20240219
14352100
1.0
FALSE
lowmod15_SpatialJoin
002
Projected
GCS_North_American_1983
Linear Unit: Foot_US (0.304801)
NAD_1983_StatePlane_New_York_East_FIPS_3101_Feet
<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_New_York_East_FIPS_3101_Feet",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["Transverse_Mercator"],PARAMETER["False_Easting",492125.0],PARAMETER["False_Northing",0.0],PARAMETER["Central_Meridian",-74.5],PARAMETER["Scale_Factor",0.9999],PARAMETER["Latitude_Of_Origin",38.83333333333334],UNIT["Foot_US",0.3048006096012192],AUTHORITY["EPSG",2260]]</WKT><XOrigin>-17954600</XOrigin><YOrigin>-46918100</YOrigin><XYScale>3048.0060960121918</XYScale><ZOrigin>-100000</ZOrigin><ZScale>10000</ZScale><MOrigin>-100000</MOrigin><MScale>10000</MScale><XYTolerance>0.0032808333333333331</XYTolerance><ZTolerance>0.001</ZTolerance><MTolerance>0.001</MTolerance><HighPrecision>true</HighPrecision><WKID>102715</WKID><LatestWKID>2260</LatestWKID></ProjectedCoordinateSystem>
20240215
13091800
20240215
13091800
Version 6.2 (Build 9200) ; Esri ArcGIS 10.8.1.14362
lowmod15_SpatialJoin
File Geodatabase Feature Class
dataset
EPSG
5.3(9.0.0)
0
Simple
FALSE
0
TRUE
FALSE
lowmod15_SpatialJoin
Feature Class
0
OBJECTID_1
FID
OID
4
0
0
Internal feature number.
Esri
Sequential unique whole numbers that are automatically generated.
Shape
Shape
Geometry
0
0
0
Feature geometry.
Esri
Coordinates defining the features.
Join_Count
Join_Count
Integer
4
0
0
TARGET_FID
TARGET_FID
Integer
4
0
0
OBJECTID
OBJECTID
Integer
4
0
0
STATEFP10
STATEFP10
String
2
0
0
COUNTYFP10
COUNTYFP10
String
3
0
0
TRACTCE10
TRACTCE10
String
6
0
0
BLKGRPCE10
BLKGRPCE10
String
1
0
0
GEOID10
GEOID10
String
12
0
0
NAMELSAD10
NAMELSAD10
String
13
0
0
MTFCC10
MTFCC10
String
5
0
0
FUNCSTAT10
FUNCSTAT10
String
1
0
0
ALAND10
ALAND10
Double
8
0
0
AWATER10
AWATER10
Double
8
0
0
INTPTLAT10
INTPTLAT10
String
11
0
0
INTPTLON10
INTPTLON10
String
12
0
0
GEOID
GEOID
Double
8
0
0
GEOID2
GEOID2
Double
8
0
0
GEOID_1
GEOID_1
Double
8
0
0
geoname
geoname
String
254
0
0
State
State
Double
8
0
0
County
County
Double
8
0
0
Tract
Tract
String
254
0
0
Blckgrp
Blckgrp
String
254
0
0
Low
Low
Double
8
0
0
Lowmod
Lowmod
Double
8
0
0
Lmmi
Lmmi
Double
8
0
0
Lowmoduniv
Lowmoduniv
Double
8
0
0
Lowmod_pct
Lowmod_pct
Double
8
0
0
uclowmod
uclowmod
Double
8
0
0
ucLowmod_p
ucLowmod_p
Double
8
0
0
MOE_Lowmod
MOE_Lowmod
String
254
0
0
FID_WCTIGM
FID_wctigm
Integer
4
0
0
STATEFP10_1
STATEFP10
String
2
0
0
COUNTYFP10_1
COUNTYFP10
String
3
0
0
COUSUBFP10
COUSUBFP10
String
5
0
0
COUSUBNS10
COUSUBNS10
String
8
0
0
GEOID10_1
GEOID10
String
10
0
0
NAME10
NAME10
String
100
0
0
NAMELSAD10_1
NAMELSAD10
String
100
0
0
LSAD10
LSAD10
String
2
0
0
CLASSFP10
CLASSFP10
String
2
0
0
MTFCC10_1
MTFCC10
String
5
0
0
FUNCSTAT10_1
FUNCSTAT10
String
1
0
0
ALAND10_1
ALAND10
Double
8
0
0
AWATER10_1
AWATER10
Double
8
0
0
INTPTLAT10_1
INTPTLAT10
String
11
0
0
INTPTLON10_1
INTPTLON10
String
12
0
0
MUNICIPALI
Municipali
String
254
0
0
F1990_T
1990_T
Double
8
0
0
F1990_C
1990_C
Double
8
0
0
F2000_T
2000_T
Double
8
0
0
F2000_C
2000_C
Double
8
0
0
F2010_T
2010_T
Double
8
0
0
F2010_C
2010_C
Double
8
0
0
MUNITYPE
MuniType
String
50
0
0
SHAPE_AREA_1
SHAPE_AREA_1
Double
8
0
0
SHAPE_LEN_1
SHAPE_LEN_1
Double
8
0
0
Shape_Length
Shape_Length
Double
8
0
0
Length of feature in internal units.
