20200325 13052300 1.0 FALSE AssignDomainToField I:\PADUS\PADUS2_1\BlankGDBSchema\PADUS2_1_3_25_2020.gdb\PADUS2_1Combined_Proclamation_Marine_Fee_Designation_Easement Pub_Access "Public Access" # AssignDomainToField I:\PADUS\PADUS2_1\BlankGDBSchema\PADUS2_1_3_25_2020.gdb\PADUS2_1Combined_Proclamation_Marine_Fee_Designation_Easement Category Category # AssignDomainToField I:\PADUS\PADUS2_1\BlankGDBSchema\PADUS2_1_3_25_2020.gdb\PADUS2_1Combined_Proclamation_Marine_Fee_Designation_Easement Des_Tp "Designation Type" # AssignDomainToField I:\PADUS\PADUS2_1\BlankGDBSchema\PADUS2_1_3_25_2020.gdb\PADUS2_1Combined_Proclamation_Marine_Fee_Designation_Easement FeatClass Category # AssignDomainToField I:\PADUS\PADUS2_1\BlankGDBSchema\PADUS2_1_3_25_2020.gdb\PADUS2_1Combined_Proclamation_Marine_Fee_Designation_Easement GAP_Sts "GAP Status Code" # AssignDomainToField I:\PADUS\PADUS2_1\BlankGDBSchema\PADUS2_1_3_25_2020.gdb\PADUS2_1Combined_Proclamation_Marine_Fee_Designation_Easement IUCN_Cat "IUCN Category" # AssignDomainToField I:\PADUS\PADUS2_1\BlankGDBSchema\PADUS2_1_3_25_2020.gdb\PADUS2_1Combined_Proclamation_Marine_Fee_Designation_Easement Mang_Name "Agency Name" # AssignDomainToField I:\PADUS\PADUS2_1\BlankGDBSchema\PADUS2_1_3_25_2020.gdb\PADUS2_1Combined_Proclamation_Marine_Fee_Designation_Easement Mang_Type "Agency Type" # AssignDomainToField I:\PADUS\PADUS2_1\BlankGDBSchema\PADUS2_1_3_25_2020.gdb\PADUS2_1Combined_Proclamation_Marine_Fee_Designation_Easement Own_Name "Agency Name" # AssignDomainToField I:\PADUS\PADUS2_1\BlankGDBSchema\PADUS2_1_3_25_2020.gdb\PADUS2_1Combined_Proclamation_Marine_Fee_Designation_Easement Own_Type "Agency Type" # AssignDomainToField I:\PADUS\PADUS2_1\BlankGDBSchema\PADUS2_1_3_25_2020.gdb\PADUS2_1Combined_Proclamation_Marine_Fee_Designation_Easement State_Nm "State Name" # DeleteField I:\PADUS\PADUS2_1\BlankGDBSchema\PADUS2_1_3_25_2020.gdb\PADUS2_1Combined_Proclamation_Marine_Fee_Designation_Easement d_Category;d_Own_Type;d_Own_Name;d_Mang_Type;d_Mang_Name;d_Des_Tp;d_State_Nm;d_Access;d_GAP_Sts;d_IUCN_Cat RemoveSpatialIndex I:\PADUS\PADUS2_1\BlankGDBSchema\PADUS2_1_3_25_2020.gdb\PADUS2_1Combined_Proclamation_Marine_Fee_Designation_Easement RepairGeometry PADUS3_0Combined_Proclamation_Marine_Fee_Designation_Easement DELETE_NULL CalculateField "PADUS 2.1 Combined Proclamation, Marine, Fee, Designation, Easement" GIS_Acres !shape.area@acres! PYTHON_9.3 # RepairGeometry PADUS3_0Combined_Proclamation_Marine_Fee_Designation_Easement DELETE_NULL RepairGeometry PADUS3_0Combined_Proclamation_Marine_Fee_Designation_Easement DELETE_NULL RepairGeometry PADUS3_0Combined_Proclamation_Marine_Fee_Designation_Easement DELETE_NULL AddField tmp23 OwnTchk LONG # # # "Owner Type Check" NULLABLE NON_REQUIRED # AddField tmp23 MangTchk LONG # # # "Manager Type Check" NULLABLE NON_REQUIRED # AddField tmp23 OwnTDef TEXT # # 5 "Owner Type Default Code" NULLABLE NON_REQUIRED # AddField tmp23 MangTDef TEXT # # 5 "Manager Type Default Code" NULLABLE NON_REQUIRED # AddField tmp23 OwnNmDef TEXT # # 5 "Owner Name Default Code" NULLABLE NON_REQUIRED # CalculateField tmp23 OwnNmDef "DESG" PYTHON_9.3 # CalculateField tmp23 OwnNmDef "JNT" PYTHON_9.3 # CalculateField tmp23 OwnNmDef "NGO" PYTHON_9.3 # CalculateField tmp23 OwnNmDef "OTHF" PYTHON_9.3 # CalculateField tmp23 OwnNmDef "OTHR" PYTHON_9.3 # CalculateField tmp23 OwnNmDef "OTHS" PYTHON_9.3 # CalculateField tmp23 OwnNmDef "PVT" PYTHON_9.3 # CalculateField tmp23 OwnNmDef "RA" PYTHON_9.3 # CalculateField tmp23 OwnNmDef "TRIB" PYTHON_9.3 # CalculateField tmp23 OwnNmDef "UNK" PYTHON_9.3 # CalculateField tmp23 OwnNmDef "UNKL" PYTHON_9.3 # AddField tmp23 MngNmDef TEXT # # 5 "Manager Name Default Code" NULLABLE NON_REQUIRED # CalculateField tmp23 MngNmDef "DESG" PYTHON_9.3 # CalculateField tmp23 MngNmDef "JNT" PYTHON_9.3 # CalculateField tmp23 MngNmDef "NGO" PYTHON_9.3 # CalculateField tmp23 MngNmDef "OTHF" PYTHON_9.3 # CalculateField tmp23 MngNmDef "OTHR" PYTHON_9.3 # CalculateField tmp23 MngNmDef "OTHS" PYTHON_9.3 # CalculateField tmp23 MngNmDef "PVT" PYTHON_9.3 # CalculateField tmp23 MngNmDef "RA" PYTHON_9.3 # CalculateField tmp23 MngNmDef "TRIB" PYTHON_9.3 # CalculateField tmp23 MngNmDef "UNK" PYTHON_9.3 # CalculateField tmp23 MngNmDef "UNKL" PYTHON_9.3 # CalculateField "PADUS 2.1 Combined Proclamation, Marine, Fee, Designation, Easement" Mang_Name !Mang_Name! PYTHON_9.3 # CalculateField "PADUS 2.1 Combined Proclamation, Marine, Fee, Designation, Easement" Mang_Name !MngNmDef! PYTHON_9.3 # CalculateField "PADUS 2.1 Combined Proclamation, Marine, Fee, Designation, Easement" Own_Name !OwnNmDef! PYTHON_9.3 # CalculateField "PADUS 2.1 Combined Proclamation, Marine, Fee, Designation, Easement" Own_Type !OwnTDef! PYTHON_9.3 # AddField tmp23 OwnTchk LONG # # # "Owner Type Check" NULLABLE NON_REQUIRED # AddField tmp23 MangTchk LONG # # # "Manager Type Check" NULLABLE NON_REQUIRED # AddField tmp23 OwnTDef TEXT # # 5 "Owner Type Default Code" NULLABLE NON_REQUIRED # AddField tmp23 MangTDef TEXT # # 5 "Manager Type Default Code" NULLABLE NON_REQUIRED # AddField tmp23 OwnNmDef TEXT # # 5 "Owner Name Default Code" NULLABLE NON_REQUIRED # CalculateField tmp23 OwnNmDef "DESG" PYTHON_9.3 # CalculateField tmp23 OwnNmDef "JNT" PYTHON_9.3 # CalculateField tmp23 OwnNmDef "NGO" PYTHON_9.3 # CalculateField tmp23 OwnNmDef "OTHF" PYTHON_9.3 # CalculateField tmp23 OwnNmDef "OTHR" PYTHON_9.3 # CalculateField tmp23 OwnNmDef "OTHS" PYTHON_9.3 # CalculateField tmp23 OwnNmDef "PVT" PYTHON_9.3 # CalculateField tmp23 OwnNmDef "RA" PYTHON_9.3 # CalculateField tmp23 OwnNmDef "TRIB" PYTHON_9.3 # CalculateField tmp23 OwnNmDef "UNK" PYTHON_9.3 # CalculateField tmp23 OwnNmDef "UNKL" PYTHON_9.3 # AddField tmp23 MngNmDef TEXT # # 5 "Manager Name Default Code" NULLABLE NON_REQUIRED # CalculateField tmp23 MngNmDef "DESG" PYTHON_9.3 # CalculateField tmp23 MngNmDef "JNT" PYTHON_9.3 # CalculateField tmp23 MngNmDef "NGO" PYTHON_9.3 # CalculateField tmp23 MngNmDef "OTHF" PYTHON_9.3 # CalculateField tmp23 MngNmDef "OTHR" PYTHON_9.3 # CalculateField tmp23 MngNmDef "OTHS" PYTHON_9.3 # CalculateField tmp23 MngNmDef "PVT" PYTHON_9.3 # CalculateField tmp23 MngNmDef "RA" PYTHON_9.3 # CalculateField tmp23 MngNmDef "TRIB" PYTHON_9.3 # CalculateField tmp23 MngNmDef "UNK" PYTHON_9.3 # CalculateField tmp23 MngNmDef "UNKL" PYTHON_9.3 # DeleteField "PADUS 2.1 Combined Proclamation, Marine, Fee, Designation, Easement" OwnTchk;MangTchk;OwnTDef;MangTDef;OwnNmDef;MngNmDef AddField tmp23 OwnTchk LONG # # # "Owner Type Check" NULLABLE NON_REQUIRED # AddField tmp23 MangTchk LONG # # # "Manager Type Check" NULLABLE NON_REQUIRED # AddField tmp23 OwnTDef TEXT # # 5 "Owner Type Default Code" NULLABLE NON_REQUIRED # AddField tmp23 MangTDef TEXT # # 5 "Manager Type Default Code" NULLABLE NON_REQUIRED # AddField tmp23 OwnNmDef TEXT # # 5 "Owner Name Default Code" NULLABLE NON_REQUIRED # CalculateField tmp23 OwnNmDef "DESG" PYTHON_9.3 # CalculateField tmp23 OwnNmDef "JNT" PYTHON_9.3 # CalculateField tmp23 OwnNmDef "NGO" PYTHON_9.3 # CalculateField tmp23 OwnNmDef "OTHF" PYTHON_9.3 # CalculateField tmp23 OwnNmDef "OTHR" PYTHON_9.3 # CalculateField tmp23 OwnNmDef "OTHS" PYTHON_9.3 # CalculateField tmp23 OwnNmDef "PVT" PYTHON_9.3 # CalculateField tmp23 OwnNmDef "RA" PYTHON_9.3 # CalculateField tmp23 OwnNmDef "TRIB" PYTHON_9.3 # CalculateField tmp23 OwnNmDef "UNK" PYTHON_9.3 # CalculateField tmp23 OwnNmDef "UNKL" PYTHON_9.3 # AddField tmp23 MngNmDef TEXT # # 5 "Manager Name Default Code" NULLABLE NON_REQUIRED # CalculateField tmp23 MngNmDef "DESG" PYTHON_9.3 # CalculateField tmp23 MngNmDef "JNT" PYTHON_9.3 # CalculateField tmp23 MngNmDef "NGO" PYTHON_9.3 # CalculateField tmp23 MngNmDef "OTHF" PYTHON_9.3 # CalculateField tmp23 MngNmDef "OTHR" PYTHON_9.3 # CalculateField tmp23 MngNmDef "OTHS" PYTHON_9.3 # CalculateField tmp23 MngNmDef "PVT" PYTHON_9.3 # CalculateField tmp23 MngNmDef "RA" PYTHON_9.3 # CalculateField tmp23 MngNmDef "TRIB" PYTHON_9.3 # CalculateField tmp23 MngNmDef "UNK" PYTHON_9.3 # CalculateField tmp23 MngNmDef "UNKL" PYTHON_9.3 # AddField tmp23 OwnTchk LONG # # # "Owner Type Check" NULLABLE NON_REQUIRED # AddField tmp23 MangTchk LONG # # # "Manager Type Check" NULLABLE NON_REQUIRED # AddField tmp23 OwnTDef TEXT # # 5 "Owner Type Default Code" NULLABLE NON_REQUIRED # AddField tmp23 MangTDef TEXT # # 5 "Manager Type Default Code" NULLABLE NON_REQUIRED # AddField tmp23 OwnNmDef TEXT # # 5 "Owner Name Default Code" NULLABLE NON_REQUIRED # CalculateField tmp23 OwnNmDef "DESG" PYTHON_9.3 # CalculateField tmp23 OwnNmDef "JNT" PYTHON_9.3 # CalculateField tmp23 OwnNmDef "NGO" PYTHON_9.3 # CalculateField tmp23 OwnNmDef "OTHF" PYTHON_9.3 # CalculateField tmp23 OwnNmDef "OTHR" PYTHON_9.3 # CalculateField tmp23 OwnNmDef "OTHS" PYTHON_9.3 # CalculateField tmp23 OwnNmDef "PVT" PYTHON_9.3 # CalculateField tmp23 OwnNmDef "RA" PYTHON_9.3 # CalculateField tmp23 OwnNmDef "TRIB" PYTHON_9.3 # CalculateField tmp23 OwnNmDef "UNK" PYTHON_9.3 # CalculateField tmp23 OwnNmDef "UNKL" PYTHON_9.3 # AddField tmp23 MngNmDef TEXT # # 5 "Manager Name Default Code" NULLABLE NON_REQUIRED # CalculateField tmp23 MngNmDef "DESG" PYTHON_9.3 # CalculateField tmp23 MngNmDef "JNT" PYTHON_9.3 # CalculateField tmp23 MngNmDef "NGO" PYTHON_9.3 # CalculateField tmp23 MngNmDef "OTHF" PYTHON_9.3 # CalculateField tmp23 MngNmDef "OTHR" PYTHON_9.3 # CalculateField tmp23 MngNmDef "OTHS" PYTHON_9.3 # CalculateField tmp23 MngNmDef "PVT" PYTHON_9.3 # CalculateField tmp23 MngNmDef "RA" PYTHON_9.3 # CalculateField tmp23 MngNmDef "TRIB" PYTHON_9.3 # CalculateField tmp23 MngNmDef "UNK" PYTHON_9.3 # CalculateField tmp23 MngNmDef "UNKL" PYTHON_9.3 # DeleteField tmp23 OwnTchk;MangTchk;OwnTDef;MangTDef;OwnNmDef;MngNmDef AddField tmp23 OwnTchk LONG # # # "Owner Type Check" NULLABLE NON_REQUIRED # AddField tmp23 MangTchk LONG # # # "Manager Type Check" NULLABLE NON_REQUIRED # AddField tmp23 OwnTDef TEXT # # 5 "Owner Type Default Code" NULLABLE NON_REQUIRED # AddField tmp23 MangTDef TEXT # # 5 "Manager Type Default Code" NULLABLE NON_REQUIRED # AddField tmp23 OwnNmDef TEXT # # 5 "Owner Name Default Code" NULLABLE NON_REQUIRED # CalculateField tmp23 OwnNmDef "DESG" PYTHON_9.3 # CalculateField tmp23 OwnNmDef "JNT" PYTHON_9.3 # CalculateField tmp23 OwnNmDef "NGO" PYTHON_9.3 # CalculateField tmp23 OwnNmDef "OTHF" PYTHON_9.3 # CalculateField tmp23 OwnNmDef "OTHR" PYTHON_9.3 # CalculateField tmp23 OwnNmDef "OTHS" PYTHON_9.3 # CalculateField tmp23 OwnNmDef "PVT" PYTHON_9.3 # CalculateField tmp23 OwnNmDef "RA" PYTHON_9.3 # CalculateField tmp23 OwnNmDef "TRIB" PYTHON_9.3 # CalculateField tmp23 OwnNmDef "UNK" PYTHON_9.3 # CalculateField tmp23 OwnNmDef "UNKL" PYTHON_9.3 # AddField tmp23 MngNmDef TEXT # # 5 "Manager Name Default Code" NULLABLE NON_REQUIRED # CalculateField tmp23 MngNmDef "DESG" PYTHON_9.3 # CalculateField tmp23 MngNmDef "JNT" PYTHON_9.3 # CalculateField tmp23 MngNmDef "NGO" PYTHON_9.3 # CalculateField tmp23 MngNmDef "OTHF" PYTHON_9.3 # CalculateField tmp23 MngNmDef "OTHR" PYTHON_9.3 # CalculateField tmp23 MngNmDef "OTHS" PYTHON_9.3 # CalculateField tmp23 MngNmDef "PVT" PYTHON_9.3 # CalculateField tmp23 MngNmDef "RA" PYTHON_9.3 # CalculateField tmp23 MngNmDef "TRIB" PYTHON_9.3 # CalculateField tmp23 MngNmDef "UNK" PYTHON_9.3 # CalculateField tmp23 MngNmDef "UNKL" PYTHON_9.3 # CalculateField "PADUS 2.1 Combined Proclamation, Marine, Fee, Designation, Easement" FeeJnID autoIncrement() PYTHON_9.3 "rec=0\ndef autoIncrement():\n global rec\n pStart = 1 #adjust start value, if req'd \n pInterval = 1 #adjust interval value, if req'd\n if (rec == 0): \n rec = pStart \n else: \n rec = rec + pInterval \n return rec\n" CalculateField "PADUS 2.1 Combined Proclamation, Marine, Fee, Designation, Easement" DesJnID autoIncrement() PYTHON_9.3 "rec=0\ndef autoIncrement():\n global rec\n pStart = 4621 #adjust start value, if req'd \n pInterval = 1 #adjust interval value, if req'd\n if (rec == 0): \n rec = pStart \n else: \n rec = rec + pInterval \n return rec\n" CalculateField "PADUS 2.1 Combined Proclamation, Marine, Fee, Designation, Easement" DesJnID autoIncrement() PYTHON_9.3 "rec=0\ndef autoIncrement():\n global rec\n pStart = 4621 #adjust start value, if req'd \n pInterval = 1 #adjust interval value, if req'd\n if (rec == 0): \n rec = pStart \n else: \n rec = rec + pInterval \n return rec\n" CalculateField "PADUS 2.1 Combined Proclamation, Marine, Fee, Designation, Easement" MFCscript "identical" PYTHON_9.3 # CalculateField "PADUS 2.1 Combined Proclamation, Marine, Fee, Designation, Easement" MFCdup isDuplicate( !DES_oid!) PYTHON_9.3 "uniqueList = []\ndef isDuplicate(inValue):\n if inValue in uniqueList:\n return 1\n else:\n uniqueList.append(inValue)\n return 0\n" CalculateField "PADUS 2.1 Combined Proclamation, Marine, Fee, Designation, Easement" MFCscript "Centroid" PYTHON_9.3 # CalculateField "PADUS 2.1 Combined Proclamation, Marine, Fee, Designation, Easement" FeatClass "Designation" PYTHON_9.3 # CalculateField "PADUS 2.1 Combined Proclamation, Marine, Fee, Designation, Easement" Category "Designation" PYTHON_9.3 # DeleteField "PADUS 2.1 Combined Proclamation, Marine, Fee, Designation, Easement" OwnTchk;MangTchk;OwnTDef;MangTDef;OwnNmDef;MngNmDef;FeeJnID;DesJnID;MFCscript;MFCdup;DES_oid DeleteField tmp24 OwnTchk;MangTchk;OwnTDef;MangTDef;OwnNmDef;MngNmDef AddField tmp24 OwnTchk LONG # # # "Owner Type Check" NULLABLE NON_REQUIRED # AddField tmp24 MangTchk LONG # # # "Manager Type Check" NULLABLE NON_REQUIRED # AddField tmp24 OwnTDef TEXT # # 5 "Owner Type Default Code" NULLABLE NON_REQUIRED # AddField tmp24 MangTDef TEXT # # 5 "Manager Type Default Code" NULLABLE NON_REQUIRED # AddField tmp24 OwnNmDef TEXT # # 5 "Owner Name Default Code" NULLABLE NON_REQUIRED # CalculateField tmp24 OwnNmDef "DESG" PYTHON_9.3 # CalculateField tmp24 OwnNmDef "JNT" PYTHON_9.3 # CalculateField tmp24 OwnNmDef "NGO" PYTHON_9.3 # CalculateField tmp24 OwnNmDef "OTHF" PYTHON_9.3 # CalculateField tmp24 OwnNmDef "OTHR" PYTHON_9.3 # CalculateField tmp24 OwnNmDef "OTHS" PYTHON_9.3 # CalculateField tmp24 OwnNmDef "PVT" PYTHON_9.3 # CalculateField tmp24 OwnNmDef "RA" PYTHON_9.3 # CalculateField tmp24 OwnNmDef "TRIB" PYTHON_9.3 # CalculateField tmp24 OwnNmDef "UNK" PYTHON_9.3 # CalculateField tmp24 OwnNmDef "UNKL" PYTHON_9.3 # AddField tmp24 MngNmDef TEXT # # 5 "Manager Name Default Code" NULLABLE NON_REQUIRED # CalculateField tmp24 MngNmDef "DESG" PYTHON_9.3 # CalculateField tmp24 MngNmDef "JNT" PYTHON_9.3 # CalculateField tmp24 MngNmDef "NGO" PYTHON_9.3 # CalculateField tmp24 MngNmDef "OTHF" PYTHON_9.3 # CalculateField tmp24 MngNmDef "OTHR" PYTHON_9.3 # CalculateField tmp24 MngNmDef "OTHS" PYTHON_9.3 # CalculateField tmp24 MngNmDef "PVT" PYTHON_9.3 # CalculateField tmp24 MngNmDef "RA" PYTHON_9.3 # CalculateField tmp24 MngNmDef "TRIB" PYTHON_9.3 # CalculateField tmp24 MngNmDef "UNK" PYTHON_9.3 # CalculateField tmp24 MngNmDef "UNKL" PYTHON_9.3 # CalculateField "PADUS 2.1 Combined Proclamation, Marine, Fee, Designation, Easement" Mang_Type "NGO" PYTHON_9.3 # CalculateField "PADUS 2.1 Combined Proclamation, Marine, Fee, Designation, Easement" MangTchk 0 PYTHON_9.3 # CalculateField "PADUS 2.1 Combined Proclamation, Marine, Fee, Designation, Easement" Mang_Type "LOC" PYTHON_9.3 # CalculateField "PADUS 2.1 Combined Proclamation, Marine, Fee, Designation, Easement" MangTchk 0 PYTHON_9.3 # CalculateField "PADUS 2.1 Combined Proclamation, Marine, Fee, Designation, Easement" Mang_Type "STAT" PYTHON_9.3 # CalculateField "PADUS 2.1 Combined Proclamation, Marine, Fee, Designation, Easement" MangTchk 0 PYTHON_9.3 # CalculateField "PADUS 2.1 Combined Proclamation, Marine, Fee, Designation, Easement" MangTchk 0 PYTHON_9.3 # CalculateField "PADUS 2.1 Combined Proclamation, Marine, Fee, Designation, Easement" Mang_Type "DIST" PYTHON_9.3 # CalculateField "PADUS 2.1 Combined Proclamation, Marine, Fee, Designation, Easement" MangTchk 0 PYTHON_9.3 # CalculateField "PADUS 2.1 Combined Proclamation, Marine, Fee, Designation, Easement" Mang_Type "STAT" PYTHON_9.3 # CalculateField "PADUS 2.1 Combined Proclamation, Marine, Fee, Designation, Easement" MangTchk 0 PYTHON_9.3 # CalculateField "PADUS 2.1 Combined Proclamation, Marine, Fee, Designation, Easement" MangTchk 0 PYTHON_9.3 # CalculateField "PADUS 2.1 Combined Proclamation, Marine, Fee, Designation, Easement" Mang_Type "LOC" PYTHON_9.3 # CalculateField "PADUS 2.1 Combined Proclamation, Marine, Fee, Designation, Easement" MangTchk 0 PYTHON_9.3 # CalculateField "PADUS 2.1 Combined Proclamation, Marine, Fee, Designation, Easement" Mang_Type "LOC" PYTHON_9.3 # CalculateField "PADUS 2.1 Combined Proclamation, Marine, Fee, Designation, Easement" MangTchk 0 PYTHON_9.3 # CalculateField "PADUS 2.1 Combined Proclamation, Marine, Fee, Designation, Easement" Mang_Type "PVT" PYTHON_9.3 # CalculateField "PADUS 2.1 Combined Proclamation, Marine, Fee, Designation, Easement" MangTchk 0 PYTHON_9.3 # CalculateField "PADUS 2.1 Combined Proclamation, Marine, Fee, Designation, Easement" MangTchk 0 PYTHON_9.3 # CalculateField "PADUS 2.1 Combined Proclamation, Marine, Fee, Designation, Easement" Own_Type !OwnTDef! PYTHON_9.3 # DeleteField "PADUS 2.1 Combined Proclamation, Marine, Fee, Designation, Easement" OwnTchk;MangTchk;OwnTDef;MangTDef;OwnNmDef;MngNmDef CalculateField "PADUS 3.0 Combined Proclamation, Marine, Fee, Designation, Easement" FWSSatement ""Geometry of wetland easements are aliquot parts, actual easement acres is " + str(!DOCACRES!) + " per FWS."" PYTHON_9.3 # CalculateField "PADUS 3.0 Combined Proclamation, Marine, Fee, Designation, Easement" FWSSatement ""Geometry of wetland easements are aliquot parts, actual easement acres is " + str(!DOCACRES!) + " per FWS."" PYTHON_9.3 # CalculateField "PADUS 3.0 Combined Proclamation, Marine, Fee, Designation, Easement" Comments ""Geometry of wetland easements are aliquot parts, actual easement acres is " + str(!DOCACRES!) + " per FWS."" PYTHON_9.3 # CalculateField "PADUS 3.0 Combined Proclamation, Marine, Fee, Designation, Easement" Comments ""Geometry of wetland easements are aliquot parts, actual easement acres is " + str(!DOCACRES!) + " per FWS. | " + !Comments!" PYTHON_9.3 # CalculateField "PADUS 3.0 Combined Proclamation, Marine, Fee, Designation, Easement" FWSSatement ""Geometry of wetland easements are aliquot parts, actual easement acres is " + str(!DOCACRES!) + " per FWS. | " + !Comments![:150]" PYTHON_9.3 # CalculateField "PADUS 3.0 Combined Proclamation, Marine, Fee, Designation, Easement" Comments ""Geometry of wetland easements are aliquot parts, actual easement acres is " + str(!DOCACRES!) + " per FWS. | " + !Comments![:160]" PYTHON_9.3 # CalculateField "PADUS 3.0 Combined Proclamation, Marine, Fee, Designation, Easement" GAP_Sts "2" PYTHON_9.3 # CalculateField "PADUS 3.0 Combined Proclamation, Marine, Fee, Designation, Easement" GAPCdSrc "FWS" PYTHON_9.3 # CalculateField "PADUS 3.0 Combined Proclamation, Marine, Fee, Designation, Easement" GAPCdDt "2022" PYTHON_9.3 # DeleteFeatures "PADUS 3.0 Combined Proclamation, Marine, Fee, Designation, Easement" CalculateField "PADUS 3.0 Combined Proclamation, Marine, Fee, Designation, Easement" EaseJnID autoIncrement() PYTHON_9.3 "rec=0\ndef autoIncrement(): \n global rec \n pStart = 1 \n pInterval = 1 \n if (rec == 0): \n rec = pStart \n else: \n rec += pInterval \n return rec" CalculateField "PADUS 3.0 Combined Proclamation, Marine, Fee, Designation, Easement" IUCN_Cat "V" PYTHON_9.3 # CalculateField "PADUS 3.0 Combined Proclamation, Marine, Fee, Designation, Easement" IUCNCtDt "2022" PYTHON_9.3 # ExportFeatures "PADUS 3.0 Combined Proclamation, Marine, Fee, Designation, Easement" "Q:\Dpt-Pew Center on the States\GIS\USENV\NC_CoastalWetlands_202401\NC_CoastalWetlands_202401_MAP\Default.gdb\PADUS3_NC" # NOT_USE_ALIAS "FeatClass "FeatClass" true true false 12 Text 0 0,First,#,"PADUS 3.0 Combined Proclamation, Marine, Fee, Designation, Easement",FeatClass,0,12;Category "Category" true true false 50 Text 0 0,First,#,"PADUS 3.0 Combined Proclamation, Marine, Fee, Designation, Easement",Category,0,50;Own_Type "Owner Type" true true false 50 Text 0 0,First,#,"PADUS 3.0 Combined Proclamation, Marine, Fee, Designation, Easement",Own_Type,0,50;Own_Name "Owner Name" true true false 70 Text 0 0,First,#,"PADUS 3.0 Combined Proclamation, Marine, Fee, Designation, Easement",Own_Name,0,70;Loc_Own "Local Owner" true true false 250 Text 0 0,First,#,"PADUS 3.0 Combined Proclamation, Marine, Fee, Designation, Easement",Loc_Own,0,250;Mang_Type "Manager Type" true true false 50 Text 0 0,First,#,"PADUS 3.0 Combined Proclamation, Marine, Fee, Designation, Easement",Mang_Type,0,50;Mang_Name "Manager Name" true true false 70 Text 0 0,First,#,"PADUS 3.0 Combined Proclamation, Marine, Fee, Designation, Easement",Mang_Name,0,70;Loc_Mang "Local Manager" true true false 250 Text 0 0,First,#,"PADUS 3.0 Combined Proclamation, Marine, Fee, Designation, Easement",Loc_Mang,0,250;Des_Tp "Designation Type" true true false 75 Text 0 0,First,#,"PADUS 3.0 Combined Proclamation, Marine, Fee, Designation, Easement",Des_Tp,0,75;Loc_Ds "Local Designation" true true false 250 Text 0 0,First,#,"PADUS 3.0 Combined Proclamation, Marine, Fee, Designation, Easement",Loc_Ds,0,250;Unit_Nm "Unit Name" true true false 250 Text 0 0,First,#,"PADUS 3.0 Combined Proclamation, Marine, Fee, Designation, Easement",Unit_Nm,0,250;Loc_Nm "Local Name" true true false 250 Text 0 0,First,#,"PADUS 3.0 Combined Proclamation, Marine, Fee, Designation, Easement",Loc_Nm,0,250;State_Nm "State Name" true true false 50 Text 0 0,First,#,"PADUS 3.0 Combined Proclamation, Marine, Fee, Designation, Easement",State_Nm,0,50;Agg_Src "Aggregator Source" true true false 150 Text 0 0,First,#,"PADUS 3.0 Combined Proclamation, Marine, Fee, Designation, Easement",Agg_Src,0,150;GIS_Src "GIS Source" true true false 200 Text 0 0,First,#,"PADUS 3.0 Combined Proclamation, Marine, Fee, Designation, Easement",GIS_Src,0,200;Src_Date "GIS Source Date" true true false 15 Text 0 0,First,#,"PADUS 3.0 Combined Proclamation, Marine, Fee, Designation, Easement",Src_Date,0,15;GIS_Acres "GIS Acres" true true false 4 Long 0 0,First,#,"PADUS 3.0 Combined Proclamation, Marine, Fee, Designation, Easement",GIS_Acres,-1,-1;Source_PAID "Source Protected Area ID" true true false 100 Text 0 0,First,#,"PADUS 3.0 Combined Proclamation, Marine, Fee, Designation, Easement",Source_PAID,0,100;WDPA_Cd "WDPA Site Code" true true false 4 Long 0 0,First,#,"PADUS 3.0 Combined Proclamation, Marine, Fee, Designation, Easement",WDPA_Cd,-1,-1;Pub_Access "Public Access" true true false 20 Text 0 0,First,#,"PADUS 3.0 Combined Proclamation, Marine, Fee, Designation, Easement",Pub_Access,0,20;Access_Src "Public Access Source" true true false 150 Text 0 0,First,#,"PADUS 3.0 Combined Proclamation, Marine, Fee, Designation, Easement",Access_Src,0,150;Access_Dt "Public Access Date" true true false 4 Text 0 0,First,#,"PADUS 3.0 Combined Proclamation, Marine, Fee, Designation, Easement",Access_Dt,0,4;GAP_Sts "GAP Status Code" true true false 95 Text 0 0,First,#,"PADUS 3.0 Combined Proclamation, Marine, Fee, Designation, Easement",GAP_Sts,0,95;GAPCdSrc "GAP Status Code Source" true true false 150 Text 0 0,First,#,"PADUS 3.0 Combined Proclamation, Marine, Fee, Designation, Easement",GAPCdSrc,0,150;GAPCdDt "GAP Status Code Date" true true false 4 Text 0 0,First,#,"PADUS 3.0 Combined Proclamation, Marine, Fee, Designation, Easement",GAPCdDt,0,4;IUCN_Cat "IUCN Category" true true false 70 Text 0 0,First,#,"PADUS 3.0 Combined Proclamation, Marine, Fee, Designation, Easement",IUCN_Cat,0,70;IUCNCtSrc "IUCN Category Source" true true false 150 Text 0 0,First,#,"PADUS 3.0 Combined Proclamation, Marine, Fee, Designation, Easement",IUCNCtSrc,0,150;IUCNCtDt "IUCN Category Date" true true false 4 Text 0 0,First,#,"PADUS 3.0 Combined Proclamation, Marine, Fee, Designation, Easement",IUCNCtDt,0,4;Date_Est "Date of Establishment" true true false 4 Text 0 0,First,#,"PADUS 3.0 Combined Proclamation, Marine, Fee, Designation, Easement",Date_Est,0,4;Comments "Comments" true true false 255 Text 0 0,First,#,"PADUS 3.0 Combined Proclamation, Marine, Fee, Designation, Easement",Comments,0,255;EsmtHldr "Easement Holder" true true false 100 Text 0 0,First,#,"PADUS 3.0 Combined Proclamation, Marine, Fee, Designation, Easement",EsmtHldr,0,100;EHoldTyp "Easement Holder Type" true true false 50 Text 0 0,First,#,"PADUS 3.0 Combined Proclamation, Marine, Fee, Designation, Easement",EHoldTyp,0,50;SHAPE_Length "SHAPE_Length" false true true 8 Double 0 0,First,#,"PADUS 3.0 Combined Proclamation, Marine, Fee, Designation, Easement",SHAPE_Length,-1,-1;SHAPE_Area "SHAPE_Area" false true true 8 Double 0 0,First,#,"PADUS 3.0 Combined Proclamation, Marine, Fee, Designation, Easement",SHAPE_Area,-1,-1" # PADUS3_NC -10708985.932500 3413622.500400 -262699.130600 6939873.458500 1 file://\\pew.pewtrusts.org\pct\PCT Data\Dpt-Pew Center on the States\GIS\USENV\NC_CoastalWetlands_202401\NC_CoastalWetlands_202401_MAP\Default.gdb Local Area Network 002 Projected GCS_North_American_1983 Linear Unit: Meter (1.000000) USA_Contiguous_Albers_Equal_Area_Conic_USGS_version <ProjectedCoordinateSystem xsi:type='typens:ProjectedCoordinateSystem' xmlns:xsi='http://www.w3.org/2001/XMLSchema-instance' xmlns:xs='http://www.w3.org/2001/XMLSchema' xmlns:typens='http://www.esri.com/schemas/ArcGIS/3.1.0'><WKT>PROJCS[&quot;USA_Contiguous_Albers_Equal_Area_Conic_USGS_version&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;Albers&quot;],PARAMETER[&quot;False_Easting&quot;,0.0],PARAMETER[&quot;False_Northing&quot;,0.0],PARAMETER[&quot;Central_Meridian&quot;,-96.0],PARAMETER[&quot;Standard_Parallel_1&quot;,29.5],PARAMETER[&quot;Standard_Parallel_2&quot;,45.5],PARAMETER[&quot;Latitude_Of_Origin&quot;,23.0],UNIT[&quot;Meter&quot;,1.0],AUTHORITY[&quot;Esri&quot;,102039]]</WKT><XOrigin>-16901100</XOrigin><YOrigin>-6972200</YOrigin><XYScale>10000</XYScale><ZOrigin>-100000</ZOrigin><ZScale>10000</ZScale><MOrigin>-100000</MOrigin><MScale>10000</MScale><XYTolerance>0.001</XYTolerance><ZTolerance>0.001</ZTolerance><MTolerance>0.001</MTolerance><HighPrecision>true</HighPrecision><WKID>102039</WKID><LatestWKID>102039</LatestWKID></ProjectedCoordinateSystem> 20240103 14462500 20240103 14462500 150000000 5000 ItemDescription PAD-US Team USGS Science Analytics and Synthesis (SAS) PAD-US Dataset Manager 1-888-275-8747 PO Box 25046, MS 302 Denver Colorado 80225 US pad-us@usgs.gov 20220301 ArcGIS Metadata 1.0 U.S. Geological Survey - ScienceBase 1-888-275-8747 Building 810, Mail Stop 302 Denver Colorado 80225 US sciencebase@usgs.gov None. No fees are applicable for obtaining this data-set. The File downloads in a .zip format https://doi.org/10.5066/P9Q9LQ4B Download or view data from https://www.usgs.gov/gapanalysis/PAD-US/ or https://doi.org/10.5066/P9Q9LQ4B . The PAD-US version 3.0 data was developed using an Esri ArcGIS version 10.6 File Geodatabase format to utilize the expanded capabilities of the File Geodatabase for overall size, attribute name length, attribute aliases, coded domain values and topology analysis tools (See PAD_US3_0_GDB.zip attached in this data release). Users may download a shapefile (.shp), Keyhole Markup Language (.kmz), and ArcGIS version 10.x file geodatabase (.gdb) formats at https://www.usgs.gov/gapanalysis/PAD-US-data-download . Various Web Mapping Services ( https://www.usgs.gov/gapanalysis/PAD-US-web-services ) and poster maps ( https://www.usgs.gov/gapanalysis/PAD-US-resources ) are also available. https://www.usgs.gov/programs/gap-analysis-project/science/pad-us-data-overview https://www.usgs.gov/gapanalysis/PAD-US https://doi.org/10.5066/P9Q9LQ4B File Geodatabase Feature Class PADUS3_NorthCarolina 2022-01-31 3.0 U.S. Geological Survey (USGS) https://www.usgs.gov/gapanalysis/PAD-US/ U.S. Geological Survey (USGS) Gap Analysis Project (GAP) vector and tabular digital data PAD-US Version 3.0 Protected Areas Database of the United States (PAD-US) <DIV STYLE="text-align:Left;"><DIV><P><SPAN>The USGS Protected Areas Database of the United States (PAD-US) is the nation's inventory of protected areas, including public land and voluntarily provided private protected areas, identified as an A-16 National Geospatial Data Asset in the Cadastre Theme ( https://communities.geoplatform.gov/ngda-cadastre/ ). The PAD-US is an ongoing project with several published versions of a spatial database including areas dedicated to the preservation of biological diversity, and other natural (including extraction), recreational, or cultural uses, managed for these purposes through legal or other effective means. The database was originally designed to support biodiversity assessments; however, its scope expanded in recent years to include all open space public and nonprofit lands and waters. Most are public lands owned in fee (the owner of the property has full and irrevocable ownership of the land); however, permanent and long-term easements, leases, agreements, Congressional (e.g. 'Wilderness Area'), Executive (e.g. 'National Monument'), and administrative designations (e.g. 'Area of Critical Environmental Concern') documented in agency management plans are also included. The PAD-US strives to be a complete inventory of U.S. public land and other protected areas, compiling “best available” data provided by managing agencies and organizations. The PAD-US geodatabase maps and describes areas using thirty-six attributes and five separate feature classes representing the U.S. protected areas network: Fee (ownership parcels), Designation, Easement, Marine, Proclamation and Other Planning Boundaries. An additional Combined feature class includes the full PAD-US inventory to support data management, queries, web mapping services, and analyses. The Feature Class (FeatClass) field in the Combined layer allows users to extract data types as needed. A Federal Data Reference file geodatabase lookup table (PADUS3_0Combined_Federal_Data_References) facilitates the extraction of authoritative federal data provided or recommended by managing agencies from the Combined PAD-US inventory. This PAD-US Version 3.0 dataset includes a variety of updates from the previous Version 2.1 dataset (USGS, 2020, https://doi.org/10.5066/P92QM3NT ), achieving goals to: 1) Annually update and improve spatial data representing the federal estate for PAD-US applications; 2) Update state and local lands data as state data-steward and PAD-US Team resources allow; and 3) Automate data translation efforts to increase PAD-US update efficiency. The following list summarizes the integration of "best available" spatial data to ensure public lands and other protected areas from all jurisdictions are represented in the PAD-US (other data were transferred from PAD-US 2.1). Federal updates - The USGS remains committed to updating federal fee owned lands data and major designation changes in annual PAD-US updates, where authoritative data provided directly by managing agencies are available or alternative data sources are recommended. The following is a list of updates or revisions associated with the federal estate: 1) Major update of the Federal estate (fee ownership parcels, easement interest, and management designations where available), including authoritative data from 8 agencies: Bureau of Land Management (BLM), U.S. Census Bureau (Census Bureau), Department of Defense (DOD), U.S. Fish and Wildlife Service (FWS), National Park Service (NPS), Natural Resources Conservation Service (NRCS), U.S. Forest Service (USFS), and National Oceanic and Atmospheric Administration (NOAA). The federal theme in PAD-US is developed in close collaboration with the Federal Geographic Data Committee (FGDC) Federal Lands Working Group (FLWG, https://communities.geoplatform.gov/ngda-govunits/federal-lands-workgroup/ ). 2) Improved the representation (boundaries and attributes) of the National Park Service, U.S. Forest Service, Bureau of Land Management, and U.S. Fish and Wildlife Service lands, in collaboration with agency data-stewards, in response to feedback from the PAD-US Team and stakeholders. 3) Added a Federal Data Reference file geodatabase lookup table (PADUS3_0Combined_Federal_Data_References) to the PAD-US 3.0 geodatabase to facilitate the extraction (by Data Provider, Dataset Name, and/or Aggregator Source) of authoritative data provided directly (or recommended) by federal managing agencies from the full PAD-US inventory. A summary of the number of records (Frequency) and calculated GIS Acres (vs Documented Acres) associated with features provided by each Aggregator Source is included; however, the number of records may vary from source data as the "State Name" standard is applied to national files. The Feature Class (FeatClass) field in the table and geodatabase describe the data type to highlight overlapping features in the full inventory (e.g. Designation features often overlap Fee features) and to assist users in building queries for applications as needed. 4) Scripted the translation of the Department of Defense, Census Bureau, and Natural Resource Conservation Service source data into the PAD-US format to increase update efficiency. 5) Revised conservation measures (GAP Status Code, IUCN Category) to more accurately represent protected and conserved areas. For example, Fish and Wildlife Service (FWS) Waterfowl Production Area Wetland Easements changed from GAP Status Code 2 to 4 as spatial data currently represents the complete parcel (about 10.54 million acres primarily in North Dakota and South Dakota). Only aliquot parts of these parcels are documented under wetland easement (1.64 million acres). These acreages are provided by the U.S. Fish and Wildlife Service and are referenced in the PAD-US geodatabase Easement feature class 'Comments' field. State updates - The USGS is committed to building capacity in the state data-steward network and the PAD-US Team to increase the frequency of state land updates, as resources allow. The USGS supported efforts to significantly increase state inventory completeness with the integration of local parks data in the PAD-US 2.1, and developed a state-to-PAD-US data translation script during PAD-US 3.0 development to pilot in future updates. Additional efforts are in progress to support the technical and organizational strategies needed to increase the frequency of state updates. The PAD-US 3.0 included major updates to the following three states: 1) California - added or updated state, regional, local, and nonprofit lands data from the California Protected Areas Database (CPAD), managed by GreenInfo Network, and integrated conservation and recreation measure changes following review coordinated by the data-steward with state managing agencies. Developed a data translation Python script (see Process Step 2 Source Data Documentation) in collaboration with the data-steward to increase the accuracy and efficiency of future PAD-US updates from CPAD. 2) Virginia - added or updated state, local, and nonprofit protected areas data (and removed legacy data) from the Virginia Conservation Lands Database, provided by the Virginia Department of Conservation and Recreation's Natural Heritage Program, and integrated conservation and recreation measure changes following review by the data-steward. 3) West Virginia - added or updated state, local, and nonprofit protected areas data provided by the West Virginia University, GIS Technical Center. For more information regarding the PAD-US dataset please visit, https://www.usgs.gov/gapanalysis/PAD-US/. For more information about data aggregation please review the PAD-US Data Manual available at https://www.usgs.gov/core-science-systems/science-analytics-and-synthesis/gap/pad-us-data-manual . A version history of PAD-US updates is summarized below (See https://www.usgs.gov/core-science-systems/science-analytics-and-synthesis/gap/pad-us-data-history for more information): 1) First posted - April 2009 (Version 1.0 - available from the PAD-US: Team pad-us@usgs.gov). 2) Revised - May 2010 (Version 1.1 - available from the PAD-US: Team pad-us@usgs.gov). 3) Revised - April 2011 (Version 1.2 - available from the PAD-US: Team pad-us@usgs.gov). 4) Revised - November 2012 (Version 1.3) https://doi.org/10.5066/F79Z92XD 5) Revised - May 2016 (Version 1.4) https://doi.org/10.5066/F7G73BSZ 6) Revised - September 2018 (Version 2.0) https://doi.org/10.5066/P955KPLE 7) Revised - September 2020 (Version 2.1) https://doi.org/10.5066/P92QM3NT 8) Revised - January 2022 (Version 3.0) https://doi.org/10.5066/P9Q9LQ4B Comparing protected area trends between PAD-US versions is not recommended without consultation with USGS as many changes reflect improvements to agency and organization GIS systems, or conservation and recreation measure classification, rather than actual changes in protected area acquisition on the ground.</SPAN></P></DIV></DIV> The PAD-US geodatabase was originally developed to organize and assess the management status (i.e. apply 'GAP Status Code') of elements of biodiversity protection by identifying species and plant communities not adequately represented in existing conservation lands ( https://www.usgs.gov/core-science-systems/science-analytics-and-synthesis/gap ). In cooperation with the United Nations Environment Programme World Conservation Monitoring Centre (UNEP-WCMC), PAD-US also supports global conservation analyses to inform policy decisions ( https://www.protectedplanet.net/country/USA , https://www.protectedplanet.net/en/resources/global-reports ). The dataset is robust and has been expanded in recent years with major additions of local parks data to PAD-US 2.1, to support the recreation, natural resource management, wildfire planning, emergency management, transportation, research, and public health communities. New applications of the data are frequently discovered. Multiple attributes and a flexible database structure provide context for data to be used at local, regional, state, national, and international scales. See https://www.usgs.gov/gapanalysis/PAD-US-resources for more information. U.S. Geological Survey (USGS) Gap Analysis Project (GAP), 2022, Protected Areas Database of the United States (PAD-US) 3.0: U.S. Geological Survey data release, https://doi.org/10.5066/P9Q9LQ4B PAD-US Team USGS Science Analytics and Synthesis (SAS) PAD-US Dataset Manager 1-888-275-8747 PO Box 25046, MS 302 Denver Colorado 80225 US pad-us@usgs.gov Common geographic areas United States New Jersey (NJ) South Carolina (SC) Kentucky (KY) Iowa (IA) Minnesota (MN) Tennessee (TN) Alaska (AK) West Virginia (WV) Mariana Islands (MP) Puerto Rico (PR) New Mexico (NM) Indiana (IN) Delaware (DE) Oregon (OR) U.S. Minor Outlying Islands (UM) Hawaii (HI) Utah (UT) North Dakota (ND) Arizona (AZ) Colorado (CO) Kansas (KS) Oklahoma (OK) Georgia (GA) Idaho (ID) Washington (WA) Connecticut (CT) Arkansas (AR) Texas (TX) Louisiana (LA) Wyoming (WY) Maryland (MD) Florida (FL) Nevada (NV) Missouri (MO) Alabama (AL) South Dakota (SD) United States Ohio (OH) Montana (MT) Wisconsin (WI) New Hampshire (NH) Virginia (VA) American Samoa (AS) Illinois (IL) Guam (GU) Maine (ME) Nebraska (NE) Massachusetts (MA) California (CA) New York (NY) Mississippi (MS) North Carolina (NC) Michigan (MI) Vermont (VT) Rhode Island (RI) Pennsylvania (PA) United States Virgin Islands (VI) 2015 2005 2010 2007 2017 2006 2012 2011 2009 2020 2014 2008 2021 2018 2013 2019 2016 USGS Thesaurus Land Use Change Protected Area Land Use and Land Cover Geography NGDA Portfolio Themes Cadastre Theme NGDAID27 NGDA National Geospatial Data Asset Land Stewardship Gap Analysis Land Ownership Protected Area NGDAID27 State Lands Public Open Space Cadastre Theme Protection Status Local Government Lands National Geospatial Data Asset NGDA Portfolio Themes Land Manager Private Lands Public Health Parks Governmental Units Conservation Outdoor Recreation Federal Lands Biodiversity NGDA IUCN Category Public Lands GAP Status Code Federal Agencies and Programs Forest Service Bureau of Reclamation Department of Energy Tennessee Valley Authority Bureau of Land Management Army Corps of Engineers National Park Service Department of Defense Agricultural Research Service National Oceanic and Atmospheric Administration U.S. Fish and Wildlife Service Natural Resources Conservation Service Land Use Change Land Stewardship New Jersey (NJ) 2015 South Carolina (SC) Forest Service Kentucky (KY) 2005 Protected Area Cadastre Theme Iowa (IA) Minnesota (MN) Gap Analysis 2010 NGDAID27 Bureau of Reclamation Department of Energy 2007 Tennessee (TN) Alaska (AK) Land Ownership Protected Area West Virginia (WV) Mariana Islands (MP) Puerto Rico (PR) New Mexico (NM) Tennessee Valley Authority Indiana (IN) NGDAID27 2017 State Lands Public Open Space Delaware (DE) Oregon (OR) U.S. Minor Outlying Islands (UM) Cadastre Theme Protection Status Local Government Lands NGDA National Geospatial Data Asset NGDA Portfolio Themes Hawaii (HI) Land Manager 2006 Bureau of Land Management Army Corps of Engineers Utah (UT) National Park Service North Dakota (ND) Arizona (AZ) Colorado (CO) 2012 Private Lands Kansas (KS) Oklahoma (OK) 2011 Georgia (GA) Idaho (ID) Washington (WA) 2009 United States 2020 Connecticut (CT) Arkansas (AR) Texas (TX) Louisiana (LA) Wyoming (WY) Maryland (MD) Florida (FL) Public Health Land Use and Land Cover Nevada (NV) 2014 Parks Governmental Units Missouri (MO) Alabama (AL) Conservation South Dakota (SD) Outdoor Recreation United States Federal Lands Ohio (OH) Montana (MT) Wisconsin (WI) Biodiversity New Hampshire (NH) Virginia (VA) 2008 Department of Defense Agricultural Research Service American Samoa (AS) Illinois (IL) Guam (GU) Maine (ME) NGDA 2021 Nebraska (NE) IUCN Category Massachusetts (MA) California (CA) Public Lands New York (NY) National Oceanic and Atmospheric Administration Mississippi (MS) 2018 North Carolina (NC) U.S. Fish and Wildlife Service Michigan (MI) Vermont (VT) Rhode Island (RI) Natural Resources Conservation Service 2013 2019 GAP Status Code National Geospatial Data Asset Pennsylvania (PA) 2016 United States Virgin Islands (VI) Geography Unless otherwise stated, all data, metadata and related materials are considered to satisfy the quality standards relative to the purpose for which the data were collected. Although these data and associated metadata have been reviewed for accuracy and completeness and approved for release by the U.S. Geological Survey (USGS), no warranty expressed or implied is made regarding the display or utility of the data on any other system or for general or scientific purposes, nor shall the act of distribution constitute any such warranty. This database, identified as PAD-US version 3.0, has been approved for release by the U.S. Geological Survey (USGS). Although this database has been subjected to rigorous review and is substantially complete, the USGS reserves the right to revise the data pursuant to further analysis and review. These data are in the public domain. <DIV STYLE="text-align:Left;"><DIV><P><SPAN>The Digital Object Identifier https://doi.org/10.5066/P9Q9LQ4B for PAD-US 3.0 provides the persistent reference that should be used to obtain the data for use. The U.S. Geological Survey and all contributing data partners shall not be held liable for improper or incorrect use of the data described and (or) contained herein. All information is created with a specific end use or uses in mind. This is especially true for GIS data, which is expensive to produce and must be directed to meet the immediate program needs. These data were created with the expectation that they would be used for other applications; however, inappropriate uses are listed below. This list is in no way exhaustive but should serve as a guide to assess whether a proposed use can or cannot be supported by these data. For many uses, it is unlikely that PAD-US will provide the only data needed, and for uses with a regulatory outcome, authoritative agency data and field surveys should verify the result. PAD-US is recommended for users seeking general information about more than one agency or organization's lands. Users should seek authoritative source data directly to answer questions regarding one agency or those requiring more frequent updates (See PAD-US Steward Reports for contacts and agency data download locations: http://www.protectedlands.net/data-stewards/ ). The PAD-US includes the best available representation of federally owned lands (meaning a federal agency or the U.S. holds the title records), developed from authoritative source data in direct collaboration with federal agency data-stewards. Several ownership related data gaps exist and USGS provides no legal warranty. Agencies are always the official and best source of their land data and some update more frequently than PAD-US. The FGDC Federal Lands Working Group recommends the use of PAD-US to describe federally managed lands (i.e. “Manager Name” not “Owner Name”), unless spatial data inventory completeness is over 95% and appropriate scale for display is 1:24,000 as illustrated in “State of PAD-US Data” (e.g. USFS, USFWS, NPS, BLM, DOD) - a graphical summary of inventory completeness, appropriate scale, and update frequency at: https://communities.geoplatform.gov/ngda-govunits/wp-content/uploads/2021/02/StateofPADUS_Feb2021.pdf ) . Ultimately, it is the responsibility of each data user to determine if these data can answer the question being asked. Furthermore, the database is released on condition that neither the USGS nor the U.S. Government shall be held liable for any damages resulting from its authorized or unauthorized use. Inappropriate uses include: Using PAD-US for applications or analyses associated with one agency or a particular unit (agencies are always the best and authoritative source of their land data and many publish updates more frequently than PAD-US). Using data to map small areas, typically requiring mapping resolution at scale finer than 1:24,000, as boundary quality varies by data source (See "State of PAD-US Data") and using aerial photographs or ground surveys in areas where data are incomplete. Combining these data with other data finer than 1:100,000 scale (except for select federal agencies or states identified in "State of PAD-US Data") to produce new hybrid maps or answer queries. Generating specific areal measurements from the data finer than the nearest thousand hectares. Representing boundaries as a legal representation for regulation or acquisition. Establishing definite occurrence or non-occurrence of any feature for an exact geographic area. Determining abundance, health, or condition of any feature. Using the data without acquiring and reviewing the metadata.</SPAN></P></DIV></DIV> Protected Areas Database of the United States (PAD-US) 2022-01-31 3.0 USGS Gap Analysis Project vector digital data https://www.usgs.gov/gapanalysis/PAD-US Protected Areas Database of the United States (PAD-US) 2022-01-31 3.0 U.S. Geological Survey (USGS) https://www.usgs.gov/gapanalysis/PAD-US/ USGS Gap Analysis Project geodatabase https://www.usgs.gov/gapanalysis/PAD-US/ Environment as of Metadata Creation: Microsoft Windows Server 2012 R2 Standard; Python 9.3; Esri ArcGIS 10.6 (Build 8321), PAD_US3_0.gdb (1.01 GB) -180 180 -15.3861 71.312 publication date 2005-01-01 2021-01-01 The PAD-US database strives to be a complete inventory of areas dedicated to the preservation of biological diversity, and other natural (including extraction), recreational or cultural uses, managed for these purposes through legal or other effective means. PAD-US is an aggregation of “best available” spatial data provided by agencies and organizations at a point in time. This includes both fee ownership of lands as well as management through leases, easements, or other binding agreements. The inventory also includes Congressional designations, Executive designations, and administrative designations identified in management plans (e.g. Bureau of Land Management 'Area of Critical Environmental Concern'). These factors provide for a robust dataset offering a spatial representation of the complex U.S. protected areas network. It is important to have in mind a specific analysis question when approaching how to work with the data. As a full inventory of areas aggregated from authoritative source data whenever possible, PAD-US includes overlapping designation types and small boundary discrepancies between agency datasets. Overlapping designations mainly occur in the Federal estate of the 'Designation' or 'Combined' feature class (e.g. 