20210806 12085000 1.0 FALSE NH_TS_US_Cleaned_0621 002 file://\\MAGGARWAL1\C$\Users\mohi9282\Documents\ArcGIS\Projects\PPE_Shortage\PPE_Shortage.gdb Local Area Network Projected GCS_WGS_1984 Linear Unit: Meter (1.000000) WGS_1984_Web_Mercator_Auxiliary_Sphere <ProjectedCoordinateSystem xsi:type='typens:ProjectedCoordinateSystem' xmlns:xsi='http://www.w3.org/2001/XMLSchema-instance' xmlns:xs='http://www.w3.org/2001/XMLSchema' xmlns:typens='http://www.esri.com/schemas/ArcGIS/2.8.0'><WKT>PROJCS[&quot;WGS_1984_Web_Mercator_Auxiliary_Sphere&quot;,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]],PROJECTION[&quot;Mercator_Auxiliary_Sphere&quot;],PARAMETER[&quot;False_Easting&quot;,0.0],PARAMETER[&quot;False_Northing&quot;,0.0],PARAMETER[&quot;Central_Meridian&quot;,0.0],PARAMETER[&quot;Standard_Parallel_1&quot;,0.0],PARAMETER[&quot;Auxiliary_Sphere_Type&quot;,0.0],UNIT[&quot;Meter&quot;,1.0],AUTHORITY[&quot;EPSG&quot;,3857]]</WKT><XOrigin>-20037700</XOrigin><YOrigin>-30241100</YOrigin><XYScale>148923141.92838538</XYScale><ZOrigin>-100000</ZOrigin><ZScale>10000</ZScale><MOrigin>-100000</MOrigin><MScale>10000</MScale><XYTolerance>0.001</XYTolerance><ZTolerance>0.001</ZTolerance><MTolerance>0.001</MTolerance><HighPrecision>true</HighPrecision><WKID>102100</WKID><LatestWKID>3857</LatestWKID></ProjectedCoordinateSystem> FeatureClassToFeatureClass NH_TS_US_Cleaned_0621\abee8ad7 C:\Users\mohi9282\Documents\ArcGIS\Projects\PPE_Shortage\PPE_Shortage.gdb NH_TS_US_Cleaned_0621 # "county "county" true true false 46 Text 0 0,First,#,NH_TS_US_Cleaned_0621\abee8ad7,county,0,46;provider_state "provider_state" true true false 4 Text 0 0,First,#,NH_TS_US_Cleaned_0621\abee8ad7,provider_state,0,4;initial_covid_case "initial_covid_case" true true false 0 Double 0 0,First,#,NH_TS_US_Cleaned_0621\abee8ad7,initial_covid_case,-1,-1;threeormore_cases_this_week "threeormore_cases_this_week" true true false 0 Double 0 0,First,#,NH_TS_US_Cleaned_0621\abee8ad7,threeormore_cases_this_week,-1,-1;oneweek_ppe_shortage "oneweek_ppe_shortage" true true false 0 Double 0 0,First,#,NH_TS_US_Cleaned_0621\abee8ad7,oneweek_ppe_shortage,-1,-1;total_staff_shortage "total_staff_shortage" true true false 0 Double 0 0,First,#,NH_TS_US_Cleaned_0621\abee8ad7,total_staff_shortage,-1,-1;shortage_of_nursing_staff "shortage_of_nursing_staff" true