20220623 23072000 1.0 FALSE DeleteField R:\ssplat\dgeo\IGAM\Export_Output.shp FID_;NOME_BAC_1 FeatureClassToFeatureClass R:\ssplat\dgeo\IGAM\Export_Output.shp R:\ssplat\dgeo\IGAM.gdb CURSOS_D_AGUA_V2 # "OBJECTID "OBJECTID" true true false 9 Long 0 9 ,First,#,R:\ssplat\dgeo\IGAM\Export_Output.shp,OBJECTID,-1,-1;NOME "NOME" true true false 150 Text 0 0 ,First,#,R:\ssplat\dgeo\IGAM\Export_Output.shp,NOME,-1,-1;Shape_Leng "Shape_Leng" true true false 19 Double 0 0 ,First,#,R:\ssplat\dgeo\IGAM\Export_Output.shp,Shape_Leng,-1,-1;NOME_BACIA "NOME_BACIA" true true false 18 Text 0 0 ,First,#,R:\ssplat\dgeo\IGAM\Export_Output.shp,NOME_BACIA,-1,-1;ORDEM "ORDEM" true true false 11 Double 0 11 ,First,#,R:\ssplat\dgeo\IGAM\Export_Output.shp,ORDEM,-1,-1;FLIP "FLIP" true true false 11 Double 0 11 ,First,#,R:\ssplat\dgeo\IGAM\Export_Output.shp,FLIP,-1,-1;COTRECHO "COTRECHO" true true false 11 Double 0 11 ,First,#,R:\ssplat\dgeo\IGAM\Export_Output.shp,COTRECHO,-1,-1;COCURSODAG "COCURSODAG" true true false 50 Text 0 0 ,First,#,R:\ssplat\dgeo\IGAM\Export_Output.shp,COCURSODAG,-1,-1;COBACIA "COBACIA" true true false 50 Text 0 0 ,First,#,R:\ssplat\dgeo\IGAM\Export_Output.shp,COBACIA,-1,-1;CORIO "CORIO" true true false 254 Text 0 0 ,First,#,R:\ssplat\dgeo\IGAM\Export_Output.shp,CORIO,-1,-1;CODOM "CODOM" true true false 11 Double 0 11 ,First,#,R:\ssplat\dgeo\IGAM\Export_Output.shp,CODOM,-1,-1;DEDOMINIAL "DEDOMINIAL" true true false 50 Text 0 0 ,First,#,R:\ssplat\dgeo\IGAM\Export_Output.shp,DEDOMINIAL,-1,-1;NUCOMPTREC "NUCOMPTREC" true true false 19 Double 10 18 ,First,#,R:\ssplat\dgeo\IGAM\Export_Output.shp,NUCOMPTREC,-1,-1;NUDISTBACT "NUDISTBACT" true true false 19 Double 10 18 ,First,#,R:\ssplat\dgeo\IGAM\Export_Output.shp,NUDISTBACT,-1,-1;NUDISTCDAG "NUDISTCDAG" true true false 19 Double 10 18 ,First,#,R:\ssplat\dgeo\IGAM\Export_Output.shp,NUDISTCDAG,-1,-1;NUAREACONT "NUAREACONT" true true false 19 Double 10 18 ,First,#,R:\ssplat\dgeo\IGAM\Export_Output.shp,NUAREACONT,-1,-1;NUAREAMONT "NUAREAMONT" true true false 19 Double 10 18 ,First,#,R:\ssplat\dgeo\IGAM\Export_Output.shp,NUAREAMONT,-1,-1;NUNIVOTTO "NUNIVOTTO" true true false 11 Double 0 11 ,First,#,R:\ssplat\dgeo\IGAM\Export_Output.shp,NUNIVOTTO,-1,-1;DEDIREC "DEDIREC" true true false 11 Double 0 11 ,First,#,R:\ssplat\dgeo\IGAM\Export_Output.shp,DEDIREC,-1,-1;DECORPODAG "DECORPODAG" true true false 254 Text 0 0 ,First,#,R:\ssplat\dgeo\IGAM\Export_Output.shp,DECORPODAG,-1,-1;DELIGACAO "DELIGACAO" true true false 254 Text 0 0 ,First,#,R:\ssplat\dgeo\IGAM\Export_Output.shp,DELIGACAO,-1,-1;NORIO "NORIO" true true false 254 Text 0 0 ,First,#,R:\ssplat\dgeo\IGAM\Export_Output.shp,NORIO,-1,-1;NORIOCOMP "NORIOCOMP" true true false 254 Text 0 0 ,First,#,R:\ssplat\dgeo\IGAM\Export_Output.shp,NORIOCOMP,-1,-1;NUCOMPRIO "NUCOMPRIO" true true false 19 Double 10 18 ,First,#,R:\ssplat\dgeo\IGAM\Export_Output.shp,NUCOMPRIO,-1,-1;NUDISTBACR "NUDISTBACR" true true false 19 Double 10 18 ,First,#,R:\ssplat\dgeo\IGAM\Export_Output.shp,NUDISTBACR,-1,-1;COCDADESAG "COCDADESAG" true true false 254 Text 0 0 ,First,#,R:\ssplat\dgeo\IGAM\Export_Output.shp,COCDADESAG,-1,-1;NUCOMPCDA "NUCOMPCDA" true true false 19 Double 10 18 ,First,#,R:\ssplat\dgeo\IGAM\Export_Output.shp,NUCOMPCDA,-1,-1;NUTRJUS "NUTRJUS" true true false 11 Double 0 11 ,First,#,R:\ssplat\dgeo\IGAM\Export_Output.shp,NUTRJUS,-1,-1;NUTRMON "NUTRMON" true true false 11 Double 0 11 ,First,#,R:\ssplat\dgeo\IGAM\Export_Output.shp,NUTRMON,-1,-1;NUTRAFL "NUTRAFL" true true false 11 Double 0 11 ,First,#,R:\ssplat\dgeo\IGAM\Export_Output.shp,NUTRAFL,-1,-1;NUDISTBACC "NUDISTBACC" true true false 19 Double 10 18 ,First,#,R:\ssplat\dgeo\IGAM\Export_Output.shp,NUDISTBACC,-1,-1;NUAREABACC "NUAREABACC" true true false 19 Double 10 18 ,First,#,R:\ssplat\dgeo\IGAM\Export_Output.shp,NUAREABACC,-1,-1;NUORDEMCDA "NUORDEMCDA" true true false 11 Double 0 11 ,First,#,R:\ssplat\dgeo\IGAM\Export_Output.shp,NUORDEMCDA,-1,-1;NUNIVOTCDA "NUNIVOTCDA" true true false 11 Double 0 11 ,First,#,R:\ssplat\dgeo\IGAM\Export_Output.shp,NUNIVOTCDA,-1,-1;NULONDETRE "NULONDETRE" true true false 19 Double 10 18 ,First,#,R:\ssplat\dgeo\IGAM\Export_Output.shp,NULONDETRE,-1,-1;NULATDETRE "NULATDETRE" true true false 19 Double 10 18 ,First,#,R:\ssplat\dgeo\IGAM\Export_Output.shp,NULATDETRE,-1,-1;NULONPATRE "NULONPATRE" true true false 19 Double 10 18 ,First,#,R:\ssplat\dgeo\IGAM\Export_Output.shp,NULONPATRE,-1,-1;NULATPATRE "NULATPATRE" true true false 19 Double 10 18 ,First,#,R:\ssplat\dgeo\IGAM\Export_Output.shp,NULATPATRE,-1,-1;NULONDECDA "NULONDECDA" true true false 19 Double 10 18 ,First,#,R:\ssplat\dgeo\IGAM\Export_Output.shp,NULONDECDA,-1,-1;NULATDECDA "NULATDECDA" true true false 19 Double 10 18 ,First,#,R:\ssplat\dgeo\IGAM\Export_Output.shp,NULATDECDA,-1,-1;NULONPACDA "NULONPACDA" true true false 19 Double 10 18 ,First,#,R:\ssplat\dgeo\IGAM\Export_Output.shp,NULONPACDA,-1,-1;NULATPACDA "NULATPACDA" true true false 19 Double 10 18 ,First,#,R:\ssplat\dgeo\IGAM\Export_Output.shp,NULATPACDA,-1,-1;NULONDERIO "NULONDERIO" true true false 19 Double 10 18 ,First,#,R:\ssplat\dgeo\IGAM\Export_Output.shp,NULONDERIO,-1,-1;NULATDERIO "NULATDERIO" true true false 19 Double 10 18 ,First,#,R:\ssplat\dgeo\IGAM\Export_Output.shp,NULATDERIO,-1,-1;NULONPARIO "NULONPARIO" true true false 19 Double 10 18 ,First,#,R:\ssplat\dgeo\IGAM\Export_Output.shp,NULONPARIO,-1,-1;NULATPARIO "NULATPARIO" true true false 19 Double 10 18 ,First,#,R:\ssplat\dgeo\IGAM\Export_Output.shp,NULATPARIO,-1,-1;DTVERSAO "DTVERSAO" true true false 50 Text 0 0 ,First,#,R:\ssplat\dgeo\IGAM\Export_Output.shp,DTVERSAO,-1,-1;QMLD "QMLD" true true false 19 Double 10 18 ,First,#,R:\ssplat\dgeo\IGAM\Export_Output.shp,QMLD,-1,-1;Q95 "Q95" true true false 19 Double 10 18 ,First,#,R:\ssplat\dgeo\IGAM\Export_Output.shp,Q95,-1,-1;Q90 "Q90" true true false 19 Double 10 18 ,First,#,R:\ssplat\dgeo\IGAM\Export_Output.shp,Q90,-1,-1;Q710 "Q710" true true false 19 Double 10 18 ,First,#,R:\ssplat\dgeo\IGAM\Export_Output.shp,Q710,-1,-1" # CopyFeatures "R:\ssplat\dgeo\CURSOS PARA ADAPTAR.gdb\CURSOS_D_AGUA_V2" R:\ssplat\dgeo\SIGJF_sigplan.sde\dbsig.SIGPLAN.PRODUCAO\dbsig.SIGPLAN.CURSOS_D_AGUA_V2 # 0 0 0 CopyFeatures R:\ssplat\dgeo\ALESSANDRA\CURSO_DAGUA.shp R:\ssplat\dgeo\SIGJF_sigplan.sde\dbsig.SIGPLAN.ALESSANDRA\dbsig.SIGPLAN.CURSO_DAGUA # 0 0 0 FeatureClassToFeatureClass "C:\Users\sepur\Desktop\[MATHEUS] METADADOS\Backup Alessandra\CURSO_DAGUA.shp" "Conexões do Banco de Dados\SIGPLAN.sde\dbsig.SIGPLAN.RECURSOS_HIDRICOS" CURSOS_DE_AGUA_TOTAIS # "OBJECTID_2 "OBJECTID_2" true true false 19 Double 0 0 ,First,#,C:\Users\sepur\Desktop\[MATHEUS] METADADOS\Backup Alessandra\CURSO_DAGUA.shp,OBJECTID_2,-1,-1;OBJECTID "OBJECTID" true true false 19 Double 0 0 ,First,#,C:\Users\sepur\Desktop\[MATHEUS] METADADOS\Backup Alessandra\CURSO_DAGUA.shp,OBJECTID,-1,-1;NOME "NOME" true true false 150 Text 0 0 ,First,#,C:\Users\sepur\Desktop\[MATHEUS] METADADOS\Backup Alessandra\CURSO_DAGUA.shp,NOME,-1,-1;Shape_Leng "Shape_Leng" true true false 19 Double 0 0 ,First,#,C:\Users\sepur\Desktop\[MATHEUS] METADADOS\Backup Alessandra\CURSO_DAGUA.shp,Shape_Leng,-1,-1;NOME_BACIA "NOME_BACIA" true true false 18 Text 0 0 ,First,#,C:\Users\sepur\Desktop\[MATHEUS] METADADOS\Backup Alessandra\CURSO_DAGUA.shp,NOME_BACIA,-1,-1;ORDEM "ORDEM" true true false 19 Double 0 0 ,First,#,C:\Users\sepur\Desktop\[MATHEUS] METADADOS\Backup Alessandra\CURSO_DAGUA.shp,ORDEM,-1,-1;FLIP "FLIP" true true false 19 Double 0 0 ,First,#,C:\Users\sepur\Desktop\[MATHEUS] METADADOS\Backup Alessandra\CURSO_DAGUA.shp,FLIP,-1,-1;COTRECHO "COTRECHO" true true false 19 Double 0 0 ,First,#,C:\Users\sepur\Desktop\[MATHEUS] METADADOS\Backup Alessandra\CURSO_DAGUA.shp,COTRECHO,-1,-1;COCURSODAG "COCURSODAG" true true false 50 Text 0 0 ,First,#,C:\Users\sepur\Desktop\[MATHEUS] METADADOS\Backup Alessandra\CURSO_DAGUA.shp,COCURSODAG,-1,-1;COBACIA "COBACIA" true true false 50 Text 0 0 ,First,#,C:\Users\sepur\Desktop\[MATHEUS] METADADOS\Backup Alessandra\CURSO_DAGUA.shp,COBACIA,-1,-1;CORIO "CORIO" true true false 254 Text 0 0 ,First,#,C:\Users\sepur\Desktop\[MATHEUS] METADADOS\Backup Alessandra\CURSO_DAGUA.shp,CORIO,-1,-1;CODOM "CODOM" true true false 19 Double 0 0 ,First,#,C:\Users\sepur\Desktop\[MATHEUS] METADADOS\Backup Alessandra\CURSO_DAGUA.shp,CODOM,-1,-1;DEDOMINIAL "DEDOMINIAL" true true false 50 Text 0 0 ,First,#,C:\Users\sepur\Desktop\[MATHEUS] METADADOS\Backup Alessandra\CURSO_DAGUA.shp,DEDOMINIAL,-1,-1;NUCOMPTREC "NUCOMPTREC" true true false 19 Double 0 0 ,First,#,C:\Users\sepur\Desktop\[MATHEUS] METADADOS\Backup Alessandra\CURSO_DAGUA.shp,NUCOMPTREC,-1,-1;NUDISTBACT "NUDISTBACT" true true false 19 Double 0 0 ,First,#,C:\Users\sepur\Desktop\[MATHEUS] METADADOS\Backup Alessandra\CURSO_DAGUA.shp,NUDISTBACT,-1,-1;NUDISTCDAG "NUDISTCDAG" true true false 19 Double 0 0 ,First,#,C:\Users\sepur\Desktop\[MATHEUS] METADADOS\Backup Alessandra\CURSO_DAGUA.shp,NUDISTCDAG,-1,-1;NUAREACONT "NUAREACONT" true true false 19 Double 0 0 ,First,#,C:\Users\sepur\Desktop\[MATHEUS] METADADOS\Backup