<?xml version="1.0" encoding="UTF-8" standalone="no"?>
<metadata xml:lang="en">
<Esri>
<CreaDate>20250930</CreaDate>
<CreaTime>12193100</CreaTime>
<ArcGISFormat>1.0</ArcGISFormat>
<SyncOnce>FALSE</SyncOnce>
<DataProperties>
<itemProps>
<itemName Sync="FALSE">WGIS_CRASH_LOCATIONS</itemName>
<nativeExtBox>
<westBL Sync="TRUE">-9458231.258200</westBL>
<eastBL Sync="TRUE">-8947988.464700</eastBL>
<southBL Sync="TRUE">4636765.670900</southBL>
<northBL Sync="TRUE">5156047.815700</northBL>
<exTypeCode Sync="TRUE">1</exTypeCode>
</nativeExtBox>
<imsContentType Sync="TRUE">002</imsContentType>
</itemProps>
<coordRef>
<type Sync="TRUE">Projected</type>
<geogcsn Sync="TRUE">GCS_WGS_1984</geogcsn>
<csUnits Sync="TRUE">Linear Unit: Meter (1.000000)</csUnits>
<projcsn Sync="TRUE">WGS_1984_Web_Mercator_Auxiliary_Sphere</projcsn>
<peXml Sync="TRUE">&lt;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/3.4.0'&gt;&lt;WKT&gt;PROJCS[&amp;quot;WGS_1984_Web_Mercator_Auxiliary_Sphere&amp;quot;,GEOGCS[&amp;quot;GCS_WGS_1984&amp;quot;,DATUM[&amp;quot;D_WGS_1984&amp;quot;,SPHEROID[&amp;quot;WGS_1984&amp;quot;,6378137.0,298.257223563]],PRIMEM[&amp;quot;Greenwich&amp;quot;,0.0],UNIT[&amp;quot;Degree&amp;quot;,0.0174532925199433]],PROJECTION[&amp;quot;Mercator_Auxiliary_Sphere&amp;quot;],PARAMETER[&amp;quot;False_Easting&amp;quot;,0.0],PARAMETER[&amp;quot;False_Northing&amp;quot;,0.0],PARAMETER[&amp;quot;Central_Meridian&amp;quot;,0.0],PARAMETER[&amp;quot;Standard_Parallel_1&amp;quot;,0.0],PARAMETER[&amp;quot;Auxiliary_Sphere_Type&amp;quot;,0.0],UNIT[&amp;quot;Meter&amp;quot;,1.0],AUTHORITY[&amp;quot;EPSG&amp;quot;,3857]]&lt;/WKT&gt;&lt;XOrigin&gt;-20037700&lt;/XOrigin&gt;&lt;YOrigin&gt;-30241100&lt;/YOrigin&gt;&lt;XYScale&gt;10000&lt;/XYScale&gt;&lt;ZOrigin&gt;0&lt;/ZOrigin&gt;&lt;ZScale&gt;1&lt;/ZScale&gt;&lt;MOrigin&gt;0&lt;/MOrigin&gt;&lt;MScale&gt;1&lt;/MScale&gt;&lt;XYTolerance&gt;0.001&lt;/XYTolerance&gt;&lt;ZTolerance&gt;0.001&lt;/ZTolerance&gt;&lt;MTolerance&gt;0.001&lt;/MTolerance&gt;&lt;HighPrecision&gt;true&lt;/HighPrecision&gt;&lt;WKID&gt;102100&lt;/WKID&gt;&lt;LatestWKID&gt;3857&lt;/LatestWKID&gt;&lt;/ProjectedCoordinateSystem&gt;</peXml>
</coordRef>
</DataProperties>
<SyncDate>20250930</SyncDate>
<SyncTime>15435600</SyncTime>
<ModDate>20260710</ModDate>
<ModTime>14530000</ModTime>
<ArcGISProfile>FGDC</ArcGISProfile>
<scaleRange>
<minScale>5000000</minScale>
<maxScale>5000</maxScale>
</scaleRange>
</Esri>
<mdLang>
<languageCode Sync="TRUE" value="eng"/>
<countryCode Sync="TRUE" value="USA"/>
</mdLang>
<mdChar>
<CharSetCd value="004"/>
</mdChar>
<mdHrLv>
<ScopeCd Sync="TRUE" value="005"/>
</mdHrLv>
<mdHrLvName Sync="TRUE">dataset</mdHrLvName>
<mdDateSt Sync="TRUE">20260710</mdDateSt>
<distInfo>
<distFormat>
<formatName Sync="TRUE">Enterprise Geodatabase Feature Class</formatName>
</distFormat>
</distInfo>
<dataIdInfo>
<envirDesc Sync="FALSE">Esri ArcGIS 13.4.0.55405</envirDesc>
<dataLang>
<languageCode Sync="TRUE" value="eng"/>
<countryCode Sync="TRUE" value="USA"/>
</dataLang>
<idCitation>
<resTitle Sync="FALSE">2025 Crash Locations</resTitle>
<presForm>
<PresFormCd Sync="TRUE" value="005"/>
</presForm>
</idCitation>
<spatRpType>
<SpatRepTypCd Sync="TRUE" value="001"/>
</spatRpType>
<dataExt>
<geoEle>
<GeoBndBox esriExtentType="search">
<exTypeCode Sync="TRUE">1</exTypeCode>
<westBL Sync="TRUE">-84.964737</westBL>
<eastBL Sync="TRUE">-80.381148</eastBL>
<northBL Sync="TRUE">41.967069</northBL>
<southBL Sync="TRUE">38.404774</southBL>
</GeoBndBox>
</geoEle>
</dataExt>
<idAbs>&lt;div style='text-align:Left;'&gt;&lt;div&gt;&lt;div style='font-size:12pt'&gt;&lt;p&gt;&lt;span&gt;Crash locations for the year 2024. ODOT’s crash data system uses the OH1 Report provided by DPS and law enforcement agencies around the state to compile crash data and break it down by different attributes. These attributes are used in AASHTOWare Safety crash analysis tool to summarize crash trends around the state. &lt;/span&gt;&lt;/p&gt;&lt;/div&gt;&lt;/div&gt;&lt;/div&gt;</idAbs>
<searchKeys>
<keyword>CRASH</keyword>
<keyword>SAFETY</keyword>
<keyword>OH1</keyword>
</searchKeys>
<resConst>
<Consts>
<useLimit>&lt;div style='text-align:Left;'&gt;&lt;div&gt;&lt;div&gt;&lt;p&gt;&lt;span&gt;The information contained within this dataset is maintained by the Ohio Department of Transportation (ODOT), and is deemed to be public information. While every effort is made to assure the data is accurate and current, it must be accepted and used by the recipient with the understanding that no warranties, expressed or implied, concerning the accuracy, reliability or suitability of this data have been made. ODOT, its agents, and the developers of this data set assume no liability whatsoever associated with the use or misuse of the data contained herein.&lt;/span&gt;&lt;/p&gt;&lt;/div&gt;&lt;/div&gt;&lt;/div&gt;</useLimit>
</Consts>
</resConst>
<suppInfo>https://timstst.dot.state.oh.us/tims/api/glossary/dataset/244837a402b741fc8e7c6341ca4a6ec1</suppInfo>
<idPurp/>
<idCredit/>
</dataIdInfo>
<mdMaint>
<maintCont>
<rpIndName>ODOT Highway Safety Program</rpIndName>
<rpOrgName>https://www.transportation.ohio.gov/travel/safety</rpOrgName>
</maintCont>
<maintFreq>
<MaintFreqCd value="003"/>
</maintFreq>
</mdMaint>
<spatRepInfo>
<VectSpatRep>
<geometObjs Name="WGIS_CRASH_LOCATIONS">
<geoObjTyp>
<GeoObjTypCd Sync="TRUE" value="004"/>
</geoObjTyp>
<geoObjCnt Sync="TRUE">1284604</geoObjCnt>
</geometObjs>
<topLvl>
<TopoLevCd Sync="TRUE" value="001"/>
</topLvl>
</VectSpatRep>
</spatRepInfo>
<refSysInfo>
<RefSystem>
<refSysID>
<identCode Sync="TRUE" code="3857"/>
<idCodeSpace Sync="TRUE">EPSG</idCodeSpace>
<idVersion Sync="TRUE">6.18.3(9.3.1.2)</idVersion>
</refSysID>
</RefSystem>
</refSysInfo>
<eainfo>
<detailed Name="WGIS_CRASH_LOCATIONS">
<enttyp>
<enttypl Sync="FALSE">WGIS_CRASH_LOCATIONS</enttypl>
<enttypt Sync="TRUE">Feature Class</enttypt>
<enttypc Sync="TRUE">1284604</enttypc>
</enttyp>
<attr>
<attrlabl>DOCUMENT_NBR</attrlabl>
<attalias>Document Number</attalias>
<attrdef>Unique number assigned to each crash. It will be the same for the crash level record, unit level record and people level record. The first four numbers will designate the crash year. </attrdef>
<attrtype>integer</attrtype>
</attr>
<attr>
<attrlabl>CRASH_YR</attrlabl>
<attalias>Year</attalias>
<attrdef>Year of crash</attrdef>
<attrtype>integer</attrtype>
</attr>
<attr>
<attrlabl>MONTH_OF_CRASH</attrlabl>
<attalias>Month</attalias>
<attrdef>Month of crash</attrdef>
<attrtype>integer</attrtype>
</attr>
<attr>
<attrlabl>DAY_IN_WEEK_CD</attrlabl>
<attalias>Day in Week</attalias>
<attrdef>Number associated with the day of week the crash occurred. Number associated with the day of week the crash occurred. 1-SUNDAY, 2-MONDAY, 3-TUESDAY, 4-WEDNESDAY, 5-THURSDAY, 6-FRIDAY, 7-SATURDAY</attrdef>
<attrtype>integer</attrtype>
</attr>
<attr>
<attrlabl>HOUR_OF_CRASH</attrlabl>
<attalias>Hour</attalias>
<attrdef>Hour of crash</attrdef>
<attrtype>integer</attrtype>
</attr>
<attr>
<attrlabl>CRASH_SEVERITY_CD</attrlabl>
