20200412 23280500 1.0 FGDC CSDGM Metadata FALSE ImperviousSurfacePly_2019 389809.750000 407854.039000 124954.519000 147521.056000 1 002 Projected GCS_North_American_1983 Linear Unit: Meter (1.000000) NAD_1983_StatePlane_Maryland_FIPS_1900 <ProjectedCoordinateSystem xsi:type='typens:ProjectedCoordinateSystem' xmlns:xsi='http://www.w3.org/2001/XMLSchema-instance' xmlns:xs='http://www.w3.org/2001/XMLSchema' xmlns:typens='http://www.esri.com/schemas/ArcGIS/3.0.0'><WKT>PROJCS[&quot;NAD_1983_StatePlane_Maryland_FIPS_1900&quot;,GEOGCS[&quot;GCS_North_American_1983&quot;,DATUM[&quot;D_North_American_1983&quot;,SPHEROID[&quot;GRS_1980&quot;,6378137.0,298.257222101]],PRIMEM[&quot;Greenwich&quot;,0.0],UNIT[&quot;Degree&quot;,0.0174532925199433]],PROJECTION[&quot;Lambert_Conformal_Conic&quot;],PARAMETER[&quot;False_Easting&quot;,400000.0],PARAMETER[&quot;False_Northing&quot;,0.0],PARAMETER[&quot;Central_Meridian&quot;,-77.0],PARAMETER[&quot;Standard_Parallel_1&quot;,38.3],PARAMETER[&quot;Standard_Parallel_2&quot;,39.45],PARAMETER[&quot;Latitude_Of_Origin&quot;,37.66666666666666],UNIT[&quot;Meter&quot;,1.0],AUTHORITY[&quot;EPSG&quot;,26985]]</WKT><XOrigin>-36747100</XOrigin><YOrigin>-29091500</YOrigin><XYScale>1000</XYScale><ZOrigin>0</ZOrigin><ZScale>1</ZScale><MOrigin>0</MOrigin><MScale>1</MScale><XYTolerance>0.002</XYTolerance><ZTolerance>0.001</ZTolerance><MTolerance>0.001</MTolerance><HighPrecision>true</HighPrecision><WKID>26985</WKID><LatestWKID>26985</LatestWKID></ProjectedCoordinateSystem> 20230928 14324200 20230928 14333000 FGDC 5000 150000000 dataset external 3cf56e1fc8cc8205cbc5981374be7a2dd7af6e10 Office of the Chief Technology Officer (202) 727-2277 200 I Street SE Washington DC 20003 US dcgis@dc.gov 8:30 am - 5 pm GIS Data Coordinator GIS Data Coordinator True Office of the Chief Technology Officer 20230928 DC datasets can be downloaded from "http://opendata.dc.gov". external 3cf56e1fc8cc8205cbc5981374be7a2dd7af6e10 Office of the Chief Technology Officer (202) 727-2277 200 I Street SE Washington DC 20003 US dcgis@dc.gov 8:30 am - 5 pm GIS Data Coordinator GIS Data Coordinator True Office of the Chief Technology Officer Enterprise Geodatabase Feature Class Impervious Surface 2019 2019-04-23T00:00:00 2019-04-23T00:00:00 external 3cf56e1fc8cc8205cbc5981374be7a2dd7af6e10 Office of the Chief Technology Officer (202) 727-2277 200 I Street SE Washington DC 20003 US dcgis@dc.gov 8:30 am - 5 pm GIS Data Coordinator GIS Data Coordinator True Office of the Chief Technology Officer <DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>The dataset contains basemap features that are typically classified as impervious surface, captured in 2019. Some examples of Impervious Surfaces include: Airport Taxiways, Helipads, Outdoor Building Stairs, Buildings, Sidewalks, Roads, Alleys, Driveways, and Swimming Pools.</SPAN></P></DIV></DIV></DIV> The dataset contains basemap features that are typically classified as impervious surface captured in 2019. Office of the Chief of Technology Officer impervious surface stormwater octo washington dc district of columbia water Environment, Flood, Runoff, Impervious, Hydrography washington dc district of columbia dc 2019-04-23T00:00:00 ground condition <DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>This work is licensed under a </SPAN><A href="https://creativecommons.org/licenses/by/4.0/" STYLE="text-decoration:underline;"><SPAN>Creative Commons Attribution 4.0 International License</SPAN></A><SPAN>.</SPAN></P></DIV></DIV></DIV> Esri ArcGIS 13.0.3.36057 1 -77.117633 -76.909336 38.995630 38.792283 external 3cf56e1fc8cc8205cbc5981374be7a2dd7af6e10 Office of the Chief Technology Officer (202) 727-2277 200 I Street SE Washington DC 20003 US dcgis@dc.gov 8:30 am - 5 pm GIS Data Coordinator GIS Data Coordinator True Office of the Chief Technology Officer This process describes 2017 updates to planimetric data originally captured in 2015. The planimetric dataset provided by DC OCTO on 5/22/2017 was used as the base dataset for update by Fugro. Following the Aerotriangulation of the imagery, stereo images were generated for the planimetric compilation to allow for full view of features that could be obscured by building lean in a 2D environment. Relative and absolute orientation for the stereo images will be achieved by importing the orientation parameters from the AT results. The planimetrics were collected using MicroStation and KLT Atlas software packages and combined for final QC in ArcGIS in the final geodatabase format. Prior to the initiation of compilation, a data capture matrix was established based on the data dictionary and compilation guidelines provided by DC OCTO. Requirements for the 2017 planimetric collect included the addition of a feature class for features associated with airports called AirPly, crosswalks as a new feature to the sidewalk layer, and a complete recollection of data in areas around the White House and Capitol that was compiled in 2013 but not captured in the 2015 collect. Topology checks were run using the OCTO provided rule set. When running topology, flags were identified on the existing 2015 dataset and this topology check was submitted with the updated 2017 collect. Additionally, the inclusion of crosswalks in the sidewalk feature class has created flags in the topology due to overlapping with roads. A separate geodatabase was generated to run the topology check (DC_Planimetrics2017_TopologyChks.gdb) and temporary sets of all feature classes with deleted data were generated. The deleted data was removed in the temporary feature classes to reduce the number of false errors that had to be reviewed. Due to the large number of exceptions in the 2015 data for curbs that were not covered by roads, the 2015 exceptions were identified and excluded from the current review. This working