20240416 18183700 1.0 FALSE UpdateSchema "CIMDATA=<CIMStandardDataConnection xsi:type='typens:CIMStandardDataConnection' xmlns:xsi='http://www.w3.org/2001/XMLSchema-instance' xmlns:xs='http://www.w3.org/2001/XMLSchema' xmlns:typens='http://www.esri.com/schemas/ArcGIS/3.2.0'><WorkspaceConnectionString>DATABASE=E:\Nyaa_NSPEARS_Application\0_Michigan_Census_Tracts_Original</WorkspaceConnectionString><WorkspaceFactory>Shapefile</WorkspaceFactory><Dataset>tl_2020_26_tract</Dataset><DatasetType>esriDTFeatureClass</DatasetType></CIMStandardDataConnection>" <operationSequence><workflow><AddField><field_name>GEOID_Num</field_name><field_type>DOUBLE</field_type><field_is_nullable>False</field_is_nullable><field_is_required>False</field_is_required></AddField></workflow></operationSequence> CalculateField tl_2020_26_tract GEOID_Num !GEOID! Python # Text NO_ENFORCE_DOMAINS Clip tl_2020_26_tract co_outline E:\Nyaa_NSPEARS_Application\0_Michigan_Census_Tracts_Original\tl_2020_26_tract_clipped.shp # CopyFeatures E:\Nyaa_NSPEARS_Application\0_Michigan_Census_Tracts_Original\tl_2020_26_tract_clipped.shp E:\Nyaa_NSPEARS_Application\0_Michigan_Census_Tracts_Original\CensusTracts_No_Join.gdb\NAD_1983_2011_Michigan_GeoRef_Meters\tl_2020_26_tract_clipped # # # # ExportFeatures tl_2020_26_tract_clipped E:\Nyaa_NSPEARS_Application\0_Michigan_Census_Tracts_Original\CensusTracts_No_Join.gdb\NAD_1983_2011_Michigan_GeoRef_Meters\tl_2020_26_tract_clipped_with_ACS_data_join # NOT_USE_ALIAS "STATEFP "STATEFP" true true false 2 Text 0 0,First,#,tl_2020_26_tract_clipped,tl_2020_26_tract_clipped.STATEFP,0,1;COUNTYFP "COUNTYFP" true true false 3 Text 0 0,First,#,tl_2020_26_tract_clipped,tl_2020_26_tract_clipped.COUNTYFP,0,2;TRACTCE "TRACTCE" true true false 6 Text 0 0,First,#,tl_2020_26_tract_clipped,tl_2020_26_tract_clipped.TRACTCE,0,5;GEOID "GEOID" true true false 11 Text 0 0,First,#,tl_2020_26_tract_clipped,tl_2020_26_tract_clipped.GEOID,0,10;NAME "NAME" true true false 7 Text 0 0,First,#,tl_2020_26_tract_clipped,tl_2020_26_tract_clipped.NAME,0,6;NAMELSAD "NAMELSAD" true true false 20 Text 0 0,First,#,tl_2020_26_tract_clipped,tl_2020_26_tract_clipped.NAMELSAD,0,19;MTFCC "MTFCC" true true false 5 Text 0 0,First,#,tl_2020_26_tract_clipped,tl_2020_26_tract_clipped.MTFCC,0,4;FUNCSTAT "FUNCSTAT" true true false 1 Text 0 0,First,#,tl_2020_26_tract_clipped,tl_2020_26_tract_clipped.FUNCSTAT,0,0;ALAND "ALAND" true true false 8 Double 0 0,First,#,tl_2020_26_tract_clipped,tl_2020_26_tract_clipped.ALAND,-1,-1;AWATER "AWATER" true true false 8 Double 0 0,First,#,tl_2020_26_tract_clipped,tl_2020_26_tract_clipped.AWATER,-1,-1;INTPTLAT "INTPTLAT" true true false 11 Text 0 0,First,#,tl_2020_26_tract_clipped,tl_2020_26_tract_clipped.INTPTLAT,0,10;INTPTLON "INTPTLON" true true false 12 Text 0 0,First,#,tl_2020_26_tract_clipped,tl_2020_26_tract_clipped.INTPTLON,0,11;GEOID_Num "GEOID_Num" true true false 8 Double 0 0,First,#,tl_2020_26_tract_clipped,tl_2020_26_tract_clipped.GEOID_Num,-1,-1;Shape_Length "Shape_Length" false true true 8 Double 0 0,First,#,tl_2020_26_tract_clipped,tl_2020_26_tract_clipped.Shape_Length,-1,-1;Shape_Area "Shape_Area" false true true 8 Double 0 0,First,#,tl_2020_26_tract_clipped,tl_2020_26_tract_clipped.Shape_Area,-1,-1;JOIN_ID "JOIN_ID" true true false 8 BigInteger 0 0,First,#,tl_2020_26_tract_clipped,ACS_2021_Data_to_Join_NoHeaders_for_Join.csv.JOIN_ID,-1,-1,tl_2020_26_tract_clipped,ACS_2021_Data_to_Join_NoHeaders_for_Join.csv.JOIN_ID,-1,-1;Label "Label" true true false 8000 Text 0 0,First,#,tl_2020_26_tract_clipped,ACS_2021_Data_to_Join_NoHeaders_for_Join.csv.Label,0,7999,tl_2020_26_tract_clipped,ACS_2021_Data_to_Join_NoHeaders_for_Join.csv.Label,0,7999;Dataset "Dataset" true true false 8000 Text 0 0,First,#,tl_2020_26_tract_clipped,ACS_2021_Data_to_Join_NoHeaders_for_Join.csv.Dataset,0,7999,tl_2020_26_tract_clipped,ACS_2021_Data_to_Join_NoHeaders_for_Join.csv.Dataset,0,7999;Population "Population" true true false 4 Long 0 0,First,#,tl_2020_26_tract_clipped,ACS_2021_Data_to_Join_NoHeaders_for_Join.csv.Population,-1,-1,tl_2020_26_tract_clipped,ACS_2021_Data_to_Join_NoHeaders_for_Join.csv.Population,-1,-1;Male "Male" true true false 4 Long 0 0,First,#,tl_2020_26_tract_clipped,ACS_2021_Data_to_Join_NoHeaders_for_Join.csv.Male,-1,-1,tl_2020_26_tract_clipped,ACS_2021_Data_to_Join_NoHeaders_for_Join.csv.Male,-1,-1;Female "Female" true true false 4 Long 0 0,First,#,tl_2020_26_tract_clipped,ACS_2021_Data_to_Join_NoHeaders_for_Join.csv.Female,-1,-1,tl_2020_26_tract_clipped,ACS_2021_Data_to_Join_NoHeaders_for_Join.csv.Female,-1,-1;Under_18 "Under_18" true true false 4 Long 0 0,First,#,tl_2020_26_tract_clipped,ACS_2021_Data_to_Join_NoHeaders_for_Join.csv.Under_18,-1,-1,tl_2020_26_tract_clipped,ACS_2021_Data_to_Join_NoHeaders_for_Join.csv.Under_18,-1,-1;Over_60 "Over_60" true true false 4 Long 0 0,First,#,tl_2020_26_tract_clipped,ACS_2021_Data_to_Join_NoHeaders_for_Join.csv.Over_60,-1,-1,tl_2020_26_tract_clipped,ACS_2021_Data_to_Join_NoHeaders_for_Join.csv.Over_60,-1,-1;MedianAge "MedianAge" true true false 8000 Text 0 0,First,#,tl_2020_26_tract_clipped,ACS_2021_Data_to_Join_NoHeaders_for_Join.csv.MedianAge,0,7999,tl_2020_26_tract_clipped,ACS_2021_Data_to_Join_NoHeaders_for_Join.csv.MedianAge,0,7999;One_Race "One_Race" true true false 4 Long 0 0,First,#,tl_2020_26_tract_clipped,ACS_2021_Data_to_Join_NoHeaders_for_Join.csv.One_Race,-1,-1,tl_2020_26_tract_clipped,ACS_2021_Data_to_Join_NoHeaders_for_Join.csv.One_Race,-1,-1;TwoMoreRaces "TwoMoreRaces" true true false 4 Long 0 0,First,#,tl_2020_26_tract_clipped,ACS_2021_Data_to_Join_NoHeaders_for_Join.csv.TwoMoreRaces,-1,-1,tl_2020_26_tract_clipped,ACS_2021_Data_to_Join_NoHeaders_for_Join.csv.TwoMoreRaces,-1,-1;White "White" true true false 4 Long 0 0,First,#,tl_2020_26_tract_clipped,ACS_2021_Data_to_Join_NoHeaders_for_Join.csv.White,-1,-1,tl_2020_26_tract_clipped,ACS_2021_Data_to_Join_NoHeaders_for_Join.csv.White,-1,-1;Black "Black" true true false 4 Long 0 0,First,#,tl_2020_26_tract_clipped,ACS_2021_Data_to_Join_NoHeaders_for_Join.csv.Black,-1,-1,tl_2020_26_tract_clipped,ACS_2021_Data_to_Join_NoHeaders_for_Join.csv.Black,-1,-1;Amer_Indian "Amer_Indian" true true false 4 Long 0 0,First,#,tl_2020_26_tract_clipped,ACS_2021_Data_to_Join_NoHeaders_for_Join.csv.Amer_Indian,-1,-1,tl_2020_26_tract_clipped,ACS_2021_Data_to_Join_NoHeaders_for_Join.csv.Amer_Indian,-1,-1;Asian "Asian" true true false 4 Long 0 0,First,#,tl_2020_26_tract_clipped,ACS_2021_Data_to_Join_NoHeaders_for_Join.csv.Asian,-1,-1,tl_2020_26_tract_clipped,ACS_2021_Data_to_Join_NoHeaders_for_Join.csv.Asian,-1,-1;Hawaiian "Hawaiian" true true false 4 Long 0 0,First,#,tl_2020_26_tract_clipped,ACS_2021_Data_to_Join_NoHeaders_for_Join.csv.Hawaiian,-1,-1,tl_2020_26_tract_clipped,ACS_2021_Data_to_Join_NoHeaders_for_Join.csv.Hawaiian,-1,-1;OtherRace "OtherRace" true true false 4 Long 0 0,First,#,tl_2020_26_tract_clipped,ACS_2021_Data_to_Join_NoHeaders_for_Join.csv.OtherRace,-1,-1,tl_2020_26_tract_clipped,ACS_2021_Data_to_Join_NoHeaders_for_Join.csv.OtherRace,-1,-1;Hispanic "Hispanic" true true false 4 Long 0 0,First,#,tl_2020_26_tract_clipped,ACS_2021_Data_to_Join_NoHeaders_for_Join.csv.Hispanic,-1,-1,tl_2020_26_tract_clipped,ACS_2021_Data_to_Join_NoHeaders_for_Join.csv.Hispanic,-1,-1;NotHispanic "NotHispanic" true true false 4 Long 0 0,First,#,tl_2020_26_tract_clipped,ACS_2021_Data_to_Join_NoHeaders_for_Join.csv.NotHispanic,-1,-1,tl_2020_26_tract_clipped,ACS_2021_Data_to_Join_NoHeaders_for_Join.csv.NotHispanic,-1,-1;HousingUnits "HousingUnits" true true false 4 Long 0 0,First,#,tl_2020_26_tract_clipped,ACS_2021_Data_to_Join_NoHeaders_for_Join.csv.HousingUnits,-1,-1,tl_2020_26_tract_clipped,ACS_2021_Data_to_Join_NoHeaders_for_Join.csv.HousingUnits,-1,-1" # ExportFeatures tl_2020_26_tract_clipped_with_ACS_data_join E:\Nyaa_NSPEARS_Application\1_Data_Organization\SNAP_Indicators\N_PEARS_SNAP_Data.gdb\NAD_1983_2011_Michigan_GeoRef_Meters\Census_Tracts_with_ACS_Data_and_SNAP_Indicators # NOT_USE_ALIAS "STATEFP "STATEFP" true true false 2 Text 0 0,First,#,tl_2020_26_tract_clipped_with_ACS_data_join,tl_2020_26_tract_clipped_with_ACS_data_join.STATEFP,0,1;COUNTYFP "COUNTYFP" true true false 3 Text 0 0,First,#,tl_2020_26_tract_clipped_with_ACS_data_join,tl_2020_26_tract_clipped_with_ACS_data_join.COUNTYFP,0,2;TRACTCE "TRACTCE" true true false 6 Text 0 0,First,#,tl_2020_26_tract_clipped_with_ACS_data_join,tl_2020_26_tract_clipped_with_ACS_data_join.TRACTCE,0,5;GEOID "GEOID" true true false 11 Text 0 0,First,#,tl_2020_26_tract_clipped_with_ACS_data_join,tl_2020_26_tract_clipped_with_ACS_data_join.GEOID,0,10;NAME "NAME" true true false 7 Text 0 0,First,#,tl_2020_26_tract_clipped_with_ACS_data_join,tl_2020_26_tract_clipped_with_ACS_data_join.NAME,0,6;NAMELSAD "NAMELSAD" true true false 20 Text 0 0,First,#,tl_2020_26_tract_clipped_with_ACS_data_join,tl_2020_26_tract_clipped_with_ACS_data_join.NAMELSAD,0,19;MTFCC "MTFCC" true true false 5 Text 0 0,First,#,tl_2020_26_tract_clipped_with_ACS_data_join,tl_2020_26_tract_clipped_with_ACS_data_join.MTFCC,0,4;FUNCSTAT "FUNCSTAT" true true false 1 Text 0 0,First,#,tl_2020_26_tract_clipped_with_ACS_data_join,tl_2020_26_tract_clipped_with_ACS_data_join.FUNCSTAT,0,0;ALAND "ALAND" true true false 8 Double 0 0,First,#,tl_2020_26_tract_clipped_with_ACS_data_join,tl_2020_26_tract_clipped_with_ACS_data_join.ALAND,-1,-1;AWATER "AWATER" true true false 8 Double 0 0,First,#,tl_2020_26_tract_clipped_with_ACS_data_join,tl_2020_26_tract_clipped_with_ACS_data_join.AWATER,-1,-1;INTPTLAT "INTPTLAT" true true false 11 Text 0 0,First,#,tl_2020_26_tract_clipped_with_ACS_data_join,tl_2020_26_tract_clipped_with_ACS_data_join.INTPTLAT,0,10;INTPTLON "INTPTLON" true true false 12 Text 0 0,First,#,tl_2020_26_tract_clipped_with_ACS_data_join,tl_2020_26_tract_clipped_with_ACS_data_join.INTPTLON,0,11;GEOID_Num "GEOID_Num" true true false 8 Double 0 0,First,#,tl_2020_26_tract_clipped_with_ACS_data_join,tl_2020_26_tract_clipped_with_ACS_data_join.GEOID_Num,-1,-1;JOIN_ID "JOIN_ID" true true false 8 BigInteger 0 0,First,#,tl_2020_26_tract_clipped_with_ACS_data_join,tl_2020_26_tract_clipped_with_ACS_data_join.JOIN_ID,-1,-1;Label "Label" true true false 8000 Text 0 0,First,#,tl_2020_26_tract_clipped_with_ACS_data_join,tl_2020_26_tract_clipped_with_ACS_data_join.Label,0,7999;Dataset "Dataset" true true false 8000 Text 0 0,First,#,tl_2020_26_tract_clipped_with_ACS_data_join,tl_2020_26_tract_clipped_with_ACS_data_join.Dataset,0,7999;Population "Population" true true false 4 Long 0 0,First,#,tl_2020_26_tract_clipped_with_ACS_data_join,tl_2020_26_tract_clipped_with_ACS_data_join.Population,-1,-1;Male "Male" true true false 4 Long 0 0,First,#,tl_2020_26_tract_clipped_with_ACS_data_join,tl_2020_26_tract_clipped_with_ACS_data_join.Male,-1,-1;Female "Female" true true false 4 Long 0 0,First,#,tl_2020_26_tract_clipped_with_ACS_data_join,tl_2020_26_tract_clipped_with_ACS_data_join.Female,-1,-1;Under_18 "Under 18" true true false 4 Long 0 0,First,#,tl_2020_26_tract_clipped_with_ACS_data_join,tl_2020_26_tract_clipped_with_ACS_data_join.Under_18,-1,-1;Over_60 "Over 60" true true false 4 Long 0 0,First,#,tl_2020_26_tract_clipped_with_ACS_data_join,tl_2020_26_tract_clipped_with_ACS_data_join.Over_60,-1,-1;MedianAge "Median Age" true true false 8000 Text 0 0,First,#,tl_2020_26_tract_clipped_with_ACS_data_join,tl_2020_26_tract_clipped_with_ACS_data_join.MedianAge,0,7999;One_Race "One Race" true true false 4 Long 0 0,First,#,tl_2020_26_tract_clipped_with_ACS_data_join,tl_2020_26_tract_clipped_with_ACS_data_join.One_Race,-1,-1;TwoMoreRaces "Two or More Races" true true false 4 Long 0 0,First,#,tl_2020_26_tract_clipped_with_ACS_data_join,tl_2020_26_tract_clipped_with_ACS_data_join.TwoMoreRaces,-1,-1;White "White" true true false 4 Long 0 0,First,#,tl_2020_26_tract_clipped_with_ACS_data_join,tl_2020_26_tract_clipped_with_ACS_data_join.White,-1,-1;Black "Black of African American" true true false 4 Long 0 0,First,#,tl_2020_26_tract_clipped_with_ACS_data_join,tl_2020_26_tract_clipped_with_ACS_data_join.Black,-1,-1;Amer_Indian "American Indian and Alaska Native" true true false 4 Long 0 0,First,#,tl_2020_26_tract_clipped_with_ACS_data_join,tl_2020_26_tract_clipped_with_ACS_data_join.Amer_Indian,-1,-1;Asian "Asian" true true false 4 Long 0 0,First,#,tl_2020_26_tract_clipped_with_ACS_data_join,tl_2020_26_tract_clipped_with_ACS_data_join.Asian,-1,-1;Hawaiian "Native Hawaiian and Other Pacific Islander" true true false 4 Long 0 0,First,#,tl_2020_26_tract_clipped_with_ACS_data_join,tl_2020_26_tract_clipped_with_ACS_data_join.Hawaiian,-1,-1;OtherRace "Other Race" true true false 4 Long 0 0,First,#,tl_2020_26_tract_clipped_with_ACS_data_join,tl_2020_26_tract_clipped_with_ACS_data_join.OtherRace,-1,-1;Hispanic "Hispanic or Latino" true true false 4 Long 0 0,First,#,tl_2020_26_tract_clipped_with_ACS_data_join,tl_2020_26_tract_clipped_with_ACS_data_join.Hispanic,-1,-1;NotHispanic "Not Hispanic or Latino" true true false 4 Long 0 0,First,#,tl_2020_26_tract_clipped_with_ACS_data_join,tl_2020_26_tract_clipped_with_ACS_data_join.NotHispanic,-1,-1;HousingUnits "Housing Units" true true false 4 Long 0 0,First,#,tl_2020_26_tract_clipped_with_ACS_data_join,tl_2020_26_tract_clipped_with_ACS_data_join.HousingUnits,-1,-1;Shape_Length "Shape_Length" false true true 8 Double 0 0,First,#,tl_2020_26_tract_clipped_with_ACS_data_join,tl_2020_26_tract_clipped_with_ACS_data_join.Shape_Length,-1,-1;Shape_Area "Shape_Area" false true true 8 Double 0 0,First,#,tl_2020_26_tract_clipped_with_ACS_data_join,tl_2020_26_tract_clipped_with_ACS_data_join.Shape_Area,-1,-1;CensusTract "CensusTract" true true false 8 BigInteger 0 0,First,#,tl_2020_26_tract_clipped_with_ACS_data_join,SNAP_Data_to_Join.csv.CensusTract,-1,-1,tl_2020_26_tract_clipped_with_ACS_data_join,SNAP_Data_to_Join.csv.CensusTract,-1,-1;S2201_C01_001E "S2201_C01_001E" true true false 4 Long 0 0,First,#,tl_2020_26_tract_clipped_with_ACS_data_join,SNAP_Data_to_Join.csv.S2201_C01_001E,-1,-1,tl_2020_26_tract_clipped_with_ACS_data_join,SNAP_Data_to_Join.csv.S2201_C01_001E,-1,-1;S2201_C01_002E "S2201_C01_002E" true true false 4 Long 0 0,First,#,tl_2020_26_tract_clipped_with_ACS_data_join,SNAP_Data_to_Join.csv.S2201_C01_002E,-1,-1,tl_2020_26_tract_clipped_with_ACS_data_join,SNAP_Data_to_Join.csv.S2201_C01_002E,-1,-1;S2201_C01_009E "S2201_C01_009E" true true false 4 Long 0 0,First,#,tl_2020_26_tract_clipped_with_ACS_data_join,SNAP_Data_to_Join.csv.S2201_C01_009E,-1,-1,tl_2020_26_tract_clipped_with_ACS_data_join,SNAP_Data_to_Join.csv.S2201_C01_009E,-1,-1;S2201_C01_021E "S2201_C01_021E" true true false 4 Long 0 0,First,#,tl_2020_26_tract_clipped_with_ACS_data_join,SNAP_Data_to_Join.csv.S2201_C01_021E,-1,-1,tl_2020_26_tract_clipped_with_ACS_data_join,SNAP_Data_to_Join.csv.S2201_C01_021E,-1,-1;S2201_C01_023E "S2201_C01_023E" true true false 4 Long 0 0,First,#,tl_2020_26_tract_clipped_with_ACS_data_join,SNAP_Data_to_Join.csv.S2201_C01_023E,-1,-1,tl_2020_26_tract_clipped_with_ACS_data_join,SNAP_Data_to_Join.csv.S2201_C01_023E,-1,-1;S2201_C01_034E "S2201_C01_034E" true true false 4 Long 0 0,First,#,tl_2020_26_tract_clipped_with_ACS_data_join,SNAP_Data_to_Join.csv.S2201_C01_034E,-1,-1,tl_2020_26_tract_clipped_with_ACS_data_join,SNAP_Data_to_Join.csv.S2201_C01_034E,-1,-1;S2201_C02_002E "S2201_C02_002E" true true false 8 Double 0 0,First,#,tl_2020_26_tract_clipped_with_ACS_data_join,SNAP_Data_to_Join.csv.S2201_C02_002E,-1,-1,tl_2020_26_tract_clipped_with_ACS_data_join,SNAP_Data_to_Join.csv.S2201_C02_002E,-1,-1;S2201_C02_009E "S2201_C02_009E" true true false 8 Double 0 0,First,#,tl_2020_26_tract_clipped_with_ACS_data_join,SNAP_Data_to_Join.csv.S2201_C02_009E,-1,-1,tl_2020_26_tract_clipped_with_ACS_data_join,SNAP_Data_to_Join.csv.S2201_C02_009E,-1,-1;S2201_C02_021E "S2201_C02_021E" true true false 8 Double 0 0,First,#,tl_2020_26_tract_clipped_with_ACS_data_join,SNAP_Data_to_Join.csv.S2201_C02_021E,-1,-1,tl_2020_26_tract_clipped_with_ACS_data_join,SNAP_Data_to_Join.csv.S2201_C02_021E,-1,-1;S2201_C02_023E "S2201_C02_023E" true true false 8 Double 0 0,First,#,tl_2020_26_tract_clipped_with_ACS_data_join,SNAP_Data_to_Join.csv.S2201_C02_023E,-1,-1,tl_2020_26_tract_clipped_with_ACS_data_join,SNAP_Data_to_Join.csv.S2201_C02_023E,-1,-1;S2201_C03_001E "S2201_C03_001E" true true false 4 Long 0 0,First,#,tl_2020_26_tract_clipped_with_ACS_data_join,SNAP_Data_to_Join.csv.S2201_C03_001E,-1,-1,tl_2020_26_tract_clipped_with_ACS_data_join,SNAP_Data_to_Join.csv.S2201_C03_001E,-1,-1;S2201_C03_002E "S2201_C03_002E" true true false 4 Long 0 0,First,#,tl_2020_26_tract_clipped_with_ACS_data_join,SNAP_Data_to_Join.csv.S2201_C03_002E,-1,-1,tl_2020_26_tract_clipped_with_ACS_data_join,SNAP_Data_to_Join.csv.S2201_C03_002E,-1,-1;S2201_C03_009E "S2201_C03_009E" true true false 4 Long 0 0,First,#,tl_2020_26_tract_clipped_with_ACS_data_join,SNAP_Data_to_Join.csv.S2201_C03_009E,-1,-1,tl_2020_26_tract_clipped_with_ACS_data_join,SNAP_Data_to_Join.csv.S2201_C03_009E,-1,-1;S2201_C03_021E "S2201_C03_021E" true true false 4 Long 0 0,First,#,tl_2020_26_tract_clipped_with_ACS_data_join,SNAP_Data_to_Join.csv.S2201_C03_021E,-1,-1,tl_2020_26_tract_clipped_with_ACS_data_join,SNAP_Data_to_Join.csv.S2201_C03_021E,-1,-1;S2201_C03_023E "S2201_C03_023E" true true false 4 Long 0 0,First,#,tl_2020_26_tract_clipped_with_ACS_data_join,SNAP_Data_to_Join.csv.S2201_C03_023E,-1,-1,tl_2020_26_tract_clipped_with_ACS_data_join,SNAP_Data_to_Join.csv.S2201_C03_023E,-1,-1;S2201_C03_034E "S2201_C03_034E" true true false 4 Long 0 0,First,#,tl_2020_26_tract_clipped_with_ACS_data_join,SNAP_Data_to_Join.csv.S2201_C03_034E,-1,-1,tl_2020_26_tract_clipped_with_ACS_data_join,SNAP_Data_to_Join.csv.S2201_C03_034E,-1,-1;S2201_C04_002E "S2201_C04_002E" true true false 8 Double 0 0,First,#,tl_2020_26_tract_clipped_with_ACS_data_join,SNAP_Data_to_Join.csv.S2201_C04_002E,-1,-1,tl_2020_26_tract_clipped_with_ACS_data_join,SNAP_Data_to_Join.csv.S2201_C04_002E,-1,-1;S2201_C04_009E "S2201_C04_009E" true true false 8 Double 0 0,First,#,tl_2020_26_tract_clipped_with_ACS_data_join,SNAP_Data_to_Join.csv.S2201_C04_009E,-1,-1,tl_2020_26_tract_clipped_with_ACS_data_join,SNAP_Data_to_Join.csv.S2201_C04_009E,-1,-1;S2201_C04_021E "S2201_C04_021E" true true false 8 Double 0 0,First,#,tl_2020_26_tract_clipped_with_ACS_data_join,SNAP_Data_to_Join.csv.S2201_C04_021E,-1,-1,tl_2020_26_tract_clipped_with_ACS_data_join,SNAP_Data_to_Join.csv.S2201_C04_021E,-1,-1;S2201_C04_023E "S2201_C04_023E" true true false 4 Long 0 0,First,#,tl_2020_26_tract_clipped_with_ACS_data_join,SNAP_Data_to_Join.csv.S2201_C04_023E,-1,-1,tl_2020_26_tract_clipped_with_ACS_data_join,SNAP_Data_to_Join.csv.S2201_C04_023E,-1,-1;Field22 "Field22" true true false 8000 Text 0 0,First,#,tl_2020_26_tract_clipped_with_ACS_data_join,SNAP_Data_to_Join.csv.Field22,0,7999,tl_2020_26_tract_clipped_with_ACS_data_join,SNAP_Data_to_Join.csv.Field22,0,7999" # DeleteField "Number of Households Who Receive SNAP Benefits" Field22 "Delete Fields" UpdateSchema "CIMDATA=<CIMFeatureDatasetDataConnection xsi:type='typens:CIMFeatureDatasetDataConnection' xmlns:xsi='http://www.w3.org/2001/XMLSchema-instance' xmlns:xs='http://www.w3.org/2001/XMLSchema' xmlns:typens='http://www.esri.com/schemas/ArcGIS/3.2.0'><FeatureDataset>NAD_1983_2011_Michigan_GeoRef_Meters</FeatureDataset><WorkspaceConnectionString>DATABASE=E:\Nyaa_NSPEARS_Application\1_Data_Organization\SNAP_Indicators\N_PEARS_SNAP_Data.gdb</WorkspaceConnectionString><WorkspaceFactory>FileGDB</WorkspaceFactory><Dataset>Census_Tracts_with_ACS_Data_and_SNAP_Indicators</Dataset><DatasetType>esriDTFeatureClass</DatasetType></CIMFeatureDatasetDataConnection>" <operationSequence><workflow><AddField><field_name>JoinID_2</field_name><field_type>DOUBLE</field_type><field_is_nullable>True</field_is_nullable><field_is_required>False</field_is_required></AddField></workflow></operationSequence> UpdateSchema "CIMDATA=<CIMFeatureDatasetDataConnection