<attalias>Severity Code</attalias>
<attrdef>Code indicating the five-level severity of the crash</attrdef>
<attrtype>integer</attrtype>
</attr>
<attr>
<attrlabl>CRASH_SEVERITY_TXT</attrlabl>
<attalias>Severity</attalias>
<attrdef>Severity of the crash</attrdef>
<attrtype>text(50)</attrtype>
</attr>
<attr>
<attrlabl>CRASH_TYPE_CD</attrlabl>
<attalias>Crash Type Code</attalias>
<attrdef>Code indicating ODOT's calculated crash type, similar to manner of collision but expanded for engineering purposes</attrdef>
<attrtype>integer</attrtype>
</attr>
<attr>
<attrlabl>CRASH_TYPE_TXT</attrlabl>
<attalias>Crash Type</attalias>
<attrdef>ODOT's calculated crash type</attrdef>
<attrtype>text(50)</attrtype>
</attr>
<attr>
<attrlabl>ODOT_CRASH_LOCATION_CD</attrlabl>
<attalias>ODOT Crash Location Code</attalias>
<attrdef>Code indicating the type of location that best describes where the first event of the crash occurred</attrdef>
<attrtype>integer</attrtype>
</attr>
<attr>
<attrlabl>ODOT_CRASH_LOCATION_TXT</attrlabl>
<attalias>ODOT Crash Location</attalias>
<attrdef>Type of location that best describes where the first event of the crash occurred</attrdef>
<attrtype>text(50)</attrtype>
</attr>
<attr>
<attrlabl>FUNCTIONAL_CLASS_CD</attrlabl>
<attalias>Functional Class</attalias>
<attrdef>The roadway classes for the FHWA approved Functional Class system. This is based upon assignment of roads into systems according to the character of service they provide in relation to the total road network upon which the crash occurred.</attrdef>
<attrtype>integer</attrtype>
</attr>
<attr>
<attrlabl>ODOT_LANES_NBR</attrlabl>
<attalias>ODOT Number of Lanes</attalias>
<attrdef>The number of lanes in both directions carrying through traffic upon which the crash occurred</attrdef>
<attrtype>integer</attrtype>
</attr>
<attr>
<attrlabl>COUNTY_CD</attrlabl>
<attalias>County Code</attalias>
<attrdef>County abbreviation for the section of roadway in which the crash occurred</attrdef>
<attrtype>text(3)</attrtype>
</attr>
<attr>
<attrlabl>ODOT_DISTRICT</attrlabl>
<attalias>ODOT District</attalias>
<attrdef> From 1-12 plus Central Office – the counties are grouped into districts in Ohio for ease of maintenance and funding.</attrdef>
<attrtype>text(2)</attrtype>
</attr>
<attr>
<attrlabl>ODOT_LATITUDE_NBR</attrlabl>
<attalias>Latitude</attalias>
<attrdef>Latitude (Y) coordinate at which the crash occurred, in decimal degrees.</attrdef>
<attrtype>double(9,6)</attrtype>
</attr>
<attr>
<attrlabl>ODOT_LONGITUDE_NBR</attrlabl>
<attalias>Longitude</attalias>
<attrdef>Longitude (X) coordinate at which the crash occurred, in decimal degrees.</attrdef>
<attrtype>double(9,6)</attrtype>
</attr>
<attr>
<attrlabl>NLFID</attrlabl>
<attalias>NLFID</attalias>
<attrdef>ODOT’s Network Linear Feature ID for the route upon which the crash occurred</attrdef>
<attrtype>text(14)</attrtype>
</attr>
<attr>
<attrlabl>CTL_BEGIN_NBR</attrlabl>
<attalias>CTL Begin Number</attalias>
<attrdef>The County True Log representing the point along the route at which the crash occurred</attrdef>
<attrtype>double(7,3)</attrtype>
</attr>
</detailed>
</eainfo>
<Binary>
<Thumbnail>
<Data EsriPropertyType="PictureX">iVBORw0KGgoAAAANSUhEUgAAASwAAADICAYAAABS39xVAAAAAXNSR0IB2cksfwAAAAlwSFlzAAAO
xAAADsQBlSsOGwAAIABJREFUeJzsvedyJGmSJKjOSXBwZGZVdU/37uzszsrev3mEe+d7iNs7kZM9
stNdXUlBg4eHcz9R+9wDASSQCRLEIxNWggIyEAhnn5ubqampmZef/58CT7BJHOHv8ymu8xgHho0/
uy20bBvbsDgFOr0TmKaNyfAceRZC17Wt7Murfd9mQYj/7f/6H0g8DVEQ49/e/Iq/vDnGv384w3+/
/gzNMaCPU/yv/+1f0fI9aDW/lLxxCr2Nw6MTXJx9gF4E0Na001kO/N//30eMJzP853/5j2j5gLGC
tZ4XGtzGMfyGj4uzf8A28hd/ZoICM93Ece8NmraPeRLi0/Un2EmKd2/+giSOcHn+D3iOef8HaCYs
bx+e6+L68iMsI1v86oG/2A3TwAumoSiAQv34ajW35UtU8MLtshXF2hzUXTN0Hf/6r/+C3t4xRoMr
JNFgdR9eHcILLwf/PCwKpLaH3/bewdA0DOcjXA2+oMVzZZiI40SORdP0Z21jpx1WZQWKV1+1E/bj
PVEqh7V+51sgS9Ob7aJelhUFAgBOcw/vWofIihznkysEkyv0dENFoxJc8Cft2Y5+tx3Wa1S1U3Z3
jS7u8brdfY807r++lby1WOmnvTTASosCM03HfvcUHa+FKInxZfgFRjxDRzfuvFs5rOfaMx1WUS9/
JTnhtvfm1Z5k6sL9MCdNIoe6g253TEU99zxJHmn826QoMLccvO29hW1YmIRTnA8+o1VkMG85K0ZV
L49En+yw1ObqcmGqcHzb+/Fqz7Hly1aXFfVkKGKx45tbhEWxWo9189B//AfnKDAvCuh+F3/uHCMv
ClxP+xiPL9D9FkalPOSzr/hOR1jVMXPh1GafXu1B4819G3S/uWovSxS2ZBJUlQ/NxZ2/pk0VwPnl
FS4uh+h0GnDN1V2PKjpUx/L9+yhDgSl0dDpH2G90EWcJzkfnyOfje1LAO8fxwvt0tzEsseVVsnNL
/iezu9fnB3jIVCHWev2VbKbR8JHlGkyTt22yss9N0hgeGjBMG0Ux/yYgzhQwMCyc9N7CtxwE8Rxf
Bp/gpwnsbzgrSQd5hspLrm3DYdUF81ZPiJ2DEH56qzKQXb1sZb2r/Md6nW+eF/jw4RNcrwFT76Lp
re6z0zgUJ+V6TcynAUxDuzcyCgsgc5v4rXsq7x/MR7gefkFH06Drj6Mp3Jylx0VzP1iEtbRYfoCH
9Y9u8kBZ3Ava7qfySzysdR8FCdH/5b/8C9qdPUxGfeTJeDUfXOTI0jmSJEaj2cZsOkJRxLeiLKaA
QaHBa+3jXXMfSZ7hanyJcNYXysJjTYHu+YvO1k47LJ5Ufr00L361TdkiHvmBbEWsy0dYnuWSTTDa
WpXx/mGGOR5e4eDoLbq9QwyuPsKx1XGR+TXVDBzuvUHb8REmEb4Mz2DFc7Sf4Kxk//NMnG1osTOG
7HX9EeG39nKHdet01WEFvpYJdw9tXPpHscsp4QLDWu9RKND9Elf9ETotD7ax2g/Pszlm0wn8RhNu
o4ckHCAzNESWi196b2HpBkbzKS6HX9AucmGrP9V0rYBjxkARw7a+/fesOuYSjeGFDuvVObzac+2O
k6o4OXmeL34nWePdcmJdbYl6tX6eewHLMtAfDNFs2MAKHRaPwdALTMeXcFwP7e4+Pp/PYXoe/tQ5
EudxOb3GdHxVUhbWeHE0DVGc4POHf0er2US7ad0KxMw4vmksfIylaXEbLC3qkGDsOBbyE9rykucN
UZlepfqov20ywuJWHMdGt9NRVUItW+3ni9PKMehf4Oj4LX598yflPNJYKAtaOPkuZWElVhQwDB3t
dlu6CO46R3P/5C9P+rxOkWN8/QcGw7O1l3K/Za8uaveMbmjZFVW3eMYIq6w5y3+74K0qW+zsulPC
ArNZIEoG63CO/MQUOSItlohX03UE4Qxnwy9o5ImkhJuyYBbijz++4OTkGA2vcet3pmk+cUcYveuV
TsIWQ/fia+e1S+v8p7SvaFhVSqgY4yodXIpadsB4D2xCdYLnxPd9zIJItrfKM8S9j0rKwi+dU7kQ
w8kAw9EZ2oYO/ZnKCs+1dqeJf/u3f4Nj2xj2z5TTKc389Mf/+50/X3YFBYI0QT8NRM6l0LZbn1NY
x+4s7le7bcUywLpUM9olh7UpUxHWDP3BGM2Gg4ekpJ5qeUlZcFt7eNM8QJqnuBxdIQ4GaD81mFmR
FXmONElgWeZX/sX0vacdeRLl0Li6Xq7z9UJ7xax2ze7QsBYRFqVJqt8xYtmOAsJzTIWFm4qwPNfF
/r4t9IZVoO6kLASagb3eCTpOUygLZyNFWWhtMAW8a1EU4cuHv6PRbKDXuc2QfbqfriPO/cTGzVfb
kt0hNy8iLLkBlek7lthXmNy695pOMYpjJEmBIo/QabWe/1llY09o2jjtvYFjWBiHE1wOz9B6JmVh
lcaiQqfTEejpq9+96JNrsLZqsAuv9mwIq4qwCIwqArCoUe7YGa1aw9ZqmgbHcfHul1PE4QTIZ8+C
Q/hoiPiD28KvnWNxXlfTPibjS3TWTVl4pKVpgrOzS8zDCP/1P//1Nq0BP0Kvx2t0tdMJIh2WatuA
lLR3yjZ0g1cFibOzL2j69rMwrKwA5gTvWwc4IDk0S3AxvkQ+H22GsvBIsywbv/72GyzLgiax4Es0
3e+07W3fH7/a7lhFa1ArSJ4zrE6lGViIYjnd1K21LCr1TFuiVJTrmHGd2rVqYStcaqG0Un6vHOrN
P9TPC3mWNRsLE8PBEOeX1/iXf/4LHPPxJ4m7R2c1jYHu3gH2Gj3M4znOhmfw0ghejZwVLU1TXJxf
I05S/OXPb2/9bqcjrN2gF77aw6Zu9IQYlqkhT3OQZrPq68qbPc0deI22/Juf/t//j/8Ttm3j8GBP
HBB/HvSv0Wg0kWcpPN+T6S6mZYmWuuc5GI1miOMI3S5JjUCakY6hqyboNV9mUgsODo9weHwKU2di
Fz/y2IHZPMVknqLT7uHyy7mkWMPJBXg2HquysEljlN1qtWRgxV17BuheM3BbHnZ1qgC82mOtinLS
nCG/wrAsY/XPUIL6rt9Aq0VHo8t2bNuRG0M3bNGZCoIAWc7fGRhNJoBu4/0fn/Dbn/4E03Rx+vaf
MJv/O4IwRZTo2N/fly9akqxGm+pbRnLt77+/R5rm+I//4U+P6iWkWwuzAnFhIolCjCcj9E72MB6f
SQq4Kie76gCTvDxG25ZtffW7nY6wlL1GWTsJ95RZlagPlCu+yAtYJoHf1W6XUVs4u8I8GJXSvRr+
9MuJsLll+2kE1zHRarrwHAtXSQTHNvHm9AS+5yLNUoyGfRlb1Wz6aLUaso+MtkzT2gytoXwkG4/k
RtFZzXPyq/ZxetLBp8+fEWQzFOHoySoL37IsLxAnVJFYfvXxNO67fQKMroXmUjnUO6f2WRjWnR+2
Z6++aucVR/kkXZAaCLqvKUWxLd6kSwTCe+5Zp8MneoJ//suxAL0tz2WMgsIsEAcX8JwCblEgiwaY
hQWG1wVO3/0VBh3Amtcine7/8t/+KzrdA1xffgHy6b3vk4i1ACZpgeuzAfZ7wF6zjV9/eSdONwqu
V7ZPTDdzODh990upgro6HtbHjx8xGPRhGhl6bWd1iqPbtRIJLVRSuP39ebXv2S1N9zLVYcdEBWSr
SStaLXXX7vpSI9ncIFWJBLPsm0oW0mKTAaN5giwqcLh/AN018PHsPd4cvkW708NVHCLPZiuckJ4j