topology dataset was used as a guide to make corrections to the final deliverable dataset (DC_Planimetrics2017.gdb). Both the working topology geodatabase and the final deliverable geodatabase were submitted to DC. Fugro Geospatial, Inc. metadata@earthdata.com 7320 Executive Way Frederick MD 21704 US (301)948-8550 (301)963-2064 EarthData International, Inc All planimetric data within the scope of the 2015 project was newly collected by Sanborn using DAT/EM Summit Evolution digital photogrammetric workstations, with the exception of StreetCenterlineLn_2015 (street centerlines) and GeoControlPt_2015 (ground control.) The photogrammetric supervisor established the data collection conventions to be used for data capture, including the data schema, global origin and working units to be used for data collection. The vendor assigned collection areas to stereo-compilation technicians based on OCTO’s orthophoto tile layout. They collected and saved planimetric data to the designated network subdirectory. After the data for the tile was collected, the technician visually reviewed the planimetric information for completeness and accuracy. The data was then passed on to GIS staff. GIS staff performed a preliminary review of the planimetric data. Omissions or errors that were found were communicated to stereo-compilation staff, who then updated the corresponding stereo-compilation file. The corrected data was then passed on to GIS staff. GIS staff then merged all data per delivery block. Polyline features that were required by OCTO not to have pseudo nodes were dissolved. Following the dissolve, all point and polyline features were appended to a template geodatabase in their respective feature classes and attributed as defined in OCTO’s Data Dictionary. Polylines that participated in building polygons were placed into a working dataset, and topology built to locate gaps in the lines where polygons would not properly build. A technician closed those gaps. Then, polygons were built from these polylines in a working feature class. Based on centroids collected during the stereo-compilation process, polygons were then assigned their appropriate feature code based on OCTO’s Data Dictionary. Once all polygons were assigned their feature codes based on their corresponding centroid codes, the polygons remaining were then checked against the 2015 orthophoto imagery. Any unclassified polygons that were erroneously not given a feature code (because the stereo-compiler omitted a centroid that was not caught in a previous review) were then coded with the proper feature code. Also, at this point an additional review for proper code was performed, and incorrect codes changed to correct codes. Then, all remaining un-coded polygons were removed from the working polygon feature class. Polygons for each feature class were selected from the working feature class and appended to their appropriate feature classes based on OCTO’s Data Dictionary specifications. Once all features were put into their proper location in the geodatabase and attribution populated, a topology was established to locate geometry errors. GIS technicians corrected errors then removed the topology from the geodatabase. The geodatabase was then compacted. There are two isolated pockets of data that were not collected by Sanborn in the 2015 project, which are located around the White House and Capitol. Much of these two pockets have no 2015 stereo-photo coverage because the flying height required to collect imagery suitable for 3” pixel resolution orthophotos was too low relative to the no-fly zones over these areas. To avoid splitting a large number of planimetric features between differing imagery dates, the stereo-imagery voids were generally expanded to the center of the closest street (coincident with street centerlines where possible) to produce the final void areas. Inside these voids in the 2015 data, OCTO’s existing planimetrics (updated in 2013) were appended to the 2015 data for all feature classes except BarrierLn and CurbLn. 2016-03-28T00:00:00 EarthData International, Inc metadata@earthdata.com 7320 Executive Way Frederick MD 21704 US (301)948-8550 (301)963-2064 Sanborn has successfully completed the aerial triangulation (AT) task for the aerial photography acquired April 1st through April 24th, 2015 for the DC OCTO project. Using fully analytical aerial triangulation (FAAT) methods incorporating automatic analytical aerial triangulation (AAAT) procedures, Sanborn determined ground coordinates for each exposure by flying at an average altitude of 1100m AMSL covering the project area. The results of the final adjustment are sufficient to enable Sanborn to produce orthophoto imagery and planimetric stereo collected data that meets project accuracy requirements (ASPRS Class 1 for 1”=100‟ mapping; RMSE 30cm). This report describes 2019 updates to planimetric data originally captured in 2015. Topology checks were run using the OCTO provided rule set. The inclusion of crosswalks in the sidewalk feature class has created flags in the topology due to overlapping with roads. Due to the large number of exceptions in the 2017 data for curbs that were not covered by roads, the 2017 exceptions were identified and excluded from the current review. This working topology dataset was used as a guide to make corrections to the final deliverable dataset. 