20170824 12323600 1.0 FALSE TreeInventoryWeb 002 Projected GCS_North_American_1983 Linear Unit: Foot_US (0.304801) NAD_1983_StatePlane_Pennsylvania_South_FIPS_3702_Feet <ProjectedCoordinateSystem xsi:type='typens:ProjectedCoordinateSystem' xmlns:xsi='http://www.w3.org/2001/XMLSchema-instance' xmlns:xs='http://www.w3.org/2001/XMLSchema' xmlns:typens='http://www.esri.com/schemas/ArcGIS/3.1.0'><WKT>PROJCS[&quot;NAD_1983_StatePlane_Pennsylvania_South_FIPS_3702_Feet&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;,1968500.0],PARAMETER[&quot;False_Northing&quot;,0.0],PARAMETER[&quot;Central_Meridian&quot;,-77.75],PARAMETER[&quot;Standard_Parallel_1&quot;,39.93333333333333],PARAMETER[&quot;Standard_Parallel_2&quot;,40.96666666666667],PARAMETER[&quot;Latitude_Of_Origin&quot;,39.33333333333334],UNIT[&quot;Foot_US&quot;,0.3048006096012192],AUTHORITY[&quot;EPSG&quot;,2272]]</WKT><XOrigin>-400</XOrigin><YOrigin>-400</YOrigin><XYScale>999999999.99999988</XYScale><ZOrigin>-100000</ZOrigin><ZScale>10000</ZScale><MOrigin>-100000</MOrigin><MScale>10000</MScale><XYTolerance>8.983152841195215e-09</XYTolerance><ZTolerance>0.001</ZTolerance><MTolerance>0.001</MTolerance><HighPrecision>true</HighPrecision><WKID>102729</WKID><LatestWKID>2272</LatestWKID></ProjectedCoordinateSystem> 20230501 14385700 20230501 14385700 Esri ArcGIS 13.1.0.41833 TreeInventoryWeb File Geodatabase Feature Class dataset EPSG 6.12(9.0.0) 0 Simple FALSE 0 TRUE FALSE TreeInventoryWeb Feature Class 0 OBJECTID OBJECTID OID 4 0 0 Internal feature number. Esri Sequential unique whole numbers that are automatically generated. id id String 254 0 0 uniqueid uniqueid String 254 0 0 address address String 254 0 0 suffix suffix String 254 0 0 street street String 254 0 0 onstr onstr String 254 0 0 fromstr fromstr String 254 0 0 tostr tostr String 254 0 0 side side String 254 0 0 site site String 254 0 0 spp spp String 254 0 0 dbh dbh Double 8 0 0 stems stems Double 8 0 0 cond cond String 254 0 0 observe observe String 254 0 0 maintprim maintprim String 254 0 0 inspect inspect String 254 0 0 tree_ht tree_ht Double 8 0 0 crwn_base crwn_base Double 8 0 0 crwn_wd1 crwn_wd1 Double 8 0 0 crwn_wd2 crwn_wd2 Double 8 0 0 dieback dieback String 254 0 0 missing missing String 254 0 0 ohutility ohutility String 254 0 0 hsdamage hsdamage String 254 0 0 grow grow String 254 0 0 clearance clearance String 254 0 0 space_sz_w space_sz_w Double 8 0 0 space_sz_l space_sz_l Double 8 0 0 landuse