Alessandra\CURSO_DAGUA.shp,NUAREACONT,-1,-1;NUAREAMONT "NUAREAMONT" true true false 19 Double 0 0 ,First,#,C:\Users\sepur\Desktop\[MATHEUS] METADADOS\Backup Alessandra\CURSO_DAGUA.shp,NUAREAMONT,-1,-1;NUNIVOTTO "NUNIVOTTO" true true false 19 Double 0 0 ,First,#,C:\Users\sepur\Desktop\[MATHEUS] METADADOS\Backup Alessandra\CURSO_DAGUA.shp,NUNIVOTTO,-1,-1;DEDIREC "DEDIREC" true true false 19 Double 0 0 ,First,#,C:\Users\sepur\Desktop\[MATHEUS] METADADOS\Backup Alessandra\CURSO_DAGUA.shp,DEDIREC,-1,-1;DECORPODAG "DECORPODAG" true true false 254 Text 0 0 ,First,#,C:\Users\sepur\Desktop\[MATHEUS] METADADOS\Backup Alessandra\CURSO_DAGUA.shp,DECORPODAG,-1,-1;DELIGACAO "DELIGACAO" true true false 254 Text 0 0 ,First,#,C:\Users\sepur\Desktop\[MATHEUS] METADADOS\Backup Alessandra\CURSO_DAGUA.shp,DELIGACAO,-1,-1;NORIO "NORIO" true true false 254 Text 0 0 ,First,#,C:\Users\sepur\Desktop\[MATHEUS] METADADOS\Backup Alessandra\CURSO_DAGUA.shp,NORIO,-1,-1;NORIOCOMP "NORIOCOMP" true true false 254 Text 0 0 ,First,#,C:\Users\sepur\Desktop\[MATHEUS] METADADOS\Backup Alessandra\CURSO_DAGUA.shp,NORIOCOMP,-1,-1;NUCOMPRIO "NUCOMPRIO" true true false 19 Double 0 0 ,First,#,C:\Users\sepur\Desktop\[MATHEUS] METADADOS\Backup Alessandra\CURSO_DAGUA.shp,NUCOMPRIO,-1,-1;NUDISTBACR "NUDISTBACR" true true false 19 Double 0 0 ,First,#,C:\Users\sepur\Desktop\[MATHEUS] METADADOS\Backup Alessandra\CURSO_DAGUA.shp,NUDISTBACR,-1,-1;COCDADESAG "COCDADESAG" true true false 254 Text 0 0 ,First,#,C:\Users\sepur\Desktop\[MATHEUS] METADADOS\Backup Alessandra\CURSO_DAGUA.shp,COCDADESAG,-1,-1;NUCOMPCDA "NUCOMPCDA" true true false 19 Double 0 0 ,First,#,C:\Users\sepur\Desktop\[MATHEUS] METADADOS\Backup Alessandra\CURSO_DAGUA.shp,NUCOMPCDA,-1,-1;NUTRJUS "NUTRJUS" true true false 19 Double 0 0 ,First,#,C:\Users\sepur\Desktop\[MATHEUS] METADADOS\Backup Alessandra\CURSO_DAGUA.shp,NUTRJUS,-1,-1;NUTRMON "NUTRMON" true true false 19 Double 0 0 ,First,#,C:\Users\sepur\Desktop\[MATHEUS] METADADOS\Backup Alessandra\CURSO_DAGUA.shp,NUTRMON,-1,-1;NUTRAFL "NUTRAFL" true true false 19 Double 0 0 ,First,#,C:\Users\sepur\Desktop\[MATHEUS] METADADOS\Backup Alessandra\CURSO_DAGUA.shp,NUTRAFL,-1,-1;NUDISTBACC "NUDISTBACC" true true false 19 Double 0 0 ,First,#,C:\Users\sepur\Desktop\[MATHEUS] METADADOS\Backup Alessandra\CURSO_DAGUA.shp,NUDISTBACC,-1,-1;NUAREABACC "NUAREABACC" true true false 19 Double 0 0 ,First,#,C:\Users\sepur\Desktop\[MATHEUS] METADADOS\Backup Alessandra\CURSO_DAGUA.shp,NUAREABACC,-1,-1;NUORDEMCDA "NUORDEMCDA" true true false 19 Double 0 0 ,First,#,C:\Users\sepur\Desktop\[MATHEUS] METADADOS\Backup Alessandra\CURSO_DAGUA.shp,NUORDEMCDA,-1,-1;NUNIVOTCDA "NUNIVOTCDA" true true false 19 Double 0 0 ,First,#,C:\Users\sepur\Desktop\[MATHEUS] METADADOS\Backup Alessandra\CURSO_DAGUA.shp,NUNIVOTCDA,-1,-1;NULONDETRE "NULONDETRE" true true false 19 Double 0 0 ,First,#,C:\Users\sepur\Desktop\[MATHEUS] METADADOS\Backup Alessandra\CURSO_DAGUA.shp,NULONDETRE,-1,-1;NULATDETRE "NULATDETRE" true true false 19 Double 0 0 ,First,#,C:\Users\sepur\Desktop\[MATHEUS] METADADOS\Backup Alessandra\CURSO_DAGUA.shp,NULATDETRE,-1,-1;NULONPATRE "NULONPATRE" true true false 19 Double 0 0 ,First,#,C:\Users\sepur\Desktop\[MATHEUS] METADADOS\Backup Alessandra\CURSO_DAGUA.shp,NULONPATRE,-1,-1;NULATPATRE "NULATPATRE" true true false 19 Double 0 0 ,First,#,C:\Users\sepur\Desktop\[MATHEUS] METADADOS\Backup Alessandra\CURSO_DAGUA.shp,NULATPATRE,-1,-1;NULONDECDA "NULONDECDA" true true false 19 Double 0 0 ,First,#,C:\Users\sepur\Desktop\[MATHEUS] METADADOS\Backup Alessandra\CURSO_DAGUA.shp,NULONDECDA,-1,-1;NULATDECDA "NULATDECDA" true true false 19 Double 0 0 ,First,#,C:\Users\sepur\Desktop\[MATHEUS] METADADOS\Backup Alessandra\CURSO_DAGUA.shp,NULATDECDA,-1,-1;NULONPACDA "NULONPACDA" true true false 19 Double 0 0 ,First,#,C:\Users\sepur\Desktop\[MATHEUS] METADADOS\Backup Alessandra\CURSO_DAGUA.shp,NULONPACDA,-1,-1;NULATPACDA "NULATPACDA" true true false 19 Double 0 0 ,First,#,C:\Users\sepur\Desktop\[MATHEUS] METADADOS\Backup Alessandra\CURSO_DAGUA.shp,NULATPACDA,-1,-1;NULONDERIO "NULONDERIO" true true false 19 Double 0 0 ,First,#,C:\Users\sepur\Desktop\[MATHEUS] METADADOS\Backup Alessandra\CURSO_DAGUA.shp,NULONDERIO,-1,-1;NULATDERIO "NULATDERIO" true true false 19 Double 0 0 ,First,#,C:\Users\sepur\Desktop\[MATHEUS] METADADOS\Backup Alessandra\CURSO_DAGUA.shp,NULATDERIO,-1,-1;NULONPARIO "NULONPARIO" true true false 19 Double 0 0 ,First,#,C:\Users\sepur\Desktop\[MATHEUS] METADADOS\Backup Alessandra\CURSO_DAGUA.shp,NULONPARIO,-1,-1;NULATPARIO "NULATPARIO" true true false 19 Double 0 0 ,First,#,C:\Users\sepur\Desktop\[MATHEUS] METADADOS\Backup Alessandra\CURSO_DAGUA.shp,NULATPARIO,-1,-1;DTVERSAO "DTVERSAO" true true false 50 Text 0 0 ,First,#,C:\Users\sepur\Desktop\[MATHEUS] METADADOS\Backup Alessandra\CURSO_DAGUA.shp,DTVERSAO,-1,-1;QMLD "QMLD" true true false 19 Double 0 0 ,First,#,C:\Users\sepur\Desktop\[MATHEUS] METADADOS\Backup Alessandra\CURSO_DAGUA.shp,QMLD,-1,-1;Q95 "Q95" true true false 19 Double 0 0 ,First,#,C:\Users\sepur\Desktop\[MATHEUS] METADADOS\Backup Alessandra\CURSO_DAGUA.shp,Q95,-1,-1;Q90 "Q90" true true false 19 Double 0 0 ,First,#,C:\Users\sepur\Desktop\[MATHEUS] METADADOS\Backup Alessandra\CURSO_DAGUA.shp,Q90,-1,-1;Q710 "Q710" true true false 19 Double 0 0 ,First,#,C:\Users\sepur\Desktop\[MATHEUS] METADADOS\Backup Alessandra\CURSO_DAGUA.shp,Q710,-1,-1;Shape_len "Shape_len" true true false 19 Double 0 0 ,First,#,C:\Users\sepur\Desktop\[MATHEUS] METADADOS\Backup Alessandra\CURSO_DAGUA.shp,Shape_len,-1,-1" # Project "Conexões do Banco de Dados\NOVO_BANCO_SIGPLAN.sde\dbsig.SIGPLAN.RECURSOS_HIDRICOS\dbsig.SIGPLAN.CURSOS_DE_AGUA_TOTAIS" "C:\Users\sepur\Desktop\[MAT] SIGPLAN SIRGAS2000\dbsig.SIGPLAN.RECURSOS_HIDRICOS\CURSOS_DE_AGUA_TOTAIS.shp" PROJCS['SIRGAS_2000_UTM_Zone_23S',GEOGCS['GCS_SIRGAS_2000',DATUM['D_SIRGAS_2000',SPHEROID['GRS_1980',6378137.0,298.257222101]],PRIMEM['Greenwich',0.0],UNIT['Degree',0.0174532925199433]],PROJECTION['Transverse_Mercator'],PARAMETER['False_Easting',500000.0],PARAMETER['False_Northing',10000000.0],PARAMETER['Central_Meridian',-45.0],PARAMETER['Scale_Factor',0.9996],PARAMETER['Latitude_Of_Origin',0.0],UNIT['Meter',1.0]] SAD_1969_To_SIRGAS_2000_2 PROJCS['SAD_1969_UTM_Zone_23S',GEOGCS['GCS_South_American_1969',DATUM['D_South_American_1969',SPHEROID['GRS_1967_Truncated',6378160.0,298.25]],PRIMEM['Greenwich',0.0],UNIT['Degree',0.0174532925199433]],PROJECTION['Transverse_Mercator'],PARAMETER['False_Easting',500000.0],PARAMETER['False_Northing',10000000.0],PARAMETER['Central_Meridian',-45.0],PARAMETER['Scale_Factor',0.9996],PARAMETER['Latitude_Of_Origin',0.0],UNIT['Meter',1.0]] NO_PRESERVE_SHAPE # NO_VERTICAL CopyFeatures "C:\Users\sepur\Desktop\[MAT] SIGPLAN SIRGAS2000\dbsig.SIGPLAN.RECURSOS_HIDRICOS\CURSOS_DE_AGUA_TOTAIS.shp" "Conexões do Banco de Dados\NOVO_BANCO_SIGPLAN.sde\dbsig.SIGPLAN.RECURSOS_HIDRICOS\dbsig.SIGPLAN.CURSOS_DE_AGUA_TOTAIS" # 0 0 0 CopyFeatures Ambiental_Cursos_dagua C:\Users\leonardo\AppData\Roaming\ESRI\Desktop10.8\ArcCatalog\SISURB_ambiental.sde\AMBIENTAL.RECURSOS_HIDRICOS\AMBIENTAL.Ambiental_Cursos_dagua # # # # AMBIENTAL.Ambiental_Cursos_dagua Server=172.31.12.203; Service=sde:sqlserver:172.31.12.203,15010; Database=dbSIG; User=ambiental; Version=sde.DEFAULT ArcSDE Connection 635913.558000 691886.360800 7566573.437500 7619293.583700 1 0.000 002 Geographic GCS_SIRGAS_2000 Angular Unit: Degree (0.017453) <GeographicCoordinateSystem xsi:type='typens:GeographicCoordinateSystem' 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>GEOGCS[&quot;GCS_SIRGAS_2000&quot;,DATUM[&quot;D_SIRGAS_2000&quot;,SPHEROID[&quot;GRS_1980&quot;,6378137.0,298.257222101]],PRIMEM[&quot;Greenwich&quot;,0.0],UNIT[&quot;Degree&quot;,0.0174532925199433],AUTHORITY[&quot;EPSG&quot;,4674]]</WKT><XOrigin>-400</XOrigin><YOrigin>-400</YOrigin><XYScale>999999999.99999988</XYScale><ZOrigin>0</ZOrigin><ZScale>1</ZScale><MOrigin>0</MOrigin><MScale>1</MScale><XYTolerance>8.983152841195215e-09</XYTolerance><ZTolerance>0.001</ZTolerance><MTolerance>0.001</MTolerance><HighPrecision>true</HighPrecision><LeftLongitude>-180</LeftLongitude><WKID>4674</WKID><LatestWKID>4674</LatestWKID></GeographicCoordinateSystem> 20230809 14212200 20230809 14212200 North American Profile of ISO19115 2003 AMBIENTAL.Ambiental_Cursos_dagua Feature Class 0 OBJECTID_12 FID OID 4 10 0 Internal feature number. Esri Sequential unique whole numbers that are automatically generated. OBJECTID_1 OBJECTID_1 Integer 4 10 0 Internal feature number. Esri Sequential unique whole numbers that are automatically generated. Shape Shape Geometry 8 0 0 Feature geometry. Esri Coordinates defining the features. OBJECTID_2 OBJECTID_2 Double 8 38 8 OBJECTID OBJECTID Double 8 38 8 NOME NOME String 150 0 0 Shape_Leng Shape_Leng Double 8 38 8 NOME_BACIA NOME_BACIA String 18 0 0 ORDEM ORDEM Double 8 38 8 FLIP FLIP Double 8 38 8 COTRECHO COTRECHO Double 8 38 8 COCURSODAG COCURSODAG String 50 0 0 COBACIA COBACIA String 50 0 0 CORIO CORIO String 254 0 0 CODOM CODOM Double 8 38 8 DEDOMINIAL