Esri
Positive real numbers that are automatically generated.
Shape_Area
Shape_Area
Double
8
0
0
Area of feature in internal units squared.
Esri
Positive real numbers that are automatically generated.
20240215
/9j/4AAQSkZJRgABAQEAAQABAAD/2wBDAAgGBgcGBQgHBwcJCQgKDBQNDAsLDBkSEw8UHRofHh0a
HBwgJC4nICIsIxwcKDcpLDAxNDQ0Hyc5PTgyPC4zNDL/2wBDAQkJCQwLDBgNDRgyIRwhMjIyMjIy
MjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjL/wAARCADIASwDASIA
AhEBAxEB/8QAHwAAAQUBAQEBAQEAAAAAAAAAAAECAwQFBgcICQoL/8QAtRAAAgEDAwIEAwUFBAQA
AAF9AQIDAAQRBRIhMUEGE1FhByJxFDKBkaEII0KxwRVS0fAkM2JyggkKFhcYGRolJicoKSo0NTY3
ODk6Q0RFRkdISUpTVFVWV1hZWmNkZWZnaGlqc3R1dnd4eXqDhIWGh4iJipKTlJWWl5iZmqKjpKWm
p6ipqrKztLW2t7i5usLDxMXGx8jJytLT1NXW19jZ2uHi4+Tl5ufo6erx8vP09fb3+Pn6/8QAHwEA
AwEBAQEBAQEBAQAAAAAAAAECAwQFBgcICQoL/8QAtREAAgECBAQDBAcFBAQAAQJ3AAECAxEEBSEx
BhJBUQdhcRMiMoEIFEKRobHBCSMzUvAVYnLRChYkNOEl8RcYGRomJygpKjU2Nzg5OkNERUZHSElK
U1RVVldYWVpjZGVmZ2hpanN0dXZ3eHl6goOEhYaHiImKkpOUlZaXmJmaoqOkpaanqKmqsrO0tba3
uLm6wsPExcbHyMnK0tPU1dbX2Nna4uPk5ebn6Onq8vP09fb3+Pn6/9oADAMBAAIRAxEAPwD3+iii
gAooooAKKKKACiiigAooooAKKo3Ukq3QTzXjjZRtKhcE85GSOvT/ADmoVt0DFi8zk9d8rMPyJxTS
uZyqqLsaMkscK7pZEQerHFQnULQIWFwjgf8APM7z+QzVVLaCNy6Qxq56sFAP51QZkiuTdQxDymyr
SF8BiWHX/ZHP58dTl8pn7fsjSGsW7+X5UdxJ5nK4iK5Hr82MD3pn9qu7zBLdUWFtshmlC44B7A9i
O4rOiSOPyTcfdWIwlsnkqeMD1IBNNmVh9olSJo0gjWaOIDHmEFjyB64xj8fTBYTqyHprd3cIGQqv
qI4GfHtnOKjj1KWWDddXlwj8YjjRVJyMjGBmrVxGr3EmFUpIIvM4++u5hj37fhms+68m5Edvbo3m
RylRI0bAKpyFwxGCN2AMV0RnC9rWPIq4bE8nMqjk101Sf3Pf8BbIzS3qPLI+0uV8tnZuzdcnH8Pp
V++toooVmhjijlSRDv8ALzjkA9OvBNUrXzl2rJGBl8+Yp43LKcj64Y/lWleSkxSQwDfcbSVUdiOm
fTtUVJc0mdGDpeypRT3erv3KRuGk+0CQ7o3jEZuI0Khclhkgnpz1BNaUDiS1jfAAZAcDpyKos8kV
y0S3qrtUFvNG/cTnoMgj6c9aktLeGW2RmkeZVGwKylVGDj7n4d6g6mVLNp3ZBbTq6SbhIRyIgvAI