xsi:type='typens:CIMFeatureDatasetDataConnection' xmlns:xsi='http://www.w3.org/2001/XMLSchema-instance' xmlns:xs='http://www.w3.org/2001/XMLSchema' xmlns:typens='http://www.esri.com/schemas/ArcGIS/3.2.0'><FeatureDataset>NAD_1983_2011_Michigan_GeoRef_Meters</FeatureDataset><WorkspaceConnectionString>DATABASE=E:\Nyaa_NSPEARS_Application\1_Data_Organization\SNAP_Indicators\N_PEARS_SNAP_Data.gdb</WorkspaceConnectionString><WorkspaceFactory>FileGDB</WorkspaceFactory><Dataset>Census_Tracts_with_ACS_Data_and_SNAP_Indicators</Dataset><DatasetType>esriDTFeatureClass</DatasetType></CIMFeatureDatasetDataConnection>" <operationSequence><workflow><AddField><field_name>CensusTract2</field_name><field_type>DOUBLE</field_type><field_is_nullable>True</field_is_nullable><field_is_required>False</field_is_required></AddField></workflow></operationSequence> CalculateField "SNAP Households Median Household Income in the Last 12 Months" JoinID_2 !JOIN_ID! Python # Text NO_ENFORCE_DOMAINS CalculateField "SNAP Households Median Household Income in the Last 12 Months" CensusTract2 !CensusTract! Python # Text NO_ENFORCE_DOMAINS DeleteField "SNAP Households Median Household Income in the Last 12 Months" CensusTract "Delete Fields" DeleteField "SNAP Households Median Household Income in the Last 12 Months" JOIN_ID "Delete Fields" UpdateSchema "CIMDATA=<CIMFeatureDatasetDataConnection xsi:type='typens:CIMFeatureDatasetDataConnection' xmlns:xsi='http://www.w3.org/2001/XMLSchema-instance' xmlns:xs='http://www.w3.org/2001/XMLSchema' xmlns:typens='http://www.esri.com/schemas/ArcGIS/3.2.0'><FeatureDataset>NAD_1983_2011_Michigan_GeoRef_Meters</FeatureDataset><WorkspaceConnectionString>DATABASE=E:\Nyaa_NSPEARS_Application\1_Data_Organization\SNAP_Indicators\N_PEARS_SNAP_Data.gdb</WorkspaceConnectionString><WorkspaceFactory>FileGDB</WorkspaceFactory><Dataset>Census_Tracts_with_ACS_Data_and_SNAP_Indicators</Dataset><DatasetType>esriDTFeatureClass</DatasetType></CIMFeatureDatasetDataConnection>" <operationSequence><workflow><AddField><field_name>S2201_C03_034E_TEXT</field_name><field_type>TEXT</field_type><field_length>255</field_length><field_is_nullable>True</field_is_nullable><field_is_required>False</field_is_required></AddField></workflow></operationSequence> CalculateField "SNAP Households Median Household Income in the Last 12 Months" S2201_C03_034E_TEXT !S2201_C03_034E! Python # Text NO_ENFORCE_DOMAINS CalculateField "SNAP Households Median Household Income in the Last 12 Months" S2201_C03_034E_TEXT "$"+!S2201_C03_034E_TEXT! Python # Text NO_ENFORCE_DOMAINS UpdateSchema "CIMDATA=<CIMFeatureDatasetDataConnection xsi:type='typens:CIMFeatureDatasetDataConnection' xmlns:xsi='http://www.w3.org/2001/XMLSchema-instance' xmlns:xs='http://www.w3.org/2001/XMLSchema' xmlns:typens='http://www.esri.com/schemas/ArcGIS/3.2.0'><FeatureDataset>NAD_1983_2011_Michigan_GeoRef_Meters</FeatureDataset><WorkspaceConnectionString>DATABASE=E:\Nyaa_NSPEARS_Application\1_Data_Organization\SNAP_Indicators\N_PEARS_SNAP_Data.gdb</WorkspaceConnectionString><WorkspaceFactory>FileGDB</WorkspaceFactory><Dataset>Census_Tracts_with_ACS_Data_and_SNAP_Indicators</Dataset><DatasetType>esriDTFeatureClass</DatasetType></CIMFeatureDatasetDataConnection>" <operationSequence><workflow><AddField><field_name>temp</field_name><field_type>TEXT</field_type><field_length>255</field_length><field_is_nullable>True</field_is_nullable><field_is_required>False</field_is_required></AddField></workflow><workflow><AddField><field_name>temp2</field_name><field_type>TEXT</field_type><field_length>255</field_length><field_is_nullable>True</field_is_nullable><field_is_required>False</field_is_required></AddField></workflow></operationSequence> CalculateField "SNAP Households Median Household Income in the Last 12 Months" temp Right([S2201_C03_034E_TEXT],3) VBScript # Text NO_ENFORCE_DOMAINS CalculateField "SNAP Households Median Household Income in the Last 12 Months" temp2 Left([S2201_C03_034E_TEXT],2) VBScript # Text NO_ENFORCE_DOMAINS CalculateField "SNAP Households Median Household Income in the Last 12 Months" temp2 Left([S2201_C03_034E_TEXT],3) VBScript # Text NO_ENFORCE_DOMAINS CalculateField "SNAP Households Median Household Income in the Last 12 Months" temp2 Left([S2201_C03_034E_TEXT],4) VBScript # Text NO_ENFORCE_DOMAINS CalculateField "SNAP Households Median Household Income in the Last 12 Months" temp2 "!temp2! + ","" Python # Text NO_ENFORCE_DOMAINS CalculateField "SNAP Households Median Household Income in the Last 12 Months" S2201_C03_034E_TEXT "!temp! + !temp2!" Python # Text NO_ENFORCE_DOMAINS CalculateField "SNAP Households Median Household Income in the Last 12 Months" S2201_C03_034E_TEXT "!temp2! + !temp!" Python # Text NO_ENFORCE_DOMAINS DeleteField "SNAP Households Median Household Income in the Last 12 Months" temp "Delete Fields" DeleteField "SNAP Households Median Household Income in the Last 12 Months" temp2 "Delete Fields" Rename E:\Nyaa_NSPEARS_Application\2_Data_Layers_Uploaded_to_Data_Repository\SNAP_Indicator_Layers.gdb\NAD_1983_2011_Michigan_GeoRef_Meters\Census_Tracts_with_ACS_Data_and_SNAP_Indicators E:\Nyaa_NSPEARS_Application\2_Data_Layers_Uploaded_to_Data_Repository\SNAP_Indicator_Layers.gdb\NAD_1983_2011_Michigan_GeoRef_Meters\Orig_Make_Copy FeatureClass ExportFeatures Orig_Make_Copy E:\Nyaa_NSPEARS_Application\2_Data_Layers_Uploaded_to_Data_Repository\DemographicContextualVariables.gdb\NAD_1983_2011_Michigan_GeoRef_Meters\Demographic_Contextual_Variables # NOT_USE_ALIAS "STATEFP "STATEFP" true true false 2 Text 0 0,First,#,Orig_Make_Copy,Orig_Make_Copy.STATEFP,0,1;COUNTYFP "COUNTYFP" true true false 3 Text 0 0,First,#,Orig_Make_Copy,Orig_Make_Copy.COUNTYFP,0,2;TRACTCE "TRACTCE" true true false 6 Text 0 0,First,#,Orig_Make_Copy,Orig_Make_Copy.TRACTCE,0,5;GEOID "GEOID" true true false 11 Text 0 0,First,#,Orig_Make_Copy,Orig_Make_Copy.GEOID,0,10;NAME "NAME" true true false 7 Text 0 0,First,#,Orig_Make_Copy,Orig_Make_Copy.NAME,0,6;NAMELSAD "NAMELSAD" true true false 20 Text 0 0,First,#,Orig_Make_Copy,Orig_Make_Copy.NAMELSAD,0,19;MTFCC "MTFCC" true true false 5 Text 0 0,First,#,Orig_Make_Copy,Orig_Make_Copy.MTFCC,0,4;FUNCSTAT "FUNCSTAT" true true false 1 Text 0 0,First,#,Orig_Make_Copy,Orig_Make_Copy.FUNCSTAT,0,0;ALAND "ALAND" true true false 8 Double 0 0,First,#,Orig_Make_Copy,Orig_Make_Copy.ALAND,-1,-1;AWATER "AWATER" true true false 8 Double 0 0,First,#,Orig_Make_Copy,Orig_Make_Copy.AWATER,-1,-1;INTPTLAT "INTPTLAT" true true false 11 Text 0 0,First,#,Orig_Make_Copy,Orig_Make_Copy.INTPTLAT,0,10;INTPTLON "INTPTLON" true true false 12 Text 0 0,First,#,Orig_Make_Copy,Orig_Make_Copy.INTPTLON,0,11;GEOID_Num "GEOID_Num" true true false 8 Double 0 0,First,#,Orig_Make_Copy,Orig_Make_Copy.GEOID_Num,-1,-1;Label "Label" true true false 8000 Text 0 0,First,#,Orig_Make_Copy,Orig_Make_Copy.Label,0,7999;Dataset "Dataset" true true false 8000 Text 0 0,First,#,Orig_Make_Copy,Orig_Make_Copy.Dataset,0,7999;Population "Population" true true false 4 Long 0 0,First,#,Orig_Make_Copy,Orig_Make_Copy.Population,-1,-1;Male "Male" true true false 4 Long 0 0,First,#,Orig_Make_Copy,Orig_Make_Copy.Male,-1,-1;Female "Female" true true false 4 Long 0 0,First,#,Orig_Make_Copy,Orig_Make_Copy.Female,-1,-1;Under_18 "Under 18" true true false 4 Long 0 0,First,#,Orig_Make_Copy,Orig_Make_Copy.Under_18,-1,-1;Over_60 "Over 60" true true false 4 Long 0 0,First,#,Orig_Make_Copy,Orig_Make_Copy.Over_60,-1,-1;MedianAge "Median Age" true true false 8000 Text 0 0,First,#,Orig_Make_Copy,Orig_Make_Copy.MedianAge,0,7999;One_Race "One Race" true true false 4 Long 0 0,First,#,Orig_Make_Copy,Orig_Make_Copy.One_Race,-1,-1;TwoMoreRaces "Two or More Races" true true false 4 Long 0 0,First,#,Orig_Make_Copy,Orig_Make_Copy.TwoMoreRaces,-1,-1;White "White" true true false 4 Long 0 0,First,#,Orig_Make_Copy,Orig_Make_Copy.White,-1,-1;Black "Black of African American" true true false 4 Long 0 0,First,#,Orig_Make_Copy,Orig_Make_Copy.Black,-1,-1;Amer_Indian "American Indian and Alaska Native" true true false 4 Long 0 0,First,#,Orig_Make_Copy,Orig_Make_Copy.Amer_Indian,-1,-1;Asian "Asian" true true false 4 Long 0 0,First,#,Orig_Make_Copy,Orig_Make_Copy.Asian,-1,-1;Hawaiian "Native Hawaiian and Other Pacific Islander" true true false 4 Long 0 0,First,#,Orig_Make_Copy,Orig_Make_Copy.Hawaiian,-1,-1;OtherRace "Other Race" true true false 4 Long 0 0,First,#,Orig_Make_Copy,Orig_Make_Copy.OtherRace,-1,-1;Hispanic "Hispanic or Latino" true true false 4 Long 0 0,First,#,Orig_Make_Copy,Orig_Make_Copy.Hispanic,-1,-1;NotHispanic "Not Hispanic or Latino" true true false 4 Long 0 0,First,#,Orig_Make_Copy,Orig_Make_Copy.NotHispanic,-1,-1;HousingUnits "Housing Units" true true false 4 Long 0 0,First,#,Orig_Make_Copy,Orig_Make_Copy.HousingUnits,-1,-1;S2201_C01_001E "S2201_C01_001E" true true false 4 Long 0 0,First,#,Orig_Make_Copy,Orig_Make_Copy.S2201_C01_001E,-1,-1;S2201_C01_002E "S2201_C01_002E" true true false 4 Long 0 0,First,#,Orig_Make_Copy,Orig_Make_Copy.S2201_C01_002E,-1,-1;S2201_C01_009E "S2201_C01_009E" true true false 4 Long 0 0,First,#,Orig_Make_Copy,Orig_Make_Copy.S2201_C01_009E,-1,-1;S2201_C01_021E "S2201_C01_021E" true true false 4 Long 0 0,First,#,Orig_Make_Copy,Orig_Make_Copy.S2201_C01_021E,-1,-1;S2201_C01_023E "S2201_C01_023E" true true false 4 Long 0 0,First,#,Orig_Make_Copy,Orig_Make_Copy.S2201_C01_023E,-1,-1;S2201_C01_034E "S2201_C01_034E" true true false 4 Long 0 0,First,#,Orig_Make_Copy,Orig_Make_Copy.S2201_C01_034E,-1,-1;S2201_C02_002E "S2201_C02_002E" true true false 8 Double 0 0,First,#,Orig_Make_Copy,Orig_Make_Copy.S2201_C02_002E,-1,-1;S2201_C02_009E "S2201_C02_009E" true true false 8 Double 0 0,First,#,Orig_Make_Copy,Orig_Make_Copy.S2201_C02_009E,-1,-1;S2201_C02_021E "S2201_C02_021E" true true false 8 Double 0 0,First,#,Orig_Make_Copy,Orig_Make_Copy.S2201_C02_021E,-1,-1;S2201_C02_023E "S2201_C02_023E" true true false 8 Double 0 0,First,#,Orig_Make_Copy,Orig_Make_Copy.S2201_C02_023E,-1,-1;S2201_C03_001E "S2201_C03_001E" true true false 4 Long 0 0,First,#,Orig_Make_Copy,Orig_Make_Copy.S2201_C03_001E,-1,-1;S2201_C03_002E "S2201_C03_002E" true true false 4 Long 0 0,First,#,Orig_Make_Copy,Orig_Make_Copy.S2201_C03_002E,-1,-1;S2201_C03_009E "S2201_C03_009E" true true false 4 Long 0 0,First,#,Orig_Make_Copy,Orig_Make_Copy.S2201_C03_009E,-1,-1;S2201_C03_021E "S2201_C03_021E" true true false 4 Long 0 0,First,#,Orig_Make_Copy,Orig_Make_Copy.S2201_C03_021E,-1,-1;S2201_C03_023E "S2201_C03_023E" true true false 4 Long 0 0,First,#,Orig_Make_Copy,Orig_Make_Copy.S2201_C03_023E,-1,-1;S2201_C03_034E "S2201_C03_034E" true true false 4 Long 0 0,First,#,Orig_Make_Copy,Orig_Make_Copy.S2201_C03_034E,-1,-1;S2201_C04_002E "S2201_C04_002E" true true false 8 Double 0 0,First,#,Orig_Make_Copy,Orig_Make_Copy.S2201_C04_002E,-1,-1;S2201_C04_009E "S2201_C04_009E" true true false 8 Double 0 0,First,#,Orig_Make_Copy,Orig_Make_Copy.S2201_C04_009E,-1,-1;S2201_C04_021E "S2201_C04_021E" true true false 8 Double 0 0,First,#,Orig_Make_Copy,Orig_Make_Copy.S2201_C04_021E,-1,-1;S2201_C04_023E "S2201_C04_023E" true true false 4 Long 0 0,First,#,Orig_Make_Copy,Orig_Make_Copy.S2201_C04_023E,-1,-1;Shape_Length "Shape_Length" false true true 8 Double 0 0,First,#,Orig_Make_Copy,Orig_Make_Copy.Shape_Length,-1,-1;Shape_Area "Shape_Area" false true true 8 Double 0 0,First,#,Orig_Make_Copy,Orig_Make_Copy.Shape_Area,-1,-1;JoinID_2 "JoinID_2" true true false 8 Double 0 0,First,#,Orig_Make_Copy,Orig_Make_Copy.JoinID_2,-1,-1;CensusTract2 "CensusTract2" true true false 8 Double 0 0,First,#,Orig_Make_Copy,Orig_Make_Copy.CensusTract2,-1,-1;S2201_C03_034E_TEXT "S2201_C03_034E_TEXT" true true false 255 Text 0 0,First,#,Orig_Make_Copy,Orig_Make_Copy.S2201_C03_034E_TEXT,0,254;Tract "Tract" true true false 8 BigInteger 0 0,First,#,Orig_Make_Copy,Demographic_Contextual_Variables.csv.Tract,-1,-1;S1602_C02_002E "S1602_C02_002E" true true false 8 Double 0 0,First,#,Orig_Make_Copy,Demographic_Contextual_Variables.csv.S1602_C02_002E,-1,-1;S1602_C02_003E "S1602_C02_003E" true true false 8 Double 0 0,First,#,Orig_Make_Copy,Demographic_Contextual_Variables.csv.S1602_C02_003E,-1,-1;S1602_C02_004E "S1602_C02_004E" true true false 8 Double 0 0,First,#,Orig_Make_Copy,Demographic_Contextual_Variables.csv.S1602_C02_004E,-1,-1;S1602_C02_005E "S1602_C02_005E" true true false 8 Double 0 0,First,#,Orig_Make_Copy,Demographic_Contextual_Variables.csv.S1602_C02_005E,-1,-1;B28002_002E "B28002_002E" true true false 4 Long 0 0,First,#,Orig_Make_Copy,Demographic_Contextual_Variables.csv.B28002_002E,-1,-1;B28002_006E "B28002_006E" true true false 4 Long 0 0,First,#,Orig_Make_Copy,Demographic_Contextual_Variables.csv.B28002_006E,-1,-1;B28004_002E "B28004_002E" true true false 4 Long 0 0,First,#,Orig_Make_Copy,Demographic_Contextual_Variables.csv.B28004_002E,-1,-1;B28004_006E "B28004_006E" true true false 4 Long 0 0,First,#,Orig_Make_Copy,Demographic_Contextual_Variables.csv.B28004_006E,-1,-1;B28004_010E "B28004_010E" true true false 4 Long 0 0,First,#,Orig_Make_Copy,Demographic_Contextual_Variables.csv.B28004_010E,-1,-1;B28004_014E "B28004_014E" true true false 4 Long 0 0,First,#,Orig_Make_Copy,Demographic_Contextual_Variables.csv.B28004_014E,-1,-1;B28004_018E "B28004_018E" true true false 4 Long 0 0,First,#,Orig_Make_Copy,Demographic_Contextual_Variables.csv.B28004_018E,-1,-1;B28004_022E "B28004_022E" true true false 4 Long 0 0,First,#,Orig_Make_Copy,Demographic_Contextual_Variables.csv.B28004_022E,-1,-1;S2101_C01_027E "S2101_C01_027E" true true false 4 Long 0 0,First,#,Orig_Make_Copy,Demographic_Contextual_Variables.csv.S2101_C01_027E,-1,-1;S2101_C01_028E "S2101_C01_028E" true true false 4 Long 0 0,First,#,Orig_Make_Copy,Demographic_Contextual_Variables.csv.S2101_C01_028E,-1,-1;S2101_C01_029E "S2101_C01_029E" true true false 4 Long 0 0,First,#,Orig_Make_Copy,Demographic_Contextual_Variables.csv.S2101_C01_029E,-1,-1;S2101_C01_030E "S2101_C01_030E" true true false 4 Long 0 0,First,#,Orig_Make_Copy,Demographic_Contextual_Variables.csv.S2101_C01_030E,-1,-1" # DeleteField Demographic_Contextual_Variables S2201_C01_001E;S2201_C01_002E;S2201_C01_009E;S2201_C01_021E;S2201_C01_023E;S2201_C01_034E;S2201_C02_002E;S2201_C02_009E;S2201_C02_021E;S2201_C02_023E;S2201_C03_001E;S2201_C03_002E;S2201_C03_009E;S2201_C03_021E;S2201_C03_023E;S2201_C03_034E;S2201_C04_002E;S2201_C04_009E;S2201_C04_021E;S2201_C04_023E;S2201_C03_034E_TEXT "Delete Fields" DeleteField Demographic_Contextual_Variables S2201_C03_034E_TEXT;S2201_C04_023E;S2201_C04_021E;S2201_C04_009E;S2201_C04_002E;S2201_C03_034E;S2201_C03_023E;S2201_C03_021E;S2201_C03_009E;S2201_C03_002E;S2201_C03_001E;S2201_C02_023E;S2201_C02_021E;S2201_C02_009E;S2201_C02_002E;S2201_C01_034E;S2201_C01_023E;S2201_C01_021E;S2201_C01_009E;S2201_C01_002E;S2201_C01_001E;MTFCC;FUNCSTAT;ALAND;AWATER;INTPTLAT;INTPTLON "Delete Fields" UpdateSchema "CIMDATA=<CIMFeatureDatasetDataConnection xsi:type='typens:CIMFeatureDatasetDataConnection' xmlns:xsi='http://www.w3.org/2001/XMLSchema-instance' xmlns:xs='http://www.w3.org/2001/XMLSchema' xmlns:typens='http://www.esri.com/schemas/ArcGIS/3.3.0'><FeatureDataset>NAD_1983_2011_Michigan_GeoRef_Meters</FeatureDataset><WorkspaceConnectionString>DATABASE=E:\Nyaa_NSPEARS_Application\2_Data_Layers_Uploaded_to_Data_Repository\DemographicContextualVariables.gdb</WorkspaceConnectionString><WorkspaceFactory>FileGDB</WorkspaceFactory><Dataset>Demographic_Contextual_Variables</Dataset><DatasetType>esriDTFeatureClass</DatasetType></CIMFeatureDatasetDataConnection>" <operationSequence><workflow><AddField><field_name>S1602_C02_002E_TEXT</field_name><field_type>TEXT</field_type><field_length>255</field_length><field_is_nullable>True</field_is_nullable><field_is_required>False</field_is_required></AddField></workflow><workflow><AddField><field_name>S1602_C02_003E_TEXT</field_name><field_type>TEXT</field_type><field_length>255</field_length><field_is_nullable>True</field_is_nullable><field_is_required>False</field_is_required></AddField></workflow><workflow><AddField><field_name>S1602_C02_004E_TEXT</field_name><field_type>TEXT</field_type><field_length>255</field_length><field_is_nullable>True</field_is_nullable><field_is_required>False</field_is_required></AddField></workflow><workflow><AddField><field_name>S1602_C02_005E_TEXT</field_name><field_type>TEXT</field_type><field_length>255</field_length><field_is_nullable>True</field_is_nullable><field_is_required>False</field_is_required></AddField></workflow></operationSequence> CalculateField Demographic_Contextual_Variables S1602_C02_002E_TEXT !S1602_C02_002E! Python # Text NO_ENFORCE_DOMAINS CalculateField Demographic_Contextual_Variables S1602_C02_002E_TEXT "!S1602_C02_002E_TEXT! + "%"" Python # Text NO_ENFORCE_DOMAINS CalculateField Demographic_Contextual_Variables S1602_C02_003E_TEXT !S1602_C02_003E! Python # Text NO_ENFORCE_DOMAINS CalculateField Demographic_Contextual_Variables S1602_C02_003E_TEXT "!S1602_C02_003E_TEXT! + "%"" Python # Text NO_ENFORCE_DOMAINS CalculateField Demographic_Contextual_Variables S1602_C02_004E_TEXT !S1602_C02_004E! Python # Text NO_ENFORCE_DOMAINS CalculateField Demographic_Contextual_Variables S1602_C02_004E_TEXT "!S1602_C02_004E_TEXT! + "%"" Python # Text NO_ENFORCE_DOMAINS CalculateField Demographic_Contextual_Variables S1602_C02_005E_TEXT !S1602_C02_005E! Python # Text NO_ENFORCE_DOMAINS CalculateField Demographic_Contextual_Variables S1602_C02_005E_TEXT "!S1602_C02_005E_TEXT! + "%"" Python # Text NO_ENFORCE_DOMAINS ExportFeatures Demographic_Contextual_Variables E:\Nyaa_NSPEARS_Application\2_Data_Layers_Uploaded_to_Data_Repository\DemographicContextualVariables.gdb\NAD_1983_2011_Michigan_GeoRef_Meters\Demographic_Contextual_Variables_All # NOT_USE_ALIAS "STATEFP "STATEFP" true true false 2 Text 0 0,First,#,Demographic_Contextual_Variables,Demographic_Contextual_Variables.STATEFP,0,1;COUNTYFP "COUNTYFP" true true false 3 Text 0 0,First,#,Demographic_Contextual_Variables,Demographic_Contextual_Variables.COUNTYFP,0,2;TRACTCE "TRACTCE" true true false 6 Text 0 0,First,#,Demographic_Contextual_Variables,Demographic_Contextual_Variables.TRACTCE,0,5;GEOID "GEOID" true true false 11 Text 0 0,First,#,Demographic_Contextual_Variables,Demographic_Contextual_Variables.GEOID,0,10;NAME "NAME" true true false 7 Text 0 0,First,#,Demographic_Contextual_Variables,Demographic_Contextual_Variables.NAME,0,6;NAMELSAD "NAMELSAD" true true false 20 Text 0 0,First,#,Demographic_Contextual_Variables,Demographic_Contextual_Variables.NAMELSAD,0,19;GEOID_Num "GEOID_Num" true true false 8 Double 0 0,First,#,Demographic_Contextual_Variables,Demographic_Contextual_Variables.GEOID_Num,-1,-1;Label "Label" true true false 8000 Text 0 0,First,#,Demographic_Contextual_Variables,Demographic_Contextual_Variables.Label,0,7999;Dataset "Dataset" true true false 8000 Text 0 0,First,#,Demographic_Contextual_Variables,Demographic_Contextual_Variables.Dataset,0,7999;Population "Population" true true false 4 Long 0 0,First,#,Demographic_Contextual_Variables,Demographic_Contextual_Variables.Population,-1,-1;Male "Male" true true false 4 Long 0 0,First,#,Demographic_Contextual_Variables,Demographic_Contextual_Variables.Male,-1,-1;Female "Female" true true false 4 Long 0 0,First,#,Demographic_Contextual_Variables,Demographic_Contextual_Variables.Female,-1,-1;Under_18 "Under 18" true true false 4 Long 0 0,First,#,Demographic_Contextual_Variables,Demographic_Contextual_Variables.Under_18,-1,-1;Over_60 "Over 60" true true false 4 Long 0 0,First,#,Demographic_Contextual_Variables,Demographic_Contextual_Variables.Over_60,-1,-1;MedianAge "Median Age" true true false 8000 Text 0 0,First,#,Demographic_Contextual_Variables,Demographic_Contextual_Variables.MedianAge,0,7999;One_Race "One Race" true true false 4 Long 0 0,First,#,Demographic_Contextual_Variables,Demographic_Contextual_Variables.One_Race,-1,-1;TwoMoreRaces "Two or More Races" true true false 4 Long 0 0,First,#,Demographic_Contextual_Variables,Demographic_Contextual_Variables.TwoMoreRaces,-1,-1;White "White" true true false 4 Long 0 0,First,#,Demographic_Contextual_Variables,Demographic_Contextual_Variables.White,-1,-1;Black "Black of African American" true true false 4 Long 0 0,First,#,Demographic_Contextual_Variables,Demographic_Contextual_Variables.Black,-1,-1;Amer_Indian "American Indian and Alaska Native" true