DEDOMINIAL String 50 0 0 NUCOMPTREC NUCOMPTREC Double 8 38 8 NUDISTBACT NUDISTBACT Double 8 38 8 NUDISTCDAG NUDISTCDAG Double 8 38 8 NUAREACONT NUAREACONT Double 8 38 8 NUAREAMONT NUAREAMONT Double 8 38 8 NUNIVOTTO NUNIVOTTO Double 8 38 8 DEDIREC DEDIREC Double 8 38 8 DECORPODAG DECORPODAG String 254 0 0 DELIGACAO DELIGACAO String 254 0 0 NORIO NORIO String 254 0 0 NORIOCOMP NORIOCOMP String 254 0 0 NUCOMPRIO NUCOMPRIO Double 8 38 8 NUDISTBACR NUDISTBACR Double 8 38 8 COCDADESAG COCDADESAG String 254 0 0 NUCOMPCDA NUCOMPCDA Double 8 38 8 NUTRJUS NUTRJUS Double 8 38 8 NUTRMON NUTRMON Double 8 38 8 NUTRAFL NUTRAFL Double 8 38 8 NUDISTBACC NUDISTBACC Double 8 38 8 NUAREABACC NUAREABACC Double 8 38 8 NUORDEMCDA NUORDEMCDA Double 8 38 8 NUNIVOTCDA NUNIVOTCDA Double 8 38 8 NULONDETRE NULONDETRE Double 8 38 8 NULATDETRE NULATDETRE Double 8 38 8 NULONPATRE NULONPATRE Double 8 38 8 NULATPATRE NULATPATRE Double 8 38 8 NULONDECDA NULONDECDA Double 8 38 8 NULATDECDA NULATDECDA Double 8 38 8 NULONPACDA NULONPACDA Double 8 38 8 NULATPACDA NULATPACDA Double 8 38 8 NULONDERIO NULONDERIO Double 8 38 8 NULATDERIO NULATDERIO Double 8 38 8 NULONPARIO NULONPARIO Double 8 38 8 NULATPARIO NULATPARIO Double 8 38 8 DTVERSAO DTVERSAO String 50 0 0 QMLD QMLD Double 8 38 8 Q95 Q95 Double 8 38 8 Q90 Q90 Double 8 38 8 Q710 Q710 Double 8 38 8 Shape.STLength() Shape.STLength() Double 0 0 0 Hidrografia, Recursos Hídricos Classe de feição (polilinha) que traça e identifica os cursos de água alocados dentro da região 'sudeste' de Juiz de Fora. Traçar e identificar os cursos de água alocados dentro da região 'sudeste' de Juiz de Fora. ArcGIS Metadata 1.0 Ambiental_Cursos_dagua Classe de feição (polilinha) que traça e identifica os cursos de água totais alocados no perímetro municipal de Juiz de Fora. Traçar e identificar os cursos de água totais alocados no perímetro municipal de Juiz de Fora. Hidrografia, Recursos Hídricos Hidrografia Recursos Hídricos -43.687266 -43.140892 -21.999667 -21.518357 Microsoft Windows 10 Version 10.0 (Build 18363) ; Esri ArcGIS 12.9.0.32739 1 -43.687694 -43.141314 -21.518817 -22.000131 Classe de crição criada a partir de consulta ao banco de dados do Instituto Brasileiro de Geografia e Estatística (IBGE), bem como geoprocessamentos realizados no ArcMap com esses arquivos. 0 EPSG 7.8.3(9.2.0) 6.11(9.2.0) Enterprise Geodatabase Feature Class Simple FALSE 0 TRUE FALSE iVBORw0KGgoAAAANSUhEUgAAASwAAADICAYAAABS39xVAAAAAXNSR0IB2cksfwAAAAlwSFlzAAAO xAAADsQBlSsOGwAAIABJREFUeJzsvWeTJGeWpfe4dg8tU8uSKKCqG2JaDHdm1oZrxiVtjZ9o/AU0 fubfofE7f8LSuGu2tJkd0T0tABRUyaxKnRlaebgWtPfNAlDoxUxjeqa7kYAfM1QVsqIiIyLDT9z3 3nPO1fM8zylQoECBawD9j/0AChQoUOCboiCsAgUKXBsUhFWgQIFrg4KwChQocG1QEFaBAgWuDQrC KlCgwLVBQVgFChS4NigIq0CBAtcGBWEVKFDg2qAgrAIFClwbFIRVoECBa4OCsAoUKHBtUBBWgQIF rg0KwipQoMC1QUFYBQoUuDYoCKtAgQLXBgVhFShQ4NqgIKwCBQpcGxSEVaBAgWuDgrAKFChwbVAQ VoECBa4NCsIqUKDAtUFBWAUKFLg2KAirQIEC1wYFYRUoUODaoCCsAgUKXBsUhFWgQIFrg4KwChQo cG1QEFaBAgWuDQrCKlCgwLVBQVgFChS4NigIq0CBAtcGBWEVKFDg2qAgrAIFClwbFIRVoECBa4OC sAoUKHBtUBBWgQIFrg0KwipQoMC1QUFYBQoUuDYoCKtAgQLXBgVhFShQ4NqgIKwCBQpcGxSE9R1C /uoXRfljP5ICBX4/KAjrO4I8zwnihDiOMXUNyzTl15WCvQp8h1AQ1h+lDPrmN83zTP5ZQRG/vPra qzvJc/ElcgUWQczPHj7kw48/5M7WOv/h3/0P8ramrqOqqrjpl/cq/qyo8t++uvOr+/9dUFRzBf6A KAjrWwtJTbJCyskk4Yj/BD+IryVJwnyxwHFsPnh8wOHZBUenh4zGI/Ik5+D/+j9RnCb/y7//d+xu rF9VWuI+FEFNV3f0OYdJ0pPf8ur7FSjwbUVBWN9SpOKIl2QswwQ1T6jYFrouqiIFz/d5dnzK37z/ MUoS4scpYRyTZVCrN/GTFEu3mM+mfPLkMY5lsNrpyOZWlufyPh1DRde0V4QoIMjqdyCu11mvQIHf MwrC+hYiJyeMIs4HIx6fnBPHCbe31uk2qlRLjiSny8mMg/MeWhpSKtnUGi2yNMNz52iGTpwlTAbn eMtdMsFkKJIEx8uAX3/2HCUJuLm5yuZql5LjvPrOgryuqq+Cfwp8G1EQ1rcMkjDEr3lGFkeE3oKD yzGT+YJ2yeDO9gaNZoul56FlMaVKBVVJMS2TOM6I0hxTU5hNJgz7fYIwIopi4jgiyjVOx0t+/vBT +W8W3pI0h0atRpomlEydRqP+irg+J62Cugp8e1AQ1h+72f5FA+mqmS4a6AKaolKtlLh3Y4+B6/Py 4oJHkwuC5W3euvcD+v0ey9kA1DV8b0qWpTjlOoZtkyUhdqlCY3WHg7M+racH+FFMplkcD5e43pKt 7W1OJy4cnWMbA/zFjK1WmZ/+6EevGvBX1PnFwyx6WwW+BSgI648N2Ux/vWd0RROT+Yx/ePiQo8GE fu+EamsVxcgYToYcXI5wo5xSs0213uDw8IA0jqhWPMIUNnf3MQ2H3Ttv8dkHD/nr9z/hg6cHaKpK ub2OruTopok3nXE2nhH5PovLE+brHd55+100JUHXdNQvHpPyG4+xQIE/DgrC+hZANr5f6Q6UV2VN u9ngvQcPmP3Dh0yqm4wnUyajmOFyzunyKUkcsba+j10u82/+8t+znPZZTMdYhsbSXXBw8DPCMCYI NborK+hqhu8HLE8vaTQbHB89p1YuYytgaTla3UGv1PjZpwcYyZS3bt+lWW/Kauv1x/ePomi+F/gD oCCsbxFeP4Rpmk670eSH9x8w+/VHmEpMnjaIM/Ejy9GIGRz8gnK1idlYJ/Zd4jAgVQwUbUlrfY8P 33/I7Zs3MZQEy7bobN/g4OkjppMRdrmEniUkoY9dKlGqdXG9gEfPn5MtzlFzhTfv3KNRr3+hBfu8 r/U7a7YKFPgXoiCsb4lQVEoKPtd0CokBCnEU8+jpY9zFBG8xJU0S0HWCwCNwp1iqzdlZnzXFIRFN ehQsU6VsmSynI978wQ9YX9/AHV2SJiFkId21DT74u79i7+49HKdMlmd4izl56FOuNYnDiPnM5azX Z3tzh3q9dvX4Pm+/f9mNL1DgD46CsL5FfJakiSSqhefTn0zpjyYcnZ2T5wmBv2Q2d1kGMSgatWoV 1ShR69SkHSfTNCzHwdY1bNPBbHUxTAfyjARdVlLe+BxTt9nc3qVSa2PbJRQlIw5VVEVF1S1UcoIo 5enLF+ztbNNq1qQsouyU0TTt6jF/XT+rILECfwAUhPVHxSunspgO5jkfP37G0lvihjEXkzkL10VR VaKlT5bGkCWQpWiGiWU6kiM2dm8w7p1I4jN0jTyJWS4DnJLNYjQA3SKKM9nPSrwppbLD5u4umeoQ BD6OpeOUS6Qp+MuFvE8xoeyNx3z09DnjxRKVjNs7e5LAPpc6FE34An8M6N+7I9m3phK40lt9/ufx bM5/+rtfcHR6hGXZaKZFniRUHZvRdIaap1SdEqtrXTTTYXhxhmY7qKomG/VCA5/HKcvZlMkyQFeg WipT7VSxlJzlLMXzY8xKg0X/As2qkCWRPPKVhFDVXxJ4Ho2SQbVaIdMVHj4/4pePXlCyVHrDATtb m2j/2OTw646+35rXusB3Bd99wvqW4fWL/HMjc5bl/Ozhp5iNLs00YTLsMXhxzvjyFMfQefvf/k/M xyOG/XO00RRNU5mP+liWw/beHuOTI2r1Gkatzmwx5+zynLt3H7B16w5xAt58IpXweXsVVRzr4gmH n37I9p230Mtt0jwhzpbkTpX2zTfl91V9D8vU6KxuYhk6Z70LojjG/jwF4mueT4ECv2/o37cEhH9S wPmvhd+mAJASAXEcfNViz4UVJyANXFLRj0ozqrUyq937uLMRlVqVimNS0nPi0KNUrXHjzR/KY97o 6UM5yXODCDedUVvdZK/RluboT3/5X1nduc1icIGimZQ764xPD9h740300AdFxzBMlMgnmJySaBaH Hw1pdHeJvSmaU6NcrWKXyiQGfPz4MT944x6Waf3zXoeCzwr8K+G7QVj/GvijTL+uZm/CkHwxXvDs 0UeUmx1WNveZ9M45fvQhqlmSUTCnhwecH76g1uqilRsMXzylLkSg5ZY88mWKxtSd4y5GmI4FVp21 /TekhUevtahU6yiKRqJofPaLv2bv3g+pr+xiWAZhmFKrNsGqMhmcYk3PMXQTTbdwJwNmw0vKliZ7 aqIa/M0Xq6iyCvyhUBDWv6Qi+Bf1bb48Fma5gq4ZrKxtMR5cMuudkysq9c4aw0GP4cUJumVRrtdR RfbVZEzv+JjReMK9++8SuxOUxKdq6ShaGS8MWOtWSZOYJM1QdZN+fyCb6rV6A01VsGtdZr1TvNkY p1Kis7JCKgzTqoFdbVFfv8FsOpbHSdO0UPUmHz1/yVt338AyDamaL0qnAn9ofC8I6wsV+b9mr+Wf Ova95g/8Jo9L/B5NLrFVSAKf6WiIKSQKpbLsTYlYGdtu4k3HJCJR1HLYunGHIElk4zyPlih5hl2u YdkVKmmGoSnoVglfHBUnfXzfI01z5uJ2RkYceJCEr6QKmpwYpolPnoQomophlyhXElJ/QeIv8BWV IM958vQx5r03adQb0rrzj76mxTGwwO8B3wvC+rYdXcQRMHlFaMLXJ4SiQqnuz11My6K1soImkkI1 XVZJtmmhKCqGYcjfhR2nVKkSp5kkEz3P0EsVQoSsIaGzusZiOpFqecfQ8NIIxzZRjTL9izO8bE6n u0GjWqPW6hCFQog6QzUtSrZF7M+ZhgGlaotqoyOPp+FyiW3qPDp4LuNobt+4Sb0mkh0K5XuBPxyu P2Hl37yykmkI34S0/jlN/N/h34pIlzCDOElR0hA1TTBqXdTUpFmOUYjQNINcK3F5ciqV6IahUW+3 5RHPnY85PX6JXSlL+06ml7DKdVJ3zujiQk4RzXKNi8PHVGt1ao0mSaaSqbrsZcUBqFaJBA2iAC31 UU0Ns9qkXm+yGJ0yn53Jqs2ptim1VuQwYHD6HNOx+fjRp5Qck0qlJI+yV/iN1/QrUQ//gtezQIHv FGH9Bj5PzBT4TWJ6nbj+GJXW59ewJqqqNGYwnnF4cUE9Dzi/OKO2eZOchMXgjIuTF/Qv+6xs3aTW 3WJ08hmGroLh4HoLBoMTbLeEEi1wKk0ctUVrbR3DsZiMe1RVldlsytxdosQRlUqZSr1Fu2rRuvUA xXKuPIKqRq7qMncr9E9ob98iDhZEScbCnbOYDohDl876Plq6IPHG9Nw+5+cdNtY2aAq5xOdH4N/H 0btAge8UYb2eJ/Ubf/VlwsDVVOvrLqTfTCGQt/mGPajX7+ObXKSfh/P1BgN++ckjPjl4ieiiCzW7 VbUJ5j1yTWM6G9LrXxJjM3M92XBfW+niBT5eAo5Tpbu2T6NTJ3PHNFfWZd9p2r8kSWJWN7bpbN5E SyMqjRaBt6B3diItPzfv3uflZ7+ksX6H2bRPs92i0d0gN6ccP/mA88GYBz/6C/Rhn9lkzHSyRNUU Vpwm3f13WbgevdMn2PYjNta2aNTbV4kOn7/KBVkV+D3i+hPWf0MsrzY1kJPmCmMvlgmcJV3F0NSr +N9vEpfym/f6W27/daT1+pFU/vnVX0+WPsdnJ5ydvqSxuiG1TmcvD6RfcOvWW2zffItybYXB6TFp OOPlw7+m0WgTpjlJmmIaBk6pxOHBE2yrgrOSoCsJaCYZGkcvj0hyjfHglGqrg11uUmln8jg5nS+l jqvebGJZOrPBGUng0l5bY2PvLk8+fsjRZx9S7awReS7ueIBu6QxPnlCtNMn8GXe31vnJO3/C3u7+ VajyFVP9s17PAgW+n4T15cqXL44k4ojixxlHY5enL45wSmU223U2mhXqJUtKA66OMa8I5Z/qv/wW 8nqdpP5pUnsVxQDEuYJilWh01+iubbI4/Qzfd5nP51Tnc0k6gizqrRaTkwsq1TU0w8ZQU1BTOZ1r 1Gwarfc4O3ohj4rCWjOfjKRAVHPKHB4e4S889OMjqtUG1UoZw7SIwogMFW8+YjHuk4YefuoxOJqD qrN/8w3KpTKZrmFqyEZ7jM5y7qGrjtRhpWaVWNVJslRWjVdF6efLLL7+qX/xsypQ4HtNWK9JA+Tv CLJKORxM+auf/5IXL15QqjXY6Ha5vbPB3d0tNtr1L48wcvXVVZzLNw7Z+0o18dsVp68TmfizICY/ WOLYGraWE5JSqjXRSnXZkJ9Ox0TLpdxq01jdpbG6TRqlpEtXaqDSLGM6uGBz7xYIu4xlo2Yxga5I LVWwDPDdOd3VdaLlnEDormwDDR0lT3CXHsvZU/JgQa21KhvwS8/FtnIa7Sa+50EYyB5XtdnBqjSp iLC/cpW4/5LEMDkbjmifn3Frz8K2nH/hpKJAge8JYb3eZBe/enHCyXDCB4+e8tmjz6Shd7ZYMBsP mc1mBFEE2TatWvWVL+5zAWf+W/pXr33xFT9d3fQL6vtKksHX30MuTcSn56dMhheQ+ix1g1JzHXMS SUJB09F0kzzXmF1esPL2OwwnY1J/SZ6mVOoddNPCW/ocPXvMdDyWz9HUdOrVBkEQMBsNKdsGjgq5 ZZAlCePBUB6JdauMZjgsFzMcVcOwLAxHLLIwxF4dJr0zWZ3qcnJYorW2LY+PKrHcj2jaKrqhcCaG BKbG5uqGJKzPfwKvvxIFCvxr49oT1uerqZRXldXJcMqHT57w6NMPZW75WqtN4AdEUcDlsE+cRrjT EXd2Nnjz9i3ppYuTRB5rxJbkq1bT1xzzvkiw+/IYKr7vl1XXK958/TbyDr40OQ/nLr/6+BPORmOp r4rFFK6aUCnX8BcufpLQXNmk3lrFtzzm44nceHN6+JJgMaZUaZAqJvVmi839Wxw8fsJ8tqB/dka7 0yXPRRCMTmdlE9GuOz44YHVziziN8f05tqVRrmRsbO4xMBxid0gcRZjKHBOFIIVF/4z23l28kYdT qlCtt+SCC9/tE7oDdLNCFgWM51NODZ3haEiz2fzyCRcBfwV+j/gOENbVtSLEmOdTl0cvXnB6dEAY hcwmc2J/Sa1WIyYl8EN6UcCgd8Yvf/0L/o///X+jUaszGE9l9bHWbqLrQpz5ZdUlkIkGfpqSZulV nAtiuKeiqgphFEv1uW0J753xpdbrqrsviUz0fYI45T//8iNevjjBEJHElSbzICTMdCZPP0S1y6xU ajSaHXIV4mhJycqJR0fc/+GPePHimZz0Taefsrq6xv6N22zt3ZaTPEVVsMpVGdKXpSmbmzv47giD mxw8e4FZrrJ35w2qJY3hi/extjdo1SzGXog3n+PlBqVah/X9W6iKTqOzQbm1wah3zvzpx9QqZWrd DpppMzl7LjVeTqXO+WDAf/3b/8r+3j66rv2Wo3OBAv9yXH/CenVxhKnCdOlxOZowciPs2ipbjXVq ryqEWhTJqkNVNIIoJoxD/u//9DeYSsrSD6mUHN67d5s/e+eHXIUNX1Vu4uIT9/vi+Izjs1O2t7bI