20180621 16355600 1.0 FGDC CSDGM Metadata FALSE Cal_Environ_3_0 002 -373976.129295 539719.617303 -604512.649477 450022.491310 1 file://\\data-svr\GIS\Projects\Warren\LIMH_CALENVIRO\LIMH_2020\Shapefile\Cal_Environ_3_0.shp Local Area Network 0.000 Projected GCS_North_American_1983 Linear Unit: Foot_US (0.304801) NAD_1983_StatePlane_California_II_FIPS_0402_Feet <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/10.5'><WKT>PROJCS[&quot;NAD_1983_StatePlane_California_II_FIPS_0402_Feet&quot;,GEOGCS[&quot;GCS_North_American_1983&quot;,DATUM[&quot;D_North_American_1983&quot;,SPHEROID[&quot;GRS_1980&quot;,6378137.0,298.257222101]],PRIMEM[&quot;Greenwich&quot;,0.0],UNIT[&quot;Degree&quot;,0.0174532925199433]],PROJECTION[&quot;Lambert_Conformal_Conic&quot;],PARAMETER[&quot;False_Easting&quot;,6561666.666666666],PARAMETER[&quot;False_Northing&quot;,1640416.666666667],PARAMETER[&quot;Central_Meridian&quot;,-122.0],PARAMETER[&quot;Standard_Parallel_1&quot;,38.33333333333334],PARAMETER[&quot;Standard_Parallel_2&quot;,39.83333333333334],PARAMETER[&quot;Latitude_Of_Origin&quot;,37.66666666666666],UNIT[&quot;Foot_US&quot;,0.3048006096012192],AUTHORITY[&quot;EPSG&quot;,2226]]</WKT><XOrigin>-115211800</XOrigin><YOrigin>-93821500</YOrigin><XYScale>36983428.057351544</XYScale><ZOrigin>-100000</ZOrigin><ZScale>10000</ZScale><MOrigin>-100000</MOrigin><MScale>10000</MScale><XYTolerance>0.0032808333333333331</XYTolerance><ZTolerance>0.001</ZTolerance><MTolerance>0.001</MTolerance><HighPrecision>true</HighPrecision><WKID>102642</WKID><LatestWKID>2226</LatestWKID></ProjectedCoordinateSystem> Project I:\Projects\Warren\LIMH_CALENVIRO\LIMH_2020\LIHM_2020.gdb\Cal_Environ_3_0 I:\Projects\Warren\LIMH_CALENVIRO\LIMH_2020\LIHM_2020.gdb\Cal_Environ_3_0_Project PROJCS['NAD_1983_StatePlane_California_II_FIPS_0402_Feet',GEOGCS['GCS_North_American_1983',DATUM['D_North_American_1983',SPHEROID['GRS_1980',6378137.0,298.257222101]],PRIMEM['Greenwich',0.0],UNIT['Degree',0.0174532925199433]],PROJECTION['Lambert_Conformal_Conic'],PARAMETER['False_Easting',6561666.666666666],PARAMETER['False_Northing',1640416.666666667],PARAMETER['Central_Meridian',-122.0],PARAMETER['Standard_Parallel_1',38.33333333333334],PARAMETER['Standard_Parallel_2',39.83333333333334],PARAMETER['Latitude_Of_Origin',37.66666666666666],UNIT['Foot_US',0.3048006096012192]] # PROJCS['NAD_1983_California_Teale_Albers',GEOGCS['GCS_North_American_1983',DATUM['D_North_American_1983',SPHEROID['GRS_1980',6378137.0,298.257222101]],PRIMEM['Greenwich',0.0],UNIT['Degree',0.0174532925199433]],PROJECTION['Albers'],PARAMETER['False_Easting',0.0],PARAMETER['False_Northing',-4000000.0],PARAMETER['Central_Meridian',-120.0],PARAMETER['Standard_Parallel_1',34.0],PARAMETER['Standard_Parallel_2',40.5],PARAMETER['Latitude_Of_Origin',0.0],UNIT['Meter',1.0]] NO_PRESERVE_SHAPE # NO_VERTICAL FeatureClassToFeatureClass I:\Projects\Warren\LIMH_CALENVIRO\LIMH_2020\LIHM_2020.gdb\Cal_Environ_3_0_Project I:\Projects\Warren\LIMH_CALENVIRO\LIMH_2020\Shapefile Cal_Environ_3_0.shp # "Tract_1 "Tract" true true false 8 Double 0 0 ,First,#,I:\Projects\Warren\LIMH_CALENVIRO\LIMH_2020\LIHM_2020.gdb\Cal_Environ_3_0_Project,Tract_1,-1,-1;Percentile "Percentile Range" true true false 255 Text 0 0 ,First,#,I:\Projects\Warren\LIMH_CALENVIRO\LIMH_2020\LIHM_2020.gdb\Cal_Environ_3_0_Project,Percentile_Range,-1,-1;Population "Population" true true false 4 Long 0 0 ,First,#,I:\Projects\Warren\LIMH_CALENVIRO\LIMH_2020\LIHM_2020.gdb\Cal_Environ_3_0_Project,Population,-1,-1;County "County" true true false 255 Text 0 0 ,First,#,I:\Projects\Warren\LIMH_CALENVIRO\LIMH_2020\LIHM_2020.gdb\Cal_Environ_3_0_Project,County,-1,-1;ZIP "ZIP" true true false 4 Long 0 0 ,First,#,I:\Projects\Warren\LIMH_CALENVIRO\LIMH_2020\LIHM_2020.gdb\Cal_Environ_3_0_Project,ZIP,-1,-1;City "City" true true false 255 Text 0 0 ,First,#,I:\Projects\Warren\LIMH_CALENVIRO\LIMH_2020\LIHM_2020.gdb\Cal_Environ_3_0_Project,City,-1,-1;CIscore "CIscore" true true false 8 Double 0 0 ,First,#,I:\Projects\Warren\LIMH_CALENVIRO\LIMH_2020\LIHM_2020.gdb\Cal_Environ_3_0_Project,CIscore,-1,-1;CIscoreP "CIscoreP" true true false 4 Long 0 0 ,First,#,I:\Projects\Warren\LIMH_CALENVIRO\LIMH_2020\LIHM_2020.gdb\Cal_Environ_3_0_Project,CIscoreP,-1,-1;Ozone "Ozone" true true false 8 Double 0 0 ,First,#,I:\Projects\Warren\LIMH_CALENVIRO\LIMH_2020\LIHM_2020.gdb\Cal_Environ_3_0_Project,Ozone,-1,-1;Ozone_Pctl "Ozone Pctl" true true false 4 Long 0 0 ,First,#,I:\Projects\Warren\LIMH_CALENVIRO\LIMH_2020\LIHM_2020.gdb\Cal_Environ_3_0_Project,Ozone_Pctl,-1,-1;PM2_5 "PM2.5" true true false 8 Double 0 0 ,First,#,I:\Projects\Warren\LIMH_CALENVIRO\LIMH_2020\LIHM_2020.gdb\Cal_Environ_3_0_Project,PM2_5,-1,-1;PM_2_5_Pct "PM 2.5 Pctl" true true false 4 Long 0 0 ,First,#,I:\Projects\Warren\LIMH_CALENVIRO\LIMH_2020\LIHM_2020.gdb\Cal_Environ_3_0_Project,PM_2_5_Pctl,-1,-1;Diesel_PM "Diesel PM" true true false 8 Double 0 0 ,First,#,I:\Projects\Warren\LIMH_CALENVIRO\LIMH_2020\LIHM_2020.gdb\Cal_Environ_3_0_Project,Diesel_PM,-1,-1;Diesel_PM_ "Diesel PM Pctl" true true false 4 Long 0 0 ,First,#,I:\Projects\Warren\LIMH_CALENVIRO\LIMH_2020\LIHM_2020.gdb\Cal_Environ_3_0_Project,Diesel_PM_Pctl,-1,-1;DrinkingWa "DrinkingWater" true true false 8 Double 0 0 ,First,#,I:\Projects\Warren\LIMH_CALENVIRO\LIMH_2020\LIHM_2020.gdb\Cal_Environ_3_0_Project,DrinkingWater,-1,-1;Drinking_1 "DrinkingWater Pctl" true true false 4 Long 0 0 ,First,#,I:\Projects\Warren\LIMH_CALENVIRO\LIMH_2020\LIHM_2020.gdb\Cal_Environ_3_0_Project,DrinkingWater_Pctl,-1,-1;Pesticides "Pesticides" true true false 8 Double 0 0 ,First,#,I:\Projects\Warren\LIMH_CALENVIRO\LIMH_2020\LIHM_2020.gdb\Cal_Environ_3_0_Project,Pesticides,-1,-1;Pesticid_1 "Pesticides Pctl" true true false 4 Long 0 0 ,First,#,I:\Projects\Warren\LIMH_CALENVIRO\LIMH_2020\LIHM_2020.gdb\Cal_Environ_3_0_Project,Pesticides_Pctl,-1,-1;Tox_Releas "Tox Releases" true true false 8 Double 0 0 ,First,#,I:\Projects\Warren\LIMH_CALENVIRO\LIMH_2020\LIHM_2020.gdb\Cal_Environ_3_0_Project,Tox_Releases,-1,-1;Tox_Rele_1 "Tox Releases Pctl" true true false 4 Long 0 0 ,First,#,I:\Projects\Warren\LIMH_CALENVIRO\LIMH_2020\LIHM_2020.gdb\Cal_Environ_3_0_Project,Tox_Releases_Pctl,-1,-1;Traffic "Traffic" true true false 8 Double 0 0 ,First,#,I:\Projects\Warren\LIMH_CALENVIRO\LIMH_2020\LIHM_2020.gdb\Cal_Environ_3_0_Project,Traffic,-1,-1;Traffic_Pc "Traffic Pctl" true true false 4 Long 0 0 ,First,#,I:\Projects\Warren\LIMH_CALENVIRO\LIMH_2020\LIHM_2020.gdb\Cal_Environ_3_0_Project,Traffic_Pctl,-1,-1;Cleanups "Cleanups" true true false 8 Double 0 0 ,First,#,I:\Projects\Warren\LIMH_CALENVIRO\LIMH_2020\LIHM_2020.gdb\Cal_Environ_3_0_Project,Cleanups,-1,-1;Cleanups_P "Cleanups Pctl" true true false 4 Long 0 0 ,First,#,I:\Projects\Warren\LIMH_CALENVIRO\LIMH_2020\LIHM_2020.gdb\Cal_Environ_3_0_Project,Cleanups_Pctl,-1,-1;Groundwate "GroundwaterThreats" true true false 8 Double 0 0 ,First,#,I:\Projects\Warren\LIMH_CALENVIRO\LIMH_2020\LIHM_2020.gdb\Cal_Environ_3_0_Project,GroundwaterThreats,-1,-1;GroundWa_1 "GroundWater Threats Pctl" true true false 4 Long 0 0 ,First,#,I:\Projects\Warren\LIMH_CALENVIRO\LIMH_2020\LIHM_2020.gdb\Cal_Environ_3_0_Project,GroundWater_Threats_Pctl,-1,-1;Haz_Waste "Haz Waste" true true false 8 Double 0 0 ,First,#,I:\Projects\Warren\LIMH_CALENVIRO\LIMH_2020\LIHM_2020.gdb\Cal_Environ_3_0_Project,Haz_Waste,-1,-1;Haz_Waste_ "Haz Waste Pctl" true true false 4 Long 0 0 ,First,#,I:\Projects\Warren\LIMH_CALENVIRO\LIMH_2020\LIHM_2020.gdb\Cal_Environ_3_0_Project,Haz_Waste_Pctl,-1,-1;Imp__Water "Imp. Water Bodies" true true false 4 Long 0 0 ,First,#,I:\Projects\Warren\LIMH_CALENVIRO\LIMH_2020\LIHM_2020.gdb\Cal_Environ_3_0_Project,Imp__Water_Bodies,-1,-1;Imp__Wat_1 "Imp. Water Bodies Pctl" true true false 4 Long 0 0 ,First,#,I:\Projects\Warren\LIMH_CALENVIRO\LIMH_2020\LIHM_2020.gdb\Cal_Environ_3_0_Project,Imp__Water_Bodies_Pctl,-1,-1;Solid_Wast "Solid Waste" true true false 8 Double 0 0 ,First,#,I:\Projects\Warren\LIMH_CALENVIRO\LIMH_2020\LIHM_2020.gdb\Cal_Environ_3_0_Project,Solid_Waste,-1,-1;Solid_Wa_1 "Solid Waste Pctl" true true false 4 Long 0 0 ,First,#,I:\Projects\Warren\LIMH_CALENVIRO\LIMH_2020\LIHM_2020.gdb\Cal_Environ_3_0_Project,Solid_Waste_Pctl,-1,-1;PollutionS "PollutionScore" true true false 8 Double 0 0 ,First,#,I:\Projects\Warren\LIMH_CALENVIRO\LIMH_2020\LIHM_2020.gdb\Cal_Environ_3_0_Project,PollutionScore,-1,-1;Pollution_ "Pollution Burden Pctl" true true false 4 Long 0 0 ,First,#,I:\Projects\Warren\LIMH_CALENVIRO\LIMH_2020\LIHM_2020.gdb\Cal_Environ_3_0_Project,Pollution_Burden_Pctl,-1,-1;Asthma "Asthma" true true false 8 Double 0 0 ,First,#,I:\Projects\Warren\LIMH_CALENVIRO\LIMH_2020\LIHM_2020.gdb\Cal_Environ_3_0_Project,Asthma,-1,-1;Asthma_Pct "Asthma Pctl" true true false 4 Long 0 0 ,First,#,I:\Projects\Warren\LIMH_CALENVIRO\LIMH_2020\LIHM_2020.gdb\Cal_Environ_3_0_Project,Asthma_Pctl,-1,-1;Low_Birth_ "Low Birth Weight" true true false 8 Double 0 0 ,First,#,I:\Projects\Warren\LIMH_CALENVIRO\LIMH_2020\LIHM_2020.gdb\Cal_Environ_3_0_Project,Low_Birth_Weight,-1,-1;Low_Birth1 "Low Birth Weight Pctl" true true false 4 Long 0 0 ,First,#,I:\Projects\Warren\LIMH_CALENVIRO\LIMH_2020\LIHM_2020.gdb\Cal_Environ_3_0_Project,Low_Birth_Weight_Pctl,-1,-1;Cardiovasc "Cardiovascular" true true false 8 Double 0 0 ,First,#,I:\Projects\Warren\LIMH_CALENVIRO\LIMH_2020\LIHM_2020.gdb\Cal_Environ_3_0_Project,Cardiovascular,-1,-1;Cardiova_1 "Cardiovascular Pctl" true true false 4 Long 0 0 ,First,#,I:\Projects\Warren\LIMH_CALENVIRO\LIMH_2020\LIHM_2020.gdb\Cal_Environ_3_0_Project,Cardiovascular_Pctl,-1,-1;Education "Education" true true false 8 Double 0 0 ,First,#,I:\Projects\Warren\LIMH_CALENVIRO\LIMH_2020\LIHM_2020.gdb\Cal_Environ_3_0_Project,Education,-1,-1;Education_ "Education Pctl" true true false 4 Long 0 0 ,First,#,I:\Projects\Warren\LIMH_CALENVIRO\LIMH_2020\LIHM_2020.gdb\Cal_Environ_3_0_Project,Education_Pctl,-1,-1;Linguistic "Linguistic Isolation" true true false 8 Double 0 0 ,First,#,I:\Projects\Warren\LIMH_CALENVIRO\LIMH_2020\LIHM_2020.gdb\Cal_Environ_3_0_Project,Linguistic_Isolation,-1,-1;Linguist_1 "Linguistic Isolation Pctl" true true false 4 Long 0 0 ,First,#,I:\Projects\Warren\LIMH_CALENVIRO\LIMH_2020\LIHM_2020.gdb\Cal_Environ_3_0_Project,Linguistic_Isolation_Pctl,-1,-1;Poverty "Poverty" true true false 8 Double 0 0 ,First,#,I:\Projects\Warren\LIMH_CALENVIRO\LIMH_2020\LIHM_2020.gdb\Cal_Environ_3_0_Project,Poverty,-1,-1;Poverty_Pc "Poverty Pctl" true true false 4 Long 0 0 ,First,#,I:\Projects\Warren\LIMH_CALENVIRO\LIMH_2020\LIHM_2020.gdb\Cal_Environ_3_0_Project,Poverty_Pctl,-1,-1;Unemployme "Unemployment" true true false 8 Double 0 0 ,First,#,I:\Projects\Warren\LIMH_CALENVIRO\LIMH_2020\LIHM_2020.gdb\Cal_Environ_3_0_Project,Unemployment,-1,-1;Unemploy_1 "Unemployment Pctl" true true false 4 Long 0 0 ,First,#,I:\Projects\Warren\LIMH_CALENVIRO\LIMH_2020\LIHM_2020.gdb\Cal_Environ_3_0_Project,Unemployment_Pctl,-1,-1;Housing_Bu "Housing Burden" true true false 8 Double 0 0 ,First,#,I:\Projects\Warren\LIMH_CALENVIRO\LIMH_2020\LIHM_2020.gdb\Cal_Environ_3_0_Project,Housing_Burden,-1,-1;Housing__1 "Housing Burden Pctl" true true false 4 Long 0 0 ,First,#,I:\Projects\Warren\LIMH_CALENVIRO\LIMH_2020\LIHM_2020.gdb\Cal_Environ_3_0_Project,Housing_Burden_Pctl,-1,-1;PopCharSco "PopCharScore" true true false 8 Double 0 0 ,First,#,I:\Projects\Warren\LIMH_CALENVIRO\LIMH_2020\LIHM_2020.gdb\Cal_Environ_3_0_Project,PopCharScore,-1,-1;Pop__Chara "Pop. Characteristics Pctl" true true false 4 Long 0 0 ,First,#,I:\Projects\Warren\LIMH_CALENVIRO\LIMH_2020\LIHM_2020.gdb\Cal_Environ_3_0_Project,Pop__Characteristics_Pctl,-1,-1;Children__ "Children < 10 (%)" true true false 8 Double 0 0 ,First,#,I:\Projects\Warren\LIMH_CALENVIRO\LIMH_2020\LIHM_2020.gdb\Cal_Environ_3_0_Project,Children___10____,-1,-1;Pop_11_64_ "Pop 11-64 years (%)" true true false 8 Double 0 0 ,First,#,I:\Projects\Warren\LIMH_CALENVIRO\LIMH_2020\LIHM_2020.gdb\Cal_Environ_3_0_Project,Pop_11_64_years____,-1,-1;Elderly___ "Elderly > 65 (%)" true true false 8 Double 0 0 ,First,#,I:\Projects\Warren\LIMH_CALENVIRO\LIMH_2020\LIHM_2020.gdb\Cal_Environ_3_0_Project,Elderly___65____,-1,-1;Hispanic__ "Hispanic (%)" true true false 255 Text 0 0 ,First,#,I:\Projects\Warren\LIMH_CALENVIRO\LIMH_2020\LIHM_2020.gdb\Cal_Environ_3_0_Project,Hispanic____,-1,-1;White____ "White (%)" true true false 255 Text 0 0 ,First,#,I:\Projects\Warren\LIMH_CALENVIRO\LIMH_2020\LIHM_2020.gdb\Cal_Environ_3_0_Project,White____,-1,-1;African_Am "African American (%)" true true false 255 Text 0 0 ,First,#,I:\Projects\Warren\LIMH_CALENVIRO\LIMH_2020\LIHM_2020.gdb\Cal_Environ_3_0_Project,African_American____,-1,-1;Native_Ame "Native American (%)" true true false 255 Text 0 0 ,First,#,I:\Projects\Warren\LIMH_CALENVIRO\LIMH_2020\LIHM_2020.gdb\Cal_Environ_3_0_Project,Native_American____,-1,-1;Asian_Amer "Asian American (%)" true true false 255 Text 0 0 ,First,#,I:\Projects\Warren\LIMH_CALENVIRO\LIMH_2020\LIHM_2020.gdb\Cal_Environ_3_0_Project,Asian_American____,-1,-1;Other____ "Other (%)" true true false 255 Text 0 0 ,First,#,I:\Projects\Warren\LIMH_CALENVIRO\LIMH_2020\LIHM_2020.gdb\Cal_Environ_3_0_Project,Other____,-1,-1;Shape_Leng "Shape_Leng" false true true 8 Double 0 0 ,First,#,I:\Projects\Warren\LIMH_CALENVIRO\LIMH_2020\LIHM_2020.gdb\Cal_Environ_3_0_Project,Shape_Length,-1,-1;Shape_Area "Shape_Area" false true true 8 Double 0 0 ,First,#,I:\Projects\Warren\LIMH_CALENVIRO\LIMH_2020\LIHM_2020.gdb\Cal_Environ_3_0_Project,Shape_Area,-1,-1" # 20180622 08492700 20180622 08492700 625000 5000 FGDC Microsoft Windows 7 Version 6.1 (Build 7601) Service Pack 1; Esri ArcGIS 10.5.1.7333 Cal_Environ_3_0 Walker Wieland OEHHA Research Scientist Walker.Wieland@oehha.ca.gov 1 -124.506026 -113.502228 42.068501 32.423801 <DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>The Office of Environmental Health Hazard Assessment (OEHHA), on behalf of the California Environmental Protection Agency (CalEPA), announces the availability of the Communities Environmental Health Screening Tool: CalEnviroScreen Version 3.0 (CalEnviroScreen 3.0). CalEnviroScreen is a screening methodology that can be used to help identify California communities that are disproportionately burdened by multiple sources of pollution. The 3.0 report and supporting documents are available at: http://oehha.ca.gov/calenviroscreen/report/calenviroscreen-30</SPAN></P></DIV></DIV></DIV> OEHHA, CalEPA CalEnviroScreen 2.0 OEHHA CalEPA Environmental Justice <DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>Review the CalEnviroScreen 3.0 draft report at: </SPAN><A href="http://oehha.ca.gov/calenviroscreen/report/calenviroscreen-30"><SPAN><SPAN>http://oehha.ca.gov/calenviroscreen/report/calenviroscreen-30 </SPAN></SPAN></A><SPAN><SPAN>for guidance on CalEnviroScreen use. </SPAN></SPAN></P><P><SPAN /></P></DIV></DIV></DIV> Walker Wieland OEHHA Research Scientist Walker.Wieland@oehha.ca.gov Walker Wieland Cal Environ 3.0 full data set Shapefile 0.000 dataset EPSG 5.3(9.0.0) 0 Simple FALSE 0 FALSE FALSE Cal_Environ_3_0 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. Tract_1 Tract_1 Double 19 0 0 Census Tract ID from 2010 Census Percentile Percentile String 254 0 0 Population Population Integer 10 10 0 2010 population in census tracts County County String 254 0 0 California county that the census tract falls within ZIP ZIP Integer 10 10 0 Postal ZIP Code that the census tract falls within City City String 254 0 0 City or nearby city the the census tract falls within CIscore CIscore Double 19 0 0 CalEnviroScreen Score, Pollution Score multiplied by Population Characteristics Score CIscoreP CIscoreP Integer 10 10 0 Percentile of the CalEnviroScreen score Ozone Ozone Double 19 0 0 Amount of daily maximum 8 hour Ozone concentration Ozone_Pctl Ozone_Pctl Integer 10 10 0 Ozone percentile PM2_5 PM2_5 Double 19 0 0 Annual mean PM 2.5 concentrations PM_2_5_Pct PM_2_5_Pct Integer 10 10 0 Diesel_PM Diesel_PM Double 19 0 0 Diesel PM emissions from on-road and non-road sources Diesel_PM_ Diesel_PM_ Integer 10 10 0 DrinkingWa DrinkingWa Double 19 0 0 Drinking_1 Drinking_1 Integer 10 10 0 Pesticides Pesticides Double 19 0 0 Total pounds of selected active pesticide ingredients (filtered for hazard and volatility) used in production-agriculture per square mile in the census tract Pesticid_1 Pesticid_1 Integer 10 10 0 Tox_Releas Tox_Releas Double 19 0 0 Tox_Rele_1 Tox_Rele_1 Integer 10 10 0 Traffic Traffic Double 19 0 0 Traffic density, in vehicle-kilometers per hour per road length, within 150 meters of the census tract boundary Traffic_Pc Traffic_Pc Integer 10 10 0 Cleanups Cleanups Double 19 0 0 Cleanup sites, sum of weighted EnviroStor cleanup sites within buffered distances to populated blocks of census tracts Cleanups_P Cleanups_P Integer 10 10 0 Groundwate Groundwate Double 19 0 0 GroundWa_1 GroundWa_1 Integer 10 10 0 Haz_Waste Haz_Waste Double 19 0 0 Sum of weighted hazardous waste facilities and large quantity generators within buffered distances to populated blocks of census tracts Haz_Waste_ Haz_Waste_ Integer 10 10 0 Imp__Water Imp__Water Integer 10 10 0 Imp__Wat_1 Imp__Wat_1 Integer 10 10 0 Solid_Wast Solid_Wast Double 19 0 0 Solid_Wa_1 Solid_Wa_1 Integer 10 10 0 PollutionS PollutionS Double 19 0 0 Pollution_ Pollution_ Integer 10 10 0 Asthma Asthma Double 19 0 0 Age-adjusted rate of emergency department visits for asthma Asthma_Pct Asthma_Pct Integer 10 10 0 Low_Birth_ Low_Birth_ Double 19 0 0 Low_Birth1 Low_Birth1 Integer 10 10 0 Cardiovasc Cardiovasc Double 19 0 0 Cardiova_1 Cardiova_1 Integer 10 10 0 Education Education Double 19 0 0 Percent of population over 25 with less than a high school education Education_ Education_ Integer 10 10 0 Linguistic Linguistic Double 19 0 0 Linguist_1 Linguist_1 Integer 10 10 0 Poverty Poverty Double 19 0 0 Percent of population living below two times the federal poverty level Poverty_Pc Poverty_Pc Integer 10 10 0 Unemployme Unemployme Double 19 0 0 Unemploy_1 Unemploy_1 Integer 10 10 0 Housing_Bu Housing_Bu Double 19 0 0 Housing__1 Housing__1 Integer 10 10 0 PopCharSco PopCharSco Double 19 0 0 Pop__Chara Pop__Chara Integer 10 10 0 Children__ Children__ Double 19 0 0 Pop_11_64_ Pop_11_64_ Double 19 0 0 Elderly___ Elderly___ Double 19 0 0 Hispanic__ Hispanic__ String 254 0 0 White____ White____ String 254 0 0 African_Am African_Am String 254 0 0 Native_Ame Native_Ame String 254 0 0 Asian_Amer Asian_Amer String 254 0 0 Other____ Other____ String 254 0 0 Shape_Leng Shape_Leng Double 19 0 0 Shape_Area Shape_Area Double 19 0 0 Area of feature in internal units squared. Esri Positive real numbers that are automatically generated. 20180622 /9j/4AAQSkZJRgABAQEAlgCWAAD/2wBDAAMCAgMCAgMDAwMEAwMEBQgFBQQEBQoHBwYIDAoMDAsK CwsNDhIQDQ4RDgsLEBYQERMUFRUVDA8XGBYUGBIUFRT/2wBDAQMEBAUEBQkFBQkUDQsNFBQUFBQU FBQUFBQUFBQUFBQUFBQUFBQUFBQUFBQUFBQUFBQUFBQUFBQUFBQUFBQUFBT/wAARCAL9Ax0DASIA AhEBAxEB/8QAHwAAAQUBAQEBAQEAAAAAAAAAAAECAwQFBgcICQoL/8QAtRAAAgEDAwIEAwUFBAQA AAF9AQIDAAQRBRIhMUEGE1FhByJxFDKBkaEII0KxwRVS0fAkM2JyggkKFhcYGRolJicoKSo0NTY3 ODk6Q0RFRkdISUpTVFVWV1hZWmNkZWZnaGlqc3R1dnd4eXqDhIWGh4iJipKTlJWWl5iZmqKjpKWm p6ipqrKztLW2t7i5usLDxMXGx8jJytLT1NXW19jZ2uHi4+Tl5ufo6erx8vP09fb3+Pn6/8QAHwEA AwEBAQEBAQEBAQAAAAAAAAECAwQFBgcICQoL/8QAtREAAgECBAQDBAcFBAQAAQJ3AAECAxEEBSEx BhJBUQdhcRMiMoEIFEKRobHBCSMzUvAVYnLRChYkNOEl8RcYGRomJygpKjU2Nzg5OkNERUZHSElK U1RVVldYWVpjZGVmZ2hpanN0dXZ3eHl6goOEhYaHiImKkpOUlZaXmJmaoqOkpaanqKmqsrO0tba3 uLm6wsPExcbHyMnK0tPU1dbX2Nna4uPk5ebn6Onq8vP09fb3+Pn6/9oADAMBAAIRAxEAPwD9U6KK KACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAoooo AKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAoopOaAFopMijdQAt FJ9KWgAopMijdQAtFJkUZFAC0UUUAFFFFABRSUtABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRR QAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFA BRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAF FFFABRRRQAUUUUAFFFFABRRSN0oAOlJupMiuZ8bfEfwt8OtNN/4m1/T9CtMHD31wsZbHUKpOWPsA aBOSirs6ikJFfGXxI/4Kb+AfDnm2/hTStQ8WXS5UTkfZbXPruYFj+C/jXzJ4+/4KNfFrxc0sekT6 f4RtG4C6fbiWbGP+ekmf0AraNKTPPqY+jT639D9Ybq8hs4TLPNHBEOryMFUfia8u8W/tUfCbwPI0 erePtFSdfvQW1wLmQexWLcQfrX43eK/iP4s8dTNL4h8S6prbscn7deSSL+RJFc4Mdhit44fS7Z50 82/kifqt4i/4KYfCXScrp8Wua44z/wAetkI1P4yMteb61/wVas13ro/w7uJf7kl/qix4+qrG3/oV fnjRWioxOOWZVpbOx9r6h/wVO8dzKws/CGgWwPRppJpCv/jwBrm7r/gpl8XJmzDb+H7cZztFkzfz evkyiq9lDsc7xtd/aZ9SH/gpL8amYkXWgqOy/wBl/wD2dPh/4KUfGWMN5k2gy56f8S3GP/H6+WKK PZQ7E/XMR/Oz68sP+CnXxVtWU3Gl+Hb0cZ3W0iZ9ej11ek/8FVfE8cinU/Amk3Kd1tLyWEkexYPj 8q+GKKPZQ7Fxx2Ij9o/SXQf+Cqnhe4wNZ8D6xp4/vWd1Fcgf99bD+len+Gf+Ch3wX8RNGk+u3mhy MMkanYyIoPoWUMK/Iuis3Qj0OmOZ11vZn7seEfjJ4G8eqreHfF2i6uzDd5drextJj3TO4fiK7Ne3 ev59VYxsHUlXXkMvBHuD2r0rwP8AtJ/E/wCHUiHQfG2rW0SnP2aec3MJ+qSbl/SoeHfRnbDNI/bR +4I+lDV+Zfw9/wCConjHSTFB4w8Oaf4ggAw1zYMbSc++DuQnv0FfUfw1/b4+EfxEMUE2tv4W1KTA +za8ghXd7SglCM+rD8K55U5R3R6VPGUam0j6ToqpZ31tqNpFc2s8VzbyLuSaFw6MOxBHBFWV61md o6iiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooA KKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAo oooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigBOlGRSH614h8dv2uPAHwFikt9V1D+1 Nex+70XTSJLgntvOdsY92IPoDTSctEROpGmryZ7czHbmvDPjN+2R8Nfgr59rqWsDVtci4/sjScTz hvRznbH/AMCIPtX55fHL9uj4jfGJrixtbw+EvDkmVGnaXIVkkX/prNwzE+g2j29fnQ8sSeSep9a6 o4f+Y8OvmiXu0lfzPrb4uf8ABSL4ieN2ns/CsMHgnS24WSACe9Ye8jDC/wDAVB96+Wdc8Qan4o1O XUdZ1G61W/lOXubyZpZG/wCBMSfw6Vn0V1qEY7I8OpXq1dZyD8c0UUVRzhRRRQAUUUUAFFFFABRR RQAUUUUAFFFFABRRRQAUEZoooGdt8N/jV45+Ed2s/hLxLfaOoYM1tHJut5P96JsofxFfZXwh/wCC oDRvBZfEnw9kcKdX0Vf/AB54WP8A6C30Havz/penTis5U4y3R2UcVVo/Cz92fhz8XvCHxa0kaj4T 1+z1qAD51gkxLH7PGcMp+oFdirbsV+A/h3xNq3g/VoNV0PU7vSNSgOY7qylMci/iO3t0PevtT4Ff 8FMtX0b7PpXxNsTq9pwo1vTowtwg9ZIvuv8AVcH2NckqLWqPcoZlCfu1FZn6T0VyXw/+JXhr4paH FrHhfXLXWbBxy9u3zIf7rqfmRvYgGurzXNqtz2VJSV0OooooGFFFFABRRRQAUUUUAFFFFABRRRQA UUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABR RRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUnNNZiv agBeK5bx98RfDvwz8NXGueJ9WttI02Ecy3DffP8AdRerseygE143+0v+2d4W/Z/tZdNgMfiDxkyZ j0iCT5YMjhp3Gdg77fvHI4xzX5b/ABZ+NHi742+JH1nxZq0l9MMiC2X5be2X+7HH0Ue/U9ya3hSc tTzMVjoUNI6s+lP2iP8Agot4h8cfatE+HaTeGNDbdG2qNxf3I5GVIOIQRjplvdTwPji4uJru4knn