20260209 15293800 1.0 FALSE County_ExportFeatures 002 Projected GCS_WGS_1984 Linear Unit: Meter (1.000000) WGS_1984_Web_Mercator_Auxiliary_Sphere <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/3.5.0'><WKT>PROJCS[&quot;WGS_1984_Web_Mercator_Auxiliary_Sphere&quot;,GEOGCS[&quot;GCS_WGS_1984&quot;,DATUM[&quot;D_WGS_1984&quot;,SPHEROID[&quot;WGS_1984&quot;,6378137.0,298.257223563]],PRIMEM[&quot;Greenwich&quot;,0.0],UNIT[&quot;Degree&quot;,0.0174532925199433]],PROJECTION[&quot;Mercator_Auxiliary_Sphere&quot;],PARAMETER[&quot;False_Easting&quot;,0.0],PARAMETER[&quot;False_Northing&quot;,0.0],PARAMETER[&quot;Central_Meridian&quot;,0.0],PARAMETER[&quot;Standard_Parallel_1&quot;,0.0],PARAMETER[&quot;Auxiliary_Sphere_Type&quot;,0.0],UNIT[&quot;Meter&quot;,1.0],AUTHORITY[&quot;EPSG&quot;,3857]]</WKT><XOrigin>-20037700</XOrigin><YOrigin>-30241100</YOrigin><XYScale>10000</XYScale><ZOrigin>-100000</ZOrigin><ZScale>10000</ZScale><MOrigin>-100000</MOrigin><MScale>10000</MScale><XYTolerance>0.001</XYTolerance><ZTolerance>0.001</ZTolerance><MTolerance>0.001</MTolerance><HighPrecision>true</HighPrecision><WKID>102100</WKID><LatestWKID>3857</LatestWKID></ProjectedCoordinateSystem> 20260209 15293900 20260209 15293900 Esri ArcGIS 13.5.2.57366 County_ExportFeatures File Geodatabase Feature Class dataset EPSG 6.18.3(9.3.1.2) 0 Simple FALSE 0 TRUE FALSE County_ExportFeatures Feature Class 0 OBJECTID OBJECTID OID 4 0 0 Internal feature number. Esri Sequential unique whole numbers that are automatically generated. Shape Shape Geometry 0 0 0 Feature geometry. Esri Coordinates defining the features. statecode State FIPS Code String 2 0 0 countycode County FIPS Code String 3 0 0 fipscode 5-digit FIPS Code String 5 0 0 county Name String 46 0 0 state State Abbreviation String 2 0 0 county_clustered County Clustered (Yes=1, No=0) Integer 4 0 0 v001_denominator Total population under age 75 over three-year period Integer 4 0 0 v001_flag Premature Death flag (0 = No Flag, 1=Unreliable, 2=Suppressed) Integer 4 0 0 v001_numerator Number of deaths <75 Integer 4 0 0 v001_race_aian Age-adjusted YPLL rate per 100,000 for non-Hispanic American Indian/Alaska Native Double 8 0 0 v001_race_aian_flag Premature Death flag for non-Hispanic American Indian and Alaska Natives (. = No Flag, 1=Unreliable, 2=Suppressed) Integer 4 0 0 v001_race_asian Age-adjusted YPLL rate per 100,000 for non-Hispanic Asian Double 8 0 0 v001_race_asian_flag Premature Death flag for non-Hispanic Asians (. = No Flag, 1=Unreliable, 2=Suppressed) Integer 4 0 0 v001_race_black Age-adjusted YPLL rate per 100,000 for non-Hispanic Black Double 8 0 0 v001_race_black_flag Premature Death flag for non-Hispanic Blacks (. = No Flag, 1=Unreliable, 2=Suppressed) Integer 4 0 0 v001_race_hispanic Age-adjusted YPLL rate per 100,000 for Hispanic Double 8 0 0 v001_race_hispanic_flag Premature Death flag for Hispanics (all races) (. = No Flag, 1=Unreliable, 2=Suppressed) Integer 4 0 0 v001_race_nhopi Age-adjusted YPLL rate per 100,000 for non-Hispanic Native Hawaiian and Other Pacific Islander Double 8 0 0 v001_race_nhopi_flag Premature Death flag for non-Hispanic Native Hawaiian and Other Pacific Islanders (. = No Flag, 1=Unreliable, 2=Suppressed) Integer 4 0 0 v001_race_white Age-adjusted YPLL rate per 100,000 for non-Hispanic White Double 8 0 0 v001_race_white_flag Premature Death flag for non-Hispanic whites (. = No Flag, 1=Unreliable, 2=Suppressed) Integer 4 0 0 v001_rawvalue Age-adjusted YPLL rate per 100,000 Double 8 0 0 v002_rawvalue Percentage of adults that report fair or poor health Double 8 0 0 v003_denominator Population ages 18 to 64 Integer 4 0 0 v003_numerator Number of adults 18-64 without insurance Integer 4 0 0 v003_rawvalue Percentage of adults 18-64 without insurance Double 8 0 0 v004_denominator County Population Integer 4 0 0 v004_numerator Number of primary care physicians (PCP) in patient care Integer 4 0 0 v004_rawvalue Primary Care Physicians per 100,000 Double 8 0 0 v005_race_aian Discharges for Ambulatory Care Sensitive Conditions per 100,000 Medicare Enrollees for American Indian/Alaska Natives Double 8 0 0 v005_race_asian Discharges for Ambulatory Care Sensitive Conditions per 100,000 Medicare Enrollees for Asian/Pacific Islanders Double 8 0 0 v005_race_black Discharges for Ambulatory Care Sensitive Conditions per 100,000 Medicare Enrollees for Blacks Double 8 0 0 v005_race_hispanic Discharges for Ambulatory Care Sensitive Conditions per 100,000 Medicare Enrollees for Hispanics Double 8 0 0 v005_race_white Discharges for Ambulatory Care Sensitive Conditions per 100,000 Medicare Enrollees for non-Hispanic whites Double 8 0 0 v005_rawvalue Discharges for Ambulatory Care Sensitive Conditions per 100,000 Medicare Enrollees Double 8 0 0 v009_rawvalue Percentage of adults that reported currently smoking Double 8 0 0 v011_rawvalue Percentage of adults that report BMI >= 30 Double 8 0 0 v014_denominator Total female population, ages 15 to 19 over seven-year period Integer 4 0 0 v014_numerator Total number of births to mothers ages 15 to 19 during seven-year period Integer 4 0 0 v014_race_aian Births per 1,000 females ages 15-19 for non-Hispanic American Indian/Alaska Native mothers Double 8 0 0 v014_race_asian Births per 1,000 females ages 15-19 for non-Hispanic Asian mothers Double 8 0 0 v014_race_black Births per 1,000 females ages 15-19 for non-Hispanic Black mothers Double 8 0 0 v014_race_hispanic Births per 1,000 females ages 15-19 for Hispanic mothers Double 8 0 0 v014_race_nhopi Births per 1,000 females ages 15-19 for non-Hispanic Native Hawaiian and Other Pacific Islander mothers Double 8 0 0 v014_race_tom Births per 1,000 females ages 15-19 for non-Hispanic two or more race mothers Double 8 0 0 v014_race_white Births per 1,000 females ages 15-19 for non-Hispanic White mothers Double 8 0 0 v014_rawvalue Births per 1,000 females ages 15-19 Double 8 0 0 v015_denominator Total population over seven-year period Integer 4 0 0 v015_numerator Deaths due to homicide (ICD-10 codes X85-Y09) during seven-year period Integer 4 0 0 v015_race_aian Crude homicide rate per 100,000 for non-Hispanic American Indian and Alaska Native Double 8 0 0 v015_race_asian Crude homicide rate per 100,000 for non-Hispanic Asian Double 8 0 0 v015_race_black Crude homicide rate per 100,000 for non-Hispanic Black Double 8 0 0 v015_race_hispanic Crude homicide rate per 100,000 for Hispanic Double 8 0 0 v015_race_nhopi Crude homicide rate per 100,000 for non-Hispanic Native Hawaiian and Other Pacific Islander Double 8 0 0 v015_race_white Crude homicide rate per 100,000 for non-Hispanic White Double 8 0 0 v015_rawvalue Crude homicide rate per 100,000 Double 8 0 0 v021_denominator Number of students expected to graduate Integer 4 0 0 v021_numerator Cohort members earning a regular high school diploma by the end of the school year Double 8 0 0 v021_rawvalue Graduation rate Double 8 0 0 v023_denominator Size of the labor force Integer 4 0 0 v023_numerator Number of people ages 16+ unemployed and looking for work Integer 4 0 0 v023_rawvalue Percentage of population ages 16+ unemployed and looking for work Double 8 0 0 v024_numerator Population under age 18 with household income below the poverty level Integer 4 0 0 v024_race_aian Percentage of American Indian and Alaska Native children (under age 18) living in poverty Double 8 0 0 v024_race_asian Percentage of Asian/Pacific Islander children (under age 18) living in poverty Double 8 0 0 v024_race_black Percentage of Black children (under age 18) living in poverty Double 8 0 0 v024_race_hispanic Percentage of Hispanic children (under age 18) living in poverty Double 8 0 0 v024_race_white Percentage of non-Hispanic White children (under age 18) living in poverty Double 8 0 0 v024_rawvalue Percentage of children (under age 18) living in poverty Double 8 0 0 v036_rawvalue Average number of reported physically unhealthy days per month Double 8 0 0 v037_denominator Total number of live births during seven-year period Integer 4 0 0 v037_flag Low Birth Weight flag (0 = No Flag, 1=Unreliable, 2=Suppressed) Integer 4 0 0 v037_numerator Total number of live births for which the infant weighed less than 2,500 grams (approximately 5 lbs., 8 oz.) during seven-year period Integer 4 0 0 v037_race_aian Percentage of births with low birth weight (<2500g) for non-Hispanic American Indian and Alaska Natives Double 8 0 0 v037_race_asian Percentage of births with low birth weight (<2500g) for non-Hispanic Asians Double 8 0 0 v037_race_black Percentage of births with low birth weight (<2500g) for non-Hispanic Blacks Double 8 0 0 v037_race_hispanic Percentage of births with low birth weight (<2500g) for Hispanics Double 8 0 0 v037_race_nhopi Percentage of births with low birth weight (<2500g) for non-Hispanic Native Hawaiian and Other Pacific Islander Double 8 0 0 v037_race_tom Percentage of births with low birth weight (<2500g) for non-Hispanic two or more races Double 8 0 0 v037_race_white Percentage of births with low birth weight (<2500g) for non-Hispanic whites Double 8 0 0 v037_rawvalue Percentage of births with low birth weight (<2500g) Double 8 0 0 v039_denominator Total population over seven-year period Integer 4 0 0 v039_numerator Number of motor vehicle-related deaths Integer 4 0 0 v039_race_aian Crude motor-vehicle related mortality rate per 100,000 population for non-Hispanic American Indian and Alaska Native Double 8 0 0 v039_race_asian Crude motor-vehicle related mortality rate per 100,000 population for non-Hispanic Asian Double 8 0 0 v039_race_black Crude motor-vehicle related mortality rate per 100,000 population for non-Hispanic Black Double 8 0 0 v039_race_hispanic Crude motor-vehicle related mortality rate per 100,000 population for Hispanic Double 8 0 0 v039_race_nhopi Crude motor-vehicle related mortality rate per 100,000 population for non-Hispanic Native Hawaiian and Other Pacific Islander Double 8 0 0 v039_race_white Crude motor-vehicle related mortality rate per 100,000 population for non-Hispanic White Double 8 0 0 v039_rawvalue Crude motor-vehicle related mortality rate per 100,000 population Double 8 0 0 v042_rawvalue Average number of reported mentally unhealthy days per month Double 8 0 0 v044_denominator 20th percentile of median household income Integer 4 0 0 v044_numerator 80th percentile of median household income Integer 4 0 0 v044_rawvalue Ratio of household income at the 80th percentile to income at the 20th percentile Double 8 0 0 v045_numerator Number of chlamydia cases Integer 4 0 0 v045_rawvalue Chlamydia cases per 100,000 population Double 8 0 0 v049_rawvalue Percentage of adults that report excessive drinking Double 8 0 0 v050_race_aian Percentage of American Indian/Alaska Native female Medicare enrollees having an annual mammogram (age 65-74) Double 8 0 0 v050_race_asian Percentage of Asian/Pacific Islander female Medicare enrollees having an annual mammogram (age 65-74) Double 8 0 0 v050_race_black Percentage of Black female Medicare enrollees having an annual mammogram (age 65-74) Double 8 0 0 v050_race_hispanic Percentage of Hispanic female Medicare enrollees having an annual mammogram (age 65-74) Double 8 0 0 v050_race_white Percentage of non-Hispanic White female Medicare enrollees having an annual mammogram (age 65-74) Double 8 0 0 v050_rawvalue Percentage of female Medicare enrollees having an annual mammogram (age 65-74) Double 8 0 0 v051_rawvalue Population estimate Double 8 0 0 v052_denominator County Population Integer 4 0 0 v052_numerator Population under age 18 Integer 4 0 0 v052_rawvalue Percentage of population less than 18 years of age Double 8 0 0 v053_denominator County Population Integer 4 0 0 v053_numerator Population ages 65 years and older Integer 4 0 0 v053_rawvalue Percentage of population ages 65 years and older Double 8 0 0 v054_denominator County Population Integer 4 0 0 v054_numerator Number of people that are non-Hispanic Black or African American Integer 4 0 0 v054_rawvalue Percentage of population that is non-Hispanic Black or African American Double 8 0 0 v055_denominator County Population Integer 4 0 0 v055_numerator Number of people that are American Indian or Alaska Native Integer 4 0 0 v055_rawvalue Percentage of population that is American Indian or Alaska Native Double 8 0 0 v056_denominator County Population Integer 4 0 0 v056_numerator Number of people that are Hispanic Integer 4 0 0 v056_rawvalue Percentage of population that is Hispanic Double 8 0 0 v057_denominator County Population Integer 4 0 0 v057_numerator Female population Integer 4 0 0 v057_rawvalue Percentage of population that is female Double 8 0 0 v058_denominator County Population Integer 4 0 0 v058_numerator Number of people living in a census-defined rural area Integer 4 0 0 v058_rawvalue Percentage of population living in a census-defined rural area Double 8 0 0 v059_denominator Population ages 5 years and older Integer 4 0 0 v059_numerator Number of non-native English speakers who are not proficient speaking English Integer 4 0 0 v059_rawvalue Percentage of non-native English speakers who are not proficient speaking English Double 8 0 0 v060_rawvalue Percentage of adults aged 18 and over with diagnosed diabetes Double 8 0 0 v061_numerator Number of HIV cases in the county Integer 4 0 0 v061_rawvalue Human immunodeficiency virus (HIV) prevalence rate per 100,000 population Double 8 0 0 v062_denominator County Population Integer 4 0 0 v062_numerator Number of mental health providers (MHP) Integer 4 0 0 v062_rawvalue Mental Health Providers per 100,000 Double 8 0 0 v063_race_aian Median household income for American Indian & Alaska Native householder - from the 2016-2020 ACS Integer 4 0 0 v063_race_asian Median household income for Asian householder - from the 2016-2020 ACS Integer 4 0 0 v063_race_black Median household income for Black householder - from the 2016-2020 ACS Integer 4 0 0 v063_race_hispanic Median household income for Hispanic householder - from the 2016-2020 ACS Integer 4 0 0 v063_race_white Median household income for non-Hispanic White householder - from the 2016-2020 ACS Integer 4 0 0 v063_rawvalue Median household income Integer 4 0 0 v065_denominator Public school students, grades PK-12 Integer 4 0 0 v065_numerator Public school students, grades PK-12, eligible for free or reduced-price lunch Integer 4 0 0 v065_rawvalue Percentage of children enrolled in public schools eligible for free or reduced price lunch Double 8 0 0 v067_denominator Total workforce Integer 4 0 0 v067_numerator Workers commuting alone to work via car, truck, or van Integer 4 0 0 v067_race_aian Percentage of American Indian and Alaska Native workers who drive alone to work Double 8 0 0 v067_race_asian Percentage of Asian/Pacific Islander workers who drive alone to work Double 8 0 0 v067_race_black Percentage of Black workers who drive alone to work Double 8 0 0 v067_race_hispanic Percentage of Hispanic workers who drive alone to work Double 8 0 0 v067_race_white Percentage of non-Hispanic White workers who drive alone to work Double 8 0 0 v067_rawvalue Percentage of workers who drive alone to work Double 8 0 0 v069_denominator Adults age 25-44 Integer 4 0 0 v069_numerator Adults age 25-44 with some post-secondary education Integer 4 0 0 v069_rawvalue Percentage of adults age 25-44 with some post-secondary education Double 8 0 0 v070_rawvalue Percentage of adults that report no leisure-time physical activity Double 8 0 0 v080_denominator County Population Integer 4 0 0 v080_numerator Number of people that are Native Hawaiian or Other Pacific Islander Integer 4 0 0 v080_rawvalue Percentage of population that is Native Hawaiian or Other Pacific Islander Double 8 0 0 v081_denominator County Population Integer 4 0 0 v081_numerator Number of people that are Asian Integer 4 0 0 v081_rawvalue Percentage of population that is Asian Double 8 0 0 v082_denominator Number of children in