olCufxc7/A5Oz/nkyXNaZYs//+lPUFVVEpiIcRFqdeG5Ezv/epMJx8cHjI4+wGptk2IwDxMY92l1 t1mtt2WUcZbF6LZDs9XBJOXsxRNOL/4G1TC4+9YD/CDkQlRcH39MuVzhzXf/lLKIMVYUQndE4s1I 11bpbN0kSg7x/Y+lcr7VEQkOMUsq/Pxv/orNbhnVqrJ7/z0iz+P82UecP3NRxeEvSRmcv8S2bWzR +B8OmMynvPHujzj8+Oes1FexK22GswVn58dcXJywvb33Whn6ZV/xK6RViEkL8H0nLEEvOVwsUz7+ 5CHnp0couo2/dImTSE7ITp5+gk4mLS5L32MyHaPaJW7cfcDEnUn5Q5oEnB0943SlxdbWzpWo8tXF 5vohx+MpH7044j//1V+xsbFH7E7ZvXGDSmuF89GEjz58ztF4KckuCgJ5HG1Vy9zaWGV/Z4vHBwec PvsQq7pCnOtEaUyAwvDsBblyQ04OtSyh5JRkn+3k4DHz0YD17RvMhAHZtun3LmQvKk/BdpoMxzOs egevd0FnZZVStc0sTOhf9Dg9PiQLI2nnERufXzx5xOjihMCbYusKdn2fYD7j4vGHlKp1KSod9S+4 8/af0r84gcRHCVPMcp1Ktcr4/ASnXGPr3o8IfZdZ/xDT0lGdOv/f3/8N/+v/vIpjO1+ZP/yTFVZx dCzwfSMsUVzFOQwXAZcTDy8MsewymCVib0HJKXN++BxFN5lNhszTGaVKjVpzhcvLE4YXx9iVBkvX ZerNsEm4v1iwLftOr6KLyXHdGRdnxwyHA0y7TBCGeEnOx0+f015xpQwg10xeHB4gUtlDd0qt2WHu t+hN53zw/IVcLW/WOvLop5u2rGqSXKFW79DubpLFIUkckIsjVRqi5BGO4zAe9qh314jTRB5LEXae RMHMFVo7t+ifnrJ0Z/K5NmoVojBgPJ3ImJr5cMTa2jqt1at/P7ctgkDHqbewyy36p+cybjnKPZIo pFRfQddt2dTPM5HLlRK5YxmR3Fxdkymn3vhMHg0tJZFi1v0bb1I21Kuj4Gtryr7RcbCouAp8nwgr TlPOJnN+8bO/wbMaeEEkg+vydImQUGZhgGkI7VFAudaWRzVFv4oAnrlzTKtMluay8TwYjqhbpvTe vY5lEDGczBkNBoTzGVt7dyGNMCurMmtqMh4Tej5Ovcvzxw/x45i1TgfR6RL9rYUfyK03l+fnVByD dq1FFIZycldyKgRhgJIm0sM39hdMxgP8wEPVDTa2N5iNBliGQbXRJg0igqlLkkRE7gKz06ZWcuQu wpJdkr0ysZBCegBtm1kaY+UxJUMlNkvyeCy0WJoCUaagWhVM05QpDlGc0FptEUWhJNyybcmgPkFc IitexNEE7lyGC2pZRqNa5fbOLvfv3ZOPTwYBfj4nLXpXBX5PuNaElWY5o4XPp598gN7eIUoSuURU bC2uVSosZ3O5SWZ8cYJTa8r4lTgK8ZZLDMOmVG0yGQ0keZApUlQpyOuqDZPLJrsn1l55IWGUUjIM LKfEtD+iXKpi2SX8+QRXaKo2dsjRmQwv2VjflpsD0zBEE9EwloOh6bgzUeE18D1f9rccu4Tnzq/M z0qObZiMZzPmSxddVWRulVio6rlTKS/I2yGZHxAHEWmUMO8dU+90Uc2avP1sOsVd+tQaV0JRt1qW eVeLWQu90sDUDfRKncBfoNkVactR0og8VzBt66rnpOuk/gyrIhIjVDSriV1tkMRCYR+SWFXyLMUy SzQbbdrNtkyQ4LXq6ndCcUQs8F0nLNHgFj2fcmeDWFVR4oQsjUiEvqjapqLpPPvkI0li0/mUemeV Sr1JsFySRiHz2UhGq4jLbXVtHcsx+cWvf8XNvX158V4MxgymMwajgZRFiNSDSqPB4aNfodgV3NkU JVhQqVZkT+vWvQdoYoGEYcsqSEky1ESnXHL4wTvv8eSTj7g4PUE3nSsRZrKkUq7SabeZDM5R0GTV JQgkDn0mw74kSS1wiRZjKiUb58YNkiSTqvZp75TL8yOq4jkFAcPRQBqehR2nLAjKMJmqJsPZkrpe wnFK0uTsVBs0W03m7jm+G2BXWlSsMp67RNU1GbksKrFQELkp0iVUppMBtpoTLj3Mki1ztmazOYHv y/2GV7KOqyb778w939qFIQW+LbjWhCUgxIxictZc61K2Tbxpj1G/RxhHKOGMUKzHMh3KVbEQNCON fbZv3r4KsxPVRzRhfWuXTqeDN77g6PRYHuWETOL/+ftf8otf/5LB5Zns56ysbbJy15D3J0Lxmo4u j0jz/hGJaqPVV3jrjTdQIg93McUXNhhVJ4qWeJNzlsFC9riGl+dyKWq3u8bm1gYvH/0Ks9zi7PiI 9d0bdDtdguWC9oqw5FikmcKgL8hlQq3eFCtyGJ4fs7p3h2ePHrK1uinJTfSy6s2GJJz5ZMrxwXNW du4wHg7l93vz3XdJwxqe53Lx9KGslBbTGXYYsr5zC6tR4emHf0vZsqh3Nqi316QJ++SjX1AxDcax Qmu1jZouGUyGPHn5gpWVNe7efVOS7Os/lUI+WuD3gWtNWOJTXVc1Zt6C41//LWXbptpaY3ftDmka E4dlMsUkjFN57DMMXR7zDp99zL0f/ITZuE97bZ1RX0zPxlLxPRzO+X//+v/DaW7QG/VJ85SdO2/R Wd3Am024OHoqv3e1XJWNcdFIb7W2GI5HzIeXnAK1ioNulMi8gCzxWd29LyufkumyubvH8eGBJI32 +obsfVW39lm6c+zFkst+D1vr07A13Euf6dxn/e7bTAc9DNMkS0OWkwEoCdVahR/85M/IRR/u7IzU 94nEIlR3Tn1vhd31Ds3VDqsbG+SKxng4oHf4GZHv0d6+gWOalCp1DNtm4XkMT1/y5JOHPPjxn5GZ JcbjIf74UuZlTSZztm79QB6pRSVXqVRwylV0Q6jyc6lLe13VID5IpA7tK2PDr1ZRX5E9fJ3DoPAg Fviu9bBEj6nWWOXo+IQ414jGY8p+QLfb4cXLA8rVJp3uilRoC3OvkBN4ixnHzz+hs75HFLhk1YqU NmgZrGzu8vefPqe96vHi6CWLpYsijMeToVBzyupmfXNX2noSfyY1XmmakaLRXN+jU69gWld9q3qj RpRmBJ7L4eP36ezdx3TK1Ot11le7bG/vE/guwcUjnO4N7tx/hyQIWM7GuOM+wXTOrXf/nMmoL/Os BATxRlHKYDihMbikXhMq+TmNZgWyNdzlUqaZ9p99xOaDH1OvNTk/eMJy6dJY22TvzXc5f/oBmVzt pdNor2M7Nu5syHLaJ/JjKtUmge+RiIpwOSKLPDnNdPsnDJeprEgtXeHg6FSmP9w9PWd3Y4tqpSRV 72Kv4hUPvbLq/CO7C4vmfIHvFWGJFeqekAeEIW3Rx4pT0twgShUuekOsSpflckm5qcvejLdcEAQh umHhCi/fakq5XCYIPCbDIUk8olKtUW20ODk9lZ671Y2O/F5xlNCs1pj3xa5Am8uzQ4IoxJHKdJPJ eEpn1cYXjXbFwE99kkwcQpHSgRt3f0iiWOhJwM7GBpZtY1mWVNYff/YrlEAliWLZiBdVo12qUt/c YXL2lDgTscgVqZcSSaRoFh3X4/TklNoP30PRl1KprxgGSZZJA/X5ywMqm7fwp8+J5j2yIGDaSyl3 VmXgX72zLntgea0mRalRsJSGaZFW2j98xODEwLRMbNui1t2m3OgSzoY0SqKyasrbienrNMx5MZjw 6MUxjWqZbqvFm3dus7W+JvPir+YXXw0sez1I8Yv//y1BF1c3/D2+mQpcC1xrwtI1lU61hGU78uIQ kzkxphfvcOHB66ys4ZozuYxBmH2FFitXREyw2C5j0Ds/o1KryMUNrY7BbDxiMZthlyoMLi+o1OqS UITp+OrEooFqsFjMJRGKmONw4aObOaZT4eTFc7K1NqFpSD2VZpdRNYMsHMkpX4wqleiG8PH5Hu50 jGk6GE6TmbvEcxcMo0uazTZbO3sy96p3+pRad4d5BCkqtlOS0Tgii729vsNiPqOkgWmXsL0K+tIn SiIy3WZ8cUTZ1GSDPwGCYIEdNSSRksaUymU59RSEKmxFQl4hkitGF8dkuUpnc59qc1Vu8BE9smar RZ4ZRPO+3KwjXvPEd3Fdi+fPPqJpGxybDmYeUy87NBpN+Tr85vTwN4MVvzGKSeL3HteasExNY7vb 4OatOwxGfQwtR9NyqXAvlUqUHYNcreMKgpmNQRHpBDbz6Uiq18uaQ6/XZ21zh1Z7BZWc/oWotgZk aSw/+RezKbqqUi6VZN8Js0ySpxj1DpZIVVB1OdY3TVsq00XDXpCZbhiUFANhsUvDQG6lwbRZLD2p BRO1l3gcGqqMeHEvTmTcsCCgOI6k3CENXWxxPPMWuMtEVoLCsxcnuSTDzto6R48+xHKEcr0q7Te+ CN2b9ClVqxhKTLW9JkWheZzIfpWIsRGpoXmaSHW7SDuNZVWoyQ8AcbwNwoQsU+S0U4hIZ5MBg4sT SrWXAZEyAAAgAElEQVSfoKQe0WIgyUozHbLQwxtGEC/lpNIqNUhCjzRJv/6H9sXx8EvTeMFEBb4X hCXe7OIoJGQIF6cvmQ0vZB8r16pkeUqSJcymE45ePqNSbbCxc4M8yzk5OpCaq907D7g8OaJ/eS7J gyzGcYTeXaXe6khyixYLKcQUw/osFqP8Ga21TWLFx3LEGq46SRwx7l/y4Kd/Tu/sWEoHhLzBi0Rl 5rO6vk2l3eFMxBQvl9RXt3BKDmGckISx7MWpsU+zXmGlvc+wf8n5y8esbN9kZf9tnnzwcxxhn3EM WYVFYYbtVPjk/Z9TFT2scEklCmQ1VTFSxuNLdKdE6/a+lH0MxwP5vCutDayyOPKGVFt1guWE2XAs a5w0WKCaBoau4weJNFTnsUcWCqFqLF+TxWRAp93FEiSYIo+nVnON6cVLLLXCYuaxutqhu7Yt9x8K XBnBvwphJk/ShCS6+mD5SnLPN10QUhwPv5e41oQlPITCP9wb9FBzofCOaYl883KHg0cfcXR0Qq21 QrXekZ66UKjKFYVWdw3LKnF88FjKHZaLKfPpUKrcV9a2pcj06OARn334C1Y3tmTTPidF0TSef/Jr 3hBHUFWRk73Lo8fYmkJ3fYdgMSIjYX17W6ZE+L4vSeng2WO2/U1QTZm/PhxeslwuZJXSaTYx0pjt G/dQReteUyRxBYshF4ePWNm9Q2N9F1PPMVSkjsyYzfnw4fts792WOqztnX38KEGdDalqSO/i84MD ekdPWN/Xaa9tSNmBqHnC+RglDbh4doRTKcvHIFT1qmNTr1nEWZXjk5mMT1YNU6abCu9hu90hWU7Q t/aoi8ged0bohyiKQaWzwfSTXzENUt4/OGX77pk80tarFXmsFZ8snxvJhTzEixKGoxGjy1Peeftd eRwV36dgoQLfacISzeVhkPHy2Wcs/Qg/M7k8eIHuDOis70j9lBCIvvngHQxDkZuPRcRMrbYtKzMt DVBFgJ3ZkQQmkjYffvAz3njwHt31LarNBkqey3Xty+Wc1e4a7/3ox9Q2tvA8n6k4OioWsWbIkEB1 fkZvtMDiNmsbO4TVBqPJVFaCj54/5fbtN9A0W6Y3iCOf6BdV6w029u/hDi+Jg6W0wojG/9bWNvPe EYvL5+zeuMesfyoTIMRl7Rg6P3r3PTrrWyy2twnH5zi6irW6h6IadPIYo7mJNzykvrIh/835848Y XwqSatBa32XoCjV7RVZeSRhJv6BhV7j73pvEfISiVai01wmTiMAL2H3jHcgTBicvuXz6SzkRVTQH fzig0lkntSu89dZdhpcnfPT4MceXfbY6Tf7Hv/wL2q2OlDeEgcejZ095fnTIRe+Cwdlz3MWQn/zk LymVKl+UT1+KUK8U9F+LotL6XuJaE5auwGpJ4z/85V/iBjEPnzzjs+fP6fd7ctT/9k//rdRGGQpo Yv+f+IRXdNnwHs/HNEWky3wmtxyL5Q5RHMp+ljAni4pA2HbW17dpbu/jT3rkaSbTPLv79+UUbzGb CLk95XqTaslivuhx/+0fSX2SJxeTOmzt3pCVmIhFFgkK6zs3iONE6pdanS6rnTVefvgzNja3mLhz xCavWrWK1uoiE9ODMUqWSs+jmidUG00cy+Ti8BnuQEEvtTibeDQ7XbxFxOD8ORYJUbCQ+VYL0btL I7kQVbMcLk8OYTig3lmj1FxFVTLCxZTID9Erq4xOj9E0U1aTou9XrpTpbO1TqdeIvRmlcolJYJKH Yr2YBtUqpmnwg3/z30uNW+gNUEXocxoz9Tz+7hf/IKtf0d9aJMJILipPjzAKSFSd//Sf/yOmU+fB W29Tq1S/6HFd5WqJ6cBv8ScWxPW9wrUmLPEeFseVnbUVuQW57Ngyw+n9T4SVZMJk0GcxHtFuibXq MXkc4lhlKt0OvSTAFFnnIn5F0WRDvl5rSY/f0cFTWt1V4iAm9ALKzSaV5hpKHDDrXcimstjQHHtL MmEHigJ6o0tajVUM3ZKm60qlThiE+MMelWYHv9+ju7ZOsvRk1E3JsFCTlGw5pSysLguRLlGVyaLC A1lqtmRcjCBcb3RxJb9w57jjIY4I+utucPjoIXtv/Yk8Jl6FCuby70T1JlIXVJEK4bvkSSz9leVK k5v3V/G8hUwtFctZ56ML0ijALtXla3j68qUMPsxZyOpPEPno4pA8nFBvrbC2uy8DAdXEJwhTIhIc zbxS7ysqimpj6IZMFBvPF4z653jLKblqkYpN1E6JerNNo1NCH1n0nn3If/mr/8jLw2c8ePNtbuzf oipdCQKvZ+EXuq0C15ywPocuJAS6ylqnhSO2vCQhzXabOPBRsgRT9pxslFSVanHRKE+jbWb9AeVK lSBKWIopnqaj67psVC9nU8T8fzGdE7g+pZJFpyWWRAiTdMBy3McRk0CnLJvSwleok8pmuCAwNVdJ /FB67cQFLHpVne66nJ5lWYJtO5i6JcnJtCtYgjDCJTPPQymVUVUDf9ojmLuEZY+qIwSpNqlo1IuG t27iLq5WzJfLgiR0OeXMYnHkjGi1NvEm/VeppwqJoqFqlkwTFVWhiGgWUTGiuV5rXcUry+NdvUu/ N0LVdHKhkhXHMrFsVRGvjSGXsppZQpwbqJaNqSi4w1MmkwmVtX2yBBm9rChjGbkTRRFhllOu2piO I03WUSwGDR6lWpdKe4vDo6dcXpzLJFjf+3PefvvH8oPnv+1pFbqG7zuuPWFdmT+uFNVuEDISG2d8 l1ZTmJznWGJpgmXLi85MxQWQEfqeJARxjNRNA8e25H24nocbR+zs3+T8+KW0vHiuS56JeqFBXK/K Y4yY6vmLGe1GA6NUYziZYpfKUngp5AxBsGQ6uCQXix10U66ab3W72NUqaq7gu6Li0MhyhZnrIzTs nc02w3NXEoSYToon5C+X5EmEXRGCUV2u78qd/FUPbMHa3i1JPH4wR7HF9hqLkq1jWm25Qux8coai 6SBkFIrQqSly5byoqObjc9xpj9WtG5J4xRYed3gO2JRrDWkIN3UT06pgifyrcpk8CpiO+kQxUizr tKqops7F2XNKwkDtlFi4IynDUIT0o9yg0lzFIJdhhuIYLCaqk0FPEtnWzg10p4rl1AmXY54//YiS qdJptbh5+62v2HZ+q6W6OBp+L3DtCevz3PUwyTi97MkVVvVqDV3LGQ8P0XQHq9qS43NDOO3SFH+e Mh325Uqs/mDE1s42650u4/GIs8ueNB53Vrq48yXubC7TGDqdFnnk0e50pC5L9HKUxEfPTNlzCrwl ZrMhk0xV30dNM9kHEnHHQhU+OR/JiWRldQPV1JiMxrizgbyAK/WK1E5lhkWt08FSsqtjZ2tFXqPC A2mWyiSRTxpekZhqmrz5oz9ldHZI/+HP8dKQ1c1dWlu3pEZrOelT727KRn0mL3wVp1STavnF4IRw OpARO958yuLymPnwgpmXMJjFbNx8g8wTk0IbTRWG8hksJ0SE5LlJafMNGUETzXqodhW13KW5skLs j7FNDbW1RpzEUszaWt1g5s4gXkBmEvsReSIksBqz8YB0OaIpfJqDGCPz6V+85OEHf8v+rXtXk8NX 2z2EWPZqjvilSv5r+1pFEfadxvUnLPlmznk5nPPxiyM+ffSZlCm8Wf8h2zcfcPDZI0lOttges5zh LSY47T0mk5m0qYzPjhlP5yRJiJqGrK1tcvDxz9nau0GrarO786ZcvDo5f8nk4oT27hvYJZPDkynD xYS17R1qa7vMvQaj3gVWaUrFsuhu7uJUKhD7xO6Yyo1tFqGH4o+o19rymGoNhzIE0GmscXjyQvoF q6aKRUySuERRxvDyVFZ7b7zzJ3S2brD0fGbjKY1WR1ZoapZSsURuVYfcqTGbjcl7J7ijHtVWm/Lq LqpdkWkN8siYJpK4MqNMtV6Xz/3ybIQ7caX+qlFzKNcrlDa38UYzFpNTKo0mRn2dxXiA6wf8aOem OPcxOX2Bomps7u2RBh7erI/pCG/jlCzPpMJ+dH4o87mOPvk1W3ffkSvDREUrAgOlxMGbYzRWCDOV LFMZzF2eHh6zXHpUq3U5xRRkJX4XPwf11eDwn1wlVpDWdxbXnrDEJ7AX5zx8+D4LL2Fl84YUgx6/ PKNR0rh9720OH3/CwilhmchYYhFHI9a1C3W3H2V0rRKzhScnaJ3VFbJoLm05lkgiiH3C0Jf+w5Wb P5QaJBG/fPf+D2Ugn4iPEZPHRsWhWnuDy9NDgnQhV2uVvRpW5mHkCUa5Sur3ZYJprZzL6sUqVyQB nR8/JwgjSo5DkKospxPU2KOxsk+ye4Nw7hF6IS+ffEYcelL3FXllssCTqXnt/StT9fjylNPj57Ra XXk5L6ZjrGoTv3dC6PtSzlCpNTi/PObme3/B5dEz3MUx3tIjSqHVrbN194dSFR+FKeXVDaq1hqwm sySm1mpLKYTwJkazPrZlUFvfxarWOXn8vpzqLWdDosiTpvDYm9Peu0+SeJS7u1ISoW2mcjGHP7jA