landuse String 254 0 0 owner owner String 254 0 0 ward ward String 254 0 0 neighbor neighbor String 254 0 0 probfail probfail String 254 0 0 szdefect szdefect String 254 0 0 target target String 254 0 0 otherisk otherisk String 254 0 0 rating rating Double 8 0 0 stcost stcost String 254 0 0 trcost trcost String 254 0 0 inv_date inv_date Date 8 0 0 inv_time inv_time String 254 0 0 inspect_dt inspect_dt Date 8 0 0 inspect_tm inspect_tm String 254 0 0 notes notes String 254 0 0 active active String 254 0 0 geog1 geog1 String 254 0 0 geog2 geog2 String 254 0 0 geog3 geog3 String 254 0 0 geog4 geog4 String 254 0 0 size size Double 8 0 0 cultivar cultivar String 254 0 0 memorial memorial String 254 0 0 carteid carteid String 100 0 0 created_user created_user String 255 0 0 created_date created_date Date 8 0 0 last_edited_user last_edited_user String 255 0 0 last_edited_date last_edited_date Date 8 0 0 shape Shape Geometry 0 0 0 Feature geometry. Esri Coordinates defining the features. GlobalID GlobalID GlobalID 38 0 0 20230501 /9j/4AAQSkZJRgABAQEAAQABAAD/2wBDAAgGBgcGBQgHBwcJCQgKDBQNDAsLDBkSEw8UHRofHh0a HBwgJC4nICIsIxwcKDcpLDAxNDQ0Hyc5PTgyPC4zNDL/2wBDAQkJCQwLDBgNDRgyIRwhMjIyMjIy MjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjL/wAARCADIASwDASIA AhEBAxEB/8QAHwAAAQUBAQEBAQEAAAAAAAAAAAECAwQFBgcICQoL/8QAtRAAAgEDAwIEAwUFBAQA AAF9AQIDAAQRBRIhMUEGE1FhByJxFDKBkaEII0KxwRVS0fAkM2JyggkKFhcYGRolJicoKSo0NTY3 ODk6Q0RFRkdISUpTVFVWV1hZWmNkZWZnaGlqc3R1dnd4eXqDhIWGh4iJipKTlJWWl5iZmqKjpKWm p6ipqrKztLW2t7i5usLDxMXGx8jJytLT1NXW19jZ2uHi4+Tl5ufo6erx8vP09fb3+Pn6/8QAHwEA AwEBAQEBAQEBAQAAAAAAAAECAwQFBgcICQoL/8QAtREAAgECBAQDBAcFBAQAAQJ3AAECAxEEBSEx BhJBUQdhcRMiMoEIFEKRobHBCSMzUvAVYnLRChYkNOEl8RcYGRomJygpKjU2Nzg5OkNERUZHSElK U1RVVldYWVpjZGVmZ2hpanN0dXZ3eHl6goOEhYaHiImKkpOUlZaXmJmaoqOkpaanqKmqsrO0tba3 uLm6wsPExcbHyMnK0tPU1dbX2Nna4uPk5ebn6Onq8vP09fb3+Pn6/9oADAMBAAIRAxEAPwD3+iii gAooooAKKKKACiiigAooooAKKKKACiiigArhPiL4PGt2BvbK0ebU12qpEmPl78Hiu7oqKlNVIuMi ZRUlZnnvw2ttX0TSL3+3BLbWiYeLznGFHO76V0+jeLdG1+5lt9OuvMljG4gqRkeoz9a0NUsE1TS7 qwkdkS4jaMsvUAjFecyeGG+HNhea3YXMl1csPJjjZOArEHJ9xisPfopJaxW/cz96mklsj1GvKL34 U3194klu576F7SWXzH4IbBP3fy75re+HXinUvEcF2uoqpaIgq4XbkGu5qnGniIqT2HaFWKbPN9b8 D6T4Z0C8v9N043t8DiMTr5wTJ7L0OPcGvPk0/wAVeMZwfJnmRRgFhsjQegHA/KvonrTVRUGEUKPQ DFRUwkZPR2XZEyoKT00R5PoXwfbckutXYwCCYYe/sW/wr0bSvDej6Ln+z9PggY9XC5Y/8CPNalFa 06FOn8KLhSjDZBRRRWxoFcb448D/APCV+RNDcR288IIy0ed/1PWuyoqJwjOPLLYmUVJWZ4P4q8H2 