TWMUxcPN2F9HX/fs+NJvCLoTU2Qrkq4XP05KqHoZF3WeV6u5fX1v8yZcjrBUp3693NVuWMEUMAMu
LibotLuYpGPojSb0bA5f19G/OsPh8S/Y2z/G5fkHWEXyYmcrPq9IcPn5b88X0bzH/6YZEESA5/rw
HP42femYr2ojNVparyFW7e2ukjVbcIiBsJ+tWksWeVg1Wla1WnqF+nbXz5CyMMtIewjw5vQNJsEU
3TddOEkIp8SrKHs87F+gt3+M3t4JBtefYJsvf9QzUvM8KoiuzuiwojRDmmWAZq0mwqpXVPNaJdwF
U3hVFf8XUrGjqmQFWjumDsfawQhrQ8TlosjkXOm6KU6KJ4pTl0cMrQobYRDhvH+B9p6PRhrfwgOF
hhFPMJ24aLU7Qh6dTy5gPYHPtQlj1JekKc7OztFutdBq7P04KeE21W1e7enGaiBVPsSIVxm6lOmr
1xhxzYNgI1W3XTOmXHnG1KiQymQSMrIyEBYaolkEy9bx63/4DXE4QgvsHNDuEegDZpMr2I4jFI8k
DpHFYxj3TMnZlkm3g67DdV3EcfyDDVK9maT6ajtg5NcoZ6Q0pLgwGfbnJcWBtIHxaCxAvGHUi31d
B/JyUaTIshym5WAUp7i+HEAvNJy8e4NEj5EJZeHhKiudlmUUGPbPcXD0C3q9Q1xehNDvTMnZrikc
8/joUPTli2y+CodVj4O7eVi/eqxdsLsUBlYEk4xDpJSxWEg9bzLLYX1NGqylbbSVNUM4D2A7LuJZ
gaODQ3p5JHoIv8jgPIISIpFWkYgU8v7BCXr7J+hfflwJnrUq44Os2+2i0WxhcBX+QBFW2RFaD/f5
ao+KsCqIWhqdiVdkkhKqVuhCOvWTJIXrbo4y8HLbzP2Q68CXq3OYMKWlZp6F8H0LbcG1Hs9fI3c2
S6eYjAdCdWh1jjAZncGuFZ51/zl9+ZivGljJk972brzaIyIsUaotnzW8yUL2i5WOSSPGlRfIWB3a
AdvUipMWGyafXgvHzQb+/ve/4fTNCaJkBCqeP9Wx892ErebTPmzbhd9oIY5CJNHw3qnP27H792O3
QfcNDrF8tZebDJtYmrhkaDrilA5LvcKUkOxpNZRiR1UJV2x03XNNR6N1gH2vg3kconnQRBoN0XyB
hDF9nGkUGA3OsX/0CzrdfVxdRcjz+QpJpSswbRUOqyb+Ydtjxl7taSacK2G1q38zwmJKWFV7tRKU
p6b3z07EqlpsQtPCQecEDdvFNAqUKqiewdJeXpRQlcMUg+tz7B+eots7Qv/qEyxktYVZfowI69Vp
7YSxwlUZ/RarQVGaLtpN6iYEsq2iD89SQuduN/C2dypSwf3ZEOPxBSiMvMopNtIRlQcYj/oSZbWJ
Zw2/wDJ/IAyrNlTRW1MNXq3ulpP4uPRv0hhiOqzy/qtaCncFbKcK1qp3NSvxKqe5h9PWvkSc56ML
xMEQrTXIRwuWqAHRfIi57cLzG0jiHuJ5v1b8rMrMp5Zkb0h9t9UbN22v3MLds1SqhDfOiVhJlKSA
p/Argu6VFPBu2D0TNV7wSXk5xabTOULXbSo11ixFOhmhaa1PaE/wLL3AZHQBy36HVmcP10m04ibp
1ZjJIs3tKtvXO7j8Sp6b0DQDmpZCh4E8MxE/y++//ERYGveFF3LHcomf1FLiVfptBYR0gVcVOzeX
8Dah5vlAVjXFJjYcHHWP4ZoOpuEMeZKh3WzDc1vIk8lanYfCszIhle4dvBFS6fVlDK1gyo7amPnm
1/9Q/vi4vYqyBJOL3zEaneNg/wS/7r2rwRy5bW//1R5jTP8kjRI5Kk0oDALClxVCJTWsHNnPYpXY
ceE08bZzJJ6jP+tjMrmEm9toNZrwvBam8WR5eMxajP4wy0OMR9fo9g7R7h5hNPgMu0bAkRlFt5mk
YpXY/nLcVWpOzbMECfVvUIjiYhBMYIrs7GPt5p3f/ZuF6P/dP1AvmJZdCoctJgq8Ws0dVnWNxGFR
DG/JYSkMS6ulzvg68AniVRH15Bt7OGz2RNmUU5fz+VjwqqRIkSYpHNfFqE8aAtZudFpJOEYwU/ys
KOoh2RKedR9EbV5++fujUqoq/B3FEUYcVY8c/eEF/GAKz7S+4qQsnpIPZ5rf3dlv/SkbaV1/D832
3leyJa9WT4s5HWfJYcmI+sXNXtyA7jvlsJ5+I4twIQqEuolu5xgtp4EwCXExPIedhqJfpT45FwzL
sjwUmxonpjE1LDAdX8FxKQfdwcVsCMPY3B12syK+NtNzn9azNdcy6OxWzVVZmtrX7hb6vvJK7G1B
xnp1WXW3iCRRPsILwDKNm8ZnDdDJGC0TRoVL1t9urTjtiXiV6eK4ewrbMDGeTzAYnaPBqct3jr0q
cm0yvtFKUulsOkar3YVle8iz+ZOxrOK5FFvBN1kRlRom8uIGLaxRdvpce80Dd8VYEdQMivblcCxX
SKN0WLSKg0VgmV+7gGNVt9ESgvKIqcsaNLeFt51DSSWvptcIJteKsnBXEuYWx2u9jPqvrUCaxKKa
0e4cCPyDZ+zL8rvu+6t7X9N0mXJtmKZkUOwvxY/jsF5tp1JCzh/k2C3LLFnuN4J+khLWZFz6U017
DL9K0+E197Dvc+pyjMvxJYpwKs7qwU/dYuJQFKqCa9n2o6f1rNLyPJNt82v3Hdb3hO1f7XGnscSN
NsFy50h60WvIAds0b1UNK79FVvcuOaylGOubLTaRYWKvc4ym42MWz3E1PIOTxbC/i9dtb21rRH7y
DKPRAFEwunfq0eK9NzO012q767DEdmdh19EY4BAf4GSSdUupK7zqJpqy6LBIGhVukQa9nFtPisz2
aTJPsCqnuWeXi5KykNoejrsnsHUDw2CE4fgCzVIi+nufvewSsAXnJQWtLJGewzpcl911WGpgTq1I
bbumTaWbDSEIjgYXQB6utZmPaSAHZIrqlURYBsZRfKvxmUZKw+7QGh6m6FR4le618LZ9JNI6l5Mr
kXS5D6/63ia2s8y1avpabWx3HVZlrwXCZ5ksRJawDQOm5SKN2MG2PktlnFcZiuSFpIRRkkgKyJdk
/JyokO4OhlVyXZUiXvE1XtVo7WPP6yISvOoCWjj7Bl719HTzZ7Sdd1iv/up5Jm0xCQdg5rBsB0mk
iJzr8hWVsmiVPXEAxTxOoblLGBZTxe3LBDzBcpHCIXmZWJzgVYysDEvwqobtYUZJmNEZvCyB9YzI
cavuSqu4lPVxmru0Om5bfc7hDlsm+umcwrLupCPJ0sWIL5GWoZ57Tua7EkWXTopCTYTZlQiL7ofE
TsfyBAtk/0dm+zjtnEhaO6AkzOTycXjVQ7ZgEuzGOVm37a7DunURX73Xs06fjBlPYDueNLTjG+PG
X2pJoiIsSf/KkV5VilgpNdBhWbsyfELwNgg/iZIssFzovoPj1oHwzEhZiGeDp+FVd03+bqk1bYsp
TF3c5U47LMWKrv712kz45POnKXKg4zYA3QSyZG3Onyz3xfzBcvlXpFHZl3KzZMDvTIRl6AjDAF1t
H8eHbySqitJI8CojCtB8YfFgO3XBek+l2lmHteg3qs+53DljlJMkaiadaVjIMjbCr+eEqmETtxuf
b1JE1QwqKg5bICg+xyq8KmdgWk6tmUZTXI/P4WepFA9WtqFtmVa/B8fOOqxXWxHwnkYCvJu2I6PM
xXGsYZ2yIsgGXgHcoSuHVVYqtayCrFm1rP+SFAljfneaOGofIc0zjKcjjKeXaDLlXWkvZNVLuGnn
UU853/qvju/YTfPzqz3HiqIC3u0F63wdFpLCoDGyAmxDNT5XKeJyhGXKxOf63Si3JGGgw2p0cNI8
QJqnuBhfIpsN0TQYO/6IFfACdbHddVildlL1c43O6e4B7yy5W27JJ1oP8D6PE+kjJCDt2Z6w3G8c
VjUTVxNeWA0zkVuSMO3WITpuC2Ea4mp0ASMO4IujXa1VmLv6x8o//tvbXsLQ6oQO76zDut2y8GrP
NZm2TODd8aFpJlAQmVnxFJiiQMzhqBY/PofrWhJxLSQ0ZXAqcSA6rPqx3JclYQ46x/BMG5Noiv7o
HH5OvGqduNuWPBathkX4nXVYr7ZaAqkItxmmDDJdh5Z7Wnb+85tjmQLCV5gWMawqYtbXEKm8WMKY
WJvdxJv2kZyn/myAyeQKzRWP3LrPtu8rilrsxe47LIlTq+aF+pzQXTOewjSNpdxqWg6iZLro71uV
Ea+qpJCp4+6YFsbTQCkz8KYvS73S+FyjPsIKr7IbXRw295FkCa7HV0iDEVr6avGq+23b2YMm/39N
CVd6Ol/tReeQQHiWIssz0cgPyZIijqWtNsJSUsiK1c4ISzAtX9EbIANW6awMcVjb5mHd4FUW2m3i
VU2RML4cXcCM52isNQW8uyd1sAJ1sd2NsF5thZZLpVBRClbvLAiwC4VBoikVScU54xddGqHBUV+a
IfjVtiOsSr8q1V0c9k7gEq8KJ+iPLuDTqW9y/wT13q4ellhRn/BgZx0W08BEJHc58HF9LSU/DfCe
JnAtp2zRIfC+OqNQ33IfIX/My/terh0xLLOUltlidKXwKg1wmjhtH0lT82A6xHB8VvKrNrtvPFfL
g6KKjbuNejipH8JhZXmBs/NzkUZxbeIi+CltMQntBWtLL1t09IYGTVp0ZFLeyvYxEoC97CMsP3Yx
tD7LSx4WRQS3F2GpkVs6nEYP+42e6FcxXS3iFB61w7ZVvaxBK0dRg32obIdvcw2e54nD0gu2lKS1
fCKs2/Kc8ZEOvcikGff5jHc6KQiBNM2Cle7jPEpQlAA7p8Iss9xzyp4yXhYVUmNrLTaxYaHTPkTL
8TGPQwyG1zjsHKLd7sqYK+XStmlbCbFqZzvrsMJ5iGmYw7JiNFzAdOpTXdqUMQowrBZcr4PZ5ApF
oegJz3NYiXweK4VxpCSLV5UBzUvaBM2CIo9WpNEsTlUuprNKaW20f61qscksD4edI9iGVY7c4tTl
FNOJhYPDUxlzVWSTzRcDWBDZJuCtLXenoxa2sw7L9130DnqwbR/B9FpJ/P5kxkjdshw4roN58FK1
hUzwJHEaK16dsygSCgPTeILYCXGrCsNKOFxVRVbUed/UfVFJGBteG6etA6liXk+VhHGzpFckUSBD
GCi/E07HW5l+XA8r6uKvnuew+KSRp00NjoLYgpTm8XNasWJtLMt2RU9hVSkQnapQGBwdeZrCd+1b
yg1pnEB3zYV432YoC0CkG/Abe+j5XRm5dT25RDGf3pKEkT5LceKqz3LTttwmu/nmZ9pS61sN7vVn
OSxiELZmwtMAq3wybsUK4Pz8ArYzhWPlsOtFkN6MaauuFFIby4dGnpGIVb3cHfKGTxfjvQr4dumw
SseQRQk0z5P0w1yzFtYNXmWj1z5Cw3Yxi2e4Hl/ASe8ZuVXkKu026FC3dcdudQpFafUJB57ssGzd
QjOxoKeAszEC3UOnsGobqM8J3ait8PArxrtqQjZXysFKJAFTwyc828JoMgNsTSb3WFV7zpq1sASv
osqp5eO4fSgSzYNgiMnkGv49I+KVqWIACa0/3QrTfiB5Gdd1keUmNH27lZMkSZAXkRL3/xnxhWpN
reDQBXiPI8yCGWZBCNtk1e7lH83hExzvJYpXGVnuFsI0he4Q6M8UL6uMqkxSKtZgXKWxpsPyOzhq
7CEvMlxNrhAHQ8GrHo7qlMPaJvN+64qjxWqZFeqzvn9OHzrvT14h84Al3yniokCrZXPAHLZiGtDp
dIUhrSP6eaOsFRkXR5YmeP/+D/T7A7w73YfVtF/ssRYcrHJoA+WRFY1UR8GWnCwTfIbTvsh0X6Vz
qPCqWDfRbO0rSZiEeNUFdLbYPGJbixtHDmIba2yLag00FXLfTom/uyv3v4GQAB9gTLNtx0KapKJ/
xsKGXn6n8i1/H0bEU1mE0W5F3k/2NqZrwu56CDkFxdzek4cHwgiLlRtVvflZHdbqjpuBarPZlIER
/McqsNZYlEaV4BW/kS2eVVguF65llgNxV9v4rCRhNKSWg732IVzTwTSaYTC+lBHx1iNVFqjGutWi
zmLD29gDRp86bLeBXHh6lYBZ9dOyE7u7UtSbbl5V92t/dC3XuW1YOL8YYK+3h8l0ina7hckkxNs3
e/K+8+shmk2fDEMcn+w/32HlyDArYgTI4Gvbm3DCEjmNnlnfcmq6VVshhMfb0vdYJdSRJfNySOjL
PjNOE2hGJY2sbnyOrJfdTgvYZf8i1zv1sFbWYsPPdJo4bh/Iw20wG2A2vYZHRv1TJGGWhSK3aVsY
wayVg3a73X3J5b7e/CN2aOktURxhTPxSPpxRky4R12Q6h99oIU4yuH4TRpLAtm0YhiXwU7PVeQHo
blhoxDr0TIO3gTL0Q2boDFNzGaJg2tvFGbZrqztu+gueT9IbVnVzUJJFY1uLpsHWdAn3pQDJrzwv
p+SUVJkXRlhVCphoBpxGF71GD2mWoj+9QjYfSwr4tHVSge4q2tyObWfLRYktsso7GvVRZMk9wR7P
z80LX+3pHfBLOG1mgZg0l8JAr+tB1wv4riFfhtbAdHQlxOJ2yy07HxL0Lz8v5E+fRWswylaQbfoI
WZxZhjiMYeqWpBY/p61uQauZpkpoL2HDcq7Lg+G5Ruc0mQfiCbl2uXYoY7PYY1YJS8E+hWPpL6Ys
JIaNdmsfTaeBMJ7jenIFMwnhP3OxLuKKnw5xKNR6yDPMZ0NYzGK+ol4uj9n7/qOTS6lJPpRny6PF
LWdQtvw9uXqOOKgIXBK2z7Wg1iJfqzbwrLtcsAY9X3Tgb8Popbl1Yi6WmakGzZ81ylrRYTP6yPME
s9lcFktevIz1TiwiiCIURoE8qzhYKQoGXFxHORbcKxVlPc9hcVmnbPmxXey3DpVAYDjBaHwJj0Du
M9dFfeabyARObNQEdrxBqlaVrr/UzEVEd1e/ucKxl/dT5C40JHGMcB7Bs33AwVZMpq7kKsWQSg5+