EcRd38aqb7L1oIMthGbLPh0rIYp9kYnB0g+klm08Hsvp6Pbm5pdq+QLfO1x7whK5VUeDCePJjOli KT1wQhUeCp1RqSJNvYE/Y3AJpqnJRFE1NKVq3RsOabXbWKYpL2jLqeKUquy/+WMZ8tfa32Q5HbKY DokDD0U1JeH43hJHzai3O/IjP5gN0HLQCKiWS7hzsV05IIpz0kQsglDo1C0Uq4JabsmJmWjE1xst dMOWVqLTF09lX0hM9qitEs1H+INLNm+/JR+nIbZAlyoyLdWfz+Q12z9+LLdaiy03/RcHV4GChuh/ ZbS3b8q+lZhQisTQ0cUFi7lLc9dGrdSZjU5xR6ds7t2mvXGTi5OXcslEGMbUqg2pa9NDn+HpmPl8 Iis6U8mvDNFGhlMqocvE1AXLWZ/B4Sf4aU6tu4slhgqWTaXZZnzwK8qrt2htvYE3PCdC9AtVQr3E fDRhZ/8OupKSKDmTi1Pqtsre/ffQzTI//+QZp+MFT598hhYH/Ok7D9ja3HjlTfwtR8MC30lca8IS 79skzTkRfacwond+im6Lo04NI3FJ4kRsI8QwDbmzT1Uq6E4T3XKIFHH0UnEqVWaTkWxwi0pCZmZF sQyvGw8uWc5GMmXBbDSlbGARiKlj6WoJqZiYvTJeK1lG5E7RFJExVaLWbMuL33U9mpUu1fV9Lp8+ RU81uUtQPp5XeichwdjcvSX7Zdim9CUG4pLUNNI4ItdUmVWvpbkkYeH5E5uYp6cvaHZ/irfUpJFa 6MTqrRZxOMeqNJgNLkn8JaXWCk7tyqd4enwgzddZhhSKimGBVTbkc5HXfZphlOpsbrSI51NmwVIm SwiCn87H3HjwJ6TRgslkiB3GUpgq/IfVlR2qVgW7XEdJV+VSWrE5SPwMxM9lbecGYZriDs5k1SSW yqZiChslNGzRB6xLfVYcWHz2csA4+ICL/gA3VXnx7Ck/+cE9bu7vfbmn+5+z7KLAdwbXmrAEY4kK a7FYMF3MiOJIKrMTf4qaJThVsZFYVFaWVHg71Ra5ZkiDcu/8mLWtbaLQl6vehTShVLap1eqMh4HM lJoKaUOuyEmb0CNJWUEypb22zSzxpdFYLIzwvEAaiGuVEo5dRshO1Ty7Cg20HJn+IBapLtyFjHJJ gqVMRhAC0yQWgXx9tvf2iZcuaeCiagqaacljlWAWkWoaeQuZfEAek0Wu7A+RpXLyJoSfCI1ZpSGN 1Bq1q6np+FwSqSoy5csNVLGp+eJMRiIb1SblVi5ja5IkxbJNDFWTyRViD6Nt6rJSM2xHEidJRG4I SerVDkiRBqG8WvAh7D6GSGmod6RgV8TmiLmqSL/w/OBql+LZMZP+qaxmo0TEAkVScCtkIssww7Qy ctUm0x1mIcSDKdOJ0JOprNYc3tjfZXN97dUPviCp7yuuN2GJrCkF6q8qo0q1xHI+ZTqbUSnX5dKJ 8aAHuo1d78i+VegvmfkLsjigUa8wGo5kVpahCfKL8UT8i11iPOqzWPpyWakhdEeCSHJwhORAbHMW Gqr54EqTFYlthKpMVhACTXFRzidjAs+XsTNJFHB5fIAiKrRxX2q9Wq2OzIifTccyCNAdXVCyDTLZ u9HQDYf5uEctvtJsieomXYylxzB0xzTXdwmTlNngDHd4JjfniKpOpDRomajMAvzlnHKlRricSUJW slzqtQTEVFNs7xHHQDFwEDKNSNEJk5zAD7icD6WcQkDcl1if1myvMJ9P5Z7DWq1FqVImDX38+VTG LUdZxkwMOOwSliPM0HNG4zG1lS1p6PaXAbXOFjYavpfKcMGN9XWCpS+rVOFcEHE3tm3KyapZrpAu htza3Wa1232lbxCk/XXxpK+h4LPvLL4DEckKO5trnJ6ukAQz1KxEtdakVK7iOBbDYY9ysysNt/Fs TpYE0iR95823aHdW5NFoNBKkVSKOPD59+HP27v1Y+hTDKCKPRrRqdcq1pqxEuut7jIbnBL7ojXki IUvej11rMx/1peVEGIWF7ktEt2RJyGzUk9O5SqMrY4jrjYY8iorqxRJH0CSRuq1Wd0Ne6KJ5Hfoz QtfFHQ0pi72EcSzJNhYNcjfAj09IwglqEqBrDpVOh2qzQh4v6J0dUO1sSrGnVWsTBR7JYiq3BAly T/KIRf9CTlMjsQsxV1iIjTsLFz+N2XvzPQIvk89NVzI0S6e5sSMb7sPemZRIxJFPEimyItOcKt58 QnB5Io+5wtgtllTkikWK2MYjPlgMuitbdDsrMiljLISv4xHmzg6aHcs1YcIELTRi49MDqZ1r7d7h 5OKI+zf2qDear9l05K+v3gR/1LdggT8wrjVh8epzViQVnL38DCWD7sq6DNlzyhWp7ykJc7NuUqk1 parbNJq0GnUOH38kP/1F9Iqma7Q7beK4ymBwyWR0yd7t+9x78C5nTx6SBB5pnnEipAfNFqahEoRL oiyX6Q4bO7ckIYVLV3TVZASz2D7dWG3LY9XgUmTG+yyDE/mYTCVm2j9lOrSkz+/uu/9GCkl1Vceb jGQ8sqbkbO/elMewZ+//Hao3Zf3mPYxWg9FZyjLVKK3flo1tUQWKYD8RcezNRjLw7/Llp7KZLvpU TnMdp1Qh9RecPvlQhLuw9yd/zuj8VEbggEF3a5/aK3GpeE3FAteVB38iQ/umw3OsitjhmDIcXMqe lqKnuNGSWT6U6a2t7ib9wTk7t+8z6F1y+OxTmVd2Y2+XuTuUr3HqDkkWFUqNLs3VFTlRFc+33u7S Xt1kfHGIO+7Jai0cnlFZ2ZbTW7skqi7ry97VK23WF0mlBWl9b3DtCUssP9jodnnrR/+W588f4S5D 7MpVrMnw+T+wt26jVapojimXmV5Ox4Sb24SBj+0tWG01Wc5npPOhPKLdvHmXJ59+QLtSoX/0mbSo VMt1aYkRPSyxWn407LG5/wadjR0WC/cqb8u2qOop88WMzo37lOttLmXf5oINcXGeHUuDsqi6TKsm t984TkU2+5e95xjlJmmc0l5fleLR2aAvp26q25fVhd3t0tm+IeNn8iykFPps3X5PvABS0jDpn8gM ro3bP8BbLMhznUXvlI3bD+SwIFnOiIT9KMspVSqS3Nf37nD+8qn0HipG6WrRhV3hzv13pQZKSDtE /05ETz/8+//Czt5t1lY3qdVrKInIylqiqhqNZltWYvW1DUkqnVYT+/7bskp1xKr7Vkbv8hSj3cJq rWGWKqxvWzJzbNw7kWQ9HZxTqlRp79ySP1eZXAGU8iVKEkq3wRW+jFMuJoTfP1x7whKftjEak8mY 2egCu1STOUzCr4dewrDq5HpJbmgWPr56vSWPdopmEoZiPXyCkqZohiqlA2vrW/JCaJQrnJ0dSQvJ yBvID3HhBdRIqVVjfD/k5PBQBtEJS4xI+8xEEqiw0eQxJB6r6ytUHY3lqMfNN38IusXBZx9hKCmW psvFqeLPrf0HDC9OsayK1DtJDyQJhppTWt+hW66giETPKOLi6IXMlW9t7uG5Q8rNDQYvP5HHSOH9 uxh8Ir2Mu2++y+j8RG53TiOxUMKXx0rRDK+v3eDs0UfU1nbQjTJxMGLw8oBJmLO+e5MnH/6S7toa 54fPmIx6krje+vFfkCzGDE+fUlK25SBBDCLEIllBIlGa0l7bYnD6ksWoT211i872LfzJUMZEp3FI e2OPPPKJwoU8siepL/9+Z2cXd2lydH5JfnxMxdJkZpe9EmF0djgeztkTYtlm8ytHwt/Miv9v3xt/ sHdhgT8Qrj1hiTeto+XUK1U5rRuOprJ3IvLchWVEVRW5EUZkvAsfoTBDK6lOqVLDH52j6iaO7ciL SlQauFOqaoQ7GFNzDOzGKlGUyB6NSDHtX5zJhamD8VRmoZdsS6YvqGKalyXScOyB9PJVa1W5w0/4 5MxsnakrYpc1KU0QxmDRB1PE3kRhkfED6UsU3kBhNyo3WnLSKCZ8iS88ihZxGsglE4pdlvYbfzHB tEpyaJBjyUBDoY0yymVKtTpmqXoV05Iq6CKQTyxJXVmTSazzSZ/2zm2pus+CBYv+mRSuiiUYIpJG yB20V9M+4Qt0xxesttskQjgb+vJ1F5IOMaCYC0mFaslAvmprVU5hw2BJPBfWmwm1vR+wkqXYpkEY iBifhHwxJfZd1rf35TIRkcDaXtnAnY3x3LEkXy1KKHc6RMIInuYyi15oS//RVWEFvvO49oQlOi4V A+7fusllr8fzg6f4yxlhUJP6qWnvUIbwlasr5ElCHi5xykKsGZOI1fNiC4zoj2SRNAYLIomDQFYj un5FSCKeRYTPKYYpLyxxxBIxNNV6C8sS674WcjO02HMoolHEhDESX9NyubZLkIhQf6tahbWtrSvd lqrgiya656Jnqkwy8IKAPI2kqFQspxDSh8W4RywIz6yii7SDSh0vinCFmLNSkj0fDEvKFkSTXDM0 TJH7HgWyke3ORjJ8UDzecrlOfXVTbg8ya21KNdGP02Tcy/5b77AIcwzLktleIj4nCTK5VdrIQuLR IWa3geU4DC4uMEyb1oqDZugsgxDX86XBWSwEEabs0BM6uIBSvUWaxZSrdbzFVObZC4P4cj6WYlyR VupJN3Uo9WfC6jOeLXBKZdZFfDIpJyeHPK6WaDebbHZakrG+EUkV/a3vHK4/YSkKpgI3N9fxfvpn suI4E5YTVxCTgju6xLBExbEqEwdUR5em3/PTS2kKFhdPnqfyAs91C6PUZHTZk5YU0ZBWpzMpaRB6 qZJdoru1K5NJRURNpVKS1Ueq5HLvn8iZWt/YIvLnMg89DjVSxSLRwY8jau22jEEWolEx8VsuXKaj Hk3dodFZlfsHpVBULCLNPfQsZnb2ArsufIrnNFfX5ZFXXfrEkYtmiVG/0C+ZGE5ZJj14gSfv1ynl +NOBJF4R1SzOUcLILFaUiWqysbpNlgjV/pw0TeX6erucEkahzK0SXz8/P0dXcvY2uthGC28+lOQt qhrNtMmynHA2lUMJkQ1WXt8gCVxq7VWZ6b6cT+QUUZC1mBKGIj2jLKajFrowZWs6y8kl9sq+nKQa RnBVPKm6vK1tmXi+y+GzzzBIubmzzWan+c8Tjf5mikP+Td9Yv8u7scDvG98Bwrp6Ewo91s2NFRaT XTmly8RFKWQLwRv0ehdSCS5SPG2x8stbcH55gWXqZFEoc7BikfckjkSey3Q6xKo2pM1l4YXSU7i+ uYkm+mWqyDBvU281yfw5094x8+mEGFOKOc+ef4bpiPXyOWFSJjMbBAsf5jNaG6pMR9BUMYtTiJNE moTzTCSQWnKbsr9IiaKQLEllZZJ5C1beepfPhu9j+SKJok6zuyGni0JIunbjrmx+C5mBH/jyOOaN xhiKJhXoVqWJUW5Jxb5obPu+K0Wejqkx7x3LLC53PmZ6eUS13sZurTDo98nsBp6I4cmEGLfFyuYb 9J9/RLW9ysZuHbNcJw5CgvmUdr0hG++iP5WqKqG3lIMPEUvjz0e01vdkxWXapnxOWm5Qbbakvmtw +IzqfgVvfC77g2vrGzTrDc6PDuTEUpBekicyfUNXs6sB4R/ijVVUZ99KXHvCkkr0V9EjdUPhv3tw j3s397mYzpkGGe7lU7Zu3SeLQ0wRLEpGsJhTqndor+3KlVwiCtk0VVpC1a2brO3dlYJK2y7TO3rK 0o0obexg1xq0zIzKyhaRO+Py7DkX58dkZo32+i69i3Om44ByCVY3xTKLlhRubu/f5PlHf0cULiVB uoup1GDt3LmHXfmp9D9O+2dYVpl5vyfjY5prmzJdQd+6QWtth/pGX2q2xKp4bzbDNHVU23hlO8qY DI7p93qkaonW+g1On33I/js/lfE1ZpYyjwMm0zGtUp2l62FlLopeol5qyOOfqaky/aGzdZtZopKo Njf+f/be7Mmy88ruW2ee7zznPNQMkABIcGhSzZZatmUpHCFH+MV+89/ld4ciHLId4bDsiFZLTUpU qzmAJIAq1JBZlZXjnYdz75knx963CiiAYJvsQShU58dgoCorp5t5zj7ft/dav9XoQZREIA9Zpa6b OhTDhki5h5GHiIpJ5EGuttG/eI5qqcr+xN07Nd79uCOaXFZ5SKDQDz/1IWYJRCmFQJ9HyBBkKebT S+RZADEPkMwi2FYV3/3Tf8Ei2uOjB4iSBDtbW9jb2lwfB/lBJX4+iPXv5dp68d/r3dZrs77+BWst yXnRzaKnsIC6pUNTFDwcLbFMTfz8z/8MluPA0QSYmozu3i1oYY5f/dVPsXfrLbS72xheneHk6IjT XvzpGEH/CPXNQ7bGUD4fHeP6x6fQS00Ej+6j2qjDqDRwp7eHJJcwnLjo7d5gLApFaYkkFFVl5lf9 7Of/Hjff/hYfzyzH5gkg+ezEIsbk7BHKvRuIMxFmyUa51kSwmCD2lsyyIoX+xeOPOdb++JPf8O6r 1NzA+bPHeDi5wB/pFgxdh7sKcHk1RCbqvKNp7N6Ct5rxEZSsMLXNG9j4xg+xWrl49Ku/xOHuJhio ZAAAACAASURBVJazCcI57Wyo729BUhQeUhAs8GpwiSTPuBhQ819HhPH5KXY3zrF7cBu6U0cSJ+xf tCwHhzfu8sTQ6G4gmF8iD3XYtQ7NOvntJ48f8bTR1FQu2uvMQ5OnpNFsgMlohEK1Ueu2IEhlhM+P oSJDd2MT9VoV7WaLd7rr6rFO4PmDitUXGvWfu4R+n2ix66L1Wqyvf8Gii+mV649kkGGaY+pHGM6X UKwyGs067yqmUQ6hbkPSHIj5JUqOiTjw2T9Ya7Yw7Ec4e/6I2eqyXGPxZ2erxqk5gTtl9ThJIsIo h7f0oao2ZsMB5gsXsWTj8uPfoNJo8PvC7vFxbzodYRkE7Gukcf/K92A6FWg0wSOOaavEk0riPJEi nfps1KymnREhaM4f38fWrbfZ0tNod3nyR72jrLeJCu30CEs4o5BYlQtVQt685RzpcsgBEoIkwii3 uIc2e/YITrWFaq2B8dUlqp1tLowUGFHdvMU7QiHLUSIAYv+Kj8Zk/6HdptGoIy7OYdc3MJvM0TRq zJVPnArsxgZmRFiNQxh2kwWsiuGg0t6FOzqHbGrIOj3WsRU0U5U1FJqFNE9Qam4iKjSUumV4QQKI Gpxml8M4Lp8e8YQ2ms8R+96noRRrZ07+wqLz+xWtLxapv9F1dl20vvL19S9YX7im+jMXHz1+gpNn jxCLJi5Oz9i7R+wmwq1QSANJHEg71W03oVDzK6Zj4RDeao5mq4PID5CQRCGM+GOJOOrmCS7PnqK5 ecAZhDTN84II7mIJzwsg2yYbkWk3Qhom8gtTQ53i7bf272J8fgTbMpGQiDPLILDMgvrkxH734A6e QWp2WOVNmRi6arOZWzFMnq75izFMolDINtKcknpq6DY38PhX/xGt7ibMqgNoPnx3Cn9Eivou3PEF 42cyCsMIQmQEELRNaEIGvdlFrbXJfC26D61ygz2Pk9Mn0Eo11B2LU3qCeK3dosLerNUY7VJubrIF hwszm7MzOLUm/PmQLTXl1hbf3QwLdGrsZXTa1NPS2Ai9XPqYDifwl1MW5nqBiyAMYZEnNFthcXWM KFPw6P7H2NjZR5yK+M8ffMRJRT/8zpr3TkWK//d7Fqvffr/r897Xcb0ZBesVLyztCC5HY3x8/yP2 5tHNpFllDj5wbAeNZoNvoNXsir19hEymfgxB9igqvtvbxcXpEYs4SXpA0yoScLKUQSQoggfdsuBR ok6Wo5A02BWDC0utfhdCmnC/JlqMidSCcmuT4+H9ySUbk1cFIXFypP6K+2rUIyIRJd1UwWrB0zdF o+kjEC0XsMplhKu1WVsWSiwKDUIqIjLEPOG06uVqBdumqHlpfeQSHBSqieF4BnG+QqlJvsACQrJC pBYQginMeoMzEJElfBSkPweLMYYXT7FVqsBRFUiGhlSVkYoSHxlp2ECECPqZLscXCOZjyJoJ1Wmy 7mo1W6dnV7vbEAUJy9ElT1FJfOtGMQfJLuYLjIYDrJaUwUhTyQTVZhej/hXvhCuOjcj3EeUys8ro YWGZGsazIU7PzoD333/pKPy9djyf31l92S5rbfe51nJ9PdabUbA+vX4FWIbB5mOz3OTJmyWJyEQV OUXRkwRCkRCvKDcvZvTLchWgSEJWxxvlJjfJaeJFY34KsQBFqkcB39jNZhMpNbDHp4BaRpYTJ91C qVTiYAhG+qYJm6IzVYPGwRASpHTFxy+iJ8gqiVRlVtmTDou+D9O0YFQpVsxjyQW9DwMDaVeQRCxd yLOE7SkciJFnEEUR3oICYzcxHvQ5wqxMdFDy/CUS3CiFoOpYzOeQjBUs0n6ELiJi2ysSC1Sph4U0 Yh8ifV46vvlEpVA17gUSNI9eDwlES5bBU0R6/cvJCKE7ZtM2uQm8+QiT86fM1ApkAaUkRkrH8stT SGIGrdzBynUxnS/Rv7zCZDjg1J9GZwMXzx+j2dvhSLTFwkOtlUOQRYiZj939PURhyAz8WFrnUKqq +lnu14u+5ZcXm1cLUfFKxiG9PzmUaPyyfguhl68FqF+P9WYUrE8dGgWLJWuNNnr7N5CRlujoGEa5 yugWEnNenj6Frtvo7n2TR/PL8BzzxQwmqcOZrpCg1WzBDz343oqf+BSjRUct6g1pThPzyQjbt3cR kBWHDdUiglTAklJnqHBVm9D1FqJwidnlUxaWWht32R5EOBXSF9ExK1cNrKYLjrcig7JmlznognZe lJyTahp8l4zQ8jpBZzhAracx5pgKjqDpbImxDRVCHvPon6aG09EpCr2GzZ1tuJU6+wOlPEJBN73V hKErEGUNMXHTSw0WdXrLGb9eKpZUvERZZo+fH8wRzYbwFjPkWwdobB7wz4gKACFwVF3H9PIEsb+C We9wCjThcZajC7izGZytPTidG1ALC2J4BsVYQrd8NjN3eh1cnp2wkFbRVBbhkjZsMRzDH18g3rzJ x3IhXjF5gyinr1gJP5NWfeHIt95VffY21rW9KGDU9krIuRAnyCDw5NVWRfakrgvcq5/5er1u680o WC8W8dpTSgcsCsT+HD77C4dod8qwWlsY9Cc4f/6MTcB09DMcC5f9PoqQYsEqUFQNo+EVqo4If0Se tjpH3c+WHuIsxyp38OFf/Bgly4bdWmBj94CLoDefoLezhyLUWfEdUl+oKOAOL9nKk5t11KwVfC/E aDJHHhPKOWeDdOPmN9mYXKUiGUSYEW7ZsNjQ7I0vYXX2EI8v+Xujxn0SeAhmV6i0ejCaW2vVOanH iwiICJFcR3XzJn7zwX/knUul0UF7cw/JaobLpw+Y30WoHEI3k18PuY7IXzDXqr55AGk2wuXjX8G0 bFilEjsCFu4EruditVohWK13YGweN7jsMjs+CmO0b7QxvnyOGe1d4oBhhWqJqAzH+Nl/+AluvvUO 3vn+j+BOx7ybK1kK7nzzXZiOjc2dXbRaLVTrNSyGF4imQ37N7qAPWxXwT/74v8Kf/smPXvSuXhYf kjiIv+Pot85TojdneY4kSxHnAsIM6I9GuLo852HHVqeN3VaZJ638ES9kMtdF6/Vcb0zMFy2KhdJI YBj7CEdDGHYNVduhewdBtGJm++HhIdyrI1iaiMbGNhrtDSz7Rygyn/tDnd4WotUAT0/7qHdNOLqF +cJnYenBvbfR7nTRqNchi6QkH3Mvim6gyeVzVLu3cPHkA2gEnzN0QC+juu1wgzxMUizdMVbzCTY3 NlEulTh5JhqO8eDRU3z7j2ycPz/iHYtCeYizKSrtTRhknmv1kHz4lzwxC4kpP+tjuZijlYmwFQHL REJhtuGnMSaXFwzQe+97f8rewuHzR/BnJtrbN9HavsGi2qMP/h1ExUKt3kK4GLCWSjUrkDSbxauL +QDuYIwgSiAZFTQ3b2E8mzAZ1ajWEc8HSNwpxIJ2dDrMchU7d/cRBx4qlQqSKIRUKjNL3g1WePzx r5FmMVumdHUHzZs34HVq8Bcj7JVJ1DqG7SRQkhHyUGI5BCGvwyyBLKbIRINZ+iufppAC9xvHowGj b2iSSsSIL2hc1tdGXmCeFHh0coqjx/dZJuIuVzh58EtkMFDZ2EN4J0TN3OMdH8t5P/0Uf88ar+v1 D7NgvYxRpeuKLltdAlqNJvZuv4Ojh/fR3L2F4fAKMgk+FQV5nqAQC+SyjMAds38voPDPMMFkHhBS HVa5BFV3MOoPIXQ2UW1v8U3tnn7C/KnRyX1ujNMonxDNdrnG06+Fd3/Nj5oMEbjBWo8lKLg8fYK0 kLF74x4USeXjJZl8S6bK1h3qg6VpzGp9CmOlKSbthOajc+6p7e7fREJJNkmOgBrYoQQZOowwh61b UKCzsp7wz6pDinMf0fgKWqkKTcyRhyuMTh8gCpYMKjTtMsqtHfijE+4JkTVnMriAVGpDTFbQ7BI0 y4QqGhC1ElRF42Mu1G/CnfYRzskHSH3AGfcJmxt7vGOMiBEW0JE25OnnakU7PgXf+sGfYjQa8BSV MwYTD5YmMSef0NL+YIlCdyCVatznGg4esxH74vw5HMNAa6OHyXyBh8fHcAsNz5+f4Pz0GSLfxbfu 3ca9W3dQqVRf5Ba+iH6jHW4q4HwwxLPjhzh5+oQtWnQMJK9oIQlYXh7hmeij6hgov0xJemn7+aov 7Ov1ZhasVyeE9EfakHSrJbx37y4fWz45PkL/8gSNziYs24DvLbB0PTgtDVkSQChS5qcLicAGZuqh OPUWmo0OZM1mTyHhk0MvZdIAUTHpKLcg7RWVDYoPMyyePA7753jrne/An11h7rpMc6DjGoH9bMeB OxthOhoyf6tZK0PvtJGkBRr1MvzFAELqrdN3RAsKNZeLCPPxBYRb77AanozHql0CJBWFaiGIM1Tq HTQaJpNDiQFP/a9F/xzji+foGAYLV0dXHkhnQY1s0paV6lswTRsiKdPdKfsHU0HG4OoCchag4Zgo 11oo17eRZAKHa+iGhqm7wvnZMz4+GorG5IlwuYBvmKhTZuJ8wvoyWSohDFY8mbVqHZ60JkkE150i WIxgqRJUSeAjH8lGJKOK0dyDEk4ReDMsp33Ijg2ktKNqM8UhlWQcXwwwCAScnz7BsyefoGwJ2G47 CHe2iY/x4li4foCFuYDhYslm+MuL5+tjIRnRZYmHImbFAYoM7nSK0/MrVGtN3Oq1IdNT4+WlxX+8 niK+TuvrX7Be2bbT5UrXm6Mr2O80kH7jbTx/+htGIhO/PA5DBvHlWQG7ROnQAgxJwbQQUERzLkyG VYVV7WC5eMiTQ6kI4E7nzECnprg7uUKtswUUMZMwSYfkTocc1EC7C39GJl5K0UmY8KnaFUiyxmrv eOVh1O/DMCxIksaN9NhfwKr31qnO1FeSdE6cIYJE0erh/Mkj1o9V2xssP1gzrUQOQiWKZ0wxYrnM pmNqhFPoRBAskUoaEtp1qTZLDTg6XjWhUxAHhXdEK8Y3EwZ6FSZc/MjbOJuM0a7f5p5UOh9z5iJ/ 7kSCTSJROt76S6ZQkE5MT1OORCNRKDH0yTJD2i4qDrRLzCk5u9nDeHjF8pB6bwt5HGM0HKG9tYfF bA7dqsKGidWsvw60QA4p9uGoElunloshisxhKoQ4mcEdn3MP7LB3C9UyCW8VBEmGKMleeDgzXFyc Yej6ODt/zh5KKmSSWeNAEi9KUaPAjJWL8WwJ+fQM89EQ4fvv4/b+NiyDmvvXe6zXcb0RBYsWP11f XGRUwAxVwe3tHr711l0s/BxBxvAVWE4VqqIy5oQ0TzGl1gQhvNBnVIomW2vT82LIMepGqQnXXfJT uSkrGJ484qCEIpxBEHS24pAEgcSStBsLFkNu/mdRyJwrEjvWiLh5dgTNAGolB9VGB+UyCTrXFNAi iFEyNUSZyHKHQgpQbzTR6t2AO5zyTqBcr/MuIfU8yBT1ZThQihgoUkzHdKOP16wvwhznGZxGk6ea sllFlUAOhLdRVDjNHiNpKFmIDMdZJrJOinA1smEz36q2dQuL0SXmV8RoFzm4IkaBG7ffYWnBZHSF q+fPEMYR6poG0yljObriAQXRRKki0iSRwilC10Vr7w7CIECr3UC31WHXQRwlMCttzCdEgIhQr1eh pAsks4x/jxTkQbvIZxd9lEoWsmYHkqxDEnImWihI8datt7C5fQMBNdLPzrGgz5umXJAe/OKnUJ0a F9ssjvk1mlqJ8dlmfQOiYiJKXSy9BOn5FcLxJeZUPP+7f85UCEPTPod4uJY9vB7r61+wXkGNfDop ItWlAD5W/aMf/DM8HwOXkwkkmRKXKYtvF9PxBLISYHByHwt3Skonpo6mBSXl1GAYJUThAqooQjJM SBQfFkdYxrSLo4idHH60gqSYsKkImjYq9Sazq7xBH1kqQtZKrKzXNQNSTnjiEKFGSJscYhGs9U52 G4Hn81M9TETM5jRjU7gvVG11sB9HPLFbjp6jIDQMCTUFFZoiIl+MUG5T2vQzVvJHyyUWSw/Vzh4q coSrqwEUm4JiZShyAZH0V9EKBmmyshAK6Z3imAmpJM3IkHKwKXkkc2FdPBNvAYoLklUdkTuBTDFj ScSBtKooM0+MosKGzz7h6SghmRsbWxzP5a2WkJOQ/43gfbahwRufs4C0t7nFJIhWWcdyNecGu2Ma iMplXF5cIFeqnApdXIwgGlXkksHWJcLd6IbDX/f2vfchWxU8ePQRjp8+YbIGF0rPx+Wzp2htHaJS q0EpdXiIQa6EOJfQ2dnH5OKcJ4JWhXZaKwhmFUeffIIPDg9Qr1b4gUe4ns8FtpIm4nrj9ZWur3/B +rJVfDY1rNoG9nrUc7pCv/+M9UvV1iFkrYzJeIThyOWji2kSpbSN1u4+/OUEtY19VCs2H2XSXFgf heZXuH3nLcbIyNoBarrDeiY6Eo7Pn6BWqePDhx/jG+/+EW5u7mAy7OPZo494AnX24AO0N3fQ2trl 3k5I6GBinlc2IUUxUxY01US1ZsCslJGRtzAOIOk6HxsJ9VItt6DLJvzzE8z7AyANYJTbMIUImm1g HOiYzq6QRk/Rfest3HpnH598/DNIggFBEVH4Mzj1DvzJjGmndCOrSoyyDTQNi79eML3C6f3/zNM3 si3p9Q6sGhmPZcwujlB4Y0wvLpFEMWobB5DNNdFCFhKWUKxmY+aL0fHWNE2U7Q48b457BzcQj59C 1ZrMng/m5zDMEtzLh6gffBdSHjMni9hZlxenGE5maJpNbPQ6oNhYGmqMLi+wGF5iZ3cH3Y1DnE5W mD06wkcf/QTTBRE4dnmoMiML1e5tDC6uoNgN/hl5ZycokhhxJuHq5IgDdSkqzbJthigS/bRc/yYu hiMsvRW6dTo6r4c5nz4Mr4vVV76+/gXrSyLq1j2tz6aHFqm7JRnl6sZanFlIiNwhavUqnj+hUM+Q 03Zso4rLBx8joszChgeh2EIchAzwI6G0aVVQ722zNeX44QeQrRLHWXnzKZqdHp5fXkCUSD3vQ7i8 hCLmqFVKWMxnuPPu+5h7KeNr8ijCws84AqtWkTEYnqEly1gFAe9k4uUAI/8CxcYhN7ynV2do7NzG YjLm6Vu92URi6ZhcnODDX/+KY8NIhV+u9XBHL6HIUjw/fshHSL1cZ2FoshwzW556T3S0Oh+OEKV9 ZmtR32s2uECjuwG11GbZRHf3Dqv7mVYhKbg6/oQjzGKihuYydvcOUKl3OYosJKuT72HTNNg9sGZW iRBVHZpuYjyZwTqsoNH6Hpbjc27CO40uJL2M5cPfoKMbCC6fwSerkqDh9jfeR3uLkrDnmJH3sVTD fL5g/yK5Ec4vLvhz/G+zCUxThxdTTmQdhqTCrlQQrCIejDSzHKPzY7b/yLKFZm8Pt9//Y/yn/+t/ hemYUOS12l13HBTJCtOzJ+hsbbKtiFhjPIF+0Wm4lje8HuvrX7B+DxM+HUW6G9uIz2gUPke1vcuB FXIcwDFlNM0a2iULuqqh2tqFXakhj11IFllu6AhSBtIEk7NjXF6cYevgDiOHDRJGShryKEYUZ7i6 vER39wACRdLkAYP5qFeUBzMMkhzzBUHsDOQJJS3bnHzsVBykXgWOJcMp7WA1H2M5niAiJbtso7Ox DddPuQiG8z5bi/JowUertFCwf7APSRTZXjSbDlkuYZcsVDZ3kWYCs+XpyOeTH1IzIWsGY112Gjtw FxM+NvORFZtQNQVGuYHlpcZFj/j0ceSzwDLLY+h1wiu7qDTr6GwfQNMMLAYB97jKTgneMkC7ucvF QtE93knR19tUdIxOPmJmGAli7VqLsyJXywU6+/e47yeZZSxnU0zG/TVFln4XTSKYLpEVRGldwjRV tHtbmI+vcH70GKLZxHgxQ63ZQLvX5kxHmvIiizC5PGb1v23pKIoUk8E5hNjDuNNDa4d6g+c4ffgR 9HINe4f7aHa6EJo1fP+bb6FZq3xO2PC3Jj1cr7+z9fUvWL9zfXaRUeCEZlJMvIpkNcdyMYGsG1gs 5iwcLWkEwtMQ5iJSQYGmKbi6uIQhWLwjSlcEq5swmTTwluhfnTKyl5reVqnOnsFoNcPuzjZU20ZG ScqrmPsp1Peodg54GqXKS97N2HYJal2DQFqg6SnkbIbZ1ZADHExDQ0FFgyQQ/TNkoQe9vE49lnQb vjdH4F8y8512d9pytiZKVFts8laMcyTUp6o02JpEKvZ40efACqg2F63J5RFMEqOGEwhBDrHWgaRZ 8EhOoMooogUEOopGPn+8XmrAoEY1YXeMMqqdLe5/kTaNgi2oMU81mvpWlEJNPytuI8oqDwgI36yG FuaTPiSaVkoSgvkAqlXiB4cNHxERLFQLzY0tNo1TGKtQnHKwhdbY4t8JgQZpTxQHKxzc+yZnTdJx m5D8IlKEyynmg0vs33sfx/d/yaBGy6TemA11c5cfILPxmHMZy40mJ3uTeHUxMWF1Wjjc2cTh7jZs w/it09/1Duv1WG9UwXppdP1ssYMMy8UIy9kFHxIJCUxMdsrA83wftqHAIc2PpCJNCImSwZuesrHY TxWYlRZyEnKmBdQSNeMNeIspVGr8UmqMRIEUMQwlQc1yWNhI3sRcVWFbJZ5EpkXB4aOSVGePHskh iLbpTi/5hnXKDbgjF6K2gmmrPAE08gJp4HNxJdyzpJl8U/tRDE2W0ezsQyWEcRazaJN4DFRsNBah JjwVCxdTxDSx9FfMcyefIIllvf5TOCSTyEiSsIAsKVDMhL2QulPChFTksg1VNxnFTGnMCQRErgu7 2kGp0YWQBgiXM0RkDJcoDceDWXJeJFT7KNKMj4Rk3qFdEyVu0ySSpqecYVhpoLl7F9FqAcMAH6vN msITR5KQkDHcR4pC1hGnGWRZ4UxF6r1RcOzh3bd5wmqXHPizC0Y8U6+Remu0a6R+2oS0aZD4d+U0 aLeccFF2KiRdaWFHszCfjhD7LhbjHEmnyR/LyvlPe1bXjavXab1RBWu9Pl+06G90LAunp0g80jnZ jGFJQxe6VCBYDqEJ1LxuwLEqHP45O/4QgqKxTkeQDQbYWXWbKaGWnCJzl8hygfEzeeRyTBb1eeIg glpuwV+eQzALVOprRtZseEnbD7aw0G6IUqT9xRDL8RkUUng7PeRz4rFnUCgzUSSRqIlKtYHVfISl HzATnbL9JAgMx6OdRqPbRbJcIC2oQR/Cc5e8IyL1uDe6xPjqlL8f22mxwJUa4d74AjqFm1pVoNzB wA/482uZgNXSRaMQ4QcxDG/JJmtKGloQmTTx4U4H2LjxLu9GIZOTeokMAWcfijGFcSjQKdpMkpjr TrvR2XjA5miSS+SChpzIfLIIyaohV0w0N/bZWyn4MZarEEvvDIk3Qy7KUNQe2nt3sVgt1+SMNIOm 6Gi2D3hiSD02KoKBu4C/WvDu2LErmPWPoesywwtF1eL4NEURoWsy0mXO+jWiX9RaHU5BGpw+QpQC 46XHDzFLN/gauY4Te/3WG9l0f2l+XT8gBezv3+K05uWjh2xOFhQDk8ETQCMh6IRBdLUoRrmlQFUM alchkSqQdFJjGyz0ZM+aJGJ+dczHk8X0OVxXWttvFBOhWEEg5qjTsQkF4nCFyfAcmm4xYXSxnKMs C8QHBVKBj4uECSadFz355SLmBjYhYmRpLSkQClKTy9AcA9P+KSxVQ6XaYuHr5dNPUN/YRjLvo9TZ Zf772hAsI/EnCEKPTcQ0yVRJbhGuWFvFuOPmLmJvwce6DCJ8L4CWgIkTSQoYqrqWL6QRkhwQ6RjY qCD2pvw5ao0WJ++Iegm2bCJYTtHobjEVVdEUlNr7yCBhdHqExeAMleYGK+HpIUA9JkWW2B4kkMOg VMG0/xyyVcecBLqkRofEViVRvMDmWz9AIgpYLsYQIaBWb/DO9jkp3R0HIRVxRWL5BlJKHIoRRC48 d475bIpGQ4WhSZBlAYk35v7V6bNjlIlIIYisyKdiXtu4hXanhzAM+GvLkv7KxXW9y3pd1te/YH3J Kj5F567/vtndQu2//pe4desEH/z6l/joo19AyAo0G23EocAQPjeU4fWHsJwalPImhNkCy/kQzWYL hi7AWw1RJDlO7/8Sd977Pmf8TVYpXN+AYTrQZAU3bh1gOnyO7d1dRhxHcco3tmmZnJQTeyuMrx6j u/8WZLOG/skpls9+gdv33oVZaq1N1MMh39DUuB5Mlnjy8S/xnR/9t8jbKnLCJus2Y1ZWqoaHj55w buHbksFDgVyQmDBK4/ssE1BzSijrCtLJCYdXGAYViSomV09hugoyWeMm/yrO0ertY+v2t7lxTfow +tmRABZkiHYIUtiEF3gwVI1lFiEx55ndpXNzvnnv25hcPMJqdspHUpnCLuYj9vt1D28g8FeYTY9o 6AjTKsG0FsgKAZfPjlCmB4OioNNus3eRzNPjwRn8LEYYRBAEOio2YZg2zHIFs9ElqvUGxNxHo9rG bDriYFi7XIFda+LhowdoVmo4OLzLPk1RKiCK1BygB84RwgX9nkssX1EEYGtzD+1eB//0vTuQWCir XBep13S9kQXrswbpZ1svQzNw4+Amtja38f63vot/++M/xygS0R98DJ1tJQZWnssEgrfvvY3QtLB9 6xtYUUDC2RFD9kS9iv1v/ABX4xn6lxNuNG/utjiaiiZZ1ICmBGfyJ9INTUcvau6m/oKJn/3pFEUu YTyZIoxohJ9h58bb8MIMF0cfIs8i1Hq7WAUpZvMJDm+/i0lzG4tlgGqzw0fLp4/vo6Bwhu193Hrr HZw+/gSuF2M6HkJKI+zt7qPR3cfjD/49dm9/C+kL1ThFyxMC+uLRz9BqdTDxUlQbB9is7PPnJZnH LBghJggh2VdWRGWdICZoYELkhByN3h4q9Q2kqwmcaoWLbrBc8vifFOWb976PJMuQZil7B0lVTxPB 87PHjIqmKSYdiYuwBDFvodTaZvP1YhVAESKEo3UaEBWut977IwhGmYMrBufHbLeifiPFkxk7h3j6 qz+HYmgQlh5ss4I46WAwnADiHM3OHUipD1knv2CCxA9QaCZTLIrZOdrbd/i4L9IxVabBZ3tzaAAA IABJREFUxwX2D2/xz4nxNcTGepXWcD0kfG3WG1mw1utF0XoBd6O+kCKK3F8xrTJmoYD50sfG7k1Y toMsz2AGPlsyqNFdrbcQuH2E3pSZ6ykhfqUA7uAcYaFw74nSYigpmQzVFMQ6uDqDnHq4urqCYTmo qwZGF8/gz/ro7L+FgJXaIgYUitrsobd7F+fPnqBeqWBje5/V8qVaA8PBORaTEfI8hSqkMBTCGwds GCbMsrtc4PLyDCXbwd7BDaimBb1UZYtQIos4f/oR65Gof7XsP0M49yE0OsizHLP5AkESobf/HkQC CI5P17KCIkZBCdS6ydwrCocwZIOtR9S7Ev0lNvfvIR8/Z7O4bJR4RygIGZxqGWatiZMHH8AoVSBQ Py/0OWBVjF0oiYvO4XvMwycFPVmHaEdVazThL7vQFZlj09ygQJACV7MAo8mv0N3Zgm7cZRQ09ZwE 