20000920 15021200 FALSE 20241211 15001900 20241211 15001900 {5C3718F8-0BFC-4F0D-A65E-0CA6980C657B} MT_boundary -178.217598 -66.969271 18.921786 71.406235 1 002 Geographic GCS_WGS_1984 Angular Unit: Degree (0.017453) <GeographicCoordinateSystem xsi:type='typens:GeographicCoordinateSystem' 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/3.3.0'><WKT>GEOGCS[&quot;GCS_WGS_1984&quot;,DATUM[&quot;D_WGS_1984&quot;,SPHEROID[&quot;WGS_1984&quot;,6378137.0,298.257223563]],PRIMEM[&quot;Greenwich&quot;,0.0],UNIT[&quot;Degree&quot;,0.0174532925199433],AUTHORITY[&quot;EPSG&quot;,4326]]</WKT><XOrigin>-400</XOrigin><YOrigin>-400</YOrigin><XYScale>11258999068426.238</XYScale><ZOrigin>-100000</ZOrigin><ZScale>10000</ZScale><MOrigin>-100000</MOrigin><MScale>10000</MScale><XYTolerance>8.983152841195215e-09</XYTolerance><ZTolerance>0.001</ZTolerance><MTolerance>0.001</MTolerance><HighPrecision>true</HighPrecision><LeftLongitude>-180</LeftLongitude><WKID>4326</WKID><LatestWKID>4326</LatestWKID></GeographicCoordinateSystem> 1.0 50000000 625000 NAP Simple FALSE 0 TRUE FALSE MT_boundary Feature Class 0 The polygons represent the states within the United States. States and Equivalent Entities are the primary governmental divisions of the United States. In addition to the 50 states, the Census Bureau treats the District of Columbia as the statistical equivalent of a state for the purpose of data presentation. Department of Commerce, Census Bureau ObjectID OBJECTID OID 4 0 0 Internal feature number. Esri Sequential unique whole numbers that are automatically generated. Shape Shape Geometry 0 0 0 Feature geometry. Esri Coordinates defining the features. STATE_NAME STATE_NAME String 25 The state name. Department of Commerce, Census Bureau Federal Information Processing Standards National Institute of Standards and Technology 0 0 STATE_FIPS STATE_FIPS String 2 Department of Commerce, National Institute of Standards and Technology The FIPS code (two-digit number) for the state. Federal Information Processing Standards National Institute of Standards and Technology 0 0 SUB_REGION SUB_REGION String 20 The subregion of the United States in which a state is located. The U.S. subregions are as defined by the U.S. Census Bureau, except in this data set New England is classified as a subregion instead of a region. Department of Commerce, Census Bureau East North Central East, North Central area of the United States. Department of Commerce, Census Bureau East South Central East, South Central area of the United States. Department of Commerce, Census Bureau Department of Commerce, Census Bureau Middle Atlantic Middle Atlantic area of the United States. Department of Commerce, Census Bureau Mountain Rocky Mountains area of the United States. Department of Commerce, Census Bureau New England New England area of the United States. Department of Commerce, Census Bureau Pacific Pacific area of the United States. Department of Commerce, Census Bureau South Atlantic South Atlantic area of the United States. Department of Commerce, Census Bureau West North Central West, North Central area of the United States. Department of Commerce, Census Bureau West South Central West, South Central area of the United States. 0 0 STATE_ABBR STATE_ABBR String 2 The two-letter abbreviation for the state. Department of Commerce, National Institute of Standards and Technology Federal Information Processing Standards 5–2 National Institute of Standards and Technology 0 0 POPULATION POP2015 Integer 4 The 2015 population of the state. Esri Populations for the features. A -99 value means no data. 0 0 POP_SQMI POP15_SQMI Double 8 The 2015 population of the state per square mile. Esri Calculated populations per square mile for the features. A -99 value means no data. 0 0 POP2010 POP2010 Integer 4 The 2010 population of the state. Department of Commerce, Census Bureau Populations for the features. A -99 value means no data. 0 0 POP10_SQMI POP10_SQMI Double 8 The 2010 population of the state per square mile. Department of Commerce, Census Bureau; Esri Calculated populations per square mile for the features. A -99 value means no data. 0 0 WHITE WHITE Integer 4 Department of Commerce, Census Bureau The number of people identified as White alone in 2010. Numbers for the features. A -99 value means no data. 0 0 BLACK BLACK Integer 4 Department of Commerce, Census Bureau The number of people identified as Black or African American alone in 2010. Numbers for the features. A -99 value means no data. 0 0 AMERI_ES AMERI_ES Integer 4 Department of Commerce, Census Bureau The number of people identified as American Indian or Alaska Native alone in 2010. Numbers for the features. A -99 value means no data. 0 0 ASIAN ASIAN Integer 4 Department of Commerce, Census Bureau The number of people identified as Asian alone in 2010. Numbers for the features. A -99 value means no data. 0 0 HAWN_PI HAWN_PI Integer 4 The number of people identified as Native Hawaiian and other Pacific Islander alone in 2010. Department of Commerce, Census Bureau Numbers for the features. A -99 value means no data. 0 0 HISPANIC HISPANIC Integer 4 Department of Commerce, Census Bureau The number of people identified as Hispanic or Latino in 2010. Numbers for the features. A -99 value means no data. 0 0 OTHER OTHER Integer 4 Department of Commerce, Census Bureau The number of people identified as some other race alone in 2010. Numbers for the features. A -99 value means no data. 0 0 MULT_RACE MULT_RACE Integer 4 Department of Commerce, Census Bureau The number of people identified as two or more races in 2010. Numbers for the features. A -99 value means no data. 0 0 MALES MALES Integer 4 Department of Commerce, Census Bureau The number of males in 2010. Numbers for the features. A -99 value means no data. 0 0 FEMALES FEMALES Integer 4 Department of Commerce, Census Bureau The number of females in 2010. Numbers for the features. A -99 value means no data. 0 0 AGE_UNDER5 AGE_UNDER5 Integer 4 Department of Commerce, Census Bureau The number of people 0 to 4 years of age in 2010. Numbers for the features. A -99 value means no data. 0 0 AGE_5_9 AGE_5_9 Integer 4 Department of Commerce, Census Bureau The number of people 5 to 9 years of age in 2010. Numbers for the features. A -99 value means no data. 0 0 AGE_10_14 AGE_10_14 Integer 4 Department of Commerce, Census Bureau The number of people 10 to 14 years of age in 2010. Numbers for the features. A -99 value means no data. 0 0 AGE_15_19 AGE_15_19 Integer 4 Department of Commerce, Census Bureau The number of people 15 to 19 years of age in 2010. Numbers for the features. A -99 value means no data. 0 0 AGE_20_24 AGE_20_24 Integer 4 Department of Commerce, Census Bureau The number of people 20 to 24 years of age in 2010. Numbers for the features. A -99 value means no data. 0 0 AGE_25_34 AGE_25_34 Integer 4 Department of Commerce, Census Bureau The number of people 25 to 34 years of age in 2010. Numbers for the features. A -99 value means no data. 0 0 AGE_35_44 AGE_35_44 Integer 4 Department of Commerce, Census Bureau The number of people 35 to 44 years of age in 2010. Numbers for the features. A -99 value means no data. 0 0 AGE_45_54 AGE_45_54 Integer 4 Department of Commerce, Census Bureau The number of people 45 to 54 years of age in 2010. Numbers for the features. A -99 value means no data. 0 0 AGE_55_64 AGE_55_64 Integer 4 Department of Commerce, Census Bureau The number of people 55 to 64 years of age in 2010. Numbers for the features. A -99 value means no data. 0 0 AGE_65_74 AGE_65_74 Integer 4 Department of Commerce, Census Bureau The number of people 65 to 74 years of age in 2010. Numbers for the features. A -99 value means no data. 0 0 AGE_75_84 AGE_75_84 Integer 4 Department of Commerce, Census Bureau The number of people 75 to 84 years of age in 2010. Numbers for the features. A -99 value means no data. 0 0 AGE_85_UP AGE_85_UP Integer 4 Department of Commerce, Census Bureau The number of people 85 years of age and over in 2010. Numbers for the features. A -99 value means no data. 0 0 MED_AGE MED_AGE Double 8 Department of Commerce, Census Bureau The median age for both sexes in 2010. Numbers for the features. A -99 value means no data. 0 0 MED_AGE_M MED_AGE_M Double 8 Department of Commerce, Census Bureau The median age for males in 2010. Numbers for the features. A -99 value means no data. 0 0 MED_AGE_F MED_AGE_F Double 8 Department of Commerce, Census Bureau The median age for females in 2010. Numbers for the features. A -99 value means no data. 0 0 HOUSEHOLDS HOUSEHOLDS Integer 4 Department of Commerce, Census Bureau The total number of households in 2010. Numbers for the features. A -99 value means no data. 0 0 AVE_HH_SZ AVE_HH_SZ Double 8 Department of Commerce, Census Bureau The average household size in 2010. Numbers for the features. A -99 value means no data. 0 0 HSEHLD_1_M HSEHLD_1_M Integer 4 Department of Commerce, Census Bureau The number of nonfamily households with a male householder living alone in 2010. Numbers for the features. A -99 value means no data. 0 0 HSEHLD_1_F HSEHLD_1_F Integer 4 Department of Commerce, Census Bureau The number of nonfamily households with a female householder living alone in 2010. Numbers for the features. A -99 value means no data. 0 0 MARHH_CHD MARHH_CHD Integer 4 Department of Commerce, Census Bureau The number of family households with a married couple and related children under 18 years in 2010. Numbers for the features. A -99 value means no data. 0 0 MARHH_NO_C MARHH_NO_C Integer 4 Department of Commerce, Census Bureau The number of family households with a married couple and no related children under 18 years in 2010. Numbers for the features. A -99 value means no data. 0 0 MHH_CHILD MHH_CHILD Integer 4 Department of Commerce, Census Bureau The number of other family households with a male householder and related children under 18 years in 2010. Numbers for the features. A -99 value means no data. 0 0 FHH_CHILD FHH_CHILD Integer 4 Department of Commerce, Census Bureau The number of other family households with a female householder and related children under 18 years in 2010. Numbers for the features. A -99 value means no data. 0 0 FAMILIES FAMILIES Integer 4 Department of Commerce, Census Bureau The number of family households in 2010. Numbers for the features. A -99 value means no data. 0 0 AVE_FAM_SZ AVE_FAM_SZ Double 8 Department of Commerce, Census Bureau The average family size in 2010. Numbers for the features. A -99 value means no data. 0 0 HSE_UNITS HSE_UNITS Integer 4 Department of Commerce, Census Bureau The total number of housing units in 2010. Numbers for the features. A -99 value means no data. 0 0 VACANT VACANT Integer 4 Department of Commerce, Census Bureau The number of housing units that are vacant in 2010. Numbers for the features. A -99 value means no data. 0 0 OWNER_OCC OWNER_OCC Integer 4 Department of Commerce, Census Bureau The number of housing units that are occupied by the owner in 2010. Numbers for the features. A -99 value means no data. 0 0 RENTER_OCC RENTER_OCC Integer 4 Department of Commerce, Census Bureau The number of housing units that are occupied by renters in 2010. Numbers for the features. A -99 value means no data. 0 0 NO_FARMS12 NO_FARMS12 Double 8 U.S. Department of Agriculture (USDA), National Agricultural Statistics Service (NASS) The total number of farms in 2012. 0 0 Numbers for the features. A -99 value means no data. AVE_SIZE12 AVE_SIZE12 Double 8 U.S. Department of Agriculture (USDA), National Agricultural Statistics Service (NASS) The average farm size in acres in 2012. 0 0 Numbers for the features. A -99 value means no data. CROP_ACR12 CROP_ACR12 Double 8 U.S. Department of Agriculture (USDA), National Agricultural Statistics Service (NASS) The total area of cropland in acres in 2012. 0 0 Numbers for the features. A -99 value means no data. AVE_SALE12 AVE_SALE12 Double 8 U.S. Department of Agriculture (USDA), National Agricultural Statistics Service (NASS) The average sales (dollars) of agricultural products per farm in 2012. 0 0 Numbers for the features. A -99 value means no data. SQMI SQMI Double 8 The area of the state in square miles. Esri Calculated areas for the features. 0 0 Shape_Length Shape_Length Double 8 0 0 Length of feature in internal units. Esri Positive real numbers that are automatically generated. Shape_Area Shape_Area Double 8 0 0 Area of feature in internal units squared. Esri Positive real numbers that are automatically generated. iVBORw0KGgoAAAANSUhEUgAAASwAAADICAYAAABS39xVAAAAAXNSR0IB2cksfwAAAAlwSFlzAAAO xAAADsQBlSsOGwAAIABJREFUeJysvVuwLUtWHTbrvV77cc4999W3+/btBjUINQIaoxYEIIMCMAZC somwrC/7z+EPR9j+Ulg/tj5thz9sR9jh0JfDX7KNFLaEJIckjAWSGmiBWjwChHh0337c5zn77L0e 9XaMMTOrsqqyaq1zobrP3XuvVZWVlZU5c84xx5wz/toffrU9nu4lDFtppZGyLqWuKpFGJMlSaYJW 9g/38q9//3flw2fPJE1TwZn4fxhFIi3+anlN27YSx4mIBBJFkRRlLnEYSxwl0tS1FEWBr0SCVqI4 kjTeSBRGIgE+FGlxTnni70EYSFmVUlWlhGEoURxL0zSSRKm0TSN1W+MKCaJYwiiRKIwlbBuejz5V RcV2wyhgX3k0sUSpSFNXkue5RFEsaZZJ01ZSN5XUbSlJupIwCCWQUEKJJArRdsLfwxD/QvYD/wI8 jOk7+4xfOTQ6Pu53/WG+6y7S/4xPxVjiX3cK72Ueo2mlbTDWGDt772Dwu/ZN2xn0r+9F1w9ea+7Z 3ZD954ddD9x+4R/GqTvXPcbjMHp8fH86YvxDieO4G4Pzh7bnPuvwFna8zHvh3Bx+N71Pe9Fth5e5 fzj37P6a3qt7RKe/bYs5xMnufU53XMa3b817Gcwb03D/1MNr24U5OOz/9Em7z7s5Yq9wbo/v7CJw x6Rt+c7wvLosKAQWn3c8Hrat+Nl7d1JVhaRJLHVTS14UXJSrbCXPH/YUKO+9cyd/52/+I/md3/sd efnll0wnGgmwgINAmrYZTPAACx4vwS44drblIseix+chBEyI84J+gFu0VbNzECBoV1+IdhfX6GLB g0NoQGgFbIcvnYKmkbappa5rHUCOIRZGIm3dmPMjqWsINKHgxH0gANA/PC+EpZ3zfA4zpoFEAyFl J4s+n32tw1dsptVgAuipbLB/8d1kc//QCeBeb7/no1Fo2E4489AKmUA/cAXRZJpxYfetT9Zmf2En 5SbLYdKkCgvv4ZmP06k/HQt3QV0i2gZCE2PorNELRePk3v5zRm0OhNLM9eacRsymNzoDV6Hf02/M 4dsknENViP79DPqmJ5wR0/1I+cX7eFb37bsb5LizuMKdPeNn1jOH34/fWfxN3/6m5MVR7vfvS17m ktatVHUuTXiS22wlcZLIl++fySufvJXv/sG/KD/yE3+OGk5T1ZKuVpJmKynyUydFIQiSJJUsWktd VtRi0AbOwb8sW0tTBLLb3kqaZhInmTRSSSO1hG0sp+JewiCW+/0HktdHanHUsCSRzeqaWldRPUgt lZxOez5RutpInG6kDVeSNCc55Xs57vdSFoU0dSNJvJLb65ekOJUSVpGsN1u5f34nYSKyfbSVsiqk OBW8Znt9I8k6EQkaahBpnPG50E4WX0vYpNQeIdSswOX3TdONgdVYIFApVMLQyJ7+O74k85393f2p QqnphL9t256Df3leSJalg9fP76CBGeECzde+HwhtaDQB+jOaNrzOTqxOIDtTvuu3sxisABxt/6p4 YXKOhbp9Bu9SHx1+0eSOw9wxHmN7705jNV/bd9Lf75I+uX0Z3nN8X72fbtLjc/Ed1orOIX2/bt91 c+/nhtt2YK73PbP9HHOv79PwfbpjMXw2/3Pbdqyy0AmskWZo18G4Xe1/v/n3G/zw/fje63hc4qI+ SZKs5Hr3RI7VvRyLB5HySJPr6bP35PbxEy5OTHIMfABzq6ooqKqipECCNoOO4Xf8w1G1pYSxLuiq riRKYtmm11z4ML2aqpE2xs4XShyueD12HGhR94cPpG4rydI1hxCLrgkrKZsjhdgpP5iB04VETauF cKgF+lmSZZJFGykfKin2OQXn/dM7CTKRsI3k9PTIRb1KUymKk5xOBzUl40biNczPSMpjKXVTSrSO KDRV22slTqFl6cDTLDS7dwPhE/UvkFpg9zL8E3o8eYaLx9FUPYd7vRWcOGDItlH/8oNIZH+A+RVJ nK0kSRJqxuybI2y0HzU3I+1rNNGeJqaj+7nVZtxJPjp3TtD4FtIZmTR7jO9xTri59/OaWRfeqzOT jZDpP+/bnfSHcwTvbjgGroCYW8SBI7TG57ibZGeled6b+dR5nu63wfnD+8wLS/u7HYvpuxhuzu75 c8f4+/gPvvyb8sorn5Dt+kaSYCVFc6Km05SNnE5HdhC4FfAGTGZoHQlwrKaWssolqlQDgmnCZYZz EsW5sHgqo3FhZ1fNDAKrkOf3H8rjJJWi2bMjUZBSs0oiaF1pp86WZU5TFYIwr078Gw8QJYliVcC5 ylLiWLGuUhJJgkYiYGlJJGVUSX0EdtYS/woigG86k9pAr4d2tdvcygnCumqkLE/EuShsq0LiIOXv ZYt71xJJKqEkiuHgwPN3CixellHmrRAJIVSnk8v3ovqJOxRw9vxul2tFEpjxte7Eg0kzwA5CWa03 fD8YQ2w87CMEEzRFOyHw/8bd2WHy4+e0v+5imuBe3cRXLW8s5OxCMi12O3D//HaRf3Sh5fZ3fkFM BVN/77kFeV742U2sv1bH0Cs4A8VDMT9cLWty2oxAWDp6qGmqbbqfO5DURJC4Y9d/ZzWr6dx0f9o5 0Lc9JzCXN5lxu/GHd9+QzeZKkjiRIA74E+YZBrIosEAVRwo6rCiQptLFDMFSlqVkq7VEYUhNC7s3 tS5oRcCTWgWo7SQkNoXFENXShKV+XtVSBcDOYg4DtAAsMKjM0ICg7a3SLTUpmJfQdgDi9zuTrpYA +FcQSxtAiMYSbkSSqpCqUYD3eNrL7mYr6SqVMocGCFA9kjRspK1b9g2aF21xaHY1wHgVfniGOAF2 ps4JqlWDiWjV5X4h9NqRfjY2GecP8zxGxe6vMeYeJjmEDRA7jGeDc4cmo/vyswwaLJwk0H5h3lZS Frmk2VoCoxUCOyzLgs9MbSzWd2AxxPHkdE09917jSTnWAobfm2canTP3HO49fGN4ycTv7zvopXPN 8By9bih8l45+bIYL3nd0QLS5h+/55rQoHHPt921Mvloca1fD9N3X99mwX/Y5XDNUN3D8dPvmmxdz Voh7XoyJer9/KuvtWlbxhmaf7sSBxGZRWJkAs0cvDnXCr9ac4GwMHrkwkjhM+C+IepMA94Amg7+x APH7erWSJqiomeD7ui5VC4ozNT1j9RLyjmwooPZ1KvfaVtDvSlYNp1CJamklpfbUBKUEq0aSMKYW 1pQA2vWadJURQwslFslimoWrbEdND15DwT88UxxRYKJtoEUwB2mqDcD13ia3AnRu4Kc7lv/wL0zH hDNCSzUWTPrAOxnwj46OwMVOagpi14Sz7wWbAkxi9fCdU3PmcCbrsJhfsFOhZE3n6c58ybFkIi3d 139q/257wbwsPNy2huM/PGcsOKGlW7zxnIA7h2cNTUl7hp1v8+3010/hB9/mcPnGa7FUtu7tu+9+ S0e8Xm/kcHouRflYVus1BzCChhKEst7szKIwpgPoBNBsgFFVpaTtSmkMBHrhYYtJP8C5+J3YTmC8 eehsG0gNYdNEBMKBZxGkC4WYFcw9aF8QeBScYUjaQdWUEgaRpNGGVAkIL1IqjOmkGlcD4oGQaREo 5gREK0wCAudyamUT7SQ/5uoUWMfULiB44jSRrFkrmN4EUkHTkFbiLOJ31psTtiHbBWRNL47Rsvqj 31mWXvzYtHqhw2xiEDckX4ShVFUNq3S+LTO5VEnTfkBrVIFve947EUBD6Sb+rNCa38XPPf+4naXD J7Qu0XTO9eWjX+PX8HS8eOaCRubThnTD+aPYv8EZM3HucX0ajK+NMa522THVtmxbLzJvxkcMcw4e M+BE2peAAisOU2IfdofGwFIIgA4AYDtR75SC7vB26Hlc0G0IdUxqUAUqw1mKYOLVkp9yWSU7CqUW eFFb0MxD+2gHHss2FcngoctW9AYGVShJmBI7ul4/IVAPc5JamTGTYM5AqAkFJ/ApaIoZTVQcSZRQ WH3w9F2J01hB9hMcBQmHdbu7kv3+XloILHC4YjOZSJOAfYiVExKIp7AibmeA6cHLMbsKXsrIy+N7 4UsTxX35nVfFCsuFhT4GPgcYDDakOJZohO9gA4AHF88LM1kfwfBmRu26/V3a8f0L1G/uXaJZuNef O3duJ79swc0vfJ/m2JtX9jzXzJm/S9eOc87lGFU7uveSNsv/OtdaT97QLFxqZ37D6e9h5cfoSq/T yf1u3Aff0WFYMPMIqBtsJjT4T5Zk1JAswAZMCgLH4lG7qyvzGQij0HDUMwiuEoTYqYLnDfhKZUxB 9S6CDpFsEmpUIbyENYysmBpdERzZFj1dXJQhBU4c4owVNbRVdk0tbV89pZmHviiZ05BO4b4PIgmi NX8aiFnqtiGoHm9CkaSVsihFylAkVa8lzE1IJih80BpJW6hVYFV5JXl1lIxmbCNRUEscgCCbGHNM +0ABhwbMQocm6HtRc9jMzKvq+Gadh4aEWPXGzl07xgaGvxvCp3MuJyr/sgD+1NybX0RTfGjJmvTj Li7YPtZe+uuWFs5YoC6Nu9vu8mExGPNuzSPO36vHa/Q7t//a3lBQ9BQU99mXTNx2QXj3fZnH+sbv 1g/GT+fo7AgNAHkLkUyFkc8MH2+uvsP9PIYZBE+Ty6uwQHkarmST7iRL1HxDo9id89OJgDy5WGkm