20230302 11102600 1.0 FALSE fhd_Coho -124.544709 -117.196007 41.934529 46.270815 1 002 Projected GCS_North_American_1983 Linear Unit: Foot (0.304800) <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/10.7'><WKT>PROJCS[&quot;NAD_1983_Oregon_Statewide_Lambert_Feet_Intl&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;,1312335.958005249],PARAMETER[&quot;False_Northing&quot;,0.0],PARAMETER[&quot;Central_Meridian&quot;,-120.5],PARAMETER[&quot;Standard_Parallel_1&quot;,43.0],PARAMETER[&quot;Standard_Parallel_2&quot;,45.5],PARAMETER[&quot;Latitude_Of_Origin&quot;,41.75],UNIT[&quot;Foot&quot;,0.3048],AUTHORITY[&quot;EPSG&quot;,2992]]</WKT><XOrigin>-118489100</XOrigin><YOrigin>-97381100</YOrigin><XYScale>3048</XYScale><ZOrigin>-100000</ZOrigin><ZScale>10000</ZScale><MOrigin>-100000</MOrigin><MScale>10000</MScale><XYTolerance>0.0032808398950131233</XYTolerance><ZTolerance>0.001</ZTolerance><MTolerance>0.001</MTolerance><HighPrecision>true</HighPrecision><WKID>2992</WKID><LatestWKID>2992</LatestWKID></ProjectedCoordinateSystem> NAD_1983_Oregon_Statewide_Lambert_Feet_Intl 20230113 07505200 20230113 07505200 FGDC 150000000 5000 FGDC CSDGM Metadata /9j/4AAQSkZJRgABAQEASABIAAD/2wBDAAMCAgMCAgMDAwMEAwMEBQgFBQQEBQoHBwYIDAoMDAsK CwsNDhIQDQ4RDgsLEBYQERMUFRUVDA8XGBYUGBIUFRT/2wBDAQMEBAUEBQkFBQkUDQsNFBQUFBQU FBQUFBQUFBQUFBQUFBQUFBQUFBQUFBQUFBQUFBQUFBQUFBQUFBQUFBQUFBT/wAARCAJkAxgDASIA AhEBAxEB/8QAHwAAAQUBAQEBAQEAAAAAAAAAAAECAwQFBgcICQoL/8QAtRAAAgEDAwIEAwUFBAQA AAF9AQIDAAQRBRIhMUEGE1FhByJxFDKBkaEII0KxwRVS0fAkM2JyggkKFhcYGRolJicoKSo0NTY3 ODk6Q0RFRkdISUpTVFVWV1hZWmNkZWZnaGlqc3R1dnd4eXqDhIWGh4iJipKTlJWWl5iZmqKjpKWm p6ipqrKztLW2t7i5usLDxMXGx8jJytLT1NXW19jZ2uHi4+Tl5ufo6erx8vP09fb3+Pn6/8QAHwEA AwEBAQEBAQEBAQAAAAAAAAECAwQFBgcICQoL/8QAtREAAgECBAQDBAcFBAQAAQJ3AAECAxEEBSEx BhJBUQdhcRMiMoEIFEKRobHBCSMzUvAVYnLRChYkNOEl8RcYGRomJygpKjU2Nzg5OkNERUZHSElK U1RVVldYWVpjZGVmZ2hpanN0dXZ3eHl6goOEhYaHiImKkpOUlZaXmJmaoqOkpaanqKmqsrO0tba3 uLm6wsPExcbHyMnK0tPU1dbX2Nna4uPk5ebn6Onq8vP09fb3+Pn6/9oADAMBAAIRAxEAPwD9U6KK 8/8Ajp4x1zwP8P1v/Db6fFrV1rOj6RBNqlrJc28P23U7WzaR4kliZ9q3DMFEi5KjnFAHoFFeVf8A COfG/wD6KH8P/wDwg77/AOXNH/COfG//AKKH8P8A/wAIO+/+XNAHqtFeUnw58b/+ihfD8/8Ach33 /wAua8qPxa+MXhbV/wCyfiF4v8A+B72efy7CZ/BV/eWd6m7bvWdNVUR4OCwkC7VdCcZOOerXp0Le 0dk/u+/ZCveSglqz6ror4y1z9or4vzeLh4e8E+JfAvj+8ZCudN8FajEI5RMsZ8xm1PYIcNkTK7Lk YIUEPXQXHjr9pzw7o41vxUvgLRNEhn8u9ktfDd3fXNrDtz9pMUeqYaIEgNtfeoDNtIFc8cww83aE r+aTa+9K34ndLB14TpwlGzmrr+ul+l9+h9W0leRafpvxm1axgvLP4lfDu6tLhFlimh8DXrpIjDKs rDWsEEEEEVZ/4Rz43/8ARQ/h/wD+EHff/Lmu/fY42mnZnqtFeVf8I58b/wDoofw//wDCDvv/AJc0 f8I58b/+ih/D/wD8IO+/+XNMR6pS15S3h343r/zUP4f59P8AhA77/wCXNeLx/Fz9o6L4g2Hgi9Tw TB4guZxIxt/DF1Napp+4o155n9rA8FWxGyqTwMhmC1hUrQo25+vkzsw+Eq4rm9lb3Vd6pafNn19R XlI8O/G//ooXw/8A/CDvv/lzS/8ACOfG/wD6KH8P/wDwg77/AOXNbnGeq0V5V/wjnxv/AOih/D// AMIO+/8AlzXJfFbV/jr8NfAOreJYPFfgTXX09UkNjD4Hv4yyF1DtuGrtgKpLk7einp1qJSVOLlLZ GtKlKtUjShvJ2Xqz6CorxrWtL+PVhod7eWHjPwBqd9FbvLBY/wDCE3kRnkCkrHvOs4XJwNx4Gc1i /DfXvjF8SPC9vqtt8QPh/a3P+pvdPfwLfmWyuVwJYJAdYUhkbjlRkYOMEUuePMoX1Y1Rm6bqpaJ2 Pf6K8q/4Rz43/wDRQ/h//wCEHff/AC5pD4d+Ny9fiJ8Px/3Id9/8ua0MT1aivKv+Ec+N/wD0UP4f /wDhB33/AMuaP+Ec+N//AEUP4f8A/hB33/y5oA9Uoryr/hG/jeP+ah/D/wD8IO+/+XNZPie4+LPg 3QbzWtY+KHw7stNs08yad/Al9gDoAANZySSQABkkkAAk1MpKKbk7IuEJVJKEFds9sor51+E+v/Hr 4oeFzr03iHwT4esp53+wLd+Cbx5Lm2wNk5UawNm7J+XngAgkEE9r/wAI58b/APoofw//APCDvv8A 5c0oTVSKlHZl1qM6FSVKputGeq0V5V/wjnxv/wCih/D/AP8ACDvv/lzR/wAI58b/APoofw//APCD vv8A5c1Zieq0V8u/E74pfF/4T65a2GseKfCF0uoQK2mNp3gO8mlvZ/NCSW6x/wBtAqyh4mBPDBmA +ZQG3vhlqn7QPj7QZ9U1DW/BvhVDdSR2ttqPge9M80K4Cyun9sAxkncNhz93IJBBrmjiKUqjpRfv Lc7ZYOtGgsTKNoPZ9/Tv522PoOlryn/hHfjfz/xcL4fn/uQ77/5c145qXx0+LXhqfxNZ674o8G22 r6Rq8WlwaXp/gW+u574TLvtpExq6qDIgdthYkbME7iAbqVqdGzqO1ycPhK2LbVCPM1+rt+bR9cUt fGGuftEfHXT9Huru20+2MkCeaTqHw0v7a3VBy7PKNZfaAu452npzjqPVfhzffG34geCdI8QDx98N rc6hD53kWvg2+uViySNhf+11yy4wwx8rBl5xk408ZQq1PZQl71r7PYVfDVMO+WorP1PeqK8p/wCE d+N//RQ/h/8A+EHff/LmgeHfjcenxE+H5/7kO+/+XNdhynq1FeVf8I58b/8Aoofw/wD/AAg77/5c 0n/CO/G//oofw/8A/CDvv/lzQB6tRXz18M9f+N3xE0/V7hvGfw/0ubTtUuNMltH8E30skbRED94R q4UMcg4RnUAj5ycgaPjSP9oHwzob6lpvifwJ4gMDq1xZ2/gm9S4MH8bQqdYIkkA5EeV3YIBzgHCN enKn7VP3S3BqXK9z3SivjrXP2k/iCbRIvB/jzwb431+ZwkGkWPw51WJ3ABZ2LNqvRVUn5Qx6cAZI 7/4a+J/jH8RtJkkHjfwRo2s2mxNR0W/8A36XNlIy7lDK2sAlWHKvgBh6EEDmpZhha1T2VOom/wCu u1/Lc1nh6tOPNONkfQ1FeVf8I58b/wDoofw//wDCDvv/AJc0f8I58b/+ih/D/wD8IO+/+XNegc56 rRXlX/COfG//AKKH8P8A/wAIO+/+XNH/AAjnxv8A+ih/D/8A8IO+/wDlzQB6rRXlX/COfG//AKKH 8P8A/wAIO+/+XNH/AAjnxv8A+ih/D/8A8IO+/wDlzQB6rRXlP/CO/G//AKKH8P8A/wAIO+/+XNch 4u1743eEfGHhDR5/Gnw/ay1+ee2bVJPBN9HFayrHuijOdXIZpTlVXcpJBxnpWVSrCjHmm7LT8dCo xc3ZH0LRXlX/AAjnxv8A+ih/D/8A8IO+/wDlzR/wjnxv/wCih/D/AP8ACDvv/lzWpJ6rRXlX/COf G/8A6KH8P/8Awg77/wCXNH/COfG//oofw/8A/CDvv/lzQB6pS18x/FTxZ+0R8K7CbW7jXPhvqfhi 3nhjnu7bwvfLdRxuVUyeQ2qBThjtCiQk5UnaMlfRh4d+N5AI+Ifw/wD/AAg77/5c1hCvTqTlTi/e W+/X/hi3CUYqT2Z6tRXlX/COfG//AKKH8P8A/wAIO+/+XNZmv6L+0Na2avo3jT4Z6hc7wGjvvB+o WqBMHJDLqkhJzjjaOp54wdZSUVzMla6HtFFeAfC/WvjP8T/AmleJbbxx4DsY75GJt5fAt6xjdHZH G4azyNytg4GRg4HQdV/wjnxv/wCih/D/AP8ACDvv/lzU06ka0FUg7p6ocouEnGW6PVaK8q/4Rz43 /wDRQ/h//wCEHff/AC5o/wCEc+N//RQ/h/8A+EHff/LmtCT1WivKv+Ec+N//AEUP4f8A/hB33/y5 o/4Rz43/APRQ/h//AOEHff8Ay5oA9Vor56+K3if4wfCfwTe+Ib/x/wDD+58nbHBaL4IvI3uJWOFR SdZ+rHAJCqxwcYrd8M2Px21zw7peo3XjTwJpdzd2sVxLYzeBL8vbu6BjG2dYBypJByB06CsFWpuq 6KfvJXt5F8kuXn6HtFFeVf8ACOfG/wD6KH8P/wDwg77/AOXNcdbeIPjc/wAVb3wTceM/AEUy6Wmr Wt5H4JvnWWIyeU6up1cbGD9AC4I5JU8VVSrCnbndruwoxcr26H0NSV5X/wAI58b/APoofw//APCD vv8A5c1w/ibXP2g7HxnY+GfD3iL4e69eyWrXl7PceD9QtILGLJWIu41STcZGWQBV+b5CcYyQVKsa SvL/AD/IylNQV2fRtFeO6xo/x6sdHvbmw8a/D/Ur6GB5ILL/AIQi8i8+QKSse86zhdxwNx4Gc1kf DnVPjJ8RvBGkeJLL4gfD+KK/h3tD/wAIJfnypASskeTrC52urLuwAcZHBo9rDnVO/vNX+Rryvl5u h7zRXzL4B8dfG/xV448W+D9Z8WeAPDPiTRbpnttPn8GX0r6jphIEOoRH+11Uo7blZVLeWy7XIYgU /wCIWr/tR+D5ppdHf4feKtMRGk8608N3kU6hVBO6FtTJJJLBQhcnb0BIFRUxFOnD2kr28k3+CVzO s/Yq8/w1/I+l6K+cfhx8QPib8To5o9O+JHgSx1a3eSO50XUPAV5Fe25RgrF4/wC2icZK8jIycHBB A7n/AIRv43/9FD+H/wD4Qd9/8uaulVhWip03dChONRc0XdHqtFeVf8I58b/+ih/D/wD8IO+/+XNH /COfG/8A6KH8P/8Awg77/wCXNalnqtFeVf8ACOfG/wD6KH8P/wDwg77/AOXNH/COfG//AKKH8P8A /wAIO+/+XNAHqtFeVf8ACOfG/wD6KH8P/wDwg77/AOXNH/COfG//AKKH8P8A/wAIO+/+XNAHqtFe Vf8ACOfG/wD6KH8P/wDwg77/AOXNH/COfG//AKKH8P8A/wAIO+/+XNAHqtFeVf8ACOfG/wD6KH8P /wDwg77/AOXNH/COfG//AKKH8P8A/wAIO+/+XNAHqtFeVf8ACOfG/wD6KH8P/wDwg77/AOXNH/CO fG//AKKH8P8A/wAIO+/+XNAHqtFeVf8ACOfG/wD6KH8P/wDwg77/AOXNH/COfG//AKKH8P8A/wAI O+/+XNAHqtFeVf8ACOfG/wD6KH8P/wDwg77/AOXNH/COfG//AKKH8P8A/wAIO+/+XNAHqtFeVf8A COfG/wD6KH8P/wDwg77/AOXNH/COfG//AKKH8P8A/wAIO+/+XNAHqtFeVf8ACOfG/wD6KH8P/wDw g77/AOXNH/COfG//AKKH8P8A/wAIO+/+XNAHqtFcT8EfG198Svgv4B8XanFbwalr/h/T9VuorRWW FJZ7aOV1QMzEKGc4BJOMZJ60UAdtXj37V2rWug/CS11O+l8ixsvFnhe5nl2ltkaa/p7M2ACTgAnA Ga9hrx79q7SbXXvhHa6ZfRefZXvizwvbTxbiu+N9f09WXIIIyCRkHNTK9ny7jVr67Hqei6xZ+INI stTsJvPsb2BLiCXaV3xuoZWwQCMgjgjNXc56V5L4V/Zt0Lwzqlley6/4m1o6fay2lhDqOqMUskkj 8tjD5YQxnZ8o2njgjkKR6B4S8MnwnpstiuqajqkBnkmibU5/PkhVjnyhIRvZVOcFyzYONxAAGGGl WnC9ePK/W4VLRmlDVdzbrK8UeGdP8ZaDeaNqsck2n3ieXPHFO8LOucldyMGwehGeQSDkEitWvLvH GsfE7UvEUnh/wv4fs9I0qR1Q+Lby7jnEcZiy7Jaght6ucLuypK8gK2QsRUjTh78XK+lkr/189Dai pOacZcrWt72t5/8ADannXjf4Y6R+zTdWnxH8GKNO0qx8uy1rSpC9z9ptZZkVmiZ2LLKGKHG4Kdo6 YYP9IrJHcR43K4I7HNfGXiLwTr8vxK0n4M33xG13WdG1lVu9TOo2IZh5cYlxDPIWYhmgbG35Y8gH zGDivUtL+FcPwF+LGi6l4R0TUrnwtrsA0nUbOxkkmWzuPMDRXcgd2LLgspOAIwGOcttPgYOsqVSo 6NO1NNJrtLrZK+mqvsetOhl06c6kMW6la7b0fL0dm5Walu3ZST01T39k8I+C9H8C6dLp+h2hsbGS eS4FssrtHGznLCNWJEa5ydiYUEnAGTW5RRX08UoqyPElKU5OUndsSlryb4rfFbW/hL4p0vUdR0uO 6+HVwggvdRtld7mwuGchZJFBwYSCo4Gc55ztV87Vv2ip9Y8TS6H8OPDB+Ic9pAs99dWuoR21rBuI 2IJmBV2PJwD2OMkOF5J4yjTbjJ6rpZ3+S3Z6UMsxVSEasI3i+t1Za21b0jq1vbdd0d18UPDFt4j8 NmaTWJPDl5pb/wBo2esRyBfsUqIw8xwSFdNjOrq3ylWYHHUfNnjH4meMviNN4A1TSvAOqXGo6Fcv qdzqVnZTQw3kSLkrazsAwhnjDZRl3NmNQHPDeiyfDzx78cNQvbjxxcah8P8Aw+kBtbbw/o2opJJP uA8ySeVQVdTyoUjp2GCZPdbLTbbTbGGztII7a1hjWKKGFAiRoBgKoHAAAwAK4K0a+YxcI3pw6O2r s+z226nz8qNaGJlKEnC2jaad/wA1bpfqn2Pn6P45eMPjFq0Nn8K7CCz0y3gS4uta163lELShoma1 UoGUMFfa3UkFipG1XbtPgF8TNU8caTrWmeIljPiDw7qEulXl5bowgu2jOPNQlVUE4OVHIwGwodVF T4a6LqPwr+IGt+E2sbqTwjqs76loVzBE0kFmzDdcWrlRtgUN80a7QpBb5i5xV/4i/s7+GPiFrDay ZdQ0DXXMQl1PRbo280yxsGRXGCrYZY2DbdwMUeDhQKjD0cVH99KblLVNbL5f1qe5SwmGo1ZxxFRt SScZLVLZ6xv6p66M9RoIDcHmvEx448YfBnVvsfjU6j428O3EH2keJtN0lY/7PKtiRJ4oicRKmJN/ XlgA+Pl9a8N+JNM8XaHZ6xo95Hf6bdp5kNxGeGHQjB5BBBBBwQQQQCK9Khi4V24fDJbp7/16HLUp OGu67mnXmV78ML/RPi0njfw1PGP7UVLXXtNu55FiniUAJcRbQQJkChQpG1lLDKElj6bRXROnGpbm 6alUa86PNyPSSs/Nf1r66iV8/wD7WWieL7rwdqF7pCW+oaTbwR3nVYbrR57eQzG8hkJy26PdGVGG X5SucuK+ga8z+NnxUn+H9jp2laLpcmu+Lted7fSdOVTsZlA3ySNwAiBgTyM+qjcy8uOjGeHlGcnF d1udOXKtLFU/YK8k0+nTV3volZat9L3O08IeIrbxZ4V0nW7RZI7XULSK6iWYAOqugYBgCQDg84Jr WVg3Rg30r5LTwj8b/hP8KdY0HS9P0XU9MkjuPssWizzi701ZCXYxF9rSBcybRlpN7qcsF217X+z1 4T8K+FPhlpg8JXUeoWF4i3M19Gz4up9ipJJsZiYyTHynG0gjAINRh8TOpJU5Qs7a3/Tud+Oy6jhq cq1OqpJytG2um95a+6+ytrrbRXPSWwykHvxXzD8Z/wBmLStD+GfiW40LxJ4g0vSrGzkvIdAN+82n Dyx5rL5Tc/Mylsljhm3dsV6F+0rbz6V4R0zxpYQyTal4T1GHUxHbIRNNb7tk8PmDmONkbc5wRtj5 BHTufE2m2vxF+Hup6fa30X2XWtOlgivYsSptliIEi4IDDDAjB59ajERhiPaUakNUtPO//BRlgcVi ctcMXRk1Hm19Y2ez8no/N+ZN4B8RDxd4J0LWxbfY/wC0bGG7+z79/l741bbuwM4zjOBmt6vIf2ev H1teeG7fwRqNrJofizwxbRWN5pdyw3skaKizoejow2nI6bh1BVm9VvdStdNgE11cxW8RdYw8rhQX ZgqLk92ZgoHckDvXThsRCtRjUT9f1PElWp1W6lPSL/D1LNcnpvxY8I6x4svvDNpr1nLrlm/lS2e/ axcKWZUzw5UK24LnbghsGvMNS+KHxD+KVrb/APCudAOneHLy9WKPxdPPBI/kLIUlkW0kIIwytgNk lR90Fht09D/Zl0q+m8QX3j29j8c6vrLwmW9ks1szEsShVEflnchOAGKsNwCgjrnglja1ecVg4Xj1 b0VrdHv21SaPPeIqVJJUI3Xd6L5f52aPPf2jfjd4T1CO3uvDt3LfeJfC91bXthq1mnmWLySPh7N5 0OSJIRIzKCFYRYLZUrXYeFv20PhtqWgWVzqupS6HqMifv7B7SebyXHBAdIyrDjIPcEZAOQMj4seF Dp/iDwR8JfDSW/hDwl4m+0G/utOH+lXCwRAvGxI/jQIpkJZmz8wwpEnuXgvwVpngXwppugabCosr CFYUZlUM+By7bQAWY5YnAyST3rlw8cdLE1Jc8UtE9Ou/dPZrX8D7al7ChltJZlHnnJuUOR8rUbtN NtST95aKya1d9bHi3jr9pI6P8R7KPwfNL8Q9Om0iZp9D0GJZzbTq48qdpkViQxPllc/IMNgkqDP8 Pfg14r8T/EcfED4nDSzqUNtBHp+l2EaSxW4G5yH8xGIdXKsrxyE7tw3bcCvZPDfgXw54N+0toeh6 do/2jb532G1jh8zbnbu2gZxuOM9MmtWx1G11KFprS4iuYlkeIvC4YB0Yo65HdWVlI7EEdq9CGDlK fPXnfW6XRfqzGWY06FJ0sDT5bqzk9ZPr6R7aatdRNQvLTSLGe8vJorS0t42klnmYIkaKMlmY8AAA kk+lfLdjDq/xI+M2tXfwe1q58L+Ho9661rSotxp93enaS0Fs42tKdqbpARkc9wZfoL4qfD62+Kfg LVvDF1cyWUV8i4uIlDGN0dXQ4PUblXIyMjIyOotfD/Q5vDnhDTdPudM0rSLqFCJbXRARaK5YlmjB VSAxJbBHBYjLfeNV6Uq9VU3pFa3W9+1+n6meBxlLA0p1IrmqSurNJxS01ad+Z72TVlvqfK/x0+Nn xY+HenPoWu6n4UsrzUrVnjfQzc/bI0DopKl+ELBnwxA4jk2sGC1W+K+n+KfgB4L0PXdH+IWraTf6 g6XEnhrWLhL6X7QyyGcpIF2OFaYlsoFZsOWL+WK9O13Xrbw3+1xb3utxSabYXfh2PS7G5uFBS9uH vI8JFtJJIMoBBAK4LEBcMfbdb8I6J4mkgl1XSrPUZIY5YonurdJCiSrtkVSwOAy8MB1HBryXgJYi dWaqPmWkdX7vnv1PWlWwGEr4PFVMKm0uaTT0mn9nld4q2z3fpYqfD3x1pvxJ8Hab4i0l5Gsr1Cyi ZNjqykq6sPUMrDgkccEjBroq8Z8N/CDWPg1q1nL4I1G81Tw5cXYjvvDmqXQaK2geTPm2jkZQxF2Y o2fMXOTvCk+zDpX0FCVSUEqqtJb9vkfOY2nQjWlLCyvTbdr7pdE/P00PH4F/4VT8adN0XTf32i+P J76/mtZPvWd7FEryTI/VllGAY2+6RlSB8tewVg+JvBOmeKrzR726WSHUNJulu7O8tn8uaIgjem4d Y5FGx0PDKfUAjfrPD0ZUXOP2W7ryVtV9938zmqSU1F9ba/16CbR6D8q8l8bfBC4uPHT+PvB+tyaD 4u2Ks0dwDLY3yqm0RSoMMobbGCyk4CBgu/5q9apaqvhaWIiozW2q8n3FCpKm7xZynwz8fW/xI8Jw avHayaddh3tr3TZ2Bms7iNiskTjqCCMjcASrKSBnFdXXmHiz4Gwaz4sv/FOi+Jtd8K67dpEZW025 H2aeWJSInmhYESADAKZCkAjgsxJ8M/jMniS7t/DXimxk8L+O1RzLpNzGyJcBDgzW7nKyRthiAGJ+ R8blXeeWliZ0mqOK0fR9H/k/L7jSVNSTnT27dv8AgeZ6fRRRXqnMFFFFAFe+vrfTbOe7u547a1gj aWWaZwiRooyzMTwAACSTXzNoOg+Iv2p73U/EF9rV5onw6k1G3jtvD00TH7fDbnL5ZSm0MzNllL/O MEnyUNaXj/w7onxo/acsfC+qH7Xpfh3RXury03zp5ksjKBHkOqrhZIZN6DJxtYnACfQWj6LYeHtO hsNLsrfTrGHPl21rEsUaZJY4VQAMkk/UmvnXGWaVnGelKDa0fxPz8lrp1PQUlhYJx+OS7bLy833L g4AFLRRX0R54UUV558UvjNpvw2ktNNisbzxD4mvkd7LRNLj8yeQKrHewGSseVI3YJ4YhW2tjCtXp 4eDqVXZFwhKo+WK1Mj9qDXNC0/4O+ILDV7mzWe9tiLO0ublonmlV0KmMKCzFGKNgDbwAxVSWHa/D O6+2/Dnwtcfa7i/87S7WT7XeDE02YlO+Qbmwx6n5m5J5PWvOPhb8HdR1PXv+E/8AiOPtvjG43pHp kywyWumRrKGhEIG/DLs3Bw2R5hzltzH2uvNwkatatLF1I8qaSS623u/8uh0VXGEFSi72e/T5f59R aT1pa4L4qfEmXwUNH0jSrP8AtHxVr8xtdLtXRzCrDbvmmKgkRRhgzY5I6YGWX0q1aFCm6lTY54Rc 5csTj/gibTwl8Uvif4Itrjfb297Bq9uLqcy3UjXEKtOSzHLqreWNxBI3jczEg17BrGtaf4e06W/1 S+t9OsoseZc3UqxRpkhRlmIAySB9SK+cfh78DfifJq2teMr/AMXW/g/xPrU7m4t102HUnji3fKgl dzsXgYRSRtSPJyML2mg/BfWPF3ix/EvxVn0vXrm2Q2+m6LYo76baoVG+QpKMvIx/vA4wDk4QR/PY Gvio0VTjQabbteySTbav10XSx314UnPm509Fe3e33b9bnqmg+JtI8VWb3Wi6pZ6tao5iaaxuEmRX ABKllJAOCDj3FadZmg+GdI8K2b2ui6XZ6Tau5laGxt0hRnIALFVABOABn2FadfSU+flXtN/I852v oJXK+AfH9v43tLqKW1k0jXtOcQapo1wwM1nKRkcjh42HzJIvyuvI5yB1VeP+Mh/wrP4zad41m/0f wxrVl/ZGsXC/u4bW4Vwba5nxnduz5IdgAgIy4BArlxVWdBxqL4b2fo+vyf4XNacVO8evQ0/2jNBn 1X4W6hqNg0cOr+H5I9csLiQnEMtud5bGCGPl+YArAqSwzjqO68L69B4p8N6VrNqkkdrqFrFdxJMA HVZEDAMASAcHnBNXbyzt9Ss57W7gjurWdGjlhmQOkiMMMrKeCCCQQap+HPDth4T0Oz0jTI5ItPs0 8uCOWeSYomeF3OxbA6AE8AADAAFONGUcS6y2as/VbfmJzTpqD6M0688+LXgvU9ak8P8AiXw6sb+J vDd011bQSOEF3A67bi23HKoZEwA5U7SByuSw9DrnPiLqmv6P4H1u88K6R/bviWO2f+ztPLxostwR iPeXkjXYGIZvnB2htuWwDriKUa1Nxl/VtrCpycZJoxPhf8YtF+J2mlYW/szxBbh0v9Cu2C3VpIhC uChwSoYgb8Y5AOGyo5f9nb/S9U+J9/cfvr5/Fl5bPcyfNIYoggijLHnagJCr0UE4xXMfD39kPw5q WnWvib4iQ6trvjvWLGCbXPt+quY0vSC02xYGWMBdywqFyix28QUD5mfV+EWnp8Jfi/4k+HFhax/2 Be23/CRafIZmeWAMyQvC2RyNy/LzkKoyWLfL4aeKhWovEpWu1db3a0urafeZ4xUI1ISpt79tNu9/ 0Patc+3/ANjX/wDZX2f+0/Ik+y/bN3k+btOzzNvO3djOOcZxXzv+y/46uNPsfBPhHEa6De6FdX1v d3MJimmvlvpBLBGd5VwiEtgDdtwx2g7R7j8SvD9/4s8AeINF0ue3tr7ULKW1jkukZoxvUqQdpBGQ SN3OCQdrY2n5N0/4J2Hizwzo2m6Z4i/4RD4p6PP5U2g396sSm4jwWuI0jQMGaJIZBNEGDCNcl23S Vz5rUxFHF06lGN7J9bX1V0vPT5nqYWNOdKUakrXa+Wj19D3n9obwT4/1uw0bxL8NPEM2neKvDcsl zFoc0uNO1uNwoe3uEyAWwvyMSApZuULCRE+H/wC0Na+IPHx+Hvi3RZvBXxBWxiv10m5mE9vdxupc i1uAFE7RgESYUAMkoQyLGziv4b+Jvi3wT4q8N+EPiRb6VJc60jpY6/pdzthlljVR5UsbhSJGJ+8u FLSIqr1x2XxK+Fuk/Ea1s7mW3s4fEukedPoOtXFmly+l3bxlEnWNvlfaxR9jfKWjRvvIpHsUayxF 6lK6a3i/67fIwklFKFVadGv61X4mD8TvhBfa9q1v4o8GavH4U8YWySq15Hao6XysiqI7jjLAFEwx DbcEhScYzvCfx/On3SaL8S9L/wCED1/hYpbp82N5iMM7xz/cXBPKljjco3MxIHEp46+OHwEs9Q1T 4kw6P8Q/Aml21zcT614bt2i1naJkETyW3ywn5JCWVMKiRSM0pKAS+u6fqPw+/aI8Erc2dxpfjDQJ /wCONg5hkaMHB/jhmCSjg7XXd2NYujL2jqYaXLN7xez+XT1XzuebWwc6TdWi9/8AwF/5M7tWVxkH Ipa8DuPg342+E5luvhd4iNzpg3Sf8IprzGW3/wCWrbYZMgp8zrhcrk8vIelamh/tQaHa6j/Y3jnT rzwFr4cILbUEaSCTMjoHjnVdpT5eXYKvPBYAmtI5hGD5MVH2b89n6Pb77PyOdYlRfLWXK/w+/wD4 Y9oo6VBY6hbapZwXdncRXVrOiyxTQuHSRCMhlI4IIIIIqevVTUldHZe+wtFFFMYUUUUAFFFFABRR RQAUUUUAFFFFABRRRQAUUUUAeVfsnf8AJrPwb/7EzRv/AEhhoo/ZO/5NZ+Df/YmaN/6Qw0UAeq15 J+1FeQaf8L9Pu7uaO2tYPF/hWWWaZwiRoviDTyzMx4AABJJ9K9bryP8Aajs7fUfhdp9pdwx3Nrce L/CsUsMyBkkRvEGnhlYHgggkEH1pO9tBa9D1Sxv7bVLOG7s7iO6tZ0WSKaFw6SIRkMpHBBByCKsV 4FHocf7Mfis3umWxX4b63NbW11C91I7aVdMWQXHz/KsDfuw7M27JXBwqqfdbG/ttTs4Lu0njubW4 RZYpoXDJIjDIZSOCCCCCK48PiHVvCorTW6/VeTMaVRz92StJdCp4m1638K+HdU1q6SSS1061lu5U hALskaFmCgkAnA4yRR4Z1638VeHNL1q1SSO11G1iu4kmADqkiB1DAEgHBGcE0nii30u88N6rba20 aaPNayx3jTS+UghKESFnyNo25ycjHXNfHK/tPa74d8J3nhHwOv8AwkX9jmYW2uCzkbyNKSNRC7oV T97HuwzsgQeWvD7i1cGOzKGX1E6z91rZau50TlGFCdW1+TV27Xt+bX3nrWlXmm6l+1d4r1DWb/Tb SXw9ptnp2nW8+1ZJPtBVvNUs3DB5fK+Uc+eq9T83vwYMuRyK8H8Kfs4+BvGug3GreItQj+Imqarc m6m8QLOYw5XcipF5T4WNRldoYjK+ioqppXw/+K3wf0+Cy8K69p/jXw/bbvK0nXI2guoYFJKQQzoS GZlJXdIAq7UwAuQIwTrUIOVSnpNuWju9Xpdellpc7MHg8NVw941eWq3dqSsnftJNrTzsvNnvdFeJ t8dvGHhkrd+NvhfqHh/Qs7ZdS0+/i1LyO5eWOMBliVQzM4zjAGCSK9j0/ULbVrG3vbOeO6tLiNZY p4XDpIjDIZWHBBBBBFexSrwrfD+Kaf3MMTg62Ft7S1n1TUl98W1+Jyvxi8B/8LM+Guu+HFkEM15C DC7NtUSowkj3Ha3y70XdgZxnHNc/+zW2jN8J9IXS9Nh0q7t0FpqlssCQyrexKscpmVeRISgb5vmK lScZrpvix4sfwP8ADnX9cjt726ktLVmVNPVWmUn5Q43KygLnczFWCqrEq2MHj/2VZtM/4Uf4dttN 1OLUzAsguDGu1oZnkaR4mUnIKl8ZP3hhhwwrzJcizKKXxcjv96t+p57lWU1FN8jTv2urdPmeu0lF Q2t7b38LS208dxGrvEXicMA6MUdcjurKykdiCO1ezdbFk2PalrG8VeMtE8EaTJqeu6nb6XZJkeZc OBuYKW2oOrsQrYVQSccA1xXgL43w/E7xbdWnhvQ7zUfC1sgSXxKxEMQuCu7yxFIFdgBgFhkhiuVC kOeWeKo06ipOXvPp1NY0pyi5paI9N4I56Vj6H4R0nw3qGrXumWn2ObVZxc3axyP5UkuMGQR52Kzc bmUAsQC2SK2aSuhwjJqTWqM7vYWiiirEFcw3w38OSeOR4wl0/wA/xEsP2eO8nmkk8mPGMRozFY+M /cAJ3N/ebPT1S1nWLTw/pF7ql/L5FjZQPcTy7S2yNFLM2ACTgA8AZrOpGElea211LhKUX7jtfQuE Z4I4rwvUvhz8QfCPxB8UeKPBtzpcWjXEsN0PC6hgNWk2YnaR2+W3mY5w6cOVQyDhifXPCvjDRfHG kpqeg6nb6pZNgebbuG2MVDbXHVGAYZVgCM8gVsFgvU4rGcKeJjGSltqmmdeHxVTBuSSTUlZpq6td P9N910aZ5BpH7Q9haagui/EDSLj4e63JkRrqjq9jPgFj5V2v7ttq7N2duGcKMmvLPgp8EZvit4H0 vX9X8S3lloE11fahYeHdHU2sWm3bTOiywvuJAjKl0TGFY9wXD+h/GzxxqureJovht4c8I6d4m1W+ sk1G4k1tkNjb24uFQO8Z5lwykkDBHykB+QO3+CPgG5+F/wAL9C8NXlzHd3dlG5mlhBCb3kaRgueS AXIBOM4zgZwPGdB4vFRjUfNCCflrdWvbR/kdmMoRjTpYqm/Ztu/IpXTttK17pLZKV273ueZ6d+yM jeIdS1vWPHGuXuryPD9i1Szf7Le28UcTRbHlBYSFozGGfarEx5/iYHxr45fD/Q/CmveHvDOiXniz 4i6zpMkdxdaDLcNcxWtgNu6L93HuhL/ugNvRcEgZTP3TXLaH8O9N0Hxn4p8SwSTyX3iIWwuo5WUx p5EZjTYAARkHnJPPTFPE5Ph6kOSlBK71e/n89bbnNRqYSeKli8fRVR22slFvRapW0t2V20vUj+E8 PhaD4f6QPBZjbw0yNJaeXI8g+Z2ZxlyWzvLZDcg5BAxiuurx74S6PqXwz8ba34Cjsrp/BscI1PQr zymaO2V5D59rJMQAXEjFkU7m2ElmPAr2GvYw38KMbWtpbpp28u3kY4qhSw9VwoO8Ps+j2v5paNdG fOn7Rqaz8VvEVh8PfCNjG+sac8WsXOvSXLxRaS43eSN0ZLCZuSAQcKwYA/fTfvvhz4/8E2Fxd6T8 WZBo2no1ylt4msorjIUF2W4u+H2E7ssBlVPH3RXpsHgTQbXxnceLIdOji8QXFr9jmvEZgZIgVIDK DtJ+VRuI3YUDOBit773bIrh+oe1nOpWb5m9LNrTptb57jxVeOJo0cPa0ad3o2m27Xu7+SstvK9z5 c8C6n8Zv2ivC6at/wkWmeBPD10k8Mcul2ZluLnDBCcO5MYBEgDK6sCDwQVYdJ8GLzRvgJcx/DjXr ZNF1O+uy+n6mhla11slQokUsWEM2ERXiJA3FdmQ4Fe/qoXgDA9q474ofDe2+JOhQWrXUmm6nY3Ue oabqEShza3UZJjk2H5XAyQVbggnocEVHByopVIycqi6vr39P6ue080p4i+FnBU6De0Vqn0bdryt1 vfS9kna3Y0teWeA/GniTQ/F0fgfxy9ndapNatdaXrVkhhi1CONtro6NwLgACRlj3KFc9AoLep130 a0aybj00fkz56rT9nLlvfzWzM+80HTdQ1Ox1G5sLa4v7Hf8AZbqWJWkg3ja+xiMruHBx1HWtCiit kktjNybsm9gooopiCiiigAryXUfir4+l1zVrbQfhTeanptjdPaJfXuqRWJuCmMukci5MZJ+VwSGH PByB61RXLXpTqpKFRw9LfqmaU5Ri7yjf1v8ApY8I1L9p648B6gLP4ieCNQ8JtcQNPZyW1zHfxz7Q xZNy7QrZCKBzzIpbYvzHodcXwf8AtK+CXh0LxHmezmS8tL6xkaO50+5UuIpWjO1x0fAYDIyVIOGH qpA7gV4P+05pEHhnQYfGHh6K40nxj9ut7ZNW01kgVldkG2+diFaDEaDMmQGEY4UsD4uKhXw1Gcq0 1UhbZq0vvWn4L1Oym4VJxUFyy9dPuev4s7D4B/EG7+IHgiWTUrm3v9W0q9m0u8vrLH2a6kjIImiI PKsjIc4UElsKBivSa5T4b/DnTfhnoU2nadPeXjXV1Je3V5qE/nT3Ez43O7YAzgKOAOmTkkk9XXr4 ONWOHhGt8VjkquLm3DYKQ9KWiu0yPEvgNBJpPjn4jW/iJPsfjXUNUN81vJcvN5mnYAtmidgBJEha RAVAK8KwXCqPba8Y+OyT+HvGfw28SaXLHZahNr1vol1OkZ82e1nYloWbdtMfysdrKxDEMpQg7vZh 0FeTgP3XPhv5Xv3vr9/c6a3vWqd/00Fooor1jmOD+MHxg0b4OeGTqWpH7ReTbksdOjYCS6kA6D+6 oyNz4wAR1JVTx3wt+HPiW9+J2sfEPxfpGj6Ld30Iit9MtwLq5hZSUWVpySEbyQEIiIVw2WVSuDT+ Lt1J8QPjL4H8G6VZ3BvtCvYfEV/eXErw2yWyOBtVDxMxJADAHaTtB5k2+8dBXgQg8di5ym7wptWX Tmtq36fcdzl7GklFe9Lf06C0UUV75wiV8+fD661P4r/tGeIfEWoWf2fRPBvn6NpqebLt+0lyjyj+ BmKB9w7B4RhiA1fQdfMug+GdF0f9q6207wRoX9iw6PDPL4gkjv8AYlytxBvjVLcv/qkcxfcXAZ1y qhUJ8DNHJVMP1jzq67vp06b9NjuwqTjU723/AK77fM+m6KKK984QooooAK5r4j+CbX4j+CNY8OXj eVFfQFFlwT5UgIaOTAIztdVbbkA4weDXS0VnUpxqwcJq6ZUZOLUlujzb4Q/EDVvEV1rnhfxJYfZf E/hn7NBfXEcySw3nmR5WdCqrt37WbZtG0Mo65C+k14x4rTU/hT8Wr/xxDpkl14L1bT4o9fmtG8ya 1mhbbHdNGQWaNY2CkR9FDuwyo3ewWV9b6lZwXdpPHc2s6LLFNC4dJEYZDKw4IIIIIrgwNSSjKjVf vRb36q+j89PxNq0VdTgtH+fX8SekrH8N+L9J8W/2n/ZV39q/s29l066/dunl3EeN6fMBnGRyMg54 NbNejGUZrmi7owaa0YV5D8ftL1PST4f+IWjW0eoX3g+S4uZrGaXy0mtJIitxg4++qqCpzgYbhjhT 69TWXcpB71hiKKxFNwvbs+zWqf3mNWn7WDiUtD1q08RaLY6pYS+fY3sCXEEu0rvR1DKcEAjII4Iz XPePvhF4O+KFjcWvifw/Z6oJ4fs7zumy4EeSdizIRIoyTwrD7x9TXK+AdftPhfrE/wAP9cuvsMCT lvDlzeMVju7R2XbbpI8jbpYXfythIYoIiFwTXrOc1nTlDFU+Wok2t12ZVGq9GnaS/M+T/iJ8G/jJ 4b8NSeH/AA5qsPxK8KW8sd7ZTa9fGPxTZ3O4YMN4wWF1jfMm59jmN5IlZcI1egfA/wDaS03xpPpf g7xPFqXhn4i/ZPMOl69p8tlJqCIoDXMG+NAysQ52ABgY5cKVTefca4v4nfCHw18WtJS012yxeW2X 0/WLXEV/pk25WE1rOBuicNHG2RwdgDBhkVl9U9nW9vSlrazXRnoe3jUh7OrH5rf/ACOz4bjrXiHj z9nLVLvUdF1D4Z/EDUvhU2lxG3i0jS7SKbRTGxmZ2Nh8kZlZps7zkfKPl3YYYy/D348/DG4s7jw9 8Q7P4maRHdQ2f/CP+KdPjtJo7IyKplN/Fl5J0QDc7odwMj7HfajdF4L/AGpPDWrXN/pHjK0vPhn4 n0u2+16hpviZRBCkIkjgM8V2f3MsBnk8tJAwLkZC4xW0pQn7tRWf9dUKMJ0/epNS/rs/8jqvg3pH xA0Hwzd2HxF13TfE2rQ30ws9W0+3+ztc2ZIMTTxhQiS5LAqmVCheWOWPXazoWneItPlsNUsbfUbK bHmW91Eskb4IIyrAg4IB+oFcz4l8WX3iL4X6nrvwyv8AR/EGqG2ll0mTet1Z3csZI8rckqD5mRo9 3mAIxyc7Sp5/4CftEaD8edHvvsVteaN4k0fZFrug38EiTabcM0i+UzMoV/mhkwRzgDcqMdou9PSl LW/fqYypyqKVRx06+XyMqH9nGXwdcXE3w68Zap4LW4fL2Mirf2QG1QxWKXkOSiHeWJAyBwcB4uvj f4YbfNZ+GPGVja/IIraWWyvrxfurIS+YY26OwHHDBe1c9L+2doPiP4gad4V+Hfh3WPiL/wATO2sd W1rSreT+zdLilleNpXmCNv27N4IAjdckS8Guh+KHxC17w9+0V8FPDGnah9n0PxF/bX9qWnlRt9o8 i0SSH5ipZdrEn5SM98ivM+r4eKvQk462916avonp+Bz/ANmuL5Y3g7N79lfbb8B4/aKbw7J5Xjfw V4g8J+T/AMfd/wDZvtmnwZ+5/pEWd27KLwvDNtPQmtTQ/wBpr4Z+ILpra28WWsUioZC18klomAQO HlVVJ5HAOevHBr05lVuqg/hWXr/hTRfFVmtprOk2Wq2yOJFhvLdJUVwCAwDAgHBIz7muj2WMh8FV NecdfvTS/A5uSvHaaa81r96a/Iu2Oo2up2cF3aXMV1azoskU0Lh0kQjIZSOCCDkEVYrxY/sqeGdN vJJvDOteJPB0cyKk1vomqvGkpUsQzFwzEjcR1wOw5OZm8H/F3wuv9qQ+Prfxi1r+8OhXOkQWS3i/ xIJ0JMbYyVPTcF3fLmksViKa/fUX6xaa/Gz+5MSq1Y/HT+53/wAn+B7JRXmfwz+O+i/EC6fSby3u PDPimHas2hasPKuCxj8wmMHBkXG45wDgZKqCM+l13Ua9PER56Tujop1I1VzQd0LRRRW5oFFFFABR RRQAUUUUAFFFFAHlX7J3/JrPwb/7EzRv/SGGij9k7/k1n4N/9iZo3/pDDRQB6rXlX7S3/JOtI/7H Pwn/AOpDp1eq15V+0t/yTrSP+xz8J/8AqQ6dQB518fPihqXjbxZqPwe0AWekXVwIY7rWNUv/ALOj B1V/JjUfMxffGnGS2512Y+YaN18Efih4d8P2UmifFO4uZdCsnj03TIdKihjlxFtSJ8ybW4VQGkDb Sc8HJr0L49eBNI8Z/DbXjf6dZ3V9aafcS2VzdFIzbyBNwYSsR5Y3Im4lgpA+bjNafwX5+EPgsH/o DWf/AKISvlvqDrYyosRJu6vFpuNlfay7dzx/qzqV5e1bd9mm1ZdtO3c8j8I/DHxJ8bvBukax4m+K mqahpGoWBLafosMNmFaQKJI5XTKyhcOhVk656cg/QWjaLZeH9HstMsYBDZWUCW8EeS22NFCqMkkn AA5JzXjl0LX4OfHjQ7WxufsuheOftZu7KaciNNQRhILhS5PzSeYIvLXaCdvUhQPXW8TaWniKPQTe xf2vJaterZg5cQK6oXPoNzADOM4bGdpx14CFClzRl/ET5W2229E1q+6Z14WmoqSS95aPVvz6+pzn hL4W2Pgfxdq+qaJN/ZekajBEH0G0iWO0W4UkNcBf4WZPLXCbQdpLbiQV7ekVgwyDke1LXtQhGmuW Ksj0alSVR3m7vb7tDnPiF4Jt/iJ4P1Hw9d3t5p9tfKscs9hII5goYEqCQRhgCpBByrEd61NB0Sz8 N6LY6Tp0XkWFlAlvBFuLbI0UKoySScADknNX6KfJHm57aj9rP2apX91O9vM4H4weAfEHxG8OnRdH 8Tx+GrO5SSG/LacLp7iJ1K+WCXUIMFskDd0wVwc+dQ+DdP8AgT8XPh7HombPRtasZdD1N5QscMs0 SB7aVyoVTcyOXXc2SwLBQDmvoI9K+btQ8G6jD+1R4cm8aa9LrmmzW13d+HoZLZI4YJ0csYNg3ZMc RV/OYKWZI+SUArxswiqbjVgvecoq99ldfdfbTc2njK0cK6Uaiik1pbWV2rq6WvlzPTpqfSNfMeua D4ptfjf4h8AeD/FEfhfSfEFs3ie7uBbeZPbu5MEyxMWyWkkCPncu3A2FdpD+jfGD45Wfgnw9pqeH Xstf8S65JDBo9jHdx4lM2RFO3zAmHKn5hwTgZGdw4+3/AGbfF3ibV7TXPF/xNv5NVjsvs/m+HrWL Tp03MrGM3CDMkYYHCso5ORt5BnG8uLlGnTTbi7tp2t5Xut+yPQwuCpSoSqYuqoRldLfmbVtkk7er a62vqdP4a/Zu0S31SXVPGN3J4+1SOQpZXeshnMNqECRwvGWMchHzMXKAszlsBua3NQ+P/wAP9J8X W3heXxDA+tzzrapbW0bzYmaQxiN3RSqNuGCrEEd8CuI1bQ/j9Ppd7pEWq+D7i3khe0TVcXdveMpU qJvkyscuPm+XIVumQK9G+FXw1034c+E9NsodL0201ZbK3g1C5sIFT7TLGgBdm2gv8xYgtz8x9TWt GLhPkoU+Vbttb/jq/O4qzpqblipe0utORpJeumi8ra+R2gOeaWiivZPFCkJC8k4FeX6j8VrjSfjf ceFbxrK28P2/httalu5so8brPsO5y20IEBJyM984rzaz8XfEH9pS+ltNCEnhD4d/2jKP+Eks5Wju 723iKhUh3YZS7hiXCgAHYclGWTgnjIRfLFXltZf1t5ntUMqrVV7SbUKaSbk3pZ7ebbs7Jan0yrBh kHI9qK574f8AgbTfhr4P07w5pAkFhYoVQzPvdmZizMx9WZmJwAOeABgV0DMFUk8AV2Rb5U5qzPJq KEZtQd49Htp6a2+8+aPEmoa38Mv2jtSh8AaGfENxr+mLqmsaGzwWkXyO0STRTEghi5YspU5LsfmL Zjv+H/BPxC+OC2/ibxJ4r1jwLpUk8/2fwzpava3MEI+RfMlO0liybvmRgQcrt34XmB8ePDkPx4g+ IN7YazY+DbjRpNBg12fTpPs8s63DShlIySrBGAwN2eqgAkfV8bKyhlwVPIxXzODw9DGOfLNuCk3y 3steumtnr5HXjPZYvCUZ+yaT2nqua2j62aWnS/e+h5h8N/2e/D/wv8SjWdKvtUnlXTv7Mjt7y4WW KOMusjFRtBUtIrOQDt3SPhRkAeo0UV9FRoU8PHkpRsjzoxUUorZCUtFZ+teINM8N6fNf6rqFrp1l DjzLi6mWONMkKMsxAGSQPqRWzairs0jFydoq7L+B6UteTfEr9oLTPButQeF9Cs5PFfja5eNIdDs2 KEBwW3SS4KxgKCxzyAVJAUlhg6F4D+NuuafBqOq/E6Dw5e3JMsmkW2h29zHa5JIiEhOWwMDvz/E3 3jwyxceZwpRc2t7W0+baV/Lc9eGWT9kq2InGkntzXvL0STdvNpLzPTPHvxR8L/DG1tbjxLq0empd OY4V2PI8hAySEQFsDjJxgZUE8jN3wP40034heGbfXtIaR9OuXmSGSVNhcRyvGW29QCUJGcHBGQDk DlPAnwM0Xwj4gl8T6hcXHiTxjcZafW9QI3bmRVYRRj5Y1wpCgAlVYru28V6R9OKWHeKnJzrWjHot 383t8kvmebU9klaF2+/T7v69BaKKK9AwPGNPgdv2nNUm8TXEiFNPjTwlb3AXyHQoDetEcf65WUA8 h9jnIKYx7NWP4k8IaT4t/sz+1bT7V/Zt7FqNr+8dPLuI87H+UjOMng5BzyK2K4sNQlQc09U23569 /TZeRtUmp28lb+v63FooortMQooooAKKKKAErxnwv+0JA/izxHp3iWOPStFtdXudL0/XpVEFs8sK gvbzEyMEkAJKuSqyAHCow2n2auas/hv4Zs9P1iwXR7eex1i9fUb62uwbiOe4cqzOVkLDqinA4BAw BXDiaeIlKLoStbe/U2pygk1NXPJtT8VeIvjt481nwt4T8RWejeDtHeze/wBa0m5L3t2JEaTbbyJl FG5dh5yCpOWBMdXr39jv4cv4cnsrTTJYdTNq0MWqTXU8jrLswszRiRUYhsMVACnpgCvXtB8M6R4V s3tdF0uz0m1dzK0NjbpCjOQAWKqACcADPsK0q4oZZTqpyxiU5u++y8l2sbPEzhpRfKv63PN/gp8S LrxnpF3o+vWlxp3jHw/5drrFtcIBukKnbMpUBSsgUsNvA7ZXazek15h8RPgRpnjTW5fEGnaxqnhH xK9q1s+paLceSZxxs84DlwpVeAVJAAJ+Vds3wq+IWq6tqGoeEfFlj/Z3izRoIWkl85Hj1OIjb9rh wq/KXU5AXCFlUnOVW8PWqYeSw2J9FLv69nb7+hNSMZp1KfzXb/gHpNFFFewcpmeJPDem+LtDvNH1 ezjv9Ou4/Lmt5Rww6g5HIIIBBGCCAQQRXh3hrWPjz4T0WDTrrwnp/iUafstTeTapGLi+AmYmZWLA BRCoj+cB9zq53fOo+hKK8/EYP281UjNwa00tr63T26G9OryJxcU15nzH8VPit44vPhzN4bvtE1Hw h8QbzyXsoNJEl0dSjRlMxtpYGPlMu0syMWIjwPm35XX+3fFn4H6SNV8Qajb+P/DFpN5V3HBDtv7a yRcLchuN7c5kVy+NgO/DO6+/XFjb3U1vLNBHNLbuZIXkQMY3KshZSeh2sy5HZiO9TVwf2ZUc3VlW lzWsn/mtn9xv9ZjyqCgrdf8AgPdfefJ3wPutL+IH7Uni/wARxXdv4ht4oPten6owe1mi3KsQjWAs pdVjdo2dkPMaNlS43fWVeMfEqxg+FvxK074pLBGmjyWp0jxFIiAyRxO6eRcKowXIkCI5yzbAoVDj I9gsr231Kzgu7SaO5tZ0WWKaFwySIwyrKw4IIIII9aMppPDKph5v3+Zt+d9n+nXYMVP2rjUjtZL7 un6/Mnooor3zhEb7prwL9l3TX1DVPH/iifSrO0Goa7dm2eaNRqkIaQtLBcYJMYBEREZIO7cSMFSf U/ip40T4e/D3XvEDPGstlas0AmRnRpz8sSsF5w0jIDyOvUda5v8AZ18LvoXw3tdTub+TUdS8Sv8A 8JBezSRrGPOuERmCqowAAF+pyRgEKPFr8tXH0oL7Cbfz0X6nXC8aEn3sv1PT6KKK9o5AooooAKpW 2tafe6je6fb31vPfWWz7Vaxyq0kG8bk3qDldw5Geo6VcryX9oTQYLDwpe+OLF9VsPEuh2zNb3uiE CaRNwIinUgiS3D7ZHVgcKjEdWB5MVVlQpOrFXtq/Q0pxU5KPc6/4n/ELTPhj4N1DXdSkjAhQrb28 j7DczFSUiXAJyxHUA4ALHgGvnP4X/D/442vw90L/AIRTxbpeleH5rVbm1tL+CPzUEv7xs4hl4LOx BL52kZCHKL6L8O/hXrvjDxDofxB+IGu2ev3Mdq0+m6Pawq1npzyOHR4pFcrIQuBuIbnaQ7bFavch Xi/VamZzWIquVOKVopOzs7atrv2O1VY4aLpwtJve6uvlf8z5v8FfDb44eBLDVLew1TwdNNqeqNq1 1dXJuGkeVyhkXCxhQrBMEBcgM20g4I7Wy+IPxB8HXkEHjjwjHqtlcSKq6v4NWW6SAscBZbdv3uFC uzSLkcooBJr1ykrso5b9XSVGrJW7u6/EwniPaO84r8gpaKK9k5Tk/iN8L/D3xS0WTTtesI7j5GSC 6VQJ7YtglonwSpyqk9jtAII4rymHxp44/Z/njtfHDS+MPBPmQQp4rhQJPZBlKYnhG5nG4L85JPzZ 3OzBB9A1BfWFtqlnPaXkEd1azo0UsMyBkkQjBVgeCCCQQa83EYP2kvbUXyz79/Jrqvx7HLVocz9p B2l37+vf+rBp+oW2qWcF3Zzx3VrOiyxTQuHR0YZDKRwQQcgirFfL/iuTU/2TPEzz+D/C8mueCtej TzbSbUnhi0y7V1j8xppFZI0kEiDLnJK/eVUAPSr8avHPwy1OwtPij4asX0q/kVV8T+GHkNhZl5I4 1W6E2DEAXLGQtgggKpIbHsYPDYjE0lKXKp/yqSb08r381dJvpc4/7Qpwk4VU01vo7Ltrbr/w573W b4h8N6R4u0i40rXNLs9Y0u42+dZX9uk8Mm1gy7kYEHDKCMjggHtWiPmAPalrBq+jPWT6o8H8XfsW /DbxJfWtzp1peeDfIuXvzD4WnWwjkuxCIre4IVeHt8F4tu1Vd5SVbzZA3kmtfsd/F34c6b4/1j4d fGbUtS1nXolElpqtmhvb2OIOkMR1CSRmSVYnZVkVYxu28xjBX7TorknhaU9bWflodtPGVqel7rs1 f8z8lY/HXjr4XSeA9F8ZeBIY9F+FctxrEnheO5u7CSdvtEUMWoyyuzxzr9snzG0G5c+cNqxMK90/ Yp8efDHWPFQ1+61zxto/jXUpZIHk8X+IWntNamAihjhSZViS6lgjePbG6B1+2HAfajR/eu0egryP 4kfsm/Cj4ueJpPEXinwlDqGsyRJDJdxXdxbNKqjClxFIgZgMLuYE4VRnCgDijg6tGSlCV7dH/meh LH0a8XGpBxb6xfz2fmel+H/E2keLdIg1XQ9Us9Y0y43eTe2Fwk8Mm1irbXUkHDKQcHggitEe1fEv ij/gnTP4M0iK7+DPj7WPC/iePzUnu9QvpInvYpGgxC01sE8tE8t3AETl2cAkAKV0PDOq/tM/sx+E li8RaBZ/G7RY/MYSaVqVxJqtszSRhQ7yRGSZMtJgLG7KM5dURVrpWIqRdqsLea1RyPC0pq9Gom+z 0f8Al+J9l0lfL/hj/gof8M9c8TX+h6npvirwve2MU73C6ro7O0bQ5MyNHbtLIrIqyM25AFEb7iMc +2/DL4yeCvjJpMmo+DfEVnrlvHjzo4WKTQZZlXzYXAkj3FH271G4DIyOa6KeIpVNISTOaphq1FXn FpEPxI+Dfh34mRQy38Mljq9u8clrrOnkRXtuUYsoSTBOMluDkZOQAQCOG0nQ/jv4asItLt9V8I63 bWuYodQ1UXYupowTsaXZxu24zyTxyzHLH3LrRXPUwVKpP2kW4vydr+p5ssPCUudaPyPFP+Ek+OXh 28ja+8JeHPFdrKjDy9EvntHhcFcF2uDgggtwqnpyR0MY/aYbwve/ZfiF4M1jwV++8r7dt+22PMe9 R50Y+ZjhhtRWxjk/e2+4VWv9PttUs57S8t4rq2nRopYZkDpIjDBVgeCCCQQaxeExENaNd+jSa/JP 8TN0akdYVH87Nf5/iLY6hbapZQXlnPHdWs6LJFNC4dJEIyGUjgggggirFfPn/CO+Mv2dL6WTwxaS eLPhzJdLI2iJvl1HTg5YOLf++gYq2Dk8nIHzyn1z4e/EXRPib4Zttb0S6822l+V43wJYJABujkXP DDI9iCCCQQTrh8YqkvZVVyz7d/NPqi6VfmfJNWl2/wAu6OnoprMF6kCuC8UfHr4f+DmkXU/FNgs0 cxt5ILZ/tM0cgzkNHHuZcbSCSAAeDyRXXUrUqK5qkkl5s2nUhTV5ux39JXzn42/bCsorF/8AhCvD up+I3muVsbXUZLZ4rN7ho9yovG93BK/u8KWGcHoTyXg/4pfHrxN4wgiXR2sPtvmJ9l1jRJrfTbUL GrK/nD97uYq4wxIywxncAni1M8wsaipU7zf91XX3nBLMaKmoQvJ+SPrnpS14Ta/tB6z8PrxNO+K3 huXQQzlIvEGlo9xp0/MhHAyyEhBhfmY5yVQV654T8Z6J460lNS0HU7fU7JsDzIHB2MVDbWHVWAYZ VgCM8gV6VDG0MQ+WMve7PRr5PU66denU0i9e3X7jhP2Tv+TWfg3/ANiZo3/pDDRR+yd/yaz8G/8A sTNG/wDSGGiu46D1WvKv2lv+SdaR/wBjn4T/APUh06vVa8q/aW/5J1pH/Y5+E/8A1IdOoAd8eL5p LXwx4fu547LQfEWrw6bqNzul80qQXWBBHg4mMZiZy3yq54IJK+oqAFAHTFcF8cvA914++G+pWGmH y9bg2XumzKAJI7iJg6eW5I8tmwU35GA5PTINv4YfFDSviZo7y2bfZ9UsgkWp6XKGWaxnK/NE4dVJ wwZd2MEo2OhA82M/Z4uUJ/aSt52vdfLf5nLGXLWcZdbW/wAvlv8AM8m/bO0TRL7Q/Bd7rTyW1tHr kVpPeQli8NrKrGcqoBBOIlI+Un5eOpB8n1r4gWPwv0DxHceD/AXii5TVrOWKT4g6y80U8pmd9k6P 5eNpLxsGBjLnZuG4A19C/FhrbxT8Vvhx4TkjkuI47qTXZ2tJAJbVrYAwPINrfuXZpIzkLliuGG0h vXfLTABVT+FePLL/AKzjK1enJReiva7vbz8n/wAE9XKcbDB4qc69NVKd17t3HXTW68rdGeB/sv8A i+O+0nTPC/hvTvO8J6HpYW917EgjuNSco7pCJMNt+eZjlc5ZeEG3f7NofjDSfEWoatYWF15l9pM4 t722kjeKSFiMqSrgEqw5VxlWAO0nFc18avHy/D3wDe3NqZ/7avs6fpMVnb+dJJeyKwiATBBwRu56 hSACSFPkPwAs9Q8I/GG88MRNcS7fD8N94mkuI1lk/tiWQPiS425b93I21QxUjeeW3semniJ4arTw nNzd3tbskv60O+dJ491sUtN5au/VXbdu78tWeo+NPiwPD/iHwn/Ztzp2p6He623h/VPs7+bc2926 fuUGGCrtYHzA2WAIwM1teMvinovgXxN4X0TVPtCT+Ip3t7SaKMPGkilAFfncNzSIoIBGTzgc14R8 S7ZNN8UfE7TdQ1yPw/Lay6f4z8O3moFp0injUQyyk/MSC6pCsTbsZHlxkACrnwx+BenfGjwl4d8Z eOdZ8S69dXSzXL6bqU/kW6l2YHyo1+ZIzhWUoyhgEOADtHO8Zi6lWdPDRu29LvRWdnfrrutOpxVc PVpYeNfk5ls3srtXX/Bte1tel/obV/Fmi+H5YY9T1Wy0+SZJJY1ubhIy6RrukYBiMhV+Zj2HJr5q v/C9t+2H8QNUun1u5h8B+HhHBp8lnZGJ7p5Yt02JJBwyuseQVI27cAbtx9Itf2T/AIdw3N6Z9Nub +zmhS3t7K6vJHjsow+9hAc703OSxO4nLMBgMwOHf+G7X9l3Wl8RaKk1v8NblEt9Y01Z3mNlcNIFj vV8xmZwdyxuiEHG1sPjA0xVLE4lx+txiqSd2k23ptfRaJ6nLgsPWxdWPvcs4tOKWvM1sr6a31Ss7 uy06+geBfgP4E+G96b3QPDtva3v8NzM73EkfDA7GkZimQzA7cZB5zXfVz3gX4g+H/iToa6v4c1GP UrEu0RdVZGV16qysAynkHBA4IPQg10Ve7QhRhBewSUX22NcR7b2svrF+e+t73v1vfW4UUhbapJ7V y/gj4m+G/iI2pJoOoG6m02b7PeW8sEkE0D88PHIqsOQRkjGVYdQcbOUU1FvVkRpzlGU4xbS3fa/c 6mql9qlrp7QRz3MUE1wxjgSRwplcIzlVB6najNgdlJ7GuT+KXxg8M/CHSUvfEF95LzBxbWsSF5rh lXJVFH4DccKCy5IyK8d0H4X6/wDtJapp/iv4oWSaZ4ftEnTTPDESzQTrukZWa4dgr5wkZG0gNhTh RlW4q2J5Zeyormn27er6HrYTLuen9axUvZ0e9rtvXSKur676pLqzhvg78N0/aav/ABV428Q+I7jR 9W1ApaT6f4buki/0fy1j/fKxkYLJ5ZAR8Z8snkEY+w9B0Oy8M6LY6Tp0P2exsoEt4ItxbaiKFUZJ JOAByTmsvwb8O/Dfw9tGt/DujWmko6RxyNbxBXlCAhfMf7zkZPLEnknPJro6nBYRYaHvfG933Zrn GaSzKu/ZtqlHSMeySSS07JBXPfEHwqnjjwVrOgyXMlkt/avALiJmBjJHDYVlLAHGVyAwyp4Jroa8 d/aB8Wa7FceFvA3hiaWx1rxZcyW7ajGqk2lpGoa4kQl1xIFYEY5wGwQ201tipxhRk5q6elu99LHi U8PLEt04Rvo3bySbe9uiZn/AvT9J8efBm98Ea7pNnLHol3caDqMECbYJpYnz5sZzuydyOX+Vt+5g Bwar6d4S+KvwfNxF4bl0/wAbeE4Z3Wx8P3Upt7u1tjjy44rh8g7S7A+YW+SFduC21fUvhz8OdD+F vhe30PQbX7PaR/M7ud0s8hA3SSN/ExwPYAAAAAAdRXNSwaVKCfuyirXX5efzPSWMhhpSo4eN6F9I y2/O6fmne2lzwuz8dfGnwrZx33iXwNpfiG0lRZpY/Dt2UubFAMyBo5CfOfB+VY25KEZO4Gn6f+1x 4Rs4HTxda6r4J1Te5j0/VNOn8ySHcRHKNqEYYDkdmDDkAMfcK4z4teAB8QvA99pltILTVU23WnXq tse2uozuikVwpZPmGCyjdtZgOtFWliKNNyoTu0tmr/lYbxuEmm62G1/uScX+PMvwPONM/aa1q702 LVbr4WeKP7F1Dc+lXWlxLeSTxAkb5YwVMOQUK5LBgSVJAyfHvhz8K/Efjvxpe+LPFnw+HiK2vtdw 7avNcafe28ZZGE3kSO0cluifKIsuSfl3FVr6Y+GHxSTxe8mha1p9xoXjHT4Ea+0y8g8rzP4Xnt/m YSQeYGUOCegz1Un0MKF6DFYRwqxkYVKlTmS8lv5o9KlnH1GM1haHs3US6yvy7qzvfXrrZ9raHIfD 34S+FPhba3UHhnSI9NW6cSTt5jyu5AwAXclsDnAzgZJA5Oewoor2IQjTjywVkfN1q1TETdStJyk9 23d/eFFFFWYhRRWBpPjXTdb8Wa94dtWke/0RLZ7wlMIpnV2RQT1O1QTgY+ZeScgRKcYtKT32Gk3d rob9FFFWIKKKKACiiigAooooAKKKKACiiigDA8aeB9G+IWhtpGvW8l3pzusj28dzLCHK8ruMbKWA PO05GQDjIBHgPjj4T/EPwpqVlrWjyW/i2x8OXsOoWlzdTufEVzbqMzWhnEYDxEyTHZySGwN3CV9O UV5mLy+li9XpLut/L1OilXlS21XYwfBPjbTfHmhpqWmtIoV2guLW4Ty7i0nXh4ZkPKSKeCD7EZBB O/Xg3xOtda+FXxU0/wAf6beW7aBrc9no+u291EUitIzIoW6LJtU4UMvmSklC4UEqwVPeAcgGrwuI lUcqVRWlH8V0fzFUgo2lHZ/1YWiiivQMAooooA5r4hfD/Rvib4XudD1y28+1l+ZJFwJIJADtkjbB 2sMnnoQSCCCQfMvCP7QCeEbo+EvipLHoHiq1dIUvvLY2epRsSEuEdV2oDj5i21Qc/dwyJ7lXHfFf 4a2HxY8E33h++f7MZtskF2sSu9vKpyrqD+KnBBKswyM5rysXQq3+sYV2mlt0kuz/AEZ00pw/h1fh /Lz/AMzsOv0o6V81W37Q+sfB3xD4g0T4qXEepXuyO+0/+wrNwgR3KtArSCMMFGGDHP3ZAZCwC17N 8KPiVYfFjwTZeILGP7OZt0dxaNIrvbyqcMjEfgwyASrKcDOKWGzKhipeyi7T1917q2g6mGqUo87X u9+h4TdeILb9q74saTp9lp1zqPw30DzG1MzSm282aRJlhk2iUMy5jXZhQw3PuADYr6fsrK302zgt LSCO2tYEWKKGFAiRoowqqo4AAAAArxnwS1p4R/aU8WeGtGuPM03VdLXXr61acy/Zr4zBX2jPyb0k V2BBJymCFAFe21z5VTsqlWo71HJ3fpokvK34mmKndxhFWilp8/1CiiiveOEKK8Y1L4oeNfG3jLVd G+G2maW2n6G72uo6x4hWZYJLoMAYIRHhiU5ycEfQbS/sFk9xJZwNdxRw3TIpljhkMiI+PmCsVUsA c4JUZ9B0rkoYqGIclTvZdej9DWdN07c3UnryT9oDx9b6f4dn8Fadaya14t8T2stjZaXasA6pIjI0 8hPCIo3HJ67T0Adl9Uvr2302yuLu6njtrWCNpZZpnCJGijLMzHgAAEkmvFP2YdJTxBpeufEe/tYz q/ifUbiWGZ5mnmgs1k2Jb7mAwFaNvujBVY8/dAXjxs5VJRwlN2c73fZLf562RrRiop1ZbL8z0f4U 6DfeGPhr4Z0nU2kbULPToIZ1lKExuEGY8oApCfdBGchQSWOSeqpaK9KlTVKEaa2Ssc8pczcn1Cii itSQooooAKKKKAKGuaLZ+ItHvdL1CHz7K9ge3nj3FdyOpVhkEEZBPIOa8Dk0Pxz8D7NtJewn+Kfw 3kg+zGxMKG9sITJt8vZgm4Xy3xtxj5cfulX5voukPzcVw18Kq0lUhJxmtmv16NepzVqCq63s11/r c4H4R/FXwd8RtHFv4Sk8qHTYIEk0/wCytALNWUhIgMBOAjLhCQNvBxiu/rzj4pfCePxfdab4i0aS PS/GWiuJtPvzuVJQCSbefYQzQvllOORubGQWVt/4deOrT4g+F7bVIF+z3P8Aqb2xYnzLK5UASwSB grBkbjkDIwcYIpUKtWMvY4i3N0a6/Lo0FKU4v2dS1+luvyOoooorvOkKKKKACkpaKAPMvHn7NPww +Jniiz8ReJfBum6nrVtKswuirRtOyhAonCECdQI0ULKHAAIxgkHQ8T/Af4f+MPE1h4k1Xwpps3iG xvrfUodWii8m78+AARM8se1pFXC/I5KnauQdox3mKWsvZU9XyrU19rUslzPQ+frf4FfEf4WQXl78 O/ifqXie+uIhHLpfxOuZdStHYOu14potkluyqZc4Dh9yggbQwrf8ZXf9Ug/8qlfRVFR7BfZbXzNP bv7ST+R8/at8dPiP8J20Kx8c/DDUvFs15Yyz3OsfDe3lvreO5W4YLB5EmHRfJMTGR3GWZgqkKStr wP8Atd+Evi58TtC8J/Dz/iq7ae2u7zWNRxNZ/wBlRRBBG3lzRKZvMkkVMIcr1IIr3bAr5/1D4a/E b4e/F74n/EDwbFoPiG08T2OnTLo1/JLbXRubTZE0CSDMYWS38/bI3SV4gV2KxbKaq02uV3XXTU1p ujUUuaNpW010vf8Ap79D6AIDDBGRXlHiz9mvwj4i16TX7I6h4Y8QSTGeTVNDu2t5WYqVbjlV3ZJY qoJOSTyc8frPxQ/aI1CxsrXRvgppGj6jfeXnUNT8Uw3dtp374q3nxRrG7/Iu/wDdM2A6/eYNHW/J ffH3S/F2r3kum+A9Z8IW/wBtlsdNsZ7uDVbpVjkNpEZJP3KSM4hV2PyjLkdBUVo0MSrVIXS7rY5a uDjNWqWfzT/IguP2c9X8X3DHx78RNY8TWP7of2bZxrp9rKqOXKyxoSHydvzDawx16Y73wj8G/BXg c2kmi+G9PtLi13eVdmESXC7s7v3z5c8MRy3Q46cVV+D/AMYNF+MHhmG+sZobXWoIkXWNBaUm70i5 yyyW88bKroyyRyqCyLu2EgYrvKVHBYWD9pCN33er+93ZyLC06MtY+956v72eRftEeD7680jRPF+g 6SNZ8QeE75NQg04Rh2vINy+fCgbIVyoDqwVnBjGwbiK6r4a/Fbw58UrG7k0WeRL2wdYdQ028haC6 sZiOY5Y2GQQQy5GVJRgCdprs24BNfMXhnwjc/tBfFL4l67qV4+g6NZJN4Hig0qUi6lSG4SaWR5GG 0Bz8u0KcrIyn7u5/do0KMsNWmoJSjrfa70Si+/k+nW6scNS9HFQcXpN2at26/wBbncftWX1rdfCu fw1FPE2veILq1s9MstwD3MouYmIGeAAByzEKMqCckZp+NtGtvgn4+i+I9hCbTw3qP+jeKYYWJVWd lEN2sIIywkOHI3HDkhCWY12Hg34A+Avh9rSaxoXh+O01KNGjS4kuJZigYYJUSOwUkcZHOCRnBOb3 hvx5onxIvvFXh19PuorjR7hrHULDVbUKJY3DBZADkPFIqsVzyV5IAYZ+TeEnUm69e0ZuyjbW1rtd r3u7+R6+JjCrBU6X2dbtddF93Tfqc9+yeNv7LXwcHp4M0b/0hhoo/ZP/AOTWfg3/ANiZo3/pDDRX 0BJ6rXlX7S3/ACTrSP8Asc/Cf/qQ6dXqteVftLf8k60j/sc/Cf8A6kOnUAeqV458Mv8Ak4L4ygcf 8gj/ANJmr2SvB/Fl5c/Cn472/jDWJrKy8J+IlGiyywsYlikSNZIJ7nk+ZIzCeINgKkaqSwyRXlY/ 3JUar2jLX5pr9TmrRXu1G7KLv9+n6nO+Dvi14d+DvxO+JuleN79LXUrjV1vYNRWOa4ee3kjDRQEr GSBEhUAE4HmELwMmDxr+1lpviDW20rwz4ss/Cujxopm8QXml3F1cSufmAt4Am3C7QrGXGd5Kj5QT 1virXNO8RftIfDONby1W1t9Mvb+xuIZVn+3NNHt2bVPyKI0MgkPyvgqOQa9x8pP7i/lXkUaGKrxq UaVZKEZPo7tPXVqS726PS5y4WVeMpqEotJu11fz7+fY+HNP8TeELXXoJPBum6x8TfiBFPDOfE+vQ 3NxbxgIiNN5EZMpVDgKGQspIIZtqA/SfwH+Gur+ArXxPe+Io9KbXdd1eXUp59LDFSrgEIWdQ2Fcy kKc43nnJNHxd8I67P4m8IeMvDenxa3f+G3ugdGadbY3S3EYjLLK2VUpgNgjkZ5BAB5Xw/oPx78WW 9u+s+JdJ8EoPOcpZ2Md5cFmk+RHViYwqrnaVfOMbtzEkc+Fw8sDiJKcHOS25VZbLW7e+rWrvoV9Z xXtZe2cpPpbSNtPO2/S/Q8L/AGxtU1y8+NUVhPZPdR29tbf2FbwkSrIzuNzvAwcSFnEke3CltkeQ QMN9Bfs3+H/ENh4X0PULj4i2vifwy2mJBaabbadHDHCy7AMTcSNsCMmHUHJO4AjFdH8M/gjaeBtW v/EOqanceJfGGo+Yt5rNxmPfGzKRGsQYqqgImOpGMAhcKMC8/ZJ8B6prb3N8mo3ekr5htdBN86WN k0jK0jQImGj3MCSobb8x44XHRhMBiaNaeLkrubvZyat620f49D7nB5v7fLFl2NtBRbaajGbs+mrV nfrFpau9+vtdIyhlIYZHvQAFUAdBxS19WfLnhWpabb/Dn9pzwzLpkMcFn4y0+8tbuztUEKfaID9o +1OF4ldg7JkgEZJ3HOK90rkNc+F+ka98Q/DnjOXzItY0NJ44mh2ATJIhXbISpZgu5ioBGCzdc119 c1CnKm5p7N6ell+tz08ZXp140XH4lG0n3alK3/kvKvkZPi/WLjw94W1fU7Swk1S6s7SWeKxiJ33D qhYRrgE5YgAYB69DXy18O/jD4a+E/gHxB471nXbDxF448UzreS6Vpt2XkjypMNsQWYxrGC2WIG0H Z821N3qH7VHiu6s/BNj4T0ia3TWfF17Ho0JllA2RyHbK5XaxK4IQkDK+aCDnAPXeAfgd4K+Hlppg 0rQLMX1jGVTUp4Ee7ZmBDM0pG7J3N0wMHAAGBXBWVSvieWi0uVbvo32Xe35ns4OWGweA58Um/ay+ Fac0Y62b6Jytsr6PsjifhH8JNU1Txde/Ef4hWkieLpbqT+zLNr3zU0y02siRAR4RiQ75+8DlW4ct Xua4A4GBS1l+JvE2meD9DvNY1i8jsdOtE8yaaQ8KOgGBySSQABySQACTXfTp08LTevm2+vmzwMbj amLn7WrokrJdIpbJX2S/4O5qUV5N4S/ae8B+KtR0vS2v7nSNb1Hb5Om6paPDJ843R5fBj/eKVZcO dwdQOTivWAwboc1dGvSxEealJNeRyypzjGM5RaUldea7oWvnDxteS+B/2r/DuravpNx4gi16zXTt HuIBGDpgUnzzs2lnwXDmQsu1JpR84GB714g8VaN4UtEuta1Wz0m2dxGs17cJCjOQSFBYgZwCcexr zL4geLPhF8WfDmoeH9b8UaJPbq+0SG/ijeGXYGWWFycEgP8AeXK/eU5+Za4Mc6copc6UotNa726f 16m2ExGHoV08S3y2adnZ6prur2ve17O1ma+uftIfDTw9aJcXXjDTZkdxGFsZftb5IJ5WLcwHB5Ix 0GeRS/Dn486F8VfEV9p/h2x1W6061jLf23JZtHZSMNmYldiG8weYPlKjhSemCfIfgP43+FnhswaP rdv4V0fxfoMPlHXIVt1t71eUEsNzuJZmjKF9xViXb5eGC/UkZiP+r2f8BxU4PEVMXFVVNW6pLX0b v+h21J4D2HNQpzbltKTSX/gKj/7cSUUUV7B5J4NrV9B4b/a80q71N/sNpqvhn+zrK4mUrHPci73+ UrYxuxjjPVlHVlB94ox7Utc1GlKm5Xd03c6q9d1+S6+FJfcFFFFdJyiUtY+meLtJ1jxDrOh2d15u qaP5P26Dy3XyvNQvH8xGGyoJ+UnHfFa9RGUZq8XcbTjoxa8Z+FNrHZ/Hz4yxxtIyl9KkzLK0hy1u 7HliTjJOB0UYAAAAG98avi1/wrTT9MstOsv7U8U67N9j0ixY7Y3lJVd0jkgBVLpxkElgMgZZZvgn 8K0+FvhPyLuWO/8AEd+5udW1Qbme6mZmblnJZgu4gE4z8zYBZq8itJYjGU6dP/l27yfa6aS9Xe51 wXs6MpS+1ovvTv8AhY9Cooor2jjCiiigAooooAKKKKACiiigAooooAKKKKAKWtaPaeIdHvtLv4vP sr2B7eeLcV3xupVhkEEZBPIOa8D8HfEFf2a9Fl8I/EXU725W3ulGh6glq0kVzYsUXCsMkGE7i8bH KqVCbxsFfRNJgN1Ga8/EYWVSaq0pcs1pfdWfdXVzenUUU4TV4s4rwX8avBHxBmWDQvEdnd3Tu0aW kjGGdyq7jtikCuwC5OQCODzwcdrXE/Eb4P8Ah34lxQSahDJZatbPHJa6zpxEN7blGLKElwTjJbg5 GTkAMAR5l4a8Va18B/H13ovxI8WHWND8Qf6VpWuXeUWO4DIssJjAbyV/eKeWEShQRgswXleLrYWS ji0uV/aWiXqm9PxNFShVTdJ69uvyPoSikpa9o5AoorzfTf2hfAupeNrnwmNY+z61Detp6w3EDok0 ygZCuRt+9uQZILMuACCpbnq4ilQcVVklfRX6mkac535Vex6MVDdQDXz4dW0D9n/45HTDL/wjHgrX tL+0rEyyGzbUzc7SykgrFiMruAKoF2ZwAtfQgIPSvMv2kfBU/jv4O69YWVpHd6lCiXdqrRl33RsH YRgAnzGQOgx1346E15+ZUpOi69FLnhqv1XzNsPJc/JP4Xo/8/kc3+ynEl/ovjXxB5cczax4ku54t SS0a3F5D8u10D5YR72lwpJ2ksM5zXuVc18N/E2i+MPA+j6t4ei8jRpoAtvB5Ii8kIShj2DgbSpXj j5eCRg10ldGX01Sw0Ixd9L3731Irycqkm1YWkPQ0tFegYHjHwAa40vxb8VtBvIo4bqDxJLqWwSFn 8q5AeJiAu0AogIwxblgyrgbvYL2+t9Ns57u7njtbWBGklmmcIkaKMszMeAAASSa+e/iLqHizT/2m oR4M0uz1LWJ/CkcJbUJdkFtEb4l5nAIZwMAbVO75sgHGCvjn4P8Axa+L2ly6f4m8V6Fo2nb4Mado tvM8M+HJd5GfD5VSCqZKsyrnYRur5ahjKmHpToUaTnKLaXRd1qz0pUY1JRnOSiml5/gRfFr4o3fx evdU+GHw8it9ZlvLKKW71211MRw2sZmQSqcL+8XYyhtjE4kYbSVIr0Xxx8SvDfwQ8L2Ok2yfa9Si ghtNJ8O2khku7jjy4VC/M23KY3kHoQNzEKfP9L/Z/wDiR4A0q+Hg74kWdvPO/mfYW0KG3tnYuWZj jzAhw55VOQsacKi7c3SPBeq/Df472N746/sbxjb+Kp0itvEV1ZJBNZXdvCDDgbfLjZyNiqrbnKKw IKlTwqtjabdStBxnNpcztyxWtrWbb17/ADOhwoSXLCScY621u3pfdI9T+Df/AAsm4ttQvPiH/Z9u 0+37HYWe0vB+8mL7yuQcq0Srh2+VBn5txb0mkpa+vw9L2FNU+Zyt1e55NSXPJytb0CiiiugzCiii gAooooAKKKKAEryf4p/D3VbXV7fxx4GFxH4nt54De6ZbTrDDrUCttMc287Nyoz7ZCCQOACdhX1mk 7HNc9ehHEQ5Zadn1T7oyqU1UjZ/8Mcz8OvHVp8QvC9tqluv2e5/1N7YsT5llcqAJYJAQpDI3HIGR g4wRXT15B8HVt7j4n/FS90iSRtBk1C3g8vyxFEl/HGy3exN2SSTEWkKruJP3gu4+vVlg6kqtFSnv qvWztf57k0ZOcE5b/wCQtFFFdpuFFFFABRRRQAUUUUAFFFFABRRRQB5TB8Ddv7Q8vxPk1KzijXTH sIdN0/Tfss0jsIg013cpJm6wsW1Y5F2IAhUBk3N6rS0VEYKF7dS5TlO3N0Cvlv4oeMNQ/Zr+NEWs 2MVnL4R8VrLc6hpELeS3nwqpmuV3ts85gy/d2+b91l3hZD9RswVSTwBXx78RI7X9pD4oa5L4J0q1 1i30DQruwvdTuHjZLuaSOX7Klur5ClJgzCYFc/P823bv87MK1WnSUKErSk1ZLr306o93JMDh8Viv a4yN6VNNt7JXTS16Xbsu7+9fWeg65Z+JNEsNW0+Xz7C9gS4gl2ld8bqGU4IBGQRwRmuM+JXwlfxt qen63o/iC88J+JdPQxQ6lYorCWMyI/lzpwZUBQ4QsFyxJBzipfgLqmmat8H/AAnLpF1JeWMWnxWq TTQ+S5MS+U25MnaQyMDgkccEjBPe10unDF0Uqmqdn/wzPKrReFxE4R05W1r+qPK/2T/+TWfg5/2J mjf+kMNFH7J3/JrPwb/7EzRv/SGGius5D1WvKv2lv+SdaR/2OfhP/wBSHTq9Vryr9pb/AJJ1pH/Y 5+E//Uh06gD1SoL+wttUsp7S7gjurWeNopYZkDpIjDBVgeCCDgg1YpKTSaswPi3xB8An034peJPD NyLbTNK8XWd3c+HYop98SXcMiyorARDytqGTop2xysiuxJJ7QftuaVo8eiWmp6BfvqHkMutLGnkt ZXC5UxpG5+bLqTyw2qy5Jbco9/8AG3gPQviLojaT4h0+PUbEusgRiysjr0ZWUhlPUZBHBI6EivnS ++PVr8Fdc1v4U+JtO1LxlfdNHa6XfPq8FwpcRy+YSZAGZofMjVlOxl2AoVPxOIwtTK5SnQqckZdb c3nZrp1s/O3Y8j2H1arzQ92D3tr5/Lrr527G7pHjzx98ZfGWpadoviez+HcenxtKdHudMabVthKh GnjnUJgj58xMdolRW3ZBqOz/AGtLzwPp62nxL8G6xpGtiaWJZLG1H2W4CEfNGZJBnGQDtLg8MDhg B53+z3r3gj4N/ES5s/Eiaz4Y8TrZDT7ptUljks/OaVSwXZGCikLE6uzFNrPk4VXf3/Xtc+GHx78F HT7jXNOvLC8nSCFmmWC5huWLrFsWTDJKSr7QV+YBuGUkHDB4itiaDqU8Qo1tfdbuvmnt8kj2cTgp UantcO3Jeez/AEXyOW1T9ozx7q15LbeCPgX4o1kWuPtc3iK6g0KMbgCnkGUt5/Rw2MbCFzncKs+C 7/xL8Cfgr4k8XfETWpte129uH1ybTXZ/L02WdIgumwt5k2IkmyisDtAfOMZJ838feGfhh8P7SaK/ +JfiTXNRsnurm00dNZMpS/UOQxMUTeRMJXJDvj5skhhuFYHhH4a6j4m02DUNY+EGq+Ob++tbe+bW tU8XCPz0kjATaQFGMJnYxZ0DKGOCtdEs0rwl7O3NO3RtpeqjF/j+B10PbScHUoJU7q/vWbXWzf6f M9o+Mnj7W9a+HPhPRNItrzQfGfjR7dYII5Zo5tOUeXLOzuibgI8hH4U7WZsYUivWofG/h6bVoNJT XNOfVJt/lWa3UZmfYzq+1M5O1o5AcDgowPQ1+fWh6LrXgvxzJql5a6p8LNDv5Li2i1S80ma5Ngki OVijZkDl9o2B0IfBY5AzX0x46/ZZ0zRPhpfQfD2wgg8VoIJotRvJGe6doWD5hlLAQSsR95QFPQhQ QyZ5fmWMxUqteNPayab6LsrbvXVpfOxnXjUdWFGnBRjfVt6a9mr3S/4J9EVxXxo0zxPrHwx12z8H XJtfEUsIFtIsgjb7wLqrn7rMm5VbjBIOV6jyL4Y/tE+E/CGlX8fjP4h32sa5cXJmnS/0O4tZLIiN ENuYkVkUoUbOw43FupyT6ndfHr4f22gw6tJ4s0yO1uLU3kCvcKJZIxuGViPzk5Vl2hc7lK4yMV9N HGYfFU5R50nbXVXX3HZTw9ahiv3Mfackl0bTa1s00nr2aWh4p+z74UWw+NF4PGNprlv41s9JWaxj 17WItWJtnlZHkSRIh5ZVvlxuyRK/GMmvZvH3x+8EfDXVrTTdb1mOO7lkMcsVupne1GzeGlVMsoOU A4yS4IG0My/NXwn8XeJ/7e1/xVpfwy1zWPHHia5uHsdSv5JY7CCwkRZIkMzkI4QxqAMJuXAVxwtf RPwd+BumfDvRbO41S2s9X8Yl5bm81x4zJM80md+2R8vjadueN3LEAsa8vB1K8oKlhV1bcpJ7X07X bX3HpcSKrDMIKcVayuk9Fa11HWTSvezfnp0Ohh+Lvg+48Ez+Lodfs5fD8CbpbxHyIyQpCMo+YSfM v7sjdlgMZIFeJ/DTwPP+0B4m1bxt4tOut4T/ALQjuNE0DVpisMiCPiR4dgQx4dNuwkH5wzScs/qv iD9nX4c+KPEEet6h4Ws5dRV/MZ4y0SStvLlpI1ISQliclwd2cHI4r0VVEahVGAK9GeFq4qcXibcs ei6+v+Wp4GKpYKrSioKTldvW1kui0+Lu3p6HE/Fr4V2XxU8Lrpkt3PpV9azJd6fqVqxWS0uEzskA BGcZPGRweCDhhwNx4R8ZfAvRk1/SNc1z4klI0j1TRdUmeaS4Y4US2hVXaIq7ElDvBQnJyimvdqSu itg6dR88fdn0a/qxEqs6lONGbvGLuvLv9/bY8E8F/CG7+IXxB8Q+NPiX4TgtpJfs8Ok6TeXwvktk SJll4X92VZm3AEcNuOAcMfSP+FK+Af8AoS9A/wDBZB/8TXaUVNHAUKMbNczbbbaV238jhp4enTVr Xe92cfN8H/A1xZQ2cnhDQ2tYXeWOE6dDsR3ChmA24BIRAT32r6Cvnr4lfCzSfgv4+8Ff8ITruoeD 7bxBejTri1sL55XecZ+zTGGRsSxJI4Eqs2NrKAMsSfrNgWUgcEjrXlPw3+Adv4S8TSeKvEWuXnjP xc6tGupX4CpbKzuxWCLJEQIfGASByF2hiDjisHCsowhBeu1vu11Pp8txiwtOpGpUfJa3JraTadv7 q5Xrd69kWfCfw18Z2PivT9Y8SfEm88RWtlHL5Wm2+nx2MMjuoXMojYiQAZIBHDYII5B9PopFYN0I P0ruoUIYePLC+vdt/meLOcqju/yt+QtFFcZ8SfiIfh83hkDT/t/9ta1baR/rvL8nzd37z7p3Y2/d 4znqK1qVI0o883ZGMpKKuzss461438Rvjbq9p4/tfh/4F0i31vxRNCtxcXV1KfsmnxlhzME+b7uS QSpG+PG8sFrv/iTaapqPw98R22iGRdYm064SzMMvlOJjEwTa+RtO7GDkY65rgf2VfC/hbSvhHour eHbOOKfVLaN9QufnLzXEa+XICX5wsgkAA+UZJUfNk8OJ9pVnGhTly31b627L/Poezh6NGOGniqt2 01FLpd3d5Pto7K2vlY3PhH8Otb8K6h4k8R+KdSt9Q8T+Ip43u0sEK2sEcQZIY48gMcK3LNz0HJBZ vSKK8w+OvxG1Lwfolno3hiGS88ba87W2kW8cHmAFdpllbJCqERs5bgEgkFQxFP2WXYdvovm23+rZ 5/v4ipbq/wCvuSMLQ7GTxt+0/wCJr/UJt1v4Lsra1021UvtEl1EXkmPz7d23eh+XBBTugJ9srg/h B8KbT4U+H5rY3P8Aa2tXsz3Oo6zJGVmvZC7FS+5mPyhsY3Yzubqxz3dTgKM6dJyqK0pNt/PZfJWX yHXmpStF6JJL+vN6i0UUV6RzhRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAV5X+07Y2F18EvE st9p1vqRt4RLALidYfJlLBVlRz/Eu4kKOX+5zvwfVK8G+JHxwl1zx9bfDLwVb6PrGsXfnQ6jLrQe SwjCxOz25Ccu2FIbqF+6QSW2eVmdWlDDShUfx6LrdvbQ6sNGcqilFba/JHo3h/xtYaX8OPDeseJP EOnxm7sbYvqVxKttDczNCGLJvCY3YZgu0HHYYxXGfAn4/T/Fa6mstV0eLRLyS1bUrARTmUXNr9ok hLfd+QoyKhycuSWCgcDz7wv+zD4w8TeH4fDvjXX7fSfB1hey3Nloeiosjqxeb5lnkUsq/vNy7zIS r4baw49e8dfs/eEPHixST2txpV9b2S6bbXmlXDW7QWw3AxIgzHtKu6EFD8rkemPKo1MzrKFWMOVR Xwv7Xfva3Tv1OmccNC8G7t9V0/L5/geg30k8djcPaRxT3KxsYo5pDGjvj5QzBWKgnGSFOPQ9K+Tv gr8FdD+NnhO98a6ydV0fxJea7cX66jprNa7PmDBYCxcNGHJO/AYMpXPyZbeX9lnxpp9vd+GNL+JV xZeBZoJlS2eAvMvmSKzQlQyqVKoMuGXJaQBAJH3e4fC/wQ/w68B6V4ckvY9RaxRo/tMVqtsHBdmH yKSM4IBOSWILE5JpOjVzPER+t0OWEU92mubTa2uncfPHC037Gpdtra60/roeQ/sa+J4Na8P+KLGD WtV1G10/UAljZ6owd7WyKYg+YDAJCMCisVXy+FXJLe6+IL3R4LNbTWp7KO11FxYrDfOgS5eQECEK 3Dlhkbec88V5Dbfs+694D8QazrXw/wDGkmmNqTi5utN1m0W9S6mV5HVHnJ8xYzvKkjc/JJZjjGd4 G+BviHxzqN9qvxnnPiC7s/O07TbENGtqIWHzXKiLb8z5IUkK67ATyE2GEnjMNQhg5UW5aq/2bX73 b28grRo1ZyrRnZduv6LfzMDRfiTp37M+qWHhOfxVpfibwd9qnhEdsN2qaSxkZmEwjyjxox+bO2Qt I21cJtr3HQPjB4L8U6tbaXpPiXT7/ULjzvKt4Jgzt5TYfA/Mj+8oLLlQTSeC/hD4P+HMr3Hh7Qrf TrhoPs7TgtJIY97PtLsSTlm5OckKgPCKB4H+z5YW/if43S+LNM8ER+HvCUmk3J0idLcFC/2vazs4 yqTHM67ARtjwoygBMU54vL6lKg2mpvSOr5UrX17eo5KliIyqa3XXTV+n/Dn1dXjHxf8AHXi21+Jn g3wb4S1HS9NutTjuLt3uh57uYY3dYpY8ZjhkKlfMUljhtuNhD+qeJPEmmeEdDvNY1i8jsNNtE8ya 4lPCjoBgckkkAAZJJAAJNfLEHxksbL473HxIi8O6q3gW808aRNryaU8MS4nVRcM43eaNyKuTsYKQ uwsgDd2bYqFKMKXPyttXtuo31fp0uY4WlKbcuW9k/v8A61sey/CP4c+KdD8UeJPFXjjUdP1TX9U8 u3txYIxjs7ZCzeVGzgFVLMMoB1jDFmYkj1Sgc80tevh6EMPTVOG3nq9TkqVHUlzSCsDxp4F0L4h6 G2keIdOj1KwLrKI3ZlKuvRlZSGU8kZBHBI6Eit+kracI1IuE1dMiMnF3W54na+KPGHwT1C8tPFkW o+L/AAQuw2XiS2hWW6sYwPmW8RMMyoqFmmAJOMnJcKnrWg+JtI8VWb3Wi6pZ6tao5iaaxuEmRXAB KkqSAcEHHuK0jg8Gub8K/Dnw14H1DVLzQNIt9Jm1LyvtS2oKRN5YITEYO1Mbm+6Bkkk5NcNGhWw8 1GMuaHnuvR9fn95tKcZq7Vn5bM6WiiivRMAooooAKKKKACiiigApGztOOuKWigDyv4FyPZz+NtG1 BpJNfsddme8uLm7Wae6jkVGtp2VcLGDD5aBVAUeUcAHKj1SvFfh6lxc/tLfFOaGaO2sre202G4tk jLG6kaHckzOWO0oodNqgKQwJGRk+1V5uXy5qNuzkvubRy4aXNT9G19zsFFFFekdQUUUUAFFFFABR RRQAUUUUAFFFISByeBQAtJSK6t0IP0NK3KkUr9gPmP4uftZ6bN4f+Iei+GdD8TXU+jSyaJN4ihtG h0+C8ICSBbjO4PEzD+EZbbg4ZWr03w54bvvg/wDAFdP0eyjuta0rR5JVt4RJMk955bSMFHDsHlLY UYPzYAHAHjHwM+G+k6P4B8cfs361bQWmu6SrX0erpF5a61bzyGS3v0jyru0LLFDIMsqmJE8xgcD2 r4I+PF1rwxZ+Htcn+y+NNIh+yanpt5cb7rdHtXzznl1kBR943KfMA3HrXhU5TeJvWfxKy8nfVfl6 2PXr42lQpwwcI6c3M3fSWi5fT7X3nh/w5+KMmhQ6No3wwY+OvEHiKe48Q68dUX7O0LbFEseI12QN I6FVLMyqSudyurV6JrXx2+I3hfT5LzWfg/PaQ8LHLHrkE0atkEtMyr+5iCB2MrfKCADgHI9os9B0 vT9UvdRtbG1t9Qvtn2q5iiVZJ9gwm9gMttHAz0FU/HXhn/hNPBut6D9o+xnUrKaz+0bN/l+YhTdt yM4znGRnHWuiGFrQg7VXfoklb8bv8T0auZYKtVTeGTT3cnLm31+FxXl8Oy7nEfsort/Zb+DoznHg 3Rh/5Iw0UfsoHd+y18HD6+DdG/8ASGGivWPmHvoeqV5V+0t/yTrSP+xz8J/+pDp1eq15V+0t/wAk 60j/ALHPwn/6kOnUCPVKWsi38W6LeeILnQ4NWsptZtkEs2nx3CNPGh2nc0YO4D5l5I/iHqK16lSU tmVKMo/ErCGvz7/bV8Tnxr4o8OI01lPrHhXV721+z6dMssNxZXIx5rPuzFNAYFjkhYZZn3KdvT6w 8e6P8XtT8Q3r+F9c8P6RosUJWziuIXkmnkdEUmYlGC7CZHQpkEhA6sCceBfGL4VaT4Fs5Y7vW7fx R8UPEOt2U1jHFYWdsCxZ0BlgOR5Tkyb2+67iPcOGJ+RzuriK1CVOjTdle7drNeWt732PQo4eFSlU XxScXZLfXe/yv/W3T/tKeBPBvjfwfpPxS02XzrBZrYald6cwWS7s2dYjtVlx56EhRv24wytnaoHY +FP2W9KtNQkg8R/2f4p0W3gePT57m2ePUUVx5YillRwsixRKgRipZS3yeWEUHkP+Ed8R/CObwt8N /Ef9j+J/hpr050tZZbWeGRJHdpcsybtkrSS4TkgiAEGI7nGp8QYPiz8BdD1S58DSDx1oxszdS3Xj DUDLJpskbbpX+XY0kbRDAjU5DAtx92Tio0MPKtLFYihrZcyttK2rt1T018jjnOtg58tOf7qW3lvd +Xmep/DX4E+E/hY1vcaPaSPqUVq9m2oXEmZpoml80hwoVGIbADbd21VGcCvQeB7V83eHfBPxk8fe BvCmraV+0Ha28kmnD7dcWXhS0uYbq4MsjM6l9hUIrJDt2Kf3O4qrMyjS8WfAf4seMJobS5+Pepad oLxWcd5a6RoNvZ3crRJEJ3jukffC0siO/AIXzNuGUYP1eH5KVNLD0rR6Wt/mbOMar5p1U7+r/Q9/ wD2BorG8H+D9L8B6BDo2jxTRWMcs0/8ApF1LcyNJLK8srvLKzO7NJI7EsxOWrZyPWvQW1zke+h4J 4nvk8I/tbeHL3Uk+z6d4g8PyaPZ3BdAhuEuPNKNlgRkFFHHLSKBnnHZaX+zh8M9Ju726g8H6ZI94 /mSLdRfaI1OSf3aSbljHzHhAB0GOBjsPFfg/Q/G2kyabr2mW+qWTZPl3CBthKldyHqjYY4ZSCM8E V49Z/Fa/s7AeGvhJ4F1HxNpunwzQ22r3t00en/IQo8meZj9oRXLLtDrxHhCVGR4tT2eFqSlWSabu tLyvpfRL8T3PrdarTjHDtwailKzsnZtpvVeWnlc95WNVxhQMe1Oqlov9of2PY/2t9n/tTyE+1/Y9 3k+dtG/y93zbd2cZ5xjNV/EPijR/Cdmt3rWqWelWzuIlmvZ0hRnIJCgsQM4BOPY17HPGMeaWiPCk 7as1M46mqOta9pvhzTZdR1W/ttOsIdvmXN1KscaZIUZZiAMkgfUivBNHuvF/7SepT6hba5ceEfh3 aXs8VnLo7y2+oajsAVZPMZQBGSXPA4IKFSVDrb8Xfsp22u+Hb+C48XeJ/EVwtvM1laa9qpltVujE 6xSMAmRtZs5H0wQSD5X16tVi54elzR6Nu1/P0MsLVjXqxUk1Tb3027pHvysGUEHIryH9oD40Xfwp 1H4a2GmNpst94o8V2WjTW16S0n2OQlZpYlV1O5CYhuO5QZFyPmFeP/D/AOJPxZ+Hvgzw9os3hm51 641LS5I9Is5LA281jNDOluqT4YEQJH5chd1BJmUbwMsN/Sf2U/Feraxpni/xR8RtS/4S6wjnltZI GNxDZXLyMd8IkAVYmj2q8KoobG3dtAAzjj54iFqNN83W+lv6R9NSy2lTc54qqopNxXVyavraN7K9 tfuvqfT46Clr5a0b9rG4sfhvq0s89v4h8WrffYvD8KWM1s2sws3lRXXlAHOXSYsqYAKBPkLLn2z4 bfEt/G0msabqmkSeHvEmjPGuo6W863CxLKu+JllT5XDJzxggggjoT1UMxw9dxjF6v+rX2vpseNWw 9bDKMq8HHmbSvprHf7r/AJ9mdxXPap8QvDeieIrHQb/WrOz1e+Tfb2s0wV5BvCADPdmbCjq2GwDt bHiusajr/wC0t4q1/QfDviP+xPhxpmyzvb+xiMkuryMVaWOOQqAqKoZSVJBDAkSJIAvaxfsu/De0 0jVLG08OQW7X8Bha5dmuJocqwDxNMX8thuJBHcDOcCsvrVfEe9hYpxXVve3Zfrp8zkq39nCph5xl e999LO3a2vkzU+P3jm8+HPwh8Ra/pwzfQQrHA+R+7eV1iWTkEHaXDYIwduO9M+BnwtPwq8HtZ3F/ calqmoTf2hqNxcTebuunjQSlWKqSpZMgt83PJryP4jeGfFfhnxN4C0DxX4kuPFPw7vtbhtSHiiW5 klJ/0a2us8TxZQMzYy37wsMiOvbviV8VNE+GXhnU9Svru2e6s4Q8dg0wWSeRw4iQAAkb2jcBtpAC OeitjGniozrVK1dcqgkrP72/y+4645hy4J0JQ5PebbfVWVl6LX7/ACO0rxr9qbT7iPwDpviW2iku 5PCusWeuGyiQk3CxPhl3DOwBXLF8HAQ8dxl6K3x71yzt9eN34TsDc20Rj0O4trlEQOC7PISPMSZf kTZuK8t0KjdT1HwF8d/FFvLbal4w8OWNlcP5E9rb6etzE9u7SGQlZYvmKqyIqE4ZR8zAglytjHWp OMKM3fbRffqzLB436viqc3BtJ69muvnZr59j0if45fD6FbeJ/GWiM1wfLXy7+J1B2FvmIYhRhTy2 BnAzkgHxT9mP46eC9A0PUfDl7raaLZjWLt9Es9QQxi3sWxIivNygO4yffcknjJ+WvQfhb+zJ4f8A BOj39t4htdH8XXt1evdi8n0aGLylZVHlKnzBUBUkKuFG7AAruvF3wp8KeOPD9loesaRHNpNm6SW9 rA726RFEKKF8srgBWIA6e3ArP2eZVXGteMWr6O+t7aNp6bdLixEsRRnUo4eopU2+z1ts9bNNXfTr scT4i/a2+GGgQzkeI11C4RJGSCxgkmMhRmXaGC7ASyHG5gCCrZ2sGND4J+CdY8ReLNU+KHjWxitN a1JETStLkZ5H0m1CkbfmOFdwcsAoIy33TI6Dur74J+Br7w9qehjwzp9npupeX9rhsIRamXy33plo tp+VuRz3Pqa+Wd3jf9ln4oa5ofh7R7jVfDPiK4W20SK4YpZfa5yPIG8lvnXDRlS6M6oGJACkVW+s Qq05YiPPH+6no+7Wt/Lt2Pt8FQwGMwtahgZezrW19o42lFNXUZe6ou+rTTulo1qj650n4keGNe8S X3h/T9bs7zWLFPMubSGUM0Y3lCDjurLhh1XK5A3LnpFYN0Oa8B+Hv7K/h2H4U6DpniHTEtvFECfa X1axxb3ttcMWdcTRk7jEXCgkspManHQCtr2mfET9nnSdT1XRdTuPiJ4bH+k3Ftr91/pmnxxhWldZ if3isiSDaANrGMhW+cN2xxFaEFUrw0301t6r/K55FTL8JWryoYOtdp2XNopa2upXsr7+9btds+iK K4n4S/FrRfjH4XOt6KLiOKOZreaC6j2SRSKAcHBIOVZWyCRhh3yB21d9OpGrFTg7pniV6NTDVJUa 0eWUdGmFFFFaGAVR/tvTxq/9lG+tv7U8j7T9i81fO8rdt8zZndt3cbsYzxV6vMfEH7Ofgnxf4m1z XNesJNWudVe3kdZZjGIDDEYx5bR7XAZTlgWIJVTjgVy4iVeKXsIpvzdv0ZpTUG/fdjurfxRo95Na xwarZTSXSJJbrHcIxmR1d0ZAD8wZYpWBHURuR9041K8mh/ZV+FsEdxGnhZCJk8tjJeXDkAMrZUmQ lTlRyuDjIzgkHLude8WfAT7XceIbjWfiF4QMAFtd2drE15pnl7iRcAbTKrR4JnLfejOVG4E8SxWI oq+Kgku8Xe3ron91zb2dOelKWvmrfqz22iqWi6xaeIdIstTsJvPsb2BLmCXaV3xuoZTggEZBHBGa u16sZKSUou6ObbRhRRRVCKVrrVhfaje6fb31vPfWWz7Vaxyq0kG8bk3qDldw5Geo6VdrzDx/4b1P wt4stfH3hmzku5I0MOv6PZ8TarbBcRuoPytNDyVGAzrlA44UzeA/jbaeMPEEujahoOseEr6TL6dD r1qbdr+NUUyGPPG5CTlASdu1v7wXzljIwqOlW91307NdNfw9Tf2TceaGqPSKWqOr63p/h/T5b/U7 6206xix5lzdSrFGmSFGWYgDJIH1Iq5vX1H513c8b2uY2ZyHxT+JFp8L/AAv/AGnPaXGp3lxOtnYa faoWku7lwdkQwDjOCc46A4BOFPE/s3+G/F+l2viLWvFFlZ6PH4iul1WHSbYOHt5nDCZ5A+5lMmIm 2Fzt5GE5WnftdXttbfAXxBFLPFFJcSWscKO4BkcXEblVHc7VZsDspPavXbBbiOxt1upY5roRqJZI YzGjPgbiqlmKgnOAWOPU9a8Xl9vmPvS0pxTS85XWv3HZfkw+i1k2vut/mWKKKK904gooooAKKKKA Erw7xt8A7jwva3Wu/CS5l8KeJVd55LKGYmz1DIb920UhMaldzeXwEUsRgcMnuVFceJwlLFR5ai1W zW69H0NqdWVJ3j93R+p8meOfE3j74of8I14H174d/Z/Ftvqi6l58zZ0h44tp3ScP5kWyZkkVXyG2 YJL+WPU/2rrW+uvgT4hisLP7X/qJLgKW3xxJMjs6qFO7G0ZyVAXc2flwfX/wrzf4vfE3VfBVzoeh +HNA/wCEg8Ta99pWxglnSGFPJj3s7sxGcblO3K5Ab5gcZ8Wtgo4fDV3XquXOuW9tey2Wr1OynWdS rT9nBLld99O/XZaEX7N/iPUfEnwj0h9avJLzXbOSeyvvtB/fxSRyuqpMOokCBM7vmOQTknJ9Orxj 9mDQ9T0Pw/4vXU/D8nhiS48SXdxFprptSKNkiwsZACvGMFQyjadvFez16eWOTwdPnvdK2u+hzYm3 tpW2uFFFFemcwUUUUAFFFFABRUF9ewabZXF3dTx21tBG0ss0zhEjVRkszHgAAEkmvnz4ZftAeLf+ ELsfEnjHw3JfeHb6SeUa7oaeZ9iQTOpWe3HzrHGI5CZRu+URg7nJJ4K+NpYepGnU3ab9LW37bm8K M6kXKPQ+iqSuW8E/FHwv8RpL2Pw5q0eqNZJDJP5cbqEEqlkGWUAnAOQOVIIYAjFdVXXTqQrR56bu u6MpRlF2krMKKKK0JCmyHEbH2NOpCMgg9KT2A8R/ZN037V4B1HxfcC3Op+KtTutRuPJh2eX+9ZBH uJJZQyuwyePMI9Sfbq8i+ENq/hv4nfEnwxZMkHhyxksbvTtOilV0tTPG7TBQCTGGdSwjOAM5VQGy ZP2lPFN7ovgO30TTre3lvfFd7H4djlunZY4PtCupkO0EnABHsSDzjafFwlRYbA3a1jdPzadn97Ms uoyrRhRjvt927/U9Tsr231Kzgu7SeO5tZ0WWKaFw6SIwyrKw4IIIII65qasbwX4f/wCET8H6Hon2 j7V/Z1jBZ+fs2eZ5capu25OM4zjJxnrW1XsU3KUE5KzNnZOyCiiirEFFef8AxI+NGi/DfUNO0uW1 1DW9cv8Ac0Gk6NALi6MYDEyFMjC/Kfc4OAQrEcR/w1ZZ2KWU2r+DvEelWioqavdSWL+XpVwzIFjk JA3Aq4fI52vHhSXIXzqmYYWjJwnOzW5yzxVGm3GUtj3ekrzvw1+0J8PfFkV/JYeJ7RUsUWW4a8DW oRWYKGzKFyNxVcjoWUH7wzx8n7Q2t+K/GWpaf8OfCcfjXSdIQJe3g1CO1DTOTsMTPwyAJIMgHceQ QAC6nmOFhGLU+a+3L7zfyVxSxVGKTUr32tr+R7bfX9tpdnPeXk8drawI0ks0zhUjQDJZieAABkk1 5P8A8NbfCr/oZ2/8F91/8arhtYn8ZftAeNE8EeJNJs/BOjaa9rqWp6VNfPNd6jDlziNo9qSQkhFY j7j7TksNo+j7HTLTTbOC0tbaG3toI1iihijCoiqMBVA4AAGABXNTxOIxrcsM1GC0vKLu310urW8w k685e57q809fldHjP/DXHhKO3N9caX4htdDebyLbWptNYWd03mbD5bgknADvggHbGwxuwpxdR8Se J/2l2ttD0XTNY8G+BZoVn1XVtQgENxexNnbBb8kFXHJcEjB54+WT6H8tem1fypwUDoMVcsHiK3uV 6t49Ula/zu9P6uQ6FWp7tSenkrX/ABPnbWPh3P8As8eINL8XeGG1C98NmdovEkFxdvM0VkVRIGVN rExWwDMMAyBfl3FSxX6CsL+31Sygu7SeO6tZ0WSKaFw6SKRkMrDggg5BFGoWNvqljcWd3BHc208b RSwzIHSRSMFWU8EEHBBr548E6hqf7LrS6J4siku/BN5JNe2+tadBPJb6UzSlRbOpaR1Rl8phnkSS uMyfM4iyy2porUpf+Sv/ACf5+ptGEMNByulG/n1/C2mu2rO5+NHwp1bxHdaf4x8B3Fno3xM0fZDZ X947pa3lo0imazvAisZYGXcyrjckgVkZCWJ3PiB8HdC+IV1a6jcteaVr9ohjtta0m4a3u4VJyyhx wQQWGGBwHfGCxNdlY31vqllBeWc8d1azossU0LhkkQjIZSOCCDkEVYr0pUKVZPmV0/6ub1LVoKE1 dHy9rHgTXfgt8VPD/inVNd8VeMfAlp5ju013JdvpcphdGnnjwd8QR5DvQKVBIPQCT6U0bV7TxBpF lqlhL59jewJcwS7Su+N1DK2CARkEcEZq4RnrS1hhcJ9VlJQl7r1s+j9ex01KzqQhFr4VZen9M8q/ ZO/5NZ+Df/YmaN/6Qw0Ufsnf8ms/Bv8A7EzRv/SGGivQOc9Urxj9ry31K6+CvkaNcR2mryeJvDSW VxMMpFOddsBE7cNwH2k8Hp0PSvaK8I/bc0m6179nfUdMsYvPvb3XfD1tbxbgu+R9asVRckgDLEDJ OKzqX5HYqM/ZyU7Xt8y1+zT4B8F6FpeparoWrR+LPEH2qay1TxIUkDXMgfzCBvZhjDplkJV8BiSQ Me21S0fRrDw/psNhpljb6dZRZ8u2tIlijTJLHCqABkkn6k1drHDUvY0owslbsdOLxVTGVpV6sm2+ /wDWnklotkFecfGT4R2vxG8O3slhDZWHi2NIzp+uSQD7RbNFKJUCygb0BIIyp43k4PQ91rWpf2No 99qH2W4vfssDz/ZbOPzJpdqltka5+ZjjAHckVzfw3+KWi/FDT7ubTBcWl5YzNb3umahGIru0kBI2 yJk4ztOCCRwR1VgJr+xq/wCzVXrJbf5HOlPlbi2ltdeZ57pv7Ruttb+fqnwo8X21u21ITaWZnkaQ IplDoQhRQzAK3IcA/dKlRe0b4s+G/jx4P1bwoL7/AIRzxPf2U9hc6RfIRcW0rJIjhVbb5u3azELy ABuCE4Gr4v8A2jPA3w/8SXuh+Jb650e+tyjJ51hM6XEbIrCSNkVgVyWTsd0bjHGT5n+1T4s0HxL4 a8LxeEdVtb7x9NfRXHhi4094JlWbzNgaR2BURFxjB4Z41yCEbHh160sPCXNXU0tHF2u7+mz7aHJi MJi8JThVrtqEtuZWTT7P/hzpfhX4p174X6r4S+GHiXwxZ2SXFvNFYazpN0rW900SCR2MRVWQ4J3M eWckgYbI9nute02x1GysLjULaC+vd/2a2kmVZJ9gy+xScttHJx0FfE+h/EHxNpfhPwZ4J/aU8Az2 2g2+qjSpvHOq+IFUNdNBLLbFlgGZF8tliaYyFMh2kfcrgfRkH7KfwsihnRPDCss6bGL3lw5A3K2V Jkypyo5XBxkZwSDvhpYqnDkopSirW5m00rbWUdfUKmGxWDfJG0o9Hfp20X/B7kH7S3xPvPh34a0R NM1u30K71TU4raS+eEXElvbcmWZIj9/bhAeDw+OCVIytH+FPiTxdGPEEnxq1PWJdg/s660RIYLIO jPkyRIzRzjfgEcZClSTxjzfx38A/Cf7PeqeFvF7RXniPw/HqP2TV7PVoUuYY4JY2RZzsj4EbEHaV O5igBU4z6FYfA/4KfErxJe6xpTafqSpAkU+m6PfqlrEx+7LshIKMQpGAQpwTtLZNeY1jMRXnKtBX 0tHna6b6aP7rnbDLvaUo4rEKST7XaTXTda6/ijynxF488cS3E/gv4veLj4N0iPfFNfWOkySSa7GX VmWKWOMoFEZAJAXAcK6OSwHr1j+0V8KfAGiweHvDE82otZOtna6To9lLI8zF9uI3YBJCWJbdvO/J ILE8958GfCGp+Bfhpomga5eQ6hqdikkTzQytKmzzHMaqzgHCoVUDAxtwOAK6rR9C03w/p8Vhpdha 6fZRZ8u3tYljjTJLHCqABkkn6k124XBYmFqsZpOS+0nKS8r3S/D1uY4ympV3UwyUb77v/wAB1Vl5 a6/hw9v+0L4Cbw+2p3niKz0mSNHafTdQlWK9gdMh4ngzv3gqRtAOSPlzkE+efC/wXP8AHbxBc/Ef x1ZSXOkF5YfDehahCot4rNsYuHi3MGdx/e4+XcMjytna3vwJ0Lxb4q8XXnirQNN1G11K4SWzukkd bpUNkltJGxVVKbSrMpVzguGG1kBrxjwn4F+KOk/Ha4+Hk3xY8SWfgrSfsOuaQms2UV9da/aRzRPe xvqChHTZMyRFGJby5kGwx/e7alOtKcViEpRW1ur7u/8AVz0svrf7JVhJJVHdNv8AlT+yraN9fLyu fWthY22mWcFnZwRW1rAixxQwoESNAMBVA4AAAAAqevCNB/Zb1DwnfSanpPxk+JFzqkdrcRWg17WV 1GyjmkheNJZLZo1WXy2cSBSQCyLmuq+E9r8T/D+pX+geObvTfFWm2sSzWfjC3C2dxeM55gkskUqj R4fMiuAVaHClvMK+lGbVouNjkdOKV4Svb5Hpu0egpHXcjD1GKdRXQYnknwf+CMHgS/1q81TT9KuL r+17u40WaCIM9hYynKQIWQGMAtKSifL+8bruNeV/tMw6t8M9a8QXuit51t8R4ItOvZ7jbHHYywhI 1Hmt8gWWF5VIfBG1nDgLgfV9eT/tRappGm/BLxGNZt7i5guIlggW3jZttwWBhd2GAiLIFYliAcbf mLBW8PMMLFYKcab5bJtP+vLQ7a2JxeM9pCHvTqLlt3vt87pP1Ow+G/gSw+HXg/TtGsYbdTDBGtxP b26w/aZRGqtMyj+JtoJJJPua6c1ieBzqx8G6H/bxzrf2KH7d9z/X+Wvmfc+X72fu8enFaWpW0t5p 9zbwXMlnNLGyJcQhS8RIIDKGBXI6jII45B6V6lGMYUYqCsrbHBTilFRWiPlXXvC/iD9pTx1r/ijQ b5tJj8I3cNh4fTUIzEhvI5UknkljbeyMOODGCwMQbGxhXq/gf9mnwz4Z1S113WJbzxb4qikWc6xq 1w8jeYqKoIQnbhcZXduZePm+UY4f4F2evfArxjY+A/FE8WsXfixrrVV1C285jFdICZFkkkUCUPHG rbh86sSGXDK5+la8LAYLD1m69Zc1S+t+j3222a+RtjMHQpYh04Vfaxi9HfTvont9wnSloor6UzCi isPSfGmj654k1vQbK787VdF8n7dB5br5XmqXj+Yja2VBPyk474qXJRaTe5cYTkm4q6Wr8le2vzaR uV83/tQXyyfEj4SW9i82uatZ60t23hS2Dl7iPIxdcSIqtF5bbTIQvzOSdiyA/R7HapPtXz7+y7DB 42134h/EmfzL241nXJrTTdQmthEH06EKsJiBRWAIwrephGfmU134f29FPFUbWjZO/wDeurerV7dt 1sclR4Wo/q2Iv7ybVu6tZvyTs3326n0Ev3RSModSpGQRinUVxHQtDzn4Z/CFvhbrettpmtXF1oOq zNevp98nnTRXTN80i3BO5lKhVKuGbKht+S2fRqSis6dONKPLBWRvWr1MRN1Kru31FooorQwCiiig ApCA3BqnrX9of2Pff2T9n/tTyH+yfbN3k+dtOzzNvzbd2M45xnFeTH9pbTvC95Hp/wAQfD+q+BdQ ZGcSTxfa7OUgr8sU0IPmHa6k4UBTlSc4zx18VRw9lWdk+r2+/Y1p0p1PgV/zM3xf4d1T9nu41Lxf 4IsLe58HmFp9Y8Lq8qHzt/8Ax825AcR4VhvUBUCRdDwU9e8H+LNP8b+F9N17TZd9lfwLNHllLJkc o20kBlOVYZOCCO1eP6x8eNc+JiXej/CPRLjUpHBgbxVfxeRYWbHy8uqyDMjKJCShAI2ghJF4MWh/ sbeFtP0FbS91vXb7UhaLarqKXfkm3U7zMsEYBVY5TJJuR9/DtzkknyKMpxlKeAanT/ld0k+8XazT 7LqdU0tI4hNS77/Jq97ntel+KNH1yO1k07VbK/jukkkt3trhJBMkbBJGQqTuCsyqSOhIB61qV4dr X7HXw71jTbS3S2vdOuoEije/srgLLOEjCZdSpjy2AzFUBLc55Ocy+1z4t/BGKwn1y50jxt4C0+WO K/1aOCePVorUj5rmVAWVhFnkqHZlTLYJZl93L6eMxU3TqxjF9Pe38tlr5HnYutRw0VNNtddNvPfY +g65bx78LvC/xOtbW38S6THqSWrmSFvMeN4yRggOhDYPGRnBwCRwMYXg39or4c+PvtI0fxVZyNbq XkW7D2h2hGdmUTKu4KqMzFchQMnFZH/DWnwq/wChoP8A4Lrr/wCNVhjKmGot4fGNJ7NSt+KZvh1U qpVcPdruv+ANtf2V/A0Or2txNHqN/pdlk2OhXt881haMWVmZEb5vmZcsrMytuOQeMRN+yT8OJLyN m069bTY0YJpJ1Gc2yysV3Tj5t4kIRFPzbSFHy5ANa+uftLfDPw9dpbXXi2zlkZBIGsUku0wSRgvE rKDweCc9DjkVkXn7W3w4WELpmpXuu38jpFBp2n6dOZ53ZgoVA6qpPPQsM44ycA+PJZNG6lyfh/Xy O1fXXqub8Tyv48fAjw/od74FsB4j124j1LXYNMttLvdREyWdnIdsgtldSyhMQrklgPl3Z4r64X7o +leBfDjUrb41/HTV/GlvdSXvhrw1ax2OiN5M0UTzTR5nk+cgeYoLIw28q0Z/hUn36tMqo0lKriKK tGTsvNR0v997eRGKnO0Kc3ql+eoUUUV9CcAUUUUAFFFFABRRRQAleJ/EeO68ffHzwV4Q3/ZtK0OE eKrplcb55ElMcKqNhxtfryAyyN0Kqa9I+I/ja1+HPgfWPEd4vmRWMBdYskebISFjjyAcbnZV3YIG cngVxPwF+Hl5pFpf+M/E0ccnjLxK/wBsuXKSB7OBwrJaDzCWUJgZXjGFU7hGprxsY3iKsMJHylL0 T/V/qddL93F1X6L1/wCAj1qloor2TkCiiigAooooAKKKKAPE/j5rGp+MNY0r4U+H5fst9r8LXOqa htlP2GxVuT8oAPmFWTBbB+4ceYGHr2i6PZ+H9HstLsIfIsbKBLeCLcW2RooVRkkk4AHJOa8m+NVv J4G8aeFficJ5BpulyDTNYgQKgFnOSgmZlHmSCORkbyvnBOCoQ7mPsFjfW+pWcF3aTx3NrOiyxTQu HSRGGVZWHBBBBBHrXjYVJ4qs6nxaW/w20t87nXU/hQUdv1/4axT0rwzpGh3l9d6bpdnYXV+/mXc1 rbpG9w+Sd0hUAscsxyc/ePrWlS0V68YxgrRVkcrbe4UUUVQgpKxfGsmuQeFdTl8NJbza7HC0lpDd JujlkHIjPzpjdjbu3AAkE5AwV8G+K7Hxx4V0zXtNffZX8Czx5ZSyZHKNtJAZTlWGThlI7Urra+pH N7zjY8/8F/avCPx08Z6HLbeTpWvQxa7p32eALCJFCQ3e5sDMrP5TkDdw24kFueX/AGxru/03wz4K v9Ltvtuo2vie0ntrbYz+bKqSsi7VIZssAMDk54rqv2gNHu7HSdK8eaRH5us+D52vxFkDz7Rl23UW WO1cx5O7azDZhRk1z3xtv7HV/HnwauIZpNcguNVM0Ol2buYrhSqEXm9MqRASr4P3lduQu6vmsU5U qFXDp2d1Z+Un+jvp6GFHFTwE3KG6el/72n4XenoXLX4gfFjw/Gdd8TeC7O40B3dTpGgO1zqtqCxE bMN3lzDhQdhBw4bACstdn8Nfi1pfxCtBA8cmieI4U3Xvh+/zHd2pwpJKMAzId6EPjBDDocgdyB8o GK4zx78IvDPxF8qfVLHy9Ut8G11azcw3lsy7ijJKvPysxYKcruwSDXoqhiaCTpz5vKX+aX6C9nVh rGV/J/5nZlgqliePWvD9X+Omq+PPEw8O/Ca3sNbnttz6lrWpLKNPtlBZVQMuC7My8MuQQMjcNxRd W+APi3UtNl0BvirrEnhKbCTWV1aRTXkkRIMiG7yGO47hyCApCkMBg+reD/B+k+A/D9romiWv2PTb bd5UPmNJt3MXb5mJJyzE8nvWcni8VJQ5fZxW70bfkrbLzevkQ/bVny25I9drv08vPc4z4V/CB/CU /wDwkPiTU7jxF43uoXiu9Smncxxxu4cwQxnCrGrDI+UHJOAoO0el+Wp/hH5U6ivRo0KdCChBaf1u dVOnGnHlijmPFXw08MeONQ0y917R7fVJtN837MtyC0a+YAH3R52vnaPvA4IBGDWn4f8AC+j+E7R7 XRdLs9JtncyNDZQJCjOQAWIUAE4AGfYVqUVSo04yc1FXfUahFPmS1PPPH3wlfxP4itfFGheILzwr 4rtbU2UeoW6LPDJCX3FJYH+VwMuRyMMwJztXHVeEf7f/AOEetP8AhJ/7O/tz5/tH9leZ9m++duzf 833duc989q2aKzhh4U6jqw0b37etu5u6kpRUX0CiiiuozEqDUNPttUsp7O7gjubaeNopYZkDo6sM FWB4IIOCDVikpNKSsxb6M+d/DPxM0n9nDXLr4e+MtfuLnTIYFvtF1KWJ5mS1ZigtZQiEhkZGw3Kl T/BhUr17wz8VPCXjHTb+/wBI1+zu7PT0WW7m8zYLdGjEgZ92No25yT0KupwUYDn/AIh/s++EPiLe T6lc2kum6/I8Eq61psnk3cbwk7GVsEZwSCSDkBe6IVhvf2a/h9rFhYQ6toSaldWsex9QaR4bm6cg BpZ5IihlkYruLNnkseMmvChSx+HbhS5XBbJ3vbtfXb0PS9ll9OhBUpS5ut7aenl01dzoP+FyeAv+ h18Pf+DSD/4uuwDBuhzXB6b8B/h5pULRQeDdHdTt5ubRJ2+VFQfNIGPRATzySzHLMxN34f8Awp8P /C838fhyK5sbG88tnsXupJoVkXdmRQ5JDMGUMc4IjTgY57aMsZzJVoxt5N6fhqcs/ZW9xs5r9k7/ AJNZ+Df/AGJmjf8ApDDRR+yd/wAms/Bv/sTNG/8ASGGivRMD1WvA/wBue7n0/wDZt1i6tZpLa5g1 nQZYpoXKPG66zZFWVhyCCAQR6V73Xin7YkdrN8DZI76xuNUsX8SeG1nsbNS01xGddsA8UYBBLMuV GCDkjkVlVTcJJETTlFpHonwv1i88QfDnwxqmoS/aL680y2uJ5doXfI8SszYAAGSTwBiuork/hv4y 0Dxd4Wtp9BUWVpb/AOiPpskQglsZI8K1vJF/yzZOBt6YwRkEE9XSo/w46303NHTnR/d1FZooa9q3 9haLfaj9kub4WkDz/ZbOPzJptqltka5+ZjjAHckV87fEn42eBrFtL+KHhHxHZ3+vwoNMk0kk79Qs zLueJ42G+3KkNIspUDgAhwyivS/2iPiNffDf4b3N3ox3eIr6eLT9LiFu0zSTyNjCqAcuEEjLngso GDnabHwx+B/hz4e2VtcG2j1jxGXe5ufEF9EHvJ5pBiR97ZZQQSNoPQnJYlmPk41V8TU+r0LKyu5P o+lvPyOmUKlKgqqj8TaTb00tdOO73Vnddfl5B4k1rV/2n7q+srZx4Y+E2mzR3N3rl2ksE2oxxiXe 0TNiPygych+UKq55GwclqWgfDfxXrXhbRPgtbSr4iOrQX9zqqW08q6fbwhsyN9pI4DSK20cOUAPO wH658WeENJ8ceH7rRNbtPtml3WzzoBI8e7a4dfmQhhhlB4PanX+o6J4H0ETXU9lomkWUaRBpGSCC FeERRnCqPuqB9BXDWyh1pc1aSd7Xlb3v+3f5V94VFh8S43pXlZJJd0t+ru229LWPDdL+Jnhrxh4B 8VeB/jVJpMV/prPY6na3ZaIajEo3JcQoVVizbdy+UNwKo6hdyAdf+zP4V8E+Efh9c2vw91y+1jwv NqVxc28F9cNL/Z5cgtbRK6h441PzBXyx8wsS2/J8g0zwXF+154q8X+LprqCw0ayhk8P6KY4TLJuU 7/tTrIAOVlOFwCBJwUeNXPZ+Bfih4g+D1roHhj4k+Go9EsJJJLOPxXb3izW11PuJEkwxujMuWdnk OWYsxUDeUeFxFSjKM8Q06eylZ3eul30+e56OKwMctwnsqta9SLXNF6Wvt6tbPsz6EZVYfMAR7ivi Px18A9A8a/tF+IPDC6jF4JaZLaTR7KDSGaG7T7NumZNhRFCtG+Tnliw6g19Z6P8AFfwZ4h1KHTtL 8VaNqF9Nny7e1v4pJHwCThVYk4AJ+gNdN50X/PRM/UV347BUczjBSkrRd/XyumjjpTr4KfMuaMuj TcWvP9PM+RPEPwG8X+CdasL3xDrfi34keGII2mLaPeOl7YXYysM0cDyMXKlwVKHIIJb5VKv6b8E9 F8MeItX/ALe8NfE/xd4qj01zHPYapqTtDl42A8yF41YjklT03JwTtIr2i+1Sz02xuLy7uobe0t0a WaaVwqRooyWYngAAEkmvnn+1rv8AaY8YamfBPiK88M+E9LtY4ptcsLaS3udQuyshjjDnazQw+ZuK EqcyHj51dfOqYOngqqnR99t6Rvr8nfZedz0ZVMTmEJ16q0jvK1kr+SVrvpax9IZzXnfxh+EX/CzP +Ea1HTtV/wCEe8UeGtTj1PS9WW387bj5ZreRQyO0EyEq6LIm7C5JC4PAeG/BfxD+BOr6hq7XNx8V NLvoII7xnmdNStliaVsxJI7iRQrviMMGZ3AAGCT6/wCB/iN4b+I+nteeHNXt9Uijx5ixkrJFksBv jYBkyVbG4DIGRkV69DFLEL2dePJP+V/o+vy2PJlB0Xz03dd/6/U434U658Yf+EhuNH+JHhrw59j+ ytdQ+I/C99J9m370VbVrecebvx5khkB2Y2r1zXq9FFejGPKrXuYSlzO9rBVbUNQtdJsp7y9uIrS0 gRpZZ5nCJGgGSzMeAAASSaNQ1C20mxuL28njtbS3RpZZ5nCpGijJZieAAASSa+b9X1wftZeM7DRd E+3N8LtJk83Wb4M1smpzbQ0VuoKhyFOCw46k/KREzc+IxCopRjrJ7L+ui6no4HAyxTlUm+WlHWUu 3l5ye0V1fldlz/hrzRdL+N154Y1G/wBKvPCNzHD/AGfrumu7rbSlAXjuXPyEFujx/KmVDH75j9F+ NXijw1D8GNa1jVLCLxP4fltoyLaGQbLkSMoiKyA8DcyNvXkY3LkgV1Ol+AvDei6LdaPYaHp1npd3 u+0WcFrGkM25Qrb0Aw2VAByOQMV87eGPg1oni742+OvD9xd6lB4W8LXunX9h4fhuA2n+ZNG0sgaB wyhS2/5V28Ow6HjnzCtXlTjThCPNJcum17PV3v037v1EsLCdCvVwM5RnTXMuZp7uMdLJWak7pa6d dNe+/ZZ8d2msfDPSfDt7qUR8UaOktndaXKBFcwRxSbEDREA4VDEpbHXgndmvaa+ffhh4kiuP2qvi jYWV5ZT2k9taM6x7nlMkEUcZCsPkAQyOrgnduKgDhsfQdZ5XUlPDKMndxbjfvyu1/nuePTc+W1S/ MtHfd+fz3PPfiZ8FdH+Jd9p2pSXmoaFrmn7lg1jRbj7PdCNgwMZfByh3E4xkZOCAzA7/AID0HXPD ugra+IfEkninUvMZ2vntIrYbT91FjjGAAB3LEknnGAOjpK9CNCnCbqRVm9/M6/bS9l7HS177K/37 /iLRRRW5icV8UPi94Z+Een2d14jvTbi8mWGCGJDJI/IDuFHO1AdzHsMAZYqp+cofjx4W+HHxo8Qe IfDktz4s8N+ILKC81lrXzZbjT5U4jYGQKoiPnxpsL5Rjt+TasZ+wGRZOGUN9RWFpcfhrQdYutK08 aZYandbtSuLO38uOabcwVrh0GC2WABcjkjGa8rF0a1VpwqKNnppdp/f1Paw2Mw+Hw9Sn7Nuc018X u7pq8bX0av8AFq/LQ8l174ufE/Wrc3fhzwFb+GdDXfK+teNbkQLHCiNvMtsjCSP5l4bJG0A4AbK8 v+wabTR/B/i/w2l/Df3+n628sslqS0LxtGkaSI+MMrGGTBHYAkDIzT/bA+KkGr/8Wv03c1zdLHea heRuHitY0bzMSIkckhCohlbaFZVVGywJU+nfs+/ELwRrWjp4T8GLePa6HaorTzWRjRx5jpuZwoXe +zzeQpYSZxkSBMsNmlWFeeXqveLs5JpayV7JaLa9+u9jtxmX4WOApYutQtWfw25tI6XlK7d3PZLT a68/X6KKK9o+YCiiigAooooAKKKKACkKhuozXKf8LI023+IR8H38F1pmpTQfadPmulUQakoGZRA4 Y5ePjcjBWAIYAr81dZVTpuNuZb6kRqRnflewgUDoMUtFFRtsWFIQGGCMilopgeeeLv2f/APjjUI7 3WPD0c9zGjRq0M8tuuGkeVjtjdQS0ksjFsZJYkmu7s7C206zgtLW3itrWBFiihhQKkaKMKqgcAAA AAVYpPesFQpRnKoorme7tq/Uvnk4qLei2Mfw/wCC/D/hP7R/YmiadpH2jb532G0jh8zbnbu2gZxu OM9MmtfavoPyp1JVxpwirRSSJcm9WAAHQYpaKKvbYQUUUUwCiiigAooooAKKKKAPn39tDVL+x+Gs FvF4bt9Y0y4nIutQuAzf2cwGInUKQVYsxAcnaMbGB8wCu5+AXxIuviV4CS41O0uLPW9MmbTNSS5Q IzXMarvfaANudwJXaNp3LjABPpHXrXj/AI1z8HfH978Qz83hXV4bez8QRx8yW8qsI7e8AOS6gMI2 jTBAIbDnOPn61GphcY8dz3g0k1bZd7+v6nfGcatFUOX3lqn38v68j2Gikzxmlr37nAFFFFMAoooo