2019-04-23T00:00:00 This report describes data originally captured in 2015. OCTO developed and operated a QA/QC program to check the deliverables. Generally, the program consists of various types of processes grouped into visual checks, automated procedures, edge-matching routines, specialized checks, and field verification. Through the application of these processes, the data's spatial and attribute accuracy, usability, data documentation adherence, and specialized characteristics are checked. Staff identified issues in a shapfile with appropriate descriptions for the vendor to fix. The data was delivered in preliminary format for a thorough review and identification of issues. The vendor fixed the data and delivered final data which OCTO checked to ensure the vendor made the fixes appropriately. Geometry Capture Rules: Airport/Heliport Perimeter: Delineate the full perimeter of the airport or heliport. Helipad: Delineate clearly marked hard surface landing area or platform for helicopters Basketball Court: Capture full outline of the court Tennis Court: Capture full outline of the court Baseball Field: Capture infield and outfield of a baseball area as one polygon if easily defined in aerial photo. Otherwise capture infield as the baseball field. Football Field: Capture full outline of the field as best defined in aerial photo Soccer Field: Capture full outline of the field as best defined in aerial photo Track: Capture outline of track. Any recreation fields within tracks will be captured and coded separately. Other Recreation Area: For areas that cannot be easily defined by function, capture as other recreation area. Capture full outline of the field as best defined in aerial photo. Road: A generally named thoroughfare, that is usually paved and can be public or private. Unimproved thoroughfares are excluded. Capture the perimeter of roads and ramps, exclusive of median strips and traffic islands. Road polygons are formed by a combination of road edge, curb, sidewalk, street intersection closure line and map sheet edge. Paved Median Island: Perimeter of non-traffic paved areas that separate traffic lanes in opposing directions. Paved Traffic Island: Perimeter of non-traffic concrete areas in the middle of streets designed to segregate traffic flow. This does not include linear barriers, e.g., Jersey barriers, walls or guardrails, or point barriers, such as impact attenuators. Features will not overlap sidewalks. Major traffic circles will not be coded as traffic circles. Alley: Perimeter of alleys first plotted photogrammetrically from other indicators such as building footprints, fence lines, curb lines, walls, paved or unpaved drives, and map sheet edge. Alley polygons are closed along the lines where they intersect with road polygons. Paved Drive: A paved driveway for a building or entranceway for a parking lot. Delineate the perimeter of all driveways greater than 200 feet throughout the City and smaller driveways within the Monumental Core only. Driveways are neither streets nor alleys, but provide access to public facilities, such as a drive to a monument, museum, hotel, large estate, sports field or golf course, grounds of the U.S. Capital, etc. Do not capture private driveways that are less than 200 feet in length. If the driveway is less than 200 feet and leads to a parking lot, the entire paved area will be captured as Parking Lot. Driveways will be photogrammetrically compiled as polygons and not compiled from individual vectors on different levels. Parking Lot: Generally paved surfaces used for cars to park on. Paved drives usually form entrances to these features, if the drive is more than 200 feet. If the driveway is less than 200 feet leading into the parking lot, the entire paved area will be captured as Parking Lot. Delineate the outline of the parking lot. The curb need not be distinguished. Parking lots sharing a common boundary with linear features must have the common segment captured once, but coded as both polygon and line. Distinguish paved from unpaved. Small parking areas, where individuals park their cars in the middle of a block off a public alley, will not be captured as parking lots. These are either public space (e.g., alleys) or private space where owners permit parking to occur. Intersection: A location where more than one road comes together. Intersections will be captured in an opened fashion if the intersection is in a traffic circle. For standard cross streets, intersection polygons are bounded by curbs and four closure lines at street intersection crosswalks (outer line) or placed arbitrarily where crosswalks could logically be placed. For "T" intersections, the polygons are bounded by curbs and three such closure lines. Complex intersections could have more closure lines. Entire traffic circles will be coded as intersections. Building: Delineate around roof line showing the building "footprint." Roof breaks and rooflines, such as between individual residences in row houses or separate spaces in office structures, will be captured to partition building footprints. This includes capturing all sheds, garages, or other non-addressable buildings over 100 square feet throughout the City. Atriums, courtyards, and other “holes” in buildings created as part of demarcating the building outline will not be part of the building capture. This includes construction trailers greater than 100 square feet. As a guide, use the ownerply lot lines to assist in delineating roof breaks for those buildings where visual indentification is difficult. This layer should be relied on heavily outside the downtown areas to capture roofbreaks. Within the downtown area, ownerply will serve as a guide for areas where roofbreak delineation is not clear. Aerial photography will be used as the primary source. Memorials: Delineate around roof line showing the building "footprint." A list of memorials will be provided for capture and coding. DC GIS will provide a list of memorials to use as the source. Bleachers: Delineate around the base of connected sets of bleachers. Parking Garage: Capture this multi-story structure for parking as a parking garage. Delineate the perimeter of the parking garage including ramps. Parking garages sharing a common boundary with linear features must have