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divergentdave/Demographics.ipynb

Created May 29, 2021 03:58
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ACS population demographics
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Demographics.ipynb
{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"id": "8cb81077",
"metadata": {},
"outputs": [],
"source": [
"import censusdata\n",
"import geopandas as gpd"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "ff459e5c",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Variable | Table | Label | Type \n",
"-------------------------------------------------------------------------------------------------------------------\n",
"DP05_0001E | ACS DEMOGRAPHIC AND HOUSING ES | !! !! Estimate SEX AND AGE Total population | int \n",
"DP05_0001PE | ACS DEMOGRAPHIC AND HOUSING ES | !! !! Percent SEX AND AGE Total population | int \n",
"DP05_0002E | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! Estimate SEX AND AGE Total population Male | int \n",
"DP05_0002PE | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! Percent SEX AND AGE Total population Male | float\n",
"DP05_0003E | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! Estimate SEX AND AGE Total population Female | int \n",
"DP05_0003PE | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! Percent SEX AND AGE Total population Female | float\n",
"DP05_0004E | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! Estimate SEX AND AGE Total population Sex ratio | float\n",
"DP05_0004PE | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! Percent SEX AND AGE Total population Sex ratio | int \n",
"DP05_0005E | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! Estimate SEX AND AGE Total population Under 5 y | int \n",
"DP05_0005PE | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! Percent SEX AND AGE Total population Under 5 ye | float\n",
"DP05_0006E | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! Estimate SEX AND AGE Total population 5 to 9 ye | int \n",
"DP05_0006PE | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! Percent SEX AND AGE Total population 5 to 9 yea | float\n",
"DP05_0007E | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! Estimate SEX AND AGE Total population 10 to 14 | int \n",
"DP05_0007PE | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! Percent SEX AND AGE Total population 10 to 14 y | float\n",
"DP05_0008E | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! Estimate SEX AND AGE Total population 15 to 19 | int \n",
"DP05_0008PE | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! Percent SEX AND AGE Total population 15 to 19 y | float\n",
"DP05_0009E | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! Estimate SEX AND AGE Total population 20 to 24 | int \n",
"DP05_0009PE | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! Percent SEX AND AGE Total population 20 to 24 y | float\n",
"DP05_0010E | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! Estimate SEX AND AGE Total population 25 to 34 | int \n",
"DP05_0010PE | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! Percent SEX AND AGE Total population 25 to 34 y | float\n",
"DP05_0011E | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! Estimate SEX AND AGE Total population 35 to 44 | int \n",
"DP05_0011PE | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! Percent SEX AND AGE Total population 35 to 44 y | float\n",
"DP05_0012E | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! Estimate SEX AND AGE Total population 45 to 54 | int \n",
"DP05_0012PE | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! Percent SEX AND AGE Total population 45 to 54 y | float\n",
"DP05_0013E | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! Estimate SEX AND AGE Total population 55 to 59 | int \n",
"DP05_0013PE | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! Percent SEX AND AGE Total population 55 to 59 y | float\n",
"DP05_0014E | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! Estimate SEX AND AGE Total population 60 to 64 | int \n",
"DP05_0014PE | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! Percent SEX AND AGE Total population 60 to 64 y | float\n",
"DP05_0015E | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! Estimate SEX AND AGE Total population 65 to 74 | int \n",
"DP05_0015PE | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! Percent SEX AND AGE Total population 65 to 74 y | float\n",
"DP05_0016E | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! Estimate SEX AND AGE Total population 75 to 84 | int \n",
"DP05_0016PE | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! Percent SEX AND AGE Total population 75 to 84 y | float\n",
"DP05_0017E | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! Estimate SEX AND AGE Total population 85 years | int \n",
"DP05_0017PE | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! Percent SEX AND AGE Total population 85 years a | float\n",
"DP05_0018E | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! Estimate SEX AND AGE Total population Median ag | float\n",
"DP05_0018PE | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! Percent SEX AND AGE Total population Median age | int \n",
"DP05_0019E | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! Estimate SEX AND AGE Total population Under 18 | int \n",
"DP05_0019PE | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! Percent SEX AND AGE Total population Under 18 y | float\n",
"DP05_0020E | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! Estimate SEX AND AGE Total population 16 years | int \n",
"DP05_0020PE | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! Percent SEX AND AGE Total population 16 years a | float\n",
"DP05_0021E | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! Estimate SEX AND AGE Total population 18 years | int \n",
"DP05_0021PE | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! Percent SEX AND AGE Total population 18 years a | float\n",
"DP05_0022E | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! Estimate SEX AND AGE Total population 21 years | int \n",
"DP05_0022PE | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! Percent SEX AND AGE Total population 21 years a | float\n",
"DP05_0023E | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! Estimate SEX AND AGE Total population 62 years | int \n",
"DP05_0023PE | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! Percent SEX AND AGE Total population 62 years a | float\n",
"DP05_0024E | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! Estimate SEX AND AGE Total population 65 years | int \n",
"DP05_0024PE | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! Percent SEX AND AGE Total population 65 years a | float\n",
"DP05_0025E | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! Estimate SEX AND AGE Total population 18 years | int \n",
"DP05_0025PE | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! Percent SEX AND AGE Total population 18 years a | int \n",
"DP05_0026E | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! !! Estimate SEX AND AGE Total population 18 yea | int \n",
"DP05_0026PE | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! !! Percent SEX AND AGE Total population 18 year | float\n",
"DP05_0027E | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! !! Estimate SEX AND AGE Total population 18 yea | int \n",
"DP05_0027PE | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! !! Percent SEX AND AGE Total population 18 year | float\n",
"DP05_0028E | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! !! Estimate SEX AND AGE Total population 18 yea | float\n",
"DP05_0028PE | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! !! Percent SEX AND AGE Total population 18 year | int \n",
"DP05_0029E | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! Estimate SEX AND AGE Total population 65 years | int \n",
"DP05_0029PE | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! Percent SEX AND AGE Total population 65 years a | int \n",
"DP05_0030E | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! !! Estimate SEX AND AGE Total population 65 yea | int \n",
"DP05_0030PE | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! !! Percent SEX AND AGE Total population 65 year | float\n",
"DP05_0031E | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! !! Estimate SEX AND AGE Total population 65 yea | int \n",
"DP05_0031PE | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! !! Percent SEX AND AGE Total population 65 year | float\n",
"DP05_0032E | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! !! Estimate SEX AND AGE Total population 65 yea | float\n",
"DP05_0032PE | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! !! Percent SEX AND AGE Total population 65 year | int \n",
"DP05_0033E | ACS DEMOGRAPHIC AND HOUSING ES | !! !! Estimate RACE Total population | int \n",
"DP05_0033PE | ACS DEMOGRAPHIC AND HOUSING ES | !! !! Percent RACE Total population | int \n",
"DP05_0034E | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! Estimate RACE Total population One race | int \n",
"DP05_0034PE | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! Percent RACE Total population One race | float\n",
"DP05_0035E | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! Estimate RACE Total population Two or more race | int \n",
"DP05_0035PE | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! Percent RACE Total population Two or more races | float\n",
"DP05_0036E | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! Estimate RACE Total population One race | int \n",
"DP05_0036PE | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! Percent RACE Total population One race | float\n",
"DP05_0037E | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! !! Estimate RACE Total population One race Whit | int \n",
"DP05_0037PE | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! !! Percent RACE Total population One race White | float\n",
"DP05_0038E | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! !! Estimate RACE Total population One race Blac | int \n",
"DP05_0038PE | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! !! Percent RACE Total population One race Black | float\n",
"DP05_0039E | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! !! Estimate RACE Total population One race Amer | int \n",
"DP05_0039PE | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! !! Percent RACE Total population One race Ameri | float\n",
"DP05_0040E | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! !! !! Estimate RACE Total population One race A | int \n",
"DP05_0040PE | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! !! !! Percent RACE Total population One race Am | float\n",
"DP05_0041E | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! !! !! Estimate RACE Total population One race A | int \n",
"DP05_0041PE | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! !! !! Percent RACE Total population One race Am | float\n",
"DP05_0042E | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! !! !! Estimate RACE Total population One race A | int \n",
"DP05_0042PE | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! !! !! Percent RACE Total population One race Am | float\n",
"DP05_0043E | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! !! !! Estimate RACE Total population One race A | int \n",
"DP05_0043PE | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! !! !! Percent RACE Total population One race Am | float\n",
"DP05_0044E | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! !! Estimate RACE Total population One race Asia | int \n",
"DP05_0044PE | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! !! Percent RACE Total population One race Asian | float\n",
"DP05_0045E | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! !! !! Estimate RACE Total population One race A | int \n",
"DP05_0045PE | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! !! !! Percent RACE Total population One race As | float\n",
"DP05_0046E | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! !! !! Estimate RACE Total population One race A | int \n",
"DP05_0046PE | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! !! !! Percent RACE Total population One race As | float\n",
"DP05_0047E | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! !! !! Estimate RACE Total population One race A | int \n",
"DP05_0047PE | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! !! !! Percent RACE Total population One race As | float\n",
"DP05_0048E | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! !! !! Estimate RACE Total population One race A | int \n",
"DP05_0048PE | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! !! !! Percent RACE Total population One race As | float\n",
"DP05_0049E | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! !! !! Estimate RACE Total population One race A | int \n",
"DP05_0049PE | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! !! !! Percent RACE Total population One race As | float\n",
"DP05_0050E | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! !! !! Estimate RACE Total population One race A | int \n",
"DP05_0050PE | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! !! !! Percent RACE Total population One race As | float\n",
"DP05_0051E | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! !! !! Estimate RACE Total population One race A | int \n",
"DP05_0051PE | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! !! !! Percent RACE Total population One race As | float\n",
"DP05_0052E | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! !! Estimate RACE Total population One race Nati | int \n",
"DP05_0052PE | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! !! Percent RACE Total population One race Nativ | float\n",
"DP05_0053E | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! !! !! Estimate RACE Total population One race N | int \n",
"DP05_0053PE | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! !! !! Percent RACE Total population One race Na | float\n",
"DP05_0054E | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! !! !! Estimate RACE Total population One race N | int \n",
"DP05_0054PE | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! !! !! Percent RACE Total population One race Na | float\n",
"DP05_0055E | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! !! !! Estimate RACE Total population One race N | int \n",
"DP05_0055PE | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! !! !! Percent RACE Total population One race Na | float\n",
"DP05_0056E | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! !! !! Estimate RACE Total population One race N | int \n",
"DP05_0056PE | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! !! !! Percent RACE Total population One race Na | float\n",
"DP05_0057E | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! !! Estimate RACE Total population One race Some | int \n",
"DP05_0057PE | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! !! Percent RACE Total population One race Some | float\n",
"DP05_0058E | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! Estimate RACE Total population Two or more race | int \n",
"DP05_0058PE | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! Percent RACE Total population Two or more races | float\n",
"DP05_0059E | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! !! Estimate RACE Total population Two or more r | int \n",
"DP05_0059PE | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! !! Percent RACE Total population Two or more ra | float\n",
"DP05_0060E | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! !! Estimate RACE Total population Two or more r | int \n",
"DP05_0060PE | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! !! Percent RACE Total population Two or more ra | float\n",
"DP05_0061E | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! !! Estimate RACE Total population Two or more r | int \n",
"DP05_0061PE | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! !! Percent RACE Total population Two or more ra | float\n",
"DP05_0062E | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! !! Estimate RACE Total population Two or more r | int \n",
"DP05_0062PE | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! !! Percent RACE Total population Two or more ra | float\n",
"DP05_0063E | ACS DEMOGRAPHIC AND HOUSING ES | !! !! Estimate Race alone or in combination with one or | int \n",
"DP05_0063PE | ACS DEMOGRAPHIC AND HOUSING ES | !! !! Percent Race alone or in combination with one or m | int \n",
"DP05_0064E | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! Estimate Race alone or in combination with one | int \n",
"DP05_0064PE | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! Percent Race alone or in combination with one o | float\n",
"DP05_0065E | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! Estimate Race alone or in combination with one | int \n",
"DP05_0065PE | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! Percent Race alone or in combination with one o | float\n",
"DP05_0066E | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! Estimate Race alone or in combination with one | int \n",
"DP05_0066PE | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! Percent Race alone or in combination with one o | float\n",
"DP05_0067E | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! Estimate Race alone or in combination with one | int \n",
"DP05_0067PE | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! Percent Race alone or in combination with one o | float\n",
"DP05_0068E | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! Estimate Race alone or in combination with one | int \n",
"DP05_0068PE | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! Percent Race alone or in combination with one o | float\n",
"DP05_0069E | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! Estimate Race alone or in combination with one | int \n",
"DP05_0069PE | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! Percent Race alone or in combination with one o | float\n",
"DP05_0070E | ACS DEMOGRAPHIC AND HOUSING ES | !! !! Estimate HISPANIC OR LATINO AND RACE Total populat | int \n",
"DP05_0070PE | ACS DEMOGRAPHIC AND HOUSING ES | !! !! Percent HISPANIC OR LATINO AND RACE Total populati | int \n",
"DP05_0071E | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! Estimate HISPANIC OR LATINO AND RACE Total popu | int \n",
"DP05_0071PE | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! Percent HISPANIC OR LATINO AND RACE Total popul | float\n",
"DP05_0072E | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! !! Estimate HISPANIC OR LATINO AND RACE Total p | int \n",
"DP05_0072PE | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! !! Percent HISPANIC OR LATINO AND RACE Total po | float\n",
"DP05_0073E | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! !! Estimate HISPANIC OR LATINO AND RACE Total p | int \n",
