20221013 10024300 1.0 FALSE SocialVulnerabilityIndex_CopyFeatures -88.473227 -84.889080 30.223334 35.008028 1 002 Geographic GCS_North_American_1983 Angular Unit: Degree (0.017453) <GeographicCoordinateSystem xsi:type='typens:GeographicCoordinateSystem' xmlns:xsi='http://www.w3.org/2001/XMLSchema-instance' xmlns:xs='http://www.w3.org/2001/XMLSchema' xmlns:typens='http://www.esri.com/schemas/ArcGIS/3.1.0'><WKT>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],AUTHORITY[&quot;EPSG&quot;,4269]]</WKT><XOrigin>-400</XOrigin><YOrigin>-400</YOrigin><XYScale>999999999.99999988</XYScale><ZOrigin>-100000</ZOrigin><ZScale>10000</ZScale><MOrigin>-100000</MOrigin><MScale>10000</MScale><XYTolerance>8.983152841195215e-09</XYTolerance><ZTolerance>0.001</ZTolerance><MTolerance>0.001</MTolerance><HighPrecision>true</HighPrecision><LeftLongitude>-180</LeftLongitude><WKID>4269</WKID><LatestWKID>4269</LatestWKID></GeographicCoordinateSystem> 20231128 13142200 20231128 13142200 150000000 5000 NAP SVI Coordinator CDC\TSDR\GRASP svi_coordinator@cdc.gov False SVI Coordinator CDC\ATSDR Social Vulnerability Index 2020 - United States, tract SVI2020 CDC\ATSDR Social Vulnerability Index SVI Coordinator CDC\TSDR\GRASP svi_coordinator@cdc.gov SVI Coordinator CDC\TSDR\GRASP SVI Coordinator SVI 2020 GRASP CDC ATSDR social vulnerability social vulnerability index tract census American Community Survey United States The CDC\ATSDR Social Vulnerability Index (SVI) is a tool, created by the Geospatial Research, Analysis and Services Program (GRASP), to help public health officials and emergency response planners identify and map the communities that will most likely need support before, during, and after a hazardous event. The tract-level SVI shows the relative vulnerability of the population of every U.S. Census tract. The county-level SVI shows the relative vulnerability of every U.S. county population. The SVI ranks tracts (or counties) on 16 social factors, described in detail in the documentation. The tract (or county) rankings for individual factors are further grouped into four related themes. Thus each enumeration unit receives a ranking for each Census variable and for each of the four themes, as well as an overall ranking. <DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>See complete documentation here: </SPAN><A href="https://www.atsdr.cdc.gov/placeandhealth/svi/data_documentation_download.html" STYLE="text-decoration:underline;"><SPAN STYLE="text-decoration:underline;"><SPAN>https://www.atsdr.cdc.gov/placeandhealth/svi/data_documentation_download.html</SPAN></SPAN></A><SPAN>. For additional questions, contact the SVI Lead at svi_coordinator@cdc.gov.</SPAN></P></DIV></DIV></DIV> CDC\ATSDR\Office of Innovation and Analytics\Geospatial Research, Analysis, and Services Program (GRASP) social vulnerability 2020 2016-2020 Esri ArcGIS 13.1.2.41833 1 -88.473227 -84.889080 35.008028 30.223334 EPSG 6.5(3.0.1) SocialVulnerabilityIndex_CopyFeatures Feature Class 0 OBJECTID OBJECTID OID 4 0 0 Internal feature number. Esri Sequential unique whole numbers that are automatically generated. ST State-level FIPS code String 2 0 0 STATE State name String 255 0 0 ST_ABBR State abbreviation String 2 0 0 STCNTY County-level FIPS code String 5 0 0 COUNTY County name String 255 0 0 FIPS Tract-level FIPS code String 30 0 0 LOCATION Text description of tract, county, state String 255 0 0 RPL_THEMES Overall percentile ranking Double 8 0 0 AREA_SQMI Tract area in square miles Double 8 0 0 E_TOTPOP Population estimate, 2016-2020 ACS Integer 4 0 0 M_TOTPOP Population estimate MOE, 2016-2020 ACS Integer 4 0 0 E_HU Housing units estimate, 2016-2020 ACS Integer 4 0 0 M_HU Housing units estimate MOE, 2016-2020 ACS Integer 4 0 0 E_HH Households estimate, 2016-2020 ACS Integer 4 0 0 M_HH Households estimate MOE, 2016-2020 ACS Integer 4 0 0 E_POV150 Persons below 150% poverty estimate, 2016-2020 ACS Integer 4 0 0 M_POV150 Persons below 150% poverty estimate MOE, 2016-2020 ACS Integer 4 0 0 E_UNEMP