20211029 15302600 1.0 FALSE CES4_Climate 002 -373976.129300 539719.617300 -604512.649500 450022.491300 1 0.000 Projected GCS_North_American_1983 Linear Unit: Meter (1.000000) NAD_1983_California_Teale_Albers <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/3.0.0'><WKT>PROJCS[&quot;NAD_1983_California_Teale_Albers&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;Albers&quot;],PARAMETER[&quot;False_Easting&quot;,0.0],PARAMETER[&quot;False_Northing&quot;,-4000000.0],PARAMETER[&quot;Central_Meridian&quot;,-120.0],PARAMETER[&quot;Standard_Parallel_1&quot;,34.0],PARAMETER[&quot;Standard_Parallel_2&quot;,40.5],PARAMETER[&quot;Latitude_Of_Origin&quot;,0.0],UNIT[&quot;Meter&quot;,1.0],AUTHORITY[&quot;EPSG&quot;,3310]]</WKT><XOrigin>-16909700</XOrigin><YOrigin>-8597000</YOrigin><XYScale>266332319.7555542</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>3310</WKID><LatestWKID>3310</LatestWKID></ProjectedCoordinateSystem> 20230417 17284400 20230417 17284400 625000 5000 Esri ArcGIS 13.0.0.36056 CES 4.0 Final Results 1 -124.506026 -113.502228 42.068501 32.423801 This file contains data used in the latest iteration of the California Communities Environmental Health Screening Tool (CalEnviroScreen 4.0) <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 4.0. CalEnviroScreen is a screening methodology that can be used to help identify California communities that are disproportionately burdened by multiple sources of pollution. The 4.0 report and supporting documents are available at: http://oehha.ca.gov/calenviroscreen/report/calenviroscreen-40</SPAN></P></DIV></DIV></DIV> OEHHA, CalEPA CalEnviroScreen 3.0 CalEnviroScreen 4.0 OEHHA CalEPA Environmental Justice <DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>Review the CalEnviroScreen 4.0 report at: </SPAN><A href="http://oehha.ca.gov/calenviroscreen/report/calenviroscreen-30" STYLE="text-decoration:underline;"><SPAN STYLE="text-decoration:underline;"><SPAN>http://oehha.ca.gov/calenviroscreen/report/calenviroscreen-40 </SPAN></SPAN></A><SPAN>for guidance on CalEnviroScreen use. </SPAN></P></DIV></DIV></DIV> Shapefile 0.000 dataset EPSG 6.8(9.2.0) 0 Simple FALSE 0 FALSE FALSE CES4_final_shapefile Feature Class 0 FID FID OID 4 0 0 Internal feature number. Esri Sequential unique whole numbers that are automatically generated. OBJECTID OBJECTID Integer 9 9 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 Tract Double 19 0 0 Census Tract ID from 2010 Census ZIP ZIP Integer 10 10 0 Postal ZIP Code that the census tract falls within County County String 254 0 0 California county that the census tract falls within ApproxLoc ApproxLoc String 254 0 0 Approximate city where each census tract is located based on US Census Incorporated Places (2020, Cities), US Census Designated Places, (2020, Designated Places), and the CA Department of Tax and Fees City and County Boundaries and City Annexations (2021, Unincorporated Areas) boundary files. All tracts that did not fall within one of these boundaries were assigned "unincorporated county area" based on that tract's county. This is for reference purposes only and should not be used to determine whether a census tract falls within a city or town boundary. TotPop19 TotPop19 Integer 10 10 0 2019 American Community Survey (ACS) population in census tracts CIscore CIscore Double 19 0 0 CalEnviroScreen Score, Pollution Score multiplied by Population Characteristics Score CIscoreP CIscoreP Double 19 0 0 Percentile of the CalEnviroScreen score Ozone Ozone Double 19 0 0 Daily maximum 8 hour Ozone concentration OzoneP OzoneP Double 19 0 0 Ozone percentile PM2_5 PM2_5 Double 19 0 0 Annual mean PM 2.5 concentrations PM2_5_P PM2_5_P Double 19 0 0 PM2.5 percentile DieselPM DieselPM Double 19 0 0 Diesel PM emissions from on-road and non-road sources DieselPM_P DieselPM_P Double 19 0 0 Diesel PM percentile Pesticide Pesticide Double 19 0 0 Total pounds of selected active pesticide ingredients used in production-agriculture per square mile in the census tract PesticideP PesticideP Double 19 0 0 Pesticides percentile Tox_Rel Tox_Rel Double 19 0 0 Toxicity-weighted concentrations of modeled chemical releases to air from facility emissions and off-site incineration (from RSEI) Tox_Rel_P Tox_Rel_P Double 19 0 0 Toxic release percentile Traffic Traffic Double 19 0 0 Traffic density, in vehicle-kilometers per hour per road length, within 150 meters of the census tract boundary TrafficP TrafficP Double 19 0 0 Traffic percentile DrinkWat DrinkWat Double 19 0 0 Drinking water contaminant index for selected contaminants DrinkWatP DrinkWatP Double 19 0 0 Drinking water percentile Lead Lead Double 19 0 0 Potential risk for lead exposure in children living in low-income communities with older housing Lead_P Lead_P Double 19 0 0 Children's lead risk from housing percentile Cleanup Cleanup Double 19 0 0 Cleanup sites, sum of weighted EnviroStor cleanup sites within buffered distances to populated blocks of census tracts CleanupP CleanupP Double 19 0 0 Cleanup sites percentile GWThreat GWThreat Double 19 0 0 Groundwater threats, sum of weighted GeoTracker leaking underground storage tank sites within buffered distances to populated blocks of census tracts GWThreatP GWThreatP Double 19 0 0 Groundwater threats percentile HazWaste HazWaste Double 19 0 0 Sum of weighted hazardous waste facilities and large quantity generators within buffered distances to populated blocks of census tracts HazWasteP HazWasteP Double 19 0 0 Hazardous waste percentile ImpWatBod ImpWatBod Double 19 0 0 Impaired water bodies, sum of number of pollutants across all impaired water bodies within buffered distances to populated blocks of census tracts ImpWatBodP ImpWatBodP Double 19 0 0 Impaired water bodies percentile SolWaste SolWaste Double 19 0 0 Sum of weighted solid waste sites and facilities (SWIS) within buffered distances to populated blocks of census tracts SolWasteP SolWasteP Double 19 0 0 Solid waste percentile PollBurd PollBurd Double 19 0 0 PolBurdSc PolBurdSc Double 19 0 0 Average of percentiles from the Pollution Burden indicators (with a half weighting for the Environmental Effects indicators) Pollution Burden variable scaled with a range of 0-10. (Used to calculate CES 4.0 Score) PolBurdP PolBurdP Double 19 0 0 Pollution burden percentile Asthma Asthma Double 19 0 0 AsthmaP AsthmaP Double 19 0 0 LowBirtWt LowBirtWt Double 19 0 0 LowBirWP LowBirWP Double 19 0 0 Cardiovas Cardiovas Double 19 0 0 CardiovasP CardiovasP Double 19 0 0 Educatn Educatn Double 19 0 0 EducatP EducatP Double 19 0 0 Ling_Isol Ling_Isol Double 19 0 0 Ling_IsolP Ling_IsolP Double 19 0 0 Poverty Poverty Double 19 0 0 PovertyP PovertyP Double 19 0 0 Unempl Unempl Double 19 0 0 UnemplP UnemplP Double 19 0 0 HousBurd HousBurd Double 19 0 0 HousBurdP HousBurdP Double 19 0 0 PopChar PopChar Double 19 0 0 PopCharSc PopCharSc Double 19 0 0 PopCharP PopCharP Double 19 0 0 Child_10 Child_10 Double 19 0 0 Percent of this census tract's population that are children under the age of 10 years old. Pop_10_64 Pop_10_64 Double 19 0 0 Percent of this census tract's population that are between 10 and 64 years old. Elderly65 