20240702 15520400 1.0 ISO 19139 Metadata Implementation Specification GML3.2 FALSE CalculateField prgp_20240111 prgp_obs [obs] VB # CalculateField prgp_20240111 prgp_nome [prgp] VB # CalculateField prgp_20240111 prgp_ordem [prgp] VB # CalculateField prgp_20240111 prgp "PRGP" VB # DeleteField prgp_20240111 aigp;aigp_id;aigp_sigla;aigp_nome;aigp_ps;aigp_obs;aigp_ha;ca;ca_id;ca_nome;ca_ps;ca_obs;ca_ha FeatureClassToFeatureClass ptp_20240111_gdb E:\SIG\ptp_prgp ptp_novo.shp # "OBJECTID "OBJECTID" true true false 4 Long 0 0 ,First,#,ptp_20240111_gdb,OBJECTID,-1,-1;prgp "prgp" true true false 10 Text 0 0 ,First,#,ptp_20240111_gdb,prgp,-1,-1;ptp_prgp "ptp_prgp" true true false 10 Text 0 0 ,First,#,ptp_20240111_gdb,ptp_prgp,-1,-1;prgp_id "prgp_id" true true false 25 Text 0 0 ,First,#,ptp_20240111_gdb,prgp_id,-1,-1;prgp_sigla "prgp_sigla" true true false 10 Text 0 0 ,First,#,ptp_20240111_gdb,prgp_sigla,-1,-1;prgp_nome "prgp_nome" true true false 150 Text 0 0 ,First,#,ptp_20240111_gdb,prgp_nome,-1,-1;prgp_ordem "prgp_ordem" true true false 150 Text 0 0 ,First,#,ptp_20240111_gdb,prgp_ordem,-1,-1;prgp_ps "prgp_ps" true true false 50 Text 0 0 ,First,#,ptp_20240111_gdb,prgp_ps,-1,-1;prgp_obs "prgp_obs" true true false 150 Text 0 0 ,First,#,ptp_20240111_gdb,prgp_obs,-1,-1;prgp_ha "prgp_ha" true true false 8 Double 0 0 ,First,#,ptp_20240111_gdb,prgp_ha,-1,-1;Shape_Leng "Shape_Leng" false true true 8 Double 0 0 ,First,#,ptp_20240111_gdb,Shape_Length,-1,-1;Shape_Area "Shape_Area" false true true 8 Double 0 0 ,First,#,ptp_20240111_gdb,Shape_Area,-1,-1" # CalculateField ptp_novo prgp_ps "Para publicação" VB # CalculateField prgp_20240702_completo reot_leg "PRGP em curso" VB # CalculateField prgp_20240702_completo reot_leg "PRGP previsto" VB # Rename F:\sig_ptp\prgp_20240702_completo.shp F:\sig_ptp\prgp.shp ShapeFile Rename F:\sig_ptp\prgp.shp F:\sig_ptp\ptp_prgp.shp ShapeFile 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=D:\ptp_sig</WorkspaceConnectionString><WorkspaceFactory>Shapefile</WorkspaceFactory><Dataset>ptp_prgp.shp</Dataset><DatasetType>esriDTFeatureClass</DatasetType></CIMStandardDataConnection>" <operationSequence><workflow><AddField><field_name>area_ha</field_name><field_type>DATE</field_type><field_is_nullable>False</field_is_nullable><field_is_required>False</field_is_required></AddField></workflow></operationSequence> 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=D:\ptp_sig</WorkspaceConnectionString><WorkspaceFactory>Shapefile</WorkspaceFactory><Dataset>ptp_prgp.shp</Dataset><DatasetType>esriDTFeatureClass</DatasetType></CIMStandardDataConnection>" <operationSequence><workflow><DeleteField><field_name>area_ha</field_name></DeleteField></workflow></operationSequence> 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/3.1.0'><WorkspaceConnectionString>DATABASE=C:\ptp_sig</WorkspaceConnectionString><WorkspaceFactory>Shapefile</WorkspaceFactory><Dataset>ptp_prgp.shp</Dataset><DatasetType>esriDTFeatureClass</DatasetType></CIMStandardDataConnection>" <operationSequence><workflow><AddField><field_name>prgp_sit</field_name><field_type>TEXT</field_type><field_length>150</field_length><field_is_nullable>False</field_is_nullable><field_is_required>False</field_is_required></AddField></workflow></operationSequence> CalculateField "PRGP\Programas de Reordenamento e Gestão da Paisagem" prgp_sit !prgp_ps! "Python 3" # Text NO_ENFORCE_DOMAINS CalculateField "PRGP\Programas de Reordenamento e Gestão da Paisagem" prgp_sit 'Limite preliminar' "Python 3" # Text NO_ENFORCE_DOMAINS CalculateGeometryAttributes PRGP\ptp_prgp "prgp_ha AREA" # Hectares PROJCS["ETRS_1989_Portugal_TM06",GEOGCS["GCS_ETRS_1989",DATUM["D_ETRS_1989",SPHEROID["GRS_1980",6378137.0,298.257222101]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Transverse_Mercator"],PARAMETER["False_Easting",0.0],PARAMETER["False_Northing",0.0],PARAMETER["Central_Meridian",-8.133108333333334],PARAMETER["Scale_Factor",1.0],PARAMETER["Latitude_Of_Origin",39.66825833333333],UNIT["Meter",1.0]],VERTCS["Cascais",VDATUM["Cascais"],PARAMETER["Vertical_Shift",0.0],PARAMETER["Direction",1.0],UNIT["Meter",1.0]] "Same as input" CalculateField "PTP - PRGP\Programas de Reordenamento e Gestão da Paisagem" prgp_sit 'Em curso' Python # Text NO_ENFORCE_DOMAINS ExportFeatures ptp_prgp C:\sig_ptp\ptp_prgp_new.shp # NOT_USE_ALIAS "OBJECTID "OBJECTID" true true false 10 Long 0 10,First,#,ptp_prgp,OBJECTID,-1,-1;prgp "prgp" true true false 10 Text 0 0,First,#,ptp_prgp,prgp,0,9;prgp_id "prgp_id" true true false 25 Text 0 0,First,#,ptp_prgp,prgp_id,0,24;prgp_sigla "prgp_sigla" true true false 10 Text 0 0,First,#,ptp_prgp,prgp_sigla,0,9;prgp_nome "prgp_nome" true true false 150 Text 0 0,First,#,ptp_prgp,prgp_nome,0,149;prgp_ordem "prgp_ordem" true true false 150 Text 0 0,First,#,ptp_prgp,prgp_ordem,0,149;prgp_ps "prgp_ps" true true false 50 Text 0 0,First,#,ptp_prgp,prgp_ps,0,49;prgp_obs "prgp_obs" true true false 150 Text 0 0,First,#,ptp_prgp,prgp_obs,0,149;prgp_ha "prgp_ha" true true false 19 Double 0 0,First,#,ptp_prgp,prgp_ha,-1,-1;reot_leg "reot_leg" true true false 75 Text 0 0,First,#,ptp_prgp,reot_leg,0,74;prgp_sit "prgp_sit" true true false 150 Text 0 0,First,#,ptp_prgp,prgp_sit,0,149" # 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/3.4.0'><WorkspaceConnectionString>DATABASE=C:\sig_ptp</WorkspaceConnectionString><WorkspaceFactory>Shapefile</WorkspaceFactory><Dataset>ptp_prgp_new</Dataset><DatasetType>esriDTFeatureClass</DatasetType></CIMStandardDataConnection>" <operationSequence><workflow><AddField><field_name>area_ha</field_name><field_type>DOUBLE</field_type><field_is_nullable>False</field_is_nullable><field_is_required>False</field_is_required></AddField></workflow></operationSequence> CalculateGeometryAttributes ptp_prgp_new "area_ha AREA" # HECTARES PROJCS["ETRS_1989_Portugal_TM06",GEOGCS["GCS_ETRS_1989",DATUM["D_ETRS_1989",SPHEROID["GRS_1980",6378137.0,298.257222101]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Transverse_Mercator"],PARAMETER["False_Easting",0.0],PARAMETER["False_Northing",0.0],PARAMETER["Central_Meridian",-8.133108333333334],PARAMETER["Scale_Factor",1.0],PARAMETER["Latitude_Of_Origin",39.66825833333333],UNIT["Meter",1.0]],VERTCS["Cascais",VDATUM["Cascais"],PARAMETER["Vertical_Shift",0.0],PARAMETER["Direction",1.0],UNIT["Meter",1.0]] SAME_AS_INPUT CalculateGeometryAttributes ptp_prgp_new "area_ha AREA" # HECTARES PROJCS["ETRS_1989_Portugal_TM06",GEOGCS["GCS_ETRS_1989",DATUM["D_ETRS_1989",SPHEROID["GRS_1980",6378137.0,298.257222101]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Transverse_Mercator"],PARAMETER["False_Easting",0.0],PARAMETER["False_Northing",0.0],PARAMETER["Central_Meridian",-8.133108333333334],PARAMETER["Scale_Factor",1.0],PARAMETER["Latitude_Of_Origin",39.66825833333333],UNIT["Meter",1.0]],VERTCS["Cascais",VDATUM["Cascais"],PARAMETER["Vertical_Shift",0.0],PARAMETER["Direction",1.0],UNIT["Meter",1.0]] SAME_AS_INPUT CalculateGeometryAttributes ptp_prgp_new "prgp_ha AREA" # HECTARES PROJCS["ETRS_1989_Portugal_TM06",GEOGCS["GCS_ETRS_1989",DATUM["D_ETRS_1989",SPHEROID["GRS_1980",6378137.0,298.257222101]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Transverse_Mercator"],PARAMETER["False_Easting",0.0],PARAMETER["False_Northing",0.0],PARAMETER["Central_Meridian",-8.133108333333334],PARAMETER["Scale_Factor",1.0],PARAMETER["Latitude_Of_Origin",39.66825833333333],UNIT["Meter",1.0]],VERTCS["Cascais",VDATUM["Cascais"],PARAMETER["Vertical_Shift",0.0],PARAMETER["Direction",1.0],UNIT["Meter",1.0]] SAME_AS_INPUT DeleteField ptp_prgp_new prgp_ps DELETE_FIELDS DeleteField ptp_prgp_new reot_leg DELETE_FIELDS DeleteField ptp_prgp_new prgp_ordem DELETE_FIELDS CalculateField ptp_prgp_new prgp_obs 'Discussão pública - 30-maio/30-junho de 2025' PYTHON3 # TEXT NO_ENFORCE_DOMAINS CalculateField ptp_prgp_new prgp_obs 'Discussão pública - 05-maio/16-junho de 2025' PYTHON3 # TEXT NO_ENFORCE_DOMAINS 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/3.4.0'><WorkspaceConnectionString>DATABASE=C:\sig_ptp</WorkspaceConnectionString><WorkspaceFactory>Shapefile</WorkspaceFactory><Dataset>ptp_prgp_new</Dataset><DatasetType>esriDTFeatureClass</DatasetType></CIMStandardDataConnection>" <operationSequence><workflow><AddField><field_name>fonte</field_name><field_type>TEXT</field_type><field_length>100</field_length><field_is_nullable>False</field_is_nullable><field_is_required>False</field_is_required></AddField></workflow></operationSequence> DeleteField ptp_prgp_new prgp_sit DELETE_FIELDS DeleteField ptp_prgp_new prgp_id DELETE_FIELDS 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/3.4.0'><WorkspaceConnectionString>DATABASE=C:\sig_ptp</WorkspaceConnectionString><WorkspaceFactory>Shapefile</WorkspaceFactory><Dataset>ptp_prgp_new</Dataset><DatasetType>esriDTFeatureClass</DatasetType></CIMStandardDataConnection>" <operationSequence><workflow><AddField><field_name>prgp_id</field_name><field_type>LONG</field_type><field_is_nullable>False</field_is_nullable><field_is_required>False</field_is_required></AddField></workflow></operationSequence> CalculateField ptp_prgp_new prgp_id !OBJECTID_1! PYTHON3 # TEXT NO_ENFORCE_DOMAINS CalculateField ptp_prgp_new prgp_id !OBJECTID_1! PYTHON3 # TEXT NO_ENFORCE_DOMAINS DeleteField ptp_prgp_new OBJECTID_1 DELETE_FIELDS CalculateGeometryAttributes ptp_prgp_new "area_ha AREA" # HECTARES PROJCS["ETRS_1989_Portugal_TM06",GEOGCS["GCS_ETRS_1989",DATUM["D_ETRS_1989",SPHEROID["GRS_1980",6378137.0,298.257222101]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Transverse_Mercator"],PARAMETER["False_Easting",0.0],PARAMETER["False_Northing",0.0],PARAMETER["Central_Meridian",-8.133108333333334],PARAMETER["Scale_Factor",1.0],PARAMETER["Latitude_Of_Origin",39.66825833333333],UNIT["Meter",1.0]],VERTCS["Cascais",VDATUM["Cascais"],PARAMETER["Vertical_Shift",0.0],PARAMETER["Direction",1.0],UNIT["Meter",1.0]] SAME_AS_INPUT CalculateGeometryAttributes ptp_prgp_new "area_ha AREA" # HECTARES PROJCS["ETRS_1989_Portugal_TM06",GEOGCS["GCS_ETRS_1989",DATUM["D_ETRS_1989",SPHEROID["GRS_1980",6378137.0,298.257222101]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Transverse_Mercator"],PARAMETER["False_Easting",0.0],PARAMETER["False_Northing",0.0],PARAMETER["Central_Meridian",-8.133108333333334],PARAMETER["Scale_Factor",1.0],PARAMETER["Latitude_Of_Origin",39.66825833333333],UNIT["Meter",1.0]],VERTCS["Cascais",VDATUM["Cascais"],PARAMETER["Vertical_Shift",0.0],PARAMETER["Direction",1.0],UNIT["Meter",1.0]] SAME_AS_INPUT CalculateGeometryAttributes ptp_prgp_new "area_ha AREA" # HECTARES PROJCS["ETRS_1989_Portugal_TM06",GEOGCS["GCS_ETRS_1989",DATUM["D_ETRS_1989",SPHEROID["GRS_1980",6378137.0,298.257222101]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Transverse_Mercator"],PARAMETER["False_Easting",0.0],PARAMETER["False_Northing",0.0],PARAMETER["Central_Meridian",-8.133108333333334],PARAMETER["Scale_Factor",1.0],PARAMETER["Latitude_Of_Origin",39.66825833333333],UNIT["Meter",1.0]],VERTCS["Cascais",VDATUM["Cascais"],PARAMETER["Vertical_Shift",0.0],PARAMETER["Direction",1.0],UNIT["Meter",1.0]] SAME_AS_INPUT CalculateGeometryAttributes ptp_prgp_new "area_ha AREA" # HECTARES PROJCS["ETRS_1989_Portugal_TM06",GEOGCS["GCS_ETRS_1989",DATUM["D_ETRS_1989",SPHEROID["GRS_1980",6378137.0,298.257222101]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Transverse_Mercator"],PARAMETER["False_Easting",0.0],PARAMETER["False_Northing",0.0],PARAMETER["Central_Meridian",-8.133108333333334],PARAMETER["Scale_Factor",1.0],PARAMETER["Latitude_Of_Origin",39.66825833333333],UNIT["Meter",1.0]],VERTCS["Cascais",VDATUM["Cascais"],PARAMETER["Vertical_Shift",0.0],PARAMETER["Direction",1.0],UNIT["Meter",1.0]] SAME_AS_INPUT CalculateGeometryAttributes ptp_prgp_new "prgp_ha AREA" # HECTARES PROJCS["ETRS_1989_Portugal_TM06",GEOGCS["GCS_ETRS_1989",DATUM["D_ETRS_1989",SPHEROID["GRS_1980",6378137.0,298.257222101]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Transverse_Mercator"],PARAMETER["False_Easting",0.0],PARAMETER["False_Northing",0.0],PARAMETER["Central_Meridian",-8.133108333333334],PARAMETER["Scale_Factor",1.0],PARAMETER["Latitude_Of_Origin",39.66825833333333],UNIT["Meter",1.0]],VERTCS["Cascais",VDATUM["Cascais"],PARAMETER["Vertical_Shift",0.0],PARAMETER["Direction",1.0],UNIT["Meter",1.0]] SAME_AS_INPUT CalculateGeometryAttributes ptp_prgp_new "area_ha AREA" # HECTARES PROJCS["ETRS_1989_Portugal_TM06",GEOGCS["GCS_ETRS_1989",DATUM["D_ETRS_1989",SPHEROID["GRS_1980",6378137.0,298.257222101]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Transverse_Mercator"],PARAMETER["False_Easting",0.0],PARAMETER["False_Northing",0.0],PARAMETER["Central_Meridian",-8.133108333333334],PARAMETER["Scale_Factor",1.0],PARAMETER["Latitude_Of_Origin",39.66825833333333],UNIT["Meter",1.0]],VERTCS["Cascais",VDATUM["Cascais"],PARAMETER["Vertical_Shift",0.0],PARAMETER["Direction",1.0],UNIT["Meter",1.0]] SAME_AS_INPUT CalculateGeometryAttributes ptp_prgp_new "prgp_ha AREA" # HECTARES PROJCS["ETRS_1989_Portugal_TM06",GEOGCS["GCS_ETRS_1989",DATUM["D_ETRS_1989",SPHEROID["GRS_1980",6378137.0,298.257222101]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Transverse_Mercator"],PARAMETER["False_Easting",0.0],PARAMETER["False_Northing",0.0],PARAMETER["Central_Meridian",-8.133108333333334],PARAMETER["Scale_Factor",1.0],PARAMETER["Latitude_Of_Origin",39.66825833333333],UNIT["Meter",1.0]],VERTCS["Cascais",VDATUM["Cascais"],PARAMETER["Vertical_Shift",0.0],PARAMETER["Direction",1.0],UNIT["Meter",1.0]] SAME_AS_INPUT CalculateGeometryAttributes ptp_prgp_new "area_ha AREA" # HECTARES PROJCS["ETRS_1989_Portugal_TM06",GEOGCS["GCS_ETRS_1989",DATUM["D_ETRS_1989",SPHEROID["GRS_1980",6378137.0,298.257222101]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Transverse_Mercator"],PARAMETER["False_Easting",0.0],PARAMETER["False_Northing",0.0],PARAMETER["Central_Meridian",-8.133108333333334],PARAMETER["Scale_Factor",1.0],PARAMETER["Latitude_Of_Origin",39.66825833333333],UNIT["Meter",1.0]],VERTCS["Cascais",VDATUM["Cascais"],PARAMETER["Vertical_Shift",0.0],PARAMETER["Direction",1.0],UNIT["Meter",1.0]] SAME_AS_INPUT CalculateGeometryAttributes ptp_prgp_new "prgp_ha AREA" # HECTARES PROJCS["ETRS_1989_Portugal_TM06",GEOGCS["GCS_ETRS_1989",DATUM["D_ETRS_1989",SPHEROID["GRS_1980",6378137.0,298.257222101]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Transverse_Mercator"],PARAMETER["False_Easting",0.0],PARAMETER["False_Northing",0.0],PARAMETER["Central_Meridian",-8.133108333333334],PARAMETER["Scale_Factor",1.0],PARAMETER["Latitude_Of_Origin",39.66825833333333],UNIT["Meter",1.0]],VERTCS["Cascais",VDATUM["Cascais"],PARAMETER["Vertical_Shift",0.0],PARAMETER["Direction",1.0],UNIT["Meter",1.0]] SAME_AS_INPUT CalculateGeometryAttributes ptp_prgp_new "area_ha AREA" # HECTARES PROJCS["ETRS_1989_Portugal_TM06",GEOGCS["GCS_ETRS_1989",DATUM["D_ETRS_1989",SPHEROID["GRS_1980",6378137.0,298.257222101]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Transverse_Mercator"],PARAMETER["False_Easting",0.0],PARAMETER["False_Northing",0.0],PARAMETER["Central_Meridian",-8.133108333333334],PARAMETER["Scale_Factor",1.0],PARAMETER["Latitude_Of_Origin",39.66825833333333],UNIT["Meter",1.0]],VERTCS["Cascais",VDATUM["Cascais"],PARAMETER["Vertical_Shift",0.0],PARAMETER["Direction",1.0],UNIT["Meter",1.0]] SAME_AS_INPUT CalculateGeometryAttributes ptp_prgp_new "prgp_ha AREA" # HECTARES PROJCS["ETRS_1989_Portugal_TM06",GEOGCS["GCS_ETRS_1989",DATUM["D_ETRS_1989",SPHEROID["GRS_1980",6378137.0,298.257222101]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Transverse_Mercator"],PARAMETER["False_Easting",0.0],PARAMETER["False_Northing",0.0],PARAMETER["Central_Meridian",-8.133108333333334],PARAMETER["Scale_Factor",1.0],PARAMETER["Latitude_Of_Origin",39.66825833333333],UNIT["Meter",1.0]],VERTCS["Cascais",VDATUM["Cascais"],PARAMETER["Vertical_Shift",0.0],PARAMETER["Direction",1.0],UNIT["Meter",1.0]] SAME_AS_INPUT CalculateGeometryAttributes ptp_prgp_new "area_ha AREA" # HECTARES PROJCS["ETRS_1989_Portugal_TM06",GEOGCS["GCS_ETRS_1989",DATUM["D_ETRS_1989",SPHEROID["GRS_1980",6378137.0,298.257222101]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Transverse_Mercator"],PARAMETER["False_Easting",0.0],PARAMETER["False_Northing",0.0],PARAMETER["Central_Meridian",-8.133108333333334],PARAMETER["Scale_Factor",1.0],PARAMETER["Latitude_Of_Origin",39.66825833333333],UNIT["Meter",1.0]],VERTCS["Cascais",VDATUM["Cascais"],PARAMETER["Vertical_Shift",0.0],PARAMETER["Direction",1.0],UNIT["Meter",1.0]] SAME_AS_INPUT CalculateGeometryAttributes ptp_prgp_new "prgp_ha AREA" # HECTARES PROJCS["ETRS_1989_Portugal_TM06",GEOGCS["GCS_ETRS_1989",DATUM["D_ETRS_1989",SPHEROID["GRS_1980",6378137.0,298.257222101]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Transverse_Mercator"],PARAMETER["False_Easting",0.0],PARAMETER["False_Northing",0.0],PARAMETER["Central_Meridian",-8.133108333333334],PARAMETER["Scale_Factor",1.0],PARAMETER["Latitude_Of_Origin",39.66825833333333],UNIT["Meter",1.0]],VERTCS["Cascais",VDATUM["Cascais"],PARAMETER["Vertical_Shift",0.0],PARAMETER["Direction",1.0],UNIT["Meter",1.0]] SAME_AS_INPUT CalculateGeometryAttributes ptp_prgp_new "area_ha AREA" # HECTARES PROJCS["ETRS_1989_Portugal_TM06",GEOGCS["GCS_ETRS_1989",DATUM["D_ETRS_1989",SPHEROID["GRS_1980",6378137.0,298.257222101]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Transverse_Mercator"],PARAMETER["False_Easting",0.0],PARAMETER["False_Northing",0.0],PARAMETER["Central_Meridian",-8.133108333333334],PARAMETER["Scale_Factor",1.0],PARAMETER["Latitude_Of_Origin",39.66825833333333],UNIT["Meter",1.0]],VERTCS["Cascais",VDATUM["Cascais"],PARAMETER["Vertical_Shift",0.0],PARAMETER["Direction",1.0],UNIT["Meter",1.0]] SAME_AS_INPUT CalculateGeometryAttributes ptp_prgp_new "prgp_ha AREA" # HECTARES PROJCS["ETRS_1989_Portugal_TM06",GEOGCS["GCS_ETRS_1989",DATUM["D_ETRS_1989",SPHEROID["GRS_1980",6378137.0,298.257222101]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Transverse_Mercator"],PARAMETER["False_Easting",0.0],PARAMETER["False_Northing",0.0],PARAMETER["Central_Meridian",-8.133108333333334],PARAMETER["Scale_Factor",1.0],PARAMETER["Latitude_Of_Origin",39.66825833333333],UNIT["Meter",1.0]],VERTCS["Cascais",VDATUM["Cascais"],PARAMETER["Vertical_Shift",0.0],PARAMETER["Direction",1.0],UNIT["Meter",1.0]] SAME_AS_INPUT ExportFeatures ptp_prgp_new D:\sig_ptp\ptp\ptp.gdb\ptp_prgp_new_ExportFeatures # NOT_USE_ALIAS "prgp "prgp" true true false 10 Text 0 0,First,#,ptp_prgp_new,prgp,0,9;prgp_id "prgp_id" true true false 10 Long 0 0,First,#,ptp_prgp_new,prgp_id,-1,-1;prgp_sigla "prgp_sigla" true true false 10 Text 0 0,First,#,ptp_prgp_new,prgp_sigla,0,9;prgp_nome "prgp_nome" true true false 150 Text 0 0,First,#,ptp_prgp_new,prgp_nome,0,149;prgp_obs "prgp_obs" true true false 150 Text 0 0,First,#,ptp_prgp_new,prgp_obs,0,149;prgp_ha "prgp_ha" true true false 19 Double 0 0,First,#,ptp_prgp_new,prgp_ha,-1,-1;area_ha "area_ha" true true false 19 Double 0 0,First,#,ptp_prgp_new,area_ha,-1,-1;fonte "fonte" true true false 100 Text 0 0,First,#,ptp_prgp_new,fonte,0,99" "prgp_id ASCENDING" CalculateGeometryAttributes ptp_prgp_new_ExportFeatures "area_ha AREA" # Hectares PROJCS["ETRS_1989_Portugal_TM06",GEOGCS["GCS_ETRS_1989",DATUM["D_ETRS_1989",SPHEROID["GRS_1980",6378137.0,298.257222101]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Transverse_Mercator"],PARAMETER["False_Easting",0.0],PARAMETER["False_Northing",0.0],PARAMETER["Central_Meridian",-8.133108333333334],PARAMETER["Scale_Factor",1.0],PARAMETER["Latitude_Of_Origin",39.66825833333333],UNIT["Meter",1.0]],VERTCS["Cascais",VDATUM["Cascais"],PARAMETER["Vertical_Shift",0.0],PARAMETER["Direction",1.0],UNIT["Meter",1.0]] "Same as input" ExportFeatures ptp_prgp_new_ExportFeatures D:\sig_ptp\ptp\ptp.gdb\ptp_prgp_new_ExportFeatures_ExportFeatures # NOT_USE_ALIAS "prgp "prgp" true true false 10 Text 0 0,First,#,ptp_prgp_new_ExportFeatures,prgp,0,9;prgp_id "prgp_id" true true false 4 Long 0 0,First,#,ptp_prgp_new_ExportFeatures,prgp_id,-1,-1;prgp_sigla "prgp_sigla" true true false 10 Text 0 0,First,#,ptp_prgp_new_ExportFeatures,prgp_sigla,0,9;prgp_nome "prgp_nome" true true false 150 Text 0 0,First,#,ptp_prgp_new_ExportFeatures,prgp_nome,0,149;prgp_obs "prgp_obs" true true false 150 Text 0 0,First,#,ptp_prgp_new_ExportFeatures,prgp_obs,0,149;prgp_ha "prgp_ha" true true false 8 Double 0 0,First,#,ptp_prgp_new_ExportFeatures,prgp_ha,-1,-1;area_ha "area_ha" true true false 8 Double 0 0,First,#,ptp_prgp_new_ExportFeatures,area_ha,-1,-1;fonte "fonte" true true false 100 Text 0 0,First,#,ptp_prgp_new_ExportFeatures,fonte,0,99;Shape_Length "Shape_Length" false true true 8 Double 0 0,First,#,ptp_prgp_new_ExportFeatures,Shape_Length,-1,-1;Shape_Area "Shape_Area" false true true 8 Double 0 0,First,#,ptp_prgp_new_ExportFeatures,Shape_Area,-1,-1" # ExportFeatures ptp_prgp_new_ExportFeatures_ExportFeatures D:\sig_ptp\ptp_prgp.shp # NOT_USE_ALIAS "prgp "prgp" true true false 10 Text 0 0,First,#,ptp_prgp_new_ExportFeatures_ExportFeatures,prgp,0,9;prgp_id "prgp_id" true true false 4 Long 0 0,First,#,ptp_prgp_new_ExportFeatures_ExportFeatures,prgp_id,-1,-1;prgp_sigla "prgp_sigla" true true false 10 Text 0 0,First,#,ptp_prgp_new_ExportFeatures_ExportFeatures,prgp_sigla,0,9;prgp_nome "prgp_nome" true true false 150 Text 0 0,First,#,ptp_prgp_new_ExportFeatures_ExportFeatures,prgp_nome,0,149;prgp_obs "prgp_obs" true true false 150 Text 0 0,First,#,ptp_prgp_new_ExportFeatures_ExportFeatures,prgp_obs,0,149;prgp_ha "prgp_ha" true true false 8 Double 0 0,First,#,ptp_prgp_new_ExportFeatures_ExportFeatures,prgp_ha,-1,-1;area_ha "area_ha" true true false 8 Double 0 0,First,#,ptp_prgp_new_ExportFeatures_ExportFeatures,area_ha,-1,-1;fonte "fonte" true true false 100 Text 0 0,First,#,ptp_prgp_new_ExportFeatures_ExportFeatures,fonte,0,99;Shape_Length "Shape_Length" false true true 8 Double 0 0,First,#,ptp_prgp_new_ExportFeatures_ExportFeatures,Shape_Length,-1,-1;Shape_Area "Shape_Area" false true true 8 Double 0 0,First,#,ptp_prgp_new_ExportFeatures_ExportFeatures,Shape_Area,-1,-1" # CalculateField ptp_prgp prgp 'PRGP' Python # Text NO_ENFORCE_DOMAINS CalculateField ptp_prgp prgp 'PRGP' Python # Text NO_ENFORCE_DOMAINS DeleteField ptp_prgp prgp_ha "Delete Fields" DeleteField ptp_prgp Shape_Leng "Delete Fields" DeleteField ptp_prgp Shape_Area "Delete Fields" CalculateGeometryAttributes ptp_prgp "area_ha AREA" # Hectares PROJCS["ETRS_1989_Portugal_TM06",GEOGCS["GCS_ETRS_1989",DATUM["D_ETRS_1989",SPHEROID["GRS_1980",6378137.0,298.257222101]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Transverse_Mercator"],PARAMETER["False_Easting",0.0],PARAMETER["False_Northing",0.0],PARAMETER["Central_Meridian",-8.133108333333334],PARAMETER["Scale_Factor",1.0],PARAMETER["Latitude_Of_Origin",39.66825833333333],UNIT["Meter",1.0]],VERTCS["Cascais",VDATUM["Cascais"],PARAMETER["Vertical_Shift",0.0],PARAMETER["Direction",1.0],UNIT["Meter",1.0]] "Same as input" CalculateField ptp_prgp fonte '01_PRGPSE_AI_0325.shp (25-Maio-2025)' Python # Text NO_ENFORCE_DOMAINS CalculateField ptp_prgp fonte 'LIMITE INDICATIVO - Estabelecido com base no Despacho n.