vgy0sZWuZbi7kc524ReOR6mvWvB+vN4j8PQ38kQikyY3UNkEjHNeXeOvG17daneaW1pb/Z4maNfM j3N06g9q0PhL4im/tCXRriRmjlUyQrjhSOv6V59GpCFflhs9PmctOUY1bR2PX6KKK9M7AryD4orr 0OtJdxzSx6coQQlZQoDgZPHrnNev1zPjTwr/AMJVp0UAuvIaFi4JGQeO9YYmm502luZVouULI0fD epRaroNpcx3AnYxgO27J3d8+9atcR4HOj6FC+hw6xFdXW8uwHAB7gV1Vrq+nX1xJb2t5DLNH95Eb JH+cVdOd4q+5UJXir7l2iiitCwooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACkZVdSrK GU9QRmlqnqt+ul6VdXzruWCMvtzjOO1JuyuwehYht4LZNkEMcS+iKAP0qSuB8E/EC58UavNZXFnF EAm9GjY9B2IPWu+qKdSNSPNHYmElJXiFFFFaFBRRRQAUUhIAJJwB1Jrnda8caJotqZnuluGDBPLt yGOamUoxV5MTklqzo6RnVQSzAADJya8W1j4varcTMmlwxWkXZnXe549+Oue1cpfa5qV3qa6leXsh NxksIZOVU8EY7cdq4546mvh1OeWJittTufEOhab458Vs2k63aecFCyQlSDgdSD/Ea7Xw94F0jw/L DdxQl75ECmUscZxgkD35rifAOh6fYpL4rjv5Xt7VXzC0IDAY5ye/4V0OifFLS9VubqO5hayjijMq yO4IYDqPr6DvSounfnqJKTFT5L80t2d5RWHoPi3SfEjzJp8zs8J+ZXXBI9R7VuV3RkpK8WdKaaug pksfmwvHnG5SufTNPopjPKj8P7Tw7qT6jd+IIYEO7y/MUKWJHPf+VcT4Y1BvDvja2l82N4/PMLSv kKUY7S35c16B8WND+1WkOrPeLFHbrs8ooSWJPY15VqK2n2a0e2naR9pRwYgm3B46dc5rx8QlSnaK tbXc8+r7ktFax9PqwdQykFSMgjvS1geC9WGs+FbK5/dhwnluqH7pXj8PXHvW/XrRkpJSR3p3V0FF FFUMKKKKACiiigAooooAKKKKACiiigAooooAKKKKACmSxJNE0cqB0YYZWGQRT6KAOcv5PD3gu1fU WtYrfzGxmJPmYntVzw74isvEunm7st4VW2srjBU0niLw5ZeJrBbS9MiqrblKHGD/AFpvhrwzZ+F7 F7WzklcO25zIc5PsO1YpTU7K3KZ2kpabG1RXNeIfHWi+HJ2trqZnugobyY1JPOcZPQdP1FcJcfGK 8k1CMWunxJbbgGEjZZh/SlUxNKDs3qKVaEXZs9T1LV7DR4BPf3UcEZOAXPU1yy/E/RJdbh06BZZV lcRidR8uTjH6nFc58R77RtaksbV9UEF3GoYpsLINwB+Zh0xXG+CILafxjYW9zAJELnawYrhhlg36 VzVcVNVVCNrGU60lPlidX8Vb3WodVCxzyx6dsUAI+ATjnPeuCjt4LewF5M8dyJSUEQchkbHDGvQv E/w61/WvE9xdJLC1tM5Ks0n3F7DH09K6bw78ONN0mxnt77Zf+dgsHTAUj0PWspYepVqt208zN0pz m3Y8UsdN1DVZVhsLORw5x8inHUdT9QK7fRvhHqVxIsmqTR28PBKKdzEf0r2CysLTTrcQWdvHDEOQ qDFWa2p4CC1m7mscNFfFqYmleFdM0jRptLt4ma3mB8wSNu3ZHNefL8Hp21cl76NbAtuIRTuxn7o/ DFeuVyvjvxTN4W0mGe2hWWaaTYu88DjJNb1qVLlvNaI0qQha8lohPCnge08KTTzw3Usryjad+AMZ 4rq68LvdX8YeMYbe8soJxFEREwtCcFxzkjt2617LoouxotmL7d9qEQ83djO73xSw9SMvdhGyQqU4 vSK0L9FFFdJsYnizRotc8P3FrJE0jhd8aqcEsOleFaRoEt5rTaDqFx9hdiSPMxgSBTgH86+kK+ef H2m3Ok+NLpyWPmsJ4pAPXp+RBrz8dBK1Sxy4mKVpWPZvB/hr/hFtGNibjzy0hkLYwASBwPyroK5W fxcmk+B7HW7yJ5Hmij+RB1Zhn/Gq+hfEK11fT/tL2U0ThyhVfmHGO/411RqU4Wgn0NlOEbRR2VFe cfDzxfrWvardW2pgNGE3q3l7dpBxivR6qlUVSPNEqE1NXRQ1q/8A7M0W7vQygwxll3dM9q8Y0j4q a5aaj5t+6XlvIw3xlQpUf7OOleueKdCPiPQ5NOE/kl2Db8Z6dq8r1z4c3uh6AXiQX1xJJ8xjj5jU A5NcuK9tzJw2RhX9pe8dkd/pvxK8OalO8P2l7ZlAIM67Q2ewIz0966qC5guohLbzRzRk4DxsGH5i vleWCeDPmwunOPmUjn0qe21W/skCW93NEm4NtVyBn1rCGYSWk0ZxxTXxI+pqK8M0Txr4p1TxDaeX