U.S. Department of Commerce, U.S. Census Bureau, Geography Division
2010
grid
2010
vector digital data
http://www.census.gov/geo/www/tiger
tractct_37800_0000_2010_s100_census_1_shp_nad83_meters
The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line File is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. Census tracts are small, relatively permanent statistical subdivisions of a county or equivalent entity, and were defined by local participants as part of the 2010 Census Participant Statistical Areas Program. The Census Bureau delineated the census tracts in situations where no local participant existed or where all the potential participants declined to participate. The primary purpose of census tracts is to provide a stable set of geographic units for the presentation of census data and comparison back to previous decennial censuses. Census tracts generally have a population size between 1,200 and 8,000 people, with an optimum size of 4,000 people. When first delineated, census tracts were designed to be homogeneous with respect to population characteristics, economic status, and living conditions. The spatial size of census tracts varies widely depending on the density of settlement. Physical changes in street patterns caused by highway construction, new development, and so forth, may require boundary revisions. In addition, census tracts occasionally are split due to population growth, or combined as a result of substantial population decline. Census tract boundaries generally follow visible and identifiable features. They may follow legal boundaries such as minor civil division (MCD) or incorporated place boundaries in some States and situations to allow for census tract-to-governmental unit relationships where the governmental boundaries tend to remain unchanged between censuses. State and county boundaries always are census tract boundaries in the standard census geographic hierarchy. In a few rare instances, a census tract may consist of noncontiguous areas. These noncontiguous areas may occur where the census tracts are coextensive with all or parts of legal entities that are themselves noncontiguous. For the 2010 Census, the census tract code range of 9400 through 9499 was enforced for census tracts that include a majority American Indian population according to Census 2000 data and/or their area was primarily covered by federally recognized American Indian reservations and/or off-reservation trust lands; the code range 9800 through 9899 was enforced for those census tracts that contained little or no population and represented a relatively large special land use area such as a National Park, military installation, or a business/industrial park; and the code range 9900 through 9998 was enforced for those census tracts that contained only water area, no land area.
As a recommendation of the Equity and Environmental Justice workgroup of the Governor's Council on Climate Change (GC3), CIRCA partnered with DEEP to create the purpose of the Environmental Justice Screening tool project. CT EJScreen is a screening tool to identify vulnerable populations that may be disproportionately impacted by programs, policies, or projects and inform initiatives for creating healthy communities. This project aims to build a community-state partnership to spatially represent environmental and demographic indicators, using deep community engagement and existing data efforts underway across the state. The tool intends to serve the state in various ways, including communication of the disproportionate impacts placed upon communities across Connecticut, informing department and agency actions concerning enforcement, permitting, assessing populations vulnerable to climate change, and supporting policy and legislation that seeks to address the institutional inequities
en
201001
201007
publication date
TIGER/Line Shapefiles are extracted from the Census MAF/TIGER database. No changes or updates will be made to this version of the TIGER/Line Shapefiles. Future releases of TIGER/Line Shapefiles will reflect updates made to the Census MAF/TIGER database.
-73.742161
-71.781373
42.052598
40.950034
222661.463772
384991.288183
165824.425179
287815.258619
ISO 19115 Topic Categories
boundaries
None
State or equivalent entity
Polygon
Census Tract
Tract
INCITS.38-200x (R2004),INCITS.31-200x (R2007),INCITS.454-200x,INCITS 455-200x,INCITS 446-2008
United States
U.S.
State or Equivalent Entity
Connecticut
CT
09
None
The TIGER/Line Shapefile products are not copyrighted however TIGER/Line and Census TIGER are registered trademarks of the U.S. Census Bureau. These products are free to use in a product or publication, however acknowledgement must be given to the U.S. Census Bureau as the source.
The boundary information in the TIGER/Line Shapefiles are for statistical data collection and tabulation purposes only; their depiction and designation for statistical purposes does not constitute a determination of jurisdictional authority or rights of ownership or entitlement and they are not legal land descriptions.Coordinates in the TIGER/Line shapefiles have six implied decimal places, but the positional accuracy of these coordinates is not as great as the six decimal places suggest.
U.S. Department of Commerce, U.S. Census Bureau, Geography Division, Geographic Products Branch
Mailing address
4600 Silver Hill Road, Stop 7400
Washington
DC
20233-7400
United States
301-763-1128
301-763-4710
geo.tiger@census.gov
ESRI ArcCatalog 9.3.0.1770
Shapefile
Accurate against Federal Information Processing Standards (FIPS), FIPS Publication 6-4, and FIPS-55 at the 100% level for the codes and base names. The remaining attribute information has been examined but has not been fully tested for accuracy.
The Census Bureau performed automated tests to ensure logical consistency and limits of shapefiles. Segments making up the outer and inner boundaries of a polygon tie end-to-end to completely enclose the area. All polygons are tested for closure.
The Census Bureau uses its internally developed geographic update system to enhance and modify spatial and attribute data in the Census MAF/TIGER database. Standard geographic codes, such as FIPS codes for states, counties, municipalities, county subdivisions, places, American Indian/Alaska Native/Native Hawaiian areas, and congressional districts are used when encoding spatial entities. The Census Bureau performed spatial data tests for logical consistency of the codes during the compilation of the original Census MAF/TIGER database files. Most of the codes for geographic entities except states, counties, urban areas, Core Based Statistical Areas (CBSAs), American Indian Areas (AIAs), and congressional districts were provided to the Census Bureau by the USGS, the agency responsible for maintaining FIPS 55. Feature attribute information has been examined but has not been fully tested for consistency.
For the TIGER/Line Shapefiles, the Point and Vector Object Count for the G-polygon SDTS Point and Vector Object Type reflects the number of records in the shapefile attribute table. For multi-polygon features, only one attribute record exists for each multi-polygon rather than one attribute record per individual G-polygon component of the multi-polygon feature. TIGER/Line Shapefile multi-polygons are an exception to the G-polygon object type classification. Therefore, when multi-polygons exist in a shapefile, the object count will be less than the actual number of G-polygons.
Data completeness of the TIGER/Line Shapefiles reflects the contents of the Census MAF/TIGER database at the time the TIGER/Line Shapefiles were created.
U.S. Department of Commerce, U.S. Census Bureau, Geography Division
Unpublished material
Census MAF/TIGER database
online
201001
201007
publication date
MAF/TIGER
The selected geographic and cartographic information (line segments) are derived from the U.S. Census Bureau's Master Address File Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) database.
TIGER/Line Shapefiles are extracted from the Census MAF/TIGER database by nation, state, county, and entity. Census MAF/TIGER data for all of the aforementioned geographic entities are then distributed among the shapefiles each containing attributes for line, polygon, or landmark geographic data.
withheld
2010
Metadata imported.
withheld
20110304
16240600
Dataset copied.
withheld
20110307
13571200
Dataset copied.
withheld
20110307
14291400
Dataset moved.
withheld
20110307
16305100
Dataset moved.
withheld
20110414
12162500
Dataset moved.
withheld
20110414
12171100
Federal Information Processing Standards (FIPS), ANSI, and feature names.
Vector
Simple
FALSE
829
TRUE
FALSE
North American Datum of 1983
Geodetic Reference System 80
6378137.000000
298.257222
GCS_North_American_1983
NAD_1983_StatePlane_Connecticut_FIPS_0600
coordinate pair
meters
0.000000
0.000000
Ozone_Metadata
2010 Census Census Tract State-based
U.S. Census Bureau
Feature Class
829
FID
Internal feature number.
ESRI
Sequential unique whole numbers that are automatically generated.
FID
OID
4
0
0
Shape
Feature geometry.
ESRI
Coordinates defining the features.