Prxj369jVkzx2mpLESscItxudz3B+UZPtuqxAUhS4YqI1WRiQPzzx69fxp0Eb5aaUje4xtAxtXnA
9zzQFxu+5mXdCEiUgEGVSSfwBGPz/CjzbqHJliSRAOWiJ3fXaf8AEmp3dI1LOyqo7scCo/tduQSs
6Njsrbj+QoER2zLLc3EsbAodq8eoGSfyI/KrEj+XE7/3VJqhBqET3TbNxikfBZ42TawwuPmHPIA+
tW7vmzn/AOubfyoBrUu2cfk2NvEf4I1X8hU9FFZneFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFF
FABRRRQAUUUUAMmiSeJonGVYY44I9x71lXU81hbs08e9lGFdQdrn3/u/j+dbFY+s3qf8eZJEbf66
QKSFH93joTWlJXkkcePmqdCU72fT16GPeag1xazNMzwbQFWEHBZj3PfFVLe4SErsuWiXaXd442OP
VdvIP5Vb1uaCaSDyyHwhy6kHAPH86bY2bB0mhgk2Da0mWI5BB+UfxD6133SpXtY+SUZVMcoOXNa2
ut+/TbtpsT2TW0MyF3aRWHmoNhb5wNucckHbjA/3qsXEou7qA27M6MjB1AK7xwRyeg/OrULLMGu3
ZQhXCc/dXuSfU/4VW8+cxWbLbuNjhWZiArAgr9cZIPSuA+rHXln/AKJPPKXd1jyEjJAAXkAAc59+
vpihW84EW0ThNsYQvGVA2sT0OCR0qwv29chxbS88EFo/0+algmSOFY5f3TxxgsH4GB3z0IoAzbiy
uVQxPKkp8mZ49iFMSEgg5yeck+nWtVWigtw6DCYBGOSSf5k1R+0pe3SK0oSDcQmxyHdh2JBBHHOO
/r2qSG0STT4ghYSBVwWYthlx1BPqKAfmWYUk8x5pAql1UbRzjGep7nmi2OfNBABEhyAenp+Ywfxp
uy8cktNFGMcKiFiD9SeR+A+tVzcNbXhe4URRmJjI3VWYEbSPfG7jrwPSgRGsd09iiCEY4l3JIMsQ
cgcjgk49eM0+ON0VXnhuZGC/OzTdfU7Q2PyqWGSGBpBtKySSbvKXlhnuQOmeuffmm3pu5rGcIqQA
qRmT5mxj0BwPrk/SgZL5dlGUnKQIW+65ABP40QSq01yImVySHBDZHKgYPp92o3gMNzaymaRwGKNv
OByCAcDABzx/wKr1AjKhW0uYoo5UmJ5Vsq6IWPLA9jyD6jtUt9bWqWrrvaI7CEVJSueOmAcGneTI
kTwPD5sTOzBo2AYZYsDg4wQe4PbNOjIilRp5JTIw2BnGF/TgfjQO5rwypPCkqE7WGRkYP40+s+B/
s1xtJAhlP02v/wDX/n9a0Khqx2RlzK4UUUUigooooAKKKKACiiigAooooAKKKKACiiigAooooAKK
KKAIbqY29rJKBllHyj1Pb9a521ubiGS33Oj29xIwBb7wPPU++M/j9K6SeFZ4HifIV1IJHUe4rATS
o28+CSSQ+XuiG1sABlByB26+9bUnFJ3POx9OtOUPZuyW+vmvv0uVLaK0uNVkLJlJWDwlWOMADII7
ZPOK3ndY0LOwVR1JrAvZWEEdtbwrHJbuFUp03Y4C/gcnNXEv1ng+0yA7bVC8iqer8jA7ev5itJxl
yKTODDVaP1idKCS66Lfv80wNrG98GWBV8xxKWZQHwOSB3xkL19TV69YR2jyN92PEh+ikE/yqvbyO
