvi7W/h74kh1/wAN 6g2m6rEpjZtoeK4jP3opoz8skbDgq1HxC1Tw74q1VNS0Dwz/AMIlJKm6+02C482zE38T2wI3RoTk +WSQOxrkqQTeqN4vTQyY/C8Ms8ZXay7hzjjrRVXTNXn0+4iU/Mm8cH60Vz+x8jVVF1Faxh85yFH3 j/OrC2EUmMquPpStGfOfPA3Hp9asQxnqV/CuzlS2Ju3oT21mi4AGB71rW0SpwuBVO3hPcVfijZcF RkUnZG0UaVoqrhmwwH8Of1q617DpthNeXT+XbQoZJGB7D09z0H1rLkne2i44kbkD29ao31xJI3l3 S77azxdXEZ6SSf8ALKL8+T+FYxj7SST2OipJ0oOSKWreNLpZESUeVOy+a8P/ADxU8qn1Axn3rOfx xeFWcMQvtWNcLcXUk9xcf66eQu7e5PSoLuNlAjHQdf8ACvT9q1pFHj+z6yepqP4+vWnVFkccZJ9q 2NH+MGv+H545tO1Ge0dZRKvl44cDAbkHtXF2uns0LTPkM5xGM9vWnLZ77pcvwvQAfrT9rLaxnGKT vc9Z8FfHzxF4V8fab4n+1C61CC6+1lrpd6yOQQSw+hOCOhwRXonhX4kXOqR32o3cjSTzzNJgHJbJ JI9+wr5mmWW4kYIpwOF4PGOlew/AfXdM0/4geHr3xBBJceH9Kdby9toxzNt5C8+r7PqARXHicKsR TbcdbHdhsXKjNQUvdvc+nviro6+CbjQ7LzXk1SXTY59RhLBkgmbnah64wfunoV964f8Ath/s6qGw xOck4Ofb8K5vxp8Sbvx38S9V1C4nE8t1MWDYwAnVR/3zipY9UeaYBiXEK7B04H/1vzr454Z0vdlu fVxr+0V0zX1C9baPmLKOuO1cneXG+Zurdc54q/eaixt2bOCxzz19q5y8vD5ZYEjjJINd1GmctWZX uro5J6isaZiVOAWyeakuLluSTnPv2qq0m5gc549entXpU4OLPMqSTRZtUMuc4QDnJBNdHpMbQ5c5 ZRyOMfn7Vh2pHUkjb75resyklu+WAYjjPQe9OZy7nofhn7OklxNGissYGGCkHgZx/Oo/2gPFE/w9 0K78O298W1e8aDUNUWNSqx2qqBbwknuZpHbHpH6Yqn4UmNi1gvl+cZZxI0ZO3zFU72BPb5VNeL/H T4hT+Pda1vXZkEU+varJOsMSnbHawDy4UHtuZz70YKjzYjmeyMcTU5KLtu9DGvvjJrbMyfbJNucl TIdpb1x61Z8N+NNU8R+JLOwmupVhZWaRo3AYKFySCe/SvL1jad+CQVGTuBFaXhtr+0ujdWF5JZz/ ADQ+ZHGWO0jLV9PKs1rc8HlbXmddH8TNUjlumjunMaSMkbM3JUE4/GteL4ia8sdqZbt/IuG2H58D GfT0rzjTrJJoZn3NIVlKrkHBweTXVeZBr1vpOmhN+128xQD/AJ/Go9pUlKKT3N1yRhJvdH0f8IfF j65ax3ru/nxzeRKF69OD+lega9cJKu5WmG8ZUZ4r5k+EvipfC+pXkLMTAy5Utx8yEpkn6MK9006/ l1LTYmkkRZUXBUnPI6ivl8yw/JX511Pcwdb2lFX3MXWbddvOd3Q85ri9QtRuZcHr3PSuy1Pd5Un7 xRg8Lknr3H0rkNQDLnLKO+c9ailcqT1OTuLcLIeCD9a6P4V+II/D/jW2juhnTdRVtPuVY8bX4Un6 Nj865++B8xsuM1lzRnfw2D2IPIPrXVUpqtTlTls1YdGq6NSNSO6dzcnurv4LfFGK6jj3yaHfCUBh /rYM8jHoYyR9RX3dY3lprWn29/aSpNbXMSTwlX3ZRxlTn6GvjH4qKnjLwT4b8Zou+4Cf2bqIB6SL wpP45/76Fesfsd+MG1Lwbf8Ah2dxJJpE+I1dsssEmSmP9kEMtGDqyrU4yn8S0l6rT+vUvF044eu1 D4XqvR7f5fI9/jjXvuzU6xp0Gc/WoWVFOMEfUkUqxpuIAb869JepzMn+73oWQN2b06UxY+4JH403 ymfOXOPpWit3M3qTYP8AdP0IpkpCqCVOPYVHHAI87JCBnJqRo3K4DknuwbGKtWId0MW4CtjAK9Tk HFRWnlxs1qhyIxuiz1MRPT/gJ4+mKmV5VTcrEjoORjNUtTtS9vHdeWrz2zGUADqpHzqPqOfqop2X cRobGbGATnjCjmneXJ0Ksp6dKx73TLbU7X/SUhkSQAllYgbTyCDwec/rWReeHUt2KwW1s+1PkMk0 hPH3RgHpn+VNX7hodW0JkYfeZ8etI0Dxr8yMDjJyKwLUSSwk3VrbgZBXy1Z8AgcFic8HPOMVlR+A fKvvtFrd28AZ2L7TJIQW6g5bG3vim0JPuddK21trnax6LuAJz7VGvmSE+aBgf3TnJ75rA8K/D+Lw vcTXMuovqd1JwZbiNQcdl79OcY7GujaBBIdyA+mM1nys0uhmwFSJIo5EYFXRlBRgRgqR3BBIIr4u +LngG++CPxCtr7QwE0maRr3S5AeEAP7y2b/dzj3Ug9q+0yoQ4yQT2ArnPiB4F0/4ieF7zRL7bE8o 8y1u2Xm2nH3H+nZvVSa5qqUlyyV0zanJxalF2aPj3WpNT0rVIPEngnxDJ4X0Pxhiw1OVJCkFvI5w 8VwAD+7JJPTjn1rzbxP4Zk8F+I7zQ5b2w1FrTaFvNLuBPazKQCGjcdR2x1BBr0jS4z4P1zVfCPii DydK1BzYajbsPltrgcLKvt059CprkPiBovh/wfptnoEWialZeLrCY/btU+0iSw1G3OfLkjixmJiM ZxxkMK4MLUdJvDTd7fC+8f8ANbP5PqduLpqrH61BWv8AEu0v8nuvmuhywJbp1o655pA3ocH0pMjP P1r1keMxki7hx+Rqo8fH1q/9eQaiaMMPShiKCqyt6j2qxHIVwe2KSSMZx19KbGV6Hp71GxRbVj/k ZqRl3KD0YVDHIF4PSplmVepq7gkOEm5cdCOoqOSPcv0PHrmo5pAjbwM4qVZFkX1qWPUkSRtpU9T7 dad5m3npVZm+XIOCKWOYygjGCOuP51Fx2LDFJuMneOlNSQN8jHBz61GshHWnt+8XsD61akJxEkVS fT0qtJH2qdZM/K2CfeiTOMHH1psnUz5flbuPakWQrjBp9yrZNVOeOKzNDRhuMtyM+1WGiL8r1xWO CVOav2twSAM7hVpkSJtoHB4Oe1V7rH94j6VZbDrgdf1qtPllIP50nESZRDA3EYcgHeMN680VC6Ms yDqNw/nRWVi+Zm9IQJnyf4j/ADq1DIM8H9KzWl3TSZH8Z4/GrEUnXJqjaJu27A4/wrbsYvMHCZrm LW42YwTXSaHM0kirwQTzXHWlyq6PVwsOeVjc0fwfdarfI8aGZy3CgZwe1dXrvwrl0O0lNzAyR7hI 8rqcOzDgA9+K+gP2RfhKPHPiKFjH+5T5pXx9xe5/pX6K3fgLw7qOkwabe6NZXlnCgRIp4FcAAY7j rXzeDzOvWxVSnQhdQsm27K71stHrbV9k13PbzKlhcFTp06t3KWtl0XS/r20Pwr1jw7HAxym09l9K 5240uDzPmXgHn3r6z/br+HPhHwD8TrXR/BhFpd/YZ9Q1e3BbyYecwhckhcjK7R1618Vf8JFLfTKk bbS3qOg7k/SvtsLjIVqak1Y+QxOGcZXTunqb1xZrMyvs2RY2p6e9Ng0uFMHgGsK615ndfLc+So2p 2/H6mtXw1I+sajFb+btBDM7cYRFGWYn0AFd3t6UdjzlQnI17XTbdQXaPCr/ERgV2XhTwDqn9mT3c uj3qabzc3F0bZxEEByoLYx/9civ0c/Yt/ZQ8O6D8LdD8U+KNCt73xJqbjUY/t8Qka1gK4hjAbgEg hz7sB2rS/by8aaX4R+GsmmKkMdxewsJlX5SLZCGK4H95gi/ia8PEZpOMlGnBNNpavddWl5K787Hd DCQjLlb1X4M/LDwlNJFrd7JPIBJuY8cYyen4cCu9hvjHBtZ/mbnnpXmnhbUjN4gnONpwWbHbdXZy XxaPOTk8Y4xXmVYqU7nu0XaFizf6kzuF3Z/z1rFvLrd8o47E0k1ztySzNj1/nWdJNlskkbeetb04 JGNWRJNJu4zwPWo4/uhh1FRff4Y9aftPPHtXScEme0eG/htoc/7NGteO72G4bX01QWNiyXJWFV3o p3R4wx5fk1wkMweLYuABjj8cV2Wo/FDQz+zXovgCya8/tyPUvt18Xg2wAb3fCvn5jynb1rzqHUEh I/esMfhWdSN3oZxfc9R8L3EX9m+J7lS0k0ejyafZqh3P51y6whlHUkIZTx615h4l8O2/2qGCVFtx bx+WscilCgB6EHocnpXuX7GOhp42/aO8J2Eh3QWSy6rIuMg+WBtz7Z2/nX2l+254J8KX3wZupNQ0 u3hmhma6iuIIkSQOeGy3X5gefoPSuajmDwlaUFBOOl3fW+mlred9+pvWwsasYKT1abX4/wCR+Ssm mWMLuB5bbuh3U6xhtbONVRLchSTluTz/APqrzHXtflt7mcwuzRK7BM9cZ4qlpet3WpW93LucfZ9v yjuWOAP0Jr6r6xCUdUeF7CSejPV7WxtLdQmYtgYttGOp71d02ztoJxOkkcbR/MGB5z2rx3+2Lr7d LbLucxtsLDPWvbf2aPAsXxI+JmnaNqhn+xkebKkfVucKMn3rKpi6dOLnbY3hhZVJKF9zoPD/AIaj vyEitjcvKysyxRluHlUEnjge5r0SFmtru+hiXKrcSAM3cBj/AIV+pFh4F8OfD/4ai10/SbOC20zS ZEU+SoJXbuYsfUsu4+9flHoupPdWst0HP7x3wF56se9fL1sbPGTcZRSta2t9++h61OhClTbpt72G 6pI/zEAYPT+tcjqUkzBwpUr710mpXTlWVXOfRv8AGucvpG2k9H9eK0pmUjm73zjJjgZ61lTrIFOS AAevJNbV383Octj17VRmJx8xDD612Ig7/wCF9u+t/C/x9o7lXVY1uYgxA8ttpOQe33BXG/CHxhef D74n6ReRzotrqDfYLlQCVKsflJA64fGPqa7v4NYi8GfEOVV+YWIH/jjmvMvAkcN78QPDCXOWWK7W bH97aC2PzArgw75auJ9U/wDyVHpYv3qGGfWzX/kzPvfw34ubxU2pMmlXdhDZTC3MtxPGfMfaGIVV ycAEcn1rWkuHUj93IxPTkf4VzHwtkhu/CNxfW6KYLrU7l1kX7sgUqmQOvVSOeeK6rfg/cwK9mHNZ c0Tz5NXdmRzXxhiaSSKZUUFmbHCgde1cRN8dPA+n3DW8upTZjOCUtpCnvhiOa77bnB3Be/NIyJcN ++S3nBG7dJCrfzFbcqfQz5vM5Rvi14L+ziceKLCONlDY84iQZ7YxnPtVFPjp4LZgDq8nH922dse/ TpXVXPh3RLziaw05ipz/AMeqD/2WsC7+HfgkyO8+nWu/Jdm+ccn6cVfK+iJ5l5kEfxp8CPJ/yMEc bE4PmW8iY+vy9Kuf8Lp8G28YePxJZKRkBl3F8jvgKc1lw+Afh3YzSoNIsZ1PzMbgSSEEdMA9PwqO 803wBYE27aPo7ny8eYY1BVD3OVHHuTScZND08ya7+NfhCGMwy+IrEooE9nJuYgKwOVwFz8rbuDg4 NV7f4zeEriPK65YrKBkoZdufXqvTv+NY81r4ZXWbG203TLWaN4pbHbHbq0LFQsoYNghmPzAc1iXW gwx317aS2MUkCv8AvfJ0yNgityqgjByM++PfpWTjLuWnHsdNdfHLwl9q2LdSuqrw0UbeUw92xnP4 dKuw/GnwYyeY2qxxlucKsmQff5P84rG8I/CfQ7SzaUwJfxXblzHfWqiRCDwo7DHP1xW/b/CHwizS JPotncg7ir+WUOPqCMYrRRnb/hyHKAyH42eE/wDVz+ILBJCcxrCZdxXjA5TqTwcV0en+PNJ1KGGR JgqSEIoaGZefTlOnv0pfDfgvQfDcCRabYQRZ+ddyAuT/AHsnn0/KugmkmwB5rn23Z49KpcyJ91kH nR8MdgHpv4qFpi8hXC4HfPX/AOvQ8KyfdGCTk4FAhK9NxPfvSbkUlE8J/ao+GseuaU/jC2UJJZxx 2upBf+WkRO2OXHqhO0n0I9K8v8I+N/EUnhDUm0O7iTxdpNo1rOtxbpcLqGnk5KFHBBYc4PUEH+9X 2Je2MdzY3Yu44p7JoXW4t5oyyvFtO9WA6jbnpz6c18NeMNMb4O/ES31DQL6PVdEYfa9PnRyfPtX+ 9C+edy9Mnr8przcZRnNKcNJp3Xr29GtH956GFrQg3CesGrS9O/qnqvuPLlhCKFVcAAYX2PTHtTWj 9DXc/E/wrbWNxa+JdGfzPD2tDzoQo/1Eh5aM+nOSB25HauGz3BI9jW1CvGvTVSPX8O6+Rx16MqFR 05dPx7P5iZNM5boeRTlxu55X260beAR1rouYWK8m7k4GKZzxzVt49y7h0+lV2j9PrWbKREvzdeMd KsLh14FRKu/vyO4qbgYIouAoXqppsbGGUhhwanjiaYqiLljwAO9eoa38C7vS/h/oPi9JGvdI1DMM 7Jw1rdKMvA49SuHRujKT3BFS6kYyUW9XsaRpykm49DzBl3dBUT+5wR0Neh2fgW0MKNv3oRuVt3UV Z/4QGwYcj+da+zkCiziPC9hbeIdesNLu9XsvD8V3KIm1LUt/2a3J4DSlASq5wC2DjOTxW38Tvhj4 i+EHjCfw34ltEtr5YxPBNC/mW95A3KzQSDh0OevbvWi3w/sJJGwMHp36elez+C9W0bxZ8PoPhh8R ZZZ/D1sd3h7xAo33fh6Y9FVur2zdDGeg6dsZuM462NFT5tD5cdRJyOG/Wo9xHytxXW+OvAN94D1q 5sLqW3uxCeLqzfzIZUJ+WRG/un8weDXMTQ+Z2wapMynTlFtS3K8imq0iY6jjqKuHKnYwxUbRn2+t BLRRZeeaWJircVLIh7VBxu9u1IlovxyK2CCQac2Dw351RjmK9KtJJlSRzWl7mViEwFZoyOV3D+dF WIeZVHUbhx+NFLlC560/7Ifxd852HhPgsT/yErT1/wCu1Pj/AGSfi6v/ADKf/lSs/wD47X6Rt940 lcvtGaJtH502/wCyf8W0YZ8Kfj/aNp/8drd0j9mD4q2sgL+FyB/2ELT/AOO199qalj3dlY/QVy1P fWp3UcTOm7owP2J9N8T/AA9vLnTvFOlx6PaTRs6zmeGUyONoVGKOSABuIwOtfTXj74kQeG/COqX+ kKms6tDC/wBlsIpUVppQOFyxAAz1yRXgclw/3QetRXV2ZOn0rzqODp4aM40dOdtvvdpK/wByRvic VLGVVWqpXSS9bdz4i+KnwS+MnjW81LUbrw99q1bXJ/t+oyR6jahQx+7CuZfuoOnbJNec6L+xp8VL 7VFjm8KG3hYHzJf7RsycenEpr9GGmbvzWxpM8VvDvJ+duTXo0rUoqEdkc9WtKtLnkfnvqH7D/jqz sTs0MyFE8whdQtvmkxwMF/oK6L9n/wDZI8Uw+O/D8XjbQzpfh25vFfVrg3ts4S0iIfysRyEnzXCq cA4UGvuDWNS8zbEhyPvNVCOYZyxq5S5k13M1UcZKSWx9NT+PNAsNNnkgvIZVto/lggIBbA4Reg9v Qe1fmF+1J4Z+NXx18TzXo8KeXZzOqLGupWo8uFGJVcGXqSST+FfVLXTTSIiHCgVFNMZJio6YxXL7 OMpqb3WwRqOmml1Pzt8H/sn/ABcg1S9urrwoYhI/yf8AEytD8o4A4l9K66T9mL4pbcDwyT/3ELX/ AOO194WvyrVkNWvLqaRxEkrI+AH/AGX/AIqHH/FNknv/AMTC1/8AjtQN+y38U2z/AMUv1PfULX/4 7X6DE0LWsXYylWlI+Aof2WfihtGfDOD/ANf9r/8AHaU/stfFDIx4ZwP+v+1/+O1+ga/dp0cbzSbU Xc2M4zT5jNybPz1uP2Y/isFwvhYdP+gha/n/AK2qKfsufFpRz4Xzn/qI2n/x2v0SuImjwHXDEZAz niq/PcU+d2sRd3Pz8svg38fvh54is9b8K6HcaZqUcLw/abXVLNHCtgMvM3Q4r0H43eOP2s/jV4Ts 9M1TwZpNnbCJYpYbG7tEZ2UEGQs1wcF85IHAwMV9Y6pnenpiqrMZI1GMbRiuOVClKo6riuZ216u2 1+9ru3Y6lianKoX0X4X7H5ZT/sb/ABtuYireCyOp41Wy/L/XV9CfCn9hXxRafD7Tf7Z8PQJqsyG4 uFa5hZg4ZtqllkIIwR0NfYuK27fxNNb28cIU7UUJ19K7PaSME7O9j88fid+xX8QND1PSzoPhtLvz oppLqSO+tosOX+UEPKM8Z6VH8OPg38e/hj4mXWdG8GW5uYygX7VqNm6lVO7bjzuhPWv0E1K/fUpk kYEbV28nNVlX8qyk+aPK9jSNSUZc0dz57+I3xA/ax+Jml6LYaloNrYWUcMlvd2+k31rALtXxzKTO c8ADC4GAfWsHw/8As3fEO10OKKbQGR8HKi9tv5iSvrCFjPNEqqeK6xWCwqvt6Vyxowg24qze/n6m k685JReyPh6+/Zz+I0udnh/uP+X22/8AjlYmo/sz/E2VTs8OZOOP9OtQP/RtfezMMnFQSSDnk10x Vjncj89Zv2W/inJ/zLGR/wBf9r/8dqu37K/xT3Z/4Rf8BqFr/wDHa/QtivrUbFPXNa8zJ5mfHHw6 /Zz+Iui/Dzx5Fc+HjHe3sQjt4vttsS/7sjqJMDlu5rhfh/8Asp/FC1+Ieh3V/wCHGt7G1cu0qahb ZB2kDhZcmv0Xtdsfhy7Ycb3x/IVQ01P+JnbYbktz9MVzU4qMqsl9p/kkjrq1pShSi/sr83c8z+H/ AMK/E+m+DbSzutLWG4jnuGYLPEc7pmYHhupBFb//AArfX88WH/keP/4qvX9HUfYSwJYGVyT+NXM+ xr0VVlY5LnijfDXXz/y4AHp/r4//AIqmN8OvEasNullxn/n4iGPf71e3Ue3IOPyqvbSEeHf8K48R Nj/iVfMG3DdPHx7cP0qGf4aeJZEf/iUIW5UKLqMA+nO7I+le3z3Yt937t2KjIwh5rOh1S6mlwtmE X33Z96PbyA+cfF3gH4oWs8A07whbajYq2We31KJJwoGAMMwUfr0o8OfCrxjdQyJqHhNbG3fOYJr+ CYkn1AJHIJ7kewr6aYmaMxycyf7J+7n2pIFMSqhTft4DL+nHej20gvofL03wf8T2N+80HhoR29lc QTW8MGoRrudWwWKBwoG1mz3OK7G6+FPiSRir6at0m/8A5+kUhfY7uua9vdS00oAdCUx22tx2qaGe WW3RwokJA9qFXl2Bnzxpfwj8QaHujh0GYxMxcq+pJJyfTc/HH9K2E+GOuj7tlIpb+EzxkL/49xXt xe5ZjmPavTg5/GpVUrywGelUsRLsSeJR/DvxIy7vsCkE84uIyT+O6rC/DvxB/FYZHqJ48/8AoVe0 BemMfSncKvOFH1odeT6CPFv+Fb663P8AZ4yOn79P/iqi/wCFb+Jd5P2bAzwPOjP/ALNXtW0TD+Je f4XqVQq1PtpFHi6/D7xLAyutoC6kMD5seOP+BV83fGb9lnxjrFlqNppOg+alhd/a9L2XcCjyJeXi +Zx91i3Xj5RX302Oxz9Kz9Wt90aT4/1eVf3Q/wCBqalSU1r0LhLlenU/OL4b/s2/Eb+zdW8I+IfD LR6HqCmW2uPt9qxtrgcggCUnBOD9QfWuBuP2QPi5Z3UsEnhVXaNipddQtArc8MAZc4I5/Gv0kvLd rW4aP7rIeCP0NXNS/wCJhp8V8oxKnyTD+v8An1rij+5qOcdpb+vf59TpnVlWpxhLeG3e3b5dD8yz +yN8WCp/4pTn/sI2n/x2kX9kf4s7f+RUwR/1EbT/AOO1+j2aXoa6vaM5D84P+GR/iz0/4RT/AMqN p/8AHaa37InxZP8AzKmf+4jaf/Ha/SLml60OowvY/Nj/AIZB+LX/AEKeCP8AqJWn/wAdqe0/Y9+K 0+4SeGBEfT+0LQg/+Ra/R/aaVMqwI69qXtHe7G72sj87fD/7IvxTh1IGXwuY3hOVY6hannPBGJa+ pfh38NPF+g+Fb/w9rXhcXnh7WFEd5Ym7twYZM8Txnf8AKwJDjHRl9GNfRsNgusaetzZJjUrQFin/ AD8R9x/vL+oqXVrNk0mDULctLZTIMt3jfoVb2z0NctaMa65Zf8MdNGrOi7pH5t/8M9/GbQdYuEt/ CMd7bQXBKbtQtFSQAkH5fOyA3XHbNWtZ/Z9+LsV35lh4UL2Uyh0DajaZiYjmJsy8lT3HUYr7vjB8 w571M65jZQTjrivT+sTORyd9D89Zv2ffjSzB08J/N3/4mVnz/wCRqs2/wF+NSvz4RG3/ALCNn/8A Hq++Qp9eKkjyGxR9YmHNJHwZP8CvjFcW4juPBazeTnYjahZkOp4Zf9d0IrK1T9kD4lqUuLDwyZbS YZ8t9Qtd8B/uE+bz9a/Q11Dd8HsafYrKzGJULljgKozk1nOrKWpr7WU9Jan5uv8Asi/FduD4U/8A