AKKKKAIL6zt9Rsbi1u4I7m1njaOWGZA6SIRhlZTwQQSCDXif7K/jiz1/wtqOnxanG0EOo3L6NpVx dxyXlrpgZRErqHZwFJKjeSQNoB27a9zrxn4x/ByxXSdV8Y+DdKj034gWKfa7S+sfMR5HWTzJQYky sskiGRfmVt+8KeOnkY2FWE44qkr8id11a8v8jqouEk6c9L2sz2aiuI+G3xY034kyata2+n6po2p6 U8aXenaza/Z54xIu6NtuSMMA2Oc8ZIAIJ7evRo1oV4KpTd0YSjKD5ZLUKKKK2IE9q8T8P6va/B34 y3HguWX7D4V8RQrfaHFIpS2tLveVmtYiQR85Ik2hlVSwVVy4z7bXlPx4+G/if4oQ6DpeiavZ6Fp8 Nyby71CSAy3cMsYBga36bTu3ZYMrAYwcblbzsbTqOMatFe/F6efdfP8A4J24SMKlT2dSSjF7t7Lz 0Tf3LyPVGwynPTHNfFljYx6P8VJPFnw5hvNU+HvgZGkuEubppbZN4K3i2PmONx8pmk5bBZSckNGG 9yj/AGgrHwf4f1SD4gRpoPinSEXz9PhJYagGyI5rLOPMjcg8dYyCHxjcbP7OfhvWdJ8M67qmu6f/ AGTdeItZudaTT3ctJbxzBNqScDDfKeMZAIyAcqPKxsaeY1qVKDs46trdW2v216dbeR5OIpqOKhSk k3HV9fTXs/xPR/DfiTTfF2h2esaPeR3+nXaeZDPEeGHQjB5BBBBBwQQQQCK068k8ReDdT+Fd5J4i +H1lH/ZcjxtrPha3gyk0alQ89nGGUJcCMFdoO2TAyCyjdkXH7UMGua1baB4K8J6p4n8RFDJd2Fzi wFlt3CRJnkB2yIwVSMbCWADk4B7nmEMOuTF+7L77+n+R6aw8qmtLVfl6nuVFeJafbfHPUPtOui98 PaXLczskPhXU4jLDaQDAWQ3MPzPKSv3eVIcn5ThFztH/AGltT8Oyf8I9478HarD44Dgx6ZoNt9pF 3Cyu4li/eEEKEKsAzcjI6OEX9qUote1jKCeza0f/AA/Z6j+rTd+Rp27M9+orzDwf8U/EXj7xZDa2 XgjVPD/h+3TzL7UPEcLWszkq4WKCIZ3HcI2L7sBQ4IBKE+n16NGvDER56e3pY55wcHaQUUUV0EBR RRQAUUUUAFFFFABRRXK+Nvih4W+HLacPEes2+lnUJvItvNJO5uMk4B2qMjLnCrkZIyKiU4wXNJ2R rTpVK0uSnFt9lqdVSbhXnHxf+K1n4O8P3unaZdSXXjK9tXXStL0+IXN28rI+yUQjJ2KUZixG3CEc nAPHeD/2d9XsfDOmXLfEDxlo/iEwLdTW51NZ7SK9ceZJui27ZV81mLKWO/JyxzmvPq4uaq+yow5r K712/wCCa/V3GCnUfLfbTfz9DpP2Tv8Ak1n4N/8AYmaN/wCkMNFH7J//ACaz8G/+xM0b/wBIYaK9 M5T1WvKf2lv+Sc6R/wBjn4T/APUh06vVq8q/aW/5J1pH/Y5+E/8A1IdOoA5b4y/syaRrl0PFnhbS Ei8VwajFqc8MN3Jbf2gEOXiV1YLBI/BEoGdwySNxYe6abcSXGn2009tJZSvGrPbzFS8RIyVYqWUk dDtJHHBPWrVIyhlIPQ8VzU8PToylOmrX3O+vjq+KpU6VeTkobXbbS7emmhx2l/F3wZrvi698L2mv 2U+u2cnlS2ZfDFwpZlQnhyoVtwQnbghsGp/iP8StD+Fvhe413XLnyrWL5Y448GSeQg7Y41z8zHB9 gASSACR478YPCvwu+F/g/SvCg8AS+IbrUHuH0vSdOikkupJFCvI/ngmRR8sQYgltoA2sqkDl/h5+ zX4u8aapdXnxB1jxJpmkWrBtM0u6177bcpPswLnzk+RShYlMKDnr8ow/mzxWJUnRhFOfdXsvX/h7 vsj6KjlmXyprGVakoUl0lbmnZ29yzvq79LR/mZBN+3deHxc1kvgW5XTrd51uYmnJvVRCCZDHswhS NJSyEnn+NQpJ2/Bfw18R/tFamvjP4iyXOn+HjNa32heHra6jktXhALhpoyrB9yuAWO1zmQEKu0D6 E8HeCNF8A+HbXQ9DshZ6Za7/ACoWdpCu5y7fM5LHLMTye9bgwBxwKdLBV52eLq863tay/wCDYMVn OCppxynC+ydrc7k5StfdX0i31te2yZQ0PQdO8M6ZDp2lWNvp1jDny7a1iWONckk4VQAMkk/UmvMP 2kvG39k+Dz4SsNOuNY8S+LYZ9N06xthjIZNssrOeFVFcE5/RQzLqeN/jRL4J8SNpL+BPF2tJsWRL 7RtOW5gcH0YSZBByCGAPGcYIJ8R+IHj6++L3xu+G+maDFrnw916zTUJEu9e0uMOqyQ8OkLOQ6kQy Jk4wTxkipx2LpU6TowfvNpWt3aWl9NtjhyrDqWNhPFPS0p3bdvdi2r2u7XSvbW3mSfDfRvgy/gOP wl470jRfDnivTVWDVbfVJBb3XmByRIty21nD7Q/7tyoV1XO0jPpY/ZF+EP8A0Ln/AJU7n/47XLa/ 4i16xu43+MPwz0vXdBtECJ4g0e2W/it2YlpZTE+ZY4RGF3Nt4aE/e3qF0PB/7OvwI8faTHqegaXD qlk+B5kGqXRKMVDbWHm5VgGGVYAjPIFc1OlGSVNU4ya095cr/J3+Wh9BWxdWm5V5YmrTjJ3/AHb5 43fnzxt6O8uj2u+P+JHwt+BPhW+j8Mv4rvvB8t86x3mn6bqUssc5BRojdBxIqBdwZS+0fMxycZHf af8ACf4neF7Ow0bw/wDEy1h8OxYjjmutHha6sreNCsUSYG2bOVDM2wjYCOrKei0n4Y/Cv4U/8SuC w0fSZ9cD2iR6hOJJrwPsVoVMzFnUnZmMEjJHGTz5x4f/AGb/AIgahokPhLxL8QZIPBOnq1vb2+i7 lub6EmUATSODsAV0XyxvTaoXAKhjMsNaVlT1/uNq3k3daP0+VzknjqWNpOnPFO0Xd+0Sk5X6xSUm mrJWcnfTVJH0J4ZufN0Kyjl1aHW7qFPs9xfxBEE08fySttUkKd6tlR905HarNroun2OoXt/bWNvB fXuz7VcxxKsk+wYTewGW2jgZ6DpXgPjv9maz8E6PBrfwpsr7SfE9ndQyPFZak6ve24ceZBuncxqO j/OrA+WAVOcV7B8OfiDafETRZbyCx1DSrm2mNtdafqtsbe4t5AqsA6n1R0cEEjDjvkD2KM5cyp1o 2kttb/i0te587isLSjT9vhajlBuzulGS9Um9H0d7M6uiikNd55J89ftBeKNb+I2uTfB/wWLcard2 f2vVtQmujHHaWwYfuzsy258oGBB+SQcEOWX2iGHR/hx4MAA+waJotjz96TyoIo/xZsKvuTjua5r4 T/Cmf4eTeINQ1XXJPE3iDW7pZ7vVJYTCWRVxHGE3soC5fG3HDBcYUV1fi3wlpPjrw/daJrdr9t0y 62edB5jx7trh1+ZCCMMoPB7V5dGnWcZ15K1SWyeyXRafez1sRioTpU8LTVoR1dt5SdrvX0sl0Xm2 eJeFLf4t/FzQx4th8cx+BdN1FmlstETRoroxW44RmkkCsSwG7PIIIYYDbVZ+x7Z50v4gXlxL9t1O bxLdRXGoyWn2aa52qhBeMgMnzO7eWful2GBzXvEkmmeGdF+c22l6VZQY/hihghRfwCqqj2AArwH4 CajaWvxs8faH4Jezufh6qQ37NaeWYre9lVBthdXO5GVHJGAFKbQFA+fkjQWGq0XOTlJ3T1b1tuls lvsexQxFTFZfiaSioxiovSMVopJWckrt6q13r62Lngm11n4L/HG58O313b6j4f8AHl9qGqaf5MZE 1tcoqSyeZngKUJXgtkxqcJlhX0FXO+OfA+mePtDfTtSjcFXWa2urd/LuLSdeUmhccpIp6Ee4OQSD 89aL8VviN428X2Hw4XW9P8IeIdJ82PWdYuIInkvpF3+ULW2kxvVowsjMAvBJGxQoe/af2dL2VnJS d4+vbX715eh40YVMyqe5HWMHKcnto99Fpo4pJXuz6morlfhf4Ft/hj4D0rw1b3j30dijA3MoCmR3 dnc4HQbmbAycDAyep6pWDdCD9K9elKUoKU1ZvddjzJJJtJ3QtFFFaknD/F7xjrng7wqJfDXh+58R 65eTrZ2lvChMccjg4lmII2xLjk5AyQCVB3D500n4AWvhfxvo2n/FSWPxjb+KkVF1eWSdJbTUYkOy BrgyAlHRmVcndIyINi7K+wqp6loun6x9l+32Nve/ZZ1ubf7REsnlTLnbImR8rDJww5Ga8rF4FYqU Zyesdk9vPTrdaHr4bMquEpeyo+627uS+Lys+lvK1+t9Dnfh78JfCfwstbuDwxpEempdOHnbzHldy BgAu5LYHOBnAySByc9cFA6DFFLXowpwppRhFJI86tWq4ibqVpOUnu27v7wooorQxCiiigAooooAK KKKAOU+Jnwz0L4seErrw/wCILX7RaTfPHIhCy28gB2yxtg7XGTz0IJBBUkHhvg98W9Rk1L/hAPiI 9vp/xFs94jWMMItWtlUFbuFtoQ7huyinIMbnamCq+yV5F+0H4V1WSz0Dxx4ZspdQ8UeD7v7ZBZQA GS8tZAEurdc5ALx8hgrP8mEGWr1cJONZfVK2z+F3+GVtN9LN2Uvk+h5eKhKi/rVLdbrvHr810+7q eu0VzXw/8faV8R/DyarpbyKFkaC5s7lPLubO4TiSCaM8pIp4IPsQSCCelrzZwlTk4TVmj0YTjUip wd0woooqCwooooAKKKKACiiigAooooAKKKKACiiigApK5XXvid4d8J+Il0fXb+PRZJbUXcF3qDCG 2nG8q6JKxCmRPkLJ1xIpGeceIfFr9pnT/GGn6V4V+Gmultd129jsGv2t5oFtY3ITIdlDKxZlAZVY gByMNtNeXisyw+Fi3KScl06t9rHTSw9Ss1yrTv0PdfDvxI8M+LNW1PStK1i3utT02eW3urPJSaNo 2CudjAEqGIG8AqScA143+1ho/ib4iaNZ6H4Mu49TWzukXW9Gs7hPPBlKG2aVc5EYIZjuIHKuQQhZ ep0/9k/4Y2ekJYyeHjeH92ZLma7m86RkUjcWVxtzuJKrtUnHHyrjOk/Zig8K+IotZ+G3iGTwJdNa taXKtajUUmQur5AmclTlRnk5wuMc7vKxdPH4rDOjWpq0t+WWtvK6S9dTroyoUqqnCWq2utPnZ3/A 4fxZ8UdQ+LXxM0fwd/a/iH4U6fLZPNAby1azvLy9YskSFg/+q7gZG9lZfvFCvYJ8cNf+E80GgfEv T/7U1m4gjfTLzwzbySrqLF1iaHa4QeeCQ5C4UhwAFO0NveE/gXc2/jk+LPGniKPxvq8NqlrYtPpU NslqFkMgcKuf3gb7rDBGW65GN746eJtZ8G/CjxDrPh+PzNWtYVaJvJ83y1Lqrybf9hCz5OQNuSCA RWNLD4ujSqYqrNxkrvv7qXVXtftZjlOlOcaUFdfdr62v95N4A+LOmePry6sBp+qeH9Yt0Ex0rXbX 7LcvCTgTImTuj3ZXIPBHOMjPSa94m0jwraJda1qtnpNq7iNZr64SFGcgkKCxAzgE49jXw/4V+N1j 4Z+OEHiu98UXviCBra5s9TvP7CgsjdxJGTAEVHJYtIkYDOEYBUDELkL734N+H+rfFzxhc+NfiT4f +x2EcEcWheGr+dLiO2V4wZpZI9gBZjjAcbgchl+SMgwOdTxlPkpLmqXt5W3u2rr/ADY8RglQlzTd o2v8+yvb/hj1/wALeMNF8bafJfaFqVvqlpHPJbPNbOGUSIcMv8iD0IKsMggnZr5j+EvjSPwF8XtV 8DeGrfT/ABd4c12+k1qG+8PzJt0uOTKskqgmPahSNcBlOCCAzOsY+j9Y1qw8P6dLf6pe2+nWMWPM ubuVYo0yQoyzEAZJA+pFe1gcdHFUXObs4uz7XXmcVei6U0ls9UXKWuf0H4geGPFN41ro3iLStWuk QytDZXsUzhAQCxVWJxkgZ9xW/XowqQqK8HdHO4uOjQtJXN+NviP4a+HOnreeI9Yt9LifPlrIS0su CoOyNQWfBZc7QcA5OBWF4M+P3gL4ga4mj6F4gju9SdGkS3kt5oS4XkhTIihiBzgc4BOMA4wli8PG oqUqiUn0urmipVJR51F272OK/aV8AWGleH7/AOJOiD+x/G2jmCaLU4LhYfNVXCMkgY7JMo5GCNzY RPmB2H2rRdXtPEGj2Op2Mvn2V7AlxBLtK743UMrYIBGQRwRmvIP2nPF0UnhmPwFptl/bnifxN+4t 9NhZPMjjGW89g6OoVWQcttOAzK6mMsvqXgvTb/R/B+iWGq3P2zU7WyhhurnzGk82VY1DvuYZbLAn J5Oea87DckcfVjRXu2V7bc2v423+R0VLuhBz3u7emn4G1SUV5X8VPh38TfFviGC78GfFn/hBNLS1 WKTTf+EcttQ8yYO5MvmSsGGVZF2jgbM9zXszk4q6VzlhFSdm7et/0ud14y8aaJ8PvDGo+IvEOow6 Xo2nxebc3Ux+VFyAAAMlmJIUKASxIABJArxrwb+2/wDDHxJPp9trNzqXgG+1KL7TY2/i6yaxW5ti m9LlJstD5T4YKxkG4qQByuV+G37E/wAN/A8Ed3q9hN4y8T3ETjV9Y1q5mmXVZHfzJGntmkMLr5gV lV1YgojEs6769s8QeGdI8WaPPpOt6XZ6xpdxt86yv7dJ4ZNrBl3IwIOGUEZHBAPasP38tdF5bnQ/ q8fd1l57fhqeIftcTaPrfh3R/C6RaXdeKtY1C2s7FrmRBPZJLKMzAbWcIxiEbFQM574wff4xiNR7 CvFY/wBjz4ZaLeajqXhjSLrwhrV5KZv7R0PUJ4JIWJJIiQuY41IZ12qgAViABxiP4d/He60vxRb/ AA8+I0H9l+Mk/dw6goAs9SXgRujcYZ+RjAG5SPlY+WPKhJ4XFzqYhJc9kmttOj89TzfZqNec4ptN LW21u+/VnuFcT40+Cvgj4gTPPrvhyzu7p3WR7qMGGdyq7V3SxlXYBcDBJHA44GO24pa9mrRp148t WKa8zqjOUHeLszjvhb4c1/wl4fudK17Uv7Y+z30/2C9lnknuZLRn3R/aHcDMoywO0bQAoHSuw2ju Mmlop06cacFBbIUpOTbYlLSMwXkkAe9Gc9K1JFqC9vrfTbOe7u547W1gRpJZpnCJGijLMzHgAAEk msnxx4wsPAPhPVNf1OTy7OxgaZ8MoZyBwi7iAWY4VRkZJA718n6W3j34u+IPBWj/ABD8Rm18M+LI m1m20u3tUWO58qXzDZ7omEgUwFZA7twSo5dcjzMZjHh7QhHmk/u3srv1PXwmW1MVRniOZKMfvejb 5V1sld7JH2NZXtvqVnBd2k8dzazossU0Lh0kRhlWVhwQQQQR1zU9QWNlb6bZwWlpBHbWsEaxRQwo ESNFGFVVHAAAAAHSpiccngV6Mb2V9zyfQKWvGfE3xl1zxF46l8G/DOz0/VdT0/L6vqmp+Z9gsuCB CWjOWlLDGBnGCMHDmP1nRf7Q/sex/tb7P/ankJ9r+x7vJ87aN/l7vm27s4zzjGa56WIhWnKMOnXp 95vWw9TD2VVWbV7dbPb7y7RRVXUr+20vTrm8vJ47a1gjaWWeZwiRqoJLMTwAAMkmul6K5gk27I8c +JPxQ8Wa740uvAHw0tIG1u0h8zVda1FGFrpyvGTEo4O6Rsqw4Ycfdb59lzwH+zXpHhrUH1XXtZ1j xlrMtl9hluNYvHkiMRVhJH5ecNGxYnZIXAIBHPJzP2U9LNxovi3xWbGO3i8Ta7c6jaT74nlktWIM auY2bBVjKChOVbfwM17pXmUKSxCVetq3suiXTT9T6PG4l4FvBYX3UklJreT63fa90ktLb3d2eb+C f2d/AXw716PWfD2jzadqEaNGJFv7h1ZWHKsrSFWHQ4IPIB6gGvSK5Xx38UPC3wzsUu/Ems2+mRyZ 8tHJaWTBUHZGuWfBZc7QcA5OBWLpP7Q3w31qwivIPGekRRSZ2rd3S20gwSOY5CrLyO4GRyODXRCW GoP2UGovtovwOCrTzDHRWKqqc1tzO7+V/wBDO/ZO/wCTWfg3/wBiZo3/AKQw0Ufsn8fss/Bwf9SZ o3/pDDRXYeUeq15V+0t/yTrSP+xz8J/+pDp1eq15V+0t/wAk60j/ALHPwn/6kOnUAeq14l8av2lt F+G66nYaZqFpc+KNIkt5brR7uCVTcQu0e5I5eFD7ZVcEb8BWyhwSPba43xR8P/CPxbs9GvdWto9d sIGW9sjHcubaXIBWQqjbJQR03BhhjjhjnlxUK06TVBpS8z0cvqYOniIyx0XKHaLSf49OnTvc5rwz 8MYNT+KE3xM1HxBa+IGnslt9Git7VEhs7ZiWDK+5zIxDH94CuQ78bWAXs9B8faV4i8VeI/D1q8g1 LQXgS7R1wpEsQkRkboQQWHqCh4xgnxBvgx8OPFvirxD4W8N+KvEPha5h3HVPDemXUtpBIXOGk8mV CHVlKLmPKbfLwAGGdfw9+xz4V8KWrHR9e8TaVqjOc6rY6j5Nw0RAzAdqBDHkBvu7sgfNjivOpzrx /gQTV3d817vy079/Q9bE/UqlGVStWk5qKUI8iW1rX1ta19r3bv3PZ/FHibT/AAdoN5rOqySQ6dZp 5k8kMEkxRc8ttRS2B1JA4AJOACap+D/iD4c+IFj9q8PazZ6rGESR1t5QzxBwSvmJ95CcHhgDweOD XhGneIP2hfAupNFrfh+w8eaUJ1Vri1ligkcOFVVQrtKqrsCzPDwA5LBcMPPNV8R23jPUNJ0zwB8M tQ8FfFXS5zdqtjHDaR20WMsZiyr5iMhQYkRBmTAJDFZOOtnPs7NQaf8AK4tN+j1T9D5z22EhBRnJ 872aTt5pq17+l/I9/k/aC0bwl4x1Twx45kj8P6jDdD7Bd+VKbW8tZCTFIHK4QqPkkLEIGViGxkL4 v8arzRfi/wDGbTZdF8OyfEPQfD+m79ZOkTIoZHLlVjlQK0jrkOsayMHIZVCkSk+r337SHha4s7jw 9rGh6pL4vaNoLzwdHpz3dwxI/eIp2+VKmzL7t2Gj5xziuS+F/wDwkPwKubjVfHWn2+leH/FEymdN OSOOz0C5V3jjV44yUWKVPK/fA8MFWT++eWvKWLlGhKfNC927fDbVKXTe3Tbc9XDc1KvDlpyU7KS1 cb7WtZJ69FfXp2eh4O8EeNLHwfpuo/DP4mW/iDwtHCv9maT4gsFkjaP7rJJcoBKNh3YUKCpRUIAB rgpZ9cmgtfHc3gHVvhZrMilLrxVosQuVzuYzvd6awDCE/vJDI4ZgUiOW4z9R/D228M2fhW2j8INZ toBkmkg/s+USQZaV2kCEEgDeX4HC9AABit28sbfULOe0uoI7m1nRo5YJkDpIjDDKyngggkEHrmvW nl7qQjyTa/FX8r6pejR11M3qRqS9xXvu0k7a6SSSjJvrzJ3PEPCf7OOn69ql54o8beJP+Fk3eqWP 2WK4lt44rVbZghRoVTOxuGIkjZf9YSBkljreEb64+D/i8+DtXnlHhHUJETwve3DGQROQd9jJKeQQ f9SGzlQV3sQFHsFUdT0PT9aNqdQsbe9+yzrc2/2iJZPKlXO2RMj5WGThhyM10fUoU7To6SXXv3v1 f+Z8/jKtTGVVXm1zLTRJK3aySVvQu0BQvQYpaRmC9SBXpebMxa5vxl8RvDPw/tVuPEOtWelIyPJG txKBJKEALbE+85GRwoJ5AxyK8r8dfHy+8UapP4O+FFv/AMJB4gkMccuvQgSabpwcMS7yjKswVSQM EE8fMymM6Xg/9mjSLXUrnWvG1/J8QvEFyhja51mJXghUyM+2GA7ljHzDjJAwdu0MRXnvEyqvlwyv 59P+D8j3YYClQpqtj58qeqivia79orzer6JnpXg/xvoXj7SE1Pw/qdvqlk2B5kD52MVDbXHVGAZS VYAjPIFJ42/4SL/hGbz/AIRT+zxr3yfZ/wC1N/2f74379nzfc3Yx3x2qDRvh34d8PeJL7XtM01NP 1K/j2XT2zNHHcfOX3vGCEaTczfvCpb5iM4JFZHxR+NXhb4Px6cfEd3LA+oOVt44bd5CwVkWRjgYA QSBjk5IB2hjxXRKfJScq7S8zip0nWxMYYODm3srXfe2m/wDl2PPIv2cvEXjyfSpPir42k8W6faI0 h0S1tRZwC4ZQCxkiKtIFy207VPPYFlL/AIYaRp/w5/aQ8eeHbOxgsbbWtLsdVsILGJUhhhh3QyKw AG1jIxYAAggkkg8VavP2wPAMzW9v4fOreK9Tncomn6RpsrTkBWYsBIEBAC84JPfGMkcR+z7by/Gj 4m+IPiDr2o6ppWsWcluLfw/azSwxRWbxh4BI5wZEcjfsXapZCxUrIBXgyqYWNalHDNSm5b3v0d9d ej2PqqrzOOGr/X4+zhy2UeXk3kmrQSXVau2trXvY+qK8D1T4AzeOvi94517W5NW0pSlinh3WtO1L yprdRCRcrEFY7AWJBDrzvYr1Jr3yoL64ktbOeaK3ku5Y42dbeEqHkIGQqliFyegyQOeSK93EYeFf l9ptF3/D+vmfIYbFVsJJyoS5W1b5f8Hr5HxnN8KfFvgj4tWfhzXvindaZp3iO2WKHW7cmO61N4pY 2+zuxYskw3lUlZm+UqgJDGMfVPw2+Hun/DTw2uk2E1xeF55bq4vrxle4upZGLNJK4Ub25A3EZwqj tXjg/Zz1D4ozeMfEHxEjs7fXNbtkt9KtYJZLkaJGq5XDblDPvwWC4UlXwcSsKxPCPiD42/E3xRfe HovEWm+D08MutjqV2tqlxc3Unl8TiJ1HyOyF1OIl2ycb9vHg4WP1GTbpt8zfL1fo76Lv/wAE+xxM ZZpSa+swSgk5+6oxu7WtyK8tXy7brTRnu3xe8WX3gn4c67rmly6dHf2EImj/ALUZhC2GGUO0glmG VUZGXKjvW94b16DxR4a0zWrVJI7bULSK7iSYAOqyIHUMASM4IzgmvB9R/ZLvvFja/feLvH9/reua hBFBDfW9sLVYY49zeU8Ico8Rk8qQqAp3RZBBYmm6X4x+J3xtu5dC0prPwVbaDqEtnrHiKzl+1Ce6 tyv7uGFwrCNnIYhsgrwWPzI+08ZiKdZupTdpK0YrVt3e/RdOp8vUw9NTdOjPnjHVzs1HW2ivro9N lfsejfs8+LtV8cfB/Qdb1y7+26pdG486fy0j3bbiRF+VAAMKoHA7V6RXgOmfsi6dpGiW0Nv4z8Sx 6rZWsken3iXmyKwnkwZJYIlwUDkMGTecq7DO7DD0f4b+Pp/FEmraJrNrHp/ivQXjg1S2t2L27b13 RTQv3jkUbgrfMvIYcAnowNavThChi42lZJO97tLX5nPXjTlKU6Tur9rW7Hb0UUV7RxhWRpnivSdZ 1rWNIs76ObU9IkjjvrUZDwGSNZEJB7MrAhhwcMM5Uga9effEj4UyeL76z13QNak8I+MrKMwW+uW0 CzFoGOXgmib5Zoz94BvuOAy45Db0Y05y5akuVPr0Xr1t6a+uxhWlUjHmpq9unf08z0GkrwaHQf2h /Ds9za2nibwb4rtPMDw6hrdnNa3GCi5Qx242ABg2OWJzknoBY/4Wt8VvBS7fFvww/tyytv8Aj51j wherP5u77nk2cmJTgsqtk8YZugxXc8vlJtUqkJf9vW+7m5X8t/I4lmEY/wAWnKPyv+V/v2PcaWvE V/bL+FUCiPUdcutIv0+W40+80u6We2kHDRSBYyA6nKkAkZB5NQXn7bHwitoVeLxHNdsZEQxw6bcg gM4Uv80YGFBLHnOFOAxwDSyfMZbYef8A4C/8hvNMCt60fvR7rSV514B/aH+HnxM1NtO8PeJra71A fdtZo5LeWThmPlrKql8BGJ25wBzjIrkvG/xW8da18WbzwN8NbLQ5ZtHsEu9W1DXkuTBHJIVMUCmI ABihDjkhgWAwY2zjHL8T7SVKpBwcVd82ll3d/VL5lyx+HVNVIS5k3ZW1uz3IsF6kCivlfxb+zT8S PivPqHiHxh4u0218TWkATw/Z6KLhLPTpleKQTK5ZXV3MbqxKuRuVgTsVBe8T/Fz49M/9kWfwlOmX upCdLK7i1KG5W2VbfAMj8xK4lIkBk2q6jywpPz13RyqNZRWHrxlL7V2opddHJrm63stLPpZvieZy ptutRkl0sm7+ttvn3N/4k6ha/DT4x+HfGOiXMVzLr+p2nhHXdJjcKheQGSC5bb0njUqPnDZjkAGw HJ97U5ANfK4/Y5vdB0nQte0TWPtnjyznt9S1CHXLyebTdRvkaRjPIU2yb0aVijdwgDKS7sfUvhH8 VtW1rWtQ8F+OLK20jx7p/mTm3sUlNreWQZAl1C7AjaS+zaWLZRshTlVeNoUqlOMsNP2nIrSdrO3p d6Lv2tfss8HWqU6so4iHJzu66r7+77ep6vRRRXz59CFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAY3 irwfovjjSZNM17TLfVLJ8nyrhA2xipXch6owDNhlIIzwRVu10PTrH7J9msba3+xwG2tvKiVfJiO3 MaYHyr8ifKOPkX0FXqSsvZU+bn5VcrmdrXFooorUkKQjPBpaKAOU8I/Cvwl4DvLy70DQbPTbq7d3 lmijy/zEFkVjkrHlVIjXCjHAFdU33T9KWkrGFGnSjyU4pLyKlKUneTufAXwLXxVpvxJtb/wp4Lju 73SUuv7V02zu57MgSO6LbXL3LlAUZVZVUEkICxZlYr7f8UofHvxc8MjRNb+DlxHbpOlzFNaeKrVJ IpFBG4ZQqcqzLggjDHvgj6OAHYUV81h8h9hQlh/bPlluko2/FP8AM9Orj/aVFU5Fdebv+aPkH4Ae EPDfxs8J694W8UeC9P0jVPDvkW41DT4DaXhYpJHmXuZVaNmbdlWYjKfLz6Drt58bdY0lPCUWiR2J e6Flc+Nre7gV3tfMKm5S1EgMblMMQGJHzbQpK7dyPR/sP7WL30dl5EN74RbfcrFtWeVLuNWy2PmZ U8oHuBs7Yr2Klgcu/cOk5tSi3FtWXMul9O3z8xV8T+851FNPVJ62fWx5h4P/AGePCfhXWpNcuhee J9fZ1cat4hn+1zoV2bNuQFBXy1w+Nw5AbHFcr+0sfDMd34dvr34g/wDCDa/pvnray29ubqYxXEbR yMIk/eLwhAlGApB/iKkeweL/AA3/AMJd4dutJ/tPUNH+0bP9N0qfyLmPa4b5HwcZ24PHIJHeuW+H /wACfCfw7un1C0tJNT12V2kl1rVZPtF47sX3NvIwpIkYEoF3D72TzXbiMC3D6th6aUXq27738rNv 5oxp1rS9pUk210/4fS3yPFPgn4q8MeAfiJ8R77xN450vX57e10+O38QTPGJbyJYGMix4ZmkI2RKw UszMik5avfPAvxe8H/EozL4c1231CaLJe3IaKYKNuW8twrbcuo3Yxk4zmoW+CPw/ku47k+DND8yN GjCjT4ghDFScpt2k/KMEgkZIBG45PGnwZ8JeOpXur7So7bV96zR6xYf6PexSqu2OQTLhiU4IDZXK rwcCssHhcdgqfs48rV27a3d3ff8A4cqtVo1pczunp26K2x22RS14xN8ANe0yW3u/D3xW8W2l/E5O 7WLgalAyFWUgwsFUnkEE5xjpnBAPAvxh8OXcuo6f8QNL8VXUyLA9jrumG0tkRSzCRPIYnzMnHQbg eSdi47vrlePx0H6pp/rf8DH2UGrqovx/yt+J7PRXEfCbx/cePtD1A39rHaaxo+oTaRqK27FoHuIc B3hJ+by23AgMARkjnGT29ehRqxrQVSGzOeUXF8rErm/iJ4C0/wCJng/UPDmpS3FvZXvl+ZJasqyj ZIsgwWVh1QdR0zXSUtVUpxqwcJq6ZJ5Z4S8W694N8XWPgnxtfR6zeakks2j69BAsIvBGoaWGWFci N0ByGHysuOQwIPqVeNftNobPQfCGuSjZpmh+JrDUL+fr5MCuyl9vVvmdRhQTz0617HGyvGMEHiuH CycKk8O3flta+9n+et9TlpNxlKm3tt6D65b4kfEjRPhX4XuNd1258m2j+WOJMGWeQg7Y41z8zHB9 gASSACRH4++Knhb4Y2trP4l1aPTkunMcK+W8ruQMnCIC2Bxk4wMjJ5GfCp/i7ofxa/aI+FD6NFer FZSasA15bGJbiJrcqs0WfvRs0UijowMbAqKWJxtOm/ZQmudtK3q0r28r3PbyyhTxmJdKTuoRlOSW 9oxcvle1r20vsy7eeGPH37TFxC+vw/8ACF/DuO981dFuI5F1DUY43TC3ADLsVsSEYI2nB2vhHrpv 7T+IPwRHlX9rqHxO8K4/d31nGn9qWKj5FjeIY+1Z/d/vAQ3+tZuNte3cKOBgUYB4I4q44Pl99TfP 3/4G1vI7J5q6iVJ0o+yW0bbed/i5vO+tkndaHzH491DxT+0JeeE7S0+G2q2XhnT9dtby/uPEHk2z siFhKn2Z2y6bJM7gTnDLjivT/iv8MZNX8L6RdeF4o7DxF4XdbvRY7dFRGKJg2hwV2wyKAjKGUfdz kLg+m7QO2KKqOFXvObu5fp2M55nO9NUYKEYXstXe+97t3vs9lY8Hj/a68OaTq66N4m0fWdA1O1h3 6sHtTNDpzhtuHdCWdWYx7ZEUqwmjORkgcX8WP2mLnx1pMmk/Dx7nTNJnnFpeeNr63mgsbXcq4VZA hMbMzqhdwuzII6h16nxXfWei/tg+GpXvvs/2zQGtbmOd4YYtrTOYQC5LSs0gA8tArAhTuZd613X7 Q3gXUfiF8Htf0LQ4YpNTuFikhjdggkMcqSFQegJCEDOBkjJA5rynLEV6daEal+RtWS1el979fJHs YLFZOsXRcaera5m5XjFt6vlcdeXdXk1a176mz8LfhboHwm8NrpOgQSRQSMJppJpWkeaXYqmRieAS EGQoC+gFdjXiafFH4uxxqv8AwpbO0Y/5Ga2/+Jrlbj9prxV4ystT8NeF/AGqJ45heeyugs8L2mmy ASqHM5GxiCmQrqqsQQCeM9ix2GoRVNJrsuVq/pocVTKsdiarqVJxk29X7SD+btJ2Xmz1P4nfHrwb 8JSkOvans1CWB54bC3iaWaVV4HAGF3HgFyoJB54OPnz4yftM6H8V4tK8JeHtSutM0S+vY013U5ZU tCLMz+SyJ5nJ3BhIcdE+8CPMVex8K/si3fhaOLxDpnjfVtL8dywhru/Yx3ltJM+DPujdFMis24je c52seRXT6fc6B8dvhhqui/EGxtdG1rSdy61ZmQRvpkyhityjt91WTMivlkKsy7nAbPFWljK0ZQm1 C60Xfy5r6eem2x7WGWUYBxr0lKs4P3pXtZvZqHLql0fP8Vr2uk/RvCureF9I8CWU2jajY/8ACM2F pshuo7pZIEhiXaf3hY5ChCCSf4Tk14rr37Ytlrgj034f6Jca9q91MbSG4v2WztI5W80RBndhln8o MseVLK2NwcFR5n4X/ZxXxxpa6h4V/wCEH8X6TGRbrql4dSsLh2RQCstvC4VGHHbLDa5yXJPsmltB o9rbfDH4m6B4a02w15JF0r+wQ0dhOwYF4CrYaOYOyurDAYuNpDgbueGOxFeMVb2ce+6fz2X4nDGO VYebnJSrSvs/dS73SblP74bG18Lf2f8ATtAV9e8XC38W+N76dL271a8iWQRSryi24Yfu1TgAgA8D hQFVe01j4T+DPEOpS6hqnhXRtQvpseZcXVhFJI+AFGWZSTgAD6AV5ho/jC+/ZxU6B4ybUdT8GRbV 0nxNBaCSOytlRUW3uliUMrKwVVfDeYZP4cED3LT9QttWsYLyyuI7q0uI1limhcOkiMMqykcEEEEE ete3h40XD2ajZrdPf18/XqeZj6mMVX6xKbcZbSWitpou1tPd6bWPM/2Tzn9ln4OH/qTNG/8ASGGi j9k7/k1n4N/9iZo3/pDDRXonhHqteVftLf8AJOtI/wCxz8J/+pDp1eq15V+0t/yTrSP+xz8J/wDq Q6dQAftRa1LoHwF8XXERcNLbLaN5ZUErNIsTA7lYYw5yMZIzgqcMOy+HGh3Hhf4f+GtHu2ia507T ba0lMGTGWjiVDtyAcZHGQKwfixqXhbXvAPjjSdUuYtQh03T3l1Sys3ikurZTE0iNsbISTC70LAcq D2pn7Peqa1rXwa8K3viDnU5bNS0jOXaWPJEUjMWYlnj2MxJzljkDoOK8o4rlb0cdvn+t19x6/LCe WqpFLmjNpvq00rJeS5Xf1Qz4reBdS1XWPDXjHQEju/EPhd55LbTbhwkN7HMgSWIv/BJtHyOcqG+8 CDkT/Df4v2HjzUNS0S6srjw/4q0vaL7Rb4r5icLl42BxJHlsBxjIKnADLlfjD461L4Z6Ha+J4ktb rQbGdV1ezdG+0yRSMsavbvuChkdgSrrhxkbkIyfBf2h/j34Hv9N0bVfB0iX3jPek1nrltGYZdPjS RgVkLKGYPmRfJYbSrliMFd3k47GUcunKoqiT3lHv0089PTuef7HGYpw9ndxXurtbf5ats+uOO9Uf 7B03+2v7Y+w2/wDavkfZft3lL53k7t3l78Z2buducZ5r5+8Vahc6Ra6Z4X+M00tzaTah5ui+N9Jc 2qQTgSCJp9m0QTKCCpw0fzZOfLdq6GPxh8QvhVqFtc+O7vR9d8JXV7HYf2pp8bwXFnvASO4nBAjS IsuX+b5Wm+ViAqVv/aUG71INJf8AkvqunqroiivbQ5o6Ps/y8z23Yu7O0Z9cV5146+Kmg6b4w07w HdaLqXiK91iEfaLWxsRcQ29tJIIfMuMkARZLbj82ApyBkZ4fWf2qBr9vf23w68Ka54svN62trqS2 DJp3nMF/1khIZQm8E7gvTqAd9ed+CPitofgHxZrmu3t4nxH+J3iC6iinsvC1o0sNtaqM7YJdn7wL EoLAEksiK2NrSVpUzCjzRUGrN6vpby7t+R9Lg8lxFSnOrOLul7qW99NX/LFJ3u7aq3e3v3gT4M2P w18WapqPh3ULmx0PVN0tx4fwrWqTnZtlh4zHwrgqMg7l6BFFei1498NfFXiz4kfEi78QXGkar4Z8 HWWnNYW2m6whgnuLp3jkecxY6Kq7ASSBk7TlpAPYCQoyeBXbhZU5QvSi0rvy+7yPCxcq8qr+sO8t PP731YtY9x4w0O11+30OfV7GLWLhDJDp73CCeRQGJZUJ3EfK3IH8J9K8e+Ln7Qv77UfBnw5jufEH jwnyP9CtfOgsG3xqzSuSFGA5GfmVXXD4wQb3hn9k3wHY+HJbPXdPPiXVr3bJqGr30sn2ieXcXLqw bMWWJztILDAYtyTk8TKpNww6Urbu+np1179j0Y5fToUVWx8nDm+GKV5Nae802rLXT+bppqd18R/i x4a+FeiPqWvajHCNjNDaxsrXFyVwCsSZBY5ZfYbgSQOa8mbw/rn7SXjCaXX9P8Q+Fvh3p8KRJpF6 5s5tRuQ6SM0sQBJjAAX73BAKMCX2+g+E/wBnL4c+Cbz7XpXha0W6DpKk10WunidCSrRmUsUIJzlc dB6CvSAAOgrKphquKaWIaUf5Vrf1emnlY8nHUcJUUYYeUmlu2kr9lZN2tr9p38jF8J+C9D8C6Wmn aBpVtpVmuCY7eMLvYKF3uersQoyzEk45JraorzL4jftHeA/hfqNzpms6uTrEEHnnT7WB5ZDkEqmQ NiswAwGZeGUnAINdsp0cNBczUY/cVRoVsXUVOjFyl2Suz06mvGsn3lDfUZqloOrf27olhqP2W4sf tcCT/ZbyPy5odyhtki5+VhnBHYg1frfSSuYNOLszN0zw5pei/av7O061sTdTNcz/AGeFY/Nlb70j YHLHAyx5OK8f+FH7PN54Hk8C6nd6rHb6xoVte2V/HYmR4b+GWWWSJCxK4CNIX5Q5bH91TXuVFcdX B0a041JrWO33p/oaqvUSavv/AMFfqFFFFdpgUNe1X+w9Fv8AUfstzffZIHn+y2cfmTzbVLbI1z8z nGAO5Ir5l8MW/wAWpvF2vePvDWgx2TeKdQFs+l69arAkFpAFjguZv34lV8bgURWBw7YIMefqjg+9 AwOBXnYrB/WnFubjy6q2mpXM+WybXez3W9muqukzzfwB8YINb1YeFfEsH9heN4fNV7GSKSOG9WNi puLV3Ub4n2syj72FbqF3HH1Twj498F/EnWfE/hZtO8Q6Rr89u17ol9LJavbFIkhEkMg3rzje5KZK xqqhjiuw+K/w1sPix4JvvD98/wBmM22SC7WJXe3lU5V1B/FTgglWYZGc1seD/wC3x4dtB4n/ALO/ tz5vtH9leZ9m++dmzzPm+7tznvntWcKdVz9lWd7aqS+6z8/wfbQ7qWIVBSlTStJWcXqraP13XTVW 31Nhc7RkYNcxrfw70nWNQl1KH7TpOsSYZtQ0u4e2kkdQAjShTsn2ADasyuoGRjDEHqKSvUsrpvoe bKKknF7MxfCelaxo2myW2s63/b8wnkaG7a1S3k8knKJIEO1mXpuVUBAHyg5J26KKYoxUIqK6BRRR QWFJ1paKAGeWn9xfyo8pP7i/lT6Kd2Tyx7HG/Eb4P+EPizZ2lt4p0aLU0s3Mlu3mPE8ZIw2HjZWw eMrnB2qSMgYw/gf8Ebf4L2niGNdUk1271fUpL6TUbuEC6ZCBsjlkyTKVO9t3GTIx2jJr02lrrWMx CoPDc75H06d/l+pyvCUHWVfkXOuoUlLRXGdgV5d8QvgTpPijXn8VaPqV94Q8aBFUa5pUu0zBBlEu Ij8k0e4IWVhlhGq7goxXqNef/FT4KeH/AIxTaKPEr31xp2lvLKNLgumht7l3TaGlC4YlOdpVlxuY cgkV24Or7Kqm5uK6tK+na10nfs3Y4sZT9rSaUFJ9Lu3zv0D4F/Ei4+KXw5sdY1G1i07W45JbPUtP jY5tbmJyjoyn5oyQA+xuVDgEnqe/r55/Y3WPRND8eeGFSJBofii8tYzb2bQxNGCoGHbcXOVbhpJH VdgZsbM/Q1a5lShRxdSFJe7fT0eq/Azy+rKthYSqfFbX1W4tFFFeaeiFFFFABRRRQAUUUUAFFFFA BRRRQAUUUUAFFFFABRRRQAUUUUAFFFFAHjvhv/imf2hvEVprf+lXmvWUdzoeqXH3hbx8TWKE7VGx sSBI1JKnfIzHBr2KvMPj94b1K/8AClr4h8O2cl14r8N3Ueo6cluPnlAYCaE4wzRvGW3RqQX2qOeh 7zw34k03xdoVnrGj3kd/p13H5kM8R4YdCMHkEEEEHBBBBAIry8L+5qzw7/xLzT3+5/hY6KnvRjUX p93/AAP1NOiiivUOcKKKKACiiigDxLxauofADWLrxPpf2e48Catqi3XiC1uN3nWE0zCN7qBhlmVm KFoyGIK4TAY7PZrG9t9Ss4Lu0njubWdFlimhcOkiMMqysOCCCCCK4/41aDrvij4W+I9J8NtGNXvL YwxrKVAkQkeZHlgQC8e9QTjBYcr1HimsfFr4hfBzwrpa3vhnQvD2haTa2tpDpmr6utzqWpIjLG5g aEhcqhQtlPlzu+YfKPnKmJjllaUZp+zavs2k9b6/p9x3xpPEwTjbmvbfft/X3n1FRSKcqDS19Etd TgK99YW+qWM9neQR3VrOjRSwzIGSRCMFWB4IIOMGvmbxj8Kte+ANhb3vgHxnc6F4bvL2ytdUiv4o J47XeRC14WlwBkmPcqgZJzkKoC/RvibxNpng/Q7zWNYvI7HTrRPMlnkPAHQAAckkkAAZJJAAJNeC LY+Kf2mdc8N6lqmgpoPw0sroahFb3siPc6mR5gicptbahG0FDgFZGIZ8qV8DNI0qnLTim6vS1015 trZd+55mMUJ2il7/AEtuvmtkd38NPgDoHgXU11+8u7rxP4sdMSa3qsxll5RUIQEkKMKQCcsAxXcR xXqPlpkEKuR04rxe3/Zli8PxkeGfHXizQEhd5rKyjvxLZWzli4HksvzoGPKsfmGck5JrmvCnj341 eLpdUu7O38KXEHh3V59PvdPgaeGW+eFcPHG77lUNvBVjt+ZRu+XIKpV44FRpTouLfbW/d9/vNqKl Rpu1OyW9tf8Agn0hXHfEn4paL8L9PtJtTFxd3l9MtvZaZYRiW6u5CQMRpkZxkZJIHIHVlB87f9rH RG0OxS20TVNQ8Z3KSK3hS0haS5t5k8wMkpA+UBojnjeFZWMeDXEz+M/Fq/Fqy8c+Mvhx4mW1srWa y0XS9Fi+3iGXcUnnkKyKAWBZVJTa6lSM7AxqvmkJxUMK7ydtbNqK7vz8u562CpxxdRwj0V7bX7LX /h7anvXw9+I//CwPt/8AxTPiHw79k8v/AJD1h9m87du/1fzHdjbz6bl9a7GuB+HOueP9d1HUp/Ff hnT/AA1pR2iyto777RdqwC7i5QFGViTggqV24KtndXe16mFm6lJSk235q34GdSPLNr9bnhX7Xnw3 HjT4by6wk8kc/h+Oa9EUVvFIZl2fMCzlWQDaGO1uin5HYIB6x4D8S/8ACZeC9D137P8AZP7Ssobv 7Pv3+XvQNt3YGcZxnAzjpXG/tMeJrvwf8EfE+pWUdvJcCKO3C3UIlj2yypE2Ubhvlc8MCM4yCMg4 n7MPxB8Har4F0rwroPiS41nUdLskeePUI2iuFVjkgKeCqE7AEZgg2DceCeCPsaOYSSdpTir672va 34nqU8pby2eY06bb5+VyV3okt+i3Vu9/I9rrw/xR+yX4W8Z69q8uraprkvhjVbn7feeFrfUZYLG5 uTuLvLsYMwL+VIFBG14xyVwq+30telVw9Ku4upG9tjy6dWdK7g7Hzb8L/EXj/wCBviiy8E/ER4dW 8GanrFxpXhnxdd6r5+oSyMJLmCO+MrDe0iFoUKKCJLfZtKyRue7+JH7P+meNNel8TaXrGqeEvEzW r276jo05hNwMDZ5wGC4UqvAKkgAE/Ku2z+0N8O5fiD4ARtP06bUvEWhX1vrmix2+oJZSLeW7bkKS SRSxbipdQJY2QlsHb99eq+HvjnT/AIleD7DxBp0N5a2915kb2uoW7W9zbTRyNFNDLG3KvHIjow5G VOCRgnCVCFROhU1XQ7IYmpSftqT5W9Hbr6rz/Q+bvhDrfiP4daLYeMIfCGqa1Ya3YWuk6jp9jGZr 20vLCQ2u4x7VKoYY5GwQx8wBSyAgn07UPiX8Pfi9Zw+GdbnvfDmvSXUS2+n6nE1jqVldEM0EsTHI WTC7lZSR86KeZArZfjXQ/EfwFvta8ZeD4v7b8M3c82paz4amaOLy5GjLTXcdwx3DmNP3eGHzNgDj b6ZfeHvCPxg8M2F7f6XZa5pt5a+ZaTXNv86RzIDujYgPGSNpyNrDA6EV49HC1qcXQpyWm8ZLR92m u/4djvxypyksXBe5Juzi9Y/3Wn2W3fo3qb8mh2Nxov8AZVxB9tsDB9meK8Yz+bHt2kOXJL5HUsST k5zmvKL74SeMfA95cXHw08TWenaQ0hnTwpq1p5liJXP7zZKp8yGPneI0+UPnoGIHSeALTxx4b8R3 Xh7W2j13wvb2ofTfEUkoF4xD4EFyufnkCn/WKACEycs5C+h17MYwxEFKUXFr5Nf5r8GebSxNTCtx g00+jSafyez8910PK/2UMf8ADLXwcx0/4Q3Rv/SGGik/ZO/5NZ+Df/YmaN/6Qw0V3HCeq15V+0t/ yTrSP+xz8J/+pDp1eq14z+11rkHhj4MLrNykkltp3ijwzeSpCAXZI9esHYKCQM4U4yRUykoptibU Vdnl/wAb/EFrZ/Eb4o3C3cmj6bbeFV0vUFBjVNR1GeNzaqU5aQ+W5w4AKiJskJnd1Xwv/aI+GHw5 +GPhDRb7X7Wzu49Kt5JreytpJgkjIDJvMSMFcvvLA/Nk5I555H4a/D2x+OnxQl8aeNPE2i69HLCl 5Y+FrS+W4ktoicpFcJtXasW5QVAw7sSx5YP9N+G/AXhvwh9o/sPQtN0j7Rt877Daxw+Ztzt3bQM4 3HGfU18plsMVVnPEQaUZN2vq7Xvsmrel/M+mjjMB9VjQqXmtJe40vsrRtxeq16eR4h8ZPFXhb4le FfB3jnT7xNf8I6Lr0S6tbzbxbJC7CN5Jrfh2kQlNq4ORKcqyMa9E+NXw0vviJ4JufD+htp2mf2te 28mqXdxE28woVJdQv35R5USjcQCq4yOCOYu/D+m+EPjg+hXVhbah4Y+IUEly2mzRLLFFqFqA8knl kBFV02sWwztIoJwBXuHH4V20cPHFSrqst7KXql+TTR5uIqQpyi8PflWqv/WrTur217Fe9sLbUrKa zvII7q1njaKWGZAySIwwysDwQQSCD1zXyd44+HvhXwD8UNN8O+MNRubP4TvZXOp6Tpkl1L5CXiKi zREhmlb5S0q8rl5dq5LMH+uq8m/aS+H58Y+BF1Ky0231PXfD8y6nY21xB5q3GwhpLdlClnSRAR5a kbmWPJwK2zTCqtQcoRTlHa/XyfdeRxUKdOpVSnG7ei1tZvZ37J2b8jxHxF+0Na/FdbXw14X8K+JI vA1mkS6rDo+lia4uIQwAswIpVEELRq4Lq+4/dChQ276P+D9v4Kk8C2N34EtLeDw9cbjE0Nu0RkZD 5TM28B2bMeCzZJ25ya8L+GOh+Kf7Lh1v4NeKNL1DwjcI8Q8O+JI5B/ZT7/NMeY8szhpZMliMqUyZ AEYeoeCfj7ozWN5p/jW/0vwp4m0u6exvbS6ukgSV1AIngEhDGFwwZSR3I5xuPLl94P2mIfvNb20/ 7dd9j6zM8LSjF0sBF2VrrmbfZ80GlZ37aLbW6Z6nqF/a6RY3F5eTxWlpbo0ss8zBEjRRksxPAAAJ JNeEv8SfFXx6uzpvgOzudE8GP+7vvFN4jW808fnbH+wEg4bYkmGZcgnny2AJo/GT4iR/GK90v4Ye AtYs71tcVpNW1ezlaZLC0QgkEx/KTJgpgsByFIHmBh6F8VPEEnwR+Ct1feHLW2B0aC1trS3ug8kY j82OIA4YMcK397OQM5roxNb2qm1O1KC95rr1svTr9x4lbASoUqMpNxqzldL+6tFdNfae3kuzR0Pw 4+GuhfC3wvbaHoVr5NtF8zyyYMs8hA3SSNjljgewAAAAAA6hmCKSTgDvSqcqDXiH7XHiRrT4ZDwx YSyf8JB4ou4dNsLeCZY3kJkUuDlh8hX5GPT96oPDZr0ak4YWg5xWiWi/JGWGpVMzxkac5e9N6yet u7fotWdt4I+Mnh/4keJNU0vw282q2+mRK11qkQUWqyM7osSksGdj5bMGRSmB9/JAruayPCPhnS/B 3h2x0bRrSOw060jCRW8XRe5JJ5JJJJJySSSSSawfi18ULL4U+FxqdxaXOp3tzOtnYadaIWku7lwd kYIBxnBOcdAcAnCmvaOnS567V1vY55UlVrunhk2m9E9/wL/xE+Iei/DLwxc63rdz5NtH8qRpgyTy EHbHGueWOD7AAkkAEjhv2adH1FPB2r69qlrFaf8ACUavca9b2qy+aYoZwhQM2AM4GfoRnByBV+GP wZ1G68QXHjr4kPZ6z4pvEia2szDvi0cK7MI4iWKkj5PmAypVsM25ma38UPjhd6F4jj8GeB9F/wCE t8aywvM9osojhsUCZWSdyQBklcISuQR8y7k3eXGU6k44rEe7FaRj116vz8unU5MFhMTj614K1k9N FZdXJvRf11PXdyrxkCszxL4o0rwfoN5rWsXsVjplom+a4kPyqM4A45JJIAA5JIABJr5/8F/BP4me N/7Tu/iX488RaVqFvcG0s4vD19FbQTwLz5/7pQDvLEAMiuAnzdQF6D/hnDXdE0a60vw18TNYtrG+ 8z7fba/awatFNvJLbVcKE3F5C/XeW56c+hiKmIpOUYU727NP572/E9ONHC2hL217tX0asnvq1fT0 flfr7F4Z1+38VeHNL1q0SSO11C1iu4kmADqsiBgGAJAODzgmtLNcj8J/A1x8Nfh/pPhq61aTW5bB XjF7IhQshdmRQpZsBVIUDPRR06VJ8SPAMHxC0OC1a6k0/ULG6j1DTb+JQ5tbqPJjk2H5XAyQVbgg nocEaKVWNFScbytt5nLVhTjWlCnK8U3Z910dtzqqGG5SBxxXE/Cnx9P420OWDWLWPSvFmmP9m1jS VY5t5edrDPWORQHVgWUg4DNtJrrdSupLPT7m4htpLyWKNnS3hKh5SBkKpYhcnoNxA55Iq6VWNamq kdmZODjLle55d8OfFWqeGPiBd/DLXr2TXJ7WwGp6brMh/fTWfmeX5dz6zK3G9eHX5jtbOfWq+cPg 2fFHxi+Ilj8RdZj0rRbXSlvdOXT9NkkW/VjIFFtfBlwwQAuF+XDMrbRnFfSFYYSbqU79L6X7Hq5p RVCuoac9veS2Utntp56aa6BRRRXaeOFYHj7xJP4N8F61r1vaRXz6ZaSXjW805gV0jUs/zhWwdobH HJwDjORralqEWlafc3k4kMUEbSsIY2kcgDJCooLMeOAoJPQCvnOz+JXxl+LHhrU/EngbTdB0zw9c GePTE1B3bUJFQFN4wTEGLhsB8AEYO5fmbjxFeNL3Nbu+yu/U9PB4Cpi05pqMU0m5Oyu9l+D+SNnX P2zPAenx6J/Z91/aM17NbfbIfnU2NvKgd5GZUdHaMEBo0YnORnINe0+G/EmmeLtDs9Y0e8jv9Ou0 8yGeI8MOhGDyCCCCDgggggEV5b+yd4Gg8F/BnSom02707UbuSa5vYr+3aCbzt5TmNidoCooGMbgA 2AWIrG1K3vP2ffinqviaaeT/AIVl4id59QWMSSjTL5gD5zIA7ESuCuVwMygNjZHnzvrGIw7Veq70 5eVnHzev39vQ3xdDDRqyw+HveGl73Umt7aKyfTf7z32lrg/BPx08C/ETUGsNC8Q293fD7ttKjwSS cM3yLIql8BWJ25wBzjIru8ivXpVqdePPSkpLy1PInCVN8s1Zi0UUVsQFFFFABRRRQAUUUUAFFFFA HlPxC/Z10Lx14sXxPa6trnhLX2gNtc6h4bvBaS3ceV2iU7Tu27Rg8HAAOQq7fOtS/wCF0fAzxM3i DUtbPxP8DmCS71r9zb2M1ksaKGkijLDoiBgqHax8zKqzBz9N03hlINetQzKrTj7OrFVI2taST08n 8St0s+x5VbLqc3z0m4Sve6dtfNbP5oyvCPia28ZeF9I12zSSO11O0ivIo5gBIqSIHUMASAcMM4J+ ta9fPHwj8NW/wj/aL8Y+DdMvpG0TW9MTxLb6b5AWKzc3DRSJGVcKo5XAEfKhAWHlfP8AQ9c2Mowo VbUpXi0mtLbq/wCG3yOjB1p1qV6itJNp/L/PcKKKK4jtCiiigAooooAKKKKACiiigAooooAKKKKA CiiigAooooAKKKKAExxivHvhaR4N+L/xC8ISHZDqE6+J9PMnzSTLPhLkll+UKsqqqqQGwSfmHNew 1598PfgjoXw81y91yK81XW/EF4hhm1bWbxp52i+T92cAKQPLXBI3ds44rzsTTqTrUpU18L1fla1j enKKjJS6o9Cooor0TAKKKKACiiigAr50+M3g248KfEO6+I174as/HXhZraGDUrK+BuLnT4l3b5La Jh5YjGEds7myZOUVmYfRdJ161w4zCxxdPkbs1qvX0NqVV0pXRzXhX4leFfG3lLoXiDT9TmeAXH2e 3uFMyxnHLR53JgsoIYAgnBwao/Ev4raL8L9PtJtR+0Xl7ezLb2WmWEYluruQkDEaZGcbhkkgcgdW UHw7456H4M/4STS/CXgjwhZyeP8AzEdLvSY5LZNGV3QC5nNtg5UlGXcDszuPBCv6n8Nf2f8AQ/Ae qLr97c3nibxayYl1vVZmllyUVCEBJCjCkAnLAMV3EcV5dPFYytOWHgo3jvJXsvl38r+pxVqqnLkw vzb6f5v7jj9M8C+Lfjv4m0vxF4/0+Pw/4T090nsvCMx883LGInzZyCuCGZcK69AyFFyxf6BVQqgD gUfSivVw2Fjhk3fmlLdvd/12FRoqld3u3u31CvMfhH4L1rRfFnxE8Q+IEkjv9b1cpbAvEUaxhXbb MAnQ7WZTu5+VcgHJPp9Fa1KEalSFSX2dvusdkZuMXFdTybxX+znoWta5e6zo+r694O1G/czX8nh3 UGtRev2aRcFcg7jkAZLsTknNTfAbx5rfizSdY0bxZHbp4q8O3rafetF8v2hQoMdz5ZUFVkBJBwA2 0suAdo9A17xNpHhWzS61rVLPSbV3ESzX1wkKM5BIUMxAJwCcexr5W8VfFbSvhd+0BrPjLR7qy8a6 RrOnwnUE0krJLpqI0MO8yhWUg7RhN67mZQ2MRs3jYzEYfLZxqXSTfvLyfW3r+p1VsfU+rONeLmla 0usUvPtbS3p2Prykrk/APxU8LfE61urjw3q0eorauEnXY8TxkjIyjgNg84OMHBweDjrK9ynVp1oq dOSafY86M41FzQd0cL8ZPhnJ8W/CS+HW1iTSNPmuoZb7yYFke4hRtxiUt9wlgjB+cbehBIrjPir+ zvDqtzbeJ/AQs/C/ju0uVuF1JA0aTg7/ADFcLlSW3klijFsbW+Vjj26krmr4KjiObnWrtr1Vtrdr HY8VX9g8NGo1DXRO29r7d7L7jhvhP8QpvGuhywazbx6V4s0x/s2r6UGObeXnawz1SRQHVgWUg4DN gmu5rhviF8H9B+IFzb6lcNeaTr1nGY7XWtJuGt7uBCcsoccEEFhhgcB3xgsTXh/w3+LXxNFtr8Ok LpnxJ8P+E5PszahGJ4rvVVw2PJkIZHdAFLcEsMbTIXDtxvFzwbjSxCck9pLW9u6/yv8AocEI14wl JwbjHeS+5X8/Q+qeteZfC74T3fwz+IHxGvbS+hbwp4mvodatdNVT5lrfurLfMzNksshWFx82FJZQ igZbqPh58QtG+J3hm21zQ7jzrWT5XjbAkgkAG6ORc/KwyPYgggkEE9NXqRcKyjUi7rob06l4Xg9G cb8YPFWpeCfhr4g1zSLCPUr+xtmmSCaTYmB9525GQi7n2ggttwCCRXgHwC+Jev8Awf8AhroUfjPw zLpvgI2/m23iK3kFyVeaSSZWlijLOsbiREB28MAD98bOu/bJ1qaHwVpOgXMlvpfhzXL1YNS1y4V5 fsYjImRVhQbnZ/LbHYbMHG4Mvt/h+PTJPD9guki2bSfs6C1+ybfJ8raNmzbxt24xjjGMV5c4yrYx uE7OCt0s767b20XX9T62lVp4PKIwrUlNVptt6ppQVlZp2T1lo0+7TTRkeEfip4R8eNGmgeIdP1Oe SEXH2eG4UzLGcfM0edy4LAEMAQTg4NdVXyy37KOpW3jm7m0K+/4RSS11ObWNK8RafbxNGI5toaxk g3K48sr8pBaNkeQEAttrsb3w78bvAtrLa+HNc0Txnp8KF7dvEEUkd/gDCw742VJDhV/eOVLMzE4F XQxWIcX7ek1bt/lucVbA4GpZ4TELXpO6a+aXLt5rrodD+yd/yaz8G/8AsTNG/wDSGGil/ZRx/wAM t/BzHT/hDdGx/wCAMNFeufPHqdeS/tRWcGo/C/T7S6hjubW48X+FYpYZkDJIjeINPDKwPBBBIIPr XrdeU/tLf8k50j/sc/Cf/qQ6dS30YFnxb+z34M17RpodN0PT/D+qoDJY6pptuLea1uApEcoMRQtt YhtpOCQPQEchpvif4mfBnSYtX+JWo6Z4l8NmRUv73T4il1pzPJ5aMFCIssI+TOF8wGVsBgnze+VB fWNvqVnPaXcEd1azo0csMyB0kRhhlZTwQQSCDXnzwcU+eh7svLZ+q6nRRqRo03S5Fyyab0XNp0Ur XVzyr412txpviTwL408mT+x/DlzcS6leWSGS6toJYghYRnKtD/z1IUyKoymMMa73wn498O+OYrmT QNZs9WFs5jmFrKHMZDMo3DqASjbT0YDKkjmqXgH4W+Gvhjb3lv4asZtPtrt1klga8nnj3gY3Ksjs FJGASoGcLnOBjf0vRdP0SFodOsbewhbbmO2iWNTtRY14UDoiIo9AqjoBTpUKlOq6iatKza87JaP5 diZTUoqL6belzF8cfEzwx8N7KO68Sazb6XHJnykkJaWXBUHZGoLPguudoOAcnAq54d8ZaH4t0/T7 zSdTt7231CFri22ON0kalVdgp+b5WZVYEZUkA4PFeH/HT4HXnxa+MXhNm8OINAhjU6pr5uyWaJGk cWohEilQScGRVJ/ejBAQg1/i18MfDvwLu9I+KXhfS49PfRtREmqWscjsk9tcHyZBFGW2q6+b8gBR Bk5zgCuOpicXCrOXIvZR9U/N7a2/pnpywEKjw0MPUvOonddne0Umm9X2dmrpm94kuIvCP7U/hD+y /MhfxTp9zbatF5TLBKIEMkEoIAV5hhkJJYqhAwu4E+oeIfhv4U8XXq3mt+HNL1a6VBEs97ZxzOEB JChmUnGSTj3NfNHjy60fx58QviXq/ijxbrdt4a8Etp0lhDoNygEdwyMDtG0jzhNlQ5IKkkFgF+X3 TUv2gvA+n/DqbxpHrKXejRyNbp5KkTSzjpCsbYbeRyAQPlO44X5qjD4qjKdWNRpRu2rtbLR6drpv 5nbjqdWnVw2HpX9tyRWl7vm95fNRlGNuljqvDfgXw54L+0NoWh6do32jb5xsbWOHzNudu7aBnG44 z6mvDfEV5pv7S3xZ0jRba0uNT8AeHvtT6lf+bNHZ39yUVESJ0wGaMupDbhlWkI+XBfB+InxI+IHi nTbTUtZivvhn8MrrUCk+pQQS/wBrwQxj5PNCkmITSDaCq/KSASykeZ1nhz9l7SYdEszoXxL8aQ6Q 6ebbLp+sokBR/m3IEj24O7OR1zmuatN49qjSh+7Tu09L9Vo+j79djKjShGDxGIqtTbcdpOzWj12v 2s3pqfQI6cV4f+1do2pWfg208deH7iS08SeFZGmtpooPPPkzDyp12HKgbSHLFTgRnpkmuI+I3xs1 7wv4+0v4deGtZGlwaBDD/afiLXkN0twxhTyVuGUfJE7vEkk3BDSZG0L8+X8WPCfxW1RfDPhTxv43 09fC2vzQ6dPf2OnI7NeHM0ayIFRuZVEashVdsYZwpJBrF5jSq06lGEW2tLq2j6dej67aDy/2WX42 jWr1oxjdcyab91/zJJ6Sj07PWx758FfAcHgfwnmHxFeeKpdUdNQm1a8nExuHaGNAyNz8hWNdoLNg fxEYrifipocV5+0r8IpbwQ3drKmoeXbTKzBJIofMEgDMUzkoQVQMCgJZsKE9s06xttI0+2s7SGO2 tLeNYooYlCJGigBVUDgAAAACvD/jfr+n6D8QPhB47mvbeTw7bXlzZtcxSqQftdviKUNnb5QCFmbd wMEA124ynCOHjDazi/ukrnFRpzzLFtc7UnzNNbtpNpafzWUfme7yYWNgTgYxXgH7LNnpmk+IPinp cRjk1W28RzSSyeb9olNs/wDqN8+WLnKy5DMWVt24Ak1y1/rHiL9sDVta0zwxrlx4S8BaX+4a+W3k MmqyuCGUjcn7sJnKFs4dCyncAn0R4E+H2gfDXQ10jw7p0enWIdpWRWZmdz1ZmYlmPQZJOAAOgAq6 dR4utGrCPuRvZ9+mn+Z6daisrwtTDVpv21S14L7NrNcz7tP4Vt1aas+i6UtFcR8Vfippvwt0OO4u I5NR1a9f7PpmkWvM97McAIoAJAyVy2DjIABYqp9CtWhh6bqVHZI+ahGVSSjFanVaPrVh4g0+K/0u +t9RsZc+Xc2kqyxvglThlJBwQR9Qau15j+z34L1jwb4DnfxIkkfiXV9RudU1NJHiYCaR8ZXy/lAK IjYBOCx6dB6dUYapOtRjUnGza2HUioTcU72PEfFmo/8ACE/tNaBreqW1xHo2taKvh+2vo03xi9a5 Mixvg5XcMAHHJPorFfbeGX1BrxP9q+ezsPA+i6i0lx/bdhrdrdaLa29uZ/td8pYxwsgIJVhvzhge OMnCt654fvLzUNC0+51Gx/sy/mt43ns/NEvkSFQWTeOG2nIyODjNcuGj7KtVp3um7/ed1ai/q1LE d7r7rf5njnwxvrTwL8ZPi9o9zcRaRoqtb6/BHduI1IkiJvLkM/JjDqAxztQjHy9K90rxL9qz4beE /FHwt8Qazrdpbw6lp9m0trqWVjmWRNxii391Z227DwS/GGwRH+z78RvHfxcdPEerQadpPhaO3ktY 7O3jkE1zdDyMzBmBBiBE6ja3BYq24ruqqdajh5xwsm+eTk1ppbda/h93y2xkamKh9eikopRi+/Mo pN+d0r33vfyv7jSE468UteKftPfFrQvBXgXVdEk1k2Pia+s2ksIbe4nhmDAjbJ5kKkp8w43bVcqV JxuI6q9aOHpupN2SOTB4SrjsRDD0Ytyk+iv8/kcl+1d8SIbXxB4c8C6hrsnhrw1qySTa3qNqglnN