20251030 19082000 1.0 FALSE CreateFeatureclass C:\SIMEF\REPORTES_ESTADISTICOS_SIMEF\REPORTES_ESTADISTICOS_SIMEF.gdb CUT_MZS_2001_2023_A Polygon # No Yes "PROJCS["WGS_1984_UTM_Zone_18S",GEOGCS["GCS_WGS_1984",DATUM["D_WGS_1984",SPHEROID["WGS_1984",6378137.0,298.257223563]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Transverse_Mercator"],PARAMETER["False_Easting",500000.0],PARAMETER["False_Northing",10000000.0],PARAMETER["Central_Meridian",-75.0],PARAMETER["Scale_Factor",0.9996],PARAMETER["Latitude_Of_Origin",0.0],UNIT["Meter",1.0]];-5120900 1900 10000;-100000 10000;-100000 10000;0.001;0.001;0.001;IsHighPrecision" # # # # CUT_MZS_2001_2023_A "Same as template" UpdateSchema C:\SIMEF\REPORTES_ESTADISTICOS_SIMEF\REPORTES_ESTADISTICOS_SIMEF.gdb\CUT_MZS_2001_2023_A "<operationSequence><workflow><AddField><field_name>tc_01_23</field_name><field_type>TEXT</field_type><field_alias>Código del Tipo de cambio entre año 2001 y año 2023</field_alias><field_is_nullable>TRUE</field_is_nullable><field_length>2</field_length></AddField></workflow><workflow><AddField><field_name>d_tc_01_23</field_name><field_type>TEXT</field_type><field_alias>Descriptor del Tipo de cambio entre año 2001 y año 2023</field_alias><field_is_nullable>TRUE</field_is_nullable><field_length>25</field_length></AddField></workflow><workflow><AddField><field_name>cod_reg</field_name><field_type>TEXT</field_type><field_alias>Código División Político Administrativa Regional</field_alias><field_is_nullable>TRUE</field_is_nullable><field_length>2</field_length></AddField></workflow><workflow><AddField><field_name>nom_reg</field_name><field_type>TEXT</field_type><field_alias>Nombre División Político Administrativa Regional</field_alias><field_is_nullable>TRUE</field_is_nullable><field_length>60</field_length></AddField></workflow><workflow><AddField><field_name>cod_prov</field_name><field_type>TEXT</field_type><field_alias>Código División Político Administrativa Provincial</field_alias><field_is_nullable>TRUE</field_is_nullable><field_length>3</field_length></AddField></workflow><workflow><AddField><field_name>nom_prov</field_name><field_type>TEXT</field_type><field_alias>Nombre División Político Administrativa Provincial</field_alias><field_is_nullable>TRUE</field_is_nullable><field_length>25</field_length></AddField></workflow><workflow><AddField><field_name>cod_com</field_name><field_type>TEXT</field_type><field_alias>Código División Político Administrativa Comunal</field_alias><field_is_nullable>TRUE</field_is_nullable><field_length>5</field_length></AddField></workflow><workflow><AddField><field_name>nom_com</field_name><field_type>TEXT</field_type><field_alias>Nombre División Político Administrativa Comunal</field_alias><field_is_nullable>TRUE</field_is_nullable><field_length>30</field_length></AddField></workflow><workflow><AddField><field_name>sup_ha</field_name><field_type>DOUBLE</field_type><field_alias>Superficie en hectáreas del polígono</field_alias><field_is_nullable>TRUE</field_is_nullable><field_length>8</field_length></AddField></workflow><workflow><AddField><field_name>balance</field_name><field_type>TEXT</field_type><field_alias>Balance</field_alias><field_is_nullable>TRUE</field_is_nullable><field_length>30</field_length></AddField></workflow><workflow><AddField><field_name>periodo</field_name><field_type>TEXT</field_type><field_alias>Período</field_alias><field_is_nullable>TRUE</field_is_nullable><field_length>40</field_length></AddField></workflow></operationSequence>" UpdateSchema C:\SIMEF\REPORTES_ESTADISTICOS_SIMEF\REPORTES_ESTADISTICOS_SIMEF.gdb\CUT_MZS_2001_2023_A <operationSequence><workflow><AlterField><field_name>OBJECTID</field_name><field_alias>OBJECTID</field_alias></AlterField></workflow><workflow><AlterField><field_name>SHAPE</field_name><field_alias>SHAPE</field_alias></AlterField></workflow></operationSequence> Rename C:\SIMEF\REPORTES_ESTADISTICOS_SIMEF\REPORTES_ESTADISTICOS_SIMEF.gdb\CUT_MZS_2001_2023_A C:\SIMEF\REPORTES_ESTADISTICOS_SIMEF\REPORTES_ESTADISTICOS_SIMEF.gdb\CUT_MZS_2001_2023 FeatureClass Append CUT_MZS_2001_2013;CUT_MZS_2013_2016;CUT_MZS_2016_2017;CUT_MZS_2017_2019;CUT_MZS_2019_2021;CUT_MZS_2021_2023 CUT_MZS_2001_2023 "Use the field map to reconcile field differences" "tc_01_23 "Código del Tipo de cambio entre año 2001 y año 2023" true true false 2 Text 0 0,First,#,C:\SIMEF\REPORTES_ESTADISTICOS_SIMEF\REPORTES_ESTADISTICOS_SIMEF.gdb\CUT_MZS_2001_2013,tc_01_23,0,1,C:\SIMEF\REPORTES_ESTADISTICOS_SIMEF\REPORTES_ESTADISTICOS_SIMEF.gdb\CUT_MZS_2013_2016,tc_01_23,0,1,C:\SIMEF\REPORTES_ESTADISTICOS_SIMEF\REPORTES_ESTADISTICOS_SIMEF.gdb\CUT_MZS_2016_2017,tc_01_23,0,1,C:\SIMEF\REPORTES_ESTADISTICOS_SIMEF\REPORTES_ESTADISTICOS_SIMEF.gdb\CUT_MZS_2017_2019,tc_01_23,0,1,C:\SIMEF\REPORTES_ESTADISTICOS_SIMEF\REPORTES_ESTADISTICOS_SIMEF.gdb\CUT_MZS_2019_2021,tc_01_23,0,1,C:\SIMEF\REPORTES_ESTADISTICOS_SIMEF\REPORTES_ESTADISTICOS_SIMEF.gdb\CUT_MZS_2021_2023,tc_01_23,0,1;d_tc_01_23 "Descriptor del Tipo de cambio entre año 2001 y año 2023" true true false 25 Text 0 0,First,#,C:\SIMEF\REPORTES_ESTADISTICOS_SIMEF\REPORTES_ESTADISTICOS_SIMEF.gdb\CUT_MZS_2001_2013,d_tc_01_23,0,24,C:\SIMEF\REPORTES_ESTADISTICOS_SIMEF\REPORTES_ESTADISTICOS_SIMEF.gdb\CUT_MZS_2013_2016,d_tc_01_23,0,24,C:\SIMEF\REPORTES_ESTADISTICOS_SIMEF\REPORTES_ESTADISTICOS_SIMEF.gdb\CUT_MZS_2016_2017,d_tc_01_23,0,24,C:\SIMEF\REPORTES_ESTADISTICOS_SIMEF\REPORTES_ESTADISTICOS_SIMEF.gdb\CUT_MZS_2017_2019,d_tc_01_23,0,24,C:\SIMEF\REPORTES_ESTADISTICOS_SIMEF\REPORTES_ESTADISTICOS_SIMEF.gdb\CUT_MZS_2019_2021,d_tc_01_23,0,24,C:\SIMEF\REPORTES_ESTADISTICOS_SIMEF\REPORTES_ESTADISTICOS_SIMEF.gdb\CUT_MZS_2021_2023,d_tc_01_23,0,24;cod_reg "Código División Político Administrativa Regional" true true false 2 Text 0 0,First,#,C:\SIMEF\REPORTES_ESTADISTICOS_SIMEF\REPORTES_ESTADISTICOS_SIMEF.gdb\CUT_MZS_2001_2013,cod_reg,0,1,C:\SIMEF\REPORTES_ESTADISTICOS_SIMEF\REPORTES_ESTADISTICOS_SIMEF.gdb\CUT_MZS_2013_2016,cod_reg,0,1,C:\SIMEF\REPORTES_ESTADISTICOS_SIMEF\REPORTES_ESTADISTICOS_SIMEF.gdb\CUT_MZS_2016_2017,cod_reg,0,1,C:\SIMEF\REPORTES_ESTADISTICOS_SIMEF\REPORTES_ESTADISTICOS_SIMEF.gdb\CUT_MZS_2017_2019,cod_reg,0,1,C:\SIMEF\REPORTES_ESTADISTICOS_SIMEF\REPORTES_ESTADISTICOS_SIMEF.gdb\CUT_MZS_2019_2021,cod_reg,0,1,C:\SIMEF\REPORTES_ESTADISTICOS_SIMEF\REPORTES_ESTADISTICOS_SIMEF.gdb\CUT_MZS_2021_2023,cod_reg,0,1;nom_reg "Nombre División Político Administrativa Regional" true true false 60 Text 0 0,First,#,C:\SIMEF\REPORTES_ESTADISTICOS_SIMEF\REPORTES_ESTADISTICOS_SIMEF.gdb\CUT_MZS_2001_2013,nom_reg,0,59,C:\SIMEF\REPORTES_ESTADISTICOS_SIMEF\REPORTES_ESTADISTICOS_SIMEF.gdb\CUT_MZS_2013_2016,nom_reg,0,59,C:\SIMEF\REPORTES_ESTADISTICOS_SIMEF\REPORTES_ESTADISTICOS_SIMEF.gdb\CUT_MZS_2016_2017,nom_reg,0,59,C:\SIMEF\REPORTES_ESTADISTICOS_SIMEF\REPORTES_ESTADISTICOS_SIMEF.gdb\CUT_MZS_2017_2019,nom_reg,0,59,C:\SIMEF\REPORTES_ESTADISTICOS_SIMEF\REPORTES_ESTADISTICOS_SIMEF.gdb\CUT_MZS_2019_2021,nom_reg,0,59,C:\SIMEF\REPORTES_ESTADISTICOS_SIMEF\REPORTES_ESTADISTICOS_SIMEF.gdb\CUT_MZS_2021_2023,nom_reg,0,59;cod_prov "Código División Político Administrativa Provincial" true true false 3 Text 0 0,First,#,C:\SIMEF\REPORTES_ESTADISTICOS_SIMEF\REPORTES_ESTADISTICOS_SIMEF.gdb\CUT_MZS_2001_2013,cod_prov,0,2,C:\SIMEF\REPORTES_ESTADISTICOS_SIMEF\REPORTES_ESTADISTICOS_SIMEF.gdb\CUT_MZS_2013_2016,cod_prov,0,2,C:\SIMEF\REPORTES_ESTADISTICOS_SIMEF\REPORTES_ESTADISTICOS_SIMEF.gdb\CUT_MZS_2016_2017,cod_prov,0,2,C:\SIMEF\REPORTES_ESTADISTICOS_SIMEF\REPORTES_ESTADISTICOS_SIMEF.gdb\CUT_MZS_2017_2019,cod_prov,0,2,C:\SIMEF\REPORTES_ESTADISTICOS_SIMEF\REPORTES_ESTADISTICOS_SIMEF.gdb\CUT_MZS_2019_2021,cod_prov,0,2,C:\SIMEF\REPORTES_ESTADISTICOS_SIMEF\REPORTES_ESTADISTICOS_SIMEF.gdb\CUT_MZS_2021_2023,cod_prov,0,2;nom_prov "Nombre División Político Administrativa Provincial" true true false 25 Text 0 0,First,#,C:\SIMEF\REPORTES_ESTADISTICOS_SIMEF\REPORTES_ESTADISTICOS_SIMEF.gdb\CUT_MZS_2001_2013,nom_prov,0,24,C:\SIMEF\REPORTES_ESTADISTICOS_SIMEF\REPORTES_ESTADISTICOS_SIMEF.gdb\CUT_MZS_2013_2016,nom_prov,0,24,C:\SIMEF\REPORTES_ESTADISTICOS_SIMEF\REPORTES_ESTADISTICOS_SIMEF.gdb\CUT_MZS_2016_2017,nom_prov,0,24,C:\SIMEF\REPORTES_ESTADISTICOS_SIMEF\REPORTES_ESTADISTICOS_SIMEF.gdb\CUT_MZS_2017_2019,nom_prov,0,24,C:\SIMEF\REPORTES_ESTADISTICOS_SIMEF\REPORTES_ESTADISTICOS_SIMEF.gdb\CUT_MZS_2019_2021,nom_prov,0,24,C:\SIMEF\REPORTES_ESTADISTICOS_SIMEF\REPORTES_ESTADISTICOS_SIMEF.gdb\CUT_MZS_2021_2023,nom_prov,0,24;cod_com "Código División Político Administrativa Comunal" true true false 5 Text 0 0,First,#,C:\SIMEF\REPORTES_ESTADISTICOS_SIMEF\REPORTES_ESTADISTICOS_SIMEF.gdb\CUT_MZS_2001_2013,cod_com,0,4,C:\SIMEF\REPORTES_ESTADISTICOS_SIMEF\REPORTES_ESTADISTICOS_SIMEF.gdb\CUT_MZS_2013_2016,cod_com,0,4,C:\SIMEF\REPORTES_ESTADISTICOS_SIMEF\REPORTES_ESTADISTICOS_SIMEF.gdb\CUT_MZS_2016_2017,cod_com,0,4,C:\SIMEF\REPORTES_ESTADISTICOS_SIMEF\REPORTES_ESTADISTICOS_SIMEF.gdb\CUT_MZS_2017_2019,cod_com,0,4,C:\SIMEF\REPORTES_ESTADISTICOS_SIMEF\REPORTES_ESTADISTICOS_SIMEF.gdb\CUT_MZS_2019_2021,cod_com,0,4,C:\SIMEF\REPORTES_ESTADISTICOS_SIMEF\REPORTES_ESTADISTICOS_SIMEF.gdb\CUT_MZS_2021_2023,cod_com,0,4;nom_com "Nombre División Político Administrativa Comunal" true true false 30 Text 0 0,First,#,C:\SIMEF\REPORTES_ESTADISTICOS_SIMEF\REPORTES_ESTADISTICOS_SIMEF.gdb\CUT_MZS_2001_2013,nom_com,0,29,C:\SIMEF\REPORTES_ESTADISTICOS_SIMEF\REPORTES_ESTADISTICOS_SIMEF.gdb\CUT_MZS_2013_2016,nom_com,0,29,C:\SIMEF\REPORTES_ESTADISTICOS_SIMEF\REPORTES_ESTADISTICOS_SIMEF.gdb\CUT_MZS_2016_2017,nom_com,0,29,C:\SIMEF\REPORTES_ESTADISTICOS_SIMEF\REPORTES_ESTADISTICOS_SIMEF.gdb\CUT_MZS_2017_2019,nom_com,0,29,C:\SIMEF\REPORTES_ESTADISTICOS_SIMEF\REPORTES_ESTADISTICOS_SIMEF.gdb\CUT_MZS_2019_2021,nom_com,0,29,C:\SIMEF\REPORTES_ESTADISTICOS_SIMEF\REPORTES_ESTADISTICOS_SIMEF.gdb\CUT_MZS_2021_2023,nom_com,0,29;sup_ha "Superficie en hectáreas del polígono" true true false 8 Double 0 0,First,#,C:\SIMEF\REPORTES_ESTADISTICOS_SIMEF\REPORTES_ESTADISTICOS_SIMEF.gdb\CUT_MZS_2001_2013,sup_ha,-1,-1,C:\SIMEF\REPORTES_ESTADISTICOS_SIMEF\REPORTES_ESTADISTICOS_SIMEF.gdb\CUT_MZS_2013_2016,sup_ha,-1,-1,C:\SIMEF\REPORTES_ESTADISTICOS_SIMEF\REPORTES_ESTADISTICOS_SIMEF.gdb\CUT_MZS_2016_2017,sup_ha,-1,-1,C:\SIMEF\REPORTES_ESTADISTICOS_SIMEF\REPORTES_ESTADISTICOS_SIMEF.gdb\CUT_MZS_2017_2019,sup_ha,-1,-1,C:\SIMEF\REPORTES_ESTADISTICOS_SIMEF\REPORTES_ESTADISTICOS_SIMEF.gdb\CUT_MZS_2019_2021,sup_ha,-1,-1,C:\SIMEF\REPORTES_ESTADISTICOS_SIMEF\REPORTES_ESTADISTICOS_SIMEF.gdb\CUT_MZS_2021_2023,sup_ha,-1,-1;balance "Balance" true true false 30 Text 0 0,First,#,C:\SIMEF\REPORTES_ESTADISTICOS_SIMEF\REPORTES_ESTADISTICOS_SIMEF.gdb\CUT_MZS_2001_2013,balance,0,29,C:\SIMEF\REPORTES_ESTADISTICOS_SIMEF\REPORTES_ESTADISTICOS_SIMEF.gdb\CUT_MZS_2013_2016,balance,0,29,C:\SIMEF\REPORTES_ESTADISTICOS_SIMEF\REPORTES_ESTADISTICOS_SIMEF.gdb\CUT_MZS_2016_2017,balance,0,29,C:\SIMEF\REPORTES_ESTADISTICOS_SIMEF\REPORTES_ESTADISTICOS_SIMEF.gdb\CUT_MZS_2017_2019,balance,0,29,C:\SIMEF\REPORTES_ESTADISTICOS_SIMEF\REPORTES_ESTADISTICOS_SIMEF.gdb\CUT_MZS_2019_2021,balance,0,29,C:\SIMEF\REPORTES_ESTADISTICOS_SIMEF\REPORTES_ESTADISTICOS_SIMEF.gdb\CUT_MZS_2021_2023,balance,0,29;periodo "Período" true true false 40 Text 0 0,First,#,C:\SIMEF\REPORTES_ESTADISTICOS_SIMEF\REPORTES_ESTADISTICOS_SIMEF.gdb\CUT_MZS_2001_2013,periodo,0,39,C:\SIMEF\REPORTES_ESTADISTICOS_SIMEF\REPORTES_ESTADISTICOS_SIMEF.gdb\CUT_MZS_2013_2016,periodo,0,39,C:\SIMEF\REPORTES_ESTADISTICOS_SIMEF\REPORTES_ESTADISTICOS_SIMEF.gdb\CUT_MZS_2016_2017,periodo,0,39,C:\SIMEF\REPORTES_ESTADISTICOS_SIMEF\REPORTES_ESTADISTICOS_SIMEF.gdb\CUT_MZS_2017_2019,periodo,0,39,C:\SIMEF\REPORTES_ESTADISTICOS_SIMEF\REPORTES_ESTADISTICOS_SIMEF.gdb\CUT_MZS_2019_2021,periodo,0,39,C:\SIMEF\REPORTES_ESTADISTICOS_SIMEF\REPORTES_ESTADISTICOS_SIMEF.gdb\CUT_MZS_2021_2023,periodo,0,39" # # # NOT_UPDATE_GEOMETRY CalculateField CUT_MZS_2001_2023 balance "Ganancia" Python # Text NO_ENFORCE_DOMAINS CalculateField CUT_MZS_2001_2023 balance "Permanencia" Python # Text NO_ENFORCE_DOMAINS CalculateField CUT_MZS_2001_2023 balance "Pérdida" Python # Text NO_ENFORCE_DOMAINS CalculateGeometryAttributes CUT_MZS_2001_2023 "sup_ha AREA" # Hectares PROJCS["WGS_1984_UTM_Zone_18S",GEOGCS["GCS_WGS_1984",DATUM["D_WGS_1984",SPHEROID["WGS_1984",6378137.0,298.257223563]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Transverse_Mercator"],PARAMETER["False_Easting",500000.0],PARAMETER["False_Northing",10000000.0],PARAMETER["Central_Meridian",-75.0],PARAMETER["Scale_Factor",0.9996],PARAMETER["Latitude_Of_Origin",0.0],UNIT["Meter",1.0]] "Same as input" Dissolve CUT_MZS_2001_2023 C:\SIMEF\REPORTES_ESTADISTICOS_SIMEF\REPORTES_ESTADISTICOS_SIMEF.gdb\CUT_MZS_2001_2023_D tc_01_23;d_tc_01_23;cod_reg;nom_reg;cod_prov;nom_prov;cod_com;nom_com;balance;periodo "sup_ha SUM" MULTI_PART DISSOLVE_LINES # Project CUT_MZS_2001_2023_D C:\SIMEF\REPORTES_ESTADISTICOS_SIMEF\REPORTES_ESTADISTICOS_SIMEF.gdb\CUT_MZS_2001_2023_D_P PROJCS["WGS_1984_Web_Mercator_Auxiliary_Sphere",GEOGCS["GCS_WGS_1984",DATUM["D_WGS_1984",SPHEROID["WGS_1984",6378137.0,298.257223563]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Mercator_Auxiliary_Sphere"],PARAMETER["False_Easting",0.0],PARAMETER["False_Northing",0.0],PARAMETER["Central_Meridian",0.0],PARAMETER["Standard_Parallel_1",0.0],PARAMETER["Auxiliary_Sphere_Type",0.0],UNIT["Meter",1.0]] # PROJCS["WGS_1984_UTM_Zone_18S",GEOGCS["GCS_WGS_1984",DATUM["D_WGS_1984",SPHEROID["WGS_1984",6378137.0,298.257223563]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Transverse_Mercator"],PARAMETER["False_Easting",500000.0],PARAMETER["False_Northing",10000000.0],PARAMETER["Central_Meridian",-75.0],PARAMETER["Scale_Factor",0.9996],PARAMETER["Latitude_Of_Origin",0.0],UNIT["Meter",1.0]] NO_PRESERVE_SHAPE # NO_VERTICAL Rename C:\SIMEF\REPORTES_ESTADISTICOS_SIMEF\REPORTES_ESTADISTICOS_SIMEF.gdb\CUT_MZS_2001_2023_D_P C:\SIMEF\REPORTES_ESTADISTICOS_SIMEF\REPORTES_ESTADISTICOS_SIMEF.gdb\CUT_MZS_01_23 FeatureClass CopyMultiple "C:\SIMEF\REPORTES_ESTADISTICOS_SIMEF\REPORTES_ESTADISTICOS_SIMEF.gdb\CUT_MZS_01_23 FeatureClass" "C:\SIMEF\REPORTES_ESTADISTICOS_SIMEF\192.10.10.66@simef@simef (2).sde\simef.simef.REPORTES_ESTADISTICOS" CUT_MZS_01_23 "CUT_MZS_01_23 FeatureClass simef.simef.CUT_MZS_01_23 #" UpdateSchema "CIMDATA=<CIMFeatureDatasetDataConnection xsi:type='typens:CIMFeatureDatasetDataConnection' xmlns:xsi='http://www.w3.org/2001/XMLSchema-instance' xmlns:xs='http://www.w3.org/2001/XMLSchema' xmlns:typens='http://www.esri.com/schemas/ArcGIS/3.3.0'><FeatureDataset>simef.simef.REPORTES_ESTADISTICOS</FeatureDataset><WorkspaceConnectionString>ENCRYPTED_PASSWORD_UTF8=00022e686669516766663041654f7463794138674a6c4f774b537663645567317a4b61703833356d51675a44326a493d2a00;ENCRYPTED_PASSWORD=00022e68494b5638724742483142615a6965435056344674535857724c32425076546353392b6c654d6e32627377383d2a00;SERVER=192.10.10.66;INSTANCE=sde:postgresql:192.10.10.66;DBCLIENT=postgresql;DB_CONNECTION_PROPERTIES=192.10.10.66;DATABASE=simef;USER=simef;VERSION=sde.DEFAULT;AUTHENTICATION_MODE=DBMS</WorkspaceConnectionString><WorkspaceFactory>SDE</WorkspaceFactory><Dataset>simef.simef.CUT_MZS_01_23</Dataset><DatasetType>esriDTFeatureClass</DatasetType></CIMFeatureDatasetDataConnection>" <operationSequence><workflow><AlterField><field_name>sum_sup_ha</field_name><new_field_name>sup_ha</new_field_name><field_is_nullable>True</field_is_nullable><clear_field_alias>False</clear_field_alias></AlterField></workflow></operationSequence> CopyMultiple "'C:\SIMEF\REPORTES_ESTADISTICOS_SIMEF\192.10.10.66@simef@simef (2).sde\simef.simef.REPORTES_ESTADISTICOS\simef.simef.CUT_MZS_01_23' FeatureClass" "C:\SIMEF\REPORTES_ESTADISTICOS_SIMEF\192.10.10.66@simef@simef (2).sde\simef.simef.REPORTES_ESTADISTICOS_WEB_MERCATOR" CUT_MZS_01_23_1 "simef.simef.CUT_MZS_01_23 FeatureClass simef.simef.CUT_MZS_01_23_1 #" Rename "C:\SIMEF\REPORTES_ESTADISTICOS_SIMEF\192.10.10.66@simef@simef (2).sde\simef.simef.REPORTES_ESTADISTICOS_WEB_MERCATOR\simef.simef.CUT_MZS_01_23_1" "C:\SIMEF\REPORTES_ESTADISTICOS_SIMEF\192.10.10.66@simef@simef (2).sde\simef.simef.REPORTES_ESTADISTICOS_WEB_MERCATOR\simef.simef.cut_mzs_1" FeatureClass CUT_MZS_2001_2023_D 002 Server=192.10.10.66; Service=sde:postgresql:192.10.10.66; Database=simef; User=simef; Version=sde.DEFAULT ArcSDE Connection Projected GCS_WGS_1984 Linear Unit: Meter (1.000000) WGS_1984_UTM_Zone_18S <ProjectedCoordinateSystem xsi:type='typens:ProjectedCoordinateSystem' xmlns:xsi='http://www.w3.org/2001/XMLSchema-instance' xmlns:xs='http://www.w3.org/2001/XMLSchema' xmlns:typens='http://www.esri.com/schemas/ArcGIS/3.3.0'><WKT>PROJCS[&quot;WGS_1984_UTM_Zone_18S&quot;,GEOGCS[&quot;GCS_WGS_1984&quot;,DATUM[&quot;D_WGS_1984&quot;,SPHEROID[&quot;WGS_1984&quot;,6378137.0,298.257223563]],PRIMEM[&quot;Greenwich&quot;,0.0],UNIT[&quot;Degree&quot;,0.0174532925199433]],PROJECTION[&quot;Transverse_Mercator&quot;],PARAMETER[&quot;False_Easting&quot;,500000.0],PARAMETER[&quot;False_Northing&quot;,10000000.0],PARAMETER[&quot;Central_Meridian&quot;,-75.0],PARAMETER[&quot;Scale_Factor&quot;,0.9996],PARAMETER[&quot;Latitude_Of_Origin&quot;,0.0],UNIT[&quot;Meter&quot;,1.0],AUTHORITY[&quot;EPSG&quot;,32718]]</WKT><XOrigin>-5120900</XOrigin><YOrigin>1900</YOrigin><XYScale>10000</XYScale><ZOrigin>-100000</ZOrigin><ZScale>10000</ZScale><MOrigin>-100000</MOrigin><MScale>10000</MScale><XYTolerance>0.001</XYTolerance><ZTolerance>0.001</ZTolerance><MTolerance>0.001</MTolerance><HighPrecision>true</HighPrecision><WKID>32718</WKID><LatestWKID>32718</LatestWKID></ProjectedCoordinateSystem> 20251026 12201000 20251026 12201000 Microsoft Windows Server 2016 Technical Preview Version 10.0 (Build 14393) ; Esri ArcGIS 13.3.0.52636 CUT_MZS_1 CUT CAMBIO DE USO CONAF MACROZONA SUR Cambio de uso de la tierra entre los años 2001 - 2023 File Geodatabase Feature Class dataset EPSG 9.8.8(3.0.1) 0 Simple FALSE 0 TRUE FALSE CUT_MZS_2001_2023_D Feature Class 0 OBJECTID OBJECTID OID 4 0 0 Internal feature number. Esri Sequential unique whole numbers that are automatically generated. Shape SHAPE Geometry 0 0 0 Feature geometry. Esri Coordinates defining the features. tc_01_23 Código del Tipo de cambio entre año 2001 y año 2023 String 2 0 0 d_tc_01_23 Descriptor del Tipo de cambio entre año 2001 y año 2023 String 25 0 0 cod_reg Código División Político Administrativa Regional String 2 0 0 nom_reg Nombre División Político Administrativa Regional String 60 0 0 cod_prov Código División Político Administrativa Provincial String 3 0 0 nom_prov Nombre División Político Administrativa Provincial String 25 0 0 cod_com Código División Político Administrativa Comunal String 5 0 0 nom_com Nombre División Político Administrativa Comunal String 30 0 0 balance Balance String 30 0 0 periodo Período String 40 0 0 SUM_sup_ha SUM_sup_ha Double 8 0 0 Shape_Length Shape_Length Double 8 0 0 Length of feature in internal units. Esri Positive real numbers that are automatically generated. Shape_Area Shape_Area Double 8 0 0 Area of feature in internal units squared. Esri Positive real numbers that are automatically generated. 20251026 iVBORw0KGgoAAAANSUhEUgAAASwAAADICAYAAABS39xVAAAAAXNSR0IB2cksfwAAAAlwSFlzAAAA JwAAACcBKgmRTwAAIABJREFUeJzsvWnTZNdVLrjOkPPwTjWXSvIoWwgZG7g2uhgDJuACQXRHf7qA Ozq6P/GRjx33b9wm+Bc0DR0QTQ8EEQwBl2tzbYMly5Jla6j5nXLOPFPH86y9ztl53nyrJFWVpVLk ltP5VubJc06e3Ps5a3jWs+L/62ZeyHY8laMIRAIJJMkLSdNc8jwX/JhRFEmzEUoUieSrTMIgl0gC aQS5xFEojVikGUYSBIXEUkgQBBKGoQTYXyBSFHgUfAShPuOBgc9g/3yEhchqIkW+kCBLpcgTCYpE imwleYJ/p9KOGtJqdaTb7kkjbosUseR5IEUe6JcIC4kboUgRSpIkeEGazaZIEEmaprJczXnMIgz4 fXCeebGSVZpImi2lyFfS7bbl9GQqVy9eldPRiPs5PhrLfD6Xa1eekUajIb1eTyaTiTSiSG7fvi29 fkf2dg9kNk0kz4XXbrVayXQ65ue73a7s7e1JFOO4kbz66vdksVjIjRs3ZGdnh/tcJiv5wes/lMHu jgx7fYnjWFqtFj+bp5nMZjPuF68VOIiI/l0UvD5hA9s3JCv0t8uyjM/+wD71twn4wGexnT2wPX/3 Qn8XnBeebVv73c4bYRA/8H3sD9cFD+wTvw32j2MmWSoS4ffghCm3x3ar+YLfH9eK8+YxocyDz3Y7 PvLD5qNNaHvYe9VrhYRB6CY/QEqBClva9u6pBC0FsmriE8DcNuVrWGAF9h1IEIYSAhrDhggAMYsk CsK1BYRt9Zzdjty+8KKeR1ACb5YnXJRxHPIhUkiarSRNV5IVKbePGw0CCf6+c3hH+p2BzKYLeeaZ ZyRJMplNZtJut/k+9tVptWR3d1cazYiLcDjckTCM+f7JyYmcnBxxoQF0AC63br8rFy9e5AMAitdw PHynTqfD14M4Kq+HfVcu6CThAl8ul9KIY/6N17EfYD2eG41ICvznvj8+b78nBn4vApwDpdw914HI tn/886tY2z+O759bXju2bf9ewPKDjC1gfWwAC4sFEwegBHDQ9yKASIA7abEOVA6MxBnYZ8DKWVZh iMWIBZgSMPSY+p5aA1kJPZy4HoDS0osbEtOaMxDFBusTnMdzn8HftDaKlAtaz0FBL88zvgYgKIJc wijg3/P5VAb9Pbl7967s9Hfl3r170u8OZDyaSJblMp1O5eToWN566y3Z398j6AyGPUlofQKAVpJl CYEFxwawFJLJ0fF9AhceuLZm3QDQCKTSkMFgINPFnJ/1bxZm+eDcT09Ppd/rcT8AO3yHTrMlaaFW FSxlu2b1h11n36KSGkjgGP4zxuMCCwMos6p4vg6Y8ciylDcq36J7UmCFsQWsp3jAzKY5HlST1beW Ak4sWFEALVhBWPwKVHif+FYujnXQMlDJ8/MnYFEoWCkYYmOhxZVnhYR5xhcana5EcDuKgJaEnaO/ O913sQ5YuS5OWCD4ajwHgKMDXXxvnJtabGo9AXjg9h0fH8vO4EjG46ns7x+UFs/aYipgtelCxLXr dPoEH4AZtm+1GwTD4XDI7QF6cHfwgMVmrhLczvliLkWa8bXKEg34b+wb2zQbDX5XfAbnEnd7witS qDVZt5DsetddRAz/GNXvbW69Aof//LgAywdPWrdxZQ3CwjYws3P3AfRxjS1gPe0DlgbjWbBiqpfh ciiQKfRgQoUeMJUAxddtm+rzAAHsIk1W1aGwbeQ+K7lEnKS5FCFiXTgY0EZ3TKsI/0UNjV8QW9QF rY5RSBgBjSqjy1w3W6iMZwkADAtb7+xFETNeBquo1WwwHjQdjeFD0poxq6jfH8rtm7cZv+r3+4w/ 7Q13ZDwZSZ6mBHJYUXHUlN3dIa2kO3fu0AK6dPkCjwXrDVYR3EXso9/vSbvdImidjsd8HXEcWEyI N9mCxvcH+FnMB9+1tA69Bc2/1667Wa769yZAyp31hocBrh/nss8+jmFWoh3fB37f2rPj4rvba7ge j3tsAespH+Ud1Jv0CigVGAFH7F7Hf5eunQMrH8BqcTF/cVWWWOWyADRiWD1FwHgVEA3bwp6IsZho R2A/9lmciYKhLkgs8sr10+NXx1S3A4tEAYuxOFiNbtEguGsL6eAA1lQoFy40pdFQSwkAhmFxLIws xSLMGVfqddoyny3p5sH6wYLr9tqMc+Hv5RJB/6CMaflW2ng8Isjt7O/JsD8o3SZaUKG6TDg3ACau hSYV9PoBvBD7sutp39sHA3O96r914MDDt7J868qPOz3UwnoIrtWtObvWPD+47F5ME9eL8bkwlDh0 yZPHPLaA9ZSPcuLazHNWDHChnKvlnMUiWHuhHOvuoNtVoXdwTlZYUbWgflDAB8z4iIIGXUNOYABk GXfS/fC8vH0DfpAda3IBKHgqrBZrd+jyjo2YmrNeUmQknbubrFJuB0DqdvsSh7Gc5lNJliuZzebS 6w1kZ2dPeu2eHM+PNfDe6Uin2xac1r2jI3n3nVsMwsOFA3ANd67x/I+O7hO4dNEqaCaJxrgAbrDG JIi5P4ASwMsC7fg8Fi/cQQAdLrwF7Q1YzOI1l9CPWdUD2b5lEzjgsPd8C8u2e1zDB1HfxaMlCXBC ytl/zf1eeN0szsc5toD1lA+LN5WTGWDkrCU/ggAryyABgXYCWrlQ/H3Z0IWBScfFE5xdRBjIceEB F5ExLLhzWS4pA/qBNGJQGPQcETei66hHJgCcZwHoIhRJkqXEjGMpMKdZwtdIh0BQv9eTNMkJZvP5 Qob9HbWS2j1JkpTunAGa7jOWRiOQ1TKRw8NDWdF6Kwg4ABoAjtITGgQifAYgdnR0xHPFdkjVYyHC ehvu7JaWFACJlpNnASGmZpYGPqMB/Ii/BzKc/C6e5WTf3bdufcpD4awuozvgePbZJ50ptHMrqRV5 