zu0YSWVv9Y+75Fx0UHHPX/PSpJLqCSJ4pVcORteIKWYZHoO3PXpWJ6RbqrJFFLqCGWMOUjymRkLk
8/jwPyNTW7+ZbRPnO5AfzFV4plimkNxujkdiAWHy7QcLg9OnOOuSaBDTbRT6m0xUHy4/Lf3JIYfQ
jH/j3tU1oqRJLDGMLHIRj0z83/s1Ns2V5rxlYMvnDBBz/AlRs8kd3cxW6hpHCyfMflUkEZP/AHyO
P/10AWpp4rdN80iomcZY4FULy3/tFJHQuY0jIQBiBI/rx2H5HPsKnS3ivIEkuP325QdrfdU9+PxN
Q3n/ABLYGltVRF2bBGMDn+Ejtxzn2+lAbCJOisstjHGYFUeYB8gwTkYPQnr+dKwErtPsMkZI3AuU
KcDjjhgeuPf34yGkluYYrdppDn5ViYfdx0DYAzn19K0RbC3aK1JZ3WRGjJcjeu7uO+0AfkK0nT5E
rnLhsUsRKTitF9/3GpPF50DpwCR8pIzg9j+BqFLt5I1ZbWQkjnDLgHuOvr7VL9phEpiMqhx1UnBp
sX7u5liwArfvFx7/AHv15/4FWZ1ChrkjmKJfT94T/So1aUP5F35TrICFKoQD6qQSe3588cVaqK4g
S5gaKQZVh+XvQBnTwB4DLvlRGlSNQjkDYWAJxnHrz2HpW3ZzmRWikOZo+G/2h2b8f5g1QhAltXtn
AR1Xy2C/TqPY9aWKWQxRXIGZYwQ6KeD2ZfzHHuKTRpTnyvU16KbG6yxrIjBkYZUjuKdUHWFFFFAB
RRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAVnapbSGF57Ussv8YXq6+3v6GtGinF2dzOrT9pBw
va5ysNvFcFMQKyAbki6k5/idu386sx6ZJCN0MkKv97BjYrux1xu6+/XFaEka2tzgYEc7Egej9SPx
5P4GknhW4geJiQGGMjtWsqjnuedSwsMO7RWvf+unkZ7xz2tzHIuJHlcFxHlc8YJ25weAOeDwOvQ3
ra6iu4jJDuKbiuWUjOPTNc9PJcJO32oPIIFIMQGQ4OeO5I4B5rat7lBbR/ZoJZoyPvKAM+p+Ygmi
UeV2HRre2hzpW1a18iWzBW2VD/AzIPoCQP0AqcgEYIBHoaqQSXW6UG1KKXynmOBxgeme+alb7Www
ohjP94kv+nH86k1A2qiQyRMYnY5baBhz7j19+tRrB5F6kgckSBg5OMs3BX8gCKSMTzlz9pZUVtqt
Gq8kdeoPfj8KSCzintYWuN0zlQxLuSN2OoHQHntQBHPeppzTKylsnzEVOvOc5/EE596Zp6G7eS6u
UPmZCgZ4AwG4/P8AT61manLKGmiVnZVYbpCM5IHAJ9vT1NaWlQWz252r+8JOXXKkrk7RuHXAwOvF
ayhywTe7OGjiXVxM4xfuxSXzuaBtojdC5K/vQu0H2qnJciR7WaSB0RW3rJkFTlCAOucnPp1q0IJF
BAuXI7BwpA/QH9aZajNubWZld4hsbHGRjg4zxkVm22dkYxjey3HQwA25WZdxkJZ1bnk9vw6fhVJ3
ubWNWa2lkMMjHzC642EnvnOACO38NLBFO/kzqFklR3Vnkk52jIxwOM4BI9Rz7WjO/lg3NuEjf5SA
27bn+9x/LP5c0ixRdsrDzbeSJCcb3ZcA/gfwp7XUKTeUz7Wx1IOOmcZ6Zxzim2p323lOCTGTGwbn