º 4035/2024, de 12 de abril' Python # Text NO_ENFORCE_DOMAINS CalculateGeometryAttributes ptp_prgp "area_ha AREA" # Hectares PROJCS["ETRS_1989_Portugal_TM06",GEOGCS["GCS_ETRS_1989",DATUM["D_ETRS_1989",SPHEROID["GRS_1980",6378137.0,298.257222101]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Transverse_Mercator"],PARAMETER["False_Easting",0.0],PARAMETER["False_Northing",0.0],PARAMETER["Central_Meridian",-8.133108333333334],PARAMETER["Scale_Factor",1.0],PARAMETER["Latitude_Of_Origin",39.66825833333333],UNIT["Meter",1.0]],VERTCS["Cascais",VDATUM["Cascais"],PARAMETER["Vertical_Shift",0.0],PARAMETER["Direction",1.0],UNIT["Meter",1.0]] "Same as input" 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=D:\sig_ptp</WorkspaceConnectionString><WorkspaceFactory>Shapefile</WorkspaceFactory><Dataset>ptp_prgp.shp</Dataset><DatasetType>esriDTFeatureClass</DatasetType></CIMStandardDataConnection>" <operationSequence><workflow><AddField><field_name>ptp</field_name><field_type>TEXT</field_type><field_length>255</field_length><field_is_nullable>False</field_is_nullable><field_is_required>False</field_is_required></AddField></workflow></operationSequence> 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=D:\sig_ptp</WorkspaceConnectionString><WorkspaceFactory>Shapefile</WorkspaceFactory><Dataset>ptp_prgp</Dataset><DatasetType>esriDTFeatureClass</DatasetType></CIMStandardDataConnection>" <operationSequence><workflow><DeleteField><field_name>ptp</field_name></DeleteField></workflow></operationSequence> 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=D:\sig_ptp</WorkspaceConnectionString><WorkspaceFactory>Shapefile</WorkspaceFactory><Dataset>ptp_prgp</Dataset><DatasetType>esriDTFeatureClass</DatasetType></CIMStandardDataConnection>" <operationSequence><workflow><AddField><field_name>ptp</field_name><field_type>TEXT</field_type><field_length>25</field_length><field_is_nullable>False</field_is_nullable><field_is_required>False</field_is_required></AddField></workflow></operationSequence> DeleteField ptp_prgp prgp "Delete Fields" CalculateField ptp_prgp ptp 'PRGP' Python # Text NO_ENFORCE_DOMAINS Rename D:\sig_ptp\ptp_prgp.shp D:\sig_ptp\ptp_prgp__old.shp ShapeFile ExportFeatures ptp_prgp D:\sig_ptp\ptp\ptp.gdb\ptp_prgp_ExportFeatures1 # NOT_USE_ALIAS "ptp "ptp" true true false 25 Text 0 0,First,#,ptp_prgp,ptp,0,24;prgp_id "prgp_id" true true false 10 Long 0 0,First,#,ptp_prgp,prgp_id,-1,-1;prgp_sigla "prgp_sigla" true true false 10 Text 0 0,First,#,ptp_prgp,prgp_sigla,0,9;prgp_nome "prgp_nome" true true false 150 Text 0 0,First,#,ptp_prgp,prgp_nome,0,149;area_ha "area_ha" true true false 19 Double 0 0,First,#,ptp_prgp,area_ha,-1,-1;fonte "fonte" true true false 100 Text 0 0,First,#,ptp_prgp,fonte,0,99;prgp_obs "prgp_obs" true true false 150 Text 0 0,First,#,ptp_prgp,prgp_obs,0,149" # ExportFeatures ptp_prgp_ExportFeatures1 D:\sig_ptp\ptp_prgp.shp # NOT_USE_ALIAS "ptp "ptp" true true false 25 Text 0 0,First,#,ptp_prgp_ExportFeatures1,ptp,0,24;prgp_id "prgp_id" true true false 4 Long 0 0,First,#,ptp_prgp_ExportFeatures1,prgp_id,-1,-1;prgp_sigla "prgp_sigla" true true false 10 Text 0 0,First,#,ptp_prgp_ExportFeatures1,prgp_sigla,0,9;prgp_nome "prgp_nome" true true false 150 Text 0 0,First,#,ptp_prgp_ExportFeatures1,prgp_nome,0,149;area_ha "area_ha" true true false 8 Double 0 0,First,#,ptp_prgp_ExportFeatures1,area_ha,-1,-1;fonte "fonte" true true false 100 Text 0 0,First,#,ptp_prgp_ExportFeatures1,fonte,0,99;prgp_obs "prgp_obs" true true false 150 Text 0 0,First,#,ptp_prgp_ExportFeatures1,prgp_obs,0,149;Shape_Length "Shape_Length" false true true 8 Double 0 0,First,#,ptp_prgp_ExportFeatures1,Shape_Length,-1,-1;Shape_Area "Shape_Area" false true true 8 Double 0 0,First,#,ptp_prgp_ExportFeatures1,Shape_Area,-1,-1" "prgp_id ASCENDING" DeleteField ptp_prgp Shape_Leng "Delete Fields" DeleteField ptp_prgp Shape_Area "Delete Fields" CalculateGeometryAttributes ptp_prgp "area_ha AREA" # Hectares PROJCS["ETRS_1989_Portugal_TM06",GEOGCS["GCS_ETRS_1989",DATUM["D_ETRS_1989",SPHEROID["GRS_1980",6378137.0,298.257222101]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Transverse_Mercator"],PARAMETER["False_Easting",0.0],PARAMETER["False_Northing",0.0],PARAMETER["Central_Meridian",-8.133108333333334],PARAMETER["Scale_Factor",1.0],PARAMETER["Latitude_Of_Origin",39.66825833333333],UNIT["Meter",1.0]],VERTCS["Cascais",VDATUM["Cascais"],PARAMETER["Vertical_Shift",0.0],PARAMETER["Direction",1.0],UNIT["Meter",1.0]] "Same as input" CalculateGeometryAttributes "PTP - ÁREAS DE INTERVENÇÃO\ptp_prgp" "area_ha AREA" # HECTARES PROJCS["ETRS_1989_Portugal_TM06",GEOGCS["GCS_ETRS_1989",DATUM["D_ETRS_1989",SPHEROID["GRS_1980",6378137.0,298.257222101]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Transverse_Mercator"],PARAMETER["False_Easting",0.0],PARAMETER["False_Northing",0.0],PARAMETER["Central_Meridian",-8.133108333333334],PARAMETER["Scale_Factor",1.0],PARAMETER["Latitude_Of_Origin",39.66825833333333],UNIT["Meter",1.0]] SAME_AS_INPUT CalculateGeometryAttributes "PTP - ÁREAS DE INTERVENÇÃO\ptp_prgp" "area_ha AREA" # HECTARES PROJCS["ETRS_1989_Portugal_TM06",GEOGCS["GCS_ETRS_1989",DATUM["D_ETRS_1989",SPHEROID["GRS_1980",6378137.0,298.257222101]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Transverse_Mercator"],PARAMETER["False_Easting",0.0],PARAMETER["False_Northing",0.0],PARAMETER["Central_Meridian",-8.133108333333334],PARAMETER["Scale_Factor",1.0],PARAMETER["Latitude_Of_Origin",39.66825833333333],UNIT["Meter",1.0]] SAME_AS_INPUT Intersect "ptp_prgp #;ptp_prgp10_ag__areas_totais #" D:\sig_ptp\ptp_prgp_apga_intersect.shp "All attributes" # "Same as input" CalculateGeometryAttributes ptp_prgp_apga_intersect "area_ha_1 AREA" # Hectares PROJCS["ETRS_1989_Portugal_TM06",GEOGCS["GCS_ETRS_1989",DATUM["D_ETRS_1989",SPHEROID["GRS_1980",6378137.0,298.257222101]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Transverse_Mercator"],PARAMETER["False_Easting",0.0],PARAMETER["False_Northing",0.0],PARAMETER["Central_Meridian",-8.133108333333334],PARAMETER["Scale_Factor",1.0],PARAMETER["Latitude_Of_Origin",39.66825833333333],UNIT["Meter",1.0]],VERTCS["Cascais",VDATUM["Cascais"],PARAMETER["Vertical_Shift",0.0],PARAMETER["Direction",1.0],UNIT["Meter",1.0]] "Same as input" Rename D:\sig_ptp\ptp_prgp_apga_intersect.shp D:\sig_ptp\ptp_prgp10_ag_apga_intersect.shp ShapeFile 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=D:\sig_ptp</WorkspaceConnectionString><WorkspaceFactory>Shapefile</WorkspaceFactory><Dataset>ptp_prgp10_ag_apga_intersect.shp</Dataset><DatasetType>esriDTFeatureClass</DatasetType></CIMStandardDataConnection>" <operationSequence><workflow><AddField><field_name>area_per</field_name><field_type>DOUBLE</field_type><field_is_nullable>False</field_is_nullable><field_is_required>False</field_is_required></AddField></workflow></operationSequence> DeleteField ptp_prgp10_ag_apga_intersect prgp_obs "Delete Fields" DeleteField ptp_prgp10_ag_apga_intersect FID_ptp__1 "Delete Fields" DeleteField ptp_prgp10_ag_apga_intersect fonte "Delete Fields" DeleteField ptp_prgp10_ag_apga_intersect dgt_id "Delete Fields" DeleteField ptp_prgp10_ag_apga_intersect ptp_1 "Delete Fields" DeleteField ptp_prgp10_ag_apga_intersect prgp_id_1 "Delete Fields" DeleteField ptp_prgp10_ag_apga_intersect FID_ptp_pr "Delete Fields" DeleteField ptp_prgp10_ag_apga_intersect prgp_sigla "Delete Fields" DeleteField ptp_prgp10_ag_apga_intersect prgp_nome "Delete Fields" DeleteField ptp_prgp10_ag_apga_intersect id_objeto "Delete Fields" DeleteField ptp_prgp10_ag_apga_intersect obs "Delete Fields" DeleteField ptp_prgp10_ag_apga_intersect obs_ap "Delete Fields" DeleteField ptp_prgp10_ag_apga_intersect prgp_per "Delete Fields" 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=D:\sig_ptp</WorkspaceConnectionString><WorkspaceFactory>Shapefile</WorkspaceFactory><Dataset>ptp_prgp10_ag_apga_intersect.shp</Dataset><DatasetType>esriDTFeatureClass</DatasetType></CIMStandardDataConnection>" <operationSequence><workflow><AddField><field_name>fonte</field_name><field_type>TEXT</field_type><field_length>50</field_length><field_is_nullable>False</field_is_nullable><field_is_required>False</field_is_required></AddField></workflow></operationSequence> CalculateField ptp_prgp10_ag_apga_intersect fonte !fonte_1! Python # Text NO_ENFORCE_DOMAINS CalculateGeometryAttributes ptp_prgp10_ag_apga_intersect "area_ha AREA" # Hectares PROJCS["ETRS_1989_Portugal_TM06",GEOGCS["GCS_ETRS_1989",DATUM["D_ETRS_1989",SPHEROID["GRS_1980",6378137.0,298.257222101]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Transverse_Mercator"],PARAMETER["False_Easting",0.0],PARAMETER["False_Northing",0.0],PARAMETER["Central_Meridian",-8.133108333333334],PARAMETER["Scale_Factor",1.0],PARAMETER["Latitude_Of_Origin",39.66825833333333],UNIT["Meter",1.0]],VERTCS["Cascais",VDATUM["Cascais"],PARAMETER["Vertical_Shift",0.0],PARAMETER["Direction",1.0],UNIT["Meter",1.0]] "Same as input" DeleteField ptp_prgp10_ag_apga_intersect area_ha_1 "Delete Fields" DeleteField ptp_prgp10_ag_apga_intersect fonte_1 "Delete Fields" CalculateField ptp_prgp10_ag_apga_intersect area_per "!area_ha! / !prgp_ha! * 100" Python # Text NO_ENFORCE_DOMAINS DeleteField ptp_prgp10_ag_apga_intersect data_final "Delete Fields" Rename D:\sig_ptp\ptp_prgp10_ag_apga_intersect.shp D:\sig_ptp\ptp_prgp10_ag_apga.shp ShapeFile file://\\SIG\D$\sig_ptp\ptp_prgp_apga_intersect.shp Local Area Network ptp_prgp_apga_intersect 002 0.000 Projected GCS_ETRS_1989 Linear Unit: Meter (1.000000) ETRS_1989_Portugal_TM06 <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/3.2.0'><WKT>PROJCS[&quot;ETRS_1989_Portugal_TM06&quot;,GEOGCS[&quot;GCS_ETRS_1989&quot;,DATUM[&quot;D_ETRS_1989&quot;,SPHEROID[&quot;GRS_1980&quot;,6378137.0,298.257222101]],PRIMEM[&quot;Greenwich&quot;,0.0],UNIT[&quot;Degree&quot;,0.0174532925199433]],PROJECTION[&quot;Transverse_Mercator&quot;],PARAMETER[&quot;False_Easting&quot;,0.0],PARAMETER[&quot;False_Northing&quot;,0.0],PARAMETER[&quot;Central_Meridian&quot;,-8.133108333333334],PARAMETER[&quot;Scale_Factor&quot;,1.0],PARAMETER[&quot;Latitude_Of_Origin&quot;,39.66825833333333],UNIT[&quot;Meter&quot;,1.0],AUTHORITY[&quot;EPSG&quot;,3763]],VERTCS[&quot;Cascais&quot;,VDATUM[&quot;Cascais&quot;],PARAMETER[&quot;Vertical_Shift&quot;,0.0],PARAMETER[&quot;Direction&quot;,1.0],UNIT[&quot;Meter&quot;,1.0],AUTHORITY[&quot;EPSG&quot;,5780]]</WKT><XOrigin>-5623200</XOrigin><YOrigin>-14394800</YOrigin><XYScale>450265407.00157917</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>3763</WKID><LatestWKID>3763</LatestWKID><VCSWKID>5780</VCSWKID><LatestVCSWKID>5780</LatestVCSWKID></ProjectedCoordinateSystem> 20251020 16192900 20251020 16192900 5000000 5000 ItemDescription Microsoft Windows 10 Version 10.0 (Build 22621) ; Esri ArcGIS 13.2.0.49743 ptp_prgp10_ag_apga vector digital data PTP - PRGP - Área de Intervenção 2025-05-25T00:00:00 Direção-Geral do Território Fundo Ambiental Plano de Recuperação e Resiliência PRR C08-Florestas RE-C08-i01 Territórios de Floresta Vulneráveis Programa de Transformação da Paisagem PTP Programas de Reordenamento e Gestão da Paisagem PRGP Áreas Piloto de Gestão Agregada APGA Programas de Reordenamento e Gestão da Paisagem – Áreas de Gestão - Conjunto de dados geográficos (CDG) em formato digital vetorial, com implantação em polígono, que delimita e identifica Áreas Piloto de Gestão Agregada (APGA). DGT - Direção-Geral de Território 1 -8.872249513 -6.655036879 37.149629803 41.966789911 <div style='text-align:Left;'><div><div><p><span>Este conjunto de dados geográficos delimita a área total de intervenção dos 20 PRGP, descriminando para cada um deles, os seguintes atributos: número do PRGP, sigla, nome, situação, área em hectares, e origem da informação vetorial.</span></p></div></div></div> Shapefile 0 0.000 dataset EPSG 9.8.8(9.3.0.0) 0 Simple FALSE 0 FALSE TRUE 20251020 65D92E45-17DF-44A1-A53E-959A4BA2C69F external 34f8d67e3d2178605e1d4747abfec0f2adee9939 Direção-Geral do Território Direção-Geral do Território Rua Artilharia Um, 107 Lisboa 1099-052 Lisboa geral@dgterritorio.pt PT 213819600 True Direção-Geral do Território ptp_prgp_apga_intersect Feature Class 0 FID FID 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. FID_ptp_pr FID_ptp_pr Integer 10 10 0 ptp ptp String 25 0 0 prgp_id prgp_id Integer 10 10 0 prgp_sigla prgp_sigla String 10 0 0 prgp_nome prgp_nome String 150 0 0 area_ha area_ha Double 19 0 0 fonte fonte String 100 0 0 prgp_obs prgp_obs String 150 0 0 FID_ptp__1 FID_ptp__1 Integer 10 10 0 dgt_id dgt_id String 50 0 0 ptp_1 ptp_1 String 20 0 0 prgp_id_1 prgp_id_1 Integer 10 10 0 sigla sigla String 20 0 0 prgp prgp String 254 0 0 id_objeto id_objeto Integer 10 10 0 tema tema String 64 0 0 subtema subtema String 64 0 0 nome_objet nome_objet String 128 0 0 cod_objeto cod_objeto String 6 0 0 descricao descricao String 254 0 0 obs obs String 254 0 0 obs_ap obs_ap String 254 0 0 fonte_1 fonte_1 String 50 0 0 data_shp data_shp Date 8 0 0 data_final data_final Date 8 0 0 prgp_ha prgp_ha Double 19 0 0 prgp_per prgp_per Double 19 0 0 area_ha_1 area_ha_1 Double 19 0 0 iVBORw0KGgoAAAANSUhEUgAAASwAAADICAYAAABS39xVAAAAAXNSR0IB2cksfwAAAAlwSFlzAAAO xAAADsQBlSsOGwAAIABJREFUeJxcvdmuJWdypWk++x7PEBEMkpkplVRCXRTqroAG+gn6+fuqUd2A WkolyWRMZ9iTz974ltl/gmoKISYj4uzt/g82LFu2rPzf/4//uVZFZrllNi2rXcfJ8rywdTV7fTnZ us5WFrnVVWVNXVpV8GeL3brRtmVpm6a2LM/s0/OzZUVheZZZZqtVZWH7trH73dbeHQ522G31++M0 mC2rZctqy8x/L5aXuVme8du2zItNtlpZV1ZUhT2dXqxcM2vKypqqstfrxcZ5tXnOrBtmu1w7m221 vMpsnkfLMrOmLGxbNzavs8185mq2zqtVeW5NVep9rv1k/TzZNC9WmNn7w8HaprK8yGxeV/1cP052 63t9/mKLzcti6zTbtmltWVfrptHGYTa+dF4Xm+bZqqy0Kud5C9u2tR03G31nVWbWVpWVZaH1YoHz IrciL6zICsuy3M7DaH9/erJfv3612zBZUWRWFbm1VWH/8PG9/fmHD1YUpf1f//aLPZ8v+p7H3caO 29rqujKzzPphsms3WDeOdhtGu/SjLdNsh7axD8eDbbZb+3bp7G9Pz/YfXz7beWA/MmuttG1R2rBM 1k2TDetsVVlamWVWxK/NZqPvmOfJlmm046a1Tc3+mw3zYsuy2ryYTYvZ8/lmPZ+9Lta2tRVFoTPR lKX2al1WrcvHxwe9Y1VWluWlXfveztfOsiyz3XZr6zRakWeWF4XWeM1M6zwMvd2uV2vqyg7b1h52 W/vzobEPm8K2TWPD9s5+fXq2063TmVqnxf+9aLts1xS2a/xMrfzGYroD65LZy/Vir9ebXcfRhtWs bRrL89yWdbJ5GGzbNlaWpZ+rLLPrtbdpnPT3zmNvX69X+3a92GXobFPmdtc09q7d2rvjnZVFaatl thjf0+kz2qa2+7u9rf1g88TpX+21G+zby6tN42w/vvtgbV3Yskw648f9zpoi16+2KOz59GrNpjUr S/u33z5ZXRb2p3eP9pcP7+3lcrV5XnVep2XS2nx6Odv/89tn+78/fbZhmi3LCu3PdbhZv4xWVYW9 Px6sP9/0/ezt5dLxslaVtdVNbefLxdai1D3d5It9OBzs53f39tPDve03jd3tdrblDuem587W1bLV zFbTnR+558tig612ut3sdO3s0vl9ZG24g8M0WWGZ7ktWZMY/5TzP1lS1LvEyTJZbbrdbZ8M0Wl4V No188GrZPFt36mR4ag7XvFqzaSwvCy1EW7P5pbVladu6sB/e3dtxv7eShbh1No695euqB5DxwaAs i134rnWxYVlsnGYbxzA6dWW7prXbMOgwzFluKwYxz3WI52XV4S3qytZllgE47HZWZKtf9Kq0rpst XxY3CmVlKwcWA2aZFUVum7KxZcFIzrZkuc3GouRWlLnNfIcMHpck0/dxuDAYbDLPPsz+vDLw7AW3 NV8sKypMqF07DtjVag5XVdhhv7VdUVi55jIiRV7qsHCAMcKvXWenvrd+nmXA9ay8pzZ51gYu82S/ Pn+xblhsW9W2KUvbtxygzq79YNfbYOPC4eQ2mdV5aYe7vS51XZX271+/2X98ebKvr2ebhtHasrKy qjgWdu57rQC/iiy3bd3KyHDLp3Fww8WFK3IbMRzLapeOS+eHeppmm2YcRCaDyz84uCLPbdvUOjv8 uk29LctidVlaW5c6NzlWzxarNqXt6p0cBuuy5qVVPB8G/XrVWbM8t7Zt9RllgRvMrMPRfv1md+vJ HretPf/X/80e2tb4VM5QURc2DpMNA3vK2cFJFrbmufZxHmebJ95zsefLRYZ7Wn3Pp2kKh8o3+Qot i+8HzizLV9u27EMjh8daXPvRXsebddlixbxw0Wy9Xe1+u7emaKzvBt21aR7ternYhqCgKKwpCl3s sZjtsNna2podNo1VpWlvzzcM0GTX61V786cP763ebc0KN6Af3r+3XV3Y/aZVYMEBz221TV3afrOx Wz/Y5XyyT1+/2sv5qnXG43CvLOesrdqzh+3R5mpjl66318vNum60Mivt4e7OPn54Zz1Gpuutn0ar i9U2baX9OF9vluGIi15OqS5zWziI3FHuyzTb63WwbmB9Fyuq2u/RmskATrM7OZ5D56GsdCBHfh6D ddztdWjwYmU52fP52a1ukeuHVjYKCz1ywfhyj4QyXpC94wXz3H5+vLd3d3e237R6SKwsxvB8u+mg YUDqvLA6w1NplWQELn1vky3a/GGc9EK7tnVLPIx2u/XWjYMO9DwvVmeFVU1hQzHb6TZav8w2jRgw Xmi2uiqsImbKPFLEWOE5ObirDAvbl1lZ1+FRsfIRIQxEk4vlmRtDnpJnHGY3Xvq5rFDIxjvwZ+M8 W4kBzImGiJYwNPwMEZkbjqHIrOf9OMi3QReV52rXzIpp0aFn47++vNrpcpWX0QHSE5iM5vnWKdrb tK3d73Z2zgZFnnjPEwdgHOzWjzZw6XgX9ijjmRZtNoawu1zs337/ak/nm43jYk1eWZmXujg8M9Ex 35pnRMop4sByLNovPo9LwGXF63HYeT99X8ZzEjlgBwqrilWOByNJRHK33+hsVGVu3cT5yeQY+NU0 eOJcr4uDY926cbZuGK1uNjq0nCUiDwx2vnLBKkUmdV1amfvPvE6ZjcPVqrW3dursDoNVFlZ3hQzV 0LMHs/aMSEF7vk4y9ERW07ToQr8Mo6I4XgCnrfOqBcUulDpHOca2qm1cJkXdrCJ/XhaVVfzKK6vL xsZ5snM3yJhfu94ut97aotb31XUjh8U7s9+sAXvAd2G8jtwDnMdKVE+kXugeKVJkrdikrFAmMF57 3Q+io3cPj8psVq7EsiiYUFRY5NaPg9bsw8O9vUwY88kNeI6hHbEpNk1+rnEMwzzZreuUBbAPnF0i u4fHO2vPZ+3R8bDRGrBEMmJ83pLZOM4epLDP3Kdlsds42ufXs71ciMBHK8pCe6tzo8zOz6EbqdGa MtfxI+CRwfIX8UuGd+TleXEWccECchjWxeZxsjIWlMs5l7kOJOkK3vvHd/d2t9/5z2FYysK6rlMq hocipWRD+IW3xOpykYgmMAYyfEX6/FzG6zZOihxu06DP5VDsthsZyDLDwM3WcTEI99fZ+mGxLK+t JMVczI0LV83fX9HTiiXnxfNC6Y7C89wNJoeKELYoViuqSheISzLjbbkwXMjMvazsv1IC/j0bT0e4 T+iLp0lpJZdcDgbjNvXW9aNSLQ5eM89KC1lfDNbperWBCFPP6hdED2+ZPB3Ge9c09vP9vT0XV6Wj eONzR/o3WD9yQjOF3KwvxhNDj1MYrlelIM+nqw4kayNjTqQRoTpRlXxQ+loZZrkoNyhhQH1N3eEo tJ9Yd39OPo+Dh+HnM9gLjBbGihSZy89zccZYJxlJfuny4TRLLJ/lRKs6xHwv60ekwDNiODGqq5wT n42ZxTDcMlJas2werNBh39pgpXVEg+NoXd/LOJGKAIOwi3wthn5ePErDwZISs1+kSWQMfKHSUqUm pXUjDgnnmGsttW55IWfOmR4jWmvKxtaRZ59lCC5Tr8iqyjHotbVxL4gwcWhE+r5nDjEAwfB+nGK+ Iy+IVE3pfj6MfgaVgs8ytHwn7lqRd1VZt+Acc30OAcapH5Ui87+5q4dTb/N0dcONw1m4R+5kTx1/ L7PL0LuRy9zB8wvHzF5m2VbOiqiZFJFggzUAVqpuvdZBa4xzyj2Vf71eZbA4z7xvXdX6N/efrIcz xN1QCk7WNbqjIsuSwSqy2daF9GWwz99ebZwch1g7DqHjDKRYGBYMEZec38uw5qXZ42Fjf/743v70 4wddqNPpLFxpt9ko5SEMHfpOURMXlYOeZ+TxXCr3WET5hJTgIfxz4nNuvTzTdRhtJLrBOPBSpFGY mZUDm9vGapuxT6TY6yqMiJRzU1SOh2FsubyEprOnV7IEKxeAo5Dp0rM40zzpwuKBSO3c2psuKxdM l0wLy5/nMlZ+4Vkw/7sYMQ6bRzi5Plv/VhoxWb+6l8+IGrvOL6r5ocPTyKDLNOgHdbj4JTyt68zG rf18d2fbAjyvs/NtsNONCMtTdy4WRkbPRMRXFHbpBns6X+zpdLWqaGyrS84BdYyP9fRIKpkrj5xZ OWUKSrHB2Th8fjk5nMKSJqJicCa8KNGsQkL/CNlqt4Yy0HWlv08qM5JOTeEEWA/lobmNK4bdsQz+ IeXuFy7WrMsCfCFMQz7JnUN6ZmEfROLZaoswp1UO4HK52usruFRvt2F23ClbbRpwkDiW3C7DZC+3 q52uN+Fa2lc5ND+jRDcYkmnJ7OlytnGchMct06ALW+7qgAE6e72c7Xa7WdturQCSKGpr2tr629W6 odMzVeWqFJyoh0hxnEdFIwQFLfdgXez+cLDtdqto63a52cBdWBbrlsWezlf9HTBkIi2cBGEMe+Ap K3jdZPtda5z01663vz+f7HrtbCJjmnG8Zgv7N462FGRso/aA9XvubrZk3IlR2ZaR0RHRWGZ10+i8 EjwQSOjeFbmcTV7VwiGvw6AzwlqO4MA4lL5TFnHpCUDIwlo77naCRzhDRHVyfpljmuuY2TBMfvd1 VxWBl4pmwKy44MIr+EGihNkBxoqUsSm0oFy2Zl7s8bC1D493dr/baMEwVjw4FtNasx0/VxSAUQJn 3SMv+i55+KK046ZQJHa64fUnu1xvemiMFWAxEcNKxMOGZKbD/vX8qs+V58USr4tVc2kbQPdpUhTG 5QGXWfHywrd4n9lTnUg9eFdwGFlxRVZEBqXeAe9KtOWRRkooPerAC/B3/LKzuFxssw5jNExW55Uu li4s341nFKjJIfJIll/Z6oZSmAiGj+9XVMT/dm+e4hlPATBGeLbG9put8LZxMRUeeJaEdQmD4OCQ 4hOVVpX1Ouy8PwYUw/rd8HB4hQe6JddBkvEQOm1WgksCTje1ohTC+H50746R45n5GYwte4xxdeMf mIM5vsfz8Uu4Fmmaih+FNVVju12r9WE9sXLNZmObJvNzSeGAyHMYrC5Ka1rSKAeQ12zRmnP1uPRF L7TEpry0uWzsNq327dLbry+dDNVEFFkV1mAQiOzl/XmGys7TKEO4325UgMEIsdc9RaLk0Ba+bzT8 WV3WinpGnoELf7naBgwry+243ep8E7nkSy5jf7/ZWEkxYBw8ms8yeyXNpziiAomfXRmsqtD9mddX FS7u9gerCBSamnzNvr2+6D1xAPweGGl265VxEEgQdnEnC6Kg3Ow/Pj/Zv/72xf7987P98ODAP/eM O89asGe3eZBTmVYCE5wQ54CgJLd619p8JSLOFIH+x9//btu6tN22USCC0bw77JQu8mBzdxXMIxvS 42iBOdwY5VllHx/3Kko5cqpDZypFrIvtwaEJLoRrTzKOjuFGhMUbgVlhyTAMG8L2Wy/LCrawAVjP M31hSgsIMz8+Hu3d3cFaql7rareu9zQrz61uW4/MuBQrwCvGCuyAtJPQe1DVRpcy83yZEBEgbphX RROEyBxgDBqf6/jZapdxtJroDmO4EJLPb+kFf65iweAGgEgLY0FFEmPLd8pYWFwqlpX9Ffbg6SLP ycUrwU0A/6jaUHQgVBVITAjrhpsCoccPRChRJQusS6lg+H0qrREwuaHwAMYzvrBKkRG5sQATEwjt eT/pJZEtnlZRqpy/fwfGUgZLQGVY1TBcpA4C8rtO68l7cMmT0XTj7Fjb2++xOvH5jkt5JXe10cZx 0IVNILRSSpWB/ELztzDSrA9rpwJJgPhhD2WkPPVz7KYsqQBiPDOCWu0z+BqfwRrwufyeV+pIuzxd lkGuKNyQavg73bLafqnvbWlqeyga6/rJni5X++3pWbgaprPh5dhPFRAoxhA5mu02jRtDoris1Fpz cbKsVCqZoj6eh8vGeeH/OstsmFZFFZfbTe9F4acFlsBRZiwOaepoB6rLREvTaNd5sg5DzxmeFxnk jppNDsZX2bCs1s9ABYu93nq722xtU3GtPaUmumNdn08XpcYUDXgvMDs/Z5yPUnkMZ5kCw2kY7JH7 yH0Szphb0fh+Uw1c2Het5WI56WpdCPivi8qeh5PNE/ZytOfT2dYDhREwP6LEQjg4hRXsQVOC9Tqs 0ymaUmKos3WoarvbtUq1OfsYcCGkAa3wWRh4d9Q4t0rPk25TyWG8dRxEyui5KAaEZ8ua2/3x4FaX jVKubgLc7ra1/fT+3i9VXNShH83KVaX7TePGioPFReJCYUh6gMdhtKfr2UPg3A8wqd+5H+RlMGoe LXi1r6nwOh7mkmngyf3yZ5YFzYCUAo/Li4MXLIN72mzDgfMLzEHkOXDifo3A0DwtlVGTcXWgWAeZ ahhpMM8CHqZqVdAl5sUyogzK3As/t7xFSm/4kzKciFYA8QnMI+pRCpreQ5aLn/b/i3xM1VR+LXr+ 2fZ1re/WQVAIPcmD6QBjNEY3Uh4+e2ULXOuFyppSAM/RhMkJj3NT4v+WhXPwk0PPQQYoVRWL/R3N wEigM8Th+X4pAoznO6NUrcgzDBXvhKFJf0eHrixsUzdeIRRMwGGV2Zch7MfexoFUyitPUDbYH/Cy QRGPe36MEJ+lyB0Ad13tOd9YUW5sYxiDRdVeqDR10bj3n2elmEQnGAfSGBzKHbSbspQBvJw74X7V THTkUXdyjEQu0EnqIpNzXhe+f5aTJRLE8OFMK6LYEiDfK4qqkjeNp9b42tFU3cX4sebgtaSlwgTX UZQZIrQbKdsw2G0/2v12o3QeDHfX1PpO6C2sA86Is4Hx4jOiTCI4AGNFEMHfY2/13qRdMAMU5hOR cijB/Th3qwpXnNW7ulW1eGkHx7gnsOJJYDvOqeuJdsHOqERWdty2dr/fWpmvgmOwck2zkTHiqcC+ 9tp3p+FgA1QB1B3xaCo5k7bxG0EgwVrq7Dyfr+JqEHrixQj7seB32629Px7tcoGLsVjDBV56O7Yb +3h/sI/v7uz//eV3XQQO36rqjcmDqCQPNkC6hScZB+X2AH7Pl6v9/vzimARRA2kdJVken0gsQHi8 wLambM+GQiHA2/hFqzGIZSHKAocMC0x6RIla4SNObeAG32TsuCosWDJcuuRgLipdeDQAXuNVvloX TFW9YVDRgBAao6AIR6ByZlMG0G5O61DqHykYVQ0uLOmHcB2nUMgZKCrB836vvCUbBTZHpKMF5We5 1NpUDOtkP797tHfHgy5xB1+GsjCpLIfqeGfj/CwPr6w+x4vPdgoMsHgD2APQZY2plFWVLr4KAgIp HHGSUVK041iRTFoUyvDWAoLxygJp3TjxewAdrGPC7lKVtsLgFH6RKDxsN41t260docjw+1FtJZqb MFbQJOAcTYO1Femip5U9aaCiv8KWPLNTdxOVROlG39vH+dV+zjp7rI+EDFbni32825it760fF5Xm wWpP3dUs3yodYt2J1Kqm0vt08Lvmyfqu9/L+XWNrXllRshaLjCKGn2vNXlCFLUmdIp2UEw4uYFk4 XQg8h7UbllnnGbrObr+3I/uFE7BV0dWX08W+na72AjVlGpW1ENG7kbnqs7xqNgoaIAPKLlTaJ3u9 dNYNg317frafPzzY8bi3fJ3t9y9P9tyN9nq5GEEfRrJYTNGWOF+rp5Zt09rL9SzuFBDOtmrty7dn iu3GQX+4O+oM8z2/fXmy12/P9u7uaIf9XobsfDlb190EUQAjqMowr9Y2GzlMsEF4j8ABK85CcEou A3buOpsB8qvGhn5wmhF3WwgVtBEwLc6XWemgKRU3SpoA7QS6RCFmYw+SDT0DFzjb+/uD/fOffrCf fniw2zjY5XqxIoe4t9Pidf1NxM5u7AW4svmE04SGGESIjFwgPDEPy20Ai8kjVMdzgO3MkBTFG+Gw QvIcVKXkYPJzV1KTebB8mexud7BN2dqcZ/psOEAKGKZVAPdS+sXT5WIRZNXzoD54ytEP8I/g0Hh6 N46dODgYXI/QVgGD7B2g76oMnZjJIxPnTIgH4NGFIjVPmZQPxD9QEDDsPA8GyatfTpHgRPtHkR45 f4noAS94Vzb2p/cPdthu34oWXtXLhCXAIRvHjYxfB8/lclPUjIGgUoXxoCooygCVybd01fEnUgHx jbTZYIBuWIkg9O4RtimiUmUN3k3rab5AW8cX9HOA6KybKmr+LWA8z5ez44TmEVMP5pLntr8/ijIj GkhUl1WgKdyTE+l5jYSIi7TcU0Me6KXrFeFzqFlbKoRz09ra7IRXycDmhe2q2ubbVReVrAAeGduF geSCjRinzqMP9rQEl4z9wdGyfl4cIFLlDDl2Bah9vTmdoAaCKHDAVBYL4UpeLYaTZ9oLHOpb1JHx 90tb9CyZ1X4yrSKSL69K4xPXD87jae10R0g1yXK6Dsol58Sx4JZCymp22Na237buKPNCRqVsPMpi H/dNa99er/blcpNj13qwv9NgTc6fV6JrgB93OJJhsGf2qu/s8XCQc9q1ldV5o4iKt6vy1XbHjbVt I5Iw6CB3n7UH13s6n5ywXRYi+y7brfZnBreLDApoBp7cvoFuQjY2KSLk7wnz6wMTVTQQB5gqGZk+ VRGBxLKItSInFu3P7+7t3XGng/t8ggXvVSmiqWGd7NTfRATVpSU/55KrROwsY4BvxySiOhcle3lj UjE2gMpkXcpg4U2UBgrE9XQD48bnqCa0zFbXTnnwIlMurMrpCG6dVS1R2dtTU886MIqzl9ADT+E5 OfAsHp8vA+dolBPwIm0hfHXMKHG1ItGJsrDwFa/H6+94td/fk8/xNVBeJOcQiZAupAxJvAuGGZMI h+aHu6PdH/aOb/Sw6x2Pwqg1eSG2MJEOKeCFKIIDBpeOr1FZnFI0F4ECC6msrwupijoTohKKEVVV TEC045EyPrKk/g6KJDMqWZXwSGFsaS/Fc+N/L6osqsCRLYqwVR0sSAVL4aVL5VU/nqkPegabnboT WFztT0o/+TyY1rn/HtElkAAGlIiGvap4xHZr4+aos+EUCscyWQOnT+SKmHkX5/35nlYzhYCE7fjl Vko5Q+cpnU4R+KOoK6SauDAwLSpkIsiyrcAYhZwvaw0fsaob8eM4G5wr0ZOrTMZZyRTniHMowL1U xfzbpRL+RkqHs+Q0PF9u2rNHCNkqRPG9HsXTyUCKfdxuAlfmPOV2aDeqbJ6LwVoi03kVBPMMmVuY l98HVcKDA3eBoHrtdZbALNP3QzEgkt5tW507oWjLpPvK89A90DSFvVz7yCI4Z7PAeNaF9cQBkG6P +WyFshAvDDjvjz3MRAbnTpLdDJmfU+CbMFheMWKjdDh1eDlIXtlShbAurLHCfny808s9w6O49daU tdIKIipKlRgx2LPK/2Gzc0mCuyXuFDsqDtZ/rmo5oztilnVWqO4pBgA85U5YsQEsU2lLZX9bxazl 2TEQwkoSmI0vD8YsUQUl/zmB7vBySGNUaalt02zsfLkqDdHpV2DhQLp4W7FGfDAgoS48zyrP71/I v51s6OtHYDVmfkkj0PAoi+eQgSF6SHUSx+wEPut/u8HlY8AqPj7e61CAG/QRtfJTopcUpr14Ol3s 07cXpT5OzHVyL8+FA+KSKkUrWA9SAb7HL5F8OxdVGA84DVgIjor3dIekGkAcbKpqXhHyv7sKAM5E L8nBUqhUgtXkbkhJb8g486qxEjwkqsREq8rxCPsVXXqbC9gMFUw8Nhy4IqNlilX0M4Aj7Pte3yXu Xr56e8g6yutPm51lUFTkMMBqHEKgZwhnq/agAHxlHIUrZpY7lCIj6mfHq8AYYO4C66cYcRoVKbN2 OFXOKuuhIsMaTkB0kNz2VWsHqnLTqvuB4calsScyfPGLvcbg0C503FF5I3bxquRtISvJZbBeTxeb FnDkjW3q3AtKwsu88ir6hYN1b1Vf1nfqBxuunV2zSpwtIjf2lQdVwQOW+TJGNHWx67mXocORA/Xf HY9yIkSyOBKM+BpZGbQNsELOJgd/HkbtpbC5rrPNbqdnSJ0BQFA4PaI9HB/3TM8KSReia1Pbviqs B7Cnui0IJ6rYkDsFmPMX1efmHgYjsN9tdDHIaT8+HBS+PZ/PstCUdVlUHuLldLZv57NSNy4VlnuT 4ZXwcH4YnTvj9ASSXl1NGZPFxuhFE1VArULOmlb+KkDaU5qcfjnxxPi7XDr/O27o3ENDKpBHLHm2 QaGlIrIAYzxVc4/Iz3AgBFJGEMEzKAr6Hvt4yOydAk4UjciNC8Pvkz46h2TWxRAbSfWIxTqwGbGi wTvcszttRKGjrwdGQyFG0B6UqmX24+OD/endg0rsrDMVFyInLi8VGbwye/Hvvz/b358udhVQzRc7 