Shape
Geometry
0
0
0
STATEFP10
2010 Census state Federal Information Processing Standards
(FIPS) codes
U.S. Census Bureau
INCITS.38-200x (R2004), Codes for the Identification of
the States, the District of Columbia, Puerto Rico, and the
Insular Areas of the United States (Formerly FIPS 5-2)
U.S. Census Bureau
STATEFP10
String
2
0
0
COUNTYFP10
2010 Census county Federal Information Processing Standards
(FIPS) code
U.S. Census Bureau
INCITS.31-200x (R2007), Codes for the Identification of
the Counties and Equivalent Areas of the United States,
Puerto Rico, and the Insular Areas of the United States
(Formerly FIPS 6-4)
U.S. Census Bureau
COUNTYFP10
String
3
0
0
TRACTCE10
2010 Census census tract code
U.S. Census Bureau
000000
Water tract in some coastal and Great Lakes water and
territorial sea
U.S. Census
000100 to 998999
Census tract number
U.S. Census Bureau
TRACTCE10
String
6
0
0
GEOID10
Census tract identifier, a concatenation of 2010 Census state
Federal Information Processing Standards (FIPS) code, county
FIPS code, and census tract code
U.S. Census Bureau
INCITS.38-200x (R2004), Codes for the Identification of
the States, the District of Columbia, Puerto Rico, and the
Insular Areas of the United States (Formerly FIPS 5-2),
INCITS.31-200x (R2007), Codes for the Identification of
the Counties and Equivalent Areas of the United States,
Puerto Rico, and the Insular Areas of the United States
(Formerly FIPS 6-4) and the census tract code that appears
in TRACTCE10
U.S. Census Bureau
GEOID10
String
11
0
0
NAME10
2010 Census census tract name, this is the census tract code
converted to an integer or integer plus two-digit decimal if
the last two characters of the code are not both zeros.
U.S. Census Bureau
Refer to the online census tract gazetteer file at URL:
http://www.census.gov/geo/www/gazetteer/gazette.html
U.S. Census Bureau
NAME10
String
7
0
0
NAMELSAD10
2010 Census translated legal/statistical area description and
the census tract name
U.S. Census Bureau
Refer to the online census tract gazetteer file at URL:
http://www.census.gov/geo/www/gazetteer/gazette.html and
translated legal/statistical area description code CT,
Census Tract
U.S. Census Bureau
NAMELSAD10
String
20
0
0
MTFCC10
MAF/TIGER feature class code
U.S. Census Bureau
G5020
Census Tract
U.S. Census Bureau
MTFCC10
String
5
0
0
FUNCSTAT10
2010 Census functional status
U.S. Census Bureau
S
Statistical entity
U.S. Census Bureau
FUNCSTAT10
String
1
0
0
ALAND10
2010 Census land area (square meters)
U.S. Census Bureau
0 to 9,999,999,999,999
Blank
U.S. Census Bureau
ALAND10
Double
14
14
0
AWATER10
2010 Census water area (square meters)
U.S. Census Bureau
0 to 9,999,999,999,999
Blank
U.S. Census Bureau
AWATER10
Double
14
14
0
INTPTLAT10
2010 Census latitude of the internal point
U.S. Census Bureau
00
Blank
U.S. Census Bureau
INTPTLAT10
String
11
0
0
INTPTLON10
2010 Census longitude of the internal point
U.S. Census Bureau
00
Blank
U.S. Census Bureau
INTPTLON10
String
12
0
0
GEOID_AFF1
GEOID_AFF1
String
254
Join field for American Factfinder 1 data. factfinder.census.gov
0
0
GEOID_AFF2
GEOID_AFF2
String
254
Join field for American Factfinder 2 data. factfinder2.census.gov
0
0
Tract_area
Tract_area
Double
19
0
0
Score
Score
Double
19
0
0
This field is derived by finding the mean of the EPA values for each census block inside each tract.
Percentile
Percentile
Double
19
0
0
In statistics, a k-th percentile is a score below which a given percentage k of scores in its frequency distribution falls or a score at or below which a given percentage falls. EJSCREEN puts each indicator or index value in perspective by reporting the value as a percentile. For example, for a place at the 80th percentile statewide, that means 20% of the state population has a higher value. The state percentile will give what percent of the state population has an equal or lower value, meaning less potential for exposure.
U.S. Department of Commerce, U.S. Census Bureau, Geography Division, Geographic Products Branch
Mailing address
4600 Silver Hill Road, Stop 7400
Washington
DC
20233-7400
United States
301-763-1128
301-763-4710
geo.tiger@census.gov
Downloadable Data
No warranty, expressed or implied is made with regard to the accuracy of these data, and no liability is assumed by the U.S. Government in general or the U.S. Census Bureau in specific as to the spatial or attribute accuracy of the data. The act of distribution shall not constitute any such warranty and no responsibility is assumed by the U.S. government in the use of these files. The boundary information in the TIGER/Line Shapefiles is for statistical data collection and tabulation purposes only; their depiction and designation for statistical purposes do not constitute a determination of jurisdictional authority or rights of ownership or entitlement and they are not legal land descriptions.
TGRSHP (compressed)
PK-ZIP, version 1.93 A or higher
4.029
4.029
http://www.census.gov/geo/www/tiger
DVD-ROM (Only if offered offline)
ISO 9660
The online copy of the TIGER/Line files may be accessed without charge.
To obtain more information about ordering TIGER/Line shapefiles visit http://www.census.gov/geo/www/tiger
The TIGER/Line shapefiles contain geographic data only and do not include display mapping software or statistical data. For information on how to use the TIGER/Line shapefile data with specific software package users shall contact the company that produced the software.
20110621
U.S. Department of Commerce, U.S. Census Bureau, Geography Division, Geographic Products Branch
REQUIRED: The person responsible for the metadata information.
Mailing address
4600 Silver Hill Road, Stop 7400
Washington
DC
20233-7400
United States
301-763-1128
301-763-4710
geo.tiger@census.gov
FGDC Content Standards for Digital Geospatial Metadata
FGDC-STD-001-1998
local time
http://www.esri.com/metadata/esriprof80.html
ESRI Metadata Profile
en
20220608
08374300
FALSE
20220809
22383000
20220809
22384200
1.0
Ozone_Metadata
002
222661.463772
384991.288183
168694.987522
287815.258619
1
4.009
Projected
GCS_North_American_1983
Linear Unit: Meter (1.000000)
NAD_1983_StatePlane_Connecticut_FIPS_0600
<ProjectedCoordinateSystem xsi:type='typens:ProjectedCoordinateSystem' xmlns:xsi='http://www.w3.org/2001/XMLSchema-instance' xmlns:xs='http://www.w3.org/2001/XMLSchema' xmlns:typens='http://www.esri.com/schemas/ArcGIS/10.8'><WKT>PROJCS["NAD_1983_StatePlane_Connecticut_FIPS_0600",GEOGCS["GCS_North_American_1983",DATUM["D_North_American_1983",SPHEROID["GRS_1980",6378137.0,298.257222101]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Lambert_Conformal_Conic"],PARAMETER["False_Easting",304800.6096],PARAMETER["False_Northing",152400.3048],PARAMETER["Central_Meridian",-72.75],PARAMETER["Standard_Parallel_1",41.2],PARAMETER["Standard_Parallel_2",41.86666666666667],PARAMETER["Latitude_Of_Origin",40.83333333333334],UNIT["Meter",1.0],AUTHORITY["EPSG",26956]]</WKT><XOrigin>-36501800</XOrigin><YOrigin>-29365300</YOrigin><XYScale>122358479.92942828</XYScale><ZOrigin>-100000</ZOrigin><ZScale>10000</ZScale><MOrigin>-100000</MOrigin><MScale>10000</MScale><XYTolerance>0.001</XYTolerance><ZTolerance>0.001</ZTolerance><MTolerance>0.001</MTolerance><HighPrecision>true</HighPrecision><WKID>26956</WKID><LatestWKID>26956</LatestWKID></ProjectedCoordinateSystem>
150000000
5000
FGDC
FGDC CSDGM Metadata
Version 6.2 (Build 9200) ; Esri ArcGIS 10.9.1.28388
Ozone
Massidda, C., and Onat, Y., (2022) [Name Layer], The Development of Connecticut Environmental Justice Mapping Tool (v.1.0), [Dataset], University of Connecticut, Connecticut Institute for Resilience and Climate Adaptation, Retrieved from [Website link] Date Accessed:XX-XX-XXXX
222661.463772
384991.288183
287815.258619
165824.425179
1
-73.742161
-71.781373
42.052598
40.950034
1
1
-73.742161
-71.781373
42.052598
40.975881
As a recommendation of the Equity and Environmental Justice workgroup of the Governor's Council on Climate Change (GC3), CIRCA partnered with DEEP to create the purpose of the Environmental Justice Screening tool project. CT EJScreen is a screening tool to identify vulnerable populations that may be disproportionately impacted by programs, policies, or projects and inform initiatives for creating healthy communities. This project aims to build a community-state partnership to spatially represent environmental and demographic indicators, using deep community engagement and existing data efforts underway across the state. The tool intends to serve the state in various ways, including communication of the disproportionate impacts placed upon communities across Connecticut, informing department and agency actions concerning enforcement, permitting, assessing populations vulnerable to climate change, and supporting policy and legislation that seeks to address the institutional inequities.
