20191114 13254600 1.0 FALSE FullTimeMinors 002 Projected GCS_WGS_1984 Linear Unit: Meter (1.000000) WGS_1984_Web_Mercator_Auxiliary_Sphere <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/2.9.0'><WKT>PROJCS[&quot;WGS_1984_Web_Mercator_Auxiliary_Sphere&quot;,GEOGCS[&quot;GCS_WGS_1984&quot;,DATUM[&quot;D_WGS_1984&quot;,SPHEROID[&quot;WGS_1984&quot;,6378137.0,298.257223563]],PRIMEM[&quot;Greenwich&quot;,0.0],UNIT[&quot;Degree&quot;,0.0174532925199433]],PROJECTION[&quot;Mercator_Auxiliary_Sphere&quot;],PARAMETER[&quot;False_Easting&quot;,0.0],PARAMETER[&quot;False_Northing&quot;,0.0],PARAMETER[&quot;Central_Meridian&quot;,0.0],PARAMETER[&quot;Standard_Parallel_1&quot;,0.0],PARAMETER[&quot;Auxiliary_Sphere_Type&quot;,0.0],UNIT[&quot;Meter&quot;,1.0],AUTHORITY[&quot;EPSG&quot;,3857]]</WKT><XOrigin>-20037700</XOrigin><YOrigin>-30241100</YOrigin><XYScale>10000</XYScale><ZOrigin>-100000</ZOrigin><ZScale>10000</ZScale><MOrigin>-100000</MOrigin><MScale>10000</MScale><XYTolerance>0.001</XYTolerance><ZTolerance>0.001</ZTolerance><MTolerance>0.001</MTolerance><HighPrecision>true</HighPrecision><WKID>102100</WKID><LatestWKID>3857</LatestWKID></ProjectedCoordinateSystem> 20230504 11481000 20230504 11481000 Esri ArcGIS 12.9.4.32739 FullTimeMinors ACS Parks Census Labor Force Participation 16-19 year olds who work either full or part time File Geodatabase Feature Class dataset EPSG 6.18.3(9.3.1.2) 0 Simple FALSE 0 TRUE FALSE FullTimeMinors Feature Class 0 OBJECTID OBJECTID OID 4 0 0 Internal feature number. Esri Sequential unique whole numbers that are automatically generated. Shape Shape Geometry 0 0 0 Feature geometry. Esri Coordinates defining the features. GEOID Geographic Identifier - FIPS Code String 11 0 0 ALAND Area of Land (Square Meters) Double 8 0 0 AWATER Area of Water (Square Meters) Double 8 0 0 NAME Name String 255 0 0 State State String 255 0 0 County County String 255 0 0 B23027_001E Total population age 16 and over Integer 4 0 0 B23027_001M Total population age 16 and over - Margin of Error Double 8 0 0 B23027_002E Population age 16 to 19 years Integer 4 0 0 B23027_002M Population age 16 to 19 years - Margin of Error Double 8 0 0 B23027_003E Population age 16 to 19 years who worked in the past 12 months Integer 4 0 0 B23027_003M Population age 16 to 19 years who worked in the past 12 months - Margin of Error Double 8 0 0 B23027_004E Population age 16 to 19 years who worked in the past 12 months, full-time, year-round Integer 4 0 0 B23027_004M Population age 16 to 19 years who worked in the past 12 months, full-time, year-round - Margin of Error Double 8 0 0 B23027_005E Population age 16 to 19 years who worked in the past 12 months, less