OOMn6jB/GqxW1nhaztYk2+Z848vCqQeSeOTkUCFmmlEq3UNuXjX5XYMMsnXIHcDqOc9eOasW23dP
txsMm5cHg5VTn881YrPgimF8y2iK8eCGcnCr3weOcHOAP72OMUDSctEX7aTyLjyWP7uQkx+zdSP6
j8av1WhskjcSyN5sw6MRwv8Aujt39/erNQzsgmlZhRRRSKCiiigAooooAKKKKACiiigAooooAKKK
KACiiigAooooAgvImltXVMbxhlz3IOQP0qtHIssayKcqwyK0Kw7154LiW0hUb59zwvnATPXPqQ2T
+Iq4Jt2Ry4qUaceeRQ1Hy7i6uWNvJiKLyPO4wC2B8vOScMe386sJc+bJJ5EZguhIAyEbg2ccsB7d
/brT0t7eAK15cIxXlVLYVT6gdz7mufN1LDJJHbXDiNnJyp5bn866oUudNdTwMRmH1aopNWi76K1/
V/8ADnUQ30UrKhZVdshcMGVseh7/AE6+1PuGZnS3RtjSAksOoUYzj35FYunSWzsxvBGCsewKRwVY
85GMcbV/KtG3Eqs1yhM0TgBFb7wXsQT16k8+1YSi4vlZ6tCtGvTVSGzJZZXt8RQRx7UVR8zEYycD
HB9KpyF1lgtLa5d58EEkYRFC4J468lfWpHdJLWZ0b5hcLvdhgqAwPIPTAploJ1lKWqRCIRgDeMbB
24HUnJbt29eJuauN00xsltcrbx2LPAscjYLrnd0JyQfUirdotwLiQXTRmQD5PLXA259zyR0/L1pl
gouZZLyWFBJu8tH28kLkbgewPPH+NTXDE3MXkorzIecnAVT1ye2cDjvgfWqlNy3MaWHhR0j6fd0L
VULi5WG4kkJXeoEUYJ6k8njuOnvwcUkEk1zcSRTybNvOyLjIyR16noOmOtXIreKFmaOMBnOWbu31
PU1JtsQQmRQViiZifmaSU7QSfbr+lRwRS3cTi8kJId0aNAUUjJx78rg9cc1fqCJgJbnJAw4PPptH
/wBegLka2f2Yf6G3ljOTGeUbnJ9wfcfkaS3m8sypL/r2kzsX5iQemPw4/CrEfm3P+pGyLg+a44I/
2R3+vTnvVuC1it8sozIwAaRuWbHqfxPHTmk2awpOW5XjtJZsNcHy04PlKef+BEfyHp1NXURY0VEU
KijCqowAPSnUVFzpjFR0QUUUUDCiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACo
Lu0hvYDFMuQehHVT6ip6KabTuiZwjOLjJXTOag0+VN6K1qjxtsLLDls+pz6jB/Gs/TbS6OoGVo+V
+f5xwTnH54zitqUxHU7wGOfAZdzxs2C2xeynOcY7U6Ke0jlIE22RsDbK5DHHs3PeuhV5WafU8OeV
0VUi43917FN1uBCbprglWGyZGATYM/NggduefQk5PFXLe6zC7TIsSoocYOV2EcH9CPwqC6lktGzD
LGxmckRkcnjGevODt4H6mq1nY3UUDxSzF7lUXyckqqqOmQOuCT1z0FZHodCK9mDRyOY2RwWIYqf3
nzcIQByMYJH6ZBxakuntIvKkYrLMd/nBeNpYAn2KgjrxwOtUIZf7OvmiECW4J3L577VPXeQe/bn0
xwOat2f2qOaK2upFJRt6OcBWXG3ao78Hue/4UhtF2a7ig220ThSoALddo7ADux7D/JmtmgEWInyO