the common segment captured once. A parking garage will only be attributes as such if there is rooftop parking. Not all rooftop parking is a parking garage, however. There are structures that only have rooftop parking but serve as a business. Those should be captured as buildings. Pools: Capture the outline of the water portion of fountains and code as pools. This includes US Capitol and Reflecting Pool. Fountains: Delineate around the base of fountain structures. Sidewalk: Sidewalks either compiled photogrammetrically as polygons or derived from a combination of vectors including: curbs, buildings, walls, driveways, or other features. Any stair feature that is less than 5 stairs will be coded as sidewalk to maintain continuity. Stairs: Groups of 5 or more stairs outside of major buildings or monuments, as well as part of sidewalks, shall be captured, Individual stairs will not be captured; capture all stairs for in one polygon. Do not capture stairs for minor buildings, including individual homes. Fire cases will not be included. If landings exist within the stairs, it will be captured as sidewalk, not stairs. The perimeter of public and private swimming pools will be captured, for both above ground and in ground pools. No other features can make a side for this feature. Pools will not overlap any other feature class. Pool decks and pavement around pools will not be captured as a pool. Pavement around pools is captured as sidewalk. Roof top pools will not be captured. Legacy data in areas without change will not be updated. This report describes 2017 updates to planimetric data originally captured in 2015. Topology checks were run using the OCTO provided rule set. When running topology, flags were identified on the existing 2015 dataset and this topology check was submitted with the updated 2017 collect. Additionally, the inclusion of crosswalks in the sidewalk feature class has created flags in the topology due to overlapping with roads. A separate geodatabase was generated to run the topology check and temporary sets of all feature classes with deleted data were generated. The deleted data was removed in the temporary feature classes to reduce the number of false errors that had to be reviewed. Due to the large number of exceptions in the 2015 data for curbs that were not covered by roads, the 2015 exceptions were identified and excluded from the current review. This working topology dataset was used as a guide to make corrections to the final deliverable dataset. The following topological rules were used: Must Be Larger Than Cluster Tolerance BldgPly Must Not Overlap ObsAreaPly Must Not Overlap RecareaPly Must Not Overlap SwmPoolPly Must Not Overlap WaterPly Must Not Overlap RoadPly Must Not Overlap SidewalkPly Must Not Overlap BrgTunPly Must Not Overlap BldgPly Must Not Overlap With RoadPly RoadPly Must Not Overlap With SidewalkPly SwmPoolPly Must Not Overlap With WaterPly RecareaPly Must Not Overlap With WaterPly RecareaPly Must Not Overlap With RoadPly RecareaPly Must Not Overlap With SwmPoolPly BrgTunPly Must Not Overlap With SwmPoolPly BrgTunPly Must Not Overlap With RecareaPly SidewalkPly Must Not Overlap With SwmPoolPly SidewalkPly Must Not Overlap With RecareaPly BldgPly Must Not Overlap With BrgTunPly BldgPly Must Not Overlap With SwmPoolPly BldgPly Must Not Overlap With RecareaPly BldgPly Must Not Overlap With SidewalkPly BrgTunPly Must Not Overlap With RoadPly CurbLn Must Be Covered By Boundary Of RoadPly HydroLn Must Not Have Pseudo Nodes RailRdLn Must Not Have Pseudo Nodes StreetCenterlineLn Must Not Have Pseudo Nodes CurbLn Must Not Have Pseudo Nodes BarrierLn Must Not Have Pseudo Nodes GeoControlPt Must Be Disjoint GratePt Must Be Disjoint BarrierLn Must Not Self-Overlap StreetCenterlineLn Must Not Self-Overlap RailRdLn Must Not Self-Overlap HydroLn Must Not Self-Overlap CurbLn Must Not Self-Overlap BarrierLn Must Not Self-Intersect CurbLn Must Not Self-Intersect HydroLn Must Not Self-Intersect RailRdLn Must Not Self-Intersect StreetCenterlineLn Must Not Self-Intersect CurbLn Must Not Intersect Or Touch Interior StreetCenterlineLn Must Not Intersect Or Touch Interior HydroLn Must Not Intersect Or Touch Interior BarrierLn Must Not Intersect Or Touch Interior RailRdLn Must Not Intersect Or Touch Interior 246237 EPSG 4.5(3.0.1) ImperviousSurfacePly_2019 Feature Class 246237 OBJECTID OBJECTID Internal feature number. ESRI OID 4 10 0 Sequential unique whole numbers that are automatically generated. SHAPE SHAPE Feature geometry. ESRI Geometry 4 0 0 Coordinates defining the features. GIS_ID GIS_ID OCTO GIS sequential identifier Integer 4 10 0 OCTO FEATURECODE FEATURECODE Feature Code SmallInteger 2 5 0 OCTO DESCRIPTION DESCRIPTION Description of feature code String 50 0 0 OCTO CAPTUREYEAR CAPTUREDATE Capture Date Date 8 0 0 OCTO CAPTUREACTION CAPTUREACTION Type of edit performed on the feature String 1 0 0 OCTO SE_ANNO_CAD_DATA SE_ANNO_CAD_DATA Blob 0 0 0 GLOBALID GLOBALID GlobalID 38 0 0 SOURCE SOURCE String 70 0 0 SHAPE.AREA SHAPE.AREA Double 0 0 0 SHAPE.LEN SHAPE.LEN Double 0 0 0 Simple FALSE 246237 TRUE FALSE /9j/4AAQSkZJRgABAQEBLAEsAAD/2wBDAAMCAgMCAgMDAwMEAwMEBQgFBQQEBQoHBwYIDAoMDAsK CwsNDhIQDQ4RDgsLEBYQERMUFRUVDA8XGBYUGBIUFRT/2wBDAQMEBAUEBQkFBQkUDQsNFBQUFBQU FBQUFBQUFBQUFBQUFBQUFBQUFBQUFBQUFBQUFBQUFBQUFBQUFBQUFBQUFBT/wAARCAGQAlgDASIA AhEBAxEB/8QAHwAAAQUBAQEBAQEAAAAAAAAAAAECAwQFBgcICQoL/8QAtRAAAgEDAwIEAwUFBAQA AAF9AQIDAAQRBRIhMUEGE1FhByJxFDKBkaEII0KxwRVS0fAkM2JyggkKFhcYGRolJicoKSo0NTY3 ODk6Q0RFRkdISUpTVFVWV1hZWmNkZWZnaGlqc3R1dnd4eXqDhIWGh4iJipKTlJWWl5iZmqKjpKWm p6ipqrKztLW2t7i5usLDxMXGx8jJytLT1NXW19jZ2uHi4+Tl5ufo6erx8vP09fb3+Pn6/8QAHwEA AwEBAQEBAQEBAQAAAAAAAAECAwQFBgcICQoL/8QAtREAAgECBAQDBAcFBAQAAQJ3AAECAxEEBSEx BhJBUQdhcRMiMoEIFEKRobHBCSMzUvAVYnLRChYkNOEl8RcYGRomJygpKjU2Nzg5OkNERUZHSElK