than full-time, year-round Integer 4 0 0 B23027_005M Population age 16 to 19 years who worked in the past 12 months, less than full-time, year-round - Margin of Error Double 8 0 0 B23027_006E Population age 16 to 19 years who did not work in the past 12 months Integer 4 0 0 B23027_006M Population age 16 to 19 years who did not work in the past 12 months - Margin of Error Double 8 0 0 B23027_007E Population age 20 to 24 years Integer 4 0 0 B23027_007M Population age 20 to 24 years - Margin of Error Double 8 0 0 B23027_008E Population age 20 to 24 years who worked in the past 12 months Integer 4 0 0 B23027_008M Population age 20 to 24 years who worked in the past 12 months - Margin of Error Double 8 0 0 B23027_009E Population age 20 to 24 years who worked in the past 12 months, full-time, year-round Integer 4 0 0 B23027_009M Population age 20 to 24 years who worked in the past 12 months, full-time, year-round - Margin of Error Double 8 0 0 B23027_010E Population age 20 to 24 years who worked in the past 12 months, less than full-time, year-round Integer 4 0 0 B23027_010M Population age 20 to 24 years who worked in the past 12 months, less than full-time, year-round - Margin of Error Double 8 0 0 B23027_011E Population age 20 to 24 years who did not work in the past 12 months Integer 4 0 0 B23027_011M Population age 20 to 24 years who did not work in the past 12 months - Margin of Error Double 8 0 0 B23027_012E Population age 25 to 44 years Integer 4 0 0 B23027_012M Population age 25 to 44 years - Margin of Error Double 8 0 0 B23027_013E Population age 25 to 44 years who worked in the past 12 months Integer 4 0 0 B23027_013M Population age 25 to 44 years who worked in the past 12 months - Margin of Error Double 8 0 0 B23027_014E Population age 25 to 44 years who worked in the past 12 months, full-time, year-round Integer 4 0 0 B23027_014M Population age 25 to 44 years who worked in the past 12 months, full-time, year-round - Margin of Error Double 8 0 0 B23027_015E Population age 25 to 44 years who worked in the past 12 months, less than full-time, year-round Integer 4 0 0 B23027_015M Population age 25 to 44 years who worked in the past 12 months, less than full-time, year-round - Margin of Error Double 8 0 0 B23027_016E Population age 25 to 44 years who did not work in the past 12 months Integer 4 0 0 B23027_016M Population age 25 to 44 years who did not work in the past 12 months - Margin of Error Double 8 0 0 B23027_017E Population age 45 to 54 years Integer 4 0 0 B23027_017M Population age 45 to 54 years - Margin of Error Double 8 0 0 B23027_018E Population age 45 to 54 years who worked in the past 12 months Integer 4 0 0 B23027_018M