households Integer 4 0 0 v082_numerator Number of children that live in single-parent households Integer 4 0 0 v082_rawvalue Percentage of children that live in single-parent households Double 8 0 0 v083_denominator 2010 U.S. census population Integer 4 0 0 v083_numerator Number of people with limited access to health foods Double 8 0 0 v083_rawvalue Percentage of people with limited access to health foods Double 8 0 0 v085_denominator Population under age 65 Integer 4 0 0 v085_numerator Number of people under age 65 without insurance Integer 4 0 0 v085_rawvalue Percentage of people under age 65 without insurance Double 8 0 0 v088_denominator County Population Integer 4 0 0 v088_numerator Number of dentists Integer 4 0 0 v088_rawvalue Dentists per 100,000 Double 8 0 0 v122_denominator Population under age 19 Integer 4 0 0 v122_numerator Number of children (under 19) without insurance Integer 4 0 0 v122_rawvalue Percentage of children (under 19) without insurance Double 8 0 0 v124_rawvalue County affected by a water violation: 1-Yes, 0-No Integer 4 0 0 v125_rawvalue Average daily amount of fine particulate matter in micrograms per cubic meter Double 8 0 0 v126_denominator County Population Integer 4 0 0 v126_numerator Number of people that are Non-Hispanic White Integer 4 0 0 v126_rawvalue Percentage of population that is Non-Hispanic White Double 8 0 0 v127_denominator Total population under age 75 over three-year period Integer 4 0 0 v127_numerator Number of deaths under age 75 Integer 4 0 0 v127_race_aian Age-adjusted death rate per 100,000 for non-Hispanic American Indian and Alaska Native Double 8 0 0 v127_race_asian Age-adjusted death rate per 100,000 for non-Hispanic Asian Double 8 0 0 v127_race_black Age-adjusted death rate per 100,000 for non-Hispanic Black Double 8 0 0 v127_race_hispanic Age-adjusted death rate per 100,000 for Hispanic Double 8 0 0 v127_race_nhopi Age-adjusted YPLL rate per 100,000 for non-Hispanic Native Hawaiian and Other Pacific Islander Double 8 0 0 v127_race_white Age-adjusted death rate per 100,000 for non-Hispanic White Double 8 0 0 v127_rawvalue Age-adjusted death rate per 100,000 Double 8 0 0 v128_denominator Total population under age 20 over four-year period Integer 4 0 0 v128_numerator Number of deaths under age 20 Integer 4 0 0 v128_race_aian Deaths under age 20 per 100,000 population for non-Hispanic American Indian/Alaska Native Double 8 0 0 v128_race_asian Deaths under age 20 per 100,000 population for non-Hispanic Asian Double 8 0 0 v128_race_black Deaths under age 20 per 100,000 population for non-Hispanic Black Double 8 0 0 v128_race_hispanic Deaths under age 20 per 100,000 population for Hispanic Double 8 0 0 v128_race_nhopi Deaths under age 20 per 100,000 population for non-Hispanic Native Hawaiian and Other Pacific Islander Double 8 0 0 v128_race_white Deaths under age 20 per 100,000 population for non-Hispanic White Double 8 0 0 v128_rawvalue Deaths under age 20 per 100,000 population Double 8 0 0 v129_denominator Total live births during seven-year period Integer 4 0 0 v129_numerator Number of infant deaths Integer 4 0 0 v129_race_aian Infant death rate per 1,000 live births for non-Hispanic American Indian/Alaska Native Double 8 0 0 v129_race_asian Infant death rate per 1,000 live births for non-Hispanic Asian Double 8 0 0 v129_race_black Infant death rate per 1,000 live births for non-Hispanic Black Double 8 0 0 v129_race_hispanic Infant death rate per 1,000 live births for Hispanic Double 8 0 0 v129_race_nhopi Infant death rate per 1,000 live births for non-Hispanic Native Hawaiian and Other Pacific Islander Double 8 0 0 v129_race_tom Infant death rate per 1,000 live births for non-Hispanic two or more races Double 8 0 0 v129_race_white Infant death rate per 1,000 live births for non-Hispanic White Double 8 0 0 v129_rawvalue Infant death rate per 1,000 live births Double 8 0 0 v131_denominator County Population Integer 4 0 0 v131_numerator Number of other primary care providers Integer 4 0 0 v131_rawvalue Other Primary Care Providers per 100,000 Double 8 0 0 v132_denominator County Population Integer 4 0 0 v132_numerator Population with access to at least one location for physical activity Integer 4 0 0 v132_rawvalue Percentage of the population with access to places for physical activity Double 8 0 0 v133_denominator Percentage of the population food insecure Double 8 0 0 v133_numerator Percentage of the population with limited access to healthy foods Double 8 0 0 v133_rawvalue Indicator of access to healthy foods - 0 is worst, 10 is best Double 8 0 0 v134_denominator Number of motor vehicle deaths Integer 4 0 0 v134_numerator Number of alcohol-impaired motor vehicle deaths Integer 4 0 0 v134_rawvalue Percentage of driving deaths with alcohol involvement Double 8 0 0 v135_denominator Total population over five-year period Integer 4 0 0 v135_numerator Number of injury deaths Integer 4 0 0 v135_race_aian Injury mortality rate per 100,000 for non-Hispanic American Indian and Alaska Native Double 8 0 0 v135_race_asian Injury mortality rate per 100,000 for non-Hispanic Asian Double 8 0 0 v135_race_black Injury mortality rate per 100,000 for non-Hispanic Black Double 8 0 0 v135_race_hispanic Injury mortality rate per 100,000 for Hispanic Double 8 0 0 v135_race_nhopi Injury mortality rate per 100,000 for non-Hispanic Native Hawaiian and Other Pacific Islander Double 8 0 0 v135_race_white Injury mortality rate per 100,000 for non-Hispanic White Double 8 0 0 v135_rawvalue Injury mortality rate per 100,000 Double 8 0 0 v136_denominator Total number of households Integer 4 0 0 v136_numerator Households experiencing severe housing problems Integer 4 0 0 v136_other_data_1 Percentage of households with high housing costs Double 8 0 0 v136_other_data_2 Percentage of households with overcrowding Double 8 0 0 v136_other_data_3 Percentage of households with lack of kitchen or plumbing facilities Double 8 0 0 v136_rawvalue Percentage of households with at least 1 of 4 housing problems: overcrowding, high housing costs, or lack of kitchen or plumbing facilities Double 8 0 0 v137_denominator Number of workers who commute in their car, truck or van alone Integer 4 0 0 v137_rawvalue Among workers who commute in their car alone, the percentage that commute more than 30 minutes Double 8 0 0 v138_denominator Total population over three-year period Integer 4 0 0 v138_numerator Number of drug overdose deaths Integer 4 0 0 v138_race_aian Rate of drug overdose deaths per 100,000 for non-Hispanic American Indian and Alaska Native Double 8 0 0 v138_race_asian Rate of drug overdose deaths per 100,000 for non-Hispanic Asian Double 8 0 0 v138_race_black Rate of drug overdose deaths per 100,000 for non-Hispanic Black Double 8 0 0 v138_race_hispanic Rate of drug overdose deaths per 100,000 for Hispanic Double 8 0 0 v138_race_nhopi Rate of drug overdose deaths per 100,000 for non-Hispanic Native Hawaiian and Other Pacific Islander Double 8 0 0 v138_race_white Rate of drug overdose deaths per 100,000 for non-Hispanic White Double 8 0 0 v138_rawvalue Rate of drug overdose deaths per 100,000 Double 8 0 0 v139_numerator Number of people who are food insecure Integer 4 0 0 v139_rawvalue Percentage of population who are food insecure Double 8 0 0 v140_denominator County Population Integer 4 0 0 v140_numerator Number of associations Integer 4 0 0 v140_rawvalue Associations per 10,000 population Double 8 0 0 v141_rawvalue Higher values indicate greater residential segregation between Black and White county residents Double 8 0 0 v143_rawvalue Percentage of adults who report fewer than 7 hours of sleep on average Double 8 0 0 v144_rawvalue Percentage of adults reporting >= 14 days of poor physical health per month Double 8 0 0 v145_rawvalue Percentage of adults reporting >= 14 days of poor mental health per month Double 8 0 0 v147_race_aian Average expected number of years of life from birth for American Indian/Alaska Native Double 8 0 0 v147_race_asian Average expected number of years of life from birth for Asian Double 8 0 0 v147_race_black Average expected number of years of life from birth for non-Hispanic Black Double 8 0 0 v147_race_hispanic Average expected number of years of life from birth for Hispanic Double 8 0 0 v147_race_nhopi Average expected number of years of life from birth for non-Hispanic Native Hawaiian and Other Pacific Islander Double 8 0 0 v147_race_white Average expected number of years of life from birth for non-Hispanic White Double 8 0 0 v147_rawvalue Average expected number of years of life from birth Double 8 0 0 v148_denominator Total population over five-year period Integer 4 0 0 v148_numerator Number of firearm fatalities Integer 4 0 0 v148_race_aian Crude firearm fatalities rate per 100,000 for non-Hispanic American Indian and Alaska Native Double 8 0 0 v148_race_asian Crude firearm fatalities rate per 100,000 for non-Hispanic Asian Double 8 0 0 v148_race_black Crude firearm fatalities rate per 100,000 for non-Hispanic Black Double 8 0 0 v148_race_hispanic Crude firearm fatalities rate per 100,000 for Hispanic Double 8 0 0 v148_race_nhopi Crude firearm fatalities rate per 100,000 for non-Hispanic Native Hawaiian and Other Pacific Islander Double 8 0 0 v148_race_white Crude firearm fatalities rate per 100,000 for non-Hispanic White Double 8 0 0 v148_rawvalue Crude firearm fatalities rate per 100,000 Double 8 0 0 v149_denominator Population ages 16 to 19 Integer 4 0 0 v149_numerator Population ages 16 to 19, neither working nor in school Integer 4 0 0 v149_rawvalue Percentage of teens and young adults ages 16-19 who are neither working nor in school Double 8 0 0 v151_denominator Men's median earnings for full-time, year-round workers Integer 4 0 0 v151_numerator Women's median earnings for full-time, year-round workers Integer 4 0 0 v151_rawvalue Ratio of women's median earnings to men's median earnings Double 8 0 0 v153_denominator Total occupied housing units Integer 4 0 0 v153_numerator Number of owner occupied housing units Integer 4 0 0 v153_rawvalue Percentage of occupied housing units that are owned Double 8 0 0 v154_denominator Total occupied housing units for which housing cost burden is computed Integer 4 0 0 v154_numerator Number of households that spend 50% or more of their household income on housing Integer 4 0 0 v154_rawvalue Percentage of households that spend 50% or more of their household income on housing Double 8 0 0 v155_race_aian Percentage of annual Medicare enrollees having an annual flu vaccination for American Indian/Alaska Natives Double 8 0 0 v155_race_asian Percentage of annual Medicare enrollees having an annual flu vaccination for Asian/Pacific Islanders Double 8 0 0 v155_race_black Percentage of annual Medicare enrollees having an annual flu vaccination for Blacks Double 8 0 0 v155_race_hispanic Percentage of annual Medicare enrollees having an annual flu vaccination for Hispanics Double 8 0 0 v155_race_white Percentage of annual Medicare enrollees having an annual flu vaccination for non-Hispanic whites Double 8 0 0 v155_rawvalue Percentage of annual Medicare enrollees having an annual flu vaccination Double 8 0 0 v156_rawvalue Average traffic volume per meter of major roadways in the county. Double 8 0 0 v159_race_aian Average grade-level performance for Native American 3rd graders on English Language Arts standardized tests Double 8 0 0 v159_race_asian Average grade-level performance for Asian/Pacific Islander 3rd graders on English Language Arts standardized tests Double 8 0 0 v159_race_black Average grade-level performance for non-Hispanic Black 3rd graders on English Language Arts standardized tests Double 8 0 0 v159_race_hispanic Average grade-level performance for Hispanic 3rd graders on English Language Arts standardized tests Double 8 0 0 v159_race_white Average grade-level performance for non-Hispanic White 3rd graders on English Language Arts standardized tests Double 8 0 0 v159_rawvalue Average grade-level performance for 3rd graders on English Language Arts standardized tests Double 8 0 0 v160_race_aian Average grade-level performance for Native American 3rd graders on Math standardized tests Double 8 0 0 v160_race_asian Average grade-level performance for Asian/Pacific Islander 3rd graders on Math standardized tests Double 8 0 0 v160_race_black Average grade-level performance for non-Hispanic Black 3rd graders on Math standardized tests Double 8 0 0 v160_race_hispanic Average grade-level performance for Hispanic 3rd graders on Math standardized tests Double 8 0 0 v160_race_white Average grade-level performance for non-Hispanic White 3rd graders on Math standardized tests Double 8 0 0 v160_rawvalue Average grade-level performance for 3rd graders on Math standardized tests Double 8 0 0 v161_denominator Total population over five-year period Integer 4 0 0 v161_numerator Number of Deaths from suicide Integer 4 0 0 v161_other_data_1 Crude suicide rate per 100,000 population Double 8 0 0 v161_race_aian Age-adjusted suicide rate per 100,000 population for non-Hispanic American Indian and Alaska Native Double 8 0 0 v161_race_asian Age-adjusted suicide rate per 100,000 population for non-Hispanic Asian Double 8 0 0 v161_race_black Age-adjusted suicide rate per 100,000 population for non-Hispanic Black Double 8 0 0 v161_race_hispanic Age-adjusted suicide rate per 100,000 population for Hispanic Double 8 0 0 v161_race_nhopi Age-adjusted suicide rate per 100,000 population for non-Hispanic Native Hawaiian and Other Pacific Islander Double 8 0 0 v161_race_white Age-adjusted suicide rate per 100,000 population for non-Hispanic White Double 8 0 0 v161_rawvalue Age-adjusted suicide rate per 100,000 population Double 8 0 0 v166_denominator Households Integer 4 0 0 v166_numerator Number of households with broadband internet connection subscription Integer 4 0 0 v166_rawvalue Percentage of households with broadband internet connection Double 8 0 0 v167_rawvalue Higher value indicates larger levels of school segregation Double 8 0 0 v168_denominator Adults age 25 and over Integer 4 0 0 v168_numerator Adults age 25 and over with a high school diploma or equivalent Integer 4 0 0 v168_rawvalue Percentage of adults age 25 and over with a high school diploma or equivalent Double 8 0 0 v169_rawvalue Average gap in dollars between actual and required spending per-pupil Double 8 0 0 v170_rawvalue The hourly wage needed to cover basic household expenses plus all relevant taxes for a household of one adult and two children Double 8 0 0 v171_denominator Median annual household income Integer 4 0 0 v171_numerator Estimated annual cost of child care for two children Integer 4 0 0 v171_rawvalue Percentage of median household income required for child care expenses for two children Double 8 0 0 v172_denominator Population under age 5 Integer 4 0 0 v172_numerator Number of child care centers Integer 4 0 0 v172_rawvalue Number of child care centers per 1,000 population under 5 years old Double 8 0 0 v177_denominator U.S. citizens ages 18 and older Integer 4 0 0 v177_numerator Population who voted in the 2020 U.S. Presidential election Integer 4 0 0 v177_rawvalue Percentage of citizen population aged 18 or older who voted in the 2020 U.S. Presidential election Double 8 0 0 v178_rawvalue Percentage of all households that self-responded to the 2020 census Double 8 0 0 v179_denominator County Population Integer 4 0 0 v179_numerator Population living a half mile or less from a local, state or national park Integer 4 0 0 v179_rawvalue Percentage of the population with access to parks Double 8 0 0 v180_rawvalue Percentage of adults with any of 6 functional limitations Double 8 0 0 v181_rawvalue Library visits per service area population Double 8 0 0 v182_other_data_1 Number of weeks in moderate or greater drought Integer 4 0 0 v182_other_data_2 Number of days above 90F Integer 4 0 0 v182_other_data_3 Number of presidential disaster declarations Integer 4 0 0 v182_rawvalue Combined occurrence of three adverse climate event categories Integer 4 0 0 v183_rawvalue Percentage of adults reporting that they always, usually or sometimes feel lonely Double 8 0 0 v184_rawvalue Percentage of adults reporting that they sometimes, rarely, or never get the social and emotional support they need Double 8 0 0 year Release Year Integer 4 0 0 PopHealthWellbeing_Group Population Health and Well-being Health Group Integer 4 0 0 CommunityConditions_Group Community Conditions Health Group Integer 4 0 0 Shape_Length Shape_Length Double 8 0 0 Length of feature in internal units. Esri Positive real numbers that are automatically generated. Shape_Area Shape_Area Double 8 0 0 Area of feature in internal units squared. Esri Positive real numbers that are automatically generated. 