Funding for this project is provided by the CT Department of Energy and Environmental Protection
Environmental JusticeejscreenConnecticutOzoneAir Quality
<DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>If you acquire any data products from CIRCA, we ask that you acknowledge us in your use of the data by citing the dataset and/or publications in any documents or publications using these data. We would also appreciate receiving a copy of the relevant publications. This will help us to justify keeping the data set freely available online in the future. Thank you.</SPAN></P></DIV></DIV></DIV>
<DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>The raw data was given on the block level, and it processed on the census tract level. Data from EPA EJScreen. The content within the layer is from 2020. For detailed methods go to https://connecticut-environmentaljustice.circa.uconn.edu/.</SPAN></P><P><SPAN>According to the EPA, ground level ozone is a result of a chemical reaction consisting of oxides of nitrogen (NOx) and volatile organic compounds (VOC) which occurs after pollutants released by cars, power plants, and other sources chemically react because of sunlight (EPA, 2022).</SPAN></P><P><SPAN>The health implications of tropospheric (ground level) ozone ranges from respiratory to cardiovascular morbidity. It can cause both bronchial inflammation and airway hyper-responsiveness due to inflammation. Elevated concentrations of ozone can even lead to increased mortality (Kim et al., 2020). The biggest risk of ozone-related health complications occurs during the warmer months of the year (Farzad et al., 2021). </SPAN></P></DIV></DIV></DIV>
ISO 19115 Geographic Information - Metadata
DIS_ESRI1.0
dataset
002
withheld
Local Area Network
4.029
Shapefile
Shapefile
4.009
NAD_1983_StatePlane_Connecticut_FIPS_0600
EPSG
4.5(3.0.1)
829
20220809
/9j/4AAQSkZJRgABAQEAYABgAAD/4RDaRXhpZgAATU0AKgAAAAgABAE7AAIAAAAFAAAISodpAAQA
AAABAAAIUJydAAEAAAAKAAAQyOocAAcAAAgMAAAAPgAAAAAc6gAAAAgAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAFVzZXIAAAAFkAMAAgAA
ABQAABCekAQAAgAAABQAABCykpEAAgAAAAM0OAAAkpIAAgAAAAM0OAAA6hwABwAACAwAAAiSAAAA
ABzqAAAACAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAMjAxODoxMjowNCAwOToxMTowMAAyMDE4OjEyOjA0IDA5OjExOjAwAAAAVQBzAGUA
cgAAAP/hAqNodHRwOi8vbnMuYWRvYmUuY29tL3hhcC8xLjAvADw/eHBhY2tldCBiZWdpbj0n77u/
JyBpZD0nVzVNME1wQ2VoaUh6cmVTek5UY3prYzlkJz8+DQo8eDp4bXBtZXRhIHhtbG5zOng9ImFk
b2JlOm5zOm1ldGEvIj48cmRmOlJERiB4bWxuczpyZGY9Imh0dHA6Ly93d3cudzMub3JnLzE5OTkv
MDIvMjItcmRmLXN5bnRheC1ucyMiPjxyZGY6RGVzY3JpcHRpb24gcmRmOmFib3V0PSJ1dWlkOmZh
ZjViZGQ1LWJhM2QtMTFkYS1hZDMxLWQzM2Q3NTE4MmYxYiIgeG1sbnM6eG1wPSJodHRwOi8vbnMu
YWRvYmUuY29tL3hhcC8xLjAvIj48eG1wOkNyZWF0ZURhdGU+MjAxOC0xMi0wNFQwOToxMTowMC40
ODI8L3htcDpDcmVhdGVEYXRlPjwvcmRmOkRlc2NyaXB0aW9uPjxyZGY6RGVzY3JpcHRpb24gcmRm
OmFib3V0PSJ1dWlkOmZhZjViZGQ1LWJhM2QtMTFkYS1hZDMxLWQzM2Q3NTE4MmYxYiIgeG1sbnM6
ZGM9Imh0dHA6Ly9wdXJsLm9yZy9kYy9lbGVtZW50cy8xLjEvIj48ZGM6Y3JlYXRvcj48cmRmOlNl
cSB4bWxuczpyZGY9Imh0dHA6Ly93d3cudzMub3JnLzE5OTkvMDIvMjItcmRmLXN5bnRheC1ucyMi
PjxyZGY6bGk+VXNlcjwvcmRmOmxpPjwvcmRmOlNlcT4NCgkJCTwvZGM6Y3JlYXRvcj48L3JkZjpE
ZXNjcmlwdGlvbj48L3JkZjpSREY+PC94OnhtcG1ldGE+DQo8P3hwYWNrZXQgZW5kPSd3Jz8+/9sA
QwADAgIDAgIDAwMDBAMDBAUIBQUEBAUKBwcGCAwKDAwLCgsLDQ4SEA0OEQ4LCxAWEBETFBUVFQwP
FxgWFBgSFBUU/9sAQwEDBAQFBAUJBQUJFA0LDRQUFBQUFBQUFBQUFBQUFBQUFBQUFBQUFBQUFBQU
