20240704 09273600 1.0 FALSE UpperDublinParcels 002 Projected GCS_North_American_1983 Linear Unit: Foot_US (0.304801) NAD_1983_StatePlane_Pennsylvania_South_FIPS_3702_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/3.1.0'><WKT>PROJCS[&quot;NAD_1983_StatePlane_Pennsylvania_South_FIPS_3702_Feet&quot;,GEOGCS[&quot;GCS_North_American_1983&quot;,DATUM[&quot;D_North_American_1983&quot;,SPHEROID[&quot;GRS_1980&quot;,6378137.0,298.257222101]],PRIMEM[&quot;Greenwich&quot;,0.0],UNIT[&quot;Degree&quot;,0.0174532925199433]],PROJECTION[&quot;Lambert_Conformal_Conic&quot;],PARAMETER[&quot;False_Easting&quot;,1968500.0],PARAMETER[&quot;False_Northing&quot;,0.0],PARAMETER[&quot;Central_Meridian&quot;,-77.75],PARAMETER[&quot;Standard_Parallel_1&quot;,39.93333333333333],PARAMETER[&quot;Standard_Parallel_2&quot;,40.96666666666667],PARAMETER[&quot;Latitude_Of_Origin&quot;,39.33333333333334],UNIT[&quot;Foot_US&quot;,0.3048006096012192],AUTHORITY[&quot;EPSG&quot;,2272]]</WKT><XOrigin>-119214200</XOrigin><YOrigin>-96198500</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>102729</WKID><LatestWKID>2272</LatestWKID></ProjectedCoordinateSystem> 20240704 09273700 20240704 09273700 Esri ArcGIS 13.1.0.41833 UpperDublinParcels File Geodatabase Feature Class dataset EPSG 6.12(9.0.0) 0 Simple FALSE 0 TRUE FALSE UpperDublinParcels Feature Class 0 OBJECTID_12 OBJECTID_12 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. OBJECTID_1 OBJECTID_1 Integer 4 0 0 OBJECTID OBJECTID Integer 4 0 0 TAXPIN TAXPIN String 12 0 0 ALTERNATEI ALTERNATEI String 11 0 0 PARCELTYPE PARCELTYPE String 12 0 0 Shape_Leng Shape_Leng Double 8 0 0 LOCATION_C LOCATION_C String 1 0 0 CLASS CLASS String 1 0 0 NBHD NBHD String 8 0 0 LIV_UNITS LIV_UNITS String 3 0 0 UTIL1 UTIL1 String 1 0 0 UTIL2 UTIL2 String 1 0 0 UTIL3 UTIL3 String 1 0 0 TRAFFIC TRAFFIC String 1 0 0 ROADS1 ROADS1 String 1 0 0 ROADS2 ROADS2 String 1 0 0 BLOCK BLOCK String 4 0 0 UNIT UNIT String 3 0 0 ALT_ID ALT_ID String 12 0 0 PROP_INFO_ PROP_INFO_ String 10 0 0 TOTAL_APPR TOTAL_APPR Integer 4 0 0 TOTAL_ASSE TOTAL_ASSE Integer 4 0 0 RESTRICTIO RESTRICTIO String 3 0 0 FARMLAND FARMLAND String 8 0 0 OBYVAL OBYVAL Integer 4 0 0 LAND_USE LAND_USE String 4 0 0 ASMT_CHGDA ASMT_CHGDA String 10 0 0 OWN1 OWN1 String 40 0 0 OWN2 OWN2 String 40 0 0 CAREOF CAREOF String 56 0 0 ADDR1 ADDR1 String 58 0 0 ADDR2 ADDR2 String 46 0 0 ADDR3 ADDR3 String 57 0 0 ZIP1_ZIP2 ZIP1_ZIP2 String 10 0 0 OWN_INFO_C OWN_INFO_C String 10 0 0 MUNI_CODE MUNI_CODE String 2 0 0 SCH_DIST SCH_DIST String 3 0 0 SUBDIVISIO SUBDIVISIO String 40 0 0 LOT_NO LOT_NO String 8 0 0 FRONTFT FRONTFT SmallInteger 2 0 0 LEGAL1 LEGAL1 String 60 0 0 LEGAL2 LEGAL2 String 60 0 0 LEGAL3 LEGAL3 String 60 0 0 LOC_NO LOC_NO Integer 4 0 0 LOC_ADD LOC_ADD String 6 0 0 LOC_DIR LOC_DIR String 1 0 0 LOC_STR LOC_STR String 25 0 0 LOC_SUF LOC_SUF String 