Elderly65 Double 19 0 0 Percent of this census tract's population that are over 65 years old. Hispanic Hispanic Double 19 0 0 Percent of this census tract's population that identify as Hispanic. White White Double 19 0 0 Percent of this census tract's population that identify as White. AfricanAm AfricanAm Double 19 0 0 Percent of this census tract's population that identify as Black. NativeAm NativeAm Double 19 0 0 Percent of this census tract's population that identify as American Indian or Alaskan Native. OtherMult OtherMult Double 19 0 0 Percent of this census tract's population that identify as other or multiple races/ethnicities. Shape_Leng Shape_Leng Double 19 0 0 Shape_Le_1 Shape_Le_1 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. Tract_c Tract_c String 12 0 0 AAPI AAPI Double 19 0 0 Percent of this census tract's population that identify as Asian American or Pacific Islander. Tract_c_1 Tract_c_1 String 254 0 0 ZONE_CODE ZONE_CODE Integer 10 10 0 COUNT COUNT Double 19 0 0 AREA AREA Double 19 0 0 MIN MIN Double 19 0 0 MAX MAX Double 19 0 0 RANGE RANGE Double 19 0 0 MEAN MEAN Double 19 0 0 STD STD Double 19 0 0 SUM SUM Double 19 0 0 MEDIAN MEDIAN Double 19 0 0 PCT90 PCT90 Double 19 0 0 20230417 /9j/4AAQSkZJRgABAQEAAQABAAD/2wBDAAgGBgcGBQgHBwcJCQgKDBQNDAsLDBkSEw8UHRofHh0a HBwgJC4nICIsIxwcKDcpLDAxNDQ0Hyc5PTgyPC4zNDL/2wBDAQkJCQwLDBgNDRgyIRwhMjIyMjIy MjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjL/wAARCADIASwDASIA AhEBAxEB/8QAHwAAAQUBAQEBAQEAAAAAAAAAAAECAwQFBgcICQoL/8QAtRAAAgEDAwIEAwUFBAQA AAF9AQIDAAQRBRIhMUEGE1FhByJxFDKBkaEII0KxwRVS0fAkM2JyggkKFhcYGRolJicoKSo0NTY3 ODk6Q0RFRkdISUpTVFVWV1hZWmNkZWZnaGlqc3R1dnd4eXqDhIWGh4iJipKTlJWWl5iZmqKjpKWm p6ipqrKztLW2t7i5usLDxMXGx8jJytLT1NXW19jZ2uHi4+Tl5ufo6erx8vP09fb3+Pn6/8QAHwEA AwEBAQEBAQEBAQAAAAAAAAECAwQFBgcICQoL/8QAtREAAgECBAQDBAcFBAQAAQJ3AAECAxEEBSEx BhJBUQdhcRMiMoEIFEKRobHBCSMzUvAVYnLRChYkNOEl8RcYGRomJygpKjU2Nzg5OkNERUZHSElK U1RVVldYWVpjZGVmZ2hpanN0dXZ3eHl6goOEhYaHiImKkpOUlZaXmJmaoqOkpaanqKmqsrO0tba3 uLm6wsPExcbHyMnK0tPU1dbX2Nna4uPk5ebn6Onq8vP09fb3+Pn6/9oADAMBAAIRAxEAPwD1aiii u08YKnswDdxggEZ6GoKltW2XUR/2gKmfwsqHxI09SVDa5b7wPy1U0xlW5IbqVwKs6p/x7p/v/wBD Wfa5+1R7V3HPSualG9Fo6asrVkzWuIFKTSRxr5zptLAckDt+prEIIOCMEdq6OqN/aeYvmRr+8zyB 3rPD1VF8r6mmIpOS5l0MmkIBxkdKuQ2LSwtIzbAM4yOtVK7lNNtLocTg0k31EwdxOeMdKGKqMsQB 71Qm1CTe8cMJ3KCcuMcD2rBvruZbvyZre6Z2w3yrhfXrnFZVK6gb0sPKbG3eoWMFzIjXUK4YjAfO Kmn1e3uofNWVPJgGNwOcDA61yutaaqwyXgd1LtnyyowMnuRWFuCwsoPzE8/SvInjKlObuvM9ynga VWCafkd7b6naXkhjgm8xgMkAHpU0mlNrVndWbonluoHzN19/bHX8K8+hla3nSSGVkZed2Mc13Xh3 X/MtWbADoR5pY9c56H0rTD4v2srVXqZ4nBuhHmo7fkeYeIbC90jUfLvI43iiZkTZwFJHHP4A/hVS Cxv21lCXjNwrLOzFgwHOcn1+nvWj441Br3xDdRmRdsTZxzy3APasC3u3s5xLA7btuDu9cfXkf4Vn L2UKlo/Cj36Ea88Km7c7XbTy/wCCegaxqF5cWMv2crEVXeqovGR/9asDQbWPVLi5nUMbmQlcA9AR 16detQaxqzPEkcBPkuMSMhBznBwD271DoeuXfh03Pl28cgn+Qsx6MuehHH8Vd1TE054hOb0W55OH wFangZKmrTey29bv8f8Ahz0/TdFsdMgSOGEszD5nf58nHUn8KsELaRmefytqDkpHgg5ryq/1u41H yBbPLHskACk8MT+nbpVi8uNTs9OkS8kWWGRNgI4ZCR/LNdyzGmk+SGi+48meRV5OLrVFzSeqe+/Q 7weIVE8u6LMQ4TB5/Go9T1COa0iFvc5P8SpkcHpXljTGOJbWKRgwkPmOsnyOexqzeXs9zBEkbuDb R7ZSsnDfNgHrz2rn/tZuLTR2/wCrUYzi4y/D7vvOqbXlilkga5mDQqWIycAAdqmtdTk1C2WdZZSh Jxubng1w8tvfNhJWZvmAAaUHkrkd/TvWxb6tbaXafZA/nvGpZXQfKxPOM1lSx0pT9/RG+JyinCkv Y+9LT7v+Hsd+/iBd/wAkDMuMYYgc1gyOiq0jsFA5JPQCuWk8Q3ssJMaxQsnJPcg4xgGqV5fXc1us F1J8yvuKFMNzzkn8a0rZmpbamGG4fnF6tL8WN1W7jvb1pY0K9sk53Y4B9uKrxWzywTTBkCRAbtxx nJ4Ap1zC4/fFoiruQPLIxx7dhTIlDJKSm7CZB3Y28jn3+nvXjyblJuXU+rpxjCkow2VkSNabI97s QPLD52EjJ5C/iOc1FBbzXMnlwxs79cAVLFGxeITy+VDJzubJBAyOg/Kut0/+zhj7EULFTuZAQDg9 