SxY/Nnvn3qrDbIba3a3jjE9sxGD8oz0cHjv1+uDS3DxysIp1MUoPRVL+YvcDjkevp+VMRC65lt7y
ZpBEVlJ8rd0baVzjn7q/nU1p5TSILa6acL80jmXdkHOBjp/+qpbSZVsUaTKjcyoCOSNxC4HXkY46
1NFZSzzGZ90CMoUoMbmAPGT26npzz2pXsVGLlohTKS/lxKZJO4HRfqe38/Y1JFpqecZ7jEkpC/L/
AALgkjA7nnqfTtVuOJIYwkaBVHQAU+pbudEKaiFFFFI0CiiigAooooAKKKKACiiigAooooAKKKKA
CiiigAooooAKKKKACiiigAooooAKKKDwKAMkTRJLO22Tc0rbisbHJHy9h6AUfbbYv5byhHIyFkBQ
n6A4zVW2u7k24kFmzq7M4KyDuSeh+tEeo232iU3DLbsEUMsxC45b1471v7OSR5KxdGctHvtdNX9L
odC4ku45IoIVWQFi2352Tsc9uccc/hU1yxW4hMUfmSg4IHZD1ye3IB98Uy0l8yNrx5I/LeNSAo+6
oyeTnnrVSV75o2vgywxMgGwDLBc/e57jOaUYOQVsRGlur+nbqyG3ubiec3s1t5qopjQRSKR82Djn
HsCeuT6Vp/YohboJcuUTB3yMVzjB4zTBasLJIhessS4KyBV3YHTJPH6VDF9pnslhMgmeYeYxfGBG
einAHXp09fTFSdF76osabai2ti293eYiRi/XO0AD8AAPWp1eS4bbbKGHIMrfcXnH4nrwPTkim8Xt
mwKsgkBXkA+2fQjv71dtJ/OiIKhZIztdR0B9vak3YunFSeo20sYrUA5aSQZG9+SAT0HoP8BnNWqK
Kg60rBRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAU
jfdP0paKAZzlg93LYwxwqsSBAPNfkn6D/GqUFs1vrkhRpCIwC0joXzkeg/GtKDTLbytrxfMpKk7j
zgkZ6+1RXOmW8X7yOe4hLELtjk+9zgdc9Mmut1VZ8vU+bjgajlTVX7D3v2XRWS3t5lP7HHLHayyy
yFZVO+ZehYkYyBxj8KtX91e6fakyGCRcEZAIPAJzjp2p11byW/h0xGX5oohvJG7dgc//AK6yFaZy
087O9sIWjZmAOQcLgH15J/DmnBrl9OgYiE/btK6UvtX0SW/l6bas1vLt1tIreeCdnYCMRSM21jjv
glcYBP0qpZX629hKtzL5EnAV2POAoHG7vgZ981ZubhLyMKGR4o1DOdpK5wc5bIAx1rMWVZtP1RJE
KzSxpEqtgMWCBfXpk1haTl5npKdKnSTb91HQLDdQKiRSJIgUL+84K46Hgc+44/CoY797cpcyxtsV
/ImcEYI3Y3Yz2P8AM1XstZnuZBF9kLsASxRhwPxqxMkptkVYSGe5D7HYA8HdzjI7U5wcXZk4XFQr
R9pTd0b/AForO0y5BHkE8AExgnkAcFf+Anj6YrRrE9NO6uFFFFAwooooAKKKKACiiigAooooAKKK
KACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooA568gWVtTHlI0olCRFxkAsiYPOe7VDbx
bROJdOJUkIGiCgBQB/tZznPPXpSX0lwn2u6jlUJ9p/1ZX7xXAHP/AAEVBb3Ukm6K7nmjiaNncKm0