8 0 0 LOC_SUF2 LOC_SUF2 String 5 0 0 LOC_UNITDE LOC_UNITDE String 10 0 0 LOC_UNITNO LOC_UNITNO String 10 0 0 LOCATION1 LOCATION1 String 30 0 0 LOCATION2 LOCATION2 String 20 0 0 LOC_ZIP1_Z LOC_ZIP1_Z String 5 0 0 LEGAL_CHGD LEGAL_CHGD String 10 0 0 EST_CO_TAX EST_CO_TAX Integer 4 0 0 EST_MUNI_T EST_MUNI_T Integer 4 0 0 EST_SCH_TA EST_SCH_TA Integer 4 0 0 DEED_BOOK DEED_BOOK String 8 0 0 DEED_PAGE DEED_PAGE String 7 0 0 SALE_DATE SALE_DATE String 10 0 0 CONSIDERAT CONSIDERAT Integer 4 0 0 STATE_TAX_ STATE_TAX_ String 9 0 0 STEB STEB String 2 0 0 LAND_SF LAND_SF Integer 4 0 0 LAND_ACRES LAND_ACRES Double 8 0 0 LAND_CHGDA LAND_CHGDA String 10 0 0 POOL POOL String 3 0 0 OBY_CHGDAT OBY_CHGDAT String 10 0 0 CONDITION CONDITION String 1 0 0 DEGREE_REM DEGREE_REM String 1 0 0 YR_REM YR_REM String 4 0 0 SFLA SFLA Integer 4 0 0 FINBSMT_SF FINBSMT_SF SmallInteger 2 0 0 STORIES STORIES String 3 0 0 EXTWALL EXTWALL String 1 0 0 BASEMENT BASEMENT String 1 0 0 FUEL FUEL String 1 0 0 HEAT HEAT String 1 0 0 YEAR_BUILT YEAR_BUILT SmallInteger 2 0 0 STYLE STYLE String 2 0 0 BEDROOMS BEDROOMS String 2 0 0 BATHS BATHS String 2 0 0 HALF_BATHS HALF_BATHS String 2 0 0 RM_TOT RM_TOT String 2 0 0 PREFAB_FRP PREFAB_FRP String 1 0 0 FRPL_OPEN FRPL_OPEN String 2 0 0 FRPL_STACK FRPL_STACK String 1 0 0 BSMT_CAR BSMT_CAR String 1 0 0 DWEL_CHGDA DWEL_CHGDA String 10 0 0 COMM_AREA COMM_AREA Integer 4 0 0 COMM_NLA COMM_NLA Integer 4 0 0 STRUCTURE STRUCTURE String 3 0 0 USE_TYPE USE_TYPE String 3 0 0 COMM_BSMT COMM_BSMT String 3 0 0 COMM_HEAT COMM_HEAT String 1 0 0 COMM_AIR COMM_AIR String 1 0 0 COMM_YR_BL COMM_YR_BL SmallInteger 2 0 0 COMM_UNITS COMM_UNITS SmallInteger 2 0 0 COMM_IDENT COMM_IDENT String 2 0 0 PARK_COV PARK_COV String 3 0 0 PARK_UNCOV PARK_UNCOV String 4 0 0 PARTITION PARTITION String 1 0 0 RESIDUAL RESIDUAL String 3 0 0 ELEV ELEV String 3 0 0 COMM_CHGDA COMM_CHGDA String 10 0 0 ASSESSMENT ASSESSMENT Integer 4 0 0 PROP_INFO1 PROP_INFO1 Date 8 0 0 ASSMT_CHGD ASSMT_CHGD Date 8 0 0 OWN_INFO_1 OWN_INFO_1 Date 8 0 0 LEGAL_CH_1 LEGAL_CH_1 Date 8 0 0 SALE_DATE_ SALE_DATE_ Date 8 0 0 LAND_CHDAT LAND_CHDAT Date 8 0 0 OBY_CHGD_1 OBY_CHGD_1 String 1 0 0 DWEL_CHG_1 DWEL_CHG_1 Date 8 0 0 COMM_CHG_1 COMM_CHG_1 Date 8 0 0 PARCEL PARCEL String 12 0 0 LANDSF LANDSF String 1 0 0 EST_MCCC_T EST_MCCC_T Integer 4 0 0 Muni_Name Muni_Name String 26 0 0 Shape__Are Shape__Are Double 8 0 0 Shape__Len Shape__Len 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. 20240704 /9j/4AAQSkZJRgABAQEAAQABAAD/2wBDAAgGBgcGBQgHBwcJCQgKDBQNDAsLDBkSEw8UHRofHh0a HBwgJC4nICIsIxwcKDcpLDAxNDQ0Hyc5PTgyPC4zNDL/2wBDAQkJCQwLDBgNDRgyIRwhMjIyMjIy MjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjL/wAARCADIASwDASIA AhEBAxEB/8QAHwAAAQUBAQEBAQEAAAAAAAAAAAECAwQFBgcICQoL/8QAtRAAAgEDAwIEAwUFBAQA AAF9AQIDAAQRBRIhMUEGE1FhByJxFDKBkaEII0KxwRVS0fAkM2JyggkKFhcYGRolJicoKSo0NTY3 ODk6Q0RFRkdISUpTVFVWV1hZWmNkZWZnaGlqc3R1dnd4eXqDhIWGh4iJipKTlJWWl5iZmqKjpKWm p6ipqrKztLW2t7i5usLDxMXGx8jJytLT1NXW19jZ2uHi4+Tl5ufo6erx8vP09fb3+Pn6/8QAHwEA AwEBAQEBAQEBAQAAAAAAAAECAwQFBgcICQoL/8QAtREAAgECBAQDBAcFBAQAAQJ3AAECAxEEBSEx BhJBUQdhcRMiMoEIFEKRobHBCSMzUvAVYnLRChYkNOEl8RcYGRomJygpKjU2Nzg5OkNERUZHSElK U1RVVldYWVpjZGVmZ2hpanN0dXZ3eHl6goOEhYaHiImKkpOUlZaXmJmaoqOkpaanqKmqsrO0tba3 uLm6wsPExcbHyMnK0tPU1dbX2Nna4uPk5ebn6Onq8vP09fb3+Pn6/9oADAMBAAIRAxEAPwDjoFnj jULCzoeqkVO9jKITcWyv5YOXGOVqJoJo5CfP+ROd6txT4dUnsVE1ud6E4kBP51zbmafRlK4mms50 eOPAYA4I4NSSXpupfO8hI5NwOVzxnrmtOW4m8sTwvhD97Haq8d2+/cJNysMsGHeldITfQmVmikik bYzPzle4onYvaKASC7Yz6U1tRdmVRHCygcBk6VoTwtI1v5dtFjGcAd6HrqF2zOkVWi2RPsK/KT1y fWoUdUQrIfMxzkjpW1d2ttBYmZo0ZyeVU8VREtrJAXEBOOAN3X9KLjcbFS4m/ew74l29iKiMdx5z EMTGrZ6fyqzePBIqhYnIUAjD4P8AKoVMDygFWVjwDvzj9KYMSWQpIZVHG3nIqurH7JKGAOWBBqwz Wpdt7SkgY4FT262syssc0owM/NEOn50uoXK1mjGVF3YTOTSTRq90YY28wk4BqWFI47tf3zMqAnBT r39addwQXshkF2Ys/wAOzH9aLXJcU9zM1TyonitYcmZD8757+lW0tJpmQbixC4Pfmnadp1qJ/Mmn RsA7QfWpl0+YXDFJI2BP8DdPzxT8h76leSGSNmXyyoHcjg0ioXzGX+Y9iKsrYXyqcREFs85H+NLH YXKTIHiIOQcgikN9innY7QOm2VfWlcMoB25HPFDWtwbt5DE3JwcmrDW8rtzGx9h3psroVGQFdwYb vTH6VJI6m3Klfn7n0qwlpPk4gYcVDJaT7m3RN7cdaGCbSHoztb7o0XI6t/8ArqC5ErzxkuVAHC4x mp0sLufbH5LKB321oQaRcrewNkyuD8q4wPzoJSuNtGb7k8bHtuK1r/Zg8Wx1eO1yNp/iz60s73Fu hfySrY+ZvvVBbyfaLSOKQOGdsAnjHHWn0sXaxUvTbWaHymLqeMMQT+lUkj5Rgm2Ruf8AdHvV9NBa S6G2cMASSx6fSnwQxXN0IEG0A5lYHjA7UhGhpdixHmOxDXJyz/3Yxz/IZrB1e4+3atI6yMIkG1Ce pUVu+IJYrXTY5YpsSSAqEU9B05rlo7SRjuMiZIGBmmN6aFqykk+1eUzMyvnCM3FTRkSX0QiX5EbD EDIPNU1CnUYhn5QhHFTpFLE5eMfuFXaWJxzioktSr6XM+6jDX8jZVhuPQ0qgu+Qq8AD0pRayIDIy hk3H5u9RqoMgKMBzmmkRbqPmQ/NgBiPfpTlfDriTjrg9KYF+Y4O4g0+H9623BKKTjinexSV9C4ls WSVN8eZVAX5qng0+SOBU3x8f7QqlJAgXzDtUqPXrUgfaoCMm3HHzULUTjbczkikUkHaExyc96bEx yI44yy7jnPAxUFuGBm3MSvXJ9K0IjElszJMCeCTjB+lMxHWjkOwDBoGG1k9DUjWTMwjjYtxkY9KZ ZnhmKqcjt61atbjbIVY4bqKT1LgrkBiVEyCdw4IIretJQ8CAKNypy5OCPzrJnumQSKsDM7fdPpT5 LsQ2aLIh8106A4walSFdJkmoxwWts0KymSR+yjgc+tV4lkit12n7w5G3NJY2styItzN+9bapzWze aC9m/M+6JE3M/v6Uc3VjScveM5Wa1gDyxK67BxjkVmSeQCruGy2WBXtzUl75rKrbvl2jjNMiLGNF eHevqR/KqE30Jt8Dp5sak7OcHHP1qpbzMsrkrncMYAHFEqiGfy1BIbtUqwKzsBIwIHOFo1C9yCIO ZpGZTHH03AjJqcRRSqQJyWxjDDGfamtGJJFjQ8KPm9TQ7jJyvXgBR0oLSTHQx3MCMotsgfdYDPao 3Zo4y7RNuf2zirEUrkEb2ACkAGqqzypHtIL+ozQJoWKWR7ZUPb1HNPjZhcISxGSPrSSsXiUKCpB7 0mG+0KMdwfejqJ3HyO63rAbjkfd981qabqtnbW1x5sc73LrtRg3yr+FYskhe/wChXPXI5pVtZFky zqnseM0yuZ2sbytc3JWdLidQMZCucD2NdZGmmSWaC7W4WbbyTvFYvgqCW6lntUTe/wDrQeu7aM4/ HFdTOkt7FdXeoSrG0S/ubYYDAj1o5Skzk7xpbW48mC4eSPrnceB6Usl4TCFUyq+RzvJ47mondg7D YG3ckNWnDG9nZKZYI5LaQYEoOcZPTd9aaVkK5QtrttQBhgMqOOd0jEgj6VWubq5iSNGlXdvIzgVZ MMto+6FNrPyXA4x6VNYQ/azOqxxyTQL8u7uT1qXq7B0KNpLcTCaQyBRH0IUc1btQCkkUca/aHAaT CjGO1VYxNEZHeMRJHnei9Cfaq/2m7sLWV5GRXuPmVV+8f/rU3ZDSFNrAkjGeWNgDgrtB+uKytRuo Y52Wx/1fGN64P6VJp5FxcMZuqqcLnqcU4xfOp+zxgMcDdkk0kyWVxeqjCVYUJ6AgYwKDqTSRTK0K