'Wild and Scenic River' over a 'Wilderness Area' both within a 'National Forest' boundary or a 'State Wildlife Area' over Federal Fee owned land). See the Entity_and_Attribute_Information Section for more information about PAD-US feature classes. It is important to note the presence of overlaps especially when trying to calculate area statistics; overlapping boundaries count the same area of ground multiple times. While minor boundary discrepancies remain, most major overlaps have been removed from the 'Fee' feature class and this is the best source for overall land area calculations by land manager ('Manager Name') within the PAD-US database (data gaps limit calculations by fee ownership or 'Owner Name'). Statistics summarizing 'Public Access' or Protection Status ('GAP Status Code') by managing agency or organization from an analysis of the PAD-US 'Combined' feature class are available at https://www.usgs.gov/core-science-systems/science-analytics-and-synthesis/gap/science/pad-us-statistics-and-reports . The PAD-US database is a direct aggregation of source data and the PAD-US development team rarely alters spatial linework. Exceptions are: 1) to “clip” polygon boundaries along State legal boundary lines (using the annually updated, national, authoritative State boundary file provided by the U.S. Census Bureau, https://www2.census.gov/geo/tiger/TGRGDB20/tlgdb_2020_a_us_substategeo.gdb.zip ), 2) to remove the small segments of boundaries created by this process associated with State or local lands (not Federal or nonprofit lands), and 3) to integrate Bureau of Land Management Field or District Office boundaries into the large boundaries representing National Public Lands (mainly across the West) to attribute PAD-US "Unit Name" and support PAD-US applications (e.g. Wildland Fire Decision Tools). Some boundary discrepancies (or slivers) remain in the dataset. Data overlaps are shared (see 'Processing Step 10 Fee Topology Assessment' in this data release or Fee Topology web services in the PAD-US Viewer, https://maps.usgs.gov/padus/ ), along with the U.S. Census Bureau national State jurisdictional boundary standard (updated annually) with PAD-US data-stewards to facilitate edits in source files, as appropriate, that will then be incorporated into subsequent PAD-US versions over time. This PAD-US Version 3.0 dataset includes a variety of updates and improvements (listed in the abstract) to address user needs from the previous version 2.1 dataset. The PAD-US database is built in collaboration with many partners and data-stewards. Information regarding data-stewards is available at https://www.usgs.gov/core-science-systems/science-analytics-and-synthesis/gap/science/pad-us-data-stewards . Story maps, presentations, and other descriptions of the PAD-US and applications include: 1) U.S. Geological Survey (USGS) Gap Analysis Project (GAP), 2022, Protected Areas Database of the United States (PAD-US) 3.0 Spatial Analysis and Statistics: U.S. Geological Survey (USGS), https://doi.org/10.5066/P9KLBB5D . 2) Conserving and Restoring American the Beautiful, 2021: A preliminary report to the National Climate Task Force recommending a ten-year, locally led campaign to conserve and restore the lands and waters upon which we all depend, and that bind us together as Americans ( https://www.doi.gov/sites/doi.gov/files/report-conserving-and-restoring-america-the-beautiful-2021.pdf ) . 3) U.S. Geological Survey, 2021, Analysis of Updated USGS Database Finds Increase in America’s Lands and Waters Managed for Biodiversity. U.S. Geological Survey Technical Announcement: https://www.usgs.gov/news/analysis-updated-usgs-database-finds-increase-america-s-lands-and-waters-managed-biodiversity . 4) 2021 National Park Service's Connected Conservation Seminar Series. Protected Areas Database with USGS ( https://www.nps.gov/articles/000/c2-pad-us.htm ). 5) Davidson, A.; Dunn, L.; Gergely, K.; McKerrow, A.; Williams, S.; Case, M. Refining the coarse filter approach: Using habitat-based species models to identify rarity and vulnerabilities in the protection of U.S. biodiversity. Global Ecolology and Conservation, Volume 28. 2021. https://doi.org/10.1016/j.gecco.2021.e01598 . 6) 2021 The State of PAD-US Data: Completeness, Scale, and Update Frequency for Source Data in the Protected Areas Database of the U.S. (3.0) as of November 2021 ( https://communities.geoplatform.gov/ngda-govunits/wp-content/uploads/2021/11/StateofPADUS_Nov2021.pdf ). 7) U.S. Geological Survey (USGS) - GAP Analysis Project (GAP), 2021, Protected Areas Database of the United States (PAD-US) 2.1 - World Database on Protected Areas (WDPA) Submission (ver 1.1, April 2021): U.S. Geological Survey data release, https://doi.org/10.5066/P9IVLRSS. 8) Morgan, J.; Rhoden, C.; White, B.; Riley, S. A state assessment of private lands wildlife conservation in the United States. Wildlife Society Bulletin, Volume 43, Issue 3. 2019. https://doi.org/10.1002/wsb.997 . 9) Completing America’s Inventory of Public Parks and Protected Areas: An Action Plan for 2016 - 2020: https://www.protectedlands.net/vision/ . 10) Online PAD-US Help System: http://www.protectedlands.net/help/ . 11) 2020 USGS Supports Wildland Fire Decision Support: http://www.protectedlands.net/uses/usgs-supports-wildland-fire-decision-support/ . 12) 2019 How to Use PAD-US in Base Maps - Guidelines for Incorporating Public Park and Related Protected Areas Data for the U.S. into Online Base Maps ( https://communities.geoplatform.gov/ngda-govunits/wp-content/uploads/2019/09/Guidelines-for-Base-Maps-Data-Use_Version17Sept2019.pdf ). 13) 2019 PAD-US Helps Connect Trail Systems Nationally: http://www.protectedlands.net/uses/pad-us-helps-connect-trail-systems-nationally/ . 14) 2018 New Federal Lands Recreation Poster Map: http://www.protectedlands.net/uses/new-federal-recreation-lands-poster/ . 15) 2018 DOI Office of Policy Analysis Seminar: The New and Improved PAD-US 2.0 (with FGDC Federal Lands Working Group panel): https://communities.geoplatform.gov/ngda-govunits/wp-content/uploads/2021/12/DOI_PPA_Seminar_PDF2018July9_FINAL.pdf . 16) 2017 DOI Office of Policy Analysis Seminar: All of America’s Parks and Protected Areas - Building and Using the PAD-US (with Federal Lands Working Group panel): https://communities.geoplatform.gov/ngda-govunits/wp-content/uploads/2021/12/PADUS-DOI-PPA_Seminar_Final2017.pdf . 17) Johnson, Lisa, Croft, Mason, and Larry Orman. 2017. "Building a complete GIS database of protected areas: USGS leads inventory of lands in the public interest." Esri ArcNews. Spring 2017. Volume 39, Number 2. https://www.esri.com/about/newsroom/arcnews/building-a-complete-gis-database-of-protected-areas/ . 18) 2017 PAD-US and City Parks: http://www.protectedlands.net/uses/pad-us-and-cityregional-park-agencies/ . 19) 2017 The Lands We Share: America’s Protected Areas: https://storymaps.esri.com/stories/2017/protected-areas/ . 20) Jarvis, Jonathan B. A Report on North American Conservation. Presented on behalf of NAWPA. 2016 World Conservation Congress: https://story.maps.arcgis.com/apps/Cascade/index.html?appid=6d3a412ee9f34ce7868667bda19e5679 . 21) NAWPA Committee. 2016. Conservation in North America: An analysis of land-based conservation in Canada, Mexico, and the United States by NAWPA agencies. Report. North American Intergovernmental Committee on Cooperation for Wilderness and Protected Area Conservation; Canada, Mexico, and the United States of America. http://nawpacommittee.org/wp-content/uploads/2016/08/Conservation-in-North-America.pdf . 22) Grant, Tamara. 2017. Federal Agencies Working Together to Improve Data in the Living Atlas. Esri ArcGIS Blog, Analytics: https://www.esri.com/arcgis-blog/products/arcgis-living-atlas/analytics/federal-agencies-working-together-to-improve-data-in-the-living-atlas/ . 23) Building Green Infrastructure in the U.S: A Framework for Sustainable Growth: https://www.esri.com/en-us/industries/green-infrastructure/overview . 1 -180.000000 180.000000 90.000000 -30.225858 Boundary discrepancies (mostly small slivers) between agency datasets and major overlaps associated with fee ownership (mostly between Federal and State lands) have been identified and are shared with data-stewards, who will edit source files as appropriate and resources allow. Users are encouraged to review topology overlap errors associated with the PAD-US 3.0 Fee Topology Overlap Assessment (see 'Processing Step 10 Fee Topology Assessment' attached in this data release or Fee Topology web services in the PAD-US Viewer, https://maps.usgs.gov/padus/) for reference. The topology assessment identifies all overlaps (minimum distance between feature coordinates to evaluate overlap relationship = 0.05 meter), large (greater than 5 acres) and small (less than 5 acres) overlaps, between Federal lands and between Federal and State agency lands in the Fee feature class. Boundary discrepancies (mostly small slivers) between agency datasets and major overlaps associated with fee ownership (mostly between Federal and State lands) have been identified and are shared with data-stewards, who will edit source files as appropriate and resources allow. Users are encouraged to review topology overlap errors associated with the PAD-US 3.0 Fee Topology Overlap Assessment (see 'Processing Step 10 Fee Topology Assessment' attached in this data release or Fee Topology web services in the PAD-US Viewer, https://maps.usgs.gov/padus/) for reference. The topology assessment identifies all overlaps (minimum distance between feature coordinates to evaluate overlap relationship = 0.05 meter), large (greater than 5 acres) and small (less than 5 acres) overlaps, between Federal lands and between Federal and State agency lands in the Fee feature class. This dataset is considered complete for the information presented, as described in the abstract and supplemental information section. Estimated completeness of the PAD-US 2.1 inventory, by Federal agency or State, is available at http://www.protectedlands.net/data-stewards. This information will be updated, with partners, after an assessment of PAD-US 3.0 following the data release. Qualitative completeness estimates balance acres inventoried and the quality of data/attributes in each inventory, including fee owned parcels, easement interests, and major designations. For example, Federal agencies estimate the percent completeness of lands data submitted for PAD-US 2.1 as: NPS (95%), USFS (99%), FWS (89%), BLM (85%), U.S. Army Corps of Engineers (USACE) (80%), Department of Defense (DOD) (79%), U.S. Bureau of Reclamation (USBR) (50%), NRCS (85%), Bureau of Ocean Energy Management (BOEM) (95%), National Oceanic and Atmospheric Administration (NOAA) (95%), California (95%), West Virginia (70%), and Virginia (95%). USGS seeks to increase the completeness, efficiency, and accuracy of PAD-US updates in collaboration with data-stewards as summarized in, "State of PAD-US Data" ( https://communities.geoplatform.gov/ngda-govunits/wp-content/uploads/2021/02/StateofPADUS_Feb2021.pdf , periodic updates available on FLWG website), "Completing America's Inventory of Public Parks and Protected Areas: An Action Plan for 2016 - 2020" (November, 2016), and "A Map of the Future", published following the PAD-US Design Project (July, 2009) available at https://www.usgs.gov/core-science-systems/science-analytics-and-synthesis/gap/science/pad-us-vision . As a compilation of many datasets, attribute completeness and accuracy may vary. Federal and state data providers reviewed the translation of their spatial data files into the PAD-US schema and several provide data in the PAD-US format. In addition, the PAD-US Team summarized and reviewed the final aggregated database and each feature class for overall attribute accuracy and consistency as described in the PAD-US 3.0 Review Summary Tables (See Process Step 9) attached in this data release. As a compilation of many datasets, attribute completeness and accuracy may vary. Federal data providers reviewed the translation of their spatial data files into the PAD-US schema. In addition, the PAD-US Team summarized and reviewed the final aggregated database and each feature class for overall attribute accuracy and consistency as described in PAD-US 3.0 Review Summary Tables (See Process Step 9 attached in this data release). A formal accuracy assessment of the vertical positional information in the data set is not applicable. PAD-US 3.0 Planning, Blank Schema, and Data Manual: The PAD-US database aggregation involves the compilation of thousands of agency and nonprofit organization source data files from a network of nearly 100 data-stewards, with select updates prioritized annually based on needs, the availability of source data, and resources. The USGS is committed to building capacity in the state data-steward network and the PAD-US Team to increase the frequency of state land updates as resources allow. The USGS supported efforts to complete state inventories with the integration of local parks data in the PAD-US 2.1, and tested a state-to-PAD-US data translation script during PAD-US 3.0 development. Additional efforts are in progress to support the technical and organizational strategies needed to increase the frequency of state updates. The PAD-US 3.0 included major updates to the federal estate, CA, WV, and VA. The first processing step in the PAD-US development was to update the Blank PAD-US schema (Process Step 1, Create Blank Schema attached in this data release) in response to data-steward and user feedback and the PAD-US Action Plan ( https://www.usgs.gov/core-science-systems/science-analytics-and-synthesis/gap/science/pad-us-vision ). The blank schema provides a blueprint of the database for the PAD-US Team to load input files for PAD-US aggregation and it is shared with data-stewards seeking to submit source data in the PAD-US format. Data aggregation and development are an ongoing and evolving process as land management agency and nonprofit organization GIS systems mature and stakeholder feedback improve the process. The PAD-US Data Manual and schema has changed over time to better reflect user needs, with the majority of changes reflected in the PAD-US 2.0 providing a more stable format to further develop data partnerships and increase automation. The schema includes all the components to build the PAD-US 3.0, including the multiple feature class structure ('Fee', 'Designation', 'Easement', 'Proclamation', 'Marine', 'Combined'), core attributes, and all standardized domain tables ('State Name', 'IUCN Category', 'GAP Status Code', 'Designation Type', 'Category', 'Agency Type', 'Agency Name', 'Public Access'). A "Feature Class" (FeatClass) field is available in the fully Combined layer to describe which feature class the data originated from and for users to extract data types as needed (see Federal Data Reference lookup table for authoritative federal data). The 'Marine' and 'Easement' feature classes also include fields (in addition to PAD-US core attributes) unique to the NOAA Marine Protected Areas Inventory and National Conservation Easement Database. In addition, the Blank PAD-US 3.0 Schema includes the U.S. Census Bureau State file (from the national sub-state geography geodatabase: https://www2.census.gov/geo/tiger/TGRGDB20/tlgdb_2020_a_us_substategeo.gdb.zip ) that serves as the common standard (updated annually) for legal State jurisdictional boundaries, the 'State Name' field in the PAD-US, and the full extent of analysis products. The PAD-US development team works closely with a large variety of stakeholders including development partners, data sources, and data users to develop and maintain the "Data Manual for PAD-US" Table crosswalks (online resource available at https://www.usgs.gov/core-science-systems/science-analytics-and-synthesis/gap/pad-us-data-manual ) . 2021-01-25 Source Data Documentation and Translation: The PAD-US Data-Steward Network includes Federal, State, and nonprofit partners that provide source data files for PAD-US as summarized in online and pdf Steward Reports ( http://www.protectedlands.net/data-stewards/ ). More information about the PAD-US Data-Steward Network is available on the PAD-US website ( https://www.usgs.gov/core-science-systems/science-analytics-and-synthesis/gap/science/pad-us-data-stewards ). Eight federal agencies (BLM, Census Bureau, DOD, FWS, NPS, NRCS, USFS, NOAA) and three state aggregators (CA, WV, VA) delivered data for PAD-US 3.0 or USGS compiled data from agency recommended sources (See details about data contributors and source data files in Process Step 2, Source Data Documentation attached in this data release). The PAD-US Team translated individual source files into the PAD-US format (unless provided by the data-steward in the PAD-US format). 2021-01-29 Quality Assessment and Quality Control: The PAD-US development team uses a Python script to generate a Quality Assessment and Quality Control (QA/QC) report each time a source file is submitted or translated to ensure the major components needed for database aggregation are included (See Process Step 3, PAD-US QA/QC attached in this data release). Subsequent process steps will outline the general workflow and processes used to compile each major component of the final database. 2021-03-15 Local Agency to Agency Name Crosswalk: A Python script was used to crosswalk data provided by PAD-US contributors, referencing the land owner or managing entity for a unit, into standardized PAD-US geodatabase domain tables (See PAD-US Process Step 4 Local Agency to Agency Name Crosswalk attached in this data release). PAD-US retains source data as provided in the 'Local Owner' and 'Local Manager' fields. These fields often provide additional detail to complement the standardized 'Owner Name' and 'Manager Name' fields, respectively. 2021-04-25 Transfer Locally Reviewed Conservation and Recreation Measures from PAD-US 2.1: Input files are compared to the previous PAD-US (version 2.1) to evaluate new records and assign identifiers to join (ExistJoinID) source data updates (input files) with the previous version of PAD-US (2.1). File records are compared via automated scripts tracking attributes and polygon location followed by manual review to ensure existing and locally reviewed data flagged for attribute transfer (ConsMeasTrn) match updates correctly and new records are identified. Once a reliable JoinID is confirmed post review, the Transfer Non Default Conservation Measures Python script transfers value added data managed by USGS (not available in source data) including locally assigned conservation ('GAP Status Code', 'IUCN Category') or recreation access measures ('Public Access'), the World Database on Protected Areas (WDPA) Site ID (a unique identifier assigned by UNEP-WCMC and managed by USGS), and 'Date of Establishment'. See Process Step 5, Reconciliation attached in this data release. 2021-05-15 Categorical Assignments by Designation Type: The areas in PAD-US are assigned conservation measures that assess management intent to permanently protect biological diversity: the nationally relevant 'GAP Status Code' (that also identifies multiple use areas) and the global 'IUCN Category' standard. In addition, a general measure of recreation access ('Public Access') is also assigned. After locally reviewed measures were transferred from PAD-US 2.1 (as described in Process Step 5, Reconciliation) input files are checked for completeness of required attributes and that all domains and standardized field attributes are completely assigned. In the absence of other information (e.g. local assignment or review), 'GAP Status Code', 'IUCN Category', and 'Public Access' are assigned categorically based on 'Designation Type' using a Python script (See Process Step 6 Categorical Assignments by Designation Type attached in this data release) that references crosswalk tables (e.g. Tables 6 and 9) available in the PAD-US Data Manual ( https://www.usgs.gov/core-science-systems/science-analytics-and-synthesis/gap/pad-us-data-manual ). 2021-07-02 Multiple Feature Class Implementation: The major feature of PAD-US 2.0 involved the expansion of the multiple feature class database structure; primarily, the removal of overlapping management designations from fee owned lands. The expanded structure, defined by the addition of the "Designation" feature class was replicated in PAD-US 2.1 and 3.0. Building on Federal Lands Working Group ( https://communities.geoplatform.gov/ngda-govunits/federal-lands-workgroup/ ) efforts to collaboratively develop PAD-US, it was fairly straightforward to determine feature class placement of Federal spatial data. Federal data-stewards defined the 'Category' (the data type field in PAD-US) associated with source data submitted for PAD-US as fee parcels, easement interest, leases, agreements, overlapping management designations, proclamation, or marine boundaries. An automated Python script process compared State and other overlaps to Federal fee data to determine feature class placement (See Process Step 7, Multiple Feature Class attached in this data release). 2021-07-12 Database Aggregation and Load Order: Input files referenced in the “Source Data Collection and Translation" processing step above are aggregated into the PAD-US geodatabase in a purposeful load order to achieve the necessary visual and analytical results associated with current database technology (See Process Step 8, Load Order attached in this data release). Load order strives to account for boundary size, type, and spatial data quality, to increase the likelihood overlapping features are visible on maps and to support assessments of biodiversity protection status or outdoor recreation access. Files in the PAD-US geodatabase feature class loaded first, remain on the bottom in cases of overlap. Feature classes are manually loaded separately (agencies referenced below are listed in geodatabase load order within their respective feature classes - bottom to top) before the PAD-US 3.0 'Combined' feature classes are created. For example, the full 'PADUS3_0Combined_Proclamation_Marine_Fee_Designation_Easement' feature class represents this load order (PAD-US feature class and a general description of agency source data listed from the bottom to the top): 1) 'Proclamation' feature class (FWS Approved Acquisition, USFS Proclamation Boundaries, NPS Proclamation Boundaries, DOD Military Lands, Census American Indian Areas [AIA] ); 2) 'Marine' feature class (BOEM Blocks, NOAA Marine Protected Areas Inventory); 3) Federal fee lands (Department Of Energy (DOE), Tennessee Valley Authority (TVA), Agricultural Research Service (ARS) legacy data transferred from the previous PAD-US, BLM public lands from Surface Management Area database, USBR legacy data transferred from the previous PAD-US, USACE lands transferred from the previous PAD-US, USFS fee parcel data, NPS fee parcel data, FWS fee parcel data); 4) State and local government fee lands, in alphabetical order by State; 5) Federal designations (USBR designations, BLM ACEC (transferred from the previous PAD-US), BLM Monuments/National Conservation Areas/Similar, USACE reservoirs (transferred from the previous PAD-US), USFS Inventory Roadless Areas, BLM Wilderness Study Areas, NPS Other Categories of Wilderness, NPS designations, USFS Withdrawals, USFS designations, USFS Special Interest Management areas, BLM Wilderness, USFS Wilderness, USFS Wild and Scenic Rivers, NPS Legislated Wilderness (from Wilderness.net), FWS Special Designations, BLM Wild and Scenic Rivers); 6) State and Local designations, in alphabetical order by State (mostly transferred from the previous PAD-US); 7) Easements (often small) are loaded last to remain visible on top of overlapping records. The PAD-US 3.0 update includes federal easements provided directly by managing agencies only - all other easements transferred from PAD-US 2.1 are from a subset of the National Conservation Easement Database for PAD-US (non-sensitive easements suitable for distribution in the public domain published February 2018). 