Towns

20170427 18391500 FALSE DefineProjection "G:\GISdata\Basemap\Surrounding base\towns" PROJCS['NAD_1983_StatePlane_Maine_West_FIPS_1802_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',2952750.0],PARAMETER['False_Northing',0.0],PARAMETER['Central_Meridian',-70.16666666666667],PARAMETER['Scale_Factor',0.9999666666666667],PARAMETER['Latitude_Of_Origin',42.83333333333334],UNIT['Foot_US',0.3048006096012192]] "G:\GISdata\Basemap\Surrounding base\towns" CopyFeatures "G:\GISdata\Basemap\Surrounding base\towns\polygon" G:\GISdata\Basemap\Basemap.mdb\towns_polygon # 0 0 0 CopyFeatures S:\GISdata\Basemap\Basemap.mdb\towns_polygon S:\GISdata\Basemap\basemap2.mdb\dataset\towns_polygon # 0 0 0 CopyFeatures G:\GISdata\Basemap\MiscBasemapLayers.mdb\STPL\towns_polygon G:\GISdata\Basemap\HARN_misc.mdb\datasetsHARN\towns_polygon # 0 0 0 sde.PORTGIS.PortlandAbuttingTowns 002 Server=GISDEV; Service=sde:sqlserver:GISDEV\MSSQLSERVER_2014; Database=sde; User=PortGIS; Version=sde.DEFAULT ArcSDE Connection Projected GCS_North_American_1983_HARN Linear Unit: Foot_US (0.304801) NAD_1983_HARN_StatePlane_Maine_West_FIPS_1802_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/10.1'><WKT>PROJCS["NAD_1983_HARN_StatePlane_Maine_West_FIPS_1802_Feet",GEOGCS["GCS_North_American_1983_HARN",DATUM["D_North_American_1983_HARN",SPHEROID["GRS_1980",6378137.0,298.257222101]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Transverse_Mercator"],PARAMETER["False_Easting",2952750.0],PARAMETER["False_Northing",0.0],PARAMETER["Central_Meridian",-70.16666666666667],PARAMETER["Scale_Factor",0.9999666666666667],PARAMETER["Latitude_Of_Origin",42.83333333333334],UNIT["Foot_US",0.3048006096012192],AUTHORITY["EPSG",26856]]</WKT><XOrigin>-15495199.999885006</XOrigin><YOrigin>-48378499.99987229</YOrigin><XYScale>31249.999970896155</XYScale><ZOrigin>0</ZOrigin><ZScale>1</ZScale><MOrigin>0</MOrigin><MScale>1</MScale><XYTolerance>0.0002560000002384187</XYTolerance><ZTolerance>0.001</ZTolerance><MTolerance>0.001</MTolerance><HighPrecision>true</HighPrecision><WKID>26856</WKID><LatestWKID>26856</LatestWKID></ProjectedCoordinateSystem> 