true false 0 Double 0 0,First,#,NH_TS_US_Cleaned_0621\abee8ad7,shortage_of_nursing_staff,-1,-1;oneweek_shortage_of_n95_masks "oneweek_shortage_of_n95_masks" true true false 0 Double 0 0,First,#,NH_TS_US_Cleaned_0621\abee8ad7,oneweek_shortage_of_n95_masks,-1,-1;staff_total_confirmed_covid19 "staff_total_confirmed_covid19" true true false 0 Double 0 0,First,#,NH_TS_US_Cleaned_0621\abee8ad7,staff_total_confirmed_covid19,-1,-1;staff_total_covid19_deaths "staff_total_covid19_deaths" true true false 0 Double 0 0,First,#,NH_TS_US_Cleaned_0621\abee8ad7,staff_total_covid19_deaths,-1,-1;residents_total_admissions_covi "residents_total_admissions_covid19" true true false 0 Double 0 0,First,#,NH_TS_US_Cleaned_0621\abee8ad7,residents_total_admissions_covi,-1,-1;weekly_resident_confirmed_covid "weekly_resident_confirmed_covid19_cases_per_1000_residents" true true false 0 Double 0 0,First,#,NH_TS_US_Cleaned_0621\abee8ad7,weekly_resident_confirmed_covid,-1,-1;weekly_resident_covid19_deaths_ "weekly_resident_covid19_deaths_per_1000_residents" true true false 0 Double 0 0,First,#,NH_TS_US_Cleaned_0621\abee8ad7,weekly_resident_covid19_deaths_,-1,-1;total_number_of_occupied_beds "total_number_of_occupied_beds" true true false 0 Double 0 0,First,#,NH_TS_US_Cleaned_0621\abee8ad7,total_number_of_occupied_beds,-1,-1;week_ending "week_ending" true true false 29 Date 0 0,First,#,NH_TS_US_Cleaned_0621\abee8ad7,week_ending,-1,-1" # 20210806 12085000 20210806 12085000 Microsoft Windows 10 Version 10.0 (Build 18363) ; Esri ArcGIS 12.8.0.29751 NH_TS_US_Cleaned_0621 Time Series Raw data for Covid-19 Nursing Home Resident Deaths sample File Geodatabase Feature Class dataset EPSG 6.18.3(9.3.1.2) 0 Simple FALSE 0 TRUE FALSE NH_TS_US_Cleaned_0621 Feature Class 0 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. county county String 46 0 0 provider_state provider_state String 4 0 0 initial_covid_case initial_covid_case Double 8 0 0 threeormore_cases_this_week threeormore_cases_this_week Double 8 0 0 oneweek_ppe_shortage oneweek_ppe_shortage Double 8 0 0 total_staff_shortage total_staff_shortage Double 8 0 0 shortage_of_nursing_staff shortage_of_nursing_staff Double 8 0 0 oneweek_shortage_of_n95_masks oneweek_shortage_of_n95_masks Double 8 0 0 staff_total_confirmed_covid19 staff_total_confirmed_covid19 Double 8 0 0 