1seF43IQYlP1TdVHx7AgCLvHFN8o1lr9g6rAxjuqGgfOw5p6pKa1wzDlkIZ36gEE7+MiGC0yq9k9 /KEG2sRkX55exQA/brb24XivKOuAUclz+/Ltm86cogX4XbO3dyQSqrPoMltnqDOdngvsZRmhkECK LGxXLHYcbvbfu69WZBt7Lc0uXg9yPlzsu2qgYDZqY3F4QIWRaD/CoSndpTIV504UgUiv9BmQTrkn YElxNnBeOLsqAwfzKh5tZAWZQtPqPbrVsWF38qVHt8HsBrxWZCeibWZ7/k5UMzm6v47Pip4HImsq 7cuzTe8ze3/cWlERQTov7nTtbbfd2QDLPHrwVOXF2RerlW1hABsYifeHvVfo1tWuQ2+n68kuM/jR auuw2tzBCuA2FapOvj/e2+evX+3UXy1vSjEEDpta1AT4bazJPJDCwi5ores7nb+yrXWfwKQVNY0A Kh5ElCMkXieugwEK1eVc4Qhw/GDVOpO57ZYmIiyVj/2gwqeA8ElozKF6D22hrhTWUv243q4qswJZ sLFgRvAyvp0v1glQ9SRKaSI8Cnk576MTB3al6kRFEc6HN8R6kcoPjxi0TS0PzgHRQdVlBlfxqCn1 O2GAVO4GdCfUxtKrBcBTHFEJZJnZOMJuft8voWI0GTpP85zoiSH0fjG8SqpYecrkFTyFzlFZ8a7D iPaoNcjeAAAgAElEQVSiPYXoidI8kYX412ANMNf5s4KDOYk1nAiiSo/VAB1MLxkNugdK+/Hhzj4+ 3AmPkLEaRhtGLpVvNkYLFvIvX5/s1y/flCpy4TFA7I+qkFqx4J0F2XZh/XxV36JGGSUMr/AZLrcb L09bwaK8LYOoSesZ1c22bsVrUtoOebQQT0bfCgANmAuPabuheIF9pg2ms7beikR4GRzz3G+33n4z LQKohV9kpGyeSs7ADJT5IVxS9CAiiUZo1u2w9vaP07NtN62N24MVeG4yBi4srUew/QfKCmBIHiFg JIRLreCbTlzEeQhr0THjgnGOAtcVdqgqi6rlggfULuRRO58DlkiUoh7XcA7sP4EstAH+m6IMcAkY MMaLz4ImxLnHEai1DA7hchGexC+MMoD9QAHrRhprSjN1z1qq11udCfWb9qPAd96hH/2EyiEvkDDp me2cu0b1NStsXEftHYHLtNJOgzNwKgZrRHWayt++yW2531s7VAYRAewSSseSE5mZvpf1EagedBYM FJGnqvfy7dgCGuY3cjpC66Mqz5/ijBO53HsacxlaVWkDein5TcJa/g2d/8PDUQZqq9DUSaFiT8+z GjoB4zzCoaLifVj8G4axeq9SmVsXAGyCAwIWFVyowGd0AOjSD3WHPMJuNkcGJrq6qQwGc/+t6J+M BRUmGrE9tfH0y+MVT0VEfAzwFLCTsN9pAvEZ0fYhIJQ0kUsgJQhnXgsAp8zLhY60WQTPaM/JsoRl Yey8HYVn2uD1lBIBGnq4K0wM7tboRETxnCJsd1oFhmBRJHa/39nHxzs5EBH8SItDbYB34CO5CJ9f Tvbvnz7b0+tZl0/tTwXctCBXRE3gjZul/7f8wViFwY198YpMYBp4zOgSYA/1M+EkpHoR7RlcTjy0 GPEOwXlZHwxMCgvOcMegqi+t72zaNXbpZrUjYXRBJsvCicvqYROm4/2VKQLWr4iqoBSAG/FPM/d2 P5/t43yx5fEv1m/vbQKrgVckHNANMoZ8E4EyZwzjkbBULvCZiuPqnR2qocjIk1k5OS69X2znm5HS 0Qlek8MNvrbpDvAOGGIiF/GhCF7j8uEYfK3op4Sx7ooW/MJpSZEB1Y+mEu1hFUnZKQt8LsTTZc48 yqJtB6wOXuPEvUytWX6PZPDhOa5gio4JZ9Mq50sVuS0aG66DTZ3fb/aM+Opu29qHu73tWgz41tqx VtGLvkgq0pxgjAywjSgzoXKCTWFNlB1xJkVQjggTe8DZyGkqjbMofiQZiqeoDpu6Won35AZx9AAX hJ4lFioz+3C/V2MkRosL9fz8zZ6vN4GG1xHQDPsKo50mTMLa3Oqal0BlIcJ4YnFV5jyP0ovpfuBh Mtvttn75sMg1Cg+ed/PARFDJGJ477ydMDZFwO8Ql0uc6riQDiSGBgCjmduBjiT2uVJDmbXhfTmBL fXMcIJ6ZBmoiGOfahNVPRjUB1iy+eryiCdZDPuEZfIeMfoZSBTgEpXxaHPDwgK+eZmrRU19aeJE/ MsyLdbGHXauKIM2rKCEAUmJ8VT1CugaukJl9uVzsb1+f7JcvTzaMztuac0B9KlK8h18eJ716RKg1 SwA22IVDbdF25JW2Wk3wXKBSygB47TldpBWn1ojy8rjd6hJf+5vd+pvOzzC6PIuIjHDFUotIFE6I cmmyxQYoIp1X21Qbm4bZ+nXQelJVyjJvdsbAydHgLOIidPw3DG+qhURXw9ke55PtS7Ov9z/arTkq 8kchhAqTp9l0QXj6LadYZLZpoFbQUFzr2cAAqWTjjFCxUCdBGHkcl+8ZZE6MqJ+xlEorIyAtGzpV 2HCSataP1DwB+JvdJuSVZlXARQYuS1VNVeiKijQVcVWJVeAwO7RbO4MZV4Vl20ypNXeW9OvrBRxu sn94/6gq/t0GZNZbkkSADv5a6miQZA6ZhGWiGZV1YXWzs3dNbqfnv9twhaOTWbOv7V2zsZ8e7+yn R/iYsIQ6EbupgJabjXMa1UrE3YCf6DgumQRGnH+GvrfD3VHRNUW8uiK66nX+Iep6suPpt5/J7wxq NXijJhIOWvfk54/38uRoPDVNI8CLy/V0OskgwUAnVOOF8ZIC2WCyinleWOb5h4BlDheXy+1U9HeF rk1Kv5xQ+r0jmb9PZz5seIGOm9per6OwWCQzpt4bUTOqR1SfrAiym1k3g5fRKkG7BSvqyJO0qaIp tcz9oKrlJMrhbgCdrazDFG0K8u5xQN8qaXqvUQRVsaUBullMHj8uhKJIvqsu1aoEBofh7cXvgiPG zy/O/n+jiHrUosi2Lu1u39gP9wd7OOxFGTjT+/X1RQ4Czs1xS3q2WDcN9uvr2f769Zv99uXZ+p6q K+/uhxTPmyImmSMIumGcfMmR3EmcsVL7iaGWAwGnCRUF+imbxcFuFTC0rpABQUEmyxuqOKSBmRpp f9i4gT1dLgJalYpEeieeFtgXHf9UGAsuKfyr2c5KETHE3msqj4p8Sj/YKzwl1hDMisZeReVABYuN Q2+HEgpDa139k71s/myX9t66SGuoaGG8idBpy6EqrlSdvtgis5fzzfZtJ6qIcDsKTa3zpsr91o0s 3D/1xDm7X6k4hQDqg+CPupDw4eil9AKOdzIEthpcNBwEbSmkXfS/clbhc8lp6TxGhdgiq4h9fL5Q YFls3+zsYSeJC9FWoGmogZzqOdGTRAtm6antllZpOJ9HxsT9wtjheI7HO/v7b5/s6+lq1x7lBFgA uW3aSWko/cKoU1QN1UqzP328t0cAc95zAu+FKM1d9chV3R6k7aPjmal4t9vvhNGJCkqHQsAcSB2p Q6BxNRbn+lV2vd10Rg57MHNnLahuJWeHEfQUVgbrxx/eOasbK4bwWw8o5zpFnrvLFOnF8QgQNfHA 6X9b43hQTsMjUUSAxglU51LyewKC8XBBW0pKAt724weSp6ZvzQF610dSI6fY726wWCylUyHhIrxh yWWF1czprVSuXZUqYEpTOThwr9xw6lAJZI/KXVQphSYFh8ctki8Uy5CirlTVTBSNlDLybHUVrQ5i PyNcg65RrfIyl4Mgkfwd6ZwlUkAwgsf7naJaUj6ax8+3SURHDokoGaRnK1pNV/vrl2f78kKTOTwk LrH34XHBHPPDMn1XOVCVT2vt744Swvcqrb8H60JXAZFqKiyQYuIHHGHjEpKbB7AfjbaNxXmAdCzn xGWm0BGVVH5JHYFSv8sYyQFFWqr2p9GrjaID8Nmkk0QpRW5fT2c5NNaqrh0DaovMjsVq/7Q82aHc W3G8t9Ph3q5zIV6V5FaQNmFvOIkZ6iOehitqKYgG3Shy7HCifma9jYwIIhkeccvqSnwp0h502zwb dWezrm7sMNxES3xu0phSr6KidXCqkKkJ4qkkemSj/PJ7i5SnvTwXDkv8Q7DC3Oz9bqez9/lyDacb h13QC+kzGB8Bhqfewre8J19qFF5Yyu3l3NvXVxQpKBR4hfEyDgpa2m1jx2pjm7a0u02paiXPeEGI Ufic97OqaDBGz210uhCsePROxFbaNEaVnXVQpATD31U6lIrrjrneGNkblV5hhFGZB7rhu7kn4H/p nxJNHlVmbr19/fasS/nhHhxrK786VXiYSQJ+wpfsO47BwQXLAOAEBJX3pZdOqo6+OfJUqoREHxub GzIVnuY590PUg8nBa8e4BNWJQwMPRFImSapC4Q1/6lUwXhoPonRUNIQE1vul0IHUHXbcJrIjPac+ QaXvVAVCDTUuexBD2VQB8CJOxuESRYJcn3TJjZVkd1iDERwBvA+mdm7v7g/24zuE1RptyNgPKsvz WYCtAOt01WOcoIU8vVyERyaKFyn5Cxy3vrdvrxf7+1eUKN2YOw7zPbV0Ax0YSryD2m2gGER7k/9V 3st5cam9ByxEMinqqQwcgzI50TQ6ScMY6qDejsI3ePsREURokpHyQnVBWYJqp0QgSREAm4nvFr2H omSIthRhxMY327a0y3g6hcc/FqW9Xq7W4WCgLghgzu2AUmmx2H+5frECkijCdO3e+pN3AGA0ZHAx POAcgYPIKImyQXcEoD7RF+qm7rAkWUOkFZEca4IxEq4VqhlUhkkpqRLSGcKfOR/RK89UcuV71T/r fDRvxqeTwSNu5ztiyJIG2ffuA6J8Nf5Gg7maj4vVHjd7re3Xy1UwgWgUwQ3zvlbv1cU4JaIt6qek cIq89a6zvVw6GUPS3dTK1s8EFbOKPO8OOztu6DBxvh0YIn2S0B5wphhe2PdTDr4ZfEdSQemgUVF2 x/hGSFZQ4FJAOI9hvFq5uJEWvCJnGdGlpJW8FK9gBuJoONckKFD+299+88bjftID3u8P3iOoip+X I9kUddKjUySA1H/PeTiFrRUkwlkkLxECUFkIBndq+KU1Bk+gdpwCIp8gbZeSQM6jcCwLORokU1Zy /XmV/IRwMH5+8lyWA8fB5XklkyLpG0/ZVCqmL4myMWmPSH0uPJjwJ4F8kB7jgLaoXG5btUIAJiqm eqMbeLieGniTmoOKaPyslGZc9BaAllAePEyVwLJw6dgP76TU+Ppy1rpWWWH7/V4yssJ75smeX852 ooVCUrG9s9NRLs1yex0H+/3zi8h8fT+rz84buz1CwvPLVAWx0asuEUmGp/J0MIBzAeO+j0oJiXBD TUGGPcr4YJMYEbyjQOPjLpraCzudLuo0kEpm01g3uVqHIqMJA+f6aRhk9pv0g/SQbofz0Numr11h QSkTuBwtLJNkgp0/C3m5kmH26hOKHOhD0bJEsSWz5eEny493ttatE5R1TvyXq5R65Ms5EO1EaQoX wFtSMJTsVdtWwliUElPEyVHCWCVx3HdXjyDhjZVAJ2B4O70XeBsRBjw4LjYwhsD5qHjAUyorV22V 1lVV2G3wZvYNQpfRzK6KeOyVR5ZcVGLzzDa08zSF3bUHtQzRlvP15cmOx6PtNlvtMzABbS8QiDFz aKbxPqTn4MCIP/KM0B6IlhLHTw3qpCiq+kFpGKww2qWcla7oHmmYYbCs9FYu9l/3zxWWtA8r1X9F UUTJmeAT75YAG4nuD+nM5TbdFgU/Tsh2o01WJfjp0qtimom07IUf8GkCFNdbk0QyDcu1NaEfpUZp GQd68WY1AGO0UD/01ClFTs5g5XQR3cibqoIDLrIKWHXWMtEG/yZM9ZRKGyH5XX7eMy/aMQ6tq5XO 003PQtq4CIPxAwxlwA0f0ZTzYQAsle+GZ0oVMHWkK6DysDmS1Mj7vTScjE5qSM5TG5KqVAlqC+XV SHV1sJSGpu4AMJYArwM/8ebfXCD1rtnoD//+9Zv9619/U1mFXH5flfbTD+90AcEBSPW4zGqPCiG7 57ETuP7p9CqN8b4jdU6VT49eZVwSWJlSwKTEEP9OVSv+8Z7CKBXj1algRXWQNIreuvRn3jZEpOCy v2CGL7eb67TXje3QWQFAB+eJtq6kSsEzirVd1/YyEBUgHeSVMs4Dfans8Q4pXy7d4AaNdIOUWQoc RAzoSsGurmkFKe043+yHvrP3k9n18Uer6r1luR94USCiRy1EL97azHQxowrJewIYVMjMaD3i2Y0I xXvZfM04dyE8GVLWav5VVwRtEbQRgVt5pQ5KRo16qvqCXEeLKI9zjCFx1QFPPZ2a47CJE7Y9InY8 lXef7NjUIoSqn5SofMAowkek/QXi62grB3ld7dvLWffueb9Vewu3TMolZWOvt9E+P1+0d9CP4oir AqmzRpWQxn4cJE3Y56v1VBzV6J1Ly19dEkhAwRRYvBLshRpsxWBFWbu0E2RvOQZv7aKKD24H0VX0 kgscvj80u0MUF++t0Pli/Rz2cdHFlDkkuY9S5V0xrD08JDweYK6zidEKQ5VsIznYxQc3hNQG1ZEE nBPiiwcEq7eIgQ3B7BZOIg6Q0w+wmHPl/WakDFTHHABfJEQP0CwZk8BuvFk5IoXEExLPxSt4HBgq cnhOl5v1KgiHRf2JknUOIDraBcSZEoaCUVwkuysMyBXt3ozW9+qFp4n+PKlvOaVZtHc4KO3Eaa8q ot+ON8Z4Pb2c7NPzq6poAp5pUKbiEgTEMSIlgb94t7G3309n+3w+qzdwQk2Vg4IxhhGsgQpJ9saf 742vIkP/PU2MDNhLxylVVBjp+NIfFUQpsKj3jdaX0OQiYgMX4tL3EqDr1ZQ80KJBRCANrsq2GrhR SfpXjkAHFvY1oT6NvqSM/uyOvbioIrafyJQ0eotjBHiGLiPdc7Tr0fev7Fhl9qfh1d5PDJ9o7Bec wpJZJnoNiqI4N69yitOmFND3mbfEYKaezTcMLy5+qtym9tBUmXZ4IiACKT14FrFEhRuHg3HeFjRJ e4SEEuzUjyoUuc5atL5Ig97TIe8wSJsTnRRRAOIX/EeMPWtPEeNEgWnEkKOG62KBOsOK/nNJb5Pi Yky7ttFz4YWH7mpfXy/27XyzK0GIDq4XfYStQYeoKjVFH2qMTkiT8/xBKwD2qWvnnWED1tsovS41 cgknc/EYAoSkHrukmQJ0vJSk0X4POfuUYTyLcSVRMiuKIRORrCAIB929u8AdaurILV2W1C8hIRie 9UpDqBQQYZjTI8TuNG8ArUJrqhWEatEnB0jmF5WfWWzIXOdGAywCTxJGSIgPK7gc1cWPdAVPwINf z3ScT5qagqfj0jCVg7Aw4mwtstKZCKV9u5CfoHHaWyT4Ln4W4wlvx+VWvLfODZBgDeXcnjt7SiWw VtVANyIiqQYz3mkMDm4rpE58MiIS6qWK5FYVImj9gHB311T2eNiresN74R1VLOAXfX+fvigtIDXa 7TcepYncOomM+ztp4pX02KxaE3WDfcJjY2wdR+JwSisqBBgxNDoUaWJQgL1OyUqcLE8n1Y2QppJQ edWkIC/vi8EdihBcog1CbgwjkTHhUNOe5SKMD/uDHYrK9ru9nAhldwiJfNFhj/BbZz1GRRVEHx7C eirKW+EIweejiOB9hPxdig+SKipy21W5vS9G+8fp1Vipl/peelHTgHbbat/OYFG57dtWhQyUQF0h 1Q2YBODCwEuCW1G2C0qCJ3qqU0VPYFRV/1Dx9nqxY5mcdZwLWBJOE+Irzf8HSJJQcm6DXWJ4RcJR pa+G1DDRvFp4UjXMI2QZntgnzudhv1OVT1EhWnOhwVWGvLcgF0VJtDc5DigdOcQAwTWDFPzrp2/2 7fVmNwoXksQJx086RjM0FWqUPzet7WiTIcqMWQqqCkvRgbTNp+VIb3+Y7f6w2E6Vv+/yQa5OS5Dg vDvJMnGXYNCLDFxYoed2Dib/vs2dvoNIUsohuk1eCAEjRBtNA2DCYpWa0JJaDFaOOdwYHxjhst4I wWHZLxFJeOoV8jRKoSTgojAwSHqAsmPhmgYxCsk3CS+1ql0lt0FhpoZWNF7GR8YXXXbK43hDeX1K xiKCOidGmMybXAucr5BjIZ9WR7inKWJ1MUYsCKKKFqQS6uxmvS+pLBeZsFZpkOMLIqIGc5Cfc/a7 Gzz1D8YmuaKBv69AyYKKzCDA8sNxa//1px/FNWGUFpEMBzJ5cjw05EbaWng+vNoofMVZ18/Xq839 bJu8ss2uifK1g+Tq0yIpiAOfFFjZAbbTeUDxjlDMA5dy75dwOKLJWeBxwrv4b7IlB5E9fVbTchyg VHYCO2QIg9JLtVw4xnm6nvVv5G4wdPKw9ASWTmLkYIKjqPWLA7p4L6hap1jLuhEJVXw4AfWLKlV3 28Yes8n+4eU/7Agz++Enmz/+N9tMmRjg1/GmUVE+fi2krQMSUPagSNHxNTBBIgXheCnNyGCWmyRl ztNFa4mhTIqeqck/DUcQTYdsgwEqMsKDDMz9/cGm1Vn6kiMipYtSP/xDH3vmkRX+TVSY6H+VGgWR Nyx3KSDgdCGdulzLQ9vYP1XgxaX9n//6V/vyfLbbmluGZl1JPOHO+nA42tD1dno6qbjxSnqnmQfe ulaIv5bJ8D20pf384VEzGaSBBdYHhWmZVX0Xfy0GpCChjMOExvHyeoFcBGnO+iK3YRntbrdR0CCD z3tRVphRfIF171piHrmPNmvIibd/CdSPuwpmLnUKetgFJ3gbWF37nweG5X/B+UTeiCtRv5Uvco1u CWwtvR98qTOYMeumnX1MFLn6/e7g/JHR5xiKCGmFXbNZ3JEEKrKwhKBwiwAuCQqe6E+83XT48F4i GMpIKW94G83lXslDyyRbq4oCAHxEVhLwi7BemFuw2F1OxCMOXc44IGKZE47SyKklSxLGHt4q7VML jStlptKdigfCMGL+IZQOykPsY13rALfbrVpRWD9xb6JKl4in3nSKoXEv8toTYfZv3pJTQrSmQ1za d7VPdkUVLNelSq0yXCrJm+CZhCumjAOM6ns/nCp8f5iLqLVWqhNFm8C6xNrCUOMQ0IvCiGTIEaPM 6Q5ISqshWSNFDtaRX8KpMMjOMZF8jdprPK3JbxQW4ArVDpRjpIiyiFo4sMwb3G/sft/aocltn412 j2Di/Y92vvvRznlj4wK/SEPb1ENHhEDKrIJLREmCKygghYtOg1DUt8p5pvezrAW+p8ETrlzhUIOv dzQ5JTULCQN4lwVr4mO9Bmsg+QouiQ4GpYOOH6Z1c+dBISAGaqzf/x5ptSub+PNr7F2oakBM3lWl HZtGbVQYPGAEegyxvorGssy+Pb0qOuUeCojXTMIkiseIPO/NpLH85/ePdoeaRGieobSw2dbW8ntV 5TMdV2/WFkcSVVENgzHRIFivM6z3mdFyrqayrBsZeb53hb94ZQoWdA+MoM8rdSgJJ815ouJMxOqx lfYg1EOUYcXMypSWl///UU4OYC/K1SldqhIXiyjvKoUAMKPVrlQWQpNHIn4RcvNArtSAhZys4DBE oy0gK+A6l5ADQWiN8ByhuXSO/mAUZZACC1NXeSrdpzadN4kX5x25mqZffv9vmma/Rxk+4cYVRNME kNTm42Xp79pPSVEzXdxoxvHSuIwVFTD6LGvhBrRCzKMz0rk8kD8BYaVXL9VMFwZMKVBqekYulzmL S9AXqFQSYbA9RLqqcmlQrPdMOqExgPRIcX1vvJKidCxSm7hpjtEpLfGWJ0VrUsJzfMrn131/S1ET Atf8LkXjnQkUOcS2B3DlMmMQ5j80W0fkBg9CWGfsl2ZKBBYo3Aitq4wou/keDWOkmXfZVGoJeTxu 7dgU4lztePa7H+xy/6M9Vzt7pqJLM3S0HmHgJAapqBKhve84SsLoxP0Lff40OFXRT1b6hJdQukzy zSoQLR4xpUqxItyosJLmedDp5w5Hk6YmOQbmf0/YJ1w0LmrI06Rzl/5xlVuvFhJtC5aI9jaqyN7P ur5x4dgDd8qM5AunOy327eksWkV0Ob4VZpxCFOoOIVW93+40DCNp/LPuVHx5Ms5r9UoE7XMdqeQd uLMUzDR8tlR/JhOGTtG/SMBCFZ9+ZM4wXw4FZDFmJJroT5KO2m60NyfOOfhzBB7QnkS1wHirN3nW vEf21oUD4GFpqoVzrXyIBNbMLyYPkHP4k1JlHFyiGUBPxPOFFUk/izJor6gFDpfoL4SIbWXt2Gqh KLcedhuvLqoNhhTU82ojx1c1ymeU6btiyo1HB86FVOOrDKsEhN90wzUcQ/1vAfSLW+T4klokIp1U 2kpUBvYkvSOPjtSB37gmlCp1MXbIG2W9tuMtFrQX4G0qtUHs28quU/zZ5MoWj4ej8LnfvnwObXQH bqWUqQEKVDpd0VTTYyT0lolaImO1mqJQVS8LSuyTtVmtgRKA+1e4LCHi5/2IrvagkVoxAVryMKJ4 OH7nsjCBscgiO27nQycYCBDGTVLSPjZNnQnRlMBEFT4TY0h1TZwZYZruHGg7Ej6SADJNEvcmWcQU 2UciEjxziGCokVtDTgW50EeKd9/IWB13je22VAWv9mCrbTdH+/b4LyI8Pl9R5jwJ4wKkVwke4Hyp hBGloacaSgJorEqycw64zBrOK7KUV/8k8x1gNz8nTfFQp9XQX7UuuHFwLUsnxkqhVcN1HaKgwsqE 77XrBHtQYRTeFDpokkCKKB2jhHFQwQVeVkwkl8xN4fMFAZ39r5PKVUo/wQ1ZPmYtMHgLsTwiGhyB KDVJHFP+ME1z8kolv5uG1nJvzkQ4GK6GYRKN6BMYKpeccUkiokJar8A6SaH1vgydGQOXZogtGmyr CyGg5kLUrJRfUtilghvmbRKh/eUDMxM3ClCYZkQwpNahgJPUzqaU1A2w6DWiJwWtQSC62i1CpO5t np0/TOqjSsBtzLFSY6R6ABWcUcocfCjqPNnr7aoXd7YqI9qRE/EpJGweF0L8Hdo/stouo2MbSfnU qyGh5fIHL+SCdzyX86AA7LH8vAz/LbmbsPSI8SmsxptF2f6NMxoTazSiPDHuKcMGPuVqwU6fwHwq 59cGwgFq7GG3scf9xg7i0pS2ZoMu8Fxn9pef3ksOhvXC00BH+Hp6tU/PJ/t2OitU9tL6ECOq0v0G Q5CStmsyqQXI8RYAe0BTgf7iSrlsMkCYvLUwNU9jkLp1HMFbQlroKlRSo9iw4vGiEiMdQTkWT4O8 yZTBCZo661XWAHtFEkbMkXMRo6EkIEhlkDL7FKOcKJ13QuP8PaHFKI1HO4qhBgD3Sbefy+/po7BP iQxiRKMhfp7sY7Ha++7FiuFsv061ZU37pnjhrS/eX5kiGp8+ZK6XFedPQzxUcXJ9fKBdXQ7BCqS8 HrEUf5iHJ7mZmBvJeYwmmqic+d9L8wMdByUd9qlJCUTn5xTVpIEhgeMkNTfOulqfGOOGZLHkfIq3 SIo1FgA+rdZNVznYn949qEr46emkyh8Fnf6KnDJYmqe1We766QK9Q7s9tb3haLnCAOf/66+/2N2h tZ/e3dlfqsL2Gc7Ee4CTcoegmw0tS76mHU3PIXOkCehQD0SfcIgEehSgu0tCeX/tQMeG2uUW2156 22wgTSc5o9TF5/dQDK2AStyhOuELo+ZVwhgEkYT0FCZHy8xKxe+NKZ6E8yKijiGIqR+PqqLYvCMY WAYAACAASURBVPQGUh3SBfJQzlNGJ5fSnY+BO9SNLSvyFrSeuHFQv1ZEet/lzr8POrA3lYRoj1GV C04X2lzewE2fmAT04oITHS2L40SpETf0Vt5ShaRaoAsr4N1TR83Tk5eFp+K422GzsePGOUGJoEnb DWFrN0+23TKXrRPJk3D5l09f7fPzq+bIQYiVNKx0jgJjSoB4vFcaQ0bUQzSlgoBE42NMV1hdRyJi JFi03bwpZYDdwWJXg7HTE1JawLuyTj6FyIl7XgV1fIYsj2gvC5zDh6KCizHSPkn5TNHGAh7BIAXS 4sEH066Mr795uh/OidQpRXh87nWlCOFOB76cGwIn4Pr0IPSQZntAwHC7t3Es7UTbCTiROhIwfqXL X79p4hd/SO/dU3NmWcOFCi0GXOlUEmP0RmNF+LocjvVEkfJN5cKLRUkbLcr2ITdNBI9YYeK9YWA0 AyzoCYj2paEPibOUMEUZM0XQjlex/ppMpTXFqAB2T1IchVCsFrTcOzLut60iNNLqy22069WnfnOn VWygyIFZVjO796pyZkmxGWLBW5+u6LzfNIT3tRvsJgUH7wfGEOH0+ZsockDfQE8NDBVyLY3jdB4U pfeJClIoUAqubFc1cjxE3JwBDCVZEdkTwoNULF1lJReemYagaP8ZLLJ4GxME3f1+60NNIHOnXsIi taWEFjcGACOlxQxORdKUEgUgZhYSw2msu0qomWUzD0doGprehLbBitdgBqYnMwmEZklydMLcqbDr 4EBzavVQri1agUsJ+KX00UVJ4dJHYDk1oAdLQmOaFIqogQZaUjwdIucvMCjWdaTSmK8Is8OKE1Vp AIFaHNyo8SdEGOTrlMpFbNXgx40LwIXcLc+7p+u/KX1G3bTY15eThlZSbPj33z5pFBOg49u8niT5 knhlqZ0moUgR3Wr0Err0oQyqidREvLQgpWjwzdAl/ksY5ahsSs4m+hx9LqPTQuiZc5G6YPKnNiZd Vr/U8Kp4YBzOYb9V8YD94rI5mdKjGaK8JqYKYYyZK6nU/A8EVkVooZalCEnfSzUOeSDHH5MUMsMj 7m2yP0+DVcXenosHe2XCt6gaHh3hINCs8upvUA7C0vBU0tcKgwk+1TGMNYoD7jzTUNyIIkv4h/Pb FGiJfERFmgjsjXwX3Rk4lCQ3lBqjiZiWtfVxb6w9KWOslaV2rigmKYsATxKB2WcOCgMMFj9Oww1W Z8/nm/Tocn0XSiZu8HkmIh5oJiyBhgxr4IgrS2QFYoS5CKgMPP7hbu9tRXRaNP6ul8UnVYn/2LAm MaMUQQNmOBI1NbW9nokAvSjBudguZrtxUuEMo4auFg6JyU7cfFcf9ajalWu95YtZA8giSYNeTdV/ LFB4rzHYLVLPd/utxEExnm/E0ZR6JRUFVZpE9ist0ygaP9DeimM+YWea7O6411SWIndQcl5GL6cD yoksVltGxGXMVesktCcpCpqbNZ0XcTO69V05FCPQtg4k2tW77BP3Ig0/8DDTyWxeRWGoxWD51Xv4 VLVh2gqRl9ohfCwT6o8adRV8MxmIMpp4VWq1t4qKV/F89hyMYaRU7nZ7pa/YBzrL++BTcSgaNLQh +bWNPuM6XJXifj3f7MvpbC+EzyEWKCVKvHik3gkwDnlAN8RpenSM1PIoEOwrGMppHqCI2z4UgQvC hBaBzjFjTmz+APiRwGEcGZ+H0fAmYz/Y3rHp6b5HZx55STKZ9haMEeXyzUbDBCj9UyRRCiXn4hjD 4YAiLa0nvS3nsyJlgdiqrEU6xdlqKtsyhIsWHAYabKho9m/Gg/9+zAf7S//N/qX/ZH8bbnbbfLCx uRPOIpAfR7a6USIC8iojqpJEFU5RAUOkOugpXma/fzvZby8vWt+/vH/Umgj6IMMI7KbI4FZ5hU0F hspsKV0z3tuevDrtmBfaUqEuGlOZvIvCHVNWAE9cnW8TOj4+t9KNK8/nPZZOS4HG4fcn9dQ5gROS btefrW6gRaz29eVmfc8kqsW+nW66j+LnaVgHhpHqG5hsJsD6YdPa/Q5cdaNfKuLkAO7uuH59fpGj fjlfrK0A3L11qcZga56gOx0ZYzWxl2orul1vUhMVs7/kLoNfI+CI2gQy4t5SJSJ2kqWGSU/wsLgg JeuEqCDN0uJlRQGnrXeiWshRvOn+Bg8r9capEiREDflYb6fxZnDvxC7DukqvaAosymPQaC5dlKu6 ZnYl/EpKmQv4y2CDZo5B9CO6IupxKQ0sLFZ6tyW9LNUrx4ErIk8mhUrtDHgQhf6h5iAQWJLEXn7n AOER6cFTyF470MilBmgVeZH3itQ3NZAyhVcNt2GwwDv2TWlHpYBbRVcsneb8nRkdlqkcfH/ca+It E6R5L573tRvt6/liX5GMDiKfhAwViXj0k4pXIZzqGmBhkKMWFU3Jf4jE/jAgNTXxCgyXAiclaXTN KkVUCqMjv8HA06XvNBCv1sEZqxn3lDlvTHhQVKqazU6GDsM8v1w0IYUoUzpRvIuivpAclvEguijs cuFS0TLirHeMnagSpKXSZwLo9p/lO6UQC4FzYJSVc4j49+Omsn++vthP6836eme/W2OXrNSFVAFB w0icI4YhwlloXJuyBD+P0A+0nyrkxLCNMDZOSww5l3AgIj67PIeeA0eY4BHhl9EIneAInyTk2K3k hnTIkF8atG51Be6zlVie8C2lolTEvVqdVAmkeSXO0vcxcEokItLnZ3b1xpYdBZVa7U3X7mrzmNm3 F2evz6nCTTqlqVOeTeCUyAg+HA86yxA8JeMSKT736LhBU6u1J3oM+85++fzZI06x2zPrEOEjY5G8 N4TQUF1VEQAVVDIKV9FV0SGmAtfYCI3Zw5FG8UDvxbqqPBszFnDKfrvdZfvQFNJBDOOVu6ZBGqSg Abo7cOgYkrApGSsvR/u8vhDJ1/DF0J1ShEtZ2nuNPDpzK6tysSojo3WkELwQHj76pKZhUtiYpvym sUSeGmDEerFq9SW561BhddXXFU2oaj2J2X9puIKaUPtOC4kha2tvkyD0rFrSGz9Y67VXIy4sT1Ik +C37qjIGGFGepQEXwBvKAhUoaBiEqFKLGN0w8hzgZszV4zJyELQB86opw78/vRrzHjlMfkkB7mNo ZYyM+t40ExcnNLbSWC1XTE3DVZNCZZJr9vRYvxvi/ADxAOY4CX4RXWiiTGjpJ7Ucx+lIFxcxn1XJ C1kaGfIi9RBiFMBXWseuQtHA26Q8+iKiBYPKAteiC5+94NILqwNQVzuHt/wkDEf8r3gPnvWwQe9r a/dtaT8sF/t5vdq2yO3b7gfry3tbq42OAxGss57D0HAhBNYTsZeO9cWUorfBIV6vVDSJjA+/RZsI 51up4jxax7tEfxts621DNdX5UqpmhjC8y29/V8FICiAqEqCGsTjpU6RRRmVNodBAiV7qrd76pYsp jSjXtUqqF0lihrVmqPAwMMSBzo/BSirok4P/3FmMI03yM/dBfZwuAS4FCJQklJ55szYNyUXheyd8 7Y2TRrWxEiCO8QGaUXMy1UQpyla22412pwg+1EzibLI27DnOh/u9LRs36l429TQ95GgiBvWfVbEk ul6wAeEIXK7HeY2k7KwFBQf1C2uOQPCw+ECYqj5wwBeNeWRirr8B7auVi+NIIkarp4zyL6kfqQH5 iaduHKpFc/5cbAzgWZsAPT9ATsBKQHK4W7Q1UKIlpIZXg5GESiDurUaT9yKUJq4KWvAslLSnAblh N1uhdI7IxnGRxkPKBgUI97REfQCLr3BGbqSPqFgybSW3h93WSgoIrycbp7NXM318kIyXxAUrLllt 89CoKvZ43AuU/uu3L2+kQ2gN//bLJ/v0haGmvaK9Pw7S8FvmaV9SZ3URoZArDu6ZZFqC/RU80zeA Pcm5qB8yJblZrlSMJEutJjG2XAOAxKT/PlVaI92hsTAEIDSavKOH0jLvcA4JFgdXt9tW6YtSS0V2 PloMp8OFkHqDpFRcm5x3AujV3EHY+5pSTeuv46AcQCpVSllJM2i4LkoNV31oC/vw/Jtab/rN0b4+ /NkaRPrUDkR6NLrSRwyodTUIWqFoIDeNf3en6x0LLjcUCg622IPaXQqr0YBi3JU+01u4cJhSCADo Z7aehj14f6gTHEP0MMlws4eqevuZ1nNtiPKcFlFVrmzKYOExh67jsyzZH0iflPiTlr9IrKRyrImq tKtd+9muVwa83OzX56+2ZzBq6QNFmWYjFjpQMhOWJS6w2lrSGka7Dm1GLpuspD/wySShLXwTg8Az gW8CltNZks/29HLWmDgN9s22usPSukqKJxp6ixUnq6Ay6lSQpPABGsnfwZGlflvx8mIkns42GGFE rgD6qYeTs3rY7QWBwEcU6VWhDv4ieFhip77p//jYcKE9al9xhjcvCn8mTTF2ng4Pbtbf6BkKnKtk 8KkPTYWDguej1AgPw2VEnCLRctA0dRcOx9X2eyaLlJYNPouvKfiuNOa+fCsbE+6m/j0Y1KQbtPSA pTEVmNL/fkN5Gh7JKk4PHhDJGNJMmqolb9JR8h7EHN4Ue+EX/NogF32jenGzngOkwcvMe2uVtjKT 8U/v74VPYNBQxPz0/GyH3U7P9Xx6ta9PL9G06y1LSCQnoN8jHZfVSWC5fF0aE/9m1L6zY2PebIzZ Cv14Tjx9jimNTwRDDJb0jTDmTj4VTSWxt9U47RvvyrAevSlk15p6VYe/o54wkfUmu3UX63v3rolQ CdcGuoIwRaV/oeskcUJGRfm0YzlEJvaE6qvSoPUPkSTvgzkZb9Jif9q8M7v/aEtV2yVr7doDPDOM 15txW+b50RMnNjzel3X2aqMGcmpqtROcKcODcYKh/vL5WTjc42FnRVuIz6T5eOhF0Sv3NpvT5ZEk NRMXSSNSMA7gVEmVgr2hkMSdkAquF6RS6xKVLpRYwYZ4Du4EDpl1ovQv2g88xCiWnK9XnSF4VN8Y xwX+hljmYWN32VHPM4yjqoI4XKJWpHBcN92jPHESNWQF2pBHWRo7lnPXvDgAUVfa8tNs385XBRRS oJCG2GL7Dc6dZmpkpm92vqIgu9Xnp6HLiqJkR4BOtipKCeuOs8u+YjM4wpokXzdq5ueMCisMdVL9 gjYS3y8nj+QTKX20v+0K54V5ym5WotudxLKSTKvLDIdCaGgppWGLpAHqL6wX+/z52U5XoiJIobXd 7dvgYlAtJHVbbS0IH4mB3DtgFCCQil0bOkdtWasaAo8EA7qtnSiGZ0STSJ4oB5dyXpIwGnm5XA2w GFAmQSuRzZDW8AvMCOxisxEXiRHoGtOdH+1A68A0CZt53O9EZmXxHrOdAECqb6Q1vBM4gBjnMdae zyVnxzt/hbzIBN6stL4b7ddPX6UakJQqHDP83nj8nYFj/1mvKqV9yVYp4IrZdtFQqmvjQJiH/1JM pbHU+TaS7H0TvgqZ6EjtpBsucm9Uf0MIEe/mxdeongqEdyIjKq6pbkl5nM9HH8nFAHObRiYfQfrw qIK/g+N17fAgnqog4IdWBzj2BaOGQ1LTdlnYsTT7aXyxP5NCfvgHq+8ebSpra2+D/f76SQ5Gxooo RnpqSC2H/jn7T7N9aPaLBxXpQ6KLOJnZJxNr6tHs8jj7LRVL1DhpefJIg0q3piBpfmSc+xg/pWA4 QPZUM/Thuj71Sfy+iJIxDpCrGURcFADMzrnCYEORkbAtfL8/cLPAiXC+v35+sudp0fNSgSPSJ8J8 PV01E3SYMusxjI2n5XDgXOUjE3UDfiRRp8MBPgDCtatcxgWnjRElEmZOZJnTr0t66FLpYGC/f32S UXdhytxmhs/EtB2CHYkksrZBDvUZi96OJTsR5FviMk3gpggXYpM+FIQ77jSZRE2CBoVwgitgeFqu u01nRtBXSh6KfLvWDDiA0NiQoOs7gyCIflFGdyYso4pmDV4kP0cWDEH7MkewrdbIoBjmHgbPqxJ6 GDAhvJHUHJvozvex3y7l6n1xCXAWKFsg8pfbK43RCqH9swlXMa78o747hN+CBAnzljYgxPnqAePo 6QSfD4DO5SXHF6iOBG9T2t1xp/4yqpZOoXBlU3mBgQpZJzULZrExmff1AphPOov07NVFAl2Q+j8Z p+9SL99lbtw44Sg8xwjhi7fISmqV8SuJBiYj5nwsL17IOKHcEFVGB/Kd7Y1BXzL35A10X1ER4rNS qT6aweURY0Kxh+mZTQEEix5AwSS8ok/YCeVXAdtcySQnFO8Z8rlOk/GmR0Bafh/9JVKWja22L1Z7 KBb7UKx22e8s2x+kcdUsF6ePBAboHCj+HSsZ4Dt/DveNWYcw/fljoif2gjXBWO/bRp0CSTqnbTYq PqCmqY4DXXLmL2JE6bkjSnWYRLibLW+j21J6nCY7SQssUnZFNaqa+9rqblWoX6A84SPkiUoTcJ0I qk7L8UZoKmfPgPcUkjSz0Ox2QzMNJjkj5jNb6a/jZ5jqhExzAQ3HAwyyFzH+Q6rZVXx9oANOh0G8 FDsIFuB8yTmui+4KopJQkhhEe755ixTPBT6MBpwUF5TiIsW8WrWQTvuZIAMiyPEJU5FHZKWeXeA7 PElY8wL+nZic6DQYd7Wz3c5BM6mcZE2VVGoqEWGRDvqkixDgEz8C3Z7wwDHTToJlMbIeSwqGBP+I VolTdxPISlg3cNFp3QALU/Omt2xoYWngjgEXPBAWPzcnvFHBw/ITovJvcUymUSHkHeqOeL6sEECI wkSSveC5ve+utvv9RlERC4rXtHUQ4Hh/2DIOUgdSMiKaPMNBj8pZVEVTqoT+kIYPxNxB+v3okSLV Y0I0WJiM1q0Xp8QJcD5+niK+t7MkgqtXYBMGpzaf6D/zcD7m/CXSaOT6IlVqk9lUvyAJ90oRWQqo 0lQWy7wfTkCwZrZ6UykX2geEuBERBDEsalp9I+QGW559V9UNYFfYnMuggNvx81w2HS6pbBApOHDP 5rLnLs7nawB5E5wHQ4LRv6GMSUVJ8i5wYUfbrYNlu9Ju9+/s5eHe1t0xWn2c8EpaJS+LPlN4Z6nb 0rPWMrTA5YUBfh9jniUXkoZ6N3KeMk3q0Rxt1GRknFMjXHJZCrtcOVOr1VQu0WeC4xU4mWR7BHm4 IJ1X4rxbgUpeL+KzU1A0TebuqEgwQ8gSaWC6OQbu0aLePTWHQ8DEWLdbZRrcJWAOoijuxD98eG/n 3/9uI+zyZbHT+SL58J7GftQRlB57VREsk7MPXgY2hxHa1Z7pvE3tQSaIieDgwTRLC44o7IQhkRCl G9/z6UpHteAf2mceD1vbtBvJQl8vTEYqFYXS86f0lBRzKW03ePakHkz2IAbOcoZUJDO+M4QLZ9LS NrDYVRi2RtlH5E86LY14Cm2wBrpZNBqfj2BWyhAAwBKWaTZajHwnHaxguHre+jL01hA+ary6G56W iGQGb3L8BIPAHwIAv1LFkByrp4uMv2JxqXqI1j+e3zAOvAEHTqEqKcVwDu+/CvTl0FKRQ2gfCRru kw5uaHO5aiJ4Cs2WZnvE9A+PdrdrVRliQ1W0YMtEJPQ2CHAAojUM64kS8Zt2tB8+XoaD+XLrpNaI hAkeGb0uOGSS4ojGX+8jAxAlSvUUQUAlaxu8sTRQI82205QYybREahfsfUmkhCAi+8FiOODtzbk+ hCP60xJbPwZMKCSPXjKV9qWo6j8H8IuzSCRIDi3lcInMpWqlRmKR3sFn8zQPA7is3oqT8D4GeaqC TEqmyTQI+3kpG86d0lbxiMB1XB2CIgeRPJ74YGZ/yUb7n/bF37N9Z9nxXueoY2AvigNUiZbVjig6 pL68mGQkjTTVf3K73+7Uv8kZFkUjFDvOUun0fZL2D0AxfWqwEzU6zQfxkn5oGCiTjQCug7ys6p6U JxzMp81L4vbSxPLgVJrr4i+588CRAhhzp2aNS6uVAsLlA0dlLSFe3m9R8XR882aT/f581lBc3u3D w4P9j+qjdYwfu4328nJ+oxmV6lLwyrPeNYQBMWTSTw8l0ySvkxwjeDT6XZ5qObF1yUrNtGSCEUUk zirlkUW6XZk1mU/ulpLI7aoe0hZ4JwpZO515x6O4U2aVVUSymscZzAIVANwuiKC88cEWbJ+a9ElV NdDE03vW6iaqxGQI4dASl6cKMPtN+VLd+cIGkhcJpq8IpYWqD2lMOyxYyY0ED4hcealrRUbJUivs HinH3mIUkGs4czl8yq43+boGDrm3N5dK0VTDUx205kXbdlEK6e0Bg0BTru/T2aM8/jdY1PvDVrPZ CGGpOGHoRFJFEYHoaKC1gxHoDCeghWh1wJ4JxIyUAouDaIomUYjSpdTRoymGQHSK7jiQAl+jFJuU ClCYTNUSacGLCuKlWzyNPAe698G4x5BQzdEA2LnwNQkpLkIUX+OkYPGdFY9x9AYLvJFXijLZrmgT iRam1KbiBomD7cAwRlO9W7lP/9W8w9CrAhTmMovmEkUBChga8U7pWq00jmGIWhGlas0BFH7hgLj0 uBW908bjOBrpkrzsNNtP69X+W3a1f6xWuxyOdtvsJUpINCOwHHiAMIxDLEcYyrFUAkMpk8/XgFQu CRGepiz7uif6gZRc10UROkRNfhMYwqf0YKzMtlQLxUyHkOmtS1JA0BBZJ0D+AWIMaorX5VHnSNLQ 4ni9Ta+N9i7wG6qqTWOv3U0XGAcKhgYS+3y62i9fX+1vX1/tqbva/X5r211jx10l/ffs29nK9at4 EBVqpmNul5vPBvVCjjs0FUm4J64N9NYnK4cSRRyvIYR0NveLYMXoo/QUDgchxyiaSK7JOFI8EcYe 6hwolAqj9rsvHDOqg95B4Tr1vj6+WA5huF3BqLmAps+F8Mqs/9IzFt5YLYn02veZQGgMpYtSE0Li B9OU5zdsghxelwqMy0vy4hXpUPD2wdQV2c5zfi6kxOw0oodG6N6uAHaqHHjFT0Q+hY0OOtLrJypB 9CiCleiSoRSZBmqqN2mxj49HpZcSuhsYglDau8PW/suHd/YvP/5g223jc+BISQlb+16R0QuTZ66k CZlt6428JaA5Dck0kEoaOHg99EOxiVw2n3Cbh3zG5LIdiuqcYCcWOumlWi9IW2JmYSRuwu009440 NFQSQs2TdEC9fNoooiyvJIojBm4VfYHsOGYA7pv0gpIOfZJFTqQWn07/9o9L1n6XdPGWIOgiLgPD 54nDQ5WQnss3pxOTdqK/kJSAP/FQfVHqgiSvNLXiK5E01kVZTRDBZtt4f2hEoHQK4D1FM7ld7J+X i/1T0Vtx/87Gh5+sa3YSnhOeqcjM1V/V3SCWdBHfH2qZyXujAY6wXeqnEh/JhfHKwukrnEXSv05D UHJF62o5AfSFn7VpFEV78QajRark2I56asU38fsnPp2q1h6liYMYaflbm5Qw3rjoQZDl3ZnB6Liw 94mC5/32/Gr/69ff7fNlsHZTWQmkoVmVQCCL1WXvktqbStV20iMqqz7GzjtTxNej+orETows8+Zl T2uBcMC7OdMaGacigU+VPm4OOofcMQpoE61b8KCyaChX478X20SEJgptPOWjdSeJIkI3Ap9WBZdz EL2RKTr1et4bQccKnKRmVaY+YT+veOAkvxPT5GJ2ZxgsEUBD24fcHS/FBUgTPFTxGJ2r07aFtYR0 0T4Aw1ud71R81PDoUq1ZhgQLEzYqCbVRNqVdhfskwFGtC25xaXh1LSJnmG/UvuHkUP6smwG3X227 rezHd49SigAYJeIibydq+3h/p7yfyAqsBpkWDv3T9WZfXs/2+eXFvry8+PerGRsj1avigrcCcSEa A7sZo82omr21B74Z8jvwTQT0azCrG+k6d/UCWpDw4qS1eHF8s9ApLj39dRgkVbS8381HvmOCMud9 6iL6WCdvhPWdgj0viekoXYNjaEAl7TMcDk2Z3np/XtbbCNVjLXUZUh+mDvQbfgUzGw/n0jrqNSTi QmWjcKG+t+qapFi8J9QNsA/V5ZIpGlaXNBeKKLh56x/lwr+8vNrm1siYCOjWMzNsFzpLYf+89vYv gLz7oz3/5X/Yrdk5/hWVSKIrVT0F5KYCA9Ehcke+thiBu8Pe+xejb5KnpPqrsVQ4SFL6EKCk71DV xQr6ykYOWBdjXu2u3cgAaJCotLoWW0qGxIZMS2pfouoqCWtP25Nz8PTfeWasK0527VjvyeZ6UgrI IIfdPMsoPPVXu1S13fpOrVtrlduHx6O9O+ztYbu17rrY0+urPV86+/35ZEs2q20mk1NkMIxPU1cG FJQV6YnFpCvUNqB5ECkyL9L3hkifiModPVjSri6saXcKMGj1+fJ8Egdst2utPuzVDaHm5czT2Nfh pPutPVXFzwF9cf6orkdUm+AOOTJgoYjoOEg0bLctBF53uGoPi/NJpq4CRCj40p6GwfMOi0gJSfEg mfigw1xgrIf2aCshNA8vafZyPVIhap700Fzz3dSQShd3NCNHqsBQ0E1biSqgzii8kbgzlDc95/VZ cB7qY5URw9vdUempvaF0mezd+wc7bDf2sN3ZHoY8sjYQGiEa7lwPnn++3S72t9dvYghzsU7nTk24 zFukskea6aOj/MUVMXWDxm6xUPQ+4nHVcR55NhenG9GcjoZvLgra6hI1pDl5spXlI3LkcpH2RRVM hkkqm0A4MInBQtxNq8E7KU8GJ0VtTm/kTm/PSJ3s4qApc/ewXqqqfL90sk1pwO6w1aZzISiE6Fn1 nJ6+uGyvRyrq5aSViiKHpHzCEwbukBQg0iAG4WiAvYkIrLTSG+XFYhcx2CVaNFhEJWrK3TjBUlrm RDjbMrP7Cj33O+s2D3baH+xSH+xCBRbVSgwWRESlq4kH5f1lImQGP0cVJvpGcZYr0RWppwO1fIaw OxasKhQVAAlAa+DvwxF7Pp8s24I7+R4pEhYm6kWYpPzgZEY+OxRRg4KQRtdhUGk5SvMuiZt97Twy Bajxgs7oo/EY0FKVdlmgxdx0HjDyW4pBbSOBO6q0T0NnT5eTc600JZv74Hv78nLz6Aoamxjo8QAA IABJREFUUkzJhusnw0AfHrroYI7SfTIbRHrzqLRHkSH22SdWefQFrejD/cHOlwdhWETHGM+KnYj2 KooufCARHsEK0teQsUVGlT4/IL9PP6L1DtuAc5T0lCYzpUlBdBuGlj96ZbuN7qLbFt9LHz4bMkyB Xel5MVj+0I5tQHEgNPS2Bqc3SNgupr5SOk8VL3m0PETkQlsqtXNoWKj6izI1s/ITdJVzSV27Ko8o gIVwJjZ8k7vDRoMcpSfFJVhme//+XQDzzmiWseBH8wrpMonlUxFiQjAgPx76fO419miYPHpT+Fog Qe3NsmpspS+xJnRlTprZDt4PoCJ9jW2rdBDuuDhIwZZWb1kMvkhyPN60y8EKzAnwk3QVxj4/IT6P Uxz0HNGhJkFAbVxS9AzCg1pBnKoR9uo7PSRwLG+0zZzgSIGghPCJDpaPWRoYjBnNtu6N3SHp0EnT