20260209 iVBORw0KGgoAAAANSUhEUgAAASwAAADICAYAAABS39xVAAAAAXNSR0IB2cksfwAAAAlwSFlzAAAO xAAADsQBlSsOGwAAIABJREFUeJzsvWeQHemVJXbSPG/Ke18FVwUUgIZpoNEO3c1mk2xDNodjOJzZ EGOlnV+rVUihjY2NGIV+KGIjpD9SaEbSGi5nuMMd+mlv0N1sh4a3BRTKorx5VfW8d5mpuN9zmfny lUEV0GiSJ6Kiqp7Jl5kv837XnHuu+C8++S8KAIjTa8j2NaISuHgK0ntXMCTPI4Y0hpWlstf8y+qX kPraftWbuOKf/FoYB8U2tD/yCO4XZEnCtV/9Ep4TrdvajunGHDKHOjT7vxG4ZAZtI2EcfvXVdV8X 8/mwMjKC3iee2NR25WwWS5+fxZ/+6fc3fO38zDQCfj8GHzmy7uvCoRBuXLmEp557flP7sLbiwWvv vYP93/pWxWNaHR9Hz2OPFR9TFAWzFy+i++TJ0gsVBVPnz8O/tIC1ZjOk9triU+LECqTOOigW0fAz +EAMSGchN1VpHhdGl/DLW7+BF1H2vwtWfKv+OIZ74obbsaZ5nAj1InO8R7udeT/kBhcUq0nznbbe CeKR7/6R5rVTX3yBhl274GpqKj6WikbxxfkziO+u17xWHPew7co1Ds15MN2cR+Zwp3YfptegOCyQ G92ax6PXb2GoxqN5zJkQ8Gfu59H7+OOqzSoYPXMG/S+8oHltcGEB0bW1sntv+POPMd1COylojtl0 dRrpU7srXv/W168h+W3jayx68TqGmrzF/48NO/B38c/wPetJ/Nt/9b+jqroG94rbFz6HCD6/U7LC LhoukWYXklzrKN+ZWoBvbERXRETNvB2LCKJNrMPggVOAyCPjtFY8SMViQsIfuued/QM2D24DQ8tz HHvNRq8rbY/f8umnbbcePMiMVlVbG6rb29m10XvqFHpkGcHFRYR9a1hYmUOozlRcFCsZLEXgwcfT G35uO1cDZ4LHgSk7Mia2FhchcQrMWR58OgrTjVnt/kZT4FdC7DouvUFG3J/G2EcfaV5LxokMlh7C gh+mWEy73VACQiAOWEqGEFCgxFLYDpQK57z7xAlc+8UvcORP/uSetivMeuFPeeG9VjKQNs4KTvWB 7XLl60aUOdCzhZcXXtlsrobVZsd2cODkkyheHdndTUUrj6xk+Abaz6hdYj/NYj36UI/WqBNyVz0U U8lKG0Fx27B2cwp9kgReWP+124YkA8LWb7LfBWSzWTwsMNvt6Hz0Udx5912kYjE07d3LHud4HjUd HeynU3kEC9evYy44imjCD4UMhv5u5MiYpcHFUuAiCfYAeSLFxVYFrxJFJBHDYqeAkDNr6GHVB5uR Pdy1sYeVysA+HMTe557TfsbUVNl2BZMJfK0LmUPkspQgTnhwavApuJubi48psowrv/kVAp+Nag8z mQF4HopZe39wchzYpGOSjETQNjhY5qVHfF5cee8NSLEkYBZgc7gQDfjBO6vARZPMYNPx3uKn4O/V nzetcW2fq4I4Uh5hJRJRtv3WWfrCco/RAvFS1aOoNru3ErBUhPFytgl46jLsd40CWDe5J9EqE3NN 1V/eToIMoWg2My9RIW/v9xDhUPC+bHez3pjR+/Z97WuYuXgRmUQC7YcPlz3fceQIajo7cP7yb5nh UArhUyoD0+0FZB7pZkaMHufDSSCVhZKVtGFWHmuI4A35Jo4mBwHnDtwhm4SUzSJrU3tR60NxWJE+ tk/zmDDjhWIzlYW98vUh+maxEWJ+P7u/6HwW4BkZwfjwdUT6G6BY3RDmMiz0poiKa6gBH02xe4U+ 03RhEskmecPPoQVH0qePkhl8fuY9LCgBzcOt4gn88J/9G4x/8CFS8TjMZgvuu8Eiy8/FcwZKD5Mi lvy+DZDe34aRq+dx4sX18zzbAX8P4cvvCjq6ezA5Prbj221oakI2mWQ5knsxXILZjL4nn8TK6Chm L12CvbYWdT09Gk87GYki3dugCQmZx3FrAVKb1r0gjyB5ewJZK8+8rhOO3YjFY+DBgwKSGtjhF8h4 GF+zXzXUyy48myzl+wjpRBzByCJmLlwoem3e6Wk09/ez/+OBAJbGRzETmEdqoBGK3Zx7I3mlFH0I gGKyQXLZitukBUEd+q0Hxaw1HZykII0skrpzLkOByWpFbXc34rEIXNvIYRFEy3tDuj1RjPNQigLZ Wf6wWRY2n5wWeAS5JKYuXUT30WP3PzR8SOGdmgYvlK8Vsiyx0EIDRcHa4gI++/gjyJIMjs/lnhqb miEanL9YNIbJMW2ooUckEkYikcT4yJ1N7zPlbfzT04bfdSIQQDoWyz3PjkMGz5cvHCaLBaaGBvim pli4WNWqKo4YXXKq8EyPSdcaQg4JqAbsdSaYb8s4q4yz514xPZJ77ncEdfWtOPK0tkBCRQ5C4549 xcd6Tp3ClZ//DKlUAlPLU0gf6QKa7k80s1UE5uYgHDi27e2IqW8c3NQLaSXDlctlj1tkExSDXEIl ZAbaMBINwfvemxh84hnYqrTu7+88OA4urh7CVHkl05v8Lfa+9E2IFq3b3Lh3LyjdHFhYgJzNoK67 GzOpFJAtT0Ivh4MQU5TnWQdmE9DVgSmD91dCQ70bT7bKxh5WK32HbnBsPQV+8ZvLePmP/rjyxto6 cfnKJXiTSdT39rKHkvHYNhIUWmR4CTL/+7kYcnVujLnjUJq0FcgvG52PHsfU2AjqTzVsazvbvkQE hcNW07wUM68OWOGZn0ZPlTan8fsADiYISnXZ49XOFvCiCFt1+XMFLycZjVZ8nmCy2eC6DznChNOO nu4G8JtYnExmM6rrarHq8WB0Yhx7du1Ga2sbLNZSXvGV9nZ88M5bmF69gNquLiSiEaAmt22WYI8m obisLNfCr0VYqMils8zjpIphJdhgRp+zC70rJkAXtrBtSzKcUQlVI9pqXiwYR3AxAEUoHR8nK/D5 ovjgVz/RboNypAKnLTRRTiiShCmkzTXx0SQurL6l3RcKYui1Ub92u9EUgtkA0rrqZmNteUWyEura OuDh1wwLEpuBKy7CnFHlsTggLVICEdr9T6S1ha1MFhaYYEc+9MyDgvR0PM4S/6lY9J7TCgXs0Jp2 D+CA0cgcbCOWYty9E3DUUUJxAw/jD9gy5uZWce3GLI4d6d7wtZFQCG//9iNYGupRc3AQNyYm8PZb b+DggUHU1tbhwOEcH+j5b72Ef/e//jUcNTWYuzUE5XSuiuga82L/kZNYHhmB4/ijiPvCWEyuIn2g A3wwBsvZcaDP+LMP8u1IPzOQLy2WP083mnsqhf3f/Kb2+G4PYU1c01UJszBdnkL6mPaY+eUQYBU1 SX/Kt1GFPdvfWlYllOt1PCxJZhSi7D5tRZHePxfxwO/WugBtqY0T4QXU1TVBuH4H2b3abeu5YYaI p7G7sb+sYMXPeVmRoABprwLx9gI7P8SPKxzb802P5ewaGaV0llGZBHD47LWfMUPVW9uOWDoDp0Vr 1B6YwRIljlUM7hVSSzVu3x1hYVLzPm3F5F6Jo741D9CkJe99VWDlW9hqxIxuBVCuaKME9/2A1e3G rZgDV98YgymTQLOLR1O9C0ce6WFpLbogKf1JMDvtaDg4WAxtKaSt37ULcb8fM8kkxt9/F3aHHTGv jz1f3dmJp//iv8HwlXNIJaMYeOprcNbVo64rZyjofQvn32ccKbr5U6f7sXtmHqnFEALmOMKqfFV/ 7+EtEX5/12B1udDEubCYlbWcMhWIvmEE0ReF3FAFxalNSfDeKKR9rYbGnyqbeiNt/mIcmSd2MeOv ziROLASwe2QI/YfvPZclms+O51it9+BCZgUFiCaBdU7ORkj21ePGzB0cyKTRPri5fFolUKUk5TaX 8Vi+KpCzZnYM6xmjLOWu1gGFlPcDtF3KnXF9Odcm4vdjbnER06/dwKuvHGRufiFctNlsZQsZFVic Dfn8RUcH++XaA6yseNiKTMbt0OPPbGpfiNNnPrgHjhuzqOqqhzg0j1EuAl7hEE/FYH4QPDz6DDVf sQJ3caeRTaeLvwVRhJT/X32euwcOIjJ2FdE6C+OrsRBadX8b0UEIjNu2A5DrXLkKL61gZBsK++YN w/XINnNYzAWmk3+vScrCsroNZDtqsToxt22D9aDB+0veDn1BiiIj7KngbudB3kIlCHITsqm1is/T Db82Obnu9pPhjfk6OwGiJtBNw80FIHyJJF26+dKP78auuVoIt8x4c/5j/POMHeknc+Hl/QCnKKia DEK0JVU7oiBk2Xo+V4898zZIutOZlT04t/Jj9nfAlPtMMlQ1shMTIze0L05mWbgqJRLgUzZGBqUF PLu/HQ8SvC8CLpiA3JwvqskK2s21qGvaXtucSC62sBSA1FWfa88ZXcolCGnFyPn6kNpqK3pgWUrI bRcCv65n8TDCPDSP/vb+Eg2BfrnAiHuJYI68aZQczyTpgqt8zqTU+pU7ohCsBwopHxQsTicWl1bx ZaGYaxEFKO21sC/XQVjicdN7B4N3nIDJwNvMZBELSpi7ekXDpQh6liHwUU1fHagrI56GaVJ7jEI0 hQOnn9MQoKkgcv7d1yBNrJSFUxQ60e/SjivshhYnuBKnSRRYcUE8PgBe10vovT6Ej2u07PqGoAn7 nK2QdpX6GdmpGF1CVhe+UdjGB+OQq3OtMVwiwwiq9xWJDKTehpI3JyuI3V6FSX1+7wGiXO+EMOcr nkhhOYjUswPFPIB4dxV8KM4aT42QNsnsXt02dsBTI/BhSrhvj5y2KUSTjANDN60e4eVlZFIpFkIZ sZHnR6/es8HaCDmDuPOgUJRVeFSP0bH7fOUGlLhiO/V9bhoZCe1RK/7YdhIxJcUaiOVap+FCSz5s 6NxNpE/uKj4vRDOQ6+s0YREllevDHI4++11NiOubni5fYDkOSpUdWX3zM/UNigKkHlUoJMnIrnpw yZTrZ7QleVgyPNwQ0E2tbjqDZUsbe7BcanPEWKm7HtY3r0OuczJGOvU8snOTlcBHklBsZtauIySz ECZWoThKeVCq7gnBBITJNUjuUuJdVuRc2JeVwS8HSr2D6Sz40UVI1J1A++fJXx+yAplyXtvIeRNE suzUDsG8KFmGYjWDi1FrS+6Ly3bVg/dHwdPOGSAoJtFI78P2doTK9TsBKomb7ixuaxt0vKaR5fwG VbF/tY0VCthrYinWamJksO4VnMIhurKGu198YfwCSmxvtJH7ZCjWo1LoUVftZK0qmykAkBGcu3Jl XRKxlMmAXw1DcFlzbSUG4DISMgc7YWp0o4ZoEfT6SFJrKFQgZRKqlhUqdXKNPVcRPF2qWBNtwSem EJifZ9SLAqgoQi0vauIrY3NzNsQpNaCqNMouG7uetDvLwSaVDGPCIrMfWyrH3NfDnNn8vcWljXNp 1CtMnpzcWlPKK/EcJMo9SwpsYys4cuo5mB3a/Nb89euoPtIKV2MjW4QLuHbtcyRanOxYlqZvw1ul sg+7gab5UUZrucuWhxxOm/s3bIoxKynqFEWGM0GGAEHJgoeMDJe7lpjPHOXiWLuTI4XasgLqfTWQ CpUCqsw0unMrj4EdWHEl0EhfSPPmL2gjFFsHtrURBe7qWhw6eWpbm5m7fBkdR49qVlVaaS69+Rsk WqphWo2gqaWTVSV3FhwUCevSPNYmJtbfgiAg6vXCWf/lVUqJQLrp13Ica9Mh5nsBiVAIl5eGILtL bSOo7QYViMiwFJGRjNMLLiv46VVke7XhkhrUOyeshDWJfDJ6GtAN3VVf9j0T102/MJDBtdDtRPlg FWjh59Z0eUXy6gxY/FGbxIyHHryOSEyIW2VoSnB5GJG4yVNkFASmRiEYGn26v6kSTD9q2KurYXG5 WM5Ss027lXlpxLMiY6uu1BJMUgZBTxweJafQQnvFaRQr2NXODNTw1QuYm7oLh9OJlqYmjI6N4qXv /xBZjoMc8+PGtcsYfOpF9nqR3EKyjjNNOevZ4jOj/gFVPO4XHLqTu1VQXoq2oTZYlOzOtNcwQqN5 LQZHTRvuByxOR+X9pzadDd6vZ8nfb9gbGhEKJ1ClNi5bBHksaoPFwquQhRkRDXgOwlKpubvMcymA wrWMDC6aKCvR7xRIA2wzqNSErzYr5FlRSMj6+BJZTTGHvTaRRlVMm4+zJ3mAy2pzY/RaCtF07+e9 EXYeMoMdpfSPDlmXxbACTXk6WkDQtr3rXYSAPS1a8hwPCec+eAdnP/sU/8O//jfwLM4jHo0gk85g dWYcdfUNIB5vU2MjLEoSMZ8HYuD2LQScJXfOmuGhUHy7SZCl9yyOgV+kHjcelrzrRifU4qrWJjEp oDFYQQjpRAY3Pz6D7YDCCzmzPZ2hSiD3/yglV2MxmPo6c1/igwbHsfBoI4NFif8H5mGxwgweGNSE SN5tgzicIzC6OAvsNif4tXzOxFSFWATwbYX0T1xTIjwaMOSNrrXNYiPppWOJThwfPK3ZLn2Hn018 nCORuikszJm43bEG8D25UJQyilwmC94TYsadohS5yQ0umcuDCqPLkPa15NQYKH/Fc8z7JM0rVmTT HHuFYC1feNsuKJkh6T1vKYt/+Pu/x7/+6/8FvLsRre4GjF/9AneGh1FT14C333gN/+P//D/hozNn cCwYwqWLFyHeadbKkdRKOlbuJrhYd+vKS+lUxdjb3MWIfpvaDhk/bBOyAuvnWmG2nQJ5AGrRttnL 5X2VDwIbhaHEzbkf2Aq/y0w36ANIusst1eyHclEHjzxbZqRJyK75fOV8ZiIchSU6X3rAXgVcWYZC CeJMGiZrzsObwUUmj0NeVYHUS4blyj/+I/s7GPYXVSZMC7lNKbE4oqac4ciQJZybhyADtWJ1zptU LPj2Yq5x2V5dg/o8v60IRUHQI2GtWrtAdSsiTJSHUoPyZjWOYhVQXR2UdK8lw2Wa8zGGOjWjC6IJ JlJikRVMrZyHaDKxwpBMbVG5HUE6Fsfs5AgcVgd2P/4ke5QMJUu6SzIcCaFoUAsQsxzMEDWtOjcn byKTTsGkkpiRiYMnmpjxzQeO6N3Vh+defBnDt24imUiw7+PzTz5G377+cqa7Eo0zV5tVEbYBknD9 Ax48KAexEfXhXre7WTQ2OLH6EAgJki5UJh5nyqdGmPj0U+x++umyx6mYQlItLQPU4lPCxZ/8BMe+ Xy5V/d7Hv0ZWndyXFWQuD+Nqk5Zz54oL+Mu259F+SNs/S8bwQSLzSBczNs65KI48elobjgP45G// BomT5VLmfm8Ea9RxQA6GPwRByRnT5qoONIx74KktVbgbU0709HXgkMqrEjke5z54G0+/+F32P8eL +M53X8Vb//Qr/NW/7EAsGmZJdqtFF0ZzQGd3N3zxRLnBmmxPov/OFIQnvlokzgIUjmOlfarafPXA IbWYYORSfZKzAFoVqWpFap1GoIsvOzUC3Pht2XPk9EhkR1SLYVS1MlaqOJPtERMZ+AKk1a1dSZvs HESTAEkV6ssZCfNXr2ryaVS0SK6uorNT6wWlA37DZlii08i6xDSflfFioORxXBmZg89tYQd27sIH xXzPI0efZCoQFMZf/8Uv0DQwcN88z4p4GLqDMlJOC98AxMWKykkmA6SXNKppa0cyK5fJVUtNVYjl 6xgiJ2tmQHBzK5huKVFqHMEquA/36VqhgeueVXSM3kbvvgOQOAHfePVPcOb1X+PH//5v4XA4cPqZ 0+jq6WEe1/7BQVTX1KJ//36k0llU7dkDsctjUIFIRVD3xYRW1/1B82ruEVRJeNiNlaxIiJuvUfGW /Z+WIpDzHGna//FPPilrbXHnBx54RkexODSE6gqKDBGvFz/8/mns6ivPYdFXmEyyzEf5GzkFVqvx XRbwyYhHja1ZXaMMq03XhiMKrMqqlg4iMq10+zK+/yplAkv4P+aMiad0M+hTE5blEF558Xjx/6lQ HCvdWnkiIl+SJDOXN1BVLS1YGhpC26FDv9v6a4pSdo8yTtRaxPj1lJqSJCzcvoW+x7ZXVadFImzX etSOtAlYznn6nC8CZV87YxyknSbWM2p3VaOptQ0pwYHT3/1L1W4pqOk7zESZH3/5++z/Hls9zrz/ OvbX1kLUx8iFvFR1RwNkVYWD8UM2KlHpy64P2sZRdekroOUu12bRcirXf0cgT6RgoLx378I3M1Om I05hCoGUG70XL+F7f/4Xhtv+7P03DY1VEcpDsvqrPK+VsbEcVUB1rGJKYhpg94K+J55gBko95Say sqIVDPxdAgeIkyv5nkFeQ1XI7qlcdSD2e2otiqlz54qPUaWQcnVcuiqnr0/X6D30GU8sj2F89hP2 twger0SfRfbkblYAmPGNw33hEyy2dOHoqSfz+av8PusuTvrft+IpUn1EZlh0cCQVSHpe1RY74DM7 0bKzVbCc3fbvRgqr9KzunSZhVqIukHdI3Be9l1j4n1pABFGA3W5cGDFvosL1MIG8Hjo2tUIpGXJl kyzuzYDIveGVFaTzRr+AZCiU680kb0MUwOXpPNlUGpHV1TKKCPVOrt29qyPyKkAwBn5JrXelQEhI qA+pQi0lx1iPrK1h7a62H5SS3JrtUrfEygpcMQESrw3XhFgG/JI2R8kF44zQrB6bRjCfW5+zRyF2 dWs7qlq0hrzt4EE2KUikRcRpQSqdKvPeAhtw7eJIw4NcJd0J7bWcbnJj3+4+fHDuMo489sS6+lj+ VQ+ml2fRcjSnU294dZOAmDjpQXbXwyGv+sDxJcqT2GpqEFoqn0hSwE4y6+8btnD6WlrqYGpqgr2m RjP5RRia2zFF9tbBQVbRO/Tqq5qwsKa9nVV7x2xhyFW2kp65ksWAu4Y9X8CnP/8Jkk/vwiV5rvhY anQWPx99DTLdvHkb1MS5Mdi+D4vtWv+wz+tC/f5DuGsRMSXP65reg5hRbZfAy0G0tO9Do07PfvGj T/DhF+9pHuvnWnGy+ztbPi/m1SjqT/eWJd0JDbt3oyM/x9Coz/eTz966Zw84u6sJF65cRe+e/nWN VSQUwKUrZ9H+aCkNIJqyXJk3FHJkEZ6Zg6ODBlve5ybJP0ADuniI67UeZI5n47xEg0RyPJ7GF+dG 8djJktZ3AbRIxqKUeC/3fum6SZgUON1EjdA+t7i8hqFb2huqAKudytLaiy4aTWJ+3AezOsyjHkf/ Kt54W0sHWVpcRdd+A3b3YgCiX0uXkdMZvP7WpeL//kUvRFKn4LT5lDUhCUd9ParzZEcKtykJT9QM mqqk+Rw6hxT6UAN1YRukciqJWg+LvD4dn8oqWpBBFlmVt5FRJEi8kpNeUu87OZD0flPpc4rQq5cS 8i0z7D3q7YCGbmnzRVkjyns+jcPE+qgPmIV3NEJNYTwzezSL9ppWTSheCZvRvKN+yJpI6cJxy050 cXXsWBOKzrTxHJbFFF54/CnDbSUyWQx/8TE83mUoZhNbVEgT3t3SAlEvZVFAwJ6Cg/qSHmKDlWs5 yGjzVrrWiPsJEtMzIpBSX2TZMAkV/BPj4OP5m1GWIMVKN2YqlYW1s4KcZuE1koRUMgnRwNt66Y// HG//6h9w7JgMiy48JIPlXVYQ9Fde1XYfUFDXoH1+dGIW/OCRTXcQRIeH0bmvsaR/lU+6j3/8MbhH tLm51NSvDbcht9Ug26ZNqGcHO/A+jcJy23IFocf7wK9SUlnRNAwvZiTEL34Od2Pu83mZQ3xpFV2P PoqdRguqMY/KkkFfJpQKOSw6Z42ifUtUFUMUehKpopjIIDiWJ6GRp1nbjT3uPXDHBTStiVCatCmm mI3H2fdfx+ETT6K+qYUNLolGwhifHMXFj97EgWe/jp6DJX20wvgysTYiahsXCy+wyYwc9jDXBsWx JZw49ixioVJMb3925+SW1wPlXG6MXYXiKV+hlHQGe9ydhmoNhIE97XjlpSP5lBsHq6p8PzPrxeuX 8o3XFWCrqf4qkNI3BbVR20lMZZYwmRhhf/MK8KJ4oHKV0KBhOB7cmMtGnk4d58C8sgmDRQvpDiym VocTMCj8UR6rLDeepzWUEcE5oLm7j3m9tOhuNs1AjdDLd3KTluRoEKa1knTMvBzGLaVE0m02t2K5 XsaqzEHmrWhd8JU1olu72nH2s/eRCYSQlSSE3DwiHS7wXbVlYSoRdsloie6YAJ87A0V3sI0hM5Q9 uuktKRfcnupcg+kG7QZ84gHMhJMUpgde/WVUfzgO6WanIcGWPL/FiVkEPjOQXklL2OfgYSdJjz+g zBMlDhp5rVw4Aa7GCsV+b72A9hTPpI8KWFJ82BcIsOtFjZ6TJ7H41q8QVMkGE/9obnUanSpme/e+ QYwmIjkpljws1VWMza2GHzE0+c1Yq8lC5hVk8qEh25dKq4WRblcFyIxIVw4unioziJSEN12dYYrC 1LZDU7NNsSzq5+NQGhVEggHcvHGOfT4N1bD5kmjuzXdzKAoj1qqxMjGO4NcKwoglHiAbSLEwZnh8 FB5PtCfgngzBdmuW0RsKtkO0WrE7Xw3/8P/5v5E8kavsGgV9JLOdikQgUqd197IF060pzTjvRlMj Mvru6voqiJsYQsA+dPXBKF9S1WwzcfiDBF3wgQMNMFqjaVpKf2K9rDSX00f/igka3ivoWBdv3mR5 kqjPh+jqKkx2O3YPDGDx7ix8gxt4YIXqVWGeJpuqw7FUBiXRCwvx5dol4B9/BIdsLruv6H/rzJJm sg5NKL72858XCzCSJMHCckWq705RcFTowhFOO1KLj/PYO2eFKcszwxm2S0iaZfAf3tAWJChFRQZP FDSj36mBmQjCpGyK28vF85SWMuiCHf+99YXiBq6k7iKMJJON0bfm0PYFbwRcLAnRG0XTmoT2I0cQ VJZxeegLpnwhPdpb+tyz44bM/wIi3jUYzxXnmGoDNTgXPzqV1Zieq7vC6FlOo83jhEISTVv0Nr2T k3A1NVEOS4E9lbPwfYu58mN1TET2dEn/5/cBzD3Oq3WSEXwQ8AdiCAa1pfbFJT/8MzNlWt1qpEIh dgMZgfIA6XQW0zNemA1W7jWfjFi00LdVjmSK3HztAuB2OeCJRjedwyLCaJxUV1UVIDY8Q1GY9I3e o6JFb2dIAAAgAElEQVSEODH7Wy0WNkSh0Lfo/yzIPC21agNrTs7/TQllLhRHIhVBwsPDSrzqdBbW 9jZYBnZjYDyL4brc51ESfKolgT6hHlx/17oRQvWHY3jiv/3vNI8t3BnGTW5Z42HRvi2OXMFMk1Y0 8fFbbgz1lTpjqbDVt2TFlX1RJsVSAAkEHJH3Qh7QyhfbL0zhsW//qWYhJq/z7PDnSLWq8k5ZGX3v JVl/nhokuGkaW4HFYkV7dz84kwl1ne1wP9XE5InGnVHILTsnmUzqpe1iLZ5uzFEPCE6JzpP2vMw3 phAMDkH0cagLicDhXMP3eqB7YWl4GMGFBaSb3bmQkMijg3ftWGrIsPCQVoXBK6NAbRWEXa06xYWH CDvIPqB+rkL7BlWX7hsrWlFwY3QZk//xc+ZJ6PlWxPUhsTga7V4Jnjt3sDQ/B3fVYNlz7731JpIO N87cqix/Qglw+mx9xYww/NtYmcwIGZn+b5RW4o1A1TVi5FPOoQBiVXtXl7F8KddCUwAJIba5D2vk hgsgKR/TvAdSRx0TZqSRWVJ7DcS8rAwT36t1YHJ5Fn5XKVRqXfRi15IdDY01OO3RNt/L1VZkN0hn 7DSoCh9w3ofeSpFHteCAdKAXSigBnrxynof1xjyOf/OVMh4Zfe+0kMgNW+8E2Wj4iSQoWGkpGWOb QRqWFo1A/nuypDdWgSACsX9uDgdefJERjM9/+i7EqbYkZA5YrSnlnOIWGUuKF1/c+gg/CL0I6cTm Bzl+VUGGo/vEiQfyWQ29feh94gnD54hlTAZpPaxX3bE4HGg5uf5xkDEhjtFmk620P5Q/QL49aDNo P3RIk1Cni292cQrZAa2ukikfCtENsTIywi7QkGc5FwIJAJ9Ks/dIbTUQZtaQIeldndaTHkv1adZ+ 1NOxhwn1aT7v2v1R8/gyIbVWM4PO5IrDMWR54ML1zwxfywWjQMP6VWg95q5exezlS8iQ13+01D+4 WZByizXNMVUHGg1IoL/L9o2G56q6a+avXWMcOjVEMlaEmrCIuE1mlq/aCyytLiKMBCZ8k+jN9rCN PWwgPslWdIm+CogHAhtqWZH3Nzszg5gBXyscCmF78oXl2M7syY1A39+Na2eRFhSWg1HazUBnVy6J nJHKdZs2icX6FFqXPTDpDJZierhat9hxbhOK01q60XmOncdKsk7CVIWwhHXGy7h79iz7t2X/fsaj o8rggncBoW/sZ/MGtwJHMic705/thNzXmGumzlOQmJBg/rqiSU8kK02tQtysl4k0rlrGWTuOmlBM ECmO3j1nxWR4AfWww4co3lFyqxBVQBZjHnQOTUGaXoazR5tc/NKxherKl3lT7jQox+ODDMVRXmxI PHTEhQ3AcYj31ObG0heQykCcWUP28PbyqNGgF+bfaGMTwWqFw20H9IaLEtRErORyreGr47mbk2nT m0yIeJZhFqJQTCJk0pg3mdgYeptiRntYyC2cbNg0B5NgQlfQySpkUjbDNKeqkgJspHCQKj1GxS1z Uoa0FM4XDXLng+YrUqsOhXQUCtH3zRRI/PFSNZ+N5uMh8gKkpRCyrTnDTIbK8v4Q0o/tLldsLSiS skEtOsgKquobWVsOefCzly6xvOJEYhmZvq0PdamLW9BpoTwZB5mm56iFFAiiAP/0NIJzc5i9dhWp 5/NSPtReJIrsuH1TU+yHfT1UTFkNQly8PYkO9GBCWWUl2QIo63+K60MAcfzi7luo4ex4BQ+Zwfo9 BeW5SEzQSILmYauYbhUk7ytcmYS0u/Ko9c0iYEniQ0nLrG+LVePb0XZIOpkby2oUx/YezQ1h2FdK dFOI2nn0KPN6C+bz2i9/iSN//Mf5/3ILhHdqGq7GhmKYTQF/IhTG2uQEe78aI2c+wO5TT0NkI9u5 omdNNyUrbOzNVTwpTJ787DPse/559ppH861CpNZR29mZGwzS/zhmr1/DXVVRQupugOnGLNJPlU9T t6YVHGnS6nFRZTYW9qP9yceK6YZ4KARrVRUe2/84xj7/FH4xDT6agnhnkYXoNLiGRpUxEx2MQcny ODpWSjHYLXZkj/Ss+/1QyoB+6AwGVbaHiovU5E+DL9TClaS2Ky4qAUxzLlTBVjRYA1wLauHAdWUO IeSscTXszGW7Z2QlZt13FJKMdDSKlG7Sxz1tKp1mVUKjvqqKyEhMV4hAne1UDt/IwSFmfnBpifXL GfVR0epNX856lUraT1p1jVp46H0btfbQsZLnsBWs3J2A36eduacHGyZrNeWUJThO05pDF5scT0Is m9sXyTXtZiTIU4uYDU/D153FsTU7RF0LEQ2JkEe1OSglmkRL0g6VdhzipP9tk2DL8GiEi7XOHHT1 wCJaYM3yTHVT49ERwilmANR5PaKWUE5QH5aQN65/zOxYha2qWptfVCin6IS9RruwkOdEn6UuuDAl WUXRbJe8Kpo8VBYWmc2sElt4nCgYu6dLJ4CzNiFiAfirq8xoVre1Im3i2feTjXNFqaLiZ2ez7Hqw uUvhc01bG5r25jhXh156BdlkkhnU0PIyrvtmwAeiyO7OFUoKo9HUKX6O5pvmOYllsjfJDLhoCman s2Iele5D9XO0f/QY6wK7pszhCDoxTQkyuBg35Kyi7ShfUALIBMMQ/mnz6ohmXoTFlDsMu90O+zqr fygcRsix9bDs2sWchEUZZAWBlUVEVS2aAjj0u3tgFcsNHE1tvj0yA1/MU649XQFhZ4laQH1URBQM 6aaHGL4PwPgv/lbzGHXy97SU+v/Wm/BMBqHG7jDuJfQs47M3fr7u59ONP2ixMFWIzYAM64ISRrap 8sJAK7vp8jSbwkzJhBzURpGD5WaaGSf1EE+RFBIUBamRu7jhnIPUoLBQSWpyQ+7S3ljc5BIuWLV5 lJqsiP2dRzWtOXRD+K5dhbcqiT01A6gPipjsKORgZbTP+yFvc8rTQwWOw95nntU8dOe99zDwjW9g +O230fvYqaIhpUS2ESg8I6OkrgyTh0kyPeS1FyqOrBUtnutHXG+0PenMW8c9qGluLSMHV7e0wJfc 4kwEUsAwmyE+yvXgojINCyeyFYES7btgTNb7/6QKxsEAFMv/q7aX8YOn/3xTr//k9jms7d2Cd7MB aOU+u/QJZlAq7wvgUSM3oEc6ADlM7HithyNwEvzNb+Fm8/qtMUboXLFgLj956F7Q5rPi29/ZXMe9 58oVvPjs12DNa46r8Z//37/BytH1yZaUwzAaB1UJLPSk1ey+QEH8zjhGar0s57NTiNhz06AIQRXl gbCWXkP9HYuGJ6ZEU5iXrmmoAFQZpcVh+sKFMi+4kOMpIO7zIZtI5EJKmpaezRa1pQr5sOL7s1n2 mNrDosQzGQO1h0/9deTlFSWUldxcSlrMCt6PEcgTIs9wK6BRXjWdnUWvmLZPFIiLP/0HyM0lT4ek d9IpImuvv30aUc/tbsP+g08zbp0eQqXpTlmJTaKfipzTnB86DxSViLXOajRHqlAvunGM78XN1Cxm FT9aUIXlvJ7NZkFhpJuzIqakWQc5r2K6krpALBFFJpuBw+bA1MI0lhN+OHkrjveXCGf3E+Q5/Tz0 CVq463hU6MU+/i+gyCoukiLgUPwUIv73MFW7flj1sML5EMvP0KCEsscA3HX5GRP8QcGVFNnwCnXT vMkTYb2f6hwghdfLw8No3E1eYwlrQ0M42VaH1bXSYpgIeMG7eoohI5OqTiYN+XxkmGjYgx5Tthhk R8m48uEkXH4fGvr62H5Zq6pyXEFFyaUU8oUidVcEhZZTZ8+iPS8Ns1mo1S0KuHX+Y3zYu1BsL2LI 256j4U5NCLgTuUtqHxI8IewdPIbOI6W8H+XsKNdF6rHiWq+IvfG9mHcRpaEOPxhpgV+O4i1laFMf