"DP05_0073PE | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! !! Percent HISPANIC OR LATINO AND RACE Total po | float\n",
"DP05_0074E | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! !! Estimate HISPANIC OR LATINO AND RACE Total p | int \n",
"DP05_0074PE | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! !! Percent HISPANIC OR LATINO AND RACE Total po | float\n",
"DP05_0075E | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! !! Estimate HISPANIC OR LATINO AND RACE Total p | int \n",
"DP05_0075PE | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! !! Percent HISPANIC OR LATINO AND RACE Total po | float\n",
"DP05_0076E | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! Estimate HISPANIC OR LATINO AND RACE Total popu | int \n",
"DP05_0076PE | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! Percent HISPANIC OR LATINO AND RACE Total popul | float\n",
"DP05_0077E | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! !! Estimate HISPANIC OR LATINO AND RACE Total p | int \n",
"DP05_0077PE | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! !! Percent HISPANIC OR LATINO AND RACE Total po | float\n",
"DP05_0078E | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! !! Estimate HISPANIC OR LATINO AND RACE Total p | int \n",
"DP05_0078PE | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! !! Percent HISPANIC OR LATINO AND RACE Total po | float\n",
"DP05_0079E | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! !! Estimate HISPANIC OR LATINO AND RACE Total p | int \n",
"DP05_0079PE | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! !! Percent HISPANIC OR LATINO AND RACE Total po | float\n",
"DP05_0080E | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! !! Estimate HISPANIC OR LATINO AND RACE Total p | int \n",
"DP05_0080PE | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! !! Percent HISPANIC OR LATINO AND RACE Total po | float\n",
"DP05_0081E | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! !! Estimate HISPANIC OR LATINO AND RACE Total p | int \n",
"DP05_0081PE | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! !! Percent HISPANIC OR LATINO AND RACE Total po | float\n",
"DP05_0082E | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! !! Estimate HISPANIC OR LATINO AND RACE Total p | int \n",
"DP05_0082PE | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! !! Percent HISPANIC OR LATINO AND RACE Total po | float\n",
"DP05_0083E | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! !! Estimate HISPANIC OR LATINO AND RACE Total p | int \n",
"DP05_0083PE | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! !! Percent HISPANIC OR LATINO AND RACE Total po | float\n",
"DP05_0084E | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! !! !! Estimate HISPANIC OR LATINO AND RACE Tota | int \n",
"DP05_0084PE | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! !! !! Percent HISPANIC OR LATINO AND RACE Total | float\n",
"DP05_0085E | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! !! !! Estimate HISPANIC OR LATINO AND RACE Tota | int \n",
"DP05_0085PE | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! !! !! Percent HISPANIC OR LATINO AND RACE Total | float\n",
"DP05_0086E | ACS DEMOGRAPHIC AND HOUSING ES | !! Estimate Total housing units | int \n",
"DP05_0086PE | ACS DEMOGRAPHIC AND HOUSING ES | !! Percent Total housing units | int \n",
"DP05_0087E | ACS DEMOGRAPHIC AND HOUSING ES | !! !! Estimate CITIZEN, VOTING AGE POPULATION Citizen, 1 | int \n",
"DP05_0087PE | ACS DEMOGRAPHIC AND HOUSING ES | !! !! Percent CITIZEN, VOTING AGE POPULATION Citizen, 18 | int \n",
"DP05_0088E | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! Estimate CITIZEN, VOTING AGE POPULATION Citizen | int \n",
"DP05_0088PE | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! Percent CITIZEN, VOTING AGE POPULATION Citizen, | float\n",
"DP05_0089E | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! Estimate CITIZEN, VOTING AGE POPULATION Citizen | int \n",
"DP05_0089PE | ACS DEMOGRAPHIC AND HOUSING ES | !! !! !! Percent CITIZEN, VOTING AGE POPULATION Citizen, | float\n",
"-------------------------------------------------------------------------------------------------------------------\n"
]
}
],
"source": [
"censusdata.printtable(censusdata.censustable(\"acs5\", 2019, \"DP05\"))"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "a0b53a63",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"{'Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053')))}"
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"censusdata.geographies(censusdata.censusgeo([(\"state\", \"27\"), (\"county\", \"053\")]), \"acs1\", 2019)"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "1538a5e5",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"{'Minneapolis city, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('county subdivision', '43000')))}"
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"censusdata.geographies(censusdata.censusgeo([(\"state\", \"27\"), (\"county\", \"053\"), (\"county subdivision\", \"43000\")]), \"acs5\", 2019)"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "a46b85e5",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"{'Census Tract 254.01, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '025401'))),\n",
" 'Census Tract 258.05, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '025805'))),\n",
" 'Census Tract 260.18, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '026018'))),\n",
" 'Census Tract 264.02, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '026402'))),\n",
" 'Census Tract 264.04, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '026404'))),\n",
" 'Census Tract 268.09, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '026809'))),\n",
" 'Census Tract 276.02, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '027602'))),\n",
" 'Census Tract 1020, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '102000'))),\n",
" 'Census Tract 1036, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '103600'))),\n",
" 'Census Tract 229.02, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '022902'))),\n",
" 'Census Tract 237, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '023700'))),\n",
" 'Census Tract 269.09, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '026909'))),\n",
" 'Census Tract 271.02, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '027102'))),\n",
" 'Census Tract 1018, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '101800'))),\n",
" 'Census Tract 1021, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '102100'))),\n",
" 'Census Tract 1023, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '102300'))),\n",
" 'Census Tract 1029, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '102900'))),\n",
" 'Census Tract 1097, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '109700'))),\n",
" 'Census Tract 1099, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '109900'))),\n",
" 'Census Tract 1031, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '103100'))),\n",
" 'Census Tract 1101, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '110100'))),\n",
" 'Census Tract 1113, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '111300'))),\n",
" 'Census Tract 269.06, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '026906'))),\n",
" 'Census Tract 270.02, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '027002'))),\n",
" 'Census Tract 273, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '027300'))),\n",
" 'Census Tract 1004, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '100400'))),\n",
" 'Census Tract 1028, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '102800'))),\n",
" 'Census Tract 1051, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '105100'))),\n",
" 'Census Tract 1055, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '105500'))),\n",
" 'Census Tract 1037, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '103700'))),\n",
" 'Census Tract 1040, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '104000'))),\n",
" 'Census Tract 1041, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '104100'))),\n",
" 'Census Tract 1049, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '104900'))),\n",
" 'Census Tract 11, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '001100'))),\n",
" 'Census Tract 24, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '002400'))),\n",
" 'Census Tract 33, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '003300'))),\n",
" 'Census Tract 240.03, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '024003'))),\n",
" 'Census Tract 248.01, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '024801'))),\n",
" 'Census Tract 259.07, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '025907'))),\n",
" 'Census Tract 262.01, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '026201'))),\n",
" 'Census Tract 262.05, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '026205'))),\n",
" 'Census Tract 263.01, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '026301'))),\n",
" 'Census Tract 263.02, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '026302'))),\n",
" 'Census Tract 265.07, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '026507'))),\n",
" 'Census Tract 265.11, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '026511'))),\n",
" 'Census Tract 267.06, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '026706'))),\n",
" 'Census Tract 267.10, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '026710'))),\n",
" 'Census Tract 268.12, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '026812'))),\n",
" 'Census Tract 272.02, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '027202'))),\n",
" 'Census Tract 275.04, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '027504'))),\n",
" 'Census Tract 277, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '027700'))),\n",
" 'Census Tract 1007, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '100700'))),\n",
" 'Census Tract 1008, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '100800'))),\n",
" 'Census Tract 238.01, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '023801'))),\n",
" 'Census Tract 106, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '010600'))),\n",
" 'Census Tract 258.01, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '025801'))),\n",
" 'Census Tract 258.03, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '025803'))),\n",
" 'Census Tract 260.05, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '026005'))),\n",
" 'Census Tract 260.06, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '026006'))),\n",
" 'Census Tract 260.07, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '026007'))),\n",
" 'Census Tract 260.14, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '026014'))),\n",
" 'Census Tract 262.02, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '026202'))),\n",
" 'Census Tract 262.06, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '026206'))),\n",
" 'Census Tract 262.08, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '026208'))),\n",
" 'Census Tract 265.08, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '026508'))),\n",
" 'Census Tract 266.10, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '026610'))),\n",
" 'Census Tract 117.03, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '011703'))),\n",
" 'Census Tract 117.04, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '011704'))),\n",
" 'Census Tract 120.03, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '012003'))),\n",
" 'Census Tract 215.03, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '021503'))),\n",
" 'Census Tract 216.02, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '021602'))),\n",
" 'Census Tract 224, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '022400'))),\n",
" 'Census Tract 227, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '022700'))),\n",
" 'Census Tract 239.03, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '023903'))),\n",
" 'Census Tract 244, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '024400'))),\n",
" 'Census Tract 249.02, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '024902'))),\n",
" 'Census Tract 249.03, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '024903'))),\n",
" 'Census Tract 252.01, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '025201'))),\n",
" 'Census Tract 253.02, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '025302'))),\n",
" 'Census Tract 222, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '022200'))),\n",
" 'Census Tract 239.02, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '023902'))),\n",
" 'Census Tract 247, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '024700'))),\n",
" 'Census Tract 256.01, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '025601'))),\n",
" 'Census Tract 256.03, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '025603'))),\n",
" 'Census Tract 260.13, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '026013'))),\n",
" 'Census Tract 59.02, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '005902'))),\n",
" 'Census Tract 81, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '008100'))),\n",
" 'Census Tract 107, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '010700'))),\n",
" 'Census Tract 203.03, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '020303'))),\n",
" 'Census Tract 204, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '020400'))),\n",
" 'Census Tract 206, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '020600'))),\n",
" 'Census Tract 207, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '020700'))),\n",
" 'Census Tract 265.14, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '026514'))),\n",
" 'Census Tract 266.09, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '026609'))),\n",
" 'Census Tract 17, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '001700'))),\n",
" 'Census Tract 59.01, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '005901'))),\n",
" 'Census Tract 78.01, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '007801'))),\n",
" 'Census Tract 82, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '008200'))),\n",
" 'Census Tract 95, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '009500'))),\n",
" 'Census Tract 96, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '009600'))),\n",
" 'Census Tract 267.02, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '026702'))),\n",
" 'Census Tract 267.16, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '026716'))),\n",
" 'Census Tract 257.01, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '025701'))),\n",
" 'Census Tract 257.02, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '025702'))),\n",
" 'Census Tract 259.03, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '025903'))),\n",
" 'Census Tract 259.05, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '025905'))),\n",
" 'Census Tract 260.15, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '026015'))),\n",
" 'Census Tract 260.16, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '026016'))),\n",
" 'Census Tract 265.09, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '026509'))),\n",
" 'Census Tract 210.01, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '021001'))),\n",
" 'Census Tract 212, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '021200'))),\n",
" 'Census Tract 214, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '021400'))),\n",
" 'Census Tract 215.01, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '021501'))),\n",
" 'Census Tract 215.05, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '021505'))),\n",
" 'Census Tract 218, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '021800'))),\n",
" 'Census Tract 228.01, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '022801'))),\n",
" 'Census Tract 232, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '023200'))),\n",
" 'Census Tract 234, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '023400'))),\n",
" 'Census Tract 251, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '025100'))),\n",
" 'Census Tract 264.03, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '026403'))),\n",
" 'Census Tract 265.10, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '026510'))),\n",
" 'Census Tract 265.12, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '026512'))),\n",
" 'Census Tract 267.07, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '026707'))),\n",
" 'Census Tract 268.10, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '026810'))),\n",
" 'Census Tract 268.16, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '026816'))),\n",
" 'Census Tract 268.18, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '026818'))),\n",
" 'Census Tract 268.20, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '026820'))),\n",
" 'Census Tract 269.07, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '026907'))),\n",
" 'Census Tract 270.01, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '027001'))),\n",
" 'Census Tract 275.03, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '027503'))),\n",
" 'Census Tract 1.01, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '000101'))),\n",
" 'Census Tract 119.98, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '011998'))),\n",
" 'Census Tract 120.01, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '012001'))),\n",
" 'Census Tract 121.02, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '012102'))),\n",
" 'Census Tract 202, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '020200'))),\n",
" 'Census Tract 203.01, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '020301'))),\n",
" 'Census Tract 215.04, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '021504'))),\n",
" 'Census Tract 221.02, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '022102'))),\n",
" 'Census Tract 1048, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '104800'))),\n",
" 'Census Tract 1087, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '108700'))),\n",
" 'Census Tract 1056, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '105600'))),\n",
" 'Census Tract 1062, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '106200'))),\n",
" 'Census Tract 1086, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '108600'))),\n",
" 'Census Tract 1093, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '109300'))),\n",
" 'Census Tract 1098, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '109800'))),\n",
" 'Census Tract 1102, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '110200'))),\n",
" 'Census Tract 1104, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '110400'))),\n",
" 'Census Tract 1108, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '110800'))),\n",
" 'Census Tract 1255, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '125500'))),\n",