U1RVVldYWVpjZGVmZ2hpanN0dXZ3eHl6goOEhYaHiImKkpOUlZaXmJmaoqOkpaanqKmqsrO0tba3 uLm6wsPExcbHyMnK0tPU1dbX2Nna4uPk5ebn6Onq8vP09fb3+Pn6/9oADAMBAAIRAxEAPwD7CsNe MP8Ab1pp0ML2cSpBbNGvmbmYEN0B3Eds+5Nc38KP2a7XwvqOtSS6lcWmqy7XhaOQhhuG/DjPzKDg YPHWrP7N8NnpvhewstYuJovFDl3Zbti3nZOS0TD5XznnHPr0rufF0x0jWF8Q2Eb288aiG8WXLBoS 2C4wTyM5/GmtdTZS0cUfNfxj1p4dQ0gTi30HXYb2XTNQiubUmGUyYXzkkxgq3ykr2Nbnw7bT7nwr PoGs6hOvifSLjyWYuHEOXzG8S9wRzx64Nd98Ztaj1jw/eGa0hvdJnB+228qgvEBwsvb2z3FfIH9q 6/4WnXWDHczWluzWcuoRZZ4Y3GArd/Ta1IVrr3T6I0HxJbR+LrrS9TZtRuZUEM1jOgjjnfcf3iOO A231xjGDXzD+0UljZePrXUNLt2sVtpPIlVsFmkhk4f8AIAZPofx9E0HxRot14kt4baO7vry5ZGtr XewuoZFB+YtIFB65OM56YriPidpZ8RyanDfM1trC6rJKk8i7FkULllKgYViNvFJ9Co6bngnxT1pv EXjfWNTKkPcXDSHnnLHPbvz6V33xAsba4+CPw8+y26JqECTfa2WPBl3SFoyT3wpx+FeT+J2Vteu2 Dbv3pCsR6E1674ijbS/hnoMIkWaO/jhuvOZADEQmGhB67R29c9KqppFGUH7zPbPhpr2m3Xwp8PWT Sxo9jZKzWJh8wyylySD1ycbjnjGa9O8BaGfF8WsXWl6te2mmy3DNDaI2FnXapAkOeB83QdK+WdOu b/w34J0i5TUVVb0NLAiTr5luysVbK9gc9/SvcfA/xjuPOtbCytoo9Yu51VWkGYcNEq7wvAY8Z9D1 rLnQ27Hd6b4ik8GeJGsL+SF9UtL0CWZD5sKxyA7S2B/CRyeOorrvH/j7WNeUeEtB0mT+3WAS8vVU FbaMgfOpBwGK9AfX2rzjxX4Asrzxpq8Vrqi6dp9vZR6lrGqSXapLLDgr5YDcEs6lhjj0zXnC+N9T t7dLb4Zrq39kj5ZC2URJmJVXaZwMsQfUim5WRMnd6F3446hbQ6WuhXkwv7KNPItl4EduF7EA9c/x d6+UNY1G+0nXgWnmntUtzAkuM7ATkZ9QPWt3xp4i1bXtc+w3reRLayNC8e4MAQSG+buc55puswwa bdW1slxBep5YWWeJyUQnsSR1rmlUHz20Zg2+qreTG5naK7lZ9zu/3TjAycVp69qF5qdvGJ545YVi MFusKgbUBOBgAY/nXM6hPaWkm6wkCT4IkVwGj3Z9O31pLXXobpR58QtpVcFVyfLc9Dg9vXmn00KT uKuofZdMWKbTv3zkMkzEgmPoQAOMVYj0tdUjV4iBIo3CMrzjHTOe3FPe8tvtkUPk+ZNMNrMzEqSD n5SM8YFVkcW8gnjkhVmyCgJXA54/KjcpaFW5Rlk3MXcY2swye+MA10NpZ747JJZ3dCwcwxt8gXr+ YxS6Etvqc0UazKkITIkc9OOSRV21udO0O+izM1zYpJ5kkezOV9OOxPHWnurDfLY+sfgXZ6r40sL6 4N1ENEeB7eW01M72kAXJGV524wM9ODXzJ4q8H+HPCPxQuNO1ULJ4au2aaJdOuFlkhBGQm4jAO7A5 6Cun8RftCab9ktYfDFpqHh+QIRN+93oT0AUegHY14ZrmrXWtXkm9Lt5mfzVnICuMc59Bz6Vr8KQU 24qzN3XLi209njspHazMuE3cvtU9D9KxZYntbj7XamRULBS6vtY56dOnNVLHWmvIZo7wsbyJSNuz JPuBQ94YY/PikVhIpEluQQQR/U1mo63OuVa65TZfWLzUrieEXE93IXDzyXDkg4GOTUkOmz6vpshN xG0CPua3VjtGeN20fSuctNW/s7zHR/NSbDCFmwNuOh960YtYvvsN5FpzJFZzIplZiByP4R6nngZq 7nP8S0O3j0Gzg8L6W3yXsNxGY3WTKgOGOSccjj09q43xhpun2Or2kdisnlf8vEO3Ztx93H8663RY 9X8P+Hbm21bSN2o2brdw2s2V3RkfeAHUf4V57ceJLjUNSluPLWJiS+4ZO0ensOaLDl8NrF7SL5tM vgftMm6SRSFxjK55zzWXdH+z/El5azgrg4ZAvA54Ix9aZej+19p8x08t/wDXFSwH5ds1P4gmso76 2u4ppS95b7GaMdJE4J59f0ppEps1fGdpNpVrbQXC+XHcKJUbgo64GCp9c5B+lc1qEK6bdwB0aNmQ r8o4zmur8YeL4vFFn4d09FiKabbC1WeQkeY24kuR26gYH933qn44t7O68aQQ6dqK6jbxxxg3BUKu 7aCwHoAcjmn5FXV7j9FH+i3MThlgGJD5I6kjA3Z9SDT4bi0juJVigEUSnDOxLcHrSm2Md95C3Ibf F5W4HowP5d6S60v7HOljA7Ncuv7/AMpwVXPOAfX61FzVxdtCi1ksf2t4Xj+z7uCp++ewA602zuDY x7Z4N245k3H73pj2zWkunR2MKSxBY5lG07yDvz1waTybaW3WYRpJMAVcFj8pB60Iy1LGm+KL6zhS zUpDbxEfNFyQP85qveatea5rUl3dXkk2n6apNvuf5VZuuB7n05rLumWwtXeGIXFxdkpFHnoTxkU3 7H9j0lIkKyIHGYi2GeQdT9KolxW6NTStfeW4byF2QpIssibiVbB+VT688810cfiy9t9YXVpI1u7h SGlTBUkHgAnrnOPes6x0v+ydFMtvDaxGcDCytvOCc8D1qKa5jsZo4DsN/OwRFcYCc8MfQ0tRztY2 PHHiqyub6W9a3ddUuwjHcRtX5VzuxzncOnpiuLkuvlmurtjI4JG7ux7ADtW54s8LxeHZ3a6vGvIG VZDcRHcryd1U9/TPqDXHyXEl1eZZlEq48uEn5YuOp9W9qdg5mW7GSJbpLqVmeWQYjtwMbfT8PetD UGPl/wCmvvKHclsGxEuR39T7VkWbXMcbmNVMnO+d+XJPp6VDDJI86s7buSRuP9PWgnY0PLuGhAlY s+3uNoXHTAqSxtZdPaBnl8mOdSyuoOBzgj3qa+OHhyxZyu07l7+tT/Y01HSjCZWlvozmCFefl6nP pU3voZPQz5YYbiYfPIzFuST8tapsbe3O2K587AHKdAfQ1ft7SzGk2puLWS3iZCpuo14L1Vgt7S2s 5NsjSyM4VJY2x8vfijlI1eo/StWeyWVU3YdtpHb2NdL4e126+1wRpctbyTSAErkKPQ4HJNZuoXOj aaY10+V5ZZIwZmmH3D/dGP51FvjdYXjIWcMCpjypB7c+tYtWG4q2h9UeHvgmfEWni413Wzd3V0xi RLhWeMHAPQ9x09q67T/gSND0O+vdBudQ0XUFRohc6TOZbNyB8yvGeSDxnAIrxf4afG7xdpkbaEix as9ywWSa5f8AexbiOjnoOma+7PgzrMWseGIo7ix/s29QCKSITLKDzy3A4z71107ExlbSaPi/TPjV q/w71HVtN8UBLeG8jYi80tdq3EmCNpGAFBB5yO1cv4q8Cato/hdNQs9QTVvD9+PtV3DaEMkUpHKg dyOM4719i+P/AAjonxS8eNpsGk6Zqun2MKLf3BRUZ3WQkRRPjqc/M3YAD1rxH41aCfgJ4sspNCsN Qt/DF3GZL7S4ZI5/sr84KMQdq55PAzXRZdDS6Tbirpbr/I8y/Z68R3vhddRvI4m1WKB4xLbu5Mlv GT95Bzn3FfXC6po3i+/s7OF7TUnvISTH5HzIR13xtnb9T+VfJ+ueDrfRdOtfiL4M1w6squhvbSQb WEpGX+Qfwg5X9a63wv4qm8YaFa6x4Ytxo/jCPUEW5ulkMizq5+RXBPIA/Os9E7Mzs4vnpvf+repv ftNfBvwToNnbWek2Emn+J9SZWRLfJVgCd7BRwAACcVxM3w38QfCrwj5esada+I/C2oIrG+W3V7mA Fc4HUgfSn/Fr4jeObLxZ4fuNesIY3szJax3nlFI5o5RtZupx149K+mJriPVPBiLHqP8AaSQ26A22 nopwAAACe35c07mrm5SUZKx8N/EfRPBU3wz0y80VRbaws7JNDnLlexb0/GqHwd8O2WtWYt9Rgito 5JGSO/KOd8mOEJBAFdf8VvAOn3mn+ItR8z+z9dspPNKcqlypPO0Hrj2rh/hL8Vrfwtbw6VqtgbjT hPLM7Ku7l1Ck49BihrQmaSikz0rR/gbpFxqm/Vdb1Cx00W0jJc25IVrgD5UyegI718365HNpur3N vb3AeFHbaZPm4B9a+t9K8QaZ408I6la6TqcN9DHCym3vWEciKoyNvORXyXdWc1zqDeSoUFsANx+t HQpSXK2jsfAehX9xpsN/Lfta27zltluisw24AcgnnrxXqS6frDaXJLq2ta1d2NsCsyx3AijCdcBR jvjgViWXiHR/DngfSrW0tY5Z1j2yTSMu7eTkgDrz0z6V3914j8JeItRe78Q31v4Z057eO5hsLCcS eZIF6sFzjkD5TznrTIVupwPgnw3p+qfaJ77T5JbO7uSLaNrgmVmBwq85+UHrWb4y0Ox0H4n6XYJb wx2kcsRmhtwSCM/MMdz1r1H4Zw6rJv1PTtG1jWIrmY3LLDpuI0BY7QGbAORt6cc1wfxK1DU7r44v cLo8Wm6jbMjJY3R+WIoufnIJHucU13HZtSPp7whpehtp09raahtsUyqeYjrGqnoPLBGST61zfi/W dAj8Q6dp+pGbS7O3sme4lllYq+D8pAz1POBxXnHwoPirxZ4nvpJtbksEvGxbxadAuydxzkBhgIMZ yfTvV+8+E9v480fVr+fxFd674gsJGWeSYqsOwZ2og78ZPapvdBTUtInZ+EfiRbazeWy6ZA+rW4Vo zcX0BWzhP8OcAliFwcD1rQ174X6odKl1TVvtGpLK7CGJX8hFJ5LlcDCAc4Y1wfwH+JV98PdUl0ue 3mvtIyzpJY24Z1YdW25GcAda6L4rftK3Hi0T+G9Ine4OtumnQGO3KSRRE/vWIPVj0/CkmUvdk79D B+GvhDWfH2hf2Vp1n/Z2gXOoSSXV6s3lvfKDgqv92MAdcc810mi+E7mTx1ZW9o/2/QdMhY2kBJji nwSGERHRR/exzWTrl/c6T4Y0nRbCC4tdM4ihVYtrXkv3TGrZGEGOW6eldh4J1rxp9l1ecy6TZaip W385bhSltbovEa7VOB1z6mqvqZ3aW257do/j7QdI0l/tAFhfxxhN1w4WODHACnv7Y5NeaeNvE1r4 s1i3n1OFUtFZRG32jckjg8yNj7xBzhVGB61QsfCUk0cL+MNdXUUmf7RDa5LRr/dzEoySeoLEV6DH 8I/CkmqWepvfR6dNcRnatuUU4OOAhz19faqCLto2aKW9voOhw3ukW9w1g6b5by5Ym4kIODx/Cozx /KitSw0HT9A1SMXLf2hZMSPOku8hOeAEXAJPrRSFzRp+7LU8s8ZfCD4pfA7wrcWnhq9Xxd4ZJEjR yIWubEKc7os4ZM9SVJrrPBnjrU/i54AWSG4sdZntVEd5aam72l5bkDGRInDjOMEqPevoXWPFkdvG zWqGdYpRHIfvKTjgV4J4++E+vrr0njfwbaRWvimGRmu9N3qkV5ERkfL03Dv71nZ9DXli3dKz/r8T jPGWv6Z4PaHV7ufW7u5tpRHJaasyyQTKR82yZBtyp5ALc45FcN4s8G+HvFGli78Na5fwadfTK5ur