RMMj93LNzFjtbd8PDHZBWQsBsSSyqzGc+fx9NDU04s7iFNLNLqQdZvSNSphPBxE73AFxyY/B+zRe 3QgRJBFRknBKFvRbI1CS2qGSqVADBqNPYrb6/R1d8X8fQMnXLUMhKZadN1bNfjPqdKoUNBiFkzmY zSakdMZTiaSZx6TOm5BBoF7CQj9hASSg2N7SwH4KkHkeiZ4ejTdBBia4uIjGPVqpH2ogru3p0XgQ FIIpiz5NZU/Jymyijlo9teBBkTJtwbhSF8HYhx9i19NPM3IoeUrbVWIgozrqH0Om4x7vgXvIVwvT azjYcaBskLB6ERFpZUvmnQzFAvjMCbyZuMmCJRMEZHRaO05YcFDoQHNTJ5yOajjc1VCqbFAc1tKI bkcuuy8lpjE5WIu70Rhk1RijyYwXme7c/9nWGlyfvGnc8XgfMSC0QckYf6k2tODIVDUu79r56TM7 gXgsjp/9h38Cp+rdKsAfXgWvS9LqQTmecMgDiy6kZPkJA14bS/L7oxBJ2qXwfD6ckhtcue9dkpmO VEWwgoQCfjWkaW/h42nUSSZYVFOXqZWFj8fB2bWkUE5SQOoialiJXWoAR2cnI5vqQYNHpUx5wYE8 E6P+TQrV7hV0hrbTE6qYiTlrMMmZ49B++LA2JA0EMH3uHDuOzuMlwTujCvPdL77QPEahL/XpqUGh bC2qcCLaCjkWx+WmZc1iEI6vIX0pp8dv4a1odneUS9lskHVYvnULPvJE02k0xyWkkwIrKBS8Ujr3 w2c/QVpUYI1k0UnyMuoNkEchVNmwK9mIWtiRUWQMYaGYhCZe1re5w3A9fqTIIN4oxUwCgHoRwEx3 veZLGcuuwhrOAHvXL4NuCes0V9KstO6aHigBY80qRbJgr3gI47HPN5VE3wnQCKRNQxGQWOnQhrN5 yEIIh21d6zaRNpqqIAocpNszmufuTg3h8Pe+Z/i+x/JSOauTkxjPrEDJN9qahhdzZW0a5GkzwXRp KjewkxLrKm4b5SWoq39g4KgmTPJbFDzqaIVD3TeXTOJiZBWSji9EVJv9zgPax3xRw2uQSIpqw1iA 1FHLSv7Ug6hUlfJFWYfZ0LiQx7IZtDfWYsxgyC1V1YyweUOmaIbnKjQs2KDCS7k3YoWT2B3l2KhH k0DvpYWIDBmddzJ2fY8/rnkveYHUq0c5t0IOb2ZmHNyTg2xJtIwuQZA9rJlckDn0LlpwpT/KDEkO SbhmACstECQUKCuMEZCxCpCzlVVbWgYH4VJ1Q+hzfWtzM/B004BYC9umZ+pquUQysd0H0YYzyh0W 7j3N7cGIsow2rhp1cDIPa0chCkgOtiM7XHng5VZBFSvh+jQSFUR26bjsYv26xjYb7kOr+wZCjs1d sNuFS9h87inBRjdVNnD6dgY16GJvTDhQ4yzv3Rudvl220upBlAyFt0PO3+xZWnyExtxkYQoDSAs/ lckN8ewuXYzZ/laYL9xlA0PVYRPlevaZJXS2lfYnGI7iynAC6TZtJY/1Euo0lRg9YT3PzgCZ/e0w 3ZzTqHmS1znju8TyOAVjQvSQsMeDpVu3NO9PJVO4ePW25rF4PInFtIyqtlb2ftZaFI8zQ0GtLYIg MC+IQAMxaPADPVYA6c1bVhaKTHBKrzOP1VGD8d/+NucBKrlkOnk/1e3tRQ+LwkNKkNO+E/GTPBby TkK3h/HKiy8XuWIh4pXFy0mjZDTIqFGuqOv4cSzfvg2fSGma3HdMFdVj511kZRGxybi2N6YyVjlM NEbRd/UW3PY65nErznuzE0TloPNDWJ26C+zNR0E8B6mvsWSw6oMmpg5IzdAXcBcxpNjP58oE9nHN GFdWoWAFcS6N/diPHcc9TOaoBGl+DWeiV7DCCATGwmuR+Fr+6zCGIpnQmmjHbDKcmwC0A6AVqsvv gGAQyrnTIiYuX0Br354NVRFyIc3O687XVtWym3SrFaYiaHUteLckBayiL1QClbxleRuNwTTcwRMF Hyt9R0omi3QonOMAqaeCC+ZcolpWIMRk1NTXo+exx4rhLd3knpERRhKlHzKsB7/97eImRj/6CC+9 9AqO5CcWxWMxDF27gpNP5iRZepmhU/DBW2/h8WeehbOjCyf27GOG5u2338T+l15ir2s7rCVuUiWS tKee++G/YP+TwSEjRbSEAmi/ZElC64EDbHsU/pH+P1FTyKj26rwmCq1SVivaVPMr2zoAn7+8KZ7o ApTYv/nOW1gKLSPo5CDlmfPs1FXbISgczg1U5gbSmK9lZwzOll1sIEYhkZ6OJyCYyt+n9hrV8M/O FqebN7Z3IX55CKEnSo33oiPB49CkA7d745hqzWDvnA1U4yueTEgaJUEvog+fbKUOkbUVzCi+dSd6 DEfv4IT5BORM5ZvTumZHf9SOq3t3Rm6GUzi0N+2DrJtuUsCYnIJrxaOZ52cIVt6WDY1WrvB9rzu4 vhFkngNTBMBDA1oEDj/yuGawLCWhP7v+W6TbS+fRfseDU098XUMbGDlzRpMHIiImhU2kMkFMaz0o XLI7nOjq7S0arPfeeB19e7QUgysXzqOzuwc1qmQ9f+a9MgJoAQme14RGFLaVzdZUfTccxzEDNfzO O4wFT8l9mvKjZobTcVW+A8ohSVkEmq1INjlzn6W/FKqcEKVwmVb9eqAF69LnZ2jjsAeS6O4riSgE V1dzdBGNPpiC/d/4pqZIsURCACoPWnTFRZw/ECn2KFEJsxFuzD2kOtU7BVqlMqYJZDgZdmkQslTy BjiBesViWKtexBqXYUngBzW2jNzy4MIic/n1/Y2UlyCD0fwIldmN9bJmr2zCuBoeioKGuqacZG4F D+v83/0YoYFGKG5V+EpJeIMk9oMCFQNMvRu3Iymu8tewhaEg/KeqSFHeyYgW0H7wIEaHb2FhLse2 Z1wrgxxNa3v5VG7qyJg1GElPXlJdT49mNgAZJL30Dxm0lK6DgcI3CgfDy8vM87pXUIjpnZrCYO0u JH1h3InNQ1LlmfM7taltCZMrbIAIewsNv8gTlZ9+/gWcfLI0dOLy+XN4zTesIfxSu095T6/C8p8F iJ467YVPcjON9mY8PWvB5cw080a+akhGKBRc38AsEcfMfQMLjWmc8C7ADQfipgxckRrcFcaREmR4 3WnErDLa1sxMssTIaNEK37FqKcpmbAc0F6/nsVOsT8wIlBylHBTpZVXC2vgE5j54v+LzgiRhLJqC O7ZU9MgSmRytxLu8CFc2WqajREgEAqz1xLacKU70LYQzRBI2e7RcoEQ4BltcK9YXDaUYA1vNfM7E 45gWRZhujpXen83CGY+hdlVrCINpGe5h1UKayULy3ztfjkr/zDNR5e2YsahEaqRzRF9zQ8lzUjZ5 I7udTjz/6EnNY4l4HL/8rz9l/Yq0gBI1gW1TlpkxLORy2GtDoTLPm7hJRCKlkVxGIZfJbEaShtKa TMWuCEmWyxxkUnzd8+yzRePFfzrCOFGWdOl6T2UktnAXR6EZwJzlIO1qKoaE6kWFOkkqihfIMoS1 KNwLUZrqoQOnmbdoKHdA2lhmpwsvzB3FXHAJV+WvlobQpnwhJceGzggyvmhcYuEafRlc1WyZ2xtw STg84WC5rLhVYqqRJMdDXfV0uYpZDjd3bZ9oSkRB3czJLcNqseLVZysTcVe9Afx2ZA7NqpxHYVVL vPUWm0VnlHinJtzdp0+X9T/6pqfZzUaqoQVQspk8RdJLV+PWm2+ybaiT7pSzoDCMPMoCiBS5dPNm mWbYF//pP+H4NyiJXAIxzo16MsWFAMxLpaBISWYx6v+gqGZKoGpaYGGBLQDFcxAMstBNXTFTw92o nQZk5HkQQ/2jd98Gp8rLCryAhqbmMoNFDdN7nilNh2H7KkmY+ei36BFLXlZIEHFnZITtbwGU66T8 VbfuPBeoCvMzM/iH//AjZKUMJDnneHA2Gw4N9GuoBVQIUYeSp1/4LqbPX9BUE2ekS7CMKUg6jRVS aNgFEcXlcudyQzjmwxjsHETWZaAioUNFfRYapjrRl0bjSiPMc4uavNb9ALmN4tjWW2KM0Fzfjr+s e1Xz2PXpy7gll75sNSgcVtZZOsKOLPO0FhtSbL4clXZnWlLsffQ3aeLrh3h8qWPL11GIbWmqQ+zs dcMxZDa3mxmP+6a2ugVUKvtvdt96dw2wwQUFkAGiRPWup8pn4U2fP59Lvqu8ExpvX/A6tipDRAb0 +KnHNTmsn//k75istboySKChufpjoiNvbG7G3v6Bkue8soK5ZEKTByPvkAws7b9Rtc1t7UCDWWvM IspkafJNJsOuA7XHTvtODdv0uJqwSVrvFJZeD02WeVDCvA9KvxVypAIBXMlNmSpDOgvzzTnsHTiO +p4erI6NYfL2dcwulPpo49Ew+LVS8WxDQaloFXBI6MBl6b41kzGQxnZ27/YlRQqwqmJogntaW5r2 KCG4yv3PdSVgQ6pm5wLIYD0oY3W/B1NQP1klMAUG+nzdzUUeS6WKjxEe1HANSq6rPbmsOVchNOpr I09w7soV7Dl9ulQxjEbhmdTygrxzs+jQN4wrCj7SheCLs7M4dOQY3FWl15Kxkg0M1lbgrK/XeL90 jDRglNRdWQ+jLt85t3SlqP1f+Fw714rYrTl4E6Ow1dei/5vfZDmw5elJOKqq2T5OXLkIu2BZdyBF EcS5iqaYjLVQwWAR/65toLPsOrBP+dDW3oPW3fmFheMQrDdBai8VRkxTwPTM9c0bLOqcvyF58FUD DQgID99BRszdINtVJlUPD/iyQNUrfb/XVsHmIJotRSKhHrFAYEMulhoUHpGXoEeBc6QH5az0uRgq 43+ZoFwWFRrYOcmHjNRXeGNuSKPcyQsxdOpDQBL869Pq3XMGw3XvF1yNjWXGqgCvz4/rk+dRW+PG 8cODLJSQ5BTS9RG4+Q7m9Qy99hrsdXW4a49CkROsAqw82w/5/CTz3pjmll6SWtWVIMx6IfVt/npR Y8/g0XVH1Rew2JDevMEir+Ll6uN4M3iZKTkklQz4YIx1Yz/MoAT2sj1S7Nh3zd67waJkI/1UfD7D sRyXr2r9sJmizqywBiWqbTkxSwIbkEkKlkKruK6OFbfBCp3JZPDJxduVt5FJI5vJYOH69bJt0Wpt sdnAGQwcII7S/I0bZSEReVcFpYHiY6kUM0xssIcq9KRkOunJU/GAPDa60Rgjm+OKjHIyXlyeSKmX QqHj1z9G26J9WlGpHzCmdyDAwiJCKp2CpEiIJaOYuHKBhShmTtQYbEpex1ZWsevZZ9h+UU7OFJpF Qj2xZy2CuevX4RnLFQjoZqN8E+2/urIqmk0s2R0jHXyVR/H+m69rPpMEAbJZCaP5ZHvpxQoabBsr l5gdDnb8lXTc0pksAsEw+6Fs6/7+DsRsd7HnuedYxZEqwr21tVih48kkixphTNeMA8uPEWWiYFTo 966aLtaEXMDY2G8RaF1fqocS+POzM2jvKlFFfD4vXD3dmpziZiAWbiRLhjfsmKd2nZu7Yzgytguf hm8jihSQfABDUrcDsk0q+1QVE+CAFR0oxf9NXBWqIwJSJhlRW2nFMArvyMuk0WfdntwXSkYwZpWY BlZdQEQ6FEe4y6RZCVgfmcGuzWFO8z8Zwu9YT+GR0yWS4HrYaD0SHXbYHj1V8fml27dx4HHj8Up0 8+1raMIjx8tHuv/jmhcdhw+XGTkyCuRhqZPuBVCYRePFCyj8nQyFGHtc/Vxx/27dYl6DkZc3d+1a 2Xvo/8LgDioY6EFJ+TFbKNeG09KKNaTZwIZT7n1sEEcBVJk1Tcxg9rPPsesbL7AmaGUtCHRoF+bO Rx5BtYrzxYZz6Lz3dCaDX/zyZxouFd3sX3/52zCr6AqUdB8dvo19X/tauc79r3+Nf/fX/1bjgciK gioaGpx/LLSY40eSsTcyWOprZXJ6HuaaaTz6wxx5lQxswciy6KPwQ8+9P8Q6E25MXkPv2irqu3ty HQCUWmlu1iTpJ/Ma8OtiHV/h0k9/WjpG+vwj5RXy6mjJqIn0T21YZMaKpuXotYMKyLTZ8ZzrWO6f 1MNtsOQ705hKzSHkzjIRfOdkAncUbUJ/RQlhxROGzWPCLjRiEqvotDQg3eWA3609B864gO8//gT2 7smtLP/nf30Xwy4/owREHTJTvBxpyFUJLWmezXekKSHUwvCgsZGS6GZ747aCBzXH8X6CeE/+cACn dh/G+NkLiNhMaJKtmIuUPI/NgiRg9r/4oiacmv5AO95sPdAN3HXsGNo5oWzx+MnPfooOVVWQPFvy Upkh08FkBuqbch6xyaTAUceVtLXyIE+XvFGh3gyOWr54nunBM36UrGA8lsTk8k1w4xfRFFAw+PIr lfc7kQbnTYFf000ySmVxB3GsBkqUlLmxcRw+dhR1XV3FbgLqJbw+fBFcrOThU7cCDcbJmHJWj80l nGlJstacVp8ZTQETrHYHeDHnylPzInNjqTk3b8RNKQ72u7kcBQnBZc3adb+w4AgZBcqCH1lqitwk X2Ur4GZXkVrOcVUkFakuYsvC05rzdshzDClxzBvNYc7v5yDXhjnFj8nkKg6Nt6O+vQneZoUZH0uW Yy1L//7mp/iadwD//LtPQrGJWKlJF6uEDSGReVskX0KcLfJKqcr6ZYCFKPcDUpatxEbf4pedg9pJ 2G12HOzuhy/ohf3wE/jlubdgra4FL/CQvFFAqxRTrNYVhvASyNshQ6DP/+hB57PawNAUqprWaq2s TUHGRu1NFRLv+rmB9L+5Fjh6pLVIFaHXkkeqLzws3xnGDc8IpF7dCC9qYndZIdNEG5IDt/Oaokmu Z1IuGihqKCe9d/WoLraZtQiq7N2o319q6fOTVpgosn0qcMyI4d4fjeI2t1LUKuM9QYQdOSoRQaQw hkZ90TBVyldRLubZF/6seLKJ1EaoRGZkJ7HCTZLoDeLilY9zkzDuAzL+AK415QoChXFl94ILyhRO cr34RBnDdWUeT/qc4JvsaPWaGZXhbluScbNmM9dx9/9aRDSVIC3pIojqQN5pz5IVthSPgDvLqor7 pzfOQ5AUlKXz4eh1YWFYhdqCuuK1Wahv4q8SKBndUNuIaCwOUziFR77zPMsXUbg6/O674PJ5F8K0 9jIAACAASURBVLPVyryTlgMHNF4mk2tRtcncb4gWCy7+5CeMl0V9gQVjQiE87Rvh9ltvsQIJ/SZq hLpPkWgMlUDjuITlIDIHO7CcDqF9ebkY/qfiMSSanKVGZ7PJMPzjUxnYK9iAyNqaVkPM7YJMpO48 NUehCUfqYy2I1JG3sDtYjVNff1mTPyD3lomQGbBpN1o9hs68i0x/y6Z5WIzPoZMEkVcDiKV1ukiJ 3GoS51LbMlQFLCKIkJLAaW4v07IfjS/gwHg3HIoFlmqeEUwJaVHGmXYP9s7byvJQFFaTkbo0EN2S 8J8gcdhrenAVSLVutx7Mk5a37qFRgt0I91qZpevNKLTdSe+RJsWoc090DLFoFIsrC4zk6XK6cGX2 Dg68+mpRDI8MWehwa6mdJCvDcjEBd0uLJuluxNVy9/biv/z9f2ZcN4vLXTw3osPBwjQycnt1uSzC naGbLDlfQNjjYUl6+q4KPCnKCdL92XPqlOE0b0LM78eBl15Cy8AAy4+pE/X0m3TJ9GeXcn00GSd9 pDunbCHwLF9YKKT4lhaQoBFteR08GsRCVURFlTKiIS3W+SCqnmgxdHTI2G7EbaP7K5G3iZoUfW+q lo2PKjtYn4+5naRkuGmQvAav5IYnbgIJLoXx4CScy7mdz3HIgZRZxmq1Lmd2H+YHUDHhsjKNVlSx PsqPwzne1mMTu2HfW10xxONlwJrkmcuq8ApkjhQ0S4tA4V1s5JzRJijXKUnGhoTCaNVNRRU5Cr/0 7n9h4kphFNJ6Y8XpQq1ktMhIEEExmSxnHLOKVioFXmdI6DGqNhltk1Z5o32hKmXI4zF8jo6BfijM KnuO9sHgc+iYKx03HRPHS5pSPP19Z2EEcnAK5uEl7H3yqRzdo68Hs8hAzibgv3gVe156cf1GdLpB /bGy0jwd9+KtWwjMz7P/qYrKzns6jX06VntL/vUXfvxjDQGUjt/e3MIqjSeeKJFdv/fqH2F8bBSZ 9jZN4zaFoDMXLqD31CnDyhsNRqX9IONL9zgZyQLDnjwvizeOjK6v0nxuHKmn+4syPFJnHUaGJ9A8 N8e2QfwtzmLP3eP59w04O8ELYumad/OQ9pTnvMlgU0GE9omOm3HUTCZEvWvA3pLxJ9miljkLmkJA Y9i6Ma2BQO0UKzTefAsGizhDEfPWVkRK+AcrcxfvO45zPRhStGz4Pq4BwYC2emhJ6S5Q0k6YCYDk 8EzjQA0sTMKGpgaZeRPr3UrJWcTllKE2l3kXx/q59PDNzDA+UPFzFIW1whTC9AKojE/P0U1L552m 9VaC1+vBubPvGT7HRZKQUykMv14+zktaDqBFzAnAaR7PZllYZLT/dEEb7QvdXPRj9BxVvqglRz+K ikC6UurPSSeT8HiXIFfZmIfk+fxd8LNeyJzMFhCJB4J8nDW4E3Wkxt1UDDVoRBWpCcjLQZY7UeeF qORPul/h/E/xeKi3T2e/uPx3oj8+kmtRt/CQsR16/XUYgfJL1JpUCN/YNi5fRs+uXdi1t7+MJT4+ Nlq2DaJl0DZmLl1iRksPOkZikpMKhbu1NXd/rq7mvk+OQ1VdA+K+KGDOm4R4GorVrNEMIzDO1XCQ yTaTPbAP3cCUHINcmwsrKVzUS0pTtVgP+lw63sIxL964wSqRPOsvLDHbSRiyqaYLUnsdWyA0Bosz 0A0h74pcXkKB0q8HJc1olaAG2QJIUEwwZ6HQSOp1UPAf+GimKHD/ZYGmBX2CUhPuI5ZuzPRKCDq1 XsWeuVJIaE4B76dvY14uHWcT3LDBjBlom3+N4IIVL7d+H12Hjhj2pHWdOLGlYxj94IOyHj41JmdH EdtlnE+g6owws4ZIT7l0tD0cQeexY2WrN3k1dIMa7ScZFKN9IW9jLBIxfI7yROtF+erPIcMy/drP kD7aBsg1yIwvY7hxEX6DSrcrIcBd3QOlZeN8Kk2OkWUJv7n1aw3VxxUX0B7v1Hi9nG7+IiHm9bKb T62rThwyogRQrstoFh/RRdS5HAr3auvqjVtadOeSqmvEgieDRb/HP/6YGS11LyR5wfTZ/pmcyizl qD3Dw8yzob9rm1tRS9PqY1ks376FvsefwG2sP4eScmH7nn4G5quXMTE+XVHHPeRdw/il80gkY8XK XzoUYZQYavehhZYWPeqJpGtenJot6uNRDi27q4nJsBOKVx8li6t0zZkEWmnoQu3e4o1DBmzy00+x +ymtC1y2/TyX5E6IdKaNe/22hS2kUW5iATWws2nXx7gumHY1ImivTBOgc9YwJ+Oiylg97DA77MSk M8R6c+aIcGqUk6Ibdqvkv/sBLhzHaHqyjJKy8Rs53Hn33bJrkuV0W1pxTZwvLliUnlBCcwis5can E44qbtTpOWgGRoaS4R1Hj7L8ESnCGnHQ7gWeO3eYcSw4FYWQjxrNqT+Scl7kSKzdvYvjP/iBxliS h0XeHXmDasNGXmXzwABuXy/vUTRC79HjqJ5rYqKDRliSgsg0UphXyK+ZId6NotDpyUJ5jsv1NXZ2 ovXaNZbPK+zrF2deRyBvmsQDgXocbD6E2sYGNPSUk//uGYqyqRaPQqtJ3WgdXpa0I73vFfMTI5iT fcxWUf6bk0Qc58oF2QqzChssVfDaUnByFrwSb4enOoVwLVdMtlcC0R1uxUoX7+8l8heaETYUItxB UCm9Q2jBGgvMNwda6RVZweL+UlKUSvPLyQjmm9Kwpv3oXbTixu6SESSiscbj3kLRh25MCpkoVFYL 7rGhuQaLwScfnIHVZkN9g7biODFyB1UkCxQMMseA9XmqQGKG5DXdPfcF5hGGUmOHrdG1qcZtNeyc Gcp1nVJLVoatrlySgQwNGcrL5z9ki5jsyLPm4ylDn8HN2wz7Oknlo9D/SCCt+Yw3AJHLLbPi1w+9 bMhS3i6oBUMfy64HKhs/dvK5HflsTubxqxs/QrKCprsah4VOLO7hkbbYkJA4OJYVLLZvrmpnDSuY XUfZ9HcJsoEAXtHD2kF1B6q2kWYWeW2Fn3WrkYVkuijA1tmBjolVzNdukk6RNxLFaU8sLBZYgYUq wmkRSFpkOJIC62zQg4ootIVKfZmFIgC1E9FxUAWv/cgRxoCfu3yZ5ZHYDEObjamOEmWied8+5llQ zuvQkaNooMR7NAIxn8gmdPf2YXXFwzzeVV5ESGewCGQM9j3zLKyXL2PMHIFkN5cNr2D8uXUquaf+ /C81/1Mem47DqDBXQKyzBopby8MS72jnNVAlsaO6lVVGC8NqC6BzcvjVV4vGlT7zkdNfL14H4nbn l1UCfdDAt76FB43VyQlEZucwwLXgmqJNThuh1VyHRVOlRprKIKXWu96Nt/8HGBs5msN3/sc/1vSl FfI/FA5Q0p0uWrVXQHpYmu3QBRyKQx5ZYq0kRHLsaOlHenkIK7UZTehupxFSMz5wi6rGZJLe3YB6 4anNoG/RgqE+rRGk7R301bGcCjHNCwl2Sh775+eZ+B4dG6VUqHBCRqj58OGiN0r5Giqe0Cj5J/7q r1gIRoaPPIqLH7wFpdaB2SseprLwQt9RHD2hzfc1q5rg//GdN9lvOqfjn37CaA5qiHYSwasvqWoQ 5eiNN5jBonFhmwGrQl68yPJWqxMTpe9AVYRhrULHNxbEkmsc8A3NQE6nWeM1haHqPlQ9QZkKIgVe 6H1JPlACjT5An4y8nyBLTX1y8zeu40qXF82ONgwsZpi2eyXV1D1oguIUWVWpuO+bGDhBbQL9szZc UUT0c4UbrnThV8HORlLZKpzeNSWa08a/T6DFwgjsQkhlWSKzEvh4xvB5PpJgTbJ6T4IoGSQqZzEo yJDUMN0UVl2SmRKrlBwefOUVTdM0YW1ignH/DPNiisJyNgXQDVjT1k6cGBTWcK6+Cns93dg3m8BA Rz0O9nUyT+iTs7dh79rFpFjUCeuLH76N9bBvzo7Hvv4q9ixMIBz2wJNYZTytJ2qPofcbR1nimIpR BS+BwjHqaaRJyuRJUZ8lHaN+OCg7p4LAuFEFo8z05MNBJA93sIbh4n6myq9f7+oqRm7nqDfh+XnM SFJOEqfNAvmoljNpujVPDY4s9PRNTbGQiySVaR+pcqgGGVSjWYwFVVJ1mE9G+XJovMid5BpbIU6t Mhki9f7zkSRaR8PFnBQN1NjzvT8rantRMYAqxlQwohQDE2XMnxM9vUUkt5Xxa3YwcUqVRXWJ9n6B LDMR4ij0pBCUkoxBzxIkfhVzLWn0cj04HNvFVsOR5CK+kCeKeSv66bDWY601177DHpeJoLaxwaK2 nA6uGY89lhunJUytYpSbRcKiXa1roNPFppU5xaN2ahVeZWODRQZm020vsswMARmQRw0i8XAkjk9u zODQY8aNz1RxI2PQ/cTXDduoFpND7GItM1hUHRZlXE+Vq9LyUgAHTM0avhCBrfT5z9DnuSrJE9O5 oGtUvS0yOPT5roYmOG4sssni2WobpIF28MsBHNvdi0eP5xLKhw914xe/uciMedejjxZvToG8uHg6 14ZC7SAqvhZJ/jbXtjJPiUr4pM65z24vMz5UpVMzx/WolOMLzM6WVVfnlqeh7NGeL+LFhXQ9oB++ +zY6vpn7zAMHBljy/OzNTwxVVOi4OKcV9b19bKEoQL9YsH01m5HIGyx1Bwudf/qu1BEZY/enzcVi DfudV69Qy/IIC3709R0tetM17toyPh3dwzRQQw9mPFXXo3h96DwEswnmhHGC2W4wkmoj0MnbqI9q OyADe/udd9DS389E/Mm7IgavHjPNpXpYo68Oe6bD8CkxHLR0wuS2oVNphFhTyt/RQNCVwDQCro2N CY0+IteWQG57xCax9pyNIAnCpt1auhkXdHIqlcCTQqTVygxPf395f1ogGMOnQ3OGTbKFUIwuqEK1 SQ+SMqayvP7mo7wIkXwL50INaqZ1NTez9+kNVqWbuBIoVKCLWr0tVtFaWWHNs92yzI49FgzANzMF e5bHvr2lY3U4LPjhXz6Fv3ltVEMdGHjkJKaGriHYUwUhGAcXyXtK+QnT4WUP/uOP/jfWX+tKifj6 Kz/ATiA4P888UArjCpwzogLFuEwZN+7jqZv4MJ0joRZg9nmgD77UTcNqUI5OcpgRWVstGiy6R2mA BRlbo7QQDWQlj6wwSYhC282Gjxuh9eBBzF+9WvFaM+pKKCzcYqx//Z6njptbH9dOqzztUPP+/RoJ j50CcUl2P/WUYVLfZDHurF+ty6DO1oXdYZHxdNYcErKBAHZ5vOA7mtiXSmPXG+uckO/cwHxTilWE vkyQR2Gk170eIp4HL7a4rdFiBqBKkf4mYgx4XdKYzg/1z9FKT9cCGSC6ITM+H773xH64VVpWlUDe 0szyFORGF2u54aJJ9A5lwM/FMJKYwzuYwmR2jYZZ4hDXjq9X2A4ZHlowMpk0okE/UyigMxMPBJmx LeSPqLhE9weFU4Mvv8wY8eT1EU+Lwku+RuthmkYWkRnsKGtZU2a85Wx/bwiUm6eBo2qDR1OY+WAc E/FxjA9dRkN3D1ILa/DUcUCfC16/NizE8W62EFC4WqjkEU1CX2XMpFPsfHGFKesmgbXYKQXyqfq1 Oo8qk0oVBQJp3wuDZ8k4Fjo32HHKMus3LKiM3JccFl1Y/S+8sOPbJSt79Wc/Y6S4ShVIFidXKBIR TUFNVaBhG6HMFFyzs+hNNkA8sZ8xdpuOnUDbBzdxYW+IcW82AunBb+WWtcKE9rw2F/39VYA+rNPg XnoGFaXYuqIPAWgFpmEPepz70Y/KwkdKyFIKQt1onRsPb7xQ0vb1n5sbn+Uq0iMyp/bA/MU4PoyP bOpQKHd07swbjPXOtiFoPc4jvUeKlTXyrIjnRWxzCr86j2qpPNG/+zuk2lXRyRamWmf7W1koTOoI zJBEk4ivLCFmysIuW4DmFtyxzsAfn8RhvxNC3AbzycEyNjuB84c1tAPWPqYbzOGsrcM+TwMCY3Oo ae9AxOtF3B+Ef0CfCuGQ1IW0ZKAv/OQnxeQ6Je8v//QfkEzE2T3okkzs84lHRvyxQurgvhgss9PJ vCCjYZSVsBGdhRjQtKIe+s53DF3YewV5UX1+K8wHO4tCBeRtZV4+hpablzBj3kDuVlZYmdZZJ2xa RvmZPU/jLw4eKn5RlcK0BwlS+NyujPRWQCuukcoH3RTsWjDIoxntHaUCaPUtqBQQ3O3teOOjETx7 shc93Q2GvYraxzZHNqVl6ZNzryNpA9xCqZBgiclInzIu9VMBg77jQjWNcmGknW8kIU1hGg1jkIdW ENyTbypOb9zedunt1xB1cP8/e+8BHdd5XQvvaRj03gtRSLAABHsXKVIkRYmULKpZliLJjlwSxylO ef97eSv5s1ZW3kuy8v68JE6cxHEvsmSqi1QhJfbeC0iCIArRex8MZjD1X/vM3MG9M3dQ2Cw72Wth ERxMuXPv/c53yj77wJ+XBM/8fLkfmTc6mdsGFAfucaN/DDHuYWR7Y1Fiy0fcknw4mlpgvtAIz+pI YYMRoyvi3DNkbT5xAolJE+uPZ52FD2WIB69rU/Ul2Kq7kKSEfMYM8ZrHVZsKixRrX3klZBS76m7i au9NOPMD771gKFlCUEnEqzC1wboNNYSU3FxJgs/EYE2ll8UddKZs++mAifYkawp8GWEkNur/eKbR C2k0wL26HBW1CTiMiWkfkyEuLVXTIxgNd1NBzBtsm9Ak8VUGSgm39JL8rNrdbTB80zsHouA5A5jj 4pAcF6fpc+X7shJVe7MzwsxxtHv458bduAwH++jUcHuRF9Y4WIJM3IzvD4pcTrStVNkzo3aVGcbd Ea04rJ6HGyxuFmxe5sIf/fhjDFM4UEIsT0Q4aHB7kZiQHPJUHDF+jNErMwdCNl92CuytHZqUBlVN WC0tiSmGZ2EhfF4f4p15onWlB4/Xg1tXJvKn1IBruXQBW9ZuwPxKbUHtZ++9HfqdYXH5yjVioAoW LQo9fvxajWZsGL3cvvp6GVjLKvPla2fgXhK8hh5vVClw871YNAwfSDGYHTZX7k7APAVPwtTPs81o lDrlXYyJkbpV5tZ+FHaZkd8bWTww+gywoh/jcbHwFmeIHpBe0vmXBwqrsUw+YZN+suswfCYrbuzb pwllxoI3tZI36Ki7gcxErQdrs4/BOTaGRibKwzcWvx/jthHE9ulQJTxeXLv1YWQF2u+HOXwUexBc 3AzxpjsIg5W72Tqju3gPnjteg5GiQCVXgc8f2d/JEE5NHqXX7LC4UbhIq9bnH6Dh0JG9meEi4SVh GwspHAqYx2HXB7//cHcXzL5EeG1OuNZoPTfLpWYYu4fhdPtRs3evvM7cMwDLiA2eygLt9wiCIp3z 2hJgyk6HZ1HAm4+53oG8xCy0wiWKE/K1SfgMNocPjA/iYLeqWdsIZDnN2IINU34/5uemIhO3XboU krRmwcddVaiZzxkTzD/SM+V4NiV/NvXWeRtRAt98zoYNwvC9Wz1T3OW5O06F3oZ6YAb0L4/ZhyFH PzLaU+ErmMjTeMqykeM0Y+WOJ6O+lkbZ2REoAY+MmO667A3zLXqd7pPBNTwMsxBhlcEBgccTsvJQ oRpjRZw7tBcjJdqTlVnTi689o+04+GDfGRgqlkmCOxz0zLhwKAkcDi5IpgfCyaFcZLX79+seP290 9r2Fj2WX17lcUr0KT3brLQ5W3iwJCdNrDzIZtX2UPj98pkiKi97kb2KmU7/d9jE8+9wLSEtPx97d 7yJ1xQrxOGmsuDG7rSa45+fBfKsX/oQgbcDrk/97S7LgXlIMw6kG6fHlmui4fh2XXa0wtQ/ATxE9 GiSevsyAsaqw58G8oiiwqbKp2A+UzZqHOGMMUj0eYeAzue3sHZVzXHP1NDqyIotO0b4/uWbkTlmo q2U2C3GVtAWqWKiH1CrgNcyZPz80PJfXyny1Dp5y/U2KpNoJ4igz/FFyF8bRcdmpoimK6kERWWOS kZNZpvtanrDJnsscxXTkbfqabkVNuuuBrnJNzhAe7BjUGCzCEzP5LkHynYK2y5dg6Y0u66L26Hxu T0T/lx4MTjO6D0y/vYmYX5U7rdFJdwu8GaN5S5OB11rvHDAkbUsYhzdLp93E6EPxypWax5jAlryX zne2TDJyXo07zdyNekeR+8EVxMbHw5Wk/Uxv9yCMS81iiJhro3HlgraUlCE1PR0bt27DmabGEFNe cmxpCSKr4l48C5YLzTA39MjYOtemBRNieSajtvBkMsIzOwdGhrb8Qk43VtenwlpUCCQDnozEQAKf PwYDepoakZc9kXtSU0Uu3jyJtmyX5p6Vf6OoZZKeQG4bGf+8fopjQV4fxQb5nXh9WDQRbqHDgQ3f +IZcN25evA8sQw54lTmiPp/IFvGc8e/cdEJJ97QzHaBMk8Hq1YwLD8AqB1F38GD0C60ydjwYajMp v/vHHGh3RFe4VIOCbjcnGWYwk77E28Ho2NDElHiPF6bOYcyZPcGKng5ezghMJJkqZI23e5DcGxma XL18GWMDcfD7Ajfl+EAk8fRuwqgaNDsZEllEsdl0PazbBTe2vjAdKSK8rWQqcPgpaQEkEIfLeE93 s3SpOh2mQv5gDLJsgeszmOCRCUp9yW48VboMjz/5jFS51HjvjV0Yu3YdZqMJ+YUFSE9JQ9fwSGjd 5BYUYrHLhdMXL6Jg6VLhu3kWTTCs6HWYuoZhiIvRDffCQcE7gpVOs9kIT2wMLGcaYLrVA2O/XTw1 X0Eahl2jyBftKX3kDMQg0WFE/LgJsVnZ4q9bHW7U36hBR1tkdVevkkxi7KqXXpIWJOYNWWFkno6e 