Kjaf/Hag/wCGRfi0uB/wieR/2ErT/wCO1+k8imORkZSjKcFW6imGs/asm5+bMn7IXxYP/Mp5/wC4 laf/AB2q7/sf/FvdkeEs+n/EytP/AI7X6V0n0o9oyWz80G/Y/wDi7uP/ABSXH/YSs/8A47Tk/ZD+ Lyn/AJFH/wAqVn/8er9K6Q0vaMl6n5vQ/si/FtZVJ8J4GR/zEbT1/wCutFfpErfMKKv2sieUcy/M frTeKmK5Y/Wnpbb657mliFY91WI0l27VZgPQE1NDp7scqa29P01m4dcHsf61lKVjWMTnDpssn3Vb H0p66Hct/wAszXf2mlIf4AABgcVoJpyBegz9Kx9oacqPK5tFnX7yEVVaxdeMMK9PvtOTByoyfUVh 3WmpuOAPbFUpXIscV9jPoakTT3botdQmmqT93j1q9a6WvGV/SquI5GPRZmPCHP1qdPDs+7cU/WvQ rDS0XLFR7VblskEXABb6VPOJnmv9nvDnKmm+WV7V2V9Yr0A/SsO6tdlaKVybGPSqKlkjAJ4pi1qS TouVqORe2PwqaIZWo5qlbjZGqjHApPLNPjBPA5qVUPHFMSM+4s/N96hFhhQMcVuJDu609rcBegqW y1E542PtTfsI9K25IefSoGjx2o0FqZn2EelPWxyelaAXpU8MQzz/ACo0DVkVjYqvzEVeZT60nEYp d3WpAicbu5qFycY/pUshqu3erRLGMT3qNhSs1NY1QjYl/c+F4R/z0k3fqf8ACqWlj/iYQHHGTn8q vav+50XToxxxn9P/AK9VNJbbqEbHgIrHnoKxp/C35s2qbpeSOo0G3iWxSZEIkZmG4kkkZrT3dKzd BnE2mp8ykqWOFzxkk1o+22uhbGTF3fjTPM3c5IGeg6n6+1P2k9OKacLk/r61QiHzArY+4M+tIxba ct8g6ljwaZNNF5gQKzlumxSQPqaTy0ZixWWNj/dJoAeshZgAqyL3bsKkVcndjn2J/lSc7eCwGO9J 5nIBY/hQBIxU9Rg9R2psD58xNn+rfA7DB5GPzpzP7557im/8vRPUOgPHqD/gaQD+aXaG460jZ5Iy aBuPGKYC7SvSncU3bx6Uwh933sCgCXA5HX1o7UmeO1Lx9KQCLwTgY9eKVlEilXG5WGCPUU3il49a AOP16xaNcsMyQny3Pqp5Vqo6PcLDdNBKP3M42kHpnt/hXW6tCpVJSMof3Uo/2T0P4H+dcTdW7W1x JExIKHAYfoazlG6cWWpWakNvLRrO5eFv4eh9R2NQ1r6h/wATLS4bwf62L5Jf6/4/jWPuqYS5lruE 48r02FFO6V5l4n+P2geH/EF1oljpmueKdTsyPtkHh6wN19lz/wA9DkAdOgJx+ddR4D+I2hfEjSH1 DQ7ozxxSGGeGVDHNBIOqOh5U/p6Vtyvcz5kdN2pkmcZHBry/Vv2jPDen6xeWNlp2u+II7GQxX1/o unNc21ow+95jg9u+0GmfEz4zafZ/B/U/E3hi8l1QyxSQWl5psP2gW8xiZg8oIwirgZLDgkAilysO ZHr+i6tLpt9HNEdpBDewYV3sWjp4g0m7ksXWGG4bf5J48qYffA/2W44+hr5h+B3xUXxh4DsZtRi1 KC8sLCGa+1HUrYwwzkqS0iSHhgNpORxgitLQv2xvDWhagb+DSfE194XDGO51220p208AHBbfnPB/ 2a5K9Oryt0fiR005x0uem/YXimmhaMiWI4Ze4pDHtVWx8rdD2re1/wARaHrkel69oV9DqFtfwiYT 27bkmjP3W9j7dfWvN/iL8WvDvwtltLbUWutSvdU3NaaPpVubi8kIH3kQEDHbkjv6UqVaVWClazfQ 9D2VOKUpaJmrZeK/D194obw5Dreny68ud2mx3CGdMDJ3JnIwOfpW7dWElhMYp49j9R3B9wa+dvCX jDR/HH7W3g28tdC1Hw9c/wBi3i31rqunGzuRIQ+12B+9kY+bJ9K9t+LPxs8MeDbqDw9cW+qa/wCJ 2iM8Gl+HbI3l35ecb2UEBV+pHtWkpSUlFIwhyO7ltc3oLdbjIVdxHNbGh6AmtJMsU6x3EYysTA/M PY/WvLfh78W9G8ZTzJptxLDqVtn7XpN9GYLu3wQCJIm5HJHPT3rtdW8U23hGxl8RT3qWNjaoZppp OFjUfez/AId6iq6nK1B2Z2QpUpJtdRupWklndPHIGDg4IbqCOtVK8/8AFn7YXgnVtI/tqTw14usL JVUrrU2jMLC6BwAEk3ZycjG4D69K2de+I2g+GPBsXinVbz7DpEkMcyPIpLtvAKqFGSWIPQe/YVrS c5wTnGz7HkVFGL0Z0ppvT6V5bpP7Rnh2+1azsNT0rxB4XF9IIrK617TmtoLlj0CPkjnjrjrW/ffF fSLH4jWfgmW11EavdJ5kMgtj9nZQhYnfnoAMHjg8Vtyswujsqaa43WvitpGhfEDTfB89tqMurX8a yxNBbF4QhYruZs8AEcnHHFdnQ0A1fvD60Uq/eH1oqRl5Y/mP1ra0TRW1JZpGlWC3iGWlZcj6flVO xsJL66WCPG9z1PQDuT9K6HVpY7W3j0u1bEUePNbux9P6ms2aIo2salvk+YduOT6cVtWi4GCDnHP+ FZtqqopkDZwcA+p/+tWpazt7YrnkbxNW3xwMfpVmSUKvTj196htPNmjL5G0HqSR2yaZJcDbwML6m sE77FNFa6ZelZc+DzV65m3cYBPY5rMkk+bb3rZGbBcfQ1dt2HAGMn2qnGw47nvVy1yzbjyPSqJNi B/lAA9qdNJ7ZNQRtj8KWRiygf3R24z9fWoAz7z5lPcVhXi/Ma3Ltht65J/hxWHdDuen1rWJJkXC4 qtVq4xzxVU/eroRmW4vu1palpltY+Hre4kjJvp2G1ixwAeen0/nVXS7U3tzDAv8Ay0bB+nc/lWr4 nA1DUktUBKQqIlA6B255+iikhvYoaPp7NamVhjzT8vuo/wDr1NJYhpDhuBxWg2y3jCoMIg2r9BVU PXUopI5+ZtkK2O3+KpJLIqoG7nGakVtzKPU1Mo8y7RMbtzgYH1xScEPmYXGjxrelQuUii3dfvYXv +NN0/wAPRzYeUsVwzEd+P/r1oXUuLjUnA4DBFPbG7kfkKtW6iG1l67lRU/PrWPKrGvMzldV0xbIK R3rPjkxXQax++jfvjkf1rGa322YlzypwazsaMRZATyKGZccCoQ3vRvpWFcbI2eKgZuvFOZu9RMat EDWPTimSfMCPXilJNLCvmXES+rqP1oBGz4mIVbKL+6n+AqppClr87Oqxk1L4ofdqEa/3U/mTUOjN tnuGPaE8msqX8NG1X+IzrNEVhpFsGPVcgegzV7BqrpeF020Cj5fKXHOe1Wd2OcE/jXSZEeW6FgSO y44FNXcz4Mgxj8/epDjdkjt1x/WkYAr3QDp2oEMEfl/ek9z2pcbVx0J560ioUbu+entUnC8EH8qA GKvzBic9xxQY1xyT9Cc087geKbtYMDjJoAXyyyn94ykjgjGRVSOwa38o/ap5drbSrNxg/wCRVvc2 DlefQU2QM1u+BhtvH4cigCRsjJBwfpS/Nj5sU1ZGYg9mGfel56ACgAXoMkcfhSt8zYGD7Zx+NNzg e/vQFPBK7e+M5pgO245Bo3E07PtQwz3pANU9KWmn35paBhJEs0bxuPlcbTXH65av5YkYYkhbypf6 H/PrXX81maxbpIwZhiOYeVIff+E/0qZdwj2OX0W4WO4a3k5jnG3HvWbeQNZ3MkLfwng+o7GpJke3 lZekkbdfcd6vawovbGC+Qc42ye3/AOo/zrF+7O/RmnxRt1R85/smT29v4R1/Tboovii21i4Orxni VpC3DkddpAwD0yGrP8Gs2sfGj4w3fhZwbOTT4rdpoT+6kvxGQCpHBIO/PuT65r0Xxl8DfBXjvVTq eraOG1Fl2SXVrPJbvKuMYcow3cADnJwK6Twt4R0bwRpEel6Hp0Om2EZyIoR1P95ieWPA5JJ4rqcl q+5zcr0R5r+ynqWlR/BHTIbRo4JrN5l1GNiFeKbzGLGTnj5dp57Y9Kv/ABA1bQdY+AvjC88MvZy6 XNpt2RJYoFjZwrBjwBk5HJ9qveJPgD4E8Va1Nqt/oY+2XBzcNb3EsC3BznMiowDH3I57118Ph/Tb PQ10aCwt4dKWE24s1jAi8sjBXb0wQTn60OSvcaTtY8R1dbzUv2Mkt9NJa7XQbZht5zGpQzL/AN8B /wBa9I8CeI/DX/CndLuoprWPw1Fpiq7OQI44wgDo/uOQQe+ag8GfB/wt8O76e50LT5LSWaMxEPdS yqqFgxVVdiACQD61lXH7OPw7vNSa+bw7GheQSvaxzypbM47+UG2fhjHtWcpLY0p8ydzN/ZX1K30P 4O6SNTvI9Otb7UbhdKhvpljZ42kO1FDHkltxwM5zmtDRLy00b9sq7fWlX/T/AA2kOlNMPlIEg8xE J/iyHPHOM+uK7TWPAfhzxLHo8epaTb3EejzLPYJyiwMuNuApAwMD5TxwOOKd468A+GfiTZQ23iLS otQEJ3Qy7mjlhPByjqQy9BwDg45rGTUm79T14yXs4xv8NjK1RrX/AIbV8B2QljKL4fvFA7jd5hUN jnmsr4XNBoP7THxk0/VQIfEdxc281r5/Dy2QQ7fLzyQAY84H9304lt/2d/hrb3VhdDw2rXljIJor pr2480uG3BnbzPnIIH3s4HHTius+Jngvw38XZbKfxNpUN3fWSbIL6B3guEXOdvmIwYjk8Hjk1lbp 0tb8bkp+/wA7tve3yt2NW01zwtqHinWYbO40+TXrFEGotEq+dEpGVEjemB0J4xXkn7VV/B4g+BM9 9pF0uq6J9ttpbt7CVZUkgWXDYZTg4bb34x7V6T4P8A+FfB+g3OjaPo0NnYXQYXKbmdp9wwTI7Es2 QSOTWXqOj6F8K/hve6dpPhibUtFgRt2i2MZuJJ1dvnAVyd/DEkE9Biqi1GSsdM6salNwlZXTOc/a G1XTbj9nPX7izubf+z7izi+yPG4EbqXTYF/DoBXC/E2SGytfgPf6wFPhe2ng+3NJ9xZDDF5LMTwA CHyTx9a4XxtoHw98QaDc6P8ADvwdrFx4p1KRYooLq1uhDp4Zw0khEp2JwCNw6Z7DNfVS+DdOvfBd p4b1a1h1SxjtIraSKdAyPsUAHHrkZB7V1q0Ejw6snUm2cp+2NZaFb/AO7uEu1vhqUkMNhbyFfPNz 5ikBAD82F3Zx2z2Ncx8ZLG88L+G/AHjucF9U8KXFv/aMmCWa3lVYrkcck5I+mTXcfD34G/D/AOHn