true false 4 Long 0 0,First,#,Demographic_Contextual_Variables,Demographic_Contextual_Variables.Amer_Indian,-1,-1;Asian "Asian" true true false 4 Long 0 0,First,#,Demographic_Contextual_Variables,Demographic_Contextual_Variables.Asian,-1,-1;Hawaiian "Native Hawaiian and Other Pacific Islander" true true false 4 Long 0 0,First,#,Demographic_Contextual_Variables,Demographic_Contextual_Variables.Hawaiian,-1,-1;OtherRace "Other Race" true true false 4 Long 0 0,First,#,Demographic_Contextual_Variables,Demographic_Contextual_Variables.OtherRace,-1,-1;Hispanic "Hispanic or Latino" true true false 4 Long 0 0,First,#,Demographic_Contextual_Variables,Demographic_Contextual_Variables.Hispanic,-1,-1;NotHispanic "Not Hispanic or Latino" true true false 4 Long 0 0,First,#,Demographic_Contextual_Variables,Demographic_Contextual_Variables.NotHispanic,-1,-1;HousingUnits "Housing Units" true true false 4 Long 0 0,First,#,Demographic_Contextual_Variables,Demographic_Contextual_Variables.HousingUnits,-1,-1;JoinID_2 "JoinID_2" true true false 8 Double 0 0,First,#,Demographic_Contextual_Variables,Demographic_Contextual_Variables.JoinID_2,-1,-1;CensusTract2 "CensusTract2" true true false 8 Double 0 0,First,#,Demographic_Contextual_Variables,Demographic_Contextual_Variables.CensusTract2,-1,-1;Tract "Tract" true true false 8 BigInteger 0 0,First,#,Demographic_Contextual_Variables,Demographic_Contextual_Variables.Tract,-1,-1;S1602_C02_002E "Percent of Spanish Speaking Households" true true false 8 Double 0 0,First,#,Demographic_Contextual_Variables,Demographic_Contextual_Variables.S1602_C02_002E,-1,-1;S1602_C02_002E_TEXT "Percent of Spanish Speaking Households_TEXT" true true false 255 Text 0 0,First,#,Demographic_Contextual_Variables,Demographic_Contextual_Variables.S1602_C02_002E_TEXT,0,254;S1602_C02_003E "Percent of Households who Speak a Different Indo/European Language" true true false 8 Double 0 0,First,#,Demographic_Contextual_Variables,Demographic_Contextual_Variables.S1602_C02_003E,-1,-1;S1602_C02_003E_TEXT "Percent of Households who Speak a Different Indo/European Language_TEXT" true true false 255 Text 0 0,First,#,Demographic_Contextual_Variables,Demographic_Contextual_Variables.S1602_C02_003E_TEXT,0,254;S1602_C02_004E "Percent of Households who Speak an AAPI Language" true true false 8 Double 0 0,First,#,Demographic_Contextual_Variables,Demographic_Contextual_Variables.S1602_C02_004E,-1,-1;S1602_C02_004E_TEXT "Percent of Households who Speak an AAPI Language_TEXT" true true false 255 Text 0 0,First,#,Demographic_Contextual_Variables,Demographic_Contextual_Variables.S1602_C02_004E_TEXT,0,254;S1602_C02_005E "Percent of Households who Speak a Different Language than Indicated in Other Language Options" true true false 8 Double 0 0,First,#,Demographic_Contextual_Variables,Demographic_Contextual_Variables.S1602_C02_005E,-1,-1;S1602_C02_005E_TEXT "Percent of Households who Speak a Different Language than Indicated in Other Language Options_TEXT" true true false 255 Text 0 0,First,#,Demographic_Contextual_Variables,Demographic_Contextual_Variables.S1602_C02_005E_TEXT,0,254;B28002_002E "Number of Households who have Internet Access" true true false 4 Long 0 0,First,#,Demographic_Contextual_Variables,Demographic_Contextual_Variables.B28002_002E,-1,-1;B28002_006E "Number of Households who Only have Internet Access Through Cellular Data" true true false 4 Long 0 0,First,#,Demographic_Contextual_Variables,Demographic_Contextual_Variables.B28002_006E,-1,-1;B28004_002E "Number of Households who Earn Less than $10,000 per Year" true true false 4 Long 0 0,First,#,Demographic_Contextual_Variables,Demographic_Contextual_Variables.B28004_002E,-1,-1;B28004_006E "Number of Households who Earn between $10,000 and $19,999 Annually " true true false 4 Long 0 0,First,#,Demographic_Contextual_Variables,Demographic_Contextual_Variables.B28004_006E,-1,-1;B28004_010E "Number of Households who Earn between $20,000 and $34,999 Annually " true true false 4 Long 0 0,First,#,Demographic_Contextual_Variables,Demographic_Contextual_Variables.B28004_010E,-1,-1;B28004_014E "Number of Households who Earn between $35,000 and $49,999 Annually " true true false 4 Long 0 0,First,#,Demographic_Contextual_Variables,Demographic_Contextual_Variables.B28004_014E,-1,-1;B28004_018E "Number of Households who Earn between $50,000 and $74,999 Annually " true true false 4 Long 0 0,First,#,Demographic_Contextual_Variables,Demographic_Contextual_Variables.B28004_018E,-1,-1;B28004_022E "Number of Households who Earn $75,000 or More Annually " true true false 4 Long 0 0,First,#,Demographic_Contextual_Variables,Demographic_Contextual_Variables.B28004_022E,-1,-1;S2101_C01_027E "Number of Individuals over the Age of 25 who have Less than a High School Degree" true true false 4 Long 0 0,First,#,Demographic_Contextual_Variables,Demographic_Contextual_Variables.S2101_C01_027E,-1,-1;S2101_C01_028E "Number of Individuals over the Age of 25 with a High School Diploma or GED" true true false 4 Long 0 0,First,#,Demographic_Contextual_Variables,Demographic_Contextual_Variables.S2101_C01_028E,-1,-1;S2101_C01_029E "Number of Individuals over the Age of 25 who have an Associates Degree or have spend some time Enrolled in College" true true false 4 Long 0 0,First,#,Demographic_Contextual_Variables,Demographic_Contextual_Variables.S2101_C01_029E,-1,-1;S2101_C01_030E "Number of Individuals over the Age of 25 with a Bachelor's Degree of Higher" true true false 4 Long 0 0,First,#,Demographic_Contextual_Variables,Demographic_Contextual_Variables.S2101_C01_030E,-1,-1;Shape_Length "Shape_Length" false true true 8 Double 0 0,First,#,Demographic_Contextual_Variables,Demographic_Contextual_Variables.Shape_Length,-1,-1;Shape_Area "Shape_Area" false true true 8 Double 0 0,First,#,Demographic_Contextual_Variables,Demographic_Contextual_Variables.Shape_Area,-1,-1;Tract "Tract" true true false 8 BigInteger 0 0,First,#,Demographic_Contextual_Variables,General_ACS_Stats_to_Join.csv.Tract,-1,-1;S2201_C01_001E "S2201_C01_001E" true true false 4 Long 0 0,First,#,Demographic_Contextual_Variables,General_ACS_Stats_to_Join.csv.S2201_C01_001E,-1,-1;S2201_C01_021E "S2201_C01_021E" true true false 4 Long 0 0,First,#,Demographic_Contextual_Variables,General_ACS_Stats_to_Join.csv.S2201_C01_021E,-1,-1;S2201_C02_021E "S2201_C02_021E" true true false 8 Double 0 0,First,#,Demographic_Contextual_Variables,General_ACS_Stats_to_Join.csv.S2201_C02_021E,-1,-1;S2201_C03_001E "S2201_C03_001E" true true false 4 Long 0 0,First,#,Demographic_Contextual_Variables,General_ACS_Stats_to_Join.csv.S2201_C03_001E,-1,-1;S2201_C03_021E "S2201_C03_021E" true true false 4 Long 0 0,First,#,Demographic_Contextual_Variables,General_ACS_Stats_to_Join.csv.S2201_C03_021E,-1,-1;S2201_C03_034E "S2201_C03_034E" true true false 4 Long 0 0,First,#,Demographic_Contextual_Variables,General_ACS_Stats_to_Join.csv.S2201_C03_034E,-1,-1;S2201_C03_034E_TEXT "S2201_C03_034E_TEXT" true true false 8000 Text 0 0,First,#,Demographic_Contextual_Variables,General_ACS_Stats_to_Join.csv.S2201_C03_034E_TEXT,0,7999;S2201_C04_021E "S2201_C04_021E" true true false 8 Double 0 0,First,#,Demographic_Contextual_Variables,General_ACS_Stats_to_Join.csv.S2201_C04_021E,-1,-1;S1602_C01_002E "S1602_C01_002E" true true false 4 Long 0 0,First,#,Demographic_Contextual_Variables,General_ACS_Stats_to_Join.csv.S1602_C01_002E,-1,-1;S1602_C01_003E "S1602_C01_003E" true true false 4 Long 0 0,First,#,Demographic_Contextual_Variables,General_ACS_Stats_to_Join.csv.S1602_C01_003E,-1,-1;S1602_C01_004E "S1602_C01_004E" true true false 4 Long 0 0,First,#,Demographic_Contextual_Variables,General_ACS_Stats_to_Join.csv.S1602_C01_004E,-1,-1;S1602_C01_005E "S1602_C01_005E" true true false 4 Long 0 0,First,#,Demographic_Contextual_Variables,General_ACS_Stats_to_Join.csv.S1602_C01_005E,-1,-1" # UpdateSchema "CIMDATA=<CIMFeatureDatasetDataConnection xsi:type='typens:CIMFeatureDatasetDataConnection' xmlns:xsi='http://www.w3.org/2001/XMLSchema-instance' xmlns:xs='http://www.w3.org/2001/XMLSchema' xmlns:typens='http://www.esri.com/schemas/ArcGIS/3.3.0'><FeatureDataset>NAD_1983_2011_Michigan_GeoRef_Meters</FeatureDataset><WorkspaceConnectionString>DATABASE=E:\Nyaa_NSPEARS_Application\2_Data_Layers_Uploaded_to_Data_Repository\DemographicContextualVariables.gdb</WorkspaceConnectionString><WorkspaceFactory>FileGDB</WorkspaceFactory><Dataset>Demographic_Contextual_Variables_All</Dataset><DatasetType>esriDTFeatureClass</DatasetType></CIMFeatureDatasetDataConnection>" <operationSequence><workflow><DeleteField><field_name>Tract_1</field_name></DeleteField></workflow><workflow><AddField><field_name>S2201_C02_021E_TEXT</field_name><field_type>TEXT</field_type><field_length>255</field_length><field_is_nullable>True</field_is_nullable><field_is_required>False</field_is_required></AddField></workflow><workflow><AddField><field_name>S2201_C04_021E_TEXT</field_name><field_type>TEXT</field_type><field_length>255</field_length><field_is_nullable>True</field_is_nullable><field_is_required>False</field_is_required></AddField></workflow></operationSequence> ExportFeatures Demographic_Contextual_Variables_All E:\Nyaa_NSPEARS_Application\2_Data_Layers_Uploaded_to_Data_Repository\Baseline_Indicators.gdb\NAD_1983_2011_Michigan_GeoRef_Meters\CensusTracts_before_data_Join # NOT_USE_ALIAS "STATEFP "STATEFP" true true false 2 Text 0 0,First,#,Demographic_Contextual_Variables_All,STATEFP,0,1;COUNTYFP "COUNTYFP" true true false 3 Text 0 0,First,#,Demographic_Contextual_Variables_All,COUNTYFP,0,2;TRACTCE "TRACTCE" true true false 6 Text 0 0,First,#,Demographic_Contextual_Variables_All,TRACTCE,0,5;GEOID "GEOID" true true false 11 Text 0 0,First,#,Demographic_Contextual_Variables_All,GEOID,0,10;NAME "NAME" true true false 7 Text 0 0,First,#,Demographic_Contextual_Variables_All,NAME,0,6;NAMELSAD "NAMELSAD" true true false 20 Text 0 0,First,#,Demographic_Contextual_Variables_All,NAMELSAD,0,19;GEOID_Num "GEOID_Num" true true false 8 Double 0 0,First,#,Demographic_Contextual_Variables_All,GEOID_Num,-1,-1;Label "Label" true true false 8000 Text 0 0,First,#,Demographic_Contextual_Variables_All,Label,0,7999;Dataset "Dataset" true true false 8000 Text 0 0,First,#,Demographic_Contextual_Variables_All,Dataset,0,7999;Population "Population" true true false 4 Long 0 0,First,#,Demographic_Contextual_Variables_All,Population,-1,-1;Male "Male" true true false 4 Long 0 0,First,#,Demographic_Contextual_Variables_All,Male,-1,-1;Female "Female" true true false 4 Long 0 0,First,#,Demographic_Contextual_Variables_All,Female,-1,-1;Under_18 "Under 18" true true false 4 Long 0 0,First,#,Demographic_Contextual_Variables_All,Under_18,-1,-1;Over_60 "Over 60" true true false 4 Long 0 0,First,#,Demographic_Contextual_Variables_All,Over_60,-1,-1;MedianAge "Median Age" true true false 8000 Text 0 0,First,#,Demographic_Contextual_Variables_All,MedianAge,0,7999;One_Race "One Race" true true false 4 Long 0 0,First,#,Demographic_Contextual_Variables_All,One_Race,-1,-1;TwoMoreRaces "Two or More Races" true true false 4 Long 0 0,First,#,Demographic_Contextual_Variables_All,TwoMoreRaces,-1,-1;White "White" true true false 4 Long 0 0,First,#,Demographic_Contextual_Variables_All,White,-1,-1;Black "Black of African American" true true false 4 Long 0 0,First,#,Demographic_Contextual_Variables_All,Black,-1,-1;Amer_Indian "American Indian and Alaska Native" true true false 4 Long 0 0,First,#,Demographic_Contextual_Variables_All,Amer_Indian,-1,-1;Asian "Asian" true true false 4 Long 0 0,First,#,Demographic_Contextual_Variables_All,Asian,-1,-1;Hawaiian "Native Hawaiian and Other Pacific Islander" true true false 4 Long 0 0,First,#,Demographic_Contextual_Variables_All,Hawaiian,-1,-1;OtherRace "Other Race" true true false 4 Long 0 0,First,#,Demographic_Contextual_Variables_All,OtherRace,-1,-1;Hispanic "Hispanic or Latino" true true false 4 Long 0 0,First,#,Demographic_Contextual_Variables_All,Hispanic,-1,-1;NotHispanic "Not Hispanic or Latino" true true false 4 Long 0 0,First,#,Demographic_Contextual_Variables_All,NotHispanic,-1,-1;HousingUnits "Housing Units" true true false 4 Long 0 0,First,#,Demographic_Contextual_Variables_All,HousingUnits,-1,-1;JoinID_2 "JoinID_2" true true false 8 Double 0 0,First,#,Demographic_Contextual_Variables_All,JoinID_2,-1,-1;CensusTract2 "CensusTract2" true true false 8 Double 0 0,First,#,Demographic_Contextual_Variables_All,CensusTract2,-1,-1;Tract "Tract" true true false 8 BigInteger 0 0,First,#,Demographic_Contextual_Variables_All,Tract,-1,-1;S1602_C02_002E "Percent of Spanish Speaking Households" true true false 8 Double 0 0,First,#,Demographic_Contextual_Variables_All,S1602_C02_002E,-1,-1;S1602_C02_002E_TEXT "Percent of Spanish Speaking Households_TEXT" true true false 255 Text 0 0,First,#,Demographic_Contextual_Variables_All,S1602_C02_002E_TEXT,0,254;S1602_C02_003E "Percent of Households who Speak a Different Indo/European Language" true true false 8 Double 0 0,First,#,Demographic_Contextual_Variables_All,S1602_C02_003E,-1,-1;S1602_C02_003E_TEXT "Percent of Households who Speak a Different Indo/European Language_TEXT" true true false 255 Text 0 0,First,#,Demographic_Contextual_Variables_All,S1602_C02_003E_TEXT,0,254;S1602_C02_004E "Percent of Households who Speak an AAPI Language" true true false 8 Double 0 0,First,#,Demographic_Contextual_Variables_All,S1602_C02_004E,-1,-1;S1602_C02_004E_TEXT "Percent of Households who Speak an AAPI Language_TEXT" true true false 255 Text 0 0,First,#,Demographic_Contextual_Variables_All,S1602_C02_004E_TEXT,0,254;S1602_C02_005E "Percent of Households who Speak a Different Language than Indicated in Other Language Options" true true false 8 Double 0 0,First,#,Demographic_Contextual_Variables_All,S1602_C02_005E,-1,-1;S1602_C02_005E_TEXT "Percent of Households who Speak a Different Language than Indicated in Other Language Options_TEXT" true true false 255 Text 0 0,First,#,Demographic_Contextual_Variables_All,S1602_C02_005E_TEXT,0,254;B28002_002E "Number of Households who have Internet Access" true true false 4 Long 0 0,First,#,Demographic_Contextual_Variables_All,B28002_002E,-1,-1;B28002_006E "Number of Households who Only have Internet Access Through Cellular Data" true true false 4 Long 0 0,First,#,Demographic_Contextual_Variables_All,B28002_006E,-1,-1;B28004_002E "Number of Households who Earn Less than $10,000 per Year" true true false 4 Long 0 0,First,#,Demographic_Contextual_Variables_All,B28004_002E,-1,-1;B28004_006E "Number of Households who Earn between $10,000 and $19,999 Annually " true true false 4 Long 0 0,First,#,Demographic_Contextual_Variables_All,B28004_006E,-1,-1;B28004_010E "Number of Households who Earn between $20,000 and $34,999 Annually " true true false 4 Long 0 0,First,#,Demographic_Contextual_Variables_All,B28004_010E,-1,-1;B28004_014E "Number of Households who Earn between $35,000 and $49,999 Annually " true true false 4 Long 0 0,First,#,Demographic_Contextual_Variables_All,B28004_014E,-1,-1;B28004_018E "Number of Households who Earn between $50,000 and $74,999 Annually " true true false 4 Long 0 0,First,#,Demographic_Contextual_Variables_All,B28004_018E,-1,-1;B28004_022E "Number of Households who Earn $75,000 or More Annually " true true false 4 Long 0 0,First,#,Demographic_Contextual_Variables_All,B28004_022E,-1,-1;S2101_C01_027E "Number of Individuals over the Age of 25 who have Less than a High School Degree" true true false 4 Long 0 0,First,#,Demographic_Contextual_Variables_All,S2101_C01_027E,-1,-1;S2101_C01_028E "Number of Individuals over the Age of 25 with a High School Diploma or GED" true true false 4 Long 0 0,First,#,Demographic_Contextual_Variables_All,S2101_C01_028E,-1,-1;S2101_C01_029E "Number of Individuals over the Age of 25 who have an Associates Degree or have spend some time Enrolled in College" true true false 4 Long 0 0,First,#,Demographic_Contextual_Variables_All,S2101_C01_029E,-1,-1;S2101_C01_030E "Number of Individuals over the Age of 25 with a Bachelor's Degree of Higher" true true false 4 Long 0 0,First,#,Demographic_Contextual_Variables_All,S2101_C01_030E,-1,-1;S2201_C01_001E "S2201_C01_001E" true true false 4 Long 0 0,First,#,Demographic_Contextual_Variables_All,S2201_C01_001E,-1,-1;S2201_C01_021E "S2201_C01_021E" true true false 4 Long 0 0,First,#,Demographic_Contextual_Variables_All,S2201_C01_021E,-1,-1;S2201_C02_021E "S2201_C02_021E" true true false 8 Double 0 0,First,#,Demographic_Contextual_Variables_All,S2201_C02_021E,-1,-1;S2201_C03_001E "S2201_C03_001E" true true false 4 Long 0 0,First,#,Demographic_Contextual_Variables_All,S2201_C03_001E,-1,-1;S2201_C03_021E "S2201_C03_021E" true true false 4 Long 0 0,First,#,Demographic_Contextual_Variables_All,S2201_C03_021E,-1,-1;S2201_C03_034E "S2201_C03_034E" true true false 4 Long 0 0,First,#,Demographic_Contextual_Variables_All,S2201_C03_034E,-1,-1;S2201_C03_034E_TEXT "S2201_C03_034E_TEXT" true true false 8000 Text 0 0,First,#,Demographic_Contextual_Variables_All,S2201_C03_034E_TEXT,0,7999;S2201_C04_021E "S2201_C04_021E" true true false 8 Double 0 0,First,#,Demographic_Contextual_Variables_All,S2201_C04_021E,-1,-1;S1602_C01_002E "S1602_C01_002E" true true false 4 Long 0 0,First,#,Demographic_Contextual_Variables_All,S1602_C01_002E,-1,-1;S1602_C01_003E "S1602_C01_003E" true true false 4 Long 0 0,First,#,Demographic_Contextual_Variables_All,S1602_C01_003E,-1,-1;S1602_C01_004E "S1602_C01_004E" true true false 4 Long 0 0,First,#,Demographic_Contextual_Variables_All,S1602_C01_004E,-1,-1;S1602_C01_005E "S1602_C01_005E" true true false 4 Long 0 0,First,#,Demographic_Contextual_Variables_All,S1602_C01_005E,-1,-1;Shape_Length "Shape_Length" false true true 8 Double 0 0,First,#,Demographic_Contextual_Variables_All,Shape_Length,-1,-1;Shape_Area "Shape_Area" false true true 8 Double 0 0,First,#,Demographic_Contextual_Variables_All,Shape_Area,-1,-1;S2201_C02_021E_TEXT "S2201_C02_021E_TEXT" true true false 255 Text 0 0,First,#,Demographic_Contextual_Variables_All,S2201_C02_021E_TEXT,0,254;S2201_C04_021E_TEXT "S2201_C04_021E_TEXT" true true false 255 Text 0 0,First,#,Demographic_Contextual_Variables_All,S2201_C04_021E_TEXT,0,254" # DeleteField CensusTracts_before_data_Join JoinID_2;CensusTract2;Tract;S1602_C02_002E;S1602_C02_002E_TEXT;S1602_C02_003E;S1602_C02_003E_TEXT;S1602_C02_004E;S1602_C02_004E_TEXT;S1602_C02_005E;S1602_C02_005E_TEXT;B28002_002E;B28002_006E;S2101_C01_027E;S2101_C01_028E;S2101_C01_029E;S2101_C01_030E "Delete Fields" UpdateSchema "CIMDATA=<CIMFeatureDatasetDataConnection xsi:type='typens:CIMFeatureDatasetDataConnection' xmlns:xsi='http://www.w3.org/2001/XMLSchema-instance' xmlns:xs='http://www.w3.org/2001/XMLSchema' xmlns:typens='http://www.esri.com/schemas/ArcGIS/3.3.0'><FeatureDataset>NAD_1983_2011_Michigan_GeoRef_Meters</FeatureDataset><WorkspaceConnectionString>DATABASE=E:\Nyaa_NSPEARS_Application\2_Data_Layers_Uploaded_to_Data_Repository\Baseline_Indicators.gdb</WorkspaceConnectionString><WorkspaceFactory>FileGDB</WorkspaceFactory><Dataset>CensusTracts_before_data_Join</Dataset><DatasetType>esriDTFeatureClass</DatasetType></CIMFeatureDatasetDataConnection>" <operationSequence><workflow><DeleteField><field_name>S2201_C03_021E</field_name><field_name>S2201_C04_021E</field_name><field_name>S1602_C01_002E</field_name><field_name>S1602_C01_003E</field_name><field_name>S1602_C01_004E</field_name><field_name>S1602_C01_005E</field_name><field_name>S2201_C04_021E_TEXT</field_name></DeleteField></workflow></operationSequence> ExportFeatures CensusTracts_before_data_Join E:\Nyaa_NSPEARS_Application\2_Data_Layers_Uploaded_to_Data_Repository\Baseline_Indicators.gdb\NAD_1983_2011_Michigan_GeoRef_Meters\CensusTracts_with_Baseline_Indicator_data # NOT_USE_ALIAS "STATEFP "STATEFP" true true false 2 Text 0 0,First,#,CensusTracts_before_data_Join,CensusTracts_before_data_Join.STATEFP,0,1;COUNTYFP "COUNTYFP" true true false 3 Text 0 0,First,#,CensusTracts_before_data_Join,CensusTracts_before_data_Join.COUNTYFP,0,2;TRACTCE "TRACTCE" true true false 6 Text 0 0,First,#,CensusTracts_before_data_Join,CensusTracts_before_data_Join.TRACTCE,0,5;GEOID "GEOID" true true false 11 Text 0 