ZpO7fSWfZBkaet0OMhHVSyUyeu5Hz4JAijOFQZZ7Bt9zpK9QHrXluC/DKGVnRKnh6YxuJQmjQ3db
OGoprKU/7SOYDdBgLfLF56Uibv58hR2thgGAWcCWPq+FLe/jTVFAjNUeSoF4zSYihm8iubGdg2o2
PDSpWWTZmI4uUcgQ0N2yOgaFnAYdhiHCMIbesmCbz0+1J5MpKuSDJe2G46A/nsh640PGMYhbUI10
qeqkPRGv0g24jR56fkcA/v70GkU4FX7Vy9fm9lu+FjDQQsxP28x2ZZvq+GukLgPTbew9qYeLgNho
9gmm0BdWAAAgAElEQVRFPIVuVkPHN288iUrwzagjIfe7RpFNNQeQUcAqPnE1q4r7w3IyqzjEs57r
VBn5jiYTZKXjIGnUc+yFNDLxx4brQI9D5OV2HnsMC7zKdNBtHcC3PQRRgMH0ClYSwV7VU2BJ8XM7
vXy3d2VTdusqyPHXx2OZWZY8KT/lQiSrXKNi3hZ5WJUJh3pZmXEHjMoAhebAchpIognyIn2201r1
uDOJfshOZw+gOrvP+mziV7N5iJyTw0rhPgLssYD6GvI0R5MdE2wHYlpfVuS+xyznuUtIOnV9HLQO
YOkmRsEIk+k13BfgVd+1rS/1ze2AFHALFWmrO6w+d5cZza4rDP5RFucFxpMxojSB5zhbO5Str58X
mEw/9nw0mh2Ms3ghYlcHUwAr8PbtGyRJhCwaPWvfBL9ipbGs3hKqMgjqa3RYhoz78h0bs5m6ko9J
OxRlQYftdNDr7EuZnJIwUTBEQypW2g+ttrkp4yGTPHx1+RmtVgOOIYJlqIOxSPMk4yIkQCojxbd6
Lcsnf5XW75wHqyo/K4qMVuTypGJXSs0EQQgtz+DaT3cGxK/YQ5gvhPs4VboQlrvsJ5UbHAfzRWip
oquHU8ACiWGh2dhD1+/IixejMxTxBI01zQa8W8Lfjm2nHSgvCvi+VzvppicjqlEYY3w9RERW9F4L
moet2pY7rV5kD9Dtnvgh61hOOS7OzzGZztBuOrAt90m95YJfjYlfKeCWqgxN00Kalw6sTBFd21YU
GTX9S8END1AW2GLTax3AM115HzlbWpR8LQmzYqvSoa2vrw1WZ4pC0YbmYQLPc2Faxe46LN02oPdc
AWRzuw4ifjsGYO2AMcJqNnyljcUmlyfeLHEcI5jPkREP0yiEmqHpNcu+QvUecVhO6bC4RUZfdxwW
kS1SFjSngcPWgaSUQ+qrpzn2e4dSIQZ73Na5Bnf5ifhM4/VmFf7g+Ej6dEfXn1EXe3ovoV4gtoAg
z5GINsiWbCmb2kV/Vef1T+5S5aOeI1w3mwVqFqGtoh+qMjSbLkJxWGVfISfUOJbIIst7cqahN+PF
+FOqGbB8tth0hSF/PekjmY9ggQ9Myt/YSCheuq6TeYt7VecrtmorJIqdzwPYtlUv0B27buWwhPqc
0k2auqEq+sHKPlUDbMvAyekpxuMh0ohTYx6/geFojIwRuAg8KkpDxcGqsFsOo2CvmGNbcg0ZYVFu
hN9zanMRr2ruoeU0EaYRBpMr6MlcWmySiizMCTxr1O9dYjVszxa0ik2aJvr+14MLdDptKZjsuMO6
OYnbeu7sJM6+YuPxh1EMzQiEhrAqGq9oY5GhzijGcpBEanrLYz6b+zEcjwV7qlJCFgY9x8I8jqGZ
7E4o4Fm2zCG0mNaVFiWJqCzAcoVfVUnCjCZXsLNE1EnFihsl0PVbsfVhwZMJqS9UENvclnkZbMuW
qFevkccyn0mBrY2zqM+pfKJpqzn24WiEWRDBsTQ4KwRHC5QDGCRle/xMvCCYIwwjcVhM/2hc745l
KqVRi1LMuZBG6RgdEWlTTpL6VZy6fNA5lLSUeFUw68MVCeObjauIslRRWLPWehVhVdWyjRI4iwKj
8RAfPp3h7Sl7JDe1ZVUoGU8m8FwXVqs+idiT9+TrW2KbMZa6qHXKsTdJRGC/n+tQrlq1uqzSbk3R
kfH1j9Mc4yJPGJ3xBi+XBl0Sq3pKaZQpYg6/actjjxEWFSXbzT0cHf+K486RpJPX02uRhGEK+DXo
r9JgJUez7h6/pc/esMcStU3DhFMWJ4oNNubw3O7v78OxbRTZFHWxZ7hORdV/bIqwNltuf9zlQuEL
Wh/opASolqERq3ZYany9y0qhiK193zFwf4bDkaIoSDqoHKknU2cYs6lbTqbnOEp+2XQdHB+/wV//
+p/R2ztAlMUYTK9hxHO4JUC/Na31GqQRdFS2zWh0gxstNzYcDHF4eFATyqiyZ8V69XMOPyeiRdC6
aXnwG12EwQhaoVopVtWiI+PrNQ2GbiJ/RIAVRREms1k5il7FvWzBaTiuDJyoSKPEtGzysjQd3t4R
/vXdf4JrO7geXCLKZnCK/Aav2qLdBt23sz/cKlU3N7r9oux4MJR+WQ0uxcJenJxuvyW0Xs2Zmz5v
rKzNg0CqOiR8r+pz+TnisDjg1HYQBdPvLtzpdCZcKwLEsfQHAlmao9V01evlncAuCcPzYPhdHLb2
kEUx3r//He/f/0/8x3/6DZbcoN/fv/XbTVS5nZtWw3QWIEmmOD09lPG2G7vhyMVqNgV4L9KnNO/V
2WFt1fUukbBWJwe1GVuhfx2PxzCsRCRmKRW9KhOQOUuR5akQNKOirBRq30gHSWfICwHrQ7LZy+Gp
BNjDhLiWeu/+3h6OTt7hoH2AOA7xP//9f+CPf/wNeRIjS989It2r2rI2+aDStgBiFXA9F55vrkDX
62nGUzudTmFZZq24T88C3W9R6bbsKHYvtqrut9WksY7rIF9bpSxHlqZq8jEZ5wvJ2q+NWBrpDLwe
UZQgpq66pH8cnmpjzrFNlimE0N+O3+Cg1cM8DtAfXuDjh78jjsIyqrshj37TNsS922bzMxG8TruF
bu8Ik9E1inSTGyfofgDXtREH9dGae5nzXAivbdN2GXF/ucVRjDTXYRm20nFZ+fj6BK5F0JeVwvSb
7HbSGXiDRySA+uRXaTCgwbYsWI6PgzxBP56KKCAlYaL5GG6RwrMszLVQ0lq29TxGg0t+vebrfmsf
1l2MvMd4LuM4wuXlpUxztDc0aF3Qx6JAu9OGaWiIA/wYDmv7zmpXQ6wV7bymwbJtOIYNRZda7bgz
CikQx6JemsapzFn84D6PRqNStjqHZTswOWCXQwccD3GqwXZttA0XkZViNpsgsDU0dUNSHc91gNG4
1GCqhuJ+PyUsh4VhncYWFaa421pnJI6O+hdot3w4jc3U66R1StfRajZlSnYt7vOX8bAqNt3if1uz
kse6447r+UYHwYrcOo6fEQapDTSTfXtZcO/VZho3IJ2hvBSe72FuUg1Wx+nREdKkQJiMERsF4iBB
0B/C67RFd4vmezeSH0HIeYjfO5hyMCvWbZqI2BEnpOMSRfAtGFNyz/NQgGnzhu63Onmpl0dY2z8a
AWVvpJR2y6pU+qX7TfXNJMZ8OofeacCxVisXzXPMCIs3q2nbiKP7Yx+y20VdlDrttgXNdNF0DJHe
Pj08RqOw8PfzjzgLBhgHU7zterc+g2V7Rlq5rstn8XOMR2iJrZ8wrGE8niCKM7iODmsLDovVVTrN
PG9tj72z/dv9hQ6rqNGxbL079blWCvy/8FMcx4XjWbCssmlv5TdxhjxLJcKSzmUy3u9cdLYHkd3O
a9FsthBZLnzdFKyqYbsy2/BirlRq2QjtWvatKqDjONJXSME/crmyNFuoOGwTQxV6RpwgywPYlo+N
G5u7Cw17vZ5MYH61ZzLdayNqVoM9eJbdelK+zMFEUQjCSyRiriPUpFtN0gSO49/bokN8h+kg3+k4
HprdffiGjansl4HxZAgkISbjEXLXkK4Et8S3KmPrCblZMUH3JEWcxPLaw9SGsi1rzREWt2KYOjrt
NnR5GKwWI3w08J4k8DKLytL42e+z5/cS/owyQSsynjpWw6BFgkG9xNi28b0E6sU4VhzB85rQ2bmc
Jbcc43w+F7E+tvDs75+g1drHYDLGHCkuBlcwshidJe1/OizHorjMzcKxLAuOy4k6sQD34TwUwPfh
nSq/S366Pm4Uiw3HR0fY2z/C4PocKHjsGzThoxWIWDnFlqV9a2J14oT9PFYA19fXKDBCw6ViwXM/
RhNnYdlczM/8kEdUCjmMgltjI3Q8vw28U0aZ2280e+jtHaLQNcyNDP1gilk4h9XdF5pDsSSNbFvm
LcoA++VazQaG46mkYaRI7B8UtxQalk2cnfCw1g8HBMEM0PooKN+zaQyLXQGmKVw70+CtqgogG7Wa
NZKYOzdC+9bWa3hGH7nf5E9lRQKPagjPbi8tBLCmUtK6CI4KeCeulMJ2PEQB+evsL9MkQYpT4PCI
7HQN8ziE5hr4OLjAvIhl0IRrWZjMAnFkldKowqdur5t2swlNu5DPHU8nKvL8hofYxLqjQyTgPZ1F
6HUaMDftsErGP6uEMuw43/DmN5B2b7T5ebvtMLudizaaDZimC1NLXoSN0JFQjoV6WKsmjlZG18QW
GtdrQNMtFEWGOM0RZrlIGINDUhsuCivH4LovvY2Fa0g0RR2sSw5PLffL0nSYHMB7Zz8bjQZMjrRn
hBXMkaQE+s1vr8E1F1yqXSStodPaQkpWSlWLVLHpr2jg7m7bTqaEy8u0iq926VrK2Co6miyC/sJM
zhV+DikEpQzCGp6IvFGiKIDnN2HaHqbBHONpjDCI0G61MU+n6F9+xts3h+iztYZ/IOkfWe4mAjos
XYnCuaYF456xXIwUOZQiSecI41iwMddRIn8PxVebePrTaR4cHJTOc9Ogu4bJlM3POXzXghRqt2E1
urmeDrovo+7bihbrFaU+2UQbKqN2Qaq4U8803rZUhJxHGfJc0QrWEmHpGpJ4riqShoVpkME0bPie
gcl0iLMv73Gy35V0j5LNy8J9rP6FaQI4ukSDjQeqf3QITAsns7mcm/F4im6n83Cl8Lb2y9qMjrOA
iYa0Gm3YikLamppNXwoT2EKVsm727Ahr+0XC3dXA4tRjRlie70LRa54LTuRwXQftbguzcR9aMV+b
N8+KDNPZFLPpHKZuIQgDBLMRLs4/I0sitFq/wDB0BFGsIiyWAUruUFKKaRGXYiP0Q06o0+ngy8WV
DKEgt+vtm9NyDNgdKzssNkHBoyNNZcDi5o2n6fBgD739E4yHV8ji+jQh76Raw3anUOxumMVZb2/f
vhU8iGPWn1v9qdhwtm0j4KTTNXTzV4NM4bpCbbjuD9FoeujPrvDx0x/I0xSdpi/tOLQZB01Q/I8y
yLYjPC1ObZaFkqF0WPdvi1QGAvIkkFIIkI2/HE3+lYNbDKEgkRVrNe6PKdHN9uxep/2T2pMc1t21
oZbRNjzWluWZX2g8j5yEYlIFIc+wkeEvzzDGRYmmw3Cb2G/0ZMf9tocsCRCP+tBYySsK9DpdubGJ
UZHNTl2ZIs1FBjlJMpFGFi13Ylhs3XnAYzFaZCM0P4NkyfFkKj10d9+vhlDk0A1j7SuBKWFWxPC9
7lq382o/MOiurA5Tp59njA7osGwng0/RqBU4rFX2f4tSKCMr3YTjd9D2OiLkNw6G0LUYRpFiNp2J
G2JLTVcamXXEaYaU+a6kf0q3PU5T1ZxdTXumw3rgwrH9pNNuYjidyj6cX1xif68nEeTtHcyRZ7n0
Kq67891xXSSb1KF6wLaVT2iolz17CEVtDohAxo71EzJiIBid51k5puoFZ3HF3BKeSRItctNBs9mD
b/sI4wjjWR9aMhe+9WA2QxhFElE1PRd+wxeHRYJplf6paMqWWYML0ii+Jo3eNVYddZyLYOBgNMJo
NMbBwf6tKEvTONEnhuN6KGRAxno9ShAEIvO81cf7xpe4hjrai8Z81Wc64W4Z/SsZ6lQKdSwfzgru
hFWsZ8ZGiYx99tFr7Am7ehpOMZ32YWUJTBmxXUjvoFQ5JR3swJJIh8oC6SL9I8OCpFFSIEgaraqG
dFjfsmazoXCshE3HBb6cn8v04eUoi7tBfIs0C8OwUeTpWjiBFUbo+8oh/4xVugL1sh9kas7uOSyR
VKHwHsHyF9iKeqhLvMqA6TXR9XvidkazgaiCOnm2aJMhtjQcT8S5UYWh2+1IdZAWxgnycocq0ugF
q4YL0qgBy7gHRL/TGyk4VpII0/168HWUxe2SF1YUe3DcBsLpTAoZqzZGv6PxBL7PPsqf7eFcyP/r
dtTmU7IpxS7ebjvOjdVjL55rrJ5leYJCxvnq25ttWOFVhgXP76LltUSdYTTrI49mosu+PACBg1Ln
YajmDToOmg3OLdRuOyxJ/yrSqKoaMlrySBr9TsWLzo/qCKOJwrGyPMeXM0ZZHdi2iuS4vTyNRAvM
9XwEMxM624WwWuNhNXwfzVZr832EpW1TUb6OwYmpGd9rObjhkVNqxLJyGGkILZNi9/bacxZqp3U7
pd83Ri8EjEnCfPn5e/4HKMEUDbnloNXYg2u7mMdzTKZ96GkI585Dgdyxi4srAdfJqWozfVviVc2p
8LdEGqXzCZMEmksHky3G03/P9ve6+HR2JsA6JxBfD0fSHrO/v7f4e13LEAYztLs9mJaHIpmofrsV
Gtf73l4XB4en6F+fbWWpaVvHh1ErM5udo2++YXnkkmjzRBO42RwzNrpukYi1qlRoG8bTqSIsIJfJ
As98fFfPkmdcAmJNqWZAc3x0iVfpBqbzMYLZABYF++5xLJPJFANOxinD8nardStiImm0hLlgi3YW
kJCCwF0lL6vxLY2rG+M8vIbnYSSVSBVlfT47l6EIZH5XaWE4H6PR6sDz2xheT0T1QlsDcZT4mez3
Dq61F1kNUxgzjr43EmO5U4+KkKHcbLe03V/tScYUi9EHBztsI0Ll1Ut0E5bbRqfRkYbj4ayPmHgV
+U337BRB9vPLSwHWaXRUTJeWHZCw3NnAnJM0aou21U3VEPCkLedxTmK/18W4dFiMsvqDIcajmyhL
zU2MEcwmSNIccUoVCNIs8GPdu4sT9nqv0cz59PJJ528cziRtqEVrTg2fAI8xRiiqRy2Ga1FehlHW