FBQUFBQUFBQUFBQUFBQUFBQUFBQU/8AAEQgAbAD2AwEiAAIRAQMRAf/EAB8AAAEFAQEBAQEBAAAA
AAAAAAABAgMEBQYHCAkKC//EALUQAAIBAwMCBAMFBQQEAAABfQECAwAEEQUSITFBBhNRYQcicRQy
gZGhCCNCscEVUtHwJDNicoIJChYXGBkaJSYnKCkqNDU2Nzg5OkNERUZHSElKU1RVVldYWVpjZGVm
Z2hpanN0dXZ3eHl6g4SFhoeIiYqSk5SVlpeYmZqio6Slpqeoqaqys7S1tre4ubrCw8TFxsfIycrS
09TV1tfY2drh4uPk5ebn6Onq8fLz9PX29/j5+v/EAB8BAAMBAQEBAQEBAQEAAAAAAAABAgMEBQYH
CAkKC//EALURAAIBAgQEAwQHBQQEAAECdwABAgMRBAUhMQYSQVEHYXETIjKBCBRCkaGxwQkjM1Lw
FWJy0QoWJDThJfEXGBkaJicoKSo1Njc4OTpDREVGR0hJSlNUVVZXWFlaY2RlZmdoaWpzdHV2d3h5
eoKDhIWGh4iJipKTlJWWl5iZmqKjpKWmp6ipqrKztLW2t7i5usLDxMXGx8jJytLT1NXW19jZ2uLj
5OXm5+jp6vLz9PX29/j5+v/aAAwDAQACEQMRAD8A/Qb4nfHbw18JdV0fTNXh1W61DVo5prW10nTJ
r2Rli2+Y22NW/wCei/nXMf8ADXfhLt4c8c/+Ejf/APxqk8eL/wAZcfCsdf8AiQa5/wChWlR/tWfH
Y/BbwKBpk0Z8S6m/k2CMFYRKvMkzK3UL/wChMvvXWo0oqKlHfzPMxGJWHp1K1SXLGJN/w154R/6F
3x1/4SN//wDG6T/hrvwjnI8O+Ov/AAkb/wD+N1xFz+1Zc237MKeLrhYbLxnPF9ltre7UR/apNyq1
xCjH95HtO/5fl3KVr5B0n9pb4oaPq09/b+NdUkmm3blupftEH/AY5N0a/wDAVrWKoy+z+P8AwD53
GcR0cJKC+Lmjfb/gn3r/AMNd+Ec5Phzx1/4SN/8A/GqD+114RPP/AAjvjr/wkb//AON18a+Ef2y/
iVoni2DVNW1yXW9PZ1F1p00MaxvH/Ft2qvlt/dZf/Hq/S/TdQi1XT7W8gYSQXEayo3qrDIqJeyj9
n8f+AehleaxzWMvYy+Huv+CeNf8ADXfhL/oXfHP/AISN/wD/ABqj/hrzwl/0Lvjr/wAJG/8A/jVe
4ECuT8afEjw78Po7Ma3qAguL6TyrOxhikuLu6k67YYY1aSQ/7qnFQpUZOypv7/8AgHuvnjvI87/4
a88I/wDQueOv/CRv/wD41R/w154R/wChc8c/+Ejf/wDxqvZ7G4e6tIZWhkt3kRWaGbbuTIHBx3qH
WNYsdA0u51HVL2DTrC2j8ya7u5VjjjUfxMzfKKOal/J+P/AFaf8AN+B49/w154R7+HfHR/7lG/8A
/jVL/wANeeEv+hd8df8AhI3/AP8AG63fh58e/D3xb164tvB0Goa7pNqXFz4gjtWi09HXjy45JNvn
P3/dqy7ed33d3H/tpfFLUvhj8Lbc6JevYaxqd9HbRTQtiWONd0kjL+Chf+B1pamnyyh+P/AOTEYl
YahLESl7sTU/4a88I/8AQu+Ov/CRv/8A43R/w154R/6F3x1/4SN//wDG6+B/+Glvij/0PGrf9/RR
/wANLfFH/oeNW/7+iq5KX8v4/wDAPjf9bqN7cr/8B/4J+jfwz+Pnhj4ra/qei6TDrFpqun28d1Nb
axpc9k/lszKrKJFXcNytXp1fM/wZvp9U/aKuLy6mM1zP8OdFmlkb70jtPOzNX0v61y1oqMvdPvcP
UlVpqUh1FFFYnSFFFFADfoKMe9Ka+e/2h/21/h1+zr5lhqN22t+JlXcmh6WyvKn90zN92Ff975v7
qtVU6c6kuWCA+g+PSjIWvzX1j9pr9pX45av4o0jwdaaV8P7zSdLh1ZdEXbJqF5bTbPL8uaZWVmbz
F+6sf3lX71cHZ+CPE/ibx54t0rx78TvGmpadpnhix8SW/wBq17+yVuFuGhWRZGuN0cPltMy/d+9H
tr0Y4GX25WJ5j9ZKP89K/EfQfDuh+F/hhY+M/FfiDxhc3mualf6Zpa+F7yPbataqu6SeRv8AWbmk
Xaq7flVm3V1Wi/EXxv4B+C/hbxxofxs8YQ+ItXuprG08L6hA13BcSwyxrI0TSSSL5f75f9ZH8zKy
1vLLP5ZfgT7RH7G0o5r84PCX/BRzxz8K/HGq+Dviz4cs/Ekuj3DW+oap4Z+Wa3Zfvbl/1cm37v8A
yz+61fcvwn+M3g742eGl1vwdrlvrNpwsqRnE0Df3ZI2+aNvZq86rhqtH3pbFKXMd5RRSVzFC0UUU
AeG+O/8Ak7n4Vf8AYv65/wChWlfNX7ZOqeGvGH7Q3h3SEmleaE29jqt0Jt0USNJ/q1X+FlWRmb/e
/wBlq+kvHh/4y2+FZP8A0L+uf+hWlfBf7RuueHPEnxg8Q3vhe2WHT5LpvMulmaT7ZNuZpJl3N8qs
zNt2/Ltr0JL3Yf4f1Z8FxNiPZYbl/ml+hj/GjUrvUvil4mF4BELO9msre3+6ttDCzRxwqv8ACqqq
rXF17JoeoWPx4tb/AE3XFs7X4gLaxnStakm8j+05I2Vfs9xuby3kaP5Vk+Xdt+ZqwvBfwsk/4WFq
WjeL7e50620KzuNS1e3gZTN5cMfmeWrfd3N8q7v9qpPzWth6laftKfvRm/6ucX4b8Nal4u16z0jS
bY3upXknlwwr8u5v+BfdX/ar9Hf2XfF0Wn/DmPw/r/jPQ9Z1nS3aP/Q9US4eO3+Xyw7dypbbn5h9
35q+GL/42Tw6fqNj4d8MeH/Ctrdwta/aLG1aS7FuysrR/aJGZvmVvmb5Wb/ZrzWplHmO/Lsyp5PV
c6Pvy+5H7L+INBHibThaPqWoWNu3+t/s648mSRf7vmL+8T/ejZW/2qw/DPwp8N+D9cuNd06xuJNV
lt1tDcXl9PdSLGrM22NppG2bmY7tu3d8u77or4V/Y3+NNz4O+JCaXr3iY2fhm8tmhEGoXDNAs2V8
vZ/DH/d/hXb/AMBr9E9S1iw0Wxe81C8gsLVPvTXMixov/AmrF80dEfrmV5jSzSj7eMeWR5z4m1b4
reJNRFl4U0jSfCOmrxNrXiZhdzN/1wtbeTb/AMCkkX/drgfEX7OfjX4peKPDtt8TPGOmeL/AemyS
Xk2l2OnSaY13c/L5PnKskiyRr83G5f8AgVdj4k/aEg0/SZ7nRfCHizX5mKxWW3Rri3t7qZmVY186