staff_total_covid19_deaths staff_total_covid19_deaths Double 8 0 0 residents_total_admissions_covi residents_total_admissions_covid19 Double 8 0 0 weekly_resident_confirmed_covid weekly_resident_confirmed_covid19_cases_per_1000_residents Double 8 0 0 weekly_resident_covid19_deaths_ weekly_resident_covid19_deaths_per_1000_residents Double 8 0 0 total_number_of_occupied_beds total_number_of_occupied_beds Double 8 0 0 week_ending week_ending Date 8 0 0 20210806 /9j/4AAQSkZJRgABAQEAAQABAAD/2wBDAAgGBgcGBQgHBwcJCQgKDBQNDAsLDBkSEw8UHRofHh0a HBwgJC4nICIsIxwcKDcpLDAxNDQ0Hyc5PTgyPC4zNDL/2wBDAQkJCQwLDBgNDRgyIRwhMjIyMjIy MjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjL/wAARCADIASwDASIA AhEBAxEB/8QAHwAAAQUBAQEBAQEAAAAAAAAAAAECAwQFBgcICQoL/8QAtRAAAgEDAwIEAwUFBAQA AAF9AQIDAAQRBRIhMUEGE1FhByJxFDKBkaEII0KxwRVS0fAkM2JyggkKFhcYGRolJicoKSo0NTY3 ODk6Q0RFRkdISUpTVFVWV1hZWmNkZWZnaGlqc3R1dnd4eXqDhIWGh4iJipKTlJWWl5iZmqKjpKWm p6ipqrKztLW2t7i5usLDxMXGx8jJytLT1NXW19jZ2uHi4+Tl5ufo6erx8vP09fb3+Pn6/8QAHwEA AwEBAQEBAQEBAQAAAAAAAAECAwQFBgcICQoL/8QAtREAAgECBAQDBAcFBAQAAQJ3AAECAxEEBSEx BhJBUQdhcRMiMoEIFEKRobHBCSMzUvAVYnLRChYkNOEl8RcYGRomJygpKjU2Nzg5OkNERUZHSElK U1RVVldYWVpjZGVmZ2hpanN0dXZ3eHl6goOEhYaHiImKkpOUlZaXmJmaoqOkpaanqKmqsrO0tba3 uLm6wsPExcbHyMnK0tPU1dbX2Nna4uPk5ebn6Onq8vP09fb3+Pn6/9oADAMBAAIRAxEAPwD2N5Vh iMjgsseScL1GOeKdp90l7bpPEG8uQEoHUqce4NV7q+htZoI33ZnJVcDIz15/Kp1eOIgGRIy5+QE9 T6CrlExhPv1LZcogAyCelOKqw5xu71AgMkayA8seh+tTeWuTzg54rDU1EVMZBAz61HIgV+g6c1JM pIDA9P1ob95GCeCKTWlg8hFO4cdqQcE5HFRpktwetS545PSs0SCZJPNIwbOKF6jHFKO9PSwCFCyF Q+w44PpVRrSdn5mU+5QVcJzQeoq4zcdhOKe5FHHKp/eSBhjptxUy/LnHFGOKU47Um29WNKwYJBPp TR0peShx0pqDAOO5o5dLhfWw/cfWnCQ7hnpTdvUmkpXaGSuhJytMp0bYyCeKaxAY45rppzvuZzj1 QUUgYGlrW9zMMA9qKKKBBSxnbL83Q9KaeBS+1Jq6GnZ3LNJTYmLIM9afWDOlO6uIelV/KZdzlsse 1WKhlzuo5uXUUknuMRfOHHC9zTpYgIwozgDFSQjCYpzjIFNychRikirG2U5PI4qGdR2qaVNsoYKM d6bJGNnFdEJdTmqRtoUnHFR0P5yn5igFRjzdwyU2+1dCZzNElFFFUItIA6lD17H0qvcWcU7RedCr tE3mRk/wmpQcHIqSZTIodc7sYPuKwnE2hIdHJhCyjG0ZIpHlZmP+ycVRtLD7B5zR+YfPcu29sgE+ ntV54Qp2g9RXHWjZHXGTkrCrMcEE/Smq5+YZPTIpqKSM4zjinbeM1zXYx8TEkA9ulWdqsSCARVTa T0qaKQqSpHNVF9xolMYUZHamEYGTxmhpc5Apo3uQDyPpTbXQYuQD1BFHcZp3lqOuM+lJsIbJ6E0W YDyy+XtBGaRRnIzj3pR2UUZU87ckcGmANHuCqD8o5470JjOSMelVZUuZJS0coRAjALnv2NVktL8N G0l0DtXDAdCfWqvoFuppuxIFMHIzWclrf7o2kuVbapDYzgnJ/pir1lHJBaqsziaToXHcUrX1Ad1p