Population age 45 to 54 years who worked in the past 12 months - Margin of Error Double 8 0 0 B23027_019E Population age 45 to 54 years who worked in the past 12 months, full-time, year-round Integer 4 0 0 B23027_019M Population age 45 to 54 years who worked in the past 12 months, full-time, year-round - Margin of Error Double 8 0 0 B23027_020E Population age 45 to 54 years who worked in the past 12 months, less than full-time, year-round Integer 4 0 0 B23027_020M Population age 45 to 54 years who worked in the past 12 months, less than full-time, year-round - Margin of Error Double 8 0 0 B23027_021E Population age 45 to 54 years who did not work in the past 12 months Integer 4 0 0 B23027_021M Population age 45 to 54 years who did not work in the past 12 months - Margin of Error Double 8 0 0 B23027_022E Population age 55 to 64 years Integer 4 0 0 B23027_022M Population age 55 to 64 years - Margin of Error Double 8 0 0 B23027_023E Population age 55 to 64 years who worked in the past 12 months Integer 4 0 0 B23027_023M Population age 55 to 64 years who worked in the past 12 months - Margin of Error Double 8 0 0 B23027_024E Population age 55 to 64 years who worked in the past 12 months, full-time, year-round Integer 4 0 0 B23027_024M Population age 55 to 64 years who worked in the past 12 months, full-time, year-round - Margin of Error Double 8 0 0 B23027_025E Population age 55 to 64 years who worked in the past 12 months, less than full-time, year-round Integer 4 0 0 B23027_025M Population age 55 to 64 years who worked in the past 12 months, less than full-time, year-round - Margin of Error Double 8 0 0 B23027_026E Population age 55 to 64 years who did not work in the past 12 months Integer 4 0 0 B23027_026M Population age 55 to 64 years who did not work in the past 12 months - Margin of Error Double 8 0 0 B23027_027E Population age 65 to 69 years Integer 4 0 0 B23027_027M Population age 65 to 69 years - Margin of Error Double 8 0 0 B23027_028E Population age 65 to 69 years who worked in the past 12 months Integer 4 0 0 B23027_028M Population age 65 to 69 years who worked in the past 12 months - Margin of Error Double 8 0 0 B23027_029E Population age 65 to 69 years who worked in the past 12 months, full-time, year-round Integer 4 0 0 B23027_029M Population age 65 to 69 years who worked in the past 12 months, full-time, year-round - Margin of Error Double 8 0 0 B23027_030E Population age 65 to 69 years who worked in the past 12 months, less than full-time, year-round Integer 4 0 0 B23027_030M Population age 65 to 69 years who worked in the past 12 months, less than full-time, year-round - Margin of Error Double 8 0 0 B23027_031E Population age 65 