yRzDcSKwZY5AQFXafQ4rtdF+N09tFd6J4zjfw5q0247NSiURlT2UlCCPrXMX6XPgldSvfD2o2M9p dTC4k8LTIr2d2jLjdGc8NnsMDpRoVe3u3scx4x+JEd9p+o2XiCxg0LVNNnjkiayBEdywIDNDIMlW AAYEHHBrx3xV4w1e41K1kvrmS8imkSRGkOPOK4G/Pc4xya9M8VSaJrngG9ismR7mEEmOeMRyWcwO fLUA8jnGRwPrXj/iTxFqUr6FYanpi6fNpcYiRfL4lXn52H8RPHI4rCT5mkZ6XPJdZkM2q3Z+8WkJ z2Bzmu68U6pdX3hrR7V7xZrfTkKwxYztBOcE9+cflXn88xOouzYYtL2PHWujvGjvGhtyWgjQhJNv P8XNaVdlcjZnoV9dWkXg3TkubeEvDbxLFJAVd0H8bFR65PBOeKRvG2r+D4bm0+zW8GouoVJLtPMu IwMbcYPykAfUcCsfxNqc+urJNpsEll4cM8aR/u8+WVUDkgY3YBO36fWuobwraWXim0jla41K2kEU kklzHg7F5PsOAAc8DNYWvsPfU9J8G+B5Lv8Asfxpff8AFxjJHu1Kx3kSooHygIpG8J1OOeaofFXx dpOqRXUfhlHOpXRDxW8EuyGxt0BLApng88A8jBrktIlv10nxKmhWVpBp8MwYaiDi6BaTCpbsuNz5 4/ujB5FZPjb4cwaXpemXKSalHfXlsbm/k1OAxBpCcERt/EP9rnNay+Ea5uhxt15N1pKG1ijt72If vW3cy9TvyTyT6DArlrO1udQt7h2kZrazBklUnbkelegx/Da8sPCltqyataK93M0a2z5OY1GTIW54 zxzzWDd+HtYbSryc2Zew8wCa8hQGPfjO3cPYjNYrTcEncbrvgnTrPwPZ3yXTjVbhw0sRGI44yuRz 3NcXZWREiQrLuDjBOQQRXRarsutJgje7P2mJWHluMKB2x7muXhxDbzrIvmbufl6j6UX7Fq6eoskk mizMLO4wuTmF+V57YqW41a2uIcPA1g5DFmyzI57f7v40tjHa3N4WZmZFO5FcDLHsPxNbV1J5OniI Wpi2yM0crLguOpHuKd0XpLUrW9qi2KfapkeLYGj8vqeM8H34qz9sYtEoX7GCTt2cPt4+9/hWNJY3 FvD9sspgISx3xMp8rOM45AwT0GO9U31MSOTco9tcMhU7mO1vTa35deuKfLcl2voa15ciC3YFo0k2 5XeACR17dyaq2M17faha20TS3N1dsscawoXZmY7doA7fQVTtfOhhh22UTuBk+ZlgR/eI7V7F8H/D /hbQdDPjDxTqsts6SrJDp+nuqTysD8mFHRe+enNUktmK/KjzXxBoMllcXcFzqSx3tgT5SmPDyPkZ Q9+cnr6UMNM1jTbW4svtEeoh8Twv9yPHXHHb3rrvHz6Z4+8W3OtR2tvoGg3lw86mZllmVFAXBxyT 3x0yTiuJ1jUNL0PW3i0ySSXSG+RWmUb/AKnHTmn6FuSewv8AYaxbZobcTwNLhFcZw47fRhVndHbz 7JLSRCmRLbjcoWTH3cfTv3qG/wBcLXzW0G23WQq6ujchh0J7CoL3XJ7y/N/5s8jykfa5JG5Deox/ nFJlqSOy8G+ILbTr6J7r99NI2xZEB/djP3SSRjjjGKyPFukNN4pvY5z5UTAlEiUAMDyPz4qlc5ur ZLmBY7fe20ZIHPXpmtPXoTNJb3rKDJNEiKQ2PmUYycjpU3HGVro5qe1lsYZ4WVthwoAx271keIoT aQw8KpilEjZU/IG7c13lray28UkgMd8rAearrnYD3zxjkVzXi63jvtNkMlwobIZY8FiAOMegqkyW 1LVF3xB4Pg8N+ONJ0e/vbeBHkhN1dAExwpLhi2cAsFDdhzjisy8l0+LxpLBaOLq0jkKRTbCgZM4D 4wTjnODUniK6Or6tYT6gz3LLFH5hlfO8BRwT9FA+lUfDfiBLXWr7UbeNdx3R+XIvAVuwP+zxWlxP Y67VdFmtoxZQJHJqkkwaGOHgbSCSST0wKkPhO+0O0NxKxKM2fMkQfexknPXj0rV8D60uvarc6tqE 8dl9h0149PluMYkdTxuB4y2T+ApZJF1mxkk+0Q4iYSFWbAI4yAD1JP5VDiXTqHP2tub4yGcqscab 0Zzyfr7VLLpUkcDyuIwyhiJEGBjHT3qaayg1C4khjlihcL8gXLB1xkgHHJrj9c1MwQvIl3IJmHlb MY9jyOoxSUXc2lJR6EFirXWrllUyC3XbEQdoH95yf0rYkjke1TVBC5iYmNGUfIMdvrVDwXY3Osa5 Z2MQQRb4xuYbFbByAT2yea9u+OF5o/huxfw9pn2XUjcIlxcblObe4P3yh7Kf7pz0qzHU5D+2dHbw 9bR27T3mt7SLmaWMCK1QdPL55J75rlm0WXUIJ7rT7gs0SGW7lnKq45xlcnnnHbNb1jY6Xp8VuCJZ I5Qplj8vDMByVGDwCeM8VT8Vyab4gvG07QLaHTbe0hMk9w7hmGT90E4y/t6UjN9mczrXiK+8Sy2G nRkNFYxLb2qLgJEM8kjuxJJJ96sQ29to+l3SwSLcXy7d3mAgHk8Ie9O0CwSxkljg2hlT965X/Vqe M/mau6jdtFeGZN9x5Y8rf1Qgd+aHIpbXMm2guNQAC7URgPmHC7h1Gavw2iCSO1XZMw6MvGT65qNl S8mQ2xZIUJJGCF+oHuanjvo7TUIm2+ZsTnjjJ/wqNQ5W2WbjUoo5RCYfthUjeXXBB6Y3e1VJNNxI 8iube4Vt3lo2MA+nPWrUeqQbUkdo/MVdxVOrc5HPrUmp38NxDHdkFJH5ZYmLFfzpJditNUQWslyb Wa3ikY2gGdhk6kdTg9DVdGgsnPmHzG6AYIA98d6yJJnuJC3myRxJ93jOeemKtLeXXnfKhVlXP7xe D781RnymnayP5UjssIjWTO7aN5Bru/BvhGDxZdfYbFo5JZIt7Etgqw7ZPevNobiW8JM0uOc54AzW jpk93pglaPeHY4QoSPxPPWjqZO6+E7e50PWvhL4vCXbJb3sbKGWQeYDGTy2P4uO2e1fZNnZ+LfEN toGpaP4is7bRtSt2SS8s7XyGaE9Ef5jtc9scivkPXvHXh7UfANnpz2V7F4jtHMkN7KQ6y7iAVYk5 24H6171+yf8AG5dN0FvBGs/Z7y2uFa5tWYkLAOd249tp5GOSDWsbGcneSnY9Stv7W8K+ItPsrKaH SY5od0kbFY9tumFcDJJ3knK9z19a9U1RPD+uaTc2xhjurRoxPCzfvWOMBwxzljznnPUV5f4s8H3G ra7a6xbX8Wr22xypuW8qV/lAVQ3IOOcLjkVyyfFqfw3faXbXWh6hLp8dw32iMKqt5RG1ogqngcA1 p6GnwtTjscl5Om/DH42XdillLPo3ieza3tY5lyiSZGTs9eo59c1xPiLw5q3wP8YFLm18rRb2eK5E /wA+LYbsnHqcV3XjLxd4W+JvjCS1D38C6Nbs2n+bbSBxdE5yQBxtxjnqCO2am+JH7RHhr4hfDubR Nf0918TW0JjlbaWQuBhTG3TB68etXdO1xtxk3F6Rf4Pud98SlsvjR8LbqLTLiHUrSODzLWaMAfvA MgFuPm/2RmvJvgKt1faHfA266jFYuEubJZPKv3YDJIII3Lx37VxHwH+JF58N/FkWlahJNBYXR/cI 6BzHI33SFPX6V0nxN8OXnw51O68ZeFtbE8l0zLqNtEmx4iTkqVHQeuKjToyLOS5Jbx/E7P4tWsPx Ts2m8OXqpBLALe4gnP3CvIjIxkAH0618sfDnw69149ttHuFYtNKYsRnoR/TivoLwHDL4s0K31C3N ve6gxD/bLKcRTRux/wBWVbqQM8dK8I8e2N34P+JGoSItxBJDN5qmYgTHJ5JxwPwp7mnM5Qv2PWvF mg+D/DvhHVm1XSBFr65S1aFtjSnpuYZ+pOMjFeI/DbwlF4v8cQ6dcTXBs5AzMkRIbgcAceuK7nx9 4uutcjt9TvbSSCFbTFrBcPvc5HLlv6Vx3wh8eal8PfGdn4gsra3vLuLcoiuiSmCeScVFyJOShdHs +s/BHSLfRUsdI0wnxBAXE4uS210XLbvm6fLimXfh3R5dCufEr2sXh7VEijS0t7dE8l2IwxKHPPQ/ jXQ65aeN/F2ry6z4g8Tw6Df6taGY21rGqiCJeFWXOSpK9B1ORmuG+FfgWXx7qb/bL2XUjbRG2tLG 7nYmVycb8D7qLwee9Nv3dC3qrnu1v8eNf+HXw90W3l8M6fqlgscMQvLFiqoIwB+8RsknHXsa+XfG fii4+JPxY1PU4/ME+pzvsWM/N83QDOMDt7CvUPiBNP4ct9N8Ki4U6tMywXENspZ7ZBjbwe2DnH41 5B4R0uyufHF7b3jiOKJXHz5Y8cDAXq36dad9BKPs1od7feKJvDsUT2yXcs9vbIFuGO1Y2x93b2+t XPANtrOmWGpynWrPTi1v9skkmy3Dfw5xjcfSs+7s73xxo9vH9qy0kjQy3RfbHheQAvoqjJ+tYPiy e08If2Vbx3ketTvEss0UDYiGD8isB0OOT9aixs7OKO0t/GsUcYFrJGk7owuZI/kMSHhsdiSKyfgn DoWvfHCaO4vPL0VbUp5l0N8ijIyEPYnpkc4z0ryC48US3k16YreFZJP9Z/zxj9NgB5I/Gui8Gasu l6fdLbtDaNcSL5vzD7SygYOHbhckk8U0rGcoua5V1Pf/ABtJ4Uv/AB5qtzYzSf8ACP6aiwWjyLOR JL3AUdAPTiofDseieIdY0+4m1maNFb9/G0jxxOM9MDhR9TXI+F/iPoul+Gmgu5v9EtWKQ2aznzC7 H5pMdzjv7V7T4Jb4ceKLCNvD95Nbapb7JWiulWWKQnjBGRk5qhSkloz1ex8F+C7DRJrtIUgiTaVM t00uW7beelam/wAHa7II7bT49S1KOLCBQNisB9xSMjIHU4xXz/481ldL8T29jBrcMMWAbhNOLM+S fuKm4/N9K7WGy8darcaRYaZFeaNYzF1W/ureJbow8ZYJnap93OeeRVIh3VtT1PwfqnhjwzN5V7M1 nckn7PbxSefK7AcgKMknnsOKKzdN+A1loF0dXl1m+uNQmXdOL+bcbkL/AASPHgBD/dBxRQSlJ7Ca f8bXs9JkN7aNZ3N6yoskI8y2Ugfec9RnHTFaM3xcto9M0j7Fdx3lzNIFVerzZb5+h6dfyryS48OS +H/EmmaVazrPYXcTiOZflcupwgJY89wO+BSeNtI8Nf2hZR6rGbLX7eWNJo0LQ/OSdrAjG4YIHBB9 ai5tyrufQPjLRvD/AMRNHsjr+gR6lFIhNusq5MYxn7w5TPGBn8K8guP2MfD+pao0unajq2iBk82N WcShFIwchhkAH+db/gG+0CFBbLe3yLZzlJJrK/k2xHHAw2R3/pXq8Xw9g1i4tri61rXZo23JGkl2 YhsIzg7QM/jUtJ9BqX2f6/I+EPE37LHiO107WLrS9WtdYl0y4kS+t422Soox8+D1BBB4rzea+0mS CS3urZkv44G8mR5iULBSCqnkjBAIB4OWHvX2R8ZPh3oPhHxbFqcNvZW+j3Uf2e7kkkdVWRfmVtwb JZsYwTgnHrXiXx2+C9npHg648Y+F4dQj0TzNl59vwrLIwwu0H5yMnkkAcis+WzTQNLorM+PFjDap GAcFpcAjvzWxcbpPPURkbXLF8+prMsQG1i0JUsPNBO3r17VJMwbUWdWbyVc4jkORz6+p5rSpqYPV nrtp4403w14Pj0XTtP8At8sqkTXp+4JHxjnnoMfdx0rsvhj4R1P42/EyDT9Wig+wWMK7rS0zHCIt