aXKsCRwR2pMc9c1IhuM/SnA460UU4zcXoJq47OaKZijJyOa6I1U9DNwaCXPlnAyaSMtsy3H+FPJw CaVcFcsR9K0lJR3EotskiOF54yakBz0qBW55NTL0znrXOpcx0LYU9OKjZd4yetOOCcZpQMLg0bjI txCYxyKkJyAaaFO4kdPSnHOMYoSsBXuomcB1J+Xkgd6aHBXI6dxVontVcwNvZlfrzg9K1hNLRmNS F9UVpog65K5quUAXCgD6Vod9pFRmMNk4rojM5ZQKFFWJIgOagYAHFbJ3MmrD1PapkfapzVWpVbIq ZRuhxlZ3LTKJoMKfxohlJmwV4A21HCdu4dj2p06HaJV4YVzyh0OmM+qJXbyjsUDBqPf27fSnGNmj 3E5J5yKFGScjpXDNNM6Nw3E9OPSpOCeRtamBcAsOfaqlyZDKlwgJaPque1OPmNFraFGSetTwsNvA qvHKs8Q2qeecMMYqWDKyFGNNKzDqU5tH+2zme4mlRugWN8DA6Ux9AjYAfa7rrn7/AP8AWq8dSslb a1zGp56tjpUkN3b3JHkTRyY5+Vs1oUR21n9mhEayO4Bzlzk1IIsbsN19qmI9OKXGBilyoVis6bFy TUTMdvXGauOu5cZxVV0VSQxyT0FTazv0JktBq4ZduSOPzqVfu46VErjAxncO1SRtluR+FXNKxEXq RlsZUDn1pA5AwKV8fjTK5m7MomZyCFwM+tPK8AjvVbJJ5pyyEYB5FNS7juS0h9fSnMMAcYpMcc96 paO4NC7himx4AIPYmlBAzxzSLzk+tdFV3hcyhpIl3LjG2hZD/wDWpFII5pV+VvasTcXaScg8+lP5 28UqkYJAqN5WXov1qtEAofnb3oaTbx+tN3oxBBG4UyQlsAj60m+wEjS49KjZ/M4zhcdqAADyM+lG 3jJGBSUmhPUYUYYKYA70I+VyR3wcU4H1piYUMM55zW1Ft7mVRJajZAGziqjJ81W6aUBOa64uxyyV ylSqcGkoxWxkTA45FWBKChGOcVUQ9qkBINZyjcuMrAJXjUqMlO3tViCRWjJ4zn+tRlPMXKde49ag kLxRnHUAgVxyTvZnXCdkWCzBwQcA00qM4YdRnmuW0W9tPEL3bK13FPby7JY94wD7flV2WCzS+Wyl vboTzLuRN45A69q5tLmxpwM6XbRcBMExge1XSWYAhiu/jd6Viz31rb6fJOkwb7IcMxPQjqDVi01u 0mljgUOcx+YJMfJ6Yz68073GjRk0XT51/eWsbMRy2OTVi3sbazb/AEeJYweMKOKZJqFvA8McrbHm bbGD/EfQUt3fwWUBnuW8qJD8ztwBWoy3RVaG9inijliO9JBlCP4h7U+S4EcbOyPtUZPFAExppUMT 0yOlZcXiC2mFmyRT+XdAlHZMBeM8+lNuPEdjaPdCQSn7OFMm1M4Bzj+VK6CxpMpDqxGSODjvSMh8 3IHGOtY9z4v0q30z7ekjTxE4AiG4nnHSqJ+IWgS2yus029lDLGI8s2fQUOaSsLlOhddo5xzUQ61n 23iGwurRpJJDA0ah3WUbSoJIGfyq+CrIrKQQwyCKwlvoS1YU9elJSsSR16UckZx1oUbq6JvqSCdj gNyBT+G5BxUFFLmfUdyUgZIz+NPzj5sZqEIxGRzUuW78e1Um7DQocu2CABU275eMZ7VXLd2FNaYn GBTUrDuTGUKwDfjUbv8AK21uKNhX7wz754ppA2lVOT7U/eegmyIZyMdakDyMQDxj1pmSo96cshLY xzWkaUdr6mfO0Sjnq3T2oJ4KrnPqe1N3ZPXFGc8E8DvWqorcTqMTCqMDt1JpE4Q+9LjzO3yn9aYI n3HD4Xr0oU1zaicXbQWil3BxlTkDjNJg1uYtFClBxSUV0GBInSnU2PpTqljHxsVasPxNiG2up7zW RY20kY8vbhXDDk49c+lbI61zfje3trqDTvtaI0UUrSMzlgFAXOcgGubEr3Gzeg/esecfDae7m8U6 glvdS+Q8TSPIp5JBGN2enX9a7XRJrW78UWN9dz3q3M3mQQrKAYzg84Pvn9KreEfEugv4aiSK3a2J f7NIVQsQSDgkj1xT7yw1XwtBphby9QsortpYyITujU8/nk150L2O7qauvWmptqs2nWOi276c22ae VZPLeQ5BOMEZ9Kp61ayR6WltaaJKxuXFzP8AvcBCpHBOferMWk6p4i+yaxd3SWN2C42w/MY1OQAS DyRx+VaV/pV7d+GJtNkvEluXUL57DaMZB5/AGiXkJ6GjJZpqemQLIXhIVZFaNvmU46A1Ya5tr/R3 l1ezSC3BJeK7AIAB4Jzx71y+oNqNpfafYzXaWmk+SiieOUBi47nPY10Eeu6XqD3dodzrbIxm3Rna