nmjPh4zKQeKdZQQXDQlwJnnSz0+Ts70tSRikIiai6kp41P/H1Zs2uXofWX6JfUdV3U2U1OqWxwo7 wjGO8Gt//w9hR8fMaFqkSN6lFux48ABw/M7JBKrNCY7Y5L11gWfJf+bJs5ywRUkfIz3I4gf5hJ+y cRv2Yta9xKdOEz9dmug9fY7L8iG2bJlRKQCyIkWRgZ4rguU7iUWlCFaW0LIn7gpsXiOg5gXRppVJ wHpFZS3yv0nHoPugaPF5FP+WMi+NbYoTazV2cN042Cx0rzzH9MJP3bO2sbcC1RH+qZHMzF4deF6U GPjSwcAWMBp9J1kgtWxgkQt5qcK149Ch+MDre97uY9/CgXLgq7h/PNdbhNAnB77cotvcdVPQunzX jgXrWrro3tc7a/cSigR8LWAeUUxx40CehszsD5+iAYeFIcBzzGYxQVVwYvSJm6N9vIRrJmRncTgZ iQ6tOHWLpmE4ZDjg8yfkkp71dYhqidCif6Q4uYArYBci+NEQAcsRmXwKHsC6VwUI2crG4aPpXY22 SHwkWUzgeHivlBQwuCrCGk5QNl3grLdCMQ5T1w8eQPY1s8a4AOZ94ALQjccZJ0tfycfLxVQ8qMfZ TKczCwFOHgqPfaqcb0i09svebghffzzH15dXYVSjwTjoh7fbJn687jVKcdDwQNh8b2inxhx1OeH4 3jzcyFAcYkErY7IdLGgGIDYeYE7Gp/jv6S3Pg5PQiR6StBy2D1WebHIW0P8nIF5QeDLeKSoFSpdO rWgKdDMlcK6O7T2nS10Rn0mdqwH9wbAXn5a0+BBxz+ou6TjkaCkZBPl91zjz0ItjhKwK2Ulx4m12 x6nKy1RaUWF1aT9dBxaurULpJF85azvEWORmLIFUSVYQ4U6UJ/gvp3X87bKKzeJ/icP8IY7RixM+ 6LnG1no/R4ni7cntocI3GPNkmNhRZ4juUzKSTkeUlg7EU3AWMg5PR/P1tKXty/HyL18+x5eH5S28 U+MbrHwwKzqFFtO9JlrIp+lSKpwR3I3swx6hCXhr5TZV8h7HyWOYqDAQLQSwObK3vLzVGOXbizoX FV428hp7BrHdJ18KbPDUxNfVNv779x8xm43keoJb63a3ix00lIbkJb/Q5W0psDp1tcYrE1jnEFSs HkUE6pA3OSS090WudTiuD0ID+iS+4+m2afax2qx58LXVhTg9GfbkAsvhTZINozRFp2kbea91AizM jQhd8mhgx5R+4ne8a3TifXXcSH8GmpT4Osol5FBBIcI/82e0Z23jqQUcMqV/VEyjiH260sYcNFPK 0bKy7dwPWCfkl0dAqPRGJL22Cg/Y7Xa6+Lz8gGqO0fLLBf9Ia/SOyWqzXicWk0H8+cuTtHwzgNDJ UOm5PPUyGMg18VuSNGHlk1D7vN3Ft/XGWWt4ex9ZqQPAn2PcI2HGrqjeznnzyaZRTov7Y+xF2rPn Fit8ZnpwNglc+52YzSbpOUWhG8QA8Fe2XxaYauxJ+oekICJeGRNRDqK2kHfQswSrmN3JQETdT3ro 69rfVQaSqyRG8V4ArRSZ3P4VabLmE3HpWsufPj3M1W3tj208r8ik29wOGIISKOCVjsxIS8tdXCub B74P7aDY3Q0+yqjO3Y5Jte5ATLIVLkYBlb2zfabGvU48htO6L/OfYj3/a1yWH/U0nRq80XBuSHEt ow0di66rswrlx69gAqsPaskA7QHu3j+//zBhc/xnxYxJPhOdmC0f1TmN4FUptmqnkUti/R44FQRG UoaR8DDaWxnAPeU5w9cKwjFbMAHDui+yBDBZlFFY1inggXThIp7FEWhvz7KnFcYowTms8LaNT52l D0Wggy4dx0XOtbbNuTo/UEuYS0zAixmRehGPsYzT8zo6F/OveA4KOxMhN5cuTpASAc/UgVqkERiR 1sYUXk1NqVXl/XpZrWOz3cd0OhElib8d0uKgYjBKsGIl4yAfIncRDy1BLXCxIH439pXD7TdOfg+y INkp2M+siirNw4jrO4nrxXFs8uQbuTkR2ZfpLZUGWlwlgbfPRsy0HRcjn6rYeXgNLUV5xn3j60TV oziYXGjbFuQNfEEKkca3wVAky+omtE6Xq8QlevJe52FmWzOOL08PnpeHwzhe0TetYotYloTkqwHF f3x/id9X69jnCQpGxctX+jWMAOkamj78pZNOBooA25V7CKopAHoZ0+i/xiGPTk6J7rGxJDMx6QrC 8mTdC5nQqS+2t+Fn2U+9oFfN2qBsAOYpSXCx56LbuVRtPtdDZMHkvGldb0qER0DTCcqVs8z5yl7m DvX6saOLUsdxhA9FG481TzorsOXFsf1kJweqjNjhjBHp0e/UbN69yruz80MiObdwT+9L7ux7eabx kMpUL7uRpFFQXMCsPlz38b9un6M3f4zu+HOcll+iTxp2Y4voclWwQwSCbIqfuw4+r00S08QRIiHY Z/qoP83hDhkAB9vkGUODh4vmjpV8fke+C7jO6/6gU55OtCf/Nlxir/Hvv/wmPRx6UX4u22UIz+Yg VU4hRo/2ClPHrdE5YoIzLCNojpbIZuQ0KhKnY7N41njAlECUo9Lx5rhqLys6al7s0XgcH5eP4ifx rAhOWe/FUWwkUbEMCmjFjYYPTXW0aeAoE79Mp7GZX3ndZTeThGiRbLHfPmKU2FXTADVCIz8HoBxT WLc41ANLcmpie9oq9otniV/Hs4y/fquQE6dRQTrWu8lmEjeY5M8xgoOZwfnkz9Ln1QrWE1QHXDbp Qsp/AAvTs+Wnvs8X4AOBXVEtBUxDaEz7W/tT31m+XFiKxWCARMHbONo9RkdEjkWQ3F+hA7hClMk8 NdMvUcTDfBIfHh/iYbFQa8jKHwo/YuJv2100hza6rdlE//HtR3zbbqPlAgF8ApR3uvEwmUpIyv04 gn6zmpf41aS02i5V0m9ZfPKPcMPEylYghVt5l78MXc3iYENDtog2x5NTZhJr5W+VD55OAzfdmWGZ gRoZmCmKQnJc5M3Ohk2Ge06ygdBq25L8OzGy4l7ZbdPWL9r+1fJDsWxnUjiiu7vP/NYEGl/Sp8oR TStnWbR4Lw7hUL8fTlERbMExs9vQnysGu093TlpOSFMr8oFWe5FuGpk4gyvCx04Tf27X8ZfmJS6D h9gTezacqCtXDqT+dsm3Rzgsc8tKvMVMB1FGV/m04aV11PWBrDmv+HPy97D4YQu33etvRURp7Erb lV4vNptN9HZ0Y8OYCU9Cqwppcx3t0twxSM7AF7DKOwDZdJppPqmQYbbFGfSg75qyM8ZVtoxyDX3n bWYr6eqiK4A39YmJ++rwSLdTOhd8+VlkAVfQKZNRidqiSUshbdQVLJF6T0WEQVMgE8CYs2Q3coRw Z6VOhYIFE4DlBgdat6vGgm1mly0fsALC7IEJs6LaJG4HTUFUEY0TmUFADbj0pAGm20XepOXCAJ8z RNLQEPpaOFGwoD9w8E0X5ABYk1xfiINkDbFVygT5Xsk80x5kolwnrQFmMReLTMFLG50+M7rTh5WQ kzawwrRo+5IBLxxBkgRe6KFSXpQcDZudWKAx2WQ++am2RRxcjAbxNB3Hf/mXP8YfPn/QA7rd7oUN vO538j7/9fk13t520WzZTIbAdIwA/fya1Y4nPJW6opQm2iJ4s2TKhJNUpL5PwzbLBJAMHdTWl/Je YQ2SJGVUlX6PTyXx1AAhsU7BBwuXd0lwzEWRc6JGXyv6jc+56EAkbS44U0Y06eQJIc/iJ05U6yMl gqYrAzfLkccnZVE/DLzKw4oumKAGJoFcsUu/h8vo+aCXVeLayuTLwmPXDduoXAfGBMHoHBixEbt5 guMrGXHQWNqLROo8MDa0K1Ks48a5lgK0paUDJ7KYlT+De70kkOOyjr+dvss1Y/fhz3F5/INthxq4 eXRB4JGZR8jBhzxGB1A6xY760e7tfU7BwrwOv3jZl/Tpfjr6Od82q/jl5UVuHMhyeE55nj48Pmrp QyisQifEierEjBZ3PMkAiYh//cMXbaLhEen+94axbptYt/uYnE+xGJrKw2TB8ohnVoJ4sBm+Ox23 TmPjNkXZ4UVj46wFBN8hYRWuo5xWwYBEfqboR3x/fo1f3lZx4T1ZLOL1bRXfXt5iS/eWyougOcAp g85DBYB3FBKsl0XguAr+yDAP+/37cMEWSIRVRj5wZ9j98pYnvm0U6+3W2Yl8rsMxBtMsTkAb/WHs CYrhGg5G0ZWZwEikTp4hwlZsGGASLwbJWkhJUQL30Af59XKK5Xyqa3iE+8bUFB0tzX7++j3+9OWL GfTCuNPWiIJeFsmrk/3URWq8hjgs1yvpJE6I1Wo3eSeqmJDeGI2Q7AjM7YhA5kgnt9/y9FH4g3lX 80EvPj3O4i9fPsWfPn/UDeY1+eX7DyeSMAMz0pyO0Vy7ku9sd000e1ppA6Hy5MrED9mYJAu9k0EL FeKgMy23J17delMiW211PIlByGWTsuQtnmyVbx2ZC0FpAcUB4nOenRoN4Ci+lFjOyhtKbpZ7LJNQ c7mgwFED+ztwD+w2cp0O94j1vPCyBJ5rCVCkxfLIN+BdDHV3ZdU5OlYww1H5b3JOMJlVmxmWH5zI g642sPDt+M1K3T2cYjTuyxUWjSCbqsPxIOa6dX9ewCAILytBmdHtjAHRxQjnyS5EmY29TvylfYs/ xi5G01ns/vW/xvnjH6M7nuhF+fG8UdfAho0DbQSuMuibkChtnscveWspVRo3T9sIQX5HobDZr6Iz eNW15mQm+kt0BmKrZpOYDM8xGyF6xoHAP1+WN1r992I5HsZSLzjPlDd+EDu/rVda5uy1ZfRwPpd9 shcrQCTdSz96jIvqsMsFNpRgruWB9HregjcdKB19vU9QDfCv1zWDbA3AzwZQYuSTIBKImzK9xGJm hzker4CbhqFIq5hgNgLpW8d4x5X7m7I6fubuRHxcN4adkZZWdMWOc/NhLoPFPt23aTEm65quwkg6 HU+TVgRVCS4UW3aIq0AdJMGjRKGguAmgOXld7XQICmQf2euLTlXuthm9xoGwVMqVmW08MwpMvSLB m8RPnz7ofo0lAr/au95v5C3yqr8+7m+BoqIrqF0E60B75sxBRTupW/BmqpJx2BySacaWb7PCddMn GK1ou2vs5jmeiqrw08eH+PS41AX8/raJ591WH8jbuqt8i9j+Ha6neNsCpjcKJnUrDR7lkY3Orjgt 7+1KtH6Vm6VvgNpN2tfiEsFPSea1pSneqlQgaXlX6wGQT1MGLOSf5/XxXe8HedU+38aaYCXbgTJP 6cKahDZW3FRuSdMo9HQ8xuTil8D5dTwkNUZWkGml/RgMr8CKctzUz8651+JRd3i6BqkkoDuq8RJw le/FCU9XQStPB9nfm26hUz8z0WQ2J0G1AXh5LRUHKf8MqBtyfX1v4cwWE9H4eB7rh4eID3+K7mSu Ex3LH9QP4EwEcXJATgeXmFEUeoSSNNHkUoOjCS4dkW38XnXMF5wZ/HtFqUiPJnHoWOYAEiNwprhg MFgmg4iBZaNsV1FCDlSwkIV1OtrAsbKXLi9fE67d8WQOX9khDc/gXqdYtGOLjEtvx8EAVliLKja9 TauDWfguGtwM9y151fWCIBv8C08uYzxl24zuj0UQY5Sp1iwLTE494KuV3lsmfdvGmINvfyBz4aQw CzhfkjFBSQDSkKNsRzgtY2rl/wkiQcGibhpbHDIKJtqsCjYJJrCVnl9J1Y4H8epmTAjpxVYpU2p+ uP+pa1RNoGB2vRl9wohQFI48YDNYhHcMpwhlR8g8kSbD17bkbipYkiGIHMgaO33CFYHtOC4Fq4Id ybzMkgBZKren+PSwjM/LpVrN8z7Z6mqJO/ESb5IX/PThKf76x8/xtJiprfv9bRX//utvNtFTcRsI yJe4mFGhPar1ZKYH06ZWODG3zOb6Nxa9Ysm74GPGagT4paWI3QsY+UzTkPGgiHNsLM2ZMskveUaZ 93fTsNxEpGwYKXawgytxp/CJRJdKU6ctov/ZBcuAmX5t10k7+VbrGvIwdLvn6A/Q2nWj34KTAMDf a50+V/pm3exVMoXlBrxrIs2xV8UsSUO5epc7KSMgAOvhIEO2z08PMZ2MLZkZESVOEIJxJQ3DTB8U uizu8kjDvC0dPfAuUsyVTkl3YTZcJCC1jfVgED+mi4inP8RyPNdqGkuT1XZn4bi2oNY3Ql5Wcxp9 ERPL4I1CTciCfP3BNvK+0O1wEpNeDSl5onHXdtiMJLh5gtew4eVZEP8b8H441LPAr4VIKsoOFBa6 TbZbIj139DNGPXfDmwsZlycVHmSWq/MxVs0+Hkez+BwRD0MkSBlVR8gHnk7J0HfohB04LXIw/44u S0sgQ4dKyNlgqCeRPYWKCPiTIBAWIUWc7amrZ8IporHzKwlkBXfmO9KJqkjIbdVPiDS56GqT46dn hcJ1tqkiYD4dFkx4ng+NzdNZxB6bb0uIVrK1cUMjWGKOjuDuQS9P+oyK0eOXdQSoYYTlFOMoUMF0 IsWCaDWyrALvMiTAX1y/FsyrZcs6dJpWJnJ7SwjWpI0Z7aABbD98PiXxn6K7MtDnai5tlLynIGDi /zyQ/exPHx9jMSPmiM3DJ7WKyjDjRu938bzbxX88v8Xfv//IEAITSXcHXAS2sWEcHZIfl5q6nq1u OXq8osVrfax1sciDYGwDviCtlk8yFa7kSTHiMZNzysqkrWbhUo6reGTnAFaXfaZwrUxUsYGeuxVH 1KemSWt4F3ozMSxvYsyrOHkBylcXmMp+FPbFuCZLN1vlhLyJGNc48ft6OBw2YkBVnyzvS4nIE5nX /2r0U1XxCS6wXdiB8S3dv+zMVIjOuEg28bxax3iKqR1jHbic3SmF9VwpHI4b0x+jB9UgMjgXXRV4 Cc+DhDu8QGBbFPXOKT6eD/HYmcrAjmIjc780xZMDBLmHaAuhsuSIwYjCQXa9fVb8yfsxReyt+5mJ yNqMdaRmOCbGVxbH6pwmeDhx2Ll7ogNY4S7K5KDtp+UmtrEhSbsVhgIBmQOc55uOjzFuMe7HJruW gwKH2zh0rvGjgfF9jcvyKaZ0/BAk0523aBASkCMJgluWZwgv5qmTWlmFqgyiaQ/x99+/xdfdQSlS 0lDibqLnzuRNdXEdA+0ScefmFDyTX8MI7ywMCnoSNtlspwBaCULce7BqbUGdTaCNZXtQwMVgiNOo XSyeHh6VaaBFw9F6Xoi1eHVRoIZPj/rsLB3+9OVjfHvbqqOUFpmtYgL2RzSnnU48jJ0uTecrRQT5 qPmM//PlVYs1DAj+93/5UyzgwMnu+3Sj+3jMxl6mDPROp1jL9MzFyac5THYcDLxmVLS2whg4EdPk TBSHa3xcTmM5H6mSn9gcACBHT8S+359/KFEF87F/fP2hkZAKyvYG0Bm8CzNACg/sXG/CnNbMA1ZK dLgbFAnYuNf0arLFi22eJYW42b3Y+F6ESJHdfApWQnDFhpWTqgtYLkASaJcLaxrYSawt0D+3fmLi ++/6vXRhNrArZnG6g+bTSsFlja0NC1iGfJVadTK7SxPLwSQmnKBazXvLWh1URZbrMDm5y5CsBPxF 1Lj0hPekcPMKKx8sbXnz+kDs03IEfdbaHva8bHQW+OyDcXEI8XO51ub35Cj7TgyLdYrSelnQpAGg E3I4upE9OcGbzoWui00e4Kw2fRUSkYcRJzCHzHRsuonZ452bxpCYMyyKOIB4FpWiPBkpzbikHMiA JAlLGQlFtRYFfcmYzOnB4E4guq5FK2b5t81G3R/FHSM7v/gcyD1pDU+XoeyLe20TK3Ci5hTb00qW xT8tl/FlsYiprJcsWFeaNK+uddPCpbZcb42HvRiOznHu+tCiGEDrISBFInq3Z+mDn4do4qmtuuU0 y0RPymaOP5NrpO8MsD7UuD8buWCpk2+87eawkLV5A7/tpBRp/Rx8rnKq4LlbrVYOg5m6MC7mizgc YaxDOTrHx/k0ZiNb2PTHI93Xyzn5mWYUpgMrdtoDOffCa9PGVkGuB1lFaZt9vcbTwzKmkEQVxmxH CVlvlwC+QijEIBdPCvkCei5uLNsaWuwQ41zZ9sgsJmOl3tC8gRMsSGcdDfWQiCTX68Tb4RA/1vt4 3my1Cj2eT/HPb98kmt5uDvFNAQ1oh4Dv7A8EXuRkEo9meYe8A1byGLrGgVjqnIAON7DJn433jAlo q1a0/zx55feUm7gCR7Nm3EJi1cIXjncz0vMI5kSglNbkKFfpzMW+Kp6L+EpwWBQdZM6Jx4AsXpIW OPaI28ZrhZ0J7o37s33phx3TSro9W/DIG0u/t36Os7rkrsGJy9hX/Ky0uOEzaAki/ov5PfLsTwAb cXd7sjOB3DJhG7M4mVlD6uVKcnzkI2/8zKGjtkcRx0enaAbUqnMymbKDSeOlF8NzJyaM9uBMAlFP wmXAbBQLxZiuri4DHvCKkrLBsVj8O8mtEiOi3VUSEtdnkF2u7hMFArUC3lOOi9OySECz/b4Waati F0ykMQb8AfJFQiZvE9tnbcTv0iuuAS/6hOXRNWLK0mS3k2fbK0uio/Mw2dLRhWOHQg9O38n34SAF 7yWySp7mqDuwQBLuQ+jESaPTbDKN7tsuC5bTdWxylnmWNeVfXejBetjSPc5n7sB1SKJ66Ii/xMhL 11kUFSAWAdzajhv8B+YBQtHyRATaJpccYJ1sDM2X0ig6GKj5kLnBhYBWQyGyrlYQjd8nTWA0IXQf ws8YAwHywWkphjREPdWHf//1dz2jf/7wQVbl5cumcBJUDWWNdHsPI/ov650eSvk8QeGnGpsTGuPe OabDmU5chV7CbeJhmGA32xOYPp9MYzhgu9FRxfyP37/Hv//yNb6ztckwA9jol+e3aPZNNDv4PDxo nknlcKLIpHtclQC2yj9TyIH9sKD1X0mJZoOTDqG2GjFHpPPO0pgaIv0hUdt4ge+dP2hQ3Rwqhi0z tg2U36xB/n/dlnG7NMxT5LnbZunaEEPfIpqyG6nsOVHas/vhxU6PLMYaZeOV3XBzjS1yiP0uRh22 VlAo7JOthULiVWX7InsarybT8dMnrzlkmRKTLqP8mbCGZXjHC3y5M+0tszI+hXPm62UjyY1f2rz2 KuY4TphnpZW+oqMQvrsgqiunM5TZozHFXwNsZxBPxzYm2Xk6tNf4jSgQQ0iKTeKOzsXmWXPnyvPX izNExwqiTYdWXgIlDssM0YnhIlpyP8Tj8cayWlMGBUZfDjlIx2+7g1ja6x3/vHexIr4tXUtY8tRh xD3mRzG+IpBHZjPuWc7G9yWKC7zp19U6vl/XMYfBzTViE8hBnITVX19wC7nG03yi+/Ak9QfdJARi R37RLUvq1qG4ZM4i43eSQ/lLe6QuS4OxkpzBiHXIiC5h2gSjnNQmBLCAiSEfShxNnlcXe9ChRik/ fw4+KDHAJ/xejYBHqC6Yb3qT2sNVlfcTnhWbTUwm1S36XfWIatHzgWVeB77lOJ4eZxo3WV7YGvoa r4dD/PzyqkXeB1Qui2lMByx9Sotrk0Fxy/K95a++XCLl3WPbCi4OrfUUME+rVxvUM3+CDXx8eFC7 SedCZ0DB+5/ff4vf3rbx649nrYRXXBSkLyevkWH6Kj8RDAQWfUo7NF/37OQIaZBihd5Nvz4TjzG/ 7/XO0RPOhlUsxchrU1lOlL0wJymPc1q1DseEigKkNrphYADqfLTtSa1b8lQqS4t/5N+JXJmiYxu7 nTRDmzDojo5RArwChrQ6GukcS2vncqeYqYpySBzIhEZ3CtZRwWmbCFvDaYIU3uuZUybtbOpBTdO9 XAHqgeaT0DIzzitzh+soh9CkZ/BdxfC3Y8DNRz4dKbkHokukrAN84mW98YZODY25MxrXOMdlMY3v kUl/tdEsnp6A7XMTo+sx/s/D95jvcSWY6c+H3Pn783P8t19+E9YB9eBxOYs5+rTU8g3GE6UJ25kV b/JJzOcWR4vvxGZW5El3zyx7GEN02OTYngisD7Dy8kh9Hd0aMpRfnt9kLqn6ybFFFyWzRVwecNw4 x5VNo/hf/BycKHoaP3skTpMUPcaUbxA/VnvlXDLu8v0pTnC0Zgr5RSoUAtK/v61j1xzjeFpoPKLz AuIgnOEcg/j791/tQy9Cb610asvMAZnJR5KbRfz1p0/x158+xhf0f2LBg9E6MZrP3zYHFbbaYstt 5MhzbN4XE4vGQK4rhYAotwvCaOtS5bJAwcooejorJVQz4rc6zoxXpWe8+FuAz7J3wlKGLnCgujGf zYwj7vZ6jxbzqQrt/03Y7KmNR9FG4E0SWmM3WeASb+nd2dcU05etQxdvqV50xLfnAfULpW3MaBAf F4v4+Pgo4zOIcKLvn9v4/XkV//j2HD9/e4uvr9t43ZJ2fLKXNyS8lH1QCO156YdC4Zc8EOoOznE8 HEzu5DQvJbyEmfbakXasRNaZiGsOUqZCp+MnF1EPnaQ0pv3b09pcJDXNasw8BonxjRwnAXHJ86Qi Nzjt0M4EhVLSg5GgZnNte3wyVsvqltbMbEdDMWJnTFSalNmhk+3IlVRx/cXv4/TYf66JAAAgAElE QVRWFBJEQrBhcNUsrpLl0DlUIRKIbsa63DFUmDJDspJ4kl+jUVEHNUJud8/VkdqdNH9PcrPFB0ui LfePA0QWIjKeK5eAEtq6xa/giltBvJxjeT7E9HyIXRKQsT/hb64pXcwlXwhwFmX6AbISDEJnmZIp OvMl2sjuUIC5VRJVRFxoqrvVc5brcuXgpYJBK3uwqsspXrfbWAkENrGYnwlkAcEZiQlZghRnxjbG IfBYx6K5+xL7H0Z59GVxzHP8OJnFmq6NDd9uLy+20+HsQF4ZW54l9UF2Zs+01sz83S7aEV3oNZ73 Tfz2vBKVR6OwNLdWJ+jZouvVqNVLSVQvnhbTeJpPFUIrz7PjVXCNIu0Aq9MtWJzDtt4DrqELQG0O m2O6qoLVzSe2rdGz7w2zLHCiIxGy6BdIvK62ULINj/EzxfcNfF2bY3tbqhCQy722c68/F/+d0fPL FK9/2yVZb2xXkQQ/bocqf1XQM5OoMCouAn21Hly0fszIo0F8WT7El6fHeFguNVIzNj5vt+JK/fs/ fo2fv7/F9/VORE/xMfTEmnBnOQgr785NQ6fWkYsCc5wOJ8W1paszdSDz4Phn+ERs3HDqlLdQmsPy QNpJ+Gb7qtRbSYl0xS2ozFzASlfh4WMGv0etu5NQ8CY3Vd2mO0DTHIy34Iradvxyun75Roq3Ir2T 1frSh/FC8itybC2rKxUcbcu0y3azlFIhTpgqGNKKqUAlziYJTBZytcoudKYRJKbmUqbCpJcri1c5 fhqA50Ei7skjEw9a/WVsxxtNjxgVQ+ZnQTFdOSp7K2rmvlyMBbAmyz+jwXzXM/SiQlMhykoY7bEP 0THRVYvpSOA013+aBzXdKOPCBCZ22i2LdCvnSY/pxXXT01ZyHzBZlgpco25P3Q8j4Opobh+/mmLE i3O94h128CHICyGtJ+EQbJadzyhslqc407kVN5V24kSokzcAL2yx3QlMf9lgpW2sDu0tHb5sqfWw mkfI4Uvo7/fVTlIfNmz8LS8ptJ9ZwNn2WRoHE900Ai0TKOpK70Fp4Z9PYdwfTvrz4adZfO74OXek th4qY05tW8XIT98vitgYrzpvxJl6lJNIZ7U/xuNsHtOxVSvgyLVhl7ZQSwa79QprUtHpqrtaYEiI 9pe0K6gKvb46bCgNLEconHjXE1vGTZXSMekrNko0YdcGjXSCOI32kcwMYzGeOx1FL0En/vj5Uyzn M914Zk6ih1622/jxtolvz+v47dtLbA6NPzCsdrY3cgFAnQ/9wOtJnDPh7XBx4XfF0PpCa9v6cmO0 VOQcx93RmA9+T+lTLiZ7guPMyEqblc1y5immOFUdQDKym8MhZnNcE0cqRqyle5k4K0BePBjblvhv y2Ps22ESJf+nUjz0oJoaUC8/M323c0+9LZZ1vbL2e7dJWtnSKmxCfulO7LGAPBkKok24YODR5eJn vErYhKQ7vIgOI6iCZCz6hrhpY1sFS0Z7ydh3unAKmDWSl06wOGNZHJPLZZNGn3oiKSabHbhAUe8t MVBW9csSW4EUHl0F5ALWs51FUoUFCTKuvNaMLronzSl+/vY9HhZTp7TM+N+h2kvJVegQKFJpM3Pa n4Sj8Apy6XDHtFstuXa2zoHHxtZ/D+Gz04lvq42mgNeNR106oz88kWzTjSsuBlpOeDund43uip+F hAticwfPNqxQGPFsLCmrndZE1vlgEFMO+/FIMi6I1BQNiiTvBZVYzzabUvGOetF2e+qq/v7Lb/G8 3sehdefCXWD0Y0Nr7lUm3VFYWIqcznJFYZNJw0An+LbZWO7Ell+GlY0eJuHOfcwVTRpmlJWmtLr0 JHk6wOV+2PJ+WVaG8mEgou/bbqctIUs36EGb/cZ48pku+SSPLlofP9dNzKbgUX11gTDnX75+s/MG jSAbYk0iBufZiicbO4NAMnS5e/UIiVwLbluB7rh8ou/DF/2nDw8y8qIK8vdiuYiff/yI//H1t/iP Hz8UHkqBQjqDbfJqi5eQHQD4MrSASmyRNs7ETJmpKVTT61KgGMTTHaLfcUaQPGWoFN0r/JBDq3FS 4F0yzAs8VWIPHY58pdILSPmJAPMoeQFrmaVMglXabsayI1lQx5drV05YHnz59GD/oYruUVMvcG7B 5Gypdt5EQK3Ty6OaYqOUIE4cIUouhIoOh3jpJFqNV850UNdm0P/G/XQvou2oR0+l+5zNrvYYJgTJ /tzaqDL+eFxEMlP8G4tuMwKsKBua/z0uVgioxj5tFDOQoEDv7K4cXOuOTkB2dlzC3MBnxkP9HgSr ip4CM9H2r42h/NsHcWaNJ+fNcqh1pyW5ypkDjG2oMb7fgBN2JDGf1GkCTwAVgDkpgaU9SZgtjy4W OaQ5dSK+rlfC3XRS4+umMYbxAavmTnw/bOPraiVPf7oKxLSPkiYZNCckzJvja2w0RrJBO90Si/h8 WKtwRxQ7RUxGejOdZAfdiYuWSL7ySIy+LMaxGI1jM7NelWeDd2Z1cK4gY+/Xt7fYHUfx9W0rjlN0 h+rsNTtgGY6aREaYvo+XwzW6EGp7HuW0LWfSWW9UeBUgki6wdHm9jg0UOXiEkaaelHfEbrVeFrDP lBNJbmjpwbi+5bPF0oBujTHzebWJj4uJlgkf5zNHnAlnNbkbDE00HDrh4yEex3OlWB1ItM4FiNPb kzhdUrSuRdK2t7aszzWMrFPN+H4/iun+r58/aONAGs2HBwIsOzc7FTodfNF/fn6J//H7tzg0mW92 ddy2+xC/5MZpUx6TnQSSG9P2WdP6gt5I5IKnUKm36rh4QNCyUWYFpRUXilEpvZ84QcUDYkS7Gwpr RjG507QDfjYnMFY00DWMexV4l1l+uXlSocp1t8Fpv8AUPD0Mxfkp/PM2RN2N9PTyaz1vuxDdjLQI 9cHACjgdIm8r6gLAa5yz95VZwulBVgUEIiCnrrap1rgZ20qCaxoFmlzvLslEd6+sC4oWpnUbAKus vbewyT/v5vaZvldZxLy49cNmsN20Eb3ALap/M7O7o2n8PIgYdWdxBNJ1Gq/GLcY/+07hHUV0eT/e 3vCKR8JBp7+LB7hV6tgoHvBqD7qXBIfybbXtgpLACczzeIH5Dj6Csy3Btke5HLwdLRcDdyW1hqUR Y4qyN5ValLYlFBwdWt6eyrpXHv8ZjELsGZRR8AulD4GvIfht5GwwHhr3YgkA0LzEYridSCu52R1j MmhiMsDrH5dUlAYOecVuGpY5agcgksI5KSjeDmeiNpt7LKYn+NH3ZdIon8k0uhM1KLmLdPUOPfF9 p2DVtlOeZMWzTPoKXCcUAiXpcghKJwYj483tFP911AunOJ0ocIx6k7iyJcSYUBt52ZhYnsP10/LK Jpmv67UO7tuzmhIysfJZFuART1eXo7asClIhALMeNETxaOXW8Lc//0HUBOZ2RqJnTqQ4CqmH4PfP 17f4sdnFekdb7y5E3BRe5vEojoBsnAYAci3WXbldyow4b7ooAuYnaROfYkjZotJOwl+ZMyNPYooq /ES6sx8gAYrgShSTplEhFWtcGy4Dzrps0mLlNsSwutNmMmNOBoJ60f2+GnepDsM3qmyMxUJnYwKX KN1XS3Jwt6wxIM/ywS89jpg03eBIWUcrKj1B8+oUlbKj7EFfK33e/NwFXov+AHM65SOMI4C2jEH8 306HSbmOPv8N885069wS3oIS0mM5dWkeodOvT/fE18muoVkEs6uy15JfAJFAReb0icpYa6shGxYy HtKd/tIfxKQ7CSJsq7sj0hyyKQdesdqnI/CxSpFxOC3saexpqnjKmrlpo88zMBjoOogziPeXvOlR Suz0nfBlYj1vK2HrNCfzYcxGqAiMURWYDbDk5+ESzWjo8RLlgAJ8/cLRIWFnJLwmXyYI1eBNwsSE LzGyumBxYEG+5d69bbfpBAoAbZLtdXVVnBfdiRUVfAeI2KTkpDmfCMO2t4ahjlUxRNHRsK+En8/L uZ43Jgi+p7bmTB06MSx0rmxK0z3ozBwy49fChRjagpwklJpluouwogvC5iSl9mbajlbATFSsV2LD KpS1jKEMpHyOdxwo5I2tM2RkHH2HLPaStX9OXt7hoC6W50LusjKksEKjgjYoWOo4+T4fnx61Tv/1 bR3P2038+v2HHgbGILGAV/t4QYktY7g7XgNOMZ1OI6ZdE+Ma0lnpaDIpOGPBa2ul7YO2j4BdPiX5 /y4NiRs2txNrmdZ/i1wH0atdT3Xxc2slu+DcFDnV55y5eDsbjjE2AtTLHM2dFn8UBcIaOI+RPaXi AObdhcp2R7h3QryErNTFkFcXx3eocIhcoEtHlSeILF/8plchAZMAvHUYpHlLdF+Me9wIjYIZ56WT JePXIUsqtKNnK1lpz7SdMdm26A4G6j0iF6M+Eelb4XOBdetefC4VtgwyKPmR19TunsQ0xvUxx8jS R96wxhbhurdndMbDwUEYy/V8ivG5jX87baM7PMf2uvTDpu2rT1c9sApDAIS9xqf5WBskXlyiyY9H RmAeYEBfiMw274PysX1902aPhxpyZJnf/fLjVXiHJPIcUmle567aG0FKJwEJ4qNl50irguejxM21 4MgOgK6OLkiZjso68PoekuUCGgaqjtMxvdSsjFCyM1ifsgFGwsHEYcSBFxD7dBS9AWtl2SrLU8q4 o0XvRaqliHBAQfdp1VAsp1OB2PY39wl1bI7Rn3grzqMtfy1wNnHmbPMMgRRCLqOwCLrqtK6xWoN/ efmDhEoNBNQLsjqxxiHsVQ6pXTl48PzSHUqSlo4MVpR0o3c2kx7b5yeCZDR+mjgtFYrwZcbPTlwO NAV2s33BFvl4ivl0rIR2ilS5jND5cd+2x7PuvQoW5K3f9fdbvGz38bbeqlBYMAqohv0Fa8c8lVIy IQ+qMVKZXnRPVFPY57SbiTml+NYbnVya81LId5R4JQiNvZgvljF9mIibwQW9HJFc+IZcoTtQtsvI LiOB7FCQlSHzDe3O4J9bAbDYVDhE4xqNzMus6YJvYi5TNx8Ux0TYLMwtibSOPVMecrnp1lqdhl/i Gn8djGAqQckbamMmvlJeksrM01pAgQB3bpS1ZdleZ1dHRh38GIPmSWxluyqmcgKy2pB6xVzMb3eY Hp/lsvBOz+2xMGPubwkl7jRMDfBsqW5RD+N9CK4tYQ7+abOM8V6GxvazEEszWPbP/ls+XDh+iL3P SwpG0olFvx8fn2aZI0kYxEDAMt09G0F5hEGGVYimuwGb+5En4NmfA/d1vVX3L6fT0SBmg76wVr49 DqME7I4yt1BxXQpbyHFc0XJcaxMq+0PnTdIh8IJaN2kOmnWTBsilCClnT/zMVYQSmjgnIXRku2yl mp8O8gJTV06k3XQSveasIBWRoUXANeiMslMaz1EvBtNJjKc4UTjZyUz+c5r0DZW6DXuTsRfcCa2i koX0meGLwaVCy8d450JtYJ2R0ik30Dok0NCk0ZGZ4OlKUrSXWKecoNQtDkmJ4rsh62GZRtet2Ur3 msGdRgEO1+jjUGnu6pzgk2E5Lit27udVbqdAT7yRYHJgxiK1QklJWRayvV2uxvv/78//jK8v5Pat ZdlRKc3F+cEr/OY8kMS8pPZkXl2ZBqZ5XhYSmbPopAYwsyDX4wZsawSotr2Yj2c3wD6KiZsrVfOJ HJ/ksSs5NyJppiQmM8+kWFGxvJWetIE1/iIyYWIWlAyPM97KyTc8T5pCebQsoGj17/6R/Hl8TrlB ZKS8DO1SZmJ/NRGv7kGafD6Ij/JCcvvsh8Y3xIU2N0GyZzZfTdQKNH08hGxa5bSZ9i65YhfnKwme fqHMG/Imjg1deZNVKk/ZLie/JzerHknTiqbGyLrXZbuTxbl0lClESKnHOYm4cHiu0cQ5Nr1RzHo8 0Jz+FCyAeu4NW2Xb/3YGEWOEsVPSvFlewIty5qXcWrVdg3TaCHYYTPoxueKLD67Eg7zT4gTqAo4f Ym5nuElnaDVBLWccaGusyfLcLNqZdkNHo2dJSw/TFyo92V5nZvmzrKH4iCSL7EtMbFs6KyiDfM7z Wa4J6iiNTAiXwlRvPOrF+MivYdnUy5xBx7axkSwbokHXGNuNgiC2Ucd+dNLXecGDIV9LQDDFM+k1 GAqI6EqRmtBZsd0dqKCVb5wUE6NR7CWF8dIkVYu2ZYaQXHI54ck9OTrYox1bchZtbE6xU8d8EUvk ewAJYD1dHkWSUZ5OlfeY57yvZB82sld1VXRgwiS3Wx1+I6Lg+POkvXStEYxEwfp//ucvJoPlZotE DcVNJ5kSmcCRvcWZ32w0B2wALEMxPPpyDknVS8HSgyYBlrpuup0TsBYBeGabw80VnULbHQOgLYrw to0fCo50NWYE4uL7SDdSrxMgaQi9AqI1ruRNSP4PPZPSQigmSUATPyiN9aPLCHKNIyB2+lnp5qRB oLusq7aSdhFFsuI2m7vGmpYTxxa0/jMEcvNZeH7ZOPK3aBlY05iVz6ZTvLehheSMRxrB+Dm8AMhy eHgRkurXDWLc7YsOwkNfC4HrO/8rNjvoOeU4id00rPWT+TL4Sx2wjRFg745L/B46Y41GdJy26JV2 bmAbZF4Oj3AFz9sumhZfSTkpUre5IKMh2CIvlMm4u55pAJjlQYPoikltzI/QToHDstUeiJJg8m0v TptjLCZTHWI6wFqH3+64fsPqbixL0HiFu2j+O8l9uL7pbjtHVyiRdl8BrmBo5tTZAQGwV4ft3gJu ZTRGE8PrMEYaD62fZWspl43zJRazuVQDEiCj++TgkWeUzRg5gOTbhUCda6uUaB9sHz886BDiM/z9 x6uDVqF8YOXES4zXfN4XJR6nBTKHPQVhcbZnGCJtCoe4Vj3Sm8cKJx3jtiLuIwVqqLSixcIjJDQT HdgKe/UWDlb//uJoNCEtdGca9w2DCD/Tc+NcwJvVS3uK8cUmkrxXKF/InoRGorQjxnR4d+IARgwn EzHfVV8QN59NKYIH8zCDg9cV0ZZD6vl1HeuD7bjBDxfjqTAuQl9VsI64o4mE6Qy9m7ihEnetZhHI boKnH6zCRkTI1A0yb0RlQfOmk2m6pHioWIxuBnQKteEUki6QU8l5g4wSYDfqUvKUcPPqEURCS0Db 5AfJRfLKF/XpVniZMa4Es/kstPwZdc13MKCPtxNFgtk6OwVxoajmJlZqfMzZWfKInjk63qTw6yua 612rmaeUQfyKlH/vYvouiDOBTl3DJDwC8BpEx7qaBJNBjMbYl1BExnrY6HoVgKvIpo6TaYhJm4Ed 2Lb32PRj1yQJtNPoYRBWkvegSKkaGW+kT4+r3v76Ib27ijrFRNFV3CNRGbLTyC0gncXgfI557xT/ 9biOGSvx7oe0V+lGwzbs2qhbBOv0OIo9kTMBCD9lRFnvtnoRiZ3iWUHPtm6gBmzlpSXgHw5Q6jet C6UL3csChuvRU6GxPu/UnOOk7qS21Dw7ubxBZAurHd4chykhHdnR8/0uRFaNJpoS5N11agWqny/H WK23WhS1J/hoZ0Ek4GuIduEhGWKwnhaiJPo7np8Py6XkQRqbs4NTnkLfqTZm+ydnTqk7l3h8XMRi NhNORccMxYhnZDEnFm8pljqHGzwnvKzQA1K0wPkGhU2iKsHllXEP7SSLqwzVYDSTTc0R+RA/W9X2 1ixohM6QCxYbWKJftluNo7gwTCf9mI69KMGd4SibIG/m2fKyIJAXP2M+7znKB+hNGIXKrtnuDODb r+udDiKAY6VVU3syUBWT07Rz5cKYH1PBqtpqFL6SG7J6JwskdgafyYU2u3caNNITjRJsKST2tRyj jO40UrEWZQRp/UCnq4jlMVd0Ywaj7QuVYCoVPgmpAp+hTqiLq5cuXQuqSKRDg6wqEvAF/zDWRIGr EShHXU7f6uR0OjLKJp4ga1s7P2jMSDdWW9CUkV5p2pKPliCqbFjExbJGra5jhRDwwNpc0JHd3Ej+ mxJMlJjtKChe1AbIUjo+WM9dmSPSWs/xgarOeDSI0dFFRvY7GuucqCL/rzwIzP/yZ/aYVEO9ia8C aYXR9e40jtT2VTE3zyafC34OUq9rG/PzPjqnvQqKLGkGvn6q04ikc3zT4KaxLYQ1yU+JRJpRL/Ys ReQoS7GDKuEx7NTFkLDRxpDLDRdrRr4l7iHyGjeOQtcO1WHYn8W55zSbm2ljnh686MJRcjwvRw5J SoizIh5Nm1o0h406NmgFbUuhoqgLn/BYy/jKs6euE7WCPd04mE2yzeg3nutbdFwtNpJW8S52DV0p 2zTejxFyGoDCAeEU2EWD4zUxfmSTN1anSiEZKmPTjhrcQ5F4U1AuRjyurhIWZwakNWMqVjjQcrjJ OTe3hpLvpTpCHMC0JiIarddYkwtG6fHTGYPXxJx4Z9oDVq4ZwGJrEX0OWV4LDEy/d943wj7gb+l9 iBjtD3ahPacfFhsUbpCJk46TLzKdvYQSA0r8xXY09uThD5U1cflXZWFBmGGMy1IZKd45AfOllCg4 N1FO0q0sPD9QjjP0eleWwhpdspuhs+rjwJCFVYEFeAtVuoZPk4yB8INwk8UYd6pQxsrYky+9RLQu bpK7wJtKBwdpuN6RKeUQkKJM2d2mjYlO+xIXJz9K27fEuMR0T8/5sqKRB/7ZXYPYzdmVKfRUflnw VVrrO2Up46DTE221bID78fSwiMXUOKATgIyf8ZDBgMYYsXN6h0WW7CbNBoviYOto/xp56GeRNoE3 mfbFni8raf1+O7v6EOnHsdeNfWcQT+c2po29z9j+WqNntrzGLznY2p9f4Hg34kkmhsYIJZFrIV5a 7sL1pNPn50CD8KjkpGLIrJ9ns3igW5Ljp/E4Fem04i0rTEXPZawah4dcdXlR8nNoISAtqsMhXre7 fLGHcQZwFnYJidamgpokcoHTP5ius1OGIJOCizkdkzz/GYuiI3vmPbwx2R7XhjcPBJoJ+VP5sJHx oHhjPbPwFfrh5RVbNzSBpiH0NX6V+sISN79nxYNkK06xUlxd8iHB5YwfO0JPPmmQrxE71zvuccNC 8wz6RVfLYT0/4Z+Pdz5SnLFCZc4iijnnACeXKwcTDVC+e+JhgVtBVxGlASkbWtNcPNF5wanD6eVK otDeBUtkSSWueKavHZBcRREo34B0uEn2a6bqK42GtjR9xSlK+AnRrvJAEGhamyttNbKDKRGjTh8m Tk4ecBy+FPHX6gKSNgCYJVO4AvI9ZslaRq6XxtuI/+Lh15iV0hsTjHzRpLlCWEzBLBM/VvbpNMDp oOKRwRRpv5feWJ7J6+HhVKOr4bNpDO7YQJ/vA4sZjEaGh3JjyMh1fVcBezJOY7t1vqI346QjMMA6 OzOS7Sk0n81jv4dPdIxfd21M+/14mk6l7+xgaSwBdC/m01HMZg78FJtZ3kR+MbQanozistqIES6R L92Az4dkwvs+GKcyHd8bpPtWk6IED4oVfXnk0zWDkUkmde7EYOwNkax5oxebnp1nF8dtbOny0gts Oh3FZM9q/+T4t3xwxReic4HseLVyn0KNFAz7bHy2ZkMkXFwrM6xR11EIka1QBLX8SDoJI+egd1XH NnxY6PNWWjJfjus6CpKXWArcsUmegENzEN7KFWasHPask+X3jid0EPiWdeLz8iExNdussI0b9x5i uz/qbwVZ4ElOYAP6Qz4r8MesG//HX/8U//3rdwW8KiREcjO23OXT76is5sjGjyWFPegYqWCd82Fg 7f/l86d4nE69EW5ZTEy1tEAOhe6320Wk7efB2Y950LB9oxqrizLBGmvm9b6Jt81WzzG0JayJbDFU nmvWHdoTLrmFkFAGdFdO0eHAkv2QHHYv8bCYyAMPzSVLNW52+bdRSNkKc9PEbkecrlQkfqelRQpG KVqDiZdOkzEZLE/cFNrqxOaEpb1mTZwJOiIKpmUuRUu+VHpYPSKaiuD4ZjAEkSzhqFS7m5Z09kE3 WAdOwAvLmChUjYLDaSsTOXdKmWCargJoFiErOiZdc3hRIN7xthAuMxZUiMQNmzoXXpRaqjt33hiW CErmkIg13Bto9NImBHuSDAIo7I5ioeVCbaYwu1OEOxtB42RNxwCtriGgJj+C+svDnQEIXVwEDocU kHOaHWNzBuDnGowVyAFgTUf1AEaB6kDEVMaYe9oOdjCMB/yzfMsZOflKWju7C5PvfXp31dbUpobG KmsrqM+ONYmeCSvsZQ/Nh0n5kP29epILvfRnse43saRLk6eYyZCV4AyQKnPD1PDZA9xSLm0LxYHC 8gZ1BdimpNa5DODPCxUqCrloJXS8uhcez/g1vLTXvMCd7ti6xnzO5VbBeIx7CEB4mstdcDoQm91y E+yLCfo1X4kgYI+3Dmww6CkXEX5vguBs/45syAZDBTZQZL1xTLJzXGXlTGAG4zyLgZ9/fZHgWF0W jrPnvTh40H2e5qP4y5cn4ZR02LMxhoHevPLPlRmqTlgjLiO531k+CwWJQiGZEPkJG5sXsF3VZ88w jzd82xFOQzJN3pa6tvxOZdjIM0lUl0Nue/G4fNBYreInsXrfgneN8hz4iSGzVImucGqWMV+W8/i8 TBeVDK04TptYNyfZqZNTyvLkkvmSKljSTuUGqDYoVYERgRQm4vSVCmlQAqBuTnIAXGi0CfAGwLYU Ll7EUXt88DihC5vtqF9uVOwZsso/K5Kl7EOgK7gl5c8jqdq6J9uvWI/GatUptmXVe3MIpUDS/qu2 3MdcmwPmmp7NRgL/lYqTw6RdAKR3JEx1IIsd3Yx+a9O1MkZVAmlyaPKFcFEhWdvbF4nEM+6+JC5c H2/cit3kLqUH25gFQ38Q+zgKx9ieDorzkuMnD5IsQkbqVDgRGc0GXT5r/2bdo1V7Em9lLpKbS663 3Nj94R3gwXiS16U2xR4vfTJLLJ5kAXW5GTRbesWCBBjRdv1xrCfT2M0fMs3Z15ZANrhDc8wR5Gd1 zu5IezgXbX1uZEFs9yCVImGxbpUgCY1eBs8sQ8ltJ8ggXK/y3+fgk9khBh6127IAACAASURBVIUi Q1vXqi01967XxjW7Yo9kvg88u16EtBr5xoDhEninEDzpHVaFZUqRDsd3Avksnnou1JW4Y9B9BnPT BpXCw3jsLSJb6YRgA4czed6PB9oAj7XAOgsDepiZT8V356o5kMJbXRZgcK/o+DQVyZP9pM0iPKct hUA8N3IhTxIvK3kqLZyU2i13Dv8NNqiE78s5hiPzGHl+HzEiFLzhTSovM/ADl4eCScsBmx81QHff 0XJCDAHZXZsbyWjPdTU1DjvsazQYKO72Itfy33U0ZFiNChaniHCYbI3tOQV/x3OzU45zjs71voS4 jH34UHODlWhskiRiZrohgXUSZ9kD3hYpiTNpbgZDSYJi3xX2+t7mJK1tFbiQ1AEM0fDb5oto28Wm DvKb3sPEl27wl/2mhFe1d86WU9ANtJezKSdbgZPC1cBWMmILugTXSDKFTLbVciLlFhRMXS+Nm0Xg NFgt0DpHKukR82G1pYxfCgdGQNh011Od03QIh2asz7nv9eNts4tNc4zXAwnA11jyWZO/xZwPUGq1 P8TJkT4vfwYPZGE117x/5/eC59yayfcrRaZ6HvBkyheT+5j2Wjf5j+orWJ9CNhO/yg0oXQD35zRZ xubhp5inyqEnuNIvIh8esTBvJyxnvmdzOgpXI+aL8bmLKF5xVC7q2JBo7IXIKXrLOROfUlakQJGz CpUcCGTClxvKU2O+TWJxF7aVPH9HDjn7hJUli/zKdLhc5SMfuKKCmw4Ic/WhWPhn2RypByeEFhY+ nmbankMNIPPAFsRSTPCZMxaNgozelkAQ8xgzEg78lAVB8gYpktqqdUP5gxyaomTQBbIBbYFz/NnV sQZdtZUmb7ujwonhWf768hKnw97dKAdIakKFj8EnnIxuSyQwpcIcAfOxgmYkxW2Uz4QPV783tMkS TiL4bkH8BduDc4f5QHuJ1w0ypGP89PmjqBc9sg+VeN7RewQNRk2RKFE+DNTHwdWkCWJsVZ5i0hq8 PfJYZwzEnYhCG3iQkRaUZTBbu3NlpBlR0qajwjazMNhDPYWyFZygrixb8ZtRXur8GHWSW6UWUtFi /jkiw+VJXykyPuHS65rfI78lj2IeVzNQhtk/aQYFrhtst9C2lgsqhqTv5EnDw3kmI1BjalIxSCkm rIDNFoxnxba768LrhyIiG2sWB9rs+eZSjBjF2MBI0KnPytze6EaCYfFnirVMsYKfhlPjdOJioe61 H7MJCnm0drtYtZvoXGYxGRwy8hvPp31ssfo5X+PjbBoflwslDNWMq/ubui8vw+6mhO9jlNQXq/Mz mVCaM0aGpIcIgG3No1KRlRuqxylxcLBY6V7jf2uf4zMnSQumYzmLxj0RYBFz8319X7TLEI+pF50p WkNeUBdxvvt1MTM2IrcP84kYU+h0K1VFUh9TEz32JmfOao2jnGhFYs7nnOcenIkviB0KGJGe4hYZ zNTSJ7HJLYMqfSX3piYQXjax5ksSo+WJ+Xa85LzEjNYmWOPt7mQbnmGMBOg0hBvtmujCsM/uTPta ebRlOrmetaEStAG3eWZxhkXgzYKAz8efB1H0TBPBwSVRfsQ/f7zFP37/LnL4rm3i43yiQ5/DqGWZ gGkeG9mxwzuUsMP3ReRMFNowDQIvMNCdHD5B/5kHos7gs99LuT3gUDvgM7DEAIroxGa3VUHWdMX1 47rooHOgL10aW8DVdqMOnK4MEwJDKSkHwyRBtIaqtGqF3ym5czbX6lwnJA8FpEOfcGoZSeXg359N Ii1qwa1VquO46BC3uL90jFLltOzEILdP8rIpVlhDaqNuHKswo1eSCIkl6ZIy1p2RRjpVh1Oqo9LI iVjaD5Xs2DJVmE5QwpXUm9QqWY4V3b4cOkWi4yHsOfnaAaM+lRQaS+wYq+TBUUkgjNh4ojsAlu7M +AEPsjSNPNT8Oxm70Y36Zt86QgU5XOJ1R1hm6Rz9MgjjyG0WoPUPZFSnVmMD/ZHIq5xM6iY74tv8 SnwSLpTwbnK8q22qv2uy07JIqSDJbZPCkTtF6CgtqTWjOHWwJnH8EvVIL5UA9XIk9fjUTD7FYbIw AL/degTLa0fHWinWZnPTbVTzaXlMlsIYdPncRMMjsq+Vfx6YuQjRtaHLk9ninVApnFSOigNda3ku iRh5Ek7zPuNxKHBdfIQMdPASR6nF6ZQLRwrZj5YrgVdWeexz2Pmz8TMVvEs4a7uXf5dKEPcd9nsG xJ4vO+kAbXppWwIoOnbi8GjbXmxDjlYXG58mdZwywSMpXa4PhjOOp2Son9t4OZIheNEB9u1lHd9f cDM9GtwPSJzGybge8LWsRPBBWec7HZwtnH2w41HGKA9JFEsqE2QdYgIJm4IukvBwrC0+hxwjK8Gp Gq7o9tYbpWs/zB+SJuNFX9F5ppOJ8CuWBbaLNvWl0o0MupdjJzcz21ev7AHrEpDNVt+DkltGxkdA P64/wL+kCGlZYR/ilDWkqvtGSE3ypAiNefoUm9ZgaNEETHQrkL/kIRoBRQfgxDTP6GaQl5FOBbWV dUxt/mozpvFPiSapxdPfaYPjKm5b4KtlEAKdE8g/HyIO3RQmK5yD0MmJ/pk/e783XsH1Q3+FvzUF SgcCF/9EsWJD6LQU13N3UjygyHPwBWPDVAVLB5xM7awQ8CaWh/kswzY2KaRwi+CZ4aZs1ZrmINxC L7q0gXZWff+Xgyjq/uefJw6YLaLL3sYvLCk6YulmvmCuzNW+2xxu1Il4AlodL6IZL6LtEEjAdz7c No5IW3jWuFGWy1gyo3snTMZLF050a/X60Y5c6FXS6sDDKQTFRV5PMcNLOpLPol0v+lrIUPAlmePa co+HdjYQQfRsz3rGNcu2TJY1houULIMzoNMggJdjiKEHTknLw2zx69zEJOnepoKOgHhZDiWOyXeG a0aXzvjEEta2R8a/ip/H99sR5jFwvoK1mHWamOjM4SHDgK1tn6EnbLZHOY7S0cvLTGGnDoiFjMrz BSkXyxrAbYqzjhFNNhZMa8yUED5iMZvGXM96L7YHDArtdEpx1KIGxxfdH6/UBItIZxmxP+zlXvH9 bRW9/kiF0vxrJ2SLSzeexuq0VmGm4HE9ebZZDuAskaD7Ow2RCk2t83sxmfBhi3NExerJ94Z/Z42u C4v7J+uxepjdsRB+LwIWfyHXqRmsgFSDm+cOx79GhmnSnLl4SnXOSHDzjoKrgaA1O5EqBIkhCYfw ulEvU4WdujBUMTRfxTYb/uSSAREbntdCD+7NngPsypQMLqKSsmUjYnPBw34Xy8lDTNng9LvxjF2I LHuJXT9pXHRj5PRougt3V8Zaig/GCaxUH4pXjd8J2lIQeMgZWxEA8znHskuhqEZsd1tteklLGfdH 8hHabQ8aQ0kh0WBniM+ynwT4ZeOR8gmbqvn2g4nIGleRWoDcgPvEkbU6mHDz0D27eW0V+ZQ4rXP8 7byKT8GLvYwVv//ci91um2Nl3xweHki6CL5304k2dXPi1ikRm2I1FO7BiIjfFuMVW6k72ZICzrPK dbI/PM/UTb6UvuMFKYh7pIedRQVcOw5PtpAQJrnGE3nD8X3UceCSISNIs6z5uQDWJVHhM/L7hYVJ kmKmtzSJHCJgaEideC+S78UhA46itGZsdXiG2jZeNsc4dE96v0T7Sd4TzzVWy3RLI7CvII5+Y295 dcEc/APx1F62h/ixWum+y3Pr1MZ0AJEWPzC4Wv65JOmAmzFe0s0pc3TIz7bltzC8dLuQJRAH83Km 68H3o8A7Ps3TDZ288gmJNBvcIQ5BCHGNxXziLhK31G4v1rud6gXKAMY/nn26au4tQD3PPhMOv0fE X94XphznE5ZyrpwGUjaSyn9kILnoF4jZXE9x4LRHVpMbMq1tMyBgykOOUh6Dr+RtuZC4/TaDPJno 2dlV9hifBF7WzWUv//fmpJLuB6dKUcnNTsmTmbuRLgjcT1cFSU8EoFJv+9p8EkjASenuEa6/+UvW xsEuv4qd6xDMTNa5YT73tT/8lOrkvDl1wdxKxAs71xIauSKAuUiSlHFgJbpM91HA8hojLTBPP3nF gll1L0b29SrDu0uvjeF4LBfNp9k0Nse9JBM/jmvb8rrjT3cKR5SZMGvcr0bsWwhs5TbmJo1Tut/2 9XOUqM1Iy0mJRrHFMgW3BftLqROBid2JWHZO8efzKka9p2hG/WgZV+Faca1u+kN3tXxFtfr63ox0 9yLDdaVLYGBSKnUfDhM61AycyANJG0gtRLyU4UUqR9fyrOdnlfCX5xAm/PYI98f6zXEfY7+JXmzG IoBzniOsVrYHdyv8OXR64GGMUBQn/tz3NKDCVbX+z0QiHXj5jonhntpAZEQ6VCkKaBCnvTjs6TxN u8Bbi/Qdde7Zpe56fm7Pp6MtitHgHVsFFENTIAyD7l1juTZrRHQNs3tivKV4gg+D0yIlsqe6zQH8 /pe9NtvG69m+XmhUWazcmo2ETXiXOfzpujR5a7FT76qfXw5FeGP/8ftXRZ01SPCueNLj6cMGTEi4 g0qIXtvutDD58vCk9+3w6z9jvz0If3UDUZylksJVPLq6J4qLPZfL/6DCG+RJtPM62Fslf0zZrQ6Z YfnCJkSaQOnORqeQNmvmaTDoSGv2bsukhy65WDq537nQecXubRvV2u4L5dJpl9Jyy1QnIQuVlEPk iykgU1ZPWRATp7v234U2SD9Vrp0OBrD5m9v2kjSAybyu8deGkQuT2ECstqfi9LgwC2fJdN46nSqx pmA0Uz10+zxi5a/TQ6VkHK/92abwQIkgqHHM9w6lO26bdJiVR1vOjybG1gucWGF2H/WwFg9PD2Qu Thi1ZOUCbqWUbqsijDA5xdfjYjdmrLujjYdo4kBMvCLBKCh0ylnchVfWIiQPIbZ43NeWLVPii5n7 1zsZVoAuw1gnPlCOWs4PAEfxeFn2P0V2FjdYt8OVWwC45Ez9mB4HPsxStjJ6RxHQ0uGmYfU74bX/ SeTZbncYfTpXnqOMcbulCiVNh/WrpVveId5w2gzDZTvI/wOHhQDaH7ax2mxT5H6NDrieoAtcEk72 Zr+4UJPY3G16wnfIVpSX+w7qCxs1k4Wd3m05Ed+ba+PDMg/X3MDLPiYxVHn950aXX2NqiyEG7n2l nZfnlvS8vBtjllQ+QOQWknQKDiNsYX7+8RLPu4MaBig5XA/82t+2O42TaBFlLcX3wVBBEWF98yPl ocX4nY6jPGzSf6ULg0HgdydGtrgSkaoVNFDKmCEKvxJ64ctYk8h/L2GpbYeNtxRZUe0nOWenlCyk yr3UaDddFcCksIEyynTnYeeqGiOt06simsiZi4R+o/87vlsElJZnlX5aruxLH6cXRQ+YLWIktUkw GqyNBwBRJw+jDejcurJWbs97jSUVBip5jTo3r6YVtZQFy0Z6XbmZysAvaed2Rc6uKiyeLTIg1wcw WN1PjiMuUK38yilyOBbIwCO/Xy05qgCXjvO9v1VdR1+PpKwkfkc35xHBsiEVD/ZoaevzXoKktT2q /U4bD51WrO63Pm60lhfVn+FA2nSeT/toTk59l+SpyQa5bKNLW5eSIPA4RhcnPPckiKWI8d94sZtO GwOkL8kh08FVHbC6fITr/n6S9+TPhfLAeCh+nUblc1yTwsK1h9DK93cARX1/b0wrRVzcOTmLOE1J 70G6Qdj00N5c5XzhYh9i2kNpuhDfNfQEovCKG33EY6gE3h1z5STPkr3yObY7Dko36ywNlLSM8JsM x8r/tMOgipUkYKI+VIiu74s33J4Q0HwykqENlEJAwSn3FBtbidtcU+8zqgcWctl1UVxlD402sTnF y26nJcfn+cJj44EQWzrCg97Zj0ka13JJUxf5DtbTmmJBwcyC5RviLDqNb4pRt1LdM6PnZo0RqfaH mcvK/vW80/qRt8QZZXchLUk4cl5Q21sck3TYTBdRkfGgGKTxlxjaad1SBE+ddCUdyYJwO58zSVmc EnGMvAI1gG7sjdNFvKbexOBobck0OpRd6zkmfRNS5SEtNN58JXFYBQH5xfHP9fctuVA5VHJDtYWs 9ns0NODMpod1PoSz7MzMg2H8hRfi8aW+83AIKAmW4u4Swh1jDK6P58vGHll4M/VxZDjFdrdPDWfI akYeZtkF1jbQCxF/f+NW2U1i9V84o2x/KAiYwU3iDGHz3Rhwu/CZDC0MjKKcBobzTqui1Q4mse+N Y4sE6Uyqcpr65YuhbofujgLYsWsHPxf3TdmSwEGyMtjeXhQVbb2O8X31FtPJKJ4WCweXaNlC1z5U 90PRwg7mnBy40n+KUKwOCJjDWQJYynAtFBJqUxFbAZOwRPogGBU0FnHvGn02CmU5eQIEcwVu/nFp HCnnVlb6vNj5bqlDyirMM8loJ+b75Wizv7xXvhfWnCrvUR0fmCXGd2BhjuVzl25CLnQNujC+i0TQ mCVmR1j+VLYlT4WHYBp+Pu4N+M+ZikCxU6RYrxefHpbxuFzoOcFVwQehsW0KiANGeB/wL7MI+8wy KovPj81GW2y4gwvE+eNJTDq9OOwO8U8tSRopIn768CGW4LGMuN2QJ9/rahNv+63qjLtgO0qoHtF2 sdWTwprTQavP+xms8qWNUQYnZtclABgGN7a2F+K73NloLa44am8I4IMInyjTElFd8iWAjwM2IxO0 DC+VENsvv+d+n/63vLyanXSqJBs7TxCutjZJad3Fn4rnj4WvttPQIJPYFdwQsb3Td93/O4j+BbwJ CgQ5aRAJPfqaYAmgSBfgFRt7wvcnES8if8mNExD/gpUKvmKmK/AQ2wHD3Up9l0oFkUqe2KbSPGoZ YqLtLdqsy1b2EFdsATIB+v1GClKkm6eMHcuutVSh4CsFvKdFXzoyUlQsUm8E2qJY8LNRhndii0s4 7LxFliys3MfXXrQjmO3z+D7pRjNexoUUZY0a9nqXcwEPKv8OfhMMdKRMSYA1FGALY22P+flD+D/g W5d4mE1jfzrGK4GlLB46PclbEEtDGVAnRdERi58w3zRVLME7ADXnX0Z12fbIOZLqYtMsUl1tJvFY l5d5jhhOzsa3zo0xxkurkrKVVZLHVQVNQIFgmZWTik0kfT9ghm/3B43xgwkHKs+EMxf1zojMzIoA HeUoJuB16ftlKIYx0QUOHE50nNyqarXQDjwJ5MhHwRVkw7upg5Etf/fmykCnROEiOQv9H4c0yxeH ZrABVWqgWPLr/c5MAYHzBHFwvbyo4L23Id9eG+GPw4mcWTbtQUx76sznhe1yKiNTB4vGG19PNQTJ 1dT4XyEUBcYWcFxZaHZLuXdWAsprA5Kq/7Jl0UqcNlMvGN2GUzTMqcImxuXKvjoGTaubUNutedUO DpIZZKdlB0P8vCuiO0HpG70rLYFVB+11jnrdmFBHxQZgmN8nQlsKkvlLZm4CTc3ENwu9/Ik8LgiI Fq7f/09AIt2PHtprR/ygx+U0JpMMoczQR0YpRXj3D9HfdaN7wKakDWBknILYxAinyqZF2Em5eEJg lbjZwD4F1DwuzjRbuLCx44WgwLl7yEPh5rpalrD+juq00guxJDTVtRq7LIeOLGM5AvAduc6iMmQH yzOjg0KFxSt2mGBTnb7D+D5aRG/gDZuuBR2ENIREnaeTrLaSdqGUFjK5S7ItTp1jaZUr2RoAmXuJ pERYXX8kfSdWMr6v53dJRr6PMMbVMGeArailHci/zlJUx5s2LNL7ddEdutujmyEyjC6ca1LcLoPr xkWZQzJW7x0y56JjGMCOr7pPOK0mjYPfxPOgzSlYVjYApvoZhvCo7e0542Unl04Or/D9JeNPJGae fYVNmG4kW2O2vae0k+F5ucBhNCVJVBKFxN7Dcfk+LCfw0KIAsWCQ55lMJq9KdOfAVRFrTmngZ5dZ Gxz42XEyd+ULRBwPTRwuaG9ZQJldsMDZYTxSd+t7bL2raUSuL7X9v3nSycAv14W3TLvsAGqDJrCw 7oaSZnhwDTjaqC49FERWzEIk5wK3qH7oqhkuoz0XIF84NgYZb5U3vossQN7nzsGTAFt4Tl7cjBq3 6Z/bbfki0bGJhMha1M6LkP3chV11GmirxfiCtACzO0YN1ryk2Sp3z7KYG0he2sfSLna6uqFu/bti GC/nY21ceOl2zUEsdskyZCPCeNWJ/spi4W2PBE5O/SbBansSHa/WW5ZcRy8NWAwAb1qJaDQCOE2L ZF3LHN3VsqcHmbmQPhyqXzbptoqUDRu9rS1cz9cW//PiH4lln1gQzH86zdKUspJXBy3IoBOTOMeH 6z4Wl4iX62MsMpNQnxmvc4Wwcs38Mu2PB/GDzLXyeKQ1S47qYubT2dPdqPt2oZMYN1nrXqv7GWRc wuXTxYrfaw2rU8bZ1FkP507B2KCtTvguBtwFK1R6UGIp6tgEdmc02bHRvRYJUxeOoASuiV80N67p W5ZKgdpcKhSUz60Xmn931DhLIUbEbWdQttmwwB0aoo1kOou0ue02ScfLIGZZR9P5na20ai1DKL5I t44Hjbk4qIiSQ4c15Jr4emt7ypYXLHpkjpRdZY0YF7mWZY8TpuztxkDc70Lq7gRQevEmx+OpveTZ al8i1oyGx52u5efHhxjzZnfYAtNxHQRxcI92YJLpHGGLcodeSD2QR0FfG7d3f6UNVW6vfLKkHUGe 2LYXcUfjm9uKRW4VOxIMHs4zK1pGCk4mRIxJ6lRnIssWt64UkEOmoKhYXbsOj8AUrN+TKZ1M/rmD PDC0tSK1mVuCxo5kWkI3+aiSzchB0XwsXnoIcMu5RcjcTH7vHH0UJmL7Q3TAMK6DWMwm8ZHZfYo9 r2+YAHlJDapvcdfjhBuvoDkBtUHabAUeCwiWLMOe7J+GH2I8Gcfgx1uM9i5UBsIz5qs2c7fo+AxU zQQdS4a4kSbpubNyQS9CrQHau4ja9zKL1nvjxZJiJVbiAlYkP0JSR5a9SBPq71zEXft1uZBqfZ/l UFyezjXIDlkOuxHLuXh2hAd4tDdzm5FhOpnGar02/JD0E4mPKaGp7bRUx3w/xXi1rMIpcq2ehS8k 1/DS5waazwdGaMNEe+Krb5EFBFs1HE29AFEno07PxEQVImFxRWJ+5+aheHS/zByIPC8UiqGKDz/3 rIRzKqt8ptSV297G3mi2aOJnIs+iUd3gnNogYjeL3XrH3DhSNEYjU1g0nnn7Kh8q2eX0HBcmkN8d mJ5FFiLprkHnfoKImeJl9vDgqZ3RKB7mi7jA8hdwn1pMNoXCXPvxMDMBmu++xZpGy4s0PqhUJ3nu wxIwGVl0piZiNutpgUKq9yfZ8vTtSnq6xI5rQVdIzFeGuqgwHY52AdFS4xxv+50M/WpCoUzBKQST pZaoYFnQfNcTiteUKTR3mkEGPKYXUo1lXr2D03j+G0LL5+XOLDYumDApTiht6OybZXC7IqX83wsL gHvyOJ0rjBIS3+NiroeTUw7b1NVhJyzhw/Ih/vT5U6w3m1hRsACkZfvadzzZ21qENlpVmOj4Rr3y 6zaNVsEvXbohQjdxNDxprQ38f+3sBO7qJcsHmp+hUAc9kHaqcFeJiqWrAsh3hpDHg4iFB6xjg5kQ 7+hY6Op4IMbxMJvFU9M4oShvziUxHbOcs5hoBGuFD1boRYWl1pauUnKqGN2kUVn4HLDh8bVoIfVX /f5yZ1B2H1s6teZ2N6jk5gJqNaZIZZ9jiLzPurEYduO8mMd6/hgtXVcqFNSB4xBKt4KsZISIeBAj JvC0N/HCpr6TcVCuhgHlzLXMbp7Oid5tgBwLHnPigh6RvKGzGNqMdWFXGuEY6VK2Jea3Dw3nUJrq UMRmed2XXClHS55R7hViYCX/qFgyCnsro/WFqAeJn0lc5O6lHNZ4jumy2LjRKcPMF5TQ6cavLxuN 26YUDZOTSAr0WeRgi5J7t2slOEWcRr+PXIeTrGXA3QziI2Ye5aHPs9tnPM6QYW/sbbDH74GHJuWK 4AmPsXbzsEFgDPsC9k/7Rjik7oHMFAHqk9cnjbHlYRRiuTtgjdw1lnfeg213BMDLORgicI9lCdvu Q6x2R1kGWZJzFu5LZ0/eQu187NKRpmcmRFod762VN3eyNtVDayzCAONde4deyoGaySyXetwrYaQc G0SW4vak1XA6eApvyc2cEkAG/fiyXMQX/KvhZiC0BIwM27di9KZtWHpU9QdDFSPY34vzxLY256vl KmA++oz+phQxket2Rwm4eRn4mXRmnJYf5vO4XmGHU9fT+jdfILXA5QmF3085KyCtGJs4x0Nt3+qu WMlEN4nGELiCDqRuFzeGgNGR/ddZ/5eweHMgAspBCPCpeAkLX0SecaMj3P7nfad0zxrkL8tSvMG7 eXbdPQX+068tVwx4ZniV88/QV9wtpD21vMn8gFV8lFN3rjHuXeND/xJ/6QHoPsSqN9IYx+BHNyjL EAG+Ho9ml5AdiQ875BY5qiY2qq1QmiCCLSmRhmfKWw4nBclGxyt0xbrLMcZ2PaIhaqvpu1i2w3j/ m9zszJzb4uRe771cUtRZDhRJ4DV2ZHqCU6cJN/H6v2ylHdOWWZdJUeH+V3CvSK6Q/0Rm9kQCbIHg mKOaFxZsiO+gggc+JYsnC/Urkflys2XyQXOT7SYGyvOu7aT89a3Vw42V55bP5IxMuuSuQmyZXKCw 0P0amG+jh6eaIcHMHjQ3ju/GCFi0jLIi573Xu6cib5jFC5COCK7Ixi57fOiPet9RicjHTKEsduqV akUTFs89XmiN8F4ObHv2Z8Eq/o82f/xwgDDkI41nVwtNXYjK3tSNmDdLYvKmOLoqPZ2OHAcWE7fL 6p5MgpN8Rz43frFwmeS0xO/n03IR/+Vf/hQP85lbxM021q9veoEpLox/WyQa/X6sD5f4sTnKGYH2 WRFMUsHj9ngQWMeDx8NFF8WNJ3fxcKQjRBpBZWcL4ovi7eVZ5vnQKm6Oo9ldkgrDjdjBKcntJGMt YQDrvdN9xAjXWMfY24txbxhbGOjM4WAIyTqGOUyh/YQLAQZ7vW68wGGI0AAAIABJREFUrlYaJXFm VAe43ccOJ9jUZGYDcUuqkVD8FuBqixtRGfQQ9EUNYBumQI+yvH4nIyw80ae2I8K4Z5brmO1v1rmL s4IR9MAmBUWX5RKz7jn+tdfG/3V6ifUu4ldsmacPMR7T5kNkxXuJh45CAjYSsVzMYt89CGIYjcex 2e1FM+ALcrDIIj0pIIyQSn++Ep3F6twLAw4pgdXn9ClHLCvlu904yHwUabaT91WGclZrcA+c9GOm PN/fHlhOjoKUWy9qJQ35eXAMHXiocCJGrrQmmkkyBMmzETeP78G9H47hM43VveKsYH0rUVbY1vhg 4hmCAqApQc0YL6iTetRE0KlQzMOHF+MW9whMQLmbCuLw4SLMT0Tb0AFI4KvE2PJrI0uQbAC0kZdY TDGXNEXhRG4ijqVEkQ3vKdHyo8c2SbiihenDwTlO6BRPfN5LPA2mujcqY1dG/KsmDK47gmbIuVjc ID/aNbyHh2hQxIht4CWVcFCWAL1LrI5NvOyAV8B7ucFOxXLBKlO5pA44vsobKGZ3DT+FLyXZklNP PllKZnYXQufAaURng+BSoRRsJPDw5mYVya5rNbrcErmRY+wmcPKcKQFkdzrG77+8xWbvF515WZIW TM2IDifuiQ++2ceg+6bRgzmfk6P8fcoBgROLv6vVRndVrHlv2YyByDwuQyf4i/EwVZW6UH4BvHCw k4A/CwGznQbemDMP+e+8pCLTYc4m7Zt99wFGme/hJJHyAwbAdut8sFc1D/3HL48qSHSkz5tNvKy3 im6n6+LPo0doKzpNnUaeskk4rf8t5nx1wHq4k2Fu/tjdSUOcIG2hKrPRXQY0AaWYpLyJF0EBtJ2+ LXuSS/Wpe4q/xUYcs3V3EGsWMuJv2XSQYkSxpkhjg8337myNNzGSsG0SrSaj4PlUWJ3MAX8xjxvZ 9qel6OGGmXSQ5nC6YXmaCCTQ9Ra4jBltj+PiIG1bqSlu+0ePVErhqW25cgRw3bR9iuVB7re5VryY 6F3p6mCXYxc+HxkDGvPuC3M5ymEBe+dldyqqAHF5BFTJRTU5cg50tY86FADZPnOgjUiWHqoDk21w 3rtrPt88Bxxu+CdNJtAZTI5W2Et6exUHT5NPbyCdKsWWaw7HTlmFYw7tDECGAC6fekMYPA9luOJY NeNMuCi8qpiYmwfPjGdVWkCRbt3J6p5hpiCM0qM1h/5itogBrrvQfKgXR8MoHTotaT2ZVC5x2Nqd mPxDrrGe4RuGVRKVZE9b6uBzWJKVJAneO2jTHO6s3dQBpjxC8hheAHlsg1lZIuNsNAtWsRr+sJzJ B/twgPjYjbfdQYb/CDOx8FDXQIsNf04SDrZrzOfpyHABiD0qD42N382ETrwNi13t5KBoiRu7ndOa zVURKLmpOr3fGdEpq1BNpL+r03tcWHTSKrGE/icTnuXwmDbEEGkZW3LDJvtXRrzcHDpcopVYt3AT yzc8ZvDg/fHTYzzOp1rfr3aNRgYEruBt+6tNFwtLfI//FFG0JDTv8a3/hF3lP2u9jUNlZuGVTa/t eownlHbv5omeY9CiH/FT/xx/7p3ivPgcp+lShE3CDGAq+1lyhJmN8y5yvjzDKWJjmH+m0pwl53Bw Bt0vLxPPhj413kiZ4qMR89zqOis2qp8Bo5gp5jPsxGA6bKsGREHIKHlLegwg56++WVPznRUUkbKV kmxR7DUO0z2cPB5pZMswDq31+RySkZhPhOf+6rjPtKRL7APHWDsPeAvcFQDOdaFoAyOwVOlB3cg0 JkfE0f2xcXcxVRoNh2iaJDL2FRVC2Q0S2/kApUtitBaNQr717vYkQxJWmCEwes8N8Jc5pswZoXpk yoMoLYzWktwYz5PHyfUS0/FAHvccGEriyclEUX7bbXr2d2IxGcfDeCC3VaozzwkNEktQ/iC5j+x2 euYltZXho0foenr7d3zWmInU2hoVDBaaz+lYogJ4rbO74zzFJdLDp9PaCRps58RW52RMzAcJz2zY jw/LSTzMHUuFe8HLeqdiBSmQzk7s3JueMJ0ewCD0EHVEFhzzAOOZnaGi7ojywrLJyHBYlav2IrBe 5EfEuI1pBFxIxlUKX3u2SRmjk1N97lFhPJjc1NHQtiLYLte/t/GgOx5qpoDSMxkrJiPaNrdkJu7U SDQGHLV0w9qslxU5d4N4WE7jy9ODgjAfZ228bvfxuhlJ5NrtoL+yt9Z7TOtWwFI0riTsdH+9+Vqb XPcu5srdpGyG3wvT5fNlmsbpfFRnqLFfo27pTq8qWB9HnVgOB/H14XOcRw/RPXejpfuBUPzOkro6 HkYPeHlSIIg7ZM1Y2caQFlSuB/bP8kkrWxYwq9apLnS1Jg5XwK03lxQDCJnc+5LQCDzHGi5Z714c WjMIZuK8TW/L5MIh4N3+UoSOaa2eJ0IrW5QUM2tszKmBmpA8KJwUeGy1pFGhiTjQSTUQrBlN82BN QvIh/53jLOyagdRKigjZ26SpYoskDCmb7zEOF6YX3Q8Sa0ddaKEnSFwNRqUOk429D3bGXnliKVjX m2/FgqX9uK4BbAoRl9MyOlPEvYAqudFAEI6ItQD8+c470CZiz1Lr2OjnfxwN43HSF7OdP3sV0C1M B+FaUcy/va7UYcn95aYvvieU92mF/eA7/LrEqXUC48RwI5fdbD18CsnmOAFoETYZp1Ksq4yykYWO 2KLygD7Np6IN8KUICNjAzzgcFZxI98BDpjQeLFry55ZDw41OkSwLA6k4B4BPXKJzyjCDNHjr90dO IMkiYTsTf0Zr00y3EOcoV+tgWRop8s+0iihJs1kMtCiozVwGbXAJFVV1oyL4mvIAOLMxt40qJCbw 8bN3e4IxvEOSMaGwGpND+cmIYvme+2av7dSH7kQz/u60y6TujFS7CYqN3yiuis8sQ0M+qwuj/Kgq wJSXnG1dkgjFJpeSgSIyENBrLM94mTqP7Cj059FxQLydTGM7m8d6/BRtbyjme6/PuAx+5q4Mmxir 8ukABto+SjbCeIkDJWOWHCnYKpstfrp0otkhW/G158+EuoBBHc8JIwnurBQ7Acda+IDbCVqnZ9C4 w6/jz9aLKuNAHCd4VuxHBWOJh4rRU7kEAvHZGg9NZ3jn1sG1wbxutd3rfnK42AapF2fGTiyfeVlx HEU7t1hq0bPDHiUPPNsd+QCd9oaiNrBw6Qw4Ns3XMrO8I2jF9tYO1Gil3xMzSp0Unfzl3GiEq67G t8vUDu4zxYrtNOM1//F1vRZPkJvBZpBUcVsYGQLSvc9YP492xb2zbpbiAxHVxFA3CkwEpFd3O2a6 axGXbHWIxG/PbxI4f1qM4+NiEhO4eB0K6jjeTni2QU06xorFUwUaJ5ZnIX/x2+iw3olTyzzfgaWe yytQVIUkFf3uJC6iIKgtJel2ZLN6SHVszR7nMz30/D7IYZy4nNqDcV/xQqv1TviG2sIGoJU/727P ixD7rFM2zeEyy5BCI7yDFlKYilt9CpwIZ2r1GRfooHLuv9ma+AG4j0ZOxqkRyb/Wp5/BaGNYYpHn BtVbVI8o8m9XYX0njcn22flybPx8w2/jWTLKyzAvdxf5QoAPKUZUmqpT2FGUZQMPnKLXhv349DC3 WRsLA9jMGpl9Gt7E3fm3ch1zE6vYNDG9u+9cXU3KlYoht1nW/PGw4DaRCTyMdCquzuR76Hbj02gY /cUs/vmwjJcrPkcAsWx7uu9ScnAMsL1JecR7u+Riw3ZLtjnpBupDn3W+X86i1HBH4etJ5A1OkqEm vDywsbdHjz73SCtvQOmG1WHJ/A/qij+bO0vb48hHna5L1i73sfJmU/SOXgGpOVUjznJ8dyBSCAzg +6aCKzFpnK4edS7akoMP8WcRd4Xuk+cfusRQXmHGht0dl9kiW7uCDi7nSwzF/xqIjS9vKrm8piRI ywTjbVxz3kUZ8WkxQ5EeRNNt1ekeDseYTqwhNKBuY0s9D9qsO50ZXldXSycxU4SFyWAxgzCEmbE9 Rp6Tqc/8u/mYieaidBzRYXg3sAfvnKRAQGsMHrZiMdM4E0FJUrgR6oBL3EccvQLd0wHRyRW2FDbN P1ON02RPbgTZJcgmZtSNJUQz4R/GF7joeApxkegumEk5XbBS3h35Z5I6nLXG2l/CS3U+tLIOC1Ao qqqsRzvZZQwM9AukfMfEl4+UdGaCOVSwhEYkZ4o9iwoLr45A8btrQY1EKlJKgH6n7Fe3w8NvIqPG IQWhJr7FJoYbLCa6xcwl+dF1TR6bZD/pRy37XBWFZFsRBpGdVv2ZbEP7qN4ZnXan6ByQ4JA8QoYf L4B1hN42DtThAkZ+Wx9MzyinV9XFzHQE4MyXUOOg3DXojmwp7bzIZK/jqKmRFwyq0QMo6+PEOcz4 dpjpv8xG8ddJLx4mo1hPFtEcr8JijsdLDEemrYhtnRFRnKYKHsgUYWjc3DO+A4edOvjTWQ+18i9F NuT+JOmwkOR08tQLCQsdIBjKhHzNR3oeOUDd+1p7CrVGyjt5nSUZuEsYbxoxi+Rzp40U2KyDR8uA sl0ydmSf9hSXV0Gl498fo9MFUjE+xE+kM+Vgc0hJysfY4g7o9Np4wWZld9DPt+ngNVptIu30eptq ykfs4tyiPqRSOpsi56YAnXEPcJtDAJE4OJavh7sl5yQwFhqKsO2OsVYbciYemptnulSB9QM86fm/ sRpq0/TPEW7oTmnAxa9E7XHY3eoIl0cSoAxzle26RDFXPbO2Qi4pDmnwZ/HVtexKLoMZ/xlCISOy jHgvP/CSP9SNkx+UTPJZ52KpOlJA5ZenR3E8uKi4Jg5uY8ZQH+Z5s5aFBNA03ZRo9gCy2qTRAHNj y1OrSKnms1iLB3CaouW0tr0nFeeJkCmyvNhKGcG2hRRn2V1YS2Ymubs3Oh5OJZHW1FV568Jo4i7L YaLCydCTaR7vCdTnvyM5KicEvi+g781rS6Q8ipJHMIH/yYrm5rMyvos1HW1ky44sWFSljsNokYX4 BaHQduNwOcfhSmR6xHA8iE8sLeaEJ/Si99tr/Pr6ptEikfeb5Ynaeom2iQE3CM0YrAMpqRg85FzT 6XiqUaTPuNb0Y043IHEsEomdMBZ+DoTef/swj3+btjEYD+M0nMRReYj88QeNgHZKMBDNqDCZLexx f9zHeDJzog8EQ7oU+akzPqDd7MWZzdEZagGg7UbpOpLwMGK3JiwyAvLvYNNvL7adrmQkjat64bMC qUsaxKqBhOvwXyWMZ+CDnq/cLLo2pdJA/mYpT0mJD8+kC1ZGxamzYTmBz3769AvktK5TdBAVXucc CqNj+zoaxO9ff8Rvr6/yhkJapLQmtslNq+2fuIzaYJsZfsmOq9srkN8uwDUlKfJOcqeewPXlfHZj tGsRIT1qJmSxQJA1sZcIlfd4Z/gZR9MIntgV7zLPmFQcagRoYs6x3WwFqBeWXcHAQDWrPYGuuDhc owsMc+qKDnK8tNqyEsI7Qnca8CS3XqkLePY15Ic67MWYWJ8R7pafBqESMDQDHniwI0+J+WQQnx+X YrLbgB4+FGyOjkBQxhZFkotp3BM2xd8UMmYIg/l3uN+aL1u2cLGHpMeKhIrDAg+Z3RywfqRvkl4q o5fknkjkkHCioaUre3dlVHwBfrCgpbGyxTAfQ+v5TEDhga+Ieao9U3c5vxtwNxjJKCa5Ea4IFEYg 9bSSLk5PCV+4hCO6qgvf96xUFtpezuhM39bppy2hMtwyMiqVnALKj9gQO+22tq06qXgYE/ika+Xh YKz5uJzFp8eZ0ne4h6zTGZnKgUK/l2JfTQTWPoDLcO6S1Q4X7HH5GH/6/Jek69gyZjabxX67iwMM /s41vr9900P9OJvHdbGMX0a9+PDxMb58/hxv/+3nGM8PMV1GzCe9OG6+OkZ9Mo/9eSL5xWQ8ic9f 5vH6utJYpKi58zFe9tjoLuLpaRa/fXuLwxl5SsR81ond9u/aEFMUJB7mQIT0mB7600knZu1YvmBo E2WciN1M+igRLkGRf+NZTAB/wSibCU6inYizk/y5mqnrUEq4QSADY5wMAB0jL3UGnCjuIQES2A8D +JOIw3AACE8hwqRuNo65ihjUoXM8r7ayM4ZX2J1ACejFNcNNFLKiLZ+7fDoc8ek6ITrQ03ymrknd 7miijbq7UI9gKlb4r49G0UJmzqmCDooNH2MetkeMl6dhNy7gfxLJ+93gmdw3yNa4Zsav+L+/v200 vrGRZfjQBNQYUJ9SR7oQYHdKv4HK8H21i3/8eJF9ON0wvMARlKghbq5kJe5j0DeJmHvXHGlmknUg aynDLfKWy9vSH428jueJHp39IJBGC/LPzTLBrhPjcV+JGazV37ZOjz0efBEVXZV6IydBe5Th1EOD hZdyOak4yebObL751imCyi+hgg84JS/ukLRhUztmXom6I3UQcdtqNAC13Pw0H5RTwNUhkTKHEzBO F+ZkXFi+drZkXMwwAWQOaq0R6g5zg3XfjHocMy+I72trqIpmMpmxz/fDnJBZXGGgbDT90lDQKUQK UC18RsCiJRCiUqTQVt5aWAbz/7qQPyuGy6Z3jBxsQvcHbvI5/vCwUOeDyd3zFpmHDwdutFKD8uT8 /7h6s21H0uRKzwB3OMYzRURGZjGZrBZFNnUhrX7/d9CldKGbblJVrMohzoTR4XCH9/r2th8npOzO RTIy4gTg/g9m2/YwRYrBYZ0TQY20IY0ul4obf3x60t+93x/iafMYj+uHOJ/bOJ5O8enxUb5Q2J38 bz89RrVcx+LhU8zXdzGpvsXj00YXyevrcyyalfC26Yzo9CruH+7i09NjrNab+PWPXXQ9xFcSh5bx 9se3GKZjrB/QIA7x5aGJ1YLL6xS7ZhE9BMUBXITAj0YHlsby6YwhvyhAeyRUVLMX86fY+B08HgYX VDdEV8lbbGHsKt03RBC9+SykaWURGWuQ8hGC4viq/H0w8bkcU7TONSatp1+oAP/9/pjOtxw2Cx1k jO3//vwikFmdgRb4ELO06hahukjY+PvpXqjkZpX0tXQ/Bd4oWYr86/a91nRZ5NibNU4J8C1EY9a4 4+D159JVtAi8RcMgbFUVO3DILJ7fdypAOJz52bSATiiqBOxzNkgX3JEeBYDexe+7QzwfTtEL6x1j Kc7fIi6nc3zbn+J5f4qWwcbpKNsZTUlzuGUxv0NZ18j0lgwNImo2bonDooz/vNnED0/3HlUmEZSN ToUGi5dgRG4HPlR3MnYg0/lZY7V5MZJhQwujKBq3BC5VJZXePEfF6vczIxD7ZLRe2uh+MFqY6t9d NWiSkxWQythkntue4xbxYwxJ8UhULA5eRZCspBCEmCm5UNReOojyMxBV29mh2BS7vbHbKlXnQuCy w2JzPK7k4dupfBuzihku6xQ/v8ILuw0wBOi6pHd7VgB4T5SKcJnPWDATplF8D54HLHJG1F8e72Le 3Ct37t//IECzVYs5HTMhKNu5urSDsg5iuJEaPeX8DQp94B2d9ic5HFB1suB4Wj9++RIXHE7bXfz5 vok3gFjkKMFlgUofDKwR3qaBjIII7D0Op0fRWlSqeuZQEGCLN3G5QtKkKsaSxuxzyX8GxM7w9DCK RMRrUTAbg89aLFxESk72O7IdhivS6+X7YdOyZvCUIniBDWfNbA4RpB30pNzC/myMbq6fPnDSzMR4 pGg1aW9UquR8p4uGd1dHD2/uQJyXBfto+dj0v75s47ftVtYvqs40yQTrsWrEdkjFKogDlf9m1w4C ZAvHSZ3rzFY5VGOsabAtpvDsZfmyl6m/nCg/DAJZ14D25cAqjiTC6hSi7KBXBaJeqZZ2yYS3zTmZ jHReQEBcAFR1dFwylOz6+GN3iJfDMe1olBUeA7QmhmVHDqtjvGMSQDd22MuFVDrdDIjV3lEriM7R /+rXHjLYgNLzbrGMf/zxiyj7vAcsQBD8nFpHXR8VIY2DJoGZgJtuGYcKjpPtMZgsgk9pKlIsVZNO II8lvrTwh0xdZtPIuTB5YOM0Dme0hxjjLWOpqZWJal0yyXsATw4IZRKmjzae4otlLmA4LW5tFF6q g8CYlCaZMhqzAb4nPJkLl1mD2NYyMreHu8WhvHCbsvHlbf98JB/wZD6XFkI6ONq/x95L4BlMQcHO AFmLpcn3THSD/WW9ZPpQ5jIqBl5gqgFJDlmy3+j7tSmsvFEL/+PjXfzy4xctxP/4/VkXC5l8vA+T KQdpu2weSHXyHSFXn72L15c3u0/OqaPG+O233+P97U3vYnZ9iPmMHsqj8L/+/hzn+SW+/jiN7Xav 6RDukkhvrsedhidUWnfrRbw8v8V+d4yvPzxJbkMLgmNq113j/v4hvnx5lKPG3/7zGM8vz/GwrOMf f1hm7qWTj5vl8ubq4cfoMM4RzJB33qNBnLoVapo4oudUi2iZUEMi+cSkXfvHO6yBtolW3URWpqEZ WS/Q/cOwhP9DOYIZcBK3g8NdAAfghkj2zDy8xjHe3n1g8jnP14i/fnuL//7rr7Ef+6g4IMH+UlPn C9xVjoYFyYdEVytDzMpYk0wJs8JnG8m+u6njDg7fGgpDbX5Z2pW7GvPh7cv5Yo9+aBg377uJXITl rTjO4uEO+Gce33b7eH5+0YG1oqKm85AzRHGnJauQ8A4b8XFB47jwdjqJMLpZrtLKiLU2jUMPobaL d8B82XpfxVED06IrZ72IW3a9amjAQQX9BOcOHVj/+svPBrglvbjK+YAMMf4G4nVgdIv3opEvBDQT OotY2X5ZcmsyPwQLjIabbqnT2CQ+W6NY/oDCPfvftB0WkVJtEp/h4iQUqhstAgBhs9HBp5ggSNCs 0tViTdluKF3EOBP8IQIZxY3Kw4zWSOLs9PiaTe2MKF6OAlAVW61bg7+baZOSiBVnZlmS/J2QCHXl 5Vt1r+mb7agy5WUajQ5Tbo+zHBolf1DMWDEJzARtxthaoHxGi7c1mVR8VWIq9vtJg8NRlwHX0LGl lMf/fSpsYbbFSucST5uNLgmmZjhH8FxUqfEv3SpyD3hnYGtsGtHq0klDgGgXb9t3YWGfPz/Fp8eH 2L6/x9100IX1PkziffEY9V0b4wRhLZcQbpyYv0Xsti/RnrZRT9dxP29itdzEw/1G1eDrOxymiM9P m3h63Kju/+///pebMPcffnyI1zd7VW3PcteLu/XGoZ5i8JeUJAu8NYQQUZMDmJba1i4A4Iza+X5D N5gmIi/yazwwOJIHlzw7DZDnpFCGccX+WWJnE2klR4N3BqaUFi4SeaemFO7b6dTJRZNoLTBCaDen +7XWFJXGy+49Xk6HOIkjV4nab98qWiZcQxHGM+mEtc+6ZSJq9wlwxlrk3dTmSudpJQn7kIpWh8d6 fcOKpzi+okdNrFT2TGdgkyruNmCAJerOpGyhsRmozDQPAz+KFtYKF5i95Lj0G1WxnsDz6FlHpeMZ Y7wM8WVzF1/vp+kAMpfUjnTy/e4kzFvhu1hT2djnps/VADB9yRjI8L0UQpFlV600jOQLge7v1VPn Jte0DsDbZv0ilcnG1huITS5WNBu7SkOx4n2UVYjHqfbkNsBcUmdSwJtmci5ZXW4vqplM8Ln9+PXi Pgnwyq+hSXOLUyRE6ZhY9ICZC6dIen5+WmBYlW5O1fcqe9pZgZCpw7OHVEao60vY28gtXB1DU/AK 4x9a3BmAKda4boSQkLk4jxbLZrdfxkbcLnoKqVQhVUJJ2yg5DDqoir0L1ZDH03DbzinjmYxNvO5a 8bJUQS7xtJrFl/t7xYCJQpHul0SzcYFMLiWAI5nv1TTuH+6jG87x8v4SL28v8en+Xjo5aTUnq5gt VrFqRmkF/zhmpd1YzvH56T6m4zEup210x5cYB6yPfSABqA6Dx+d3a8z3gB+wG3lJOgIbciYQmO/g A8TriwOE5yMemljhzr2zw0P6+tO2y54HQuqgqdTu7KFQsV/m4MFfnIrL8qxRQx42hVj+aR6pCy9l Td73JlQq5Vki6PJicFTwmuT9ADIDE6yyCqZK59lzn3HYov3b9u8CFTE/hC/FupdxXs1F0wgo53va VC8nmWmNw++pOORKsO6QlxDDF0lu4Fst9Lzbs4mtrEV7ppn+gcGhYIK0pikSO2lH8/AXnUiWRs6f BE5x0pBzCvC35+d2F37NJPHCAZN0DUgFOyXSc1j3l4sshcAdUcts3/bRVkyuzaMDd7YNN4UPQHvS nOSZ546IQ9JxgxH18879IyU3f0jTCBlwzeJhtdHDsnd0impzhK+bjgnT1Cp/Rq1Fh8cXpo3i0BpH gM8+TlRG2fIU4qeqjATNC5teDp/gEZoMmL1cmOK2ZE1tno+cWzIxC+BKqKUAdk/g+Esk8xFXLLQp lHGXFjoirKr6mH5EYXEgCISnDvQhYdkSv5fNSYw7tjkMFmxzoslaqtmhfLD5GTgw9bCqJMfGOqx8 YFEUcDsXljltIE7MYuPnMypSiKK+kLhCNAO3NQqIFTY2xPtA1BO0hzEeNiT0LrQJnu42eifgKADn vPcjerjUf3ZwlHTA9+LW/fb8LX779rc4HQ/RVEMsL68xv3Yxny/jWk9iOV9G01/i73+85uABztZE B9Hh7RDH3e8xtIcMYoDx3sZp78qag/TTw0ZtbLv7I3bHF1WKzd2fopn00e638fb27s1GUFAPV+8k vy0uFRk5yr7IgwuqXVfqngzj3MFkGMwFGsi0672h+JeKB9uf/hLvXafpNdIgcCiB9bJO8ro4kLn5 vV/YzQbZIl4OKNpsBO7FK00XVrZxIh+L7Q7Az+ZDHzmPv7fHWKyaWHSzGN7JPuTPM/Gext16LiUI h4H9unwwSZ6G6F6V+Wh5mjyjTKXws6pl2cPfwXuGPqSLuxlV7emiY4KMEy7YVIYme55UDg4D+D58 qVAvSrwp1kYc7MjhCjkXUndJJyo5hbL0nk7jfjlXFUrG4Ptuq0sFXFOOtUw864n2mQNAOhVMGP3x 2aDeFO6jD0NfmLLQZg9gdKcpgvp0G7QJM+CQkWWEJ1IFxHZudZ7bAAAgAElEQVTvzsDOeiWU4Nzm 8CiM9dA2uf1xrlklUlsLEMqfZ2KYlZYZrB67Wz8IM9kOCm6BXBIrIVqcGA6zTD+Ru2mjRcPv14nN 90COIjwq9VBXm8wtcY3A2lbA7EQuEJJAyG3CJbtTdCiJfXk7YsttJi4SiFB5ofx3JlEeFwPkGyyU tKGqYkv5e8ClIKXhWS4Vxrh0lTCBiaxaMI30LS3gP503nWRE5Dw0BzIeTey0E+k1Ko25lRbqdj5Z 2vz9eHqVbDie9dP9nYDYh8VcXJq6tXkJuA1SC37f69tz/D/D/x3vu50CRGEp9/v/jOXzb3HfvsXz 7D66P/2v0S9WauXvZ7N4PR/j978d4i//o9XtXtGvXztZBXFZXI7b2EN/YWIIfLDr4z+/tXGHZGX7 FvvDTm3MPc/39E0HT8NmpQXo+ti3e6n5GUeZLApNYBZT7JBlP3RU9Sa7GZwvcvgBZ+dCunPXKkiB 9fnpzoEHPBsCRw9UA7wH2NoTxvJLs/yvQ+xa3l1aHpcKPqdrlmpCml7ZGE/uBNbRoe4gGIOLn/bw PPbx7X2n7oIEpTOK8AqWPa2QqytNAoVf8fmhGvgidxKztX5ilac9+FVUBvll6L3bbcOgOfuFcJJi OkA34CPJmKrhBXPjVqu5DkprDFlGg/Yp/EU6hxZC8v6gZGYuSA4+B7LaxIDPxkFKcQAp/PFqUz4q w+XMFXIrLKUSz4x9xb77p59/ir/vd6p2u+/2RNEslgJGYbLIqfD0Am5YrZLWYFprCW/x10tPIaqK 4nfFf9O0K1nmAo8VF88mThElTOkMf4QQxqjawQYehQrYTaV6ERUXrV8AcufUwTeo+WPoAe2ImQ9V xMxC8DNoTv14s/u1iintcIwPiWmdwk6V/+BUWZWZ42JdGdIYJomsGNkRiyRootsExbx8l6jewPfc QovFm/Y6bAy4KvtDKy0dt6CmPBpkWsgKhkVwBQzxH9hEjRcaN1qxQ9DzUdn2cSgWJwq3ieZ1yVwx b2ENLSRbov3iGcIZ62M/nlWp3q8XAjGJDUe3ucUZ43hW1SLHi+4SL2/Plmtgyge7+PgcA4fD/ZeY TBfR9W1cj26du2EiSxRuUTZJd97LDoVqiKHGKHfLPvrzwVKakwcNPM/99iWOcHXOZ029Lu0++vbg A4dACoWDDHG9gL+5eiqDAlpE32cmZc6SbiBEVJIbj9mJurpelzedHGuESmpRwQ9kkoV54yV26ciw vnraJiNG8CiFx/q7FvtmqABqM0H/Dq0GOUzluHSYPq6atWyulWjNhZ/W357sIk0xWK9KJLmOaO+o JGgn95NzXGfYOVPFwM1K07z0n7/mcEdWTiwPDZpmN6WAMgfz4pOHF9QF5DFcZHLEgEJgUqcwVTDM vGSZ4vJ9Wd9ctr++7eL3t63WHLbZGO7JNPFmYU3VZzNHFQbK66Sl7/RrlxE95jQe1ovYns8WMmcL LseJ5AM6YPfDEPQ7mf6N3lFoJjqwiEniZbPY4UzJPK3gvBKvfqQvewTvKdfNNymV1ppeyRE0gxkh 0mVkl6QEcrWsoicb8Hsb37T74Gdw2DkGyXoqCg7xkdg8pk27JcoRvf2n0uhfvkj871nVpEWInAHq VKPnyBhCHwcIwGKL6+VoLReHVXGvVPmfNiX82eK6yJ+R3KYk32oB++Hy98L/Qb5Qgj7837xRl0s2 Xpjrtl7qEJFbhZTqNLnFQSBdFuQGYXDePlBpUJc3uomvH/w2j9aTea9KED9t2z2bb1Xp0ALLYxFu lp0+7wt8mfdd7A67YAj443SIfxnP8UPXx+LhT3HdPGmCA68HAbIcEXoqVCx6+uTuUGlUMRBBxtQt E4q4ia99m7gE1cRcF49u6rnBbzzNHDYKeG/4Vwc961IVu43rOCwKJ04cs4ymFy+OCSzAPfY0cifw Qmdjwg0Sr4fPMIYuxaatYkul1XXGrDqTfLlU+Cx8P9a2fbbc9mPbKztmrbVOhwxtLptBk2eGOFOv DZsslsbbqgPeoWyPqYZ1WM1s5DeZajg1yckhrbloDSmidyJ36goVIuHKg41K21/CMfi5GmZqypZu qS2+7Rkrz8VL1oLWr90gZrVKLv3vAOOQRaEc/PG+lfkiz1M2NQrzLRF1iWfhqYUBZYYlK40cm3K1 jYOnldOVfdxyb0onzIEKniqxQNnLHxPzonopYnH2QsmeqPkLreVxkqzdCjL4FJJcKu7l55+WuywQ tWzpI+QJb6WHLo92cBLJIBA9m9S3mi+coluXyVrhN7HIPf1SLPrVHBzt1w5dkR88Cwn/dG4VjZYl gM22h5YgU4pLcIKikQAmhXuZMSteF6WaxrJ1LGZddJAoJxGrhW08MOWzQ4AxC8dredFIONoRV2Tb EIOubif5vpdLJ90f36VowPjDakkbIsntCMCBdbcCRPaz40Ve+LtpR2mJYFhTVmcSs4zpoAoX7ywq CQWp2tCfqqhUAr6VPKIX0N7lOxEB1Yfn5/s7AcKf70a3iNOJbEBexzF+XFTxb/Up/lv/Fsv4Eufl Io53TwQhxuX8/mHjrBvfMpAl43EOfW7x8SrcYr0GoJ+r5WLyC+6i9x32deei5Hnz3UxuNMhpWMWB EXVlf3KcODkEeXdQaayru6o6hbzJP3iqWQ9nXZzjw6h+PcEjiZh1yXODyvN4v9Ho/RmcZX9UdYIb