20231130
22043900
1.0
FALSE
SLF_Suitability
002
Projected
GCS_North_American_1983
Linear Unit: Meter (1.000000)
USA_Contiguous_Albers_Equal_Area_Conic_USGS_version
<ProjectedCoordinateSystem xsi:type='typens:ProjectedCoordinateSystem' xmlns:xsi='http://www.w3.org/2001/XMLSchema-instance' xmlns:xs='http://www.w3.org/2001/XMLSchema' xmlns:typens='http://www.esri.com/schemas/ArcGIS/3.1.0'><WKT>PROJCS["USA_Contiguous_Albers_Equal_Area_Conic_USGS_version",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["Albers"],PARAMETER["False_Easting",0.0],PARAMETER["False_Northing",0.0],PARAMETER["Central_Meridian",-96.0],PARAMETER["Standard_Parallel_1",29.5],PARAMETER["Standard_Parallel_2",45.5],PARAMETER["Latitude_Of_Origin",23.0],UNIT["Meter",1.0],AUTHORITY["Esri",102039]]</WKT><XOrigin>-16901100</XOrigin><YOrigin>-6972200</YOrigin><XYScale>10000</XYScale><ZOrigin>-100000</ZOrigin><ZScale>10000</ZScale><MOrigin>-100000</MOrigin><MScale>10000</MScale><XYTolerance>0.001</XYTolerance><ZTolerance>0.001</ZTolerance><MTolerance>0.001</MTolerance><HighPrecision>true</HighPrecision><WKID>102039</WKID><LatestWKID>102039</LatestWKID></ProjectedCoordinateSystem>
20231130
22043900
20231130
22043900
Esri ArcGIS 13.1.2.41833
SLF_Suitability
<span>Potential distribution of spotted lanternfly in the United States adapted from Fig. 3 of Wakie, et. al. 2020.</span><div><div><br /></div><div><br /></div></div>
Potential distribution of the Spotted Lanternfly in the United States based on MAXENT modelling of suitable habitat.
File Geodatabase Feature Class
dataset
Esri
8.1.2
0
Simple
FALSE
0
TRUE
FALSE
SLF_Suitability
Feature Class
0
OBJECTID
OBJECTID
OID
4
0
0
Internal feature number.
Esri
Sequential unique whole numbers that are automatically generated.
Shape
Shape
Geometry
0
0
0
Feature geometry.
Esri
Coordinates defining the features.
slf_suitab
slf_suitab
String
200
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.
20231130
/9j/4AAQSkZJRgABAQEAAQABAAD/2wBDAAgGBgcGBQgHBwcJCQgKDBQNDAsLDBkSEw8UHRofHh0a
HBwgJC4nICIsIxwcKDcpLDAxNDQ0Hyc5PTgyPC4zNDL/2wBDAQkJCQwLDBgNDRgyIRwhMjIyMjIy
MjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjL/wAARCADIASwDASIA
AhEBAxEB/8QAHwAAAQUBAQEBAQEAAAAAAAAAAAECAwQFBgcICQoL/8QAtRAAAgEDAwIEAwUFBAQA
AAF9AQIDAAQRBRIhMUEGE1FhByJxFDKBkaEII0KxwRVS0fAkM2JyggkKFhcYGRolJicoKSo0NTY3
ODk6Q0RFRkdISUpTVFVWV1hZWmNkZWZnaGlqc3R1dnd4eXqDhIWGh4iJipKTlJWWl5iZmqKjpKWm
p6ipqrKztLW2t7i5usLDxMXGx8jJytLT1NXW19jZ2uHi4+Tl5ufo6erx8vP09fb3+Pn6/8QAHwEA
AwEBAQEBAQEBAQAAAAAAAAECAwQFBgcICQoL/8QAtREAAgECBAQDBAcFBAQAAQJ3AAECAxEEBSEx
BhJBUQdhcRMiMoEIFEKRobHBCSMzUvAVYnLRChYkNOEl8RcYGRomJygpKjU2Nzg5OkNERUZHSElK
U1RVVldYWVpjZGVmZ2hpanN0dXZ3eHl6goOEhYaHiImKkpOUlZaXmJmaoqOkpaanqKmqsrO0tba3
uLm6wsPExcbHyMnK0tPU1dbX2Nna4uPk5ebn6Onq8vP09fb3+Pn6/9oADAMBAAIRAxEAPwD2XSNR
fUElZ1RQpG0KSSAR0Pv1rSpqoiFiqqCxyxA6/WnUkmlqAVDdz/ZbSWfbu8tS2M46VNWNqF/Obqa1
gaIIqBXLIWOSM46jHBHr1qalSMI80gNGyulvbRJ1GN2QRnOCCQR+YNMvL02k9mhj3JcTeUWz907S
R+ox+NR6LCsGj2qISVKb+f8AaO7+tXmVXxuUHByMjoapXtqAtFFFMArEvbzV7a6kISI2+4BMW7uS
PqrcH8K26KmSbWjsBhDxBIqt5toFKLuYMzI2PXayjitmCTzoI5TG8ZdQ2xxhlz2PvTZ7W3utn2iC
OXY25d6g7T6ipqUVJbu4BRRRVgFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFF
FFABRRRQAUUUUAFFZ1tYXq37XN5qLTKM+XDGnloufUZO78a0aAA8CuVub211RlaxZ4rqdfuSYUSD
GODyNwyMeuMduOqrD8Qskps7T5tzzKxx2XO089id3H0J7VnUScbPYDaRFijVFAVEAAHoBTqwL+PV
MXls9ut5b3C7YcMFEfXg8E+hyTjjt0rYs4Xt7SOKR97qOWq76gTngVzl3qxvkEQS4tUQF5Ff5HIH
TgfMB37dq6OoLqzgvYwkyZwcqwOCp9j2qKsZSi1F2AydHuJobyWzlFwQ53qZmZihwOAxyCD14PUm
t2qenabb6ZC8VuCFdt7ZAHOAOgAHarlVCLjGzAKKQuoYKWAYgkDPJxQCGGQQR7VQC0UUUAFFFFAB
RRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFMlmigjMk0iog6sxwKfVa90+11BI0uovMR
G3BSTgnBHPqME8UAM0/UF1FZJYopFgBASR+PM7kgenTr7+lXKhnuIbSMNK20E4UAZJPoAOTUdlqE
F/5nkeZhDglkIB+h6HpSutuoFqiiimAUUUUAFUTYs+s/bZHBjSILGg7Nzlj+BwPqavU3evmFNw3g
ZK55x60WuA6iiigAooooAKRmVEZ3YKqjJJOABS1late2e1rGZZpJGCuEiU/3uMt0HI7noKUmkrsC
hqmr2t1ixWE77gPHHM6DBXHzEc59PY8VPozi0stRdIGZUuMhIhy37tOgqoF/cGNbaKMu6u0hcu/D
A4yR7fQZqey+0i/CWjhQxDzhlyuOn13HGBz29q4YV+asle+nQDctbiO7to54t2xxkbhg/lUtFFd4
BRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABVS61CC1yuTLMOfJjwXIzjOPT3qS