leeeRi7yysXZmPUknkn61HRXdGMY7I+Yq16laV5u4UUUVZzBRRRQAUUUUAFFHGQAck9B3Ndx4S+C Hj7x0qPofhLVr2FulwbZo4v++3wv60FKLexw9FfSnhz9gT4lawqPqMukaEjDO25ujI/02xq3P416 Tov/AATgtxsbWfHEsg/iTT7ALj2DO5z+VOzLVOR8RUV+iWl/8E+vhzaj/TNQ13Uf+3lIs/8AfK10 Fn+w78JbVgX0W9uuvE+oSHP/AHzinZl+xkfmaeKBzX6iw/sbfCCFSG8HrLk5y99c/wBJBUc37GPw gmYkeFTFnoI7+44+mZDTsHsZH5fUfhxX6U3X7CPwnuR8tlqtucY/c6g39Qa5bVv+Cdvgq43Gx8Ra 5Yt/ArCKUD81BP50uVh7GR+f9FfYmuf8E5dXiy2i+M7G6Of9Xf2bw4/4ErP/ACrzHxN+xT8V/Dqu 8WiW+swrnDaZdI5I9drbTSsyHTl2PCaK2PEXg3XvCNwYNc0TUdIlH8N7bPF+PzDmsf8AWkZhRRRQ K4UUUUAFH60UUAdN8P8A4leJ/hX4gi1rwprVzo2oJjc8DfJKv92RDw6+xzX6L/s3/wDBQ/w/4/a1 0H4gJD4Z8QSbYk1JSRY3TdBkn/VMT2Py+46V+YVH15HpWc6amvM7sPi6mHe912P6BYLhJo1aNxIj AMGU5BB6EHuKn7Zr8hf2af22/FvwLmttJ1R5vE3g4EKbGeQma0HrA5zgdTsPyntiv1F+F3xb8L/G PwvBr3hXVItSsnAEijiW3fGTHKnVGHofqMivOnTcWfUYfFwxC03O3opobOadUHaFFFFABRRRQAUU UUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRR QAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFU7 /ULbTbSe7u7iO2toY2llmlYKiIBksxPAAHegCaRgsbFm2gck56Cvgr9rb/goCmkyXng/4X3iz36l or3xEgDRwnBBS3/vN6v0H8OTyPNv2w/25rv4kS3ngzwBdyWPhTJivNUjDJLqXqq9CkXUerd+OD8a +g9K66VLrI+exmP3p0n8ya8u59Qu5rq6mkubmZzJLNM5d5GPVmJ5JNQ0UV2+R895hRRRQIKKKXB4 H8R4296AE96D0/SvffhD+xl46+Jyw31/EPCuiP8AMLvUUImlX1ji+8R7nAr7P+Fn7Jnw8+FoiuIN L/tzV0wf7R1YCVgw7omNqc+gJ96aRtGlKR8B/Df9mn4h/FJY59I0CaDTpOmoagfs8GPUFuWH+6Cf Y19PeAf+CdujWQjn8Y+IrjVJerWelqIIvoXbLH8MfhX2GF6Y6DgUu2rsdMaMY7nB+C/gb4B+HyKN C8K6daSr0uJIvOm69fMfLZ49fyru+W96ftpQopmqSjsR/hRgnuak2il2j1ptlEO00bD61LtFG0Ug Itp+tG32qbaPWjaPWgCHb7UFd1S7RSbaAISvvSbc9qlZeaTbVXAq3tjb6hbtb3cEV1A33op0Dofq CMV4/wCOP2Q/hf443ySeHl0e7Y5N1ozm3bPuv3D/AN85969pKik20rIhxT3Pgn4hf8E9df0vzbjw drttrUAyRZ6gPs8/0DDKMfrt+tfM/jL4e+Jfh7ffY/EmiXmjz5wv2mIhHP8Asv8Adb8DX7Gbcdqo 61oun+ILCSx1Wxt9SspRh7e6iEiN9QalxMZUl0Pxgor9BPip+wT4X8TLLe+DbtvC9+2W+xy7prRz 6YPzJ+BI9q+NPid8FvGHwhvvI8R6TJbQM2Ir6H95bTD1WQcZ9jg+1RY5ZRcThqKFOelFIgKKKKAC u2+Evxi8VfBPxXFr3hXUms7kECe3fLQXSZ5SVP4h+o7YNcTRR8WjLjJwfNB2Z+yn7Nf7WHhr9onR Qlqy6T4pt03XmjTyAuo/56RH+OP36jocda94B4FfgL4b8Sap4P12z1nRL+fTNUs5BLBdW7lHRvYj 16EdCK/VL9kT9s3TvjvZw+HfELQ6Z46t4/mi+5FqCqOZIfRu7J2xkcdPPqUuV3R9Rg8cqqUZ7n1V RTVbNOrnPYCiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACi iigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKK KACiiigAooqGSRFjZmYBQDk5xj8aAIL6+t9Ns5ru7njtraFGklmmcKiKBksSeAB61+WP7Zv7Z138 Y9SuvCPhG5e08CwSeXLPGSraqyn7zdxECBtXv1PYDV/bl/bEk+JmoXPgHwdfMvhG2fZfX0Lf8hKR T90HvCP/AB4jPTFfG/v0rspUurPm8djub91S+bDH+RRRRXYeAFFFFABRT4o3mkSKONpJHYKqoCSx JxgAck/SvsP9nn9hmfWFtfEPxGSSzsmAlh0BSVmlGMgzMPuD/YHPqR0qkXGLlseBfB/9n/xf8a9Q 2aFY+VpsbBbjVrrKW0PqN38Tf7K5P0r76+C/7Jfgv4QrBetbjxD4hQZ/tO/QERt/0yj6J9eT717J o+jWWg6bb6fptnBp9jbLshtrWMJGi+wHTp9eTVxU/Cqsd0aUYictnnrTlWl6U7k0zUSl/CjbTwvS goj2ml21Jt9qcq+1AWIdtO2+1Sbfal27qAsRbTRtNSbPejZ70FWI9tJtqbbtpNvtQKxDtpNpqcr7 U3b7UCsR/hSVJtpm2gBjLmm7alxjmkoJIivFMZfSrAjLkL6024028XJi8tvx5/WolUjDc3p4edbW JBtqlquk2et6fPYajaQ31lOpSW2uIxJG6nqCp4NPuI7yE/vEdR9P8Krs7t1Zj9TWP1mPY6f7Pk92 fJfxs/YMsdS+0at8O5l0675dtFun/cSe0TnlD7Nke4r4s8S+GNW8H6xPpWtadcaZqEBxJb3KFWHu PUe4yPev2Erjvif8I/DHxd0M6b4j09bjaMwXceFnt2/vI/UfToe4rH6xrsZzyu692Wp+TFFew/Hf 9mfxH8E7p7tg2r+GXfEOqwp9zPRZl/gb36H17V49XSmpao8KpTlSfLNWYUUUUzIKsafqF1pF9Be2 NzLaXlvIJYZ4XKPG45DAjkEHvVeijyYa9D9VP2Lf2yYPjNYw+EvFcsdr43tYvklxtTU41GS6joJB /EvfqO4H1urFhzxX8/2l6peaHqVrqOn3U1jf2sizW9zbuUkidTkMpHQg1+s37G/7Wtp8fPDZ0XWp IrTxzpsX+lQqdq3kY4+0Rj8ty9ic9Dxw1aXLqj6nA432i9nU+I+nqKTI45pa5T2gooooAKKKKACi iigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKK KACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACk+tLSN0oAa7BcZr4D/wCCgH7W zaat38LfCF75d2w2a7qED8xIf+XVSO5BG8joPl7mva/20/2nIvgF4D+xaVOjeM9YRo7CPqbaPo9w w/2f4QereoBr8irq6mvrqa5uZXnuJnMkssjEs7E5LMT1JJPJ9a6aVPm1Z4mYYv2a9nDdkVFFFd58 wFFFFAgrU8M+F9V8aa5aaNodjNqWp3b7IbeBcsx9fYDrk8AcmrXgfwPrXxG8TWWgaBZPfaldNhEH CqO7sf4VAySTX6c/s/8A7Omh/AnQSsAXUfEN0g+3aq6ct6xx/wB1Ae3U457CqSuawpuWpyP7Nv7I +kfCCG21zXBFrPjBhuEuN0FiSPuxZ6sM43nn0x3+ilUUKvrT6vY9CMVETaKXGaUDmn7aCkhqrmn+ Waco207bRqXYaqU7bTlX0pdtSVYaq0U9VNL+VK40hm2jbUm2l20XKsQ0786k2+1G32ouFiLaaNtS 7fak2UXCxHtpGH1qTbQ2fSi5LRFtpu2pdtBzjpRcViBlz0prJjrU9NZaa3JswtVzMv0zWhVWzTaz H8KtV5ld3me7hY8tMQ5/CsPVtJ2ZmgHynlkHb3FbtHT6VznYcTRWnrlitvIskYwjk8ds1mVZBFeW dvqNpNa3cEd1azIUlhmQOjqeoIPBBr4b/aU/Y5m8Lrc+J/AlvLdaMMyXWjrl5bUdS0XUsg54+8vb I6fdNFXGcoPQ5q+Hp4iPLNan4z7s8jp9c0V9t/tTfskrqS3fjHwLY7b/ACZdQ0e3XibjJlhUdG5J Kd8kjnOfiVlKsQeGBII7jHr6f/rrvjJS2Pkq9CeHlysSiiirOUK2vBvjDV/APijTvEOg3smn6tp8 omt7iP8AhI6gjupGQQeCCR3rFoosmrMcW4u6P2o/Zn/aH0n9oj4fwavbFLXWrXbBqumg8282Oq+q NyVP4dQa9lr8O/2f/jhrPwA+I1l4m0stNbcQ6jY5wt3bkgsh7BhjKnsQO2a/aLwH420n4i+E9L8S aFdLeaTqMInglHBweqsOzA5BHYgivNqU+V3PscHivrELPdHR0UUVieiFFFFABRRRQAUUUUAFFFFA BRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAF FFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFACGuU+JnxE0f4V+BdX8Va5cCDTtNhMr4PzSN0WNR3 ZmIUD1NdU2Apr8sP+Chn7RR+JHjoeBNGut/hvw9KRdNGflub0ZDfVYxlR/tbj6Y0px53Y5MTXjQp uT3PnT4vfFTWfjN8QNW8Wa3ITdXsn7qAMSltCuQkSeyj8ySe9cbRRXppW0R8VKTm3KXUKKKKZAVs eEfCereOfEljoWiWb32p3snlxQoPzYnso6kngCs20s5768gtbaGS4up5FiihiBLu5OAoA7kkV+mX 7Kn7ONt8FfDI1LU4o5vGGpRA3U3BFrGeRAh/Ise5HtVWNadPmep0f7PX7PukfAnwsttCI73xBdIp 1HU8cyN12JnlY1PQd+p9K9aVcChQPTFOAqz0UugAUtFSKuOtBQqp+dOVR34o208CpLSE207b+NCi pFUUFpDVWneXS4xTgKgdhoX8acBTgtLtFTcrlGY96NpqTbS7adx2Itpo2mpdtLtpXCxDtNG0+tS7 aTbTuFiPbTWWptvtTWXNFxcpF5dNK8VNjFMpk2Itv4U0rj6VOVFCx7jz0pOajuXCm6jshYF2x59T UtFFeVJ3bZ70I8sUgoooqSyhrUPm6e57xncK5iu0dBIjKejDb+dcbNGYZXjPVTg00JjaKKKokUHB GDivj79rb9llL2C98c+DrMC7UGbVNLgXiQYy00aj+IfxKOoyw5zn7AryT9o/4s3Hwx8HxxaY4j1v U2aG3kxnyVAy8mO5GQB7tnnFVGXK7mFajGvHlkfmF+OaK6zxZovmCXU4PvZ3XEagDGf4/pnr9c+t cnXoxkpK6Pjq9GVCo4SCiiiqOcK+vf8Agn/+0w3wz8ZL4E1+72eGddn/ANGkkb5LO8bgHPZZMBT6 HaeOa+QqUcEHOCOQR1rOcVJWOijWlQmpxP6CVPy0/wB6+Yv2GP2jP+F2fDNdL1e583xZoCpb3hY/ Ncw4xHP7k42t/tD3r6c75rzZJxdmfbU6iqwU11HUUUVJqFFFFABRRRQAUUUUAFFFFABRRRQAUUUU AFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQA UUUUAFFFFABRRRQAUUVG0ix5LMAAMkmgDwT9sr4+L8CfhDe3VnKF8SatusNKQfeVyPnm+iLz/vbR 3r8cZJGmkeSRmkkdizOxySSckk9yTXu/7Z3xxb43/GjUri0n83w/o5bTtNAPysit88o/33BOfQL6 V4PXpUY8sddz4/HYj21Wy+FBRRRWx5gUUV2vwz8Dv4mvLvVbqHzNC0YxTXu4HEm5wFhB9W5/BWpb asaXMfVf7DP7Oot4YviR4itf30gI0W3lH3VPDXBB7novtk+lfair61U0drWTS7N7JEjs2gjMCRjC rHtG0D2AxV5a21PThHlVg20tKFJwBT1UdM8+lGpoCrtqQc0nA4OAfQ0/hVyeABk5449al6bliqvN O25rjtf+I9rpcohsUW/lB+dw2EX2z3q74R8cQ+JGkgliFrdKu4LuyrDvgn+tcSxVJz5FK7GpJs6d V46U5VNRtdW8ccjtPGEiBZ23jCj3rgNa+K+yRo9Lt1ZFOPPmzz7hR/WnVxNOmryZTaW56Ltp22vJ Lf4raxHIDLHbTJ3XyyufxBr0Lwr4stPFFuzRfubhP9ZA5BI9we4rGli6VZ2ixxlGRt05V3U5Yw3T n6U7btrsWuxuR7DS+Wak2+vH1pk80drC8szqkSDLMxwAB3pN8quxWE8ujy64u6+Lmk29wY4YLm6j BwZVAA/AE810+g6/ZeI7P7TZSsy5wyMMMh9xXPHEQqPli9Rc0Xoi75dHlmpdvvRtre47ELKcU3b6 1NtpGSmhkG2k2ipWjqtI3zkelTKfLEunS9pKwu7ml8yo8n0o3GvPlJyd2evCCpq0STzKPMqPcaNx qSyTzKPMqPcaNxoAk8yud1yHy70sBxIM1vbjWbrse+3R/wC62PzpoTMKiiiqJCvj/wDbUab/AITf w+HJ8j+z28v0z5h3fj0r2r48fHCH4R6fawWtul9rl6GaGGRiI4kHBkbHXk4A7818e/EH4r+Ivie9 q2vTwTfZSxgEMCx7A2MjIGSOBwc0AcirFecAjp83Q+oPsRXDeJNE/sm6EkQY2k3MZyDtPdT9P1H0 rt6jurSLULOS2n/1co4buhH3WHuDWlOfIzjxmFWIhp8SPM6KnvLSSwupreXiWNtrY6exHsev41BX o+Z8Y7xeoUUUUCPSv2efjLffAj4q6R4qtiz2cbfZ9Qtl6XFq/wDrF+oA3D3QV+2Oi63Z+IdJsdT0 +dbqxvYEuLeaMgq6MoZSPqDX4CV+lf8AwTP+OP8AwkXhC/8Ahzqlzu1DQ/8ASdO8w/M9o5+aMf8A XNz+Tj0rlrx05ke7lmIcX7KWz2PuIGlpqkHpTq4T6YKKKKACiiigAooooAKKKKACiiigAooooAKK KKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooo oAKKKKACiiigBrd6+cf26vjOfhD8DdQjspzFr3iAnS7HafmQMCZZB/upkZ9WWvo1skcV+Rf/AAUA +Lx+Jnx4vNLtZvN0fwyh02AKflabOZ3+u75fogrWlHmkefjq3saLa3eh80AAAAdKKKK9M+NCiiig RPY2U+pX1vZ2sTT3NxIsUUUYyzuxAVQPUk4r7P8AiV4Ct/gf8GfCHgWNlbVr6VtV1eZDkyTBQuCf 7qlio/3T61x37BHwttvFXxEuvFOohHg0GPdaQtyZLhuA+PRBk/Uj0rqf2pfEQ1/4uX0CPui02KOz VewYDc36sayqSXIdEUowb7n0/wDs6eJP+Em+EGgys26W1Q2UnrmM4H/ju2vS1X1/SvmH9ivxF5lv 4j0B2yUdL6Jc9idj/wAk/OvQW+MM1z4u8UaJalcWcscdvN6Kq7ZCPffU+3jTpKczqjJcquesahfR 6Tp893L92Nd2O59B9elfPWj/ABo1O4+LWsBHi8iaFbeOFlyoMWTx75L1oa94gng0y7vbq5knWOMy ESOcEgcDH1xXzzo+rSabrlrqJJLxzCRvfn5vz5ryZYqWIu4aJGNeryOKR9bz/EzVZLdVjS3hlzky KpP6E4rPv/HGr6lYtazzr5bffZECsw9OO1c/GyvGrIQysMhh3FLXlvE1pbyOm73uFKGKkEcGkorn RI5XZd2GK7hg4PX6+tNoopXb3AKduK52sVJGDg4ptFC7oCezv7nT5lltp5IHXo0bkGurk+KuuNax xK8KSKMNN5QLP74PA/KuNorSNWcNIsrmktmdtpfxX1e1uAbvy7yE/eXYEbHsRVHxR8QNR8SLJb/L bWDH/UJ1b03N3rl6KuVeq48vMPnls2L15PNdn8J7uSHxWIVb93PE6uvYkDI/L+pri60fD+pSaPrl leRnBilUn3XPI/ImlRl7OcWhxlaSPovYKNgqX7wBFJX1h6nKQbTRtzU22opmWFdzsFFO4ct3ZEUz CKNm79qzd3Oc8066uzccfdUHIqDNc1SXM7I9CjT5Iku73o3e9RZozWR0Eu73o3e9RZozQBLu96N3 vUWaM0AS7veoL4edayr7cfWnZooA5minzxmOZ1P8JIplBB8aftkaVeW/xIsNQkRjZXVgiQv2DIx3 j2PKn8a8Cr62/bV02/m8P+Hr6ORTplvPJHLGWAPmuF2HHfhWHFcv8Bf2Z9L8deFbfxH4iuLryp5W +z2dpIqrJGp25dsEjJDcDB4oKuQ/s3fA/RfiR4T1i+8RWMzxG6WKyuIpWicbVPmYxwRkqOc8j2r1 nSv2R/h/pt0JpYdQ1JQc+VeXXyH67FXIr1vR9IsvD+l22nabax2VjbII4YIhhUUdquUgv2PjD9tr 4B2el6Pp/jXw3p8dpb2ipY6ja2yBUWPOIpcD0J2k+6mvjav2K13Q7LxNot/pOpQLc2F9A1vPEwyG Rhg1+UHxS+H958LvH2seGrws7WUxEMzDHnQt80b/AIqR+Oa7qM29GfL5lh1Tkqi2ZylFFFdB4oV3 HwV+KF58G/idoHi6zZv+JfcA3ESnia3biVD9VLfjj0FcPR14zj3pNXVmaRk4SUl0P380LWLTxBo9 nqlhMtxZXkKXEEq9HR1DKfyIrRr47/4Js/F8+NPhFceELybdqPheURxBj8zWkhLR/wDfJ3L7AKK+ wlbcM15UouLsz7mjUVWmpofRRRUmwUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQ AUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUmRS01qAPPv jx8SofhJ8IvFHixypl0+0Y26t0edvliX/vtlr8Obq6mvrqa5uJGmuJ3aWWRuruxJYn3JJr9Ef+Cp PxKNn4d8K+A7aXD3s7apeKp/5Zx5SIH2LMx+qCvzpr0KMbRufK5pW56igugUUUV0HjBUltbyXlxF BCpeaRwiL6sTgVHXffB3QP7R8QS6jImYbFcpx1kbp+QBP4ConJRV2J7H03+zfq1t8LfFGlwSSBLD 7PJb3MnrnLFj/wADUV5T4g1iXxBr2papMcy3lzJcN9WYn+tdIw3KV7Hj/wCtXHTRGGR48ZKnb+Ve aptqzCEm1yne/A7x8/w78eR6kE3xSW00EkecZyuV/wDHlWtzwTr0kHjSG6mbLXcrpMT/ABFz/jiv NdBt/MvfMI4jXcPxrpUkaNldThlOQfTHNZVFzLlFKbUkux7B8WtU+x+Ho7RW+e6lwfXavJ/XFeO9 evFdN498SDxFqFm6nMcdsg/4Gwy36n9K5ntnoPWuelD2cLE1pc8ro938A6p/a3hWykY5kiBhf/gP A/TFdDXi3g3xN/ZOg69bbwJGhEkPPO8/Jx+Y/KvV/DeojVdA0+6zlpIVJ+o4P65rzqkOVt9D0KVR SSRpUUUVzm4UUUUAFFFFABRRRQAUUUN8q5Y7frTAKVWKsGHVTkVRuNc061z51/bRY675VB/nVCXx zoEP3tVg/wCA5P8AIVfLLsTzRXU+lPA/jq28VQeRIBb6hEuWizw4H8Sn+Y7V1m0rxivj7Tfito+m 6paz2N+73iyDyViiZmZuwxjnPTFfUMPiZtQ0u1mjt5LSSaNWkjmXDISORjsa97DVnKNpo9bCy9ur Load5fx2g2j5pP7o7fWsaa5eeQs5yf0qFm3MSTkn1oyK2cmz14U1Af5lHmUzIoyKk1H+ZR5lMyKM igB/mUeZTMijIoAf5lHmUzIoyKAH+ZRu96ZkUUAZmqRbZxIOjCqVbk8azR7W5Hb2rHmhaFyjDkUE s5P4heE9J8baTDputWS39mJPNEbMV2uBgEEEHufzq74N0Ow8M+H7fStMtltLC23LFCmcLklj1yeS SfxqxrDfNGPbNS6Sf3Dj0avz+ji6ss/nQ53y22vporn1E8PT/suNRL3r7/OxJqFw9vEpQ4bNN0y4 e4jfzGJI6Cmat9yIepNN0g/60fQ054yquII0FL3LbdNrjjh6byr2nL73f5mjXyZ+3x8LxqnhvTfH NnF/pWmsLS+KjloHJ8tz/uvkfR/avrOsrxX4bs/GHhnVdCv0D2eo2sltKD2DKQD+Bwfwr9Cg+SSP ja9L29NxZ+PlFafijw9d+EfEmqaHfKVvNOuZLWUYx8ysRnHuBn6EVmV6R8RJOLswooooEe9fsRfF Q/C39oTQJZ5vK0vWD/ZF5ubC4lYeWx+kgQ/nX7HqMcV/PxHNJbyJLCxSWNg6MOoYdD+dfuL+z/8A Edfiv8GvCfineJJ76yQXBz/y3TKSj/vtWrixEdmfS5XVvF02ej0UUVyHvBRRRQAUUUUAFFFFABRR RQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFF ABRRRQAUUUUAFFFFACAUnrSmuZ+I/iyLwL4B8ReIpiBHpenXF5ycZKRswH1JAH400TJ2Vz8i/wBt b4hf8LF/aS8WXUUnmWWmyrpVrg5XZCNrEH0MnmH8a8Mqa8vJtSvrm8uW33FxK00rn+JmYkn8yT+N Q16sVZJHwlaftKkpvqFFFFUZBX0H4HttA8J/CU3cmoyHxDKjXf2IQnZuJARWYD+5gn614PpNidU1 S2tFB/euFJAzgdz+ABr2aaBLiJodrFGAUKD27AfpXFir8tka03FSTmrq+voev/C/wnB488Fxa1cy 