VgKWbxkagJrF+TjHFrCe9uECz87HkjzIJCxCKbKA4SQpY04OBCyu5Ygx+DsyCLF56WJbOk8x4XT/ 7mUOxpTyRBpxRF4XMniwamIJNJ6D7CIW2gqxokgk0knOQLmAu6OLXBfhetyFrmaeSgZaRAQ+1kpS 8LoKxIaw0ENZpXDj5rScJuOxHN4/lm63J298/w3Z2zuQ2WQunU5XlrO5zMYziYOYQfX5dCaz+aTk C+GcPvf5zxLQAC69XoeBdgTZYTFFUSjHx0c8D7iciOHdvPUOM5IAsuc/93l+Fu+blUXOUqGcK3wG IAhrxHer4iAsg9e5Z8EY6OAzePgA0HSWm7+dAQW29V1GGw+zth4GcbhOflyO5+5iU0EeahIBNxIX m8M1sPN/EgC6BayP2VjLErr41RnPUJxls2kuv4c5VnFtAFopMQ2xqmYcS+xiWUwaOo8Rix4ExZIi QfcQFlx1B7bFsJ7Ny1z8y/2bJlxRgqhZIQCGCxcuyM7OrnRafel2+ox7IeB/48ZzBA2QQAFCs8mU lh4sk26nI4PBDoHAMlx2DlhwAB98R3CtEHDHv0fjE1pJzz//vFx/5llptTulBYV9mktkfCssbpI5 HcgYHQCABpdQL/l6FtYHbgPW8+JUNp6UdWWgalYkhh/0PxMmeEzZyfPGFrCe8mHTQgPSamVZwP3s hvl6cN5SifZ+zSVcRzTf/MK/lNIQFBnvsLAY4O4hM6hgqNth0QI4NBYWSpp5QdyoyoT5i1GJo3pu CmBKkeBzUMVolDNWKNWg2ZFBry95GkgUInMIa06D7QCqTqstp8cntKJwrNHhiXT6PWl1mjJdTNdi R+oWRtJqNctg/Xwx5X4Qk8LxOp0WXboobkkMwFupRWQgZYu7jOl4MScFR02oEpSDs9fBZ7jrdz0b mC9/R++3ftxAYZlInxBrDwx73T8+f0eEHTy39nGNLWB9zEZ1x9OMIJNyLkvIBYFJxqyeF9N6wBz3 J91ZFjNAK8eqBMmBoEXoxM4ZeLcMIM4Hiw8WFoAkk5AZMqVa+IvQYjVBpIs2SZVW4cdz8PnSSsRf wLEA8aIZ3TTAZhw0uC+UBSFW1et06b4gMD8c9mU+mfLzoDooE0PdQwAaLCkAFWJVeP3+/fuSpMsS QEBlgJva7vSk1+yULhniZRZjMk6WH2Pyv4dddGWLV4vbpzQ8bBS1QPiTAC7fejKr0UCYGcwIN6p1 /pf7oDyJsQWsp3zoxM412O6GAsHmzJ+/jQam9LOgJZjtVO3cYl2eVURLBwF2slYJOHkBUIK7FkkM Uir4U7CqwliWXvbL9uNbCBqj0kXgL1gLLK8QlOYJq4sIAKTVFRCleA4I8kdxpGxzEl0zBLrUugsS SZYIvq80AI/YUVuD6Yi3AOAWidbJAWTMsjTXFLWMzVYsw50+z+n+fY1d4dzgGsLqCuIG6RWwvoyG YAHnstTGu+78fYjphSyXizVqQJ2DZUmPOgAFD/j347SyfMvKaAsGyhGygGW8c51O8aQKlLeA9VSP s9Oi4koZ291ZVwyu1xntDrTezxFrsRbe4RPS0yWIEbvCgsOzkkbBhwrh+4H9VeMH+Yxs3xLBIkXc qzpHQirdDGXBa2lOUCB4D4tL3cIgyKUz7EiyyiWOQT1I5fR0XNILZrOFLKYTGY/HBDV8BvEnlNbA QrLAOawrfAZgNJmOSv6VWmhdx/cK5Oj4RBbLVBrtDl1CvG9UDN8a0eytLn5cLy785YpA+c47b0nc 1PPAw2JexpKvu37B+wSuR3XJLKbnlwZZvJG/Pe8Z6zeis9bk4xtbwPrYDBcAXbubP07LnGWu/Ku8 mzqrCQ+U+3CxBbBSKmY0Y0D4dwEHssqEmRthd20tctbFymMEVQmIARbPIteFAxNFQ/saJ8JjtUqk 2anIirC4MHgOeSG7g6EkbeVBIQaFQLpZQXiGBTZ1gDaenBLEnnvuOVpUoB/g3ABe+A7Y5t1335XB cE/ilmYJ/XiOnZMG7gsG3f3zGh2fyMl4RGpEs90iUBoVwILcZTbOi2MFHhj8JKwsi1f5NYQ+5wsu oT8nzoYNHu/YAtZTPaw+zwiX/oSteFhn567PDsVd0tEiHKfLe5PB89AVKGuMHpZNLoFqsrj9hwx0 NxCADhtSILCOCR0IA9JaH6iHYWUjFm9YMeXx4P7BkHexnwSqDBlS4/iQ2wHdUbcw6BHiSyKjB4pD JOPxXPIE5USFNJu5TCfzMhO3WMyY7btw+QILq7HwYBEdHR4RLEAQxf4mkzFfb7cvs56w2WjTLex0 eqRFjEYj+dGP3nIKEbp4WX4jQVkA7WfT9ALhZgIAAiUArmsus+VMRqMTuXz1Cj9v9Yml5eI+bwD+ vqgKweNzCX2wqmcLQW2BKw76Sh2s7PlxJwG2gPXUD0aVSiBoNuB6cI0olCk26JonHwsMcwcmBeRZ MCs15lCuL7c9rKDVfC4XdxG4npLJ3ggD6bWacu/4vhzsDsiViqMeLQ+4XXm+JGmz3+vIYr6i6xUj xpOkXJi0lVBc3GzRigEtApwrAJ5ZWnjOJZMkTSTLUVw8krRIZXcXhE0UHScSN1oSRwEX+nK1kIsX Lsh4/LY0Gx0Zn55KmqCWr8P3251Y4hbczEDCDsC1K/eODuX2uzflmetXpdVu08rh8cElGgwITlSz kED2mwe0sn781jt8ff/gIgP5l/f2Gb9K4M5GkexdOFDXMUslTBbSH/QJfovlnBYWkhF379+Vd955 h9/zwqUL5I7BkrKaQ195obRi3Cg2AIJfr1d/X3/L9wYY57me5sLi4Vt/9ppkep4g2cIixfelSxvH WwtrOzbhlQbM1woGzaoCP8qMJxfkJZsJk84JANZqb2uTWKTf7citOyeyN+jLbjeWw6MTmY9P5Or+ vkRRIZMVpGCQ3UNsI5J+r0/rYzIFeOWMG126eFmKVUrBN4AIrBQAANyy0emYYLe7M5Tj41MuXKgt XLx8QcaTBYHu4GBPxrMJY1etVlvu3LkvzRZKdVK5eLArx0ep3Lz5jqM4tOTq1ety5/Z9OT4+kc9+ 9jMSt0LJ8qVMFhpgb/Y6EoIl3+3IKkkYq1JtrCGtLZ7/ZEIAu3btGktwVNEBmUaU3gTS7w8IFkUY 0rUEIBmtwdxDFjqLFQ/rNW02YxZa49qApIrvY+6f71KapWWxvfWfPHjs1ks93mX73+QKPkk1hoeN rYX1MRimumCjKl6u/tbXHWQhG2UTnhoz3n42DIBIoxHLj95+V7777W/LajGRr/zcz8szz1wh2HS6 Lbl165Y8e+NZBrlxt7158zbjP6ARwBpBEHx/b1/GEw147+4eMOOGbTHwOkDi5ARAsZKoEUq315A0 q4LYh3cPZWe4T7DrD3aoYIo4EoLr7UZb9va0ZKbTVhcLYIN9xW2Na7G4GUXPXXW/sA1iUbAGqO7Q 6/M8sA+A0M5wh0F9ACgsK2yDmJOByBQUirgh/cGA+7B4FUCvtEKoI1bxr3BckFgxFNjOstfNrawz 2oMHxK8ex6iTUi0Zsok4isGkgPxkxxawnvKhenjqEtKKcuGe8t7HEJWjYXrpc/3Pych4AFfuk68V Mp0tpNftyt17d+SN11+XL37pC9LvtKUZBnI6OpFXXvmu3Hj2uuzv78t//t/+s/zy136VC/zTn/6s /OM//iPPBVyn0eltCuhh8sMlQkzohRc+J6+99iYn/k//9EvyzW9+U/79v/+a/Ou/viGn4xP5f/7f v5Rf/fpX5fDolvzCL75MABq0dglQaZbL0dGJJIuZtJpNubB3RfKsIVmSqeRLkMugP5DJ5FQ6QYvA 2k7b1OrK0oI0B1h/1y9fkWYjUjAancobb7xBUAJz/vLlyyXHCmDnZ8cAdPPFQvo7u7QYKZToJGUw DGRRb0dLpawD1HpEDAWDs2U2dbJo/W9/PCpw1cGvDlqqiqrEX8ta+iRXJFJ+kmMLWE/5gMuhEn06 GNx2RPOS2sDC40KD5tRpV54WOEyW7KvPe52vmspHATMsFc0GKjsboDFfTOTipQN5/fUfUGr4+vXr XIx/+7d/K/P5Ul566SVqUgGI7t29TwBA8BkBblgZ3/nOf5Pr167K5z//eRYuw3L6h3/4BwLZ/aN7 tJ4+8YlPyD/9l7+VL3zpZ8j3Oi0mdJ9QEA1LqkhXcnj/Pq2bk+MTuXrxWTk9OeH+bt26Kc8++4xu HyuYLBcrbjudzugKgqKQpQCvGV0/WHlWKA3lUgAP/o1nWIpWpgMQ63S7sntwQY5PTlgriO+Oh4oJ qowyrrXykmyhay2e8bxUTPFsQN3nZNVH+JhdsTpo1SkK9UqE0iUEV+YJKYueN7aA9TEYPveK/6Z2 FAT0KiY7Mn1GEjWKgpW2bIxisQQmk16vK5PxKS2oWHL57ne/Lcv5VF564QXGln745muczF/84hfl b/7mb+Tf/fxXeEdGrd3rr79Otvuzzz4r3Y42gUBG8ObNmwSLF198Uf71u98hWLz00hd4jJ/+6S/K D37wfdIaTIPK9NPbnaaMTqH82ZL7h8esC/zMp24QoHAcgAjOxVQ9zToAQCEzlzr3DAMW3sWLail1 OyrIByDCZ8BwB6DibzSsAMAioYBtNZbV4bbtTkciV0eI62jZPoAVgtHaTMPqII2qULlVdV6a/b0p C/hBKQvFBwQUAybfFaxTFZ4EbeFhYwtYT/lgkwdkAk3/irF3VWXA6za3Nd7gXEcTjSuLis8ugnLC xjE7yRTJXJ65dlm63UgaCDQzq7aST33qU1TgBNP9d3/3P0qn05b/8Ju/LoP+ULrdzzLIDqvqYP8C 9wsAeOaZa/LJT36alIVf+qVfIpDh8dWvflXiuO06yaTyxS+9KLuDvnzlK18hqCGrOJ+tWLDMmFK7 I+PxRJoN5THt7qp+O4C22+3ItWuXqewwWyIulkjYhKUF6gAAsE2ADDJ19QAuAEi4dwAmsypwHNPQ gjWGYUBIJjwVHdBBqMrq8d+OBAoL2GJeWh+onzclhvNq8uw3OA+ogsdEzqy7oHUelRVfb+JV8d9P pgLn3LEFrKd8kLYQOioDXkCZFygLsKrca45y6VxDI4A+IHDLchwlTkHErt/vyuuvvipv/+g1Odjf lWtXLsrt24eytw9LZJcfAaDAJURmDq4fNKpgHSHY3ml35OR0RD8VLh4mOt5brRYEClg0AJKjwxO5 dGkozeYBmfn3j27J2zfflk9/+tMymo61XdeFIQEwCGOZpVMHHi0K+QFURkezks+ErB9oG0m+ZLME VU2IZZFqMBnHBiCdnhwx7oXPWFsq/E1ZmCxjLSHiZ4hrwdLSGsWWzKDV3unSAlMxPi2c5uddkB+u KwmwrgsRrrtJx2BYVtEAsu4K+oqjNh5mjT2uYRZWnRTqv/+kagbPG1vAesoHy+mcZFXggMoKnl0H LvKnUOMHDXZI1xrPSkyzPcBCcXERELjcgiMDHCRLco2W8lMvPi8/fON1+eKLL8i7c7hHIEvOy7IS FcuDDvqchFR1J3IZjUdl6h7RNnXXlK9jrhEWN9wsxJ5gecHCUo7VRF0skj8XEgh0rbqUqGEpTWdH 7t+9R1CBdXZyMpZBf4ekzLy4xEYUsK4ge4yMXqfdlTgTOTmeSLejtAFjsFN+BoqjwyHBDzErfBe0 DLNsJt7T/oVTBtLbvT4t1OlkQgvN4l3tRpOfNdDD9cbnqE/viocxjEfld9mpK4g+iGdVPCKJFMf3 y6IsyYBhsjv1fVUFzkoebeLm43hZ5No5CWhamFu1hu3wh3+TIxDB4hJnXbm5TE0sI2PVbPiG02C3 OJjG5SHWpppVKge8JH/ozt3bLD6+e3jbtRSrinvrJRwArjjSwl21GlQAzrJpesJOGLBcVBbLqTro UFIYlkeqkjamVQXAwrFOT9EZZ18W05RkUXCbAC5XrlypslrIZRXUsikXnB0TruhqqVYTC6EXCwKP Zfyw6KxsxreMsE2DdYhLcrpwHUz+GPvIk5DuYrOlhFiIG6r7pedgdYybGjW8lxhV8ZiAYKPV9D7i ZNXvqzee0lJ8Qv2ZtxbW0z5cNg/kUWO0m547VYqthMVLP9s2GFAn1dZftjtrboDP5SR3otTls5/9 tGSrqVy5fKAZuu7A3f1N90ktCVIqXE0cdNIp4lCAvY7ylELCpgMsJ1GwHpcBcFqAV11YzbTlEgFw UHaTquwxzhPHg6WDHoRZposGoIGC5avXLtP6w7m2I8TFWmT303rhfpWoGUmDWUKAi/UMNLY9zg1W EsDJb4Ja6cyrtWh1kQZqAMFuq+qWw+tcbqN/Y388J+uAXf9ZzykkLmrPj4OPtYlW8X7269+oKmnk bS3hdpyd1pwY1tUZN7XQeFXa94F66+RpkSOqRcilZp93E3Q1xk5/3RaEBpXDIGNr9+UUTHXU4C0k cq3lm020n9eFqQuyIj3aYjDSpP+axdGqjKUWOJtl5S8GFB+VnY+zTK0cpwDRanbI+xIQTNNAmlGL dATEpmBthZGWr7TbTVkkqZbKpOr2aKNZLbi2BWolMlZ6YueO6wALzORV6EY6aWRz3co+hQC5VpOW GbhqeN8ynrgEfissK/Cuu1sPAqTiMdbq2T42WUnvJUbm/75rFtYTiq9tLaynfKhKZiF5iKJkAIcj g56zvbmNGgQ21rKqhdrUN7CClQOGO9y4xWJCS+QYOuqdhqQBGjW0WJKjgFmpbIJiYJPYVymwfetD ix2VK11XI1Df1PYhTgPLZ1wHrkFi3OnI0f1j2R325c7tQ2mEKvFyfHwordYlWUyn0u61CVgAlOUi J2CtUFJEvtRUAtHmERikTziVURzn0qVLfM2C7VaQDDBCPOvW3XvMpOI9X4e9JFa6GjwDceWwrUoL rtFor33384Cr/vfjGnUr7oNYWD/JsQWsjxkHi2Y5ddBNJUCD7Ag5KRYoQNj2FhwNcstSZZ7lowOq BbBght09OT1N2eY9X4IOoFkxABTlkb3UvLpP0MjSGJd/x14P5PKsvfq4s8RF01vSoD2AEXQB7W+I noLmXtG6yRZy+fJVnr8BQ2mdOSBBfC2LXfyt0WCszbrrmCVkTRQsWQAQM0UH+34WpAeB1K69H8vC +fj9EBXQ1PW0bVGX6JMzbT8GTpvIo8EGJvwHHebG2bHYU9GTeH6vnzeJHt9SexJjC1hP+cDiAylU DQ6vMapN6GIzwJnfVXYQJs10XTAP4IYSmTxvSeQamVrmKIG1QinhTtkGTHdcpeF9kLCCYD9tX9Wi qUVXEVmrz9JKSd3fUcXyZvYt0XOH+wfgwPNqntAiQlIAlh+pDa24iqvFLWlBAidfuALknkTIZI5G a+dqGS8AnvUbtBiZBehROG1KC+gaY0Bs2UKlNegSi3Dy7jsbIPiNRn23aj154dqsPSEelj98oHw/ lAm7tnZz4Lk7Pto2S7gda6OhYu1Vl5zSktJJB2iIEAOinrubjAjQOwuqnKToGej0sFhyQUdRiZOB rJhpHKFQOFKrDA0cuHWOADqyQmqTha7hqgkKghYBMFMLC8fHpLaFAVeJuhHqghK0ckrLsDlDgfhO IWmBIuLEyfECTKCfrvGoCzsH0mnBLbwp165dl9lYrZdOB5LGhXS6TclcdpHuXDOghhOyndC+Cgso omYkiyJYbjruvkYVLCLEybCNKZJaHAu0BlhY49GorDcEqAG0MCin3ACRNJZG0ykyIOAfKGChVZkP PhbYt8UPqofvtoWPuSW9H8PaxLx/L58PNzQReVIlO1sL6ykfyl7XGjWrIbTEE2NQlg7kXR7t4+FU UX1N0kKtAarTuIA7Be8Qk2KWDsHppcQR2nmtyNpG49GoEUvC5hPoloPFp3dSi9dYQ1K4TGZRRCCI iWtJH7lmnHkqYdDUBy2nnMJ9OGaazSULcMyVIMwzO52xyUSvuyPtdp/KogAOkkVPJnLh4BITAMsw o7WE47PZxGIig90BBfxGk6m026m0e0MZDLt6joupDHtdZvqW4ILBWnPa7NiPWUGD4VD2Dw5K18dA hfLJzlKzImm8fjKeuMwk0oKRFGEkyySllDIKhpsRCqJRSaDXyoLvAPAwCqRIc1pwGQ1XvYkE4Ms5 dx9ukgbiAAAgAElEQVS0AWqNkVbyIHB40HvB2vcxN9WoFlbqdO6ntQ+JZKuMIQVY6fgbFi30ytRd VE6WuY5+P8g8zUrV2Gqn6y4wbl4+iG4B6yke5vat8bCcF0hLC+FkmOZsJx9IikmTgx2QSpBBSQAt xRuuo45+hvtx/QaLIqWSAcimyM5lWUjyKQAOonV5yh0w6KwkQe07aBMUZTGYxtpOzE1GZjHN4oFx ZjwptyDZi5CN7GlVwSICdKK1fNxCOUxINxVUi0Fvl1YRBpjytPTMpcw1vrZK5pLksMhmskwhJtjk fpOVax3fVOKk7cdKbWBVIQYFlxKLDN8P/0aBNIAMQIl6QzZN3aBR75feUF0indUan2YyW67Ig9O4 mp+0UGvFSJj1R1FaXNHjn1Pvs2bRyKFmEfq6XubW2r5MhrrMJlJ0MuL8O68/dD0RsQWsj8HweVVr 4FVKKAMrXDcYpt8ykRSAkEscLl0Q25J1WGTo5puIFIlEKIJmdgwdaKBN7u6slCnOWFDcCHWSah/B KkYFsFLvAKKBcAv1VXUJldZQZSQ10G9LxKRZTu8fS9RQ4bse+g5moSwXY2l3W3L9ynV587U3yMPC wGIwq8BAAwtI1RmmEqEjtbMebDEBkBLXhAJBdSqUui7QsD4BTAAln9Jg5FW83okatM6oaR/F0oxi L45TkPHuc7EMjIzPhf1YKZEf4zNpZJ/2EGx01c4pXn8fw6czvN9AvgkV+rQGfx91nXs/TtiIYskS qMv6X8clHjxLy49rbgHrY8h4Zzt6V5cao+uyxBIx1oDJ4moJXcsuyZeUNaaqAF/TOBNjXEGmpTsE MJjvmIBYmCBM8h/Ub0fdIOw2332wFvRVh2CN+VRyKsrZ0uylujdBEJd3Xj7nKLLuS6ODWJe6rHmS S5bmtBRXSz2mJQJmM9VUV3njUMIol16/KZP5hICLuj+AUOr2b+VE45OTUqTP6A1mLRioWAAcAKZ6 7lW20AckSy5Y4N6vBaw3cLDgve3HX+znqTlgrFtZjx7D2kRneK8cL/+727/9tvYG7HYjwc3AGnnw VuWViT1o//a8BaynfGjpCWJOKuC3RgwFnQGZtdwpOvAt3cCyc0GAUhOVkiGRUhBXCVl7CFdwnuZU 3QTQ6WuaT2RgPsakbJJNn6ygpunFKETZ4tBu1xo6fAacroguGZtbUG8e1hAsK5TOIF6BRR9InEeS I74CuXQ0eFjMZTxFjWLMuBke8+milDWenC4IJMPesKIfBAj4J6USAwCLvQ5X6r4o07ySoaHUsQMY oyawvMbVSuJvVUU94THxGaM/mIVhcSCzIvi9vYC0gZ+9btpYBpTmfpoF9pOQIc5LccGzIn0PC+qb BWg3DSPZWukRrhcEEWHh4pqigNxXumg12q7o4Rztr0BdzsLFP7eA9ZQPdb/sTozJVt10TZxPf3AN 0BOk4LbxjUyajCHB5nAyJ4COUEEL1g9oVOqoKYjBzIFqJ+JSkPdtNduymFdBY/Qi1AWKxab8qKKY r8U3igQuosNVBjBwV8bCR8A5rFwGiWU0nkuWq8QNFEI77b50egNpBBDvQ1G3AmQZc+oNS5crCDOZ zkYM9djCr6RdnOvVVFoCFCZgYVnCwILtZgmZDj3eM1dRaRcVKdTP4NniNyCyOI/Ftmx7drd2LpW1 OvMpIHUL6CzTXR55+Ps3wMJ4L4Dl87B8V9zicufpadl3t72f/Roa2cJ2Wu2gW2wB6ykfBZnmMFis TMexxPVdFytSUPCbVGAotSGVOFDWNR/8YM6gdlbkLAxmWy9YEaEDyExjLI12ROApQkxs/B1KkqEB oVoGaBC6SjNZrBz7m+YeOvZo6QYoEBozQ3YQ555xQhrfCrbc1ctXJc2WPK9G1KaOO6RkoGgKcOz1 Vf64jJs5wibu6AjYo9U9Mop+WRBdvVQtwNHpMWNY+D4AJNz1YRGgoBr7tMC6tbCHFQbAwn4Yf4o0 4eA3PjW5aqYcAgWtMhMIKypaD7D7sSufBe8v8Prf5WteFvgDjQ10hjpAPmj4wOrzsbRP5Kok3Bp/ zRrUWn0mwgms8TS1EJ6IWVsh5yAsfBjfmN9bwHrKh1lPxnuhnIzXrouhcKbFsXi05hD/UVIGcaFs JUWoXY/pnonL+CAFnyUygxsmOZss8I6YrndRWTprxdq7r7C/QmvyEChHUwpwjarPoCDagSP3t2Dw H3pVtLAQnHdWllohhWQr/ezBwVDarQFVR+eob+z1ZL4Yl+zybjcvXRNK0gTgPmmzCXLAEBSH5RSj KHzF7SiFk6W0rgz0AFwALJyzqTfAosJCM/exjEWxqLviIZmlZIsXwwqrMXAuOAezHPAj2aIHqOF8 7Fr5FAMfsDb9+1HGeQD1XgHLzxCaxYjXLINqsT9zp3FDAIjRdUdGRTvNlYPg5UAL2VRmlVMN2G8B 6ykfNLtdaQvv6l4MqzTznVuI1+HyQQ6FKeWiJZ12IavlUvIE3ZSdawOLCqKAiFcNlCAaA+hqTT7R JbnVGZIbRLUEUVkZuKagTIzGU5nNl3Ln7n1O7Ml0Kp/57KcoFQOVUtQm4jPgdTVQDrNCL8JUGq0u dbOg0d5qojvNhC4heFbanXkqg/4Bs4Zo38VOOZ2OtJo9uXvrrly9epWPQhJpdyLSGqjIGjupl0wZ +6QSBIXs9DUeBbDA/iEyaJQCLDosMlhWGPgeADAry0GG0oDJL4y262RkUtPTqrP9fffR1wczMDI5 G79aIPAImnbsTdYXhqlM+JlAe5/ubpKuAaN9hzqRdNOz313b3HADZXsNrrTJ9JjShn13FkhLIa++ 8hrVXGHNggqDuTEaTzQR4yw3cy+3gPUUjnLiGI3hnMp+ndjV32ucLcaxYGqnEuAORlUH3Ze2ZjXp