VHXBxz+FaRemo0i8unWNy1pcxoMW6nyDE21QD7DioF05dMC3UmpXAt4N7yLI+4HJzyT6VS07xbY3 gkjtLS8WOORYUkaAhWJBII74GPTuKtw/bYrqH+1L+22yhoxAq8O244wT7EVd09gMFrQeJZxqFze2 8mkElNiTnaB/AwweGziktrdb/XpVsrmaKztYPs21pSVnYg8YJ5x6itHX9Km/s+4tdP0u2ntZEZnh ztLSZ4IHTrz1rJ0vwlZ2miRanLpgg1WFC+HfCq34Z4qLO9hmHfeH9X8O6WzwvCkyJjy0IxcLuJII 68A9a5G2v9Y8N+JrSK4sT9oSQCKBF4IJ7H39RW1f+KLrUfDkv2j7HcXcdw6xyzNn92euB19QPpXI a9eRXD2MjnN1b2yF33kmQ8cZ7YrCcluikenT65qt1od3cazo8Jt/tSRoApLEcnnb6cfnUlj4l1KK /dtVtpNPsxIUhiaLDzA8KFGM8cV5Lo3i+80u8jaK5nWJWJdC33h6V0uma7pWqayupXE9wdRu3kST zGwkEZyAR7gYxihVE+pLR7HCbmG3up9QeOOFCWQrz8g7n3pLfV7a8sIrixnLRSjKMVPPOK4Hw94m e2N3pepXs11MYZEjjdcIAo7nJPI9qZoGrTzeXFa3F7aylTHFZLFviXBJyGyOufauqFeKskjGUGej QS7jtZyzHkfLjAqxXI6tq9xbm3ivbt7SW9dBGkahpLfgZ3c8jOa6m1mjuYUkidZEI4cHg1M4c0vd QlotSUdcZwKmEgj3cg00hQPmXBqM9eOnvUNOOhSfYUkk8000/wAtvSq9zJNEg8iETTZyIs4JHc1K i2wsTlyAAWOKzNZ1210O1E9yJSpYLmNC38qfJf6ksIL6WAxHQyDr7VmaleQT2Z03U4RC92DHEjMP mbBPUdOlXL3VoO3c3IZ1ureKeJ90cihlPqDVqEdTVLSYJI9LtYnjWNoolQorbgMDHX8KuspDfKck ckVpQ31Imh7AcDHWoz8px1FHmkKS3b0FEQLqSRgHkV1J30MWh4faPucfWmrOwyDF9MUo+VsGnhQO gqfZxRSnIhhUjkgYbn6VPSBQOlLVCMmiiius5BytjrUgINQ0o60rBclziuT+IM8z6NcafDNGpks5 ZtmDvO1SePbjmuqYZH0rmfE9ij3o1D7aUaK0aNoY13yYJPIX05rlxelPQ6KHxmLoKf8ACKfDizub KzS6url0cJs3BmY/0Ga9EnnvH0gSraK1wYwfIc4G7uKztF1vSbuG0isZU2yIfKQJt+7jIx2xW7a3 1tfRNJbyLIqMUbac4YdRXBTWlrnajldW1rS/DQtNPuCbNr1mJdTkRs2cnJ9zWzbWanSlgnuDcBk2 mUnBfPfil17w1pniW1ih1K380RtuUBiCD9RXL+I49X0TSrOytLOa+tTN8wt1IaKMEYHy1Uk1qOxu 3uk6JFZrPqEKvBaRFQ8rkhV/xqzYy21/pC3FkmEkj+RSu04xxmuU8T3d1qNhpxu7X7Fo7HfNFPKE lkYEgJyfbP41p6Fd3WqxSalp9i0K3EiKVmkIAQcEqueCKV9bIGUrS81+21U6dd3Mfm3kEkkHlKNs BXAx75z+ldDYzXklhph1DT3luskPIQP3ZH8R44z1qLQtL1KPVby/1ZLbzCPJhaIfNs681ZbUtStZ P9Ls4IrUT7BKZgAI8D5jk9evHtVLRajOctPHtxF4mfT9StUEMzbIRbku6MDg7vxrpbrWbe6h1C0t Uae5twEkhztJ3ehP4/lWHrVxaaZqkOraPBBdX7yfZmiifG4k5O7Hf602607VZ1Fxc/ZBfzSCVLbc FZQoI4I5bGffrSTa0A43Wba20LUlW5WMQsViEYKM/wDeO75eOvavNNQuxd3exl/cxttXGAxUdsiu x8X2N/eFZJNPv7cW6SM91NEczHJxlvpgc15spJwUJODknd+tclV62KQXK7t5HCk8HPapYGSOWNpl bZvXKx8MR7Zz+uai8whHbzCH9OeaXBkOGwVB45wB+dZepR0covEh/tuC6RtrKS3mfNlv4SO9b3w7 u7l9X1HVZ7h2SxtzLtLHaGJOMjPsa89ZsE7jtyMDjn9K9H+HV5Zx+F/EizLgtAod+hA+bA+n+Jre jrNET2MTUtdum1xtWub43NxtDAqvCBlB2/hnH4V6f8LtUgGk/ZJb2MyPKXghY/Psx/KvBJbhngCO FZVzgK27kc8kV2vwvtdXfxRFLptvHKkcZMpcjao+v+FVRm1UT7inFOJ9IGE7Rubjr9Ky7jUYoZmj