x2rWhRVWVr2OXGYyWGhe3M/wXqQrp+nWf2eNllMrOJEwCSGGO4HTkVse55H1qhqMd1mG4tpVTyQ+ 8H+JTg4/SqV/rrWM6xGBHJQMdsmcHuOlempwotqWiPnHSrYxRcHzS1vrtr5m2AMjJqzBp89xGzx7 SAdp55qnbP5tvHJIpRmUEp6cdK2NGvorTzI3DlpCNu0ZrtpcspK+x5NfnpxfKtUZ01u8E7QybQ69 eaeljdSKGS3kKnoQvWusa2twzyvFGWY5ZmGe3vSG8tVODcRD23iuv6qk9WcP16TS5Y6nZNbTL1if Hrioq6SszVR80R9jXj0sQ5y5Wjvq4dQjzJmdRWhY2sNxAxdTuDYyDTJ9OkSTEQLqRnJrX20OZxZl 7GfKpIsYa+08EgeYDxz1NN0+JAzghS8bYY91JAOD+BB/Gm6YGVZnwSAOB6mrdlNJPYwzzwmCV0DP Geqn0rkqScLwWx2UoqaU3uOa3ja7juSW8yNGQc8YJBPH4CnvLHHEZHdVjAyWJ4ArJ1SaaEmWGXdF KgHyt909iPrRbzyy2Cu6tsz2UtnnHQDNeG8yX1h4dRfMv8zt9k+TnvoazPGqAsyhWIAJOASen51y ep3P9nzywrIsjn7oH8H1/wAK257O4ktWMjKJcA5X5treoyOcGsnVNNlm0yEPKnnbwWkC7N2Op/Gu +hi6ntPZqNm/6uc9WnBrml0OeMsjS+Z5jh88sDjP/wBapL5VN7v88TOUAJHAAyaa8K204LbZAwDf K3BHaqZ8QaP5k1tKnk3EfyhsnYx7/Tv1rsclFWk7BGDk04K/oX5orT+zohtUyseR19e3auf12zt3 05mLJCV5XoAxweKfJrdin7wTCRlJAVM9PXn6VUm16wuJJYZgzW+3AIX72R+YxzXPWq05Rs2jqoUa sJXSfc5xYwtwscu6IY6juD3+mDTXQxO65dQPvKeD16VdlmhiMscA86CQ/eYY2/3Rz6fXmqby+bMZ Wc7gOrDO7/IrzJJLQ9eMm9Tk9SeSS8kaRcYZlDY+9znk9zyP0qpxt6c+ua7nUbDEKia0CRS/MQVw xOe57Vn22m2oidXiMkrN8uSThR0H4Cuhct+W+yOyGNSpp8v3GCUjglMdx80KsQfKYAuQOPXA564p 8UDCUyQzwbYQZEDyA7sexHXj0Fas1jMJHNr5QhkQLKgGMjP04rL1KxNl5QkwGaNSm1CA45ycmiM0 9jWM1J2vv/W39aDbIS3mrRery72A4HXJrsbvS59XhW2t0R33ByHbaMDrzWJ4aEe+Zc7mXDKT0Geu B29/wroJxM9tLFDcS25kXBaNsGvWwdNexblrc+ezXESWLio6ctvx6mY/g1IbZRcXUfmqfnWJgTk4 yOnQYrC1PRjp7x7ZhIjDlmG3B/Oum06zls4WEty8zOQxDc4OOeabqVj9rhO6fyY9uHO0HIBz17UV cLCVO8Y2fqGHzKrTr8tSpzR72/LqcYCXE0roGz3zjaSeuPzpqZdfLCpnO7JwDwPWrl9bQ2Hm227z Zt6kPjGFxn9c/pVKORonDrjI9QD/ADrypJxdmfTU5qpDmhs9i1bR/aJYxcJKwkdUWQOBgDGRzweM d+Kh8g+e8ZdVClhvJ4yM8ZHrin25dwtuYnkWRwVVSQffb2yfoaeylLeEyI8UBfOMnMnJyR2yBxT3 Qm2pWHsVg8uC5D4hywTGA5JHcYOCO/NIl2n2UQfZQYlYO7Dls9OuOB04/wAagvZY57yWSIMIyflD HJA7Vctp7eSPbKh81gsCxQpjcueWPPLfXvj8GnrZESjaCk0QLa3moS+dHAXMrEfIABkDJ+lOsb+8 sZCkBPzdUIyPc49eK1dZiufIjks1aO0iTDRoCrJnn5h+VXNCjikthdDaZDlQgJIiGegz0z1/GuiF B+15Yuz7nDWxsVhnUnFOO1v8yms3iC6t2YQYjYYyUA4Pp3qWDw1ul827uPNZjlgM8n659a7ZNZRb RIdkhKptJyOeMelZPLsABljwAO9en9ThdOUnL1Pn1mlWzVOCpry6jAnlqE3M20YyxyT+NSRTPBKs kbbXXocVeh0W8mjD7VTJ6OcGqdxEIJ5Yg2djlc+uK6uSUEmzzfaQqSaTuWWu7zUmjtmkzk8DGAT7 4qUaDef9M/8AvqpdJmgsrC8vZgAIVLFu+AM4FZUE/inxDCl/aSx2EDDakZ/ix/F075x+FW5RVuZO Un0XYiFOcuZwcYQjpd7Xfoe9m7gH/LT9KjkntZV2uQw+hrPorgjhYrqbvEN6WLLz7ZcwybY8HK7e pOOc/gRj3p1jazx3E1zJdySLMciJuijAAx6dD+ftVSpobh4eAcr6GueWBkp88ZN+RpHELZo1MYqt dXBiKoIyQ6n5zjaOnH6/pVeWaNYWaF2iZnEjkfhnOexArI1G9WSCWKMyXCSnJDkfKMAED0HGfxNe Lj8fTwycJO0jspU3PbYsXpW4WKK3ljto4MF0SMHKj+H2H0qeMtEhTzMRk/Ko4x7e/P8AOsm3hl8+ NmJjVzhW5yT1/kD1q9dad9rt5G+0PCUG5pQRkDn14H/1q8ShWr4n3pRs317r5am84xg7JmnZzbNl tsdhyd2cgfXJzUOuTR21mksuQgbBbsBgnn8qz3luLeMNFJ9odkURoRjcRyTuHGSPoOKp+I4r65sv 3DLPIhJETnAI/qete/gcVLmjBq7OWrCLVm7I4TUtYv8AUWa6srVo7Zchg+BjHA/l2rlZHaR3kfBe Qljjnqa3xoWr6k3+kzJF2CSNjHtgcCodR8M3el2bXUk8TIuAQhOeTj0rmxWLiqihUdm+57OGhThG 0LfL/Mw8jA4p/wB5SF+Vc5+b/GkkAVsL93qM4zSrtMqeYCsZxnHp60lo7HS9VcEKnLOWJznGM5+t WrCdrO4Sby0mGMhWz+f4VM0elLfxok0htWX52IOVPPt9O1Q3cNvBKwtrjzoioIPcH3raMXHXsYyk pe7Z690W9av4dQSB4jIMBtyt91T/AI1j4IAYEc+h5FSOXkfnLEjIxx71PBpWo3KLJBYXMiN0ZImI P44qJuVSV0rsqmo0oJN2RGFV4ixQ7h0Cjt9ayNene4ltHmZQsCbRtOGIBHT0+tdC+kapEm+TTbpR 8o5jYA84x+Jrn9dS4tjFFOhhBSQbZVK56HHr1A9q1jdSV1Y0w7i56O//AAxnwzpuVbUSwvJtXMcm B+JOOf0+lXdK1cRyN9svJAgGAHy27nr7ViqN1uFUtnfzk4Uccfj1qV73z79Z7oGdRwVJxkfh055r qp1pQaa/4B0VsJCrFxkt/v8AxOsTWrGWTyoXeVz0CRsSf0qvqVza3eklxdmONjj5Rksf7uK5+zWR byURzLaO0Z27j1BxhQffPWq0tu8c7Q7lZlBLYPAIGSOfSuh42bi1JbnDDKaMKicJNWs+j/S35jJZ GllZ3dnY/wATdTTKluJI5Zi8UPlIQPk3Z5xzTJI3ikMbqVdeCD2rhZ7cXolsW5LxDpkVurzGRW3H cRtHXGO/eqZZiACxIXoCelOVA0bvvUFcfKep+lS2VnNqF7FaW67pZW2qP6/SnrJpIj3KcXJ6JasQ PE94rCJEiLD5GYlQPc9aiY/OcY68Y6U6OCSabyY13PzxnHSrSaXcSsVhAkYRrJgA5Ib0yPeizfQH OEN2TQzE2rJZJP5ojHmyL0285yOfUc+353YNUa2W4MNxBNh0wZV2F8jBIAPQYFYMcskLExuyEgqS pxkHtTmKzTjhIlYgcA4X+daRqyjszCphITupK6Ooi1+Jbjyrh4yMD95EDtDenP8AMV0mkIbq8gkh w6KwcspGMZ615vbxW5uGWeQmMcDy+rc44yPx5xXW6NrUdpf29nCkyyR/ITJtHAHIOK9LB4u8v3r0 Pn81yxRhfDp3tr29T0fzU2uxbAT7xPGK5K/eOa9mkhB2E/5NS3+pTXrAZMcWPuZ798+tUc46ccV6 1etz6RPmcLh3S96XXoNKRvhZY1kjyCyN0bBzg1tL4gkUYW2jCjhQD0FY1GayjOUPhOidONRWnrY9 qoooqTMKKKKAEdQ6FWGQetZ66dJDKbiNvOk27BG7bUHP3sc81o06N9kgbAOOxrzMwyyli7TsudbP 9H/Wh00MRKn7t9B0dva26yeSHMk772LMTz7A9PwqW2v4RO1lNsjuVUu0a5IC545I5OO1VljVplll wxR2aMquCoOcd+uOM0eTDPcpd3kStcpHsUp0APXnrXg066pylzW5tvu/H9TvtcV72CcNKgKKpKHc NpyDjpWfJ9qa5ijtIofsZRmMhzkNzxj64/Wm3FkXEEJidgSVeaJgu0c8kHr/APXq5BbxsgNuXEKb laMDg9ucjPauKlWrxq+20vrsXOMHHlK8OmQpaKGiVpwuSx67qz2slvP9GmiV1bqsgyK2y0VrCgPy RjaigDp2AqP7Rb3ESyxFJiuWTAzzyM/zrixlL281VqSen/DmtKo4K0UcTr3gaCGzu9Rt5irxIZBF jKnHJ9+ma4HnzQMeW2f4h0NevahclrO486MuvLMh5GAMEYP9a8517VbC9SOOys2gZH3MzIFPTpwa 3weM5/dim0uv+fU76PO1aRjxYycgNxzkHj34pocrgpkHvxSoVL7pC47/ACinRlk/1e4s2MEZ49q9 Ra2/pmz0v/SHF2VAqlgAuGwvrz1r03wjKT4XsidoClw5Y4/iOP6V5gQZld8gbedgq/Fq90mhvpie Wbdn3ncvzcYPXPTIrrwtf2NRyeqtp/XyOHGYb29NQWjvr/XzPX2ZUQs5CqoySTgAVhaxoug+LLdR dNHOYwVjlhm+ZM9cEHH55rmLDxbJFa3MWqSTTLNERGVAJBOQfwrz/UTHGBPDCYZI9rOWQozZ4wD7 5NelUx0JJJK6e5wYTLKvO3zOLWzX9Ir+ILCx0jUZrPT9Rj1CA4IkTI2EHoezH3Hr2rIcoduxSuFw 2TnJ9afOFEmUjeNWAYK3v6e1I0EyqrNFIFcZUlTgj1FebJ3bsj7GmuWKUnd+fX7tBi/eBwDz0PQ1 NdOTKybFjVWJ8tDlVPGcHJ9Kh3Nt25O3OcZ4zSUi7a3J4XnZSiFSFBbDY4xzxn6dutS21lcX7GRA rkvhhvCnPX/H8jUt9crNZwRzQsl4vLuYwN644569MU+3vGsY7c2kqmUqzTKeFPXAOTycfz71pFR5 rSehzTnU5G4JKT+77+zOrh8Aafdyq9tqsnldWjaMFwPrn+ldTpmg6T4egMsSKjKp33EzDdj3PQD6 YridF1u4uXkkkuI4XHGxMqSPXOelY+va7e6jcSQPczNbq/EbMMZHGeK9mGJwtCHtYU/ef9fI+WqY HMsZWeGrVvdW/wDSSv8AMn1jQ3uNRurrRk+2WJbeGgGfLz1UgdMc/hitdLCbR9GD3tt9mkZNjSBQ eucZK5rA8O+IZ/D960saiSGQASxE43AdCD6jn869P0zW7LXraOS2cBweY5VwQcHj0P4ZqMFToVua UXab6dPkbZvWxeFUITjzUo297q9Nn29bWZ5bbaFdOsFw0QlgfDEI4BwfrV/UPDUMcUk1rOwCAtsc Zz9DXfLoGyOVpJN7BTsC8c4qCx0f7XamR2eN92ACvGOOa0WVJLla1Zyz4iqSlzp2S/r+tDyQqw6q R+FWbYTKYV3ERTyAYz97BHavVD4dlKnM0Z9sVmvoRWZAdPjMh+YYRSRj37VzyyqpBp3O+PElGomu X8f+AiI5JznP1rSs9L8yFZbkuiOwVQByff2FT2eiz+aksmIgrA4PzE4roK9mjh3JXkrHyeIxai+W DucTNGIriSPOQrlc/Q1ettGnuYRKCFB6bu9akekwSXf2lirxsS4Xsc+talVTw93eRFbGcqUYbnYU UUVyHUFFFFABRRRQBLAI2lw6gkghWxyuf/1CpY7V2cg8KD1qr0rUt5fOh64YcE/1ryMwwNOpJVH8 zsw9V25SjPG0U+wI2zGQ/GPp9amt3ePUp7fZ+6EaujBfqCCc8nv0FNt9NliaRptQubje+7D7QAMY xgDjnnjFSmzbc7rMVkdQpcKM4Gcflk158KHsKjlCN0/w+86r3RXupV+Ui3kVy5U5wMAZ+br0OP1r mnuTb3BlM4jUnCg8c89T+X5Vq62ZUugo850KqDgE859qwpLRXmWSVRI6sMbjjZjJ496+UzOup4lq S5VG+3X06fM76ELRvvcnQfKcqFySSByOTmvP/EWn/Ybma5VyTLMwAKgbR7fyr1Cxgt2tXEqo4Zjk SYPGAMc9q4vxnpcsGnxTGVXInxlMnC7fvH05/pXTlMIw5qsp6yWnqaKo/aKCWhwqkAj7wOeopyuG wrlyCQTg/wBKnS1uzGbnyJlhxkyLGduPrjFQ7sMHLbsnqRkj+levGSezO1+g5VJLiJWPB9iPrUfQ YYcEcEfzoXlwzEct/nilSJpB8qnPJJJwMVWr2Qtt2HKhxk4xgA8cZrO1O4QwfZGePdLhQzH/AFfI OT7VquGgL/Ko3LhlJ/lWFeW6XmqupikVeELqwwGwTwMdOK0jHlld9C6LUnd7bmZJAv7t1EnlfdeT GRkdSPbkVMshUruuZXtkV48xL8yqc4zngZ+tVpY57R5IH3pk4Ydmwf1p9tYz3SSNCoIjxnJxn6Vv zWO9pON5PQWHTru4t2nihZolzlhjtUSBJNqECMhT8wBJY8kf0FdBoV1bQPcRNvhZmyEfoo+tZmpz zNPJKg8uCd96BcDdtJG7+daypxVNTTvc56eJqTrypSjZLZ/1v/wBhnNtqiy3KLMyKuVDEjO3jJPp 3HtUV39l3OYSWYtxtUqm3HbJznNOiW5SJ7/GVZmjLvzliDn3zz1qnWTeh0wgr3T20JIoxKSoJ3nG xQudxyBiusudES+itQxELRoFYKASeOmfrWBGboWltDbiJ2eQyIYuZEI4wfSuq0uC8htf9LnEj9QO 6+xPeu3BwjK8ZK6f3Hj5rWnDlnCSTTenXt/VzHtvC7C4/fyh4gOAnBP1rtvD9knnBoyEWDGEC8EE EVnA/NnkZ9K6WC8sraxdoGQqnIUHDHp1z3r2MHh6dOV1ofL5ljsRiIJSd/yNOisMeJYGYosRZl6g