4ga4whkKwkEOq8Fs/wC1279KWC0trUYt7eKIdP3aBf5UAclqN7Kl5BdXF0BG5MckKxkyIcEhEHXJ
wBn1APTiultL22ENpF5b2pmBWGGVdrfL2x9Kt+VH5nmeWu/+9jn86hv7JL+zeB2KE8o68MjDow9w
azp0+S7bu2VKVyzVa41GytJBHc3kELkZCySBTj15rndTl1m2Dw/bnZ9gYmFV3Yzjjjg8dOc8inpM
qL/x5TuTyzMULE+pJbrWFbFqnoldjhFPd2OoopASVBIwfSlrrICmCNBKZQvzlQpPsM4/mafRQAUU
UUAFFFFABXO3Flc2946RpJcNMcpI2Tjnox7Bc/l05roqKzq0o1I8sgOZfzLeXyblfLk/hOflceqn
+nWrWlylNUeLGRLDu+m1v67/ANK17i3jureSCVdyOpUj61QsNNmtb15pZVdQnlpt4LAkElh68Dp7
1zQwvs6ynDYDRlDtC6xOEkKkKxGQD2OO9ESNHEiNI0jKoBdgMsfU4qG+nuLe1Mltb/aJQQBHnGea
sjp6V2gFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRVaTULSKRo3mUOpww5OOM/1FFrqFveM
6ws25eoZCpx6jI5FLmV7XAs0UUUwCiiigAqvc3tvZhfOkwX4VQMs30Aqd3WNGd2CqoySegFcxLce
a0t/KuCy8DHKoMkD68k/U1hiK3so36sCJvtt3ql1Lawny5HBYsMmP5VAyM/7LHAP8Q6VYtNGvL61
juLq5ltZGXPlIMYHuD0NSWrSpe2unRMFfJuLx0bkHAIT36qD04xXQ0oUIP3pK76gZ+jTeZp0cbOW
lhHlyZPOR0+uRg5rQrk472NboNbXMcd1jaUY8kejL17/AFFbdlqn2iYQTxCKUjKlW3K3qAcDn2pU
MQppRlpIDRooorpAKKKKACiiigAooooAKKKKACiiigArJvNWmt9RaCOKN0RVZgWwzZ64+nH59q1q
huLWC6ULPErhTlSeqn1B6g1M1Jr3XZgZ82uRia2S2VZll+98+1k+ZVwRjg/N3x0rWrmZIPLlntZM
sqNhWJOSpAI565HTPtmlw/e4uD9Z3/xri+u8knGa1A6G4laG3kkSJpWVSQi9WPpWCNSv5AZRKoIJ
xF5e0cH7pzznt2+lT2upXFvAsUsYmKcLJvwSO27Pf371T3EebNMVVnYyPg/Kv/1hU4jFLlTpS1A3
7W7iu4g6HDdCh6gjrVisPS7Lzbz7c8XlhOIyUwz8EEnvjnj/APVW5XbSlKUE5KzAKKKK0AKKKKAC
iiqLavZpI6F5PkJBIiYjIOCMge1JyUd2Bm6mFtdUZmO1Lhd+49Ay4U8+42/kagkj34ZTtkXlHHVT
/n8627i+shap58yolwhKq33mUjnjrwDz6VhTRG1EUEV0LmQhWDIoCrHnq3JJyAcY7jtXnYrDtS9r
B2AsPe3003nB/s7Ku0Rq29D6kggZ/ngdRk1a0KS5ZZ0nkeVA5ZJGB6lmyoJPQcCqVEbzQF/InaMO
OVwCM+oz0NZUcZJTvUegHSEgDJOAKzf7atmY7EmePtIq/Kfpzk/XGKynRpVKTTTSoeqvISp+o6Gn
1rUzD/n2vvAmvb2S+BhRWit8/Nn70ntx0H8+nFULlv30abC7FWKLtyu7GAW7YGSceoFWajlmSGB5
mYbEUsSPSuN4ic6imwL+g2zqbu7kYu00hCs2M7R16Dj5t36Vs1R0eKaLSoBcACVsyMo/h3MWx+Gc
fhVmQzhv3aoVx/Ea9uCtFJgOlhjniaOVFdG4KsMg1Ui0m2guEmj8wbDlULkqDgjPP1q9RVOKe6AK
hhu4LiSWOKQO0Rw4A6Hkf0P5U+ZpFhcworyAfKrNtBP1wcVi6Ptsbg21xJuvJQNwXlVwC2Cf7xyx
/wA8ptpoDdoooqgCiiigAooooAKKKKACiiigAqOeaO3geaU4RBknGakrL1wSfZYjjMAkBmwM4A5B
+gOM/wCGamcuWLYGe8z3M8lxIuzeflQ9VUdM+/f8aKbIxRMhSzEgKo6kk4A/OtKDRYfLBumkmlK4