20140703 11430900 20140703 11430900 1.0 FGDC CSDGM Metadata Microsoft Windows XP Version 5.1 (Build 2600) Service Pack 2; ESRI ArcCatalog 9.3.1.1850 en REQUIRED: A brief narrative summary of the data set. REQUIRED: A summary of the intentions with which the data set was developed. REQUIRED: The name of an organization or individual that developed the data set. REQUIRED: The date when the data set is published or otherwise made available for release. Towns Towns vector digital data \\DPW\VOL4\GISdata\Basemap\HARN_misc.mdb REQUIRED: The basis on which the time period of content information is determined. REQUIRED: The year (and optionally month, or month and day) for which the data set corresponds to the ground. REQUIRED: The state of the data set. REQUIRED: The frequency with which changes and additions are made to the data set after the initial data set is completed. -70.392492 -69.962905 43.810551 43.542816 2893138.677720 3006537.262658 258670.251569 356181.474187 REQUIRED: Reference to a formally registered thesaurus or a similar authoritative source of theme keywords. REQUIRED: Common-use word or phrase used to describe the subject of the data set. REQUIRED: Restrictions and legal prerequisites for accessing the data set. REQUIRED: Restrictions and legal prerequisites for using the data set after access is granted. Personal GeoDatabase Feature Class Microsoft Windows 7 Version 6.1 (Build 7601) Service Pack 1; Esri ArcGIS 10.2.2.3552 Portland Abutting Towns 2893138.67772 3006537.262658 356181.474187 258670.251569 1 -70.392492 -69.962905 43.810551 43.542816 1 Abutting towns Portland Maine Westbrook Maine South Portland Maine Long Island Maine Chebeague Island Maine Falmouth Maine Portland and surrounding towns. Suitable for use in general cartography and mapping when a regional focus is needed. en FGDC Content Standards for Digital Geospatial Metadata FGDC-STD-001-1998 local time REQUIRED: The person responsible for the metadata information. REQUIRED: The organization responsible for the metadata information. REQUIRED: The mailing and/or physical address for the organization or individual. REQUIRED: The city of the address. REQUIRED: The state or province of the address. REQUIRED: The ZIP or other postal code of the address. REQUIRED: The telephone number by which individuals can speak to the organization or individual. 