DJ55wTjB68V0eyaje54v9oQlV9movV/L8+pO6zTTKSLi4iQqF24XI2kEg5HOSOT6HFQmzF7dA/Zl
RZlZgz4yAu0Dpn8McEGq1vMY7KSQSzXLpKytGzEBnJOEABA54PTAzV67hkt9IRZzEjx8RRxqZMt2
UDjP0I7Vmm07o7JwjNOMldMzLh4LGC4tF8m5eXI81cHaMYx9eDxmqSGWR2CbmByeM5Pf+pNW5ZVu
7FZojCC4DMiEZ7449FHH8+lPtUksdSj4JGT8yoXH930Hcgde/wCXdCrBQ5nufL4rA4ipiPYxT5Fb
pok307/8OT6EfLlaVC0hY+W6KpO3pgk9BW0SL5cGIJt2yxO2CevXHbp69DVVpZ2lERVHvAm9do2r
GRjKk5PHI45659KdZx/anE6vNHDGDGkZ+U84yCevBGPz5rknNzk5H0GFw8cPRjTXQkbzYXuWLBnU
LNGVXHzYK4698D8zWzbzi4hEmCp6Mp/hI6iuWv4pIUuLxmDtDOnlqecgY79R1PT0Pqak0/W1iv8A
ad7xzv8AOzcYPABAHQdvoB6VKpymrxRrLG0cPJRqytc6qiiisj0QooooAKKKKACiiigAooooAKKK
KACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooqO4lEFtLK3RFLH8BTSu7ClJRTk+hx8s8sP
2Ys5eN5GkCFRjO498j1Jq4kE062kbD7POELb12uQgOVXJ57j8qpbjPLZRwZkMSLkBdwyck55A9O4
qXSZZYX8qCAMJSAHdyMKoxnHOOc8A4rsrQbeh8xl2IhTg+Z7tJbu+iX3XJ57ERXw3vJLblxKybM+
Xgfe45JJA6ep+tQWvmSsn+tO5cW0gIYRbh8x564wcHnp70lxfXUV80SzKkcjZM6r1HIOASeBjH1+
tRIsxu47oRC4gSBUVCoIkYsQPpjGAff0rncWkpdz1qdeM6kqXWNvxLsdvJY3DfZ0eSCFeuwcOcZO
ARnC/wB0c7jnmoTbBLlYmkKW0cBAuoyBgMc88cdM5/2RzzUMjXUViyxSSRFEYKS5C7wM5B4JJJA2
nvu9K0rWeO0kYTM6xuilXlI4AGADj7oPOB9fpUmxAskr28Xk/wCsR8KACqhwSDz1YnnJ9Mk+9u1S
d0aN5mgcMWZVALHJPOTkYPbHT1qGziuoyxit4zEjv5SPIU2hjk5GDzz+Aoub5yqzjyUeIH5t+5HY
8BN2Bwe57YHWmS2UdT86CeSP7VI+Tv2FVzt2gbuB05xVbSYd+sW32rdksCM9DwcfqKuTTyRoVieF
pNwUrIhjMzHBO45Jx8w/E46VGYbyLU7aaKBRHK0bKFU7QeScjPGBnniuinWSi4tHj4rLJ1K8a0JX
Sadm/vt/kdpRUNtcrcIeNsi8OhPKn/D3qauM+mCiiigAooooAKKKKACiiigAooooAKKKKACiiigA
ooooAKKKKACiiigAooooAKKKKACs3W5kjsRG7BVmkVCT2HU/oK0qwPEcgwF/eAxxMwKgkbm4GcfR
q0pW51c48wclhZ8vb/h/wMKS/VNWluLV1G47Qd3AHAJI79P6/W1psqR6fcSqz7hABnIyCS2NuP61
l28El5IsMezOMruON2P8/wCcU8CSG1miMKHzCCrnqOccY+n6V6MqStZeX3HxlLHSUvaNaJO2m0nq
/wAX91hbcCcSv8gdVA3tGdi9BkgcDOSxPH3fepNLvoIDKt6AkJdpdrkEZ6Io9flH0yB3NV1MU11H