ii01q08Nx3c1txEL2eS5EAznMayMQrDsevvXo/j7wLpusaHcwvENQ8NapE0Mke4jarDBQkEEexBB H1pKSjZGbi5XZ4Z8Mdnjr4zeOfGoZJ7CwEfh7TZV5BWPDzkHoRvIwR2J/H2Tmsbwf4M0bwDoUOja DZDT9NiZnSESPJyxJJLOSx5Pc1tUSd3oCVhF+8PrRQPvCipGdDZ6lJp7u0BVWYYLMuTj2pYpi0mS eTyzN/OslpOTjNP+0dFX6k0+UFI30ut7L0AUYVa0LWVpGVFXczEAKO5rk47k571p6bfSRXCyRsUZ c4bHTjBrGcXZ23NYy1O7uZFs7WOFeXclQ2ewPzN+J/QVlSXW5jjlAMDP86yZdQkYnJIkZcf7iDoK giu2l7EnoOK5o0+WNjVyNW4lLcgdBx7VWEZLA/zp8km1Fh43ryxHPzen4UkeSvzNTESQjc2OAfbp WhCvljI6Cq0bMighxn6VLFMW4Ze/3loJNCNlxyPrRM2cc1GvygHP9ailfdkrn+VSMq3jjlc5x71j 3TDnNaFy+c9TWZcc9sitokMzLg8+1VP4qt3HsKrxxl5FGDit4kM19MSaMCWKVonx95Tg49KvL/or RPLkytklm7luS35YH41HZjEY469qbrUckpzuYsq+WG9T/Ef6fhWkI6kTfukVxqPmfd6ZqH7U3rVB dPlx95qP7Nl/vNW7bMklY0Ibpmk69PenJeOZNwYqQeMGqMOmSLG7bnyaWPS5eu5qNRaGl9tk27N5 2ltxGeM+v1rS/tg+SELZVjuPucYrnDp0u77zVN9gl81fmbAxSKNiY+YsQ7dPzpGsd1j5f+0c1dhs Qyx9T0qe4hCoT2xWFje9zkLu1+ybQWzuquWz3q1qjlrkDB4FUvwqCWNY1Gx96c7bc8Go+fSqEJmr GmqG1C1U8jzBVXB9Ku6MpbVLfj7pLfkKiWkWy4aySJfET7tUb2RRTdLwy3rA4xFtHGai1pjJqk/t hfyFT6MpMN6vfZ/SlDSmip/xGdjbp5dvAg6CNcY+gqbaeuahtWJtYCBx5a/yFTfhW5mJ/EMDP49K Gx1zhqVm98HpUe/dkZP48GmId8vDAk56DJowGzyQaRCuNo4PoOKGxyeSKAGsp6Lzj3oKhgMgN/wK kDK3Cqdue1C/MxwCe/sKAEdGXHlllGMbc5FMWSVto2yDB5BYZx6+9TMp6kn6VGzDOAmG69KQxIWK w7cElGKHPoD/AIVYU9cZx9eKgiULNKBkFgHweR6H+VSdMZQ+g4oAec0zMq9FBXH407nsDSbmz93I 9c0AKsp6kYpDeRjrIo+rAf1p3XFNaFCP9Wp+qg0APD7sEd6XNRcr24pd5+lICTNQ3duLy1khzgsO G9COQfzp249qTcRTugscXrUO4Jcjjf8AJIvow/z+lN0OZGeWzl5inBx9f8/yra1ez8ySZMfJcLvX jpIOv58GuTUurAjcrqeOOhFYyjzLlNIy5XzDbq1ezuHhf7yHr6jsahZa6DU1GqadHfRpiWMbZF9u /wCXX6GsTB/un8qUJcy13HOKi9NiDbTSlT7cfwmkIb+6fyrQyKskO761F5bLV3a392msrf3M/hUv UpFAqwo+arL7+0f6Uz5+6cfSoNCH5qX5qm+b+4abmToEx+FIYxGdGzU7XTSKFZeexqP94v8AB+lL mTumfwpWTC7LMbHAqSoI3dv4cCrCq3pVozY0irljrF5YWs1rBNtt5v8AWRMoZW/A1W2t6GmlW64N MQdOKKXaeuDRtPoaskTuPrRTlU7hwaKQH//Z dataset external 8917b1741c54c0b34d3ab479b495660429cdd4ac Office of the Chief Technology Officer (202) 727-5660 (202) 727-2277 200 I Street SE, 5th Floor Washington DC 20003 US dcgis@dc.gov 8:30 am - 5 pm GIS Data Coordinator True Office of the Chief Technology Officer 20231011 Enterprise Geodatabase Feature Class external 8917b1741c54c0b34d3ab479b495660429cdd4ac Office of the Chief Technology Officer (202) 727-5660 (202) 727-2277 200 I Street SE, 5th Floor Washington DC 20003 US dcgis@dc.gov 8:30 am - 5 pm GIS Data Coordinator True Office of the Chief Technology Officer DC datasets can be downloaded from "https://opendata.dc.gov". Road Casings 2015-04-24T00:00:00 2016-03-28T00:00:00 2022-02-04T00:00:00 vector digital data external 8917b1741c54c0b34d3ab479b495660429cdd4ac Office of the Chief Technology Officer (202) 727-5660 (202) 727-2277 200 I Street SE, 5th Floor Washington DC 20003 US dcgis@dc.gov 8:30 am - 5 pm GIS Data Coordinator True Office of the Chief Technology Officer <DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>Road edges are defined as the edge of the improved surface including the improved shoulder but do not include the unimproved shoulder, only the travel part of the road. The road network is compiled to include all open intersections. Features do not overlap sidewalks, but have the sidewalk area cut out of the road polygons. Overlapping features are acceptable if one of the features is hidden.</SPAN></P><P><SPAN>Road: A generally named thoroughfare, that is usually paved and can be public or private. Unimproved thoroughfares are excluded. Road polygons are formed by a combination of road edge, curb, sidewalk, street intersection closure line, and map sheet edge.</SPAN></P><P><SPAN>Paved Median Island: Perimeter of non-traffic paved areas that separate traffic lanes in opposing directions. </SPAN></P><P><SPAN>Unpaved Median Island: Perimeter of non-traffic grassy, unpaved areas that separate traffic lanes in opposing directions. </SPAN></P><P><SPAN>Paved Traffic Island: Perimeter of non-traffic concrete areas in the middle of streets designed to segregate traffic flow. This does not include linear barriers, e.g., Jersey barriers, walls or guardrails, or point barriers, such as impact attenuators. Features do not overlap sidewalks.</SPAN></P><P><SPAN>Unpaved Traffic Island: Perimeter of non-traffic unpaved, grassy areas in the middle of streets designed to segregate traffic flow. This does not include linear barriers, e.g., Jersey barriers, walls or guardrails, or point barriers, such as impact attenuators. Features do not overlap sidewalks.</SPAN></P><P><SPAN>Alley: Perimeter of alleys first plotted photogrammetrically from other indicators such as building footprints, fence lines, curb lines, walls, paved or unpaved drives, and map sheet edge. Alley polygons are closed along the lines where they intersect with road polygons.