20090604 ISO 19115 Geographic Information - Metadata DIS_ESRI1.0 dataset Downloadable Data 002 file://\\DPW\VOL4\GISdata\Basemap\HARN_misc.mdb Local Area Network Personal GeoDatabase Feature Class SDE Feature Class Vector Simple FALSE 0 TRUE FALSE GCS_North_American_1983_HARN NAD_1983_HARN_StatePlane_Maine_West_FIPS_1802_Feet coordinate pair survey feet 0.000032 0.000032 D_North_American_1983_HARN Geodetic Reference System 80 6378137.000000 298.257222 Explicit elevation coordinate included with horizontal coordinates 0.000100 NAD_1983_HARN_StatePlane_Maine_West_FIPS_1802_Feet EPSG 8.2.6 0 sde.PORTGIS.PortlandAbuttingTowns Feature Class 0 OBJECTID OBJECTID OID 4 10 0 Internal feature number. ESRI Sequential unique whole numbers that are automatically generated. sde.PORTGIS.PortlandAbuttingTowns.AREA sde.PORTGIS.PortlandAbuttingTowns.AREA Double 8 38 8 Shape Shape Geometry 4 0 0 Feature geometry. ESRI Coordinates defining the features. PERIMETER PERIMETER Double 8 38 8 TOWNS_ TOWNS_ Integer 4 10 0 TOWNS_ID TOWNS_ID Integer 4 10 0 NAME NAME String 30 0 0 Shape.STArea() Shape.STArea() Double 0 0 0 Shape.STLength() Shape.STLength() Double 0 0 0 20140703 Dataset copied. \\DPW\VOL4\GISdata\Basemap\basemap.mdb 20060606 14284400 /9j/4AAQSkZJRgABAQEAAQABAAD/2wBDAAgGBgcGBQgHBwcJCQgKDBQNDAsLDBkSEw8UHRofHh0a HBwgJC4nICIsIxwcKDcpLDAxNDQ0Hyc5PTgyPC4zNDL/2wBDAQkJCQwLDBgNDRgyIRwhMjIyMjIy MjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjL/wAARCADIASwDASIA AhEBAxEB/8QAHwAAAQUBAQEBAQEAAAAAAAAAAAECAwQFBgcICQoL/8QAtRAAAgEDAwIEAwUFBAQA AAF9AQIDAAQRBRIhMUEGE1FhByJxFDKBkaEII0KxwRVS0fAkM2JyggkKFhcYGRolJicoKSo0NTY3 ODk6Q0RFRkdISUpTVFVWV1hZWmNkZWZnaGlqc3R1dnd4eXqDhIWGh4iJipKTlJWWl5iZmqKjpKWm p6ipqrKztLW2t7i5usLDxMXGx8jJytLT1NXW19jZ2uHi4+Tl5ufo6erx8vP09fb3+Pn6/8QAHwEA AwEBAQEBAQEBAQAAAAAAAAECAwQFBgcICQoL/8QAtREAAgECBAQDBAcFBAQAAQJ3AAECAxEEBSEx