Civilian (age 16+) unemployed estimate, 2016-2020 ACS Integer 4 0 0 M_UNEMP Civilian (age 16+) unemployed estimate MOE, 2016-2020 ACS Integer 4 0 0 E_HBURD Housing cost-burdened occupied housing units with annual income less than $75,000 (30%+ of income spent on housing costs) estimate, 2016-2020 ACS Integer 4 0 0 M_HBURD Housing cost-burdened occupied housing units with annual income less than $75,000 (30%+ of income spent on housing costs) estimate MOE, 2016-2020 ACS Integer 4 0 0 E_NOHSDP Persons (age 25+) with no high school diploma estimate, 2016-2020 ACS Integer 4 0 0 M_NOHSDP Persons (age 25+) with no high school diploma estimate MOE, 2016-2020 ACS Integer 4 0 0 E_UNINSUR Uninsured in the total civilian noninstitutionalized population estimate, 2016-2020 ACS Integer 4 0 0 M_UNINSUR Uninsured in the total civilian noninstitutionalized population estimate MOE, 2016-2020 ACS Integer 4 0 0 EP_POV150 Percentage of persons below 150% poverty estimate Double 8 0 0 MP_POV150 Percentage of persons below 150% poverty estimate MOE Double 8 0 0 EP_UNEMP Unemployment Rate estimate Double 8 0 0 MP_UNEMP Unemployment Rate estimate MOE Double 8 0 0 EP_HBURD Percentage of housing cost-burdened occupied housing units with annual income less than $75,000 (30%+ of income spent on housing costs) estimate, 2016-2020 ACS estimate, 2016-2020 ACS Double 8 0 0 MP_HBURD Percentage of housing cost-burdened occupied housing units with annual income less than $75,000 (30%+ of income spent on housing costs) estimate MOE, 2016-2020 ACS Double 8 0 0 EP_NOHSDP Percentage of persons with no high school diploma (age 25+) estimate Double 8 0 0 MP_NOHSDP Percentage of persons with no high school diploma (25+) estimate MOE Double 8 0 0 EP_UNINSUR Percentage uninsured in the total civilian noninstitutionalized population estimate, 2016-2020 ACS Double 8 0 0 MP_UNINSUR Percentage uninsured in the total civilian noninstitutionalized population estimate MOE, 2016-2020 ACS Double 8 0 0 EPL_POV150 Percentile percentage of persons below 150% poverty estimate Double 8 0 0 EPL_UNEMP Percentile percentage of civilian (age 16+) unemployed estimate Double 8 0 0 EPL_HBURD Percentile percentage of housing cost-burdened occupied housing units estimate Double 8 0 0 EPL_NOHSDP Percentile percentage of persons with no high school diploma (age 25+) estimate Double 8 0 0 EPL_UNINSUR Percentile percentage of uninsured estimate Double 8 0 0 SPL_THEME1 Sum of series for Socioeconomic Status theme Double 8 0 0 RPL_THEME1 Percentile ranking for Socioeconomic Status theme Double 8 0 0 E_AGE65 Persons aged 65 and older estimate, 2016-2020 ACS Integer 4 0 0 M_AGE65 Persons aged 65 and older estimate MOE, 2016-2020 ACS Integer 4 0 0 E_AGE17 Persons aged 17 and younger estimate, 2016-2020 ACS Integer 4 0 0 M_AGE17 Persons aged 17 and younger estimate MOE, 2016-2020 ACS Integer 4 0 0 E_DISABL Civilian noninstitutionalized population with a disability estimate, 2016-2020 ACS Integer 4 0 0 M_DISABL Civilian noninstitutionalized population with a disability estimate MOE, 2016-2020 ACS Integer 4 0 0 E_SNGPNT Single-parent household with children under 18 estimate, 2016-2020 ACS Integer 4 0 0 M_SNGPNT Single-parent household with children under 18 estimate MOE, 2016-2020 ACS Integer 4 0 0 E_LIMENG Persons (age 5+) who speak English "less than well" estimate, 2016-2020 ACS Integer 4 0 0 M_LIMENG Persons (age 5+) who speak English "less than well" estimate MOE, 2016-2020 ACS Integer 4 0 0 EP_AGE65 Percentage of persons aged 65 and older estimate, 2016-2020 ACS Double 8 0 0 MP_AGE65 Percentage of persons aged 65 and older estimate MOE, 2016-2020 ACS Double 8 0 0 EP_AGE17 Percentage of persons aged 17 and younger estimate, 2016-2020 ACS Double 8 0 0 MP_AGE17 Percentage of persons aged 17 and younger estimate MOE, 2016-2020 ACS Double 8 0 0 EP_DISABL Percentage of civilian noninstitutionalized population with a disability estimate, 2016-2020 ACS Double 8 0 0 MP_DISABL Percentage of civilian noninstitutionalized population