" 'Census Tract 1044, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '104400'))),\n",
" 'Census Tract 1067, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '106700'))),\n",
" 'Census Tract 1069, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '106900'))),\n",
" 'Census Tract 1091, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '109100'))),\n",
" 'Census Tract 1092, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '109200'))),\n",
" 'Census Tract 1114, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '111400'))),\n",
" 'Census Tract 1226, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '122600'))),\n",
" 'Census Tract 266.05, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '026605'))),\n",
" 'Census Tract 266.06, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '026606'))),\n",
" 'Census Tract 266.11, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '026611'))),\n",
" 'Census Tract 271.01, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '027101'))),\n",
" 'Census Tract 272.01, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '027201'))),\n",
" 'Census Tract 275.01, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '027501'))),\n",
" 'Census Tract 276.01, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '027601'))),\n",
" 'Census Tract 1054, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '105400'))),\n",
" 'Census Tract 1013, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '101300'))),\n",
" 'Census Tract 1026, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '102600'))),\n",
" 'Census Tract 1070, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '107000'))),\n",
" 'Census Tract 1075, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '107500'))),\n",
" 'Census Tract 1109, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '110900'))),\n",
" 'Census Tract 1115, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '111500'))),\n",
" 'Census Tract 228.02, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '022802'))),\n",
" 'Census Tract 216.01, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '021601'))),\n",
" 'Census Tract 1030, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '103000'))),\n",
" 'Census Tract 1034, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '103400'))),\n",
" 'Census Tract 1039, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '103900'))),\n",
" 'Census Tract 1066, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '106600'))),\n",
" 'Census Tract 1080, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '108000'))),\n",
" 'Census Tract 1060, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '106000'))),\n",
" 'Census Tract 1064, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '106400'))),\n",
" 'Census Tract 1076, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '107600'))),\n",
" 'Census Tract 1090, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '109000'))),\n",
" 'Census Tract 1105, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '110500'))),\n",
" 'Census Tract 1225, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '122500'))),\n",
" 'Census Tract 1088, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '108800'))),\n",
" 'Census Tract 1089, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '108900'))),\n",
" 'Census Tract 1100, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '110000'))),\n",
" 'Census Tract 1111, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '111100'))),\n",
" 'Census Tract 219, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '021900'))),\n",
" 'Census Tract 1112, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '111200'))),\n",
" 'Census Tract 203.02, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '020302'))),\n",
" 'Census Tract 1116, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '111600'))),\n",
" 'Census Tract 32, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '003200'))),\n",
" 'Census Tract 68, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '006800'))),\n",
" 'Census Tract 84, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '008400'))),\n",
" 'Census Tract 85, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '008500'))),\n",
" 'Census Tract 110, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '011000'))),\n",
" 'Census Tract 201.02, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '020102'))),\n",
" 'Census Tract 203.04, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '020304'))),\n",
" 'Census Tract 220, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '022000'))),\n",
" 'Census Tract 231, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '023100'))),\n",
" 'Census Tract 248.02, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '024802'))),\n",
" 'Census Tract 254.03, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '025403'))),\n",
" 'Census Tract 256.05, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '025605'))),\n",
" 'Census Tract 258.02, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '025802'))),\n",
" 'Census Tract 262.07, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '026207'))),\n",
" 'Census Tract 267.13, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '026713'))),\n",
" 'Census Tract 267.11, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '026711'))),\n",
" 'Census Tract 267.12, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '026712'))),\n",
" 'Census Tract 269.10, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '026910'))),\n",
" 'Census Tract 1005, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '100500'))),\n",
" 'Census Tract 1016, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '101600'))),\n",
" 'Census Tract 1025, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '102500'))),\n",
" 'Census Tract 3, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '000300'))),\n",
" 'Census Tract 6.01, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '000601'))),\n",
" 'Census Tract 22, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '002200'))),\n",
" 'Census Tract 27, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '002700'))),\n",
" 'Census Tract 201.01, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '020101'))),\n",
" 'Census Tract 211, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '021100'))),\n",
" 'Census Tract 235.01, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '023501'))),\n",
" 'Census Tract 208.04, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '020804'))),\n",
" 'Census Tract 230, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '023000'))),\n",
" 'Census Tract 252.05, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '025205'))),\n",
" 'Census Tract 259.06, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '025906'))),\n",
" 'Census Tract 268.14, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '026814'))),\n",
" 'Census Tract 272.03, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '027203'))),\n",
" 'Census Tract 274, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '027400'))),\n",
" 'Census Tract 1012, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '101200'))),\n",
" 'Census Tract 6.03, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '000603'))),\n",
" 'Census Tract 83, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '008300'))),\n",
" 'Census Tract 249.01, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '024901'))),\n",
" 'Census Tract 267.08, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '026708'))),\n",
" 'Census Tract 268.15, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '026815'))),\n",
" 'Census Tract 1019, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '101900'))),\n",
" 'Census Tract 268.11, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '026811'))),\n",
" 'Census Tract 1057, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '105700'))),\n",
" 'Census Tract 1065, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '106500'))),\n",
" 'Census Tract 1094, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '109400'))),\n",
" 'Census Tract 1009, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '100900'))),\n",
" 'Census Tract 1074, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '107400'))),\n",
" 'Census Tract 265.05, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '026505'))),\n",
" 'Census Tract 268.19, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '026819'))),\n",
" 'Census Tract 1002, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '100200'))),\n",
" 'Census Tract 38, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '003800'))),\n",
" 'Census Tract 209.02, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '020902'))),\n",
" 'Census Tract 241, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '024100'))),\n",
" 'Census Tract 261.01, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '026101'))),\n",
" 'Census Tract 267.14, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '026714'))),\n",
" 'Census Tract 267.15, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '026715'))),\n",
" 'Census Tract 268.07, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '026807'))),\n",
" 'Census Tract 269.03, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '026903'))),\n",
" 'Census Tract 269.08, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '026908'))),\n",
" 'Census Tract 240.05, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '024005'))),\n",
" 'Census Tract 240.06, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '024006'))),\n",
" 'Census Tract 260.19, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '026019'))),\n",
" 'Census Tract 260.20, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '026020'))),\n",
" 'Census Tract 260.21, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '026021'))),\n",
" 'Census Tract 260.22, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '026022'))),\n",
" 'Census Tract 261.03, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '026103'))),\n",
" 'Census Tract 261.04, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '026104'))),\n",
" 'Census Tract 266.12, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '026612'))),\n",
" 'Census Tract 266.13, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '026613'))),\n",
" 'Census Tract 268.22, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '026822'))),\n",
" 'Census Tract 268.23, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '026823'))),\n",
" 'Census Tract 1052.01, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '105201'))),\n",
" 'Census Tract 1052.04, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '105204'))),\n",
" 'Census Tract 1256, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '125600'))),\n",
" 'Census Tract 1257, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '125700'))),\n",
" 'Census Tract 1258, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '125800'))),\n",
" 'Census Tract 1259, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '125900'))),\n",
" 'Census Tract 1260, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '126000'))),\n",
" 'Census Tract 1261, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '126100'))),\n",
" 'Census Tract 1262, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '126200'))),\n",
" 'Census Tract 9800, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '980000'))),\n",
" 'Census Tract 118, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '011800'))),\n",
" 'Census Tract 121.01, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '012101'))),\n",
" 'Census Tract 205, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '020500'))),\n",
" 'Census Tract 208.01, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '020801'))),\n",
" 'Census Tract 209.03, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '020903'))),\n",
" 'Census Tract 210.02, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '021002'))),\n",
" 'Census Tract 215.02, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '021502'))),\n",
" 'Census Tract 223.02, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '022302'))),\n",
" 'Census Tract 229.01, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '022901'))),\n",
" 'Census Tract 233, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '023300'))),\n",
" 'Census Tract 235.02, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '023502'))),\n",
" 'Census Tract 236, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '023600'))),\n",
" 'Census Tract 238.02, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '023802'))),\n",
" 'Census Tract 245, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '024500'))),\n",
" 'Census Tract 246, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '024600'))),\n",
" 'Census Tract 1.02, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '000102'))),\n",
" 'Census Tract 77, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '007700'))),\n",
" 'Census Tract 213, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '021300'))),\n",
" 'Census Tract 217, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '021700'))),\n",
" 'Census Tract 221.01, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '022101'))),\n",
" 'Census Tract 223.01, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '022301'))),\n",
" 'Census Tract 253.01, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '025301'))),\n",
" 'Census Tract 240.04, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '024004'))),\n",
" 'Census Tract 242, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '024200'))),\n",
" 'Census Tract 239.01, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '023901'))),\n",
" 'Census Tract 243, Hennepin County, Minnesota': censusgeo((('state', '27'), ('county', '053'), ('tract', '024300')))}"
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"censusdata.geographies(censusdata.censusgeo([(\"state\", \"27\"), (\"county\", \"053\"), (\"tract\", \"*\")]), \"acs5\", 2019)"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "ce071aac",
"metadata": {},
"outputs": [],
"source": [
"acs_df = censusdata.download(\"acs5\", 2019, censusdata.censusgeo([(\"state\", \"27\"), (\"county\", \"053\"), (\"tract\", \"*\")]), [\"DP05_0010PE\"], tabletype=\"profile\")"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "79f32aac",
"metadata": {},
"outputs": [],
"source": [
"# Download from https://www2.census.gov/geo/tiger/TIGER2019/TRACT/tl_2019_27_tract.zip\n",
"tiger_gdf = gpd.read_file(\"zip://tl_2019_27_tract.zip\")"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "5eb7731b",
"metadata": {},
"outputs": [],
"source": [
"tiger_gdf[\"geography\"] = tiger_gdf.apply(lambda x: censusdata.censusgeo([(\"state\", x.STATEFP), (\"county\", x.COUNTYFP), (\"tract\", x.TRACTCE)]), axis=1)"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "37e99f7b",
"metadata": {},
"outputs": [],
"source": [
"tiger_gdf = tiger_gdf.set_index(\"geography\")"
]
},
{
"cell_type": "code",
"execution_count": 10,
"id": "afb53904",
"metadata": {},
"outputs": [],
"source": [
"gdf = gpd.GeoDataFrame(acs_df.join(tiger_gdf))"
]
},
{
"cell_type": "code",
"execution_count": 11,
"id": "47b8d3a5",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<AxesSubplot:>"
]
},
"execution_count": 11,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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2JDWZoiAN9k3x7j/+PL/8k+/jL//wIcaGZzdd/mrXMKefucHNq6OEQpF1z40Nz/Inv/Wf+H0hXC4Hh090APBfnz/FUP/6nIehYIQvfvKZDffTfXGIm1fH0nxVW4vbJX1P7RCMmHzt2xfyXQwhRIHQRAf+5OuWhJcCP6mU6iM60OcB4H1AjVJquXKyAxhOtCGpyRQFZ7Bvijf94gdWZskZGZzBuxjgHz7wy3GXf/LRLv76rZ9due/2OLn3ZQdoaq1mfGSO55+8RjhsAtDcXkttfQXfe7SLf/mbh+Nub6Nm4ktn+/m/f/7l9F/YFiPN5TbR8NBXTvHfXn0HbpcccoUQhU1r/Xbg7QCxmsw3a63/p1Lqc8BPEw083wB8JdG25IgnCkooGOav3/KZ26ZhvHCqj4V5H1Vxklz390zcso0IT33nctztD/VN8ZmPPMkTj1zasAyRsEUkbOJcU5P3zS+f4Z/+MuHvaVuxLGkvt8vUjJdvPnGZn/jhE/kuihBCpOttwKeVUn8NnAU+lGgFCTJFQfnSp56l78ZE3OeG+qY5cvL2IPOHf+JOvvLp51fyVyby4X/+9qbPf/dbl3j2e1fZta+J3fuaMS2LJ75xMaltbyemBJm2+uSXn+fHHziGwyG9lIQoduYW6a2otX4CeCL2dw9wbyrrb41XKYpG7/XxDZ87fyr+dI3NbTW84x9/jhIbB1YEA2GuXhrmkS+f4dGvnltpbi8mxTKKPvuiwfrQ6BxPPHMtz2URQojckSBTFAytNTe7Nx5Uc/n84IbPHb9rJ+/4x5/NRrGKljSX22TN2/ifX3wOLcP2hShqGoWl83fLJQkyRUGwLItvfvkMA72TGy5zrWuYyCY1infdv5fyipJsFK8oWRIM2e5G3yTPno1fIy+EENuNBJki7x792jl+8cffw3v+6qubLjc3s8SXHnp2w+evdg3fNmBIpE9q3LLjP7/wXL6LIIQQOSEDf0TefflTzzI1vpDUsh9676P4FgP8j196GWXlHiDad/DyuQHe+87Ng1SRGmkuz44LV4Y5f2WIk4c78l0UIUSebJWBP5lKOshUSjmAU8Cw1vq1SqmPAq8E5mOL/JLW+twt69wB/DtQBZjAu7TWn8m82GI72X2gmRvdo0ktq7XmUx/8Hp/56FM0NFVhWZq5aW9RDszJNgky7RHvXfzEF57j5J9KkCmE2N5Sqcl8E3CFaMC47C1a689vsDyAD/hfWuvrSqk24LRS6pta67nUiyq2q/bO+pTXMSMW4yNz9hdGrJDmcpvEeRufOdPL9d4J9u9uyn15hBAiR5Kqr1VKdQCvAT6Yysa11te01tdjf48AE0BjqoUU29figp+vfeb5fBdDxCE1mdn1Tx/4DsFgON/FEELkmAYsbeTtlkvJ7u29wFuBWxPnvUspdUEp9R6llGezDSil7gXcwM04z/26UuqUUurU5OTGo4vF9jI2Msuf/c4nmJ5czHdRRByW5Mm0xUYJQy52D/OX7/265CMVQmxbCZvLlVKvBSa01qdjc1guezswRjRwfJDodEN/tcE2WoH/BN6gtb7tiKq1fjC2De655x6pPtlmBvum+PbD5xjomSQYCFNZVcrc7BIXz/RjRuQEW6hkxh97bPYufu+56/zTB77Dm3/jh1AyWbwQRUJhbnj5ub0k0yfzpcBPKqV+HCgBqpRSn9Bavz72fFAp9RHgzfFWVkpVAf8F/InWeuP8M2Lb0Vrzz+/6Gl//wul8F0WkQZrL7bL5+/iVb51nZm6J3/3lV9HWXJOTEgkhRC4kbC7XWr9da92htd4F/BzwmNb69bHaSVT08vt1wKVb11VKuYEvAR9PMEBIbENXu4YlwNzCDKM4rrSzLokZNp58/gav/72P8MGHniIg/TSFENtEJj1AP6mUughcBBqAvwZQSt2jlFoeIPQzwCuAX1JKnYvd7sikwGLr+N63uvJdBJEBh0OCzFwKhU0++rln+YXf/TDf+X63jO4XYpsqpoE/KSVj11o/ATwR+/uBDZY5Bfxa7O9PAJ/IqIRiS9Ja89yT1/JdDJEBh6M4kgVnm07QXH6rialF/vwfH+ZLj5zj93/1B9m3SxJyCCG2JjmLiKy4dHaAob6pfBdDZECCTJukWSF5rmuIX3nzx/mnD3ybhUW/vWUSQuSVGRv8k49bLslZRGTFQM9EvosgMiR9Mu2RSbO3ZWm++I1z/PzvfJgvf/OcpDsSQmwpEmSKrCgt2zRtqtgCDEMOD7awoWvl/KKf//v+b/Nrb/0E568MZb5BIYTIgZT6ZAqRrM490o9sq3NITaYtUu2TuZnrvRP89p98mh9++WF+63+9gsb6Stu2LYTIDa1Vzgfg5EtxvEqRc7v3N1PfKCfArUyay+2hs5Bv9NEnr/A/f+8jfOZrp6QJXQhRsCTIFFnhcBi86tXH810MkQFpLrdHtlIR+fwh/uUjT/D2d38Znz+UlX0IIbLD1EbebrkkZxGRNT/23+/GkBHKW5bUZNojGzWZaz19uoe3/e2XCIYiWd2PEEKkSiIAkTU7djXwi298Vb6LIdJkyFzatshFTvWzlwb5h//4liRwF0IUFAkyRVb9/K++gp/9lZfnuxgiDVKTaY9cxX2PPHGZT335hdzsTAiRNg1YqLzdckmCTJFVSil++Xd+kJ/95ZfluygiRVKTaY9sN5ev9e//+T3e96HHZDCQEKIgSAojkXVKKX75d3+Iwb4pnn68O9/FESKntJX9gG9HWy3DY3NYluZz/3WG2Xkfb//tH8XjcWV930KIVKmcD8DJl+J4lSLvlFL89h+9BqfTke+iiCRJa7k9ctFcXl9Tzq6OeirKPLhdDkYn5/n9v/gc8zIdpRAijyTIFDnT0FTF3kMt+S6GEDll5ai5vGdgiqb6Cpoaqui6OsrFqyO88e2fYnhsLif7F0KIW0mQKXJq36HWfBdBJEnJQGVb5GLE9/IeeganGRqdXXl8cGSWN779U1y5Ppr1MgghkqMBS6u83XJJgkyRUz//a6+gobkq38UQSZAY0x65qcnceB+z8z5+9x2f4elTN3NQDiGEWCVBpsipxuZq/vbf/5cEmltALkdFb2dWLkZ6J/ioAsEIf/TuL/OVb53PflmEEAmZGHm75ZKMLhc517m7kb9//y/xB7/8IeZnl/JdHLERSexti1trMpWCO5vrUR4n0ZR1CpRGo1hOYadjD2u95l9Wnr7t3xKV+MRhWZp/+I9HGRqd5Y2vfwUOmY1LCJFlEmSKvGjfWc97P/ZrvP//PsLpZ24QDpv5LpK4hSVBpj1ueR+1hpmeaaYHZmzbxaF7dye97ENfOcXQ6Bx/9qYfp6zUbVsZhBDiVnIpK/KmbUcdf/m+X+BTj76ZH/vvd+e7OOJWpgSZdoj3LtYfaLR3HyleEDz5/A1+508/zejEvK3lEEIkpsnfoJ9cD/yRmkyRd1XVZbzpT38Cy7T45lfO5rs4IsbKQRLxYhAvANRue/PFptN/9lrvBD/zmx/g5OEOXnHffl5+3z5am6ptLZcQorhJkCkKglKKN/3ZTwJIoFkgItKFwRZxaxmD9r63VpqfldZw7vIQ5y4P8c8feZy9Oxt5xX37eMV9+9m3qxElU4sKITIgQaYoGA6Hwe+/