BhJBUQdhcRMiMoEIFEKRobHBCSMzUvAVYnLRChYkNOEl8RcYGRomJygpKjU2Nzg5OkNERUZHSElK U1RVVldYWVpjZGVmZ2hpanN0dXZ3eHl6goOEhYaHiImKkpOUlZaXmJmaoqOkpaanqKmqsrO0tba3 uLm6wsPExcbHyMnK0tPU1dbX2Nna4uPk5ebn6Onq8vP09fb3+Pn6/9oADAMBAAIRAxEAPwD3B2w4 XuaCKZGRKwl9sUsjc/SswG5IYk9xWdqjZliTPYsR+g/rWhG6yZAJyPWse8k8y9lPZcIPw/8Ar5ro w8H7RXOTF1EqLt1IFcxSB0ba46GtCG+EssSygI+7r2NZbDc+PSnHnH1rtq0Yz9TzaGJnS03R06Dk +1ObmsS0v3tztky8f6ithJo5Yg8bBl9q8+pTlDRnsUq0KqvECPTrSNkrjFGcGkbkYFZGowYJBPSp x0qtMzxR7lUFs9+g+tTQzxzoCjAnGSB2oSAeVB7Vn3ul2t4zeehO5QpIYjIzn1rSz1qNhu5oYGT/ AGHpxRI2gOxQQMMc4qCXRLDzfL8tssevmNgAkdefbpWu7rGpZuvYUkUOxcvgsxy1NeYPyIrPTLay YmBCMjBJJOec96s+YsPyNkc00xuj7o+noTSSQlhukk4A7VrGMer0MpSl0WpIsi5ZgcgVBJNE38Jf 8cVW9QDxQTwBiuiNFJ3OaVdtWHSSGRsngDoPSmUU4oygEggGtlZaGLu9RY08xwpOB3NOn8vcBGOB 39aipdpxntSa1vcafu2sIBk4FWAr2wDngnjFMt8eeu7pRPIZJCc8dqmV3Ll6FRtGPN1IycnJ70lF SQxea+3OB3q20ldkJOTsib/j2sZJiVDFerNtA/HtVaKSae23SgNtPysVw3+H4imaxNJM8VjbokoL AToTyFq0RHb26wxdE7E5rhTcp3O9pQp2BCHwxbaFHAqDqaACxwBVh4hGMdcDJrruos5EnNehLyIE J7DOPb/OKoXWowGRkIZUiA3vj5VJGcev6VfGXt1UHLEZzWXNYW07v5kCOWGGJHUVhCN5Nrc3nNKK T2JX8Q6bDASJy2zqFQ5P04qyurWFyzxRTh32k4APQdaoPptp5ao1rGAOR8tS2thbxqSkC71UgPjn nrUyoy3KjWjsUjrVi6DbOAjNxuB5+Xcf0NTQ6tpbIfNnZGDFcMhHQ49KT+zLSRwzWkeUztJXoMAf y4rSOk6dKTI1pEzMcklepq6kpxW5FOMJPYmYGImRPun7w/rUq4KZ65pVXgg85qGM+XvQn7p4+lcp 1Fac+RMzA4xzWSrGQbz1c7j+PNaeskLb+7jb+dZo4FelQs4qR42NfLLk+ZGv3260p6UjELID60rd K6DiFLYcDFSxyvC+6NsHuOxqBj86VIelTKKkrMqMnF3izWtr5LhtjfJJ6ev0q5nPTmubfIHHXtVr Trs2pKzFmRjnPXbXDVwzjrE9XD41S92pozc4K81RnsShMtt8rgZ2+v8An+pq5G6vgowZW5BFOY54 rl2O8qpehZI4ZhtlZckDoKsFxtznj1qK4torldrj8RTJgAqQJxngewoAWJBIxuH6fw59Kekscku3 cC3oOcVk317IWe3XCRp8ue5FTaPbBJDMQAxTp6Ct1QahzyOb6wnU9nH5mzjI5rPuXcyFTwB2p89w yuVU8VDGDLMA3OaulT5ffYqtRS9xEdFWZo1iQFQM+tVyc9gK3hPnV0c84cjsx6Mu5Qwwo5PvTby8 AGTwOwHeopZVijLN+A9TWczNIxdzyf0q40lKVzGriHTjbuXILoSNtddrdverLMWOfyFZJGav2sjS QBm5OSM1c4WdzOjWc1Zk4ODkUE5oZSpwetJWfmb+QqruYKO5q/My2lsz7Sdq5wo5NV7SMtKrYyoq lqYmvbz7G4aOMfMknQgj0OcH9K5cRK7sjsw8bLmY7T43a5e5uQHKjMcy9GB//VUjNuYn1pzSHaIw flH60kal5FUdSa0pU+RXZlWqc75UTWpCs5I5A4pZSREAfvOcmrWVQMxAHvVIyb5wzH5QaiL55c1j