0,First,#,CensusTracts_before_data_Join,CensusTracts_before_data_Join.GEOID,0,10;NAME "NAME" true true false 7 Text 0 0,First,#,CensusTracts_before_data_Join,CensusTracts_before_data_Join.NAME,0,6;NAMELSAD "NAMELSAD" true true false 20 Text 0 0,First,#,CensusTracts_before_data_Join,CensusTracts_before_data_Join.NAMELSAD,0,19;GEOID_Num "GEOID_Num" true true false 8 Double 0 0,First,#,CensusTracts_before_data_Join,CensusTracts_before_data_Join.GEOID_Num,-1,-1;Label "Label" true true false 8000 Text 0 0,First,#,CensusTracts_before_data_Join,CensusTracts_before_data_Join.Label,0,7999;Dataset "Dataset" true true false 8000 Text 0 0,First,#,CensusTracts_before_data_Join,CensusTracts_before_data_Join.Dataset,0,7999;Population "Population" true true false 4 Long 0 0,First,#,CensusTracts_before_data_Join,CensusTracts_before_data_Join.Population,-1,-1;Male "Male" true true false 4 Long 0 0,First,#,CensusTracts_before_data_Join,CensusTracts_before_data_Join.Male,-1,-1;Female "Female" true true false 4 Long 0 0,First,#,CensusTracts_before_data_Join,CensusTracts_before_data_Join.Female,-1,-1;Under_18 "Under 18" true true false 4 Long 0 0,First,#,CensusTracts_before_data_Join,CensusTracts_before_data_Join.Under_18,-1,-1;Over_60 "Over 60" true true false 4 Long 0 0,First,#,CensusTracts_before_data_Join,CensusTracts_before_data_Join.Over_60,-1,-1;MedianAge "Median Age" true true false 8000 Text 0 0,First,#,CensusTracts_before_data_Join,CensusTracts_before_data_Join.MedianAge,0,7999;One_Race "One Race" true true false 4 Long 0 0,First,#,CensusTracts_before_data_Join,CensusTracts_before_data_Join.One_Race,-1,-1;TwoMoreRaces "Two or More Races" true true false 4 Long 0 0,First,#,CensusTracts_before_data_Join,CensusTracts_before_data_Join.TwoMoreRaces,-1,-1;White "White" true true false 4 Long 0 0,First,#,CensusTracts_before_data_Join,CensusTracts_before_data_Join.White,-1,-1;Black "Black of African American" true true false 4 Long 0 0,First,#,CensusTracts_before_data_Join,CensusTracts_before_data_Join.Black,-1,-1;Amer_Indian "American Indian and Alaska Native" true true false 4 Long 0 0,First,#,CensusTracts_before_data_Join,CensusTracts_before_data_Join.Amer_Indian,-1,-1;Asian "Asian" true true false 4 Long 0 0,First,#,CensusTracts_before_data_Join,CensusTracts_before_data_Join.Asian,-1,-1;Hawaiian "Native Hawaiian and Other Pacific Islander" true true false 4 Long 0 0,First,#,CensusTracts_before_data_Join,CensusTracts_before_data_Join.Hawaiian,-1,-1;OtherRace "Other Race" true true false 4 Long 0 0,First,#,CensusTracts_before_data_Join,CensusTracts_before_data_Join.OtherRace,-1,-1;Hispanic "Hispanic or Latino" true true false 4 Long 0 0,First,#,CensusTracts_before_data_Join,CensusTracts_before_data_Join.Hispanic,-1,-1;NotHispanic "Not Hispanic or Latino" true true false 4 Long 0 0,First,#,CensusTracts_before_data_Join,CensusTracts_before_data_Join.NotHispanic,-1,-1;HousingUnits "Housing Units" true true false 4 Long 0 0,First,#,CensusTracts_before_data_Join,CensusTracts_before_data_Join.HousingUnits,-1,-1;B28004_002E "Number of Households who Earn Less than $10,000 per Year" true true false 4 Long 0 0,First,#,CensusTracts_before_data_Join,CensusTracts_before_data_Join.B28004_002E,-1,-1;B28004_006E "Number of Households who Earn between $10,000 and $19,999 Annually " true true false 4 Long 0 0,First,#,CensusTracts_before_data_Join,CensusTracts_before_data_Join.B28004_006E,-1,-1;B28004_010E "Number of Households who Earn between $20,000 and $34,999 Annually " true true false 4 Long 0 0,First,#,CensusTracts_before_data_Join,CensusTracts_before_data_Join.B28004_010E,-1,-1;B28004_014E "Number of Households who Earn between $35,000 and $49,999 Annually " true true false 4 Long 0 0,First,#,CensusTracts_before_data_Join,CensusTracts_before_data_Join.B28004_014E,-1,-1;B28004_018E "Number of Households who Earn between $50,000 and $74,999 Annually " true true false 4 Long 0 0,First,#,CensusTracts_before_data_Join,CensusTracts_before_data_Join.B28004_018E,-1,-1;B28004_022E "Number of Households who Earn $75,000 or More Annually " true true false 4 Long 0 0,First,#,CensusTracts_before_data_Join,CensusTracts_before_data_Join.B28004_022E,-1,-1;S2201_C01_001E "Number of Households" true true false 4 Long 0 0,First,#,CensusTracts_before_data_Join,CensusTracts_before_data_Join.S2201_C01_001E,-1,-1;S2201_C01_021E "Number of Households below the Poverty Level within the last 12 months" true true false 4 Long 0 0,First,#,CensusTracts_before_data_Join,CensusTracts_before_data_Join.S2201_C01_021E,-1,-1;S2201_C02_021E "Percent of Households below the Poverty Level within the last 12 months" true true false 8 Double 0 0,First,#,CensusTracts_before_data_Join,CensusTracts_before_data_Join.S2201_C02_021E,-1,-1;S2201_C02_021E_TEXT "Percent of Households below the Poverty Level within the last 12 months_TEXT" true true false 255 Text 0 0,First,#,CensusTracts_before_data_Join,CensusTracts_before_data_Join.S2201_C02_021E_TEXT,0,254;S2201_C03_001E "Number of Households who receive SNAP benefits" true true false 4 Long 0 0,First,#,CensusTracts_before_data_Join,CensusTracts_before_data_Join.S2201_C03_001E,-1,-1;S2201_C03_034E "Median Household Income in the last 12 months for SNAP Households" true true false 4 Long 0 0,First,#,CensusTracts_before_data_Join,CensusTracts_before_data_Join.S2201_C03_034E,-1,-1;S2201_C03_034E_TEXT "Median Household Income in the last 12 months for SNAP Households_TEXT" true true false 8000 Text 0 0,First,#,CensusTracts_before_data_Join,CensusTracts_before_data_Join.S2201_C03_034E_TEXT,0,7999;Shape_Length "Shape_Length" false true true 8 Double 0 0,First,#,CensusTracts_before_data_Join,CensusTracts_before_data_Join.Shape_Length,-1,-1;Shape_Area "Shape_Area" false true true 8 Double 0 0,First,#,CensusTracts_before_data_Join,CensusTracts_before_data_Join.Shape_Area,-1,-1;Tract "Tract" true true false 8 BigInteger 0 0,First,#,CensusTracts_before_data_Join,Baseline_indicator_data_to_Join.csv.Tract,-1,-1;S2201_C01_023E "S2201_C01_023E" true true false 4 Long 0 0,First,#,CensusTracts_before_data_Join,Baseline_indicator_data_to_Join.csv.S2201_C01_023E,-1,-1;S2201_C01_034E "S2201_C01_034E" true true false 8000 Text 0 0,First,#,CensusTracts_before_data_Join,Baseline_indicator_data_to_Join.csv.S2201_C01_034E,0,7999;S2101_C01_007E "S2101_C01_007E" true true false 4 Long 0 0,First,#,CensusTracts_before_data_Join,Baseline_indicator_data_to_Join.csv.S2101_C01_007E,-1,-1;S2101_C01_008E "S2101_C01_008E" true true false 4 Long 0 0,First,#,CensusTracts_before_data_Join,Baseline_indicator_data_to_Join.csv.S2101_C01_008E,-1,-1" # UpdateSchema "CIMDATA=<CIMFeatureDatasetDataConnection xsi:type='typens:CIMFeatureDatasetDataConnection' xmlns:xsi='http://www.w3.org/2001/XMLSchema-instance' xmlns:xs='http://www.w3.org/2001/XMLSchema' xmlns:typens='http://www.esri.com/schemas/ArcGIS/3.3.0'><FeatureDataset>NAD_1983_2011_Michigan_GeoRef_Meters</FeatureDataset><WorkspaceConnectionString>DATABASE=E:\Nyaa_NSPEARS_Application\2_Data_Layers_Uploaded_to_Data_Repository\Baseline_Indicators.gdb</WorkspaceConnectionString><WorkspaceFactory>FileGDB</WorkspaceFactory><Dataset>CensusTracts_with_Baseline_Indicator_data</Dataset><DatasetType>esriDTFeatureClass</DatasetType></CIMFeatureDatasetDataConnection>" <operationSequence><workflow><AddField><field_name>S2201_C01_034E_TEXT</field_name><field_type>LONG</field_type><field_is_nullable>True</field_is_nullable><field_is_required>False</field_is_required></AddField></workflow></operationSequence> CalculateField "Total Population by Census Tract" S2201_C01_034E_TEXT "No Data" Python # Text NO_ENFORCE_DOMAINS CalculateField "Total Population by Census Tract" S2201_C01_034E_TEXT "No Data" Python # Text NO_ENFORCE_DOMAINS UpdateSchema "CIMDATA=<CIMFeatureDatasetDataConnection xsi:type='typens:CIMFeatureDatasetDataConnection' xmlns:xsi='http://www.w3.org/2001/XMLSchema-instance' xmlns:xs='http://www.w3.org/2001/XMLSchema' xmlns:typens='http://www.esri.com/schemas/ArcGIS/3.3.0'><FeatureDataset>NAD_1983_2011_Michigan_GeoRef_Meters</FeatureDataset><WorkspaceConnectionString>DATABASE=E:\Nyaa_NSPEARS_Application\2_Data_Layers_Uploaded_to_Data_Repository\Baseline_Indicators.gdb</WorkspaceConnectionString><WorkspaceFactory>FileGDB</WorkspaceFactory><Dataset>CensusTracts_with_Baseline_Indicator_data</Dataset><DatasetType>esriDTFeatureClass</DatasetType></CIMFeatureDatasetDataConnection>" <operationSequence><workflow><DeleteField><field_name>S2201_C01_034E_TEXT</field_name></DeleteField></workflow></operationSequence> UpdateSchema "CIMDATA=<CIMFeatureDatasetDataConnection xsi:type='typens:CIMFeatureDatasetDataConnection' xmlns:xsi='http://www.w3.org/2001/XMLSchema-instance' xmlns:xs='http://www.w3.org/2001/XMLSchema' xmlns:typens='http://www.esri.com/schemas/ArcGIS/3.3.0'><FeatureDataset>NAD_1983_2011_Michigan_GeoRef_Meters</FeatureDataset><WorkspaceConnectionString>DATABASE=E:\Nyaa_NSPEARS_Application\2_Data_Layers_Uploaded_to_Data_Repository\Baseline_Indicators.gdb</WorkspaceConnectionString><WorkspaceFactory>FileGDB</WorkspaceFactory><Dataset>CensusTracts_with_Baseline_Indicator_data</Dataset><DatasetType>esriDTFeatureClass</DatasetType></CIMFeatureDatasetDataConnection>" <operationSequence><workflow><AddField><field_name>S2201_C01_034E_TEXT</field_name><field_type>TEXT</field_type><field_length>255</field_length><field_is_nullable>True</field_is_nullable><field_is_required>False</field_is_required></AddField></workflow></operationSequence> CalculateField "Total Population by Census Tract" S2201_C01_034E_TEXT "No Data" Python # Text NO_ENFORCE_DOMAINS UpdateSchema "CIMDATA=<CIMFeatureDatasetDataConnection xsi:type='typens:CIMFeatureDatasetDataConnection' xmlns:xsi='http://www.w3.org/2001/XMLSchema-instance' xmlns:xs='http://www.w3.org/2001/XMLSchema' xmlns:typens='http://www.esri.com/schemas/ArcGIS/3.3.0'><FeatureDataset>NAD_1983_2011_Michigan_GeoRef_Meters</FeatureDataset><WorkspaceConnectionString>DATABASE=E:\Nyaa_NSPEARS_Application\2_Data_Layers_Uploaded_to_Data_Repository\Baseline_Indicators.gdb</WorkspaceConnectionString><WorkspaceFactory>FileGDB</WorkspaceFactory><Dataset>CensusTracts_with_Baseline_Indicator_data</Dataset><DatasetType>esriDTFeatureClass</DatasetType></CIMFeatureDatasetDataConnection>" <operationSequence><workflow><AddField><field_name>S2201_C01_034E_Num</field_name><field_type>LONG</field_type><field_is_nullable>True</field_is_nullable><field_is_required>False</field_is_required></AddField></workflow></operationSequence> CalculateField "Total Population by Census Tract" S2201_C01_034E_Num !S2201_C01_034E! Python # Text NO_ENFORCE_DOMAINS UpdateSchema "CIMDATA=<CIMFeatureDatasetDataConnection xsi:type='typens:CIMFeatureDatasetDataConnection' xmlns:xsi='http://www.w3.org/2001/XMLSchema-instance' xmlns:xs='http://www.w3.org/2001/XMLSchema' xmlns:typens='http://www.esri.com/schemas/ArcGIS/3.3.0'><FeatureDataset>NAD_1983_2011_Michigan_GeoRef_Meters</FeatureDataset><WorkspaceConnectionString>DATABASE=E:\Nyaa_NSPEARS_Application\2_Data_Layers_Uploaded_to_Data_Repository\Baseline_Indicators.gdb</WorkspaceConnectionString><WorkspaceFactory>FileGDB</WorkspaceFactory><Dataset>CensusTracts_with_Baseline_Indicator_data</Dataset><DatasetType>esriDTFeatureClass</DatasetType></CIMFeatureDatasetDataConnection>" <operationSequence><workflow><DeleteField><field_name>S2201_C01_034E</field_name></DeleteField></workflow><workflow><AlterField><field_name>S2201_C01_034E</field_name><new_field_name>S2201_C01_034E</new_field_name><field_type>TEXT</field_type><field_is_nullable>True</field_is_nullable><clear_field_alias>False</clear_field_alias></AlterField></workflow></operationSequence> UpdateSchema "CIMDATA=<CIMFeatureDatasetDataConnection xsi:type='typens:CIMFeatureDatasetDataConnection' xmlns:xsi='http://www.w3.org/2001/XMLSchema-instance' xmlns:xs='http://www.w3.org/2001/XMLSchema' xmlns:typens='http://www.esri.com/schemas/ArcGIS/3.3.0'><FeatureDataset>NAD_1983_2011_Michigan_GeoRef_Meters</FeatureDataset><WorkspaceConnectionString>DATABASE=E:\Nyaa_NSPEARS_Application\2_Data_Layers_Uploaded_to_Data_Repository\Baseline_Indicators.gdb</WorkspaceConnectionString><WorkspaceFactory>FileGDB</WorkspaceFactory><Dataset>CensusTracts_with_Baseline_Indicator_data</Dataset><DatasetType>esriDTFeatureClass</DatasetType></CIMFeatureDatasetDataConnection>" <operationSequence><workflow><AddField><field_name>S2201_C01_034E</field_name><field_type>LONG</field_type><field_precision>0</field_precision><field_scale>0</field_scale><field_alias>S2201_C01_034E</field_alias><field_is_nullable>True</field_is_nullable><field_is_required>False</field_is_required></AddField></workflow></operationSequence> DeleteField "Total Population by Census Tract" S2201_C01_034E "Delete Fields" DeleteField "Total Population by Census Tract" S2201_C01_034E_TEXT "Delete Fields" DeleteField CensusTracts_with_Baseline_Indicator_data S2201_C01_034E_Num "Delete Fields" ExportFeatures CensusTracts_with_Baseline_Indicator_data E:\Nyaa_NSPEARS_Application\2_Data_Layers_Uploaded_to_Data_Repository\Baseline_Indicators.gdb\NAD_1983_2011_Michigan_GeoRef_Meters\CensusTracts_with_Baseline_Indicator_data2 # NOT_USE_ALIAS "STATEFP "State" true true false 2 Text 0 0,First,#,CensusTracts_with_Baseline_Indicator_data,CensusTracts_with_Baseline_Indicator_data.STATEFP,0,1;COUNTYFP "County" true true false 3 Text 0 0,First,#,CensusTracts_with_Baseline_Indicator_data,CensusTracts_with_Baseline_Indicator_data.COUNTYFP,0,2;TRACTCE "Tract" true true false 6 Text 0 0,First,#,CensusTracts_with_Baseline_Indicator_data,CensusTracts_with_Baseline_Indicator_data.TRACTCE,0,5;GEOID "GEOID" true true false 11 Text 0 0,First,#,CensusTracts_with_Baseline_Indicator_data,CensusTracts_with_Baseline_Indicator_data.GEOID,0,10;NAME "NAME" true true false 7 Text 0 0,First,#,CensusTracts_with_Baseline_Indicator_data,CensusTracts_with_Baseline_Indicator_data.NAME,0,6;NAMELSAD "NAMELSAD" true true false 20 Text 0 0,First,#,CensusTracts_with_Baseline_Indicator_data,CensusTracts_with_Baseline_Indicator_data.NAMELSAD,0,19;GEOID_Num "GEOID_Num" true true false 8 Double 0 0,First,#,CensusTracts_with_Baseline_Indicator_data,CensusTracts_with_Baseline_Indicator_data.GEOID_Num,-1,-1;Label "Label" true true false 8000 Text 0 0,First,#,CensusTracts_with_Baseline_Indicator_data,CensusTracts_with_Baseline_Indicator_data.Label,0,7999;Dataset "Dataset" true true false 8000 Text 0 0,First,#,CensusTracts_with_Baseline_Indicator_data,CensusTracts_with_Baseline_Indicator_data.Dataset,0,7999;Population "Population" true true false 4 Long 0 0,First,#,CensusTracts_with_Baseline_Indicator_data,CensusTracts_with_Baseline_Indicator_data.Population,-1,-1;S2201_C01_001E "Number of Households" true true false 4 Long 0 0,First,#,CensusTracts_with_Baseline_Indicator_data,CensusTracts_with_Baseline_Indicator_data.S2201_C01_001E,-1,-1;Male "Male" true true false 4 Long 0 0,First,#,CensusTracts_with_Baseline_Indicator_data,CensusTracts_with_Baseline_Indicator_data.Male,-1,-1;Female "Female" true true false 4 Long 0 0,First,#,CensusTracts_with_Baseline_Indicator_data,CensusTracts_with_Baseline_Indicator_data.Female,-1,-1;Under_18 "Under 18" true true false 4 Long 0 0,First,#,CensusTracts_with_Baseline_Indicator_data,CensusTracts_with_Baseline_Indicator_data.Under_18,-1,-1;Over_60 "Over 60" true true false 4 Long 0 0,First,#,CensusTracts_with_Baseline_Indicator_data,CensusTracts_with_Baseline_Indicator_data.Over_60,-1,-1;MedianAge "Median Age" true true false 8000 Text 0 0,First,#,CensusTracts_with_Baseline_Indicator_data,CensusTracts_with_Baseline_Indicator_data.MedianAge,0,7999;One_Race "One Race" true true false 4 Long 0 0,First,#,CensusTracts_with_Baseline_Indicator_data,CensusTracts_with_Baseline_Indicator_data.One_Race,-1,-1;TwoMoreRaces "Two or More Races" true true false 4 Long 0 0,First,#,CensusTracts_with_Baseline_Indicator_data,CensusTracts_with_Baseline_Indicator_data.TwoMoreRaces,-1,-1;White "White" true true false 4 Long 0 0,First,#,CensusTracts_with_Baseline_Indicator_data,CensusTracts_with_Baseline_Indicator_data.White,-1,-1;Black "Black of African American" true true false 4 Long 0 0,First,#,CensusTracts_with_Baseline_Indicator_data,CensusTracts_with_Baseline_Indicator_data.Black,-1,-1;Amer_Indian "American Indian and Alaska Native" true true false 4 Long 0 0,First,#,CensusTracts_with_Baseline_Indicator_data,CensusTracts_with_Baseline_Indicator_data.Amer_Indian,-1,-1;Asian "Asian" true true false 4 Long 0 0,First,#,CensusTracts_with_Baseline_Indicator_data,CensusTracts_with_Baseline_Indicator_data.Asian,-1,-1;Hawaiian "Native Hawaiian and Other Pacific Islander" true true false 4 Long 0 0,First,#,CensusTracts_with_Baseline_Indicator_data,CensusTracts_with_Baseline_Indicator_data.Hawaiian,-1,-1;OtherRace "Other Race" true true false 4 Long 0 0,First,#,CensusTracts_with_Baseline_Indicator_data,CensusTracts_with_Baseline_Indicator_data.OtherRace,-1,-1;Hispanic "Hispanic or Latino" true true false 4 Long 0 0,First,#,CensusTracts_with_Baseline_Indicator_data,CensusTracts_with_Baseline_Indicator_data.Hispanic,-1,-1;NotHispanic "Not Hispanic or Latino" true true false 4 Long 0 0,First,#,CensusTracts_with_Baseline_Indicator_data,CensusTracts_with_Baseline_Indicator_data.NotHispanic,-1,-1;HousingUnits "Housing Units" true true false 4 Long 0 0,First,#,CensusTracts_with_Baseline_Indicator_data,CensusTracts_with_Baseline_Indicator_data.HousingUnits,-1,-1;B28004_002E "Number of Households who Earn Less than $10,000 per Year" true true false 4 Long 0 0,First,#,CensusTracts_with_Baseline_Indicator_data,CensusTracts_with_Baseline_Indicator_data.B28004_002E,-1,-1;B28004_006E "Number of Households who Earn between $10,000 and $19,999 Annually " true true false 4 Long 0 0,First,#,CensusTracts_with_Baseline_Indicator_data,CensusTracts_with_Baseline_Indicator_data.B28004_006E,-1,-1;B28004_010E "Number of Households who Earn between $20,000 and $34,999 Annually " true true false 4 Long 0 0,First,#,CensusTracts_with_Baseline_Indicator_data,CensusTracts_with_Baseline_Indicator_data.B28004_010E,-1,-1;B28004_014E "Number of Households who Earn between $35,000 and $49,999 Annually " true true false 4 Long 0 0,First,#,CensusTracts_with_Baseline_Indicator_data,CensusTracts_with_Baseline_Indicator_data.B28004_014E,-1,-1;B28004_018E "Number of Households who Earn between $50,000 and $74,999 Annually " true true false 4 Long 0 0,First,#,CensusTracts_with_Baseline_Indicator_data,CensusTracts_with_Baseline_Indicator_data.B28004_018E,-1,-1;B28004_022E "Number of Households who Earn $75,000 or More Annually " true true false 4 Long 0 0,First,#,CensusTracts_with_Baseline_Indicator_data,CensusTracts_with_Baseline_Indicator_data.B28004_022E,-1,-1;S2201_C01_021E "Number of Households below the Poverty Level within the last 12 months" true true false 4 Long 0 0,First,#,CensusTracts_with_Baseline_Indicator_data,CensusTracts_with_Baseline_Indicator_data.S2201_C01_021E,-1,-1;S2201_C02_021E "Percent of Households below the Poverty Level within the last 12 months" true true false 8 Double 0 0,First,#,CensusTracts_with_Baseline_Indicator_data,CensusTracts_with_Baseline_Indicator_data.S2201_C02_021E,-1,-1;S2201_C02_021E_TEXT "Percent of Households below the Poverty Level within the last 12 months_TEXT" true true false 255 Text 0 0,First,#,CensusTracts_with_Baseline_Indicator_data,CensusTracts_with_Baseline_Indicator_data.S2201_C02_021E_TEXT,0,254;S2201_C03_001E "Number of Households who receive SNAP benefits" true true false 4 Long 0 0,First,#,CensusTracts_with_Baseline_Indicator_data,CensusTracts_with_Baseline_Indicator_data.S2201_C03_001E,-1,-1;S2201_C03_034E "Median Household Income in the last 12 months for SNAP Households" true true false 4 Long 0 0,First,#,CensusTracts_with_Baseline_Indicator_data,CensusTracts_with_Baseline_Indicator_data.S2201_C03_034E,-1,-1;S2201_C03_034E_TEXT "Median Household Income in the last 12 months for SNAP Households_TEXT" true true false 8000 Text 0 0,First,#,CensusTracts_with_Baseline_Indicator_data,CensusTracts_with_Baseline_Indicator_data.S2201_C03_034E_TEXT,0,7999;Tract "Tract" true true false 