with a disability estimate MOE, 2016-2020 ACS Double 8 0 0 EP_SNGPNT Percentage of single-parent households with children under 18 estimate, 2016-2020 ACS Double 8 0 0 MP_SNGPNT Percentage of single-parent households with children under 18 estimate MOE, 2016-2020 ACS Double 8 0 0 EP_LIMENG Percentage of persons (age 5+) who speak English "less than well" estimate, 2016-2020 ACS Double 8 0 0 MP_LIMENG Percentage of persons (age 5+) who speak English "less than well" estimate MOE, 2016-2020 ACS Double 8 0 0 EPL_AGE65 Percentile percentage of persons aged 65 and older estimate Double 8 0 0 EPL_AGE17 Percentile percentage of persons aged 17 and younger estimate Double 8 0 0 EPL_DISABL Percentile percentage of civilian noninstitutionalized population with a disability estimate Double 8 0 0 EPL_SNGPNT Percentile percentage of single-parent households with children under 18 estimate Double 8 0 0 EPL_LIMENG Percentile percentage of persons (age 5+) who speak English "less than well" estimate Double 8 0 0 SPL_THEME2 Sum of series for Household Characteristics theme Double 8 0 0 RPL_THEME2 Percentile ranking for Household Characteristics theme Double 8 0 0 E_MINRTY Minority estimate, 2016-2020 ACS Integer 4 0 0 M_MINRTY Minority estimate MOE, 2016-2020 ACS Integer 4 0 0 EP_MINRTY Percentage minority estimate, 2016-2020 ACS Double 8 0 0 MP_MINRTY Percentage minority estimate MOE, 2016-2020 ACS Double 8 0 0 EPL_MINRTY Percentile percentage minority estimate Double 8 0 0 SPL_THEME3 Sum of series for Racial and Ethnic Minority Status theme Double 8 0 0 RPL_THEME3 Percentile ranking for Racial and Ethnic Minority Status theme Double 8 0 0 E_MUNIT Housing in structures with 10 or more units estimate, 2016-2020 ACS Integer 4 0 0 M_MUNIT Housing in structures with 10 or more units estimate MOE, 2016-2020 ACS Integer 4 0 0 E_MOBILE Mobile homes estimate, 2016-2020 ACS Integer 4 0 0 M_MOBILE Mobile homes estimate MOE, 2016-2020 ACS Integer 4 0 0 E_CROWD At household level (occupied housing units), more people than rooms estimate, 2016-2020 ACS Integer 4 0 0 M_CROWD At household level (occupied housing units), more people than rooms estimate MOE, 2016-2020 ACS Integer 4 0 0 E_NOVEH Households with no vehicle available estimate, 2016-2020 ACS Integer 4 0 0 M_NOVEH Households with no vehicle available estimate MOE, 2016-2020 ACS Integer 4 0 0 E_GROUPQ Persons in group quarters estimate, 2016-2020 ACS Integer 4 0 0 M_GROUPQ Persons in group quarters estimate MOE, 2016-2020 ACS Integer 4 0 0 EP_MUNIT Percentage of housing in structures with 10 or more units estimate Double 8 0 0 MP_MUNIT Percentage of housing in structures with 10 or more units estimate MOE Double 8 0 0 EP_MOBILE Percentage of mobile homes estimate Double 8 0 0 MP_MOBILE Percentage of mobile homes estimate MOE Double 8 0 0 EP_CROWD Percentage of occupied housing units with more people than rooms estimate Double 8 0 0 MP_CROWD Percentage of occupied housing units with more people than rooms estimate MOE Double 8 0 0 EP_NOVEH Percentage of households with no vehicle available estimate Double 8 0 0 MP_NOVEH Percentage of households with no vehicle available estimate MOE Double 8 0 0 EP_GROUPQ Percentage of persons in group quarters estimate, 2016-2020 ACS Double 8 0 0 MP_GROUPQ Percentage of persons in group quarters estimate MOE, 2016-2020 ACS Double 8 0 0 EPL_MUNIT Percentile percentage housing in structures with 10 or more units estimate Double 8 0 0 EPL_MOBILE Percentile percentage mobile homes estimate Double 8 0 0 EPL_CROWD Percentile percentage households with more people than rooms estimate Double 8 0 0 EPL_NOVEH Percentile percentage households with no vehicle available estimate Double 8 0 0 EPL_GROUPQ Percentile percentage of persons in group quarters estimate Double 8 0 0 SPL_THEME4 Sum of series for Housing Type/ Transportation theme Double 8 0 0 RPL_THEME4 Percentile ranking for Housing Type/ Transportation theme Double 8 0 0 SPL_THEMES Sum of series themes Double 8 0 0 E_DAYPOP Adjunct variable - Estimated daytime population, LandScan 2020 Integer 4 0 0 E_NOINT Adjunct variable - Households without a computer with a broadband Internet subscription estimate, 2016-2020 ACS Integer 4 0 0 M_NOINT Adjunct variable - Households without a computer with a broadband Internet subscription estimate MOE, 2016-2020 ACS Integer 4 0 0 E_AFAM Adjunct variable - Black/African American, not Hispanic or Latino persons estimate, 2016-2020 ACS Integer 4 0 0 M_AFAM Adjunct variable - Black/African American, not Hispanic or Latino persons estimate MOE, 2016-2020 ACS Integer 4 0 0 E_HISP Adjunct variable – Hispanic or Latino persons estimate, 2016-2020 ACS Integer 4 0 0 M_HISP Adjunct variable – Hispanic or Latino persons estimate MOE, 2016-2020 ACS Integer 4 0 0 E_ASIAN Adjunct variable – Asian, not Hispanic or Latino persons estimate, 2016-2020 ACS Integer 4 0 0 M_ASIAN Adjunct variable – Asian, not Hispanic or Latino persons estimate MOE, 2016-2020 ACS Integer 4 0 0 E_AIAN Adjunct variable - American Indian or Alaska Native, not Hispanic or Latino persons estimate, 2016-2020 ACS Integer 4 0 0 M_AIAN Adjunct variable - American Indian or Alaska Native, not Hispanic or Latino persons estimate MOE, 2016-2020 ACS Integer 4 0 0 E_NHPI Adjunct variable - Native Hawaiian or Other Pacific Islander, not Hispanic or Latino persons estimate, 2016-2020 ACS Integer 4 0 0 M_NHPI Adjunct variable - Native Hawaiian or Other Pacific Islander, not Hispanic or Latino persons estimate MOE, 2016-2020 ACS Integer 4 0 0 E_TWOMORE Adjunct variable - Two or more races, not Hispanic or Latino persons estimate, 2016-2020 ACS Integer 4 0 0 M_TWOMORE Adjunct variable - Two or more races, not Hispanic or Latino persons estimate MOE, 2016-2020 ACS Integer 4 0 0 E_OTHERRACE Adjunct variable - Some other race, not Hispanic or Latino persons estimate, 2016-2020 ACS Integer 4 0 0 M_OTHERRACE Adjunct variable - Some other race, not Hispanic or Latino persons estimate MOE, 2016-2020 ACS Integer 4 0 0 EP_NOINT Adjunct variable - Percentage of households without a computer with a broadband Internet subscription estimate, 2016-2020 ACS Double 8 0 0 MP_NOINT Adjunct variable - Percentage of households without a computer with a broadband Internet subscription estimate MOE, 2016-2020 ACS Double 8 0 0 EP_AFAM Adjunct variable - Percentage of Black/African American, not Hispanic or Latino persons estimate, 2016-2020 ACS Double 8 0 0 MP_AFAM Adjunct variable - Percentage of Black/African American, not Hispanic or Latino persons estimate MOE, 2016-2020 ACS Double 8 0 0 EP_HISP Adjunct variable - Percentage of Hispanic or Latino persons estimate, 2016-2020 ACS Double 8 0 0 MP_HISP Adjunct variable - Percentage of Hispanic or Latino persons estimate MOE, 2016-2020 ACS Double 8 0 0 EP_ASIAN Adjunct variable - Percentage of Asian, not Hispanic or Latino persons estimate, 2016-2020 ACS Double 8 0 0 MP_ASIAN Adjunct variable - Percentage of Asian, not Hispanic or Latino persons estimate MOE, 2016-2020 ACS Double 8 0 0 EP_AIAN Adjunct variable - Percentage of American Indian or Alaska Native, not Hispanic or Latino persons estimate, 2016-2020 ACS Double 8 0 0 MP_AIAN Adjunct variable - Percentage of American Indian or Alaska Native, not Hispanic or Latino persons estimate MOE, 2016-2020 ACS Double 8 0 0 EP_NHPI Adjunct variable - Percentage of Native Hawaiian or Other Pacific Islander, not Hispanic or Latino persons estimate, 2016-2020 ACS Double 8 0 0 MP_NHPI Adjunct variable - Percentage of Native Hawaiian or Other Pacific Islander, not Hispanic or Latino persons estimate MOE, 2016-2020 ACS Double 8 0 0 EP_TWOMORE Adjunct variable - Percentage of two or more races, not Hispanic or Latino persons estimate, 2016-2020 ACS Double 8 0 0 MP_TWOMORE Adjunct variable - Percentage of two or more races, not Hispanic or Latino persons estimate MOE, 2016-2020 ACS Double 8 0 0 EP_OTHERRACE Adjunct variable - Percentage of some other race, not Hispanic or Latino persons estimate, 2016-2020 ACS Double 8 0 0 MP_OTHERRACE