8w5Ge2rTNZ0P+wAbPTTcpuBAo6APRAHUQPT7P5FDNfvDkTg3GrXbpXBQRlh0UiEbnx01nt53HCGN
5ouqIecTPkwavWt0TB+/nCMq5xSmxLLOL6RiqPrqOEEamE76GE0iwbjSbKb6rle0LtShVtnFzi63
H8qo6PFoU93xagmK7dS45foYCeJSDfObsCxC3qsQOvo28F612OSWi3azB9d0EUQBJrM+zDQSzOmh
q0lndHl1JfrmsiVqtzfYkHtTZKZzWiaNsgVHxtMvkUbvKo1+yyg30223cNEfLKKs6/5AQH9qnFdR
lo4ErYYn+5anhVRdV1cwfHjS9cbsNbC6Zeaun02lML9rrTqa6D35Mvln/Xte4VW608BeoydR0Xg+
wjwYPohXLRs5Y9eD4SK6kiGbUjm7edrxeOiwlltwpGpYSc08gjS6bPzsk+MjieqSUkaaUdb5+aVU
ESutLDqoHClmkwi6bkALcrQaqyhm1GStV8exWwu8jsTR7TurXTXKQTHl4WCHPJmsdVvEkNhiY3sd
tP2OsOtH0z6ScAKHDcTfubMZTV1d9TGnbEz5GvGrZqNxy2FRBjkr9dUr0uh4FixVDUul0Sd4EnK8
2q0G+qPJIsq66g/wZjqT1LCKskwtR7ftIwgzXPav4dhdOPaqwKwaeQpt2zuwaw6rqJG8yw5fPDqJ
vW5PNNJHgzlBn5WfhwVeZTpo+D34TgNxyhabATh73HnkKeQk5svra+Rlukej0B6bkm85rGXSaIlx
Bf0lqRmSUqm88IRDYxR1fHSI4WQqPC4aexMJ/rOSyM+jkTRKuWm2O3Ec2Txin6G+UgB+64/nre/A
jqeE9fAX9diL55kqk7+ISXbrj7Wv8KrC9tBp9mCbNoJoJi02ZhZ/E6+6G11d9/sIhCh68xoHRlTA
d2VhhVdVSqOmIVNwNFOTCiOlZh4aKvEt29/bQ+PzF4xn1PpSUdbF1TVOj4/RalEHXn0mdRBzs8Dh
4QHm8xDzMEfD+1qK+al2UyR49Ri725pTrt7tuotddlaruwVuOhVUxEt991QnXtVEr9mTFGwSEK8a
PQqvWjaOIru4uhKHs7xBYkhVO05lTBkr72AWmqSNUjXkZLA0f1Bp9HtGDtTRwQGmwQfOtFhEc+cX
F/B9b4FlSWqo55KWJkmCJErhOV4pkPg8u1UZfPVXu4xh1cVZ7J5Sw7K9/CxSJ12lkwScowzIDUsk
YVpeW0nCzEbI5hNwMuD38KqvoqvrPqazufwsGJKmwTINaVC+KyqnlEbVJbF0TvFR+JkYh1Q802HR
Dg8O8PnsAkEULaKss8srHB0eoN1WWFaVGuZZjCxLRUliFmZo+exdxA9gu7vOV2k7mxL+CIH6S/ed
8FDKmYFFActxEWopGn4Lvt1AlIaCV2nx/NF41bJxZDz1qEj+pBY7m+nopDzXu3c4BJ0JHQlZ6V5F
GtVYNdQVzeEFDsvzXBzu9/D+89ninDHKIi9Lpu0soiwWBHLs99rICh2j0RCWYcN1nu+0bu/zNla9
mpyzy+t8uw5LdUCjHlYuoF0bmyP2cioGb6Yki6VZmfLFtutLP10QTTGdDWBSEuYZp0Yqg9d9TIJA
qAyUcrE4YVrT0Gm3vhq/VZFGtZI0yvQvSdIFu0zG05OD9QKnQYoDsat5yQUTLOvyWkD55WEVbNnJ
8gi208FwqEmUZVv6CtQctrPmqy7eV1sBD+v1NG53/adFgdwwRAPdpSBgmmMcjBAGQ9hLkjDPEaw7
k+iKzY65QPS6oUtER931u+lgkmY3PYMlaZQM9a9Ioy/IzRhJHez18PHsYnHqWDH88uVc9mnZiVoG
+wwngrM1W13kiKAV6ZNS4q9IPDv5UFyR1ei4d1cP60cAJp55CDeUBRuu34HtOAjjEJPZEEk8fTJe
tWxpmomcy7SMrqgaSsdHAqip6/Dv0Bkqh8UmnFtKo/GN0ijJDNTGeskVU1HWMS6vB1KRlNd0HZfX
fRwfHy7Y79V7bbPA0eEe2p19nJ99RhpzhqL75H14iZN9tToRR2twHW8Ue2rhQp9mzzx/dCKppqOw
XbR9EiRdhPEc0+kQWhLCeUGLJVPBwWCI86trqQxaho69XkfImpR6cWwb9j1YFNti2GBULKV/w8ls
8VCxwGnPZLm/bNGQxsCm6M8Xl4srnmQZPn8+kyhrWZWUKWASz9DvUyF1TLkINHzVuvPo8/GNf23D
tG1tePuHvvugex1P5nNO3lN2n6kfWeu646PT6Al1YDqfIJipFhveiy+5LmzB+fTli7DWaYd7ewJ4
Fxiq/kHfF3LmXVtmuUv6Z5sKhDfU7EDOJ3xS0+oDRod3enKEq8FgsY8V+33/+loisOXojwD8LJzI
NB7ud5oqNYdH+82l5udX2+khFDWyXVxPi6BQe2IKaMHxFGWBdIbRdIA4HMMu8mfjVZUlcSyRynAy
EXG+pufh9PQYF+eXix7C++gMNI6WX6R/JI0apgLHbUUabdhUdVjNhWq1WtjvdvHl8mqxEhndffj0
BZ12B42Gv3gvt+lalKP2EcU5LNdClk1hPmFXtl4kfLVVge6ru3qKEEhW8uNvYF1/Wl9avexuGvvw
caiB9hoKTrFp9ODZHqI0FpUFxPNvSsI81qhvdn55hbPLS5UKmgbevjkRCoOw3Mt2Iupf3eewyGiv
xtPTYdFRxJz2rEFSyYb/OKXRxxi3f3pyLFEWlU9p/OzJLMDZ2Tl+++3XRcsOjSlgnM5xdPhWKp39
ywRFEb5iU08x7YdRa3j5kZDgB92FaXsyGPNRRnIiWz2MHR6rKCZKUQ/GrCoFNKDZTAG7sAxLtdjM
hjCzb0vCPNZISRgMh/j45UyqbnRMx4cHODzYFwA+YtNzUQhoTv2r+xzP8nj6r0ijJQeLGu+rsna7
hb1OB2dX14uHFvfr8/k5entd9LrdJQAeMPUCwWyEnnsCv9XDbHQO03hsplDpYe2aIsiPaS8aVb+K
C8jFTX1z123IIM3HGp0bn7a7SnT/Fp1NDYYoZDCE7bVEZYE3zCgYIgpGL6Is3NoOP3M0xh8fPkok
xQ33ui28PT0VAHsy6YtsjAyccF3pH7zPYc0iSrtoIv8ipFFWDUvSKMqq4Sqrbbzub06P0R8OEZfj
xmjEtT5++oKG34BDveRlAD6aIphN4TeaCIMpsnQinK1vnh/+ry5ealcX+o8GustCj2eYptQDfxww
y0tnOz4azQ522u45iWyCSdhyY7po+F1RWSA5lJSFTKbYPJ+y8PX06ak4q9FkJjhVu+Hjl3dvpUeP
DoYgPKM8vpfY0N3+wSpCEwBcSKOFSCPfIo2K1MzqpaCpMMqZiBfXfeXg0xSGaUqq2Lu8wJs3b27p
zTOimk36cF0Prc4ehtds6P7+PMPdns20CquXo9x6TiXtFBpvCraYPO5vJOVIODl5FUqdW7J7mIgk
gmaSAnro+D3YFqVSAmGt62n0rBabb5FD33/8hAFnDBYFfNfBb+/eCmu8wqlCRl3l9BhGWPc9UG6R
RstBEwvSqHYjNbNqj1VhWZyowyIB10KRJDAtSwD4VrO10MySY+D3PMJ0MkSntw/X7yKcXYnM8uOi
mnrduD9rYPcyh7XCNfiUlEGvg3TtC0ypwpSYCIcpcLoM7yfTgeU20Pba8i6qLASSAqYrfbJQfoXO
inQA6f1zbPz69o2IClZpuUxI4pj5ioj5QGsNHdYNXsVBE1QaJQhftsqwavhC0ui3BP56nTauBkPZ
73kQCFQQhBHef/iIf/b+Csehm78B4NkF4HicNdhBHM2Q58HjItat3bg7vNDrN6q+DlazR8BjrKye
ibPSDaSGCc120PI6cCxXUsBpMFaqoChkRMWqjIJ8n798kVSKmJNtmnh3eiI9ecvtLYxYiEXRm4pK
wwP4FZ1aNZ6e73UsG9fB5AaE13ThQK2DMU4nRSxrOBqjME2JutI4hu26uBwM0Dk7x7t3b29ho+Rm
Tcd97B2cotXex2gQU5TnwQfgK9O9XrZ1DOv5tv09eMmeJ2ksP3PUuqn58F1fohoSHYP5GFoSwV3x
YCBO6vn85Ryfzi/EGVGy+M3xkTQW3xXkUw5LAe669jBTPYqXpJHL8fRKuUGx8l3TupdsuipjRZBR
1uVgCNfzpAWH/Y+FruPD5y+Cve3v34y5J2aapAGm4yHa3So1vP52aliDAOtnbmWsFYb1MwVXjEOy
gppVpXyvNBO3keYZwiQUR5WEM1hF/iShve9utygEs/r85QxfLi4ljaMTOT08wLu3p7fSpmWHJb5l
TgMAACAASURBVJSTUsOdzc/3WZhQ6718X6HBMgzV6+eQNJrBdwjgY23G6ImcsSEHvHJBW5bsA/FA
7sc/3n+U4yPhtDJT1zCfDWE7njRHJ3GILJ19Jalcp9acbTorDT9A83MdDmIX/BWrbFIaIJCtmSgM
E4blouG2JCUMoxBBPMM8HMPIErA9d5VpCB3PZDrFx0+fpXG4SgOPD/fxy7s39zormoj2LQn3Mcq6
z+ZRgqKcjEOHJZI31H/XShDec1ZS1fyWdbtd7Pd6+HJ1BU03BG8zUcjUHurB//HhE/76T3+WFp0b
3awMk/EVevunaHX2MewnyIvo632t/r2FxSYV4zjBeDyS66hvfhdqZ7Vguj92ezIRUW6k21uvaoVy
ey2NTJSStNxE6t+q4rHelcc0SPjX3KBuSGoiE54NG5blCFPd0HQkWYJJMEYUTlGkbFoma2m155RS
wcPhCJ++nKE/Gsu+MWU7OTrEL2+Vs3rIOSpnVerLyvm735GKNHI1aEJ4cWzOLh9pGYTmsG4ciNgV
o6z+aIgoYbSa4Hi/h+vRWCZVX1xewXdd/PrruwVOJ3SaLMR0PECnd4hmex/T0cVXeNZWH8wFMJlO
cH55jcP9DpzdzodWYrU7BTKqtXyy5wUraOpnYi6KyKdSDU9LUUzGMrk4zTTRDWf3L3/Hxcibscgy
REEsJEIK2zFI4PfFlm45MPXvxU26+Cod3p2ly/26GSlbekRugHgNqQmGBZ29f5YLx1RPdo7YStME
s2SOKJqxgQ8WQXW5Q1YbVc2CAP3+QFQ5qyESpC6cHB7g7Zv708C7x3dDEH446iNplOdUKY1aijRa
gfDlfMJNcJmY8rFZ+9P5pewL097jg318Lv9NPMv1XMHrKtoGq4ZROMJsYqPZ7iJNEoRBHwZy5bTY
hFE64TJO3sq9sNP0nR9pLqEQ/sobQ8rgGvsJdRWVwEAYRIjiWN7DoQKMTBzHRRxnUu0Z9C+EkW3Z
lmiPW7aNLCOOYaLV6WA6meJqOECnwwhHh9/04fpuGaXlKuSqFmOZAmlVZFF+Vz7txondHHXppLiv
3G86Kc7/sxxxULzBuY2M+FQciGNN0kgkjY0ihVVg5Y6K+88q4Gg8FnnjwWgsKSDTnHbTx5uTY9FB
vwuw3/9ZNwf70LxXpTSaQLMVadSzHWnvqcZ9CQgv4+mxdlPs9xNc9YcSYTGi/OeDfRzuJTi/7ssw
1t/ff5Bp1ZzEs3BaeoHZ9BoG10y7K03l8XwoIDydLsmoLD6QSrNp42ljYaTbvb+Hc/1WB+BnhVVC
7QXOSUiIfHqVNzubmTXDhMkhCqaDNE4QzK6R53zC5aLDRKY1vxzTJhwE9j/rliY/G47BwAa6ZQkQ
K6V424LLySq2JReclTh+KSrkzXHwjlqOpvhLzuHjBJrqe9X+oRwZMRADFvEoHkOptCmuL88QJyFS
kS6OkaYx8jSGURRysi3Z1orLf2X6R+Y6ZwheXvURlSJ3dBjdVhNvT0+EHf6U9qfKHlIcYzRFR6CO
n6O8LKkayisi3KeqhpuiBnBW4dHBPj58OZOo6vLqGr/+8k7OxWA0wTyM8Psf72EadAJKVplfhpZh
MrqSNUjBvyF17DngVrNgWbbo269IbOJJphj8mWBrrv3tiPhncFYvAN2/DbsrHKdMC5acEzSVLnFh
6HROpiUz8yx6nioVLKOSIJwiQwK3wd+pdhR+RFEobhAQwff5uSkKLYXrcVMloVTj3w/AIKrddctR
TznCeII4C9RCLdUhuG/87Orn5e+L8VFC2b5bQirEGSXl/nJSC7/oqLIlB2UL23t9I+k5ims2C4SL
RGdVKYWyCkj9qsP9PYmqHmpcfsiYVi/wZl6Xe9KSW6TRDEoamY6yvLuNQheAf1PG41NRVl8asvuj
kaSAf/71F6R//x2T2VymUf/+/j3+avx5MddQpG/yGJPRJTrdI8G0RgOllMoG+3lwDZ1CX5u+iYty
QK0E/OyNrKcT2aSZcZItesQWUcQ9JoFHlU+r0hHhSSTLjkm+C1B0Ezkx2tGVc2LkZC6cE6MWdbPP
0wBZlgi+o276BEWewrN502dSHbkVAVV3EkOqe403mJIeKZiXlFEA8gRQgYfahwonKJ1w9W/RUFhy
Yotju70Fiab42dwLfukbcFCL/r0owiyYYzwZ47o/xHQWSARL59v0XOmzOzk+RLPZurcH8HvGiFSc
1gJHKVPmpeMioL1MGiVedTGd3wLhKVWzSfIl+yBPjg7w+4fPQiH5dHaG//Kf/hn/9Nuv+Ns/3mMa
zNEfsuH7A/78p9/QbDTK49WQpgHGoyu0u4fodA8W+BEZ8dY2QiwNkr5TmUS1RWUb3oF6qfkSnzbH
0wS2bQoWtNzhvmxlrCFL0+EfZbGkQ7bbhOY2biIT3YChmyKDYpuWlMJV1FQgLzLBB8IkQponMukl
z+igEnmdah90ZTdp08t026u/fPzNcl8nMh9tJdhfXbhFLvnyfXxO2se2mulsJjgVo6p5FIkz4Q3n
OQ7azYbIw/R63UdhVd90WCWVQXGyvo6wSBu4pTRqWgji6Gbas2VvHHuptN9ZWZuFoaSCLD4cHx9J
mvi33/+Q6OvieiAP0z/98stC9I+qqGkyw2SkC9WB6eD19TXyjGPOsHHjw4fEWPY+Dvtnm9+BLVOY