2LWzx2Hv6kZZ5RJ5fO3DT6DrZi3qmmukxaq28wrsI/UwD3ajVPWe5u/8zUls2lSMJ//42ZklyacA DZb9SjUeeXh69IbdH3+A9LsUPuohbygWWUPaXJXBYYAhKMZn8hhg+Kge1sw4+EZ9yLRakbpyJpOo DZizNHI8Vji4sEy3mrFsReRza69UwzWQD5975h7LVEi0WmSD0eyR0yyZW2Y43Xk6oMesR/YVykGd tll2MjBUoHfCyjFDh/BzHQ4xCGGcIM+wDcZekzbH5vTJUBE1EhxGPLTksRC3kFwlKvH6LT6YOKSF XmDYPEEOaXj4ke1IVFe2w6ZfF5eWyTzJ44cPS7U2ZrQH44uLhG5gud4OX4J1xlPR/epJPwx542Ph Lg1QRSxnG9HS0Yj97cfxpznZyCyaGFVPpLrjkZhbDMTFwMdcUnAgBFr6MRJrRcysMMpqWHtPOCTP FvR2u281YNjiFel0Q1Iq4m7ewMJtjwqRODElVY6blU6l9OJvH5TzzHwrISY2Ozv+ttz6qdDWfW9I jKwYqm9GRTUx2gQSItMZh6b3td8xMhJmaMHmy8B7JmQcwbxHolEF/wsKmCS//M47of8rC5pl+hyd Hrp7gmmGwcyplIZVm3379yMruzzkAZPsOZKYh4Xp2vBzZLwLCWlpIU+C/5J4ynK/57p+/+Z0MToy IueKxtf51pvobhsA4izi7XOajbo3b6aQyTc5EwbT53DigKsadrjwrV1/gz/6wp9PELxJwUiOhy9/ YoZneKQz02hHaW5uOH4cfRWZITE+v8eL7rEBmPfvR+WjjwbOa5jTbTQYcPzn+zEwEJSXwT0CFzyF yva8/SZ2PPn0lMqJMwHLq5+0HcKYVeXyGwxY3puNoRQfXGn6Ln7YxqYLxYjRQzy4qwmJyRcQOw2V yrH+O5eZIc/HHN8FkOSnA48/GG5MsjaHnbFoaQ108nf3TIRXI4PD8Dc2aha2m55Fp/akOEdGcfmq VuOrq6cfNuu4vp4SpZk9HlSqlDmUG5TeDFUtw7XWma8kIfBuGswIEb0oUDY3NciLoiFTh5JU7SwN U0hgZUv3PXmOOieklKcCB6K6wugjBw8fFIIkj2/pM88KwZTUh1pfLxJbI1MlHir0TgPGQXuEsTP0 2cRYEZd8Lfiz1/8HNqQtwZPPfg0mSwwMo9FnAoSD/YgM43mtOSVaHhsclPXDNA9b5/ic65/sQ7vR Bn+BihdnNsG1shTOs136m47k3HywjYzj7OnAXNF7KhXJZFwnBbhcLlin8OA8MxgJlV+5EFtcHpzo PYubWROd5TccfehLcoeGQNwpBvq9ePvfzuP5F2ehaFaSrp0Yd3lwpbEXuYvurM+KHfQMH5LzRzG/ sgQxMZFGKycvD2eOH8OqB6LTRY4e2I+/+/CE/O7jtOMgzBz6kBhQdgw9Zh+GISz8dOQl47U27TZn au9DSeGcSSfuqLlGyu+kJnCRN58+LW1ammESbEVxOIRvwwowvWaGiaxSGVxeGcoZAaFQ2OQ7sMVF SbTbBwdRrGrqDX0O2dkqw8D8qp7RDe9rZH4tTkdcbjJwivOhT/Zqpv0YjSaMO8dhs41oQsK25mbU 3ryBdWNjyM3LQ1trq+YY+L1YYGJ/aFl5ZUR7lp+Tod9+WzaC4ZYWjA8MwGhwRIT4RpKaOwfhydOW r/15aUhsswamuPM6meJg94yJZn5sQiLizFYYzrfAnDxxTd1xJvg7hoCCsCnXY2MSnbGgwN5EetXk YtFTZN6KkjOs5A5YPWLZTS1GadD205NzeUQ9ZGBsCKd3vxUQ3LSPBQoHLi9iu0dRXlqFuYVuFJde w6kTnTB/8UsLYTa55GDVBEHGjeGVl2iz1tjrox6wqEZ6SipMQW7HZEhNSsaJH/9gyufxW5N4F5ec ggS7QTMfkLMV57bHw6VTfk313F7Iaxvx4BevtuHv/n4TFi/WsqYJh8ONxp7TmvHdU+HGtWokJCVi 4aIloRv5Z9/9DorLymC2xKCouAQ5efrhbVx8fNS/yd/j4uEuj9QkMvaMwDsrU+OdkQ3NSSjTQWpu gQwy0ANpCJNVUmno1BVVgpIsjSdOBPrnTCapCCmtNrMT8zk9QnZokpBDqFgkhFAu1Ox586ac/ceC kZopTYOVNY1xdbez3VnjYrFslTbUZF7K7dHxhHjbLlqEztgYNDYEqB9lDzwgAyTUOvesXw/MXwAA IABJREFUcnKxR7zcYBCjcOZnP8PLX3oFcZWLZBIRj7u5sR6xsbHIyS+EkQoUfj9+cPBdqOs3vmVl 2DKyDO+NBCSQt+atw6adL4T+ztaoukOHUL7hIc25a3Kelk1GhnEEMdrdLdeBU3kI5vQoEa3uIWbX S1/jOXiLM6WAkF0zKN9hqL8XrmXFwjXrDZJeTZ2BcWL+ZAusHXa5b3h/8N6zJu6Fef3XJg70boJu 4HB1NXY+83mYg1OkJ0PXWB/2FEdWjcIR4zZCcaAy4y2Y1W1FS05gp6Bn9fCCKmxdGyltc+pkFy6+ f/52vgpGRlyovtKra7BmDL8fcxdUIK+gEFcvX4IjWFXavH2HGKoThw/hXoA7WWApTlgs/zQ2EkFw IEA0CEv7zBn5nd39mhmWOiFY4GED5m2ZXGE2Go+PoVLdmZOwBD25waE+XD9+JPR3E8ebJyZKmKiQ E5UeQ5IaFTY9Q8Go3ynIuqch9Qe9LorrSZsNJxbHxYlnQcPBzdpgMOoOm01ISED1xQsYVKUMjAaj 8K54rhRNKCam2X6mjOJSzp264Xu0ry9U/KDRXv/ABtiotZU/IeY32Ncrm1qmamLPw6VL8M61Y3Ax cW80SI9hQfFcPNEKVCSUYOn2J0IzDhXwO/K7hRAbK8a+99w5pLu9SAsed4LJDLViFT3M8GphR3MD fPTygsn7ZY/tFOfo7HtvoTveGuhl9NP76pO2IjfzZ+wgSbaGlD14PWNSzfdGcZRufeOhw3jxhRcR rxoweTfgUpHZWFIu6rHKbEBOX6Zo3qjXjYL8yBsnJXlm5fJw7P+0GS+9rK1CORwujDlmXj0zWyxS GeLPfYOezdHjmfn8MAdHjyswcUT7JM4MF3FJUGNKGfKpvhf4c1dhMKAjywCvsi4KiqBudEk/2IR1 r3xZ96XDNTdg6umV31tbA4qxTqdTIozwvFx4ZwXDS4vDgSJrLPrrG8QIDQ4OoHz+gqhpRZPJjMrF SzQRSH9fbwT7n4uSecBzP/+5eJr8O88rBexIBfB7PMhPSkGyNZCPmrPxIVn04QoWeigrL0fMR+/D FGtFYkM/RmMNcDxQjtzZ2bAfrZUNgD19U2m+87gqFlZhzYaNocfaW1vQU38z9H8aGHXTNCWP2/vb 4S8OMBAmKM2QoTc9Pif8MEkLE6lErjXBSMXrk2ZyJcpjuGmzDd6bHJa95oYMfJyJseKuM1OQidyV 7kLuQAyGE7zY4SrDl5+LzO94vT5ULcrE17+xGG+/WYeenpmPUL9RM4D/+M5lvPhSBZzOcfQP2tHR a4LdPo6Rkc/+SPbJJuKEtyRtNhchTeUttCa0wTvNogkbVpVFxLwGOTiUAvqsYO2DG1G1VOu1vfPJ x8hWKZEKefXixYje1Rt79+KZx3ciJehdKBi1jWD/Rx/qfh6VQedVVCJNVVljwv2GXb9nctkXviDz C+c8+KAw0GkAGK14G2/hwYc2w6wydG3NTXBOg2tGzy8lNgHPP/QsMr+QjR9/7zuodXlkAOr45gpc 7LiKzKY6LNk0IaDHMD58jqLVYMCqnU9juuBxM5flT4kXr45KGApohE1ewNw2CE92Mkydg5KAJ0wd g8gbj0W8JS1kRKmJ9dznnr17BosH5+nrk3/XVC3RXKDpICc+A8uaA26sxWfU9vcFRyZTUbPB3ykt AyTdUvqFcjGF7iTsMBVi545ViAkjw4lSpdGInJwEfOk3F+KRR0vx6s+u45N9jXCMeeFyTT9j8cPv X0VzaxfWbJgPg9mCBQsrxSh3d3ej59JljkcOPJFic+lpcFosMMfHi+jcTCeW3A8wJGTiU61fRG2j 1IwU5GROtEnYHXbsP7ofvkuBZH44TP2jssi5wNSKloqHcLuUGceYHfve+FHkHzw++OdGjqS7bUxz s4x2p7CoxCrh3t3vye9z5i9AQVERxux2jI6OSIim4OAn+9AzPASb0yFMcO+oPRC+xcYiriBfBA+V HFUoTDMY4DCZNcaKGA/qn08HTMtkZmfjUvVF1JbFaiayj6fGYuRIHZrikiVEpczzykVLsHylliv4 9muvorO9TQy04gh0dbRh+HoNjN2BwHBkaAiX3z4lflRcvBWepGEYshOReLQepuIcmP0GXNi1S6gR OfPmYYU/H1c+2QvnvBz5nvG1PUgd9qFswyoJLdnC5R4dxZaHtkhEctcMlrOhAdsffjSkwDlT8CI9 /ezvav6vV/Vpq74ilSWv04nuxgYcT2jA5vS5+MqzgXHjPIlMNkaj5eTmJuDLX61E7/BNGC1pOLhn ZgKF/f0jmLtwEbJUMxx3Pve8GFPlmJV/B/r60N3VieN79qBgxYrPhIyMBlazqFSqDZbe7Z+YkAh3 fmpU8mLsmcZA0jwsd8HFxCohRerCwRBnKlCtwLUyMmwWradpsvRvB8xX6Q07jfp8v18m2Wx7/An5 veFmLT79cA9u1tRgVkmpVG4TFRmV/l4UBUfEM4HddfgInnzyaQkZf/Sdf4M71jqpCOOozYahgX5k qHJUM0F2WiZMlwfhmTtxLZk3qnr8c0jNy5MBGmyh+f3/9j8iXpuUnIKa/l7EeQNpEPEAk5NkQMaS FQHO2vXqK7h4+BL8foOE6aWL/XBmJ8J/qx9L1zwk5/b8rl2iD6+ox85bsw7mhHhcvXEByeZ4LH1m O07/9KdY+Nhj0i+ZNjQSUoi4KwaLpc2MhMTbMlRqTNXhTf3t4mUTgmdFS5Yi9cP38eLja0NGgsYq PLkcjoEBG8ofegjdtQ2YPV+HP+UHSmdn63LHxscHNMaK4GfrfXfeVHU3arB62QqM2eyo3fMBfDEx KJmiujUZ7JO0LykHz96zCLg8EY8bmZtye0Pd+vJdhuzoM/chN3PiO1ICebK0uyfBKsMMwj0pjuUi v4kSxuE499pruqPqJ76GH6Mjg0DO3R0HXl97I1ToUNDX3oZxlSYWc2634xUqulfMafHnn/7h/0P2 gxskrBsK5vHGWgN9dcrzBwcGAq8zmfD8l14ResS+D/fovHngn4tnTyM+IRHdKqN2+tgR9Pf1icFs bWmW3FpTYwNiVL2UpMwQ+YVF+PrGp/Hqxf0YzA14fjn+hFBVj1SEZZ//PK5cPI8HNkYOQWb7nlIo IKRiGDRg4TCZ/Ri3u7AosRSZr2ySqTscKbjxdyccExYyhjo7UfHII1genyDFDJ6L8o0bQ03SCarN 464YrM6rV7Fyjn7Je7pQPFvhsehQJPRaQ26dPImFs/PgcLrkR97HB2RlTZ4783i80s9UtfMxVEWu JdGy3r58FaxhzbP08PZ//CE8Ho+4vknJybCohOPCUXv9miyONRsCORz+29fTjbMnT4Tc6nCwFG4b GYma/xsbs2NwoB+WKJrofD3lUgh/ysR7GMfGA4MB1JaH/Z4sIadN3BAGHfXJqcAFJxWvsDSAa3RU tyyvILJ3daKEfuXkYYxU3IWqbBhYUQsvdtT192mOhRW4rqtX0a26/syhkCA5NDgg11+NcAOoIDsn V2ga6o2489o1zXNsIxPFIF5z/syvqERjbS1Sy8qkYsjPzQuO9YqJiYkY+UWcPHIIP/3ud5CaloZn fuMlDA8OyvAKOfYRG3Lz8mWQBTf05JQUbC9ajHcvHgZGnZi7WTuOj/y5Ibcbr/74h3jh5S/dNum7 YK4Ty19+RjhzBL2l+iNHhAbBdc5kP1UeFNKxWtWD1Vw+j4ofcekZWLhk6d0xWJSWqMgvwOzyOzNY BMMKxqx6AwposNQaSWRK1w3U4eKwET+rOx16PN5pxO9uexhLFiuNsDrKlTMVMFKOweuVi/7ph7ux at0GHDnwKbY8Gn32YndnBzZs1pbu09IzkJ2bhwtnTkf5DA/aW1rQ1RFgTldfuoCqJRNJ4py8Alw8 eyYin6FO8npXR+Z3DAOj8LElQhUrUwGAiVBf2kSOxehyi375TJGYnR3RHD0+xZi3pChhDW9mVsDC hetm4vGrdb8UsBhQuHhJBI+NVS31sSiEVnUIz9/HDh2SAabhBqqxrk5aSMJBNYZwqENNenF6qY+l K1eh3GbDm7tehzfWKgvbnZklFceOtjbd77xy3QMoLpuNc6dOys+404GB/j4YDSY89vQzcizv7Xod Zap1ujy9GLec7UL3CMhKT4DqCGlzy3Hu1IlQQWxkeBij1dUaD4vnlF4WeWBEZ0c7CmczCjAgIcWt MdYBCZteeOvqkJyciitHDqFi+3Yx4rxmlD5nSM02LxY8lGb2/mPHcf70ScyeOw9mTTl3GmDbhboL flZGJhZt3nrHrTfOcSdaDh+WuHU6I8dI9b+aMKqhORDZgxahG2ihDRHj4qyw1XROS65Gjfa2VnGp Fy9fIW5qSmoqerq6kB02FYa4WXNdjFM4B40LUW+HjIbujnasXLtuyk4BBbbhETToiMzpglObacg+ U+KDd47EhAQ889jnIh5vb2mGb5oN3yzhh1N++Njc+RURVcKU1DQc3PsxDnysrRR2dndhrlHbAaFW 0tRrEwp9h6QkZKSkYN3GTcKYp1dNcNG+/qPv4/nf/ArUeOOnPxbvsai4GGnpmeKp0Zs6uG8vWppu oXBWsRBK1z+0OfSaIYajRw5jQVk5PB43jp08jrR586QBm7kshmvjy5fDEtw4rPPK4RsakseVRnMx dCkp6ArmQYdtNjz7yjZJInR2dqDr1i3EZ9HYmhDX24c//NM/C31+jNmEj994Ayu/+EXZpBpPnpTK MsNDNZero7MTS1esQgPTDuEi+NMFrWXd/v3YsvXuNAfzJOmJwEX77NaaargWRekZpOZOUBJYxkP4 /XLCAvmtwI0SjZkfDcwLXDl/Dk98/guhx2iQWFoON1jMM4zaRiO8q18VNLU3Y2jMpsl/mLqHA/ku lQH2psVR3FQGZUY7n0Nt7Wg+FelNqqf96oWE/LHenGBUa1/sCcwP7NF/D3oEqWmR3o3dZsPAXej5 DMeYfQzzF1ZFMN1f3/V6QB9OvZn7fMLup2ST6HgZjXjtJz+C1+2CNcYqeunJqamS+2SHSFpGpjgD StXdPmrD1UsXAk6DytZRpubimdP40m9/Q5OQL5k9J6Q1Fxcf6fEmp6agZPZsMVjnLl7QdGwwemK1 Um086AHl0fsKbvZsp2JHASuLhKe1DYVFsyRsJker68J55JWUwO9yYevzL4bSFpfPn0Nvdyc2P7oD 3YODkutkVwOH7oYTT0vnzpUuEOkEud2LxNzEmjvsn1MjfjrKkEGwUnh2bnTt74Mnr+FEbZP8zmua arDAJF6WD/GJ8RISdtS0SEVRD6K3vXyiU5+udUPtDY2xIpgLYJ6KqKkOkAybm25JvuCBTZEJy/sD P0ytkbIqxmEHwMfVIeHwmFTbqFQ58ZgDrVY3bhWqPWYjDDmFiD/RgNUvvRx6VAT4SOK0X5WcQ3h4 wxA/IzkNpYj0QAeMN6VpmT8R38DrRUpMIpat1JfjJRuciz1aa07t7sDodj3caqiHkXk7Jk39kM2G 76fk2lgo0Jt8fDtgmFN3+LD2sdFRoXqw5YQUBiV5e/O99/DMCy+J4SBPa0FVFY4d2B8hKZKQmIRZ pbPxxk9/GuGdpWdmoa2lOaKCyJwoMTgws4o4z++ld96RJPx0QM+rpe6mCB6Q67ZgYRWWrlwplc09 b70pVXO2pTG1Mq9iIVasWYumhgZcPXVc7hUm2dkAHg6b3S6538zsnNszWLb2dgy0t2Px0hW4n+BN VnvmOE7UH8ZYQXTCXEdRCrwF+vIYbKrlrLa52TnY/oA+oZFlY7r4ocnGjjE8/cJLEc9LSUvH2Ogo jh86KAl6uuFVS5aioGhmoeZkMEzRFhMO9iauiI+Umr3adgzOYL9W6L05ZIMhknpNcIFwQSdqCw5+ WOGFXxpyrcEkqiJbywU+VnsT1rANwOT2iBFLio+8FhVzlqH5kyNIWFAW0RYiE6x9Pk2uRHvgBjGW 0Yb1ckHwBlfAahlDc/Kixp1ODPUPiBfDgknt9esw9PUjPqhjz2toTc/E2bY2Gc8eOiaPB32Njfho 70faRmVeH5cbZTpdCyaLGWWbNkUMVKCyAd9D3fpiMpo0fC05bp0GeGLdgxvx/W9/H3/719o8HT2x f/0P7b0XFxcnuSeC371FJZo4MjwU9TMIyuZQhYRtV3wfl8stBYD4jHS5BtzYGcIxdOba7Lx8GX/w //ypbOKMaNKDnDy2LZFt/9PvfQfPvviyZn3k5ucjKzYO83LzkbF0GRr37kX+2rXC06KarLuvH5Xl c3H9yhU5P7dlsAwOB559+NFJK2T3Am6nA8e7TqOhYHoqpnqQRK6Ei+NCpNMDiXxlc+cFPtPlwo++ 86+6z6Ox4uKqXLxYNwS5G/DPYC6dUhHKWqQdvEDE1FXDHq5xJN38Q/AWThy70WKSBtWZYsnKlagM 87glgRpFkz47tQgetweerKwIfprQAKIkl6cDXjMaIrWHzGvFgkbV0uUapjv5PWeOH8WqBya8ufFx J260tSBHpTChNPlnLF0SoRPP5t5PPtyDT8NyWGxq1krjzQwJSUnw+nxT0n0U8F5sawm0HSlIz8iQ /lR6Xgz9lJFmDI0vnT+Ll7/624iG7vMX8Dvf/GPJfd2qr8MffuNfYBtxYuvWMhQtnIXyhwMpj9Zz 5ySELwr2NJLZz5BPwcF9H2Hj1kfkmoRv5gf2fijRSHpGplBBWNQ4cO5MgCplH8OS9RukoZ8h5rGD +2dusOi6xbs9Go7H/cKZ995ES+ad9QQS1AdqMATc0/mVVfrJ6KC7zUWXlR19gsvIyPA9M1b3GkIY DTeIVsudi5wHIbnCuzwVWilcsOk3fLiFAkuMFavXr48oeDDprpfDCg9lmeT2uz0RxR/mm5QfNVIK ChCXkYHlX9CmDNh+ogcOXeDodzXGXeMSCpK2MHFcui8HPz8tPXLSE3H0cC2een4gVKHML5olzfYs 9MQnTnAlk1JTceP6VV2ng54lw9bY1BTUXKvG6nXrcfXyVXR12mCJMSFrdh4Gu7pkQApz4IXLlknf JUU1uzs7RQaJnurxwwfhsI9hw0NbpUhVsWgRGutuaiqVBUXFkk55YNNmuQ45uXlYPrscnV2dWPtQ wCCyMs/qN9972gaLSVIeUPvJU3jh5S/ifoNJw8GBbvjuBjXHZIR7YSGO37ikb7BU4O6mJq7peUA0 avdz8MNdgyJ9G8Yuvx2LFc5NuiOwY2GK95vsCFkk8Hq801IJIWKs2gosNytlNsF0oJ6GrDkOn088 BbWBY3hI71FY4i5XaABsYkZGBDWCOZ+Z3lYnTtzCd/7xH/Hbf/iHYrSYvGdVMynMKyQthhVTxUh2 trULFeLWsWNwjY9j/sOBvsLTv/gFli5fKW1S8fEWfOGra7DkqcdwZfdukXxpPH5cvj+VV4cOHcLZ k8fx+NPPird38+ZNeKwxmNXRLp+/YfNWnDp2RGgXD2zcJNeQ35HcNjXIJVNoEsTRUyfgsJgx5HZN bbAoyHV1zx4srKjEqqpFSPrKQnHR7jeYP7hZ4ID3LonzEbeMdtRcvYIFCycGPobD7XZhTjA81AOT pHzOZLmAXxeoBQHDQaLi3YTeZOSZGE8uxOlSQWYCzkEMz51Fk6mxj43ixIl9GlfJxHTEqFMqhxTY y0zJFIM23NYmvYhqUOiPfD16fOFw6EwcqqzMw+o1WVi0bAneeu1nWL56rdBr9ApApGKkp6fjAybI lyzDvg/exwuvfAVHjx9Dhmqe6KInnsDh/Z8gJsaMx58oRfnGNfJ98isrYevsRPmmTWKU2y9dEmWG uKJZuHTurIR2pY9skzxd/YWL4uURaWkZWFBZJUaKeURyzsiqv3LhPCyWGHmc7T0sHNBTy8jKxtCY HaXr1wuVwnzj5LGoF8c1ZpfSZl5uHsbhwbnqiUmwJqdHqmRR4YcoLZINPh10UvhrZBgJCfreTGdb I0oNmSidooCT6DLB0D4I08BoRB8UPaERb2AUOkMVKlt+svcj2KiPFFaNoefEhCp3G/JY+vsjGdts o3CMOUQF9HZC5Km8CGLc5RIlS5Z7FcRN8lm8UWw6LS/ewRGY6wOqj4SVldMxNwwGC8avdYQS39TN MnhM8DVGGgyTxSrqodawa8obddxswcfvvxuxeI3WGNzouqI7Cs7hcsBT0yfJVT5GjW8eIL1p/7gb dZ8eUCXkfaGNUhQMRobRpVKpZfcCiwI0BCarFadOnRAZH825aW2VDoe+gX6YDQbxMugZMxHd290V 8qTpHTAkokyy+h53cDJPcXHE+DAuWL0mZPKTx02+QOhtNcObnaw1Xp1D+M1V22AN8/AUUFmW9BjS GBaqyMN+vw9OHVmj8vIY/Nn//osQ/YHkY4aCp44eEfZ7OEjFuFVfj3GXEy9+5WtixBbMnYfW0dEQ wZXnv2NwAEnxccjIywgVCkh/uP7xx8ieP1/Y/MWrV4t431hmBsZ8HvR0dmD+ykBRzjpnNt7d9boU C7o62yTRTpKrAq4dt2tcCldnLpzD8uefl0LOARqxsTHEB5P3jHbM9XmT8ZHigNmzwazRDWgNQOL1 RvzRV/8gagsJL/qun/xI+pumuyvSZbwbYHJufTD+vV38w1//Febt2IGUObNRXFkBvQDBduEi/vjP AzfITMAdaF4lPdWpJ76Swfzmm7tQtHqic36yYMV3q1E4MWrVBEItZKd5PvXLDxzA/M0T0iKToeHY MRSv0K8OH//ud7HuK1/RhECrKiMn4/TcvCmyI/mqKmDbxUv4q2/+GA6H2ohPbJD/+28fx84nnora r3r+7BnYsjNlgUU7vtYzp7H2lVfgttsxNzZBdnCC+k4sxW/a9kgojCT/icaMpXkFe+xjiM3NjUi6 0xv0nj6N1rAhryaXF9u2PS1532uf7EV3YqxG5scQrDQzqR0NWTlAV3srSudMTICmcUxNP4OYMD0z dUWZ9AeSTInTx49JA7aa3M1Kak9Xp1Tt1EhJScGpE8dQtn69KK9Uv/MOvvxbXxdjxsrrnvfegTU3 V8JaUllOffd7SMkPnEc+X9HGp/lm4zvpG6wskk6SHHQaLl84hwe3PKy5B5evD1TsL9VcF6NOLzZu aaCIQ2oIewrvuab7/QbjXlZrKqqih3jTBasZU4kb0oP8rGEmKgMh3KX8G/k67CulxO79RldPN5Ly pyc5Y6MUSnFphKYVW18UZGVni2eiNliTYe6ccqxZpe1gOHkqIEFMA5eckYnusCbheK/xtjpE/JIz 9eGv/+5ZjQG61aA/uYdhFzsmFqiqo3U1NajS2cTYNtZy4QLsQ0Ngdu3rv/fNEN2CBNn8vALhT9Eb ZX5MyJxmixzTW6+9Gnqf1IICtJw6hUSPF1UVlXjsf/65PM7k+bUr2mEek+V/6bUxHcRm6Hs7NSeo P34/se+D3TJJd7Ik+d1E/H2mdUwHen2YU+FulQu4K/Y3NUlTOqVD2FB8O8czU9DYDAwMIHmai19R LlDAxC/L6uqFQ0UOdkxoXhfUiVdCWibQmTyXycUWCzKztDQZAzXdx8YkTLampiK3sQGaPdBtlL5U Gsq4+MhIJSkYXhtVhpSgcWA/ZHhEQhHBf//H/4vLF1vEm8kNDp8Ys48iPSMRD27dFjKQPFbmzMrK 52ka6RlKlpSW4sUvfw01V6vR29MtEjn0gupra8QrJZ+NPxQAgGqd0/tVpnkzbM+dMwebN22e0g6Q +a4HkoPrjx3Dgm3bJI/OidK/Vh4WdYg4UuxuYKrWHSpSxkRhyv+nhsEgYQGJfww1FzwyvUG6t4vm W43Yvft95FYFhhXcS9CcJY/aYRxzhpQzevv6xIBk6AhWUhCgJ7ipZZWUoio3H5VVkdPEGa6xZzAc Pl/AMF4M6uVPhS3bd0je7v/8LYUW22Tys4Kvf32tGCPmchVQAYKcNbXBCszkNIY4aqz60cjl5ReI +oNr3ClFJqZ8RkfDuk1IHj10eGLyu9+HsyeOiaFUwHNWGNbDG22t0fgxlUFvjT+c8P1rZbCmKb44 LchOFOUNObpo1Zy5Ejb8F3TOndkspW4OLaBLP50m8xidPrep8OqrP4U5KxOLnn1GM/HpbqG7owOH 9u0N/Z9KCc89tCVChYF9pizXhyOcs8V7Si8E5GP66hv638nv909LflzppyUOHmzAC18e1RgscqBO HT2M4tmzhWnPZn620YSOn5LI69bjg3feEoM1MjSMFWvWSdioFJ3Cv+8LX3ol9H9Wan/+g+9ixO2G xWBAcdEsCQnZ00jnYiDY0N3W2oKzpwJqtp3U2Q9q6XMICCc+MzdmjrWi60bNr4/BGh4alE71u4Wi 0jIMslqiU7Km5c+bX4nYaSTNfxUw2t8vLv90PBRWb26pCZEc2MDJJkFPgjeZ0ghLsTaGh6wiJejM DVSDlb3f+OKSqPm0vt5eHDrwaajEP9DXi8GhQSRazKI/7jOZAhWsaeTjXE4n3n73jRDtgZpgrBKS Vb79iSdDz8vJz5dEvIJoGmb3EvRm9K5LX4+OSOMkaGsbkNYcNaQDwG5H3fUaXK++LFVDomLRYimC MVRmczTPzZH9nwrhk7kvGhv2LdI7m8xJIL+LXQWdJiMSCgtRU18Pr9+Luo8/gn1+NvyKSkihGddH amG+1gZPZSF6/UGpm0TAlxcLY0cH6tuvoivX/etjsO42cnJz0dMX/aa4eukiVqxdd9+ORz0LLhq4 I1IJgGJz4W52NO1vkQNOSBDRwqi9e2F5hYKqKq1s9eXLmscUwTYF1DsqWBLZ0hKOFc8/rh0tpYI0 EZeVhpQP0stKYKRaZXu7TFSJHXPAWJA/LW9udHAAbbPiZYQ74TcbYTYl4dKViyK6F4LOOetob43Q wxrs75OBqdQ7p6yKwu7n47Zxh/RfsueuxzGOzAyt4WaejIaQryXCyaMcsur3eSVprk6wUxpGeU04 H66qKrIzIy7OhLobNzT0m+tXLuHRJ54Sw91YX6dJp9AosX+vo60Vs+fORVZOtgwawzY3AAAgAElE QVRfiUtIEDrOzevX0VBXK2EhFVDzCwuFmsA+wtQgT83F0WWtbTCUzBLvS5lryR7FG0n20Mh6NWnZ lxqZ7xrp6UBXRlCWGfcK5Lnch4TrvYIkXbu1omYKyOUpyr0/+uw+rw+ucdekOt8EvRwajlnLlslA CPLnFIPUfP48bHMi24cojTwnb454RPQah1UJ0/5bt3QHp/J5aoPEpmBe53AjpW5bYQNtf2OjVDDT S0rEyLH9Q930TGrAnI0bRSJXD/TgwtU7h5qapEqVGhePshWz8f7eD0WaZLJKKYUfXaN2IMEIf2zg /mQz/KrYfFR+QSvGyP47NfIKC/FPH39PBp/oYde7R7DAm4Mdq7aFWoRyKYXj8sA+7kZ9fR0SkxI1 oSTDQd5rHa2t8tiNa1cxN6g1RZw9cVz011qaA+ojCubMmy+voUhkV2en5KNobDn84v/9XxOcq7qg LlsmxS/9CH0Owc89efQwNj38SKhQxQS4c2xMKBHvv/ELzCotE0+LMjWxKsI45W5irDFC7IyNjRM+ FwsXbKjmj5xXGHCroQ7zFmiJ19wYDY5hbbcCK59Ot0x99mUkTvS6jjgw4A28H3FPPaxoMr6/CuCQ U2uyPoOZC41sXPY93WtwMkpKWSky50Vn2yvkRVboCsNK1Wz/aLtyBd4ynXxbzAAyS0sjmo/JGxJ1 ziWR8kG305RMNVImTWkszr/+utywHEJAA6SAxz5TkCu1cc0DIW7Wtg0bcfzEcXhTU1CgGtul9kCZ f3TRQzJqDSwXHRUF1KDaqxoMR3vS3BhIjk74XeFNw/I1ayMep3HyeD1YufaB0GOtTU3SKVE6J/C5 DMMo1Kd+TlNDPRYtW67JPSlg4psGjWEXDQ/78cLJ3Gy/4TBXhnl6IP+MLPOu9ja89qPvS4jICiN7 ZCkISMJp9YXzYiDV2PXTH2NocFCq8kyNkAzKKuKiZRMcuEDi3Y8uin7SSBmNGKdihs0GA5uwAxl+ +TfmRB08C4tg7BiEuaZDJpJTXLLT1oq2ooAELn3P/woJddDX24PG5iYUPRRZubnfoPtvuoNcGW8S Y9joszvB7Y7sIkh1WPXyyxJWRuu/mwmMqSl47ec/wxNP7JTZexSxW7FiJfYEVRPCjRYXT9Hy5Rh3 j6PDEl1AMBrIyUo9FTOpwWqydeDk4UOYM3++ZlgJiwJMbE8GGp/CGeRhd7+5S5qXq5YtkzactpYm VOhUIcNpHGqwp4+9fZQlevK55+UxUiwOUkbHbJahHbE6tISCwkI89/KXJj0+Gl+q9MpY+s4uGCxm JFpjsb5qMcznT+H6qXr4TSYYxlyAxSiiBJ6KAhGL5GQkb1EG0m45kW7rQMqoCSaf4dfLYDGeVtx4 aeMwaCsZPHF0m6eSxeFutriqCrWXLiOjamHE4uqvr0eSy42P3n1b8zh7ozjuKQKSl5jITYzOQCCO N9t0JKOjghNZplgoM8EdHUsQd2qsmJ/rbWiQZPvQyDCuXL6ExUuWSRsYB0y88Nzz0m7TVF0Na1ZW aJzUTMCWrPAhJPQkOFdPQfx4mL4YDJhlzJDw6drlS3A6nHjkiZ1y3zH0m0rbjF7K+dOnUFLG8Csu 5IVRyI9SMwromNAz4/1GD4eb2qXz5yTULp+3IHR/Ox0OnDt5XO75kA5WcLLP3AWVyMljSHgElYsW S35L4YJxMjW/f0p8vAxMWb/pIXlMWoj8gYZpiulNBRK5Fy9bLmuw6VYjysvmwDk+LuonhVl5uJIy HupPNVDNtmsI3oJ0mG71wr2iVFqaTBnzULHPjptZI+hP9vx6Gax6ex/qqj+V381DzMf44VEl8XhS vli5acqBGbxRqe3Ehs233n4T+evXawiQpqEhbKfca9j9R32n8LwHdagP77sOl0tNSvRJwpQ7GF1t uvz3CtJ/FRxvfq9A1dCWYFsKyZQ8V6wKUuGDREuG0DQu/F0XBoMogYx0dEQlmjJpPdjaKn/nezHU zZ43T356GhslV8OqHgd48Lxy8aekpuDYoYMYr6iQ85CtCvkMI04YnB740iNzbzQALKrQyLQGc0ed wVA41h0w/glOEzb3z0ZWWUC4z+N2ISk7B6WWWMl18eedX7wmOSG1ZMxkYGhIegOHjHBCNT0UeoU0 emp1XI/bjXMnT2Ct6L0bJWdkMhqwcs166fRQJ8/ZRPzUC78R0SdLqsInH7Tjpa9+Tdp41KB0T13t DQkPiZNHjCiYVSxpkOTkJJGs4edOnqSAGN8t2x+Te721vw/xcVZ4TQbUHD6AruYG+JZpCxx+ixkG TndKi9fMysTSObA0XRThg18rg8XytDsrmDwM/qsGG3tnouXO7vHPPf4EPj18CPGzyyT3QvIa9YH0 Ss0xVpNG64fgLvj9b5+FTSXjZbEYcPl8M9LSzVIhYjijBoUFlcGbdwP3UvqGBqp41SrJeXEggXCE 0tIkT0EoygY8BjLfB2tuYOMD67WL57230TKXuRet1pmxd0R67/zxVqAsAb2H9mLh8nViAGl8FCoF E/nNLS1obr4lFcnilSvR0nxLmrJ7h4Zkg2GeSxk9n1c+Dx0HPoI9LxGWW73wFqbB4/OEZE5Y6aI8 