Adjunct variable - Percentage of some other race, not Hispanic or Latino persons estimate MOE, 2016-2020 ACS Double 8 0 0 F_POV150 Flag - the percentage of persons below 150% poverty is in the 90th percentile (1 = yes, 0 = no) SmallInteger 2 0 0 F_UNEMP Flag - the percentage of civilian unemployed is in the 90th percentile (1 = yes, 0 = no) SmallInteger 2 0 0 F_HBURD Flag - the percentage of housing cost-burdened occupied housing units is in the 90th percentile (1 = yes, 0 = no) SmallInteger 2 0 0 F_NOHSDP Flag - the percentage of persons with no high school diploma is in the 90th percentile (1 = yes, 0 = no) SmallInteger 2 0 0 F_UNINSUR Flag - the percentage of uninsured is in the 90th percentile (1 = yes, 0 = no) SmallInteger 2 0 0 F_THEME1 Sum of flags for Socioeconomic Status theme SmallInteger 2 0 0 F_AGE65 Flag - the percentage of persons aged 65 and older is in the 90th percentile (1 = yes, 0 = no) SmallInteger 2 0 0 F_AGE17 Flag - the percentage of persons aged 17 and younger is in the 90th percentile (1 = yes, 0 = no) SmallInteger 2 0 0 F_DISABL Flag - the percentage of persons with a disability is in the 90th percentile (1 = yes, 0 = no) SmallInteger 2 0 0 F_SNGPNT Flag - the percentage of single-parent households is in the 90th percentile (1 = yes, 0 = no) SmallInteger 2 0 0 F_THEME2 Sum of flags for Household Characteristics theme SmallInteger 2 0 0 F_MINRTY Flag - the percentage of minority is in the 90th percentile (1 = yes, 0 = no) SmallInteger 2 0 0 F_LIMENG Flag - the percentage those with limited English is in the 90th percentile (1 = yes, 0 = no) SmallInteger 2 0 0 F_THEME3 Sum of flags for Racial and Ethnic Minority Status theme SmallInteger 2 0 0 F_MUNIT Flag - the percentage of households in multi-unit housing is in the 90th percentile (1 = yes, 0 = no) SmallInteger 2 0 0 F_MOBILE Flag - the percentage of mobile homes is in the 90th percentile (1 = yes, 0 = no) SmallInteger 2 0 0 F_CROWD Flag - the percentage of crowded households is in the 90th percentile (1 = yes, 0 = no) SmallInteger 2 0 0 F_NOVEH Flag - the percentage of households with no vehicles is in the 90th percentile (1 = yes, 0 = no) SmallInteger 2 0 0 F_GROUPQ Flag - the percentage of persons in group quarters is in the 90th percentile (1 = yes, 0 = no) SmallInteger 2 0 0 F_THEME4 Sum of flags for Housing Type/ Transportation theme SmallInteger 2 0 0 F_TOTAL Sum of flags for the four themes SmallInteger 2 0 0 SHAPE Shape Geometry 0 0 0 Feature geometry. Esri Coordinates defining the features. Shape_Length Shape_Length Double 8 0 0 Length of feature in internal units. Esri Positive real numbers that are automatically generated. Shape_Area Shape_Area Double 8 0 0 Area of feature in internal units squared. Esri Positive real numbers that are automatically generated. File Geodatabase Feature Class dataset 0 Simple FALSE 0 TRUE FALSE 20231128 /9j/4AAQSkZJRgABAQEAAQABAAD/2wBDAAgGBgcGBQgHBwcJCQgKDBQNDAsLDBkSEw8UHRofHh0a HBwgJC4nICIsIxwcKDcpLDAxNDQ0Hyc5PTgyPC4zNDL/2wBDAQkJCQwLDBgNDRgyIRwhMjIyMjIy MjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjL/wAARCADIASwDASIA AhEBAxEB/8QAHwAAAQUBAQEBAQEAAAAAAAAAAAECAwQFBgcICQoL/8QAtRAAAgEDAwIEAwUFBAQA AAF9AQIDAAQRBRIhMUEGE1FhByJxFDKBkaEII0KxwRVS0fAkM2JyggkKFhcYGRolJicoKSo0NTY3 ODk6Q0RFRkdISUpTVFVWV1hZWmNkZWZnaGlqc3R1dnd4eXqDhIWGh4iJipKTlJWWl5iZmqKjpKWm p6ipqrKztLW2t7i5usLDxMXGx8jJytLT1NXW19jZ2uHi4+Tl5ufo6erx8vP09fb3+Pn6/8QAHwEA AwEBAQEBAQEBAQAAAAAAAAECAwQFBgcICQoL/8QAtREAAgECBAQDBAcFBAQAAQJ3AAECAxEEBSEx BhJBUQdhcRMiMoEIFEKRobHBCSMzUvAVYnLRChYkNOEl8RcYGRomJygpKjU2Nzg5OkNERUZHSElK U1RVVldYWVpjZGVmZ2hpanN0dXZ3eHl6goOEhYaHiImKkpOUlZaXmJmaoqOkpaanqKmqsrO0tba3 uLm6wsPExcbHyMnK0tPU1dbX2Nna4uPk5ebn6Onq8vP09fb3+Pn6/9oADAMBAAIRAxEAPwD2qbAQ gHvxUEpziJOT3NOYmR2VTyO/pTLSNlZmbueKwbvoSTpGsUYHYU2N2lJCjjsafcZ8tgPSkhZbeAsx 7UdQKjbvtqx44BpXMjSkAHDcVLAhkmLN161eESbt23mhRuFiKCBI0wQMnrQ8ccasVX5iOOKsYFNI ycfnWiRRjoutABVeEqc5L9f50x/7dVCrNbjjqAc/zrdwKimA24oewGIsmrqy7lhKZAbHX+daYAXr 09PWiQbRx17U6Fdw3NzWe5I9VJI9Kl24ApVwBjvQSM4q0ihVHfvS0mT6GsyfzhOoWPIOd2WPHp0q