pOKcZkL9ITZLLqGZZDqQGvCbTfT2D+/s6tc2nVhw0rkszl5rD12vXfrhEqiWp1KGmGQ8VsVypkoq
csrT0jmBkZO2VkxnlVY57OVvm3yqMJoK5qHwqeikxpOJTLThuSaGRq5Tq+Fjr9vF3t6e8I1eGtWo
VElFl9wO9+OuSc9g+TPH0/OGD3lzW+W4L3f9HKz7jOkvqRt/f/9R8DTSOnp7PRwdHorT/8eHT+Js
zy6uZJn/9us7ESeU9N+gesgEkxFgOQ1cXV2h0/KRpHNY5k2avAnjw54PpzQv5N4x748n1mjalpxU
Kg5qHoYCd4ynU0ynM4RRBNNzmK4xW89lNNLtv74pjVVF7jBk+pZKZjUL1YQWAs5M8SSKKrEcOiaN
0r1S75M1vMTlqbF32rIxkuFNxcEOrJBS4mU6nWI0mcoFFPJ5UQg5kgNNmw1fWlMYUX2LV/VUo7OS
dpxSZJER8d2UkDLIRZmvczy9ol6V8egLh6e+xLhN9kZSRXU6n2M0ncoUa+Jbb05P5Xjef/oiDpcT
pHlcv/3yTiSgl50Wn+jMOtKczPgUTZ9V4A06Ld68WY6rq2u0mzY0Z30tTtu0yklxfTODICWHBaQJ
nVSsWtiki4GzATyHPyZIoxFG0XjxIYtrsnRx6LTG8ykicp9SVqX68JJwgTHpX6V0r9zc710oRi7U
jyLtgQCriqbmElHxO58qCnRV0RTVEDhqi6kfnVQ1k2/VjkEUGoSSoEmVlM7zLsapegbLQRMkyeaU
c1aYlppPuBlKw0NR1unxIf72jw+C/Hz6fIb9vZ68/u7tG3nP+0+fVaR1dSUP3F/fvUWnrSRp1HSd
DJZmCD2EsEd/FML3dDQ8+0nTd55rgkjkhZpWJOl9jh/WSTGSmkxE6pprTd4jMyYNgatcx5Z1bzr2
4722PGFZqStJliQ9urus87ImU1W1oqweErtT1U9+r5qKZZR7SkeVIIxiaUymkxLHUMGd4qQ0AbO5
aHnBuu0Wur2u6FOtEx/iTcttyNVmtSqMZf+XWRG3SaO2jNxS5Q0NOoX7NsBy/9b+Hx8d4fziCuNg
jslsJox3Oiuet7tO6+KqjzRJ8dsvb9Hr9VSEaWjI8xhN34JuuLi8ijCaJNB1C55LvJZDZtdnPO+s
AjM1bPi7H10tnNQ8LNO9GcYTTilnJHVTDWMk5ZROiqk6q7ntVktNP9rqEeyI0cmI48lY1VTVzaqC
xNfk9yUwLa+Tx8P3SsVTOS31b+WkWPqno6rY+4pkqvA/VvSkoGFbQhr0XAcN35MnP6cfryOaesiY
csq2yp5HIduWxuOlUB9IGs2Y/jlSNVwmjcp4+i2m/0yRSZad/P0fyKn5/uUcB/v7UklcOK0ComfP
aJFkU0pC/5amODw4EM6aTN6xmZpF2Ou2kKSsJmvoDwM0PAOea66NoyVpkGmKCoVO6VbUp2L3JCeV
MJKaq4JRle7NZpJRfOWkuN49T5xUp92Sa7jMHfzpHdYi4pGvTLAapmj8Wb6ype+l8yF7vIqe5G+y
XP2+fI03s1QRpSn4hjJyS0usSptLTIr0CA4u9YlNeT5aTYLoHYmo7C1FKrJYyOAnr20e3gLe07tK
oySNJunNuC9QQ2v10shPtcPDA3y5uMBoGgiedXF5KWRSRdvQ8e7dG8FwSTZlOjIJ5vjbP/6QNUAc
jOeehQPLoJviMFkXcVrgYsxBsS3BbV1bqW+sapTZsnFdEs+0JAXVsGtOiutGAecTTKfBgtB820nZ
aHDNP+Cklu9V8x/nl7eagitgXIiaZZc+L0RV7RnPZwjiuVT5JpmJRqooDfKekrtTvf+Gy/TyE62q
j2VUU/GCln8uU5f7vt9QK274RKrfLJUULIojAfcqoDteOK9UnJNEQVXFjF9lCWLRhVhGIfJvkxw0
1kFLq16vCqFyPkrua8VpkynvGhquTWo6CkOX6GU6GuM6jOBZtkQrxITYD8jIaxOOgAuHPKo40dR5
iZMFAVWceuWEqTRq28Ikr8Z9EYTfNAfrPqPDeXNygsm//x0Zo6yzcxwdHMAvqQwitXx6Im1d7z9+
xGg8FQWKv//jvUwMOjk5Eq6WdE6YrNqGwiXksA5qmTGKPr8aYb/XgmOrrowVzIxdGG9ckX+uqhs1
Nd5TFe1mUd2bTIQfKE6qXPSPjaRucw5ZfAowGE1h/u8fPixuaJq0KggHR31nv1v1M383SxNMc/ZW
aYAdom+Nbjm1xc+3yJdLEUX1/avevLtn4KYymS87rEU6Vv5cOiB5rWxIlt+Vyg7VEAW+plptShyJ
fXBRJM5pgRmJY9KgmwYMtgKZCieqGqZv76vyQMvH9/KLDgRFjqCIRMAvD3Pk15kA2k0qkjou2q6L
hkPVBwueZaHpe+IY1mFMS7m4KDmsSs3hgh1ekUaVjgxVICxcjyYLEN4x2WZVD9yFI8u+nJ1jOJ3J
sZxdXOBPv/26wAB5PAf7e9LG9PsfH4Qhz/Xxx6fP0jhORVa28vD9nMCjFyk6TQs5cuiOh/PzCxyf
vIVhARcXZ/A9G77LdPjlKVyj0YTne0iXCmJ1MZHRJv4a3VT3KkyK6+O5Toqfy+ITP5OVQoozXk2m
GJCHlXq3HwcL5rdUppgCqEiFpZaKkaAI5gUGWYRhHpUgs+onqyIf6a0rq1tVOVwqiWU0skiHlrZ8
9/JWwPMiQim5QeJURH1hKYLjuVFHe+tzqlkPqre6dDLyPwOW7wvd4nsXRRxgiVVV0jbKIVcO+OZz
1UvLvYnVz5WPq5zfjWOVKmDpYCunq5s6DMuAYVPZCRjlCUZRgmw8gAW9dGAOer6PDquGvicM9+ew
2h8ynmuSKqkpleWFMOv32Uyt65L+5UukUdsyME8SaBZlW5giulvhYN1nJNBSfmb8P/+moqzzC2lX
Yu9hZbxO7XYbf/2nP+GDaIexHzPFxdW1OGr2Yu4vcdwYbeVCgE5xfNiFL031GvqDALruCK2H1cSi
SG5N73mKyTrTNcGx0miFJ+QFJg3vYSgP+6q6RzyKzuqlTooFBhafKGTAh8bVcIx+ECBggEFye6/x
MIZ1EzV8f9HJjSn7oK9Uf/wxpm7ym3435TBL6ZgyDeONw1K78ld3nMuSfIx+Jx1evEd1G6mbs/w8
iTqriPLOz3e/FtHlYltlvyVzfeJh0qLErwIJSbck3Ba5fHG6cdWvSAdmNRR7cJKnGMcJPkyGaJo2
9v0GDppNdH0f3aavBj+sgDxK2oSuXUjaO53RceWyaJhCVwA7HRaVNLjfTAm5qBll1MVh0ehsuq1z
9McTqcoy4vrLP32tgsDCxl/+/CepkJ5dXEorD/sPw9//kPTm6HBfCiAV/MFWLMM3EM76SDMdnXYT
jUZLihS210GazKWjg61mXIWPxblEUinLhINHHKjBgi22QBMqHUkYpuKk6KwYQfFc8AHGtStdMEUh
FISFk/I9WTvKSd3/IL1JI+dlm9lUOhD6sxmCLEds6ChcC27LhWsa8v6Vg+5CIpVIhFFJsaiOFVmV
muUSwqnxXgQr+QQxBKClV1YR2M3nLW71KlJZitQWv+O5KG6cSsUJu43FLX3hJm1dvKbT6dx2PrJv
JKtx/0ySBk058dU+3rgh5eFlLS45vUedr9LZVtEbIy1GKDOGw8EcAZ86oqEVI8wzwbYiVh+JldgG
zIaNeVHg/XyEj+MRep6Ho2YLeySUNhpoeExrn+84WFamugEbnblIEw55sCwhjVahI5ucFWtJLV42
8RHT2jZ+9XWUdSrRYq5rODu/FNoDp0jf916Zz+h5wpLnKLQ4y/Dx8xdMJhOcHh9hb68Hz1Pyz6Q/
SCSFAnsdTyZLdjtt+A1OP+ogDGdI4xB5FivnJQ38+bejYY6yy8h/I42CUtObobkrfFdF+jRCAV/O
zzELVBRFBnrV/aDOlamcFGk3S07KfYB2U1EbAq5tIUXPZFTb1WiMWZoh1jSklgGz7cHlQ08ntSRH
FqbwKJiQR5SvUNhOheHITWncKBY86YCrqEccVY40yeSLpX5qJlW8JDoFU2MJ30DBCoxJAT4DZomb
CX7G5lnhw6jXqy8hk8mJUqV/7i/bQgzTkPcS05HUsczDlo+icnqLKKvq1t+SVZGsvtTIzTF+vmvj
sKfannguibUNxzMMWRZm43MSI8gScRwxF79lSDtBP49wdRWgObBwSLmVZgsH7RZa/vN4W57nwvMc
0ZhiZEKn5fu+9OMViyZnAsNKabWS2qmbw6qirD2OBRuOxPF/PjsrB8R+nRfwXB0c7IvTIu3hejCU
G4w42Cz4A0fTqYraOu1FFdc0Kw20CGlcYDbOYTkebJvnsCkAfRQGIjeU5Yy6Mom8+Df8qh6ci30o
01Q6hCKbPvu4K5Xe6nsFryzyjCUtOt7/vJcsXUkyMcpjNwALU8xg+BofWOwAIO2FkRS7LciTYrr3
0BpTTipYVA0H4zGu+iNMSfHRgFjXkfs23JYHWzBZtiPlIlbQMm14lgGb7V/Hhqe668spJ5VyQaVf
VYHU1c9JwXSlkim+aQsWRyeOQhMBvfvAoQrPuhGGU/kuIzGWQflEEba8OKZCvnIjR8ZOel0KcDJA
IDVyEPJNcg1mlsPMdeipBiNRTk6cXhmyV9GSXARGcTIOql430reMe0qH7Bk2vEMbp+gtnryUAL6e
zTCMQkyTSAoiPEmmZ2GOAr9Ph/g8HuNk3MJJp40jcrnouJ7gSHi+Oq22TIdOONp+PBbGeHAPabQC
4ZkiitJozU6zGlhxKhET95UN0oyWqBN2n3F9NpoqRWw3r3B2eYnheCIaYJ/OLjAYjkR/a6/Xk0it
4shVEVcSjRCGE1iWC8v2YFLc0fGh+y25rlFEqki8aGdjo32lNMI70TRt7O0diyM4+/Q7OBnuxm4p
ut38v4JxFlBEifUuFFVK9ZGFjNKyACXvG0MGeVBWRz30iddR0ICdD8pJ+Z4rkRRxKXU/PeykFCFa
pXwjNqKzF3YeImHhRoNgU7pnwfEdCZKEcB2l8HQTvuGApQsbBhzXxiQOYZKYKDd4GZ5SMEyiIipH
EgsSMJv5o3JogzjEnIM9DQN7noeGaYkDUxGaAoyrkFJwmer1JWoBX1PgvYqKDPJY7jDueW1iMqzl
6UMZF449L8H1qJD9zBKG1pAJMyKoV0VhSxFZ5cAs/p6pnfyOLGUVydGRLf9bMZyVjpNlK4G+upns
s0cw8xDv8n3M5hHOByP8/+19Z5MbV7Zklq+Cb0NvJI1m3pqI3Y0X+23//z948XZ2YmekEUWyyUbD
o7zbyHPvBQpoNkXT3eK+0FVAbYkGqupmHZMncxpvsSoybIsCpaVSRlZOfklWeB9v8GS9wdPJBA8n
Iw0on4YoJ5MR3r5/L1LUHL6WWkZHabTv+wekUVFuuEfhvs9ZVD84o8X9YiEFc6Z8LL5/TNiQJQHS
G0ajgYz4EKjI6WKU+cvrt5gvV9KJZLQ1opyPpnOIIC2v/jpBGscyUUvQcj1fwMh2+LVSO+Hf57ib
2neVgJZHiWlJrShOMIEtTQ7TVDoQsN7Xm7tAJEDFG7cjz889TmCS8oOmBKklM0C7iYw8T6SJ1h+o
Wt2jBw/AmWOCVBCqetRN55YZFAGqO25DkGdkWtLLgNGU66DxHQSDUCIn8Wtg2Siv0RcBTw9ObSF0
PNQesMgSbJZr2KEL96d4IRtfwj0OKh9tdNdSm9nVkQpDRb9RUVDPD3ASkIXLP9igrirRVpfD4KjI
gBIe1KRicVkeusCsorRWOk0GxIQt3qUn7ABOd+ckilPpqud68MLDMK7iVKQ8b6nlGjXIaXKjpKZV
La+X78uklyRsEtAIXLvvuQ58ghtPtKln6Z/zIS1uvh5xaVFOLbfZofvUxdcx7EfyeFlWmC03eLde
Y54lAl45agEu0vUYcV0lMZ5tt3h2coKz8eCTqAcsREeUpi4rCemXy7XU0WRmsG4Q0Z6eLtH2njQq
TtH49paJsoS6gFa6gBT5Y5T0sSXRFgvyf/oe8/lc/h0H0nk8WJQn6XQ8HOD89ERqONSYN4YX+6iL
tdwYeRkjbS0FWJRhcqmmy0iFGYoDh4q6GoBUDbhBf6CiwL2wpHpdJtXTX+0/miBC9o4aASsKVVuW
75mJDf1RpadGwIBlIhtRTwE5O6T+R0b4uPelcC6RVCJUBAVUMTgVKCDlOKjZ+e4FCHRtykRTIaMp
O4BFRydGUxGjqRxXyZpCMlLucH1f/o7rUq3hyI6jPdj8DFVVGicHi6KhfAFliV8Wc7who5k1JT4k
dHSkpsGPbM3zIdGNBgJuEAEC11XiaKzBiNSuYpALW1wDmnzcfU9zqghw4u+nIzgDciaK03QBI8dM
3oykqgIq16O4rG2RynusYNVscckbF3AjkPOm1q2dmfeiojgNdhrg+LNrgC/f02mp5P9q7OYuwI3P
/eTBCR6ejbHZpnjNjUVJGgKX3YiMNHlef5tPMUsSfJec4NnZiZBRPxYNEXwYZW2SRKISFqxZ02oj
hlgq/WOUZxDKxf0L933OIqfq7GSC95wfbFqJmtj5+xT5aP7OgwcPJI2kisLVfCHARWItC/qrzQaj
wUBsxybjoYCcMfwwNVX+GanStEo+mxpcdc05XQVYfFgWUzSTwpnutqVehP56R+PRAvyq3HIEStwZ
uoOuRquUyKNQg3bnRwGdakApInTV6OtT5oevn0fuXSGJ6nSPzQiqYizXW8mMKqlLWSj5bwMX4SBC
QFI19y2DhtKSaIqBg12RL22jCR2s8gzxNoZLHlvPFeXeKq9Q5yWssv54l9CEtcfUBkYVBAFE++/l
kr6xgFjKxm/LVjY8Xxx5QyQSkq0d8qN8Tva2C59zc66DgRMK4LHYzFqTukkYRrmiKrBTxcIvByUN
C908FMjpj+Z7vINoJVETqZk0VYGcCoPV16p1KSkqQTY8jODaXYpaC4hL5KbBje+zMulpp1EgIM2o
TKeo/Jrv0QC7+tnR77A1HFBLnDNqX7bhCZaTUV+MJ55tY7yezfE+3ko6X3OzRB6uqhSb9xlWaYof