2021-08-10 PAD-US 3.0 Review: Once all attributes are assigned and feature classes are aggregated, the PAD-US development team conducts a final review by summarizing the database (See Process Step 9, Review Summary Tables attached in this data release) and reviewing tables associated with each feature class. In addition, 'GIS Acres' are compared to known sources and spatial data are compared to previous PAD-US versions. Federal Lands Working Group data-stewards reviewed the translation of authoritative spatial data (federal lands and waters) into the PAD-US format and USFS, NPS, and FWS provide data in the PAD-US format. In addition, Quality Control / Quality Assurance (QA/QC) reports documenting edits to source data to meet PAD-US requirements are shared with data-stewards to continually improve update efficiency and accuracy. 2021-08-18 Data quality assessment and appropriate use of federal spatial data: The PAD-US Team and FLWG recommends users review “The State of PAD-US Data” ( https://communities.geoplatform.gov/ngda-govunits/wp-content/uploads/2021/02/StateofPADUS_Feb2021.pdf , periodic updates available on FLWG website) to better understand the appropriate scale to use data, estimated level of spatial data inventory completeness, and update frequency of agency source data aggregated in PAD-US. The summary graphic, developed by USGS cooperators in collaboration with the FLWG and SLWG following the publication of PAD-US 2.1, is updated following each PAD-US data release. Overlaps between agency fee ownership datasets (mostly slivers) are available for review in Process Step 10, Fee Topology Assessment attached in this data release and displayed as web services in the PAD-US Viewer ( https://maps.usgs.gov/padus/ ). In addition, “Guidance for Base Map Developers to Use PAD-US” ( https://communities.geoplatform.gov/ngda-govunits/wp-content/uploads/2019/09/Guidelines-for-Base-Maps-Data-Use_Version17Sept2019.pdf ) and PAD-US Steward Reports ( http://www.protectedlands.net/data-stewards/ ) highlight PAD-US as the authoritative source for aggregated data only (that is, more than one agency) and document data-steward contacts and data download locations to obtain source data directly. Agencies are always the best and authoritative source of their land data and many update spatial datasets more frequently than PAD-US. 2021-08-20 0 PADUS3_0Combined_Proclamation_Marine_Fee_Designation_Easement The 'Combined' feature class integrates other feature classes from the PAD-US 3.0 geodatabase, as described in the name (and in database load order with Proclamation boundaries under all other features and Easements on top) including core PAD-US attributes only (The Marine and Easement feature classes include additional attributes specific to those data types). PAD-US Development Team Feature Class 0 FeatClass This field, in the 'Combined' feature class, identifies the original feature class ('Fee', 'Easement', 'Designation', etc.) a protected area unit or record occurred in before combination. This is included to assist users seeking data in the 'Fee' feature class as data gaps exist and 'Category' (which would otherwise define feature class placement) may be 'Other' or 'Unknown'. Use this field to extract select data as needed from the fully Combined inventory (e.g. Fee_Easement) and see the Federal Data Reference lookup table (DBF) for authoritative data provided directly by federal management agencies by Aggregator Source. See Online PAD-US Data Manual available at https://www.usgs.gov/core-science-systems/science-analytics-and-synthesis/gap/pad-us-data-manual FeatClass U.S. Geological Survey FeatClass String 12 0 0 EHoldTyp 'Easement Holder Type' is the general description (e.g., 'Federal', 'Tribal', 'State', 'Private') of the easement holder, following the PAD-US 'Agency Type' domain codes and descriptions. This is a core attribute in the National Conservation Easement Database (NCED) that was transferred to the PAD-US Easement feature class. See Online PAD-US Data Manual available at https://www.usgs.gov/core-science-systems/science-analytics-and-synthesis/gap/pad-us-data-manual EHoldTyp U.S. Geological Survey Easement Holder Type String 50 0 0 Shape Feature geometry. ESRI Coordinates defining the features. Shape Geometry 0 0 0 Loc_Mang The name of the land manager as provided by the data source, to complement the standardized 'Manager Name' field (e.g. 'City Land' is a standard 'Manager Name' while 'Agoura Hills, City of' is an example of a 'Local Manager'). See Online PAD-US Data Manual available at https://www.usgs.gov/core-science-systems/science-analytics-and-synthesis/gap/pad-us-data-manual Loc_Manag U.S. Geological Survey Local Manager String 250 0 0 Loc_Own The name of the land owner as provided by the data source, to complement the standardized 'Owner Name' field (e.g. 'State Fish and Wildlife' is a standard 'Owner Name', while 'Washington Department of Fish and Wildlife' reflects source data in the 'Local Owner' field) as more detail may be provided. A Python script assigns 'Owner Name' from 'Local Owner' (See Process Step 4, Local Agency to Agency Name Crosswalk attached in this data release). Efforts to complete and standardize 'Local Owner' in cooperation with data-stewards are in progress to enhance database utility. See Online PAD-US Data Manual available at https://www.usgs.gov/core-science-systems/science-analytics-and-synthesis/gap/pad-us-data-manual Loc_Own U.S. Geological Survey Local Owner String 250 0 0 Pub_Access Level of 'Public Access' permitted, described as: 'Open' requires no special requirements for public access to the property (may include regular hours of availability); 'Restricted' requires a special permit from the owner for access, a registration permit on public land (e.g. self-permitting Wild and Scenic River, backcountry Wilderness registration) or has highly variable times when open to use (e.g. seasonal Wildlife Refuge closure); 'Closed' occurs where no public access is allowed (e.g. land bank property, special ecological study areas, military bases, many easements, etc.). 'Unknown' is assigned where information is not currently available. See Online PAD-US Data Manual available at https://www.usgs.gov/core-science-systems/science-analytics-and-synthesis/gap/pad-us-data-manual Pub_Access U.S. Geological Survey Public Access String 20 0 0 GAPCdSrc An acronym to describe the GAP Code Source or organization(s) that applied 'GAP Status Code' to a unit boundary. This field also describes the methods used for assigning GAP Status as follows: 'GAP - Default' is assigned when GAP's categorical assignment of status has been applied, without more detailed review or inquiry. 'GAP' is assigned when standard methods (includes management plan review or land manager interview to assign GAP Status to a protected area) apply. 'GAP - Other Organization' (e.g. 'GAP - NPS') applies when the measure is assigned in partnership with GAP, including review. 'Other Organization' is assigned when another organization applied GAP Status according to their methods (e.g. The Nature Conservancy). See GAP Status Code Assignment reference document for more information: https://www.usgs.gov/core-science-systems/science-analytics-and-synthesis/gap/pad-us-data-manual . See Online PAD-US Data Manual available at https://www.usgs.gov/core-science-systems/science-analytics-and-synthesis/gap/pad-us-data-manual GAPCdSrc U.S. Geological Survey GAP Status Code Source String 150 0 0 IUCNCtSrc An acronym to describe the organization(s) that applied 'IUCN Category' to the polygon. This field also describes the methods used for assigning 'IUCN Category' as follows: 'GAP - Default' is assigned when GAP's categorical assignment of status has been applied, without additional review. 'GAP - Other Organization' (e.g. 'GAP - NPS') applies when the measure is assigned in partnership with GAP, including review. 'Other Organization' applies when the IUCN Category is assigned by another organization according to their methods (e.g. NOAA). See the PAD-US Standards Manual for more information. See Online PAD-US Data Manual available at https://www.usgs.gov/core-science-systems/science-analytics-and-synthesis/gap/pad-us-data-manual IUCNCtSrc U.S. Geological Survey IUCN Category Source String 150 0 0 GAP_Sts The 'GAP Status Code' is a measure of management intent to conserve biodiversity defined as: 'GAP Status Code 1': An area having permanent protection from conversion of natural land cover and a mandated management plan in operation to maintain a natural state within which disturbance events (of natural type, frequency, intensity, and legacy) are permitted to proceed without interference or are mimicked through management. 'GAP Status Code 2': An area having permanent protection from conversion of natural land cover and a mandated management plan in operation to maintain a primarily natural state, but which may receive uses or management practices that degrade the quality of existing natural communities, including suppression of natural disturbance. 'GAP Status Code 3': An area having permanent protection from conversion of natural land cover for most of the area, but subject to extractive uses of either a broad, low-intensity type (e.g., logging, Off Highway Vehicle recreation) or localized intense type (e.g., mining). It also confers protection to Federally listed endangered and threatened species throughout the area. 'GAP Status Code 4': There are no known public or private institutional mandates or legally recognized easements or deed restrictions held by the managing entity to prevent conversion of natural habitat types to anthropogenic habitat types. The area generally allows conversion to unnatural land cover throughout or management intent is unknown. See the PAD-US Standards Manual GAP Status Code Assignment reference document for a summary of assumptions, criteria, and methods or the geodatabase 'GAP_Status' lookup table for short descriptions. See Online PAD-US Data Manual available at https://www.usgs.gov/core-science-systems/science-analytics-and-synthesis/gap/pad-us-data-manual GAP_Sts U.S. Geological Survey GAP Status Code String 95 0 0 WDPA_Cd The 'World Database for Protected Areas (WDPA) Site Code' is assigned by the UNEP- World Conservation Monitoring Centre (UNEP-WCMC) to all areas submitted to the WDPA. USGS maintains these codes, assigned to overall protected areas by 'Unit Name' (includes 'Designation Type'), between PAD-US updates. Areas identified as 'GAP Status Code' 1 or 2 meet the definition of protection by the International Union for the Conservation of Nature (IUCN) as primarily managed for biodiversity protection and are submitted to WCMC for the WDPA. Other areas will not have a 'WDPA Code'. A derivative PAD-US product, with all 'WDPA Codes', is sent to WCMC for the WDPA following each PAD-US update. This field is incomplete in PAD-US 3.0 and has not been reviewed by the PAD-US Team, pending additional code assignments for new protected areas by WCMC following PAD-US 3.0 publication and development of the WDPA 3.0 Submission. The PAD-US WDPA 2.1 Submission is available for download ( https://doi.org/10.5066/P9IVLRSS ) and display via Protected Planet (https://www.protectedplanet.net/country/USA). It is important to note statistics published by the National Oceanic and Atmospheric Administration (NOAA) Marine Protected Areas (MPA) Center and the USGS differ from statistics published by the UNEP-WCMC as methods to remove overlapping designations differ slightly and U.S. Territories are reported separately by the UNEP-WCMC. See Online PAD-US Data Manual available at https://www.usgs.gov/core-science-systems/science-analytics-and-synthesis/gap/pad-us-data-manual WDPA_Cd U.S. Geological Survey WDPA Site Code Integer 4 0 0 Src_Date This represents the date (yyyy/mm/dd) GIS data was published or accessed (in the case of infrequently updated files) by the data aggregator. If month or day is unknown, the date is yyyy/00/00. The date an aggregated dataset was delivered to USGS may also be assigned to address data gaps when the original 'GIS Source Date' is not available. See Online PAD-US Data Manual available at https://www.usgs.gov/core-science-systems/science-analytics-and-synthesis/gap/pad-us-data-manual Src_Date U.S. Geological Survey GIS Source Date String 15 0 0 Comments Comments from either the original data source, aggregator, or the PAD-US Team. See Online PAD-US Data Manual available at https://www.usgs.gov/core-science-systems/science-analytics-and-synthesis/gap/pad-us-data-manual Comments U.S. Geological Survey Comments String 255 0 0 Loc_Nm The name of the protected area as provided by the data source; the 'Local Name' field is not standardized. This field may or may not include designations, different formats, spelling errors, unit or area identifiers unique to parcels; however, it links directly to source data files and may provide additional information not available in the 'Unit Name' field. See Online PAD-US Data Manual available at https://www.usgs.gov/core-science-systems/science-analytics-and-synthesis/gap/pad-us-data-manual Loc_Nm U.S. Geological Survey Local Name String 250 0 0 IUCN_Cat International Union for the Conservation of Nature (IUCN) management categories assigned to protected areas for inclusion in the United Nations Environment World Conservation Monitoring Center (UNEP-WCMC) World Database for Protected Areas (WDPA), the North America Intergovernmental Committee on Cooperation for Wilderness and Protected Areas Conservation (NAWPA) Protected Area Database, and the Commission for Environmental Cooperation (CEC) North American Terrestrial Protected Areas Database. IUCN defines a protected area as, "A clearly defined geographical space, recognized, dedicated and managed, through legal or other effective means, to achieve the long-term conservation of nature with associated ecosystem services and cultural values" (includes GAP Status Code 1 and 2 only). Management categories are not hierarchical and follows as: 'IUCN Category Ia': Strict Nature Reserves are strictly protected areas set aside to protect biodiversity and possibly geological or geomorphological features, where human visitation, use and impacts are strictly controlled and limited to ensure preservation of the conservation values. Such protected areas can serve as indispensable reference areas for scientific research and monitoring. 'IUCN Category Ib': Wilderness Areas protected areas are usually large unmodified or slightly modified areas, retaining their natural character and influence, without permanent or significant human habitation, which are protected and managed to preserve their natural condition. 'IUCN Category II': National Park protected areas are large natural or near natural areas set aside to protect large-scale ecological processes, along with the complement of species and ecosystems characteristic of the area, which also provide a foundation for environmentally and culturally compatible spiritual, scientific, educational, recreational and visitor opportunities. 'IUCN Category III': Natural Monument or Feature protected areas are set aside to protect a specific natural monument, which can be a landform, sea mount, submarine caverns, geological features such as caves, or even a living feature such as an ancient grove. They are generally quite small protected areas and often have high visitor value. 'IUCN Category IV': Habitat and (or) species management protected areas aim to protect particular species or habitats and management reflects this priority. Many Category IV protected areas will need regular, active interventions to address the requirements of particular species or to maintain habitats, but this is not a requirement of this category. 'IUCN Category V': Protected landscape and (or) seascape protected areas occur where the interaction of people and nature over time has produced an area of distinct character with significant ecological, biological, cultural, and scenic value. 'IUCN Category VI': Protected area with sustainable use (community based, non-industrial) of natural resources are generally large, with much of the area in a more-or-less natural condition and whereas a proportion is under sustainable natural resource management and where such exploitation is seen as one of the main aims of the area. 'Other Conservation Areas' are not recognized by IUCN at this time; however, they will be evaluated to determine if they meet the definition of Other Effective Area Based Conservation Measures (OECMs) for inclusion in the WDPA following recently released guidance. These areas (GAP Status Code 3 areas only) are attributed in the 'IUCN Category' Domain along with 'Unassigned' areas (GAP Status Code 4). In addition, a few areas are included as 'Not Reported', these areas meet the definition of IUCN protection (i.e. GAP Status Code 1 or 2) but 'IUCN Category' has not yet been assigned and categorical assignment is not appropriate. See the PAD-US Data Manual, Table 12, for a crosswalk from Designation Type, GAP Status Code, and size to IUCN Category. See Online PAD-US Data Manual available at https://www.usgs.gov/core-science-systems/science-analytics-and-synthesis/gap/pad-us-data-manual IUCN_Cat U.S. Geological Survey IUCN Category String 70 0 0 Date_Est The Year (yyyy) the protected area was designated, decreed or otherwise established. The date is assigned to each unit by name and the current designation type represented in the PAD-US, without event status tracking (e.g. Yellowstone National Park: 1872, Frank Church-River of No Return Wilderness Area: 1980). This field is not fully attributed and data gaps are difficult to address. See Online PAD-US Data Manual available at https://www.usgs.gov/core-science-systems/science-analytics-and-synthesis/gap/pad-us-data-manual Date_Est U.S. Geological Survey Date of Establishment String 4 0 0 Shape_Length Length of feature in internal units. ESRI Positive real numbers that are automatically generated. Shape_Length Double 8 0 0 Shape_Area Area of feature in internal units squared. ESRI Positive real numbers that are automatically generated. Shape_Area Double 8 0 0 EsmtHldr 'Easement Holder' is the name of the organization managing or holding the easement standardized by NCED to Proper Case with all acronyms spelled out (e.g., The Nature Conservancy [TNC]). This is a core attribute in the National Conservation Easement Database (NCED) provided by the easement holder or data provider that was transferred to the PAD-US Easement feature class. See Online PAD-US Data Manual available at https://www.usgs.gov/core-science-systems/science-analytics-and-synthesis/gap/pad-us-data-manual EsmtHldr U.S. Geological Survey Easement Holder String 100 0 0 Unit_Nm The name of the overall protected area following the PAD-US Standard (i.e. full name including the designation type in Proper Case without acronyms, unit identifiers, special characters, space or return errors), complementing 'Local Name'. As null values are not permitted in this standardized field, categorical assignments are sometimes made from the 'Manager Name' field and an auto-incremented number for each protected area when data gaps occur in source files. This field is in a state of transition as data-stewards move toward common standards. See Online PAD-US Data Manual available at https://www.usgs.gov/core-science-systems/science-analytics-and-synthesis/gap/pad-us-data-manual Unit_Nm U.S. Geological Survey Unit Name String 250 0 0 Source_PAID The 'Source Protected Area Identifier' (Source PAID) includes the persistent identifier (e.g. numbers, letters, or combinations of each) associated with each protected area, when available in source data. The intention is to maintain a reliable connection to join authoritative source data to previous PAD-US versions (to transfer attributes not available in source data) and support links to other data. This field is not fully attributed and significant work remains to ensure persistent identifiers are provided by data-stewards. Several Federal data-stewards provide 'Source PAID' for PAD-US and the FLWG plans to continue work to ensure this field is operational for the Federal estate in the PAD-US format. See Online PAD-US Data Manual available at https://www.usgs.gov/core-science-systems/science-analytics-and-synthesis/gap/pad-us-data-manual Source_PAID U.S. Geological Survey Source Protected Area ID String 100 0 0 Loc_Ds The unit's land management description or designation as provided by the data source. 'Local Designation Type' is not standardized and complements the standardized PAD-US 'Designation Type' field as more detail may be available. Null values indicate designation related information was not available in source files and categorical assignments to 'Designation Type' apply. See the PAD-US Data Manual, Table 9, for a crosswalk of 'Designation Type' (e.g. 'State Conservation Area') from source data where 'Local Designation Type' may include various, related designations referenced in source data (e.g. State Natural Area, State Ecological Reserve, State Nature Preserve, State Critical Habitat Area, State Wildlife Management Area, etc.). See Online PAD-US Data Manual available at https://www.usgs.gov/core-science-systems/science-analytics-and-synthesis/gap/pad-us-data-manual Loc_Ds U.S. Geological Survey Local Designation String 250 0 0 Des_Tp The unit's land management description or 'Designation Type', standardized for the U.S. (e.g. 'Area of Critical Environmental Concern', 'Wilderness Area', 'State Park', 'Local Recreation Area', 'Conservation Easement'). See the PAD-US Data Manual, Table 9, for a crosswalk of 'Designation Type' from source data where 'Local Designation Type' may include related designations in various formats (e.g. NWSR, National Recreation River, National Scenic River, Eligible - Recreational, Eligible - Wild, etc.) or the 'Designation_Type' geodatabase lookup table and PAD-US Data Manual Table 8 for domain codes and descriptions. 'Designation Type' supports PAD-US queries and the categorical assignment of conservation measures (i.e. 'GAP Status Code', 'IUCN Category') and 'Public Access' in the absence of other information (See the PAD-US Standards Manual 'GAP Status Code Assignment' reference document). See Online PAD-US Data Manual available at https://www.usgs.gov/core-science-systems/science-analytics-and-synthesis/gap/pad-us-data-manual Des_Tp U.S. Geological Survey Designation Type String 75 0 0 State_Nm Location name of State or territory by United States Postal Service abbreviation. U.S. Census Bureau States and Equivalent data serve as the common standard to apply 'State Name' and to integrate State jurisdictional boundaries into the PAD-US. See domain codes and descriptions (e.g. Table 16) in PAD-US Data Manual or the 'State_Name' geodatabase lookup table for details. See Online PAD-US Data Manual available at https://www.usgs.gov/core-science-systems/science-analytics-and-synthesis/gap/pad-us-data-manual State_Nm U.S. Geological Survey State Name String 50 0 0 Agg_Src 'Aggregator Source' describes the Aggregator (Organization) credited with data aggregation, version of PAD-US when the update (or data-steward review; if data did not change) occurred, feature class name (except when source data are mixed or split into multiple feature classes) the data reside in, reference to the original source data file, and a reference to describe the State location to manage boundary inconsistencies between agency datasets (from State data-steward submissions only). 'Aggregator Source' is attributed in the format 'Aggregator name_PADUSversion_featureclass_filename_filetype' (e.g. TNC_PADUS1_4_SecuredAreas2008.shp). State aggregations also include a reference to the State in the format 'organization name_PADUSversion_filename_filetype_StateUSPS'. Aggregators may not always be able to define the geodatabase feature class as data may be mixed (e.g. MNDNR_PADUS2_0_MN2015_PADUS_MN_1.gdb_MN, NJOGIS_PADUS2_0Fee_OSPRI_August2017_NJ). Organization acronyms are used and underscore replaces spaces and periods. A data aggregator submits data in the PAD-US format or is a nonprofit managing large regional or national datasets with required fields for PAD-US translation. USGS is identified as an aggregator when data translation is required (e.g. USGS_PADUS2_0Fee_BLM_SMA_ADMU_Union). More information about Protected Areas Database of the United States (PAD-US) data-stewards and source data files are available at http://www.protectedlands.net/data-stewards/ . See Online PAD-US Data Manual available at https://www.usgs.gov/core-science-systems/science-analytics-and-synthesis/gap/pad-us-data-manual Agg_Src U.S. Geological Survey Aggregator Source String 150 0 0 Mang_Type General land manager description (e.g. 