SS9nDluTv8kZcNggbarwOqPlqa7E+vqaZW0YaWZjOpeSa6Fi6YOVZTwR0p2RDEQBnOMmqtKzFupp ez0Uege01cuo+3eNYJOSSW7/AFqQXGM7eBnpVGZZGtpVQkSEEKVxkenWspv+EgwnkfZymwd1Jzjn JyOc5qZ2W6uXC8tnY7HoKhljLMJF4Yevf2qY01+VPOBXCdpj6tMJVgUDuWI9Mcf1qkM7Rmn3433j Mh2kAD/P6VWQXH3WZOO+OTXqYfSmkeHi3zVm77Ez/dJwDjpmmA7lBOM+1EZYFo35I5B9RT8AcVsj lasRsxGADinu4UZNJ/EKdgHrTAYAWO5vwFSCiloAfDPJbtujbHPKnoa17a9jugB92TqVP9PWsQ9K PQ5II6EVz1cPGeq3Ouhi5U9HqjoHODk8YqCD94zTH+LhfYVnJfO5EU5yndx1/GthVTyVKkFSO1cE oSg7SPXpVY1FeLOfvXE11KQfl+6Ku2tyWgwpwcYYe9UbmE29y8ecj7w/GowWRtyMVb+denGEZU1Y 8aVaVOtLmNWpoImLb+QB3qpbzrMBnhh94VofalWIAL+HtWNXmtaKOyjyN8zYoAlm+Y/KvJzUc8yo uyMhUxyao3F8FdhGNzHqAeBVJt8xzIxPt2H4UU6D0vsTWxcVdLcdNL58uR9xeF9/emEYpyrimt1r sjpojypycnzMSrlj/wAew/3j/OqdXbAE26gdSx/nU1djbC7suxKCGduijj602JPMkC0OwChF6Dqf U1JAuFZ8e1crbSbPRSTaiWLYsZWxgRrxTbsMcYycntTJJRHiKM4UdTVlpESJTntxmuZ3i1Kx1K0o uFzOdChw3Wpodsab2ByTxURzK7H8aV5S20AYC9K6XeSSOWLUW39xNdyA4QfjVWlJLHJOTSU4Q5FY VSfPK4UUUVZAUUUqkBgT2oASsmLRWiiSNbggKMcFxnn2atalFTKKluVGbjsab5CbvSmE5BHbHNO4 JwR0NRXDeVayyHsprzbXZ6T0MGQ75ZG9WP8AhSL6HqKQDAApTxg/hXsRVkkfOTlzScu5EB5chZh9 4/eqU0Mu5SKjWQhgjrg9j2NGwtx56ilppPzCmtcIhI5YjqFGcfWmK1yWimjcecgA0u31JpgLUcm7 A2nGDz9KdhfSmMnmLgHANAEa+fgnABNSpd3tuP3RGP7p6UwwNz+8NM8pv+eh6VMoKas0VCpKm+aL sNinup5i90y+YeoAxgVYJ9KhWD+8xPHHtS7mj+/yv970+tXCKirEVJupJye7JAWVgynDCpJLiWUY +4vcDqajByMiiqcU3cUakorlTADHAqXoKag4zTjUyYRXUaxwKZTm60gqlsTLViVcsD+4wOoYiqdW LFsPKn0aoqLQ3wztKxdp7OdqqOAKaMngDmgggkHrWGh3q6QqAEkk8Dn60skhkbJ7cAU3JAxQo3MB 6mlbW476WRZt0VYWkboeKrMQWJHSrMmRa/KMJu4qrUU9W5F1NEohRSsxY80lamQUVKsQaEsDlgen tUVJNMbi0FFFFMQU9UZhkUynpKUGAAfrSd7aDja+pfDbm96q6s+21VO7sPyq4V7isnVJd88af3Vy frXBRjeaR24mXLSkzOMic/MOOtLuU5G4ccGmNAnPHWk+zR5zzXrHgDxIBgEjNRyuDhRjcenPSlMQ AGM8DH1qKKBGUuclvftSY13HCEZyHG/uw71MqhFwKZHCqfMBzUtFgbbIYBgMQTgn7uelS5qMMBcs p7qCKkPAJoQS3E+82O1OPFMUcinnk1TRKY0k02ntwKZVR2IluL71G7HIRfvHv6Cld9vA5Y9BQi7R k8sepph5jRF5Y/dcD+6ehpyNvOMEN3Bp1DYZcEc9iKW2wJ33H7goxS5+XJqAlo+H5H96pAd2MdKV kVdiUZ5xn8Ka7YO1eWPSmvHsTcOXHOaq5KRLjmn2zbbtP9oFf6/0qMHIyO9AbY6P/dYVM1eJdJ2m jWVipyDg0+Nd75ZsAck0zI2gY/GkrmauemnZks8nmPx90dKYgUuN2ce1NpQSpyDg0lGyshuV5XY+ aQu5AyFHQVHQTk5NFNKysKTu7hRRRTEFFFFABR26UUUAFFFFAGphlBCkEehrn7l995K3+1j8q35X 