UZpJnp9oShGIbwopqly9iNRwAilK9eZBmCVAw2uRVbqROiwlL/dStpUkcSqn8siHzssj8Sw8dVEc pWoq2WTXEsDhlwaEmOI0o/CCVme9kMfTg2Tw5GURJI9EMOjqSqq6kKurW9lsatIxmsRQIepQoiaW JgFrPuJzSgPzF06FtcQSy9PDexJkoVRtYd51K1VYSCypRIFqhxZ7sSRakk89L8X9ezxZxi+J+J9h tZNaYjx9/Ut3zTL/buXDwmYXA6WGnXj687zJ5mJ54+edPo/vsM/gCqalMTm329vvx8+oeN957cVt x/0dVsRlUs4Koh6AH7Xcf2YEmuXcjcH6uc3jkmNeAEw9kr4xm5ujqqH1nmlXILl4nH7m68/YMzyF Sua4XTH+WK1WNJmIjRjWN3CM3e0tAXE1CXUxQxPC+Yf9g1xf3yqDnCAwFlbdeZlgLUUCIdISQ9pl aymOhdw/eyrhTUgzELSJMFX+D0zSOIh5f+BUaDNuQdaEJyuWIi+kDHKSEk/FwRDj1CQNjDmrWkIg eXGSNLiXtt1KFcHEbUiDSINMwjiWQo4UiCBUHos9cau0yRkqhHEIs1U3UAhLgiC+eeUxn4nCo9sZ axFqWqpB0jSGtmK0rT+Owz6TO2HPYUHnFrR7TM6lzLImZ/8MS+bsuL0xGfZcX3xtj3f98UL6ozzj PLbkLij9e7DZOOEo8+/AXYhWaxoY1tP+NZdoydNr58bAr1UP+zk35r5n64WmfSaL0/k90/q3vY/v /U5NZvxUb7f93ETBjGCNGBoSNBNiNZ1bXin0mHj743OBkhQnSqDURhDSAhwINAblkkADANButQwl W4JMqfF8IKiCSR9HGQUazM4I1IZazTqSTsNEsnDNABiA3vh/GCayWa8liQs5VndybHLJi4MIdjty m/SBwPfqSY+IOyxFqoMEkkkbJrKKWlnFOwnbhKB/nqvWVtY5Tb402ZJOcTocpMmVT4OZBG/l6hGE pmo6uiPCWIVjwtAEKDB7Ps0YM/HtROdMwcFE44R3J/10x/VNjHMC4xxWMdw5fcJqXmMafdL18Zz2 5NvZffcea6zD55WPcIy9bdP+4VCaCX67RCj3mpbrBRy+W13dBEC6TW76DictB35BMXfe9Jjia2qS D5nntu/uOWP81DcGc+/Mp/nq3zpWKrTUtHRN5A7DolcQZoaxBmxsIL12VSH56cAQGHCUIGgoqI5l p2IDx0KjcazkStIfwHynt8ngLIFIUZ0UB8rApwIhq5YkzaSqAlIQIBAgBqBR1VJIAtwqSslMZ2ej lsA7WO4YMJqXMQKfVYsLSZ/oFy6OplYTLkg0PAh+Qzxj0R6lCWuaiXjGKE2kDWtOGLj7KZAikQqB 4HUpcZ0I4rYTySjgJAMTwuAEIMOSf+YKq0vNqPGEmV9wY0zIZ3bNtb28c17Wt0vP8ZmgS3iW75qx oPRtAEsmpu9YPnd5AboLd+wZ9msP481lsWeje/VYV7+Q/dphu+D4+GhHr+EM25p3kIy1rOn7cfGt sbNiiOsNN6vxnDECi1wQ40kjOA1PXXmSstL4M3Ch4Lkj3wrBzlFPW4AWRbwLbnUucgWhcS6wrP6B NdQDgrENatkf72SdXYkIGO0h22oBaoHhEIEdD+Y7vHDw1QuFRIm4wgRCLNFwHfK/DNAdgAmv2p9q zso7h+YD1npdB7KO12reBpFUUkgT1ORYZeu1pNFK0nhFHA4tMEuFAHNT0wj4WNwmZMTXYaXeNLDs 64IxjhRwFwqri6aNNW89c901DawmcOm6vdREe5F+9n0a3sPexy8ofBriOYzLPd9O8CmQ/UfTss7d ly1PvpvXNqf9mt7DnjLFfIbvy897GgutF9mw5o9e43H72Ztv1kHjf48+R4qLaw3PG2J9w0gI+33/ F/UEDb1BJoSGZlJRHmky9Ttf32uG5mQaEGxd+/QWQtMiGUio/TBtS613Iqcr3cpKtmSu35+eSkSz rZEkAwbWUINTJr1ROcF0p4cRFAVN/QIBgnPgocvaDU0lDQFCjgZ9WAhf9U6qkwAaEED7/amRKAok TVadNgmvHzXDOpKkyeRw2JvUMhrZCC9mGq8poKQOpSgfJNtkkoTwWIYG34Npq7SPuUW4hM9cMnmG wsuPTfhwC58aPp4wcwJm3NYYQxprUPrdtPfTHbp/Lvs8c0Dv8pgNBdOLaFu+4xLTfPzMw377nmte i1Wsz76jwR0nG9acIHqxfp8fn+E7t++1d8h1soBfqnd8eR73m8ocXmbvOydUe21T/45hTm13Nww0 7qgNIFQyjk61GC5q4ErkYLX0DPa5jlpiP8CQ4I1DD8FxAhwGIahYUCBJmEmyXtHMuy+eyj6/k+vk CbUjZGvAT5qGzDsFYRiQJiGgSoB1HycMrcG5m821rJIt7wctCtpSURUmR1VDzyHxL4aYxBRmp7yQ EG1t7WRRU5hOg0akzHMSSeuqlsY4AyB00UZR5FIh80QC5CqVoAmpaSoWF52dNHP2/CWHNQvmtJil 6z6KJuXDhy4XBnMLw6/99NrR5WD6sjajP/tzLjNvx/f1LaapOT3E9lwTaM58n/SYH/Wm4PS7uaP9 CJr8WBsfj6P7t0uCnW5cS5bE1Jw8H0zuei1dIa0/e4sDRwzhAM8Y4wcNoYzxgGCwB4EUTHQXEdvB 70jZgr/h4Vtt1tohaBgQHjANSTUXaYqaLHEQUJsSNIVcTsCOpJRsnUl5PEkb11IAHA81r5PlG0FQ ZhAkaKdRbElBfWhzCB/RgGp49fA9gqIj5GkAsbMsydDXMBNwxNBmJALmfV3J8fDAJH0wWRmwbQQC AroP5VMC6cf9vcRNKBukrGGerJoewnV6JfkePsa9SIiQnxUMwo4oOKeOj7WVy3YWFarq0R3yuV5E c/PjYfNCYQkXeRHTwt+XMT9nev6luNp4YvfnDs4at+Tt51x/x/1e6psrrGz/XBrF3Pj1Jn4wFCzG le+bF21HgRg+g69f0+d3hfNQY+0xM/d8f7tjaoRPM5/XTqeCPpgkXOw3BfeI4exA6EldQMsBidQk qWM2gIwnleUz4jsIdKb2JK2s1lsDroO3pKRQsM1B7oRGto1vaV6C9K7t1czSEMQtQ3pee+VjcqoP cijuaX5C20GYUFBakqQZROt1JJaUkv5QMzWNeSLm7TOZCOpGYpqY+hzQwLjwIXCR+TSI5XDcE4Av C50QAP4xWMi/FSBGuGikiSo5QUvLWw1PisEdC2nqQrjWTSGnEiK+5DNl0ZYxiEuTZixgfGaWe677 IucEFA7ytEa4xwDwvMwamPT7Uq3qxbCnsdk3NhF9GIf3rt1DTRfKi+NX4/c0/v1cXqqxIJ7rv4vb 9L/7X5AmwBxmfrCHfbdWII6POajADaQfb6T2H7lmnvc6p326v7s5vNx2fdfPvt8ZM9NeF2PFs2Ej YRkYWxsyZpjQ/KMJSAC+ICcJEh4hPQjB0Z2glaDJKbugVeGGRaQ4GIiVuBZANzyPUgayzW7Jaq+D nMKDqYfB2goTehOp2dXgYjXEiRiQC3g7WknVVpIi5IZCUCc5cLRY3y+FF9pABggF9GEaaiB3VaWS Zpp9gfGCSAWNQUgSWK1SNScpamSEgHdyI3Jq5NQcJUljCZKUaZXxvADpV+Fakmjdx+MtTCyLBfg0 sXO7tp2Uc4IB70snyRjfMQzthV3S7eclWtNcH4YLcaj9XCK09LPwrInmW6BL2tdcHy853/e858z7 oVk4xyPjfxefgedb09KjaQQcq3lhYu83TXXjN+/GWpBPK5oM2EhYu+24zzrot8k4OsW+nL7yX38b t784YqQeQTydMKe58qKgLQGXwoVY1ACrEb5jFEoKLPCVdtsbstnBHA9a5SU1ZS3JGgRQmIc6sMCd oJnwpmC4JxspmgMFGLUjXEsdSs2+SpRSASKqDgS6iuyfa4lXKymLEzU3hMngewgQm0Uzr/eGtqS4 l80yEQKbS1aSQfhAOJWlaoxlxcypGB2E7yRZLCm4YDWwrVqqptBEhYwr1CwPuB6hPUmIAGkoqX1e evclWGHV72zTyTWnnbgLd05IuBO0b9u/g421tHNC89JjKJD0/nMa47nDd934XnOm4yUa4XDRD745 e63bR1+bY3xo/nn98MDSvcaPFizkl1oao6Vn8WlQ/mvMOWaTnmJb06Nrk+fZLLpT4eb+nPbTCKxV tmWhCOUB6OgkCaL5NX862OCabVPpDzC9uNMZbAnXHitN+WItUKbiZW4rePpg4gFCMpkQeJ7RnFrE 5RmQ3Xj50D5MS4YCIXMDAqNtejzjmUCbxJVqZcQiDhCgPuUG/rEdLXgBw414FhwCMRIJQrvK2ScK R9A2jgfZbK+UplG3kkEA1pEUJzDqQdGA8wAphmOayUhuKBVUOqPBhCb7HYOh3ZfuBn66pMCxNsTX MtI8xgvXBd+nfJb5Y3je2Ovim1g+7can2vu0oXkweB4onl9cY6HnRg/4n2FOC3J/jtt27+FcNWjv nJls35FdXEv9GN9vrP3Zd7T0XoMLsb5eEJzfROaEj/7dtTiZcPb7fq732LDeu9c6lXA7h6+5P/t2 BwKL5ExoOU0sLRYe11/U3Ui5UO0gBbKy4E3OJNi8IZjp8BLC3NJrmV6GGRigJSloXpl0MszhDjBc twkla5r2uRjBw4J2FjgZEeDJQ655mKBJIyXA+g6sg1mXKmM+SWQN/IpqZilFDVM0lCpH5tJS2kQF Ma6D8CEvCwISFAu0AU2QuF7JpIJ4rgTJ3+0zKTOLrHwIRnwPExoAfDQqGGEnjKU8uFHy+lKbi3Zb +5UKh97r0k/APsGffj68bni4XqzLNaslc3AqtOZxiEu1uaHGopsV1eou/5gV4jh6c/LyY0TZmfb2 Bcan16btAlsSVn7B129y5/sRdG3OaVnutZeP+Tx25Lu/29+pmde3iTk7FD5L7Y2fqxdWHdNdH2pY YQUaDIQNgG4rfBhmgzTEANe7yjY1iZYAovP6RK8WtBZ8x6yVJsEcNJya14ErFVBL6TJBIE0M8C9W xdFUMIorgYPFdJhmUGoJ04Cex+J0MrGNgZRBIXEL7As+ALDlt5KFmWYQDYBLwUQtpTrtpV2rJoWS YGpOplJCS9zvJVmnkqZrxduQ1iYVZbnnOTE7QxLTf5CjIXhrqu1h3FbIEhEosXbMdp4zb5aOXjOw 2M0wwf8YK5jOhV6Ijdu011+yU7u7q8/cmBNaPnXfJ9h8bfX96Mep8XrH+gwB7j3dvo81pKlmMX7O 6TEnGLR9+550jIb39z/b9LAb2FSbdudSsMBVG/ZrWUgtnTPGpeaF7zDTxJS1784/vzY3Z4rO9S22 OZ8Y9OxIZjLeT0fZrW9InLTFJhjgG0XMONqsdaEiBAeETBR7AF6E/52KvWyiG2ohVV7yfGhOMN+I aTGVTUKTMAg1Q6hlucZrMMl1Jtn/AdHHQ2jqF5iBCeMTGeaDPO3Q+kwoEDKGti0yKcBUROK/SqoQ JcyeS1Nnyisj/0o5YhFybRUn08+SecCI4cF8PFXkf0ncSoNspm2iwizIpTYpR6CllSjmwSoXyuq3 L6sHPoc4j8UgbJTB0gTrF9oQmMazUxN1Fq/7vXs/Pcc34c7FNQ61urFJON/XaZuX4B16Xk9KxD+b 0kgr0LjA+9Q89QsF1c74vXZqMg52fIc4Xz8G7v3cz6Za7nCczh32epZrc96rFcLDPgbeNiZ4kGoe k7hW93wXZjj3bsafj+eMyqpeyxyOHX5RzXjOLJ3bSHzvEsvQvCQb/KwgsU6ShuTNFLwlFkNtCFZj 0iAfOHpKcijTu6RMD0NyJ8iXMUJXUBwilqiMpAGwH0GzQhwiEStqalGKJIHgG5nEgIjrw0tDXUEI IUyiCAJUP4MwQCA2AHhoU2VdmNjHmmYaDgDlmlMLVXdCWUWJHMBYyHM57A9ys0NWhpCaFD2e0Mbi tRzuD9KmdecJpaZYVpJtVnI6HuXm9rHsD88lTEPQuuRUGWpEmJIDhr5gccNjycSBxP1s5gbXBJwu eJ/mMbcLuS/YzPMJK9q+074t/0Sf3/GHBMiheWa1uXZh1z1vYswJP5KBSTzW8lgK1JrwhJH2palH hlrWuO0eE3qx3XzY72Ebeh3/u2g62r4PFriPINvBCZgzvSbt23iW3h2sF6RGAs7rkprde/bvb6r1 jI9LtDjblJ0vbm0Ddy4sWRSXbNg4YnsyQmU04Dnvii8cDwcWMGCcIAD2BKaalsaCNnNEHvT1lt9D 46njTPbNXo7HPflNBN5hdqUrQ/pEpR1gVjWZ9RAgEG52N+hUf5YNQ8dMMLLJGArBRe8hiKamcAL+ gTp223WdAAAgAElEQVSBFH9puGNfICjBi6qAxQVqaiL31stPPiYPD3dSJSXZ8hCgRYlEg5r1FHwq SRGaZGIKmY8LFItColUkRZNLtl3T+2kLckBQ2WDsOnhObStL1pIlqFRj8DKkdDb8Fvsyx+WgfC9u bsfpJ4vV1Lozzk4MdwKcW6iuhuFiFOfW9/nvh0J4LMRUM8Ac6OsyUliYMbfQxWA3x5hgsXqdBBb7 mmopw01jXFPPFfZz4UjzGowKU1cDc8+yfRn/1HPHbc1pWIEv+JrCbwgRjDeYZdxo+XNrZvs2VJ7P 7C/D+1wk+DzCfHz/uGmvlGgZtJKafFQ0yySRKimkyEspciVgQqiRfmBq0OkOCDU95aIHTQDCAWaV xa6QzgX4OPLiwdRXcL7WoqbI5W5MpigBG13TEENTYqZS/m0GR1pysJDgL4taCggIJsxl9TJqeXkK L5qGKkhsmKbN9YX0yKdqL0EeyjrbSZZupApzljdLb7eyr57Rm6ncWaOuo/0oZG1FUiVYoBQaoOJ0 FR4sEnobcW96JpH6OUzI1QIlon9x1mvSv7A5AuD4xbqTyPeypxraVHj4MBC/uj/VmKbHeAGdx+R8 2s140du5M2jfxteBKDs2x+A5Br7pOB+mfZ6Tor5F6nx7xlzxvT/3ml4IjsHpvqLS2Owe9K7TioZt Lx2O3uNtb3ym2z/3nst9MUK2qyI9rLYznlP9ePi1W5+56DviNi81AJlIPmIG17ATyUVCmZhD/owJ 9UhPMLlw0BRCYDTRny5QUhQMLQEJ9PA5vv/wg+dyOBwkzgDai9zf7WWd3siXf/+r8uTlR5oH3hSi gIdxs9rK/n5vKreIrDcryVZgkfexi9y9oGp3waPQ2pR1niDWD54/S7pDf02mCMYkJipckS4Z/UO4 TZbtmHueKXGqVBnswOMgZY2KC7wNY0s6BYOsNQ8YU0QbMBwmIeQulg7y1VcBzN+QoUshx9cd+j73 mPvCxmai7+hfrrsjL+1kLo41P+H9mII/jnE6odszf19ido2xKR2j3rS1lBYDvlsthu+lkSxTjZ7F ek02D9BzPvrhB4zn+z09fFqZ/dyaZr6N5aMerZ0Xk/ZUSGqeqdFmMGmjd4idm3+aycu2z6u7c+au dc/znTueY+66iIv8qcTxjsB3EAI8x+8JTTWkfEGmT2hBpoWuYyzigJi/FOxzkzUBEsnkiIe2U5e1 HO6P0sAkShM5PN/Ls/cf5OXHreSnQp4/31N7QSJAHNDY7oJ7OR0L2Ww2stlqEQzbWeabhwnWBrJO dvQCkj3P9FolsStSM+jB1O6CatDiudK1lEj+V7USIDe9NHIs7jVDaqxFN6B56bsmr4FedAhhO7jQ DCEYYT6ifqOOQ0G6Bsi2MHtZiccAxchWUUW54lgNzGrrQXQn0dykWRYsY7B33rzz72CDMy4Qkr4+ XAosX3KwzBg0ZoPLQUNlID7M+kazgODdKr4KDmCP4bUDjQd5zippEQEQLYPVlx1Twew6BM6PV6/x zQ2X5Sl9lH623vv3mtD0nvOYW485vUhG1/E5eDG9ln4p/DDsx/y5CD+Wqs4lg/nC3SiTsEnl2NxJ KSf13pEPZYITDYgIj6EF3DUfluFQgXiaplTRQexE/1dZRo2rKgBo1yxiut5s6FEkQF/jHpqhdL9/ 0HxTTSubjZZWtzuRgSRZiXmdXEteH6SoUbZeszxAkMFDyHTOhtRpaKuSxRsp0xPNSknA4NeUNnl7 kIfTM9lltzoikfLBYOVhk4Ews4Vby7KS/f2B+Nx2t5WY8UA6McCYB76l5c30MzwDBSkKtkJ7hUl9 pvT8+Hf7AucA0RefCJdXKplrw4cTTRfHECS25/v6rHgPsMO9hFBRjcZMgYXsHW0ibW3iRZn+R+cV miFPrwtlsaFlJlX1AsA8eirnvPEzDHpqntfvDZ17b30h0TkhF5x9Zy6Arcc8HqXHtCz8Mi7maj7T d2cPF7fq54Hv3S9rZ323LtsgbV73GJylOFhxYlAQsaJVwBCYTK44SZ7fPTcX1WoGhqnkzVHSTdap 4xE1zoiMdvwsihPB5yCq5JDnEjexxFkgN7c7kjLxgFfXW30hsAgN6L7ZZOQ8aSAlBgNZGDSvOb6n 15FJ8yBItLgEAHbQKuIwk6I+8ifTJIMwarIdpCh+gQwPzYq54Q/3Dxy0NBO5e/ZMyjSQ1SaTqjiK IMspBBouxmLi+2+lPFXy7teeUiA/foLAaERLo5+6qGqkVi50sagmoC8jTTbMPDYnH+aElc+rNZyA LhnPv0O7AP385Jlyq+YwGXfhTIXP8kTXNmYEJQrfIs0QssLCQwuTDp8TxyylpVBCem0l71pOmvUk 95QE/Zy50ajt9mM1xMTsKnO9qpNeL5g2Q2/vvKZl3/tUi+rf73CMxuNmuxAsjv340cZ9usy8tf3S a/1hNMvX9WFovo0Rpf+6851nJA5oOj8v+FuJEWISZUjgZ0pbIRxHWjk2gQTJtYQRGJ26g0F7WMG7 xyyemnDvdNirgAmUHrFebZWHdYKncCXXjzc6rZgyo5Xo5WtqUI9fecTzUTwVXWd1HZhwKOuF8Bdb fNUuJDMIYZjJ3cN7smlzDcUxUe2Y8IhPLKqDxEEm6/RaMpTuArG0QRIGDZJmBaCmodmJXf14bOXr X/lAmvoP5dVXX5X33n1Pbm9vJM20diHN4aCVj33yJWqGx8OJwvDD957J6XiSNEupXWHssixluzAX YSLi8z/52c9Iu8JSzJkfngz5wQ60PJHsxFEtYDpB7DnjCWqGbHQPe5+5sJplPo7bH10UPp7PUIDZ nbw3o6YaJj5HxMV2/Vjy6l7qQBM3whTEO2PmDe5qCrerye266W1GBROZweHtweGpM8Jvn+kmOdQO 5gWDK5x77Wk4Tu7A2WaH2RNsn+aE3hjzCS7YIFytb3ju8JzhMPQbimpnrrNgGRD3OSTceWavwVUH gsuBpKHJHmoOrDOWKzZcOW1i+N44T5AxExyrh9MdhQyj79qKaV/Wqytp4pVIeMXqMFXeSHVoWV6L mUabhgA7DoDZtvJzearlvW+ApKnmXJJG/If7IPMo6xtCqsYhtRbsmtkWQqpkodX80Mh6h5L1tl6i st11ooXM1gAzlpiWKR1Pzx2uL08Eu7nDIqVyoMHKNaUzJrb2A6bp6XBinOBuu5UnLz+Rw0OhHLNV IhH6BoEFU9BkryiKUh699Ijv8PBwoAa2ebTh39AIgPeRSBoGstttKcB2Vxv2B/wtUDk26Y3J8tB7 DF1MxJ0UvXCYRtXjMyxkmKmI/bz0GC9A18O17DW01zvA7iII796z16yWsDY6SGBGtyVpKgiBCttU smjNBpSfpRk2+tJqvIP5TLoisWoy2rJl0+cfmzZWC4UgHGe/mBNaVqNYwmp6AanPeImb371u6mCR yTP8ceOJl+Bpw9u5eGroFXC1EVZrVrEKpGhbOeBDB7yHldaV7qWPTSNZtrRODOi+3u6klFzy5oEA MQ5MDBA47/cfSppuGIVSIu3wNpX4+hFTBYMNzio1jONLNA6vFikOpdw/P8j77zyVZx/ey6uvv2ow JpHNdit3jebVOh6PkiYo7lDI9c2N7B8KuXv6TB69dCOn470UXy+VQ8XYxEBWq1Reef0lsuyBIaHU V4vYxSBWvheBbdANKmkjFaRJsJEIOb0cgYD+pnEqH3/zY1pbEQVYC/CwYllvE/n4x1+XBjGETSmN XHd57sGUuHnpSm4I5isITEQtsryhUO6f7uV0ymW328hut1YzV2pWCsLEzvMDva/4W+Pi8L7OZR7o 4+eGE6b/2+Yhsqr4aGp1k8q/RnoNaNzu+O9eiKqwGGsF48U2bWN+IbDtBoVGNhKD8MuSarrBMEe/ cz8+Z09YMdqUvberHVjNfLqofX30mcjDd+HXtOYsJf8YjK6eMbfGm4jvGnsMNxfxHPM4m9+bazEz w/ODcwm1FUyVKkDTGjc7bENhG+sE6cUz/kE2bUANMpp/Cu4mN+thHQaVFH2ZNdzroWpVaDH4OQYv 6blJU0yljEAzclsxWydwohJ5sE4CYzFKNBg4b26kPj0QS7IvjSB31crh4UQaADQOmEW6cEVOh1xO x1yFEAByak2B5Hkh98/38vTpU7m5vZHjEWRO1SBwHrScnhWlkxisehbHCBoJUyTr03Q28FpCWAH0 b9Omu4rewhbVe5AxNaYWJSGIrCgYC2pFTS9UlKIizoYeR5BokX4Z6WtgHlI4GV3A7nq2gCvG7ObJ TnbVWjLkEEOVHkOAtS52nEdBiPxeTp6r+ck0nJDd9HDOw1hqgLlLRp2amWOB5JpT/Yrr+zLOpdQL q6FLftxPd8H3/dQdFJNvSRnkM9CTau5pvE29NuqQFL15lbqGFu/h04b4WQdEmzt4ykyd+3tOSx2b jHPjNhzfc1pOMHlsq83i+lxr+up35j8gCyVmmoybtx5C+zlmL2BcWCeY86mpDGXP6+5raBQMy7Pa dDeKekYCrqXDRetCkUaODM0C3E9d9qUROZn6EDH5RLAeTUAy08ukIF9GkjJXloLbrJ5cHqUs7yVO VpJmiRTtWqI47dz7MM/iLJPb28c0fw75c9ndbNkRLF5WwgnXsgVdAXhZGFK7wT2KVLN5bnZr8rqs MFBzCxpfH2bANDcIlIbACxA+VEtbnUh2VSuqlTrQAGz79Ba4R0Xq1LqRLRgKwBcZUZFCGaZwuFPz gJ+VEmBbYOZSJaPSpDWlvRpgfRTUJUmpEFzIH0YoBRQMpxQa4yrrnDgbQ4sQc9gJP9erM06lMn+w 1Jqpyt1jMN0UnZ3cg4lq/+Ocsmzi9Yt6HvhVUwnzDBPeioIQWW0XzMK+/73w6OVzH5PWLRhjbg0z YZx/ftsjbiBw7JAQ7WJyl4HUPoeFvd88SO3PS+a26f709r+dx7TwFcjMvTZqx1J/y5VS2W0k7lMO BY6OpU3ui3A2O95eB4/52H0/LkvLHY7puE2flQKMoW+q3eEMpkdg3F3jvnzt9Wq10XqEzLpgQmvK XIs7IK0KJxeAbSZx588oDeTR4xu53u5kXyeSbkDUrKihEFCPMnKs0BZY4qo9KSB/+/hK1qhKk2kt QobzmOo3qpXpoCuzHQ+SkPeERcsiGFWtdQsRm9iWDEiumrUEIYpmBKRDQNtDeI+6vXWYLBER+EcT VJKzAKsOovVKsYistdFJndDBBs4FRwSCu63+C2c8kzqbxQeyI6MCwDVqSgnQfqiB4D3jed5cGmoF /cSyB3PucxzVY/kifJ4OH5nx3vm1EcfkGk1A+ywVQVRo1rpIrGlQMN8YNKlh+75nttlw3TEYAv29 Bm3vO+6XX6CqNqURCSghd+IuHoWZBuNT00OeNi0p91GOJY/aWEN50XYDL6jet2lNuBhEaSM8OiEo gYDOXBtTzL5JUtY6yE/fGfZpXG8VdyuGfKb/uE+dRnymKvi4/65W2z0flCjza8zFBGUNHjwWJtWF hX/Aiuoj6vBl/A6g8+FwpABD1k+w3ZsmligDwHwtMTyFooKCYTDUPfUnw2UwAAlYAzWDoFHHEO3q YgskBZCP3FLIuV4Wyoky4TkM6nQ8TjQLU+PmDgPJwW5GJecq5+dYLKd6L3GVySpNDbUBaY0z2R+f 6cI3ISC4P0t5Ga4MgF1mWo0T/VxaPgMKcOigq0eTAeKMddQ+EusCb4wTAj1A7BHS6pSSbdWsxO/o o8YjgrCK9u10cD0s04not350QkHTG0/o5cNfDMK2MfbuuRPUmpI+s4jcOnh/DZaBKZCYDQYu7WMN WoyaGL0G5dc23J168t1gZIaeqWGAdP9M/d9mEZsqUVaThiVRGpwTwgvQAOMXxyM30nymYz5cjHPO hkuB8iXtqh1pY3bIoNVy3Lv0Nza+MJSMm6rRRPmd1YM8ZvLMRurTIOfwuKXn6LFCfjJ7jw50J/my yRnLB9DaPnVfhyyQbJXJ1dVW3v7y2/Lbv/W78rnv+Y7OlAvAkakeJEp3DHEpqw8lb/aSy4F8LZhK WoGnrwRi1XENVjU7NpQ0UyLMCiGq7JhIKC5BLc8WetBUMshpZf6kcICIUMET0oSFNljGJ8l4nkb+ 8z5NoxWfqT1pOJFqKVrGjBqbwZ40VhLpnyM6Fori1GlOzJCaqrCnac3n6AeYOxg8JKjbaNI9M7ME SoZFiazSoTZkF2iPAynY7PPCW7PHviOrZcE8JKF1NDHGk2ZOm+rxFC3J7l9sfdyY/akCHLgJTPRA VnCOwOzvJrFJ0gi0lGA6KAvDiemb8NMF5GA+pi/2H05VXLQPmh4A9W5bNPk1HRJpNcgmQi9hZeIV EbeWsqzbMmg9HksXkxmC+eNzljThF1n8rWOiW+2oGxkzT3Q9awYWWhOO7HZvMXffJRzVN6fmnAhL zzt2QPkEc/zB/qumyISmU8FhGcX2ZLTxUz/9b8nf/pm/Jz//D39RPvunv5Xfw1OIFMoozlDmzyVG ypZG4+g2uyuWAsMiZ9pj1ParkEsLGTo1vXI3kQhmYxBVcwH5lBkj2lqrMUO9jTWjaF+Zw1TRqTQv O4TjKt7KMbyXKEplv3/W5fiC8wBtQ01Oo42sVrmU98hFr4n5kJHCCiZ1nUPwqOaVn0ISRe2hqWfU DLM25Xq9hR9TjvBcmuKtwNYQw0iwMlux7iFNTmwKBDEhYjUX1rjayPBFL71mF+DtX/K5ybY0afrf /ZrFnEnCd2MExxU2v9Hkt12i39SzaQ/P9edJ8u3+PeblGZ0uZs7HxUK+/hMTT+JvhAXZzQxQBLVx ar/zZvp4bPrvhlSOc4er0Y7HYtw2DisEex4Xf6h10CpAnZlcAppby9W0+rbmzLKxqW/vaX8uOSDG c+SSw/Vy+46Bkwlxf/hAPVkKDJtnN8G/+v3NzZW88YnX5ctf/qr8wv/7BfmBH/6zFFa4EUy4GuXk y1yy9VayuNWULMS9FPiGVgLhpSAxilIgn9RRtROkroHJ6JQW0+wLmoIZoDszmJoAZL4szHoIMpiV BOARgBZroYowkTJSgiiImhBWYEozUggFL5gnSCs344AJWbBYas48VhbABn4WwkRtEzkdgTshxQ6q 5yBxYM1Cq+gLvJXYofEcYN6jKzSvKYyVSyYA6pmjSFMsu9b91K73UR363XL8Eq1mxkyuqLpmEvvN TRw/BjH/nas1jDN+2ntgoVRcHP56ebYfzBDLjcSZa+N+jUiV43N6bcnNgmE0UtOCCiv7/dREhMMD ERIIdLcZcfEO4X1GfjNES/iOJS2i15C7T7zn+YWgTaC5vNCDBXBfM5ro58CerPeuN+1t8PNQm+6P qefVFUpzGqY7Hue0UJ+2u9TueA7HTIdiBBN9BiaQGY46dcVrGSlcA83q+d29/H8/90/lk596Qz75 qTclP524OFUYBVJDHUKoD/CAvFAPmyk/b00paickCRoaPzEYpS6g4KByn5SHxWvqht49FmkVVdMT hOcwl3zJQFnNGFHxXFBEwXSHDoNiq3QYmAHhuWTGa7oZUgIgiOLYaE8qGWDGIkEg/jwcHmiC2sFL E1sfUTOu1mEtKQOtjSDEeDZGU4SgRQYLmoG4j5ZBA4Y1xAjOT9aJO3nkIbI4n12sczuWT+0ftz3+ zm3K3fmBVVW1mlAwARMC6gsUDRNb58PA7E8b0jRB8iZazFjgmpxZEIjGNOzb7U1TbFSgrYCgqvMQ ZMbUFDNB7jZsKMOCIvM4Uq8FTwWYO966CY43Ht/hjvfShjP+XTcNZFoZT6fhPFHTeZr7yz3mzPJz wsU9x6eVzV23dO5Aw+qYzmbt6FgakBQYDoQK8161cnN7RaH19Olz+Zm/8XflJ//ij8obH39Fs4QG 0EiOjKVL4rW0wVba6ChBoNkUmAoGKisFBHAfk145TlRwQBOj3ISQSZWzBLqCzdIJQQRBAEusVW8j i1xUtcGINN0N0hSHSDLDAhMKbPN6+8+YZJSNNrwDj8zYM2OiGd6XHTwCyWUh2Xqj+bBYeUdpE8xK AQ1QoM3FEjKcBAx7zR3WmvvjHGiibAvCzpQQ07hHV1X3axTuMa9u68LUhbGsXS0dw8t6XG3QDsjE yN9vFheEFbxS85QFvcoE13BxYSwGS6kvNTkp5uFqc715Y2pimlPV/LFtuVicFkyB+QcvrfKuFfcM MF+YDludKeSBDXBFFbC2D37wfM50HwqKqYfV1TB97c6/v3Z0w9psHvoOdKzn2p1r+5JjLCz9GJ3/ mhe551x7dN3ZFMUd7mBIiPTUudKybeWVV1+SH/zh75P/+//8u/L3/87Pyb/z7/0408BAu4HgCLEI yVC/ks3mSgriOoqNWbvbCkPV4vReNMFAdYAJFiNMBxMMwc0qNK0wQV8AgDMFDAWQCjuSXqEJYm9E rnhT4WbgfSNVIpag0pJl2h+k0TH9IFEVIHnZm4XGVFayp2ZuUEEIQa+EWJBAeQ0qEMEdTm1Vq/5E sRHSZlybLpuAmiIu38jdFl1zrPei9Mc51VvB9+iiSXD+CAYCB/uGyQmrrnNktbigDp494KKGFxWa Dd3mDk/Id/SaqDsWJjsD3pHpI65GIkqLp9l9GEA/0g6D6gKCNBFTbiioJ4ANZpwzaw4DvDy1jF+w uQkGrfZn35F+7tO+lrCmhs+quCAz/zqb34tiSb0DY/4ZLm7pj0Eg+g7ysLiWYZLZhWgXsMEYyCI3 GghCWN5862Py0//+T8p/9Vf/W/kzb3+XvPzqy7LeIAWIVtopkBUUDC2AzO1agOVjsiiWZarmkBKA Xa2kxkLPBTF3d2fUBU7vojHDQgjFLB7suppEDOYWcqvrpKBANPQHnQP6E5iX1ObZOuBS3eychIaY yucGAF8bTZDM9UoT+FnvE8emIgaGgh2S6gqhxgj+GjNgqAbLNDnaa4tQU7A6r3j86kYvcQo82+9c FVwzXNjn6gXWHBC/PEEgEOD472Py8IOfwXuM3dxQFpawnf5dGdIvYsm4IbWMUDKJiYzgGm0yploO 0xnZ90KzDjUDFGe0LnoLMrviH/9gsqaBVmyCBq6E3akX0cUQ+xbGwmnMgJ+O2rwpjrlvsp4Y77gb tzj2CM+NY2BpJSZGFgIbY2rpI4rhuSNwXsu61FHj05Yu1a7GZqbPhBxjXON3E+sCdB9QFzM1GRN2 Au2BxUkTKGQKnr/+xuvyp7/z2+TLv/+2vP7Ga8Sz6A2s4Q1EWmXjgUtvqIGUxQOrSmPh2zfTaVwm txYZ9HGm5iN4ShZ8Zj4uNb3CwBZfhcdNCZn4h3syDzsCZSWkB5DePIDfmATIs0TQ1whhPLehMFjc ytIuSMOAUKOgUs8gGoPGmWQrrWqN/6H/RghWYdEJVzU9UQVMi7xqWE/cpz7h88SOwKKY9E6YgaY1 8t645sEUKPUVMphOJP9haQPIgIFF0fcSLWNhrEy217k25wBY6w3KgkbKWv9B5yHuwubUhLP367Qo m+2W/gvUpVSBh4W6MaRimkVmzoD/ZT2SOaMc1EQfm3zepx8JI1dIuEJgScsaL7jp9/3eZfE3+/l4 8Xb3CGyaJX1HEPpWY4WmOxUCep4vpfP4fZ07fJjWOQ3TNy/HJu2SWTkeBxwxawx2XiZNzWGzOmr1 Z+uV0yocCD9hXb8gkO/9/u+Rv/4//W+y3x/lx37ih+S1158Q2wENAAIHC3WTVRLEqZRVJg08aNBI EiWMol1QEsioZf1DCCL19MB008of4GQpoI2ddZVtNLMesSWkRQZ5tWFGT7ih19mV4lrwAoEHBPzN YerCgCAfxXKkDSDrTmIIO5I8WblHvYj4HbSM1TqSMALFQpMPIvgaBScwPoiBhGkNgYcFE9UhzVsI bgg9LDRl1SNlGFI3w7nQKJ9tMqf1AwXSjQeJpuYli21oQo69i0sTTheMap3QTHDdKlJ8ajiZrEmj At8Fced2Z7tQ9HvQWDAW6tk61iIZhAw1a9XqIHw0EaMuyCM1qppYZhaFsk3xjvvsABBQrs7Kecy+ QWilFIr00s4M4ZIWMNW+PNc5gsU/vqY6laEaWJ6+1VD7y8egtTZdNC1xQ9uDFdIVmbRNLjVmaeOY +318vm8sxudND/XUupupe5/x3LtUaLk/Y5hOeFh4vnB0GhdA4UI1H8xN8lSkIOi8SjbUKr7789/B FwAs6xd//gvyY//2vylXt1d9cC/SzyB2L4kki1Mp2p2kqXYUAgGCwAoGalixJvQji51hK5obHsIK dIcS4T9mu4fGR2pDDa/IRpJ1RsGB3RkUC6YZgSDAeUHIdBabKJADytaj2o4BpvuAV9UsgYdZXAvP qnwr3W7tYFOwwtxqQmkqzTIA6gX4bNKkbB/jBwGLPO8GtTBYnWpySlg06aQ9C8idIBBqFmx2Vfzx ghpiLXaCyAsdFi+C9lK0MOvhQBjtkuSpDV2HPk1iacfEQW8iPLJtQ3pm2UKLpj+NmlMaQUPtSY8R 6k0y/EupKVPu2tQ5EQetJMAR25o50XJ4jo0p6yaLe5H+n9UwOlKrHoNAcvMFhFXRwj1ktqAOl7P0 kWG5No0cCLl5WFCd54we+5yg8X3+IiZdL0SHHtq578btz2mcPaTRCzyfoItZct4sIAWL+wG+f/5M bh69RPc8Ah/tBCFRE1SGOJFv++xn5A9+7yvy5d//ivzKL31JfuhHvo8aFAfTuPVtPCIyhTbNybCe A9IeNCwHuFcucZpQYGTBWjWLCkUutC3QGiBIKmYBNRK6xgOsOcHRVhJDAKhJR+2Nbl6jqRgVXLlX