b5yqg98AY/M8141OjPEycgM+myRrLGyNnDDBwaZbljDhs5VmU5OehI69+nXvTQ7boz58bl5GRoQu
GjAzhjz7Dt/EPxxVOV3boBYM94xBe8kyBgbAF/Ejuf09qki1C/iGxpI5xnPmSLhh7YXAP6fjUVFW
sVWTvzASS3t9MNrTpGuc/uo8N+ZJ/lV7TtUhnt4I5riM3TZVlB5yCRyO2cGs2o5Ildf7rBlcEDoy
kEH8wK2pY2cZXnqB1FFcxKhuJDJct5rkAfMOBj0Hbr9as2d89i2yVpJbY9yS7If1JH8vp07IY2nK
XLsBvVzPS5ugPuid8A9uef1zWm+uW2w+RHPK/ZfKZP1YAVmKG3SSPjzJHLtjpk9hWWOqQcFFPUBP
MVtM+zOhMlvOIoG3FcKV3AnHUAbhjvtpVREztVVycnAxmjy08zzNo34xuxzinVw1azqWv0QESSsz
8xlUYkI/ZiDgj2P86lpgiRXLhQGPU02SZlkEccMkrkE4THA9ySBWcrN+6NJvREtFQw3Cy5UjZICQ
0bEbhg0TOxZYYj+9kOAeu0d2I/zzilbWwJNuw4zxLKIjIgkPRSeagv2jjtVQgYLDC9jt+bH5Kavr
aQrAYSm5G5bdyWPqfeqz6cwhf960jIhEO8fdPYk9zwOacJR5lc39g1ZnSwRmK3ijLFiqBSx6nA60
5kLHO5h9KSGVJ4EmjIZHUMCPQ0+voznCiis7V7qa3hiSBkV5nKbmBJUbScj8hSlJRTkwMx7y9uSy
tMVh81mUxttYr0CnHYdc554/FbNB/alqiE7gzytkkkjaQST9WH50xEWONUQYVRgD0FaGixZ+0XLD
O5/LQ/7K9f8Ax7d+QryqE516ybei1A1qKKK9YAooooAKKKKACiiigAqK5nW2tpJnIAUd+57D86lq
K4torqExTLuXIPBIII7gjpSd7aAUYdbgcos0U0LMQDuXKg/Udv8AGtJ1V0ZGAKsMEHuK5mayjsru
W2IBjmBkQHuvAIPuOMnvn61PDd3ltwkolQDAjl7fRhz+ea41i+SbhV0ArXNo+nzG2FzM6iJZIpH2
lgyk56AA4+XqO/eumhYvBGzfeZQT+VczOJJ1nlmbdLIhHXhRzhR7DNbk16lppqTH5mKARoOrsRwP
89KMNODlNx20Aw4TnzfaeUD6B2AqWmRqUjAY5bqxA6nufzp9eTUalNtAFFFFSAUUUUAFFFVDdMko
kkaJLRiyq5PO4Y79Ofm/L3ppXGk2W6a7rGu5jx9M01biBwSs0bY64YcUttH9omFww/dpnyge5/vf
4f8A16VrblQg5Owkc0cpYI4JU4Ze6n3HankhQSSABySanmtobjHmICR0YHDD6Eciohp8PALSsgOd
jSFh+OeT9DS5omrw7voyr9vtNm/7RH5f9/Py/n0pBcL9rQ2kqSyuFDRqQ2UB6+2MnmtWkCqudqgZ
9BRzrsXGhyu6Yya3huFCzRI4ByNwzg+opIbeKDd5aYLHLEnJJ9yeTUhIUZJAHqag+3WhfZ9qh3Zx
jeM5qVzNWRvZXuWKKKwNT1Np3a3tn2wjh5FPLHuAew9xVU6bm7IqMXJ2R1OisG0W0KsGAjAyDnOO
Kv1yXhzU4bIy2txL5cTHdGzt8qnuPbsfzrQm8VWUcpSKGedRxvQAAn2yRn619FGa5U7nFPDzU3BK
5u1j6+SiWkoRnCytnaOQNjEn6YB/StiszWZ/3AtEzun+8fRB1/Pp+PtRW5fZvm2MDLmfyoJJP7ql
vyFa2mab9ikllErMJVQKh6IFXH6nJ/GstwpRg4BUjnPpWlols0Vq0zvMWnbdtkcnaoJ24z0yMHnn
+VcGXvWSsBp0UUV6YBRRRQAUUUUAFFFFABRRVG71SK0uPIMUskmwORGBwCSBnJHofypOSirsCe6s
4L2NUnQsFO4bWKkH6gg1katZwWNus9usqSFlXglk6/xAnAHv1+vSnyardSuDBGsKAdJlDEn/AIC3
A/Gq08lxdbhPcMUYYMSDauP5nPua462JoWaeoBUaQqjKdznYCqBmJCA9QPTt+Q9KkoryFJpWTAKK