'Federal', 'Territorial', 'American Indian Lands', 'State', 'Regional Agency Special District', 'Local Government', 'Non-Governmental Organization', 'Private', 'Joint') standardized for the U.S. This field is assigned by a crosswalk from 'Manager Name'. See PAD-US Data Manual, Table 6, for “Agency Name to Agency Type Crosswalk” or 'Agency Type' geodatabase lookup table for full domain descriptions. Use the 'Manager Type' field for the most complete general depiction of Federal lands as ownership related data gaps (i.e. 'Owner Type' = 'Unknown') occur in the Federal theme. See Online PAD-US Data Manual available at https://www.usgs.gov/core-science-systems/science-analytics-and-synthesis/gap/pad-us-data-manual Mang_Type U.S. Geological Survey Manager Type String 50 0 0 Mang_Name Land manager or administrative agency (e.g. 'Forest Service', 'State Fish and Wildlife', 'City Land', Non-Governmental Organization') standardized for the U.S. See Agency Name domain codes and descriptions in the PAD-US Data Manual (Table 5) or 'Agency Name' geodatabase lookup table. A python script assigns 'Manager Name' from 'Local Manager' (See Process Step 4, Local Agency to Agency Crosswalk attached in this data release). Use 'Manager Name' for the best depiction of Federal lands by agency as the 'Owner Name' field includes data gaps (i.e. 'Owner Name' = 'Unknown'), where parcel level ownership data are not yet available from authoritative data sources. See Online PAD-US Data Manual available at https://www.usgs.gov/core-science-systems/science-analytics-and-synthesis/gap/pad-us-data-manual Mang_Name U.S. Geological Survey Manager Name String 70 0 0 Own_Type The general land owner description (e.g. 'Federal', 'Territorial', 'American Indian Lands', 'State', 'Regional Agency Special District', 'Local Government', 'Non-Governmental Organization', 'Private', 'Joint') standardized for the U.S. This field is assigned by a crosswalk from 'Owner Name'. See PAD-US Data Manual, Table 6, for the “Agency Name to Agency Type Crosswalk”, PAD-US Data Manual Table 4 or 'Agency Type' geodatabase lookup table for full domain codes and descriptions. 'Regional Agency Special Districts (DIST)' include limited purpose governmental units that exist separately from local governments such as county or municipal (e.g. some Regional Parks, Greenbelts, Water Management Areas). 'Designation' is applied to designations overlapping fee lands as ownership is not applicable. Use the 'Manager Type' field for the best general depiction of Federal lands as several ownership related data gaps (i.e. 'Owner Type' = 'Unknown') occur in the Federal theme. See Online PAD-US Data Manual available at https://www.usgs.gov/core-science-systems/science-analytics-and-synthesis/gap/pad-us-data-manual Own_Type U.S. Geological Survey Owner Type String 50 0 0 Category The general 'Category' for the protection mechanism associated with the protected area. 'Fee' simple, is the most common way real estate is owned. A conservation 'easement' creates a legally enforceable land preservation agreement between a landowner and government agency or qualified land protection organization (i.e. land trust). 'Other' types of protection include leases, agreements, or deed restrictions. 'Designation' is applied to management boundaries not represented in title documents (e.g. 'National Monument', 'Wild and Scenic River', and some 'State Wildlife Management Area') overlapping fee ownership parcels. 'Marine' includes outer continental shelf lands managed by the Bureau of Ocean Energy Management and Marine Protected Areas inventoried by the National Oceanic and Atmospheric Administration. 'Proclamation' defines the outer boundaries of areas without internal ownership defined: Tribal Lands (Census AIA), Military Lands (Department of Defense), Proclamation (National Park Service and Forest Service) and Approved Acquisition Boundaries (U.S. Fish and Wildlife Service) for planning purposes. See PAD-US Data Manual, Table 3, or 'Category' geodatabase lookup table for full domain codes and descriptions. See Online PAD-US Data Manual available at https://www.usgs.gov/core-science-systems/science-analytics-and-synthesis/gap/pad-us-data-manual Category U.S. Geological Survey Category String 50 0 0 GIS_Acres Acres calculated for each polygon converted from the Shape_Area field using field calculator "!shape.area@acres!" rounded to the nearest whole number. See Online PAD-US Data Manual available at https://www.usgs.gov/core-science-systems/science-analytics-and-synthesis/gap/pad-us-data-manual GIS_Acres U.S. Geological Survey GIS Acres Integer 4 0 0 OBJECTID Internal feature number. ESRI Sequential unique whole numbers that are automatically generated. OBJECTID OID 4 0 0 Access_Src An acronym to describe the organization(s) that applied 'Public Access' to the polygon. This field also describes the methods used for assigning 'Public Access' as follows: 'GAP - Default' is assigned when GAP's categorical assignment of status has been applied, without additional review. 'GAP - Other Organization' (e.g. 'GAP - NPS') applies when the measure is assigned in partnership with GAP, including review. 'Other Organization' applies when Public Access is assigned by another organization according to their methods (e.g. NOAA). See the PAD-US Standards Manual for more information. See Online PAD-US Data Manual available at https://www.usgs.gov/core-science-systems/science-analytics-and-synthesis/gap/pad-us-data-manual Access_Dt U.S. Geological Survey Public Access Source String 150 0 0 Own_Name Land owner or holding agency (e.g. 'Forest Service', 'State Fish and Wildlife', 'City Land', Non-Governmental Organization') standardized for the U.S. See Agency Name domain codes and descriptions in the PAD-US Data Manual (Table 5) or 'Agency Name' geodatabase lookup table. A python script assigns 'Owner Name' from 'Local Owner' (See Process Step 4, Local Agency to Agency Crosswalk attached in this data release). Please note there are instances where 'Owner Name' = 'Designation' rather than an 'Agency Name' as expected. 'Designation' is applied to management designations that overlap fee ownership or where ownership information is not represented in the data type (e.g. ‘Owner Type’ and ‘Owner Name’ are not applicable to Designations such as 'Marine Protected Area', 'National Monument', or data included in the Proclamation and Other Planning Boundaries feature classes), while it remains a core attribute. 'Owner Name' also contains unknown values where parcel level ownership data are not yet available from authoritative data sources. Use the 'Manager Name' field for the best depiction of Federal lands by agency as several fee simple ownership related data gaps (i.e. 'Owner Name' = 'Unknown') occur in the Federal theme. See “The State of PAD-US Data” ( https://communities.geoplatform.gov/ngda-govunits/wp-content/uploads/2021/02/StateofPADUS_Feb2021.pdf ) or PAD-US Steward Reports by federal agency or state ( http://www.protectedlands.net/data-stewards/ ) for more information about inventory completeness. See Online PAD-US Data Manual available at https://www.usgs.gov/core-science-systems/science-analytics-and-synthesis/gap/pad-us-data-manual Own_Name U.S. Geological Survey Owner Name String 70 0 0 Access_Dt The most current Year (yyyy) the 'Public Access' classification was assigned to the polygon. See the PAD-US Standards Manual for more information. See Online PAD-US Data Manual available at https://www.usgs.gov/core-science-systems/science-analytics-and-synthesis/gap/pad-us-data-manual Access_Dt U.S. Geological Survey Public Access Date String 4 0 0 IUCNCtDt The most current Year (yyyy) the 'IUCN Category' was assigned to the polygon. See Online PAD-US Data Manual available at https://www.usgs.gov/core-science-systems/science-analytics-and-synthesis/gap/pad-us-data-manual IUCNCtDt U.S. Geological Survey IUCN Category Date String 4 0 0 GIS_Src The source of spatial data the aggregator obtained (e.g. WYGF_whmas08.shp) for each record. File names match original source data provided by managing agencies to increase update efficiency and data transparency. This field is in a state of transition to fully meet standards as the original 'GIS Source' is not always provided in aggregated datasets. See Online PAD-US Data Manual available at https://www.usgs.gov/core-science-systems/science-analytics-and-synthesis/gap/pad-us-data-manual GIS_Src U.S. Geological Survey GIS Source String 200 0 0 GAPCdDt The most current Year (yyyy) the 'GAP Status Code' was assigned to the polygon. See Online PAD-US Data Manual available at https://www.usgs.gov/core-science-systems/science-analytics-and-synthesis/gap/pad-us-data-manual GAPCdDt U.S. Geological Survey GAP Status Code Date String 4 0 0 dataset Esri 8.1.2 Simple FALSE 0 TRUE FALSE /9j/4AAQSkZJRgABAQEAYABgAAD/4RDuRXhpZgAATU0AKgAAAAgABAE7AAIAAAAMAAAISodpAAQA AAABAAAIVpydAAEAAAAYAAAQzuocAAcAAAgMAAAAPgAAAAAc6gAAAAgAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAE1hc29uIENyb2Z0AAAF kAMAAgAAABQAABCkkAQAAgAAABQAABC4kpEAAgAAAAM3MwAAkpIAAgAAAAM3MwAA6hwABwAACAwA AAiYAAAAABzqAAAACAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAMjAyMjowMzowMiAxNTo0MzowOQAyMDIyOjAzOjAyIDE1OjQzOjA5AAAA TQBhAHMAbwBuACAAQwByAG8AZgB0AAAA/+ECqmh0dHA6Ly9ucy5hZG9iZS5jb20veGFwLzEuMC8A PD94cGFja2V0IGJlZ2luPSfvu78nIGlkPSdXNU0wTXBDZWhpSHpyZVN6TlRjemtjOWQnPz4NCjx4 OnhtcG1ldGEgeG1sbnM6eD0iYWRvYmU6bnM6bWV0YS8iPjxyZGY6UkRGIHhtbG5zOnJkZj0iaHR0 cDovL3d3dy53My5vcmcvMTk5OS8wMi8yMi1yZGYtc3ludGF4LW5zIyI+PHJkZjpEZXNjcmlwdGlv biByZGY6YWJvdXQ9InV1aWQ6ZmFmNWJkZDUtYmEzZC0xMWRhLWFkMzEtZDMzZDc1MTgyZjFiIiB4 bWxuczp4bXA9Imh0dHA6Ly9ucy5hZG9iZS5jb20veGFwLzEuMC8iPjx4bXA6Q3JlYXRlRGF0ZT4y MDIyLTAzLTAyVDE1OjQzOjA5LjcyNzwveG1wOkNyZWF0ZURhdGU+PC9yZGY6RGVzY3JpcHRpb24+ PHJkZjpEZXNjcmlwdGlvbiByZGY6YWJvdXQ9InV1aWQ6ZmFmNWJkZDUtYmEzZC0xMWRhLWFkMzEt ZDMzZDc1MTgyZjFiIiB4bWxuczpkYz0iaHR0cDovL3B1cmwub3JnL2RjL2VsZW1lbnRzLzEuMS8i PjxkYzpjcmVhdG9yPjxyZGY6U2VxIHhtbG5zOnJkZj0iaHR0cDovL3d3dy53My5vcmcvMTk5OS8w Mi8yMi1yZGYtc3ludGF4LW5zIyI+PHJkZjpsaT5NYXNvbiBDcm9mdDwvcmRmOmxpPjwvcmRmOlNl cT4NCgkJCTwvZGM6Y3JlYXRvcj48L3JkZjpEZXNjcmlwdGlvbj48L3JkZjpSREY+PC94OnhtcG1l dGE+DQo8P3hwYWNrZXQgZW5kPSd3Jz8+/9sAQwADAgIDAgIDAwMDBAMDBAUIBQUEBAUKBwcGCAwK DAwLCgsLDQ4SEA0OEQ4LCxAWEBETFBUVFQwPFxgWFBgSFBUU/9sAQwEDBAQFBAUJBQUJFA0LDRQU FBQUFBQUFBQUFBQUFBQUFBQUFBQUFBQUFBQUFBQUFBQUFBQUFBQUFBQUFBQUFBQU/8AAEQgCNQNo AwEiAAIRAQMRAf/EAB8AAAEFAQEBAQEBAAAAAAAAAAABAgMEBQYHCAkKC//EALUQAAIBAwMCBAMF BQQEAAABfQECAwAEEQUSITFBBhNRYQcicRQygZGhCCNCscEVUtHwJDNicoIJChYXGBkaJSYnKCkq NDU2Nzg5OkNERUZHSElKU1RVVldYWVpjZGVmZ2hpanN0dXZ3eHl6g4SFhoeIiYqSk5SVlpeYmZqi o6Slpqeoqaqys7S1tre4ubrCw8TFxsfIycrS09TV1tfY2drh4uPk5ebn6Onq8fLz9PX29/j5+v/E AB8BAAMBAQEBAQEBAQEAAAAAAAABAgMEBQYHCAkKC//EALURAAIBAgQEAwQHBQQEAAECdwABAgMR BAUhMQYSQVEHYXETIjKBCBRCkaGxwQkjM1LwFWJy0QoWJDThJfEXGBkaJicoKSo1Njc4OTpDREVG R0hJSlNUVVZXWFlaY2RlZmdoaWpzdHV2d3h5eoKDhIWGh4iJipKTlJWWl5iZmqKjpKWmp6ipqrKz tLW2t7i5usLDxMXGx8jJytLT1NXW19jZ2uLj5OXm5+jp6vLz9PX29/j5+v/aAAwDAQACEQMRAD8A /VOiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAoooo AKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigA ooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACi iigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKK KACiiigAooooAKKKKACikpaACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiii gAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKA CiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAK KKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAoo pCcUAJ6Ckr5P+IH7ajaH8QY9M0CzstQ8PWd0qXupKzTNdR/L5gt13RqrD94oZmZW+Vvu17l8YviR D8Lfh/qniB/La5SPyrKGQ5Etw3Ea7dy7hn5mCnO1WqeeJ3zwNen7NSj8ex3u4N0waVm6cZr8x/h7 8bvF/wANdcm1PTdTkuhcySTXNnqEkktvcySfekkG7/WfKv7z73y/e27lr9BvhZ48g+JngfS/Edta SWS3qMWt5m3FGV2R13fxLuVtrcZXsvSlCpGWx0Y/LK2X2c9UdpS0UVZ5AUUUUAFFFFABRRRQAUUU UAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQ AUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFAB RRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFF FFABRRRQB5D8dvjha/Bm10J3tvtVzqF8qNDhty2qMpuJF/hZtrKqqzL80inorV6hp99b6pZwXdrK lxbXCLJHNE25XU8qysOo5r5J/bd+GEvnWHjqzNxPGdtjfRs8kiQj/li6L92Nd24N8yruaP5dzMT1 /wCxl8Uj4n8Fz+Fb643anovNv5j5eS1b7uNzbm8tvl+6qqrQrWXN+85T2p4KEsDHFUv+3j6VorHv PEmlabrGm6Vd6pZ2up6kZfsVjNcKs915a7pPKjb5pNq/M237ta+a1PFFopKWgBvevmr9sb4r6v4L 8O2vhvTrTyk1+CZJtQkKsBCNqyQov3tzLIu5ivyq3y7m+aP6U3dK8T/ah+E998VvAMUWi2sd1run 3Kz28bKitIrfK8ayMV2DlZOvzeUtTPmt7p35fKjHE05V/hPz2rtvGPxb1nxt4L8LeGr1ttloNu0a srf69vuxsyr8v7uPbGv8X+sbd81epyfskz+EfhzrvibxprEen3Fpp8lxb6dauuEm2IY1klb5WbzP k8tfvNt2yV4DpWkX+vX8dlptlcajezbvLt7WFpJJNq7m2qvzfdWuDlnE/TKdfB4z94teQqV+lP7N +g/8I78FPCdp5xuPMslvNxTbt89mm24/2fM2/wDAa+XPhf8AsZ+JfFXkXviiT/hGdLbbJ9nK772R flb7v3Y9ys33vmVl+aOvt3QtItPD+jWOl2MPkWdlAlvBHuLbI1Xaq5PPCgV0UYyirs+Uz7HUcQo0 qUuaxq0UUV0nx4UUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRR QAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFNyaC3Fcwvia5ZXn+xSLZ xot0WMNx532dombcI/Jy03mKV8gfMFKsfmZY6ZEpqO51NFJS0iwooooAKKKKACiiigAooooAKKKK ACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooA KKKKACiiigAooooAKKKKACiiigDA8TeGdO8YaDe6RqdrHe6feR+XLbzLlSOD+ByAQ3VTyK/PKw1P Wf2afjRdKg+03GlXDQTQtJ5a3trIu5d21m27lZZFVt21tu5W21+lIUbRivJvjJ+zz4e+MWL68M+n 63FB5MGoW77iqrvKq0bfKy7pC38Lf7S1nOPN8J7WW4yGHlKnW/hyMDUPGnwa/aa8MR+GtfubDU7W 4lt5BpeqO1ncR3Df6tY23K3mfeX9yx+9tztb5vdsogxkV+ePi79kr4ieHb/UlstIOuaXa7mS9tZo 908e3d8sLN5m7/Z2t833d33q5iw8b/Ej4P3llaLqOueG3gjaS306+WRYdrBvm+zyfKy7t38P3v8A arH2nK7yiepLKKOIjfCVlLy/r/I/TfPqKOfrXw14W/bk8U6a0aa5o2n6zAkAj8y3drWaST5f3jN8 y/3vlVV+9/D92vR9V/bq8LxWEj6ZoGr3V/hfLhvBFBETnnc6tIy8f7Jrb2kTyqmT42nLl5Ln09wO 9cF8RvjN4V+F9s0mu6rHDcFPMisIf3lzN97btj7BtrLubau7+Kvirx9+1d498ZT3KWeoHw7pch2r a6b8siqsm5Wab/Wbvuq21lVtv3fmavPPAfgPWfiR4mttD0K1NxdzfM0hGI4I/wCKSRv4VX/7FdzM q1nKt/KepQyFwj7XFy5Yn1Fqng3xt+1VrunajqiyeFfhtG6z2dtIy/arqP5v32z5v3jY+Vm+VVk+ XzOWb6N8J+APD3gO1Nv4f0a00tXSOOR7eFVeVUB2+Y33nPLfM2T8x9a6RWCqMdKXnnNdEY8p87Wx U6q9nHSK6D6Wiig5AooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKAC iiigAooooAKK5xtRnudSaOI+atre+TJ9injkwv2fzMXKuu6P5mXCx7m/1LfdZgpD4j8zVoLJoPLd vMEkbPvmT5n8mRkj3KsciwzMsjsv3VXbuYqrsY+1idDmkzmsaHVbhbR/OsZJNRhtluJLSzO5Wdg3 7uOWRY0c7kZfm2/wltu4VXvPEkdn/aQjMBh04xtd3V1dJHBEp+aVWPzMrRw7ZMMqqwkj+b5mZQft IJXOi3Ubqo2t4k9xdxoJA0EojbzIXRSSit8rMMOPm+8vGdy/eVhQl5uu5oQJd6RpIS0LhcMWHytj aT8p+UfMvy7vvLlF8yNCiiigoKKTNLQAUUUUAFFFFABRRRQAUUUUAIOKpX98lnZzzSLKUijZysMT ysQAfuqoLMf9leauNXNeIJ4rO+F/dwyPFp6brVWNuEuLiY+WixtI25ZufLX5kVvtO35v4WZzlyq4 zxBJPMoH9j3l7Fb3QdYoxbMt1shMsbfvG+VRLtVT8rCRVbiPc1U9YWe00+5N9LLLb2yRr/aGrx2r WkLQxmYX8iq0bbfM2hh8uGjVlWNcyVm6h4ftriOe1vY9IvdUUqJZZ7KTUZJo7hJo1doS2+GPzp7h QpZkWESLuVWby9jWtOFil7dYni824e4+1aPBieDFp5fmSx7m+1N8u1V8tufJHlny91aHA7yu5fn/ AF/XUVPNjkF2t1qBt5JvJluGV/NVluvkiW38nb5beZIrTYVvLWNtzf6xdnQ746hp0MrNbmcZjmW1 m86NJlJWVFkKru2urLyq/d+6vSqNzZT3l3dvbIdIu2H2aXUPIikmngWNzG0bbm27ZJSV8xW+7J8n zbqpG6nu76V1huLW7aCwkktIryOS5iVppNyyQMWhjXG9WkjZmkCyKvzRx0jeMnB/1/X9bs6+l61h 6HrE2rNPuij8uOSRBcW9ws0LMs0qbN3DCRfLXzFK4Vm2qzbWrb7GoOqMlJXQ6iiikUFFFFABRRRQ AUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFAB RRRQAUUUUAFFFFABRRRQAUUUUAFFFFACUtFFACUjIp6qD+FOooA8w179nX4b+JGiF54R0+DytxX+ zw1nndjO7yWXd0/irM/4ZL+Ff/QsE/8AcRuv/jlewUhBqeWJ1RxeJiuWNSX3nkNr+yt8L9PuobiL wsrywyCVVmu7iRSy9NytJtZf9lvl9q9G0HwzpHheza10fTbHSrZ5PMeGxt1hQtjG7aoxnCrz7Vsn PpTPyp8qM6mIq1f4kmySloopmIUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUU UUAFFFFABRRRQAUUUUAFUb6aWztZporeS9kjQstvCUDyN12ruZVy3+0wFXqSgDidSure+1S1kbVr KeJLppLSGzsvOu43jkjt5MNuf5VaSaORljXas/LR7WZoNN0awm0P+zxp32m1hnVJdHSVWkg86NfO jvP3zLcN+/kmk3M27eGxI21m2tUkms9SWW0W4uJ2hZ5LVY5JFnjjViI42Z1hhkZ5V+Zj86qV6Luj xbltPutJgt2mg1XSM2n2Vrq5mW2uLWdfs4WW4ZpFvGYNIwVvvM0O4Assh1PNnFczb/r8yze3FtZ3 U7yadocOpo7XWZrwRv8AaJP9Fs3Y+XuVpow0e/7y7fLXzKivoXQpYbWt0txHDpt5eKWkib5YZLhb qQTK0u242xpIqtIyyffViy37fUrhtYuoBqEc6f2iIWijQ3DQr9lSQRtsVfs7bj5n7wyZDL8w8xFX Km0VfEWh6rpUryQTavJqIuGazbyrmPL26rOyxwtgRtDt2ssjLEu2SRVaRkPST/4b+uxaXTV1ZVRt MSW1uo5Wiu9Sja4b7LK0Mk9vLHKVkjaTc6iP5lUQruxtWOp5jdNb6aJbj7Fez+fJa/2lcASx3TRs 0du0MLKlwqxtLlfM/wCWKtlj+8XFt7K3tPDc0Nytxb6Yn7m41PVIIVu4ZrQMv9p3EkzbZM/Z7do3 8tjxGx+U/u+gnuLfS5pbi7K6I7STX93cQIPs80caiPdcTNHtU+WYW+8rfu9oZkjagrlUW/6/ry/4 BD/aKWlhqOpWk+m21lfQPqEeuLHH9kjVYY1SSdvNUzZVd25dq+XGF3LtVmuTznT7mWV5DYWz30aT SX0hkWfdGkcYh/e/usyNGu3b8zLJ8uZBJUMtndWNxBeG0e91IWu+7uNNhhiW7aJW2wHzH3AM00jx jdtVlbdIN3z1ri6uNFntGMl1c3bTw2Ba7kj36iojZjJDGJEjRl3tJIypuZYJAsbfu8A9Y7/1/X/A vsR29/cW7Ym1Ozsr3zIft0N4u4szTLDFJGn2hvJjm8mVY1+b5pFP3lkVrui6w8txZ2zXMhH2VmA1 KJYru+CrAftAVSuwKZCrq0ancw+VV27qSzTtCyJb3mnTpHHc27XLXF00dxcNMuyZYztkSNm5RZmV Rz+7VY3qX7VFf3V5bhrmOO5uJrK8tllkkmim8tfLYSQyN9lVoVEg+6f30bfI7EMERly/CbMGsJ5d k94h065u8JFa3Lp5vmbGdo/lZlZlVWJ2sw+VuwzVK38Rebb2d2YPtFnejfFe6dJ9rgMbSKsJ+X5v 3iyK+5VKKFfc21VZsmPVvKsbK4064060juNLu9Q+z2B+2RPMxjk86OKONZLld0jMWRkLGRflZpAy WtRj365qDObmBlsYLa1vLe282SB5pJFZk/cMvVYWbLSKPLVmjjUbpAv2j6P+t/62NnTdUtdZhaay m8+1yuyZFby5VaNZFaN/uyKVZfmXcvVeqtVq+vrfS7Se6upo7e2t0aWWaVtqooG5mZuw4rm4p7qe SC+ksN+r2kUkrQmxVZvs8u5haxzeb5aybo4PM/eMrGLO1VdGVlvY2lrZlLN0FpbRPp1hqOnRRy3F oZJzG8CRpCUjjhaOFf4h+6/eL+7LMi/au39f1/Xmdnmjr71y9+Dq9rJLDLFftHdtHZ3GnpC01k2P s8rhpGZTJGzT7jj7u5NjNkM+e51OG3u7iNo7SFmnLTas67LJUXbG6xx/6yNmXzMNIrbWPzLwqzZR NY1HJ2sdPRXM2PiWfUIdNmXTZreG8lVd0jrJ+7a3MwkVofMXG7938zKu7dtZv3fmR2evTXXlQmZI rm4Rb6CSe0aMy25m+aP7O0nnLJHG0aszKqq8qtt+9GoP2iLGr3kfkytqVpAmlWk4mnuNSljSNY40 Ey3C/e+7Iq/f8vbtZv4V3cTrfju28IXMEEljHpt5MBawyWEv2m1TUrhxJNHLCGi3Mu6Obc21pFeT btZsNa8P+LNG8SSXsmgXtsl69/bwpNNM6XVzCW+1MjefDv27Wu/LjXcu3dsaPny5/GF082i6ffXd 1NbJY6hc3ElzDp7q0UcUdx/C8cjfcXZ5itH5m7crbZFjbKpKXs5SpmcOT2qdXb/g238maNrEI/EE 8Fl5Ya3uvMjsrWdo7dGbDXEk5jjwJm+2M/kyMwfbHIu1tzLJomjvb3lnJFp50eFoECw21vbx+Rbx x7Y7OYqzbtrzSOvk4VduN3/PTz3RPjn4a1Jfsd7cm5sFubeJbu+tWMAuGZpI2DN02NHu/ebW+Xcv 3atrDpkusS61a6dphvprg3UepWe5vMXb8rLu+63zfNt/1m3d/Ftryqua06NJVKit5HZTwPPU5VLb X+v6+R2mnsuo28Nqb3S5ZZpBdCxkla/8uaG63Xe2R3UsscjKi/Kvksq/L92Nbkl2+oTPFKkgk8uy uX0mCZY721Zpm+aV1m2mP5Purw3kzDMm7bWFJ4kuNUi+x3sNjdaa8MiXlvdRs32lSuPL/ujjduyr K33flpdb8SWml6beT6hdaqdNjgUzSRNGhZbmbaNvl7ZVaFcfMu35ZAf3j/d6cPmWGxKvCRhUwtWj py3/AK/r8rGheNb291cXd1dWMsdtI0eqXloRbPbLEftVuJ5PO3KiRt8y/Nv8/dtWNmFXNP1u4gaS znuI9Y1BJY4pU0y2Ma252weZ5haRlU/vvO2s27y2+VZCu5qb61cSWt5ci1k1FtOkvJYLq1lKW0rx 5VYWSKSWRm+d4yPLb95BI3lqfLVpLq4jtZ3gmkuF077dDGXkkkgMVwz+cCZpJF8yN3eGJY4wy7m8 v5l3LH6hxX5dY/1/Xz7nR2F9b6pZw3drLHcW08ayRzRNuV1I3Kyt3HNXFbPFctpl+y6lapPNHJdT 2skc5Z5rZpHt5VRmhtJN37stI2ZA3Qw/NIrKy39B1tdYs7Z/k81raG6aS1ZprZlk3Y8ubaqyL8p6 c7SrFV3LUnXCqpe69zcoopKk2FooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAoo ooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiii gApKWigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAoooo AKKKKACiiigDI1OxmvoUe1na2uodzwSP5jRiTYyAyRqy+YnzZ2s3/fLKrLWz5Oqf8xK18y8/67RX P+jf8C8mP5f+mf7yP/pp+83+K5iSIXGuyR2Wo36lW3XhgmikijlX7Oyxukm5o2aP+GMKu2SRjh2j aqRzz93VFH+0GvbO2vP7ctL37LbW9/nTbeZ/NVhIJJBFHMxkjlTcI0+bay7v3hVQtya2LXD2Lre2 9hPJPbn5pnkmeRPN8yOeOTdBGv71fm2/MFVduEDLY6ml6tiyXmqndds376waLzFeJpVik3QrsjVX X5vlO6NY2YtuVsyz0WW+jtd0VxbRTQJp90tq8i3K+VHcK/mXcxWaSLcw8uSNVk3fvNxWRttHN6a/ 18/68i4/2iTUYrxfs51aWzmmtdM1Ly0uYvlt90ayx7tsYZV8z5ZPmkXDbVVTDfavaQ2fn6VrUZg+ yzXrzSXMdxbW8c2+WK8m3SLIYQ0bqojkC7XYfdXdHLY3Un2MWejPpzy3E98/2q3tn+zQOssm4uqH a0izMqurSRtI3nN8u0qJpNWuPOmneC8g060lnlMlrDvaZY1CmOSJo/M3NI0jL5KtuWFW3/PtYK6c 19/6/wCH8iK4s0S3nWHQtQgVob79xYXMdv5haUMxAWZV82ZsyJJ95dzbmjZmzPeXX9li8v5VvrS3 t7oT3DS3MJhmi8pVeTMjHyoY87mC+W26Fmw2795RhgEk1pPHcaTdXMt1Hm6tNJeRReRq8d1IzLIf LZoY2hVmb92w2s0m4R1Y8PWrQ/ZGs7G3sbbyYl89dNFvvtf33kWqx+Z5kbQhk3bl2/M21V3MIwla vT9CjZQxWenxaa0JgnMEOnXlrp8ssH2a33SwwzW8ELSeSrt91gylYxlm/c7RcuLj7TpwvxeXNxBJ ZXU0OraMPMjSFmRo9sO6Tzpdm3a3lyBtj/d8zY1TS7hNTtILVr6fT42/cabKt2jTRzCGSOS3ZvOl W4nhaOZm3Ky8L99o2ap/Lgku1vraWSG91F47uC3tY/slzJB/oqytPDM37xl2orOyLJHG3lrtb7z6 kr4NP6/r9ehcvLqO/uJdPk1myWOS6a0NvCWjuQDa+YYVkWUMs3/LbcvIj/h/5aVXbUJrO3e7Y3T3 C24W8vFs5zD+4kxIsdp5nmbpA02xo1fcFXLOFjDLPdG1hvbWTVNZeW3szG1yunb2DRorNNHtg2yS N5yfKoZWaPasfyyCodVtLm5uNS8i3kW5t5DewvGvnzPutmhVrdpwsMM25XXbll2/M+PONA5PrHf+ vP8Ay8ifULRMAyzmzsob6MKuqbLiC6kknhlV03N5issmY4xuXax/1bKsdJdagircyC52auJxbfYb G+jkeVot1wkKrNtjWWSH5m4Vtrfe2osi2LdbXR9avWSWKWWWO3DwxxyTXiiS4m2tI25m8ndI21do WPbL8237jbu61JGuLFFlnmKNuvbGPy3gWSbZCyCbdFI0ab2k+Yn92p8tvMVaRfn/AF8v69SFVj1B 7qY2X26bz4om1DS5EhMix3cgWFm87cfI+bzFb5W3SBVO5o6uWEJivoW+x6lBg3XzT3fmRjdOrfMv mNndjdHx+7j3L+7+6c2+ms9Yk1F7p7O+jtY5knsZdLkkuxZOrRyR+Xu3ssk1uzBghWRY9qq3ElCa fNLcz+XBZzamJVzfjSTGkF8LVla7O+QGSNo2jh/dsWX5kMh+bywlb6fp/X9alPTbmFY3msrSzsZZ Jd+n2y3EdpHLdLbtC1pO0Mkgkkj8llb5WVVVNqsYdw04LiHUNLvprGe4u7aELcJZI0yXsVxn7R5c m6RWXcJIcQv5e1flb5W2rDqWoWyXerW1zPJaWGx31KRr0I8ETQ/JdLJ54a3h/czR/Kqt5gZl27Wd jUdNtL2dv7UuI5baCRrSWS/g8mV2mmhkjhjmG1Whb93G0YVvM+VWYsrKw/hCn7su/wDX9fd5Hzn8 TvCWj6Lql9rXhyWZbS8t7qN7OzhVmsZPLXzlkjZf3a7ZNrL8rR+YrL93bXW/ALVtT+IfhnU7PXtU u/EVpbSLatpjOyzrHMrRmR7jzF8yPbJNujbcy+WGXDKq1taZ8HbXwnNFdWFtPdzalZRx3VnrEHmy Rx+ZEJ1eSFvJ3BW/1fzM21vLZl3LXn3iCz0vwvqFv4n8CSJcW+9r280tZcrbfKyLIsLL8rR7pGVm Vtu5fl2/e8H2kqVe1TY9ydD+0KtN0301/S5L49+D8PiLxVqenaPqtm97oenW8CafHDiRo1j2x/aH ZlVZG8tv+2e1vutXn/hT4ha58OdUbSLvc9ja3DR3VlIu5oW3fvNvzfe+Vv4ttd18bLyGx8Cab428 P6TJp+v21xZ3iazuh+1qNvl7pm2s0ysrRr5e7+6zfxLXifgOKf4kalqFrErJqy28l3HDb2TMtwys u5VWGPbH95v4VX7q/LXkOnTxEZfy3+4jFZXiaMI4vBR/xf12PrzS9UtdZ0+C8spluraZd0ci/wAV XtPWKw1C5vYxm4mZZppJGaTfIv3dq/w/w7m/2f8AgNfOHw5+Il14G1RdL1iSb+yNzRtAy/Naybvv bdu7+98v+0zfer3Lw74gfxhHoP8AYcdvq8UkA/tG5tz5bW8zt8itD5jNHtEcjMzbVbjy2ZtsbeJH LMTGpL2f2Tvo46nWXs6vuz+0jv7VJdYa0+1xLJ5sc9k8sJ8u6ijkUOrLN5iyRr+72/LuZm8tvl2s a0rW88zWHV5UtdQ8xoprSR5pFnto9xV4Vbaob/SITJIqsAf3ZZtqsvLWN7KunQXVtBIIwyt553bV 2yNujZf4fmG1o/lZWX5vmrmLz46eBlWSKbV7ia2UR3sjXWnTXltHJHcec3lrt87zGz+7+8sflx7V +Xa32mWYmVSHsaq96J59bB1JTlOhHmPSobv+z7WAG9uNJ2wWMf2fWF89It0uzy/O3fvLiT/V/wCu kw3lttbd+8BH/aEzPJqX2211D7Rp0h00XC7WSSTaBJHKywNGoljkk+UtIF+ZCqx0NYz6bbXEKX+s 21qhSxtjtjumHmRwosysVkkbY275ps/M0rSbowrKl9qS3VvcXiHUpYFgtb02piuLfZGshcsmyLzG k2qd1vzu2IrKvmNu9w8jSOkv6/r0/A6/2zSY9s1xs+my6TFqU0l3HpcFnHLfRXXlrDp0UjNcMzyR rKrSMqurSeYwRm2yLtbdt3Z9YgjjvpWW52WIYS7bWVmb5Fc+WAu6T5W/5Z7vmyv3lK1J1RqfzaGx RSClqTYKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKA CiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAK KKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAo39ml5ZzwyNKq SxshaGR43AIP3WU7lPP3l5rD1rbaRwQXjS6jBHLLqMom01romOJvMRI/LUKskcjQmPKtIwiO0M2Z F6hsY5rK1rTDqmj3lmFt3M8MkOLy38+Ftw24kj3LvXn5l3LuGelMxnHmWm5zF1DPFapZKtzfXjQX VpJILq+tYnuZEWbhl8zy42+bbNubycLHHlm21ftVj1DVrK48gok051G3e7guJGEf2ZIuPMVRZyZk 2+X/ABKJfl3NJtr3dvayeI389o2uZtQEMMk0k9rNGot45mjgZifODNbqzJHsjZVfcGaOTdFq0MNv pgvdR0+5kN5A322O6Sx3XSszLDpszFtrfNdMsYVtpZPmk+Y+ZocXw37L9P6/rYt+XFNDu1KA6jb3 cH9n6gWhuVjlkWTygFs2VlETtJLuk3fcWPc0ifMtWO5TUNesIZJLdrqa3WPUZra2uLe7aaGVmt22 rlo7Vmivf9Y21tyqrN5jbq9xc2d1/acw1izs5kS5b+0bto98gt5ldW3QyRk29s8kkMkb7SfmVm+Y tJb1i8j0Oz1RpUungjcy2FmtxIbm9uED3TLG6yM7K23aIdowI5F2tGVFBXP6W/r+vn1I9QuFntW+ 0yW8941nJI/2i1uHzPaSLtmh08/M6rK2/cjbm/cbWbcjLLrOlLb2l06W2maaFkmtopDM1u9wtzty qzIFa3kkumX5l8wsVU/fYbefi8SXSfb7fVopNKia6k09rP8AtmGZriZovMEdtN50csM00lx+7Vvu x26/LDuXHTXS/YTdlb6DTNRln897z7D5dtO8u63tklLH96w2wqVWRXZo4/uKyqQlx3v/AF/T/W5H d+XdNq9rcbL4GSCzuz5DXNsY5JmP2drZZG2yeTMu+RlVdssbtuRdq25ludJbUFt5b1EdE+zyXEZv IUuJppOdit5xVWZdylljWPbtZVVtsE1w2ryRyaZLb6jIdt9aX93D5ltaLJbyRxyW7IqrNllO5fMD bZm+dVaNTFZyacLeGexn0ue68xZ4p9OszL/ot3dbt2yNi22Xblpt2xmRpWG1SoCtL+7/AF/X9Mrv Fbafb3ItYLkW0Zi+z2ltBe2kdva2ciKyqsasC27zGVVVftCbE+aNd1LeWb3UN3by2YKZu7KQXT3V 7CWnkjMe6BlVZo2WQbvm2w4eNW27ysN3HZW8bXHm6Xc21qmo3RXy5IbATR3SSb5pVZoY5I5F+ZnV pNwkddu2Ra0pNHb7O8SQak32Qw2tjJI1vNLbsU8tryOSYszMqzMGaRmZvKbCNu/eBnyyelv63L1w 1zJqEkYBnmtZ4biFP31vEIXXy23SDcszD9823H/PPcF+WSsWXUNOtLdZAsFqBONTsI5NGmWUeZHJ JMscfDSXTKt2xVF8xfM+aNv+WlGz1mzudYia2js7XTAsF9a3Mz2klukk11NH5saxyCQSXayt5cm5 lbcflVtySaunTJo8cVydSWXTrWKZL3UpbhpLeOC3aRVjcyXDbZlLfvJsNu8iTzNv7sKFX5n/AF/X /DdGQa3rNr4J0m6vNRvBb6boZhuFmuprmNUt2UwsJJvn+1Sf6xlX7zM0IZVbbI3LfDvx14V+Jmlp H4al0KS5S1x9nms/LnsvJdZLKNrXPzxw+Z95ZFUOv7v73y9JfW0dza3FhA0hmmjayhs7yRrr7ZbR /uZJJoLgqWjWS43SNG26RVj/AHjblWvjXWP2ZfHel+ILW/8ACFjJqelXF00+j6jZX8LOsatI0MjS