RF8uPcw/eMu3blvm79B8OdJ+IBuG1TxzrVgZpk2x6FodtttLT/emk3STP/tDy15b5elbxlOlG+i/
M9G0KjtudLcX2g+BdJtYZrjTtA02PbDbo7pbQr/dRR8o/wCAivif9vHUX8Zahod/pWo6XqHh/S7c
q8lvqMLyG4mk+YeWrbvuxx/Nt7mqv/BQLxNquseM9K0sWF5F4f0iPb9seBlhnupl3Mqt91tsar+b
V8mfSopx+0fmvEOd88qmXxj7vcSiitjxB4M1/wAJrC2uaFqWjLLu8pr+zkh8zb97buX5q2PzyMZS
XMff/wAB/wDkvn/dNdD/APRs9fT3cV8w/Af/AJL5/wB010P/ANGz19PdxWOK+OPoj+icD/u8RaKK
K5TvCk6Ug6V8Yf8ABRD9qef4QeEI/A/he8a28XeIIHa4u4G2yWFlnazq38MkjblVv4dsjfKwWtaN
KVeahADN/aG/bGvPF3xU0r4J/CfWIdN1bU9QXS9U8XKokWxZv9ZHbf3pV/vf3vlX5vmX5p+FF54F
+GWpL8QtL1TVNQ8HatqVx4L8VQeNtMhmnhkmjaaO82ruWRd0e5o2+ZdrL826uV03xB4C8UfDv4dL
e+PZPBlj4PtZG1Dwzp9nIuoXmp+ZJIt5aTKvltJJ+7XdIy+X5de0fAD9nH4gfte2+j+MfjLr+oHw
PaBpdP03akE2os33ptsartVtvzTf6yTHy4+9X0nJTwdL33yx+1/X9WMfiPMIvivrvxkvdL0v4bfC
yS51+z8P33hPUf7JeabT57GZt0LR7vmt/Lb95H5kny/Kv8Nez+Ff2Wf2sPE+tWPiLWfHmm+FdZt9
KXRFvrmdbi9ks/M8zy5PLjZZG3fNuZt1fa/hWHwt8M9Dh0HwjodrpWk2vypBZxrGhbb/ABerZ+9u
+auz0vxFbaou1W2Sr1jb71fGw4sy7FYj6rhakeY65YWrGPNKJ8CaP/wT5+NfhXSdfs9D+NFpaw66
0kmpWa28qx3LSKyys3LYZgzDcq153qn7I/x8+EureBdTl8NaP8RdE8CTPPpum6Tcfe3TNN80bKsk
n7xt38X3VWv1R85P760ecn/PRa9uOZVvtWMOWJ+NelfGLXfAfwxnt9O8VzeA/ibp/iC61bxDpOpW
Miz+I/OaPyVb92yssf7xWhk2r8zNVm68H+If2fde1DxD4O1+Xw74n8G2qjxTrE0m3T7zU7iRZI9I
tIQu2barfMv3W2s3yqqtX6cfHD9nPwD+0BorWXirSo5btVxbatb4ju7Vv7ySY/8AHW3L/s1+b37Q
Xw78U/B3x3oOlfGvX/EXjv4Y6bHJJoElm+xb2RV/d28rN/qZNu1Wb5mVV+X/AGfUw+JhiHyr7jOU
eU++P2Vf2qNO/aE0S503UbQ+HPiBo67NX8Pzq0bpzt86JW+byy38J+aPcFb+Fm+gduDmvwu1z9qL
xjqnxa0b4j2cWmaF4n0kmOGXT4HRZoQ/yw3PzbplWP8Ad7m+Zl+983zV+xnwH+MWk/Hn4XaP4x0c
+Wl4m25tGfc9pcLgSwt7q3/fS7W/irzsdgpYe1RL3ZGkZXPR6KKK8oo+f/ihpsGtftRfDWwuM+Rc
+G9fhk2HDbWNoG+avmr9oj9m34d/CPwXd6joviu61DXY50jj0+6vLdm2s43fKqq3yrn8q9v/AGov
l+LOgf8AYjeKP/RUFfnhxXpS+Gn/AIf1Z+acT4qjSfsqlPmlLr22Pq74F/sz/DL4i+AdD13WPGFx
Z6vc+Y1zpseoW6Y2zMu3YV3LuVf/AB6sDwtNH8WPj98TPCbXHkr4u+2WVtqCnd5X2ebzYf8AeVlt
9rV84ccetWdN1S80a+jvNOurixvIW3R3NtI0csf+6y1nynx0czoxjTjGjy8vxf3un+Z7F8WP2T/F
fwb8HN4h1vUtIuLZblbdYbGWRpG3fdbLRr/drB+H/wCzn44+Jl15Wg2Ftd26xJNJei9Qwwq65VWZ
WbbJtb/V/eX+JawvEnxg8aeNPDcWha74kv8AVtLinW4SO9fzH8xVZVbzG+b+Jv4q+lfgN+2zoPgz
wlpPhXXfDp063sLdYY7/AE75o3ZV/wBZJGF3KW+8zLu+Zvu1Pvcp04enlOLxfLKUqdP9TzfQ/wBh
/wCKmramlve6VbaNbebsku7i9jZVX+8qxszN+NfpBomk/wBh6Lp+nLI862kEcAlk+8+1QuT+VeI3
X7XWmaLo7a5d+GdQ1bwsOZNe8LTR6nb2o/6eI/3c0P8AwKOuz+Hv7SHw5+K1jJP4W8VWmsTQxtM9
hCrC92qPm/0dl8w/gtTOnVtz8uh+nZVgMDlyl9Xlfm7npyLgdqq6lqVrpds1xd3MNrDH96aeRUVf
qWr4a+M37efiCS/u9H8G6U3h2OFmjkvtUh3Xe7/rm3yx/wDAt3/Aa+WfFHjjX/G14bvXtZvdYuA3
3rqdpAv+7/d/4DUxptnlY7ivDYWXJQjzv7kfYP7dXxS8I+Mfh5pGjaF4j03WdSh1aO5khsLhZsRr
DMu7cvy/eZa8e/Y/+EPhz4weM9a03xLby3NtaWH2iFYZmj+bzFX+H/erwSuk8C/EjxJ8Nb+5vfDO
qS6VcXEfkzSQor7l3btvzLWvLyrlR8BUzSni8wjjMVT93+UX4jaLaeF/iV4n0myRorDTtWurWBGb
cyxxzMq/N/urXv37Z3xw8HfFzTPCkPhXVG1F7KWdrgfZZYdoZY8f6xV/umvmjWNVu9c1S91O/la4
vb6eS4nmb+ORm3M3/fTVSp8pxRx7pxrUaUfdqfofov8AAf8A5L5/3TXQ/wD0bPX093FfMPwH/wCS
9/8AdNdD/wDRs9fT3cVnivjj6I/d8D/u8RaKKK5TvMvXNZs/DWi3+r6hMttYWMEl3cTN91I41LMx
/wCArX4K/GT4nX/xk+J/iPxnqJYTatdNLDE3/LvCvywx/wDAY1Va/Xv9t7VLlfgTdeHdPvI7HUPG
GpWPhq3nkPyL9qnVZd3+z5Ilr8wfiv8Asvt8PPBd14u0vxvovirQ4fJbbHb3Fpd+XNNJDHJ5ci7d
rNbz/wAX3V3fdr6XJ/Z025S+JmdTY0/2L/2fbf44fEprjXIfN8I6DtudQjb/AJepG/1dv/wLazN/
sr/tV+s8+sRpp/2W2WOKNY1jjhiX5Y1/hVV+WvkL9lPS7f4afBPQ7VflvtSX+1Lxv70kn3V/4DHt
WvXv+EyH/PSvns6rPMFUor4dYhTqezlzHW6judo2b5o2Rdrf+hf+PVtaBeSWEkDO38PzLuZfl/h3
f+Pferz6Dx8bXdiban3m+bbXFap8eIZbprXw/ZzeJdQVtsn2ZtsEf/XSZvlr+dsm4GxeW5v9dq1v