Xncscy39cwD5sUAjVHiB2t1YIrQEazBYCpP+rbfQNBTFxqira8rtW3fZFgwaWxDVS3kemTQQkG+2 SBQkvcvFLyazsXQoiqfWR6sZ0fqhpTUaswMPCpSvX3lOppMlFwdkmKlB34AhmTqmO55dt+YmXEsF XyyUPFlxYcECwGsAJ4s/mdVkCw0Lx/oWGnhhWOGzn2kzC84Awcps1tyu2jX1Y0h4ZlbTkVRTZ8n4 xdT+2OQ++oBXFWCv13Ouz5f1ubQJuPy/NzVytWE3ErsW+IxdLwOwFNc2Wcl4BlJvmx2OUlcShUe3 rdboNob1lA8lempD1BKMDMRMatv1JdSSF6MLaFDe7rDaAR7WGTS17DOknpbpd07kcL07NDONThwP 4nxkZCMeFeMO3dTOPGis2u/T3YKFhL+Pjo4kzWC1IbAPjfRC5oulZM2IzSDQjxCTuMgzuglHpydy EOxq01ccFi5ikcvJ6JRtw4aDPs8PYnqr1ZhnBosIJTbtTktms7FETVwlxMkAOIE0XcwJ58++hI5q YQ0vjANlwXG8Zj0HLdaFY6CDDi0XXEcXnwLzHO4zry0WoyuAbrda0vS4VfXFXbde7H3Luhpw2ij3 ERpgaBbDnwdrdAnSPJx1xnPT398P8tfjZv7v7w//39a+7LyhApDqflu21ixQNOB9840fSRhHMtgZ StRsyOl4ymxwp9WQSxcvyGIG1z4vGfFbC+spG3qn9OoGjWLgMd2t+Fnbevk0B6fmCflk18AQmTYN zFOntJKnsc6/KUppQBh1zQhcrIoPgE4RrwVJS5E71P1IQksHk7PbhZuQ0+SHdUVKAGI9USDj+UKi VSFhjPbzTckDBStIM3e6fbZ+X66WMqRltpLx6FSyVC0guH6ULJ5MSq4UFoVZN/PFTDphp+xWY+4F Bt3LyUT2hgOCKYAIrp5P5rR6QrxnbHhb4LAe0N7LQM7cLiuWNnepLnlccqxwPbPctWRbByy/yJuA 7GScC5dttGPAGjVA849jnzcmug9GpTosYmUbMo8+AJ1Hqyj5Ys5y8l/bZInZvqzHIfltac758e6t m/LjH/+YLuG1K1cpFYT3x7OZNNE0hGqxrhj8URbPdjz5sSm1TLBijKkiiNrrm+KkvuWkXp+LUeRY QFrGwlpERMOcSB4hyBVPh3CjnDtjbGWSKWwBQCAQLhaaQ8TIArp9sIloRLCJW00Zj09lsLsji8Vc hntDLsDD02M5PBo5QgXY7AMNkLuayP7OELkiSUeJLBCgT0XSIpCdPe1tCIDBGKfQct+TZJHQ8uFd fZGuxdx8UT64w/ibllhLA/VwCxEQxoJiG692u3RrVI75tCxIxr9ZP7hQcMM+LTtp1AW8Znwtnyy6 plZhlJMHdK+x1zAMlCwWtvL02P2HvWYZ1E2ung0/ZuXH1vxxnhUFq6m+L3/4evFGlC0rBdJcmv2+ 9AdDljyNJ1OZLxfSXrU5r9nIpFG1L2cAf+NZbMdHbtiELlUZrLUXXbGzZTlGcLESHdsHFqrGqUxd 2YEVFTzVuiJHiVZXlfnxCYUVZydmQNv+DeupgTti0JA81EA8U9POHdD4ECgBOeNYKL9Ap5yT8VgJ oVFTprOVRHHB5q15sZCT47ty5eoBtwdBFcoHO8OeDPq7bDAxHY+l0+pKkmpmCoBhJTadbkPmC+Vh sbQoUouD5xqpxpXJI5slA/fVgsQ4b7h+1ufQsnhmddHlWyxKELRAvAXZbT913XujAPg8dR8gfPDC cYwOULjPGbufiQOYWP7Nwwva4298t7qSqG81gXpCJVoHkiU1w4un1TOIPigZwPlaWPVzqGdR7XvB /Z+4Jh8gAOP6IWSA5h+wtC7sDmW5VNKx1QtsAespHGuAVbOw1rdzWu1WzwdOC2mg9SAqrCMsZGd5 oASGVIVAIixMZAFTXbDG1CYPC6zSwEnBOLa8kv18N0jVG0ybCnIz2uIL3XoCCRuxDHf2JAoRv2ow foHMXzOG5bGU+4f3JWoW0m23XCFyR/JVznKb0ehUBr2eBAWKs4V3aQAGAAXBdMjLqMWIc9IW8eyT 6KXiYTX12i2VinFie0YaNbcOoAUAwsMsKbyOq4fyICQw6LaFkQy6PX4e22KfJXHUNWVQYq6LFzm6 ieUzHkQj2JRZDGBBRQ2N722wksx9xHf35wRFFgCyGcAFELAuk1xudw73yz8nJF38f2+yDMuOSbUa Q8TfogXIwE05OVGgw29kIDedLekKKi3HEW3f8yrZjo/UYKNU97c/z60uy1p9cRveyvPKfUOMilLJ GrtCgwelPoAZCoae9g7DPyOn+ABZlOViUabpQXOAxhOOk8EqQxAXhaxBgsiWBn5zcItWXLy4U3Zb bTk8uifdXovqCY1WR65dvgo7jr0Fl4tE7t6+LZPJUjKCoMjlS9dlORvLdDwj2ICgenj/SDpNWDAA GGHZThx1ZTw5ZnOMVbJgI4p79+5Is6V1iN1BV3p91LF1ZL5cyXiyIOjge5iOO2JUcAsBNHAVsXiw WABqAFlYX2ZRAcwg/4xgPygZ+AzyYWaNkPax0BZoerNwViilZgJeG3xD1T8//3cu+xy62FtQKyQ2 /lKVeIkqiykQxoAM0DDMUqTVtkpkAokf3wL33NW6rvsm0GrwN1hn9/tWnM/+911iE/k7OT6kvE+v 22HdKjlrs7n0uz263svZnJUXxnXfAtaHPMBQ12HkqYqywFFqVOHOiOxOKik63UCOJQoELr6VYdHy 0p1IgAwXC5iRmWKgygnjuaYVkI2RtvQascxOD3m8ZtxksfA7oxO6VSmsIbT3eudtaTVUf6pPK6XF RdxptVn6AtXRk+ORDAbQpjqVZ64PZT5P6OIxI5nrfmCB9btdWhj9/Z6cnoylN+hRShlF1PPRqXzq uWdd/V4sN2+9RULp6HDEdlnz8UpOkxFrD/NGKPNVwm7Q3WZflsmJjGcoYO6zhyJUUp999pmSbwWp 5lWayN0792Q0ndDyI4mzAVdUiacXL1yQgYtPkVcEixIaWb0eFxcC7Mj0FcgywmUEYIDwieibUxSl 5ZZl0ohC6fZ6VR0l9cCQ7NDPkGHO364qkLaspAXK+Vm/TCYn+aQCDASh3XFd6tebWK4JSRQzaYH7 EGNfABDjoxUrbWHmaeqfLf15MHl0Y1CedBmdlCmTL+uj9AgKkQuDniSzsXTjUPJOU06WSrCFtXxy csrf4vLlS7K/A3rHljj6lI2clpCphdL+sYyge8V02yME0tnnS0sdOPEwWTEJWT+o8ROUuCAGhMV7 595tWgqXL16SEdQ4Q5G3335bWs0mAQzZt9V8xdKcYa8vt9+9qRYM3NK8kMnpiLV9CdwlSMhAwaEI pYMSHXaUgfzLUpoAvUizRaeH96XRVMvnysULDNSfHN6nVXZh9wIBaX//giyXUzk8PGZB8/XrV6gr j/gXAu/UvlokMtwdSLMVynCnL4OO6lgx6L9cynw8ISkVpTqQfEESAMfY7SvD3SRorPmpXstAuzp7 xMWSoe6uX5qrhYSMG10wT51CssrdKysR7KekBQwLq1JzMPKltRvDfjZpYq1bVPVqPDs33NQcCOLZ tvI+v6mrdH08DLAedYCknC4X7OQ97Hak1+nLZDaVO/eO5O7du7J/4UAOj49pocPi2lpYT/ko9dv9 oDt77ylw6V3SxbOw4JhOd0HRLKDGeVCs5P7hkYxOJyppHCo9ABMaDR2++93vyquvviYvv/yy3H7n tnzzm9+Ur371q3Lx4mWZzyfsunzz3dtyejqRl3/hFzVtnaZy8+ZN+f6rr8vP/MzP0MUy+WCcy2Q6 kR+/9SZBp4uOz7OlPP/884w9PffcDYLHcjWXfr/H4mxodC2WIFJ2uC+QTmfThbqbi0TwHyY0eFUA qSIZ8e68u7vP10BMxHVpQ6m005FmRwPncAOtjATbG33Al4qpA4Yf39kUN1JXrWrhpRZLvWavAh1f 8wrngvO1c7EMpF8LGa65WWcJoP6oAu6Ve7d+Hkpwq1MRqiTPkwUs0ytDzWqUxtLqKMWkCJSegtgH r0eS8rfeAtbHZPiUhpKL5Trw0gJjXAFYpLwrlesQmSzm8uq3v8X41JVrl6lz/p3v/DcCEmSNB1km 3/72t8mTefGnXqKp/qd/+mdy5co1abd/iq4agOPOnbvy2muvy1e+/HK5AAE6f/5//hljPy+88AJV Q8NQyZOwZMBI/8u//Ev59f/wGwz6z+ZjWdycyrVr16TVhqxyRxZLKCQs6Q7DmhrugCkdymKuhbUA HFhYsEQGg6Hcmt/SusKmdmu2ADkWICxFuEBorW7dfJCRslpELBQjjZoFwlpDFzOqgwBfQz/I0qqq qAcGSBWorcun+LEoBvAd18qvwfNLfM6zsB42fHAyMDXrrT42UR4edowHkUbfyzDqBbTLlslKpqOx BM1YBt2+HBzsyfHpqIz90b1/pKNtx0durJFHnflVTXarvqmsgkGnL//y7X+T3/7N35QXXvicnI4O 6RIBYPAZLKYrF67IWz98S47vH8rREdL8iVy/8SxVFyD50u8PWB7zyivfL6WEu50+3SkAAqgICM6b iBvWIO6WoDg8++w1+cLPvCDj0UQuX9mTk5ORLJYTApGWtSi4qiJCVVwLmgJoFUyPhw1phLq48TlS NIYBLTEsBoxmnrHxaasFFj5qHXXB0s1wbbzsbo99mOqncbD8FL3/sBZktnCNCqDk3iqNX1/2JTHX oyyYWoNfSLyJPhCa5IpXavXgOWFVChpwJ7HXJWHs/U1kz0cFo/cyeCNptai6gRgjyqtmiTatXaYJ Y6edCxdLd3wLWB8TpdGqZtA9l5LJmIxVgazpQJHBnovcvnMo//Iv35FvfON/ZHYPi//FF3+awKGg AGb6ioqc7757Sw4Pj+T+vSOK4E0nYCKjPqwvnU6PVtJgoK6fLg7U9jUIXJYtIwB5ag/fe+W78l/+ y3U5Pj6VuPE1unBRLIyNxY2uTCYj2d0dMq4zm02cVpVm73AMlLxQijnJS84Unpthi9YUrC7W/yUr BSo2Zs3JusXxYf3Z+RhglJnQUqu+0iz3xfmYzkjOBqj1WUGsbC4RnFX09F1JP3tn7qhvBa3z38LS LUSx+YOG7/b55NkgCiW2jtfn4NKTdgcxICkNBZAVVW8DbdHWbMhiqZamlvO0qc02X6ZbwHrah9YK rv/b9LCMr2XzTtntVWoZXkqr05VnbnxS3r15V/rDAbvi7O5fkPt3b3H7ThvNS4Uu4C/+4i/K3fuH 8r//H39O2Q+y0smrashqCY0qbVmFO+ZkrK4YQA8h3/l86mRGBqXmEwDo6rXL8qWf/QID8jeevco7 663bP5ZOWzsrpymKqaEbHrChKywhLGwAGCYzspVUMpWIlt8nP/lJElZ3+3sy2N2VGcil0ykBCwsU MSw0zaisIo0bkabgQBTnbwqk5v5ZIbSftod7rVL2LgPox7HISVOXT+Waz7bCsmdf/M6P85W/2Ya6 w3BD8fPDhrmuBGPE6hrgm9WBdnPrryc1KhnlhNcxbnTU9WtolQEyusgOstMSmog80bPZjic7jDDo mn2R0+7NYdbGam8IvcMqr9M1gVAKRbPdk8+98KL83//fXzNmEDcggDeldEsUhTKbjkvCKIKfcAHR bgtxK3CnVouEVgrAC7EllQ/WXnqoE8NiXK0WdA2tQ7NaBqpNhWwaKAyj0UJu3XqH1lqvBynjSN55 98cssxmNTwhQiGEBRJC5BCP60sUr0m6qy4bvh3Pcubgjd+7ck3fffZdB/3a7q1m3ImcLLwIWiKOF WjSdbq8UnPOBw9QZYKWZ24bhWzf2b2s3tGY1seuQT9A9G7A3i8fvmGMkS9899IPgkXvfEgLguT1o 1KkJdg6WXEhXSiP4MAbOym4U4OgBsLIsYIA9Qwck15uA9I7IVSh8aGe7He9pqLvn7nQU4NPmDTaJ 2eGYhXeW/bNC2MrC4swAn6sM4Jp7lkuv05Sv/vKvyq2bb8trb/xQuu1Y9veG0ogCGToLA2b6T33+ BYIERPH+4A/+gKnng/2L0gwvymtvvCK3bt2Wr3zlF+gy7u3tcyIenxzKL371Zfnmt/6ZfQPV+klo JR0fnzAj+IlPPCd/9ud/SjB68cUX6T5qIHpBVxDbA7wAnnfu3JabNzW+g2NjAEgw4Xf6O9JsLmhx 4TW4sJ/5zGdIlzCXEPEmvxuNb6EYqx0gClD0iY4mCmjXQkFYgUK3gd69FkBbpg9xOwCCAZ8PTgpQ un/QGqxsyQLuFuuz4xhINTzhQLP6zrOAym5JlomE27VauSazysI36w6cKXNdDTzt+z7MinuY2/ig 9/EOlDl43VxfSAAWs9lUc9DfGjQa1TTbxrCe2rEeKFXBvWpoJrCMbZmb6Mp4StM/DGSxyqQ3HMhn es+zfi+KUgnhxuUrMsZhAX3967/COBjqC7HAADyNZleSLJXpbCrXrz8jly5dLoPVcA2xKD71qU+x TowTP9DAdquhQfDhEAXThfz+739DTica6McCB+nT9NNZe9gbckED0ABwKSSXEc+aqpDf3o5ZcSuC VSNAE4cGLSN1O49VfM+pmNq1MwsPIFVfrHZt/eC2b1WZ/C/Z65F+Hz++RH5TUQXT68N/za/Xw/Ab V5i6ge23qMW81IV874Dhu6OsnYQyrKdiYfv1nzcJBNapEY8yVOlWb7gsU3Lfm30EWIu67gJvLayP +KjP9zPp7LVCZ+Ncmeh/pV9VsosdxdS2ozPZaJKegAC65AtJF0vqUaFOECxoMNqhCgrAiuMWS2rS LNAWVZj0jbb02gNpNTsym0+clWFidlgMauIBAP3u0HutPVmsTvl5BM5Rl4dtsBiQQdSSGVhEcNHQ FxApeXPPtMAYLiiADAAFVnc7RqlIJKvZu3Lr1i26hCxWjltK9EQsimVHlWvmi+tV190RQZ0ksrlh 1CF37uGmYQsfVouvVOAXoPvPBgiWTaxbNJblPC+Tlz+Eh+WDtA9KBc4NnaeD2DU0rQCxXi9Y/7e/ 30cdltQw2kd5Y/A02zBQboTz3ALWUzjWaApOjYH9kWuTGnPLVUiUWapqH5WKQ5JANngpiyKRUBKR dM4GqnFUyM4ulD1Hki8K6Q+RAQxkNDllTR+oC4g3LJeJTNO5pOmKwWWzeKwQWeMtOjGtDo+9LCSR rFhRwA0twnTitqpymgCFxqqdZcJvKPXAfsHDwvaIcVkxNa2lJVwM5VSpK6UlRSiyBtPdhlkZaGVm sSs7NyOR2vlaFrGKG2kBOK0pLLgsJd9NC41N1VOtszoBswKAqiWYZSDts3UKwyagCstONCWHvT5L 1r6rAXNZ6ygeILv4kB9fs3PxWf/+3PNfe9S5THfZ1UVGFg+0WskUEh2YK84KfuQjbsdPbKxPFktO aakNCpo3kQnLO7rd4TnZrYQHgKaFpSpW15UWVBKSWFakEACE0Cmmw+43o9GJxNFCelBXiFqymGs3 m5ZjZGcZQEHlTLC/Xq+zZmXRUoFAH1uWw+UspIni2ci0xJUwiW39BqZcNIWWqwCwLK5DCyzUtvLZ ChM6JGil6VjbgBWq3U6KgFucccNJOLvsGADXrpMJ45mbaNfcvo9tY3EmZtoAAoGwkNgAy+/k7Ksf GCC4X4b/b7EtDPuMxY/s8+dl64r30OarspoqNxMD8SHEESCvA+vFd2l9F2yTlPL68R8RtMrkAyr1 jYSLG4VUNBKXsMDYAtZTOHzrav21ikhocibUvjoDYu4zdElCyRwBEpMYiz5EI1VaPKEsZhN1S7Aq qTAApciVJHlBYT6UUKOlRasNfSYNDq8SpTSY5aCTXtU7ux3t/Ucplxj9BGeS5AoSyCZC3RQ0BmQ3 zV1CTAxlQ5qtwySOZXdnn1bU/buHrl4ulOFwR5ICwfMpyAp0F0m5wsIPRFaI26DsCHEhqB96lorx kzAsvmUA4gOQkT2xWC2+xP2H6qoSFGEdhpWlucnVNGKvz+/y9+9bXOu/XXFODOnBFhauQ9kXkp/X +ZOhR6T7jex6+7Eus8o2HXv9+B9scF/oB4D4KPwE3BQy9AnQ4AWUMOw4WwvrKRnnTZCqHs25he3F RnEAACAASURBVLW5w4XxwP1qES4WM5QJZli0C+1TGBVQ0gR5s60ZsTCW3b0dkktn4MyEIr3BQJKZ umLLFer60COwsSYpfOPZ6+yGA6CxoTQCLAiRg72LMk9mlDJOkrYkdC1dD79QLRosJFAkmIZPEdRf 0LKClYPYFWWTT8ZKil2Bod6S/eEBLS/L0sEltGMTRNjdJ5BOo+pYbIBViuM5prlZOn6A3Mp5EiNh OipCGXepAc0mXtUmNwvnCxfcYmeI022qa8TwYz/njQp8zvY4xJyx71SPoZUE0w0u4CZL/oOO0rJz eleYF7wh4Fboae8HBqCP5ajb8YFHqU1FsucDJoGTockhyI/iXvQUtPe4A7eZH4SHG8AXMKm18Ll+ jGyZSCyZlqZEmYTZUrLUuUTQJ0/QsBQ2lBCAkiKQKG4TMBAgj6MG40A2icnZQiyLDSiGMp+ZIimk TWCpOD4NOksXmUznU1pYbJSKyZmnskjn6qrEsfR7A6a7Vd1zRdcLsahmR0mkb777o5IdjThX2I2o PhEHEYPuaNm1szOQRht98UauO5CS0pA+911Bv4bPLAtbuD4ptJSMwQJLVtKA+KDXrdm282NY/rDr gd8CSQXYrUEYSZoVbIt2fDKiVYnzACCbxddyhFYDrqrs3Z8m6/papRsKXhjvTnCPEXPTAm0ClKt+ 8IHQuHd+XK5steUSFH687QMPzGVYqZhDmBuOv4ZiIoQGwHDHmavk9hawPvyB2JPX5cZ7g/9fLjD3 Pj0z8ldAS1CVEiNbwyBoQMgR22bQVkc/QZBJkWbXPUJoT90B15IeMZxsJWGQcXLkWSIJZGnzlcQR 7uwtulJ5vpRG03VZLpQzhHKYJFkwiwg3CxMffJpuayCtWOkHENqj3hVcqFjdrBIEJJUozCULkJHU oGszCqXT6kC7l5m8ZJ7I/sGBjI5PmKXsUIpGpN/pyrvvvCNpnklv0JdG1KRrChdxZ7BLi+vgwr50 ex0ZT0aSHh9TvBCghiA5grxBoyFLcpB0sVo9oS1Ia2RhZUUWnzKrDgXjbH9GNj9+pow3CMcU4ALD 9QKgmrxy5SJn0u51JYKm2HQmQQarLZTu3oGM3rkpcbMt4+VSDif3+HmcQ6OhZU7IijJeR1BrMqFS uo4ZrKNKU94sQ5VrZutuKdKE59mEdQnxRSilGVXDE/AzbXtzdTf2RvQIseXM9VzHB0rYgOwLCxoF 5HAHnauN88RvwnBBslTAbKAN3LYv4Yc8XJ7ONYmglXXGyHJ3bGpa6d0TIMYJQ9NdP4uSMjamcLhH CgsWYgwNLAts4X8u+5Jjy0zCIiE4UTwZFkWiGTJ2j46k0jd3MsDYBuU2sKw44an6oFaHWk7KXgcP DH/j/DD5oKiAhYV9oo6RQVYqSqiWFrNEFnyldC/urugO3ZAEllWalaRNdsPh4sfdH+epFgAsMbhT zeZdaUizbDfPQHKYURE1zVCi05ZGM+L5w+LLz7EwzC0DkFn5jlEVjCm+WGoWzU/B2+fM4qIel1ON MFeTCzoPZDyb07LAvk9HE1YNXLx0hcB67969UtOdACTanBbHxPvo81i4ukd09a5CB9Cs18xnaQ06 0nGBm5RTk6Bqba3Raj34zs962Uv7/pZZ9YvpeWSPw4bhJx3OzGwmY2Bp6h3X5KJx44TuP+ZgAvCF F7Iljn6ExnsIB+DHPFvxb33nHFJ5LqG9h5q/84K3UL+MGMtBvSAUSjPMRF1sdP1CWkkAoIjWUeQt bpSfVIoDeK7oCDphtVmmK/61Ce5NaJ42mk3ADaDgoC5iuo10l3Q70CYsKGyLHUx47AeEUhJJl1qr CIuAcZ/M0QWyguBq7mql6llRGchO8xaY1SriGfWMGNbxxYLwBkZGNjXA8xntRlkw6wqvk2JR1s+t ZI5zLAq621p0DUtZ26INh/pdTFQwz3Oew+npMa28CxcuSLepMR7+5wfEPUa8n4ypMoD6DK3+TWBj v5WfrfSlaUxYEHPCt6jq8dZ6dvMMJcKe2bOOAs/6Hqo5nHurlpz+NtsY1oc6vKaB576PTSgbqtLG pi3KUpzqs1h3uPlFjFvpa7zDLudrnW/szgh/ErCAmBHuuHgorRTumXPvArSjH/OzrTayfLFyduBC oA0TYklw3eiOapwFN1QrAdGAafVt6nwiAC0aRDC+VtbjBRIh8IriYcorV7QCf7+rld65ccxjaCil Ir1uX3Yu75DAmsyVBwYgYGwLJUxrmlAFLT2Nj1dgagvTztHoFQAwWEjGKzMAjBsq9qfWpVpKPiXD z/gZ4OI9sPQRWo7bPf6N84R1hf2YG4rzNnAwrazUs/Qm47E0d5yyqgMgA8xSRqYsQVrv6nxeMN6u gR97s+9mgGTApWEFi6fJGUvT/63Po0DAbjSJZn9767VZKn+4MMIWsD7k8bBaeFc2qxkdi70zM6Sx LwUfdbsIODncAQUt6/Tr3zmtaSf2CyoAMm6dOFNBuyB1beq18zLqt3CHZ5v3HAsAcQQHfji+E85j 52i3uCE7Y5k9jLI9lRO6w7AFAZJgwrQ6CRYaH2GdpCo8KB8H3XU0RsMuzQ21omwRWPHs7nBHup0e mhYSAEC2wLnfunmb1gi6QJvVZ+cKNEVGEYDlLyrLAJoVYUBhrekpFe24WPUMW317DNufAZ1aSacE rINGR7qdDn8Pyj27vpC4gUA/HkAJCR2MGYi4roO0Cf9RSgfg1ta2YmXw39UHmvXrAxbnnTtvuO32 701cL1/uxn/Nrj09+xp/6+EJh/XGFvz5nbW+NvHpNmp3IRtbwPqwh5fVq240VgCIoUCkz3CjvB8a P34ckXNVspmpaaXuFkCrkvvVuAUmmE5O3MVc3ILoFXiNC+AChIwdDPo9LhR0moFFEq8SCRsgbGK/ 2rsP5R2maICyGF+501xC3InNjTL3KUL8iBkh1xwUmUMDuiilZXl6iiylxsNWK6T7NX5jiwYuW3I8 puuH8+w2tE1U4Uikpg6BY3Q6TemghCcOGDPT3oPVQjHrxLewyoXpySdbZtEvarbt7TNm3WAYedW+ WxkLgxrGbCJXrj9TBvxhXZl+GICXjTKazRIcI+s47b4/gI/F3S3ISUPpQtuMwc03S6tOWvUtTUdH W3vd5pc928OvbbT5hmvs0y7MnazXINb3uWmU73trApniNUvvg62y7XisIzj/JftpEYBmHMtjShPG YNIDALxCWAMkeI1VCtxpZ3kcHAx1FxVAaKVxEjt5XjYgrWq5rJ8dSmoKTNAmYlQpeUh2N4eiJ46J Oz/klK9evea+T8Xa9ikCACKzwmg4ouVYCB4UAAzEUi35oewxgUqBAHrvqnnekiw7kSUE4FBU3dnR OFEeyHKxkkuXrpRt6m1w8YtwO5BVtQbzLE/KX8SmSorF6LuHGqfTc/JVQg2c/RIfi2vhcwBa6Mqj XTsyo4ssdZpPiTTg3oHEm2d8D6/h725LA+QKHgHbY+F1bfChGUizcqC2UY9J+VaP/Q4+sXWTy+bz tGx/fiIAZr/v+pqF6kvm2HWt/83r6iSz2Umo3ECfYHmxghDHRTwz2BY/f8TGetlG1etEravK2nJb 2UQqi5/NNHdFz5DBdTWGJenRuYRscw8uFXrb5ACbQlbLBbMxbYAFyn1cVx3EmgAWAJc8C7jIwDZv AAwRC/PiGxaf+bd/+zf51re+Jb/3e7/Pc4sjZYBb/MPkVNDXDm4kUvG6kBBDU9kcAGa325PJBG3C OjIcmkSK7qPf7TOThn3u7O8wwaB3/UT6ra5THN0hwCAWlyQRu9oQsJh11SRCTJWK6Ay3yP+3NUe1 jtAYuCaW4bMFbRwu24eV+Vjm0LTjKQsMeoQLegNwEMPyY1QmVmjs+b5rQYZ4FwbOB/vAzQHt1Qy4 aN02FDAr66dKKuh3Otvw1H/U55gPRub+0eq0lmHuPM0KNJCv0xrqpUY2Ly3bWG7n5qnFLTVHunUJ P0LDTZxaHL7NgKqmejG4EBjTYT6lBKuYVAcXEC1ALsXiz6UJPfXyTlu1ncLcAD+KkxM9DgO1dpIV lEOX5Ec14Rq6hZgluUwzsMZhpiMgrJmyUCK6JexwIkKwunz5MiVo/umf/okTEl13UKz83HPPyV// 9V/zfXwWbZz+p//5f5E/+qM/kv/0n/5X+Yu/+Au5cuUS1TovX74or7/xKoubp9MR95fy+LmMxyNp d9RVOjmdkYWviwjcnQWtl9HhCWsjce7aNisnkXRnf5evXb56xYGKujf+YjXroFxMzgWyzCGGFVyn mTaQALjUVRhswdnCtSyf8aJUa6vFZhywYNuNliyCufQ6XdWzD+CCabyQsbcClK+MSqEGpJPpVIFu pa4yOhghFoaB88VxyYfbGfI9aO/j92o21bLxdePt/OsuWz3L7HO1/LIiPyBviQrT3rKkCcAWr9s1 gq6ZAT736XT7zQqESgiFFttoxrvcuoQfuVE2VnUBapARkd4Vx1li5xutu7KmEswCG4HPcbT074fz JRBHolkPKRmw1hstunhGJGV4i/0MlUcFgh+bPkQNalyNT7XW0DJaALtXX31VA90uo4bXr169SsDC dgAUTMYf/OAHMh6fytWrl12b+YmcnDTl05/5FNP7EAy8du2q0gOyFSc66AgWE8ICAIlytsCEd/GU DBYAFqpKHGOB4PzVQoLs8o50Om3GiTS+szlY7JMuLRbku0VmTeKa+S5VPahsQnl++c8658k1dGUN Jpj8yqvCv8ErA0y0Oh1ZzGbsfdhtt3UfsLoc+x3bs/FtmpYlTKBiAvTQiIMu+ukxrz2uIWOM7ngP Uad56PAttDp3C8fFb4JhlqlleXEumCM/fONH5U0Cr1v7NQMtswxLtv2jne52PK7OzyVOueFi60pf cGUKuo1raIDXDLEsm1jWFDqLal3Vb/OA1QXqAGwlyhUj/gNmPPSSUh4DdhTT5g0sRGXOs7FFHnDy Y2Hg7k3L5fJlAgmeASb4G9tgssH6wsLCXR6LFmUz165ekRs3rsudO7fk537+Z+kSBgFY8ol86Utf ot6TKRioXI1mwnDOk9lECmnJYpVIO9KsHgCL4JIoyKAJK0ALLqG5dBD4M9cVTSp8fhgvuZeWNwa4 WVa+jDLdNidIuPabejGaegaxKj72Ohf1wb5HHFJvEsv51Klg4BoXjGMlSJhkoJHAxcpZtIz3kblF txlkDu1ak3KxUt4WO3S7ID0sMeN/AQigyroz3P8As3b9u/qA7QO6uYeW+MA8wW+B39HqJE8noM24 2k2w2xOlS6BiwvaFc+/0F2qtPtLZbsdjHrXYFcpV4AGydgcgAUvHYlJqYen7j3DEIqDyAkTtgEEx THLI96YI2gPGlC+lLgFNMQWrQgtVATCYeDDZszxjGzDcxbH9r/zKr8j1a9f5OD0FJaEhv/Vbv8WF g8n3sz/3RZkvZ/LVX3q5lAUGKRK668pqD+X+/bsSN0T293dJrwBgkUqhVShl9gwDtYshhQXnLOOw jBbu8lgkRlWwu7edh5/Bs2GLBZ+zbGCdR+aXqGy+tpWV5mfQ/AA/3D6WADlXFg/TEWu32hp/Mysx bhBkDfSUr9WmyobvelptpAX38ffB/oHM5rPyc71uVxVcXdefDzrq8S4f+PGMygO8bvE2S1qYVTVf VskI/qbOCoUeFraFlY1/d2daIrQFrI+QpVW3svi66+yCQcgwXXZjRJiKjG1f/me63g9CM1dwSg6X BjZRWI2yDvJrOAEdM5yuExyNWGNe+CzAjuoJc26Dyflf/+u3aO4jEIy40/HJcekCYmLiPUw8vH/h 4r6MJkeyv7sr0wCB91TanYbGqNrq6mA76n2VnY4raRT8++LFS9TqivKK+IkJ3u/0pNPtswO1glog Bwf7ErdiFRdcKA3Aj1/5agx27S0O5CuS+gHlhy13vwMOhoGfPQBCFpTXLGurDLIjtgVL9Z133qE+ PQasImuMwd6CIjLoD+Te3btlHJE3DNcyC3+TPNuuZFrw+cOjQ3XBGh15lFHPBNapC34NpSUdjBqC gUSKHwOzfpF2zWdLVam1ebMFrI/QUNWGyrrSoVpPFrPyXUZTeTgPk3ywO29QgphuJ4AJEzpW0inc P4BU7nhUjImhsh7BWka2aF3t7uzKfDFdKwwGUGGxwYJptdrsmLMz3Cu5RVbyMp/PpNfvyMn4kAsR 8Rc0nrh3/5YcH4cy3OnL0fF9bTpxsFcW5ypFQGNjjFvFWOTqui0nS+5r1UpkNFKNeRwT3wEdedIC pM6ZTKZqtRigmOXju2p2DY1w6gfhzWoCYJ83fBfwPMqEuXG4dr7bie/1V3/1V/I7v/M78v3vf19u 3LjB7w0Ah+VEysj1a3L33j25du26o2isuLBBsL1xXVum4fcAcN0/vM9jI6aFGkp028FxV8tHC2LV uVt1wEL5kEn6WF2jvY/4WaejiREbYe0GgtgnPo/vwcqCRzrb7XjiYz3d7Cyr3NlDADL10j5wDIuW EhutIi6UU+IE4ITclLo8zqKjVeMaBqAYFRmrIJK333mbOliITVmGCGCFYS6ZPyEt7Y4FNp2hQeuR XL54QKVSdNkZT04Z0wLV4c0335C9vR3ul+J/3W7pOrDHYRDJndt3Zbi3L/lSY1YALDLdCwUAuBRY mEY2XaUrUh2a7RYBFQBQT7H7C88SBwZQvrujAfSzff38Zwuw26jHyyijg/rBdlPms1SSlVp0iFG+ 8fpr8tr3X5Hvv/o9ef6zn2ZWFdd3MZ/K3/3d38l/99//D/LHf/zH8h9/73fl9PhEvvOd79ASQ1b2 1371l+Xv//7v5Td+4zcIFK++8m9Mhvzar/2avPnmm/Lbv/1b8jjHpsyi/U6+9Wogrs0nYEGtyL8r g/eha5IBqk2imU80RkGCAUmHLWB9hIZqYlF3sXrNgpieocRSBgyACKwiq3zHa7SSXBW9J418np2V ukJpaLQz3kKLTvsZgsGOSJFaHM7JJH9Jg+84AFwWzE11ZzryhS98gRrxytpWGsD+3gW+D/DY3Rvy OLCcWHYjIifjE7qTiFMBQE4nIqdHR1SaQCkKLIWqI3PM1D4LiNOctY1oUz9aziRZqDQOLLkLly/w PFFAfHDpIhUhwkYokxNYVloyBFcJAGp1kL7bZ88ALD8TZjQAK79h4M+zNEqXvQbUdf4RFzHoCo1Y TscjuoaNVlOCRH/rbrsr+xcOtODXURAOj49kb2eX3YreeOMNWk7vvPsWPwtLBpYlsohzdBPa2+ON 45//+Z/l+vXrjFfh+7700kvyJ3/yJ/KNb3yDwI7mHI8TqOpcLliKVjCO4WdKUYLFmyUVJKzfovYh QGNVcruWS5fN1X1tAetDHhXpE0hj+uuqtc6YFQWuVI0hpxSLxatcupf1hApcTlHGyfUBdFCColU3 aIiDH934XBYEw2eidkOKFcToKDLDLBqsrBwMa8aqVBMcO0LDCNPVYpo/h5WHiYbgMbJVHWm3qtIM LAjj3aBzM5jrGgOCGkQs6QKM9EzCuC237oIEmkqcJ9LoNETSQFq9lkQtcInm3M/9u8fUu4KrgHOA mODx8YhZwf6gJx1YW3Abi1R63Z50u5fI5QFP6XR8QsBF/MroAOam2IKyxWZWgGX5bGH6GURSNsBz 1Q0UtJy2lsURleemtyGTUfFBcTyays7eLn969HpsO82xH//4x/Lsc5+UT3zy0/Kvr7xK7tvVa8/I nVu35eozN+Rrv/yr8s1/+ZZ88aUvyNxlQCFnvZzP5OWvfFl+9MM35VOf+KR8+ef/Hcm1i0VGtxx8 ODQPgXVDsNrQBcf/2zpsWzDfMn+0MBGDazXlZDQqlVFJkHUF3qQwuAQJo6TIrHpyzNiu4alJFJC3 nieycsTidguUkIDdxzHQEWkLWB+RUaWHbQJBGdJZNyhHzt2Er8VB2E7BrCSLbTnOFl5jEtwpjbq1 o7wtunT60FAXuF6ODQ2Xz7G4kHJGaUjOUl03KOyH+BbcIvQxVAJm5U7BFXJZsAhTrOo1pueq+4JL C04XCqshc4LFD4AeDHp046Arj0FQWaHQuiWDDnhFDVIvoIb6gx+8wuA6LAojY5Jo2MFdXQPs6VJj KDxXqhqoq4Y7trmZlsHbpNrg/0b1Bxb+psXuv/ag0e6quJ89dFFnfP1zn/uc7B3sy8svvyw3nntW nnn2hhzduEFrymJDn3/+c6SJwLr63GefpzWFa4frYYH6L3/5ywSer33ta/z3H/7hH9K6wjXpeIRX P6lgf1sBuAGV7+LiWpmFatfKvgMArN7Mw+KcPlkVAn2+RQayMyqpeI9mydS6BbcFrI/Q0IlSqSkw K1cGIZWCgAada5OLi8tbMJY1dMBk+/RBje8bNPqBfAbEnOviNLg0e6UPbsNuBpXqJMHwTFGr0jEs M1SdnFfP6Ok3lTpW3aZIBPa3WjYAMtORyuZaDoTtIJUM93KVpYxDQZHUb/dF2ZumEhB9xQJdLKo5 j+Ni201xNvsuxuLmqddqDUvA8quH3wdQ2Wh5Lq8F6I2nhOQFXkdDWjw3XfMOcKvwvfFsel2IIf76 r/86ActidwjMAzTgGn7+858vY4wGcCrMeFYKxv/bZG2MnoFOzUZbaXVAqRDp9vqygLvWVE7ceDqT dqcrs4VSK2zCmbJrWe6TJso1qwXsH0QX2QLWhzzqP4wPWiYsY6+7P9biIDaRCGZrpEUFuPLf9lrZ 7stRH9znlISqx+NkorUhJCAaSKqYGigEyoHyuw7XG2EaMFVf1F8YzvxzWvIocibwFokkOeJeWlwM wMIgqMQAP+VnUds9TaXT7TCADrfDWs1Tu4tyLEFJmjTrQAPnFefHJGt8MqhPc7CYlk+G9K2uTUD3 foftzxpf+AXKdp5wbU9Old9mDHtT/sRvRakaV1wNAi/eRxnSW2+9JV//+tfle9/7HoEN2VpYXni2 WkbcEMqeAi5pU2afXbNZdlNCKVeudYxHJ8eMm+3s7Uvc7lDmGNex4+RtsH8MuKIAULu+ZSG9CTHy dWSgi3MbYdT5cVvA+giCllpYjrBZliWsy4OUn3MCbNaa/oMMggv1s6AMEEqWp5JKRgIpjwMX0Inc afE0wEsVQtWis6JsaLorkGnmRwHOHcUdy6cNgGrQ1bIbBNUBVCnIjRq0b3dUO51lPyEmtHK+sDjY MSceUIkB+l0gXhpfpwduUQF5GSVU+pIxpQKqy/r5tAXfFTTlBSO01i0s/3d4lFG2BXP7Ms0t07vi Qi80SzpzNAUAG74Xia8LdalswSN5gW1giYIm8vrrr/OavfLKKwQPgInFm/h9mW9WNRAa6rwxqfYa WV55pg1OwZ7PUpnOZ2Snt9HfsdOVYrmSZaKgubN3wIqJk9GERd2w4hartJTZNpA1Eimsq0YUSrtp taDrQn9bC+spGuYGgpqwBlCeMoMf89r02U1twNbpD1JNDCeSx0mMNuvUjm/w7krB4rL7jrZHhzY4 Mm+4/8FW07ZdxlGKNYi2Numqjsd+xoykQnCjHKgoS3umFs5CYySsIcxRepLIYoIC2hljWFboDAvL lA3wOfJ1In0NtY11XXHbzu709fZZ/oIxgUC70xug+SD2sKzZg4a5xBZTI12DoolabA0QAkBjgUee tQGXj8C1WJYxK+wL18MY7iwuPjgg98q0weAmYjvs852b78rO/t7Gc63HsHIX90NjEBYzN2LODdxo 0DPSLFzlu3V5fawkyHhY5t5bTSMkcEBoHfa7a9lYO75Zvf7YWlgf8rD4ku8O2ut1QKrf3bm9t581 YPIAi5ZP+X7t2cWrbJ8MxEPrvQBJFIaKBvvZ2hx3W3SIYaoSC93xsfJAm1+mcL00ZrVpsm2KS3CS A/xcQHblagG1sFgXjJadqDoEtoHlgM7OyxSuERpoqMtqVIPJJCxjWMiEqZunRdPWHdraemER27+N 3uAL7VUSw2ev/ya9p7p7/8CuMbXf1a6PD6gWl2PWrK3kUL/7jhU3a+G5Sisb0RK1mrC4COBxTBdN ZYJivg8axXy1XLvlnQFt72+qS7RajBnq94+k12wxE00LCjeyoijpGEgcWIwN54ZAPwaADAPy3Xit 21b1CbMS7VpsAvstYH2Eh49XdUKjbzpv+mENoOx9Hwjrw4APBc7+sdh2C+l/lg0h8KrWFCdrI5BW 3OAdXqWME0nLoCq4FFWA9ey5WWGRakqBNIpUNrOFTtmTUsQ9veuy20zUdBLQCfleMAEPbx3K5SsX KLHCWIzrbej3z6vLoSAOhmNgocDFwrlYNguAYJ+vFFTXdaLs2tj+0yQ/F7Q2ffdNw4L7FuCuKxxY nKrRQNnSmN8VFhW13uPG2udx3bCtJRTwncxyhbUF8MJrP/rRj+S5T3xC8tPjtRtWfT7hWP41xDFN lwuxxP5wSIUPtWbVGvYVUQ30rZEG3rMuRPOZarTbuZv1Wp/r/tgC1oc8LHNSLQg/qOu1nDeg8Kr9 SdZsKM/F/0zl6jltdyeXjFHFjAtaTyRR0h1DCyi3fzb3LEjMhM4W2rCrtIx2GkZZR7EsBFMZKgEo 2dHjVVke5TgtaOHwu5VBbb1Tl/V0aF01GkkQRbKz25e4hYJjdHHOZWe3asrQ6rbk6OhYZqOFDAaB ZMucpFUAT7MVS39wwLhV1YZLLSoACqwQuKlYxHCJsOCODk8cmXLMfcASsIWIhWULyOr2/LIZX03T uFpWC+iDo2XZ/GB93XKwTKZvVRnI+PLLGHOvOYU1Vc2cuoFpyAMwNOlg86sKZNt3wDZXrlyRxVLB 5UGwWm8+YeoVBtpwTfH7g7DL+Fu7wzBGoxmzX6VZf4Oe1m0aAIOXtjsYSqcF60p/Y78rkm9prZ3P g5fTdnzYox5beS8aV+93oBDEHwAu9h9Ew/AmmF4gCSJ4DdkW9InTia8Ai6C3uTSMZhGo4Br6FonR JRD/0gWOf2dl/zyk19m7L9U7ugWikfXiXX6l7icWswXHwYq//swVJgWUyKhgZQPuK0p8rMnyrgAA IABJREFUFEgVzGwRmB4T4me+mqjJBhufCIFjA2LTbPJvMJa587N75i6+l/iVLcxN7iW/kwNDA+LY OwdagO/h9z3P0qWr70ICm2J4davSLLnKCgpo7WK+MIQQFXwGquA5D3HDi9koN8gCbZiLvr3u35gr s8lYskApJr6qhR17myX8GADWeRPwkY7jtLk1tqUUeBoFIYCgatkO0AKUhaGqnmJw0QHcvMahcQxt rWZJZ6jMfN+d1QA5BoO2qxlpDeYWWpbMFAwgvhfmMV0RvA4wuXBxjzGsSutcGdxmWSD2pYF4VW3A WC6StYC6BbQNOHBc0iZcx+V6jMksDMbNnEvoE0/rMjL14buMmSsz8ps2+FaVb7nFDqzM+iOrnMTc 9y7/shZjc53E69vbHOD31Rf12mzIlII4qzQIZJBBf8Bn2MeZuvTI+ELxA3lH1Egw44xEkms9Ju2q kav9hpbksASKP7YW1kd8VBk/40tVRaSPZf+uTROzd64eEZMKMzXNUxICpUgkz2CdaDt52FTgTiHo zqA9RfcwyQIy1qFkiaEcqPXj6UJGYF5D+ctEA99Y9jOX0bM4EhakFVVPjqa63Updmli0uHk+n7qg u7pfcAXR1VktN9dmi88KIo1Ys4nmIkHDy0pKcB2s0QSusTVMrS8os3johoUq/+tTJeo0iPrvaa+b 1eIH9W2/9htb6ZCBVeQF8d/LHPBvbmfiQmxSEupvatQW3KhQ88BKCNeFu/Y+OysBkjgX1K3HN0Av ScwHVGgYgGGjHBJF+DdpMJTMdc1U8lLix//e5em56+GPLWA9RcPP/HlsgcezX69vHV00iAci1pDA 6sJi1uYQbDMG7hfu+iAU0h1Td5Cfc9QHu0NvLPp1jTL4GXRghloomN6xyCrDwlRwsSC86YNTmmau yqM7vV2lNMDacG28NMiMIuYGeWCaTk+l04YF1XBB6jbjLpBL1pt81d3GXBCLK1n8zIYBka9AAAuj avSwDlYPs3bs2hhZ1ddDt+ulrH2VQo69+A4GkwpljFMeeMxNvwMGrB02XTb3kIqQWsuqBfUuYcOa VVW9VakhExnC37CgTBUXRNCw6trsqjFoeVEp1yVuWEi/PufMJfevi+8q8zu/z7m9HR+RUc79RwAs mOykb7InoZvMnIm4i6srUqCVPcFMo/ikNeQJkwEKSlVMx1wXazFvQVY/61NZIgZaVVt7FiSj6NtJ jGB7U1RAYTZ5SSu1fLCIL166IGGksRQt/dBsVJ5PJU3UzWy3ey7mU8VekEVTSZ2cFAmAsLkiPhj4 KqO+BWXgwkA6G3hUrbRs1Okn/vCtKyxef4H6THo7J3MDA3eNjQGu1/j96VmVlroXJypBxEq3jIyM 3xjgzA/qTW39GdtrQ9rq864GjO8D5Ww7BTWlxOj3Fq8Rit0I1q7NNuj+9A2d7LZonswx2GGnPJay 6mG16OJxWUlMIAASMzyoUtbO0uBBRSEylYgJQdsIrllV3Q/eU30xqsulpT8gH6K0A63I7X0/iwgQ syweKQlaM6LxpxYWLGJq6hLmFNNz2TVIPHvyxBazQt9DgCDllB0JErQKU28wcqO5pEaNsPiWH1TX axdvtJ7suW7R+NvYDcJA3a6Nr8tljHv/86HnQn6g39uPsXklX1SccNtY/Mo/6/Jvr2aUpixByLmA TMIAxExaZPOzikGax7B+XQ2oN1EbthbW0zTcHbBORbSp5SvHYIT1iUbrySYowgtu4nuGGsswEMUI tGEqC6uLleTJUvJ0KSEUSCPEgjStPp1CP11dDs1aObeIpTSwcFBmorWGKm+sgXcaJ9SkT6kCahk+ XZiwYgqy1XeGQ1nMlrK3u0d9nUWQEpjuHN6jJXfl+r5ICRqwBrEYm85Vi1zLMsTMVNUC8S1YZ1Aw BUgZSbUOWCh7wbn6LqGBx5pLWOsT6V/vynqRhzaq8AHRLA0DbP4utV6JhbmS73MK1bOYaS2oXf0G Va2q/X0WIBFvrADdMsaQf9TcY+QuRkQrXq1a7Mu18eLv7xxEz6radC42toD1IQ/1ZrTMBYPxBGc5 m9ltrHSEj+zf5r1h0mgMAb1tXONMxgpIWXf6ck5exuIMNiGRndPYpxahwpoIclllIFIuJIpzPiCY h/57yXwh3WZD+p2htJDFA18p7qroIE8c3KldJ1scyBgpa0cbQOdedoJpaiwGQAAd8sEeurw4ukOO YLirRQSnKknk/u37cvXiNTk5GclsvJSdnV05GU8lzQK59sw1CeMVGfEsB8KCgWuYQn4XIJDL7s6+ uh2wVqKYRNdnrl91F991vml1+Zn5ai7NRlvCFpIODu4hgePcMr9ZgmZUC2nieyMw7dxHpPi50N0C BLFzkVQpe9TjsdFHQ+Wi05U28TBVA7i9OEdzky1GtbZsi8oSetiwoLVvFXLWOCDCeW6iM9hzvdh7 /Rkde1ab369blD5wm3SIu75Wkq+u5oO/2RawPuTxXikKbPvlabgbWJWvs8Mz7viKdMzCMM3sgghW oEw0lFL3ipaWextZnLBApgZxETX1x5Nj6Tnrg0zpOThWrbJ+rN3vsZbP9Na5CBnsBvMd7lpDFsuZ 9HtDWSxmdCGNFtDuKeM5gu4Vm6DOnHRJIL02hABbssgAKlAWbUqvB9BQzhTu2nBJSQ6VFekBaDgB oAN4xxQVRP2hEio1U+hZQTlcxOVDF77FiuyzflwLg12stRST1xV/szlEKT8TSYDCTJSipFW9nYkH QkzPV+P043z1gPOTGOclCepZTpun9flqpGF/Hz5X8HHTb7aA9REd7ydedR6h9GE8IP++rckhjQGZ eiY65USdHvvltRvaUh7AsVxAm6lFHeXxeCKDEIW2qE/TnnhwxSbjmQOKhnZ66Q7KVlsa24pkMBzI coVGEdAp17oyDZQrQOLzACd8bjaZy2KOrOER99nraXEvQVCWFBM0awiuZKsBqZOGjE5nKgaIxqGO EMpF6sDG3JTyOtYkfv3CaB+wzN3DufA7O1kWdWs00waffJkgXe8kgLANfe6Q5SwdgGqoyQBfOtgv yn7cC74+NoHiptjRRuJpLSi+6e8tYH0MhwU/K86Vvf7wLKBxqDbtz/6uF0JXAzQFa9DqehOW2R9t eNgIQ5mMJ7LbG8jxyVievXaDALS3sy/B8v9v772aJEmvLLHrHi5CpiotGpLgAgtgdgDYGLGzDzu0 Me4DSduHtX2m2T7OfyONf2GMND5wlhxyh8MdRQAtqqtLpgzpknbO/a7HF54emVm6qju/7qxQHh6u vuNXnHvuip11MLHgSoE1nmelpNCnSkstsHUkR+PUoEyG9YO5kkPD3kDOZqdN7AjfmUzGkvQ06A3w A2AZ8fPsbEbw29vTz6E6KhGaE2CSx0wAKH+pYLG2z+MxRQE2XHUWl0/0tOybz7Bud71pH2dj2VPd i6KDiP25eBSyeKR/wB3tkcIB68vWS9d4pn0PbfIbPcIsO59E2jUuA4TLblp+kfq2x1f5vXc9ri2s Dzx8U3vz/VdbBzPGG0XOF6Md76JO990oC0bm8wuu2VWmKGXZy+TmzbsSRwMZj2paO9CWunPrnhyf HdGaWUwXslrlMh6jTfxOo+u0u7svaTLge3GsMaww1M7EGNS+In9KWe3IBkIbHSCFjs2wjKDjvruD z44JjgCd5Womg9FASjQzKNd8IwJHrix0uJAI7JrEiWX+II/ScwkC+/PZ7r7In1lWdkya8wbWPPgT nrtoJ68pJkeNJq2tQAK0JgtU8hldYZgNazLAm3I3GJeB1auMdhazzc+y99uPl7mlXUH59vO3Oa4B 6yMYXRbRa62j471t6gz26DwXF8hVLg1Z7YwJsYG9DMYDOTuZyr1bD+XRV4/kYO8GG6RCV/zF0ZH8 0z/9g/z8578ktcC6MuNCR1sq0BHo1i3mtK78xpqImWX5XKKkx88Qv4IFBEUCbdyqqqHI+JUDBNIN cODKaekP4tJFXkqRI34V0JKBexqlPUkT0B80e4nEQVujHb0NVfjQa43mAdi24+s/t5pLTXCEEkHo kO3k2W+I6pwIuptoXVMg7c75EH356vPxJKN1XCZPU7+hhdVmlre/20XHeBu//7rjGrA+otFpZb2W S9jiz2xdEcoorJmCFiODg4DJjSLnEuxzwFiBYHxPnj1/Jo8ePZZHj54w2JoOhvLs2WP567/+v+X+ vc9ITQCIQGAP7h764/36139MgPr9738vv/3tbzkBGxVQZCRRegL3x0kzG8sbzVHZLLUUSfoaf1ou V3J6ekYAmox3ZTiGjAlcKrcPrlUU4mtsUVYDsFQvnaF4gpkSVgnWdLnWpE2f4No1EdtZMozQdW5m ptJRHtAZBvu8WC3l5GzGLj2rrGCXbVpRcapuKbdJ419mlWxL77+rUW/cKNvXX7eIXvt7/vJdz9/m uAasDzzMuHpbJ3iba7n1TokSFH2iXaeh317mUgGwikyODo84gb7/8Afy5Zdf8Xt/9Vf/uzx88ANO yh/88KGcHJ/SEoL8bi9SUicyitBc+tnP/hm1xdHU8xe/+IXcPEC/QDRagHb7ihMdVhXkSawYGSn+ KFCmOSYMXMnxENk0gJNaIiwKrnIK9cHVkriiJdbrJQxswzVVpQaNXcHygbsJwGpY9zwOavEYM7+h J1zAB2oCymQ0oKVYRfZBr66o6wWAQpyPssGQtoFIXqs0qdeAdM7Kcz+o77ul7wO4ggtoDV2uZFcI o+v772JcA9YHHqZegDIIdUVcn8FGz0o1q5rmLE4rPbjgwiBnC1YW4iadn68r8RO4TUUuy8WSIn2R U4IMqkJuHOzJP/7n/1f2dvbZoPPF02ckm55OpxL3Uymc1rgJ3yFmBS4qJusvf/lzOTp6yQYIcIVO To4kSdA09IjCfChazioAViFHJ0esP8N+aXwLwegV13nz5m0CDiYygu84RhCvW62WEq2gnZVJMkxk lI7o3LIBZ1bSwtJCZo1T0VVzNYzasQUWGygaKpJnQOXzrHydcYt/NfsJ4b88k6Tfl6MXz2VnNJaj 0xPSJaB5jsxkfRY08samcYV1adA/ZJyOrqfXsKNd3tNl7QUtF9avv/O32Y+rtQmjVwGVyyzN9vP3 Ma4B61swLOjeNRp+3kaDLxuVrNAVB4xl1/M+KKEsWkoP3XGkln/+038maZTSEvnRj38odRDJndv3 5Pbtu1RGABUC3Z6hqrC3v8ttuXnzgKDyZ3/2Z2x4Ohz25fT0XysvLIAe+Us5PTuSl8cv5eFnd/j7 pp+FILlZFgCS589fqProLZX2hdWEQarDciaDQULglELVRGFlgRYBwML6kBiwodpS6nKCXKvxNiL7 RjmMHVP7M0DDMiahDKsQNIwwL5iYADAx3uYABNYclgWfzGRqfPKmgcllVKvLmN/+8FUjusqCrgpU H/O4BqxPfFx2/ek1a0299Ln3Ka0rAA9cs7pADV4m+WohRb6SedyTg71dTj60nX/w4I6cnC3ke997 KMuVum+L+VT+xR//ES0I0x8HQKFe7yc/+TEnzWCYyi//CBbXIcFntVpwmUIm7JiDQYqDY3evA9/o WoMibDRoALCqtYnP0IIeLdz39nZVQM5xpeEOoiGGxsnANAdfLPSUEPT3eonGm7RUc13QrMdsLcRn 6glWX2iABHcYSql3Hjyky4rPBwMlqQKcbu7flHrPyTtDJcLpVilnK9TqAq9S6mrnOth43CBwdhQ1 d33nUx/XgPUtGe2MoFIVTBp5TSxtRbicRIpmu6hJlGeSLReSLaZS5yuZ0S27KVVRS7obS3lyLFm5 lNP5jJru4DoNBiZ/CxkYxJkKWkAAKnXlChkOB/LNN19TjRTgCOD67MZ9efb8CTs8o429ltYg4wcA 6W10fzF3EEFqAAAsOAAWXENSFHrgYMUMfBMKnErwYq7xI/CjzO3zs4BG6Fwft/OBdwNSK4Q2FxXb dXKics5YxoQArfDbzgvVDyh4iJyr8t54vkKLUW1mL/3hg2cX8LSlWPzlfVrCNurC+2DTv81xDVif +OD123IJPYGHSwcAABMGAXBYVRFcpbgnxaKWVbagywcQ0o4tC0n7CIZDdA/WhjJST0+PCSwALHbS kVr2D9Baainj8YCEUkyond0hXSd8bzo9kYfDh5KmMUtz2Np8CcCDYCCUIbTNPbSsMPB9rblTBVBY SidnJ9rJGbGvBOAJawwuXyBxLybj3SRjQODEJNbAOwLeytey7TUXtF0711YDtVgWPsM+P372kvE8 vKYl5WJlK5YwOf133DgQlMcNwgtaX4UYunmuA+8c11t1tbbFni7KgH4q4xqwPvGxLXxlFtZlwKWa TMoIN7VPlrIgrlQXcuvmTZ0MdSmnZ8cSpwOK9MHDASDtDscyOz1jQB1ZuzhBw89SxiM0QV3Q5WMH 6XwlN24caNC7ymV5BPb6Sl1EVxxsoIFYGgDLWmxh2+aLBbcNAOdbE6YVpR1mFMjyrJA8BJNe2fQ2 Sa2ImTEydPkpXLDa4z111go6KwRgBcDFIwB8NNnRDsqTCZdjC61Aya8ALFhcOQCYJTxenIxUCpXu eR3aQX0JE72L+Nl2Hz9V0LoGrG/BaPOu/IFJrKK3LlvUDrrDqqKWnSpGgNqATib9cCxJhC7E2rIJ HX9BfVgsz6SXal1htipkiJq4wcDRDIqmSQSUGjApEIgGmM3nM4rtjSdD1dDqqYyKAdKyXrosXErL KF+q26UTLmzqEBnop3UzIVETvKwIDS1SXR+WGQ5Gkjj5G3bk8YLdtk4N8APkQEnYVONsK6Yaex7b gP1BdhFgBA4WYlPIUM7LucQQM6SKZ0TuWkx2u+rLk3MV9OiaUm+HpY9vDhphC5C2Z47XLuU2WsKn MK4B6wMPBl2dYuOGScSHDWkG70tOCK1ZzpZdv6GNAVQ5wAK7ACPI1EJpVNUYSimzmcQpilRyVT2o 0JYe3XJ6Mugju3fcFA+PxhN5fngkg14iWV3JqD8k9+rurdsMskMDK03BPo9IadjZHcsqA8Ao1wrL 7u/v0kIByMHVhCs3n081qycoah7LKB3LTBYuvhZImgCIVP6YBc/ZUrJiRQsNulUEF7f/DQ0hXzYK Ev7ERtYQn6tGeiR5uTwf2fMoAFasTeBy6qBoGAqZGLyPrjHjUZ/8teFAwQniE+wwBCsRMs8owyE5 VNukodqwR4Y9Mh2veL0Em1aWr4Dqb/tFANblWn4q4xqwPvjApazp/jAoKYtCHpaTm0V9n2pjqSie FTJHVPxkP3kFK6erXjUXpPKaQjSHAI8L2uW4qAt0pUF7+CV0O2WIMpciRxMsieKarov0oI0VSlav ZJGvpJehUeZAwCgY93ekyGpJQ7WqhumQ6x2xbjCnlhPAAITJ2fyM1ggss8neLhtXnMHSgoVTZpz0 SbgWqEvTUEZospkt5OQYdIYxraWXh4fMBkKT63SayWhnIqfzU2pYLQ8PZdgfEegQe4tIWNN9x+hV GgBHk1ccSEq5INPn5F7U2oDVhX32WtZDUllqmSK5kKby7MVLOTw+lpsHBzLc2eW692/ckAjNLFZL SeOelCjEdl15RsO+rJaaKECNJEEFJFVIAkWaBAF04Zxd5LdboJ9nuT5Pu2g3aWhbiu1msO1lP3ZL 61w51QfbkuvhwMpsA+s94h6dwLZd0Gz+4JZzSsaeiJ8/nO4VwspUD127jGRWkwtVSlSDGQ6FUKT5 C6nwR+tBGxBUBSZZj30JQRvI8V6Fiz6UBO3oe9qoAgFyuHCqi+RL/UZ8H9YZaAyamYMloPGsMBo2 HYAZN6ImO0ifWrYDFzUKNaC/XMyoFAptKYAentcBYlGw8m4oudYaXvTQ9NXt/7nmpevguX2WJKpF pSqo6zgWEgU2oVn/6FrbQ8o5BYg0Qoja2sofa2vZfsfXnHI3HdfEtjUfX3kElwDOp2ZBXbZ/14D1 CYyui9K/OxrMdX93cz3scOPaLNHtgeVGSWJMIMRaNpePExA6dfJDHA+uG7J3ADPUHyJR6GuOI0NH y45t4WMCDDOQUC2FqudioaJ9kbqO+Bo5WG4brHEo96ulsQ5FVGw7wQ/qu2FEUitATnsJIssnoqq9 mh1c75vxkzatkLI0+sEaVJR9vhl4xzAlBW5vpPQFaTVvbQ/fJW0TOF/Xuqk7+Fff1nENWN+yYYqj 54f2gkOpjCkyUCKZ0V5DMstWWUlHjwzwNXteAcoImQ3AIUbiENLASz+zridwf9SyAA8K2ThEcRBs hxuHbBrabAHZVtnS61KjHKdspW29AEI+BQCDxdILoTvJfUHQvHCdc9zQ76yFDX3elVmqNunNZTJC ahfhEgAFF5eZQafx1SP3C0H0iwGrqxTGt/BexQKqO5QSvu2A1d7nawvrIx/ri/38xepPUtN7hxto r7cP63SiFgCiKWSKw63y7/4IDEeIBwXKJQq15RddJkcJgJwL1BJUK14D7IhpabdosMuVbY5wmwap +7K/dyDpYCDHx0eqt4XGm0NYcdwzWa20zg8F0n7rLdO0QnYNgW/UB6JIOo4S6m1ptx4loFq3HwDk Rn2ec1ttH63JQyM67TKCRbluzY5lUMxtEsZ+sfRlwwesNg+qq+/eVUbd4mB9m8d1DOsTG+fKMaxx pmNQX1qb49R6NWu4pjcQJFBDyKBu1TTB0GEukQveo4wELiB4RBVoCIgxra0wtsZrrDbXEQdgJz3Z 3z8gmDFPFgQyX6DP4FKm87k8ffpEepHyo9TFDCQKY6kTuIlK8DR3k1YN2kcFMcEOwWskKPCW9Slk A9UabqV26NHDtOY6KZ9ss7U8eFtqYa21yfW107BwIDUYDJsCbI25qSoFkh+Xnb8u66qrvOai8++D VP2Jx6VeZVxbWJ/g2CrCZ2DGrrp817l+/nLrfl/NHd65gsxCYkJV2p6JREOysde1fL260cSkWwit LBAf4QrCqrEGpf6Nnj/ptJ9GQ2QXlxL1ArpVsJCOjk7YixDAhy44iHOB5gBrKA2V2DkY5I0YoMXe 0PUmDPvSx7Iozg5CKTO19BDrCsPMUQW07yHehzqpWTcaTC8321w1xNC166jHZN2Cy6wuq0f0CZmv MuG6ipFfd9RXLK351MHtOob1HRqwoABBlk2EVQUOFtw1lUMuZTXX1L65SbBakIbXRg2wOrQNkzbI hDu4Zo1rlk9jVVoSg1913Xsg1RKFslxltErQIQeUiMV4Rc4WOFW3bt9gl2cMuI1VqbQApSUowADg EMvCH0p4FEQK8rBg5Yz6Y8mW0GpXPhX0sbAun/jpAxY4Ub4oHdw9XXZNLKWQIOJuTmOecTXH6WLC wAXeNdx3sUtmbH1/4vk8r1eNYdUtAPy2x7C+c4D1sad9dQKoy8M4kLN0LGis27iWh7GLHXwjlgG6 UjRrJKGhqMCVgmgSC8ks4AIC1ZAZBskRf5j4CctUYHkojcLiYr06liiIpUBwOwBFQZuRhlVBThfg DNk5tgpDjo/yMF4hr2v/joEgO1y4eTanJfXZZ5+RAwWQ291D4XQhs7M5O/CgUaIx4EE0BaCAGgEL KsiE9XsAPADW/t4etbcmox0uM5vNKfnST2t21QGgwmrbcMsCaLyrVQYgsuPc1pUyd1RVGAaSl3Xj DvrNTVmLuUWA0SdwdhE5XyWGtY2pXrr43rbSnYsklq9SovOmgOjXYdqfn3C4TAL6OwdYn8J4+3dJ x/1xwXJSukg0WvcbDB24kZgY4iLa5E9pgB1k09KpB7osG91FvdC0Jm+dptTdcJPGXEwG4zVVWXlu jLp7EWvzVP8KnKik0VspS+1feHBw0LSfx/pR4lNIwbboABBQJahLFSitAexyWGNVpetF37+Nye6C 7jZRLUbWuIxWT+hZRb4F6ruN2CC+7zoXX8Yqf1cjaMXJPqbyGz9o3lX+9KrjGrA+8NjWyBKjKzt4 bhlz95o0/lpnqflmU+ZjboSW5hjvSTECkzES/Bc2gXS4jhE5UtBwstgNLTxnBaE1GImtDWPbUwtw 6p5k4Adwx6CmAMAoSQvAOtD5BgPPYcmEie4BftOydPP5gvuHjCS7Sieh9Ad9AsVoNGRqFFbgcDhq OkCHoRZEcz9ax9Q/3li/Xy/YVmtY9wuUTsAiNHc0GH3bY1vxctDB6Xof2/O6Wb5X3abvXND9Yzhp F403JRGeXw9eddxdEXtybe1pdXHC1VLmGnQ2KeFeEDvrSnWlEM8iOLkmERi+DK+Bqj46Fj4BERO5 pP4VuE8oSgEPi7ynEP2gYU0hFgRrTiVeGKgHWGF7RiP+LoqXZ7MpG05AjTRDZi6KZDJBg9dQ6jxi u3cDSfYeXELmRjtEtzsTGw/LjpeB1DqruDnxbZ9L5yp36ks1idu3b+Vsu36DS2SKL1J0eJvjsvVf 1Or+dca3HrA+9mE64zb8i/wKBtZ6PWrnuBjW5mdq7HiKBK4m0Wp2IIkSQ3kgTiTqgU4AK0tjVqAI wEXEShBgBxZRT6oWcqEAOu1h9AFILWuZTSV5hayglt0ANLRwRev8VN/cNSLNtVQHTSngEqIw2hqc UiI5d5rssL4CBVMAFzYFYIWOPbMppGi07AcuoR5Ld1Noycf4ReM+QRX4Zb/D/XEu8QZgNX/rtX1o N6y+IGb2IbenC8CvXcILDti28aFPqHkWbdB6leaETTzZAZAPdPDUAC505zAJLXjP3p611gO6bKCV segjqxAbigPj9GwHv75jqmCfbUCwtqxosQB4Cr4H4GKGEsF/cq50o6ytF8HI0RkAWAiwz86mJI9C pQG1g5QzdhkGvH94eEgJmWEC4IJeuhJFsf0ItkMFFYH4c6U5LhlgQGQ8KyvNWQez1U2086EW4Nod bAPWtuvoTa+/bcATtOJr/vL+32Xrf1cWYHv92x4vG9dB949stMHqVYepizbA5xrNN+v3KO/riwtW hgaLlb7gXfxgeKPVl9lsYI2Df+UkhhGst+4+7TiJ1en5MaEGHGBPRU6BM1TrzCwgfCEbAAAgAElE QVQnbc/lXLdILTgT3hsMUvK0aO2stGtNmZdKjUhKmZ+uZJCOaQUCZLDNWvozdPI0ztV1rd/pnDog st/XbV23i+dnKAJHoXOqMs+EcVMQpdqDixOBIiLt47CZ0XsbY9PyDjrO6fr1x8SAv6gh7VXGNWB9 ZOP8+dNSZlbBXcUl1Aqa5lFDWF4piq3fBdrJcPfWOUwRvEbGL5EeYkgsr1kz3StMZM8qAdpAvUEt EvTVcb/JRqyYMJuNSZvMG5jpKKMhfQMNLxxghCp6R/oBynlYvJxKOAllHECSeEk+12J+JmElsrO/ I3WUSDHLKeCH4uf+ICXowWVFDA6yyqBZsODaBe5ZXhQ6q6rKm8YSsMIQF0On64IJiJC7btu+Truv 29krEOEcXX563rWFX3tA1rauPobxNmKz36kY1od2+a7szjlVGBIIoKHkegtq6lzr88S5ceBYNbvV yyjKV6Ovn3PtdHlHy4LscQJeViCV04tTiwAyxAgm11Q3UIb7OuvFDCGygXHMCU0wiBPVkwLDHF6d a8fVuFKujZduqMrRQKiuqnpyNj+Tw8NTumsQ8TPCJrSspsdT6lWhfg/iCd88fUo5ZWQQZ6tTGY/7 kgwDmS2m8uT5lB2nh5MxYFbKupC8Rk/FngzHE9kf3yDVAb+1XORy9+59Pb6uwUUN2RhkFZ1rd3xy pk0sANQRcpNoNa9WFFVGl9CvTyXFfvuKpS7GBZFDsP/9Bhd4NKBu61Vh+GCyrmXcdn1sD6hjtC07 s+qMlOrH3LqA7Cou47a42NtIFl02vnNZwk9qXKzlxrFxgRBfEMRWZS1tcOCFkaGHZTEjDqcPFa7d wXOb4MTgEaQ3xnnbxQAAYfKr7IsXjCbq6jD1hwLFyiQIxiyT0b5+pkFVy1eff0Eri+oN7EhTynKR SV6VkqDnYJhAhU+KCuspCS6mYbXMl1LlUFuoJe71qbt1Gk4JekbwpCVV1FLksKrAz3KUDidTMxrv NW3AaizLwm6nDVYUzDSaG2gZw4bDRWbueUumYdV7pM6t5/CKYxuHKTQVii0ZyjZQvSkP6kOPa8D6 WEYTg1pbXb5A3/ricne5JnZ1Xg3LYuBYVNvhaeBbJWesQ7CjQbRaXK1frcFM76QGXEpXMAvCxOmU bGnWlnGW1H2yvaA2/GxGLhWY6ni+OJ3LjYNb7O1nBFHtKVhKfxBLkAWSZSvKKQNw4r4qnWaZaqz3 44RB+kWVSRLnEgjcw7jZRxBTKY3jjp3GoVSny4LodBlJ6dAJbm6gldWY6id5/J4lZa/bbpmBlcXI 3sQqaTdFrbfEsi7m8nnn9xWD3l1A9yF5XteA9ZGMddDcvfaMn3Uw3ZZr8xage2V3WheI976LOBTa XBFg7OKHGdIgY7s1lKM9kFgJa2bTsvBdHo2LmRvppJ7p1ypiwoVEt2WCUY3GFajJK2SxgnzMXCb9 Ma0Y7eWnXW78TjfoP5gXczafKMs+AQtF13D76NqxRVkuS4BXCqlm9CvUTtXIJhpzvw+3LlUyKcHX Md5RM+hz4Qyg7Ln1IPS7KvvH31c1tdc+CdXAzv8NH7ReJctWe+637/69yvfb778K6HwMVIlrwPoI BvNxHRaWDVIQXOp8XSTjPqNwnqMvNAC0/iLv+GUuVZFpaY4FwlUfxkkt+24DncumJtF+Q7sk+5YE Jrx2vNGfBKitY2DMnqHhhbNiAELWHRrvT2q4XLkkAZpbDGh1gdE+HGhdoDUjTYep1KLdcMoylEB5 FNxGtn9HII4WZ8SMoLqAc8mXkEqOSTCFy5mwvdfa0kP7MbqN/XFTR8jOP86Ns9cGOCx2bhUtq8xM t3Vlx80Hp9cBLDu+7RKX8JLCafvsIqHAV7GyuuJmHwK4rgHrAw8CkTXAaQGWdtTRJ8Yh8l04E+1T zfc1gdO8ROhf4XNkvwBaPfsMwW1MdMpsck1O98ohn5f7AtlzEyIx1lZJEwdz4GgMd7WooA6BO7tO YJ38mnkLXewrKLTY+fjomC27QPQEsOmyqvRQVmicoZYOsotZUEpdKR0BzR+gqCDDHoPslGDO5xKH qexMdF3avh7Sy+Vaqqaxos67TcbPMpewK9jcRSfwi6ft2PhxwtcJUgPIuwCvdKB4WfGwUUv84W/H m8jTXLuE38FhcSqznHj5dTaXcBeaAzSKvjjC4wbvasMldHdlAIbTX2dmDXEoJxPTFCs7sLE//w5N zlbj8vj+psat9HeNUKn0BmQfSYto1ehhvSzPIc0gFDT3wvoRn4ILBwtJ3TVtw4XAe54DdDV5EFAV AjWCahWh2w8GO+NgvaIcrkEyUCDrOIa9Hiw+Ld6GhDO07DFggIEqoZM4Xmu5o2GEWY7uOHGaOw3F 9blcJyd8CsTm+X61uI+Bpv/3qjGprqD/q4BnV5bwKqTUdzGuLawPOLae7g2CjysubsTbu1KJXXfJ xjxzFltFpjmqBKvSc1O4CPxCmhqqFOonIjtcGGOcm8TyOr7juFsMZ6koYJ7rpEeQG2AJsOEX2TUm lGKxaiYiS3kcRypKtaYR1hGAIy+UER+7llnco6qirhaA7vjwTKTuyc0bOzIZ79HCMisK8T2lYKz1 tPK56sWTB+apNbQfLUuIZZoOPxtNLc5zoOxzX1qlPdqxrwuvk2CTtBpYhyCfUtKKS9k+mSu/7Xya pfapjDcGLG3dtHln8dOpn2Lq9G2PtsuBwT547IUHA8gV32JixRqTojZVVcsgca6T+z4bL+ia+C+7 