w2dVTygEbCt5flRmfZJSU+yyh8YNQ3OKIucCQgZT5GyCwEnBWo9zJaoGWooMz1GFYPmrKULPI+5P s1EBCAD0vvQy7jF0P4+FlWpr44mB9wTAHbny8dM9Z05Ft6aOBaoR6Y8itK6wsvewmmlvIk3bct33 cxPUOnfwPWrhwtSEt9Vy/wCg23OtgOJldpU4h293VszI1G6EcGD9SjDx9V2TqzTKTDGvjfTPOjEC 8sgAACAASURBVAuK9y7K4Xg5/aIziearcg9KYL6mCpXbPPE440W1YEBiNF2FLi7bjMaCxNtv/cv7 rnzzZdyettNjj+dMzRfFy9wjtlKNwsi48G2oDLCqwcskl0qFlk1pstms5ZOf+ri898778vCw71jy 4FEhawFVWaQdjrCn0N5U/pTBxhjegmsi1CBUzyHTuRTAiWKIMqka1Xp4z7VWgQagTLIphFmBHFs5 MbK6iZEERwF3ek10/thEkpajxIIRFBjqCaRGFmsZrwaFLIGHIKDZxBZS7Qb5EwUzWK6QJToUwAU5 lWmSabtScME0ZpB1AVJsSlNYaRgI9+nETmfCze1K05Szl3l+GF5keGJzu+l0AhvMyPTN4iJ+n/05 UNZ9vuk51gTqzVXj+DCwhH6nAqe/17QC9fhZlhYDtH7wwCokY2wCKU26FcQ24h3T++whvrrmoP5u q8rM39f+rXmk+Il+DqcATMIIzgZtp7vSUH9su/27M5BN4AhrTlFPyNECUO//+zIca8mMtJ8vYXpz 7Y37M9f2gIcVkEHuppqAqq4hJ9wRDJjcQLjgf6YiL138YShvvvVx+a1f/1fywfvP5O7uXq5vdsSR rBcG5iTMtyBKJOai1crKEADZOqNpiHOP+1w+ePdDydLnXGwvv/pYwhhVUAqdLORB2MyjGk+oD6vB 1aBAwHyynkGo/cpbtexe9d5BkDE7agScDOXpCy32SgJsxgkFbI8pcUgNiGiOqrlssJgQhFEIMghU zTrBMmImLjGsdOe2jgI1OSNidQB+kee9L2m/rCWMd9NLJoWdQKqh9WanH5fpD5yNBUaN2uz6l4Cs 9nsb4tTNI49XaajNqIeCWhRJxMqZ0vQhppULFsKiWUPkEpAG0hGphxbvFBEH+BXxjyqwcDvVXjSt ic1mO/beaas+YeyOFRALCCwt4NLDANSAoSSYZ3YJnoOx5lwb3zPUD2ayD11i3g1/1wIZ7mVzZtv4 u0uFE+/iwa7G351vE5sLhBV2GJpKtoCoer4oyM3C1a+U9KgUh1h5Wm0rT568JLePb+X3/tXvy5f/ 8G2aiTgIBFpAmQUsQmkTJV024L4wi4PWESxPpTx/+iAfvHsnRfEBr99crWR3rXnZrdmqhScwudQh wIeIY02FYzIjbDOdELpru4+rAsvSHXBdXSBIWhnu5HGRl2N2MIDCUSglJ7SpZmtrEwK/giYFgQVn gglqHtlf5r4GEws1rpAFacl0x/npC4Cdvl3J/4LVjDJhUAzunaZYnk4HZUvje5hnFt+zjpe5+7AX tvxWFxNmgWi/Mubu8ASfbSiNwWVsFRzbhKWuWP7dXF+mz2SZ7cggYvBZWzIuUCIv3y+za5i8YgYe acR6cnuvtjXP1EK0oLnZGJ1FifQ6KqyAmeFDAy1YbI3OFCPYB4Jw9BzWBHckZmCe4ZLnv+zwaXUv cPWZ08+1d5lmZkB3aVBLzyTvJ9gKrAWAZ6bYE8iSRmugKWeIjygUgWuALQGHQQ7z1SqT4x75qLQk kzUbmQ2Bpf4wGUQCJK9j2SYUHwWGhPqHtRwOhazXa0kS1VYSo/FELarw5PQOwTxEEjzECzIExtAQ 0iyU4+EBLj4pGSakXiO72CwwqJu3kj8tuZRUBCswCB4gfAiTGemTT4wVxGSz+bugkXEIjXcMRTng zQQXi1PSLDKbVZHnIDuEqX9IAZfDRIQWaBaEB9S1n/lCd4aAp32hYzOpP1dzlXvMwI7JbrNLwiSf grl+U8P4uYyXisV0jfatRSS0+MiSZ7PvuxUIwy/BTEeVJWi0UZBJ7GRPOHf06WNA0jWhW6rrEitD 4V2SiTFHmd3UQATsfULNuQkcEWWGWNMJuXyvVjlpRqwippIxfUFIbzGvpiDXmFKNG5yGTvnAa2qa RlgFMwHpl5rH9rtzZtfS937Bct4cXzouE7RWYEXAVFBLT8NvULiSphzKchkmMHI82ZjAtj0xFxYW OThVwI7uPnyQ3/6N35X7hwf5ts8ik4Oei/AULTePiYuflbT5iQIMWtDD/XM5IZQn20m63sr2tpX3 v/aOfMfnvp3tcoEzw0EgdVRxf3UpCKQKIAjZJNqDAItWqpENB8z2HYJQNSetJ2g9E8o3A75hzUQI awjJsjzRGZAyM6sQ14LATgPkCAMZtGXSwAx0i1AovCxBNomRsRXVdzDGLR0LQRIyFxjm4Sa7obBG AVv35Q09RC6O4Z5jX6KbT2g4AbiTI0ayUkoG8CCaq0YLUu2i9wri+ZAuuqcwTEHaoRaRU/iCrIvS aOrEwCZlMJ6ufh/6qPNLZbhb2t2Yp26O9o6pDaFSEiuE8AemybTJC/iZrf+nragQxf80UQEcHdCg 1TdHrQ6CUBAEDXpNzAIsoFZAs0pRXDjwbyY2VQs+ByUDJeXECCsI/TiMZMW6lW52USWO6gYJ01kh DfdwqQlWw5wTVOPD51Wzn9vD9b75jnmsa/i9zwpwoYaxtuYzBceOpbmMJXq9thPDNAFYjb2SudwN yIxpwmKjuUbWM01MEmr9P1ZrUY0Bffjww6dy9/xOjoejfPDeB5IhXzrzaK1NGA7AaqSWiWQFXAzp lqtKdlfXUn34vpTHpxI1J9muM7n9U98qX3n7Xbl/+ozeyI994jV5/PIVTdTElNQC1RDto3pPYFLi EDNgWpfYRKrzU+eB9W96m6j9afwhUjt3QK9hubcx4hb1XGiSoEwQxC4LEmJBxYCZDOwNKZ+h7UG8 l5iAtl6ewfhgmqYMpDbrCMIA5gDTGvN1e17O8MXbSWE/V2+Zmqmq0QxLj49ffIpYT2bkaFhlhy8+ ibnQ1L0P7E3DZMbGxlwfoPmgkjZMLSCbIOzCSa/wgTLuSVtgmTRgosMU0FY71RJtGhBv1warQLcF C/lCYFFQwAHTag1KSyB1F4v7ni2QzyKsjOuE7rOSk+w16y3rcPa5490xF8m1cAi07znvpnNwU4BI ZFpuNQ1Bm1Cv9JRLpZt5D7T7hMe8J256jL2aY6E1FixjgTbX7tL1vr6dE5C+/tqjC80zETW+vtgj huCw4CzzYZGfiHgJDZuow1wODw+S1KkkFSLZE/KNkJsbwDrORwD057/vu+QL//RX5R/8P78gP/2X fpKB0tajwV3daAFKBgW3SUF5TcMMJRzayZ6JAVFx59FLT+Tu6VPl3wAvy09yOu5ls7qSNFmbNkPJ D3s+6Pb6hplREagNbQGkQ4CmPd9Rd1sVyADyS3KnWDMaaWGQYdR4HbHz1VHNpIYpFkisEwz9ZsVq QyINcqSjMaXV4QVkn1STAE5HEi2qCUlLUJ+MeYLwEIQrZgYAyKwvZZpZYDwBhpNMQXzFirR2oqZX mU4i+zsoDsyoYapYBygui8VlFpS5y2CSzE1GJgw0Wb2YLLE5MRSrNZW8YyRkMpOT2h0qMXVeZwPm 62wdmLzMywYycIDQJuj4+k6Q3lqxQDyreoGnk9qndWj7uEMSZl0MoV7jLkJdKAlTfus4LJsqvXCA 0IejQrEvv/7X44AY6OYs5WD6bH6txnfeJcLI14avfZ+G5dO8ljQ3V7vyCcthe+PY2R4uwBHnx4Ok q5UKLRaaKGkCagpfdfVzMUAJiUCQPEl1KkjshKmGisfw/D1+9DK1oN/40m/LJz/1CfnzP/oDLOcF k8QKLkufUKIoSJkhc0pBW2OhBmgjaSKvvfGY5tTV9SekOB3lG2+/K9kmligxJpxdmMazyQBlaBLZ SrUmoAm0/RTENUM9MFOYHULLBlELAP6lvCs1l6jFYIEjhAahRYjyN7UA8ZNcKxNHiPtq4j/wnnSB qfaphWJRkIPpkmGGYjFHqaa9cQK6PdNqsCOOjw6T67IzqHfOYkjuRLEvWzclJc3yPZiFvJADzyss WVGoPkpeam56NACtPM/3rAOpiRBxX9UCNWusCtiO7d7zTEzsal+5GZiTBcUZG0qNRbXXTgAtYi7j BzKTPTBwwej03nnRZ9r1Hb770GtsojaBhSHwXzOT+N6Buc+MUBuP+ZJ2Eozi7ty++bBQn4nmu+/c RnVOWPoE2XjuLmt89hr3O5scoN/EY4KlDA8xaVLqmqRJXECelKmekxghxpQzTPZkkumFgfzWl35H /sk//oJ8+P6H8qlPf1JefeW1rqyVAofsSs+DokagHrk4BTPcgOeGiLm9Tgm0P336QM8RgPmi2Mur rz+WplJNyT4UcCTs4EgmyCKuAMTTDfleHfnK/BfEVe7UBiRG2AwESc6MEn3YjNIkNPUxme81ks4p rYFCCLndDc2jS3xo8CIr0ACqog/K38LzqvlmzQRyyDrNymBzg5etY9a9OF3VzoSx4TBmAhvnATAU NbGQEFEhdTLuKwga67XTOE3NEeZfOvM4h3qKiwrcN8Uj6aCooUmdyGFbr667vipupuZV4NMgjRlK x6yZLxGwI5hz9Brq+9DiH7pZ+XCaXsOax7c6u995RvtM/c95Iu9YWHSfwQyEV8kIr14I20U8vadP azr3DlqPUDp37lig+TTvFzle9Hz3mNfap5pV9770DBKZccSa/tdMfpNixVaIoQkFfIOxfxqlpTQF q9Yq/oDsDMCwnj+/l9ffeFUePb7VlB04p9Ed0SRHcJjbTt5wQx6lmcHvKwEOfX/3TNbba6avaatY 2jok1wvJ+YK15sRCv+JYNUOkZA6TVFOWTAZWQVvsshB6cBhBMDNwOUJMosY5Ks3DLBJqDiiY0TCl AJj3NkupEmjVLCZNo6mJz9ndk8HaLJ+m9jm01BjODebT1gXMpIWGGMoiHXMvmQvAXfBukQilL1jB RM3GxN/xDIYHGXCdmV1tNe0+d9WcidABQs4C5DjCpA0R8I1BgRMB+coU1O6SvRjPLAOOTSqfLm5z pCkMzS/0C8xcdyH7d/pekxgv0NHlnmMqrFz865Lr9Fq7sRAL9C5Kggl/pIV+6RFckJfKZ+otXeeb Gz5Nybni7NhP+2yvm244xIINNxBHjAVPhjji1Uz8nDXbtLQXMjXYyWaKm7IStAVDRb75M28Rh/ri L31J3n3nffmVX/4iOUlvvPka4vDNglIvEpexCf7t0rdYegLj9qwWV8vuBkHDyPwAz5vIV7/yDgXE 9aM7aYJI6BCEmYng5LKQ08NR1qBBMOjZFnAY7jRW7Yd7PKzhHNDc6oz+ZzFWNRGhGaiJFdPfjydQ DaChtolDs0WoJ7RCmBFiCaEZGKGvwkbHDR5TqaCFQVNNmJywqY4StjFNb8X1pliRCvg+jtC+1J6u YXERFdJqcfWV6JgRAcomiswis4VJwYL0MJpJf3E2mSno7HXUDrHJbQwPD1VmtBVk95hUoDbu+GF5 Lt9E7ycvNzbzfJbpvqQN9O/Y4mFWUCwf/XUuxrR87nRh96Pj11zOazNTAd7f0ydMgjNevkuF1tx9 fG3MmZ/De1szsO/LEq5lr9HrtMKWned2jptwYS3+Cu8rBRKr1RQmCLrPusmiCTAXARwbPghNRYC2 +UlQ5h6/76428me+93PyHd/1WfmXv/ab8n/9zN+X3/6Nfy1/+T/4C8wDjzzZBNYr5Dk3OdXJV1LP gBIOkY1BzRUyqKJQnrz2WD58/5m8/Ydvy/vvPJM0CeU7QXloGtnnR6YlQXZThrzg0iiSY1HKeq1M ZZvqpdvhtXkC4KxiW8HbmauFamatYlEIK4IGl2gpMZqQ8HJqwjSG8qB6dLbuXki6WpvPLU6j5gfG j7jVCql3SinhhYI6gv+XlaySa1kh+4NdarNazxAPcEHmfifvNRaLV9EaRWA5vXbW5AGe4+Jg/ok9 P8nU0wXyLJww8N5S84JAtCz3EcYy91zDRWL71FfsmZhoo8BiVzD1rHS/GTX3fGNhdQ7fGbYzzADh LtJzJpfvvDlTzjdmS+M5PlzN3GdOuodPUJ4T5vZ8W/TC/XxeCMMisM8KU3/4DFChlBMnsjZlfmJo C8CANNe4ajlcdAjuRWXmHLyrXFIA0sxrBW2spLCCICBZku71WFbrlXzX93y7fMu3fYv8tb/6X8vP /6N/Ij/KtDOvktXd0uxqpS0jSTIQMxX4prBiHUEi+1K1AG3VExSkW7l96SW5ub4mhlWjIkiG8Jm9 FMcHCZKNROFaSqhtm51sQL9QIIEUBAhKnA8tTJVzkFBP5FilCLKGrUfCJAQ0iia21NbaOpIwU0Z/ k2rlawSBC5jxJ62cw/qHxADVHatuejU+cUTGdKIAwTmxajoYZwZHg1qR5lJWMc1b+Khct65Phe80 K0PC7YOWjdAyn0FjLiAso1jWSEOiV3dt9e2ZPjukzXmh2S8ymLW7za35rE9oqKe6k9sVuPOCwd1x fVVUOGYmRIz977yLPVY2bvPcMcGiJmOzpNkM+VXnvYrTw128Y+1mFi8zx5zAOSd4x9+d11rn2xue 0yfdHJ/jftbln9O/aLHYzdemUlIqrlavxl/buL8m1uKpcec1swUnugR5CAhOhjiX9fjBUwZXrmY2 wIIDwFzKahXLf/Sf/Ify3/83/7N84s03ZbPZymqdEIRm2fkEbG/gY0oKjRMtitoA4JdKiiCSw/6O 98/CUFZPttTMgIl9+O5TOT6c5MmrN2RAF8dc4mgvSbSSq80jMpahIeG5mwAoUiVF1ZKaADIg6wuC /gAjtUZFHTz/jmYdi8WiEhDiJcmCt7meDPGSwgZaXcpnJmcLYgaaKMmhhqjophMxWh15a8ZMpLAC lwvtIvSJKXyPslpt6XqnmeWQLU0ro8mj2pua79CS++KuoHUwqUWcyCbBczvJ0h1NpGvIvNPxju8u HDsxe80OnmOb0VTDWbR7fQZNnYDzGo/PFLImsBfLII/spJxAM0/1WlOey8SWvsihWGL/vsabxLwp 2C/SOTDZd4zH1Hefc6Zz6xlDV9DOF5iY9s0nsOeEmW9c7KGFQ+YBhl4DG2cfsd/1BTqgWSFxJHBf JIp078X0Ml1nbIAwtAFTAIJZDXiCJksLYsUVbA6rKAbuoxk/rRcNDf2Jb/m0/MhP/JD8yi/9c/l7 P/sP5Pb2Wr71275ZvumbPynf+tnPSIwcRWRF6zVNhdQzMSp1qadwt+P3ZVHJ4f4kd88e5O7Zczk8 5PLkpccsaR+lyssBKx0mW9asJCIPqBHWXOUIgK0vcijuGEbE4hTMFgHiaMPMEIgXRFA3TUI8F/A2 w4TXgFyNG8RnGI9oBdNWsTaWh2Kb6jiAVsdMF0jXbLAjmN1YZDaLBQcem0BbyP7wnOFHKAB7yGvJ mo1kzAsGjU01N130+kLBT7LxkPDO5dWeTgQN5k6kbgJqVkGSyiYxrPXOjBriC/zZvd8ZDIPhN9Ns qGPzy5pw1ozrF6YraJ3g3RkAvefcTHd2pcXAmeNbGDbQOzAblmYu1ZCYZS1iuOtfInh6V7zd4H0C 5xLMajwO43POYVWBx9zyPaNPS/4omtfwPr2J2bc736Y9p0tLbrRxF9441RqvyVoBDpHZ9kfrx9uG uy8V4WJDBrNiUjwyv/u0vswLRWKkqTRjSKfIowQ+1ff/wOflzU++IR+8/5Tlwd5/9wP5wz94mxrO Z77lmzTrJgQmcKFSa/3FmzWDTgMIwjqXJAlktcG6CWS9XlE4Zlki6dpUikQ/Gat3krw6SELsBrmx tLYcAGKwlsHPQkLAQ37HcAxg4NDA8vbAAOgYVZhbMLYhSNTjhoBtQvI2+wOTbRmyJv7HwGJNbkiT 2sTSdXFPqLHIMenJoe5uTsoIi9hqzBtjL1sYqajk0nO09CXjVZgAYObyhkcT2F3BsBLQFoIylQBl quKVrBJ4RI3Q7iaOfW8XFIwwZivOs+JhojkO2hibUlNw+hI8Z27S2/nJ/liaAz2jFdNyU4hrL7h5 AXogjQWZbA28seQCHJuB5zS1/llckL/XYs8957nPfH0IPObZkpk2h3XNablL9xmbysNr9LmXhmwo yIfgvLmrHFnnQAUVHWfO9O1MwsnDUkgZNzY0EZbRQghLySBozWiAzhmJZwKCGaRqvGboEc5/6cmt PHnlMc2Fpx88k1//0m/Jr33x1+VXf+Vfyluf+oTSFQwrHCRTaBxSw+UPUxEmDjxqIqtNKNkKuBVo AmanNZym0yGXIkc+Ky1o2kSNnIq9rKKNbDIA4Gs1BSNNsQyyo4aLwKul8XQMjEUcGEizxinArKE2 GNWYi9BgVOiY3O0Md4E2SlYiB72vuQgVSKcvqCNdBR5SPExl7UDJngwQ5lvEOcj+kHcamX2Z/Rwy iyIAIxxJAwGsg3gLbTCWLI4kg2Y1s27Gk2qIyQzNPrx34noMiTO7aVfBaHlxTnd793e/C7s/b7oI rSnB1NpdLGTN0B1WcMaGaRI+MN8UScMG37sw59PlmQP6PvYmtH7+IhbpOS3m0nPdwyfIXJPxckHs /9t+NmxnasL7D1db0vAyi78iUhj6h+biHzqg3KMTWBbsVa+dIfCBF8VIdw0K7sikYHPT2jIqt2Wk GoGndf20Eg8rL4ehPH7pVr7zc58lhvQ3//e/LX/2+z4nb336LU4qCkPRvFFleU8uFNOuYLGQo4Qw EpxnvIr4l1dSnCq5e3bPyfLya4+JBSG+La+P0hbwbiYSN5kGdINFH64li7aSl3tTSl4nNJPvGROP Oa2wKyMQlvnf9WXDs4ifwLII/vI5bfyTZm212oGSGxsp8qNWEsZ4gUdaa3ENVmVW5Ic4IIi5OvEb Uj6QuwkaIQNfGBjd7+bWPGR2U0b9q9aGV4l7pQy4LQQhgxh7a/K7h2WhW1xS4x9tULnNKqtE2ZhZ 0nsNQk1TxRyGmpr19Fjz1ZqDw0newWkD/MLVJPuwFfc6TZOjdSxVWCEwuuI/RhYg1tAUJdECJohQ gHAzXluPZujDb4Z9XQKwXQwL1wxTxbjXXYJrLR2XmWeXH+NrfE4Gn3CbHxO/MJyap7Y4XB+toNaF ZgeGc4hXzAhdHCp5OqZ1j9prBlI1W7BbA5hHc9S2oIlAzXbAXMaJRXbxGMGF37HATb7069treevT b9Ld/s9+8YvEIl5+5bGkaUwvJBY/Mh9gQSP7AYiaBKOojajZhfMe7h7k6fv38sH7d5KfCnn05EbZ 6fpoXUAwhEEeHDTOLwjlancru/QxAfm8eWCmAa1B2FAjg4BrjccwYYl7BNxqSmXNGqECSj0aGokP xnqHcXX1C5WVrVqjUgC42xPoAa2rUg2OYLVqXmzVAMfYJIBN4eQ0Qv781PEO6ssjTYSwIxavUjDi GBklcjkZ3loabxkW5IabdAIAcaPMgwbOm6ZWwfPayZGfDkabcYQSBJWJOaTANpV1wJnDOTb1i2rC Q2xnvAg0NfR0wXgXj5nE2NgIrDO7BDQrzWMGLpsKLniRVkzhMxSkQ0xpDjNa+nvuuGThjxfd3N++ 78ZtBp5+LQmtMRa2BOBfcixhX0vY3Biv6v4eGdMWT3X777bF0Bx+aOLyiBGwgEQrFaLyDHmSOzrV BxReKE21EsgjxQ6UqQ68q5QWnivszigyYRIAwizCwkNlnf/8r/zH8j/+d39d3vn6+/IjP/7n5E98 66d7DY9mCHZLFGa9kzDcShtsNCd8UJB0CQkNQQH8bLfbyWqdydt/8A3Z7jby5HUVXgpal3Kq7snC BjCdrLWE/Uo2UuUnYlhWawRLfnet6V7g8QMxFUIYYlDN3b5ciQoHANy1lKHmxgI9JM9zUkDgmQQW Rh4bPYwFAX9kSLBCShMFalG+vEKIi9mhUYgBWq0Jk2pTo84j2ZvRaKBNMIFgUEtZB1Ij+0CI9wUP J7gp0O5yA8Yb3huvtcVjG+aulxhqGJOwSNSiejfSrGh/IUQRhAwsjWmmTYoeSCzFi/S6ojpKWSEf WCSrdKexhA4obifm0INlpqfh1ZpTBgtsMOlNNATfh2H1M+1Mg9Q2UF2R8/8o29WN2RiG4P65xeY7 Z1m7cg5kvoWGvaCNLJli53A99/d2gdvl2xiG970MX/O15+uD+WTSB/+mYPvd47v2MxBDWbHa0zV7 L5fiEmvQsXKvbFsUUMihXiqw279EANCayYHqt8l6QK8YMBdgWwYxYII/hLYwHYwWXoAwSLNU3nzr Dfkv/tp/Jv/L//C/yj/7x79GAfDpz3yCAcMQGlhsh/0DTTORvYQ12OxXmpOrrWR3s5X7Z4gzbJjO BovgyasvES9Dhd/1Rqvv2DqDyKha1Ee5P33Izw/5M1PaHqROmKKa8tgm9oOqhljGqMlYbKKMjvJw emYWPopObOhdRIrkQPaG/qQMeIwPAV8KVJQHa+RY7OmswFjZ7KYYr3gN7SeRoj7RvAbBlFlMrWka xlJUB36+Tq8oeGmKoZpMsJY9UjtHtaxS5YIVKJABbTddkeYRVomcDgem+empKZp+GAVEcpidlIPK Vsebg7l8d/8uPZfwip5Od2xrFe8kizYUUg/lB3I8PUgWr9Q8R+B1FPE50M9NeuNkjbCLRQ9Mvg/e fb9LBol7IwMG8Ew7kS35EBqq5l1Drn01jbvFaOIMWdWQifIymtI0OzC+wYrRFUuLcryw5kBqd7GO WpvkYLe/j/NauW1dolmNP3MxqPaM8HOFVd+v8xrjEtZ1yb1dgToUfmp5uRxDrIu8rBjfinTcaDYn DxQFVEzsqUdIU2CFUe++ZzZGmChIt0KOVmRwI82moHwoUxLLUBtswzhHGc+qhQnya6EDpmAos3aS NS9yfb2Tn/7LPyV/62/8rHzxl3+N+dsfv3yrlaPzk2SZpl7ROm6lZmpEvilwjoCJvfqIJsn17U42 O5BHYzntAfTfaAI+TF8k7MMEDi1AW8l9/iGpATbVjOVGIQib2keNfOYQPOhnLafqJG1Ym+wUjazS jUmnohSJKEYaHQ0rgLZ5ONwTNCe8Tma8TRtsK/46L9zgXUiZQ0FJbQd4DczuWkLk1oUQi1CaDAn4 kGgRmiM2jEDW2Vra8NiZdKCFUDMi8RXhQDALkUTQpqFRCWIxMI2VVEpIwTxQLb2tdEgkuKkcbgAA IABJREFUyP+FnPXQrGFW53KMnqvAC5AOupCcyfHMZGIBkVZWyZoaGh0dpor4MJ4ukLsP7+T53XM5 7I98d9c3V1LkyEsWyM3ttbz/zvuaxaOAth3K45cfS37M5XA4kgT8/Nm97K43stmtqRkfT0d5/a0n ksiO99GUyKWpirMYfHR2Idpz/J9b2Ha60Mcm+CUL3V7ntjX2zs0dvvMvNd3cNuYEtMUW+75o9Wr7 Tt12p1qqLSbS9cKU0sPmmsiKTG8Vqlz/hUbfKIl9SDkhaAFMiicwE6PJdw7nECUi/hnw2XoQR4zW 4qSUBHrSwH4vUE1GI9i1YMOQqGgxpk++9XEy4//FP/8N+bl/+Avy4z/15yXL1KOGicxCEMCxiKuh D9B4lPfVJI3cPNrJYX/ixIc2gKIZwLYevXRNE4lhMawRaEqkQ5AiltGQQS3WQjc5Jl4JDUuzNDSh MRfpItccVgkHEOnaTN5bA9j3+F8omzVqL8JEU7A3r45SN1qijK/OLGJmUCgLmrUQfNwo+IwVA8bx E5gNYhDR52N5T00HJhdIodCO0ghCty/WYDcP0jKg/TY54sglijOG5mjhD5sTX3E1MvTJxAcmpMIL mi7mBDchVJepQGlBJIO+t6LMJUxQ6cjGJqqGx3TaDPku1VQz1ZrtWPV2n8jzZ88ppNIskfyUy/3d PTc65OzC5FHzupRUErl/di9f+8rXuStDk0a/wc977xsfyLMPn0qUBPL6p57ohA5Xajo7BNa5hetb 8HPn+QRHv2B7Z8KccJkD9H3n+UD/F8HQcCxdf6mGNgwHG5uL04K04+eycJM+T3+e4sDwvKtsoGXG FN6WLN0X51WlSLUuHDEXP3GWki9a1THmauxAUwodnmeryVT0bJEwWpYdS56J7QA0G/iMkJc1L8np wVlJpx5mq5V853d/u+wfDvL2V74mX/rV35B/4/Pfyc+pCZjEfhpzVEhQZVIhL1IJ7Az8GhC0ajk+ HNn/PG/ltdfX1D4gYNIYO65mFm0T1aisAEK7jdUKsdBJWGslwkI0/C4m121VG8NCxKKFtqgms+VU mVzdHC/gLCvJUOgTBV1ZmbqSU3MwwdTWO6K0DDd0h0UpGICtOzcwOhWcyCyBRIEKjkNzRAEPJMFo EOpU9ZOCWS9MMDcD12lyqQdU349qgZrrzJBjye0yDHmMhc3Hb98pBbt6hAkPhKZSdcdAdgqShiKn 8sgMDiuMKakFRmg5E/72JQ3p4ca0XRMP3OxgxiO6aiPXjzQLBgnA2H1R6OS1JzS3r26xGelGeDqe uEMnmY6jvgtw5qw2Z+Hcns7ReykvW8Tudz7to+cJzTsPxqD/HDg9J8TO9S2Y4U1dIpjmntW+22Fi yf56V2j5hNqcA4K4lYnQ0M1y+F2HofN3XWMqd0z+OgWGTX5qI9EosIwpSBzKBBFrNWgt0RWsNIme S7W3hQgQZoMMDLrbq0Zms4paLwEOLICXX36JdIeH+z0zlv6pb/+TcvPoSs2Rbj2owAqDg+Tw+7MS NbQj5OpKZXuFwOMVF/thf+A10LZgVsJrhBWXxRvyoprmoDndWahVFzDpA1FIjMkKYsv6tzmZWE/Q 5ktioQrlY9GMbJG4T1P3YuFEIcigWvUZnjcIOghNLExgR0pk1BQ+0Ep0fNQ7aScInh0VgIJEsbg4 CYw3Ebww5sbRQgddpRrzD0/TIpPoihWPOc4m3a+lG2gan1JFMoO9zTs0i5wgMuEfFaDYCZm/yxT8 BB7XhRihHiTz0muYEkxKCOuIxRtNdRo8K8hqZhJf397I1fWV3tJkY9CCIkjTbZg2hp2vUEMt14+v pQ0rji8RrCCSm+bGZNiA+Q3tuCc1+xb0nLCaO5YWdq+BdDfqnm9usfqOc46AJfD73HHpefbcOa3S 34brhT2vtZmWu5xz3CbpQOpTIY3vbcF2CLiOjM0vmOPKuLRZBdnG/egODS+aBvY6ubgNA97u7DQr bRkrJNKrgYUAOEWl5H5hamZMDRS2GSBe/9ir8vE335Df/s3flV/+wq/Jd3z3Z2W3XdnhMO5PaDla NRrCAZlP8XN7FUm22iJwTu6e7eXZs6dyPB7k8ZNWAoK1O2ZDoOANYKqi0s9RSaY0GVWA4n+snwgB YGL4qDch9YthpdPNT8FgJgNjIwvJi1zWK8QYwvRa8XqA/BrjF0qWrOWYI797ypTQmp5FtRcIcgoq Y45pjiw1Ga0b3+aRUpeamrnwZJZorzO3e5CbmhlIqWSuogAIVHDbb70v+gezV71t0KxUJQflRD3D 6mCAE8NCAFrKC4KhX/kaktVIllmhqBEEqD3J985ppWZh2JGNPbm/zEdTwNbMOakkr+8p+KDQUo9C VSUB9qibiy+cR4UyTPe+f267OIbhNUOh41u4g+8cT+bSMdaExoJgLOQuxaGCj8DBcg/fWJu/upoD 5+/hb2N8nUbMgP8ID7fSkGAV+gT8AGhn9fJgmNO9z2NkCYCNqbgCU9F4p6iJROQ34XqU/VaBF0pb YFEgiFlBdXtTePyoWeBzAqKI9AeOowx63He1WbOW4bvfeEf+1v/xs/LO19+T7/3+7yJTHloSbFib dpbJ45DDC6YRFjdMmqiV/f1zefcbH8jH33ydrHp4x+JsRdBZ4hVDe5JkKw0KoAZIwRuSKgFSKfpZ nhREV7e9eg6tVqIudZPE0GoqlB+aAjkvUNwA3sO1Se0LIYdQHai8yIQRyzbYKfXDJO+zk5wVpBkb qKx5pqiBOYsCG41qsEpaNXsRBQ7wrVzaDECj0fgs3oBr6oacuDIvJAJwT00Rgk+FEHKZkchK4FOT EmoWVyxsk9vKJBREwj/NkgAXtCWr6q5HbY7aoqER0HsHj6NZTDA9jZeZ+f8Zh9oTLAf+hxnAWHdj Te+jOKqmKOqq3pid2pJfO9PPLhIw4dtCsmBrcrk7dQ85fzirRsJjuiT9JpwRPMM1OzrHL4jmtC8f SO/TctoRSO87lsyyZe2pt4LGZt45jU3PMTVOnVxglAWoIwBFh2tEfbjhBWbsQHhZW7LL4WTdkEZA 5YejMYF0l7OVb1g9hmxolGUHPyqi9oDnPO4ftFYfo+d7c5PtIwQQExlkPxI3tZQBUtD8u3/pp+S7 P/85+Sv/6X8p+4fn8oM/9Hl54xMfM8xlNR/W6x3bhhBpyTpXTGZ7tZVXX2vl61/9mrz51seoGVX5 UY5RJnGykV2cSn6CxrIi2z1eJVJEuRyPD3I4PfB5rnahbLZgjINjpRoOCYpIGx3GskH+d3JHwLAu ya0qipOOmalrZ4t9Qttq2p3si6f0/gHotsRMtctrCn7QKfDymLQQxFHQJuJMsmQlUYtitajBiFzz 4ElBuCC9D4q/5hJFuQSpmrw2E6qaULk0QSnH014yQcGOBNU/eH+tBoNylAGZ+PDG0cNa7DWTBitT 6yK0VXkwHjQHayWcwosL7XaVbNhXXIu00bYILcbsWDzQ00qvcpep1tFIRivcaklqWTkB0jZesD3q ZkB0FfigBoGTsU/Brtq+joFmOiUXDxsjit3y2aH9YktX09mCvVpqbRgk7cOt3M+7hdXxhKa54Jfw pfOL/jIsqp0RpPbvOa1lztQkxEEH0RB3dK+fiyl1U4ybK/guoLWXYB0kiRRwjpE5MLjzYJNY0gJN qfqpNLSsdoCatjOanUCzcrKibbaS0+nA7yG0DmaC56eTbLY7toGJDJUcuzKwBphH0OpoEhLXUtc6 xCFMrldfeyI/9hM/bBaAMc2A4YCEWqAOIdz78OQpV4mZFTAAUSKPX7mRMG7la2+/x0EDDnb76DnN lefpjWZToBm4Yv4s5floUHO2QnWcgAJMVlstzgoKRpASi8IiPBhNipiLoUXYDK34vaqOUsBVG2n8 Iqr7AHfZF884dqf2KLHRFOCRo1ek0fLsVJWh1UYZhV0SriVJt3IsD7KK1tB91F3PvOaVxBE01Fzy CoVmgcNpdAGFLID1OJBsAy4VlFD4EuEAqLVoKEJ2jMnHxR0i/hDcMsUvieehTYPTECSFjkb8LZKi LGWdXGmh2TrneDC9kMn0gWddJxsKOmatsAC4+ibM5jUWEDrBJ4cRxhYHleCo4y9whijOyYVruGuD Rfb/k/buv5Kl13XYrlOn3nXv7e7pnieHM+RwSA45kSWSlhhaUiQ5lhVFUmRbEOK8gAD5B/KTESTw D4mD/BAg8Q+J4x/iBEmUwLHjIJEcKIAFKJFEiSIpkRQpivJQIjV8DDk9/bqPepx6BWutvc/3nVNV t5tK2SN2961bderU9+1v77XXXmvnuUL2GhSIzINBdL3rEe8c79rPdHStCVPRYEmekRzeaLkixP9f /KlzhCrRLmvbr3MI9G82EFLAS0q3xRMF4XjIsBd72tcimKHoHoNT2SlsVIhuk14jZXJPUuIyYCXK fPND4g05uOsdI6oOuKkCAg/xKbeb4uiOs5BB3EQwwH/IXHpgshKLcSC/PgIENPMkLxPnYj5b2p3b t6yPWcBecMG8S8aNpNkwsc2RmThZtV+S0wML8IfvnLP2HQzRbVswoxuB0AjCZIU5xLkCVmdgwx4C I7Iv6WXxekjQxN916lT+BaBbEbr2dHNxA9HQrqIrNk79rrpveN+UggtTIYufHTkougIE182Ijh9I jwDNWeoMNPDLksr10svuyIb9E1vSSFZKD6Cc6CDYsJzE7+CeALhnyYfDgW7DWpFI22UqgrIcoz2l 7Ti36MPeaG6gQ8ouoWStd7lCB1j26wVL0+B04RGKo8DHKpt7Vgeqii92nyfUEsjXXHSd2guWrQmW 9CjtOAngWRMCFuWu3RCF748ZVG+Y6HVR+qPxoamF+HdttjZdoXlN+X6IzXl481+7x+rfPVbuHXoc y4Q6B+kVhwfNj5XZ172+Hoe5a9eXbOk1ccAtVjhcBS3Am3Ps3d7963l8NtnMsGgymT64/hMYjSxH Cz9utMoKnP7DcqILLbscRxFNYMssCLZhIX3MkZwe1EUlFTwoRsrWopxDKx4igZxbg3TMwD7woVft M7/9OXvfq++x5154waWaFdjk6qMuZuBAAJjxmUgdKAs7uzF1PhfUHBb2z//oDTs7u2mvfeBDdORd IjiVO/gIW1WBYFrYaDC1Xk/EWFAdyBWJzpvbTGE4m9iZK4yKROupsHeuxGVzY0jPpsCKJ+CcKWX6 9uSf0Gmj4ScwLho7RHotxVPOz/H1ZGaBUpHS0MXQKmxi/rv4adLfF8DJEo3dSBw0aZ4RWQU4Wjgg QFCV80+oUShbUOnksizhUOzW81F+QtaF/WMC8lo7yEBJqeisbbG50mFG3A6BLBjPCX9q7iVt/vg3 djA9O8J7gd4KQihJumiQuF4bDgcFLfw+7nn+orhWYIqBSebBTBmExOd238PGzjOYrCr5HgHwP+9j dzTo7b//oTL02LU+LpAeCiZyulaeiYfUSwRzDGuNfxwkohHlBmc5nnbsOtsPBqwYxM2DlYhdar9H 2oxhZGYAsK7HOpYWMfRT/OfBUC2t1wMxUvU9glF48ClL29piPmMwC9a8XHngFj20H/gYyKRfsk/+ 5mfs4nJmH/jQ++zGzalMNsnz8lEg/q4rRvgXxhEZl3N+9ODSlgCeqTUu+gEkWTa7BeWKYcuOLt+i 2lDVoYSkDVrkXjZIQE/zfWQ30QlIG5a+wr6hWWoVpYidBQwm1i4TA9WEJUthdAbJk4IGerHlUDZK TQQG4lEwVgV+1I1Zwp0HQGBMXaSPDKRcGjvhOBhp2GxkkArr2C6lVoRxbV3hlIRZpORu3knVVBx2 JOR6VsGyEQFZJFWKA+J7Dssykm2VbVERA5k3kjFONHlH2Uv3nQdl2cxvbbmZKQvqSAGDI0DhwsNV