2Qu3oCa5tTlc+vNc2FV5NmuYStBR7imkoozXeeSRyk4Cj+I4pQuAFHQU0DMx38kcr7VIO5pDfYAe x4NLSEZoB65oEIyBwOcEHIPpTGhwpxI+frUtIR2osO7IYi3mFGOSOQakY80xlzhlOGHFIJAo/eqR 7jkVfmRa+xJn1qNmP3V+9/KlZwELDkdqI1IXn7x5NUT5jYhwc/f6E1JTJB5bB+3RqfSQSCnqvc0o UCkZj0ovfYdrasaxzVYs6ufLwFzjB6E1NI21CR16ClRdqhaLdATtqQxtICCV5PU0sk5Xdlc1OTnj tUTf6wFvuDv70rWQ07sjilYRjKHvUvMkJzwSKfnPIop2Jvrc0oX8yFH/ALyg0+q1i2bfb/dJFWa5 j1E7q4UUUUDCiiigAooooAKKKKACiiigAooooAsanKVs2GMbvlrG/StDVZQzRxqc/wARrPrPCxtC /cjHzvUS7ELpN5uVYbabi4IAJHvVil5rqOEpv54aPkbv6VIBOGGcYBpx+a5H+ytS596SGwpp606g imIDgCmlxg4zR1GD1poGTimrWJd7hRTyM0yqTuS1YYYULbsYOc8HipV602nEY6HmhgmxXxjFQxnY xQ9uR9KmA7nrUUqk/MPvDke9JFEpfjpTCc0isGUEdDS1SSIbYjLuXHT3pEYnIP3h1p1MdTkMv3h+ vtQNdh9OOAuBTFYMMilo3FsR7CvMf/fJ6U5XDcdG7g06muu4ZHDDoaB3vuT283kyEN9xzyfQ1oVk K24EEYI6irdrPtIic8fwk/yrGceqOuhV+xIuUUUVmdQUUUUAFFFFABRRRQAUUUUAFFFFAFe/3fbX yCBwF+lV8VrXk9rLDtYNuxlSF5FY7rPHjfGUB6EjrWeHqprle5GMw8oydRapi9DTZHIAC/ebgZqN mTd/rQDjpmhmL7VCOQOScYrpbONRdx6xqh4HXqfWn4qIvJniLGB3NQSXM6bSYXxnkKuaLitrqy2r g8DtSk46VnpdHzmxE4DHvxVkTYYbkYY68U9yVcV45S7MGwMcDNJtmGOcewqwegpjOEGTyewoGV3a ZQc4HpSJ9p3MXCYPQVMiEtufk/yqQjinsLciVt3sR1FOHWo24mU+oINSgE8irIt2H0j9MUhJFNqU huRGP3cmP4W6exqSkZdykUiNuGD94cGqE9dR1FFFMkYw2HeOn8Qp4IIyKKj/ANW3+yf0pFbklFFF MkYynO5fvD9aUEOuf8inUxgVO9fxFIpF+2n3jY5+cdPcVZrJBzhlOD1BrQt5xMnPDDqKwnGx3Uav OrPcmoooqDcKKKKACiiigAooooAKKKKAL8cUcZGF5HRjyfzNPmhjuITHIgZT1BpRhuDwfeqIe4tJ T5qtIjdwxOPw7V5Z6u5VuNMe3BMI3xj+EDkf41T3DbnrW+l5DKrENt2nB3cGs24szcs00UbAnpjo fc12UsS1pM8/EYJS96nuURxyetLSMksb7JEKn0agoepP5V2ppq6PKlFxdmNIXdnblvakkDeU23kn qKkAx0HFHtTEU9kuMMGbsOcfyp8SMrE7OccGrNN3Ddt70BqRAzrjKgkjrTTLIh+YDk/Tv/8Aqqyq s7BEGWPAFbVtax26gAAsfvMepNYVq6p6bs6sNhXW12Ry8sr7oywC4bJq4rDb2xXQPbeYeeMVlXFi A52fu2/Q0UsQprUqvgnD4WUycmkpWR422yLg9j2NJXWmnsefKLTswqNwVIcduv0qSigSdgByMiio 1+R9h6Hlf8KkoBoKCMjBoopgRqdjbD0P3T/SpKRlDDBpqMc7G6jv60h7j6KKKZJGf3ZyPunr7VIr MjB0PzD9aKjH7s7T9w9Papa6FptO63NaKVZkDL+I9DT6zI5DC+4dD94etaSsHUMpyDWEo8rPQp1F NXFoooqTQKKKKACiiigAooooA1GKjAYgZ9aQY524YDqM1UawEsSpLK7FW3Bu9IsPkA28Tku53Ent XmHqjZbaG6uAfKwqZyQcZNMLvp4SMKWR35LH7o/zzWhHGEUKBjbSTW8c6bZF3AHNFwI3jinTbIgK