gNTAFJuFQIzeUinJbbzUyLtHNIBT83HQU3ADAZJHpTicnimk4k/CmA7GOgpjAkEGnk4GablSeaQD I3Krtbt3p4kBGaQrn3qNRtYgjGTxTbvqTqtCfcMUoqMDJp4GKSKF4puBml7mjrQAm2k28U/pUcr7 AMKWJOABTAdwB0poGT6U1J9zbWjZOMjODmpM+lKwC4G2gdKjMm09qaZhnBIoAeW4z2qKRsng80m8 H6VGzKDnNIB5JJoyaasiE85/KpNxHCxsR68U+VhdFfYYowAeT1PrUK3mQq7MEkAjPvXF/wDCYakW ziP2+Wp7W51y7BuobYOqnrsrKMos6JYOpH4rfed04wrEngCqoBlG8/6tefqa52HVdenn8mWFIx/E XTFbXnzeVtBX8qNGZSouOhpWwWNcsfmbmrQ6Vz4uJ2cZI3fSqUniC9jcqNhAOPu1SkhwpSlsdaKR ehJ6muYg1y9nztaL8RUF/wCK2spRCZohJjJBHSq5kV7Cd7HX96gmR2Py9D1rj/8AhMZv+esPPtUc vjG7eSKCBoWkkbA9qTkrDeGqHWNx7gVPGFEYHXvWK17LHbeZMy5AycCuZufHlwlzss0Vl/2l5zUX SJp4epUdoo9DfPl8dadEhUZPWuFs/GN7cW7SOiBlPI207/hMdQP8Ef5VXNE0+qVb2sd3Siud0zWL u7jZpWjVh0ULV43c+Pvr/wB81d0YunJOzNFyVHyjJpsbEj5qzvtlwTwyn8KPtM+M7l/KlcXIzTJw c1XuLlISu4HPXj0qmLyc/wAS/wDfNQXpluo9jSAAjBwOop3QcjNaCdJw23Py461IRkdKx7aSaFMK +eAOR2HSpxeTkfeX8qV0HIy+cig4YYNZ/wBsnPdT/wABoNzPjO5fypByMvB2RsMPlPepxzz2rnb7 XEsUH2iVQW6Ljk03TfEAv4v3Uihl/hI5quaLXmCpTWttDozVeeQq/wB/aNuR7muY1TxLdWtz5ULI xA5ytMsfEeo3U4VlTb6helLmVzX6vPl5jrIWLlgXLKMYP4U94w4HJBU5BrHXU7jcNzIB/u09tTk3 7UkRm69Kd0ZunJGkqLEcs2cDjjFOw0vfav6mqVvJNdOVkYYUA8Cr5BVMA/jRclqxHsVRyufc81na lf29gyh42fcONi5rRKMemTVd0VC2RyexppNuxLdlcyv7atsEqJF7nK8Cp7XVrOaRFHmNIxwCV4rT SJEiKlQxPXipIokRQIolUD26VV7bCtfckwFHOBSYPZePc04L3PJp1SUcDpvhJkvs3bK8a8qF7/Wu zRVjjEaABQO1QWyny9zfebk1NJwuB1PFYrRaFVa06rvJkfySkqUyPWqU0DwvwCynp7Vei6E08enr TJUmjHyyJIQjllGeBWHPbzxR+fKjIjH7zDpk13IChsADJ6muO15rwSvazSb4MgjjAptKx1UJtuyM DU7W+v4jBp85VVXcWUck1Q0PQ7u7mLanI00jcfMORjiuuttQt7exIghCy9CPWp7RymZvJCFuoNTZ HS6kkmrGPYeHxAGklhXapwFbua1odGtLd/tHkIH9R2q7v89k7AHJHvUr/wCr55osc06kpPUz3Lks ikc1hyQRiYlkUsDkGumt41aRmI46VmXVjHFck792ecUktDShKzEs7CyuYD5rct07YNV7zQXtyrwT K3PAJwasxJzgKcjpinTRs5XJbI9aehqpST0ZatIfIiX+/jkirpdvsxbcMiiCCNolIbdxVS6tJ3Qp BIFG7LZ9Ko5202WreQNGQSSc1I+cdeDTUiCdDTwMnGaCXuKIwFGDioZGbng8VKWPSmOCBknFIkcj k9sUZAUEihAoJ9aduAzxwaEBGzYHAp4LAZP5U0qGPBqpNdSx3SRCPKMMls9DTHvsYus6deXt+JHG YhwgWlg8Oz28gljyrDp81a1xc3MZ4jG09COapnU3ihcyN8y+vpU2SZ0Kc+VR6FpLSJlzIgSXvVG/ RoJFKHKkcY9aPOvdTtbSTTCj5f8AeyN0AHUVtTac0wQsy8dQK1VNzV4owdeNJ2mzjdT1hrFEE8zp nlcKSKxv+EsuHyIizN2CqcmvR7rTrKW2aGaJChGMkdK5b+wNNsXVLZSzKdxkJ6+1ZShJPc66FelK OsdTW8C315eyXX2lpfuKV3jGOtduFGMk5rlfDQEeoMo/iWuoy3TitI7HFif4jsNldkj4HWoYSpky 5y2eAatfeTnpVIKrThe2c1vHWLRxSupJlxWy7DHSnkDrQoA6UjGspNGq03AZ9aMn0pF5OadSGVE2 8begpkjZkCDrinFf4hw3rTI/kbL8e9Zkj2GxB+gp6KVXJ++aQDzDvboOlTIP4j+FNIaMy40iW5uj Ot5LEcY2KeKq3PhkXCBZb6ZgDkZ5rfUEnNLjnmrHc4eLSDaXRIkLKpx8w61px3Ud1mAnay+1aWuS LDYM2F3E4Ga5CLfLcjyyd2eo9azlozrppzjdm5brmVxk7QeDU1yxS3YgZAH5UyOMxxhDkkd6fJuZ dhXIbjmmtiX3Mr+3LOO3cpMjSj+EHk1Uk1sXLpttnKL9/aBmq+s+FVMjT6dF5bycSBTjdWvoejpp NmYwzGSTDOTzzSV9jRqKjzJ6kkGqRGZES1kUMQMlelaTxI/LIDSKrqMYFNdpAwGDj2qjK4sSBc7B gelPYbsdqaTwMDnvTiwwKQCbscY59aq3NyyWk0kK75VUkJ6n0qTzGR8tnbWNcXUs148VuMMG5Y9q VxxVxukeJ4b6f7JPHJDdc5RhW27ZBAzXCR+JILO8Jks3E4JXzGHQf4dasDx1ZJeLaXTbAej9j3pX NZ0m/hR0drJftqbiV4vs2DtA+8DWl5qhgCwB9K4nWNYjsL6G5gn3GdP3cajj6k1FaaqwmS5ln3Fh lwxz5eOtMn2bep3hkDZGQCKqXV3bwqTK3K89Kx7fVoLmUW6XSLu5BZsMaf8AaYTfrZTOJhJ8p9qa V3Ynktqy1Y6slzFkSLIGYhdo6fWoDbC7unlmTCqcbfWtGy021092it4lT0wOpqxFaM7bpOFzznvW nsm1bqZPERi21sQ2K/ZwUtolVepCjArVy3lZI+bFZN7rljpUghwWfuF7VV/4SuycElZFIHTHWt4y jTXK3qc0qNWs+dQ0fU057U3KlWchfas640mSM5g+dfQ9agXxbbF8GJwvrVq51yJYcxq5P0xXM5Jn fCnUp9GS6LDNBqiGSMqNrCup6c964zSdakudRgR4ioJ5y2a7HzAwOKE0kZV783vAwJjIHU1SiIid t6/NV9elVLldzc1rCSWjOWae6LKSKw4p2MnNZ8bsjVcSZWUZIB9Kc6dtUKFRPRktLTc5pp3ZrM1I BzxTtgfjtTV+UbQMmiVnjgcxAF8fKD61CVyULsKkBOV7ipUcPwO3UGseO51kKd1rFuPfP/16GuNY ZuLKIc9Q3/16oo3OlIT6VCJGAAk6/wB4dKe7cYU/jTBla9iiuIhHIobJ4z2qnBolrHMxjBUgdc1c izLK0h6LwKsxLgEnqeancak1omY66Pdx3Tyfbd0THIjK9KTJ8zL8beMVsSukS+ZI20dKqtcWRiYy SR/nRYr2jvqVSe1Qljyy9jzTRcQZ/wBcmCeBmpzgJjHFSaDdxIyTxTGYt93jBrB17X4tJkX5/mP8 JHpTbLxJJetiCKJ3K7ggPOKNyuV2udAJc/KeDTyvGay2utTwM2UfI6Z/+vVuzkuGj/0hFRs8AHNG xIXhnYpHEAVY4J9KrRwfY1OADIRye5rRY/KR39awJLe7eaTzp2ZSf3YUdKBpXMXxPo15qsBlVFBH GEHzV55rejXtiIsjfIBkjHQe9erx2cmx1kkn3qv3R0/OpbbwwLu1nFwzSGVNvuoqeU6Kddw0ex5P pek61rNgLqG6w1ucFTyQKSxvrmwmkhf5iwwS4zwK7Cy0q70fUpUsX8h4mwEPImHbNat/oj+IYpBN