PNLErqrxqmV29CSK9xZ1QZZgv1OK76NeNVNxOmnUU1dDqKKK2NAooooAKKKKACiiigAooooAKKKK APEfi5YWtt4jiuEaZrm6jDyBmGxQPlAUYyPumlvvAp1bw3peo+HdO2mSPdMrT7mJP14/lXsF/pGn 6nt+22cM+3GDIoOMHNWYIIraFYYI1jjQYVVGABXG8GpTk5bM53QTk29meYaV8J/tdpb3Gs3tzHdj /WIkgfgfdwSOP1r0qDT7S3cSR28QmwAZdg3tgYGT1NWaK3p0YU/hRrCnGOwUUUVqWFFFFABUNzaW 97CYbqCOaMggrIoYenepqKAODi+Ifh7TtZbRrezaCCNijSxxhUDD/ZHP41q6J480bX9VfT7MzCYA lS6YD464/wDr15D8QdK/sfxfcbIjFbzESx4PUHr+uaz7W9vfDmqwavYQyQRNzCZBkMvcZ715f1up CbjLZP8AA4vbzjKz6H0rVO81SysIJpbi4jUQoXdQwLAD2615P4i8ca1rHhi1vtPWSziV3S6aJuMj aBz1wd36VgaBoGo6zFPrVzL51miu9xmch2HOR+YreWL97lgrmrr62irnqEHxD0/VNM1ObS4pnubS IyLHIh+f34zXK+GfiM91f3EfiprY2yr5kW635SRccDA+vWvPtN1DULK+kOjtNE8oK7Ysk7fSvWLr wVL4x8OaZdXcxs9QSNt48oAMS3JYeuBWEK1WtrHddOjMo1J1NVuvuOvntNG8WaPGJEivLKT5kIPQ 9MjHQioLHwZoGn2wgg09NuckszEk+uc1Z8OaInh7RINNSZpli3YdhgnJJ/rWrXoKCdpSWp1qKerW pm6VqOkX/m/2XPbS7G+fycdfwrSrhvAvgW68KXlzcXF5FN5ybAiJjAzkHJ/lXc0UnJxvNWYQba95 WCiori5gtIjLczRwxjq8jBR+ZpYJ4rmFZoJEkiYZV0OQfxrS5RVv9G07VIGhvLOKVGJJBXuRjP1r mtR+GHhy+GYoHtX45ibj8jXZ0VEqcJfEiXCMt0cx4T8F2vhMzvBcyTPMMMXAAArzr4n3+qSeKhBD JcLbxIojEZIUsec+54H5V6h4ug1O58NXUOjlxeOAF2MFOO+Ca5j4aaRr2n/bDrMUywsQ0ImkDYfJ DEDkg+/865asL2oQTS7mNSN7U4qyOm0zVYNP8PaX/a93HBcyW8YYTSAMzED175rcBDKGUgg9CK8v +JXgzV9X1EapYD7SgQIYAcMuO4yefwrm5bjx3oOhW9lsvYYWzhlXeQDwFyM7fp1pvESpycZRdl1B 1XBtNaHtqX9pJdNbJcxNOo3GMONwHripUljkzsdWwcHBzivlo3N7bXry+bNHdZIkckh8ng571NZ6 hqdjBJLaXs8EbMA/lzbcntwDk/WsVmPeJmsX5H1FRXiPhz4ma42rWNtfXML2pIjkZ48Ej+8SO9er 6V4o0bW7mW30++jmlj5K8gkeoz1rrpYiFXY6IVYz2Neiq/260+1/ZPtUP2jBPlbxu49uvcVYrc0C iiigAooooAK8mg+IOuTeN0smjRbMzmLy9h6Z65616zUTpBEXuWjQMq/M+35sDnr1rKpCUrcsrWIn Fu1nYlorjdF+I2m634g/sqC2uFLZEcrAYYjrx2FdlVQnGavF3HGSkroKKKgub21s1DXNzDCD08xw ufzqyiegkDqcV55rXxa0qzSWLTYZbu4VtoLDbGeeTnr+neuR8ReKtY8U6Db3kTrZxwsUnSK5C727 Hbndj865p4unG6jqzGVeK21Pca8v8f8Aj/UtG1WXStPjSPEY3TMMnJ9KseBfHtnLBY6JevcPfH5P Nb5lY9hkc0nxT0LVtWFk2m2JnijDGUoF3ZOAPc9T7VFWq6lHmpPUmc3KneDPKrmS+vr0XeqTO74D EztgsvoK6vXPHdhe6Hb6XpujxLFEMfv13bRjquDWjb/CvVtXgt7zUtQMFy4xNHKgdlA4GCDg8Cu7 0LwFoegh2igNxI67Xac7gR/u9K5qWHrapaJ9XuYwpVNelzyseFNc8R6fZ3mm2ccdpKAhiSTChhwW IP0FeleBfBs3hiyuUvJo5muQpdFXIXjke9dgqKihUUKo6ADApa7KeFhCXNuzohRjF83UpWuj6bZT vNbWMEUjnLMqAGrtFFdCSWxtawUUUUwPLfA3ijxLqfilrbUxKbdlbcGiwEIBI57V6lXnnhv4jrrX if8As0acsUcpISRWGSR3P4V6HXPhmnDSXMZUWuXR3OP+IHhe/wDE+nW8NjOiNCxYo5ID5xirngjQ Lrw5oAsbyRHk8wvlOgB7VzHxJPihtQtk0lLr7HsGTAOrk98fSu48PNet4fsjqIcXnlDzQ4w2felB RdduzuvuFGzqN21NOiiiuk2CiuY8V+N7Hwq8MVxFLNNKCVVOw9TmtvS9Tg1bSoNQt9whmXcNwwR/ nFQqkXJxT1RKkm7dS5SEAjBAP1rkl+JPhttQktDebdmR5rKQhIOODXSWWo2eoxebZ3MU6ZxmNgaI 1IS+F3BSjLZnLT/DHQLnV3v5Vmbexdoi52lic5/+tXAp8JNdkvmiZ7eOAEHzd2Rj2Fe40VjPCUp7 ozlQhLoeIav8J9T062luLa6W5WNdwVEO9j6VxtlqGpeH76U2sstpc7TE/ZgD2r6hrFvvCWhalffb LvTopJ/4mP8AFxjmsKmBV70nYznhlvB2PGfD1hcnxLYX+palDDM8wkYXDne3J6/XFe0ap4p0bR7i OC+vo45ZMFV6nB715z46+Hmq3Wsy6lpafaUnILRggGPoAB6ivO9XkujfGG9ZmuIAInJfd93jrWSq SwyceXrv3M+eVG6sfStnq+nagJDaXkMwjOH2t0q4rK6hlYMp5BByDXynFczQbhFLJHu6hGIz+Va9 p4w16xtobe31GZIYSCiZz/kVccxX2olxxS6o+lqK8Rb4u619kgjSCATL/rJCM7/w7Vv6R8YLW4uf L1OzNtERxIhLc+4rojjKMna5qsRTfU9PpskayxPG4yrgqR6g1zmmePPD2qhvKv442EgjCzHYWJ6Y z610isrruVgQe4NdEZRkrxdzVSUtjxTxX4G1HTfEcc3h6xnFuSvltG2SH7/SvVjqL6R4VS/1IOZY LZWnHVi2Bn9a1SQOpArjvHvivTNH0mWwnVLm5uoSY4TypGcZbHbr+VYezhQUpp2uZckad5JnE6v8 WdUvV2aVbC1AOWcjexH9Kl1Hwz4j8cWun6v5kYLxBHjclNpHU4ridP07VdYMo02xZyPmYQqehPT6 V754Pt9RtfDNpBqgYXSDDBiCcdq5KCliG1Uba/Awp3qt8+xzei/CnSrKWG4vXe4kCDfE33N23DfX rWH4m+F9/da40ukJbRWUmAIwdoTAHavXaK7JYWk48tjodGDVrHnvhf4XWuj3MF/e3Tz3cTh1CfKi kdPc16FRRWlOnGmrRRcYRgrRCiiitCgooooAKKKKACiiigDIs/C2h6ffG9tdNgiuCc71HT6DoPwr XoopKKWyEklsFFVNUS5fSrpLM4uTGwjIOPmxxXz6934p8Kambmd7q2uCeTIcq/8AQ1hXxHsrXV0Z 1KvJbQ9w8VeJ7fwrpa3s8LzF5BGkaHGTyevbgGk8JeKIfFWlG8jt3gZH2OjEHBxng9x+VeIeJfG2 o+KLW1t71YkWD5jsGN7ev5V0PwghvH16eaKQ/ZUjIlXfjk9Djv3rnji3Ouox+EyjXcqllsem+IPB ukeJZI5b+OXzYxhXjfBxnp6VqadptrpWmxafaIUt4lKqpYkgE56/jVuiu5QinzJanSopO9jyrWvg 6sjtLpGolSefKuRnn/eH+Fcl/wAI74x8Iyvd20NxDj5WktzvBHuPT6ivoKggEYNc08FTbvHR+RjL Dweq0PCtM+K2v2EccFwkF2qE7mlUhz+IP9K9M8IeNrbxZHclLWS2e3wWDMGXac4Ofwq/qXhLQtVf fd6bA8n98LhvzFUbfwPpul6Pf2ekqYJruIxmV2LHvj+dKnTr05ayughCrF6u6Ny11XT72VorW9t5 pE4ZY5AxH5Vcr591LwZ4m8L3AuoVkcKSVntmOR7nuKt6b8UfEOnNFFdlbmNOGEq4cjPr1zUrG8rt VjYlYiztNWPd65fxB4C0PxAC8lv9mue00ACkn3HQ1Tsfif4dure3ead7eWXAaNlzsPufSuzRldFd TlWGQR3FdN6dVW0aNrwmu54Rr/wu1vSi8lkBqFuOcxjDj6r/AIZrN0HwJq+uyXESwvatEuVa4jZU Yg4I3ev519FUmMA4AFczwFPmutuxj9Whe582a14S1fQbwwzQiXbyHhO8EeuOv5isN9xbcRjJ9MCu v8Q6P4l8Na0+oytKWdmkFxExYc+prpLCTSfiDo9lpuoXvkavFuKGOMKG7DPr61wexUpOK0fZnN7N NuK0Z5Xkj3rW07xRrelRRx2eozxRRtuVA2VH4GvQNS+DkixIdN1AMwHzLMuMnnPI/Cubvvhh4js5 kjigS5V8fNG3AOO+aTw9em7pP5C9lUj0MOfxRrdykyS6pdMspBdS55wcjHpWx4Wg0PX5LbTNZn1B bwy7IJEbcgTrsx2yS3Nc7qWk32k3b293bvHIhwSVOD9D3qC3uJrS5juYJDHLEwZXU8g1CnKMvf19 SVJp+8fT+k6XbaNpsNjaKRFEuAW5J9yfWrtc14K8TQ+I9EiY3AkvYkAuBtwQ3rXS170JRlFOOx6c WmroKKKKsoKKK8t8W/E6/wBI1y502xtYdsHymR8kliv/ANcflWdWrGkryInOMFdnqEkiRRl5HVEU ZLMcAVFa3lrexmS1uIp0B2lonDDPpxXgK614k8T3bWl1qUkdvcHDmQ7Y1HJr0D4X6UNL+3odRtLl 