OOKyF+IERvWtWsNrhtgPnZBOQOy/5xXdPG0IW5pbnlUsrxdW/JC9vT/M7OkwN27AzjGaw28REFcW wA7gvz/KsjUfiALC6MA0zzMAEt5+MZ7fdoqYyhBc0np6MKGWYqvLkpRu/Vf5naUVxen+PJdRmMce khFUZZzcZC/ht5rRPiG57RRD8D/jRDGUZrmg7r0Y62WYmjLkqRs/VP8AJs6Oiua/t+7/ALsX/fJ/ xpP7evPSL/vn/wCvVfWYGX1Kqeq0tJS1556IUUUUAFFFFABU9rL5cwz91uDUFFTKKkmmVF8rujWe aONsM2DTwQwBHQ1Se2g1K02Th+cKxRyp49waig0x7a7hkhkAhiiMSoSScEg9Sfb/AOvXhSdSnJqS v6fqekmpK6NF3SNdzsqr6scCuGnhk/tC7Z/LdfOZ4DuJxn/Paun1eOd7a4DTQxQbE2MwOQwY7s89 MY/WuSEcyXIzOrW6riMh8s59+xr57P6ktKeiVr3/AE/rpc7MKluMmUrZlXdg27LtG5GD14Jzj6Hi i4tknt/scxfyZE2Eckk9fvfhUrsgRfMjjUykB1Zh1P8APpipt6iQR87iM9OPzr5qVSaS06t/Pv12 /I7UtblCx2z2zeUwaANhYRGFUDHI6cjv2qhry2NtZyh9O3SOpxJFCcDIIGWA/StoRRxQqJXLiM7t 8pBI980XJiNq4mBaJhtOOcg8f1rWNeKxCnBO1/v+61/uv3GrqOrPKWKhgUXaeowc45olb98xYMpJ OR0ODVi+jih1a9jVjEiSuqhRnuRiq4dQ28EFsfxLnJr6+MueKfc2tqRjbkE5PrUnlrucnKhcHb1J /GmjasmDjg9QM0pCiX91yOvzcUJaFN66GTaaFqt7qKCFPtUiciLeSQo5wM13n/CMLZSTNqcsZ2oC DGcYwMnPHJwMVzkN7PbT+fbyPDLnIdGIOPSpL7ULm/nEt1LvYrzt4/ya3jVpqL5ld/gZ1/bVZKzS VvmVpxuM207VmUqSoAJXke/vXOXtpOklvbB1kHKxcAHk9Cfqa6UsrHcdue3tj1471ja5G9zcWxVU UsNnZRn3qYSfNa51Yd2la39WM8TT2cdzai6XYRgoh3q+cZweg+vtU8mjMuiNqqTo0HmiNUyN/OeW APHSoprC+sLcySfukkXaRvALDjjH4inw6jO9tLBJ5L27zRvJG2ELY4GMYwMdcV1x5btTXTQ1k5tK dFrdX8+/z+f/AAIrOV7WL7VbSlJ42+cFgAV4xx35zWzo/wDaN5drdTTMIlBB4Hzd8EfjnNdNB4U0 G50iS+is5NwjZgrTMwyBnqDyKxtBLmyl3yiRlk27lOQRtXHP0rvp4WdKceZ6PVWZ4uIzGliKVR04 +8nZ3Svr21ZswwS3B2xIWZewqtPI0EEkgRnKjO0dTXUWMaRWMIhiKyzpkyBd2PrXNtyCpAIPBB71 6lSm4x03Z85RrKc/eWiOJvdSma+lkhU2zNlHCkhj6g/lVdHNu5kkjYznbJGzH3zk+ua7QadYht32 SAn3QVYstAtb6cxpaQDAyWKDAryvqFWcr31PpVnWGp07cjSSM+y1i0u3jhSRzMwyQy45xzS6jZ2U 0cn2iYQNIBhi+ASOnGcHGauLp9taznZbxpIhIJVACPWrd54TbWdORku/JmIzsZQy4zx7j612eyqz puLXM/67nk/WcPTrxnGThF9d/wAumxkaRaW9stz9meORHcYZX3EADofxJrQxRHog0VvsMMhnJO7c FwTn2rRuNMFvpqXDOfNLYKgggde9a0aMoQta1tznxWJhUq8yle+z7mdRTxDIdh2NhzhTjr9K3f8A hHojyJ3A91raFOU9jmqVoU7czPSqKKKzJCiiigAooooAKKKKALNnJsm2no3FXYJ47iPzIiSu4rkq RyDg9ayQcHIq8DDPcWsjeb5qqxXbu29gc44+ma4cXTs+Y68PLTlF1G0ivbJ4JohKhI+UjNchqBmg 1DZJbMke/iSRCFJJGNpxjOCa6fTE09ri8msy7SLK0UrNIzDdwSBkkcZ/nWfrc0j2EMsu0SpJskgi beqscEZOM5Ax+dfN5vhIVKTqyu3FaL1PRw82pWXU51kmjt55ZYUlmLgqsRPIBG3r0559KvskiQCV kO08cc80yPTVjWSdbc/eMhOCSTjqB/hWhOkXkx2zgs6IZVO4DH1Gc9/TFfKqg66cmnZXd9ui0td6 aHa6ig0iguXiaRFLBW2nseuO9JInmROmSNykZBwRUXlSmcyPIGVfuIAVx9TnmpMuseWXc/on/wBe uCSircj1/r02NlfqeV3AaWeaaYMH8w+YB/ezz9KYNzHy1jDSDoc54/kasa15Y1y8CrhRM2cHvn/G qe4AI+fmHG0DH45r7ijNShF7aI1cXYYDgYIB5p+/e5G0fNgZPJFNR2XcF/iG00p3fKh5x0A96aeh bWo6ZGhJiIU853Dqac8ilAqJGAACT3z+NMYFQRsIB4JYc5+tAk2KyochgM5HeqcrNroSo3Se7CNo 0kLuAUXna+SD7HFY2tyw3V1AySRw20y7wqlnCdRz3z+ArVfEibSoAxg4zzW54Y8MLp94uopIskMs LL5br8yNuGMfgD6VthlzNxsOVWNFe0k3fojgYbeO8iuJA1xLNHF5hJ2gAjrkk5I+nNWbG/tYbwyX 1vHexRRGMLgjzcnAOT0IB4PtXouvahmxa1WBx54KHenGP8+1ReHdKt7IM0Lq84yWCn5QxzwcL05r thFKdk9V5HPPHqVJucdHsr2066paEejabHpj2OoQ6mYNPng3fZbiXP3huAUkgcZHbt71gePJZNP8 QQNaN5O6AOwTgM25skjua3/FmlX2rWkEcVmszIzHKSAbcjg8kd8etcJqOja5E0Md/E5KpiMPKrYX PQc9K6sRi0qLpKNtne/9W+Ry5dhIzxCxNSom7NNO23T1+Z1NheyT2EL/AGh3DLzj5R+XapT2yOKw dJgNjGhYsrN99d2R+XrV661m3tGRZRJhxwQMjitMPjqdSPvOzXc5cTl1SNVqkrp9kaAGa39Bh228 8mGVmOA5HGPaubtrlLmISxFsZxggggitBdUu0i8pZcIBgDaOB+VelRqRUuZ6o8jE0pyi6ez63JYr eO61K4aWTbAjMzvnrz6+9dJHJCLcTIVWPYDu6fLXCXd5FZWrSyk4HYEZP0rPg8SzXM0ioSLWOP5U mfbub09Bxnip+u06Ds92X/ZVfFR5o/Cv6+82I/EllfeIN9uzyANlcIRlR9a6ZGW88pofKaE/N5Ug AI5wTj868l0fUILC8kmmjch12jYM4yfeu3sfF9tHahY5YFQE4Enyt/OsMHjlO/tXa52ZplEqLSw8 W0klqdZPEPs8kQ2DeCIlAxg4/wAea5JpZAxHmP17mtWz8VQXLYxGwB+Zo3zj8KvRyWsgLLpr4z1M KjNejLkrWcJHiQVTDNxqQPQ6KKK5DpCiiigAooooAKKKKACrFu8vlyRQsiyEZQuCVB9wCKr0qsUY MpwRWdWHPBouEuWSZdWCKyQxxh1M8xJaOMZDHJycDHbGT7ZqCezunvS2+M2ix5CnlmfP6AD+dU7y