noc1l3VlJb4Iy8Z7jqPrWuqhVC44HapGAEYbqBkYq6dWUHoY1sPGqrSOb6igVp3GnK+XgwrddvY/ 4VlyExEq4KuOoNejTqxqLTc8avh50nrsMdskqM9Ooq/aaYssayPJkMM4Wq1pbvO+wfVm9K3reBbe BUXOB61hiatvdizqwVBSvOa06Fe3sY7VmZSWc/xHrj0qcE5pzHnHrQgBOf0rgbbd2erGKirIl7Zr NnbdKfar0xZYyw61nE5OTXVh46tnLiZaKJHLGssZRu9ZpVkYo33h+tatV7qDzF3qPnXp7j0rthKz POrU+deZSopAcjIpa6DzxrruXHQ9jQjbl54I4Ip1Rv8AI28dOjf40DWuhJRRRTJCmuu4ccEdD6U6 ikMajbuDww6inUx1Ody/eH605WDDIoB9xaQgMCD0NLRQAxSVOxj9D61PBN5LYP3D19qiZQwwaarE 5VvvD9aTV1Zlwm4vmRsA5GRRVG1n2MInPB+6f6Vernas7HoxkpK6CiiikUFFFFABRRRQBoyOI4yx 59B6mmRoUyX++3JP9Kan76TzT9xfuD196nwcZ715Z6pnjW7dbqS3kWRHjbb8w+8MZz9OvJqu/ibT 3WNo2keN22lxGcL16/8AfJrSOn2hyzW0JZjuYlAST60z7BZbFQWUO1TuVSgwD64oGUV8Qaey5WSR hjORE3T16U5vEOnIMmViozgBCT71c+xWzBkFtCFPUbBzUNzo+n3GEe2TnBO0bc46ZxQDJNP1CDUI ZJItyhGwVcYxz/Kqk0B1ecMrFEi4DgZB55weh/X8K1I4EhBEaqgPUKoFKqhN21QCTk4HU+tNOzui Wk1ZiW1sltF5ac9yT1Jp2cA85FGwY5HPrTfuDg5HoaHqwSsrIQ84NKAUPHWpcDbmkLcc/SpGQ3GW hOMDjvVCtPAZSGGRVOaJEGVz16V1UJpe6c2Ipt+8iCiiius4yhdQ+W/mKPkY8+xqGtRlDqVYZB61 myRmKQofwPqK1py6M48RT+2htHWiitjkI0+RvLPT+H6VJTXXcOPvDkGhG3Ln86RT11HUUUUyQpjA od46dxT6KQ0wBBGR0oqP/VnP8B/SpEVpDiNdx9ew/GldLcpRbdkFKsElxgoNoH8Z/p61ais1XDSn e3p2FWqylUvsdVPD21kQw20cXP3n/vGpqKKzOlK2iCiiigYUUUUAFFFFAGgqDGF6D1PApxIi7fjQ cn5Rwv8AOo5Q24cjArzEeo9FoWaY3oOv9KEOR7jrQp+dyOnSgLjDnOD+ZpUADUx3VzgZL+3aqWqL qKpD9g27ud+4+3FNpoE7s02OPc+1N2t97ofSuYfU9atpHRoQdqbi23OPm/w7VYW48QNFvWFMlchW HOST/TH50hm8WJHSl8vnLdfSsK+bXI7sSWqIYhEPlcjG+nG4192ZWgRVxwy4Jzj60W0EbYOCRQRn rVXThdm1AvceaOMjuMCpWmKPgjA9akbJSQrEVUnVjz2qdWEhJU5xUjKAh3elaQbhK9iJpTja5mUU p6nFJXonmhUVxD50eB94cg1LRQJq+hlDPQjBHBFFWbuHH75R0+8P61WrojK6POq0+SXkFRt8j7v4 T1qSkIBGD0qjNMWimISDsPUdPcU4kD/Ci4W1sLQMltqgs3oKmjtJJOX+RfTuauRxJEuEUCs5VOx0 08O3rIqx2RbmY8f3R/WriqqKFUAAdhS0Vk23udcYqKsgooopFBRRRQAUUUUAFFFFABRRRQBpBgTt PDY6UjAnHpRRXlHqgMg9SDUZZ4ph84IY5xiiitaWrszOrorokth+73ccmnMwyecnpgc0UUS+JhF2 ihQgAAzx3qKa4WIELgtRRTpRUpWYq03GN0U2ldzliT7VeW4iKjLgGiiuqdOMkkclOpKLbH+dHtJD Age9UJ5jK3HCjpRRUUqcU7l1qkmkhsUpifcPyp0lw8g2ngUUVs4Rbu0YqckrJ6EVFFFUSFFFFAB1 rNmi8mTA+433fb2ooqoOzMq0U4O4ykJAGScCiiug85aseltJOVYDYoP3j1/Kr0VvHDyoy3949aKK 5nJvc9KFOMFoS0UUUjQKKKKACiiigAooooAKKKKACiiigAooooA//9k=