2IykL5K1hTxXtJJRjoZwrc8rJaHoteY/EPxZ4g0jW4bTSw8VuFVi4h3eYx5xkj+VenU1o0fG5VbH TIrerBzjaLsaTi5KydjN0/V430qym1CeG3uJ41JRzsJJ9ATmsjU/iN4b0ueSCS7eWWMkMsMZbkds 9K5zxv4D1rX/ABCL20ni8hgqBWYjy8d6hj+DULFTNqsvKDcFUZ3d+fSueVSvdxhHbqzJzq3tFHpO mala6vp8V9ZSeZbyjKtjHsat1naFo8Og6PBptvJJJFDnDSHJOST/AFrRrrjey5tzdXtqeJXXxX19 L2cJDAsYJVFKfd5616N4D8Q3PiXw79su1RZklMTFOjYAOfbrXnvjXwp4l1DxZcTWenvJbynERjKh SoHfoB3610Xwx8Pa9oc17/acLw20ijYjSgjeDydoz27159GVZVuWV2jlpuoqlnex6PVa90+01K3M F5bxzxHqrrmrNcz4m8caX4Xmjgu1mknkG4JEoOB6kk13zlGKvLY6ZNJXZy/iL4R2twJJ9FmMEmMi BzlScjoe3Ga4FtN8S+DbwXXkz23lsCXQ5RsepHBr6AivF1HSBd2DFhNEXhJG3JI469K+fdSn8SaD qsn9o+eJHY7hcjzI5QD78EfSvOxVKnC04przRy14RjaSPV/A/jl/EkV2L2KOA2yhi4bjFXNO+IWi aprw0m3eQyMSqSbflZh2H615fL4m0zVPDMmkxWdvpN3Iyl50B8uUdwSMkfQ5FQeEdA1uDxTpt1DZ zNDHOjNPFhk2bsH5hx0zx1pxxNT3Yx17sFWlolqfQVBIAyTiiuJ+I9j4gvtNgTRBMVVi0whkCsRj j3P4V31JckXJK51Slyq52oYHoR+dLXzvc2XjfSyJJk1aMIowyszBV69QSO1Ph8deLrApuvZyoJOJ ogc4GMdM1yfXkvii0YfWUt0z6FIBGCMisHWvB2i66mLq0VZO0kY2sK8oi+LXiNBh1tHwAMmMj8eD WpZ/GW9AjW70uFzv+d45Cvy57A9/xpvGUJq0vyH7elLRm1efCDS5btJLW8mgi/iQgN27GvQ4YhDB HECSEUKCe+KLeYXFvFMAQJEDAEg4yM9uKkrphShC7irXNYwjHWKCiiitCzA8aQ/avCmoW6zRxyPE du9sZrw/wHL5XjbSjk8zBePfiuw8feD/ABNrHiOS6tbdrq1bCxASqNgx6EjFWfBPwyvtO1WDVNXe OMwNvjgjO4luxJ6D8M15tWNSrXVo2t1OSalOorLY9Wooor0jrILm0gukKzQxyZBA3oDivGdW+Emr 25klsZYbpAchB8rd+xr22isa1CFVe8ZzpRnueJeEddtvAV5c2epwSm7mdVkEbBljX39/avaopVmh SVM7XUMM+hr5l8SRyx+Ib4yq6lp3I3KVyM9s16d8L/GLXi/2LqFxLLcDm3LLkbQORn/GuPC4jll7 J7dDnoVbPkZ6fRRRXpHYFZ1zoOlXl2t1cafbyTrnDsnPP8+laNFJpPcTSe55p478Caprmpw3GliB bcIE8rOzB5yfSrPgTwDfeGdSe9u7mF9yFPLTJ/HNehUVj9Wp+09p1M/Yx5ubqFFFFbmoUUUUAFFF FABRRRQAV4t4n8KeJNZ8ZySTWk01q0nyNuGBGP5V7TRWNaiqqszOpTU1ZlbT7GHTNPgsrcEQwoEU McnFM1LSrHV7Y29/bRzxHs4zj3HpVyitbK1i7K1jyXxD8IsK8+hTknr9nlP8j/jXDxXHiPwZfEKb mykBwVI+Vv6GvpKqt/p1nqds1ve20c8TcFXXNcdTBxb5qbszCWHT1jozzvw38Wre42W2uRiCQ8fa EHyfiO1elQXEN1Cs0EqSRsMqynINeVeJvhNtU3GgMTjJa3kb+RridL1/X/B960atLDg4aCYHafwN QsRVovlrK67kqrOnpUXzPo8gEYNRSW8MqFJIkdSMEMoINc/4L8VDxXpT3BgMMsLBJB2J9q6Wu6Ml OPMtjpTUldGbL4e0efmXTLRuQeYh26VSm8FeG5njd9HtQY+gVAAfqB161v1Q1HWLLTIZXuJ4w6Iz +XuG5sAngfQGlKMOqE1HqXURY0VEUKqjAA6AU6vN/D/xWt9R1KWDUoYrKDbuSUycDHY5rvLXVtPv ZPLtryGWTbu2o4JxSp1YVFeLFGpGS0ZcooorQsKybjxNo1rqIsJ9RgjuT/AzYxxnk9BWtXgvxM8P No+ti7Nz5325mkxjG3GOK58RVlShzRVzKrNwjdI94jkSaNZI3V0YZVlOQRTq4f4U3Sz+DEi83e8M zqwOcr3A/I13Fa0588FLuXCXNFMKK5nxX41sfCghSeKSaaYEqieg9a5VvjNZbjt0yfbkYyw6d6ie IpQfLJ6kyqwi7Nmz8R/Ddrqmhy6g/mi4tIyY1To2T3FcP8JLSCbxLM8sZ863iLo2SMHoQR071YHx