KyqrNHGsiyfd/eKu7c22sqkpR+E9nL8Ng8ZzQxFTkl07f1t+h3Pxl/aS8T+FfEGraDoZ0+G2t7uG 803VrW9e7YwzRtIWbzG2yK4mUqu3y41+Vd37uRfMm/aA8Ws+n3k+oanZPHulWWwm+ywzT+Y0jP5M arC26Rm3blbdu+bdXN/GLxNL4w+IWq6hdTw3d4rLazXFpJutpmh/c+ZG391ljVv+BNXM6T5l1cRa b50cEF5NGskk+3bH833tzfd27m/iWvLrTlI/ScFlmFp4aDdOPNbf5H2n8N/2lNI+IXjjS9Ms9Ja0 kuGuLy/lZ0sy021Y4cfvv9I2w7lbdy3lq6qvl7V7S9l0fV4LWNdMj+3Wnl/aLqVJ5G86NWjG24lV WuAvzbZG3bsq1eKfAH4c+GtB83W4NcbXdXs4biK8h0a58yIqrNt2x7VZtyx/L5ny/wAX91qxfjJ8 c/F3g3xRe6TYW1vplu22SyvpI91wVWTb5i/NtXc0bL8y/d/4C1eHicTVxnNhaf4nzsctp/W+XDaW Pf8AXIobXQ9QutTty2lw2rTXXmwNIvk7W3My7fmXarV8i+BfiFpPhnxJq6QreLpF5cedHfNCsf2V W+VvtNvH+7mj+ZV2/LtXc0e1mqHT/iLe+P8AWtJbxNretSSWhU+ZY3vkyfu9u2SMNuVZP3atu27m 27t1dbD4P+Et1ot1qOq39/oc6iONo1+VPMeSST9yv7xmWNV8vc3y7du75vmop5YsLTl8UlI9ujSe GjKnX+1/KaHxQ8F39nqF1rMLR6pos7LJb31q+6NIz8san/pmqqqq33du3/dri7GTUdFeDU7G5ksp tzLHNa3G2eP5fm+625flb738Xzf3Wr1/4MSDwes2nS3uo2ugakyy6Fbaxbt+9+780cy/u2VtzNt2 /wAS7W+Zt3m3j6XxFZ+LU0VvCzW2ntqkdpY3StMyzK3yxqskkjR7mjVd3/XNV+Xay1vTqclT2WIP mK2R0sbXlNy/I7n4f/EK28P2MiaHNDpl/qEM0epWF1I0MEu1pJIzb3Hmbo2WPdHuZvvNH8rfMy8P rVrBYaXarcXzXF1HJ5cIVmaAwt83ysyqv+uaRflZlZvM+7tVpOu8P/B+DWNWtp59U+zaNcN/o8t3 bbHum+ZtqxrJu27VZt25W2/dWvJPidapDJeppN/PdaKt35gTc0MBb7qyLCzNt+X5fmbdtr1MLXlK UuV35f6/r/gHdlFHEKpKlX/8C6v1PdvAXxibwnpsOj+L0lgsmt1istWliZbm1s5Xi8xVZWjk8tlX 5ZI23Kyr8r7VVfoPTdas9UuF1HS5W1TTmvo50vLG+ubiB0eNrcFfLVo22yKytCG2J/rmKtX5kRXE kUcsattik/1i/wB6uv8AAfxh8X/DOGaHw9rMtjazOJpbcxpLGWH8W2RW2n+9t27tq/3VrtWIOjH8 OrEP2lCVpH6G6ZDcaZZ3N35cVpc2lraW9yptbi9nIizJIizttkuhtkZY225Ds5O5mZFsagkenMwk t8SWk8mo2s729xqLeX8pnK/LmOVhNNHHGrN8p+VWVWjXzn4U/EvSfif4FTWyYNM1CzMh1GO2FukW iXG24aS+Xzl3DzQ7fMfMX5sdpmr0a38OzX1vHI6tplvcGYvYwb4JI450DSqzQzbftHnZfzl5UMyr yxkbsupLmPzupQq0ZyoTj70f6/qw7TIIri9uTpVzboYZ2Km3gk+zKsk4+0q21/LkuPMhny33o2k+ ZfmbzOtxTRhelKtQdMI8isOooopGgUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQ AUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFAB RRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFF FFABSUtFAHLWusXuoSPHD5cbiVGmVkjkaw+WF2tp9s5zMyyMysvyqNv3vl8zLtpo/wCz4b/To7p0 uIYIrRrRI7m6vI4GllXddM0iNFNH91pGXHnN86ySfLtatpk97dRqykxtxa3UEEbT6bMY5la4DSMy /dZY1VY2ILNu3KzbcXV5C0EmvSW/7hIQ9pJc3H2IW0Kx/aGkuHaNZoFeSOOOSP8AeDbHGWT/AFij RHnT5o6svQnU911u/trb58XlbvsONv2uTdtxzt8vbu3fN5Xl7f32+oLO6f8AtTUJrOOO9uYI99yr xKuo3May3QjhVWESpGsg/dSOzK6+Z/10ZLeytIxqU6eHo76OSSSeOODT47d2kt5vMWNvOdd8jXDT zRyYVPm3bufMkuW80kskax6xJd2812YoZbS3WRo5I5ZXmjkkVWjWPbH5PzKrLtYeYZHXDCN7r+v6 /pGVquh28OpRTJeSPe6PayLBNa3E8l7Y2csG3c0f737W7TW+V8xfmK/xNH87dBi1TSdKvoNQ8UWV xqNtdXEK3UnzQefcyLJCssLN5iGNpljjhWb5o2T5ssu3autLeSz1K3sbaWyiVLiNLVZltYbuSYLI 03mwhpI28xpF3ja25pG2t8jVR8Taa+rWOqWkSXmoLvkSW3+WIqrWjLshWRPJuAxcfLNuj3O25v3a oqNnNpWe39aIpeKb2DULVtT82F9MVGe0uLlttsymzmb7TDeQ5a1VlkKm4b7qxsFX94rNcutQuZtU 1C1F1ZXDG622sL6r5MguI4IZo7ciOLcoYLJIwYyNs5wyvsjgks9Uh1DWZreNZZWe5DzafG9nOu6G Hydsc2+G6m2qq+czKq7du3/WLS6pqs2rR393pUtxPpy28E63yrI9v8qPMslukI866yfJ3RqwjkVt qsW8xSzmlo3bv/n/AF5E1vqG7UrW4EMl1dNHKbaO8hhivpYJZbdmkj3OjRww71WRHTzD5cfVlXzH K6pczSytHfS6TIt1fzxwNc/v/srK0dtCsjyQSbWjfZtbck2F3NIzCTUopZorlG0W5vrO6Ny97Z3R inW4jVPJWGNWmCx+d8rqMbNok8zy2ejULe5uleLy7jVoNPuJLuWKSONZLiVds1vBGskaxsq71Kyr IpWSGMMzHzMIuz6/1/X6ffU0Wx1Oz1zzpZvEdxHM0UczXU1k1ufLjnj8wovzIJCscjeWF+aSH5VH nKrWknabSoJZyurtBELc69DH/o9x9nucyR+UgSac7WWSOORQI1Zl2Kf3jtJis5L63ntrC3v5rE/Z zIitdTLtmlgjb7ZKyhmjU3XmR5aRfNYfxfvLtvcR6VuSzk/s+z02BQ+hx20czR2sfnKjQxw/Mvmb V2j5vli2rGrbqexMfeSu/wCvw/zQagr7WYN9lmu7iQw6feX0kLXV1HtaERyRyN5cTLbszRqrblZm Zf8AWK0DXS2Nw7DUb5maOe4keQsbsx29xu8uGz8rDx4laMyIvmMvk/NIzK66a6W8FxbIslwbySGN LjW1jtxLMsMisscny8+Z5kv3U2qGk2+WzLVO60+48mW0U3CXE0F8Y7NLubyJN0g2s90I98LYZdqq flDybVfylZUaOLj739f1/S6nzZ8ef2dTrNxrnjbSr23vBHHeX99hlW2RreT5oflZpGkZPMVv9qNx ujUrGvy9b6lay6etrf28knk/8e8kDLGy/N8ys21vl/i//ar7U+J3iL4ip4qtdM0fwNDqdvKt/a2t 5rl1ZsmpRuqs8O0bdse1dyx7t0iQ7mX92234hisJv7UWzaPdOsnltG33f9r7teVUhHmtyn6jkVWd TDONaV+W3LrqvU9k+Gvg+y8BX2m6vr50jWLPUre3fyLe8kF1YxzxnDNGw2napbd95lZoWX+9XrPj bwt4N+MyQtaahu1pYfJt3eJo4ZGXazK0jf73zbf738S14aqrEqqq7VX5VVf4a6TwXrmq6fq1la6S Xa6uLlUiVJNu7zP3bRru/d/N8vzMrbWjVv4axxGXNy9tTl7xpWhUcvb83vFd/AajS9UmktVXUtEn hjlX5ZI1jb5VVWX5VZWX7u5mbd91fLat7SPBYvPCVxHrV/o2jQ3p2266tY+ZdMske1biNfMjby/m +VvmXcu75dtdn4s8dR/DeHTLDwyLCeF1kuJvMtZY5PM8za0jf6tVbcu3aqrt2/7u3n7j4rXFnrl5 rCa7P9pvbT7RDHBB9ojsrz5Y1XbLtXd5Me1plX/lqyruWqjOpiqVpe7F/aOOeIrRp+0ekR/gX4Uw fDmXWtYi199V8OiwUz6c9szx3Myr96WHd88fzLJH/sybtyqvmNtJ8YZI7C3luYJIbac/ub8QLcMz Kq7oWjWaPaytubduX5Wjby13LXi+k69faDeNcWU3lM0bQMrRrIskbLtZWVvlb/gVT2+tQ2bRynS1 1GGDMn2KQ/NcMY1VvnVoz95dyqzbV/4E27io0KVWXLiPf/lPGwmbUcwxHs38X5/15mH8YNFvY/E0 85ttQjsY4oY7Fbqb7R/o6x/6xW+7tZlZl27o/wB58rVD4B8UW9rf6bp+vaTYa7o90y2uya/a0khX c3zedGy7fmb70m75V2/Kta1j8TP+EJ1bU9Rm8NCPSrDU/wCz11W+uIbqCPzGZrWZk/dyxqyw/LcN Gq7maP8AdtG27ufFPhPRfiFZ6z4jtLJ9G1uxt1kaO0WG7tpfMWSTzJFVfmZvut/Eu5Wb7rbd6k5U pfu/h/rofXKsnS9lUMH4++Jfhmtjb+GPAOgwxSafcsJtbRdyyr/FGsjbpJl3N95vu+X8u5WrxGu7 vvh7dLov9oM7a3ct5dsselxyN5LMsaxrJ+7+9ubb/tMv+0rNP4V+Bfizxl4btNX0ax+3m7nZILeO aNW2r8rSMzMu35vlX733W3bfl3VKtBP3jrw0qOFo6S/7eke2fsO/D/UodU1bxjPFJBpj2rafah4+ LlmlVpGRt33V8tV+7hmZvm+Vq+ya5L4beCbX4c+CdI8O2hEkdjbhHkwy+ZJ96STazNt3MWbbu43V 1nrXrQjyxR+aY7E/WsRKr3FpaKKs4AooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiii gAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKA CiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAK KKKACiiigAooooATFchrGn+TrCTi5t2kv7iGNY55DbTP5brIscc0fzMqKt1J5LK3meYy7kj3V1zV TvrO31SzntbuGO4t50aOSGVdyurDaysvcc00ZzhzqxzN5D/Z1jdX+srJNbWskcl55zQrZyMot2N4 iyyN5McPls+3euCsjbZG2sz7u3WR7Ow1Fftkcm/THbVblEGoRtb+ZIywp+7mY+XtKsqFVWZl+Xh+ u+grFls7uwWQ6eUnRUnkW2vJJMyTs25f3xLbEzuXbsbarLt2hNrVcwlT5TFvLcBbiK6060hutTtW WWwlmi+xapdvDho2k8vzXKR2+3d5f+rb7rbdsd6Ga31W4juLQprhEkN/aXE6f6PDFIpj3W8yx7WP liZurN+8wWVJFqG4aPT9N+zW41HQbeCyuoobfT7JJFijjZUWSNVjkXcqgGOP+JWb9223arNUZbrU 7aE3RE41VfIe8jSJoGW23MlruhPnb1Dq2G3BZLjEimParMfh/r+vyKi6baRxWEMWkW17DDcC2097 y1aJrdUuC8iKi2+I44lt4mhb7sjRw/N9yRtLT76/08Xkl88l9Bboz3kqWskZWVYoSFtoVjZpI2/e N/rJGVjsBb7seb9nkksbtdS+0Th9LtftdpqGnyXTNHul85WWFvJkkkTcrLCvyttLCRWjWrlxN/Y+ oLc6nNbxx2f2qcaneQ7/APQdqtIjTKscdvtkMXysW3R2+47m3NGyY6a7f11/ry3Oa1zxFqWn3N1a r4b13WNVupZHsYBqlrD9ojgkaRX2rMvlxBpFjZtpZo2hWTczbazJfiZoNnH4Yl1W/h8PalJf3Fs1 le3EOpraXxkTzo2eORnjcRySKrqyxxrN+8VfkjrtNS0uf/hHY0ubaMJDpE9vNFNLcamm5kj+VoeG vF+VvmbEjYwv+taotc8F6d4m8RPJfWVjqM1rFbPB/aumvcRwKZpDJ5bMwjDsq7f3eGXbG0nmL5a1 lyy/mOuEqcvdqw+a0ff8/QXw7Hc6hZ6ZLHdu0YhXyrvTb37TAiqYPMhkkkZvtDM0ci+d5YYLv/1b Hc0UdxbWvhmS4tgbXTLeBriOOS7htbTS2tvLX7I8kBOxA8b7v9Yo2zK3y7UrGj8AeHYWk+yWcUWr XFq1jb3dpZQ2WrRlWa2uLyNm8tRtWSNt0ca/Kq7fMVo1HJaD8HvGHhDxlJqHhvxzqEjSndqFj4k8 7ULe4jZmjSbzB5atN5cMPyL8y7drSbWXcc0or3h0qNGtzR57dr/8D+tj1K9tbPSFku5LS30e3t7i RxqtsYV8i3bbcXMkxkUeWkkkbK+3czZV9ynLRrHFYXMsunzRQfZ5Z7qxutJs41ubZ2lzNvuP3WUZ ozuYMVXNwQfMLRsfDLfxp8dPDmoa80XhHS9biS4Nxd3drZvEXKx7WWFXaF7jb5aqrbWLKqrub5Wq eH9p7Q9M0VLPx9FqH9rypcQ6hoP9nKqrHMytGs0cyr/yz+VVVmXa/wC83My0e0idryyt9i0vT+v6 8z2K+s7dlvF1PRYLy2nhhvNXsRatcwblRz5kX+j7rqXdDEu37wWONgqnar/Nfjb4EXnh34oW2q/2 bY+HPC8ljbwvcWccd1bWbMq28m5pfL+bzJFbzPlZlbzPvKyr3ek/tQ+Dr7yZRq+tXTaey3RW8hhj kul8v7OY41hkjVm3MZmV1ZV2yNtXbHs83+J37Q0Ou+F49LtIxY2zQwzarZpbxxJNdNI0kjW6/eKt I25m3M3yr93955ilKFtTty3D42hifZpcvN3tt/X4nSaf4N0q68N3FrA+l6jq+oTTLJcmWMxtJlVj 8kxr+5VZJlZVXa0m2Ndq7mjj891vwHqmhzX8mqWFzoNlbmRYpdQhkZJGVvlhWaOPazN/e+VW2/w1 wXhLxtqyyTyW+pSWM+1lVbSRo2WNvvfMv8Nex/Dfxdq3xDv7Dwf4g8Qx/wBm3Fy07TaqPtU0zMqq sMbSbtrfe2/d2szfebateZRxFSNSpCUubmO3EZk8HipYN6f3meWXWo3F5J5ks0kjKqxq0jbm2qu1 V/4Cqqv/AAGun8UeEH0d5ZYCs+meatvHcNNHuuG8mORmWNW3bdsitu/hVl3fNXuut/APwD4U1O81 XVbu9h0Czs7dpreSGZlErSqvmLMv3t3lsrRqPl8zd8u6OvEPiN8UtG02E+HdJ8H6OlzE2FMQa5b9 55jKVu0l+Zl3R/L+8Vvm+7t21UXVovmqy0Mcnni6s5yrS5o/gZl1pI1BNT1Uz3k/+kNIlzdQN/pf zL5jM25tsn7yNtrfL833t21W6zQdM8Ha9qb6bZWlxFI0dwILy9k4WPy2bzJNvy7o1Xd8q7W3Mrf8 9Kj1jWNR8TeHNNsjNAscjyT+TNcRtcLJ5k0n+kTNtZmXz2+b/Vtu+Vd27bz1xpo0nWLtZmu9Jls7 tf3e6OSSKNZNrfNuj3SL8vyr975m+XbWaxGExn8GpHm6WaPUw8cHV1hbm8rHqlv8H/Dnh/UphqV/ /ati9g17HeQzKVtVjZf30kKSeZJHI25fl+793737xeG8KQlb6O/MserSG0KLa/2k1neQKsRXzlk3 NGojCsFVmZvLXd5YVvl9Q8da7YeIPhrox1C60XR9XuopIoH2TRW/2VZGRfLh8uRtrKqsu5V/hZfm jXbxPhjwlBY3UVzpF9H4ptpbLz7n935NpGsci/aFmVv3jLH+7ZV8v5mZW2/LtbeNVxpypylGUiae IjPmjVl7xc+GGm/ESOSfV7QWxtL/AMy/+zagsT/bZtrYVYtyspZj975V27W+b5Vb6F+GOpW3iKyu tVgstRsFSeSzWDUrfyXTa3zbV3N8u75f95GrwHwn401jV/i1bx6bcPdz3UkcdtJcZjWCFVZmWSMM qzLHHJJ/Fu3Rqyt/C31dp9jFpkDRQp5cTSSTFc5+aR2dj/30zVx4bBR5o1pI8DEYeWBfs1Ucrl+l oor2ziCiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigA ooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKAEP 6V5p8U/jz4V+EvkprVzLJfyx+ZFp1nH5k8i7gu7HCqPvfeYbtjbdxWsb9pP4uP8ACn4fyzafOkfi DUJPs9grBTtOfnm2M3Kovsy7mj3Da1fnneXlxqN5PdXU0lzc3EjSTTTtuaRm+ZmZv4mrGpU5PdPp cqyh45e1n8J9Pa3+3lrE9mi6R4UsLC53jdJfXbXKkd12qsfP3fm3f8Bq14d/byu44rSLXPCcM7+Z /pN1YXZjXbu5aOJlb5lXHytJ8zfxLXyhRXN7SR9f/YmC5eXk/M/Tn4c/GTwt8UrZZNC1WOa4CeZL p837u5h+7u3R9wu5V3LuXd/FXetmvya8O+IdR8K61aavpN3Jp+pWknmQ3Ef3lb/2Zf4WVvlZflr9 CfgF8brb4y+GJZGhax1uw8uPULdFYx7m3bZI2P8AC21vlPzLtwf4Wbpp1Oc+OzTKJYH34e9E9eoo orY+cCiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigApKWigBoFVL+yt9Us5 7W6ijuLadGjlhlXcrqw2srL3FXKQk5oA568sb1diRalqEi3H2iAzRpb/AOj79zpK25P+We0Rr8rZ 3fvFf7ywK2r3lrdtFFe2t08cN1BHdS26ojYG61LIsm0Zj/eNtf8A1zeWzYXbtahZQ6hGsdxAk8ay JIFkAZQyOrK3T7ysqsPcVjXWm2Wj3n2htPlks7eOW9QQW0ciWs4LmR41RfOaaYTyfdDbtrfdZv3l nLODXp6mcJIdI0jTpFmGm6Pb7Li2ubiGSBYIdsjSRTQqsawxxwfKplOFbbuXcq7pReSafF5JWPw7 cskiojRLLp0t1M0LeZvAVmPnTFFVmhaVmk+U/KyyWNjqWhwz3S2p1K4k/wCPmGOSJZbjy43VJ93l xq08irbqysyxqF+VsL8y6W/2q8e2hlt4r35bnU7m3h+zTPMsgiVvs8is3lyLbyp5jN92NfLZvvKz mjf+v6/rqyJNQ0v7S98qaGbWORdWfUVu13Jbtasi3jfJ947WiDbtvlqzeZx5dQX0MdlpJgc29rY6 X5kQ8ywSHTbJY1We3ndZGUssKpGu6GTbuZuF2/urY1TVplmZj9gleCN4rSbTJJXt5JtixrJJHI0c myRZvMEbfKrp8yKvmSQ6hGtzJqEsSXs0xSa4s1WzY3FvcRq1u7wSXH7mNmVlEa7VVv3j5kWRiAJb f1/X6l9mfWHvIvsUmoW63UEsf9pxrFAjRzBWEa7PMLRtD5ysy4ZnTbJt5jZfNc6Tp9+Dcppthvnl k1Oa/LSWkLRtI0376NlDLKxURsfLVAGzx5dT3yyw6orw29tbz3X2eH7b9neeSRUaWR45Aqjy1VN/ lyM+3fKfl6LJRXTZvt0MkEFzpsHnyKIbQRoY/wB+8000q+Y0ciz+XGBtj81fOY/KZG8sNXf7O/8A X9f1cbHpt5pP217PT57czNJeNBo/2Xy5JEm3EEyKp864VgG3fKu1vnVsSNx+n/C6yuNPl8H6zDqu r+H7W+JgtlMkFqtqy7rZZJPOZplh8ow7VYclXkh+7NXXW8cl0PtCWdlHd30jXdhqEmly70uGhkVH uIWCtGyW6xxszSIzfNH+7yqmC10dmtyj+HjbWUkFrbHT4ra0CtaMjRmzm/eMrLCZJJG2bV2sqp5n zBp5VIcKs4fBf/hv6/yOC0n9nvwVolzLenw8bi3sZWW5spvNnjypWZbqFPI3SyvthVo4/wB380kY 3bSrR+FfhR8NtWmsvESeFrHW4W/0RNTsfOnsp2j8u1ZmtWZvvSeZ82JF2x+Y0nzbq9GvGupNYOow pJPMHlhsRPCY/m2MslvI/wBnZobdmt4pPNydzbcZXy1axHqjf21m5tIYtV+0fZ7Fb5PJb7O7/vFj mXzFkZltZJvLXDbVj8xY/vVMacI7RN/r1ecubnlzbX8v+D954b8TNa+GHwxh0+dfB+g69JrjSW0l xpMMdvDbW6hXjbcpbbJ5d1B8y7dylWyuI1rA8L/FjwpdaXHceCNKsPC+oWN4jq+o6Z9pmW3Wb98R ceZuZpLeT/VruZfLmjXc0kLV7RrHwn0jXri0j186pr08F6gt5daZriCRjtmmfZCyqqsqeXtk2xq0 S7Y/m/e1tD+FXg3S7O0S28O2pt/MSaWGfR7pw8Fw06wxMsjNh1M37zdu2qvzJGvl+XjKnLm5onoO tg3Rj7WLlVXX+nfb/MuppY8cfDey8NzG38yWGOOWfRbLZY2TRs+2MRzdVjkg8lo/9Yp27lj3fLxV /wDsn+GrmxgmWxki1b7PJPPONTzvuvlMceWt2URr86+Ykce1VX9238PsTPJHawX15YyXf2K6uLgv dxK9xBHiYK8KQo24lWCqow/lyfN8+5WgvbC83LMbPzr2GC3e7uLKJYG1Dy/NZYIm89WTbJhtsjNH tlZctuZl3lGM9JHnKvVjS9lGT5e39f8ABPN/B3wpg8M69BGlzJrWjXd9LB5loECxpHG+6O6kVd7j zI/L8vIj3L83LbK87+OPhjRtNv7ObT9Im0a1uvM82JY5FkSZWVpMxt+7ZFVvl8ttrNn5tqrX0JeW SPLOL6BNbtLO1awvJL7T2Nw0bQ+ZOVCx7bhZf3CmONVXcrj5mXy1y/FngFfGsMum6nZPHazX7TS3 mnRRwSO4jXybjcZW3BY1+ztuRmZtrKsaqpr56eUwo0/9ltGSfMrq/wDwf+HChWdGpGUY/C/X+v66 nyj8SPFlj4ka1gijummtNxN5dSNJNOZNrMrM0jMsa7dsa7m/vM25mrldP17V9FinTS9X1LSRNt8x tOvJLdm2/d3bW+b7zV7j4u+EKW+k6/PqMGqJdHbeQX95C0wgUqsm2Zodys27zlkb5lXy93y7o/M8 g0fwRqWu+NF8L2fkyak1xJbbmk2xr5e7c27+6qqzf3q4MPLE2/2iPLM8vGfWVVjiF9rt/W59B/sj +B7qx8P3HifVJFnubotaWkn8TW6t8zN833mkXb8y7v3X+1X0Z+tZ+k6Xb6LptrY2kfk2lrEsMUeS dsartVef88VeGOxr6unHljynvTqzrPmqv3iSiiitCAooooAKKKKACiiigAooooAKKKKACiiigAoo ooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiii gAooooAKKKKACiiigAooooAKKKKACkpaKAPz+/bL8VT618ZJ9LPmR22i28NukbTblZpE81pFX+Fv nVf+2a/8B8Ir1v8Aax/5OA8VfW1/9JYa8krzavxH69lsYxwdPl/lQUUUVB6QV6b+zf41uvBPxg0G W3TzYdSnXS7mI7V3Rysq/e2t91vLb5fvbdv8VeZUU4e6zmxFONelKnL7R+u46ClpqfcX6U6vUPxg KKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKSlooAaaxdU0 WTVFuozMktrdJHBNY31ss1uY9584bflZjJGxX5mZV2qdv3g23waTApkyipKzMzWbOfUNOeK3nNtc fK8UuH2rIrbl3KrKzLuUbl3DcuV/irl9Ys7W1a8hubqGa3XzHu476dpIbawm/eTNcxyT7WVjDMkb 7cRhtqrsWTd3gxQVFFzKdJTOQhEc+rXkC2fktcTxT3EFu0cVzGytIq3UzpNuaORbeKNRt3YXa3y7 ljpwW91qUMggg06We9gtb24nu9Jmt1W48ttlw0bf6xg0Nv8AuWdZI1T5pPuVd1K1m+3WkF5NBd20 lwpt4b+aNftE3ned93yfvW8cO6Pa2W2tu5USUtlYpfaba6nYW9g/l/abuwgt3ja0nklZmjuPN8vc rOrNuZP+fiT/AFnytVnLy3fL/X9a/wCRAbu2lvMQCK2OpSWd3HBLFNYTzSfMzM0mMySeTbj9xt3B YdsnyP8AKq22nLZ3Jv7ZI9KVNQN3K8X2SxWNpt0gnhkbDlvmbzdpVtsjblEmGZeWzTpqFle+ZNZ3 N35d46wTShtzQrHCsMiSK0LQsEldSqqRI3yszmN2m6hbx7LuW/so71pI4dQunUOr7ppo47SO4VY1 Zo7hjGqlWb+Fl3ybqCevK/6/r/hthBE+m31q6WyLqz2013c2lteLLcXhjO77OjTqrSQrJdNtbdGs beWvyq7LV60t7zS7PS7KO2kCWEdurDS4YYbaZSGiZFjZ2aOOPiTapzhVVWk+ZTQuluLHSRbTWdnp xuZZf9A026PnXrPA80qQyfufLmabzG391Qt8pbMc+ky2cGrEWemafYz3U827Ja3uZYI2ZpJfLMas 2LiZu+3E/mbj5m1gpcsZf1/kQx6VPpNysj21lHNCkKrfWulcNJcXG682KsjSIJGEbNu+VTiRmk2t tpWf+i2sDXTXqXCoIV0ySaaO5nljxcW8Mcklx5ckgj3LIysyzMrbmCxstJp9pbvZ21va2Glyzx2u lM6x2fkyiNZ2ZS1rIytBHHtdo90jMreZhWaPbJtLJcaY6gw3s0wS8nTT7eX7QlwPODKfOmVdkmGX bGZFVd7Ku5YwyszUVL3v+D1/r/gmZaXVtY/YpoYNPuLyDzovtFjFDH/aFw3nPd21sGmzHL51v5jq 7MPl+ZmZWZJ5I57O6iWxSO5urN3sLU31pclzH9lWTy2u23nDSJGzXGGU7RHtaT5qr3WrHS2dLvxJ DBBazw2s1zcXlurgRQfaZGZfJCrJIv8ArE4UQr5ieWaie305tNubA2Gk28v2W302XTNMlt5JLh44 2nbTds0ar5fksdqtt/dzSNiP71IfMto/1/X9XZd/0Lw+tnLOLLT4tLkmtDdf2XJDDBZ+V5wjWTdt ijVI4d0mfLLQ7cK21VW3097ZhDLZTPcR22nJKtpJM042zP8AevpGU3EanczKfm279yt5wWrTPqP9 sQSSwxPOEdILaOW48lYvPUSSSSbfLaQx+Uyxsm5WWVVdlZmXI0pYFaOCKZJL3ZHNp32mw3vBLJDM zXtxCsUbW8krNcK25lVtm1SrSMtMekZW/rb+v13J7yzsvs15d2Q0+z/037PaXkN4u2GZ5GjlmVWj aOO6824uV27W8xtqu3zbV8x8afDHVvCOvWfjH4f6NYadJbyTG+s7to/u7m3Sq0knlxxsq9I/LZVb /aZV9Xkvg632u2raPZ6fNYs8evNN5qtCiLJFJJwqmNWknb/WY2/MG/eNtoX1np0M11JLodo82JMT a9JzJNJNNFbxrMVkXZJ50yqqtujWZV8v95tGNWn7SOm4St8v61Wn9eYz4U/ECbx9plxLOunpPbMs Uv2KeR9zc5kMckatGrbdy/M33iD8ytXfleoPSvmzw/q9t8Hfjpf+HxcR2fh3UIVkMt5IY1gOGkVj JIq7lz5ka7WZfm+ZiystepXfxq8L2t9PCL6OazjUFtQiljNs8mNzRxtu3SMqsrN5att3KPvHbXmY SvV9hfFaTjudmHk63ux+JHo1FVLe6jvLeKeB0mhkVWSSNtysrd1ardeobhRRRQAUUUUAFFFFABRR RQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFF ABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFJQB458bf2ddG+MkYvJLiTS/EESRww 6gm6RRGrM3ltFuCsuZGP8LZ284+WvhX4hfDHxF8L9YOn+ILBrYuzeRcL80Nyq/xRt/F/D8v3l3Lu Va/UsKcVh+KPCuk+M9HuNL1rT4dRsrhdrwzqcdxuHo3+0vzCsalOMj3svzetgfcfvRPymor6E+Nf 7IureA0l1bwt52u6Eix+Zbn5r2H+821V2yL/ALS/Mu77u1WavnuuOUZRP0fDYyjjKftKMgrvfgX4 Kn8ffFbw7p0dsl3bx3Md1epMnmQm3jbdJ5nyt8rfd+b5WZlX+KuN0vSL/Xr+Oy02yuNRvZt3l29r C0kkm1dzbVX5vurX3n+zL8B5PhLo8+o6qI5PEmpoomRVVhZx53eSsn8R/vbflJVf7u5rpx5pXPNz XHQwuHlH7Utj3leFApaKK7z8sCiiigAooooAKKKKAGgUtFZmta1p3h/T5b7U76DTbOLb5lxdSrHG m5to3M3yj5j/ACoGlfY0hRyK4v8A4XJ4C/6Hbw7/AODW3/8Aiq29B8UaR4ns2utI1Ox1S2STy3ms bhJkDYzt3KcZwy/nTKdOcdXE2qWkpaRAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABR RRQAlFLRQBk32kWup72nhHnNDJALiMmOZEk271SRfmXcVT7rfwL/AHa01XbTsUEUyeVXuch4g0uG G3lsbe02WN5DcRSRCxS4snnnkT5p4VxI+5pJGbbhdpmaRl+VqpMqusDRSwSSNPexWq/2/cBZrpbg yLDwvzf6mTcvzeSqSRqrR7q7s/pWVqmljVoUi+03NrCwZZFt5DGzqyMu3zF+Zfvbg0bKwZV+aqTO adHrEwo7dro2wCyX9rcyfboLO/t5kRF86CTdI8iyMs0bFmjj/d/3dq+XuWtJHZxW9za6i9vFaQ28 lxrjX72yyXkflmBJLmNU8vy5Ejdt2Y8eSq7du5V6C30OEaTdWN3a2dxa3D3DS28dsEhkWSRmZWjy 25mDfM38TbmwN22otQsLuO1dvNn1KCLzLg28RWO5mcSLJDGsitGqqu1o9rfeG3e33tzM5Una/wDX 9fpczLf+1dWVSbnVtPmkkaGWO3treNbMNFLIjN5nmeYVEkKs0bSKZI1woXzVq3qVvqd9Bq0Fv5u1 5GVYrqUQCWM2wAWGaA+ZCvmH/WMrOpWTau3yyNmzglgUq91JctvdyZVTcFZ2ZV+VV4QfKvfC/Nub LU++s7fUrOa0u4Y7i3nRo5IZV3K6kbWVl7ika+y9zc524s4A13b6dY2+rBbjJ00mGO2tLtd90s0p 271Z5GjYttkbc8cir95qikvLdrfNtfx3OmTPZ3UErXc8asZrpm3JdbmWRW+XbAvy42of3ci7ekvL eadQsd1JavuR90KpuKq6sy/MrcOPlbvhvl2thqztQk+xahPN5n9n7jaxG8vZN1tJumZfJjj8xdsj Ftu7aMmSP/WbdqsU4cv9f1+Ohmw3Ul1f33lxxyX6SW6vNYxrBeNCLyZVWSKYf6lVV8SBj5mZmjVf l3Ubaa1tYb6fzrK2tlS31OUG7n00wwtczTtJNbn/AFJ272Zmx5zLIsgVVq7NCrXENtMJYYry53RW +rmG4iWWG4ab93mTzDJIu6SPlljWBTtj27WrSNqMNikazXPhmzeGCzWbVLiGaWGRmjVfL5k8yR/O aPdJIw8yGPbHIrEszllff+v69f8AM89+MXwv0zxRoj6pN5+n3mjeXYy3K/abtzaiZSkm6T/WBYZJ JH2qzeZ8vm/u23eHaT4XfRdF1l9Qjt3R7O1ntZ1LK6TPMm0fNtZW2ec23+JRuXcu1q+qPEGiw3Wj 6mhuotEutS0uWRrW+eM3ONs3mLPMWkzDG10hxH8sbdGZW21494Z8J3nijQdDjjtLaHwxFdNfX99I i26PbRsyL5km5m8z5LlmVWZV85fmVdu34TPnXdVUqP2l03vt935FU6fLP2kVyy8v67eh718OfGEX jvwpZaohVbh18u5jX/lnMPvLjc23+8uf4WX1rrl4rxT9nGaHTtP8QaIlxFfSWd6sjXNs++GQPGq/ KWwT80b/AMO3+7ur2kNmveyqu8Vg6dWp8XX12PQhLmhzElFFFewWFFFFABRRRQAUUUUAFFFFABRR RQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFF ABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUlLRQAzAZSMcV4x8RP2VvBPxE1k6rNHdaPeyO zXEmlvHGLlm/ikVlYbuT8y7Wbcd26vaaa31qXFSNqVeph5c1OVjiPAvwf8IfDdZH8PaHb2M8u7zJ /mlmYHblfMdmbb8q/Lu28V25wO1IufWnY/OrInUlUfNN3FpaKKRAUUUUAFFFFADKX6UVyfxK8bWv w68E6v4hu13xWFuXSP5l82T7sce5VbbuYqu7bxuplRi5y5UeXftDftKW3wnMej6IINU8UNtaSObL Q2sf3v3u1lO5lztXP+038O74c8UeLtZ8a6vJqeu6jcapeyf8tLmTdtXczbVX7qruZvlX5Vqnq+qX Ovate6ley+de3s8lxPJtVfMkZtzNtX5fvNVWvOqVJSP1bLsuo4Onf7X8wVb0vV7/AEG+jvdNvZ9O vYd3l3FrM0cke5drbWX5vutVSisj1nFT0aPtH9nH9qaTxdeR+GPGd0ia1M+yy1PasaXLHkQuq/Ks n93Hyt93733/AKlGPwr8ia/Q/wDZh+KH/CyfhrardXHna3pQWyvC8haR9q/u5m3MzNuX+JvvOsnp XZRqc/uyPz3O8rjhX7ej8LPaaKSlrpPkwooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKAC iiigAooooAKKKKACkpaKACiiigBu2ue1fWBbyS2cd9ptpN5KgyXkuWhmlk8u2LQ/LuWR/MX7y7mT au7cdvQrWIltq4jj8zULFmCQh2Fo4DMrfv2A835Qy4VV58s8sZPu0zOd7WRj6hqFjcJqlsbuWCVn uGv7FJ5Jr1o0hVT9nWGQtCdrW0i+WN370fKskm6pGtfserb52t49Vnnxb39yuVkRm3SWsCtNvVvJ tUZtu1GZfM2t8ygn0e8vLW406SLbb3MN8jx3LLfWTeZL+785ZNsjZVj+7XEar5ibvljNWY7ZJLqa S3s5Vs7u6UyvbxNbTCaHcGmmYsrSRt5MMa7Vbcu378bfLZxcspPb+v666DdNjuF/sq3Ml9YRC1WQ WVwnnyDau1o7i4LSKzfvIz8rbmaNjudd1eAeJPA0Xh//AIR2XUbjULWa0W3sYrfRbCZ5HkVmaQrP J5YDNP523aPu+Wyrtr3jRVZYbK8tobfULaSCN47jR5vKhuXuJN083k7vL2/dlD75HIaQDk/vPJvj l4TvLeSwm0m1uj9hMMj61d3mWtlbbDDGs0km5vmTezNu2tJu3fM1fJ8Q0Y1MN7Tl5nH1/T0uXGPu /wBf19w74ENF4L8XX+g3VzCbrVLW1uLcxyiTc3lNIy/JuXgM3zMy7tqsqkNX0Jt6V8WXmqRXN1rb 4+0XVjGsljq9rdzzb5ftas0kbbiscf72RVZmbdtjk3LJIy19V/DzUNR1XwXpF9q7xS31xbLK8kC4 Uq2WU4/vbSu7Hy5zjivP4fxPKpYBx+H3l9+z87/gb0nb3DrKKSlr7g3CiiigAooooAKKKKACiiig AooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKAC iiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigApKWkoAb 2FfPX7bWqXOnfB62ggl8uG+1WG2uVKq3mR7JJNvt80aNkc/LX0L6141+1d4VbxZ8Fdb8q0Nzdab5 eowHft8vy2/ev94bv3LS/L/7NtqZ7HdgJRhiqcpd0fnfRRRXmH7EFFFFABXpn7OvxPtvhR8TLTVd RJXSbqBrG8dI2kaONmVldVX+60a7vvfLu2rnbXmdFOPunPXoRxFKVKX2j9dRhlBB4p3tXgn7I/xA l8afCm3sbmVDf6FKNPZVdS7Qqq+SxVV+Vdv7v/a8lmz1r3qvSi+ZH49Xoyw9WVGW8R1FFFUYBRRR QAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUlLRQAnSqW oabaatayW15aw3du/wB6GeNXVu/KtV6kxUSipLlkBwl58ItA1K4S4u7ZrmU3zX8xbaonk+basiqF VlXdx8v97cW8yTf3Q44pfSisadGnTlKUVuAtFFFdIBRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRR RQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFF ABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFIwypFLRQB+ZPx5+ Gp+FfxK1LSYl2aZJ/plj83/LvIzbV+8zfKytH83zN5e7+KvPa+xP27p9PXQvCcUsEkmqtdTPb3Sn Cxwqqecp+bqzND/Cfut93v8AHdefUjyyP1jKcRLEYOM5hRRRWR7AUUUUAfXP7Af+s8dfSx/9uK+v elfOH7E3g9dF+GdxrjrH9o1u5YiRGbcYYmaNVZfuq3mee3y/wsv/AAH6Pr0afwn5Jm1SNTG1JR7j qKKK0PKCiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiig AooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKAC iiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKK KKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAoopKAPhD9ub/krul/8AYFh/9KLivnevsP8A bo8F3N5pOgeJre2R4rF5LW8nSP8AehX2mEs23/VqyyL8xHzSr/er48rgq/EfqmS1I1MDBRCiiisT 3AooooA9Y/Z9+OeofCPxNDbTTeZ4Yv7hVv7eTcyw7vl+0R7dzblX7yr95V2/3WX9HFIbB9RX5F19 z/se/FyXxp4Pk8NajIsmp6FHHHb8KrS2ZG2P5d2WaPbtZtv3TH1Zmrroy+yfD8QYCy+t0/8At4+k aKTNLXUfDhRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRR RQAUUUUAFFFFABRSUtABRSUUALRSUtABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFF FFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUU UAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAc74y8K2Hjnw3qOg6lF5llfwNDJ 8qsyn+Fl3Ky7lb5lb+FlWvzg+Lnwl1n4P+Jn0vVEMtpKWay1GNdsd1H/AOysv8S/w/7SsrN+nzdc V5h+0B8Mf+FpfDXUdMgj3apb/wCmWHzc/aEDbV+8q/MrMnzfKvmbv4aznT5o2PcyrMJYKtZ/DI/N mipryzuNPvJ7a5hktrm3kaOaGZdrRsvysrL/AAtUNecfqad1cKKKKBhXb/B/4rah8HfFp1ywsoL8 ywfZZ4bjcu6FpI2bay/db93975v91q4iigxq0o4iHsqvwn6kfD34haP8UPDdvruiTmayk+R4n+WW CQfejkXPDD/BhuVga63jca+Bv2PfihdeE/iNB4cnu9uia1uj8ieZViS627o5F3fxNt8vau3duX72 1a++dwz716VOXNG5+UZjhPqWIdPp0H0UUVZ5gUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFF FFABRRRQAUUUUAFFFFABRRRQAUUUUAN60e1c/fF4dQnkJ1G23fZF+0W586N/3zfu1jy+05b95J5a /u5F+f8Ad5jiFuNQjjhuft2rWM8l1aXNvdwQrFtZm/1iMqs0ahPKXbu3LIrN5n+sVmPtOhrX00ln azTQ28l7LHGWW3hZA8h67V3Mq5P+0wFcr4w+JNh4JivbvVmH9kwSQWiz2QluZxdyKzmGZFj2267f I2ySSBWaYK2z5PMlXUEms5NUvls51sXW7a7uLqI2Vgyh4bpIZtm8NEqzbmkVd3mMu5RuWPK8aaG9 54N1XS7eSfUbUMts1nqVjJdO/wC4VYFhkbH3Zmhka4k87biTcy7d0Sl7sWwhUUpq+36HXW/iKzuN Fi1L5oo5FXMUm1ZVk3bfKYZ/1m75Nv8Ae+WvONY/aN0HQrx0uLG8khWSaFvLeNplkjK5LR7vuMG+ Vt38LfKu3NeaeDfhbrXhvxZaW2oand6doWvRzRTQgrHJJGyyRr50fzRq25ol2t/FcKq/Nu28VrWj ab4Fs9J03wzJc2Ft/ZzW80Ud1I8YjaRt0KyfN50Kssm1mkk+XbH8vl18fjs0q4fDe3+Hl/4Hf1/y Or3Y0pyn8XQ+o/C/xq8IeKmt47fVVtrmZFfyb0GEhm2ny9zfKzfMPlVmrvsjkivjzwJ8MdcuLGbX I7e/sjp9wptSLbc3nrIq52/M22NvmZfLbd5ci/K1d7Yw6p4dmthoupWN1p/n3UiWFgk9tc3V5DaM ds1vu/dqrRovlptX5l+X5lrXAZpia2HjWrU9/lp03MaKnUpc7PobNHHTrXzBH8YPiDpds2s6hLbL Z3A/cWl5ZNGjbtrK0O1VZl27vm8xtqr83zMm7d0n9pxrbQjd6zpURmW4hhP2S52GVJDJmSONuu3Y F+9hmb7y1rTz7CTqRpTvFvuv8iPax5uU+gh+VKK8b0j9qTwRfRtLezXeiQj5RLqMSqrN/dGxm+b/ AArrNM+MXgrVbMXUXinSVgLrHvmvI4mDOW2qyttZd21tufvbeK9+NanP4ZHRGnUlDnjHQ7qim71/ vD86XNbkC0UUUAFFJRmgBaKKKACiiigAopKWgAoopKAFooooAKKKKACiiigAooooAKKKSgBaKzJt Ut7aadZXaJbeBZpJZEZY1X5j/rG+T+Bt3zZX5d33lrSoAWiiigAooooAKKKKACiiigAooooAKKKK ACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAopM0m5fUfnQAtFJvX+8Pz pc/jQB8PfthfBeTw9rjeNtKgkfTdSk/4mSxwqsdtN8qrIdvRZP4m253/AMX7wLXzTX60ahZW2qWc 1pdwpPbTo0ckMq7ldSMMrKeor86v2lPhtZ/DH4oXGmaZAlrpNzbQ3VnBHM8jIu3y23M/zbvMjkb7 zfKy/wC7XJWp8vvH32R5l7VLCVN0eWUUUVyn2QUUUUAaPhzXJ/DXiDTNYtljluNOuY7qJZhlWaNl Zd3+z8tfrDGdyg9iK/I2vvL9ln47r8SNGXw3qhkXxFpdqrNMxaRbyFdq+dub/lp8ybt33mbcv8Sr 10ZfZPi+IsLKpGNePQ+hqKKK6j4MKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooA KKKKACiiigAooooAaKVjSNXP+Kre1u7MW8wgkvZRIlgk1y1uxuDDIMRyr88b+X5nzR/Mq72pkSly q5jWenad5CwxW11aw3kGyx0+0v5rSUWbR28cki27NH9n8v5flT5o+q4kkZTa1CO4v4Zrk6Pc/afI tLr7NemOdGaORpPJji87YtwpX/WcLuaJt0gjwseoahaa55UMk7z6VrEkdpAN9nJbXUfkvcMyhtzS RypujZfmbau5VVd0lVrNm1DUJrhdIt2uYr23uZ41gtzcQSSWwhZHdbj5biNGVmk/54sscYkPzVoc Gm0f6/roWLq0ha61OS4u3murO2+1RTwt9pvLTd9pVXithGyqyqzojKrNLhlYNt+a3rniqw0G4tH1 e+bQrb7aLaGS4eNYbxvs7SY3HdtX733vLbdD/dPzZtheCx0sW8F4Y/s/l2FnaaWLWGG6lt1ZpY7V GZtu7ZJC0cjZTyG27dvmN5z421K08QeMLXRrHXrBNIt9U+zXOk21s3l3cjTW09xHJuHkyTRsu75T ub7S8e3cv77GtUVON5HVhIRqT5fv/r7vw7kXjr4X6b4++H1vrPjzTtT1ULbxx6jZXNxJatNbR3DS qzRWe39591ljZtkZKszM0e6vIdKvH8ReKLNdQFhFZS3fmmJl+y2yR7t3l7o1ZlX5vL3fNtXb/DH8 vqvx+tbvR9a0mB2s4vDr6ZcWNpbiWaNlmaa3ZWaGNNvlwxxvt+b5mlj3Rt5O6uo0jwfc6l4N8zww Y9O0jWooJJbFZIbuCNm8qGZWjkh+ZViRt37z5mVvl+aviMRGOOzH2V/dhZtWvd36+Xlc73+8qRjN +6Yf7K/xub4kaDc6Pf6BdeHdV0Vvsf2SbUI75jHHHC2HaOOPy5YzcLG0bRqwZSvzNHIsfcePPhof EEE99ZWuhyeJJLiEpqGp2UkkEccc3CvDHIrSYhaQcyKGcLu+XCrgfD3xNbaXqGvR3ng/WdC0Pwyj aWvizxF5cdxf+XM/7uBV/eSW+GjaNvutu2qu5eblp8YNGtdfSDS9It7TQb53uZdbun+wwzvn988a tH++bO0f3mb/AGfmr33WoUqcaeIa/r8l57FVJxp1LwVjy74v+JrbxlcTXMF1DZQQXlxbpDHEZI7v y1+abzwnzM223Xy/mC4jbdtryvxX4d1LVLGXUrKa/m09Y/KMlu6uyBfJVQxkMf8Aq/tEMbbVXd/D 8q/L6t8QvEQW1u4r9LGG9vopI7rSbOy+yvBfRyKfOmZZN0y+XLJtbc0bNtbb1rzi103ULzRdZuLP atvaxRtctJu8tt00axr8v3m3bWVW/wCef+zX5zjK1Knmt6nvc0b+n37d/I56bp4XGxlLqcd4qs7f /hH7ma8jZWVo5GWNvut935f++m+b/arg9W1a61LWrm6aNbadm+aNv4dq7dvzf7P8P8Vei/FSaz0O 3u7O4juDNa2/9oXW63837I25tsLf7Squ5m/i+ZdsbKy1Hpfwdm0PUNK1TxDe3H2S3WSO60W0X7Pc xSSLuj87zof3e7arLIq7tqyKv3a9nKaywVOX1uW3w+mn9fJn2+VV6OW4OX1j+Z8vo7bf11OZ8E+G 7m+FtqOlNJc6tb30IhtoVkXy2XdIvzRsrK37tvu/wqzbl27l9U0H4v8AjbTfE14dM13Wdat44WgW whjkvpQ0fyMzLJuxtaXdu+621d33dtfQfw9+E3g7wjosth4fu9N1K9kie5trsbJrj/WSokzHzPmV Vby/l2jiTGPMZa87+Hfhix+I3xV8V3mia5d2dqkVje2d4NLWOTbJ5nmeYkkKx+YytJ5cm1m2svzM vmRt9FUp4ipP93L0/qwSx+HxXtJyheMf+AclqP7Tfj2LUrTUJfEFpp1jCITNpsmlGNpGb95tkVlZ lVo/ussn3drfK25Vvwftc/EHVrpk0i28M6jArL5kv2W4i8vd/eVpv977u77te0R/APw/r2qR32sN b63Orxtc3UcColzNGfLZWX5l2/Ky7d25fu/WvqXwH8E6L4RFxpHh9RqZhikhknS4WR2+Vd0kca7u jfMqop+Zv9X95el/WacJPm2PK+uYGcLyo2l8jynTv28Lu1s0i1Dwpb6hdLndc2d69vHJ838MbRsy /L6t6fd3bVt/8N+H/oRB/wCDf/7TXJ/GnQfh9bpFp2i+E38P6nLFJqavc3XltcR7mVWhZZJI/L/c t95du0qy7VZmrwjVvDkOm6pPH5kNtL5Me5Z5N0v3dzLuVf4WZv8A2X71dP1j3uVSPaweFy/Gx5vZ OP3n2daftveD5NKhubzR9VjnkkKyW9v5MhQ5yv3pFZty4/h/2akb9uTwKtusn9la98zMu3yLfcNu 3/pt/tf+OtXw+1nHFdT2s9x5DRsy/aVj8z5l/h2/Lu3f8B/h/wBpWLxbP7ZL9iuJJ7Fl3QyNCyt9 