spcEZYjNRzOjTERIVQnPJzg02NR5wBIYDk5NLqU9tSzJLBGgVYyFcbiMnioGMUq8RbH7HpxS3cgi n+4CmBjac1XWcyN80TccCmSWSr+ZgqRkAZxip/KMURYt+XWiUSMbXd93Z0/E1cs9Ge+U3L3KwQcj c3t2qWaJq1ykFgMqs8j4bqoqtObUTNlpRz2U1dS3mM8nmEMkYO1x0PYH9aiFsgGGmUHvVXRm3fYo hGFuykqXxgnsaW2t5JrWYEAheOvGaIp4lgddpDnueaepY2YjQcltxGKNjMkt1k8tYUC7yeQOea6i bRVstLWWXK3BwG/E1S8NwQWF1HfXUbyICVChcjdW74h1GC9SGO2YsDy2Vxj2ouVFHNrhJg6HJQ4y e9SzW8V9Isz5UA4OOaznElvcln+6DyM9K6nwtBZ3GoeVekeUAGAyRuPpmhaha+5lRNBaOvl7yIjl Bjqc1Jea680ILxqm3ODnmuxn8Gm4vp3AECFsoAMgLjrWBrXhltNsPMM8UisxAfApuBV2lZGK9/YP pRguFYSMq7WHp71i3Eixf8esjFQOvvVy4O7CsiEKgGRgVVnkW3RB5asT1HNKxLd9xrSxNs87d5gX lqmQQu3WTzNvB7Ypjzjckht0BIxnmooryKOQsVK5XGTxTEhIsBZV5U9OOeKdFBKUjeKTJft6VNHN b+W5VWbvxxml09ozb5xtzyFZjmk9hpjXmaFJIHjDOQMP6VXjhZlLuwRc8E96tXsqiNTHbncXHzbs 49qiu5Fdo45GCpxuxQh3IGhlGBk49RSRyEMJMAhODmrsYt4gJRKxif5QpOTUDRRRs/BAJ6GmxjWn gd0cRncOgz/WmSXTAq4i3kHOM1BHGxnKoC3pUmNrkMMFeMUXGtUbOl31xArSwsYmPp2rqW8Us2lf Z5bdhMcBnBzketcpp6FoQWGMGrkkw2O4Ull4A6jNFrj2H32sCeO5BOyNQBCuORWVDrE5Ma3GZY0I IXPbrVtLmGVDFdQKw9RTZ9EjKCSCbb32ucfrTaaJeux0v9u217p7SQRsJkH3SKoWs1zayBLi2aB5 BnzYjt3fWq9jo1/KRb2rrGVw0jlhjPp71cv5biyZ0vbgSrAoCkADLGo8i7vdle6vFkuooQG2J87g c/nWVM/9pX7yOAsYGAcdBUElzJGk0u4jz+tOimUusW1UXGT0GT601YTlpYVhBbyG5jG3YensP8aS fU5IZQRFvDYdS3YVRMpMjP8AfOcBc8Af1/Gr0W65ttrDMi9R6LQSZoBVRIxOWPIHarkmwRKI+S4H Q0rwW8hBhcLKpywPT86kW1/ebhNHgc4yOvelqBLM1qkSKxOcAnaoqsscEwO2Yxc/xj/CrU9sGljX Kngcg1UEllI77t0ZHy4J9PpQFyXglVVywj4yelW4FnnkgiyWtky5QepqpciBYUaCXdwN3PXmra3r afBHbxN5srjO1cHGfcUhtqxFfzKbpltIykYXa+eKh3Rf/rNRTRPIyqzkPK/zBRzSXOmwxXDoZGyM fx47UWbM7Nlbe6EiI7UYYzirkM85j3s4EQAByvpVKOQuR+6ZyuDj0rVgsTcR77htq9kHb8KtjSGw XN06yzJJtjXkA0kGpTyow2xkr096S/kWARwRrgAc8VDCwEyIw27zxnoBUruOWmiLT38jSDzIoG3D 0OePxrUs7k3Xl7I1RwNpx3rJkDQtvVYmAPULnNaGk6idPv47kRgsV3bD0poSep1aC6MLA3h8xcjg nntXOaxKqW6Q3MjuAf8AVFsEe9T3fjqO8uHY2AiZjhthwCayNYkWXVbeW4HysgLDJxSb7ClJNaEL 7JPkQhYwAeewqCeVjyvzgLxg9Kdd2sjT4hjGxh13DipXtpUxgjCrwA4xmmu4FE+e7q5j+bGDmnzf Z5fMglRl7ZWnML3zlyWCcY2mo7iI3c7Ri4ZTj86YDv3cEGYyNoGB65qKK3mu0DKp3DOW6Zpq2agi Npf3acEelSiyJT93JuC+nYUC1J47WS3hYyIykDjJzUEckH2o/aUZlAwcGpLS2unaYly2BjqM9aaI 47Qu7xgDPAYck0uoxTtnuU2RhYY+gPNQuN7yuWzjJq3bSy3YkTykUlSU2qKooVtyQ3O3qtDDYmtp prZlaMckZG4dqafOuJHl2IrjnAXrUlxqSRxKY7cycdPSq6ytNtZR5RP8IHIpI0TSNayZzbk984wK uwqFUoUIPc+9UbCRYiNx4Bz1rThnjZifPAYnnB5rRK6ApXESh/NCv5Y6nHBqSG7+027LIMAenfFW 7t4nXYzMUHccVBZQRO4EbYyCxDdcCnJ2QJNnSWSf2fpqzzHaW52+prjNb1A3d6UzuVTlyO7d60NV 1SVbTDyBlTiMD1rl0jeQY3AMeSSetZRXVmkn0RtNbk6ct3MoEZb5cnqBVBRHNcNJI/kgDGSM5+lO Nw39mGN5d6qflBOcVGoiezjNzKE47Z5pmTeoifZVm2puYN1YdfyqWCQ2d9yrMp4JJ6g023toVUvG zTMo+VegbirMUjXsSq6+XLH6UgIbvTvs0ok3ny3bOfUVLHawS3Cpbu5dzzkYHPalS6a9jNrcsWcf 6vjv/hWr4Ztbi/mlhjZluYiAsYjG3HfNAuuhS1CQWcgt/JHnp0welVLfybiYq8BDludvatHU90et SbnUumdx7ZqmksdlCJGUefMePUUA3qU9QVPMWOGNo1U4JJ6nNFqyo7PudZRjaw7VBIzyzbFyzM3B rSML+X5RBEicE4+9RuTco3MmycSROxkJyTVyC2hnhWWZgZG+8Wkwf5Vp3Hh54tNt7/zleNshwBgg 4Jxz16dqzVB2jaoI7cU1caNbRtJjwtxM4CA/cU5J+tdBDo73EbXFoItmcEZ3MOccL15rASaWFWjf hgcqAeKv6Tr0WhPPdxph5UKHnkN1BFUkt2aJ2VkZGs6VPpmoql+u1ZBuB6jFVPJaSTzUeGaPG0A8 Gm3uoz6ndPcXUmWb7idABWdFctBA0W1cls5zyKRjJq+pos8ccTwNbsk5PysDxz0qS3VIkHmNvkGR weBSLeL5dukEaOwAJLjJzmo3M245twFz95BikO1tS99nsjLETCuSwLEk1oatp6zwSTK6CHcoUAZP QdDWSoc26TbT8pxV2GWFQqmVm4yV9T6UuW5VlZpmHfgiYBWJ2nnB6UkULNMWEoGRwCetS3RaS7kx iNWbnjjiq7BkeOSMqR2I/rTRBYWQrOcSLtyARmq5bbqGAgwucn0piKsk3yrhwcnnINTWpUX8jspK gHinoBUjlSS5dGfhjxirNs7KtwEOeO9JFeW8DG4W0bIJyS3X9KeLyBoWMcZV5eqls0DEsw3kXTiQ g44I+oqSFmuoh9ojZ41/5bYximwPILa4jVsAD7n4iq5SYxNiQKqH7ueeaVwRZTzrWImGTfByQVAy P60JKt2kiSQYcjO8jBqtbNPAx2sQF5I7VJJes6sEjVd3BI6mgq1ivuOwgY4NTyQyMYp7dHkLDDBR nn3qtGc/KOTVhLRlTb5hQjsRxSJZt6a0cSPFLCCcZJI5rCnR0lZgGUZrW0i+OnmUSKG81CM+lSSX VjLZSmWX96eAE5/Gm2Ve6Mu1uZd/ll8qeNp5rZ1HRriCa1mLeVHOgKgNyqjqf503RtE+0yCUsCjf dJ4IHqaqa9fGEm1SdpMcbj/CvYCmtdwW2pn3lzHNcBRxDGML7+9V3YlS6qcduKcyLtVVT5upzTp2 TysqCChwfQ+9BUn0GoJGtSQi8mnPFi2jDMBg4we9M3lImQE7sbs4/lU73EThMpkrzyf5UE9C1D5F t5RwTIMHj+VPvOJorlcRI3XjGD701BA0Zu9pVU756ntTJbu4v9qjJj6EAVLH0JJZogiXEIwS2M4r r/C2qpFHK+1YJyDmTGMjpXGBorWZYwS+f4K2IrKSFormWQBs8RD+6fWi9gW9xdUsXnubi4+zMwJL eYDwR61gTSNOxlI46KB/CK63UNVg/sueKBt0jZTC/wAIwP8A69cksYeMDcFx+tDfQmfkO09VS9WW X7oGcDmtGe5yNkETFt2Sx6is2AN5DzKcMjY3e1TxXDtCWkfhuB6mmJJF271G481I3ctGqnanXBIq BBOVBUBV7A1SdZDIV3DchypPcd6nF6yjDE5HoKLhc2pzHFHBNKVIdclo+QPUGsK61D7TI0qqBCjY RCOv+0ahha8uUhSaVVQMehHI9ajSSKGV1WQOoONo5BNUK/Qlhsy85naVfLYcEmpgLSEkvEWfryeK gnZgy7ihUHGAcbTTA3lk7h8p7n09qkLGlB5k9vI0SCIqDjC/e/GkW9uTIsYkINUoLqUzxwRuYyOQ fate0BmyJdruATvC0FI0bF3nt5YnKlgNwwO4rEkvZ95X90w3beUHFa9lG8M5mBG0H7uOeararpgh u/tEQxDMQcjsaBu5SlJeZwVHLHIxgUku0W5UpGVHGKWdhHK4dick4AqnG7NJIm0knsetIQBws4Ih XYBnIo88JmUW4B9c8U2Bm81kK9OmO1TXCqYTtbOexHShPUQNcwGJY3t0aNuRzyDSxmEENDZ7s8ED Jpq2L2uyVhuHBIrZt71YrGaJ4dkcn+rfb1PcZqkikiCwsYrlLgvbPGSu5SSeeaifw/5EP2iV1Vyc qhY4P1rdu2tysBtJid4CsAcha2bXwvPdWAlKbyw4bd2oSKsefrAfmUhMP1FKbE28gZwvzg7cDjp6 V6Dc+Fo7KwNy8Yznoe1cFq9w0qxOuAqnAC9qbS6C5SlGIs7iCpB5461cCxXPyhm3dueKoQLJNIkW NzMwxn1rVm0i60y5ZZtokiI3YOQPxrNpkS3IdRtprcxs8RhDJhcDGR+FQadZ/aLhEJAUnGW6V0ur T2+paNb5VkeLlpM5DD0rNje3htjME2RAYOep9qqxVrsuarqKaTYLbxsrSAYyv8R9fpXGqJLiYu5z zuJ9asXMxvJSzHJJ4HpTUOzESDcc4NO5T7ixKwDSlgGPAzUmUayZRy4PJJ4pslrIY0BYRgZJB64q MFYSIxjDdSeKRnd9STcERSQCcYIqVLYyEMF+Udagyhy+0kFuVrRZIVt1a2lZmbrHnlaC76DH0+YW nlrbuImbcXJ+8M1Zhi8yHyoZFjCfNITxtFXrq9next0LKsiptWPb68ZPvWdDK+mxsJLbzpTkO3cj 0IqW9RcyT1Lejiyvbx3it5XKDHnsP5eldC0H2hJZHj/cKmFYn5jxVLTruzlsB9gi8qMYEqjqtS6z qAgsI7C0DF3Gd5PQZpOWli4pJXZy8ihbp1h+V2baMd6tLp0siM5tyqkkKQMAioJRtYlSNw5z3HvS vdahOz+bcEZfzEKnAU/SkpWMFJdSEQmK2kWRJFTdgj3qsfLlto13eXtyRz1rYinkuI8T/IwbDjsR 61VubdHcqFwOgK9armRbelytKZFjibyyWXlge4phgu5T5kNwBG3IB7U6SKeNy8TswBww64FCvPj5 bfA+tUmA2dhGFihbzDFu+ZumPaqojT5ZhEQc42g9+tPlhKTLEGZtueoxz+NSrZmJ0up2dVXIKevb pVPYgdFEN298bc8A84NMmfckiqA2Tke30onuwoCQxYEjY+YcmmuXg2iAZyO+KTHclS0SVI5Gk/fK