TVFxiXjD7P1UBoUuSC6Gs6MRC1PnoWLHJk1llb1zWQUTId3WR3fIYIqujl54PH44xxwYHZkIRcfG bOJ9kFOlTPLJyS/A3t3vS6KdTHJynmwjNuFIacaqJSaEuFvMJdGgMEHOe7b64gXYFc18SbS3aUNN g1+eT7JquLEi6CHyhzIxatBj43Hx/mSV8vihA5L7c7ldGHc4YDJbcOrYUXlua9MtabymsSb9gVOe ed34w6HC3bZ+XQoKE+8MBdXwJ8WhbDgVPWm9nx2DxV3Nbp9qSGh08GQavF4xSgrU47hDz3M6o34O JWJYKGAyU2a6MScIA7ZvfRiHDuxHH/WJBgYx68Hp67VTfWLztny898aEYJvb7cfgABOslBAeRH3N m6G/xcb5sHbjEjz0yPbQY01HT8ISpaM/9F39flEYuPahVvWSGO3tQ8pFnfaHvhHcuPYxTMYYmGNj EJMU8DY4EMHhcaC3RysyR7j6B1H+4IOSh+LNx8XDRmaGI+MMv32+qPMGCVYH1aqTPG5WqPQ8HYy7 ReVA+RsNV3JeLhIztaJopEIoFc3BtrbQ5/O4WIxQ2mnIwA9VEdOSxFDB44WpYwin/UM4/YubsIw4 saZqhbDGFXAo6YJgf2pHdxcWL3pO97t1VFejZNvEdaMG1KNPPImXn/4mTpxQaAmBBU38zd/tFFG7 MyeOobN94lxTe4oJ/+tXLmPr9sdQe61ao4hKRBttq3h3BL1N0iTUxkp0qq5fk0Q8KQrKWmDqQfGo 3v3Fa3jyCy9o3lcS6D5fyEiSPMskPzla77+xC1/5vT/QPJ/kDqXy2NjSjKzF2v5SC4wAvUbSVDg8 iNXBa02wJCbCnp8AXB+CpSAbxoxkGThiMsdgyWD+Z8dg0SWcbgtCNKwqqYBvNOD5dLW3o6nAOlEi DfJtdt84BXONdooLE3wsp6YmJePL3/h9XD5/FgfqLsIf3AHi+uzISc9C+8WLePGrX5vRMTEXsWhF BY4e6MFAf2SytqFOS+bLzY/B2o2ao0O+tQKJcZMrF7q9dnjy3Ji/NVLxgmJrVTpjr8hfimsGkmML 5Ib1+QPH5/WN42zfIQxVRrabWK85JX/Ude2aeCzJQcUDLlZWF6mmORPQ4HGXng58Rem49PGHyCuZ HTBQYTs06ROK3jxB70cRoiPhld4xvUE1vCVZ8JZM/H9hi09jrMJhnaYooBqLl81RGSwtlq5cLQlz NX7ynX9D7bVreOypZ2VIhpqKoDDwrdMoxLhc46LIsPf9gM4WJZJIHrXmZMM3MiJkXAWkMXAGIRuc 8woKI5j09ARra66hvKJCw/RnYYEFhskw7HQifDvy9A8jy2bA6MgQPIlWePsG8c7gcRSNZKC+rRtu vwdxzTGYH1eEpYnz4Nq0ABav77NjsJh3UM9Mu1O03GrEd4L5rIkPMWKkNJIcabnQjH39R7BtaCH+ 8nt/D1+sGa7ynNCCSGjtxkNVW7B+02Z4XG4xhglJibqlZr0F2dXRLl7V9BEm2UvtKsPkeRCfMeBB KWFS+DGwSTccgbA22MhrMKo+I1huDhtaIX8xGmThz96wQXJK1MZifomJdA665VSYyXAnzdDevFQM ZyTKUAXn5YtIzgxrNhbd/0i9f3qDNKb0EFhWt/f1weVxSU4zoLA6gbzMSIOrlrSJjbXCNjamoWRM BuY0jx6qnsG3BCzWGKnYhRqijUa884ufS0KdIHGV8yc5Yo6ywVToZArhPNUhDAYkJycLIbWuoR6W +fNChZJsw9xQmN5x/ITueuvv7cF3//mfJDxmnoobLsPRkeERyUeRUBo+OVuPlNzf14fVQcmYnPh4 dNfWSljIVi2SfUtWrQqRfMnBO/P2LtjgxAXvBL3FATdOOG4gMzEzMHfJZPzsGKxfJnxGakx50Znh R1ZpZogBrcDj88rupBbx62htQXFJmbDdufCVPFH4xWM1p7fLjtFRtr4ojwa4JzMcjfjZgB+oeiLg rTFvdWPvXgmx5m/bJjkshhx8PBy8SRHFoMzo45mMTbQiOT4HRTry1k2nI2cgth05IhOtTUYjug8d lmuU0m1DHKxoktyZX4yXadiJhs4hrH5gg2ygyjVVGyzmlBpqayL4bqHjC15/5bUnDh1Eb2+UUdph UR3PnR67fnUw53fp/Fk03ryJp194UbeF58f//m8y54+bda/JIFpubEKfCQYHBvDil7+KopLSUKpm 109+iBde+ar8v/baVekPfOzpZ5GYmCQJ9ZSUVGlqbmbHQdDzY+L+b//iz8ToFRaXAFmZokpKqZiq nTs1OWB6wolJKZg3lIervjb4pFdg4jwkxk5IXPyXweKNUlGAh9OfxNiF65LT0LuxNugIAlLdkwla elCKpjlbH9S6SmOjNphjxrF9Zy4Ki+i10VV3o+5aF44f0a+a8SZQ5h3ap/BYfpmgR7X4aa06ht58 QiLkkfwStO9LikvwQHC3J5ifPHfypFQSPz15CIvmLURGRhpiC+OACn9QzO9R8VyitUmpB0zYBwfF 9lBO/J3Xfy7eDpVofX4fmhsbsHhxJny+TLS32yX5TsPU0DAIi4XDfY0hYumFs6elQs3f9TqpcvPy Jdmth1NHjuDhxx4XJU8WHEgGnomxYuhIRjtbcShoqOCn3/2ODIgl633JylXY+dzzkuv68IPd8Fgs 8MdY4B0bk9ae1es3hKbCk8zK87Dx4Udw+vhRkRlnC9Cp4PDYcAz39WHtliexrLULw71duDRQg0Z/ L6oMBYjPyb4/BotcDjZYMkcxne7yXxa4axtmZSH9airGZzC2nfwW/lQunvlAWcoqt7YcRktT5O7L C81zR7A/606gJEvvFzh8U6+lR0Gfai4e8a/f+nvUjLYAWjaIwOoxYlZqMSyx2oIBe9mM5bevlMFK GjeZOfPm4eu/+fWIvzc1NkZ9LUfAMbxkJVIBs4ssePhsNklEU8WDWlPbg/SC3q4uuDmKva5W+FDe tFQpBHTZRvBP3/oHJJnMMijikc89IZOfqe55aN/Hsllx0g0nWSvoVc1bVEAlUIfDHpIdpvHsOX9B jJ8xnoWRwOu9TkeASBwTA1eYNAxna7LCTV4XqRgciUajW1BYJLQb3uNksp8/fRJDo3bEzy0PdUjw u9gvX0HhrInkPvsoKS0+MjSIjMysiWO7GOgeUJrt2UbW29IEz+xs6SO0pJYhE2V4pLEcw9dvINma jJghNwztI3Cmx95DAT+DQcqaNdXVksT+xp/893v1Ub+SWLpqNa5fbkBLU0PE30pnl4dm55GLc/7E j2CxTU62pAs9ONCB6j175P9sgFZ2O+Zwrn7wQcRrmHtKRAxGE7oijVz/MMx1kbeHcWhyhvhMQ77O 7nZcWaz/nlnDFmxeuUG3dYj5Mz1QfpmDItRYrprirYR4nIHHichsP9FLVv/o378d8hS5gNmqFfp8 r1fjvTg4ibqlFV948YvilSnnPfQ9gsRVNgifjjkKT/kcTag8JyZWJLMV8NqzlYbzBCmRrW5xOx9U MVWDMwncrgmjTgXQLQ9tlvBV9PGDjyveHB87uC8wKFjB+s1b8OE7b+N6zXWMjjsRb7Zg/vz5WL52 beiccVrzsSOHYJlXDqvqmBTRvukgPT4eJ777XWQVFsJnNlOEHbUWO9zztOReX3Yy0oZnwV1VhFmt fpQuW4O6U8fvrYeVV1gkP5fO3Vn173bASgbzEp9V8CZctmYhTh5pRVuLK/R4bJwBzjA1gPz1q6as vrF8H3fqNB7aGimY98kH76OuNNLgmbpisa3ywQgeGEXaDCddWLchMgw+HeTZ3AnUi+Vuc8QWLV6C LSrBOKWFRc2lYvjDmZT0tNREX0prkw9Festvfv13o4aEu995S4xmaFCD1Sqh0VQDV1gsqCZFQmWw 6g8fxoNfDuSH1KCB4Knhv+ocmslkkqGmyrnjD4eWKm01E88zR7w2BPNEKEpQCpqeU0xmJoof3CA0 EW48N6urxbCHHxcsFs11c4+Po8c2gp6uLqlqEjdv1GDD5i2S8yQJVcH8ioUYs9nwyBNPyvmgqGDv hQMIb+03tfbDU5EP46gT1oR0odBUPLT1/uSw7urMummCi5C8rLva03eXFS3papfN+xgdbUJfElhj DSLXEZ7/iTZKSoEyDj1czTHwnnHSpxWBGJNIgZC5rAbDUW4yeu91VaU2oKDh6FHYgx5PYknJpCO6 vE4nHnpmgsd04vgRWDwGuM0zU1+k9LDe5xh8PlkI1lhraBrN5559TsZZLVyyVHhJNF7bdz6taRTm a/idabBKyqhQ0Iv4hHjd8W3kF9FrVQwWQ24STSX0jnKP0GsloZNN4Gq4bDZpdVEUDthgrZCGe3Uk hdxutyTGidPHjognxqodK4dMvSiGhHk6hVfFnFm4cCAfI9+L3Rnt/X3IWrxYJuEo8j78l0ob5HIl V6WG1rFHphsF17PfLyHdUGsrKh5/HO9+tAeFmVnY+sijInNDUipfw7wbW3vYZkSjRgoFP5/fk0db 5opDl9cTqNoyPcM8ssUEv9UifYbq/tV7brB480cbCf+rBNvwEFLTZ1ZxmQ5e/tqX4Hb9EIN9JoyN +iFr6DM8k5WHdn7XLs1jcQYjfucP/0R+lyEg8dHlXeyWmbUJka0eHhISMbZRxLS0hThADO9Ycmez bvXZM7IZsAwfjo72Num1m6yTgDyk3W/tkvYcjtoKDxtzsrNx6dx5mNaukUElJOsWZWWJzA710zmp mCoJzJNx1BYNBxnizX29KFBNPyK8fr+QnpXWH87J/PxL0ZuK62tv4KWv/lbgtV6P6HDdrLkm+SUa ZM7YZGX6xtXq0MbH59Hj6uvtFgPMzZyf+c7rr6GzowM+owGLdu6U0E4mPiclicQQJYpu2OwhzXW2 5gjJMyhd1DvQj7yKCpSsXSu5scrHHhNu3w++/S9iDGlMeQ6ZyOfnzSotRcns2WKUP9mzW4z0vMpK 6ftNOHoeWYXFGHYMwtHZA9fKQJXSlxSH8Z7R+2ewaEnNxjv7GF5wKflO8vfa61el909pNWDLy92S TPalJkQVwLtTMK/xW3/wFRzctzfU1nM7Sfz7BoMBf/B734z6Z4ZRaiZ7OG5cvar5/3MvvIxltTck wXyu9yY88KPPaseoyYmkMRNunDqG6w1XtFOqPT48vvxBrFBNqWG+hznTWSUlotFEgTk1ZpXOxn/8 0/+VY6P+U7jHQcY27zF6Owf3fYSHd3xOjmnfnt2yyFjCp2dAT+bYwYMiIdNZexOj7KkrLkV6UFG1 p7sbe956A2s3bJQEOx8fHhwQ78rtces2fvOYlHNmG7XhzfcCTfU9w0N4/723kRBjDbHG16u4U5Sh 4TFyYvO6TZtx8OMPRYmUA1g5Xi8rLI1AD5JJfUUqhgbjo/fewRgrk0EPmd48JYSut9XAk5kIxALn Ws/B4POj2OvH1778O6H3O3/+LGyZGRhh/2ZPgPLjtA3j0aB6BofAUiOLVIfwe4KbBnshlUR9V3cX Ctc/KIl4cuWOVx8OFMDMRnT1d2Dg1VdRuGzZZ5/WQGbu97/9LWninAzrHtwk4mft1IQOYq4vBjeb ++AtnlyeV3AbBul2jJg69g8YYZa5/dK7xQTrfzYwR8Kf9tZWVF8ahyEnCeTOG4fGYOy1wesbhjeb bTQT7GqDww2D2oAxeT3Qj6zsgDfE3fxa9WUpp6vB803+ECtyar2mH/37vyLGYkFvbw/sNhuy8/Kk B5Q/X/ytr8uQiDnzF+DTD/dIg/XmR7eLAeO4K6Lh5k0hWtKTuHLhnLS1qCtmNBCMNC58+7SEsUr/ IT2awsKAnLQCl8eDvGCim+eBGmJptlHhhumBhoweEGdc7njqGXns9R/9YFpVeZ4Pf2oq5rLHMiyX eNXWDF9w6o6AbTR2bW61qKAIJxvrEDdqx7Ynnwrpd/Eep6HeuiPg4X7w9ls6x52gOUejXk8oHOV0 nFKko76uEzEtg1iwbYdcp7ajlz/7BougmuKzL35xyudx0athGxnGj956Fc6agNi9GvYxG2Is7B0M hCgGqkJOYoC4k1EwTgFnsvHizBTUwqZXdeH0KZHoMFvMcjGiCawplaSpKjEkazJPwNHkeh6oqTMy j0jFAj5/NIzrxSpSf2+f7ntF4wHdbYhUrsMFX3o+TI298KUn6ufhomDxshURTO73dv0iFFYxLGGi meEfeUYEk/I0PKlp6ZqEPbWimO9SCJu89mpQRfTM8aOi/rn5kR0R4SYNHTl7xSWlSB0cQufQEDJK SyVxH47Ovj6oTRilcfwjk99n6WGyy9MFQ8Zknz9gRMMGa0TA50dOeGeBAUgYHhFvcjJQF34qMPxk ol8xWumzZqHkphPFzz4Sktb2rhq/PyEhE6C/DLB1ZtX8JbDnZmt6zKLh03/956h/Y6igxsWzp7F9 51PTas9RnwvmDRjfs0qiPyklEswLqJU+2d4Sq0oY84JSbmUwxoefXDsU8XrzSB+WpkTeVIPDLaKz RI9EjfFxp+zc4Y8TzI8ooPQKpU4UcGdl8pqtS9HAZlt6G2pt8UlhANwrS2G50grPnJxpGS0SNrkR aI6bk1tiLCLLQo1yerWff+mLoY2No9S5cXDoqAJWE1lsWbthgnSqByam6bWRZc4pznwfMsLpNbIK +fjTz0iYqmDfB3tw/vhxxJrNIXVR3hvMw8XEaFuXmNyPVupxu924dPZMRPTB9zp55HDEkJT+vh6Y jGbZKBm6swChniV4OyiaVayZA8rzNZ37WuGGhd6npDSifYzEZPUcAE5huvdJd9c40sK66+8n5i+o wL6Tx5C//M40p9iAqh4pfrtkzIysTKzXYc1PhjkPPqibeFaD2lM3blwSadlwmFv7kavSCVfARCmJ geFVQhqs9uYWXZ2uTtUwBKoJrNv4kMaIu5zjYgCiwR0kE+vxnyaDpywLMUduYPzRqadKd7S0RAgp 0lukxhTVM8KNJTedlWvW4ePd7wulQwn1KevCxa3WMg9vCP7hv/2LLHqqMgz09si5ZGsMvbdnX/oS zKQWhC3gTVsfxo3qy3C4XGiqrxc2vKQy/EZkLKrUPJc6YXWXLgYm0CxZKrkftoXR2//Z9/5DzuXO z39B8xrm5xiuUo0hHPQCA9dtE65fuwrD7DIkTWP4yExSOObEqZ2D8HPCAsWsaVBczMwTKPBl3T0N ptsBS6Hh4OKZLOE+FXgDjk5j4gwR6zdisz3SuCatnA2z0Sg3hwJqEE3bS1DhblMj7jv8fnyy530x diQSqrlHD255GJ98sAflCyKNo4JrVy7f3scmxkoey9hngz8hFl1hQznIJOd9wrPLUjp1ttTo7urE 3IpK3d3/7ddeFW9k5dq1yMjKCW1MvN70esLBXBW1yxkec8DDozufEoPDTayxvl7uY3oQ4YqlClP9 o7f34sRBVgd9SEm7JaHVYL8Xy9YAC1Uby0Bzs4RKXcZxvNVbjfdfPYE4uwc71m2W5uJ1mx6SxmQm t2nQboiOl0ceo9ejp6zLFAgN8s9/+H20dbYjZ/6CMCVUg3hels4hmMYCXRZ8vsEHdLsGcfjTfSEt 9rFRuzDsuzonpHFIxZBjuXYNfX29MpyEOmCOvR+FnsMqKo1q/9DEeqc3z5Fwof+PjMAFr8wlDMzc DsC82BqImFtuXkf/PTJYximkYQneGIc+mRhaqQaF1G4HbA/48Q++J9wXhlXUQ1IuAF1tuRCUrw2q ZKYUFUmbw1NhWkB6uHLxgoQZCtfnboKNpN/712/D7feJjlPFPZ6ePCMYDFixbr1ofpMHxAqaGswB iYRJFO33mYTQ4fAsLJTZdcbRHrTHp+Hs2VP45P33sGTlajjoYV6rFs/D4aCWV7ckz5UNYmySnkzO s1y5bkJUUMHJo4c0HqQCGsY3X/2JLMwtj+5AWnq6/IT+7vVKa044GC7/8F9+geMHJ6bADA14hSyc lReHzPx4XHzjDVTu2CFj13iPUsJn1DWG5iwLxrOSEN9qgzHGglmzSkKbBVt/3n9zF77029/Akf2f SC+geiCq9hiGAmKKaWmoMdswWKh1BozDDmwz5OOl3/+foceOHvgUGzZvDeVy3/3Fz/HiV35LPuuh Rx7VhJ7UDiOpsGROOf7937+NOevXC+lTHe7p+V+eE0dRk+mcUBrNj0fM6Qa0l8ZpdO3MBYsCLnb/ YA8iU9N3B8wXTAWefOWk3E1wKkz55s2o2bdPbgKCxim/qkqaVSk14u7uRmxiEjKSU6QsPh2QX6On 1jgZaCDVYaUeuDu/+dqrKFy1Ejnz58vUW4Z7nyWQbPrYU8+IBC53VHX5nAnsc6dPCplRXQWiNjjJ mK3NzVKG5wgsNRhG+uIjPWlLUz/8bRMLnDCYTegYG0LXwb0w0SMoLYE5KSTCpq8AACAASURBVBFn r19D/qJFcLvH0XjlsshcK3SDmYKcLnojehQNPv7U87+BTFVeKhzhHh7VC/75b3+Ai6dHYTYbULGM z/HAEhOLuHgPErJiMfvBgJJt+5UrMiyDXmy4XNBQXgJe6ziPl41slQmGjwYDHn7sczJ6i/pUZMIr 7UB63iRH0DOcNarykZNBIaCG558CLUsXZRq0Hh5h43NtjaiRztmgrXKqOwWIxIwMOHWkjKhhp0bI dKUkpCKzMRA6Dcb54M27/Z3ws4gF27TtGooiJZPxy1euieCs3E2wekdujM/nnTS8pZd54uhhZK9Y LrK/ClwOh3BTJqNIsDVHHqNKZzh8/tDr1a8hOZAVQrZHqEERN4a74Y8T1APjQqIHRUIwR7R/7pnP y9/2f/QhWnq64LdYcOr0KfzJf5/YpRtampC+eDGK55brUkgM/f1Af23E93t65eaAPEkUfLz7PekC YII2rzK4gHNyMNDeLglv9mLqjVWfTnM66Qt6UIZKRAMnSCemJIfO36htVDyP+AQ30jM9yJsVB1RZ 4c5PwzhlvUcccPTYkN3Tg4ySEpRvCpvWpApQ/FzALq/m8xma0tMhOAZehjzonDOGrXFxqXjz9dOi FvHUV6vgHnNJIcNgH5dw2+BwAWH5Us5+5GQd5sWY5FcGCG/c8jD+41v/GGpnUjZcTmGnhxUfHy9V zpikJDSfPStTjKjmwTCXfDSqXnD9sTJos4/Ab546rxkyWMUrVkDZD/ft/vmvncGKhvGhIVgKp54W fLugV3XuxAmsXLdOuvCpaaT3HC5iJmpN5XOQrJYF8fvRfOaM9KtpXkP3vLsXZtNEVSmFxuhoM7we l/CFFBhTckUHqvlWI6yxCRovoBXn4BofQ1FJ5Dmg8iW5SGpQgkRNN2E5/+c/+J4YBIfRgKXPBnTA bx44IB4VaRxyDCaz8Gv0pEUIhj/i4qttmT8wsHPGXhL5VcHwVNFCp4FVeFfh/YuB0681ovwfm4f1 QOY4aSkkaa7Z8OCEoJ3BIEaBOu7tbW04fvgQimZxYINJwqbf/qPfFX4U9c6J7x5+D+4FefBScTM7 GVdu1WCh7jxIQ8T/rKpUhFo7isWMV7//Xfy3v/hLzWuYvqDyaFdnP06dChROrOM+5F8fQq/Jgbje MVQ8vC3QAtahHSBMJjqNrvJZSn8hmf00nDRiCreNTP/qixcln+l2e2ChFHNKinync6+9htK1a0Pa +jRYTL6TzjDbtQhNNW2wV04+4ehXgod1J2DYNxmsqamaTvfpgBQHdc5iMpD1zCS0ekyTGmTkv//p PljZrG2NQVb4OHeDAeUbN0ZUCUko/Mmf/wBnzkROp/6rv34Uv6HTUPt//vIv8C/f0g4HJXbsKMKf /lWg3UMNNsVyQapB5jd3UBpfyUcZTchcu0byFOqpzbwxd+16HVu3bMWceQtEAXMytF68iNmZGTD0 qwyaMRPn6moxYrOhMqiprrDSKQHDRcicY7hZqd23D7Mys4RsqeTS+F0unjklC2/pypUaTh31x86f OqF5j1nFxZKjYVgZ3lpGj4baUKw6sjfu6pXLAUmXri5Z0OQMqomb5H2JVEzwMZbwedym3hF4C1Lh S44TRrenPAf1125KmoLnT5mmPdTfA8yauP7epFg0tDdJqwu1szisQgF5ZdT5oi6XUmCIi48XT5p0 Ert9wsO3piZj0ZNPimqHMiyEqLt6FQt7e3XJ2szDqbFs9WpRF1FHKJfPn5d/mXQ3pSSF0jCrv6jl UnIjnrd5syhfMM9se+89mK52w1acEiGied8MFisE+WENn3pgkpA3yG1/jsMRwTshA9no9aIrOIKK iz8uL08mEStSvSRcTjUvLhysxJDprDn+kRG8u+s12U3V4O7Llg5luAU5ShRFYwWKrjunmxRv3TJj ZchfGgyQ/jCKtVHGhOeUC0sh/BH0VnpraoRSwu4D/nCRF04xq3DOitURHhiLDrZbWrEsVuIahwaQ VlKC/NWrRWV0tmoUGxugKbioTvyzarZs9VoJz48fPiiPjQwNC6mRQxrCddUJ5oLG7NzwsiPuNeqg 8X4rnTNxH5DRvW7TpmmxzEmX+KOvfRNvfvA2Gl2j8LINhvdRZS4am/vQ98keFBaUYdaKFSgpnour jY2h6d3+OAuuNNRhYU8FWhobJeylt6cYVno91NZSegmZlGdL0evXm/HhhxN6ZOa4ROnVlM9V6bsz VcCqKqfhUE2UnhTHqLW3NEl1ko3kitPXWMdR9FoqRug82e3oabqF2Eztvc2XDnV2inaaYpSJRKpF lJXJzICO3n6Mu7yIr+uDJzUW7uRYCV3vucGyxsWivq520lK3HGxSElbpVGqmi2OHDkS0L+i1M/BC 7P/wI7jNJskVcIFcvXQJmx6OzHFNBj1/gRf2+S99OepreCOxNYThEy/6sy99EdeqryA6zfKzBxoj DuH84K234PV50dneHmGIOOJrTlY2li5fKcadoEJlzd69kkzmjRp6P58P9UeOCN9osgR4d1ureC+c FiNcn4J8JGVlyU1O6V2+t5LXcaoWn/J6ZeBCTm6esNHJPmc48ugTT8EU1uaj8LYopUPv5KKy4ak4 Q3cDDC3TjFbEXKuHY+PElD+OubI5ulB/9aKErxLGenww9tthHBqVm886apRwnFXM8gULRAmBVXGu M16TkB58UI+LG6o6FF6/oRC25ibkLazQ0HPso3ac6GpGS4pLRBXjO0dh5mRmmwO/+fVvIDU1TcOx dI+/i/0ffyBFFIaB6nFkPZ0deHz7Y7oSQqRi2HOy9Deu9etRMj4uktu8V5j3urjvQ7grCiINFru1 k3odGG7uQ4IxBmNOB7yp8bfN0eLBUnpjOohWCp8O2I0+ndfPKinFK1/7bSnvshHXPjiAoTtg+v5n BN3/lQ88gJOXL2H5b7wgVUx6WOTO9NTWiuFetnyVhiD46I7HhVqwe99H6L1Zj6GOfjFA/X1jqL98 Cxu3TwjYhYO5suUrVmHvnveRsLBSNrfQzuz3o6qyCitUDHVuXpy8rLDda69fx8atD4dCJE4Iom6T Wgo4HCySrFi7VkKs8JFaepSFycCwjQuZoTRzT/TMmOvhMVLhc7N5O771L/+A+MXlsDi9MDrcKF6w Bn0xDZibkSXeeVV+cFvIDeiue9JdqFq6XHhgBDlmbGQmWZQ9fPU3ajROAr2lzY8+iPzCPOx57xR2 Pr0a2bk54h2p1w2r377sJHiyA+vdFfw3qa4PZmpsqXhso/398GZmIik/TyKVdz/YjYTUVGTOnYs3 P9gtRpLvrRYgVECO2mS1bxouFiAIVk5nL16OuJRkrcFiLGvt7MLXf/ebGBzsh8vnweySOfjw3bdQ e6IBQ3Mz4UoNxNu/6mA3OaVDeDNxcOVMwfwJyaMKJuP53AnI6VF+wh83mUlOjHSShWcWRYMs/PlK slnv+axqhj+uMPzzC4uwzmDEJwc/RUF2LmoPHJQ8zbMvvoRXf/h9uKq0vZG8aZmYHbjVjX/+1smI aunGHdENFkMbvrZ8fgUuXZ4gnqaXlyMpL08MgLo48MjjT4hRYa6IksYMvSkkqYa6nSQa+Dp1X2E4 2IbCUEk5hzRCpC+Et50wHGusuyktasyhKVwohqFKQaGkoBiFVes003h4rtMzMmQitBpNbDA2GjR5 I57fJ559DiePHJK+VLYLKWATOAdE7HjqaaGamM1ubN+5U2gp0wVbsvZ9sFsGeRA8326vD+kLK6TS x80qY/48pBUVhXKKtW+9JaZe797i96cqLr3k0PflYBYSgFX3Or1mTv3h+zLPpbl7XbZRrF2xUnYw dQPnjiefwRanE7293Thw8gjqxnphHJ5ZmfizCrKBTeaZsc/pGQw5xnBcJW8s/Vi3oUDDG/LTN3dF HX/lcTgCxsny/7P3HuBxnde16Jo+g957JUCCIAn2TopiEdW7ZEuWLMt2nMTxdZyX5H735t2a5Drt 5jlO4rjIVbJsdVEUJTax906ABEGABIkOovc6/X1rnzmDM2cGIEhRlpx4fR4LHAxmzpxz/v3vsvba lmDVSvTemae5uxgrVxWFkU55o+8KSJSo4Jgm8oa+8c3Qilt/zzDs5gS88+qvw/rxmMy9fjVUwrm/ txv3Pzrh+bzw/Jfk805YrVL25o76xDMcjR45L7ho+QIUFl6WsroWQz3DuH7sWMhfsXrE8HJ+oCrF ZHlp2YRh6+rsxL5dO7HhHmX2oAp6AQxz2GSu7eG706CGFRPqZL0TLCzQQ9F/d14velb07rPz8oJT nkOO2WoJuwd4O91qC9OSFavw7mu/wmOfV9p1mD9srKsTbTBKyzA0pvFmqDvdwhFBo8G8oDqTkBv2 kSOHg9Nvhru7Q/p1WeziffHLH/8I6YHZlSra29rknDj9PnTW1AS/K7Xh2TOrbcSm907OFg0cZwWE GKzhzg4YdD1YKngj5uTm40u5L0jF4Qf/+Pf49wAaZp5QTkrRo6GlGfZJkuFZCxeGqEeS5zR2VZGu vRVkZmXjT771p5P+nglVFiS0bH/2g3GXpsehB6cIR8oFsp3mnoceCcsnfOev/gaFCZsAXQfK6Qun 8faOY2Hvs3pNlvRVZuXmTsj06tqNklNSpF+NPCTumlx0qkcTExON6OjwlpVf/fw8UlMnpHSJwUEn +vrG8ItfTxgp7dBVNt5aTMY7zqHjxKLurs5JB7zS82RjtLSYmEyIjY+T0OxqTZUYJD3ZdHCwHzM3 lspQBs4RpAQNeVIU25sKk5WCnE6nzCRkVXLR0uUSgmvzShIyuj3iZbKgwMGwHARB0NOaF6BN0Nvi aHmGyyp4zTg9nQ4JJ22rcxvVgbfBc2J3hKqx6qrA9JR4z1KXS483Xv4ZnvnSi2JAtTi05yM4szMR HYHGUrV9u+Q5QwzWyMAAfvCdfxS29xe/9oeTnsiYmBjkTJMR/tsAJgsjYcvuHUifZP7cf1ScPNGO //1f/xmff369sKsjgbvwjFmzZJOrrCjHlnfewry580Qznf/Oy4vBxYsTLVvshBgddaOurjeMUxop Ia6C2lVkzv/z3/1N8DmGRVTepJJmx7atYeFZUOrX7Ra+UCQwqc6hKfqqswpyrOoD0kKkd3BU+30P P4I5ZQuEg8WiBNMNKph24LlQ+Use93xse+dNnDuhhMb5RUVC/O1paJAks6pQ4Bsdi0hQtdlsYhhJ K2G+joKEWorGo09/Tjw9diHwc0nNUEEDq/U62Uj9q5++JNeARFsapjlFxci1FODwgYMYj1JMhHlk auoPibvawgklawpv0TucDINtbUJAZcEmxGDN2rhRHky8cw7Zo7ou8NsBb8Dp9BJ+XOgHN/zG4fdL aZnkz0glcoI3EFUf2erASg6rUKQH/LZh//5GXL+2DTVVzcjJS0Z6ZoYsFC0mQhkDSjZtgjk+HjVj I8jasB7Rs25gzOnF+pXLMX9uIZpbujE4PIa//Ns34XKF5zu4qKgoqgeJodxsqDyggvIx2997V4aP Ms+mx6E9u2VW3lT4xQ+/P6mxUvNFTJZrDQgbgBcuXS7vrcodq9Dz/OgRUWyPlT1WPFkAmD2vTJFX 7utH+cFDiMrPkynarHCyBYbnd2R4WLhRvI/oJe3buV2oJddqakQqmixz/sxwj+Dr2e/IhuWoqGgR iOTnMc9F0HNnLyhD2jMnjmHzgw9Lbkr1hskRpLIqvarzp0/K9CttRbGuphqGtlYxgqRCUImj/fJl jA8MSDgfv2CRkIepdjEdqgejhrjZoSPi+H5MidBYybnb9+4vkJCYhsTkDCQmK65159UrWDAjVAxP D56I1qZG2Ka4sDxJehmJTwpunV7VpwHeeHT56fpHQntri4QBdNNVcbjfNqgRZWNTH/75n/bLz7m5 8SgsjA226GjBQRbDQwMheQl6EA9/046Y1l4kJ8XKo6t7ENlZSRgYGEVvn1LAiIqyIDEpCiNmM4ZS w0Nzt82CYx99hGWrVgeVCdjszD7Hqb7AVHrutwOSUKmXrg3jGTKSWsAeWepw0ThoP5dGgNOao6Oj Qxj11E0/fqAWtbWnMXt2Eo7htAxgzc6Ow99+98/lPWlI2DPI0fXs0bxw/gwc0VFioChvw9wUN0Qa IxJ/6YWeOHRAOE40ivMXKyPkCHpbPGf05GiotMUI9sqSb0jjzXmL5adPicEjjYIgv5AEXobkhTrx TLY2cTQa1Rzo5W6874EQY0etMNWwql0Xvb29SNK8hn20A+3tQi5VYT6QWA+jvx7GTsDUMeEJ3fiw CnPmzQ95Uy3IJ+LBTwbmLnjQVHFkteU/AuhOK4MoXZNWJm82Cuq3Ec3NA7BYbq3iQMXNrpqJhH5q Shx+9N0/xK695fju9z+Uc/l7f7wGiTnp8DhHhW+lh4yjonBhb29wvJQ6fWYyaBckhRR7u3skvFLB 4RM3iwi4uLSKFAmJCaitViZ1E/QoSC5lyEkhP4/Xg8a6Bjz13HMh66ny/PmwKIb3R2JiNJqbG+S8 qli1Ok+4Tvx79T043ov5LOYs9+/aKVJMJHpeu3oFX/jyV4Pee5woZBjEkLLjYrKWo6lAo2axWSUE 1v49jWEk9PX14sU//CP5O4oJXjx/Dtm5ubAHjp3GW3st9FXjpnPn0FFdjbJHQ3NgZp/RD3mp5NYm brryvAG0tjSheJYiWK8H+4v4mMpg0Wrz4k5XWfPfA6ZTLg+Cpd2hwbDk450CF5WqGqqOktJziljx 9BnCBfcc0ZOPZsvJUY63pWUw5HpTcUG/ibHM73KOhbVIRVKgiI62w2wbwdqNM1G2OBPzHtokU2ku 79qF8nffxYzVq9F4sQKegSEsfOoptF2pkcrcxYsVSGiIx432dmnbicSuYg8k1U5vtLTg9V/8TPhV bBQmZaL+eq1wjKigStFCEo5ZhGFOasbMUEqBWuJn6M+hJ2Ss00vh+aXx5PflRGkm3vMKZ0jC+7// 2f/Br189JO89q3R2MNwsnDkrTB+Nieqv/z/Po6XlBzh1aiK0NJs5p9AQlotjexBD0hd+X8k5k5TM uY/0wFRwHdLIUb+ssz2yNhxzegynmX8cDTSKs7hzu1DVTAnKS/P8c0AHN3P2GF69XIUN94U2lz/4 2BM4X1GOHhJSx8YklaBVdGAVcVJL0hvjRkNb46QG61Yw2bBMLiD/ZyikU8F4/eDBA8jVuM6fBOh5 Ml/CoQVTaX5tee3XIaE1GdLjHNceYSPwOp04dPiQ/GyPiZGRTUT39XqUn6kKY17YbR5YMsJHs6e6 emSR6LFqVSqe+JySUG5rvQGfz4iLFzphs3pEz0y/ALmQezt60WsNTR1EOeIxJ4IxSJqRiuceXhfi UaWXlODCzu3o+3Arxu6ahdgaH/qamlAz2Ag7F+PCBbhy6hTic7IQ7bDhvbffxOb7FW11GlASTrtd