8komEcLQx8bBO7g4+QQXgyEqTZV7iCR0lbUKTp8e4dat25wzqQgaQsLlLE5Qqbch1bZx9PgYjmVA l2l3bTCe58MPf42trW2KyEDDUuHoGve6+ED4gmZ7vb769WYUrC/tY738h1f/jdjsAo/Ce50WYsll SF3mDdk1bTtNhGGE6dSHZKYslHwZukA389XzJ4igcnpxr7fNvSbqVdHOgczVs+EFFxBCBxNimcf2 4yH8VFjvuAyHd1VhsiAdPhdT112w2ZeyB6mYerMJDNWA2d1COB0yU2oxfI5EI8pCF+bOAZarJTfQ pSKF6VS5t+RoBaRSFUIaYzVaYholEC+O16+6EOGl4LQgtdTF1dkRRPkZnGaEyfgSEfXXSjbvSIJc RpwJnDzkOBYg65zE3NY06CRJqHdYDqAZJS5KFJBhku5KM5EE9Bp1nrQZdhmxrGLRnyMsNJxeXqK3 d5eBh7TrKVWaSLIcne09RPMBNKWBQs9RLFfIKCSDdGr1LhupaXdb6Dr3AmmnuBxeYj44g6I5cOrS uiemiSjbGzCrDUj7GYtpKb3HT0OWshBaxyq3INt1lGoeZOr3KQ51FDEbXuHi+AEsx4Bp2NjZ2MR2 q45mpQTbNF5cPlSc17DA6/XVrTejYP0166Wt4jPtnwDT0HHvxh6uFvfZfzbqX3Ihc5oKoihGmkvs VctiF0UWcf9D1HTWNjl6mUkM1JDmHg7lg4pAqd6CriuMU4H4lLP9dMOGb/jIFtTz8ZgvX5AI0yq4 H0XWHbKcRLaD1HehWCX4AY3qq6hVa3AHZ7C1HItZgFRSmK9O/R/dbLNQlFhZ9LqWoyXm7gIyZRQq CiRRwWA0RppfYnP/NtzFHEWUo9Wow6xuIHz8iHeEy9mAcw5JMqHaNOpvQlBtmHaVj6dULBRZ49h5 MowHhIguV3hqmlDMfeCtf77IkcU+I2ko2ZmGGIJm8S6s0t3HkCafssYYGyrgmpwDlTKmoyuYJBid z6GaZd516TINDhTUt7a4gFOPjl6PToVDwJrxTgp+wuNoNjR9yQMEnSa4lQZm8wEPNtgnWeTcDyPm 2WoVQZ2OYWUxyiUTQi4wbYIU7bphYDXp4+mTB1BVnR0HhCaS0INlkibrBWLmq72Ur9cbU7D+oB5D wSGre5s7aBydYTwZYxlJLGY005y5T0W5gnq9BiUdYjqcsleQyALl9gYcy8Z8eIXZbApd6/CEiY4q ZsmCWKYcQJ2LHYPq0oRvJILRLf0QuphB0AxkScJyASJi0u4gzcHIlphQLjk9yYu175aIEvEC1dYW H9/oKJSm/RdgwAKSanADnOwlfpwzV71k6tDI8Kz5yHKVx/qC5HPwBU0saRdllsro7hxy0CrlLFKj no7A1CzX5YJJEqSlIk2aRDozoUDguxzTxULP1hYW0xlWqwWz58PVDAvaNZVL3MvylzOsZksoObC1 fwtp4KJUJ08hhW4kHHPmjvoYj0fwlgnnENZs8i6C2e0QTf5v4I4QBQHjdUhpRt8fKPiiyNHduQ3P W2Dukt3IA0oNLpCrkyMkiz6/HiY+ZCbyVcimdvq6pPcq1Xs8VfVGA+aDUaGlFGt/PodPkguzjKpT xmixgqRO+M+6oqzFsNdV6ytdb0bB+gOXIEqolKv43nvvYzRZQBBUFoSSXAGIX1LCoZt1JMUCeaHC Uh0gT4FwwZaPervDbHRKuolCH96zjzk1hmw/nY0Nvrkjn45upKpu4eTkBAH1oIQU89mCTbebGz22 2ozHU0RGDaPTE5gKUDZEhCuwTksy62h1tpHFHvx5CG+54OJGGqmrpx/xDRREHpwKAewUTruhgnNX L7ERWcwiNCml2rI5d5D0Xd2dHTQ6XdgrG0V2Cqdc5d3J/Z//GLYhouhswqk0oNgVLmhMSVAV1pTN J1NuYNPxiPqCQRhwdP3V0Ue4c/dt7N+5yR7GR8dPcTWdcYRauVxj1ha9VortSnyPBwWrVMXx1RXe 27699mgGc6RkDypVWbBaUB9JW4dihL6PLIp4QBJHMaZXREtVkBJzCxIk3WIUdWtzD/Pc5d8RFdIg TJm6UKs10N17G+4ygNNqIpicQVHoAUEC3hGKOMBgOIDT2YURxHwkPrka4NHTY9y98zY6dcpqNKHK JK64Xl/V+gdXsEgYuiLUcEJ9Eg3N7hYkcw53dIbz5ye8UxmOF2jv3ITrX0BQbFRrXbQ6Pbai3P+L /xObd7+HyXzOhmHq2VAxECwDwXyKy+OP4LRvQMoyiIqGVZzh4vQxugSr65/BqW1DMavwli6CuMDN b3wXtxQNZ8+f8tGTtExE9iwUA3EG1CoNFkeaSgHLMpjoSVA9pB4M0cVg5iOTSpgORyw03dnZQuwO sX/zAP3HS0pqZHHsahLCqu1gY+cAov8U0fQUBvW08hju4IIJqoPLEcTtQwj2DlYUVlEEvJsRRQXl egu//k//DiUlRamxCU3T+MiITIaqVTF49hg//MGf4s6tO1ysbz15hJ/89C/w/PjXiOIAi0RBpVpi MgZBBWn6h8Vv1rtRijKLPZSqdRbH0o6JeoLLcR+1ZhuJomLlFUhWHvLA5wdDf3TMei+7sQVHtWDY FbbekNrfru8xNFFTNPjTITRRRqWxzZFmhJteDJ7wcVpVFCyXK855lM0KlvCwu32Xhasf/eqvICYu K/on8ynau3fxw2/cQ9vRmWp7vb6a9YY33V/884t9fJwDV9M5fv3gQzz+5Bcsyvz1gydYeQEc2+ZA U8tScbOziYunH6PR7MGqUBpzAX8xQbCaobmxQWUP2/s3MJ2M1l9bSHH19BO0Nw6x37vFR5fxxRH3 ifRKG93tPVydPuO+16MPfwbD1LiRvJy6eLQYorZ5A/nsGbpVC63mLWQiRXlVsXPjLcwHz5k2kMJA OLuEnCdsKh6Nr6DbNQymKZpdE7dub6NSJaKmjEW0wvjJh5AVnWUJitFAkAUYjefIhHNcXk2RdjfQ tExkooQkzVByarj1znvQhAQPf/FnUI0SdvZvotFssfVnNh6h3tyA02izvWg1PWd889ILIes2/sf/ 6X/Gwf4hFyv6ce/vHTCm+OnIw2p1gjvf+ce4OnsOp1Xn75/sMN3NfTS2y+i0e1ANG/P+GZNX7XqX A2QVIUehaBDjJUq2hiWp7Sld2mlBq+1DrWzyjrFcrfL7pv6EiQzq5j6ujj7E/SfPYNll6JKMZ8dP cLC/B7Q3MDl7iGqjjTwKsBxN4IslNLp7+MHhOxg8fcjOhd7uAfTSAZM2/FiC7M1hixmJ9K/XV7je jIL1JcXqtx32BVtYxgsXDx58jI8+eoTdw7uot3fgRCEfL6hXE4dLVEtNvikhSvDmcy541KtJCK3c 6CEFSRlczMYX3IOqt9pobt3hp/zpkwcogiX3hcq9fW4UL0ZnaNVKUOwanj78GPEyhl3bRL1WRUZ9 Gm8GQTIYRkf0B4rNWnh0VAX6p0941E6KdCpAtk32oWwtwKw0YMwmUDIPQm4jilbwliEWFFGvmVjG BCzUoGo2pFhAFq/Yl5cpNqBWuOlf7R1gs9bmnyH59EhH1RBt7rNR5iFx3kmVT+Gy4moIqEBOlIoi YXHmVm89Mf3B937IiTt03KZeD6Vfb3Y6+JPvfRf3T7cRjp6ipOWYuh5WiyEqtoHuRg+BUEYce3D7 fY4US6EiXdLvABxMsRod86SUw05BuJwGWls3mJvfPriJ6cVjZLHKKGpCzhRXj+EmMa4unvER1jBM WJYJu9KAYJZx/uiXaOzeg0i9NGho7fZQmDX4qxlzwKjAd7duIISC0F2h3Wzh3Rt7ONjZhWXo18fB r3i9GQXr/3dKmCPKAT8l9TbdTAqD7MiWQQp1q+KwSTdKEihGiRviVHAI60t+QTYBI0W06qPc3UE4 XyAXVU5ppit4PnfZh0dFx18toUoiPH8JzSHiqAMhy7F9eBeriISib3FYBD3hKVB1EXjoNFu4PBrA 80xYJRMO2W+oWokSNLsKfzlFIakMoxOdKmuydIsa3ioMU4ZiGIjSFEKaQrerMLKCe0ueO+CADLKl GIaKVSBiNOjjxtvfw/DsGIjW3kWHvo6mM4q5Um7wzU2aLerP+fMhW1u2mlWcTlX8yfe/D6dUXicm iyITFBzb4XivF9vNT03o5ZKDb3/jLWzuHiKcX+Li6jnuP3oEwdHxzlvfxGZ3A+eDMSaTPlSpzDhn DyrmXsCaMndwAo0hiTQhFCFYAl+wWqmMcrWE0JushxZZivnkAtPBc/49FEkCUZSxtb2DemcLRbJm 7ZOeLXRqSHIRQgZ+gMiqxQbuwpvzcZtsWE61xjYgSvOmfuCtgz3USxVWwV+vr3a98QWLYriI+X05 HGA4d3FxdY6VO4Gt0yVJ07ockkE3hIyMQg6KnLHGlIJDvRQCvxHDifhYRRZiOOhDFURolQocUVmP 9/0VT9GI+FDf2OFp1GRwhqh/iVKljigruPmuEwbGUPkItj5a5JyuLMvqup/izlmaUK7VWWlNavFy rYGrwRDVVpspDgkJKLOQqQoxTfWcBhKC3VBvOcl4Mkeyg9kyYBpqRt17SqmhXZEigVDzhHQ+j0JU CM9CPbEsQeCnfLOTEdp2SrAMA6kE+C412xW8fesW2mUL777zLcbjvDxmfxb/8bIV/fLtZLdR0ajV Ua0C4k4XnWYDjWqDpQMHezfgOCXUqwOsVm3eCRZaCfNEwLPzMzx48EvIdASzWjwhpddWSBlbjFbu HGarhTxfrFHOwZLN5OPxJWarBJpicHp3o7PBg5QgTvioTAgas9LFcjJgegbtIPPVhNO6aUdd6Wwz dYKM5RrB/QqK5c1RLZU43OR6QvjVr69/wfpreld0LKQ+ysXUxa9+8ytc9S/hRREm0yk/VbubN+G6 c5YVcIpwFkOVBf7/oH/Fdhq1bPJNQok3BVQsZktsdLsQ+WJOGesrCjk8V+Imu1GuM04lE1UkcY50 tuD+yvDsBK1OB7E74ZBQjrmyKUI+4WMYefIogdojQoQIqKoESRSQhQGSKEHJKXN463R0xrl+7fYW EkGDWWpjPifI3XpahnwGIY24qW8ZFkQxQ04SCgEwdGOtDZtPGNFCmBXaAdKi959NRpyik1TLiKnP puusORNEk3crNw8PYRrWi33Up+YVFsF+jqn/Yr2ks0hM75TYs9fr7qwFvOKal97rbqBAb30kzQVY cYbQm+NBQeLbMmcd0oAkJcmJVKBSsmFJGdzBKUpVkmKkCBdjhOEccSFBsSpodvfgWBSOUWJOGWmq FNVCnovIAo8RPDLZjxYTfigR8poCYonqMHz+gB9CmihxhH3T0Xnyeq10fz2W/CY13F/eMC/z5Ojf VmmB42fP8OsPPmBWd3NzD7X2AR4/fIjdUgfZlEJBKVo+hUG0hfYu+k8+RiKRxAGQkhi+72M+PoeU R2g0dyFrGtyLx5x6XO4d8pf33Blm4yGTCwZX56jUmig1aywQLeKI8wdnwz6bl6ki0U1MtAD6JhUC 8y09lEwHqzDGKJqg2e6i1Wri2ekv0Kw3WUgaBy6jVMgT2KzVWbUuU1H2AwxHQ755ZaUFd+7z2wxK yenu8tQwCQOYVpUjwiiEolFvYEmva+nyxI5pFIKAbncL3ugYUSqipnVw0K2hTABBQUCpXF1bnT79 0b+MLn3x91e2IPy7KF55L+5BCZAkegzQn+jf10WP30MATEmApgsIayVsbR/g5OkDqNEC7iqH6dRw uLuLG7vb0FUZf/HjP4MlNSHVm5jEUywWgGpV0Wgc4t7b7yJdnTOrzGh0WPRJiBuiovqrFSobB0hi nxv2tCsO0xjtsoz61jaK5RWiQkKp1MDdnS7u7G6ty/N1/sRrsb7+BetLFt8OLyLHySO4cGcIKUiz EBjbQk/3JFhgNu7DKZcRrYaQZJUtOBmAqZ+gtd3FxdP7WIQJ5+aphgklSzAbPodYLcGoNDlSS5JU SIQuSdc7DKIzkLCTGOukuKbmudXa513OtH+BJgmtFIFN0jQZK28c4KMP/hLtVodZVw2y87gL5re3 SCtVb/Ou5+T4Efe9So0drChv7+ghNF/A7s4NlFQBviJiOLjghv3u4R3uQZFYkwJdI5+ORDrry4ir RaC9eLXE5ekRvy6iTYi2hUpvD2ePPoYphfjhd/4YP/zuD9BqdvlYTYWGmulMwmCD8OeL0xdjsD7N inzxEFmz0T87Lq5/T+vit1bLr2sfeTZJvyaFLstJbrXuotXoYKO7gVqlvP7dJTEsERgmKi6HfYiV NpJYhD+n3peLk4d/hbpjYD4do9regaXbGCc5To6PsHf3XQyefIhmb4ftPxINLISUqQ0p2acqG1BW Lt472MZ7b9351Py8zge4VmB91evNKlgvdlY06XGjHNMgxk9/+hM8+fjn7IkzSgZPwgg1rNtEtlzC anZgltt8oXurFWS9wObOHhbuHOXa9jpIlJrwZgmdziH0iysuWr0b7/ARbDy44AnWN7/zj3F68pQn Xt1GBWUpZnKmbpbR7G0hWc4wPXmE5SBE9+A2BEnFcjFFupjj+JOPUWO2U4jZ+TN0926hd3gT93/x E5w/f46Db36HyZj0PdUbLRzcIU9ewFTNaDXiqR19rK6rKNcbmI4H3L8ZD884PJWOlpZpodvrsZL+ r/78/0B7+ybKtTLzry7PziBeXWFjexPVVh2m1oYXUiBrAkmUuNBxUXl5w37hxv3rbuRXC9fvYqO/ LHb0X+q1UXbh+2+/g7k7Q7NcRavRZtDey2OkIqvYO7iFzbyANz7FJE5gORUclpvUrsPz+z+HvX1I 2DFcXDyDopVhN7cAq4ZVkLBQNlyM4M0GzLenHh0dMa3GFg7qNva/eQub3c6LYkXF+Zrr/rqsr33B Io3UF9OfF56PDx4/xS9+9mMECbAIqUcElKpVTlSmxirxlEjBffX8iFXi1JwlrDDl+uXBFG4sYGfv gO01dFNTeERAk8AiRnvvLQTTUwQeJUIH0J06nN4uqtUqsqICh2Fxc8RJCklJEY3PGc1CCBN3PuUJ 1mo1x3h0Bb3SWvscBYm9eapu8d/HwwtEFPIak8UmhestuflPhmrLthB5TwliikcPn7Lnzi43oJnl dSpPUSCOAkyGI7z73X+ENKPA1RxhISPwl9g6vMtR9WWHJoxVeHGBKRXEhcsDhEa5gd1d0nVVXn0O fHb4eyW09vf6Hb2y+3q1aP3WEfJFOo2pG9jpbWKj1eK0I2rer4/PLz+O/NgyJosVTi5GLM61yg5r uMieNHRDWAlQtsvYsE1U7Son7rhBgGmY8FQ3g85UCZE48VLBdFIpDfDW3bto1Wps3xKoVH9ao693 V6/D+toXrFcv+Jx2VwXgRhkm7grzxZz7Q41Wiy94UpKTGZZCDGjSRlgZapSTX40sKGTwzWMfi9kK hVlGFgfckKf+U7r0kawmyJIc7cYWK8e571IhD9sa7ULO/lxUML04ZghcYVTge0sk/TNU620mblLf CJQMI0tQTJuTpwW6OcQCml3Byg+58a5pdTQ395HJJlqdLQ6RoGDScLWAqSnIJZJExIyVoaJtGioc R4eglZAVBR95uxtb0FQJYiIgo2IV+Fi5U3Q6G5z/J8Hmr62aBlRdx8X5Jc5OTvHf/+iHuLl3yHIF Wq/eq3+TG/fLjopf9j4vO1q0k9IpeZn+/7I/+SIfl1aa5eiPJzh1Y6i1NrTpJRD70GmQISW4e+s2 ssxDt9rD7YObaNe7zGn34whHZ+c4NRz+WVBvkkS+omFja6OLXr3KqB9KT/pd3//1+mrXG1OwXl7Z JO6k+CiKwaJEm/l4gGqtyWbXJPB5J0O2DW/hor5BoRI6hz2IooocMtyFC6fSREHsLJr0eQvue5GW iZvGVgOBt0AYByBVkKVavFuhwkd3tu9OMSP6ZaUFu9SEJmkoApdDGEjnxZjgPIEqSmtyaBhzKMV8 5aK3fQPCbMIjdNYXxQJ6vS3kwRLdVhtXNABYubzTCjMBmqCgt7HDhRVJwLunLCRSgcDom1K5jPnl 00/jtrI0gK0rMKwy0mjBHycKMiTV5MguoiXQRG2nt41apfaCvPlyCX/nDoTffvfPitYXP8dnU8l1 X3I6m+D55RBJtIBm0MBAhFykqNea+M6372E0ukCv08ZWbwclp8KCVtJVGbqKQu2j37+CxmQICZVS Cd+4dQM1sj6p6h/+Oq/Xf7H1tS9Yn43TaepGLyiHjgSOEELhhrjOQalREDKmmPoXokL9EJkxxpAK 1txIlDqcFojTHBVKXs4y6JqNjMMOYki6CdV0kGnU/7hkIWNOO684hAjS/oiIU4pnd1mHFRNVAALK 1SaUCtEPJhAkGc3eJhC57EuUoaDklHB4+y73lmh8Xik5yJIA8WqGJIxg17q4ePwBWr1t1i1FuYiQ 5BJpgTzwYJctZIIMXzARxBk31cUshFPrQFMVTK/GsEilTj+cLEa9u4tStYkkmGFJUEIe9ftYkU8v i9FpNmGb1PdaH8FeVVv9QTuNv+Gm5NOG/KvHyFcEFLSoOJVsA2mwgDsb8wOGCRZJgFa9gnfvvYUw ucl5iTIl4LwI1iXa6VZ3A24Qs7xEazZQrtRQ0mQc9Fp89HwRB3C9XtP1tS9YXzxSGIqIg60tmOqf YP7jn6C9+0P0z59jdPSICQOikSFdjlEuWZy7J1Ncu2jwU5vwu1u7u/DdEex6B3Hkwa42IUcOU0UJ 4zIfX3JRdKo7rKCmRGifvH6zS6QZKdMbELU5RMVG6PkQkwi1bhOXR7+B3rzHOJowmAJxAMPW4BAF oLMFP4jw9Df/gUWkhI5JYg+13j4zn7wgwmgyRrla55CMpCDVu4T+s49gSzcQQ4Ze66LbaXEBXYyu 0Gx0sdFu40wmiqgBUaJUnDkkQcHO1hYKUUYsniIg+oM7xoL0YbGIW7t7qJUpCEP+w7RHfw+nps9P