3+JW2/7taSqOMuW5vHI8JKXLaR9/eDf2qPDHjK8WG10rX7aDZLLLeXNmvkQKkUkm5mWRuGWGQLtz uKNXY+FPiNouoQSrceKdLu55L1ktlWRYW2yMGgj2tt3SbXVen3vl+8rV+cfg9rj+0l2x3Utj5kbX H2aNm+625d3/AAJf/Qq7ezluPE2h3NwtzYyss3kyLbRyLuj/AL37yNlb+Fdrf3l/2tqliqcZRPMx WT0qUvjtE/RHTdXsdTFx9jvLe6FvM1vN9nmV/LkX70bY+6y/3etX2bGOcfhXyP4I8A67o/hpLotq WloLOOaHXIZpI1s7FVM1wsir/rmYyLIqx/eZm+ZWWRaq+Iv2h/GekaHbaxLqkVtaNL9iVLeKFpLm ZVRmby23N91l3Mu2Ndy92rya2b+xqckqUnzbW/rTp5Hyc6co1fZU1zeh9hMTuHGffNKO5xXwR4g/ bI8YazoMdhbpb6bO0eya9txtmk+Vl+9/D/e3Kqtu+7trN0v4zfFj4Jy2lhe6kskCIs39i6tJHcNG skf7tWVW86Hau1vL3Lt+X5fm+b3I4jm+yevDJcVKXLK0X67n6Fc07614L8O/2u/BHjOWK0v5pPDd 8yKW/tLatsW2szqs33Qq7eGk8vdldo5217xwwBBrdSUjyq1Crh5ctWNh9FJRVGAtFFFABRSZooAO tJxyaB0rK8QeJNM8M2JutV1G00y2zt868nWGPd6bmIoKjFydkeH/APCfXMOr+LruzS20uP8Atl7s XepQLd7o4rf7EwhijmV1laa1dV37FMayNn5WUet6Dq1ncxafqVlEqWWuw/bftMkq7mk8qLy125+Y tGpb5enln1rxL4d/C3TfH2m+JNVF1a31l4h1Zb25t7fzvLifbLJ5Fx+8j86NfOjkVo9v7xg3zKq1 ZuPhf4ovrHxPpk+ualZRJLHqd5NZWYdb6b5Zl+y/MrLIsiv8ysvzLD8v3lrg9pKKg+Xfz+Z7OIp0 KlVwU7KNunon5tr+vL6PpaxNFv7u9k1GK6tY7f7LctBEYnkZZY9qsr7njX5sN82zcqtldzMrY267 zxAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKK AG1S1C/t9Ls57u6mjt7eFGkkmlbaqKo3MzN2FXe1fJv7bnxKuNO03TPBdlcRiPUI/teoI0RL+Wsi +RhjxhpFkb5fm/dr91fvTKXLHmOzB4aWKrxox6nF/GT9sLW/EGoX2l+C5f7K0Rf3a6lsxd3PysrM u7/Vq2fl+Xf8qtuXdtX561XV7/Xr+S91K9uNRvZtvmXF1M0kkm1dq7mb5vurVSivPlOUj9Vw2BoY SPLTjqTWd5cadeQXVrNJbXNvIskM0LbWjZfmVlb+Fq9w+FP7W/izwVd21pr1zJ4m0Pf+9+1fNeRL 8xZo5P4m+b7sm77qqrLXhNFEZSiXiMHQxMeWtG5+pHw9+Iej/E/w3b65oc5ms5PkeF/klgkGN0ci 54Yf4MNyspr5K/bq/tD/AIWNoXm/aP7L/sr/AEfdu8nzvOk8zb/Du2+Tu/7Z/wCzXnX7Pfxek+En jyC6nbdol/ttdRjZpNqR7v8AXbV+80fzfwt8rMv8W6vo39t/wc+sfD/S/EMKyvLot1tlKuqoIZtq szL95m8xYV+X+83/AAHqlL2lM+LpYT+y8zpxfwvY+JKKKK4j9ACiiigAr1j9mLwr4j1/4uaNfaBH 5cWl3CzX93Iv7uG3b5ZF+796RfMVV+9/F8u1mXh/AfgPWPiP4lttD0O1M93MctIRiOCP+KSRv4VX /wCxXczKtfo98JfhvYfCvwVZ+H7F/tLwgyXF40axtcTNyztt/BV67VVVydtdFOneVz5nOswjhqPs I/FI7kdBS0UV2n5qFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAU UUUAM6cmuU/tJlme7k1i4u4IjcSNDpll5kBWGSRWjO1JGMn7xFZQ25mt/lVf3i1peJGVdLkR5ViS eSO2ZpLx7X5ZJFj+WRfmEnz/ACbcFm2ruXO6ufaGWS8vGk+0Q3Jntf3stg5maNb2Uqpmt2VXj2/d X/lmrbpgwkZatI4603flibJknGqBZJdRjja92xDyY5IpF+zfdyqsyR7gzbpCreYu3dtZVbntBsrf UdAsIbGGOeJdItYLeTb9mlht5jtm8u7tR5e7ZGjeXb7VVo1O5VeNl0LKC8N9BPHbRzzNIslxPHDJ p6PcR/6PNJIu5mkVo+Y1ZWX9yv7zmNlrSXpuNPUPMdVntoLeSCxvExLdNI0Zt7i6jW38y3bzo5OV Xau1mK/LtjowbXxPz/r+r/eS6hq0Mp1Cec50+SOeG4vLS+uCsVtArLIy+Wu2O4E0jR7VZZCqbtxa PYvKeAoLaztfEPjHUru51CaeOS6Xekj/AGO18ySVY4fOVXZflDL8qr93atY/xm17U/Dd/p2qaZqP nrpT3Nu7TLDMFu7kK0a7R/q2ht/M2sy7ts0a/vBJJUPxG/4SmP4ZlIJ2s9IS0t/NW8lZbuWMr8yy Nt+9ubay7l+5t+bzNtfH5njYU6slytukr/h/X9WO6lb2cpJ6nn2sa9Y/En4sQzRXX9kaddXEfkyX Fmr+W/lqv7yP7rbpFVfm/h27vlWvR/h78T/sWi2F9qnhXWrA3cIvtRuZLRJJYZJRul+1JD8sLKqx tt+ZvLZdyq25a8m8J6bBHfaLZalef8S3VDbT31pCVL/N5kluNy/MysjK25flXzBu2sq17XeTzaT4 VubO0v75cW+w3tvEslwpMOWf+8/+r/5ZruZv7vDD4fLcRiadSpOfxXcpdde1r/l6GuEjVrUnf4v6 0PPfiPe+JPECwJpB17V9D1QrILiZo5PtMi7tsaxxfKqqsbNt2q24MZOi1q/GG01OS3vItOa01Lw3 qTWSWEMUgLQSIvyraqr7eflLfL8yybdrLuNafhjTtMWWW4bR7o6loc00VhLqFs1tG6mSSSN1G3y2 XczMska7V+VdvyqzemWeye1v9Us7bz9REjLHJduzN91FO3areWGVU+6v8IZg1etDCvFe0hUqOMpe 936a/m/zuW8LOMby0PkPXg8N0kNzbyQXsUcaSN5/mLIqxqsbL975dqr/ABMrfw7V2rVjw1p1xrjH SxcSW1nczx/MsSyeZdeXJ9njXcy7mbcy7dy/xM3yqzLS1rUv7U1BpVbdHHHHbo2zYzRpGsasy7m2 ttVd3zfervvDum29r4fs7izmiCyQKbm6V2WbcsqzTBVVlbdCsNu21Nvy+YytuZWX88oRVbGScvh/ M8mhH2lfml9k3fBfgpRpral4z0VZraynvPtmpMkZkdTIsRWWRWyyxs1xJ5jbmXy925f4qvhfRtA0 /wAI6xDpGvWK2jyLPp+o6zeRxWkEkjXDXNu9rNH5qK/n3zKs/wBo3I27zPlXa7VrzxR/wrhIYFv9 F0q3X/SFv4ftHlia6YjzLi4ZpJP4flWPbtK/LtZVXxS81y7t2l0uGWOe18/zF2rt8xtu3d/Czfxb d33dzfd3NX3yqyo8tOhT5vd5uaWnlv5X+VtDvxGJhhlqtZfL/hjT/aj8ZahceLtKshq0nk6aGurG O2u1uHto22rC/mL8zMy263G6SRm23Srt+Xc2r+zDqsPwx1a8ufEVhN9ivTbT216u5GhkVZo93ktt aSPbNMrSLuVWj/i3K1dj8K4dO1bwXq/hRNKgsna5tbqe6S0gVXt/MlkjLbZI5JF8y3kXcvzK0i7W 27mj6uz1fTPFNheeG08GWlv4q3eTcXFrpcPk28bTLH9oj/eeZ/q5Ayn/AIE21c19RRzONT2cvhlO N/U+ohmVKrgo0FTtF6dv6/E9a8RSfbpm06eaaIQsuoLLYCSS4EUckcm1lWP5fM2zR7c7mVfl3Nu2 zXEN/Y+FpI7KNo7z7P5FnDp8CqsPy4VljkZV+X721iv3dv8Avcj4R8M654X1i+uYtSh1LQUjWytr e1uJilttwrkLNMyRiNlYN/rG+XC7eUrRtWudPkuYb69nnFtZ+WbaO5eOaea4m2s2ZJv3e5l2w/vP l3SKrfLtX0Pae1fvRcZbf1+Njw+W8bI8i8ffD/So/F/gbw7qfwuu/FKf2dZ2Nx4gsLy6it7XdM4k 3Ki7TtZmkZmZWYSfNWl+054C8P6h8LdN0fTbux0+/wBDlWPT7eTMkjqkPzWu47mXdGY2y3yswi3f eU16D4k8UiT4feIYpb3z7i106SO4juoFhuCZsrbvINyqrMo3GPCs25fljP7uvjubWPFngvxhdeG/ EWrWZvZhb2V3byI0jLD+7kVVkVdv3Vj/AN3aq/7Nayl7GPs6cT2cDGpPlcJcvJ66nkCyNEsqq3yy Ltb/AL63f+y0Ku5vl2/d3fM22p7+3jtby5hXzF8uZlVZNu7b/tf7VS6LF9oumhaFp/MhkVVWPc27 azLt/wCBKtZSlyx5j9MXwc8SXRtWXS5F82Fp1WaOdVWTb80e7b/C3y/M1ew+H/Del+WbODxNpkSa podz4gtZFjT9zeRorTWC87WaONlZl+8q/M0a9a8i8R29rDebbK1a2W3VYLj5mZfO+bdtZv4fl+Wu 1+Cnijw3oHjbw+PGUCHSNPa+lt7yKSTdbNdWfkzKyx7vMWRVjXbt3Kyq25f3itUacai5n9o8PH0Z VqPtYL3t+U978BfELx1ffBp72A2N7DazNp9vc311JbCEyW8cdtuW1VW8tWlXd96Tc3y7dqsvm/jj 4cTazdHVdU1n+0Lq4Xy7Jfss0dpDtkZWt7NWVt0cLfdVmj+Vvu7q3/2iPijJ4Hk0zw54Bv7Wz8O3 ll9v+1aXP5v2mRpJo5N825vMH7tV/wC+t33V23/2ffAGq+LPCP8Awmd9fSYsb37Ra2sOnswlEHl/ LHF+7X/lnt/d8bv9pWrlzBYn/mHf9f5Hy0o1aFL63C0VL+v6sYPhz4SwfB3VF1XXtKuNZ1a3t1ut MeMSR2SzLNH++Zv3cg8ttq7WX5ty/d3Ka7Dxn8Cx8QvDM+tax9r0zxLqF9Nc2s66Rd3ExhG5fJuB G0nlq2I9u7c0artVm+6vqFr8NdD0fw1rjX32u/sNWk8y5nublZLi2eNWbcWVdiusjSbmZtox8zda 5TT/ABg3hv4RazdxWsOnahbtdaNpVtpj/aGnvLgp5a27NI0mfM+YqrbWADL92uLCzxEcT+/lzRlH btL7u39NnmU8Xiqlf2nNfb+vQ8A8N/BnTbix1K4vLxZbCzlVb7XJyIbTT7fPyuE3LJLJJtaNV2/L u+ZdzK0frXwf/aA0PwX4eltpLuxttChWKSG1ZZo5AzSQx3Hlr+8+VfMkm8v7zbtyqq7tvzhdab4m 8feMD4ctbiHX72O7mjt49PkjS0dt21pIVXbHtZVVtyqvyqv8K/L6freh+GPB3woh8NXOu6VeeIdY sY/tulXkEkNzZTMSv7uSFl23ELXEcf7795823cqssderh6deMKftZ/Du++/9fI+gxOGlUhThiqnN Ju/u/wAp9n+BfGmm/EDwvp2v6Q8jafex7086Pa6sGKurL/eVlYenHGRXS8sRX52a5fXvwG0Twpr/ AIX1fWltdRkjv59POotNA88MMbXHnWsTfu9wWFfJ3M22Rf4t239AtD1e08QaPYapYzefaXtulxBL tK742XcrYPPIIr2YSjKPNE+axWFVH34SvF3NaiiimeeNrM1DVP7Nt1mlgkeLfiaRZI1WBP4pGZmX 5V9vm9qsXdx9nt5JX8xlRSxEaMzfgqjJ/Cvl7xLr3xJ1q5+IOneIdDstN8M2eqJPoz30/nS31qs0 itJJtbyY4/3UflwzQqsit96SRWkYXvSjHubU6ftHuey+IvizpPh3QbnWLy5i03T01C3sLeaYee95 K8iqI4442/5aKy+W5bo/mMvlrubwT43ePtW1D42aRp8rSQ6DptpHLJHazbpLeSeNladV/dtHcqsh WPzPu4WTb8zV2Hgdr7W7zxDr2m6xqhWQSQ3ZvrmG3UR+Xhbia4WNtrKpkZVhj+VlVdyx/e8y+BMd pdfGvxja+KZrfxHp9taTXFxdalIs6t5MywrM0033o1hkZvvbdu1vmZV28OOlVjejQ0l37fI9HC0+ VVJw3iv+B+W3Q+iIfjTY+H/hrH438cyN4WsrdGF5DAjXsUatPHHbyN5KMytIskEix/eVZm3btm5e nt7sTLZW+lNNcSWcn2VrrzpbqGOFZGV/MkaRfMm/0cxtzJJHJJ8wKs26C+1Vbq6voIpY7ixuraZI 4LS/23l3dJuSWKBvMXyfLWPa20/ek3ZjKMWsTYa3lvdTlt7nS4Z2e4/tCH7LBZxwSSyJOqyKxZlZ YfmZlTEYkTb91u2EXy+8eFWk4+7/AF/X3/I19AkaazdwkkVvM/nW5meUzMsgEh3pIqtGQzMvl/wq q/d+6ux/DXL6H5lnI0kMct5FO4huLiSyW3uWmiV45LiYnZvVvKiVfLj/ALrLujZdvUDvVdQpS5oj qKSlpGwUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUlLRQ BGq/dr8+v2xtQv7v423cV3beTb2tnbw2kmxl82Hb5jN833v3kki7l/u7f4Wr9CK+Mv26fBV1Hreg +LUIexkg/suVdq/upFaSSM/e3NuV5P4Tt8v/AGqyrfCfQZHUjTxq5up8q0UUV55+oBRRRQAV+kHw D1KHxt8BfC/2mzX7O2n/ANnS282JFlWHdA24bfut5e7b/tba/N+v0d/Ze0u50b4F+FILuPyZpIZL kKGVvklmkkjbK/3ldTXRR+I+R4k5fYwl9rmPjr45fs+6z8JdXnnt4bjU/DEn7yDUlj3eSu5V8ubb 8qtuZV3fdb+H+JV8nr9adQsLfVbOe0u4o7i2mRo5YZV3K6nhlZe4r4A+NX7MHiD4XzT6hpyya54b Z5GS4hRmuLZFXdm4VV+Ufe/eL8vy/Nt3KtFSny+9EeU5xGt+5xPxfmeK0UV9UfCn9jV9e8FXt/4t ln0zVL+DFhbRj57P+JZJl/iZv+ef8Ks38Tfu8oxlL4T3sVjaOBV60jw74R/FzWfhB4nTVNLfzrWU qt7p0jbY7qP/ANlZf4W/h/2lZlb9GPA/jXTviD4W0/xBo7SPp97HvTzY9rKwYq6sv95WVl9OOMiv zM1zwPr/AId8QLoep6Pe2mrPJ5cVo0LbpW3eWvl/89FZl2qy7lb+Gvuj9kr4f634B+F8kWuWxsbn ULxr5LaQfvIo2SNVDr/C37vdt7bvmw24DejKXNys+Wz+nhpwjiKb95/ie50tJS11nw4UUUUAFFFF ABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRVG+mls7SeaG3kvZI0LLbwlA8 jddq7mVcn/aYCgDn7vUUvNSf7Fdec8vkpGLK9R5ZBDdbbn9zJ+7VYy6rIy/vPmZeGWPOFZ3sE+lS Wmirb6xv0q3tYf7FvJLa0ztHA2lo7RRHcQyKyu0rRt8qv5S56C6+06p++srqO6dbuaO1uLb/AFNm 6wvG32lRMvnKsqyKyL0ZlG1TH5ixySzX99cLNJdM8NxGy6TayRwypCZkWOeRhJll3QTScMu6NnRo 2Zdtao8ypGUtf6/r7/zINNslvr1riOCz1XTNQeG+a8jSFbZ9vmNDNHjc8syrHaqWZgu1I2j27StW 7WPU1jtpb+2ku5oZI5gbW9+YSSM6yow2QrJDCsi7S2WYLu2eYqloY4v+EgjsRLBb61aT2KpcX6zb dPu4Zo23mODdIsnzRx8PwEmO2RvmVoreSx+1HUpfsU88KNqs8MOmSLer5itHby+VuaRZBAkkJ+Xd Jt2rt2+XSKj7v9f1tv19TyT4/RtHofha6t9QS8mt57pZbq2eRh9o8xfM2szMI1WRXXyzJuXbtX7p 24+g61omi+Bbq813XT4suLyOMr4fe5mXy2ZmVvm9dq7t235dq7W2su7c+PWsQxafZaKhku9Lsb+O C5Vp2+0wyxwq20ySMzS+ZDcRtuCttZW3MzSYWHxZ8J9P8MxXU2naukWn6bpEl9dRzmNpbiVpN1uH +Xa8bNDt2suP3XyqzSMy/leaU8RUzKtWoxvyxW/S/W2z673N3SqQlePY47x54s0DxR4m0260lZNA la8muLy9jg3A7pljjmVlZW3LHD5zR7fvXHytuVq9Bm8UaevjTSbmXWdLtdO1e2a6fTZSsN7cSSTJ 5B27/m/dq0fy/wAX97cqx854R8J2nijQdR1G2gj0Owvo5IoLS5t5rhTIPLXzFZpPm2/vNrbfvTSL u+Wuk8SeBNO8fzaPdeItPjvb2x/fLFHK0kW5lVmVvu+Yvyr95f4fm/iWvOo1qjnKpiIx9+3wr9H9 /wA+x7mW0eVyq1Phl2/r+vU3v7L0uGaCe3hEcsSSIGhj8ln3O0jeZt/h3SM235tzLu+981VIbKHW 1Lm1S3S+t5LK5luD5M7Rs3yxt/F5bLub+Fl3fMv927qHh681yGyngm+zQ2cqzT/Z5ArzbThVPzcK 25mZm/55/wC1uXK1vT9cs20xtIjBh+1SJepeFyu1huX5zu2LujkXd8u1mRfu/LXV7StGXtJRlt7v oeh7SEeY53wz8IdK1KxeW6N3cs8i2zXU9rJagTRs3nSbY1VVjl8v+6saq37ttrR1sW/w/a21TVE0 e4aO31YNvs5IFeDd9o8yORV2r8qr5ke37rL95fvbrW/xPqXha+t0Eei6zeL5cccb7tsbSKq7uG+b y/4l/vbtyt8tdI8mqalC+mJpWl/2WGuNPMdndhVNsqrG0abTlW+Zm+6u0wtH/Esja4fC4atT9pGM ub7Wne/9bHDL2cXLlh8Xl/TOG0/xJpeg+F7SO5vrbWte0x5o7J5LCS+tFaNvMaSKXy1b5Y/L3Nub asfyr93d4hrdtY33inUJ7b7PBY3N200G1GVYI2bcqsu35dv3WVfl+Vtu6s27+KAv7Wzn0vSbfSgt oo1S4gfLTyNHI0nltI22NWXy/wB2qq25mj3MrbW930XRrbxFo3iU6pb3dt9u1Wa7eCwkWOaVRtZY 2Mm37v3lWRf4t3y7t1Rmjr4lxw0JcseXzt9/3X/U4sdl8+eMFHp/X6Dfh9b6lY6fYWGpQxy6ba3s n9naosfnQh5GkhZlm+7Eu7zF/vSfal/hX5ulfwL/AGl4007XYtQubTUrBJDBpjN9kkuvKdjuO4bl jZmEbMqsrK3/AAJuc0uzt7qx8MWniPwvY6ld6N5n9k6jJDF+7aTa25Y2ZWWRV+b5o937hm+9XVWb 6pFeyCwVZ99zdTwm6u57WOM+RGqLI43KI/MR41jVfmjaOZdzK0jeng6OGrKjGN/dit9Nv68vmd3s 2qPK42j+Oh3N/qGkTbpNV1BI7S2mVnBZRCjLNDJCZJl+625o2VSy7lk+ZW61514j+Kmo+BZtFu0u l1rTdQmIuriby5Gl8lYY5JLfypfLRWwzbG6Sbv71b1xdQeKNFtI7vVra/kjuUukk0fVxG0Z27Wt4 ZlZWmbdMkO5hD8txG3+s5Z/izRU1S40O4vNPmbQ55mDwwKmIJpLyFoJnimVfmbc4k+RmXzGXuzH6 LHQxTpfuZcu2q16/l/w55lWL5bxKvijx+i+AfF8VwltYJFBqdlY2F5N5F7MYE8tR5bbt3mNukVl/ 5ZSW7bT5ny/Jvjzxx4p8cfEq0fXfCqaVrt3ZLZ2VvfW8iSxncxjaNZF/56btvyszNuXd/d+prHRP DktjcX2qaZq+rap9rmvUl023vhFOVuJZIHh2t5a/6zcvzf8ALRm3fMzVwvjn4eWUl/rXiCxbU7H7 DcreWsN5pl425ljVmn+0Mu6Nt3mfM38S/eVfmp1KtaNPnVv6/A9jB1KdNtVY7nyn4m8G6to1qt5e zR3Ks3zNHI0jLu/vf3fm/wDQq563uJLW4imibbLGysrf3Wr6P8cfDDxr4+sbSS+fVEufMaGKO/WZ pLhVjaVl+b+6q7lX+Jmbb/Ft+fte0OTQb77O8iy7l3Kyqy/LuZf4v92lRqe0j7x97l+LVany1Je8 Ubdo4riJpY/PiVlZo923cv8Adpqr5rbV2/d3fM22i38xZovI3ebu/d+X97dREzRSKy7dytu+Zd1d Pu8x7HvHaado+i6/4Y8U+IdSvLjTpLFreG2hjRrie9upVmb95IzKq/6lmZtv+783yt9AeFPjLpHg n4cz2Ok3FxH4J0nwt/aV3fpukvbS+mvGV7VplVVU/NJtby92MSLuWvnP4feFdR+Imt23hPT9StrB 72Tzo1vHaOGaSNW27tqt823zNu7+83975s7XNNk8K6l4i8NajHDctFNJYXDQ/dZo5GX7zL80e5fu /Lu+Wqb92UYnz+JwUMTP2Mp/3uX+6fXuvftiaElvPYax4O1r+y9RtIZ7K8UoIdSsp03GaPLLIq+W 3yqyq275W8tlbb5h4/8A2ndK1CR7Twnol1pOmraSNavH5NjJaX7LJC1wvlq279zJt+8PvfLtZVau O8XfDfxfpnw88OzXbz+I9MfTotQslszLP/Y1n5K/JIu3bDGy/L8vy/6P/s152rQNZ6hC93HGir50 EcNvu86TzFXbub5lXy2kb+L7u3+Kq96G5y4PLcHbnT5jtPgfcXdlrWu3tp5e610pmZpJJF27poY1 kXay7pFaRWXd8qsu77yrXunxA+HOgeJPE/gZtPjs203WLc291eWFt9j826hVWhk27WjXdNJGrMsJ aPaysx2qsfhv7PerXFj8WNEtYtxj1OZbOUK6oQvmLIrKzK3zRyRxybf4vL2t8rNXqetftCav8PfH V3pOqaXZy+Go5bi60p7GCOG8is5V3QxwyR7VhWT93uZl8xVkb+LbWUaVX2sqvN+7tb531+9fM48f QxMswk6b+ztc7PVP2aF8eeJptM1QX3hrRdJsPs2lBbu3ml1GVW8uS+YL03Ilv5i7VZiy/MuK9S/Z 01SW6+Gdrpt3LI2oaDdXGjXcUiqGt2gkKxxMy/KxEXlfMuc/3ql+E/xKf4iR3sul+FbjRdAjnDxX 14Vi+2NJ5rzSRpGGVv3mz5t3zeYzZyu09l4R8+Tw9ps13pEfh7ULmFbu80uJ0kW1uJf3k0fmJ8sj CRm3Ov3my38VelTpworlpxPlq9apyexqdP6/E6DpRUEkkcbRLIwVpG2qpPVvvf0rhtZ8VCPxjoVt Dd3i3dxLLENEKxx+Yquytcux+by1RZGVf+Wm2Pb91qc5xiryPPOpa8lu4Y5dN+zXsf2loZn+0FRG FZlk27Vbc6su3b8vIb5hXkmh6T4r1r4ia/DrR0m60cXckLWMrNF58KyLLFJ5as6ySRxtbqzMF3Lt X5f4e1bxtoOj3V7oOpeJZLrUBu84XBWKaNdkbNhokXaqrIrbv4RvbdiNtutoPjWw8VXC/wBjXtpq NoLdZppIZiXiZj+6Xbs/iCybtzKy7V+X5vltw5ve7HRHmpp+7uC6Tomk2U9q+m2Wm2DzrGQ0UUcM 0kirHwvTLb/L+b5m+7/dz8RweE7vwr+0/beHRdSRq1x5lw01yghNqsP2iSO5ZV/1LQxtH8yru3Kz Ku7bX1dNrlv4W0W7uPD+l3ut3Gk3JsLi00NFYXEyW+5bdVkZvJgVpeFVl8tl2/d3brPjH4R6N4m8 UWniWwk/sTxpagPa6hEzNvEfRZowy+ZHllV9rIzJ+78xVasp0oylGpJa/wBX/Q68Hio4Vy/vRaOF tNJ/4Vn8LJo/FXiyDxLqWk20jahJI0GiXMKyRzbQslq6mFlhmmbcWkZmDMrK3zV1fwa+IjePtHtd V1F5lmkfbZXTs1vb3q3EK3ixxQttZmjh2ruZPuqzKzbpKxdH+Fvh3xZYeHdR8R38nxGNxYSWX9rM n2eNJvNWeZltreNY4fMlhbzGkbcrRRxsW3NXoNlDDoN1eSrFpOg3d19jlvGWzby5JpJmVl+0fu1m Zj+7XgMrMrMreYq1pS92Nuh5tadKTv8Aa/Dv5f18yS1ezvotC1N7jTzPeTrdJuna8jlka0ZcWcjF dvyBm3KvzJ5h2jzGYJp+rJpy2EBube1tI4LRJrHUrzN7a+Z5kcfmSF5PNZ5FjjHzfMyyESSfdrn/ AIlX/i3SvB+uP4Qh3eKZLmNkgZJrqMxzSfZ42ieTbHGyqqysuGSPDblbd5jeSa9+0df/AAp8PW/h Hxno2o33iW0smtp5IJDDFqCk7Y7iO8EnmL+7V2ZvL3eYf+We1q1cor4iaGCq4hXoWlLt19fTv/TP p63vILya6jimjkeCQRSrG25o2KK21ueDtZW+jCrQ6gDpivLfhb8Rr74neE9B1u4KeH49Rkm8mOMx sbhlupdsEbMxyyw27eZ+7+ZZN0bLtbHW6BfTxrFbLHLOiSR2727TrJcaav2dZNt07TP5knT5lLH9 6n3l3SEM5OVOfJNa7f1/XnsdVRRRUmoUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUlAC0VlWuta feahd2NrfW899Z+X9qto5VaWDcu5fMXO5dy8jd1rUzQAtFFFABRRRQAUUUUAFFFFACZ6VxPxQ+He m/E7whe6HqEcbC4jZre4ZCzW0wUiOZcMPmUn+8Nw3KflY121A+tMuE5U5c0T8qPHngPWfhv4ludD 121Nvdw/MsmMxzx/wyRt/Erf/YttZWWufr9QPiR8J/DnxU0lLHxDZfaDFua2uom8ue3Zl27lb/vn 5W3K21dytivkz4jfsV+J9BvGl8Jzp4l0+SQBbeV1guYl+b725ljZVXb825WZm+7XDKjKPwn6LgM8 oVY8lf3ZfgfOVFdvqnwP+IOj30lpP4N1qWZNu5rWza4j+7u+WSPcrf8AAWr0TwX+xj468QX7Lri2 /hiyj+9NLJHdSSfK3+rjjbb95V3bmX738VZ8kj2KmYYWnHmlUieX/C34d6h8UvG1j4esH+zmbc89 00bSLBCv3pG2/wDfK/d3MyruXdX6fadY2+l2cFpaxJb28EaxxwxrtVFHyqqqOgrk/hv8J/Dnwr0p 7HQLL7O021rm6kbzJp2VdoZm/wC+vlXaq7m2qua7jd14rthT5D85zTMXmFS6+FC964v4zLn4S+Ne P+YJff8ApO9dp3FU9QsrfU7Oe0uoY7i3nRo5YZV3K6sNrKy9xitTx4S5ZqR8m/sk/s/xNa2vjnxF YyGfzN+k2tygCKvy7brb/E3/ADz3fdxu+bcrL9fdBRtAHHFLjioilFHVisVUxlX2lQTavoPypCwX inVy/i7wPYeL2tJJ5byzvbQt9mvbG4aGeDdt37WX+8q7fmole3unIrX1OpopKWqEFFFFABRRRQAU UUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAc5rHhW11hNRjmluQt/BNbyK0 zTRKskaK37mTdF0jXhlK/f8Al/eSbob5ZV1WOJ7ySGR7qOW0a4dVic+Wyy28aI6tIfLjlk/ebgrS Kw3eXtXS1mcW2mzkXkNjNJtihnuhujWZ2Cx7l3KW+dlXaGBbO2sGG8k0W4uBCI9PtHutz2l/EsEe 6e5WMNDNH8hMjLNJ5bbpGe4j3NHuC1ojkqckWPtZo1vrW7v5DazQwZZtTtUWeE3Uy+XbpcRnyvla Py2jXezEQlm6NJmSm3bw9f6NCP7UQ6M1vDp+kxWSQztD5kM8VrDM5CsreXGyzN5K7olLf6yr9nqT 2Fq3lPqlr9ntYd1nfWU14YViCvKBIu5ppmSVVyJJNzIdoZlkDaF1dXlrIkYW8v7q3uY5JI9Pt1ij kgmleNdzTNtbyl/eSeW/mfu8qv7xY2DGMVL+v+D28jx/9oCyS78P6YXae68Qfbtqw/xQRyeZIkLL GzRq3+rXd95/L3fNtryvS9Z0r4l/GTx3MNLt4zfWbx6eVSSS9kWD7OFaOGSSP5mhVpNu3d+72/Mu 5ZPeLLxBLa3L6LpfhuTxBpn2a4hu5tLvTe+aY52s18+5uo0jmuFjtgsitcNIrb1ZZNqyN8mfDOSD xd+0vbtBYWF/Zvf317YRatBdSNFcRxtNb3CszLIsm6FdzSKzNub5VavmMTgYSqVpT+3p/XyZ9bgK Ea1GtLtE9c8EaxrxXUIZPEtxp8zXqf2imoWc00kSwhZpDuZWXdJbxXELfMrKv3dzKqr30fi2z8F+ G9O1TxW80UpuFhn+xwtNOhWRYSUhhZnk/wBIkt4f3as26YfKuW2+PQa9H8P/ABnINHnsmmju2+yX l5H+/wBqxyboV8xVb5o925dvzNH8v3a9I0TXtP8AE3jjV9X/ALVub+40m2t0h0xrhnWx8yFpFuPs 8cjbbiRZmXzNu5lXarNukr4bLa+GhS/fe9KN/wCt/mcGC5vZezR311eQ6lqyXd0rjCbC21ZGVf8A Z/u/w/8AAvmo1jxfDpsdrGmlW979ouo7eCCRijLn70jbI2/u7m/2Vb/gXBy+P913OtvZ+fBG0kcc kcyyfaGWNW+Xbu2/M0a/7TTL91lZa6fUjYwzWn2ryfNjWS5WSX5ljaP5WZW+6vyyL/F91qyp5hU9 6UZep6F6NaPLGXwknjX4jaZ4H8MXWsa1dR2uno9vFd3xlmgZRI0cLMfL3MnLbV+b5fvM38VeP6t8 UdV8bR6T450i905bDTNSvLZr7R71dTeOFvLSOZo9vlxtJHuZo2b935kK7tzMsfXeMpo/iF4H17RY Li3ibVtPvbDdGvmSQwtuh+0Kqtuk+VW+Xb8zMq7l+9WT4s+EN74q8F63odvr+uWEupSW81msWr3l 41hcRmNoX86ZpJJP9IWPcxaONY1VlWOTc0ntYPHzbjN+9rpH+v1OuiqUYqVv+GMTVPhhL8KNBn8S 2KW+taIvkhtP1NZkvU3eSywzLDGyxyeWPJbdtVvM+b721vX7y00S81XQvEczNNPYyG0t76C5kEcs UkkcMiIUeNW+ZY2+ZZP9X8vzba8X08a5qCtp3irWdYutJNz9u1DUNSsVjb7VtaPa3lx/Ku6NoV2r tXb/AKv5WWvSrzwL4J01rfUNEuZJr24tp3srWZ+JCysyMiybW+RW+Xay7dse5t3JbrVIVJTw1oxV 1vr2ena369DxY1alZ8luaN/66HXyWejXduJoZTKtzCvl31s4VmVdxVsD/a+ba3ytu7LuWl1LxNoP hDR9T1M2ElxDFPGLlYLdpG8xvlXcrFflVWXazbdyr/tR7qOh6Dpul6XH9kcW2yzVLnUrc+TPGFjV Vk2zL/yz3fekZtu35lb5q8j8eXzWt7q8lhFc6rpGp2CS29wDbwIxM6j7RMtuy5CnzNrSRq29lVl+ VmqJVvq8faU4x+f6+VzXEzlH3Y/i7HqXj74f6T4i8P69JrU2n+HL3VNFa0u5biRJIdOWRU8nz1aR Vm2zxttb5VZV8vG3p6L4I8M6T4f8B+HdB06T+0NH0qxtbaznnZZTJHCiiF9wXazfKrbl714/8NdH 8QfEjQtQin1zV/CUtteREXOkC3jl2xP+7tQJI38tI2h/1bfeWeTzFbzN1etR+Jb2aKa+gt7a7sLS 2+0yvps/2x5yYRIsMKjb8/zbtzcMrR7f9YfL+zwNSFel7SMeXm/pnFzqpTVjoo7vddzQAS7440kJ aFwuGLD5WxtJ+U/KPmX5d33lzmanY2MOr2Gpzpdi+Q/Zka1M7Kd27HnLH8rIu5trSKVj3Fvl3VpQ zP5iRTRGOdzI6rEGaParBV3PtCqxVl+U/wC1jdtzV/6ivTcUZehnXQuZo7mO22QTGL91czReZGr/ ADbdyhlZgOPl+X/ezWQPA2jLrlzfJo9n5l5bSW91N/z2VmUsrR42tu+bcx+b5VHzfw8X8Sv2jPC3 grwZqOsaTq2keKNQtljaLSbLVofOn3Oq/Lgt2bd93tXg0f7bF5efETR9Se2v9M8IJaKuoaPGlvNP JM0bfNuO37sjKvyt8yx7v4ttRJwvaR6mHwOKrwlOnH3Ud9Y/Brwh8UoZ9L1H4c3ngiWESXEGo2at CdzSKzpuaNVbqNqsrKF3bdu2vkH4oeB9S+FviLVNK1K1vCtrJJ5En2fb9thVm2yRr/Fu2/3v9mv0 z0ltXmur64nl01tNe7V7D7MHd5LU28f+sO7aJPtHmsGXcvlhONxLBuveA/DXim7W61nw/pWrXMae UJr6yjmZV5O0Myn5fmb86zdCTjbmOzBZxUwc7v3os/P/APZNm0fWvixod3JeXbnHmaf9hiV/Om3K rKysrbVWNpmZvlZdvysrV7t+0p+z7J4os18a+DdMvJ9XmcT3FhDDHanyfLkkaTydiyNMz7fvbpPm 27f7vtHhX4b+CfDd3Za74W8I6ZAs1vH9muNLsreFYo2ZvnT7u3cszM237yp3O1W1fH3i278K2+ii 10rVNVl1TV7bTi2l2JuharI3zTT/ADr5cKqrBpOdpZTtb7tEafLC8iq+bTrYtYij7vTU8U/ZP8I+ Lz4M8TWnjWyvX0y6khsLLTtauJlxZrHtkX7PJH+7GJG+621tqrtj27m774hfs6+FPEnhnVLTTdO0 7w7eyQTC3vrHRreRoGaF41+Xy9zKrN5m1WVtyrhlr0+4RVMEz+biKVdoiL8lvl+ZV+8Pm/i+Vfvc bc1ial4J0vWvEP8Aa2rQf2uYzayWllfhZrayuLd5mS6gjZf3c/8ApDK0i/Ntjj/u1cqceXlPLniq k6sqsfdPkL4V/sk+JbrXtZl12K3trawiubW23TMVubra0cbbV+ZYfuyfNt3Ky/Kys1amm/sHa79n u7i98V2ltf7JLe3t4YZJoZI28tssWZfLZmjXdtVvur8zfdr7B06OWFZ4ppJp9szFZZhH8ysd2F2Y +Vc7fm+b5Pm3fea1tk+0Nll8vaNq4+YHnPP/AHzSjRjKNpHZPOcZz8yl/XzPPPD3w/ufh78JbXQd Lee9vdHQTwpYy/ZGvpo5vO8ss7SeWszLtbLbdsjfdXgdH4H8TX3iDRrNtb0tfD3iFrZZ7zQ2vY7q S03MyrmSP5WVvLba38W1v7pq5q39p3Gh3kdsWttSl3wQS2+2byNzbUmZZNqttUrIy/7LKu7+Kqtv pn/CQpqsV5dyX8lt9njgW9uDbyQ71bzFt93lNhpEzMq7gG2l9vFadeVHlTnzJynuZvhnx8+t+JPE 9g2j69a2mjR27LqGoaU8EV95iySN9mb703l4WNl8tWVh/FurOv8A4Wy654hTXb/UWl1CCOSGMtBH JDJG0ar5bRFf9Vua4+Xczssv+s+7t7H+09O1SaK1g1CCW4kjW9ijhuPnaPd8snyt80ef+At0rB06 Z/B8en6NNrMl3Y6bbWFo11qg+0Xt00jSQK8kqybi8kgi+Yxhc+Zy2793l7ONRRvrYi19jidS+EWo affxzaH5d9qMjvHc6vrs4uJmt2WPfy0bYkZf3Kq0cirGrN8rMyydzY+KtC8S67rGjyzr/afhy8t1 ucxzRpbzTKGt1SZlVWdo5E3LGzY83a33vm4nxV4f1iTxFoQs/F8Phuf7Xa3Wo6KyWuoR6gkLfubd ZLjy5FmmWGT99tZv3LfMPLWtbx14n8T+FfCV/daJol/4q1ay+wwWmnrtt7u+ka88mVpJvLaFY2UL IzKq7U3M3l/Ky9E52enQ6ZKVS13r/X4fgVtYuPAdj4uTxL4ggsdO8X6Da2tzdKsxVbOS+DWsW6T5 Y5Hby2hVpOVX/nmsnzaPg211PVPD+hXevSzt42/s1bHUpbGW3b+xrma1hluFCj92R5kMbLuWQ5kX /lm1VtXhh+IVnr3hKwh1TSZbG6cXkkq3VnE6XCzfvopGi23S7mZvLVtu5drNtxu0V1KCx0mZbVle z02IRotvcrbabZrayT7WkuFjXbloFjmjXzPLwFMe3czTCHVnFiJqKUXv+hoSXA8QW+p3FvBHqNrs WC50yRmeS5hNv5iwvbzNGtvMzTruWT70e3djcPLt32pXFvNOttfRm5ku2jitNTjMKSN9l3rDBIFB IJAkaTbNjEy4+XEdnUoWNxbefc6ek7Xqtpv2i3y6Yj/eKuZPmkaMXGGXbtVuVba26hfRhbieK/1H yBNthuZcXFvE0Mkk0dvHDJ5m1Ljc6K0iHc2F+Vd0e3c4ZXj/AF/X9a7l57Vv7U3Cx1DH27d5v2z9 1/x7bfM2+Z/qv4PL2/6z95s/5aV5h8WvhXo/xO8NWllqiSaZd2draQ6fNqM0gkspJ5VjfzJi8kd1 IfLjXy/mYsv+sXzlde2/tiGFTeSz6dG6f6bN/wATyTy0aL9xe/w7fLhXbwVCmT7yxt89adrp1rdR tp1w0kdza2rwGGHVp3lFtIzLHIzblfzGWHiRvmVvMCyN8zMf4jSlVnCfPQlyy/ryE8C+H7bwn4Zt dHsrKTT7Kzkmjt7WUxlkj819uDH95SPmVm+cqQZP3m6unWqi2cEd3LdiKNLiSNYpJguGZVLMqk+g 3N/30auVB1R2sxaKKKQwooooAKKKKACiiigAooooAKKKKACiikoAZ6c8V88ftDftOWXw+sZ9E8NX VvqPieQtG8kbLJHp+1irNJ28zcpAj7Y3N/CrfQ/pkV85ftTfACDxvo914p0OykbxVaxgyw2ke438 a/LtZe8ir91l+ZlG3DfLtzqc3L7p6GXewliY/WPh/rc+P/BvxI8QeBvGSeJtOv5G1QyM87XDNIt2 rNukWb+8rf8AfW75vvbWr9Cfg/8AGDRvjD4bGpacxt7uHal7p8jZkt5O3+8rc7W/i/2WVlX84PD3 h/UfFWtWmk6TaSX+o3cnlxW8f3mb/wBlX+Jmb5VX5q/QT4B/APTvg3ozSStHf+JLyMLeXwTCqvXy YvSPP4s3zN2VcaPN1Pqs/jhFCMv+XnT0PYqWiiuo+FCiiigAooooAKKKKACiiigApKWigBMD0opa KACkpaKACiiigAooooAKSlooA8h8L+B/Fum/HHXvEOrapcXGg3NrJFaW9vqUxsgGeHy91pIzLHMq xsu+P5W3O3y+Z5a+t7etc74y8P2/inQ30+6S5ltZnUPHalEY/MMNluysVk+Xn93/ABfdap4F8XXH i3S5Jr3QdQ8P3kL7Htb6Jl/3WVtu1h9OlYxtTfKbSvNc/Y6+loorYxCiiigAooooAKKKKACiiigA ooooAKKKKACiiigAooooAKKKKACiiigAoopKAOW8SajMyvZmGWOGZGVUjmWObUC0UzG3tpBNG0cy +WH3H5dvRvvNHCutXlrqFw80v9pWlm0kdwulqrtCSrTL50PzSbkjWFV8tmaRrjPlqu0rszaPa3Av C1uYZruH7NNcQu0U7RgttHmrhl2+Y5Xa3y7m24qpqceyUWc14zxancPDtlufs8kK/Z2ylu0ahmb9 2zfe3LukYN8qrVnHODi+a5l6leXGkQTJJqEct6qQXF39luUjmeZnjjhhhhuGZI47ho5IxmRfm+6S zNIs11pN1epJY3R1K7j/AHNut3OlmwSSOMyLfKu373mbF+7xJGpWNVyxYmpXbahp6vqlut098I72 wS7jKwv9jZ/s6fud0n8M2Dsfad27aPLbH0192mxa5PFdva/ZotWjvrKG1vZpDHDGGkZYYmZ7iaNp If3HmK0cf7tlZlFUYc0ZOyv/AF/w/wDwxHrfiLUbXxbG0F1pmkRT2Fkt5FqWq5ubaeaWZbSNrbcY Y1km/c+ZGzPMzbF/1KtXMab4B0LRPiF/wlMHhy5vPFcUcdrK8N7JPbafceT5aedJuaSRpldd0nls yxmOSSOPLM3QeLm8ReGvCuqQeHrCO4uLGSO9h08Hy4bayhU+Xb2u2BVkaQ2q7oWZfL+0v+82rGrV /gV8ZNP+NHhXTtdsttpdTWvnanpVxPHJfWDSSf6OrLGv+pZfMaORtu6Pa235m2+fUlD2/K97d/6/ r0Paw86kablHbZ/1/X6Hinxf8Gax4G+IS6v9sjkgvriS8hmjUr+837ivllm+6zL/AOO/7Sr23w71 C3Md/aRXKSeY63ce5tzFfmj+X92vy/u1b7q/LIq7flrc+N1nB40+Edl4uay1TTb2G0huYNOvY1hn h894d0c8fO2ReNy7vlZa8Hh8Qaz4O0HRNU0y5mWOVvLuY2hbyyy/MqyN/Fu3N8v+zu+8vy/luOy6 dHM/Z0/hlt+P6nm06n1PESlL4d/0PT9TtfCmp+NRpWoRQ2l/PG3lW9zDJaPqMm3zGa2kZVWby1/1 nls23d+827VruLdhfXUcgt5PPt/Mt4WkVhuVtu7av93cv93/AGl/hrxS38VXHh/wP4hkn8LaZ4k8 K65cyeJL+TXfMv0nKtumtWWThfJjtV8uTy/LVfL+VvJkkk6D4A/FS7+JHhmW21a0263pPlxXV6si st9uj/121VXy2Zo5G8tflXcvzNTqZfGjT9tT/wC3vU+uw9OFeNSpSj7sbfjqjtpha6XqUFqkWPtj K0axzLGy+X5arHGu5WaPbukZfu/6z5fm21JrniCTwnrgtbeyv9WvI2+0NbxzSR27L5cinbt+9Juh X/lmyr5bMu1t0lN/4Sz+y9Q1Kx1WwS/0do2ae5VlZ7G18tVYGNl+ZWYyNxuZlEnytt2rg6tofiXX NXeK5l02zgilEnmxRmZrdlk3RiNm/wBYq7d275f+PiRW+b5VPaSoUY1KEve/rvp/X3cVafN+6hcu eC7Nrixi1nUrMS6neS/uCsm63tLP5ZI4VjZtqqsiqyr8235f9rbe0mK7jvJdMUw2aS3MVysUMKtP Cvlxr5e1ZGjZWWFo93y/Mvy7ty1znhW/bTm1DwrFqCy31uzR28kdn5bWqtGzeZJGyqrLuX725t3m L/eqTwfptxcaOJtT1G8nGhXF0k5uIW/0qFoXbdKu5m/1bbt0iqu11jXczVpRlVkrVPelbb8X5Do1 I06aS/pnReIl0vUmg069sL64KrGxls2khmiM/mQxr80e1WbcyssjR/K23azblrzWz8Ya5cWdj4c8 M5nWCKSAT21ufMkjmkU/xKzQncy7mVtu5flbaq10N1qVlY+DtZ8PG8n1WSwvJVENy/2VrW22mMmZ vLkWRfM2qq/M3+rZdrKqrwM3iHQPC/iax1eJLh7Oznh2LFKzy5jfaszeZHt2/KrMvy/e+Vl+6vjY upKrUp0qPu83xW3/AA321/Q8etKpiJxUZfF9/wAj2X4M316NDfTtJurC016PVBcavp9/CyhbdpFW by0VV2ybYyqqGZVZvm7KvsOkarp2qS3T2dyZXEzCVGkbcjI7Qt8jfdXdBIvy/KxVmGc5r5U+NHhr xHpGr+F9c8Baetro3g6x1LULrWLKaO6liX7HM0KxLI7LI0i3E235Wbcy7ljjZWb3fwLrTeIPDPgq PU9etZNdeKO8E9zbRw3eoxrG6/ao7dubfzl+dl27o1kkj+VvmX9SyZTp4aNKp9n+v+H8zpjh/ZUI vmO9tbV4bVkhht7N/tDPsjBdCplLM38PzMPm/wBlm/i/imvrK31OzmtLqKO4tp0aOWGVdyurDays vcVdor3zn63PIte/Zz8Kat4u8O6vbaRo+nWOl/avtWmRaXF5d/5ke1PM6L+7PzLlW/CuiT4S+Cbh N1z4K8O7wSg/4l0L/Kp2p/yz/ugcduldfcXC28e5/MPzKn7tGb7zbe3+RWFBrkusa5r3h+XS9V00 WcELR6u6Rpb3azLJ/wAe0iszboyhDKyqy/K2CrKzLlRv7atJW5tiPxJ42s9D8HXPiOEnUrCOJZYT AQFm3MFVlb+625Tu5+X5l3d9eG7mazd7qLyLiHmWO38yVRgbvlYqpk/4Cv8As18x/sm+DoL7RdTt NS1S28daRban5kfiKfTJIbvULzdJNmaRpPMkWOOT/lsv3pmVWZVXd7ZN8G/Ddx4s13xDHb6pp2r6 zNbtqVzYardW/wBt8mExxbhHINqqrY+Xb8y/nhGU5LnRrWpQo1HTm9vL9DY1jxjb6VNqEMwmgurU CSOKMpJLdL5Uk37qGPzJm3eTMu1Y/Mby32q23dW7pmoR6vp9texLMsFxEsqLcQyQShWG4bo5FVlb p8rKrLz0rFsfCOjx6kNT0u1j0x5Lr7bPNpyRxrqRaKRd0zL/AK1f3zN83O5Vb66OgXt/e293/adg +nzQ3k0MW5kKzQrJ+7kXa7cMu3721t275Vq9bnPK3Qi1aG/0/TL+fw9pljd6tLIsghvrlrKK4f5U ZpJY4pWBEa8fu2+6q8dV38Vz+l6xeXGmm51LTp9Omeby1gZVkbDPiP8A1TSdNy7m+6NrN90bq6Dt xVku/UypDb+H9IdorYR29pAdkMOyNVVV+6u4qqj5f9la4Sb4paRqXixtNi8QLoA0XW7fTrr7fCi2 +syXVgZoLW2mZtrOWnhkwh8z9zt27ZFZtLx54Jn8SeDtXsINW1S01C4kjk+36XOtnevHHcCZbZZ4 wu1cboQ3ZZG3bjuJ56Pw78P9a1jQ7DWPsdr4hmjs9csPCdzf7HsZoXaRLm3tdytG24MrMqru2urf ekDc86kufl/r+v61NIcrbT1/r/hzu9b8L2vibUNPu7ptVt5tLn8y3+x6pcWkUzfK37yOGVVmXK42 zKw4b5drfNyz6Hb2t9cnUdQg8OXWv6nFeS2lveSQ3FzPHDHbsFm8794rLFABtjT5RyqyNuXuF1BU tZLi7RrGGEyGRrllXCozYk3K23awXd67W+bbytYHh3Q7TVLWDU77w9Y2dzJcSXsUUliiTwu0mVkb 722Ro1h3fxbl/wC+VVjGouSO5i2/hGWfh1PDfjGK/N0s8V1YWmjWlv8AZ4Y2t/JFzNJJuBXPmKY1 8uNfl8lW27d23zPxt46li+J3hfWdOt7y4vtN0m5OqWohOyCzkaOS4XEixyK3+jxsDJt+7Dt/1jK3 rjaBJpuqXupaXOyPdLawvYTyEWcarcSyTzRxr92aRbiTc38Rji3fdrwKH4cm5+J17baJO+sW+nx/ atQWaVpPtcizeZ9mmkb920krKu75VVdv8TRszeXmFR0KcadHSUn/AF/XYpyUfU7zSfEkdnp51e91 eMrdXUN3t1GZhJCZwlwtrbzeYq7dqRr5LbOhkb92yq3zj4R+Juraj8ePidD4j+Hklx47D6XqNl4T upbXUYdIFtCWWazmaRVluS15NceSnk/Ks22TzGbP2RoPgex0m6Gp3kUGqeIm+efWJrZFndtix/Lt H7tdqhdq9h/ESzHyTUGu/EXxR8Tat4d8C6H4isLKyt9a07WbKSHy9Z1CFbq3+zzXHy/6TG0fkx/6 yOFWaSRtzRxr2KlL2cFKT/X9Tvw1SEFLmjfT9Tpm8TpaatoPhLxBey/2rr2qahb6c0lui/afJVrz 7ZHDMsjL9mkQRx7m2/dk+ZWjrtf7UJuLuUy2+i30tlaqsV/dea0E0jyLGslureX/AKxgu6OT94wZ d37tTXDeAPjF4T+I2k2FpaSzQ65o9u15d2DpJLfWUluVhnjSO6iW6m+Z5bfzlh+b94u5ZPlrso/O 0fS73T4BNp8NvGxVbCEuLC1EckcP2VRb7ZZP3Kt5OG2tIfvL5at6VKSnHmjK54+J0qcslb+v66/g Xb26vIbOZpLqTTUvLlrfz7qWFHs1YeVE0OFdXZ5BGyrJz++55Xy6y12aaklnYXEGiLBcNCVjnSey tpPLjhtLd42ZWj3LJbyCGHy/mX73z5kW8vjFeXq2z/ZdRn+1wyw6TNas010I42g3ecqsbr7Oisqt 8iru37lWNquSXmoXFtfm1u7jUFkt7pI59JW2C28sUjKsa+azZn+bad2Y91u25Y87W2OOUuZ9f6/r X/hi8Y9RvtRDh7iws2+RkZ4dytHN8rIuxtyzJu3Fn3KqptVWZmXRsbJLWNlVpHVnd/3sjyNlnZj8 zHp83C9FHyr8uBWboN1ayahqywvbrcPcefJAlu0E4UL5IkkVjufc1vJtk2qrKq7d23c3REVmdtK3 xBS0UUjYKKKKACiiigAooooAKKKKACiiigAooooAKKKKACkpaKAOS0T4b+HPDXifVfEGmaPb2msa