to 69 years who did not work in the past 12 months Integer 4 0 0 B23027_031M Population age 65 to 69 years who did not work in the past 12 months - Margin of Error Double 8 0 0 B23027_032E Population age 70 years and over Integer 4 0 0 B23027_032M Population age 70 years and over - Margin of Error Double 8 0 0 B23027_033E Population age 70 years and over who worked in the past 12 months Integer 4 0 0 B23027_033M Population age 70 years and over who worked in the past 12 months - Margin of Error Double 8 0 0 B23027_034E Population age 70 years and over who worked in the past 12 months, full-time, year-round Integer 4 0 0 B23027_034M Population age 70 years and over who worked in the past 12 months, full-time, year-round - Margin of Error Double 8 0 0 B23027_035E Population age 70 years and over who worked in the past 12 months, less than full-time, year-round Integer 4 0 0 B23027_035M Population age 70 years and over who worked in the past 12 months, less than full-time, year-round - Margin of Error Double 8 0 0 B23027_036E Population age 70 years and over who did not work in the past 12 months Integer 4 0 0 B23027_036M Population age 70 years and over who did not work in the past 12 months - Margin of Error Double 8 0 0 B23027_calc_pctEmp1619E Percent of population age 16 to 19 years who worked in the past 12 months Double 8 0 0 B23027_calc_pctEmp1619M Percent of population age 16 to 19 years who worked in the past 12 months - Margin of Error Double 8 0 0 B23027_calc_pctEmp2024E Percent of population age 20 to 24 years who worked in the past 12 months Double 8 0 0 B23027_calc_pctEmp2024M Percent of population age 20 to 24 years who worked in the past 12 months - Margin of Error Double 8 0 0 B23027_calc_pctEmp2544E Percent of population age 25 to 44 years who worked in the past 12 months Double 8 0 0 B23027_calc_pctEmp2544M Percent of population age 25 to 44 years who worked in the past 12 months - Margin of Error Double 8 0 0 B23027_calc_pctEmp4554E Percent of population age 45 to 54 years who worked in the past 12 months Double 8 0 0 B23027_calc_pctEmp4554M Percent of population age 45 to 54 years who worked in the past 12 months - Margin of Error Double 8 0 0 B23027_calc_pctEmp5564E Percent of population age 55 to 64 years who worked in the past 12 months Double 8 0 0 B23027_calc_pctEmp5564M Percent of population age 55 to 64 years who worked in the past 12 months - Margin of Error Double 8 0 0 B23027_calc_pctEmp6569E Percent of population age 65 to 69 years who worked in the past 12 months Double 8 0 0 B23027_calc_pctEmp6569M Percent of population age 65 to 69 years who worked in the past 12 months - Margin of Error Double 8 0 0 