p5JzkjOCfX8a8N1/WpvEs32i6khtTDFGgjiTapVQFyB68Zya94+APj/R7rWUGqeIv+EUaGIWrulq JZrpSGLSGQ/KhLEcYPReKyT1sTflep7/AKh8I9JuvEWo3Vjfx+H9F8OtHp9tJFGgjnuQm6Zv9pwr Ko99xri/FfgnxX4kWZJZ7mayttPkkikuL1ZBJErbVOzYAq5PQete1/Dnw3o8nwsu7kRNfJFdXM8Y J83aDjMgP8UjYyW9TxWc3iTRfidrx0SztZBbWmjqJ3kjMcYfPyiU8fKOfl7n6Vqbcykrs+ZYbXQt J8M+JbfV4BpPiLTrX7TbyJLiKXdwCiN8pYk4K46ZrD8B+GNW8QaZYCGCUeFbUm4na4fy4Li6/iOS duOntxXQ/tVa9pka6T4ZSXTr3WIYvPvr6zCqkUan5IRtGCcfjzXlU/xX8Qa9o8HhzSFbTtNWPy2j efEZ/PgDv+JrOXLcGaXjG80a2u7q41PTMNMGMG7a0vmDjjHG3HtXhzuEmZljZ0z64xk969M0vxJp 3hmDVIZLP+1/Es5aJdRmPmxx5GDsHIPH8VcHr81i14n2CdmCqrNvG0h8fNxnsax6gn3G2duWu3Mn lqkamVe3QVPdavJNJ9mSLz0YlgqtkjPUDPtVOxkga4lnu90ixjcsYOA3I4NM1G4trqbzLeJYE3cr nhfxqgu+g+SOWSHZIXSE8mMrkjnHP45/Korq0W4SRk3TRon3nIxxyePSn3GobGhjeQhQmfMx1HAx n+VQteW8kEwiLRtEhUFHxv7DP60Gq0IoZJ9L3WttIbtGBWWNvmwPVSRxVea5Xyz5TF+ATH1YfhU1 rqEcjYZFiRhhfLJOOOhrWFvHcWccCwrazA4iuFHX1570A7S3RFodvdappdxutNkAYZuGYAcDgYPN V7zRUa3mDMIo5RxuGDWpC1zeLDpjxTG8IwtvEMCXPRlPb1NU9Yj1KJ7WCWTzrl38tIjggHOApPej qZWszF/s77dHFAylrmBQg7b8dM+tbX9jz2VlJdxSLLbzJmSDI2n9e1Xde8F+ILeybUVg2Pp0YllS NfmCHqSKt+BNa0RfPg1hbnywDLCkeD5gYfd56c96qzex007XM/SbCWaF7e5lhjhRQwO7DyAngL/K rWoSGO0tF+zI6Rqy5lb7uRx6Umi30Xh3WIpr2wmuJvNEVrptzFlZI5AeSfUDGB60/VbG11i38yMG O3hl27ZOSCemfcAYFLle5LWtmUrxnFjHvDRmQk/uhxwMED2rBmt2uNMczK0SNI3zydNoxzz0rYu5 JordHLPFGpMfm7Q2QByR+n51mxMupR3iedK9wAzeWB97A7dqaQStfQrPraR2ssTgTLJbhVjVPmyO AQfwrF0e0kkt47ePq7F5do6Kf4fqat6Ta+dbyTMCs6xsvlbsng8k+mc16L8PNA8MarYyQ6lrP9iX 6xGRmkYBJmJPyg4PQbcD61S6oUr8qMf7DPYWa27Kp8rl1Xn3wPwxSXV062MMjWcZuCeV5DfX9RXS +H9QjsbnUEeaGZl+VZbhN5ZQcjb7kVl65p93FKt3GjWtpM2FLN8mevFSELFvwK0s3iKQTqcQWkki ccKxXAH1yf0rzOOOS81i6URqyQ7kLc7V55b6127339gWGotFKzX08YRPm/iasvS7e30O0jilBnaQ b5dp43+nv+NV0uN9hfDdu2nW0d20TtLJJsgjyRvP9413R8GSahol14gu3WysI22xJnLzSk8kZ7da 5nTYRIpu52yxyEaNsqtReKvHksmiw6HBFhy+9X53biMH8KnVsbStcxfEGv3lxcfZbSRpN/yrtzwP X1x7mrFq0q6fFZWqoJWw0tyzYAI64J6n8+1Z2g6bJMsu6TySP9ddcsfdVxWnJcw2lnarG7COJm8q TABHOaqRkrNk1nYyWTySQoQsnEkeSxXkZJJ9z3ovwZVEnnbrl2IO+UMuPQDqO+evWs77Zc3dw86z yMZGyyjocdyKmmvlhZYPskKlkwz5LO368GoGXreY6fCJRLsiYDO3IDHnjjtzVSbUmMaIzFgMf6tR gex6ZNVmaN1ZJFZSF3cYJPPOB+NT2WnfbJWVUIDLlUmPJxVA5Dfttms4Em1488bR82fwrWs9WhvY obNbaGyMsixm8mzwpIGWHt1rLtLOxW42XC/aGZcL5bYETZ6+9djr3wf1XTfA+neKbcrdaTdO4Crz JHtOCXHYZ6etUtSY3ei3NT4xfCdvhf8A2SqzrJJdQLOrJMJBMpPDqR0B64rz+GaeGP7XcNI6BtuG GFZuvJ7iq815c6rYwC5nuJVhHlwByTtUdFGeg9q6az0Ea1AJ7ZvtaQOkJs5TtmkkI52qO3vSluit be8aXhXUrHWZ4LjV9Ghvoo3YPDbxiPJx8vIPCjI+vrX1Npv7JOla38P7fxLNHeaULlGkeOGVZQB2 Izn5R35z9Kxfhf8ACK18DfDPWNav5IRYSSqkrzIVfzhj9zGDg8Z78cV9VeGdU8Pp4OstMgkXUUMQ S5tbAvc7SRkr8vHfmrSdyIyaabZ8Yah+zLb3njBdD1XVYNE02Ky+2W+oFSROp6DGeC3OBmvP/F3g mf4SarHqOlXs1xa27qq3a4Rg5XcEKgnbkevWvfvFGlzfErx5d3thp2pyaRop+wQ26MFYyIcgAf3Q 31wRXSfEDwLb/E34e61HY+HhosDTi5aVVMlw9wAR5bDsOepPFUlqdMWr8ttzhvhT+0HpPjDwT/ZG utJD4ktrn7ZZxlAYbiTOVx6Y9857V7H4g8jxB4fudY1GINK0e794CnnqpDMqtjjOeo9zXwx4k8Mw aRpFjfaUl7balpyiLVoxkG3uNx2sD7gZHpX0/wDs/wD7Rdz4i8G3GiapbnWdQtbSSGKOHHmH5SA2 D94njp09KH2OPWk4vobvwl8OpoWjtfzQy3S6xdm8isIXDGPzM49NwwAOTXHfG7wFcapcDUNP8L3/ APbccu2OKS0KwLBg9B/E/f2xXp2n32kL4L0eOC2m0jxHp9rGY4w5jKSAAtv34GOvQc1s6f4u8QeK NTs42vEv4fmkhWS0ZdzY2jc+QD/L61qUpKOltz5ltfhJD8WLHUIPC9t5OtaEoae6x5SyhRnCqfm3 5HtjFN8FfECLVvDjeG9R02bUfEy3JjKE7vNj/iOD0PHWvffHH7OviPS4r3xPpXjCHRNYvMLdW1mv kW5yeFOTzXzb43+Ffjj4W6tD4yurKeFo5N7zcbDnpjB7/TvU9LByytfqtvTszq/hy7/DD4jS6XqN 4+naXqKlrWeJRIsUh52Ddxn1qr+2v4T07w5c6DeWt8t3f3sRaUiQMzoOQxH411GoXl7+0/8AD37P 4V0CN7vS0V5bl5gjpLjLDbnJz7YzXzO2n6hJ4hu9K1+2mN9Z20iHexLIwP3jk9MccUJWHGV05R2e /qX9H1y2b4Yayt3PHJeI6QWsE7lpCpOWZRjjp1zS/BfSL3WvF0c1t5Sm0jNxvmjDKpzheD3zXCLC yPJls46Amvbv2XfFOm+D/EGpSajp1veLdwrGHupRHHEQcglj071CZDfKjo/iB4d1nwfouqard6+t /cT5kJhYBi7LjByMjg9qpW3jDw74Z0rR7bwtPLf6vPiKeWaR49hK43ErjIySdvtWx+0h8QNE16Cz 0fw9PBcyTsBPb2gZsyDAwDj5gc15pofw817TbLVb3UkOlRaeF86GRALiRXXkqD6AD86bfY15VZOJ 638PtHt5Nc12WOxufEepR22Zr+4uVSINt3Oc9Tj+6CegrxDw/wCJLzw3qfiC/sbMXU0sT25kK5EY dsE+3H867PXNGTwD4NstRW5nk/tePdbW8khUgn7zcdeMCvJdNvVV5GuGYWxbdNGrEb1B6E0O9ibP lsa82parqzswKokMJQiHKKgPXGDyfWrljc3HjDS9O8K6DYW9lLCXa81OSbYJQT3J9BxgVb8NWrfE rUhommyQ6Ro8Y8x7m5baWX1/+tXfWegadpfh/UU0rSGuUhKxRX8ZYAbOrZPBJPNSP4no9Tc8P/s2 f8IXpsE2stpatDOlwt/cyFo5crkRbegA6n3rh5/7AvY/tUdglvKJHaSRUBW43OTlAfuqBwOK9A0W 11zxF4UFrcWs9zpcaSESX8+xXYjjbxzzz707wFoen+ONPj+3pax3Om2zRmO3m8qSXaNo3Z6j2XrV Wuiou2rL/hiPwfri/bNI0pvJhtHhe1i2+a8hHJGQSf8Ae44zUOh+HvAsaPBdafLBeRsWMUZdZZW6 7cg8KPU1wjWej+FLowgait7lk8y2JQEkcA4OawINQkhuJLmae5klC4AVWbYo5wSevvSsytWrXPd/ Afijwx4PvpL+Kyt5ruZvJttP2DefRmY9Rk9Sea90+Ffim51y6mvZPO023WT7vmf62Q/w+iqPTvXw 3D8RI1jmAtPtD4JDCEFh2HA6Cux8C/GTU9Mjs9PsYdQvyuWa1WEuWJ5LH2zQpGEqbb0P0LfxFJcW pntopLizifEylQQ5BAO0j3or58+G/wAUPEXxI1CGwikk8L20h8m5ljheVioHJxjahOcZ9KK05Uzn 5+XQ72TRfDfiLwdo8PiKdovMtY55ksrlgYXUAjYf8muZdl8JWd08tlqXivwtPF8t48UZurfPOxlf 74xznqAKsv8AEjw/4Z0jTAlkJ7mS1AmzHteNggG1D7+lang3x1ovjG6i/s9Vt9Ojibz2lKiYSZww wfujH8R59KyOvRI8S0SZdJ1q+OgeS0F/i4t9szidVLD5Sg+TcOcZBr6G8J634i1C6trWHXrh9Fgi Zrqa5hjaWIk7SdpAxg46jjrXI/ED4X+HPE1xe3OhyrZz21pJLHbWgYwscdG5BU5AOQfwrhPD/wAR PFvhnWheXNjNeabHbJBdiNvNMm5Mlg3ORt4w1VcmUeqPpjUvhb4e1m3lguYZNb1GQF4rq7cOwLAj 5U+6B7449a+V/wBpiH4j+BfBOraTrws7zSL+FInmhnEjDY4MbMOoOF2k9DgV2Hw1/aanttLv2ljs WurdURJLq88tmj2kiNVwTvHAIHcivOv2s9B8Z6p4Qu/HXiW4XT7W+lt7Sz0ZGOVj2s+6T+83Xp0z QwjLpI+MNJ3SavCGOcHrnGOaZruj3OlavcWs67ZIJNmM5H1B7jFdJ8KLW2vPin4XS7VfscuoQCb0 2eYN36Zr1f8Aas+Etp4H8WS3Hh5xcaDIywxSNKJTHLtDNGGHUAEH2zjrUzFZN9ip+yz8PfDPxY8Q a14f8TTPBJ9iNzp7xOEdmjDMyL25HXvWB4++Der+GL1Bocj61pb2rajFeRoVJjXAfeOoKHg+3NcB 4T8QXXhLWrW8RnMkMnyqhwxHcZHQHOD7V9FeNviNq66It0NOsorzU4JZBfW16jQCAgM0W0cJJ99c ejYrJajS3i9mdn+xv8fNO0vwXrXh7xJd+R9hJvYL6ZwI/J2gPEMnr8vAqj4q/alh0m8n8QaF4ZUx 3hkhFzKGEMi4ARf9vack9smvjm0mm1m+eKGB47dSTHEikg+pbHJxXWeGriwsNUtovFf2y8023yWt oGKEegGegxTuyeXl32Oz8DeDB8SvFWu2+oSyDVQvnQ29pgrIx+ZizdAqr1/Kuo8beAYDql14fsLa Cyhs1Ul3GHhJXP7x88n+Waj8F6pa2Wm+IJ/CcGnwxMnmzrJKftMFurZyWz+BAPOawvD/AMRNJ/tf ULjWbP8AtAXzeY0zzuqnjjKgjOPekK67nlOuWsmkXTpFKLgQsVaRSCDz29qwNU3XEyyyFQx5ZY+g 