TqSVlCD9rrXoP31GJrboBfY63+mQpnFyrx5+8mnR+2J7DrsgtOef4ScZ5ju2bhFCKJPpJKGeOHJo Un317u4xvPzjt3DfQ+swozgfGdk5aGttRv21q7KJpGdlK/LTfqNQShYuygoxWCS7Nly/FhJWUVue k5aY11KT8/w9Ge/cPCJtnixUvP2rV8RAMZdGo8dqI43K81/9/ZD3P3pgv+bz/bhUXo57H35EzunZ k8dFyLCtpRWPfG5izqQKbbGA67+wuDioIEE5mj3bPxCDqKV4MLRcf/d6/Nt3/hFppaVCceiuq5Pr duNyFVo7m6ZozTH4Udt0Dffg44nHcQePFCwwgfdu5RF4U5XdOqXbhdCRAbeGOzlB2OPzY+nzz0/K jbpTYH5hzvz5Svf+FAbryeeeDzForACdaW5AUqEyu02L5vPnIxravd9/Ba++fC5MleDP/vMyPKab Gkz89N/+BZ4IHQr0aNTXs+2GBonEyNrqagn/9d0G9bVXcf1cGxKiw7vwYyLoX/kslrDwjwoCnsJU uOcqifyxRDuq9+yBd9XEOVEVABLz8oQAvf3wARQmJKGprxeOvFyUBKraJDjS44+kBqrH0lVrJG+z c9t7kntkzoYFE5JRiQcff1I8WPaFkmbAzgk2JOunJdfXdcp/399ai/37GvGlF2fj0c99HuvvuU/O l+qVbn3zTfz4RwqZMz09BqWlE6RKuwzYjQ4Zskv5GybLFy9fKQ3PxLGD+wNyL5G17+ndrb/3PhEg 5IbDyi21vSJROOhEcGIQK7VM/LOoRKFAGjumPpiQZ1ubFjwfW998PUzlQw9V3UGP82fPYP6TTwZz nuRgcXNqqqnC+D1zJzdYPgOw3XsR+bveR25mnvQQ3Y7yJ7+A1oqyxLtr305U2UbgnTNR9vQPT64D Ph3c7ARNBbrR506fhMlihcNul3FPcXlTtereOXAn4vy6McrIjo5g1d0bQkJohjhTsa0/TdDrcPAR FRUkFH5Sn6OFOzcR/TkJobMKNaDyQEJhIc4cOiSh421/rskU1H7617//G1FooMYTvRJ1EjgNAKuR bIZm5wMHpuqN9vDwRJg8NOQSorI6G5Dg+7372rt4+61ytLcPSw5t1aoUPPWFCdpIVyfHwGeGFQyo B6/2a5IqwSZz5oO0YpjaASr8bB7z2o33iJjkRx9sw65tE61GrDRm5Sjr8kZLq4S0qjGjZ0Tvnvky VjUJGu/amsu4VnNZjDnTG2wNovDAVGC4fHjfXhnPp+YQWfVt6OhAbvEEF5QhIecRtFRfRofHO3Xz 81CUF9/r3IG0q2bcG78Yz7/4e7gV8MSxUqDyROiatw4Norm7Gd4VAQ2hzwDY43XD7UJW6WywPsXQ 4k56bFOBF5gLgbssdzPmRLS7KKspn1WD9alBkuI3vz6qJPadQHxSkhgBpjEYivG/JIuSu8Sfme9i 3ujn3/8e7nnw4VuaMclN6eypGlRfVsQGee+x54/5KRXTUTJ55KnPB2kb2vv3ow/fDyMZq0M6BgcH 8dgzz0pBiHjr1Zex+aFHgyEhuyO0FA+OK6OuWvB9ioqD4/Vef/lnePRzz8pnT2Wwjh08iMP79wgT nufyC1/5qvQbHzpzCrM3bw6bkchuh173EPzWtJurNYzavWjI8GL/jQqsra+bECubBsbYA5eagrde e1Vi7eGYaJQsX4bmN1/GbwLaoRFTvq67W2Fs/4aMlBaUOzlUeUGGa8bPL0Pt6DAbE4O/H3W7oBfv sDvsGO3ujhgS3ipMJltEaZ5/z2BIQ9oBN4Lh4aGbzvUjXSAjI1PuD1bJnnnxKxIKVVVUoKikRN7n jVd+LqHgV77xTVw8f14S+Mwhqc3JU+HsyXNBUT3C6/Xh6pWJXkDVk1q7PnLS5ML5s9i7c7t4WlTQ YHKbnhjZ7qQxkB822TRxkbGWmRKGYJeCCm6i9P64jqorL8p9wp7I+x55DBVnJxQsGA7TC+Z5VN+H r2NBST1/dF7OnjsLj8sFY3YW1nz960HP+cD27TK2btamTWHGiqBMtKmjH+bK5nCDZfUYUNaaCAQo +cHn3UacOHdSvmCkyS/j4+MY7O9DZ2cnGhobZOS2NyoKhbNnixQx23ky7uCOx7zPzve3wh4VWGg+ vyKArwGlRAie8KkUI8g3ccdGK6qXmm7xYCOmwRA2My0SpMfvNhCXmYl4Xb+VCsMtTpfmDcGHHsxD xMYqE1O04L9ZDtdrgk011ZqvD/tct1v5/rr7jWV3hhEeb/i5OX6iBb29odXCuFlOkdAl3C4nxkdH ZOowpXsNPZoJKiwI8Ob2+4Wvo/a0qRro2mupguRGnpuG6w0Y7duDsfFh2GwOlC6aqXCL/H4JiWiA WM2SmZo2u0xeotqBCmqe6UegcXzY/EVLJCHP/My//v0/obd3DG7XGAwwo6goASUl6YiJtYRNW1qw uAzzF5zH0SMN8Hh88rWiHKGvGR8bh9PlhFHH3Od14tBYhlVk2V++eBFl6xeiNNB8TtUJGuVIkOlC MsNxIlfLy06RPhpbbmLf///+AaVlZXj0aYV+QWoFw17t5k6Nt/sfezzEgDGU1ubyOBhk96njyIww bk4qq5s3B69hiPTQmRO40FqB8vm9iBkbCDdYyQMWRM2cAW96uERyY0O/WOxIk0/2fLQThsxMSZbF LlqI+ECXNUFxuk9CoI5JR20u4HbBVowtb74OY/9EHq29vU1akEicG/V6UHK/opk9KQyGkHFH00VN 9WXYMieXheVN9earr4h8jgrmTyj703I5fDIzy8FGnSokEWP14D99i9W9UEPU09WGra+9ESac5x4F kjTaRypsFquoqEbSoz93/GSYgCE3MqfBB+toOAWm4foQGq6GWri8Lh+u+7vhy0mCn4uCD5MPhuJ0 DBw+i51OpZ0myRQLC0ww+oAbv/weuo2K4cu2pgSF/xbOWSkDHbgKOTJLNXCx0YnIS1aS9MOuNtRX teD8qVMyDZweL42Dx+tVFrPZgjllZeil5vw0wb+JiU3Cj19SqmyrV2fhO//2LakEEi999ztCGmaj el9PrxzW3etnICfHjAP729HVNYJHnwptF0vPypTJ1TbdxtnU0IC8AiXqWbNho/RBau8VORcRhsCQ Oc98Mo2KtprIQbIsiDE1wWb2lsZ6PPjYk1N+38nUdKeLGWvX4vw772DZc2yan8D10yfwXu8+DCS6 4TcoKaqIIaGfycwICc2BzBjUXq/F4kVKd7oWYxYLsu+gB/WbRlZWttALIoHl+r7z5dJdrsKRno74 nNDE/HQn7mjR2NCA7MLJ/46NxbMeeiikcsbWB3NzK+7eGD6QVTuSSQuWkZlb0Ye9b/ziZaRaF8Fs DE0Un66rhNkU3sxtt0dj7fpNIZrxquBd+Q4fjIbQyqrB3ICsdSkRB8FeOftTmtKQ57weTooxw6dv kDa6MYBRDEDhlQ14JzTMcp0J2OsPjI/XdGi1ne7E5gX3CS0ipbhYkUEZGkLd+7vRO1IHl8UDU34U HPZcxFiLcHn3buRt3izz8QoXLQoKDV7ZuRMWztHr6pQBE51tbVKChEQKSAAAIABJREFUp1495WWY bNeO1WLRJC19YhHTccjIzg7y7f78f/0ltr31BvJnFOH+Rx6XKIHKvETp3N14f8tReL1uSWKzMqg2 Mz/2uWfCiNynjx8Tw0rQG2TVjxwzLdrbWsUonT91QrYrvh8bjfkdGPZxilGxGK5YMVQFM0YVlvrI iISn7JtUvSUqeLCxXQuG19T2onqu1+OWItI6nYLGVOBYeqxZg5q9e6XCTWrOiYPbUB7fhsGoicgo etwIs82tG6PjDexqkWA2oqG5AfPLFoZUsliFcOh21qnAYQRhI318/mDMqwddRT3hkZ8pQ1a93jBX 8lZxMwkPbXOpWlV89de/DDFYTAyqO92/a/gNkif5jcPrw5Dv1oQWq/1teCQ2VqgOQfj96BvpQf4D G5Cm8/pV9Q3teHQiNiEBG1atxSsv/VBE8+bOny85Heaqnnj2C6I/RWOmXTc+ltkDeOyplSHkYG4a RbNLhayqlvfVoRLPfvlZrN24ShQxSABdt/Ee7HjvXWx+6OFJu060YPWOlJSv/+l/ltezDaz87Gkh gW968CFhnP/iB9/D4888FyTFMiTbv3un0BhouEhTKVuoUGNIl2D7jcPhQHJamsKmD3jeV6urhDmg KvuyUsxvTe7arc6fpNHyjI7h7Gu/RnvsOKqzhuGyTDgIBj/wTNJdMC+L13lL8YAvOTJbm0MOy/tb UFh+XlxH4vyZUzhx6RxS08MbTSdFhAZXhjlMFkYCy6/UpdaDLQ880WyAvZ0pzB8Xqg72aH+/DA5I TLq9GXi/TXB7jNJ8G6mx+LOGcbgj5uJowKZKUTDnqkW03S73F4mPNBwEe/bW33t/eAN8V6c0Nb/+ K2WoRUlJsswBvBUwT8wH82jvvfG6tNhMt52mp6tLmpm1xm1myWz5exoR9gTSyGipDrHx8cKtYw6S yXvyy0Les7tbNml6Zfc/+ngwhCQNgZ5jmHG6jeJV/fHjWDm3DGmb78X3Lr0VYqwIk8+AxXnzYPal 3Zol9MzOxLEzx4QkuO/IfhzsuwZvaRKSJpfkDoMML9A/ZzFjhk5ZUYvJFghDoDux498qj8gzOIiY LiWvkZOYCEtiCmZFSCj+DpOcv/HxsHzXnYYJxhAFz1tZUAy7mbhPDHjRJJpGkvrVo+HadfzFn/0c 9fWKQGFcnD2iAACn5sybpHKnHdi6+cGH0DZNDfn+vl4JzZnaYKhHKoTN7sD1qzVYtmqNqJvyNezk eCBCXoqEZIoM6kGjT1mgsoWLptV6RoOt5YudOnocP3/pTax6/G6Eq7gDTUePojg1HcWzSpCXX4CN Fy9gx1B1MKryGv1wm/04d+LM7Q2haM9y4LVf/BSX0w3wZd46YTMntwiduAULNwWUHfT26QjMPbz8 ox9IY+atgBd/zfrwMeZ3GqM9PSEysp82UlJSRJHi42JscBCJiVaYi0KNVky8C2NeE4y9oZLTftut dx2kIy5EJUJlulNbaSqwWyAnLQ1lS5bhzZdeQmqE/Jseg4MDovRJpY77HiiA31cIo4lDM/w4+NGu 4BgxFje4EFmgYXWNMs5TDWWV42moF9mZSCAP7NqVauV9DEZ0dXZIszFFBpl8X7thI8oWLcLhvXtE J6yrvUNyY6zc6nHl8iWZ3B0JK9feJV7lzUAKA40eE/pk4V+urMIH718XQmzp4iY0nbVIVVzdNCiT bHd7guPk6Ml+7Y/+GLFvvoYYDt0NsN0rdu7EDz88ensGy5cci8tRLvgSbh5TR0JqURHsb53A+Jpi pTz9MUD3tuF67U3VG/Wou1aLy1dq4IqNQeHme5AZIUydDFR1TEoONyK8WY6cPDHtlh42c5ri46aU 4GEpvkE3SJWleZvPhw8/3BbyXKzDIR35+3dtl+c4Bp25FYfNiO7uXhzYMSGbPDAwAq8jCp4oK9p8 1TAalOvgGhuFz+1BWpkDL85apry2exBjg8OIsTuQm58iRFv1M0R8z+nE2Pg4hhx04ycWn3t0FCaz H87LnTK6KXj+BgcRZXdgxd1zgzs68yevf/AazqUOQKYTBNgOvK1nDCfDmp2BsvlrMA8ThEzTjT74 shWDVIyJcenDFdWo93YiGrYQb4r0h44rV4QJTzUA5h05T1FVDSR1peXCBbj6+nD/V39fyvr/5X/9 lWjDsY9vKqUN0hpIFiUl4PXTH8HDkVxGA8wXm/Dk/Y8IqVSp4JmkxSd4rENDuFR+XgQx1dyQHrym TNBHQlN9nTDQWenu6enG6PAI9u86jOvXe/HCV+9TNNFpyDrahZFef+2aNB1fLD+P1sZGCXMXLFki 15GMdtIyqAGvBakR5Cq2NDeHcLVIF+LfRcdMaF113KAa7oDoeO3ZcQxbtkxc91dfOos//hMbigtm SB6PubMhgxFL7n8w5PNE6iYhEUkaAznWN4Cj+z68PYPlt5nlcbvgTTJ36Wpc6GuA5zan8aigQP+P /+W7mDGz5Kb9YYqiwCDOnDmNQbMRacuU/F3rhQtIuon+lxbk6rDUrYdMCcnJRoKuejgZbly6JPmS yaYhEzR+BWVlolowFdqrq7Fx3YawKiCrWOlxfSjIDw0/tu+sQG9yPjJ1x9rb0CCVtCzd92Mj6pz4 xDDdI/Ksdh4/gpy5EwYj+NmHDskQWD0uv/kWnv9K6KBX5kjcNqA7PlTsjsnWPIMNpoLwDcI46oK3 MMKoqKYbONN5WjwsGiWR1rVa0X3tmgwzoDY40XDyZLAHUa9w+ZOf/CjkutTWXUdWWnpIQ7B+s6LE jZoz4ww9wr28CC2tzXKfmowmMXpaw8ef2USckJAQdi2Cn11dJfr0erBpefa8eaIaceHsGanM5RYW 4M1f7oDVZhQNfOIaQ8LVa6T9a86CBVJFlEriWmVmIYfjui1GMXrlVRVYtWx1SMV7sK9PEvSqJHJH +w1UV1aiZO5cqWZqJX1S0tPFk5MKpHPi/LHdaNOmYmy47z7R5SL4eWTm09v0R8hpa5FcWID0TN3U nN8kMufORdv7V3FDvd/8VJZULLiqFz5dkNjGL69n4dMTYGlWRVNjI661tSJr6VKkfQxmN7lFkWL9 3+GzAQeseNq4FCabFVUVJ+FPiIJj2IusnEI429vhSEyUMFtIpjQwOiNPna3S++4T8rAK8rnWlJRO ylynB8N7OCMzC6bmHrjnTRiY5o7bl2mJtHhVMEH+zAsvijIDPSP27L716hZs334VX3h+ARICx1p3 9So+98KLiATOLOQA1g+NN9gYCGPnINLS00P6f8kfI7mUCXaC/2XhZdGycGPPtp2MzEzx3J589h50 dY3i9OlWmM1G5OYnBo2VSskg1YbDRFi9JBhKjtosiNERqePS07HpkXmf7qj6krvuRvexXXDNyxYj 0NnRhq6OTgwNDYh2z3RB3tHBPR+FGax3PngfcZr8A11NGisJA36HiGDFczLW/W8LJKR4fJ1wCVUi hPVaX1DFgmEhvS0O6MydpmY/PdfDp09iRlY2srOyhXPEJnl2IpARTw+RIE/Lb5+8K4Ievha7tm2V 6hy9cya9GYaWls0P82IZThYW08tR3pvCgPMXLZZ0wo3mluDfFM/Kw5w5NbBZJ9ISU9EhuNGf7ayD P19JpvsDsxxvF2Sn07gx9F2wZBHy8o+IwTKZOJZMl+/2K6KWojEf6D8rP3MKQ5kZwY4FyrWz44SI zkj5dA1WdFIScpNzUefxSH8ce544Bp2cLO4qvPFu1t+n7j7kY+l3IhorfWjzO9wEt9gK9FmEYdw9 qZIDvabs+criHunpwbl330HppnuCIXckTh979DjGKn/pUowYDNi+b4/QIgpXrcIgx8AzFxNof2Fa Yu3iFdg/3Al/jMKt8gXSJwuXLcPRA/tCEtScvPPMl74cQvAl2570A4aX1NiS9iaPB5Xnz4mkC0Gi pipV3NHWinUBjfm8wnzMmpWCrs4u/Oif/wUdbR2w202S51I9JOJS5UVcvVqNiuEbcJfevKgwXdCQ qzQOq9WOouJkOBzK9z978ioWL7ss1XRWSWXAiG59k3TaeaGCQm2wxkSjpa0R4/GBDYBioPiUQUoo Z+ypSEhMlAGPTA4mpSRjxVqlehAJDCEpE0v09HRh9wdbQ19wh7W7f4dPHtFjoQaDt7PZAxgGAr6S 3fKx8qda0NPudQ7i1On9cPjNsuOnxiaLl6kWTjqvXpWcljpzj3In8x5WuFgEK458jAXSGURp6Twc qNgVNFh6Ss+B3Tvl55amJsydHzpwlglxKiaM7fhQPDfSh9bcvUFa4o4dOiie3MkjhyQJf+rYUdGo UmWHiXOnzsBud6O/34A3X6vEgoWpKC1NllFjNFhM4DNndSXLhPEUwJ8bMFY+P4ydA4hvHECVp0Ka l1XQ8+P8zKuaVjBSF9TvocXQ4FDQYEXHRKFsYRn+7h+z5Dj7eoaDHQH1169LQ7aeKkIhQU5j+vt3 fgxPvBFIzgxeb1NrH8z8v+nAODweMZQysFlzzAWk3x7Lm1bU4JngvTP2VZUJSVRjG0DJ3HniYtKL qr5UifHxsSBJbvX69ZNWV97e9xE+CXAXPakZIqlO7WHiNWlpeNvSZHDExUnC37Z6dYgUrL5KeOXM CRhtUzdfO7t6sIWaYjqH1Ds8Br97DFHRodeus60bti43XDrJ3OH2Nnh7ejHWHDr5ZbC7C9Upqbhy baJdh94vy+c9HZ1wRZjuO9bTg87KS+EH6/eLp2EOsLvl+F1OxIxbsRgTFTTC3NAFb3400KYkdg1O txCPjX2j6DUNwdsdqmpAJBiihBk/mZelx0hJanBseo/TBdOQFUe3vwv7sAd5ixcjf8UK9NRHHiwS CcnJKbAbzMEuIa2aLqMGtXGa3EI1KmDPKGkOHGbhHBuXRc8mbJI6FRgkH0tuVWHxLMwqLZUhE0yF +LsnNmuTyY+YWAfmpESJ9tV/+Z9/IINiODmH+utX6mpxoyAGcHnhD6xnmUPY3i/UkdistLBJThTv 0+erOL9Q3wBOsPqodZqo7EoaBXW3DAY22o9Jvo/ab8y7sfpIhVV6k011daL4wHYkh92BwQjzK833 Lg8tKU6FScMzAytCh4Nd9reCmNgERJ+tgkFVXdBg7cZNMt6JF9zkcEiei9NAqJioHk8k5YhPGhQf iyRmePTQQYzfgkopGdfWQH/bpAbLCLRkGOF3TL34zGN+tCeHKxRYXMNYNXtZsC9OxVhlJZbkF4ZV /TiFJbegQJLHWlRXXUJ3YnwYZYPjnJLj4mSohL4LIN8RHQxhQnD3Brz80g9R8uQTwaf47czHjsJb GtomZeoZgbcoPcyrslxsRq21A6P2cNXSmR1GpDk9wUrdZCCpNNWegFYODY1XvBR+jqc0CwN+IKp2 COmsKN4ic5t5qKIeoDJQUBoMbMiUBKbhIItdKSwZ8IsffV/GkrECx9FdlGGyOeySCOeEHBVkphfN KpFeQbV6yd4/crS+9Rf/Pbg22dTMjZ4e2ezZidIbSG7Ths33S+sbG5pJR+Dwjfeaz8OblwxTQxc8 xeli4Ieah8KmZdOA6IfV8jtGmqqttOyFnq/yM6eDMsr0tK5WV6Ph+nUZ7lrTdkn+hps/VSfUCmqK JUo/21d5/zslA5xssqDIGu4C3xRWO2ZveFBGfutBYxRqJP3y7097qEWkacfyvDqy/lbe6yakwcAH BkTrJod/stcYDQpZUfc5/A7C0dF9D5W3E+n5iO8TeE7/evW5ya6VHK7ubxY+/jiO1hyDJ/fjCRbW pwwjuaoe1iSN5905IjQS/WemFBXB09yADpsFfrtmLRg4fr0LVw8qM/zIeq87dkwMM69xyowZMqGY mzTJqJ6h4ZDEc3HxTLQ0XEZffhy6DS788qUfYt6ixfjWX/y3YN8gtdj/8//8S5kTuGrdxGxFhkmt Tc0ya1DF3h0fyvh5nld6ZfRQKelDz0xLPKXXxjFnrCBSBobGigZq9wfbRKeeBoERCdvI1o0MoK6i Fs15cUFvdNDkFa+HxOjbAZ0L7Zpleoe8RdWx4JR1PpRWOj+ysnPCigzE0twS3Di5X24Uq8GG0Zxo FCDxzuWwUtPTUDJHLzU3fbDj+3f4jwHSTUwRNMTJSUu6ZEPXsBOmtj7JWxn6RyMXBtweYBIHig38 lnEXUjpckhi30nv1+yfV+HIOD6Grpxfe7NDUQmxqGmatXx/iYbVVVSE2I0Oqc/w5lcMVFi5Ew969 8ns2/lL6l+TKNWkzcbimEmMuJ+595LlJm+z1h8WUCKVkEpOTZWGzyZiVPovFKl7ST773L/jy178h Cg56DTgaMMqF04hVlp8XD5rjxDgkVcv/Yq64rLQMp3rr4UuKDlFqqbpYEVHxYzpgBMSwlVQLFgo4 RJZihhQfVGdHqkTbU8cOT/o5Pq8Pnec7cPBAO8bHPdh8zxws/Frxp590/3eHT0G19LcJbCWpqryA jOUKqVGPBHM0ejs64c1Nhn+GCdaT1xTjZDPD1NgD44gT9t5xxMfEI8rDPFGoWOHcpmgsnb0WBasX Sv7v+pEjSJ05ExmBilok3KivhXeaPbX0psghJDh2TAtWvqjiwHl8NBzvv/UGLI098MKL9954Tcr9 XLh6j4KTd8LOQ1KiGCom3knyPH/6lDRDM5R64LHHhQ9GNvnaDZuEeEomfk3VJSSnpEkulS02zDHR o2QuiyGmHufLz2JMI4MTfP7UKWGrq2BujdVMLSjSxxSNCuaXSWTl57BvkeAAWRrV45w0rVsXMXGx 4onxfEXStON32L2rNbjJ7N1XDbP9JprunwUoMq1kP3/2uVPcwSIL5PwO1O5mtYnnaMM99+HtLe8g dlO45G9u2Xw0HPgQ3hQPEtvGUVC2DFe7GxHdPIYZJQsk16fm40zH4/G664D8nDxowVxLIe5+7BE4 AvrkBAdxXj1wQP6OLPdIsHgNMNd3h4aEhCt885nMSxsZHkHVxQvBWXsMhalssH3LO9KMrKqJULhP NQZ8L1bbSOnR6mkRrU1NMlKLOSiCI98P7t6FqJjYYA8rPbCdW7eInjzzqhw99t6br0mDMmVlaDSZ z1L1srRgtfFyVxP8EeSh775nc0grEEd6kRahBY0QB0iEvucILl24EDKW3jnulAnw+mpgxZnTIrXM 8Hbfzu2S6NdK8PzwX7eHnGv+PDo09tk3WL9N4E7ZOjj15OFbhcHnh+NCi+Qu/D4v/FYLjDq5Z/LW XCPDMLSHatgb/QY4TDbUNR8KYW2zfE9CnqepFaeOHJWnWKlhHwwbc7lbp2nIo9zlu7u74IyODskB iXy01ych1Uhnp+b9lRuto71D+teYE7n34Udxl0ZwsKykBA319WHJeo70SvM5EDsYhaINSrUqyz8f dUePSt5Iixmz5mPmntNIH3Vg2boHxZOKhFkbNqDivfdEecEfUCNlnkkMxrlz6Lp6FYW5uUgvCPXC umpDBQyZr9JrZalgPx1HX4WEPTExuNHaIpuuarAyc3KxcOlSoTfs27VDBkBEGslFUT39yLHdH7wv Y+G0iW/2/y3SNCxvuPd+/PTf/lUMGS/Dc1/9mtAg9LLWZ44fw0CUgTPtQp43eL2IiYtTtK0CXhHD URpHfaVc/xwLAzGxodOcaYx4TFqwOZtMelVokOHpz/7te6KVn5is5C/JjI+Ez77BknOmnDjKkUxH 4mO6YFc+E6iUz60eHQuZBnI7GhAkAt4Y6FfkeG8CNXlNmRXG+uzh00LdXQZbb2Dl/Y8JpaS1okIS vfpexZ66OrxT/S66dH14eV12/OXd4ZOOXE4/2poMIbmTgZF2zFyWLdUr7sxaHDt4AP7UVKRrhfAC n7uksEiSx/peS/J9Csih8yvtGnq2NTWbGnZ8AGgMVvf169Ikzckp2t5Jn9st5Ewvq8Vag5CSgifv /pIYksmMlQpHbCwubN0q55ECkmY7p0zbRDkgOjVV9MxUAb/JDBY/n7LfNHajfX3BBnZeK4Y+1Gez 6BJrDA8p58JJNgTH5TVev46iktkip9Ld0T4tFQTZNDo7Q1qDOBRCbb9RwRDr4SefQn5hUfCc83ro VUIZrqU0DyPPkiYDfVUYkn3CgeRUd3X81nRB6Rp1+g7BjYryNpz8xIcKHgtnbaqgZ0XDykZuDpcl HntyCSoqPvrtM1h2DVdHKlt3iMZAQ0UPIb20VB68CdU9iEakt7wC9z88MRfuZiBDl6S35auVqchT gRUe3kQb181CbGxouZg4dPwqLCXzZXEy98KJOlpDx143Lfic26RoBmnhM0FUEfTgGeSMEa3BMpms oiqpveFUUNveyyGeuuGXw7GxMqdPP3WGXhoXk/o8R8Sz94zlfG0Fae2KVTh45JCoPUQ5HCjOyYMl JTWs0ZvngW01fc3NUtXTgtLL/P4Np05FbGSmQaEyQ2x6uiTfC1euDHsNG7tHp1GtTSooQPnbb6Pv YqUYG8IeqMyS+d5w7VpYfooGhlLK9I5IFamuqpT+OYL3MoczRAKvDQ0HxfPUJ6KiY6QThAqnZMRT mYFKCyq44BluaiuOBL2lSH1/4+NOkY3RbyakSpAvdTMDqgf/Tvs5dC4Sk5Lg83tDWpMYieh7Mkmb 0FInSH34+398TH42W0ziQHS23fgtMFgOO95/63VxoZnLipuEJHqrYFsGcxpsD4pkzPoM7H2aWjdJ C5aOFU3s8OSmHgwBvvDVr+HtV36GP/6j8DzOsXMNouGu9SYILsxIE3E+aVAad2AsQrVuEjA00IYL 5KyRPMjQSDtOjAbt8UefkGQx9Zkoyxt1pQYVly4hc15oLyk9o8YzZ8IMFkGmOT1UvQdWtXMnYpKT UXLPPeItH//5z2Vqi94gkgsXiY7C5wba2kJyKQUrV6Jx/37cvVlphVHB17Q2N4maAytzDAFJJlYr h+QUsp3mmS99JWi0KdtCJntEb2qwH6mlJcFeyMvvvovf+6NvSjV9y2u/xtwF83Fo797gHIVzJ0+g 4txZxMXF4d1fvyoJ95mlc6bkT85fvFh695j7uhnaW1uQodGKJ5lU69V1tLfh7InjIQaLBRYSYLVT nskPa7hWK9VObc5KD4p5qhw+Vjx5Tj76cNtn32AtXLYCswKN0OrUWXI7poOB1okqgxasHlGrabi1 E4Xr19xU0O1Og8MrabTWbroXW7edweOPTq8B99PC7cxrNOjGUbExfcsbr+G5r4SGqFzMXITqkANW jDw+H5p6ekJkjOnd0fCw6scwjteQD4Z3DA2jYmMxePEixtweeP0+GXlftGZNiHGiseptakKWzhjS 02FYziZbddITkZiZidSxcQmPtLmp/M33orWpEdmc6ac5R/QgOWaLhku7SLngaJz1JXxqsqmscjZA Hz16WPoG6YW4LeYQ48v3t1it8plPf/EFea62pkaapntd3di3cxfOnetBS8uIFOSSko4hMysGTz1z t0i7RAI15dmCQzJqd0Dum5XIjhttIvWsDkNlaMeJ0vGBgb4Wi1moKSQZE6Rw0DCpE6hVcJCF3uOk l/jwU58Tw873pYwNKSIql8wYmPij8gTDjhnTgGt0FC3l5UGyJFUCeVbUi8v4f0VA4/1Og4QzlT8i vI5xF8yjblnwwxw4amDF2yru59j4mCSPTUYz7DYbluUVw+1xybFG26OVSsP4COzRscgrWgCUGbD/ 1CHU7D+ErE3rRcLikwbzQ2oejpUY/vtnr5zAs08vRnSEVgQ9/BFaYO4EqGvU29sT0YMdGhgMm1N5 q1BGuufgYvk5EX3jdBUuNoYr+iEfBQWFuLB7B0xz58qATYLhOz0e58iI/MxQmTpXnVeuwNPSinmz ZwenGzMc3X5gX5gnRU7W9aNHRTuMmlhqeoGvY0M0fzeTvKsALFFRWLJ8ZVgagkMarl6uCjFYKpgU Z2ik5SR2d3Tg+pUaFM6cFVyEpEAwnL586WLwmEdjopFYNg/RbrcoSkwGv98vKg9c6NveeRt9PcwV 2dHYOCQjwoi2tiFUVXVj754GfPd7zwjLfgIGaa0hLSIhIUl4YzSU3DTKT5+SGYMrEpVQkZ4bPTV1 UrQK5pOXrQqtHFJRgoZOqeorJNGL587KZHMt6Fnl5BUgOzcPZYsUBQ0VVGZlqDqZtp2ZyczJKh8q 2quqEE+xeV24E8KSvz6RsP5EYTSgrGweYpOj0dnZgdTUNHEXOQiU/5WZbAGnis+putD8HW8W8bj4 lJ//8+OR1M3wjvmx9dihj2Ww+DmUDpZJulOgv7cnhEXMdgteuFdffxVRdjv8PiO6evtwvfHdMO4K vUKWgamKqQVzbiXOaBR1+sOG376zY0KVVIXFbENJ5nqYjBM3xRB60OnIQPOVQIOrEC2VHwd7uyUH 9HHABXNjeBjO7CxZaGwqnpuZLWzsSGDC2x2oGopC6NmzYnBKNm0K3ncM56nGkTEyFjKKXQZGJCWh u7U1LJHOPNeNykoZ5VW0dm0IaZWtOkPt7UIMnQoU4uM8QDbfM0zKzM4OkkLpGehJ0BTP46g4itup fa9MlvcNDOCG2SQbv8FhR4KmWX8yr3Y00E/IITAcLMHPIg8rKzsXA/0/xd69jWhtjUCuCbzf2Mio CO6RHDp7zjwxJvSWKKHM8JQKtfzs6Uzo0YN5KfK11PkI1IwjPSMS2E/IMFmL86dOyj3H49Crnra1 NMv6Nfsv1aDZ6IMlJhZJRTMiivY7R0eRHBsbWdD/NwxVcoa7nsNhVyQpDX6x+MrcTf7fxGsJGimZ bGzQPQeDIu8aY0BedAL6OzuDRnmykWNTDZO8lWGbeu/j8S+8iO98+6/x059MvrPy2P/qpS8if8Wy 0ObovXux6oHwaiCllS+lhU9ptjb2Ir7vOixmJXnPHdFldkm1LCZCDs5otUgoxeS0tueRkitDCTdv o6FcSsXlKqTOmSgg5C9fjtaz56DVKqDHVX21BldaW1D27LNSxavevVsW24InJvoOtaCKQu3VWhQW sSoWHTxPK1auxhtb3g4xWIwU2GzuGhmRn1ldZF6QuvlwOhEZWXU+AAAgAElEQVRjtqC9vBzDpDiU lsKRnIzdH36Aex54MCQkpEEkOZIqnyy0MFdzufKi5Fk5t69kbqikEV/PTYlcK9Vgkaf1zPMvSMuN Ly0VaZoBJry36UWO9fWJ2KAWp44exqw5c2XTo1dGXhc9owVLluFb//WbyCt4A7k6qgiXA5UWtLQS 3nP0FPWGkWO+SFJdsmJliIjfdEGKgjpx3ZmQKGqiDJH5/UOumz10qAfbd1hl3BiQS2ajN/NdDCEJ klTJNzM//sRDGOodRlN9M/Zt+xAuswlF6++WE3Xt0CF0XL0qnkcIj+fThD9gbAwGcWddbifcbo+E jooHpbyMv1dfp14UNZ+lJvHUvABDlOXLluKVt96BadMaGVzQ39+PtpaWSWVrbxeslqkXVH9T0+1O TW0WlcZJv7wOkfr7bgZ+97ae6zJtyOmaMGgdP/gJEvOzMffhh8KqYzRkNB7akIk4tHWr5FzIBVLF 25hrFG4Yx8JTO7+5CamLwifEmPLzxPPg7L3OjnZs27UDecuWiSelghQHShlP+l28XrQ1N+FqTQ0W 6NQD5hQWYcDrletMGkLltm2iJEpv8fxbb6H54EEsWLocdy9biSiNIeb3OXS1Ggm5ubjc1SGLjh6U 2tvKB+f1VZqM0qzMfzMU6unswLpN9+DtX/1S0hjaRUplhZ1b38OSVauDDefkaXG8FsOuaxUV0uKj rQTXHj6MeQ89FJJXS83IEM+FBo80B4bwzPHy2Oi15RUWBhe9Fj/67ndCDJYWPH56aWqukQ/mmG7V YMn60tyiDFNJLmWvJOWj2VqkQt847XK6ZKaiitXrN8iE8cb6+qCTwnUqZyI6IQrzls7B7Pkl6Ovp Q83VWlSePYfBjg4se/552D9DulLMUVGmQj05vHCsWHg8nBLCL6bkG1RjFcloaRPxkhw2+OCIt+Pe tWtx5Fw5/EsWSo+YtqJ1p8AdeLIJ2Zx5V3mxDv29TrS1OXHx4o3psax7b20CEc9ZumMDzIZwhYh+ p6IvNl3krVqFa+UVuF57VTSTuHBk9x4dxfHDB5CekYUbddcx5vWInE5qQE9dDcNqzp/H8Ee70FBf h4VPPRW243PxsopH707PP2M6w9fQiEcfeEimLzMvw0qtCmqdb3n3bbisFiQXFGDFiy8GjTsHoaxf uCSiVjrpHf7WG2i8dh1PPPK47PQMV5gr4jCQTQGDwLyPerxMSicE5lKySZl9fFqDxeMq0I2xY6L9 