KKQBSbgGC5G4jIGecf5IpaZIyRje3bgEDJ57D9KAFd1jRndgqqMknsKSG1+0IJrjeC2dse4gKO3T
v9elEUEk7rJOuyNTlY88k+rf4VepOVtEdVKlbWRU+wgpsNxOV6EZHI9M4z/WrSIqIERQqqMAAcAU
tRNc26TrA08YmYZWMsNxH0qbtm6jGOwslvDKQZIY3I6FlBxUlFFK5RQm1aGC/Fo8U247RvwNvPTv
n8cVPdXsFmFM7ld33QFJJ/KnTWkFxJHJLGGeM5Q+nT/AflWRrkitdwRg5ZEYsPQEjH8jW1OMZyUf
vKhHmkkWZtcgWP8AcI8jnoCpUD6k1lrqF8rlzdOS3UbVx+AxxVeiuyNGEVsdkaEFvqE2bmTzLg+c
/q4Bx9OwpNqldpUbcYxjilorVaaI1UUtEh7TXDwiF7iVogMBM9vQnqfxNMAAGAMCiihJLYUYxjsg
ooooKPRpYo5kCyKGUMGwfUHI/UCudeY3V5cXDDB3GJVz0CEj885P4+1KLfWbX7TJAsjSBRu3yhvM
x02ZHXHrj8aiWIWU72byqzqQc9CxIBY+/JPNXjJSlS0Vj5gdJGJ9kLcrJIqMPVSwBH5Zrp65tCBd
Wx/i85do9eef0zWtqGpCzeKGOIz3MxPlxKcZx1JPYUYCypt+YF6qmo3rWFsJxC0qBwJNp5Re7e/0
q0udo3ABscgHIzVbUrlrPTLm5RFdooy4Vjw2B0rvYE0E8VzCs0Lh42GQwqSuXtS+nNFJGJZQgw8a
yEbhjGQCdueh7VZudUuJoyQfscIGWJIL/ieQP1+tcscZTceZsDforl49QuEikWG9zHjLNLlmT/aB
Pt65H8qtWely3qm4vLu+++PKUybRtAHO3HXOfetKdeNR2iBvUUUVsAVzU0h+2XbzMFZZSDngAYG3
9MH8a6Ws06YX1ZrqRwYtwdUHdgABn2GM/XHpXPiKTqxUV3AzFZXUMrBlPIIOQaWr13pT+cZbPyxv
yXjdiAW9Qece4x7/AFz28+LyzPbtCshKruYE5Azg49s/lXl1cLUpt6XQDqKKK5gCoGuo1fYqySNn
GI42YZ9CQMD8TU9RW90lnZ7ZxIDHks+wnIyTu49etNF04qT1dhrPcxfvJrdVhz1VyzL7kY6fQnFI
8qTvFHCwdy6P8vOFBByfTgVp9RkU1I0jB2Iq5OTgYyannXY6fYK6aHUUUVmbiMwRSzEBQMkntXHs
5uGeaRRulO8gjp6D8BgfhXS6rJ5Wl3B4yy7Bn1bj+tc30FduEjo5HTho3bZIbm6MPk/apvLxjAbB
/wC+hz+tQeUh52jP97v+dPorqSS2OlQitkK8lwwOLqZWJ5dSAx9s4zjjpSMWd2eR2d25Zm6miimK
NOEXdIKKKKCwooooAKKKKACiiigD0msPVor+S/8AkhklswiNhAn3wWz1O7+70rcor0Jx54uLPmDl
WhvJ5ITDbSoTJtjmKsrRtjliCPu4JHJ56YrqsDOcc0UVFKlGkuWIBXMXk8/nyJeySkh8xwhcKcH5
doH3u3Unk9q6emtHG7IzorFDlSRnaemR6U6tP2keW9gOalS+TefscqhF3Y27y5JACrtOPXJzxira
aNdTKk0l15EiuHWIIHXg5+bPJ/AjHv1rcorOGFpQd0gMvWrD7Xb+ake+VFKlR1dD95f6j6e9VtHu
Lya7KfaTPAqAuZcBhnOMAAemDn09a3ajjt4YpJJI4kR5Dl2VcFj7/nWjp+/zpgSUUUVoAUUVlX+p
ury2sKTRzKVxLtUrg4JIz7ZHI61M5qC5pAahIVSzEAAZJPasG5vnvnITZ9mV8odvzNgdc56Zz26V
XaMuAJZppVyTtkkLDP06f4dqfXl4jG88eWABRRRXAAUUVUur37M+3YdoXczlWIA/AH09u1NJvRAl
cs6fnMoQsbdSFTcc4IyGx7dB+Bq7UVvCILaOIHO1QCfU9zUtZyd3c9GKtFIKQkKpYkAAZJNLWBq9
7JLPJZr8sK4D46ueDj6dPr/OqdNzlZFxi5OyKl3dNe3DSkkxhj5SnOAOmcep/rUNFFemkkrI9GEV