e/lMaR2clxalds5LgAhmA4A+bIGT2p1pqOoSahcLcwCKBBiILgq4yfmz1zjtXz1eVGdO9Xqj01e+ hFcDUmnjSC0IhEq7pN4yV6kgY/D19Kne0uHulbZtjVeoHzMf7pyPu/rVuG5aIYI3L6Z6VJ9u/wCm f615sFh3FXlZ+hepx1xBLLdqzO0Qikb5Fbhx71z2veKX067eztoAZUxueTpyM8AdetdXOc3Ep6Zc /wA6yNW0a11q3G4gSAfu5l5x/iK+UpVaftv3yvFaemv4nr07Lc83uGee4nnnIWSRmc4HBJPOKgrc 0zQbmbxB/Z0oZfLz5jqNwUEcH6Hj862ZfCOjwOYp/EEaOp5RmQEH6E19rRw0qtNTp/D6iqYynSny Tevkv8jiuhyKc5XeShYjrk9auapZ21rqb2tjcG6jGAJBg7ifTH5Vr23g/UXthPcoLWPgMGOXI+nb 8aUKFSTcYq9i54inBKcna/8AW25zh3EHcxz1wc81YsJI7e9SSdA0a8srDOR7Z712Nno9rZtvCeZK OjvyR/n2rMtom18JPeKFA3Ivk9B0POc1usLKLWupzvGRknpobMNpavcDbbxqGGCzIAq+/T36+1WG tpba5dDIjR9QoHTvwaZ5vlSBWiLRquSxGRjnr+VPa5a7YSRqAPl5xgEe1emkkjyG5N+RBNp9rqNz FHPEWbopyQBz7U1dMi0+5CQEopJLBG3KSOOT61mahdavb3vmxxL5EDh1ZWKhuhweefT86uWGpz6n L9oudkbgmMxgbRng8D8T1rOMqbb0970NZQqqKd7x9S/tZ48Pwe+01h+I9Oe4UXauAsSHK4OT3rpC ICoMeftDMAsbt8r8YwD29fwrHvr2GxtvKvAA0mcqgJHXnvTrU4uHvPQWHqSVT3FqctYWS6jefZkl aNMFhuGf60a14e+x28M7NDO6h/kkUgDj1B7fSr1xqGnxRmbTkljuhgByMgD05JrAuPFCyvLBdtK2 CR8qKOehNcVBUVO0tfPoeq/rM1zUlt06mXpuvm1hMUyM5yzeYWySe361rwa/ZTRRh5NszcFArHk9 umKxjo01pp8t3cI0UkYymHGc5GDx0796zI0jaT99NtGMkgbieCf54H411RxFakkn+J0zwGDxLlOP fVrv+P4DrlnMsx+YRvIeqhckew4zz+tQpG8gYqpIUbmwOg9f1qeeGVLK2kfy/Lfds2gbuDzmm20z W7tMjhZFHygpu3Z471yPfU9SL9z3f66DIWSOVXliEqA8puxn8qjq5HbX3lYFnK0bsH/1RIbHvjpz Wro2kx3JkurmIBd5Cxc4HrnNaU6MqklFGNfF06EHUk727Gl4AWzd9RjupI1LImzcQD3yRn8K7Ztd tYsRxpI6qMBumawbKxNxL5Nuirxk9AAK0v8AhHrnj97F+Of8K+kwkalKkoRW3U+BzKrRxOJlVm7X tpfyt+h6lS5pKKkyFopKKAFopM0UgFzRSUUwFooopAaO6YWSG3RGk+XhzgYyM/pmq2posSfaPtSw Ku3eHxt2559ME5xnNXEiSS0EUqK6MuGVhkEHsaxnivLzUhN9hijsfJMY3oBIRkHBB5AznAH19K8H FRThLS+56kNkS+WvmmXLbiu3G44x9OmfesGbXZbbVvsCRKYoxgs+7d25yetb00Mc8TRSruRhgiuU 1oSf2u+37mRuxj0H6V5GApwqzcZ66Gs3ZDW1qwn1WeCGd5HR2VlC/KPmxnOP5Vj63rhFrJbWDiOZ HKYHBKYOSPTBxRawWQ1OeaAss5BEiHODzyef6VyeqOp1a5K5GJTkg81k8mw9G05Xbv8A10PQo1HU naPRDU1C6jZ5lu7pbl8AyCUgsvoTnJrWs/CusazbLfGRNspJBnkO5vfoap+HdJ/tnWIrds+So3yn /ZHb8eB+NeuoixoqIoVVGAoGABXs4HBqtG8/hWiOfMcd9Wko0/ie545KH0bWJIgRJ9muB143bW4r q7fx7FJZ+Ve2jvKxwShAXHv71ieLlSHxJeKvIZlYrjuUHOfqawsAjIJAA79z6Vj7Wph5yhB6HT7C liqcZ1FrZO56EXmEEjrGJHALRomSW44H1q3ofhZtMd/PuzNCeUiC7RyBkn3/ABrkdL1WPRre0nso orjUJ96y+YWJT5gFAAOOa7yx1ozafFNd25hnZtrRKc49/pXo4aVKrK8t1939eR5WLhWoxcYfC9PP 7v1LpsbVVLeSDgZ4yf0pkcVvN5bwRQNEc78j5gfT2PqDUdxfB5LdbeXhnG4jrjPTmqt5qSQuILSG KW3cssxTja3fpXe5QR5qjUehKdHjks7qFgVeXeEZm3bQehHA+uOa5a28MarpdwkjXUP2YNucLJnP HuB1rrbO+3wyb1CpEgwF9K52WN5ALjy281B8sZ5GfWuatClPllY68PUrQ5o30+8t+TOunx3TICWf aUHUckZ/ShrO1u/O3iN3hGFMsY2sxGdoJ71NHZ3EsYdIyVPfIqOazktzulQjccjJzjHp6VNla7jo NS1spanLTGKz8QRrLHEAVzkYVRweOeKzZxanUrplMLIXLAgDnnse9T+JcrqEabi2IgST3OTWfaWU 96GWFFIX5mYkDArzPbShWtFXsz2o0Yyo80pWujYi0GLV9NljkleIM235QPY1xd34evLLVri1twTH gqsjjO4YGe3vXpei2ktnaNHMQSWyvOflwP8A69Sy6dZyvIZU3s53kbiO2K7Kt63vbM5sLipYVuCd 4/1qebnwhq0ll9shtD9mI2yui7goBwWGeeoJOPetDwv4Ujvsy6lZOIVTEbrIAJDuOSQDnPT8q7PR /Fun6RposZobhnjkcHaoIwWJ7n3pLXWtLubxobNJoBIxYLKABn0GD+lYxVJcr5rvqvM6amNxbUou Nl0a7HMalpmuovladp5WKMsAWkTBUdMfNnpWdZRSbIYF3bztBAPU16HfrO9jMluAZWUhcnHWuOtL K5tdXtUnhZG8wHnuAajFObnFatCwtWLpyVkn+L9Td0e1uLe8LyRMqlCMke4rSnuLyKUhLfzEPKlV PT0qSKUyh3Uhk/gA4NatjqK29sEeNt2c4BHFe1TxVRO17I+frYaD97luzpKKKK6TnCiiigApaSig BaKKKQBV+2tgib5Fy3UDHSqDQ3M1vKLOSOO5AHltIMqDnrVy2nuYYc6m9ujvLsj8vIBz069zXHia rXuI6qFNP3mTfbbcRo7SBN8ZlVGGG2gZJ29eM0h+ycai5VQIceaxwAhwec1YwM5OM+tUtOW5SF7e 9zJIvWUj5Xz2HOePeuE6iI2RSd3jLOJMHO4kD6DoPwrkfEAeHUZnddzIvyjPbHSu6uZpofK8m2Mw aQK+GA2Kf4ueuPSmahaLe2UkDYG4cMe3vXPRw0KVRzXUbk2rHhks97Br8otgxlkYqqkduvGap6hZ 3VpeBrpUd5cv8vQnv0r0DULOGDUZIxhzC5COeo9a57XtMu9QkgNpDJKyggqi5x05pVaD5W7t66Hf