p0VvfRjCtG2Mn86pR5lpuaOsoNuXwv8AA5zw7plzrmqNcbwUReB0xXpFpocaFJJHO9cbfUVj+EvC 17ou9p5Fy/G0dhXYrGFOep9a6aFJpXkjzcdiVKXLB6eQzyh53mYyelUdcWSXTJkgZhIBnC9T7VoS SLGuWYD61XE0W8fOpLdOetXWmoqy6nNhoOUlJ9DzaUSbz5u7d/tUzINdxrOjNqW3y2SMLzwOTWCf C8wt2m8z5hwYx3rz3Bn0UMVCyvoYtbMP7uJEkcFvc1QbT3TkwyDHXg06KFpDk7lX1pLQ0m+Y2rFt up23p5i/zrvkjx9K84swIrmA5J2ODzXpKMGRT7VpCx5eMXvJikdxTXUMnTNOPTiobmcWts8pUsEG cDqa0OQhcKFwFwRUdUpdetSoYxyq3psJqzBMJ4VlUEBhkZFdFCTd0zlrxS1RZWcqAOuKsrMhUEkV RorSVKLIjVlEuLHg7u9KFycHoKN+RgdPWlz0Ari0R2jiM0EDFL0FQyMGGATTExxdQMAgiq02fuIc FuMU5mCqAo3E9AKdDAQwkflj+lK7Yaj4o/LXHSpcH1oppb0p7DKGorcyHYgjMeON3rWBeIskm5Gh Kntj/wCtXRXMNzKcwyhAOxGapNp8wJy0RJ/6ZipYJ2ZkLEJJdsAgYjkAjp+laUfnLAvmFd+e3Sn/ ANkSIokjlVJCMMQvWrCWZEa75csO+KVjRTRz2r6Fa6m4e4X51UgY965LSfD1zpuvXBjuWji24Dd/ /wBVejTW8iZZhuHqKz7qJGgkyCflI4HNJo3hVaVr6Auo2zWhcXSP5XEjjscUR6nDNYie2ZZIz/FX G3/hS4eNo9PvHjimOZEYYpukCXSNMvYdQZPIhB8pRwDzSuy/ZwaumdpbXzTkDKkHkc1k33iWzg1A 2hlCuv3iRiuR0vXohK0ySKhVPlVn5JOOBW74n0q1vYbWUqv2txnYp4GKL6F+xSnZ7GtdeJ7JY/It 2WWcjnb6Ve0q/luIdsQdFKnknvXM6doTMwMEKKOjMBjFdPb6VHZzo6SuOOUB4Joi2xVY04qyMWbS 7uO+a6klHnB8oM9RWrYQSLIskrP5g5ODjNaUkEchxIue4qIoy9ePQ1ol1RzSm3oy1BdFphGRge9X awory1S7JkmUFTtIJ71pf2lZ4z9oTpnrXXSneOrPPxELSukN1G0N1bnDEFeRjvWBauy3UZCksrdK 6WC7hu4meFw4HBxWfZKUS4kCYk3dx0FTVgpNM2w9aVOEo2LQcsu1fvdz6UqoFYnnJpEaPbkthu9S 5yABXPJ9jpin1Ibhd8DhFBYj0rj7phaK7T/IE5Oa7baqgk9K808davHPcmztdpAALuO59Kynornd hE5z5UUJvFO2cCCIFQfvNXttowe0hb1RT+lfNJPbBz6V9HaM4l0a0k9YhU0W3c0zWlGCg4+ZeqGW BZpEJJ+Xt2NKWYtgLx6mmfbIEZg8gDA4INbpnjjmgiZdpRR/wEVUwF4HQVYa5t2Yr5yg/WoSEbJi cOB1x2rai0nqYV4tq6G0mR60tV/siZPzvyc8Guo5C/EwkiDjjIqRWcDIXPvTEXaqqOFFRJcHzJFJ wq8V5qdtz0Cwz7/YVXmkJIjXjjmjIdty8qaRBvkIwc9KTdxk0WAq4FWB0quisrBR26ipvMXvn8qp DFIwc5pGIUUEg9+agfMj4z8o60PQRKp+TPvSKAW3E59qcoBXBpDGM8UgCTGzNQE053OdppjfQ0MY jhZEKH1yKoPYM5IDjH0rQGeuKB9aBptGMLKR5inQDqaw/Fvhm1fQpFjmMUjdNx4Y9a7QoGOc4PqK qS24uZClwqvEvKg+tNRuUqji0z558g6Ynl3VuWuI2+UdiK0dLv7vUdUjaLEYQYOWxxXZeObjw8lu 9rBAr3uceYh+5/jWH4VsbWe4TyRvmPVOmfrWTjZ2PWhWcqXM1qehWNxDFaGNJFZgN2FOT0q/ZO1x GsrIw3dM8VDZ6bHbxKxiCy98HpVi0vLeeQwRON6dR3qzz3d3ZNIGHIH51iahcXNzHMmnOGnj4Kt0 /Otyc4+X1qGBP3p2hQOpIqoq7sRJ8q5iHT9LgmtUe6gU3BA3n1NTSaRYpllgXJrRVQo471HKNziu xxSiedGblO/QxreQ20rLaxqiM2Dx3q9NNJsKvhT3x3q2Y4Y+CANx/Wqt+CZFCgnIqXBxjZM1jUjO om0RqpIwBmrisNoyaqwRSRygswIxVtcFa5LWO9yuZGv/AGiSz8m1l2O3JPqK8vvbbIfzAVkXqTXr l9HkK4HA61zGvWdqNPnmMAeYr8oAOSaznG53YSt7NWPNRzjjmvfPCrl/C9gx6mP+prz7TrG3W0id rdFkKgnjv+NeieH3B0eFQPu5H60Uo2Y8yre0gtNmatQG0gkJZolJznNTnpSDpWx45XNjbZz5K5qS O3iiyY0C564qWk5H0oAoyDDkCm1PcR/NvHQ1BXbTmpI4akHFjY7wFmEmBt6CqtzOs06iP5QTzTYV 8yTeRu9RV9LRSQGQbRyDXmK8kdhLFGFjGDUi8E8DIpNijAGeKUg7s1oA7ufU9TTGJC0u7HXNLt3j HSgY37wyaQLwcZzmpSOMelABHSgBoDgdvqaZtdH3E5qcdMGgrlSKdhkQCuxPf3pXzt6UiAjNDuEU ljgCkJkWOxpORxUK39nK6hbhCzdBmo/t8EjbY5Qz+goSGWsGuN8W6xexrcWOn4WbYCTnnnHSusa7 WKL5iSfSsK+tIbi4lu1hH2gr8pI9qrVI0pOPMm9Tzaz8N3MbfarmQSSsejc4Jrf0jTZtP1Azx2+z b1bsa62ws9thD58a+fwWOOhq4IEI2suRWVjslXd2inbz3E6l5SFjIxnvXn/iK4u9N8RBrKWTcF+U gdc/zr0GTCsVU/IOgpsFpbS3QmlhR5UGFJGcUpK+hVGqqUudq67HG6bc+KtVnDhisakBi6gCvRYo s4OMetMfciMygZxwKbp1zPOXEsewL0962oRXNZnJjaznHmikkX6Z5iDccj5etPqvcIoiYgYLYzXe 9EeRFJuzKMzG5YgMwHqO1DWjlT/pDk4x/wDXq8tuBtwflx0qOQmMFyDkdq55Ra1Z2RqKVlHoZ1yi 2kElxLPJ5aJ0HJqfR7sXWlQTjIDgnDdeppPO81mDxgqwwQfSmjEVp5MCBVGcCueW52x1WqLE93GE KgBj0xUUVpbXUWXXcR79Kz2lSNcuwXHrWVqPiCS3tiNPbdIxwfYVDdtzeNFy0idFcaXathVcRtjg Z61qaCgitHjDq+18ZU+1eP3+s315eCaaV0lUAAKcV3/w1maTS7sOxLefnJ+gpQmnKxeJw04UeaTu dsTxS44prDIpcn0rU8wa77MULJu6VFMSqlgeQO9VkkdWPIyMZH1OKWtxF5k3d/wqMwJn0qQE9M07 8aaCyZh2Q/f7cZ2961cnBPoKrWMeIQ0gCtnNWuuMdKzirIAByATThwKTtSgEmqAMZ60LT9uDTQMZ PXNOwWADIp44HJpAOMigtT2GHXntWdc6ssbbY1yR1Jq/uNY9xEhuGcLUtgWLfUlmJUqQakciVSoP B61n+XtO5OGqWO4KJmUYJ44qLu4gGlWETiUW6ZByDUTjTdPdLiUJG/KqWOM0anq8VnprXDLkL90f 3jXHWmqrrOsBr1CR/wAso+y10OUYR13Lp0J1W5L4Ub11rtsJ8RrvUDBI9auWsn2qBJmG0HoKq3Wk RzxAxKI5Acj0NXIlkjtgkhTeq8bawk3J3ZvywjBKO5RutVjt4pnTcxjPQDJqzZ3hvLRZomY7+m4Y qnp9pK1wZ54wVcd62FjAxtAUDtSKlyrREYhUj94vzdyKRIRDJuB4PFSuypne6rn1OKq31w0VsZYt rle4PFUlqZu9i4euOtOh+RwoHGK5+0u7q5ug7ZMfQ46Ct63zkE1VJ++icRT5YNMt0hAIwRS0V6J5 