KPg3Gtyc/lqWdMVowsqQ/2qxQMEbHQuVJI36HqbLtVzYPJ50e/4WU2mzZCTn6VPMFyupRwnorNe/
GWV1F+s5ZMhTMeNyOsNytZKGBAUVV4wwtlsMZ31MJiNJpViYJnh16z0G0Dl1w5uaCRVaFuQlK5Df
uva3253j0yG3z/x09/w73qNhRNx0Tq7/jR2UEbCOOFiiJCKRlJI9mq9Y14PUmUuwxmyh9mz4TPl8
VRqQDCwtEbkeQivgMCrcxoIXeNhaOWZ0kfJt2IENz/IFN8q4EJCyihpuWanMjs40ppakdLy/bJMc
kCh3jHEbnq6+ly0flfCH2qxFta7kRfu2ATB+9ND3yeJmV0B9TQY1I4DAV13BQU8IKQerS1DtghwP
Ek0RCHJMWVis7kZyBthKE8WZSE3X4a4D3L4uZ2pwrG/wbsBH95JhCsbuHdOAHbgRNOMGVVGJ4J1E
pfqhUlB3F6kKU7wTwbkdUCPAc5JdmW3cfE54PglE40EPj1db/Dqf4912g3VRwPZtlC7wj9UM2zzH
n87P8eTsRKK0Dy2Op1AkkMeRb0e6koY06tLtuQJCSwn3Bd8WB+tDi0Xy89MJ3k5nEs2Tl/WpUdaB
okUU4eWLZ8LPuprNpcZHIiWjjzWZ33EsEep4OMR4PBSdfdV5VQPYNz3vR/8uPiZ4eUvHXb8GghS5
YEVZ7BQWGEVRZloiKep/UirdtdB4NjymfIGnJh50yhfYLoa2B8dyYZUW/MBFETRSssjyFG7gwfE9
+f0iLdByf1C6vajgVY3UuQj8lFRyn/dGB5rmhuJgNmw33eoW0cXBxvv0jltXi51vhuYTZpFHlLDu
VBao45UyNHBcGailzK6MongEMW8XqRkQOxyNOXotLhUHfFGMPF6SPuqxHkPF2EVwuZ4n7IDZPppT
TjGSihLAdimo+rkx4Lh2vCRyc3Ccgh9EbVUhkSlDYG580j4IBgJoBDPWywTQHDkOBDYFZDrtNs0G
OgtR8lrcglQjgRSJybCPs6sFfpnPcJnFqF3ACl1cFDHii0I4X98/eqBlYY4OpetKmkPJYS/w4Yc+
Kj43vftYTNVKDkIa7X17lIabbMFIVOQ5upotJGroWtp/LnBR/YED0wJcLMyTa5RlAvLTxULMMRQN
oC9igaRMkKBKADP1rt97VVrts2VHRZuc/PL6jdSkFuut3IjZtWddqnJtASm/H0rAocayVMbhsGjv
+iKVjqKBx/qVpHw5LrMNHKpchA5cOKjJEMgYTTWwyooyyKBM3zDyMTjpYdjvS0ODEbD7MgJTkgAA
IABJREFUv/78Z6lHsU3OoiqjEJNeHW5U9ZjnKVZVKcFl1DjwYe+L6XrTysAwCXUcLfmEObdu6mmz
LqIjslVbYcnIKF7RCAcRU0bP1yDmi6swQYyPHtutIWn/n5aKSARwJMLG6KIfXbdTMpGbdFV0NE5+
SpZxjqpQx03A7Tqw7Zjskp6ic2z3zQdjJ8YZRh4zv7cH82YH6AUsHtQKMmNIC3MqjpiaIUFMfa6i
NANoqm64BzR2754PJ3IREbRKz5Lxn21d46/T9zKO8iMHfnvXXXaY/oQX75TA2s4ZR8XUtcifKPPU
b5GD9aFFjtPJeIjpYiXEUNqCsWP45VmGav0/efxIuobr9VrE/0iOZBrFdJFk4G2aAeJGTcXYvnDB
2A3kzTXwA6X7dA8A1u7kiJUOG4eMGUXxY9QfY3Ke4O30Cj9fTpFTaJKa9wQlXqMCUqrOJs/DtK3l
HvXlwevLqSz4oYcYJaZFKvVCJ3DlhsfsJ4szlfLpaMqv2XF20B/1lQ4Wx86opjuZ7MQk3TCg1O7N
E3Vmo5pN+3O8xqs0RlNUeGR5GDuKg8MHTzrHMwpKKOuNKaMm/LnZyGikRmRav5+SYvoHIFZiRbJZ
vBQUZ07c9wIMKPZF0NKRGIeDyfK+rREVIXd2vscUjhLAJx8DN52uEpgUuOUCbnKczDEjsMnxUfy2
Lujv6nBU8pQam74JyIzh/kagGiQm/SyFaV7FNWoazoo0igY1RzdFmEp6Nuo10+Ua4TiSc1LaLf42
m8r5e3l6imEv0qmneueMItgFW0+nu4H04Ig0atyev/WU0ERZjx8+FCIpbdxok0bpma8FC+EueR7O
zs5EDJCAsFgssRbgUiqyjOI5zcAbHjuO/JuMtHphKJEXQUscc3jTEYoN65qKzPmlwMROodR+5XMj
Hqn8AoxW1TbJyZtBNEqwdnxMlzOsKGRIomg/lEjJ6LcxE2B9uud6whjwWhstMwOHKV+tCuhxIrxA
U0Av6VuZlTuQcqsGgW1hEPqSLpuRHkZU5Hkdp+i/eWaU0aSmBuihRm4akkMf9oZ4Eg2O6kiMFuhZ
VyFOMsQUk2cEp0dKaFLAzUkA4/f4kV+busjHIqRuWmlALOdkd5tjGidolzV8yxVeEB8DMnElClMg
RlOEKLxbJ5cPghsc2cQTKEsps4ziBBdb12mmLmI5LgbUdoCvjhl/XyI00jS63VQdxZlU/bhpoFJP
Qhtrh2pQvWAw2XTUM3i37Dn4ab3AushFHYIRmXR1dT2tgI0kL5Gw/W1ZGDuhnOud0qhwsL490uhN
S6JGz5MaHLtd7Hp9SVp40xIDX6lbRXjcNEplc73FNlFRlyiG6CZSuVUzejw33KhMzT2d2ovDuav8
F4RTRWrNDTXM3XhNVziS+47ySaQ3dDwD0rRARRlsS6d6noPasbAsYsze/yR7MjpXx0MaXxlrUrak
ewTWHm37qlYwoUSDRZ1imXykgM5OX1HDb1sMKPfd1yDV70tdcTIeC4v+piDj1uLOfR3JUaYTriMh
r/HhMfOF+zm5DCnn4xiSViUyvUEJanzwc/J6fqtOZsZsXN9l9Ve2jQwGM5XcriRl4R3AABhVDiSV
ZAGfd7PPSCNve6l5RnUHUdPtnnT3PhzdmptAriK1owjNgJpEaHqo2qT0QgExNTY6FnEmkoX7gfNh
wI1czJocl5tENwiYemrgsixsLFXv42uLHRs/XU6xSVO0rMAmFdbbZNc8YPTOetq3Ol1AICANIZ0v
JE1h+nabgHVw43ccSUP5/NwPptOWpjyn2V6PTRRpK6GR2Jwo0PppTa04hHweAS6hP1z/W0JBFFFJ
8iLVedorxyodM95sxDDLZZpHsLJhsbHVD+TGtIuiCDJ1i9BxJZsh+A48X0pBvIZ4E1zWKeabNbK2
luaT0/9QAb2GR84epzZ6gcgiDTrR1G+Rd78esD7z+jNRjaM35ulYXRRGkI+pErlDazKIOcFdcei3
Qt4Z+OWGtHTx+mN3cDOKYGpB5FplrdqAqBo5+AQuATBGYYzAmELycymAHh24A/OF+7Mk60a36NwE
Ptg80MV/lWrk6k7KG0BVSddqmybYcGMUhUisNHyPjKiM+KB8rhsijELZAT1qELDgmjct3ElPLhzZ
4HmFdbxCRddtzo44wE/LGd6n2x1lhfU00+lURN39VAJTdkl/7kjT61MW5+AuZ3O0ti30hsePH91p
Dc6AF4HLgJcBMA4Fs44kjR+R0dbpG6NYR7HUGVEXGbmDH9mHejKFXXIOexOgGptpvwInRlNM/QhQ
PvmSen/ynJZZicD2MAoH8CMbkdViyO69q7p/zJJWWYqr5RLrMt8V0JlJyOvdFLB1Ad2raqpoo89o
ashoqicUj7GOpj5XTdf9Oi/Yrz+pItOhIwxuxkeY7FIl1n1WcYot26kc9mXOrSMw8/GzojBuvkDV
whYocBWnaJcNQtsROgXBixpTjMBYCws3CZ1m0TBMJ9mNofmDU4TPH8E+Ao7fax00DxzVOCD/it0d
amdvk1oNtNo2AsdBatnICnZllJxxY1RUNWDx6zwr4Y96mrqgmczbbK9GQbDx1VymzI12Fu/KCR9N
Jh2DKq4kSuO0wJ7GoTqeUk8TQGOtxrlGMDaEXbE0I3XkjgQB+/1Iq21YUmM6tjO762Xkmhl98WHU
O4yqAcXsBLzqvSy3EhFQWQsbZrxJkYDN+iNvUkzS6cxOo1sq2MoNynNkZq8LUJLmFaVkIhJBuQGi
/hD9oI/nD1/Aty0U2QybLBOQ4uzqIkul3sn9xJRV+FlxBjCaIu+S0VTTos+bUS+UlI9ANRruo6kv
Lct8FmB1J5mum7fffqo06LMFrNipcgLrBps4xYpaPPTsIzeE4MW0stRRWKt0oz7WnTQdSZVGSo0a
K5RYpDnqVY3AosKnD/unGdK/vkU5W6OtK9i+j+/+57/gv0zGGHwjgHW8WBMh65jjM4vVSkYl+P64
WBshIZXzozI2pZn5Jlzlz5le8jgk2xz1IJBjyX+eblK4HKMIXNShJ5uGl5xDYUOCHdNqgplw1Cyl
3fWhWppEaftaWlM0KHO2PpWekqFumOaAAFi342mIuR0aB9+DSj9JOv58hr3RbRceMHXpj+zM7nuZ
CEyykSDYRc5ppkCp1KAkst7UfLcdVI4jn+c168U1SD2lAzejZd5gzA1dPCbzEp5lS6ZBrmPYi9Bz
fblZT6KecPcKcl78AG+n7/F+8Q6LNMG2LuHpArorncEKVVoISDHl47UQkeJBOpLMuioKh0RTk7E0
Db72RvBFKSFBS+lN4d6WyFrYNs4mQ3mYwiJPohgMsNtBEGMqaU6ojsJEweBjF7JmCwvQ6Q26bir8
s3Twv1d9TPpnGPcDvL7a4Me5jeb9Ei/aWhQ+mUL+XjWw7uJdeLVSIMXhXBZ0TaeSKTin7APdNmcU
xuhIaiEs3GrCsLImo5FrhattglfxBimHqF0bg0kfzTzGiesj9lzkjoVym8FLC1iBhzyk6RuZyIV0
g0CVTNuWCFgiOJkE1umnCL7qKE0fc7MIrgmhg80IdjwboM5qATWOSZkIzERou3EpGVj3OkTb66C2
G6Ei+HlKgoiLXS2jHKJcke4HsFhnkrqV0IlUxLQTddQ3D9N0kbJIqdJ8U+tVAMUyiS30ASmHWp4U
us0tgrO9KsVTqTlVP8J+TzII1qJYxz0dDeQa4c5ebhL8ejXDLMmxrRvMtks0LqWgHfi6gF5sVQGd
QOUzmtIFdF+bSTDIYJpNIi75ZrfZ5PqqlPD3tHAyA6Vm8Fd1KWksUUvRd80OZZErANPgJZpOdKUW
CRy1UW98fkYNwxAX0QjlcIL+4zEWzRUuwwp/W15hUW/kjsROmnQlgwCjfnTvbse8yDkWQrLibL4Q
zXJ1Q7FUGD7oS81AHoPBwV3uY6/zSV2j//YS/+fqEmldS0ub4mrbbYmiaRAOe/DqFueejyJ0kETq
Yj73Q5wEPoqCg9K5Sk8M98zwzwTQmKa4KAlqGsREX8ukqLprLJJABDZGw0fcNDMDKvhWqkhNBmSN
OscBoCmQ2816spsq5QgLdVlininD2ris8PO7qYCaivQp2LgXg1QzfHtA635mcM40SoyfgKGm7Ab6
O0RjRqqiMGt4edqVyfD6RKyRKq/dY2BDoifeKEINTSZy4gsyUWrguAiYBgaO1GlJPeA1ezoeyE2L
QMLXR2rF29kCyzSRlI9zpjy2Ek1F7PzaKNIcba4K6CR2SgGdjZuQHo3UxSLBU9WmOGd5G9HULQGW
HoT+xro+qnZMhreNB6djeZhaGDtrTCO31I2SKIxFfSV+x3SydT4MYI8fuPjLdwH+/stG9J9Oxha+
fxnAGzpY2SXmSYZ2tUDP8aSIT4MIQ6XgR9aS7tLhhozkq9lMpHzJ8eFmYJGenZzxYIAT2oSdTJRy
wme+CEZef3r6UM73366mSOmC3PMRF8p2yq04iGrj0fkEv6Yb9R7bFmfjCX58+ljSSyWXouzRpG0v
9mkqmmCTRbpjharN7Hh6jDB0p5NpZsUGC8XdjG5/J0prjRxQoKLFoH9YBijYzBEOh5In4qfS5tcz
rryOebz40kvfkQiOT/9v7y8kOrumVMtO2gf2QvsBwOJ1Z0a6lNySUSJRUth8j3wPBGSne+2pRrvs
TA5As5BtoqVGgxLVexUZmCoqrA2qDi49CviRo26sR4lJSRTKdcjf70Y6rIFNF2ssKKaXJrjS0kR2
QH0qG+wDitRUWgJ5qdK+smEJGD3OukaOdPm6tanjWcmvWTfVET8fsPZy6R+OryS0lt/8rOc1L65r
OXZbtTCO5vBhDCU4LsHQd01iW0H1TgVg5BexvmLrGlgvsvA//jPbrxmSrMbLJwEenvHufFgDYxF/
zi7kKhYyK8Nt3slGQQfACGb98NYKx9TV5vzbu8srKcjymLFmcDIeKaUAXTP4msXX+uOTR3Lc/np1
icID+uMemlUiRfgRXEwmE/wzjeW8UeSNiprce4Oxsny/Jt5oNl5J27BCgVjdsVXTFmsySUB7J9Zt
2CVjm57ikdzsnYiN11slDGwdqfE/ATOlnW0x5ZWSANNAlYLycbx87GdUqVJCTpF64Z1f+thledRI
PtwgTLnV3xRPAOHmdf6pKBgo+SPhYO0cqzoquya97UVa282VNM9MNXC6gMBkhBNvkidm1DvTDjSz
JBawyigWSK0pz5eyQB7nkjo+Gp2jsTLMFm/Q81mPpHEsKQmM1vvimckmwW1GUzTyaKDS9brO9VD4
frks2O2P8vVPu1/IBcdJ/JIHkeJ2PprdoVd3mDRJJdKhOSLvxLwAeYc3rsHqhSiaIS9MJbfiI47V
v1MKh+qikn+jyaiqBGJGeL6mmMk0UoWvBsDIC1twwp78MAJYpQr6jMT6AfCv/zXUr+3DV6xJEaS4
bOlRmirBm3gtfBXjcMMHu5HsQo4ofkiVxc+8I/E1s6j++s0FLuc0PmAKZEmLmEJrVAPl8bytRYoH
QYt1lv+7mqHxLQxGEdaLWDaXMs7gEVAa+dRCevP2At9/953QFczq+lPyLbtuJGTK4/dmQM0YFOxA
TUdmVKZl0VmBGqM2BWwFN/uOmsHaGbuZZPS7Ui9TXDSTlqnXbSIeFq/FhZhpqBCj3Z0WmxKu1GJ3