RxUeZJpJWs2c5Be3Nioa1uZYXZSrGNscZzjjmu+8Dfa57G5u7u5nmLuEQSuWwAM5GfXP6Vxll4b1 G+1FrNYGjaMgSs/RP8a9U02wi0zT4bOHJSJcZPUnufzrbLqVR1OeV0l+Zz5rXpKn7ONnJ/lucZqn hTV9Sv559tsu+RipaTPyk8dq46e3ktriaFyN0LlGx0yCR/Svbq8Z1gp/bd8eSDcSHg/7RpZjh4U7 TW7LyrFTq3g9kRRubabzG2s4IcDtn/8AXXR6TrhvJViufllO4gpwuAO/PWszTNDe/gLyO8UfVDtB Dfr7V0dv4PtZrZYZFkguFXdkfefjnqcelZYenWbvBaG2Kq4dJqb1/I1rJ7VZA86sxU5QqTx+vNbP kpLDIJLdAu4soQ/eHr2wTXEpoCWF8HS5njkBIC8cgdQeua6Jr2W5tzamBJAwC4yR+or1KFRq8Zqx 4+IpJtSpu4+/RFtkgt4THLOBuUtyB6fX/Crel2ktrC4mIJY5HsPSq18BBfiaSIS5wyFj90ik/tib /nnH+tac0YzuzFxnKCUepryFljYoMsAcD1NY8939n3TalCSn8IxkL/nil/tib/nnH+tV5tWNzG0L xIyNlW+UkDFOdWMtmKnRnHdHEeJZo73WkaHaEZQq4Xbj5j19+a0dJ0ybTLht8yOzxnEfI7jnNZeu apJqN+HaOPdbHarqDlkB4zk8/l3p3/CTXb7iYrYHbjJU5Pt1rxeekq0pS+R9D7OrKhGEe2p1Sk4D vFiQ/KdvOPx9KrTXFtDN5TSAThcBmYZwfrVbS9RnkszLeIiKR+62/wAQHXuawdZuIp9R+1QPkYAI 5ByOo/lXTOvywU0tzkp4dyqOD6Gtqm29ubZrTZN5TZfysP1I646dK1RbRfaI5ngHnDOGXOAP/wBV cZZ3d1avi1cxPJ94tggjt1Fbqa/HbWoEsks8u7ltigD1HBHvWVKrF3lJW/I1rUJxtGLv+Zd1e/ur CLzIoFkiIwz55U/Sqejaw97dLbvGOFZtxOT1q1YatFqSSRzxLDlfus+dyn8BSabp9hbNLJAd7rkF xIG2+3FV78ppxloR7kIOM4+8aipiX5EX5upHUntUscE8m4CIlkO1wOzen607SzDNdRI2SuM/Nn0y Oa6CS4hhba7AE89K9CnSU1dnmVazg7JF6iiiu85AooooAKKKKAClpKKAJIyobDjKMNrD1B61oxGO JktY4nVEjBU7flwOMZ9ay6vW10mwI5wRxk1x4qm37yOmhNL3WTXNtDdxeVOm9NwbGSOQcjp7iort r6OWJ7WOGWLOJUYlWxxyp6evBp73kSNjlvcU5LmFyAH5PYiuN05pXaOlTi9Eyas5Z9P1yK6s2/eL G+yaJsqQQePfGRV6ZnSF2ij8yQAlU3Y3H0z2p2NyYYdRyKgowb60sXvAcbHhcSsQAA2cgZPfnNRF kZjs24/2aXUIjHYLI9u9uqErHCrA8DgDjjoPwqhZArIw/h25yTk5zXj4XGypZmqEo3vp6bjxFHmw 7nfYvUUUV9geKFcJ4l8GTSXEl9pvz+YxeSFiAQTySD6e1d3SMAylT0Iwaxr4eFePLM6MNiamHnzQ KmkaLDZaRbW06LLKiAM5HOf/AK3T8K0zEp6cUkJJhTcctjBPqakrWEIxikgnJzk3Ip3VkJouUSQg 8buCOeeabDBHAu2NAo7+9XqY8YbkcGnyq9yHe1kZmorAIPMmXcV4UZI5NYROTkAD2FaOrW0q3Hml W8sgD7xIz9O1ZwBPQE/SuKu7z2OzDxtDcSmuyohZuFAyaeQQcEEfWlt5VW7jVo3dTkEqOBx69qyS u7Gzdlc4LVBbm+naNmyXJAxxVLcuWOwcjgZPFd1q2kQagFVP3JBDFioZjx0JHU1lnwtHgk3DOxPZ QuOa82rhqjm+VI9ajjKXs1zNl7SlzpNoXx5gJUEjP8Rz+grndW0uWykySH8xyw2qc/56V1VtZLb2 0NjFJJwxAYMAckk4/Wr66ffrPIzRZhIyPm5XA9K65Yd1aaT3RxRxSpVHJPRs82eJlXcVkx6suBTd qCMMXyxPKjsK7yS2S6hmgnbfFuznPI74/CuHwolKxjzEbJ2jqBXBWoeza63PToYn2qfSw1CQQFwz NjgDP4GkboeNgB6e/fmnBTCwLIyNgkbwefTFICC52uQrD5if1rHpY363LWmFo9YtgxPEgHNd/DqN 5apsjt42BJOS9cJBI0sdpYRuRJ5wcSIc7c/1/GtkDW4iyQ3CXCKcB9oz+Nd2Fm6d7K55uMpqrbma Xr+Z6lRRRX0Z84FFFFABRRRQAUUUUAFLSUUALRSUZpAW4r1kwHG5f1qw118yMoVoiDubdhgewxjn v3rNorlrYZST5NGbwruO+pBqcUerlI5GRkhcsU3HIbHHQ+465qrbwCB5R1bdyQeOlaLKrjDqGXIO D7VAtsqE7DtUnOABXjUMsxEMXCtV97lv17+tjoq4iMqLhHS4yipRDzyeKkCqvQV9FY81RZCsbH2F O8n/AGv0qWinYrlQirtXFLRRQMKM0UlAC9RzVUWscBZokChjk4q1RSauHSxjXFgbm+8x2/deXgKO u7PrUVtZSRWFxF5YWSQ5AyOela8ibTkdKhMMbTCUoPMUFQ3cA1m6avcPaSS5WchcPHpu77SQJNwD 7fUjj9BUVlc2t9Mfs7sCGUnPygluB/KpPEGkC6aS3WdwdyHdIdx4H/16PDXh37LJOWuA+Shxs9Cf evOftPbciWh6ydL2HtJP3i7bn7HOJiI5n55U4B5I6+3Nacms25BTa+WBAziqGo2aSWcRLTBW4IkA D8HOTVVgkmUbBxg4zW7nKm3FHKoRqpSZlazcmxspZDKTJKDGidhnvj1xXP6TavdzNIrRokKjfwck e3vXb6j4Ti1fTWuoriWW8WP93CrqEB9Dkf1ql4c8IavaXDvdKkCFkypcNvUHkcZxxXiVMVB1/edk j2KbhHDuz95mB4j8uW6t3RWKbDnAIPFYbFSoCjGPXqa9Z8QeFLa+smltA8d1Ep2ANkP/ALJBNcRp nhu4t79jqUBj8rGIyQdx6jp2rPnWIn+769zahWjCl7z2LHh7SfsyC8nX964+RT/CP8TWkLpYiyCN 3IJyyqACauUYPZWP0BNetThGnHlR5lWpKrLmkdnRRRXsnkBRRRQAUUUUAFFFFABRRRQAUUUUAFLR RQAUUUUgCiiigAooooAKKKKACiiigAooooACM8GoJE2HI5BooqZbobV4sytQgtImN1dSyKrELgdM /lmorBXjuriKFlyrAfMM/KG5/SiisJJKorGkW3Sd2Wm8u/PMZaBQcPkgls4Ixj9aq3FpaR2RuFhZ XZRjfkEZ9RRRVTScW7EwbU1FPS5FYWEzX0U6uqiM43K/PPUEevTrXRN5kSRky7gikyZTLPgdsd8+ 1FFfO5vBRqQS6o78NNyTuOMw8uNhjMmNqudpPf8APGTj2qteaVb3ZL4KSH+Je/1FFFeSpypSvB2Z 0WuY76Pcx3CIRujZgN684+orfhktrKIQSQTfL90wqXBHqeOD7UUV2PEzrcqmkyeVLY//2Q==