</SPAN></P><P><SPAN>Paved Drive: A paved driveway for a building or entranceway for a parking lot. Driveways are neither streets nor alleys, but provide access to public facilities, such as a drive to a monument, museum, hotel, large estate, sports field or golf course, grounds of the U.S. Capitol, etc. If a driveway is less than 200 feet and leads to a parking lot, the entire paved area is captured as Parking Lot. Driveways are photogrammetrically compiled as polygons and not compiled from individual vectors on different levels. </SPAN></P><P><SPAN>Parking Lot: Generally paved surfaces used for cars to park on. Paved drives usually form entrances to these features, if the drive is more than 200 feet. If the driveway is less than 200 feet leading into the parking lot, the entire paved area is captured as Parking Lot. Parking lots sharing a common boundary with linear features must have the common segment captured once, but coded as both polygon and line. Small parking areas, where individuals park their cars in the middle of a block off a public alley, are not captured as parking lots. These are either public space (e.g., alleys) or private space where owners permit parking to occur.</SPAN></P><P><SPAN>Intersection: A location where more than one road comes together. For standard cross streets, intersection polygons are bounded by curbs and four closure lines at street intersection crosswalks (outer line) or placed arbitrarily where crosswalks could logically be placed. For "T" intersections, the polygons are bounded by curbs and three such closure lines. Complex intersections can have more closure lines. Entire traffic circles are coded as intersections.</SPAN></P><P><SPAN>Hidden Road: A section of a road that passes underneath a bridge or overpass and is not visible in an aerial photograph, but the location can be interpreted based on the road on either side of the bridge.</SPAN></P><P><SPAN>Hidden Median: A road median that exists underneath a bridge or overpass and is not fully visible in an aerial photograph, but the location can be interpreted based on the information visible on either side of the bridge.</SPAN></P></DIV></DIV></DIV> This dataset contains polygons representing planimetric roads, created as part of the DC Geographic Information System (DC GIS) for the Office of the Chief Technology Officer (OCTO). These features were originally captured in 2015 and updated in 2017, 2019, and 2021. Office of the Chief of Technology Officer alley District of Columbia driveway median OCTO parking lot planimetrics road street Washington DC District of Columbia Washington DC 2021-03-11T00:00:00 ground condition external 8917b1741c54c0b34d3ab479b495660429cdd4ac Office of the Chief Technology Officer (202) 727-5660 (202) 727-2277 200 I Street SE, 5th Floor Washington DC 20003 US dcgis@dc.gov 8:30 am - 5 pm GIS Data Coordinator True Office of the Chief Technology Officer <DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>This work is licensed under a </SPAN><A href="https://creativecommons.org:443/licenses/by/4.0/" STYLE="text-decoration:underline;"><SPAN>Creative Commons Attribution 4.0 International License</SPAN></A><SPAN>.</SPAN></P></DIV></DIV></DIV> Esri ArcGIS 13.0.3.36057 1 -77.13 -76.90 39.01 38.78 external 8917b1741c54c0b34d3ab479b495660429cdd4ac Office of the Chief Technology Officer (202) 727-5660 (202) 727-2277 200 I Street SE, 5th Floor Washington DC 20003 US dcgis@dc.gov 8:30 am - 5 pm GIS Data Coordinator True Office of the Chief Technology Officer external 8917b1741c54c0b34d3ab479b495660429cdd4ac Office of the Chief Technology Officer (202) 727-5660 (202) 727-2277 200 I Street SE, 5th Floor Washington DC 20003 US dcgis@dc.gov 8:30 am - 5 pm GIS Data Coordinator True Office of the Chief Technology Officer All planimetric data within the scope of the 2015 project was newly collected by Sanborn using DAT/EM Summit Evolution digital photogrammetric workstations, with the exception of StreetCenterlineLn_2015 (street centerlines) and GeoControlPt_2015 (ground control.) The photogrammetric supervisor established the data collection conventions to be used for data capture, including the data schema, global origin and working units to be used for data collection. The vendor assigned collection areas to stereo-compilation technicians based on OCTO’s orthophoto tile layout. They collected and saved planimetric data to the designated network subdirectory. After the data for the tile was collected, the technician visually reviewed the planimetric information for completeness and accuracy. The data was then passed on to GIS staff. GIS staff performed a preliminary review of the planimetric data. Omissions or errors that were found were communicated to stereo-compilation staff, who then updated the corresponding stereo-compilation file. The corrected data was then passed on to GIS staff. GIS staff then merged all data per delivery block. Polyline features that were required by OCTO not to have pseudo nodes were dissolved. Following the dissolve, all point and polyline features were appended to a template geodatabase in their respective feature classes and attributed as defined in OCTO’s Data Dictionary. Polylines that participated in building polygons were placed into a working dataset, and topology built to locate gaps in the lines where polygons would not properly build. A technician closed those gaps. Then, polygons were built from these polylines in a working feature class. Based on centroids collected during the stereo-compilation process, polygons were then assigned their appropriate feature code based on OCTO’s Data Dictionary. Once all polygons were assigned their feature codes based on their corresponding centroid codes, the polygons remaining were then checked against the 2015 orthophoto