aCXgnBUbgR61l614qfR7LdqbWcK4+ZRLliPYd68RufHXiK41W4NpqsqW/mEou4cKD+ldNWcV8ZEY dj2LXvEksssGlabdGzu52+9LH1GOQD2NcbrnjDX9AijiiupjIkpDNcRrvcADgY7Vw6eKNeuyqC5a d45xPtKb2VgDyD1A55FQeI9au73VI73UlSczQ7j5ICHPQHjv259K5pVL/CWonVaL8Qtbjhnml/0y by22+Y3ygjkkAegFUfDR1/XtfsryGOW7ljkLuJmJiUYOM/ma4ewZrrUraEblR5VSQM+0cnBHoBX0 9pUd7ZafDDp9jZpbhBjY4wffI61VGm6j1exM5cpJoljq1t511qt4kssv3YYxhIvp61sozMeACe5p YyWiAlUBiOQOlKXSMYGPwrvVO1ktjmc+rAR5++2727U/IFQNcqo4FV3uGbvWsab6GcqiLUsqDvzU X2o7h6VUzmitlBGTqM045VkHHWn1mJIUPBq0t0Mc1nKDWxpGonuUqKOaK3MApR1pKKAHk9hWTcya dF4ltzLDOb1rZtrKPkKDPB9606yPEz3cNjHqNnaR3EtkTMVdmBwBnjBGfpXPiY3puxtRfvlXTdfi cTzWjRtGs4jdJEETWoIPJz15ArqNGiSHSl23KXCszP54G0Nk/wCR+FeKaj43ij8QR6gthGdJvMeb HIMea478+hP6111p4s1C91qfSILCFbF4kWBVUlPm55IIxXlwnqejY7xNXWO+EFxbvGkkgS3lHzLJ kZzx0qxaXhu4pJGtpYSrlNsgGTjvwelPt44LS2ht0CBY1CqAc7QB71FdXVwl5BFFal4XB8ybdjYe 3Het/UDkvircpZeExuIzJMnUds889qnt7i2Gmz6n/acdpFcoIrSeM52p2O04+apfH0pPh57aeBHt Z18ovwXDnoFHvSaPYxLpo/tO1iTT7MhbaK4jwUCjbuPY5qJfEBr3gtovDiW2oX8hWRRH9pOQzN1B 4+lc/rmrDT/Dlo1zqFjc2rhlLXCkCYg4UDGcVW8ReMZodWj0i3toYpCQUa6jJjlXuV5GMCs34ow2 N14JQ/aLeI2xV9sa5zu7LjpznmlKW9hC6rbrb6zaaxYG1juJ4PMxDMSM7cliNvT06ZqG08f6jczx yS6ZazXNsrrvaTbJz3AI6cetbOlwWN7oY8/QpkX7AN12GKCRUXIAx0ziuBXwxdXFzbX4hm8tnfCw yBpAgHyggj61Erp3RRX8WeNpdXhh+zTzJcXMJjvY0+5nJGAPpivPZ1PklI423j1PB966a58nMjpY xxPb7g4kJ3MSTzkEc1gSFlbjjngle1cspO92UiLy55YN4AIUZJAzSMCoQbcBWBB7A063vXVpIYz8 jHDj6dD9OaJHYuSz425OFHHTNSxjJRHHcExyyOrHamRgke/WnQz3McVwkc8kcUoVZAO+M4FR7lDB RyQecnB6GnB2KuVAPmD73p7Y/Cnd9BDIfMjIUyEsWwCO471q6T4m1fw7atDpl20AlP70r3H9KyG2 RlMcqeff1/CkKKrjcWVSerc8+lVFtO6Bq5Lc39xf3kt1czNNNu5LsTV+yu4bJZZB/rAhUAjhg3By e3WoIbETW+6GF5Jud2M4A9arz27wDy3dSX6rngD0pN3dwHG+ZbprhcwjplTjj0/z606CK71acrDa zTTdAigsMds4+tQeU10rIgViwwOOnsK92+G/hfV/C2gib7NC1xd4YtKfmRccDjHvW1Kn7R2JlLlR zOj/AAUvrrT47m8u0tpWGRCB69z6GvY/DmlSaLokGnySeZ5I2hs5yKfb3N6277SkSemw1I9wxGM1 6lPDqOqOKda+jLM0oRD61QZyTSMxbqaSumMbHNKfMFISB1phYk8cUhznmtEiLilz2pwcd6jop2Qr jt/zZqTNQ0uT60NBcVW55pxIGMVHSg4NFguSZ4paYGycYp9SMKdGQG5GQeCDTaKT1GtD5z8X+Gpd K8VXVidyRsxktlHIkUnI5HevRvAWpW99byaPPbXLXVsnmDzX2u2B93Gc4rrPEGgafqEB1KaFjd2a +bG8Yy3y84/HpXKa7LDctoXjLS7e5WVm8q5WIAlQD0YDua8ipSdKbtsepSqKcTu9IsLDUrOO4eKS KR15jMuSvscHrW7Iwhgc4JCrnA5JArmdCJXcksEVh5pLIqThy7Ny2PoSfyqlNHP4X1xNQvPEEkum OnleRIm9ix5GMfSqvoWamkag/iI3Tz2e2yhmCwCeIq24DlsEevpWrqFs8+lTQRww3DEfLFOPkY+9 