JvtA00HRPVzNizqRuX6YzsFV4x3jgisvXdrQiixGh5fIYlneULOYHNqcbNqdlyqdFh83WtpblgAx WBQdNPK9Eo5vWUfeeNJ/GmQvHQ/WMmLi47XOQZEWNeBYxeOKL8yUWGZ988axdrmHcV+V0uGW0cAa OKu6ej3gDkp+oAdkthu3Gy1kZtYwh62cSQHU6WRyYEExwmRWlzx8xiRa43fPvn/fd6YaMVDh0OKi VpFgkwFVfTlNp/KTgwrdRNESwmYtdrQGt02mvE7r6LInLX45JZpadiwK+XG5rQNPgLfJbvzfqK/P F3NF5MF+TWfPxTTGEx5LlE8cRBEUv3pZwzWO8gWyplEj1xRklhZQk4e0HBHQmtbMRddl90k7Bcic bmJTMd+4nk5KWHnttcGqNdwes/mZ49XRiOGrQ67YbCRPjcqMTcBiZfPLSVQyBstpHFufDg/iinlq R6QYLHSCNThISpSYCIDZ4umvTwNEy2lMHeEVylkz9ZMeevizMQllozE8MM7hw014TyYRy3lY7O9e oCu/VzYlEBknk3har4XnIUhfTq7xb+ff4p+ve5kL7j//Eod6IWKf7KlpddP9FLxFnLuULfWSC6FM mMQKv3oA6fQ1m4nh7RtdgaU3/aTjyagAuEBmSJqEf1psLxInnColtaBnvMS1LjHr0AhOpsAgUXr6 lO/Kad58R1UYSgNqopL7pSsaHBQ40GjnEPBu5jPJRMgC4F1yGCtOLVO64Uqxe1lbGsWP2CVNZX8M SEzFzUEO3eSD9DkFrtKBi5SK8b3Si1VlJsxyy7BkgILv1jUQSUBMNnk46SZKY068V8x33EZ7Y7V5 YcornUsuuWGCaEQ1WdvWKCCtdvpuVoJg45O6yfS6X66XktqI3JwuGp5IGicV5UEOtmp9PP2Wlzxu psa6qMg4OD1ZdZv+ebPWM6OifTly3tjKSCdVBjOrJVThxDNOShGSqq1xTlk2a2/cBI+Z/pE+07aj ITDTmxQ+hI0IXNJCDitcJD6wCXejeB8CjFNX6AMOACrLYlU0AMMAcTkyzehtfnZXnBBEDPWhJRwj Y6jGM3IDHqB5XSy+ktpcgl454fGBKmZ/IoCqnf1gaMruVy2EOVNUR6qiGqgF1U2k6igkM25LOY7Z IOUylQ3godjmkuJkKIe81n04rpbwiOYSh1JZ2bbGMWEaQmTyyMNqeXNhvOVAfpeKw+ctRFNzbHwD a5qacgraXw5D+TyVSyKBePuwZ4puYiwcAs4LrOOXp3X8fP4Wvwxd3M9WcXr6KfarpzhcJ7Hv2MxO 8S00CKgnVCvyj08fdNfk6TxJe5+ZlQ7itWCYTEuqYwXFaunZB0oDg5QQFfa3wGO1vz4US1in3Tpy 3cpd1otduj+qUllZg9kYhGekfh3TpymVBbwvvgeZgIJBdCnBUsd/zCRfNrcOjnTbLanO9hPDbNAD I/tGEVraRyM81NCGIuG4GDQQygCJFKerS1A+YfrM5WFbbJq/t72WCiXdQvhHgwSpCApeVYJyi2NI ZvbkoIz/qki7I2zyrH4SxE+BqanM1URDGNZ2IYHewmYzmb1I30Rovpk5pholu6+SmVlcLiwP4x1S LWOG6PfAjSA7HFVWrgD4VBBvIajyTpfNQgcW75Z/ajyqlJAiMHziEq08YPpRJX0kLpLj9uKb5Tgg 9UvaGLZRdU/KCS8LCk0WMmWFD1NRXbj0I3TUtisO3ZQnvA4621GwGrgFXSIWn57EvGRR3Kkc1XQi k33K1KFQLArX6ePA+vCJ4vQvVrRgY8aEEhwHg6EMHewgoU3kGjyGCeQ3i0Mluk2TOIYOxXVS4b7D JdZLW/066svtiqaeeSnYr2riKRp4BCr5Du+mvHVyWRXWs/4p4/biTUY7eSUINrVlydhmQdNCyw5I XDRjOkzKkIWAX1FBP66W8XlZx3xdx0P9EOPiLvaf/ilOU9wQsGU2DUAumPiW4coh0Bjveygc9iVn ElvxPTUBc6q1LjStLV9KVh4UubcHKfwvGl0Xa91io5IW1WqL8RkXUdn4kNsjR9rTXqgiStqDLx6w WT9bJVTzqWjJsDU5I5R2/Lzam9ksLjMfuIt5xPoChmVJl+guya3ylNDvQKx4pn0pteKAa4Sj5WWF 4yhxWOyB+UzfWyRLnRGs805xaOgHVUmmhrTgkGWtirmSfmt1HjL636UUMQ2jyIPsSmoipg8tKxj4 mV2+dw5QYYlZrbFmZC5wBR44y/WXdynzvfwZqpTljefqh58NedQX71X5gRzqwqUS977Zv+UwjHMB jhzSJAjVHrxZHWBnD3vo64DOIodLSyaDc1frOrDWq3Vc9iUTjSrKxvEcNjgKqDdVak3aqkikq4+S shvzjwoFwfKCTNRV7pnLX/FWdPOSVzaX+T4P6oiViIzBbL3Kr0IaheAoBmwytBnvn3pK2g+/JFlY XBiOenrDIWM/ci9mDo8SrSVMQliCW6VyK1hMbBkA//BQ+0z+IETSRmZ9vGAyxkaa1vEGQL09xgl7 DIGw/ru1iAHVlzYzRChM66dWWJ/LmJUmLYCtdR2vu30c25NaML2oGbbE0DfwOupvYGNZPPIkEwPf QQHmCHnBW1NuoFYkQw4o5DhQP3D6jEk8owMl5n0yVSrPcD7FPz2u4/HLfUy//hLt7J+jn86i5RnA z8NqmlYljQmnt4kn++mqqdLz+z7e3l/iy9N9LJt7VULOAfgQJxORrg3GYKMkTrOhcP+0ktmpxyIV e20xtVKit56tHTN532Aq/FkWM+CPPKvk3dTq8BFbHO0ZA56ceotmcencup2O6YlmIJykqHHSmiQK 8RGxbTpdFm5iobkII1IlwSYnuoqUI9sAy8Z5RSfgFOTX/U5wiH3QIlbwiljPalmv0VW29eEVU6Fq WD9pNJUu4aV2IyqXb1hLm7nGqkqxOCIqjOr8jOGeAz7E75virMLQw22raXsfEetKT89C4dQP8ddv L/G6dxiG7n/tP18msp0SudkH1hLNaUCj8P7jIVuAXavzkK1O8hsb6DS7Q3zbHbVe6rmn9+oUhNOW jsFr3xbMTNlxbzX73pQfOY5SLvpG0Vg/k43VuqU7pb5Qgs8VDgo+PJ2gCycpXUIlgJYPBGVd/kWD p3CGiPxBlTWWxl4xXWQWYMpTZIVjyYRu4XKDndv4tn+P2XwpUabyDXnZgMsit46aYukg1W1lAzht K8kr/DBvgmNYtd9XizkW5oHizElLyxLmMIYEh5gTszUOMoUyYMuc5E+7SFYfolBxVSKqhiBLuGIM Ehztbja9p3j0/fvTIQ7tKWazO313s+ytLYPlycFuKxtPzmQNDdubTZOtn/zLNWJGA7jQgUt7yKoe GVfDq8mQA7A7opfALcE0EBhPXn6L1fnvsbq/j+GHX+JSVdGiuD/hynESMA/rWRVyYz92JQaDV1wn MWGRRhW7yzVWl2t84gAQg9oXl0b3ksJ4SGLZ+QdmV9wqVBFCy5COz5VkxoIYM8kUFkEDaSum1oU1 ygBCwafhyV9/kYMAMWKScZG+hP1MioYV1JH4EbibIAxVcrO4ipJia3Df/q7wGQZJUSOFg7MA+o7o ONMX+JmSkeTBwqjDxGSz4iVDlY0SADaHSx9TcLS60mflz98tHH7KcOKG88nthNab9pSuI5PIk1oE PcTTu1EUCycHma2k1hXy6LSP/RS+HH52jdosZS5w6PQXTYp/fd7qICVDE/iC96yDLcNpNREnYCON /IqyRCoY7W3b1JQko4K54ov1cjjHy6GNgcmp9g/yIldvbosFUOnypaih4+BncvBKK1nEz0wRxClS W9Pb45uWhtZm6hRnxa/jBZRpNHbY9KHlIYbp/Jc+rYVlkl9AfG9qTe/y3zIJUF+ai1iun4PHxwVn 4AApsVlM0OQoyvhcC9xmgbn69POdu1faVbAwH7aamjAyTrsY2bWyaFTC+mgkn9DqfpfucMFO6f3e XkZ5W5G0U4BFjOuq703csvW0jjIVpYkXOMvPflueyrj90e3O7ZjGiZIX5YVh/kkynSHTCgd0tck/ MjeEupCaStkNiyyKaZoxiOKoWlX2HDMTm+/K5dMLxMY0GCHu2ywTp8E7YDqf7WfGzUvbL8Ji2pFw 0RRdZrm98JtiDIMkY51+TsqzlGWKyb2iZeRmdz+YaS83Rwrfrmq/y6VY5FaaBhuwLlY80opmy6SN nWoIS7MsEAZTkrRHEzxjPiZTl7/TIZ7FkBGFB+z/j7bbh40kVImRqtpVBTKNNe3kfK6Wmc8uo72z 2zfWmQi8F55nH78jAN+fbNIHZwn3EFEZwF3tJCu8pvYBIVdTWXSbUjNNU0DbxThE1X7nwwe2lqnV JdEKHR/7mX/4n3IiXcylyJAt89CrSiROjmQmXEA20E1ESSjutfxrpxMeFPsEPNNkVldvtlDnUDcN xVibn+H+QO7iKd7biwwaLeQ3iK9hloZUvqRh/3NYSYHQMCwzxHID3d/2B3tWcabDOcLXRrauwDVO sgVhx79IJhElVkgvI8enmgzaZM+5dZWTfikTNWrmoDCoTsvHCJgbXucV2Pd8FlVv/yCwcA4oFpH8 0EXoM/ltsVhmPptbu9nSxMyUAGbYaybs5GF5U6orN8gTH9pNney2BdXhwtjc7R0L0wAohxgkw46p ICZsiZHwoinDdUszhstwDP4ugfPqbRjkuIXyhvJnoj0rm4CR79PdnRZqxQ0tIan/bEnh5iXaH718 1ASvwXJkGmfSpNtyrJRNyyjeRlR4HH4LopiIFeP7q7JwmU0Vfajr+KOax9g8xGqcOlsS4SvPJPPk IBjLcwqMKiPcbMnjgBFZFZ9Nk9h3i7hfLFx9lhg0VeEWyjtuq9hcOyzBQwiDtsaJDETTjlAJa0MI A8xWQ7+3HG4ZeptuGzLmKxyss/27wFzMTcNy+qyeBzDcP5u8Q69TgP8rBoCZYi68M1NunH5kTE2H wyTiEV7brI4DOJ4cCC7KTOT5UDVR8iGdetu38dsf76JSwPcS97wI0S8ElfLZsRa3HIXMSttcFw84 yJ18R2N7Aq0Furtbkb1RHrJqw0UudlWogQuT98SuqIz5e4BqtCehP0CtGMdYY9y4AEZxiKz+DCuz JznJZZsOqMwy5AB1h5XT9+xUxIGElzdcZUmF8BkIgufuhHZTg2SXzYWbOQN4skGs5sJjfxSWgtpq DiwOCXrmlVJF+pyGCQ31FI2TNkFrRq9wrWQzDABbaPRpT2yvKFodx2sxDdSNqN7ED5IjZnP/5MlW OivwoDgw2CBsJFnM5vSwvYC3+AVBqivTIQt2Mz4rLYhtBevFD2Oack6HvQY2vi3kSdV1unkEWGcw PaWsTniVvgReYtLfqcrgeyFKZZrG73GJ7U1YSLbaPKmNwmQOeYhscc+Onp9MsMnIkTrM9uMp5ksG EFiBDDHykjnYkw9nqpqtmeWykOxknj2gvAYbJXxeC1ayAGMWWcDQOk8rvJH8wiUipXXOhc0N+Xg9 xJf+FA9nhgk/x0VVrsXfqj6TC8bnkABXCgEqCX9fFtNPD5v4b3/+WYcnzwVyKb+HSSHl/c0sLwW9 MqxLhwrVncqepIJOcDsrUEXTCxQ2noKqggpO7WNqW0uVLMCc5wWmo5YV8e0okfjhdIqHtROkObgf rhv9TOLQqzP5lZ0TlLI6cTVpxwUqei5fvveimSfc8KEZbGRiZ7IqF+vz/t224COH9ynWM6bYji6D +wXFgX916VUztXi8WypADUf4jEUCI/cEOHouIyfZOqllFEjtpCZLcYzbyrTwBruYMCptIKni7SWq +VkW24trHRTeHEAMkN52Bx0eSxl1NnG/Wso9FBoKrh/4tuvwq0kuh2ripG5dlhCj566kebCsT6xp 2PscWAf2RdI0DKf4GZYzo1wMfDesajD6o2hhz4E7cm6wj3RgwSMCC1LPCPO2sdcRB4etYyBuTQVK i36R1iT0pVav0+Om8LnwVsoEK5ne6u/ZKjpN0BchRPZErEGIS6TUpbPnu8pNwOYhmt6kvNIns0GK ywE/mcPBt4Zv1OOJP5cOpkp+oef3hzCeUujnJhM6k9A3uQrsnLRwoSKgZSrGv3aBTE5MWl1AYdBB Svur6zIlNEXNn4cEWAV9e5kQgbLpMze0EaSpnLSheIlUbTxXRr9DexEhUGRaibmx6PXm4QC8uVRk ZaBkcSxWkujr5Bh7nWvYmdwnKgpueN4vn+fTeIw/XffxdVzHTi22rVr4LIt5LyKsKsOc0liWY/pF 4bqxdv706U7QgmKgAJRpjaguJk4B59lQ3qNpdC/mipgDBg4WVS1mg2bzJ8M/LV+UIykqDTSMmdYO h0M55MRvSrUDlTvcK6UnZd4hsV18LjGnszUSkbOGatLYg7x3hc1F63xCsBSsqRt5rGs6pvdvsqWm Y8ipaMUTe5UGcrTW8k0tFmTbITbzhS6qTw/rOOIYIUGf3Qtsj1OrTXNFamWDmOm6wKaShbFGq0mC 3rc0dlfS6oIcUOCkIyXUJK1jVsdv23eZBiL/mszraOY5sJkYa5RJ53CVNpLBAHIpLtK4ctjaRWSx MtRRYIBFQ4tt23H5zSUtg9+D/xnPmEv87dDG7/udDmn90QxvLc4tXDbNxH79yKl0YMkcMUnARIKp g0jQHcB2gWthBcHRPSrTQZajuVhXjW/x6rlOWay1SHhXjd5dhko6APiam9ZgW2JJHBwFWU0bZHy2 THfImCDJOGY3PlFdd+rfEZZSXlq24YUrvxzxnBwiqSmDWswqTpM2mSWpOctO3vERkE4Tqc1Bgtgq yYFRqQqGQiuoQ6PT6N9pKcZaCiclS5ubT5IItBd/PqaMU/yvlOE3USqIdHA6vHAS8AlKtaTob6aP qOs5sOa4dcKgJvW6jImzfL6FV/oyKXwY7JKloKSqKMk/RZYhp2YwqJRUZUtZwkZnMcbD5BCP04sE yx03qdpbT4M9bjcvyIJy3+j8ffC4OMipidAK6ma/OBmlTJDV+kg2A4A9qkIVC70yx4rP0k5oKT2w oLrwFLfkwSY5VlNqTN4AnMEiwVmTvnEDU32D+zChLfFBrUOaQQnZh3DrxMmi3ScX0dw++FQw2NG/ 6aDLCbUsuMFRZB3hqupGWGbN8RcoyCGrm+sYnzA61Gev4hssd9qz2kMnx6r59ypVWdhlxsOLP2fr 6vJ3cJA7eYg/54uuDMEKvcj4n3FM/M1wQZiN6TSiS3gid2Cy/6iA7+R1RSdwiaEhN9PtnDoWXRw5 VKPqazjQPJlm8mrOmdcRFxr/KABWSovErbSnHVt/TkoMQxDWsQeDJc4tK1UKB7ml4mzRiMRbko90 QfCZblPEiBrOxVqGYVPZYXCYCAfKKsHmdCYojvVELx2AkWlaiQbS4YE9BEZh5tnH6FMqBboGaAUI VlUcWgzoBo38JXYG70oOkQSoSYozLmaAj2mZnBeULA3+xeLPUiLJdZpUsFipIKAEFNfIwK2Bm90b ucyF7QvvA4tWA3kMDpjIbGA+Az67BfkuT1Age9pdyFfLGjOkB6ow4JqcMTfLA1sj/dqV2hRDQz87 DqXiZ6+bHSPCmVnGaqlYzApJKIGV/E/jbuLZ6IXm8XylijEoJIsQJUpnI0UBWMJZZVVsLzCCOevr EPfVMer5LM6Lu6iahbhjkqawEIknk/lb6kjzJOEdiiwsdw5fQGTvAdTz3OUhDzgrpwlbndDGaNoM fsTmzFYX2Q3+akyv7pYrVRgOh8gsviQ90s60jOsbKiW/M9koZzWv3MEMU+H74n56BiDNCCFVg02j i4PP9Py+1boUz4fp7UB7aV8re2G50qP1AgZQO550Cll5JycLKoGsnzmA+j4eqBJorapGVjf8LEXF j5ZQ8f05MFYzaAHuIJzZaPNITeLkFAqh1WA8ocSluh3SadTb09+dCo8LqOhegTz4s8iirsjbUn1h a4BKulC5/3JYpWUt+wm/LOAYmhGGTASD2JEXjTDtdqax68BycWP6igdhtncGk7Km2DN6CcZAs/TO uMhVhNxi7/yzeP+LnJjyb+l+eD5gWlx2OrAUJY1ifzmPdmhEX9CGV3iD01emDS2jWyhOPyxoJQJW OKUBX2735Xqtg+dcCKFJCHMEuR0L6fnZ8ACf8JjYxEwsWKmiCUgMapvlZT0TeMv0pp52Ubd2RxAu loxtFgJtEtM8yvW8BmJcWFMFNsYDAmO4JVgnnqNNBesavVIDB4TDpo3n/UFjfPlz12beKuV4gsVr pxu/xNP3mi6i5bKei82dhUxydybR9BAM+7hb0jaZPHLJUcEAACAASURBVEcbqKmlnDOdps3Ptayi IOxJEs2Jo8NcMUvks3vh2JkyBeuawvmQ0mFFuc7BhNVHN43q6CqB3Lt6vMZ6MsQ9BJLJMrbTRSyz EvZGKBeCJ5OyHkkHC0S5crW4Mto2d4zNJJFspgtxSZT1gTQJoqk2pgjJnpIxacSSpSTCwHfz/Z7W LgJlkevYOoj/TrgBc11aTqoSTm3d6GBs+t9thlg4deoC4BfKf6lXBQLsQXYmpo0KpGV9YDiXlBg8 /aXc4JDClzwNyYrXe9HMFVoBVW49BTt01cMa/gKeg2RJnvFQcCqtrcf7tS5kDA2xn1FqtaoXy34s LzMIDUWI98RnkgQq3CqaFZ/rPDW+rjTdyn4v3wKD+3S3UtuMRpDTS+tGaTxWVbBsZNPM5wX3Y9AE zrZYJam6kqMHBE7aejouoBANkFRlo4cEt3SrD2Z36ZHf2cFFnUly8lo4gKl6UbtZfxx8hUfJr+vd yn0DKo29sXRgKdmEgAmMzQ6HnL7YLlnkUVkkm7S5kZ8zomEr3hWbXdxJqY548OAfVeqZvhtXyz9H nNKJJms8GCW/yMxPdpz6txl4KA6irJJVfcWqpLrGWHsBm02Q8qFSDgtkZNOD+TCFsSK+6MBczZT0 EF+8JqiZzkCSB7cU1Y/dSGyPzPegwhP1A6Lg5axFKO8wDofhI5HXOYPZjpXDRuQ52kHAXWM//J2e LHqCqQWTpX6RZVhV4Fs1c6lvm0ZNZX4PL74ijuXvyTY221a1lUM6GshVo4RSMpmcxmu1ibbexFAR W266AO9Ggn+tP9+Kp8tZhMcbLSMDTctUS24KYGgVlVYrsrFirpKTVSLHuN214EtVQcUj3pSeqiuG BCItjjeuxgEhD/CjvcIP+nvPt5+Ftc0j7RiVDup+3eA5fUqPdA5WAccShvMkMQj0bT+SxVgmwIhu c0qNPIfqyWEnZm7fOFDw47I95Ncl5co1aZttUs75uYDhGDvOshrrZaZIJUjLibfWHZ7sy4UOcelz lUvgS0oJUJqkjbeKsqwN8QyZpMse6SNf0AeaXX3FScwOpiQ8aGqfidim6nDIFN87i7c54EWFWHpA ZWfcDI5VZeZmhYJikAli6oElkO9i30GXaHXJkdqtvSkc0piznWINqVA4nPtMCmLyTnI2F7Oq6Q9J XS2LEzkg9NF2Ho9q+sXUBbW5PhSRXZ0AOfWUyVwfKnOYtGAgSGZ8FHhICaC0xojF6OBKbq4rI3VR +Q0CV1zEokqZezWfgYX4xpWNhhi/Bmg1cUqyrsrcjLQu5vqO0SoZbkxujHWZaV7YN2Zpw+2CusBB VSHeTOxmvVgIf+EBK/k2Bt3y/BoHN9+JynAxsS1Hwt83IWkaoPjlX9mAPN+IHaZu0uOZu1X85Ytf e5kWFF7R9/9ovJEeYiwM7lsfwuAqTqjRz4M5/mF74LRs3dI+CM1Att3ufJjEc3Ufi/ldLGZLKwrk +UUVaSmO2yPnKPIMC1aBv5i5ZG7R5fuULa6SkBQEO405RoCnQ0o1zC0qEfHajDkhxt1SgLdEsZZr wAUqEo9ySCg+DqJzZ+4RFySESTZszftAAZDPRRtULX9aIjH6V7thbag1mdiqnHWZcAkvkkyJo6yd DRRlolZS1U3xa8pLydpTH+4VAD3gMpVFymZ4lhPx4GbCRYEMWjl6Jo7bEHo6j8fl4sbhK1wyO8jg zYYw+nzL/+OAlOFAkpB9uNPFeLqo9l2ODLzDPt5PJ8ltHHSRe4bunqmxBg22qlEYjKaOuDvwFFlL VIxpy3RbmDY4sKFlsUDyfwMa+bY/iNu1P581MfWwB9ikV1odlBFpE2W4aTNQWft0hdQ9xmXaa8KM rnc6knLun1/zAKh46P1xFZRtixxYin0sVRb9cQl1QD5jNjYkN6fO2g7lluqh1FYD9roR5mBjFxMl K9TcVCz4RXMrU/oaFhdvBkb2zJMo/JZoQxRhncC48asCtKY/fJIid8deTOXpxCU2o1mxsYerSHFq DbTw8TafqpqiPQNP2swxuVvFcgXXaxKvx3287qi4mB5Ndcjy64vZXM9CNhsCiUv7lVHi37cPmTOo zYz1juACPxMnB9FCgV9ZzM0GL+Z0JdrefT6HvA/iEp9exv7FR/6WOZcj7nLQUOvfzBLVDrPwRjkz /EiVXS3juryLyWKtRUx19Ho46H2xyPnOxe1CWBy+UVi9sJiYAjLR5CDJYQIbXVVESrlU5WDPwqWY 9BTshHzAWGVRppciHKJBhWKSrrJFs6rhT9621pJCq7E3Oquy7cEpz2pBNsnZs78ZILMPbGpj7UiB 73XM1sandgcOVJ6Tx/AeHFk5wGqHy6WJW5Jf6STEJWNJVlOTa4drLNcz8w9F8PXle2ipMMZ421/i P37/FlsZRiJRdUVmPzVjbBxKPNfVfHmbyHG5AZof231slk0sVnMHu2KOmJW6K2e7qYDTcRAxTe0n l/j922v87WWngcVPnx6MPaVb6Qxvsnoa7WSMbY+jbh8bsfnBGDP8AXsZWsdZET37wOd7Q3UABhFB lrXJdxj6+GO/j9/eD55KTkbZdUvviRIlpXuUM27XKw3zuIQh3U7pGAlHno7SNa7wrdusYnK3SR5W Zw8nbSJJcpKPInDW01Ir/RuoZ8JsONzvNqsMBjXeUCLPyRCQ86USms2JYW8NYCJ5G98vUWBbWEur xN2sZBzZwdAiXJWr93Y8yeWRY8H8FCLQJ/G42sR6tXB5mq4R/Cw2ClNPlgA4xCc8maRbDMUV7duT cZXrVAcVGjCkCBxskOV40bsj6R5HOVJykHHzKhma0pfPgCdWmqRx8NpPPI3lqBYlL7BDAT2TxdVu G8ip0WGukilJgTzbWZb+aUxXTP8/3BVGmZ0ZcLcTqUMBPPWCKkDLITC9lCTgTKmXIwRBIQ5otRLX mY1dfBreYtPM4jKsTea7cjgDLnexQ0ahgANPbTi0uAz4zg6ChU/s2Db4LmwQLVodIBNNPLWmVLL7 z8vKOr3GgAK6AcM3kwc3qiRMLDVmmVYqBWPBzhheTzqr3siLSSjkhsbtFZnM/XoZT3dL4Y9GGlK4 zzuDzwOhGRJwKh4eNxsdLg4QPWudaXg0Qa/IOjctQ17mfcQqD28bPPLrVn8QF6bLQ461xsus7vAe 4KCrRNi9yEiQtSz5SbaStGTytsKWSVNyDgCiycCQMHRC7nVWvqKTmxwMDFZHYvjkhNvnSVUfZGSW wrftwVxCML6s5qRv1fev4uW9jb+8vsZfX1/ih80mFsuVpFQQuJFcoeEsyczCSemc5LFf+7slQffl dI6X/TG+bTmsdnEUDUeoYDxVMw1UOPSZmovd7tQ0V/98x5H2u4vhMo1xhbf9LA5dix901FyK48EH 1uNqHad2K22QQHb16/Ixk5WwpyR+oBDMeIgi5ykY0jR7SSo4PdOtwam+9LZulTwMdb/MxqdXX4p/ PI1918eu7fQwBepV3LqmMqgNrdE+WduExQ2cFv5vHrb8tBOHon1UYgoTukwb6Zc+xVkUcEy252Mc IKIlV6lE1UseE56M4L5A1JmV+llyi7fnw0d8mFSpm7wpaP2DuV3AI3t7SKqgQQEkWLVmtlopoldN KzM00x2hw1SLtCb9ET394/8NnrY6HduJO0uwj4rDxBiTqjjzLrTJyJukGubzc0hoGDH08crhvtxE PZsLrAWgT7/Wj/Se0qImb6ZgDzqw8YIS1mOnUHluZBISn42fyaQKdnoxi9MYXBpTp4JTaRtghkCL W6mTbW4ushwkKfUoQSQsUC/58uuGBxxM2jrrchzi82YVa7lk8L7K4efnXwJrnS5D1QEIflEAhKvR wtHz9IvILGfu0Zr58rX/P34VYDI+NJUBWUb6/UX4JxWWHZZsOYT9DXccEAvOJUTn2T5mdvNy48Kn VT60fQxsJtqtYRSswJ1TROV2W/CaU0Um9QMDgEzHWcxjnbQFG/cN4sbJsnMc42V/UCUjdkC+u/KP BiwXwxb2j0/HlGGiqrLw7qgi3+T00KoIQC4GTMH0uj1d4u1wUFXF8y/8TCa0dALK6pTm0aoO1o3s ybtBTrBBIIi0zEkc/fnTp9gfONmOTiYR4u2qgoqDX6N94TQkvrxgFPyj8rOQ6KZVdJ2BWS03JZqM UdOyId0AzMU6eDKIJCcCY4/53aAHdjdZxoLkD42/q9gIiO2UQP3pbmMvKVqZnP7Rl3O4cFtJ+d5f Y3e0bS0vnBGybnTxzBqVvkdcF46kCA+KsFquFgKH+SwHxL5UVkdKeB/CxbWCF1lkDwZbPxJVvv/n JinJFy8wUxFWBqoxltAhlaW1W7V8nHkLw2czhSJB1QTDBOzK58sbqLSOsvCFJiAvKPt0WyWQMgw8 uedzWdw4YTpi6FrdlC8YLjb38WV5J/5LoQaIrjKphEeUUTotOkJzNrscL/EJGx1LJl983C4lqfDz UrWuNjUP37TWsaVxLyqDXDd0uJomIo6WlBTOEEQiAz+t4DqKTMs2gkpGrUTqPaWz40Ch8mJdEBen 4ARAdONPVvz72ftduoV3Dp55VXAJqSCdIg49AiiB9tBJ4BwSplrQDvtiLZIV+elfISUbeH4/tPKW sle9L2B5zNWT2NRUdgu1eVzSTN/ETUuSJIJ+8K4xLhILL4huq7mkrzEwGBJ9w+ESShOSdMeTb3Eo L9yyQ6w3G6dr67l6Qs37EgWhqW8BEbD4Obj1cykjZ41+HxdSGQixzkSGVgYBhcY53hHIMwjhINRe GqNZNnJAGS5nEWVPL2hbXSDIp2y0sSWOsocjwRwhR12FtH4HO0ClUOoSeF/yvgS6P6y4YSP+/OOX G9MdzEbm/MuVpitK/mhIWTnfiIwOv3TKrRJsuRGjjeOlVU/tKRylLwb2tkxlw/795V3VnJKcoSVw 68IXufBiZvHwsIovD3e6sZTJl3a80FlZzGArB423UcRX6n2PR07iTE3O6RygH4DeEsypAUfDthnR L9yZVkAePTijbW6YojCXkVwH8G8nVU0uUpDMA5XrQZIUS2aiWNbF4ydBXoVlSiwKnmP9nqsrH0JO 4/0wTyxiUz9aa60c4uEatUSrSVKUmk5A5mICJwBcJFWkHlRV8/Siovxm40/1PlfTIX6MS/zz+Tl+ nX6J5Xwam9VcG0pAbcqv0Lopqy8rDt4Ph4YqS1o0sCDJjbi4bKAnNn9/UeIv+w++l8m/BtLZ3CJw jh7c4FwgnESqgqsuLdpJFuz2dHRWQI6+fVAwuZqqOuE764KRAjoj0qSsmMT76RLN28Hg/Xxj7CxJ kvxsTfcUT+X3SjqPnnbSQ+zJZS0ik07wRuGnVE5nmx8qhIRK385m+nmEEJ+GMbZdH89vu+gG8hHt fEAFiO0yNI8fnh7iy8NGk3egRPYC+k1VfKJlMFDA/HEW9+u1YvQiff7FnxJWiuW38WKkZPjL0drg JGKytSeAHLYoVbDN4aKSVhSulirdUVy0T/P7eILpLvKxcTHV2uzrTIaGysS+1f6TooGOC5C+ERv/ Op7jOJzjj+27zQpk1QSx1KETzi0kg3Eey7mDYbayBSLwg6hBOJh0c+n7hU8X2k8cX1qTwmvEmPNl E/XcpazIZZzYZOTFJE6clK0XMS+U/la6JbkL2IeZ9cuiYaLG5iJfjUOI6kemb7KesO3vTRoCyJpV hMzs4Xc1Tfz0Batb4xmAdmBPJYqKW5mTGTkR/Tz/nYPreDjKF3u5IDTUY9z9eYi3bhLNsYQSzFSu Un/WdRPbwzFtOIh+d3aiJj0pU7OA2ZMgOY3mrY6AeIJkKKsbhR+U6irLbluf+DZJeMuVQXrV3wIt mMukykbJLMXEoLI2URrC7POL3EjGfrqxIRqicUy/LXGyLLGyE4ZNEDUhS3E6z54W+27Sx6c4x+P0 Gn9wyGhDgZPYiROsx/5H/rcQdLk0eLbyjUp5iIznBGZb0eD8uzbmWEDLQYKqB1a9R+JeKz74JDpW AMIY04HBRi8+G38dF0MzjprgySsq8S/z7UxpUYxcekeZnuJ3IQdUkpb3p5u7JhWkp4oGxBkulHaP g1eXknhTnm7r8IcikQ+e6lODoVQb2JWYPeM2U2oQXBvoIi6Oydudz2r3hNnR3h2O8nMTr2sacexb yVCsp+TQgWJhGEKVPe8hIu40FMDG2xBAS24ANA0Y4hhELjDhJAnIFtbY3oCDKeVZCe14hlE0mSdH NSNvefEOz7osqGAEqGNCmYcWX1LP9mpOYnGDBWte1CtnDIKt4UbRt7Ht2thf2jhA/aFy5WuK+pOq oZSL8ZlOszYaLLrvNyId2zt/KpUJhYXsl3ENrpmKJj+RA+vfvz3fnA5Ob2+6LbkB+YA8fB4gP4AD i19/WC5j05hvVUpEVxwmDPCSyagDvNwLhDfupZI3TeDkd0UMmGxUr9FM08pY9iUz9cT0/pzi28NB 1hRHMDL8fpLg1w5XKczBnc6nVq1DVDOHoSbj/traHM7uielDmi9DTP1pSA6APbEoFDDGk+/B4tD/ 5IBLoiliYXtNlz4uJGWxlso4gug9mig5DGI2S05aRtWXLDrbxYAtePro6CdLbAQiY5qnm9JCcjHs Uw1vi17LmmgHzK/JMXsmA4nnJXcEA8YSG+dnWw9trMcuBhbDbCHAvLSwpkm47dMEN72V7Cuf4uWU rUg2A9YADpWXl1jmlz7W6N9Sw0mbxtdVCo6ggazgZIHrCHaSw9lqrDnHRjGmn4m4KWIvfgOJbfHz WBvFSNLum/48fv4++GlT8GBSHMFmKZNE1hhtt/Da3ES6WCAJ60KxaZ/UDAoDMTZoao7/bktZXJmB xZWIKjacW3HbGMNiW5LJ2EBpoLXyhJpU5X7HgXawFTgHVj/RZpXRXk5+m8QAt4ip5ZZQ6UAhRo4w 0noxk9D+cb3UgUaXwEHJpcyB1bY8tyqWcKRkVuCqWBdoZo8ygZRHmdK9x7gACym9ShXLh7NCYpki qlLRIe6+nEVfoFDZtUcRYxl+yb6Ithqys4wPTIQWrxnupfz5z2Kwf/30KROnrAoB0x6vrdj6FD34 rzlZInlY/9ff/vPDWngyjTuMvQBop9N4PxwFGIIP8QXBkX68f4jP6424Vj99+aKJiW72OQuc6ssb lQ/GgrmMZ2Eh3Oz8vtLGgKP4IVoJy8Og6vrt7T2+vVuoyeIgGADhJuZ5tHdmHzk8nl5abRytKaAr +Xq6pTw9cbKO8Thix9ZMH8SgtRFhTcVWTeNxvYg33BBTSybvb1n8+oBBGYWeSf/K/tYVoyZXtAEC Vj09pY0yzmTqAgfKeeziOlBPYTiYEWTgDcJMUjJBmCdeSNhHT0LYHtNbQgHkIXXje/nAEkaULqcl 2bcQViffEwcVU+9JHKJXRcP3p5hfL7FtNqIzUHFq86a5njai+D0el5tnk77eMD+TWe/DaFBbJhGw mZX6PExr1U6KsHqNSqcLLYarNAG6csugdTbgjm3TGgF43vrAeeJcKUkoqw5+toYruAswMbOLBhfZ TFpQTzD1b/qsP+9wHbBFtM0CU1idutIiaXKk1Vz8Iqg+IlXKGtsXkdNffGDJNz8tm8sBKW0g5OcZ 2ZOTeJzP4gtpzlSbVatEblob1or8404WoOsi6p3gLUyPUf6sh5WrCuMo2dclJlSf4yTetofomEDP q1gc6njeuuXUpVCD+3izKyavn8QCuycmbYTOppaSw4Gvrwo2L/ndfqtOhGqLiSbtOvuAf6hIq5kx MrDl5/1eVCEuVhYEXnHFifV6dvKTbJC4kFnjN4G6HYvBAKmWN4uFDANh5O8I8WDtKUIuBxYyFnVl rAOLeHPxOdJBFNuT4vfMmFW6sgSa+55Tl1btrNguMuMedHMB1k9jPV/rpuUD6ZSuJ7E/Q3rr1Jpo UgOIeu2VetzM+LAAjw4I4LD5j19/j1eIbrDLeZAXwEe0eRNZLJfMNz6/AjvTRha1vAz19P9NYyu2 JFztHBSM/2HK68FqsmMMQyBrBsCqlDVgkvlrtkihtGfah6+SsbW0nOUQVYFj4a6sUyBywvNJvywW i7SNvO3anzfqjwNGtA2Nxs1AlD6xfE99BqsKiiCZP6QNNvNtrn2oENVkw6eVNQRR2eAmIIucYmzP MekRq05iO3+IcWpysPWYOAS4mqRd4DlZIG4wC0KkwhpyaihOmPAUt1CqMCUv6mMbx6Ql2KSNRSiy uES1rsy5tff7NnZxSj8kGxoyzEGP+b7bK7D1hFuohgGIhY3viDPWtbcKCadOTaJEc3HrxkFnpcY1 XvetLh/ggfvlMl7AWVhXYD7jEHdrvMO5VCMGJtXTKg5o6i4HX7I5VXve7bTxocsQrIx7Kwe9rIXO vTAqpDdwj/71H/6kIRFJ4Nsdk3jswO25foWndvM3oYlz2tFNz5CwAmvscDrGoAuq9kXKOk5zxm5/ EV4HlqUpm2gwDEgYJNCNAMEMMR3amJxg+3sSaW4blQ5TOlteY0fUw0W7XGPXHa1ISTwMny8OaJgD 9orDM411zanodKBbeIaKPFLcSc7xxJwL0aoMX7Ryb2XPt6e4n3OxT2NYgG1SDbsaE9dMlujmKuqM 0iWctjE8AD3GMgETjy/jhlSxMNWz0RfgWtu38fl8F1/u7+NpszQng1Fn28an1VpWEUxBkP2gDudn cRsSzFCmQspJSdkFqu4ji71tFQkkQh7mZoEwm4NjGh02Mgrz7IV7iN6v4An/oyouXSqtZcxY+7Tw KIZ4pN04yIK2pld1w4kuDWHGeilEIy1aoV3YidUVkOPEzPwerw7VkAeYtJAlIKKY7NsqRBFLOSqX 4V6O2XU+Tqk1MkswBaLcI05ESSxNUV60Bc6FKx5Mcm5NQ//C3fKtlFVgme6o5RjiP/o6trGIJuax ygw8vi+tPK3aHruRJKkWmxwRNpOBzonF2NkKBDu0ciG5tfUAoVwqzm50uykYF+Jl8bwSh9yKByGa uukN5CoSak9SD1KmD9cPxiwlZERwRaaJ8zk1LQNTvYYuObXT6XyIDfe2bjXJ5LDhkLPzgRUVc4H5 pCXRHlKJ8gz5GbCwwXFszqfodlnJMMABJllkKrWxKVKOTdUY4/NmI8umExcc0AHcMzhd7L2LB0P6 NwM6UjHmtkvRWpBoOdI8pb/w/hSyy2DIkWnzJVKklODwFDEKYN/yUmZcEjht2AHpNHQxDlRCJtJi 8MShIz4Vaw4nCdYvttuX8vv8LqVvTOKn1i0oB4RcLsp0tjEIbgihWNGyPxQMAtyhlGlcYRaxoOJP jFBQUl3FZgoWVzyNuZRJMBo0jdwX0F39o05An+rOGPQiU/WfJb6qLkz4lEPWRRvgRyfn1DHipcee 1ipHObCQinxdrOUAUV9cGckBU1SIdHhgAsDtczpJd8Qik0cUPbF6YzsGwL3iQcpqQ/IIJ8lOhkvM FU5gcmVxYyibRthVToEIJVDiL32H0mQi3vd2TtjVbWxWq5if65js3f9QicmqdVaL5Ep1ZX+etJQR MzsjwYUtsRBNhSgUB/HgIQyC0TSTmMj0zAu1YDI36kKhDqSwV2RAvLyt0/DkkwWVjhaU0sKvuK3A oqYe/3Mrugr7OLiMR5h5DeP5L7FQfNd/7c9RXalejdnwDJg2VWCCqdUUDYBbncuCSyKnox3OXsoa tHbUvgpJyUhrkEKoFDeJtaVMyHSP/s5tgMNe2NZ1EPVk217i7XgWcdhC80wI55PSdiUorviqtMqx GBp3VaoKO2Tq0E1LGJ7n9tiaaLtkKm68lGqsPbfpxmAjyoWeZ+rtELwjMyGQQ7icp7GyzwFcvzjF mo94Gq7xesCptVVw7p8+NVpr0IsV4qGwiavaP/Adr0/LVFQ9y43DpQjtKJcCLgdqZdVa91ZN6DPU ukwfFhtddpqiD/in6WbJNJ9rTGsfWLJrysNZbRbrsMKIzy073Q3fmQNbBxZec+kf5svQwmb5xVEt p+e5UKqcoNs5xML2Mm21860hEJnyzebxQDUr3NDOH1bQ+NDiz60U87eIzYKuC0+tU7zs03HUOXoJ qOVpZ6Z2ia7y7cx/uHT012NMlIDCzVqJeLY9nuMvL6Y38ALAAe4AGU/nmHEYHfYC2Sj1V/pClKOO p6di23WduFiw20U7IIaK6UOy1rEJmfRIKyzEFaFMh6orrMJ2dzy4rWB0YCS+481jEayqpmamkp1b 7Nt2G79v32O5XtlxVKUxVUmlgwqDNyX0pioUX2thGuX5UM0JkGWse1G7ZK8i4zzm+Nh1FR6TuEC6 oaziV+CFoqS8YSV9yny3LBzSRsaHvLAoJaKkUJSNB6dlYi5OO54+7FmytWTKJlt0gczczE38MBzj f+/+Fm/Dl5hcn/R7leKr9t7R5IMSWJyaAsM/ziSqmNJSJj4sWbGqM8+SCS48JPtP2ItsTu+kVsWJ 3WwoVY4aQtjzSgcfC3ZWxRYHDA1sfMDfDmAFjpSDMePAJCGK2OlCcYVLxUCF9t5CErZzLWWbxLzY G50vsUp/KfppgHUlH5+HOA0RD2ucFhyKQN/HIUqLyr4AuLcW0h77wkwV5NLHq4JKmD5HPNQL4UDf Dof4/X2nZKHreYxpX3zZsj2ClpKSKv462TjznCZsVtYBfmpe35f0TucCYh566kbRgSpwT+5h3E6Y 9tXOnbxSJZ1NIoXMyd7lmd5yRJ1coXcK54qBD/QK4UxUnElkZXqL1EKRf5SsfRn+eODB96TiV/DG 0Mfb8WhLGsGdmVbNxcq+Wy7VzUBpAOOFMkV7ybpAS8nfh04XDeoaz/zVWvsdzuXtwCr/2KDMPWo5 vLTZ9SRLhll6T03MqaJMPQ2niPPZbR6b6ngUH+VpzSmZ6bFUIWiydrubeR6H0nZ/UFVFec3pzwZm gREGAE9KbREAPuPQFFGyILVRxVcpLKZ0McjvoslYstnr7yZ83EpMJwiRALfYdW2cTpjkb1VRktDM ZpzPPEhYK4UEbGv4/zwnJa5wiyGeJVFZh8IYuNP4AQAAIABJREFUvcTjzpgjx82pLi75odIoREJF njcdrYJqDE3o/HcUYajJdshczK3RgYpwlJTe1cLVqqZkBGpkACt4Xnp281NaMERaiWwHRScZ6/h7 rOP/hDXfTuORMIoVaTr2J1f1Anu9JN2IJApZ1FWl5BSZdScKQr4HKr75pBHvTOCuLhdaDh9aohg0 TVxx8/guscj0h1xvyIFqeFZVnDEFzHZQ8hb1nsZoZCygv5ZqmefoaQQHx/Fyij/eX3UA+YC36l8J UcolvMTqHp2p13rJ14SPx7s83V9ivZ7rWfH5EeuuVjhsXoXxYa9Ete5Rv80FNYqXTLESUfdus1Gl +P8+I3t5E1NbJNXk7Xlw5ixPLjyFZozKP79duHZATfDnVo1OtS8KmZPWzRWoBdC2QjI+pM83WPPJ v1NlEySnjwNvPH9Hl8lqSVUel/zMWJQ+X4FY0hduYtoL5gJw/eYJt9CV2LKa1tfkVr9U48VUtFCI JCJPB19Hl9lxxGYAxixJ+VktbAu0qidyjHBLmO2NS3VOej9RPpQCMTM5mXZkULq0VfkesXNKG4PA ShlQlpkJrpocWMd2rg3vMTuaI4hn1i2ySAGjt7ujl2m2RnpYSok1SEwSi8bV8lhKTCWZ4re2Ki1d HEaQVU220SW4wa2R/ZKUzItqX9IjyvtJkB70abWKp8cHsYJnufD4/EkAvxkKCvdCdQ9+guUM5EUm MMVnXhVIjublA+X0G2fZ2eJFizKJV0x37KDqA6v4mvNYlL5iX2hrJ9MBQx5VmStndrLlKEWgKmZ2 HobDeHGLlN+B2K/XYRJ/6Sbx5/1bTDeL6IeNn13xDJOG3c8XTEZDF951WuC43UomfIZkyD5FbaBb NkBqWrYhzswhpJrglsUHCmKypBpJMOZn3ygbYdlKD/5z8ed1iiU/y2REJ7P4+/FM4RPdrSzZkvxr Po9lY0AekH+gGgHOmIRavM+BlXEGmvA9irtqahRpx/TZyTmQl795UbDQ5bIABaLoPHVYMInlggMn rWQJ/NJ18be3rdw+oWuYZpJrNUXLMvDJL86BxbrwMCVtkUrhkGaZwcZmIJQUl4I1Wpztyehy5e4C GIOhlcTfwqN8wJuI7E4nl6Im4fw/76rUcQrc9j5XzVzCV8GlYAZgvDdvdOgAmstzbkIbHOlKkuRT nF0M3No2h6rOYj3zvm5TVrebJKnr7VarmNYXMRGWSTOSVhyQUyeoblQMySzOBZRT1DnPib+E9mea YKs6IgNpIhYmC1eOjxnJ1HbGvPQhM9WZSkCGZrg8MrJGsInhfybNOlXV4ZkyD6MVpaoqAamykfWJ zUM0wSxbwZsCzC9Yi+nWfvhwKhMzWkt/Nld/YD+0Nj89PWmsrRBY2eVM43D06BoAlvFtkSEo8RjG L8BlJn+UkAy/YsTDY1wk4DbYr0Wq1jJb1QyfNPblTazHkP9d7HdFdbnqcirOmDwyS3KwcsG3nAVe fm6pQJkUgmvQXohCka34BE3l5Rg/7fexOnEof3EgadrEcElJScBIPe2ASliALuRkLmsAw/fXSdMH 96AY4PCr0BrmQYe1CDC//I8E6Jrlz/UqxnTynHirHHhLVuYST3FEsW4zpR3Fgiito3U0Tggq6eOF lG0lZ+PFPoufPz05JSkTbsCO+JysQdtfm9uFmllFzNTV0+NqoUAWeY+LE3RVJcv0CsxVMXSS4tgS Gw0nm1XE6MG4D3jXb7tt7K+jWkIqOigL7CtpUC3SlBVN0aqD0eoAR4Mr0zu6rxL+6/cxBUtkGp2Q QulUimGk/kz656sFm9bSe7IWO6U45f7QRe7Ws7RtEqkzReXSkV+YBxYyslUojINkfXwh+XJmIEMM dxLZDXBRNrWdVTEHAIJYrjRZF1bI0E5SP86ETMNJswAdvuCs7VkVNFWVYAO5pKSBn51BbYSvpBGY zCq/x6h4OWmd6SAB84GU4jxDTd0reYTKSQJGT+1VmZWcQA6C08lBj/yapljQ/fWzq5gAysvf+sPr GfsgCWnTXVH+2qq4EvhOR0m//JSvyOwshdZ546gMZvOqlSIqDDdHOE72tYIxnKlJCnkV8Lycx48P P+jh45z6ut/HS9/Frr1Iq7gnml4AsQ9DDmBNSzJj74Zdsf1KcEYy20s749srw1ZTASAJjSCFXBLl cFXF4sWgwwPLF/r8+qhWs16ih+RmTvuVTOYtLYfoDBkXVg+mK8heeDqVMPhpeIvh9B77wy66+ztH t5OMgseVQG0nJTGpwfFB2JksZBygakB6J0UEvJvN3InffG8mipv5UtidyJe4e6DthEIyx2wxFRRU biKVetM1Cf6CY0yn9sSnMuPZ/HE4ym/pDaeNwSNvXCNo9f7y+h7Pu70cKD6vVjcagxJpkIUlYRLL oOftPsY1IRRY35hl7hscO6KLIA+He8x1uNndqIoZfEORSS/xvj/KxkYtKhVujBoUwBl8O7WxHVgz 6OJMD5govNcVVqmQBL/ooHK1LOkKnEW11FRl4Hs+EKdpNc4knoOkEL7dQbglXC0XYsB7mneN9XIW JygacY6TQnl9rbtysxmmuIak48zreFivddEdzyftkWF00aA06LRqOnJg4j1WM1lGOrRUx6H0K5j2 co/Fmskt56YpUMxCwRbIlewOg6e8q347rrpDedgsRBq+e3yM7WGny6yiXOb9MPZ0hlh6hadnku77 cZAmjRNX6np9mLz1qXykv/MUgylESdPSf1f16p/KB7sdLHlFo9eTEFKBppbrKJcQUNWIrgmYSRgr gHMRDX/gHxkokeP3YnRX3BmV+KG+PluP9Eu3NXJm3EhsSnJxJy+oH+43sawX+plzxW9xKHfGKtKn 298lD5acfpXv7nAE+mePo3PQcqv8zFT/OLBK+W/GdgqokyPmZ2iulZKghTMWvygO/dHVTbEmvFWV brNwH5ADK3pNqhgj7+pDhyCr7xqT7hxXsanNeAbbk+yIKS5T1BM21GdVxKSw4BNF/cUHAHBeL01V EA2UcTktWM/E1BehaCZ5+UhgrWRsc9z4v9fzOmoRRH3w243CVQiYkLzZMFac11GNOKOCcTXxfjrr cNCBku2k3v90EsvLEI8LDlgqF2N4Ojg0FRvj/UhlD/Br7zRfJo4Sa4dWBxG3PEoLOIFcHtAhqL6o EnX5zmpdAPye46nV+2L9ECrLBcfkG63q0Hn8r0vsljzjdlb83Gm+17Qb5zDDHryaeNijX8uuYuS9 VOlgIYzWF620rmBt4qO5ilZVLYsfxmOktO8zODixVB3QhkhQHPzjj5/iYbnQumy7ZRz7TgtPTr58 jzEEqMMCoNr1dNYXMoCXq2bvBdby43yjwgb5kDqIdHXhELStDONSh3y4gnRqurW7kLNNm5HUKolL tSQzifnYcC4tJGCpCny26LPvzcUpEywl2qYdL2CbU2r9r272LFFt38JJalynmMmV2wSc6nCyQZoW gVjkJTLswxWhYDPFMcGlb7Jn//8WneVlTJ3GgWKfX+mSD8bpXwzjdEiz6WOU9uv37T6w3Fmh1xoH 6Q8hIHpi4xBQApSSJxnXAfFr8eE2I9eR9bajZVpjgfPN5fhmF8yzv+EhqijNC+KmQg1QxNDGRF1l TkS4s2Mmf75cMgKdpf1i8Tua7VrCGMRJ8oIqBy2t1HnSqIqCyFurpfR4WVWWZCwZS5+HB5NMt5rG U6znsz0LF9BlOKutpTLR38mFk1/anuP2e5oMaSdTDnddRGrwdZjopuWd6BAHOLaOcVY1EujKGVSS nr2EvLxTKixKJeX+EgzaXVTd0XZwWMsaSVQRXzZIZRYtMMAg3yyThXM6Cx47kDY+yhcNOkRJDaft