imagery. Any unclassified polygons that were erroneously not given a feature code (because the stereo-compiler omitted a centroid that was not caught in a previous review) were then coded with the proper feature code. Also, at this point an additional review for proper code was performed, and incorrect codes changed to correct codes. Then, all remaining un-coded polygons were removed from the working polygon feature class. Polygons for each feature class were selected from the working feature class and appended to their appropriate feature classes based on OCTO’s Data Dictionary specifications. Once all features were put into their proper location in the geodatabase and attribution populated, a topology was established to locate geometry errors. GIS technicians corrected errors then removed the topology from the geodatabase. The geodatabase was then compacted. There are two isolated pockets of data that were not collected by Sanborn in the 2015 project, which are located around the White House and Capitol. Much of these two pockets have no 2015 stereo-photo coverage because the flying height required to collect imagery suitable for 3” pixel resolution orthophotos was too low relative to the no-fly zones over these areas. To avoid splitting a large number of planimetric features between differing imagery dates, the stereo-imagery voids were generally expanded to the center of the closest street (coincident with street centerlines where possible) to produce the final void areas. Inside these voids in the 2015 data, OCTO’s existing planimetrics (updated in 2013) were appended to the 2015 data for all feature classes except BarrierLn and CurbLn. 2016-03-28T00:00:00 EarthData International, Inc 7320 Executive Way Frederick MD 21704 US (301)948-8550 (301)963-2064 Sanborn has successfully completed the aerial triangulation (AT) task for the aerial photography acquired April 1st through April 24th, 2015 for the DC OCTO project. Using fully analytical aerial triangulation (FAAT) methods incorporating automatic analytical aerial triangulation (AAAT) procedures, Sanborn determined ground coordinates for each exposure by flying at an average altitude of 1100m AMSL covering the project area. The results of the final adjustment are sufficient to enable Sanborn to produce orthophoto imagery and planimetric stereo collected data that meets project accuracy requirements (ASPRS Class 1 for 1”=100‟ mapping; RMSE 30cm). This process describes 2017 updates to planimetric data originally captured in 2015. The planimetric dataset provided by DC OCTO on 5/22/2017 was used as the base dataset for update by Fugro. Following the Aerotriangulation of the imagery, stereo images were generated for the planimetric compilation to allow for full view of features that could be obscured by building lean in a 2D environment. Relative and absolute orientation for the stereo images will be achieved by importing the orientation parameters from the AT results. The planimetrics were collected using MicroStation and KLT Atlas software packages and combined for final QC in ArcGIS in the final geodatabase format. Prior to the initiation of compilation, a data capture matrix was established based on the data dictionary and compilation guidelines provided by DC OCTO. Requirements for the 2017 planimetric collect included the addition of a feature class for features associated with airports called AirPly, crosswalks as a new feature to the sidewalk layer, and a complete recollection of data in areas around the White House and Capitol that was compiled in 2013 but not captured in the 2015 collect. Topology checks were run using the OCTO provided rule set. When running topology, flags were identified on the existing 2015 dataset and this topology check was submitted with the updated 2017 collect. Additionally, the inclusion of crosswalks in the sidewalk feature class has created flags in the topology due to overlapping with roads. A separate geodatabase was generated to run the topology check (DC_Planimetrics2017_TopologyChks.gdb) and temporary sets of all feature classes with deleted data were generated. The deleted data was removed in the temporary feature classes to reduce the number of false errors that had to be reviewed. Due to the large number of exceptions in the 2015 data for curbs that were not covered by roads, the 2015 exceptions were identified and excluded from the current review. This working topology dataset was used as a guide to make corrections to the final deliverable dataset (DC_Planimetrics2017.gdb). Both the working topology geodatabase and the final deliverable geodatabase were submitted to DC. 2017-05-22T00:00:00 Fugro Geospatial, Inc. 7320 Executive Way Frederick MD 21704 US (301)948-8550 (301)963-2064 EarthData International, Inc 2019 Planimetric Data Capture Update Original data was captured in 2015 and updated in 2017 and 2019. Digital planimetric mapping was collected in strict accordance with the feature types and formats specified in the RFP. The planimetric information was collected using SSK and KLT Atlas workstations. Quality control (QC) and editing tasks were performed in the MicroStation environment with a final review in ArcGIS. Production workflow was designed specifically to maintain the 3D