ZYeGNpPM3schSQBjj1Y+uOnFSxwyRxby6ENIYQHYsjNg4Ye2Byeepx0rjnypNbPsfRYd1ZThJJOL
WstE32XyNZIpIbRJ5D5I3ZkmaQMQpOPk7AYxzwfqamsDBIkCEMsahSPMz+9fHqeuMdPUewqk5KaU
Y3nVpFBRJpzkkbsLhewIIyx9e/FLLcIFuLdrlnixITDwGALcYBGccgfjxWSV3Y75yUYuT6CahdSr
eXKWrzNLn5Ujbrhfm4/LntzUNsj3lxvllDqAsiwJyD2AABOBkEZPpz1OEsrSSeRZMg7AQqYwHbqV
yDxkc9O59K17OeK3CJIgilFuGlQLjBXr9eTwe9b1Zcsko9Dy8DSdejKVZXUnda9NzOmime4EVtbv
5uMTgghGfknJIwRgnnIPI9MVuRW0gkEk1y0pDEqu0Kq59O/AJHWpLZGSEGTPmMdzZ7E9vw6fhUtY
HptkboxZZI22Sr0b1HofUVbtrkXCkEbJV+/GTkr/AIj0NVXlCFVALSN91F6n/wCt71PbWrJJ58xB
mK7cKflUHGQPXp1P6VMrG9Fy+RaoooqToCiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooA
KKKKACiiigAooooAK43X71bh7hAqkrII1cEZAXse/UnmuyrNvNDsrwszIY3bqyHGfw6VtQnCEryP
NzTD4jEUPZ0Gtd/M4myjXzVZ94Qckp1Ax2+vT8acZF35YuI1VhHk88DjBxxyfwzWtceGL22bdbSi
VBzj7rVS+zX99cparA0bRA7UOVCggZOfcj9evau91E3dPT8j5NYKpTj7OdNqa1ta/Ntpfy6pFKKd
TNEZogyIcfKdvB4Y8dSRnv6VduJxcJy+/wAw7h5xwQc4yrAHBUEYHuTzVKa1ktbhoZUKup59vp+l
TwxuUkyjFuUz5TNztJ6jv06+tRWowa5kbZbmOJhNUJK6V9Oqsv8AgD0unihligATdhnZOcleMg56
fd6UR4kuQ20Rs+Au4lhGSMEn36H/ADmqZBVmGQ2R1HQ1pWWnCZImaRv3wdRn7u5emf1/KtHTjCFj
lhi6+IxHtN2nddlrb9f1LmmWsqoyEp5E4Oxt27Dr0/keR6VoS2Ki4tpC5aQuRI56sMbsewyq8elS
I5vLHKqBMh+6eMOp6fT+hqRnEn2WQZwzbhn/AHGrgqNuXvbn1eEpwp0kqXw7/eWKjLSSOYoFDOPv
M33U+vv7fy60Rq959wlIO8g6t/u+3v8Al61fiiSGMRxqFUdAKzbO6nSvrIZb2yW4JyWkb7zt1P8A
gPapqKKg6dgooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAo
oooAKKKKAM660mOe/W9R9syjGGG5T+FUpdJuSmyVvPUHeGQ7SH9SCeRyeM4xxiiiqc27XMY4elFy
cVa7u/Uxbq1CjbchV8kHYCpQyjI+Xn8h1znvg1qwSjUrN1ijELxMGj579QaKK7FJypc73R83OhCh
j1h4fDJa/j18gS6WKZbrBCTHy5owMssg6YA5Pp+VX7fTd/zXK4jDl44c5wTnO716njpz37FFY11a
1j0sqbmpc3k/v3/zNSiiiuc9gKKKKACiiigAooooAKKKKACiiigAooooAKKKKAP/2Q==