uMhYlVSXUOQylimDkYLASLVzw/8AtQfDHwnYWHhfwRpmra3DbosdrYaLpzs7giRnIWQqzFdm5ieT 5gOW+crS/ZH8I+Ko9a8Y+I/HWhyxa3qDW7RapqCYuZldN7RgE4RFHk/Kqrg5Q8x7U+lfJjHSNQfo K8fDQxGIbxSfLzdGndJdN167fefWZjVwGBjHLJRdT2a1lCaUJSevNblbdr8vxbLZO5m+F/E2l+Mv D9nrOi3cd9pl4nmQzxdGGcEYPIIIIIOCCCCAQRWrgHrQAF4AwKWvdSdrM+IlbmbitDz345eH/DWo fDnXNU8ReHrbX4tHsLi9jhkYxSfu08wqky/PHuMagleo6gjiuU/ZC+HsPgf4M6NesP8AiZ67CupX bx3ErxP5hLxMI2O1H8po1bYoyUGS20GmftZRal4o+H8XgXSdE1PUL/xNcQQR39tatJZ2Pl3MDF7p 1yY0IJIO0/db0r2bTdPttJ0+2srO3itLS3iWKGCFAiRooAVVUcAAAAAdMV6ap0qGCvBJTqS178sV pfybb08vQ8rmnWxrT+GC07Xlv87JfeWqKKQ15x6Z5z8VPj34U+Es9nY6pLc3+u3237HomlwGe7uN zhBtXIAyScbiN21gu4jFUvCP7UHww8cazFpOk+K7d9QmwIorqGW181iwUIjSooZyWACglj2HBrT+ H/wZ0rwP4m8S+JpJpNY8Sa9dyzT6ld/M8UBfMVtHknbGihF6/NsHQBFXovGPgPw/8QNFk0nxDpNr qtg+T5VxGDsYqy70PVHAZgGUhhk4Ir1r5fGKhyyb/mulr1922y6e8m99Nl5KWPk3O8Uv5bP877/I 3utLXhf9lfHLwKfsej3fhvxp4f0//j3bWJJ4dXvIRyInkH7rzcfuxKwwxAdhkkVJ/wANAeJ/CLC/ +JPw4uvBXhn/AFb61b6lHqaQyH7gljhXeqMRt34I3MgP3siVl9SprRlGXpJXfpFtSb8kmX/aFOGl aLj6p2+9afez2+isrwr4r0nxt4fstb0O+i1HS7yPzILiI8MOhBB5BBBBUgEEEEAgitWvNlGUG4yV mj0YyjNKUXdMWiiipKCuG+M/xV0/4N/D/UPEt/H9paHbFbWayrG9zMxwqKT+LHAJCqxwcYruawfH Xg3TviD4R1Xw7q0fmWGowNBJhVLJkcOu4EB1OGUkHDKD2row7pRrQddXhdXXl1OfEKpKjJUXaVnb 1PLP2dfhDq+gq3jjx3c6ne/ETUoJbW6F9epNFaQ/aHcRwrH8iqw8ttoJCnhduSK9xrwb4c+OPEfw x8V+EfhN4p8PxG2ltZrPRvEtjdKY75LWJWBe3PzwkRbQ2WPzj5QVOR7xXdmftpYj2tW1p6xtty3a VtXZK1rbq1nqceW+yjQ9nTveOjvvfrfv69RaKKK8k9QKKKKACiiigAooooAKKKKACiiigAooooAK KKKACiiigAooooAKKKKACiiigAoopGYL1IH1oAWimiRG4DKT9adSunsAVR1zWbTw7o19ql/L5FlZ QPcTy7S2xEUsxwAScAHgDNXq534iT6Za+AvEU2s28l3pEen3DXlvCSHkhEbF1U5HJXIHI69R1rOr JxpykuiIk7RbRyfwPS48SaXe+PNRwuoeJzHMluvnBbS1jUrBAvmYzjLuXVVVmlYjK7SfTq80/Zv/ ALU/4Uj4S/tf/j6+xjy/u/8AHvuPkfd4/wBV5fv685r0uubA64aEurV36vVmWH/hRfdX+8KKKK7j oCiiigDM17wzpHiqzS11rS7PVrZHEqw31ukyK4BAYBgRnBIz7mvN/hd8CrPwfrXjfUtUsdKnOuXU kFva2ttGIIdO6JCUEagFgcSAZVtiE5OSfW6K46mEo1qkas43cTRVJRi4J6M8z8U/s9eD/EV8mpWt tceHNchhjt7fVNCuGtJoI0G0BQvyfc/d5Kk7eBjAx4r4n8VfFDwJ8TIfANn4r1nUNNaGG6TVo9Bi 1C8trXLxhiiEtKoYoHkcByyZVecSfWteJ/G62tLT4ofCy/W1khv5tW+ztqEcUaJ5YRsQvPvjcElz tjD7XzJmOUgIfHzLBQjTVSg+R8yvytq93Z3scLjDDyVaMev33016P5ntg6ClpF+6KWvo1sdQhrx3 4cAeBfjL428Gkedb6wD4ss5erL5riK4SQ8AfvFGwBT8ucsTxXsdUv7F0/wDtf+1fsNv/AGp5H2b7 b5S+d5O7d5e/G7bu525xnmuSvQdSUJxdnF/h1NYT5VKL2Z5N8B7251Xxp8Vb2KK2sdE/4SFrSCxg 27luoUVLiY4Uf63ETdTzu75LezV81eJpLX4TftUeHbi3T/hH9D8WRPHePaqZE1O+LbVSWPfiPazx MJFQEtK+4kM5X6UzxntWGA92EqUt4t/jr+p04nALBQpShJuNSPMm/Vprto09ultnoo7pVaCTcARt PX6V49+x7/ybz4X/AN67/wDSqWtT9pHT/E+q/C3UrPwwnmNcYi1BIoRNctZMCJhBGSA8mDwpIyNw UhttSfAXxR4PvvA9tofhaaSBdDjS0u7C9h8i7tpcZYTJgfOW37mA2lw+CcGqlL/bI30tF/O7W3pb 8T0YRccpny6804t2+yoqS1/xOenoz06ikVgwypBHsaWvRPAPKv2Tv+TWfg3/ANiZo3/pDDRR+yd/ yaz8G/8AsTNG/wDSGGigD1WvKv2lv+SdaR/2OfhP/wBSHTq9Vryn9pb/AJJzpH/Y5+E//Uh06gD1 aiuO8CfFLRfiRqGvQaELi6s9JmS3bU/LAtLmQgllhfPz7cDJwB8ykZDAnk9W+LPi7wLrOr23iPwJ qms6e1050m/8KW32sS24wQs6F90cgyAScBju2jC5biljKMYKpe8X1WqN40ZylyW1PXO45pa+aLP4 4GHx9ceLfHlt4n8G+D4F+x6FBe2UsMUk5RTObmOMszyHP7rcDHtSQj51JrtrP9rj4U3t1Dbx+KQr zOsatNZXEaAk4G52jCqPUkgDqTWdPMMPO95peuj+5/gej/ZONmm6NKU0t3GLaT3tddup6P4v8YaR 4D8O3Wua5d/YdLtdnnT+W0m3c4RflUEnLMBwO9eG/tBfE7SfGHh7R9F8P+LNPl0XUNTgtfEFxpep RNNb2LsEZmwGCREsA0jEAHapDCQitT44eLtC+Ln7Pvi4eE9d0/UmhtIb6UJMC0caOs5DpyyMVicB WAORg4wcbel/Bj4X/EzwZo+pr4L0+0s7+CG/iFtALOYB49yhmhIPR+V3Fc+uAa4cY6+L56FBrlaW t99XfbocmJwdSng5Tacal7LW1mrPVWut9NdddFbXkI/2IfCK6W2njxJ4oOmNL9pFkb2Ew+bt2+Zs 8nG7bxuxnHFeJftMfDfX/h14h0i9uvGi3lnfzRLDfTN5F1DJBkRSzrEC87Rxv/x8BWfkjC5UN974 +XA4GMV83/CrwPoF58fvH99cr/wkuu6ZeteQ+II7uQraCdGj+wyRFsFo1V1BUOMDB8tlCV5+YZVh pRp0qa5ZSa1u+mu3XS/+Z6WGqrF4r6/j6s3KlaSs9W9Ek29En1dm7dGe0+E7Vte+HOlQa3cWWvvd abGl5cQhZLa8LRAOyjAVkfJI4AIPTtXzv8Hfg6viC48caCPGPi7wuuha7c2tpo2l6u0CQWbEPC/l sGbD7nIbo2CeeTXon7KUx074d6r4Wx5h8L61faT9r6fadspk8zb/AAf63G3J+7154o/sz295qHiT 4qeIdWvftutT6++lzyRxCKEpaqFjKJyV4kI5ZjhVySck+jKMMR7CU497+Wnf1O2VP6vHGU1PSLi4 +b5tHbZe62/Lbucr8WPhro/w98A2/wAO/Dkdxqvirx3qaCXUL+R5bmby5VlknmdYzlY8qCMDAd35 Icm5+0Lca38TvHWmeAfDFno+o3fh+CPxLcQ6jKWWeSNii2rKPlG5ZASrkBhIvKgZaT4D3lh8Yvi/ 4x8fXepRahfaS50vSLRLQxpb2LM5in3MNxeQCQdQVzICMOoXY/Z1S+0Xx58QtO8XQ/Z/Hd5eJfyv 5zNFdWRysLW4ZiTEjb1zj5Q6KTkbV8nkjiZL2TtCq7XX8sbv727/ACPnce508fCtTqOc2k5vpdXf L8r8r9HbSxm+OPE3jf4/abL4O8O+EdY8JaLeGOPVNe19DayRQksXSOENmTcECnDEEMVYKGD1geAv gP4a1j43eN/D863n/CK+F7nT72z8PtdPJZSzTWp3SSo5YucrnryPlOV+WvpnxN4k0vwfoN5q+sXc dhp1qm+aeToB0AAHJJJAAGSSQACTXyx8IdU8YaX4g8T678N/Ck+t+FL+dbq5tfEUsVrqLzsquI47 gyMzrtnSYNKCCu7B3MWfoxVOnSxFFVv3kr66XaVnbRdL/wBduzB5pVoqOChyqTTSls024tu72uo8 t7pJfNn1np+nWuk2UFnZW8VpawIsUUMKBEjRRhVUDgAAAACrNfPkml/HXxxqkmvrdaf4CXTpomsP DN1It1FeYUiVrieLJ2kOwCgdVHCMokOhp/xB+I3wrs45/iZplpreilFjfWfDEUkr2hXG+a6iIX92 V3MXjXC7CNvzKK9qOMj9qDjHu1p/mvmiquXyUuWNWM56aJ3d30T2b9G12bPcq8B+HPgbQl+PXxAT xBp8eq+JYLqLVdN1LUSzO9rKFZRDE5IxbugjEq8jIX5cba92sNSttUsIL2znjurSeNZYpoXDpIhG VZWHBBBBBFeE/B/U9V+Jfx88f+L7q0h07SvD4k8I2UcZ3tcNHOZJZHbdkEEKcbQMSgZJQk9FfAyx kY14pNU2m722emnnrf5HkLExw8/YyunO6Xy11Pf6Ka33TzjivH/2ffGmpzfD7xBZ+Iru61e88Iav e6JLqhjaWe/S3IKy+WoLFijKu0b2YrnLFq71TvTlUutLaddb6/Lr6mXNL2igot369PT5lj9pfwVq fjL4cltJkk+16TdR6oILZP8ASZxFlilvJtZopiPuuqk5G3oxqHQ/2pPAWveE9U1jT765updJsVvb vTUtX+1InQgJjDbTgMykouQWYKc1y11+1Nqvi3QrGfwH8OPEurzXl3HEtxfWflWZj37ZCJkZlB4K 5YhVJLMTtKnH8D/sr6l4o8PXOr+NvEvijSPFGuGT+2bSx1GFYplDuqKwRGUr5ZGFyQAxAAHA+Zli J1K/Ngveutbp202s/nt2PuaGFw8MFKGavk5JWik1zXduZONm7WW+lnZa9NPxX+00vjiym0rwB4H1 Tx1b3FzHZTXc9i6adJGwUyozMODtbafMVVG7ccqMNkfCH9n34o6H4Utbub4j6p4X1cp5C6TPEmoW 9pCrMAoVpGQkhYirLjaNy4OePpTQdBsfDOjWOladALexsoEt4I8ltqIoVRkkk4AHJOa0K61gXVmq uIm20umiV/TX8TiedQw1GWGwFFRhJptySnJ22vzLlXnaK9bHhN9Y/H/TbO4aHU/Cmp/2ejPb7baV J9UKjaFmBYJEWBL/ACEAOqrnYWNch+yjdT/Ejx14w8Z+J728fxraOdNn0yVDHBZ2rMrIioy5Uh4p VxuzwSw3NuP1LSKirnaoH0FW8F+9hU520uj19PuMI5ulhatD2MVKdveikmlfVbap/L7tBcAdBilo or0z54KKKKAEpaKKACiiigAooooAKRlDDBGRS0UAeJ+K/g34g8K+Or3xp8K5tI07V9WQw6xpes+c LC6O7ctyFiORMCCDkEESOeGLF8vWf2lPEHw502ay8cfD/UoPEnywac2j5udP1e4YhI0ilALRPIwk cROpdY1z8zEKfoCkKhuoBr1IY2MuVYqmppW6tOy6X7dNVttY8uWClG7w03C/zX3Hzp4f/aou/Bf2 Cy+MeiHwhcX1gl/Z6paQTyW11uwWhMW1pIpYw6Kytu5DElQU3e+6Hr2m+JtMh1LSNQttT0+bPl3V nMssT4JU4ZSQcEEfUGptQ0201axuLO9tobu0uI2imgnQOkiMMMrKeCCCQQeua8HktP8AhTP7QOgW OiWdt4Y8B+JoGjvFZttjNqKqRFHbxqu23uGVUzkqky5ABkQE6yWHxyfsYck0m7XvF210T1Tt5vXs tslLEYK3tp88G0r2s1fv0a+75n0DRSKwYZByKCdoJrxj2PM+Wf2skl8LfFT4Y+L9Nt7nxTr1vPLF a+EWt5J4p40UvLcRBQfLlTcnzYY5ETYxEQfqZeVH0r5XvPEWvftCfGXwtrHhnwpc2ug+Cdens59b 1DUDa71KJ9pR7UBZ1fhQgJ2nO2VMM6r9Udq+hzO9OhhaE/jjF31TteTaTttZa2et279DwsttUr4i tD4ZSVtHrZJN679u2gtFFFfPHvBRRRQAUUUUAFFFFABRRRQAUmQOtZnibxNpng/RLzV9YvI7DTrR PMlnkPAHQAAckkkAAZJJAAJNeNW+oa9+0hcNcaPql54V+H9pcukOoWEk1tqeoyIpXchxsW3LOeoZ sw4IUnCcVfFRpSVOPvTfTr6+hhUrKD5VrLse80V5N8IfEmtaDrN78O/GGof2n4h06H7XYaiEP+n6 eWCJI5ycSq+VYNgnggvy59ZrWhWVeHOlZ9V2fYqnUVSPNsFFFFdBqFFFFABRRSFgoyeBQAtJXkfi D9qHwTpuprpekS3vi/V2fYLHw9bG6dhsLllbIRwAOdrEj04OMSbx18YviJCw8L+D7TwZp8iTiPUf EkxM7DdsQiBRuicfM2HV1OByRjd5csyoJuNN877RV/8AgL5nG8VSvaPvPy1PRvHXxg8H/DVok8Ra 5b2E8uCluA0sxU7sN5aAtt+VhuxjIxnNY2g/tIfDXxH5/wBl8W2MPk7d328tZ5znG3zgu7oc4zjj PUUnwz+BGi+ALp9WvJ7jxP4pm2tNrmrETXAYR+WRGTkouNwxknBwWYAY7DxF4I8PeLvs/wDbeiaf q32fd5P221jm8vdjdt3A4ztGcegqY/X5+++WP92zb++/6CX1mXvaLy/4N/0PMPFv7QS61rNt4V+G K2nirxRcODJcEs1hYwjaWlkkXAYYYDCE85H3sI1OL4A+JPiAz3XxM8Z3t+krqW0DRJDbacEWVnEb 8ZlB+T5iFcYxubAYexeH/CujeE7R7XRdKs9JtncyNDZW6QozkAFiFAGcADPsKu6hqFtpNjcXt7cR WlnbxtLNcTOESNFGWZmPAAAJJPTFKOBliJc2Llzf3VpH7uvz+4XsOe8sRK/lsv8Ag/M+Rvj78NdF +COr/DzUvh1Z2+n+J7rXY7aGzkvJmlu9wI2gvNgRbiqOMc+ao3KMhvXf+Fm/Fjbj/hTn4/8ACS23 /wATXinx5/aM+H2sXekeMPATXWr+O/D/AO+g1OHTpFt4bYusckV35qqTE4mZVK8q7cMhb5vrjwn4 q0rxt4dsdb0S9j1HTLyPzIbiI8MOhBB5BBBBU4IIIIBBFfRY/IZ4LC0alOEqN7p2ildp31TT6NWe jevRI8TBTpVsVWp4erZaNKNrWta+z1vvbyPDNa8ZfHLwH4buvFWuaf4Zv9NgMV1daVaic3UER2LJ GhXKjaNzMxLhfnOSoAr3O9tdM8beF57eQx6hpGqWjIzQy5SaGRMHa6noVbgg9+DV/ULG31Sxns7u CO5tbiNopYZkDJIjDBVgeCCCQQa8D04+K/2c9Qm0m20HVPGPw/uHZ7BdIt0afSi8k8hhEeTJMOY8 yOwA+vB+XlGeBl77c6clZ31s/wDJ/gey+bDv3m5Rfzs/8n+B5rP+0f48+CngeysrLwVb+LNA8N66 /hi/1651OOxQhS8cAYbStsoLW4M0pZONpO6Tcv0R8E774oah4flm+KOm+G9O1OTy5baPw9PM3lqy ZaKZH3KHRv4kkdWyQMbdz4Hwd+GeoP8ACvxBB4meOC+8ZTXWpXtrHaKRafaowGiMc6urFR1WRGXJ KsGAJbuvhb8PLX4T+AdH8JWOpalq1lpcTQwXWrTia48vczKhYKo2oCEUAABVUdq0y6nWhSg6kna2 ztp2/A9GjUi8LCPJaXzvb7zq6KKK9kQUUUUAFFFFABWJ408J2Pjrwrqmg6km+zv4GgchVLJkcOu4 EBlOGU4OCoPatuiplFTi4yV0xp2dz57j8afE34L+Ef7Jm+H1v4l0bw5Z+WNft9YjtkntYU+WQwuG dWEagMMn5g23IIr2nQ/FtjrHg+x8Ss/2DTbqxTUC94yp5MTRiTMhyVXCnnnAweaXxp/ZP/CH63/b 3/IE+xTfbvv/AOo8tvM+5833c/d59Oa+Zvgv8L/Enxd8A6SPEHiq4Hw1WcvZ+HVcPczRRSyKsM9w ERtqsq4AyCAMCMquPn6tetg8RHD0rz5k7LTS3d6aa+bPZqTpYul7R0403F6tc3vX8m2r6dFFH1Bo PibSPFVm91ouqWerWqOYmmsbhJkVwASpZSRnBBx7itOszQfDOkeFbN7TRdLs9JtXcytDY26QozkA FiqgAnAAz7CtIsF6nFe7ByUE6tr/AIHju1/dPkzxNZeIbT9pfxz4r0tBqmreHbSym0/w/dQiSTUL J4wlwbZmOY9jeYd0atl3K4O4q30b4J+JXhr4iQXEnh7V4NTFt5fnLFkNHvQOuQQCMg+nBVlPzKwH ivwj8S6R40/ai+I+q2l9b6pDFZW1rp9ybxtyxAKJlhiI2vEZVyXBwDtxkSk1a8baKnwV+Nlv8R4d KuL3w3qllNY6sdMsk/4lh3pKbpxGu6RWKMXZgSME7jlEr57CylS5sRSd4Sk79erV1+Hlb5n0eOwV SvjIU+ez9lCyffkTstdG+q/mukrvX6G+teC/tS+FfCN5pui3uqeGbfWfEmoXkWiaVLLPLbxRyzEl TO0TBmiUhmxyckgbdxYe46dqNrq9lBeWVxFd2s6LLFNC4dHRhkMpHBBBBBFY3j3wFpXxF0F9L1VJ AodZre6t38ue0mXlJoX6o6nofqDkEg+5iKSr0XBJO/c8zL8S8DioVW3Gz1s2n+FvzPEPgX468BfA /Ro/h/q/jyC71+GeR7rzjILO1lKhnhjlZRGqqQeCwJcvkBm2j6RBzXEaf8FvBWk+A73wdbaBbjw9 eK/2i0cs5lLclmcneWBC4bO5dq4I2jHGfsp61qk3gjWvDeq3cV+3hHWrnw5bXaQ+S00FuEWMsoJA ODjjsBnJyx6MFg5wwjlKS9yysr7Pz62+W+xlm2YUcRjlKmpXqXblK2r72SXLftd27mt+yd/yaz8G /wDsTNG/9IYaKP2Tv+TWfg3/ANiZo3/pDDRVHEeq14v+13okHib4LLo908kdtqHijwzaSvCQHVJN esEYqSCAcMcZBr2ivHP2stVttC+D8GpXsnk2dn4q8MXM8m0tsjTX7BmbABJwATgDNRO3K+bYuF3J KO5N+zRrZuPBOo+HjaW0H/CK6pcaF59qnlrdeSR+/Kc7WffluTltzZ+bA9cwD1Ga8X/ZD0VtP+Cu m6jcw3CaprFxcahezXTO0lw7ysFlO45+aNYzkcEfNznJ9orkwS/2aGnRHo5pThRxtWnDaMmvu0b+ bK99p1rqljPZ3ltFdWk6NHLBMgdJEIwVZTwQQSCDXF/Fn4jeDfhzoMY8WPCbTUX+y/YzCJjMjELI THj5o1Vstx04wWZVPM/GzxJ4qHjrwD4Q8LeII/DUuvvevPqBs0unUQQh1UI/y4bJz34XB6g8JpNj f6L8YbrXfjZDpUAvNO/svSr+NUOj7dhaaJmk+ZHZWcDzcBgZ1GRtFcOLxjg3TpR1uk5Ne6tL6/1u zlrU6mGpUa178721uldq+1tWmlZvXczP2s/Afwv8O/Du+Njp+h6P4ut1hksrWzaO2ndHnRXbykI8 wbVfBZTjDYxzX1NpNjb6XplpaWkEdrawRLHFBCgRI1AACqo4AAGABXg/iX9kfQNN1DStf+HyW+ga 9pc5uoor8SXtrdMBlUkEjEp8wGHTlckgFgpXo9H+InxJj1nSJvEPgBNK0O9uk017WyujfXsEjZK3 btGPLFuMBWzhlPzZIwDFFvDVpVK0OXmsvdV1pfVu3n1PosdWjicvoUqVVz5HJvmdmnK2iV3de7e6 b3d0uvr9c3ovw58PeHfE2r6/pmn/AGHVNW/4/XhmkWKds53NFu8vdnJ3bc5Zjn5mz0lLXtypwm05 K7W3kfKqTV0nucN8Ofhn/wAK71TxZJBqP2uw1zU5NVSCSHbJBLIB5qlw2HUlRtG1SoyCW610dv4V 0mys9RtrOyj0+PUXklumsR9neWSQYeQvHtbzD/fB3cA54rVpaUacIx5UtDWpWqVZOc3q7fgeLeCf hLP8OfjY03hzSf7L8DP4e+zyeXcbllvBdM4LhmLu4RmAdgcKdoI6VXgkjuP2xbjZ5oaDwf5T74mU Fvtat8pIwwww5XIzkZyCB7jWLa+DNEsvFN74kg0y3i1y8hS3uL5U/eSRr0BP5ZPUhUBztXHA8Gqc YQoWUVK//DBPEVrp07RurPTddfm+55T+0NZnxZ40+Fng42tvPFqGstqUpumzG0VpHuliKbTu3pI3 XjIAPByPbkUKoAGOKX61zOtfEzwl4fvp7DUvFGj6ffwgeZbXV/FHImVDDKswIyCD9CK0UKeGqTr1 JfFbfpZbfmzmhRvNygrtnS7gOrAfjXnnxu+IvgzwP4Nu7fxjcbrPVIJrZbCHc012ChDogUgjIONx KgFlywyK+SdU8ba78TLPVdY0fxT4xPinXPEM9h4e0TTrww232aNYXzIiYVNkcgywbrhjkB2r6O+G n7PGoeGfFGneIPFfjTUPGt7pUDw6Wt0rRra+Zu812zIxkYhtuWPAAHO1NnFDHVMZeFCGj+07W18r 9unofazyfD5XGNfHVtdfcSak2uzs0lzaXfaVrtWPJ/hB4u+J/wAGfA95qGseF9S1nwHaz5Vr9zFq lvbZEe9YGdtsUaRZ8o7eZAwbYGYU/wBnHxh8SpvBtwfCfhVtTvdZ1CfU9X17XCsFp9smnCF4VXZv iWOE7gmWDucABQr+3ftTeKLrw/8ADMaXZpZo/iS7TQmu9QlMVvaJOjh5XIHQKrc9s55xtPffDXw7 ceEfh/4d0W8aN7vT9Pt7WZ4SSjOkaqSpIBIyDjIFbYf2lKlUy2lUfL7rb05la+ifZ3/BanjZt9Wz OEcdKKhVu0lF9HbVp310tfTd6Hg3ijxJ8Z9Y8XWvw7vtT8L+G7jWLNrhNY09LkP5auFljt2c4adU y20AEKQdynBHeeJPCt38EvgL4kXwheeZrFtDcajJqeq4lmnkLGSaWRgo8yXZkKWB5VA2QDXM/Fn4 N+OviF8XH8QaVq3/AAj0Gh6Yn9hXaXRdXvDIS++Lb8qlMo/XK+WfnG5BzXjD9opLjwD4+8DeNJ7P SPGttazWSva2dzJaXvmRnAjDBWQ7Tt3P8uSsil1O2vNdSODVV4hvqoyb8tl2d/v0PRjCGHwdCVOo pQhaVRWV03LS7t7ys0rX0d1Y9g/Z58I6V4V+F+l3Gn3N3fPrSLq91fag37+5mmRWZ3G5gpxtGAT0 5LHLH0KbVrKC8itJLqFLqWN5Y4DIA7IhUMwXOSAXQE9ty+or5h+D/wALdY+KHgLw9eN8XtYfRbOy W1j03QI10+WymCxgwySKSZNgXA3rkghgcN83c2f7H/gGaS4uPEA1bxZqU7731DV9SlacgKqhS0ZQ EALxkE9s4wB34WtVnQg6FNWst3/lczxNLAzxE6mIxLldt+7Bt/8Akzh/WiOh0j9pf4ba94nh8P2P ieGfU5pzbRL5MqxSSAkYWUrsOSMKQ2GJAGcjPpysGGQcj2rlf+FW+Ff+EF/4Q3+xrf8A4RzyfI+w 4ONuc53Z3bt3zb87t3zZzzXBaZ8IfGXgbxBpNl4R8ZSweCftaz3lhqq/a57aJM4trZ2BxC67UwxD JsDKxLMD2RliKdvaJSv26fe9fX8DhqU8BWv9Xk4W/n1v84rRv+Wz/wAR7RRSDpS13HjBRRRQAUUU UAFFFFABRRRQAUlLXkf7SGseIvAvg/8A4Trw3q0dtdaAj+dpd8V+xX8MrRqwkBdCJEIVoyrbidyA N5mK6MPReIqxoxdnJ2V+/Q58RWWHpSqtXS1+R65SVQ8P65Z+JtD0/V9Om+0WF/bx3VvNtK743UMr YYAjII4IBrQrBpxdmbxkpJNbBRRRSGJWV4q8K6T428P3uia5Yx6jpd5H5c9vKOGHUEEcgggEMCCC AQQQDWrRVRk4NSi7NEyippxkrpnzN4i1DW/2SdSu59D8OXWq/B1YLeWeN9RRpNJuJJ/Lk+ziRjIy sCjGM5BdyQ6DdX0sXEkRwRyvrWN458G6d8QvCOq+HdVj8yw1GBoJMKpZMjh13AgOpwykg4ZQe1fO c37J/jXw/a6Dp3hn4i6lBbXV+134pvEvprSa9YykiaEASFZTFI6Nl9rmOJmBIzXvqWGzCnF16ip1 U3dtN8yte7310a8215s8GUcRgZyjRg502tFdLld9l5flZ+hT/Zp1Pxp8FfGGm/CXxL4T0y0sr03N 3a65a3Kxm5Cby8mST9oc4iUIAkiRhSy4HH1rXyZovgvQdH8SeMPhl441jV4NGsrtfEPhjX9WvZYL prgW3mXk8N18sbGF5DJjHDPIzBsMR0/7Lfx4h8ca14g8ES61/wAJD/Y/77SNakWXz7+w3bQZ98af vY90asxA3lsgHaXbvzbDVMa546nDZKUmk7Pm2lq3q72cejT7O3HleJjheXCVJbtqKbV1b7L0Xqn1 uvI+jKKKK+PPrAooooAKKKKACiiigAqvqF9b6XY3F5dzx21rBG0ss0zhEjUDJZmPAAAySasV4p+1 NHJqnhfwv4eNxJb6fr/iOx0298oLvaFmZsKWBwQyIQf9n0yDyYqs8PRlUSu1+ZjWqOnTckrmD4B8 BN8f9Yn8f+PLS4n0fzivhvQ7pfKhjtQyss7oGO9pMDIb5WAP3kMe36HVQigKMD2qDT7G30yxt7S0 gjtrWCNY4oYUCJGoGAqgcAADAAqzUYTCxw8b7ye76t/1sTRoqlHu3u+55Z8VvDep6b4t8OfEDRLK TUbjQ0ng1HTbMbLm/tJF+6p/5aGJh5ixNwxzghsZxrr9ozVLiNYdI+FvjO51GR0jhi1DT/skBJYA 75ssEABJyRjjkgcj2v60m0eg/Ks54WpzylRqcvNvonrtfUmVGV24Stc8bX9pe2gxJqHgLxxpdkvz T311opENvGPvSOQxIVRknAJwDwa9S8M+JtM8YaHaaxo95Hf6ddp5kM8fRh0IIPIIIIIOCCCCARWk Y1PBUflXiup6TqnwN8Zar4g8P6HqniTwrr7td6rp1gfOnsbvcMTQRlwXEpc71AyuwHcFULWbliMK 1KrLnh101Xnpuu/3kuVSjrN3j6ao9sorxvR/2iDbzQzeNPC2oeBdGv5jDpepakdyzMHK7Z1C5tmI ww3/ACkBzuwuT6R4e8ceHvFvn/2Jren6t9n2+d9iuo5vL3Z27tpOM7TjPoa6qWMoVvglr2ej+56m sK9Op8LNyvDvjb4wvvGHiK0+FHhS6t01LV4ZP7avWjab+zbPaN25QMBpFYgZIxlR8vmK40/iF8dH tdaXwp4C02Pxn4vkSYyW8FwogsAmVLTvnAIcAeWWU9iVJXdc+BnwlHgPRX1bWY47rxnq7ve6nfSQ xCVJJdryQKyD7gZRwCVLAsMAgDz69Z4yf1Wg9PtS6W7J93+BzVJvES9jT26v9L93+B23hHwbpXgv R4tP0yytraMYaVoLaKDzpNoUyMsaqu47RnCgccAAAVt9OlLSV7MIRppRirI7oxUVZC0UUVZQV85f tg+NvEVpo+meB9G0XfF4s32B1a4mkjh81lIjtUMTBllkbABkxEQcNuUyFPoTUkupNPuVspYre8aN hBNNEZUR8HaWQMpYA4yAy56ZHWvhD4Paf4w+NH7SUGnfFTU9TGseD4P7Qt7VVhhWOaK5gYAqibCj 7gSyjLqEw2AtfU5FhIzlUxtSS5aK5mne76RaS3tK19dPM+bzrESjGGEgnzVXa6287+qufZPwp0C7 8N/C3wnpOpW4t9QsdItba4hyrbJEhVWXKkg4IIyCRXmv7Jtlb6ZafE+ztII7W0t/G+pRQ28KBEjR REFVVHAAAAAHTFew+LrjVrPwprE2g20d5rcVnM9jbzHCSzhCY0Y7l4LYB+Ydeo615N+x/Dps3wpf WbTXv+Eg1PXL+bVNYm2LH5N9IE82LywBs24X/ezuGFZQPPjKU8JXqyfxSjp56v8Az3+XU6pQjTxV ClFfCn+iPcaTGeopaK8Y9oKKKKACiiigAooooAKKKKACuC+LXxUj+GWn6UsGn/21rmsXsdhp2lrc pA08jEAks33VGQC2CAXQHAbI7yuV1r4eWmvePfD3iq5vrwXOhpOlpZoYxb5lQpIzfJvJKlf4sDYM DrnkxSrSpctB2k7a9tdX9xrT5FK89jzKT4c/F/4iaDfJ4l8c6f4Yh1OEwS6Hpukx3UccLxBXQyuw YMSXBwzAHlWxgDidD+CVn4L8eaV4Q1O7vNH1PVLaU6b4w8MXslhPfJCkZe0mtxvRCB85k437EJJc vn6urx+Pwb4s8YfHiHxPrC/2R4b8Mb4tGtWjid77zoXjnlLJKSnzBCNw5XaNqturwcVltOEqc4qU 5tpXbb0676LTtbU7qWJk1KLajG3RW16euvc0fiN8RNT+GnhzQNFtYZPFvjvVo/slhGsHlJdTIi+b cSBTtjQZDlQR1xkKGZec0n9mGy8QR2t/8R9c1Xxpq5SRpbea9dLKCWRgzGBE2sgGAvUKQM7V4C+g +P8A4e/8JrqHha/gv/7KvtC1SO/W5jh3SSQgES24YMpVZAQG6ghRkGuwr0Hgvb1pfWFzQVuVdPO/ d37nOqzpwXs3Z9X1/wCGPN/E3wB8K67oei6fZJeeHJNDR49LvtFu3t57QOV8za2SGLhcMzhidzHO STWn8PfDvijw5Hf6Tr+q2+u6RbiOPSr6QN9vkj+bcLon5WZRsUOvLbSzcmu2orvjhqcZKUFa3bb7 hSxVadNUpyultfp10PnK6+EOrfs6WmueKPAviOT/AIRy1VtSvfCmpJ5kU6oGMgjn+9ERHwp2sSY0 3lh0928JeJLfxh4Y0rXLRJI7bUbWK7iSYAOqugYBgCRnB5wTUviKzvNQ0HUbbT73+zb6a3kSC88o S+RIVIV9h4bacHB4OMV5b+yfPbW/wfs9DRJINR0O7utO1G2kcSGG6WZmkXeFCsDvDDbkAMBuYgmu enBYesqUNItN/NW2+/Y9XEVZ5hhJYqu71Iyir21aaer72atd3etm9j2SvI/GXwDk1LxpqPjLwn4w 1fwX4ovkhSeS3K3FlcGNTGHmtnGJCIyVHzAKQGAzkn1yivao4iph5OVN2vo+qa7NPRryZ8xWoU8Q kqi2/D0Z5V+yf/yaz8HMcD/hDNG/9IYaKP2Tv+TWfg3/ANiZo3/pDDRXOdB6rXz5+3tx+y/4hOcf 8TTRP/TvZ19B149+1dpNrr3wjtdMv4vPsb3xZ4Xtp4txXfG+v6erLkEEZBPIOazqR54OK6m1Gp7G rGpa9mnb0Oi+Ac0lx8F/BbS28lqw0m2UJKVJIEagP8pIwwAYc5wwyAcgZn7R954n034Z3N94Yu/7 Plsp4ry+uogDPFaRN5kjRKWVXYbQSjkK6b16kV6iAFGB0rnNf8UeFWsdastY1TSja2kaxanBd3Ee yJJRhVmVjhQ4OAG+9nvXPUio0PZylbS19uh0RxkaeLWKlFW5r2eq3vbXc8I+NXiux8NeNPhj8UPD +lXHiO6v4JLKOOO3O27ilj3QKHYM0Mu6RiqrHvcGRSQBg9tN8WfDHxIjPhTxZ4S8QaBp+tf6HE/i bTja21zOeUgSTccSnaWTocp8p3bc+G/ArwrB8QvjdJNby6trPw+8PyzTaJLqX2nybZkkiMUMLGXC FRsIDZ3Ig3ICfl+1toxivBy11sbKpXk7U2/h0d7Kzd+zOVZg8Xdw1jB2g3vyp36ebdv8rHk37Leq XV/8FdBtdRnEmqaaZtOuoGULJbGGVkSKRQAVZYxHwRnBBPXJ9Zrw/wCIGi23wP8AGA+JWkQ+RpGo Tx2niazVisPlyOAt6qg/6xHIBAViwkbAUlmPtOn39tqllBeWk8d1azxrLFNC4dHVhkMpHBBByCK9 jBzcY/VqnxQ/FdH8/wAzF4ieIqzlVSU27u22vVLt+RYooor0igooooAKKKKAErxm/wD2UfBmoeE5 9Fla8kurq6a7u9cm8mbUrhmYsQ07xsVBOM7Aucc53Pu9norlrYWjibe2jc0hUnT+CTXocr4O+Fvh bwDb2kWh6LbWRtYXtoZyDJOsTSGVo/Nclyu9i20nGTXRahqFrpNlPeXtxFaWkCNJLPM4RI0AyWZj wAACSTU9fOHxPS7/AGiPiaPh/p015D4M0KT/AIqO9sLqFfMmaNmgQA5JCSRlSMH585UFFasa9aGD hGMI6vSKXf8AyXXyO6hF46vzYmpZauUnq/8Agtvbu2Z37Sfxd8Lal/wi8mg64fEep6JqUOtjSdHC 3ENxHDud2knUER7ESQ5BJAbLIQQy/SOga3ZeJNEsNV06b7RYXsCXEEu0rvjdQynBAIyCOCM14/8A GhtE+E/gaTSPCPh7R7TxH4rlj0izsoLO3RbhmO0tIh2hlVXIywZQ0iBhhjSfs3yap4T1Txh8NtR1 OTXI/Cb2n2XUZF2Ewzw71i2ckBCrAEseGAGAoFeXhatSnjpwqu7lbbZOzst97K/3dxUcAp4WriU/ ei72/uXUb/Jtet3poe403y1/uj8qdRX0dk9zzjk/D/gaDQPHvivxDD5hfXkszMXmDAPCjx4VAg2j btOS7ZLHhdo3dZRSVEKcaa5YKy/zG5OWrYtFFFaCCiiigAooooAKKKKACiiigAoopM0AFc38SPBd v8RfAmu+G7kxpHqVpJbrLLCJhE5U7JNhIyUbaw5HKjBHWuloq4TlTkpxdmtUROEakXCWzPL/AIL+ NLhrFPA3iUS2fjjQLSKO7juZjKdQhUBFvoZCAZY5COT95HJVwDgn1CvL/iV8NdauvFFp458DXdjY +NLW0OmvHqyu9le2jPvMUgX5kKv86umCSNrZB+XmIv2tdA8L3k2kfEnSr74e+IoY0lNncRtewzI5 ba0M0CsHACjJIUBiVGSrY9V4SeOftMJHmb3itWn1st2vNXt1Z5UcVHBr2WKdktm9mvXa/wB3ke70 V8yeEvHnxb/aLSXWPCOoab8PfBX2+SK2vrqxa61KaONMbtjgwurOcHaQVKsu5th3bsPxd8WfBPVH 0r4o2t1rHhlCzQ/ECzsgsTZEZCXFtDv8r55GjV+NxCYU/M9XPKa0ZOkpRdRbwT978rN/3U3LyFHN KUkqji1Tf2mtP80vNq3me/UV4BB+2V4Y1zU7618L+GPF3jKCz2eZeaHpBli+dcjIZldeQw+ZRkq2 MjmoG8XfHb4oQ2FvpPhKy+F1jcRrNPrGqXaX9wqFoyFjg2jbJtL5SVOeRmNgCZ/snExdq9qdt+Zp Wv5fE/RJvyLeaYeS/c3m/wC6m/x2+9n0LuGcZGar6lfx6Xp9zeTCRoreNpXWGJpXIUEkKiAsx44V QSTwATXgWjfsqav4fmm1uz+J/iCTxwEigttevv8AShFAF/ewNDIxEkbuzuAx+QiLHKMZMrxx4Q+O njj+zPAWrS6a3ha5uAur+K9ImFtNdWIwDG8TZMcrhWLCNWQmRFyED7rhgMPUqJQxEeVbt3jpa7tf fsle7fS2pnPHYinTbnQfM9rWfpe23n0t1OPg8I237an/AAkXj26SSz0/SI7vR9G0e2tY/tUkghWS KeaYyLvO6UsISyopAG/Bcv1P7LPx40jR/hvZeHfHfibSNH13S5ZrGKzvSbOa3gg8tFjn8wKokBbA x95V7skuPoXwN4N074feEdK8O6VH5dhp0CwR5VQz4HLvtABdjlmIAyzE965v4hfAfwP8TLPVE1jw 9Ym/1CMJJq0FvGl6rAAI6zbd2V2rjOQQMEFcg+jUzXD4mMsHWTVBNclrXglf773u+ra3OCGWV6Dj i6TTqtPmve0m7flayPQOGXjpS18ub/iz+zjpdhq2s6tpPif4faOi6dPpdqsdpLb2UccccN0jylS0 7FTmHewLOFTO8GPupv2wvhS3h/VtUtvE6XX9nxh2sxBJFcTs2QqQpKqmQkjBxwuQWKjmvMnlOIkl PDL2sHpeKbs+z00frv0bPRhmlHWOI/dyXSVl813RneMv2htW03xpqI0DSbHVvBvha7htfFN8tz5t 1AJFJaaKKIswjgwfMLKSxDqAPLdx7VoWv6b4m0uHUtIv7XU9Pmz5d1ZzLLE+CVOGUkHBBH1Brwj9 jPXrfxb4b+IGt2sckdpqfjC/vIkmADqkiQuoYAkZwwzgn61Q8O+KPD3wb+PnxE0+yki0fwJa6Nba nqyLA0dppt/lUSOFUUIDNCyMVUM0jKADlSo6sRgVKdTDU6bU6SW2t9k79nd6fJW2OPD42UIQxFWd 4VH10tva3lZfqfStLXlepftSfCvSdHtdTm8aadJbXO3ZHbFp5xuUsN8MYMicDncoweDgnFel6fqF rq1jb3tlcRXdncRrLDPA4dJEYZVlYcEEEEEdc14dXD1qKUqsHFPumttz3KeIo1m405ptdmGoaha6 TY3F7e3EVpZ28bSzXE7hI40UZZmY8AAAkk9MVR8N+LtD8YWb3ehaxY6zaRyGJ57C5SdFcAEqWQkA 4YHHuPWvEPiuIPjl8YtL+GSy6w/hvRUN/wCKI7KMR28rsEe0glmLK2D8zEJuzlccqXi1fHX7Lena hqVrq/w/1X/hWOuRwSWU91otoqxXNvICGVokZAHBIKyA5BAPJVCnoxweHhGCxFRwlJX2bSXS/XXf RPRp6308+WLrzlN0KfNGLtvq31t0083vc9wrxv8AacU2eg+ENclG3S9E8TWGoahP18mBXZC+3q3z OowoJ56daw4/Dfx58Bak6aVrui+OPDNjuNva60zQ6ldQ4jIiaVYwvmgI6rKzYYyMzg8BMb4qftT+ En+GviTw7rsd7oHjeawmsLjw7PbSO9vPIhT/AFwXynj+YOHDfMhBAydtedjsqrV8PNYZ+10v7t21 bXWNr/hbpe5nWx9L2UlXTpv+9tfyez+8+mIyGjUjkYp1cv8AC/R7vw/8OPC+mahF5F9Z6ZbW88W4 NsdYlVlyCQcEHkHFdRXHTk5QTasz2ovmimFFFFaFBSdetLRQBXvtPtdSs5rS8t4rm1mRo5YZkDI6 MMFWB4IIOCDXm+ufsy/DLxBdrc3PhO1hkVBGFsXktEwCTykTKpPJ5Iz054FeoUVzVcNRrq1WCl6q 5lOlTqK04p+pzPgf4a+GvhvYvaeHNIt9Mjk/1joC0suCxG+RiWfG5sbicA4GBXTUUVrTpwpRUIKy XRFxjGC5YqyCiiitCgooooA8x/aK+I1x8NvhneXWlzyw+Ir+RNO0dILI3ckt3JnYix5AzgMQTkAj 7rnCNR/Zt+Fd/wDDrwbd33iNY5PGfiC7k1TWZ18snzXYlYwyKBhQc7RlQ7ybTgivFf2uvjB4eh+I HgFbbVJNQXwtrQvNVsrMsQrpLAwAyRG8gUTL1O0lgSuTX2JG26NSPSvRp42Msv8AZ0I6Sm1KVlq4 paJ9lfX+96HlvDv6+6lV6xirLte+rXd208hfrXzj8O/EOnWf7XXjXQfDOredol1pR1HVdPh2/Z4d USaKKQphRhyhBcgkl2bcSVAX6OPIIr5kuP2afHl9rvi7RF8a2uj/AA98Q6tc6vdrp8B/tC689oi9 uxYYjQKjqGVjnJ3IwbavTlvsGqsK8+VSjbW/dO9kndq2i016pGOYqtzUpUYczTvp6eqsn1/I+mfM T++v51S0nxBpmvfa/wCzdQtdQ+yXDWtx9lmWTyZlxujfaTtcZGVPIzXkP/DF/wAHv+hTb/wZ3f8A 8drOvvgvqnwKa81v4L6TbzveW4t7/wANX9yzR3LLv8m4jmkfcrxs53IXCuhYDa4BK+r4GouSjWlz vbmiox+b53b7rd7blvEYyn79WkuXrytt/JcqPf6K+W9H+M3xi+K95rfh3wppPhbQtS0F59O1bV7u +eZDdKQgeCHbvjBYSMvmI6naQTlSDvfDP9qPS9PsdY0H4m6lH4e8W6BJNHcC/gMD3sEYUpOEXdH5 jhh+6id92CyZUjF1MnxVOLslKSteMXzNJ7PS+m33oinm+GnJJ3ins2rK66a9T6GpK8r+Gf7SHhX4 l6pa6VHDqfh/Wb2D7XZadrlobeW8t9oImhIJR0I3Yw2SEc4wM16rXlVqFXDy5K0XF+Z6dGvTxEee lK6CiiisDcKKTOOtU9N1rT9Z+1f2ffW979lna2uPs8qyeVKuN0b4PysMjKnkZqeZXtfUC7RRRVAF FFFABRRRQAUUUUAMlG6Nx6g182/s0eKtP+GsGoeA9f0y48I3I1S4/smTV7dbdtTiMiquZQfLmnUs inYcFTHt3AEj6Vrk/iX8OdC+J/hO60XXbYS2sg3pKpCyQSAHbJG2PlYZPsQSCCCQeOvSlKSq0/ij f53/AOGPWweJpwhPC10+SbV2t01ezS2e70f3o6sHcMjpS15N+zN4z1jxn8M7aXWLO8hezk+yW19f RvHLqNuqIYrkqxbl1YZIZwWViG5wPWK3pVFWgqi6nFisPLC1p0Jbxdjyv9k7/k1n4N/9iZo3/pDD RR+yd/yaz8G/+xM0b/0hhorU5j1WvI/2pL2DTfhbYXd1NHb21v4v8KzSzTOFREXxBp5ZmJ4AABJJ r1yvJP2orODUfhfp9pdwR3NrP4v8KxSwzIGSRG8QaeGVgeCCCQQfWk720E720OF0v4m/Gn4geAZP EfhnQtBmstV86Kwit52F5ZbZWTzJPNIik2hGHGMsyttwCtU/gp8LfAnie3TSfGPhi5j+IWlzyXt/ HrU0jTXrNJg3AYELcQFkx0ZQc53b98n0no+i6f4d02LT9LsrfTrGLPl21rEscaZJY4VQAMkk/Umv FviVfXfwy+O2i+O72wNx4UvdMTw/d30coX+z5Hud6zShhgRElV3ZGOc87Vf5irgXSdOviJOpayad mlfdrTTX8DjoZbVxFWEU+eVtna3d2v17Ld7I9vsdPttLs4LSzt4rW1gRYooYUCJGgGAqgcAAAAAV PSKwZQR0IzS9a+nSSVkdtraEGoWFvqljcWd3BHc2s8bRSwzIHR1YYKsDwQQcEGvC/gjHb/BPxJcf DLUbC4tptSvbq+0fUwpkh1CAIpw754nVFIZQiKAinqwL++V5h8b/AIP3HxOs7G+0nXLzQPEujxzn Tbq2mMabpQgcSFRvAKptypGNxOG+6fLx1Ka5cTQjecPxT3X3bGUqcHJVHuk/+GPT6SvI/wBnvxtr HiDTtd0fxTqV5eeLNIulW+t73T4rQ2weMbVQxEpKhZZCsnBYHOACpOJ4S1e/+Mnxyvdcsdd3+CvB 04hsIra3Y29/PLbSJM/m7gGaMvgEBhtZduA5ZpWYwlClKEbubtbS6tvf06/cdNKMa0ZTjL3V1/C3 3nvFFUtN1rT9Z+1fYL63vvss7W1x9nlWTyplxujfB+VhkZU8jNXa9ZNSV0ZhRRRTAKKKKAEPIIri vhH8M0+FvhVtMbUJNY1C4upr2+1OYMr3U0jcuwZ2wdoRTzztz1Jrtq5vx38RPD/w00mHU/El/wD2 dZTTi2SXyZJcyFWYLhFY9EbnGOK5qsaMZKvV05b6vpc0i5tckep5rqcd3r/7WejWt+/l2Og+HptT 06OFwd8k0ggkaTKAjIJG0MR+7Rsjcy16/Z6Dp2n6nf6lbWNvBqF/s+13UcSrJPsG1N7AZbaOBnoO leB/Gj4leHvFF78O7vwhrel6pr9t4rt4IlgvAk3lsZI5ULKC6wyEKrMFKspU4YEZ+ih0FebgJU5V ayi+b3r39V+mx01ueMY300tb0f8AnqLRRRXtnEFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFeG+Dt Wvrr9q/x7Y6ULmLQLXSbRtZjlkUxPqThPJljUsSM2yhCVCgmL5gSFJ9xr56+E+oW3j39qj4p68l/ LdL4etLTQLNAgRERizXCkFQzFZ4Xw2f4m6jbj18DT5qWJm1pGH5yil+f69LHlY2VqtCKerl+UW/6 +4+hqKKK8g9UKaY1bkqCfpTqKBWT3ECheAMChlDdRn60tFAW6DRGo6KB+FOoooCyWwUUUUDCvFfH f7WXg3wX4gv9FtbbV/FOo6aksmpx6DZ+etgke3e0rsyqAC2CQTtKkNtPFYnjf42/Ey4+InjXwj8P /A1jr0mhR2IN9dXyRiN5k80s8bOm8Mp2qFYFShYk7go8c0bwB4r+JOl/GXwreeDPEPhe+1a7PiDT zdSSvaveJJmW283dHBIJGI2EKRj5mZ/KjI+uwOT0or22YSShaLspxulJx1cbuVuV3tZbff8AK43N Kkn7LBJuV2ruLtdX0T23Vj6Y+LEfw/8AiT8FrjUvFN1GPCFxaR6hFqTAxyQblzFNFldyyfOAF2kt u2FW3FTy/wCzzo2lfGD4CeDdT8ZaJo+v3cKXMMJutMt9kKLcPGqxoECoAkca4UD7gryXRf2cfiT4 q1rQ4L3SNO8JfDjS9WtLqPwXqWpf2hsjiYvKyuqOH8wz3GQ7AncFb5UTH2gqhVAAxiscc6WAw6wt Crzty5k0/hVmraXXM7rms2vdVr7muDjUxtd4ivT5Uo8tmvid7316LpdX1YKoUYAwPavJ/E/7Knwt 8YeIL7WtU8LJLqN7IZriWG7uIFkc9W2RyKuT1JA5JJOSSa9aorwcPisRhZOeHqODfVNr8j3a2Go4 iKjWgpJd1c5LRfhJ4J8N6lDqGleEdD02/h3eXdWmnQxSplSpwyqCMgkcdia8z1D4b+NPg54nuNZ+ GcMeu+FLqNvtPga6vfs6W8pcnzLF2BSEFnd2Q4X7wGcoI/eaK0pYyrTk3P3091LVP9fmmmujMKmC pTilD3WtmtGv689D5Y+E/jTRvgT8MJvHvxLu9TtvHPi64mmvbfUIn+2XDQPIsUUcGB5aBMYJCqPN UFgpQDodFtvjj8WZp9cfXI/hDpTxxCx0VtPg1O4kBXc0krOFKHLAbSARggopG59X9oRf+EW8cfCz x9KBJp2h6tJp96sn7uKCG9jEJuZJTwixkL1GGLgblr28MNoPQV7WIx0FFYunTTnUvdtKSjZ2UIxa tpHl1d9GkrWPJw+Ek5PDTm1CnbRaOV1rJta6u+1td7niDfDL41WC/abf4yW2qTw/vI7G88NW8UFw w5Ecjo29UY8Fl+YAkjmsHxV8LvjJ8XtPi8M+NdT8IaV4UuLiOTUpPD0dw15LGh3iNPOUqMuqfNwR gH5hlG+jgwboc0tefHNK8ZqooxUls1CKt56JK/qd0ssozjyuUuV7rmbv97YirtUD0GKWiivHPXCi iigAooooAKKKKACiiigAooooASvPfjR8UH+G+h2MWnWkep+JdZul0/SdPklVBJM/Ad8sD5akrnHd kBK7tw9CqndaNp99qFlf3NjbT31lv+y3MkStJBvGH2MRldw4OOo61zYiFSpScKcuVvqaU3GMk5K6 PjD41fAi48H/ALI+nz3zW+l61pFzHe6lb2sET/bWknaOJZZQAxeJLggEMV5cYbKsv194B8M/8IZ4 H8P6B9p+2f2XYQWX2jZs8zy41TdtycZ25xk4z1r5/wD20vjP4OsPh7r3gK4u5L/xJeLARY2RwbfD rKjyuVKqBsUlPvsGXG0NvH0b4d/tL+wdO/tj7N/a32aP7Z9i3eR520b/AC93zbN2cZ5xjNfSyoVs HkeEw0otQUp8t1a6tDXu9b6nz9KpSxGa4itF3k4xvbo7y0/LQ0aKKK8M9wKKKKAPN/iD8A/CvxA1 Iaw8V1oPidP9X4h0Kc2l8mQqnMi8PlF2fOGwpYDGa8AvLjV/gn4g8T+H/iF4Z8SfFvwItxFqenap qFimorZwiGXzZHeTIDqdiFWKAKJJAFDbX+x6QqG6gGvYwuZVKMXSqrnha1m9Vrf3Xuvy1eh4+Jy2 nWkqlJ8kr3v0fqtmfKniT4keFv2hPEvh638ODxJ4Y8W2f2+fwh4kmtzbWN9NGhEiBiH3xNsUuGjB 2oVOCxRtHRfjl8YfAmmw2/jr4V6lrNybArbXfh/ZctcXSE8ziEusKOrR8gcMjlVYNtj9i8cfBHwR 8RtF0zSte8PW1zYaXxYwwlrf7Mu0LsQxFSqYCjaDt+VePlGPPtF/tX9nHxFNF4k8Q6v4m+HurSRJ Brms3P2iXRbr7u25cjPkSnaBJwiMAGVdxdvWhisJWo+xp0+a20ZXvu9ISi1ve7i1a9+XV2PLnhsV Qq+1nU5b7yja2y+KLT9E09t9iLw5+0Xr3hXVNStfjD4X/wCEFtpN9zpmpRE3No8YDsLaSVC6m42x uQBgvjARTtDwr+274FkbSLWLS/Ec+r6ljZpKacBcR79phBDOFbzVdWTy2fIIzgkA+v8Ajz4f+G/i f4ffR/EumxatpxdZhGzMrI69GV1IZTjIypGQSOhIPgOk3En7UXxl0fWrSPxBZ/DbwuiX1hcvCltb 32pxXRCyLuBaWMojDsyYIPllyG54U8FjKVSrKm6bSd2n7sXb3bJ8zbbvo30una6N51MZhKkKcaim m9E17zV9btWSsutuuxe1fQfiB+01MbbUoZPAvw/h1EpLp91DLDqd3GioysysuwgseOdqsSSJDGpP uXgf4c+G/hxp72fhzSLfS4pMeY0YLSS4LEb5GJZ8FmxuJwDgYFdH0pa+Gw+Ap0JutJ81R/af5Lsv Q+uqV5TioLSK6f1uFFFFemcwUUUUAFFFFABRRRQAV4N+1p4ivI/DOieE7e5/si18TXos73Wp2Edv Z2y4aQNIZEAZl6IT86rKvXFe81ieMvBmkfEDw7daFrtp9t0y62ebD5jxltrh1+ZSGGGUHg9q5sTT lWoypxerPRy7EU8Ji6deorqLv/wbbO29no7WHeE/Dek+DfD9jo2i2sVjp1rGEht4ugHUnJ5JJJJJ ySSSSSa2a+XviJ8K9V+Araf8QvCWsaxrVh4fLrP4c1O8lmhSxk2q0cBAyioAp+fcAI1ck+XhvpjT dQt9W0+2vbSeO5tbiNZYpoXDpIrAEMrDggg5BFRQqtt0pR5XG33eRrjsMoxjiadT2kZ3u9mpLdNa 62ad9nfyZ5n+yd/yaz8G/wDsTNG/9IYaKP2Tv+TWfg3/ANiZo3/pDDRXYeSeq15V+0t/yTrSP+xz 8J/+pDp1eq149+1dq1roPwjtdTv5fIsbLxZ4XuZ5dpbZGmv6ezNgAk4AJwBmk2krsD2GuQ+LHw9g +Knw/wBW8MT3clgl8qbbmNQxjdHV0OD1G5RkZGRkZHUdDoms2fiLR7LVNPm+0WN5ClxBLtK743UM pwQCMgjgjNXqiUYVoOL1i1+BrQrToVI1qTtKLTT81qjwrT/iBr3wHhs/D/j1NQ8UaYcJY+KtPtS5 aNULSi7j3FlaJUZ967i6KW+8r16j4E+Inh/4l6TNqXhu/wD7RsoZzbvJ5MkWJAqsVw6qejrzjHNd HgHqM0YA6DFctKjWpTtz3h2a1++/6G1evHESdRxtJ720X3W0+WnZC0h5GKWiu45DwhP2adQ0Pxh4 m8TeG/Hup6DfardG7ijjgSWBGYsZBNGx2zj532ZC7M5+Y815T8A9B+I3jbQdZnXx4PB9l4hmuNSj aO0tpptQkZzFdSoAyyQ7GEYyuAC6lcdT9i38D3VjcQxXElpJJGyrcQhS8ZIIDKGBXI6jcCOOQa+U v2e/2cfBfxA8E3Ot+LtOTUdfuNQuBdWsUklmdPdX2m3aKJ1VT8u/btXAkAxgCvjcXlkFi6UaCaVp NrmaT27X79P0O7K4YXDOaqz5IvooqbbvfROSS63+R0118bvhl+zv4O0XR/CU1n4jhe5xdR6bepLP sx+9uZGUFWk+4ArFM5wuFTA09P8A2j/FWvafc65pHwn1u+8MKmYLxp0S6nYxqUK2wVmZCzKN6FgF y3OCtd7Z/AL4dWNnDbR+C9EaOFFjVprGOVyAMAs7KWY+pJJPUmvPLWBf2dPil4e0WC6vbf4beI91 jY2LK9zHZaozptXzGUuiSAHau8je0jEAAkenHDY6MlCMrQ0SUVt961Xc9n2mVyo1OSLdTe83ZNdb crVpdr3T162PddFuru+0exub+y/s2+mgSSez80S+RIVBaPeOG2nI3Dg4zV2kpa92KaSTdz5gK5q6 8e2Fj4/svCVxDcQX17ZPe2t1Iqrbz7G2vCjFstKo+cqBwvJNdLXEfEr4Uab8SpNJubjUdV0bUtKe R7TUNHuvs88YkXbIobBGGAXPGeMA4JBwxDqxheirtW08uv4GlPlcrT2O3pCM9RmvOPgr8QLvxVp+ p6Frtzb3Pi/w5P8AY9Wks8GCU5YRyoynb8yqdy/KVdXBROBXpFOjWhiKaqR2f9WFOLpycWc1pPwz 8I+H9Qiv9M8L6Np99Dny7m1sIopEyCpwyqCMgkfQmuloorSFOFNWgrCcnLdhRRRWhIhOATXiS/tl fCq3Hlajrl3pF+ny3Gn3ul3Sz20g4aKQLGQHU5UgEjIPJr0rTfiJ4d1jxpq/hK11OOTxFpMcct3Y MrK6I6qysuQA4wy5Kk7dyg4JFbV/pdnqtlcWd7aw3VpcRtFNBNGHSRGGGVlIwQQSCD1zXfRVGlK2 Lpyd7NWfLv11jK6a22OGq6tVXws4q173V/yasO0/ULXVrG3vbK4iu7O4jWWG4gcOkiMMqysOCCCC COuasV4Z8Lm/4Vz8dvGHw9gzD4fvLGHxDoenwcwWMbOYrpBnlN8x3rGuUAJI2kkH3KssTRVCdk7p pNejV/vWz8zTDVvbwu1ZptP1X9aC0UUlcp1C0UlLQAUUUUAFFFFADXbapPTivAf2XZo/FHib4t+M jqH9ozaj4lk06OaIoYGtbVALcpsHPyS43ZO4Kp65Jf8AtheJtR/4QOz8C+Hra5vfFHjC4+xWlvaO yP5KFXnYsBt2bdqMGZRtkYk7VavZvCfhXSvBPh2x0TRLGPTtMs4xHDbxDhR1JJPJJJJLHJJJJJJJ r2lH6rgHN71tEv7sWm36OWi84vseNJ/Wccoralq/Vrb5L80a9FFFeKeyFFFFABRRRQAUUUUAFJS0 hIXqcUAfNfibSfEX7Pfxgn8T+GPD19r/AIF8TSST65p+k2a3l/HfEOwkXhZBGWwQGdkUvNwpZK6O 1/a08K2PhvV9Q8U2Gp+DdU0/dImhavbmK+vIS7LDJAjY8zftwccIwbcdoDn0zxp8SPC3w9sxdeJN dsdIiaOSSNbmZRJMEAL+Wn3pCMj5VBPIGORXzf8AGj4w+Afi7qmj6Tp/w71L4tabY+XdXeoaKs6N pyzAEKpjUMzFAS0bMi7kUE7lOz63CU/7ScHiKDcYqznHS6Xdy92/S7ae3Xf5TEzWX8/1esk29IvX V9ra26/ee6/DP44+F/ihZu1jcSaZqcN29jcaPqoWC9gnUO3ltHuPJWORhgnhH7owX0GvgP4wWupf Eb4raB47tPhb430m1tr61iuFh090ur2GEq8kpWLbJDKoZY0fewcAbXjMRB++k+6v0rgzTA0cIqVS lL41dxunyvtdPX7l2etzuyzG1cU6kKq+B6PVc3nZ7DqKKK8E90KKKKAOU+KXw/tPil4A1vwvev5M OowbFmwT5MgIaOTAZd211VtuQDtweCa8yufgN8R/EMltb+Ivjbq8+lRuZHh0TTIdLuHOxgoE8bE4 yQSpDA46ZwR7xRXfQx1fDwdODVt9Yxdm92rp2ei2tsjgrYKjiJ8807+Tav62evzPnj4PaRP8GfjR N8K9N1W+1Xws3h7+3IV1V1kmtp/tRiZI2VVCxsPmK4PzDIxls/Q9eG6un9h/tiaDfXp8m21zwpPp lg33vOuIbkTyJgfdxGQ2WwD0BJ4r3KtMc3OUKr3lFO/d6pv7195ll6VOM6S2jJpLstGgooorzD1A ooooAKKKKACiiigAooooAKKKKAEpHzsbHXFOrH8XwatdeFdYh0G5istbks5ksbmYApFOUIjdgVbg Ngn5T06HpVRXNJIib5YtnyN+yk0Gl/HTxfZePfDH9kfEPVZ5tVs5ryJBGo3yiZLXdl+d8h3I7q6I eQEJb7Rr87f2VV1zxx+1Bpd9qGq3Opz6BZTvcTalqZvnZREYGEUoyrKZpy6gHaFJ+Zjy36JV9nxb Q+r4+CbTk4RbS2TtayvfSyT+Z8rwzV9rg5NLRSlZvd+b+YUUUV8UfWhRRRQAUUUUAJWV4q8K6V42 8P3uh63ZR6jpd5H5c1vL0YdQQRyCCAQwwQQCCCAa1aKqMpQkpRdmiZRU4uMldM+Qbzwrpn7OPxL8 EeEPhc19f+MdYdn1S01S7xa32n/vDvnbaFSSPY/ltEm4BZNyvuCvs/Av4waD8A/h/B4A+Iy3XhHX 9Dha6kF5EJYruOe5dla3aEv5u3zFDAcgh+oRyvsvxu+Gul/EbwLqkN14bsfEerW1nM+mQ3XyN5+0 MiLKGRkDOiBtrrkDBOK8W+A/xS0XXtDsdD+L9ja2njPwpB9ti1LxPHF5scDTKkcrPIA1vKG8lcSY dwYpAW35H28cQswwEpVYubTjz6++373LJb3jZuLXLppq1ovjZ0ZYHGpU5KKafLp7qWl0+z0ve+uu h9Nx69psmijV11C1bSjB9q+3CZfJ8nbu8zfnbt287s4xzWTofxJ8K+JtXXS9H8Qafq98YHuTFYXC z7Y0ZFZmKEheZFwCQTk4zg4+afjt+xuy6VqWq/C9bqK+vb6K5uPDwu44rJlCupaJGUAOpcsAzgKr yBcZC1658DdV8O6pqWuWaeBNP8B+NtG8u31XTrWGBmjjmUSRFbiJQsiOqg46hlII4BPyWJwNVJYj CTjKl1vpNbbx7XdlJNpvtoj6ShjIuXscRFxn0/lfo+/W2j9T1+iiiuM9AKKKKAEoorI8W+LtJ8C+ H7rW9buvsWmWuzzZvLeTbucIvyoCxyzAcDvUSlGnFym7JDScnZbmxRSdeawvGXjrQfh7osmq+ItV ttJsUyBLcuF3sFLbEHV3IViFUFjg4BrWEZVJKMFdvsZznGnFym7JG7kDqcUda+Zpbr4k/tS6fHbw 2P8Awr34X6htaW7ll3arqdqTJxGoyIkkUR5DDo2Q0qEqfovQdDsvDOh6fpGnQ/Z9PsLeO1t4dzNs jRQqrliScADkkmu3FYX6qlGc059UtberWl/Jbdexx4fFPFNyhFqHRvS/ou3mV/F3hy38YeF9V0O6 eSO21G1ltJXhIDqroVJUkEZweMg15P8ACv4maf8ADzR5fA/jjUNP8O6p4dK2VrLezLbpqNkq7be6 Te235lUhlVm2shztztHt1eRftSeDNL8TfB3xDd3el/bb7TrOS4tbiFIvPtypV2ZXf7q/IN4ByVBA ycCvDxEZRXtqfxJfefTYCdKrJYTEfBJrVbxe1/u3X+RZ/ZPG39ln4OA9f+EM0b/0hhop37KZz+y7 8Hj/ANSdo/8A6RQ0V2nkvR2PU68e/au0m1174R22mX0Xn2V74s8L208W4rvjfX9PVlyCCMgkZBzX sNeLftfakui/BP8AtF7mOySz8TeGrlrqaFpkhCa7YMXaNSGcKBkqCCcYBFRO3K+bYqEXOSjHdnh+ mePPH3wH8eXPgjT3j1fwh4Xll1S4t7ZIp7g6XLKmTIRtYSJ5u/Hy4LljmILj3v4c+MviH8Qda0/x Cun6Npfw9vjI8Nvdef8A2r5IDLG548sb2CvgZGxxgt1PM/s6/Ckal8F9Qv8AxBc6hPrnjayYajfX F350zW7K6QbWO4DEThhnJy2DwAo4jT/i78Q/gn4utfh9f2Fj4n0/R44o4IrG1lj1G/sipCSwLnZI YhtVlAJ+RuSFkkX4/Dc+BlCVWUvZT2W/L2Xe1uh7s8Cv7TqYPARTio2125opKTjd6Xs2unXTY+oP E3jPR/B66YdXu/sv9pX0Wm2uI3fzLiTOxPlB252nk4A7mtrPGe1fMHgv4T+PPEniC3+LeoyC18Yt fNLZ6Bq0x+zxaa6FBbuUj3RSBJHYMA3OC6bmfH0+udoz1r6bDVqlbmlOPKunp3f+R52Mw0cLP2am