mfwi25sD95H+h+u5LaCwwUwy8BJXzEADYAc9Mz8UvSqs3aGJ6amh0S/RFFGnN5VOETTbmNqTBp9m 2/5JRmAOPfcYKP+4QNjZa1I8edB8UkztyG+TwIyKj9+VH9qsKjBW5iz1zmObKoenA/avK2gN3m1B 2p+DnnjyYDjmoie5EicYFj+ssjiXpsWW8mEFqu6oTN1Ff1OUe+h0sUQBnwmCe9BUH6J751mTg5d4 v2eevWM/+uMft9/+zU/b53//i3b/3gN75dV326sffJlkwSEiNstQtzfnos+6HwikK4yPAEQubTqd WL83tHfu3uPoBwICMxWWQsiUlgTQt5ueTYYgpMZIECnyXsqI/4X/qO4JugMWPu4VMDSXMuEmg4U7 ROXIKq9YNrLsQvCG+zCzHrzuI1uHc1DpjiFQc6AuWMWg1AcPi36NuPPAiQTq68vXTB00vwrYbu3m tkXGFCxjv/8MNhYSzj0OOnd3feJatEQrSmWBOLxAjQ/WNq5RYULdQYw0MevBAedOP97dFPgs1Qit KWfR79Y2X19w3fSKPmf+UPpybRCPw8KWDE6NdQU7Hh1U5FWgYLA0RSYl3qCuDkYYLjUTNucUJ9Pv hv0OXqXi4YNrEHaXb55DAetJcKZ8I+ZDvccwpMZrus7aIW5YXjq2cafdAWuzQ8E250ceC2pP0vU7 9DkIX6ACI5SHuU1lUMykIjE5YBabB+N2t1L/njiI7WuO9y5jY4oXJYwinlwrKODL3natvxv5ICx4 Tx1bF2gZC9th5jWArjvAes0i4pIxeItBWvK2YN/OsR19urD54owhMLC+t8s7Zj/0iY/a+1592X73 d37PPvn/ftr+6A+/Yr/4b/28fefb37UPvPY+u/lU1wYufZK6FNKmQlWEkvDpZ56ij+E33/wOB4eH w6n9hR/4sAv0eZu8QMaIE76y5Wpjw614PQGqSzBQJEmUvsggsPHArMSXxvuEsgLZ3xbKl8KMNLws VQd0EjFfx8vs4rOOSAgFyrNeXCpIbVe8xwh+DBTgZwEoB2ZWUyaAB9QAkEpTBH9ghBQj9IVK+WRv 4TMD1CwiMcPNivgYiJ1w7e6yvAbZNfheYrwhs1lv5263JawRGaFwIwWJWCMcVoYbEcaM0B0FrQJN lG7ogOH1FmBS2aqU2J7ikTJOZLeY1UTnEUFagRj3r8+Ba0wpgOrBwO7cPTYLHEvE+sQaRBOopne4 fA3uGdYsr7EeEzqEXe2XKI/rFDY2MwPj/pBy/vfm74Z09aFsovnahwJLp8bO9ku9x3UrDwWRJp54 HEuKDiFs8Yj1smpS1ZW/3/H3OXxNes8ECRzLOEssCt28JTtDXBDuNQFAlyQ/fP9QtMQm6G/tavPA +sWEqg044WjqkEVJnjHoCExhA6aZNIDc4EbFFzCEvTvVTMHeFi8KmzVOBgQVMN5/+Mc+bldXC/vV //Of2X/7X/+S/cEXvmx/89/46/ZTP/cT9szzT6dFi3KJtXPBxUs/w8XKLi7P7fz8nJnJnTvPsbUN cx4C1JgKhDkFzDDQ0u9Wdjk/J0BbevaFmwHyJH6+Wq6sGIxsvQEILHwLNCcwz8ltCo1vBy0VmKV+ QUxwVVlVzK2gs7ECGkrbXX/C+yy+kTAeR+jZqd2UkOzBvGF8gZjvW9u9e+/YeDxmWj4vC7pjb6uZ 9QfIgqX6ymFgn2PUrKGG26H3hQDHEp0BSFtHMcuJkNyIMhphnuWlpAKOdL4g9wNFC143SmdkTI5H IsvRe0P6RkoUWFvIwoKEzKBM+Z0rG9sN6/dCtUE5FDquek35BtBtGlkWOYBO+OQ1CXesSaD++/i+ +90JU4DHdbjaGE574+5vRB3wUeLm1KVjgSNlkM7fOkIoTRjfoZ/t6p8dKyEPXXv8WxC3IzNsBoe2 JM1+gMF6WK43zM6hbpvczh+vy3Xd/b7+oZ+Xq61wFiyG6BjSINOQpUhlk9Io25VV25l1N9h8AkFr XCq/qVxkHZsx65LZAjqFGJDG3ycnJwxUFfhF/QGD3Qo/B3APzk+/z+5dQc4XTC6gS4Vh7NJuPHVq /+l/8R/Z3/3P/hv7vo++ZncwX+Y3lac5QMBKgny4tt5gZ6dnaNc/Z2cnt+z5595j33jzG1YOOjY6 Ka03VBaCYITXB3hdbedWoq1Je+yOLVdD626UVY1GktDBNdHleNOleUa/NBv1urYpwNtacgPiFQID JPG0j8+5IFgMfGtABj70t8yKoXCmIKnycwBURscRwbMDjDAB2/jv4uLCfvM3f8tu376tAE21Tcez gB0tpb6A/3/n6Tu8v5PpyN7zyrutw1lHANgoOycyua2/QjUYQLRE6Vh15sT9gpiJsupkdEL6BRVT Ic9MigaE9JAxOTEWWeNmbcvlTKa7TjlApgYHIwQt4F94L2Bb2rwHQG+OL0EacGy7YmZdkGV9M5FA y2kC0DFwWCGjCoPYnpXstirrz9fpoZKrvSmPbbTobiYMLNuA6YXqoJEsy+of7ZV67c3bfK/2v3Ua 175fVu1LvLSD2X4DIQQN2p6SIZGTxtDwnKsKhxNUTfYD6nWPQyD7k9z7/N9LpNqd7qBOraNFCQ5T Z6TTWaAaZs+8E8e5MfxNp1xTq1njGpD9GIzGzofSiArBcLQ5wV0CautfHsdeej0GSIkHuta5GTOx H/2JT7CUI8drKT0p6kzNFrxOYFyf/tTn7Pc/8wWWlj/9c3/ZPvjBV1milGVlnd7CHp4/sIuLyl54 /gUav+5KkD+1abe9NTc0HpBN2WDkoz+wkl8gskCB9chIBiAfUm55aEVvYKs1cKGOrbdQBxUTfsUS DO47qbRmxxR+itQBQhmI7uHURr0zliwr6JKzA6YHuSzA1yBRQ4E9nc4SUtRihtHH7dtP2RtvfNVm s5lNphMGkfPzC7t5dmbVqrKn7ty0b7z5Tbs4v7Dn3vW0Pf38LZaBIqmqo9ne0LGYVIKqoUKdLYzB YH6zhJwPMjRo4C9pDkuC7W5lq+rCM0q8DnTxsUZg2IESscfXQ3mL/8gHy9yamWUT22tuVkoWwr6+ nplEdiI1ik5nwc+BYBfjRDo2cQj09jZhc0NoM+YwyKHSa//Pwg9rDliLsNl+fhtrOriv8/etM53D XcjOY8T84j0PYVXHficFh4Qh7Qd0ZVeoikZ9eGl6WUt+XHRh90u5Q6/V/vmxz9B+fsl2PTXGXaqX 2U1pk+HEpUiQskewgpKoB6layaFdowsLA54AmV10vggYl86pcuwKwWTtuBCCEzuGHuxk2y7cFK9/ dnZip6cTBinIybzy/pftn/yv/9RGv/JrPvBrdnbzzD72gx+xL33hy/a1r/6ZvfDcc3bj5inBb+A7 k/FNm46fsvOLc/vOd96i686Np05sOHVXlS6uBUoU6kTyVOxBcgcKBcLpOEjtLj1IBsL2DM4/yzWU QzEvOLRRryAzm+UkN4w6seowAjP0UolcrS5pIvgeKsg5rxfe7UKXDDIt6B9AAQFf1sCVInY2Go3s 9ddfZ4YF38cHDx4wu8Iw+Hy+sNV6Y9PpyE5OJnbvxjt2dXVJOZ5ev1RWtNtY3+cDOQxONKJ5MhPM higeIPaOMCbymhDoPLgQyO4MrNoubAd1V5pirAmyA+dD0IeCRfD10KmDtr66dW354n22eB4klL3F qS93FSrQFsC1VH7HAHiUhIc2Ttqg/MkTd8vapdN1Tz9Wmh0r1RSE9zfooec+Fk87EJwOZWDpd9TV TZ+vOHC/inq8BsGqV2r6JA5QuckdZ9IfA/efJODmj3LYnfCkAp+HIO6uS2UDgrUYJ4F0LufCRJRk hOU4jDpEPEFDTd0/NN4Im4hSJhxcVJ3LKf+tdKAAxLOOjk4TiZEK4+pIaWA6Zs/AmEWbdDod28/8 a3/F3nrrLrMriH1ho7740vP24rvfZX/4xT8SLoQ6u5pzjAcdsNPTUxv2J3w+Nne12tloOrDhFFmR Yxb8fMDgfOAWuFhWqtUbhlpPPm1OPR+VVMsVOifYLn1phxlMHAZJOgZ0Bf+MInNCl0olDukQVlL4 T/cAHLGldQZdW2Fom3QQKIBWdnk547W89NJL/KwnJyf2zDPPOH+qw8wKRpQIasN+abefum2Lam5W rKzo82giWx2wPootzuYRr2uWGCxpOJiNJgLMS0UXibIGEtR5JoaMht/Vam3DHpzBI7B5x4hUif6B LMrbo0fA2XxjZUvd5zZFSMyeVL9WCkiHM4Y8SDYDWfPPx4LM/kZs4kqP24CNf6Pqq8i5orZd73Kz a7zecTrFdRlM8xGdzuQClD67niFZmI71S+xLZ8O33vq6oNVWHW28+2PKxDrDwumu02rpKpHQ8B6I XFjznAAO6MZ0vEQMm6sAV8MxRy8O/AbDwgJjg20c+jcyEnDKg88balRHQCBHMBC10b3Du4bFkxs0 gKf1g+7nB5E3EQgLe/jg3O7dvW+3f+QplkvUdALIO+jbcDBlABwOh3bn9h0GWnys2QycLEmYkBhL Oy9v2Tszuv7icH0kgmgTxugCQ1RX5hKVewviXmKDI8ug2EpvaqsNLMbUh6P8zHYBUVaX9XV+V5AZ waVybgsXEZjlu7ldzi/t/sNHVD595pmnPXstWU7HaE6vKjk7uev2bFhC0XTMTHO5viSZk+MzmGVc VTawseSUeR3NE540hU6f+lssu0g4BT6n563WMw/aGGwXb4zd0S5mIU8yM4gEIkfJLwuuvK1/fRfp +r3mShb6zXoDBt503Ya+LkBe9zgW4PY/w6EsqNm6rz9rdAsODB5f/+g89lofjy/pdfRcjdJZaMY5 BENjk16Gd+Yk48dd4fdAobjuAfqT5t6g1w3XG24ajV8s7ZIbpWEq4PpYYbKZL0hPRJOOFcd4wMCO f1dQQ3nINwcDnuqDwLXEktUUvRQBCPQ5XUFSJ12NZ1DPSTIo8vwTWxtjM9DVOp1OrFeCEwXFCcz0 DW00hBLogFgPjCtgnPrw/L49/O5DG58Cw4NlPHAhbXw86u4HpIsh3YoOFXGYRC2IjYF2/2Z3hYlC 63b71FynMgJaeOs1MyFKuEBpAnwmWHxAEZQnFQZ5xWViKx7ZDn4v7q2l0sx6lQ2wNgu7AAAgAElE QVSmHRuUobrg7fqsc0RRRmjtd0tpZnt2iMAEnAkie/oeMV4Dztiqng+NUp8LFl0gdthiCHlFTpRi KLC6SnOevmao9tAprT+YiCirWfxswaZsIufv1Xv1e1jPen4OdKWsSq+XZ1mHT/50esdzmu/xZBvs cOYUj2DRt8ff8vdvZngJmD9ENdjtiQPuv9aTlKh7QczfLv83XDo4fdCew0VhzTWuOV3d3nW2r+lx mNV1pW3+KMEPUsa0s+1K9Wh3iOFXYBIATuLTNF8MwSa6itL5RkorXgm6VVKEnNVmA1bBrt0JiBzh AMbhrXH/luICq6qidXvcYMnRuFYXTn140/l1IEsADoZgde8dGVIMRyPOFa4XUlIIHA2b6umnn7G3 3vq2Pbh7zy6uzm02v7T5orCbdyYkyuJS5lcXKfvjnKOPxnCYE8YNo6zzgxPIrAJZlITRlXUwLN1d Ea9BN6xaeIZY9GwAxnpnzW4kAX+3pyLvKnz1RP4ijQABZrlcJGZ/3+zkbGj9oi9TWKd14Lsj1EzL epXRvWJnCwyjdhC0SittaCUJqTp0gClCaodjOhtwppK1OxeW87i0oiQpXWyFPYFTpUAt/lm9IMlq xyiMMKWUPUXJEf8b6yoBzMc22bG/t4PWsefGoXroeYewqQgWKUMKA7maNdXYVBo12v8ACgxNZYO8 RM2vJeFOCS9qf5bOXjCI1/reSqzjwcOnxX2/gWuFigGrCV1wwQFNGZ+Q4GgG2sOP9F6hXfa4rG// OssHF99iSo/TE5UJlAJQdiEIYOExKPjcVjwkRyNKQPy91iwHzwe0h+UylYFe7hETg5EosoyYdfMR mKpaUNt7PJlQ8kRt65C54FElY99S2QOCCcpBLBaQU7/+p1+1v/93/0c7OzvlrGGI42mwXtK5+Y24 f/+BdcqtPf/up6lfj64TykjykVw0L8w4NGqi9Bj/jkBBRYLBqfULOMlsWG6BLY+BYAZxD0QYw0F2 B7ASJxUIdjC5wIA0WNzxZQi8xDXrPaI8BC1kC1cd10dHeUkNLDwH/TlYhBXQKAOdAuMncLy+wWyS myUE8NBFI+gNeZ0R70Nv0LcuiLI7dHIr2yILc/ej9vwrM1xABghSIPtyXEdNBQDv1HqH2ihyRyiD Umrn2ILl37JN+Hj+0P7vp9c8BmqnDESbWxy/wzIy+jP/b3Z96X2o34YmCOXDhc3FIzhN+5lbBMDo RCbZlWOP/HcTJWJf1BAP/fvhTC1+nj/aWF37mjkD63OAa1B81vgeOzZEs6xurvGVGgFK93nfh7L9 3unPrS7wNdlhO6hS0x1fBAmUPZDzKlvMwBpWRwoPDDGuKfKmTldaBPmb+nAtNvZGpVjO/I12KJQU Ou4MDYAf2QOtr5hdiHhIrXhkKpQ0UdCUPZUwGpwAs9k5NyV0owBEP3qETGlhf/s/+VsGWS6CzJ3C JuMTm47hVZhuzp07T9vZjRNbbC5tvj63xeKq/jkFBUmvkNa9CKm+cNxvUY/KFqsLctPg3yg+kgwu 2FVFkwCZRlnYulgwy0N5xjKMrtMaD4pgpWxrYzu4Q7sgHa4B3K3gMHEciOMyvDNSt1AkI2i+WqDJ IFVVWm2x0yraRUzvofQbjqbW20rCuLpcseRFxlRVD62sBnY6vePZcrpnwerHL+FwQWmMMpXNiJ3K P7z2spqxxDWqqh7OfnJCZLxsGwxvB6383yMQHFvk2jgx5pEcWY5t/GPXqTzLJaSB3+2WTA7QNUYz 5Rgu1AwKOah/nLh6OBinYHjssTuAnzXv0/57Hfq9+sDwMna+Au0F0AMOpPxeZ5lRhls/rtRrfqft Iff0GQ8dQPnrlOPRDTLQ0dEiYAq7q03HFrMrm5ye6QVdhC+6ae0bEy/I9BhZgRtPUOvKLd3xW2Eb JteWjl1ePFLHMUwZAKqDhQ3tqwXKSY3aSMlBs2RUCfVZv+hYoQQajwZ2cjohlQLyNmSOYxynN7HR 8LRx3RyGZvnUsS7Y2ShfF3NlfmwqeIIRg9xdbW4E9FAFwINaUNHTBfiI7BGie1uM+YDRrtZ/v482 fmKTc/yEhMaCAQ+ZCXIWvmWMGyGXQtVMKZqta1mVGs7mADGeq9+JDDbGrOAtiE4dqBzBZ4u1hvcG kA4qALq4u+7aKu9Y4ntBNoqylwoHzoLXEotDx63KmD1CDRYGt+JTQTsM9AdgeBBtI5k0KzEf9zh0 0u5nD00Avb0Gs1eLLdN4/qGMTXiMz0iGeKUfyiTN+rrGd4BvFM8lkZaZ+/XYUT6+1CzhrudSRdai 8imVkZ0j2VT7fh1+pGDfvmf5684o5LtlN5ADzAdxL5+GiMV1JLu6/nqe7DmNkhAUhmJYWgU8BAYS 4MwAZK125GSB0BkQQDol3EElKxPrNwXO4pwSAepORA2tpmJE5jsxG6gQku4Q7fI0AC2p5XSqx4ZR Oxva8aJFCH/DLNmaksCc5aPbjTwEJ5NTZmL5ogXgDfAYAYd8qlJBETSCmkrBz6FgRkxIglC1eURY tFPXyhUH6hreaQlies8JXHfRtXNeWY0/QK6GyplJLTNWNPEqDg/jdaWSEC3vKHUwSsXSEQ0KJ+CC DoKAs6wWNuiDd9XFOHOWLWkAm0GvmFunK+VY4oo8NLrSCaM5rgvgRBbkXCrcK5I+XfJY2vH6Xoq+ 1gtgBNXjeOSaa7ERm5v30ObZX7ghC7Pf9dsPivs/j/fYyzZQ4JJyon+nOKCPFCmI4bTSNePoBWaH zJbBuZa8vm6jiWh6rPt3KGgpy47Plazcjj3yYH44wMTz+H8PvgY4lou19i0AdoymHSor63tdfw3N 7Ei0IMlPS5b6+DUfwxOPfbcliYsoV3w4F6cmNupouLZHs7s2pr1TaQO0rjk9r9EXMORXtfJijkfk 3YP0YKZF5xmTfhbeC1pZpD+E0acckUmtoGsyNnK6wbFR69renaavrmZ27537dnI6tdMz2UChKkGm BpxGLfT8pshUlZZfTrtgVudD3By/CYt3BkgoVbh7TUfXx74dumSYvyQ24ngOMiqYrqLsWxNlsu0o 1AywwT0QOWWizl6zE6uRBXDm0BsUOXsEiqO4fp/P46/HsDrmHlfAtFYK1ilzFw6GjAgLqdvhnKLI sFJbIE+Ks6T+XRJT8++YY0mS2AkcE5cpF+2dxm0owYPM1IHjLLZQcoaikDhA9L0KND8cqFIAa2cl EbRiQe8v7Cd9kDFPySFBEPo32tkewLfyTE2dW97HAyNFzQZD05vvMFB+IAjX//f6EniX3adjz9lv dKgRzVDoGmGQyAZsMejCUEUg+3XvWYsEZZWX4Bu8jkQOwN875MD9532UPL19FIbyMFSdxOmqhc6J bHaYlAVti5UtN9DXFsgGQmcAf3VUxwfyoBJgfPyc+u+c7law4k3x00SloQDcyMzy1B7XwszLvcqk zNClr+H9dx7Ye1952aaTiZxgqOipxacxmfQQfJ/IoREAaW7hHDBJz8hIAnOEyChk+9VllghFTZxE G5ZQaChAFBDlI8qiHgPGYn5FFU9+Yex2xheL6/bhXxfDy511hSO45ZoTM0l58I1BdX1kMO4pqJEq yRgziGzBq+u5eQSGFX2QKqrXOtOCmgTKQ89evOzA5+agdGSSLGci2IY8izIliusBv4OY3w6mH2PH ITFQrqaCJF7CZANSQjHSlWdNkYk0pybikY/P6Ge6E+l3Dz+Ol4z6fd5LkKYpM+2Z34GueP1n6qD1 yeTnOuKtaZewWKvBZ0pzhMe5YM3Po73QxPyOP3ZZ1/FY5pZndvp0CFbSsgqPAVEXMMw/IMi+H6wa 9/m6cyGUdbG2IcfU0bC/h+5rfvHAp2t1NkVaIDdKIHvQ9LFBx0PYvoP3JCC9dknZA/N4i1UKuZuy 38qMZawbg1JOwdFlhmOAWvmvUwekRkrhuk5+U7GoNM8mtx9RIlbLtS3nlT3/wnMsDwWYqyupAJq3 vJDmS6khTulGhwqbk0rQChjgMAGTw7AyLehXEK8DraGUHAzLRtoDuikCSLGuf48Sm0B5mUrawMco cAeN/PAEdJXQIFf6RAEbH7FxvdOEvA06W+m5W44VIdD0+sCVSo7d4CG5nrDKYo+s/szR+dViUDcX gRBNWgGt2mySAEJZqu9Nv+/tbWYjoQFW8Rp7XKAKZipjgxAZQ+qxufJB3fYYTayvaIHn2FOe8RwC 51NGeXAT+ByshHTUSOIwu3dmm+s6NovKYxKCSdvQPsgpCGlDx2vEtVzTxeR0hWfO9fX5O+ell9/t TvY6NbfRff54rsTPG+VWcAX1H7rVyKuxRvBt4JtF9dTvY/83A8Wh6457jHsmCKtZfgoiwJ5dGQAa 4X1p0P06Em/+WocOolJBKtir+QcEMA3/v8p2vQ1nA5FtoKWPMkcZR1NcP1xT8Eb4YpFNqRbv8M/o BgIQx5/DmBNZA790l8/l6A7NWkHYhN29UlO6tSwWDBQE4Wn6AAWJpT18+NAuLq7sAx98VUiPi8xF 4ItuJR5YolCewOfKRwVU/iRNML0OygQx0EMHKjI2KA1obMWdQgoph1abmYL7DgzzUxv3zqgRJW6L aBoCdWXtxWyRFAjH/rwMY8mF7AclIZsReC8ppSFdJ2hP+RlRL8jUd3M/ZE1dNgqcfAupZoL+Wkja FLFZUzBhqQwssARVAtlvWki8fwwe0Z73hoqXsgT7lwvNKMKajeaxuC7MFfbJ9KesTMvYoDZByQJU yqxyKkDaeCmjSCVylI2pk7W/8WJD4H6vDdcqU+A8KNXBgIekVw8oArZouACzkkBhRBZ9l/sUATY7 sgyxfT0KNAoyxI0ijPutQPaTQpf+rUs+nWZYI3REkIIuHXhT8ekhRAJFhTxbBGVmvtZBjJ/jEoBv CkfO7OcOlKf5Zwtf0rhP+c/jYjn1QPl1iCfO+DzNzIZ16v7jWCczfxCQaGR6GVA4HA1tO19bBTAb C88Z6oig7NjBVMJB0BzMDF0iEEeBoQSoPIDXHmRrhiOC0CUt1eW4XK01y4gPc3n5yCYTjNJo2Bav CyAYA7wA6FfzpQ36I2Zrjy4u7GtvfMO+9qd/Zn/jF3+GWdlmjVzAp//ZIEgFIResXw/LFpoziF0e JSc+vtj9O1sh6FFPfWOD4sSKLmSNuyKJYpbOW+jKhLRwwBnD62Hj4jpjmDuwDmQk4L0xsIPDxKHp Huc1lZrjRaHaCk9DLSaEUG6WLkibqYzl+tjKVoyEWpQgOyiVgoeF70JBA56Qu1pPHi36ylbbWb3h QhIFeKJKZt8QHsTrBVovJGSjOJvleMSS2mc4qVBr7tkISzC4YYN7RsJb4vA0DkgPVm2LqQhYyXx3 f7avDajnAW3/lKY8YS3gGI2QtNdQTsPEAxMU2NwL7xIio5L6Q3yL+ftEaz6uLbLG4/iP2XKzs9XO bASitTepIuP2uiM+oALFzmxOLxIcE/6+G33mkk0ARXAcJOeVYom6k45dFghkhU3hENW6LY8Dvw+B 9/qMzedERggjFZLGcSgwiwMbIHE3D73245oueJQpPY1TKqXdOKVHg45V1VysaqsIYkNmpD7IMNTr YyXxpsigsFFAMYiHFBEkrod5RP0bgHVwqxCspIip7taQixsYULEULwu0AzyQofGerLa2Xe/sm1// tt397jv2yvtesaefedoHdc22SwQbuRrr/NIDgSLwMbonU/oGWYvr13uWIW/BvoPM0MmCON6WI0xw H274ALpkL3lSZeFgLAVOWDrQxAOuO5jFYvYpORreA2wAOlmvpL1OaoKP53QxRrOw3XZMXadBf8LO 3AIa5dAxh8P0dmHD8YTTAMy0KD+8s10pjI8eycjiImvg5kO3BR5xKvfoDh0LkDr3S4kG8qWiXIsN lBYTO4YQPyRNA+WitL21kTZSaEVgDQC3Po3zzEPAe2A4ycWpCUznwerwIy9LmhlV/Roch0JmpU5y /pwIVOS3kaYhaaEdhtcJPYTnZF6FZF1sbw4lYL2piZVf98blhfFZx6SaBF0E2HHqOkZAredZbUcH KkeJ62uQ2QiuUccRNgCp16rX4nIdD8W+ywX8mtdbP7l9d/f0t/KglpfyqfFGrA9+mgT3QQlRdtX+ Xo59r3kAq7uE+QW0v/w1aQLRLcldTjrcYCDQiULgA9FODgUADTNVZFKs0XFqeNYClx28FA0xmQ2t SZZkCbldshzEaA1OBhIxqWSpr0iCgqIZCFvZUu/p6Wdu2xv//Gu2nC9pqAphPXSidCohYG1yiLXG xXJbrDANBQaFawgLM+jOc5FuALZC1UBntLqHBRnBUhfXoiYJl6exmglxW7GPkcrLt0P3jXeSw8DS z8JrYMPj1Oz3JJSI4AiS6RbpNYXq1OFjFlVMbdeX8Srvv3Mk+Z3452FjIrqSXmqobIeszYBigyi3 yf/ygIlDZVleyl/RdeRrHCRjXxPnq8m1mBDo8rtqZLHuJMTh6bykiKVeL/521tXMYNJz2ye9GjA6 bJucr3awWu28DMwOML2jiLiwZJNGlzp//A7592bJGNeSb9Qcd2s/71B2gisYuC5/cNvyrDDPKCPf 2mUZYTM79AAWexnBK8uE6+sNJdNG8MkB/+OD3O2Mtf6dRhc4+93Wd4kDNbT+j2Wd12VWrQyrXbOG Y2ul0RAqDmAiXxlJSL54oU2ddmYcdRDA/F1P5SDHOFwf3Wt7nPLIXjhAC513UCo8LWfrnCqlCwUd VwSNgMXFROgl8cAwewgcSwHOdb/dr0+YpIPYbLdqzCiaCOHoI6kbWauzTHXwP3hDlOrF8wrwddSR A4BIyRkXjGO2gg6d9YnXAPOQ7Q5u1ZYuNN3gT7kFWEIv9C2Q19PFRevfibew5d6xaoMSVvcXWufD cspSkM/j62lj5kA0A5FjQTBhRQIGLCRHNyKNp/4ZuHfAzLbI+IDXKDjWeuh1EBH+psMHo0Yd23Y2 tiuk9poCUzRh0kKnfZzbl+XZlK6j3fPPge98Y+xaz293tfZxGDyIvSIQuPiksiZlT/KYDPM1fc5o MrSvp7npUsZzGPvJcCTqm3nm1AE1JVmfKfhE8DsmtLdr4sZ1sMjA+r3fqn85cQUbgad9rS2a0tFS LTU9DpV1T1LiPe7RDm5lqjtDNTDdXy4qEB6Rqu8Kq9YzW1ULabjjV+BYggKIlvXCHrTJzYajsd8g vwnO9F5XkErW+D/5GtTzhjyykxKdRErymrv2kLcFKgQCGMDtZUU1ibtv37cvfO4P7Zvf+LY9/65n KV6HbAHfAuYMYf0UNwtdLMz5LTYzqWPCJp7s9LxNn1JeZlsFNjhKSNAwkOnohGJ3r1ZnLaimCYQz 2P0IInB9hh4UmgRx4oBZTyYbrgWkVc/5SCXpekbhJhpbB4RJB3DwH5uNTZCN2XRyk4oImGvDA8GC B4DJNFYNgsDigj2vBQAFiSLIkkH0c4UMcu76Y3Z4UE57z8fLNvcepAyzvtdwEOJkJEZXYqPlmY7T MNhgCdzN+W6x+XNW9z5oHpsjsoxMbC7Dufw3mlvKiZcs8aFaivcrYnIDmT0+i2tqZe8TZVnzkTqW e5ypayVWVCojfqMUJDSQDUznEsqHNumhz9apg0n+76lSageQ/DolBdQO8Imgeii+tINPXvq1QnRj 3Or4Z/nzPUrJHIfxpljs4vOCTT4k0EceVgfuw5jsr+TkC+CvI1eXGoQNeyn/BHRPqdnokqSRcmfP 1iVa4HJxEa6FbEcZD70HY7CTYK603ZG1wYQA83IIKG+99R37vc983i6vruznfuyvumkE8B0e+65t hcxCADmCFYIWKRLMvsBFkCkCby4zAi1cqFFIHgZ4nLpp9eci8TSMXdWJJK7HkxsbQpuW5zeDVTCa 8HsIVgtylwIbwabhzGHFBrO7Q/u8JUmw6PIpQGDjI0MZjWRkG9kudeOhYMrNt99iZ8DzLVfR0DbG eTQ6hQcGo2ECgSC+xKgOgrpzrzQMrhGrlBXhnoizI79EXCuMIuARgGxNyC/6hJhV5Lwq7L4gld0q 9erPSnebtPiD9Arsrl5L2ebJh25j80Z52KQXuPGt34xGJuCM9rzcydv7KaM5jvHknyUvSWng4d6I K9BGGCdBLnbcyV87DsD8vZtt/nRP4priPVLQT9d8qOmw35xoB5Pm58uzuHYzI/69/dmjPL+uvDyE Xz1pFlZCRI7YCYiH5BWl0qye3N74mM2usEExtVH3lKFuuTm3xWpGEui2xi2gB1+xQ5jfVGU+VpMz oXsORQcMKWNxI5sr4cIDNQQC7AogeF/8nED4CkD+nEHIlju7eevEbtw6s2VV0T0GmQ7fa6fhbaie duEms4X5g4xN+WVj5g8BmB00kRlx3exoodNWd36UNRYYCt8u3ZNPGYn0xzus3ABgB4ewqmBjtbbt YMOyLYxMV7Q0w0gHrkF4FbtnTtSFPI4yXIn1FXDlKUGKPed74fMgBIbX4Xx5YYNyolGq2PAdzToy C2Ipkyb9A7TFjJgaKj3rbJTJ4h+QEY76J2Ty87OCEAqS7wAqqAD+mWdKlLDeTMGd8mCe4VfIcJdz /Z4NMClhtgEGhwySSrVReDU3Cju0GeFY68fnJGsxxRSkhNUpO2hiOs2NlG+OdP3NsirbUtnv6aCI z3mse5YHqcC68WfIsyC1gv45pIVZlkPgsWXgUL/eY0qoHb9HBLd21zapJhwqy5r/djjzye/NfnYU AS6jAV1LQ0gB/hg+tV/mP758LCFLoswCpcxQmy/UEZjKajCWJzSBX4euSRLs2Hh0YtV6LjcUBDdg UugSIpMaQsYkYVe6MCk5XF48tNnlJctL8nZ8+Jna7yd9e/s732LQHEJ6gdjYymazhzadnsgZZ2v2 7HPP2E//9E/aZz71efvs7/yBfeh9r7HLuEQWOIRIfpIBERcLgUrMcJRwVJQgI1tAs0QJpRDBwBd2 VvBL5BAyNrH03slfY1m8JXWBzkBLmLHqpFx3Kxv0RqINgFu2A6yLdrJKwLC2j5JFAU9ZWN0ta6wH lS+U/0GWhffrQbEUVIfUBI/NLPWMxG8S+9oxE1I9lM12tz2zlYa2cU38nDx4ZDTCrBDLg40RjRcR tM1KuzrrpOIEMmlYpg3oziMD1K3NZhc2Gk2d2nB8ESfLqFjUgVc27akSWJ9rke8Hq3g0aCAZVCGc LU1r5Pc7BanYgIcDVHuDg+80W8khe9rv2oBOP9JN0/e4X+pGcIyyPWWL2fvtHGuk0kk7KDUzqfb9 bWZXadKgscIOCPzFtexBi7GqGvOx8W+BgzXf+0kC0+OCW8kuFfXS0c51802czFzvutgS+uvIGgA4 d9ZkyZLHs4brjEZEFJBUTlEaebViljUaT/lJ176ZCUIjAK1WdnJ6gzhTlA/Eh7YbLurhcGTzq6t6 zg8n8xivhdYv3Gc80/nGm2/ZN998y1566Tm7uID/IGSMgVfIEYbZRmiJQ/cJpRgrHKTjUeAA/F9S q4o8JO9OkrtCT3ZfQAxQXh4y4/DOILIj31AIAhw56pYktWLjw3Krw3tYWLnrw86RIn7AoPCQSgKW oSgY3OTk5QRdAtQElMZDZjwcPVptqPIw3MqZSKVHeEI629H3GXlXqxU3ENnqfckdQ9NdfozA3CZ8 OjI3/NcbyDNRmmKgUIBL5XLZx2b/6hIKDLs+Mypmy1uzCbTzu3LRkcFhcJeKgws275IpziC4hLlv ZFQZ+F7jSHnwiIxMaznHemKzhepHAOapY5leM6dhtDdcnmmg1F6s1Pjpl+AxAs5P1ygH7RiPEqZV Y5xxA1uBo34fbyZ1XKEkmho18TZWciubbAeLlAXtB7lDgaX57TbHphrXlz3/UMB5HJbVzujapX88 ynI3MHaceROaLFSCsB6I9GdAtU5pgEmmy2yAY6QTVx+gR7XQrs1cuRNjPzTwJOVhY/OZykVavPfA derZain3ZDHv/YajY8huEsoqyJdo85JQui5st9pRZXS5ntt73/+Sjc9GTL+vFpc2r2bW6RfkjZU7 2UChmwnAm0Eo060WkFzy57T2grGGB1YqSlCRoGf9Dko86HwhzQ/rMx/6LUobDGNT63cFcGMIeWub AtQ5bGTIu6h9bmsFzRIu0uRmPaIQXwyTolMaYLu6cWK/4/1gSU/lUGxozyDofO1dznxB4mfIDIGh dHqQb46MSEoTcJ4hM73uXuIAMVI6aM8F2WOop8KZ2UHbaI1niyW2TG26QZcdUFdopqudGp25uiXu 8EN6rYSV0OrMvRgTubTZnaszE89W2pulXksN6k5sBGCriQQZr5mntjmGRLVrNaDT/KCz3THugk8F bArrC5xFNE4wrlE7+XiGlagE2vg13pYRL9vBQAd0x8exkqz0kwaGFAAic9LFHwpU7SwrdQ4jQ83v b7s0bb7nISztWMka73UsWOFR3r98aJPRCZpUhp4T89XWxfAUck11yaFUtqE0imcDgY/474DOQPcW WHi5Ww6pAsgUKnXnMPPGuUJscH8/ZFnIcqgDT3UEbT7qoZNBL+0snPaj3qktFws7GU9tfjWz3/yN T9HC6qWXX+DpxeHjZUGpZQ74EvhG8IR6QwrLAka1aHiTasA2dc/Myzlg9CDREmNiYNK3hz+HO3FS MNgoq4EUCXkoOJGQuQJzGtmOUwIdEj0325jJis3kc2sMznKkofYU8CN3KSJeSL0tx33wPfmC4ufh IHQQF3GwQOQPZTKyT5973IDDBRMKyS8D/xoMJu7GvGGZ2ONAvPwEVcLqvjXVMPEvosriORgMX69g 34aMFQcRLjDmKH0+0d3FIzj7Ut1b5OnADCOLtOkTfnY9wLy/eeNP+D78O2ZF0SwZ82wE3T3m3GjI sKkIyMBnZ7HmEaiobI17jT2CII2DTTMy+N3oMfJb832lzxuHy/7Uif5XN6uIe1WXvjmR87Akcva3 RoZ5qFw79PcmzpeXjPp7+/E4/C291uEAl671cJArzy/v8oYCy9gNVM6FrvlgyhEAACAASURBVHfr UlyCoqLtlLAs5/JgA8ChBtkG5GJcqRTBRzdThqBQGg2HaXCqkF3Fu2CzY7A554ckygFGRgJMVpai dv/aXn7vi3b/4YfsK3/8hv3up36fdl/9ft82SxBShSPQSabsy1UaC4nmnoG9ANjHtSubi64NFxFv EnMicnSiM8hxFGBgHXgtYjNDfsZ1s+pgKEItuoFK1TyoMNPA+6RMErlSKl0ULLGxR4OpGF47GGmM GWxDBkUUCKmgciG53HSoLiiDVFnEbAjBCvIxNakQAWrkWJqumBLKPZi6Dm0LXHK5s3LowYqdQDUo JI0MAmvaPAxXpHH0wEjjHKjmRJURsMvrDYGaOOqZB8H6RimjxUlyLWG4yFjVpeTnauEmxx7XPUcH OgJJfNeHQXi8K9jpUo6Gc5SeB8UNRKmAT7AuJL+k74/hmUobgMn1wqC2CAZsZpRxre1OXH6tncx0 9nEl1uFHsyQ+hFkdv1fX0zbS5bRfo91YOfScQ++XvUL2WcsduFXLC1sXEyvWpXXXKxu44UE8sHAg doeO4BLzZ8WGA7kMJD7kCYsrbHxlMb06O9AbBhgsdnSUg1wnPG1d0oWyys49on08MivJIsciD1Ln fP4O//eF9zxrg0mfZMw3/+ybzO7w0pgBVPDZsITtAVcCPjVHhqQSkCl4bVcmY43YwBEQWF5tNQuF 56Ec27izjWgTyh6TI7FIospyUhaAUk8WV8A1BpSsQemlkYq+2QYKFCIxMsDQGgwNB2WUYWJKC7EC AWykTp9nUCidagAZN2qTbXwGSY3PKDhhQ2GMSKTcJrqv0h+fbzkTZ46Eb3aSRXXAs0e9k6x80/cL 3KrXRVkKWKAgf44Nhp7kitDUqTcnCa2+2OuCT4tFeA8QNvkegmtGSkKe+WgOO8sUDi777H+bmE2d tbnLdjwH3dqrqyuW0Dj48PPlCnO0XZsMBwz8cbfoT4AmAdYouHXbBQ8Kjfi4HJFXEMiiEaw47xel qsv2RJaZwPMUUNJmjX/TfzEjePyRf96ULabvaz8Dzcuw/fduE0nT1Eu7jG5cRat5kGNz7fduxBzn