3FtOzyo0MSAqSrYG3PXIx+Oa5Lx9f+Gbrwl9l0CKY62tyrtdXEPluY+dykgkeg/CvoDwL4di8J+E dL0uJdgt4l3DOfnPzN+pNfO/xN0P/hH/ABtqduq7YpJPPjwONr8/zz+VeJRl7STUmddR06VT2lKO nZmgsmnyaXpP2KBYnWyiW6kVSpluAP3jH15zz0plc3Frk0UKxqkYVRtGQf8AGqNl40vrjU7i3aKA JHnaVVs8Ef7VdtnGyZw/V6mIcqkVa2rPoP4V22nato9zBc2VvPPby53PGCxVhxz+dcR4Lgjuv2iv FOnSxrLYRRTeXauMxpgxYwvQdTWD4F1bVNQ8V6VZ2k72nnTr5jW7FdyA5IPtjPWt7xddH4Z/GTUN dtbZbh7+33MkxO1lcjdjHQ5SuOdOXO4p7noYSpTp0pe0V21ZHZ/Fa10/S9Ns7e1tIbeWd2LNHGAd qj/EitP4R6j9q0Ce1J+e2lz/AMBYZH6g15v4l8ZN42uLa+NsbRVi2CIvu5ySTn3z+ldB8JNQ+y+I pbVj8lzEQP8AeU5H6E1MqcvY2luefGf77TY9gopetJXmnoBRRWRrnizS/D6/6ZdBZcZEMfzOfw7f jVRTlohN8quzXqO4uYrSIyTypDGOrSMFH5mvK9a+Ll7dFk0yFbOPoJZPmfH8hXE3+pXeqS+ZeXMt y/8AelbNdkcLKXxHLLERXwnseqfEzQ9OYqlw17IO1uuR9MnArlr/AOMV1JkWVhFCOzTMXP5DArzu k3Ad66Y4eETlliKkjo774ha/fZDag0SH+GABP5Vi3GoXV2xM9zNNn/npITVNpB61A8/vW6go7Ix5 pvdlhmVegqNpiSAASTxhRyaqtc7e9eifs/8Ag/8A4TT4jWZmj8yx07/TZ8jg7T8in6tj8AauxrRp utUUF1Poz4P/AAc0zwLptrqF1B9p8QTwq8s0oz5G4DKRjtjpnqcHoK9O3dajJPP1pMn/ACa1P0Cj ShRjyRVibzKPMqHJ/wAmjJ/yaDYm8yjzKhyf8mjJ/wAmgCbzKPMqHJ/yaMn/ACaAJvMo8yocn/Jo yf8AJoAm8yjzKhyf8mjJ/wAmgCbzKPMqHJ/yaOf8mgCXfUNxCJo9uOR0NLz/AJNGT/k0ActrkTwz xqwx8uaXR/8AVyD3p/iR86goPUIP61N4XxJ9oXqOP5mvyfD1P+Mkm/Nr8D7ipH/hISXl+ZW1jpD+ NN0n/WSjtgVY8SII5oAo28HP5iodBiM1y6g4+TilUqf8ZJF+aX4ChH/hHt5P8zQoqy9jKvIG78ah aJ16qRX6zoz4do/Pz9vHwGPD/wAT7LxFBHttddtgZCOgniwrfmpQ/r3r5nr9Hf21vBf/AAlXwRvL 6OPfd6HcR3yNjnYfkkH02tn3KivzirvpS5onx+PpezrPz1CiiitjzQr9Jf8Aglt8QjqXgTxT4Onl zJpN4t9bqe0UwwwHtvQn/gVfm1X0x/wTz8cN4P8A2k9KsmfZba9aTabID3YgSR4998YGfQmsasea DPQwNT2dePnofrtRRRXmn2YUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUA FFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAlfMn/AAUO8Yf8It+z RrVqj7JtaurfTlHqC+9//HYzX03ivz//AOCrHijZp/gHw3HJzJNc6jNH/uqscZ/8fk/KtKavJHJi 58lGTR+eVFFFeofEBRRRQI6r4dWYm1uS4IGLeIkZB+8x2jnscZ/Kvbfhvoo8QeNtKtSN8SyedIP9 lBuP8hXkvw/jNvptxMQ6+dMF5+6VUdfrljX0V+zvb2sM+q6rdXEMDKq20QkkVTzhm6/QV5OJm7SZ tCN2rnvTckmvGP2htF2rpesKOButZW/8eX/2b869abXNNXrqFr/3+X/GuW+J0dh4i8D6pbR3ts86 R+fEomUksh3ADnvgj8a8OhLlmmdc4+6fOemWv2ySQEcLGT0744rHt9NitLyW4DOZJM5U9ByP8K6X wmu63ln6hmwPoKw9WX7JqVxH2DZH0PNe3u/Q4qdSUW4xe56j8AdJ+2+Krq+K5Sztzj/ec4x+QNbv 7Q+k7rPSdTAwUdrdz7HLD9Qa0/2e9L+x+DZ75lw99cMwP+wnyj9d1dB8WdJ/tj4f6sirmWGMXCfV CD/LI/GvKlV/f3udCj7lkfOk3iqDTNP3eQ7iNQMAjmpLPxn51uk9qJrWYjKSI+GQ8jORXJXubu1k iVsFhgE/WpNJt5CtvZod0rMEG31Y/wD169GS18rC9jS9jzfbv+B634f+OGvaK0cOqRpqkG1SPNGy XaQCDuHUEHuPSvadH8WWureFY9eMc1tZsjSFZFywVSQTx16V4Z8b/C48P6xoYt0+SWyS2+UcF48L +oIr3jS9Bis/Ctto0g/draC2cdvu4b9a86sqcoxl3KhzK6PN/EvxSvtS3Q6aPsNsf+WnBlb8e34f nXDySNK7O7F3Y5LMckn3NcbJqF54e1C4sy3zW8rRPG/OCpIP8q1rPxVbXGFlXyX9SflrvhTUUuVH BUU5O7Nqms4xVdrpWXIIIPccioXuK0sYWLTT9qgebjrVV5utQtNTGkyw9wfWoZLiqsk3NQNNQaKJ Zeb3r7K/Zh8Fnw18PV1OdNl7rDfaGyMEQjIjX8st/wACr5J+Hfhebx5420nQotwW6mHnOozsiU5d vwANfoZawxWdtDbwIIoIUEcca9FUAAAfgBQfQZVQTk6sumxaz70Z96h3Ubqs+muTZ96M+9Q7qN1A XJs+9Gfeod1G6gLk2fejPvUO6jdQFybPvRn3qHdRuoC5Nn3oz71Duo3UBcmz70Z96h3UbqPMXQp3 eux2dw8LRuxXupGKh/4SaH/njJ+YrK1oD+0pqp1+N4/iTMKGKqUoSVk2lofoeHyjC1aMJyjdtIs6 ndi/uvOVWUbQMNUmk6gumySFlZg4xhfrVKivlI5hWp4r64n797/M9qWFpSo+wa921i7q2oLqEyMq soVcfMfem6XeDT7gyMrMCMfL17f4VUooeOxDxX1y/v3uCwtJUPYL4Tof+Emh/wCeMn5ij/hJYe8M h/EVz1Fe7/rTmX8y+483+xMH/J+JN4g+yeJdF1LS543Fvf28trJgjIWRSpx788e9fkZqmmzaLqd3 p1woWezme3kVTkBkYqwB78g1+tnTp1znivzb/ac8Pr4b+Oniq3TyxHPMl4ixrtCiVFfGPqT+Oa+7 4VzrEZjWnSxDvomvkfBcWZXRwtGFairatP5nl1FFFfph+YBXRfDvxRJ4I8feG/EEZKtpeo2938px kJICw/EA1ztDDcpHqMUbqxcXyyUkf0D29wlzDHLGweORQ6sDkEEZBqbbXmP7Nfig+NPgN4D1hmDS TaTAjkHPzIuxvxylemDPNeQ9HY+9jLmin3H0UlLSLCiiigAooooAKKKKACiiigAooooAKKKKACii igAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAT0Ff lX/wU28QNqX7QVjpucppujQqAOxkd3P49K/VM1+Nn7c2rf2x+1J44ZW3JbzQWqk/7FvGGH4Nuroo q8jycylajbueDUUUV6B8kFGcUUUDO/8ADjLBodqoLfMGchuxLH+gFaJmDfWuTTxRHaxxwNA++JFj bBGMgAZpf+Ewh/54yfmK8+UJyd7HuxynGzV4wumb1+weaE4HB/qKu+cuM1x8niyF2U+S/HuKmj8Y W/mIXglaMMCwBHIzyKyjRmm3Y9LEZTipUqcVB3Sdz3PQrf7LpNshHzbN5+prnPHEX2e8gmHAkTaf qv8A9bFZC/HDTVUD+zLrH++lZPiX4rafrtmkUdhcRyo+4MzLjGORTVKd72PGhkuPU7umz0XR/jz4 j8M6DbabYR6ettax7I/MtySeep+bqat/8NH+LL2yeOaPTGWRGRl+zNyDwf468JbxdCykeTJgjHUU kfiyGNQPJkwPcVk8I+e/KevHKsV9XceR81/wOv8AtGT6e1dv8GdLGvfEbSYmUtHA5unHsgyP/HsV 45/wmEP/ADxk/MV3Xw2+J954HuptU060tppbmHysXSk7V3ZOMEcnAqqsJ8rPJrZfXwqU6sbLY+k/ 2gLKX/hELbWIBi50q7jnRigbAJweDx12n8K8Rb49eOVvFUa38mOf9Fh69P7ntVnX/wBorXfE2h3u lXmn6aLa6iMT7I33AHuMsec15f5w69/WuKlSfJyyRnzKlNqSub2qa1ca1qFxfXcglurhy8jqoUFv XAAA/CqpuOOtZn2j/OaPtH+c13I47aG1a6tPZkGKQqP7vUVsW3iiOQBZ1MZ/vDkVxv2j/OaPtHv+ tMhwTPQPtSTLuR1ZfUGomm461w8N/JbtmN9hrRh8RE8Trn/aX/CoIcDoJJqge498VSXUI5lyj7vx ra8G+EtU8e+I7XRtIj826nOSzZ2RJ/E7HsBQEYyk0kj6W/Y38FbLPVvFtzH80p+w2hI6KDmVh9Tt X8D719NbqwfBfhe18EeFNK0K05gsIBDu6b2/iY+5Yk/jW1uqz7bD0vY0lAkyKMio91G6g6CTIoyK j3UbqAJMijIqPdRuoGeR+Nv2svhr8PfFWoeHdb1W8t9VsGVJ449PlkVSVDjDKMHhh0rD/wCG5PhB /wBBvUP/AAVz/wDxNfFn7XX/ACch42/6+Yf/AEnirxGHV1muFh8pgWON2RjvXbGjFq59DTwNGUIy bep+oP8Aw3J8IP8AoN6h/wCCuf8A+Jpf+G5PhD/0G7//AMFc/wD8TX5fXWrLa3DRGMsRjnI71fqv YRNP7Oo92fpl/wANyfCH/oN3/wD4K5//AImj/huT4Q/9Bu//APBXP/8AE1+ZtMmk8mJ3xnapbH0F HsIh/ZtLuz9NP+G5PhB/0G9Q/wDBXP8A/E0v/Dcnwg/6Dd//AOCuf/4mvzAstTW9mKLGU4z8xFNj 1ZZLlYfKYEttzkUewiH9nUu7P1H8E/tFeCfix4quNJ8O6jc3d75b3ISazkiHlqVBOWGOrDivQ6+B v2Hf+S1zf9ge4/8AQ4q++a/n7ijB08HmUoQv7yvr3Z9tgX+4jHtoFI33TS0fpXyJ3nyR8UfiL4p0 v4i+IrOy8Q6lbWkN46RQxTsqIvGAAD0rlf8AhanjL/oZ9V/8Cn/xr661H4Y+E9Wvp7298PWNzdzt vkmkjyzH1NV/+FQ+Cf8AoVtN/wC/Ve9DH4eMVFw1PHlhK7k3z6Gl4Fupr7wVoFzcStPcTafBJJK5 yzMY1JJPrzW7UFnZwafaw2ttEsFtCixxRIMBFAwAPwqevDk05No9aKcUkxPr0r4g/bs0V7X4iaBq nyCK+0zygFHO6KVsk+vEij8K+3/avk/9vrToP7H8GX+3/SRcXFvu/wCmexWI/MV9jwjV9nmkF/Nd HyPFNL2mWTb+y0/xPjqiiiv6CPwQKKKKAP1s/wCCc+vf21+zJpNuTufTL+7sz7DzPMA/75kH5V9Q CviD/glZrLXHwx8Z6WT8lrq6XCj082FR/wC0hX2+teVUVptH3GFlzUYPyHUUUVB1hRRRQAUUUUAF FFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUU UUAFFFFABRRRQAUUUUANzX4g/tOX39oftEfEiX7w/t+8jDZ4IWUqP/Qa/b2vwj+MFwbz4teNZ2AV pNavGIHQZmeurD7s8PNX+7ivM5Ciiiu4+YClClmAAzk4x60lT2K7723XON0qj/x4UGkPjRWmZmmc sMNnke9UJ9Vht5WjffuHXC5rT1BfL1C6Xrtmcf8AjxrltW/5CEn0H8hV9D9wp+7SiaX9tW4x/rMf 7tSyapFFHFI2/Eg3L8ua52rl9/x42P8Aun+YoNOY0f7at/8Ab/75qQapA1u03zeWrAH5a56trQeb eTIyN3f6Ci40yT+27f8A6af981La6lFeSbE3bsZORVjy1/uj8hTgoXoAD7DFF2US2qCW6hRslWcK a663jW2hWJMhFHGTmue8M2H9qeItMsy5j+0XEcW8DO3LAZr6IP7PsPP/ABPJMf8AXsD/AOzV5eMr wpNKb3PgeJazhOEG9LHjW73pdx9a9k/4Z9h/6Dkn/gKP/iqP+GfYf+g5J/4Cj/4qvO+t0u58S60W 7tnje4+tG4+teyf8M+w/9ByT/wABR/8AFUf8M+w/9ByT/wABR/8AFUfW6XcXPA8b3H1o3H1r2T/h n2H/AKDkn/gKP/iqP+GfYf8AoOSf+Ao/+Ko+t0u4e0geN7j60Zz3r2T/AIZ/h/6Dkn/gKP8A4qrs n7N9rZ6PcajfeIZbeCOJpQotAWZVBJON3tVxrwqSUYvVlKpFnhysVb7xU+3WvSPhL8ede+D91cSa dbafexXJXzku4iXYDoBICGHf1HtUPhL4af8ACUa5Z6VZDzby7BePzjtWKMZJd8ewzgZr2jTf2Y9F tlAu9TuJ5P4vs8KRKfbnJr3q+BhhIp4mai3razbt8jOniJ83NSjsdR4e/bs8P3UYXWvD99YTdzbS rMn6gH9K9L8F/tK+CPG+oWtjZ3V1b3ly/lRxXMBALEZC7lyPzxXmFh8CfCVjg/ZJrjHaaQEfoBXV aL4Q0bw5N5um6dDbTDgSgFmAxjgnO38K4ZYrAwi7Xk/S35s9SGMxV7yse0/29pv/AD/2/wD33R/b 2m/8/wDb/wDfwV5bRXh/XH0id/1+X8p6l/b2m/8AP/b/APfwUf29pv8Az/2//fwV5bRS+uS7B9fn /Kepf29pv/P/AG//AH8FH9vab/z/ANv/AN/BXltFP65LsL6/L+U+Ff2sJ47n9orxrJE6yRtcQ4dT kH/R4q8Csfl1NO3zn+te1/tH/wDJbvFX/XeP/wBEx15HDHYfalMchM244GT1r6ek+aEWfpeHfNRh Luilq3/IQk+q/wAq317f57Vn3sdi1yxmciUgZGTVya6ht9vmPs3DIzmtzpRLUN5/x6zf7jfyNDXc SQrKXxG3RsGhJoryFwjb0PynHFAzI0P5bx+x2f1qK1/5CiD/AKaH+tbNrp8Vq++IMGI28tmq0cdh 9qDI5M2/gZJ5oIPpT9h3/ktc3/YIuP8A0OKvvmvgb9h3/ktc3/YIuP8A0OKvvmvwPjT/AJGf/bq/ U+jwP8IKKKK+DPQOP1b4kWuk6lc2b2U8jwOULq64PuKqf8LZsu+n3H/fa1Jq/wANf7W1S6vDqPlG Z9+zyM4/HcKqf8KlA5/tX/yX/wDsq9CKw7SvucTdW9kd1p94NQsbe5VSqzRLIFbBIyM9qsVnWE1p pdjbWb30Ba3jWIlpVByoAORng1P/AGpY/wDP7b/9/l/xrjlB30R0qStqy1Xzn+3PZxzfCfS7pkDS wavEqHHIDRyZ/wDQR+VfRYYMAQcg8givnv8Abi/5Izaf9hm3/wDRc1e/w7JxzSi/P9DwuIIqWWVl 5fqfB1FH+NFf0kfzqFFFFAH37/wSk1I/b/iHYA4Vks7gr6kGRc/rX6ICvzY/4JUyMPH3j6Ifc/s2 2Y/XzXr9J16V5tb4mfZZf/u8RaKKKxPRCiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAK KKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAjPSvwe+K3/JUP GH/YYu//AEc9fvH2FfhN8aLM6d8YfHFqQwMOt3iYcYbid+orqw+7PCzb4I+pxlFFFdx8yFT2LBL6 2Y9BKp/UVBSrIYnVxwVORn2pM1h8aH6kQ2pXZHQzOR/30a5TVv8AkISfQfyFdNch1uJRJzJvO765 5rmdW/5CEn0H8hVdD9vg704vyKlWdSnjhsbDzHC5Q4/MVWqLxJ/x66Z/1zb+YpooZ9utv+eq1v8A hyZJraUowYB+cfSuFrpPDkz2+kXbxttYTLyRn0pIE9TrKK53+1rr/np/46KuaXfT3N0VkfcoXPQD 0qi+Y7b4flP+E68PGQMyfb4MhTg43ivuhptI3H/Rrn/v8P8ACvhf4fbf+E68Pb2Kp9vh3FRkgbxX 3SbfSSSRdXJH/XIV8zm3xx9D874ov7aFu36jfO0j/n2uf+/w/wAKPO0j/n2uf+/w/wAKd9n0n/n6 uP8AvyP8aPs+k/8AP1cf9+R/jXz58Td+Q3ztI/59rn/v8P8ACjztI/59rn/v8P8ACnfZ9J/5+rj/ AL8j/Gj7PpP/AD9XH/fkf40Bd+Q3ztI/59rn/v8AD/CjztI/59rn/v6P8KX7PpPH+lXH/fof41fj 0mxs4Y7wvLLnmOGVAu73PtTsNcz2sOhsdNhtkuntpkZjmOOWQHd7kelVb6zk8SR3dpJki6heBtv8 KspGfpUw8/VLofxO38PYD/CrFxcJZxG2tjuZv9ZMO/sPatqc3Tkpx3Wpdk0+x8+/8Tn4c+ILaWRm 07VLBiILxo98E8ZyMH1BBI/HnHWuzT9ozUreL/SdGsp2xxJbXBCn3xzivTLexjktTJeqrWfUQuoY SH6GuevPBeg6pcEnQLIvIcBYoyh/8dIr7r+3sFi4xWOo3a6r/hzk9lUp/wAOVjll/aWnGQ+gxk9t tyR/MVbh/aR3bTJ4cl2c5aO4z+XyVf1X4P8AhNMILW4jnP31t7ltq/8AfWaoQ/BHSpo3kt9U1Kwh UcyF1YZ9OAM10RxPD9TeDXyf+Yv9qT+K5ci/aR0jcBNo99GePusjfzIrYtPj54UuSoeS8tyevmW5 OPrtJrzzV/hTrNvGzabqUWrgf8u91EFkPsM5BP4ivNri4ns7iSMwtYXUbbXVCyEMOxXPWvXw+T5R j4t4fX0ZnPF16Pxbeh9Xab8SPC+rMVt9ctA+cbZn8o/+P4zXSKwZA6kMh/jU5H59K+NY/El1t23K QXydxcRhj+fWtvw/4sudMnVtBvrnRLzORb+aZLeU/wB3DcZPoRiuTEcJQtejNr11NqeYKS11Pq/1 4x9aK4/4V+Pj8RPD1xPNAttqdhIsV0kf3H3AlXUduhBHrXYV+f4vCVMDVdGruj1qdSNRKcdj4D/a O/5Lh4p/67xf+iY68Usf+QnH3+c/1r2v9o7/AJLd4r9fPj/9Ex15JDp8EV0JFuNzbsheK+qofw4+ h+vYT/d6foUNWH/EwkPutWNc+9B/un+lW7rSVupmlMrIWwdoGelGoWcV0yGSXyiM46DPStzr8ypc f8gOL6j+ZqfQxiCb/f8A6VM1ik1isAk+QYIcAHOKks7VbGNwH3BjuLNxjigfW5ZX7wrnLX/kKJ/1 0P8AM10EcyM3yurn0DA1Rj0lY7oTCRiQ27GOKA3PpL9h3/ktc3/YIuf/AEOKvvlRuYD1OK+Bv2Hf +S1zf9gi5/8AQ4q++VO1ge+Qf1r8E4z/AORrr2R9Dg/4J82X37U2t2t9cwLoemssUrxgl5MnDEZ6 +1RL+1ZrjMB/YWm8nH+sk/xrqLr9lfSrq6nnPiC+UyyNIR5CcZJOOvvUa/so6SrA/wDCQ33Bz/x7 p/jXgqWB5dtfmc/Ji+bfQ90ooorwXa57PSzPhr4iWcjePvEh+zsQdSuCD5Z5Hmt7VzkljJ5bf6O/ Q/8ALP8A+tX6Ebj2JFLub+8fzr3Y5pyxUeTY8mWAUm3zGb4b48OaSMY/0OH/ANFrXhf7cf8AyRq0 H/UYt/8A0XNX0LXzn+3RcrH8JdNgJ+aTV4mA/wB2OT/GtcgvLNaL87nJnto5XWXkfC3r9aSl/HNJ X9JH86hRRRQB9xf8EqP+ShePf+wXbf8Ao5q/Sla/Nz/glPb7vHHj+cHKjTrVOn/TVz/Sv0kHavOr fGz7HL/93iOooorA9IKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiig AooooAKKKKACiiigAoopKAFooooAKKKKACiiigAopM0ZoAWik3D1pu71FAC59q/Ef9qvTzpn7SPx IhYYLa5cTY/66N5g/Rv1r9tGmVfvMq/7xxX4/ft/aYNL/am8VS5XZfRWt2hU8EGBU/PMZrehJKR4 2Zq9FPsz54opvmL3IH40jXEY/jX869Dmj3PmB9BG4EVH9oi/vik+1xf3ufpU80e4izqMjTXssrKF Mh8zA9CMj9DXO6jp9xcXjyJHlDjByPQVv3UyzmGQSeYWiXP+zj5cfgAKyLzVza3DxeSG24+YtjsP atFqj9sws1Uw9OXkvyM/+ybr/nl/48Kj1zRru6t7FIow7Rowb5wMZx6mr39vd/I/8e/+tU02rGGC CTyt3mAnhsY6e1UdWhyo8Mal/wA+4/7+L/jWxpWj3drplzDJFtleUMF3A5A/Grn9vFv+WP8A49/9 apo9WLWbzeVkKwXbu9aBaGd/ZN1/zz/8eFXdLsZ7a4ZpE2rtI6j2pv8Ab/8A0wH4N/8AWqxY6oby Yx+UEwufvZ9KClY674fqH8deHgzBFN/ACxGcfOK+6W0u03H/AImkH/fDV8qfs1+CfDHjPxokev6+ 2jXkE8DadCpXN3MX/wBXyPYdMda+5P8AhVNl/wA/1x/3ytfAZ9m2Hw2IjSq3Tt20+8+YznJcXmc4 VMPFNJW1dupw39l2n/QWg/79tR/Zdp/0FIP++GruP+FUWf8Az/XH/fK0f8Kos/8An+uP++Vr5j+3 cF3f3Hzf+qWZ/wAi+84f+y7T/oKQf98NR/Zdrz/xNYP++GruP+FU2f8Az/XH/fK1Lb/C2whmV2u5 pQpztYDB/Kn/AG7gv5n9w1wjmX8i+842LR4LFUupbhLqM8pEildx989qcom1S5xje7dB2Uf4V3Vx 8P4J5vMe9mLdvlGAPSlk8G2emabM0l89vCql5rhgOFHXJ7Cn/buCeik/uL/1VzGOrikvU4y4uEsY