B23027_calc_pctEmpGE70E Percent of population age 70 years and over who worked in the past 12 months Double 8 0 0 B23027_calc_pctEmpGE70M Percent of population age 70 years and over who worked in the past 12 months - Margin of Error Double 8 0 0 B23027_calc_numGE65E Population age 65 years and over Integer 4 0 0 B23027_calc_numGE65M Population age 65 years and over - Margin of Error Integer 4 0 0 B23027_calc_numEmpGE65E Population age 65 years and over who worked in the past 12 months Integer 4 0 0 B23027_calc_numEmpGE65M Population age 65 years and over who worked in the past 12 months - Margin of Error Integer 4 0 0 B23027_calc_pctEmpGE65E Percent of population age 65 years and over who worked in the past 12 months Double 8 0 0 B23027_calc_pctEmpGE65M Percent of population age 65 years and over who worked in the past 12 months - Margin of Error Double 8 0 0 Shape_Length Shape_Length Double 8 0 0 Length of feature in internal units. Esri Positive real numbers that are automatically generated. Shape_Area Shape_Area Double 8 0 0 Area of feature in internal units squared. Esri Positive real numbers that are automatically generated. 20230504 /9j/4AAQSkZJRgABAQEAAQABAAD/2wBDAAgGBgcGBQgHBwcJCQgKDBQNDAsLDBkSEw8UHRofHh0a HBwgJC4nICIsIxwcKDcpLDAxNDQ0Hyc5PTgyPC4zNDL/2wBDAQkJCQwLDBgNDRgyIRwhMjIyMjIy MjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjL/wAARCADIASwDASIA AhEBAxEB/8QAHwAAAQUBAQEBAQEAAAAAAAAAAAECAwQFBgcICQoL/8QAtRAAAgEDAwIEAwUFBAQA AAF9AQIDAAQRBRIhMUEGE1FhByJxFDKBkaEII0KxwRVS0fAkM2JyggkKFhcYGRolJicoKSo0NTY3 ODk6Q0RFRkdISUpTVFVWV1hZWmNkZWZnaGlqc3R1dnd4eXqDhIWGh4iJipKTlJWWl5iZmqKjpKWm p6ipqrKztLW2t7i5usLDxMXGx8jJytLT1NXW19jZ2uHi4+Tl5ufo6erx8vP09fb3+Pn6/8QAHwEA AwEBAQEBAQEBAQAAAAAAAAECAwQFBgcICQoL/8QAtREAAgECBAQDBAcFBAQAAQJ3AAECAxEEBSEx BhJBUQdhcRMiMoEIFEKRobHBCSMzUvAVYnLRChYkNOEl8RcYGRomJygpKjU2Nzg5OkNERUZHSElK U1RVVldYWVpjZGVmZ2hpanN0dXZ3eHl6goOEhYaHiImKkpOUlZaXmJmaoqOkpaanqKmqsrO0tba3 uLm6wsPExcbHyMnK0tPU1dbX2Nna4uPk5ebn6Onq8vP09fb3+Pn6/9oADAMBAAIRAxEAPwD3Ciii oGFFISM4JGaKAF5ooqu9yNwWIb2P5CiwrlikPSoAs5XLuB3+UYoVJEO95WbjABAH8qLBcn5bIH0z SqoVcCs8avaIi7nkBbt5bZ5/Cp0v7eSYRKzbz0+Q88Z60AWqSj8KKBhTSACCB+VOo9aEJoVD8wqQ kDrUKE5AHX6VIQWOCOB71VhXDeuODmj5m4xinY460AcdTQFhvlr7/nRsI6NTgD3NB47mi4WQ3aD1 aql1fGBCotZ5c8Axrn8atOM4XtmlcfuW+lAIgtbozKq/Z5o8L1dcCpiSR0oiA8tfXaKRhzUsYh96 Rvu0UhGQagRGaOlO47jikOOwoGGeDz+tOU80gOOtLuH400AuOQTSnpR2pC1MYo4ApOcY603q3Ao5 Y9qQhxIPFIFULgjP1peD2oIzTGJtweKPm9KXBzQcUAO7UhUNwc9aWimAhAPak2kfdP506igVhu1i OSPwpFRIxwBTiwBx39KQL3brQAfePsKVhmnUhoGNULyMDIJp2BSH74paBIWkpaSkMKBRS0wGmNZG Xd2OetT4xUSk7hUvPpTQgPSgdBSFsAk4H40AjGcimAtNY0FsHHf0poDMSW4HYUCuGSxAUd+aZK+f 3S9T1PoKk3dhUCkefJn0FJvsBKMAe3SgEcjtQCPejBPQVADSqj1pOgPXP1p2DQ+3Bx1o1CxBk9Dk 