8 BigInteger 0 0,First,#,CensusTracts_with_Baseline_Indicator_data,CensusTracts_with_Baseline_Indicator_data.Tract,-1,-1;S2201_C01_023E "Number of Households with at least 1 person living with a Disability" true true false 4 Long 0 0,First,#,CensusTracts_with_Baseline_Indicator_data,CensusTracts_with_Baseline_Indicator_data.S2201_C01_023E,-1,-1;S2101_C01_007E "Number of Assigned Male at Birth Individuals over the age of 18" true true false 4 Long 0 0,First,#,CensusTracts_with_Baseline_Indicator_data,CensusTracts_with_Baseline_Indicator_data.S2101_C01_007E,-1,-1;S2101_C01_008E "Number of Assigned Female at Birth Individuals over the age of 18" true true false 4 Long 0 0,First,#,CensusTracts_with_Baseline_Indicator_data,CensusTracts_with_Baseline_Indicator_data.S2101_C01_008E,-1,-1;Shape_Length "Shape_Length" false true true 8 Double 0 0,First,#,CensusTracts_with_Baseline_Indicator_data,CensusTracts_with_Baseline_Indicator_data.Shape_Length,-1,-1;Shape_Area "Shape_Area" false true true 8 Double 0 0,First,#,CensusTracts_with_Baseline_Indicator_data,CensusTracts_with_Baseline_Indicator_data.Shape_Area,-1,-1;Tract_join "Tract_join" true true false 8 BigInteger 0 0,First,#,CensusTracts_with_Baseline_Indicator_data,MedianHouseholdIncome_Join.csv.Tract_join,-1,-1;S2201_C01_034E "S2201_C01_034E" true true false 4 Long 0 0,First,#,CensusTracts_with_Baseline_Indicator_data,MedianHouseholdIncome_Join.csv.S2201_C01_034E,-1,-1;S2201_C01_034E_TEXT "S2201_C01_034E_TEXT" true true false 8 Double 0 0,First,#,CensusTracts_with_Baseline_Indicator_data,MedianHouseholdIncome_Join.csv.S2201_C01_034E_TEXT,-1,-1" # UpdateSchema "CIMDATA=<CIMFeatureDatasetDataConnection xsi:type='typens:CIMFeatureDatasetDataConnection' xmlns:xsi='http://www.w3.org/2001/XMLSchema-instance' xmlns:xs='http://www.w3.org/2001/XMLSchema' xmlns:typens='http://www.esri.com/schemas/ArcGIS/3.3.0'><FeatureDataset>NAD_1983_2011_Michigan_GeoRef_Meters</FeatureDataset><WorkspaceConnectionString>DATABASE=E:\Nyaa_NSPEARS_Application\2_Data_Layers_Uploaded_to_Data_Repository\Baseline_Indicators.gdb</WorkspaceConnectionString><WorkspaceFactory>FileGDB</WorkspaceFactory><Dataset>CensusTracts_with_Baseline_Indicator_data2</Dataset><DatasetType>esriDTFeatureClass</DatasetType></CIMFeatureDatasetDataConnection>" <operationSequence><workflow><AddField><field_name>Temp</field_name><field_type>TEXT</field_type><field_length>255</field_length><field_is_nullable>True</field_is_nullable><field_is_required>False</field_is_required></AddField></workflow><workflow><AddField><field_name>Temp2</field_name><field_type>TEXT</field_type><field_length>255</field_length><field_is_nullable>True</field_is_nullable><field_is_required>False</field_is_required></AddField></workflow></operationSequence> CalculateField CensusTracts_with_Baseline_Indicator_data2 Temp !S2201_C01_034E_TEXT! Python # Text NO_ENFORCE_DOMAINS CalculateField CensusTracts_with_Baseline_Indicator_data2 Temp2 "No Data" Python # Text NO_ENFORCE_DOMAINS CalculateField CensusTracts_with_Baseline_Indicator_data2 Temp2 Left([Temp],1) VBScript # Text NO_ENFORCE_DOMAINS CalculateField CensusTracts_with_Baseline_Indicator_data2 Temp2 Left([Temp],2) VBScript # Text NO_ENFORCE_DOMAINS CalculateField CensusTracts_with_Baseline_Indicator_data2 Temp2 Left([Temp],3) VBScript # Text NO_ENFORCE_DOMAINS UpdateSchema "CIMDATA=<CIMFeatureDatasetDataConnection xsi:type='typens:CIMFeatureDatasetDataConnection' xmlns:xsi='http://www.w3.org/2001/XMLSchema-instance' xmlns:xs='http://www.w3.org/2001/XMLSchema' xmlns:typens='http://www.esri.com/schemas/ArcGIS/3.3.0'><FeatureDataset>NAD_1983_2011_Michigan_GeoRef_Meters</FeatureDataset><WorkspaceConnectionString>DATABASE=E:\Nyaa_NSPEARS_Application\2_Data_Layers_Uploaded_to_Data_Repository\Baseline_Indicators.gdb</WorkspaceConnectionString><WorkspaceFactory>FileGDB</WorkspaceFactory><Dataset>CensusTracts_with_Baseline_Indicator_data2</Dataset><DatasetType>esriDTFeatureClass</DatasetType></CIMFeatureDatasetDataConnection>" <operationSequence><workflow><AddField><field_name>Temp3</field_name><field_type>TEXT</field_type><field_length>255</field_length><field_is_nullable>True</field_is_nullable><field_is_required>False</field_is_required></AddField></workflow><workflow><AddField><field_name>Temp4</field_name><field_type>TEXT</field_type><field_length>255</field_length><field_is_nullable>True</field_is_nullable><field_is_required>False</field_is_required></AddField></workflow></operationSequence> CalculateField CensusTracts_with_Baseline_Indicator_data2 Temp3 Right([Temp],3) VBScript # Text NO_ENFORCE_DOMAINS CalculateField CensusTracts_with_Baseline_Indicator_data2 Temp4 "$"&[Temp2]&","&[Temp3] VBScript # Text NO_ENFORCE_DOMAINS CalculateField CensusTracts_with_Baseline_Indicator_data2 Temp4 "No Data" VBScript # Text NO_ENFORCE_DOMAINS CalculateField CensusTracts_with_Baseline_Indicator_data2 S2201_C01_034E_TEXT [Temp4] VBScript # Text NO_ENFORCE_DOMAINS DeleteField CensusTracts_with_Baseline_Indicator_data2 S2201_C01_034E_TEXT "Delete Fields" DeleteField CensusTracts_with_Baseline_Indicator_data2 Temp "Delete Fields" DeleteField CensusTracts_with_Baseline_Indicator_data2 Temp2 "Delete Fields" DeleteField CensusTracts_with_Baseline_Indicator_data2 Temp3 "Delete Fields" UpdateSchema "CIMDATA=<CIMFeatureDatasetDataConnection xsi:type='typens:CIMFeatureDatasetDataConnection' xmlns:xsi='http://www.w3.org/2001/XMLSchema-instance' xmlns:xs='http://www.w3.org/2001/XMLSchema' xmlns:typens='http://www.esri.com/schemas/ArcGIS/3.3.0'><FeatureDataset>NAD_1983_2011_Michigan_GeoRef_Meters</FeatureDataset><WorkspaceConnectionString>DATABASE=E:\Nyaa_NSPEARS_Application\2_Data_Layers_Uploaded_to_Data_Repository\Baseline_Indicators.gdb</WorkspaceConnectionString><WorkspaceFactory>FileGDB</WorkspaceFactory><Dataset>CensusTracts_with_Baseline_Indicator_data2</Dataset><DatasetType>esriDTFeatureClass</DatasetType></CIMFeatureDatasetDataConnection>" <operationSequence><workflow><AddField><field_name>S2201_C01_034E_TEXT</field_name><field_type>TEXT</field_type><field_length>255</field_length><field_is_nullable>True</field_is_nullable><field_is_required>False</field_is_required></AddField></workflow></operationSequence> CalculateField CensusTracts_with_Baseline_Indicator_data2 S2201_C01_034E_TEXT [Temp4] VBScript # Text NO_ENFORCE_DOMAINS DeleteField CensusTracts_with_Baseline_Indicator_data2 Temp4 "Delete Fields" UpdateSchema "CIMDATA=<CIMFeatureDatasetDataConnection xsi:type='typens:CIMFeatureDatasetDataConnection' xmlns:xsi='http://www.w3.org/2001/XMLSchema-instance' xmlns:xs='http://www.w3.org/2001/XMLSchema' xmlns:typens='http://www.esri.com/schemas/ArcGIS/3.3.0'><FeatureDataset>NAD_1983_2011_Michigan_GeoRef_Meters</FeatureDataset><WorkspaceConnectionString>DATABASE=E:\Nyaa_NSPEARS_Application\2_Data_Layers_Uploaded_to_Data_Repository\Baseline_Indicators.gdb</WorkspaceConnectionString><WorkspaceFactory>FileGDB</WorkspaceFactory><Dataset>CensusTracts_with_Baseline_Indicator_data2</Dataset><DatasetType>esriDTFeatureClass</DatasetType></CIMFeatureDatasetDataConnection>" <operationSequence><workflow><DeleteField><field_name>Tract_join</field_name></DeleteField></workflow></operationSequence> CalculateField "% of Households below the Poverty Level" S2201_C02_021E_TEXT !S2201_C02_021E! Python # Text NO_ENFORCE_DOMAINS CalculateField "% of Households below the Poverty Level" S2201_C02_021E_TEXT "!S2201_C02_021E_TEXT! + "%"" Python # Text NO_ENFORCE_DOMAINS CensusTracts_with_Baseline_Indicator_data2 002 0.000 file://\\DESKTOP-J9TVK45\E$\Nyaa_NSPEARS_Application\2_Data_Layers_Uploaded_to_Data_Repository\Baseline_Indicators.gdb Local Area Network Projected GCS_NAD_1983_2011 Linear Unit: Meter (1.000000) <ProjectedCoordinateSystem xsi:type='typens:ProjectedCoordinateSystem' xmlns:xsi='http://www.w3.org/2001/XMLSchema-instance' xmlns:xs='http://www.w3.org/2001/XMLSchema' xmlns:typens='http://www.esri.com/schemas/ArcGIS/3.3.0'><WKT>PROJCS[&quot;NAD_1983_2011_Michigan_GeoRef_Meters&quot;,GEOGCS[&quot;GCS_NAD_1983_2011&quot;,DATUM[&quot;D_NAD_1983_2011&quot;,SPHEROID[&quot;GRS_1980&quot;,6378137.0,298.257222101]],PRIMEM[&quot;Greenwich&quot;,0.0],UNIT[&quot;Degree&quot;,0.0174532925199433]],PROJECTION[&quot;Hotine_Oblique_Mercator_Azimuth_Natural_Origin&quot;],PARAMETER[&quot;False_Easting&quot;,2546731.496],PARAMETER[&quot;False_Northing&quot;,-4354009.816],PARAMETER[&quot;Scale_Factor&quot;,0.9996],PARAMETER[&quot;Azimuth&quot;,337.25556],PARAMETER[&quot;Longitude_Of_Center&quot;,-86.0],PARAMETER[&quot;Latitude_Of_Center&quot;,45.30916666666666],UNIT[&quot;Meter&quot;,1.0],AUTHORITY[&quot;EPSG&quot;,6497]]</WKT><XOrigin>-28810000</XOrigin><YOrigin>-30359300</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>102968</WKID><LatestWKID>6497</LatestWKID></ProjectedCoordinateSystem> NAD_1983_2011_Michigan_GeoRef_Meters 20240709 18053300 20240709 18053300 Microsoft Windows 10 Version 10.0 (Build 19045) ; Esri ArcGIS 13.3.0.52636 Total Population by Census Tract Baseline_Indicators Data Source: American Community Survey (ACS), 5-Year Estimates (2017-2021). Highlighted Variable: Total Population by Census Tract Other Fields/Data: OBJECTID (OBJECTID) State (STATEFP) County (COUNTYFP) Tract (TRACTCE) GEOID_Text (GEOID) GEOID_Num (GEOID_Num) Label_Full (Label) Dataset (Dataset) Population (Population) Median Age (MedianAge) Male (Male) Female (Female) Number of Households (S2201_C01_001E) Number of Households who Receive SNAP Benefits (S2201_C03_001E) Median Household Income in the last 12 months (S2201_C01_034E) Median Household Income in the last 12 months_TEXT (S2201_C01_034E_TEXT) File Geodatabase Feature Class 0.000 dataset EPSG 8.2.10(10.3.1) 0 Simple FALSE 0 TRUE FALSE CensusTracts_with_Baseline_Indicator_data2 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. STATEFP State String 2 0 0 COUNTYFP County String 3 0 0 TRACTCE Tract String 6 0 0 GEOID GEOID String 11 0 0 NAME NAME String 7 0 0 NAMELSAD NAMELSAD String 20 0 0 GEOID_Num GEOID_Num Double 8 0 0 Label Label String 8000 0 0 Dataset Dataset String 8000 0 0 Population Population Integer 4 0 0 Male Male Integer 4 0 0 Female Female Integer 4 0 0 Under_18 Under 18 Integer 4 0 0 Over_60 Over 60 Integer 4 0 0 MedianAge Median Age String 8000 0 0 One_Race One Race Integer 4 0 0 TwoMoreRaces Two or More Races Integer 4 0 0 White White Integer 4 0 0 Black Black of African American Integer 4 0 0 Amer_Indian American Indian and Alaska Native Integer 4 0 0 Asian Asian Integer 4 0 0 Hawaiian Native Hawaiian and Other Pacific Islander Integer 4 0 0 OtherRace Other Race Integer 4 0 0 Hispanic Hispanic or Latino Integer 4 0 0 NotHispanic Not Hispanic or Latino Integer 4 0 0 HousingUnits Housing Units Integer 4 0 0 S2201_C01_001E Number of Households Integer 4 0 0 S2201_C01_021E Number of Households below the Poverty Level within the last 12 months Integer 4 0 0 S2201_C02_021E Percent of Households below the Poverty Level within the last 12 months Double 8 0 0 S2201_C03_001E Number of Households who receive SNAP benefits Integer 4 0 0 S2201_C03_034E Median Household Income in the last 12 months for SNAP Households Integer 4 0 0 S2201_C03_034E_TEXT Median Household Income in the last 12 months for SNAP Households_TEXT String 8000 0 0 Tract Tract BigInteger 8 0 0 B28004_002E Number of Households who Earn Less than $10,000 per Year Integer 4 0 0 B28004_006E Number of Households who Earn between $10,000 and $19,999 Annually Integer 4 0 0 B28004_010E Number of Households who Earn between $20,000 and $34,999 Annually Integer 4 0 0 B28004_014E Number of Households who Earn between $35,000 and $49,999 Annually Integer 4 0 0 B28004_018E Number of Households who Earn between $50,000 and $74,999 Annually Integer 4 0 0 B28004_022E Number of Households who Earn $75,000 or More Annually Integer 4 0 0 S2201_C02_021E_TEXT Percent of Households below the Poverty Level within the last 12 months_TEXT String 255 0 0 S2201_C01_023E Number of Households with at least 1 person living with a Disability Integer 4 0 0 S2201_C01_034E S2201_C01_034E Integer 4 0 0 S2101_C01_007E Number of Assigned Male at Birth Individuals over the age of 18 Integer 4 0 0 Tract_join Tract_join BigInteger 8 0 0 S2101_C01_008E Number of Assigned Female at Birth Individuals over the age of 18 Integer 4 0 0 S2201_C01_034E_TEXT S2201_C01_034E_TEXT 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. 20240709 iVBORw0KGgoAAAANSUhEUgAAASwAAADICAYAAABS39xVAAAAAXNSR0IB2cksfwAAAAlwSFlzAAAO xAAADsQBlSsOGwAAIABJREFUeJzsvWmTJMmRHfj8PuLIs6pPoAfAcHZkuFxyubIiK5T9+fthv1FW ZoRDcgYYAH1VVV5x+WlubitPzT3CMzLyqs6zuhSSqOzMSA93Dzc11adPn/oXFxcGN5gxBlprnJ/P UZUVXNdFFEfQjYbWrfyubVs8hpm2gadLhG2OEAoBNFy0cByeF1AbHw4MAreF7wCuA+jWwHNdGNOi zHOo8xMEDn/mXDp2ph0EkykOjo/XP5ufX2D1/ie4Zz+h0ga8Kt3a9/JcYJHXcIoVPF1359ciMBrm N/8A5/f/Gf70CNk//T/wTv8KL5/xTFHEe0jLGXxdwzGb++T+7t/jq//zv+D4D3935brb1qBSDU4v cqyKFk3rwHU9uK7/KPf512Z8pvnlOI58XWf294Dv+/YZd4AoirC3N4Xvuzf+7Wd7HLvTCtg4Jn7Q Lcqikv/uzcDA4af5gNbqBqiWCNoMx6mBLw7H7b6sjeT/+XNv/bOg+7eqGtR1jcDjX1w9N3nWxBm3 8OiN+ge5pZsBYo+uENCu/TkdYuW0cNoaXlNurt1x0bQabZXDXRoEqxN4xQzQNVovQKAycXBDZ8Xj Op4Hx91cy9Bc10EcBjjci2FMgazs7rVxAWf333y2+xk/082zsOv5cOS58AMfSRyh0Vo2rigKPjur l+2wHNlhGFnZyMZGXJdf8dA7jUFbzGHmPwNuDX/89n5/bYw4vKYsEMnZXQ0iPbTQqkZWFJiOR4N3 BlpjozVeFR0VL1ycmTjmK28GnS/R/PxvaHWN6OwHOFrJr8Kmkq+dxmPecN94r0dJhDQOUVQK82WJ 2bIC3Oiz03og66OsXWYziRjT6Ri+73VZhOnWwefI6gU7LBuF2DUvYckjno6BaRT08hTj8gRtkyOI o/sfhQ6r0UCjAO/q+bbGoIEHzw8QR+H658l4hPaLr1HEKcqTnxE0lTi2m0wHMfToEPACuO//haHh nc6RznR1cYH4cI7RdHrtIuDPGW15ey7CoMb5UkNp/vxzpLX1qV97r/l5t1pLWt3fZ/47jLJ2GTct Rln8kz4K/+ysXrDD4q5S1wrZKodqmsEHTEyFEYKRCOOWz/1OxlTTVBnc7AyT8hyxzlHLDhjf+1hM XdtWw+EX067OF0iK1xooN0QwShGPRhI99hYEAUaTiTyUs/MTSesurYMd1+m2DfzZO2jXQ1tmBLZu PT9x++fvkf3pvyNkyvEP/0F27vXv+4jO2O95rwPfQxr7mK0aC6p93uQHm5OCMY2karxPdDSMkvl8 usShYKCg0RgLH9zF6fCe83W6aVAoJc9JEPjwvA388NlemMNi6leWFfK8WIfP/MCY1/dhslINGjV0 ZnczOhSmbXQqXPROU8KvFgjzM4xMKbuacrwObLqf8bz5oPlMLXleBmjpBFwPCH04YYJ4PJboqn94 GUXKA+66CPiaXe8r13j5Ol2t4C0+SHonruqOp+tkc1Tvvsc8HSM5OpaFxWt1gxCuH8DoBrqq5L/D 0QhhHMs99z0HqpGt4ldt3OAcFmXaGmFbQ5sWSZAgGYXwOodlP3uDRhvo1oEz2Etui7D61K+qamR5 iTiO5Gc20vq8W7w4h8XPUimNqqzle5eOyvMQRSGSNEUQeBJmZ3mBLCvEQdzks+ThYPRBUNs0MHUF U+eAKuE0BaImQ9RWiFxbjRGTNXz/h4MAaaNbOWeiSXQmxg2AMEY4SjGKQtkx+2PT8eZZBiPYnEFT V3AI+g8uSL7j+V9zjdzFXe7gt5yuEcfkrp1kMTvH+f/8Z4uzuS7cdAwvTmGqEno1h5NOMPn6Wxx+ /Q18z0Uae3J9VdO+8rTwcmR+t8+5q+7RWXGj0AXiNsM0bFE6IcbjKUZ76aVjFaUS7K/WrqSEww+o f902lmWjWheO66CsaiiJsHoc67OzepEOixFQ0zTyFYYh0lHSVUg2ADx3mzGjLtfDYrGUyGaX0+IH zbC9rQo4xQXCaoZJWyBytITvXKt2wW45CC7Ij3BYTANbz0fuJjCej/1JiiQO5YG1mMTmmHxYeY0X f/03qMVMIj5eRIQWrrN1MTuujT9quugqcW2F8TrTrCh6IdowsecZJ0h9HxNXd5fZAuUcKBf2yK5B rUqYshDnxkVzMI1h2gJ61aAhreMVOi1J41oNrRr5rLixDMHsPvLZdmLcIHVdItArjD2FUQBEHlM3 D/U1mXhVN8iKBo5DrNLZSW8YpuP255BnwpTGZg9tKxsyqTw3AfWf7RkdFhd3ksQI6KA8u9C3FzvN 8/m6SBZcUVbyoTIC4MNIR2VWp/DLGWJdwDMtfKPgGgVPOFXAtk9Ym+A39lsJ7QUEvduDEhGknk6Q xAnyqkYYhYJPST1z6xA8NDEvRlQ+8ShjQfO+Sjg8H1snvHzCxtgapBQTbzsxz4c/2cPht7+xHB+X 6XVgnfbwhAbvwUhCVwWqIoc/mQjHLIl9VKrFoni5UVZTrGCaWq7ZDRP738UCDiPquoCTX8jroqO3 CCb7MI4nDp3m0Cl0lBFuAbwbLgwSp0XsawRBi4AbZref8fNriFvu2C1ZLyJueR11QZ7RK06Im5iG ZkRlgDAMEMcxgjD47KxeqsPqCXPc1Xct9M3rHOu00hheR7AjrlVmGYrzd4jzD/DrJfxWIXAh+IL9 w5tPjO/nchcucizPtKR1XhhJqZkP0E3GRe2GdLAeSlYLuzfbfQ2WW8ZFwkWxPr8rr+qcyXbQRcd2 V0CJVaowQjqZXNnVe1NaSyrOxTKKIyhVoTw7QeuHCMK/QRCE8F0DtylQz1cIxkeCeb2IXV+qcQpt NoNz8SPcKpc01/gRAn5f53DISWtqOHWOxgsQ76dI3ASO54tz6mKsrh7NyNX+hHfLdwxCj5+v3R7o pGptYIj5Md3bAYhLNNfvKFt20z2TKK9lIcZHygKNwAifAfcXDbrbz/P2hdCD8UliP1DuTr7Top23 iEMPxkmAxoOrN4TLO1nbQNc1ymwlKZc/nspDeZvD6s+aERmrPdyBucsSsL4RX7um+naTP+qJHsKK 7x1jt+C2DyXr5gZ2Nc+RmGGRF0JGdU0rEaJiul2WCOIYyf4hVJ5BnbwDTs/ROi6c0QGcYEPPeA4z rYapCpjVOXD+PYL5T/BUIc6C9yUwzVbU6sA4AQLPRRK4UuHb2HXP3OWfNwYo4SJKp3A7zPLSOQl3 7qbjWXBdzmUHjuV32UOacDO+W3Xxsz2uPUqvBz/odDyG8+3vUWfHqIscWJ7Bm/8ovKbNvmkX8c5q TZeqcRELBtb9932qkXy+4iCQaIUgPEHrndZhGbdzzHa/hs5KScncui9JVwaOS85l/XX9Q1+rRu5V my3l72dVKREEI02vWOGs1Yi//g717ALN+x8w0jUyFhMYXbj7cD3/2ZyVZsp39gPckz8iLc7W/Qi8 DtleHmOtO3R0ISbTMZZZccWh9BjVNQHW2mHZtPByxEX4I04ijCcj2Yw/O6uXYY/2hHO3S8ZTxOkY DdOayR7KeARz8Q6xWiIwSta+0i2WldqJUQWeg5i7r+tbsqdwbLpytPBrbjNHqpm6tjjFdWYjrJud Vc85u3Kdgq0YRMJct+V09v5VHfZiG4oMQqfrXdvqabx0LNeR62MgGDotwu7vFDEVpRCdv8P8/EQi WHFijsHqh/8Jk60Qf/l7pEffSFr+ZNYRMtXFT/BP/w3R8oNEVU+Bqsm9bTXqfIF//nCGveNjhIJT bqyPZm97TobV4k22EGM8Tq84q13P0Wdn9nT2qE+3hNtSHmYlyEcYp9AHx6h++B/QixPhXzFq8rrU jY8FHVMUeBKJCNO4W8SOcaDqEvmFRrVc2PDJcYRjw0eI0ROPIY6MO28QIEpiaEYo3fF3Wd9qtKt9 5/ILewxrl9PqqpwdpsWooofnnT4Ck7Tjci/ktkllSpODbyMzRoW5dqBdH6HPSliLoK3gM/IUx8jo RqHIVnDKAsktrPzhNd+I3zDiYEtRfgETxHCiEVw/2tyvMrMk2XIJd3WGKD+DXy6kx5JY4GMbz2F1 dobFyXvpFsiqGt53f8A0/AdgnF56rds3xd9wzRuirv0ibiWctwH1xVY2r258TV2jWC1sFTeKECcp wshytj7bw9uTbMf88NwwQhBGaNMxivk5qtUSKGaotUZI7GHAmJdevq5MOEypWMVrdINWdT8lE1lI gQaNpH/+ukdPBSFKbWTXXTuza4xO01IrrrHuvG6K0obnuU2HEDdCLOcWdYC+MkWHxSOwVN/AFfKo F8coaoXAVAhcEm4NakOiaWSdOt/lpihSnFDNniABvlsvhBOO4PhbeKA0gJMnlyFavYcKUuGOGY8Y mUFTZHDOv4e3OoNTLuEVCwStdVRPgfDwOrLZDIvv/w2rdz+iXi3gk3YwHqOtfnfptXT4dkO725n1 josbGAtH7PIg75BGh6TqGnVVCk8vTMj3AqrZKfIf/hVG1fKMq+NvkLz9FnHap5KPcht+tfbkoIdL esT0GPriFNX8XCpiQeJCinlS4XNQkxQJguR0W0wJbboYeg4uQ8sGrB/WoARLi6R7Ohh5FLVBbnzs jdiu4V5PiehpDbdEWDfhILdeMxuhHYPWsaoPO4/fYS3DQqTURnm/AjqXGK3jY6UaJFpJSlhrB77X ItUl3GyG6uIDdDySipsYnRQJsILJOHBVDq9aSIWx8VOYva8BdyL0iuF5SFuTVgg1QfMWjdpDGypA VWjPf0D04V8RFhdC4JQ02KHyhN1cbitQrN+n7zyQz+Vud7bnzM1+/B7FT38FFueIespLx5/b3gDY FSAsd5eOuNsEd1Ecumox75dqNfLutNaM9+UC+fwcxfIC2XKB6eFbW9A5+wHmr/8Er6lAsk5T5NDh GH4YfWbFP4I9A0rrYHr4RlJCM/sZX4zDTr/KPmy9bhX/u1AapdKIfFeisJ0+55pnnT1l0zSSiEUi vGtCdEndeqLibacuUcTHpzwWw3Kv/R2jQeN7MFZuSwqXTAPp1BG22E8CXMxrlEVpo6WqshQBo1H8 8Cfk6RG86RG88YHF+soMTb5geIDjL9/geBwK2ZJW1SWW1QSNF0mUJvenk9cRp+kGKJwItRPZVLbI YGY/If75vyFQuVQwuf4ruFDhCJ7wye7g9iWrtq/SXoD2HhpfTMnKskTx/kcpTNyWfhK/DAI6KEoj 2b5Aj7ywS7hU17rVKDTlCq2q4UQpKm4WXaWQjm72r/+E8q//jGb+AedZiXw8QRIGSByN1NTr1J8b JyO7z/Y49ixlJT4wUTJGO57CV0srW7PljUSlIGAbihFgXrcNQkYbXTNzX0Ekz0pwr0FZvKcPCOGP JFISXq87GWJBWkt6RQCKZPs+exxW+bqsUR7KuxTgP8a4OErPRw0fARpMAhehMVBGocmXOP2whL88 R9RUslh7/hhNlys08wt4f/7HTXmf6SUdi+shiP93uPEXcAKLRQVoERTngoW1yT7ceAy9OoOXnYrj qr0EpfFQlyWgP4hyRXLxVwQE1fsG767NaJTG0msnn80djWddGtvUfVetKgL85WoJo6o7NZnzfA4m MZLQQ1nRWUWYnc2QzzJhx2N8hLap4RYL233RrCQdz4sQhQmx8kJUcSoKHGb2Dj47GUYTJMYTgnHQ EM7Y8PsaP4ITjxGlqTx7n8H4T8Rhyc41miLYewNzuryWJc4d2/JWmTK20j8nLkP4PDYFCQTUt/9u rGvUdl1JK298cAjI+wHGX30LsBm7j7g6ZrukVYys2haTg7cAd2A+wKRaMC2ravszMuTNsN9wcBwe g99EKdA5jGtOZa1ySaMPJhzmGYWqLFEvL+DV7Bi4KmHjkudUF3BX55fvJY/nh5awOQDlibOlTQa3 YGpJXGYKvzhHXM/t73WFguceJPDKJYLsBEG1hLv13nwve5/Za3o/h9Xoq+kZ+/aWH96jyjPE0z1M jo6liFJlGZYn75H9+GcgX9kWqluMxyYc4LkhotBWmKsLBVPP4DU1VL2AZxpJ5wJdSuVaPgOGuA2p Ki4SHcln6ngKzjiBbgKJ9MKmRAhN7Yf1+7Hlyo9TBBHbwD6D7p+Ww4pH8CaHqM++70iFu6FRPmSk N/B3jLQEhujadpg+kgy6jU/1bCm7499OqXd8H6M3b9epaS/tIulix/0SfIPfd86K39NhZZnlTTmq 6voiLfi9dlbd34rQH2WOw/iWc7JxnbjmLtAQRQtVwa8Jbu+OLK5nkfWV0ys/FdlpV2t4ZY1a5Yia HBFXKpFDtle1pJMwEpsjLOdXnNXgFj6YqZoO6x2y9z+Lw1KrpWBsxJCKk5+hT362eNWVloPdRQdL U7BV4qoo4NY5Yp0haEqoeiXsedJIhlAaKSWNIXWkxZhKIvwhyXVBCKVc5IGPmJ0X7daFe6F0Y9g2 sM/2GPZsIuEEkoPxHsrxEZw6g9cSSG4k/N7W4pRIynPl6y5m2QfWuQjmvD7YOtdbG6s/jN7YwB1S T/melpYVqlkEU6ykKHD9OTF9bVE3faPzLhOUFy1VJth4TnFnz4MWgL1YOysBrAc9d7xjlmB7N/HA obEhxjcVRgNlVB6bki2pKqAWGbx6BbdVNh1+5KoXcSZUJTA/Q3XxHqsf/yrEWMr4UBd/nY5e+UOr BHItWK8UFh/eQy0u4KpanJTr2Y1FCMkSSW/+vmF7FJ8NqfhuHKHqe2VZqOk2znWF2LRC0eGz9Nk+ NYfl+0j23yD6D/838uUc1ewEzfwEWFG8r5C+w4+uyjlAXVU4PzkVkFsahDvelhA3hS5h/+USz6sG eyMqKNz/QZMozrXH+aVGh0wsqG0atKsaiBLEozGqusaiKBGyGZiLj4oPxOiIv5gWmROgbiq4Vfkg mFqrW5FVWc3naMsSFStn0mfpIPUtP279Pmsl2oc1umTib64qbJDYpdnXGiPgtejh5V+RppAvl2hO fkRQ5kIBocPh67mBFHmOcrUSFdg+SuMmRu7WXNQAO0fGKBkOVq2LSeQi8VxElFjrvDgbu40qr9k4 fkmd+bP15j+nXAadCfGFdLqPKElhjr8S+RCVL1AuL9CuZnDqlez219EBdplPXIo0AlZvpPd58MeX rtU6GqWoZTX9yIuw//cQd5CLhJiYqkoEFB8UDMZDQiDX91BMRijPz6RkHoxG1lmdfLCdACxOsJJH QP7SUW1aS80yzJbI89Kmuo6H8SgVxdOtV6OqKlSrFZKmROxqG9F1qhR5Y1OoQBQ5LfUiqxRq9vT5 nmBGLI48lMm73rkwa25k5M/PztFcnMKUOVrqsZHZLhSORvBLS42wx2FSF/TOb5BqcnJRkkww9iIh CSs2SHeba1BnUBcfMD/5ANf7RgioVmKcUk1WE568rs+qpR9vL2JuFLXV+YVkJICmN9pDMz5EW66k NM9/q+57lzrrBEpvxtElVlrrsd8gc8yd2xUG+kfSFW7b+bfe9ibXxnSDgzHcppZqlW6UOA/HTTAa pwjCEH4YSqoYRJE4CMr+krdGIqMfxVCnPwNLTu1pLr8/FygdmvYtiRUu8qZGtXYuXdjUlfidupJK