PlA71saTNb24DOXVzlSaxmf5AVxnse4NWImOwiQnOM46UmUnZm5JLZSyFRJKpzycdaki1CEu9rjM RAUA8nPrXOCSRwMFlJ6Y+tXoUP2uNf4gwy2etA1ItanpkU8hntJFdR96PoR/jWC8brKw8na2ep4r QGYbrzUznOeKnuNVgv1EdxCUlHVwMfnQhWTMh22ptGA471bsLWS63yjhR0JHU0ktovysh3oerDtW 0rx2Nl5pxwMKtNDSL+jJZCRoLxma4KYSND1Y9Oe1U9UtdSubcWokBtoPn2DkKT7/AIU/SrBS5v8A VxcW4lQtbuFO0nsKdDLPMsmxgsf3XAOM03cpIoQs9ssWcgZG4dhXf2Hi6yjsoLcQu7ovOeO/auYs YlurmKOONZXyQIgRycdKg1G2urjVreEWfkeSwEqo2O9MFodfqHiKC702ZEjKu/AB5Arjv7GNxASb ZdrHcMyY/pVzVVisrm3WMbS4JINU5NUmgtVkR0KsvBJqGmyrrqZV1aQacyGS2f5zgN5nAP5Vs+as 8kVlaQxtKrEvcE5Vl7cVhi7fVmjhuiqRq2QQxJNbojtrSBfLjVmx+72v9z3OD/OmidN0JrNhbWyx rHhpT/rmPoa4/U7hpSscYxAvCj3q7qeqtcz7EYlFbJbP32H9KqSKok3YBDjIXNAWKI/cqCx5boKs y7IrZdp/eSfpSxxKZjI6kxp681BcOkpYs/IPyrjpQS2mRFSJQcvt7mpBGJJNg3FM5Un+tI3ICgcj vVyyjRXO487ee1K4WGQwHzFSNw5J7jpW5bpGqkAhGIy2O9VY4UvAwg2W8o+XcTwalkjNoqr1LDBk Izk1lJu4neOvQfJcJLHJGgKyLgrnvWeG3u28uHHJI5qyYvOkhAHLDG73q1PbyWUiNLEFbGCcfeWp XmYu8tWV0WXyZvKmIO3kjgsKox3FxbsQJGUgfWrJjQh3UsFHCD0NVZIN1yki8BlPGe4ql2Gr7Muc vbu5PzFRnI69aaJItyxY8vI/zikxI0LRxp8yjOTTpYlkQkKVPYFSSfU5paBtoPAe1dWkTcueSDjP pzSTMxGVXOeWC84qwZY208K6sJMYz1BHvVWFoz86Sbs9s9abt0G2tkLlnk2xvzt+YHjGKUKmOeT6 7ac8KtlyPLJz9084p6rHtG12x9alMErK42d4pZnfh58cgdB7+9ZX252SaKNWkn3bQ7cCn3jiG7Lh iz8AY9aztQuFldYfmyFy8i8bmNdDVwJVREjM9yWLhsFemD7GnxMM4kyABkc/d9qgt0ldSkoRlUAK tIMmRopEOFJIUmmO5dj3uxYqQhBbPpT4Z8hi+MDjIqtG7XCNxgAYCZGRUu53Xbh1yR+FIZqQxwHD lG+Zc4DVLGyC+RcSHBBAyMfyqjGZGSNWYYX0NTr5Yuw3mHOR2pDuVsSGUEq3H8OacsHmhuV/E9KI 4WNyR9oVsgnBzipGt36Kyju2DxnFMCssxgchAxHt0NaEEYuxE0pYRq3zL6fSqtvbSRspdyQM4JIr W0NFImF2zhC2eBk9D/XFC1HFnQfa5Lm02jzJNNtCCok/l+NU7JL+OO4jIgSCVi5TGSPTBqK2S6ng OxyIIpMmMnnGeuKng1Qw3FxbjyjE2TvKfN07GmXsVbOxmtryE290hmlberKfuH3roF0/WVgl1mTy 3UfMz7xkkHrj8K5K387/AFiJ5e1u55q4+rXqxfZxLK8bjGwHimA/Utb+23ERuELSgFQWYDH6VmXU JezVVtJQpbkJ6Vfa1/s9ftEwBuG6Bv4B/jWVPqd4byHy5W3Fumajm1sJhNHveOO0tiJRgbz/AAim 6nd/ZoBZWzF5CP3snp7VvSRtNbO4wtywwnoTXKZVC2fmlzz9aL2KjG5XghAYFwSeirTsKp29X7sT xinAlCzsdrE8t1wKjYK5AAOP7+KA02Hq6Q28wl3MGHBB4BzUUVuk2w/KpA6GpCC0XzgGoMHK/wB0 jrRqKSsx0kJhDbmGc8UwF42XyiSTjcSOPpU0qlwqs3A7UsUMjxMVBBB+maCHuXbCWNTObhirY+XA 71YjkcwqjDepGce9U0hDxNkjdjdnFWDP5duPK/1m3GaxluYyk76gbxoA8ZUEkDGP4as2zS3KKZyW XO1dx6VShjDuAikuBlyeanScOSshZ0QYAzjFIIu248r5UxVivXIB71CwMiORH8uSOD0z706YCS3J 3bVX8zUcRkFiyrwHOGP407mjfvaE4dYwoZGwOMDqfrTDLhgHJGOM4qSFFtt8iyEEITyM1Xe6kax8 xv8AWS8E+24VbghuKLCJK6HGxm7Daen506O2GJSPKTZgBQO9TW2pyaXdW8cQjYMOQwzmorWKLUp7 gSsYxuzuBHXn1qUuociVmVpJGDqHyOuCKsxurRg7gc+1UZ7do52jZt8RGM5+6aoyRurkDGB0yabh 2Fyl4rCWaa5OxwBtCjk/SrGqf2Pe2kMUabbpQF3KNuOe+azpL9pwsQ2rKH3FmHy49BWhqNg7mL5l dmAO1D82CM9a2tcm5h6hAlpqKQWVwsxZeXXpSbUdXLhvNwMYP+eaXUktYrmNoNxJABHvzUP2iWOG RFw4JyaQxLWzdGaViyyM3yoOSfrWmweM4IbDDjPGKn0qV3spG27pU+7kYwKqncj+Uy7mHzZJyBRf UNbCsrIY05IyORWo0K20x3L8xjyD+FZqyo0iHLgggYx0rVCLJumeTcFUrz9KGUimgjbrlWA606OJ xHIybnXzMHvxTthIZsgRheSfWoiR5SRKwUl9xbdwaBjp0G7bvGQM7PSut8EwST6pbeVDFLsRmZZi