WtrZsuf9ZN6+w9qbZ2aCL7Tc8W4+6vdzVSwKTapfyErNokJH2W6X/l59ceveprm5l1K4UBc9kjXo BX0EWpRUl1/rU+VqU3Tm4y3X9fMS5uJdSuAFHU7Y4lHAFW2ZdIjMcZDXjD5n6hPYe9DMmjxmOMh7 xh87j+D2+tV7Oy+07pZW8u3U5Zz39hT8zL8ws7P7TumlYpbry7nv7Ul7em4ZY418uFeEjH8z70Xt 6bpljiXZCnCRj+Z965nxZ8RNO+HxERh/tHWmXctsDhIQehc9j7da7MLha2MqKlRjzMiUowjdnWlY 9Ega5nKidVLEyEBIlx95j0Br5w+JmtWXiDxhdXlgwkhKIjShcCVwMFx9f6U7xf4k1vxIq3Gs3vlJ J+8isY+B/vbQf1bJrlMdu9frWQ5G8tbrVZXk9PJf5nkYvEc6UIrQs6dpl5rF2lrY2st5cPwsUCF2 P4Dt7132k/AfxbdNHJNDb6aNwObmYFh74XP5GvXvgj4dtND+HenXsEa/bNUDz3E/8RUSMqJnso25 x6kmu6rzM24nq4evLD0IrTqzsw+XwlBTm9zmPh14Dt/h5odxZxzte3d1IstzdMNobaCFVR2Ubm68 nNdPRRX55isTUxlV1qru2e3ThGmlGK0R8B/tHf8AJcPFP/XeL/0THXilj/yFI/8AfP8AWva/2jv+ S3eKj/03j/8ARMdeP22lzw3yynZsDk/e5xz/AI19ZQ/hx9D9ewv+70/Q16x9f+9B9D/Stis/VLGW 8aIx7flBzuOK3Ot7E+m/8eEH+7/Wn3n/AB6zf7jfyNFnC0FrHG2NyjBxTriMyW8iL95lIH4igfQx 9C/4/H/3D/MVuVmaXp81nO7ybMFcfK2e+f6Vp0CR9BfsO/8AJa5v+wRcf+hxV9818C/sPf8AJa5v +wRcf+hxV99L94fUfzr8E40/5GlvJH0WD/hfMyW8WaMrFW1O2DA4IL9KB4s0U8f2pa/9/BXmd14F 16S6mdbBirOxH7xOhP1qNfAevhv+PBh/21T/ABr5L2NK1+Y19pO/wnsv0paD1OOBRXn9dDr6BRRR QAntXyl+3xfINB8HWe8eY11cTbM9QEVc/r+tfVw7V8Rft36sLr4geHdNxzZ6a0pb/rpIRj/yH+tf YcJ0XUzSD/lu/wAD5Dimt7PLJr+ay/E+ZqKKK/oU/AwooooA/Qr/AIJRaV/oPxE1I8fvbO3X/vmR j/Sv0C7V8b/8EvdBGn/AzW9TK4k1DXJQG7MkcUag/wDfRevsla8yq/eZ9rgo8uHihaKSlrI7gooo oAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKQnFLTZPum gDm/FHjzSPCM0MWpXDRySqXRFQsSBxnj3rnX+OnhpVO1rpz7QH/GvGPjB4q/tj43axpQlzHpOm20 QjOOHctI5HqMNHn0xWBXm1sROMrR2PHrYucJuMT3uT4+6Iv3LO+kPsqj+bVUm/aFsv8AllpNy3+/ Iq/yzXh9FY/WqhzPGVj2ST9oZufL0TPpuuf/ALGqU37QmpHPl6Vaqf8AakY/4V5RRUfWKncz+tVf 5j0yb4+6+2dlpYxfgx/rVKb44eKJM7ZbWMf9cP8A69cBRS9tU/mJ+s1v5jspvjB4rmB/4mIj/wBy FB/SqknxM8Uzfe1q4/4CFX+QrmKKn2s+5LrVH9o25vHHiGbk63qH0W4YD9DVObxBqlx/rdSu5P8A enY/1qhRS5pdzP2s+5K11PJ96eVv95yf618YfttaSbfx5oeo4yLzTzGzH+9G54/Jh+dfZVfOX7bW gm78EaFqyrlrK+aFj6LKn/xSL+ddGGm1URlUk5RPjeiiivcOEKKKKANGBvM0+Ikr+7kYbR97nByf r/Q1zmrf8hCTPXA/kK6DTmLQ3MWT90SAcY4OMn8GP5CmSWsMrFniRmPcjJr0KXwn6tkdX22Cgn9m 6OXq5ff8eNh/un+Yra+w2/H7mP8AKsbxJcRWP2VNpC4bAUe4rY95qxSq7D/yCJ/+ui/0rE/tWL+6 /wCQ/wAa1bG6W60e5KhhtlUHd+FQIg9K0NF/4/G/3D/MVn1oaH/x+N/uH+Ypoa3PVPgf/wAlm8Df 9hm1/wDRq1+oTSLHjcwUdBuOK/L34G/8lm8D/wDYZtf/AEatfob8VudFsxjP+k9/901+N8bQU8ZR i+z/ADPcwcuWlKXZnXz6jbWsZkmuYYowcFnkAFQw65p1xKkUWoWskrHCokykk+gGa8H2itjwf/yN Wl/9d1/rXwEsHGKbudKxLk7WPbt3fPFR/aIv+eqf99CotQ/5Bt1/1xf/ANBNeAqo2iuahh1WTd7G 9at7JpH0H58X/PWP/voVk+MGT/hEdaLfNH9jlPHcbTXie0eler3Sl/hTOqjJOlsAP+AGuqGHVGrT ad9Ucdar7ShU/wALPMfDM019oenqB/CVSNegG410TMmkRGOMh7xh88nZPb61j+EpU0rwvZpEQ126 Hc/XYMngVoWdn9q3TSsUt15eQ9/YV+xLqfzhK/M+4Wdn9p3TTN5dunLuep9h70l5em5ZIo12QLwk a/196L68NyyRxr5cK8JGP6+9Toq6VGJJAHvHHyoeie596Rn6bD7eJNLaN5QHumIwh/gBPU+9fMF1 dG98bTzag29pL5vOMn+/0r6TtreXUbhvmOfvNIT933ryH4seBB/al1rWiBrm2k+e5hVfmRu8ijup xn2Nfc8K4ujQryp1XZyVkzixUW4xkujOC8Ux3Eev3wuc72kJBPdf4ce2Klm01rrQ7W8tgZPI3RXC KOVOchvoR3q1Fqln4gsYrTU3+z3UY2w3uOCOweqkf9p+E7wSIcK4+8vzxSL/AIV+tJu3Kt1sebKM eZy3T/A9J+EPxktfDOmpoGuiQWEbs1reRLvMO45ZGXupJzkcgk9RXu2m6lZ6zarc6fdw39uw4lt3 Dr+OOh9jXyVNfaHrSlrmBtLuj1khXdGx9x2qpHLe+GbgXemaqVwfluLGco34jINfKZlw9Rx05VYP lm/uO2li54dKOko9+p9kUV806L8fvFGm4W8NtqsY/wCfiPa//fS4/UGu30v9pDS51C6jpF1avwN1 u6yr+uD/ADr4nEcM46i/dXN6P9D0aeOoz3dj5i/aO/5Ld4r/AOu8f/omOvNjz15ruvjlrlr4k+LH iLUrFme0uJo2jZ1KkgRIOh9wa4WuynCVOChNWaP2rBtPDU2uyMPU7iWO9kVZXVcrwGIHStte3+e1 YeqQyNfSFUZhleQCe1bi9/8APatTsiUtWkeOzJRmQ7lGVOKhsZpJLC6ZnZmXOCTyPlNTawjPZsFB Y7lOFGTUFhG66fdgowJzgEcn5aA6jNHuJZbl1eV3UL0Zie9RW9zM2pKhlcr5hG3ccd6fosMiXTl0 ZBt6sD61HbwyLqisY2C+Yfmxx3oEfUH7Dv8AyWub/sEXH/ocVffNfA37Dv8AyWub/sEXH/ocVffN fgfGn/Iz/wC3V+p9Hgf4QUUUV8GegFFFFABRVOTWdPjZke/tVZTghplGD6dab/bumf8AQStP+/6/ 41fJLsTzLuXcZyO1fnJ+1Vrw1/47eJWVmaOzaOxXJyB5aANj/gWT+Jr9E77UINN0+4v5pFS2t4Wn eQn5QiqWJ+mBX5Q6/rEniLXdR1aX/W31zJctznBdi2M/jX6bwNh+avVrvorfez8041xHLRp0P5nf 7kUKKKK/ZT8hCiip7Oxm1K8t7SBN89xIsMajqzMQoA/EigqPxWP2L/Yc8Nf8Iv8AsweCYWTZJd28 l84xg5lkZ+fwIr3msTwT4bj8H+EdE0OHb5Wm2MNmpUYz5aBc/jjNbi15EtXc+9px5IKI6iiikaBR RRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQA3rimSSCO NmY4CjJPoPWpK4b41eJz4P8AhT4n1RXKTQ2MiQsp5EjjYh/BmB/Ck9rkyfKmz86fHnjO5174ma/4 htLh4Zri/llilic5CbiFwfTAFek/DHxzc+KoLm2vlU3dsFPmoMb1Pcj1+leF424Htitbwv4juPC2 sw30HzBflkj/AL6HqP8AD3ry5pSuz52p7zbPpeiqej6ta65p0N7aPvgmG5cjBHYgjsQauVwnGFFF FABRRRQAUUUUAFFFFABXnn7Qfh0+J/g74ltVXfLDbfa4x33RHf8AyBFeh1Hc28d5bTW8w3RTI0bg /wB0jBrSL5WmLyPyuHTPaitbxb4fk8KeKtY0aUFXsLuS3wfRWIH6YrJr6NO6ucHUKKKKYE9jIIby Fm4Qttf5c8EYJx9Cfyq1IjRuyMMOpww9DWdVq8t57ox3K3TxrIgyoUYDD5T+o/8AHq6aDs7M+34a xFpzoPrqiauW8bf6yz/3X/pW59huP+f58/7oqtqmgf2oluHuWVogRu2ZLZx712n371OFrodD/wCQ Lef9dl/pVr/hCU/5/GH/AGz/APr1es/D4s7Oa3E7P5jhy2zGMDHTNTZkcrMmtDQ/+Pxv9w/zFWP7 BX/ns3/fNT2elizmMgkL5BGMYqirNM9F+Bv/ACWbwP8A9hm1/wDRq1+jvj7Q7zXtNtobKMSyJNvY Fgvy7SM8n3r84vgb/wAlm8D/APYZtf8A0atfqJX4zxxJ08XRkuz/ADPbwUVOnKLPHf8AhXevf8+a f9/k/wAa0vDfgfWNP16xubi2VIYZQ7sJVOB9M16jt9v0pOntX508VUas0dyw8EQ3kbTWdxGgyzRs qj1JBAryJfh3rwUD7Gn/AH+T/GvY6Xb7fpWNOtKnflW5pUpRqWv0PHP+Fd69/wA+af8Af5P8a7jV rebTfhneQSjy54dNdWAOcMENdVt9qxfGe3/hEda3/Kn2SXP02muqlWlUq01JdUceIpxp0Klv5WeP eBbMXPh20llby7dVJZz/ALx4Fa99em6KxRLshThIx/M+9Y3hu6Nx4dsIkXbCikJGPqea6BY10mMS SAPdsPlQ/wAHufev2M/m2XxPsEappMYkcB7thlVP8Hufeq9razalcnDE93kboPei3t5dSuCSck/M 8jdverepQlrZbWyubaOA/fdpcM5pkeYy+msZLNbW31FIIs/OdhJc/Ws1NOso2DJqqKw6FY2qM6DJ n/j6s/wl/wDrUf2DJ/z82n/f7/61LmtsZu7+ycr4s+FOha9HJc2eow2OpHncsbCKQ/7Q/hPuv5V5 Dr3hnV/DGYr2KRLZz8s0bboX/Hp+eD7V9Ef2DLx/pVp/3+/+tTv7Dl2MpurNo3GHjaTcrexBHNfY ZbxJicHaFRc8PxXoctTDqpsrHy7HI0UgdMAjjkf41dSawn4uoHgb/nranj/vk/0Ir23WPgzo+rFn SS30uY8+ZaTAp+KEfyxXBa98Fdb0n57Ka11aLsbeULJ/3ycZ/Cv0TCcQYHGWXNyvszzZYWtR1smj ll8Pi85sL23uz2jZvKf8j1/CqV5pd3p5xc28kP8AvLx+dJfaZeaVN5V5azWsv92ZCp/WpbTXr+xT bDdSCP8AuMdyn8DX0EJqSvBpox91/EuU8i8Wf8jFe/7y59PurXLW+rtPdLD5S8sRuDZx1rr/ABpc NeeK9QmdVV3dSQihR91ew4rgLHH9qR+u8/1r84xN/bT9T+iMtt9Tpcu3KvyNG81d7S4aERghcDOS OtaI/wDr1gatj+0JPqv8q31GM/57VzHqIgvro2cHmqoY5xgkiorXUGubWaYpgxg8ZPPGaZrQ/wBC Y/7a1X0/H9m3n0P/AKDQSWbDVGvpjGUCYXP3iaZHqzSXawmMDc5G7cfU1U0Hm8fH9z+tRWuP7WUf 9ND/AFoA+pP2Hf8Aktc3/YIuP/Q4q++a+Bv2Hf8Aktc3/YIuP/Q4q++a/A+NP+Rn/wBur9T6PA/w gooor4M9AKKKKAPE/EGl3kmvaiyWVw6G5kIZYWwfmPTis9tHvtp/0G6/78t/hXvm4+po59T+dd6x fKrcpxugm9zxv9pjxcfBvwE1ELIYbzUYYtNhHIbLgb8fRA/5V+dtfUv7dXjYX3iXQ/C1vJlLCFry 6VT/AMtZOFB9wq557N718tV+5cKYP6rl8ZtWc3f5dD8R4pxf1nMHBO6grfPqFFFFfaHxwV7H+x/4 Lbx5+0h4IsGj3wW95/aM/skCmTn8VFeOV94/8EsvABuPEXjHxpPHlLSBNKtmb++5EkmPoET/AL6N ZVHywbO7B0/aV4o/RyloorzD7UKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKK KKACiiigAooooAKKKKACiiigAr5q/bj8TDS/hrpujo+JNUvwWU9THEpZv/Hin519JtXw5+3XrE9z 8Q9D08k/Z7XT/NVc8bnc5OPXCgfhWdR2ic2Ily02z5pooorgPGR6V8Fdee31a50qSTMFxH5sak9H X0+oP6V7HXjXwZ8Oy3WrSaw6bba3Vo4yeN0h4OPoP517LXHUtzaHLPcKKKKzMwooooAKKKKACiii gAooopgfD/7YXhM6H8UE1WOPbb6xbLMSOnmp8j/jwp/GvCq+5P2vPBv/AAkfwv8A7Uhj3XWizi4G 0c+U3yyD/wBBP/Aa+G/xzXvYaanD0OOokpaBRRRXSZhTp5php8gjYqY28wYHY8Ht+P4Gm06N/LYN 17fgRgj9TVRlyu53YLEPC4iFRdGZP9qXTdJm/IVU8Taze6fb6c0Fw0ZkRi+0DnBFWLy1+x3LxZyA flPqvY/lWV4y/wCPPSf+ub/zFejzH7HCSqR547Mzv+Eq1Y9b2T/vlf8ACtnTtcvpvD93cPcs06TI qvgZAIBI6VyK10ehwtceGb9F+958ff2FK7C7F/4SLURx9qf8l/wrW8Natd32pGOedpUEbEKQOuRW F/Z0/ov/AH1Wx4Vs5IdUZnAA8sjr7irRUXqeyfA3/ks3gb/sM2v/AKNWv0U+Jl9c2Ok2jW1xLbub jBaJypI2Nxx+FfnX8Df+SzeB/wDsM2v/AKNWv0P+KyltHtNoLH7R2Gf4TX47xp/vtD0/U9rC/wAG Vjz3/hINV/6Cd5/3/b/Gtbwprmo3HiTTYpb+6kjaZQyNMxB69RmsGGxubqQRw280rnkKkZJ/lW94 T0TUbfxJpssthdRxpMCzPCwAHPU4r4mpyRg9jSPPzI9ZvmZdPuWU4YQsQR1B2mvEF8QartH/ABM7 v/v+3+Ne36h/yDrodf3L/wDoJrwRYZNo/dP/AN8muPBqLUro6sQ3dWLn/CQar/0E7v8A7/t/jXpO oSyXHwtupJHaSR9MYs7HLE7Dz715V5Mn/PN/++TXqt0zQ/CyZgMMult1/wBw11yUfa0+XujhqN+x q3/lZ5x4N2ab4YsZHAe7ZDsQ9E5PJrQtbabU7kgHJPLyE9KyPBFrNqOi2arljtJdj2+Y1u6r9pSH 7DY204gHDyBDmQ/h2r9WP52no79CTVLW98n7JYwEW+Pnk3rmQ/n0rG/4RvUMf8e3/j6/41F/Zuof 8+1xn/daj+zdQ/59rj/vlqPkc8nzO9mS/wDCN6j/AM+3/j6/40f8I3qH/Pt/48v+NRf2bqH/AD7X H/fLUf2bf/8APtcf98tS+QvkyU+HNQH/AC7f+PL/AI07/hGdSPS0LD2Zcfzq94V8Hah4k160sDFP BE7ZlmYEBEHLHn26e5r3Tw94U0rUJLmaOyUaamILaLcwDgdXPPeueqsRKdOjhoJym3u2rJdXY93L sBRxMKlbEScYR62vr2Pn3/hF9T7Wbfmv+NH/AAi+pn/lzb/vof419Pf8ITon/Pgv/fb/AONeW6lE kGpXUUa7VWRlUZ6AEivns/x2P4fpwqYiknzNpWb6H1OU8NYHN5SjRqyXKr6pf5nmsnhvVJojFLZ+ fEePKm2un5HisDUvg3Y6pln0Q2shP+ss5RGfyJI/DFemXXiS1s5TGS8jqcHYOBUP/CWWn92b8h/j Xh4fj7MsO+ajTa+Z9BLw+wr0lXf3HwZ8VPh/qmifELWrC203ULi3hlUJIbdmLAxqeqjaeSelcLD4 f1RroIvhzUVYt9/7E4/HpX6Xr4utV6LMB6cf40f8Jhbek35D/GvT/wCIj4x6ywt33v8A8A+0oZLS oUo0o1NIpLbsfm43gvVpGJfQr5m9WtHJ/lT/APhE9b/6A2of+Asn+FfpAPGFt6TfkP8AGrdhr8Gp SbIpGV+u1xgn6Un4j4qKvLCK3q/8joWU03tM/MHXLG40aJTqNhPCGPypcRFM+4zVG3uYZbaZ0h2I mdy4HPFfTH7fLFr7wpkkkQT4z/vrXy7p/wDyDbz8f/QTX61keZPNsDTxkocvN0vex4OJpKhVdO97 FiwvLe4mZYoPLbbknaB3FW1t4g28RqGznO3msfQv+Px/9w/zFble8cy1R9BfsO/8lrm/7BFx/wCh xV9818DfsO/8lrm/7A9x/wChxV981+B8af8AIz/7dX6n0WB/hfMKKKK+DPQCiiigAqvfX1vpdjc3 t3IsNrbRNPLIxwFRQSx/AA1P7189/tofEgeFfh1H4dtZtuo6+5jdVPK2y4Mh/wCBHav/AH1XqZZg 54/F06Eer/DqzysyxkcDhaleXRfj0R8X/ELxfP4+8ca14huCxfULlpUVs5SPoi9eyADHt7Vz1FFf 05Spxo04047LQ/m+rVlWm5y3YUUUVqYgSADnp1Nfsj+xH8N2+Gf7Ofhi1ni8nUNSVtWuwRg75juU H6RiMfhX5XfAP4ay/F74w+FvCqKxgvbxWumX+G3T5pT/AN8gj6kV+4trBFa28cUKLHFGoREUYCqO AAPauSvLaJ9BlVJ3lV+RZoooriPowooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiig AooooAKKKKACiiigAooooAKKKKAGntXxL+3X4fvl8ZaHrS2ch0x7L7M94qHyxIHY7WboDg5HrX20 Kp3+m22q2ktpe28V3bSDbJDMgdGHoQRg1Mo8ysZVYe0jyn5JUV7Z+1b8J9P+F/jm0bRLNrPR9Stz NHCpJjjkDYdEJPA5U47bvSvE64ZR5XY8OUXF2ke3fBnVI7vwzJZdJrSZsj1VuQf5j8K7+vHfghpt y+qX18rbLWOLyXHZ2JyB+GM/jXsVcNRJS0OOVr6BRRRWRAUUUUAFFFFABRRRQAUUUUAVNX0u31zS rzTrtPMtbuF4JU9VYYP86/MrxZ4duPB/ibVNEuxi4sbh4Dx94A8N+Iwfxr9QOexwa+Pf20fAf9m+ JNO8V20WLfUU+y3OOgmQfKT9UGP+A16GDqcs3HuY1I3Vz5sooor2DlCiiigCHVIftFqJMfPBwcd0 P+BP6muY8Y/8emld/wB2/wDMV2EbmOQNgMO6now6EfjXM/EK3jtP7NSNiYfLcxs3Urkcn+tdVKWn Kz9FyHHe2pOhN6x2OQXrXV+F/wDkA33/AF3T+Qrk9y+tdn4HhjutLvI3J2mVTwfRa3W59UpIfWho f/H0f9w/zFXP7Dtv78n5ipbXTYLOQvGWzjHJFXdFpo9D+Bv/ACWbwP8A9hm1/wDRq1+olfl18DyP +FzeB+R/yGbX/wBGCv1Fr8a44jKWKpcvZ/me9gJR5XdhRRRX5l7Or2PT5qfdBRmjb70Y/wA4p+zq r7I/aQ7oMmsbxkhm8J60mcE2koyf901se1YnjiR4vB2uOnDLZykH0+WunDU6ntoNx6r8zixk4fV6 ln0Z41omsG38NWVpYMY0VTvmXgscn9Ksf2vf9ftU/wD30azvCPibUF8O2Q+0cbTxtX1PtWx/wk+o f8/H/jq/4V+0NM/mmom5N6kP9rX3/P1P/wB9Gj+1r7/n6n/76NTf8JRqP/Px/wCOr/hR/wAJRqP/ AD8f+Or/AIVNn2M+V92Vv7Wvv+fqf/vo0v8Aa1//AM/U/wD30asf8JRqH/Pz/wCOr/hXYeH9Wg1r TVmgcyGNjFIzrg7xjIrws4zT+yaMa0oOSbt6H0mSZHUzqtKlGfLyq+p1vgXRbzTPDcEMskjavreD 85JMFuP6nk/jXq9nax2NrFbwrtjiUKo+leMf2ld+cJhdSiULsDhzkD061J/beof8/wBcf9/G/wAa +cwPH+FwtWVepQbb0Wq0S/Vs/T6nB9WWHjh6dRJLV6PV9z2nB44rxPWctql8B1MrgfXJp/8AbWof 8/1x/wB/D/jVRmMjF2JZ2OSSc5r53izi2jxDTpQpU3Fxberv0Pe4f4fnlE5ynNS5lbRHnNxG0Mzp IMODzmo69EmtYZyDJEjkdCyjNR/2ba/8+8X/AHwP8K+PjmSSScT6v2D7nn9Fegf2ba/8+8X/AHwP 8KP7Ntf+feL/AL4H+FP+0lb4Rewl3PP/AK1f0OGSfUoDGCQrAsw7Cux/s21/594v++B/hUsMMcAx GipnrtXFRPMFKLio7lRoO92z5I/bnt1u9Y8KRvuCm3nJ2nB+8lfMcNjHBDJEpYpJ97J56Yr6h/be ONc8J9v9GuP/AENa+dtD0O98SalFY6fD59xJ0APAHdiewr+oODLLJMP6P8z4zMpRjiJ3Zj2umxWb l4y2SMfM2as16BrHwT1/S9Pe6R7a98td7xQOdwHfGQM4rz7cK+1U4y2Z5Ma1Ofws+g/2Hf8Aktc2 f+gPc/8AocVfeH261a6+yi5h+1AZ8jzF8zHrtzmvz9/ZBmuofiVrMmngtfJ4fvWgA67wY9uPfNaK 316upC7W4m/tIS7xICfN8zPX13Zr8wzvJP7WzCpPm5eWKtpe7McVnqytU4qHNzPXU++qKpaHJdTa Lp73vF41vG0wIwd5Ubv1q7X5FUw86cnG2x9tTrQnBSvuFFGPcUnPNZeyqfysv2kO6I7iaO3hklmd YoY1LvIxwEUclifQDmvzP+OvxLf4rfEjUtYR3GnRn7LYRsfuwIcA/Vjlj/vV9T/tlfFweFPCKeEd Pm26trKE3JQ/NDa5wfxcgr7gNXwv6fTFfsfBuVOjTljKy96WkfJdfvPyHi7NPbVI4Ok/dWsvN9Pu Ciiiv04/Ngooq5pGkXmvatY6ZYQNc397OltBCoyXkdgqr+JIoKiuZ6H3v/wS7+E7MfEnxFvIev8A xKdOZh9HncenOxf++vWv0JUYUCuG+Cfw3tfhD8L/AA74TtApGnWipLIv/LSY/NK5+rljXdV5U5c0 mz7jDUvY0lAWikpag6QooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKK ACiiigAooooAKKKKACkbpS0UAcB8YvhXp3xe8HT6Ne/urhT5tpd7ctBKAQG+hBII7g1+bHinwxqP gvxFfaJq8Btr+zlMcidvYg9wRgg9wa/WRq+Iv26rXTm+IfhtYlSPUZrFvtLjglPMxGT64xJ+Vc9W OlzgxVNcvOY/wz0oaV4NsQVxJcA3D+vzdP0xXU1Fawra2sMScJGiqo9AAB/Spa8aWrPn3qwoooqR BRRRQAUUUUAFFFFABRRRQAVxvxe8Bx/Ej4e6vohANxJF5tqx/hmT5k/PGPoTXZUVUZOLTQH5WzQy Ws0kMyNHNGxR1YYKsDgg++aZXuX7Wnw3PhD4gf23axbdM1zM3yj5UuB/rF/Hhh9T6V4bX0VOSnFS RwSVnYKKKK0EFfRX7Gfxti+HfjhfDmtNGfDuuSrHvmUMLa56I4z0DHCn8DXzrRQb0asqE1Ujuj9p /sNtyPs0H/ftf8KBZ2y5xbQjv/q1/wAK+dP2Nf2hl+KHhdfC+uXIPivSIgFkkb5r23GAJAe7Lwre owe5r6Rouz7SlWdWCnF7kX2OD/n3h/79r/hR9jg/594f+/a/4VLRRdm3tJdyNbWBWDLBErA5BVAC P0qTj0H5UVxHxd8dXPgPwut1ZRo15cTCCJ5BlYyVLFiO+AD+dR7ONZpSSfqka03UqSUIN3fmdvx6 D8qOPQflXgHws+Mmval4stNL1icX1tfN5SP5YVo3wSCNoGRxjFe/1M8PCm7OJpXjWoS5Zyf3hx6D 8q4b42fEj/hU/wAN9V8SJapeXMAWK3hfIRpXO1d2Odo6nHXGO9dz7d683/aC1jwbpvwx1ODxxLIm j3uIFjt1zO8udy+UP7wK5z0GOaj2NPsc/tZ/zM+Xfhb+2Z42uvH2mWniOS01PR9QuI7aWKK2WNoN 7BQyEemRwc55r7qeMfMpAIPBGBX5l/DjxF8MvBPj611m/g8R65ZWU4mtYZLeCIBlOVeQCQl8HnA2 5wOK/Q/4f/Ejw98T9CGreHb9L62ztkQjbJE2Puuh5U/p6UKjTTvyg6s2rOTOj8mMdETH+6KPJT+4 v/fIp1FaWXY5+WPYb5Kf3F/75FHkp/cX/vkU6ijlj2D2cewixpuHyL/3yK8i0vQ/7Cm1OPzBK1xe zXBIGANzfdH4AV6+vUV4Frnh3xR4Nm8R+K79pJ9N0yC81GK3+1FhIyqzRKV7jO3I/CvkuIslq51Q jh6c1CN7vS9+x7uUY6lltSVVwu3t0NHxZ488JeAJIY/FHinS/D9xMoaO3vZ/3zKf4tigsB9RV3w/ 4g0bxhpZ1Pw7rVjr+nqdr3GnzrIEPYMAcqfqK/JDxB4k1HxfrV7rer3kl/qd/KZ57iVss7Hn8vQD jHHavRv2YviFqPw9+Mnh2S0nlFjql5FpuoWqsdlxBKwRgR0yM7h3yor5mp4f5fLDezhJqpbe/X0P djxLiVU5pJOPY/TeiuLu/hR48jvJkguZJIA7BHa+IJXPHfriov8AhVfxB/57P/4MD/jXzn/EOa3/ AD/S+R6n+tlL/n2/vO5orhv+FV/ED/ntJ/4MD/jR/wAKq+IP/PaT/wADz/jS/wCIc13/AMxC+4X+ tlL/AJ9v7zuaxvFnjrwn4AaFPFPirSfD0067ooLyf96w9fLXLY9/51gSeF/FngPTdV8T6y0s1hot hcak0K3Zk81oomdEKg8gsB/k1+XnibxJqfjHXr/W9ZvJNQ1S+lM09xKSWdic/gB2HYCvXy/w+o06 jnjajkuiWhyYjiipUjahDl9dT9bvD3iDRfGOltqfh3WrDxBp6na8+nTCTYfR16r+Iq7z/WvzD/Zp +Imo/Df4yeG7uylkFpqF5Fp9/aqTtuYJnEbKw743AjuCOK/ReX4N+M5L68WLWVt7dZXEDTXUhJUM dudoODjGaxxvh5CpVcsJV5Y9nr+JdDilwhy1o3l5aHoei3dtpmh6rf3cayQ2sZlbKgnABJAz64rw nx18SrnxwkUMlja2NtDK0iLbj5jkYwxzg8e1W9Y+EPxot9TszZ+JbB/DpLpqGlWd1I8l2ChCktJE uACRkK3I65r0fwf8CbLR7ix1HU7l7u6jAka0wPKEnYE/xAGv0zJMvnleAhhZy5nG+vc+QzDF/XMR KstE+h4Fb2815cRQW6NLPIdkarksWJGAMf5xmvsPSdMW10mygnghaeOCNJD5an5goB7etR6f4W0f Sbp7iy0uztJ26yQwqrfgcVqV7i02POUrbaHA/F34kWnwp8Mi/jtIJ9RuH8m1hIChmxksxHO0D09q +XofjlqkfiIaydC8Ove795Y6cobP1Bzn3611P7WWuSX3xAstMBPk2FkrbR03yHJP/fIQfhXiFTyr fqfMY7F1JVOW+i29T9APh345tPiN4VtNatV8sy5WaE8mKQfeUn+XtXS8eg/Kvmz9kLUrqC58RaVM GWBo4byNT0ycjI+oK/lX0nUexp9j6DD4ipVpRk3r8w49B+Vc/wCPvHGl/DjwfqfiPV5BHZWMW8qu N0jHhY19WY4A+uexroCwUEkgADJJOAB61+dP7XHx+/4Wt4qGhaNOW8K6RKwR0Py3k4yGl91HIX8W 71UcNTm7OJOLxkqELuWvQ8f+IXjrUviV4y1PxJqrZu76UuEUnbEg4SNQeiquAK52iivWglFWS0Pi ZSdRuUt2FFFFUQFfYP8AwTa+C/8Awm3xQufG2oQ7tJ8MKBb7l+V7xwduP9xct7Fkr5H06wudWv7a xsoXuLy6lWGCGMZaSRiFVR9SRX7Yfs2/ByD4GfCPQvDCBTfpF9o1GZQP3t04BkOe4B+UeyiuetPl jY9bL6HtanO9onqSqFzin0i9KWvPPrQooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACii igAooooAKKKKACiiigAooooAKKKKACiiigAooooAazV+cP7VXig+Jfjfr7I7NBYeXYRgnp5a/Nj2 3sx/E1+jrNtUk9K/Ob9qrwNJ4M+MOqSqP9E1f/iYwEf7ZIdfqHU/99CsK3wnFitYWO/0HUl1jQ7G 9XGJ4Vf5c4BxyPz/AJVfryT4a/ESx0XSItM1R5Ih5jGGfZlFQ44Pfrn24r1e3uoby3Se3lSeFxlZ IzlT+NeNJcrZ8+1ZklFFFQQFFFFABRRRQAUUUUAFFFFABRRRQBwvxq+HSfE74e6jpCgC/QfaLKQ/ wzLyo/4EMqf96vznngktZpIZkaKWNijowwVYHBB+hr9Uq+Kv2uvhd/wi/i5PFNjDjTNYY+eFGBHc jkn2Djn6hq9LB1LP2bMKkbrmPn+iiivWOYKKKKANjwh4s1XwN4l0/XdFums9SsZRLDIvTPdWH8Sk ZBB6gkV+qPwL+NWlfHDwTBrNji2v4sRahYsctbzYyQPVCASp7jjqDX5LV2/wd+L2t/BXxjBr2iyb lx5d3ZyMfKu4c5KMB37g9QQDRqehhMU8PKz2Z+u/TI70lct8MfiVofxY8IWniHQZ/MtZvleFseZb yD70bjPBGfoRgjrXU1J9XGSklKLugrlfiZpmian4Rux4gma3sYSJBOn3436KU9Wz2rqq8K/aW8QN 5mk6KjfJhrqVR3P3UB/JvzrSmuaSO3C03UrJJ2OH8I+K/DXgbXP7SttPv9YniJEElxKkAT/a2gNk 4969Oh/aW0Tycy6TqCS/3EKMPzyOPwr51b7pPcCvrjwZ4L8OLoelX8OiWK3MtrE7SeQCSxQZPPfO a7KyitWj2cZClTSlNNtjvAfjbUfG3m3TaHJpOkqv7q4uZcvK3soGMD1NfGH7bnjabxN8Vv7BgZms fD9sqFBnAmcBnY+4BRc/T1r7/XHGcY6fhXw/8XPhfqWi+G/jN421m2kt7jUdXjsrDzgNzW/nqWkH s21FHsp9a4Hboj5+TUpNpW8j508B2lnqHjrw5a6hCtxYTajbxXELkgPE0qhlJHPIzX1J+zn4a/4Q j9qzxp4e8O3M83hyyt5o7jzG3Dhk2Kx7lXJUH0U18q6PDc6Rq2g37o0UctwksD/3gsoBIHsw/Sv0 1+FPwg034U2mqGC4k1LWNVunutQ1KdQHncsSBgdFGTxSMzu6GYKpJIUDuxwKK5fxs8y/ZlGfIOSf QnIrxM5zF5Tg5YtQ5uXp/n5Ho5fhPruIjQ5rXOnVgy7lIZemQc0tch4Nkl+2TKMmHblvQHjFdfWW R5r/AGzgo4rk5G21b07eReY4L6hXdLmutwqrq2l2uuaXeadexCezvIXt5oj0dHUqw/I1aor6A8s/ K34u/sN/EXwD4ju4/D+jz+K/D7SE2l5YYaVYyTtWWPhgwHBwCD1r0z9kr9ifxRaeO9L8Y+PdOGi6 fpUourXS7hla4uJl5jLqpO1FbDcnJIHGM1+g1Kfm680rIrmYlFFFMkKKKKQFfUtNt9Y0+70+8iE9 pdwvBNE3R0YFWH4gmvy5+MX7DXxD8A+JLpfDmj3Hizw88ha0urDDSohPyrLHnIYdMgYOM+1fqdRT K5mj89v2Tf2KfFMPjrTfF/j3TjoenaTKt1babMytcXM6nKFlGdiA4PPJI6d6/Qml/WkoV1sJu4UU UUCCj69KKKAPCfjV8M08vx54xumSVpdOghs415MW0oJHPbPHGO2a+UvLfyRKUIjLFd3bdjOPyr74 +LFmdQ+GfieBRlm0+UqPcLkfyr5cuvAzR/s32uumPEx1ZrktjnymXygfpkUHz+Nw/NP3F0b+Z9F/ A/w5YWPgPQNWjt1XUrrTIYZrgcF0Usyj8N36CvQ+e1c/8O7NtP8AAHhu1YFWi06BCD1yIxXjf7U3 7TFv8JdKk8P6FMk/jC8i+8uGWwjI/wBY4/vn+FfoTx1aXM7Hq88MPRUp9jjP2zP2jl0e0uvh94au gb+4TZq15C3Nuh/5YAjozcbu4HHUnHw9Uk1xJdTyzzSPLNIxeSSRtzMx5JJ75JNR16MI8qPlMRWe Im5yCiiirOUKKK2vBfg7VPiB4s0jw3osBuNU1K5S3gTsGY4LH2UZJPoDSexUYuTsj6x/4Jv/AAGP jTx7cfEHVbbfo/h1/LsRInyzXpXO4f8AXNSD7My+lfqD+lcN8Hfhbpfwb+HGh+EdKGbfT4QrzYwZ 5TzJK3uzEn8cV3WK8ypLnlc+1wtFUaSj16gBS0UVmdgUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAU UUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAMavzu/a78Uf8JF8bdThRg8Ol wxWK4HQqN7/judvwr9Cry4js7aWeVgkUSl3YnAAAyT+lflN4l1qTxZ4t1PVp/MZ9QvJLh8nLYZic fgMflXPWeljgxcvdUTLm6KoxgKOjZHqf1PStLw/4q1Pwvcebp9yY1Jy0Dcxv9V/qOay5ZDLK8hOS xJJ+pptcjV9DzN1Y988HfEzT/FGy2mH2HUT0hc/LIf8AYP8ATrXY18p7iOhweoI45r1P4f8AxUdX i0zW5Nyn5Yrxjz6BX/oa5pU7ao55Qtses0UdRkHNFYGIUUUUAFFFFABRRRQAUUUUAFc78QvBNl8R PB+paBfhRFdR4SQ9Y5Byjj3Bx+o710VFUm4u6A/LzxF4fvvCuvX2kalEYb6zmaGVD6g9R7EYOfes 2vsD9sD4SHV9LTxrpkGbyzUR6hHGP9ZD/DJ9Uzg+30r4/r6ClU9pBSOGS5WFFFFbEhRRRQB6N8D/ AI4a78DfFiappbfadPmIS/0yRiI7mP8Ao47N+HQ1+nnwy+J2gfFrwrb674eu/tFtJ8ssL8S28ndJ Fzww/XtX4+123wl+L3iL4M+KY9Z0C4wGwt1YyEmG6j/uOP5N1B5FJnpYTGSoPllrE/XevHfHXg+b WviNqurXUDHS9M0jzlZh8ryhH2geuDkn6Ctv4J/Hjw38ctBF5pE4t9ThA+26TMw8+3Y9/wDaQnow /HBzXX+MFL+EdaAG7dYzYUe6Grg3F3PscJWV+eDvfQ+MxBI1uZgD5QYIW/2sZA/SvsL4czG48A+H 3Jzmyj5/DFfN1nobN8HdQ1Tb9zVogG/2RGVI/NhX0b8MVK/Dvw6p6iyjrprtWPZx8+emvJs6avE/ 2yVLfAHWyATie2P/AJFH9cV7ZXMfE3wDa/E7wNqnhm9nktYL5FUzxAF4yrq4YA+6iuI8A+CviV4J k0P4YfBPUhEd97bzByo5Ja4EqfmsnH0r9HpP9Y/fk15/42+DGh+NPD3hfRpi9rZ+Hru2ubXywCSs I2+Wc9mXgmu/znk9aAAcn2rk9e8SP58ltDFHJEvDNIu7Jrpryb7PazSd0Qn9K81JJO49WOa/JuO8 3r4KnTw2HdnK7fp2fkfb8N4GnXnKtUV+XY6Xw94iInW2mjjjSQ4DRrtw3vXVV5ioLNlRyo3fl3r0 mzlM9rDIeS6Bj9SKvgTNq2Mozw1Z35bNPyfT5BxJgqdGcatNfFuiWiiiv1Y+I16hRRRQAUUUUAFF FFABRRRQAUUUUAFFFFABRRRQAy4hjuoJIZVDxSqUdT0KkYI/Kst/CekyeGR4fawjOj+SIBZ/wbRj A/MZrXr5b/aS/bBtPBcdz4a8EXMN/r53RXWpoQ0Nl2ITs8nX2XPOTwGo82hhWqU6MeeZ0n7Sn7Tl h8G9NbQNBeK78XyxYSMfNHYIQAJHHdsY2p9CeOv546pqV3rWoXN/f3Mt5e3MhlmuJmLPIx6sSepp l7e3GpXk93dzyXN1PIZZZpWLO7HqST1JqCvQhBQR8niMTLES97boFFFFaHEFFFFABX6Of8E2v2dn 0XR5vihrlqVvdQja30aOUDMdvnDzY7FyCo/2QezV8k/so/s/3X7QnxStNIdHj8P2O271e5XgLCDx GD/ec/KPQZPav2a03TbbSdPtrKyhjtrO2jWGGGJQqxooAVQOwAGK460/so9/LcNzP2stuhbVTt56 0+iiuM+kCiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiii gAooooAKKKKACiiigApG6UtFAHA/HS+utN+DvjC4s08y5XTZgq+xXDfoTX5iQKqqxyCFQ43Z5JwO PfnP4V+sviTSI/EGg6npcpIivraS2YjsHUrn9a/KbVNNn0O6vNPuVZJ7e4a3lXIxuQkEfnXLW6M8 3GJ6Mo0UUVzHnBR74oooA9i+EfjZ9Qi/sS9k3zQrm2kbqyDqv1H8q9LH618w6DqT6PrVjextsMMy sT7ZwR+RNfTwIIypJU8jNctSNnc5pxs7hRRRWJmFFFFABRRRQAUUUUAFFFFAEdxbQ3lvLBPGs0Eq NHJGwyGVhggj0IJH41+fHx7+E83wn8bS20KM2iXu6ewmPPyZ5jJ9VPH0we9foXXGfFz4Z2XxW8GX Wj3G2K7X99ZXTDPkzAfKT7HoR3FdWHrexl5MiUU0fm7RV3WtFvPDmrXemajbta31pIYpoXHKsP6d 8985qlXvehxbBRRRQAUUUUAavhfxVq/grXbTWdC1CbTNTtW3RXEDYI9QR/Ep7qcg199/AX9sfQ/i pZx+G/GLQaD4knT7Os7Ni0vSwx8pP+rc/wB0nHoe1fnfRQdeHxVTDu8HofrvbfC+0tfhvL4R+0kx yxtm7Kc+YTnzNvtx+VdXo+mR6LpNnYRHclrCsQYjBOABmvzo+A/7Z/iX4Wi30jxCsnifwymEVZH/ ANLtV/6ZufvAf3W/AivvT4b/ABY8KfFnSRf+F9Xh1BFH723ztnhPo8Z5H6j0JpttrU+qpY+OJVm7 PszrqKKKg6QooooEV9QtWvLGeBWCtIhUE9K43xFZrY3kECcqsSjjucnNd1XM+IrNrrXrBQCQ4A/J iTX5zxnlsMVhPaQj+8bS+TZ9bkGMlRrODfu2b+djJ8NwrNrCRyJldrBlP0xXdxxrGiqowqjAHtXN 6baNb+LroYwoVnA/3q6Wq4KwP1LB1Iyj7yk1fyViOIMT9YrRcX7rSf3hRRRX6IfKhRRRQAUUUUAF FFFABRRRQAUUUUAFFFKMlsAZNACVn+IPEWmeE9IuNV1m+g03Trcbpbm5cIij6nv6AZJ9K8h+NH7W XhD4TLPY20q+IvEaggWFnINkTYP+tkHC49Blue1fB3xV+M3in4xax9t8Q35e3jbNvp8GUt7cf7Kd z6seT/LWNJy3PNxGOhR0jqz2j9oL9szUfHEdxoPglptH0Jsxzagx2XN0DwQMcxp/48c84HFfL3Bo orujFRVkfL1qs60uabCiiiqMQooooAKu6Lot94k1iy0nTLaS81G+mS3treIZaSRjhVH4kVRbAGTX 6Nf8E6/2YW0PT4/il4ls8X95GV0O3mTDQQtw1wQf4nHC/wCzk/xConNQVzsw2HeIqJdD6O/Zb+Ad h+z78MrPQ4/Ll1u5IutWvE5864I5UH+6o+UfQnqTXs3vSdqWvLbu7s+0hFQXKhaKKKRYUUUUAFFF FABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUU AFFFFADWFfK/x6/ZDuvGWvaj4k8K3tut/dN5s2m3I8tZHxyySDoSexGPcV9Unmm4+aplFSVmROEa itI/JvxJ4W1jwfqj6brmnXGl3ydYbhMEj1B6Ee4zWXX6p+OPh7oHxD0d9N17Tob+Aj5GcYkjP95G HKn6V8T/ABu/ZQ1r4brPq2gGbXfDy5Z/lBuLVf8AbA+8oH8Q/EDrXLKk47Hl1MPKGq2PBKKMg4I7 80VgcYHpmvp7QdQGraLYXikbZoUbjoDjkfgcj8K+Ya9Y+DvjBFjOg3T7W3F7ZmPBz1T69x+PpWVS PMjOcbrQ9Voo9aK5DmCiiigAooooAKKKKACiiigAooooA+d/2rPgmfFelt4u0aDfrFjHi8hjHzXM I/iA7sv6jjsK+Mq/VX73H555/SviP9qD4H/8IFrTeI9HgI8P6hJ+8iQcWkxPK+yN29DkV6uFrfYk c9SPVHg1FFFemc4UUUUAFFFFAB7Vo+HvEWq+E9Wh1TRtRuNM1GE5S5tZCjj8R1HseD3zWdRQO7Wp 9qfCH9vi5ght7H4gaebuP7v9sacgDj3kh4B+qY+lfXHgr4heG/iLpovvDesWuq2+AW8l/njz2ZD8 yn6ivx5t7gw8YyP1rY0LxHfaBfx3+k6hcaZfRnck9rM0Uin6qRWyjCS03PUo5hUp6TV0fseDRX5/ /Dn9uzxl4ZWG28TWdv4pslAXzm/cXQHrvA2sfqvPrX0p4D/bC+Gvjfy4ptXfw7etwbbWE8oZ44Eg yh59x9KzlTlE9uljKVTZ2PbKY0CPMkpUGRMhW9M9abZ31tqVstzZ3EN3bvys1vIHQ/QjipaxlCMt JK53Qk18LGLCizGULiQrtLe2c4p9HvRSjGNO/KrXG5OW7CiiirJCiiigAooooAKKKKACiisTxR46 8OeCLU3HiDW7HR4gM5u51Rj9Fzk/gKBOSju7G3RXzF48/b08HaEskHhnT7zxLdj7s0gNtbfmw3kf 8Br5i+I/7VXxD+JSyQXGr/2NpcnH2HSQYUK+jNkuw9ctz6Y4raNKT3POq4+jT0WrPub4pftMeBPh QssF/qq6jq6A40vTcSzBhxhyDtj5/vEfSvjL4vftheM/ias9hp8n/CL6E4Km0sX/AH8i+kkvX8F2 j614R3JzknqTzmjb7V0RpRj5nh1sdVrKy0Qv8+9JRRW+x5wUUUUCCiiigApeT05NJXoPwN+CuufH n4gWPhjRIynmHzLy+Zcx2cAPzSt/IDuSB60m+VXNKcXUkox3Z6n+xP8Asvy/Hnx0NX1iBh4J0aVX u2bIF5KOVt1PcdC/oOOrV+uFraxWlukEKLFDGoRI0ACqoGAAB0GMVzfwx+HeifCfwVpnhbw/ai10 3T4hGox88jfxSOe7MeSff0xXW4xXmTm5s+zwuHjh4WW4tFFFZnYFFFFABRRRQAUUUUAFFFFABRRR QAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFA BTJF8wAYBHcGn0UAfJH7Sn7K8V3FdeKfBlmIrxd0t5pFuuElHUyRAdG9V6HtzwfjvGOvFfruy5+l fDH7YnwZh8H69F4s0iAQ6VqspS6hjGEiucE7gOwcAn6hvWuapDqjzcTR+1E+b6VWKsGVirA5DL1H ofrSUfpXKecfQHwx8TXPiXw2HvMtc28nktMR/rAACD9eRmutrxP4b+PIfCsh07UMpYTESCUfN5Tk A5wP4SCOOxFe0W9xFdQJNBIk0LjKyRtlT9CK45xszlknckooorMgKKKKACiiigAooooAKKKKACqO vaHZeJtGvNK1K3S6sLyMxTQv0IPf2Pv2xV6imnyu4H50fGb4S3/wj8WS2E2+fTJ8yWN6V4lj/uk9 N68Aj8e9cDX6V/Ez4c6X8UPCtzoupLs3Ze3uVHz28uPldf6juDX54+OPBOqfD3xNeaHq8PlXdu3D KDslQ/ddD3Uj+o7V7uHre0Vnuck48phUUUV1GQUUUUAFFFFABRRRQBNHdPHwTkVajuY5uCce1Z9B 