cvZprmO5tI/ssqMqBPvIecH3rz6DULu0nkmtp3ieQEMytgkHrXnVq1L2sakde5yVKkOdTR9Tghhk EH6UteefCeLVhpN1cX7SNazsr27O+c8sG/pXodenSnzwUrWudsJc0UwooorQoKKKKACisTWvFmja BPHBqF2I5ZMEKBk4zjJ9BWxDNHcQpNE4eN1DKwPBB6GkpJuyYk03YfRRRTGFFFFABRSE4BPpXmT/ ABcjh8QSWs1iFsY3aMyBvnyDjPp2NZ1KsKduZ7kSnGHxHp1FeZN8ZbASbV0yfZuA3GQdO5xisrxB 8Wrx7t4tESNLfAAkdcuT/SspYyile5Dr00r3PYqK84+GeseIdRur1NXa4kt9m+N5kxhsgYB+navR 61pVFUjzI0hPnV0FFFFaFBWdqug6ZrcPl6jZxTgdGIww+hHNaNFJpNWYNX3M3RtA03QLdoNNthCr kF+SSxHc5pNf1mLQNFuNSmjaRYhwi9ST0rTqtf6fa6pZyWl7Cs0D/eRhScbRtHQTVlaJwWjfF3TL yfydStpLIs2FkB3oB79x+VY2peBdS8SeI31ixv7G6sLiTcJPOYgKMfKe/rwKt698H4nJl0S6Mf8A 0xmOR+B7frXCXGg+KPDU5YQXluRx5tuTgj6ivNquqly1o3S6o45ue1RXRfvfh54ol1e4EelfKzlg yyIECknGOQPw/SsoLq/grxArmMR3UDdwSjf4iuo8IeP/ABANbtdPvLg3UEsgjYTLllyeuev517PN a29yMTwRyD/bUGinh6dVc1NtPzCFKE1zQdmfP+j+PdastfS/nu5rhGbEsDP8rKT0GelfQkTiWJJB 0ZQ3XPWsh/CXh93idtHs8x/dAhAH5d6Na8TaR4cWJL+4ETOPkjUZJA46eldVCnKin7SV0b04umnz M2a5vxr4X/4SrRhaxyJFcRuHikfOAe/T2zW9aXUF9ax3NtIJIZFDIw6EV5TqWh+MJPHYvYxcNCJ9 0brLgKnT8OCauvJctrXTHUfu2te50Xw78Hal4WF69/LA32gKAkbE7cE9e3cV3VRvPDE6rJKiMxwo ZgCfpUlaU4Rpx5YlwiorlRzviXwpoviFon1MskifKjrJtPXpzxzWWfhV4YOf3NwMkn/W9MjGOnbr XnPj69v9S8bSxBZVETCOEDdjjuK9z06KaDTLSK4OZkhRZCCTlgBnk9ea54OnWnJOO3UyjyVJO8dj j3+E/hpi2BdLlQoxKOD69OtTD4W+FwQfs0xwAMeaefeuzorX2FL+VF+yh2K9jYWumWcdnZwrDbx5 CIvQc5qjeeJ9F0/Uo9PutQhiunIAjY9M9MnoPxrWrzvWvhi2q+Jn1VdS2LJJ5jIY8kHPQU6jnGK9 mrjm5Je4j0QEEAg5B70U2NPLiRM52gDNOrUsKrahf2+l2E17dvsgiXczVZqnqmm2+sabNYXQYwzL tbacGk7203E720PM5tO0T4n63LdWd9c2txCqh45IR80Y7gg9cnHJr0/T7NdP062s1cusEaxhmHJw MZrC8M+CNO8LXM9xZyzvJMpU+Y3AXOcY/DrXTVjQpuK5pL3nuZ04W1luwrzm/wDih9l8WDSo9P3W 6TCF5DIAxJ4yOw59TXo1ZE3hbQ7jUBfS6XbPcg53mMcn1PqeOtVVjUaXI7FTUn8LscdY/FF73xam ljT1W1eUxLIZRuzng+n4Zr0ispPDWix3/wBuTTLZbnOQ4jGQfUe/PWtWilGaT53cIKS+J3DrWDc+ DPD13LLJLpkJeVdrMBjvnP15reorRxUt0U0nueaeJPhjpcGh3UulWtxJfA7olV89+mK4nwHcafo/ isR6vbyeZzEqlAQrHjkV9A1yM/w50OfWv7Ub7QJd/mFRJwW9fWuOrhffjOmloYTo+8pQOtVVQYVQ B6AUtFFdp0BRRRQBheLtek8OeH5b+KESyBgiqemT3P5Vw2gfF0SSiHWrcIGY/vohwB7ivUpoIriI xTRpJGequuQa5DUPhh4cvTI8cEls7jrE/APrg1zVo1uZSpv5GNSNS94M0dL8ceHtXl8q21CMSltq pJ8pb6A10IIIyDke1eG658Kta0xmn04rfQqSQIztkUdenf8ACsmx8V+J/C135Uk1wuOtvdqSD26H kdO1YrFzpu1aNjP28o6VEfRNIQGGCAR6GvK9L+MkTMqappzIOcyQNnHpwf8AGu9tfFOi3dpa3C6j Ai3OBGsjhWJJxjB9+K6adenU+Fm0asJbMvpp1klwZ0tIVlPVwgzVmkV1dQyMGU8gg5Bpa2saBXnf xS8NQ32mvrhmkWa1iWNYwOGG7/7KvRKbJGk0ZjkRXQ9VYZBrOrTVSDiyZxUo2Z5z8KfEdzqNlJpM 6Lss4x5bjqRnGDXpFY17PovhLTJb1oIbWAHnyowCxPbjrUPh3xjpHibetjMyzJ1hlG1seo9RUUrU 