dj+P9fh57n0OKzqhLD+zPpf/AISP/pp/49Ud14vt7Nd1xeQ2y/3p5lX/ANCr5c3eLPE37zxB4sk0
qBvvab4dXyf++pm+ZqktfAfge3bzJ9Hj1OdvvT6lNJcyt/301fvPtpy+GJ8p7acvhifSK/E7Q5ZN
qa9prN/dW8j/APiqxfid4Z8O/GfwHqvhbxBHHfaRqEe3zI23NDJ/DNG38LK3zV4s/hnwPLHtbwro
u3/rzWs2XwD4Xt5PtGjfbPDV5/DNo15JD/47u20RrVYS54h7St/Kfm38UPh3qXwn8fa14T1f5rzT
ZvL8xV+WaP70ci/7LLtavq3/AIJe/GiXwf8AFi/8AXly39keKI2ntY2+7Hfwru/4DuhVlb/rlHXH
ftjeCNaa80HxFq2qW+qwKy6XJq3k+XPtb5o/PVfvbfm+auZ1T4Oap+zH4/i8Ral438I/2l4V1S3v
bfS7LVPM1C+WOZW+WFVby90fzbZGX5a+9hiKeOwdpfFL8y6cub3j9s6Kgtp0ureOaFt0cihlb1FF
fHHWfMH7Un/JWNA/7EXxR/6Kt6+Bv+ES1v8A4Rn/AISL+y7v+w/P+z/2h5LeT5n93dX17+398Yrj
4I/En4c6/b6Taa61xpGr6c9lfbhBIkptlYNt+9/u18g6F+2B8ZNf8a+fpCQ6nZfZ/s3/AAh9jpRm
0r7P/wA8/sy87f8Aa+9jjdX0tDAVsRRjUj8PL+rPz7O8DTx1e0pcvL/wDKrZ1DwVr2k6DYa5e6Pe
22j37MtteSQssc3+61dNqn7USeBZVuL39njw/ofiBvmSXVoroW+7+8tvJ8v/AI9XHWf7dnxWbxVq
GratqVn4i03UI1huvDeq2iyaW0a/dVYf+Wf+8vzN/FuqqeU4qceZHy8chhGL9pW97yX53KNbOueD
Nc8M2OnXer6ReabaajH51pNcQtGsq/3l/wA/3f71bR/bAsvDqjUtF+BnhnStZX5hf3v2i4gib+8s
LbVX/vquc8PftnfFO41bV7jXmtfH+k6i6yXei65Y+daK33V8lV2+T8v93/x6iOU4mUeYmOQ0+X95
V97yRc8G+Ntd8A65Fq3h3VLjStQj/wCWkLfeX+6y/dZf9lq9M8cfBK3+M7Q6jpGjH4ZfGb7Ouowa
dHG1lZeIF+95lv8A88bj5d391m/4Ey8O37XyeF4/t3hb4L+HPDusL/q9TvluLz7O396NZBtVq5rw
p+3D8TtDvprnWp9L8dK139ugh8UWf2hbWb/npCVZWh+791W2r/drfD4DGUpe0p6HrYDBzwWlStzR
7dP+HOg8H/tF2PjGQeDvjnazyXFu32ODxjHDjVtNkX5dt0uP9IjRvvbv3i/N97rUnxI+GOp/Di9t
vtElvqWj38fnaZrVgwktLyHGcxt/7L/DXgHxL+IGp/FTx1rHizV47aHUdUl82eOzi2Qq23b8qn/d
/wB6vXPgf8Vvih8OfDM2n23gq48b+ALlvPl0jVtJmuLJW/56RyKv7tv9pfl/2a7sZlkXH2lP3Zfy
jxeAo49a/F/N/mQWtrNeXEVvbwyTzzMsccca7mkb+6q1d8SeGdU8I6tNpetWNxpmoRjL29xHtYVp
6l+2xdaBBcp8P/hz4d+H+qSK0barHG15ew/3vLaT/V/981meEv21PEtvpEGj+PNC0j4n2Fv/AKib
xAjfbYl/urdL8233bdXlf2Ti+XnPH/sGnye9W9700/zK+k6Tea7qVtp+n2019fXUixw28Me5pG/u
qtSa3oN/4b1a50zVLSawv7aTy5re4j2tG1bOtftheJLXSZ7b4c+ANI+HIvI/LfVdLtZLi/Mbfwrc
SfdX/dXt8rVU0D9tjXTpVvpHxF8IaJ8SVsh5MV7rEbR6lGq/wtcL8zf8CXd/eaj+ycS48w/7Bpxh
/F9700/zPvr4E/8AJex/2TXQv/Rs9fTY718L/sL/ABtuPjv8bfGWtzaNa6BDY+HLHTLWytZGkVIY
5pSvzN/vV90r1NeNjacqNbkl2R+t5fyuguUfRRRXCegfFf8AwUwt7XW/Cvwz8O39vrF3Y6l4k/e2
+gW6z30m23lVVhjb5WbdIK+G/wBob4W+FfhLpelaHo3ibxVea9eTR/2toGrRx+Rp6qreWskkLNG0
y7v9WrNt3N92vvz/AIKHeHvEGreF/hjN4W1KTRfEP/CX2+n2eqRzND9lkuYZY1fzF+ZV3bV/4FXx
R+0B4F8YWfw1Gp+JvjTP8RJNPube5Gjs100EKyTXFq00ckxXcyzW8kbKq/Lur6XAS5acPeMZntFr
4yWzs4LdG2xQxrGq/wCyq7aq3nxQW3by4Fa8uf8AnnH/AOzN/DXiUXiaa/hVoPMlVl3M33Vpn/CT
R2ce1JF3f3Y6+EqVKkpuJ8vLGSvyxPW7jVrjXvm16+b7N/0D7aTbF/wJvvNWjb/ESx0u3W1sIf3U
fyrBaR/KteZW+g+JL63iupdLks7OT/Vz6pNHaRt/u+cy7qstoOvRKixNpc//AEzg1i03f98+ZSjT
qFRqVPsxPQf+Fjatcf6izhgT+9czf+yrTW8aa83/AC/afF/uws3/ALNXlevXGveF2VdX0u80zd91
rmFlVv8Adb7rVlf8JlJ/e/8AHq19nIPrH80j2f8A4TLxAv8AzEtPl/2Wt2X/ANmqRfiNrFv/AK+z
hnX+9bTf+ytXin/CZSf3v/HqP+Eyk/vf+PUezkT9Yf8AMdV+0B4yt/FXwn1W1b91PHJDOsE67W3L
J/8AZNVG/wDgb4LvfgrL8QPElv8AE6DXL7T/ADNPiu44bltSmWP/AF21Y2aO1X5f3kjL8v3d1ec/
EvxQ154TubfartMyqu7/AHt3/stew/EL4L/Ffwf8O9a1LTvi1rWoeB9PsLn5hq7SWjWsdvbLHH+5
mZV8ySaSFY2X7sDbq+vyv2kcLGMpcuv+R6+DqSqU+aR+m3wRvn1D4M+Ab2Z90lx4fsJWb1ZreNqK
0Phno7+F/hr4U0iQbX0/SrS0Zf8ArnCqf+y0V4NT42eufEX/AAUw8IXXj/4ofBPwxZvsutYuLiwj
dh8qtJNbLu/4Dur6C1zV/hl+wp8GbR/sLWWnRvHaRRWcKveancbfvMzFdz4DMWZtq/8AfK1wn7VM
Syftdfs0of8An+vW/wC+fIrzz/grVMV8I/DmMH5GvbxmX/tnGP8A2avpqKeKWFwsn7uv5s8Oo1Rd
bER+L/hj334R/HL4Z/treDPEGkNpUl1BAVjv9F1yBA6q27ZIu1mHVW+ZW3Ky/wAPy1+U37SPwj/4
Ud8ZvEnhFJJJrK0mWSymk+9JbyKske7/AGlVtrf7StW/+yv+0tcfsx+NNV12LQhr66hp/wBia0a8