IHoRXL9+Kautyob9oa07K5utlpIncW4NMA2oc17MhRVRW2kDprq6iTgu2HSDNvwGxqYLYR/cI1hk KgFU2olqcHl5QaBa1IDIzoxOy8QtHOiUWSOAWwn/yS0a7fIrDmSjuwi7LmQyAO4nk4k4Nk5JkMMy FhMUOOdsHuCmMBgiqtVYmWdH+cnl9w5Z1RKAPLObtW26GEjusTOI4OXLoM42mTGh0+ZEXEqRdLu0 CIv1qMC9op48shd8UMkJl7UlPVVE1x2x2QGS152ijizEYBUOz0Bgaa7plbhRCbNQiRpYl0oLZcUZ 9lMbJLi/Hyok8MK20IhHDbTxwWwExpVY/3Gja4keBR0MvTLDRkm/2bFRwpIJ/C4GnZRp8o5xv6as Wn+UfjrGaGJDB3YWmy2Ace2ZtDH3u2WBY+WdrhwniY2iDOLq6tzeeOMNu3//vt24eYP/Npsv7GQy slu3nqJFnByM0pA/jUUgf8BLBW2D+kT1dAf/c0giLqbd2UuLrlkOpXL58MY+/ojPdthN+1AJeezR zsTy62u8Yxiq1FzMwKRSkHyS6w8SMvY1BTPZXdfvlKc3btns4sK26GjtKmZSM4KrKACWdrUE1+rS Hp3fk3b6ZGqbypUud4krpaFKyOv6/B8wGnoSZqMNbF5BTbQv9YeNTqegCZBGAbfoTkE6w2A04t+B hbEdTlsvZFs7G09P+PoXFw95mr/rxeftN379f7NqgXGigpyq7rarucQN1FOvbDSZ2oASIdi8ymQS tUAnJnAnZVa6bpA2gdtxWBXdx26fQWRcnhJTAgl0tn7IzwOGeOg/gQhLsB0FH8sGnURySC5ZlsJK jYEMWQlssyAKiAIE17XD/ZCENAibWii6t8DCyu6QGAqHuz2bK2Ef7vpYTEK2GGcS/geQnoTcjUtM xxRA0B98kTM76o7k/hOHJ+WhZYCKzBjBOzqTnPNsALcFpViofNEdSg8/O4lFi0iYSF3ieNjXiBRX ghOYJT0Up229gdwfk0KOrm6aRAEfp+gQjPomFQJ/hiLI/fv37Fvf/ra9ffdtZln46eVoZG+++Q1b LGRpBhWNxQJmHF27deuWffRjH7XTm0OtYfLsgP2FOoEOx5xiEl3uJvF1PyDUnyFY5Z190LodBFIG 1M4oU6XTfG4zQD5pR+8QZqg/x2sHcz7zNW39TvPQ0O9i+H61nTumvLMeNOa8hC5hHLruwwdwaPM5 DBEureyPbd0d2squbNOBCL9OkshOgAuV6GC5eUQAzR0O5wY2JBecvDOD18D7kUEOTSzIkXg5oy+j 8M7VyqYnZ3KC4funDwS6wyoE7tZmn/qtL9iv/vKv2be+/Za9+O7nmRFeXclpZjw5IfdHCggYKwK9 wOf1HGRFaYtytpYYiVPbN09oaSGzGw0nNio1w4fAAzyp2l2xE4ifAzMbdKc2Kk8ZkCoQLrsYZO7b xfIhA59EzHq2K8R1WsGYtOhZD6A8S2OcxsK4OPYCbM8zzv2TLkQHxQ9bk3yqDIbYmhtfqjRBsKVJ GCPZcokGhzC7bAnxu0RHkEPFQwT2nvhj7H7h9aRoACwTeFXuB5Y2j0rxmGPMEos6jcI8HaRVUCIj u/RbbgNon0FWuh6oR+ACZopADmKsxAGFjbnMdK2Jf3yjpQDQNHXII0ncU8ofdUt79PCRnZ5iDY04 r4qD48aNG/yu7927Rxfxk5MTBrL3v/+Ddno6VaMDx6HPU9bkXWbNcYlNDKn9yIMQM5YOCKggU0MP C/sn6BbHs53mWhFmFvfsOieePEs6FAgfB+7n2W/qLl4/VxgZmPTlYi24hwIlfVKHsuQCHcKqHBpX clLh+MeqsMrAtYIrMDKVca0TPqABxM5KGKO6Vjm+RPxHbMiBVIDc2S3k/+XGgSKll2Eb2Fq5sgDH P9YAONHxUqmAD6Osp2ujCWbBtmwbY0F96Q++aH/61a/ba6+/av/Ov/eLdvPmGWfyUG6OJhPytQiU U9xOQ7ckRxoGfCFbI1XM/DQLq656M2w21JZCSQMziX5X3brwqQvFSnye5QqehCB3IrMYklbBwLW+ ss0SkjPA0dBYwLuB/SwfQGxcfFB2QemWI5qBANsIVK7+4CVN6GaBwxWNDJz6wpySokUQH6MCIVDM l1LmllQdIksRgI/PMBxOSfjkhIIBOpDszsoqUR1wYG1xD5OefH366jLrTqoyPh+QBwN87TI3cP4J CeayZ0uMaAWFjIRagdR4QelkImMLTMU3Yr3orytTgjnfzqwU0HEfwJebTKf26vtftRdffLE+uBCY wqFJmdXc3nzzTfvWt75tL730kn34wx+2Z599VgP9NVXgAEjtbxnYZl3WNrqcCcCOTqwUejFHqhlU dm1dDLEZMPLXSZ8/iRTmQaUpn5zfvzaW1cadokGUv2f+uun303hUfj3HHhurvBQMExDZ2OX3sgzm OcouShhjsxVDqlquWT4AINdcYXzxgVfhRuL34jSh8gFBeB6d3gVy6kCMuThAncxY5fPGysPbtzjh wrKKShAgN5J9rs2r0+/CPv97f0C5lx/+8R+097z3JZY5uJ5J/9T6g5EoEr4Yc27UktndQPOR9cye Kzbg5AL+5e/T745s1JtSMTPa9gh4tOfaLtREQNcSJTTGe9YzBbV+ySxKQPXaEHsg54J7JVeWirjG sDe2HgZil/IyBLi/4YhNHux9UQGvYnmKQe4lDVExnE7dqdppJ98s2QnrcBM3OQHjdNpSzbQe5/Hg SZ7WShlgucPJxoBF7JHBUUoaITdsjXIjH1BGdCwMoQ7rSR4BwLQwQ4n1FeM8Ev7jmmIl4d1NV78t C5VbEmVslyKhg4/DZ99WLAKSZFkOA88XFxf24MEjK3qwizux20/dlgA0Z2yTvAseo9GYzZ1nn33O bt68yb/jEA/Zl0ObOfsaW+Va3mFLD31P4vrVn7ODZtKChyAnE1JRsBeQ9oODDoUafHcj3Lg/+Fdk 0oc6eAmwz4P9/kVHRtz4Xp6wk6tDLkp6ZVbYA7Skyz4TAxaHXRdzt3kfqwNFbqV3yQiaa3RGvKPS u33KynCJogSI10tA0v39wu4dt0RBodm9gAgfTCSwacZjaE9h5AU6WRoJklQNsg6ZGsR13Lv7wO7e fYe8q/e87yUGJwqd9AH4w4ZdVIOOS+CENpQco5csPUFXCOZw3HBcO4IA2d/l2PoI3syqBHwTEN4s bbmZuZJD9LlcQwz8r+JKyqCcX8QY0YYuOvA1ZNJEfCYAcWRDaOsXZEpzfAYBkHOVIYWrwIAACQlm jkIhCA5Q3/v98fuP52ocKN17UR1CHSEtplTmCwvCYkMGgQeCKoIvAiTLVcrdhDVZyqDkqsNZkXoy grOfnM8EGVYCOiFmU4KX11XHrGZfOY8PmZbUUZl/1qqauPwYFsb1BIlLgnApgGEyoJ5eqDGyaAjs c4rSRtP/rlDSDwoq49IFnM0ZZP5J7hj3E1DHYHCLIHyegazXiVkfRMtoONXVYM31a2ZTbVwomhiQ FtrVAWZFDmAoYkT53f48zUCTPrOGvAVLsJpxHTaV3e6K5AEiDxL5AZCu8Vgp2/y9J32wUuuUbCiV hbIr6co1HduddyDrLdqZ9zBaIrtISfqm2l9Dv4m3gx8xkITlj5+U2GwxlwfQRCf41oqevjhq/3gN Prua2/27j/i7QFhwmp7fv9KSpRO1ov9us7Hlbs6OWX+AUR9pT8Gl+tH9mU0mY4Lck+mIwSKdPipZ oSqgoAZb942VsMByQwze6G3KEiCIB7/GfnfKDCu/YYLRwyKsiZ1IuUHyMcXGFwRPaGUn1G53oBVf hrqYuk/e/ZWOF/YjSLNOHVFJBWrJwq6qc5JXaScGvlm1tmHvlGVkTXit2eFSIeAh4ThjeqRFFQqU 6ji68B41tpR9M/D560lfX4A4A2O2QCGbgtet1ho7QRa3pbIqsBe9DwJinX151OOGYZa9sx2aLlpp bC7ITGttM1tK5WO3ILcZgnAsF1zrS4TU7ESPwEEE39dQox2vzcUME/DGcGxntzo2Gg5tOAC9JZVE mm90Ui7hhTRSFP8bjZEUgNIGrkUGkYFl40MBnTT3fk4eDZllZbtbBht0nnvN79Flj/S3pmxM/vLb CHrApH10TRYU3kDbu5a0hw4/9sH7VnfhsY+82dANio++nsTgyl1z6KThKgZYJMR8UEdu5T/H2E6t aeEPAqAhxSvHFyxo4j5eVuCXhGet3RPPpTP87WtJDR9cnV8tqBRKLGcJQL+ye3fVkTy7cUobegrW DXYEioEnTE9AqpzY6cmZffsbb9vnP/1le+1D7+fv9vvP2HDielCeXaRSpWNf/9M37Wt/8jV75tmn 7eVXXrbTM5AzPQNwYmqMjzStljxgsSvnCqY0kNDrc8NjszFrUaCgsw4yFpeIXa+Xti3H7PChA4gM jYPCpTLKGEEiFWLrUr1BS+DgcsVghZEdyEgTX8wYzHHSCk5KZYGy3mZGEwYTcWKqrI/yEPu8JA9s 1/WsJVLnWIyRCfjYFqWuCbSTWmm7omcrWpPBOkolYKgwJGMQhlRXhdW9JEcU86TU+SIRw9a7rS2g HIFsubO1PjJJqD8Y5K2Bg+E76zvnyRnk7W2TVTFq8mg2EcEK5XTR69vNm+DHOesnxw4jywj5oVap E0GfKiKNzajDGqq0zP5AVeFz43djvuZYWQiSBPh6i5o2U3BwXWq0orH6/cO955EfFJgA1lX/xvrm gbIFbDHl6/A5rL7R2VeZmSRi0jrKr+lw0ElmHo8D9Ov7Wat7pMH09vfVfq2yQr9+A5LcUF5lwC0w b0d9btmXV8u57JtcxwiqBPwi1hVLMLwVgHEsRmx4uNtE6chWeHYSadPoahRIkrsysjUEzClkjkHS 7JdWACjvAPQHaU/CfOC8IPuCS85nP/M5+9Ovfc1e/77XrNsb2GAk3hPxHnTuKCcj/Gs+X9o/+Pu/ ZF/8/Jftw69/0H7+F37aPvaJ75eONm+Y28H74gnvxTzNJSblJqyyJFMHFV1PLAp0MXEPsECF0XQZ yGBXT6E7BFH8DKRT6KF3VlQm7RXAoaA2WnDGENmizGLVGEB2BaFDdiPVPqFZx9n0thu+xl5qLhqV 4yCcZgd6Qysq4RJRIvJA2nRsMrzFTjGGrJWx4L5uKISnjaH3QWaFjQ9AgP/KLB4E3zUHzZGxi7KC Zs6K3yOGv+lchAElb7DIVDbkf6AHrrKQdF6A+yS+S/9+jiyvA4dizGbqWmLRK65sbRcCgRSW3Ijk 7GoKmP2jKQfHlToQ5Egrsy5tWpLLvvljDR/rfuVdPpTrq43ZgGJkoqWEyWxOxWhv7NrqDYcUnJiA AnZcVW1XAQUlAVlGsGgmoaUjLTsy6zdqltXlPzlwmvGUJVgcvNGJFe68AxxD6EUYbqz/Q/SJ7Irr IfLoXuY4WrvcbYPzse7aQTuy1Pw9y0XVtckA7PAOtZeWsysruiPb2sIuLh9YtVuydEIqzw2MEwh0 Bc75IXsAiOp+eVSoVOlI2RNnfRPkJRYm7o75JpfR5soGo65NpkMbTvo2ZFaBetpsMoFqp6Rl+sPC +gQ30f3Dad2h2/NsNrMXXnzWbj97wxbzOUF3cK0kc4INA8BWi/380QN7+7t37Rf+5r9qf/LG1+2z n/2cvevl56lWGotBpE2l3fQYzDEGqnSK98SMyjcXgygoGo7lAf/iWA68A2Hn1TEbliMbFBNhdJzz 69mwf2LdDUaNSjud3LGrxbn01YEdegDHiy5W53a+uEf9dZaMyGwRCIGF+Sxn8JcC00kgs1hMEaLy 6f6kGd5Mu1E6I9hAKLGiSWxqb3W26GAObbPWQud9IT2ksAFxw0TS7PVU/qkcVhBA6brpzAUeu7ty DNYrqMR8pEw9QKOIugYUEXRmadjBw7Rjy2XJpgAa0v1W50s+kMjoYB2HTvMWMmosj0F87iNQ1fOW +5Zc+X1Kig7NwHLs77GeFuvQ8o/yMDZ38P/25yfz1wKDXuUS2P7C8KrtXPeIkyQpw1Z2qjlRVjhu Upx9Ih0M+Hnd5HKXntovsC21k+7noWClAB+v3Aza+Zo6hmulf293epvUnTpgLR/NbXy7T5CaigUr 1PSVbbob6/Q7VlTSuBLtQMqJkRHJi09ES9X5EsXDn4GviMckwJ4nCUdWNG+In12eP7LtbmGT04FN T6CZbgw6o2mfcsfUw7LSVmRtwiyib4OhbKj+7Bt/Zl/+ypftpVfeZT/5Mz9qUGoZoJvUU7ePjQIH apHifudbb9vf+y//e3vttffaR/7iv2C37zxln/rk5+wf/L3/2X78X/4R+/gPf0SYy25jo/4pzVJb HGNPUVwWxT8XvxhsNpStPbDfB+ykkaRZuKMQNswOEwDj2p1HU/el7TaSfcZ3ArxsuRa+NxhINiZK gWFvZAsG+i6VWdGCxwJF1rWoLm3YmzLr0YGtTqf6DQooysBw/1skSuBwtTlq+qy7Ym2VnVtF4wad 1j2MJVF5wmy5uCKju9sfW7ffNzx7uXhoy+XcTkdPMaOkMStURx23pAnt5IRAPDMuz+DxwGsro8Vh AXKvLM6jE8mGAQJep2fDzpRrdF2o6VGC11etbJZ1OiFUyFlSdyDqutDhqMB7efe7bumHGUN0N2Mr xuZL/7bfoWw/su6kK7ySBI9gBdsrdILZHGhqxR/iOEnZdsXPzHGfTldKG25eq2CGta5uKrmPzHgX lPZB44Jztw6QqvrD2kVWChsuBMAlqQQqLUEsjsMrAvRh/CpvNvi/NLL7QzyuY6Vi6m42Qf0IYvmj 7HntzRHQWsZCJzGkiTk7xppWKSLb91DZ7PkFI1nF6eWpskwjVD/HIC6zBZ85pFiere384X2bV1sr R6fW7+sbpRnnfGXf+dZ37MbNExtPxzyl0TVEN1EbZWmzq4Xdvv0UeUwASZ+6/VTm0iL1hLqlbh17 61tv2//zzz5p1WppP/ITH7enn75lN26c2fRkan/4B39sv/PJT1u37NhHP/59fqp7gA07gkhXfeCb JxCCjHdCIyNBF5DZIYKSk2DX64XEDKEF5eMzGZxY87fVUcXIj/Ak4n++aAXySjsJ2BUCME1blwsb D6Y2X54z20LQKk2zlPxd3E/QPImF5OWOg8a1fVRsEMyELmwO3tiuYpdQiqQSb+TwLjNK8M1wWK0N vQ9cKS4XndOL+X1brq/sbPI0Gxfq7gr4r52MwLhxBdjgR3EG1QUXQxni0EaW+zJoJBjI1iD6xkC+ dRdjv8cA5ZFFDRD48H11k66+XHDSZsg7YE3MU/fw2KNd7qTrVNYIciz2F48Lr8kDI9r/nX2MB7SX MB+le3jHmyrEmVXJRG6j70+NIJSI6OaGO1CeMeFQG5YTJ2TKnVkD6MIEya+kTtv+OE478DQ5V02+ VnSM97li+9lWs7PaeKe9GdGyO1a3BUamyJZQw+KdltUVZ9wYBDDy4coJbF9jYZOPAwnfi3qUhmk9 YpR/yZHiBTUCmQdGZnBTrhZJsxxt/CVKjNXCHt1/ZI/un9vpySm7haokBWpTIbPs2uxybucPr+ze 3fv23bfu2nAwsldfe9ne94GX6ozu8uLKzh9d2De+/i370he+Yt/97tv2r/zsj9vL73mRONPZjYGd nJ3xtPvt3/g0Ry5IkMSmEeqaAlTWHq8lUJwVTu86tmRD2gXpu041SEtrg+4YLDe9TeKX4TTLtLnx DuyS9OHaLC9GriNXfMWhIFpGl5lKRTMPgLhbW67m7MZKlwtnqme/oG9g0dP5Ji2A6E5GNqwQKnPV +frSFusLp6UoU1XjRNQGfrc40bsQUuzZthjwYLOO/B7H/TNbLmf2aHvXzia3XSFVBqFAXfA5IE3E +UfHTpTt6IDgoDPHpjLguAb7883jWTQ7y4AaBEeE2B+zEsABxFScG8Hu7IENVJfH7uJ9QGtKmyqH 8puZQ7NLpswK937k2lUxWqJNis8vLGv/99P7cYNmzH4TM0zSQIANeOhI1qcOLhRI1PfLZldOvCT0 KS5hZDP8O70lMf+KDm3QMR4/opP8ElPXsw3Wt0vDQ/es/bPjWBmq/87ClquOraCtDmwAGxanA6y3 uJiB0yhdj4tExgCTU2ycBWb0XAkUxEe46+AEkEEpsqvo2GHTVnZxeWVlf0gAvwSnZw0wGaUbTC42 hibAjVs3OQN3/95Dvic4MWxBg8kwX9l8trD1amMf+OD77f79B/b1r71pDx4+sBs3Tu32MzepDf/l L/6xfeXLb9j5w3MGur/wkdfs+z/ymg1HE7lGg2vTGzF43b/3gEoPH519n41HKjc2LElCF0tjNH4D 6tMt5iRVgmYtbCcxkqvmWBSlo5lRiDgJUA1ZEu4P6RYhw+MaUIk5InmZbiEjiiiNNHwOLfgln8dz PEBPv845FGF3Syt2GLAWt4zAP7JkNzrd9krpX3WAuS1ssbqiKmuAoLgedoFXy3p0aIByGR5+GCaH 7A3IsABqd5KlXu1Qpl7JRbsqnGxasjQGbYaOwG5yG13jREdIuA0+IDqAXVx/jh8xm5eKRVh0bYoV s0IB6xId1MC0M+ZJydjfDDX9IxvYTY2h6AwHTpQrFDQfTXBew+bEew9sVAkTanQt37D5Bk4lVQpW VuNF6iSHMCDBdNITNHkRlU2ehaVZxBQ8KJOUq6kyk3+c8mh6dv0zXkL7njTLyXa2tl9SNt9vP2h5 AO9gAKdS5hPlG1+sKKgYCsBdLe+iZp5D+hh/voQksWsxoXMI0IST7FvgFZoVxFtys643tqjW5OgM p0MbdMXpms8uZdwA+/dNYYPR0M5u3OQiGU7AuEd3UjrgKEkvzqG60LXnnr9jf/0Xf5Y1+Ve/+if2 md/5ffuNX/9d++gPvW7TkxP77d/6jL39ne/ah15/1T72Qz9g73nPy7acz7mhBj0pCoDOAUwJGQI6 h3/ph3/QxpMRCZncCCgjmM2jDAk8KSSMcZqXjc4INhd/7sYWseCYxaxF76it4YMKAX0rdGSc1NqW vAXYCrMJdl830M73USlo3S/nVKEAb6zrrGBJ+shuraJV1xWH2juQD/JsJBgK7JjtVraEmaqD2TLq oOurn9j6X/4MpW3RtxFUYjFfSJ0sNBF2NDDp2UCjQiDLdgE4X7FjjGwc0wuQ6yzWUplFMKEENCkU nsO6QqvQJedY7QZuW5bZlbH0d76OfxB6Ke7QlfaNV/OR/HCpG0PJ8bneePXMaDM41M9ztc/4To6d /vFAsAJ+2FOS3NqowiuZdbZ05g8HidSR3OI6aXoiuzL5L2hNQneNpSDn8bZuXqsDMLIpTqnwMFRQ 53dOY9mMdvSY7KoZXPdB8UPZ0bGmwqE/H3q/RJvw4efZ7BEBSqaKlF1A2de1i/OHdvvOc85Q1yYE KL6YL6nasFgiCwPQDuxjw01JR2EEGB+8Rbt/PofVPU6AwibjkY3Q2KFulTSlwLJHENyu5jYcmPVH he26fZucgWUug0/xlMD52tpwXNj0dGjjKazbSxufDDic+sv/+6/avXvv2M1bNzm4+iM//nH7xA9/ lAoLo/7U+jZyJchwXd7ZBz/8HvvX/+2ft3/4P/0f9s7b9+z5dz3jAfpK2kZU2xSOgMzLu7/6otCu 94lWzJFB/C4yB0rRIMt0e3OURsQhQsTJwXpI7hDHKZpgZz4+QmecrfToEbRYdpal9bcDmy+uatNX UUgUkODSA/pADwuUTi2V2Tr0yADEo6zDCaWhXADoDD3kkIl+gMxPhFoHdXnqI8vyzYfsx4ev2YwB 6N+B9+TaOkNpCtPaDUEIztndri2uZjY9uUH8kYEEs4IAgWEdV+uWK6DRtZq6Ujrc8oZB2g2JuY+Q yayBWZfKSmVWTT5VHgriDzWH6kA9GMECFcehzdh+4Drxr+U1m1BZ1yS2vQAAIABJREFUVhBQm2VT BAP9W7MZ0vEST1wpLxM96+frUZixb6WNmFELtgAEoTnEng2tX8AcBYfnvhZaHL6x/vJMM+FzTXA8 J8u2S708Y3rcvx3LuvLnlvPFhc1nVyyPAOgWPXCFVISHMy82AwLVHCROMG06I3s0q6zoTbmgAUdR XndYMiPqD3q2dAUDZGGLNTYdZI3dJt1Lol2oCvR6NhyPbXZxziBZLc5puHCFU7vsWEGC5YrPG58i CGIvALTtW7/sshT8l37iX2Q29Z//nf/K3vjKG/Zzf+On7CMf+36qdkIsD50/wAgXs7v1F0PWsLsb X55f2fPPPUtlBYKRvjExX8VZQbEpJR2ChgSHk7tWoUTGUDDuZ0/tZwQflEUoqylHM5zKdxHZiLfR MctIezTO8mFovDmC0G5348TEQDIaFsyyAICTua82Nr0OkTFSOhl6VKUN2I2F+cTClptLZmADmxL/ WGwu7fL8gQ2HGuiWBpGyK2Yhm8IWK6hehLaYDjR8OPDG+v2pgbaqHSol2bVDBZuistPxLa4JlKoz 0ri2NhhCzQD68DC8RUmKDBd9YPw34r3F/dfo18YVS4UHNjlL+UYO4cKoofW96r7lmyttqgapNrPl iizsQIjxQi/FstR5S5kcvwvSSAT6N/GyfBPqeyWNw3XY8p/Fd6BfT9fUybC85BKtYIRALY2ywgYl NMgAEahRAmFBfP+UIrI1A5mCnHDEQ4Eh/qwglO6Jhu5bgb++J/uBph2ADnVDDz1vH/NytQYYQuAd sXkQjTl2gexg3WPLfW0TA0wC5RJ0eYY9fBFbW64BvAPUxbhA13bwyluZLfsTm5ZDG5VDu7x8aNXa bDwa2XgkrheHfyEKCFE8wwCyAHn62FXgfGE0YmSLJbKtkW2Kgc2qra0hh7Je27gv9UlcCzM/zhzq pHjuhefsP/yP/327eHjfbt24bYPxiYHvsC1Ku5xfULoX3anSTqyPlLnYEY8BZYDBZynlA+iQi/Oz Jh2hs61s0D1xO3NpYtXqBuF2zREUt7kHoF5giHssHIOE0Y2klOtMJbhCGEFSdsFAnn1RIQMSZQMC xaC7JVOZ2dZqYcPJWDN4KNfpJo17gUyjsN6ua0vOJ7oaAQa2VwuWlFioy2pGkHZVLl2P3uWoocRQ jOn0jZ9vOiv6SALL6tKKvrQlsCyMQIHCCLnoPjJAjCUtePiwvI2OrYs04vsaj9EpRAMG7fQVD0bg ZsA4AT9sC5QzUIEQepgA3VSCxMJvgrZptq79c5Vejjd6B1uMfGUmqdQ8ROIU+z+ytNTlbW68+Hcy 55FRs3fVzBqa+I2Y9vsbWU2rGMBXdzgvuzr+Wgo0OLgRIrGXEKBqIxJXRq0nF1yGO+Fa8b/pIZ5l zE4I31J3MpWliA8KlklH7rqSrh2E2l3Hdqf12O/Hz0q1nAXA9sZ9ZjTzxTmFzIbTsdkK8iJIsrFY MWoyYDrfHw9Yys2vLmsaBEY7tiuc3EtbjU5ts+vZiK+pIQJ57cm+Kl+IKCmxDmEYgRISQYslzmZj 1fyhmOIA73EaDc9sgo6Ua6IhkHFEaCDnZVz/ycmp7cohSY8dSjrjy8INLm3XG0rcr+hz9GQ8KsjJ +vDrH7B/8o9/xf7Nf/ev2bMvPGMFsobtqs7COGrjGxknP+t+SC0D8K3WNh6ccqOJrQ3pGGREfZst ruzq8pFNR2fuOiOZ4rpL4yoSgZ/k3xkW5eXVOUtsiAMSz0JA2XYZTKy/s75Bfx3dCLnrxCwy9dkL ZC0wqlXmBFkXZi7Qo4JBCJQRgF2SSymV2OjwwtINGe1yMVMJCtJAAdb6wKpd18aYCyw6toAPZIXT G6D3yspBx8rhhO8PHBMdQ2WQ0JSXoQVeE7glHhg1oh3cYGqD1YibaDI6tWF/qkn9ep+mTbNvMSX3 uNjQ0RipA1fmZRibFJ3uXMaiGejySJL4fPmXk5dBEaxoJuzZAEvlWvUV6y/NMEa21Z5GyTO+EEhs roed420+UE2lINjXpf2EUTCpS0CmCZnVvPa61C0MJZUm0RNVBFRacKjid3EgkjPpev1cE1mEVaVA v6aaDXAse2oHnkNA+6Fg1QxwXhJSmgQLciyNqeAO7XYSaMNiiwFebkJ0eSgl07NdH1mWiKO4ao7s bLE4O7ZaPmI0hjAgOVQuFUxbeh+ajgitL89Hf7A4QFIcDOuFRzljDErPHhEnWuNnMMOAg816a4Ny yFY+ZJMXFXS6JjYeTSgouN4s+HnQWEDGg9OhWsyIh9G0tejb2dmpff9HXrf/4b/7h7ZcaK5Ss3vI HnqiBdRYFD4P/Bh1AuEEg07WZHiTrOHV6qoGN5FNDvsjW2DTuzBZ+B3nrF5upqx1HTsFAeBqft86 y8JunD5jw/5EjGSUrHCm6eJeirQqrA1BWw41wE+U/SHQorSGJyIknbVJq92c3VIObK/Wtik3UoL1 QXaMZ0F+iiMf4QZkIBif2rAHgF+UC9zfKjYFsklil9ISQ0aGsg/4Fkar+L4LdKNBp5ADeLWa88BB p5myPWjA2IobDU7Uw96kMezbDCh59ywnbLpVlsve5EKSsdGZfWxXJN4iuKL056C1jz/hPg/6mExo druaG0jOOTwAaCYiQirmEesryTKQ6HzG7x7auIkqEB6MzcySDxcZYGBEo8d126S8ogYFPhvIvCgV Bbr6tEAdFFOGhbIbRF2A+XRS3MVEB5ouMe0RuCWy03YZ2+zu5Y8clzsUmB4PtqcsGQ8EUIHtURtD YA/uMmh5c5gYnT5v0/ophfReBhEdBSSP/IOh62ZBUvbikbIl6B651Esuk1z/3VNrmoUyIKg0xWbC o17YS9ier21x+cC63TsC+tcoXwa26w5sDXLpriQtAY0EvC9fG2WYV1qAfLCgVovKVstLW/dH1uuP bDyc2vPPP8dOJgawab1FW3VNyW8KsIqRlcl/UNpMAsE7u5WNBmOWliub1diYtlLBAEvvP593y7/g hktzu1PELo46P+tFZaPhCYOl5rsEUvd3mP+E5AhhaymA4mTG9wJQN0ZaUCDiukonoyLIDsa8HpSJ K8824vtFAOH86LYj7XpKIiOzngoT7CCzurDZ4pwkUc6ycfOgs6pNhqDEbK6LbhboDn0C+7jHeA2U gJC3hrckKS74XBj32nVtMZsxyG/GaysmXRuGKGTmP3hs0dfy0PxMaR4zx5yUFaG/DHHFmdRkR9Pa 0RxlMzYwGiL83hR1nIPnygt4dgeTBi51Q9MVZVZhxyVL+CbxNMfT0t9bn6fxC+l5u1BFqekN4grm T42sSeKSmD8Urqd4JSUP+k/Sqwn3AjObCFgo1YXVKrty1/NWeR0jRfHvB674YODJP+/jHtc1Nkry hIDfAFNa960/GtqomLDEQOo+xMLGPFsliVaWjwhEw6H0gmgMIQ0jnND4O36+PX8gob8tZpowi4ig xaEA99PL0kRPt+uRFDojqzOEhQxVAnC84J/ILG5+ZR1v5VPPG7weP0VOJxOfS5PZK7EUlC/Avoo0 D7lezW0DBYDhGU/ym2dP2YsvvmB//EdftZOzid159inbdlEWrq3YSjStt0HKDPAc+FkJwQVbdSDi 59IxUA7A52RpJaCcozQI4hhjien4Voq8/wXJIizu6bpaWrWa2XozFW2BpUDJFH67AQFVm08zxwp+ 2DTAU2JGD+oomKWL7g9wOLkRQQNL2W8MH6O7qcFlfH8rK7bYvENmHJi/W6BRs7qwR1d32XnCZ0bQ 4dBHrZiA03nHEoXjNDgcYCuGGT4Y52KNrNR+H49ORJDcKuhuqwubzy/taneuIN3pWz/Thj+uEZ5l KT6eleudNZ+f1CtQMoPVj3USfYTNptJn54EZVIg6XPAw4Jylq6KOUBVkMtsxphLfdYNGwRc5NOwr HJSNjkx3PspWi797ksY1FNcWeypUGWqbN80JihumLi9Aepfk8LsQChCCDIjbEstM7umJwrCvSPEk j+uoEu3HoWytBt2Bf3QH0OhGelxZuYUTc2mnZzftwjo8DVE24Oca53CXYfrTyQYeCx42RupMaHwD b4aghrKQoHTceGc21yal1F7St4APxYVJOWO592AxSNIOtlcjzjrh9J/2e0pbcdphvABpMLhHOLFR rroUsNjiIq5S6gVXQKF7cI6gg6ls7umnn7Wf+Ms/Yr/yy/+33Xn6lt2+c6uWKhHYrCQanxufT5id ygpI5ipYDxjM8L+4bnTjkFnEgte8pQOzwFUoabwfrKgI4XLEILhSmprUjpVtS/G7qI+kwS9Jl/hm In5V75s09oL3A/UjFGaj9CBXjmU4eFGiruA/NjWgFMqxKzROoBFW2Hozt/OruzLqCOqAl/gigapT xUDBYUaZ1+Ig6sOAgwfQnGM81t3y80EqSE48JUUKy93QOuu5rZZLm83PxcManrqlWvgHpHKwJkK6 4GPMkkbWnjZ/fq9xQEJRdmK9yZibmK8IcUFAF+yuLq3bGaYGCI1SFQArdM43Kxsia99A9G3FjKtt 8lDjVllZFf8en6MZ2JpwgbrT9eKwOOgbgcMPe5WoWJ/6bFh/qqC822/g4+FwrzzrcrcqL+HlBo5A XfFw4bxh1sxoSsBE4D3Mxco/y583YKWPl167pI716SkDCzfxdm1DLCw0mkcTLtzNnNU5cRLSADoL WWWBbR2T9ZzVCu0s6WPjbVEykkND/zt0G2F4ES1ZzC0FkVGGENHORS0uRQe3ZN9u7PzRQ5ao05NT mVV4axfZociYHXvn3rft5s2n5TZdnyAalykcCI6Nicgl/8QOGe9/6Uc/YZ/85Kft0aMrm19VNhyh 3AVYvbYeNjgHSnE9csBG6hyjEvxcMKegi7JLDyPzrG3EgriIoS0Em8PpNDIlpPPki7nmOssyMu8V IFkmkjVfyWbN5w0dpqhJmAR8vWNEs1iCs+oaln0MmA/Jjw5l1GhZo2PIMR9EfF67nLw3m7ktVheU hpHTNXAxZY0RlPmpfLRJ6pzA8rx8dtAXpQqwLDwHEACCPKRSkNXMLi6pI4/Be7zu7OrcqsXSVtO5 TUc3mHFp84T5SdrYwMt4R4M9D76ZK2jkGzyVN5hFPWWQJd62RdcbHVMJMWLkCeU/ynqZdWjMar6C mxSoQHIwKsoJsVxiwRQ8jFlWL9GohRlCdeJgcf3VHb+8m5iQfP7ds8rQ+OLDm1W5iGAdEOqsSnOZ shdz2RkC7ronnGINDJV/w+f3KYfIPvlEP4T8mbkKSK6BFY9m+dfUFMufc4hsel1Ai6eXYHkD81ls Zpy0l9xu12bLC77AcCRfOSxQYBEoJVROQOOpT2oDf45siOVEZbPZJbt3N24+5WCfYyPucIKMIS6Q 4y1UroT55iCB8u4ejUwLXSRs/vFkQqwB9zI05i+vHhKoHU9P+T547nx4YaOOukzRGYqMiO8NjKcz 5qBwbHEwt2+c3LZP/KWP26c++WmbjMfUigeJls2C3YpGsoPu2PodEO8k84FgFjdUaqxh+ClBOvFx kjRJu1vV/iKDpFm4GWz0aOBkg8wNQRMnIMYwEGQQPMHBgtRFl9yxWIyF23VBiqRJSlXDw+VckBmV 2JCYNBDfDbGHkjkIvghc1K9aWOXUCVin8ZBaI+NSN6nOeICRVGsddMgK3aAdwD4Y+XT3wXdcFDY5 ObXR4IRihbPLC343uCsnpzf5vc8vZ5SUtpOtvfPw2/ZojrnRCU9/qsL2x+omehaL7q/0yGJ4PRb7 /umf/7v4SQrmXOdwUiJsUDE4B6sC3+ccc5zAdksEJ8zgLkmSRmBj6e2vi++PB66XaOri5S5S+QZP 2V9Oxkx4V2Lnd1rCd8mdp5mNYf0l+AWu5R7MvdRLc5ziE/Jzw5EHtQyzM2Wnh2gZMaqUcMFmsIru vzjHGonKP/d1ncLj2dUu+RLiQylQaDHjgZmvQVfZUR798Vx02+ZL2GZBwE8OODwxXFnx6uLcbpw9 JbdlV2rgiet0BpR0SO9BWB2N0TECY7q0XekcH3TxSneX9sHnCjpX0OWCaaXP3oHlTQ4ZgH/ymNAw ANYRtaCfAswAhUXEKQz5E7jhxAM/x6L96Ee/n6M+v/u7n7VdsbUf/rEfZLDEhkPptNzObUVTVDdM 5UyYXK4D7BWYKYAfj3ATCqmbSNPbYmfcPBQHhCYWKBSY+0OFtbU+umUop2odbi0YBRjNkTHFZ0mJ E1XBs9hiCLhPUivLRwoIbmyD8pArQiYg9TyYlxe8rl3H+piD3GzscjG3IdQoXFZIahRLUk2kgCAs lEPObteEg1AWazpp4ztCZj7fzRQ80SjY6v3YCOhLkgcEVHSbB9MRA+R4dOoAeUXD34sZypah3Tx5 liKGdPTxkkWLPlQXmkaibUIpXu9q+YBBH/eSnWpCHBse4LZ7YN0pDmnIM0f5hc2ITARZPKR+ZnRI kn6af05xo30eM7mCB9kz3j++xzRYHdemAzBwxXamsgvFjayrrK/T/x+laNC4itEiVAYiNYOaA74c FVvr/ycNOPk0+MLY8zAUny1096+3sM9Z67LpPpZBNUvo9lB0U+iwxIgNme4DdINEbSD1jZthYzuy t9HtAieGgJB0kYoeB1wJZrs7Ldrr2txbG52AYY7gIkY3NvdsfcFFEB0U0iig/Y4t3jVbwjW6Bztz BbagF1itPeWnF1NucK4g61LyxNNYws4mE0kei66hshVpergNU3MK5WpPpVoAtepU9uy5Z95tP/lX /4r901/+v2gh9gMfe91ObpxwA5bIYsKQAIsRGM3OeOpjfCcQ27RJVZaQJ+WzhfoM0LTSwZCfXvxs IbPP8louRiyXvfwWJSIWutuQDYa8FmAuBccx4LUoHXUowpLpvpolTpATJjGMjnm0MJMVMbYrm7Ty 1EbjUx4uWxJSd1bxdDaqcxJQp88kSLeOb7i4YGB/bDggiIGfh84juH7OZMd3j8/EzHyLZsuQxrlL zKnC96z0cSeYiiAO0/wWGYuy9Oh+qqunkSmRn1W6RXOhfX/bA7mU8imVlW27UinBaBKwNdzbi/MH zDZOp09xIJ4SP2WfmRUrBoj0La70eeDITS0y6qh6ZuHphZd5Kp096wqXI9WMEVvqznkerA4Fg6Ix d1p/qLqiCbyLZTF4hz7Aj6y830XQmnuGpTVHoxLcYxzCpLK0sbgUpHJli1ivKbDlRhXNkvdQsMqz