RrlzF011VBPkTXZkt4U8rEX8Ouqf3YiN0dFOOFKIlvye0l0zqavfmVIIyR3kSAzPrzFO+YRMh9cI
FRUYTc1TpnyxzPQ5EaMpB27rqOMaZ7CrBl5j4emjB/jXP/83bFZT/PtqJiqjpoCuXMivG3jcyuIx
cQdyDW9X7695PLrh4Oz4Xxx8OPx+i15DpmqKXtjHcHiOyN1flCJYf7mWkz4YnyPNt5gtt4hC7Rai
tXXoQ0FUJhN+NGTheox4Hstdl8Xg05OBtFZFVEwuFgrvEfxyWC3Jc7d0bDSA8c7EhxmAXm5iLGMd
gZWFeoh2uhLDI0fpeMmgMzdRUctFShEywwPbtOStFGLRRbEyA2ADRmCkUPg+xjJP9tsqBwSrX359
IxIvBH4W0h+enYol+22G5N3FyORfnj2Rpsav6RqWb6M/ilBvSpGVYaQj25OaTgDeTWcIwwjPnj2R
SOBT17HprrC9w0N1ji6gcZn2Ph+7KQOR9t1r+hNs2JxhdCEpoU7XjJbaL69fY7bN5DkfPTyXNHrv
fWkEJBXYKUQ0EZXKNToyVYrtf5BGXndUUoKQ3ejJVhrpIYeFmQvutx/B90su95Y3NtplbWMsU0VH
IFgVVivRlOcpOgK7vy1TPtalygZ+C5wM+3j54ByPH5yhzrd4/vSJuAEZ3tRdLp4/Op/zmtusPpAS
eh3VhIM3fHz3kIOgLgqundGqs78geQ2JpKsAgYswCuVrkUHRphDc1IyeKLXKp/fFDt1Fv9cXjWv+
rgjcSe1HFbD5XA0LkFmCLFmjaXK5S9/2kuFVjhydjuXBE8r614LCZBJ9aQArSqQ1Pfj2M5F8z7IJ
mNqw4LxJ5fiEUaDcbdhF6QeSaHAeckbeymohqhQk5Q066SMf40F/p0ZhFikK9My7Wixl47GNTzVI
gpURiburxZGm//TkMX79tzlKujoHHuoB8HdqZEUOArjIkxw9zjFaFl5fXMjro1X850i2/NY6bhh8
CkDL5IW+KR0vRm+L9xew6CvYNPjv370Q7S+zultg50upgdDYw92EKIff7mYHX5cp3LT42pjVXFGS
OE0l3aOv38aQO4WOAFS8+W5TASlGVJznixxH9P6ZVLPuFXhq7zGS+tP3391LJ/zAIOOG9Nvdbmbm
1zv/73y2+4aqHWwpW9pUSLIEa+uKeZD6sb7rjPquIrMlS/nW6VilU3JH5OtoFEvdsiq4EQubJbJk
jtDn0KzadE0VI15nO3F88oXoPhL1hvJ5sp2haYs7H7AV+eEBxwcivNBsfEpsLCmon2fY5BnWHGRl
3Ysa1VEAP/CRpwXilRpryatWOfz0LKmNkbkvRX4WeQNXBpfnbSEsfGvZyoyWYeAzEmN3h5wvdnve
XrzD1XwpkQFpCi+ePhZlgLu+65nFC9oh7WCdYnCiTF43XoYmL6Qgb1UQoFUDvkqWhK/NuCZ/i2u5
XIq0r2zOXiTzbDe91m9VlLDWKR+7fIskxTxNsMxTmQmkL4Eid7bINinqNIdNBrqOpuim5IUq+iM4
DQd9jIdjDAecRFGRoXFHuvulzW2Mb98HqPyuW6YffYKDr8Sqq1BtWasUOyORPOn86r6eSYogdav5
ecfu4+Cca+F16XIfHRQK/WnVRXaQijxGFY1EB1ue5GNjCXeweEGTq/L4/ASP2hNJRebrrSpgZqmk
j2umHE6LgHZFjKb0mINLOhGJdRWk5c+aHqkBrJFljNRYFA5UNEXl1qzJcLHciCKjAJYfwG4aLKYz
1EWJnufih+cP7hWsuJguU63UTgqkcYb+qIfBpIfVbAsKQT6Ievj+uxd48+atKFFS55ygxSiUvJxv
TXKGNTLeBJQRb4MHZ6df3ai4r9XqlI/Xn4mmaNaQ0ryC56jnCYlXqA6s7xGoSBgta4SMpliDYpeS
ar8cPNYzfYqS4AOOv/Mov++lrhNTzzwCrN/SNjxeO9v4A7eOL35pn/RbbMlSejlPl2Ixb1Hs7ne8
+MU803UkbaQwHgu2V6sNZtsYi1yB17YqJGXkrBYPGtNEanqxfhBZLsasXfSGIt6nivylqFqQJ8YU
kiQ8U8CP60TSrdZlKu7KTNmUE/7vr7QaBQUNfa0Vf3da6sICt4DeKMJytpFjQGDuDyOs5hv4ExZl
R1I4/vvP/xSlDjrKOK9eC5Bx0PVbAq3Ly6mYUcjNyHVFfO9ben3Hq2kIUomMq/EaE5DijGhRqAJ6
SH06CuLVaIsaAQMGau1z9KasRa7Yk0YHZa3ZVdQs9PH4ILJUe1zTSO4Zr1SEtSsS3q5aw32eWqll
aQHjb+makiJh4OP5wzM8fXAqpFXWEFg7YNq4NHNX1K+yLFyVGRZVKm5DD2wPL0Yn0q7eZvmeJ6Y7
lAQxKfQHLqJh1HEErvH39RzBdi0RGO+Y9KhhfYKzX2x3M32TURVhdbtS45IRlK9Ia0gCpZoqIyZK
yNhpjTZo4AvLee+SwxrQS61USf7adL6Qc/b9y5fSDv8WQIHON6/evJXoigf12RPVtPgW073Fmh3s
VJcgzCNH6ylqjZnnK5JCjB36jY2WAo9M/Yg77JTSObpthZZAdx8K451OxsLZO6CfyN9sOwIA94dY
5i8pR51j0YEvnCXcm6DeM2Lp9ftf6jcv1gEoQ8wH0yfWFaYU6dfheqJrXbyKrqoM81mKqzjG4+EQ
T09P8PzhqTzPah2LOQTtu3+9vBTOE91H7MATMqUXulLA56nYtjVWdSERWE2ZWerkw5JBZ99yBMxI
JCQLnyMTvLMy7WE0poaKlTzvp4AII0lTAejRzr0/xi/xEtbQxmDcxzarRE0z8Id49EiRTtnRFJG6
2VzO3vcvn3+VqudtLCqB/vzLKz0VAJyOhmL99a3U2XicWSvdZLk0elaZAqltkUvdUyn5kipECZcS
gWXjxKffoQcrK2TOj1SOrGJXXpVPOEJGXXklNTz5YPdVxDYcH0EUIQgHx0oHd78kAyRhlG6O4sDx
lRFW+/8PePzei7WBR2cTSRtZa7hcrnG53eAqjRE3FSwW3XuWSMcursg0jvFsPMaz81OcTobycOsK
8czBMsngy8zXCRrH1tFXISkkh1y9wEVv1AP42FkwFSL9YteU+shhb9cCZoy+KDVNMUN2zagprmYM
9SPwhR/1oc4e3YpMSYDeg8/OT/CPyykaT6nCpk6Nn95PlVIp632PHkkaQ9DiHNzlbCYb4+XzZ3KH
/z1Aaz5f4NXr10Jd4XthR+yH717eeZf1Y4v10MUqlnlYghIH+000RTdvqUn5Njw/0CBVCL+P3WUK
3/lNC4vTB44l1xZH0Ay9gz9nREWgoljhcc1TaBu1hTQr0RuM0RtOEISKY6Vswu53n3dTwvbrIyxj
Yv8HWH3q4sE3PK+n6QkuFku826zF0DRpFau+9S28zbdYXqaSSr48O0Wf1lmywRuMBxF+ePlcKAxN
a8lm22SpVqzQLH2OGlHZla7cvpL1MAKncpFnJaqcypYNkqaV2odDN+KKMreWolKMBnInJuGTF7Yx
suBm5h2ZWlqGBMdpf0nTfQfxNpO/Sd/DV6sFnq0m4sBD0GNjgAD6+uKddA6ZHjKlffn8qZgK3FdU
w9dAH8FXr99gud3KFdwLfPzw8oV0Me9z8bWsNtQn05MWAlAarMpCWPbk8FmhjQAKpPKkQGg5GJEC
Mxxg6AXwOGOIFlmWYkmOFScehHhqSb1QIqrJWEa0urLPSgyykY57XnJ+EZjOtnjRO5WufBLTso2T
Hv3DhtkdL4MvMoivv3MrNSxDkPtjfd6i5MaP0SM8Tse4mC9xsV5jmmyRO8pWnh3Cn9Zz0R3q1y1y
mQ9scDIc4lx3sHgyHwcTPMZEX3glluvkQDNMBr41kPFhpvlJZjXXAZnNWVpQchIFW951K4YJ9mKl
ah+2jTEHyznuIQ5FAWbUPqcVIUX82NEsSoms4rhCntG4IETpAf94d4nT4UD0zbhRmG4RvMghS3Qh
nlEFi/g0a7hrwwXaVHE4nDOXYgDRqnPx/YtnwhO760iPM5OcZeU5Mc0VnivWLAlWpMXwOArbnTcI
rUFW8Jg6noqkOAYTqHEv2l6lpC6strhar4VuI5I+PGckeI5GUkhnFHscKVc1ybA25stUQIl29HVT
CJO9yDaI15wiyOH6Q0RR/94jrJ1h8008rM96LpMP7CDrD9D6ksUo5sdnj/FwPMKb+QJv1ivMsgSt
byuT0yLD+1UKLysw9j3Z1EzdjjcWv2Qdik7PDzGWc8wLnXI7dGcRADOSO53NQmlcEj974z2RkrNs
OTtKlMQNHJqeyO9O50tYFZX4KtQc0n04Fla73VaYzqa0zRHW+3YVS/Gdg7zv4i1m660yoyCb23XF
UovF1F9fX2CbpkJ7KF/9KgYNjMKOaypfu9QI01bsqWaLpUjukL/Gi5gpEtnb7AreZoTHv0misdHl
lxuGHHeeh/2NhAoMXuSLbA9leELGSbxpxLnUHfvs+noR+idjiajGUQ/n4yGKIpP38Xa2Fv9Dzl7u
gUrXpyaTg3RbjcBR1x3C9Kf9vNjerwqZOqGpBIOo8YMxmjqnJdNOIlm/KdzvMtf4rXQJdUp4fyrB
/2EXjx/TRE68ny0HYnJK4EoaJUBonfSQr4C4amF7tJL/7Y0lg/6OLfIhfHCJ7nqSSfeSKYdEYDoS
MyBWai3unulEmjSSw+B0OKkbOI2rLMyTXP5OkxZYLdYoBqFYs1FqpkwKOMMItW/h3//5Ctl2I3I7
oh7KYV0/wNnJWPhPTC8ZbbFTR9FBAtrXcrU4GkaXFmX4mYg09Hqz1cPhqq5Ii3pOBtDN5kv/Fjt3
BCWRz9Haa+ojdauUAkgXsECDUZqLctTU0wBF2e4kF9cZdnrp/NSbjASsOG86DEOcjPoomCbGCd5e
vJX3slwTqOrfBiqd9rWtLYP7nh9KxzaIOLsbYjyiggO7cTlCjwPXpQLQ7sV07xysPU1KqTXgFrqE
f6xbXYw6WJinO/Nk2sPP8xmusgRWYCM8GaBMS/xjNpMO0PlkJJy0z3p+a68ZJueQxNS8EDv1OFf1
E0OhkEK+3nA2DTJpIEE+WGejNmkuJq85ia4cEuYwe6H4WQS4YBBKPevNbIHV5RWGtF8jxSLUwOVQ
IJGF3lrm6Ki+8Pb9pbwm1lqULZu6wytFZj04rMdhjs05jJSw6EoRCLNMHpQWlvmttlXdW93GZ1R1
PHR9vGSIn7OHSaZUbJmeiXCecjPi4wCo9Of8HQI/aSSysyQVV8V8EjhJHqbCp9jQ8eN4qMDKp7pH
KI0WqhPQCINjWK9e09w1lc/Jxm8lP9sD1Ynu+FExoQu+cp5aB9u0lqhyOBzLvz1I05SFAAAEk0lE
QVQ9YSRXIo3n8Gz6NVOckf/uQ9dUBzjuOTwxQ/BfLS9jpGW4fidWw3/YxeL2D08fwuMF+/d/YJXW
8EeRMJbfZlsUb97gL2UpXcSvMWzgNcC5QD7M4h2bVAp2pphCmsjAaIbxI5n57Fb1BkebnXdyei1q
h2mj60SwzTieRJpGlsHi+AuDczHNoJpoI/pK8j20WG/e4eJyJi475I4xUtyD1R68jFDjIWBR57yS
79H6Sr8skVyhKofSbBrKUG1K04ztUqRq6gP/x47TkABUdc2ZSIEXnYlaJf3cASaH3VV9SAjc9IQk
tcToUoW9HnojDVY6iqIUMZVPuWhAMbu6Epsv+gMSpOgVaDT0CRuObYnd/cnoOlApRypy5AJ4nN91
A9RWIl1RHs84XiP0HalXcZZQiRFwaL8DSLvMSQ2xf+mS0oSu1fP8iKptJ2Lb/8UPhUD793PwG+0X
poRHz/vHusUl81yBi7FlId3QyquBP+nJ4Oo0T1G+u5BN9uLBmUQit7UIgOenI5xj1KnFZFjHqa6B
qYHaX1ZzUWslatD2i16SQeTpebXD16O03MdKBjgrxY6cYGVAy1y/3e+l/EiZF5Ie1QuR59r97g28
HbXUBmzKardJUldFR0nd4HK5REOFC+Pj2FX5PHgoQGJazghTAFhcUli5Y0F8P7ojcsFpKTIxZMqT
78YIKuj1EI5cMdcQYwfPw0hUXw/rkATZ2Wwm4osCVNpolZGhgDSjUTlWrURTJ9qunax08zxKvdSC
64aIwgiuFwkwizFrbyhjNgR/ct+YAgLHA+D7KGTHAKAoYBDpjz009AH7tOE9qcVRq43RKVUvFsul
3DCqshBaBetuy+VKuph8/+amE5L7FYQyeieqFjT9DYbXlFG+wIRid3n8se5g0WiTF9hJQO5NhLiw
kDN0912sqhJ/ff9OaAHfP3qgdbhvf3EzdA1AuF5dTPF6uVBzd1ktHKw3yyUS8b1rMHDVaBCjEXLM
bF0P4XuJOJ4kva+bFy90FSnV0jjgRjQhvWly3yBHdrAk8iI3zfPAKdlZsgHSrXIbpyyyq+WBjLKn
FmNUfpr8b39Mpc6UFmgovWJklruSy76DMHIPwIqPYZ9OMdebJGYxmmLRnA0B1qVYaxP+EYHKdPU0
qFMkj6nycY2qpqacRRIplRUieD7FAQ5Z66SmPHz48Jokz2995CLgMWIeDCcCLEdnq3OMDn/CVH+T
1EjzBI9CdiA3oplHbljQm6BOUqy3U1gOpaPokO1jvpzjSTTBYHSuo3Rb6myjycNrx+7zb9N/BFl3
toRvkxfaYdvGs7MTvF7FigjoKJOMZZLjzXSOJyeTOwOsm4CAuu6UoG6dEn95/BCrJMF78sniFGHY
R6/viCkuX+sOFD5xScfqA5Ha77lE4SDJUaaFuMpwBMbzWCS30bc9nEUDPHt6/lnnQVQ/kwQXF+8w
XSxE5XOv3XX4e4T8s8kYL148P6AntEzl6lZ8FKNggNFocpAacnVleL6mkUHg/5yBcAIWR5z4Htn5
ZWRnOsCMoHhDUk5AdHBSxqzT6fSa9plxDTpe/w++ar/8kXE3XQAAAABJRU5ErkJggg==</Data>
</Thumbnail>
</Binary>
</metadata>