GMmump8NNesZmYoyK9n3XXO540pFjJVYOjvFc/kFDotSQP5oDJOM0WTUBbPGow9pDNvxyk3EFEas 5fwC9Yef0MxOGX7LzxiVWaYfv27qQRiY14qSLR1205F76cQjceAk3JZSMMiybM2UJx+M/LHeKNkk JNWuZ3FYaNnuafxsL9BhXZlWkqTyBRwL9iDzBVcXMNkMbbkE6kIiCXKRRF6ZD97HfsaiY/MLHhB5 uO4hm3vDy2SUFKWdBQuBrWTlmQXBRyOkSQQ/OEJe24dfpE+OjmHKGjEf+r19nDN9yVdXHBadT9gq REyF7LpDk1VoOidgaSXWnRKIJsbM/9DGQetH8BLq37OcP6QcEKB2hI8koHbTisP6JcZuiPT4rXzu zWJmf8j37KKgzblu3crJHpxrwO6mKpG/+xGYncBjgeQem5PMAeA7DfGqrkXLd100jEhbOjwHgWvL JZxoyY2X4n98nnucjPgc5cZ9r2/5MWsJJ0IVfcHH9+39vG1u4q/R/Jd9Qxz4QYjxXgjs7VvMoSpR LGcoZydoF6fwObuQwyJkZqANu+97RWuM65623iE9z7K274Bk9RVAZ6cktRKZZqa/fB0HwLpNibYE Cj9AyEEITBFJ/Gxa4aCRsJm6nkRbTu1hkSRoOr2oPg4Ryd/BLi5Oye13q6txyrYxbYyTENFW+ji0 tXjeL3ycuFD3vvwK4zdfSGRiz8qgLivBJe17DKue9puaTnU0uRJ7CeBeFsh//kGY+h/jrLKW8S5E hVZIKd0hrL6bAyV9nd10TopUug6m04mkfn1LGNt8lktmCjVyXXb9nFYos58hIJVn02I0SkXdd9h4 zWfU+UjJ8Fuvcwfu91LtxUVYN5mQQaMYQfAGZu8Qrf4DVJmjWs1Qzk9hFqfCwuaEaClV3+GYFjO+ 36clBNJesqZr8N4mvu4ypmGExR0TdLDIpgLFh1WQq4AOx18DvYyAWgTwtYNEtwLMk/VPB1Rrqy6Q dMMpak0hxRQLL4T2tNU+7/oSH7sl2U6n6QXzbMP5bdarW0hj8laFTyYFDRykOOo0uRa8zjqKAXsA +3YabiaMcurVEvriBM7WPM3bzMbOBNrtEBPOGd+ceX/dXESOtIcJFaVYAcvztYR472CYNu/tTVBV SqIsOyvB4lttefnaF81KWtj6pn0SgXkvgu6rd2S/1Hn1Dd08Bx5ziK2JIECvdrFzYMf1op6Paa/K YdHkBrJXji0WJpSGUz8ZIZ4ewdS/hS5sOwqBe0ry+pzG4xCruOmYd3NuTNmKvBRQnKmbEEhdD1rZ 3r7bQBAqSIxHCcaTcfeTwUNggCnVGmTy9GbYhTzUPf0iX8oHJoukW5S22do+PCQsHnz5BQLvP9uq GRn8RSEDNlym2I8spyyLi9iONjJx+7YFRcdWUUq7rIUrddnsIuHCFllluS+XBaqHiaHifWLkzbSQ 1xmlOPj6G+HYUQSSGN7HKEnw6LHDiiFlf6yz3N4AeFdJIGUHlaKU9XIm911SPTLqO6iD/Kx+NqL0 J5b1TgUIO2XdOrE+qqor215GJ0hnxnZ3P7BOhpVqq/ZrHU9PWu0HH28Ob8Shbya52w2PETSxyNax 58JokNOyBIpYCxxaCILXZKNG27b01Bnaq3NYQ7O7KHccH+CkGYb/dQ0lPXTUEF/CVCs0nTwvsS8Z yyVM+EtHutP7SQd/nkmDK0mUBPWJXvTyvTcdR3TJOfo8jkVy9z7GfkiSHpcF8azNg8xq6NC4E1N+ OYitkgCdX1VWCJcrIbY6wzlXj2BMj+hISfAlF+mmwoi9hk7/y7VdCdvGNcvCA8oCHhu+LZR0/YNc ZeLcGe2qaILJ8TFcPhOywXB24UfABUwF6bDERXS27fikamqb7jn928kusDp/LzIzQbSJsvreREZb BOGlS+Ia651YH4nLMGN0m0DX6WGdh3VgxMXosGRIzGDoK6uj/emSZyaKICRgd46SDo7/8tmWe26o SmGVKiTJ7eSaaFRe3aSyVgHlYydhD+V87jM67VU7rJ2tGPKQRABTRg6C5QCH5QLN8hwmn8ErCUiT 7rAZ5WVF9a6pMDFkFma7HSpLHCQ0qquE3ber8I6h3Lb16+OWAarSJkMHEPqd+oPVdKJOU3F+ZjlC wwEXd3zroYrETX/TO5+q0YjuUIjg6+PQF+7ZrrYeSbsrH1Cuva47LgzKRosAbNfM3Y9PY5GGagzS h3nrUSjhvPkv63wZ+4rw0dYrLc1DhBeh0VZzlD/+EXkUIz04RhDFQuHpF2h/V+87y5M2bBurB6OC +rTNOrC+cY3yS/34vaEDHP4N09jSTrzqG9+vnBanZrM9jn27naPrRqb1UdYGXxtWPLuOkbXz7fpf xQFaJ8z3JV43jDx/NQ5r23iTY6aLyQh4+5VUaRip5JRhOf8R3uoUAR3XDalSxcnXWQ7FoaZhKKCL /7GAUPfQf5Td4z35fBDfsux3S46sKZS49TDuctOXKGsd6MyGcNGsZzWs73fc8b6C23Sk3Ls4uMc0 Lmh+3lE6xujr32L1v/1fWPx//y/MciYb1SWmCyOR7bvBxbxWn7AkYztTkgUWEhuuXllfbHa5Kf71 H3FGeOLf/SdMv/qNUFJE7kY1ndbW7pF4H329xh5M5MQvBdK73Ovmb4RucbmgvNN4XE6AXx/FcRBV tY3yRG+OctVMUTkGsOPo9QNVJMojF45j62oZG8iNlEWmuq6RpokovNoRgjdDCZ+0w9o2pkwxO+mj b6EPjlDNz1Cc/WTxrmtuEsNV7p66ylHnKwnjLVGQeb9NgYZ/eh0Rd/3YfFTOf1fNeWuK0WBjYyk6 EFYXvf0Dq19FkJu/7wD8XYwOuyFb8Fy7AQJSBkapDKWliB0bf6n2cF3Ew2Oyakbybi8X9JTG6wzq HMs//ncsXMrDaPhViYNvvwPaby557U3D+eXdXdxuX1XtHXTHqZotVzJxuk/Pr7w/6Qqtgj7/AdX5 lyinh8IzZESRrTIUBQcP6zWm2JAhz9SXn4/H6UiU+3kofMjBY5jFutiD2kdzvXjHZj1s+nC7M+kK IUxDe7DfBpuOEJoZaVuVi6uzIn+VDssC9twRPHmAOGnGjVOpMkqvXtsIlWD4nDD0JViuHUrdNLaH jGVq4jRUESBo3DmSXm++f9AEHO+kbRQ/PJcDWj/W7r4dW0FCpmeQ1FX+suuTlNYekj8bzviz1cUr SHaXQkjzNTsRJhOMxpbUmxcFkJF+MZjQ3RmdVCUjygw68dcHMZ6z9O11cY0o0u5o6B5eAh2qpiPo Lk42mS355P616+lQW9HlOo4c/IrRkS+FAHWdv+r+xMBXOdTJ98jH+wiSRCKfmoWTaonIKGhjF7fv aHh+3xdaoVIFGm8E40XX6qe9BBOl3ivPpe2VdbqIKyCnjID+GjNzZdPnpmnTUCMaZ/09luLRDfSZ X5V3KA+wAAAgAElEQVTDGhpvKDXmbZvLHprVOVS1hGkKacTu5bWkvB6GiCZTNFgKTmGJnXbB0HHR GEn0i8NGQ5ZvRQCaDz7pCR+bEW5Y8nc3q4dv5XWu8qU4dgsI/ZsbymVSkR/KTD5+CabECchcRHqX XEwr0R3fk1ykh4gQSKIs/AgVqSC2kiApWV/0ENzIsDHocpImlADvESIMthaysOD4aHmN4kit7ti2 8fzU/D3qkwOsxocyoo76bwlyhK6WTUxAfQHNrXskxSNXCisN1NJClbw68qhhRZEFoDSR9E8qxx3b n06qLpVVf+1T926qOQMCqmGwE8Cmtr1DHEgu4VduDL3JqidQX2VjlMszBBwXbywgb8mrAQ4O9kU1 wfcMQqpKdOqSfNAYxQhxc+u5YqQhDs2QhmAbrz+q6/D2oT67/uT23zq3caSMlMv7qtONR+yAbDqK cfQwjxWxxTCOsdQ+FoGHqvVtz1+UkD8gG0vsGIyahZXKEU0yqwq77cDuYnZ5XB7mevU11LcPoBOG kMJBAOpSCL7bpFSJ9Cr2F77DIt5DkKY48kskgQWtySrbNlZ+pwzD60KcVkVaBPX0X5HTcrpqaBzb 4bM9mmGLYLX9jLrd277W8ssI6MvkeIpyCs/RYl99NZL2q3dYQ8cVj/ekH69cjpHP3qPhg0h2s0su DkNdW8LtF7PSfYl3d3rCqCvupEaECd2Vgj/G7g3Q3uKMrq+LbowxgwVRn0cuxXTzHtv0EKGbIuIM xq20lRHXkrSVYg63oi5ZCZ/SOI4SHf273m6JEImlOJGtAjuk+V69R3Tgo/0DHL45FtpCsVrh/Mcf gPn7jYDZwEh3aRcf4BiFoz/8HRJqZt0hzRuHDpy6hK406uhQpk45z+q01jf9TsoTTJ0XlCbqqovW 6VhcjhiWdUqWnKodgvN21B8H6vJvSbCVOrdwzyywL79/9Ot8RSbePgiRTA8QJaNOrE9LM3CezZGf L+H6E4TTiQgQ8oMgRuHqQhpid1bd1v9aR8fwd7FYocpW0CQzklCYjjCeTGS6sPBaHuJabnik+kfv Jicok4eo6EDKwR1mHUqqyYjsgRaV6MVrYGFSNB5H2ROMHSz09du48OKxVXJtD0VPTRuNJZVZixlM MRc+Hkg+3YoA2ALT79x162CFCPrgb1CxP5WqF+TuFTMELQFx7vR04B6M6MIH4kR28ZAIAtR0rhRr JO7ZUA22kknmMHeb0M2zYhDHEt5peQEk+6IcS/uY6mJfXOAGxNSrT8nu9nckvfryfErlr1Zdurb9 WsqSh4jicC0RnbMPmC1nTH87GoWIYXZN3uKwukiKppSdYdATZ/l3wkH7nBJe9wGRQRyKuqR9OGx5 HEGMpOE4dB9hOoYXxgg4ICIdw8nnaKQhm4zqQtQspSl7x9olka9azlH8+BdoSv3yIYpj5OOpHefl B/DjBPH+ARJKyHT8HaajBcHKTiFzuwQ/rHKRxtBr3+96qNbDaK8xiSD5r2dVNO4i97umMTxQEEDZ llXjofZSGYhxPfWEqTYnXw+iQFY4gxFajiiLptD+DO38PaL8XIQI5fiuhxXbT7rhG1TAqEVTJgH4 fkbD1LnwrrSuhBTKDYrdDcRYPqwqBJWWCKhwAjhubKWUmY6yxSVOMD1+K+/VKPa62tmc7P8kLYYq ure1L5FZTyyV/KiE/MKYwL1BWVXr0XRyB9aHGbLarfUDWAh22yZrF6bglCkb3dAB9wRUGWWm1JoB z6iImxWrd+x3ZITEAShS4ZQGb/uecq6ERaIYSRJZxQ3fPrd15aMy9Zr4et08yMFHdwnQ2P79Jxth XTfI4OOiLi7cqTipvg2iv9ntZE/oDtSiopaXyRfQ2RnaugSIqchUGzKlG2kRoS4SZzLWJz8Bq4U8 4I3jYMVBpYwiggDhaIL0i6/QHB3Dp06Y60N3LHvm+WsBve66uEzo7PzB5Bo7QHT3da93umtvnuUm uTye9MPdfp/6vjgC73xvgq79jEg5n07CZV3yltjBQcUeQG1bW5h+W019oGh9ULDZcLBD195yjw9N JgEx6jLpHpAcADyOruEXF3A5l1GT4Np0XCsHrRdBM8oVoinLkAEQjW1UbDj6yxGpH0odxSC1oRbF Up/OLXkDx0ksKVIayx0EXOTUo+d9aNjaA9Suj4J6Yloj9loB23knGJUyQu2mkAkmKjwm/k3rymCL dDyWIa2Mjui7GYWwT7Inb/KrdzYS9TEVUw2CMJBohxESf87oqCd62gnXEaLYTk0ivsRroD4c24jY +kP9rjRJ4LPMyvsk3Crr9Ou62bT3hKFMyg6ladtuLnRSgtvueID69p5dTvYm+8QclrMONzfMXsvp +KX5vxDlyKDf+pl86JM9+eqjsezixDoX7tCrc5GJYVpSLudCQuUOxN40+Xsp2RuEqpS0BSXQri6w OH2H2WQf0eFbJHRcYYiAMszUv99yNayROekEfhTKhGg57o6yf9+YLJvz1rDXS6/rUkJGmne5bxbP 08ioRFAq5K2LaWpTpsa4UlAM0SJ07ZBYHp0/zxGjaAK4lS9RUuywbYq7v4PKDaCjCdz7OqstY2Tm JWO44e+FPOuc/AuC/Eyqeolhqgc0boAqHqPe/1rcJiNfiRb9EK6fSAooUZGfwbiNqLFSn79xQyAe YzTulRm6iU503KrCaUtmfSvzJLkZyfwUEiZlAG2GaWTdeUwyvzYy0o5R1dEolGJOoR1kJsDo4BjJ KLXNz4aN0J5gPMtlJptSmqZI0hjLxVI2DTopvna1yqWdJk44I9GXKh3/xkY71tGRsMkUrp9HKbpm xsN4MuoarblBb9A8RlopErnW1TJDVTVyPukoRpKGV4ipZNrzR3x9n+bRLEnU/kw6SH4tDusy7X84 dabjQj0hj0Uche9jcvQW5sACwnwI2A6y5ACFf/lHtH/5EzQBYhnVdQ3xkFgQ9cvnp6K6unj3V+ho hIQP1k4ZCmdNYu1pDNsvYTqT5YXszHRsLUULr/FZZLe3nCQ0Hm1Ghl1jTE3OluxzrKD9BP7xt8Dh l1gKzuPDZTTK9ItzFMsVvHImsscqGMM5+FoGxDJk4NItnW5gh1wASa0PB/bzHLw3v0VN6kpdIFLZ uqonsxGTCcKDL+BzshHxy56H1T1LsvhECtuDFygcxCO4nEY0mHk5lIKRKNyklrx7iePFZ4Rk1gkK 6dVzkTMy8x2Y0Mi8SF1V1oF4FDPcx3RvulZScLpN0nUbKeowEqL0D5vH6bRovfICf2cVI3ppGssL 5JR02WRUgyzPLb+Q3LzWyDEYkfWaXMProknk1WGaEh+ZbH1O208d33s04nMbSzN1XlSdRhidbGyv PS/u9Tm+aoe1zaIdOqrnKqhs1CTsf/MfYhCjN19DMfL6Swxn8b4rv99gXd+VTLWWHajEKA520iJE 6ZOVmKYRbhXvQU4t9qIU/MSwNaeupJ9QZSt46QTed38viwo7KmmCUHBGY1cA6CcI9bSY7XSbkj/R 6Bg6PYI/OYTHRc8EsBdH5IJhad6P0cZjKWIwwgxCTqkeTJ0W0nPfDPPQ/ClHJhaZN38D5UdoZz8h Wr0XmWlyn6hp5dFBdpXgXe8uZGPqV5GHx/T9hqG4PRNyZwuT50uav6m2rRuA4DqMSuOuWd6HF0Sy 6VllHE8WueBYZSWbED9DSb06UH2t6CC3n9DF4Pw9D5MJhRh9FHQebFWjJLeyILzgpbBtMz2XcDvC HmKl5CcGAVvbLNa16z4ICTTwheLj1Uo0GCUCDDku7f79lK/cYdl/H0vY7EFJqskIyfFXyN7+FuqM o6osH+UmowaTExLEjIUxLFyuHa9jmkXH1JQlmjCQyI5DF4rZheiXU2ZmVdZQF2doKblsAqTJPlqv hSKS5PqScnZdtTYKkPYQYisQnKluPSspzCk+EvmwOcmuMjZXB5O38EZv4UW7x5gJNYJtMr5NPzhG TFbV9r16xO5DWdCU3qZemB+iaiqE1UIWk+g/tY0MVjWcM0lnQb7X4G/phJlGPcCZXN5cB9fs+HRI 3XtIymSkh49pWSAYJSkBDUpGtCRhOlbxoY+Gek6TbYHxrzgawhGCLVK6p6LkEdtkmKJbFQfiWBxC ko6wFhG8zgRoj4kx2iHAu8xGn3Zz7iuFhFasQoStNvaKEdsA+yfnsORGvBYZWYKTQQRv7wg5B27W RoiPvdO6jqRI8DZOR5cmW28bKRXQCm1VQjWp9PtV8xna2Sn8urCNy0UjTo2tSP6bb5DuHyFo5zDa QPsR4sm+tBjVHG5KzMm397XUDhY6QNEGMqz1yG9kxDxEroX9cI7FcoK0myp982fRf17PNWhUosZk DO18BcU5j/OfpE9UBuOqWoDuhgNr41SA+2EU9RTPmagnCNbD+2QBcEZAfbTiUn9NgG9LXq45AKRS 62iOTk0iGN+X1E42FGlKtthmr2vVkzqJX1lHRZa5ki+maRuxwOs5VzweK4i33Zu+f1WckxBKozXr vW+Y5vvyZ5+4w3o9VuUrlO/+DPXTv6BJRpJ2sUGXWBXtOjGWG7DxnUZsYnV+Dr3glGj20nU6TUoJ /tJO3yD8+g+ImyUi2/whuFiShCgboGAXnmiUK2Hpz1WI2h8BjIzqrOvK9+Eo1/KKZCBFALjPTWy8 uxEUZ5QYfPe/or44hjr93i6gIke6x2qf5d7xdXcheT6s2ShjU0XrePesGNa835cGbQ7/TD5rAtj8 6jcFfiQE1tNRIp8br9M6qkj6WnvaDKOePsJaLJYdjeF2iaC+IngXY5Qo/YWdECAjOKa4dMKzi5lt hr7FXq3D+hgtoee0Ilvh4mKG+SqXMr3jR6i5S7IM3YXMqWsnsmysn6F4u/VxGhfY9OhI2N+U8jBl gWVWwCkyJG9+C/+7v8fo4BBjcwEfWsZ0sZIjgm0OQfIIyomxcAwWJBhyYo4bCH8pYg+cR3B8o5NF rIvVPDq0h3ZYvYSvXcQyCkIIm3zI+4f7YyrALARQZpol93DvLdx4Ap8pYRBJemv23kAVKxSz90IQ 5nsyRe5TKYvXPI5z7iPQvqK2+/rMPe4drCRzRRqGrcr1FU1p7GeE06WbNsULse9NJTp7qCjYqpoG aALqadnPzaaQNhWkE+XXsIr4yTms12bJeIrpV7+FUZXIOBPrUe/+Av3+zzLWS7EyJ3SDSwWly//e YiQDZuzVIqHVsViTpAEswQexVMHCN98gHO8By4vNHwox1aAioMsWEC+EYeXOlaGOVp6lrZCyMkVQ mix4RlbGh6KCvp8IDvaQS/gSniEMeisdbbOlQJQ95fcdufU+ZlU7u8iFfCdpD2HDNpFq11YKWWQo Fgiz91Zx1ItB0gXvqRntwwuTR2tZ6uVXekfVc6vua/3907pzXiwP0kFIm9kmNReCaId79dCaTSF/ OR2oN0ZsCWP6ul5jzj2lgTMzWb2+SxDyah3WNkv2pacj8XiCw29/J//W2Up06MvpPsooQpvPgbK0 Y8w4d7HnkN3j+LKjMo3JVlL5kmRCoiNPlBaWQQwzPYI3OYQbJnbhdU3cvIVMGyuZKG0rYbZS5qKp c2ns9Tkiw7c8LlbUSieG4bkHqRAsh9W+X2LbD639nC320kdaVBRluib/TTztumNJAy2xElJUrXqF 5Up1qQ6PzftNigMxuTaGkSlIQee0WnhNhrCcwzhzKqBBcco2o4TpFzDBwy3o7Wvugehd98X5KEni TZVqTR0ZHM86kt6JcZOCUBx6qZdfihUL1aOL7PoBFzYFVTIn4S7R1at2WLSeePYanJZUR8YT+aLx nIvJHrK3v0G1OANO36P+0z9KCwmrVfKanhpwl+NL5U2J9jnTNj5neRSiqnyMnBaFO4KbToT3xIeH 8slWroVOiMNYHYtVeZvUTki45RKBKRD5RqgIheBcIUqSOtNDBKOPnJh9owQwGZZWS9xK6jJtZaRh F7K0pQj2cbkStm1WHaBEVRbisJKAbVe+lfcVyoUHT5eI3AKmzbFazkB6mhONhDRqojE1IFDrErHO rYYVNOb1AoZ9i79A3ewuNnye+83ZGejDPzw9aOMUtc4tttVVAXs+18fouEsVUjTsCawzkqqQJHRY VCBVd8KuPgmHhQFoeJ3S50s1nmuyf4h4uo+WGFK+wo+mxeqPRiItaVFxPITUfrrjyKzLvXxW0ldI oFyuAaMnVms4ep5NMNak6EygXnkIxiRCeuvohFW01FXYC12ELrBSwFkTw50cIRQW/GOkRJTjsele i1DOPgk0atOg0nQ4nZMwtgJ2U75MjlI6miBJRxZAV0tM3RwJR6CJ/I/UCmRAV+M08NUc5myBItpH M34jLT1srM7HX6Ms53DrXO5pM/0WQfB0OlVDXKvtKogPQ6+43uhgyJRnusYNw0ZIrgD4jLz6qdZ3 MQr08TgE9FklZAtPP4eTk4PuY6/eYQ3tNTotplIsnceTPXzxn/4L0r0DFH/5bwhWp+J9fBnj5Fwe jdW0AthzvFhPPiQGQ+5QmNgUiX8TUUecKShHku19jejgC0Rpp0JhIG0f2ovQhBM46f6ggZhRjobf 5OAMWyIby8aV17vRuGN4//IF07eDSLGgSymlQtbpapGHxu+n41gW6iLvRO8GGNSd7jGxPLqoxo6o kgGoMmnZHqZm4UDeixOvGwTNHPWCxNsZ6tEbcVpOPLLUFKEJcKjE00vuOGtG+SZFfKznfQj827fo h0bkgjtxRiT7DIfDXrdBjH4aD0F/9jAyuiXznZQKcVZscbrnrMjPDusFWM+Oj/ePUB++gT6bIlRs jL5qwsom3yov4OiOxyUDEnw4JG12DkvkmdlIHaSo4n2Mjn+L6PgrBFEi+uFFtCcVQYfYVhDDk4jB AruGqaXKkXoVQtdIT1thQrTBGJ40Iz9c9Wi7BmqncNtaKX8zSjyMklCkqF0OHP2Y4jBTTF0jcWpE rtWZl6i1e+vhohelVqPg0ck3tfQEtukRnHRPlBtID/FcRjpNlyKx9ehpqA/OVopI6yGRh+iXvc42 +KEF7/tJUsS94ti28my38TANZF9t3gHqrEIyMmOzNY0OjF+/Kqb7tr2m6GqXMfIhIVO+LgmmbUwI eGSrl3bCdW8OuVDBcDaxA8QjeOO3iI6/gzd9I2A7FxdBazV6Cz9KrHzM9n1rG9H4GgXagvGGk6QT OJReeWDbrn5ZZ2ixKzYCjxPydlzB2NYzqO78OXNSi0arSrj1CpFP2R+rgjAcFNMrXA6N7x3qCsGq QF7k0MsLacrWpsXk6A1CAu4upXwDtI4nX1Zk72mdl+ngkLVKwxOsAYm0ikowKVEIFc00S5Fgqkim vGq66UAcMuxwelXU9Q860hbEBnKZ2HNPe/UO6zVVCm81KddV0hy8LbfbG0cl2enQW+H3YPoLTbs+ mslbtF/9A8L940tYT6+ueq3JAqSGusKidlBRsSAYPQ7zaEevWvedYCeUqaFDpX4UnUSpWjgiCHYH FYlWoymWaLMLhM0KKqb4Xl9osNGaVKsYpdRKlDOGx7UDIlqY+c8oz85F7cE/eIMkrnF0yBTax6o2 mNUOtJ/Cjyc2XX7C59DtnNT2BOmnclzEpoqitHihEFRtpwV7HQlf2GnX7joKs39DlYdqjcf9KhzW dt/Rc7V6PKRxYnP0xXdQqwX0n/5rpw+1Menro2ZRY2VYbjKVHKCZfgl/cnDvh4Jgf4UQ74uu3Oy2 UoV8yoUoQnhOK6RGccQyHXp7WP3NRkmfUfYOSXUugnyrswat59rhG4NrYZQghEr50QabokRP4ru4 mJ3BX54h4YzLCPApG9SMEMY+Ur+VmZWBo5E3xMLGor31XNhWuxUpPuZn1h9amphVg1VL5YdNtMpp 1Ewb2XBNCRpWBSmLw8nSVvH0/uf2Kh3Wa6wK3vm62NxKFjzZ5d1ABbt8AcPpI3oBVyKsbesbaYkt k639Jdy9t1Y54t5GsqkP5ZHmwOkz0SO2JN9kjBpsgSErGuQVQe87sMw7TlpQnCNSHFDBwalGRn+J 19f9eHRrvryPDGa/IlcuAn5BAh2lcJiOrxYIphPky9VaRTT0gFHkwGtL5NpFzeiwkzN+anMGqeJG OfTxU8VewJFN2T2UoVw6plaqjX0/JB1W35pjB8taPt0n6bB2hbyfktNSZYEmm8NrCiSTqUQ1/Qpi ClNyHh6lbaWytqvBFCg4OGZ6BGf6RpQqP8YkmvF80UanRrodKvrU95mpmovZ0oq7VTUbs++28EQK h1LVagVfW2a1VFxJWuzu6fAwlpzaoqJaqlVM7sah2RsbTyZo2HxeV5vRbWupEHu/eOyRw+iCcsos Gjyvw9p2Xr096ufIZ3BY9etkkUldoA5WP7OAFUb+t27p3O6HY714h7WL7ftqFBruYdJTxYpUuUDU ZEj2LMG0N+ICdZbB12qn8B9/1rIqU2t4ky8Qpvv3bllZH0siBw+taqVi+Bh9greZyBYbH+cLGx0R d7vzNGRGS7qGJ+qsg3vV1TF67J5Oqde351QjNnv7Ip3cKQuw19B3MU4TIImk6iVKCRS6E/39flqs PTBnPEYchaprVEJ4fT6Ywhmw5fttb60M8sSfZV9Z5LuPx5FEWL2c833tRTusoUbOMKz91JzVWqpj NIFJJ1BMJwYVFC4eATLPT+CpaicgH5hGWNsiITM6sEqev3TEVuvAD8e2xeeJbdMm8jGRCrkJoahT dEpM9sddgVH00tsWZd0gCjlFhgA8CaquTMOWde1BZk1Sg2xVNYipjZ5E4jxl1qRMVGIBQPRE128h w12ZgvJ3Il74vM+qM2iet1ObOHKrwwWf+Nz6+0R9r4IChJ9ylfBTdFJXTDhIbJm5TEpkOthwVJIM trh+VzJhgvb4O/jjPVEYuJ8ZNFUpvXqiThCEiNNU+gmfRgfq4TBJcXRhLKRY3XjiQNjcXbqsfLoo dYO2zKEWM3FIjK7olCfTiURVTO/omDgot1At6qZFQdVX9mpSKNFxMfFTRONWqphSpWMfNnXEXGBs FNr6TCbx9INdaXSgmtXWB+SyfUzUNVS6eMpiFTErasoL3WQw9eeTcVjbRLlP2WkJKzhbQBcLuLra +mUXbVJ3W0ajX7XWC2DGhwi++TvLt7r3verkjHW/vBjdPM3joSmZTJVPam1tieZ9lMmYesqZpKjV SipYJWMfn+OqApkVqFSNgLr5gvkaGw118Ri/5XqScffUb/JcVLVCUzVwqkKcWnv2DrlpEEz34chI OLMZniunoKRHczhBukWDnJ0K5DG5z8eWdwf3twfmn2pTui+z/VU5rF+LibMqctRnPwHLE/jd7Lx7 HSMaAftfIjj++qNTOC5yRndPtfuzkidRZQ8qPaDGGR1QG09RN6WVFG60TO1he41MDupbT0TZwrbl rHd8FgupxtIXOLioCRq3bIXWwtcit6sW/+4hPmAj9KbAyAJkKrdw+3oMPFWiKRUqU0qTtfC25D2f LkVzO4c1pAZt2nBeNj78KhxWj2F9qka8o1zNYM5/hJtddHygwe+7EFoUobadiVAhXLTErQ6/hh9T FuXuD9ywktTrrj+JEeiu2FjrSPpJzXvbvP1Qi8WBE+9JWsfIVLccgdVA1bnVv89WMEUlVAUrYBfC 78ag8UQ41KMuSzvyi1EBhfs42LSLmHiXmrpCk69QpyOZJSia991cyKsDHLoIjI4hu0BTGrijQzjJ VBqqZZN5oB7Nu1rvnIZif0/Flv8kHdYnw2C/g7EqJw/u4Gd9FwrZwdLw7IUizCdVwq48L//4Efzp G0R7b+7srLa11Yfjwp/KHFWirZZWzoWcsQeO7CS1HB2gDUd20C0rqZzS/e6PMD/9GWk+k02g8EKU rQMzskqbgllx/FWRY9LWcKlT3fcdDo9fl6gvTrHKKxTTyXo0liixwhWRRjv01nYn0KE1tR1yMeUM QHUBvQhQcNBqegh3/yt46f6T9Sb2xudAWmq6at5LLm69WIc1DFc/6eiKeb2qUZz8hLAu5AHnHt44 HurxG5lf2KgLIToe7U3k4e/38H7gaTX9Cs5Xfwt/enSn9xR9I9/DaJRI6wSZ3nbA5hM6LUJm6VQE 9qjPcMOsg3tZX763Olo2WmDaFcYGTZGhmp+jPv0Ad7VC6tCtAKGuoYslqvMQq2KFSpv1WHqOVN00 CwmPdq32QMoEaSZG5UhMAibiruBW9jyyZSntRMTA1hsMo2WPk4gMsrJCEmoE2sCvzuEtFIriAk28 D8NmdNHtsq1Sl1URXr8axK609NU7rJfq5R/UujSE9EwVT9GGqaRlTpggOvwGTb6ArgngniCJLssQ MyJTXgz/7W/hHHwF7x5UBmcwcJPNqk+vkW/HyfujvTWG80uNTc6gQqrKRWmBTrguSqmumjJDwwjn /D3M+c/wyyV0GokDokIrpw45HG5bs2HaPn8+tci3MjTpJGhJ+TAIRMyuhUsJafY9djMerYJrK6PM RDd9GDkS0Oeo+S4Vk/fn6D5HwW+WUnBRTYaGMxujRNRPc+2J7rzzyPSSq2oQD7SLPKC9WIf1GgDA BzGpaHmID7+Aqfdsxcrzpa+QGlnLDxoNSY6KKuqXjSPQ69GRyPW692C196OkqGvEqIqs4+3m2acw frYBdaZ+oYkUcl3CLWYIygsEaom2rlC/O0F2cQGzOEd78QGaMjoklKpKlEWbOLSyKP1UZMfSElSX cfN+J1uAIquHbIKuCflwutCO59NSIizx9LrHl32K0tPoWWVVvpYcLt+Ugu2VOodjRiKl3ZI5r33b 4C6tVo+/Jvrzfqzq/DAg6Qe3bpzk9pDkTUT2gh3WJ+6ohos2jLD/9usrvyOoW52/R33+Aa6qrDxo ZwTftR9DH32HIN27n6Y6d/m2RZ7lO9s3Xo3xoaYiQ1Uiv3iHSX2GMQeVsYvG1dgbBYiaCE3poCwW 0Pl8E82FEUfIIhDum51O3T9ynQ/bSRPi72JxYqQn2OiY8tGXTmvw/c5J3d0LCNTL9J6tl5Ab5uU6 L0gAACAASURBVJLzVRVCq/hylOJCLVFKVD16ImDeRoDreUyPMBGpd1bjMZ2ytpNzOp4hN1IWmuQ1 nicDX1+4w/p1mzSNfvgR+PBnpNkJHJbkt3hXKj2At/dFxwO62fpJJb3ygVUo2DyQr9FaVaFZnkKf /RW6LFD5DorQkj6pwTRKU4ySGCry8fP5KVAWMBxX7wcySaiI9+BwNh4JlJyULLwzB4nXO6XrLfIc icQqRmOcSTG8jdLXef197Vobb7zziduiaQq0qwa152E/drDUS2SVRkvxxSfAdR8bQ6az6iWXLXZ7 uQ3POqyuVayfbI0XbMOQ8NdkAsQ3CtWH79GuLuB1Qyl6E62r9BDm7R/gUUXgDg8UHw6KqAnIztH1 y/wXk/ie04hXefkpkuI9PL+GiiGOSCpzoS+SL1zwITXh9/Yw/d2/Q+N52HvzFvFoLCJ+FDBNu7RQ ZRnK0/eAYeq9Adqvsz5dJJ6uHQvyi6PqJKxLpTHiMNKtA/HnbO3hox3c8Lk53eJkUaJYzFBWKcpg Ch26d9L4/6X2FJE3nz/qYvH+24Z7t5s4HezAsV+4w+oGujy5KNlLMBkAUebQF++BMr/8O1YQ4z3o /a/h7n9xK6bRV364k3ECyidTca1y+OUcqc7g+47MU5QuSzLTR2MpQFAFlNQJOo3pV1+jiVMcfmF1 7Sm57FcKk9Tek/zsDGp2ZtVe77hGKeBAYElovh3vVAooBNPZ4iP41OXPRnhh8ntXfr9RhRj80/fQ iuCBsePoqXiQsGo4ghtbfOe1r4ceRxUOGDG9kEWleO2wdl3fC3ZYFicYgm+bn3/aRgY4y+9mdUGZ BgHd+4JNG8Ro9r6COfhWhnneZrxfYRiKpAeNXfL8ek2YlXCYutRgbaqQL2JYfV8AG5rpcJgO+nEk /12tqLmkJBVkQ3hjHLSVQknmulT5LMokA1UpadOhTrfenY4yIdqvrrf+W1YP6WTYOG06BzU0Vhip 8sBIgtfDWKuP56gGURcFDPlpJLt2k4/o3FqTw1T8iQcdE8cKpFjzuOthE2U91vtYp9XdI1Eo9RHt HBxrXrbD2q4S9kzcT72nkKbrEsXJj3CqHBUfYtGds6OW3IO38A6+hjfev9OxBLQMSF9wRa3UDgX4 OGmP5zCRfqkLSXs99hnKrEI7hkqXtfQE9i5GGQe+o+CVFRbLTDSrKBi3yhTyskYy4jANH3EcIQp8 HE3H3WBP6xwKx5NJ1ptK1TUKm+wK8CO4MqjWRet6KN0QyvioOMW71ogcOsQNkN9vEMS8wiCBiUdr +WA6WFq9nOPdX36Ac/KDVIVbP4SXjvBmmiKR45yhrnPkfgI/3UOQjD5SoPFuJiTYJ9zX+Fzmuc0I 0nR3P+yLdlhD6x9Uew132gNfr3WtGlyKvNaImUAQIRt/Bf/r/wXu5PhOrPAet2I6aB8+y2R+Dc7K cGJzxagig1fOOTobZvJWlDyFghAEkuKO/GrdXlIoRlMl8rMPWBUKXpUjbkq8bemgDfRqgUbN4R69 xWT/S3EU/ZIgw/3g4ACJ0974bPEZJEYV7B0iHo1kdBWNVVqqEZRLViNXCGWW39XWnFw7iCYjpNOp VL8kcuzOIokCJFGI9/81Q3txgralHDbTpERGrcEx8Kol/LO/wEn+/SPe/e1rfpogQWYV1kr4c2wT iyLr0F+lw/o1mR/GGH/5W9RMC9/9SUiPbTSF/+XfwhsfCXP7xr8njhMEokzAhcgwmxFJ01i1hyfN BjvqQVssbPITJLeqSUgKWK8QLN9DNzVaNxBJFul17I3kWs+H3zI1s/wocptk2g5aBL4HTfnVphaJ ZBprDLVyhZ1OUuhl1VEXAVM172bAXTAqp0XA8VZJIve3t0YXQgQlNsXjX7YONDb8PfErO2Xmsnl2 ipGIDrbSoK3hSlRG+Mrl3zcV4uwE1exnGFaHvY9Tlb2r9ZvBU5nVfuMswxyeN0ZIYtzA/G0RrafS gL6vbUZpf+LRFR/bIERy+AXS7/4eyzJHfvYOOpxivP9WIq2byqYbzKqfF2dLwoKJDAYEPJUJBtnU 8LITGR9mkgMYjsO6wekaTg4qFgiqOdpwAsT7QDS+xD/iMag7L3NXRD3U4kUU45Nx6sSTuGPLmLLh sRuoPMdyNkedxJI28m+qPEOZZWjdLvUmKC6O/+57ek++7XX4r78nl0v4w79XVS24JZuy2ZLDVLXW ZNWTDe/ANRpBnaGcvYOZvhWVjsccpvocWCffk9rw/fM7dOw+y4pDY/7IB/7lOayek4FP3wi0+j6m b79BOT9HY3w0XnKnEVLisKJApvIOF5tUsEh0fPJ0kLV+hahewtclKs9H2ezdHCXWOZxqKRGFHh3D iadbr6dYVSD0Di5mzhDkRBZSBqhbVVfkMBkYqinoFuVQZluzoHGBrFJyj51GiRoDaRAqX0mLDSM5 n05/NMLe0UEnzXz7lRIEJxi/NS1s63bYadcSKHTKEFaLy5GUsmGVUiZz2xZqp1VQ2qAQrMwXUimB eFSZbAS96uljWT+d2/KgnKfDLbVGnpedNDbnGdrf+dvNhy/NUW3s0wfbty2MInz59/8R02//Fsvl SgZ53mQ9KTQgH2lLpM32Cz4DdmU7rVG7oSw+W127Hn/jObrkTzU5Qii4BNzZR7f92bs+qtaFqjQo hkxeFR1A1CrpE0zFExD7u+o9DGqUs5/x4c9/gbu8EKdl39vYiiMrhmyYfvMV3P/4f8iYKm9wzpZy czVGksxE1Ep3f0497aEsSpRsi1K1+Cw/TmT6jkydyQupMvIYVGKmE2NRYObECEZHGMUxIl2s26sY iQkPT0QIH5aysmG69zSKBz38LW9uh1cItCEbbzc6jKOmtx3WS3QMT+nhX1afoQ8vjOAFVLy8WdiP zoqRFauCdte25DzuVEVeyqilp+8XdEX+Ru99g2rxs5T1teZcxW1Kho3+qsUZguUZ4jqHF7jwRb1g DOMxPRhEEkaLzA77/9KABE1HqoEVaQ2iS3XLeYkT5zh6K33cS8LkXohYkxohpALBmi4fyo65l/u4 dS9ZiWX0Iy07nGBECgOHVXQUBq6rGgrtcg63WMI3TTe+zROcitOQq/kMAaVwGOVFCeJ0hIaVwP23 iL78HWJWh8sV9PnPaGYn4NkFk0O5d1HcKTw8kPWEzecaptGnhrYrw5Kc/b7x8OqJvkx7ck//AuzS 2KlrjIsljEIpBzPn7/EH7s6czGsJek/HbBd5l6aCaRtL4KQSRZcr7UoHmZYZihcu3sGr5tCtQmE8 VIFV/LRTmQdGJ0NAnukTJwt2QoYE4wlUE3i/8THh/RHt/F4OxhWtMf4VNdt9L0DrhSID4yiNKKCk zKaqePlabbTFqiPBeGP27BgwZcF5VrvsMAgHarmCamqgWMlka0Fk2VBdKVRZBjdfWL0zwecst4td D348QjjaQzA+hEnGnLor98CLEpuyCoXiMRaGdVjPRScS+orIHnURlpzSr80DvCLr1SBt398NDdRB IKPCyTHaiPJZJnHPJn7K4IqOylGZVOm0lyJIY2B82PVvb0uqEjGv4K5OEFTncLvUsTQeVDhB4IVX FiMXMRUZHOJP2rXTh1lgYFMzI6eWo+fpunYnaOJA2FMo0YN1UpVrK37K8eHEI7ijifCsZEoOqK5g dbDkNZxilHMC9IaEazcWWFkY10XcGozjEFEYrM+hKgu0fXd1Z3WjUXN0e1UiZORI50dCLDE4IY96 VvnBpUNm1J0gPEzgdwN1Zf0+IvD+nMOLtyGrV0Nr+LVEVpuHv5u0ovWt1T027jIVjJN4PdFY8BhF QbiuZ/CJiz2MmFjR4mfWuOQSXb+oJPJTBZJ6Lt36sjipLx9NEO69kX5JGSZLzSr+z7WcJzoLT+4N h77axeRFkeBPeZEjqjOEbSOgvJzTkAxKh8XXErBuXBFMlPOUjKNFON5DeniEw1EievAE9PkeaeDJ OeaLOYrlUigM62um4+MxggjRKMUkTYReMbxqGWxBGsb6b4BZXkHnOWLN5iJrjPVYLdWMIIPI9pOa rgrZq0o8UZvVc1ULd9mrcVg2dP60gXdGRHQyHOklC7K1JXdpLbkhwmLKEcXhWi3SHou7do2qvHtv 3EMaxfka90C+94nBDMXhJNoj/YBVNa5eDUeTL6WRs1WDGl2BgypK4HHEeaChl6eoLt5Lg/P469/D aRsZMR/5/TTnLtIcT+HuHaM9O4Fz8j1QWtoOHUTRUKeK3xvUtUGpDRxDbIkkJxdJHGLv29+gWi5l kgQjHj5zfA/+S+nkWVFL+w3nFyYBBf4uOw3VaminERJoHPiXih/dSV6+Fyx4UrVU0yENXiaLs5XB F1q10NT8r8tnef6fK7p61Q4LA7ThUwTf6aCyLJfudS2Th+0eLKnODbsbd1nSUIhFbp4nToSxjbM3 pZKPaQLUdrMRhw96S9ypWMDLTqHTA5ggBThWPjtD4FhHJufNgbH5BRBPpZrWzD9An/8E98s/WDZA XcIjeO95qES50/IHgyiWKTakL6jZO9QFFUQtfcBqWdn7w4bpTE6L0SeLETxPI+oNHsaoilIkldmP SKKnDFX1XNuMzE2EILkmbmYQSaZmr1H037tIatcC77GszX9DcMc68KUdp9KcZmhTRklmeS+qAu35 O+j9n9CkU2nLeY7pzX3q+Zyr71U4LAtqWg//Erz8Q1sPjrPXryzJrbmbk+kF0Fj27VPBzfFsOfw5 7TL+YR/4psqB1RlGxQlKUhbYwM35gOUcbieEJ0wIxkGCZbFZOUe7msGtcgTJ2Drwms3PJay3CGTA BOmijJSCKEQy3UfpRyg558YxEr1ZLfa1TLqofTLaIsjdGg3TKNR5LhQJYbQPNO6tIqgjxFKBsbwY LkfVo4Wmc+1gKbli9jByqnR0dXPd4E2WAM3/j6WyywnUEVpqydtXSkM26SilTCKp4eXn8Ffv7Xuy Y+CJp+xIlPXM2MyrcVifuvXA+n2uVRa2CM9d7tq3HfC1pJbPbVLdIY7E4bBkkNcrOPVSmoOb/BRh JRMBoXQr+A8vX9IoL0QbjUVloVnNxWkJRhWnombg1Bk8TrRxUxm+yjYWRkikFVD1gMRPFSRQ0Uj6 +nyVCwjfD/Dox3D18QIXIqO67PREGPROnAg/aqjF1P2VFfkbjeDFCaAqqFm1Xkg9R4sjxXbm4lKd 7NlNm7/hoApOkTbSfL0xSi03XiDzD4O2FofFfkkVHyKYHMuE66cYTvFSZIlevMPq8+chPvMpGhf2 fYid/UPUNzMPNz4eR3oHOZHmuZ09c1NVYGrmgjUZr4aTeNArqwXVp/lMvZbUfWpaRAGHLiRQ4zfw oxHK8xNJmYOO6a/nJ3CrpeivEyeiPvvk8ECqhMSXivNT6emjmF98eIyAGNEFI1dytwbntg6L6IYM fNINzt/b4ai//T0mb95c6ffr6aLX3VViZMan2imdXV8AGepcMXpzoM1w/pH9V5ztUD6Qzs1zEKZs M3JQ8e/yHAGxtdVcwHiwn1DoGU8DvD83lvXiHRbtU0wDL7UhNGz2LAW72r0pd9FAJ3PM9IGlcioW