q+Zz9mETXikzAYDlkQVgc/kgM0cyEFU9LWUW4bN9XISLpfX6PpZAOeUFRy+wAKUqIEwHJxbBd2Ik ErFDyk2ahJs3qLzASAaykorBTGCnghvb9P4xsJm18dGd0nOI99AiLPuwPnzMDQdqBA1Y17bDYZN1 KyOKg0z6yntfsZdefrd96Ytfst/5rc/aR3/o++z27dvEdZBJhTSKvvghu4wAOMOKnFkPwU+yRur3 R0tfAnw5LhAnvcs5M1uBRdjOdl3cFwXmOKFry3P/HXxHypyQmQGfq6yL0gsBlhXallMDyCAU6N1I 0wfdgf9hcJndTd/QPLgwogVpZsgjw4G6A23xLacG8BwOwDuAH9mTvkdABcM0I1kbiEo8MBx3iDFC RsdHjHCPaDeHALlbM3gBciAQD5JrCXrDKQ1AFutLcs14HdXMSruwbhfijsOstGpupBg0zkFgHYQI QGOSnMHYx4Eq2k7p2fqFXc7uExqBpySx0A5K0L4twbmjoqnknoFxS9kD3WRt/MRSd4ke//zawKnU lAJTniHGuHVzA+88LQ5RzAC26985xmuijljQQ/T+7Hb73GXAEbqWfXXVnO/GTNxHSvfjZdPoNw7x YyVfKnvz8alkT5d/VwxYOP3Zkg43WJ7yBYmJ/KIRZNhZEAExunESWis1tLztc7EhqwHtYDw+YSAB sTDa6pFJYdOjFAMXa3Z5qRsZMi0YhQEeg7dmt15fQsgRR7bE4Ii2O8BhSM/AJgv1OMXmwrpK1xil LF1n4PwMbtEQvoGQXMHLqyNHT8a+sJlRf2wf/OAH7K233rLf+/Tn6Yj9s3/tpwzEa97IrZdLAIuR BZQTZlHCCxL+EKCkNN9l16RFh+kCZY3xUOcVRFVROXB/iKV4qa6NLj4XsDmk88z6IB6I4UqXwUGZ Vm4HtqMztTYox5e40NQUCWY9SzYo8IXELT0o/TOUMH4Qz4q4JrXu8dweR3DAk6KhrTvzEpsEnuNw Aq6rAqetxju0umUUgZIctBQI8amZEU0RfAfUxi/A7MfnB8CvQ4ztdwZtZYIqJ434F0p6BDjROpq6 9gnjyWYOM0yIBwu60bsN5+xgt7bD/Cs8KQdTWy4g56xOKstf4DwwMiVXVkRn4H+6kVKu6G7DaQjv 02t59rmMNQeQ3S3IqQgRmNI1Njc3HlEepo18mEibf/48c0t0hzCscJ6Zr22UxNEg2I9/8e/HuVf5 4xC143vpGLYfGC0Wy5xES90hLNDdFhpOcjcJDEKkTnFVcOpvNksFAXZkIF6vL0SzZF1KlKj2hHQr 2NYYI0B5CdUEMas1nQ9pYzkLayZOdAVgVlSIAKMdJQ5OYuBtK4mT0dgULXmSRuW4omDlpq3haOzy IcgIwQeiDAwyvO3SlpAzDrY/sx+QGPv2/lffT7rCr/3ar9snf+sz9v7XXrEPf/h163kZyxS7nFKF AdiFMtDQInd1VeJAohdg4zHrJPCvzJJGFD5gTs17iCdyHk3lLbMxbIwsXdb4DVjjc5VUJOFurLMJ zXkoN0AXqscsi0J7yMJ8ppCONG4JhoAInl3odqnz12W3jBlrAT9FBTQEI2A2/c6QRqdb2qFpXIcd MCeLMnvmvKgrL/i1y4BXZaC2VTRi1BElsRQl5mhgPY5Z6XdYYvWhsLogVhRO2wjaKOVANr1cnBOE j7EiJbq5TErSoAo1i3wzCZPT2h8OptZZaGYUnpTr/taKjRNnCQkoa0DA4ncPNRFX3SUWSGrBytYs tX3tISh7ly9koIljeraLIJhcbXRQM3NqbPh6ezaA8FZ4aASHNnYXf43ucRw0QXGJ5lQ82r9/WJ7n ePBqg/XHs6wIzE08Lr1v+p2SQnA81aPs8K5eFxIlYHyDUV4lI1VyeqQFPl/M+eV0QAh0Lg5SebKd nUGvReJGrMiSBpqxmy9mzMQwSxYncEhmUDMeNXSUga4fhM7VYrlgaYeskIzdlTozZLCDpNofMKDR OINqBr4ocR0bnOxDw8A3yie06FfVmkA85hjnS3QXlR2enT5lH/vYX7ThZGD/yy/9I/vHv/Qr9uLf erfdvHmD19lnpqihaZVy7lwT8tImioYaBijTYFOvMgFkS+BK1KwfTKh3xYaBky7lyIOyUwPnIf+s L06ZGL5lZIoKaqVtEcRdMgSZKr4pbqQtGhx41SGzvIpGIZKVoQY4grf7J5LOAIUHHxCmblUJy7eN LQAsbwt6IHa2sLFHhoasxOV03NyTWOZOzQ0K94F8uobax4JY2/zyiic4sj4GOsyRQp6nD9nkpVMc pBjC8pcBGQdPz6o5tLsW1FPDtVLZfD2nqwyEGXEIIstW3HBuFr8bBQDBCMpUMVjc7hbigfuBeUmt R6i4DmyxXdhqveXw/cq1u0TtwmfT4VBRkgddUYhYbm1TSlIIB3dFtVhlYghqMSMoKGBN4rM8Epw0 zErhWCDoeJl1WGUhx4La3dE8CASWlgbx3RsQB2StgLFPbA5MOSgZ+f1rv290MiMZCC245Bje+AQe /PTa8TptbKvEFD4sz2v9IZyyxCnAdJ9bt99lRsCTvh9ljvS5T6Y3aEbA9rhLGGP+BRuyD9F8iADO L5lq42cYUKaAb1naEPbs4P5w4Yapg/AmGmLQqkvXgA2EMhInL7CFojMkkEuhOArpqZxABoYMbgKV BnfeUbqLmyq+EIIdgwsDtGSb6Wc4HNijq7cZ7SfjGwJje0N73/tesV/4xZ+3v/0f/B27e/eunZ5i REZZWPi6YRMgQNYnhJc+xJa8FqeUDBb1bm6bYgkkxpZXc7uaPbI7t15ihhCmFgGEM9NskR7Bk1ms Lm2xvLTp4KYWEUm8CUdc2sx6/RMSOFUFaUiVxMoNrO7NdqstRQCpzIEA4xkMOnWUfllrwBxzgJiX w2GxWlZWdO7arZNn0a6x8/mlLTnl4Pd4DTuujl08uLKH9+9rgWL8Z7nUWsLgNIH3QTKo6JiNhmM7 mdyg4gMwqihNSMItBrZb73xguqJMysnipvUxmL2C+sSchOLFYm0PHjxUFsfpBnclrzNKZd6BVeYA fJ5V4PpwoIW5Cr672Xxm5f/X2Zv9WJZm1337zlMMmVmZlTV3d1WP7G6aFmkR1kSTFEUZFgRbkGHD pAW9+MEwDD/4P/CrAb/Qg2TJAyTLBiQINilTgCZblilZIimKUlPdLVlsdhe7uqpryIyMiBt3vtf4 rfXtc869cSOr6CsVOzMy7nTO9+1v77XXXmu6dJc0sxgOg/VSeFq763E1YVmU5zR3ukNl4Fn2S+xR /gmdylna2bYPI8liJ1O/oYDaxN14ZOczA1798KFJVaJ9cCRw5e9zHaZToJyiTtp41D6YTcDfQboi 4O5okBGgS7OrkQUmPuckw4c17wdNyF+gHh+qEemmxr5/KsOZIh66F7DMUjcfx6l0qyKI9odF8E5E Qy44J7nLG36fmzYYjW375aupN0ddgAs9nV/HbDF1R283IN7pVK2AWgDlAae4VQ6SciDSaHTianqh D8sC57gjkCpSI2+zmEUbRm+xoDc50soTo8GoBDQv/iyzNi1nIcwgtne0wd1yzeaChn5lAw9+MrJg f+ck7p/fjxcfvxgffXgRr7++jsnZucuRAtorC1RKkMOqTRCUYJXmC3WaL2C6PYjLyyfx9OJ7cXby ULpZOiyKmQZdvlwQeVpJ310NiXqxKjBoYVOaLCTT0+ufxKB/bm0ku9f52gICQNalOce1SFpGtxvX l1fxa7/6T+K//S//p7i5QeXBpgTKGAsrX5kCdAlK6vVK5rZcFmkIAAAgAElEQVRi5ZffGfT7MRqR +fEdGekptm1akWQd1j/Ln7Go4U/BpZM6xMJej7WWfmlmpCt1IYXmiBjfwXhY7UZUdeYaHarc1NWu KX9vssrzviUwzmfnINLPigJDVbm4W1OcbSyeqK4hlcBqpSF6BYtCAUkaS2YQ2XTx0ilmtUcoCrmp HUR2fu0FPMbjYzFVgHkOxNSkVDhIeVoFk+LbXbpjXbt8/u3X1sA/GPGBE9PxDqH/l+9FYPMkRhOn a96rErDYeNn14pTotXfR7zoaqtUbmziVbdPQkiHof3NKL5ceii2sXZU8RbYE8ihApTqGOKV0LWdL psWHUGcHUH5OBwwA3hry+WfeZ34NWRTJkiKkR+cRs9fNJmaLa4ObdG0oUxX81rqZzhrK7SajYqxF 6pkA5AZx19tBjACMOc3BcvrG0ligsJtHyKHsIMcu4nr6LN577/txdXktUiJdRIiLZvwXC/nlXBkK nSTjV4XxT6AnkLa96eEziSAriyVLMHfOh3K9ubz+QKUVfKMsz5Nn0zwJN8tdbBeMMCX7uiNxQkpM riHlRQsS5ZLZuEmMUCZtj21TjhvOZirNKbC8zcYSJhqxYXNsQgHo/oN78Z/8p/9hjEbgfSbzihbR wqW6r84w5agXYY2F8P3aXezaWjIUkQlEwbR4rOcrzQsiUS1eWNtO3wQsgg8Hx3Bs8TkFk9JscacV gB1nHA/dw/V7dvWhDp0XHryiWUSxzAspthmksumyX9oYV6os6JpgcDVkXGM6ix0dYQ66fV4U+CRZ H9MHmqDAz3G5UKalw7RQcFD0GPQmFSaZwV9cuuIq5AqjNiVRnE4j4vK720pfvg4cGYQysDmYHQ9a iRdlSVgD4bx3945AVQerGoe6XQImvpbXrGbC3+Zg7Qej4oHQFGLce99Gl1AqmNAI1C1zOgupDFkV K0aCS4GxtKRSKTmQ1rbgMZaX0YArqXhRZSD9ly+cMpZ1DAkOZGRy3F1JJTQVRHWKMAsHclGka+wQ U2rYwk8xQLut9Kd6Iw9U68uWzEqnuibsk2sEB2qtmTQN124824fqAHhRp4N+ii+6ul7gF5JvIYAu VHr99jtvx//xN/9OvPGp1+Kllxj5gaKQ0rKp+DiP6fyJZuMwR/UgKSUDZERKQ/7OtURy2Bc+x0WG GiHqSFOKMo8bOR6dKyDWpz8LxBSD6fJSzYLxeFK9v1QkkCcmYGgdyrInZqtrmZ6GlESNO2bpYjqE 7bt0jQspkkPq9PQkvvLVH5ANGv9OkKdcZL5OB4ICk7Pd9ADQRpVXYlfy1i3wKDLvsngpvWGuDzun CnbbDtgNlICVDj9lS1KRGMZwPKlMZK21XrpibEJzB+Ly4iIuLmjuwJ37jA4zHZpl0x2WQvsbxthi U2V0LwOolBlqvht6ng7tNFJ8iHLZKPPXZQDeY2kWgeT7sNY5DPkZTYJeB48Ca04ZckjuXi3m1yyL zNEqJWvFa6ofxzCkmh5whKNVBZF9hn2dle2XjscwsGbG2gxYt7PU/ZIyX+8QS9v7bA2HquZ7Nn+3 Kw5WYYHLDjw2mlzXiVWIf8p8om0xMLl7uyS4mT6rtYcK8Nwf1ARPTB8Q9cvZL41AFNOBzYrTGmNO c7qSEsD/5YSiBNVgbmGZa9YRvERZC+xtu/t4KJhyx2x2nUopp1LY19YGL6m5tNjpMDm4iiGeVlM7 JJ4ZwvXJmZ0+FuLJyUT/ocSIbTy8H4naaUVZkuNmcWmRvd5EP+dnltg5ie2WsqVn0FU8N4K+5ViG HStMzObPKjninD1Lcl4yr+kAdvudSsZHREpJgZipLJXKjjWuN+ubmDFaFOvogmcVbASi7WJIhmyX G3OB6OIVw4yq22Q1AspQq08WrEXdXatpNDMZd25FtJPWvw0+a/BV/9RDfHBW+GY582dt//QOYM7Q xr419iRuFEPbMF4WC2WlAP7IX7tJYyrI4cY5BG/dxTt0pDmYb6vE7WqWNkfrgs6lQPWyvXZYrE1F cs0DtuZE+TJSLl89m8ZkuI3dwEPrWboON8sYYICrudk8mEwb4KFScS9Q7fa6fYeP/PwuMfdDgb9j MxA0g9KRa3Dk74eB5OPKzibN4jAANV/fJXcB+a05snfIZCXDo2vXEzYIqbb93TxTtolhf2wdct1A t9hVyrULm3kLy3ustD7VFcCvxIeRW47BbG2CEsSIj+asFFwmsyM2JQFJabRnsJKn43fzSSSlzA5Z VhEWVLzoSPlAPxewTKnpYWGyJrIupbt9L/ZulwDp9rqdW6wS0Q6EAN0JlXBdexCPH70UP/Kv/K74 K7/wV+PZs8sYjvoaw6DLuEOWtmghpXrnsrdw0CvDt2ITb6B8wKa2WivdV2eLDvIuDQYRg9OqC8uu 2GsJs8k2CNPC/h7otHZQs59iElJ1D+n6UYbKCcfdSw1xc1+VHHDqM61AACKu1N1Z3j95aYmfJaCv MSttruKuXcBxBSt14IpUEKerukIG+TPw4ogUXcjGs+jjhlN01lzy0qEqQ+P8fVmGt8FYKeMBb9Vx trEJOI6IuKPO0WB116ZLQF+b/4jiZ72J81GXOKZJldJSSgjGsLAvq7lWDsy6jquIq6vLuHw6jfbD rjrRlMscADLCXc7idOyRJLqRfp+6POWAVvA5yK1aB+zw5pBxE5OrA0QTu3O2XmWtDaXVw9ePj3lP /7z+dIdcq9ufo36t6porMNjANw/cJocxhS2zhO2yAdSla2cWVAw4V0iZMFxJQDM/SLiRwGO/ITNe /GxznZgWAc3lkBaFpGc8a5g3UScoM4jCJBywPCLDRlnpnSbjs7iePasY8LwupQgn7lLPWcd8PtfP R+OJgqJ5FXaN0bxZLrQykAzPqdsZxmJmaV6Il8g+g4usF5RIyBAPJf2izQtI2unEC+cvin/1V3/x r8ev/oN/FD/wlS/Ea6+9guBCTLGfHwyjM4TvhL48XRN3zZLTxaXCSr4PZ6uMpdCuUGYpFn8h8SkQ TDxBIF1wP0SczO9RPPc0cS8X4555UimvLHa8bcy9eNGvB27HqBa5FEpgpKFH0dvSqbOyaAsSapm5 VDm8NMO+ylBYGxwICYAn5twYQ9J3LvwuDTwLZHbpr/IfHawReNha/1tph+cgLxjkwvy78cmJ7xGB S7Qrc9bEXyszkpKpRoJMahFltOhjyIwZGLNTVXHByj2/i7/UiF2WzJaSKwEURnxP+KHHyTKod6K1 6sbTJ9P4/jtP1BGkmcCeS5oKZSOE5Grdyt1oP+MjgAtfVsOpaILvzeg1+FV7GFaqRSRskd+lDlp1 AKtDRyYR+xnp/iP/TdWO1FyfX6YePvf2a1pZF1iFgJXigR5dompwIpWfvYvuNxdrucMIAKE6Lnhf llBSYuifN1Iyp/YsHLKVJbo5PezrXT7YpdjYAAA4HRayAQ9MutThRnlw1nI2OSRrQwk2Minz2L51 pbBHV2s0YRGblcznytPfJg/OUioQkw1bRlg0+yc8y87KuzXg6SgGmuVbxIau4Gpjd5wRRM7yeiw8 8q1uN1576Y342Z/5d+Lnfu5Pxa/88q/HT//hH4/T0/P46P1n8dLLL8aXfvCt8rmLQKBvg2VYOu2Y 4SQzsC27gVVjb+B/+bM87eC9aUHTVlfGsSk8OGpx42WpNJk2TZyYlG6V3DFdK8kn08AIdRtX8Js6 w+hs29GhrX15FacvvBCzDX5+DJFbtE3ChMkAhzsH3wlSaiUfU8/B6fdKcK399vCeXEsehvKPDb3L NUPns2+wPhcvLHZNMHBfW5Yn5qGxmDLRYGKr1UBWkDLhnFHmYhaAwQ/TAJByGwDtMXxH0xZaKynP nZSX/c11+PfUc9tiSVYOD8GEC2gqS+usKcB43ajZsmvLfAXe3uk5Bibcb7q4W8vyQDweMAp0o33S 69CZhiqzr2Nu05ZiRtKqsyF3SpuUgoJ7NQaOs7w8DOaHZWAGr2bAviv4N3+/yZk6vNbPe67pLo6g Gv/aoihiM1gMViibeRCsNHmBnl1RRekim4KLmfAg3Gw2Hq+AbnDx7IMYDe9pKt4Goi7OBI7LFWZY NI+6MsykM4hygkqzzUoAaqep1tAxe1gberuN6Zzp+3W0e2ifg+N0Ynp9KYnc1WxptjHlD2VomU7n tefXs+iIgIqzj7t0k8lpwUo2RdlhWGFEUueMkRyUT8YW7AN0R9hvTVDpIr5muVxUETzDmIPT3Tg5 OYkf/pd/V/zn/8V/Fn/mT/+5+K9+7s/qvc/vnenzfO7zn41/79//Y3F6OlZXst+dR6cP6dXZEcHZ 9uSeL2wOre53nEoZXMBbGgSSuoWcCckQF+dWRzrnCM8ZY1tKIVIKCYzetAhaG9nIE2yTO4P4Hl0u OE1rBQAWwi4mw9OIFqXoPNrbpzHogFfmfFtmbjl8XXNojPPUHCZxnuRBuIpnN/M4BdcDQoAfNxxE e9XVYDNZp+3JjMA5SHoDbcmYB8wh1pLamjFdbWII7ohJyfWlNjiOSqv5OnotArEbFOVjHd0wSZWw s/ZxhYG6u3VAstSs4CZ26t661FfXmXW/hAR9Ha3eRp3P7JRB8bj/wlmcnZ/Gu997X3DK9JqJjYhH Dx/FYIxJyyKePH0v5pez6OyuzNVqMQubNAbTHch23UWMPfC7+bmrTLUq5etgctgdZU/aCah0Y6tp gP3rcnfGWn/PY0B9XcLdfgjbxnIM3THJM5fGW9GVS2KqD0QMYm9irun3wnR3KeATErzKJ+RCJROn GeCmpYrpvhmryQgvqn6sNHCs4d08hQtG0B9OCludE5Zu0KJ27BA4jFIjKqFzibYRoCpJXy6sxn+s 5+5NZAliWO5ACLwun5dW81LGAZSzJVNQQKLUgIg5EFVD3CECIVm42M49YUGLzkyRfUcW0GP6Hv32 rtxb2h2e147T0wd635/52X83fuwP/P4YDYfx6PHDeHLxLP76X/sb8d/9qT8fP/sn/3i88uorcT1/ qg1KR5EH7H/Kwo6ynMQEPY7Die97YewjGdFOuUkLS+YK23NtizG+S84sYkNPaSvhPzhzsYnuwGWJ wHSZUJjnxrX86MMn8dvffic+86nXY7kYxAmctXYrFrt2LHbdmG9ty9XM+hgdyQn92yl/AXrVSdvE DMfuEXSTImtCYog6Q5vNvYxv/b+/FQ8fPYzZbBmTk7GdtsMzk1pbVAMd20m5mQLm1I4P37+Q36XZ 48XfkXlCJFMaRMuqhZ4sxiyBwAzLtb9rI9XZxT7HiXUobG1vqNe4YXalF9trUVs8qG/SsOCT9jbO zk7i4um1JyzWGxmksLbQnzofP4yr6VM5VekQGcCu90B7jpX5IzdA6KKGUfsiHJvZa3bzEm9y59F0 jprO0Hzto+HpgEXfwOz33r/isN1RUubPSSGgEUqDTPcRgUdiDjV+OgC5BE6yc37XLmUYOLO0cGRv jRZTiPQpuQ9S1l5NzEOJYbXx5DfZWa4LMVJNLdfPlJ00bLizG6QTE8fo9MDL7pBYwlubWqB6Svu8 tZO7tDbdqnQRacfTaZPbMPODZHzu6mk0opwgBCIJl0mx1GWOZtAQCQS434LzeNN7cBs7KzcdtgEx cxHdtUdVSNVZ7HDWPvXap+PR/UdK6wfjXjx4dB43sx+N/+HP/IX45jf+hUQL758VBjog8a4d55NH cfXkItadRazLPKZGldy5bwzlNjkxfHZUEorzMaf6cFw+j0myUl0tgQvto35/ErsegtLW1JLAX/EF fO+d78c3v/7P4x/+6q/Hr//aP46XXnocP/Oz/3Z88QegL5xHD52kDl2Y3JBJJynZlDB2HKRZK/tY h+b00ODCdbiHXjyZjDeZlarLxtm24tnTa41kXV9P49nFpfCdxD25Lh999CQevHC/TCEYz6MJMJ+v YjIZCYK4vprGvfsQeu9VpqDiFhUPvlrpoDGDV6SVmyMlxzZ7szPbJEfqnlVllEuvDGZav8utIA11 l/UC7ihKbnm1jpvpVL8Pzeedd74Xw+HTeP31V4Q5dkdd0Wp206fCJRkNyrm9PDyy+9gueLA+51HM qI4mTXehDOZel6kVdht/Ouyo1plrAzcrvdPnI4aHAc3/y/5SR1BMmoQ1alecppmtrn+WwAXc71r+ xV3AlLcgEIChoJV1+eRpTIb3Ytcr7XMpMhIVm18UUJBh59Il4gLJB7C9z2kRiFoIe8WpR1jTNrEo 1AI6sUIjHcNNiJUbMCt3iOiyKK3X5HxX7soCQtUmbovYqIteNJ/Q40JNgYVs1jtmCANahVXq6Zvk z5psfxOrCYBzm4yCleD80u3HyeRcGuQEBN6fofHPf/7N+OoP/kB84+v/LN5868149OCxGDvohZEp nU6GnptcIJPiMlMpOPhEkdypMLkSKJSx0Hnt4etojC9LtGRU6wbLHzAPFHOQKCMxrdhuptpY0+ub +Pt/71fiN772dW34z37+03FxcRl/5//+u3H+wnl8Gu9I8e5CpWOylOvsxPePYWphgR3+bPdpu0F7 MwifUyenDNSmZ/uOzt46rq/scXgzncX11bU38NJTETzIwGYz7McG0eu3Yz4DYwTM78rCbTwexZOP LvTn0bhnnlOHktl0l2T7s86qLpiX4C2hubs2a/29ywZTN9SgeE6L5rRC9WAOVGYZVqaldKfkyYOJ TPKxKA6MGC1jxhTBtq0ZSJRAW71W7OawvdEtm2q+FJA4IRgRtptlYex34/LzH36X7BjWpVvt6Zjl 5bHrUP50PFg1stD6MtVZ5/HMqv6zCLaFx6g9VrTWEmRvOvXsvUA5iLq2cHJaVpsKAIS7k2PVRQ8r Ck+RI60pXs0Qq3S2jMg4SDHMWUTJso1cpJT7JZWew9MSP4og2I92323zddv8pWHPGYVGUQQsb2IN aRRdKo5y8ZO84XlPj5B46Ji2cVfsfAIepMt19Ie9GKJEgTyLFCFoQdlJRPhRJapXJGrA9NYzn3ql SwdYymfabPvRXpnFPJls48d+4vfFX/6LPx/f/e478elPfybOJvfUadT77DYiQ5ouYOJmdnOaRN5K Fz1JdwQAcYyKKkPVlk8agOc+a20kryLRPNgEuDZvlwpYv/kvfisuLy/jp//1HxcJ9u23fzv+95// G/Gtb/1WPHh4P+7fv2/t+yKRvd5CyWCBlWy2gOtuCnF4AYZb0C+7hzgK0ZGkdCoc/QafyWobL76E rhif+UzBM6853dqb6U3cOzuLTg+MyAoi6HexFqExnJxOpPbZ6Z7HcNRRd85zrb3obcDG7ARkl+mC u0lDfW9LPjc3uF0yZlOB68oeMG04OeG5uazn1bEhBdZfZA7AFoyKnQxjcjqSs/jV5dRKGLtNfPTk aYxPwevgp7XVMEGaXLO2/VN7BUK/0fSCWe41x+vYdzhegh1zw25+9sMM8/bL7//MVyQJr+Y8aq8/ 53E7OHpgLBtHWYWlMkn9nCzzfUB3K+6GqYfW+uGCdccVJpVBxV0ajA/8+0mn9w21aoCE9ggiqfSh jWRddFmRc1KAK4mwiNsMvC3Yvyxen7aD3Uhs+VrD118CprdbvBBCuck9dTPV4q5cduk2mnhJlsjX tLQtTsjEJ5eMBjMNqLKpM83WDSiDsyT1es/dVioO6qgWO293ttwVItv63Oc+I3D+g/c/iCcffRin kzPhTXxPjZ20RzEcg/Vh2UV24VM08ZLs+ljkELXNbrRKh/VwIyVLPvW8D85Ig75gXQF2ton33/tQ Gc5rr78aX/jSF+LlVx7H41cexz/8td+If/KPvx7n987jy1/9Usl6vTK5ZquipGBiL3LJBCWrDSTo npiAyntKbkgSm3LPs7mg0Soctu/Hg4cYnrj8Y6Caa0sDg9KXEpDfZXSL5SbpID5T2eA8zs4tXcQ1 ldZ/wymHgKL7VjHUM3C2y/O9yaqNdzdsU5VEe7yitHqna9U4QOrfdzbpfYTqq0fUpBoCnaXfifEJ 7ubrePLh05hN5zEYPYg2+vB9pHqg9izjavZU62QyeCDxAY/j5HA7IgO1ycX+Z849d5sLlZ+x/ryN APQc9nn987IXq+dmlxVRR4qr5/O5qq4nmCMJD/uzIUGUQ9fNb7W3N0qnVihKfgDjKj110zbIn+D1 2xlq8Vvsq6TcSk+ttJjWX9k1yNfjpCOAoX3slJ9T2xuSml6t+l5HA9bSApconh1yTDIcORiuLaYv jtegpy4cDPpUdCAjoNslUJm2tTYOs4InsV7SJl1Ff3QSJ+g8LRkv2YkigRKDaAAz5EiQcgYzWSG4 UyX+aoVvSOEvzUFDt3tHxmNMi5PFgoTwt1YxGg9jNpur5GF94eV3Mn6gLLWHGibGErtF7FazWvZZ mQsZhQEty0V7GFWnjT4KmzClb/VM/Q5PIGurSLmNkiYDGRxtBppvbqbx1R/6Yjx+/Eh8sLOzbvzk H/oD8Wf/6z+nzPPh4wfx+MXHha2+jWF7EwN0tng5HGwot+DcFb32DES5snzrd9Fv7aQUTqgQJy31 4tMBBr9G7MLWm3h6caGgNTkZxWg0VuZMMACEb3MIoeFVcA1mGSGs2CGcsaxuTE7OBD1A1FUTBl4U 7P0iQFdhOcX+ypcnSZY10fSwlb9/wjtr9XPgUNg1GbzT2lilk8jhXUaJSNwJStvWSnOXZMlSaCtZ sDmBHHbuANLRZX2hZsL9h9x8fX3hMaQEx8Ud6kh1JAfRm7FlP4A1cMi9EqtgfWVmj+z1MMAde71m gMpr4gPWmJTX5+65z69LRhn2GWCvkoySWe0FTZeB2XCohp+rJ5RMxvpD7tL0O/04Gd/TpkzgixMP TSrkPgaaZ3PZZ7E/Zz2pq50f3G65tb5OxVUp9AiGX3mMBycxl6GlSYooSYKTSPdJQ6Rh63dOYE6y QrSjVIUK4ZJtEOPBmcdg4CL1LDuz21AaAfKOKs4UQUeY1HAs/7vlzkYEadMtX7vSIWO2cNG5juV8 GePhPTkxixfW7sWofx7PLq/i7W+/E7/7R38o7t07q3CGUf8kditjhAPUQdECb5moCsEznWtoiJmI V/hYYH2wjaj5d3xeylLPHaojSLDdbeJ69jS2K0wuMCgdRWvja0vAn21smfXk4qN49fWX4s3Pva5T v7Pmmgziq1/5crzxqdf1XWc3c3PjCnEvtYuqlnl2kgS6m5qBJZw+pZovxiaV6VAWwfkqkimJa2qW UR3gTUyvZjG/WcZysYrFDCOSmzg9m+jnIpcOu7FZ4XvZi9FwFJfXlzE+aceIrmIubvG+FnF1M5Mk 0KB7Wtt/JQbTGDSG7lKXb/tB69ijDmS5sQmOxvLmq3WM1QU2LpR8KbDOztCl/tWzRUyG900y1UhV Xx3UXhf5om68+7334rvfei9e+fSLMZzAObJ/Au5R7LXr2YVMT0TAhrfVOdWge9IdkvB6u8Q9RqLN AO4upoNQgyxaf+nqf45xtPK67ON9n6Qc9J/ldak1XTsMHQY6O3RxDSzT7UPdunk1ylwcYmUNxFR8 KdHm21lZjI54knjRRr+ncRgAcRMtk8RY2vMkxiiBrrYC1qwGgRvKTZycnCsYijckMp/nC7HRInsb jHoxn87kioO2laWCaXm2os3oj7SnfLFcRvnk1XvzWtr0DnRokIsMi5qnArJZuu0OOIdZ+GAFo9F5 rC938ezpZYzvDcTGtnzITgsNFxeCp7SztrjB2PiT96HV/uj+S/HDP/wj8fWvfTNefPBKPP6Dr8au w3xeL0aTifEHDEo7g1iRaSFlLEftabTXvZiMz8UnIlA9eXIR/+jXfj3+0l/8i3F5cxn/0X/8H8Sb n/1UjCYDBRVGhL797e/E//k3/m785j//dnz+i5+Jn/zp3xtvvfXZeP+dZ/EPfulX4lvf+VacPTiJ j96/iLe/813dA0ZB/si/+dPxysuvKmDBZfrJn/rX4uf/11+M/+0v/2L8+E/9/mwLVnBINie475q9 lLxzDku1nXGl3r++Y8RJ715s5MCCXBAjTJmtrmNBa5/5ustpfPTBE+uqnZ4KhKecA6viAe9JTjUE pMsrYY3DSaHPZOZEBrZxlvnkyXtx73SrwXEvKHcvs9RQl7ffqug3zrhu87GOA8Y1T4mykO+roLXe xKBs/v1AYZ/LXu8lZU6zzWUsJPntZglNnLP7JzGbncXTJxcxu0aQ0v6NHJZ8LsB71T8doA2oOEAu 7nSSvVFi1/6HTTJnfcgcBq0E4rP72VRROMwyEyKpCaL7j9QWy2ZQHZgO37O6snWH1kzzUpXVs6v5 XA4pJnB0oBBDJJHt69q9HYkBehlTsfogQQQ5l2FrrHVA8Bj1J1Ua7LlCTs6iBaWyFvE1Dyhr/EQz Y+tALBBzVso4SSTT3eoZmIZJZInWjsiNROLJBNUCTq4iL1LwW9q+noHMjknK3LIgFx6yLnrnkvDV 3FgrxienyqC8cKi9wat8Q1jQ4/FJrDY30UFJs/CghMmVjpzAfOYmUWFAaVVSIN4UzIP9+I/9RHz7 W2/Hd7792/HhBx/Fq6+9Vi107ula5BN3Rbl2N0vUL6b6nlaNiHjv3Xfjb/7NvxW//Mu/HJ/9/Gel 6vq//M9/KabT62LUYQLk/ftn8Zk3PxV/9I//ofj7f+9X4y/8ub+smwt+AjHxq1/9aixW83j80uNo 90PBgblPBZ5iOsA9/OoPflmf75f+zv8Tf/dv/4P4wpc+X/solgwly2OVmEwOlNJQ3bmc/i//BzHI cX8SC1jhjFqAPW7pWJq9r2FtAefteOHRfbs0qUy0MetJf1K6h+u4uYFo2lXghYs3Ho/dgFlslN0r 86XL1sKb8TIuLj6KNhn22EoShyCvZaE9gN4Ed5sbdj9oHc8eROtoqzrcyxCa72cahTfyuIMu2bjY wrlxRXAajcdxfTWLxc06NqeUD7WfpdpWDP9XozCrWHUWcrvZ/7y35V7ScKP+Lvm9DrladSaloe4G XmrDl5oqcUuCp8qO/O9Nftp+xlSXlP47s5Fl3E9CCKZ3JoMAACAASURBVPV1rT4/LNDdTGIMClhy NjdxudnsqBapegBs1Ngqm3k2/SA2rXvCGdQRkNU5YmJuSeasV85nkSWwsOT7hxa75gkh/LHZVzoZ pNfURh3BkbRdBjIVkDrdePLdZzFg9qy1lbIlX3dyPtbNmF0tVE6e3iNzgVi6iuHYKbWkedGFQqFO zHiCJwGjG8PROGbTa5/2Kgt9Emek57uexgNtMFrM6vB1nVHgxZj6RovlLLqd6xgPUyHBAfb1N16X 0B8a9B89/TBeeuVlHybbiO+982788i//Snzzn38j0Gp+4YUXNLpB+/7Nz74VD194MV589Di+//57 8eTJk3j9U6/Fv/FH/rCC9dvf+1Y8u3xqgTMtrJZKiNdfeyVeevVlgebf+I1/ppLxjdc/FS+//HK8 9PJjgdvbzjK+9JXPxfT6Os7vnXpMBDudsqZQoICScfHkWfxff/uX4q/94t9yeV9K+QpnKzwWYYUq Bd1dbZqXJA5q6MDESRacNkTJxBTs4If1dlLwVPMCl/EJmKQ1mXjf+YyyECecvrDBxbwb49GpMnYO LNmok0EhFgmLvzeO+c1UQ9LbASVaDSw3sRdOjr0wdgfucriJmv9Omcs+W1cuyvuvpd9rBDKNfcms lGqiVZXd48kwXnn1Jc23DgZIG6UZyzYWG7IuE0c1wiJp7aU15YoPQx0kfKgkjnxIcai7fBkdygRD szvIPZaUdDMgORgdC9rZJKp6DVXZd/doDz9bbihxObf39cn2rp9BD2OlazcFRfWgND68Kc5oc4Ht Yjw6iSdP3tdcGEPGlIp8BzIkGPEaWBZQ7ZsHmCqlyuJ956l4S7/owtDl6PRjvp1WaafLSH6vgIkE hRklgeftLi+mXnhbhNtuRFOA26JBZwB8HGk2EZP7yBCTri8Y9JIMyJDSp1cGZsssG95zaG4lGKyT t8e/kylNIpY7nWa7HeWwT57Uj6LFDg/oZn7prKx/Vl2/fr8b9x+cx3vvXcWTZx/GAh7UthMXTy7j 53/hF+Lq+pn8F5nsv7q6junNVEvh7bffle/j6dlZvPfu+8pGfu8f+NF44zMvSfn0rS+9JnqFJKV1 TVPPiQNlFL/7R3843njj9Rj0BvHioxetDcVh0B6JE/Tqq6+ULNYOx+ouNk5DMpcf/KGvqFT+2j/+ p/osw4GF8poL3+MTK+liVdwYqA1QPdDAonmAeWeKyFXHYFmIhd9GZgoBWUx2jUZ1YjzyJEW1yeUx 2BFlAaylp6CE25GNYTVYLf02c/pOTx7ICdo0hlQtqA1Tj2VBB6GpuXWqvZBE1MNNm4PTlTz0c7Cw 6vXopukgpUNmpZPJCJOyS2neI3CI0gnSSrYTw6eA2cllIXa3S3hyUlBL2pQs4xb+1AxWdWtUr3GA R+U+dIlWl4/N+3/rW5Xsu4mPfdxDDZCtIaKcyWziZfVreo3THUxHJXW/j11aTfaILGenHPFyGDpd LyoxeRYufndE/mFxaN6JY0TZtIjhcGK3kBIvW6V8yNlCg+h23lU5RCeFLqFwAvTGrU0Nd0UcK4LY zSJurmZxcjbWqQsmBghuR2dOL0t0YBXGDC268kxBpnU73wxAc7mdCqQX9lJOBStVgtXYWHMzWNkW HnIiAHnqfWGNpQxyIcE9NklHdloOzIj8vf32t+PrX/9mPHh4Lx4+fBT/6Ne+Fv/0G1+Ln/iDvy9+ 5Hf/iABURmSms0sRJb/5T38zbq4X8fa3v6sJfvCqNz79kqRpUI9g7tEtfnfOCNxQJggAUC26o168 +eZJFfj53BINbG2tawZ42ZElhf/jXhwsWqgOP/lTPxZf/cGvxLMnVzGeWKNLXaWidSXsR0J1lsjm wWsPOmMZaeg6otLgolPUCMom6dq7BaqHphkKQC9J4VLGg6klCbjXS06Yx4o06CypITqPxg6R66az K85VD+nl/h5WkmWsM8XaoPbWJqo26z7BtM4eDnlJ2bkrr6df3O+47W/qEuDUJCrWb8r2CLrbuHx2 FdPpzBrmZ4wfsc7q4W9d7zKD2k5lExoT6MI3Puh+4KkDTh7K2Txx0KrL3Rr38iHYLP+qMHMwjdH8 95rSUd/jux5UAQ5Yh+47zRtSOsW6364qIM76p3s3znQFjx6Uod1dLjBnTv2eFy/lII7RSIEko5e3 ZqSFDa1Nzv/TaWJ7dSlaYtAJ2t/rxhptasZoMKcQ4GjQnJUwOoU53Fa36KwI3BGgXnjpPCanY3WL uGmUgVzgs/tYuZsLxtxiRMFrKvqFB27VUu72Y719Krt2efTiBsPcYzmxNPvGoKtcfLMNv4o+JQjd