9LEjSMvMwo1jR2Sd0fvrb25GJvsYc/LQevAQMtYqrS79fb3Y9vZbQvr8yh99U+4HVtMifYdb5Q9y E+N32Ltrh2w8NNIcLzbQ1ytKEmdjTgTXE8FzQX6ddrNkmEfPTA+SXre/+zYef/Y5IbAy0U9KhgrK RDG3yfmi2vDy81/6Cra8/mshnrLqzPNlVq2XqCBYTUjPTkNaVipWu5aL13X67Fm0jowgvrREkpCT wdDfL5WT2wUnaNzs7yk/6/V4g0aHIR2Pn4NWSdyj4bJaFU+L4EXg68JVHxBitRXVAiMKZ+chMSEB +48fgqG7T4iAdxout2vShCIpEX/73W9LxzvbIa5cvobhoVHJJ735xnm0tY3IDa0t38u1u0UP604i OjER/sQkPPjIo/LvkaEhCY+Zq9u/e5cMRuCD1UC2oVzdswcz1q0Tj73r2jWMDQ/DsXo1Uo0GCW85 LEKP7AULcHnXriDnipSUkeYWxHg8uDfAaWLD78E9e/DQE8q8PeZSmAT2Rkdhpq7nTw1JTx08hCc+ /2zY7+glrt+wEft27ZTzy+KI2qpCr+bll34gQzS0VTGGPSo9gAucfXVcYPScaWjIn6KkS2P9dbnP 6X2QZ8XkPA2rmoJIKixGwT1KEYIeKg3ftaoqCescjiiUzpuHJ55VSJcM3RiOUpiv5lKlhMQskDAP 1VhXJ8aByhDK+oYw3rlWVAE9hm+UWmY4y6lTVHi4/5HHJIS/2NMlVVpLeQU2btos55dVP1YIVfny D955U+Yb8nypBovnXA8eT0KAwU7DP6N4VnDKFTea+uu1YWx4FeyJHB4eCjaCm7mouVNwEXFxq4ud ZK3sggw8O+sp9HUNorulF9X11XB73FIOjbJHieia061oMMU5YtFUeQUjY4rMRmy0UqEZHFEuRJTN ITE+q3Qerxc2qxU2i10qe26vGw6TGS1VtRKiON0K1yguOlaM1OjYiATisVFxWD1vedDSG00BD8pk hkXGBvXDZLKE5Kn8Xp9Ir/h1ZdIJA6Zw2hWBQB8cSVY8/fQjGOgZxvs7duLzX56Qr/1NgWEqyX/L 19wlI6aowPjo5x7F67/4FdqqLsHicmLY7ZLwjElpbcjwm4YSvkwYYBorQs/Aph45HxnVl3H02DGh ktBbWfjEE/IeSfn5wuSnIdGD4nn0sCo/+ECM1oz4BGzQdf/HxMQiPjFBFnBKahr2HTsiREP2EkYC jZ5L1/6igoam4uwZmYD8g+/8Xzz3la9JSKNuKk8/90WZ4aeV5KZ3ogXDNjYqs8mXi5R9hVr4/H4x QPRuiMXLwz2TK5cqpbrIFpZer1epsFKYMEA1oDTLlaoq2cTJC+P9faOlBXt37hBvnT186j1PEcyP PnwfDz7+lPybBFNSSJi4Z5/nhvsmDAYNFiH9l8uX4ejpk3gwYFBuR0Gb54ZGauubr6N9tD9I5aCn de7UCaxcuy6is8IqLFMGL/7hN4LPmXnSqcPMBBhDBTWEonfBk8NkdWJaAuKT45A9K03iUEWHxy19 TDzxXPsulxtWyV94A31TBumHokcRHR0tJ5U8F5/BKC43KxMyLCAmVpN7UhLozjEn2ttvID0tDUaz RbShmRcxwgevzw9LoElV+RvFaNHDoo6T6rKqOSrpHYtwltXvqVYODSGephX2WDtWLV6Mgzt3YPXG TcFesI8L7tCpG6fH++KuvGrd3TJFl49v/Pm3RA7XaDDINbtUdUkqTZ8+ps/TYql7cPsHSMrNDSGB Mm9Io9VRU4P0gA4UB2g2l5cjISsLq7/2Nfl3++XLyCYjPoInlpuXjwMH9sOWnYWMBfNhTEzAZFXw nupqPPG5cO+KYnMu5ziWrV4r1JmS0jlKn6WuLJ+QmCweCkOjRB3Tn83GDAdJdCSvicZK9UK04Dis n//ge1IVo8elB9cgew3pJfGzomNixDCTi8hjO8vFftddkh/TGsrXX/55WPcB73Nuyup9zEot1zKP i4qkk4GecCRWeySQaH388KGw5zkJhyH/OUMvvDMT8O3/+9dYv3StMNvnLVgU1vitonzLOzJRRxsd SUhIg6IKrakLXYwVXyhTkLiwDfD6vbAaAVuUDT2t3YiJi5GF3tvTi/j4OPlbi9ks3hkMRpgs0bC4 zGJsTFY+T0NIsTm/hJ8WswUWG8M100SYZ2BuYESed0Q70NPXh9ToKOGAeWgU7TbJO00YIsUrFE/R 5YQjJi6E78SKCw2sxcbkeuA7aTws1ZgxvOQFpffIn5mETUqLg8VUhGP79mPJ6lXiFv+mSJjVly7K DarVUJqQy1W0r2cUFOD9ndvl+1P5U88XYpOvvrlVQK8THviFOBCK8T6XhGZhfxJ4Tv87bkKR1AAI tZFVC1bJnn/hRRyvD9Vxku+Xni7eFENe8pD6Wlow9wFF/UDd8SWUq6gQz0Vt7yCDvurSRdT392HG AxOeAg0VeVpar43VQR6zxecLyVFyo2WIxQngFMFTUVBULFwixxqFl6QueKoh0NuiWigTywxB6UFc ulCF8XEfDGYb3C4/HnxodURlTm3bE0O/SAZLC60ccVRUlFB6qB5KeZmPC4bxzCOx8ng7JGEtWKii oaakN1Mb9AD5/QZLU+EtUIyoJ9omYbB2KEYkUIGirrZWro0qACgGix4PIZ4VyZlutxgom80a9Hzo aTGM6+ntQXp6uhi5oaGhgJQE80RmjIwo89FoueVDjMr7MQR0ezxwWK2w2qxwOl2yGHnzaw2I2+OF xWyUhFxMdGxgAQYSfQH6VODFwWohPV7FEHGa8QCiouOCHBLJaVmscsJMgfFFkq/ShIba5Lwwbl3K ccjOY7Ni3DGOJfPn4cqZcjhSE2RXvB3whvjwvXfgNBikl3D13euFihH5tZ0SKuglPfSgMctMSMCV mhpc2LIlbCw7jVh6d4TKotuLfltl8Nyz3079W79pHFf2TUx2UcFELMdiMQkc8rzfj+RbbJeioRk7 eADQqS+oVT82KVNhYbKJR8mzZuHSpUrctW69hBQVFy/AFB+PYt3QVlIoWBnMmj9fjDernLNnlsho LrPXJ3pVrNIRpBfQAGiNCwsHamjIYaRspSHHiIuNIVnNpUvifdVcrhKyJUOw9945iVMnO4OKA+lp Vmx6MLTq+nHR2dEhi53HdifA70djfbnyAjY/OP3+2UjwRUfBV5APS3S09KwumDNHlF770ifkuzkn cjqgLbHbbZIfVOeAisEKqahx33U7ER0VA6NRWeSqhTOZLdI5T08nPiEJzQ3s6naI3CqtCQ0QFz3z TvSCPF6fEN34oT6YZFCB1URDYIPR70F3bw/SMlnh8HFFwO0chWvcj9GxUaRnZsNgNIkyoRqymW0B 3e2A16e4qiYJFeki84bhe7D/UI6DVRybAVa7Vb4TQ8vgifX55EGjy6m7vPEYUnIwAnN69Dhj45Ph 9vgRExONohl52HvkiMT9t1I9ZOjMKbnXbrQiefFi0XHnFJbDhw9h6ZKlYf1UjPfJQF68IoIWegQ8 +tTnhb9UdakSDU0NsCQmwp6YhLi83Gkl43nNKLHCHrmpQM+k/eAhfOH5F0K/n9uNk0cP41bAzaC0 eCa2vvxjeDVqlwQnzaQkRgtZdDKQD1h5rRYd/X2wZWVh9mOPofbgQTF2vO4qmNujl9V+5iyyExPx B7/3ByGh2fb33pGcz84dH8JuMoUYK963leXn8OyXvyr3WtmiJZJzYX6Mwxw8bhfSszLFY9SytVeu Kg0arIQEB/LyZ4gHOJkHxZyfdkgFN6qaqkrExsVLqV/NWWkJuBfLz+PEsSPw+LzY8dH2kOts8xlE ieLQwf1yPuxmizgb3Lxbm1twZP9emUVIFYUzJ4+HqJByA2Sxh99xvLdHxs73DwzCFDg+enbc/FUM D4/gyJFDSv7X5xMvk+dcTzBnH6hhdChEY7+i/Byirk1M5hkfHsKYiTnBiQ3W5jVjxO/B+cpyVNdd UVgB9IBUd0uGOphNiKF1ZGgUMGKqQaNViguEfjxFrLCNu8fg9nUjwZopB0vDwbhd8lsej+SqEBcv F9bpditekcEAl9MdrOLxwYs2PDKC6OgoJCYkwmq1yPvzJGmpCSpjnVD1rLloyFpnmGQIvCdDO79R CTVJd6CWlPodtax3tWKnngO1oijvYTYjOTlZ3tvqMGPzyvXY/vZbWLt587Q4Kjyu/Xt2o210BMXr JsaVsRcOmZnYtmM71q1aHWTH87h4w6jd/NMF9YtWrF4jD5Xr9dHxIyhYo/z7ZpiMLjEd0AtuaqjH P/zv/0H3NeR3XAxtrQo1Q/XmmtXkqt8Pb0ka3DPCR813Do6hpfIicgIDF7ShLj29a4cPwx4Tg0yN kZXQ3+kMMVjMf5FDVpqeGWTU87vKZuX1iqDgtl3bUfb4Y7iyZYt4VFSWoJoAR6g/8LhScSR4X1M5 gaOptPinb/+VeN3q90tOmQjbo6LMSM9IFSPJeyESaJikEThgOHa+/x6efv4Fad25VFERQhPwU7+r sQFf/cY38cpbv8SVfCu6jMMhgznuWvcQVi5U6LjdNTVYuXS5RBzMIzFXxH5GcqxIhSCHTA9OYNZP w9nx3rsiMcQqIL8nowVZxw4HzLNLZN3zCjHg66MGvm6aNg2oYdgdNFi+5Bg4k5IRq46sv1KDdxt2 oTU1tLF/cUsK7CsXoNPMczegjPlSFz4Xp2IUjLBYTUL8Uw0FF7FqWEaGhpGY4hCLnZqWJgk7l3MI QyO9iI5JgNlsEuIdE/AMBRMTE8Uqs7rIkqi8F/yyg9FYsCJDj2Xc60FCfIISGnJX8bNcP8Gj0i4q pQVnYsABjWtfX6+Esfxcn9ejHHdgN1UJoqrRU/WeVEqE9obQ0yBY2ZSbLyYaLqsT925cj4/27EFG bi4Wr1gZDD/JOtbqQnGoBqVTCtatQ/Ek3kLO2jW40NoqicVFS5dhz/ZtWLbq5vI0NwOTmek2u1TC tA3Ek+FWeVxa8ByyinbqxHE483JC2rW4YZFtn5yfH2RsZwbOKykNV9uuhmXROAS1/fhpfDhUg8TD sShJKMT8nPmYvVxpZKZUTM6iRWGJdHqIDP8YSjK8pRQNjVj2okWo3rtPjpMektdgwDibpnOykbdh I6JSlPOTvmQJfvLjHyEjLw/JDntQOVQ/voseENMZKmgIaVwiKXs4ncDVthsYPXoIrmBFUekLo9Ry jMcr5XoaQlbtmPC/5wElfKTSKO+t999+M3gvupxOGXHHiqJnYAT2PbVwLS0UA8C5gtFuozSDqzBF RUn+mDBbzMH8GxuVeS4iGSwWEfSgI8Dhp3yooMgjEuKnVaEeHx0O0Y03tg/AXjDh2V1vvhxmrCLB F2uHeSK0UnNCinFg9Y/dLPydmsCWSSe0pixlm82wWc1w+13y++GxDjgcMTAYFKPE3coeFY2EJKsi c+z1wxiwOazojY6NScKRHh1bWhL45Y1GyUPRA5N0erA6ESqnxxBVbcORi2lUigJKHorHyV2UYaxF 5yFO5KxCjfREHk01hnqyaWxsLHp6nIiNjcLqpcsw2D+Mj7a8h0VrVsnQAFZBadS4i+0/uB+umGiU TlJSV8HFnVBQILmRurffRH5u7m1PK9GDXtrLb70exkyPhE9KhV565LhZMFmt4/AxP3Wtvjrsb0au 1uPAUAUGMIYWdx8qu5qwq+skVlw+gI1LHkAUrBGrfjyXszZuRGdtrUxoZguOOvB0zGRE3fgoku9a K5589a5dyJ8dmqy2JyXBEh2FbG4ir72GDfeGGyyK7rF3j/QMFdm5+cK5imSwMrLsyF+6OGIfJosK MxNTMDugHMFNnakAbWcFG6mZJ7svwHEjaGhOHT2Cr/3BN/De1rdx1jQMI8eUOaxITM0IOydcW0w7 cOPVTusRnXUdSKGgdlckaEX+CJkn2NcbFDKcCo0tNG4Tx+aZl4NLFSexdN29UpF3ed3TVuYLIY5q qQJKzkepvrGPRypuRhNi4mhVlV3UyXjWpIRcTLAPjnUixZwHm82BwYE+cc9t9iim7OFzO2G20pgY MDbKMqYfUbFxcLlGUNt0DsXe+bLb0IiMO8cR5feJYeLxKAx2JTSQ9/K44PGzCql4TT4YxLX2uMbE cNHOydcJRBJer3KMqpdKgzQ6Oir5N/0YKr4fP3eCWKpUFplPi4mNl/eITYpG7owc5OfnorGuFUeu XZcGWEq/DsOP4k2bbklokOX8sfh4XDx2DIVFM8MUPG8XSRrW92RgyDU+PIyjP/7x1C/kJuZ245/+ 9v9E/r3JhKVf/OItHZ9JV1w09o7gzNXjYqy0GIYT+52XcOR4De6xzBXZmEigoginNrMyWPbIIyHf UaVQWB0OeU2k76c2vycVFWFoiEJziWH6UccPHQoxWDQ4+3fvCAsVic2PLRA2/+2Cm6Te4ykoKpYE OTFrxkzEtrchLjYe20/sR++QG0drJlRSbRYL7v7mn4S9L+9nboxvvvoKlq5YKR45hRvrrl3Fkkly p/TUGEKrTgSHULAIM+FUKKCihl6td9wYXkXuLojB6R1bsey+R5CflA+MRBi4GwFCHFVpAeqXUflJ 2p/V36khEl9PtUTmtKwWG5zGMQn7vAHultYQ2B1R8LjGhSBqhRVupzNoAFm9oyHrG+iWSbc0OPSw +PfMYbFBk0lv5sV8PiXxryQZldcRTJYzATks7nqcotjApujgMZNaobjkwfKo5vjUvIaat9J6ldqL zBBWOtkdiqsdlxqDmY4CGKrJIj4MT1yM9IPdjioqk8yxeXnYf/wIFs2eE3GSSCTwWNkHRq+VAnHu Ebd4loRrfBzdx87Dkp+O+JzJS8gMG5c888xNk+6ssk3WhNxaWYlbxYg9NHdmqqhHpikBVzztYa/l K13w4IKnEU3l55GnJrqZ1ykvl/CTkjH9nPDS1hYidCja8xo4EuLldXolBzV5nb1kCbYd3C9qEgz7 VfDe1y9QgqztI/v24K5Nm9HbqxClV67KQMGqpRELHwxXKcmExKm9aUYpVHrQwmg0ShWZObG58xfK g4n46P0+2TDU5nQ2pl88eRCv794imz1llnIcE1XktPQM7G6+iMrqg0CFRyrHxr4RLFo28X23vvMW TDEx6G5qwo3WVuGWsf2KYHjJjVYvtKjv+yQZeHnGHJw5dQ7OFRqJGrMRfXNScPnIQeTMKkVaiwWd iZHzfGEGS83bEKqnpf5bpT1on1fDKjPJaAYzYkzpcFrHpdLWPdqE9NgCcT+Zq1LewyBUBovNITfP 4Ah3OCOSkYVxDEqVzj08jqHBflhsdsTFxYuLRKMwMDgAs1VJkA8M9gvdIcoRLV6Y2UyWu/JFJL/G iqSD7F5T0Jipx61N1ssJ1+S0VKgVEBomGjiF3qH8jdpczffhzsd2ARo0e6wDs8tKxEj/w7+8jYRj VYiKMiEuPQWFyxYiITtLyHc0YpMZMiaLqabJBRdbVobL165hpHwEZfNvbvx4U5/cdxjWgFRMcXYo 7cLtcaJp6PZzVLcCvYCb+hyveaTfZVoT0RgYKW8YHENdXD/c6fFYVJuPC+4mkC1GkBen3kut/n5c OX8SuQsWCh2DoRWJpmqujv2GNFa1Bw7IYqJRcrFXjl5z4Fw64cbW/a9gw6IHkVVUEkbtYCjLEV5n 3n0XtqgoZGZlBYmYqra6Fpy2HB2o9g70D8PhMOO+59cpxRUdBtvbMXSxErnZOcFwUAX5bDREzGld ulAurUzPvviVkNeMioKBMgxEZL3Hx3H2/BkMzk3HIHNpMUpVveb8SfTOS4N65Q0uIHtEx9NzWOHN DM2vVlZdwIa0zZJj7hjox7x1d8Hp9eLph0LpDszRdgT01ycDr8NAXQPu+b1vovzsUejnkhvG3Mgo KpY+zyVHc3EkqgnDNk/IEBV9vkJyWFyYqiGSNwp4VeoiV42XNhekcpxIYRj3Dwj3isMT2SbD3V6E 9ALqgUIotVhgtdkx5OyGEwPwu6LFKFCsi0zhlqE69PR0C4XfR46Vz49Rfx8ssR6M+fvkAvU7KRzo g90ehdHRcdgsVviNyq3MEjCTlIpnqHhd6jHzoeTgJvJ1ailWfY36PdXKIz0t0hvUXJd6XhTPayLh b7OSiW9E0ewZuG/dKvzFX78q4afDUQfHK+excFEWikuptWRGXGa6TH7RjpuisWK+JXfRImnyJZJm zEDX4CD279uLe+4NFbeLhJioBOQkhydQib6RTlgy7oys9FSITU3F9cOHMT40hFHLhOfEaT4dPW2K vE8AxsFx+OLsQqmw9HtkFL2hZwjtCeOiS5+WnY68hhE4DGbMNWTDCANq/Z244G8WI3agvwLxr7+O vMWLxViN9feHFBeYF2FVlhpaNFgcUMEBF9wQ5FhT0tAUfRlvtHyA5JaDiBkzwj/qwtLCldL0rmLu E0/g/IkTGPpot9xbipcHjGeG5nM6mxqxYekEOZXLyOczBD0dam9R7ZRhKe815jy1ygnsuWSv5WB/ H372/e+J98L7VR46Rn9UdAxcbjd++bMfw8KWNKsFlbZhmeNYUV+B5dzwMzPhMkyPna7HkeEmeD78 AO0D/chbGlmrbLpgeFg4s0QUZN2x4bQOg8enGCWqMzzzRXR9+FOctU00/Ed7LHAHJlKriJjq0tII tBU6tdVFtHqGBxETnyhGx2FOkF49t6sTFhv5V16hFTDp5/d7xUjytfR6xseGpLJoTbBhxN8p3hff Vxob/RZJ9jPnJPkyeyLgGobRoqgxiLdnp6HzwOGwwUv+lhhVyr0akZiYKgZUIX6GJtn5t9reL+13 VQ2zGjqqRo7PMcyMjYkmDz54DrgLssFVJABZwWUYa/Zh9YrZgRyYD8PDLnns2X1NHsSMGYlIzzyO 6BgLylbOhsVihCMxVpjYWvkehhEMEUfz/di280OsXbbytpLxLvcYGvobUZgQqo/0SYC9gXy0VFTg oqEdvng1yZ6Oib58wDDqhLmmDe75yqI3DI3D1DEAV30LfIGIoSfZhzLXLHjMftSk00T4kTyQiYeu J0rT99qyDZixYqWUy3kBGGIxDIzXeDTk/nADYLhIWsFgV1fQYKmmc8DuwgB6ADtgjjMgeagR6e3F wiNi8p5hGxf/jDVrZMISjWMkTbihpuYgsZFgKqOroRmGI0eEtc/P7a6vl9zZ+MAA6ltbUU6uVYCv xE2s6JGHcePQYTz+5NNBLXh6WrXVl2V6DX+uvlKD+Ng4maY84vHg97/2h2JIR7e/iSskUI+MK9VY ric1gauZ6Hyu9hLuWrE24uBWFWPpMTh6tgp3bX48YnGDHj37NcXADg4Ir5DnWq0O06viNCVuIPQA 2ZBt5SBXowNtbi/8GuVan8OCocE+MMtH73DM74TDaUTUuBEuix9GlweWBiWH57NbYBwcg1lbEVPJ lNr8lTaUUpQ9ud9RJnYMsQlJmkqbMjqInpfbMAKLKVYMF8h/YiuO2Q6fwQu37FGBSqTPG5zJZqEB cCkKoQazG0PeXtgNsWKorHy9zyeh2pihDza/XcJUhnBmsxIw8ACEgxPQP4rUYqAaLG3PJKF6k+q5 UL0s5WcX3G6lxcdoYDuRGS4XaRMazS3m00xGRCVZsGBeHioqI6tO1NX1yYPYu7sRixal45k/f3RS rTEyte0LFuD9PbvwyKbNwaGacgMGjOpUfV5Wix0On0FK6JN9htJF4A/L84S9jp8zndepiq7ThD/W Lv2hrjqXtGwRXqMf9dmhAQQ9r6xVK2Fy++AaHpmgF+Wc7REAABHASURBVFJLnaPiT52SBUbvisal vaYGGbNny/F0VFdj1qYJjyYhPRPm66EH6TH5cdBUg/a9zSgYisOy555HeokSLhI0huwciGSwOCuS ZEwSLy9XNWHZ8hykF+XIhGg1zNS+F1uOKCGj1f1iz+P8BQsl3FMHkbJi989/921kFxWjvbMDM+++ G/70dJTNKpbvS+VQGqwNpUvRvP0tYHAM3XV1IuPjau+GubEennVzAKtZwm7nrHRRGmWzMXNR9rZB jOSF015IldDOYOTnHN2/T67r5UuXMG/VOiy9/wm4dm5D0/7DGB7ohTU5CXFp6RjvGkBqQQnOvb8N lrhYPPiUUoh55qvfwi+3/hQ9xQmBThU/7PU9yFi9RDacs1veRrLJj5lRM5CRnQ+bw4Lizy9EXrGi 8V9+6iRylwdG1Wu9KEWiRem7k6ZitSdPo4CgVe5U/97sj5JQkDkkmLwYdHcI0z3OlCIeiTnahiFP lySs+3v7ESPGIkp2I5I6Y20JlLaU93L5RpUwzmxDcmIafHCh19cmF5ILpn+wA2nJ2TAHqoRj1Han 2dAk2PUGic/xO/H36r+1XqR6DoK9lAFD7bA7lMqp6mUKhcIkRQAxcHIe/MKiT0lPwrf/xxfx+9/6 Ado6bl7unQ6YT+FiO1F7BTO7uoRDQ1DczOBRjjnREZ4rkYUx1IlxzyjiB4Zg0OgPaTEwNISi9AxY GhQjW115CRXlLRFfS4nmKxdeCv47b0YCcheF5mFkvmLhremIGa+3ozZnDDNu2NGa4sKYLdwI540m wD87Hh6TEY1jLgxs34o1T000L9M4nH71VeQsWCCaWwxn1IQ3f3fhvffkOW483Q31kx5LbdYootps YQMQmMxuq6pCdISOAC7uztQ0UT0oyI8FTzU3YH2rlIr4jAzJsWkNViQCryiUpqUjdeUKxFPL3jOR 3+F3ohwMtbkoffOnX/5PGB0ZlfW6e8c27Eurg88I5F+6gNSZc2VjMHi8uFx7FZ0jI/BT1MBL9RR3 +MRrfqeBXpCIwBmb2Rl5iM/KQUdjHVZtfAC5s+egrf461j74GM4e3CvOQ96sUnjcXiQ8kIrO5gYU zylDe1urOBH11Rdxo7EBGW4bhk/VwWA1I94eizRTIuJG3HBEJ6H4a38i0VZKdl4w/6yCuXJVP96s hj56gqaa29IL3vkCFIH4+HjFqBk9cLrc8Lh9iDLHw2w3yRwyxtkOQwI8XkURVIxHoMpIaePR0REZ u22zWRSLazIiJjYB4+4RjHlHkBJF9rcfLvco3MZBuRDcTcjp6u3rRXpKjuSpeAw9Xd1ITEmJ+B3U tiK1R1JltquGKUQyWZeolxNksQhlQ222lvyYyQjXiBs2uxFGeh5Gn+zsbPrOyUvEf/uzp/Gtv/jp TRnkLpdv2mO7kmbORFV1NcbLz2POnLnSX7W2bOq+L3V01lLdsICpcOlsFT58L5wfFQl//P9ulOEN IeC4q/FmGFzaJPtE8tTg0nloLKb4BjEU5ZVHTqcVfbFejDgmXpfT60BCQTF8gXwGk8UDOYoB4cIl 2DRdeu+9YZOkiebKC+hNtaKn5wrg4mY2cc4dTpN4duNWX9C7u5I8gHUdHUjTCFdSxodhJ70sdS4k c3AkwNII1o+PwZGZgfVff0E2VYZFU21CzK3RG+LxqiTnru7QJPbZM6eRv/5u+TwaRSJWY0Bz770X H+3Zjeeef0G4VnzwPq9t/v+bu9bepg4z/Ng+Pr47zs25EkMSEgKlhMCg0DJ6obR07TptVadOk7Yv 0z5MlfZhv2DStC+T9g+q7UPVrmNqacto6RTWMiiQpiU0hFsIIXEc7Ni5+H739LzHx3a4FaYg7ZUs iHLxsX3Oe573eZ/3eSeR2qq9nhnnMupHJtAEF1r6+tD7yr4Kt+bJZrFwcwb5RgecyznkzUakbQbh GBcWM7DkDah3eLD7wAvSECiVjMilkpgcG8fM5EW0behBV+9GTE1cxOKtCK6On4W7oRFpmVhxonvj Jrm50xGWDhjeji70bn4c/UOaRdT/EoqOqBjaxa45enK+j1osXnQyJqMrZjnmIsSmVS76ZHFZsynO pJA35GAquSqIxaQYkEUCRsVZ0WYwkYm7QC6r9X64fp3eAUpO9F2LmYCI0ppk66wBqXQSRrsQRfI1 j5XPx6+J4Aylglz0HMlhIhG5A8ibESVVGwZ6UtYTU6G8TYc/K0WdUZMz8OcpLuSiAQpSFfn9auJh DuKMJe/eWsLm+8G/UJ5PNOXkhT7IuEssln0g4Z0e3BQTDIVw9YN/SEPg/zFYRrRSBT1fTQqxSBhh U9lCpAS4SjVlVaGEW0pVFxVozsK7pMKeMWLBk4MnoaCrfQuKzatnLostbkSv30Lr5s0y+C2JymCQ cpBLV/WOHHm1aDKG/CYNhVr+OYaCrxHtiypMJQMamrtgDK7gujuCW54cisYS+uYdiFhn4K0h4Bl8 jsvHj1fkEJwQ4CILORfy+Qrxz/KZA7/3CzYFvjl8WLqavNkx+QVu3JCFvOt8Prz/t3ckAUVOn0ai VMKGvXuxXE5a4x9/LAQ+zwelqUkslndzyzZFmlPXccmXEi5o85wLm7oHYem3IBdPorfsQ0Veb/LC KJ766c8ReHscW7fvh31bvRw3r3P/N+fh6VKx69lDWAxofcYP3/oLfH0+DO7TSuuerZrq3dvpkwdj XZ82anN7Z3vvwYcbNftO4ageeklF3ohjNBoC0ZY7kI+iwl3fOMMPqZDLQjFbkEW6LDPQflZkEkYT lhNB0UXJFCJXbRk42uCXZFVX59E4J/5CUZNVxAsLkizsdqe0a7PGGOKGBbhRLyM0WhIwwGghMU9n BxXByCwsNlWSBjuLQuIbTdJ9VC3aWFHtGE5FnqHQ/iKDdD4v1jWKifycqcJjacmLfulVi51a5TsH uqVlz6RVpLxCc/4spIClFW1MiOXuWge91bn6KppOYzkehsd5bzKenVuOfKxl7NnTjl/+6qBcTNTI cei4Vk3P2T0+9CDa+OjoWxh1V5NSXTKBLf4FoLMZpitzSKlVNMXmWrA+i4aogp2hFnS5uhCsd9zF zR6IJJZELLrlpZeE+GVMjZzF1NIs0sWsIDFcyEBN5KBcjSLf14pCd7MMWHu92+T7JacFxZ52dEdi aJu+iawFsO/ZDP/oDfSmUpW/yyBXRoKcWiO+xtYtWwT9MCkyUbIEpFBUVpItp3DpyL/uOGaTaoTZ ZpaxKWTzmDl1Bjn6xiWS6O5aJ7OMVKFzoFrf1Uh+7IvP/y0jQYnRr/HSc89j8soVSXg8J2+4lkTS w23iFET/ouMAglOz8D45CG9/vyDRxsEhxEIh2Yo0bU/C0eCWY+fvk/xPRaPiZhueuAy70YTdLx/C +ZPDCPlvAv+xwKIWEZ6v6uOSsSjmZ6bRu7UqmF2rrez3CyHdGXopxZOca6p5sRLN6OZ6wvmUFx3q Fy7LM7tqR17JaG4KSlUqoHmtZ5FOJ2AyEam5RcDmcTQhEJxCx7qOSiKg6JMSCKI7xaIgk09gOeuH 3eaC1WJDLLMs7qR6C5Q1c2DpGjqbB5ApJmCyGhAM5dBlc0r9azSZkUiuyBu4SjfGZJzLSkdSZA0i giXq4jGz+6fxUroGzFjUFjyUREtfhbA6EpMTM6fLHrTnSOUS4setvUdrn7DkvbVYMHDoEOZGRpFa iqPVs3oFfPXDVRF5yO0/3xVWm7EynE0y9srh9+7QWMl5cp8ZsxV7DpPhCWwMdmDMOou2iCo6vqxS fb9ceRXP7HlVEMhXXxxHqMOIklIR3cF1JYyhpw/esXuwsb0TIW92VTeKR2f+elpujKQeii11q75f 4uxsmwcWPsqfWq6nGTfHvkHvbRY/fD6iSD700pD/J9K6cfq0IOZitoT5sUbksve7gNkba8ac6G2d oj/s8SkYqFnEsMpGqKUFgzt3VdwVuMikvbMDwflbIgcaHTmHzVton/wz+T63aY/5ZwS58TylXi0w MYGFp1i5OKEE0yI7YIIl73hj+IRwxE+8+EM0trTj65Mn4Otsp+4GLT0D+PLYR3jmx1WJjaPOgzOf HUXHhh7YHmCiYq1CdFi1+qTKgoeyoZ3O28h0faEIk8KSUR8OpgWxAXWWVqTVDGLJMBwmTe9ExMOE wUFouiVycaaUXSjBYnTJnUA0W4W8zOHBrK3Wstisgu6WYmE41QbUq20Il2ZRKOUlaWYz2tgGGwEk 8etcDXCo9ZhcvIiFUADN3lZBfXR54HMWzVoDgaGVoprmjMdW2y0kFGbnk1oxokMKUil2tVjZo9S6 oKvlHloyZGnGMtcqr5sIgQPfLimjU6lHW7a1DQ0iHgxh/toU2uvvXOH+KKKnt+pSwTu+z9uK8Q8+ gFrD9/AC4fwcOZN77QGwZgyYsM8i6sgLX9UeVhF1FLDiyOOxYD0OPvlaRa82uHs/xkdPYa61zHVe XsCuJ+9MVgyeuZ0hYLalKGpqhiGV1Tg1ot56B0yzEeS7722qJ6+h1YPAxTnkh4mSasTFyQQS4YhU ArUzguSg6MdF7Zf/ZOg7ktXDhyZkzmrHViyKDxhXcrGTeOLcGQy98QamhocrP+/r7saRw+8J78Zy NU5L6AQbL9pijJjDIN9ze73wX7iAgqGEV157XRwZPnn7ODrWd6G3v1/2Zp749Bgcbjcab5uXJB99 N6nQowy5Deq+7jITSFQiIkp20orl8lDrhumtbZ2jMbMczFBaYEaDqw2RlVvIUTFss8uZw45gJkW0 pogCvs7WKoipfX0bsiTXOc9ndwixrUsq+LcMJQPyag7h9Bxazd1QjCryRU2PI2aA1GvYm0XjxeRk hBldHX2YmZ6SZNPU0ibeWKlEDPHoMlSr5idPfQtRINdbESkKX0UurUze03uIaIEo06SwvMuikDdK cqzFSpKQyyhLJBplQp9JihoXt9WI3/7mAP74p6OP9MPjAlUiwToXvbsKSCVMokGjFIPjObWgi5Yg azGj2DdQNd3j5/r8i4fw4WefomXnaksSCkjnJyYqti+14V0yY8WpJSed6J71ZtA/a0N9VIGa1Uak 9CCSeWxoL4ojJxE35rBt6xPSuq8N6p24xp5cj9gcjXyJ+fgCkn3NWmlIRX2hiGKTC+ZxP/Js5+uI 7R4Rb7LifOBLJCwFQfc5pYictYS8r4T+m7eE8OcyVz2IWCKXwwgH7r+Y+GGDN30ulzj1+edY19Ul jhHbduyoeKk1We2CpDp27cLRT4/hBy8cwtzNGXTv24f2GjU9LabPnhtGtNuDvK8R1y6OYfu+5zCT XkC0z4cL42PYPjiEH73+E2TSHJ/TuG36XA0M7lq1ICSViMt1ezer6kcZFbcGcTvgRYvak0XzwNIQ lzhg6flKgksEiEqEYDea4HY6xdOKpnXkiIhWOKLDk5aclMGwgAZHB5y2BgTTsbK2iq6mhCaaF7yU koJsrPK3Imb/qtEh/mt2OCWZsrvjVlqFZyOcbWhokk0hREtMOLQ5Xo4syHPXuVXMz81inW99eZhb 20fIY+AQNxc70oJDRK/mMqoUBwgp9gQF6u8Lj4d2zFaLRcpIJlRBV8WSzEMuhUI4uH8n/v7+OUxe 1wz91zJunj2rNQ78Abhd9fjeC8/CpBqQjRZQogV1iQK+PALBBMavL+DPf/g91nduwPXpa7Jq6UHn FO8WDQ0PBv+5sopbluX9jceR8ieQUHJojlrgzqmY9STgSBsRaKyS81c7U9jot+H8uhUoR97Gq7/+ XcVXiUkvfemGdKW4hfz2CE1OSrLSOaeBvd+Hd3oaI1fOIt/fJg4B6plJmcD4KvwtNp83wbRj4x3b tWuDia51yQKb4kCz2YljzddFD6Yn2duDiZU3PPKeje0urN/CG0QJLd1aUmvqdCPsj+LbE9NYnOfN NHNf1oAcIddjJZNFtPg64PC245P335G9hhwVGig7sg7t2Cn2zLFcVpT6tH45c+okMhYVV4eH8fSb b8rrZGdxaOsefPXuu4i//Lhc0RTXcjFMyerGsHUFJ4/8FQd6tmPf08/JZzd6huvNFnFpbAS9NUaF NocTnT2bYCE4WYPg2xCrYRbc92AU/gtYSoTZGJESFgAAAABJRU5ErkJggg==