F1qNja6Ub6edUgCCTjAOOvSp7HU7PUkX7NKGfy1kK4wQCMjP50JJaCOO1DV9PPiGLTr3Qmlu4IWa F0CtlcANtHXHas++0ltUGoWdx4fhSAW6yW8yjYemQhI7g10smpaVZal9t1ex+y3Ss0ME7rkunXgj pWNDqGoeI797m1t2n06OYxxvHL5ZAPDbhg5xjP41m0hlXSNHln8Opquk6xqpBhCrZrL0IGMAse1c hNeQ2uuxXUG430UY3/aIcs8zEqVZsemK9bm8P29tpNvDb3LWzWanypXOQpxjLdM9a8gvJgJZFmL3 RicZuYjgO+flLZHbnvU1FZIaM3xV4YewtBqD3dowkODHb8bZP4hgdMVn6JpjXnhTWriaW3VLV1OG Qb2bp8prT8T32nWf9oWkFxeSXMqiRpJNpUMVGV4Jzn1rhBJM8RhGcN94AkDjpn1rCVk9hlp76AJG v2KBNkeHwcGQ56/WrFhpttNcs9+JrON43kjxGTk87QPXsM1RsbaB7jZeSSgMvVItx/mK1ZNduYbn yYL0zQqvlqSgDbcYIx29Km/cZjNHHC6YctldvQ9O30qIqGUozFuCT3/z0qZgn2jDNvJHAH8JPrTC mQQC27nIHQ+1R1AYiEOwjOAP4R398+tSRhWnXKrvb5QwPX8f60iK4cIpJZTnJOMe9RkuoGWxxxg5 Oc9KYGpaapcaNM0tnL5UittIHOR6e4qC62SmWTyPMkdS20ngH2FU1dHZQ7OzdR8uBSxu+SoGXCYy T3//AFUagd78OPDNp4m1GIyzRR/Y5BM0IPzOvt9CB+de/TSADYOFXivJfhFokccp1W0mIkA8u5Vl 42nkBTnrkelepStuc4r2MFD3L2ODEy1sNLE0lFNLAV3nIOyKa2e1ICC2aVs9jTENJJ6ikPPNPXPr QRwcCncViOinH7tNpiCilGM804qKLjEKknpRtNSYoqbjsMCHrT6KKVwCiiigYqnGQeQRgiuM13wB N5Ms/h/WLnTi26RoAxaNj349a7KpopONprKrTjNao0p1HF6HznpX/CU/27ZW8BmW7iUywLMeCvU4 z1Nezy6Lb6nY6fDKtw1wJQLn7PN/qmwSc5z6Y/Gte68OaZqWt2ep3UJa5tRtjYNjj3qaHw9p8N4Z lEiTifzyVc/M2CMkfia8/wBi4O17noQqKSucl8RdP03SNLtbiWwvruIMUIjnICdMFs9a1vD0txPp 9kbW6kiaJUeZ5rdVMsbLlUzjtkV1txDHeWr29zCk0DjDKRkEe4rgyb+w1a6tNbt3n0R5mmgZUZvI VTlFAA46DiplGzuXudfq09r/AGXMbvyQAnBkGQpPANVNHm0/RtPtNKWSAXHlGby4c/MCSSwySfWi 80hb+8ivLVvKdo9kpKfeXHygZ6YPNZ/hSyvvMuv7asVF9bMYI7xiC80XUHP409bgZvjHyvE/huG9 h1d7G38l5BA/ymYgcA/yrgfD92buC407UI2g0mYLI7Sg7k6gBD712vifw9pVrpKaX9mubm+DM9my Jjy2ZuF3dAMn1rlfEWk6vpuhpEzqZIQGltrdsGItxye+cHp6VjNO9xnH6zZKbj7RawxpZyO0UUj5 VDt43ZJ5PH51jR3scOqOzscISuIwCN2CBjORV/UFv47G2hlcPAqMiozq3lgkk9+DkmsPyicYdN4O VXtjpmuZtJlHUal4m+12EdpaaZbWir/rHjT94TjqSf6VQso7e2u7a+dWlt8BsnBIbPORjpn9Kzra C4unEcEcmWbaNo71ZOmzjUZbaaORJIDlwMZ+p9v/ANdJNt6gVZE8+4OyPMjPtQdN3pUNzA0CtvbY +7BQnkY9qsz7muHLbQVIIKjj8vatt7G2GkSXM9zJNdSjdCYvm2gcHcO3alHcDmmJKllBO7jPU8j/ ABpF3nYdjHJAGwdTViZLYwqIizSknLkYI7AU1Q4U7VKnj73HfrSegyZEZpWtYZEcyFVPyYIPPA71 6D4N+GV/qElrd321NN87zCGGHdR2+h6fStH4aeAIr+3/ALX1ZY5YSwa3VWyQQTkn26cV7EzZ+leh Qw1/ekc1WtbRGZZ6Vp2h2rW2mWqW8btuYKScn3Jp5OOtSytuNVnPOK9anFJWR585Nu4F89KbRRWp kKAT0qQL701OlPqWykhAMUGlqNm9KEArADkHFMoycYoqkIKUE9qSigRNRRRUFhRRRQAUUUUAFHSi igCaOQ+vNXAAwEi/fxhvcVm1dt5crgctWNWOlzejOzsWoJVJI9f50s4yvKgg8EEVDKnlPvHQ/wA6 