pNbtO6vpdfJ9U2mLRSZpa7TgEPQ14r8FZJo/i98X4Zoo9LQahaumkxyFghaJv9J4UIDOArnBLZBD 9AT7TJII42Y9AM18pfDv4f2v7SuteOPHl2dY8MaZrFxHZWLWN0Yp57eOHy5lkyhR45CI8gbsNGy5 +UlvFx8qirUPZLmkm3bbTlfX1aM6uFxFSCxNKN4wavrbdO35H1aGU9CD+NL+teOaf+zzdeFL6O98 K+PvEmmPauv2PTtRujfaZDECB5JtyVLIEyi/vAy8ENkV7HXq05TlG81Z/edVaNOMrU5cy72sLRRR WpiIeleU6L8d/J8XReGPGHhjUvCGpzTtawX8w87SbuYkmKOC7wu95EG4KyKchk+8AD6vWR4s8K6T 428O3+ia3Yxajpl5GY5reUcMOoII5BBAIYEEEAgggGumjKkm41o3T6rdfo/R/ejlrxqtc1KVmunR njfwa1K41/4+/Fa60ab7H4OspobNrWG0dIbzUsf6RPuY4EqFWRwgAcPGxyQGb3uvnn9jG6stP8I+ LPC1vbRWM3h/xDd2ht5DH9tMW4FHujGxVpMh496/KRCAuQua+hq6sypU8PiZUaMbRjZLS19F72nW XxP1ObLqk62HVWo7yldvy12+WwUUUV5h6YlFFeWeLPhv4r0vVr/xJ4G8VXX9sTvn+xPEd3Lc6QyN jeFQfPEQfnUqeCNgARsCHz80YxV7u3p5g2lFyfQufGr4W3nxE0ewu9A1T/hH/GGi3H23SNVVAdkm 0q0Uh2k+VIDhgMg4UlXA2nMs/iR4x8C3kEfxK0jS7fR7iRYx4k0KZzZ2rudscc8cnzoCQczfcBeM HGSRgX37QHjXwbZz2HiT4T+IL/xDFG3kzeGovtunXhAIWTzR80Id1Y7GVnVSpOScVFqnx08Z6hGv hyT4Ha5e69c7obyxuZ4v7K8lkZiBe4Mb5XaCpUDLMuSRg+piMtx2IpwjTmly3t70LO+97v4fwTfR s8mnjsHSqSk07ytf3Zf5b/mbXx30O88OapoPxS0OHzL3wz5g1eGNgjXmksCbheq+Y8ePNjVnChgx wxwD6fp3irStU8MW3iGG9jXRri0W+S8mzEnkMgcSNvxtG05O7GO+K8I+HvwP+KA+Huh6RrnxLvNB tljjFxpOnWyNPbRh93kpeBt4IUBeMqv3RuQDO1oP7HPw90uAQ38eqa/DEgito9QvmVbVNzuyxiER 4DNIzEHPJJGCTnxa2MxdSmqPsPfhpdyVreqvdX29T1KOHowqOqqnuy1tZ3v87dN/Q9C/4XJ4C/6H Xw9/4NIP/i68x+JHih/iV8UvA/hHRvFsmk+HdRtbm+fUfD2qKJ710DqI0aNWKhCjHLEI/wA4Hzxg V6d/wprwF/0JXh7/AMFcH/xFeWfFP4Uf8Kz1rT/iX4IsbdE8P+bdX3h3f5NrJE0PlzTQqPljl8oD OBhtinBZdr+Hj/rvsb1EuVNXte9rq/4Hp0PY8+m9na/e2h7N4F8F6b8PPCeneHtIWRbCxQqhmfe7 EsWZmPqzMxOABzwAMCt6qWi6xaeINHsdUsJfPsr2BLmCXaV3xuoZWwQCMgjgjNXa+hpqEYJU/h6e hwSbbbluFFFFaEhSMcAmisLx74m/4QvwPr+v/Zvtf9l2E979n37PM8uNn27sHGduM4OM9KqEXOSj HdkTkoRcnsjxb4P6a/xN+Pfj74harHGV8P3cnhXRrYlXNuIT++lz5YILF8qQ2QJZUORtNfQ9eOfs p+FbvQfhPb6xqd59u1jxVcSeIr2VcbDJchWG0BV2/IEJGMBi2DjFex16WZz5sTKCekLRVtrR009d /O9zzsthy4dTa1l7z+eoUUUV5Z6gUUUUAFFFIzbVJ9BQAtIWC9Tivjfw1+2L8SvEkviNLb4bSXh0 2Se3aDT4ZpriyndX+yJPDkMwV4ZVlYBc7hgIVCyW1+D/AMd/ihN4e8V6l4zsvC+ojTYbHy7QXEUy W0ysbmSWIqFW55jyqhQWRSGjMSGvp5ZDUw0+XHVY0vV826utI3fb5O584s6hXjfCU5VPlb8XY7nx 1+1gkev6h4Y+Hvhy+8Z+KNNu5UvrVYXjjjgt9rXDhsZJJLQpxy4zhsxrL5x8Uvilrvxr+F9lr7WW r+FfC2jald6b4y0a01OK0vMbEC7HlVRIAJCphYKXdwm08Ov0Z8E/g3pXwR8Dw+H9NlkvJWkNxeXk 3BuJ2VQzhckIMKoCjoFGSTljyvxM/ZV8NfEzxFq2rXGteINHbWEgTUrTS71Y7a8MIxE8kbowJUBQ Ow2ggZJJ6sNjMqw+IUYQ92L0m7ty6P3bpLTWPWLS17cuIwuZV6DlKd3LeKskuq11b10fRq5h/DD9 nL4UeJrHw/4y0nQ7/wDsSe0ae10DWWkktUklADztBNuzIVVVzuMbBEZQcK9e36N4Q0Pw7e6heaXo 9hp13qEnm3k9rbJG9y+WO6RlALnLMcnP3j60eEfDdt4N8L6RoNm8stpplpFZwyTEGRkjQIpYgAE4 UZwB9K16+exeMrYmb5qkpR6Xbel7/wBeZ7uFwdLDwVoJS62XWwm0egpaKK889AKKKKACiiigBKWi vOPjT8YovhLpujpbab/b3iDWr+PTtM0hbpLdp5GYAsWbO1BkAtggM6A4DZG9GjUxFRUqau3/AF6G NatChB1KjskZXx68L6sk3hz4heHbKTWfEPg2SaaHRlGRfW86rHcIMfMJBGCyEbuVxscsBXZfDX4l 6D8WPCttr/h67FzZy/I8bDbLBIAN0ci/wsMjjoQQQSCCfIU+KPxo8BzaVqHjfwPZa9ol9GyzW3gu Ga4v7GUqGUSIzlWHDKdp2g87/uh6PwWhute/aI8SeK9H8GeIPBfhq+0ZV1GHWbQ2S3Wom4ysoi3E MfLDZZRwS5ODJlvdqYVvCtVpJ8i92SkmrX1i9e7bXXXqmmvBhiksSnST99+8mmnt8S+Vkz6Wooor 5s+kCiiigAooooAKKKKACiiigAooooAKq6nZxahpt1aztIkM8TRu0MrxOAQQSroQynnhlII6gg1Z ZgoJJwK+Z/jt8e/DXxF8A6l4J8BXzeK/FWvXDaPb2WneYuCpUzSM4ZP3QQnD7jG3Od0Ykx6GCwdX GVVGmna6u7aRXd9kt9WtjgxmKp4Wk3Nq9tF38kcT+xN4KNl8UPGWu+H7a5XwH9nNnp1/qcOZ7799 hZIpTCnyfupC6DGC0YYMVBH2fXDfB34S6P8ABvwXbaFpKZY7Zry4y/8ApNz5aI8u1mbZu2A7QcDt Xc12Z1j1mONnXi246JN7tJWTfm7anNlODeBwkaUt9W+13roFFFFeGewFFFFABRRRQAUUUUAJXmfj z9m34c/ErX5Nb8QeG47zVZI1je5juZoDIFGFLCN1DEDA3EE4AGcAAemUtdFDEVsLP2lCbjLum0/w MK1CliI8laKkvNXPDfgZ4nvPBPiDUfhH4l1O1ub3QILSPRNQljFnLqtq0LNiOEsd/k+WyF0JyF+b BDEr+0d4AvLPTtQ+J/hTV7rQfGugaVKqzxyA29zaqfMkjliZHV8L5hUYHzlST8qlaX7R3wN8U+Nt a0rxx4J8S3OneKPD9u32LTWYeTM27J2EnajspZW3BlkARW2qCa6jwD8ffhx8brU6NYarbXV3eW4S fRdSh8uWRXjYvFscbZcKr7ghdQBycEE/QyveGZYb3v8An5FLRPrzaW5Z79r3XQ8BWtPAYj3f5G3v 2t1vHbvszv8Awj4kt/GPhXR9dtEljtdTs4byJJgBIqSIHUMASAcMM4J+ta9fP7SeMf2ZtOuZZY/+ Ey+F1kZZI4bNG/tXR4CzGOMb3Kz28ShV3MwcByeEjxXtXhXxVpXjbw9Za5ol7HqOl3kfmQ3EWcMO hBB5BBBBU4IIIIBBFeJiMM6f72nrTb0f6Ps/L7tD18NiPafuqmk0tV+q7o1enWvGtZ+PWs3XxC1j wr4K8ESeMZNHRftt4mpxW0Mch6x7mUrkdMFg25ZBt+QmvMv2kv2hNPvp5fDEFzqun+GLa6ntNfvr OGJJ7wRGJXtbQyyLvIaULIAMhSGw0e4NZ+Fnw1+MVzo0Z0fUtJ+EPhm6eW+ttKg08X9/Fv2BI7gz D5jtQtuL7wX2lVAVI/LpYPE5kvaU6io0U7c7+07aqKtJu3V2fY6quLo4SXs3B1KjV+VdF3bureSu d63iH47/AGC41QeF/Cyo3meToZu5PtqZJWPdLu8ltvyu2GXcoIG1jgQxfAnXPiXq0mpfFjWI9St4 3X7J4d0K4mi01AqMvmPnDmQl2OQQRjG4qdqxXXwH+I/iKW2g8RfG3V7jS45DI8WiaZDpdw52sFAn jYnGWyVIYHHQHBHH/GDSvGX7NngmbxLoXxX1PULC3uICui+KI4r6W+maRVaNbhtrqnlgt5aDICOw IySOulw3h8VWhh/rftHJqyfNyt7a+4vxXKctTOK2HhKs8O4RW7vG9v8AwJ/nc92+LXxO0r4Q+BdR 8RanLEBBGVtbWSTYbufaTHCpAJyxHUA4ALHhSa+S/iJ8G/jF8VG0z4g+LVsru0tLSO6g8OaXG7XF mrKrELaXEZSSRWw0kTvmTYYww+THtmh/CPxp8SPGGleLPibq0Vvp+mXY1HSvBumNmG0lCoYnnnG0 yyIQ2RgruyVbYzIfeQABjtX0WGx0claeG5Z1HfmdrpJ6csfPe8l3snbfyq2Dlm6ft7xp/ZWzb7v9 Ez5c8FftIeO7Pw/d3N/4bsfGem6PGZtW1PT76LT7/T4E3LIt3YSnctyPJlYqpEbHhCQN1fSmga7Z eJtEsNX02b7RYX1vHdW8u0rvjdQythgCMgjggGvN/id4L1Hw1qV38RPBUX/FQ28GdU0dVYxa9bRg kRMqgkXCjPlSgE5OxgynAh+B/gnw0I4PG/g/WNYi8Pa1aGS38NtfK+m2LSMryCOBcrHIJFcMoYhS 0igAcDlxf1bEUvb0ocnpffs9bLyaSTXRNGuE+sYer7CpLm9e3dd/NPVM9epOvXmlorwj3zyr9k7/ AJNZ+Df/AGJmjf8ApDDRR+yd/wAms/Bv/sTNG/8ASGGigD1WvHv2rtJtdf8AhHbaXfxefY33ivwv a3EW4rvjk1+wR1yCCMqxGQc817BXlf7S3/JOtI/7HPwn/wCpDp1JpNWZUZOLUouzRufETwr4gv8A wXb+H/A99Z+Gd7x20t15bKbSzAIb7OqDAkAChRwAM4KnDD5/+Nfwnk8C6h4budD8YeNde+INxdFd At7y8W6RCpQ3DsWQBY9nDZODkbgUDEfXNeJftFXv/CE6z4P+Ic7W81j4bF9E9i8/lz3ctzCscSRZ BBwQWbuEVmAbGK+fzXDwVGVfrpr2V9Wl3S1PXy3GVsPXTpvV36LW62d+j2fk2bnwb/aE8LfGj7Zb 6O1xaahZgM9jfoqTNHwPMUKzBlycHByDjIG5c9N8SfiVonwt8L3Oua5deTbxfLHEmDLPIQdsca55 Y4PsACSQASPk/wCGPhXXPhH4+nhsvD0eg+Nr97m50vRptRiuotR007Wexd1ZmgkTyi0U7YV2R1bg Yq/baT8QNH8eaj8SviV8MF1s2aRXCTw6tEselQwo3mPFAZXEhx+8CkjDgkEE5HNh8zrVKCUo+/ez dnZeb0v8tPuPo5ZRgK+Lq1MNUtRik4xlOCnN6aRu0rXvrra2zeh7Z+z3beM9QTxN4n8aJqNhda3e LLY6TeXCvHZ2gQGJUQAeW3zsrZCsTGCyg5J9grO0HXrHxFodhqunziawvYEuIJNpXfG6hlOCARwR wRmnahrum6T9m+3aha2Zup1toPtEyp5szZ2xrk/MxwcKOTivoaMY0qaXNfzZ8hi6ssRXlNwUfJbK 2ljifjx4T8TeOvh/d6D4Yk0+Ke/Pk3T6hNNEogKtu2NFzu3bODlSu4MCDg6nw58OwfDD4YaNpd89 nYppOnoLyeMiOAOqZml3EDgtvYsQM5JPeuwzxxzXgvx8+Omj6L4C8b6Be21xYa+YW06DT70BGuo5 1ZRdQsu9WiC+Yckggx7GCMwzy4qpRwaliqjs7W1++xrTrVq9KOBj8Lle3Vt6fke6WV5b6jZwXdpP Hc2s6LLFNC4dJEYZVlYcEEEEEetTZrzvwP4u8N+C/hP4VbUfE2jCyt7KCwGopfR/ZZpo49jCOQkB uY39/lPHBrkPCPjbxZ8Xfi3balpUU2mfDPRJLqNbxWRl1q4UGHghsmEF2ZSAykx5J3YEeqxUeWGl 5Stov62QU8BVqKpN+7GF9Xpqui7t7W+/RM9ybO0keleZfs/+P9V8deFdWj8QPHL4i0XWr7SdRkt4 wluZI5SyiHuY1jeNQWAY7TnJ5PpxIHXgV4B8XtS/4Un8XND+JCWt0PC2rQHSfFM1rHvihwV+yXLx oQxcMzIZG34QbFAZlDfQYOksTzYdL3nrH1V9Pn07uyPm8XUeHca9/dWj9HbX5flc+gK5q4+IGk2f jy38I3by2mq3lp9ssmmj2w3gVmEkcT9GkjCqzJ1CurDI3Y6RW3KCOhrwL4e6JZa9+1h8VtW1GH7b qGhQaXbaXNOxf7HHNbM0qxAnC7jnkDPzP/fbM4XDwrRrTm9IRvp3uor8ZK/kXia86cqUYfblb5Wb f4I6fx58Ldft/Ftz44+H2q22meKbiCK1vNO1JCdM1KNCwDTCNfMEqhxtkBJAjCY2sayfht8YPEul eItD+H3xJ0K4tPGF7562usWYjbT9SihRmMwYMCjkJzHtyNyttQOFX22vBf2lryOPxp8HbaxEn/CS SeKIZIGtYmMwslBF4N6j5Y9rx71JAKjJBCnHRh5vGf7NUjfTSVveXKm9+3e99PRHLiILB/7TTbWu qvo7tfj28z3qkpFI2jmuW+J2vav4T8G3+uaOtnNJpaG9uba9DgT28YLSojqfkkKg7WIYZGCvOR4d SapQc5bI9qK5mkup1WKWszwzr0Hirw5petWqSR2uo2sV3EkwAdUkQMAwBIBwecE1p1UZKcVKOzBq zsxMA9qMDriloqhBRRRQAV4n+1bpetap4DsWsdL/ALX0OxvV1HW7Vb82rS2kKs7Rn+8pxkkHcpVC qseV9srk/ivdabZ/DXxO+sLeNpTadPHdf2fF5lx5bIVYoMEZwfvN8q9WIUE15+PpqthakG7KxvQk 4VYySvqaXgvUrDWPB+iX+lWv2LTLqxhmtbby1j8qJo1KJtU7VwpAwOBjitqvN/2c9Qv9U+CPhCbU bb7JcLZCBI/LZMwxsY4nw3PzRqjZ6HdkcEV6RWuEqe1w9OfdJ/gTVjyTlHswooorrMgrzL9pbw9r Pir4G+LdN0BpRqclqHRIS/mTIjq8kShAWYvGroFx827aeCa9NpCAwIPSt8PWeHrQrR3i0/udzCvS VelKk9pJr7zk/hPq2g638NfDV34YXy9BawhSzhMgkaGNUCiJzub50xsYbiQykE5FdbXhuvfB/wAV /DX+0NY+EuuG2i+e4PgrVFEumSscnZbnKta5Z5HwrBWcqDtQcej/AAt+IFp8Uvh/oniiyTyotQgD tDknypASskeSq7trqy7sAHbkcEV1YmgrPEUZc0G/mm7tKXm9dVdOz13OXDVmmsPVjyyS+TS6o6ui iivOPRCiiigArwj9qf4uat8NbTwxp+mazY+F4taunjuvEF1H9pksYowrHy7UKzSlgdu7aVXgMVLq 6+6+YvXcPzr4+/aw8cfCvxxp9wmn6N/wn/i+20meWDUdBlaSLTYdwHm3EsTYKISzhWDAHOdgkyfo Miw8a+PpqrByj1sk91o3f3dHrrp3T2PCznEOjg5uE1GXr9+2u3Y97+CfwWsvg3ot9BDq+pa7qGqT i8v77UJy3mzlQHdUzhdxySTlzkBnbauPR64f4HeLr3x18JPCuuajHcx6hd2MZuGu4RC8sgG1pQq8 BHKl1IwCrKcDOK7mvLxkq0sRP6w7zu0/VaHo4ONKOHh7FWja6+YUUUVxnYFFFFABRRRQAUUUUAFF FFABXguvWiXH7ZXhmTVjKLS38LzyaMJpWSE3vnFZhEMhXk8hvmUZO3aSPlUj3muA+L3wrk+JNnpF xpmtS+GPEui3YvNN1q3gWV4SQVkjZTjdG6nDJkBsLu3AbT6GBqxp1Wpy5VJON+11bprbv5XPPxtK VSmnBXcWnbvZ/wBW8zvyM0cL7V43oPxh8R+D9a0/QPinoltpFzqE8dnpuvaK0lxp+oXDsAsO0gyQ Ph1A8zhtkpBAUZ9krnrUJ0GlLZ7Nap+j/q2z1N6NeFdNx3W6e6FooornOkKKKKACiiigAooooAKK KKAErz+8/aA+HVhr17ot14x0m11KzkkiniuLlY1jdAm5S7YXIMijGeSrgcxuFX41fGTRvgv4OutY 1KSK4vfLJstL+0JHNePuVcIGOSFLqWIB2rk4PQ+MfBf9l99e8Vav4/8Aipotu/iC/uJHGgvbW/2G JmJzKBHJIsuVIA8zDBt7MHYrJXvYLBYd4eeKxsnGG0bWvKWmiT6Lq+mi3Z4mMxlf28cNg0pS+1fa K/zfRHn974w+IX7RngHVdX1zxvoHgr4e6Pd3Npqd/pEd0j3YES4/dud0sb+aqiMshbzOUZgor079 jH4XQ6Rpus+Pv7FtdCh8SbBpelKssktjZozAZmlO9vNO1zj5WCow4IVNH9pjSYtTuPhb8PIbWHTf Cura1FHeuJ2tbTyIFBSyOwAZlBPlrkfPEuB3X6GRQqgDgYr1cdmklgFh6EeSFVt8qt8KfW28nJbv ZJJWTd/LwWXp411a0ueVO2r/AJmunZJPpu3rsh1FFFfGH14UUUUAFFFFABRRRQAUUUUAFFFFABXz hrWpW+uftqeH4bW01LWk0PSpLa7KRypZ6LcyxySpMWB2s8sX7sggDlCGZl2r9HH7pAr5s/Z58L3F h8eviwfEWoX2v+JNIkgtrbVLu9MgFjclriOJYwiqhG1S20bQeEVQCX9zLVGNPEVnvGD0/wATUb+i v369VdHi5heVShSS3lv6K9vnY+k2UOpB5Br5suNL8U/spzyxeFdI1fx74D1KS4e20O1iaW40W42h 40RwWZ4ZH3g5T5MBss5PmfSlJjPUVw4bFPD3jKKlCW8Xs+z7pro16bNp9uJwqxFpRfLJbNdO/wAm eF/s/fs+Q+EYYvGXjC0S++JmoSXF1e3skokW3aZyxSNVAjU4PJUHl5ArFCBXulLRWWIxE8TUdSf3 dF5JdEuiNaFCGHgoQ+/q/N+YV4P8eLOK++NfwSi1VpF8PDUrySXfK0dv9tSFWswxBAMnmK2xTy3z AAgsD7xXmP7Q/gHVPHnw7ceHY428V6TeW+raNJLJtEdzC4YEZ+UkoZFAcbcsM46jpy6oqeJjzO17 xu+nMnG/yvf5HNmFN1MPLlV7Wdu9mnb52sem8Y9qWvPfhr8XrbxzeXei6jpN94V8V2EYe60XVFAd kzsM0DjieDzAyCReuASBuXPoVcVWlOjNwmrM66VWFaCnB6CEbgQelYfg/wAE6L4C02XTtBs/7PsJ LiS5FqsrtFE7ncwjViRGmcnYgCgkkAZNbtJUKUlFxT0ZpyxclJrVC0UUVJR5V+yd/wAms/Bv/sTN G/8ASGGij9k7/k1n4N/9iZo3/pDDRQB6rXlX7S3/ACTvSP8Asc/Cf/qQ6dXqleS/tRXlvp/wv066 up47a1g8X+FZZZpnCJGi+INPLMzHgAAEknpigD1uua8beA7Dx3/YX2+a4h/sfVINWg+zso3Sxbtq vlTlTuOQMH3FdJS1nOEakeWauhpuLujmbnwDYXHj6y8YJNcW2rW9k+nSCNlMdzbs28I6spxtf5gU KnPBJHFYPx1+K3/CnfAsmvDRp9bJmS38mJtiJuz88j4OxeMZwcsyD+LI9Er5Y/aW8cJ4j+IXh7wx YeF9V8YWvhzUIb/XbK1sWuIAHQ+WhVRln2MzLlhGc4YPyE8/GSjhaEnT91y/N+X4nu5NhfruMhGp HmhHWSvb3V0vdWvstd2jy/XPB/jj4ceGPCsfiaPXNL0C3kurfQdK8M6jH9vjv5pJGiWeRVwxdHlU NGGwONqlmVuq+Fv7JXjm80eLXtR8bJoWo315ba0ts+nNdzpPGrPFJM0rIwlVppQyEMM9S3b6r8E+ ONA+ImhJqnh/UItTsN7RGRVZSrr1VlYBlPQ4IHBB6EGuhrHDYChyN354ySSv022fTbpbTTZnbjOI 6+NppQio+9zO20tW0mne6u23e93ZvVHz/fX3xX+A/h+e7vLiz+KHh6xtTJLPM/8AZ9/bqi5LMx3r KiqmSTmRmk7gc+NfHD4iW3xB0nwt4y1b4ea3p15pT293Mz2sc+l31nI8cixSXeOhUjGVIVpHQqSS R9PeOl8PfF5tc+HQ8T3ml6jarG+pWunMsM7wuoIXdJGwZCHTds9VViAxU5nxz8OvoP7OviLSPDTR afFY6V5MaykuBaxqBJHlgxJMKuoJ5yRyOo5cRh1VpzjGd6cVto9V666W6s68BjsNKtRlXox9q5rX WKs7a2Xu9fsxT63PG7xf2bfCdjLq2jadp+v6vb3JsbfTZr6Vo5p2G3LCdzH5IzkzMCgxkEsAK+kf hPpd/o/w+0i21TStK0TUAjPNp+ix7LWAs7MFUAkZwRuwSC24gkc1wvh34F/Db4g/C/wl53hxLmxT TreS0mmHkXflshceZJCVJJMjMwB2l2Jxnmj9nfUbjRZvG3gnULmRX8Nau8djZzOZDbabKoe0USHO 4bd2AWLKAAcYArXC05UK0ZSUVGS05dFfd3/4f5GeZVYY6hJ06lSc6b97nfN7t7Kzv3et1u9z1LxV 4V0rxt4fvdD1yyj1HS72Py57eXowzkEEcgggEMMEEAgggGvDPFnwb8deHfD974c8PTaT44+H0yFR 4U8S+ZHcWsCncLe2u1OSSSQjy/6rZFgnaTXb+AfjZbeOvif4m8Naf9n1bTLCGG6ttY0xjLbhWVQ0 Mr/d83fvZdhIK5HDI2fUq+oweYSpq9J3jfZ7XXVdn5pp+Z8RmGV+9yV4uMml62avr5WezPnr4CfH ew0jwb/wi3xK8QR6H458PyNZ6gniC4jt3mXcxhdHZsSjy9g3gknG45DKzHwH1S28Y/H74x+KNGv5 bzw9O+nWcNxDGPst1LFBtkKuVyxjK4G1tpEuSGBQj2bxP4D8NeNPs51/QNM1s227yf7Qs45/L3Y3 bd6nGdq5x1wPSvm7VfDkH7JPxsn8ZwQeT8M/EwFldWti5VdMueHEhgyfMT5JWGwfIskiqowqyfRU 8RhMRDFOP7upUjotOW/NGTS2te3ur/t3V2PnalHFYeWHU/fhB7682zSb+/X7z6wrh/it8GfC3xl0 WPT/ABLYfaGt95tbuFzHPbMy7SyMPwO1sqSq5U4FZfgT9pL4c/ErxBHofh7xJHe6rIjSR28ltNAZ AoywUyIoYgZO0ZOATjAJHpdeC44rL6ybUqc1qt0z3ObD46k0mpxe/VHzZZ/Cn43/AAx1i31fRfiB H8QbRY1F9outK1t9oSKPbHHC5MgSRhnL7ky4VpN+TXM/FX4hfGHUPDWleCvE3g+x0SbxRJDpn9ua ffsYPPmmhIjIXe0YWMyxurFvM+dkYqpDfXVcF8cvAP8Awsj4Y63o8YuHvDC09pHb3Hk+ZcIC0aPk 7WUsACG478EBhnmeYVMXhZqpShKVt0uVtLp7tlqtL2/JE4LAwwtaMoVJKPZu69dbvR67nYaLo9p4 f0ex0uwi8ixsoEt4ItxbZGihVXJJJwAOSc1drjvg/wCLD45+GPhrW3uvttzc2UYuZ/L8vdcKNk3y 4AH7xXHAxxxxiuxrz6E4VKUZw2aVj0Jpxk1LcKKKK3ICiiigArxn9ofxbfXlrY/Dbw4I5vFHixJI AzyxqlragZmkkBBOGQSKMDJw5U7lAPsp6GvDfgD4d03VvFvxG8TX1nHfa/D4rvrKHULr97NDDGqq iRs2dgCuy/LjK4B4AA8jMHOpyYWDtz7vy6282dVDli3Ulry/n0PYPDOgweFfDelaLavJJbafaxWk TzEF2WNAoLEAAnA5wBWnSZpa9SMVCKjHZHM3d3YUUUVYgopNw9aNw9RQK4jcqR7V4P8AsowyeH7X 4heFrm5k8zRvFF2kFncBY3htHCNC6xKqrHHJ87rsVUOWKjFe814t8Tf2aYPHXiDV9X0rxVq/haXX 44LXXrezcPDqFtHxt2t/q5CoVN4JAXcCh3vu9TBzpOFShXlyxlbW17NP79m/nY8zGU6qnCvRjzON 9L20a/zse0gg9OlFfJNn8bL39nvwz4t8EXUF1eeLLXV5YfB2g3UM83nadI6LahJVVvMRdz4Uvv8A 3fl5UgAdtYfGX4reEp577x18Mbq40W75sovCe2/vLRt7gRXCCT58oobzUwoyoIy+1OiplGIjH2it yv4btJy21Sbu9+l1fS9zGGbUZPlkndb2Taj6tbH0DXnvx78WWvhH4R+KrmTWItHvJNNuobGZrkQS NcmCQxrE2QfMyMqF5446V574o/bM8GXWkzWngWS/8X+K7iORLDTbHSrhyZRG7K7qwQmMFRu2Etjk DgkTfDP9lvQpba18UfEayPizx9ff6ZqE+qsJIopHQAwCFWMLJGPlHBGRldoCqtU8D9TtWzBOFto2 96XydrR7vXyT1tNXGPF3o4K0rrWV9F917vy/E4D4X/snL4n+G/ha+g8Y+IPC+j61pqXGsaDpWoM9 vdmW3RQ6lgAhcANIrLIPmKKQqg1Q+IHwxOpfEK5+CHw8sdJ8LeHLnRodQ1i6u7SZribbeo4dZmy0 5jyAgLbP3kqFgVGz6817W7Hwvod/q2ozfZtOsLeS5uJdpbZGilmbCgk4APABNfHvjT4/S/FL4o/C uGDwnqXg6zOvWt1pniPVlkhlvLdlVZoI1SNvkl8xFO2RkYFN+FOV9zL8bmOPrTrR1jBOSvayau07 P42um769DxsdhMDgqUKT+KVk97tbNf3U/kj7J03T7bSdPtrGzt4rW0t41hhggQIkaKAFVVHAAAAA HTFWaRfuilr4Ztt3Z9nFJJJBRRRSKCiiigAooooAKKKKACiiigAooooA8++N3w2uPiZ4NW20y6i0 7xFpt3Dqmj30ylkt7uFtyMy9CCCynIYDfnaxAFT/AAp+Jn/CwtMvYdQ0/wD4R/xRpc7W2q6DJN5s tm2T5ZLbV3pIgDq6jawJwTg13LMFBJOBXzlpni6z+MP7SnhzV/BcN0+k+GYNQs9Z8QJAyWeoqyRC O2jmXIm2SP5m1sLwXXPBPr4aLxNCdKS92CclLs7bf9vWsl31XW/kYiSw1eNSD1nZNd9d/lf7vkfR 1FFFeQeuFFFFABRRRQAUUUUAFFFNk+42OuKBM+XtR0mPx3+3NEbq00iaHw1o8TCG6naaZ1+d1uI0 QbI5ElmRdkxztIkUElSv1F0r5z/ZA8I6bZ2/jLXL6L7b4+GvX2m67qrquySZJd7C3wBtibcrH5VJ bORhUA+ja9zN6kfbRoQd404qPk7bteTd3/lseNlUH7KVaS1qNy/yT9EfL3w98L6V8Uv2sPiR4i12 yvpbjwpLZW2k2ep8JA2xwZljOeC0RkjPT97vxuIK/UFeY/Gb4a6hr1m/ifwddS6L8QtLtJU0++tV jJukIJNpMsnyPGzYxv8AuPhx/EGm+Dnxc074gaLa2F1Lc6d4us4FXUtD1hVh1GJ1VN0jxhUyjb0Y OqKp3jhTlQ8bOWOpwxEH7sIxjy/y2SV/STu7920+jawajg6kqFT4pNyv/Nd7eq29D0miiivCPbCi iigAooooAKKKKACiiigAooooAK8E0u+t4/20tYs9PuI1WbwhHLqUFs4w9yl0ojaZR1kWJ1ALchHG ODXvTZ2nFeA/szWEum+Ovi9Br032nxqNdV76YF9r2TR7rIoC7qqbTLtQMWVcK3Ra9bBpKjiKj6Rt b1kld+S/Ox5WMvKtQprrK9/RPT1f5XPf6KKK8k9UKKKKACiiigDjPiV8Nbb4gWdpNDdyaJ4j0uQ3 Gk65aqDNZTEYPB4eNh8rxt8rrwecEcCvxK8WfBBvs/xN/wCJ/wCFVPHjywtgnls/3IrmzjDMnzBk EqZU7oQRuZiPcaRlDDBGRXdSxXLH2VWPND8V6S3Xpqr6tM4auF5pe1pS5Zfg/Vdfz8yjoev6b4m0 uHUtI1C11TT5s+XdWcyyxPglThlJBwQR9Qav1zfhH4deHfAM2pP4e0uPSI9QkSWe1tWZLfeqhAyQ g+XGSAMlFG7ALZIFdJXLU5OZ+zvbzOqnz8q9pv5BRRRWZoeVfsnf8ms/Bv8A7EzRv/SGGij9k7/k 1n4N/wDYmaN/6Qw0UAeq14b+2loc/ib4A3ej2rxx3OoeIfDlpE8xIRXk1yxRSxAJxlhnANe5V4N+ 3A1yv7OeqtZXH2S8GtaAYLjzxB5Un9s2WxvMJATDYO4kAYzkYrKpbklc3oR9pVhC9rtFnVP2i7DQ ry18H+G9FvPGXjC2RLe507TbiSeG0dTGjCa8kXJALkGQqfmU+ZsJNei/C+fxRdeCbGbxnbx2niOS Sd7mCIoUjBmcxquwkYEewDknjkk5r5x+AOg/Ey6+Fujp4PvvB3h/w/eEO+pw29xJfqwkCzOyyqUe T5GU5+XgBSqhSPrheVHOa8nAyq15e2m2lbRacuv4t+e3ZHsZvh6GDrPDUV8Ls23dtr8F6atdWxaw 9L8FaNoviTW9fs7PytV1ryft05kdvN8pSkfyk7VwpI+UDPfNblFey4qVm1seHGpOCai7J6PzV76/ NJ/I+WPiprfi3wp+0h9s8Gx2+ni+0uOzmGqWssNhqt6PMaODzdoR59hUI29fu7Nw5U/Qfw58bWvx G8D6P4js18uK/hDtFknypASskeSBna6su7ABxkcGk8UfDnw94z1fRNU1jT/td9os/wBosJfOkTyZ NyNuwrANzGnDAjj3NdIBjpXl4bC1aGIqTcvclsvu+7r6nZXrUalOnGnDlcVZ+e+vnc4/x58I/B3x I8qTxLodvfyw4CXOWimCjdhfMQq235mO3OMnOM18c+PLjwTcfFjw74bj+JWua34bu5Yl8Q3+rai1 3aTRI4kgtxJGU43FwXyVjMu4EFXA+1fiF4Lg+Ing/UfDt1e3mn218gjln0+QRzbNwLKCQRhgCpBB yrEd6z4fhH4YsfAeo+EdM02LSNJvrWS1lFmoWQh4/LLliDufaB8zZJwM5qMTg/aVVUpQimtW2r38 rfqz0MvxWFw8XLE88nslF8vL/evq7p6pK2q1Z1Gm2Vrpun21pYwxW1nBGscMMKhUjQDCqoHAAAAA HSvK/HX7M3hrx94svtbvNQ1m0TUjbnU9Ns70x2t/5JGzzUwScAAfKRjGRhsk9X8H/h3/AMKp+Hml +Fxf/wBp/YTKftXleVv3yvJ93c2Mb8de1dnXf7KOIpRVaHy3s/60OGOJqYKvOWEqvqubZtXun+Cf kzJ8L+FdK8F6FZ6NotlHYadaJ5cMEY4UdSSTySSSSTkkkkkk1rUUgrojFRSSWhwynKpJzm7ti0lL RVEHmHxd+D+ofEDWvC+vaB4nk8JeIfDz3Btb1bKO7QpPGEkBjcgE4UYOeAW4JIIyvh78ZZtO8bP8 MfHM/wDxWtuf9C1CG0eO31q38tpBcKNu2NwqMHXOzerBGP3V9krm/Hnw68O/E7QW0bxNpcWqae0i yiN2ZGR16MrqQynqMqRkEjoSD6lLFwqU1h8UrwS0aS5o6333au37raWujT1PMqYWUJuthnaT3TvZ 9Pk/NL7zbsdStNUsbe9s7mG7s7iNZYbiFw8ciMMqysOCCCCCOuai1rSbPxBo99pl/F59jewPbzxb iu+N1KsuQQRkE8g5rwfWP2TxdX1h4dsPEt9Y/CYSfbLvwn5zuWuFKlY0mJLiB2zIyFuHBK8uGjwH 8ZfFL9nDwPdWuuaLp2s+DvDliNPtNdjlUTzuxZbSYwhlxEmbeGSP7+SXV5ADV1Mvo1qT+rVVOX8r Vm09lrvLvFX3Vm9bZRx1anNLEUuVfzXur/ovN287Hc/su69dv4f8Q+Erqw+zL4V1SbTYLiGMeTLG Hb5fMCoJJVIbe2xCQ6MRuY17ZXkn7L/hSfwz8JrCWZrIJrDnV4LewiKpbxTqrJGXYl5CFx8zksMh ckICfW6+Wy2nUpYWEKqtJLr08vkfQYiUZ1ZShsFFFFekc4UUUUAIehr58+EttdfCX43eLPCmt3mo XkXiqf8AtTRr6eICG6kAeS5BCfKkoDAHCqCIgcKDGp+hK+evifDq3hf9oXQfF93pHinxLoFnpkgs bfQ7ZLlLa6bMcilBgqpjYNuY7mbABKptXw8zXs3SxCWsZL7no7/L8Ttw3vc9N7NfitV/XY+haTcO 5r538W/tf6dJcR+G/BWgarrvju+QRWum3Fr5CW1ySQ8dxuYMpiwzPj5flPzgbmVfDn7O/jDxNpcO r+N/ip4zt/EN5HHLcWmiX6WNvany0Bi8uMMhKsGBdNobrjOSfrMPhYVcOsTUqKMZfDu3LzSXTzdt dFfW3g1sVKFZ0KVNykt+iXk338jrPij+0RpXgfXoPCehWMvi/wAeXUkUcHh+ycoVD5YvLMVKxgIC xzyAVYgIS45q38TftFaTDp+o3/hHwlr8EuPtGj6XeSW15FuQnmWVzENrbQdu/PQcfMOL+InwFk+C /wAHNe8ZWeran4n+Jthc2+op4ol8xrlFSRY2AUs/7pbdpA6uWVhkt8qqE+q9M1C21bTra9s7iK7t LiJZYriBw6SIwBVlYcEEEEEdc169d4PCUYSw0FUi203K920leyTVo6+79re/Y8uisViq0o4ibg0k 0o20Tb30d3pr0Pkvwb4b+KPxk8ZeOdSg8YeM/h9ZSP5dtHrelmNJLaZcCKGAuFikh8sgzIxdt6t8 jFt3pf8Awy03/RV/iVn/ALGD/wC117lgDoMUtcdfNq1RpU0oRSSSSXbq7XffXbpoddHK6ME/aNyk +rb/ACvZHzxcR/G/4K6bbGCay+L+hWsZM6yRmy1YKsbAKpDOsgGxDkh5XZyMHhhrx/tgeA9NBi8U xa74I1A/Mmn69o88c8kfQSqI1cbCQyg5zlG49fb6Ty1PVVP4Vn9coVtcTRu+8HyN/Kzj90UaLCVq OmHq2XaS5kvxT/E474d/Fzwd8WrS8uvC2sQ6olnII5x5TxSRkjKkpIqtg84bGDtYA5BxRg+Pnw+u vHFz4PXxRYjxBbyCF7WQlFMpZV8pZCAjybmC7FYtkEYypxl/EP8AZp8E/E7xNDrOtWl1uODeWlpc tBBqDIjJC86rgs8YdwrKVbDbSSuBUvh/9nPwXo/gW88LX1lL4ls767mv7u61uT7RczXMilWmL4Gy TadodNpHXO4km3HLLOSc9emmnz+110tHpruQnmF+Xljp111+XT72emqsZ5UKfcClLqOMjPpmvlHw 34T+NnwZvtR0HwZ4as9S8H2WtXGpWkdxqit9qspSipZQ+Y26EpukkLNwXUnLciW+37M3i3xx4e1b xf4l8Qy2Hxdv0V9NubO5lit9DQE4tY/Kfoys6O3zY3kgOdzSbvLaEHzVMTFQezVm9e8U/dstXq7b K70MY5hWkuWnh3zLe+i07NrXy/RHV/tqTRn9n/XIH1ax0xZ5YAFvFZmuisgkEMW05EhKAg4YYVs7 Rl0679nPVrLXfgX4GubKQTxR6VBas+wriSFBFIvIHR0YZ6HGRkYNcF8If2V7nwvfeHdU8c+JpPGV 1oFokOj6dJGRaaY+dzsm4kylTtCMwXaEXj5Y9n0IFCjAGBRjK+Ho4VYChP2nLJy5lotVayTV+i1b 7pJ7jwlGvVxLxtaPJeKXLu9Nb32+X/DC0UUV88e8FFFFABRRRQAUUUUAFFFFABRRTWYL1IH1oAWv K/iR+0r4J+GmsNod3d3Wq+Jv3Qj0PSbZri5kaRgEQYwgcghtrMGIIIB3LnlPHnx2PxD1K4+H/wAM Uutb1O98q1vfFGmjzLHR4Zg2+bzkdd0qorMoDAFuAxZSh9G+FPwY8K/BvRZLDw3p/kNPsN1dTOZJ 7l1XaGdj+J2rhQWbCjJr2Y4ajhY8+NT5ntFaad23ey7K133W55EsRVxUuTBtWW8nr8kur+enmePe PvHPjD9ojTk8B+GfB3iXwZY6of8Aib694ksXtFt7VWUskQV/3jv90rnlSQRtZnT6E8K+FdK8EeHr HRNEsYtP0yzj8uG3hHCjqSSeSSSSWJJJJJJJJrW2gdBilrmr4v2tONCnHlgtbd2+r+Wi7fN36KGF 9nUdapLmm9L9l2QUUUV553hRRRQAUUUUAFFFFADXOFYjqBXwVpf7YHxbtLLUtT1Cx0a6TS57izut HaJoryOSQnZLJEGLpFBJ5cWWChvNCEtId6fe9fMvxt8H+FvCH7Qnw28YTWlvJN4gv59H1S1aUyy3 vn2otYW8lzs8pA22QjHEi5DE19NklXDR9tSr0VOTi3G+usU3bRq3Ntfo7adV85nFOu1Tq0qrgk0p W7NpX+XY779mLwLqng34aLd+IJJX8SeIryXXdTWZPLMc8+07dmxdhCqm5ccPvA4xXrlfOvw78T/E L4Q6HceHNY8Dar4m8P6DdSWkOuafKr3U1vwYSlsWLSD51HythF+U8xtXoPhH41Hxb4itNJ/4Qbxl o/2jf/puq6T5FtHtQt877zjO3A45JA718ZLOIY6q6lVOE5PazVn2WlrLZdD6SngfqtJUoO8Yre+/ n6npFeY/FT4F2XxG8QaN4lstYvvDHivRY5VsdV05Y85b7omDKTLGp3fu9wBEkgP3jXp9FepRr1MP P2lJ2f8AnoznrUaeIhyVFdHhvwR+KHiYeNtb+GnjxLm78U6b597a6x9kjggv9PEiLFLhHI3kueFX AC7Sd6tXuVeQ/HTwrq1rfeHvHnhSxkm1/QruP+0BYgG6vtJJJuLVEPyzE8OqNyCpKEORnq/hr8Wf D3xUsbuTRbiVb2wdYdQ028haC6spiOY5Y25BBDLkZUlGAJ2mu/FwWIisVShZP4ktk/Ton0+7ocGF m6EnhasrtfC31X6tdTs6KKK8k9YKKKKACiiigAooooAKKKKAEblTj0rw39m3/iT+KPi74fvP3Orw +LbjU5Lfri2ukR7d9w+U7lVjjORjkCvc68w+KfwsvtY1SDxl4NuI9M+IVikVvb3V1cSC0ubUSFpL a4jUMGjYO7cKGDBCGG2vQws4cs6NR257WfZp6X8t7/f0s/PxVOfNCtBX5b6d0108z0+ivGvCPx21 K28WW3hLx/4ZufC+qPstYtZCs2laheEsfLgmIwN6BXRWO7JeM4ZBv9kFc9bD1MPLlmt9uqfo0dFH EU8RG8Ht96FooornOgKKKKACiiigAooooAKKKKAPKv2Tv+TWfg3/ANiZo3/pDDRR+yd/yaz8G/8A sTNG/wDSGGigD1WvI/2pLK31L4W2FpdwR3NpceL/AArDNDMgdJEbxBp6srKeCCCQQfWvXK8e/au1 a10H4R22p30vkWVl4s8L3M8m0tsjTX9PZmwAScAE4AzUyaSblsVG91y7nKfET9l7VY9F8Q2fw48T SeG7DW38y98Pzf8AHlISVBEbKpeAEBtyqCHG1OFAAvaDffF/4V6PYxX/AIV0DxB4b0+BLYWPhm4n F5BCij51E5/e7UUgRg72Yrz1ru/gf4q8ReO/B8niTxBbx2K6pdPcabYopBt7PCrGrEqCxYq77uQw kBGAQq+h15VDD0qiWIoNx5lp6ej2PeqZtiJQWHxUY1FF9VrfRayVm3pu2/uEU5UEjHFLRRXrnz4U lLSN900nsBx/w5+IX/CwD4m/0D7B/Yut3Oj/AOu8zzvJ2/vPujbnd93nGOprsa+ffhz4kuvAN78a tOjs7a91XSdak10pPeC1tpILqNZUUzMp2MqRtncu0HHzYywj/wCGuX1jS4r7w18NvF+t28vmbLgW BELbVcDa6Fwf3iqp9AWPJXafIoY6MaaVeXva9Ozt0Pb/ALJxVSbVKGmnVJe8uZat9Vqj6ELBRkkD 61BY6laalC0tpcw3MSyPEXicMA6MUdcjurKykdiCO1fKXiXwF8efiNpOmeJLrxEunI0f2lvDekXU 2mSpGY428reUJ85iHBEpKxt0OGIHD+AIfhfqfhPT7mX4L+NdSkZSr3mn/aLqGUqSpYSrJGrE7ecI oDZAHFYVMyqKfJGnb/E2rrTayf4nqf2BH6s60Kym00moWfK3fR3cX00aTT11Pu6krkvhr4q8I+IP Ddja+D9Us77TbG0gjjgt7jzHt4tmI1kUkupwpGHw3ynPINddXt05qpFST+4+SlFxk4vdBRRRWhIV 578T/jr4T+E8cqazdyPqKpFKmm2se6eVJGdQygkKQPLfJ3DGBnllDehVSutF0++1Cyv7mxtri+st /wBluZIlaSDeNr7GIyu4cHHUda568asoNUZJS7tXNIOKleaujyW0+O/iixs4LnxF8JvEtlFdoslq NH2ai5GMsJkGxoSMrgMMn5hgbTVLWf2ovBA2aL4s0TXNCTUY5Untde0kqohK4DSR5YtHId6DaG5V twAwT7mcYz2rwX/hMviJ8ZPEfiKw8D6ho/hDw1o+pzaLc6te2zXepfaYMNI8UR/c+WxZUAYk7dzc EhRGHy/HVNYYlJRtdyWi/wDAbP7lcxxGLw9O0Z0m3LZRe/33/E8c+Cn7QF/8EfhrfrrHhDX9a0b+ 03nh1/T4saW6SXGyXyAY41t4x95IsfNI7A+VnA+3FbcoI7jNfNuufsg6v4ss2Ov/ABa8UapfSJdP ITJstfPlDKjJBuIjjEbyo0YPzByA0a5U4dvdfG/9nmbQre7tI/iF4JsbWXTLey0CyLXRCKxtZJQE 3Rk4SMspkRVU5DOVZ/ucRh8PmUVOjVh7e7cvijGX+Hm0Wz0bW6VlY+Ww9fEZe3GrTl7HTl2k1629 e3Q9h+PXxO1r4R+HdP8AEVlpdvf6Db3sQ1qVnzPDbM6pmGPcoZyWABLcHGVIJK8HZ/tseF9e8W+F dL0LSNS1PT9XuILO81FozCNOuJyVhhYEYdyVbdhsBVJQyYIHnf7QC/GPx18OPG+qeJ7e38CeFbKG zaHw601pdfb8TAuzXW8MrqwQhQBv+VFUtkt6D4T/AGdbLxr8EvhqJvE9xL4g0GAajo3iK1QssbSE SxKYph+8iTEICsFYrEo+QErW1HLctweE9vjanPOUnG0ZXjH3E03ZWdm9bSa/xWaJrZjjsXiPY4Sn yRjG92rOXveb0020Xyvc+jRzzS1438NPiFrHh/4gaj8NPHms2up69FBHfaRq/kpavq1u4YyfuUJV HidHXAILKu7bhWY+xgg8jmvlMRh5YefLJ3T1TWzT2a/q62dmfSYfERxEeZaNaNdUxa8/+Mnxi0r4 P6BDc3UMmqa1fyfZ9K0W1ybi/nJACIACQAWXLYOMgAFmVW77zF6bhn614F8QtcsfEH7WHwp0nTZv t9/oUGqXOqQwKX+xxzWyrE0pAwu4gcE5+ZP7656svw8K9Z+1V4xjKT/7di3a/S7SXz7nNjq8qNL9 27Sk0l82l+C1Lnwn+HvxBvvig/xE+ITaJY376EmkwaXo4kbYrTecxlZ2IDKfl+QspzwRty3udFFc uIxEsRPnkkuiS0SR0YfDxw8OWLbvq292zA8eWevah4P1a38MX1tpuvyW7LZ3V5CZYo5McEr/ACOG AOCVcDafLv2Pb6KP4OxeHvsNzp+oeGtQutJ1CG5lSX/SlkMkpR04KZl49ORlsb29D+LWt3vhr4Xe LdW06b7PqFjpN3c2821W2SJC7K2GBBwQOCCK4/8AZb8E2/hL4S6ZfRX19qF34jSLXr6e/lEjm5ng iMmGwCRlc/Nk5JyTXfTkll1SMuso273Sf4Wf37db8NRN5hBx6Rd+1rr8bnrtFFFeOewFFFFABRRR QAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAIzbVJ9K+WNL0bUf2w/FUOta5DbRfCTR7+8isL BHuop9XYIsaXDHKDaCXZWGGUh4yDlmr6nb7p+leD/s13cdv40+MWj2QkvdNt/FE14uqmJokknmUe fbhWHWFowpYE7tytgAjPtZfUlQpVq9LScUrPsm+V289VZ7rW3deNjoKtVo0anwSbuu7Wqv5aanrn g3wLoHw+0aPSvDuk2uk2CYPlW6Ab2Chd7t1dyFUFmJY4GSa3aKK8iU5VJOU3ds9aEI04qMFZIKKK KgsKKKKACiiigAooooAKQnAyaWs/XtJ/t7Q9Q00Xd1YfbLeS3+1WUnlzw7lK742wdrjOQexApq19 RSuk7Hi2sftgeGrXxvrHhXSfDfinxRqWlyPFcf2JpqzgMhCyEAuGwrnaWKgZ6EggnyX4U/Cvxt8U /iw2ueKbzxxF4R0vVk1fTz4kdbZ2njIdYTaEkLzIMSxgJtjkUKpceXm3PwG1b9lfxppnjmD+ydS8 I6XrURm1a4ac6hb2M6/Z3EkSkRsF804KKXLbWxtyg+ndB/aK+G3iPWbDSdP8X6bPqF9BHPbw+YU3 72CrHlgAJSSB5JIk/wBmvvcQqWApOWTwdSE42c2rtNfFt8Lt+D1XU+IoueNqqOaTUJRldRva66ev /APR8cYowPSlor4A+4CiiimAV4P+0Ppus/D3VrD4v+FreK8vdEtGsdZ010djf6c0quQrDPlmJsvu C9CSxKpsb3imyLvRh6iuvC4j6tVVRq66p7NPdf8AB6brU5MVQ+sUnC9n0fZ9GQabqFtq2n217Z3E V3aXEaywzwOHSRGAKsrDgggggjrmrNeBfss6zH4Qttb+EGoL5Ou+D7iQrI0if6fazSvLHOiBiV4k XcvO3emTlio99qsZh/qteVJO66Punqn81Ziwlf6xRjUej6rs1uvkwoooriOwKKKKACiiigAooooA KKKKAMjxV4U0nxt4fvtE1uxi1DTL2Py5reUcMOoII5BBAIYEEEAgggGvELT4heLP2e9a8NeHPiLq dj4h8J6jJ9htfGLLLBNbusZYC8BDoS7FUVt4+WN3cn5iPoWuc+IngHSvid4N1PwzrSStp1+gR2gf ZIhVgyOp9VZVYZBBxyCMg+lg8RTg/ZYlXpvfuul4+a3ts7JM87FYec17Wg7VFt2fk/J/euhzni79 ov4beB/MXVvF+mpNFObaS2tZPtU8cgzlXiiDOuCpBJAAPB5IrzqP4peOP2gtcgtfhjJdeDfCFr5k lz4w1PTVl+2sGdEjtYZOHQlSSxwwxg7CNslH9nT4Y+HPA/xq+JegWOmW08Phv+yzp17dwRyXcTT2 Z89vO27hvxkqCFG5tqqCRX0yqhegx9K9LEfVMtqclCDnK0WpSta0oqS9yz1s+rav0Z5+H+tZhDmr T5I3aaje+jt8V9rrokzw5/BPx08Mr9q034kaH4wmb5Gsde0QWUCL18xXtyXLggAKflwzHqBV/wAK /tMaDceAtV8ReMYf+ELk0jVpdEvrSab7VtukIykRjGZeGBO1eNrnlV3H2OvMrz9mz4cX3jgeL5PD Ua+IBdpf/aobmaNftCMGEnlq4QncoY/L8xyTkk55oYrDYi/12NuzhGKfpZWjZ97Nrs9TonhcRh2n hJX7qTbXr1ena6PTAdwBHSlpOlLXiHshRRRQAUUUUAeVfsnf8ms/Bv8A7EzRv/SGGij9k7/k1n4N /wDYmaN/6Qw0UAeq14x+1zocHij4MJo108kdtqPijwxZyvCQHVJNesEYqSCAcMcZBr2evKv2lv8A knOkf9jn4T/9SHTqlpSVmNNp3RL4F8M/EDwTq2naG2oaFqXgPT0MEFxNHKmqeQsZESMFAiJQ7ELY G5V3YDHFehWmt6fqGoXthbX1tcXtls+1W0UqtJBvGU3qDldwGRnqOlc58XtJ1/W/hr4gsvC97Jp+ vSWrfZZodocsOSisxAQuAUD5G3duHIrzX9mPxN4IjtV8K+FNAvdP1Oz0+ObWria1IMVwGKtb3EzK jPMHaTHyhcBtuACo8uElhKkcOn7r7v8ABeh6n1Z1sLLFp3cXZpLZfzSfS70Xd320v7Zrut2XhvRb 7VdRm+z2FlC9xPLtLbI0UsxwAScAHgDNcRpvx48L69410Pwzo0lzq95qln/aBltYCY7SAxiSN5yc GPeCuARnLLkDcuc349/ErwVoHhvUvCviXxGmiXmuafPBEVtpLl40dTH5hSMEgZJxkjdtYA8HHy/8 Lfixp3wU+FeotNNqFp4/8SCBbS41K1lSKGz8vZa3KswcSQxruI2puY/JtKqGpYjFzp1lTh8K3fby 9X0+Z6uX5VDEYaVSope0lpBWaUujle20etutl1PviuK+KHgbVvHmlWtjpvi3UPCkKzK122nKvmXE QIJVZPvxtlRhlOMFgysDx5L4N/ayjbw1oFpf+F/Fms+J5bBLi5is9JBeZQiA3SqGAMLuzBWX+6ch flzgfEr40fFPVPDst9D4PsPCnhDUpl0r7R4liMkyLM0kf2ieM/LDEAFDCVGGXXHmBqmvjaFSi7Xf pf8AFrYijkmOhXUfdi09HJqzd+ier+SZz2h/Djxb+0m2rXg1S20TQJoRp134iisnDeJmgnzDO1sW UJtVF+YYIJZASuUj+xNO0u10mwt7K0t4ra1t41iihhQIiKoACqBwAAAABXn/AMAYfDOg/D+w8MeH PE9n4nXSU/0i4triORg8rvISwQnYCxfaCTwMZOCa9LrTL8MqVNVJO85JXf8AX9PqcWYY7E1lHDVm uWne1o8u9te+qStfZaKy0EKgqRjg1leGfCuk+DdBtNG0ayjsNMtE8uG3jHCjqSSeSSSSSckkkkkk mtakr0+VXvY8hTkouKejPJviL8OR4avoPHvg3Tre31/SPtFzd6daweX/AG1FIMyxSGNdzSnbujJD DzMZU5yOp+HHxQ0v4k2d21pb3umajYuI73SdUgMF5alhlDJGScB1wykEgjvkEDsKxNJ8F6PofiTW 9esrTydV1ryft0/mO3m+UpSP5Sdq4UkfKBnvmuSNB0qvPS0T3Xy3XnsaU1QjCpzp871TXfS9/lfb rY3KKKK7TAKKKKAMHx74m/4QvwP4g1/7P9s/suwuL37Pv2eb5cbPt3YOM7cZwcZ6V5p+yB4JfwT8 CfD6zSxyz6oh1R/JRAAJgGQZCKzER7Ml9xByA20KBt/tLeINZ8LfA3xbqWgJI2px2oRHhDl4Ud1S SVShBUpGzuGz8u3ceAa1fgj4J074d/Cvw9oOlap/bVhBAZY9QBUrceazSl12kjYS5K4J+XHLdT7M XyZZLX45rTvyxf3W5vnd9jx5e/mK0+GD/F/jt8vmdzSUtITgE14x7B49+1v4qi8K/APxS7XHkT30 I0+BFlRHlaVgjKu9W3fIXYqBu2q2Cp+Ze8+Gfh258IfDrwxod48Ul3pumW1nM8JJQvHEqMVJAJGQ cZA+leI+FLLVf2iPjRrWr+IWls/B3gHWms9J0m3l/d3WoQsd1xMwIYlPkYLgL+8CgnEnmfRWpXke m6bdXUolaKCJpGWCJ5XIUEkKiAsx44VQSegBNe1i1HD0KeDWs780rf3krR+S383boeLhZOvWqYt6 Rtyr5N3fze3ofKn7TU//AA0Nr0fw58D6BbeIda0WdZNS8Qyvsg0fcwVohICNzHHzoN3EZARnQ+X1 mm/D343/AA7srDw54P1zwtf+GNKdhZTa99pN7LAQ+2GcqCuIy4CmPbxEnQZStP8AYtsYl+A+masx km1PWby8vtQuppWkkuJ/tDxmRixPJWNAfUjPUkn3avQx2Ong3/ZkIp06TktVe8tm/LZ2StZd3qce EwMcUvr85NTqJPTSy6L/AD/yPl+3/Y31DVNLudb1jxzfQ/FG6uxeHxTp/moYA0ao9uEEihowN4Vl 8s4KjAUbD7P8Kfgz4V+DOjSWHhrT/s7T7DdXczmSe5ZV2hnY/idq4UFmwoya7mivKxGaYzFQ9lVq Pl7bLyVl0XRbLpuz08PluFw0/aU4e933fr6vq+oUUUV5R6Z47+1jovi7xB8FdZsPB8P2m7mK/bII mcXElqMmRIQpG5zhQVP3kMigFiAeo+CnjDwr4y+G+i3Pg6TGiW1ulnHauxMtp5aKvkyAkkOo29Sc ghgWBBPct9056Yr4n+C/iDSfhj+0l4vmj02+0zwjretTeGbGWxQx2EV/G6nypIAzkEliI3yoAd8I qlhF9Jg6Sx2Aq0FpKn76/vXsmn5pK8bdpdz57FVPqWNp1nrGp7r8rapry6P5H2zRSUtfNn0IUUUU AFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAyQ/u2Psa8M/YytHn+DKeI7m5lu9U8S6n e6rfySBVBnMzRMVVVAUERKcepOMDAHtmqX1tpem3V5eXEdraW8TSzTzOESNFBLMzHgAAEknoBXjn 7F//ACbb4S+t5/6VzV7FFWy2tL+/TX4VH+i/A8mrrj6S7Rk/xj/wT22iiivHPWCiiigAooooAKKK KACiiigAooooA8+/aA0SPxF8F/GVlLqcmjxnTZpWvI3ZQgjUyEPsVmMZ27XVVJKFgBzXxD+yL8Ht Q+I/jmz1u3luNO8JaFf2d5dpLcNm5u4o2ZPLxHsbbJyVOGSObAYltx/R5lDKQehr8/vjH4SvfB/i y58GeAtR8ea9Y6Jd2lw2gaFHKlrpcDvJdeWZkDF5jIyPHK0Z2AAFnZPl/QeG8dU+p4nLacuV1LO7 2S2l5X2SbaS6NPf4fPsLBYqhjZrmUdLLdvdfLe9v+G/QEdKWmx/cXPXFOr8+Pt1sFFFFAwooooA8 b/aQ+G93r/hSTxV4Vj+xePvD+2+07ULSIG5lWMOXtshGZ0ZHlxF91mKg8E56v4M/FbT/AIyeANP8 SWEf2Zpt0VzZtKsj20ynDIxH4MMgEqynAziu4ryrxh8ELiXW5Ne+H/iH/hXmv3eV1K4s7CK4g1BS xfdLA2FModiRL97DuDkEY9anWpV6Cw1Z8rTvGTvouqdk3bqrJ2d9NWeVUo1KFd4iirprWPd9Gr6X 79/kerUV4Z4Y+Oup+D/Glz4P+Ld14b0XVWsV1S01PTrpobGSEyGLym+0EMJdylhjIK56bfm9k0PX tN8TaZDqOkaha6pp827y7qzmWWJ8MVOGUkHBBH1Brjr4arh7c60ez6P0Z1UMVTxHwvVdOq+Rfooo rlOsKKKKACiiigAooooAKyPFnirSvBPh2/1vW72PTtMs4zJNcS9FHQAAckkkAKMkkgAEkCtbrXNf EqG2l8A6811oEfimKGzkuBossQlF48amRIwpVsksq4+UnOCATWtJRlUipbXRjWlKNOTjvY8g/Y5s bnUPDfibxdq1vq8mu69qZeXVtYQxPqNsqBraWOLG2OPZKQFQuBggMVCqv0LXkn7J8NxD+z34NW51 GPVJDaswnhnMwVDI5SIsehjUrGV/hKFR0r1uvQzWfPjq3lJr5LRW8rLRdNjiyyHJg6fmr/fqFFFF eUemFFFFABRRRQAUUUUAeVfsnf8AJrPwb/7EzRv/AEhhoo/ZO/5NZ+Df/YmaN/6Qw0UAeq14t+19 4gt/CfwT/ty7SSS10zxN4ZvpkhALskWvWDsFBIBOFOMkV7RXlf7S3/JOdI/7HPwn/wCpDp1NWvrs HoeXXH7X/iTUNF0+8sfh61jZahHGo1++vWfS7WSV9iM8yR7WRSybxuRlbehAZaL7WNf+Eml/2Np9 zp+p/GPx5qbSzSwl547KJiypKoMZbyYUUBVkyFPmEblRlrY+M/7NOlXXi/T/AB14b8H2eu6hHdPc atoTXRtk1QsAFfcxMalHG9l2gSZfcSeG5z4Z+I/ht4B8faNFZ/CvxB4Rk1OcWcWs69Zykw3LArFH GXZyu8NIpKkdFyCuSng4q9LE+5UfLpZySur72srPtd2721PvsH9WxGBU40Fz2blGDum1e3M5S5kv tWSaeivdNjvgtqHi6x/aAWf4tw3Vp4q1TQl03RfLih+xzRRMZZwxi3DzcoJOoA3uMKDEtfVpjVuS oP4VwXxo+HU/xI8IJBplzHY+INPuodS0m9lBZILqJtyFgOCCCy8hgN2dpIArxb4a/E744td6tpWo 6ToviLVfDrxpqOkyzC11CUTLviZZUzbYAOeOcRkEZIJ7q2OnCso11e+zUUlotml166LX1PEpZbTx 2HeIwkowcfihKT6vSScr+7qlrLR+TR9S+Un9xfyqG/0611Sxnsry3iurSdGilgmQMkiMMMrKeCCC QQfWvDZvF/x9vmuLm18D6BpcE80dvb2d5f8AnTWo+QtcSujBZIsbxtXDglThgvzd78L/AIoSeO5t Y0rVdHk8O+KNFeNNR0p5luBEJV3xMsqfK4ZeeMEEEEdCap4mnUkoWav3TV/vOOtl1ehB1VKMlHfl lGVvN2b0u7X2v11V+h8M+BfD3gv7SdB0PT9HNzt877DapD5m3O3dtAzjccZ6ZPrW7RRXXGKirJHl ynKo+abuwoooqiAooooAKKKKACiiigDz/wCPml+Idd+D/ifS/C1hHqet39qbOK1ldUDJKwjlIZmU AiNnYZPUDg9D0XgLwyfBXgnQPD5ufth0uwgsvtGzZ5nlxqm7bk4ztzjJxnrW9RXQ68nRVC2ibfnq kvwtp6s51Qj7Z1+trBRRRXOdBXttPtbOa6mt7eKCW6kEs7xoFaVwioGYj7x2oi5POFUdAKmkXcjD 1FLS07isrWPJP2YfDOreB/hgfDGq2EtqmjapfWdpdzDYb+AXDstyI+sYYswCknIUMCQwr1uiit8R Xlia06895Nt+r3McPRWHpRpR2irBRSV4R4w/aKv9d8TXXgv4WaJL4k8T212tpe6je20kel6YQ8iy ee/ysSPKbAHDZ+VnI2GsPhauKk1TWi3eyS7t9CMRiaeGSc3vsur9Ee8UV88Tat8cPhDZ6bqOttZf FDRjJGdVi0qxMWqW+8bWW3RNqSxowUhiodtxyEUbl9G0n4//AA61rQbPWYfGOkQafdSSRRSX10tq zPHjeuyUqwI3IcEdHU9GBPRVwFWC5qbU47Xjdq/bZNfNK5hTx1Kb5anuS7S0/wCA/kd/IcIxJwMV 8U6PpP8Awknw88f+LdKu7W7h8LfEq88WRJ5n7q/ht1WQokq7tu5GJVgGBIA6HI9M/am+JFv4g03/ AIVL4XvftXjbxDcW1nJBbPKDZ27nfJJK0aN8mxMOmQfLkLEFetL9rL4OaDZfs4eRpEH9lW/hby57 G1iuxDbnc6pJ5gdtsjlXcgnMhc4BJdg/uZZQVF0Y124utJJabR/m3Wkm7L0bPEzKo8R7SVJcypRb 36vp8rX+5H0F4R8SW3jDwro+u2aSxWmp2cN5CkwAkVJEDqGAJAOCM4J+ta9YHgH+xv8AhB/D/wDw jv8AyAP7Pt/7P+//AMe/lr5X3/m+7t+9z681v18rUSU5KKsr9T6ek26cW97BRRRWZqFFFFABRRRQ AUUUUAFFFFABRRRQAUUUUAFFFFABRRRQB5R+0Z4wvPDvhLSdHsIrY3PivVrfw4Lm8hE8VqtxuVpW hb5ZcKpGxiFJIzkAqfQPCPhu28HeFdH0KzeWW00yzis4nmILskaBFLEAAnAGcAfSvHvjxav4i+Nf wS8Oz3MsWlzaleatJHCFBeezhWWAlipIGS4IGMhz3AI937Yr1MRD2WFoL+dOX/kziv8A0l/0zy8P L2mKrSf2bR/BN/mLRRRXlnqBRRRQAUUUUAFFFFABRRRQAUUUUAIehr420Gw+JcP7QvxXsfCkkcNx eanYLqGoxyR3EdhaOC8Uvl3J3vIIiRtVti4kVUwYjH9V+Pri9tfA/iCbTtRttI1COwuGt9QvWCwW 0gjYrLIWBARThiSCMA8GvKP2PfDHh+3+FNl4s0uO+k1nxEnmaxf6jcNLNdXMcsqux+YqB5jS7SAC VKlstmvTp075diXzuPPyw082pat7K0XtrfseVWnfHUIcqfLeWvpbRdd+uhW8ceNPjR8PPCuoeIdX bwCun2KBnEKXzuxLBVVR6szKBkgc8kDJr1n4e+PNP+IXhHT9csp7ZvPgje4gt7hZvssrRq7Qsw/i XcAQQD7Ct+8srfUrOe0u4I7m1nRopYZkDpIjDDKyngggkEGvL9X/AGWPhbrkMEd14SgCQwJbqLe4 mgyq8gt5brvb1dsse5NfL0cNXoYmLVTmpO176ta7rvp009T3alSEqTtG01t2fk/89fQxLn9rLQ7n