5raNRxA6/wAM+NvEPg26E+g63qGkS+tncvGDznkA4PPY5r2bwv8AtvfE3w+qx3tzp/iCNR01C1AY n1LRlelfN8dxJHwDkelWo7pJMBvkPvWqlCpubU61Sn8MrH254d/4KHWLfLrvgy4hIUfvNOvFk3Hv 8rqMD/gRr0fRf23vhZq0iJPf6hpTsuS17ZNtX23Lur84v1FFN0Ys7IZhWj1P1P0n9pP4Xa1GWtvH GkoM4/0qQ25/KQLW/Y/FjwTqgJs/F+hXQBwfJ1GFsH04avyS/X8KayK3UA/UZqPYLudEc0qLeKP2 EXxZoR6a3pv/AIGR/wDxVRz+NPD1rGXl17S40H8TXkYH/oVfj95Sddqk/QUvlr/cX8hR7DzH/aku kT9Zrv40/D+xkeKfxt4fikT7yNqUW4fhurmtU/as+FGkyOknjK0ndRnbaxSyg/QquP1r8wPwx9BS U1RXch5pUe0T9Btc/b2+Henr/wAS+x1rV5N2MJbrCB75dq808Sf8FCtVm3LoHhCztBuOJdRuWmYj 12qFAP4kV8iUVXso9jmlmFaWzseu+Kv2rvih4ujeKfxPNptu3Bi0mMWuf+BL836815Te3tzqV01x d3Et3cOctNPIXc856nn9agorVRUdjjlUnU1nK4UUUVRiFFFFABRRRQAUUUUAFFFS21tNe3EVvbwy XFxM6xxwxKWd2JwFAHUkkCgZo+E/CureOPEmnaBoVlJqOr38oht7aIZLMe/sB1JPAAJr9jv2Xv2c tK/Z1+H8OmQbLrXrwLNquoheZpcfcX0jTJCj6k8k157+xP8AslxfA7w+PEfiGCOXxvqcWH4DDT4T g+Sp/vn+Ij6dBz9Vba4KtTmdkfVYHB+xjzz3Yq9KWiiuY9gKKKKACiiigAooooAKKKKACiiigAoo ooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiii gAooooAQ15l+0Z4fj8SfBbxTbNGHeO0NzHkfdeMhwfwxXptZ2v6THr2g6jpkpxFeW8lux9nUqf51 MldWJkuaLR+SqkkZ9eafGvmSKvPzEDgZNWNU0y40TUrvTrpPLubSZ7eVD/CyMVI/MVDb/K7P/dUk fNg56DH44NefsfPv4mNkbzJGbgAnICjA/AVqeH/FeqeGJw+n3TRqT80L/NG31U/zrJopNX3FurM9 78D/ABItvFkgs5ovsmo7S3l5ykgHXaex9jXZV8t6bqNzpF9FeWkxguIzlXHb/EdeK9V8P/GmN1SP WLQxuQMz2vI+pU9PwJrnnB9DCULbHp9FUNH8Qad4ghMlhdxXGPvKpww+qnkflV+ucys1uFFFFAgo oooAKKKKACiiigA69a83+OPwasvi94bMWUttctQXsbxuzH/lm57o36da9IoqoycHzITSe5+XGuaL feG9Xu9L1K2e0vrVzHLDJ1Uj+YxznuKo195ftCfAW3+Kmk/2lpiR2/ii1T9054F0gyfKf367W7Hj oePhO8srjTrya0uoJLa6hcpLDKu10YcEEdq9+jVVaN1uccotMhooorcgKKKKACiiigAooooAKKKK AHxzPGeDx71bju1YYY7DVGitIzcQNUcjI5orNjmeM5DGrUd6rffGD69q6Y1VLcCxRQrBhkHiitiA ooooAKKKKACiiigAooooAKKKKACiiigAoooo9RhX6S/sI/scnwfb2nxG8b2ONemTzdJ0ydMmyjI4 mcHpKR0H8I9zxyX7Cf7GYvHsfiT49sSIFKzaLo9wn3yOVuZVPYdUU/7x7V+iSL04xxXFVqacqPo8 vwfKvaVF6Cxj5T2p9FFch74UUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUA FFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFI33TS0jdORm gD4v/a++BN3b6tcePNEt2ns7gA6nBGOYnAx52B/CRjd6EZr5Z+7bs2TtdtoO3jABJ59eRxX63T26 XEbxyRq8bqVKuMgg9QR6V+aH7QHhvS/CPxb8Q6Ro6CKwt5wyxgECJnUOVHsCQB7CuSpG3vHlYmio vnXU88ooornOEUDcQB1NWG/Me4qCP/WD86m9BU9QFjuprG6jmgleCaPlZEO1gfrXtfgv4mWeraSP 7UuY7bUIRiXcCFcdn6ce9eGyHMjH3rSs/wBzpc8hx83AyM/56H86UoqSsS4p7n0tb3EV1Ak0MiTQ uMpJGcqw9QafXCfBmaOTweUWYSNHcPuTPMeQMfgea7uuSSs7HNJWYUUVzPjTxqPB/wBl/wBGW6M2 4lfN2YAx7HrmlZvYLX2Omori9J+K+kX0tvFcrLYPMNu6XBQN9QeOe5xXanIJB602mtxNNbiUUUVI gooooAX8K8K/aM/Z7j+I1pJr+hosPiaCP54+FW9RR90/7Y7HvwK90pV61pCo6b5kJq6sflbcW8tr cSQTxvBNGxR4pFKsjDggg8g57VHX21+0V+zrF4+t5fEPh6FIfEkKbpoAMLfKB+kmO/fp6V8U3EEt pcSQTxvDNGxR45F2srDggjsa96nVVSN1uccocpHRRRWxAUUUUAFFFFABRRRQAUUUUAFFFFADo5Gj OVNWo73dw/HvVOirUpR2A1FYOMhgRS1lqzJypwasxXx4WRc/7S10xqp6MC3RSLIr8qQRS1tvsQFF FFMAooooAKKKKACiij1ycD19KBh+lfcH7Ev7E7+MJbD4g+PLIx6GjLPpWkzDm9I5WaUf88s4IX+L r06w/sW/sQyeOGsPHfj6zaLw8pE2naPMpDX392SUdovQdW+nX9Kbe3jt4UiSNY44wFVVUBQB0AHY CuOrV6I+gwOB1VWr8iWOIKigDaABgAcCpqKK4z6IKKKKACiiigAooooAKKKKACiiigAooooAKKKK ACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooA KKKKACiiigAooooATFfOH7Sn7MbfE27bxL4ekSHxEsYSa1lOI7tV4Xn+FwOM9CMdMZr6PprRhual pS3IlBTVmfkz4g8M6t4T1aXTNY0+40y+jOGhuUKn6j1HuOKza/VTxp8P/D/xA0s2PiDTINRg52+a MPGT3Vhyp+hr4Y/aQ/Z4HwbntNT0y7ku9AvpmiRZxmW3kxuCsw4YEBsHrwfx5Z0+XVHlVcO6eq2P F4R8pb8KkGVyfQUxflUA4yDmiYkR49TXMcRD6CtS/BttOt4Txnkjd/SqFtH506JjJJq3rMm64Eec CNcdMfj75/rVFE3hvxNfeFtSW7snGT8skTfckX0Ne2+F/iRpHiaNU84WV50NvOcc/wCyehr58qSF eSc+1RKCkTKKkfVPXpXB/Fjw3Nq2lx31sC8lqCHjA+8h7j3FeY6P4t1jSeLXUZ441xiNm3J+RyK3 Y/iRr91H5L3kYEnyFhCgODx6e9Y+zcdmYqHLszrfh/4e8OalpscxEOp30YXzfNXPlMewU/zr0Drz Xkdrpd/8JdaTU7x0vNKuf9Hle3+8vcHB9CM16fo+uWOvWv2mwuUuIs4O3gqfQjqDUSu9SZXepdoo orMgKKKKACiiigA57V4X+0J+zpB8R7eTXNCSO18TRId8f3UvVA4VvR+OG79DXulL7du/vVwnKEro lrm3PywvrG50y8mtLyCS1uoXaOWGZSrowOCCD0NQV95/Hr9nyw+Klm+pacI7DxREgCTnhLkAcJL/ AEbt3r4a1zQ9Q8N6tc6bqlpLY31uxSWCZcMp/qPccGveo1lUXmcs4crKNFFFbmYUUUUAFFFFABRR RQAUUUUAFFFFABRRRQAqsVOVJU1YjvSv3xkeo61Woq4ycdgNOORZBlTTqylypyDzVmO8ZfvjcPWu mNVPcC5RTI5km5VqfW+5AUUU5FMjqiqWZiFAUZJJ6CgY1iFGTwK+6f2Lv2Gn8RPZeOviPYNFpalZ 9M0OYYNz3Es4/udMJ/F1PHFdL+xr+wh/Z7WPjr4lWGboYm07w/cDIi7rLcKerdwnbgnngffaxrtG OlcdWr0R9DgcBa1Sp9w2GEQoqqqqqjAVRgAegFT0UVxn0IUUUUAFFFFABRRRQAUUUUAFFFFABRRR QAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFA BRRRQAUUUUAFFFFABRRRQAUUUUAFFFFACHpWVr/h7TvE+lz6bqtjDqFhONslvcIGRv8A6/vWtRQI +XPHX7D+i6l5k/hbVZtGlx8tpdDz4PoG4ZR9d34V8z/Ev4J+L/hexfWdKf7BnC6hbHzbdiTgfMPu n2YCv06qnqGnwapZzWl3DHc2sylJIZV3K6kcgg8EVjKlGWxyzw0JbaH5QaMgN4GbhVUse3AGT+lV rqTzLiR8LyeqnivqPxp+xnr2n61q0/hWa0n0mUmS0t7iXbLGDz5eSMHB4BzyDzXzDqml3mi6ldWG oW8lpfWsjRTwSjDI4OCD+INckouL1PLlTlD4ipU8XEY9+agqxgAcDgVFzK5NGuE9AT6VseH4La41 rToLtttvLcIrnOO+cZ+uKyYwPlXoOKbqEhURKDg/e4PvU76CPovxRoS+JNBvNOYqrTL8jHorDlT+ deJ29j4k+GurLd/ZpERflZlG+GVfQkV13w9+KUl3Pa6Rqq75ZD5cN2DyT2DDuegzXqZ6EHp3FYJu OjMk+XRnO+EfG+n+MLd2t8w3Uf8Arbdzll9we49/zroaz4/D2mw6kt/FZQQ3igqJok2tg9c46/jW hWbtfQzdugUUUVJIUUUUAFFFFABXm/xm+CGj/F3Sv3wWy1uFcW2oovI/2H/vJ+o7V6RRVwk4u6eo WvufmT418D6z8Pdem0fXLRrW6TlW6xyr/fRu4NYFfpZ8RvhrofxQ0F9L1q3345guowPNt3/vIf5j oa+Efi18Gdd+EerGG/T7VpkrEWupRA+XKPRv7rjuDXtUcRGotdzjlBp6HA0UUV1mYUUUUAFFFFAB RRRQAUUUUAFFFFABRRRQAUUUUAKvByDg+tTx3jrgMciq9bPhHwjq/jjXLfSdEs5L29mOQqD5VX+8 x6KvuafM4K9wSuSaNY3XiDUrXTtNtJr3UbqRYre1hQtJK56KqjqTX6c/sf8A7DNn8LBZ+MPHMMWo eL8CS1sTh4dNyOvo8v8AtdF6DJ5ryn4IfAHSvhFaLeSMuoeJJFxLfbeIfVIv7o9+px+FfRvhf4u6 54d2QzSf2laDjy7kneB/sv1H45rklmCk+Rnq4NUqcuaotT6Tj+7Tv1rivC/xU0PxNsjE/wBju2H+ ouPlP4Hoa7JW96tSjLVH1EZxmrxZJRRRVFhRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUU AFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQA UUUUAFFFFABRRRQAUUUUAFFFFABRRRQAxo91fm7+0/oOsaP8aPEM+rQFEv5/tFnMqkJJBjCYPQkA AH3FfpJ2rj/iR8MtA+KOgvpeu2X2mMEtDMh2ywOeNyN2P6HHNZzjzIwrU/aRsflvGu51HvViPDSD Hr2r3H4i/sgeMvBdxPPosf8Awkulc7GtQFuEX/ajPtnlSeleL3Fhc6TdyQX1tNZ3MZ+aG5iZHUns VbkfjXDKLT1R4soSg7SQsY3Oee+Pek8RWq2WrS26lyYQqPvGCHwNw+gOR+FbPg7SzrHiLTLNSuJp huLdAo5JOOwAOa5q/uftmoXNxncJZWcNknIJ46+1SiUtLjLe4e1mjmjbbJGwdT6EHIr6U8L+Ibfx Ro8F9Aw3MNsseeUcdR/nsa+Z62/CPiy98J6kLi2O+F8CW3Y4WQensfeonHmVzOcebU+kqKyvDvia w8UWIurGQHs8THDxn0I7f1rV49D+VcduXRnPsFFFFAgooooAKKKKACiiigAqjruhaf4n0ufTdVs4 7+xnXZJBMu4Ef0PuOlXqKezug3Ph/wCN/wCzDqPw/afWfD/m6r4dyWdMbp7Qf7QH3kH97t3xXhVf qsRuBBwQeuec/Ud6+cfjZ+yfaeJPP1rwasWn6ocyS6aTthuD6p2Rj+R9u/qUMVpyzMJU+qPjeire raTeaFqU+n6hay2V7AxSSCZSrKfcf5FVK9O91dHNtuFFFFABRRRQAUUUUAFFFFABRRRQAUUV9A/B H9li/wDGnkaz4pWXS9DOHjteVnuh/wCyIfXqe1ROpGmryKUXLY87+E/wZ1/4tap5WnxfZtNib/Sd SmU+VEPQf3m/2RX3X8N/hboPws0RdP0W2w7YNxeSAGa4b1ZvT/ZHAroNF0Ow8OaXBp2l2kVjYwDb HBCu1VH+Puau14tbESqaLY6owUQooorkNArrvC3xR1zwxsjSf7baL/y73BLAD2bqP5VyNFXGbhsX GcoO6Z9HeF/jDoviLy4p5P7Ou24Ec5G1j/st0Nd5HIsigqcg8jFfGvrxnNdN4Z+ImueFWRbW7aW2 HW2uDuQj27j8K7qeKf2z1aeO6TPqbd6UGvNvCvxs0jWtkOoZ0u6OB+8OYifZu344r0WGaOaNXjdX RhkMpyCK7ozjPWLPUhUjUV4smopM+lLWhoFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQ AUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFAB RRRQAUUUUAFFFFABRRRQAUUUUANkBI4OKzdV8O6Xr0Yj1PTrTUYwchbuBZQD7bgcVqUUAeJfGzwf 4Y8AfCfxdrOkaHpumagLJ4o7qG3VHRpCI8qccH5u1fngAABx0r9C/wBr7StU1b4KakNMRpRBcQz3 UaDLGBSd2B3wdrfQGvz0H1yK46uj0R5OK0klYWiiisDiLWm6reaPdrdWNxJazr0eNufp7j2NemaN 8ZLtEWPULCO5K8GWBthPH93oPwryuP74571pWqBsE4y3PP8An0/nUSSZMkmel33xeuYwr2+nQ+Vu wUklJcj8OnX3rpfB/wAQNO8WM1uitaX6qS1vIc5A6lT3H614rqknl+XGRghd2GXGMjPB/EfnWbp+ oT6XewXls5SeFg6bfX0/Hp+NZuCsS4K2h9S0VHbzG4t4ZmXY0iK5X0JGSKkrmOdhRRRQIKKKKACi iigAooooA4X4pfBvw78WNP8AL1W38nUI1xb6lbgLNF6DP8S/7J49Mda+Jvir8D/EnwnvCdQg+2aS 77YdUtgTE3oGH8Dex/Amv0TqG8srfUbWa1uoI7m2mXZJDMoZHXHQg9RXVSxEqfoRKCkflhRX1t8W v2PYL1p9V8DyLbTcs+kTtiNv+uTn7vptPHuK+WNc0HUvDOpS6fqtjPp99CcPBcIVYf4j3HFezTqw qK8Wcji0UKKOPWkyPX9a1JFopNw/yRRuH+SKAFopM+9LQAVq+GfCur+MtYi0vRbGbUL6TkRwjO0f 3mJ4Ue5r1T4R/sw+IPiEYL/VBJoOgsQ3nTJiedf+maHp/vNx7GvsfwH8OfD/AMNdJGn6DYx2yHBk nPzTTH+879Sf5VxVsTGn7q1ZtCnfc8r+C/7LOleBPI1bxH5esa8p3rFjdbWrdflBHzsP7zdOw717 1yepyaSivInUlUd5M6VFR2CiiisxhRRRQAUUUUAFFFFABW94b8b6z4Vcf2feMsOcm3k+aI/8B7fh WDRVJuOzLjKUHeLse9eFfjlpupbYNWjOnTnjzRloSfr1X8fzr0i1vYL6FJYJVnhflZI2DKfcEV8e 1reH/FOq+GrjzdNvJIOctHnMbfVTxXbTxTWkkelTx0o6TWh9b0n4V5H4X+PFrd7IdbhNnJ0+0Q/N GfcjqP1Feoafqlpqlus9ncx3MLdHjYMP0r0I1Iz2Z6tOrCorxZeopMilrQ2CiiigAooooAKKKKAC iiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKK KKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAgmhWaF43VXVgVKsMgg9iPSvjH9qb9m 3SfB2h3HjHw1G1nbrMovNOHzRIHOA6Hqo3EZXpzxX2o1YfjPwvZeNPCupaFqC7rTUIGgf1GRww9w cH8KmUeZWMqlNVI2Z+UPrxiiuk+IfgDVfhp4svdB1WIrPCxMU2MJPGT8sin0I/LpXN157Vjw2nF2 ZJD95jkjjHHvWtZp05wM465Hbn+dZluoOO/OeOtbVoDEHfBJRdwK4BHp19yKlmbM/U5A0z7flUnA CElcZ9/bFd98GLXTLx7zzrDzb+EiRbh03qi46DPANeb3jbpMdec9MV6N8D9Ujg1C/wBPcgSXCrLH 6sVzkD3wc/gamS91hLY9hbrSUUVxeRyBRRRQAUUUUAFFFFABRRRQAjyLEMscVnXWtJCDtXn1NTXt u0mSpzXOajaSZPWmvMdia68VOuQrY+lcJ4+0vRPiBYfZNdsY75VB8uZsiWL3VxyPp0rVvLOXnisS 8s5eetbQ913iWkmrHzF8QP2e9U0aSS58N3H9rWfJFrKQtwnsP4X/AE+leK6hJdabdPb3UEtrOv3o pkKsPwNfd1xZy5OAa5zxF4N07xJD5Gp6fDex9vNT5h9GHI/CvQhiLfEQ6Kex8V/2k3qKBqL7q+kL 79mnw3dTl4GvrIHqkcu9f/Hga2PDfwJ8MeHZElXTzfXC8iS8bzMH1C/d/St/rETP2DPCPBPw/wDE XjmVfsFo0dqT815c5SIfQ4y34V9OfDH4N+HfA8kV7eoNc1deRNcKPKjP+wnP5nJ+lb9rYvGioi7U XhVUYA+laVvZynHWuOpXlPRG0aUYnoVr4ulwP3h6Vs2viUyD5gG/CvPrKzl4HNb9lZy8VxtIbiju LfU451BPBq3kN0ORXPafZyYAxW/EpjjAPWsnuZjqKKKQBRRRQAUUUUAFFFFABRRRQAUUUUAFaGi6 9qPh+48/TryS1k77G+VvqOhrPopp8ruhxbi7xPZfC/x4DbYddt9h6farccf8CX/CvV9I1yw1y1W4 sbuK6iP8UbZx9R1H418h1b0vVLzRbpbmwuZbWZf442x+fr+NdsMTKPxanpUsc46T1PsHIo4rxDwt 8eJ4dkGuW3nr0+024w31K9D+GPpXrGh+KNM8SW/nafeR3C91U/Mv1HUV3wqRnsz1qdaFRe6zZopq tmnVsbhRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQA UUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABTJFDLzT6RqAPOvjB8 G9C+MGg/YdSjMN5GCbTUIh+8gb+q+qnj8a/P/wCKHwh8SfCXVWtdctG+zOxFvqEQJguBz0bse5U4 Ir9ROaz9Z0Wx8QafNY6lZw39nMMSW9wgdGHuDWcqakc1ShGpr1PyjtF+YDsMDk/jWhMwismLAEsc AN19Tgjp2r7l1n9jX4f6pdefaw6hpALbmisrkeWfYB1bA+laEv7Jfw7m0caedNuQQSRdC7fzQSMZ z07dMYrldGVzh+qz7n54TMWkOTnHA70+zvJrG6iuLeVoZ4mDpIh5UivVv2gvgHcfBXVLSSK/W/0X UGcWsj4WZCuCUdR1xkfMP0ryOs2raM5pw5XyyPZfDfxktLm3jj1eCS3uBwZoV3I2B1I6j8B3rs9F 8U6X4hZxYXqTuoyYyCrgeuDXzlbL+7AB59c1b0fXpvD+vW2owAs0TcqeN6nqp/AmsJUlujmcOx9L 0VgeH/HWj+JIkNtdrFOw5t5yEcHuB6/hW/3I71ztWZjZhRRRUiCiiigAooooAKZJBHL95QafRQBR k0e3kb7uKo3HhWGTJ7VuUU7lJs5aTwTGynBGapSeA9/TbXbUVXMw5mcN/wAK/wDZT+NA8A7f7o/G u5oo5g5mcdF4HCnB21bj8GxLjJWumopczDmZkw+G7eHGetXYtPhj4CZqzRSuxXYioqcKAKWiikIK KKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAqeyvbjT7hZ7WeS3mXpJExVh+VQUU9ndDWj uj1Pwv8AHa/0/ZDrEAv4unnxfLIB6kdD+leueHfGek+Kod+n3iSuB80TfK6/VTzXyhUlvPLazLLD I0MqHKyISCD7EV108TKPxanfSxk4aS1R9kcfWl/Cvnrwv8bdW0kpDqa/2pbD+MnbKPx6H8fzr17w x8QNF8VRhbO7UXGObeX5JB+Hf8K9CnWhU2Z69PEQqbM6iim7h606tzpCiiigAooooAKKKKACiiig AooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKAC iiigAooooAKKKKACiiigAooooAKKKKACiiigD4Y/bn8THUviNpGiK5Mem2PmsmOkkrZJz/uov5V8 2AbsAV7d+2No8Gk/Gq8livZLqW/tobqaGQf8e5xsCA9wQoP4mvFIP9YP61wVPiZ4Vd3qO5cXhRzw M/e4+lUGO5iffPNXZvkhb1xj1qko3MB71kjBE6Eqo55Azk81638KvHFtJpI0vUr4R3cT4h+0v9+M 4wAx6kcjGa8jm5Rh749KbbruU5zhjj696UoqW4pRufVA+ZQRyD0IPBorw74f/Ej/AIRjzLS/WW4s JWBRl5aE9MgHt7CvZdK1qx1y1FxYXMdzF6oeR9R2NcsoOO5hKLiXKKKKzMwooooAKKKKACiiigAo oooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACii igApY2aNlZWZXU5DKSCPoe1JRRr0A73wv8Zda0ErFeMuqWijGJjiRfo/+Oa9g8L/ABN0PxQFSC4+ zXR629x8rZ9j0b8DXzFSj1zg9c11QxE4eaO2li6lPRu6PsoNuXrmnA14D8LfilPpd4umaxcyTWch Cx3EzZMTdgSf4T+le9JIHUMDkHkYr1KdRVFdHuUa0a0bolooorU3CiiigAooooAKKKKACiiigAoo ooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiii gAooooAKKKKACiiigAooooA+L/24vhzdQ65pvjO1iL2U0K2V468+U6kmMn0DAkfUe9fLdmPm3c49 vz/niv1i1rQrHxFpdxpup2sd7Y3KGOa3mXcjqexr5i8XfsL2NxfSTeGdebT7eQ5FrfQmYRj0VwQS Prz7muWpTbd0ebXw7lLmifHt02I1XjcfwI9qgi+/6/jXoXxj+CfiP4Q3tqNYSKaxuiy297auWjZh /CcgFWxzg9e2cV5/CpKk468dK57WPPcXB2Ykx+6CenNPX5Yc+2f8/wCe1RyEPIe4zjg9qkmb5OS3 J/lSEQVb0vV73RLxbmxuJLaZf4kPB9iO4qpRR6ge1+C/izb600dnqypZ3h4WYcRSf/En9K9C/wD1 18pde1dLpvivWtNt0gttUuY4h0j37gPz7VjKnfVGUqfVH0RRWF4Hv77VPDNrdahIks8m4rIn8SZ+ Un3x1rdrmtbQwegUUUUhBRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUU UUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFAARmvTPh98X5vD8aWGr+ZdWK/Kky8vEPQ/wB4 frXmdFaQm6bujWnUlSlzRPsHT9WtdWtIrqzmW4t5BlZIzkGre6vlfwZ461DwVeeZbv5tq5zNaufl b3Ho3vX0P4V8aad4uslmsph5oA8y3c4eM+hH9a9elWjUXme9QxUaytszo6Kap4p1dB2hRRRQAUUU UAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQ AUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUm0UtFAHFfFL4b6Z8VPCN5oGpiSOKXbJDcR8vBKudrr n0zyO4JFfEnjr9lHx54HE08Fimv6fFk/aNNO59vq0R+YH6A/Wv0PBprKe1Zygp7mFSjGpufkXtZZ tjjayEhgw5BHUH3zSTHO0d8Z+lfU/wC0N+y/4nvvG2r+J/DVpHqljqDCeS0gcJNC+AGAU4DAkE8c 5Jr5e1KyudNv57W9t5bS6ibZJDOhR0I7EEZBrjlFxep5E6cqbsytRRRUGQ+NdzL/AIZzV/dty391 c4zjFU7Zd0mcdPzqe6+W3JH8TY6cUmBu+C/iDqHhJvJVRd2LnLW8jEbT6qe3vXqFj8WNEuRD532i 0Mh2lpUBVc+pB6e+MV4TbrumHH+en9TVvUmxHGgPPX3/AP1VDjGRDij6eVlZQykMp5BU8cjPHrRX N/Dfzz4J0o3DF38ttuTn5N52D/vnFdJXI1ZtHM1yuwUUUUhBRRRQAUUUUAFFFFABRRRQAUUUUAFF FFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABVjT9QudL vI7mzme3uY+VkjOCP/re1V6KafK7jV73TPW9K+P91BbLHf6Yt1KowZYZNm73wQRn8a9E8B/EC08d Ws7RRPbXEBAkhcg4B6EHuDXzDtPpXrf7N6xXj67ewSeZFG8dqWU5UsBuIz6gMPzrvoVpylZ7HrYX EVJzUZO6PcqKRaWvTPZCiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooo oAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAjZcsOa8H+P f7L9j8Wr19c0++/snxF5SxF5QWguAv3Q4HKkdNwz24Ne90mBSaT3IlFTVmflj8QPhf4m+GOpfY/E GlyWoYkQ3K/NBP8A7jjgn26+1cpX6y6/4d03xNpM2narY2+o2Uw2yW9xGHVh+Pf3r49+N37HF5oa z6z4GSbULIZeTR2O6aP/AK5H+Mex+b61yyo21ieZVwzjrDY+Z7VflJx/n2pt433VGM4ycGrT2c9i z29xDLbzIdrRyoVZfqDyDVG6bdM5PO3jBrnOLXqS2MW+TPT8Mmk1CRmusE8KOBnP5VY05cDcc4Ue nP5d6oTHdI546/hQB6v8HvGQaIaBdN86gtaMe46lP5kV6pXzBo2pT6LfQ6hbnbNbsGUkZBPoR6EZ r6V0q+Op6XaXflmLz4lk2E5xkZxXNUjqc9RalqiiisDIKKKKACiiigAooooAKKKKACiiigAooooA KKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKZNIYYZZAh kKKWCL1bAJwPypgcJ8UteaC3g0yCR0kkIeUqcfLzhf5Gvq/9l7w7/wAI/wDB3RmZNk1+ZL6TjGd7 fLx/uBB+FfCs0l14t8QRqFV7u/uFjRFY/eYhFXnpjiv000LSotE0ix0+DiG0gSBPoqhR/KvUw8Fu ezg4q7ZpLS0UV3HrhRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAF FFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABTWXNOoo AzdQ0Ww1OMi7sbe7GOk0Svn8xX5WeLLS6s/FerwX1n/Zl0t5KJLUpsELFydoHYDjGO1frHivMPit +z94V+LWy41KCSz1WMBY9SsyFmwOitkEOPZhWVSHNsclej7RaH50Z8myc4xkYABwRWZn2r6m+IX7 Feq6L4dnu/D2tjW54MymxmtvJd1HOEbcct7cZr5aZSjEEFWU4IYYIPvXHKLjueVKnKno0LgeWBkZ Yn64+neu88JfEy+8NafbW9xCt5YhyAN2JFT0X8d3B9K4Z124HP7tehIyOM8YqW8wvlQqclVAPy4y cdfrkn8qhrmVjOSuj6Ph8UaRPp8d8uo24tpMbZGkA69j6H/A1Xm8caDAMtqlu3/XNt38q8KKCKzh T5d5OW4w3HGP6/jUY4rL2ZnyI9yb4ieHlXP9oqfpG5P8qZ/wsnw7/wA//wD5Bk/+JrxCj8T+dTyI XIj2/wD4WT4d/wCf/wD8gv8A/E0f8LI8Pf8AQQ/8gyf/ABNeIfifzpcn16c+9Hs0w5Ee+6X4u0fW pjFaahDJL2RiUZh6gNjI+lbG09+K+W7hyZAAeS24Eeo7j3rptF+JGvaLhFu/tUK8CO6Xfx6Z6gfj Q6XYTp9j32ivPtB+Mem3jrDqcTadKf8Alop3xfn1H413ltdQ3kKzW80c8Tch42DD25FZOLjuZtNb ktFFFQSFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFA BRRRQBnfDj4fG/8Aj14dkSPdYb2vZFx8qGJcgf8AfWwivt4V8y/CC+az8faeFHyz74n49VJ/oP0r 6ar18K04Hv4G3sroWiiiuw9EKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKK ACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooA KKKKACk2ilooAjZfmr8p/HV1/aHjzxBcGBbTzdRuGMKrgR/vG4x2r9WZF3fSviX9sr4PweF9Yj8c abthtdUm8m8t1IXbclSRIvqGCtkeoz3rCtG6OPFRcoprofM9uonuEUgAO3I+6Mex7cU92+0Xw3n7 zZOWz7nmlsV2mRwCNkZ5C7hk8fyz+VTaPH518XJO0Hk4yOuenfoa4zyNS/eZWXYSf3ahME9D3A9s 1BTmbc7Hjk546U2pJCiiigAoZgqk9+3rRUdwT5IXH3j3/KgCkcNOPYZPPWl56dM02M7mdzn5u+Ke vGT2HNAEX35sgAAHsM9K0NN1a+0ibzLG6ltXzn925AP1HQ/jWfD3Yjt61J+OKW4tzv8ASvjBrNvH tu4oL1VA+ZkKN17kcZ/Ct2P40RPuJ0h1GRjFwDn1/hrymP8A1f8Avcmp0/1a5HXmp5Ik8qPS7j4y OYz5GlKr+sk2Rj6ACsuT4vays3m+TaCHP+qKHGPTOc5ri6huvlGB0zjp+dHJEOWJ7J4R+KVl4huk sbuP7BfPwgJzG5x0B7H2P5129fKe8rIHQ7WDblb+Rr3zwf8AEbTdc0+FLu5jsr9FAlSdtqsQPvKT waicLbEShbY7Cis6bxJpNvHvfUrUL/szK38iavQTx3UKywyJLE3IeNgyn8RWBkPooopAFFFFABRR RQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFA0dn8CJLfWviVNDE3mnS7Vp5mXlUdjsV Sf733j/wGvpuvnT4BXWg+DbzxHdXl6lpd6lNE/73hdqrjAP1JP419CW91HdQpNC4kiddyupyCPWv Zw6UaasfQ4OypJInooorqO4KKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKA CiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAK KKKACiiigBPeuW+IngfS/iB4R1HRNWtmuLadCRs+/G4BKuh7MD0/LpXUg0N900mriaurH5Ishtbe VWXbL5hQqxIddvBBHrkn8jVvSV8u1nk6HG1ecHnj/Hp6198fGD9mXw18SrG9u7O1j0jxFJmSO9gy qPJ1/eJ0OT1OM96+b9M/ZJ+JFzbm2k0y0sirffuLyMocd1KljjnpgdBXDKnJHjVMPOL91XPGKK9/ g/Yr8dSKTLd6PC2en2h2z/45VyH9iLxe0YL61pEbd1HmHH44qfZy7Gf1er2PnSivo7/hh/xZ/wBB 3Sf++ZP8KP8Ahh/xZ/0HdJ/75k/wqvZy7D+r1Ox84NUF44GR1OPw9K+l4/2HvFLMA+vaSi+oWQ/0 rz34j/swePfA8Ml1/Zy63YqebnTCZCoHd4/vfiAR9Kn2cl0D2NSOrR5Ai7VAx1ok+WMj14qR1ZZC pDKy8FWHI9jUMzbVUduW655rMx1Hx/6vOD1z7elLSLwox6dqfGAzLnpnvQSTbe3OAMVYxjjFQph5 FyBjrU1ABjdx68VVuZA2Wz2LZzyM8Yq03Ct9PSs+6O7IPrgZ9BQBW/hq7YruOTyuc/L+tU60bWMK vzc9uf5VRRcZhDYTOw+9x80efc4Pbpj8al8J+NtU8K3GLWQS27Nl7aXlG9x6H3H61V1RvLs4UGPm +b5Xz7cjt0/lWZbruY9h05Gec1O4n5nsVr8ZrWSNPO02VGyA2yUNyfQY5/HFdP4f8daP4kbyrW4M dzjP2ecbH69ux/A14LJ8sSDGBycHp6cVnu5WYOGYOnRl4IPtWTpJrQz9mmfVNFeG6X8UNf02BFe4 jvVQY23Kbif+BDBP513Hhz4taVrEi298P7Nuc43OcxMf97HH4isnTaM5QaO6ooVgw3Agg8gjpRWZ mFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAjttRjgnjtyTX1X4Ds207wbo1tKCsqWsZ ZW6qxAJH4E4/CvlWtu38a+ILW3SCLWbyOFBhUEpOB6Z9K6qNVU7tnbhq0aDbZ9YrR6182+HPjFr2 j3Sfa7htTtcgPHNjdj/ZbsfrxX0Ppl9HqWn213FnyriNZU3ddrAEfzr06dWNXY9qjXjWXul2iiit jpCiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAoooo AKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKT60tFACbRR tFLRQAm0UbRS0UAJtFIyntTqKAOG8XfBnwX463NrPh6yuZ263Cx+XNnGM71wfzr5w+Jn7DlzCz3n gvUhcR9f7N1BsP8ARJeh/wCBAfWvsb60jLuqHCMt0YTowmtUflZ4s8C+IfBF40Gv6NeaVJk4a4jI RvdX+6w9wTWNDyxPoO3rX6x3un2up27213bw3MD/AHopkDqfqDXlviX9ln4b+ImeQeH10ydiD5mm ytB+G0ZUf981zyodmcUsG/ss/PaH+I1JX23J+xP4G85WjvtYSPPKeepz7Z21s6P+x/8ADnTG3z2N 7qfGNt3ePt+uE21HsZGf1Wp5HwVI2xc5wM88dBjPSsyY8gfnzxX6S6j+zb8ONQtFgfwraRhRhZIG eNx77gwJ/HNfL/x//ZTm+HOnXHiLw3cTajocXNzbzgGa1XpuyPvr6nGR1ORSdJx1JlhpwVz53Ubm UHua1raMttXkk8YX/PrWbbITN9OK2rFUWVS23aoyQ2QPXFYnMUdblLXQQ8mPA+Zdp4FQWa9SOv15 qK7ctcSH37HI/CrdlHtZcgn+fHJxR0Ex9xjcR24Xjpxz0rOX55BkZBPpVu6Y7S3Occk9ear2q7pP XApoEWZPlVB264z1A9P1qj3JPJq3ctw3fgDgdc8/hVSmtBrQ6fwp8QtU8KssaSfarLvbSk4H+6f4 f5e1e0+F/Gul+LIv9Em8u5Ay9tLxIv4dx7ivm+nwzPbyLJFI0bqcqysVIPrkd6zlBSIlFM+qqK4f 4X+Nn8TWElretnUbYZLcZlX+99R0NdxXLKLi7M5mrOzCiiipEFFFFABRRRQAUUUUAFFFFABRRQ2R z29aACiqGoeINM0sN9qv7eFl6q0g3fkOa5+7+KGiQHEJuLtskHyo8D65bHFVyt9B8rZ1/NLtNeW6 l8XLxlP2OxhgBxgysZD/AEFc9e/ELX77duv2hVjnbCipj6HGf1q1TbLUGe5N90novcnjFfWXg64+ 2eFdHn2hfMtImwvTlB09q/NfQRqfi3xLp2nteXU815cJb/6xmJ3sFPf0NfpzY2sen2dvaxDbFDGs ahRgAAAD+Vd+Fhy3PWwNNxcmW6KKK7z1gooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKAC iiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKK KKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAqhq2nQavp9zYXUQntbm J4ZY2GQyMMEfkav0UCPhLxp+xh4v0HWJ/wDhGlg1zSGYmEtOsU8S9lcNgMR6g8+gqpYfsm/EaTTb uZtPtbWULiOCS9TdJ7cZA/EivvfApNufasHSizkeFg3c/JfWtB1Hw7rFxpmr2U2n30L4lguE2spz +v1GRT4vlhc8bSPqOa/S/wCInwd8LfFK1SPX9MS4ni4ivISYp4v91xzj2OR7V4/qP7DfhqSIrp/i HVbRt24NMscoH4ALWTovpscs8LO/us+I7lgzYGDz9afZqOTj3+v+ea9Z+L37MXi34XxvqCINd0RB 815Yod0PP/LSPqo9xkfSvKI8R25Ix0/DP/66wlFx3OWUJQ0kiG5YtjPJJJPNQ0+b/WYxyvFMoICi iigDb8G663h3xJZXmSIQ+yUDvG3Df4/hX0irKyhlIYMMhl6H6V8p9eoz7etejeC/i1LpEMGn6rGb izjGxbhf9Yi9sj+ID86xqQvqjKceY9noqK0uob62iuLeRZYJVDpIvQg96l/nXMc4UU2SVIV3yyLE mcbpGAFYl5450Kx4fUopG5+WEGQ8fQcfjQNJs3aPTjBPSuCvvi/p0YP2SzuLhscNIQgB/Xiufvvi 5q0+5baC2tFOMfKXYfieP0q1BsrkZ68AW4HJqvdX9tYqGubmGAEZHmOFz+deFX3jLW9Qz52pTgZz sjbYo/LFY7MZGy3zH1bk1fs/Mv2fdntt98SNAswwF59pYDIW3Qtn2zjH61g33xigViLPTXcZ4a4k C5H0XP8AOvL6Kr2a6lciOwvviprt1xE0FoOf9VHk49Mtn+Vc9eeINS1LP2q/uJgRtKs5xj0x0qhR VctirITaPSpY16nvxTFqaPiMdvWrGMmztUe+TzUdPm5kbnjpTKSA9g/ZT8ODxB8YtLkZQ0WnpJet n1VcL/48yn8K/QCvlT9h7w2Vt/EmvMrDcYrKNj0OBvb+afnX1Z/DXoUY2jc9rCxtTT7jqKSlrY6w ooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACi iigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKK KACiiigAooooAKKKKACiiigAooooAKKKKACk46UtFAEbIrKQwyPevPfFXwF8A+Lo5RfeGbFZZMkz 2kYgkye+5Mc+5r0ak59aTVyXFS3PiL4qfsU6toaT6h4Mu21i1Ubjp1wQtwo7hW6P9OD9a+aLyzuN Pupba7gltbmJikkMyFHQjsQeQa/XPsa83+KnwJ8LfFqzYapZCHUlXEOqWoCzx+mT/GPZsj6Vzyop 6o46mGT1ifmdRXqvxZ/Zy8WfCeaW5mgOraIpyuqWaEqgzj94vWM/+O9s15V/OuZpp2Z5kouLs0FF FFIk7jwl8QtV0DRGs4lhlt1ciIy5zHnkgYPTPrS3nxA1+/BD6hJCp/hgURj6jHIrnIFEdrEv8RBc 8YPJ/XinVnZEaEtxdTXjs88skzsclpGLE/nUVFFUMKKKKACiiigAooooAKKKKAD2qyDtYdBgc9qg jXMgH9alkYqjEnHbOalvsBBnPPWlUbiBSwxvcMVhR5WHUIpY/pXV+GfhX4u8UXlvDYeHdSlWZgqz tbOsS54yzkYAHXrTUXdWKUXLRI+2v2X/AA2PD/wb0UsmyW+33r8YJ3n5c/8AAQv5V632rP0PS4tD 0Ww06E/ubSCO3TPXCqFH8q0D3r1IqysfQQXLFIWiiiqLCiiigAooooAKKKKACiiigAooooAKKKKA CiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAK KKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAoo ooAKKKKACiiigAooooArzW8dxE8ciLIjjaysuQR6EV+e37Unwch+FnjhLnS4fJ8P6sGlto1HywSA /vIh7cggehI7V+iBFeS/tL/Dk/Eb4U6pa28SyapY/wCnWfqXTllH+8u4fUis6keaJz16aqR8z836 VVLMFGOSBSfp+FWtNjLXiNz+7BfKjOMdD+eK4DxS/IoVyoAwvAwSelJRRUkBRRRQAUUVf0nw/qmv SGPTNOu9RcYBW1gaTGfXaDj8aAKFFep+H/2YviN4g2FdAOnRscGTUJlhx77cliPoK9L8P/sN6rMF bW/Etraf3o7CFpT7fM23+Vaezl2No0KktkfMOPek3cgcZPTnr7Cvunw/+xx4C0lUa+Goa1Jjn7Rc eWmfUKgU/gSa9L8P/Cnwf4V50vw5ptqwIIkW3VnyOh3HJzWyovqdKwcnuz87PD/w98T+Ksf2R4f1 HUEbpJDbMU+m4jb+teleH/2RfiFrexrm1s9IiYZ3XlxyPYqgYg1967AO2KNo9KuNFdTeODgviZ8s +Gv2HbWHa+ueJpbg8ZisbcRjHcbmJP6CvUvD/wCzH8OvD6x40BNRlX/lrqEjTE/VSdv/AI7Xq232 peK1UIrZHTGjCOyMvTPDOlaKoGn6ZZ2IUbR9ngVDj04FaXl07aKNoqzWyEVdtOoooGFFFFABRRRQ AUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFAB RRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFF FFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFNZetOpNooA+bvjR+yHovjCO61Xwqs eia6S0ht14trluuCP4GJ7jjnkd6+K49PuNLury3u4jb3UEn2d45AQyOpIYfgVxX6yMua4PUPgb4G 1bXrjWb3w3Z3eo3D+ZLJMhKu2MFimdpJ75HNc86XNscVXDqbvHQ/N+1s7i+lEVrby3MuOI4ELt+Q 5rvNB+AHxC8SbTZ+Fr2NDgiS7C264PfLkZ/Cv0P0vw7puiQLDp1ha2MS9I7WBY1/ICtDb+FKNFLc zjg19pnxV4f/AGJfFV5tbVtY03TI8jKxbp3x+SjNek+H/wBiPwlY7G1bVtS1aQfeVCtvG34KC3/j 1fRuPelP0rRU4rodEcPTj0PO/D/wB8AeGdptPDNjJIox5l0nnsf++813ltaw2cKxQQxwxqMBI1Cg D0AFWGpPxrRK2xuoqOyHUUUUygooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAoo ooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiii gAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKA CiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAK KKKACiiigAooooAKKKKAP//Z Walker Wieland OEHHA Research Scientist Walker.Wieland@oehha.ca.gov Walker Wieland