Np6Dv9a4xh5UjOzI3GMKetdJ4buY4Jo/NtzMHiPyZxjpzmhAmaviNby31ma4hWOFB8rJHjGKxbc2 0RnlkZQZF4DHjPtVzU7NpSfIWZQRk73zWMofc0bjAHfFO7uablsT24gtgJlDFmLHOcc8V0EraTZ2 UVxIPLIT5Cx+Zz64+tc1auEVpGhWMK3DHndWXq17Je3ZaSQkLgD2FJsm9kP1TWbjUZQzP8q8DjFX NItQkX9oXRwifdz3qjptkJ3Mky7YE5ZjSaxqH2qaOKJitug4ApJBFN6stXfiR5CYraNVXP8ArCMk VhpNvm68g9KkSJXwwztH8NV5mzMWC4/DFF7hz2ZohDJC/wApAPI71GzAlVxwBj0p9vdzR2Z6bTxn uagmk3YXcdx5zigV7u49cKdhYbsdqIztym35T7UQR7mDkHjjOOtT9Cw2qS33QegNI0fcjCkDLRMU 7MKUuWURg5UemRj8ahXe8G6SfIDcxgcU2R97j5gfcUGTd2W7OQqzIDkNwR/9emebIHaPr6riolys RG4YJ4HrU0ZZMlCpcjkHqKmxlJXehMqyWsZ3hlZwcg5GKXy0RVPmqcruwvOfqaqCW4mkMj4Yeppv n3JkzsXyzwCtLkYNeRoJCJY97yJgdFDYqTd5cWwR71ySQM1WiuSuFMQb1HrSp50zMVAiB7E9KXK+ pa6aEWWMkjIz7Cv3QfX2oJlSxhWRDns/496jRZI5ZMSkDIHNTSySyS8XKEEcKF4rUYhmMt+gBDY2 gEfWp44HuFmCjJDLx69ap26tHdKo2ZYg5rQtriOBJJFySzDcPSkkrWBdmRPbP+8CFsRj5l61WZ5w 3DIB2GBWjLdq5lYIV7EhutZ0g+c849iKY/QyHnLxPtiwrDr/APqqRLh7fayyFcY+QnIP4UwJIrYV QACd+Dz+VWre3jnQPJGGJHDDr/hTbsZXIGvC52mNFOPugYB96idVcMsZAOPuse/sa1pdMhMQdGYH 0YZppsrYWx3JvkAyCoIov1AyLee8hXEzuCRt5boKmnn2p5cTfvCMFqrndvMZbjoVYE//AKqtKqRR mNoirHlH9fxp2Hc19JtVlgglvC5UMCSeuM+9a9/bRW93K1ksstvszlh3x0rk4Lu4dijO5AHQDrXV +HroXJjsriUQwuMvIzYAGffvRa5UX0ZnYkMeZU4YcEDirVhZLdXsNuEY7iMqMZxXXHQtPMjJFKZI ONj1XttJhXVZY4CVeFA2/POKTRpyla68NaNYzFbq2mEhBK/P/wDXpunxWsMaKu5HC/KB1x+FQXc1 7JeMZQZI14DOp4/GnwW1xPEtzG0aAnYME5/n7VVgLcpnSOaXc8kKDqRgCsIRC4uhPkqY+vHFaM6m ONkuZJcggiLPDe9URqCvMI2URBuCpU4NJjvYbfy/bpFkiUxgDBjHSsWC3e8vmjReAeW7KK3YZ4Z5 fs8ShZX4VF/i/OmXsVvo6yWokzKfmkK9ye1JiauZuq30Vvb+SjhYE6L3c1i204nRncBSTkUzUgZ5 V8wEMx4X0FSwQbZAiAEdKT2E3YkiuDG/AJPY9s0wo010rg887vfNattpcDRvJNcIgCkqCecjtT4L eOMZUhy3BGORSW5NmyosTSXAtkA2LyTjoalvYRbXCqSp3D+E1Er3FvLLbxdHbGSOT+NSMsL3G1pQ FA5PX8KbHewpdYUwPvdsUhmCqHBKuvK8c1NG+1BiGNIz0L9W/rULrE5dkI2D7wbqv0pWK9o2iBY3 n8x0U7V68ioo4jk+Z8nsetXU8qGPeDsTrjPWq9zMbliQAB2PelczdrETJsiA3Zwadg/a/nztIxyO tOEZaMdyDUklvJFcp5zYHXiqixRI4oPkcBWBGcEcCmiJXtBsJDA4JU1KZGkiZUfG0nknGRT4bx4L cMmCScbSoOf0plFeWXLoE3Bhj2xU0jOlyqiYkyAZAzSSys2ojO35wCy46VbllVbkBo1ZCuBxigCB TmORjH5pVgNrHFTRwtvLSWaAEYChhxUUZB8wlSVz/D1p/mxK7KiycY6noKAEhjU3iJKSoDZVgCce 1SCNyoABw0nfP9adbuC24qfv8Z9PTNIZnfbtHybzxnp06UhCvEQbo7TweN386VLC+nQSxxSFGHBy P8ac4nnZx5bks5C4zg47CumtZ7a2tY4ZdgkUYILHP86aKSucHbGO2to0kCtkEsXHNWLIrJAHVT1I GD70l1cfZ5FWe2ZuxK4OPyqGwQ28E0u8vHuLYJwQPpWb1iZM2EMojjMY6HkGmTLM7O0wA9APSs6P Xf3RCwnAzg8VJ/bkUy/vY3U4wR7U7NbArt6mFct5szmJQoUnP1rodNsPtygFxEhUjlc5rCaIzS+W i7fMfge3rXYiyk0vT4bhZXPnLgBexHXp06itFoN6syrjTUspVSbKnpmHkYrRismhQt5qyoQPLBG0 ge9QPK8s26dWJfsM545qa6NrPLFJJM8G3GI2B5FFxHTw66bG0j82NGUjjZWHeeIC1280RkhZ+uG6 1j3919kjKRkuHXgn19qzIZjO4ifLMe9SaqZuy6ySuXfvmq82tMUQJuTDZ+Xis9oM4HXnuelOSzZO cr9RTuUk2aTXtzqDofMcsw7deKqSws8+XuH84n+MYJqzp1vC8VwXMn1Rc/hntVu1gLzLcFf3zDbF GecD1NANaiW4bRh5783cgyD/AHBTLpzcRfb3UNt5ZQefrTL+G6ik8qQkuxLH1NNtrqND5c4xH0YD vSTDbQwnuTqWpvP5KxovCqO1XrXZGzEyBGHcjr9KtXmmHTL4hPmhYblb+8DVB8Kf3oQDPUEH+VD8 