VNRt/DvhPxd4zsbKc2z6r4e0r7VZvIACypJvGcbhzjB6jKkEwf8ADWVjY30Mmu+BPGfhbw8Ec3eu axo8kcNs+VEYYJvJDklc9Q2wYIYlfYvC3hPSfBPh+y0TRLGLT9Ls4/Lgt4hwo6kknkkkkliSSSSS SSa1WRWGCowfavq5VsEpWjRbj/i19drJ/Jr1PBVHGtXlVSfpp6d7EGn6la6tZW95ZXMN3aXEaywz wuHSRGGVZWHBBBBBHXNWa8H1T9leDSPEEniH4f8Aii+8Ea0ZNsJEYu7S1tmEjS20NuxVFjeWTzdr bgrKCgWqlx+0j4g+GkF7Y/ETwNq9xfafIom1rwxYvJpEqOFZGWWdk2kFxGQSRuXg87RnUwtJwdTD 1FJJXafutffo16P5WLhiqkZKGIp2b0TWqf6/ej6DorxGH9sz4S3WpadZQeJWka8nEBmeznhigypI eR5EUKmQFzzgsCcKGYe2qwYAjpXPXwmIwtvb03G+101f7zqo4qhiL+xmpW3s7mF4n8B+G/Gv2c+I NA0zWzbbvI/tGzjn8rdjdt3g4ztXOOuB6V5GbG3/AGc/ifeapHbx6X8MPEkcEdwbdAtto+oriNHa NdqwwTJtVpMN+8C7mRcZ96qvqGn2urWNxZXtvFd2dxG0U1vOgeORGGGVlPBBBIIPXNXRxMqacJaw ejX46dnfUzrYaNRqcNJrVP8Az8ih4b8XaH4xs3vNC1ix1m0SQxPNYXKTorgAlSykgHDA49x61rAh uhrwjxP+yXozeJpPE3gTW774c6+Y441Ojogsm2urHfbgKGDBVBQMEJUEqTu3ZWn/AAz+IvwBbS7r wXeal8TrW681db0jWtTjgzM2ZBc2xcYizI0pcFnLeYMhj869v1PC1kvYV/efSS5emt5fD5J3162O P63iqT/f0dF1i7/hv6/qfRtFcL8Ofi1pvjrztOuY/wCwvF1juTUvDl5Kv2q1ZduWA/5aRHehWVfl YOvQkgdznPTmvKqU50Zck1ZnqU6sK0eaDuhaKKKyNQooooAKzvEVpeX+g6jbadf/ANl6hNbyR299 5Il+zyFSFk2Nw204O08HGK0Kr6jp9tq1hc2N5BHdWlzG0M0EyB0kRgQysp4IIJBB65qou0kyJrmi 0eQfsdNbt+zj4RNtFJDHtuQVlkEhLi5lDtkKvBbcQMcAgEsRuPtFeA/szWt74D8UfEL4Xm//ALS0 LwnPayaZNLEEnWO7R52jcrw20n72ASSx4BVV9+r1c3iljqsou6k+ZekveXzs1c87K5XwdOL3iuV+ sdH+KCiiivIPUCiiigAooooAKKKKAPKv2Tv+TWfg3/2Jmjf+kMNFH7J3/JrPwb/7EzRv/SGGigD1 WvKv2lv+SdaR/wBjn4T/APUh06vVa8q/aW/5J1pH/Y5+E/8A1IdOoA9F8QXl7p+h6hdadY/2nfww SSW9n5oi8+QKSqbzwu44GTwM5r4/0GH4d/ErwlP42+Inj21i8aXEhvIZ9Mv2trnSYo2BS3ghJOSp RiD5ZYlyVLHDt9oVymsfCjwZ4i1KbUNU8K6NqN/NjzLm6sIpJHwABlmUk4AA+gFedisNKu01ZpdH t6/I97LcwhgoyT5ot296Ls7a3jr0f6a36eLWP7Vl/ob2eu+LvD39jeCNdmMWiSq4a+WNNuZ54S2W jYNuDRgldoGH3ozTfG/xdpN34Ftfi94B1mzk1jQ5IYmuYRv+1W8roHs51DAgZlR9rjchHG0tkfRT Qoy7dilcY6V8+fFr4BR6b4JvrvQbW48RTReKB4tudFuAj/bSTia3TCjC7CSAVdjjbhiwrlxFLEU6 Mry5lbtqn3VvyPQweLy+eJpz9l7Oz1V7xlHs09rrRu9nvZH0JG2+JCepUGuE8J/CtfB/xJ8U+J7L UpJLXxEkLXVjcq0rpNHuCskpfiPaxHllTjjaVUBa0vh/8T/C/wATLG4n8NarHqSWjLHOojeN4yRk ZRwGwecNjBwQDwcdZXpRdLERjUi+ZLVNfcfNqpVw/PTWnMrNeV0/zSYUUUV0nKFFFFABRRRQAUUU UAFFFFABRRRQAUUUUAFFFFABRRRQAUm0A5AGfpS0UAJ1rznxd+zv8O/HXiuPxLrnhm3vtYXy8zNJ Iqy7D8vmRqwSTjA+cHKgKcgAV6PRW9GvVw8uejNxfk7fkYVaFKuuWrFSXmrnKfDv4W+GPhTo8+l+ F9N/s2xmnNzJGZ5JsyFVUtmRmI4RRjOOK3Nc0HTfE2lzabq9hbapp823zbW8hWWJ8MGG5WBBwQDz 3Aq/RUzq1Kk3UnJuT6t6/eVGlTpw9nGKUe3QQAKMDgUtFFZGoUUUUAFFFFABRRRQAUUUUAFFFFAB RRRQAUUUUAFFFFABRRRQB4f+1Qp8J+HND+Jlmcav4Lv4540/5+be4dILi3ycqm9XX59rFdnGM5r2 5G3Ip9RmuL+NXgxfiB8K/E2gmz+3y3Vk5t7fzfL3ToN8PzZGMSKh5OOOeM0vwd8YDxt8L/DetS3g vLi4s4xczlPL3TqNk3y4AH7xXHAxxxxitquNpSp0sLK/PHmd+nL7tkvRuTf+I86nF08XN9JJP5rR v7uU7WiqOl67p2tfaf7Pv7a++yztbT/Z5Vk8qVcbo2wflYZGVPIzV6sFJSV0z0E09gooopjCiiig AooooAKKKKACiiigDxb9rTx5H4V+EOqaRbPHP4h8Rp/ZWm6b5bSy3ZlKxyiNE5JEbtg9NxQHJYKe 8+E2jXnhn4X+EdJ1KIW2oWOk2ttcQ71bZIkKKy5BIOCDyCRXiX7SuuT658Xvhh4c8F31tD48hvrn OoRTRTS6VbvAvneZbOdrb4m8wbsHEOF5asbxz8I/iTcTaZ4q8ceKfEOtLDJN5umfD2U20umFi6wv boy/vxtkdGYhZAsnLOqmvo8RTo4fLaDrSUFK8no3LdxWi+zpve929LWv85TqVauPqulHmcbRXRd3 r/NqfVWoalaaVY3F5e3MNpaW8bSzTzyBEjRRlmZjwAACST0xXKW/xm8C3Wv3Ohp4s0gavb3YsHsp LxElM52/u1UkFzlgvy5+YFfvKQPKNB/Zm8GfEbS9K1a+8deL/H3hyT/SYbPVtbaW2kbayBiFVXV1 3MOCpBBB7iu9tf2ZvhdZ6C2kR+CdJa1aN4/NmgElxh85PntmUHk4bdleMEYGOCEct9mpe1lJvtFW +9u79LL1O5zzCUrKnGKXdu/4LT+tD00EMMg5FLXiv7O0kvhPVPG3wzm1a+1tPCN3bixur1FBSyuI Fkhh3A5YxkSLkgDG3bgYVfaq5cTQ+r1XTvdaNPa6aun800dmHrfWKanaz1TXZrR/iJXk/wC1VZz3 vwF8VJbQSXEipBIViQsQiXETuxA7KqliewBPavWa83/aM17/AIRv4I+LrvyPtHmWRs9m/bjz2EO7 OD93zN2O+MZGc14uYW+p1VJ2XK/yPRw9/bQtvdHU634f0H4j+EZtP1C3tdZ0PVIAWAIeOaNgGV1Z T9GVlOQQCDkA18x+Jfif8Uf2V7i9sNT0e++IHgeK7Mtl4g1Ccm4WBl5immXftIlljVXkUbtjhRhl 8v6b+H+g3HhfwL4d0a6eOS60/Tre0laEkoXjiVSVJAOMg4yBS+Phov8Awg+v/wDCRj/iQfYJ/wC0 Pv8A/Hv5beZ9z5vu7vu8+nNfR5TjlSUYYmkqkJWvF3301i1qn08+p4WYYN1E6lCpyTjtJfk+6Mv4 afFTSfidY3b2dvfaVqVi4jvtH1aD7Pe2hYbkMkZJwHXDKwJBB65BA7OvkH4IeBvE3hf4L+Hvib4e mvn8Sw6cy3/h+6RjDrVjFNOYlwEMgn8loxDINwCrGgXYxr6g8DeM9O+IXhLSvEWky+ZY6hAs8YLK WTI5R9pIDqcqwBOGUjtWuZYOGGrTVB3hFuPo1+j3Xl5pk5fi516UVXVptX9V/W5vUUUV45655/8A FL4H+GPixDBLqUElhrNrJFJaa7prLDf2xjYsoSXBOMs3ynIBbIAYAjjfCfgH4i/DL4p6LY6d4g1P xb8Ob2CZtSm8Q3kdzd2dwFJRlchX2MViUKu4DMpKjIavcqSu+njqtOm6TtKNmrPW1+q7NbrzOCpg qU6iqr3ZXWq0vbv3FooorgO8KKKKACkPSlpKAPCPgOtzN8a/jbeatLFBrb6lZwPp0MZxHZxwsLSf zNxDGWM5KjlShyBuAHvFfPHh280r4a/tQ3vhfwuI9TTxYk2qa/bRxFpdInVS6TNOASY5i5Hkufka QMpUSBW+hq9fNLyqwqdJQhb0UVHbpqtPKzu935OWtKlKn1jKV/Vu/wCv3i0UUV5B6wUUUUAFFFFA BRRRQB5V+yd/yaz8G/8AsTNG/wDSGGij9k7/AJNZ+Df/AGJmjf8ApDDRQB6rXlP7S3Hw50g/9Tn4 T/8AUh06vVq8R/bK0++1f4Ez2Ol3P2PU7rxF4cgtLjzGj8qZ9csVjfcvzLhiDkcjHFTJ8qbRpTip zUW7J9TX+IH7Qmi+Gb600Tw7HH4z8W3d2bOHRdNuU3Iyn94ZnG4RBBnO4dj0AZl566/aUm8ZTWXh /wCHuiXF14zuJ3S6s9ctnhi0mON9sklztP4AKxOTg/NhGtfss+HfCUPw30m/0rRLbT/EFvE2n6pJ JCovUuUYedHK3LjLjcEYjClOBwB7btHpXkKnisTFVFV5U+iV9PJ9/wCrHr4yOFwtV0KcG3FtNt7u /ZaJeV/mUtDtbyx0exttRvv7Tv4oESe98oRefIFAaTYOF3HJ2jgZxV2lor2Tw0rKxzWm/D3RdF8X XPiPTbb+zr68gaG8jtSI4btjIHEsqAYaVTvw/XEjg54x0tFJWcKcaatBWRTk5bi0UUVoIKKKKACi ikoAKMivKP2ovEmt+EfgvrmraFqH9m3UJhjklRCZfLkkWNhG2R5bfODvwSADjBIZc3T/AIT+Mfhv YWx+H3iyTVo2jWCTTfGc73FtFGoGxoDEqtGVwV2gbWDc42LXm1cXOnWdONNySSba879Oux2rCv2E a7dlJtL1STf/AKUj2qiszw2+rtoVmdfis4dY2YuV0+R3g3g4yhdQ2D1wRxnGWxk6dehGXMkzjejs FFFFUIKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKAC iiigAooooAKKKKAE4YEdjXjmpfsseEdW1QNc3WsP4fWZriPwyl+yabFIwbJjjUAp8zs2FYAFiB8v y17JRXNWw1HEWVWKdjKpShV+NXPnz4h+BNI/Z707SPG3g+3l0qw0i6ij1jT4rmVkv7SR2Q7kLfvZ kaYlC7ADJzkKoH0CrblB9RmvF/2rLUXHgfRZL4yDw1BrtlJrnlysgNkXKuGCkMw3NHwuTnBA4yPZ 4/8AVrjpiuHCxjRxNWlTVopR0++79Nvmmc9GKp1ZwirJJafePooor1ztCiiigAooooAKKKKACiii gDxP4l/CzxDpPxMtPif4BFjLrsdobLVtGvNsKapbD5gFlCkpPlUUM3Hyx5IVCr938PPG+j/Gr4dW mvWtjL/Y+rJNEbTUokLMqu8Tq6gspBKtxk5B59K8j/a78Za7Z3HgDwb4f1+58PT+KtVW0mvLOP8A epGJIlyJBIrLhpVJVRlwCN6gEOfDLxlafsy+G7fwB46gutN0/TftMtj4qELNp1/GzyTqm4ZMdxjz R5JBJ8r5WbegP1FTByxOW05zfNUekYpO/IuZO/R2lZK13a/RafM08VDD4+pCOlP7T6cztb0036HQ 6f8AsxWPgv7TdeA/FGs+E9UlnaUSeYt1bFTgLFJA4AkVFMmwsdwMhJZsDHr+i/2h/ZFj/a32f+1P IT7X9j3eT520b/L3fNt3ZxnnGM1V8K+K9J8baBZa3od9FqOl3kfmQXER4YdCCDyCCCCpAIIIIBBF a9fG0sFTwcnGnHl8un3dGfUyrvEJScr+f/BPKfiX8Ldek1tvF/w51W38P+MJPKiv47xC1jq0CMMJ cKFJDqMhZVG8KWTIBBXo/hr8Srbx/ZXcM1pJoviPS5Bb6tod0wM1lMRkcjh43HzJIvyuvI5yB2de YePvgNpXizxA/inRtRvvCHjTYqDXNJkKmYJyiXER+SaPcELKwywjVdwAxXuU61OvD2WIdrbStqvJ 9XG3q1000PKqUalCftcOr33jf8V2f4Pqen14x+0xZwaha/Dq1uoY7m1n8ZafHLDMgdJEYShlZTwQ QSCD61ynxAk+KnwJ8K3PjjVfiXF4z03S5ITcaFNoMFmt0kkqRFfOjYshHmbgQDyoyCMg+s/FnwZd +OPC9p/ZKWZ17TdQtdU019QeRYEmilUkv5fJBQyLjH8XY4I83N8vlHCXpzU4yvqr7xs2rSSezXS2 u+514HGKpW5ZxcJKzs7bO9no2ujO4X7oryX9qzxlbeDPgP4rmm8p5r+1bTIIZJhGZHnHlnbkHcVV nk2gciM9Bkj1odBXh/7RmhnT/Evw8+IU+n/2to/hO/lbU7XyfM8i3nRVN5gBmPkMiSbVUnvldpav SyuNN4qn7XZa27tK6j/28/dv0vc5cxlNYWfJu9PRPRv5LU9L+Gfhu48I/DnwxoV68Ul3pumW1nM0 JJRnjiVGKkgEjIOMgfSvJfGXwf1L4T+JZPH/AMKre3swkB/tvwlGjJa6pDGhZfISNG2XHG1cLgls 93EnuGga5ZeJtDsNX02b7Rp99bx3NvLtK743UMrYYAjII4IBq9JzGw9jU08VVoVZS/m0kns/Jr+m nqtQqYWlWoxS+zs1uvT+tTE8DeMtO+IPhHSvEWlSeZYajAs8eWUsmRyjbSQHU5VgCcMpHat2vEP2 OnFj8E7Pw/OfL1fw/qF9pupW/XyLhbl3Kbh8rfLIhypI568Gvb6jG0Y4fFVKMHeMZNJ91fR/NGuD rSr4enVlu0r+vUKKKK4jsCiiigAooooAKyPF+sXPh7wrrGqWeny6td2VnNcQ2EOd9y6IWWNcAnLE ADAPXoa16z/EGk/29oWo6b9rubD7ZbyQfarKTy54dyld8bYO1xnIPYgVcLcy5tjOpzcj5dzx/wDZ F8KQ6f8AC9fFNxd22q6/4suJNX1PULfYQ0ju2I8qq42c7k5CyNKBxXuFeLfsuXSeHvB118Oby2js fEng6X7PqMFuWeGQTM8sNxG5Y7hKpLEHaVbcNiDaK9pr0c0bljasns3p/h+zbyta3SxwZaoxwlNL tr69fnfcKKKK8s9MKKKRmCjJOBQAtFeV6l+1J8K9J1m10ubxpp0lzc7dklszTwDcxUb5ow0acjnc wwOTgHNd54i8YaF4QsY73XNYsNHtJJBEk9/cpAjOQSFDMQCcKTjrwa6p4WvT5eem1zbXT19O5yxx VCd+Wadt9djYorlPBPxS8KfEa4v4fDWtW+sPYbftJtssse55EX5sYOTDIRg8rtYfKyk9XWFSnOlJ wqKzXRm1OpCpHng7ryPKv2Tv+TWfg3/2Jmjf+kMNFH7J3/JrPwb/AOxM0b/0hhoqDQ9Vryn9pbn4 c6R/2OfhP/1IdOr1avKv2lv+SdaR/wBjn4T/APUh06gCHxR8L9V8Ka9e+Mfh9PJFqcr+ffeGZJtm n6oT/rGAxiK4YBcSjjKDcMM5ORpVx+0JdW8M1xb+A7RpEDNbzm7LxkgHa2wsuR0OCRxwTXrPjDxX YeB/DGpa9qcnl2VhC00mGUM+Bwi7iAWY4VRkZLAd6m8M69B4q8O6XrVqkkdrqNrFdxJMAHCSIGUM ASAcEZwTXmyo05VHTjNxe9k/xPU+u1JUuWpBS6czWunS/wDT87GB8Pf+E+/0/wD4Tf8A4R7/AJZ/ Y/7B8/8A2t/meb/wDGP9rPauxpa+Ufif8SfiFc/tGNpvhW11m70/w2bRH03Tk3W15JPsdvtL42xK 0bMod94Qx7htyzLGIxMMtoxcry1t3f8AVjPDYWWNlPlajyq7voui/FtH1Pe31vptnPd3c8drawI0 ks0zhEjRRlmZjwAACSTWb4a8YaL4yhu5tD1K31W3tZ/s0s9q/mR+ZsR9ocfK3yuvKkjJI6ggeK6j 8JfiN8aLa4l8a+Jf+EU0a7nKN4UsYI7jZbLJGwDThsGUmIMHw23JxgM0Y9p03RtA8B6PdGwstP0D TI91zcfZ4o7aFcKN0j4AA+VRlj2X2p0MTXrTcnT5Ka6vd/Lp89TCdOEFZSvLy2Xz6/I2qK4j4dfG Twn8Uo5/7A1WOe4heRWtJv3c+xGC+aIz83ltuQhsfxAHDAqO3rupVqdePPSkmvIxlGUHyyVmJXk/ xQ+Os/wv8aaTolx4T1TWbTVbWSWzudI2z3Es0Z/eRCDg4VCrF898YOCR6zVC80HTdQ1Ox1G6sLa4 v7Df9kupYlaSDeNr7GIyu4cHHUdaVaNSUbU5Wf8AVzowtSjTqc2Ihzxs9L21tp+P4HzN4Z+Nnxiv 9a8TWem+AdV1y3uHe50mfXbVdKNkh4ET5+SUKSuAHDsAxJ5+TT034ifEj4QfEzSV+Ji6Re+GfG+p waXa3mk3cpTSL7yXEcQheMuy3BSMDDbUZZGYjdz9J7QOgA/CvLPi1+zn4a+MWrWWpateavYXlqo8 qXS71oGWVN5t5xwdssLSyOjDHLkNuU7a4PqtamlJVHJp9dvy1+Z7NTMcNiLw9hGnFqzaTbbVrbuy 1X2UvPcwfj78dfCel+D9Y8O2VzZ+J/EeopJpsOhW0jytJIzCJ45PJyyEbz8pKsxUqpB5HbfAvwdr HgD4V6HoGu3cd7qVkkiPLFK8ibDIxjVWYA4VCqgY424HAFeBfsvtZfBf4p3nwX8VWmkXXi+2spL3 SfFVtatbzarZNKW8mUyqGeZQA/7lpU2oylt0DFvqrXtbsvDWiX2rajL9nsLGB7ieXaW2RopZjgAk 4APAGarDqU5vE1XZpWt2737kYyrShQjgMLFtOXNzPeWlo2XRWvpq23q9Elfor57t/wBqbWvEmoWV n4V+F2v6nJfwi4tG1JlsY5ogCZJBIQy7RmHDZwxlxwdu/W/4aUvrM+RqHws8cRX8XyTpaaWLiFZB wwSUOBIuc4cDDDB71rHHUJXs/wAH/kYTyfGU/iir9uaN/uvdHt9FcB8K/iNrXj5bwaz4N1DwjNbQ W8u29YssrS+Y21G2rnaixluhVnKlQVye/rppVY1oKcNn8vzPJqU5UpuEt18/yCiiitjMKKKKACii igAooooAKKKKACkpaKAPE/En7RWraX4gn0rSvhV4z1drS7kiubtrDybdoIt5kmgkyRKSEyiHb5m4 AEEgG1of7V3w91DUIdL1fULrwhrrbvN0vxJZyWclvgFh5rsPLXcuGGX5DKOpxXsO0elZHiXwhofj CxW013R7DWLVH81Ib+2SdFcAgMFYEA4YjPua9OFbBySjUpNabqWt+7umreSt6nlyo4uLcoVU/JrS 3yt+voa4YMMg8UteD/sw+ILnT73xp8NZbqLVbPwTdpbWOqJdGd5LaUyNHDKcACSEJ5bbcAY2BRsy 3vFc+Kw8sLWdJu+zXmmrp/NNM6sLiFiaSqJW/wA1o/xCiiiuQ6gooooAKKKKACiiigAooooAKKKK ACiiigAooooAKKKTOOvFAHh/7TinXH8A+FZIbhtP1rxBAt6wl8m3kgTJaGSTcvzNuDInVjGdvzAV 7enyqo9q+bf2g/FV/r3xQ8L6D4e0y48TS+F8+JdS0yxuIo2ZoyvkAMQzbhkkxhcssq4BJBX2P4a/ Ffw38V9Je98PX3nmDYLm1lQpNbsy5Cup/EbhlSVbBODXgYXE0pY2tG/vOyXnZdO9nc5qEJTlUrJa XSv6L/g/fc7GiiivfOkKKKKACiiigAooooAK8x/aV1+fw38D/Ft/Z67J4evIrUCG+gjLyB2dVWNc cqZCRGHHKb93G2oP2lfEnivwj8LbrWPCdz9hmtLiGS/uorQXdxDZ7sSyQxN8jOvBO8hQgkOVIBHK /DL9m/wTq0lr441fWj8SPE81/wD2ividLtkiaSNwEWOOKQx7IzGF2ncAVI4UBV9zBUaNGMMdiJ+6 paRSu21Z2d/dSfm2/wC60eLi61WrOWDoR1a1bdkk9NLat/d6lL9lX4L2ejaNa+L/ABJ4NutJ8dOX L6lq2oNd3N0JVV3uChwIXYu6bSvmAKQxJZs++a5oOmeJtLm07V9PtdU0+bb5lreQrLE+GDDKsCDg gH6gVfA2jApa4sZjauMxDxE3q9tXp5K7bsuh2YXB08LQVCKuuui19TyHxV8Gr7w/r174v+GE1loP iq9fdqNnqHmNpuqg8ZmjQ5SRTl1kjAJYuGz5jET+DfizqWk61H4T+Jkem6B4pmw1hd2crDTtWVmC hbdpPmEqM6o0TfMcqy5VuPV68++N3w3uPiV4MW20y6i07xFpt3Dqmj30ylkt7uFtyMy9CCCynIYD fnaxAFa0sRHEONLE7bc3VdteqXbXTboY1cPLDp1cNvvy9H306N/megUtcZ8JfiRbfFLwZbazHaSa ZerJJa32l3DAzWVzGxWSGQdQQRkbgpKspKjOK7OvPqU5UZunNWaPQp1I1YKcHoyhr+h2XibQ9Q0j UoftGn31vJbXEO4rvjdSrLlSCMgnkEGvF/2Z9Ul0XWvHnw3XWJPEWm+DruCLT9SmkV3WCWMkWrbR 1haN0JJ6/LtQKFHu9eGWrHwl+17fQp/oGneKvDaXEpl4W+vrabYBGzfxpbnJRD907iO9elg5KdCv QlreN15NNa/+A8y/rTzcXH2dajWWmtn6NPT77HudVdS0+21bTrqyvLeK7tLiJopbeZA6SIwIZWU8 EEEgg9c1Zoryk7O6PVklJNM8R/ZL1uS3+G0XgnV5bpfF/hUtbarY3aPvtleaU26hyNroYlXaUZl2 hccYr26uN8DfD+58L+IfFWualrMmualrl2HSV4zELWzTPkWqpuK4j3yHcApYyEsCea7Ou3HVYV8T OtD7Wvzert5XvbyOLBU50cPGnP7OnyW1/O258+/FPS/+FN/ELwp4q8L3dzYDxR4ltdJ1fRvMzp1x 9oDCS58nHy3B8uP94pGdvIO5930Cp3KDXK/Ez4Z6F8WfCd14f8QWvn2k3zxyIQJbeQAhZY2wdrjJ 56EEggqSD4fpfx/b4J/FgfDLxzr9trOjrBF9g8RyP/pVtuLbItQOdu7btHmgDjY7j94xTvp0J5lR SormqQTuuritmu9trb2ta/ThlVjl1ZurpTm1Z9n+lz6bopqyKwBBBp1eEe2mnsFFFFAwooooAKQ8 gilooA+avD15e/s2+PPGc+u+F5ZvCniXxF9qHjO3kgVYTcsmyO4jL7o4IneYeaxxk8L89fSisGUE HIqvqGn2urWNxZXtvFd2dxG0U0EyB0kRhhlZTwQQSCD1zXirfDbxv8GW8r4V/wBm6l4SP+kSeF9c uZvMgZeXSynJO3zuSRKSqP8AMOHYD15zhj7OTUami8pWVt29H/5K/K2vkRhPAaRTlT/FX/Nfj6nu dJXzneftK+LfEniuw8I+D/BH/FX2UEl94h0vWpxCtrHGcGCGUEB3kLJsmAKbZI2IILeXrW/xW+Ns ct01x8Eo5ImcGBY/E1qhjTYoIYnO47g5yAvBAxkFmr+ycSkuZxTavZzgnb5yW+67rXqg/tTDtvlU n6Rk/wAke7H8q+bfiP4l139oD4jX/wALvC00mn+ENMkSLxZr1lPEZSHR2FtGN2QCUaNyASGyGXar CTivi1+2jo3ijwLoGl+F9cl8P6xrTwx6zex2ssp0WBlHn7HIQvIpbAaMHIVyCrbDWx8B/jx4C+F+ g6B4VutB1fwZpF5aRTWviDWrA20WrXTFRLKSGcAENEwcuVCnBKKibvbw+U4zL6LxVSg3Ud1FNPS2 8/Nr7K1/meiV/IxGZ4bG1Vho1bU/tO+/93yv1enbc+g/DXwn8HeENEudJ0jw3ptlYXVutrdRJbIf tUaqVCzEjMvDNkuSTubOcmuD8M/sh/DXw7eJcy6RNrrQSSGzh1i5e5htIXLHyEiY7DGrO7DerNuc sWJ5r2HT9QtdWsbe9sriK7s7iNZYbiBw6SIwyrKw4IIIII65qxXzMcbiqfMo1JLm31evqfQPB4Wo ot000ttDB8MeBPDfgn7T/wAI/oOm6J9p2+f/AGfaRwebtzt3bAM43NjPTJ9a3qSlrjlKU3zSd2dk YxguWKsjyr9k7/k1n4N/9iZo3/pDDRR+yd/yaz8G/wDsTNG/9IYaKko9Vrxj9rvXYPC/wXGtXSSS W2m+J/DN7KkIBdki12wkYKCQM4U4yRXs1eBft1zJb/s063LJBHdJHq+hO0ExYJIBrFmSrFSGwRwc EHngis6knGDkuh04aCqV4Qls2l+Jj6Hq2p/tSeKNDbV/DOp6J4E0u2g1cx3lugS8v942IHcHzrfy jIPlVc7juxlBX0rkIvJwBXzn8LPj54M+HPwZ8P2Wt+K7fVNWsdFju3t7SIGTYcCO2G35TKgKx7Sw bC72CjJFHxx8VLz9pTQW8F/DSCUx39qs2r6tfeZbR2EZORbkqCS7lSpxuUruA3AsyfO0cdhqMHNT 56sraK12+2nb/gnVmVbD/WXGC5aUZcq5bvr56t9dbaHuXjf4kaH4C8P6vquo3YaPTII557e3xJNi RykXyA8b3BUE4GQckAEjxXwz4V+MV7c+I/GmlR+H/Dup+LvLMun6sszTWEUUey3ZSAVMu1mLK64B VcgZZFzPF37HdhDq3hnSPCUN1puh3sEtr4l1NrhZZZIkaGWIbZG4Z5IusSgAnJG35TZ+JXgn4p/C HSbV/AXivUr3wjbzLF/ZEOmw3t7p8DEACIyAtOqksApIKqEGSAzLhinXrTc8RCSjDblet316XSTt 63+XZ/ZuBq1acqOL16KcGl215efV62W1tW72R02k/Er4y6B4Yi/tz4V/2ze2kBNxe2us28bT7QTu ECBzuIA+VM5OdoGQozPEGsfET9oGPW/DukaLJ4F8KOlvDc3niG1uLfUJkdiZTCqnYRhSpQnkNyw3 4WfwH4l+NPi7wnpuraTqPgbVtNuoQ0F5fJcx3EqjjMyREokuQQ6qSFYMB0r1f4d2/jGHTb5/Gtxp U2pS3ReCPRw4gih8uMBRvAYneJGOSfvdcYAqlRnibUZVJuDWt0tVbujDEJYWpJcseaL6X3v2Zkax 8A/BGraHp2nJo0emtpiKmn3+nsYLu0K7irJMPmJDuz/MWBc7iCea7bRdN/sbR7HT/tVxe/ZYEg+1 XknmTS7VC75Gx8zHGSe5Jq7Va31K1uri5ghuYpZrVxFPGjgtE5VXCsOx2urYPZge4r6Knh6NF3px S6HlynOa1dyzRRRXSZhRRSMcKTQB8y/tqxax4Dh8G/GjRZrOSbwBNcrNp95G5FxFfCO1LqVYfMhK nacAhidw24bT1H4T/GD4kLPZeL/HWn6T4evvku9M8P2ucxDy/kSWRQ43jzd2SwHAw6uVXzzw/a/E T9sDxjqemeNovDtn8J/DPiXUNG1nw9pd9eR3OoTQRfut0yqpljSV4nGDECQSyEqgH2UvAxXkqhHF SlN3UX0u1fvt0PoIY6pl8IwpqLmr6uKlZbq107NO7utVfcoaDoNl4Z0Wx0rT4fIsbKBLeCPcW2oi hVGSSTgAck5q9sX+6Pyp1FeoopKyPBlKUm5N6sTGOgpaKKokKKKKACiiigArN8Q+JNJ8I6Pcatrm p2ejaXb7fOvb+dIIY9zBV3O5CjLMAMnkkDvWlWb4i8N6T4u0e40nXNMs9Y0u42+dZX8CTwybWDLu RgVOGUEZHBAPak720GrX1LGm6laa1p9rf2F1De2N1Es8FzbyCSOWNgGV0YHDKQQQRwQa57wr8UvC vjfxR4m8PaFrEOp6t4bljg1WGBWK20kgbahfGxmBjcMFJKspVsEYrxibw38QP2a/E+uXvgnw5D4y +Et9Kt4PCemzeTqGhSEFrp7ON8rLExV3FujKTJKqxqgDM8H7B/iHSfFnw98WeIbTVLOTVfE3ibUP EV9ocM6STaR9omKRwy4O45W3LqzKm4NwvGTyKs3ONNqz1v8A8A7HQSpyqp3Wlvn3R9M0UUV2HEJS 1kL4s0hvFEvhv7fENcitEv2smJDmBnZBIM/eG5CDjOMrnG5c5X/CyNN/4Wj/AMIJ5F1/a39k/wBs +dtXyPJ87ytud27fu5xtxjv2rRU5y2XS/wAjJ1YR3fW3zOspD6VQ1zxBpnhnTZtR1fULXTLCHb5l 1eTLFEmWCjLMQBkkDnuRXmfxW/ad8D/DDQNRuRrFjres20ht00Wxu0e4acZGxwpJiAIO5mHy4xgs Qp2w+Fr4qap0YOTeisZVsVRw8XKrJJI43xV4u0/9lb4l3N7evt8B+Mp3vJYY2Wa5tNULqJpghIc2 7R4ZtvmFWAACBlVuj8F/tWeGfFniDRtKvNF8QeFjrcZfS7zX7Jba2vj8pCRSB2DFg6kdjkAHLKDy vg7wX8SfiT8YPCPxG8WaJ4f8N2WjSahbixi87+0vKYSwokrFSkoVvmVlIUrIzKPmxXuPjz4c+HPi ZoLaL4l0uLVNOMiyiNiyMjr0ZXUhlPUZUjIJHQkH3cS8FT9nTxC5p296UZJ2abSstpNJJt81ntpu eHho4yfPUoPlhf3YyW60b13Svfpp+BqaX4g0vWto0/UbW9LQR3S/Z5lkzDJu8uQYP3G2Ntbodpx0 NB8QaWNb/sY6jajVvI+1fYPOXz/J3bfM2Z3bN3y7sYzxXzD4m/Zs1f4LePdK8afBnSJtQfy7i2vN CudTCQgPBtiYGQgvGJB5jq0hJYJt2jlei8P/ALHmk654e1mX4k3p8V+MNanF3ca1CXhltX8rYscR 3YKoS5GUCkbAY8IoGVTA5fCKqrE3hJaLlXPe+qceaySWt763Vutt4YzHSk6XsPeT1d/dt0s7a39N Op9GUV8/SeKPiL8BdSTTtU0rXPip4Ql2i11jT7eN9SsuJAIJIkObjAjjJmbZy7EkkhQul/tMeK7i E2t/8F/F1rrk2z7Jb28Xm2b+YitH5tywQQ8th8qfLwd3IKjj/sytJc1JxlHvzJfg2mrdbrT0aOlZ lRj7tVOMu1n+aVvQ+gKK+e7j9srQPCdn9n8d+H9Y8JeJo5Jlk0VrdpyUQOUlimwqSRuyeWrD+M/3 AZKlk/bG8OarrX2bwj4c8S+OrCK38y7vtB0uST7NIzYjjZHCn5gshLHAG1QN2W2X/Y+PS5vZPl7/ AGf/AALb0116B/auC29or9uv3bnoHxG+PHgX4TX1pZeKdej028uozLFbrDLPJsBxuKxqxUE5AJxn a2M7TjttP1K11axt72yuYruzuI1lhuIXDpIjDKsrDgggggjrmvAPgj4Q8QfE3xR4h+JfxD0iTSpd TtJNBsPDV5bKEi07eGbzVcbnLPuHzhc/McbXQL0epfspeC2W/XQZtY8Hw6kXOo2+g6g0MN6GzhJI 2DLsUM4VFCqA7DGOnPmNKjhKbp0byqx3s04t9Unpa2zfvJvYvBVq+Jn7SaSpvbR8yXfzv8rHrt1f 21jEJbm4it42dIg0rhQXdgiLk92ZlUDuSB3qfcPWvHLP9kX4XWtnBDL4flu5I0VGuJr+4DyEDBZg rhcnqdoA54Aqtqn7LWleSI/D/izxT4Zhtt0mnWVnqbva2UpRlLojfNzvcthwTvcZANfL+2x8Vd0Y v0lr+KR73JQeim/mv+Cz2zcD0Io3D1rwix/ZXtvCMGi3vgnxFceE/E9nB5F5qkcJuY79SgD74JJC oywDAA4B7EhSvL+H/wBkfxNJ4b1OPWviRqlvq+oJ5ciWE0slqUMsjSLKGZWnD+a7YOzDSOTvyc4S xuPi1H6td+Ulb9NfkX7Gg1f2v4O/9fM+n9w9ahtL62v4jJbXEVxGrvEWicMA6MUdcjurKykdiCO1 eHah+y3Lq2rWsepfETxTrHhb5WvNE1O9eb7UysWAMgZQq5CcbCflOGBIK6Un7Kfg6xuorrw1d694 NulRo5JtD1SSN50YqdrtJvOAVBwMe+cDGqxGObv7BJLvLX5aW+9oh06CXx6+n/BPZDIi8FgPxoV1 bowP0NfLfw7+BnhLWvGHibw18QLe98R+MrGRLr+1r3UZ1OoWjqFjkjUOrYQKEfO8K3AcggL3uofs 7jwdazXXwq1eXwRq7oyzLIzXlteADKLIsxfYQ3SRQSoZ+G3VNHGYqpD2vsVbXRS97TyaSv8AM8aN arK8lC69dfusl+J7Df39vpdnPeXk8drawI0ss0zhURAMlmJ4AABJJrwSHWfF37R+pXL+HdXvPBvw 5t38ldSt49l7q7rIpcxMcNEg2lQw7khg2WRLlx8G/H3xMlWP4j+LbQaB9qSaXw5oEDJBOiKNoadt sgBfLFTu6AgqdpX2+wsLbS7KCzs4I7a1gRYooYUCoiAYCqBwAAMYFVy1sdK004U106y+56L8X+at UxDtJOMfxf3bI5X4Z/Cfw98J9KksdAhuI0m2Gdp7mSXzZFXHmbSdqs3fYqg4HGAAPM/j5pXiP4e+ Irb4j+Eb6PTbXZHB4kjbySk8CODHIYpCglkwWj4kEhzGiEZJr36oL2zt9Ss57S7gjubWdGilgmQO kiMMMrKeCCCQQfWtsRgadTD+xpe7ba2ln/W56WHlHDtKMVbt0INF1i08QaPY6nYTfaLK9gS4gl2l d8bqGVsEAjII4IzV6vEvGHgW7+DNjqXjPwVf6i1np+66uPCM1yP7Ma2J3XAhQ48hh80oZScEFQpD ba9g0XWLTxBo9jqlhL59jewJcwS7Su+N1DKcEAjII4IzWuHryk3Sqq019z80XOCS5ou6LtFFFdxi FFFFABRRRQA2Rd0bDGcivAv2Y9ah+HmiQfCTxGv9leLNEMjotxIixanHLNcSrLaHdulQIpLHaCpy CAQQPf64b4l/BXwh8WNOurfxBo1tPdzQfZ01OOJFvIFBLL5cuCy4Yk45U5IIIJB9HDV6apyw9a/J Jp3W6avZ9L6N6aep5+Io1HONej8Ubqz2adtPwWp3GffNLXz9rEfiz9mTTpdZtr3XPiV4L4fU4NWu xNqWm4YbriGTaPMi2Z3RHG0qGDBTIR7joWvab4m0uHUtIv7bU7CfPl3VnMssT4JU4ZSQcEEfUGsq 2GdKKqRfNB7P9Gt0/X5GlHEqpJ05Llmt1/l3NCiiiuM7D5/+MOl6l8FfF+pfF/w5BbXllNY+T4k0 m+1NrZbrYY0tpYcqUEq8rg9V+VF3uSfafCPiS38ZeFtI16zjlitNTtIryGOcASKkiB1DAEgHDDOC frXPfGz4dn4rfC3xB4XSb7PPfQA28hbaomRlki3Ha3yb0XdgE7c45rG+GnxU1TVvE134J8ZaLFoH jGzs1vVSzn+0Wt/ah/KNzEw5jBkB/dyfMAy9fm2+zUaxWDjK16kLp668iS5dOttVpsrX0tbxof7L i5RvaE9u3Nrf0vp6s9Rr5z/bU0W88T+F/BWgRXdraWWteJbTTJ5JbITyxtIHCSIxYbNuGyBhmDY3 KNwb6MrJ8VeFdK8beH73Q9bso9R0u8j8ua3lHDDqCCOQQQCGBBBAIIIBrlwOJ+p4mFf+V+T/AAem h143D/WsPOj3NSPHlrg54pa+ZtY0XxZ+yjbR+JLfxTdeLPhnp0ENjdaFqhH2y0hMqpG1vIoCu4eZ +G2Dy1RMnajJ9MIwdQw7ilicMqKjUhJShK9mrrVWumns1dX6a6NhhsT7VunOPLOO6/Jp9h1FFFcJ 3HG/E/4teGfhHoMuqeItRjtv3bPb2aspuLsrgFIoyQXOWUHsNwLEDJrz74M/Du88W2/jLxf8QPDt rbXnjae2lfw9dKJ4re1t0C2yyo6/63qzZ7hflQgqML4zS+FvC37TXw717XJdNkS7sZ7K8GpqsosV jcSWlxGMZiczMy+a3AUNjbhmr6Isb621GzgurSeK5tZ0WSKaFw6SIRlWUjgggggj1rvjjsNSpOhh pXqStzu+qs7qKXqk2/S1tb+Y8LWr1vaYiNoR+Fd9LN/i1954Q/7JzaDp9zb+CviP4u8KqfNFpZi+ +0WNoshbeqwEKejvtbfuViH3Fhmrf/GQnh//AKEnxRZWf/Xza32oRp/5BilkA/3FZvQV7pRWrzGt U/jJT9Ur/fo/xF/Z1KP8FuHo9Pu2/A8O8MfHfxVo+taFpHxP8D/8IZ/auyztNVt70XkF1fFkVYQk Sv5O/c7L5j9EIycEj3CvEP2wIxp3wlj8UxHOoeFtXsNYso25ikmWdYwsg6lMStwCpyBz6+3RnMan 2p4uNOpRp4qnBQUnJNK9rxs9LtvaS6hhZVIVZ4epLm5Umm7Xs772st12HUUUV5R6gUUUUAFFFFAC bRnOBmloooAwI/APhmHWoNYj8P6WmrW/meTfLZxiePzGdpNr7dw3NLITg8mRifvGtXUNNtNUsbiy vbWG7s7iNopoJow6SIwwysp4IIJBB65q1RVupKTTb2M1ThFNKK1PnjwP4msvg/8AtBeIfh1JNHpH hbVbWHVtDtbqeOKG3nkk8uSC2UsSRLIWYJ8m1kcLHg7j9DZ79q5T4ifC/wAOfFDRZ9P17TLa8Zre aCC7kgjee08xdrPC7q2x+FII7qvpXnPwO+K+o2epL8MPiBH/AGd470qBVt7iSVpItat1BC3EUjcu 5CksDySGOAQ6x+tWisdT9vTXvxS5l3tpzef97z16nlUZPBVPYVH7km+V9v7v+X3HuVFJ1pa8Y9k8 q/ZO/wCTWfg3/wBiZo3/AKQw0Ufsnf8AJrPwb/7EzRv/AEhhooA9VryP9qKzt9R+F2n2l3BHc2tx 4v8ACsM0EyB0kRvEGnqysp4IIJBB65r1yvGP2utcg8L/AAXTWbpJJLbTvFHhm8lSEAuyx69YOQoJ AzheMkVMmkm5bDTad0c1cfsV+Hb3xHr9zNqckei6lJ58Gn2lrHDLYybw37qXkBADIvl7Nu1lzlkV q7/4D+DdW+Gvh3UPCV/a/wDEs0u+l/snUBIjfarSVzKu/B3CVWZg2URem3dyazPBfxO+Ivi3xTpF pffDWTw1o0i/aL3ULq/WUpE0UpjVU2oRIZFQMvLKD8yruBr2CvEwODwSl9YwsHHfo1f7+lwo2o0H Gn8NR8z73Tau+qer0fR37BWL4z8UWHgrwrqmuao+yxsYGmkGVDPgcIu4gFmOFUZGSQO9bVJ9ea9q acotRdmC0d2fL/wc+Auq6r4Mt/Fq+KtY8Jaxqga/s9O0eVV0+0iaR5bePyCWEkWZGk8ssBiUqQDu J67w7+1Joukaclj8R4LjwZ4rgJS5sZbKeSOXBK+dCyKwaJirYOTyCMsAGb3Kk2L/AHR+VeVRwEsL TUcNOz631T87XX4Haq1KTqSqwu5O976r87p/pvvepo+tWHiDTob/AEu9t9RsZs+Xc2sqyxvglThl JBwQR9Qa8/8AHvwSh8T68/iLQ9e1Xwh4iZF8y60qYLFdug/cm5hI2zBORg4ypKk4xj0DR9GsPD+n xWGl2Nvp1jDny7a0iWKNMkscKoAGSSfqTV2vRdP2kFGqtf18jGjXnh589J2/y81szwu4/aNu/h9B /ZnxC8MXun+JGdIrC30ZTeRaxlgjPbnjad3PlSEMFZPvFsVi+IP2mL/WNd0ybwFZJq8OmWl1L4k0 LVpU0ye0x5exmebGDGwkDlN6jJDdUavoxo1b7yg/UV578UPgT4X+K2yfUobix1WOFraLVNOmMNwk TffjzgqyspdcOGADvjG4muGtRxXI1Tqfo/v1X4bfee9g8XliqqWIoW3vq3HVW+HR29J3T11Xum18 N/iVofxT8L22uaHc+dbS/LJE+BLBIAN0ci54YZHsQQQSCCfmj9tT9pCy8J+JvC/w+j1rVNF0+8vY pvEut+G9VihvtNtflATaiSzRnMsUxJRN6KEQt5j7J/i1+zzrHwb8ReH/AIifB+WPSrXQ8y67o95q gghv7QOhkDTT7lRBF5zOzthdiMq71Br5n8A/GX4dal8bLb4geMvCnh+fTPFmlhfEmlTfZp49OvBc xxG+hgZTujlZVkaElrgZnlIZAjy8lXFVowVGtaM9LvpbujojgsFKu6+FbnSs7J2Uk9bJpN/J9T9F vgn8GvD/AMB/ANp4U8OCZ7KGWSd7q6EZuLiR2LF5WREDsBtQHGdqIO1d5TVYEcUv6V7sIqMUo7Hy cpOcnKT1YtFFFWSFFFFABXmPxutfi5fWFnb/AAqu/C2nyzRXEd7d+IhOZYWIUQvbiNWUsv7wnzFY ZCcEZFenUVEo8ytcuMuWXNa58u6j8Q/HX7KupXOsfF/x/D458BXtiyWd7b6HHaXsWqIS6WiRQ/KV liEpDudoaLBaLgyeieAP2qPAHjq//si51Cbwd4qWWKCTwz4si/s3UVklJEKCOQ4kZxtYCNmOJEzg sBXruAeozXF+PPgv4E+J3mv4p8I6PrlxJbGz+2XdmjXKQnd8sc2PMjwXYgqwKkkgg81z+zqU/gld ef8AmdHtKVT+JGz7qy/CxZ+KXxL0X4Q/D/WfGGvyTLpWlxB5BbR+ZI7MwRERf7zOyqMkAFskgZI+ ePBPj79q6Twzoupah4D8LaqdSlk1B7ea5axu7O1UySfZJUZsJLKGijhb5/L2fvwWLMul4u/Ypuxo c3h74c/E7XvAPhS4lhnk0GVTqVvbSQypNC9m8kiy2zCZWlYrIS7MOgUCvqBRtUCo5atWfvXil26/ 16GnNSpQ920m31voun9Js+eF/bf8B+GAdP8AiRbax8NPFEXyzaPq+mzz78fK0sE0COk0BcSKsoxu 8snaBjPmPhTw/wDH/wCJXijQvjP4a0X4ZeEJtUsZilrdLcNdX9hcCIwLfSxo3msqQQOjIyEdCFBa Mfau0HqB+VFVKhObXPLRdtCY14U1+7hq976/cv8Ahzx3wz8ctS0PxZpfgn4naNb+GvE9+iix1TTr gz6RqjBI9whkdVeOQyM6+TIuRtX528xN3qV34i0uw1Ow0651G0t9Qv8AzPslrLOqy3Gwbn8tSctt BycdB1rM8e/Dvw78TtBbRvE2mR6pp5kWURuzIyOvRldSGU9RlSMgkdCQfNv+GL/g9/0KTf8Agzu/ /jtfQUY5fKnH205xkt7RUk+z1lG3mrP1108CtLHRqP2UYuL2u2reWz+/8Dn/ANsKbwPceG7RdQur lviBa4Phi30e4b+0FupXXy3SJTyheFQWI42kIQ5UHzmw0/4+/ELx1pPj2x8PW/g+fUbGPw/PcSRo Z7C2SeOSW6NvcMCdz+btUgnYpGM7JG950L9lP4WeG721vNP8KpDd2t3DfQTteXDvHNESUIZpCcZO Sv3Wwu4HaMesgBRgcCvYjm1DB0Y0cND2lr61FtfdKKk1a+ut9fVnkyyuti60quIlyXtpB726t2Tv 00sfPU37IMHiyO2fx58QPFXi+Vbs3k9q92ILCR9zHC2+G8obWK/I4wCdu0EAem+C/gf4C+HzWcmg +FdNsrq03+TemAS3S7t279++ZDkMw5bocdOK7mivFrZli68PZzqPl7LSP3Ky/A9ell+Foy54wXN3 er+96hRRRXmnohRRRQAnXrRtHoKWigBpjVuqg/hR5ajooH4U6imLlXYSloopDCiiigAooooAK8g+ Inxe16LxwngXwHpFnrPiX7Mt3dXV7dKttYRmRFzIgIZjtbJUEEBkID5xXpXijxJpvhHw/e6xq95H Y6daxl5biTOFHQDA5JJIAA5JIABJrzj9mPwLN4R+Gtre6tp0ln4o1eSS81Sa6Ja5mZpHMZkJJIOw qdp6FmyAxavLxUqlSrHDUpct9W1ukunq/wBGcdaU5TVKDtfVvy/4P+ZJ8IPhTrfhnxN4j8YeLr/T 9S8T675ayCxtisdoiFgI45G+ZlKiLIIBzGMliN1er0tFdeHw8MNT9nT2/V6tm9KnGjHliFFFFdJq FFFFACEZUjrXifwH1ix8K+IfG3ga+vbfT9Ut/EN1cabozSqu2ylRZohAgO3bt3uUT7uSWAzXtteP fHT/AIkfjL4VeJIPmvoPEK6SscnMZivI2jlYgYO4BBtOcAk5Brysdem4YmP2Xr6PR/5nTRtK9N9f zR7DRSClr1TmCiiigAooooAKKKKAEZQykHoa8N+HbH4DeMNQ8Ha0fI8OeIdWmvPDWop8lnC8p3HT dnSB1IZowPll3Ntw2Vr3OsnxV4V0nxt4fvdE1uyj1HS7yPy5reUcMOoII5BBAIYEEEAgggGuuhWU E6dT4Zb/AKNea/HbzOSvRc2qlP4o7f5M1cg0teDWnw9+L/wvhM3h/wAbx/EDTbeRymg+JIBFcNAX L7VvQSzT9EUyARjeSQAoFX9H/aQ/sbxBaaF8TPDUvw21G+jkms7i9vobiwmRMZX7SpCrJy3ysMAB ecuoPTLL5yvLDzVRLs9f/AXaWnWyaXc5o4+MbRrxcH57ferr73c9przH4lfBeTxZ4mtPF/h3xJfe EPGNnaNYx6jbotxDLAX3GOa3f5ZAMuRyMMwY52qB6aGDdDmlI3AiuKjWnh589N2f3/Jp6NeTOytR hiIck9v66nnX7PfxD1L4q/CLQvFGrxW0GoXxnEsdmrLENk8kYwGZj0QZ565r0avmrUrfxP8Asv8A iiG50+5stQ+Eusa1Ek9ldBon0A3DvvaN1URx2yuVPzcchQFLGRvpRWDKCO9duYUYRqutRt7Obbjb p/d9Vez/AAOTA1pSp+xq354WTv18/RlfUNPtdWsbiyvbeK7s7iNopreZA6SIwwysp4IIJBB65rxH 9ny3l8H/ABG+Jnw9srqV/CnhmSxfSbOYKxtRdJLcSoHChnG9sDeWIAHJ5J93rwf4o3a/Af4kW3xI iWZfDGvyRaf4sCRNOYyiFbS7UAZQKcxv82CGUBGc5q8A3VhVwq1c17q/vJp/e480V626kY5KnOni dlF6v+601917N+lz3iiua8FfEjwx8RbM3PhvXbHWI1jjkkW1mVpIQ4JTzE+9GTg/KwB4Ixwa6WvL nTnTk4TVmujPSp1IVIqcHdM5++8B6DqXiKfXbvTY7rUp9ObSpZJmZ0ktWfe0TRk7CCxOcjJzjOOK 8+1j4Cw+FZpdc+GUp8MeIfPE72bXUg0y9y43JcQ4b5QjShBGF2l+MYBHsNFefVwdCqtY2fdbp90z qjVnDZ6HBfCz4lf8Jlp507Wkt9I8a2O+PVNDEn7yFkIHmKp5MTBo2VhuXEgG5sZrvagSxt47yW7W CNbqVFikmCAO6KWKqW6kAu5A7bm9TU9bUYzpwUakrtdf66kSak7xVjC8ceDdO+IXhHVfDurR+ZYa jA0EmFUsmRw67gQHU4ZSQcMoPapvCOi3Ph3wvpGl3moy6vd2VpFbTahNnfcuiBWlbJJyxBY5J69T WvRXX7SXJ7O+m5h7OPP7S2uwUUUVmaBRRRQAUUUUAFFFFABRRRQAVynxM+GWg/FjwndeH/EFr59p N8ySpgS28gBCyxtg7XGTzyCCQQVJB6uitKdSdKanTdmtmZ1KcasXCaumfP8AY+NNT/Zu1S90nxtd 67rvgKTZLpXiq5ia/ls8jE0V9KgDDMpQRfIciTG7C4T3jT9QttWsbe9sriK7s7iNZYbiBw6SIwyr Kw4IIIII65qZ1EikEZyK8X+BNndfCrWNR+FF5BKdO01H1Hw9qkiEG/s5Jd0yuRlBJDLMqHlSwdGC KOT6FR08XSlVStUja/aS2bt3Ttfe927KzPPpqeEqRpN3pyvbun29O3a1upq/snf8ms/Bv/sTNG/9 IYaKP2Tv+TWfg3/2Jmjf+kMNFeWeoeq149+1d9v/AOFR239lfZ/7U/4Szwv9k+2bvJ87+39P2eZt 527sZxzjOK9hrxb9r/xBb+Evgmdcu0lltdL8TeGb6ZIQC7JFrthIwUEgEkKcZI5701B1HyR3YnJR XM+hN/b3xr8O5udQ8NeFfFEDfILTRL+WzmQ9fMZ7gFSoAIwOcsD0BqRv2pvAUmsLaWl9dX9lFN5F 9q9vaObHT2LbYzNMQFCyNlVddynGSQOa42y8CfED9oi6udV8c3Wr/Djwq1oILHwzpN8BPcCRVMkl 223BBHy+W6AjkFVwxk9c1L4P+F9Q+GsvgVdP+xeH3gEKw2rFGjwwdXDc5YOA2WzuOd27JzxYnA4n AzdOlVU9L6u9n2uvxd2uiO/AYrA4ij7XEU5Jt2Vvd93+Z3v8lp3fYydC/aD8I+J/iCnhPSLqXU52 QY1K0j82yMpR5BD5ykjeY45H/u4Rhu3ArXpdct8Ofh7pnw38M22lafBbJIP3t1cW9usAuLhgPMl2 Dhdx6KOFAVRhVAHU1pQ9ryXrbvt08icU8O6n+ypqK7u7fnsrX7dO4UUUV0HGFcR8TNa8cabFp9t4 J8PWer3V25Wa+1C6EcFiAyYZ48h5AVL/AHDkbc4boe3pKxrU3Vg4KTjfqty4y5Xdq5574J+KyX2t p4R8URR6H45iRmexXd9nvEUf6+1kIw8bDJCk712uCPkJr0KvNP2gPBOk+Kvh7qGoXsn9n6locEuo 6fq8bOkllLGu8OGRWbblBuCgkgAgblUg+Hfxs0fxB8J/D/i7X9QstBXUF8mRryZLeI3CFkkVNzng tG5UEk7Rz3rio1Z0qjoV2nZXT7rz81+J2/VZ1aP1ilF2vyv1d2reqTKv7SvxQ8F/Df4T+I/+EyuL OaDUNMuoIdDmvDBNquU2NBFszJ8xkRWdAfLD7jgDNeH/AAD/AGPZ9Q/Z8Hgr4n6VpQiku7fV9PvN JZo76LIZxFcq8C5eMyyr8xk4mdcLsBO9ofhnwr+0h+01feNjolt4q8Eab4WTRFl1jTEktnvftXnh o1mGdwjdlJ2AjJzgMu76nrOMKePl7V6xV0vPuzOclTpqlF6vV+T/AM1rc+Xvg7rmt6R8ftc8MReK L+fRLM/Zbmx8ZagZb+7cJKyzWa7RhcqCecGNgxySoT6h3DGe1eafFL4E6b8WNZ0nUtR1vWdOl0kE 2aaXLFEIpCysZAxjL7vkT+LA2DAByT5TcfFD4rfBnTbO88VeHW1DwTb3klm1xcSxzasttnEMkzxS GLcQwXP8TIQxUurtwUqs8pUoV03C7aktbLzXRL/gnkQUsPG09Y9/V9V5dz2Lwh8U5fHHjnXNK0rR pJfD+kPJZ3GuvOqg30ZTfbrCfnIAf/WcAlSBkYJ9Arwj9j3T2/4V1quuLaW+nWWv61d6laWFuci1 hLCMRfdUDaYmAwMY29Og93r2sHUdajGq3fm1PczCnSo4iVKjtHTve273a37adgooorsPOCiiigAo oooAKKKKACiiigAooooASiuO0n4weENa8ZX/AITt9Zjj8SWMnlS6bdxvbTM21m/drIq+aNqltybh tw2cEE9j1rSdOdJpTi1fXXs9jOFSFS7g72FooorM0CiiigAooooAKKKKACiiigAooooAKKKKACkp ao65rNp4d0e+1S/l8ixsoHuJ5dpbZGilmOACTgA8AZpSkoq72E3ZXZ4t+09qUPiJfCvw8t72Q3ni DVrYX1jaIHn+wKxMkv3W2BWVW3H+43UK9e6oNqKPavFfg+urfEbx5qXxO1DSY9G0q6sE0zRYJw5u 5LYSGTznw2xQ5OQNpJAXBAG6X2uvKwSdWU8U/tbf4Vt9+r+ZyYf33Kt/Nt6IWiiivWOwKKKKACii igArzz41eAdW8d6HoraFdWdtq+i6vbavbLqCuYJWi3fI5T5gPmzwDnbjjOR6HVHXNR/sfRr6/wDs txe/ZYJJvstnH5k0u1Sdka/xMcYA7kiubE041aMoT2NKcnGSaMP4XePIPid4D0nxLb2slkl8jZt5 WDGN0dkcZHUblbB4yMHA6Dqa8n/ZVtXs/gL4Wjdo2Zknk/dSrIMNcSsOVJGcEZHUHIIBBFes1lga kquFp1J7tK/3F14qFWUY7JsKKKK7jAKKKKACiiigAooooAKyPEnhHRPGVklnr2kWOs2kcglSG/tk nRXAIDBXBAOGIz7mtekqoycXeLsyZRjNcsldHhp/Z78QeCCb34e/ELXLCaDi30XX7g3+l+QvK2qo w3xJlUTzFJdUDAZJzVjRde+NniTxNpOl6j4a0jwhpFpIH1TXY7tb0X6xuhKWsWQ0Qlw4/eAlUfOQ 6gN7XRXofXpyT9rCMn0bWq+61/8At655/wBRhFr2UnFdk9H9+3ysZHivwrpXjbw7faHrllHqGl3k flz28o4YdQQRyCCAQwIIIBBBANeA/Av9oTwv4Q+C/hiLxp4xN1r0huvOaZpry54uZNvm7Q7L8hTG /GR0yBX0pXhvgfw7pngf9p7xhYWtlHI/iDSI9cS4YfPanzyk0QJySJJD5hwVA2qNpwCPnMdisZSj To0JJQlLW6vZ20a29H30vsevRoUJTlVmnzJdNLq+36/f3J/hV8TvHfxI8UQ69HoNvH8N9U86C0Zp 0F1a+TuAnkGfm819ybBnbsB4A3S+x6jp9tq1hcWV7bxXdpcRtFNbzoHSRGGGVlPBBBIIPXNWAMdK WtsLRqYeFp1HJ73f6eQq0o1XpGy7HgPwG/Zxn+G/xG8UeNdRj03SrjU/Mt7PRNCeSSztbdnRzlpF Vi5ZF4VVRcNgYYKnv1JS16+KxdbG1Pa13d2S+SVkcGFwtLCU/Z0lZav7wooorjOsKKKKACiiigAo oooAKKKKACiiigAooooAKKKKACiiigApKWigDyr9k7/k1n4N/wDYmaN/6Qw0Ufsnf8ms/Bv/ALEz Rv8A0hhooA9Vrx39rBdPb4Q241YWx0o+K/C4uxebfIMP9v6f5nmbvl2bc5zxjOa9iryT9qKzg1H4 XafaXUEdzaz+L/CsUsMyB0kRvEGnhlZTwQQSCD1zSu1rHcNOp6pY3ttqNnBdWk8dzazIskU0Lh0k RhlWVhwQQQQR1qeuV+Hvw00L4X6ffaf4egktbC6ujdm3klaQRuY40IUtlsHyweSeSe2AOqrOm5uC dRWfkVLlT93YKKKK1JCkpawfGnjjRvh7ojaxr1zJZ6arrG9xHbSzBC3A3CNWKgnjJwMkDOSMxOca cXKbskNJydlub1c14u8eWHgrUPD9vqUNwsOtXq6dDdxqrRR3DAmNHG7d85BAKqQCPmKjmuR8f/EK 78I+LfAWrWupx33hHxBdLpM1tEqSBpZlLW1xC4AOMghiXK7SCqE813/iXw7pfi7QbzSdYtIr7Tby PZNBL0YdQc9QQQCCMEEAggiuSVZ1YzVHSUe+z6/czb2bgozmtGcx8Tvi/oPwt/sqLWBdyyam0ojS ztzMY4ol3TTuB/yzjUhmxlschTg48H/Zx+B9j8SLWH4k+KZrfWbfVri/u08PzWrG1trmSco8qhpC rZWLGGU/w8koDVG38Sa9qXxM+F3gbUTI/wARfC+ozi+1y6mV4ZbJo2dkjwG8wy2wT53VXDKM4LMw +v0UKoAGPpXkYdwzWq603eMHZLs7Ju/drtsep9Yhg8O6WHk/aSau07WtzKy7qSkne/lYh0/T7bSr KCzs7eO1tLeNYooYUCJGijCqoHAAAAAHSrFFJX0iSSsjxd9WLVfULG21KxntLyCO5tZo2jlhmQOk iEYKsDwQQSCDViuc8d/EDw/8N9BfV/EWpR6bYb1iEjKzs7t0VVUFmPU4APAJ6AmoqSjGDc9vMunS nWmqdOLlJ6JLVs8P/Zz1rwvF8bvijpvh28gmsbn7LPYraW6xwmOIMsuzy0VNqvKqg9WBDZflj9Ie Yi8FlB+tfA3wfkN0um2Xw98FTS+Pgl1NbeLNUu2gijs2l8gXX2cu0bECSSMou8KY8jzDuUfROjfs t2V7qdtrHjfxTrvjPV4HeaJpryS1gtpWkDh4EjYNERtUYV9vGQBhQvy2S4itLDcqgnq3pdJXd7ar dX6XXmduHyylhaF8XW5XeXupXknd3TV7JJ6ayT6pNHuX40teM+MPH091+0P4B8JaLqUssVql5d67 ZWoJWNTbkW5mYDgbmJCk9WjJGShr2WvpqdaNVyUfsu34J/qZYjCzw0acp/bjzL0u1r62uvJoWikB z05pa3OMKKKKACiiigAooooAKKKRm2qT6DNAHGfEr4T+HPilY2ket28iXli5msNSs5mgurKYjAki kXkEEK2DlSUUkHaK8y0fxtqX7NrXWjePbzXPEXhB7h7jTfGUkbXn2WFsf6PelQXVxIQqvhg/mgDY EKrgaaviT9sSSwvNSs5fDHwfjkaZbRLtWutdeOZ1VZdhzFGpjyyev3Sx2vHv6x4Y1P8AZoa01bwv cXN78Mo7hF1Tw1MjXH9lQvnzr6GYlptiEK7QgOPnlb5c5T6qNBUY/UsRPml/J2fZT1tPys466u+i +XnWdWX1uhDlj/N383HS8fO9+2h6d4L+MXgv4iXxsvDniKy1W8FpHfG3gf8AeLC5IBKnkEEYZT8y bl3Ablz2dfJt7rnw2+K01z4j8A6lY/Dn4g6ZJdX2mazqNnDaLqUZWVZrhlcETwsEnzIQXiKMxUcq 3pnwT+NkXijWL/wZq2taZr3iHS4PtMes6PKklrqlruCifCEiGUEqHiJ6kMmVPHFistdOLnSTXL8U ZL3l57Wa/HfSyudeFzJSkoVmnfaS2f43T/DzPZqKwvB/jnQPH2my6h4d1W21eziuJLV5rVwyrIhw y/yIPQqysMqwJ3a8SUZU5OM1Zo9uMozSlF3QUUUVJQUUUUAFFFFABRRRQAVXvr630uxnvLueO1tb dGllmmcKkaAZLMTwAAMkmrFeP/tbf8kA8Tf71r/6VRVy4qs8PQnWSvypv7kY1qnsqUqnZNmJN+0z q91YX/iPR/h7qGreA7Oco+vLdrHJJEpAkmjt2Xcyqd3OcYU7imGCyfGr47eDr74L+IX0fXtM1a71 CwNvDYx3iLOROBGW8s/OCiuWKlQflIOOo9t07T7bT9Nt7O1t47a1hiWOKCJAqIgAAVQOAABgAVzd n8I/BGnXkF3a+EdDt7mB1limi06FXjcHIZSFyCCAQR0rzJYfGypuPtU+Za3W3pbp639TklSxDi48 97rtt6f8EufDvQbjwr4D8O6NdvG91Yafb2srQklC6RqpKkgHGQcZAroqSlr2acFTgoLod8Y8qUV0 CiiitCgooooAKKKKACiiigDwz4lS6n8B/Ek/j3RreO48GXzp/wAJHo8RCOk7PtF7CCdvmNuRWUY3 YBbJJdPclbcAa4P486d/anwa8ZQ/abi026ZPP5lrJsY+Whk2E4+623aw7qzDvWl8J7hLr4XeEJo7 eO0jk0i0ZbeEsUjBhQhVLEtgdBuJPHJPWvIoJ0MXOin7rXMl2d9bfgdU2p0oye60/wAjq6KKK9c5 QooooAKKKKACiiigAooooAKKKKACuO8XfD7/AISTxl4Q8SQX/wBivvD087LHJD5sc8U0flyoQGUq 2ANrZIBzlW7djRWVSlCtHlmrrR/dqioycXdBRRRWpIUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUU UUAFFFFABRRRQAUUUUAFFFFAHlX7J3/JrPwb/wCxM0b/ANIYaKP2Tv8Ak1n4N/8AYmaN/wCkMNFA HqteVftLf8k60j/sc/Cf/qQ6dXqteU/tLf8AJOdIP/U5+E//AFIdOoA9WpKgsNQttUsoLyzuI7q0 nRZYp4XDpIhGVZWHBBBBBHWp856c0h7C0UUUxBXJ/EvxRb+F/Dhku/DmqeKbW7f7JLp+k2Iu3KMj ZLxkgeXgFTn+8B3rq6PwrKrF1IOKdrlRaTTZ8Vf8Je114G1Xw1qvhzxjplxoOqtq/hu+uNOdo9Ct lLfY2uS25zEmyYHcsnyKwXJQBe9+JHjC3+K37Jlp4vv2uLbyzBcT2UAKw3U6TeS0MiiQMYGkyeHD ABG5Zdp+lyi88D8q+HviJ4Vjk/aB8Q/D8jxJp+j+JryO6todMuXa28+WIPJdSW7giZBKpZiGTYIn wflAHx2OpVcvocjlzqp7iVrau9v8jXH4qOIw06HI7yfu9VG6fNfrZuz8redz3j4c/s76ZofiPw94 ynu9ct9WsrXbDo97qCXcFgjxMv2ZH2bikfmMFw3bPPOfa6+eNQ8CfHfwrp8KaL49sPEcGmwCWKO9 sEiuL51KD7NITn5disRJvDlnIYgYdat9+1B4h1fR7DRNE8F3GnfE2/nKw+H9aV4kECq7m4DuIw6l YyuCUO7PUL83r4erh8DBw9m4N67bvbS2lz1qWSVakIvC1I1F1s37tuslJRajZb2sutj3LUPHeg6X 