HtfNb1pUWLY2d7E1jxGJJUY2C/6cAyo6rc6nfbB1u+zFju2VYntrZxNyHjE2m6azhGlei/M5xeOz l3R9FHzt1te/YH0JvpbgeZ12F//8n/4z/Kv/+/+FqKrryeFsxMclssT89Oe/xI1OCXLsAXaDrTqG qiAZXsButBFBgVhEfIRcLVcYnB5zP8jzXGiCCGP3JnKFdD0ukwYo5853B3Da+9xgF/MMUrwCFjMs sxHq29/G0vPhTccMjzPLTU5+pl7yr//tv0Lv4Bscd8X4Yb2EMEkxuniK+raF1sY2e+ymiyUkJUGr t4tyucTF83QwRp4kuNHYYMU6oYa/86338L3DTTRrNQzuHXJSjSpLCNMC42WAWrWCcf8U+ewxDEWD UrERFQUM0cLtzQZHXHGiIws+X9zI/4VddL+z78W/b2J0Ae2SiRkmCIQVes1t3L5xE81643PyiVeb /es/kxZMwa3Dm59aiV69gtZI5Oue1eu6vv4F65X18rJ7+bTMkwiGSdOhBPXG+lgkqAacahXtio20 ENlgy3FP3hJ5Qs1vQs8UcAePGB3T6O6iuXXARWPWP4XtThG6fbZ6rJYjjPp9CFYV1Q0H/moOk1Jq TB3+6BzpasqBDqFcRTo7h6LZCDOfe01lvQut3EISLmFWWzg7O+YRO+2QLF2Hs7mHMVmJnnyIrdvv YrZYIQtiONSPKSL85i//DTJRRKN9AHc0xPFHv0CzUcPG1i7vqKhhTkegbo2opOszztiLcXExw7/+ f/4XDnQ4OXqGyWTGlNHu7h3s3jzAv/43/zvGozn+h3/x32B7o/cilIGO3V/c8fzev5TfvYq/Qb/r xfvQ97HdakAMb7IUot7oMmOf/H7rT/Wq0vMzacKaz07rJfXslU/MEobrYvU6rzeqYK3Xi36FpKBT r+Nf/uiP4YURrgZ9HJ2eYjRbMCGUWOIkYxhNhqi1NphxRGZokWB+mgx7axv+0sXk5AEU0+EJE+2g aq0tzHWTESe2YqNeqEgklUfkZrXLIakmee2SOkRCC6saksBFlApQCh+KYWPhxZjPRkgiF8PFCiXL xsn5My4K27v7yIIEqXu2RhZnEdzL+1DsDrPQ48CDXHFQrm/g2ckT1Bqkjs0gaybv2gRFx8Wzh7ho lHC40YX8IkhhrXGSYVsmFKOClXsFQxZh2xbCXOemdK1Ww91vfw+BJuPDoyfQNJmb/S93HV8mEP3K ViHA1DTsbO/zUX+d2PyiWL1QXaw3hp8/Ur4qYP3sc9HbPpMwXK/Xd339C9bveCq/HI1vtlvI0gyd apVxJ8/Oz/HJ0SMYpTJKkoz5cskKeJfi5SOXkcZyZiEuqAgYEDULC0pejn20N3YZlZzSzJH6JqIE SZGZsCmT/V/KMes/g93YZJQJTd5Ktgl/fI7p+QkXtFKpBTtXMR2coj84hZ8JKNe34McFw+sI/1Jz KsiSGMFyglZvC8+fH6Oq1KHoBhMckjiGoSlwnCbTBEq6ilKlxmxy2ika5RKW1ERnG826t0f3aJYm 8L0V0yqKLECt0YFZkxFmVLgMpN4YGw0To8kFJlPA93c+J7n6Mr/g32oJf5upImE4czQ8AAAVdklE QVSkReiG9eqbPpf5/dt19Uve9nf5eq7X3/v6+hesL1mfEye+mA5RSjBxkcjm8uv7H7N3TifGOUfH A0kiIZfAWh7C0VA0er1zwEGieRAw31zQHC5CpiwiiVK25dimxUES8XzEGi5TlVEEc2SZyH2hUJEh W1VY5RW8KIUapzwtTHNKpikYsyypOnYObiGNAmiSxFFgsmFjOrzA5uYWoqNnmI7G0C1KtjGRErkg z1Av22g2GjjoNVGv1uEHPqbTCU/MCLnyqdqzEFhPRsp829BgGQqCxEMmEP7GhhLHPLmMVxPE0QpC HrL9hQYRv8Vi+PveXf2BUogv9p/+Rl/yddgxXq9/IAXrSy7wV6UOrxYwGtWrFOwgEWHBZ5Ino3md MnLTQpzkDHyjo1qWFShkDS4l3iwXkIQc7nwBRAFCd8ZRXxTsYNF+KxGQLBdMbdjYuY3p1RMkfgTP +//aO9Pmtq7zjv+Ai7sAF7jYFxLgJonULtmWnSi2mzTJpOO86SRtX3TSN532O/SDdKZfoJ32dafT zLSeLknaZhI7zuJVkinJEkWKILFvFxdr5xxw00KacmTJIs9PI26AAAIk/jrnOc/z/1uy4zyTK8ha GMUirVpFpseILYjwlTJDllztLCzMEvAb9Oqb0iVCJPLEktN0un1S6SzdXh//aCC9sPojT47mjL0O tqnzypklplIJOl6fcqMtm1Mt/2jnhdgfw3qlwdpmmVGvh20YVEWuoM8kGg5L1wLhrKnp83itAZYl 7IOFb7u285xO5v6e0Qv7c0XrwczJna9+kVYxJVYvFC++YO3DrmhNtkPbrgCxWJzFxUXu/OxtRiND 9jKJJJlBryFn/8KzC7JDfdTzc79SodloMfI86ZBpaX7uLl+bnFCZFl6rQqdRk42ojuh4t2PSiUHU mmT0leiiFkkvYhvn1pk7cYKbyzdw2y1Z8xJ9mbXNdVmo1/oNolOzRINJApqYCZwiZF/i17/6JafO XiQWicqm1vt3r1Mv3pFZgW0PaRks7Gmk95RlkXTCW8nLfTnWIh51uzfkNx9f4yc//W80Xacwkye3 cJmZZIxkIsHK6h1u372LFU5hNxtSHH1D0VrRkyst0VA6eVJ33jzKtsD4nv3P+KmKzuPEUi3AvjIc WcHad2Uw6svYqXqjRTp/hszSZdlAWq8IY74Bo14VtAgbm/dotbpydRSdWaDfqUtXy/TCeZxkCq++ jluv4bfT0l/J65RxUmmqxXU2qj3avQAjTSeojyiXN2hUqpSrZXwBXboDdDstAgFdBmHUqveJzJ6k vHFX2tHMzJzi1Mw0s9N5Ts5Mc+vmMn/w0gW51fvxf/4b//4fIu14ntlMhg/ef5elk0skYwnS0Uk9 R7QliGK7T5x6MabebHFt+Rb/9867ss4VijmkTINCLsWpmQLzhTy5mUXW1u9z884yesjmf69/SLvT wjANTs7P7Vmp7nUV/RLZe/OH8Ot/qvepBOory9EWLPnL7H+gGitsUjTdoNEb8dLJRcbVe5TX1xmZ Nr5QijtrK1w+HWU6GUXPz8qu6NG4TzKToRcyZICn5vPwD9pERFqycMNERKwHaXWHhMJhctYS7mBM u+3KjngnmiCdmeKjX71NabMs7VyiiSy6ptOp9Cg3XeqVGpVyBb/mp9n8kHKpxOnzr/Jn332Tc9Mp gqZBsdWV6S4zC+c4PTfP97/zLT6+elXWzXzj4Va5amI2t9OOwJhcwuEHb32PXC7LL959l83795jK CjubMdp4TC4aJhqyWI3ZLL8fJTGzSDCRxRv2uF9cZWGmIHuX9rYGPNuf4xcoUO23UtrvdpRIvRC8 +IJ14C/yZEvo9QZUmm1c15Xd3iLX7uTCaVY+u0Zk1MKOhGVEe7lcplZv8smNW9jxFPXKhtzqdXsd 7t65Tzopxjc0Oo0SIzNMOOEw6PfpiJVINMXArcnCd7XZIZKZIWAK+5kVvM46i+evUpg5gR6IoptB 6UMlammRaJLir9+lWNwkPzcvR3yisSTz84ss5NIEhZvA1nbWDARIxZOcXDjBuRMzZOKOLKKL3D4x EC2UxP+YY3sr4GMhl8B5/TVy2Qz//PaP5dhKzIliWSK92k/YrzOTTvDDP/5T1poeH//6vxgFgtwq lvD96ue88fVvytvabr58pi/2LyJWe98/7jLFC8mLL1j7/K+5Myor3CZbbf7nvd+xUa0RNAI0hKd7 KMTHn/yOVDxOIDCUtSeZ/hzJMDSF60IIKzjCDsdwq2XajSbxSFzOG7rekOF4wNjfo16v0u60mZtf Qjdtmu66bCuoiRThbke0SNHuiPSZNRqlqiy4O8m0PI1sV+/jCaGYm5OZeaJG5jgx6akuhpTFtlCM AG4/zIilc/HEDCdyCVKOLWcPnZBwNBDb3olX1F7vJrnKkrN3YOkaqViEE3MznJpf5JWlk6RiMXlK KhDNsyHD4PT8PKlmB5tvUOsOaDdrtLvdnWd1pyC49/n/snmS1ZISpCPNiy9Ye355975QtxEpOcVq nXulEpVaHdsyaLWa+HWDwMBlRJpeR3S5dxnrNpru4KQL6L4hXl8c7w9gJMY5jIl/uGhhcLs0203a rbZMqxGtEuXNIlPTswy1qix61+t1+W/D0bj8vj795GM6zTrReEwaB45GIuC0TE8LkcnPyRNMEX4w Gnp0mxUGbgxTFz+e3dNOM+Ann4wyTk5ir3Ye/B5Re/S5mdSxBAGfj3Q4yLdffYmzs9PSs33n3wmP KbmK85OL2UTOXaDeduUMozbu7w5BP6+2pb0CtXcF9azFU/FcORqCtcUDR9xbDZOik6hUrWD4R6Sj QUbDASW3g+n3yRemGbYYdTq0e12a7oCh7sPrNjFMjVa7LqOvRFFeeL73ei7WsCc/r1XK2JEolm3j DT1Wbn+AbYiwsAFrK7dkYk3ItvGJmcKAhuf1ZO3MHzBoNRqYomPAcOj1/bheXw48R6NhuvUajIb4 AiY110MEJMuk4a3orMlj236Mu492P2/1vdcUuYuJkEF86cRWzt+DtyOCOMRqTVzmmLr8mxC9a6KJ a3fwieeG2uIde46OYD38P/CWTYghPh54+Lw6AX9AJrN4zSrRSAjDiRO0TUZaiFQ0JALvKLtDWvV7 lIcefsNmHDCk/7k4WRxZwiMrQyCSpXdvjbgo1A9HNCtFhowprlwnPnVeGsPFk2EsS5fjPVYgxuXX voHnVlm5dYOhP0woMcV4OKS+uioL7t1mCTdiEYoniERzDAIWxaaLGWwzFQ2jaY+ucHYiHA6qgo8f /ViETWw/TTtP2PaM3tbb7cvCpo4trL6+Qu0MiuPL0RGsPew0uouIKXx88+WXKSQcPrixzK21Ipns FHGtzzCRJDB0OXPhAmfPXCKRzMqeJuE39Xf/8Pd4WpDh2MfYGhLMWARCIXlqmM4W6PUuMui1GY+H JDJLcgwmNzcru8kNTadVukssvMjMwhmazY5sWO37DEzTptNuc/+zZZLxGCdPneTT998lMXdGHgqY 2HRdjzvLn9Cr3KWYm+etr10hFLS2IhseFJonP9Z/TNF868uiDeKxl23ZFysUz5sjKVh7N09iFSJ7 iRZOyVTfk7MV6WQg2gCKG6tkswXSqSwhaVqnSS9vTRtiOSlCeoD+YCQj0LvdNj3fSJrg3Vm/RcB2 8I39dNye9JZKppO06iWSqTSnz1/Edbv0BwNW796W3vGOE5R9VyFzTDqRRuxVBz0R8jDGCtuytnZ/ 5Ta2FcCMGviGQ/zmNJcW5tBFLUsKykOPcz+x2qcg/ajVyh4euv5+3usKxfPkaAnWg7ZJW+1Xky+K bm3Re5RKJuXJmHg5inRgw7SkPYmc1hcCNx6jaz7OzhVoDobcW1lh0GnSa7fo1jZxRYbhoMfUgvB8 bxI0DEKxDIPRSK5QOvUaXn1NRtZrRoR4NI6WjMtTupY7IDW9JE8Hm8IpM5omJQJRRVe6FWK6MEcm nyeWTJAIGlw5vUghl0GTJ3nbNi+PHiw89RPWJx0IVnqmeEYcLcESPLwK2f6SqGcZhvy7jaWbe+x3 t8/SxMyhj5eWFnjnkxu0Svfot6tyW9RodOgNeuSm8ljhOF4bLCtEMGhKs72eW8PIn5Ke6XpwYrM8 FN7pnR7tfp349KL0ngoaJrpffB8+hiI/MGhRXPuMUXcAvZSo8xO2o5woTEvHiV3X3kMKyedcbUfs 9rnes7BCVii+CEdLsPZ7Ae4Ro8fXbR68AXH9fDpFYaPISizGerFIp+OimWGalXvYYRettE4snsCw DGnLYgZGdLoNGSePYWEGLOm222treM06ISfOyK2iic73kIkRDdNpd/DclvB9oed5GJqfAH08t0nf CxMKBvd+q8prXHHsOVqCdQC7i4ZHu7R3tll7jErEPN7JuXlur5f5YHmF/rBDZnpadr+LbnnDGJOZ yqIxwG1XCNlhxuMcpq7RbdUICFsZK4xvHMFvBMmcuMDqxz/H1jT6bQ+t50kDuk67IQ344oWTBLUh oaCfYb/JcJDcqsHtMfE9KNDzEZ+nx1z2JKMq+92Hso9SPEeOjWDtvs4fCl59XMjndiOmsDTujzCt EFOFOVLZLLGILuf14omMLKYPPRcjGMVtV4mnpjDCMYZeh1RmWoalrt27hhXP4LkNwrEkvtFACpoR iuGzU9Tu3SFoBUnns+g+kX+4Jk82bdHBvv39bSXYfCli8bjmy8Pej9oOKp4xx0aw9nJQmOf2+9F4 JAel33j9dYKWxkcfvocR6KHFs7TXPkJ0dG6IBtHxgGxhFjF63G01ZR5hQDcn84Zeh0J+jtTsaW4t f8LK8jUCoSDT03MkpxZAtwl3PNxuk+LNX3Lm5e8wjpyltLlBo92RyiG6z3dcEp6kGP4kTZaP7zNV oy+KrxzHRrA+T6Qe/dyHo0N93Jdpy/1Oi2xmil4ghFsO0WjVsVNZWXAPhUMETYtms0WzXuP69etE UxkKuSzBgEazWuT0lT/Cq2+yVtxk+dpHdLt9pubOTJJ6ukPCsVk6dRHa2mDc7xPU8zKNeseLSrUZ KBRHTLCeQo1Frma2+ieF/UoiHOLsqSX6vT6lWp3Kxg2GmsFo7GM48uPVO7QqFYIM0SIZVu+t0PUG dO+v4+sPSESj9IZdBlzHSYiknDxutyfj4fv9DiORh2iFabfrGF4Hr92T97V88zr/2q3wwx/8aGvW b7cH/ZkFQagtn+IrxtESrKchWnuK8+LDsKEzl8tSq1a4t16kUqkQSeXxibaEQZ9auUSrVsIO2qS0 ELYjTvai0veqVC7jeX3p1S4Sa4QNcTxbYKZwil6nSrdZJhTL0a5VaLXqDMcdctkC+cw08aBJxBCp xdsiNfmuJoESSkkUx5OjJ1gHTfEfQsh2Uma2su0CYmA4YsueKDFE3fW6uO2aTGsJGBrjoTcRG7+f 8eYdknEbv3+I49j4NAu/rhMy/PK9EDYzaOMkUrLTXgw5a5pPOkUMu65oDGNmKscr586TdmKyH2x3 lOYpNowqFC8oR1OwDlN0Psh2d++2azzGFPl3+fykI96weOfnb+OT1jRIV4dILCps26nXigSIYoRS RIUFzCQQEDuSwImncJyItEAurd1F848I+Ed0RDCr2yYdjXFy6TznTixSyGSI2JGt0M9dexklVorj ztEVrN9z6/jAGAx+LMMil05ztlDi42iWVqtFpVFGs8LkZhcpb64RwI8RyZKemqfvtmlt3mHo1vAP 0+QXzpJbOEO1UqfXF97xdfyDDqadpN/zeOPrX+PrV14lk07LmcPthZUUTiVWCsUxF6xD1ru2ZxHF R6ZhcH7pHL9877d8uLEmQypSsVlsJ8X91XXmT11mfXWV8ie/4fTSWWaWLtFs1GRsljDvC4ZsNlc/ pd91GWsiFNXGGvWYns7w3W99m2gkvFVc31ar7ajiZ/FkKBRffY63YH2OaG1vCbdnEYWA6AGdP//B D/mXcIT3rt0kNjVHMp2l167j92uk0hlW79RoNxrEIjaWv0+reJ3C177Hrd/9jKCTwooGaFZKzGaS /OWP/gJTN4kIsz+RKL1939uJy6pmpVDsoATrAPbWsSZWUZNEGifi0PO6tKobNBoV2pWc9Fe/c/0j li5eIfXK60RsE803YBwMoQeyVEobYmSQQjpM1A4TWZznxNw86WRK+qlPSlVPEFWqVl2KY4gSLA5X x5qwe1IXj4sxm0m4hAiaKCyclsZ+m/duMZ3PYcSnGIkw0qEft+tj87PfsDhT4LVLL5FNJQkFbaLi JFCK1e5w9o5kKUFSKB5BCdah2DJ4kdvDMR23K5NzdCuCE0du6UTEfNgJc//2XdyWSdcOytO/Rq2G btg4ZoCrL7/MudPncCLhrUSbyZ/dc0CFQnEQSrAOiRCV3mBAuVrj05vLXLtxTZruzWfyDLwOm7c/ ZBSKYFqm3B4O+i6dxibaoMuli+dJhS9w9coVmQO4c4NbVuqqXUGhOBxKsA5ge5s2HI3peB7rmyXe ef99fvKzn6LRJ5rKYZg6/YGOpzvUNu6TSKVxWyXiyQSxRIp0SOf7b/4B0Whchj+IwvrD7hCqe12h OBxKsPbzMt9jylltNPntjZv84rfv06ysM7Ic6X9lOg71cpFms8Gp0xdY+0wn6CRx3QZus00imSCX n52IlbCIecAs8AusrNS+UXHMOb6CdYCXuSy275gnj9mot/jo1gp3VovERWrzsEoiEadWKlJZv4sd tnHCNu1ois21W1x96RJXX3uNQmGWsG1PRmz2xnM9q+FlheKIcXwF6zH9Vw8HscrNmg8SYYtC0uGm GcB2Yqwtv49laGgBg0giJz2xKqs3aVU2efPVK/zhG28yOzODZQVlbxbjLQM+5ZeuUPxeHF/BOoDd ldbk85gT5vRCgdXiGp+VNmg3a4wHIsZexNY3ZDRYyLR5/Xvf5fyZcxSm81KsHubAVZWyH1YoPhcl WIfANHTSiTj5bJoba5s4yQy6Bt12A10bMpMrcOncBb559aocv5GNoPtnJR8+vVqhUDzA8RasfYIb dhtGd9VjMBjgup60lTEzCeIRk0gwTTKW5vK5S5w9dQo7ZIMQK9kdv9O5oGKzFIqnxPEWrH3Y7W7f XfJ0PY9SZZPxoEW/tcGZi2/KBOepXJ75uYWdGK5JwX7yyRdYYykUigNQgnVgHWkSrSUkaL5Q4E/e eou//ad/JJ5Z5PKlqyzkpyfStDVvuC12D66qPke0lKYpFIdGCdbD+B53WugjoPmYzmT5m7/6a+mk EHOcnfitvZ7rCoXiy0MJ1qER1jIBMvHE5DMlUArFM0cJ1hOihEqheH4owVIoFC8MSrAUCsULgxIs hULxwqAES6FQvDAowVIoFLwo/D8RW7+NHFj2GwAAAABJRU5ErkJggg==