+zqv7xZPM3bW/u7f+BVl/tM/Hlv2jPiV/wAJa+hr4fb7HDaNaLdfad3l7vm3bV/vf3f4a93CYStg
sVKMP4cjyMRiaeIoRlL+Ifpp+3IB/wAMQeKeP+XbSv8A0tta8Z/4JIDPh34lf9fNj/6DPXs37cv/
ACY/4p/69dK/9LbWvGv+CSH/ACLvxK/6+bH/ANBnrw6f/Irrf4v/AJE9aX+/U/8AD/me0eOv2/vh
d8O/iNqvgvXo9btL/Tbj7Pc3i2KyWyttX5vlk3FfmH8NcZ+2p+y/4Q+LXwh1T4jeE7KztPEWn2X9
sQ3+nRqianaqnmN5m3/Wfu/mVvvfKq18K/tkWs15+1b8QLe3hkuJ5NT2RxxruZm8tflVa/TbwvYz
/Cv9imC28Tq1tdaV4OkF5DP96NvszHyW913bcUToLAxo1sPP3pEQqvFSqUa0fdifIH/BNP8AZ10X
x9eaz8QfEtlDqltpF0tjptrcx+ZGLjYskkrL/Eyq0e3/AHt38K19MfET/god8MPhr8SbjwZe2+sX
b2FwLW+1Kztka2tpOjL97e23+Lav+7urD/4JbQCP9m/UWH/LTxDdN+UMC/8AstfmN8WJWuPip4xm
dtzSa1eszf8AbZq7Vh1mWNrKs9InO6zwWGp+z+0fpH/wUE/Z88O/EL4R3fxN0C1t01/SYY7x76zQ
L/aNk23dvI+/tU+Yrf3VZe9flva2sl/dQW8C+bPNIscar/EzV9e/8PDrqT9nv/hV83gZJl/4Rv8A
4R7+1m1Zt3/Ht5Kz+X5H/Atu7/gVeJ/speE/+E4/aO+HulFfNjbV4bmRf70cP75v/HY2r1cDCvgs
NNYj7Pw+hw4qVLEVoSo9T9s/BfhuDwd4T0LQIdvlaXYwWMfuscap/wCy1+O37e3g/wD4Q39qbxrG
i7YNQkj1SH/a86NWb/yJ5lfpT8Y/isfCn7THwR8LrNst9Yk1L7Uuf+nfbD/5Er5G/wCCsng42fj7
wN4oVMrqGnTadIy/3oZPMX/0o/8AHa+fydypYqPN/wAvE/6/A9fMVGph5cv2WSf8ElP+R8+IH/YO
tv8A0Y1fpqelfmV/wSU/5Hv4g/8AYOtv/RjV+mvauHOf99mdWWf7tEWiiivFPVPB/wBtjwTc+PP2
ZfG1tYb11PT7dNXtXj++slrIs/y/7W2Nl/4FX536b8CfhRH8HovFniHxxeXWuaxp17e2jatdLpzx
ssbbZobVvMmvFa6XyfvR7vmbbtr9gZYlmjaORQ8bDDK3evye1T9la08B/tJeNPCuo6TH4kjg03+0
vBWh6jdSQ21/HJcKvlsyt5jLbLJMzRxtuby938Ve3gKvuSp81upnI8S+F+k6t4+0/wAtryPT9K01
VW6vrn/VQr/Cu1f9Y21W+X/ZbdtXc1ep6Hf6f4c1C003wfptxc6xN/qb5rdrnUrj/agjj+ZV/wCu
flr/ANNpK4f4qf8ACN/Df4tQWem2LaRFHbrH4s0XRJGu4LG8jmZW+yNNuVlZVjkXzNyq0n+ztrqd
EsfF/jnwnPqkF3pvwZ+FdwzLJrGo3TLLqbL97fJ/x8ahJwflX93/ALK121MHT/iR92MjyfqsYy90
0tUivtNuGm17xFovhq8kbdcQaprDNd7v9qGwVpF/3ZGZqprq2k3H7u1+JHhtpW/hkm1m2Vv+BSKy
/wDfVco3ir4EeA/9H0zwn4g+J91H8rahrWof2RYyN/ejt4d0m3/eaoo/jp8OJ2aO++A+hPAzf8uX
iDUIJF/4E0jf+g1P1L+7+Q/q56dpNr4qsLeebQV/texaPdcSeGbyHVYGX/ppHb7ZFX/rpDJXMXie
F/FEMk11YrpE8fyyX2jMqxRt/wBN4W2x7v8Ae+z/APAqwbO4+Bviq7ik0vWPF/wm1lW3RXN8y6rZ
Rt/10h8u4j/3trV2OuaX8S9M0ddev9P0f43+FLddsfijQ7ppry3X/auYdt1C3+zMrLUfVI9RfVuY
4bVPhjriyf8AEka38SwMu6NdPVlu2X+99nb95/wJdy/7VcPcalJZ3UtvcL5E8bbZI51ZWX/eVq9E
0vxL4H8UK39leJG8OXW7c2n+Jo1jVm/2bqGNrdv96S3jb/arT8aeKPEngjw3Fdau1vqulTN5dq1z
Jb6nBcNt+7HJuu41bb/1zrT6r73Lymf1OJwPw98H6j8WviFpHh+x0K98SW8LfbdR03S7iO3uZLVW
XzNskjbVba1e03n7LPg+x+O3w88NeE5vEDRa/q0M5hvprW6tprCP99c7poWVlkVV2tDJH/F95qyf
BX7LviS48Pr4i1bUovhn41vP+J14f1p9fsbewvIWVWWFYopFkt2/uyLuX5trKtfSf/BPPwNrnjjx
Brnxl8Y21g+q+S3h/Tr6zs44ft3lyH7TeM0a7ZWZgsfnD73lyVdWpGjD93LSP5np0acaceU+8hRS
0V8qdZ8hftTcftdfs1f9ft//AO0K85/4K3f8it8OP+v28/8ARcddf+2dr8Phz9qL9mzULh1it49U
njkd2wqLJNbR7v8Ax6m/8FPvhrrfjb4U+HNX0TT59UOi6hI13DaRtJKkMkW3zNq/wqyru+tfSYOX
JWwspef5s8HELmp14x8v0PyzstNutRkaOztZryVV3MsEbM23/gNJeWF1p03l3lvNbS7d22aNlbb/
AMCr77/4JZ/CfXNP8YeKPG2padc6fpf9nf2VazXULR/aJJJo5H27vvbfJX/vuvKv+CmPiK21r9p2
5tLZ/MbSdJtbKbb/AAyfNNt/75mWvqVmDq4uWFjHSJ4bwvLh1Xkfbv7cv/Jj/in/AK9dK/8AS21r
xr/gkf8A8i78Sv8Ar5sf/QZ69l/bl/5Mf8U/9eulf+ltrXjX/BI//kXfiV/182P/AKDPXy9P/kV1
v8X/AMie7P8A3+n/AIf8z6l8O/H74f8AiT42av8ADqxkK+M9PWR7hZLTYrbdu7bJ/E21v/Qq+Rv+
Co3xc8YaLeaR8P7YJZeD9Ws1vprmPd5l3IkjfuWP91WWNtv+0teOfE74kN8Jf+CiGreLPMaO3sPE
Mf2rb/z7NEsc/wD5DZq+sP8Agpz8N08ZfAmy8VWsaveeGb1Z2kX5v9Fm2xyf+PeS3/AK0o4enhcX
h5S1jJfiRUrVMRQrR+1H8iz/AMEuf+Ta7v8A7D11/wCi4a/L74of8lM8Xf8AYYuv/RzV+lP/AASn
123vPgV4k0sOv2ux8QSSPH/djkt4drfi0cn/AHzXwx8ffgf4z0H9oDxVokfhrVLmbUNYuZ9N+zWc