08YYcdKbQOOlK/cYEDmoXuoYX2yPgkZ6E1L9aXZnt+dICE39uAMucHkHaasIyyIHU5UjIpoTIxgY p4+7jpVIBcY46UD2petITjigYd6M4NGRS0wEPXilpD1peO9ABS5po9KdQAUUUUwDAznFFGaKAFpK CQBRkYoATHz/AIUtIPvEmlyKBC0nejIozQMKQkDqaRjnilAA7UCE5fhCQfUUn2eXB/fPz71IpAIz UuR61SE0V/szFsyOWA7Gk+zqjqUHzZqwWGOtMzlx6CncLC4w6jFKxxSMw3ClOD3pMER/xVGB/pEh 9hU+PmzxUQGZn+gqLaDHrjvQXPbpQelNxmlqhAWPQ0hHBoIGOSOfemlhggkdPWkA00CkBB7j86Uk eo/OkMT/ABqTPrUZIP8A+ulGetO+gEmeKQAZzmk60KaYDulNzk9KDz3ppDDkHI9KaV3YTdhwxmnE 4pqNkdMYoJHBJxQ1bQad1dDhj1oqMuhPBJPoBTSzZ+4340tQJxx7miilpjCiikoAWiiigA7UUUUw ILhsNHkkDcOlWKjlUshwcH1pIHMkKsevQ0CW5Jmg57UUtAxu3nk5qZPu1FUiHC00IcTjFICMdaZM xRMj1qD7Q/tSckhXLRI9aapG089apz3jRRFm+gAGSTVc3N9gSZiRQvKEn3z2+lNSQGix+Y/SkU85 J6VmWuqm4uRFmFiwz8hJIx+FX5JFjQu5wo6mknfYa12JGck+1MjbE0mfQVCLy1LEeemV6jd0qSCR JnkZGDAYHFAFgMPSk4HHegAjp3oIAXk0AUb3/Wr6YqrVm9IaVSpyMVQMshldERSEwCScds1xzV5M h7k1FQPNLFhni+TPJU5x71ODkZqGmhE9ty5+lXBgLgjFVLT77fSrPmqvGcn0rpo/CVEcuMev0pcj 1GaYGkYYUBfdv8Ka1sjury5d1zgk9PwrXQoQyDPGWPoOacPMPRQP9408AjAGAPTFLznrn8KVkAwx s3VyPoMVBJDKSDCUHrvBOatZyvFA/SmBTCal5mfNtwmPugGroB2jdjPejpzS8HnFAxoQpkg5PfNO DZHofSlpCobrTFa2wm9c4yM0u4ZxkZoCgDGKQoCMUaBqL16UuaZhlB7/AM6UHcMigLjqKrss5bKy gL6bRx+NSxhlUh33HPXGKBjzzx61WZmgc/KWQ9lHIqz3oxQhNCA8ZqtdMCVxdiEjJ7c1ZxgH0qgv /H5If9gUr2C42IyNOXXUBKmP9WEHH45qUXrhmVVkbacEgCmvbxu+8hg2MZVyvH4GnRQpCCEzycnL EnP41LkhXEe8lYYMMpH0H+NM+0N/z7zfkP8AGp6KVxXKkryTeWogkGHUknGAAfrVlgGUqRwRg1Q1 XWrLRoY5Lx2AkbaoUZJNYHjDVr3TbnTZbaaSK2ZszFVyCMjj8s01FysjOpVjFNvodCllb2NzHPHE w6qxBz1xWqyhhgqCPQisjTNUstcs2ktXZ4wdrZBUg1NIL2NttuwKN3cklPzPNNNJW7GkHHl90umC HJPkxZPU7BzTIz5YOwBeewxUMb3cYUylJRnkKmD+ZbFIv2lgTujTJ4UoSR+TUN3V7jZb85/71NZi xyTmqrQyOcyy5UDpHuT9Qa5W78RyB2jghKbSRl5nY/zFEYuWzMqlWFNe8zprucJME2OxCgnaucf5 xVaGZfPk3fIXYBVbgngdq46XU72VmZrmTLAA4Y9P8mpdGJbWrUsSTv6n6U5Ybd3OX65FySijsrpG EDJtJZ1KqAMnOKsJbkIu444ppWSa8EiybUiypGM7s9fp2q1WLpxSsdthscIBPLe+DUyqq8KoFNTq aeOO/NXHRaFIXkZoJPfrRn5ec00mmMcvXPbFLuGaaTQASaLgKQVzgZz3pNrAD5v0p7H0pTVXCwzL DqM+4oDijJOO2aTyk74/GkGpJmlzTaUUxi5opBS5pgFMLbXNOxk0hP4UhCjBHBBpeBTAO4OKgluo opCpLblXccDPHP8AhTAtUVUS8hkfy1kyxxwQanLBAS3GBRYLkh6Gs9f+Px/90VdV1dQVYEGqLpMs 5eMIQRj5qlgyeiq0k00SF5PJRR1LNgVi6j4vsdNC+ZNFMSeVhO44/lUqDexnKUY7s6KiszSPEFhr Yf7HI25OqOMHHrV25uY7SEySsAO2TjJ9KXK72CMlJXRi+J/DkniBLUR3IhMJJyVLZzj39qvtbi+t hDdWdvOsRAIdsjcB1xirNtdiberGMMmM7Wz1qK7iVJEmRvKJba7LjkH/APUKtN/CwVOPM33G6eLG C3lFnDBEEYiRIccMPXFS/wBoR/3WrN0bTmspdQi+0LMJ5PND5yRnsfyq9/Z7f89B+VYV/aKXuC1S 2LkUgljDAYBp9clq3jCHw/e/YDbNOyqCWD4610Ol341PTYbxYzGJVztJzitFGSinIUakZS5U9UW2 +4fpXl92P9JcdvMP869QIyCK5WbwhJNIz/bFGWLD5On61tQmot3MMTTlO3KjlfKT0/WrmjMIdWiY dn4HqccVrweFmkBU30e8MRjbzwfrV/TfC32PU4Lp50fy2zjZ1rd1Y6ps5oYeqpLmRvwR+XEFPJ6k +p71JV4ouOFFQlMdq5HE9WxFH1pxAFOKgdBimn71Gw0APak70d8UoGTSADS5IHFO74pMYPWqsAgJ NO+tAxikJxQMTAzgGnYHrSL3PrRjNNiGeSOgZ19lal8kYxvk/wC+jTwQRxQTzQMjEIH8cn/fRpfJ B/5aSf8AfRp4oHWi4DfJGPvyf99Gk2On3TuHo3X86k5xjvUOy55/eJ7cUwBpVAyysn1FRC4hJJLc qMnipHklTCeU0n+0OlAjWTLPDtO4de/SgCcBeDtH5UEAjBFM8iP+7+tHkR9hj8aAMfXtTj0OKGfy 9wd9rDPOPasT/hO7YvhbRyP96pfHkapZWhA/jb+Qrg2UMOnPato04SV2ebia8qdTlTNrWNTvtdLm KKXyFGFRATj64rm7TQNTvpxDHbOrN3kG0frXf+B7iOK0uFkO07x/Krd9rVlD4ijjuJxGqoGViMA5 680pzlTVoLYUcOppVakjnNG8Pav4dvTfT+QsAUhz5n5frWnqurf2nppCy27TQ4k2RnPzYPFamqah oer6dLZS6nEqSYyVbmuc0DSdP/tW6hsVlugiFPPYjZyKyac7ybszWKVP3IPR+Zk6NcCOTVH1F5bW C6hKq+D94sDhfXvXe+H9TvL5JY7qy8mOMKI2JzvHrWBeav8AZJZLXWtHDafG5S3KpwSOn6ZrR0/X LhN2/SLoRtjYVTtTqNtrlQqcoxlZP+vM6UPErYDICewIqSsG8lsIXa8S6QSxRNthJ4Zu3HrUdhqW s6hpyvHHbpck7irA4C9vxrGMZNXZv7RXscF46yfFVxxjCr/KvQ/DEnk+FbElWYlMBV6nmsy88Iw6 pMbzVZil2/BWE/KcdK6fRLA2VhAsowY12on90f411TkpwS7E0qcvaOT2A27TEvMvb5U7D/69EE8a 26BmwQMEEd60SeeDVdonLMQQQenHSsbLqdNilPIh8uSBkLo/THXPGOPrV4AkihY2THzKOcnC9aa8 HmN5gldMZ6UNILF1ZOMHAPpQWCsATyaoC2Il3/aZex2+tWSQMHnIqk11E79CST7oqHmqywXO4D7Y /GTgqOasQRvHGFklMjf3iKlrUYyWNpEwrshznK1QzOG2+dcDDYzsBzWqVOaTaakBI0ZVCtIXP940 /b6HFKBSd8VQCAMOMigoxOCePalBByKUnnAoCwmAB0owaUnHNAbIpaDGDjkHHtTgc9uaQj5fehc9 6d+4hehwacMUh5GO9IG9eKYD6KQHNL3oGFI/QfUfzpaa33R9R/OgB1FFFAHIePv+PKz/AN9v5CuC r0fxfp1xqUNrFbKGYMxIJA44rk/+ET1b/nin/fYreM4qKTZ5WMpTlUukWfD2uWWk2NytxOscrHKA jrxWFqN3/wAJLrdvGzKWYbAyDBz6VZvPBmszMpSCM4HeQVNovhDV7LWbW5mgjEccgZiJAeKluCvJ PUz5askoNaFDVPCc2l2El04kwvqOKytK1q80aczWjgFhghuQfwr1jxNaTahoFzbW4DSuBgE4715b qHhzUdLtvtF1Gqx5C5Dg8mlTqKStJ6ir0XSleB2nhLX7vxDfzwagkEkccW9R5Y65A/rXT6jqCabE ruoEWDljwB6VwXh/wz4lgtP7S05o4TMnyqxGXXrRqk2rJa2za993cHQDGWwQSCB07UnTTl5HRCtO FO8k79xs+rxa3rumTyWTxBHCOFGAW3cHNdZ4h1i40lGa32Ham7DLXJ6jrl3qtil0lultZQuoIRgS X6g+tU73WZp7GWPUZi9wy4Tjt26UpwbtZGXtuVNJ6vrsd54Mv7m/0lr65xJLJIwLDqB6CukDiQZB zXA+Bdfs7fT4tLPmNdM7MFC8fnUx1+7k8R3WnGWWFgxKkAEAY6GrlHVnoUqseSN3v+Z1sn9oCZti wmLJ2564pytc7+UjUezZrPs3nnLbr2Zgo6YA5/KsZtQvftJU3cpAYjt0z9KwnOMdy51FDc6qNptz eYq47EH+dSpymBxVYQHHyzSr9D/jR5cyf6uc/Rxmi6Lui2Ae9LjPFVRPcAEeQCw77uD/AFpBfJnE jeU391utFgLhXJHtRkqfmPHrUcT7/mDZBHWpGAYFSeDxTTAXIPQg0dapDT44ixjZwCMEF6ntrdIF JXcS3Xc2aYXJwaMUUtIY0Lg5pOQfWndhTWPIA6mgQFgOtQSXEqPhIN6+ucVI28DOMinADFGoXGxu JUDrnB9RipM0mRjgUAk9aQwPPTrQvPDUDmlx06UxDX+XG3inKc9RVdorg5xOBz3Spo1bywHbLjqQ MUwsPpGPy/QijcR1U49qRsN97pj1oGPzRTQwwMnmoCbg5IdRjtt4P40CuZ2v6rBpP2aa4Vyrbl+Q Z9KxT4006RSipOGYYB2j/Gm+PJPN0uyY9d7Z/IVwNaKlGSTZ5+JxM4VLLY9fWCAW6yHf90E/vG/x qo9xavGwQShux3n/ABrzL7bd4x9qnx6eYf8AGm/abgf8t5f++zWdTDzfwysJ45dj0QMwlj/eOcsB guTWlHY2uouILuFZouu1uma4HwxLLL4gtlkkd1yeGYkdK9MVQpyoAPqK5/YSpSV5XOijUVWNy9DD FBCkMSBY0AVVHYVwmsz2174mk0We3MjAFo3PQZGa6/e394/nXFXmk3txrNxfJfeX5rggLkHA4Aq5 zg177sOu3ypRRf0XwtHZWE9peqk8bvvVScgcV5prZzqckYBUxMUI+hr07VLW6vdKNvb3ssExkG10 