ZBPjOtKiWW0B+LexPxx1sDKdlEUwTrbEgKWW5cPrNtu420XkdXKz7859aP8vj/7paor3+SBnlLTO vh1YPD/js6x3PqclOhw4vrQF/RCll3YtNwlTQiWs2U8P97GR9TnmflU0Az5udhnGWJMqmD9GZblv sZa5aLLPIMi4bYnkc6gI9IXHu7UuQj3XG90Hfy0uj4s+r7BluTc4M8IUCcJN4MY5RJlJrfb0euHo JYO3GRxgK4IPDpYOi1mAp+HOSBs4Ae3nh5fKQQ8Ez2Y7byo5RWUFi85/R/HOUgBjEtKYcMm8X9WC uRr6ewt9LP3bdYjqjZV+1xKJD+vWdPsszTw3uEIgrY0E54FbImcGkV8z3SfH6WijAPv+iGNU02fL MCCXKtmZAYErBsaxGp9nKa7vsUwVjAiTxvtuhnz04ymIlguoSnybt4GZAewTuiqMkAOGEW+W1cUX 3vyyD+Y9Zb9IsDeLGh/eH3bG3Ia0GZc4HY/2vU/dZonCUlRX1HEeq1hjeUxFCim3O8f+eIi2PWmx sJAWzVo2P7Q3ct8E14H2II80HDTsnMH3hXEtQXx0MrDjX0BtfdYrtiTgPBg18gy4sPzdaVF54/7v 5mapiIN1L43nVcZxHBgLDsLZWTIhiZKvV0WtU3npYOjH2A9dvNZHpxZB98g4LlW08gXDhfZsZv/d Svbd4FZYuQiszhQkkZpFRblK2iQjxhE3hnP8bfcWz7tDvO9aYbEk3FOVIQOTVfXVeCs2ONLR5TCm 0CrdlqU3GkB2rht5qMqhyYeYeIS4qETcLgLNxvR93FZKtC5LJLeFrqq8fkSCnk9jcjfG897OnnaD LUMHw0K0nFyu8qLKZJuqxrDPzqezeSPniE8PcCTf9HuetwcdYFTlEML5rILAOfQm19jM6/h1u9f7 4XtRnWsPtq06k8cNF2EnLlmF732mU+taGQdxA6niMCvQgfWELpCUVm5cxVvtTRbM1NbJdzIRbvE5 PfK18bj1u5uCWw6A1Z7kpiaYIOhqy8laHolBXRAorqqHzWXQjmOTEl7BlvkzmPhIHpQOAqI6KLgi fZZyHMoh61s/7YAZQcuLOr2jZTpXXBqtFeR7gREwTXMfDR+ljb9+Q7riA4LPMxm92OX3xM9kKtLU 9gkrljHCnawa4H/hc9B7s+wuFx9sHtvaIBHpEqJrHCCVCEJictqwgB2Ck/h7m0agsIcan/Mm7jdr axHF30qiaG4C9JaeXnmEjq0O7YrSgwCNMxiWAQtOlv9j+jW+bh7ibvOgDUPJjv3OsUUFwCVilwIz 9CfSfcH1AYjmO2K9woAE7efxeBCILd+yOQedK6H2dEqvJqf60CKY62WZDWtH1sgErU6dhSdLIXHX ZlqXVFI8mxaD7vRsYpL49d7kZHBJnoMSu4Wp8r97vEt7xeUANsd3OV0mMo2k4n49MKsa4gmjO9FB Kpkb8gxEV+HvTuG6RLtdF78f9vH7YRd/f9/F+/YY7RGdnkNTbA6YLqm58QyH+MLjZhZeS46AROeu dFgTTNxwv+V/mkNgMTqSJFqlkeEQNBkAesEZduww2dvcwRU2ynKjpchYCuMDktFlUsOT62M4HaNr 8ZtyVYbNzS8/fJbLSplwU4nNkB+h+8WJ9ZT6zoqg1GWs90w+Ld3y9N1cNib/4NaP86UuIVriP953 wrvZ+1UF5turSsaSfAGuBU8sK7PdcaeuDsub1eJOFS6SJkIsdGBhEdtUph44dSYXjCYrTpBxq+B2 QeGhHDrpl2XbD49/NUVh8iBeTWI3tghw2KgOuHQ+SC2R+DvENBGzLj1cTqryMBIUOUkRavJFSpv0 vQyl4FxS+oupTqDA7CbYLDwt/4gPAz3nFOIC6QGD8DpFwvtlXGvkKADN9igu3lO3FJja+jkJkiEU chMqkQdwt4/JfBY9TOhsJ2VhQ0s3w8BtJSdQuyx6mjnDC3k00c4XgLVaLpd5kY0GA+UigWBpb3vf lGwW2ayk+yjPG6xBDOd8T/x988k1niYOUG1Wm2g297ZmVux6o1sc3WdxGeUZNN+lLlMJQEIE4K4f 7jSM6AhRmE7jfrNRhVQwx6O4bMX3novErglFLgSI6+gsX2CqFtIb/goIjW5VFji1vJi4dPgO94u5 APz7ufWCvDfoBPtLFwfyEVW1ItNxVYfmlbgxtbhqOZABDfGO7xbPToRGOHc8W/IhL7rZOQT5LuBg uGr+ut/p0AJYPx27GFpUF76EVfWIQG3FhGsoW8YUxqOoNrDEU4vj+PlZrJFaMR0VSfsi/h0XxMOa VGiz8oFQzljx5Hvn70TBUP4eiexFheFymzFVM2VG7xYy9NyYXPBM8MFHW7kQ/xCCKM9fwnQqW36f zCunwrIZOPDr8K7eFvu4DKecmtoMQBW+cjhtxexwXWNfdDyUP3wvuhRsuxnekaqzXFTyQNMz1uHr g38xX9iKaPCEUAcW9iA1tawhU5XoIkZm6obZ63YtsN1/UjUTlDGJMr3dM7LLgYklNZkXYwC4eJjT 1pTgBFcPyHUu0Y25WKUJhPmbFIYEi60/y9MnnU99iH1YuyrOScaDdkp1grRH6OIQ5SSvhJOWdtKA H6V3E2MzysKDTc7Njuc6E7ASiCAdW5+WycWFVD+HXtyHEjuedsMC7cZJPpnxx2EKgCsxNlIhFq1G +0iYIPp5tM9/Aj/gs1Jh0RaoamEjq6WduFxPUqiwtguhozC87XfO4cA7ZrM5wstDDUIovlZdfJ3D 7F7EdLmyq4ISUxZaXOeT/beFpUzAzSCWeuwtLJPWdRzlY4Z3VSyXVjMsl9kyG1ujfS2ESVcTHtzw R1jQmqZyYOn+8sXl9BbDCoqUQ3YzrWJLta9AVbfT61muVaqA8yUWfRXNpYor7riZs8cmhEvWX6lc POGWqHzWqzJEP/o+unUnop21J6ItPk+M5+Wxb1tlnB9+3x7imYMMrlFLwIgdsSG22rraelPgELkI ga3h7prrrkzdbAVtzhq8MSaW1IBSJgx9rDfz+PpwF58e1zbluzqchWq5EDSLA666Ij2/EhlfIr/c yUgHqgNrERv0maztupdxI2uKNbfPw1nYLtFt3TkqQm6bRaxlrGjckcpJ8YAn2ygr62EcxKfi+zM5 BMPiQATnYr8z/WMHbA+d9ibrGSD//biPT49L2eTI8ZTPW5QA7B85x7go0oG1P5FFeI3ZwAlu/ytn 2dlhlIOqgJz8EW5SfLcV+MAiSPdR8YmyhJVfFaN2FSXTqLgRoBioWqJXNa/DmJa9oh15b9Yy3bfd KEkASQmFr3pXDYopcpvIYjBtwH1/0S0pMIDbRnwPE9mwxdDBURTgSXwUKJUUCG4FPNBpPWWvw3XL LZOBEp640fn00ad7g5nHKRZPATO0heXSThaU3XxXtJc8G14MVYNCL/Nu5OYDLHbK9RAXNh+bPw8J V3AJ0sNzURvCQW4HyX17ie0J2kUbx5MJiCywe2m1bL3Ms6rxO5JG0ov34WkZK0IY0LydPX2Spxi4 E2B6SoA4pO3kamwFIiCtE7hlffFYXBMdbfQ+rnD6Eqdx/NbHYMRR7xbrMhpnDVCdl8uGncBz4Fl3 EB+ZOFrqLwG83BCYXvPcNeWapV9XpUw7LoVt5Ugt9jM/k0OLyCn+G/Fhy0WjXIFFN8gqhcsZKQ/V GO9LGQFQM0iQUVU416H5bbuL7bGL9mAXDvHR8v07qfgjVYakLFrMEjcGllemuBywB2X2pbNvMsaV i4Bn2WIRPz49xC9fadVwhLBwGr8pglLkqZVUihlRZ+wXzByJl5dkygRcJqAcjLSISrlm2FBNVbnt zq3+Xt7N624XkwnPMZ1teRc11JeZfv+5O6nyp4NwLij7imd00RSUxvpptXK2YsW7BGjH3K8P0M41 9Baq8nYXi4ZCBcD+FC/vu4iJJ8VPq7UmkI70s8zHl2VK2hRCsUGKwkOHwTs3oz1bh9IilMAJEi9E 5Mob6ngiFdfluYBkTXRs0sVC9ILNkbvm/t/l9qXTgSQaebvKEYLIe324aTRF6S0PH7/octD5TvnO Iyoni14bCYbDe9F49yJzMf4+sbBVq6dhnYTF8ESc9gumxUaS3nCEX2Jfa/7kvIbF3AiUZBOJ9jHz LSD+lMIq/b1V5s9mqqK4wYoXvmPDSG/pdFDaFsTWIsSqHfNwvlnLZKy7XlyGZgByvrxuxXMpAQFM prjNmOYY+PfUEFpDcTkVg7yJ+JfpMf4LPJcvP0b100/RLTfhMBnwQVcSANd+Z+ksW1jdGXBhUN8V kAYqxcBQRZJ1bCWBWD5MednYGxxrX8jDPgRFg1BKMf5kdSyEtSFZs2ttoQPwFjiEqToddOyqv3BK ONCv4zRW4yy+3t/F/pzEXvIBqMJOuGHSktTx9e5ebVaZTvOzygRUwaOSCNXxtCZ/s1Z4yd9fX+L5 cJKUS0k6ot2YP6UDSzw49HxVrNT2YDFUKnFch6qblpJ10i6JjPMFL26jJqeWzvz8+Sn+6afP8fXp Xr8+Dhzg11hex3h4uHfSON73EGFPR8vi1DYicvdgSh1JZTsgTQaJ8YLPlp2NIsiocGtPf+NqPzg+ BFNiChWE+/bmN4M93WLi8f4uDmofmdT20ZL5oIkzHldVvG1bdRtc4PC0ZG99vQp/1eXP71vh3PAp Pt2v4sv9xqaFkGYFB1WxPx41DWd9KzGaMwbehf2hnWXG4WMcyYR5Tm5HEGV2XnI3xCiWOp5JAn03 DoNpQyGaj1slWjyqOZI6tJEzicVgpCeKBQj3wVP8y+FldSI7qmWSLqr8mfTdSdPBwmVSnnGm+ypC W7wa6xS5mTAL9DTKZnVi7Duo0KP11FWyCJS0s5hHV1Wxl7c4tAMfQpI3pOmgEl+0WPx9b66c2etz Wxc/cW/a9JZK3ZDBeigemL7ZhYHq5oBhIVO1ZGWrLcoUbVqC993BOW95cMsKJi1/i2DazOderGT0 eYtqEj9Xp/i36SF+nm/i+ulTjOunOPajpr/IqTRS1js0ZaKM42UPrAGJAWjxeLLNK5eJUMrRHkiu Xq0DhVphaCC5NN9Z9pjC4G/hAY0tSBYNP5PP4gRyVddU4k5PczWnSqBkxnz42jMVvJ87T1FgdfFV guSbtJzFrItF7daTTgK/ejayI+EHJY4PNYfZNPZ9H8/HLl4Ou9idsqIgGUrf37Qga/fsGMvUV9Fx siT+aIVrybxso8M6wgVV6dJZPZiCw/qdxi9fH+LzPVHxU7WlwAOR2Cnf2Lbf9rti/4mHhSsGl+Fl Zv4d1bJCKczLgmDLhcA/Z2yeFo07iMxCAI/lQakC7HpdxFws1sL6nco5ZERN4MxSDvieZB0qRsXV U2Ss43w+qYDBR/6nh4WpTpq4cyg5dwDB/rJZxB3VLu9KYnCvZd6VjA6p5FCWYGTJM9yAH83lqi2J TjF+ozw0IRQSGbanZrSb5mCKAlljLCIlyCKWhf/DuJ4bQdMxNFkYzPslsbDdV+e03qFtOW30QqTk H3jLYi9DVsUtIA3f8sUW0F3VUXJ52KA8b/lEzakUqzi0J/FRrNlKoqc8uKYGFvMHcesJK8u4b24u bDDmpFmn57gM/alEpdPz9yiuATe9IlWCPM95GfBfUkMpbMneW0qN5mXz3DNCXcs+c/fwEOMmZqOT cHI6nHQwsZHkiJAjabfDhVBrkF5i5Tk6dCvv9LNZQCycZhpfZ2P8H8Mu/pdZF3fLJg4Pj7GTb/op Xhg97/faaBL2KjnHVVEh42qogsZDVruNiH+y0E0PdR1YKfFgvA/lgQOXiVSJLVMVDFbYXZwULnKo +UZaW5nKo42pdjLxQwnQYcY7qEGjfC66JNgWBwnxmeBvKSuAlpbDrdffcxBO6M8Kc/9c21OeRJoR zlIKsWnjqQBkpTKO8fr8HIf2qDZMG1z65ATZpVjIoUTarIDZPdyvYq3Bks2iFCe/XCUfLludmrXW xUleT6M2Lq0amZqfN0ibrpq8/vHOe1lkwnZIN2l2eiZ+k/nJhDO/bxVL4YvK1WTip4sNlxW3VwiM aYufNmu5xarCy6EGNkW0ZfvDSfFxsTBHisP4fPnwZYMGgmmL0plnTKstVVMVOF/Kl4vDe2RNav0Z VB8PfZ4PXBaD9ju2SyOV9AjW6eg4dpHCWiXv+XA1qMGmpCtKv3WpuRCAgkNIrExCs03lOMkZkcpf COAvDzBZ4p4x7uOGnkbDeFScC244WhkmF/CDLDNYZMQP7aJkPUlrEEDOWJzWJEe1etjo+uTiaYmL nEsRUef97yAEW4s4Qw7V/kUgYomV15E8GWMxrWNZN9FdpypRdYqD2WR7pXh7bi9K+gbWMB5eM8Uh 8ULay1klsfk8eHrh0mD2s4IlrrQwPOxGsedUmgwcxNZN3eMkjeIEOsMPO/MZbPPBBhEHjDbvbNIi I/bCh6NkXiv41exmZQTmzSdPJSoD8b5c2ek7N7P4oRnjX6pj/OvwHosvf47zP/xLnBcECXRqGxbL Jib1Qzpi5IbUze1DWNiCDq9ii2GmPhtPRErFutmimE39+24nxjeETiUZ653llPI7j3yJ6zkAdYib b6TpljCwUYcnbhMME0bebW89m1wDwGcyxcfdqwmTHPD8nk09iYc5UpeNhO0vByxnzmlPZCIwGAZG uoIhmM5xqM4tZVKSMYcczShrlMM02ZMKQKUyE03EwxowQZ7lejVXG0Q1D0dN3mb9ECtROxjKoLV1 t2KXV7trPBAoAeifkWQdvuyc/Jg/ynK8S/90ZyNySKoab08x12HH3znG5/uNTPLuNmvz6s7OC9xd Tulaa0LvLK46nPnZ+NjtLgerMKoqnh7udABz8NM4O7vRUAyWOD9+epLRgRSdspBiOGE7csB6+FM8 g4c7S7MU8AsevsA0xsYAk9lU4bMcjKxb8Qe5iDVRN0+R6pzLGHNJ/d2qlmT34FMaYiBtXMlv40bV 1EIGW84GLEr9262eI3+qGxYbQDH+6joowJ80WvWkQIrwqTEx2e/e7GsM9lf4s2Cin84GjO2lQxsh olHdzG88LwP1t2GxLU0ECnuWySIotqySil2HuIPHtFjF+/UUQ4fffGmqfKPL3IyKCnBbIm1Aamgf Jp0SGLmo5xrNWmbD80CTOJVljSxkFBhgTBIrAAAgAElEQVQJXpF1YGJu/Dw+o5wMrr2Af4iS0A7Y 7McjoLC9sF/etgK1qQYk1qaclnAbsmVqKUUudBsu6D4tajjAbZJong6p1p9nXfw0HWK+/iGuX36J 890PmjjZ2bS4s46ylSleXyxUqm4O6vc9XCoLZvmntDxu5aWnydxChLlOSuJbi5/V+QJULJw4QtA6 qliFQxUID8FuG+zz0nI8kNyNxz1twiwmbZdWvKaYqOXNVgdMTe0OP19UC7dC3NwC9bMFGa7TWNZD 9LNrNPj5q8Vi3D+Riyi0CGG1MK9r8BpbtzyfD/EmF1HEy9NYVkhNSC7HecJVL1X4munbah37Mxbj nk6uwNTArUZHimk/5bTcpo/+Hg45YT1brK7kaMinOa0X5ULveKK1qlgsOR2UShQKCqETXRz7s6oe 1B1scpwfUETwdcES9XsrU074+/k+MjHs+tif0nCSw1cxbQRTFDy21rBMDqxkEqryNyP+brWKI/SO 7GKwglrK+8zr63WXRGhtThcOSmRK11fIsLp8czglO6g5FJ55XMDN+bVUtTBosXaQDThr1LZQHosv k1lsDm30i7Hg2KkpVFs8NIWO8qUWnmrx56RL4+Fnu2fAtjRyZRLLxnbpzu/R6FLArJow85Iog6nm 0jR/mtYWt/QZtS3GbJARuAAwNoXLqFNfsMax7cnDYinpjbjUR7y1M/RT+J0TfC1iZsFgw2xyo1N3 2Lyw5LPSaCaxxC1BZT6FciMmr2MJqfIg/BU5UxHXesOVVGCM/DEn4zA8ns6ectYza9NSI4Zxmrhe yU0zXpRSquTI2bTPY20rE6hY7Jb6pZnEl2UTd6vPMdzdR3f/U7TThS4VbVYqgAwVLfohhbpJS8aE FY+pQYTWQoAUp+tqTSMVGClGOFqWC6MQesWNUgoSVeJUnluLyvHukZUUVwTSGQikkHeXXS8GNAJY fPw1raz/J1VvtuTImWRpKgADDDt8i2CQzLWnpS/m/R9mblqms2oquUX4gt0MBtjId47+CFa1UNhJ MtwBW/RXPXqWqzEYUlRSNYAflt0qOdgMvlN4ioUPLhMcJioQwvFYEqBd5RqzkcYpAr/3gz67aBTp bMom/NtpH7/uPuINomVHEaRrhtw51/eAksJ9JQhjhQPsZBrXDxd8OiEKlhj+qF2gErC8KdvygrtJ 1J820smSF/aEw0daf2tsSrufCpFNZhsYEjEBl6+vhU7HFvEsGgImlYDWVXELbh2dR2GRShE1StkA azJx6DHjPhQWheamoyy4GgWnpEfjxqBkcxXhFPHL3w0xunM7xcxvL/G6c4AMzyg8OKoCUxbvOYVL Hm3QbQD+ixdchqFIupVGkFmw+rvznx98Uwa0rkbRP5tpNOJ/c0NFQ2A0Ucm0fzY3waRLz7r8eUBF OzBYJsKop0qqkRCMIMN75GA5FnuX05QH5nQ56qHjxqn4ZXiowhASYb2T9OjQ2GTkFs1jkC/cWALb kf4+0Bw91oNFTJmizAiWOHrDRfCn3CpEoXIkUon3ttsnCc5V1LexqAOItQE0x/XceFuXbf+k1ksr sS1zOb5fCp/E5YGg0JluyvHUxvv+FNvjQQULHEO5cOrMGEOR3ngtw8sivILiACH1dDJQnJ5GkrpU toBmvKLAg4cBqq6nw/jH8Bg/bB5j+Jd/agzkpaZQ4d1eQkhErGXFLp8Q0zd2J0YE45uMY30VoreI MS5jPRvi0W1//TjGAfGyrhNjHJDCVbHsWFmLX5WfV1bQkxyjx+N43R7kGQWeQrNN90IhqetpTAZ0 PGN5PPWNFQp0NXSckugLDI6opCjDgZRT3UHAWnSkdclmtdI95/tBCNWzDKm2h9mPzIe8gEEcDhYK f919xC/br/G1OcTh0MY4iixlre6a7soJNWeFWnBQO9vSHR+d83h4i81qqQJ7PB80doHl8DkUzCBK gg8oheoykrLpbRvdO/hK4GFsRt05DrVNhefGhr6EX/A88W5RxLjvbIwBwNeJfTIlLGdDsfFv/U7P 7Q0GO9SCE8EY7v6xfKLpkK97vnNinU+YpAZx3DdxOpESf3NjMqk0nr7tXjV9Tcb2TqNgSw0xZaHX xe+ve/lfLZd1TDaLNCsEKhnE9XyRj9l4gg06nCtjesLC5jjgQquoYgGtRAc+W4naJx12K4f9Pq75 Rfllpuq79WZU9IzLC1zFjrmV9b7SYrznMVAJlcwSBG9yMs5JHCnGCKpytnjy1eahtvpceWnISBhV tM3zvKsUDv0u3CEymFX+WCYC8nlRd2uDpPQmFxntujgZ7hypXvFZFEQ+K10iNxTOC78foJK/CgDP fyOXCgiM0BqW1Pq9sLVDc9I8vpqYQ6OtpAS0AJ2wr7sYNSO9EHC6ICgOhh86ekR2TIEs35XtmvAg aQHdIsu1QkJxs+Ptj2U5hTazbAdH33E4dhuMZfIln9XxuKjjh/oWf2vP8TBo7h0J3RBCb8iPDtt0 Cg9Aqn9qSqpy/Ngfm/gdGkV3ViL3j4+P0VMYukYd3NNyFewivx228XE66QXjcEAy88NmEy+rtRjN hIsoxISRiS0wKconuH3IZJKLQcGFj3ZmE3qMyc1pR+Y1jfVs2mdspGfmhhPqiPvoTqsWwdOZjHcV RBJ+Ja/p2vjjsI0W25QkVRKtJhqNnBgmcgoliYYwXk0cKVXjXXGQ7EjBqN3pauY5seoigZo/hPMo tIN3ieyNGcmlggOWDrNmEnCyd8kcIPbKkWfWAiL98ghZ9KkQgDnkjurE2IZTeDDnsxedzQr5s3Ad OUChuVDElLSNBhU3XaYJ9KXc+0w3FTbLcyDi9iVmOM/WU3W84goylsuqCDtkChHbv4lMC5w5WcVm PY35wnmkx9Mh9rudniekW1xD5SQMR7FZzGP7vo9Dk+HHHKwEOWt55o1uUQacDo1JqBCES1Q9wCGz u5JGqNpaudpBwCJaB1PQsVgPV8Ywz+AqPNrwDWMCxgQWBojKpkhgJf8c+Q/cGYN3ckosxlF0DUVT mDOvtmaJfVk6k2FIKpQUPtbNBuVFZ5Bp3Z/Wh/nfFzJfkfTQSSljkRMaIFk5cP1dQybL2bRqcXtq R0fJjRKDmkrbRmpPPhStAy7HSGGacxwEjJoTxahFIeI70a5LQX83k/BDZj5PcZ1IDAhHTrZdGmNZ iBA26xfWTHfP/vw3EnWzVk4LFfA/mOufZqP4ee5RcF79GIPVOi7DUezaRuGiJNJ8HE46WLwJTffT TBnS9+Vecfnxl1otY9+AA2FJg6kiXfMtqo6/OxGH4stoq2IqvImf4ZCBSTLQL1rL55odNT5xaAM8 k8YxTMmRwzv72B5O6uR46cx4/s7iVicNaTi5b5go8FKD1wjsZkIQcM9hZ/SH5xg+FgX7rM2Cg2IZ U7huHBBwk1iwvJ8POpRQCYgT1iO1Ym3fxZnPmvcK7V4NbUXvBZvCSgsmknbosuJoDaolbVZCMJqK H1d4aimn8oGe22W8BUWJz81sNRGORiEvTg3ABBhKcjgxKnPoLOcTe7CXgN/EaKFoyDmlnsRGXlTg XN5Uoplkkw8Oy6GpRG3um1wWOsETDoFNJ9oB8ptBbA/YyyBbck7C+Or7zpZWW0cgidk0nh9Xek8f VjPpOi+TaRx7547qsITOs5jFelHHbqcB1aMhHbJp+rlYEgXFJDyRK48HFS/El2otRySG2Kucl8eY yR2A8giTjgecajz28rkagp8g1Iy7Kyg3EgdKxsbioqjOKTdPCpYUGa5TxdaM3QNGWykvKY0A+nRw 0JNdDMyc0OH/Jn2p1bAVEsx3j2ylVMtrvFcXVEinkhflaAcYzkvjQAhTBIqDJ50cYx+g6I0TSY6c nTylxPpFOItvFsWQgwVeksamYjaYTqLCzR05r2KaThMefTN6Pu1FtPLFDE841Ewk12JG13Qmn3Ky 8TNIC36ej+Ovky7+NrzEfLKJePk5jtO5NGQE1b4dz+pqzo0Ticqmt3we0y7s+SSR6jTix4ehotDN peMzgjeVRBqDqugSKTzwyfhzCjqA9JfcJ+vb7PluNb7AKH1mhMxsVfk5FHxwEv5+6w5aSrDq1xaR jZx+tpzbxLDmeiIFEZ5KUR9Vws2kSTN72aZyjOkKyiByC1tgF1RUBhwsWJi8ikbwEcdrKz/3luCV jq7pGqeuiTMx97n4UEGkc5DrrrEW/oGe8Qr/LWvraG3VGFTW0OogldTQmjk2Y0UyJf2qDsrEtHgs WL60TjpXGnvX2Xc/yaD1eB7T2p03PuiI7Xk3xVjn6UpZFlMS0AdwgxJsGLemE5Fr7RXmaUbwChxL Mcxt32MzARxgeZ9xu03slkUWVBze1/zzbEupIdCLwKA+P6+9jKNrJMh3impmGFdJyOzoiqCareJb Lcaz8DW2sjwfHD59KVhyE+DmyErlEo/LZSxrtH3eVpEEwvyseRQpjsYyHmybq2mDxQPZ2P6Ym8sZ yks9wDmRte7+pJPClKO0pi3sX17IDE8Ql1K+5AX8vtOuHFTZXqOu57K1kXhUxEuTCItWzbIITrTv oHSW1PQe943mImh5kLYurLuFPShqzMZ38viigCCdgQRKMediA5yOxjFift9+xLk5Rde1egj4GSzS wEF4OcVJYtXOKGSzAi9Vkzskvyk+A0UvSYDjkXPzjG8AeNaOda8T00gLD5wfKv7qbLjI4fG8nMf/ XNfxfx3/K768vUU/+Wds+y/x0V7j17dt/O///LfwCz6/0nt4Keha6IhE2r0K7J5PZ1EvamFCN/hj F0IBPL7zDNBp/n7u4nA4CRP66eU5ll8+CZP7ut1rs8o9PTXG+0yMHMVsOI7D4RZzRbGzlTapdzLp YwZOhJxp4u5LBoK4I+z2cf3oJUz+8rCO55ULlv3lgQhgl9vBgNFnNHVKkUiuOqyMs6lYieCITOsm 8Byh9k8vD3oBf//Yxusvx7gMCPH1S3xr2VAxKoKR4knFoYfjgIPN0JyS3HPUxmucPmWmKYzqqV5O uaWyrUPWgmlhhjw4VNV4rA9BrLZv0endYMlSTCIH8W27FcVFmzmF9OLeAXg9VHdCweIsL7bYPPsk aEtONbGCwVAD3nCA/xaHP6xW8bC2Vo9uX1pZpiUoBYJnGj277sDZbnOgc/BMTbmAI1lV8fG+i1cm CY55asS4F9a6233EejWPZT0X9vex3QpspyyJQS+yr7tKngfldfKiYP44toLEtta5tHpcLDT2sS4G I4LLQYtORSW2/ofNWoQ5gOPThdU2IJ4dPOmCOF2JEpIdSqbjstrHwpZuRmZ5LKoHOa9r9HIbTEW+ 9O0dn9HpI95SiHimtbRGtExpZgXM+Jqia8GjSQSVlYokLuUi2EPd6TOchrXGVOX/MSerPffIYH6V t5LiEgkY1p7Mc3t6bOvhT1sTxRfRadwASV38KMTKsZG1BxQMCzcx+esm4GfciP4uo6CjpNvjY41H WO1mB6vv4ANBbGO2WzqJMpKcdbkwGZv68WnoMJbVKP6ynsXfzr/G0/UQw8U6zp//HufhRJsjJD2c bBrjcTxIX+8LTgOMnJVDIsD0BAT38Gfs9cjKmedAfSuVjQUCsUwCxRmVex0k/a0WkGs/b0MFy8Uy 49nd3bLEkS228iVxTcCjiQPDYxojEz/T9tYj/gORaMGWRlsWATat42WWWF0+Y/bVh07Fs6XcAG1L jWUCQtPZEWphkvQ1Ps6nGOwQ/N/i5eFR3l2HSxMnKCfKusemPi3CGYF76BoZUKu/3GnRraHDRB/H cyP8TqTOVGkkp4g/hw1Og/hcdkGWZJW4ejk15CFevPMptHhJvW33wlb5Pqz7KVYe3XjJCVx1keQw vcdHacPrRCdNQ0ott/YUPyq6Fg5hedYzAt7/O4+E+tw0B/OZlQ6IwdsmeuUlhrBFhh8Kyuz5Idbr lRxgv77uZAmjmD74bGmMiPOGeJTalPoA42espk42RyPJtSyZAcw4fNaib1XBWownKjQSbaq1Hd2N +TVLL2cxPg9idzjqw4vpLUDQUosSz0M7WUIevdly28+4siBkApasZCyOB7v+aUzSOjUpClRnioo5 RLapuZvf3VM4vfYs+XvFmtg5cxlDm92X+S+u4ta8mbMkLVwKe4XJSAZQeD1mk1tnBqhogEybHHnR O8Ry0HPSLQQoq1VPyxB/HsBvhwewoYSCTJHBpxwcgYJ1PGBLzMZqqNguQmVZA3MtHdkEyGmMUbY5 ell4qV2IMzHMvJXpJJ4mo/hS3+Jl+6qOuPv017isXsSZYXX/tj96fNMm0JiZN4Ty6dD1xi1C8eQj f2/GA8lw8tQrpM3B6CbMYRkA4rxstmBVWIa2Vq3xqVEllQR2wdoeSS+XdtUaNSBXsjBw4VehkZ1N CofZPqljsVMBPlaj4cF8IZJaxJa3rMfxUh5/KKaS2TAm4oHV4bNub34cAbg52loquuwm9vi2Ocde FsleyJTsAXf4Capn6Mq9pOSzrzSp1OxR7LBE0vdkiXcbxUy0BS8xKObXfixOoDbR0tNCgTE5usiY 6HjsUYfhAD5gcAtTu5qHsriG5X2QSSK4b/ffPP3tq2YBPweXFSQXLQrUyV6ucuhQHLDMC8y7lIdZ jtRIlUQp8aVT582zzTMKW1+mgbX//MfoEE0xAM3Fgbo9oJbUEFNa2Dav52wwOXRu8cf7h+4vn5XH iWLFc+QMxwyh4IaoWIwxqxvpC+jrpjvAbYDxPKcBVP6V7542Bz6VuXjLuTVvNuGybARpDFiLHAh7 Hsip2esZaW2wkbRjVsG2VabdhDFPO6+RSOtVs6d5qOXGCfFM5FMnfBSrEnViGQZbOF/+52ncz8uB NkwnpTcjSoJOHaDmfZ2s7q7UdicGwikhqREnt+gYZkVzyqGQN3jaytZFuErqcTXe5vaPkYKfD4N4 uZjrc20JM8iN4Hwxj1eNwDemZq+JM15KRSBtevgcxuhLYopxQ2Qdz5NBPA5OqCmif/ohmi//I9ph pXBPXAZQx7MyVnDofUMBBYMROV0WkzTKxQRTEg8PM7zrWXQH3T6+1+gWD/O5ipJTpTnJKRYZ13Tj JXBY5i+/fou3s6kYL5uNdX3paImTg+LPsmh9HM4CkuHbIUfhRWA8UXipwOpOxRc6wWY5u4t06WZP 4C3yZIsg3EmdKWMpXCu0gPuzC146qYKpPC5msVqs4v10FDsfcbQi2/jzRfSdbrJyCyUyXDCGlwN4 kgNO850Ju0CPC3XvyLN0uUkLex1CHcL5hHCHRmNy245iuFzEVV0+aTGtv0eMZQTI5pJnlAKj54qC MfJnpsMqoSV0qsiOsq7oO+ud0nSBJdA0jQB8jn/AAhAFzlIeKDDe4l3lSXUpBwe0DP1vW9GAdYKf QkZlC7xVp+v4OqYGDnae71t3jivkVZ6x4cRTUvKxICXz+UTnADucjeXSAIbI+/rr27sspnkn2R5S H9gq8wyyNVXBcrtoRjoH77E5qqCIa4LJfndMXAOAPQuJ5nV3EdLtDYfx9e1VpzSnC7jEYIiZvWkB JxJvaXkleMWOpXhY0314O2cpSitmruRacm00V0Ux2rlm1ziQ2x1OOwtO3Qnodc8byfcpnvJ+Ke1U 6fBS28OKrMq2EPwNCxpFdjvCiwovmY+2lcgzvCCQX1fnxGIIffWgUiryZXwTRYCxQSaFmJ4puBUB tD2kCKXgUIA/wwuqpGUR6EzaFEbGSM6NlV2I/azVTvO92Igpn9CdpCde4xwk6i7X8xjWozg9vcR4 9RC32ToOh7OwmffDQaPQWFu+gRKD2faU3Dvdz2hjOZ9pfe+fD1aTobByf6WrtFhWbpTJE6NAwCvT PcN7HfM+XRuvqp/Wq1gvV+kkWcf2eFRmH/f7dmv0TCzQyqljmIgcqSQaMCIsmYEX2M4hWp7P9Fkg ijIqsRTydhXvJcvFpLoAoM/ADI5zoTAZ2MDXo3hs5lO5vnKAEcf1db+3lTJ1CI2g/oylKt4zZpnn 4GIdryTjaZyGjSyS2zO6POZIk2l5SYnAOp2PSl+SJlYNMlvKm5jn+J6zUPAy3JxAuqT9/hDfPnax PZxNvREbfuAtnjrUkg9p6MDeYtgKOSEKnqTcetNuRwuoDNklXuyMhlANB4eSaQtEcDmDlMal0VRw 4D6dsLIpgS8QrHEdXXirWWHYOI9G92Ggg3da712m8sCfziphoErQmc+jk5tpFavFXF5qXGTecZF+ LzgA53OFcaaSmoYxTLVIRX+jUIXcToDviHA5Ic0VG1xvYaZjQLnO0dQivwHMgzuxvrRrISCk2NuM HrS9wi0cP4X7A883WjF4F2zTeCuYq3lRu/QH+vbhoue0YjsgOkXHp3/ZaDk5Ob3e07ZERTAJnxJL Jyvf9ihm5JYtl9KflVIzFDO3xA5zaphgaBJnsYuRg4Ra98weTFEunxV8B9tf2uHDEZ2XI7k3K8I8 EbESnwa36Kz5nTbfImCPUd6yes2trlRdCw+cux5DTmWj6O1YsQiTZINrDCbQnWN+3sfg4Tluk3lc +mG8nU7xhjEbbf+Ye2TLneInLtwot6h0J/cU7RJsmyp9PvvgT7+fFwXpEE6x+t/iylm18OPL090/ jOvTcJLrxw20kSIcl2vGM0Z3ktRU4TnqqKXUZ4njayT8hN8HzeCIT3gd89lcnlj6+WljDD7FQcBI tJeCgQ6v0zMK4M5hxKdfTir7No1tG/PH+1v8hs/V4aQFAwsFTnm6NHAUAGsrNvxM0R2L8wSxleka O2h1DkMTisU5ZKPpsVXhG+c2DtezpgJZqPQhvAczEjBBDj0KK7Qq6BNgbtwzOraCTU3g1zHmctCj oJDr7EWseNuo4lvlDhLuEhQURjE+Dz9Xwm258bLdZJliKgzeVeB9cNtKRiC/l+2gDAvSbwyahG2j W+lZhTdO7MOOyQG6P7Cxx4dlXEgKouiDheGKkXbnAthl4EfBr0TE5aXDh4yiJWy8MoZL/qeCUEpm qRZLaaym1yblKGKp0qphbQs+QUFBOgHeAsCKW+aMKCh3MhQs9Fc8+1zs7bRWmghfzNY1ZozzOyYI UtdWrfPnnYdGioOlBXwJscSTu0QoJQ85zOyjyCAlfSSDMorfUL5qhaNTRh5hUSpE9ln3RGsrFwqv 5QmDOEFJoAGDSItmsrie5p+TqUTpRNJWxnSMa27zDHyDO+CzBJj4sFyJ2UyxlAJdHVyrB0WdUsHT 0g2V71Csqo2JDL6vuaX4N/aHRObuT6U4NHrbW0y6Nqa738W54r8nbAAmsjGVJKZSoCkAYDJo1hLU NIhsGgJjl14GuUtmpBvdggp8Yorwo6QC8OHgU9wSDk5RbTLlAkpgK9ynq3AsMatFbh3FkhU2CaV5 YNK10kWqTIDDMHbBtZJG1CBsc77oMw2XS92/i7ovwwY68SFUIhSGB8cmjOvFqMpYItugQTyuFuqs IM9+/djF/3l91UELg3vMJID+kI0VoDXZgGkOWA5Gu34kBxDvNIrIzJvXj+NBhTHXPcLStMWm4AKN JGbEiyyDgRFFng3k3KaS3DNlLtI52WaYwA7ehwmFja5bul4vJcrkcE/dSaNAZR+KnjKOs/hYYHMX 3TNJt6AlZPqOdKp9H1MqrDh1jpfnMFGAxRR5HGTrXoUFVw8mDueFYgwIzmizTxZ2i/UytjunoQOn jCioGR0I/soYz2i7zA4VOgn3Ru7DMqk0Nt7nMk8dVr7RlSOf3FoKkO4uUSFirhlJ7JYIY1lAOWt3 yRKo+hMT2HJj4jPS6n34HavLTCMSpz8dhngmMsIHqLPY2cXDvBW+Ph7nn582ugkIOXHo3J2O8b47 CtuAO3Q4+QWkesv3W/bNTrHhO5RMxJJOUgiad/pY8q7YiC0QeIJVtePojtu4VYOow26gijXPwV9+ XVVunBQEmxHhOvmhQGQEF6eXKBcGcw3sOo9PgG2FxCLpC9m9XXLco/CVVGt55lOASqvOCzCgiPPA 0eK76yijIkUeRrKKHbY1iWMc4ZR1UEFmyo3TunpKkfYWVozyFF97s7pQUOuZn2PNVUTvE5TiwJbQ SxJ3hnpexFmz+LbYInPq02/wsOM0ycsPqE0x/IZxobzLeWjp1M29Ksm/XbHn6eyLBOVBGFFqJO3X 4sg2DsW3w15jyxici2cW3ORKhzyIQxotqutJLJQX5NPLozrS3w47JTTv0EwykkOiHdXCWtTF6DAE DKc4uGApVk0hp+Ctp1gs6GQM8BMse73VMUgPM9xADuerihZWLn1fxS9fv8XX7UeM5MrgF1iBEeKJ mZrBy/uwWMkbjSLFs0zBqnhuU0JXcgEY6S6XRs/ruO9lkIdGFBcRkpblkSWNJXpQ8KmzYunpIqFG aMvZAewfxdoHk4agzXOjZ1T25eQSwgHzxpEC05/PGivpzP76BX6gD6n1iTzDaxzAC3leLjeFWzgw 2JQeuiZ4Wny/YSFnS7MItcGOvDI4HNiGRzY1xSJ5NvZ6VPhQd40fnx5lz8rDJGtSrUlcHJzXkAr/ tH/xli5HK1p2kH14E7kCp240DbwcK/ShFvDFpDm8Ow5Y4X+Pw2azR5zTpIq1JCZLcVAoXK87r3fZ GHEK2Zs9qQBiY4KXFW/tYkAT0mBpI5ayHToIVryU2bLRtAzCLb1GgeJgr+LqTsORSKZMmI9lcbQk SbCoASnbm1JCTtdOXCz+UvHRlsPbUDlfpKeWuznGY1tDg6/EJAmUNikzjgKnDZyMQ4BtGz9nOJJz woaOeD6Obv7XiPWnuA6q6C8w2ftYoOtUcYMxPhWxkIf6dX9wBJt4PRmBniJon7olmcXraD104udm RBuFNRnXjDNyl0gybvR+WWapRSNO7stoE4vFQgRWnjh5M6XNr7SjosC4Y+FQ4+Vorh5VnWpkQi/b 1K98xqUF1wMsj/pBfFqudI1hqx+vVdRcR00GXdTgLuRNTsfxbbfTPwNkBwQPisF1GKObsTAIn92A baTlWaM/aWRJvAbOkDxIsVTwqnWLnGoAACAASURBVPB0sjyI6yhhr5Kk7CXP5hW3iAtKCHBa7H6e 1rGk08hAjktrVwLGNZYyAPi6voIE7JQbaVHEYcg9unGdcEtYzh04S9Xr+3ggvVnbWGNbdNKaLoRr 2QJGmBeHmd43v7+/vr4Lw1SOKA7E6CPFz0QjeImP896aRkZcUnNOkId52V7VLUtCM5tFe9ibcd/7 z4mfmPkINOlLMPDawbLUkf/87asOHkB9XIZN7LbkyEn2dPOZmmNZjhXuvJhgU8J27lmAJRCVmCOv ZPvWDoU60fUTzVth7uYvTm1ORoN3Xfzx9TU+Pa4EMIoVO1q68PFy5+npBFqAfj+UanEV1MkLiQOl Qwdg8rI1kakgpENa1fLfp1zCo5UBSgHM8qOySX8JtueGO6nFXcG0Yhng9bVCCCSP8VgmNwvRIizY drAsbbjZ22W5wHfSyXqhr7L8h8+gxGDwDgVaZtI2v7vzaS0TNi0QiuTpe/oNWB6fURY7ickpml5j gWkD4CfLZhtzdWlVtP2PIh8W5wZAXUZ9Tkjqq1jXimi35xWYJeVUkrT8Hupg4dhAsIWzlbQX3ERF HkxfK8m0ZO5mK2K5ZyoMlu65le3zhZEhhd2MYmy7ks+r4qBnzx7bjo/DDUKGgO7apEstEgvRAJx4 M5bcKTe2+D/NsPvmHsC5onCasT+bYNMLw5vxqIvfIWGekCft9AxV3TAmt5EE+erS6UqcoX7fqDq7 AB6Wmzz568s8Lwms6oKdMMO6XjKw8VjXhM6mvcY9WmszX8bzehULqQo8mcD6K7b3JUVcUjTpIH1Y XnnBcxTnr7FkY2hzjedOBniJTURWlTdbBlaoQxf1wjgpHY2DTJGmgTGnFVBjysdUMA58RUMOFF7O JP6uoGCwbbA2pFgsPtpzfHla6mfY+HIYT6u53t33/cGkb+karzGajBQhF7eDpoWfSGyqq1j003hY z+NyOLgo51QExKIwrKI9lnOAsr9wZwB4q2RlyoVHAGmA2UwdvhwnPD+QbZMMy2Q1wtx9EiBHOCWW KRp9RpUwrf/89TcDt4lJobtCSgKQy5zLZ0GYqeoO0aysbEVdwHK2jrlAcsZJXiLzU+RPRUy4UkQ0 fHmUS76WNh50LlrTs3n0mOHo68Qg9NJWeomIkhIuQ4GQ6jzxr3wxxajOiHUjWMYCKLZc2BPdpCQO aU/cfB/j+LlgW4qnl22MlxIUYm0DNR2UEdSqAZor+6ynPCG3dbw45lmnrQ8OB7uvMb/uYjBbRPPy t7jQXKio2F3yenPRkkFiNdD1XvFSszRIw77SYZUFhuU/YCRcy/SrVx0E6G7t40TnCGP9Qtfrzpt7 Qe/KC3HoOZjAK+g0wWS8XS3cup6MPRV46+goymBvFCK6VWjBYykOTH1xBFRRChD6iW0NBcQjiQJ0 U24muRChIrNJfNo8iF30y8e7AHYi5XkGEXHPoxZuZULyVXQO6D9aTtBBylDR94v3Yza1yaDAa9Fz nKhN0WIEpsDKY6qCiwUh8xoterwbI9tcGJo6K9Fe7KHOdVSAKMsBAdAIgk2Ydkdv+EHk7PRsGyvs xBSSSTuSnQz4IT+H78JnximV+8f1ZKmlkJkMmkFi03TgTrik2L6Gg0BCbBZRJyAA05SEqemd5y8T Rm+3nWgSb7urxNCA8xRC4VNQYuDAXa/x/rEzgC+VUqXAlGPD/b3E509dPK4X/vM4jB5KF2nemkdh 484qWB/7s24eNrlchM16qTae7dFstnBl18bOp6xGHwDAobVGvECckFRnLgYPjLoFNgL8gnoa//jy o8YdRJT7w0H0ASQd4AukfDCeTLBkrXfaEPA7eJFJG35mGyEFP75KJ7F6sZF9Wi30ud73tQouraqU 4jgg5Ocl2cXrYMasJPilawTfpcSM8aAVXy85VnLyqPN0SokV736AvMhiK+eNntKqK05uggn8s2T9 LCuYbGd5+QYXkTH5/wN0q7PELUJZhqY9wDBXGpA6qF4tOcVMrf197DWWJg2lPstVxXxGnDoFafkk fynGJlbjAqJzdIQT9vVjm+6oo3iezeLb+1ZeVPxccV8crm07Z4qssBl3EVRidcZ45J9O2tThmNDC sYJMK+YzjOWjNpT21gC8H8aBF4TtEgdIerdTTCHGAvE3rUc39J27jN7S6MvEkdkCztZjcWD//vmo itVmLSLuGhuXJNF+2iy1QYTZz7VCp8b1fD3s45ftNt4Io6CbuPQxuZr+gAFfCRBVqtPNYz/3ShhQ Pge8dQ8r88Mo2JfSpYB/SjtHd2XOHO4nPGe8wGDDL8ulqCwU393uIPKxTAPHFDj7W/kyO1iCbEk2 ffKXT+H2RWoBR4NZcMAza+JspYPctlDCKfl5aV/T9UwkTujm4Fys59L7lowE+VxN6Ahh1p/lLsJ3 QphMscCq++Xp2bALDYaaFYiwCVMgxE6L5P3hGs8PK+Ge4NKH/Smu10aHOddKnmjYVs0msX3b5fKn jbcT6UUchhzaNCokc3XapMr2SLmE0g/ZiQGcg0JyHWNc527B406xGymWK94Gitqg09bsbP4dQKCM 7ggwTY3gdLVIgz4HKzZwVuA+iU1uMigvgbEBXzxOL9pIQD0sW7zadsvMWMqsy+9ifp9d7UW0A6w7 t1Fnu+vILzs5Kj4pgTvJZtTZ2LKibc4apXgglVMHyY1gV0UZWcpR1vQFf+L7slBgo1EM/wzrwd1K 5r06PG9SpA3jc4j46XGUa8P15zrw80cqYvZt5wuDg5la4XBWWQGx1GDDRPHQ70Gfd4sx1sycrOvn GPIwXRsVZwqLCHjNRddTdikKA7Dtjgi5agk9OuOoyjhmTOa7iZp4VRqB3BlNZ3PjJBTu5O5IQkH8 OKx9PNtVZLxhAvDG6ZLug9FeGA9aQTzNm8Z41eUmQJe/OH2lYeX78Z0B6KdTAe0SUmfxLl01h9V2 ELGa22+qFnsa7/Zz/Pbxoc/3x/EgmgdjGkuCcZBu47QaxvviUktXXRJ4JPPJLSh/p7jNqlpSGMz2 eGGhczCOSa9I9FVzFZUEvhm23QpDrVcqWDzj4DrFtULBsRwMqVXlPWnZiApmyaXSyHSji5x3TWot NkPADSwV5MV1tIcVE462f/ke3UYudLLO03QJYds++ya9ppMFYmTwLW0d+UzY3FhUDg7KtYWk2sq8 zyZ8Pz4/aNRGC1nUK/xvDgSlmFOw5YsFttioAeC5+rRexMt6Fa9fXxUYLKsBUfyqOLUw+02oZoKQ qaFQ54jKlsBG5lnLCl9Wu+cxhJe9hAw4+4+S4kjq+bQTK9cArIli4A8eLe0ZJJ5Nrv27zpgYeiqK hrd5xqo4WWSDq2gvo/GcbvJRwjRJjHM6DcrHTVsx5SWmUSAXXCS4bEPvZMcETk0JSMlFJrfQEfDv W61Rh+KOyblU40TKg8ZmHCuzECmCtniMO+BM9k633MD4gApbcqz0HXP1681apgAnhcSJK6YTqGBk KpFWzmAxTXu/N3Q+2EfT+Q0ptFhGEwoKVieu3DB6WM2rR5niDYZWHlAIKG720werG9t6OtOESuK0 RtgYxhZv/gaxM+Nqdn6M5elbJAdIbatSHiIqie2RwduE4dQ2H1QWAP5jqSUTdkJQpzItseQ9x/7S 6HryZ2XJk5mY3K9yKEjVUDRPubpXh0znwUHEy9rwTNCZO7xWgG01FGb1226nNfxbcxSEgEneoGMr ZSjA9ABeG3cUqe/SYVOE6k6KwlwQLBKpVJKRU3iv0Uycpsz1k20K0iJG8lE8LKaxnOLEK6KKulU+ uyZC3WOPmcUAgGeRJUbZaktKVvn5SwOW9KYj78DcxWuSaRnldDj3t3jarNQFc43A8yjLvNd0kter eXCq0IzatqTTPSZdnPRmOZGyYFDQKxywUXTS74bwSBZj4lEqsdsNAYeMeJSX1gRraB+ruahSYFov q0U80WjQ0aWbB1+Gw5EpQNpfpGGZMs9Ed0/NAdMQ6DzGpxxC5yXHE7oIbGkhjAKMZuS87HlNCOSk wOtKaa81KSqJH/EwjcZBmTmH52C95IPc9iiLzsGsFKXCHnYGHknEAKTmwaCs/9jv9LPBuOyHZBoD BRTFvbqSSxefHh9isWC76ZtMwRIQL+V+iR3zJovPYXEshYuRwXgQb4p5LgPdME6m14+tZSRDAO6J Tg6zjBF3Q4M0WEuxtEtosuQFyBaOEw+Ef7a0aZKlmIogDEtmbJAcLZk4NmdnJGpZMJILJXlzCFSJ EoJ2AglxgaQKKsBsFd1qFf18LeZwMV00h8svHrw6RjIIee/HJr7tzpYwwfyWdrFWMsoO8LwhSIAM OcbJQcwnN63tawBuKemNE+k75NaVwsbLLa1bNdQ2N5o2VgubwSnvkkLcdfG+28er+DzXeF4/mr5B V5h5ehQfRknGDa57NcL3yxpCEwkpNGNJguQzDxESV9PUgtI17po2PtomvjY2D6TbOh2b6M/YDdo/ qoyaFNA0BHP6eXLcoJBQVcoChpFO9zWXRniPS1upZQidspcygPzVFDwW9riLX3e1eJnCcW6gS7gz laohZUwCuy88s+5+7eZr/twU3tLU2NnpeMzEIhQTNWFJKhLyJBPAbUx6saCD6u7TAI3HBWNCulqN +J4KhOdKs2rzTcY1nkMY6kAUdJBTmgR53ttVF+iIjolFE+Er8qEr+kmlRZn9j4MI0jFkONNRxN8+ Pem7bAllZuNIk4KKJt1kec8HMbsbS1JUtbUW012yikZfqJ/lpoIHnU2W0oAvGicwo3Mgaiku3ho6 EIKKa5a5UR4T7LQyrTn/B7HdHwT6cROGKQ8QAJixTpJAZBgmLFqKh4IiYTGTSAzOBM0iux0b8INv IAkwrkQVnk1Y8Xqz41OPImkcQqEXfF4Fn1qm4Tw5+ypNWpuXTcfO37NyL7R9ApdhS0KWGuZjEprC aCleWirEaMW9qLDS/juIbd97KwO05YLVK9eB9ChP9wR7xyftYW45kmRHA/SZnMQkmYS8g17mVXyu