ki3cMkzNG0e373ysv+7XqYGUaePxCmcWJhKeEouJ5Mvh/VHtftS6befZtvmef9nbbt/vbq+sf+CX
fhP+2/2h7vV5F/daJo80yt6SSMsK/wDjrS19ufELTV+Df7Cup6TqskcV1pXgr+ypZA3y/aWtRb/k
ZHrw3/gkv4T+y+D/AB94ndP+Py/t9Ojb/rjG0jf+lC/981niMzeJwVaXL/dHRwXscTTj8zk/209U
8Vv+2d4O1zSvD2sX2neFF09jNaWM0sTMs/2iT5lX+7Iq/wDAa9k/4KieD/7c/Z5s9ZjjzJoerwzu
392GRWhb/wAeeOqfjL/gp34E8I+Ltb0GTwxrt6+l301k1zbmHy5WjkZdy7m+622vU/iteWH7R/7H
PiLVNLhkNtrfh2TUba3k/wBYska+csbbf4lkjC8elePzVqE8POpT5YxPR5adSNaNOXNzHyV/wSU/
5Hv4g/8AYOtv/RjV+mvavzK/4JK/8j38QP8AsHW3/oxq/TXtXPnP++yNss/3aItFFFeMeqIK+ff2
w/2Y7b9pP4bmztmS08W6SzXOi3knygSbfmgZv+ecm1f91lRv4dtfQWaBzVU5unLniB+IfgHWvCfw
L8MeMtP8ZaFqGveNdX3aDeeGfMaw/s62jkjkkaS42szNI0artj/hVvm+avGdW1RtSuPk86DT4Wk+
x2Mlw0y2cbNu8tWb/e/4FX7AftgfsU6L+0dYPrekvFoXj62i2w37L+5vVX7sNwF/8dkHzL/tL8tf
kx8Rvhn4n+Eniifw94s0e40bVIf+Wcy/LMv/AD0jb7si/wC0tfa4DEU8Rq/iOaUeU5miivU/GPwJ
k8F/Bbwp4/u9YmZ/EMPnQ6b/AGTMsSq0kir/AKV/qd22PzPLba21q9WVSMPiJPLK2fCfjHX/AADr
C6r4b1nUNB1KP7t3ptw0Mn+6237y/wCy1eg/EL9mHxp8MY/EsmuLZJBoen2eptPDKzLeQ3E6wr5D
bfmZZG2srbdtO8Qfs/TeGvh/4h8XXWtR3mkQ6fpl7ot/Yw/uNSa8maNo/m+ZWh8uZWX726OsvbUZ
xK1NST46aX8VEltfiB8NLLxV4jkjbydf8L7tK1SST+9OsKtHN/tM0e6l+Dnwy8PX/wANdR8Zal4L
1r4h3S69DosmiaFeNbyWMMkfmfaW8tWZmZv3cf8ADuVt1ehfDHxj4d/Z7+KXhfXrU3dh8M/H+g2s
sl0lxJ5+nXMbKsw86P8AebY7qFvMVfvRyfdb5a1PhL8APGH7R3xb1Xxl8ObjxJ8NPBmsTST6tr09
x5XmSSSM00Nl5Pl/aI933dyqq/xfMu1vPlUjTUvsx/rT/hh6lD4f/AXxf8Rfi14w+Aui6s2r/DDR
dW8y81TUoI520eNW3f6NIy/ubhvmjZY/lZlbcu1Wr9WvCfhXS/AvhnSvDuiWiWWkaZbx2trbx/8A
LONV2qP061z/AMI/hJ4Z+CPgqz8MeFbD7FYxHzJZJG3z3Uzffmmk/ikbu30VcKqqO8r5XF4qWIl/
d/rU2jHlHUUUVxFH5t/8FbmaPWvhgwbY62+o7W/4FbUfAv8A4KhQaL4bsdJ+Jeh6hqN/axrCutaS
UeS4VcfNJG7r8395lb5v7tfoL4i8EeH/ABW1s+uaJp2tNBkQnULSOby92M7dynGcDpWQ3we8BLj/
AIofw5/4KYP/AIivbjjKMsNGhWp3t1PKeFq+3lVpztc+OviR/wAFWfDNvok0fgbwzqt7rMiFYpta
SOG2iP8Ae2xyM0n+78v+9X5xeJPEmo+MPEGpa1rFzJe6pfztcXNxJ955GbczV+8n/Cm/AP8A0JHh
3/wUwf8AxFL/AMKb8A/9CR4c/wDBTB/8RXXhczw2C1hR/E5a2BrYj46h+d37Q37fnhP4yfs/6v4B
07w7rVhqV9DZxrcXLQ+Uvk3EMj/dfd92Nq4T9ij9rrw7+zJpniu21zRtU1dtXmt5Im0/y/k8tZPv
bmX+9X6lj4O+Adv/ACI/hv8A8FNv/wDEUf8ACnfAPP8AxQ/hz/wU2/8A8RWccxwkaU8P7J8stfiN
fqdeVSNb2mvofiR8e/iLZ/Fz4weKfF+n2txY2mq3P2iOG42+ZGu1V+bb/u19aaL/AMFDPCOqfs9w
fD3xj4b1vUb2TQm0W9vLYwssn7vy1k+Z927btb/er9BP+FN+Af8AoSPDn/gpg/8AiKT/AIU34B/6
Ejw5/wCCm3/+IrSrmeHrRhGVL4fMyhga1OUpKp8R+Mf7N/7R3iL9mzxs2t6MiX+n3kaw6jpUsmyO
5j/h+b+Fl/hb+Hc395q+99P/AOCqnwvn04TXmgeKLS92/NbR21vIpb0VvOXP/AttfUo+DfgH/oSP
Dv8A4KYP/iKG+DfgH/oSPDn/AIKYP/iKxxWPwuLftJ0dfU0oYWvh48sah+VX7XP7cGp/tHWsPh7S
dNk8PeDrebzmtpZN1zeSL91pdvyqq/8APNd3zfNub5dvd/sr/t2+Df2e/g1Z+E7rw1rGoass9xd3
FxbeT5MkkjHZ95933RGtfo1/wpvwD/0JHhz/AMFMH/xFL/wpvwD/ANCR4c/8FNv/APEVcsxwjpfV
/Yaeoo4Ssqntvaan4G3l5NqV5PdXEnmT3EjSSM38TM25q+4f2Z/+Cgnhj4O/BHSfA3iHw5q+rT2D
XEazWgh8qSKSRpAPmf8A6aMv4V+iP/CnfALf8yP4c/8ABTB/8RSf8Kb8A8/8UR4d/wDBTB/8RW2I
zahiqahUpbeZlSy+rh5c0Kh8Bf8ABKVoJPiV8R2s1dLP7FD5Ky/fVfOfbur9LqwfDvgfw74Xkmk0
XQtN0eSUbZHsLOOEuPQ7VGa3vWvExuI+tVnVta56uFo+wpciH0UUVwnYFFFFACDpXHfEb4U+FPi1
oL6P4v0Gz1/TjlljuY/mjb+9G33o24+8rA12VFClKLugPz3+JX/BJzSNQnkuvAnjG40cNll0/Wof
tMa/7KzLtZV/3lZq85+MH7GH7Qnibwz4f8Pz+G/CmtRaHbw2VrqWhX5t55LeNWWOORZmjjbbu+9t
3f7VfqZRXorMq8Pid/UnkR+Z3jT4R/tSePfC/jvw5ffDjTl0jxRdWt2Iv7atWbTZIfI3eS3nfdk8
iNmVv4vmqLwb/wAE/wD466z8M08A+IvFWg+HfBbakurfYSzXtxDcbdvyhVVdvzfd8zbu+av02UUl
NZlV5bRikHKfKHwh/wCCcfwz+G/2S71/7Z491O3+aP8Atr/jxhb+Ly7Vfl+b/pp5lfVVvbx2kKQw
xrFEg2qiDaqip6bXFUq1K0rzlcofRSUtZAFFFFAH/9k=