3E/TisbT/h/PHqcd1daikyq+5w0eS/55rfD1brnb3OarQlLljBfM5rwZ/wAjRafj/Kt+GLzfiTdK N3Q8qcY4rsYbGxs7nAtYkfdiOTyAuf8AgQAFZd5GkepyzIirKTy6jDfnWOJxPsvea30Ljh3SSTez ubdtbm3Rh5jvkfxHNco//H43++f51d+0Tf8APaT/AL6NRbRnOBn1rzZ4xS6GlR89jqx0FLXMfaJv +esn/fRrZ0t2e1Jdix3HknNb0sSqkuVI1UrsvUYpBjtS10lFa3U284jebKbeBjHerayRKc+aPpmq s0jQzq6KHO37vzf0Bq6rOUVtvJGcHtWybt6lNLdirJHJ8qupPcA0BlXIZuB60YWXhk6eopDCoYMq rn3FFraBe+qDz4j/AMtF/Ogzw9PMWnhvUgGkZ8cEGgoZ50fH7xfzpGlBbKBm+i/1p27Hr1pS478U hMaZgOGR1/DP8qTzYfVaftAYEH8DUo6daYEAyOvSnB+MUjZPamhT1qAJOCeKXOPWmKCCadlfWmmM WjvSA9cdKd2pgAqC6uIbWLfM4RDnJx7E/wBDU4ppQO3zDIA6UwII7mC4I2yq2egBqxtA4oCKvQCn UhGTq+gWusmATsyrGc4Tjd7Vm3/gjT7t4jBm12jDBBkNXUdKord3hkC/Yvl7t5gq1OS2ZEqcJbo5 fW/BEX2JZNNUidAAyZ4f/wCvXNDwprRgaX7GQB/CzDJ/CvWvwo71SqvqZTwlObuzivD/AIPuLN4t QmuAs69ItuQO3PeuoDOknly7dxGVZehq7nmopolmTDZBBypHUGok+d6msKUYK0UVLuTyrV2HXGBW VbkCGfJA+Q9fpWpcWVxMnlGdNueCU5/Hmse7tJ7YvEymTK5BjQ81wV6dRTU4q6RMk9zk/CF+8EU8 fls26cYcMRtPSvSZLWG4cLKu4ABupHNcT4Lsrq0t7nz7eaGTzwyB4jyMY9K77bib3K16M9yMLFqk rmBqyLG4ijt3J3qQ+5jWewIPPWu0eNJkCPk85yDg1yeoWssWpzbIp2jONpwzV5eMoSkue932saVI 31K1FO8qX/njN/37b/CrFjpv26dxKZ40ReMArk5rihh6k3axkotlMOhzhlOOvNatk8bWPlFkLNKv ykjn5h2rRsrCKxiKJlgTn5uasEAY4FehhsN7OSl1NYx5dWVYGWGaSAqIyWLKOACCe1WajuEZvLdF 3FXyR+BqNftbDJ8pOehUnj8663rqW0Sr/wAfg/3KtHpw2KqQxyibfKyE4wAqkf1qyBnk007bD6CJ y5JJPpUopoGMYFOq27iirIQqD9fWmE9R3qSkIDHkCkMpzQSyuXS4kjyMbVwQP84oS2n8zm7kIAGQ Qv8AhVvYuOgFOxjgAUXAQKAQefzp46dqb1oBouMTgDBoHakPXkU4dOKQCDvTNuW9qf3pe9FgGgYO AaUE4oHU/Wl9aAEB70gzuP0FOHSmK2ZXXB4A5oAf3paSlNABQMCijIoAKac9qdSZAoAQDvSHgjua CxPTgeppQoUUAQXE7QbGMbSZOMIOnvTfti4VvJm69NnNWN671XnLdKd0kU+9UhMbbXX2hS3kyR4H RxSM2Z0z71ZY4BPtVXIFxGe3NAEuWAHP44py5P8AF+lV7i4SEbn3bc9hmo01CAMfmYAdflNAWLhX /aqDO3jtUyOJUEicg9OKibrSbATOecCmtyv4VG88cS5Y8dOOaZHdxTcDd07jFJRaZDkrEyZ20tMj Yeo56VJiipFqQQd4hSjikz1xSg1JY4NnrSiowOaeORTTAdkY60hIx1pOKUgUxgDkUZo47Uxs/hSb AGBJpwGBzTAeak4oQhDnrmjJz9aUc5pp4OaaBju/Xml703OCCe9O70DDHFFHaigAFIPvH6ClHSmn jf8AQf1pgOXPX1ooHTApaAEzzRSD7xPahjjr+VAhScCm7S3LflSgdz1o5HbNAC0h6UFvbmgkgcig LkL7hcQhT8vO7j2qxTNoZg2ORQSc8Uhj9xwQSSPSoZMCRCOucYqQHiox/riG7j5aaYvQeaFVScYH 5UoUHIzzTlXvTC44qQMCoee9T4yvWoWFSwKf2OJmJZefY0xrOEFQqnP1q5zjml7c01Ul3IdOL6EU USxrtwDgU/kA46UuAB1o4A61Dbe5SSSshByDzS9s0gAbOaq3c0i/KIn2cYZSKFYZbH3qO1ZMbziR cfaj7fLV5bhvL3PBInsRmizAsqcEU/GTmqouAdu1GJIz0qxGzlBvTB+tNJhcXIJprk42gZpV6nI5 pwJoAiC+5zij5x1qRvUUwk+lJhYjjZoGKSD5ByG/xqcEOMiiiqe4kR4IYKemcipqKK0m7pMmCs2g pcUUVmaBUcbb1YkEHJHIxRRTAevKjPXFKeKKKAGbsZ4ySelKB3brRRQxICdvPc1FcCZo8QOqvxy3 IoopAQ7dQKEO9sDkYI3U+3F2WBuDFjB4jz1zx19qKKYywRxkdaCMiiikIMc0jpvX0I6GiigYiNvH oynkVJvGccg0UUxAPm4JppGRiiiiwDQuKRx0ooqWtAEptFFSwHDpTHjjlTZIoZT2NFFADY7K1jYM sKhhznmrGV/uiiiquAZXOcClDZaiii4Df4vendqKKAGsO4oyfQ0UUDP/2Q==