xLC0Rd/F9YcJyc57IQLSsG5ydR9BzKwRv8mlRqutMJKs0i7MAIKITPSYJEyjNJiwXWNdOC1424Z1 3MaUOKUppQG3CnGm1UollbEcwGWxmNOSAYt9NZtz2Zu3DuTx4yd06QASeITW1mRXmz5gMwAY1MUS gJnSI1AYbZ2Ydyb7UhahPH36VMaDHbl/7zPXoXpF7tpopMF90B+MblFXhdPFgvhfwj9sJzKYWC+1 vBxI+e6YD9Q2THLHzrlZR5ddE+1gvg9+iOf5lk3Q4ZZ2ZfK6fquLouK7vNtc3y5AtPX4CZKuoP66 ycfm/hng+n0X3wtg2TauYxpNnutNV/3dG9aDsAmaG3ehm1Lth5v88kNeGE4HC+4gY0iu0SoeY1gu MQT6QJiMnZWhvCm1tNpCy1bfaBf65oVJtYVaVUfN2tO+fipw1x8kMj06lSdPnhDYkPnrD9OmAzRA CN9Xa2nhOugg4D1gM9Y41nZjlKPJSslWaulgjIeaVYxCLaFB9tAyjYj/QOFB2wiqVYIJxG48Uqv+ lqsKMCuvKax2iqobNIYLsmxdVsxVhy+9vD6m3XpcGFfJDr6t0Qaxi3hdXd972+ONAcs3bXHh2g2F cYxPy9r8MAOGEM6tC/5e1AjY2Tr8d11e45jtzY3DEUOrNf8K7HgVcFFpGQaake5HqQxLY9QyaFsM xsvywWrzQty0MjZS+5STAbCIRHFISwWdZ7DIeDIkQRPAAavn7GxGOZvbt29T771ZByyyHNSERPpU kUD1NGJxoGnA1cOSqv0OpjviUdkKulkKXqRNTNQCwO8tl2pNwcKCFYjMI+N6Xrt3yxRiT9BJGhYY XeW1ML5T/bKKge6A9qvQDnzeFoZtj8/B8htXhB1k0Xc1rhJ077KwbPu2gffrbvtbsLA25VAMsEzw 7ENkEj61oXEWPx7iaEwmF4PXF3zfAKvhTjkWqulf0bpiF2KUpeRMxUcmtYz4DET7GpLnxYTBtRCg pe7ts3Id3yq1uBmBdIxVVkncj+XBg/ukE8DdAnAAuEwvHa3dQUE4OTmjDHKcgf+l7gSWmc+0e3TF pq740+wCRAEZHK96kq1KybNAyp4whgVaQwN+dM/WlIAGaF0czpazRq6231r72E0hsCSD/7rr+UWj ra9l79lEN9epy5V7H8OPh7Xn82X7eFlI6HVA6zro/sEHOjFrbKp9+ggqG/MECqDuKWNJrABkUbBR IgB0dZOtcw0jMEFBL2BjhUJ6ISSGNcBOLXYn1mcT2M8eXla/dv4uq78LLXiTjgGI5fNcTk9PZDo7 VctqMpSD0YEcP39Ji6efDvk+3EOCRBzKbH7CTjula07BoHOcMEMICsNytZAo1LgYeFiwrPDdqtRt gQWF7+TIAvK1StiAqgErlEoNrg7Qd7sswI4/1k6+w2HHzyzcLkrCVVywdzmumo30x2XLfzALa/Ou rJaVPb+2ri4f6m5ZOYu5YUoQ9dnuXUEsI5TS7gF+NRaurixEkJ2cKe36DE11cKMiR0I1t2PdgxBj c9I057CxpFiQ4j0/fxc14DK3bjROZZGt5NmzZ3I2PZHJZMJl0EQV8S12cxahxtXZ2Ym8fPlceklM cMtKZLkU+BCA1rhTJEVeS70QidOYsTO4hIg5oTQHJH7Exixg7ieElACqig0WOG+X1/gWTlc20N/P bRPvqgknn2TqE1Jtm9o8rvACSe13Na7q2vkW2EWA9Sbb/xayhL6fzc3h+9ee4NWHXgzu+cb7XQu7 mGELvzbLcdQdxOCk7Nl7IHKuJ27PnX7f1bMVdV1U5ywr8LAcj6q5DizG5lrbW2ZwttCOM8jm4Q/P Uef38O6dBjisrRZkkQFYebGS+eqUrqGW+BSSl7AKEbDXwDu02wFMoWjHZ7DdkzhxzHhtSsEgupv4 6oKumBSgJccMK/o66u+DPgFlDLwXpwkf14kFp5TK/o3s6nhh8P2qoHVRkL4diA89Ltb7MAjaMTn/ ff/zbVnCbfvyuuMtWFhra0o36JrWcPFwJw1WlItNMXmn1TDKYfIDUusj7bgOporgsnGeVYavkPzo ymrQWYakUfdbGtAPGGiPHS3g3ETzJxkzaPY+A0BO98pZZAQInG80jcC2aE9CDMgXGzA+/uaRPHv5 jERQuHh0t+DuVIGcHM/k+Ggqo+EedayG93fYugsM2v4gkv2b9+kSGqhB4gbaXXHUJ1At5ycyGo64 LYtFxhjdYKTifQi6j0YTpVmYommpOljYTBXvAxkV2x/KqsolW+WUc+7HqURpQgDkIQdRBMeT/7uk hrsRNGf2NRQRfKZ6G5z89H/b2qvfk0WwDbD8z7uAqOu4XPTd95glNF7RJgPXNujbPqBFpcMmubvz 2LuelpVRC0iA7IFBjROAOBT4QA1aaRYPukznDp91eDbaQS1ZmTMTlq2gVxXKYrmSAVjc/B0Ex9Ac tSfTk2Pp1ZVMxiPpx7FMz07k/u2HssiQ5kdziIouV9hTHhIm6unplBMeci/j0YhAc3J0zOA4wAKA gJGmQymypcS9lLSEvILaQi7LxUK+evRI9vZ35Pvf/z7duXTQb+JcUAX92//r/6Faw3CwJ7NqLmen Mzk+PpH7nz2QVXYmX375pYxGai3Bajq4OVadqtlSxoOxHOzdlny5ImDd2t+XJOpLzqYUwkB+EqG+ UBtgwNri0UOy0ZUyRUms6hB5ReAaTnakEhXyCyOcmR6BH/1iKZDokhNKQl0DDtaBPz92xsvhkgnZ pQzqg0NX6U31imqiF/Gsuh790TWv/bGNeOr/VhuYDITb6+8a7W26Drq/11GxKwzAxMW3WaICWRMM BSNrm3XRetZcN4BSXglbv+PkxozJFAQQqXNtALFC89NQElgSmGglXJpIzmZnEoYDR5bMSBhF0Luf DmhFAcCWy5Xs7OzK86cvaB3dvn1HDg+PZJhCZFBZ5v0U2bRUirqQNK2kXpXy4sUz+fyL38l4ZyQ7 O2PZPdjnJE7RHEIKNkl98s0z+fGPfkIC62KxlPFohwH1B/cjCXtrgibiUSC7zqZziU5PZWfnQMbj lLSMkvuGLGfE/QIRFpZbFCkNYj0xHEhRY97TZq/cn7aDVXvSsf7ZccceaWwqOUS7YOuk1DZmm8z2 9+myfdtH+xheA9Z7GH5auH3HsGC7e6XuW6uTzkWDkxLywu5uNxz0ObGyTNu2L86WkiSRjPcO2LV5 dnoiRU8Z1HTpEP2JUqkTpwGVF1LHlZSFdjyWJJDFfEouVz/V9uwAPpNb3r2xQ0sK8SZYMUnak6JC K64eeVeDkbpuiB2dnBxLfzigmwigOzk9kvu375AICqoDABHrTfuxzFczHrO9vT0NnqOQ2mmyY9ke XFpYdnkuaZI0UjBQFIVQIMCRLp+zqnDcCSgtF8e/29ty7fhMV2zKXvsyyr4EjS33XfAy3ue4Bqz3 NNoT4fzn9uhnhS5PXliLema/pJA8yyWNlA4x6g+kXEz5+RIlMGGgZSzDPkFqsVhJOkzoTsL1WywX bEbKSccuy3MZDyfy+MVLkjoBJsdHSjWAnDDqjhfzOYFnb29HhuMd6YW1rPI5LZmdvQnBEkHuk+kZ g+yIL8FlQlt5uJjffPM1rTmU78C6my+mMp2eSS/p0crC3D86PlTQHY9kvizl6dNvCFj37zyUwHW3 gRoF6hbBbPc1tdplNKgr3KRinHdf/HPmD58P1XZx7POu8/1dHvUl5UKv+v1rwHpPo0mTt9QVfMqT AZRPIL1s8C5e15KkoaAy5ne//53cvnEg+XImERqWRqkM+pF88+gLuX1zn8qek7FynlbzlcRRIY+/ fio/+tGPZHo6lVu37ih/Kqzl8ePH8qT4Wh48eCBHL5+zU81osivz1VySGq21AknSSCbBmJ2Ynzx9 LGm/J0EvkDv3blMR4dGjr2RZqAUGouhwNFLF0WzlFEFPGQeFDhbqAmGZTaencnD7gFYV3M9VhuD5 gK7ubFFQfXQwUD5VVJsGloIPrEq4uAAoxJR8jpV/zNbWz6Y1ZTSH9rJtsGo4bs66MtKpWXIb7cCu h7TB/HWPyzVgvePRrvGzDN6aMb65jL6HyaD67JfdiFAjFyAmg1KoKpC/+ev/JL/6419KsZpJUOXy 6PM/yJ/+yz8hVeDWjQM5fHEoT795Ii9fPJMffPZDyYtY/v7v/j9J4qEsV3PSEcCTgvXz+KtH8oc/ /EH+h//wH+Qv//Iv5ej0RP78z/9cvn78FeM6u/s7zAAijgZS5v/0P/+Psrc/kd/85lfyox9/TxaL km3lIXOMCQwggasGwMLzYX/A7YYlB+BDoH447CuwDftsEIGOOMOR9iaE9TWbFbK3vyt7uzelBm0B 5TRwBSu4wGkDVgYoBkDNJGnLDV8QdG4DXXsZP3N3DUzvxsK6Drp/oLEGqs2xdkvak0VJuBfps8Ht o2eGVlxlTwZJJI+++kr+9Ld/IiWyg71E/tf/5X+Tn/6XP5F/+sffyXg4kkdfPpLT02P5p3/8B7l1 8z4tImQDnz95Lju7Y/n893+QX/3qV7LIpswkIlz1u3/8e7bbOjx8QVInMmuff/4HuV89kOd4HYVy 794dGQxTefDgntx9eJeUgJcvX0gUo2YvZpkOSKFwSTGGg5TBeDSR0ELljJwogBKWdwrqzEjWktMa g0IpZGpgbUHp4ex4hlJCMjewrwaIvqUDRv8mIG2WmjSNYlsxRrOm2p918Y3aZM7roPu7G9cW1nse fpB9DVYKWMZ052e69JXWSdckEBklIkWWM94ECkM/0cD33t6BPH36TIq8krv3HsidO3fk668e8f2b N27LZLLLdRwcHMiX6GKDtPxSu9P8+te/kv/4f/yV/NEf/0oWRSZPnj2VP/1X/0r+7u//ka7hzdu3 5dHXn8vJaSK9JJLJ3i7B6eREuzqjdResJbDQAVawrqzFF5UTFoibDRlIB9hAGgaqDbJE49WA4Hpy esj3hkNIJweUpwkDyNZkEpba6BWur9X9Yb0AODZB9bLuSp5dP29bS13coXZavn3T2YiPeUx5H/Cu x+uPawvrAwxz8RgcBtGSd3lHbXCdaPwYCk9Uc5d3FIdWh2g+rcH/QVYMciwiL04y+Yu/+Avypkap Nkb9d//u38s333wj//1/929lZzKSbLmglfTf/Jv/VoajiazyQv6r3/5WVsu5LLNMfvWbX8vp8ZFU ZSG//OUvyfae7I6lPxzLb37zG7lx57b8zX/+O/mTf/mnym2ql3Jw619IvlrKv/6v/4yAAguM+xJB rqakGgP2i8BYBcw+4vXJyYlky3njLuJ9trcXtP1K2SBCoCoRw1qCq7orQS+R5ULrFJHpTMNUsmVO SkaT9ePxXN+LDUDIGSK5dW1FmeVrSg2maWWupC8xbMBlBdLWiLXNRbLXXeoX/qOt812O+oLfuoob e9n2+WDetX8+7aNtwRqod/3Wtt+9trDew9jGEKbULtupt+Mkpu0enLPGGvfGLddj+l7outV1IpIi LlPSFYM64I1bN2V2BsZ2LaOh1tdFEKqLIhlPdqTIIf3SY00fSAOQgkET17qKJB3EMhiPZQhVhaKS A6hXSig//C9+QkLqIBrKankmgxQM8pEkM+VxTc/mjIchiP7jH/5IXrx8RusKdANYWth68LvOzqYy SCMHFmvOlTUXpV7WSJtXABwRhwNgpclIO+1ITw5fHsrsDBYXag5Fbt1C0B3yMsLfhNaXHT87tv45 oTaWxyQ3QLI/Ste0JpLJv7yq+Ny3cdRbGlRsA8PLQPsy0Lo+4u9xdMVSqCHWyTDepDX4mS11bdb6 7rhHgW5EmhHLSWptqkpZ5IjlLGWxlGWe0W0agtEOEkQtsiqgtgnmPbrO4McKKajwAAmaUB5/9QXZ 31BJmC0X8n/+p/8od+4/kMUql5/985+Q8IlgP8AGBc5ogAo2O+JhQXBbTs/OZLHMSO5UIKllNlNF Brirq8WUwABwgdoptiXLclmdrOT45IVM8oEMhgoaiGGBgZ7ENZefnx1LhG45KAGCUqoHOGCim+XU ffw3LQDfCvBbdW2rDbys+cO7ypJ9bKOdUb2KS30R/aP9/JrW8J5HG4varwkyngCfLYM/NhbWVoIb qXROLPb2EsnLSnoADDYJDZti3aquJCsrCfJSigqNH9AKfiVJCVlb8O1F8gwNTcG+DwStH1jOA9mV UKR0jSfuf/aZzBdLWeSFTJcrSQZDufPgofzhiy/leLqQveFQepBizpZaTuQaOihbXDXdAUD9BDEm LbEBURRbnPYTSca7tOogccPSm4MDBvhVyqqQOgSgKpE2gsyE1x0Ix+Fg90CSKKU8DQAR5TcqUdNn ITXKdDaJoO3j3ztHRfAbSPgWgV/X1yUH8y6yZG866i2xty5C7EXf3zYuKxPqcom7tusq7iDGtYX1 HkZ7orSpDfbe5nfWj20lhvVJ1hNfsOJNLS4UQ2NKA8BQwwjd+KSfSg+NSAvUukELdN3mKoJFAmVQ 6LyjIJgFxj0HoqV8+ehLSftDuXHznnz9/FBO5wv5h9/9jr0CR+OJZPmpRGChRz0ZjqHCMCDgHJ+d MpD+w+99ny7ifL6UybgmQbUXZjI/m8rh8xeyfzCRNE2clZXRhQPoDAZ9stzP5kcknCLQDuusFw9k OCjZMHV//0BGgxEBi2x9ZlbLlkjfph67Fm9v8qi6MoAWy+oCLN/S/VTIofVraFpddb02rrLeV2m+ 0TWuAes9jq67HONSzev13zmLq5Vet1XZXR71iBb7AvCE6NvXc80t2L4qkhDglq8kX+Us5kWbdxCh KOVOiw5NMCIJepj5aMBay9179+T54ZGcLqdSBiJ//JtfS9IfybJA3V4t5SqXoFqxSSu78hAA0Gor leFQd4JxKcavoKIA1xOxIXyOWsWM+7OCSkI+Z1fn5y+ey3A5kCgWGU7AvFf9dYBsgk7R/TEBazyY yPHzI5lPF8wGwqXEOvt97XTD+JSTuVlbQ5sWw7aAsS/l4ltapkbabrn1riycj93C2jZ8cNysLOhW Lu1yGa9jWB9g+JaS/2hDbziYAL7V5ET5as893GBle/POwMvp8CGWxW7EADFoTNWlZIz9KHGL2uar hfTyTMrUNThFpxsE71HSg2UQu3ElLxDZo/xKr8cAfhUkcjpfSTqayLCfSDoMJV+eyWx2RgY6rDVs XNTTWkZkCAFeg/GQcStIHQOchumAUsirbErKQpKsqMCATCCyh1qiVMnXX38tSRJy2+DeFSXaDMWy Wh7Li/yljNORlNhW9oVd1/TR8kQmr1BwabJ/niQMHlE07ne7aWev2laY/902K/5DWDgfw+hy59qP fjmTfyxeFRCvLaw3PVne8W5xP9fLrLHGabRrUJzsdOvAjBiNgZqBVVVT4sSC6/zz1Gx4rs3qcvOG DUyN8BiEkg56sljgh1Bnp5LKiG3BgiLArZZ0GfsQq4ug5JCTy1XDtYLLOABtoJBvnr+Qyf5tGQxG UoWp5FUgh0enMow1BtZLRjKM+nQHsQ7sUprEKpnjBPy0JCfjgVpltSyWUwniUqS3phyAswWLDKVG IJfdvzOgYikC7kfHJxKFiexMDgiG89MFtbFGQ2x7okBfauaPnXLCUBbZYsO1g6XankgWj2pTGfCc PRJdIXUbyK6HXAmsLnMht1lXPrDZuAasNxzN4Wxdv/YSzRjYaZi6VA6sqM2uQuyonTNAY2xJJaxU 3K+nUsPKxlb3sSzQAh5WQ4/BcaqxA1wQbMeasRzNCM0ezuGtSUomeAnOOJZFcBwBerT4qjOJkU3E +wiQF3nT0h3aWLTYkkhG0VhWWSnLbC4SxpKEsaTjXcbFJBqRqJoXS6nKnmTFTOosk0U2pw4XwBDM 9n4cUZSP3XTyQsoglySNZVXMZbnU3oAvD59SrQHggXZg6gqqhTQazBhQh1JqnlVyOpvKnZt35HQ6 dTGyHUrOwO3cH04IXLAKWWvoGrq26Qt+cL0tS0wLjAoQdQO2+Aw0CyOotq0ufwLab3Qt409a04/H 8K09A88u1zTw9gPbZvr52DZTZzXp6XYWdHMDLrMQzwOzvy+IN7Yzgn63b0pae99r/77fHbvr+LX7 Jl4D1hsO16ldVaxwh/fPh5lDJk/ZnPyKOlgICMMKYosvqo5aJTRASh8Rm3IJQWox1ZY6bH4CEwIA yLbO6lI69VJui3XccSqh6CQD8IogIhhHUqy0DrEGD4qgGEgJkivubgCuXqS9d8sAACAASURBVIIA mAouO9E6WE15UEpQgBwas0gZwLbKK1IY5rO55NlcgrqQHXC/Bn0WXAOwAHAAHVAs0BBjudKuOQBi cMRAT+AEXIlkg1xePD3ixQ8CK+sEwS8r0ag1cA0qSlqIiJshy4hsqKmwYhKDNMusHvTAMHmCuKk3 ZFNVdBFqleP4sZZ2+zNTUdXeiWtrrB2XuYoFZhOy/Rs26bdZL3Vr3b7L63+uCqtrzXj/8arDT1DY 9/2YoHWW9uOr/j5sG1fdjnZs8RqwPpLRdf44YWBJuc/gXWEyarbr/LJ1y/0019KGNVTVi9tJKoMb FVaCXtH0MAOoLcC1KiXHxV4VdFsrSiSDOLpJZq3KTK1FgKxUjF1BN6sfDyl3Mxqm0mcT1LVVYy3f dSVh5x0awJMtV7K3uyuz+ZzWJ6yH/qivy0gpk3ikTH9YYegEBCClC7fJplbhQJWd0U7lm/SEdpbQ ByH/+Pqt4q9KkLzsM2yvD1ZmmbQ7qTfnuD6fNFg311hbirZvPvC1QeIqoGoWZtuya/68igJ/+MfU /+2ubbkI8NtZxWvA+kiG9R6EZUWKAi4MJ4bcvq44YZnIs7uavg9LCcFndtCB+2gxGkorwxWFZae9 ChFUX1WFxCBqcmXq3sCcoz5VXpHjlaMFTQCAS+hGotxHG5rCKoCLmhGYGDcLKkniQNKoz5ZbVDh1 uvKQMZ6jtjBfcVIyLpRooH846ksBWeNKJwM0uDLyr1Q5ApMRoOUD3WI1d00rJk0Di9USMsWqiWWu hDHnB2lfLY4qbzJ9PMZ0ITcVQttWgj/pLZhvz/3vdmW3/GD9ZVYFm2DAffXKWfx1tIcPTu3gdrsU 5nXACgPWbtuqMlDlzYBhi/MWlm1bVzVAG4C3HZd2VpE3jStt9fV4p0Mvno6LvMMkr2sXQEYIDDYR SZfr74MwigYPyI6hM4y6C6FrtOA8U7iWRSWropQy1EYMcOsQkG7iIqVIhlZadFXVogNgKahhnU6T HstDornMpcrQIBX66rnUJKeCld6TIs+kgNvnOiprxx7E2kQWy5nsHxxI0NemEVEYST8ZyLKHmFEh pydntKDwXQTu0ZAVIFbW2nIef8aUBw3D3COL7YBs6rstdnxtOdXR2qzl9AGm3bzUdxttXf667Xy2 LYzuc67Hwn7Hp1Rgm33lCR8Igg7rxN8O3yX0weEiS+2ia9OsS79DtoFWicio95u+BdplpV50LPx9 3LZ914D1EQxrT79hLdmF5fWo0/fRxUUtLG1YsW62aox4NAeF5UO1gARtLlB1h8COCvPhHQTfQQeQ KHVtBnsELP6hTTsarEYFXTYUbGMNsKpYvO0Vc9dVJlKtJKCWOqykTAImARAT68nZ/EyD07Wqolqd 4Gq+IMg8P4QETUptLATCsE2l5FRDxefoYoNYFSyP5XwB0S9aZYlrcAppHAWeilr06ASkzVI16KwK D5uUhUvPh+f2mFvFI+SAsK1iaqPt2l5kGfnbY26yWZBt0GxvW70l09bet3YczF/+qgM3CzZNwU3G SwZY8TealbTB1t+mLq5aF73Bf79re69dwo8MrDbea19k7Lyj/eutxhDt2KVS6wbBcgysCm0UKvcH pxDB9BLwVwJoCvKQ4h4sH9hlsLzQ8AGNMdaTFHEykEwjAybSBcCQd7/jMpAo5cmXoA3kNNz6SUTa ATYK24l41nS1kgo6VkEo/SQhWRUX+ukqV45XEBCIWF5UwapbstYQjTPA1UIsDcCDQD1AS7XhT2iN WbauCcjS/dCsm6RKWEV5jsZaNq2jteW06dK1Y1MGJu33fGusTXXwrbUu0PAHEw6u0NomuM8j61I5 8IeBqG9pdYHUVVzSrsHmtB31fmZtwaVux9x8kGpn+Wy0QdcHL395/2aDcW1hfeCB82CxKsaxGqUG 7TFIsLCLjg0qHG0L8XBHFrXluSTpCOj6rO9D5YBOI+NbcJEi6Q0SidBhpxfKDK2pepCiUdeSfWN4 gSoy0p2sAH2lBCxstHo7MlOZAUWRdC/StqyoK8zQqBSt6iF93O/LCp3mKUYYNS6QTmaRBw8fun3r kbyKWBaY61HQk4N7B01AOctXMhoP5MbBgeRlJkWSyf7+rsjxVK0puKSON0U7dKfH0h4DGz0G2lfR DxojbqbnYd1x2R8GlBiWXTSqAbbbD3Zvi13Z683zvgk8BgLmemFchZTac5nAq7hkrzPMnTY30B/+ jcAHaR+w2q5xW7L6su3zjy1jZm+0N9fjSkNPkLtIPffPd+fay8Nbg50UM6NnVoBiEq8bx4KHZ1QA vNgdBi4aAuCl9NOepEmfFhBcQdU3z6nKAEmXuixktlxJUcZSI5AOPSlYKAzWI/unQXCwzIl87Men 5n8BzlVeS5hlkoL20AM4lYwZLedTybMFA/u4bmenZ+RV7e3ss8VY3EtkMVvK4Ysj+cEPfsCaQ9zF Ucs4SGO5f/eBjAc7Mj095e+jrvHFixdyeHwow/FA5ZX7cdM9GpYWLC5uv0CqGRI64w3AIAWh0O1D 1x1zc9QdQzF43MTBMMxtBVhh+BIzTUNX933jZrWD7+Y2tuNnG+cYiQInFw1rEL9h38P6tf2agqiB Zui5XAYi5rL57mV72W3uMG407Zicrdu+44OgD948ruUmd6w9fBJu2wq7Coi3QfIasN7DeNW7HC2t DlfR/5yn1skoa1ZQ1RbwH5w3NakQV8q0GQWupxh3RKQRoc0AVwWTNZKKd3WNX2HAHSTdwJFVt+0L