4s0vwzc6jGmvamkklrYqrM7oilmY4BCDCtgsRnawGSDWtqV1LZafc3ENtJeSxRs628JUPKQCQqli FyegyQOeSOtebfBj4V33hGfW/Enil7O/8a65cvLdXdqZHSCHI2W8TSHdsG0HGB/CpyEU1D+0V8Tr 74f+ErWx8PtG/i7XrqPTtJhbYT5jsAz7XYDCggZOQGePcME13Qr1I0ZVsQuXsutunz/4Y5KWE9vi o4ai7tu1+nm/Rd+2phfAj4vX3jOXxBqXi3xJpVhPdXSxWXhMNHHcaSiS+QRKWxI0kkjIMMOpXbjf sW9H+zzcXvjTS9Q1nxlqmu+GNHumv9L0K8Ys0E5YMrSXBYvMEO7aHyQCF3Ebg3P6F+zh8LNNY+F/ E2oW3iTxLqV7NqkZ1C8WHUpVbdgAoyyOoVGLckMyu+B0X3/T7C20qxt7OzgjtbS3jWKGGFQqRoow qqBwAAAAB6U406uIS+tJO1ttL27pJLp83q9TvxGIw+DqzllsmlK+jS0T/lbbfVq+jS0ucL8T/heP Fi2Gs6I9vpfi7SJo7nT9QaPHmbN3+jTMuH8hw7hlU/xZweQeJ2fHjUre+8QiXRNFkgjY2XhGSNbg XHzOMTThhtfaVKlH2sQu4J81e70VNXAwqScoycb9nbXv/XzPlpUVKfOm1/X9fqfGPww+M2neA/DW t3GzWPE/xp1+eYX2ntYzSyRzRecIVZMIBGiqNyoSy7iMAKAvV698TPiR8SfFGifD/QZrDQL7UPD9 tqGu3ixut1pTv/rlVS+UYBowqEbx5gO5fvr3Pi34O+M/+FnX/iLwX4xi8O2mupF/a63FlHcujwx7 ITErLggg4ILLjk5bIUY+j/sq3+n65qXief4ja03jK7kaQarZxpBEfulEkhO7zEDKP3e5VKhVAAFf Pwp4+EfYcjaTs2rK673ve767H0dPO48zq1cM5VUvibTi3ok0tEopbRs1fRux6/4Tg0fwfp2leD7b Uo5brTdOiEdrNMhuWt4wIxKyDBxkYLAAZ4p3gv4g+H/iJaXt14d1FNTtrO6ezmmiVgnmqASFYgBh hlIZcqc8E14xefBj4qaD4jv/ABFo/jHR/EfiHUrE6fJqWtWcts1jCCCogjiZ4+WG47kwCucHc+fW vhP8PIPhX8P9J8MW93JfJYq265kUKZHd2dzgdBuY4GTgYGT1Pu4WtiKkuWdLkSvv+Gz+84E6FShK rOT9o2tPk3JvpvZKz7nX0UUV6pxhRRRQAUlLRQB43r118UvhnrV/rQk/4WZ4Zup5JG0e1tYrO+0m AMXUwkH/AErCblKHDswj29WrnLv4mfGr4jWHkeEvh1H4NtrySaOLXPE14u+KIB1VmtAvmRyEhSMr IvqGU7q+hqPwr1aeOhFXlQjKXd3X4JqLfqteqZ5U8FOTtGtJR7afm03+Pocf8IfhxB8Jfh1o3hS2 vJNQj09H3XMqhTI7u0jkKPujc7YGTgYBJPJ7A4PGM0tFefVqzrVJVajvKTu35s9CnTjSgqcFZJWR ynj74V+FPihpqWPifQ7XVYY8+U0gKSxZKk+XIpDpkoudpGQMHI4rlvEX7Lnwr8UfZ/tngvToPI3b P7OVrLO7Gd3kFN/QY3ZxzjGTXqlFb0sbiqCSpVZRttZtWvv95jUweHrNupTTv3SPnP4hfA/X/hi0 Hir4LzW+hzWFisGoeHTB5kGqQQ7pE4ClpLgnKbid7B+HQ53e1/D7xdF488E6J4giWOIajaR3DwxT CYQuVG+LeAMlG3KeByp4HSugrw3wZps/gn9p7xPoljfSf2FrmkHxC+nnJSK6adYncFiTliHY4wPn UYwi44sfmdaToxqxUle3N9rXa76r11XoaYXA0qLnKm2tL26fJdPyPc6KKKZuFFFFABRRRQAUUUUA FeP/ALW3/Jv/AIm/3rX/ANKoq9f+lY3jLwnYeOvC+p6Dqab7K/haF8KpZc9HXcCAynDKcHBAPauP GUXXw9SlHeSa+9GFem6tKUF1TRrxf6pPoKfXhy+IfjD4N0f/AIR+18D2/iyexh+z2/iNtYjiW6wu I5ZIZG37sbd438sGw2CDU1n8YvGvgv7OvxG8Fpp2mtdLZv4i0u8jktAzy7Y5HjZt0MODy7t1x8oL ADljmFKNozjJd7xdl87W+exisVBaSTXydvv/AKR7XRXl+t/tNfDLw/dJb3Xiy1lkZBIGsUkukwSR gvErKDweCc9OORXd+H/FejeKrNrrRtVstVtlcxtNZ3CSorgAlSVJAOCDj3FdlPFUKsnGE02uzRvG tTm3GMk36mrRRRXUbBRRRQAUUUUAFFFFADWGVI9q+Zvh38VJ/wBnv4Y2Hh3xd4J8UwzaSZPtN/a2 UctkPNmZ0xOJdp/1ir1+9kda+m6wPGngXQviJojaR4h06PUrBnWURuWUq69GVlIZT1GQRwSOhIry 8ZhqtRqth5WnFNK+2tt/uOmjUjH3KivFtX76f8OaWi6xaeINHsdUsJfPsb2BLmCXaV3xuoZWwQCM gjgjNXMj1rwjTPgd4/s9PbwsnxJuNP8ABlnOv2J7SHOpyW2VbyHn48ry9u1WTOQxyAoWMZzfsr+I dM1SKbQPivrmnWdtatZWcN1G1y9tC6KrorCVFAO1SNqLt2oRygaub65jVFNYZt9dUvW2uxr7Gjd3 qpfJ/wCR6nr3xq8EeF/Fa+G9W8R2dhq5QSNFOSqRgqWAeTGxCQMgMwJyvHzDKaF8bPAfiS8e10/x Xpc10Lo2awvcLG8suQAIw2DICSAGTKt2JrB8C/ASw0WHXZfF1zb+PNW1i9W8uL3UrFdvyIVjURMz quwNIAVAwH24woFdJqfwd8Datp4srrwloz26wNbRhLKNGijYsxEbKAyfM7tlSCCxI55q6csxmueS ivJ3v5JtO1yJLDrRNvzOwyKWvHv+FF+IdD/f+G/ir4ptb1vkd9ckj1SEx9SBE6qFbIX585ABH8Va /gPx9q0Hi6bwD4qi8/xHZ2Rv49XtlRbbULQSLGkxTdmKUsSGjxtBRipwVFdEcXKMlGvTcb7PRq/9 d0ZukrXhK/5npVFJuHqKWvRTT2MAooopgFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQA UUUUAFFFFABRRRQAUUUUAFFFFABRSbhnGeaWgDyr9k7/AJNZ+Df/AGJmjf8ApDDRR+yd/wAms/Bv /sTNG/8ASGGigD1WvDP21NDuPE37P97o1q0aXWo6/wCHrKFpiQgeXW7FFLEAkDLDOAa9zrxf9r2T Uofgp5mjQR3esJ4m8NNZQSnCS3A12wMSMcjgvtB5HXqOtZ1LOLTN6EnGrFxdndbmV4N/aD8OaH8L dWhns7PwxrPheO405PDF3q0bSu9smEjikJLSA4VA205YMBuxkp4N+IF/8Mf2WdM17XtVi1PX5LGS 6tZNQvA7XEkpeWBGaV0LlUZcqDuwjBNxAzxsWn/Dn9nT4X6bo3j3SvDes+OI7a6uI4FshO12fNka JWkMJZQcqgZwB8pxkKa3vhL+zVa+Ib0fEL4ix/2x4k1gvePpNzGxtbNZACkbRyAsWRPl2sdqfdAJ QPXzdKWMqNQTXNa2j+G/V+fZH1ksPQpxrzxXu0XO8Gotupy3VouT0jrdu76bsj+G/wC2Zo3iBtSu PE0un6DplhZWm6RpHNxPdvkS+VAoYvEG6YJZQAWzvOz3zwl4z0Tx3o8eq6BqVvqlg+B5sD52sVDb XHVGAZSVYAjPIFRXHgHw3ef2T5+g6bL/AGTj+z99pGfsmNuPK4+TGxMbcfdHoKj1q10Dwf4X1+8k gj0fTGjnvdQmsEaFyShMsxMWH8zAzuHzcDBzivUw1PFYeFq1RTS62szwsVLB1mlhKcotvZtP9E79 fwt1OjqlputafrH2r7BfW979lna2uPs8qyeVMuN0b4PysMjKnkZrxH4V/Gebwx8BYPEvjuS8SGCR 4bC8vQovNWhyTA4iySHZflwWbIQyFyp3Vy/ha++Mdn8QvEfjaw+G8Cab4hhtJ5tLvNUjS4byohEi I+R5bfOXYSRjhSvDYzjLMo3pqMW+bVpJtxVt3bz08+hh9V/2qpg5TSnG/VJaO270XzPqFm2ox9Bm vnD4I2HiD4u/Eaz+MOs2ujwaTLpk+n6Za25ke5t9tywDNvXG7b5yl1IyGHyjJFdXqHxumuPhz4+a +tP+EP8AGHh2yf7RY3E8dwsEssTNaskuPLk3nbhcZ3fKR03b/wCztoFt4Z+Cfg+0tXleKSwjuy0x BO+b9844A4DSED2A69aXtaeMxNNRd4pN/O6Sv101M8Li6VOlU9nL95LS3Tld+b0d0kvnc9GrjviN 8N7bx5Z2k0F1Jo3iHTXM+l61bKDLZykYPB4dGHyvG3yuvB5wR2NLXsThGpHlktDGlVnRmp03Zr+v +HXU8C1L/hoHw61tNEfDHiey0+dd8NvvtrzUoRlDv3/uomIPmHaQAy8bh8rcHp/ji++I/jfx38Tv sV3Y23gXSJoNF03VYJIwt4YXMxkUSbd6lSjKOSrx52lQa+uOteK/Ez9lbw148bV7jT73UPDN7qmZ L4adMRbXswwY3ngPyvtYFvl2klmJOTkePicLWsnSk5Ja2b620s/XU+ry7M8I3KGKgoOStzxjsm1z XSaWsbq6V9WttmfAPQtB0XSdC8SaxqNve/EHxjZi7mvrqXbc3alRMYooyxwsaMikRgDEaEgYAHt1 eI/Bf4G6h4b8RXnivxqdPvvE64tdMXTi32PTbNUCrFbxsi+X1deM/L3yz7vbq7sHGUaKUo2/rd+b 3PHzWcKmKlKFTn8+npHySslttokgooortPHCiiigAooooAKKKKACiiigAoorP17+0/7D1D+xvsv9 r/Z5Psf23d5HnbT5fmbfm2bsZxzjOKaV3YTdlc0KK8h8K/GrVtO8QWPhj4jeGpPCusXUn2e01aB/ O0nUJeirHN1jkkKSMsMnzbQoJLMAfXQQwyDkVtWoToO0+vzT9GtDCjXhXV4dPk/uFooorA6Aoooo AK8Y8STs37VHhKHSbeRLxNCuX1q4JXY9iXIgUBjnK3C5O0A/OvJGQPZ68x+LXhTXbjxN4P8AGXh2 wj1zUPDb3QOjPcLbG6S4iEZKytlVKYDYI5GeQQAfMzCMpUlKKvyyi9N7Jq/4ffsdNBrnafVNfgen UV4zcfGzxn4bkt7vxb8LrzRdA3lbrU7LU49QNom1mMrxRJu8tduWbsPU4Ur4M/a0+HXjCRYZNTl0 C6d2RIdYjEIIC7txkBaNQeQNzgkjGORmY5phHJQlPlb6STj+dhvC1bXUbry1/I9lpK4/QPjB4L8U ef8A2b4l0+fyb1dOO6YR77hs7ETdjfv2ttK5DbW2k4NdhXoU6tOsr05JryOeUZRdpKwtFFFakhRR RQAUUUUAJUF9Y22qWc9peQR3VrOjRywzIHSRCMFWB4IIJBBqxSUmk1ZgYnh/wP4e8J/aP7E0PT9J +0bfO+w2scPmbc7d20DONxxnpk15940/Zh8E+JIXuNL01PC+uxov2PU9IzAbaRW3o4jQqjHPU43Y 6MCAR67RXJUwmHrQ5JwTXp+RjKjTnHllFWPINP8AjBrHgS6t9N+Kem2mhLO6w2niHTpHl066lJz5 ZyN8BCsOZOG2SHIC8+vKwYAg5FYfjddE/wCEU1STxHb29zokEDXF1HdQCaPZGN5JTB3Y25xgnIGO a88/ZM1f+1vgT4eD3v2y4tTPbS7pfMeLbM+yNucriMx4U9FK44xXLSqyoYlYWcuZNNrurW0fffT0 MoOcKns27q179vX9PQ9gooor1jrCiiigAooooAKKKKACiiigAooooAK4/wCIHwl8KfFH7CfE2l/2 kbHzPs/+kSxbN+3d/q2XOdi9c9K7CisqlKnWi4VIpp9GVGUoPmi7M8ff9lrwVpw83w2+s+D74/K9 9omqzRzPH1MZLs42khT0zlRzVv8AZ58XeJPFHhnXbbxXd29/rOia1c6TJdW8YRZfLCHdgBR1cgEK vAXIzkn1WvHdMY6P+1VrNpafubbWPDEOo3yfe824iuDDG+TyuIyVwuAepBPNeRUw9PBVqVSiuVN2 aWi12dttGdaqSrQkpu73uz2KiiivcOIKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAoo ooAKKKKACiiigAoor5r8SfHjx54i+OWreAvAI8IxwafB8t5rlxK/2qZQpljQxNw6bmUx7SR5MhJH 3RtSpqo7SnGPnJpL013fktTnrVvYq6i5eSV/6XmemfFL47aF8LtS0zSJrTUtf8Qalua30XQrcXN4 Y1DEylNwwg2kdcnDYBCsR5P4Stf2ifihr+o6pfa2nwt8PTRpPYWT6fa30oDY2xlWG8EKMuZCp3HA QDIT0T4E/Be48Axah4h8V3EWufEPWZHbU9YEhlGzf+7ihJRdkYVUyoUcgD7qIF9b9q9n63Qy/mpY aEZy2c5Lm168sXol0u021rpex5SwtfHWqYibgt1GLt/4E1r91vmePeCvgTrVl8QLPxj448c3XjfV tMgeDSl+xJYwWfmBhK/lxsVd2U7cnHHXdhCnsVFFeTiMTUxUlOq9tFZJJLySSS+SPUoYenh4uNNb 66tt/e9Tyr9k7/k1n4N/9iZo3/pDDRR+yd/yaz8G/wDsTNG/9IYaK5jpPVK8e/awtru8+ENvb2F5 /Z1/N4r8Lx2955Ql8iVtfsAkmw8NtYhtp4OMV7DXj/7V11dWfwjtrixs/wC0b6HxX4Xkt7PzRF58 i6/p5SPeeF3MANx4Gc1MrWdxqXK+bsQfDD4Q+IIfiBq/jvx9d2V54kuFjtrKHSJ7gWtrAqEMu12G 4Ox3bGUgMu4HJ49n4X2rhPht8aPDfxOWeDT55LLWLaSSO60XUFEN7blGCtviyTjJXkZAJwSGBA7y ubCqkqd6Lunrfud2Mr18RUUsQrNJJK1rJLSy7f8ADnAfEr4pSeANe8H6XHo8moHxBqAsjdPOsEFs OMlnbgyEElI+C+1gDkAGl+0hqF5Y/AzxdLp9t9smksjAybGfbFIwjlfCn+GNnbPQbcnIBrp/iTpe l6v4F1y31jSZNd077JI8unwR+ZLOFUsFjAIPmZA24IO7GCDzXA/sv2bat+zr4btNXMepxT288LpN ItwjwmWQLG3JGAmF2H7uNpAwQOav7SpKeHv8UXZ9tl+tzaVGMsB9ZovlnCSj6t8zUlr0ta1uzuc5 4R+DvhD4baPb+PPGXiePxZHpFpb/ANm6pOmy1s7WOMLCsUSMyuSWBB5LMVKjeSze0+B/FMfjbwnp mvQWdxYW+oQrcQwXWzzBG3KMdjMo3LhsZyARnByB4Z8Sv2atQ0fQ7uH4ZzR22mXVrPDqPhjVLiSa zuiyZWePzC2y5Vlj2sSBlEO5QGD+r/A/xGviv4S+FdRF5JfyvYRRz3ExYu80aiOUsW5J3q2T365O c1xYBPD1vqzp8ml973fV3ertpueZanThFOzqTvJtN97NO6V31vrpZGR8TP2c/BHxQu7jUdUsZLTW JkRG1OymMUuFIwSDlGOBtyyk4wM8DGP8dPjLp3gzw34t0K8kvvD+qnSJH0m+ZdqXsjIUH2eRCTvS Rk3A7WXIbG35q5f9tnVdd034Z3VvH/Z83h3UfJt5lkcxXcNwsyyo6EtiVSsbKUChl+9kqGC8P8bl 139ppvDmkaB8PfEOlX9hI7yap4ggNlDDC2xWAyxD5OxjjLgR/KrZbGWKqxw8q0cNTtUaXT4r37dt 7n2OR5DhpToY3FNRpVJSUmmlbkSd3d9W7Wte217o+lvg3fXGpfCfwfd3lxJdXU2k2kks8zl3kYwo SzMeSSckk9a1fEXjjQfCVxp9vq2qW9lc6hOltaW8j/vZ5GdECog+ZvmkTJAwoOTgc181eNPFfxH+ F3hG28CJoej6BpsnmWa+NoC9vYqj5AlMUC/6HKXlT5mO3zNxA28jqfgb8OPCWteJNS1zUfGlv8VP E2m/Z7aO+nVXWxRVV4vLUs4LEgnzQSSwbkN5me2njJScaEI+8rXvp/wX8tPMwr5VTpwnjKs/cd3F R966vpdr3Y76qTUv7p9EA5GaWkGMcdKWvZPkwopKWgAooooAKKKKACikPQ4614RffHjx58PbKa68 efC2+XS7RGWbWPDV5FfRyOoy0vkEq8UBVXbc5+X5Q3Jrqw+FqYltU7XXS6Tfom1f5HLXxNPD2dS9 n1s2vnbb5nvFJVHQdcsvE2h2Gr6bN9o0++gjubebaV3xuoZWwwBGQRwQDV+uZpxdnudMZKSTWwUU UUhiNnBx1rwe1+M/jr4ZzXDfFzw1Y2Xh1JAg8V+HHkntIyyqUWSA7plBbcnmEAbii7cHcfeaRlDD BGRXXh61OndVaakn6pr0fR+qa8jlr0qlS0qc3Fr5p+q/yt6nJsfCfxr+HpP+jeIfC+sW/vtkXP4M jqw9mRl7MvHnf7IWtTar8L7y1jlub3QNL1e7sNC1C8WQS3enowMLkuBnG5k+UKAIwu0FTTPE3w78 V/DnUvEN74G0fTfF3hfxFPLe6z4T1SYRSvcSqEke3mcFNkgIZ45cgCMhPv4HNfsZ/ErSF0Of4XD7 Sms+HfOmVri3eFp4XmLvvRh+6lieURvGSRuGVdxkj3FhubLq06D5oqUXb+Vaptro03FX0T3V7aeJ 9Yax1KNZcsrSV+70tZ9t33X5/TNFFFfMH0oUUUUAFFVbjUrSzmtobi6hhlupDFBHJIFaVwjOVUE/ MdqO2B2UnoDXkvxH/ag8LeC9Qk0LRkufGni9vMSPQ9BjNxIJFWTKyMoITaYyGUbnUHOwiuqhha+K lyUYNv8ATu+y82ctbFUcPHmqSSPYiy9yK4Hxd8SPh03iK18C+IdV0i61PU5BEukXQWYM4CuiyqQV QtlCgfG4kbcmvBNN/ZT8f+P/AAtFqviX4jeIPDnirVknh12xlmF1byxebJ5USrFKirHsdz5eWUea QAvIPqXh39kH4YaH4Nfw/ceH49ZWRzJLqN+Qb1zuBGJkCsgG1RtTaCAcglmJ9apgcro3Vev7R6pq EdvO7smu1t11ieVDF5hX1pUVBb3k9/Ky1T9dvMxP2mPhv8L9P+HK6prYj8LrpaPFp8ujwRrJI772 W3WHgSAuS+3K4+c7kBdqxvBfjb46/FqS4vra00/wDFpYi26Zq+mXMbag58vdveSMgRHbMR5Tb04V s7lkrf8Ahr+yDoXgnxZa+INa1zUvGN3pf7nRotUYNFYW6keSoU53PH82CNqAtkIpAI99CgdBivIx GCyvDwqU8Iuac0rz1ja2yS8urfpa2/oUK2PrTjUxHuxjtH4r33u/0PPvgz8XoPi1ot/O+nSaHrGm 3TWl/pNxKHlgcdCeA2DyPmVfmRxztyfQa8s8QfBfUoPE+oa74E8U/wDCD3erbW1WOPTIbyO7kUsU kCuRsb533Y4YkEjOS3k3xQ1f4vfB7xFoOs6t4ovfE3gyzurea/vLPTra2+87o8LxqckFDwzEJvdM EMFNfJyx9fAUf9qpylbeSta3e177b6H0Cw8MRP8AdSSv0d/u2t6an1bRXzTH42/aJ1zw3pmpWHhb Q4jduztbGJ7e6txHKBtlS4lUASBSPlydpJypKmuv8C/FbxF4d8Rad4U+KEVnp+tayhutMvbPItnL Oc2TsRtE0eQBtZgwZAWLEGTopZtSqSUZQlFO2rVlrtqZyws4q6ab7J3Z7PRRRXtnEFFFFAGX4m8T aZ4P0O81jWLyOx060TzJp5OijoAAOSSSAAMkkgAEmvHE+PfjTxpZzS+Bvhfql5bNbLJDf63PHYoW cMUZUY4mTAU5Vx1x8uQSfGiC2+IHxm+HHgiYyXenQyTa1qlmluHQLGpFu0jMhGxnEkZXPO/BwSpr 3VVCAADFeM5VsZVnCnPkhHS6tdu1+t9r9u5wN1K85RjLlUdNLXb+Z4Jq3wj+JXxWmhtvH3iTSLDw 5DPBLLougwSmO+VHLOskjFXXI2gYZhkBtoKgnW+HOgv8Hfibr3h1opIvC/ia6+36EYYVMENyI2a5 t2KKPLO1AY1I27Ijg7gwPs9c18QvA9r8QPC9zpdw32e5/wBdZXyg+ZZXKgmKeMqykMjc8EZGQTgm pll0KbVeld1Frdvfy9P11O7D04UXJfzbt6vyOkpa88+FvxEk1uS78J+IJI4fHOhIkepW4dWFyNql bqIqADHIGViMAoXCsB8pPodepRrRrwU4f8N5GkouDswooorcgKKKKACiiigAooooAKKKKACiiigA ryP4k6bqfg34laR8RtM0m8161TT5NG1aw0+PzroQl/Mhkgiyu4iXh/mOFIIXgsPW9w9RWB428e6D 8O9FbVvEOox6dYh1jDuGZmduiqqgsx4JwAeAT0BNcOLhTnSbnLltrftYqNVUrylt1POrf9rHwHBJ cW+vPqvhTUoHCPp+saZKs4BVWDFYw4AIbjJB4zjBBPRp+0F8OZJNMjHjDSw2oIZIS0wAQBQx80ni E4PSTaScgDIxXzXqvxe8fftReJtQ8H+Dvs2g6DLDK8gmbZJJbAoMzyDcwy2BsiHSUq29QWqjov7I Gv2/j/TLTxTaRnQNUknRrjwzdORp7BGkTf50bMUO0oM55K5bOA3x1PN8yryf1OCqQvbmacevq7+t ke1gsPgsZTnOU+RxV7N76X0ul93XZan2JZfEDwxqOrQaZa+ItKudSnRZIrOG9jaWRDH5isqBskFC GBA5XnpW/mvk+H9iC80nT7yO28V6dqZl2ObXUNEAWVkO5Y/PEplhVjwzREEg98AViX/jPxj8C3td Y1SHxlBerOqyaf4k1hdU0y9tmyDHHPFHiO5ypcZxhY2JLbgjenHN8Vh1zY+hyLunf8v68jB4SlUd sPU5n9x9mUV4xaftPadq1pDd6R4I8ba1YTIrJeafo3mQscfMobeMlG3IccblOCRgm58M/i14h1fx HBonjbw/H4av9WtX1PSEV2w0Icg20m/GbhF2yEL/AAtlljIIPsRzLDVJRjGV79bO33+ZxPD1Iptr Y9booor1DnEoorJ8VeK9J8E+H73W9cvotO0yzj8ya4lPCjoAAOSSSAFAJJIABJAqoxlOSjFXbJlK MIuUnZI16yPF3iS38HeFdY127SWS10yzmvJUhALskaF2CgkAnCnGSPrXzxqf7SHjvxRDBq/hrQdD 8D+EX+WHW/iJdG1W+ZkR0WKNHBGQZCGBdXVSQykFa57xp+0P428caVrXhBvBfh63k1/TRY2kC+NN Pe4D3EbBZAN48wOssRRQBnruYONv0FHJMTOa5uVJb3nFWXze/dbrrY8CtnOHjFqN79Pder+47r4O aD8U/iJZ+FfHPib4hS6fp1zK2qDwzYaZAiGFw4ijM4LFo2jdW2uCwBHIkUOv0LXlFj4y074BfALw 3deMZPsEml6TaWktqjLJLLcLCq+TGAcO5Kt0OMAsSFBIo6L+1BoV1qUVt4g8O+JfAltMGWHUvFWn Cys3kALCLzS5UOVViN2AdpGc4BxxVPEY2cq1OmuRNpcsUlZdrb2vvq+7NcLWw+DhGnUqPmaTd227 v12/BHstFfMmh+NPjR8dLUeL/BF5onhLwmtxJ/ZdjqcfnT6mqSojfaWAfy0O2b/VkMD8vIKyi/pP iz9ofwjpjaRqXgbTfHGoQ3CsPEFtqsFrFPCWVmTyiEO8AugfaoB2na+CXbyiorwdWCmt4uSTXq5W jp1s3+DtSzSD95U58r2ai2n913r6H0ZRXglpr37Q+oRNOfDPg3TFvJHS3tLu7meXTwGJV7hoyVlB RNv7rB3SoxChWUWBq3x6uB/wj93oXhu2ub08eL9Lu2a102M9c2k37yWUBWK8hCXjzwGrm/s+SdnU hp/eX9P5Xb6JmyzCLV1Tl/4C/wCvv+Z7nRXg2paX8cPhrZz6pD4p0j4lWcMbXF1YX2lGxutkY3GO 1+z7g8kg3KN4OCEwDk1h6x+15D4w8I6x/wAIF4S8Z6rfPaPFaapY6KJ7e3u2hDKrnceY2ddw2kcH G5SCdI5XVqO9CSnH+ZXsvXmSa+a16ESzKlTVq0XCXZ7v0tdM+k96/wB4fnSswUZJwK+avhz+zO+r eBdD1O68S+NPBWt6haR3erWeka7MguLtxmS4mEqFhO/y714CkbRnG439U+Afjrxtfaf4W8X+MI9V +GemyeaFiMiapqwUqYob1wApCcguhBfaGIDkMh9TwyqOLr2S30107WbT8tV6pXsljMS4KXsNXtr+ fVfce7ap4i0vQ/sn9o6ja2P2u4S1t/tM6x+dM2dsaZI3OcHCjk4rL8efEbw58MtBbWvEuqRaZp6y LEJHDOzu3RVRQWY9ThQcAE9ASPOtD/ZB+GukyapJd6TNr0t9G1ur6vcvcG1tyqokMJJGwRqiqj8y KON+KPCv7KnhbTNSstZ8R32r+NfEdhd/aLLVtZ1Gd5bdEk3wRABwpCcE5BDMXOACFBGnlyleVSTS 6cqTfp7zS9X62ew3Ux8laNOKb820vXRX/rU42/8Ajh44+NM2iaP4A0LxL4FW+v0lHiXVtHWW0bT/ ALOzs5LBlDs2AgBw2E/eLvIHa6R+yf4EsfhnZ+ErrT/tLQk3D6lFJIkxu2hSKS4TLNs3bFby+Uyq 5U4r2VVC9ABTq5cZiKeKoPCwpqNJ7re76Nvd26dF0N8LhZ0Kv1ipNyqdHtb0XQ8R03w18cfDcBgt fEXhbXYU220K6tDcKywxoqpKXT5mll+ZpA5YAgbWIYgT+G/g344t9W0vxBrPxQ1S61uO6imvbOGM DTZIQgWS3WDKrk84lwOu7YG5r2eivm45bSTTcpNLa8noey8RKzslr5IKKKK9Y5jyr9k7/k1n4N/9 iZo3/pDDRR+yd/yaz8G/+xM0b/0hhooA9VrzT9oz4c6l8VvhTeeHdKt9PvLx9S0u++yapeS2lvcR 2uo211LC80Ucjx744XQMqMQWBxXpdFJpNWYt9GfIfhr4A/FDwj8VNL8XaX4N8GQWOl2zw2eiyePt Qljgdw6sVkfSCwjPmSNsx99y27B217N/wkXxv/6J58P/APwvL7/5TV6tRXPh8NRwsXGjGybuaSqS koxk9Iqy8l2R5RJ4g+N8kbKfh78P/mGP+R8vv/lNXHfB/wAO/G74T/D3S/Cw8G+ANVFiZT9rPjW+ h375Xk+5/ZDYxvx1PTNfRFFaunFzU+q0++3+RpGvUjSlQT91tN+qul+bPKT4i+N7KR/wrz4f4P8A 1Pl9/wDKauP8BeHvjd8P9Q11LDwb4A/4R69mW4sdEXxtfLFprEHzhG39kH5Xc7tgCqpzgcmvoail KnCUoza1WxyuKk1J7o+Y/jh4D+Onxj8P6Zp8HhzwJ4buLDUI9QivIfGl9M4ZEdRtxpKFTlwQwPG2 maD4d/aks9W0C41lvh9q9npbzPNbweIry0e/LxuiCZl0wrhN+QAgB2gkEgMPp+isnhqcqjq63dur 6eWx60cxrxw6w2jgr2vGLaurPVq/4+e58s+Bfhn8dvDt1fXniOw8M+Np9Qgmgu7PUvHt4NOdZHDH Za/2MwT5RtxkjBYAAHAztZ+BfxVt9dHiHwN4O8DfD3xEEaM3GmeNbuW1kRtoKyWzaMEIwvAXb8x3 HJAr63pKTwlGUVFx2+/79yo5pi4VXVjOze6suVrs4/C15NWPBPhva/H3wL4NsNF1Lw14J8T3tsZD Jql546v1lm3SMwyG0lz8oYL948KOnSum/wCEj+N//RPPh/8A+F5ff/KavVaWuiMVCKitkefVqSrV JVJ7t3fTfyWiPnr4c6B8b/h+fEx/4QzwBf8A9ta3c6x/yO19H5Pnbf3f/IIO7G373Gc9BXYf8JJ8 b/8Aonnw/wD/AAvL7/5TV6rRSp040o8kFZESk5O7PKv+Ek+N/wD0Tz4f/wDheX3/AMpqP+Ek+N// AETz4f8A/heX3/ymr1WitCTyr/hJPjf/ANE8+H//AIXl9/8AKaj/AIST43/9E8+H/wD4Xl9/8pq9 VooA8q/4ST43/wDRPPh//wCF5ff/ACmqtqWqfGrVNPubOb4feBFiuI2idofiDqEUgDAglXTRwynn hlII6gg169RTTad0JpSVmfOnwY8MfG74Q/DfSfCY8HeANX+wGY/bP+E1voPM8yZ5Puf2Q2Mb8dT0 z7V23/CSfG//AKJ58P8A/wALy+/+U1eq0VrWrTxFSVao7yk236vcinTjRhGnBWSVkeVf8JJ8b/8A onnw/wD/AAvL7/5TUf8ACSfG/wD6J58P/wDwvL7/AOU1eq0ViaHlX/CSfG//AKJ58P8A/wALy+/+ U1H/AAknxv8A+iefD/8A8Ly+/wDlNXqtFAHlX/CR/G//AKJ58P8A/wALy+/+U1ef6Z4L+OFp8Z9X +IN34X8CXktxpselWWmr4zu447OAMsjguNHJkLSKWBONu5h8wxt+laK2p1p0lJQ+0rP0/pGNSlCq 4ua2d16nlX/CSfG//onnw/8A/C8vv/lNR/wknxv/AOiefD//AMLy+/8AlNXqtFYmx5V/wknxv/6J 58P/APwvL7/5TUjeIvjewI/4V78Px/3Pl9/8pq9WooA+KPD37J/jr7HJN428CeD/AB/4jnkL3Gta h8R9WhdwAFRAq6WeFVVHzMx68gYVfSvht8OPHvwibUD4U+Evw/0s6h5f2nPxF1Obfs3bP9ZpDYxv bpjrz2r6Nor1K+aY3ExdOrWk4v7N3y/+A7WXRW0PPpZfhKElOnSSa621+/c8q/4SP43/APRPPh// AOF5ff8Aymo/4ST43/8ARPPh/wD+F5ff/KavVaK8s9A8q/4ST43/APRPPh//AOF5ff8Aymo/4ST4 3/8ARPPh/wD+F5ff/KavVaKAPKv+Ek+N/wD0Tz4f/wDheX3/AMpqT/hIvjef+aefD/8A8Ly+/wDl NXq1FAHlP/CR/G//AKJ58P8A/wALy+/+U1ec/FjwD8bviXq3hPV7fwn4A0nU/Dl79stmk8Z31xDJ 8yMVdBpKN96JOQw43DHII+nKKwrUKeIh7Oqrr/I0p1JU5c0dzyn/AISP43/9E8+H/wD4Xl9/8pqX /hJPjf8A9E8+H/8A4Xl9/wDKavVaK3Mzyn/hJPjf/wBE8+H/AP4Xl9/8pqhvvEHx3ms50tPAXw8t 7pkYRSy+OL+REfHBZRpClgDjIDDPqOteuUUnqrAfM/wx8AfGb4f32p61qHg/wJ4m8Wao5a91y68b XsbsmRtijQaORGgAX5Qedo7Kqr6H/wAJJ8b/APonnw//APC8vv8A5TV6rSVlRowoQ5KasjOnTjTj yxWh5X/wknxv/wCiefD/AP8AC8vv/lNR/wAJJ8b/APonnw//APC8vv8A5TV6rRWxofP/AIi0f416 t4s0HxLY+BPh3pusabIYprj/AITfUH+12bKwe2fbpKZG4q6ltwRkBCnJB6v/AISP43/9E8+H/wD4 Xl9/8pq9VpKzjTjBtxW+5Tk3ZPoeV/8ACSfG/wD6J58P/wDwvL7/AOU1H/CSfG//AKJ58P8A/wAL y+/+U1eq0VoSeVf8JJ8b/wDonnw//wDC8vv/AJTUf8JJ8b/+iefD/wD8Ly+/+U1eq0UAeVf8JJ8b /wDonnw//wDC8vv/AJTUf8JJ8b/+iefD/wD8Ly+/+U1eq0UAeVf8JJ8b/wDonnw//wDC8vv/AJTU f8JJ8b/+iefD/wD8Ly+/+U1eq0UAeVf8JJ8b/wDonnw//wDC8vv/AJTUf8JJ8b/+iefD/wD8Ly+/ +U1eq0UAeVf8JH8b/wDonnw//wDC8vv/AJTVS1rWPj1f6Pe21h4K8AaZezQPHBe/8Jvey+RIVIV9 h0bDbTg4PBxivYaWk1zKzE9VY+O7f4J/tD/6JDd6xYzWUMJLpD8Rb6KZ7ltoZxKdHY+XhRiIhtpJ Ibls4Hiz9nH9o/xtdx3+san4RvNTXzY/NPiq9SFYnjWMpHEmmAR7lDB8cOGGRwS33HRXkVMpwdaP JOLa/wAUv8zjeDoy3T+9/wCZ4L8PNI+L/wAOvCenaJYfDf4bqbeCNLi4t/Gl5B9qlWNUaZ1GjH5m 2gkkk+5rpP8AhI/jf/0Tz4f/APheX3/ymr1akr1KdOFGCp01ZI7m23dnlf8Awknxv/6J58P/APwv L7/5TUh8RfG49fh38Pz/ANz5ff8Aymr1air33EeU/wDCRfG7/onfw/8A/C7vv/lNXH+PtA+N/jTU PC1/B4M+H+lX2hapHfrcx+Nr55JIQCJbcMNIUqsgIDdQQoypr6FpayqUoVI8k1oVGTi7o8p/4SP4 3/8ARPPh/wD+F5ff/Kal/wCEk+N//RPPh/8A+F5ff/KavVaK2JPKf+Ej+N//AET34fj/ALny+/8A lNXz74k+AP7RHjrxKmveLrP4aeKry1kB0+w1DX9QXTrNC5dlEEdgpkJIjXLu2VUhxJ8pT7Yortwu MrYNuVB2b62V/k91523OTEYWjiko1ldLpd2/4PzPjvRfgH8YNQ8eap4t+IXg/wCG/wAQdTuNi2UN 14sv4LWwjAkBiSE6XIjphxgMCQVLZLMWroYvgTr0NlqVqvwG+FPl6g8kkzP41vmkQuMN5TnRt0QH 8KxlQvVQK+o6K1qZli6jTdRqySsnZJLayVkv89TKGX4WmrKmvnq9fN6nxR4J/Zv+OHhzxx4e1jWr Pwf4s0jwykkeh6NqHjC722gLEx7nOkMHKAjDBFOY4sFVjVa9y1uT4ueJNLm03VvhZ8NdT0+bb5lr eeNryWJ8MGGVbRSDggH6gV7LRUYrHYjGTjUrS1Wiskut+nm736suhg6GGi4Uo6Pfr+Z5Fp+qfGXS bG3srL4afDq0s7eNYobeDxzepHGijCqqjRcAAAAAdMVY/wCEk+N//RPPh/8A+F5ff/KavVaK4b31 Z2JJKyPKv+Ek+N//AETz4f8A/heX3/ymo/4ST43/APRPPh//AOF5ff8Aymr1WikM8q/4SP43/wDR PPh//wCF5ff/ACmpv/CQfG0dPh18Ph/3Pd9/8pq9XooFY8q/4SP43/8ARPPh/wD+F5ff/Kaj/hJP jf8A9E8+H/8A4Xl9/wDKavVaKBnlX/CSfG//AKJ58P8A/wALy+/+U1H/AAknxv8A+iefD/8A8Ly+ /wDlNXqtFAHlX/CSfG//AKJ58P8A/wALy+/+U1H/AAknxv8A+iefD/8A8Ly+/wDlNXqtFAHlX/CS fG//AKJ58P8A/wALy+/+U1H/AAknxv8A+iefD/8A8Ly+/wDlNXqtFAHlX/CSfG//AKJ58P8A/wAL y+/+U1H/AAknxv8A+iefD/8A8Ly+/wDlNXqtFAHE/BHwTffDX4L+AfCOpy28+paB4f0/SrqW0Zmh eWC2jidkLKpKlkOCQDjGQOlFdtRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQ AUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFAB RRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFF FFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFAH/9k= Jon Bowers ODFW GIS Coordinator 503-947-6097 4034 Fairview Industrial Dr SE Salem Oregon 97302 US jon.k.bowers@odfw.oregon.gov M-F, 7:30-4 email preferred 20230113 ArcGIS Metadata 1.0 Jon Bowers ODFW GIS Coordinator 503-947-6097 4034 Fairview Industrial Dr SW Oregon 97302 jon.k.bowers@odfw.oregon.gov 7:30 - 4, M-F none Standard Ordering Instructions: Download at: http://nrimp.dfw.state.or.us/nrimp/default.aspx?pn=fishdistdata; Technical Prerequisites: GIS software required to view either geodatabase feature classes or shapefiles. To view online maps see: http://nrimp.dfw.state.or.us/nrimp/default.aspx?pn=fishdistmaps http://nrimp.dfw.state.or.us/nrimp/default.aspx?pn=fishdistdata File Geodatabase Feature Class Oregon Fish Habitat Distribution - Current and Historical Coho 2021-06-01 Oregon Department of Fish and Wildlife, Jon Bowers, GIS Coordinator vector digital data These datasets are collectively referred to as fish habitat distribution datasets and no longer have the version number in the dataset name. <DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>Oregon Fish Habitat Distribution.These data describe areas of suitable habitat believed to be used currently or historically by native or non-native fish populations. The term "currently" is defined as within the past five reproductive cycles. Historical habitat includes suitable habitat that fish no longer access and will not access in the foreseeable future without human intervention. This information is based on sampling, the best professional opinion of Oregon Dept. of Fish and Wildlife or other natural resources agency staff biologists or modeling (see the fhdBasis field). Due to natural variations in run size, water conditions, or other environmental factors, some habitats identified may not be used annually. These data now comply with the Oregon Fish Habitat Distribution Data Standard that was adopted by the Oregon Geographic Information Council in April 2020. The Standard document can be found at: https://www.oregon.gov/geo/standards/OregonFishHabitatDistributionDataStandard_v4.pdf. </SPAN></P><P><SPAN>Historical habitat distribution data are within the scope of the standard and are identified via the habitat use (fhdUseType) attribute. Historical habitats are only identified outside of currently accessible habitat and are not comprehensive. Data representing current habitat for anadromous and resident salmonid species are generally more comprehensive than data for non-game and non-native fish species. All datasets are subject to update as new information becomes available.</SPAN></P><P><SPAN>Key features of the Oregon Fish Habitat Distribution Data include: species, run, life history, habitat use, origin, production, the basis for each record, originator name, originator entity and reference. Habitat distribution data are mapped at a 1:24,000 scale statewide and are based on the National Hydrography dataset. The data are made available as GIS files in both shapefile and ESRI geodatabase format. The data were developed over an extensive time period ranging from 1996 to 2021. The data are now managed on the National Hydrography Dataset and have been synchronized to April 2019 NHD geometry.</SPAN></P></DIV></DIV></DIV> The Oregon Fish Habitat Distribution Database contains dozens of datasets that represent species specific, and in some cases genus specific, fish habitats within the waters of the state. The purpose of this database is to provide an inventory of fish habitat distribution in support of various natural resource applications, mapping and analysis. Oregon Department of Fish and Wildlife, Jon K. Bowers, Ruth Schellbach. Numerous fisheries biologists from ODFW as well as other natural resource agencies and tribes have contributed toward the development of these data. Data originator names are attributed at the feature level. Jon Bowers Oregon Dept. of Fish and Wildlife GIS Coordinator 503-947-6097 4034 Fairview Industrial Dr SE Salem Oregon 97302 US jon.k.bowers@odfw.oregon.gov M-F, 7:30 - 4 email preferred Oregon Aquatic Fall Spring Winter Summer Fish habitat distribution Anadromous fish Migration habitat Resident fish Fish Habitat Spawning habitat Rearing habitat Native fish Non-native fish ISO 19115 Topic Categories biota inlandWaters environment Fall Fish habitat distribution biota Anadromous fish Spring Winter Oregon Migration habitat Resident fish Fish Aquatic Summer Habitat inlandWaters Spawning habitat environment Rearing habitat Native fish Non-native fish Datasets that are classified as "Level 1 Published" within ODFW's Information Asset Classification System are made publicly available. Level 2 data are maintained internally and may be shared contingent upon completion of a data sharing agreement. Datasets that are classified as "Level 1 Published" within ODFW's Information Asset Classification System are made publicly available. Level 2 data are maintained internally and may be shared contingent upon completion of a data sharing agreement. <DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>Care was taken in the creation of these themes, but they are provided "as is". The Oregon Dept. of Fish and Wildlife cannot accept any responsibility for errors, omissions, or positional accuracy in the digital data or underlying records. There are no warranties, expressed or implied, including the warranty of merchantability or fitness for a particular purpose, accompanying any of these products. However, notification of any errors would be appreciated. </SPAN></P><P><SPAN>Please note that historical habitat distribution data are not comprehensive. Data representing current habitat for anadromous and resident salmonid species are generally more comprehensive than data for non-game and non-native fish species. All datasets are subject to update as new information becomes available. </SPAN></P><P><SPAN>The lack of a record identifying habitat for any species in any waterbody is not proof of unsuitable / inaccessible habitat unless otherwise specified by the End Extent attribute in a downstream reach.</SPAN></P></DIV></DIV></DIV> Oregon Fish Habitat Distribution 2021-06-01 ODFW, Jon Bowers, GIS Coordinator Version 6.2 (Build 9200) ; Esri ArcGIS 10.7.1.11595 -124.432154 -121.918476 41.997542 46.270815 State of Oregon 1996-01-01 2021-06-01 Procedures_Used: These data were originally created through a process where 1:100,000 scale fish habitat distribution data (current as of 2001) were plotted on 1:24,000 scale USGS quadrangle maps and then provided to ODFW and other natural resources agency field staff. Based on survey data, supporting documentation, and the best professional judgment of the field biologists, different types (spawning, rearing, migration, etc.) of species specific habitat distribution (see the fhdUseTy field) were marked on the maps with colored pens. Additional attributes such as source contributors, agencies and the basis of the data were also collected. These hardcopy data were then digitized by ODFW GIS staff and stored as event tables based on the PNW River Reach files at 1:100,000 scale. Habitat locations identified outside of the 1:100,000 scale stream network were captured as upstream points associated with 1:24,000 scale streams. Beginning in 2007 and ending in 2008, the data were migrated to events associated with the Pacific Northwest Framework Hydrography 1:24,000 scale stream network. All habitat distribution records are now in a single, consistent linear event format. Revisions: The first 1:100,000 scale version of the data was completed in 1996. Significant revisions at that scale were also made in 1999. The 1:24K Mapping Project occurred between 2001 - 2003 and data were published in 2004. Data were migrated to events mapped on the 1:24,000 PNW Framework hydrography in 2007 and 2008. Significant revisions since 2004 include additions of anadromous habitat in the upper Deschutes and upper North Santiam basins and coho habitat in the coastal basins. Numerous, less significant revisions have occurred throughout the state, in particular where the location and passage status of blocking barriers was recently verified. In 2014 the data were migrated to the National Hydrography Dataset (NHD) as Hydrography Event Mgt. Tool (HEM) compliant event feature classes. NHD data are current as of April 2019. The fish habitat distribution data schema was modified in July 2015 to comply with version 3.0 of the data standard. Optional attributes for describing additional record Basis details (date, name, entity, project, method) were added at version 3.0. Reviews_Applied_to_Data: All distribution data have been reviewed by ODFW or other natural resource agency staff (typically district biologists). The date of last review exists in the attribute table for each distribution record. Related_Spatial_and_Tabular_Data_Sets: Oregon Fish Passage Barrier Data Standard Dataset (see Passage Status attribute) barriers to anadromous salmonid migration http://nrimp.dfw.state.or.us/nrimp/default.aspx?pn=fishbarrierdata National Hydrography Dataset (http://nhd.usgs.gov/data.html) Other_References_Cited: Oregon Fish Habitat Distribution Data Standard: http://www.oregon.gov/DAS/CIO/GEO/fit/bioscience/docs/OregonFishHabitatDistributionDataStandardv3.pdf The attribute element fhdRefID can be used to locate more detailed reference information (please contact the data steward to obtain the detailed reference information), however the recently added optional Basis detail fields will eventually be populated with this source information. The data schema was modified further in April 2020 to comply with version 4.0 of the Oregon Fish Habitat distribution Data Standard (https://www.oregon.gov/geo/standards/OregonFishHabitatDistributionDataStandard_v4.pdf). Optional attribute elements were added to describe methods of anadromous fish access, related fish passage barriers and habitat end extent determinations. Also, the Oregon Fish Habitat Distribution Data Stewardship Plan (https://www.oregon.gov/geo/FIT%20Documents/OFHDDS_Stewardship_Plan_Version_One.pdf) was finalized in July 2020. The stewardship plan outlines the process for proposing, evaluating and implmenting changes to the data. 1 -124.544709 -117.196007 46.270815 41.934529 ODFW Information Asset Classification Policy None Chain-node topology present. Chain-node topology present. These datasets represent the most comprehensive statewide compilation of fish habitat distribution data available, however the data continue to evolve as more information becomes available. Any inconsistent or suspected inaccurate data should be reported to the contact person identified within this metadata record. See Entity_Attribute_Information Attribute accuracy is described, where present, with each attribute defined in the Entity and Attribute Section. See Explanation Distribution data are mapped based on the 1:24,000 (high resolution) scale National Hydrography Dataset flowlines. Positional accuracy of the NHD geometry may range upward of several hundred feet in limited cases. Most positional accuracy is within 40 feet. Adjusted the extent and habitat use of a number of records. Western Oregon Rearing Project Data through 2008 were analyzed to determine where coho observations had occurred outside of previously mapped coho habitat. Mapped habitat was extended to include the survey areas where the observations occurred. Jon Bowers ODFW GIS Coordinator 503-947-6097 All datasets within the Oregon Fish Habitat Distribution Database (95 stream-based and 63 lake-based were synchronized to the National Hydrography Dataset (NHD) dated April 2019. Ruth Schellbach ODFW GIS Technician Oregon Biodiversity Information Center Oregon Biodiversity Information Center Oregon Biodiversity Information Center https://inr.oregonstate.edu/orbic Oregon State University Ichthyology Collection Oregon State University Ichthyology Collection Oregon State University Ichthyology Collection http://ichthyology.oregonstate.edu/home U.S. Environmental Protection Agency EMAP U.S. Environmental Protection Agency EMAP U.S. Environmental Protection Agency EMAP https://archive.epa.gov/emap/archive-emap/web/html/labman.html ODFW District Biologists and fisheries biologists from other state, federal and tribal natural resource agencies. See the RefID field for reference information on source contributors. USGS Nonindigenous Aquatic Species database USGS Nonindigenous Aquatic Species database USGS Nonindigenous Aquatic Species database https://pubs.er.usgs.gov/publication/fs20123100 Fishing in Oregon Fishing in Oregon Fishing in Oregon https://www.amazon.com/Fishing-Oregon-Eleventh-Madelynne-Sheehan/dp/0916473163#reader_0916473163 Oregon DEQ-National Aquatic Resource Inventory Oregon DEQ-National Aquatic Resource Inventory Oregon DEQ-National Aquatic Resource Inventory https://www.oregon.gov/deq/wq/Pages/WQ-Monitoring-NARS.aspx These data were created through a process where 1:100,000 scale fish habitat distribution data (current as of 2001) were plotted on 1:24,000 scale USGS quadrangle maps and then provided to ODFW and other natural resources agency field staff. Based on survey data, supporting documentation, and the best professional judgment of the field biologists, the distribution of usetypes (see the fhdUseTy field) were marked on the maps with colored pens. Attribues such as source contributors, agencies and confidence in the data were also collected. These hardcopy data were then digitized by ODFW GIS staff and stored as event tables tied to 1:100,000 scale PNW Hydrography. Upstream points of distribution on streams outside of the 1:100,000 scale stream network were captured as point data. Linear events were converted to both coverage and shapefile format for data distribution purposes. 