OK4HM46ruXhaqIZqWr/VjS994QfiO7/1dnzjm99QsH3rc5+Kv/dLvxqf+8Kb8cUf+Fw8eHAm0baX H7+qOUxmqH7Pv/p7VeJQluFO0xu1YjD2SQdY3lrjM1iAXymiErRCnnmYuLL81phbqFtXSjdmQenE 4lasIVP7+QFeMuhdSZ82Ft9oPIrXXns1Ht13F1PvU/AUFGkVB4tDtEOS1U7BIgmMKvnEdyJwtQID 5w3vVxo2ZOft/livQVltdro3GV1nNrGcv9MnsmwkzxRahYMAhZqIeHxr+wMyASHiovbi/gbIbu2x QJWbLTdqLWOyf13ufOgtuSe3n3NYFtldGTKy9d9cHmNyu4gPn3wQi/kq7t9/ELvdWDxCRsjwhKSh IAKsgtSymirhFTxM79GrzJRMLk2akd55L/DUiVAGG/85f7cma+6bmdavuR+wnMgljrSfxR4jqUod d4tnQ+kSHrnOKp+RvYLzR2kvPf/Cw2qOhFBeMeskbCAYHZiLk6WbLiZ7MX/cbGSCaqtye+1lS5uL KG4VjHMN3jpt1mhMUcj0B+STrO0TCEM57aeUIexi/KAbO7owpx5LMb/F5D/kZtTBm83j9OFA2FTa SQHyMwIzmjzQxVjNoUAU8S+GWDVyg9igqQqz5WWMemcesNSi8k3iogGUcnEh85FpbTTU6uFk/sNF Zrm4URMiuy5vvPHp+BN/8k/E137ja/ELP/9X4k//N/9jvPb6a/Hi4weWiKZDGYto9zx4bbstm6c+ fPhCrHcnUl+gO6YMJOCs0U63Omi6igtgRwtKZ05xrmlsFmWr2uTcA2MN2iwNe6i7ujo5mpMdr71i adeJce9E64FgK/keDiXJMCcdwsTcodYLs37j6v7R6eL6s7EYmlcJP8fJiKypK/s3YAM1CPCAxJcS l+nt1tLJ6O5jLxfbGA/OYzQ6sQyxSFDF5LaittfYTtU4aGYbZSDcGUae3c+nOdQb0aRU7p2wuoON eWzTVtlYTizB0h/Yi/HDD56oY3h99Sg+8+k3YjQciEhL4iCpHZyL1gsN0Z+McA3qyrkmaQp1RtUo f0uwckxJb8T0JExAvA5QzdGdw6DUDGKHa6ZA/3fKG+8HJA52u8HbR9MZf43J6RsJmOdv/aLFJp6i me4pUVpwK2ECLEZLoVD6cGhJ+kI31a19Tv7T83vmKZUUXMoJ7XbRG8/b75OPzUnn0KxyuCwb0Q60 oXYb4S8RZHJr8ax4D+mvI1JXJHLTcAIej7Kr8tpkXnw242S0xtdxctZVk2B5cx1Xz57G+YMX9L5S rdx1xI+Zz6fCohbtqRQP2zuf/jzIGiQm1Z1LKA4MaXZzHePJqcpA/sOi7Gb2THOC4EXqohHE4Th9 +Stx/95Z3H9wFv/9n/3z8S/90BeFk6XekzZJi+7RqbIX61CBx6/UJc2HWP2ojHZQpSwCfsLMi/yz cI7iG364wSBvrnax2Jn7tWvj4l01/m4/ykyjBBalolB/BoIRHchJ/4E168muSkcHja41jt0s7E03 Vi1mLI2Byepj14sl7Hc5FbXVcDHVgW6sO4dcQ2zLnj59X58BZQx1k+kYIx+NS9LCmTxlxXh4JhCe e27V2sL1E3yQBrWp4mArtlodM2VYnKHkoPEhAH+YTTQ3og9iiMDWG2viQnuXtKlgoIkR9PfX1YEE /vvmW5+WM9NyzgGOEmvEaraSt6WkwmlyUX9uOPg9tmZDWuYPwb0sZ1OIZ0XxxL4IdXncDCQFCWt8 3OR03RmUquHr20GpntKwnd9t0H+fhKuDuixADrr55nLvOcBN5CZwsXDgaT4YkVMJ524W4w2c5GAJ 4CcuD4VjSWWgqIkGHQ57rll/nOzMqgqUS3JJkQgEAL0Bd7IVNh5tfMws7FhMIHCN6g1sLz55wimk OyNTlq/TeitAmVNYYbK0gsSo3roURMKj05/oxg/ha8kUYCnMigCLc7O5O7TDNbGjm3s1fxrIrKF4 kA0EcCNwMDuZ7ETC7GwG0d0N5Wu46qx04uG0w9xilhVscPCYV19+Nf6tP/ZH4/f8vh+JB/fvx+kJ BhWeP6SU9IGI044lUsRzi14M2pPYtoaijHgOsytOEhQMghuln9P3vsxphetobq+edN9Wig0OJHTS vGluj3A0HwRAzZFWm80cLC2u7Tqmq2eVvpkyi4Zdle4FoogcSlvkte2WDN623hnjagmrmqhbbGE2 7kFtGyYLsuxWF+E/MixJJHchXp4pWHFgCK/czmKxurIbknwCBjEenkt80YoeHHTM42UWQpbrjDu1 1CtaAN3PJu5TglkGneZDS7J8bylaNy/sXobhTZ5/ldLGrid1h8TNUHLgkLiZLcRD694/l2iOVF4x txUHrmU12e06blYX0d8wZ4tCh2dnocw4+PI90n9xL++rgkv+vfmVmnjmoRfmXjfxFp7XuF53mNMe f/jfOfz67YmwWTqjpj14EqByEGqcsF2VCqUcMkhpX0KKiR4XtrWOdTrnMolOPdlw3kgPODuGkOmY SKcTqPJb47kW52Kjypq+kkX2EDItW/sOWoNd55GAeNRQN8oilMLjJsxFlwSzM4KishI3MxyK23Hv 3n11oTRahCTtZlKdAD2ZW5CJWXkiyY98v+ubp3HWTmma4gSDYgJjIKP7CrpWRwUQJCtEz34e8/m1 rdN7dC7TkKAtmsTDFx/Eyckg2lt/HjakJln59/bIZqe67r72qt9VepZUW5kAr2mgmdpfQ+gCz5GY cWpt3MgSQZKtRuoaFdFO2WwFozjs/O1lFaXZAjGRScTMWjwTCRa2LMHS2YnGrnZtHRQEBq4NChuW XuYgcpYn9QQ+K4PR8OBkNGpTDumzS1liq88rTwBEoWR6u9CYioxHekwwnMfJ+L4bNi24OmT6M70/ BxLZnvQiGkPC+0YTmUk0f24N/cr8I1UDjoj53d6klCwMiaMM4lnKw4c5UUViPKFuTWmg6eR7Pj4Z F5E+e2/Kx5Lru+n6oCk0hm1xiBItuwzOJxeK78XBLWqItuRxWsE+0fT4vx9mlrl3mtMq+5elqeyQ +l25xupy0ooefr09SgQlIBhqryvag3Bl+J2tJjcrZwmzlCsDvzl9TVojg0xUF5Bt4SmSNE779UUM JSlcpFI4ibQR+bSetdKpUN04TsClwFaysAQTNbgMsVTMWXeD8K3j2qAWYFtvLpS7JTMBdxKYibY2 q4qj2G0k3RDD/jDOJ6eWQ8aKvduJIYRDCQiSVRUtqg4YUj+WdNvAYihXmf/CiVpAvm8ez2Ex90/O lGnaRmqnMlGmGz0rP0xnT3XNBD6rJLEUL2qt6xY329pJlL5cXsm0wOiFd5SE29xgjVOfrCbHdYj9 XNcEIIwBFIVG0XfT8MHKG8q4AOvF5dlfnLeCVWNgODdaDhyXN3BmVVmb188DCNfsqByxoSEQSIsr N6NEHHBQMpTqYUfmzqtNY4EjjEkKP5OKLNjjqoi3geNAb4AQeqbrtVhdFx8CG6G0tzzHQV3qBhVA s09YrGfTmt2v2k49N1UzyOX/pglC/bOU4HY3VP6OJYPdB/mbr+M/s9ZQ2F234TFulSWZFEwLHxhm E51ipZevpwC6LdeedQYtRIHZJNGawe5sS80AxdwmtlnrYx17NLOjDDTNYFVnZy6xm4tjn0x6uK78 Ow5UceT3HMhkUBOlIqgkoROHLAJ+rueNgWRdn6MU3ARtZNXcRVomF0KJ+irttFFdLlY3P8cxdCOt +y4J3aJPLkOByijURgYkACw4Tt+1+CCQ5JbRbcOO5uSfxa5HIKPMHERPapiFswKAySzWsKubnaFS 3A1RFlqScUaR1JI6/KM3Nu8pE40ieJ8dD4IaG4tAC9N6OLIXoBeQgdpeB0NSXGtn0Y5LKbO6XMFs tSvsaddvidXumwSAbrsqDxG7jauTPx2SG2TAer4wbzQjTw5yzCJWC6NkPaIV8h6tYREuxPG60SV6 Dqhc4y3+XWXVJSsmENUzpwmONl+38UmUBfg7kUX4KUU5kmtTzEWtrwZROMdb/Doy4lhzD4tUEZlx 27OJYKeISvK7DJej4ir4ewt2OJLRSKpo7m3E8tWV8VVZRl7XLG+zpD52jeprU5uUFri5Arb3OUXa iikz3djEKt3aDPebV6dDmTlnbVpK0cJbxBykGvcp3UxBMM7ajDkTqLPs9O95MMNcrebnrzE9P+fw M+bDBiSJ6ZXSTV4Et5VD9u57hRc2qSH1+zi+GJOs3MAPXoNOewao6rAoZaIxUZVu6VzSSPuk1IC+ kDcFm9Yyth5vAHxWt6zIzgi4VEZiu68tcsN8AbpJLfTZXWuniYV001WKms+SIyeL1txYFnkT10dZ VoLrGHmOFBwkNqf0ly9m+gXyHSRazP3VDj7JM7EhAoPW8rhj7EFSINaaupleiSTrMpNtD3jbFmbG IiHYGduxDIgoF12Y/BGbNjN+W+FZYH/cL9J6ECkFva4n2tND0SoTZWyoSOAmZ6jZOq7T7LyhxQGo xSY1CbNJz2wuErA/S3lguVUUHcoEoDuKd2tGOqt1JschoQwzhqBrpXSqeVXeMJbbsWSPB5ybM2ae 78T5GQFDSkGba+RBZX4eQdg+k2SFGg5Hc1/lJkDtyFxADk6Ru6y2RZLG+xGwJKInl6fciHXnLEdz 9Lfy+REiTJC6Sbw89jjEaBoXW05P9RG5n6kc6xZWmVxVordkWgs8sFq6k4tyw2K+EBVFz1Vrf2M1 jV6rCvSsu9tll/9MptZ0is5sUoTaAqnkzzNLc8Azdu3AVlyADr7HbYxsnwS6j2f5N1x1HMe4MjiC e3JvU0zU94sf+XtID8vtYM8wmdBVWyBdTZ9oo6eTC5t2NJxErz8qYwM2DE00F8yB9P3y2ZM4OUVD aqggtsWEdddYSJ2OZGHheKGg0N0M9Hs8XxcJQbMir+vPapCUQDCbTuXKkmQTA6ZkWMMYtDqxnFnE bV0YspJqKUarrRYaRTcKGOOTM5WnN7PriN1VYZNbjTQjPFtfbWW/iU8eEQAhNw6K0oIzxxtmDAHF 13UpY9890nRCMLAEYDjyKSYC+vM73baL8nGDhGar2jyVGkS+g08sdyBkWlp0CbWxwN4Q2EMVU/5Z +wuwlPY0nIQbSGDdc5pk2WQ9ymW1uQuLXJmhVWjZPC7tXa7a6itb5YWjxfsUaR4oIfyuMJtirOrZ Qjq9M7kNcd2Gg5Poj8j0l7FZsg7l7+WumZo9O82owvrPwFmXYiZEuqnjQJk+BnsAcdXWr7Om/evf BKubFAmYKZSFtYLEsQ3dLLd930v5j2SMsmhTd55dXMRH60288ZmXpZNV86FshcY1BpZw5p0BKwNy s5xjfTrYZVnHZ6f81OhUyWrdhMC4xdgiWvzpK3pIz7graO//237Qqn/HnfysGpr/vhfcqAvaNm7O 72S7s2Kk6jYw+eh++uoxCWRqb2LSBTsAiLdpJ64zvLmGFCmHNmabgyXx/+kMDXsjGbGiEDqfThUY oBlMr+HrFJ3qYp2eDHI22LNnH8TN9jKGEzbCRCUpYCbqo7wmxE2kXXD8ha8DQ1pZ3pbUiCxqGK0B iqYGjVPjXQsFkmqvF7NprTCqzwHNcjWJp5fvS6aki3Oyrh+gsgOeKR5o0ZcFK12lUtJuNjEenlgS OflThbCaIzRZWm43Bt9r/KT4MgpUf36wqv7OTW0NYtMi8KCIcMB0VrhayxghO3xJFIUDkxwXBZEC kuq5OnXrjaVB99FEZiQmLFJum5dGk6bfQkWV7zSX+zF4IQ86XRiDVKJslScExN3Cy1t5HTDgW8kN FfY8zk3CdMjou50YnY003ykT35Z1pmS+udmJZX96glxLUeZsiAZaZLCUSqkhXkEWeSg3S0T+vd58 zc3Y3JTNDeZg0sTEapwscZ+7Omfcx37b87Eg5b3OVPOF+H2ORui1GetzcHNWTtKAtPI4IAxnFpuv e7crtPdAKZUTgytPg+NUa2wd0hn2S+u7gHntL0E9EHvrbnXz26YszmHQ2iuhSxe9PKUa78tsXXpY dGDACSrL75JaKpgw1rEq2BaVha6PU/dyiwyOijS4s7fgCtngc7WtmdkDmBaXZGeXWwVEMizGMigd i9opaT0s8OvVRzY9oNTT3TJWlkYWk/GJQP9MbyXJQSAdjiLaAJZd862KzrhOl3JKqbQbDLQQyqUr 6hL9GA3Goiio64jLMphYH4LoDHNEbRiuw9XlhRbAySk8tCLrzIiRsChGTcC0FsHkBKRGlEVH45O4 unwai6XfX6eYvlp6Ku6L/x8+Dk8kEWjbY+FuZLjZKbS43Fb2V0jZCHjHlUTmqiZ5ahEIwql1inKB +J7mX4rCZiJm0CREEN1J22vTWsSmTXBZ6l67iYCNWt/aU9qIzo6TwwNHe7FGJgRCpA05+D4cJMkf 4j+ClZRdy8+VgXAQtFinjCgxOD+K4ehEh1jzsLXSQIUCVtSLDFa17Ex775qbQtK4EEc27d4WLN12 FCnUmTsozw9pBU1MSN34lg1XVLaVrjCM95vpXIqkL7/2oBo7ytdry7DFZrp7zPUi8JiBIz93vW4y SLjCuf1dPhkl4VjW1fy3zG6PZajObjOY7Td5mq+52s4tmAmMpGFvi3LyEIYlMFP65g4OxrScRpMl STGRgNBjo9HRKaM7DJ+ud9Fj07Q8FlIOM2VUYE5szswkNguCF3wlYyQqx5BNgRwo9xRIc+u4mn+o ACApENQQpDhqcUFnJEXxsIjB8ZCWVHsV09mzGPQm0dkgkYM1OLwrnKkd4PjwBLY8zZWFrQlo7RgN zmO3Ir1fKZuAB8W84GJ9Eyft8xj1zquhcEB65v4SyyOYi0xK2bJbxmyJc/U4TvsvVOqoVpZABcLB Xd3OQoHYx6C8wOvxifqEqRZACfLuKlLmWQGATE3mV8qk/LrcbMZZtKEp6ehi6roi+WPxRA4mEYY7 29iAwzWY0Lm4uJ8EEtZEesllQEhVhwTr8/rqXpf7pdfarETK3QZTB2sdlKkk2hU2k4oN3l0SC9Qy 7cZ84WHxLieBmp/c74vorYbSEyMjzEyueaW0LovqgbwHGpmEGgRZDpZJi4JBHA1ch2WM0UCCT77v frabf64Z9QUPKtMUUm5oYaZir0iyVNbTyYn9DLaN+b5W+TwciOrI+8UbJe3+++4H2jqjOhZwbmNS tx/PC1T5uMvzcT8zTT6DD8LMcqtMrdXzhEewpgvHsKzTiunOphYAnMmxIrENDjgJe7u+AHHXvCt3 ujIQ6URcalzCzFzatO6AGJexfjp4BJvK2RYlQF8BTLo3W24UWQ/l1Zl1gyhFENnjBK2y/OL+HLaw klIDC3tAJ9JOugQhzdi1Yck644CoSAmZ2V19kXyCMS6ClEWOd2RppKxiu6hGT2bLKwUH1eMNTCIX FNdLGNFmKUxNXDSyVgTkBvCuauNLt3Pv4vlUd+JOLLhaJ9vSPMCUsmq5p6pkcbapNlQhPQrDgPqg YS3b3ct5CGrErJiO+H6l1r/krbmHSO4QZABHy4Hn5o2vr7LbIv4n6knxl6s08MliZbHEZTbwvi3P x4g3cSw1gcjYl0U7vGx6DQbzPmsOorlIpaw7xoDUlBBWWeMpGXhsIprZRxWnGqB8PcaipnXRh8oN t5+x+Hnupmd5WcTpnkMb2APfy3pJ/FcVwGIZc2SVO604fwFScaNZEGW97dEuaurAscyp8e57VIvj Qe3js6vnPfKa3/Xc2xXEcSzMGC1KwvKCLt3QwsPKD5gyxWQ92U1CGpNOGCWddHyUqSw9tV90oZVu k6JneaxTggVne6KkAAhb8K7xwt51Bdy3h32VjQCnWxQ6CZByvzWRr1hclIucU+iFK1S6mqn+4JvO 5uOLMvw7t/68FA6cXTVnnrJE0AaQvtfSGAHZmDz1imMMCxii4nYRq/WNAjPOP15HSQgsG442+8ay OMu2ZYc181eyjtbIEr+phHDY3fudPkyG9HXx9a4xk+ZCOr7AyF08tJwqDtLoLuWDghUa4js4Py5d HJC24ocpg8s6Qy9YrnPOypVRqHxYMsYaTzC2W0WgzlmE704HmGA5L5mPu3fq6tL920KetCInHUEO kw0ct90m5surWHdMPh5o8N2vDb6UM3SOC6niULhNh7IxFb7zfCwnwwehmRElJTllfefrHHYGqxvm H+h/BIBvnX0T0PuDvnAglcHyWDDnsFCGQ00KKCZ7pg/14fY82srH//vv/HH3mj1WXtelaeOvtx7e n3TDGc1j38HN8mHSrclmgGXFMkprry0t8mGPksejHokJKTiU9xKQDVaibMf4Bh9IQa4hd4E9UxDI oC7MZjHi3wPawCA64a6ePiaLWg7RjQ1YvZuzH8nc8plLdoW5Ks8loNLRgy1NuQMAbjkWf04CkJx2 IPttFuo2SWt9iKPNSfQ3G3WnKNc0SC12PiWjSYwKgEhe7DZi5LbXHcklszl0HSiXYxCtVTeuF09j enMZJ5P7Ipy6HLFMTGJQdz2SuVy3o2933PdOyINfaNIgPtGjsJnRzqJ7SLgHa+BedSnJGACHUGv7 IZM04YJBECXAwa2BqlGmAxQISqKRwSEJxgbX+7Fb0rJ39qiuMGUAGa3Gq6b6TDRXMEGp6BiKhc5i KHNFTkYrvWTaDrBev4O+s86dfPCM+Yjjk+V2FPPB5wAAIABJREFUAeH3iYl1pnXXtdvr2qk76FnC NE9p3pt9sL7Rpi831aUhK5BDoxXDwSYePNhJMno0osOLuGGWsCUDViZVd5Ob3cpmF/Iuq/iPe9xV Gja/y61M8aAczc7w4XOzQVA/VXn4nYFUTlwIRNFgQfwwFUeJ6JRpHjspelfgU9z43iSig/vMjRdX mfvSyVjMK1l42pRbzDBnRW00hxaL9VIBHWW9Rfk5Qmhvpg0sUD6JiRKUO43ldCospuJjFBzCI0CF 1p/yrgSvMhqEcoO5PDwPnEskDqlXMsiNlA0nM5+TeS7mJhP85bsNRhM99/rZRVFUtVwvGSjzlL7g lIZ8z5WC3ajfV5YmB2kpQWDLPovL6Uca9LVm1iEp9PkYwf7R83x5FAXDBsbRfP1PCqD67zDnKe/X 0eXUZ6EA6JMkkTFvDKZv+9sYTU5jGVOV5gQu276ZCsHZZKDbPB5J2pRMS5rm4GldEx95oD8GMRQV hjUzlkjnjE5k4MtmloqsRoF2Cp5qArVtyss91N5lBpEObpvAu4pukTPyIWP371K0H3TDssxrSg2b g3TkDtXXSnw141dJU6jv3fF7e6wMsx9CN3q7oZpO2wF7rnCrtjhYUequhOdsdvYjqjPGutuXa6aJ B3189nP353xehnn4+8eef1dXtZlW1cn53fQJHTLtcWx2V/plycvQsVIHp3RbPDTqkkyjJ7SRtzUp zW+bVlSoxBg8E+dnU06TYh2eppZSFVgtNB+WYmQ6dbNzoWHHMs/YbgkwR0uekqTTHlaZjlx2AfIX u9jMipQvc2grKwTkPJgtu1raCOIebRfaYLvVxsPGKhX4jOtYLjBLZdDU+vLCDx48UCZ4eYV9uKVk Vr2lFleLzE6scg9qj/q+yGYww7T29+HLLWHni51cjxfc9Tg8tfQ95ENXi6od/q7B7btOqNs/O1x4 VTZQjZq0xY0Lmihkszg8s9k1/9mLUfckLp9eROsenb2hMiyoLeoQazB7XcxV/f11eBQ7KSnZCt/a yCyi1pa3LdxySWbVieHwVCRgpJy59r3+iQXrtgNTHSJ1/7nm7ZhOL0WrGNLQQbamzBPa0AGeIEHV Y0LC+sr7itLToB00SytnuGUzlVKv2Rzhn5c71hcy2QkgH7mue4qeh127WmQwGyKL2Ury2mCgn//C 5zTLixt0NntaHbv/JB5X0Taqe378PtdrqsaC74IOjmVRx9bPMWpD49X2mkb5v3e95rEKovo8MAg1 X7pLmy8AYQcLM5iNU6BrJcsveDHIzGixeRHxtrLQhnfRQilhoX9DWB/ZFvSMCDDVtLtGfthgadXu Eg71gVhZ20k+hnQfY64MRWRQ5HFFs2LS3xb1BBm52JRsz7weS8nSMZN2FMFHjQBEB+k+4syJyecy OjvGeobR7RtsoUsoLGQ9jen8qS7O6eSBOoB81tHMHRt1PsHxyD71Wdg4KXq4qwMgoHKLrBWRQpeV ZlU/D0No/ltdXvgAqTOA4wvk40u/Y8Fwf1GQeZD1LGKxXMZ4hHV9T2M5eClyvcCHprMrmxpLwtfq AzKkUJfZGKiydMrtcm+Ef8GrKqMobQLb3J1Y1BUszeNJifV6pjJQ+CVdSWXZrJOVxnwGo7E5d5qO WEm/jbUKcTU9C3ftTSw2l75+rJcUpmScJ1jTpnt4PMiqHM0Mxde/YcrauMLqEDPnumMShIDV7A1+ sgwkO7D135OOwIFn3O78/AQCSGUSLFOUrUtbUSE0Sg70UeTF94a8784OvY6Or4PDruHh5z4sdQ/X 1u1s6vlrMD/XsUN073U0d2sYqpukyhTuSqvv7XodvTGjGMa3ZMlZxlTIKuDN5CLlZ2RnGshkMzMp AWmyqCP6Btl2iY5fNZqTM0J46SEs1N7FyflZLFc30e61VZYAzhKING/WRuv9xnK56Or0nVHRJSI7 0nhOIXnyMLuXl+9IHdR6Wm1lWkj6wmHyiWMpVjYLw9mMElEek0GgRCoVgtI0WC7nAnxRBlX2QCkk 5VO/r8wpkTDeDWPcs29h5Y5962Yd3tjDNnR6yO0vlP0bXy/GwwV27HEs1XcTAHB9EJs2aqPeALK8 7A6FpaDuKSmd+SwevPDQAo0t8BsbLGQ56eDlAAMzXg8Z3bp0Zw0AGWzbHo9Sh1OkSLhqk7i6eSKT DkBXOHGtHXrmXc0QYvOl7LXXdTlYNioct9UW1rzfTmKQpRsr+CG7a0XRVoPKVRliMmleflV3e5pP 9TVWsEJEAbIlTZQjmdXhY+9QuHXf9w+wZ5fP4sMP3684hBChgWTooFMWt1u9OB3f0+/CG8wOcq18 UFtmNe/3fgZ5G5I4xKeOBZ7DYHZX9n5YBjbXbv7O/lqsOVnNbPfwupEZ63vXHyy5MgSGInHMqWRG nIcz1WpMrzrUDbC6qjEtf0BKipExH811eVGI9a3yBu+9tcqOzRLJA1x4CC6w5RGZG+s7WN64EFSX EW3KFL0O7F8TUTP70Ffc7qI/8umuYJiDmCxayJzccFxu4Jyt5x56HvS14Sgd5rgxb8Bb+J2e8Diy NuJgdiBlJVZKVwXsHdnUXPpO/hVjNoMhVma4Z9futvs36ZM/vMG9gQ8X2V3n+id5j1oqJA4s1rnv uH77HynJ0Xj/8P0nGok6GQ/lnG31CLhbPjyKdoRpCmKFMGJRtNdhp8M3glaiIWU00yilGFGCCMnb kynRNOnJ8ET6WNJGgxPmgNhuT+T8PRCjvqU1SplIo0RcN7qwrOGi/GGjBvPUFOikN+9RmOT/VPiJ CVx7eznHhYSTAknwOQrnilnW6tI9Z2zleQfH4cZnTSF+KSimQ1XgKYzmUHYXRQxp0yUAn+41+8Hv rrLuLqxoH8s8Xk4mbt18fJKs7DBoHb7/4c+Ovn/BskuXsGbhihekLAWH56nMQK0EYMDbL4a8zLyI +9ltxq9jch4LR6qIxU49p7TzQydAne+r4MJUD2A1paXYp9lVKIu+0BIE3BerMEvd+DPJqKAEiQxW 8Lp4GOjfVBQDPhsflUyJCX/JdWyRvAGcZUQCoqVJexBO+U4yOSi4mzqRm0EsGDtaTuNk9yA2KGLK Xcc26vyXYznqnFWZ0CehLrTuxD/8c93eO8XUnvdQebEzLsIGpiTzhHzUmlrqxbRkjnDx0bO4eobL kGfR5gT+0pghPyaQMoYMRqQmSRm9IUPWZy9fB+E1BUTJENUKB5pikAMOAWtpHDIzIon5batmCgGs zUGCU1PHZFyybWmCFcE3Y0HF6FMvT2C0KofMOTVM7EzK17IEg2QkNK6nL3cp4USVsQit9fFrb8Mq A/sYzOfw/h4+JkhAv2iKgwM00EzRICvZ3Ga7il64+WO+aN2BzHWx/1nq7Cp/v/nZKjytqIUc4k6f JJAd/tthiZh/vqv0+/jrVT8UsA4/QHbrYsVcF6UPWIEF8E2mQ1yNERPmoMrUe6J5lSBgUQwtG02l p4/eMplfLMzLycY8E6cX4LanutvK3oR3FT6UvyCdPyv2OSh1o9dg+3p+z/bvxtr8/Sz+70yPElMY CLwq5uCKCgLkUL5Tr1cwFbAt3qvCk/y5wMTmSwKSNwXfyY7GGw1UoyjhTMzzW7XGUvyOHoeLQIG5 qClUc/4HDieH2NT+69nvjXs6XTx1YG7fdzbbYF/LKACAfL2N66tpTKc30hljFhQ8k84bmdKGCYQ8 /cEiKz0pqTF5gxW/SQkACmfqyNE75YzJfvgmIoAGPKqRcD/WlDNks8Tp7mqpaMgaprc5e/CUYPXL Ih6qBSwLTRIUzp4Y7kwV9Asfrh50zgy8xgyb13v/77r3Iog6WOVh0QS5n5fZPi9ryQfNL/5Lkxfc nVKDTtr5sdOAvlysW+P9bHCv3NwvaWvy8XGnawkYQgmBSPzc7uLv7HEsizr2OCxJm8/f/24N4mjz ybnJMA/94KN34gZeTNh6azA0OA88ZHXRooFVsh2CgoD4giNpRlFlX68QTn0zyH4AxVP2RaWbXJmZ HEd50jIkGQg9s2i97l0lIDiuMpn8sgQU5GZ1qoOrFc3vzM6UXRX+GJnGbHVlCRuwud0sTscPRFiD a5Q4G+MS+TzkZrxB2QzgaB66ZUVcX12WLMvfJ7PWxAmf/2hmX/WiM0/JZQlqr4RqyUwVEwSx1Mhq U9Pp6IIrhgvFpWe5nsYcETxJTk9EHrVQY6OkkOTJOB69eF/D7Is585HzGAw7MV8TcHgvggTBgs9m SebMOmymWm8QdYUpASVF41lPPqaMFTgUWQs9zwEKGiiSM277F0UIyp81pRkcOxyB0CsbBlRRKTFI tdPZtDJ2uVx7qLviEOZhnJd8b3McXrc6CCg4VRhwasT7/nr9HbmjzwXBm+97/HdzgB4jmD7QRYAR rtW86BKQj2JRh++/L4W8/7sFL6q+693B6hB0P/bZj33XQyxqP/O7GzO7K3DeMlL1yeHNRrfsu995 P977/nsxHvfjpZcexelZK5Yr+w8GEimk7QpWGKqiGGmjCAOsXVEGALd7PQJEKQ8l0VIrV+bQdW44 OoD801ClhzuMKRMDfgWxsFp85cYmc5nxF97HreiGNvtgoNeGqkD3D8Be7rIscswkptc6rSUJ3HMX VJiB8DsHwZvry+ic+X0BPVGNHA4x7wT4PY0nH32gwHY3ae/5J83+YqvbvZIRwVZM7rzZmcJFF0qH nzRQx6oOWvmwgy7X3HODsPVTrjpF/yrFiOJwpFKYrHoFJ2oTDx+9oID13rvvxny5ifvzVbRHuBBh QHFTdUZ5jkr9jdcTWFXOPKZJqjwqxc2iRU/2tIptaxndISqcI48RiaZicjAlYvLkgAI4DPkZ0wtk b92SzQkPFVDt91NW3+qV2VU3jqyGWtNuEsbgukujq3TkmhysmqDZKK6Kq3Vzcx2/n3dnXYcBYC+z 4D5TuaDIIdx3IJ7jhkNhtxFvLf0D9j/D8fKq+RFqkb06SHjqojh0H5hxHHu9wz83v0MT59o7AA94 b/XMZV0hHAP5DyuG7l0vnL+EazFytd97chHvfu99LZab6SxuMHU4PYnFYhnX19fxpS+/FV/9oS+4 tSyXj7J+ktPVdZtY4HeRebH+eWGzK8vx70DGRKKkxm5K+VjGX8QZY4SoiAY64zMTn2yN0kUa4QQP GuOyyOpLa0vZHMzoIkzYpwsWVhwdDu9FF0njlWfhmqx+umOVkBkZTasXo/6ZSK6md1jmRjytO1Ur b9/gYzd0/3+bJyfMc4wxWpWeuBbhLmKmDUzgAmMp9xCscTOt1Bx8OjtrJCD0B3bJ7m9RRy2mnGWB twrTPE66cfH0SnhWCsN98OHTePXsPAYMKxfwGsUPfqGz7Ua/6+s/bOP1iEroPBabm5iHy2YkYQj4 yoZbBDoUHywPbNnsxkIWhw8JHw7JjTqCostodKVrAUUZUFirTWoga7uxcF+70BikPGQt9AqbruST LSVMgDC+pnetSkYWJthmcp7uupcfR8bMPdXckM0/723oNMjYoW2hjoQCSp8JDgViH2A2UCl4bTm8 M2Dc5pd9MqzIFJznVwTNoNf8/IeZ1HEQ/a6gerwzefjnW87PzTfkQWDRBHnS/XeIpQ3j5HQSv/32 d+Wl9+KLn46XH78Swy62S93Yday/bnDTAL7rcuyJPMJSj2pQAi6qiy6nkpV9+jStDn+novmnlZhB 2qT/i6Cqv7diUEYXJBlTDE4TsIe0KuecIlBm+oVJp8xwcS257/7MGAB4YRCsJpOTUt6Z1+NSxQ69 BtdxDCrZwK0b/vHg1WFJUt+rIhJHVgcGt93FshUxaBwyxK1RB+NSnEegGtgUwZ0/AqivVVUA8PtQ AfAH3FxY2K8YgAh3ohReGLPkO52enSirvbxaxfj0JF5+/XX5xSXwnJ+fDICu6aZnb8vV6kYD4Fyv xWZaqZSS8a7mm+h1KA+HMR4WztMWjKKvw61d5IssbOeA5SFrd+80TyepFcaDvHntuoNj0YmCtAbX NzPbxamrbL/ERNiVUeh9ipfhnq57XTZq/Ra5b2ymMvutWfKZsdT37a7OcLWZC/6ZHfZmhWPzFQsR 2MylVjVoFR5VDbjfVjVtKiY0M69mQNnvEtc/r2lO+zSHjyv/jv378wPT7X+/C8tqPo4GLDYpFurT 6TS+/OWvCOjDUQZsAXVQshJe7zNvvhLjk4mkhc8m92I8mliZsk0AcqmYzrRwlTSbVgZgvRg9FJxq Bzr5YcKrPV3rX+X8XX4ZAP8U3xNQLEvzrso6unoqGYqrsEwjWJQQ3xUsGXTWJYo2hgUyeV3IkVpG sZoVXFamocI/ivuOPouGd61zJQ7WZiflVC7Iyem5iI3HJDaO3YTfCcAptxEN0xEc9wOiMaNWWOsC rtAuFmsUR8moUBs1ZcCbM+3lh+hdCEOi9Nv2nOGYTe3MBloJmVC/SzOhF+uYSOrnO7/5m3q/Ry++ EPcfnEe3Z1cN+nB0tDS0W7BGAHLdCxGOrRhLhrDt0f3bRgeBxM44VjKURRqHhkUvuhBAy9QDWSEu yP3+WFwx+HruOpBBAtYjXz2SJ2KFGyIwqefdSF0DjE5+eKKtNJVdi8Fr8f7LcZcqz03DVcVmaB8N PrxKzXU9fH9wMKUzc/N+6zXhDhZKkDdwHSRy9IMsU4114aVOFHjkbG3alpn24i68pLcrNYo85Ou1 eAhVPA93O3xUeNcdZeyxnzVf6lh5d+x5x153ryR0erffwUIu9cMPP4qbm1m89dZnotU5i/EN83FW fRz2TgRMDwd2pBHOohSfTqAljbcEAYDC9locG4GyJTtayco+ZVgz6tJoKiBjB9KmW+QCU8uJJoC9 KDQMpDBptrJPLBNJjWHY9CI7RBn4yOzydLHyQ5E7FuDMDfcpvFiUUYjCxVIZqsFl43MsEuRn82Km 7jX4WV0SVrdj76I/P0Dd3RpvnqLIj1xcXeha0ZEkcx2Px8LZlqtVnJydcxrEBS7Ku3V8/913tQVh T/PZLy4uYzGbx4svP9RmkbRxmfXj9ZHi6fTWNufA9GF1I7uwwXAQ11cmhJ6cnErJgznL+czWX0xL 9DsD28ini7Ckbd3lomSGmyWdK+R7dd5Y3cHNg03cwNHr9JVB5aZrtTexbZPdDJSBmRFOAF/Hps2h uLSHI2RVuFZF3kZlZxkDc4cVOsc82psypVDWAe5JdD1N0uUW+x64M+2ut92SahUK4z1eW8ZkG53H UiJyzSlfPdmxn5nwOta2r8euagjEOG+zfG2Wd7viZ5h/T+16S3vXTZomzSGDwbE1d7jG9v71d4jP NddpNiPcnLurBP54KkNz3yhgNTWXfIN8ESstdNlVDTRwKo6ONnkrRoMzLSx1h4pwGuk3iRvjLqIP aH0WzXikQ3bOvggumRraDSQzhZKasyClglpLgbBoKFfkCqzg4c9aycSgpbTDvgvwdiXPuqznGfcg zRYru+gWaU5RduhrZSY580Y2IlJ0oVQoEyxie81FopJWZRPzigW0+//5OMQx8n0Obxw/IUA9efIk Pvjg+4WI66bEfD7T7z148IKl9Totlezvfvd94VrwqabTq7i+vlEgfnZ5FY9feRjde0NhWW0mDook rbg/lKDrjWY6edw7fxR401LKYUh7dX0Zl5cMgCOlTNfXbuG56bIzqwNBMkSp61ROXzFd2OxkZ6ae IhMTPbTM+soEq7lEOYJhOmH7NL0uJGU6iH3cyD2ormyHe6zN0pGRiutQ+2oqREo610oTGnnR4dSO QStxUb+X51ezY1n0+Uuw8f0yvkYp6uBVy2aX4UPvgeJHacSvYFSqECwNnfc/D9IMWKmxz4Hd0JmO ZqetDlC+likU6L11QA6+HQr2AswnzfaPr9nDV87XNIftGHZV7f8shQ+09I8d8DKhSMGy6ofdrha6 tLmFhbDhx1IFVTYhDGmjAWVN5yO+Vyy/5AbDibppx2w1Ez7iN3eb2441zo7kc0dJxvB0wUNq6RpS dQc5ApW0pMpKp6xImV+J7ZVOh3CnbZG7kQNLId0xpIpLrlJ3sch0/tFtYVNo5GLVsozKxhwtfR7I pYXkuo8L1NdKgUqb9OPT7bwJhzfu8Hlp13T4sHCbgzMzdE+fPlW2xbWlCcI9oREym83j6upSMiUv nJ7FQCoTEU8+vIh3vveO6CmUx29/550YDPsxOZnEAs4PA+PYDhVXFY3XlC4i9IcH91+OHXN4m2V8 8P3vx3d/+3u6ni+/+ii6p9hW0X1caEC32bRwo8LL2JlcbuhkmVepS7QwRtUiRFrGZbhei4yLTCdV KcpzaBb0cMReIC3Dgek1KtpEyZDylAfE3vXSIAPaK5mTOX2aEWWyQVpTDnC8njvOZfxFB9QutkVB tdrs/L8yBlbL1NR4GNeFiGv/gJrrWHfomuaiRT+sKF7smerunLXVVIVaidbrhk6qidOHYn7PA8Kb gPfzyrHD1zr8973XrZ6yL39EaV29Q4lWgoww19VXvd0d3CsJWbiafzvYUNstcjNgQdZpppzqbt1J