MI3sSaJ9apll5F01Mr34+c1SMjl9hlGECQLUJkKRu0hCsrvtJGaqbzKaKMsShfIRRB78ZGKnL5tG IkmC9AJ+n7+DU+YII0/+Jif5c5VZlnknbMdbQuyrXi2hiJGRz+RYpQda41O1dR/OWyPjvEQXa41D UcbnWOgNs7y+ckUiwucWCLQjFUhDjbLOySima8ZFvSoR1tpiWxu/iLxugL1jRNMD+B0znp+fKEd0 3xeVEryMFUYhrnZpZFnVMiHcqwtwdEfWVlI5ZYT92CbaX4OZhc9lL9phfeqjviz1oFmD7buoC5Zj 5SOKIpmTIEqVIiNr2dPdkdak0KKoUOSFTMJ59uhKTFhFsuDISqe+l6pKBJyE4rmo6WSt4KQlX5Jo KmGIFvIkIyKpjiVTuOM9mHyJpLyAaUoYL5IWl9DzEapCOFAExUUtgTwo04iKpR+m0oM3fIpYfTVx iuiLYzkvOoo15kaIit0FlFseRPZ9271uOQDEQ8zqLNUazIa1r9gP2PX3xWzeHTy7UhDlSUaBpH8h o7etzUiItTLWzciAiojkrw7obp1chrB6DYdnGBR1LmmskEgf+1N8IWnhi3ZYvX2qDktaUapaHAzb D3b5Fw48paZVL2jGSKAfqikl9yiQ41j5GLbhFKhvoUE8tQ2Kl4IvcfpxQm45VSSkWGBTWonCOCBD K1K/0ZQcZW8pBe5oD14ygTv7EUmTwZga7B9WJaeupJL25eRKkXIQ+aBIC7ErE9AxhEJNGBojM02K BOV3PCtR05tEqh2eKJHdkIbQyRY3gWf1q5LLzoIOqyYVw3HEoW3rr/fDKcRhdZNgto3igmXdOe5h Vc7ZUCKY8jrEBXmvnrBy/txr8cU7rE+XMGpTQbLQm2ucFXc0IYRSe0kUNHYz3HmcsqyQZYU4wJfk rITsSDE+qg7QSXCUU6dWIFFDS9kbOy6rdxx8fVusoBbnMLqVSqITRnCqFbzTP8M0hYDkhtEMnZTv ogwC5OQaOA4mbIXpFjX7+iriX30VlY7eusi1JA1vvmwEXZQlcjNVLbgaOwcYCd13of6ST4CpYCXO lxy8xlbm+LwoJVXE3s2tUbBPk+nzOh0WjTjHsGz/KVhPY2BLxnWZG1M/GR4hvWjXH2vYivOinFXH Ym/yFU5n30uVjotOlZVMZiZTnRcvNIJu5h/1oLgojQnQLs9RlDXGx19Kitgsz2CyOZZlaVnlFHtT Dc5/+gnu/jEO3xzhYG+8Zp/Hkk6xdacVx1SRLOF4Am4TG1s0nPyVM+xDGPjYm47EOTFFV9lKsK26 2cPhdATvlrFfvfWpnURHOxwJIy7bU3nz58Qhq1mpMF8s0eaUe24leiOZdE9E7YaRF57ENk77+Tzk i3ZY/SAK2nNXJx7SRM5XFBQqKKWvmXTjYjyyipa3YQd2LBjVB3isl7HdrtUMiD8tTxHM3tuR7qZF QOIl210Wc8FkmCax6YaOi+O2FFn6QYLm5EzUCuC2UPkC+Q//CvfsBxk576djuEEIVynoxQw4/RnL 82OoozcIRnaatIgdJiN4SSpUhXQylQZxptRM21r3As3JCuDAUieE1rHF1EgHIYGTKeyOysVaXmbQ RlXUbNLlddlULvTpWqgp38i1WuzdQaGURHu+e7tqLFNDYmXG0TKhp9oayBKqHJpfPNeOpPvY1g+F 6ecEPrW9aIe1TT78FBxW38zM6Oo6uZeeECpSMVdkdK8a0yKZmivR1fPdo54gKgqjbY0mm6Odf0A4 +xk+SaL94idbvFZwKP3cT/AxjgDsuq5s5bAlvpXB8R00p9+jXcxQn71DuJzJ1GtqbAmm1ygZogqz En6SXlzAjWKRDw6/+BbTvQNMDg+l2sZeS58SxNJArOT+6k7FkzIzVLUQrlZdwud01I4uIKkZ09mB g2r9Xm66b5+yQyf4edFBZWUtjos/k4bpDlwnYH6bai7fr9cwY0rNogBJr4YTrRurXR9Il3UtjeIy LeiJWD9C65D78DwZz4t3WEP7VJwWF6TtFdzNO+CCYmRFwP3m67Ua5nZ01/NXBdkOQ3wpRo1Alyiy 91CznxDkFwPCZicFrJSkXBaf6WqJXJijMZyGjdNUl2yEG6UvltBFZl8nRElXqnA9jUp+zuMUGVp+ scy/d4jou7/F3sEB9g72r9xHGUrBc2C/Hn/FoZ5ZBr9VophAOmsDS5uwg0+Zytn3E/yLUWDTSK8j HRYtDD1J+Qo4MqVHa1eiJAuu20qgOPUbGtn5+6qs0LAdqa5h6nqt7eXJyC9HUlw2Y3s87hPK8Mo9 fGbE4VU4LFspshIfnwrvSsieOz59mYDre5K63O6cCVjbaG1bm/+pTaIOVcArzvB26sGLXGT/P3tv 2t1GliUJmu8rAG6SYsms6qrq7poPfc58m///H2bOTE931nRWVmYskrhg8X2bY/bcASdFSqKkCIJK vTgMSSQIuDvwrt9r165ZHWKbR+iKtcliZqqbDFieVEHNJuC5UoM9WJ3CrWvUmxs020u4o5CeRmPI Lo8DPZ6YEu/x+7OeJy2U1V2d4/wf/xMW5xfvBivK7pQVtjc3iMdsijGE5aVGd8ZIKHXQtoff9pKJ 4aDzFHSu+l5BiT6HfB/j2fvFY004SJ1G7ww/87hFGn1g4/O5d9ud9LLcvoVPQ9bJpt2x9/OM66JB b/voHdJdfj9StaHYPt16FgHrYECBZx+0pnJQafzwbmZFMii7guxOfUjpUXfjymRXT2/dZdxxqEl+ vauxiHyE6cLIpzBDuflVmUUtoqeRnOm8GB3VXSxbG58Dx/5mo2yqz3bw0GvExo6NMwx9GsPiRoGK XyzTNG/HckuqCwcwe9h3YFvYdN3Z+1sOyDZrXP30N/RXr2HbvQB/Hhe/puCgZ3FcBEkijXyJ9+0J 6BYC10VMo48gQF7VKgFJ+DQSNtQuvT8b4fcnpPGhxZuWiKNSKX34cZWbwHIZFJ2/G4jmWQSsA5D8 vIOVljiRppU+D1SeR/qCr8yKpFDjXPQBO6TG2CFxUz41R1Rlmu2K7GmjVvbBUkj4DrM/TuhIeB2I PBuREwKDb5yYKUUzWLj59/8P9voGqGsJ84loef0G0WoJf3kCdCt0uxhYv5XapjZ2lMD+41JE1H0P iwEsTpG//RW26yA5fyHna8rtVmWJ+vpSMsVcFU1N+fiuQdxWe/svjVJ7PpZnZ3KxYYE4DzM0SSiY 2Up7vVdGNWVT/FnVtA98XM3n+H1vFzu995X3vWgYpkSlUkRnBx8E73+L9ZSozDMJWNM6jg7Ypy5D SDRl3PR5lEtRQLXQaK9p9TEdGAYpdhqpefVUEjK3F4X1KFVso7wyAaV2LKPtVeTSUDd2VcxObNgj kbPmJqTyJzHu0fW6b1rN1PV0ZS4rLB0XcWrsrDKO8GxvKDasURbXDeCvTtR542U7DBTb8nMsb67R O55oCvVug45zeEUGt6vh+T7iFy+FefVlAac0OBkDGIF9K4ylyc4mwq0ZxP1rMBNyxJsiiVTdXDZG W0sqovdeJR0jVQ/e53oUoOVQddvBn30UWgZH14MbBUijHhmHr39n9rkpiQ1p+VuG9cHBS/7r+QLv AnoJuI+yJdPYTZLEe3fmj3ueXqM37GqZ4HcMAYu9bqotOMhe/wK/LdAS12Kmwh/NHnnrLBnIshw7 6k+RGMmMS+TOw3BwV+bodluT+RS5lCgIdhOrgjMgFJv9NiOdiwldW5cory5RNxXscqsuoCBw2+CE Jy9ewvJ9VHmBioF11DA3/HsS7muEPTWqRsR9XAyQDFJJHNw+nzHTe+gtmZdUD/2cn4ebqlR57e+1 SancZYlEy64ns8uuClD97vQCAxZOc4W/9158JhnWcCtozflZz2lNKgoT3mQ7FjzfVSn4GF6Lumwa xXn6zuB8WaOmOnWiAoLYE642DRwPBiif58nCta4vUfztr/CrbPydWenV19j8v/8X1iNOY2ghRN1d tuXgDQ6WD1wDdR2rnVxm3nd5wyBQhguc7b/H7Cbf7rB5+4ZxeD9gfut8b0uz31qGqnHPNbojLXPf 4k1Mbt21aTZZd37fdUygoIeiQc2ehprzFAoqzyRgTamo+ftc1/o5LaoNEFBXR4y8nVGL/TFDpeoy NjQomHhXOLIxnAbWHbnfaU1vmVjt8+/zw0/yozrBd6yzOARdlzPgZMy0WwtD78OZWcXf93r6rU/4 rBjqwYDIJZXgHtxmjDrvAylY+snNhxt8vNnyedUkGUyWNjHiJVE5UpwYpPKG/C4LZUs1VbMBSk0y FGhwJfA+987QR89oE3/OGi/yUZ7r3IVk9t3xz2cYqeZ3R5YuNsdtTErNoPWYtFruUW1ngOwj1fSi DVXbB2aGsDZuMORJsQsnsb4eYm5z1R00MtN6oXE0vudt3jeJ95SjsayiXVgQoaHRqhoVH7qOlIgw YYx5S2052Gx3yOWq5RtzCLLSO+qoN2h57PxzzKTY+wMxK99HRgC/foP8+mqMXCYoqSwmztb1WJeZ OaZxFEenQKoEDXE9H61vyK/TsU2UKmqbLtIYQxTAGukg/EFICgsNWMsCrsW5ycWTZdi/VykocjBF KsfRPPe4XWOsey/Sc8yu5suw153P4nFR3eHYlkTwXBspcSEMaErDPO8qhiRDGZje1vk2s1kCJTGc 7v5sSS7I4y+Q8T29Wu/6cJcnCF9+h4DD4R+RqU6PkeICTTrJrKeNWGQY8B2lXfKdZh05RqRHGyL+ 2AjwECYL9LvXMqvounoviyyBQgY+GqCGBM5LBcF5T1BgBu3ERm0vkkAphSP2vW5gRsbFtsZrMbLp WZIOI6k060ly3aLzny5Y/R5SMzxnDv2biY8jDFjzYHW4IBNe9byj1JdSayTI/iHbr6dZLF0GBKGL F6uXOs/degO7KdFu+UG7/7y53e3AhZ+E8Pv7P47KhgjGA4iZWUzf90K4qyUufvgBQRjeu4mU28iM Y8QNx+AgftbVDdxyh9610dMA1aHKg4U63wmcj6j26Xr756ktF30Q4+RkhfL6Ct22glNlBzxOOF0P 2/ewpFb9fs1CFhsBkkk23yurRppXJINIQpqBicc7ElTVqNGIjwlo5Om5SYq/vb2Bk1gIn8CV+fcK WBxPo3Jrksb77PmoAta7wUrfwdewvpQYoWy7j6YzeFhqhhAgpn/eeI4sqdqqVHb1OWva7u9Yoqq6 e7/jMQMV+VLbbaZsabFIEIWGLW+uITOtDK3twTu5gBcnaDY3qMpcRFjXMaUi+U8Dx2yiUUP9Pqdl 3VcPozKTW7chkx4Gh1uGXm8KoAyKhhpBygsJqDSw4JpUR8nvqmv6Ihrdf002dL1pUDxhSWhIufZv Erx4CZmlkuozL/WPJmDddXj9mtaXClb6sEtb6tiyK3NuDKbZLsOb9Q6274s8SvdmWAEi+vJSsgAA IABJREFUGiiM1uzzdfcdfwxSKTyvaXBzvZYu2Fwx1Px8MM7MjSnvqNVOXGgYgv1zyPpraNGVG9RX LTKN4lQGaGcdOPoZdjRHjRjsjGDffW7Lol00NcrdTiM9HsvVKDIQwDSCRO4YGfUkCnuugtNeDnng 6A2hAtNYIdjOx/D3B27VYYQEAg9tnqJwzCzpUy1Dbv7ylY+xrqO0UvDO8P9RBSyuL3EBjCnD7fLr MJrRP3hH+C0u/rwU/PznH62njjBg6f0jO72uYLe5rOc94myUSIkTdHl3x7Vm9rvChlz0ZK1TaYFg d5nDpinE2FXkuvuu8ToQH8uv3ioAUNNKTssT1sln5jGxC2mbLOnuDKcyQ/584MB2i6rppTl1cLYx XDI3COEr+Lx/y/AcObDdtD4WSYowSRSQTPJlyjqMGZQxyuU4kwHWpyYM+V27skRbNajaEo0fiqfn jEqzzLiSxQKdG2EgveOJ1qFb/+X2jZn6cJEuknulldxjC1afn4WMoLS0oUwdPA9eE39k+h4vyPTY 6eLcR4q7S/g7GEO8/3i/ZNY48V+OMRPV9ewbeH2FwDLEVvbuqdDSuC4o5MtWfj8rlbiafgLPTxGs TuDGMdo8R3P9Bv36SlSHyWHGbPv5i/YYqGm+ucbg09o+hE2FUP+QbZnBwzFMEhgarb36mbW8pG34 iK6F0zbqSnV7PxuziRhIeI40gtDwtsar3r0OlILhx4gjQWkSq4SkXlVTG49F4luMkg3Hj5oKQ1Wh pkQMu8WUoiGPjU8gw9kMTWWj9yjy2MPzmXGYziIJpNSqJ/P9abvChln3xW72CtqG/nOfaOfRBKwv md2wTKD7Cp8ziqJbgOtkizUFK30Ix8dOwY2GELxoEzFu/rMJ8JbLsOft73q/tUXZ3hx1Rjw9pkW8 h5vMaithNAW7bZLRaVFWFWxKHSv4mEHjiUne9hbc9ASLkxVO0kgZSJXE2NkWdkUBixpXzIxENDfK CNadjIYGFHZXomHHr01gLRJTrsxKFv3WKEnDjaZpAZZYfmyubV2hKTPZwtPBZ3otLplnFAV2VUsl etRdh6asEdAVetYPMpQqk5Fx3EfSP3WDLMuw22zEnUpPlsLUmjyXxw6L06E0A9Gd7aD2YjiuC7dt EMl0xKhgZGsSt3wEYYQgitQAGKzHSzd/0fVbvLToIeamfJ88+lEErGl9qYvP4GI00E2gmTIorinY PNS1m7Im/s4UaPj36XeMBnm3//m7wch0Nafn/1KA5EGZgQHz+DIsBis6MdOKPh96FFkBu87hdg0i KnJSYZQ2oZaF1LUVBLjY/WOXkJZf02iN73mIT07F19pdXaLabYVDMcOqBweRzbJtmPn8DXJlJn8q v7nG5a+vFayS8wv4cWzEhFmJgY42A7bbnbme7YCzsxM0VSXddz4PMa1JxnhKBIm9lSxRGTNcG05v oakKDPPP1WAsvBjMeqtD27lwfv5Z58LfP3VMoKVOfV8b5dUoZO90koAAyrbD5voaJ6EHV4RV81P+ 6TXUF9sho6TM8hXcsz9KUdX6HTwJH1q/hUrEVBYb27V3f34EAevLhunJmGEKJFNQmcqoKaWe40pM P7mm4DIFp+nfU5Y0/TllONNrzCu0qfM0HcuXCsLamP3BOv3YsiunXCNotwg8W36IDFrUYZdyJ6+F Pmks60bm+Pi7/LcR5LxdfpN7szo7lc1W1tYYukqYVcWAU9YqFeXQPNDiq0W2LdE09O0r0FKPPUyw XC0ReYu9ikKsI2glEGhKU1tZHztuugGJZmHLzGK0NsW2bBTAGOjITA/k0jygts2ko6gMNIHNKgxl rqBpux4cy0ZAPSvYEt4zfCxdLXgWcbRx2JsQxuj6XbXGsINS9wXL16mxwO5hZ6OnmB9xtPgclvu0 wWp6n8a/fdHnNPvu/ud88oD1W2zAu63WDwWNAyHV/PkxGurjb84Gss0U++E5vyyIbzrpv01X5rMW N1xVwC/X8NpcMi+16A1UDTXXhUfsM2tVyWTwI2ZLVEQgncAhjnTnAzo5BtVxjMaleQRLyB4V5WqK QniT5TArY8u/QXH5Fh0NJTjGU5vgpnKRHoW3sBATiBhGmwmjokKG7wt8ci3CBpQgbuGKKmoeE7jG 61BCgtw4xMVmpSDlZNy6kgqEPBVlsGHUTCf/CsnD0L1ZYdqUuXTHkQM2pyBsCwvf1THrpspjtGzk zgJtssBAhdQgghstP4ok+9svY67K6/mlKokJannoY/7kAesYeFb3lYUf8/iDgsT0/dujI1/6GCfZ ZKk9HElZSJymXF9Ko8prdxgcWxii0zf0qDk8jtmEa6zVmXFITpnW88wUZLd+/zW7S1XgBZfFF7c8 GxB1KeE/ar5bxVYdP7LIdXkeGECennAyU6DWOyWXW8rf8Poyk6lz+G0pxc+HlhlLZgCmZLMLK4xg 9Z7Rm3dc6Va5klc22mbM0irbR+uQwkBYvzf+hwzoJKkSY5udtzR27RBW8kckizONZIkaIaD9OG5c Bg/m3+wvVA7SPNY/zgxrwoSOMnP4iPUlMaoPrQmP4xeHZ7vR6fmpg1XXVCh+/TO2v/4Zm75CGofC p0Jr1EofiysGEMoWB+cv4fkesutrtfwX4Uhj2BlBvdtrLKnnsgi2g+b0pRmnIa60W6O5voZPR+SJ qMlsl129j2CBs9yLowCr5MBM3+Yl8nWDuq4gR637zt2yUVkMyRQtBKyEOlWvxBti9hiM71fZ9LAZ COlyTZ/D01Q4npx6mgKLyFPZOQXP+S6g5X3rBPAX56bM9I4hq7q9pm37JRpnojT4rr6OLsP6UqMq T7l+b+tuU9/f/lA/5RraBs36Es7bv8DbvJbNfFGGGJIV8PKleEvseFF7iqan4WKJZJFKhyohGE4G t6SMq4df5A62xerOZnDaXMMS8N3AqjNxtvaGFo6H8OUPkjd+X4f2wKC/veLQx1CHKEk7GJp7N4/j elisThTQNE4zkkIP0kdGo752Q9S2i9a2FcypfMp5QLIxzDHMMvo7bTHNUHJOYCwPLRzfMjLen5/t T1gy+WbviwlPGrC4nkIE7DkuA7qb2bJjwN1FBSgy1D//G9zNWziNsfEaekqndGgWC8Sn50hPTw2H Sexudr9c/XsKJCxvP7jmQYuNjyKDXeyEYxETkvbC7KKos+Z54lN96KN1H4ZKkJ64lnCiBw7POEVP ozOjVtv+OU1GyZKVZSCo00/WduDp++Rw1fSRFJvdUodSahCzeCWw3XZQjeTJY90j1r5kZ3j99GMk XhnFhkP3vvUkAWv+ITnWN+LYFoFg0hpIyHzKcYxpUTa4z9ew6DlIZeAo1iZnq9t417FLaAIJ7ebF uaLpKU1KZ+85AfOyrNDRmOOObrB8WOsGDUsvN4BtdSC3wPYa2EOs16A2qAkWI5bC/1HW2LJF8rT8 VoA6wfnxWfV/Hk9nM1j0GNh1lMTy7Lgo4aMOJmVrRldtge2G39VxLGYsV/mfSI5UdKCw4iipI66X XQqMRxug3hHoN643DLYTgdZ0EE3QOxyhkWnmBAA7jseZX2HsuE/Z4af9Pq99FIcfpQ33RAGL/7+f Z/Ft3U8Y5cbNdpQHbo6ChzVUOazsCglqDMslatuDTVJjSKJuB9sP0TU1tpdvde+l+BxBZW74OSbF cyuLAnWWwefg9K0XMRr4fG4rXMA2iBHCKDVdOBI3qa7QUbrGWGiZwWRHqqe7XY7G4zEtxMub+HFT KsRDoL9f1VUKaORYTYvH21AGhhrqjo28NNedbjkUYmwCOkNbUl5g4InkKG2jznPkmwy4uhSWZXTm LYxq8ShtD/FyJRlksuHVQR0zQVUb4+vz74XtodHozde7UayRwsJS8ENjT08SsG531b7eN+LLkUVr FHkh/faW2cAR1INitWdXcDc/I3LoOkzrdRtu6GOxTIzT8SRuTjICA0/VILZd8ZLMk5g/SFfgHJ/V FIhICbizBNZ7HFmJEI5w1FyqhVSJXTsgdgwt4NDUs9DYnYZoF6cniOO53MvheUhHYPeN5V0cHMqR qvFlZ8+SjzOKEQe5meGSM8VmC1nrUSCjVOJwSRiYwMagWWzROSSzTrnS4T3r7akjyEzttpnDu7th LqY8YWPHtz5HuGAy8vjYWOA+pdTxt/X+xaFYBqs8Px6zCQar7vpn2Fd/FfdqTh2cKrJ3aCKzr+nf 0+KcHflFlEh+yPxq3yi8u7H3nyVyuiY7+PnBHn7v7jGxtL65vkZ2cwM3irA4OYUVHiyzzO8Y7Eid xNDXxmJwYxBb73K9H7UGpluEFJkbu5rzl5rCjLCrwYJCctOhK5tRCaJToJWI3+zEWLI28QpDNLlW f/p7r5k/NifaQty4ziWNYxI8tJ60icaymaNbcRd9lPruk9MavmVZDy+WSxzFkULDE8cqfeiJW13/ DOfyL3C3r+F0ZtPdXg9/4O47BQaOrm3gEPP6iM+6SJrjbKG4XWKCQ9QBLlIGpspOAVAb6V3Mj2Vr vl6jvbnE0C5RBJE2cLFeoy85dMxBHgt+GEqvSpjXOHjO0la4W5wiTFOVg8K29lH59olQ1qb1CCgz C3NkHaYBa2J8Iy422ZTxO5Xlo6aNrJfCdg5SOMMo+v4Y0minkSmOSBXwSZXl2BSldDi07ARwggQO z/0zhQDn0yOPWUQfDS67b1m89zP0JAHr4IDzLWA9tCSfy818BMFqcnXuih36X/4EL3sDt6vuCljf i0tO2cWhvLn9gWQWSR11zQZ+8CgMWF6pc2c+O4Z4SVVOS4HLsqkcNT3/GLBGGRcuYlXWCI535EK1 lcZhWNYNeYHLn37CcPmL2PtwfYTLlco3omsy6yGFyiZlgdgVEMQJ4jBQwNFVYIY1I5uqY+i4GIIY 8TIdZ+TMUA9NJnhO1LximUgxQgaSKrwA3BiWn4jQun+u3gRMZnzvDQxjkFYQaHJ4zQYhKoSu2XcN VVYr+jp6sOMV0J9hCBJjhPsJMM1nJR3jjecw0naEoPu8dfttPQS09+InHQNBlEsBS/6ANzJmIBYz zcdNHzjz3x2MiaB5y2Fgg/3cvX/2Ur/o3mvDdes4xq5a4NjiQJHWsK37Bxnpk9wQy2o+gqRVQttU 5GBmx3lCzzF0CwUC+hfmN7DLnNEIQeQhGKjQwAaA4DozOuPSuZq0BWOMu8+w9ux3MyepMx612k1M MzvUjOIQljf/Zr+zhYMtAnTLH+AE6TuZVC/aiMmw7gaJacMbyKUTR45lYNxnSPwBgcMRKBPoaCgb WxWCoUCz22JbZehWPwAsPz9BWWQquT8Vspg+7xxS+NDLH8Fozrf1UHZFGoNs7Z98sfXswYmX6OMT lJtKmREDRuBYaNoBpdXDbTr4Ne3LzGbiB5BjMznNGmwHsbui7u+dpza0gIdf+V3oWbpa42iNZgGn ruM9+4UuM+1mCx+cDhhgh4kCaHF9CYs6WhwXYsDsGoRhInyKeBhvE1MV0LQ9dlmhIMfXogKEH7sg RM+ATBNY30v258FZwbwn492U0g07jPUGHTWwxO9y4XLMyg9ROp6RPkaM2olVEvrKdN49F5eZmsRL b/+QAb+paXjRq3x1hxpun+PEYyDl9WE30kRJc71Mp5bH51NJorvBOnNRWzac5PSzutnvk1t63zJ+ nfz9Odp5zzX4pKP7tn7TZbIC00Y/liSUGAexju78D7CbHbptjQ09uki5uHor6ykpK6QLhC++Q8iO m2YGO/gUsIN/i9x5+8nf/9pTcGqsg5yMYSfMSj9uyTtuPG1P4dMKfpEpU+ot6l7lGOiYnW/hsdx2 jfZ8/uZX7P5Wobl6LSb9/IkoG8OZRb8uYbE8bDwQng85qEy54n7ALq8EzPPnXhRieX6hYMGASS2t oSrgsZaVAQXHdJZoo5ewL34w3FTHhWt7JoOUbMw9pZH1bmhnhtrWGVDe4NUPrzQX2VY2ynVBvWZl hcTiGAiM/PJE/Bolm+Xf1MOvNlIw7Ukf+UQV088pDXkeH5OhfQtYR7aM0jDLQc6XvWd49/de3CxU R1i9RPXmLyjzX9ByPKYupQyKqlTgaLcpLMoJJ+z6OHt9KUrfid4wOsJMn21+775Scb4mDKzrDeZj HGTeLRN17SRtM4hiQDVRmXaUBazAMTgTFUXrEl5bw7OpNtCiLXLUVYlhcy2XH4scr+m5qbDQtjKH 1R53PHgqH41JRMDZQWaSjXG/YaBxOfeXRKZMdUgabTDUA9yRZ9bQfccJ0Kcv4abnxkhjyhQfQyMY egx07ckuYRdX6Dc2utJTkO6yHUrSRGRRRonnAGma7LufRhzncM2DoULX7FCUO4C41icEn8+5vU6G sx9a3wLWkS2l1m2PumqORpFhv2hDFS1QuAmKqgWu38LL18a9hZuAm4FpPeV8hdGYXzMCJNR9GtTN s2hGMQaYuq7RVlSh6uDdA2BMqgtTB45PGbLBNdIHxBpnEBvLOJIjWJJFrqdMhUB1XxcoSxdBEChr pZYWddsDh0/dIhs3uM9z2W+6AzNeXUYGQ8fHECZY0XVHjhOjLAxtwnqDK03a7VMo0PfG7l8zHmsT ROiTc3iri0dTCwYJBnSaGuibEk72Fs72NYZqh21XINd7YNRdJfsi4UIHXpKKrLqneOj4Dy/tWQO8 tkBV3GCIFmOG91iKArFIFZ2fkW0dMa2B61un8F1eCl2deVc/Bt7VfGn42PUQLVawTk7RZm+lMMoP ahckAuapI3VfN8VkPybDMnudHKYe+WaLarNG4do4SeNbTs8Gu2IGZpkAOBo3a1OM2RQ7g2Q0KBbY DhzqwwcR0sTQFOpsi3pXILtu0K5OFLRYutKdmdhVyDJxaFHeZdnvKREWBjLb6TJtOwg9D5FHpQbz GJJ566HDKo6UcVFxdDrfuW49refJ1Ofqlydw0hdwyKR/ZFAYCPQ3NfLdBv36NfzdL3CLG5V9JwGl WVzYknM9BE3GLoOnjeC8Lt+7HVunK+FWa1TNK2nLPzboGDuuz/nMfvj1nixg3TWF+LbMkgSzAMjj Cla3FV19hKslPHyP9sWFGeYlVkNz0Wx77+8xAwpdG4FvykTuG5/jL3zru4pgD3YcaD5ss7Fs4TiL kbumrZUXhFhEIaqRf2WOyUY12AijBKuUbiu+8fKbqAzo4TEr2dygDmJlXcoKZ+c0lUnzDcdAmLUD Aj/AMvSNHv1giQdGGtNU4k5HSwBeAPq+RW+yGTYmHM+SOCADSxMnGCJSHB6ndDAwW+Q5DQPidIlh 9yv8tlCgYRZlsiqzNK5I+Z9+QMlfsSoMG17fAXlWyNHIH083r2qUeSHF1tahJ2OP+Mf/AjdMPjqg GoFJCVXjU5YZ6jdZ4dGC7vN26DcCqVkySDiC4eb3LZsESD8UEdKjlXg/yABUBEDOC848Armmbr9h jR+6ehq7YdZGhVIK+nUmy5kz3s3H19AemDExUJEfBbrLBD4CqhlQfI+lHoecXWJM5gZoM6qEMfqB ony5Wv3EqxhYbIK81mHW7z6M2+BUdLHn6JGFqqPP4YCsGeB7A+qGyqKt5hbLmsUoDVBaNB15ZdO5 j7rsY4bIPMv2fPQemxKPS0gaGmXUpc7Dzd4i2PwMv8n0meEQ+LR4LagGofMUG3VAX+Woblo1CmwO hdPKzDVWG8zo2VRw6xKOXWPAT7Be/FHcsY/fl3xvWRpP1l+PXHfEMI+2JJzzN74FreexLC+UWigx K4YGdaA8D/5igSCOEATeLfLke55p/4eZu7unlBydcRyqtNB8q2b4WiGKY33R5IGZyq6mC7HRC5s/ vxslQLwU0F5evYVVkfVtyLjMv8ivIkWjM/rNe26ZQWIg6gZ18yZmPXE5hSA54lRAWYrbVdRmDpKl fFPksLNMXU1mnnWeoeeAN39OHfa2l2nGY1fXNqjLAqhyeG/+F7zyBk5fizQ7H+xm0GDWK8yfN4mu QV1VwtLi5QIOHYwUqcmRMNkur7HyPwa/8gZ1uTNYlndg2n/c+/mJXKwH3v+jDljflilvfm9hwEcv N5CXYMstPZpMMEWhy3EgayqTI43TMubvsvxq0NRmBEXfE6ZFDpIBzG+vqTBksGAmbjakR5MHmyJ7 wV7sjRuUzzURI6cyTRmG5yCKEjiLBbLtFm5TybHGPO+AvDVKGH1LeRoXFpUbiE1xd9tmNIqZEf9N OgKHnUlaLYmdMWBtboi674+a2UqZ7VC9+RUOO5BNI9rEQNllPq/jIXpVIJ4kWR6zLCMtjfwaQbWB 3U/dzAntM/83wD/g053ItpHRjTrLFLyaOCITRbiWTMt0vXo5AhmawwB/qFFkawzJmRoXjzvETysJ 1dd4DhnWtL5lWWYxWDnUBD/iQM6jqntKsxywIHoNas7PuW14KqInuUy0+apqlVYjZq7HlySVNnRn vg/HNIGvHFg2Gh6WvnezQen4iJsBATt2fB4Gnq6XvtXkOUGN9pZuNsONMoh6u0Etc4jD3ZzlIGWN OwSobQdvXm/FdheG6FUIOhpQ2OgtB+5ihXhxBivwjZZ5VcApfro1VkQaxXB9jfJ//ck4V++xMip2 AV1yir6i3OjjN3bAwFuu0e9ew+9NADy8KSNZbbKz5xiPgP4OFW3J3ECNhm1eaQyJKaPD60kLtqpB ggZzPQuquNK9+7FwzdwD9DG/94Do6nEGrMng9BuWNbmG0FfRO3CxjmzRLDXoa7rQwx6tYwrOxXG2 zjm4xExLGRDNafNM5cmc7hnJUKNTBnXfMiHKVsnIjp6+V29hVwkCLLEMjSSMtLDIEqdv4FgWEksq sxxdnqmcDK12/MTPZv2Ed9kaHaKET9dWsKpsbHp0CNoQEcFyi6NACywiX1I1dLup+VjqIM/MNiZy LAFyivTdTRus8x/hrC5gE8N6xJIYYJmh3V5jyNbYdUaldMpk654E3hsjW6PZT5adBqPz+x4eA0/H TqBl/j5h26RJqHxkPTw7zqY0x/+J67F7+WMTlqMIWNP6hmE9LIdyLIsAr1Vs4NaZxjqm4yTQy9hF +sEUMKZFfxhhJE0Fi9rr4/cnnGj/jwcWMxhZa00BixSEvlVgnIaOmbk1ncFuHMsxYnwkfXLzdo0s u25p3Nx6QcvwuCjdPFqUyX1n9FVkdsfTnF6PX/IyZNbXDqhI62hqNQB0RhyhSZbo28gEjwnY508v foSTrtQo+Ng13cz73Q2s7VuE1A+bBRcen86CTHxx1ExuOic37DUTx8tgLuSIy41HN4VW4XV8rnv0 yR4jbPD4LuEzwLDus8461s36+y3D/j66xQ8ig06TC7tqOPM2ssKZaPxWyBt7YAMDkjUZ4tKFhuYW 9l4jnQHTWNqb6zb9SeyMelVD39yCdEca1b40pKFp3ZjH3JvsMfjVtXhjPQH8ukNdlkZypu2wu9mq m8guJUHw4OyFRl7sPaGVAdeCtUhlzPGxS8aq2QZDW6G//gludolYEeqwR4yKhLF49xV85zy2qfwe 99fYsj1osVvoaArrUc7GHXXwbUngmHGC99MM7q5PhTIYlKegdZQmFHfXN8mZw9prZB/V4g5oYdVb eIGDJlkKl0JxZdr55FUpYn35mw3lWRrHR011A6pX9ANO/RCu5ypgbIpan5/YM4YQsnwvG0SeoyC0 3eaw60KBw6gomK7kXtJE40GGkkAM6l4hwWEQ3kYMiJklzzdOE8RRKE7WJs9ws9toyDtYneC7779D KM6Zkb0hd4ujOg1K9PUOPTXAyMTnBtVlu+e68biqHM1P/wN9dg3ka+la3YX7zFgLHax5XiY4aUCc +vpi3xvpGqNBzzankdoQm10Szxa6ZAE3XcCmWYZLswxHfDHTnvj4d/UQbB6fYX0MLHQ0Aevbmq9j C1ZGXoYyxmd+jeiCgnfArm/QFze6EZcjLeC3WJQoHvxIGuvMprw6F/dpKqsYFBahB2+c9JchhHyd 2ehrEbY5nCZHKzKl4YIx6Mxn37hpiQNl7zkJR2NHBQJ6LhJX6wIT/DwX6fkZ8mKLNt/Cpe5U/0Jh 8XABx3tQnaPdXsJKz2EtL1AWOXw/NHZodzZqV+Xorn9CcvPvcpQuqdvV9VhPhFlYKk1Jr+BwNXGr TAGQGVOA8Id/wDKNhYlOGlqT4cUUgXhIcvZJVggWS0Tj2FFWtdg5Fj6lPfApXe5hn2UZn9JnFbD+ nstCozLajMJ9w/G8H32DoM8R0bzZclBzsHkkLTFOiLP9G71lkiimrnsUogsiDM0KyXKhIWS5KVMA sCGGZeSMtTln0D43MOcHrfEACYxPGM/sLE3X7YHP3UQZ2JeLzLjKUoGapSnJpKWfom96NE0P53qN XF0JW5w1km2ZIbZDh/b1X9HfrI2xRnoCXHwPP13BnVEIepaCuyv0l3+D15Zi64cOs9jb2FslgcIO qCl/PEYynh/xONtW84YBfzzz+0/P6tFTolkdalN2s3khxyN2Q6XeMPy2Xf/RVFnaYu+JSkcVsO5a wE/n+vcSvPY6WCXn846H7S71yrpEm12hKHvN0ZHTtKXE8NW1AgRb5/yI+jb5ULf9AHkqbJ37dLcZ YWDN8rFkGZUa9CdZ0mJtM3gcQHb+BsmbVMxsyIEaHFEkJgVOjvW0DakHfLAjPIZseIH/80HksaPG jt9cNpllnOYSm0Klngl35rgqcsBYMokrdgiDVBxtdhn6bi3reOvie3TpCSo4cEh3uHprFCrY9V2e ID5/YQio7C5evUZR/YTBixCtTmSVNizP0a5ewD19JfzIqraws0tYFXXzRyll693SkUKKLa8TmxB7 qsboyt2RENujscx1Ml9mFE5SzWPw4/uX73bqklaeYzqMixV6EoTVWvy0G+ej9d0l4vf+z/1RBazb QetgMDD76fgYfJWLHzC65FC470iSq8Pdr6nRbDfIhkrXP9tssX3zBsVPPynD4iwbcxbfGsdBxrLD wLY2avoKhlRQMGM7g+3Cct1RjM+01puKpE7Dk2KwmvObpB3AecA8U7CqqLNFRxtRDJZ8AAAgAElE QVTfR8hNRcoTgXG6LNPaK6UIngHl57mUSKrKtCYQ2kZph6h4d68zDD0zNEdegAP9EMUBo0egwXqk EMEZQj5XkaEnVSOMsPqv/w19tADIrN9cA6//HWhKPT9fzkpiYW5U4WCgy6sOvdcA27fATwOqKIV1 /geE//TfEJ+/RFBdw6nX6IgiSSLmoAs2X904nE0vxgPji7ifJ6/HoihEHhXOxQAvMq2HMAhkryWy LSwUmzWqPIeQvr5H/A//gm6VAu6nKN5+2niOPgcKWA8D/UcXsLiMW8kh0zpE3UN342vLupQoVEZl lIHrqJYs4o3200KsKJZBPcqmRLN+q1KEhqNSsRxaObPcWhSnO32F6MUZQvrxcYB61LTSiAx5RATH rxoEogkYkuWdQzB0A6p+breaPXRoEOGttCG7EbViRkRdwYGuyuOIytQxlMcqBgT8YtbB33F9VF6I jmWRQyPPAp0ToqdDtR8gciyktmHjt2OHLbSo0EDfwIGujJqhC09O8eLCV9e0e/sLrte/7omXCu7F v4+AeI8qOUETn8io1b28RN23sC/fwvnlbyh/+TPC//3/QJiSIlEh17mZzlvZUeHi9rVlEOXUgZWe CmSfXH4YiKqyQNtXTGRNwB/nI3eZjSZO0VtLpBQd5HXpqflVIWLwV3ey0zU2bPrHdQqnbh9ldx71 MbsjzfNsAtaUVU2cpIFtGPOdcWbKvPFHP8LyaGdnDrdSVua4skhiNJQSrr0EAwmFj8Qzpo3CIEVi ozbPeH7MVthF40Y8FDTvLoLLKCu0m7X8C40ulI/M9uGtVtqkiWNjQQxmVF4g6725B62aXoXFZ/jy O7jREm4zYJ2uEJRbLN0BIQmlfE+2G1gDCaDmTBhIGbwUwNwQbWRjCALkb18rwPHmWuUFqmiBoTYm InYQw08XyggV1P0YLqVw6gLLVSTuF8F0ZqkcJUqtSv6Ng+vCT2LUrotifC6vqxF27IrueZ/jFXbe LX2JRdljKTkLA5Hdo6EKbN1QNnX84UxVcaRTOAOvXofmEZjyVOL/VgnFkQas22t+8oZPcqjJv4ZM azoXlkUiZh7ZKQnR4fxgdIK6XSNg2faIZeb2KAczwJ006pkFWEDR9MhpR19yDGYam+E2cbBzfPiu i8rxFciDrpbLDTc4OWC9F0j7isoNQpdsw3liViVhPcOgREF356wcO2Lm5Vly8q/e69eAt0HbWzo2 WqankSvQualr1BkDF6cmDeBO0wp2zjhbSNWF2HFkSuFc/iRpYWFqdSsxwo7llkBkByEHwwnCy4bM dDuHzobrRApCbt/BZ1nN+T+GUj6PbSMKAg14M2DXuk4O6pKs9UZ431SFGLWDsfM5BivqcA0swe8E bNIf6HbN60InJJaARVmLJDtFBJaOASm/VqfuKUH8j/uwmAzvt1rPImDdXofuw9cQrL6Ee+7vsSzH wxAuUOYx3Ha3l+j9qMXZtqpCfnUllxZ1zjwjDUMZFN7pyRQXg52BhtpSjoXOj+BGAerGgP7M7uRf yKek000YIUkiMc8npvZ0E2NJxO8TWeNYULMzWlDT5p6Qkq4oBNSTo+S5HvzwD/BtOszQxebQ/p9y GErSTAUSn58UBpaIKIwOGDMvl8RRB6gdW3I0DLLIdxgcw4VykiXcZAl7tZJW1nD5M+x8J7Z9K0xp ek3jtENMTWqsw4C6spBTOiYv4fWN6QzuA9VMsYFZoBRSpadx6+1gMdyUpYiwAymtHPtxPNikNLhm ZIg/c2sqQ2ToSN+Ilh+V9k/X/5P25l0j3OcesOab+msqB7nM5+54g5aspbwQlb9C2Bts5uAl9/7F uzXB8jzbiP0tpYdkhWUaaaQmFLPfdN40hjPaePW+h2USot/k6PsGbn+YQ2Q2E4YBllF4W1JmprnF 49tRDpllLLXK71vj9InKRmpstd9N/zoc/wj6MyubOnEMZgT4mXlo9Ea44xgQx+yRADzPndljU/6M qm/VoYz/+M9YfP9HpN/9qOHtzX/vxRHTa3qBPBSZTRnplwN7v2Y3tKrQEhzf7hB3pdyATDi6fczE szo/hdXz6t5GhVgiupSl4YhVyxIf6MOU8g48APNaRY5hu4HDNmRgYwhTWJTG+Yj3Gp+RTEyM/Gcf sOYl4NeUWd22OToeKsO9i5lItEJXX4+dNn3zo4IWUR/OE3JNjHOfOu4jxsQJQwYBKjNwY9DkMxjd W8wj7iBRjPDaHMYM4kutu0YKt+brdDBmyJvH2icrYHGCznVQrq9FUjVKn+bLCRZoSXhlBsl8qSol N+MHMZwgkCYVO3bej/8E++WPJuOrG1xtrtE1hs5AVVDqrfM8O44gUXyvrRFGAbyihqPZwPuY+eYa 3ffOEEukD2Pj+RhalsqW3KmJ/U3L6RtEfS1m/UCLMnK9Rmb8+9ZjVRrmayKOPvuANZ3E1xmshj2d 4ZjIovcuAUMhCi8FTl8i8UIEL35A3zXIiwp9XcGlggElS3Y71Otrtf4VkCwXjtXLIIKuMf6oGDC2 UQzPiDOCzCpcF14QiL0uvSvXQxOk4gVNS27KdYv+7ZXKH3Kcpuk4dZbHf2V1h/7kXNZbXKQVkKJh 98RnmMpFEuAjCM4gc7MrZGFvDZ0wRZZGNgPtMMCJFwjPzpTZMdAGL39A8up7lWs3f/4TnCo3GRVj qVRGB2xcG+uyRdWy+GLAd7H1F/A7B4GE9GysLs5VgvI1tpst6vxG84/SphqVSnVmDhCGLjrPRl41 ECFu1lCe8l2N2vCa9wOKtkc78bA0a2n+Tvsxft4IuetmQGWGUdhQW0wpP+WD6NlIkUAT/B7afaYJ 0n9eF/8jEvajDFjzTWsu4NdJZeCSOmTToKprzcUd9SKk43iwwgTOULG4U2bILGFJZYO+hTdu7stf ftW4CEdVGBgM05zcKv68G1nZ5DOR/W2pJOK4DGkHHYNFU6MoHSN/zFKR4LMdyAR1Gt9geUkF0ZLB gBWdPZZiMn4wDHwGjThdIF4m2gu7XY6uoOpopTDJLCmkSqrnSuK5/NnYl1E7vSGXibIydIPmWE4Q wfF9RFGkOBFS9TQ1jPsdZaNJAeh57B1KYkw611GGmRuauFWUovUClOoIG+UK1w8QiLBJjKpGz+bB +DvzIeaOwVDAe4mCjysbzf35gT+ao85Bbwt2b6HlDaM4aGXtG1aMztTFmugEmtHsDkFpT/piZtyi 5vv3AXoDAyAzt09dfE85fP0MA9bo8ziLtl9jsDKGqR3KohbD/ehsve51gGbp4KJn4Mh3aLIN7DhF GPiIgnAfMBzvShmTyU5okWUAcILm3NjURRCoTcb4mBGEHOAlQ5vBu+2UBThSEQi1KZlFdfQHZDZg O+L5eL2t7p5wHnbYiClphpCKDsL30QceUs9sNwallnpeoj6Qh+Ug9kmk9NCQdjGQHd4YJx4+hiz2 ptCmZbD1aCrh2uo2MpuiTZmRsSFwZqgFZJ4zs2HgHTjT58dS9Kr8CK3jKzCwNCwpn0wN+DyTRA1H bPK8wEAfRF4fBtCqhEO9ewazjvZvxLAyDU9Tbjk+OUWYLDU/OXGw+MV8qC1JTL3CMEr6jDMGI+1h