elements and topology of the planimetric mapping once data is migrated to the ESRI personal geodatabase environment keeping the needed attribute information. Draping was done on the data to view in stereo. Topology checks were run using the OCTO provided rule set. 2019-04-23T00:00:00 Fugro Geospatial, Inc. 7320 Executive Way Frederick MD 21704 US (301)948-8550 (301)963-2064 EarthData International, Inc Fugro Geospatial, Inc. 2021 Planimetric Data Capture Update The planimetric dataset provided by DC OCTO on 6/15/2021 was used as the base dataset for update by Fugro. Following the Aerotriangulation of the imagery, stereo images were generated for the planimetric compilation to allow for full view of features that could be obscured by building lean in a 2D environment. Relative and absolute orientation for the stereo images will be achieved by importing the orientation parameters from the AT results. The planimetrics were collected using MicroStation and KLT Atlas software packages and combined for final QC in ArcGIS in the final geodatabase format. Prior to the initiation of compilation, a data capture matrix was established based on the data dictionary and compilation guidelines provided by DC OCTO. Topology checks were run using the OCTO provided rule set. When running topology, flags were identified on the existing 2019 dataset and this topology check was submitted with the updated 2021 collect. 2021-03-11T00:00:00 Fugro Geospatial. Inc. 7320 Executive Way Frederick MD 21794 US (301)948-8550 (301)963-2064 Fugro Geospatial. Inc. Fugro Geospatial. Inc. This report describes data originally captured in 2015. OCTO developed and operated a QA/QC program to check the deliverables. Generally, the program consists of various types of processes grouped into visual checks, automated procedures, edge-matching routines, specialized checks, and field verification. Through the application of these processes, the data's spatial and attribute accuracy, usability, data documentation adherence, and specialized characteristics are checked. Staff identified issues in a shapefile with appropriate descriptions for the vendor to fix. The data was delivered in preliminary format for a thorough review and identification of issues. The vendor fixed the data and delivered final data which OCTO checked to ensure the vendor made the fixes appropriately. Road edges are defined as the edge of the improved surface including the improved shoulder but do not include the unimproved shoulder only the travel part of the road. The road network will be compiled to have all open intersections. Features will not overlap sidewalks, but have the sidewalk area cut out of the road polygons. Overlapping features are acceptable if one of the features is hidden. Legacy data in areas without change will not be updated. Road: A generally named thoroughfare, that is usually paved and can be public or private. Unimproved thoroughfares are excluded. Capture the perimeter of roads and ramps, exclusive of median strips and traffic islands. Road polygons are formed by a combination of road edge, curb, sidewalk, street intersection closure line and map sheet edge. Paved Median Island: Perimeter of non-traffic paved areas that separate traffic lanes in opposing directions. Unpaved Median Island: Perimeter of non-traffic grassy, unpaved areas that separate traffic lanes in opposing directions. Paved Traffic Island: Perimeter of non-traffic concrete areas in the middle of streets designed to segregate traffic flow. This does not include linear barriers, e.g., Jersey barriers, walls or guardrails, or point barriers, such as impact attenuators. Features will not overlap sidewalks. Major traffic circles will not be coded as traffic circles. DC GIS will provide a list. See Figure 3. Unpaved Traffic Island: Perimeter of non-traffic unpaved, grassy areas in the middle of streets designed to segregate traffic flow. This does not include linear barriers, e.g., Jersey barriers, walls or guardrails, or point barriers, such as impact attenuators. Features will not overlap sidewalks. Major traffic circles will not be coded as traffic Alley: Perimeter of alleys first plotted photogrammetrically from other indicators such as building footprints, fence lines, curb lines, walls, paved or unpaved drives, and map sheet edge. Alley polygons are closed along the lines where they intersect with road polygons. Paved Drive: A paved driveway for a building or entranceway for a parking lot. Delineate the perimeter of all driveways greater than 200 feet throughout the City and smaller driveways within the Monumental Core only. Driveways are neither streets nor alleys, but provide access to public facilities, such as a drive to a monument, museum, hotel, large estate, sports field or golf course, grounds of the U.S. Capitol, etc. Do not capture private driveways that are less than 200 feet in length. If the driveway is less than 200 feet and leads to a parking lot, the entire paved area will be captured as Parking Lot. Driveways will be photogrammetrically compiled as polygons and not compiled from individual vectors on different levels. Parking Lot: Generally paved surfaces used for cars to park on. Paved drives usually form entrances to these features, if the drive