BUvb+KxUNKDg9CB3qpJrlkyIPvF+CPSoNd0+4ucNFJ8o5YMRgVzUltPHJtwT6EVzVak4vRaHpYXD UakLuWp1vkrtMkTB19RUJlCsVZWU+4xXAajBrkUbvHcSBA2Qqdav2K6nc2KCdySMsxIIJ+tc0pxb 2sehHDzgtZJodqtxLfXZYABEyoGazTkZB4Iq/sdlbYpJHoM1nyq7yESjaw7CsJa6no0lyrlREqLJ 87DOf5V2/wAPEETXkang4bFcZ04A+grsvAsbx3tyG43RjA/GnT+IzxtvYtHdnpS5FIBihe9dB4Qj AEcjio1t4QciMVMwyCKYikDBFACkAciod3vUx2ng0hiU8gCiyYtehF5QIwTmpQoUc0iLt+vrSsuR jNKwxhPPSnrwM4o24HtRlcc0CFGCagmuobZ8SNjIz0qUc8iq97NFDFvlj3DIB4zQwuRf2pagn97x 9DR/adpn/XDpnoaz7m6t3AEO2P1/dg5p8M9msO2VVdx1OypuI1YZo7iPfG25c4zTmjVwQQKhtwix DyxtVuelT9aYIhNtCq/d5pJoIvKIA5UVN3+YgegpkrIR94Z+tONr2YNtI4vxrEws7dlJEakggdM1 yFnN9nu4pecKwJx6V6LrmnnVtMMMbASKdwyeDXGW/hnUp7gxtDsUHl26UYinJzvFHp5diKSw7hUl a1ztNP1K21BD5D7io+bjpSzq5kLYIXGBTtH0CPS4AqgtI33mPetO5gxDjOcitI0lbV6nnzrWl7i0 XcyrcZfGeAKte5PFZ6boZMqOe4NWorgyuVZNuPTpWKi2by01OY1C5N/qXll2jjB2r1roINPiitdi knI5yScmi4tIGuFm8sbx3qpexX29Z7RvlQfMvrSV07m0mqkVFaIuQKocRlAuOvvVz7vI7Vmadetq CsZISjLwWHSrc7SQwsQQwx0NaLllrHc5580XyzL0M6zLlTmnuCyMFOCRwayLImGIMXGGOQM9K1on 3oDkV1UqnOrPc4K9FU3eOxz9ybhHaN2b6Z61VVyvDCt3UrZpAJEGSBzWb9lwiylSQRnNctWnLmPS w9aEoroyk84OBtzzUyyK+VAxkY4pXgUsDgU6ODMgC8saxs3sdDdtWMito7eNti5J5PvXM3dvdTXE knkEc9q6542jYqwIIqOWzkuo9ittGc5p8jbsVGuoe8upzFvaqiKzAF+5roPD1ybW/aTYWXbg4qxD okKgeYxYj8KszQpbQ7o1Ve1JKzuOpWjNcvcv3vii1sbSW4licrEMsFIJ61iR/E/RmB/dzDn0FcT4 sk+w3qSrM7R3Pyyxhjg/5wKy38OXEkcbWjKyyLu5P3faiVSXQulg6DX7xvU9PX4maIzAfvQfpUyf ETRZHVA0gLHHSvMYfCl0rAu6Djrk1YHhifP+uWl7SfY0eCwv8zPYl1KF1DKrbSMg1INSiA+61c/p I8vTIIi5cquCxq080SNtZwD6GtUzzHSinY6EEdqQsR1pBweOppT8oB61RzC8n6U1lBHB/GnZ45pp NJsBc4GBUFxIIoWcoXA7AVMVwKZJtMbBjgEYzSYGDPO8jlo/PUH+HZ0qS1unif8AeCdwezL0qAAr KwVLg4PUMCP5VZtV/wBLTd5w28neRj8eKkRsqm4cgUNH0XNCnIyKGJ4x61aGipc6aLyQO00kbgbQ UbHFVRoCKCDdTtn1atU5zmoWuo1c5Ykii4Gavh4JnF3OM8feq9Z2X2WHy3cyHdkMetWIrpZRnGKk Yg9OtF33FZDeccVBMHwueR6VYxiinCXK7ilG6sZNzbh03RqN+arwlo5PLZcbv51qvE6FmK8E5qPA POBXUoRk+ZGPtZQi4PYw7i4laUgnGOMCrFpcF4PcHBqxcaekr7lO3nn3pyafEi4XIrL6vK7Op4un yruRwLEFbYNuST+NUtUR3tiD/qv4sVeuLWTyT5R+YDjHFZKTTO72877QwKknsaxnCUHqjalKNTWL 2M+2/s6WHekszyKeu+uh0yzCDz90g3dFLZFclDpsunXEkOEdZDuDg11+k3QltliY/vEHPvWtCV5W ZnjaSjDmhqjQZQwwaoyQBB5R3FXY4wav010V1ww4rraueZGVjHltXjVnAO0HvT7JdwdkH71eQT0r R8lFiKyMWXr83aq9gYRJKInDDPSsFSUZpo7HiZTpuLKse66u/wB7264q25ycgcU27ubLTWae5nSL cMYYgZ+lcvqfjPSFtWFtNK8ueAqkZ/GoqRUVZs2oc9WScINrZdkdBcXcNsAZXxnsOtVrzULQ2TMz BkYEY7iuKttchv5QpZhIegaq3iC5lgtESPIEhwTXG59j14YN8yi9yzYpoup3Ui3dwAqMcRsOo+td M02gxWyw25EQXgFVryu2eSOdXiVmZecAZrpbebz4g+0qe4IxioU9NjqrYW0viZ1MaRXbEWbtLt65 XGKt2+mytKPNUBPY1D4XeE2zoCBLuyfcdq2obqCW4kgjkVpIxlgO1aJX1PPqSlFuKFyLeI7U4UdB XI34uLy8eYuFzwBjoK7Q9OlMOi2jnc6HceTitY0pT2Of6zCg/e1ubaM0hIxtUd6eAMY6kVjCHXCU bz4BjqAP/rVsKpK5J5A5oOMWjvSkcCk70gHEbhkmqd2qXEXlSgkdeDirecVXlmhD+W8qhj271Sa2 YnfoVhpFvtGC44/vGntpsDkFt2QAPvHnFSJOvWNgydM1YBDDNKULaiUk9BERVUKOgGKQg7l5p9Ie oNIYZ7GsyVdsjcd603OEJ9qyJriWSYRiMnGPm7UWuNDlJU5BqdbplbJ59qb9nkLlcVJFbOJAWAxS Wg9C2rMec4zT1I7mkx2pOh9qvmvuRa2w9l4qMxIx5WpCVAz2oIxz2o1WqHuQPAhXjio0gBQ/MQfW rJGRihU4wOlUqjSsS4JsqFCigk5BrKv9LNzIZY3Ctjp610DKAvIBFVH2q3y5xW0JKa5ZIj3qT5oP U5o6ews/OMbGVWwR7VDA8kdxGUyrE45rquDVC80/zpVliIVgcketE6Gzj0NaWMveM+peGdoz170t Iudoz1xzS10HnjJUEkZQjIPBrIF3Z2Gtx2S5M04zjPCgf/qrarmdZuNBtdat5L1yt3xtIY8fWonZ anRQTk3CzenQq+L9Bvdc1KxjiOLYAhyOx9axrv4f21inmz37eWF5UY3MfbivR0dZEV0YMrDII71z 2utYPqlrbXc7q8oIRFHBPFZVaMHeTWp14XG148tKLsl2Rwtvo8FpcGWOR27Ddipb2yS8t/LZiMcg +ldtb6NaxBwV3huhaom0G2XLqGOMnbnrXDKFtD2I4tN3dzjrSwhtI9qKN2OWPemkYkYH73es7VdV uobx40iMG1iMMOtM0eVpnneRmZsjqayutjuUJcvOzZgBMgUXL2+f+Wi9q6zQNIt9OgeWKdp5JfvS seTXIgE9Aa3tIvdQ2xwQWvmRpweMVpTV3Y48WmoOSZ1sKeYxyeB6VcHAqC3QxxBpAA5HIHQVN15r 1IR5FZHzFWbqSuy5tx3NALDtmiiuA6xc7u5B96TJBwfzoopiY7jtVQ2EDtvkRWk7vjBNFFJjJkt4 40CIMKOwqQAAYFFFF2KwUh6UUUDD7w9u9R+TGpz5a4+lFFAmS0UUUAFFFFADXBK4FNSUhwr4A9TR RWtPX3WRPTVEx7elKGxRRWb0ZoGAab5aqrY4z1ooppgyt5BwWTueBTCjL1Uiiit4VJbGMqcWriUU UV0nKwrzrxd4a1PU9e8+3gaSAgAsO1FFZVoKcbM6sHiJ0KnPDex3mn24tNPt4ACNkarz9K5HV9C1 C48TRX8V2MA4GV/1Y9qKKmtFONisHUlGo5I6qK3kMY3EZx19ad9mkI6gn0oop+xhbYz+s1HLcry+ FNO1Rlnv4d8g4GOwqVPDOg6cjOLKJV/iLAUUVyyik3Y7I1qjilzMsRWmkNGxtra3JAB4UcZqaO2C cJGEHfAxRRW1J2jc5q15Ss2Nxlz6DpTqKK6YrQ5Gf//Z