hSViy7maTaB8o6sO9XDIssoESuzZ+8RiqsTxRsvBZD/FmkRLu4jBViicDK/KDSRMdDVgitrQPPO6 O69VXk5qBLGzYiQvKEJzzzTYrRFRjcKRGmcDoWY9/pVCZmyEjZtp59hQ9BtrqWLw3KyhYdjlujqe g+nrVWOykt1ZtpdjksT/AFpqO0bDYW3npt61fSWXcvmzOcnayZ4x6ULUncpyKzjMnzHPQUBC8QkU AANgg9hXQWFhbLJGSGkbqck4A/Gn69FDbwj7MqhXfJ2df0ppF8mlzEgaVlCBQsW7cx71I2Lu0eeS Ni6sAOfrSLZrMm/DZb72DTP9JWNoNw2Ft23bkmmJIjhjj84xMjpuI5Jz1q7YvBZyFlhWQxuGG8/0 qe20aVvJubiRh5gyp69O1TDRFkV3jLuvXDDaTQOzFudLfzlfy1YONzSDoKzbn7LGz8MWzjj69qu3 RuLXdBHd4j2/Mu5iPyrOQLLMqmVcMRtATvRcLDrexWc5ikKD/a4q7Pa2sdrhXZZsYY78gn2qm8cC xSOXmYRHDAng5qrKEDDy+EZRwe1DdiZNJGrJNp6i2VMjy1G7Pc/4VVFzbxRMhTfubIb+7VCSRd4w QAB1zRHMszYILIp5boPw9ajmZDmzYGogTiRkBCj5ewFOGrD/AJ7uvsO1ZsciMjAj936Z5JqMImOu PrScmDqNFvTEMl7Np7lblYwTLMRj589B+tYGpKtvezRLuIBJJyfWtSyZLYDIZmxnAPesS8Ms1xKZ SCxJJ5qluU1Yfp0a3EoUj5T0B4yac04dDHhVOe3WiCKWMExqcj+IVHCm2bmL3yab1ZEle1mSK4Cy Plt2QAR2rqtP1vzdBazlRSytkSMe3pXHRsAZSy9Wq7bs06pbxyKpd9pOfWmwba2N7T7sXd6005RF U8c8bRyfzxTvFuq2uqXST26MAiBeAFUY6YqrqsEdmIre1mVkPUr1FZF4Edo7Yy7A3zOx6gUk7rQd iQQ3E1mk0rBUXJyT2p8Xl4UQXCb8/SrcQsbuyUSSsgTOM9T71RudNtX/AOPKQscc7j1pPew4s07O 3SeJy7gODyvcVLHEJsMvyx4zuPSsrSbUQyhZGYxsfmBOAa6rUGgSBbGIRmNMNNOvc/3RTsbKdloZ 8c3lKzqSsAOFQf8ALRv8K3bJVsbZrq5RTO46E9B6VjWdvJqEkzKVVY4yEH93A/nSJJOlmFmmLMT8 m49BSbGk9ye9vNt75oDO06kENztHtWJIBn5WAwcEZ5rYjWF3UzXARtnD4zkgVXk8vaFaKIu6k7mO 3+lK5nJ6kE0zvYoxJbZ8vJrOVbd5AZchAclTzmtdPLOnTo0WGJDIw/HNZZhRiSxbP0zTuKTJzLJK 6payIFHZiBUpNxu2SSquBjAPAqpDAjyEMzfKCRgcmrhjVLdfMxuJ6ZOfxobC6W5Pczxi2SJXOFUK XIyT/k1EttLdOqpG+AOy4qIJEyhmVsKcj5s1curgXsSqsjxEKACKTlcOeJmy3FvptwynmVRg5Oau +G9R03U9SW1uYyjEEqw6E/SsufSYJU2h8zd5Mk5NaGgaN/Zeox3Vz86pgjHHFaJxsJSbfkad1vS5 ljQkIucHpxWfagS20byH5vNHJJyRWrqGoQuki+UwLkncp/zxWcNqwQnYMGQcE9KlGjZf09ZB9rdS gVcn5jjjHb3qcLc3N4VQRlkB2gDGc1lm5IkkHl4XfyRW1ZXKJNMEZzMGHAHGKoEyVZDZxizuQZLs OGj5yoU+3rVk6qIH81IHKoMNgcGqFzdmyv7a7ufM2FmUMPvc54+lUb/UIngVEkaNCSrfL979aB3K NzOzXV3KcbXOFB4wDUcSnzURAMgbue+BTJWjKhE7nJJHJoidTeyyooGI+STwOKRA92BsrgMuCXA+ tVJjhkU8Dbz7GrMx32sTFgS8h7/Sq9wXOoyRSOFAJBdBnH0qWRLVFEWWZMSOWB5KgYzV4GJACU2o BgL6U5YWjuPs5YylmGyQnGfY1ZdIIX2qGEgOHDHcPwNS0yXF7spkjDO3CL1z3qWJS8YYw9f9qoxJ C0mA2wD7wJ4zUwuosfLIce1SyGvIzJLgLbttl/fA42jr+FZ1qPPusXG87nILc+vGaKK22Rqy5O80 UTQrIERyT15PsPWnWJ8xwZpWUd8r0+tFFLoTexUnRo5ZIwQ3zcN6g0yAfv8AhcBOuaKKaGaUcUnl ibzUw3XNWdCS3uLq4N2glwARuXOKKKhlLchvNajivSsFohjGQp21Z0km7dpZIYyuccCiim9FYEtT SkuraaGSFLVA3QMO1QKslzNDDACIo+Tk8t74oopJWRV22aap9jV3WM4HJHqTWXeOJJlQgL6gCiin 1Nbmhp405vNF+soAwImjI4NRz2KzAOH4VsJkdR7+9FFNrQzFCBYRGCScHj0rKDZmKOAmTyWB4ooq Yq6FLVErLFa3CvFcedJjOEU8UTSb3Ds2S554wAaKKU1Zmc1rYsOiSGEttUY254AqJ1VG2xhSe5DZ 4ooqCZDowqyA+WxGckjsPpUstyrvuR3aJchVJ6f5NFFINkRyzGYEeZ8qDAHtSBSttCC4+9wOmaKK 1jsaQ1QJmRHjwq4k6k1rwasljPKrRxEGQE7k9jxkc0UVaZSJNc1uHUEtLWKGJQrhiyDv+PasWSEP HlXQMZDyx+lFFF7g9yPyZSzuxRRjnJH6URxrOgiiUiIcux6miigRVuEF1dQwxn5Q2Mcjj8KlGbeS 4nj53PgZPWiikgRLN5n2PM5O98YUjlR65qrsjWNWJYsOnzdaKKl6szqPWxFJEI3hRgN7MScdTmpD HEhKlY8j1aiiqehqkf/Z