FWQUUUUygooooAKKKKACiiigAooooAKKarF3VI0dy/3dq8N9D0PWguASrZRgcFWGCPwNBKnFuyZ6
XRRRXpHzQUUUUAFFFFABRRRQAUUUUAFFFFABXO3kg/tW6D/KRt27uMrtHP0yTXRVHLBDMUMsSOUO
VLKDg+1Y16XtYct7Ac2s8TSGNZULjqoYZH4VJW1d2EVzaGBQsXIKlVHy4IPT8Kzp9HeC2eWO7uJZ
UG4I4XDYHTAUHmvPngJL4XcCtRSBg2QOo6g9qWuBprRgFRXAbygUQuVdX2AgFsEHAzxnipaKFoNO
zuOhvBJJ5UkbQyHlQxB3fQirNUJkZkymfMQ7kwcc/wCePxqxBdJM7R7XSRRkq47eoI4NTKPVHZSq
82j3J6wNVsp1vXnjieSKQAkoMlWAx069h+tb9FOnUdN3RvGTi7o44HJI5BBwQRgg+4pa377SY7pp
JkZlnK4Xn5dw6E/yrL/sq+Jx5K/UuMf4/pXdCvCSvex2Qrxa97QqUVLHaXUt01qsW2VeXLn5VHrk
dfapNQsf7NETNMXjfgswAw3+B5/KtOeN1G+rK9tC9rlaimebGBkuo4zyccetSBJGG5IZnXrlY2I/
QVT03Lc4rVsSijPJHII4IIwRUttAlw7tNN5NvEPncEZ3HoOQf849aTaSuxSmox5mRUUSBEvJo4XM
kC7dkhIOTjnp+H60hIUEkgAckmmtRxkpR5gZgqlmOAOSa19O0lXQT3ked33YmHAHqR6+3ak0rTRI
BdXKHrmJGHT/AGiPX0rbrjr1/sxOStV5vdWwVFLa28zbpYI5GxjLICcVLRXIm1sc5s0UVHNcRW4Q
yyBA7hFJ7segr6k80kooooAKKKKACiiigAooooAKKKKACiimGMGcS7nyFK7dx28kc49eOtAD6D04
oooA5hWmaWX7TJvuEby5DgAcemO3Ofxp9XdUsUiD3kTMrsy71HKtkgZx2OPSqVeHi6bhUbfUAooo
rmAKrXkj26rcxcujBSD0KlhnPp657YqzSEBgQeQeDTTsxp2d0XKKyEguy4EtwVjjXbEUY568FvU4
9cirKz3EAO9ftC9QVwG/LgH9Kl07bM7FXi2XqKihuI592wnK4yrKQR+BqWoatuap32CmyRpKmx1y
vWiSRIo2kkdURRksxwB+NKGDKGUgg8gjvQrrUBphiIUGNMKML8o4+lK0iK6ozqGb7oJ5P0p1QvaQ
SXSXLJmVBhWyePw6UK3UDI1CSyt9UZrizEu9FZ5GOdo6cDHtTdWeGMQ2dvGioP3rbeB0IH9T+FWd
ehJt47gAHymIc+inqfzArEhiklnFvHEwmYA7WI4XAwx56YI/l7V3UYqUVPsbU1C6bZNa2sl7ceVE
doXBkc/wj/E1vQaTZQHIhDt13SEsc/j0/CpbO0SytxEnJ6s3dj3NWK56tdyemxNSo5sKKKKwICii
igDZrLmMGu2s1vFK0bRyDJK8/UDPQ84NFFfTyeqXc8w00BVFUsWIGCx6n3paKKsAooooAKKKKACi
iigAooooAKKKKACiiigDI1h7okRrEWthtZ2jXc2Qc4xnIGQOgPeoLawuLxC5Y28ROFJT52Hc4P3f
bOfpRRWE6EJz5pagR3kFjDIYIknmnXG9jO6qufXBAzjsP0zVaBZleTfxHxsG/ce/fAOOnXJ680UV
5mKqe+4JKy8gJ6KKK5ACiiigCJ1kSXz4NvmbdpVujjqBnt9fc1chmSeIOmcdCD1B9DRRSkrq504e
Tvyle8dHFsFIdWmxkHI4Vj/MVXX7dbShYGikt+SVkGGHPRSOMfWiiqWisTVk1O6BtSlkGY1MS46t
EZN3JBxtPTjr70g1GVOrxsd2AJEaLd9Ccg0UVr7OJUpS3uaMUqzxBwCAcghuoI4IqCxurS53/ZgA
U4YbNuM//qoorFQXLJ9jbmfu+ZbqK4nS3iLvk/3VHVj6D3ooqIq7sVJ2TZHaXDzGRJVVZUIyF6EE
dR+o/CrNFFE1ZiptuKbCiiipLP/Z