SjF/n1apKrrflYD5DLDrRbyJVhHT385ntdheAR35K+13k04LrUJZnAltLFRlWT0HpVS+VLCo7KtS YbKw7jfmSfmzcvLDIzsrvn7eVMJskMZpj2LXark7uXE2YZke4wIu81ofA5Q3T4b937urLj/+2Adv 9+9LgtMou/bj4cMXdajw/V544YGC+tnZWZycnMRHH32k1yH7ef2NV4W1Pbu89DiLuGNQGZCq76uc Su9JGO3rBXJBZqaTuVC+D0dkPVz7bbRW63j27EIJU6/vjutiQdcR+oedvXMGknur60dQUMc4M1bf s5QKyqYOEMwWgF6mOGBHhfdGF3mNc3dJZLN0KuUsWY4ljQygd+Uw7GBgz0GvURleFGlthBg5/dXl RUtea6oEWWVFnWgPuQaUwWThkiEtmV+TxFXI0nvYpYMV1YBURhKgr8ZsbMSRCinNIOdAWdZUowmw a/xOxU88UF4Aw/Ksb8F4n7sOP56jdbhW71q3h7+z9/cqNrVimXOPjWKCr4OumPjnmrbYD7BHme63 o6hBamgLBDSBeaqVc1DR8hZooGtuTmoJqwqMHvfvy7VlvbHqZl54MoPh2Ok1pYDHfYqMcLkB/fZE OBKALfrdPjHXwhn8leiEMaleSxmL4b5axXhyvyiMFu86XRy7Z/TbG9kcoU9lgmPJ4Npt8anUECAL vDE+tIWK0Wh/3w5O++MxzyvpDk+lGmM4Rqo7uiQU/HEx4ku99eZbMfziF29hBqk48IUvECDWcb14 EveKQN6ru9eF8aDbuVw/k8aZMko1GAzGa0PxvaWYsYz5YhbDwWl0BhOtgz4dx247Hj16GI9ffqSh 8adPn8TTJxfx8NF9ZShrpH76pw5SeONt3LE1XsZY1LJk2alOUGcKJgaj1f40up1pTEb3ot8/jTWj YutODMiWy8RClVkzvyktt0I0zayjwgRLsE/nIPlVwgmgJER6xoKTzvgLRFEMswUn9AexoFu9WEYL PfkwlqrXKqKM+BLkYcLh18wM9F/KaDf+jfuprK/Iw5jbVUH6jbVRTFajsYkbYzUW97PDjEfoihx1 w/k5X6uJb6VW/OE4zrEsrPldjq3n2w8fEjy46gsUhWOnbrZknxu/SSyYr7cxR5oKz4UO/MfbXK29 4efD1C//TJZFxK67eeWJcvIotTgprVjIq1jNZ+rwiOjZ6msqv912lpWBwS44OaVdOiAFv7II3iw2 C6y7wUv6MeiNyyzX3PyszS7Oxo88TrNZibkNqA8vCiAYnIbXGQ9PY7udCFTm+6R6Q56EGklIeeGC vUCxMA5QD3XXNy2vTeO2NHgve+GlpOzHS8A6rW8ugo97MATtQegyy9Z4zWZ2q0WwLcPILY9zMNDc xY26Sye3E6POWWxXbmCIz7Neq+NGUNoASkueGhUK8YMFundaWExdaqavP0J4cRi/9a134/vf/75m +vgMjx7fL5ZRtnEThlM2nIbW1cHNMZ6ysEufPnXxzb1qx2a1icVuJikfyJOTLtQNN2eEbZXuMWsE mIBMqFZaKBSKxnB/je/4uttst3akgYtHl9mZf70+lQEyNA++RiZOB7O4FClIFCMLDbvTR+U1C1FW 76MGUwYpr/cka0rnq1+aR9XBg2Yb5V3RwNJ+cTC2vZzln9wQrE7LYkiylbySDYvtM5jfpRlsJFPT WIvN9VwD5rfjQfN3DukUh9QFHqvtLuYbpMNbMW7Ej+aDH/VLCc4rLFh7aOKVBKm5v6rh52MfjIdI mg0jw/zyde1s9xrKEfuSLWIzdzkouRHKjCKdTHCDcU5GJhuxUuq5A1e8A8uJ2xufWvKk6Gcx8b9a 3pT03gJ8KFfKt7DdlZSz7b0LRqDB2WIBX5rV0CFQiciuaJ5cG/Ws6QiuNSe4HdojT/r21al7+xRJ YLNugpdS5ci13H/+/kl11+s3H8sVgxntGJ2eyvHaQ+eNzZmjGnv8LBt7kEnQLVxvpmrxB47eLbzv HkR3fRU382caOld5hJEFm3tFd9fZiMu1dew6ZNV9YVvT2TQu3vmegP5HLz6M07OxuoTSDZPG1cCe ibw9THi4dp20a8vPfuDkonuBPTsfEcxqqxGixfU0JpP7opl0GA2SZ4Zsy1X69cr9NIWgMTena5ok ysKnSl/CBoepHsz3QewuJMC9OYLiAhYIwvQScNvi/yjoIR2sze3TAVjhVwbRDUQVJYsyHtRUKnVp bGUGlYTiFqLtboqIZ3h3pZlQOwu5o1mysczYyRjxMFTD4Ph62sORWp+MyNn8nebay4OnbrY4NlDm mcyMj2Z9r4/tCY3hleqpAuzrv1XZcTVLmCd/XQLVDy+EtL02oLdXJsmM0zeJqI7tuzY7TF3kbDnZ yqmJNK5bxAZIE3hMQFadoF1XEjVQKHxy8LN2DNonsekiGMhcIp/VXSllclAlCqnTfBSPYSRXyxdz Hsv5TDOIpO2ePSsYCNg8IG3yW8rgtZOU99MsAAABJ0lEQVS/O7ohDdAwLzKu0pJypcQQcTWe+/i4 UtDlLgPLxn4GXeMzzc+jCYHCxapflydn1pI/LDsKD0WUK8Ma9LsNmKFVNlA0IE9gAHy1ZRDd95cs rUXnTtrquxiNjRfdu3fPDRExyX0A9TsTGejqqCizgNUp3Oju7J/S6qXhtqgDyAa9c9s87SLmy0tW TIy5Boz8FABbE2I4Gjc6uNWBIApTYpsO5lkSNUt9X6vEK4t1GhuwDSzSV6DWmu0RwOlClmAn2kIZ bcpDstwv2a0VB+3awDSDaN1FzXnHag8W8D1NKUTLKHSandqXHgjfXzK5HthjbiqY6qBc8c51V+Pi h54AdyuOVs+9BbzrTw1aiLEoBfkjuO7zEgCCG8FutobKYs18F5YR/x8oeS9zl2apZQAAAABJRU5E rkJggg== ArcGIS Content Team Esri 909-793-2853 909-793-5953 380 New York Street Redlands California 92373-8100 US info@esri.com 8:00 a.m.–5:00 p.m. Pacific time, Monday–Friday ArcGIS Metadata 1.0 Esri; Esri Offices 800-447-9778 380 New York Street Redlands California 92373-8100 US In the United States, contact the Esri Telebusiness staff at 800-447-9778 for more information about our software and data. Outside the United States, please direct all inquiries to your local Esri Office. This information can be found at http://www.esri.com/about-esri/offices. Software purchase price Data and Maps is available only as part of Esri® software. File Geodatabase Feature Class ArcGIS® software To use this data requires software that supports FGDB files. http://www.ArcGIS.com Downloadable Data Esri Data & Maps group 4.38 or 7.95 GB (gigabytes) Offline Data https://my.esri.com My Esri Downloadable Data File Geodatabase Feature Class U.S. States (Generalized) 2016-11-30 2016 Esri Redlands, California, USA Esri Data and Maps for ArcGIS® 2016 - World, Europe, and United States Location: \usa\census <DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>U.S. States (Generalized) represents the 50 states and the District of Columbia of the United States.</SPAN></P></DIV></DIV></DIV> ArcGIS Content Team Esri 909-793-2853 909-793-5953 380 New York Street Redlands California 92373-8100 US info@esri.com 8:00 a.m.–5:00 p.m. Pacific time, Monday–Friday In the United States– Please direct all inquiries regarding software/data pricing and consulting services to your local Esri Regional Office. For support, you may contact Esri Support Center by telephone (voice) between 5:00 a.m. and 5:00 p.m. Pacific time, Monday through Friday, by dialing 888-377-4575; facsimile (fax) available at 909-792-0960; electronic mail (e-mail) support@esri.com; or visit http://support.esri.com/; Esri holidays excluded. Outside the United States– Please direct all inquiries regarding software/data pricing, sales, support, and consulting services to your local Esri Office. This information can be found at http://www.esri.com/about-esri/offices. For other questions or comments, you may contact Esri headquarters by e-mail, telephone, or fax or write to us. United States U.S. States States 2002 2010 2012 1992 2011 2013 2014 2015 polygon area population households demographics society boundaries farming polygon area population households demographics society boundaries farming United States U.S. States States 2002 2010 2012 1992 2011 2013 2014 2015 The data are provided by multiple, third party data vendors under license to Esri for inclusion on Data and Maps for ArcGIS® for use with Esri® software. Each data vendor has its own data licensing policies and may grant varying redistribution rights to end users. Please consult the redistribution rights below for this data set provided on Data and Maps. As used herein, “Geodata” shall mean any digital data set consisting of geographic data coordinates and associated attributes. The redistribution rights for this data set: Redistribution rights are granted by the data vendor for hard-copy renditions or static, electronic map images (e.g. .gif, .jpeg, etc.) that are plotted, printed, or publicly displayed with proper metadata and source/copyright attribution to the respective data vendor(s). Geodata is redistributable with a Value-Added Software Application developed by Esri Business Partners on a royalty-free basis with proper metadata and source/copyright attribution to the respective data vendor(s). Geodata is redistributable without a Value-Added Software Application (i.e., adding the sample data to an existing, [non]commercial data set for redistribution) with proper metadata and source/copyright attribution to the respective data vendor(s). The terms and conditions below apply to all the data sets provided on Data and Maps. Proprietary Rights and Copyright: Licensee acknowledges that the Data and Related Materials contain proprietary and confidential property of Esri and its licensor(s). The Data and Related Materials are owned by Esri and its licensor(s) and are protected by United States copyright laws and applicable international copyright treaties and/or conventions. Limited Warranty and Disclaimer: Esri warrants that the media upon which the Data and Related Materials are provided will be free from defects in materials and workmanship under normal use and service for a period of ninety (90) days from the date of receipt. THE DATA AND RELATED MATERIALS ARE EXCLUDED FROM THE LIMITED WARRANTY, AND THE LICENSEE EXPRESSLY ACKNOWLEDGES THAT THE DATA CONTAINS SOME NONCONFORMITIES, DEFECTS, OR ERRORS. ESRI DOES NOT WARRANT THAT THE DATA WILL MEET LICENSEE'S NEEDS OR EXPECTATIONS; THAT THE USE OF THE DATA WILL BE UNINTERRUPTED; OR THAT ALL NONCONFORMITIES, DEFECTS, OR ERRORS CAN OR WILL BE CORRECTED. ESRI IS NOT INVITING RELIANCE ON THIS DATA, AND THE LICENSEE SHOULD ALWAYS VERIFY ACTUAL DATA. EXCEPT FOR THE LIMITED WARRANTY SET FORTH ABOVE, THE DATA AND RELATED MATERIALS CONTAINED THEREIN ARE PROVIDED "AS-IS," WITHOUT WARRANTY OF ANY KIND, EITHER EXPRESS OR IMPLIED, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE. HIGH RISK ACTIVITIES: (A) THE DATA AND RELATED MATERIALS ARE NOT FAULT-TOLERANT AND ARE NOT DESIGNED, MANUFACTURED, OR INTENDED FOR USE OR RESALE FOR INSURANCE UNDERWRITING OR WITH CRITICAL HEALTH AND SAFETY OR ONLINE CONTROL EQUIPMENT IN HAZARDOUS ENVIRONMENTS THAT REQUIRE FAIL-SAFE PERFORMANCE, INCLUDING, BUT NOT LIMITED TO THE OPERATION OF NUCLEAR FACILITIES, NAVIGATION OR GUIDANCE (I.E., AIRCRAFT, NAUTICAL VEHICLE, ETC.), OR COMMUNICATION SYSTEMS, AIR TRAFFIC CONTROL, EMERGENCY RESPONSE, TERRORISM PREVENTION OR RESPONSE, LIFE SUPPORT, OR WEAPONS SYSTEMS ("HIGH RISK ACTIVITIES"). ESRI SPECIFICALLY DISCLAIMS ANY EXPRESS OR IMPLIED WARRANTY OF FITNESS FOR HIGH RISK ACTIVITIES. (B) TO THE EXTENT PERMITTED BY LAW, LICENSEE AGREES TO INDEMNIFY, DEFEND, AND HOLD ESRI, ITS OFFICERS, DIRECTORS, EMPLOYEES, AGENTS, SUBCONTRACTORS, LICENSORS, SUCCESSORS, AND ASSIGNS HARMLESS FROM AND AGAINST ANY AND ALL LIABILITY, LOSSES, CLAIMS, EXPENSES (INCLUDING ATTORNEYS' FEES), DEMANDS, OR DAMAGES OF ANY KIND, INCLUDING DIRECT, INDIRECT, SPECIAL, PUNITIVE, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, ARISING OUT OF OR IN ANY WAY CONNECTED WITH LICENSEE'S USE OR PERMITTING THE USE BY OTHERS OF THE DATA, AND VENDOR'S HARDWARE OR SOFTWARE FOR HIGH RISK ACTIVITIES. DELIVERY OF THE DATA, AND VENDOR'S HARDWARE OR SOFTWARE DOES NOT CONSTITUTE A WAIVER OF THE RIGHTS AND OBLIGATIONS SET FORTH IN THIS ARTICLE. Exclusive Remedy and Limitation of Liability: The entire liability of Esri or its licensor(s) and Licensee's exclusive remedy shall be to terminate the Agreement upon Licensee returning the Data and Related Materials to Esri with a copy of Licensee's invoice/receipt and Esri returning the license fees paid to Licensee. IN NO EVENT SHALL ESRI AND/OR ITS LICENSOR(S) BE LIABLE FOR COSTS OF PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOST PROFITS, LOST SALES, OR BUSINESS EXPENDITURES, INVESTMENTS, OR COMMITMENTS IN CONNECTION WITH ANY BUSINESS; LOSS OF ANY GOODWILL; OR FOR ANY INDIRECT, SPECIAL, INCIDENTAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES ARISING OUT OF THIS AGREEMENT OR USE OF THE DATA AND RELATED MATERIALS, HOWEVER CAUSED, ON ANY THEORY OF LIABILITY, AND WHETHER OR NOT ESRI OR ITS LICENSOR(S) HAVE BEEN ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. THESE LIMITATIONS SHALL APPLY NOTWITHSTANDING ANY FAILURE OF ESSENTIAL PURPOSE OF ANY EXCLUSIVE REMEDY. Third Party Beneficiary: Esri's licensor(s) has (have) authorized Esri to (sub)distribute and (sub)license its (their) data as incorporated into the Data and Related Materials. As an intended third party beneficiary to this Agreement, the Esri licensor(s) is (are) entitled to directly enforce, in its own name, the rights and obligations undertaken by the Licensee and to seek all legal and equitable remedies as are afforded to Esri. In the event that the data vendor(s) has (have) granted the end user permission to redistribute the Geodata, please use proper proprietary or copyright attribution for the various data vendor(s), and provide the associated metadata file(s) with the Geodata. In compliance with FGDC metadata standards, Esri has attempted to practice proper metadata methodologies by providing any data source information, descriptions, and file names to assist in this effort. <DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN><SPAN>See Resource Constraints &gt; legal constraints.</SPAN></SPAN></P></DIV></DIV></DIV> publication date: 1992-06-01, 2002-01, 2011, 2011-10-27, 2012-11-28, 2013-08-15, 2014-05-02, 2014-07-03, 2015-05-19; ground condition: 2010, 2012-12-31 1992-06-01T00:00:00 2011-10-27T00:00:00 2012-11-28T00:00:00 2012-12-31T00:00:00 2002-01-01T00:00:00 2011-01-01T00:00:00 2010-01-01T00:00:00 2013-08-15T00:00:00 2014-07-03T00:00:00 2014-05-02T00:00:00 2015-05-19T00:00:00 Esri ArcGIS 13.3.0.52636 1 -178.217598 -66.969271 71.406235 18.921786 The dataset is converted to file geodatabase (FGDB) format using tools in ArcGIS. The geometry is checked, and if needed repaired. After processing, the data set is checked for drawing display and number of records and file sizes compared with source materials. The geospatial part of this data set was extracted from the ArcUSA 1:25M database, and then generalized. Generalizing reduces positional accuracy and the tolerance was not recorded so the positional accuracy exceeds that of the ArcUSA data set. The positional accuracy of the ArcUSA 1:25M data set is 1792 meters which is based on generalizing–to a tolerance of 500 meters–the 1:2,000,000-scale USGS Digital Line Graph (DLG) source data. Attribute data 2012 Census of Agriculture USDA Farm 2014-05-02T00:00:00 2012 U.S. Department of Agriculture (USDA), National Agricultural Statistics Service (NASS) U.S. Department of Agriculture (USDA), National Agricultural Statistics Service (NASS) Washington, DC, USA Census of Agriculture 2012 The farm fields come from data published by the U.S. Department of Agriculture (USDA), National Agricultural Statistics Service (NASS) based on the 2012 Census of Agriculture. http://www.agcensus.usda.gov/Publications/2012/ http://www.agcensus.usda.gov/Publications/2012/Online_Resources/Desktop_Application/ ground condition 2012-12-31T00:00:00 Attribute and geospatial data 25000000 ArcUSA™ 1:25M ArcUSA 1:25M 1992-06-01 1 Esri Esri Redlands, California, USA vector digital data publication date 1992-06-01 Attribute and geospatial data 100000 Dynamap/Census Boundaries v4.0 TomTom Dynamap/Census Boundaries v4.0 2002-01-01 Version 4.0 TomTom North America, Inc. Lebanon, New Hampshire, USA TomTom North America, Inc. vector digital data TomTom® Dynamap®/Census Boundaries v4.0 publication date 2002-01-01 Attribute data Summary File 1 (SF 1) U.S. Census SF 1 2011-01-01 2010 Department of Commerce, Census Bureau Department of Commerce, Census Bureau Washington, DC, USA Summary File 1 (SF 1) 2010 The Summary File 1 (SF 1) data is based on the 2010 Census of Population and Housing. http://www.census.gov/prod/cen2010/doc/sf1.pdf ground condition: 2010; publication date: 2011 2010-01-01 2011-01-01 Attribute data Esri Data; Esri Updated Demographics Esri Data 2015; 2014; 2013; 2012; 2011 Esri Esri Redlands, California, USA tabular digital data Esri® Data 2015; 2014; 2013; 2012; 2011 http://www.esri.com/ publication date 2011-10-27T00:00:00 2012-11-28T00:00:00 2013-08-15T00:00:00 2014-07-03T00:00:00 2015-05-19T00:00:00 The following steps were performed by Esri: Extracted and generalized the features from ArcUSA 1:25M. Converted to North American Datum of 1983 (NAD83) by splitting the United States into-if present: Alaska, Hawaii, Puerto Rico, U.S. Virgin Islands-and the 48 contiguous states (including District of Columbia); converting each to NAD83; then merging them together. Created ArcGIS® layer file (.lyr). Created projection file (.prj). Ran ArcView GIS Avenue™ request ExportClean, and created spatial indices. 2002-01-31 ArcUSA 1:25M The following steps were performed by Esri: Copied the Molokai coastline from U.S. Counties (Generalized). Created ArcGIS® layer file (.lyr), projection file (.prj), and spatial indices. Converted the data set to SDC. 2002-10-10 TomTom Dynamap/Census Boundaries v4.0 ArcUSA 1:25M The following steps were performed by Esri: Copied Data & Maps 10 U.S. States (Generalized) and renamed it. Removed all fields but STATE_NAME. Attached and formatted the fields from Data & Maps 2012 U.S. States. Converted the data set to SDC. Created ArcGIS® layer file (.lyr), projection file (.prj), and spatial indices. 2012-02-07 Esri Data ArcUSA 1:25M TomTom Dynamap/Census Boundaries v4.0 U.S. Census SF 1 USDA Farm The following steps were performed by Esri: Deleted the fields POP2000 and POP00_SQMI. Added the field POP2012 and added and calculated the field POP12_SQMI. Converted the data set to SDC. 2013-03-28T00:00:00 Esri Data The following steps were performed by Esri: Deleted the fields POP2012 and POP12_SQMI. Added the field POP2013 and added and calculated the field POP13_SQMI. Replaced the fields NO_FARMS07, AVG_SIZE07, CROP_ACR07, and AVG_SALE07 with the fields NO_FARMS12, AVE_SIZE12, CROP_ACR12, and AVE_SALE12 from the 2012 Census of Agriculture. Put "-99" values into these fields for records where there were no matches. Converted the dataset into a file geodatabase. 2014-08-20T00:00:00 Sources: 1) Esri Data; 2) USDA Farm. The following steps were performed by Esri: Deleted the fields POP2013 and POP13_SQMI. Added the field POPULATION (alias POP2014) and added and calculated the field POP_SQMI (alias POP14_SQMI). Placed them just after the STATE_ABBR field so that all the 2010 Census fields are together. Put "-99" values into these fields for records where there were no matches. 2015-08-24T00:00:00 Esri Data The following steps were performed by Esri: Deleted the fields POP2014 and POP14_SQMI. Added the field POPULATION (alias POP2015) and added and calculated the field POP_SQMI (alias POP15_SQMI). Put "-99" values into these fields for records where there were no matches. 2016-08-10T00:00:00 Esri Data dataset EPSG 6.2(3.0.1) 0 20241211