2001-06-01 Jennifer Lloyd - Jon Bowers ODFW Fish Distribution GIS Coordinator - GIS Analyst no longer with ODFW. Contact Jon Bowers Some distribution data were adjusted in order to reconcile endpoints with blocking dams. 2003-04-01 Jon Bowers ODFW GIS Analyst 503-947-6097 Distribution disputes were resolved based on documented observation data or the professional opinion of the ODFW District biologist. Some disputed distribution was converted to other usetypes (eg. spawning) and some was removed from the dataset. 2003-11-01 Jon Bowers ODFW GIS Analyst 503-947-6097 Distribution data that were previously mapped as lines on 100k streams and as points outside of the 100k stream network were migrated to a single, consistent linear format on the 1:24,000 scale statewide standard Framework hydrography. The resultant events were then evaluated for gaps, overlaps and anomalous measures in relation to the stream routes and corrected where necessary. 2007-08-01 Jon Bowers ODFW GIS Coordinator 503-947-6097 7:30 - 4 email preferred Analyzed ODFW Oregon Adult Salmonid Inventory and Sampling (OASIS) project Coho spawning data; developed a set of extensions to the Coho distribution events. Merged these new spawning events into Oregon Fish Habitat Distribution Data, in total adding 53.3 km of Coho spawning to Oregon's fish habitat maps in the coastal basins. 2008-11-09 David Bradford ODFW GIS Technician (503) 947-6096 0830-1700 email preferred Performed final migration of 100k linear event data and 24k point event data to 24k framework hydrography. Performed extensive quality assurance on all data. Mapped and reconciled all events onto Oregon mixed-scale hydrography. The event data were then mapped to species /run specific route event themes and converted to a feature classes covering the extent of distribution within the entire State of Oregon. 2009-01-26 David Bradford Oregon Dept. of Fish and Wildlife GIS Technician (503) 946-6096 8:30AM - 5:00PM, M - F Coho habitat use in the ocean tributaries south of the Rogue River, including several small lower Rogue tributaries, was recently changed from "unknown" to either spawning and rearing or rearing and migration. This is based on the professional judgment of ODFW and USFS fisheries biologists. 2010-01-01 Jon Bowers ODFW GIS Coordinator 503-947-6097 An additional optional attribute (fhdESH) was added to the schema of the fish habitat distribution database. This attribute identifies "essential indigenous anadromous salmonid habitat". Species / runs that are listed as sensitive, threatenend or endangered at either the state or federal level are included. Only spawning and rearing habitats of native salmonids are considered for ESH designation. The Department of State Lands administers the ESH data that are derived from the fish habitat distribution data stewarded by ODFW. 2010-01-01 Jon Bowers ODFW GIS Coordinator 503-947-6097 7:30-4 email preferred Historical habitat distribution data that were developed during the ODFW led 24K Habitat Distribution Mapping Project in 2000 and 2001 were converted into the Oregon Fish Habitat Distribution Data Standard format. They are now combined with current habitat distribution in the habitat distribution publication datasets. 2011-01-31 Mark English ODFW GIS Technician The BLM OR Hydrography Publication Dataset, was provided to the Data Steward in March 2011. Migrated BLM data to 24k framework hydrography using the Locate Features Along Routes tool in ArcGIS, with a search radius of 150 feet. Overlaid the BLM segments on the OFHDS coho data and used the ArcGIS Symmetrical Difference tool to locate differences between the two data sets (i.e., extensions or additions to OFHDS). An outline of OFHDS attribute values was developed, and OFHDS fields were added to the BLM data and populated. The OFHDS Use and Production fields were populated using the ArcGIS NEAR tool to query attributes of adjoining downstream events. Finally, the BLM coho event data were loaded into an enterprise geodatabase event table. 2011-03-31 Ruth Schellbach ODFW GIS Technician Excel spreadsheets of ODFW Oregon Adult Salmonid Inventory and Sampling (OASIS) survey site UTM coordinates, where steelhead and coho salmon, plus coho salmon habitat that were observed during OASIS surveys, was provided to the Data Steward in March 2011. The UTM coordinates were added to an ArcGIS basemap using both NAD 83 and NAD 27 datums for comparison. Migrated OASIS coho salmon survey coordinate data to 24k framework hydrography using the Locate Features Along Routes tool in ArcGIS, with a search radius of 150 meters. OASIS survey endpoints were overlaid on OFHDS steelhead and coho event data. OASIS survey upstream endpoints greater than 100 feet from the upstream endpoint of OFHDS steelhead coho event data were reviewed for addition to the OFHDS. An outline of OFHDS attribute values was developed, and OFHDS fields were added to the OASIS data and populated. The OFHDS Use and Production fields were populated using the ArcGIS NEAR tool to query attributes of adjoining events. District biologists reviewed additions to Coho salmon habitat distribution for approval. Finally, the survey event data were loaded into an enterprise geodatabase event table. 2011-03-31 Ruth Schellbach ODFW GIS Technician An Excel spreadsheet of ODFW Western Oregon Rearing Project (WORP) survey data with UTM coordinates was provided to the Data Steward in April 2011. WORP survey UTM coordinates were added to an ArcGIS basemap using NAD 83 datum. Migrated WORP steelhead and coho survey data to 24k framework hydrography using the Locate Features Along Routes tool in ArcGIS, with a search radius of 100 feet and then 150 meters. Overlaid the WORP survey segments on the OFHDS steelhead and coho data and used the ArcGIS Symmetrical Difference tool to locate differences (extensions or additions) between the two data sets. An outline of OFHDS attribute values was developed, and OFHDS fields were added to the WORP data and populated. The OFHDS Use and Production fields were populated using the ArcGIS NEAR tool to query attributes of adjoining events. Finally, the OASIS steelhead and coho habitat survey event data were loaded into an enterprise geodatabase event table. 2011-04-30 Ruth Schellbach ODFW GIS Technician The Rogue-Siskiyou National Forest fish distribution data was provided to the Data Steward in May 2011. Selected steelhead and coho distribution data and exported to new feature classes. The feature classes contained LLID and from and to measures for each record. Overlaid the Rogue-Siskiyou steelhead and coho distribution on the OFHDS steelhead and coho data and used the ArcGIS Symmetrical Difference tool to locate differences between the two data sets (i.e., extensions or additions to OFHDS). An outline of OFHDS attribute values was developed, and OFHDS fields were added to the Rogue-Siskiyou data and populated. The OFHDS Use and Production fields were populated using the ArcGIS NEAR tool to query attributes of adjoining downstream events. Finally, the Rogue-Siskiyou steelhead and coho event data were loaded into an enterprise geodatabase event table. 2011-05-31 Ruth Schellbach ODFW GIS Technician New historical habitat distribution data for chinook, coho and steelhead, pacific lamprey and redband were developed where the information could be obtained, primarily from state and federal natural resource agencies. 2011-10-28 Ruth Schellbach ODFW GIS Technician Rapid bioassessment data from the Tillamook Estuaries Partnership (TEP) were obtained in GIS format. The data contain coho and steelhad observation information from snorkel surveys that were conducted between 2005 and 2007. Observations were compared to existing Oregon Fish Habitat Distribution Database (OFHDD). Where the TEP observations occurred upstream of habitat that had previously been mapped, new records were created and loaded into the OFHDD. 2012-03-30 Jon Bowers ODFW GIS Coordinator jon.k.bowers@odfw.oregon.gov Between November 2011 and January 2012, maps at the 5th field watershed level that included both anadromous salmonid habitat distribution and fish passage barriers were provided to ODFW district fisheries biologists for review. While the primary objective of this excercise was to identify priority fish passage barriers, other objectives included the collection of both current historical fish habitat distribution information as well as additional input to resolve discrepancies between barrier and fish habitat data. Where data were not observation-based, biologists collaborated to formulate a concurrence of professional opinion on the changes. Data were input in April of 2012. 2012-04-30 Ruth Schellbach ODFW GIS Technician Adjusted the linear extent of some habitat distribution records to align with natural waterfalls. This also involved the deletion of some habitat records upstream of the falls. 2013-03-29 Data quality control checks were run to identify micro overlaps between records. Feature extents were adjusted to remove overlaps between adjacent features. 2013-06-06 Jon Bowers ODFW GIS Coordinator 503-947-6097 3406 Cherry Ave NE Salem Oregon 97303 US jon.k.bowers@odfw.oregon.gov M-F, 7:30-4 email preferred Feature extent and habitat use changes were made based on recent observations and changes to the passage status of selected barriers. 2013-06-26 Jon Bowers ODFW GIS Coordinator 503-947-6097 3406 Cherry Ave NE Salem Oregon 97303 US jon.k.bowers@odfw.oregon.gov M-F, 7:30-4 email preferred Feature extent and habitat use changes were made based on recent observations 2014-03-13 Jon Bowers ODFW GIS Coordinator 503-947-6097 4034 Fairview Industrial Dr SE Salem Oregon 97302 US jon.k.bowers@odfw.oregon.gov M-F, 7:30-4 email preferred FHD to NHD Migration Metadata process steps: 1. Previous to beginning the fish habitat distribution (FHD) migration effort, ODFW’s version of the LLID route-based, Oregon Framework Hydrography dataset was migrated to a set of linear referenced “events” mapped to the National Hydrography Dataset (NHD). These NHD-based whole stream route (LLID) events were then converted to a whole stream route network derived from the NHD geometry. Both of these datasets (Framework and NHD-based whole stream route) were integral to the FHD migration process. 2. The event records for a specific fish species/run, (eg. Spring Chinook) were mapped (Make Route Event Layer) on the data’s original Framework-based whole stream route hydrography network (EPSG 2992), and then exported to a line feature class. 3. The exported line feature class was then deconstructed to start (downstream) and end (upstream) point vertices with the ArcGIS “Feature Vertices to Tool (all attribute data is preserved). QAQC checks were conducted on the start and end points for count and frequency. 4. The start and end points were then located relative to NHD-based whole stream routes, using the ArcGIS “Locate Features Along Routes” Tool with a tolerance of 300 feet, and unselecting “Keep only the closest route location”. QAQC check for the “Locate Features” tool joined the output event table to the start and end point feature classes, using the unique fish species event record feature ID (fhdFtrID), keeping all records, and then selecting records where the output table RID equaled the whole stream route LLID. Records from the output table that did not match the start or end point route identifier, the LLID, were deleted. 5. Fields were added to the start and end point feature classes to preserve the LLID attribute and the route measures found with the “Locate Features” Tool. Where the original species event record had a beginning measure of 0, the start measure was calculated to equal 0. The start and end point features classes were then joined to the “Locate Features” output table on the fhdFtrID and measures were transferred to the end point and start point feature classes (where not equal to 0). 6. Points not found or located, were visually inspected and manually checked for route position and measure. 7. Start and end point feature classes were then joined together, on the record’s unique identifier, fhdFtrID, and either start or end measures, as needed, were calculated to one feature class. The feature class attribute table, containing the LLID whole stream route attribute, and the start and end point measures from the NHD-based whole stream route, was then exported to an event table. The event table was then displayed, using the ArcGIS “Display Route Events” Tool, on the NHD-based whole stream route network. QAQC checks looked for measure anomalies, duplicate feature IDs, and overlapping line features. 8. The displayed events were then exported to a line feature class. Line features were then selected by hydrologic subregion location, and exported to a subregion feature class for the species/run, and subsequently an event table for route transformation. 9. Using the ArcGIS linear referencing “Transform Route Event” Tool, with a tolerance of 3 feet, and NHD flowlines projected to Oregon Lambert (EPSG 2992), a new event table referencing NHD flowline ReachCodes and measures, was created from the subregion event table based on the whole stream NHD geometry route (LLID). The new event table, with NHD flowline ReachCodes and measures, was then displayed on the projected NHD flowlines and exported to a new line feature class. 10. This new subregion species/run line feature class, with NHD flowline Reachcode references and measures, was then projected to EPSG 4269 (GCS North America 1983) for Hydrography Event Management (HEM) import. The feature class ReachCodes and measures were used for HEM import, and the fhdFtrID was linked for the Source_FeatureID field. QAQC checks after HEM import, were a check for multi-part lines, or gaps, using ArcGIS Data Reviewer and a route created from the HEM feature class on the Source_FeatureID field, and a topology check for overlapping line features. 2014-07-31 Jon Bowers ODFW GIS Coordinator 503-947-6097 4034 Fairview Industrial Dr SE Salem Oregon 97302 US jon.k.bowers@odfw.oregon.gov M-F, 7:30-4 email preferred Added optional attributes for describing additional record basis details. Reformatted origin and production coding to reflect current coding scheme. 2015-07-22 Jon Bowers ODFW GIS Coordinator 503-947-6097 4034 Fairview Industrial Dr SE Salem Oregon 97302 US jon.k.bowers@odfw.oregon.gov M-F, 7:30-4 email preferred Recent survey data from ODFW fish research projects, the U.S. Forest Service and the U.S. Bureau of Land Management were integrated into the Oregon Fish Habitat Distribution Database. Changes to seven anadromous salmonid datasets were incremental and distributed broadly across all species’ extents. Selective updates to anadromous datasets were identified and implemented as part of new forestry rules on private lands for salmon, steelhead and Bull Trout (SSBT) species water protection. Attributes for Essential Salmonid Habitat (ESH) were updated. Steelhead in southern Oregon meeting the criteria for ESH designation have now been identified accordingly. 2019-07-29 Ruth Schellbach ODFW GIS Technician Six existing resident salmonid habitat distribution datasets were updated and one new dataset was created (Mountain Whitefish). Data sources included ODFW, BLM, USFS, Oregon state University Ichthyology Collection and Research projects, U.S. Environmental Protection Agency EMAP, and Oregon DEQ-National Aquatic Resource Inventory. 2019-07-29 Ruth Schellbach ODFW GIS Technician New datasets were created for 25 non-native species. 2019-07-29 Ruth Schellbach ODFW GIS Technician A total of 63 species-specific datasets were created for waterbodies. A fraction of these datasets represent reservoirs where existing geometry identified the presence of an anadromous or resident species, however the majority of the datasets are for waterbodies and species that had not been previously mapped. The primary data sources included the ODFW Hatchery Management System, ODFW Fish Finder database as well as ODFW’s Recreational Fisheries Program, Oregon State University Ichthyology Collection, and the publication, “Fishing in Oregon”. 2019-07-29 Ruth Schellbach ODFW GIS Technician Updates were made to existing datasets for 8 non-game species and new datasets were created for 41 non-game species. Input from District Biologists (both documented and opinion) was also incorporated. 2019-07-29 Ruth Schellbach ODFW GIS Technician Data were reviewed by ODFW Fish Biologists as part of a 5 year update to the Essential Salmonid Habitat regulatory layer maintained by the Oregon Department of State Lands. Additionally, public comments regarding potential changes to the data were also provided for consideration. 2021-03-19 0 fhd_Coho Represents linear stream reaches of fish habitat distribution Oregon Fish Habitat Distribution Data Standard Version 3.0 Feature Class 0 fhdBasisEnt Name of survey / verification entity or organization (e.g. agency, tribe, contractor, etc..) Oregon Fish Habitat Distribution Data Standard Version 3.0 Basis Entity String 30 0 0 fhdBasisDt Date of field verification or other habitat / species determination. Oregon Fish Habitat Distribution Data Standard Version 3.0 Basis Date String 8 0 0 fhdProd The means by which the population is currently sustained Oregon Fish Habitat Distribution Data Standard Version 3.0 Natural Natural production Oregon Fish Habitat Distribution Data Standard Version 3.0 Unknown Unknown production Oregon Fish Habitat Distribution Data Standard Version 3.0 Mixed Hatchery and natural production Oregon Fish Habitat Distribution Data Standard Version 3.0 None No current production due to local extirpation Oregon Fish Habitat Distribution Data Standard Version 3.0 Hatchery Hatchery production Oregon Fish Habitat Distribution Data Standard Version 3.0 Production String 15 0 0 fhdEndExtent End Extent Determination String 15 0 0 fhdOEnt Name of the source agency / entity that provides the data Oregon Fish Habitat Distribution Data Standard Version 2.0 Organization/Agency name Originator Entity String 40 0 0 fhdGenus Taxonomic classification at the genus level Oregon Fish Habitat Distribution Data Standard Version 2.0 Valid genus Genus String 25 0 0 fhdSpNm Species common name Oregon Fish Habitat Distribution Data Standard Version 2.0 Pink Salmon pink Oregon Fish Habitat Distribution Data Standard Version 2.0 Steelhead steelhead Oregon Fish Habitat Distribution Data Standard Version 2.0 Coho salmon coho Oregon Fish Habitat Distribution Data Standard Version 2.0 Lahontan cutthroat trout lahontan cutthroat Oregon Fish Habitat Distribution Data Standard Version 2.0 Bull trout bull trout Oregon Fish Habitat Distribution Data Standard Version 2.0 White sturgeon White sturgeon Oregon Fish Habitat Distribution Data Standard Version 3.0 Chum salmon chum Oregon Fish Habitat Distribution Data Standard Version 2.0 Green sturgeon Green sturgeon Oregon Fish Habitat Distribution Data Standard Version 3.0 Pacific lamprey Pacific lamprey Oregon Fish Habitat Distribution Data Standard Version 3.0 Mountain whitefish mountain whitefish Oregon Fish Habitat Distribution Data Standard Version 2.0 Coastal cutthroat trout coastal cutthroat Oregon Fish Habitat Distribution Data Standard Version 2.0 Western brook lamprey Western brook lamprey Oregon Fish Habitat Distribution Data Standard Version 3.0 Sockeye salmon sockeye Oregon Fish Habitat Distribution Data Standard Version 2.0 Rainbow trout rainbow Oregon Fish Habitat Distribution Data Standard Version 2.0 Eulachon Eulachon Oregon Fish Habitat Distribution Data Standard Version 3.0 Redband trout redband Oregon Fish Habitat Distribution Data Standard Version 2.0 Chinook salmon chinook Oregon Fish Habitat Distribution Data Standard Version 2.0 Westslope cutthroat trout westslope cutthroat Oregon Fish Habitat Distribution Data Standard Version 2.0 Species Common Name String 30 0 0 fhdOrig How the species / run came to exist in an area originally Oregon Fish Habitat Distribution Data Standard Version 3.0 NonNative Non-native origin. Species not indigenous to Oregon that were introduced to waters of the state. Oregon Fish Habitat Distribution Data Standard Version 3.0 Unknown Unknown origin Oregon Fish Habitat Distribution Data Standard Version 3.0 NativeNonLocal Native origin, NOT present within the species mgt. unit (SMU) prior to European settlement (1800) Oregon Fish Habitat Distribution Data Standard Version 3.0 NativeLocalReintro Native, locally reintroduced. A species from within the SMU that has repopulated an area within the SMU that had become void of that species. Oregon Fish Habitat Distribution Data Standard Version 3.0 NativeNonLocalReintro Native, non-local reintroduced. The original stock within the SMU was extirpated and native, non-local fish from outside the SMU were introduced to re-establish the historical distribution. Oregon Fish Habitat Distribution Data Standard Version 3.0 NativeLocal Native origin, present within the species mgt. unit (SMU) prior to European settlement (1800) Oregon Fish Habitat Distribution Data Standard Version 3.0 Origin String 25 0 0 fhdSubSp Taxonomic classification at the subspecies level Oregon Fish Habitat Distribution Data Standard Version 2.0 Valid subspecies Sub Species String 25 0 0 fhdNMF Native Migratory Fish designation based on Oregon Administrative Rule. Oregon Fish Habitat Distribution Data Standard Version 3.0 yes Qualifies as a native migratory fish according to Oregon Administrative Rule (Division 412.635-412-0005) Oregon Fish Habitat Distribution Data Standard Version 3.0 no Does not qualify as a native migratory fish according to Oregon Administrative Rule (Division 412.635-412-0005) Oregon Fish Habitat Distribution Data Standard Version 3.0 Native Migratory Fish String 3 0 0 fhdBasisPrj Name of agency / entity project Oregon Fish Habitat Distribution Data Standard Version 3.0 Basis Project String 30 0 0 fhdStNm Stream name from GNIS Oregon Fish Habitat Distribution Data Standard Version 2.0 Stream's name from hydrography dataset Stream Name String 50 0 0 fhdONm Name of the source originator (person) that provides the data Oregon Fish Habitat Distribution Data Standard Version 2.0 Person's name Originator Name String 30 0 0 fhdLifeHst Life history characteristics Oregon Fish Habitat Distribution Data Standard Version 2.0 FluvAdfluvRes Mixed fluvial, adfluvial and resident Oregon Fish Habitat Distribution Data Standard Version 2.0 Unknown unknown Oregon Fish Habitat Distribution Data Standard Version 2.0 AnadRes mixed anadromous and resident Oregon Fish Habitat Distribution Data Standard Version 2.0 Adfluvial Lake resident that migrates to a stream / river Oregon Fish Habitat Distribution Data Standard Version 2.0 Anadromous Spawning in freshwater - migrating to saltwater Oregon Fish Habitat Distribution Data Standard Version 2.0 FluvAdfluv Mixed fluvial and adfluvial Oregon Fish Habitat Distribution Data Standard Version 2.0 Fluvial Migrating within a stream / river system Oregon Fish Habitat Distribution Data Standard Version 2.0 Resident Year-round resident only Oregon Fish Habitat Distribution Data Standard Version 2.0 AdfluvRes Mixed adfluvial and resident Oregon Fish Habitat Distribution Data Standard Version 2.0 Life History String 30 0 0 fhdBasis Basis for fish habitat distribution feature designation Oregon Fish Habitat Distribution Data Standard Version 2.0 DocObsFish Documented observation of fish Oregon Fish Habitat Distribution Data Standard Version 2.0 HabitatEval Habitat evaluation based on modeling Oregon Fish Habitat Distribution Data Standard Version 2.0 IndivProfOpinion Individual professional opinion Oregon Fish Habitat Distribution Data Standard Version 2.0 DocObsHabitat Documented observation of habitat Oregon Fish Habitat Distribution Data Standard Version 2.0 ConcurProfOpinion Concurrence of prossional opinion Oregon Fish Habitat Distribution Data Standard Version 2.0 UndocObsFish Undocumented observation of fish Oregon Fish Habitat Distribution Data Standard Version 2.0 Record Basis String 30 0 0 fhdAccess Access Method String 15 0 0 fhdBasisD Detailed description for the fhdBasis attribute element. Oregon Fish Habitat Distribution Data Standard Version 2.0 This is a field for storing descriptive text. Basis Description String 254 0 0 fhdRefID Reference identifier - link to a reference for the data source (e.g. fish presence database, fish habitat survey report, documentation of a concurrence of professional opinion). Generated by the Horizontal Steward. Oregon Fish Habitat Distribution Data Standard Version 3.0 0 99999 Reference ID Integer 4 0 0 fhdBarrierFtrID Barrier ID at End Extent Integer 4 0 0 fhdBasisNm Name of surveyor / observer; one who made determination for opinion-based data. Oregon Fish Habitat Distribution Data Standard Version 3.0 Basis Name String 30 0 0 fhdESH Essential Salmonid Habitat Designation Oregon Fish Habitat Distribution Data Standard Version 2.0 Not applicable species or habitat (historical) that by definition does not qualify as ESH Oregon Fish Habitat Distribution Data Standard Version 2.0 no Not designated as Essential Salmonid Habitat Oregon Fish Habitat Distribution Data Standard Version 2.0 yes Designated Essential Salmonid Habitat Oregon Fish Habitat Distribution Data Standard Version 2.0 Essential Salmonid Habitat String 3 0 0 fhdFtrID Framework unique identifier for the fish habitat distribution feature (generated by the Horizontal Steward). This has now been replaced by the PermanentID field related to the NHD and is being maintaine by ODFW as an administrative attribute (non-standard) Oregon Fish Habitat Distribution Data Standard Version 2.0 (no longer present in version 3.0) Sequential unique whole numbers that are automatically generated Feature ID Integer 4 0 0 fhdRevDt Date of data entry into or revision in the Framework dataset Oregon Fish Habitat Distribution Data Standard Version 3.0 Date as an 8 character string Revision Date String 8 0 0 fhdRun General run timing for anadromous species Oregon Fish Habitat Distribution Data Standard Version 2.0 Spring spring Oregon Fish Habitat Distribution Data Standard Version 2.0 Fall fall Oregon Fish Habitat Distribution Data Standard Version 2.0 Winter winter Oregon Fish Habitat Distribution Data Standard Version 2.0 Summer summer Oregon Fish Habitat Distribution Data Standard Version 2.0 Unknown unknown Oregon Fish Habitat Distribution Data Standard Version 2.0 NA Not applicable (resident species) Oregon Fish Habitat Distribution Data Standard Version 2.0 Run String 30 0 0 fhdBasisMethod Name of survey method or protocol (e.g. Salmon Spawning Survey) Oregon Fish Habitat Distribution Data Standard Version 3.0 Basis Method String 254 0 0 Shape Feature geometry. ESRI Sequential unique positive integer Coordinates defining the features. Shape Geometry 0 0 0 OBJECTID Internal feature number. ESRI Sequential unique whole numbers that are automatically generated. OBJECTID OID 4 0 0 fhdSp Taxonomic classification at the species level Oregon Fish Habitat Distribution Data Standard Version 2.0 Valid species Species String 25 0 0 fhdUseTy Fish habitat use (e.g. spawning) Oregon Fish Habitat Distribution Data Standard Version 2.0 Spawning Primarily spawning with some rearing Oregon Fish Habitat Distribution Data Standard Version 2.0 Migration Primarily migration Oregon Fish Habitat Distribution Data Standard Version 2.0 ResidentMultipleUses Resident species only, multiple uses including spawning, rearing and migration. Oregon Fish Habitat Distribution Data Standard Version 2.0 ForageMigrateOverwinter Habitats outside primary spawning and rearing areas that support foraging and may include migration and/or overwintering use. These habitat can serve to connect isolated populations of fish (e.g. bull trout). Oregon Fish Habitat Distribution Data Standard Version 2.0 Unknown Specific use cannot be specified Oregon Fish Habitat Distribution Data Standard Version 2.0 Historical Habitat used, or potentially used, historically but not currently Oregon Fish Habitat Distribution Data Standard Version 2.0 Rearing Primarily rearing with some migration Oregon Fish Habitat Distribution Data Standard Version 2.0 Habitat Use String 25 0 0 fhdComment Comment that provides additional, relevant information about the fish habitat distribution feature Oregon Fish Habitat Distribution Data Standard Version 2.0 Text comments Comment String 254 0 0 Shape_Length Shape_Length Double 8 0 0 Length of feature in internal units. Esri Positive real numbers that are automatically generated. Primary attribute for mapping purposes is the fhdUseTy field. This field describes the use of the habitat, by a particular species and run, within the particular reach (e.g. Spawning, Rearing, Migration, etc.). Secondary attribute is the fhdBasis field to understand the source information behind the creation of the record. While the data are managed on the NHD, NHD related attributes are stripped from the data previous to publication. Optional Basis detail attributes were added in July 2015 and are inconsistently populated. Optional attributes for tracking associated barriers, anadromous access and end extent determinations were added in April 2020. These attributes are also not yet populated. Oregon Fish Habitat Distribution Data Standard Version 4.0 dataset EPSG 8.9.3(9.0.0) Simple FALSE 0 TRUE FALSE