0qcpXZMPdSg3qcV408G+JNY8Vm9spN1s20RfvceXtUflzn869PtkeO1iSQ5dUAY5zzipaKqFKMJO S6jjBRba6kTW0DyiVoY2kHRioyKlrkviDq2raRoKS6RG5laTDukZcxrjOfbp3pnw51XVdW8PPJq3 mGVJSscjx7S6EAg+/U9KPax9p7O2oc65+U7CiquoajZ6XaNdX1wkEC9Xc8Vy+ofE/wANWMcbR3Ml 2XGQsCZI+ucYqpVIQ+J2HKcY7s7KivKdV+MaJcFNL0/zYQR+9mbaW9cL+dLo3xUvdV8T21o1jDHZ zvsA3fMuehz0/CsfrdG/KmZ+3p3tc9VooqOaeG3TfNKka/3nYAfrXSbElFFFABRRRQAUUUUAFFFF ABRRSFlXqQPqaAFopqyRsAVdTk44NVNV1ay0Wya7v5xFCDjJ7mk2krsL21LtFZ2ja5Ya/Zfa9PmE sW4qeMFT6EVdnlEFvLMRkRoWI9cDNCaauhJpq6JKK8w0P4pS3/iQWd9BBb2jkqrlsbT2ya9OBDKG Ugg8gjvUU6sKivEmE4zV0LRRRWhYVUvdLsNSULe2cFwByBLGGx+dW6QsoIBIBPQZoavuBw+p/Crw /fHdbrLZv/0ybIP4GuV8Q/CnUIj5mkT/AGmGNcLFK2HA5PB6dfpXsdFc88LSn0MpUIS6Hznbt4u8 LXLxwrf2zDO5VUspwMZ7g11PhHxt4jOsbNVeeazSImTfDyoAznPHP1r2FkV/vKDxjkVFLZ280UkT woUkXa429RWUMJKDvGbt2IVBxekjz2z+MOmy3nl3NjLBCWwJA27A9SMfSuw0zxXomr7BaahEzsu4 Rsdrdcd65nVvhPol7ueyeSzk5ICnK5+nauJ1T4XeINLfzbErdqMYaE4b8vwqfaYmn8S5l5C5q0N1 c9h8QaHbeItJewuiwjYhgVOMEdK8Jn0vVvAviC3u7iGRUim+SVcDzFHp1xkV2vw7fxSniCSHVEvP sgQq5mHCsBwMmrfi/wAUeG9Q1ddC1OznlEUm0zIceWxGOPzqavJVgqnwvpcmfLOKnszrvDfiiz8R 6RHfRj7OWfyzHIwzu9Ae9bleH6p4NuLnX3g8L3EUtpGUKolzzGdoyW9OQea9qs0kjs4Ul/1ioA3O ecetdNCpOV1Nbde5tTnKWklsTdaMY6VR1nVYdF0m41C4VmjhXcQvU1geDvHEPiya6hW1eCSDDDJy Cp6fjWrqRUlBvVluaT5epd8XeGV8U6UtmbgwFH3hguea8q8VfDmTw7pENzDNNeTtJiTy4vlVcHmv daQgMCCAQeoNZVsNCrdvcipRjPV7nzRD4W1y7tEuodKuGhyEyEwSeucH69a1FtvE/h6wiKabJbux 3LOIQzgdgDyV/wDr19BgBQAAAB0AoZVYYYAj0IrBYBLaTuZLDJbMxfCd3f33hu0n1NWW7Zfn3JtP 5VyfxF8Ia34i1O1uLB0e3jjCeW0hG1iTlsdOmPyq/wDEbxDq2hWVsNKUhpSd8gTdtA/lWt4I1W91 jwxBdagMXG4oxKlScd61lyVP3Ermj5ZfumX/AA9Z3On6BY2l4wa4hiVHIYtkgeprToorpSsrGqVl YKKKKYwooooAKKKKAPO/Hvj2Cwt7jSdLuH/tLIUui5Ceoz61wMGk+OtWdWWLVCHBIeRmRcHg8nA7 0UV5eteq1J7dji1qzab2LNn4U8c2txalYLxV37wBOMLzyTzx+Ndl4q1bw74iNv4cu9SkhukcbpET ciyY6E/X0ooqqkFQjZapu2pUoqmrLW503hHwvH4T0yS2W6acyN5jsyhQDjHFbcVxb3QkEM0UwU7X CsGwfQ0UV3xioJRjsdKSjZI878V/DGXWtb+3afPbW0TgB4yhXbjqRjrUUXxG/srW7Tw8LISQW7Ja ST78FiAFyB0Az6miiuLEL2DUqejb1Oer+7d49Wen9RRRRXoHUFeK+M9O8Yw+JbrUYlvjbCRmgeFi yonQcDpx60UVz4mHPDfYyrR5olAfErxBaaXDYrP/AKUhIkklT5sdhVnUvijr+6zEJihKorSgIfnO ehz04Hb1ooryfrFVJrmOH2s+56T4V8bad4nLwQeYl1EgaRWTAPAyQfTPHPNdPRRXrYapKpTUpbnd Rm5wuwoooroNQrkNZ+HOiarcXF4I3ivJVb5g527yOGI9qKKmcIzVpK5MoqWjMjwV8PdQ8Na+9/c3 cDxhGjVUySwOOfasmy17xhL4+SKeK8W284hofs52rGT1+nvmiiuSpSVNRjB2VzGUFBJR7noPirUN HsNDlOtgNaSEIY8Elz6ACsnwHB4YmtJtQ8P27xuzGOXzM7l5zt9MdOlFFU5/7SoWWw3L99y2Oxoo orrNwooooAa8aSIUkRWU9QwyDTgABgDAFFFABRRRQAUUUUAFFFFACEhQSSAB3NRfa7cgHz4sEZB3 jmiik2Jn/9k=