4ydxl7j42meez3dxip4VkeZyW9zyNtbXlNH/TK+tuzAj9gStN/snudk/yUc++wytTVW8/N5oDeeJQ+0yUEgIG1lF0ltRgkxRUAzD4Lff9uOgNV/77Av5Lk5R05Ip0xZrex0oBa0RB/2+kK37MCOW7T3sRycW+OzDp/nsw6epqSrlJffs5RX37uNFJ3fKnOhCiKRIkCkKjlKK//0HP8r3vtXF/Jwv38UpWpIn0y6r7+Nd7Y1c+/ZV2/dgRizI4kDxuQU/X3/sEl9/7BIlHifv/Yuf4djBtuztUIhtTGswczwAJ1+Ko75WbDmeEhd3vXhvvotR1CTItEnsbTyxpyUrASbY11yejEAwwjvf93UWFv0526cQYmuSIFMULOkDll9mLmaqKQKW1tTXlDP6ZPamdYyEcjtIa3hsjnf848NE5DsihNiEnMVFwRq2MVm1SF0kIgGELbSmNQyBxWDWdhHw29vHMxmnLvTz0c8+nfP9CrEdFEueTAkyRcEa7JvKdxGKmpXDJtjtrLK8hP7Tg1ndR9Afzur2N/KfX3iOy9dH87JvIUThkyBTFKRgIIx3Qfp85ZPkybRHLvq2hkMRjDyMIzAtzd/86yNE5IJEiKRFZ/wx8nbLJQkyRUHKR/OfWC8UjOS7CNtCrgKwUld+koX0DU7ztW9fzMu+hRCFTYJMUZCqaspo3VGX72IUNanJtEc4R31bS/IUZAJ85munZBCQEOI2EmSKgqSU4r6XH8h3MYpaOCQ1mXYIh3PzPuYzyBwaneORx7vytn8hthoTlbdbLkmQKQpWfWNlvotQ1LSlkamrMxfOUY2wO88pvz746e8TCOZnAJIQojDJjD+iYElNWp4phZZ87BnL1XtY6tdUTodxuRy4XA6cTgdOl4HD4cDhNHA4DQxDRZPDK0CpaJ1G7H/LfyulYhcXavUiI/aYLnVyfmA87v6nZrx87uEz/OL/d1+2X6oQW5qGnKcSyhcJMkVBmppY4KufeT7fxShqbo8TCfMzZ2mdkyYjrTWRsEkkbJKtvAxH79216fOf+NJz/OSPnKC6sjRLJRBCbCXSXC4Kjt8X5C9+/yHmZpbyXZSi5nQ58l2EbSFX03MWQq3zki/Exz//bL6LIYQoEFKTKQpGKBThkS+d5gv/+Qxjw7P5Lk7Rc7ocYMkI80xZlkUuwnVdCFEm8MVvnOOnX3MXrU3V+S6KEAVK5TxfZb4Ux6sUBW9qYoHfe/2D/Nu7vy4BZoFwSU2mLbSGXIygKpQgMxwxef8nn8x3MYQQBUCCTJF3wUCYt//mx+m9Hn9AgcgPp0caOuziLsn+e2nlqFk+Gd9+sptzXdmdSlOIrcxC5e2WSxJkirz70iefYaBnMt/FELdw5DklznZi5OC9NM0cBJkp7OKfPvAdmW5SiCInZxGRV4sLfj738afzXQwRhwz8sY/Tmf330rIKa8adnoEp/vWjTxDKUTJ6IUThkfYwkTdaa/7f330d70K2Eq6ITBiGXIPaJTc1mdkPMlPtWvr5r5/l1IV+3vZbP8rxQ+3ZKZQQW4zWYBZJnkw5i4i8iIRNPvb/HuOxr1/Id1HEBgxHcRwEc8Hh3CbN5WnoG5rht/7kId7zge/g84fyXRwhRA5JkCly7lrXMG96wwd46IPfy3dRxCaUIUGmXXJTk1m4/R+1hi984yy/+KaP8MK5vnwXRwiRI9JcLnLCsiwGeib54iee4ZtfOZvv4ogkSJBpn1x0PYhECqtPZjzjU4v84Ts/zxt++n5++WdeIoPLRNEqljyZEmSKrLp5dZSvffYFnv3uVWanvfkujkiB9Mm0j+HMfsAeCWe/JtOOBnmt4aOfe5azXUP88e+8mvaWGhu2KoQoRBJkiqywLIsP//O3+dzHvp/voog0SU2mfQxHdkeXa8DcYumCzl8e4pf+8GO84afv53+85i48Hle+iyRETmgUVpEM/JEgU6Ss69wATzxykXMv9DI77eVlP3iE//0HP0J5RQkQTUv0vnd+lSe/fTnPJRUZKY5jYE5kO2A3DEWBjvvZlD8Q5j8+8SRf+PpZfvuXXsUPvvQgKgezIwkhckOCTJGST33gu3zs/z227rFvfPE0Lzx1nRe/6iAOh8ET37zE3MxSnkooNqQ1SimUoaL/quiAFKUUhlIYRqyJXCkMQ+F2OaiqKsWyLCxLY5oWpmkRMS172k2LiCPLI/WdLgfhrO4huyZnvPzFPz3M1x69wFve+MN0tNbmu0hCCBtIkCmSEvCHeOhD3+PTH4o/J/HUxAJf++wLWdm3Ag7ub2YlstGxv2JzNeuVf6P/0xo0Gm1FF7R09G8dfQKtdey25u/l52ElGaBa+3eiGEGzvuYvdn9lOuk180prrbGs6D6tlZsVu2+hrfXzUK+L52LlTsby67VufX2xbWpgs6EikT0NLCzGz2GqjOiMQA6HgWEYOBwKwzAwHIqdh1romZnDYRgYhoouFwtcVwNahcfpxGlAKGyiUBgKlFYoYm+ljlOZeuv7Ge99Z+3bvcGbdevDt27n1uUUoBTKWHNfqzXfwejC2ox979ZsUmuo0lBe5ln9rsU+j9XvgbX6dyyYt2J/W6aFGYk9v7yOjj0X+9vlduJn9XuqlAIFCrXuu2vFvhNOl2PddyPpHJtZnh/99MUBfutPHuJ9f/kz7N7RkNV9CZFPuZ7eMV8kyBQrgoEQAV+I6rqKlce8i36++pnn+dInn2VhzpeXcjmcBtfOD+Rl38XM2KSJV+voaOZ4I5rnnunh0N2dnB0YS7iPijIPe3Y3crF/lPAWGB2drsOuCoYHp9NbWcG+g830Xhxe/7jDgFhXz7BpYcQJFJcvJm4VCayv9zRi+3E4DJShMFAYjtULA4xY7XZE0xZYfXy5Rnxt7bhSCofTwHAY0QsNh4rWmBtGbLnYy1quVTeiAbEVsTCc0Zr0D/zbd/iN33iAnbsb03vPhBAFQYJMAcDzj1/mvW/5NIsLPn7ql17B3qPtPP+dywyNL3Dt2kRey2Y4jE1r3ESWZHChfe3sIEdOtnF5aPM56b2+IBe6hqivKae1s5oLPaPb8rM2MwygjVz0U9SJy2mZVs66wgxeHeefP/gr1NZXJF5YiC1Egwz8EcXjhcev8Be/8sGV5tQvPPj4ynM779ydr2KtyMkJVtwug/fdsjRj3ZPUt5YyvUGT+1rTc0tMzy3R3lRFTV0ZF3vHMtp/ock0yCzGwTDjo3O84y2f5h/+3xsoKZGR50JsRZIIr8gFAyHe9/bPrOuvt9Zy/7J8knyN+ZFpXOP3h9hZXpnSOqMTC1zpHmNvQx0HOrZPU2nmQaZNBdlirl4e4d1//sWczMsuhLCfnL2L3KOfe4HpsfkNn7ey3NE/GdkemSs2kvn73n1piMaqspTX6x+eoefGBEdaG+lsrMm4HPmWaQ5LVSCDBPJxOHj6u1d58F8ezf2OhcgiSxt5uyWilCpRSj2vlDqvlOpSSv1l7PGPKqV6lVLnYrc7Em1LmsuL3ONfOb3p84UQZEpS8Dyx4W3XGnbWVjO5kN6gsWu9EygFdx5sp3dqhjlvIPNC5UGms/EUSk2mzlPuqi99+jlq68r56V94MU5ndhPbCyEIAg9orb1KKRfwlFLqG7Hn3qK1/nyyG5KazCLW2z3C5VO9my5jFUJzeaGcYYuNTW/7/PhiRutrDRe7h4ksRrh7bztu19YLMszwNumTmcfDwYf/32P8ys/8G4987SyRLTa7kRDr6OiMP/m6JSxe1PI80K7YLa1fv9RkFrG1A3w2opTC6YylHmE1Z6RhrM3Dt5q6JPoYK+lNDBVNJ6hUNC3KcuAS3V7srgGGckTXVWtPqNEE4aWlLhZGZrPwDojN2RPYDA3O0HqgntHZzILNQDDM+a4haqvL6NhTy/mekS0zEj3Tmky50IoaG5njn971NT7wL9/mjnt2sWdfM/sOtnD3fXulhlOI5DUopU6tuf+g1vrBtQsopRzAaWAf8G9a6+eUUr8JvEsp9Q7gO8Afaa2Dm+1Igswi9f1HLvCdL55KuNzopeznp9x1dAd9N8azvh+RGjsrrdqrKjIOMpfNzvuYnffR3lhFTX05F3tHC6c9eQOZBplivcUFP08+doUnH7sCQF19BT/1P17Ef/+5+/HISHQhEpnSWt+z2QJaaxO4QylVA3xJKXUMeDswBriBB4G3AX+12XakubwI9V0d5R/f/Kl8F2NV/lvkRTw2xm1zY/YEmGuNTi5wpXuU3XW1HOlsys+olCQ4DJX5d7xAYuiCaba/xcy0l4/8x+P81hs+wNIW7bcrikd0tjWVt1tKZdV6DngceLXWejTWlB4EPgLcm2h9CTKLSMAf4qF/+RZ/+N/fh9+7aQ13bhXmeavo2RmyDQ/N0FqbWjqjZA2OznLt2jj7m+rZ3VJ4c167bGjGLZTYzirwVEKD/VN85j+/n+9iCLGlKaUaYzWYKKVKgR8GupVSrbHHFPA64FKibUlzeRHQWvP9Ry7wgb/+ChPDhde3MV8jVsXm7K4Y7LCxyTye3sFpDKW4+0g753tHiBTAoDUApyPza/lCSWE0P+tNvFCeffHTz/Ga191Nc2tNvosixIYKfMafVuBjsX6ZBvBZrfXDSqnHlFKNRKuGzgFvTLQhCTK3ublpL+/+nY9x/pkb+S7KhgrlBCpuZW+QNto7jcOpMLMY/Flac75riM62WkKGZmhq4xywueJwGNvmMmpkaJaycg8+XyjfRdlQKBjhn//+67zrPb+Q76IIsSVprS8Ad8Z5/IFUtyXN5dtYKBjhL371gwUdYELhNAWK9eyOBaenvZzc0WzvRjcwMDLL1OgCd+9tJ9+5/F0OG0Y9F0iUqk3Nzt2FPxPTC8/cYHoqe7XmQojkSE3mNqW15t///AtcPdef76KILSob42gGr05QUePGG8h+TVjEtDjfNcTOtlrCThicmMv6PuNx2NBcXkiV/cYWmRzB45FR5qIwaQq+udw2UpO5TX35Q9/lkU8/m+9iJEeqMgtSNvrKehcDHGrI7eCcgZFZJobno7WaeQiQ7OiTWTBVmcDY4Ey+i5CU08/dzHcRhCh6UpO5DV27MMDH/vEbiRcsELpAU88UvSx9LJfPDbLrcBN9k3PZ2UEcZqxWs7O1FtMFAzms1fQHwxx86a7o26k1Sim01iiW3+LlFEeaNQ9GxR53mIVTHzAz5aV5Ry3jo/nv77qZLzz0LC9/4MiWqXkVxaVYajIlyNxmzjx5lb/5rY8S9Bdux/xbFWruvaKXpY9FayjxWdE/cvzZD47O4nAY3H2onXO9I1kdhLRsZsHHTJpzty+7t73FptLYo6mpquCDzO6uYT7z8af4+V96eb6LIkTRKpzLY5GxmYl5/up/f4ilRUlGLApbf98Ud+1qzcu+V2o1q6vZ0VSTlzKkrrBq+8NbZAajj77/8ZVZgYQQuSdB5jZy+XQfwUA438UQ20S26xgHr05QUeLO8l422f9ofvtqpqSwYkwGb05g5HvYfhK0hr/7yy/RdT770+MKkSyNwtL5u+WSBJnbyOBWnf9b+mQWqOwejLyLAQ7V53eGnrW1mp2FXKtZYD8R31KIjh31+S5GUkLBCH/yhw9x7cpIvosiRNGRIHMbuX5xKN9FENtILrpLXj4/yO4CCO4GR2cZj9VqOguxVrNAZi9aq6q6NN9FSJpvKchbf/vjPPvUtXwXRYiiIkHmNqG1pvtsX76LIURKtAa310QVQFXdcq1mR1UVOwsg8F2nAJum/UvBfBchJT5fiHe/44uSpF0UBAuVt1suSZC5Tdy4NMTspBw8hX1ydSga6J/mzp35GQQUz9DYHGNDc9xTSLWaBVKMtXqvj+P2bK0EJT5fiH/7x0fyXQwhioYEmdtA99l+/uktD+W7GGmTLpmFKZcfS74HAd3KtDTnuoZor6xiV3N++40CYOW7ALfTpqauviLfxUjZU49foef6Fu2/LrYHjQz8EVvDpRd6eMvP/At93aP5Lkr6CrCWRuT2YymEQUDxDI/PMTo4m/c50GXCAnt96qNP5rsIQhQFCTK3MNO0eO9bP01ki+SsE1tLrivPrlwYorOhOsd7Tcy0dHQO9Noa2vNUvkK9DjMjBVjFmoQnH7tMX89EvoshxLYnQeYWdvq7Vxjuncx3MTImtTQCwLI0FSFVsP0nBkZmmRlb5O697bkfqFSYbwlWAY56T0aJx8Un//1xOfaIvNBIc7nYAr7xqWfzXQRbqIKtpylyeTgB996c4NiOppzvN1nhiMn5riH2N9bTUpu7/ogSDNlIa1rrK3nyW5f46kPP5bs0QmxrEmRuUUM3J3juO135LobYxvIV1oRnAgVbm7msZ3Aa77SfO/e0FXxZs0ltwTPIvv0t9MUmrvjUg4/nuTSiWElNpihYWms+9/7HpHZDbEsD/dPsaanLdzESCoQiXLw8zMGWBlrrqrK6L7VFf+qtnXVU15bnuxirtCbiC63cnZ/1EQpF8lggIbY3CTK3GDNi8sF3fZVvfVaaecT2VesonHRGidzsn2JuwpvVEeiFekFpmZuXq76lmplAiB2HWzn6ot3sPdJKdW1Z3mrJjx7tYODm+gE/s1PePJVGiO1va2XSLXIzE/O86zc/yuXTffkuiq0cTrnWKUT5DGxudo9S2ujBHwznrQypWO6ruW9nIz4dZnBi3t4dFGaMiWluPrp8+SvU1ze17vHSunIaGiooK3XjcjkwVHTAl2VahIMRAr4QS94A87M+rAT7SFZnZz29l4dve3xmapHmthpb9iFEMjS5b7bOFwkyt4iey8P82S89yMzEQr6LYjujAKfME5DPxDnBYITDLW2c6R+zfdsH9jcTjDWRWlpH47fYvytx9fL9NespwON24nE6Y+taWBaY2kJbmmA4ws2xKbRS3LG/ncl5L8MJgs2GmnIqa0sxlIHDUMxOe5mcXeKOwx1YWhOdcEjhQLH3NQduW18DpkOxYIaZ8fkJRUw6JzXj3bnJOtF5sAW9pjZTo6OFUtHC+QKhuOv5/SEGB2cS78DtoKKijPJyD2VlHko8TqpL3AQXA1howmGLYDCMzxdkYSFAwB8Ctf57W1Li4sC+ZrrPDcRN9zYr00wKkTUSZG4BoUCYd//ux7dlgCkKWX6rzxbGFqNRn7I32F1YCjA8lcXfktacvzqMBvZ01FNZ7uHqwCSBOLWyTofB9dHplfsH6uvoaKmle3SSxQ0CtEQMR0m6JU+JBs5dGMz6frzeIF7v6jzpJw+3cfmF3rjLul0OKqtLqKgqxVPiIhQIMzY8y6UNlge4eXWMlzxwxPZyC7EZLTWZolB84r2PMHhTEgeL3Mp3C+3w0Cx7j7VwczyJGq8UuF0OW7e3EQX0DkUDyBK3k5N721gKhrgxtNp0bN3SJaFnbo7IdGavd3EiN30MnU6DvEwDsckXMxI2mZ3yptTP8sILvfCbNpRLCHEbCTIL3MXnbvK5/3gs38UQIi9qHPYfolzO3B/2AqEIF66PANBSX0FbUw0D47O3LRfJsP9hVZmHxcn5nHR0MBz56UutLXtnGUrUr1QIkT4JMguYZVl88G++mu9iCJE3N7vHbB8A5DLyO9BsfNrL+LQXFOzpaOCupmoWQyF8oTAR0yQcsZj1+tJKv9laXcEMuWn1yHVjX2dnPSURi8vP9ti67606a5HY2qwimYREgswC9l+feJpr5wfyXQxRrArg3BsMRjjS0s7p/lHbtmkYBXJw19AzOBX3qfrWCqbml1LeZJXhwt7OBYXh5JF2Ln//Bmht+6nZjOSl0V+IoiBBZoEaH5zhw+/+Wr6LIYpYAcSYAIzenMRT4iBoUzCgbB5IlA3ppo9yLOUusXiumsuPHm6j66nrWav3mZ6U0eUit7SmaFIYSYLCAhTwh3jXb32EgC+90aVC2KFQDg6zsz5OtDbatr2tcGhPN8hcGs1dwJSLYL29rYa+0/1Z/cxmJhdZmPNlcQ9CFC+pySwwWmve97bPcP3iUL6LIopcpQXH2+sBvdI/0OF0EDLgSu+E7amFNnPpzADH7+rg4mDm/Q1VoTSXb6Khqhynw8HEXPKjpD0uJ+PncpMfEzKbt7y01M3+znrCaEwr+v0Kh018/uiFtdNp0FBTTv+FIUKB7Cfkv3FlhLtevC/r+xGi2EiQWWC+/KHv8sRXz+S7GEIQ9IXoPh8/D+Lxu3ZycWgqp4Fm34URjhxr4fJw/H6MySr8EBN6r09S4nFyz4F2eidnmV5IXNPWWV/NnDmdcDm7OBwGpDky+8Cuhmgfy03kLlyGc8/1SJApcqpY8mQWSouYAPqvj/HBv5V+mKIwbNZi232mn+N7W3JXGCASsRjqGudQW0NG21FbIsyEQDDC+YtDVJcnl1y92uHKconWM9IcpV9bW871U332FiZD3/jiKWanZQ5zIewmQWYB+dZnn7Ntnl4hsi28EMj9PsMmo1cmONBan/N9502S3TOd4dweO9Id+NPZVEU4mLsBSslYnPfzN2/9DOFwYZVLbFfRucvzdcslCTILhNaa577dle9iCLHG5tGN35v7IBMgFIowcXWS/S116W1ga1Rkpkz7c5uKx+FM/fThdju5eS77U1Gm4+KpPv76/3yaUEgCTSHsIkFmgeh6oYfh3lz2QhJic4kGOEfC+csvGAxGmL4xzd7mNALNQsnNlKRki2vl+PNwpNFcvquznqC/cLNmPPfdq/zJb36MqfEszm0vRBGRILNAfPdrZ/NdBCFSEs5zjY/fH2auZ4ZdjTUprWfZPC1hodBmjqPnNGqES92FP9b04qk+3vjT/8pj/3VeppwUWaO1ytstlyTILACWZXHqu935LoYQ6yTK1RgqgH51Pl8Ib/88nQ3VSa8TzmMNbDr8swFeVN3IXquMfbqc+5uiA67ubGvmhL+Ew7MODs0YjJwbyWm5HGn0ydRbZHYd74Kfv//jz/N7P//vzMmAICHSJkFmAfj+Ny4wNpC71CNCJEMnmNM5aEP+QqfTwOEwMAyV9nSPS0tBAkOLdNRXJbV8cIv1uZueXWJ+3s/4xAJj4/NcujDEHRX1BCf8VNWUM9Uzw3TvLOFAbl+XkUafzDRzzOfNzatjvOVXPyTN50KkqfDbLorAQ//yaL6LIMQ6ZRUepiY2P7FmOge4UqAnfShWW16dToOdB5oxS5z0pNBHeXExQNWIYmdHNf2T85suW1HuSb/QeRK5pdn2xo1xACr3t1C3sw5La7SlsSyN1rHk+QrQ0Rpp09Joy0IDhlIopaIpTpWK3Y/O4GM4okG/M/avy+3AYRgoBaalY9kvop9WbWMFurl8Xbk2qv2OPqxx1ZTTct9ONJrYf7Fb9I6hVPS+jr4WC41lAUpj6egyJc2lLPiDGAoMZWCseU2GAkPHXhPgYPXv5ZvH5cSMmDgthYpdSKnlgiwXVq8v/Pv+7RF+43d+hI6mmlQ/OiFuoymeaSUlyMyzkf4pertz28wlxGb2HeugpNzNxdP9my7nyrB/ndbgdDow1zShWhGL3sujaODwHTuY9gWYSHJu6YUFP4EbYe4+0c6Z/hH0Bp0GrS14bN8onu8fmSU0tZiXwUwRy+KGL7Wm5PLqMm5OzmW034paB5O+9KeBbKguZ3IxxfVH53ju7z7DP7/pv3GosyntfQtRbKS5PM/OfO9qvosgxIp9x9rpvZnc1I0ut5MSjwuFZn9nPUdbajm8uzGlNlG3J36gqoDr5waZ65nmxKE2KiqSS0geCkW4fKqfA2VV7GyM30/T6wsmXb5CsdE84d6lILsP5jYp/jIzjf6VtkwQlWGbu6XTG8wzveDj1//hczx/ZSCj/QsRbWHI3y2XJMjMs1PfvZLvIggBQEmZm/7eqaRTE81NezEHZnGOL9H3Qj/Xzg9y49leDtZXUVaS3OwzLrdj0+etiMXlZ3pwLARoaUl+cM9A/zRT3VPcs7N13VF1/65GekZnkt5OoXC6NnmfynM7088yO/rkpsPKsNo2zRgTgKVAiN9935f41gtSOSBEMiTIzKOAP8TZJ6/luxhCcOjOnew73sGO3Y2UlLnJJMtPz5VRqvwmR3Y3JlzW4dw8yFy2NB+gPMWcOZal6TrVz93tzahYYFJWtvX6YwK4Nwkyr/aMs/doaw5LE2WmkzLJhlqUTGtiIplEmUT7x77jw99kcGIus4IIUQQkyMyj09/tJhTMT21AQdliI063o9nJRSJhi95rY7hcDibHNh88k8j0xAJulfjwolIYPNR/ZYxjh9uSXl4p2L27EcNh8OITuyirKeHMjeGk1y8kidIFzZuRlN5LO1hpRHt2NJdnerhIlDUhGeGIyT999rsZb0cULwuVt1suycCfPJKm8mVbcCTGNjM+NMP40AzH7tsDRGsBw6EIsxnkCJwamOF4+60z8qz9rDUz00spbXPg0ggNzRVMTW1cLqfT4MiBVsZvTDJwZpCaxgrqOms50F7P6Z6tOcguUQA5Mj7Pybt2cOVU7voLJsqjGncdG/ab6dEiHDFpqatkbCa5AWUb+d75Hp6/MsC9hzszLJEQ21fSQaZSygGcAoa11q9VSn0UeCWwXOXxS1rrc3HWewS4H3hKa/3ajEu8jQxcH893EYRY59JzPSt/7z7WnlGQOT48y/jw7KbL7DnWzvho8rWmvoUAkZDJoYPNeCpL8AXCuF0OnIYCS2NGLCYHZrj8/ZtANCCZn/QyP+llDzs41NFI99DWm741mXRR/VMLeEpcOesraUeNYHo7zmy/wbBJW31VxkEmwIIvkPE2RPGJpukqjsqVVGoy3wRcAdZmPH6L1vrzCdb7B6AM+I0Uy7btyVzloqDlIIZIJ14IBcLcOD+U8nrOcjdGwKKjoZqhqcy6A+TaRqPL15qb93HnHR10PdubgxJFa7vz0Qphx9cynVrYeGorymzZjhDbVVJ9MpVSHcBrgA+mugOt9XeAzC8Zt5lQMMK8TFcmCtSx+/Zk3C8zGbkcoRxwwvWBSUxvmOry5FIibTWXesaob05u5qNM6Tx1pnYamQ8l8NvUF76uqtSW7QixXSX7a30v8Fbg1mF571JKXVBKvUcptTWHbeZJWAb8iAI22j9FTX1F1veTyyCzzIiO0A6FIjSVlOJOY1rEfEm2aTocNqnbWZvl0kRlOEg7benMmb5WfXUZ3YP2tCLVVkpNpkiHwtL5u+VSwl+rUuq1wITW+vQtT70dOAS8CKgD3pZuIZRSv66UOqWUOjU5WRxNyN55f76LIMSGpscWcGY5CHO5HczOpDbwJxPXnrhBea8Xx/U5hkZmOdyaWuL4fLJS6P/YdX2UHXsTp4/K3NasybSrqdxhKKrKtmeNuBB2SebX+lLgJ5VSfcCngQeUUp/QWo/qqCDwEeDedAuhtX5Qa32P1vqexsZcHBzzZ3J0jjNPXuWLH3oi30URYlPZjr/2H+vANHNXHWZFLNCakD/MnvZ6Ll8d5e69HTnbfyYikdTeJ6vcmfUQ0Exn4I8NhXJkmKppYcmeGZ9qKkqTGpAlRDzFMuNPwoE/Wuu3E621RCn1KuDNWuvXK6VatdajKtoj/XXApSyWc9t48J1f5qmvn893MYRILIsHo9bOOvp6p7K3g03s/qH9DE5G+5teuDTI4YMtXBlMbirNfLFSzI7fOzjNsTt2cO3cYJZKlObochtiskxrMtPJ7xmPNJULkVgmv9ZPKqUuAheBBuCvAZRS9yilVgYIKaWeBD4H/KBSakgp9aOZFHir672yNfP0ieKTjYEdbZ31HH/RbqZmfSzZVKOUqlmvn/nF1e4qM+OLlG4wh3qhSKeJd2LJh5Fh/8XNpBr42sUomCBTBv0IkUhKR1at9RPAE7G/H9hgmVPAr625//L0i7f9tOyol9RFoqiUV5aw+1ArA/3TDI/NM5yDUeubCV2ZZk99Od56FxPTXmbmljhxrKOgE7WnExZNTC1y8s4dXDnVb3t5INbsprU90/ikwJHh/rRNmZfqpCZTZKBY8mRuneGV28SRe3bnuwhCJMeGCp/q2nJKa8q4eH6Q+Tlf5hu0QW1bFe6d1cwvribSvtQ1TGdjdR5Ltbl0T0eD0wtU1ZVSWVtKRU0pZdWllFWWUFLhwV3mwuVx4nQ5UI7o7O6pfuSlJe40S5a+TJvLFfbExbWSvkiIhAq7jWgbOnz3rnwXoQBtjRG+xSaZBOCJtOysp/tyYdUQVrRUcaZ/bN1jltZUuzx5qZlLRrq/kJm5JY6c7ODMwOiaR1XstnmwZii10mVCoWhtqmZwKZry2OkwaK2pwNezCCn1esj8t957eZxjOxuIlCq6x9Lr12soAzPDHEySiF2kKzoAp/COM9kgNZk51rGnKd9FKDh2BDPCfirDo0NZuYerBdYHWQM+FT+46L4+yj372nNboGRlEJtNjy6g0tiApfXKaFRLayKWiWlZmJZFMByhb3Iu5a3a0R3SsjQ3eyfxT6SfBs7hyPyYI4nYhUhMgswcq6yRq99bSYhZmDIdYFHTUFFwaSgPvnQ33X0bjCRXCiOk6Wwo3GbzdIxPLHB8R0vG24k3zieV/J1283hcaa9rx6xBNVKTKURCEmTmWEmpG6fbke9iFJQCi0NEjMowB2BaKW6yzEhiFPnS6BInOlsKLFF7ZmUJzAQyfj06TpS551hL3n6/kYiZ9rqZzhoEUpMpMlMsM/5In8wcCwUjRELpHxy3I2ktL0yZfiz5rOXKxNJSkGsXhtnbVktdUwVByyJsmoQti6VAiMl5L5Gcv7bMPo2BoRkOHWmmezT93KTxUv+8MDjC3fftoPv5waTiYDvj9kyCTDtqMqVPphCJSZCZYy88fjnfRSg8EmUWpgw/FiuHs/kkK+LbfK70tbPYDI/MMjwye9sybkOxo6mK2tpyHB4HvkiEsQUv0wvZHD2feXTmCma2DdOMv/7p/hGO39PG4PlxwgkuoO3MvToz50NVa3QaX1Q7ZupprCnPeBtCbHcSZObI7OQin3/wMb760SfzXZSCIyHm9pTLKSOTdf3ZPo7+4D66esfjPh9OonbMsjSjY/OMrsn3uftoC8FwhNaGKsrLPFiWZmrWy8jUgi3ltmNw3PWbE+w60EDf5O2BczI2Swh/cXCcnQdrYCLE1PjiJttIa9dxmaZFY2UlE4tLKa+baXN5S10lZXlI3yS2j4LqjZNFEmTmwKXnb/KXv/YhvAvpj4YUYqspxJpMBfQ9dpPj9+zAW2LQOzy97vlAKJLWdg2l8PpDXB9c3xxdU1lKZ0stEdPixuAkoXB6Tbx2ZWCoc7jpS3PdRN0f+ifnqCh1s+9oCze6xuIvZPOZta68NK0gM9Pmco9bTp1CJEN+KVl2+XQv//jmhyTA3IxUZRamDOOBSKTwgkwAtKbnhQH2/vD+257yB0K27mpu0c9cbArLEreTY3tb0WiuD6QWcNoVZHZfHaWps5KJ+dQDs9JSN7P+zd+ffa0NOJTixH070WEr+hXSQLVBSGm0Vhyp2cHypDuaaF5SvaYhXa0cEFYfWdvQrpRaqVVVJQbHm9rXLLXm3zXfX7X2IKPB4TRoaqlct/149LptrG4/7E/vYkSIZcWSJ1OCzCxaWgzwrt/8KDMT9jSZbVdKosyClOno8kIX73vnTRBEbbytxAKhCJduRpOie9xOju5tQSnF9f4JggkCTjv6EEK0NnJnVXVaQWZrazUjPd5Nl/F7g9wcuH1w0b7OBs5bU2n1n7xVe00Vw3OxY+rmxcmaH+3Yk58dC7HFSAqjLHroX74lAWZSiqRzyhbjyLBJ0Y40MdnkIDo14NqmT+9SIL2ALsWaxmAoQtfNMS7dGEUDR/a0cHxfK6UbpFiy8728cX2M0iw192703t0YmOLFdR227KOmrMSW7WTC2t7XX0LYprDPAltY99l+vvTBJ/JdjC1BZvwpTEaGs6LEXV9rdu1t5OiJDg4casVTEk2oXVrmprG5CncSeSztcvXRa4TOTXCgo2H1QaWoKE89iMnknQqFTS73jHHxxigR0+LY3hb272hYt0ymn8Vafn+Yo62pzzyWTAk2S+DfdWmYA9V1Ke/3VmWu9JOw26UQc8CKrUOj0Dp/t1yS5vIsCPiC/N//88ktmydQCLA5+NeaA4db8S8E6L+yOo+22+OkuaGCydF5AnPRFEBlZW4aWqopqyjB5XHS3zfFwry9fZo1UFZZQvuxFi71r58BqKW5ioXF1PZn2PRehSMWl25GB83sbK2lqryErpujtl+IjQ/NEe0Jmfx2w8EI9ZVlTC9unKpps/fBtDThkSCVNW4Ww2l2S1DQMzWT1rp2mp/1o7WWC2QhEpAgcw3vvJ9LL9zk2Iv2UlGd/mwO3/7CKYZ7Jm0smRC5l+n5MxI2OXSkDZfLwcLsEtcvDN22TCgYYWJkbt1jfl+IwTW/n5q6cppbqhlfkzIoXRW1ZdTe0cq1gUl8WjM1Pn3bMiWlqdeUZSPW6B+NphpqqCnHaXPXg8mpRY4ea+XS8AZTbMZx+foYTqfBXftbCVgWIzPzzC0F1i2TqIfF5KyXQ3XNnNLjab1pDmWwu6GO6aXhlNe1y76aOrq6xxianGdHU03eyiG2tkKuglJKlQDfAzxE48TPa63/XCm1G/g0UA+cBn5Ra73pFaM0lxPN//aVj3yPX3jRO/jLX/sQn3//Yxlt7/nHumwqmRBb1+K8n6vnBrj0Qi8DN5IPZm41N7NE2BekobEy8cKbqGmppPRoI939E3Fnr1mWzsE/m4PXpuaWMLOQVE/5Ux/9H4lYXLwywvWrY3gn/ZzYuX5O9GRq9rpvjvOS+vaU9w0QsSyujE5wz852DjY3JF7BZgZQ6o2+xq7eDdI0CbH1BYEHtNYngTuAVyul7gf+DniP1nofMAv8aqINSZAJ9Fwe4T/+8kuEYznyzj9zPe1tPfq553nh8St2Fa04SItTgSqcD2Z2youKmNTWpz/LSs3RZvpGEje1mgXYzSUbzbI3esapq0i/xUZxe/N4shkJLl0c4UhNekHiUijMqf5hro5PcdfONjxOR1rbScd9tW3cHIrWfl/ui5/QX4itTkct525wxW4aeAD4fOzxjwGvS7QtaS4HduxrpqqunIWZaFqP7rP9fP1TT/OjP3v/hqM652e8fO/hcwDsOdLG9Ng83/zMc5x58mquir2NFE4wI9YqrGBranyBxpZqauvKmZ1JPgVP+8FmXGWupAO1cJoJ07MpG83xWsOe+lpmvBn0d701yExyNUtrFvq91DWVMBMMJF5hA2f6R7irs40zAyNpbyNZdSUlXOxe7U98uV+CTJEmXfh5MpVSDqJN4vuAfwNuAnNa6+UksUNAwiYJCTKJDj74jT97Hf/wB59ceexf/vhz/PtffJHdB1t52Y+d5ORL9rP7cDtOl8EXHnycT77vWwTTzKknhEjP5Ng8Ta3VdO6sZ6D/9v6UcbWW0zUwCfPJ9ekMhtNJtJ3dgDxbOUvHBmZxKNhgWvKEbi2WSiHt1dyin0NNzcxof0ZR9EIg/SA1FbsqaujWq03kZZ78j3IXIk0NSqlTa+4/qLV+cO0CWmsTuEMpVQN8CTiUzo4kyIx54L/dw/WLg3z5w99beSwSMrl+cYjrF6MDFhxOA3eJC783mK9ibkuqwGrMRGGbGJ0H5tm5t4mSyhKudg1vGqSkGr/YPeuPHTbrQ5qJqRkvx0+0c24wvf6Ft/ZFTfW97r45zv0n23l2Ov2ayImF1BPLp6NEr2+W72yuzcl+xTaV39PelNb6nmQW1FrPKaUeB14M1CilnLHazA4g4Qg8CTLX+LU/+Sn6r41x9qlrcZ83I5YEmFmQpfOnyFhhN+cM3IwOJjpyZydXu8cwN5grPdVBOUsF2EJhZvGMtDi1xOF9zTgMA8MwMGITKIZCJpMzi0zObRzEqVuKlU4pr18ep2NPJUNLi2msDQuBIHXlpcwsZXfqXuuW6t7O5pqs7k+IfFFKNQLhWIBZCvww0UE/jwM/TXSE+RuAryTalgSZa/zFr3yA80+nP+hHCJF7V84OsHNfE3OLAeZm4+RwTDFW9voCBTciMhTJXj/R4ZE5djWUcn48fm1mbV0p7XXVeJwOvEtBBsZmV+Zd17dcIZo69RHrwXCEVq+TMUMRSfOKc09DHTNZTmt0a5cFqckU21gr8LFYv0wD+KzW+mGl1GXg00qpvwbOAh9KtCEJMteorC2XBOp5IO94odo6n0z/jQkqq0s5fnIHEE0c7nQ5GJ9YSLk+VqMoL3Oz5Euh1SLLSblDG9TS2sW5tHEQO+sNMOtd7ffoMBRtbbXUlHlwGAZ3713t+1/hcXPHwXa0jgagWmssS2Mt/2tpLG1hmhrLsqLLER1s9fIdO+j1zaO1JmCaeMMhlsKhpN7bswMj3LGjlXODowmXTZfpuKUmU3JkigwU8sAfrfUF4M44j/cA96ayLQkyY7pO9TDUk34uP5GBrRPLFJWt9rEszvu59ELvusfKyj00WKlPoVhR7kkpyMz26SK9wUjJu3Fzgl2H6+mbSTw4ytSawak5BuM8d6CjgWtDU2mVYXBmnkMtjVwfiCbiN4BGt5Om+kqqa0sJu+Hm0mzc0eim1pwbHOWene2c6s9OjeZ8ZPX74HY6aK7LLG+rEMWg0FqF8iIYCPEPv/9J3veVP+DOlx3Id3GK0FYLZ8RW4VsKcuOx69zZ0pBS59+SksIaORwIZTfIBGgyUp+z/VYZBcNKMR8K4ljTLB0IRRgYneXi5RG6z40QueHnDup5SW0bR2sab/tMT/UPc8/O9BK9J3J9dpraymhe0R3NNThSGEkvxK2itf35ueWS/EoAl9vJm//pF1BKccdLJcjMvcJtNihq2yT2j0RMrj9xnTtKKthbX53UUdbtTi3BdzZn/AHw5mDEe3f3KPXl6SdnB/AHMwuGR2cXObynZcPntYabA1NcPD/MwIUJ9vkqeUltGzXu1QD5VP8wd3W2ZVSOeCygc0cdALta6mzfvhDbkTSXA4889Cxf/9TT7DncLk3mebFNohlR0G6cj6YiO3awhR63iW+z2sEUv5LZvkwKhEK4s7wP07Q4XFnDdAajtJdsCIbng8l3UxifXmR8ehGnw+D+vS14S00uzUxwbnCUEqeDgM0Dpq76pikrcbFLBv0IkZSiDjK11nzs/36dz/zbtwG42ZXd0YkivmxMmSdEPG6PE1eZC58vsOmAEn8gnNJ2s/0N1ig8HifBDGsKE7nRPUZls5vFYHrBoh1BZt/ELAc66lemb0xGxLTouhYd9LOvvpLOQw08NtiXcVluNRMIcHJvEwd2pd7PV4hlmsIe+GOnom4u/9x/PLYSYIo8kiBT5Eh9cxVn/d5Nv3MOBZPT6eVszKbSHPQTDQTDHK2vz2gb5SWZ17l6ytJ/rVNzS1yZnsy4DBu54Z3jxUd2Zm37QmwnRR1kHjzZyX0/dJTGtpp8F6WoSYgpcmVu2sux5s370+1oq0u9xjAHPT7KSrPdYB7Vc3WCcnf6QZ4dQWZX/zgNNeVprXvkUCujvuzNAvRTdxym3JObz0JsUxrQKn+3HCrq5vKTL9nPyZfsJ+AL8ms/8LdMjyc3t7Gwl1RkilzxL4WwRr3c21C3cnVjBiNcDfnxhqJN5LUVpXHT8+SbO4PALxVLviDHDu7guZH0ck6W2DCntwV0tNYytclsQ/F43E6uhmYSLre/oR7XQBilWMnfqS2NMhTKUBhKoRQYDgNlKBxOA2eJA4fLwc/eeSzNVyVE8SnqIHNZwB8mnIMUIWIjEmWK3Bm4Ng7Xxtc9tudoG10qgqk1vqXCm1YSwOPJ3eF6pG8GhwfMNGpoS1ypjczfyNWRSTwuZ0ppkQ4ebOH784n71vfOzNIya+BbTO2zbmmsYn9bY0rrCFHMirq53DQtLj1/k7f93L+yMJu95hWRiIwuF/nV0zXCEVVCU1UZ/QPJDzhZFia7M/IAOFNMq5SJmdklTrQ0p7Wuy2lPOb2BEIf2JD/AprzUzQVfcn0xI5ZFSVnqTd4vuWuPDFQUtiiWPJlFW5M5NjjNm37qPSzMSHCZb7n+0oskFdnn0nt5hAN37OByGjHEnP/2WWjsZhi5DW4C0/7ojzPFoMrpsC8YHl9M/vi850ATT88mlyGkxOlketybchvKS+/ek+IaQhS3og0yn/tOlwSYCRgOAyPWH8nhdOBwGBhG9DHlUNH7ax4zHAZKKQyHwjCM1b5NRjRVdSRi4nI7cayp6VCGoryylN0HmolETCzTwrI0pmlhmdG5j82IRTTiUaCI9p1Sq+VyOqP7MxwGzliZlvcZDWD1yhzJlmmhAadjfSW+RoNW686nGr1hkm21sgzrWvuVWr9GtBwq9ne0PCuxwvKysZ2urrcc3alYqov10d5yGVceXg4EtF6NC/X6La08t/Lv6mtcnmcaK/qvFZtz2lPqpHVHLaFghJnJRdp21FFa5l7Z7+pub98vsXIv1/oYhoq+NyqWsir2r1r5V628sUopVOzjdridRAxjkx4Vmluf1Dr6zt0aI6vl4t1a3jXvSWVjBW1zTioqS5hZ8DEa66e9f3cTpSUuQhFzdZex9RRQVVtO6dqBOXp1sbU1X/HitbVxnLHmO6GW14997yvdbo4fbIttO9aPMPY+L88PvvKesqZf4fJ3cPm9X1NuHftj+XdiuhURz2ohX+ysJLjSlUite91r31m15jtbqZzc3d5yy8ezuow2FH6nxuGIlhGi/SL7RmdYjE3lqYEDOxooLXHjtgwGxmZvf+PWKPG4OLMwtukya3XWVDNFaiPQK8o83HVsR0rrCFHsijbI9C3Gr3lYDpaM5Q7gy0GVsfqYI/a84TRwxIKb5XVW1zXWn1hX/o4d7Fn/78qBf22wsPZkpmOnTc3qv2sCqOV1IuHVQE3r6HOWZa10bNexTu6WaWHp2L9mNKgzTTMa3EWs6HJaYZnRHHQEs9ccePiuTnovFeJQi+JWUVXGWG90Huq6xkrCgTAjPdlLDRPP4Xt2cbE3vbmw09GmmhgciQY0Gtizu4GKqlK8834uXU0+iMmGO4520H1uIKv72PeqXbwwu/o672tppfucvfmDd3TUccVaiPuc02OsXDJcHY1