rjHHYfKHf0a/AWMY321zGHUaxZfFd8tb5gvAVPlyE9xAV+LTneMCgzh4PXYEbUkz1fjCHb5dJyLW mofkOHNJh+Bz8fMIDEiyDddCBZyHDw9yxhbSt7XV7WK9XsbDw1oHAZ+LbR2HEcRSyK72UIMHNNU1 B1OiOHCd7GpLqOpIiw2u9nq6iM1iIZnNvz92+hl/HA76C9kNZMzLuYsB5FCkZzVWzzwH2FUT/lH4 XYTjToQn2k7FydO6J3TiFJWkCYC9pI+kD6EOp1nLiOQIkolA7IY55FrGTNjlCpbFqWCmIs7hdGxP 0WFwh1cVYxSeX1pQeEPOdTkc22jOp3hYLfVLKXLiPC5n2u7BUwTQBsrxRFJJdWIfNkMhev4reFNs k60SEBxEAda1NSTD6Lp4flSW4rAfKziVEbRCXkRwRY6WgAD8vIcFHvBcq4v4k0wwsEjPZxsZOv5r En/59KwNImMrYuePg6k1TE5wwcQU4MC4dvH14yM2Kw5g2wepYNGWG0wkR85VGW5JybTT+r/EU6ks FRLmd7BOdH6lZFg7m8wtd2OMlgBxbAawJmYDKPDNHCyRP0ffPYQAUPXFNapYdCqmfarXwR8UdyVz u2EcB40tMUakKuMP7b7WtADLieyUana8aArSdhcDD/OcfIL296ipzDnV6cv/ZvF7HJBmzDbJRRnr EW8a6aYoy53Y4TyMfC8JPrMrFZieUgWInVollxDZVMD74c8NTXal6nbJr7v6plLQGDHARZ4nffwQ 51hzcIx/iOt0kQAxD4hBXGEbSlT2n2FjyGd7OziuTMTXjDu78vBmlLwM3rjuGm+c5yfKDWUNbIeD YCg6qlnv/ByHPKpweYTyqAF4y1cSSpR8LvHz2IRyeiuNyTrC4RmXh3FMGaXGlboAVuqKYjsbenB4 axdxOgl6AD/hvoH50UkRGsFi55f3d2FJ8L6woyYsdQyYWyElA4Njc+qVrryu9HMNtBvrZKlEZ97e fdU4yOgS3VmmU0jJp0xPNg6FWp29P69oMipmhzzgPf6gjGApxPiF0qJKGoPUI9gSK5eRg9xBEN0F rJdtHxpMM9/F9udehA8Mlmfa4LKJvY20zHC4C7bStYpsoYhQBHg3dbikT7+GzR7eHvZBtjPiZ7GM U2K6YB87bOjAv9n1Vdy9jFgzl894rI0+4FVpbxzXqVkBklThq1ajOc7EKr4FW2zS0Cd8NyRJYGkj dawqWLzkRUDLdo2bMJ34JZRFsbxrOClsDFZuqpjc+YtczNzN8HAVzZ79h4h5Aq9It8Qi5NW45hFC q/fa+kRuFpokrYoLL0o8pYFOaF4Mx1NZEsPvo5qbJc58PosrraxWsQ6ysC4uA1xzTaufq/YfCxEf kfoe2kS5c5IqP0mdtMbcMC47BUkWII1HAQusEwNQJ2SxrGVJ4c1bjsJ2RDUeR+eobpWtTybzaGup a8jm0mA/D4akLhTP8TCe5dUe8bkexWYMr2kQHadScmzYuppn47AJPh3gMi8IOAR362l5ic/rZby1 jIXO/UPASgfIvbbHNtfdtjt/knN6AwXVYujwUm2Sk9MmL4scfYvDKqkosNE1dvXeRgInHDSWXKRT LWMW/8dzwAaWF6Y/HSUL8nLopuIkvFS/E+O/eVSTkZj0h+tJzhTvJwI/Ir7tDh5Le4vUuZ/wwnCZ oBsT7YJ/n+4kuj+ZlVn88+8+aDpNLJ25IqURlpkGktlicc9EfRHz3Vw7aVpFUmYxcJYDAqx83HcL 43sxqGOmqDdzyor9sl96wk1sIzSmeF7ZzIFLturYuF9K++F3wEtTKKufdas9TJhWl6IHlAWDpTzA QBUW0Iz4YFE57fDdmPngTGIiyPMHkVWcxlRx8DP0XNI9KluzjT2crDOjofXDWmTQLBAPpxTzS7zv DvGwWiTPikPK4ake56khTENQmMaCZBTeyvhZp6c7D1AmJMUVmYCeGftW6fnhS2B7nNIUroRm/tZf ruj4TNr8rrviBSAJBZBT1rQqZnY0FEifRvry95nw4ea6+GrPTQrxduucp5s9g7VFwMAeQJ8HF7fE aAfyse4fFvG0Yiy0R1DxZle7S+xSbY0gXRenktKUk4IBWVCia3g9Qxdxvh8nGIr/1XylTpDvVY3B hvhO4EqAjXRKuX0UEOxi5a6B72FuGYCuWMVS1fNMZGhHc5UcRNYdY4P2oremiLuM3bwIT/Nx/H01 jn/eDrGeP8Xwyz/iRGHh9MyiiwCVURpy8GF3ivVq4UIkCQjmccP46XEdm8U6/t8/vsWvtOaEG6iL pRO86poIP9PoTeFyhBaHWlkWsH5GC+dFB1tmC7QnEx7uqzZxdCt4qUFVkPxIQQxWFaiGwMs5YUkC DYWODa7TzBSB8SS6M46lpoN4NDbeBjlzyhgy6uO3wz5+fX+LXkRNrL5PSuChyNGtreuZNoKEU9K1 vTysJYzeE8ZwMs2EYiovrjSILPpXsB4J6HOcKksi9+dF8GUWPEJjqTggLg/Y4NkYQD5rJOaQFTib xRTnVsbuNNOT9pUshcJOZzF1Ot01gjJ6zINzggLgak4ef56FlG2JPUrq/kK5SGM/PncnSMS+c8jt eLf483xWObXerE1kgcXzrvvdD+MRTBQMm9BiBPzSYxIycZJ7gtxXKsIoDMsAC3xTXmGrzTEyG/rW JZ+Z3E0gnq6JT+2jDk2uN6wEpirGzCFFXcuGUYx6Nyny6NJYXiyS08KXuftWTs5ZbfxFSTlY/rpN patgPAOo7CZu5cqN86qemCWb3DG3bo+Noqx4iATo6cYaM6IFBQRek5K7NO0BHZvW9dmlqUvSds83 TpwTKjgBnGPzZgBWLV2QC7NaWkBKiWdJiGmSf0JrmZ9fWzd4Ygpz7ePKA4FjphxRoUhwoncxgMDI jZGYdaCoK4BB+Y+nHo4TBUKsmPdIadi+5EnESY2FBqkjnJZ0VbTAdD5sTT+wn6bg0d3IeXQk25Zi AaLOMbc02LKsJ6P4qWrjf73/f/Fc9TFcz+S7jxMB8hK6wCKG5c/ZqwyhuouVPPORnbC5u3TxfrzE H9t3hVFAKfDK2y+gnoUI8eZo0zEe5B5/nI56MSBjrqZ1zFnnQ59IyQiutZCDwf3mjEZk9wkIv8Rg PJYF9zqdLz/O53g9HCxuBZimI0Erd+viffvhrSGLGzhTFHQOOfy/51N5KV0GTpj+dbuLb0czqt3B I88axsNsJTxKWXgcKFJxMJj4JMcnq70xyH8/jKXV1LOW5NnEI7/7z9trvCgb6P6Fg/Iz4BdN7Gdv qUzmJgp/JSezdqBCcxFFA/4dKFDTsmChWeA9s98ZnbexVasI3BiENtXIi0wO/W5tzHKLf/+wmMm8 0ZZNSInowpd6R7iuUBGUpaDuDy98nreJ5HiKjBfPEj/9sx00ZCF+i+3xD00O8osj2ZnUD2yiWTxB JRpDDCb09RBv7wfDO/yFeULNcsr3ZjZnkZULjr6P317fdDAp51EsACR+cD4ZeScxFGzQxbaA7pLH 5OikAgUzKkWz8Se+ENwPOTuwkEnwN/NlXLDY7FwAF20Nw8NGOy5LWHncWNTLxWI7QqovDz1+1F7b Qsf35yjOEcJWcL/MOHsusl1KzXguac3upKAlMEM7301FlS2FigjCX2t5b8UnOx8A2bfwV+FLEaut 1tLGgo75gvHsImT/IZi81nqNh+dM8jWxk9OIzkIdUqZay65Z2JZ5WRyo4EO32Sy6sSkGtgN2N2Ua iM37xHvSRrGPl0ETf7/u4stlG4OHn+O02MTx2udYQ+G26oD7Kfve0UDgPK11ScG2c2ZufMFjyjUG s0iel7hNCgJwxyRlAONT2yTjnyJ5EUh7TnoDJ6MxG9vqCsTW9RnEwoIwvWQPsj2pYnwzRQWcj8jy UgA8PvdxHIJ32nudz8n9p7DRSfASsZaHEvG6ZwQ0ERRyplOArMKYjmqNUhRRDky6O4quXDdlSWOc 1F5qHkcltUn3AtNUlITrMM8hqTjGd2ShzJ/hIMfUkXsrLM64puxpcCng2YXXpTGySvG6cdky+rkw ebTUM67k9e8uuyqaUpD16pJInhHJmE6sMTaohOikR9B9MqZxMImSIm4kzzHvnURY+j0Kqu1tNy3q Ae6v8KeSx/i+31srS/cEObjYzLCMyUxFRlYOlHFv+xiuEa8PcWQ8f7iJihysRCeur5116c7IXuTf SXrGe617zbufARwpJeJ/y+tLBQviW1qmOMfDD7QkKjlXip7HL+sGmlV1soiTkS54d1tg/yKAPvR+ ReflcdFjp8akymQ6AhS5cXQ09llyGGZR73NyiFjHUiAFoEXMrDY2uVEiEKYtL2JW0QPmdZ4+FGIL vPmi8IK0EWTuzw/FvzcXLMcadmKJ1/F3RW2pcAL6G9+QYR4WO4haM4UXk0MeKHUGnTWLC8YCTm/i f8HY+E602IM+FszlteUo4wnXyI4PZRw1/mG+FxSMz90ufh5sZWK3/eEf8bH6FG/Y7hxOaXFqrSTF nwdaLO+5Q2PlH851Arvje0JFuaIamMb2YNdJExHZjjlFic9Syd2ycuI1xEDdn1u0bN26WxwqliBD GdLpO03Hkocw6tExUvAYhWS2SIeQViEqPmNCJwym6vjR9vSihxG8jeXEdXcQd4niB/OZjoHi+Lbf CmB/l4sAi4WI6jaMxWQa6/kilvVM63u6doB9Dks+Ow++ns2zw1ShlPBC0zXofmdmYpGG8VK3fZOf 15pIUSkIFBYLweOyNut4xbPgkCsuQb5+sYwJWndI4CtHMksQijBPHniNbb155QwUevv6HSu+kxWj jKTGZZWgzXMtx1zzEwW/6oAE9+JwtOnlBSwqydL8HxBEC1yhqIHeGkiNXp6YwKRsk41bQxNVNgxM E55QcC5xRxYn86kKlIEtN3be4/FAShTeQ2FjPdvAfWwGCyX4IALnXaFBKqEZVqbgsQUNxI4lCW9K FZCSD5/qPMxa2WdHww9Sw4tkRqPSJaoLHtUzr971MuJs6FMaLADQE3cFOqEJrGaU6JzWBFEIF6o0 BhIxpE0a2wnRl8ytAisyRR+7Wp925l3xOR3nVQh1dGtO/zUvhup9aubSyilXsYDd2VHRYXDKYVub HgzeBlW4cNINdneQmUJTwlpRucu9oQ99N06a1Wwh50VZRZ+OcWzPcqGUr1EW5/VsrNGXa8XBwOr2 j7eP+P3bWxA3p2I5gMqBBizTsimA8HYUttlFdE08b+p4ufUxr+o4/u3/jt3iJd4ax6xTTL2kSH0j bX/SJOztlWTWDAHgHkxrrmkVxweSpH2dh+TUMabw8OcYUv6M9IFZFLUFUncEv8edJAnQ2gynmWD1 uLKpXUoqCtG0HHJiUyvQotJIJFCZh7Q5ixhLYYfVzgn+OJ/qYIPb98dxqxcA6Q76VYiSDvMEAB7H ejKLh+kixjxDh50cINA40i1oUysSZQkmoYs1cZS/i6lPcaMDIkhCiTeTaCeEzOYSQt2erzUgtBPP bTdz3O9jTQbCCA4THZX5aiYK+z1j/OJh57mF1GsrY8txHJNlfzlfHR+gFFyKUM37SXFl3Gsa/8y0 dipdMIWBINQS1wb0AgarpdnFT4L+d9q2SKgPPShT3QsF55wKCeAMBYnM5oY5rkimrnHl9/P3VMoQ eqvovFsvugL3ZD2dBiE34GLXm62J+JzAKJPxJerJTbIyxuWG92DU2YVXob4DEaB5P6CqlE1exYmq h5g2nR/MDUuXTflDM3sCwt68nuXCqV3cbmO1WsU4MiNPCcZsgy7WJkLf10tiLgqjFq0ntjUP66VA Vav9kwhKRzNktHQUO2nDbDAl4FWxyzZOKThZ3GCVp5CWf8JLIbA2rYWlg1IQptvuAtKIua/0lJTQ iEXsc57RVjlsjKm4jN74DG7/ecDgmMhdU+6J3EwY4FOl+Z7bOk8fb8n4foSaMsYYMB7EZjqPzXQW z8ulxh0JueVVREAmfCSiVqdNxwAAIABJREFUksw1EjMdace8jk+LOsaLv8Z5OY/r45fYnTpFalEA eebpoIpPN8J0uxyYPGuvLGOHAv/TYQGLDyQSxNXzOY7YAuEs6tkox0eHQCKgLSCAw3PdqsvzW5Y8 Hvl5ybanSyxnF/l0zcCMNNJ67FGauES2rTaHBJpysiJ653AjFLSTeRyUmj7W/DNIyYOI33Z7bQHp wugo5IKA5pEtaz/SAQj7n6J5vJy01OAZoLOyNVKxlc40c4HeuXtKqgvnX42XPHFdUgzAJJ9426UU IDvSsskSEz67Fbq0+dMm1suptIuMXoJUclTTVris/eXyARmW9B53xHJmyClAnRXPPZIYiuYNGZDH d8TJuE8ULSb3FMqQLZ/g+vkwoXtVWAwjGtOBOhf72rl48rtv8fq+1VTCZ3lYzDOpPWRhzAFSpiNw WutjS7NQDiOKXhPjqRuEW9vGaoUEqY8NkM+kFtUCHJlxVeoFhXE4FBav+C3cNZQqsuvx9bT43pAM 7z6dsO4U8gRuDK0XHwiSoZN/aVU5ffzCyupYsUVUc0a+s07HqaQ0ziuTD1YD2I6wmZti33U2L9ww Kjtt6Bxf7hRSO93G3VNmK8QeHdYBi1jP0h4Tk7Ivxad1e2UE9So41/+KTzLAX1ppf3Vzs2h40YjZ LdPxSvbDhszn9lgXFStkIrlgHguWtcyFdTymZujwlGpyaWNeUbBI3x3H9NKqK5CDwIjAAKx46Q58 TcFAWM2TBycdHz+zIc3lZHuecRP12WAqI8WmGsSXySB+7I8xm/8YzdNPcRqO46N5F1NYa3sl8tYO EoGRrGWCb3pVou3VCVv47WxZn+CAokTaH9t5XD926ly0wcmgTNGWE/OoeTjSFdRYXKoHMgRWDPuM ehM3SA+3qRZqrPJam5iIU0GYXCzfe39OfMs+jqzHz3qJAOn5wB/NSRgaVAjuAb9DHCO2lqbSaU3P M0Jh4OAQDpQ+UpIPSRTjQ85nVxYt+aeZNgCHimJFAVKIhQiiLoL8HjtCOB6N7hd2OuMrhQVMZka0 OnY6mSRe5FaOqwMvdeHRJlHxbcZWzVtMKkgSf3mWRW3pBnEUq71PiCb90+RRT+G0n1t50iGicv7T 2UiVgfMqIcbj8p4ye7dxaPCYO+jQAcPSoZ7OIIWHxmeiw2PzSncnwKh4YyZ2TLMDFICqgaOrGs50 4BB3xmcEL+Q953CHOuPIOP47JodNnMiB7J3mRJdXNuPmeWZnlcaNojVgjk/3Q6UV8JuBD7K8QBQs UaPHHPnpcAr0EbvDQa0wLyUFAyIgfBhsX/5sTIerJKAjmxG6ETFbc/Wv9T9cHf18p/3irb07sm0z gx0KAS+II7GrGFxyKZCkxVLwRGLN+Kvy8w1aphWsEnqKtbE7O29MuEnx34B1tfycLvqz2BuDPTkd egFRMT3tKTjG0Cha9hIb3MM92eaYqKlhTULaUcxno5gOsJTmYbJFLSDy224rR1WKJ+AnL8fj8BY/ X/fx6eNbXLtNfPS9+EXfdnuPQwKE3TF2Q3pCd4cl8RoLaD29+X8yAlRBwYKakMxz0Ax8Ws+0av99 R/bcNTo0cSlA5oLiUElxKaO5APl7ZqTHqtHQhxfFRx2xHBug3Fqlrwc8gzL5M2u0iVj4XujyLY57 Px7jt7c3FeKn9SaWq4XGuY8jmYp+YSlSdPN8Z6AIjw+DBKI58RlbrI7w1pkRz9fAFJE0kNTmzMaB EpZP4KnVMRVxM3l7KtyGMsDP6JaBLbg2QKssjkhCwnFTY21VBONZTGo7arCMoVMqInzhTdnB6fmg kEjfZ6dZ1B4sCXBskMUPmGLYcZTf4yBSqwnEV4PdI2+5W7yR/tOclQdJcAi0Z97G27D1xlaR9+f4 tvuIOWGyfPZRpXdOltlpUIi1tMjHsisHw7KKQQeRsGFPHnTF8kUTiDqOo454njVgjcyalNngRGEd wkWT8/j50WErQzz0cH6V7M5RaoaY/5w2L/EzpwwPn0FT2dwm6U+KcFme8JDlxgzZQarDxQSHsQ0+ QVIsm0HA2MtFhDAJJzPSm/YU/RsnkDo3+Vx7K0QfQxsMGPr729s9mFQdmMiWjIvmNzEmFn8ebiIb E94Ns8PTVia5Xu4iCvblccVuCN5IMVKaz+JTDaDYD2murbW15PpwQjg+nP/22+trxMMm5s9PFmpT HAHTcVyS5tAjGl0a309dlLRdltzYtz299HnolJ/nE1UEzEzRGfJnrl1U/UO0P/wQ19kydm0X//tf /4rX81mHhuxJhkglPErw+2yqmAqFwSi+vb7rvkKYFKh+xwB5+IcxGfTOyHt6zLCCfeyVfOSH504p 6WD6l+xFxhzLJZS4JNIlRGMAcMbja7wfIDH2sVrWArJ3dISHU6znK426irq/nC1NAri/dHK9lKKf beJyFl/323jNiDIOQnylOL0HQBQoL3Is49A5no65uvHSgXHeRpRpI1Q2n9lta2OtwFDTRliCCFjX PxuZ2sHLK5Kl47XuetYggXsoQTiBDWzCSagGtyOQhb8AvH3weUIgTVsk41xc2eNpKLcHOnBGptx5 699JsM9Ti1xFjIibbZsnjFYUZL6R1RHaLkKdIenq5MaB0ZztPCPh6XxRLuOoruN0OusvYcmNt+jn 6SRZ6lBiIBlPhVGBp4k3doeRzK3iwRdUIqdcfqctsMU/mzDWu1PSxi+1x8MBY+5ABos8vLi34P4q gixUk+s1Hh/WwrDgKF04GAbFsz4LllTVipiioEwE4gEw39fMd/V8LwMyOxZaygEoKeBdIQUoqtno MU6lOVviAvJQR0IxYyQED8jkDp3YIzHhT8c23ncn2SB7nWtOkEa5DHxQcIJcFtOET1XaXRI3EvlC edkBMOVm4ER2E+nAUPIEKYnQvMjFzdDCboPeJb7KvB6TJbXLGlby8jbb+BrzJYZtCSan5MDxVZzK lU4aTrtjg9/YQIzh2XSmQiMwG+6U4sFpe2njrR0DK5m8bWO8f40RReCnf0ZT1dE2x8SlbJ/rUFmT YY/pyzTr8VCyol6sdDZvcoctaUNW+1eVV9ssGtjI8IbAhIfIK2sbRvnUObrTLTm1foCA8ykAwsUA eXOEoWPZhb2S4G19uq1DPgF8jlzlF3lIIR1jR/PH4Ri/b1mlO7WJ6/J2OsTrEasWqAgX7fDBq+gr 1QlkujSHo4Iy0iCxJDohmUp3YB9QuWiR6DvF2xQttrkIiylYNipMSAHOHTSWOdMBEmO+BjQZW9HQ de2aS3zdHxWnhoOBAYSBOFH6WQKyuccWmEMPkAIiidQVFA+KjnhPBso5vOHpsW2z8N6YFd/8KJzR gD/hEnKtzaUS3bo2gaLuWL4GJ20y5plm5Caur48ZnZmwV6fy2IqJfFK72BaOovA+ZS5OdH15X5H4 MKuQhCV9K/hSGj5q5E8bcel7AechnApv7GI0dzfNp6XbOzQnp0QlvukkbEv9NDarAzU/IDss0wYw yGdlq4qeZE2ANnyGGFF8gsZ/M5PjFFPBGiAzMedJJnaZqnJDupG/imIIOQycp2WlnOJMXr792Ukh WE+cGtbFqfnTKOVTqOS1mfXlB0K+PsLKjN3ov7slMKht51B8H9kj5w0YXrN1FafFWE2J0tIDpE3R NXq5X5qD5QHZv9fx5HR1nvfpQAHtRbegONyuim9C6E0pQeSsgqWIr5vwu8V8IZ4QLxq6L7OdMUUb xxobkvnM+NXuPeav/47Z5RDHH/+msVkjKAECFdo/XmBIqNx887mOl0FsSB/Bpx05D9Hwicdoy6Wt X26G0cTh331gs0pSC//tSNyZDxQGGXbBy+noKhdl8Dun9SRfiL9nhiMvG4oHCj15j28HdGR0cKNY 1VWsaxvfyXk1cUemewJOf/vYalnDiMULczizBbTLAsWPUxnOk3ydIBiWgp3aPONr3s6qYMn33uJ0 d86Fu8dnN2AtzArPeWx68VjXC2xRtJQLlZ9b3AvoDvas672K0GfnwH/dn+KXj128YoOkZ6PVJwR8 551SsAT3DdfOCYsRCh9TiwXfpgp4HJKrbj2RlO2UeDDfk66v5t9x4dLgUmaGNDlSMBiI57Dg8xY4 Qp17pq2jAgG01zTBtYfMXSRJolEwBdgK269Ibp/x2Z/WclXgGYI7KfKnHFHYsPs506Y+ycsuQEw8 toWWDbYgGjITee+Nf/G964WLJlzDW9fKqshW5GhWcyQsBn694q3MhQKrAVtw2vJN8UCAbVTYqUZD uhI/uIvpwpN0bhL4YvwMGbFBhVAOmZ0qaVnhLNEq2sXgKp+isUIZofa38ZbJOMJbBOQbeDQG4w5L Uee4BfC4yvYYJNdYk/4bipVa0IwJKv8vE6FLN0Irf2jsZSQZUMAzwtrExveSDKCBTMM7Wnl1doDH CpGcxeN66QTnxMGsFWeraCvab9u9xiu6raaQc3FaxdHxAHAPmc7dq/k42GrMY7ZvYlztY9Tf4ufL Mf5+bmPdbKOSoLlSp/H724ceAAqzUnLXEzmaKkpMXaJIRD6duj6eNyvHLAk0N9dLRTuBkB7KSjpe EGgKCP3H/qyixe8QZiIJU7qcZohuiXmrK3BJA/Os/V8el8LB3g84n7bx29sxRg/zeGDhUtlTS+aA OQZvuybemnN8A9hVmKpfJHAripZfANM/kmxWYiSNebANVK6erV+Kmwf3iwOHzoz/7cM1+X7hMY90 aVFPxFB38fr8tBbNZDpBKjXRy4y9D1tZQSECm32gaSvOYQv+g6Ab1vmwizMM8ZxSukyBEnSRUwt/ V0FT5iD//mRsVQnK5tbx3mHDxOF/vJz1s+dkHExnWoDwTlJA2NK2A9NYZLJoSxWNumDHChqGOjPF jifNAqUpdVahmoLhKE6Xxk0J309GBrLVMzQ0tfOpMWl0h7lplgKmisPQXEDIvtBOONTF5xTh12J6 bfLJOMj7pGkG1v/DOCqsnC4ne2jFRAWSvw54mbGgSagKSZ8N+088CF0sl0ur0PkabPLuFqqZZtF7 Q8PVPwwAb2exhkCZxD+Zf0H3H9vdkNNZFV8+6Aa1BQD2Jlgez4f41y//FmPZzFzP8ZJcZ5oH87Oi zNHHaSNmeoK8gpIgxyNNgkpZ73Ihpa4X4NlHPwLMJNZoGCNsBnJD1OC6Cev5ht0NXCOLpiHNMaPb sz2xrcSc7KBgugDXCZsO8BVOXwfAZsHOBBhRLK4OJuDPaTxlDLpYQ6fRpKruPwO8hQQRZAmL5ho/ dk30x72kH5z4jDrtOV1Vs+uyGNUKhN1+pwLLIcE1h4KC+yVk0IfFUksSXk4dWtg/D/p4mNYxmM5i iGW1RvaBRMW2ci64mKUhANSsNygokDN5KTYTAkbm8bTgeZjGbXeM4YGYN7OVJVlhYSLHVeOBwl66 mzekTaNT9efnjToMIqLe9sfYHbBVaaJrb/fOSmB+Yb/L69/p2RQGd4SSByi+zmt4DtXKnSHPNWEr NZYo03hZL+LzZqGunmvC6Pe02Vg7ly8gBy9dBic+o5Ftg4xPFaM8uka5ccAc1yLCtsaaXm624HaK DY4LxmVwGulrH8KfHh6E3bEp3pESrSIziJ6NaNupExzIScHGg0SHycn5ahqSYvcySJXnTZgTkqAx 9sMInG9yJ4UbZXmd05aBBeTOgovu3uOu8OGLY+K5znzvMbIiYXoEHpujxeZfxgRVH7/99k33C1cG xftBsM7lBVtLBaBgGUVxbg0JSecoKk8bD+Np/PTypHfAbqqGI8DSZMNcDPzAzXgx7RpwiVnatcpu IrcYeF8L0JPxvz+03RLtOaJTWMXFbfh0klwpBUiw5p14vpZvt10BAIy5IK+7ndbzdCZcuGKgL/ZK bgkk95E5/u1uJ8zN9GPk3DakQ4xmttot/lceqgUY6+cXAN7V2skqbmUpVgDjSgKRVSyFxG22VtM6 SVLYn6MHheXU3JQeTOu+259UiLjhHmkhTJpSwD8TO1gF1riZ9I+FVJjhAigPLLPgxbvFazeIw6WP 7rCPwXitAkhs1vmMbc9VwQqMmy6E/oB0JLYY8SnsGLYUrYO/kL18Rd5hDE0nX00+IPImA7i8EMvh IPYnYtUtXIasVsG8KyoAPjvpxjWjk9NiKJBQEkQqFa3Cmy0VOsWPOxBBCx5ZAEe8k0zdtsL1iLWH DwauSReMZxcgMs9ORRAG2CejChvCtMF212ioIldGUg2oqCTviLHMGyhTDADYn1fz+PFxHT88rhJD tF3LdDpTp65lDJ0Lo6TOTi+AdDCJ7Z6GjLlA8abaTPDdoJcv+nA+UWw8XaCN/lKvKUWI6QPW9DkP UNwjfi/6PNKQCk8ynVGrlLbRWfN3tuosK+j0+Ls21j33leALnmXjtcLp5rDZwZc8fko2pnb7pk4H /BicCliH643JAN0fz4KcWNM2xhF/vtiafHr87s6alNDE8o6ymHOhgwRMliiWE9YlCu3K90ALKxZL g0G8PGxUvMo1EfzQT3WtxQNzwQLXMZlLReWKIZxjoEbwKMaVAHXaQ/4ZZyR/RlsKgi6VhmFLFjov tZ/CoJzwulyAW2HFaj9qLjBj0jlPVrYESg2R3imtgm+mOch//OqCJQtYERlv99OQmV7/JImaeiE1 lrZ3exo7jtrcz58tbZbRR4nV7k2YLVawwWl04WmZwX0KN6VwXwo+QuElIYhr8X4gMchYX0IpdxKi 9IZEJImE6tPdthuWNhgP8oEga+d8/rGI4YR6vY3jl1sd41Mb/aqLaVXHYjyKPfhJ2tZAR5kPagHu GqfhMzF2t01iDnOZ39Gq04o6oukWJxKSGVXEc0G1jy4Ryc1FeI4mM/GsLrFrzxFDzEScQsTYgS/X aDyJxXIWtSz+eq3Lt9gQ89JopGHZwijmg469IR5V3DP5xI9G8fXjIDE263GcHr6dPpKyAYbIc+C/ a9itctMLVwiNmbpZsEQ/v2Aj9tAvAmUD/BRxO8Kad4jv/A8Py/jytM6Q02TyS16TXm0yTwQLcvam xkwKWbdTIIoIqyl18dbP0AgcI4TGXJ+lMCtkbL5XPBSmADjKDI+uwfDiJPDRQHQGMC6i8Qix5cBZ ZkzXML3EANrtlcbzSejDUUJyDn3gCz6jnmU9kxdpGeEOzo6IkynEFLaI581CIRc8fwjW9yROy93T WuD9+Sg8kmUE10wctJI2rhgxDkYMA/FLs9+bMDJi3zQ6R8zT6bdoa2UAABk2LaP4rArxlV/bXNNa UQaUe1cmPBUsXpKzKAwpMzi3HgcqewcB2PYT/oCtlLWKlm+PLYXBNvjhOAhqxKN9U4AocpPa40FH 4gcWFCbP8eC977dixHMq8PsG2lYymtnqQ+nOfGAJiT0Wepy0oZ5ElnqATADlxpUocUdNIZ62Yyj9 Ct3TsOUEtVRFfCSB9rTsmYIsZv1NW7zSGekTSy5k61/+vPCV/SG+bg8xhFtCxwggzBZGxdtaOXOU RtqoWEDhrswAZfF2d6dAs1c8wvMAisO1iv8zmMVb9XP8JVbxE0lFaRGzWeIDNbGOjhh0CK0V6dm2 e3bgbasCAdAv47t+qEPCNjGImcmVO+pFZkwAz4QnV8/qeNABgvfWOt5Px/iP1z+0yZM8icMCUHnI 9TA3TmuJAUnNBMhyr+tUpYYIxgx0eMWfmkP8P//6j7gM+5ixeaun8XV7FGa6gnm9O8a/33bx+8fe qoEknwowT9NDXZ/cLHG9EOayjVLwrkJFJ+ocyxLImK1HcY+CMxWqL08P8bBeqAvjkKLj56WbnL8f HGxMOXx1uLDxPRlL4kmkg9DuGLIjgDWeY8qhnMZiOpNTBhxEWQzJCcXPsBcFI9EZKB5oOcFQsVlB VgOE8vnTs6xXTsdzTCBeimfVCY+zk7dNADhQGZ1eFisV193RKhM5eMhr37+j5fvhuKrEHUuGtsM+ iNq1uSChMB5VOQQggH/bbe84I8VMWzuKfg2FiS66TZ2vv1exqKaA0SmRwH2dutCCf83HdTyu1vGI o7C2rQ6goRiifpCJIfK9pE8YpXR3ePfD8miS6ui0pHCicnqNJBVfq8n2YvvWehqheGzjCOiGpO/i AUPkyIZrMY+n5cIr8kNjrpG2BfCtzmItU5RodRVYO2Q7x+wMu9pkUo0oYFBIP8RJ8UME/V+mYajG 0x+Jh2LO9kytsu03ZOVbfLiyeJUOXv8uuR9ctN2pVbGl4AFOUrAEz/ao0r32pYDBaAfX4CZLsc9p xdo4uZlO12GMoOUm/TYf0ryGTFZcY51Mf+KMmbBqXoui6pOIO+rBGbr49PYfsVhEnFfPXnKwTcks Ri0L5N/kCDbhdtr8Rlwnl/hAX3lBm2cTPXR/fHYTgu2Qwd/B5Hhp+d3SUzIFci11Kk5jT2t+bZWS jA0Pcg/GulFuv9CZkfYi6kpU6t4UvHtlLKCg0rWN4/Pzc5y4f7drfNufbeGDpGg8jm/7ozlXREcp wDOvSXqv3ekQJXU0DzZeFrZYB+6rOH5pUZ1dMT+DEITn9Tx+ftnEz58eY71CeD3QhpoRSjo7RlvG n2RaK62YAxWWdtfFf/3xGr+/f+jg5vl+XNbx5eFBY6RcNJvUYHL/zm2cwO4qAOSJktVN4vXoCD4l 1r1Y8d6w+ZXroznhrVXFdL1SJJjVF7foGbNGVYbs4vpZyRCvHNTYNVWTShMM7+Xo3MdILzv3FtrH QGMmHuu6Z0r+wa8U6CeJ1pJfmRYBRoijAn/Xuyk6hR0ZqBNAInxnSrhKKdMSdUSTWBcHZDsyNPTB ZmVEUjyYeKaT+PX1Lf79+hZftg/xtJgKWmBBghUTU444mpBKDbpn26WVfancfhYcrOkLKP0dnJEc laZgP+mPo0w+QFAB9a7Cq+VSrGBmdtn0atqDbGbTMW3gREnInU2JnZdsIbkypUAJOHf4heZ8vWic no5ewtSsFClJjf4UTVU2M/5CtpLRcrFIM7JQcDPlYoqESFIREjzSyyjJk25LraFTepBkFYwa5h/p Qc1tWVHfiwus6+ffo4capnHT2cc83SwdiFk+l/3fFZiBCfHoGpPTIeJ0iG724GRi1cpU+CfdRN2c SLVZTMGQeugFSH/w+27V57lYJf2EzeeARYEdBE5F9pIGfLgM8DCXlO5rT0axXx4KFSOiGOKLmRxA CTxggzXmIMFzXVtBiq/xGrzKnx82sW/Oon/sbmBXDpPlfv+63Yr06AY0qTSSbany3wm3ZUwvLiEF vfJL72AMmTQL3+L4u8V6PomfXlbxzx+f4jGLFVtXFhJyOIWNzQg39fVlFOVeedwJdS6/vGK7fFJh w399c+tjw0ZxOpOmbzs43PMCgEHkkwZAPqmV4mMXU4qvSbbyBkk3WdlAy2u/ifPpHKMZSTOOfz8c T+raIWjTDe+O3j7SzcOHRPSPF/9kRsGaxBhc69zGSIevCxaHOddilQWLxRjFqh8YGuEdVqGGL1jb G4zIeXXzgl/s+uDgWitgGMdRMpCUTn4lxabvvPSgawZq4Z1U4AuJO+kEjIwJ2GEI2P96E95HfQBT ayreQ3BjpEB+H9iEWpqT1Z5ixQkoUl9yKnRK69ngwwub8wZM1bGKUW1/H56VI+xVRaJ7C4iQlfRW TqgLLGbpiRzlhamfWMucaollqMtStDrMXz2bXpPLVcEZgaXqSyiaibwlEVbzcRYOZbmlk4McLotL ANtC5Cv8giS1avV6D5EAF3AnyM9C5MXNkJwCUzP4ZJIFuSh4lEuhM+lBhBSk8R2nD50YAlwKs6O1 Uuzc5l/CL8znMdfMHvoWfPt6tKOI7WAcv3KS3saaK3jBzYdzS813cyDn2DbJ3DNJZRjHxjHhflBc OOEVm+QwToBRnBKUGIRZH9eHyKgw0I4shGeYukgXxBjJFZG9MUEW0jOBj4xj2Th5WSnUg1E81L3w CMYcxg2KJeM/BQWul7hueHojWJ9N9bIgbP5t+67HUq6XWoMJWPW1ZmPFSjw7f6ej2UeM+1USv8FU OZXZZsqJgxds0Mfn9Tz+/vkp/vbDkwiWX98ZPQ96GT5vxjEBq9HmCzE/nailSVu2leezOtX3I6Jq ntFxHMFhT+d4WCwU6noZ9bFerCz/kXyJqDPwodaE3todhq4Z23Ai16ATqRGYiL0vWookNt6eUd5m 85lsciajdJigU1FHxrNuDhQTDu4W6zHBFM4IBOqpk3ojQ8ARtCJfD1EF6CTTmBO6El2QLLyF87GN 7NWFPm4WcToCf+SmU5v/qUZ9KVlq0pzRGpL+U0e7P2vzyTTl4FfLrjjcbNszUHDG82qhregPz08x m84FNUGsBX7C5PA6t3sGhZ6Ie3dYaj4sZadFFSdHLyL6Odb17jz4RXxI5kvJUG5drKDw43WU631u IDcUbGr4+zdtkyhgtKbaKOSGEIKoDdCcYSYzM3gtMqZvtDEqHQD6QoqaHwAK0XdbZk4r6RiHLqSA zPKmYhORIGcpglwIr6FtgiZIFXeITPtl9WzfIpPZKMRiFnNSZjAHN8R9pAF+bggyA6FsaYnBmKbO uHJSTDFh4x8zAjLGchMpZNwITyvuKbk+dnrg35lvhhXUR9fHt9Mlqt0u5pNpjOHAKboJAi5dp8LR FVCw3yMQdjwV13VdX+QOCXXh/dLGXi+iO0uur1N6/BAB2HKwQCzhVJd2LEeJ191ehUHfRxInvLGs yePlY6ukzRSj0NCWvmz7YgvLGRmX3SRfb4RfGMdUgVHBDflp7bVGRx+aq73M/JP1LwsF6i08Otjn 0ySFZtjGXRyrQ8sbLZGF00Tx82YT//j5h/jy8qStIjbSeDwNeuQiyKPclfOsYdkMzeZtB90CyyLD BTwnjNaMOi6++MWbRrCSpY296oudN4UEV1OeNcbk1awQWTmUvBwq/lEsK4zclETvUMReP2i0sIHD MBqaUc6/hKLA/aWL472D0AHBlEi6v3yCWkKhGmj6cdG2SSIHpQ5lFA4SB9Nc2PjgcjjYk1CbyD42 LxtBOeZ0+V77L2dMCR1fAAAR8klEQVQjILODCdC0J+UMMtLzDb4Njj7gRVu6xGJaKQn6y2apEfrl YSlsG+hEdssKwK0l+eH6qxxxHw57YaqaktKsQCNhof2bculLJmeD3ppBJ7jaOVPAcdIJlK2n5I6x 0pfPVwBJrHePeiloASVCzgdPXk9wn7ChSCcBXUw1PIUz5aKirSUjngpUujboZ/j0UZsvdbfnV8cB ulukePFzeNFoyUtYrEY6vSDmd+ll5UZBklViUAo2KyvWi0UMITqcjow5chRNaoO3R4WGWFw8LarO f+yUk6ZVew7IfVLIZc5+SYBF3H0PHRB12RILHhw9SH3EanCMzfEWk+kwtrOF2f2KRzOmIXmEliIR 3/YIo73FWs9G8ePTxi6p80W0PQTF7w6uXAORKqUEGIq8qg6W0T7xI8S1Kh7pAlFUK2WcZmEBIF+S jgB83w7nuy5V/uFIUsRtMtfH0iisWwYCsreESByhW+AQmutzOVakqU3SDlQLVA/y+7fWevLsWnlh SxWug90M4E5Vwqye1yv9eyLk+WoA4+AktJcrXDXAWFn40EUjrk6ba9nnpCQMWoPyi5JCc+5InrFC gsMUXEaZnW2rfAJFz5HHV4/0UvLv7VPOM5fvQXGAkIeZD5puaFvpDnypv8mYcDhK0XXSOTSNqBDZ 2ti4kqlDbBo5dK6NSeJOQE+BOiPamO6OKDKTsilIdhP1JKTJREWKV4VFF8uc4rZxk2Y48Rx9N9j0 2BrR3Ox2Jx1AMioUrWksGsl6Vsen1SIeMXhkS984bMbGQ4bLOSx8ANmFWNedLWQu1yifdx0RXZKT WjJvTnFc7ihow7lY4qSoDR9byd+Zz2GDepT+pKHA7jb+YZfPq1bhxUKG2bb8nyPsv9P6C05kuQAK er8kBlzdSfnP2fRPMV4UGrl9ugOQkdnVycbgZWz/oF2AGSjXT7NSbiIkGsaD3twg2fpOCJF1AaXQ KZJRAtU7fKLS7hh5A6a8NDdwr/Re4mWmWwHQBScB/+B0JhFI63BZ95RrnThbRkZxjWD8SiZFh8fG Nk6xwab2VMWu/4sDWJWYMoiJmMTYfPDP6vhti1UNKSZYB9O2V2Lmy4W0ws42nzWxK3zo8CGO+3PM FyNZzvBAIeRVEAcLCP53TTedm7G8eUrmaVp1JDs4cCk658EHBJdcRu8jZN4U/NpUIzG/YbzDqj/i meRNMpssyTgYjbSJcyWWXi55VOUvjdMDi8nFZE/fM6VTS3A/joflVEUb3MSJ5oz/lYTLCoTl+2py gK9n6EOMbDI1E4+UEEwLJttPFz0lB7dyB6QVtICZgx6pE2RYRp72Oor5cSLZzwrXVBu6JS5sZQJw jM8Hb0EpFiVbgN+1mmCYmZvt04Xc2Lt0zZvl5B2STwj5UqlDE22Gda2F9cKrhJxtveSFUZECm9pc 8geAASS5GtoKhiXSdGqnCqenp3vDCSmXDRBk6YQFulqhhENoDFiEzSbxNJ+JpIu7reLVBpXTp8+p NmF0vBgucQH3PYUiEQN89fh5pcNilSnCkjcCo3xh+XLgFF4pe7x63+/0otWTadT1NFpEwGyrIC92 bXygmUNcbGmZ2eZ0GWfU99bOCdTnDsMnwctZDzd/prgoWJenRlrCYxev4g4JmGhzr5TbpBhX9iqF CpFtM607q9nfXrcxGbNCn8TjeiGvI7YjzdUBNnB8TIOwXTSWGwLWLcM0wH/yVma5oKXH+oXPwzqW hBMcKtCP9dpEQc2kcP/2vlPAA6Q3WSOLNe6X9h6PlkXKadhe3XIz79Y4/SiO/SB+uQ7iM/5BLYZ9 MPB5WR3oSeRTf8XdlbX4PJY1JxpyI3e3JJmwNaJbPZyOwpU2i2U8zleShKB3hPf0x9s2rm/vAp0f 1tP46XGjnzWVZ/9VbHhFq/FiN2d7Rk3ruBI4Ma4kXmaTCPsZQ0cwGIP4EefelAgdeOAjgW+XN4Pt +84BJOQrSi1hi1wORXX2sqkGC4QNj4AYnGaqtTjXTEWqWGfzcvLX2Kx/XhQoDE+bhWgIPJAC+LWM tnMmxUmuBtnZ8x6s0O2Nh8LkzsJoGhVN+Ffq5ijmmX7Ny0SsvMB+Upbg/XUmUU8mjM6DeNuB+XXx aT2Px9XCKdyLma4RVAVGVMYv7jnBH9MZYcKcyGziznGeLmJY1TGQEsRaTuGV6ULBocDnprx/3X5I vP7w8CjSrQMxhtHjnDo0s57i7mnBnl2kTrH9591niuFwZSTln5G6RKFmzEPvB9WJ8AqAciym6BSn M3O0OJT+8vOneOWZ08h9jaf5JH5+eohPODGwiWapgBg61Ss0N3jyQy3ZrJa6pxTmX7+9a5SmIJZu vbJI0hIavQSaF02idNfjAqTthqxwu2h5yGG+6yQgdSRid+mcToukRZmBdhClC4HiUKx2ta2oJyI7 6mez6SiWNjlYlTxBW8v4ZBNuJa1g2sZoRCCLz6OgWLVJ9JR3tvyLHMC6o3K3Tbye2nht2lijWWPm J8ABjI6Oh5vtOhrXyzk3jmZQyxIW7lIyfAEdoRzcmnPsTgd5PEHAGyFWbRpZeaCL/ONjnx5a3x0u lXuYW0cz3tOTnv9/Y5dWdXaZYegU6UG8D6ZxvjUxaA7R7N81RkDj5LTjHtpxlNMbQz6kN8/R3Z7U zSKklZMG/206ePLQVlWvwsRoo47r84tfzJElRXSJdKncy0VVSwPGKUpaTVDGUosp364ME5k1nJ5d DOez2HFAIbdCptLaxWM4Gcl3i86p67s4YtRIIaebhvyZWjZto/I+yt6XYqAXz86y/PMu5RqFfyeP qRG45kT0hU+bVTwu57Fe1FHhaUaWH0nn54uwEoVFaG1uaIGXiMRobE3oVp1laVtkJQWxSJKVdT5r FRkHxuTUVYsKgj8a4DvXaxwfR3IGzFe6TuDkEdN1jXZ/wJvBdsl4gkH81NZvJEG6fm4MVDCaq8fO ihFZXbwLlfmHHo3ndJe1Oy7eORqBj8MuNquV7I4bbFz6uT5THsOWKcnRxJ7zogdR1NMuaQKnrYZ2 5Cg3uuYSlgE1SeoHts48W5XJr2iA+8s5XubTGK3mUQ9u8RcoJEtsefp4PxLj5yIOzoeWeNzD26Rj doiHqD5YOylc1WGyJF55JEy7GDlppGyAB1inBgCxNhYWYvhUN0cIwJEviYczHImvu73AdPhFTgOx URsVgBfEM7Z/ASdJLYJZaq3ka+6RTyPd3T/d45hme0YAxYQb8LVtjdti3TASQDK+3q84Imc7SbB+ VdG52YoYVi9uBrKJFZPerahAeigHrQWaVHa10TrFPA/a893+PfxTZbBVE12v171Je8cTp8VFTHg9 kwXzSUmKfleCrZbw5KamgDWZmq1/ziyPbi/G8bUbxfTUxcf7R0yfXtQB8DPVeUobaO4LQl4Kkn4c bhh1E9vDWaMxGzm18OjNusZx51BVRkSnzyXaZuOknD14OddWq2oJbtGrSb3vIlm84l0srhohcT69 6GXmdwxDeS3DkUZzpnnSVWp4SZzkPMCQPoEewBl5MDMx2ooCj93FF55RTEVZli3GXTQVpKU3uJeL 1SL+8vIYG1kVkyruzt6dPPsKA/XStN6QTUEluMgZAsY4mCYSHaXcgMkcTlqgSD7Gc6qN5U0BvCTs XIZdtCNzBUlPlnsqiwGlmFucfbl4fBXRla7ibDcPM8jN+5J9khxR4UchAv7uosv4dblSXGy2iShL /7U24Dbyo+gKioGegnvt6SRfMd+fXlmNYIY3Dp6wswYFQ5t9zAj0u9zNcr24tlqW5YjqEdTeXcjX GNn0mYtXldxHcZF14ZNt9IR8Q4o8RgD4cNGpuhsuGChvEs8yixTgAI2ATAwi7eYGIkXrFXOjEj9u fAF7m8uCtjXz/PsJRuEaSsFO1wEvBLzio23i634Xb9uPuOjkcrfh9rxIaWwvoYcdQC/84BW4mi7L M55HGDqYXJmoyvLnqE4ycsgEZ8Bqxx6RClLFBm8fORS4YHGDtA3hwU/mOKBwg2HZBTGpLVds/2vM S35LiFxlK+I/K0xCOjr7Y9ExQcnggVUqiSgUTs55/TjE254XkHWsb7Qy9wrJMTNPpJVMygjXixez 0BsKzUh+WqIu8B2H8XEdxL/6cRxZ/3/s46eHT7qG11GXbhU+dZEmSTCufMI+FgSHblYSpMNWZmTk /6w35LPi64R5HRa/PKB9DHYQaf09utTQyc87pVuS7sxm4iHR1XAAADJra8tDhkBYoRKDWEg4Ti4g W0DMCEcCuCmU8mTvtk6pVpBp8dRKqyBb3Opa61liHJH5oUMfeKBFaqy+g4ubOVuoVbw8ruwukK4S kmBlSg1eYcZEvoPI29Mxvu0P8QFLnAlBHlF0sLf42O31nYUxcm1F53Bh0Pt0tVMIXRm3ggNAzgl4 zEGTIOcTSkPJTWRJgXgd4Tk5i+nCi72LYs3ofjDW7LsY35hIGN8wRjSOI8BcEW10797gazJhE81Y nVgXDqa4j+LRxQFxAVu+XGN6cVGFec6IKWWJglVtSUSHOCdrIS2W9Prp8EjMbDC4x/jdPd4zBo1D ZFVPnayOAF9Mfwwd29id2B56oVfeBrHrCc/VgUkITuKi3TAuHOIQs++064iKDY0uvHzZ/UCod8ju SELX+wbLeBNjGubvx+slPtqzNlKstdkUTMEfMOW7kGFHtR4JX+HnsUVgRub/usJS19zu36cXOHlU xWVQycOMrbSbKVzWry9OogMKDFYhrOWr9NwyFuSW1WEaGkeHY52S/D4uE/OkzN9E5kMi5P+OE7TY 01C8JS0B79AGCe2U529JPhCOkud2uapYMd6IJZ7iZ20e8/bAn/KJZY4bN7eMfCXD57t+6vumjMnn xIp6OI6HWxXr4zk2+Eahvl/MteSwrYyFt3QsdI6+zl18fnqKl81aNjNiw8tKqIp+NJcb6ds74wIb woVyDCkcLBH0PNSOuCeD8L++vQqnw+TP4DvYlvFFPofc+ZPjc0GS33YxybHmPOMwwCW1twWKWP+8 dOlxDhETUB9sCDgBMFtddmrJ2BKZgJXhJQ6dADN0ao0LCEoEtKjgcZ8fH7xMogvVc1U0fI6UUhp2 Lj/UBWeoAy/RO/pGxnvoDLDuGYewN0q5GiRTG1TyLpEy3caNzoKQ0xGHwlTPNNu96e0a++NBSwh5 n0EH4uCQ8aE7HaxUwERlTfS+VaexZBwT7tiIUnPL6Lt6OpPHO0oCmUjiInpt9R4icXmBgb9Zxwt6 QFKZ6bpYPjw9qLMDE+P5lg87kiJoEtUgJsAdcAbltHuV6QFaUecKXlVcZWG+O8TbdusYPy4c9j0p hkfZ4lBjb7RZ9pTgGpcU20eJKwmTny04JoSZgSCXB8EBt2gP53iaG3O+28toHBDJUlQP8Zr4EIDp MqPPrY94QbKDuMUZ7IY4r/NZ602y1h5nmK6ZOKndEyZdAPgUQMBMXsABL6DnY8tBLDg1OG8muWKj nBzhbVRJl9Ym0ZhY2n/bHE2cKPLsuph0SV2Q66QJdRJGZwgln49TWsTCLBNup/0waLOkWCTwHeK6 AMl9kmeTkd5VfkEkj7gS6Mn3Qrpk8qlM1rgvkh4VIzlGDydsqw0uavVE7zxcpUI9LVFMdfB/wWmz HN7i78M2/jY4x/kC+LuWhYyoJ7CBU25DK6rIe42ZWP1ajCp5DCJeRqsk6H55forTwro7rpmirSp+ t4m6wiXk5IpNiccGAFdOY2/vwIEmcVVasDMhvTDg3DSuBFdNLOoc4QH9NWIJDjAemVkR9rPiPgFO 5rlqC2Y+B9zkSp1TkWMUiRT3ZQrvD+EveGMLiD2O4er/7+k+UBAGgiiArg2xIHj/Q4qKmpAg+v6s XiHZNr8e28FGG4dGNknwHOJInM5fBgNbGWPCBhbfH4U7AZO9cmzexLosxR97WXamL+unj1ZeNbnb qwTCuqExPPP4hQauWrTIRLa0T8o36gCN02Ko5ppAHy7KRBuVkd36g2G9dSUsqq3ZqEsywcLz6okr EX1ic9lgMMKkR/5FyCuSGiOcSxjcYweI1ekODRMEerS3SkXVbqzTbrVZt6sQyalY78tNy3Yxi7+k 0Vi+YKSBJ3yfVTvtd3nxlgndC7DM8cGGnQ8mHn7CnuMe6UJkMXMwYgLZ1MBNc3sKR/z+8A8eWmsz y5mbtwAAAABJRU5ErkJggg==