kWXzlKnrXLNXXMjqjK3usRGO7GOBT3xIpx1HSoFYrJ2z6VYiwTu9axi7miZUu7e1vUT7TEHZHVgD 1DA5FY+tWuitqUE+o2sklxIhWNV+623nn3/xro2ClyxAyBVG/wBOh1axe2lZ1BbIdGKkH6im1co+ e/iLqdleXsNtZWkdrahS6oqkN5jddx+ua4zbLbo8e1FMWRxz83+HWvXPFljo+naXqRlS5m1DzBbx efGPl7lhx05q78OfAUJsZL3XdNCuTtjSRSCVz1INcvspTnZBKairs878J+C9a8URh7GYRQI2GnbI /HFbGs/C3xTYO8sX+moTjfG+XIPqD6fWve7S3tLGEQ2kEcMY6LGoAqYyrXWsHG1nuYOu7nz34U+G mqa5cSnUZH0+OM8MYc7z6Dmuy/4UtZxgCHWp0J+8THnP69K9OeUHiofMKnPWtYYOmlaxnLESueRX XwkvFupLW32vCNgS4ztBBxuJHPPXvXM+JPDmoeDJJ7WRopIbtQqyleozng9jxX0XBKHHFeO/HB7v 7XpabM2zK4Bx/FxXPXw8IRcktTalVcmkdT8JtTjvPBUdr5itNaOyOB1wTkE/n+ldweleIfCu8i0P xClk1yrjU4QzqVxskBIC/lzXtzA46cV04aXNTRjWVpFJ8eYQDTWXIp8g/eGmk4ruRxshopWOW4pK sgVTg1JkVFRSaHccX9KbRSFhTSELRSbgaXNABS4pKUfSgCWikzS1BYUUUUAFFFFABRRRQAUqsVYE UlFAGlGyyoAeh7VGcxSEHqPSq0Muw4PT+VWpHEi7s5b+dc7jyvyOlS54+Y91DoHXqOvrSW8hLYPT +VRRSYPvSsCjbh90+lclWm4SutjenU5i794Y7evrUE7GGJ5FUttHAFU/tGpu7mOKEKGOzJPIwcZ/ HFSF9QDDdFFg4B5P40jc5nUvCGq3bT32ma19nublfm3pkH0yfYYqzpWna9Fo0SX+og3S8MRlg3oc muis2ZfNibojHH0NRzscYrSjBN3MK07IriVlAB5IHJ9aR7jaM7SfpTKa6b8fMwwc8V3cqOC7F+0H qUbk4p5YkUsNkzkEswGfWrTwAL0pcyTKUW1chtWxLj1ql4r8N2/ifQ5bGUIJfvQysM+Ww7j9R+NW ghVgalluXji+UZc8AGs6sUy6UraHlOo+C4bTxR4b06xV0u4wZrqeNu3TIz24r0g6VcxIM6pOwxwM VEG1A3Pntp8Hnj5BJvOdv5VqWxuJ7dXnjWOQMRtByMZrnp04x2OicpMrsrKcN1qJz2rQnjyNxFUJ EIbiu6EkzinGxHRRRWhmFFFFACEU3b3p9FMBmPXg04UEZoAxQAtKBkdaSnAHFJjEyacretMoosIm oqNWx1qQHIqGirhRRRQMKKKKACiiigApwLdATTaUHbSAfnaQKuQyI0eG6dDVE/NUkLhcqw4NZ1Y3 izSnLlkSS3DWkJ8qNpW/hReSfWq0+tT4OzS7w7cZPlnmrgOxlfaDt4DelTrO5OPL9ya85aaM9FMx 4ddYSy5066ycZXYfQVflBYBsEZ7GoL6BtSl8pZJIQp4kTv7VVi066NzIh1GdxHj73etaU+VmdWHN En2kkgVbtoV2bmGTVCDTJoboSfaXKd07GtZAEXGetdcp3RyRhZjwM8AUjgheRx65phcAgDkk0y5f auAcgfzrlhNznZHRJKMbsgaQI/TNPF0hHzD6Yqqck0EFTzXa4J7nIptbFmW9kZNqBSf9oVDAuoea DiMp3+am71UdCTTluSo2qh/Gs5Uf5TSNbpLUsylwNsifQ1Awyp4p/wBrmcYIUj6UgAPL4FNXS1FK zfusia3ym4HNVyCvWkmvDC8qrayyKp+V4yCD+tRy3Vw4kVLGcsg4yBg/jmnGvHa4pUJ9iSiqX2u4 BAaynBzjgD/Gr3kzBckVupRezMXCS3EopuWBwwIpwwe9MkXBxmkpS3GKAO9AABmnhSO9MA9KkHSk xoiwTS7T6UUUXCw8LSiiipGLRRRQMKKKKACiiigAooooAKcDkYoooAUSFeOo9KmE5IG1sEetFFZT pRktTSFSUXoSwuy7TjJ7gVG7PDP58YyGOGU0UV50lZtI74NtXLayqxUiM/NyaZJciPd+757UUUOT tcZAyv5Yl3fKTzTLg8DHQ0UVvhlaRhiPhIhG5HHFOW2c9TmiiutyaOZRTH/ZwOtSqqIMjHSiipbu tSkrPQYcDJqFnO4+hooqopESbGKBEmFGM9af9ofp2ooqlGPYTnLuKLh8YwMU6OTc+D0ooocUCk2O lRXXpyKoFcNkdKKKdNimGKUHBoorQzHg5x606iipZSP/2Q==