AOz0bMkehVAnxTy3CxOCgFVRyO1796VYZRQVRK9EBNRB7GQgPa9kf7LPbT+bn0q2OIOdxYt5NJyo 5hXiVdDvgkxOoC4W6A7IEi4inagQ0cN6hwO4f2rFYWg20Jp/KHCBlmGumn8jacvQ+PyoLqvF3rcJ aY9tS8cykl1ZNAw/NtQO5Puupm+hhK24kO/qtq2dqwbXfarHRRbaK1/LW4L+lyUlto1rwPqIRwNc brjk4MZAE1XNGLoLnWoEpZpduECqnC5iHBmviyxRohyyfAzgh0p1gMsHV9CuIZ3M69pGvudJnwIc 0/5Y6qCQVY5YUyH5Cl2SQ4mToYRJLWkyZIdmxMBg7UEGBvWGABjEqb569FiD5GhPlqYyRvFy3JfZ YipHh4ckk07nZ7yzD3tDWmNo+QWuGL05uKQRrMahJLEK91mgHBYSKA5qASiQMW63AQgKOj4dwA+4 m6pFG0T8WJOfNbPPbJi1w/PZwTY3JniXm+QH4LdlIW20XS2/1Oii4e+XT5HYFgw///7lLp09tmka 14D1EQ49YSrFa6/XF4S7uJx7Z3Gsq0i527dpYVHsxVs/I/GFVASnnFpTIG7aBQMZYk5ONjRWcijf 50RAFEsD4MrpwoTdZPA70jwne4TAeJVLma2kqHtSBuBWoRQokCQK5OvHT+TW/h5d0eU8k8XZE1Ul PT2VORjjlEAG4PQpFbM73uUkRr9DyMoAoKIQJScDBuwRi4IbhYA9BAPv3LlHNVRaXhmUHwAyOoHh 4k0macu12SSqaulld4suH3jaQfku4Trfsmkv0z73/m/47lLbCjNQ9GM5wRb9eN9KumpG1Hdhu47B ueuuBZLkpryihfUqo/2dawvrPYyNwKt3DbVfX2WwYNp73cTGjAHvWOeI1fCOSQZ6SXcRtYm8yLAI axp7dBdzABh00MnFguSMcqhYHG2TjsXUbrI6qWaAxwICgLBeholMhhMqmxZQbcigEb+U27fvy7Cf Sr5YNtZM0kvk7u170otDGe/tymK1lNUCRdMaNwLowBJD63poamH+2ySyuBHACLwsWEDzxUyW+Uqi HhqoqlAglEkxjLi4nsCbTHAUi/vWlV/e0p70Xa99oPHdRz++1LZ62lZN2x3rCtT7nwXeMn7Q3QfI q+pOtbej7Ua2Xdh2TOwqEHQZ8L3KuAas9zzaJ2pbrOoiS4uMduNrsbTQmWewtUyygCQEFfCDiwg+ l1lxIF0ytoPcHDGzlpJxrZgyybRCmCXEWiopG2ANpHKgxbsyfj9OVTkiEAbjcUnV4HD1UlId8qKW w8NjOTs8liHiXEnCtl0Yhy+PJRkOSGuoHIETcjQoy4FFBnfw8OgFFRxQSwiXEQDUD2KZjMZNUBrg hXjYcKDgwGYStbqAFvRuT9A1XWB9Xgyw2oXHXefPd7n8ydwOvhsA+Kn6Louo7Xa2g9+2/qAFGD6t ob1MV7yrPZBc8X/DX0dXwP68S/iKd9yN714+ri2sD+wS2nu+S3jpOtYBpHPf0OtR17UxcfgIuWO1 usDHqqO1y9jQJQBUVUjAUODpaX2YK0rkBHbbbpaV7x5CZA+JnBX7A4L3BZIogDBSNYkAMa2MVtiN G7fo+s2np7TOYD0dvngpqzxjFhEANT/TEhwCVr8vw3v3WT9I+kag2bJVtuQjJhrWAasMqqMANKhY AMDiQGNXjbXi9gVur1+vh+V9i8sAC9tgCggXxVt8SZquGJYPUP57fjbQ/13fNWuDHYYParackTgx uqzEi0ZZbQJW2231RxusFGwvXH0n0Pnvv+q4trDecMCOufgexjAvn/EiYGt5tV7sfVtuPbT2zz41 gGiWcE/INnCPbEsBYKLsAzTT9WKiBYbJARljxKQcRYLtrgBU+CyvmPbnd8NYghAuJS54Is7G/tFC 817PphDAiySJRHrIzpUQ9JvJYr6UfDWXnWEqq3zZuHBozgqqw42DPVITzhZTyVcZ+WJZFrLxBGJU u5Odptg4jFVvB1ywuC7o8AKcRkksh8dTCgKi2Fq762CbZpL3Ssa91hsesDyJ+2yTraokpuaPoypg X5H5qxQM8ViWOB44GgBuF7PBsauVRmDA4KffDXzarp8PXgZMRsz0wclka3yWfXuZ0n3fwMqsqbbb 6Qf9O6/fVvxsG+Wg88p2oYjLlvHjbxcx3b8VgNXeqc14AO5I7RoxM4ffXyNLY4C7LdRt0Y2lW0Yt cgSzgQeYGE53ndjCJ2oBYCLSICKJHan4niwLBR1TbPATMwQkZMUQaypKWa7OpK7Q2golOKgpzNjG nd9HRhAQaVaAoMwmYPYOOur4vcKxzRFDAicLAJdREMusFN3bHlxMKTh/x1Ei6Ny1WlWSreaSxGC0 i0STVIJJT4A1VRlJGu3K2fxE9idj2dsfyxdf/EFu3rxJhj0m7XgykmfPnsjx2ZHs7k5klp1JGsby +e8/l5/97Gdy594dOTw8lPFgJI8ef83JfDC6K2m/pt48AAwSzFQr7YWyw4auuVQAF2RCwasCoRXA gfKiEM3QasmhrwWtsggAVMkqA1EU4Iki6VxqqLLSGrW29vpH+KxQG7m2kNqWUMMGb7mPvuvp1xIa CNn37bu+9dZz6/QtMX+dVjbTJYNzkdtq2dBttZRtYFm7xpuv/fWuL1gHUM2X19fvZXiFethPErC2 meTt9wn6Xlzi3Y9tv6Gs6sYaqqFttSbXEazcSdQTt1ZeMI4VuaAuI+dwuNuLdHErcKuYFYRFQK0t WF3UTFYQai7EniojMKOGmBJcQPwgLDsFTnNDke0zNr2uSgul6WZKLUmvkkiQHSzo+hUZLJOMruDO eCRfffkFm6Ui91guMwIYQNICxXADASwArc8++0y+//3PqN7w6Ouv5fmLZ/Kzn/9MxuOhHJ8eycnp qeztH7C2cJkXJI2iezW4V5RJhmBc3Jeqr9cN3MXUqTRA/wsyzzjA5gJS9RXKpFYl4KRzzLKrKnCk HDetVSJj5x7HsMv1alsTtg57z7cy/Edf18qW98mnuVNz8K0qf4741pxPvbDfaM+XyxQhLhtd63yb 45OOYXVnG86D1sc0/MBu1/AzLVYnyPddyOMqlxA74YDGUEHVynMfYLUVun518jDpAE6OJFojXoWL GtIxwLqaVpYG7nXd5ulQYr2xMhRFAbJZPpWqxl0cYn8o4M2o7w5pmZ0xdNvHUg+UmgBuWBomdAGD g0gm4z05OnnB+sH62TNZrRZSlrns7e9w0kHznXLJSZ8KpgAfDMg0J320oh+QsgEAhrsIzauw1o4/ CMjPe+A3oOU9+hbqpU6ry64Va4bauGpmvQPI1fLB8noOz6t+dsWW1ud8DVhdWT8bPgfMt8psWV8V NYc8j4ut+UmCNn/Kp174bqm/zfa+z1Bvb6eB3kXjKuVDb3N8MoC1PtftavXtadOPBcQMtNrgpbhg d3ZbZq1/xaDsRReMswyMLErCKOsBnXopGAyOHAmXE9YTAuzqh6JBBX4LBdBYPpYQfQwdTcLcn+Vq 6SaHAirkZFhSxNbwpSxWZ06yOaQOOzpOL+ZwrZayWMy4mXqnjyRJ+xID+apQhoMAMvNsOhGGu5IM EtITXr58Li+eHxJgIVUDMmgcoQxEZWU0iqZuT10vJY76kqagM8SUR4aCKGJgdvzsOY+Bxzw3UqjA 7fMoDF1xFnv0LaMmJtWR9m97Bf712QUKvrXkr8NcOVtH5cDBLMC2JWaPBkJ+BnGblfWmgHSRdfk2 PJxP3MJqnvFfHCe7QfglR+sb6PtwCS8eelfenk3p2kbjVl0JcFGOQ512BJ8QTatVv6qVoaJLiCb2 BpoovQlCKcpCKmT0eBxd0fOWNMJGdpPoWkma4g6/JBBEUZ8xrLTfk9UicNbWjJYVYma7w4kEQSpV iRKhRKbTE7l970DyfKHKoXEqt2/f1ZhbHJI4CoE+zBn0JcQERIkPtgFUCWhl/eIXf9Rws0xWxlQd EPO6ceOmNm/NNJBtYOW7Z+vztD5ubcqBvX8+BHG+RrA7m7YJWv66fXDz1SQMLPzAeeQx7/11+URU AzIsi+OyLZSij+1rb3NZqx3cNtplRe1j+bbHJwNY7QCdZ9U31stVyXLve9gk79os3+ryS2DW37ts KFDByqIV1ByLdarbcokIESNDCRcOlhaC8GAzsIMOuVgKRLwzI1heiYxQmNwce5BQ1xMacTII9C2W tSxmc1pUcOHU0kNTipUMhqkUi1yypbozSALgOfS1wFbPioXEidYtgm+F7Y6TSG7cOqBLCNCxSQqQ xWsE17GNiGVRl32l8jNYBpYWvodtnE6ntMrUUlnHfzCQtYTKBFxWWLF+AbOf0evicW2AmBHiNs7n +s8yftvArnHfW/QH2wafohB0sO/968R/7IpJtbdN13GxBdWlGLpx9XWoL7xO9m/baAPoRw9Y6wOx 6S6tA+vbv/sxuIVrsOre0I24lfYvbX334sH5wgtkfUHjOeIxtHpCTHZYU4jtAIgi6rOXDIMjlhUh 76eZMMjEUPqYBTtOycCbIHQjacupG1hqWzHEjfAFZNYYq+KSuDtn0k/6EoSlZPlcZnVFnlW+yGRv siPz5Zn0YpHdvVsy3h3L3h4A6oU8ffZEltlCTk9Pm+JmHJY4BghBB2skB/s3VNiP4BdIDDUJarqr CwgteLivg74G9WFhFUEoJYQFnauVUy65okwPNO5JOeE1w86z7qLT/dnkKq3jhABY/3y14z5dLlfb 9bTYlc84t/WbnLQVdFceI71t3fhuZBucuv64vi3u3FUBiwoYWyoC3oXh8NEDVnv4oGWvPzKD6sLB 7cWTFvC2LSztmnPZcIFU9gVTSgcB0AnusQwGhcLszINTDbUCWFax1BUC1bXEkU5MMttN0A90EUqx V1L6E85Zcrrdmm2sCtVwH48mjFtBpA+AuUBsBpQKyAeGCHxDKRQUg0ySgcitOzt83e+POcm+fvRN E/OiOgOyfdUxP4MlNl8s2PYLAXFYUOB8UTKnFGYalYNVyIsXz500ckRrbwUJHafawPU6TStL/5tm uQW3fXfGrHb7a5MzMdryJ13u3kXDz+bxjHpghd9AJtR38zLn4jFmmCQbLpsPWDb8uNj6vPkW4vnE gb/N7f27aD+6nn/nLKw187j7IDgJI452wPRjGFreoZYQ+wW2RkNXaVlh5hqQ2OjRNXyLDJm+Ah1t TLGSJNCV5DVkZXIJSaXQaHlZBVoXyPR+IoX0aAFRcpla6Ap8ebai3DDoDv1BLHnm4imQpcFwnZMB gtiOciUy2Z1IL0jk7OQrmU9ncuPGPktnTk4PmflD44m6ztlIAok7ZOxOTp8yCA9A/fLLR3LvwQOZ TtFBeibHJy/l1u3bcvfuXXn+/DkfYQkAXO7evUHO1cp1c2GBNppNpAOpUgW3e/fuNWU7AC64i7Ck TH3UrCUWVntxHgOsNucJwIZ1WKmOL9p3UZbtKhaGAaQ1oDAgsoSBL5UTOKDx2fjtzCVe4/iYleN/ r7GqvEC6kU+xrEnd+O4ny5w8npnvqpq73LVu/7Wtq6sC4CrH55MCrG/L8GNV/iBRM9QY0iab3bJR 7vvN5+tsorpxm/EDXlxQbackljvZrp9gVSNLqMBJJnsQ8TmaVjD9TwFAH/jVVVIOl2wAFu/yrEsM pMpLluOAfgC9G2qxn83l5OiF3LyxKzs7EzlaLeTuZ3fl6y+/khs39+Xl8xcy7quKBLWxKu2wHMc9 OTg4kPFkSEsK7iD2CWCHizfLVjqRHEhD3QHbMltoiQ4sEhUrXHOUFGTWk86nB1ijB5+I6Tc1teUN TDCpfQ0rNGj1AaHN17pKlq396LtUfoLARldQ3563raRtrmBXsqFrnX5tpW2P/Ybp5m9Td/Djyn59 pP/7l7mc7XENWB8IqGyoooKygTdcCHdCbRIBSfQz7+6NrCCJjQ5UQsjfoYAZF5bKDsMCsaFSKlrr UwcoOSFLskmtszKnB+VOeJgKcjTQ6Ia7TBZzjViFWSFqlSGWk0ShRGHK4mYomsI1HI2GBKO7927L fHom9+7f4SPiVUUu8vLwOV3BdJHKgwf3JI7vsBv04ydfy5Mnj/mbACHsJ9QbAHDj8YiKDOhSDSoD Cp9XWUZhP9Qqgo8FyxLuTgaXjwRY6M1DRMs16cjVqoDltcq1+QM7AUHMME4bC4IuIwxT2KJQ9kz7 EkLKGdYsLByrbNhCh7hs+FwpW49v4XSBYN0Ct65rrr0u/33/M4ud+ZlGfxlTg2jHzcwiBGBZjM0v SbLts9/xEwrt7XyVcQ1Y7zHo3nV+eMHV5y0sjaV7tH1v+fUFjlIecKxwoaiEMXKBACwVf3GZSSMh InjMn6u0gzQbUICLVGhsi/0H9aKzOkcE75ttZHmPAh+aq0JHC30H0aoL1ASAG3mYyPiFfekPbjSA Mz7Yl5cvj+QHn31PptOnsntvTxZVKfP5sUwmI+n3E8mypTx5+pJghkzjw4cP5fe//z2/j1Kbnd0x O0ODXIpaI7iPo3QoRb52U1Dug5gWBiWbl0stPYGUs3f8OMFiANJm52cMv0uMuUtmXcHdMsuhqCoq UHRZMP76Lr8+1uDgv26yox1gc5XgtoGdPbfRBjr/N3xmvP9de27gZVaqvw778wHV14RvZxOvAesj HAZU64tijUrbrmd+xz1vAKTuCsY7VjQ0rKjl7tjtThML6MS7JpsF9KipTjmsRpAvoDApS4A87hUv MAAAS09QNWfAp5R3veg0QxaGSynLE4IIwCSMVM5GokqSXqp6VkEkT755ITuTA3nx/Fj2d++yaDrq 9eXmzVvsDQjS6GI5JWjt7Y0JNicnR4xxoTQHIDYaDZjtQ71fWJWSF5kskfF08U1MCnMhfXkYX0vL LBr2/WNH6kQyF3ynEsQK/RCz5jj4Vq5ZGX7sxgcNP1Zjry8rPm5bVD6QXNaerH4FQNz2Xai/Gij7 n/mgaPukfLZsY3mrV2xz23zwt+e+W3gNWB/pOAdW2wCt6ULi7lTNCdflADZc3rtGATp015jhY78b d7Gw5JpBeLKicdGg4q9Cj2aPHImkRQ6+FqgJup6CWAdlB2Vxg0XO+kH1EzXQzp6EAMpa4qSSYCgS l7BAFPdAb0DgHsDFfa+EUsmQgIFUDF6jOw4yeMO0L3VcSiG5zOdTghJUE5bLuczmp+puJFqYDF4V Jg3cwUHSZ4yrWqmoPX4H1pQ1oMBE0cyhgpbV/PklKgQ0sOg9/SvLilmMxg/Smxvk9ycskBRpSnrW ssq+i3Tx9XGeGe/Hi9ruVNCyTC6yUraBnG/tgDjst6P3O/D4IGSJAVOHaEDfgZXfZNUf/m+1XdTX oT5cu4TvYVxEvVALSMkGOrHc8k5TpskI2ro2VtysxZWeKNcqCAoJnY5xk1UKIomqQHJysJR/Q20o wpZaDQhM0zArcafXydoEgfEz/GctK4yC6yCAOsRSyqqQ5aqUknWN2sQikFj6aV+mZwvW/c3OlrJ7 57YcHx5zO0+O51IMCrlz94bsHuzJ3/7t38jp6bGcnh3Lzu6ufO/7n8lXX31F9QbsDrKI1ncwKwtJ k4GMkgmtMGwrAIsZRMcN0knk4jK0LjcVOQGaRGiIHEJBI44oFGhZQAMsnz3PYH/tx3M2J7q5jpah tCzfttG2noxu4WcDfdZ72IoztYub249dmTkftNpA6T8qLUYzlj6QYp+6pGzaCQMDuW1W1VXjfP64 Bqy3OHxhOxukIjS9vVxjiebDSgPkBCu1XiAV4wMcv+++3j6/Zm01XXQadxKunEah1GV07l24bkKB 5eEKQgoZEyNNepLG2p8iB1UA8axQA64YZLvXkKSpSBbl+1UpJ6upVMVMlnPN0sEbTJKUJTWwqOyi //zzz+XO7Yfy93/3D3LvzkN59NXXdCmjOJAnz58SdKCb9dOf/lQGo74cnxzJF198QSJoFO1L4YTm hkPEu4bcHjSroHhf3HeTSIHLaAoAK5tcdvBsgtOawjphXYKLZnGkIJTEFT7juAIAaVnEmhGzND+s t0GacvsQwMdnZqm8iqZUW+bFl4cxl9YHi/ZoWyu+Bdl287r+YL1i2G92BcitK7WBsXHZ2hYZxjZL 8HVpDe1xDVhvOEx6xawdOwW48NFR2U4OuzHzZs7iFmbokI+LoLUOl8aVeOiJdW4i5plnYfu/s94A bSRBfSo4gnUhZZFLVi2lKjPZT3bZJxA9CVGwHIcJ9ax6dSUxWNymtBM4TwAAB+VJREFUg0Sip4r1 NXIm7hKx/ol5pjEMWBi0HtKBhINbki9jKSs0Yx3KIE7Ydh64uMyhsDCQeb6Qn/78p7KaFVKMczk9 O5TRAHLHA0kGoaxW0H9fyN7BPkX++uO+DEcjOTw6kr29fTaZQE3galnIyckZY1/cskFMieXVMpcn j5/KbDaX6emUBNMYHaYR2wKlAzpfLoHAGBQsKZAw4d44sT4MlBmRMU9um3bhgFVIMIACRIR4mnK5 IDkNkCaFAjI7ScLEAM7vfDFXakeRyyAcNL0LkQwA2BntApM/z5a8TmxC9wCWYc3vH5/MGJMzwOjh xhKm1C9TqwYS1ErzaAL2MBqdhRZFKFtarvlkZaFy0l4vQ/Ab8aglVZuF2D5Y8tLz3EB735IZNnCT 27g2oQ5CgirIyG2AOq9qen6Cbb68Bqw3HWb9dL2JS5mI5hQZaAmh/VaoIEWwQqbPozU4DVPaSZfe gCrGtpCxU2qE0ypHOU0VUy0UQWxwrfB5xQ45eESSHugZi1SQCqXKnkrONFnNVjMC/y6Jrzq90+US PCWh0OBqupJluZRilMsYllDSl93dPZb4YMDl3D3YlSSIZXo0ZZwK3K3RZMDPprNTeXl0yLZe+/t7 KvDX68mzZ88IRrB2bhzc0iLopXa05sTlBIxYqmNtswCuG1kub384Md2EQ1yMQICEgZtsBlBKutU4 DjtjuzILBKpRBgTrGN2lIfFsmTNryGpWnmX6fPqAbZPPFfOD8+bO2r7Y8hhtCwnur2/RtSWWzVLz 37f4Gj6zJIPF3ny5ZmyfJSBgUdpv+GTU9z2uAeujoj20ffzLv78RN7C7IOgKBJmeFE4ehne+AGl6 OIEua9iLJEdwHRPnkrpLZdnrHXbdnKF0RMqxxCCOIhCfrQgsuGP3hwNSEshlQmOKAHf1ngziVMol ml4ULHhe5SifUeY5rCMlq+rEsElrrmWapAQEszrArbKJCAuGVosDDp/HhISC7+6UHXEnv17PANqs EQgA+ul8tmaLtHQmh06On9F1mUQMLG/NM7riRhYjw5/PCjdLxtbnB60rz+3zY0l+ttEftn4DQgMm DBwzX8LGvmscK3wP50X18nVb/ezra/ageO1xDVjveLC+DxaVy/zpa7OhyOLcyuN5ldHmc3GyeqRG xkf8DCH1310wF5PZBY8v+n1rt9Usgzs62oORf5pINJpIOhpJSqtCFT+fPHtBFzIdjBikR2YwxHdC CPGllDQ+OjkiIfTghuq8gyJxdHQoT58+lZ///OcstYE+OyYKLCKtFXR1dF7q33d3TDPK9j9oSQ0b YGE5AKGBlU1SHD0DZ1pkXnyJAAlLNRdZgOcV9RpQ8lP8PhMcfwakFlfjut1x9y0v32Jql7qELeqA xZPMuvKD4AawfvC9XSvpUz78AL8PoG9ybb5tK+wasN7xUMkXgBSC5644WRkC2r6CUiwdRakt6ZBX ASy1IEAgdXK5mBhQJpBQ8rySDKqibLSKtP5IGfNewNW/oNtWl173btKIumZ5NpdiPpcEzmY/gWCy LOYzOTk7lpMpBP4C6cWJ1EUtq0Uhw7gv2WxF4Nm/fcA4DcijkEbW8popfxfSMBbg9t0UfA+upBE7 aYlkALkjggFcSVh4vo65UT6aHn4tlrnvzlnXHj/Vn3uWkbp3ClzcNsTEnJvln8OrqHH62T+Mdpee tkhf0EHQNGCzfTPLzGgYvvXY7u4DzbE2LcEADiBsy/lu4KuW07zNcQ1YH2D4GNTwsJoL0SuIvgJP ZVs2CBYUAvAMkDJL5tUawt2qXKYvNOG/7Vkoh4Vu/d72B4GMhrsyh0DxQrNlZRFIbR0zROQXv/iF nE2nkg5HUmaFSNmTcTqSl0+fy/PnS5buAL1hbYG3hYmBiXJwsN9YAwCi5XIlt27dIoiZGgP+lhk6 5gC8so3OxUYt8I+HX+hrSqFddXq0umJVdrB2Yr7ryIlNyeecyQHSIlqtu/BdAwCb7Lb+je1qNYfY yGKWZeOKdV9HwWZcrqWs4G+3z5r3rxc/nmXWlX3HgMyPf5kF2WQuL7w6ry2sT25oFxqd5QyLw5Vg owdc55ttkl7HeuYkcalECy5rcFg/ZyYIgIOmE7wI0e69J1mAejoXBO4ooPW3ieU5TutdJ5b7LMQF 3Zcw2JWkDqWYn7FOL1uhZKdH9w4WC/6QBIV2FfhlYKnP52fkVQGMkJdAbIthtiAgsx2TAXpYJhsD ywvgMQCdAPGxfp/A1WNsTDvvoGjaJppZGzaxMLV8PfTAWRTG1EZ20M+AwcKyuBMndEtxgDSRWO/3 vgvWxMw8qoKfFWxcQa/Jansdvutp3+kCm/ZoUx+MC2bP/WyinUtYt2ad2TIYbQuuXc/4oca1hfWO h6okqMsFoiYlzSm3rt1srH/X+g68aWFdNnhH9JpDKPk01N6HjixZoKMMkpMx7rTK02rW75lPl02G 9T4paGHply9fSj/VoD7eR4ypKlZsMxZEtSSDvqT9WHaRTZsvJFsiiJsQXGCFvDw5lcnuDrNtYLgr k1xJoFg3LCrNFkacxAhyW03f4YtDOdi7xW2yQL/v4vnBaRJlW+J4/iT0nzdxLmexENCchdJYUaQg 9Fh0je31rQ78tilHYPttW3xXzQCsDXZ2rM2qsc/82JW4YYkJDCO2moVpxwDHBMOXicHv+tsKQLVs YJul71utbVfXvzG+r/H/A68oR8pQnHaFAAAAAElFTkSuQmCC