qf8ATLuMfNJzk4/hXc3zNt27m+ZstXWAUnFOoKcnLcKKKKCQooooAKKKKACiiigAooooAKKKKACi iigAooooAKKKKACiiigAooooAwvF2uf8IzoM+ok2+2NkU/bLlbaFdzquWkI+X739K4b4G/GL/hbm h3VzJp9zY3VsY2Imt/I8xJF3RnZvba3VWXc21lPzV1PjLwLpnjzT7e01NZjFHKGbyH8tpE3KxjZv veWzKhZV7ov92m+Ffhxong3UJbrS7do3lgjt90szTMEj+7hny3Tav3vuxx/3awftOfT4TeMocjjL 4jr6KKK3MAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKAGVzN9rlx cSTGwnjFskbW4ultTdo1003kqMRybgsTq3mKyj7w/eLskra1C8hsI1eeVIEaRIw0hCqWd1VV5PVm ZVHua5FrcTJeXV5b7p1gtb2aO+0f7RcosdxLN5QaH5Zmj5WNY9zRsFf955i7rRzVpv4Ym39suo9U ZC1wIpb3Yqz24kVo/s+7920f+rXcv3pv4ty/xR1iaXsurPT7ia4ttRvNQsrGRX024QXNwsUqs832 hWiE1urTI21UVcO/yt5wjpbXSre31CW3itzHPY/Z7c2mlCG18y189WtZDiTzPLhHnLt3Kr7bgCNg yrVhGmu7GW2+1x3H9oSJbzX1k1w6GZdyXSKqN/ooCwsqsJPlkbn5v9ZRy6vfz/r9CtdTvPLLeQXv lmP7dcD7ILrUI/Ohxbr/AKtlX5VDbrXblpN235o2Y8B4V8VafoPxS8VSW+v6Drt5qesm31BbHSVt ry28uALb20lwrYuNvlzqrNubzFkhX/VyeX6New3uuT3/APo99Lb+XNHZot5JYxiSNWjPmMqrMpka STay+Ym2FJF2sV3edaZ8NtJnsNX+1eE4U0fVr+916XWPDurzXS3VxJGmLxbfGd0sajbGnmbWDKu5 W8xvPxcK8qX+z/F5nVQqez579f6/q3zNW8h8PeKfhvZeHtB1CPW7UpIZLm31WHzt0cfmyTTFd3mM 0zw+Z8rfNcq9eB/FFtQ+HtnerqlmL60uNKttOsLOHUbuOGJLaO4vNQu2jEHkrMu1JFjZvMkW2k2t uZo29S0vwdH/AMIDf3ng/wD4SaGaWK8s72xuHht761yZrWb7NcRxMqzRzW6t+7ZlbyY2+b93u4CO 1fwzoHizw/rv9p+K7CTTo9RsbPxtbTX17cTbrhfJW3kkb7Qy/ZrKRVWSNWknmZdv+rj+Kx/8aNat HlqRXy+T/p/ge5hZUKnMqm7/AF8zf+Gei3998I9QsLvSJ9LuphN9mt722a0nkG5W/fRzbfvFWj2s vzLt/hbdWKulD4M6zJ4c8MaPfyWt7cW+preW832u7azVljeGRWh+7mOZV/eM21lbzNzNtj/4R3U/ Eo3eD213QpoppItWOqahNNvkVmj8xrxZJo7qRfL8lts0jR7Y428vbtX0bwja3Hh5pv7Xu31LUV02 1gaWaPy4JZPOn2x+c3+9t3Ku77rfNu21xqUYzk5fa6f5/wBdiYxrx5sNRuo6akNz8WtCFhPqMeov eyRyeS0USt57fw/dk2/Lt/i+7XHeCfFWofErUl8O/apLG7vGVbeSOaSL7GscbeY3yt5kjbfuqzbd 33q66z8P6b4Z1uw1U232KaScyosqG1t7tlbdJHJ5c0zLHDIqsr+X5SrD8zMrLJXlVn4qtNP8TRz6 Jpsfh24MV15ZjeeWNY2jZV/efMyzfvPlbcqt8vyqqs1FfD4bCTp+1qe9zfD/AJ/gKrUlKcI839f1 Y9e0X4S2tn4gnSy+I1vc6tIWilt2JklkeMNjcv2jcxj/ALrf3fm+X5aL3wN4q8L3VpLpUkUOtw2E 026CZJo3jjWNZI44fsq7WYtFt+98q7f7tS+D/C15Zt4NutAsbwyIy/a7sz2lxZNC0g+0ujKzfvPm WNW+8Y49v8Nd34p8Zab4X8cQ3WtXhsLKHTvLgY2sknmSTTfOPMXKjb9nj+X/AG6+njhqPLzSjyy/ rua89RS5I+9/XkfPeueDzqPh+48UWy2dvFM0cklvZ7o44N0jRsqxtub7235tyqvzLt27a4DxZ4G1 a+uv+JbdWepW2nwrqNxBHcTeRMqx+Yvyrt+Zd3l/wtuk/wB5l9D0PUL28024SSFbEaQkd4jQ2837 z7rKrMsitHu2xt8u35laSsKPxbPDp98sU+oreXe6Of7RKssUyyKvnN8y7lZpI0bd/d+Vvu7m+AqK hgsRGvCPvfgVNQy/ExrQj734HpHwJ1S58efDPRLXV59Fk1ZXW0jgvFiae5sUZV+582B9na6j2lPm WTduXczNvfs56p47tPDc13470+zsIJk87FiyrDYn95NJJJIZ2SaOTzUZZo2lZm8xppN3yx5PwV8b aXq/hfS9V0a+tpNcg086fdaZNHAkyt537vy42aPcvmXC7pPMXzMKpXzG/d+sMlv8R/DOp6dfaXd3 EHmOskN/NHGrSLKzCHzLdm4jKqpZd391tzLIB+oYelN0o1J6S/r7xYqS5pR5LL8vTY2PC/iHT9cN 69qbdJ2dppGtZVlWWPzJIYpjIvysWWDp95du1vu10fFZdtodjbaHFpKWyPp0dutqLaTMi+UF27G3 feG3+9WRDo+n+F7jVdYu7v7FDcXS3ck099Msany/L+fzJNn8X91Vx5a7f3atXpRvb3jy0k9jq81i agutLZaubKSyku2VzpqXETpFG3lrtWdgzFv3gZtyhflYLtyu5sXS/idoF9DDJJrOmWzSQxTM326P Zlh80Y3bZPlP95V+8v8AtKvBeOPGU/izwzqOmeFdXvrnWNDvYUmngkC3Gox+RGxmhEH+sj3XCqzK qrujkX+GsqlaFOPc1hSk5WMn9l+2vZ9Q8Y39xdz211Lrl82p6SQ0kcNw0ke1fO2rE0keybd5P3lm j3fdRV9r/sW1+xQpa266TNbW8ljaTQRQ+ZaxHav7r5WVV/dxMFxt+Vdy/Livnj4X6l4Y0PSbOG3n utHebVi+oWkOoNZ26RyQy7fL/eJ8q+XGzM26T+Hc3yrTfh148vtd+LOoeHtN8W30ltHcJDaTzyre F4reaNpt0bSN/ro4Zo/OX/nsrKq/dXmhioyhGR6FajKpOU47R/r+vI+nYLdYF2qW6s3JJ6tmvIby 6+IMfgfxrd+KYbe2vBI0emW+j3bJHHDGu77V53ysu7lvLdv+We3d+82jsL/T9avJrF5tZtbbWo5f tdvZWskkcckKsomjkyzecu1lXzPLXazK21d22nS+GdI8Y6Lr2n3M0Fwt5dOt21jOTsljKrH3+WRV jhyvTcvTk5zxFGeIg3G/Xr3XXf8AHTrqeJzX0sJ4Nkvrvw7No99rNtLrdjELWe70ufzZIztwsjrI rbZM7vvKwbbu77RgLF4zjhvYbTULTQtHW7kSGV9MjRdMtIvMjXbul+ZT9nVvmj6XPyttX5ensPh7 pOn6tY6mjag+p24w9z/aMyi6/dLFm4jVxHN8q/L5ittZmZdrMxq9qVzYXGjpJrkUdlaXka2k1pqU kfllrhljWCRdzRs7Myx7fm3M21d27lxoSlRjCpLl9H+vobx2sVPMTSotNvdP0mXX7jUZIYZ77Tnh +WFmZ/OZpplYwqZHYKjSMvmfKrVX1T4X+F9c8faF42vNGifxVosU0NjqYZlkjjkVldW2tiRdrNtD btu9tu3c1cvofwpn0Px3eeL9F8W+LJ4ZDJbL4W1PUPL0eNVYRlY7drdmiVPL3xtH97H3jG3PqcPm Kp81lJy3QY4z8v6V3xi2rzE20/df9djyj4oP4d8ba34R8JeILaCYT3635S4WNvLeFZFXyzJ+8jZp NqrIqruVmCt81dBJ4r1c+DpNfkis7aKNWmeaW9W2tEtGVZBdeZJGzfu4z83mLH92T5fu7m29vaWn iS91zTHtZ7YStDf3kOo7Vj8vd5iXKtuU+X8xVl2uv7uP5Y9zVzfiD42aXa3tpo2h3kiW0Uz295rN 1GzQxRwq3nLG7fNJOP3e35XVvMX726uCr7PCynXlO3N/l5+e3TVmNpJWmOluIvHVxaaT4V1Gb+zo bi3nutS0m/ZJJLdrVvLmkuG3GbzP3e3b5m5Y1ZpPmG30nSNBt9FtbKOJ7iT7PE0e+SRsyFirNJIv 3WkZl3btu7LN/ebPEfDjwLcaP4k1PXP7XkuGnK28lvNLJM7xBd0bTb9rJNtaM7W3bcybflkVY+61 aVtzR2yStfLDJNAoRmjZlXGG+ZV6yL8rMu7/AIDuVYaL96vUXvP8uhSvN3YQ3TSahbqwu4CUmxC0 YMTbZEG9nXdhv7q7hkM3y/L8tbS9F0fwLoBtdG0qHSdJs0kkTT9KswqIuWdvLhiX7xLM21V3Mzd6 8tuv2hPC0Px0svAq2muaxr9xaQTyjTrWO+tNGbdNHm48pmkhkzIqSNtKqskO5lUs1db42+IY+G8G tanr2veHbKzkTGh2GqXKaZ50ywlmje6kmZW3Nj5liXy1DfLJ96u/2sGuZHQ6c42Xf8TE+IXxa8K/ CiPS9Bube+A+120EdjYR3CMpkMrWkMG0bZDJNCIVhVtu3duxHGwrprq485pr2C98p4/t04+yC61C PzocW6/6tlX5VDbrXblpC235o2Zuf8L+P9Z8bax4f1fT9M0tvCmsaUstrrED/bZrW6WfNxbv5Z2+ VNCo8uTcuySFlkXc0cddLqEN5r89/i2vZbTy5o7NVvJLKMSRq0Z8xlVZlMjSSbWUSIFhSRdrFd2t OcZx547HDipQaXJHX+u2qt+pZtdRbS7eONZrp7K181gkmnXU07W8CeWy+YzM0kjSfMrYZpF+6rf6 yqrWc8klvp85iu4bCS2lGkxyrdT7BNIkM88lx8zL8sc3G11kt32yTdC5d0mlLqMM8iWbWt5Omoab fzX7bJJFkjeGIxssxZfmX5W8viOMMrGpbTyjbhdP8i7vI5766t1svNtrNplkkRo5nj3qG3S4bdu3 SK8gj3J8upzb+7/X9fgU7GaVls9R3XGqq/75DpzSNFqM32VCssJ+0NHDblVlXy5vlMhVt27a0nd1 zKxyf2p5wSQ3i3Jgurm2s1hWSFY5JIUkaT5pI185fmib/WFvur5ijS0SeS80mwuJiXllt43dvs0l tuYrz+5k+aP/AHW+ZehqWb0fd901qKKKg6gooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKK AEpaKKACiiigAooooAKKKKACiiigAooooAKKKSgBaKKKACiiigAooooAKKKKACiiigBKWiigAooo oAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigBCMjFc7ceF7aTT2s 7KS40y2aCK1WOwmaBY4Y2/1ca/djyrMu5Nrbdu1lKqy9DmjbTIlFS3OXu7W30m7Btob6Z445buHT rFPKheUFzIxYbUaSRrj7s0m1mXeAGVmpY7GS1uEt7eDVYUSWG0+1NcrMphjXzfM/eSN8rFmhZtvn Mxz91VkEGh2qSPphgHlWVrCYltdLuE+wWU0O6F4flCM/Lsu1l2L9nX5Y2HzZn2xtG0O7u57bSrLV 9O0g38jBYUlhkm8ySbzIvMCRxtJCG3faNrsr7pP3e9rOG635f6/r8uhDAtjeR2TWog0eC322yTKV 26d+7aO0jjgm2/Zbplu4zgwt8v7tt2Y6frMeqalfaVe6bd3ugiC+8/UIbyGe6LzSWfkQ2/lRttaF XuI5pGjk8tWtm/vSSR6El5ZaPq0Siazlt9MtHhnu7ppGl0+JY0km826bcNzhrRvLkZGZVaTc+3Al hjubH7OI7e5e40uCRfsaTTXP2q3YssSiaZ442nbyY2ZpCxTcy7sSeYwxQXLp/X9fic9ay6R4y8ea rawy2uoeIvCLR6e891Fb/bdJNxZ+Ybu2JiZv3yyxxndtRvJk67GVvAl8UeIvEelwW2u2OvfDnUoL uRpNJvrqO4jCrdXStNDIq+ZIzLNt8zd++WPcv3VaT6rtPC9pbXBEsEF1beRaxx/aY2muN1u7NG0k 0jM0m1mVl3fMrBm3MW+Xx7Tf2XGt/E/iDW7vxXNf3ut+IbjVbmSazLOtjJGEjslZpG/1W1dsn3Qv y+X91l8TGYb23LHW3W3a67nsYdxjCXPv069fy6/geZ/C3xRpGi+O5vBp8SWMWt3W7WptPW323N9J NHuk85mj2ySfdk3LI0m1fmVlb936c5Fxq19qIEEUmnosEDq+Wu/MjVvJbarfeaSPaq/NuXb/ABbW 6/VvgppepRi4uh/a91b6oNbs49RZmhtbpbVbdPKUf6tcL5n3W2yM0i7W27fzy8JfFS68MfHXRBoe hm/8JQ39zerPp+mTBruG6uWhkkRYVZZGWab7HHMq7ZPJt4/l218piMBKNXmq+7+vfb/L7z6PAQVS nJQl8J9U654R1DxBq3iHXlTfawWsc1h9pjW4t3ijCszbt3lxr8rbVkVlZZG+VfmZeJ1O6n0vxHdv biO1mtZmjjMcHk+Vt+Vdqt8ysv8Aeb94rfNu3fNXa6p4utPGt5dfbbXxHoGqeHoY73TrvU7K40qD UdqxrJ5EM22SSNd3kyRsu1vOj8zzP3e3hbCx1TxLr97bLbPqP2PToZ5b+CKK1jdtqx+XtVVXzFb7 yxqq/wB3/WR7vDzTC1MSoyw/uyhby/p7ef3I8fMsNUrctanudpDH4WWwRdQ0W58L300cdzDKl1Ir Oqxr5f2eSSGRVVpI/vMysuf9YysyquqeDXvvDeh6ul5FcaNBYqGaI5njTc080e77paNWZdzeX8yq u3dtVt/xIkXhfwzdaK+r6V4tuYdOP7u5dZZbKQMscn2VvmZdse3crbdu1ZF/iVfP/DN7B4c1ywuP EWl3F1ZGBZLeOWJW+Rm3LIscnyyK3zL/AMCZlZW2tXoYvMXhXTo1/e5t5fy+ttGQ8Y8LKKlrfqza 03wpqPiZbzTPD9tFexQTRytHDdqyttj2szOyru+Zvl+Zdu6TavzMy+ofCbwDr+g6VHHq3hrTv7Ui lhnnur2SPy52jhmWMwJH5nkssnl/M25tskh3M1eJ6hfDwX4bt7hdATxDr2pq2naZJbND5UklxFbw wwssm1FZpJ1jaT5vla68zc23d7n4B1i/0e4ttG1rTzaa9bzvHPNaapeXVpPeTxrJu2tHGWWRfMk3 eX5MbRyKrbt232MuVCMfbS97p/Xn/W2p14hy9lF9Jf1c7bRPEWiTand21u63niWCyUtDKIYtSuoF VWDNG21lG+b7rrGqtJ91VZWbZ03R9Otrye4gto0vEaSNrx7ZY5SsknnFFYKu5d0nv82d25txrzXU Nc8Rf2tp2gI+nabcyRXRtr6+b7a9pIln5ayw+Y0bSbZN+7f8zLJ97/WeXu/BZtQt/CMdjqXjGbxx qtv5n2nWDbRRQzM1xMysvlMyA7Sq+Wsnyqsfyx7sV9hCalGPKcE6coK7Z3F1evYwz3EqObaGLzP3 KPLI23cWURqm5uAu3buLZxt/vc58TGgs/DtvfXc8sUGn6lZ3LvHIwwq3EYbcq/fXax+Vt3ZvvKtd rjODWN4o0dvEGjy2i3L2U2+OWK4RFfypI5Fkjba3X5lXinNOUGjCDUWjgNc8ap4T0eWLSE1GztI7 m3b7XqWmXC29rC0gWSONWjDMq7c7GK/LLtjb5VVeM17xFrnjXTJLhdNtIF1aKGFNQkZWspfsTXE0 jfvP9XuYfKsi/dVt1bHxf8J+JPFWmPZ3M+u6csEkd3Hrngac2txNtVlW3ni8zzHi3yOzLHJ/d+Zf mqTwLrHhXSPhzaaLq87azdabJMfsniOeF76RvtEyq0zTMqtNt3M3zfxf7S58uo51qns+a34HoR5Y Q51rIb8KNesvDuiQ21y9xPqUVqMafp1qZ3mhbbcxyNtj8xf+Pry/mby927/aryTQ/hz4h+G91ceP 9V0vVLuBbUxx2ukQrBfmOePy9qxtMzfaFZlWNVWPc33ljavSrPRPhZ441g6pfHTYYtI1yHVNKR5F sNs0MEHlyY+V9qyeZ8v3GZm3K3FQ/E6fwjrN5olhLr9nf3Vpb+ZJrF5MrZj+0wx+XNJHtVl2STNt yG/d7ty/Mx5sRzxw3utc0dFr/X/BCVWpByUF8W5D8L7/AE7xJqeja7Z+Jdd0a8vBCy2/iK9hmkvI VZs2skat+7kXzx8rfMrSNtVtu6vVP+FneG1/4SKaHxJp+rvo91HBeWdjcRSyWEjsIVhmCt+7YyK3 zSbdvzbsKrVifDf4P6X4bmn1a9nj8Qay1xJm8lPmKjLM3KjtJ8q7s7mVlYbqmn+Ha2fivxHHZeFf DMHhXxFYkavNZRtbarf3LG48xZNiqsissiFZGkVlbzvveZuXqy2jOhSTnDlk91e//DHl0Ukr1P6/ pHRapD4i1bwfMqCKx11vmECTlIm2yZ8nzlVmVHVfL85V3qreZ5at8i4un+E9M1CPwzpFzO1vJ4eS 0uW8PWNz9rsoJIYmWNZJGiDSKrSxyR+ZtYtawyKqsjVuaPrktxDa2Vmtxqc8USi6vroosassvlyK 0ka7GmXbNlI12q0eG8vcuafg0aLqGta5rWiahFfz3F0tnqsCXscxs7iFW3Qv5e7bIvmBWjZvl/Kv RqSk5KK/r+tDd80dDqbLznE0sxmTfI22ObZ8ig7fl2/wtt3fN83z/wAP3V4zxJZr4417QH0HxtPp 0mi3EOpXun6TdW7pdW8yts+0RmNmaORVlVcMi/M0nzNEm3Ua80z4leGbS90TxBHeaZJcK8epaLfM 0cqxybZUWSF/m3bZI/vfK3+0tR+Iv7K+H+n+IvFlp4b+3anIkc+pNpMFvFe3yxLtVmkkeNZPLj3f ef7qlV/ulyn9p7EK6ZzHiqa+8RaTq2jeEJrnUvJv2XUZWusKqssrTW0M7bv3gkCrt+ZY/MC/Kq7V 8k8NfA/Vby40251hCmjXUElw7abKs0ixqFVdrKrIWbzFZVVm3Krbfm+Wvplo/wC0vsF2kcU0cf72 NbqFkljZht3Lu+aNljaRdpXd823cvzVQ1TUrbw1JZWlqrNe6ncyyRWyNvaRlVppcK8i7d21lznar SLnivExWW0cXUjWxMubl+S3/AKW5lUXP1KurX0tl4bvX8FW2mXuqbYZI7WJkWN13LFubay9I42Vf mH+r2/w0/VvF+npq2neGpPEemaN4uvBDdR6X9pjluZYVfdKscbbWZWWOZfM2/L8zfw1zXjM3Wi/E Lw9q1r4avvEGo/ZdRe4vrJVjt7a1ijZo42DCRmmaSSKNVj2s26Z/ur5dbXiD4c6P45tob/VdMh03 X2itR/aVvHC97a+TcR3UcazMrblW4jRtrZVmXO2vSjzurN/8N67b6/gXDR/vP6/rsbEM1/o32Eah qFnPZsGhlvpx5ErytLGtsu37pZgzK2Nu6TbtVd21fPvi54Ri8b+LvDWla58P7Xx34fSOa7aeWfa9 jNDtlU+VIBDKZZI4I1VpFbDSbt0bSVY0e48WXXxScXthAdJ0m5k0uHVp7S4jmu4ZrWO4Zo9rNH8r xwxtIyqpaORV2s22uv0O1juJNM8hfIsrWExLa6XcJ9gspod0Lw/KEZ+XddrLsX7OvyxsPm6acvaJ qSFUqOnJcm/9fp/ww3S/Ddv4ftbLSdGstQ0vT7NbbTrfyZUeGO1t03JtWR2wh/1LNt8xuP4VWRce P7FepYtarb6NBBttkkUrt07920dpHHBNt+y3TLdxnaYW+X9227MdSi8bRdDvLye20qy1bTtIN/I2 yFJYZZvMkm8yLzAscbSQ7t32ja7I+6T93va82oWOj6tCgls5bfS7R4Z7u6aRptPiVFkm826bcNzh rRvLkZGZVaTc+3C9S0PLlaXl/X/DhJcy3O65gtr6wuTIrsbw3E32e7khjjjXyY28uWFVkJfy5PLV kZs7t0i7UL341R2SOT7L5iwstzLGqBFjZjNDtVmZmZ1jZZGX/VsygY/eZUUNzY/ZxHb3L3GlwSL9 jSaa4+1W7FliUTTPHG1w3kxszSFmTcy7sSeYz/7LtWmuI7SLTtUNr9jtXhu2Z7iNoZPNVpp28xnZ VkWWNWXdu+bd+83KGsbx97+v6/E1o9JtYYbGOSLzfsWDbSXDNNIjbGj3eY25t+xmXdnc25v73Ovj ik60vSoO2MUthaKKKRQUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFF ABRRRQAUUUUAFFFJQA3uc9K8xHx+8Gt8Tj4J/tD/AImx/d+dgfZvtGf+PfzM/wCs9umfl3bvlrhf 2nP2hrX4f6Td+GdEl87xPe27RySI7L/Z0bL/AKxivzeZhsqP4fvN/Cr/AAlWNSpy/CfT5bkzxlOV Sq+Xt/mfrtR2r5X/AGXv2jb3xWsXhPxGl9fanbov2bU4beS4aWPcq4uNqttZdy/vm+XafmZW5b6o 7VpF80bnhYnD1MLUdOpuOoooqjlCiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKAC iiigAooooAKKKKACiiigAooooAKKKKACiiigBoFVL+zhvkWOeJJkWRJAsihlDI6srdD8ysqsPdau UhoAptZwS3UV2Yo2uI42iSYrllVirMoPodq/98iiwsbfS7OC1tYo7e3gRY4oYl2qiqNqqq9hxV0C jFMnlV7iYz1rMbRbWa6W4ki86ZZ/tEbTM0nlSeX5e6Pcf3fybl+Xb95v7zZ1KTAoCUVLcWj8KWik UN7HivHfG37Lnw88b3t/fTaKularfPvmvtKb7OzSeY0jSNH/AKtpGLNukZSzevyrj2OmNn1qZRjL 4jWnVnRfNTlY8N8H+D7H4Y60lp4tvYdRtrO3t4dE1C6tmjghCh2ZST+7SRfKX5mYttVfm+bbXlPi rx9N/Z01voeiXeq6Vd6r9otryaOOMTrbtJHNNt+zqsy/d3KzfKq/xfdb69uIUvLeSCaOOeGRSrxy LlWU9QR3rl9Q+FegX2n3tnbxXWkrcv5vmaVeS2jwSeW0XmReWy+W21m+ZfvfxZrxMTgJShy0Lf1/ XkbKv1n73zPn/TdLstO8H3mrtH/ZuiXzx6TcrYX8dw8ZHmLJMzMzLJJ8rfLHH8scytG3+srqrjQ9 R8ZapYDxBY3WufYIYZY9NgulVpvOWdWeSSRYWjbdArbV+7t27fmbb19j+z5oOh+EfDOg6Ne6laro CrHZXc0/nSKm2NZflb5VZvLDBlVdknzLt6Hc+H/wzg8IeHrHTb+4h1iWzaR1f7FHBGkjSSMZI4xn y22ybflbbhRtC1FTLfaTvKKt26fd/Xc6alajUpvm76L7/wDgf0jwr43Xlx4M8GW2u3zWGm2Ol6vo 091fBp7xo4Y9QtJGmmWPb5zeYsjMy7d3+9JWd4W1TWfEnj19T8T69puueHtYK65pN5JpkMbXOmLJ F5dvHD80ytumjX5vvLNHuZm3Rr9JeMvhvp/izwrrmjLJNpkmqWk1obu1dllh8xcb1+bqpw34Vwnh H4Iat4WuLCzGt3+paP8AZ42ubjWNXnutQhulWT5o22rHIm5l+WRdp2/d2hVrg/svEcqipefU1jXo Shr8RQ1TxBrxMFnayLNHfPJdzamz7LVzLHtgiWQNug/fAfLH833XEm7cW9R+Hb27eE7d7WGKCFpr g/6PfG+jkYzPuk85vmfc3zc8/NjtUOl/DbQtJtYIreKTzoYpYxN5jKWErrJJ8q4j5ZFbaF2r0VVX itqzlXTbGNWt7iKNZRAsbIHcfN5at+73fK33s9g3zbfm2+5hKden7tbscdapGcFGMdTTmmitxudl jG5QGJ/iY7RU9FLXpnEMHPbFch4isZZIdUS536zBcPHNDp8lsvkxJGY9ylvLYtubLc5b/nmu5c1o L4x0WTxlL4VGoxDxBDYx6m1g2Vk+ytI0ayrn7y742VtuduV3bdy7tWWETSqrxpLB947v4WVlZeP8 /dFR7smTJSt2MOTwho15NdvPodoEvori1vYZLSFlu4pG+bzflYsrAfdz8275l/u4nxM8A6P4qihv 7u/k8Pahpu27g1+BYjJZJHIsjtumRofu7l/eK21Xcr/FXbs1wJLfaEI3fvSzY2jafu/L83zbf7v1 7UWtzFdRl4ZUdFZo8ocjcrFWH4MGFS6cOXlkXGc4vmTMLT2tT4esNTsVHiWPZ9ttZrGVZRM03PmQ NJIVClZG2/vMLG21fl4qaa616PW79IbG1k09LCOW2kllMbPdbpN0bY3fLtEXzbfl3f8ALTovA+Hf D/hbwzDr3izwEuk6fdeJLezsrcPHJDHcTWayQwQLG0iqq+Wvlqkapt2s3zZ+XqB420fVLq6K6hHp 8lmmoW89zNBhrbyWiWSTzmzGqrujba33sqf+WbCsKdVVZcsZdOmxd1KWmpBDq1l44tbzQNFE0OnW 8jWV3cra7bZfKmWOazUMytuaNZFDRqVX7277obI1Tx19n8ZT+Gbbw5qzRWt3HOJtHdVW4ZlWaTf9 3btkmhZvm2t5nzNtZlbV8K6vBc3EOn6Xc3V9faZiO+h1K53taxyMP3EjqzLJMm3Cv+8P7l1aQM5d pdQ0PTNButa8Xrodxea/tby49m+Riq+XGsezdt3Y+9yyrJ821flXOpNzhGVOXqzTmim7bFrw144s PiR4XtNZ8J3/AJttemb7PeXlhOqr5UxjlV428tlYMrLtba3yk87abqWuaJ4N0axfxO9lpcmq6vBa xxtM1x9ovppgsCRsyhnbds2/L+7WP+FY8r0kN2ZlgaOGYxTJ5nmOhTYPlwrK3zK2G/u/wtuxxUeo a1p2mNDHe39rZySrJJGs8yoWVBudlDY4Vfmb0rq5ftc3+RjpfyPNvjl8WvDvwa+GWr6xqjXV/Zw3 iWs1rb5u2aaZhIYJiyyCKJlf5t33Y2VYxuaNT1vi7StevL7QL7w7cadBfWl/H9r/ALRti4n092UX MMbr80bbQsit0aSGNW+ViVyPhr8UJviVeahE/g/xZ4Q+wR20/wDxUljHbrdrNGzBY2WSTcyfLvX5 WjYqrYO5a3ob7WrvVPtls1qmigNbNp17Zyw3RnW42NOs/mMvl+WrMsfk/MdreYqtTvzehttpbX/N f8Oa1xZyXQuopZf9Fmj8tUj3RyK3zbm8xX9Cu3btZdvXn5flXT/i5qP7T+i3vhD4c2/i3w9Z39yL rUPHF88FxBpufLukgj8u4ZZNytHC0CsrRrJ+8X/WV6r4w/aA8GaJ4O8T6xp17LO1nrT+H75rC1Mc 66hGqrKF82Pa8kca7lZsxt5aruqp4f8AhvoHw4+JXxLurLT9S1BvF1na6rqcN9ZXVzaOiyTR3Ecc +2RZG2SbltNu75tq/u2VYcqnNOUYxlp1NIfuKcqk469PkekwEavcGHyxdW1vcR29zY3k0Un2VoS0 kcw2qzGRv9Gk2yMMKY2+VgytFpcxuZrWeGW31S8gsbfZ9uh+zahHDNJ+8kk+QFfMWIN5flx/PAVP /TNb7SyupwLLdW+pXp/e2qzv9mu0hFyklwFkj5aNR9nXy9gDeWqyM3mblivI5xZy2t9qlnPDbSRw QzatpxXdd/6ObeRm3JHI3nEt+7VcsyKu1ozu7jxJSk9X/X6efX5E0NrPpZi08TW+iWdxBJY2VvaT R/6M0e4w/Z42gwzNDuZlbcsfkqqqy7mqePxAt1NHIZpLcJJBKlpbxu9xLBMvlxm4haLzIR5hk9Nv k7mYKJFWjcatYWun3Fzp+p2Uekxpb6i39mm3Vo45JmkmuZJHbyzDIu5mYKGwszKzMV2tksNSul1K yE0kQVJJo7SOedROZGuVCteMrMikeW22FVaEqMFlZQQnmcfdX9f1/SLH9j3UkZS8j8y/ln3Jqdow b7LIbXyzcxxz7lh+beqxp5n39zbvMkrTvNBXVvPS/wBk0fms1q8StDNbq0PlsUkVtyyfPL+8XaQr 7f8AaNh9F0+Qz77K3bzrmO5l3QKfMmj2eXI395l8uPa3VfLX+7WoRU3OqNJdRaKKKk3CiiigAooo oAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKTNGfegDz n4wfB/R/jF4ZfTtRT7PeQ7nstQjXMlvJ3/3lbjcv8X+yyqy/Dfj79nXxr4J8TXOlw6FqOvWqnMGo 6ZZSTRTR/wAO7bu8tv7yt/48u1m/SgcjrxSdff61EqcZbnr4LNMRgVywd4niv7N3wLh+E/heK71C 0jTxZfJ/pswk8zyl3FlhVv4V+7u2/eYfeZVXHtZPWgdfel4xVRjynnV608RUlUqPVi0tFFMxCiii gAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKA CiiigAooooAKKKKACiiigAooooAKSlooASloooAKSlooAKSlooAyYWuv7YnSRCtksMbwsIxkybpB IN27P3RH/Co+b7zbsLBqml319Mv2bVptMg8plYW8EbSMxdCrhpFYDAWRdu3/AJaf7IqnrFzqNuuo yXGn2+q6ELVna3hVmu22o26Py8Ms275cDK/e/irF+D3irxL418KrrPiCzg04zt/o0MMDR+ZGP+Wn zSN8rfw/d+7u+ZWWjSOgvae/Y6OS31DU7yyuftF1pNvHGjvbRtC7zMx+aOXMbbdu1fmjk53N/dVq ms/DelabrGparaaZZ2up6kYvtt9Dbqs915a7Y/NkX5n2r8q7vuiqniqLOmi93NA+myrerNDZG8nC of3qxxhWYvJD5kfyAt+8O3NS298dY0e2ufsl55OoL91Q9vNDC4+V3WTy5I2243Lt3qxx/DU6dTV7 XRoahNLZ2c8sVvJeSRoWW3hZA8jDnau5lXJ/2mArx74K/CPVfBnj/wAc+LpfHeq+I9K8XXj6hFpN xbeTDYNu2qreYzSeYsflw8eXtWHay/LGse/8Wvi/H8M9R8N6dbaTPr+raw11PHpdrJtupLW2tzNc SQKy4mlX92iw7lZvMz91WK9jL4S0q4bQHaxjQaHN9o06OH92tq32eW3wqr8uPLmkXaePm9hWPu1J /wCEtXjD1NHUtQj0uze4kSZ406rBDJM/4KisxryrQ7Xw98SdKvLPS7O6GmazdSalfeZJGs1pLvVV bY275JGhm+Zd3zK68fNt6Pxt8YPDHw1vPJ8S6taaekiRvDGJGmuXLGTczQxoWWMeXxJ93O5fl2jd oeGfF+h+PLbTdW0qT+0bCZZbixuPsUoCtGzQyNvZflb5yqr8rMPMxuXdjKrRdSpGT+H+v+GMp0Ju HNJe6eb/AB5+AutfEDS/DH/CJa2uia7pviOHWpNR1E/aI1ZY/La48lo3WSRFC+XH+7Uf3lrp7Lw6 w8F6Rqeq3WoatqWnolwtuY7iJJLoO5K7Wje58kyNH8snmbVt4G+bazNsRtqOpS3Yu9auNFbUvKgt I4Xh3W91EZPPjt1mtVZ1ZYt3mP5m5dzKsaqGbZmtraZLX+2ZIRe3ExNtG0i5gm+zsrLbSbVbds85 t33trSdF4XohRjTqc8RxqLkUb7FuO1stG81re1WH7RP5kq28GPMlkYAyNtXk/wB5vzrxb41SeD/i TqWq+DLk3B8VafZS38dtDp/2jzY0h2+buW2uOY1upFELLubz/wDVss0bN6fa6Peaxpen3GpPNY6p bxKsd21rbm8ik3ETMD+9jVZVC/Kv3VLfN0252imL4deDTf8AiDX9R1eOO4uJ21G+hl83y7q7aSKN 4VHHlrJHH91dqp92NflEVaMa0PZW+IuNomP8NfE2g6xo/hG3az1xtR+ztBYXXiG3Z9RuBaRiGWa5 ZN3lurTyRt53lt5jONvNeDNZfFPUPG8Ot/DHwx4f8F6H4vumSXUNReO01GFYFQMqDzrq3dZo7X93 LDbyKy5k27f3j/VVx9p1GWWzllvbaK9kmDwyxkMluq+VthmgZfJZmKTKzM0mGcYXH7uhujvIzJNc 3pF2sa3Hl2V7C32aZ5lgWMb/ANzMpdfMkX5lCZZY18vYTw6qcqv8JzxxTpy5lFfP+vn/AFY5W1+K cXgOzs/DHiTXbfWfHsOkSXklvHGYlu5YYxJOiTeWsTSKrxs0aqsnlkSeUqsq1QtfHGvahrGh6/rG gWkfhtri7azvJrjyriC38lmWQWzSfvJGjDNuX5ljjuNq7ZPm7nVrbU2sXn1CCG55jkjswRcRNPJE 0D27H7NvWDLK3nfe+Z922NdrWWguYNQbSdLvTA8UP2mOLy7dreyTy/JhieJdsnlsyvIu3qYZF8xV AUuND34yctuhn9YSd1F3/wA7/wBf8AseILGLxBZ2NwuqfZ9Nt5o7+RojG0c6Rssi7mYHC7lVty9h 715bpXw+0WHxJrnjy/1ue48QQF7yfUY55Z2srX7JKtuLW38xlhjWOeaTy5I5N0kkh2t8jVu6L4cu bPUHvtIudUs7CeW1m/sKHzIYI42u2bzFaaNfL/d75JbdVDc7d23y6vXPhrT9a8R3OoWGq31pqGI0 lt7R5JrN13bo5GUKv3lm3blZQrbmU7lZq5sRD2dWM4Rv/wADt0Nefmh7j0ZsSRi0TW7nTbpLB7F3 LQ2KNdo7GFpj51qq7hI0lw0jLGVkkxF8x3baS68i3mj07SZ7LTvs6ppVlHbX4hMLMqySRrb+W0fm RwIkkasrHG4fu0LM3H+A/GGual42Ph+80+S+slMutW2v2l9JJa+RJuxE7Ku2RmaZWhj+75P8XmW/ zd9Yxk3UVnB5dxDpN2sLONTmkmRPsvBmG0+ZJmRf3cjN8rLLu3bVr0adRVI8yOOdNw91/wBf1+a1 KS+KLaS9jkTU5WtHu4JEdZ7PyHgmh2wsOd/kyTfKv/LRpfu/u6n0O6vJAzxL9pu44bO3ulvb9RNH J96RZo4VaGOVY5VbMf8ArCyj5VVGrS03Qn02dZTqN7dMybZvtEisk0m2NfM27cRtiP7se2PLu23c 2asRaTFF9nG+4zDPJcLuupG+Z924N83zL+8bajfKuF2qNq7b0HGnUvdv+v6/rU1aKKKzOwKKKKAC iiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAgjmWZcjd1K8gr0qeiigAooooAKKKKACiii gAooooAbxxXknxt+P2jfBezjV4f7U1q6O+DTI5fLbZu+aSRtrbF+9t+X5m4/vMvrDHamfQV+VnxB 8aXXxC8aar4ivh5dxfz+YI/lbyo/uxx7lVd21VVd235ttY1J8kT3snwCx1ZqfwxO08Z/tNfEPxpK xfXZdIt/MWRbbRz9lWNlUr/rF/eMvO7azMu7/gNX/hH+054q8BeIxLrOqaj4k0W42pd297ctNIi/ 89IWkb5WX+791s7W/hZfHKK5OeR+gyy/Cyp+zVONj9WfDPijTvF+h2er6XdR3un3cfmRTwtlSOR+ B6gr1U5Fbitu7V+bvwJ+O2pfBvXAjGS+8OXUm69sVbLK3/PaP+7J/wCOsvyt/Cy/oP4Z8Uad4v0O z1jS7qO90+7TzIriFsqRyPwOcqV6qeDXbCfOj82zHLqmAqWfwm7S0UVoeSFFFFABRRRQAUUUUAFF FFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUU UAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABSUtFABVS7kaG1leOOSZ1Ussce3c/+yu7irdF AGP/AMJHpX/CRf2H/adp/bf2X7b/AGd9oT7T9n37PO8vO7y93y7sbd3FO1bVbbSbRprmXykHChVZ 3duu1VX5mb/ZXk1JJptpPqkN89tC99BDJDFctEpkjjkZGkVW+8qs0ce5eh8tf7tcUtr4vm1ewuNe XRINHs9Uu38rTY7y4nuomkVLBioKrGyiRmm3LNHujWRdv3o5uy1y7s5X44/BPSfjHr2jlp2TUtOh kFxb2zwxyPFIsjQ+dI25o4/MhZVZY5D88m1fvMvWaP4ZtPDemQQ+H9Oki0/T0litY4oo47qARyRb rWHzYxujnaFmaSSTLFgwbDK0ertisYre6lNu2iaYW/f6t5kc9kIkmjkn86bcZMrtXc23KtI/mOGU VZbTMXWnmZo7jWVSOU3T2sz26eWdsrRru2wyOs8ir827a3/LRYytacsTlqV61WEaTl7sf6/r9ChZ XH9k2bPBqFlBpFqjo08cUUenWEFvOwaLaJNyyeVmNm3bFa3LbU/1bQahb2+g6Hd2tvaWGhxeRcSz JC0lvbvBFF5MZa6jVfs7bBb/ADYZlWNlXd5e5Z7pZyzsHkTVBbaj9nheO1OpOpmTa1u27y1j4j+V 1Od0HmFWVg0UTeXc2kNv+6nee6kEdj/ochT7dH5r/ZpvlkX5v3k/3vmLR/64VZwy2t/X9f09B8Wn zW+pW13/AGLJdl7q4uZLieC1E6zeYkEU29ZF+VbdpFHytI0SBWYMNskNnuvNSuLaM/atRj+z207S HyLj/R5lZnnuLfcnzRzpNHblU3CRtyhZH8uG8XTVW1tJbCzvrm5k1KM6aullJLy3ZnaaNVkZVVWk EO6aQ+XIxXp50ZFlbv7TpbCWQ65cWJ8lYWTzre5uFuPLhlkljt/lkWSHdJ5a7YWZ2ZcKrUD0/r01 /rX0JZYmfTpDZ2clnBfJOlnZQmW1Wd5o/OMtwyw+Zayb/OG71ky26RlVaWpXVstxeXFnLZyTx3Ml zFcwaFPeiOVbWaFstE3zTK0MittIbbth2hpFZr0jeXdSmwZJdRaOaKwW7t2a6iZrjbcy/vpFaS3V mgbau0bY12swaMCvNbW8kUWnCTUjAbhYLNr7UZbNn/dyQzRRuuJpmWOOaYGTduZldZPlVowUr/1/ wP627iXlnbacl3Z20cFunGnxWdnamzubm3jtWkjtbeYyRruVndlkU7VXevysrOt77CJJBZDT7dDD N9pfT9mLN9935i3HmeT81wvltLtU/LJJ8x+ZJKLpl1q0vFsbf7XHfQfaLmx1qC4ENwkkLRrD+8XE OSi702NtG7dHuk3VYvorLWrK4e9kj1TS2uWtkt7WN5E+YfZ5IplVmEo8xpd25dq/xL+73UGiS1t/ S/r/AIbqZdta6gkjxaddwQ6lDJDPeW9ysEd3fbfNh86eSNWVVmWGNlZY1bbCy/L92Pk/Fmk+Km+C niq3v9W0u88WuskrjSrKRrWST5WW18lpGkbzVVY9rNu/e7V+XatdxfQzrHGmrXVt5a/2f/pF1BH9 ikuBcf8ALGMyeYsrN5e3czBWMO3cyuDkPbajDq2oXUs0wtYreS7kj1CdrMCaOeTyG82AeW0LR7lb dudY47fzFZmrGrTVRHZh6nLJQa/r+vvPLv2drW+sfAdpB4xtNKsb8Wk2n/8ACMGNxOySSLtjbz2V d0m3b5bqzeWbfdJ1Z/f9JM8kMs832hWuNk4tLnys23yKDFlODypY/M3zM2G27QPAtW+Ldrq3ia10 TwxpVpbX1yq2tvqNzZ+WFWQxtazRr8y7VXyWVmX+78q/dr23w7cLFqGrWsCLbQCQ3K2rbEljZ5JV ZvLVRiOR42kWRmZpGkk+7txSjCNOFo/j+P4jnN1KvtJW3e36/idRS0lLVGgUUUUAFFFFABRRRQAU UUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUlACDFJWFeeMtC0jU7fT77WtPtL+4kEUNrPcxxyzMcb VVWbczfMv/fQreHzUD5XHcdRRRQIKKKKACiiigAoopKAI5lzG49q/JbWNLudB1a90y+i8m9sriS3 nj3K3lyK21l3L8v3lr9bPvLg1+f37WvwpuPBPxCufEFraSLoeuSfaPOVTthujuaWNmLN8zHMn8P3 mC/6uuetH3T6vh7ERpV5UpfaPCqKKK4j9FCvsz9hDXvtPhnxPovkbfst7Heedv8Av+dHt27f9nyP /Hv9mvjOvoH9ibxEul/Fi60+a8eCLU9Okiit1LBZpkZZF3L93csazfM3+1/eral8R4edU/a4Gb7H 3tS0lLXeflYUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAU UUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABSU tFAHzr8Zvgr8Q9Y1C81vwZ8QdZWWQmRtFmv2t4x8rfLC0e1V/wCWaqGX+8zSVX+CuofGo+Pp9M8e tJHp/wDZ32mKWazt5LfcLiJdvmW+0eY0fm4Xd8v3irV9HNkjrik5C9cmp5fe5ju+uSdD2M4xfy1O cOhyaTZ3U1qJZbiOOFYTbBGvJoIcMtvJNOzeazN5w3Oy/wCub5lbMlTR6dKs0vkfabWS3uGCSXk0 k0c8cjxzSlV83/ejUt/q9p2r5fyt0NLV3PM9mjnI9NN1Zy2zC4tLGc3cc0Mk0n2pmaQ7ZI51l3Rr t3sqj5lDR7fL8vbWbPe28FxPJeyy2sEiW+o3tvJfeXLpm1WYSTN5+1YSbdY9sfysyybt6tIV7QCk 207kypLocXp+jz29pCy6XJaW0klu728V0Xv5XX7Mqy3E3mLlowjrIu6XzEjX5m/1bac015HcXfzX M72Z+1R2drbLH9ojaNlWEyyfI7eYrN8rR7f3e7C/NJ0X40mfajmEqMY7HL/2XqF1a3Nm19egbILN p7ry1M6qN000Zt2jZJJFdl3ZXa0YZY9o+erBHfLczXlzay2M9w9vHPcW4jncbTDthj2w7nt90lxu eXay7pGXarKydjg+tL+NO4Oiu5yUMaQ3MU95/pc1pOguG/s+dv8ATJI441mttzN5ceyR1bbuVd7b nXbJuQRtb2pk1C31p/Lg3T3Ym3PJ9ll3I3k27ctNln2xR/Oo2Oo+WOtmTTIzqEV4jm2um2rPJFGh a4jVZNkUjFd21WkZ127cN7MysWuj2lrIslvAbbZ5xEMLNHGWlcSSM0a/KzM/zbiN3zN/ebLM/ZP+ v67f1qZss0+nxz3l3cx20sNpbvd6nPlbFljZ2m2QtN+5bbv+ZugaPc0nl7RW1KFLYgNFM6iW5hWw u5/N/tVZI2maKFZJtu7cuF8z7qxSKqrG26nrpJ0eK2uJZ9Gs5kMcP2r7B5X72a4VrkKfM+Xz28va v/PTazeZwtclrXgHVdctksE8R+I9NWG3u1tLeC8kt5ZnVowss14vmAbn3so2/ckULGvlyKzI/wAX 9f1+PmeQfEDwDpum+ModU8C3ehafZeH7i1tJ4W1KNmhuI9zeY0YZm/5Z7WX/AFjNFJ+7b7zfRPgH SLnR/DOloI5LeBo5ria1vJGnufMlk8zLStt+b5n3Ky/eb73y/NFoPw18PaDdSyWvh+wtlhmzZMGa UQrnzMxoy7bf95JJ8sfHCt/sr2nrXPGEIO8ep0RpUoycoD6KKKs3CiiigAooooAKKKKACiiigAoo ooAKKKKACiiigAooooAKKKKACqV812tlcG0ihmuRG3lRzSGNWbB2hmCttHTna30q7SUAfl18Xtc8 U698QNUl8ZCSHXIZPIktWXatsv8ADHGv/PP5ty/e3bt25t25vpr9mX9pz+3vsnhLxfeY1X5Y7DVJ m/4+/wC7DI3/AD0/ut/y0/3vv+k/Hz4B6b8YtFEsZj0/xJaIVs78plGX/njL/ej/AFVvmX+JW+cf gn+ybrfibxNPN4z0+40bRNNuPLkt5PlkvZF/hjZf+Wf96RfvfdVv4l5eWUZe6fbSxOBx2BtV91x/ rQ+8KWkHAApa6j4kKKKKACiiigAooooAbXI/EP4e6R8UPDdzoet25ns5RvSVPklgkGdskbY+Vh/i p3KzCuuo+nFMqMpQlzRPy/8Ai58Jda+EPiZ9M1RDLaSlmstRRdsd1H/7Ky/xL/D/ALSsrNxNfqr4 t8I6N430eTTNc0631OzfOIrlN21irLuVuqttZvmX5hmvkj4mfsS6tpBa78G339sW3/QPvmWO5HCr 8snyxyfxN83l7VX+KuGpRlH4D9By7PKVSPs8TpLufMNehfs9a/8A8I38avCF4YDcB75bPaJNu3z1 aHd/wHzN3/Aa7Xwr+xr8QdavAmqQ2fh63jkj8yS5uVmZlb7zRrDu3Mv91mX7y/N/d+pPhD+zt4X+ EcKzwwHVdaYqTql7GpkjbZtYRf8APNW3P/tHdhmbatFKnLmuzXMs2wiozpQfNzdj1wdBS0lLXafm 4UUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFAB RRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAlFLRQAU UUUAFFFFABRRRQAUUUUAJS0UUAJRS0UAJS0UUAFFFFABRRRQAUUUUAFFFFABRRRQAUVhXPizSrTx JaeH5brZrFzE00Nv5bfMvzfNu27f4WooA3aKKKACiiigAooooAKKKKACiiigBKKWigAooooAKKKK ACiiigAooooAKKKKAEopaKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiig AooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKAC iiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKK KKAGb6dXLX3go3njix8Sf27rUH2OAwf2TDebdPm/1nzyQ7fmb9597d/Av92upoG7dBaKKKBBRRRQ BWNtG1yk5jUzorIsm3lVYruGffav/fNFWaKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAoo ooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiii gAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKA CiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAK KKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAoo ooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiii gAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKA CiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAK KKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAoo ooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiii gAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKA CiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAK KKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAoo ooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiii gAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKA CiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAK KKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAoo ooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiii gAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKA CiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooA//9k=