is more than 200 feet. If the driveway is less than 200 feet leading into the parking lot, the entire paved area will be captured as Parking Lot. Delineate the outline of the parking lot. The curb need not be distinguished. Parking lots sharing a common boundary with linear features must have the common segment captured once, but coded as both polygon and line. Distinguish paved from unpaved. Small parking areas, where individuals park their cars in the middle of a block off a public alley, will not be captured as parking lots. These are either public space (e.g., alleys) or private space where owners permit parking to occur. Intersection: A location where more than one road comes together. Intersections will be captured in an opened fashion, as illustrated in Figure 3 and Figure 4 if the intersection is in a traffic circle. For standard cross streets, intersection polygons are bounded by curbs and four closure lines at street intersection crosswalks (outer line) or placed arbitrarily where crosswalks could logically be placed. For "T" intersections, the polygons are bounded by curbs and three such closure lines. Complex intersections could have more closure lines. Entire traffic circles will be coded as intersections. Hidden Road: A section of a road that passes underneath a bridge or overpass and is not visible in an aerial photograph, but the location can be interpreted based on the road on either side of the bridge. Capture the perimeter of roads that are obscured by overpasses or tunnels. Hidden Median: A road median that exists underneath a bridge or overpass and is not fully visible in an aerial photograph, but the location can be interpreted based on the information visible on either side of the bridge. Capture the perimeter of medians that are obscured by overpasses or tunnels. This report describes 2021 updates to planimetric data originally captured in 2015. Topology checks were run using the OCTO provided rule set. The inclusion of crosswalks in the sidewalk feature class has created flags in the topology due to overlapping with roads. Due to the large number of exceptions in the 2019 data for curbs that were not covered by roads, the 2019 exceptions were identified and excluded from the current review. This working topology dataset was used as a guide to make corrections to the final deliverable dataset. The following topological rules were used: Must Be Larger Than Cluster Tolerance BldgPly Must Not Overlap ObsAreaPly Must Not Overlap RecareaPly Must Not Overlap SwmPoolPly Must Not Overlap WaterPly Must Not Overlap RoadPly Must Not Overlap SidewalkPly Must Not Overlap BrgTunPly Must Not Overlap BldgPly Must Not Overlap With RoadPly RoadPly Must Not Overlap With SidewalkPly SwmPoolPly Must Not Overlap With WaterPly RecareaPly Must Not Overlap With WaterPly RecareaPly Must Not Overlap With RoadPly RecareaPly Must Not Overlap With SwmPoolPly BrgTunPly Must Not Overlap With SwmPoolPly BrgTunPly Must Not Overlap With RecareaPly SidewalkPly Must Not Overlap With SwmPoolPly SidewalkPly Must Not Overlap With RecareaPly BldgPly Must Not Overlap With BrgTunPly BldgPly Must Not Overlap With SwmPoolPly BldgPly Must Not Overlap With RecareaPly BldgPly Must Not Overlap With SidewalkPly BrgTunPly Must Not Overlap With RoadPly CurbLn Must Be Covered By Boundary Of RoadPly HydroLn Must Not Have Pseudo Nodes RailRdLn Must Not Have Pseudo Nodes StreetCenterlineLn Must Not Have Pseudo Nodes CurbLn Must Not Have Pseudo Nodes BarrierLn Must Not Have Pseudo Nodes GeoControlPt Must Be Disjoint GratePt Must Be Disjoint BarrierLn Must Not Self-Overlap StreetCenterlineLn Must Not Self-Overlap RailRdLn Must Not Self-Overlap HydroLn Must Not Self-Overlap CurbLn Must Not Self-Overlap BarrierLn Must Not Self-Intersect CurbLn Must Not Self-Intersect HydroLn Must Not Self-Intersect RailRdLn Must Not Self-Intersect StreetCenterlineLn Must Not Self-Intersect CurbLn Must Not Intersect Or Touch Interior StreetCenterlineLn Must Not Intersect Or Touch Interior HydroLn Must Not Intersect Or Touch Interior BarrierLn Must Not Intersect Or Touch Interior RailRdLn Must Not Intersect Or Touch Interior 0 EPSG 4.5(3.0.1) RoadPly_2021 Feature Class 0 Road features. OCTO OBJECTID OBJECTID Internal feature number. ESRI OID 4 10 0 Sequential unique whole numbers that are automatically generated. SHAPE SHAPE Feature geometry. ESRI Geometry 8 0 0 Coordinates defining the features. GIS_ID GIS_ID OCTO GIS sequential identifier. String 50 0 0 OCTO FEATURECODE FEATURECODE Feature code. SmallInteger 2 5 0 OCTO 1050 ROAD OCTO 1055 PAVED MEDIAN ISLAND OCTO 1056 PAVED TRAFFIC ISLAND OCTO 1057 UNPAVED TRAFFIC ISLAND OCTO 1058 UNPAVED MEDIAN ISLAND OCTO 1060 ALLEY OCTO 1065 PAVED DRIVE OCTO 1070 PARKING LOT OCTO 1090 INTERSECTION OCTO 1091 HIDDEN ROAD OCTO 1092 HIDDEN MEDIAN OCTO DESCRIPTION DESCRIPTION Description of feature code. String 50 0 0 OCTO CAPTUREYEAR CAPTUREYEAR Date 8 0 0 Date captured. OCTO CAPTUREACTION CAPTUREACTION Type of edit performed on the feature. String 1 0 0 OCTO A Add OCTO D Delete OCTO E Existing OCTO U Update OCTO DCGIS_ROADPLY_AREA DCGIS.RoadPly.AREA Double 8 38 8 SE_ANNO_CAD_DATA SE_ANNO_CAD_DATA Blob 0 0 0 SHAPE.AREA SHAPE.AREA Double 0 0 0 SHAPE.LEN SHAPE.LEN Double 0 0 0 Simple FALSE 0 TRUE FALSE