+7vfsaEsYZNZVlzFpxt9mPPWWh1S/VXcf78TtKtpTprBbkbQUFe0vJhwycZd6MK1YjZlpgVJYgGUS6/GuIQd9rQpSDvsdaatIfm1b2MxkfvJGqhzOD11ZVcLA8My6muW+HAa4ieSmW8n6nfQsLWA4DCzTvuPgrTXza0Xi7SeJbgIOR/Lfkx011dx8YSTp5Ze1N1envI4Qxa5oB/5U1pYTCkYww9FaO8mjkz/SJ1NsJJc/y46dDQV9HMhJ0W7ZyeTiEvvvbLV1F5sFmfGYOnGA60iyv2qJ00n1hCISTj1obmuSIFPYRUVbJ/N0y6Wirck8+eJ9+S6CiEn1pCNyo3DDrSxxF/Y1tx2/E4fLQBnGSiypVLTbD4AViR94jepAnJ6v6dMpbixkJp5/PJlBUeVuF0eNWvqHJpLf+RotEmQKkbKiDTJ3H2qlqb2WieHN+/qI7JPm8gJVZFHm8EShT8aQ+QdS9opmeqY2OuY5aCy5/dHBmXnuOtHCzQs29UlNMcgMJ9FUbxjGpn3cmqoq2F1fwzPDQ7zk7lauPZN6P9O2pqqU1xGi2BX2pXsWKaVw2pTPTWRGajLFRnL11Whpq2FmzpebneVRorfz3Ej8QNJbZt8HkervfXx+karyEjybDLrZrCZzT1MdQcPkmeGh6P7TvKhtaZAgU9hI5/GWQ0UZZF549gaf/Y/HGOkvnE79xcySmkyxgVx1kWxoKfymUJXrs8Ma18an6TzQYMu2rBSDzHl/kGmC+D0mRw610lRXcdsyaoMg89iOZga988z6/CuPpRNk1teU47Fhukwhik1RNpfPTnn5yN9/Pd/FEDHaKtIR/CKhXNVk+s3Cn1bWjrcik1YD3eiBa3YUIr3VTA3nB8dAaxpbK6I1JCqaa9Nd64Y1XS01cM+eNk4Njdy2O524i+dtWhqlFlPYSJPzATj5UpRBZiScxlFGZI20losN5eA4bDgUfUMz2d9RhjwlbnbsrGd6yktJqYv6hkpKSl3RJOwopicXGBme2/Qtqx43eXFzC89Mj/Hy8hbCbs2zs+ObrLHq0sg4BzqqGR/KrO/q3LyP+w+18OxUmn08lWJyYf1EGrXN5Wuf5q7dbbwwFD9N0Xmmcb2oZE3CeoWhWPl7+fHVxPgwU7p+cgEhRHIkyBRCFLXWtlr65/KTBzQV/nCYvtHooJ3FcJjJhdv7kNY2V7KjrRbvnI+B/unbmoZHuibZ4YjOoBT2h3G4UmsCrtpdlXGQGQxFmJ5YtLWz1nLwV+p2sru1nlMbBJgAgUiEQIoV10PzC1ybmOZgsz1dBoQoFkUZZErVmRBiWVVtGWyBIDMZs7NLzM5Ga/lcpU52tNVSVVFC96Wh23JDLgegeyqrCVkWQ0uJ34MLYxM01ZSyOOdPuOxmKtsqYMy+aX0V0FpTieE2uDSaXM1sqr7VfV2CTGGfIglDinLgjxAisWLpKutwbc8sE+GwSW//FOe7hqhtruLg0baV81pzaRlTY4uEZ0O0myXsdEabm19e3rLpNkMRk/ZjjRmX7cr0dMbbWMvhNJg3gwzOZS8N1beuXM/atoXYroqzJlMUFunmVKCK5FJ7i3z/VAYFHZtYYGxigbbOOmpKSim1PEwYczhq3cwTptlTzg+U7WDq2gyvONbJkmN9lyKl1jQAGQaeUidBf3qDpSrKPYyF7R1oZRoabzBk6zZvdW1ymp6pGfY01GV1P6JYbJEDT4YkyBR5Vxw/ta2nIAY55CDO3Sq9Z7QNb8bI2BwjY3MA1NaWcW5xCr8Z4Yc7Kgj4QlTtqGR0ZoEbC3Obbufek210PzuQVhkaGysZC22+/VTl6rv6re4bvPFl9+ZkX0JsB9JcLgpAAQQz4jbFkr801byN28XsrA+XI3oK8CmTZ6fHeHp2LGGACdCzNIfhSO/04dzC3ROe7UsvsBaiWEmQKfJPYsyCVBgzMWW/DGaRBNPxHC6v457aJgwztfdgatHH/jvb0tpnQdSQp+nC8DhmsXRWFtlVJDP+SHO5yLstfM4R2ZaDA2IksjVSmmUj5r/+dLRm7vD9nSmvO2r5U52GPMqGF3K8voEqvXr6UtPwsuq2deVZznWtVfRBDWi12unA0AptxbohxFa89bXoW16ggWJgco7dzdIvU4hkFGWQWbz1FoXJMKRCvSAVyQ8ltEWCzKxejKWx7aGZee463sqNi6Op7cqGF1JlOek6lVnTdeWJekanF1Jeb+BlMxJkiswVyfG1OIPMgmgGFKKw2THQJPMyZF/QrpHOWnOwvY5yCyLBCNq0ME0LbVooj4OhOypxORyUOpy4MXBENDpkYfojBBZD+OYCeOf8mGH7mmOVil7EmWZ2mngXy7Zu07EzzYvbwfE5ewsixDZWpEFmvksg1pLm8sJ062wx+SlE9ssQDGYeZLbVlVPtN+l96kbc56t319Eztcl+3EAT0OSkssRNVWkJHkd0gIxGY2nA6aa1sw6tNZalsSwLrTWmpTFNCyv2r2lpIqaJZVpYKEygvKKEne11BJZC9PVP3b7/NN/m6+PTHDvQyMC1yaTXseUTteGY4UlzANLQZPZycQqx3RRlkCkKjESZBakQLsZyUQZfIJzWek5D0dFQSZ3h4OrzPcxENq7V81R6kt7uYiDEYuD2nI+tjaUMx9IPJWf1d7XkD3H5xhhozaFDrfi9QQbXztee5E/QULCzoZbKEg9uhwNtgUcZkEKQacevXWe4EQ3M+wJprTs8MZfZzoWIdhDOdylyojiDzEI4e4oVxfFT23oKoltJlsugFBxsqsJAYWgNWqNNjRWxsCImZtgkEooQDkaIhE3CwQihUIRwMEwoGGHsxhRjSezHUeoE7E1Anhal6O4ZB605cqRtpWaz9+wouzxO2o408vTsxq+oobKC/uHZ2x7f11HD2NBcFgu+XqbHDAWUud1A6lNbDktNphBJK8ogsyBOnkIUuEL4mWS7DKVlHq5+91p2d4JNXQ/svBpTKlqzCZRWeaiqLCUQCGGWJOqnGP91VHZUJh9k2vA67PhaOBzpFWRsZhHL0hiGXB6L9BXC8TUXinJYb7F8uFuGNJcXpMK4GMtuGUpLXVnd/opCeCs34A+EGZtcYG4xkLCcG+UUvTA0Tm19eRZKlz3pfr3DEZOZhdRrQIUoRkUZZEqUKURihRBkZnvwkdudm8Ycy47R3Tn5ODbfyUbfCdOyaDlQn9QeCuWSMpLBZzIylXrqIyGKUZE2l+e7BGKtQjnpiPUKYVrJbJfAk6Mg03AaQIb5OLNY43/gnnYCpTDi92263GZfiUtjk1RWuPF5bx+0tF7mryPfx4zFNAcNCbEi/4fXnCjOmkxRWPJ9xhBxFUIKo2xPQejK0Tzazkp35hvJ4tHaKHVycXicwZnNB7VsljvVHwyz61hLxmXZqKtkQ0kJJ2vqN3w+VZn0qTy0s9meQgixzUmQKfJuK89lvJ0FFpaob6rKaxmy/d1wOnNzCDTs6PuZ1bciuQuKRLXb3VMzeEoS1A5v8jr2NtdxsLEh7nMHPVUMPzFAxw2TQN8CJ/a0cGRvS9q10Y40g8zO5hrqq7dW/1Mh8qUom8uFEEkwLQxMquvKmZ/ZngMd0g00UmVHrJz/emVIVIoFX4AX3dHGlWdTm/KxuqyE/Y11XLg2gqU1tfWlzC6tb5I2QtF9Ly0GWFpcfc7pcnB4bxOucjd9IzMseJNrylZpRu137G9Paz0h1pE8mUKIYhbwBVmYWaJtTxORypJ1J/btIt1AI1U6bEVn9clEFovqUQ7u3tW+sgu9ye7OLAxvui2/YXH43h1oK9a8rqNb1Dq6TUe5i52V0ZmLKks9lOPk4rVhzs2sbtcVVrR4yrC0Xpnh6LJ/HnVHLQrFwYpqup/qBSASNrneHZ0/XSnYv7eJsppShsbnmJ7buI9puhcYJyXIFCJpEmQKIeIKBaMz4Yz0TNB5qA0zYhLwpzc7Trqy3ZMiVz01rKCZcZCZzaIGwyZne0Zs2VZYm1wY22QGoCloq62iuayMK1fG4jbBzyxsPgDJrIzfjUNr6L0xsXJ/V2c9NY0VTC34GBqdXfeBux3p9cc9sa8trfWEWEsVRtNE1hVlkCldAIVILLRmTu+B7hF2He1gbGwht4HmNvmthheDUJnpVrL3Zti5ZdcmwZvDUNzZ2caly8NMWenPnJPs+XloYJqhgWkAWhoradlRy0IgRO/gVFrdDypKPXQ216axphDFqSgH/kgKo8IiA38Kj2EorFvm4u7rGqKluZKSMhtGSicp283ZuToWhL3BjLex2cjujNn4Nm/0ezaU4lhzExcuDWWcHstK472Ymlzk0pkBBi6PUWu4qPTB0R1NuFPIMHB0T4vM9CNECooyyBQFRo7ZBcftiT8auu/yME315ZRVeHJTkCx/N6wcRZl2XEhl862wgiYHWuOP6k7VRuW8a2crV64nM9N7Yu4MB00szPvpfqqX4Uf7qL7m567qeg60JX79R3dnnqJJCHSebzlUlM3lorDkavCFSN5mwdfA1RE69rdgGAbeBX9Wy5HtGHCjaRLtZsvsSVks6tXTwzicBrRkXu8Qr6bvwKEmgoadL0BRU7cmjdCa93f5r4A/TDCQuGtHOBih57lBNHDXizoYdASZnIufTeHonhZMyyIYMQmaEYKRyEqCeqWixYhYJgpFyDQJmyYRa7VFYG1ttGEptHl7udc+sLy81qwOgord0NGZljSgnNH9WVpjao1lWSvLWVrjjIBzPBz9HmpWtrP8t175d/Vvy4o+b2nN/S/ZR1tHXcL3UohbSZAphLhNKMHJeej6GG17mlBGGYubjOAtdJZlw3SPSe2o8Pvo2JV8P7CmLy9AXW0ZN415fOEwh/fUMdQzk/E+np0ax7HXRTC8vK/bA9uXl3dw5fu9SW9TAT0vDFFa6WHvPU3cHJ2+bZl/fPopfuXRr6RZ6vXur2vnXLc9g61OHGrj9MjG2zpQW0fgocG0t9/SWiNBpq1U0aQwkuZykXfSJbMwuUs2TyA+0jNBucegqrYsi6XIbnBmmrkJ/gphis5ELK0psXuaTaUp21vKXCBAyDQZbgxQXVdqy6YT941M7z33Lwbxn5mkqabitudKlA1J9bNhm2RhENuP1GSKvCv8029x8pS6E9ZojvVO0tRZj1Ffwdy01/5CZPnLEQpnOJ84UN1aReOxNiIVbhaCIcKmhcfloMTpxK0UDlPjdCocbU4iloVlaQylcBgKw1AYSqGUWmluheXUkpq1D1ZqD4fv2oGpLUxLE4qYaK1xORw4HQYOQ+FUBmbYJOgPs+QNMD/nw++PrItBlKFwOQ2cLgcOpwOnI1qrEgiGOFTXwAtj9vSbBDh6vI1nZ1Zr2Kb8PmqP1eF6JkgobLH3aBM9lyfS+pwT5blcrijac6SFcGu0D7FSUBIxuPbE5jWcvvkAzZPlzJc519SWQrlp5zSkWydyk8GyIl0SZIq8k9HlhSlRTeayiYFpGtvrqGusZGZy0dYyaIdi//07WBpfYqQ382bWW4XDkcQLxVG/u566422Mh0IMjM8xMDULUxsvX1HmYSycWeqn+1vaOH8zxeZVNxgeJw6HQqEwtcY0LaJp9c3obTnOdkGnUri90Z6ARizwhWiQodE4DEVpiZu21hpKylzMhAIs+IM4DIVDKRyGwaw/2k9XoxlWt/dtvD43w50vayFombwwO8FL72uj+9nUm40dxuYNccvHFXeFm2eWVj+c3aXJ5ZIavznNgR/ZzcWBcQAaaysoNeysydw6kZtp5qhbSTHZOh9/RooyyMxqKhCROrlMLkhuT/KHh8nhGerbaqhvrmJ6fMG2MkQ88I3dU7BL88CJXQw/PGDrCS+cQk2mq8TJrlfuZ9LQ9IzN0jM4kXilmFCawex66V2MWVpjRZL8jS0PYmF1QMhapqnxLgW5diMaeNV1VjKxEL8Gu621mmuL8XNhnp1erS29EJmiobaUhdnUBpElCjIpdbDnSAtWmQPWTFYVtEw69jTgdDlwt5Vh6NghSAF69bUrFLrCw8mjHcwEfNyYmmGkZwlPm4OgmXkN+FYa8GhJkCnSVJxBpsQ0hUVqMguSK8X+edMjc9S1VNPYWs3kaPqJttdZ/q0qxWNl49z739rxfm10XaL4TCSV81Ap9v3wIXqCfk5NpFeb6nQYrFYZFrAUf4qbHUrrGsvBm/h7sBgK0Xa8HuczQSLh5IMZI8Fxw1ttcGphEQLra9dHgj5GmmJ3/Am6eKytYFUKy4K9tXVcntpkRqMkuA0Dkg38C4CZqwFyxWTrfPwZKc6BPxJlCpGQ05X6NejM2DzhBR9NbTX2FOKW3+rzrimcr2ui1KaE8K4Er7Hz3p1U/egBTk/OMJtBuqZE+ykUqV7ubdbVRbmSP71cnZum82UtKZ1385UUvdLK7LtX6nCyT9dy9oY9I8uBhAFLpme8rTBwTRSmrXHkE9uaVGQWJoczvWvQuckFqi2L1h11jA7a34/ygjHL8dc2UI2xmkcQMJUmrCwsDSUYeEwHBiq6zNrvWOxu7ZwDx2iIeI3ejXe2UrKviYs3xmA8EGeJ1GyVWWJsDSXSeMlut0E4lFytWaKBP9nS0zOFpz79JvP9lXVcu5ZZTehtErwVmXYRi9gwQE4Up6IMMqUis8DI51GYMjiHz097MU2L9l0NDPdtMiImTRcdsxs/uVzuRDFyI9yxq4mGAycoGwuiIxrVUMJiCZybmeJF9U64YU953XanBtoCUvn67Kmu5ebjIymtk6hPpi0J8ONY8oe4o6GN58aH01rf3sFDUYleaqYVkUGbuqeINYrkvFd8Rz6yd/ARadoalTxFx8yw9sI750Nbmh17GhnsSbPmJsvV3KUOF2emRqNHQifgXYRYN71Fw74Tqz2Vbtv3uNUzP8tLX9JO99PJB26J+mRmU/+NGUpqnQQiqX1HjhoNXIkNmrJTonci03fKcMpBWqSnSPtk5rsAQhQ+31Iw420sLfiZ7B1n5/5mG0pkPyOy8cmzZ3rGtmbuW2fBSU/2T/R2XoCnOqHJ6cA4rTtrkl4+0WeTzbqEBW+Ak/Wpf6dLPU5Cka3V9FzfUMl8KLP0W+IWmugPJF+3HJKaTFEA5Cq5EBk2fS6BpSCj10bYc7idnm77En3bwe/b+OTpD0fYs6vWlmkQg8EwJJeeMa9S/cTbKytpKCtjOQMQgC8c5sbUDJZK7TgbiEQYawlRH6hgejxxYv9ENZnZTlU3PriAcqdWZ5FKWrBUJHqtmbwXrbvrbZtyVBSfogwyRaGRA1ghMtIc+BNPyB9ioGuQfcd3cuOyjaNqM6FhfG7zYKayuRxsCDK3yjk61XJevHR78/ahPdEaviWdeu3XlN8Hu8poclQyMbJ5Yv+EtcxZfs8npr0cPt6YUjqjiJGdQiXqOZDOXneebEdbmpvjs5yUFEYiTUUZZEoy9sIiM/4UJrs/l0gwQu/5Pg7cuZtrcYKT+GWwtQjrtJSUM7u0eVqiBUL27KzIWk80mjFfetOMTvl9VO2tRY9sXrNaa7nZ7bh9fvHo/qHKqzg6V4ZS0ek7lYpOqbl6X4GCCoeTYCAc/a7FZjlSSqEMhVZryrD8uMeI3tEaPe/mcgqvbSyUhalXgQqnm8PNjVwZjx/waqByVw3hiIUyolOaKsACtBU9I0b/1VgaIhGL64OrA/ZMs7i+v7mQYkX/llWUQaYoLNJ9oTAZDvsjPDNscuNMD4fu2Uv3haGEy2fzm7HDU00XmweZvdOzuMi8Q0cxfcOVUtTXltPvv31KyWT1zM9ycm8dQzc3rkUO+sOMj208u1RzaRmjI3MJ99VSXspUmtOh7j7cDPuSX350aQGXUlg2H/OWAmG6hya5a2crF8bGidxS86iA6QzyvEqeTJGuogwyJaYpLFKTWZgMlZ1xgVbEovv5Gxx+1WGuPNu76bLZ/Gq4gok37g9HaGksZ2Yy/YAJonM/39nYjCI2naBSKK1XXuBySVZqN1S0pmz5t6E0VJS5OXGsPRqw6thtOU9o7L6O/i86JeTq06u1Vbce/GKdKVVsG2Xlbvbvalx5bnnplfV0bJpKS2NZFqYVnQvdtCwsUxMxLZwug6a6SvoDmb1nns4SuLnx8ypBc3kuAqOBa5NU7K/Am2TXgLDWtFVVMD5vf42mAs71j3JiRwvnxtb3fbYyvMyRGX+yoEjikKIMMiXKLCzycRSmRCfxTOz6uZN8JzzLK1+6m+vf3zjQzNp3Q8PQRHJzrFfXZx5kRkyL62dHM9rGsbs6+P5Cdvqz3tPZzrlrwyvpm1KiAEfsBtQ3ay74Mk82fmZ2jL0tFUyNxS9Uvgf+QPTiYZeq4JLeJG/rLWoqSrMSZC67MDjG8c5mLo6uTZWU2W9ZWptEuooyyJTfS2GRiszi4q70cMHhR4cV361Z4lU/fIBrj16Lu2y2vhodZVVMDSd3oveU2588Ox3p9OFqr6laSVquFEx7fXiDNvUz3cD46CLHmxrROpYfdLOpJ2P/lpW6WLTC0RrVNY+XVDmZGvfGr/VJ9OXI0XG+LuxaCbCTEU4xhZHLYXD0SMvqA2pNAK2iL9MIr38zZhZ8lLqc+MOx1FkZnvSkuVykqziDTPnBFBT5NApVdj6Z5p8/Tu/sVGwPisfd8xz4b3tpHYrQd3aISA7yCO5wVTGTZLVddKBH/qXzaYR9EcYWfCv3j+9r5dxQZjWqiUzNLDE1k1rN74EdDXQtxJ8Z6v4XddD1/O39dxN2s0nyCiXTSocSv4L4449uozSMzCZXg77MMAyeMvs3XebFRue6+6Nzi+xuqEW5FDemZjL+Jcs5U6SrKINMuSorLFKRWZiyUeO/72QngakwzbXljC+sBiLXQl6uNUHpq5vZ4yqjynLgCYGr3gNk1lQdj+lLvo9ZqvkesyWt38mtH2JsI8vxWcG06mzSNePZ8WHuPtrCta7UcqzmqolXL0SSDjKrPSUEwqlNchBJZo70OC+1dyrahF/lcVPr8pDJPEN2D1QSxaMog0xJYSREYnb/TnYdbmN42o9vaB4DOLanluA9dVyfWh1B7NcmXaHYSF8DjtW22F6hqjT0jyXfh05lt3U5p5YDr7s72jh7fQQNOB2KizezW7uZiMu5eXvz5eA0O9qrGR2eT2Grubl8XZryQVtyy2Yr8N1sq95giDl/ZrN3ScWMSFdxBpnygxEiIWXj9GPHXrKfS9cmVmrOFDDTM0vdfY227SNZTSXlNFSVsG9XA9PaR1XAzdWhScJm/NrNJVeEyppSFufSTwFTeFZHtUdzINp3TKxwOHmRrmZl2DpgOVjpb7n2cbRGK3D6Nw8y/eEIi3Wa8jk3S0vJRv25Oc6PDsxQe7KaWZ24XBFtceJAM9qMzge++p7o1QwBenW0v0ajUDxD4nRf2SRBpv0KpIEkLqXUDuDjQDPRr+iDWuv3KaX+AvjfwPLIvj/WWn99s20VZ5ApVf9CJGRX2pJjLzvIxcujcQeA5KOrxHhwiXH3EninVx4r63ByZ2k713onWbplYMyl0Ql276/FOB0o6JOtx+nA8pkYysBQ0Rlxphb9695jHecvu5U5XFz9zuapqW61/94d0LT5MqMLixw90sTSqfGkip+rj0prOGbW8KQxkXhhA07VbZKXKY4yww1z+Z3dSM6ZRScC/B+t9RmlVCVwWin1aOy592it/2+yGyqMHu1CiIJjbVCzlyynyxENMK+MbTjCuEAGCOMzI3zfO0jtrjKcjtsPi71Tsxy4O8k20TzRGiwrmi4pFLEIhMxN3t/shffpdbNIrjxdExMcvbcj6ZIktZQNAZS+7E2qg2tafRuTemsSbDfD1yhBZhZolb9boqJpPaq1PhP7exG4ArSn8zKLsiZTFBY5fhWmpp0N1LTVQazJ7taPSa9k+1ZorSkrd+P1BtFWNFn36PhCNMDchEpwBs11Tee1pRnuO9gerXm9xUDYi1IqbyfcRHtNJuH21LSXfTV19I5Mx33+ZGMT5uxyYvHlZEJrkwpF/3QYRnRqxuUpCmPTNCpD4UFxnSRq9dZIJY3Zs2PDnNzfCD57Pgc7UqgN9U7TcryOMb15l4p8Hesy3W0BV+CL9DQopU6tuf+g1vrBeAsqpXYBdwLPAS8Ffkcp9b+AU0RrOzft4F6cQab8YAqK5MksTMNDs4yPJD/Q4vCdO7nSndoI4IQ1mXk4Kz83P8zRpnp6J9YfO0fnF7nvJR10f38w52UCbKn2HZ9dn7bp8M5mnC5jZds1YRenL6b2Gd6qvqwk5XVS/ZSnS0PUhivobKtd7d65/G/sO1NeUUJrZx3asqI1iJqVmYog+re2oMztImSaaFNHb1pj6ehz8b5/a49XOjYDkqEUla4Sgg69kiRec3tQ6XE6iLij3TEWwgEiSXy/tYa6ktLobFFKYaz5IigVu0xL0F04bFm0HajHjFgoI3pxpwyFp8SJSynGeuZYWAxsuL4lM/5sN1Na63sSLaSUqgC+APy+1npBKfXvwDuJfr3fCfwj8CubbaM4g0xRUCTmL0ypxnfpXCxkdH1xSwWbbRSEazXOKeO2OaCfGxnm/vs7uPJsHgZiJHitltYpvx2lHicvDAyv3L+/rjX1ctkg1e/O0PwCx8pruHhx40oUT5mbm8E4c5Iv7ys2S9GoDkENHKypo7936paFki9YVWOIQMXmiYICsHLA213ZzPWF+DXK64qrYCbk23SZHe7qTZ8fX/QyXn7743cca+G7oT5eFWhl4erGQaa0NtnM3rF2WaGUchENMD+ptf4igNZ6fM3zHwAeTrQd6ZMp8k4qMgtUylFm6rtI1Fy+0YHYqQxe6mynsteg2ulJfccJXFua4fjelrjPPTcxwr7j8Z/Lpy2dmi2NK5SphSVOHNy4n2yua8FdZmp1NsmWLluvo6OuilOhAQCUI8EUnRJlFhUVnengQ8AVrfU/rXl87VXofwMuJdqW1GQKIWxhRexvUusemKS9pGylCXI5Z7c/FOZCKNpvMhunv1pnCTcG489AozV0h+doaalkaixOTVmWJOqvrzWcPNC2kpxopS5ORe/Hu2hYioRve2wruXF9jOb6SsanM/8cMv0eOc3s1NkkV67UgnRDKRxtmkgo+ps1NkmGD9JcnhWFHbe/FPhF4KJS6lzssT8Gfl4pdQfR0vcBv5FoQ0UZZMpVmRCJpfozSWfkbKJTo2lZLPg2bsaD7Pyej5Q2cjYwvOHzS8EQ7l3VkMsgM4llzgyMZLSPhDXLSUjn09Bm6mtprQkEI7S4nRhK5X1WmlSDTLeR3ITnOgv9Qu482Mr3Qz0r9xPVZEqMWVy01k8R/0u3aU7MeKS5XAgRV6rBm07jRGTPqdP+4MKvIgmXuTI+SfvuOtv3vdXd2o81KRlcoPQNTMdvNs9xzGlEUjudVrndNu49+Re7s6GG562+dY+pBDWZUjEj0iVBpsg7OXwVppSDzHQCBRtmFUomdU+qyqzkGnmMVnfOvr82TsCUVZEM86um4/r1MWqrynK+37WMSHY+IMPGWkynYRBuCRPmls8oQSRQyJMQbFVK5++WS0XZXC4KyxY5dxafFA9GaQWZKa9xOzMLtSyzbN5Ev+zS6AT3v3gHV57JflqjMpeL+1pW8yHHMpSiY7ks9ZrH9fI0hbF/NXolGN/s3arQTg7tbFpZB726La31ymccNi0Gx+fY216PYRhETBPTij7vAGaYS+m1JWquTcQfCLN7VyOzC6ujsHMeFqXdvVXz3/dUrcy26XaEGA9dA6LdFxyU8fAleyYCOHGomadDvbc9nqgmU/pkinQVZZApNf9CJCHBiec2afyuMg0ylYKAadp+pdK1OMmOygqmFzdPHQPw3PgwJw410tc9mXDZTPgCIc733Z4kPhV3VzXQ88LG6ZfiD3W6ncvt5GBnDYOnbi+P05lGA1k669yiq3uEw4dauXJzOctKbg/0SfSwiKvO7WLKPLf6wC3b0dpMuI1kzml7mut4NtIX/8kEb7+cMrOgSN7UogwyhRCJOeJMr1hoHIYBKgu1LAp2NFcnFWRqDWZtcoM4MlFI56RwKMLgjWRD0sQGTo9wd3U0ibvhMKLfPUWsdk+t/osGpVAKdMP64EsBN2+Mc2R/C5dvjIEF+1rrV5KYL4+yV7Eaw+XtLP/dhIuadrVSo7icVqm0ysO8iu5rNeF79Onl4E4pqG7TvLKtFIvwyhN985UM+ubivuaAGd3mKzvKmN4kjnQYmjsbW9FKrxQgmuh9uWZaEw6GOXCsdjU5e+zdWr7nthwMMIsVjv8tutQ5Q8WOKiw0ESxMpYlgEkGzp6Ie7Uk9wb4QIEGmKACFdPIUqxwpNmGmlacxww8/mwMSph3RJvOjnc0EwxFujG6cODtkJa5typQdL7VQu6YE/CEC/lBK63TU7rjtsUjEort7hBNHO1gKhOgdSD4Qrmxsorvr9owCB460cWFhJuH6L7mznOlIz7rH9tUcpL06RFgHo/Ex0eDZgZM9ldPsrJ3Db20+w5LDgHMzG2c6sMOI4b3tscaScjqsek5dnaB2f1VW9y+2LwkyRd4V6omv2KWazsa/FFqt4kl6H5kxszgg4erSNMcPN9HlmyTktCg11Ib7C5k5CDJtuBwrigs6DRcvDXHvPbu5NjKV/HdsowWT3IDDffu7Oxm5Grd8AKYuYzacxIw/OT5CugyDu6p2cPnqNBdDk6hYz19hsyJ5Swu/PUxsf0XyY9tqUs07ODowzfE7O1PcS2Yffrbnvb+4OIHPjBDRFqVu14bLDc8tUFZh/8xD62X+Yovlgk4Bk7NeThzvyNnhxVWZWqfMQvwsDlU10bZUz+mL4/hDq69HxjGIdCUdZCqlHEqps0qph2P3P6qU6lVKnYvd7thgvTcopa7Hbm+wqdxiOynEo61IK/679HwvR491JP+RZnjyymUtj8PY+HAZNi06DzVkdf9KrsbWSaZ27cyNYU4e78hBacAqC6a0fLKfZrLf8caScu4t38lOXyM7fQ28qGwnh6qaklq32l3CvWU7ud41z/DU7RMMSE2mvfKZvqiQUxi9CbgCrO2c8Rat9ec3WkEpVQf8OXAP0d/UaaXUV7XWs+kUVgiRO+meWC6f6ePYi3Zz8XzitD6ZBok15SXMs7Ryv8pycudCBaV+Vi5euhtC9DkTD+BJxJlgIFRPaAFPiZNgIM1hxgnlZzaeVLmcjvSz+aQiyRczNn97f8NsCDgXbhsZvplkP81kfod1nlKMcTdnFsZXHhuejr7unfUNtLSV0x+cYcy/PoDsLK+h1VHNlRsznAmOb/h7lJpMka6kgkylVAfwGuBdwB+msP0fBR7VWs/EtvMo8GrgoRTLKbYxh6HYe7AlOtJzeQCpsWaMpIqODgW9MnoymiMw9vjyAyvW5A5cHo2pdXR+Xh1tBtYatKWxtMaylm8Wlhn9NxKxsEwL09KYYRPTtDBNi3DEJBIyY+XZ3jIZVHP5TD9tuxoYGUwwYCLDs5fW8CNPGBhOB2Ywwti1McZD68/0Hb9yiL5KG4LMTWoyASYXl7j7QBM3Lmw+kCNdtnzlchAtGAneJ7t4nMmN6B+enOfI3mau3xxPvHDaNLNWanUnyX4SyQSZex1NnF2I//qGp70rAWdDeTW1VSWEwxYzi35GggFGksgJKzP+iHQlW5P5XuCtQOUtj79LKfUO4DvAH2mtb20vaAfWVmcMxR5bRyn168CvA3R2ptqnK3VS9V9YIr4AN567lu9ipEQ5DJwuB06XA4czenO6HNH0K04HhkPhcDgwnAaGYWAYCofLgdPtRDkMlFJopbAsHQ1ewyahUIRQMLIuDlAqdtJW0WB8Oag2jNg8ICoakCutUAYYy6lalFpJ27I2dUt0m6v1FcvPLaeGif4TLcD4XGrNf2tZpoUnwwTbyZhd8jN6c5KwN/t1Z5s1ly8LLuWkDk+k6OrYFCeOd7A462N+0U9jfSVT04vMzvtt2X5dk4uglf7vZTNOtXFfYIAql4eLN5LL0Tq3FGRuKfVyyhkzC7bKFF4ZShhkKqVeC0xorU8rpV615qm3A2OAG3gQeBvwV+kUQmv9YGwb3HPPPfJ9FgXPMi1CpkUosH2DisYTezJav+/aOKrEhc7ylHRlDRXMe7PfA8eRRHJ6T/nmAUEmbKnIzMH0gCpHnb4qaks53Bjtb6ktAI22VmcmKq/wwFy0Jt20LM7eWE0DNDkawFCKo0db8TmieVYnQxbNr1zff7O5rJyRkbmEZalsKqcieB9ORxiMEFoFAGvj5mfAsDw0uztjo7dXa6qXZ2pavjB0sHmOyoPlTZw1szsRgNRkinQlU5P5UuAnlVI/DpQAVUqpT2itXx97PqiU+gjw5jjrDgOvWnO/A3gi/eIKIXLFjhOL02kQDm2S3seGc1ft3W3M920cZNp1ejSSCDJHDT+GobI017MNfTK3UawwEwpwbnzj7hj73ZsPxLK0ZnJuicHQxn02y6pK6J+eT1gWR2UJj/aM3PJooprvEFDBfS0dPDe5cf/l5tJy4PbBOMtMeypjN7WNvjYixxK2/2it36617tBa7wJ+DnhMa/16pVQrgIp2TnsdcCnO6t8EfkQpVauUqgV+JPaYEKLQ2TCRTqK+q5mETU2V5dxf18Tc2cymWkxWXX15wmVG5hdp21Wblf3b0riWgygz13kdN5LUK7WpqI7y9Gd8SlTORN00pmayH2VKTWYW6DzeciiTZOyfVEo1Ev2ZngPeCKCUugd4o9b617TWM0qpdwIvxNb5q+VBQEKsKIJBNFuRLcm/E52cUjx5tVRVsNtZRvDiJGOnr5N4/DqEvzzIK6tK0JZm+LW13HQtJV4pjhvhGTrrqwmGTaa8SxsmZi+rzFK+TBt+JrmIFVSqc95nSTKlsCsg1qZO/2ya4DOpLXEzukkcueDPTl/QtSTEFOlK6WehtX6CWHO31vqBDZY5BfzamvsfBj6cdgnFtidXyYUp1WTscbdhbr6NZE7yrdWV7HKWEeieRZ2dYiA2Yj3Z8GBhZomFmWhgOWdUJLlWlKEUh+saqdRuBoZm6F+MNp263AZ76+qoKSkhFI5wc3wGXyjWP7cyO/OY2xEQ5aJP5laY836FTfHw4AtTlL7Mid9MLX1VmdOVMGvBgeYglzfpcpxofXvIMdpuuc5XmS8yraTIu8Ko9xC32rQvZZISBaoT3xvgZGN5bJS8sToiPlYb5pv2MzcwQH9s+cMHmhhPlBZpAy63k2kjSKJvnCMWWJabLnqHZugZu33+67BpcWNydUpAt8Pg5K5W/MEwU4EcdJJLVw4u6JIZhZ8LyTSQ2HXsCXrDnCxp5dmloaSWr3S5OVbWws1r04SdG//OjjVWMBLqBeo3XKa+ujStEeOpkHoAkS4JMoUQcdlyYklQc7Y06WNpcvMclmsDAYcn/dHbNS2VG0YeLsPgcF0jpREnPYPT3IwTWG4mZFqcG472DW2vruTEPTsYuDbF3MLmAWd9bTl19eXRUekaluYD9A1Mb/De29B9wYZ+tokUSIyZc6HLfti5+TI17hIOlzRx9eoU5wLR78ul7nHaj1cx7Fu4bfl9TT5GApt/aDW1Hrh1zJHNJMYU6ZIgU+SdHMAKkx1dZbXWtva5XVxMv8amvL6ceFOyNJSWocdMro/akwZmeH6RYRahWdO+u4o6V0k0TU0sHamFxmeGGQ8scdP0cxM/LMeiHqg/WsbB0jp84376BlZrS5UNefWsHESZhdInM9cM3wI/2FHGd4biXzQdqm5k4oqXc8FbBqppRYdVzTDrg8y7W6roD1zCyeZ9fG+GpijzOPEFszXTlHRpyooieUuLMsjMRb8kkTw5fhWmTD8Xp8tB2OZBXQP9U9Q1VTIzsXFKlw3LU+MhXpBpKMViNvKdKsWw38uwP7VpDadDAZ4OjUAJNJ+oZJ+7mtBsCIdzawRvhTK6PBk1NaXUlVVGz/exL/zK115D5w4/O3fp6AQICgyHjk16EP1XGRqlNDWtM3g95zCUk6rSB/jS9duD+e75SfYcrKNuXDE8vj6g7Lo8QeORciYDS+wor6Y1UklTbT/DIdAJ0jxMBZa4b/9OTl/K3oxGcogW6SrKIDMSzryvmRDbXaa1F26P05Z+nWtpDS27m9IKMqmIPyCnkEOi8cAS44ElcMD97tsmS0tZLqZDzVWyCGeZk6qyMhRqdaYrYrNeofBUeeicr97gNUenlr0wMbHpxdRLXj5PsOKphGVZ/jaaOsTuhm/xBs8P8bE4Sf16Fmc42tYMt8SDpqXZZdax01lL14VxDt3lYDgUTR5fa3TyI7vLCBnTuHU5N3qq6KioYmhN/s6h4TR+Dyko5N/IlqRl4M+2Fg5lr1lBpE5qMgtTpp+L2+NiyeYgE+DqtXE8JS6CKdY+hiqLtLPgGrmoZczV7zlgRpgMbNyft7LMw/BEgkTqDZu/HwsLZXhSS0iAxqKu8lu8/cX38h9na6l21VAy5WR0coEDexoYCi2wu6OG3qG5detduhKNPB0OBa2DEPt6T1k3o39Y0BQ+xuD8PD2zs9xZ28rFwWzOx74qFxcnYnsq0iBTajILyhY+fjldDjoOta3ct0wLM2wSWAoyOzZ328wvNU1VNO9pjk0aByF/iN7z/RSmzKIFlzuzVD71DeXU1pZH54JXy/OyR8OkkZ6JlINMb2n8x4vqGicHvzU7+++VV3jYs6+ZieFZZiYXae6opbKmnCuXkhvFnamSknDa348Az/Ob99Rz/sJLeWwkes65dHWCynI35Qc9sMFLeOCl5QyGb8R9bsJ1iWMt93J2ZIori5McaKnn2th03GXttIUP0SLPijTIlJrMgrKFqzIr6yq47nCvPuAA3EB5OWU7mjhYV0ZobJbZ0VkiIZPmvS1c8q+5yFFODr/6TiZP32B+MrtNXqnK9GNxuVI/vJSWutm7r5Hp4VnG+qaY6UttlPdmpj3yu89FtGAmyI2ajLaOOurqyrl+aYhLL/SuPD7cOwVMceyeXST6Zhg21L6VNXSzlMFYKb85zV3HT/PY+ZMsv/mLSyF6LsdPw9Vc72Ki/MqGs23Vm/v4zkj0lQciEXoDsxxpb+Ly8ET6hUyC1GRmwdY97aVEgkwhMmBskq/FF4xwYXQBcEBLdB7laV/ktk5rV8YWKNvTxuHDBle+dyWJfSqadzXicDqYHZtjKUGanHxxupKvyWxuqaaxvpybFwfpeiZ+LU6mRhyBuI/bkXR+q8hFqBCJRDh+RyfhsEkkYoJePZ/q2B3DUPiWgkxNLBKKHY+rqkvZsasB/2KAnqtjjPZuPNp/8MYEJe1tGz5vD82SlfmUpV5rmJ+6/yRfeXb1Md8GtfB332fSY4Y2KI6ib7AKmFt5yB+JcGlhnBftaedUz3DWukNIiCnSVZRBpgz8KTRb9xCmUu3mt0GNgC8Y4UIQDr76DubO9TIztr4vWX1bLfU76nHVVTCwGGLAG03lc+xYJVefvpZO0RPKdFpJhzPxm1NTW0ZDVQk3u4aZyE5sCUBJmZtFI/7FpcvIzgw9trPlZ5L935o/EFlX+7gZDdQ1VFBW7mFkcIbLU9GR+IlKuTDnw1VurKZ+iiPz2jeFS5US1plfxO3fdwHj+RNY1sZlOrS7lB7z4obPN4VPcG5m7rbHLa15bmKIk3ta6B2aXZ15ykZ21AqLWxTJtW1R9oSXmszCspVzsNndjHR1bJGFzmaOvOrIuscbTu6iK6g5N7rIjHc1V6SRzSn8MvxYHM7EwVtrazU3u4Yz21ESSsrd6+4fq2/i/sYOXtzYQaerKuv7t4UdP5McxArBYBjDkdyOFDA75WW4fzrl1HI6B2evElpt2Y7XGuJ//9hmwapmx7G5DZ91aDdnejavHLk4Oc6Le5zs0+XpFXIT0lwu0iVBphAZmByaofLaINU9I9QNjHFnUzlHWqvY1ZjikNQ1/CGT83NBDv/YnQmXVUnUFqYr0+A/mfOSkaOctY5Y032p08m91W3cvDzF+UsjnLs0woWrmTeJ5oQN53lbYgWtcbsdOJ0GDkPd3nlXKUpK3fHXzaFkXmqi5mUr0GBPYYCahh5+8gfijz6790Qlg6HBDdet9p1kyrf5zFj3e5ro/1YPnk/38/JATSZFvY2EmCJdRdlcbtnQMV2IZQHfah+qS9+6AMDBF+/PeLvdk14qXnYYX9Dk0sh83AjhymKY/S/aw/UXejLe3610hjPM3DqyPp6Z8QQpZmxiOAzaK6ooXTS4eG0sJ/u020bdFyqcTnZXVFEdcRCc8jEzvkDAH6as3ENDezXUeegNLjHm96U3G4/WtLRU01BbgaE1V7uGicyv9m91AE6ngeEwKC114ylxQSCMz5vd+bQ9Did1FaW4HA5qK8ooK3FhogmZJpbWaKXYd1cLJhoDhSMWKlnoaG5NFMoVzVigtWZ4cp7J+aXV7bvBcKbW9FzmaMDjaGM2dGHd4zXuu/jG+AK65Bw/+WNH+doj4ZXfV3mpQdnOURY26IpZqqt55ubmv5NSp5Pgp/sACPrDjH7qCj/1P47zcMUUph0RotRk2k7yZAoh0pfhQbm+wkNduZu+KS9hc+OpGUMRi+EyN2VVpfjsHgCU4XklYfOn1szPLG2+jE0cDgPfYICZLdyKoTUoNK1l5XR4ynD7NPOjC4wNzjCqZ7m1PjYYCDM7vTrb0NG2Gmo7HLj3NDE8Ns+SL3jbDiorS6itKaOyvASnoQgshRgdnmGyb5rJvo1T5UQiFkQsQrGpDXd11Nr1sjfe52KQCdMPJgzPpDar0m007PfUrH/IAq/jfNKbKHPU0+VtZzTg5ceb72QudBaAavc9fH18luUfVB9dvOa1e3nmyRJOHikhWNfPWGh2w+065g7hj2w+5el94TrGBla7nVTVlnHzmzd41b5Gzt6hmGGDCDZJRTpTqLBBUQaZkfDWPdFsR1u4S+aGHNVl4Es/JdG0N0h7pYf9TZW4tcYHXB9bQMeJ/OZ9YU6+9CCXv3Eu/QJngWVtnvulsroM70j8VC52c3qcBLZwgAlQMh2m4byXkPaSTr31+Mgc4yNzK/cryz2UlLiwLItQyMTvC+ILePFNZhiwASXlJRlvIyc03Nvajs8b5Prw+qRIoQiUGc1JjTAvddRx2buD0YAXUHx9fIEfb74LYF2AuWwgcpNDLy+ntqSVywsbB5hVuoWnEqTxaiotZ+pf12el2LGvha5zA/RfHGHveCUtP9LIZZX+8UgG/oh0FWWQGfRnYZ5ikYHtF2WGbejFFE1/BHc2ldP7rQs0t9XScmInV6aXCIbXB3AXxxbpPNDK8DX7+hfuOdCMMoxoAnRDYajYAAAV7csWMS2unBuIu25ldSnVteWwSe1XfX15zoJMR4aJ4QuB0vZekPmWgviWstOk7fbk4NRiw3vRUFbK+asbDzwzIo1gbP6bKnPU0+3dwUhgbXCu+PpKV5D4x4LFyBKL3hvsLGvGYZRw0zu4blmtYW50B5bePNn6sX4XI0urF1AtO+q4fH71dzk7sYjrs35+8HX7+F7JDOE0vkRbaT56UViKMsiMRCSFkciujEZj6tXmcZdDYfqjTV3TI7NMj8xSUVPG4fsP0DXpJRyxqCx1U1fpoaa+zNYg88bFwU37L+88FH/kbUtHLWF/KGF/y7Ky3A0OMVwOYGv/7jPsIptTYTODDOZJqi7xcKyyCU00MfnN6dQvWDSamvIS5pY2yKEaLgVP/HUN5aTKdQ9PTi2waMar/U3uAxsJRKeG3FPeBtrN4nwNPm8ZPZN+Rr23B5h1nlICZoT7F6oJNDkZ/ufz6/ZUUVvO2NhCrAjR/qbhUIT+z3bzwGsOsrCvlIuLk3jDyTehS0WmSJcEmSLvtmV6jDi1Be11ZTREIpy/tYe/1uxvqaIsECLsCxIJRtAtdZQFgvSd6eXK4voToHfOR9cj56isLSccihBYCjICjGT/JayzNOenrbOekYHVE+HeQ62M9EzgXwriSRBEOnL4uW+HIDNsbJ0a/xvXxqiur2B+OvOm9414x/30d0ebmktLXbhbHITM1D7jaX8AnFDV5Ka1opJqlwdlwtyCn8GpeTaqLlUYLEbu5fKiwp+gW0iyhvzRX/DOygNcHggz6r09CFTA/kd8BKd8jEyNoRQcvWc3I72TzE172XO4jRuXR6jb34D54iYuT0zhdjpoqCij1u0hqB2UTkWoCTg51tLAjApwbW4mYTy8LY/R+bZ1fs4ZKcogM9V8bEKkTEWDqAPNldyc8hKKWFR7nMwPTkL5+jx2B1ur6Hnk3Pr1L8Rvhl5rcTY6aKahrZaWvc0rBy3vrJe+ruzP7Tw1Nseugy0r94/e2cnl033oWC2WGUlw8s3hectwpZ7qqdxw0eQqYTLsx2vd0p9TaxxK4VAGDmVgoDCxiFgWEW1lpeonvIWGo4bDJo17m5ib9mbtY16bYsvvD3NHUzvPj6Z3qbUQDLEQXF9r6KpW0aHzt3CpUsLcyXOz0ZrTk9W7ue69ibXRXJAp6g9do/OAwf2uXfi91VweDmNaGst0UK8qmO/uXllWa7h8fhB3iZNj9+1hftYHSjFzYxpuzvDS1+znsjvAyNwiI6zvkzl9I5oS6XBTLVUNpVyYHce/QZAufTJFuooyyKxrqmKoZ/PRelmjdbR/m8NY6du2zOGM9n8zlFq9clTRplOliP5LdJ2VvnFG9LmVdRQYykAZrPSlU7HnlLG87upzEJ3iTRkKwzCi24p2vltXjuj+ie5d62jTnY7dYtGN1jpa+6VXp4+LPha9RcIm2tJYlo79a2FZGs826C93q/DQNLUjs9w4e4OOA61U7WlGL/oxIxYel4HLYbC7tgwFzF/LrA5yamSWxs4GBkYW8flCKAUHX7SXhelFiH0mWkeHDOnY57X+3+jjkVCY+SkvdS3V0f5gSaT6Ghuc4dCJDizTouv59cNRvHNLHDvRERsVvbo/rTXulkqWghH2/vAhFApLawylsNbOQbg2BeO6dIw61gy45n5sIb1maJTWrHxPS+rLefmEb/U7aq2WRWuNNqNNiqFgBDNioQGfd5GQOU810FTiWvnOmqaVsJbX6YrmkXQ6Y/kknQ4Mh8LhMHC6HTicjtXfdOy35bmziv7WQPQ3yuqxwYq9prKJrXW4vtY9yvF7d3Pp+d7sBJq3bPTqCyPcf1c7lxemWAhk3tc0bGlQtweO5a5OvrimL/H5+V46SptZMmfxm/Gb3VNlaovBUA+4oWl39LEdE3dy8dtL7H/dUaZeGGJ+eLU7SigQ4dKZWy5Mtabv4WtUl7s49OJOlto8XBi//bzXNzELE7OUeVzcubOFEdNL3+L6ri4SYtpMSwqjbe3t//x6/uJXP7hy1lp7sloOktadgNFgrclTp6NTea0ESubyv+v/1hpM0yQSNjEj0cciERNN/Ia7rT32NX2VFflP3Gy33jU1kUPXRmFtX8neCYJA9+2rpe3Ks9epb6ulYVcDA33TXOvdeMTqRuoba2ltb2R0aC7pdQK+EN2n++I+t7QQ2HAe8gM/cZyzo6snvOb6Skp6ZvEca+Ha4OajadNxV3kJPZfTz48Z3GCu6Y1EwmZs+trk19t1oITzsxuX8W6zPqUyFIKLFwY5cvdOrp4bXKnhToZSUFNfEZ01avUqBW3plSDfcUvoY1marlNDOByKzqoSXG4nDW2VaLfatIbTUIrmygosrZlY9K5cshxtasLBRLw1uLWtc8g/Sa2rkr3lrdxcSm5KzVQNdZvMLgZ4ftFPxb5y9u+sZeDpvoTrhZfCzF6ZpLdk85mAfMEwZ69FB0Edb63HWe3i7Ez0+yjN5SJdRRlkohRXz/TluxQiZjumMMqH6ZFZZsfnOfbyw1y8OJLyiWHahtQ1ybJ8q8FXbXUZ7qtTzIzM4xpf4MAPHeDagL2B5rY4RW7R38nlrmGO372TrueTD75q6iu4sWP59HTrpxdr+ZiNfyFlmprZ2WjO2InxRTRw/4s6CBsWFybGCZsW5W4Xx+qb6O+aYMkbwkt0oEwF0be5vNIFByAcp5dFxJoDqm97fDa8yGx4kf0Vu/CbC0yF7Muc0OHs4Mkrq7WkXn+IK26LnfsamLqR+LcS8YeoKa1jPMn0fTdGp2EU7tnVjNvjpMldlnbZRXErziBTFJYtevIsJMdeeWRdP8Ca2jLm52xOzm4jw7PaRWJvRRlXR/qAaG1ULgcEFZJEo8cduZisO0suXhjk6F07uXKmP+f7VkDXC9E+yrVlLmprK5jsW+Tyjfj9ljv31zHWEuLMzBg/otW6GFdhADto8DiZCsYPIq97h3AqB0erDtDr6yVkrV5Q7XQeYVL34TM3nyJyrQpHBX2P1NLRUEKJy8HQ9AKBUIRAKEL1kaakgkz/TIBKt4dxUpv8oKsvOvL9/2fvv8NjyfL7PPw9VZ0Dcs4353xnZifscGZ3uTkw7TKJIkWJS9k/+lmZokRS0kOJoinTpiXLsmVJa1mUqMAokV5mbt6dsJNvBO5Fusg5NNCNRsc6vz8awEXoUN1dHXBx3mcwuOiuOnW6qrrqU9/Y6im8Ta4iA0fkvqdEpqIKOCLfthLS3z93qCzCscAmxzsbWAqEefStlEtdAq0fPsvAuPXx0k+CbD3skctTM6vY7PpWGEF2SnUub4bjbIbTl9aSSM692MXrG9MkN1ITWI+3YnM+TzABq/EkExthwsYGF2uPZRSZAAmZ5PbaKPV2Pyd9dQyHHtHjOMHvvxqnwdvLBy7DeGIg4/rb+HU/a395jMmRCOeDSeYH5jh1uYOHfp1YPIm0mT+zbd+c5cYHunlnPl0IQHaO6HOfwgKOpMjU9cNrEVAo0nGyty6VwLWV9BXYSDA7U56+4IUw9loqSUizacS2stAFe+srHu9sAASj09mLUZviMAjwHJkAuiVNqCvHWiDMuQsdPLw1mXPZcosat8dO7bN1vLK617o5EdEZXgscWL5/bZxOdzPz0ewPRKvxIKtrQU55j/HWfTcQZWUjwe+/Dt/39CUm5d2M6zo1B5vfOs74cMojkYimLKIzd2a4/H0XeHtqPq989uDUOsHfvM+N6x2snfMzvGTena+KsSsK5UiKzENl8jkCqKNRPINv783sPvnsmQrNJD+MfWWO6nb96V2LWZdwUOVlyzxeBzanjV5/HXZNR9dS1R3WohFmNlKlZ/Tq/gimSNUrrS7cHjvuZ/zcWzVv4TMwsGsuNDRTpYtW59uYWNnr1tb0ZNZsz8aJC7x677F7e3fXqvXb85y+1ARL+YfEzL07g3wXnvvoKUb8cebXc7vQlSWzBDwB32czHEmReUSO7SFCXcEs55Ce5KNfH+T6i6d4d2ElVUrLKqpwfzQ0+2i80sij9k1u2Va4JSbZV8qQZ1q7H4vM5OH3wGyYbGNZrmxml8eG+xk/g2v5W8tHN2Y45TlHUsJ0ZACZptwRgF8288rwQavh778e54VT1/A1j7Mc3/t+j97LN/8k1Qd9G/uu5gbLI0swskShNn4BjP/5EE6nzvOfOsPt2BqhaOYOQOoKrSiUoykylSWzylDHw3oO520hGUuyNr7CubPNRCfWkIbBxWMtu5YQ3NtKRsgHo0osmbX1HlquNDHVFeU79mUQ26V10h+vpHwsXMLOJMcut6dKpSUMZFKmSqMlDJLxVHm0RNwgmUiSSCSJxw7GPmqawO11YrOn6nTquoZu09D01I/eZIBTbtXw3ZpD1GBtIkJoPpMIkQgNdJtA3zK2RTMY2BK5CvSXEV+tE+d1Lw+zCMxs3yKP7uXWygrr8Qg9nj46fAaz0bE9y0gJG3N9xI30yTmvDIVwjjbxfVf6mLDdJSbj6EJn9C9qgL2C3O61vtRbMppk7Pf7ufL953g1miWBSJkyLUWg6mQ+0SiNWV2oy5f1BEPWFIWuBAtDCzC0y3V593GNQ6ffCccOlo/JhXBotDT7U0JK1x43KmD7/rmrWcH265p4/EC6XRtXSqSxVcQd0LYbG2w1QtiqE5/qU7BrXSlh9v0ab9lXQGzXTM195s+FH5s2v+NZhPeZ+bRa6kfasEkNh9CxS0FcSK74O3h7bH9/e2PrB777u2A0kj4D3Ku7EKSEryENNKHx6dYR5L5akr7kKd78jVM4nOBwgc0J04OSR3cSuF12Mx9gp1FEKZBITl1vY9i9zlgOC6bM8gDc6uhmJJA6NyfCq0yE4Ur9BYQ2z2piCSnBv/o0r89mj9ts89Tw5f+wTmvHGc5+YgNb2MtXRw5afIW+d5/U9zXgu9GOI5xk5M+Kq7q7ORJAbxckMzyMqY4/ikI5kiJTqcwqQ13AisbhstNxohVfo5+kFDwYKLzweDVTqAs9kTBYmF+3eDb5sf5SXV7n+jNtXbw9P134BoUgISQJEjt61sjR/zwhMwcJhvd1s3mmvh3J6weWC+lDnP8bQ3te6xj8II/uaKZFppXXaF0XtDbXYPfZcHW6WLfF+M7qHBRY4avHdYKE4WR+86AQvL06g1OzcarmPA04+eOx3JUSGhcdBA2YnYqx9h/cuDJkjE+7DOo/czrVGUtKHs2vkpycR9c0bnzyHKN/+qDglslzt2ZpPNnHQjC/EkcKRS6OpMhU7vLqQmnM4nB5ncQ8XsbnwzBvvv7eYaTQWL39VqBKkH/KiyBp8bVqcDN7TcWEyQ5FAkGXM3Nm9AG2wknXV02KGAsuCl2d9dQ2eXi4sMRoZJ2zrS28uj6Vl+ukyyVp8XXw2vJja7qGk3eW09fYBIgaCe4FZnnGkz35rsHl5qyzkcG7jx8kznW18t7D9A8WsyvBtK8nDYM3Fxbxv9jBicY6nJtJNibXmLk7a+qj+rtqiLy/lZmVQMZllCWzBBwRGXJERWalZ6BQWIdhopf2k0KhbtRSul/NouUbGCJThemtFJq5xEJcmhOZ1+ra0Xjb9HaFkPT0NTH+YM7UXij0aLnddk6ebGEpusnw4ipMBABoq/fznp5/LG+L6xEb8jafaL3KaqKVlZiBMDQaHB4MJEnDIJhIn8xkj9p4vrYLyeP4OyHB0FKF97WYZOBbewVlMUc6GI5yK7z1Gd3Q84mTtCV1Jr49Snwj83GtP9/M61kEJihDgKJwjqTIPDJ35EOC6otbHPFoggtPtZK6RaViCvsfzGMkD8957m30Uv9cH+7NJENfyRJfVqglswpEpsjV0mcfi5ENmtxe5sPWtfvsdtVxn8wu3N3dabLR5x7KvdA+fG6HefGYz3EWcPJ4CzavjYHZBd6aOtin3OOykyxAwnU5N3kYAeQt6nWod6deP77VBjwpT/Mbo80IwKXb2Uw+3n/B+SgD38ov/3tsfgWv28HGZuZMb7NMLAaYALw3mjnv9DH65cG0y829NsnzHzpO1G/j7YX0Qlxdoy1GqsSfJxqlMRVPElJK7n37cfeQiy+cxWbTiCVzd1apFhweBwPji1w/1pp1uYLvdVUgMvMtQNTs9jG6lrtwuWkkRNay966OGrnFTZ+nCZ138tq04+R7vO8XHvGsYQdD3zLlGSC3zHpb5j0pNZAaRjTJw3/TuHvq+DwOamvceLxOnE4bul0jjsHE6hr3VhYhS23xlfUwLzR080rY/P48U29w0hVLicwM+PUIXzg5T63tDrqIkDScBI2LPAqfZXYhf6G4Etzk2slOAqFNfF4ncW+c8YcBomFzPcfTsRGJ8VZkhff9wAWGfv/+gfdjoRhjf/gAd4OL2hebWEsTa6pQFMoRFZlKZVYT6iHZWhbGF3A6XcSih0dkNp9rY2Jumf7pZdzv79vJ2oaUizeVwb1VU305fWxaVqrgHKt015TLte0MjGaLyZRETVgy+zz5R5dG5SpRsZoKTDWxutvfBjy78/flK128NTHNcjS+v7KPKQIbERZmg5BHYYJ/+twERo5j5rHFcHNr529di1KnvcO1mneoaftRwmc6mVsPIWUqac0wJIY0QEB7bQ0Li0GShqS7qRZd1wiENrk1MUfSMGAJrt5sI/qxCOdDHQx8eQFZQAUoCZy/2ck31xd45ofPMvlb6T0FmysRLkTcvJZmB1fB10dxSDmaIrPSE1AoSkjz8Tb67x+y7PKtbiaRWIJIrHCrTSaq4Tufd0ymxXiT2essuu161pI929TYAhbNaC924cW5cZrlgSYevl0DuzrpRELFu4/z4YUOg7Oer/CI5woeI5ZMcGc6cxxoncfN8noqUS8QSp/q/vDOEjTAd5yjdP5AHd1r9Sw9CLM6u7lVUguQEsOQO0JWbpXM8nkddBxrIOhJ8J2lVAjBt1jmhY8eZ+nVKZo+cxp77PE+lhISLg3SND5S7vISUA0XpTJwJEWm8pdXGeoCZimHaW/2fPoiS8FNHi6Vts+61VnaBc0hQ0eYTPQvz9Pm8aMLsGk6rR4fb85nzmrOSY4Tw2E359B3CGtc+AINX/IkG+MdDH3bze2vRkkmBGDQ0i6h6fGy8XjxDx666ZAJyT9/9h0ExXkCEhb0mt+MJbi61s1rdUNMRwJMOwNwhdRPBo7pLYze3mSdODPhedhVcEICbzVtcv1HzvLmgXqpQIYqX0pkKgrlSIpM5S6vMtThsBRxiM7vzXiC+ULc33lSDd/5uIke17sJxmME448teG1ef1Hbz6UTMhXi3o1N6CDzKwO0Gw8dGAt9TL1bwzt/mmB9aXubMbIN6q/3QHC1sI2S+uwN9R6Ir+ac+y89FaZeexdIfd5j7vadS9T2qtt/a9QgOMtOJf5dS0SSzoLnu5uhOyt43u8gLMxZc205on8jiQQPogGaa70srpkrKaU0Zgmo/CWpLBxRkVnpGSj2og6IlWwEDk9B5XId+WroKhkvOp20uPVzrW2YuDA2O/2IPD6HQ/hxRM+weKuBW38umHqwbZHMEfsptkVbivFAwPQ20yEl3B6a5fmLXby6kc0aLPlc3xu75hGgRbyZcWlNO8kPv/Fdad+7HmoCMsfAmtnfABubMa4Ge3itZtjU8maeAFYim/hqa/BFHYQiucVrpeOJFYeXIykylcqsNtQFzErmx5eQNqdyce0iaVS+Z3a0SPdrsYo81+mQsKDklUDHw2lWlrt576GPNx5KXko0Mfj10fzG2TVXt8tOOGautFIuBh7Mc+FCM+GtBKfdYRRSSj53KoCbfMozZd6pTs1Gc613K3HtcfvR9XCE0GYs5/G0CUFHfQ3RRIJHd9dwPKcTE7nPIbPf+ongOuc6m9h8tFIV3w/Fk8mRFJlKY1YXZpINFObZWAvTeKaRleXCLZqNjR5aa3cnishUiZntY7WVdKDpgk2pMTq6UtWiNlEFN9F4njGZByhy9+b6lplxl89H1pCyHiEeu65dWiPJzTMMj7XwtVsagT1lPQWbU4XX+bxwvoMHK8tsmLC2mSGWSFIbcTC0kL5+5cvPv5vXeDKLa3ozkGR+4+B38HpvB7dGZnIej3qfm4WR1H6+8WIvX85S37RQBlaWuHmqnbsP08RnKkqKqpP5BFMN8VmKXajDYTkut8ke0WkQmsAd2eDOWwO5F97i4ssXGRhbz19olunYJ5KVF5kxmSxSKBYr4rPvbDMi00CykniOHtsk8wudvNnv4faokXFuTTYnU8Np0pVzYROcOdXKfDTMRtS6zPKe5jpuL6avvPDJcz7O1e2t/5l7j2Q+JpkaAGiawOdy4LDr+DyOPdvQhEBKiWYI3HY729HKQ+/N09lez4YWRSB2oj8F4nE46NZ0XDho8nkQbFlQt35nYioS5OnzPbzZP5FxGdVWUlEoR1NkVkOAluIx6vpVVZw/Xs/tv3wvr3Xuff0elz5ynYGh/DqclIt4ovIiMyEyizFTFPlwXMzaHc4WfLFGlmZ1/uitOBurHmKJJHuTXQ5y0fAzLPMXmUmnxp2lAsRpDoRfI756cE/YNY0vXP3Dgyvk3GmZP3usNQppogQMKQnGYzxcWEq7+rG6Ohbvr7DA47JG68EIp95t4TXfYs64h8VsVekzMLMZ4pkT7dwZSW/RVN6mEnBEdmm+TSieCOLxw1Ok+khwRL5s5aUwMdPTXcfdr9wqaN2H37xLe3tNXutoZerEE09U9jtvs2nFp+iWfFeJnVqeNTYvp+0n6Q5eZOO9U7z+526+/LUw7w0EWQpFON/Vkns4KVm7l634e5aZlMBydr6nlaHV9ALsh67Y6fKli8Us/OIU1QqLI81kNRwaWuA5d0fB88mKgHc25jjT1Vya8RVHliNpyVQonnREATdHl0tnfWQKo0BLfywSJz4zj8PpIxYzJ+rq9PJcgqIlKPCeDzZ7/l1yDlCg3jnra8YXdzE8k7kEkC4Epxob6Y37mZhIcndig7vEyZQFHjZy78/L7gYWZ8cKmnMpvLMulw3SVMvy2G389MXfTrvOnyxf4WvL3Uge7/7tIuhCQIe7nUwtiHxJF3uKVJokm8AOPFxD76XYFLK0JKTkobHCxWNt3Hu0N6RAZZcrCuVIWjIViieeAu7Sx7rrWJoqzt0992iBYy0u03HPyaFFLjbVFbVNM1RaZOo2C0RmgTf6es3D7ek51iJ7m3C3+/081dHJ1cY2vHEbwxNLfPWVIEMT4ZzbGgvkrlnZvF5dwmRkapmnWzqw7ftu/MT1JI2u9HGaEUMjmJSEkpKNrZ9NAyISNg1IyMyf0bGaPi461zdj//x2s7gc4rq7NccIhbOZTPLexhzv7+vZY1FVIZkWIyv8U0aUJVNRcQq1nCkyU8hNYX26MNfmfu5/q5+LH73Bg8Hs43lrXEyNzJN8OMv5l07Tv1y6rj/RWBwnlQv/tdk1yLMYu1Vsx9P5HA5O1NfjEDozy+vMzwdZnC+sEP5mPIFDE1mThTZmC88qpwRhFGvhCLceznD1TAdvL6TaLOpC8FfO/F6WtXLMQ0JDpPHA8q02D/eGMmWDF3e9cywZ4C1qiIy4hc6zC7UM3B3i8vkWpusSLK5vmK7pqVDs50haMsPB9H1iFZVBZftbT767tKXZx/i9zNml+TL4zbu0tWbvUNPV20h0M04inmTp9VHafG7Ltr8fKcHhqNwztSXu8gJ0V1fSS8usxtmaRqJrMe4/mue90Rnm14oQgFvoWvbbx+pchh6FJiile3Y19vj6/1S3n3pn5tJAuR8LBHPB8K6fDebWN3DM27LUnsz+2XL1uB8eXKDFbvF3RUqu2xq50G9n6G4q+WeqfwHP/Q1ONDeosn8lQMjK/ZSTI2nJnJuozgxYhcIq8hXuzbUOZizcfmwzhlhdxeFyEYvsc1VLyYXrvdx/63Hq7WYoStPwMm0nG5kLleYh0OmxE6+Q21y3WfA8b/KYeqSNZ0LN6ANRxh4s0M8a/o+0Wy4Uspa1kZKNUPpYRVOUSGOe7mzmXuCxqPzgsfmsyxeyz6572nlwJ3NmfM7vZo7PbkjJeer3ZJ8DnGtrxu207ZmzENuiNVUaKWkYxJJJovEEhoS6kE7Dho3wWJCp8YNXgI21KI7vLNF47mT2SSkUGTiaInMy/xIPisLo+6s3idoF7o0EkYlVFm/NEA/vrXun3OUlII9dKqVk6v645VNYX1rnxAt9DNye3OO/v3izj3tvjBxYfmkmQG00Qe2ZRtYi1nR42Y3L4yAUqIwXQ9eLF5lZD6mUXE400TXhYOLdOSY3J3feOvt8H29NL3Cjt5V3NrKLqnywZbFkFl1XsQQiUxMC3GJPLs7Lnd/Kuk6ur5HYU6QSHOgEJ4s7x8zsu/mhVfS+xwlAbTU+RtZWiCTye4i6+cjH4MPs98PYZpw/+o03qIlofP/33cTpLLwGr+LocSRF5vyksmSWA2eNizvrATa3rUd1oL3cSXdjDU02B461GBsjS1DZnIwnknxiqI4fa2Doa9a5yncz8O4Yvec6GR9KiZuLN3rTCsxt1pZDnJWtvJWrt3UB+Oo9LM2ULu4zG5oFlsx0x7TVcHNtuYHg7QDzM/MM7nv/3HN9vLqa2vcJi2uFZnOXCw34lXqS+xzOYt9f4sB7qdeMqAe+VYQldB82XePciVbeWXxcB9LnkHj9GgEyWekEP9r8Bp9t2vc5Zeq9VIXQSX6ioZkf/eoJAJ5xdnJrdTrrXHJZMs3o6+WVDZ4908Ur0Rlu9HQwuLqct8AECF5zUnu9C+ftMAv9mcXm5maMf/vvvsmf/fkd/u0Xf1IJTSuoYtuKEKIb+E2gldRMvyil/D+EEA3A7wB9wBjwOSll1izAIyky55TILAsdHz7DRHjvTd2QkvGlNXbsZh12nHYbPTdfoHHDYOQ3XlPFMqwgjwuYI2m9oAN2rJcejz3lIs8hMLd58PoIlz98njtLAUun46p1WTpePlghMpMyJdhcUuOpcAueoSSP7s0xbKRP3unqbeS1wBzbssXq/tTZapw6HDqT0cI9RnbpyL1QGoSA9novy+sRortqo1482cabC3vdwbomicVvZZ/H1k82ejzngRP4dQcPB3NbiovpIrSb2btLtF7x8tZsdlGbjYeB1L3w+ZoGU8tPz6zyF395j09/6lrB21QcChLA35ZSviuE8APvCCG+DPwE8FUp5a8JIX4B+AXg57MNdCRF5rxyl5ccCcy4MVUmLhpPMLSwyhDwzH/3fkb/1beV0CwSsx06HA6dkbeHSzIH+5a1Y+CdMdxeJ/ffTNP+JAPLb41Te67JUrd5Qquc6cCKmExtJcmH32tianCJ2ehU1mWFgHCHHbn2+JuUtLi1pp5FZBZbZD+Zp5nHZbfx0lUHF899DZdvlES8lrt3Psufv7VJ0pD4elZ46vIiLs2FTdgQCDyaNftDkkrquuBo5n4sfSmkPctbdBquhyJcjDZBLcyGik/kMsvv/N4bfOLjVywJAVFUJ1LKWWB2699BIcQA0Al8Bnhpa7H/AHwDJTL3kkwkWZjOXeNNYR7bX7lENJFM9cgFEKle0RMFlKR5Y3mFZ376BUb/zStKaBaBO7JBXWzrxiN3Sc6tO5yUqd7KxobB6oZ1bsnd2J32nVrem3luY311g57VGja8GgmLYnbH5wMITVSkraxwwPlmH3UuHa9T4LJLdD0JWpyEjBCREW6N1rAUziyq7SEYvZtbxACcu9nDK2t7s6YNaXDhRTsGqWLiRupfGFJiIDGkgS3QxGIoQlKm/k4aqfeTUpKUBlKCy6bjstlhPvM3tNg4a6e0kanI+W5q3A4+eENy+syfYt+VJW6zr3Htxr/l1Imr/Oc/vsG0ZwCZMFjbVY293opkLMDYKtJiT1hRCzW/cNSHt2Y59pEOC0Sm+a3Ozgb49isPeem7zhW5zaNNubO8C0UI0QdcA94AWrcEKMAcKXd6Vo6cyAyHohgWP9EfZSQwFwhlrZeXL2+srlal0Dzx3BkSNV5s6xsMv/awqua2n/Wl9aILqxeLpotMDWNMMTEwy8WrPfQ7DGIWxBOuhyKcPdPC+IB1yS+5cNXo9LxYg+epTWZdQ4SAEKScUftC6AS1Wccya4itrXVzKxo4+IaA4XD2z94ka1gIb2RdJh5LEozFOGHLPN9iLZkuX5K/8ak1hDCIRr0kEjak1EgaGoaREnVu1yZdvX+Ebs9c69NXd4uf+GyM312uOfB9TUiNocRndv4WyJ38NGOryLoR9RCJGVvryq3lHuPUNebWa3je340joXP9VOfOe1Lft3AqiBOvx87Vuo5dI+593yEF5/yd2IWeMY7WFnn8sOQwbDxzsmPr+VGSXjDuPXns67ZUjO/W4tpSfslK//W/va1E5uGmSQjx9q6/vyil/OL+hYQQPuC/An9LSrm+uxuVlFIKkVsqHzmRqWoyWotu1ywVmNu8sbrKiZ56ghPVYXU+992XGZhew1hOXYxPfPwG8clFpu6WJmGmaKrgNNdy1FE0w8itCY6fbCHcXcvEWnbxYwZ3sxcGih4mO0Jy6qMNeF6IM2ofZ0KaKw6V82tkMmO79VIrj1YKE9LZXOD5LFts73GbK0Fbx58UNcY2UXsbQhyM20li59fGszdo9M1f5e3xzHU0Lze2MjC+AGkKgBn+9G7/C03N3N6cPfD6HjxwsraR0dlA2rfb11xsbFXpcAZ0ok/HCCViaZdNR9u9WkKRx8vfcJqLydxm4MEMm5sx3O7CYmcVVPoavSSlvJltASGEnZTA/M9Syv+29fK8EKJdSjkrhGgHMtfq2uLIBVUokWktdq+zZGNbIVKKRQIXP3WT+xMBjOTjc2dkZJGJGJz5zNM097VUboK7kEBdRz2n3n+uKs5zYdHxmx5eIPjKKNea64oea2p5veTX9rPf08jkSw94aBshLs1n/OaKozUj2xwOG7fW0ndaMnNK5CMNs34/i61gZKGbwKe9jUM7aE8xs4lc+yzb2yVoWvSYXWNHo0kuONpKuLGDGIbk4WAOoaw4tIjUU+L/CwxIKf/Zrre+BPz41r9/HPj/co11BC2ZlZ7B4aS2t56G548Rd6XijravcQYwMZf5Sf8w4/S5OPHBy9x5kDkObuDBHLrHw4XveYaJV/oJLhXWpi9fJNByvJWGvmbsfg/hhMH8QpCV9U1WFjZozDmC9TS019PY1UAynsRIGvga/MyEApaMnYgnGfnLAZ5+/ymw66yPLWN32XG31xDWwIEgPr2Gw+MgVu9mZC1EOH5Q4C2uhDh+vInZUWtaaKZj5UGE7ufbmUzO0rBeT/1SA1IzGO17VNS4Ikuf7G16TzYzlwwUvI18Lo/FWit30+Tw02yvw4aOEIIGC5O0NNa5WtvMm6t7RZGp+RcxDaEJSB4cwIq9tn/uC/fC6CcEyTLe4O7fn+bqld6ybU9RVp4Hfgy4K4S4tfXa3wN+DfhdIcRfB8aBz+Ua6MiJTKUyzeOsc9PxgVOs1tp4OL8CgSc7K7+uo57Ws53YajwEQjGmp1e5l0VgbpNMGtwdmMXV1cKFF84Rnl5m7N1HSItif4Wu0Xa6nbruJjSPk1AkwezcGvObcean14GD7fsqkdzScaaTB6O7whvWApaOL6Vk4Fv7KkHeT1++pbbOg/9yO/NpugfVddSUVGQuDIRpD9ZQn6zD81tNPLizwJnnOlKV5bKQy/JlT+aWJ7ZaJxRRCjQSz+4+3pmLprGwnPmByqwAbbbX0Gpr5s3ZGSZ4fEw+3JM9PjVfep2jvMneVoxmZmgUoTIztca0RmTu/XtxfoNrl7p4e2My/Qr72F9ztZDb4r0M3z2FCSSVdpdnRUr5CplP1Q/mM9aRE5nV4EasZjS7RvdLp4n2+BlYXGEisg6RCk3GSp/ZPiTQcaaD+mOtGE47C8sbLC0GWZleh+nCei5HNuPcHUiJUs+VE/R21WOLJ4iHI0TWNwktrbM2FyCZ5Ubu8DhpO9OBv7UO6bSzFo4zOxtgOp5ketx8fGpFMqhLeLzyJRQI0zoWoO50Mw9X9h7PTcOckMoXTYNTJ1qxAzO/vsLKgmQnZMlE5ECuntW2RO79OxQrvF84wNyauQQQr91BJJo5BtCWJdFaQ3De28NGRHJ/cZHxNPGMdU7z8YVmcHCbbvcnmNx8nAynCRMHJefXKPMCmTr3mO3Lni18It13bbU/gug1p132L1PIN3dgYBrDkEUneSmebI6eyFQtDA8ggc739WE718zD4DpvhiMwWyllaT0ScLjtdF7owddez6YUzMwGmA5FmX5Umgzs8EaUgYf7rKAeLxz34vO7qKlx43Xbcdg0NFLt4VbXI8zPrTEWTkKR86rIw1TlQ2j3MD+xDBPLPP3+U9yObBLdsizvTnjIGylpaPTS3ODDYU+5dgWQjCeZHFlg+L307TmFiRtxLpGey4Pcd6KZdzcLL2WjIYgnk5iRHIFohO5aLytpRGlHm4tjz8R5ZV9KgE3onPf2MrYS5M1A9nwBzeL6LkLAGZ9gd8dHM2Iv1yyyxmRmsmSa1GTZvsPpwmHnZ0Jcu9DFu6HsNVStYj0YYWpqhZ6eSgTnHG4EJemcWpUcOZGp+mTv5fjnrjKqx3lvbQPmqyy2sgDLmAQufuZp1iNxNjfjhEJREvEk0ViC0WAcgjmT4UpOKBghFCytiK+IJbNKL5sD3x7i7JVubmsShMhbgNfUuOntqiMejjM/vcLaROonH5ZHQpz5k4sITSINSJ6NMnxifxH87PNa8MU4ea2D4ffSZ6vb2z2wUrjINJB01/uYWDWXxS/SWAJ7uz3YL82wYjy+tbg0O2fcPQwuB/jOqrlkEatFJoC+b0xTIrOIaWTq7W7ekpmZdPseIDwYhw5Tw1vC/f4pJTIVWTlyIlNJzL0seATzC8WXhikJBVzhz3/4CndNxFE+6VTEYl9F7vL9jN6e5OkPnOXN1TXczhyXPSnp7Kynqc7D+kqIieEF+meKK6W1OL3G4vTjYMnL7m44sXeZYCy7G/89xxI1F+y03RYHHpadThv3gtnnaKaffVu9y7TINPa1qTzW60G/MMNaYoNWWwM+3c4JVyf3F5d5fcVcGadtRAmu1Ok+/uW6trSSb1sIBuIC3dO4s+52FcrtU90v7FzRWgCBbmgYcYkQAinB5tKISwOhs9XBPeUAz+RG30+245VpjKnxdS6faedOML/Mb9Hs5NRLfbijYGwaj/eJ2PrMcvvemfoMUqbmML9YnkRHxeHlyIlMVYh9L9UrC8hbtDT2NjOyUL72atWMIct/nldTTGY6Jt4a4+nTbfg2DPRmH3aHDW+Nm6SEjUgMp92GXRPMji0xNzhHKR9VZOKggHim20fS2LqZSxhcijC/q1PS8aSf7k0vq+5Fwvs6KB0738Zr0RwhFiZ0myuP9u7xXdfSG9drWG59xFoiZaF3GD6CawleX85PXG5jSOtjLxJyb6CoJgRrif7s63id9IfWM18oJVCX+ufNyBneStOR6XhTPaNLjx8ALt7I2SQlJ9niNY1RoDn7+vs/ztvTKVH6dEMrg/3m3e3Hj1dH+bZDyRGxeB05kaliMquXNo8HAcQNg7hhYHfYMvavOIAQ+M51s/iodFnDh4oKnObV+M3SdMG5a32sr24wObLAwDtjXHz/GaYqfZ6kyRRf1u/BLh10pvniHpF5as3PyB+nL/6/5pY5uzCaOT7hNEXLM9HZXstGOEjvjQSD0YFUYPEWesLPZqLw0JT1mPVFvkPJvbc7Mw9F+dwuMgm//dtxCztn65oPLC8QezZYY3fhqXdiSIOhfZU9sllDx4YDXDjWxv1Q/o9J+X6Hnbm8Aoojz5E7Q5Qlcy/VYns6XVPLyrcfP0HbgQXscKYHu9OG02nH4dBxOGzY7To2XcOma+iaQNcgnpQ8HCxfu8BqpxIPU2PvjtBc50klwwhBY08z/UOVa2154kIXobUw99/eW5+yUgUmXB4HXX/LjaEbzHtzW4vqPJKnu2rQhEADvKH039bmlhrury7ntPybiUWd2lwCPOS6Mpxt9dHcsUZgc4zB6MFr6lywuAz+Uhyj+L7vRK5sfshTdGUYbr/IjG0YDM8dDG243tzO4NuPheHcVi0qr88B7ea2tY0+qUN9zhkXjcNuTb/2o8hh6V1eLEdPZBpKZO6lOmRmo+YgUypFLJogFjXfOUVRmfN8fTnI+q7aiTXN1tY6NEv3yRbcHieDd9LXDKzUtd1m1xjvNN+GdCx+n92lHXXH5bTLNZ9s4GHAxAOWiQ++mYzz4vkmklqcQCLERjKKU7PRYq/DazNAGKzLADORIR5mqHZUo9VyZ6VyDxeZMKROjc2XsiBKcGlO3LpvzzLh5N5wGyuqNJjOJs9wgGRS0uLx7h0zkH2s0QcrnP3uFh6E8rQm5/l5nU57fuMrjhxHTmQm03RgOMqYLTZs0zXaG/z4HA7suoaOtmNhQYIwJBgSIwkyaWAkUj+JuEEinsBISiQS3aZjd9hwuGzoDh1h15AauFaViLSSaqgHa6YMYTHodo22rkZqG7xoukY4FGVhepXJ4VzlcUo7r3Q4XDYa2n3MYr21fShmLvnCTOIPwO2NkQOvzUXWuNFUz+hG7hjLBtGFiZbG2bH8GGm89acOZpb3xxCe2fPXB//KPWLG47gDKx7VzFhMsxHejMPt+J7Xaut9GZZ+jHvWAf4Mc7IoflpZMhW5OHIiU7nL95LIYvHyuR2cbmnECMSYeLDI2qOlYpqJZMTpsOHZiOdeUGGaSsYeu7xOjl87hnC7AWuyTxtaamhsrcHpdpCIJwksh1iYXmX60SLTj/IrvZWIlP9c677QxMRPPrR83ONnWnk7bK4Ae3HPHRKX7jG1ZHCzeAFjtcYUkeeZMWNc3b+P8thnGTv87BN02XKIrGTw3hInPtTIyEbprMoqJrMIKm8HKAtH7gxR7vK9JPeJEa/LwenWRmQgzlj/PMMPzbv3CqW7pZaJu6pFmZVUqh7s5Q9eZnRqncGJIMUITCEEpy9343TbGbk/zcrCOisLxXWz2WbiwQx2h514jpJBVmKF6Jc2A5/flbJSS4khQTS7YF9Ho6ZaD50dHjz1kqH+TZYC28k8hcxBcqm+DbsepX99f13P9KwWU+x+CytFpi3+DP/rb3WZWjbJ3nMivz2WfulKNcQRCOqXPOAunch02I+chFDkyZE7QwzlLt9D0jBwO+2caW1EBBOM319gZLD0wnI3fpf1maRHmc5GDzPR8lvrrnz3Ve4/LL6gf1tPIzYNHr7ziJ6zHWxYXLg+HIxw7vke+u+UpzMKWFPeafDMPfi7j//um71OPGTw3PkGcCRIeEKsuRfYsK2zDCwDrl7oAoQhqLU1kibfJP18gWuN7SQIMRkey2ueZt3ypcYmPMxNf4h//SUvZmWrIfeJzLyyyzNw4Ninn0sp9trArUV6PljPRHjfgd83BV1LJVFqmobb7UDTQOgauqYhdIGmpX6EJhAidT4nEgYu95GTENZRHV+TknPkzhDdVmW97ypMr/AQHVtndCh9kkQ5iCRUPKZVtDe4CbzRXxFLZsyCTZ680MnU8ByRjZQ1LJEojbUxuGSNVdQsms16c9Z4+7uml5WaxNByf89sQnC9sZ1gcpVH4dGC5mVFvF9w0cvrf/g96BoIPSVqlmcNNkMSXRdoOnzyV/8YSfrzIzD/SX7rq36W1/Oby9Qr79vSX6mi6ptxnXbDBynjcUpA71aeW5/VSErsLXZqbc6tYuWPq7cfzCLO/EXx17q2ir2LneHTueFr7E4M916vXKqqw67fW+u1LtSQxIZhGCSSBvGEJNSSJGFoxA0jVTVJpMb6GnPwFLzo6uTO3QwPYXLrR4M1qa7diuwcOZFpU4HKe5gZWiQRL5/bMB0Djxa4+lQfU0MLrG+59nRdo77BSyQSL3kLxieF1no3oXceEjLZscVqihW2F24eo/+tUeSuuOl4iaoKTD2co/dqL+MjpW2l6mpwUX+5GXHaR3vs0p73JAYr9lFiIkOatsWkREf6Y2TXNG40trMUW2AoTeJPPugWiMxkVKP/O5muS7t7z6Tnd7+ev8AEGJ0o3NWfrJesbx4sVrpfJGZrK7kWNnetc7k1loPmaprOB4L4zvuZy7R8+pZHplhaq9JucYqq4ciJTLvjyH3krMSqIRFKCG4Nz2GzCY5d6SIeTzIxt8pMIo6wSY5f6qDW6SAZT7KeTLKyFsbndtBa62VxaoX52VKkI2Wnts5DY5Of0eHqqM3ZUucicnuI9aXKtXkrVGS6vU6On23n/ncOxvzFSuj295TwWiA0gTQkTd/dw6veVWLRDbh1cDm73sGNnkbsjbMsa6X1Jtg1J7BXxLg0G9ebWpmNzPEwZC7mMhfla/yU+Xz7m987wT/+jd5yTSQr2cRwWbYvoUfzM5NPjLTJKS8rkVkYaS3cTyZHTnEpkbmXRDWIzC0SScnQxN5OLBLByNTBCpproQjTi+sgJdef6uPeW2NlmmWKrr4m7t+d5NK1XgbuTpJIVG4/NtY4id8bJTBffrG9G7Mi0+Vx0NbdiK/GRTKeZOzBDPffSG89i5YwE3zw3UfUdTYSWLHuRml32jj1VB93rxlsJOL0s4mMZN4v8aTBdx4twiMbZ1tu0NkRZc7Wj9SsP5+EfKz+vDYHVxuamdqcYSBojbjcjS4EySJiM83dgDMvJJ3f4e/8sJdf/62mgudgFWZ3Qz7iPJs1NB0P7s/SetbLfMjkuW5SAS0FlMhUZOfIKS67Krmwh2oSmQUhRNkDqNs66rh/fwqJ4M6dSTq76iFpMDNlMqvCQur9ThgcZ2W2/NveTzLNuVRT76Glox6Xx0kiFmd5bo3F6VXG7ptLuomVUGQaCYPungbLRGbXqVY2NcH94TlGT+SfzPZgYYUHC9DqO8+FPjvL7n7iIkevyDyIyQg1NheXGxoZC0/RXwJxCXAy5kO8EWPtRZiLhNIu88FBP7HxYCqRRBcgUpbf7e9yS/1mURVFJUlsenXEC+4Xj5WwbCYNyTFHLfNYKwoX19IfX4VimyOnuByqQ8EOmiby6s1brUQ2rLsRm6G23svs/OPEkempVWw2jYvXerj3Xvky8+u8DmwjkyxMVkd3FcOQ1NR76T7RQjwaZ2FyhcBikPXFwlz4ul0/UGLLaqYH8+/vfAAhuPDcSe4OTNPyo8cAL6wXLvrnQxvM3wO/o48bJ/ys+QaIiuLEgX+zlub7x2lqT3LPMUhCli4OOzgWJLgUoW+iibmWgyKk21NL7O15lu5mLtje8v6zRc/jj15pK3qMvMhgijxoyaxMTaPBe3M0nnSzHDYTA2xujstr5nvdK/bxBNx7zXDkUq2dbiUyt3lSkqAW58rnJu470cKDgYNdTxIJg7t3pjh+po36Bm+aNa3F77HjnJxhYby0iStmcPtdXPrAJTw1HoLLQe5/Z5jB98YJFBkf6nKXvrTV6vwa7V2FN3muafDSe72H2/enMAzJhpZguAiBuZtgLMY3BpZ5eKuT5rWncMsM7VuyUB9u5PirN1j8F3W89xfz3Pr3SxzT9zfCtha7O3VbmXh7iWc93TuvX/K38txKB4nfD2HPpU1yapzcd+jZTH1qS0SmLlsHP0qGuedVLil/hRJPGJx2N5jdgCmW1jaqoruYono5cpZMTdNweRxEwsUXDD7s6E+AyKz1u1mbKJ+rOGHIrMFTI8MLtLTUpLz4Jbr2el02fDPzzIxULuko1dXnOLrbycjwEgMPrBe7Lo+DjTJ8T+sbfMwWEOpw8mo3MysbjIw8tsjVzQDmGuOYJhyP882HSzj0Vt5/sY9Z592c6zSFWvC/3c291xeYMPaeJ9lOS11oJGVxITSe1sffj7k/XeT5j3azcTvMwsgyy6TiCUWOCuW56opqOcwjmnCwvC6plNVwNwf3d/nqZO5n6P4cdX0uApEcWewmd1s8kWR9I0Ktz1385I4YKvHnCcbtdSqRyZNhyWxr8PGoTCLzwuVu7t3P3ZloYWGdc+c7eWBi2XzxOHXqFpeYGpq1fGwzeGs9HL92nPVIksHR0u53t88FS6WP+dLz9Oc0tdfSeKyJ+/0HLdoTX57gzF/t5OGa9WY0Q0pCjuy9w9sCXTjebKH/7QWkNPcQ4tfdHNvoZu4vovi/P85IInd/8qzUPY6FjIYTPPpvB8/VnIkrOW7AIscxcxinMKuU3JrOJVc9CNB3JUdJAZFWG4Zta7Y7b4kDz5lCgM/p5MbJTqKx1Od3biWZag6N677OnWVrhJPn67pSH3GXDnYkdG6c3F7ucbkpIUHfhDdmHl9Pcu2/k60N1LrdpFInxU7RJ4FA89j4amQ8+07JQwCFo3ElMhUZObIic7XAOLEnCdsT0BLMW6ZqAZ3dDQzlYTkMb1qfsOJ26DSurjLxoPwtODtPt1PX1cLw8CIDg0u5V7CA2iY/U2Ol39bulo8Ol53ec+04PA4ScisRRaRu6YaUBENRJieXmUsjMCElDervxvGesLMRt/YceOpYI2sifRZ+13IvxmsNPLyzCGSOdQRwDHi56DpLbMkgtBBntj/EnUTqgcFP8SEKCXvuz53LkplLH2o51p+eO55zDtvccDYy/NVH6bfzg52MLQdMjfNUbydvzuf+br6vpZN3h81/h512G2IuDrXseFFyZaLXu928+yB9cp3X5cB3zE4oWfz5abfptNT7ih5H8eRy+FVGAbh9rkpPoSp4ErofJSKlzyA9fqqVmbk1onlsa3x8iWPHmxkbtcaN7LRrtATXGLtfmc5MTb0t3L9fPvf8qas93H87/Y3faqRhcPbpY8SB0UeLDDwq7pjNv7eAdrLWmsntQq/fK2ylhL7Fk0Re8TEwsASYm3f/H5Y2WFGWwQ+oZwmtd2ot/MafmY9ftYUzhwfkE/todslCw2ie6uzcsUg6hE6b37+zVbnnf2LHmpqOjUiMZ509bGip5K/tu0DqsKXUa2jZXIOA7pY69FyxC4r0KHf5k4vb46z0FCpGa08j9afbGFvfZCEWhwrWd7SCYpNLcnHuUhcPH86SLKDnvdOi88xhE3Rshhi9k8PFVUJkmcsQ6CW2sje21dHe20h4I0rUgAdWZJkDNZ0+XB9sYWLdmvF2xnU6WRaPUk5UCcdnz7D+bSf3hlfYX2C9GKyIYDRE7mtKsb3cbVlEZnTjHJE8oqGkM7NIykcQmv9EeX6XtiZxp986D8bDoQWi8TjRIru99bYVnjSnOBocTZHpO3oi8+T1XqL1XgbnAozNBSo9HUtw2HXmZwMlG//StV7u3J4ouIXJwwczNLfWsDhfeJ9sm13n3OkWhv/w9YLHsIJyi8xQwNrSKF6/i/a+ZlweJ8sL68xOLLO8FTLTddbCbGshuBdeKqoQeToavS6EFJyYOsvSN3TuTATA4pqHKYqXmbuLvqfjfJ2PjaHiym4JdFwb17f+kiA1hHeJpLbO5FJdXmMZWQxxeVkyTZsyTQ+5s7jV6UvrGxGune7kvaHihGtfm8lsdcUBVOLPE8xRtGRO23VW5tfK2fOtJLhsj5OVOltqmVyw/kYrBJy/2sOdO5NF7S8poaGlhoZGH3uSBcTjwH2hbceXiZR1R+xdPxja5NaDeTqevYD21kDF2kaW+7QppkC60ATtvY3UN9cgJSwvrDM/tcpwhjjKSMg6S+D6VJAaR7Ol8ZiaEHQLH5HfPMet6cIfWMxQjsPsRjCdq+xYjokk4zb+9Q/tFzj1XPtoG9/05WedE4HSFfy3AkPKktQaHJ9bxaZrRTXk6G1VlkxFdo6myDyClsxGj5OVfUXL3XYbkXgcWQVlPsxwvdnPwJ/d3vl7zqZx5aNXuTs4j1GAOzsdDoeNY6dbuXfHXEeaXDzIIGzyZWZ1k7abZ9HeG6xM+8gyq0yH03zlA2+Nm46+JlweJxuhKDNjS8xMrDJjsurARmATaqyL0z6Jn1mKz4rXhOCZmnZC31nm0dRY8ROrEobDm6lGEBms47pNw5bj8KerzahpggG3h/XNPPa9lCyMWRSjavIrku+Vymy71nxZWQ9z9VQHt4YLv0Ypd7kiF0dSZLq8R09k1giB3+2gp9aDO5FkbTrATP8MZ14+x4NMokVKWmo9tHqdOBIGRiROfDNGJBghtBYmmTBof+oYd2ZWSy5C9gtMSLUFvPfH79J9oZt4m5+Z6UBR2/D5XDS21fJgoDLlgXIxF4jQfOUUbSOTzKXJdO863YFu14hF4sQ2YyTiSYykQTKRJLxuLpA/I2UWmR09TawsHLTa6jaN9r5mapv96E47cyMLLMwEGLpf+I0yHIqg1bktu5lP/dYoN0834LlWB8C3NvM/n07U1lN/P8nUwFYcrpTYtyopCAGa0Ohur8Nh05HAWnCThZW94koaBgkzD19S7hxeTWroQkvVskxtbee93WVzJJJU8r3c+TdIDCRaNv8zsBZLcPlcB+NpSnw1tfhxkSAWyC4U04nME+/r4+ux/MT9OV89q6sWxTqWyP1ZyjaUU4tr6JoouLNWr3KXF4ZEJf48yXiOoMh88M0HGEmD0X2vr7w7xtn2OpweJ7rLjtiqnRld2WDu0SLB+zNkc9AOffk+V58+znDSIBQtjdspncDczdT9SYSucfHlC8yuR1leLsyK1H28if4ixEo5WFyPQnMLemsLtV4HGgKnXUMOTZIUMDNyMMO4mI4cl16+yKOJNUYflbd9yv03Rzh7vY+ZiWVauhpw1XpYj8SZml1jPBiFYJSO9loWZgJFb0sAfr+LtbUihfg2EpYfrrD8cAWH1w4fyu8y+3xNB1N/OMn8rqS8tpYalsZXt4fHAB6tZp+vzabRWOtB0zWEEGi62Ekc2sYwJAu7HjJHfimIoHZnO7t/Z0Lw2IinAc7LPpodSYytlVP305RUSglTg83g3hAFKSUXLnfy8LV+ouEYl3uas280zaQizQ5I5Bdm0Rq0YVm1V7OWzDwF3U4lrfxnlJOlwEbBsZl1Pjc1XlWpRZGdIykyc9ZoewIxMsTdBFfDBFeLS7J4+OYobX1NxOvcRC3OVs8lMLeRSYOBr9xFt+tc+sBFplbCrOYZ11dIBnmlSBqwEkyl0Da3+Gnta6X/2wOWb0fTNSIlqPmZDqFrdJxqo7a9DsOmsxIIs2qzsTofhPl9jzpSUu93Y1VRJUtF5i7sXjtmTRZ+h4MrgVrGv3ywikDO4uVpSCSMgh+4ikGfXCD8R29lfF8IQcOL52m61L5dbpzw8hp3vnLr8UI5HoyMfe97/S5uG/nFq7o1nYnb1nktDutdZXBykXq/m9Vgfue/Ld8uBoq9HJ7bTVEcSZGpWq1az9zYEhdeOM27AesSccwKzN0k40n6/+I2usPGpZcvMrEUYs3iTOVqozEZzyowhRCFX89K7CaXwKmnT4DPxdj4MhPBKAR3Scc026+rddOgazx4bciyebhdWWriFIHdYwdy19M5XduA8/UNxqfTW9L3i6pqJhnKLlaklNz75v3sy+z7d86zUEDMyO8B92lbIw/D1tViLVFyecnZ2IzR09LK6vpmXkp5I586UYojy9F8FDlEF+zDxMArg1xpr9vZv5pI9dl22jT07WbeJvd9IQJzN8lYgv6/uEVsYJzLp1vwm0jsSBaRZVlJHA3mC0/nS6m+KRI4/ewpOt53iofTAR4+nCMaMWcxra/1MG5RXcttXCWsy/mcP3uJpBf8HUT+YIHAdGarYzKbgJISgUTXBNp+f3gFCK9YYD3VBPEaJ/EaJ4mt3/EaJ4laJ8k6F0bt3u/zxnqEF2PmC+C3OdyMv5E7ua8QC/JhZGB8nmunO3MvuIvNaDz7ealQcEQtmaXK1lPA4JfvU+9x0NLbRGBujfXVDTTYaVan6Ro2m4ama+g2HV3X6DrZwtyuXtxSwsDb+6NHCyMWjnP/z27h9Do5ca4ToaVKBWmalmoXqJH6LQSRQ3rBNHJYG6WUdJ3r3iqdlAoXCQdCLE1ljrO89IFLSE0nsBbNuEwhSODMc6dYT0oGJgqL8ywmxjTjmCWyygTG1lgdW4PPHOztXOdycX7Rm9Y9vp9oNMHlM+08ejiHYRgYSUkyaWAYxh5NKQAd6DzTysRUaXvLZyIwV7rtpp5TJUnDOGAhGfzyIB/4wEm+6V4nWxGjsw4/XbOSR2bcvflozFK3/NmH1+Ogsc6LbtN3prlt9RWa2NmOYcita57YiouV6AmwCQ0hUlbypCGZmg9wrqeFgYnsbUl3E47E8HtUXGa+CFSdzCcbZcksKZFwjImBDG6/pEFsn8UwvhljJVfdvCKJbkQZyyFcuz58taRzKBW5SlAJIZh5tPfG0dqR3epjCI2H/dZZCyVw5tlTrBuSgfFik4is//7ODMxCiVzm6bhQ14z8ZoDJBXP7eCMchUYIb5gT/bUeFxfOtHP/YXkrJdh1zZISW6nkmPytiINfG+aZc20Yp2sZZoOleBSEwIbglMNH+7rG8J+P8CBpUN/qp+948y4PhjgQnSHXvHRFHDsPNtKQGDL1W8rtn5SQazPg5rgHw5AYSYk0DAwpkbsud0JAY7fk9KRt12s76fvbs8Bd78Td6SP0aB0pDdaPORBiK3ELWAtHWA1HWA0F8t5HAGeDHuYmDq47Zw9y9X2d3Bo3d95sbCqRqcjOkRSZhym+SVE+SmEhq1ZyflSLdsW2uAxKCrZcHhzTehdmcGWD7meOMzlpfRa9IFXz0pCpmb/f28Gj3x/Pax8bEkbzKK3V/944bo+D0ydbGBwxb5kqluNddQyWYTvZzt+JgTkYmMMF9Nl1fLVuwqEowcj8nkoZq/NBPH4PU+NLGceqa7AzabJDWqvDxayJMmptjX7W5rKHFKzOAPdTlSKEJliwuLZzpmtdIp5k+NsTHH+6ldG53N+FkIrLLJwjcrs5kiLzCGkJRR4c1jCKkkSNFZvwIwRnnj/NajRhmbjcoQRf4L4z7bj9biYtHzmFLgT1Lhenp908MuEeT4fL7WAzbP6mvhmOMXZ/hivXe5mcXWVlu4rE9v4rQVKX31amMH+Tp0AiniSwVHiMaF7e8hJdPjTd+uOUbUQBMBXB73cS3MxuOQ+FrQ2nUTx5HEmRqVRmdVEtFsTDKjKnFoNc+NwL3P+9V02f2zn3eYH3NQmcfuYka4ak/1FmC1ExWB06e+xsOzPjy5zorLN24F1cqG0i8tUVppYLbwtpt5vvgrRNMmlw761UBnVdrTsVe7wZQwhBTZ0bTRPouoamicf1NDWRil3WBJoQO3HMQghiUjI0mt4y6nTaEBsWteiU2d3llhUoz3GeizyEeKlShPKZg1UszqzRd76Vfi17ck8ohwhVKI6kyKwSTaPYoToyOA+ryAyshgmshrn8fc9y77++ZmqdXCJzp826rmEkDVNHqPdyN0m/hwdjpRGX21jZAeX4uQ6mxpaIReJ5F8k2hYDuzx1n8o9mSGwmrB8/D4L76oAuFhAHfeFm34HXPB4HJ/uaWRycJ2oyZjQXuc5PKeHUy6cfn6f7f6etJL93TA2YepC90mo++q6UnXmsxsw9cKx/nuvP9/LWZOYGFZslasBxFBBHRIgcTZF5SLOIn1SqQ2KCccjPi4GJVWo7GlibMeGeznJ9c/lc+NvqqNOdLC+FcLrsdHXV49EFo2+PEAntFRKdp9txdtYzNDgPy6WvSWqVGDxxoZPJkQVi0YSl427jbXYjPtHMtwKznNQFxUrMaowl13WNJk1j4OsPAGg+Wb5e1u/OLxe1fpPfTTxXAf4q2OWlsGSaFcQDr45z8fku7k2mF+MbmyomU5Gdoykyq+DCoag+nMvrdHc3lCT5oxzE40lqnzqD79EM03eyx/1JKek530Vdcw2RcIy1xTXmxxY5ffMEywtBwgnJ8lYsWzQSZ2Q45SJ1Ntdz5pkmbFv1kEKRBKMjCzQuhzl9toPBB6Vvy2nF9/fUpS4ePZwjEd9V7MbCC0P7020MnoizFNhK3rBAJ1SDpV3u+xwnjzcz+spwCTaU4+0c7nQz1DqdzOeojZvPHi+ZW7sEw5p9oBLA/K152k/5mV052GBYJf4UiOpd/mRTLTGAihTVcjxm+qcQD6a59Mkb3H1gbbHvcjE2vkxTSyMO7xyxLK5LqWlMjS4yNZoSQReePo6vqYbhe6kC1ZnKMkcjcfr7D2Y5Ly8GWV4McvFqDw8GpkjES2cVTsrixj59uZvRgVkSib3VFKUFbUUl0Pu543w7Poex+Xg8zYIWfHsEcaXYt4vsib0vWNWZtRxhiIfFvV0SS2Ye19zIRpyWpSSNdR6W1/d6KtZydHdSKJTIVFScajoa0pDIsEXJCxUitBHF5nJkFZkr83sTUO6/aU3x+3u3JujoqseQkrnZgCVjHqCIE+bMlR6G+6dJJg4K1WSiOIf2tnv8m4E0pYa04oVCtXWk8nqdPLo9see1SMwaIZw7JrM8V418tlOqKQkLzp1iWZhaoz7qo+9cB4MLywS3ssrfG5rGMCRaFcxRUZ0cybaSSmNWGVV2PIQ43F+LyGacuvbyxcbtZ2ZqldXlDS5d6aGjy/p5FHq6nL3ay9D99AITOBBrmg/t72tj9kNu7m65x/djRRmaZKIKLJm7ONHbRGxzb+LHetAi92lOd7k1m7EWk5PK0zJphRXcClYXQwx+axzvbIKbfR3YbRq3hqb5wv/x31gNlj4W+0lDyMr9lJPqOHvLjLJkVhnV1l/rkD+Vn2v2MHNvIveCWSjWRReNxLn73gQzE6ucONlGbd3BtoqFUohF7+y1HgbvTmJkWXd5soB2iAJ6fvA432lfZ3kzs+tQaE+Wu9zrdTJ952Dv70Aggq2AUktPBia/M3le7vQq250baxEefmuc9pCds53NvH5/nB/55f/Ie4O5e8Erjh5H0l2uUGQjsRnlWF8TiaRBPJ4kmTRIGgbra5skMljBtnE4bTvZyhWjyjTyyOActfUeWttrmZ8tvuVgnd9FwOSyTe21tHY2cP+dsZzLboYitJ5sZn7eXC1Ld6Mb/VMZ3OP7qH+hiaZ4Exhs/UgwJDIhQUpkAkCmEjIkaA4N4beBIYnPRTGkwfJfFFbE3UokYLNptLocTI6mL1VV21zD8kwBgr0KycseYXLhfJ/fNJtG6qSxEAue61cXQgRXNzl1o4WhmSV++td/j7/5Pc/xEx97WrnPFTsokamoPFVmyBz61oO0r3dd6sbW24JhGCQNSTSWYG52DSEe3186MFhv8LKyslHGGT/G73ehOyzowW3xPWJtNYzLVUddnYdAoDjXmsdkV5lLTx/n/rvjLM2ZL4De1OAzJTJre/wsvuhmOoN7fD+vBjNk3W9fgdMdsm3vfSPoEo6Z2lKJEZKzPY08fD1zDG/nhR5qW+vZKkAAW4XcEekt5Dsxh7sSxt2d9Ryv9YJkpz/4437hgJSMzK3kZXG3axpOu44kNYbdAuvybsx6yPK93KXc5fmJzBPNDfgcjp39I7abnm/tLl8DNPdmCGXZt0uFEOgJiR5Kst3fffdHFUFBa3sHccPgnddGWHkU4Kd+7P3U1nrymvORo8rue6VCiUxFxTks37Wpu5Nw93HjwZqWGqir4fLpVjYX10nUell77xFdNxsrIjIvnm5h+I/for9KW73Nzwbw+V1cutKTyuxOJJHJlHBIGpJwJMb8wjrJHCnK4wtBek63MjGYvnaf0ATnb/Rxd6vTTT4IE1boxjMNjF8XLIYOlnQpFbYqiWxyC41bWQQmwEZ9I2Mr+1z72Uq2pIkCOFnv5+5SdgFvz9MkeLmtgYffHEaQ0lHTlLZpQEbyvOAVEpNZY3NwdzhzhYx6n4vVkPkEx8sNTUymCY9IxwPGee/VEX7lV3+A48dbTG9D8WSiRKai8hwWlbmPxHYRbykZ/c7QzsdY+7NbXPjkDRZWNwishvHXuAhvxIhEStcd48LpVu7/7rctM0DKEvncQ8EId99LxYue6Wtk+L29LmBN12jrqKO22Y/dZSeaMBiZWCa+Kx5xPRih70wbpBGZHX1N6Dad+2+PFTS/6f4ZcGW+LLZebWbgTJy1MrfTs1U4Ga2m1k1PTyPvff1BzjOjAl0QqwK7y47DoRPbyrA/e6UTfDrJ1TgzY8s7Fl3druGvd2+17NR2LIMSicNhI7i6SWRXkXNRQNJYrkuq3F/wNAf5HtO5uTX+h//fb/If//PfpKHBl9/KR4RqS0UoFUpkKhQFkoinROP2xWLnOiwlD//obZqPtdDhcTD9+kPOffpmSWpvaprg4okm7v3eK5bKwnIIhXTJMEbSYG5yhbldBfHrGn10nGljYHQBI2FgSLjzYJZLzxyn/42UVc3tdXLifCf9744VVbQ8tLpB7zPHGZ842E2m47l23u0IsVmBmNtKSczm1hpam/0MvjtB/3TA1DlmSV3HKhGq+dTSXK01mL6o0eWqxa3b+NbGImwCLuBsajSQ1HkEC9P7zLfbnzce5/q1DgZeG9t5SyvArZ/Lc59vjVBRwAGJROKMji4qkXnEMX32CiF0IcR7Qog/3vf6vxBChDKs4xBC/IYQ4q4Q4rYQ4qXipqt4Mjmcj3TJHAXHFx8tMH0/5WKy+hMe62vk8skmmtfXufd7r1pe06UcBRjMGucCyyH6XxtGzq0jlkK02DROHmsmHk2ASLnG7U47995+ZElXnDqv88Br3R/s5s22dTaLrKVZKHZZWpnZ09fEuTPteAFHLLnzszSySP93RknEzH/uJ8qSmefpJBFMRkIMbgQyL5TjHH1veIbT17t2/i6s/FX2beTforSw79XEeIVCEhRVQz6WzC8AA0DN9gtCiJtAtkJ4PwUgpbwkhGgB/kwI8ZSURbbsUDxR5Ou6qRaSCQN/jQuZo+f52Q9dYjKP5JNcOJw2Jv/kTYwSlrQpWYs8C7axPL/O6lKIvtOtNLfX0f+utVnXwbm9GfA9n+zj2/aFirZ1tFmcpLLNydNtEE0wcm86ra2qsCNUnu9zvF5DCA1dF+iahq4JtC33syZEyh0ttmxwAoaTURwvdoGWsq4IHr+/8yMEyJRQFgICq+bjFg2TQix3oXm4PbnAlWd7CUys4at3QyLPZLkc19R8y/gV+l2tqbGudNkTx+G0reSNKZEphOgCPgH8KvCzW6/pwK8DPwJ8b4ZVzwNfA5BSLgghAsBN4M2iZq14ojgs7d0OICXRW6P05yhrpLkdrE1YV9IlFk1w5oVzDH39nmVj7qccR6SY2pFG0mB0IHfpoEKYHJjFd6qFYDBC72eP8834bMVvCDYLH8SEgDPnO9lYDjG6JdAP42OeYQDCIFX61PoHruMt9QQ3rHs43MasieX2cOr8ts9E0ds0kjkeZvdsI8cJW65S0U8/c6I8G1JULWYtmf8c+LuAf9drPwN8SUo5m+Up5zbwaSHEbwHdwI2t33tEphDi88DnAXp6eszOXfGEcJgDoI0cArMUtLTWYGxUpkSSlVStW1VKerrqCNzw8M1QaYRsJdB0wbkLnSxNrDD4hjVtRJ9kGl0eplnJvWCeGHk68uLxJDc6utmMxVMJQlKyEgxjGDL1IyVJw9j5t2FIBsbTV17YIV9LZl5Lpzh5qlVZMjNRgc47lSKnyBRCfBJYkFK+sx1TKYToAD4LvJRj9X8HnAPeBsaB10jzyCml/CLwRYCbN28ekV2v2OZJPuDnP3mdiYXspW5sNi1rkfe6Og91te7UzSQpqU3EePDKgNVTLTvlcMkXSrRR8GoVCcxib0gNTX78dp2B10asmVBWyvSNLuXpIyULJovy5z10AWEXE/MBltate7DMdwaFnH+f+tS1/FdSPHGYsWQ+T8oa+XFSeXI1wH1SpYKHt24UHiHEsJTy5O4VpZQJ4H/c/lsI8RowaNHcFU8Ih9ZdboLwbIDuJj/drTUENmJM7sqadjptnOmsJRmNc3868w2to8XP4B+8thODWT3Sp0iqV2Oy+O1JxPf6q+bM9GIruOfLydNtzI8sMLmWue2llVTLPiuGjuZa6hv8NPTWpD7P49IRBz7f9t8TEXOiNA+v9w75uMrNkHdr5QK+q+FNi/rYKw41OUWmlPIXgV8E2LJk/pyU8pO7lxFChPYLzK3XPYCQUm4IIb4bSEgp+62YuOLJ4Ul2G4y989gteer9Z+nsrGdjI0poI0rDaoB7b/TTeakX9McZzU3NfpwOG4FAmI2NKEOPlvDW+wguFN+S0TTlKGFUxZbMzbkNztT08mDdendpIRTaWPDSlW7uvzZSviA8wMhRTP8w0NxWw+sL0yUZuxBLZv7Z4DnmkOfyhZQw+tM/vsWHP3yJujrV+Scth/9rYgrLUxaFEJ8WQvzjrT9bgHeFEAPAzwM/ZvX2FIefJ9mSuZvBbz9g4Zv36G5w09fdwPxgqtXg1N1xLp9o4uLpVvr0JMtffofZP3mDdlJ1OI/3NpZXYFImTVLFIhOgbV2v9BR20AtI/Ll4qYv7rw6XVWACJJOHu3iIw64zGDxYJ9UqjAL2j25xdYF8j1Eh39TJyRV+8ed/h6Wl8nXGUlQfeRVjl1J+A/hGmtd9u/79JeBLW/8eA84UM0HFk89hLWGUL4KUFUOshpCR2J7X7/3X1/b8DTDxzih9F7qZ/3bpssgzczSOSTaMwXU4XelZpCjEkrS+WJmb+2EXmefOtPOdElkxoTBLpsNm7QNPPF+RWeA1enBwjh/5of+bl146yyc/dY0LF7vQC2iT+aQheLI9eLtRHX8UFafKDVqWIYTg/M0+7n79rqnlE5EYE++UI1HjIEfFupyNwJ1FOF2Te8EyYH057tIRL2H91j1ILH8WOt3bzJslFJhQmOvbapGZN0Xs52TS4Ktf7eerX+3H63XS09NIS0sNLa01dHbW09vbRG9fE7W1yq3+JKJEpqLi5B2EfghxeZ109TZw95v3Kz0Vk5QjKLP0myiGyGIYv6OJYKzyCQx6ATvLbq+MMCnEHVwNNNd5eZQMFpxgZZZqsGRWio2NKAMDMwwMzBx477nnTvErv/oDFZiVopQou7Wi8jzhGrPvXAd+n53BtytjlSyEUh8Sp8tOOJakrr0WvUJiyAwtTmutK1oas73bZsOeI+ZOK+CAOCpUo1BoVf70kAabrmFvcbIei5Z0Ow1eN5FwPO/1Ki0yy3FEGxqPWI/zVNHTyvyUEWXJVBSN2+vE43MRWgsTjeR/AbXilNc0gd1pw+6wo9t1pJRomkDXNbStn8BSkGg4ZZXSbVrO7GYjaeTdStDtc9Ha3YDH50QAq7OrjL4zXOjHqhh+n5OeY02pfaQJHE5bap9pqVZ8UqZ67wkhQLDze6s3384xlVuO96QhiSWTROJJloNh1sJR1tbWoM6B1tBIS6OfOq8Luy7QESlRZRiQlMik8dj6Y0ikYaSukxLQBDabhhaKpVoEbvUQ3G4laCQNFqdWae1rSq0vUutpXhthD2hRA7ndG3rL/eqQW3VLJYQNHy2Nvu3VHv/efVrsfmP7BbnrBQkyKYltJpidWqOhyUt0M0E0Gie4HsEwktiRNHmceLwOHA4dj9+JzaGhOzWkLvCFoe1GD+HAJlMji6aOoV4psXcIHxovnG3nO4sHrWtWIyVEo/lfI0vVVtQ0ZTimx483l34jirJzJEXm5WdT1Za2RUQykcRISpLJJMmEQTJpYCSMnb8Tia3Xt37vd+/qNp2GlhpLYgsNQ+6Zi5E0tuaUJJEm1snhtNPcWU9rZz01DT5qGry4vU4S8STJRGqdRMIgEU+Q3Pl3cuez6DYN3aan+v/adBxOOw6XHYfThsNlx+ly4PI68PpduL0u3D4nbq8Lh/PgqZNMJFmaDTAzvsTqYnCnF7DQBJFwlEg4BiIlCmx2HU3Xsdk0HE47Mpk9jksIgc2hY3ekhKTNoafEoyZweZy09zVjy2ERM4zUZ7fZdTSTF+1k0iARSxCPJVL7X8qdB0EpU+dOPJYkEU+QiCVIbHXl2E8ilmBjbZNoJLfrNZlIEo8miEVixCJxpCHpPtNBXbN/R/RqmmB9OURgcZ31lVBaF5xu16lrrsHusKXEoSbQREooatt/a/v+1jXcXhd9F7oQQvBf/usb/Ov/8C0Imdpd5tn1ZTEMydziOnOL+Re/9noctAk7M0MLmReSkvn+vQKi8a+c4tbSAqQx9j3T1Mnth1txebesL8i9ETp4DggE4XCMcDjL+aHDzWONYFJkLk9a18o0Hywpt5NhCCGgt7MBl8eOlBKBtrU9iSEBQ5JIGsQTSRLJJLqupYRdLEEkGiccjad9cBwMFV6qyqlpeO0OECmLqE7quqQJDU2krhOa0JBIIokkjdeaCNxbZSMYQwKtHTV4Glx7rIXbzy2GlCTW47h0G/W+7JZpXdNwO2w4bTacuo5D09C3Hrj2h6/awgYy1aZ960dikLq2GVv7UiJJbr1uK0OY7VErdaQSf55gXvj4VV74+NVKT+OJQ7fptHY30trdWOmppEXTNBzO/CwCuq6hux043Y4Szaq6qfbr4In6GobeGs++0L6nv9YrLby9lFmUVtpolA0Z2sA5M09dax01bXU4a73gsBM3JJuRlGV0bS2Mz+diYaq0NT59NW6czq0HP5uO0AThjRgJiwuHb3Oir4nJtghvJVLlherui/yz7m3gtNvxOO24HHacdp3mGh8yniTgjOEXdnRD7AgACTvW8VQvwO3XU3/LmGTi0RLBjTAXLnby7njuVglrhEADW4MNTQiCxzQG1pbSLyzgpbpWhv4stzckSepZ0OrnQYAcTSotYWOj8rHPCus5kiJToVCYo5pzss6faGXw26N5x4tFL9XAUmZrYDV/ZoEgthFlYXSehdEMt34h6H7xLJGeOjw1boSuE4nEWVoIEljZKKqcQ9+JZhwaTDycITSzkVbQ9J7roPNUM/dHlvION9lmv7fo/Pl2XvXMkkgUf3Ci8QTReAJIdUBy6DoT97JYwktEYitBypXjhDsqFq8zZ9srPQVFCVAiU6FQZKaKFVdwdCVvgdl2s423sghMmyaYnS9v4XvLkRJd13nUP3ngLY/fRUtXA946L1IIQsEos9OrxGPZ/aE9x5qwYzByeyzn5tcW1xkfmKG1uxH/8SYGR5byFra7k4cuXu/k62LqwDIOu048XrzVNJooU8mlDOSKDX/SRebly9184IMXOHGipdJTKR/bcQpHACUyFQrFoaO7vZ6ldw4Kj1xsnPXCUuYe3lea2rg/UL3d4Q2zWi3DDSwcjDC2r3yMpgnauxupa65Bd9qIxVJx6Ta7hsOmsba4zsTdHCEJuze9te35yWXmJ5c5dbmHsM3G9Jz5+FZh02iq91J/1s/X4+mPs1XtK2OVFplFvn9YuXChk//uv/8g5853VnoqihKiRKZCochItRoym3wuMkSxZaTjmQ7eWMq+lk1UcUAm5vuX3/36PS69fJH+9yZy1q00DMns+BKz4/nu0Uzj7d3eyJ0JAFo76/HUuFPZ9lI+FsL7MlOklNiMKAPHQxDPHGFoVcMAm0VZ+IVU1gAT3Zyq9DtYDHa7zv/0Tz5LTYXKbFUD4nCWk80bJTIVCkVGqrHzT3d7HRPv5WfFlEDgpBOWN7IutxgNFzGz0iPyOB53v36P00+fZGhgroQzOkh0M73YWpxehWlzGe8nz9XnNOGJvXWjCqbAsFHreFJNlVlwue34/a5KT0ORASHEvwM+CSxIKS9uvfaPgJ8CtuON/p6U8k9zjVXdj+0KhaKiVJMlU9ME1051sHp7lvB6JK91u1/o5uFy7mzr0dXVytWXNEOePaQH3xzm/I2+0swlA7ECLXp7MfE5Lbp7pZKALKCKT5tqI7ge4ct/ea/S01Bk5t8DH03z+v8upby69ZNTYIISmQqF4hDQ19XACY+HB98cIpnIz88kgeUec04bmyZIVty0ZS0by9bX+syE0223ZiAzGtOKwsRAKGJNl59cCTwZ18vw+k4B9ifrdNzhf/9nf84bbxyeLmiWIyv4k2tqUn4LsKQGmnKXKxSKjDj1yj6H9nU14NxIMP7mZMGGoq5nO/nOirnrZb3bTZDqdZknC0g1nnu0QEt3S8nrZgLYHbaM7vK8MHHaWaExW+t9eNwOPMJACIHLZSeJZCBTeahs8yl0DlEXtn0PNhLJRjCKz+vCbjrb63ARiyX4B3/v9/jFv/cpPvDBC5WezlGjSQjx9q6/vyil/KKJ9X5GCPFXgbeBvy2lzBn/okSmQqHIiDG7zqmeJoYmrEkKyYdLJ9sYeXUUmZRFeSJDJ1ywZK5EdYfXz8MqFplGAcoqEorQqpfHHKZb1WO7TNY7u64zvhDANfNYGDsdNs4ea+HBo/LUzgwGI8wtpbc2hzZinKx7cpNjDEPy6//rn3L6TDtdXQ2Vns5RYklKeTPPdf4V8Cukvp2/AvxT4CdzraREpkKhyIg0DJa+9oDz332e/hLedGtr3HQ0+nEbEA+E8da4uPvqI2SRZWoaTtZzO0dG+TbNHg+rc9kTgypNskD1NdE/ha2uJm1rWiuxTGSaENMdTXUkEkkQe/Ozt93WglS9TSFAFxpCbLW5FQJdpFKoEkmDxqSHDR7XRo3GEjwaW+LK6Q5uD5rvZ17omfqEesNNE4sl+N3ffoOf/bmPVXoqZeWw1T+VUu6Y94UQ/w/wx2bWUyJToVBkJbYZZ+xLt7n+qSvcm14mZoFQ0XWNvo56ajWN5fszLN6dZWLX+yefPpGz9I4ZvDdbIGAuu7rFcDMSWC56m6UkUaBJt+tMB1NTpS8yr1sWXpH7Djy7sk4kVnzSzqXuVkbZu2/i8SR3+6e5eqGLW9t97HNQeEzmk+kOz4eNsDVxsYrSIYRol1JuFxH+XsBU5pYSmQqFIiPb7f0E8PCPblPX5KPh2eM8GMvcNWebhjoPTbUe3LqObkiMSJxEMMrGSojViUXmbk2zLf9232YdLjvDj3KPn3PuwHAiaGpZh64xMl3dAhMgUaDdS9cEPZ1+4PExlYZEIqltbaD/dv6F7dOh6VYJpvIJL2cW5R4IhLl6umNH8+7sfZn63+6j4XY7SzK/Q2bwyhsh4LOffbrS0ygvkuoq3bEPIcRvAS+Rit2cAv4h8JIQ4iqp2Y8BP21mLCUyFQqFaTaWQsS+3E/djR4C6+k751w41kJyKsDEt0cwZwPaS1N7HVPrxVs2Wi42827InPtbFxrSdKnzylGoDdlu13nw5mDa90494yh8QvvQLLJkSjOJPxZsx+2wMTqQOclnYnqFCZMn8ZlTbQXN4ai3lfypz7/M2XMdlZ6GYhdSyh9O8/L/W8hYSmQqFIqMpHvYjkcS1LocB0Rme3MNDRsxxr50GyhcBHhr3GCByPScrYeQuSxhTYiCBVw5iRdg/WhorWX4raGM7+/v0FMMmlacyGxor8V4thuj1wvkeECwIL38XHszDyesseJGo4Vm1ec4pk+oN93ptPFTn3+Z7/2+fPNPFIcJJTIVCkXeNPtczCw8jmM72dNI4JURxtYy9wU3i8NtjWVtzWWAuaTyguPpyk1cGnkXN45uxrIKMmlhXVCtyEL29c/08p3NIOca6yBHpIMVRyyxZkXh+BR2q5KennD8NS4+8pHLfP8PPEVLS02lp1MxnnQL9TZKZCoUiozIDJazof/vFn0nWqg/0QyaYOQrAySj1tgChQUuVwmMBc0nuhwOiQkRKfHkuc7G+iYX33+O21+5k/b9lellzl8+9vgFua+ZqJQITWN5dZP5ycy1NnWbRn1rDZ7TqXNia2Wy7l0pUwJYSgxdcDuRKh/lC2h8d7xzZ4RtBAJJqqRVvyg+hnZ2wlybSzPY7To3TnXueW3765NR40tY3KzuigZW8td+8kU++7mncTotKtqvqHqUyFQoFHkjgMWRBRZHrC9rlGfnxLQ0nmpgKhorfqAqI5xM5i0yAWKRzFnYgbkAgbn3TI3Tda6L+q5mNIeNSCRBaH0Tm13H53cx8fYgi4MT3LnZUVjw6G6vfSCZMxlJHCuufmSd10XY4pJVt/rzd713HstRH/IJsXh9/qdf5gd/6H2Vnkb18IQc11wokalQKDJzSC+E/tP1kCx/AflSY4hU9n2+/cHHBqa59PJFNgIbjL73qODtTw1MMTWQWUjVttYWPHa58TodBHLFfZaDQ/ody4fnnj/F537wmUpPQ1EBVO9yhUKRkUzu8monXpff87Pbdnjcdy6fK+91YpE4/W+OMj44z6WXL5ZgVimMpDUhE2bOuo98V4xiqga57BbbWA5JXG8l+NwPPnNo4p4V1qIsmQqFIiOV0ZjF34xmk/klIPX4a7lXDVYtE7i8TtaXzNX/TMf4wzk0TWBYmPCzTTJRvjJQLWf/kk/aPkAolEq4kXL7fBW76lmmIjjlzm9gazlHUjJ327r5FHrW7j4KNW4nnQ01e96zhw+3Lai+3svFi12VnkZVIVCJPwqFQlERRJHK1tXgYihgPunHZbOxNFe4aCs39iKz71u6GlifKU0ogWFR20pzZ4Ck7sSfUlfgNnzhp3jlj1oKXPsgxRrqatxO6h0uBkf3xjk3NxdWf7NaeOH9p5UV8wijRKZCoaguirwftVxvYwhzWcMum41TjjqG5g9P/KbNVZxr3+MrTWcagIQFbR5TmJGZxVn4kkkXje1+lmeDaLpGc7t/Z6sSydZ/qdNx33R2/hSpGqsAuruwEkZ1bhf+7lbW1zaZWggUNEa10tfXxI//xPsrPY3q47HZ/YlHiUyFQvFEEW6zgwnNWOd00S49DE0eHoEJYHMXJzJLaVWKbVqT0W+un3dxrvlNbAzVhDl3so31WJSBwHpR43nrCqv5uBYIM/mEiUuA3t4m/tk//1Fqawuph6B4UlAiU6FQZKECT9tFbNLX5uXuSm7ReKq+gdD8Jo+Cmes+Viuao7jL9uxE6Xq0Ry0SmWaQRZ6bsVjK8jiwsGjFdBCA23Xw2AgEUhwUztta/7Am12Xj4sUufvlXvl8JTIUSmQqFIjOlSA7JSRE33fqXukgE5rIuc6W5lUcjS8Qsih88bKwVkTSUi0QsgSZTpZaKwWxMZjHEE9Z26JEarNnzP6dq9ez1Pg+bBv3hH3mWn/hr78emOiBlRSX+KBSKI4+VLQdLTW1PLe+Eslulrre0MfBg7tDduHcjE8WJ40QswbnnzjDw2kOLZrQXlyYIF7uDVZ7IDodlV7S01PC3f+5j3HzqeKWnoqgilMhUKBQZqYgrr4BtSkC82Ex0KbPIbHC5GBleOtQCE8CIFW+BHb43jc1pJxG1rnf3Nk6hEZbFzdGMBb3Y42i3la/cUjYO+/kI8NTTx/n7/+DT+P3FdWE6UjwBx90Mh7sAl0KhKCmOCvQYLuTa2/f9p7mbRWACnK5tJBq3Kvu5ciQtyOCua/KXRGACOLTibW9m4i1lkYk/DkdpPv9R48MfucSv/pPPKoGpSIsSmQqFIiNN7RVoE5inyuz5YB+vhudzLhcNl05USCQeb3H1K82StCCW1OUs3aVfs8DBa86CXpwpyOmIFrW+VeT8qFVs6jx5spWf+zsfR9eVlFCkR7nLFQpFFsofEZaPi77zuS7ecK4hTRi15patS3ix2TU6e+rwNrnYtCeYCK8zF9nkfd5O7r81bbIET2EkosVbMvUSJmVYIjdMlFkqNrvcZo8Utf5BSnPMq1hjYhjyicyOLwcq8UehUBx5jGTp4taau+oJLAaJx5JcfOE0UkqE0HB5HUDusjJt19q41bhJIp57jn6Hg9Xl/FpN7qauzkX78XoMDywlNhkPBlgylmBfacXXQlNcf6GdtYEQy8ulaVOZtMDlPzu5ypUPXmbgtQdF17asaW+g4Xiqc87y8GzRmeXmKe4uLXRrj484KkF2uxgdXeC//OfX+Ks/rgquK9KjRKZCochINJK/i1kCPWfaqW2tJbwZJ7ZteROpQuApI5UgFNwk5oyBE+7entpZ/9zVHoQukMnsN215oQZ7YJVWTw3hRJylWBiZwZrU7vUzQX71ISWS46ebkC06t5fnGNsMgwmd+u7yLPY2je862cvDu3MEw9a6ZeMFHJP9JOJJ7n1nmIvPn+X2V+4UNVb3c2e5N58SbGc/+hRTWG0hLA1SWP0QUCJ1XeXa9T/+5qs8876TnDnTXumpKKoQJTIVCkVGEjmsZhfef5aNjSi6TUPTNJJJg6WFdSZm12G2sA4qSQHyeB3HOhpwIpDxJEbCIBlPkogl0XQNT6uPuaENHNNhQoQBaHfYaGnxo9t0hABN15CGJB5L4mt3MXPdhV3TaXF68MbtLI6ts7gQOjgBITl1vpVgbYL3VhfJU5sCEE8ajE+tEnNKrvR0cm9whqRF5aDqTnTi62pB1zWWhqbYCITTLnf+A5fZ3IylpI8Qe35LKZESNpCc/OA1YLvTnSSZNHaEjdx+A0h2NGBsrbebyV2W0NGpVVo+2YN3yxcoJRhIkoYkaRgkDGOnVeN2O8bthw7B425ETpuD011NJA2J3abhcju4OzzL6b4WHDadyGaM4T/4JMkkSAMSCTCSoNtSv+MxaDtWT8BYw+OVuFwSfV+EwJK08VRN89ZsJNKQGIbESEpkUmJsfVBppPaJNCQtDX7WQxHsbh3doYNdS/k9hcCV0HmquwMZlxhJA6EJXG47m8lEap/t2XGPP7tNClr9Xgwj9WCz7X7eDrmIJgw6PtoNSHafQlLs1p97gwck8vEDl0gds/3v73zunaLwIIXcOj9Sy8ut9Q8gtx4WZWqUf/nGm/yLM585uJwiPRI4ROXhikGJTIVCkRFHjj7ZkUicR8MLlm5TGgbhzRj3R7IUVV8JHHgpGkswOZW+Z/nxy16WNlNibHZjKzazETp7a2h3+nAYGlLApkgwFV7nrc05TLY/T0uN3cnMSkpkvz0+TXubn1a3l3sjc0Xbu6ZG5kkmUiEC7ho/F6+f4P7X7x2IjVtZCjKfYX/ki8vtIGgi2jIWTTAZDDK3nka854G7vY3Jkcfnlcdtp8ZuZ7B/5vFCQ9nH0BxO3pve3icH97oukojwbF7z8ksb42Pm25D29jYyvFRcVyldFywfK2qIkjM4tU4knsBlV5JCsRd1RigUiozkKmFUkmfxEgxqZLjSTYfWmQ4V17M6HXahk+SxW3t2NcjsapDe7jqaPR4mZlZYDRbmVrbZ9R2RuRmKcv/WJD1PnaamxolMGoBA6ILRQevEv7fWjdm0qUjC+jJR4c04bOYXJpAr+SopodbtYCOPmNR8jU9WONATyW2rY/WSMAzmgkH6GuorPZXDw9EwZCqRqVAoMiNyZPmW4tZn5IjFLARZ5gordk2kjUwcXwowTgCAllYvDT4PNi01OSlTlR+3M3aN3T+GJCkNkobE5lsmuk9wTQznLuFUDP4GH3Mb5sRYrMiORGDN/ddEgjo+jzMvkVkJBOC229is4hqvp5ob6a2vq/Q0FFWIEpkKhSIjNo+D3uvpfXVSwoxF7tjdGIb1Ge1GmeuFuDU7wRxZQgvrGyys5598UmNBsfN8cde4waTITFhw/HQrHl9k7jHy7a+db7keYdGx8tgdVS0yv//KhZwPpIqjiRKZCoUiI/G4wZjFMZe5KMW9yoTesJQOzcfC/vpGFlGJm7nmMH+rsKJGqM2CA2amjmapd6VVw7urONbxeGMDP3rzSqWnceg4KnUyVZl+hUKRkaQFrs/8OdwWkW5XDYNDuet8FkwFdk8yDzWmW2C908rUVjxfwZ5v3XGrHggcWumK5xfLr3zigzht1SuCFZVFnRkKhSIj8Vj5RWZJLJllirJvsLtwzAtWYqVrYVkJS2a0hEX502LB5kpxzCvV3aZaXdE/fP0yT/V0VXoah5Mj0ilJiUyFQpGRWAnFUjlJ3NnguYZmdI9OtEHjzcBM7pXyxKvZaV3zMLEasHzsPVRAb2xEzZ8HltQDteAGXIp7eKUsmdUoMVt8Xn7uAy9UehqKKkeJTIVCkZFKWDJL8Xw/PxzY8/f7P9jFt6W1QvOy1sKdhfzqLhaCppUvykmza/Q8c4LZlfQF39ORNNNIvgwkS6AyZYU+Wyk+S7H8g4+8hN/lrPQ0FFWOislUKBQZicXKnNEqJY4ymG1GvjpFq8dn2Xg3fO3cGS69wITyJTG1nm+n5iPn6U9ECZrMLLcKKz5iaURmnitYdKyMKhHu23zXyWN85OypSk/jUCNk5X7KiRKZCoUiI4l4+SyZNptGt0cw9JfvYSvxlUkArQ6PJWM12N3MjK5ZMpYZyhGf1/3UMcbrHEzMB6ircVelu9YKSh1jqVl0rGLljonNwd9++fmqjRNVVBdKZCoUiqrgbHctkw9nSSYMWr2ukm+vLlx8tJADjd5NP+vhwrr3FIJWYgXedrGTRy6IbT1g+D3mXaISSFpQJ9MK7Wcm8SdfkWlUyG0dSVRPbPS1rnbOtjZXehqHG1nhnzKiRKZCoSg/UuJw6Hi9Do711HOuy8+9b/bvvF2jl75ky9hXZzhd21jw+jU2JxfiTQxOme9lbQV2r6NkY5/44DmmGpyEI49FjceZ3/Ys0WFlGsPIN0mpQok/1VSI/QeuXKz0FBSHCJX4o1Aoyk53Vx2srLG2EODRwPiB9z1leNpOxg1if7bCMx/r4I21/JKA+tx16HOSwdXyCkwA3ZO9n3yhHPuu09wOhg5Y62x51L0UgMtuI1K0KLIgu7wEW8nfkmnNiRwtQT/4QvDY7Xzs/OlKT0NxiFCWTIVCUXYmp9cIOd3YM3SSEcHyuJ/jkSSTfzDFhTrz7r/rvjZCI2HmVoMlnFkWSiTA403etCIq3wSaYw31xU+mTC49aUW5pSxYYckUQpTbw5mRj58/jS9Py7biIAIQUlbsp5woS6ZCoSg7fp8Dx9o687OBtO8vj8zDsaayzEUAxqtBzj7XyIO15azLPufr4vY962ts5oORsD4JRLNrPJoPpH1vZd18+SKAzQdrPHO6nTcWy5Ntn5ncN9O8LZN5Lq4Zguvd7ak/tvXmnjEkgm0RKXcttGsJv8bXY5U957b5visXKj0FxSFDiUyFQlFWXE4btYkYU+OZXc0LE8vUn2tnNVKehIf1+TD8QZinLzUx0h1hOXJQz9YSBAAAK91JREFUWPW4a7h7v9LCqTTWt85rvdzPUHB9ZnGdRp+TcChqaiwhBcN35hAdlW1qYmbTecdk5olIGgzcLe6cOftct0WzKY4Wn5fr3R2VnsaTQ3UVDCgZyl2uUCjKhk3X6HALpgZz33j7XOV3y03fXeLMUvr6mT1abcWyi3djlKBAvqs7u4u7rbchr/Hi8SQnmvJbZw/lSvzJ83jm3arSgs9RLYWCPnTmhGUlmRRHByUyFQpFWRACjje5GL0zYWr56OhiiWeUnrE357iYLkaz/M2P0pLMo8WjWRai2Yutu2rNl5Ry2FKVARpt7oLnY0n9ShN6KF+rcIm96yUcpHi++8zJSk9BcQhRIlOhUJQeKTnXVcPgWyOmVxm/O8mxGmsKpueDAHgzTKvHu+f1vK1YWzjtNpr93twLmiRpsSWzobeRyQzxmNts5JHd7Lanst/X5zYKn5QFrkQzAjJ/d3l+y1th96sGjVnjcvJ0b1elp/FEoRJ/FAqFwgqk5OLxRu59837eq3onV6DGmTKDlpNAnPbfj3LydA2aTSDjEmNzhQtBG0Y8ibPOhaenhkk9wuRq5m4/N9vaWP7yBJG1VU63+fA2eZBSIpPgOVvHmyvzJPMUOsmIteVsmq50MTabPeFpZmk9Q1rKQbYP1dT4Cl1X6pnKsn8yYsGN0Ez7zfwTf8rvLq4GB/WHTp/AXobatYonDyUyFQpFSbl0qom7X7tX0LqPbo1z4Xuuc3+1CKtYnugCuu1uhlZWCX0nQ2b11DrcW0ACzzzfTaBF5+HiY6Hmcdq5HPcz/vtDO68F50IE50KPx3iwyDMfO8FrwYW85hdd28xr+VysarmF1nooQldbDctz66bHFYB7IcmZriYezudXT9SKVt1m9GPeMZlVEJNbbgTwk++7UelpPFlUoPNOpVAiU6FQlIyLp5q4+9W7RY3hDpSnZual7haiCxuE1iMM3TdXMkYAE69OAnD9Siv6qRoANt9ZYvzRwSLz+xn7i1FOf6aXwcXslsTdJKLJg9YtIXD6nUTX89tX/tYaRmdWTC3b1FGbl8gEmJ9dh9l1eho8tJ9oYDEZYXQp9/b8ms61nhaEXWNyOchiIP+HDDMWwFJnlz8J/NWnr3G6pTzlxBRPHkpkKhSKknDuZBP3ihSYANIwyuIz1CNJJh8V3sFn9vY83J7Pax1pSMJ/PMFzL/dx11gjGMmegCPEwV2hO3TqP3aBBikY/NLtvLbfdqOX6cVVU8sKt7nbRbpDFVgJE1hJWYWPNftoOVHHW7OzGS2JocAmk++lxLumC65f7WElEmUzmiAaT2JsmTqllBhGKlpWytTf2z+GCXOoYUGf9SeZq53t/J0PvFDpaSgOMUpkKhQKyzl1vJGHBcRgpqUMAtNp03l4e6r0G0pDMm7w6C9HOft0B285sotMm7Y3V7P5dCvuyx3cG1+kprcl721vuMzH2a1tmquTmcujvLwYYnkxxNmnW+mfy1RB4PEgRlJy/53cVuHdCEA/mbuEUr4deXSvDUficWmtAx91/4e3F59bW6mYzHqPm3/52U/hsCmZYD2yskVky4g6exQKRUYKybc53tPAo9ceYCQtshKZzTg55Ey+OUP7J9qZXQtlXCaeNHZ2R/dTx7hPHMZTQm1pM4q/1U9w3ny7y0xdftLObz6AXRfIZPabY8KkddCfLO3tx0w1AJ/HSTRmPpEqFk+wmUcJqWqoq5ovvfV13Ozp5Meeukqzz7qqCIqjiRKZCoUiI/neI7s7a5l5b5hEHjfuXCSjcYRLR5ZQadpsGiff18v0vTk2THa2sRoB9Dr9zJJZZAK46t1EVzdx9NbD+OOkoamFNeip5caNXob+1FyilcOumxZZ8XiSnp4GZh5ljx/djJsbb2l6HTLV27ekTGbu86W5wcdyHvGe+WvG6hWZ17s6+DsffIEal5PZ9RChaJTrXZ201aRvRqBQFIISmQqFwhLaWnwEHkwS2bBWpA29MUJ7k5/Oq72seh0Mr4YsL2m0EYlze2KBm+fbuf/mmKVj50NiIgQ56p67al10Xe/lvfEMWelO85f1tnofwTyOl7cud4H1DZOWvqbOGkYW0ws8a2qx5z5HHK7S3gKFFZ+jBMlJuhD8nz/wyR1L5almldhTbqw4Nw4DSmQqFIqiaaj3EJ1cIFiiUkNrS0HWvpKyznW31dL0kSssx2JMzJhLWjFNhd2b0+/McPzTPYwupz6XEHC8sZ4mzYkWiJMIxfC/0MZ7w3MZx4jq5uMAffnWPjThCU8a5orFz42tcv10O0lpoAmBQKBtSUNtMLs11xy5j+WDmUXcTrtpF7jP42QpH8tnkQ9DHT4X9tkAtBc1zAFcdjtN3vI3OlAcPZTIVCgUReH3ObGtBliYL6DodgGszK2x9u1RkkmD48eb8B9voH9sgXiiuE44moD5cYtFa75IML4+z3Pf1Q0GzL8+TXhlgt2NODvf30syS7zrvfEFrn/kPMN/0Z9rUyyaTObZZmUu9zE2W1x+dTnM6uvp65BerKnNa17pMGPJDEfj3DjRwe3+6ZzLSmAtlF+N0mIkpteuY787gfG+7iJGSc9GLMbDhSXOtqZpn6ooD4cwXrcQVFtJhUJRMG63jdp4hIUJ83UercC2Za2bH11i+CuDNK0nuXqyHbut8K4kV7pbWVrIrw5kKYiuR3n0R8M8+pNhwisHRY2u5b5s3wtu0HahI+syx188lYrjNMmpniaWTSQVJZIWtL0sY/3KydV1U9EXF062sbpubSH8TGjAsdUQCxOFl9TKxX9861bJxlYotlEiU6FQFITdrtFmh6mhzK7bUmGz7b10rS8EGfrKIM3rSa6d6shfbEpJaM58VnYl0Uwoolg8iTiTvaRRtCm/zGHHZm5fuRBYkqBlhcQ066leCIQ4e6It6zLtLbWM55GJXyzXnDZG3nlU0m384Z1+5tatCEtQKDKj3OUKhSJvNF3QV+dgqMQ3wkzsF5nbrC0EWfvyQ5pb/LRcbufeo3kSZkopCYG9xQtjy9hsGolE9RbpNivhxuYDuHQNmebzO9x2Hk6Zt5L1djQwcms257b1POJBs6FZMI4vkORZb+MusSnYqYe1+4MIsMvMDyW1fhdxwyAUzj+hrRC5faPWTf+X3ilgzfyIGwb/7jtv8/c+/FLJt6XYhwRRvZcYS1EiU6FQ5IeUnGnzMfD6UO5lK8TaQpC1rwRpa6uh8WI7d0fncrYQnA0EabvWgVPXiM1tEI8licUSuNx21gObRDazF0ovGyZNdNFYgs5jTSwNH8xCj0USuBzmE15qDA1THdYtyvq3YpThe+Zag0JKeva8r5OJNNbKzrZ67o8WaK3Pc3/cqHEdFJg56pIWw2+/e5effv5pGlUSkKJEKHe5QqEwj5RcPNZQcYFptuf06tw6w18ZpGNTcP1EO21N/szLhiI8ml/lwcwyo0aEZS8kWl0sOCUtHcUnolhFPrLF15Zh3lLS22LuMzU3+Bi6kzsxxkrKXcRcAE2aPe17cStiTHMhJTd8Tvr/6N0Db81/Y5inwu6SJIpc6WzD78xUrFRRUqSs3E8ZUSJToVCY5uKpJu59K3vWcqnpPttBMBjJa53V2TUefnWQ9bdnOGlzcf1EO93t9VnXCUfjLK+HOd9Uz8RIpvaH1Y29Nb2o1h06qxvm9mFnY415YWvRDUzI8rd4Gn5jnKa6g3Gqk1MrXDyePWYzE6ZqIUrJTZ+T/j95L+3b68shlv+vN3j6t6f57hkHTUbxDkibpvH9Vy7wf/2AahupKC3q7FIoFKa4cKqJe1+9W+lpEF4L46mtJbxpvr3fNgKYHV5kdjglGns662g63cxyNMb4zMqB5W/0ttP/nfRxp5om8Hid2B02bLqGBELrm0Qi+c+rVPTPr1Lf4ie08DipSbNrdHz6MvfHzQlnLV7+4DEzLSEt32ZS0ldbc6AOZiSWKLw8Vi6tLCU3PQ7u/+mtnEMtTa6w9J9WqLfpXH/xJEsX63jXGc7LJf9UTycfOXeKj587TZNqGakoA0pkKhSKnJw+3sjA1821Kiw1y7MBzh9rpX+6eDG3PB1geToAQFd7LS1nW3i0vM7qepjL3a0HBObFK91EN6KsLgVZWQwR3i8oheDYyRYiCYPZ6QrX3AQ2o3HOvXiK4d9/7IbtvNpjWmACJCuRBFWhGoIinOGcKsV0pOSG2879P7+d12rJRJLhrz2Er8EzfU3439/HO61JVrX0QtimafzozSv8yI0rHGvMbr1XlJGjUSZTiUyFQpGdYz31PHr9gek4yHLQ/9pDGq6eZGU1fTHvQlidXWN1dg2X38kzzx6j/5XRPe9futLN/bdyZNNLyfjQPHaHjfOXuui/O2XZ/Arl9uQiF144xdgrQ2h2DdlTDxPmRaYVmd55U+ZTzemy0/NMN6+sLtBZ72VpX+eqQqeT0cgoJTccNvr/4k6BI6dYHFticWyJZrvO0y+eYv5CLbd2WTfPtjbza5/6MOfbspezUihKhRKZCoUiI15hMH97lHg0UempHMBWIvETCUZ5+I1hzlzuYmRwPiVAehu599Yj07GJ8ViCgXfGOH+tBwMIBaOsBTYIrucXS2oFSUMykIxy9geuE4rF6c9DYAIIe/lFZjltp8fOtjFVL3k9sAhC0Npcc0BkWolAck3X6P+KdaEniXiSoa8+gK/CRz5+kb+8AD/1/NN84buexZ5v61BFWRBHpOOPEpkKhSIjcyPzhPNMsikHx6/0MroYtKxkzn7isQQDb48BEFvf5P7Cet5ldQTw4L2JPa85HTY6jzUhbDojQ/OWzNUM8YTB3XFTRYgOYFTAr1eOG/C29fL11QUIPz66DpeNlgbfzt9Sgstp25MUJLffQOyNH5Xbv1L/sNt06mo9O6epQxe0za8x8OpAiT4VDP3pPf7pD32eT37g2ZJtQ6EwixKZCoXiUHHiah+zEVkygVlK4rEEYw/nkMDlp49x59ZkpaeUk0iRPeELodQas7mtho2T3h3r5W7iCYOlhb2dcJYXC+uM8+7i3nCOXq+LwVcHCxrLLJ//Jz/EJ79HCUxFdaBEpkKhyIieobNOJWjtbaL5ZAf3R5YqlRdiGQK49+Yjzl/tYWR0kWgVZaTvJxDKo1/3IRD+nb2NTLQKVoPphWPcOLytWH7k736a7/uZj1R6GgozHPaLmEmq5w6iUCiqDj3fHuAl4sS1PhY0J/eGD7/A3M2DWxP4XTZOnSmsDmM5mFsK4vE5TS1rlcSUJTrI7V31jLXAajRbi8jSnWBaCTX4zQ9d4sf+/veUbgMKRQEokalQKDKilfKuaBIhBAFsyCrKbreSlYUgw3enOH++A3+tu9LTSUvH8SZTywmLLJmlEJlNLTXMduisxbK3B7XqM6Qd2zIZvpfaJj8/+6/+eknnrrAQSSq7rVI/ZUSJTIVCkZFqsGT66jxECii8fpgQpKyatoRBR1f2WoaV0BE2n7nWg5bNzWKNWVvvYf2Eh6WsFswUpRKCqbFLw8/+y5+kobV6Wp8qFNsokalQKDJSkRqJ++i7dpyNJ1xkbrO2ukEsGKGuIUs3lgoYdJfyicu0ACsNmXX1XpIX6pgJl64skVlK8YDwyb/+Ms987Kr1AysUFlD5O4hCoahaqiPx58l0k2diZTGInkxy4lRrpaeyw9T8KqKcoRMWqczT17pYOuliLBjMvXAZsHoPdp9u52/86g9aPKqi1AgkQlbup5yo7HKFQpERTTMnMm0OG629Tbh9LoRI1Q6URurHMAzWl4KszK0VNIf54TkQ5ty1TwqriyFWFkN09zVR3+JnZjrA0mLlhJLdpmMYsoSO5L0Uexv0+l0032jntZVFMATtdX7susb8WhCbprMRq4xl3Mr9d/JqL7/8O1/A5TGXlKVQmEUI8e+ATwILUsqLW681AL8D9AFjwOeklDl75yqRqVAoMpLJkqnbNHrOduJrqSUUl0xOrzEdM2AlQ1KF04v/QgPtzV6cGmwsB5kdmWczlCr0ruka/novkY0o0c29YyxMLFF/+QSra+V12VYaAUyPLTE9toQETp3vwOVzYnM5ONXTjK4LdKHh1DUMIGEYONAASUQa9I9aV+y9vbmWhencLTwrbXO22XVOXu1iQNtgfHUJhOByZyvBlTAz86v4vU7aeuq5N525ML208FNc9HuwT66kEpmkJDphTT/7S8+f4R/9zhfw1lRnopjCBNVdJuPfA/8X8Ju7XvsF4KtSyl8TQvzC1t8/n2sgJTIVCkVGtmMyhRD0nOugpq2ezQRMzK7xKJiE4IrpsYKhKMHQrsSLhnpqj7kRAtbWI6xJwOPDX+OivsaF123HJiVGLE5IiiMnMncjgJH+GQBOP3ecyQezOdc5e6aVAEnmltaL3n69x4WZfkFWJc3km13e2dNIXbOPqJC8Ent8Tl7qbGHowRzG1njhSJyNaPmsmO6EwYM3hi0d8+XPvY+/9X/+NZzuo2XdV5QPKeW3hBB9+17+DPDS1r//A/ANlMhUKBTF4HQ7ufjSBWbXooyvhGHEvKjMiRCs7e/lLQTBYJRgMHcW8FHFrNN67OE8doeNjhP1zCwUFqqwjUiYrXtikXXGRLkqj9fJsdOtrAYjTMysMrG0zslz7Tvv9zXWsTof2hGYAMmkQb3dwSOZpWNUlRqYXF4nP/9vP8+zn7he6akoDj9NQoi3d/39RSnlF3Os0yql3H66nQNMBY0rkalQKDKS9Lm598gaF5/CKsyroHgsQXOtp2iRuW6yraJ1dRozj3P8dBsOj4OHo/PcebjXoqvXOmAZzrU3QzjB6MrBed9/OMv1Cx28OzmXdnwze9cuBF1eJ3ObMTaTmQW4sEixnrjcwy/8xt+k+1R77oUVh4PKusuXpJQ3C11ZSimFEKY+gBKZCoUiI5oq7lx95HlvKtaFbbfrzE5YaMEugPpGH519jcwsBhmaWk67jNvrIBiPc6W5mcHBhT0WzP3EsgjDnZhMKfHb7QTj8T1WT4HkwlKYkT+/y6UPXwKPa9dae/d1Yr44cQ9w5cWz/KPf/gJun6vosRSKIpgXQrRLKWeFEO1gKoJGiUyFQpEZvQrqZCr2kadmLDaRpauljjkTST9WIgGbTePk2XbiwNDoPEsDMxmXPXmpg8VklOGppazjet0OOvsaWQplqZm5tbsaXA7iX3qPE71NuJ46zmoyiZTQsxmn/+1RAAb+8m7+Hy4Prr18nn/0219Q8ZeKauBLwI8Dv7b1+/8zs5ISmQqFIiPV0PFHsY8ye9nqPE7SO5bTYIHhu72phmabh2Aowv3RbWPJwYG9fic9F9qZXFvn7kJ2cbkzPSEYXwmwvmm+88/C+BKMPx6/39SWiqe20cff+eLnlcB8EtluK1mlCCF+i1SST5MQYgr4h6TE5e8KIf46MA58zsxYSmQqFIqM2OxKZAK43A5e+uglTp3v4DvfeMBbrw5VekqmKTr0K5Y0vWgxrvmetnrqpM7QnRlu51j2+IU2HgbWWHyU3rqZiZYmPwOB7K5/meZfleAn//FnVatIRUWQUv5whrc+mO9YSmQqFIqMVEfHn8rzhV/6NC9/7DIAH/+Bm/yXL36D//ivvl6ZyZQ5TjawUNoi8N2tddQLO0O3p1nCnDHU7nYQXzIvfrfZ2MhtwdTiSc7XeHAaYG3xIfNcev4M3/2jL1Ro64pyUO7OO5VCiUyFQpERm3KXY3fYeP6D53f+FkLwoz/9Mhev9/Gf/vXXuPvOeFnnY1XGshmcDhvzk4GSjN3X0UCNoTN0e5pl8vS0F6izm9trmJjI3sNcC4SZ/L03C9tAkZy40sPzn7rBZ376Q6a7bSkU1YwSmQqFIiNWWTL9tW4im3HisYQl45WT3hPNOBwHL5VXnjrGlaf+OrffesRv/T/f4Nabj8o0o/wUVjGStKO5hrmp7KJsN2aMrKe6m3CEDUbfm2OBwvRiIaWS6vxuhhYrmyW/H7vTxtXvOs/7PnaVpz96hebOhkpPSaGwFCUyFQpFRqywZP7Nv/txPvWDTxMJx/iffu63ee+NUQtmVj6On27L+n5KbB6j/9YEf/S7b/LKV/pLKqbL6S33uazri32mpxltPcH426k4ynIXxwoEN7nU28XbE9njOEttJ/bXe3nuU9d538eucu2lC7i8qvf4kUS5yxUKxVHHVqQl86Pfe4Pv+ZH3AeD1u/gH/9sP8fnv+z9ZXixtnJ+V5BKZ25y/2sP5qz3897+wydf+5DZ/9t/eYWzIuv7hjymfPLNpxW/rbG8LcjXG5FvTFswoRaFCe3honqZGD0uhzCWZjBLsXm+tm2c/cZ2Xvv8Zrr50Dptd3XoVRwN1pisUiowUW8Log5+8sudvr9/FT/3tj/Jrv/B7Wdc7d7mbzXCUsWFT9X5LyvmrPXkt769x85kffh+f/qFnGLw3zZ//wTt848/vshmO7Sxz8lw7py908mhwnoE7k3mNn29f7/WpNc401oOUSCkxDImmCYSmIbStgvtiKzNcAEKgCYEQ4IwXbm053dMMK1Em3pwqeIyMFCgEN6NxLjS0ZBWZMYtsmfUtNVz/wEXe/71Pcf0DF3A47ZaMq3gSkMqSqVAoFMUUY7fbdY6fOWgFfPHDF/i93/g2Iw8PVl90uuz8rX/4GV7+2GUW59b48Y//MwwTfazT0djsR7fpLMwGClofUq7w0xc6C1pXCMGZS12cudTF53/uo3zrL+8jhOD6+07Q1Fqzs9zE6CJ/8J9e4y+/9B5JEz3C8y2uPj8dyHfqO1w415HfCkJgt+lc6mhm4K2JEtpcCxv58vlO7s0uZl1mRSZMj26z6/jrvfjrfTR11tPc1UDPmQ6uvXyBYxe6LGyzqVAcTpTIVCgUGSnGXf70i2fwpmmFp2kaP/DjL/C//L3f3/N6Z08jf//Xf3BHmDa31fLcB87xyldyl7+223XOXOri0o0+Llzr4dS5DmrrvQC8/o0H/M8//7vEovnFSTpddn765z6W1zqZcHucfOR7rqd9r+d4M1/4pc/wg3/9Rf7zv/kGX/3jW1mFdTmFSzTPfQZwuraWByUVmPnjdto5daqVe7MLbMazf6bFeJxOp414ms/u8bv4K7/4PTz3yevUNPpw+1xKSCoUWVAiU6FQZCRbdrnL7eD4mTZsNo3IZpxHQ/N7El62YzHTceO5k+g2bcdy97Hvv8lP/exH8OxLgvjsj7+QVmTaHTauPn2Mi9d7uXitl1PnOzK6I5996Sz/w9//FP/0l/4g62fdTV2Dl7/7q9+f1hJbKto66/nb//h7+dxfe4F/9398mde/8SDtcloZ5VvYRF3J3WgCHvWb6w8kREowCyEQWqqMu7YVAyqEQEpJMply8W+7+R+vnM+cBC09dbyVI+Fn98QaOuqZf7TX4ml32vhf/vjnOXWtz/zGFYp0SJS7XKFQKNJllz/70lk+8bmnuPLUMey7Ehji8QSPBucZeThHz7EmLlzrzThuTZ2HX/4XP8r0+DIXrvVy8mx72uXOXOriZ3/5e7l/a5xkwsDjddLY4udDn7pGY7Pf9Of47k9fY/D+NH/0O9nrH9Y3+fjY993g0z/0DHUNPtPjW0n3sWb+4T//Ef7yD9/ln//KlzCS+1zoZTScBdc3816nqcZNMiGRhkHSkBhJA2Pr38mkgZGUez6C5HFGd7by6trWckKAMBlCcbGujon+eVa7Inl9Bl9rzQGR+ZEfe1EJTIUiT5TIVCgUGdndN/nm8yf58Z/5EKcyxOnZ7TZOX+g0HcN487lT3HzuVM7lPvyZa3z4M9fMTTgLn/+5j5KIJ5kaX2IzHKO+wUdtgxd/jZvaeg9nL3dz8Vpv1bTS/PD3XKeh2c8v/63/Qjyef3ebYtF1QSiUnyUTIVhZDGVfpIg5CcirxtDSZAAjYeTdXcW+FWqxm5c/l9kyr1DkTRX3LrcS0yJTCKEDbwPTUspP7nr9XwA/KaU88NgvhLAD/xa4vrWt35RS/s9Fz1qhUJQFp9NGR3cDP/13PsYzL56p9HSKwm638YVf+kylp5EXN58/xc/+8vfuiV8tlyGzpsZDYCm7YNxPtUUn1jT6CK1ukmtmfreTWo+LzVicZp8HI7G+5/22vmbOP3OyhDNVKJ5M8rFkfgEYAHbSIoUQN4H6LOt8FnBKKS8JITxAvxDit6SUY4VMVqFQlJfWjjr+zX/7mT1ucUV5efnjlxm4M8mXfvsNAIwyxXL5/c68RWa5KsXv3wO1PhenmupZGVvF4bLj6fAhgdnbswB0rAmo9bC0Hqa1zkefxwcSDF2QQBIZXGW9f4mmJg+rs1PUXmzcGdvpdvAz//THVIKPQlEApu4cQogu4BPArwI/u/WaDvw68CPA92ZYVQJeIYQNcAMxYD3DsgqFospQtf2qg7/xP36Y2289YnxkgeT+GM0S4d4VKmGWcsmw/XrvZFM9D761q5PU4N76qtP353F47FzoqmXu1XmGZfoi+ZGNVC1T3etE0wQf+tEX+NGf/zStPU2Wzl+hyDeE47Bitj7JPwf+LnujCH4G+JKUcjbLer8PbACzwATwv0kpq6t5rEKhUFQ5Dqedn/3l78Vu14mXSWQ6CrBel8vYt31/bqjxcL2zhYffyt2qNBaOMze4lDOms629lhefPcu/v/vr/Oy//EklMBWKIsh5FRFCfBJYkFK+I4R4aeu1DlKu8JdyrP40qYTBDlJu9W8LIb4ipdxzRRBCfB74PEBPT37dNRQKheIocOZiJ1/4h5/hd//w7bJsrxDBWC6X8sZciBvdbUzdnWVwfbno8YSA7/rAeT726Wtcvd63U0pJoSgZR8SSaeZR9Xng00KIjwMuUjGZ94EoMLx1UfEIIYallPsjo38E+HMpZRxYEEK8CtwE9ohMKeUXgS8C3Lx582jseYVCociTD33yKv0j84yM7i2v09payw/90Ps4eaoVTRM8erTIb//Wd5iaKtxxZJjoPrSfclkypwYXYNCasW48fZyf+u8/yIlTrdYMqFAodsgpMqWUvwj8IsCWJfPndmeXb70eSiMwIeUi/wDwH4UQXuB9pFzvCoVCoSiAv/nffZCV1Q2+/a2HXL3ay2e+5zrPP396TwvQs2c7ePnl8/ytL/wnhobMFUffTyQSL2Ctw2MB7Oiq52d+9qM89cyJSk9FoXhisTxlVAjxaeCmlPKXgH8J/IYQ4j6pq89vSCnvWL1NhUKhOCo4HDb+/+3da4xU9RnH8d8zs+zCslxkd8GVXe7IZcVFROSqQNqCUES00KLVtMbE1lixEW2aqqCp0cTapvZFra0FTbFNo63FVkTbxNI21ipBuYgieCkiCFSQW8XCPn0xs7jA3mbmzJkzM99PsvGwcy7PeTyz88z/cs6SJfO0f/8RndHC/RybdO7cSVdeNUF3Le34k46aO5ycBJOKfJiAHYub5i+coKuvnaIyJrYhF1xSBx8okO9SKjLd/QVJL7Tw+4pmyyslrUwuH1Ji7CYAICBm1maB2eTcc9Mc4+6uQwdTf9pP1G/zU1vXS9+5c66Gj+zYAwMAZIab3wFAgerZs1w1NT21c+f+lLarquqm/+w+mPLxupSnftujsMz8YoNuuHlGWrdmAoLlTPwBAOS/fv0qUy4ye/funnKRaSaVxjp6V7zs61pRpgvGD1b9qDo1jOmvgYN65zokoOhQZAJAAavrV6mXXtqW0jYl8dSKxXg8pvqRfbVh3XspbZeqTqVxdSqJy2Kmwy08V71vXS+NnzhU4yYO0aiGfuoUkefQA8WKIhMACtiwYTVpbNXxsZXDh9foo70HAy8wz+jVVQuvmaTJFw9XeXmpOncpPWkG/dGj/9PePQe1f99hHTzwiWr7Vaq2rlegMQBZQ3c5ACDfNTSkPvln69sfqv6cWu38YJ8++ujwSa+dWdNDVdXdZTFTTNK/t+3R/n2JdTqVxnXR1BGq6NZZG9dv17a3Wn58Y3umTBuhRYsvUY+e5a2uU1bWSX1re6lvLYUlEFUUmQBQwCorK1RX10vbt3f8xuxHjnyqjZt3SJJ69CpXnz49FI+Zdu36WDt3H9DO3QdOrFtdXaFzBvTT6xve1/0PflX1o+okScePN+qWGx/TpvXvd/i4ZtLNt83SJXPOi/xMdQDti84obQBAVowdOzDtbT/++L/asmWXNr+xU/v2Hznt9T17Dmn96zs0c+55JwpMKTFOc9Gts1Ra2vG2jG/dcolmXTqGAhOFzz13PyGiyASAAjf2gkEprR+LmaZMGabb75irpUsv1/jxLT3Q7TNm0vwFF572+4GDemvpvfNV3rWs3WNO/3y95sw7P6U4AUQb3eUAUOAaGvqppCSmY+08j7yyskJz547RjJnnqqqq24nfT5w0VA/84BmtXr2hxe2mTh2h2lbGRl4wfrAeWXG9fnz/Kv3zH2+1uM7oMf11y3fndPBsgDzHE38AAIWiS5dSjRpVp3WtzAAfMeIszV9woSZNGqqSktNv+xOPx7T41tkqKyvRypXrTnrNTLr6msltHr+qurvuum+BVj29Tise/bv2fPjZmM6Ro2p1130LVFrGxxFQaHhXA0ARmDptxGlF5vnnD9DCKydq9Oh+7Y6DjMVMNy2aoarq7lq+bI0aky0xU6YMV//+Ve0ePxYzzZ47RjNmN2jT+u165+09qqrupgmTzla8hJFbQCGiyASAIjB9+kht27ZbRw4f1eDBfTTlomGqqemZ0j7MTFddlShKt279UBUVnTVmzICU9lFSElfDmAFqSHE7oHC45G0PXSkUFJkAUATKy8u0aNGMQPZVX1+r+vraQPYFoHBRZAIAAISpSJ74w0AYAAAABI4iEwAAAIGjuxwAACAsRXSfTFoyAQAAEDhaMgEAAMLExB8AAAAgPRSZAAAACBzd5QAAAGGiuxwAAABIDy2ZAAAAoXFaMgEAAIB0UWQCAAAgcHSXAwAAhMUlNTbmOopQ0JIJAACAwFFkAgAAIHB0lwMAAISJ2eUAAABAemjJBAAACBMtmQAAAEB6KDIBAAAQOLrLAQAAQuNSI93lAAAAQFpoyQQAAAiLS+488QcAAABIC0UmAAAAAhe57vK1a9fuNbP3ch1HnquStDfXQRQA8hgcchkM8hgcchmMfMpj/1wHcEKRTPyJXJHp7tW5jiHfmdkr7j4213HkO/IYHHIZDPIYHHIZDPKItkSuyAQAAChoPPEHAAAASA9FZmF6ONcBFAjyGBxyGQzyGBxyGQzyiFaZF0mTLQAAQK71iFf5hIpLc3b81QeWrQ1rHC0tmQAAAAgcRWaeMrMGM3vRzDaY2dNm1j35+3Fm9mry5zUzm9fK9n9rtt4HZvZUqCcQEQHk0czsHjPbYmabzeymcM8gGgLI43Ize6fZuqNDPYEIyTSXzfbzoJkdCifq6Angmnwk+fp6M3vCzCrCPYPoCCCXK8zsTTPbaGa/NLNO4Z5BBLnn7idEdJfnKTN7WdJid/+rmV0raaC732Fm5ZI+dfdjZlYj6TVJZ7n7sTb29aSkP7j7Y+FEHx2Z5tHMvi5pmqSvuXujmfV2992hn0iOBZDH5ZL+6O5PhB58xATx3jazsZIWSZrn7kVZHAVwTXZ39wPJ5R9K2u3u94V9HlEQQC5nSVqV/Ofjkta4+0/DPIco6RGv8gld5+Ts+KsPLm+3u9zM3pV0UNJxScfS7V6nJTN/nS1pTXL5eUlXSJK7H2n2Bu8sqc1vEclvpNMlPZWdMCMv0zx+U9LdnnwQbTEWmEmBXI+QlGEuzSwu6X5Jt2U5zqjLKI/NCkyT1KW19YpEprl8xpMk/UtSbZbjRTCmufvoTMZvUmTmr02S5iaX50uqa3rBzC40s02SNkj6RlutmJIuk/SXpj+oRSjTPA6W9GUze8XMVpnZ0KxHHE1BXI/3JLsmf2RmZdkNN9IyzeWNkla6+86sRxptGV+TZrZM0i5JwyX9JLvhRlognzfJbvKrJT2bxVjzgjc25uwnTHSXR5iZ/VnSmS289D1Jb0p6UFKlpJWSbnL3ylO2HyHpUUkXufsnrRxjlaRfuPuTQcYeJdnMY3LM2xJ3f8DMLpf0bXefkoXTyLks57FGiQ/zUiVuibLN3e8O/CQiIlu5NLOzJP1W0tRkF+ahQu4uD+lvZFyJAvNld18WYPiRElIufy7psLvfHGDoeadHvMrHd5mds+M/d/ix93Tyo0AfdveTbkVlZu9I2qdE6/TPTn29o3jiT4S5++faWeULkmRmZ0s67Yp1983JIugcSa+c+rqZVUkaJ6nNCQT5Lst5fF/S75LLv5dUsB9C2cxjs1a3o8nWo8WZRxxdWczleZKGSNqa6OVVuZltdfchgQQeMdn+G5lc57iZ/UaJ4Qe8v9P/vFkiqVrS9ZlHm+/Cn4Bzir0d6AKf7O47zKy3pOfN7A13X9PONqehuzxPJf/Hy8xikm6X9FDy3wPNrCS53F+Jbp53W9nNl5SYbNHit85iEEAen1Ji4o8kXSxpS3YjjqZM85hsyWwa/3aZpI1hxB1FmeTS3f/k7me6+wB3HyDpSKEWmO3JJI+WMKRpWdKlkt4ILfiICeD9fZ2kGZIWNo1fR7S5+47kf3cr0YAyLp39UGTmr4VmtkWJP3wf6LNv2JMlvWZmrypxYdzg7nslycyeSXanNfmKpF+HF3IkZZrH+yRdYWYbJN0r6bowg4+QTPO4IpnDDZKqJH0/zOAjJoj3NjLLo0l6tNk1WSOpYIdvdECm1+RDkvpIetEStzu6M9TokRIz62pm3ZqWlWjFTuuLP2MyAQAAQtIjVunjy2bl7PjPffKrNm9hZGaDlPjSICWGVT7u7vekcyzGZAIAAECS5O5vS2oIYl90lwMAACBwtGQCAACEqUjmP9GSCQAAgMDRkgkAABASl+SNxTHpmpZMAAAABI4iEwAAAIGjuxwAACAs7kz8AQAAANJFSyYAAECImPgDAAAApIkiEwAAAIGjuxwAACBMTPwBAAAA0mPuxTH4FAAAINfM7FlJVTkMYa+7zwzjQBSZAAAACBzd5QAAAAgcRSYAAAACR5EJAACAwFFkAgAAIHAUmQAAAAjc/wF+ub9jPMRGNAAAAABJRU5ErkJggg==\n",
"text/plain": [
"<Figure size 864x864 with 2 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"gdf.plot(\"DP05_0010PE\", figsize=(12, 12), legend=True)"
]
},
{
"cell_type": "code",
"execution_count": 12,
"id": "9f3b6487",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>DP05_0010PE</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>Census Tract 1067, Hennepin County, Minnesota: Summary level: 140, state:27&gt; county:053&gt; tract:106700</th>\n",
" <td>46.4</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" DP05_0010PE\n",
"Census Tract 1067, Hennepin County, Minnesota: ... 46.4"
]
},
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"acs_df[acs_df.DP05_0010PE == acs_df.DP05_0010PE.max()]"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.6.8"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
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