LLSnvoIyrzGYScWVw9Q9HL7PNj+blE9+OF7Nk4xP2assjznzyI7qswpYkxWRLv5H6YI/38UPBe+o /JAehyX9h5fca6oWw/UN7Ks36pH37Q3KMERNfKcxYPHN5RWGshoh3LuLWRRQDLaMIpitmNlpCy39 Dml5zva/V5mgESao+kgdum5zo7Z/TZfkzri60FCiogmER6qDh3bEYkayw36ZpOFAF79XV8Cy5NLT EX5w6cY8EmVHbsYBnmB5WaHe7DSvx+AxsGRloHMGBE6AgBs/iKXeEKYLbHc7XF2v9XvEg/K6xy4v kf/5f6K9eSvuEzW9zk5SZXx5kePtTz/B3t3otbvxLh6MmSwz3fB0pdL5Lo5HxdF6vHsc/IDGkKWn MQFrKp3NzbNXBksibk2u2y5TF7f1BhNEPT764QzocyAbiVbypkTqx3MKWIcE+OsOVlya82oNIfA5 LTdM0YYpej+C7bPznWH3+g366zewr3412YGiEN1ujCjefE2zganFzTGgFrfJEheJWRulh1kyshzj KoMUGRUNmA3QRl75gwWstwoqzE79OkfBGbzFCsHJGV6sEvGwJhUJZVMtbbJMG//u2o/pcZzHD429 +9Ah2l5Jm/0d5VD5+DXw2hypHyE95QzA2O2kemndImYAjVJ0ri+cb+X0WJ7FWK97uQwFXYHYv0Df VWjLrdxwmInZfawAxWvAEpmk4tzydBLMACeQnSNPLKU5AD4lJhp1GvlmkzLFFJioJ8a5SaadNctF ZVF8TSZY9PvKUZRm9Kq4WUuSxw1DOD/8M6KX/woniDW18D6w/bEBS8KIjo00jTUq9KwUR7/m8u++ 9FnDqdQAP/ZK8M6yGTySFfpsKfXR1DWjOlnfo2xJeiQWYrIBbpQpyd+XWEEkEwnpu++VR4n1mOFn BhRLxqbT56CQ6w1LMkkQi3dkODt8Tom90NuQwYzPf3J6L3mRgDOxqLmk8bQ0IkS2fd8haAo56/CZ XUk6T22Be36JeBqPfcxwaOYgzS0OF7uOuFfE7Jy2QeTS8IGRmufv6zFNvkNNEiznEBmwiedZDvK8 wi6v1TUl8sfntZjmOZyVDE3Zx5tGtEBDyoHPsXKjccXyymLXub4Z+e8cwqbUQyS5GQYXBkx6EQYs 9aZeL689ybu84nWBgfhX1+gmwrLyoQ/q1MF/LNWIFZTneUjSCCED40d0ez86YE3H+lvFkmnQ+fA6 X2fQOvCXLGVY/HpuixyoPkgUeLzdGwT2gM610YU+nEWqzICBa6hKWMTmGLs45+YZH0MC6KFn5t7u DQTjmjIJS8FjMIPR7x4NLBqtjvbsNJDgPJ8xYjBZlZIslwoN03O+u/GMw7T5/FF7yqFXH4eGmbWN xhUykVBGM2ZsXYeWOBuzEhIvnTF7YZe0LEQ/aOsWDW9KZa55RWZf/JKlmA1UV1fY3dygpzUYpZZH YmvH69a1ul5IF6ZLaTGTohqo6Z520QLRcolosYTL6znO2jJwsJFj7Qp0XmiCuk1NsRABA4NtdLQ6 2zQ6ZnMk+7+ZatJ0DwdahDXk3n25zyoVI1hK0/kojsOPpkM8GLAOINpBPeHhnuPhhT4uzhy4O3c7 gn8PwWo/1K2A9bzKwT2J1I9g+ekoAWxUEbhhAxI5yciumT22GOgmzFKE3cU4hR96GmXhEtVy4i1x D4866eI6jSRFBhjJwbAjyeA0PxDK01BrikB21YoHxderswxlSgNVM0/Ipywt19ANpBLh781qOcPo 1mSME8NpRZdww9iMvTieGSyuCyN7ExJHY5PAHHjNuc/eBJohWWmMhsGkGyqUFRVCDcepLCtUuy3K vpKMs3GsNpQFvv/lemMCFrMZlm8nZ4goCmgPGGiyEThytvatXjeHaZC5YTMhDrFS1jTfp+a6kes1 xAsFncndev8ejqOD1vvmR2Ur1qEvMzTZFiG7ig+4fn14z5qMmI9js4QmvFEUiDj7MZnVewPWfGPd nZ6eAsztgDbpV00H9fAJ3A5Qkz31pNAw1cDPrEb6SPGyOT2DACc3yHMMWFw2y5GT77DLLtFvrpCV Nyh3BYa8kDIn1QxUfdlGwbK1fY28lHBkEXZYlBCmU3GHIS/1OyI30NuQH27ac5FIysyGihBzyZk4 hXt6gYAkzL/+G4Zih44UkfVaWYXvQB6EfP23WQBEKTw/gRskMsbgvN3NzRa7okREzSfeREjqPLvQ 3Z8bSdIto6uMhAHJwJ/eX2ZiFDZ0WnSnFzg5P5M3Y77ZoHr7CyKWk2wgNAWGcougLRSQqK/FTwIV I8SXqnP01U5lY+u4ciQiP51cr6leI07ljMa1h26BkYwR/2nMHSe5HnX4XBdxEuoa8hoXFBvcfyYn 1a+Hgpb5ucaKttfIXv+M6Pt/hsc+x2zNZY3fF7QMVuXA8x2kaaL3zGRVj/vcvROw5oHq/pr00FWY /3v2DPtOn9HFuRvsbgek6TU+VQv6vuN/ygxtTnK9G7jmN4KW5QLvXkdPZbh/2aQVRAksCs71Ndpr F4XtoHFDEaK5cbFbo99utIHIe4rhI5pxpabFEqrsarTFVnImBIvZ6SM6RLa1Q8CZQL3cicdZQvm5 niA8P4MfhNj9+hd0pUGblBVQv6uljpXJFmw0CmBpyGFlW5wm4jheXSJAi2S807LkSgKO/dDZmn6K QBy4munTYUvN9LD220Ab993rNN3vp8EAUwQfAoV2g2gIRmtdvDQdLc904vgDJXW+LAs9zWpPzzX0 XezY7LjC27/+h7q1BPeT0xNz7Tn8zJuA3e/dQebHrQDzHsxpyrD0d2aQ+XosC9/d0x+DX1G3LE4i ZVWGgvH4YHUrYM0zp49B+x/++WFz3uegYX7tsSXkx60p2n/uiMCXzKwm9u88aCmojSzvYzZMfe9S 2z8A0gu0+QZtfII26VDbJeoyx9KLALc0XSlmGcb7Rl93mTbyz+P2pCoCMwa6X8u+ymhrWb6Hjhu2 axA0ub6nDd82YtdbcWIGqqUbRVXPxojoyWnZhRWECJNELHoC/fxSNkWchwPVLLMI1o/HQoyHX1No NP9+99a8/zcJnXmO7fU1Cpaj2Q7bXY6myrXZ5Sy912GHmPudGwj3Y1CKTr83goYsQ7sOwcmpshGb GlXE7pIFAprNtjV84n/nL+GQ/f/zz9hdv0X981/lIcjOrYKrZ4bBqQdmnG8OR7v/pO3lZB6oaIR7 OTouYWAlDW9Lw8caO4Xz2df3ZlcE131zE/gQbeFDy323xPt8DOkQlN7Ndn6rIHIsg8Pz4DQPoA9l sHwzxTp+josf3HCJyo1RWh4aCuGR50A+leNp9pAZg7Iiefi1sKpDq33aQgSxiTVxno0ZUTtuFBFF +ZAwRjcY4JgjO5qrKznj1qC5vtJrVCSP6vVoANHBLnJ1FDs5wPBQHA3zkn0vD0JiR3lOMhWtnfen xA5nU5WiEgxjpkOc7L00G+JbBcvABo3joCwK1Ns17CrTz1iOzWfkhI2FMVqWRZYF/+yVylWNzZQF 3MVCx0hRPWaF3ukF/JzKCYVRCCVB17YQhb7kj/uSgbFVgCEFg0Pa70LO5hiq2kwckJQrM9hmnDog /YQNkRHQ9yxK9/gGdHc8iTX22QZdXYqt/9H7mRMIvocg8D5ICn1UwJpe/EsFlLuZ1G+x3s3ezPE/ VUn4bvn77jGaYDU6LUl1c7qTP78l/zpmCnYovaqekiRhCHeRqh0+kTS1Iai/V5Qiyho2uK1sitiQ OEK8CBa9Bh1tPDsI4Ib+yDinVkstzpXz6jsFn/rXn9Fu18D1JXJiX5QZtVk6khoxzSkajIfSyyJE bnej1Z7BTlXqsBkwBiwB1RTt2+1M4GPg9EMMIX9+/2ZTpkcyZ83gl+t7BPG9KoNPyWUGTZJjWROO VZOMHvwQdhSLNd/5hqjaU2qHBLayhE8teLpoK+CaYGOzzBuJxvy5IXP6kurpa7L9CbeZG4C4WFJ6 MFmngSFaFNut8TpsWrH024KYY6tpgjBIkS5OdCNNJdFjTHHZDLl+e4lh8wZ9/r2Rgd7LlT+83yTz 41iyQpswq89d7nMZKL6bft7nMPsUZeD7MKzpmKZMa55dTXDeM7j0713EOsLTlwgXJ+jXb4DtpXlP NFNXizQaDg0c7iLKXZE7pRN3Dc9pMPLDVGggUZM4DEsln8qbgYe8bmVYSmOHJIlxcnGu2bvN5hLV TYWhLVBwlMfiUDXB+QHRqDOq4yMdQARP2kNMvO5D9lFHtzcRH8MRIa5+cIl8ffC2+w5wrXLZx9CQ AMuRHnOO02LGsThZ4vTiTNrxmROi5IhOQ/SKqqLsWjKIG3/BISs0AWBRcK+qUFHLaqRQNItzNK/+ EeXP/yE+mk/PiHbYc9z2i5/BIkf1l38T9UOD1YORjNaoTpQispY4iTiXeLt92E2YVr7BUDIIm+ba ++Aj0w10pFdGUcQvkV3tA9ZzWXcBvilozdPtYwhaD2VWXLewLLmEPNNycFwqH6IUyxffwcuvUL/5 DzTrNdxyJ4oBwW1SCkJqFYxic+Pw2p4Eapph4+AI31Map1ousqY3AnvEpMYGhdQTWKJNTR1lcB08 scKph9DfYoPrGPX/exwcFNAePrcps2GHjhp92qSzn7PbSUWEuxlyQ8uvpkORV8LZZFrBx46PbIse 1s0OV3/2xNn3Lr6Hm6TCsDiYfVOESOIQCVOsoQZ2W2nLd0ODvq2l7+UMLoIkhX96AqfOYf3yZ3UG OZYdMZY5zNgm3tmBn2Wu+fg+zBuOo0GFeU9HTuzkiM1jdwI4ZYa23CmgKvMbh9Dv22/EqhaLFGHk K6P8UnvyKJnuH5QSvgNkHwtwfV+Qekjfh+XUsQTXz1388Hq0qVqeo1+/Rk+aAV2i5dRMWy1qXQFu HAkjUVes6TDcvAF4t2fHiEoIJEC6ngwtGg0Wl+qYdSz1qMzZdMAvv8BJF8K47LOXpuyQrelY/hi0 RqRM04FzFOAI+E4yLVrjW2XbVC4NYAfGbNSsSTDdNjpRSYyBkseTTvqIwNuUFa5reKNxw+GpR4XU 3XbPEDcGFAZbaovSdE/FLbOQkEsmvXcbWV6gCVwpVJSkeJQlrKFE5xK/6WCzydCa17SHaGTUexo0 F3YnVYVDwGWwMTw3jubYqHgtebykaXi+tOb5+4MfAItT1NSbd2yV6KJxMFPrB8ReAm+xEgG3yncI 09W9nwV+pplNMauiZteXyqyeZcCa1hSw5hv+qQPWvOS7+737ghLxK/JkePehYsOzXvxgx0s5t1CZ kmaixGiYCQTcsAxQtofw1XcI0tS4qmx3qLMNtXhV2rhxgvQf/0Wmn9SCoiZVflmiZTbl0gWnRk0Z 5bevNfOWrlaIVycaiaGMCjcnOV7CiqxegD1NW9iltIIY6cmJUXJgtkOCKr33yBpve3iuI0egiXw5 qR7IEbnpVMKZTdyj4+PH4NbZuQJFKB7U/HIMcNoaA7uEPL87q7c6YXgixbqBskZ2LDm2tBsoXujK e5ElIqWQmTGSUhrTQq1vBZQ7DWcwHUngUPGB4zqwOyk60F+Q+locpKZqKz0IuSjQR59E2dbzc8ky 8B/+RTQINjpo9mpFkYLnwCFF+xCwyJQgUbfIN2jwK1xKDI1munoPRiNWBijOBPIG8RhC6FcXsOY0 ibt18zx4PUXGcjdY3Re47ltTCfQ1LJeEy2SJzo9RDlv4NAl1gIS+BtaAxg0kVOcvlsJgqP9F/XIu bn52pM6//w5RGGoA94omV9dXohkQj6Hee1fReopWXw6S4AInq1Tve96azIVSM9xnzEQYrGKHRE8H dhRhsUoltFcTeC4r2YqFvo/BHRD5HmJ2se6og8jMomoR+y48x5JyQWl3ejwf2lQ0b73LsRttrvh9 ZpiSnDHlqMqxPYvSRee42IVUcO2ALAPiJcpgic6JNCngtjUcGlrYnQJsZQ/o2xb5dqeuXetu0HmR gnWXnsk0gnrvzfU1Aipb8GVPz+A7odG992yUlpwZVYoGvouLP/4BaRKrk0nAniA7gzcNKhiw2azg CBJ/tv73/4mSZh0//hcEp98hXawkfsh5QH7JZXok3P5du+bMwWv+eRd8n9ZTb/7p+KZjeYiLxiWV UeohUbv7K1hyjKHmU9Wg3m5hJxE6zhiKNXmAj6gDxU5Vfn2tLhcDEq8Phemurm5EMNyWDdabXCqd zDqGrobX1Eh645jTDf4tBQhuWJYwtK8KXPGzsR1Hcu5+IjR+Uxawix1y6nCRZ7RcYvAkLXhrCXuS BRc3LP0OKb/So3TMwHDdmvlDfhUFu3e5ZgtJ36B1vZesDGdMVvIV/FFX3g5DeKsL+IsFuqIWkJ5z PKdz0IW2RpnYPaXuOsd18qIE/BCJrMEy9JT12V2plB7SE7hxilOvV8lbyTkbYsrzfHbNgMEZkIqD ZgJolZ4JW6MmGLNNvjfMyIwG1rBneXAag7OYGkZXh3GHrKrhhyuk+Rrpd68Qp6kMYg9B6sNGEn8X AYtrHqweyrSeet2ViX0ouzKSte/ytJ7rYunghDGC5Rnay5+MyB5NHVg6cP5OWBYF9hwESaKh3c2v 5BE1KlWstod7fYWcKidwURBzCVPY2RoOcS6OMFFmmbjP4GC92RkZ4dF1erFaIuSg8tBJrnnz9hqb 0dCCn5srn05/huPF+TUaYFCvihkJR2lousDjnC9mazyOzPMQBQboJ0WiyGo9F0s2qnYyv2PWWL/9 FW1Ziu3PweSUSqbo9biS8sMjx91xXPhRiHSZwupulLW0LDnZLNit4SSDOFFmONzMnFL+ZRhVP8Vr I/AtS7ECTkAHItMVnN/+jMCoaewwU6L9GCkWxA1tNgMaFzc3G818csnBiCUlI984wE4gn2Xt7vVr 8bAc0kC6WuRgh4KJnrMvDX+P9awCFtdDAeoYgtU8QE2Z1kOzgtSJopys65p29vNfFhw/hB8vUNWF SpeeelDBShkFqgbby0sUb3418sNlrZJD48yUIvZ8BRqWarUXSaCP5FOPJR5L/kmCRtPSDerNDYad mXjrGBjTSCM8LF2kynnzVoPNBP5ZlJEIqrIsCLG8uMAyDc3zkqzJkZO2Fml1vmSWOjgoswLW0ojq ccAaVW5wecrRGCKW3mcOMJP42UeOeE3EhNyO7HBzHPsrRWMJ15ZiRc7yS9IvIbw4QVC3KLI17CEx Fl8M1uqCNnA7lsa9qB80Y5VsDAm65LGNZsN0vuZpmH8RgzO/z4tAJVeSUx1K9VDOufFR77Zorc4w +1uD7/Wu+X0Smolf+Ryb2vGYDN7HUahksdDnd5of/r3WswtY05qXXE+95hnVQ1nf3UyKQCUVFolN 6MP+zOkN+26hH8DZbVRyDFGoEoS4VeuUuPnTf0dz9VpExJqs+LZFxM0beAThJJAAACAASURBVGjj RGx1Cu41KiUNG94OYzidDads4bZkGnUYaHQxOVBPJfg0RM/PBAF1DiZzrjGIDM9ofS1SKNhiNxPW 5vGj7ZVnm2yMa3onOA9N01QSLfn8EhAcZyH1qiOAT/suDbIzls4IFZR2aQcC7LWoGjR+VZXgBXos 1R6YHTaMJtK0tyQ1XV2/lc29AmhTKlCEHRn6gwB3jspY6UI4GpsZJNZKQWIyeBWwzwLdktKE0i52 BRlsOdc5tLoWDGQ2GyO9B3dUcuDRc95Tz0XKhk3XHlvBl5wxKm7EZxd48f2P8Kgl/zvb7T3bgDVR Bo6FGnB3WPwu8H43cPGxnscMzEVVEj945p1CEdU9eCwL2XGrdxqKjl0bZ6tUNu0bl0oN7L5ZqOoO jc1OEjdppBKpXW9gOaE2MztyFoUCAxfDjmx1F53F9r25jsS+NOPGLhuBZ264yWeBJqjUUX/1R421 WGWOfrtG2BbUL9ZmvSX1w9+ZmT2M6jEC1Jl5vHh5LukY3ljqiZMFcq1a5JkRuiOLv+vYrbTFyre3 1+jsJUp2+CwXdZCIXkHuFCVrcnKbrm6Q2ZSk8YHNJdo3f8OwWCF1HBTXb1GI0tDD57hNl6sc5phQ kCxwsmBGaSmjYlGa8KA0WmQkeKLx31RzpX+iEllmTOrcTZGZg+KjEet40kbxwXxGychhIJSkDr0k bR/uxQ+I//AvWJ2/EN74e++9ZxuwDO3/y3I8PnfdDUofms88hkD7JRc7claUoDt9iYplDoPS335C uWNXqzNjIaPQHiFuWtMPQYjSCRB2PWLPkQM0tZ80Ks3sxergK7B5Gtmp6HVFtjgZ5Iz4UQrbdfH2 lze44ZjPqFPFIOX+x/+A/bc/CY+JSK7kXF/TYH15qeFkMutJC/CiSJkNiymSEIgNMSCKQGlZqN86 KEhj4Kyj4yGReSvUNMDuBsObnxGw9J8CYUthPxdJQ8dmCw07jBxjotv1MhU3rCf2VLcI0oUyr8az 0WQ79IGRZ2bpRd1jGn5YnY2Ok9tBJD4YKRN317zBwL/zORT4iXiR3iC5Hg+VE6BxaF3GE3BgFxXs 9U6BuepodDGgpMIDM3+O65ycYkFFjLNXWBcNhuVLpKsTOQU9xef32QasY113g9VdpYY5zvW1AO63 Zgs9H1GSoG0LtFmG/vIXFNe/auNYZYmgo4PLoDKIXoX1mG3lZQsf5B/R1IIli7FO6smdon267KNY 7tB2yig/WBxhKXfoKwc9aQ+UZh7NLDiOwxm5iUqwL9TY6ChzDUGze0fjCCPqEhniqEoqo+5pfHUO 41Msv+wghp+YgEVrsZojSHU12paNj5v8/CiNPHpFM1sTlk3ZGzUZaCTBwA24tAo7OZGme9FZqLId rI1xuyE+51FxlOc5MBuio3OI2ovVmWOAISWBBh3MeHgmZlqAcsyAXTeiR6h89AOEnMksNpJt5rwn ygy20xpeYM8vJqhGitrgf4MUYlkS1laFNvCMgOMT3Wy/BazfaH2IiT/XE/tqMi2WxeyABYGm88sS aIoKA/XBbVegvBPFBkwmm93yZRdGqkNDOgS7cLwslIAhGC6lUUozGDVRBgCDVY12YdSPb2sB9HTM kUSxdLQsZSHadHelU4RxMZiMoz29wXPoIaguIhyRQV35Cd5WPZAxhgZWxn6fAiobBqERohzf857D zSzzLOO5yMlGzeOxzOQgNrudritfQw5As/T14siYP2wLWHkGt2vhtyV6x4LvL5EsX4k0ys6lsDH+ HkvEphGYzsDpE+8j9UGD05RBJj6XS1qaV7LVjCbLQ3LC6DRuo2sqOK0pfTm/6Az2/lo0PWWaycMi 9GKhY2ntGgW/h4X/ftv1LWB94TUPUvf9bMqyzMgOcS+ahfKOexzjRZ+1RJZ0xN5myQDflyY6h6BJ krRXZ9qgNGcgm9trLXTXl2bchETIhj6EgWFa06BhUrNsKnW1xFxnd548JQYUI3tnsoPlmZQiGOxY kkknS+atxs5+PEBlOsrPxmCk8uyOykar0s68P8LG1LYnSdQVk57D1sSPSBXguVqr830DgDrwDFQc 5h7IPFdZdtCuZ2ZluQ4cqqW+eKnnrkh4JR+ra7HebNFvd5oAoPKo3TCTrHH+T/+bsh1K4pAGQbDe KjdGM4sNDjLrhxSebcuUNbDZOdR8jVGoUHOnN2YU1N4ib4467zxmkliJ+3XmWK2QOsjkqHn6HWJp oeugurkBnFR57rcM6ytZ90nevO9Pbgyyg0UgffbxylL5VsanKAlEW8wmKnReItD2LKVhQiqGteu4 qLYV2q0D5LS4L4A4xeCx1OqEeXV1K93zYJVKsqaj4ej6xszn7V/TyLWcXZwhWS5E9iRH6/JtINBY Wdas+ydFhxEDC3tmdUa4b3oAKRf5hmJ1HCmyDVh++gIxOVUuM7cG9eUbMxtou0jjGOmrf1LmI3mX sWFAuR07u5JcjM/O22zesHV6+IGH5SIVKbTsGuyyAk1ZgOPQWdPAG403lBF2jVytO0nFDPCYVVJt 9Ke/oMpz4YWdE+BtH+DsdIlzZlgjh8s4axuCKJ3tyXHzo4VuDOxWDskSzWoptyHK9JAce/Ff/9VI +nDwvMhgrS/VsWQnFewMPiF2/C3DeqI1BSxutjAMpE0kTalnTm+wxrnA9pruMRZKx4eThPBsS5K+ tDUjxkXZEbukZlSBTuJzdFNmr79Bx809ACGHbl1Lm5gygFQedVcrtNdv1PHCPZK/KhU5XsJxa5ZC wn1wkFVm5kMPROJMBNdVZs6aIwwIXaM5SGYelhXDCnzjz6dSalAJKvsvZXlUDzHlFI+f58lybC2m /XhzulM+8fcm1+jyl7+iKWlRxl6fgyyINC3AUtKyAwyOD2+wsS1Ic7BQcU6zHVBmua5vx5GoMEIQ xajjhfwLnYbBs0NJTtdmA2tzCasqTYcxTHH+8gJRGCjbIhbGYE+2Om8SzNxOf/gR5XYLn7i81cDN Kc3DoW82RUoM2Y0qhKdoeu0F/L4aHOWI1oeu6VQesnziDF3fFRiG9tn5FM4XM5Rqc41iszVs9SCF R0BY50VJHTo7G1XM04Sb5hxNtdgPPMv2TKRaT4qaCZHqvpIeVFMaEuYkHaw1cRD2y/CQFJamknB+ fCP2NAHq86eQHdn4HYN/Eet3kZysTIeOrHZykrwA9fpK59q1A+zKcLAkEjgy0du6U7k5uI7AeWY3 E8mSNAPenJq3b1BvNrKsb6jpRYeexSniiwv4sQe3qRRUOADeVqUCG8e52I2lBT27klK5SBZwFytZ jTHjqpsBXewrWBMv7Nm5hY06Jzu9EcYYJbGyKFqkUcQw4/FQhtl3VJpzFpFMdiqoTvZmzegHqbL3 iZZLbsldwuO34PXp62M18W8NTEvszJ3xuJ4K0vzMpXZYj5bDxeT/eKG4WcLCi53Y3WSL0+aJZ6fW fZLCCTuAsiprGn8aQNy2HIS2/HPQ1iX6vJBWFEfbxOQeiY7DZHtPueNRx6ngc0lswOBJ1GtnhqRA RsxqZM0rP3B9OHGMzvdEXK1dBhQfQ2BjoLJmvEDjRWK8cyNbHRn90cj9MjcXN89UDlZUVCXY33cq w9zlUsPBktnZa1KZgColhksSRJkO9UZf3vGQnp0LkA/KpbI8LqpQEMfrKVnTMAvnVRmFEPkZorKE H4l71bGbyLLVWtAJBG4QyuqrDAqU5U/wOQlAtVFWqB7nFm1s6w7rt5eoiwIhpXRgYeGaKQ1OHpAW wRsAJZUdx4cdLZ4Ow5pGR+aKB8dCxvya11wriziWHHTYGcMzXsTcXQ/xxUvYngN7faPvLRYLtJed CKWa5nddFO2A/PJ6pBdQF8qoXhohPqMcsCsqlF0rThGvj7jbHIPhPJuE9YxgH3//5tdfsWF3jlwq zt5RMZmIB8msixXCH36QYoGkaEajUPojTp/1vGlxvavQcWZwlxu7+tNX6BwHv1wXCixSTyCtwsqQ hAE8ZjdNDie7EnerulnLJVk+gF6A5PwEySKW7DMJpwS/iUUR4zLs+AIumG2Sw2bBjmO8+OEH2dwP W0t0DR5b7AcCvJ2Y2VwttYnm/I8oL1/DJt/MyWCfWDjxTWevyDNcM2BfJGCYdqlKQcKuT7LpgC0B /rA3wSzgkLqr7La8vkSdLtXpJXdMGWRnhBeZ6fLf9BP0k+XTBSzKQkybZ5Lynd/tvwWux63Hjirc YlwfLE3wPBfb4zZS38XCbbCILAxhjPjkBHl2KbY7yzwGjqpuUZJ0SV12svzJkH/1BzP20lTosi3q bKcgQRE/ga0MLiyPTs9g7zZwM6NHrlemVT0ZEKNdFvXiKU3MO4DrDFjFvl6fgnbMhhgkJkNXLpao re8g4w1c5SspBC1yZlSgVpULd7GUtEy/pSOP0YQn30rQG0mXg5A2eCN1gsmAMu7JkmWvLsOTPBAu lJGPMjqrmE7IHIamW7SrPZmVjR7rOI6CDzkSdr6DuzxBl9NRyEYYhcgozbOivb0rf8b+l591A7F3 9d4ItgtCXLeCzHAWL3D66jtc36xV6or8wFGf1Ss0zASLNdxiC5fX0rJEGI3PXyJerp4uYE0KCJN8 i5lrOwjkfVsftz7FdWiuS89ZNLXSn3WKZcY6qFzg7Hbwyq3cZKzsCl6ZwUnpFG2MDVxqVUlIjhGk UwChLDA7UFXpyqyCeJWkTSQAOgrg+wEWaYqW3K4CsKcmhWGMGmbF6MhjwHST2ZAUSirCJCrAP/mo SYSGOOJJArhFjYyBb+jgt/Thq9AMrkZ9qCW/OD8F7VCLmyv9dqiZu15DxORDMfObMDBqSlkNia4j v4xUDeZoxLScAXWwQOi5Coae5QlL+vn//j+F83mUTCYDnlI12x2aq0t1QePU8KBues5YdrAXK6lg rG/WsO0t3DCF+zLEsNsZ1VN+tkqTIZLK4BETK0vcXF6hLEts/vJnVDSf7YDgx3/B4sd/xuIf/rOu V727Rv3zv6H+j/8HLXG51SvELK/JMXui5d41TDCKjN23YPWI9Sn8qTleKK1yml4+8w6hFgOB52vk hXImKHYKSMbui+4xQOO6AqgrxWfSDNi6H5RRsRzhgC87YEOUwrJSYUAeu3RxKospK4x1xx/C0HgT MpsQ7mWCEuVYaOIqqvc9y0gdM0c6qC0oO2QW5fUaRxHZk4GVDsrsCLYVvLaE29U4XSRYOj08DlgX FtrsxrC/iXB3tmYNeWYkXDIQMDpS+TQgcZZKnHxujhoRRqJfIi3lwxh11aD4y59k59WenAPJUppg RZaL0uCRIGtzptIRPYNsdpLTZJNGCsIwYEkA3g3FmuecJuVwyGkjq5+v1xMDY8lMagQJp9aAYHmC 5Md/RvTdf0Jy8T38xSlacufaFo2fyLqtLYnTMdjOsdYnpjVMWZW52z8s7/tt3V5zJvtjsqvxbwpY bPc/5+6g1qgnHqYJit1SWQiZ7mypsyVv9ZY2Qe3RFNXM9RlDWQtW0yB7/avJ9Nlno3Df4gROEiv7 cRcn8JanUrbcZjm8OIY7fC8mNgNdSYsxh356FmxqU41effddUsOXOpRqeg9kFEEszUZwdgGHgnUV reh7BLRr51FtLtHZLV59/wqLkwsFg92bDgXHhziOxNyOIPqY3RH0t+nzJ0Krq6AbJaESAmlQUa0z COWG3BOaaVsjwEfcLiMXjN1H6t83mtGsLQd1UaMsGyNbRAUIzQz2hhvFPUsZaZaMOg66P1Nbf5zx HCzUpDeQrOza+h2O/sT/8M9I//CviM6+hxfEynqzfGeMYOk0/cd/gZ1tVCqyI/mUMeEdHhY/MPJN G3GtYxswPtb1qW+iAGdmCBJoe94RSzgopV+k0kD6ACUJSjjl1jDGKaFbWwipRS7/PLLRa9EUdPtv jK+fdNiTFZzzF/j+YqXN3gYJOk4E1KUceNJFIiE+btzdJkR1fQPf7pFyiNgGrud64rPLqu6kTXVS SwC4yJU8TNIxaLVVNcqCiE35VQGvyjHscvHJOlpcdQWSH1+otGIGZspNIHFICLUk+6yOILlgUYTT 8zOEaapsa1u24lHtNpv/v70z723kyq74qb1YFElJvXsyNiaYQTB/5vt/iyBBEAyQGWcc2+3u1sKl 9iX43VclsWlKvdvWIK/Rlpsii2SR79a95557jramMNoqrnulSWQBjEyqrlpFBPa8UJDnSkzHXWqi SG0xOHpDvjPgmzdjagoA4RbwGpWokTa14dBgft12bXOYTAJEJyu1P35n5N6AjJXZwyhV8uSFKt7n 9YVOHsWWeW23W+uknj59rqd//hdFYaTaw0F79atkWNPeOEocPfTS+/8s68t8AE6S9hacfegL3fW+ 3Cm8+klhk9sg8xTG4QS1RW6qB60yA7zvI2+w4TI6cWw6cKhqp6ApjPnOnF+omYH3YEBkMihnkhn8 7DSOpqmTjIyVRXtlIY7TWwJFjppDay4/ReEbtYIMzQxem1JhWdqYUZvE1mUzZYOqMjnnvCIr6rRD SSI9URTPrEREbjjOS8c27wcVVWsBbXt1rc3FGw11pRS55GdPEQWzsSUCQ9rXxqeCnlACumN1//dv rYtsNJEkVXN9oWR1plkyk1CBSGJd/3hpTtFDmDjxQoaeT5aqy8rwNcxXkbYhCTGssW7kt51e/u1b nSxPlURzO5dpOtMsnaksmCOk3Rho16LqurDbf+l4AAUE81j7Xtx3xwnP+tR111jK4e+/5PqtBN5D o4qJh/UPsUYxKTpObcjYx6m8R638auEMQa2Mca16w+7mK3nZ4sZGnU1lGujW/3duMusNGu7OqzCI IjNZbWB41536qEOBRSUpErK9VaEteBE6aY+fW2kFITPHJee7743AaiE0iq0UgxNlAno41jDgC17F 5MHZuQ0m86mUZaUcxncN0xyMt9PV//7dzdpRtq0vDS8jmAB4z1YrnZzM3SAzM5VdpbB09vA+gc0b lJJJRp66+bkraQ2n953An8dYDWSwVg0qqMxR5lsVo8R0EAU2LE35yHsLsDvjdVLqdYgFIvnlFFzB Dgnq3XDtBsJpePSdApRgCdyoYnjSydlTrZ58pdnq/EaJAemeRJmd86Jx84d8fNBNLJj/QgKajKzh ArTbja7aR79375lZ7eM2xzKEY/pQn+IheHi8YwHw2Gu+5TvdmrD+muv2/f9jTRnQNYPnw2Yf+sRw KgaZoSYQUwpA9bYyFrVZey3QsopslIXNVW1oocNid9pafp2rYUAaCnqaOYb3KP47mT/YH7wCGVhu SleWBqHS03PbrLhG766ulL95bYA5QSeYzdUvlo5FzoAvt9EpHDuY89Wp5mdn9jz+jpLwUl4R2GYF Y8pfv7ILOfrrmFkw3kMJCaE0TlOlq5VTc+icqSvAPREC3XqzIKPMy1INy3MnW0zWyfsJAP15ZGvn zSRhkMmpC3nzMwmyKlZcuErDlqfjiMICQ835zhFWeU/m5UhQIvhg74zQHpT33imf8jvD1zBjXers xTeanz91QoLjQneecR0ww7YPTQWCjEwencfEbv/S398pWJFdMRlwZ8DaZ77f59q6H9SOBaG7rK7u ssF6V5A8DHbH2PmHwWsqvfaP/TlP8IeK9L19vsbzfGPcqQe92DBoj5+eYD3VW/BpEOAbCF7M7bUa is64U63nuXEkumcQSgOZ1niMwMAoIaO+to1OCPOGWEngGTZWwQtg3IcOF0YIguiIfSn6V53dfxYH SuNIXRIq6htdvf5BQVtZhy3omc9rrRPJ/al6yIBiN7hjqhCUkq4xwDEdToXCA3fuKtjp4G6tycj0 MMopO6PUjgkpdjQLcgD/aGZqqg1kT0lmZRYSwxBpoR2gOEuQoeQj8yFIk0kyU8isYHr2SFU0cxUP Olb4NUaJNSecdpUL+uY5aE0cJHvQ3mJMyRlFmH8hgZ/BZgbAs7my3/9R6ercMim32C9wMTFoDa1E dfsI45/WfBnpaM/nmWWo3O9zB6ypsst3uQ1k0ziY1tGANQUpHkS6TDR912b80oqadwXEfTfo/dsO 7zO9nrte013Z27H3cZ/O1WGq/K7y15/MKg9s0B/eIsC0RuA03tQhCdZp49lfuzcbGP7P9lJdEik4 Pf2A5+pVbDfalbXieabFPLvznu4zh0x62xN0gcRlblh1DYQ4iKMjCM+ITrHeart10sdR0ylE8WBA lbNRvV0r6Fqnrf70d8r+/K82b9j/9b9Me30W4sZDBijlpraAnLNn+FFi7tehgeUMJzNobb4a4zA0 vC2CKY41WIUFfqzf/+lr9afPtCkr7d68VpfnxlCvkJWBfmCqDOi64zTBqA4UBieQaA47fSufoWnO AS8qje1CAeDu3ezt2+8/pWiEy5AFNhesTL+ePxYTWpVFpWyeWuCKmZL+TGviJF5fb+05DiGpOzGs qXT6rWin36cvtb+O/fvQyea+dRiw7itfjymH7utd3Zd9TefV+cJN8PPDDVnOjqpTW9W6bmq7SudI JLMB2YxkSn4iL3FteLAkiJExmQb6V8OgTV7KQ9YFrSbOV+M6iGzGUIlmaa/W70cbdb68nY2N2Lm1 2cK3da2Ovk7UFkpA8yvbhDeD0szKcZFmABl7sfnCSqgs8hWvThX7KCwMSqpadYBnoDODUBYrKS/l X1U6S0PFQzpCkq6DmASuK0kpFs6WevTiKxs+BpOpf3qlOm+Ne4aGFUoSlK2Qt+j40Tk0yssgbX74 TmsoDQDwbFt+cpGGEOp5irPMZiKHcQwITbAYAw7ccQD7zXswUBaj51U6TJHgvNtaUKCR4b6TOOhQ jt6936f7fe5GEe+nqmrttrn9nJKQ/XUv6D4RSafNdTgk/VtY78pg3jfDumvd98XfP9ax59nHAo+9 ruknNuiOm/1wF/QMFEEjSkCAXs9JrVj1Ng4lo5seIrFLTsOVnFARRQb8GlERidKqMMsrgOMeHhSS yV7vwOLxmCw3AL0nfby3yO4mM4npzjcZL/8xxQg2qfO4ucm7uE9INlJqhmRyRCAFrI5d980GjSUv pqTsDPtigjqFUFrhNg0T1nUEKSsJChBZwcY4D2Z+0dYq2sY0t5oiV1MU7rzNMiVJaE7TRlUYX1Nb Vbr+8Qdty0YVVJAgUYfX41T+IR9tGBia806cEOa9g8s6ay5AE7HXHmKD1jo7IIIhF5Yyd9jW2E1l ISr5bvx6dLj+TEGL+GINjh1D2tV4wf8IPaxjm/KhcbMOg8eHPvZ9bj8MWPu3T7ftZ237HzQfvCUJ n9CQ+NUXAWVozX05Q8HS/PN8k/hl8DYNpBkEUMOHnFSJWcyPb7etsaFqTJXAmNloUWERBimTVjtz iIFnf8mIyBicXA0O2odX45sdb8tlYLfloNOx6s3uau9e7nc9w9e9Uic0qtKkuXidkEtHOoSjuhoI z/2Z2yOwgsuBn41tA7uvs91y5wB5nM1PL10WsctN3QEaiAUMBov5/OlY0hGFW0XToMqV7y6dG3SU KMwiB84bRSFyzth0ZekaGgHWN9yKCwbgWYyHYYgUNfpgMEohjLrOok0GoEBqlaIbC6N83i8R71uT EfDn6BY66kJpg902qfApAn7TZpvmDH/t8vBD1i8VBO4qIafycH+9HbD2wasHGqysRd7Ibwrj/nR+ b5vZTE0NcPa0ilyJZIoU+N1xdeYn2le+b4PJdAxRV6B7hbwy3a1FMiqo04o3kq1TbwCD6k2XvNCu IltozQKM7ICyiMdMZY9pw1Nm8teAb2o0hzFNeZfTwvKdqF03qKLlPw41040E3+I1l3VnDskw4K1L OdQqtbMGgB0XagIGqmOw60PntEPAtJGjly/VlYUT7ysqBfm1DSZXVWmBjCi5PDvTjPOQrxW144A3 kjehb2oSHqYQEGM5bgKLPlALj8zkj3Fm5gxVLpBZBh9YWepVtWZJpArMtA+ML8Yws8CqLOg40vj7 rs+1rzgO54L50fuC1QcrjjoMiMBFF+FhBKx9QP5LdDMO/31XB/TY/W8eM860PdTkilUXG21fv9L6 4qUSM5nwDG/BgzBM56pRSqhrtflGfbG1zwR1AMiPPtLIaSb9Toqwv/JRDsD0oNK6Ka1sajeV/Iu1 HduDLwR7G4E6gpYZPfiKZ0sT/kMRtPJDbSonM9z7sVmP0SVM9oX/prb8TRbmfP1oBuzevLFSzlnD T0D9qIh68cZkiw2I9nx7rqGvjUeVPX2h5bNniqPAtNfT1ULpfG7PcX291uVf/kfd1RvL8shz6GAa Dkc2mmXq0zOdLzPjWW0uQsuKrPMZx2qW5xoWvPfYkgecsUMf7AtKhG+dShPPQUYHJjszm7wfuqbZ Qtk5YomVBdt5Ks1Xj3X+1TemMc/eJth/yOL4n5q8GMjfkCU3lpV/donkW5rAbwvLumsdlmpfgux2 rBw8RtXYT5+n39vGRR73AUcrax7sNhp21wpghZNojEGLAeVsubQMinEPbNhxXzG0xQvNaHV+gtsL g8O9kiYxWgMt+DXKpDSJ+kZdiXqD4zEFGYxsgG+0zzFfkMLZwoaIw9nMMgdwKsielGpwt/o4Uurj vOPmHd/WKHXLnKYhqYKVYV6KJPLNfcbyFa0rMDDA7jErGdA6p9tHaKMjN47rmDoEo260/icoBSoE mvT22NCCkalKwEQfeq2ePdY8m6nYFZZ9ok7KXjP5ms3GFE47BPQw+BgqA9gbpgE6Rp0GBVCp2sam CgxjyxYmXshXEEkfsrH5cqX5yUrz1SOTVnaY1bsaUrdzCaaI4d9PeXqfRRmLHDSY1TS//EU03R/K 5jrMeD7HbOSxwHSsjj8MjncB8qbqWNcP5pz+fA3q21phuVZQbw3IDgkghk4HdvU2DSwyrAqVAXAf ZzvF/oY0aiqkdMqSWKmPn6DbxIzvhP6gGk0HA6wbawbCveKxECYJLDZq4/s2HNz0no2bgAlRAEYj bYQASsY0ZUvHzja3mc27y3ndxfnmtwDbcMIIIpSdFKC0+kcrMjvAEdBRpwAABHVJREFU29gZx0Cx c8idzAvAOZLRWhKsOSQkTt8CmJWXpmjaan29MYmexjqCjvJivK9yZ0qmTQRA78w06CQarYERL+ST AdGN2wcfq3PejUoUxalmJ9iFLbVcnWm+WCrBhBYjCuIt5NOxY33zXRwleCw4jVmYbhRyA/u8PpaI zfOVZW3EUOpxe8732AIfEbBuXUh+y2ufMHqMdvCxxzwWePb/Pa2b8ZM9ftg+N4sP2jBByIkoTD7U gGVee4WidmemD/CNbJOSMGFGGkPnpE0eqLMNGhofiQd2bL66UZUXaiE2Vth9uRKpat3ISg9RMYjV MmkCr2jq1hmuBc7lNu4wW6j0IjUlHcDCnie1WZQBWV3rmt0A4GNsuVmGmwFOh27QeLczs4WGTtxe BQkyBKViyJYuoPH5o4pQ5AZ2Gwge3G4pXqcFHiRdcPPJGw2LMxuGdhhUoiFbqb2+UHP52ighby7X qjgPdOXLysIhFwE7VwPYnBsvssnIUU+McwSozhiPXTyyuYLVqXVCybKgN6yePNPzf/pay7MnmjGz CM9qZAGAzZlkM8GPwGVZ6MgIsEzKd0qxNECG21nP9yWN3jINnPmGYYJtp6KoVJW1ZrPZe8O34S/Z cfulg9UhF+pzHHc/W3N1/y314y6u2LFz9jah8eEuNk5fbhyeEyZGhmyuLx0dISSzmskLE7VRrDLu VM+W6uYuwyoYvbhaa4sPn+dr1/RKBxAXqcQpBlO/TaV+caZmFpggXY29/OsLRWePdPL4ibzV0rKi k8WZgs1G69evdL0r1M5PVWDTVeemuoAuVdc7LXmjRNz2BaX5qbInz7RcrUynq/iPf1P16qU85FVu kg0XoNDjWv3hTwpnmXXuqqtL1d/9twXc9uTUKAcG7NNQAOsdSkUdBbDJoSpbZNaAiBAqjFL1z/6g 9V//ot3m0srgy85Xvs4t85x3nVIz0nAvojM9ek9htVOD3vt8YaNF9l2k9J3NNURn8udzzU7mhtch 8bx6/rWeff1HPX3+4qaMm7AnvpP8f8ao0Nh5HfYC1j4l5GMXr48xGzIqM9sYMzkwK84TQoLvu1c/ KGBNb5Q3Tc3Jz4dEcfjUEz8Fp/uOexfz/efjQfcVJw9j2Ze7bTVrt8oIKN6JtkOrXVcavkSGRVm3 Wi4Nl0HOJS/X6lukS6S0DrXLCwsMjPEUHRvSMbJrL1LuJ2qzM6WLRw4XawrNkaz5/lJx32iZpXr8 yM38Xbaemu1a9dWlesiq8pR5rbK+MmCbh6Vef+PETKDNRjt6n5GfKNI8xanGV+LTGeyMx7S/THuq a7Vdb0wkD5OHfvlIwTeB5pSvBKF8p+//9q119jB6OH36RMvTpe2TVehKVOtXMfd3daH1f/67trtS NX29dKEdzs+oKMSovfsqo1RNsjAjigF3pVkmLU5ts1Naw6vy4pnSR8+02W7V1KWqi0Ld1WttJS2/ /mfNl6c6WbrXMK1pL7/9nZy+ryMv8BOvpWRUwB1wq+iATqok0xaxLNHK0fcnof4fRKyxJw5SSI4A AAAASUVORK5CYII=