9s10Xje4stQ1x30pGjslO7B569h7CsCRVZipOVA5aluXoU5THcNEJcpGCQAM81qaBoFzqEN59ntX uAjF1kYjYqggHOf881jzyFmO0EqBjp0rr/Bdx9ojitZLkwlUKshIVXTknJPr/WjlAy9YsXMaQrbv HMijzAOcn2rn1t5Fk5PQZ2jpXoMyxRxQtcw/Z/maX7QjEuVBwFPYcjj61gXFibiYyQkyMoUIxXG5 f4Tj3FGyKb1Kei2rSzCOOJZncH5SOcjnr24q3btczRzTmOQW0TFNnUBsc4x0rsPCPw/k8QXERtV8 +ef5YlRtqs4PzH2QDj3JArS8SeFtR8KaelrePDpwmQnay56Hoe+SfWluXFNnm66vJHDcISZnI/du Sd8Dj+IHrnAxVnwd4ohtdcgn1JcXcTho7gDcdwOdwB70un2UTRy39ysUr7yDFuIwMcMSPft71Gmp aVJYvbXulRTTlMR3EcpRgfXHc81aIaufSGg/FLw1pMN9q9zrmlajqN9YyQ3mkvaybxuH3Qdu0HAw B0HrXy5Y6pHZeIrq9S4Fstm5uLWKT94HG7IiI6Hg/pU1vqd5qenxaWsKiRnwjgbXlzwBu7nmp9e8 E6x4b09r290xLAWhVNsnLS7h2xwcDk1QrWVj1v48eN/DHijTPB+r6HdNPqVpaR/a4oYfJSBwc4B6 sc5Oe3avNtY1O1tbGBiqrLM/mHYTg59B61gNZy2+j3VoLtGlMKXCJF829TztPoRUc2oJeWmlyP8A P5cZwuOQRSNFLYi16+nWTyhIyRxnDRyZIyec/wCfSrfh24il1O2W8uGgtpAynyeMkDIH54rKQi6N x5sDTMwLIc9WyOtGi2v9o+fb28LRSRxvMGfJO1cdMdDmjToLqVtF1JtJ8VId/wDo004WVW6Muehr pJNJh07Ur1VuzGqMdvy8bT05rjZIfkjmR/nDZYN27816QdL/AOEiW337UUkLK/UrwCp/LihrS6CT voI99HHL+/iVgY1RJI2xgbeeaszal9vjtdNicmzDDDOxJAH8Wfbnj3rN1LSiynCswj+QE9MdB+NM s1TTtH1C7mQ7o4/Lj9znk+1LqT1M/wAaa3JdatFbW6KYoeBsXk47n3q9Hp8tnaLfahMsVsRjZgbs +m2maXZpa6fDrM74a6k2omMkLj196oapdILj7v2gI2URycOx9fpT6lFm68SS+H4zJ5Kq0keIIW5U L6ke/WsSD7RqGZmZzc3A2swAzt9B6VUvJ1vb0tdTGSXIMrgfko9hV+yuITNJ5RNuqjK5+Z2/woeh LbPWNT8Df8IToNjDq5ubC+ZGEsLoGSMFQVYEHnPpXnk9lEsUoQ+aN2dyocYI68/54r2z9nzw/wCH bq11PWNc1FrqygVIXTaXljLkkkBs5BUEDHetX4qap4Svm1yXRrORBcwxSx28UP71AvAY44QAYyPW jQUdT5vMmMxhgqnn5QQT7ULIY1BAV4Q3XOCT3OanuFimaPc0gm34KsAox2yagaBZlfcgDKOgPGM9 KkZfh2SW0dxGseAh3+WRu5OAfrU39m3JtY9xVIwOgzu/H3rKVI5SDGpO08KOPwrqIJZBapIGTzO+ 7AIGDx70hq3UisY4re6hZYBI0cSkRBTycdTX058A/HUl0smiXUdnf6fqkJEiyYCwHHK4PboC3avm WC8hjZ4oE82d+RMoO1SD2zXqPgPw7JHeaLdTTs6x5M1nAoLbfQDvn360c1tUTy36lT4neAV8K+Jv L8xdQjmkPkR6fh41bJOzI7gY461geD/iIfhv4ns71NMhjmS4ybiVA7R8gFgp7jkjPevtfUPh7J43 +D8N1ZudPvbBvtmneciRGJgchsYyS3TmvnPxp8J9G+JXhD/hI4NYW08aRFjqmnzIsMPmAniMD889 62trdHVKXtIWa3PVX0+z+MkltrGn+IbiXQpbzyLq61LBJlYfK5txhVOflBPWvZJr278E6A2j6Vqy rrcFuY445Io4lO1QGkYLxjpjjnIr82vD/jbXPh3qS/Y5mRElWR7dxmNypz8wPXpX1t8Kvjv4N8aa Vcw+KrSS28TXUZ/4mSuXy3XgZ+UdABVvQ4veWk+h6zFoOqfDpLG1hihltLpFS6u1BVhOT/rGAPAO eTntmofGXj7Vvhfa6rqE1u8ttqNgY3e3gHlG4UEKRgnGepPtU8fjrSNR+HmtQ3EAuJr21M6PDvfD YOwH098+lW7nxzpfiT4ay2OoaRHp9/eWDo5SLEahYyw69yFyBmhdym4t+89D571XwjqcKf8ACV6R bf2np2pWiQarbudxuS3zEg9nBOQe2cV4Fpeual8NPHh1bRjJbXGn3IlhjkGGXBOY2Hfg4NfYnw+8 Oal4YvNK0D7cs9pcRLexRNMNgkC7sdTg5J49q4b4keDNLt77VtY1XTXistSjkjvbpAB9jvAW8oju VIHP1o0NP4id2fRHww8S+F/2pPALarqcFra6gN0Vxbsw8yF8fKVPXHQ+/Sua8CeKpfAHii/8P+Kd QD/2c+y0zyXU87kwPugDn05r4N8GeONc+GfiSO50q8a2kjkwVky0Rx03L34r6K1RvFnxChn1htQ0 jUU8sFZ7eQwjO0btvsM4NO6OaPMl7OfyZ9BfE/xB4T8Zaayah4st7WCaVGg+xzBkQg5Lvg5z7VwX iXx14Q1qxurXV/Ew1C2ii8qKKRg/2hhwOew718f3+oXNnJdwT2ykROVLxvxnueOtc5/bErYwd4Q/ daobOiPNHr+B7B4c8XT/AAO8dIuma7MdAvnWS/8AsLj5oj2GR1Ga5/4ueI9L8QeILbX9Le6a2jfZ Mbh1Mky5zlseorz+W+a6hbcwAc/dXk1VkmmsbdogAySDgN/Oouxy5VJyXUgvr4SalNLCGihdiyx4 5AqexZ5piMtICOEU96zYZ0acCQH5Rj2rqfDNxb20ayPHj96wdvwGBQF76HdfB+6i8I67Frt9pcV8 I1K28MwO1G/v8dxxiu58ffEu41SYanLYW/mLC0Mvy5Uq42k8nkgfyryvT/EW3V4wJlSCL5w0oyF9 flHWuT17xNe+LL1rG3k/0ZD8yIdocjJyTRcLJK5q674pt/EOpNM01xLBBuisraaQt5MYAwc9PWsr SdDm16GVk/dWyMNzMcLn0J/OvRby98E6L8K7bT9KtI5vElxB/pk7fM0fOeD0HPFc34RvNOt/C97D cTyCa6l5hjxgqvIPrnPFXZIWulj0Dw98IbnUPBMni6e7gjsYMiGOW4WNmWM44XqR1qA/FjVfFmjW WiR6nZaPolgjCGEpsNwc5KsR1/HFclqep+Hp5rC3lvLqDTCGdoQd5RQPlBHTJbriudtdOXUY5ry8 imt9Nzi2VIsLNz1J9PpTVhep7dH+0dLpeiRaQbS11G8thtjkQGSPBB+Xb2xXFQ65rd0seo2upWNt fQzMkUVvFukOeSTjtnp6VzLeHLvQ7WDU0Ait5GwqxNudF6GvaPAdrFqumnT9B0eFp0g89L5mPmxn oWc9PzqeblE1okULv4e67ceG5PF+seM9KKBQPLjAaTzORgoD973NeX6h4n1K3uIo3mOqaeoIjjZR GQT1PHX8a6LxdZWlnpc9m/mxanDIXkkbpKT/ABZzjp6V5jNe+WwQMZioyNp/nSlI6ForS3O4T4kT W900sOnC1iaMRyxxsuHA69uvFdbZ/tJXelzBtM0yLT7jaqG5ZRjaOdpCgZz3rxxYbq8kQYTLfwt2 q81heRKVAi+U5OP51nzEcqkfSnw1+OHh+7kuo9cOoanezSb4ltkcIXIGVCKQAp9STRXG/s5+CtY1 DXp9ei0+zvbPSomfy7m48tXcjaAuBkkE5orZM5pKKZ9DaP8AEpdW8M2cGl6Ws2r6fDE0d4ZVkXAX DDbjvyK2LrxfY3WgWFxfaFbXMkRkV1WMtGzk8s5THA4/ImuHhaPQbjTZr5INPhUxwTXGlqyOGKAh s9+M59a0f+EV0XUfF7xG31G9sZG2xSwysks8hGfukgHg5PTvSRvbSxo6xrnhf+yHgj021kvHnHMN 7NvbjpsBGFABPPFchY6pq+qa5KngE3WkzrIiYjhdrZIwuGd1cknOeABXYeGLSLQ9eu4dI0CGK/tl No9zPtYRSkbmyTk7ggH51veEb6+t/EFz4h06za9hvbpbWR4GCr5S4AlIHONw5J60E6IqWf7NOma4 s8+oajqreMbgAx6hlLfynPRhEvUD39q8h/au8B+N/APhWGDxJ49XxjptxKqW6u2ZIXRTnP4H86+0 vC8a+Irq41WeVi02YWeNdhIUkHn+79K+Zf8AgoU1tY+DfCVtC0URkmmlS2h6Iu1cMx7k1dhXTPjT 4U6TPrXxE0LTbe6+xXF1eRwQ3GN3lM7bQ2O+M19O/Fr4Ky2txpugalLqD695DhXJEdjMUIVGiCYH IJJz8wIrwn9mjwXB4/8AjDoeiXE81rDdGbM0P342WF3VgfZwp/CvqvXLHxRHpY8NeKGGsTeF1Oo3 NnrDlJ7xQ21WglX76sC2M9CfpSkTDVnwJdSyaXfXUYK/JIykYBAwSK3/APhZl+vw9ufDbBBYSXaX Ak2AtuAKhV7gHOT9BTPix4ettL8WtNpdjf6fpl6gureHUdvmiNxksSOODmuStbgT3SYyyIcx+7d2 rG1g1vc+gv2avHmn/BnUJtfufCV3r92tk8JMseI90pGw4YcdMccmtm++Dfjnx5BJ4j1nStP0u61K 6kuWW4k2zTtI3ygoPuBRgAfWu1+F+g3/AO0d4y0q80RYV0XwxZ6XHdWVxhWurhEIIX2BLMWPtX3l H4T0ZZ1jlsoUlkRWYsAc47f/AKqrWW4R0Z+cdr+xh41vLHUpIr/S7d4gubUXGDID3B6EcYrwXXNA m0O+u7HVhPbXVtuVI9vVge+e1fql420uytX1dY7f7TNBAZvtUaEJCo5C7unBzxzXwn8Q/DN140XU tXe2AiEreXfSMVLkdjnr04rOVo7lyStseBWUN5cQyTRQHYhAYkcVTurVhGz7sDPSuwgI0KSQP87D I29lOOuO9Yd3DHNHKw6Z+9jrWXMjLmOcuIxHCGR2bOd3HH+eRUyxzL5O1CWZcnJwW9vyq6dPeONk Kh0BDHNQpDN92T5FxxsHbtV8ytoO6C61p7yGNHnc7cKwbqeOn6Ui3Rgt/IjysrnJkz6dKivLVGVC gIJODz39adY6eON5JZDkDPBp8ytcLpHovhv4vnwj4KXQtH09F1OS6SabUmwZGVQCI1P8KggHA61z Ov8AijXfGmt3N5qO64mnJyy/Jz9fSs5Daw3mHT5gOG9/StnTLqCORQVQoTwX5/CsnVEpeZBb+HrK bTZLmfzN7nCWm47pCCM8+nXBqpDpkWvatZ2v2BNNiH7tUjBG7jqSeprfu7qJpjG7jCj5duQoPpUe oXsbf6+feFQbFQYCt61PtdSmzQ8TWthe6TH4c+1xu1u++21BYvLzhclfqG4zXNWvjTVfENrJoeuX RnWzi8qFmGSFz1HqT6+lJeXfnCKOQ7YQMpJj5lPrVOawa8jSWKI/2pE2Ac4Dp2/OtlNsvSxy1so0 fWFguAx+YqshPBQ8Vp6fpcNnqV5p0hBfLNBKx+Uqew96tataWuuaHJPGVSSEZ8v+JWzyD6d6jhmb VfC0M8a/6bZybQR1Ix0P1FNSckJluzsbazkJZC/lLzvYYJ/+tWa1u+lXV/cRTtbxrEykxn76nB2/ Q4rYtl+2WYkgiicSgs+e3qPrUHjS1hXQ7a4gQwLIu11zwSp/WlF62CKOd0vT7m40nV7mNGltFCpL IMfu2PK/hW34b1ieNLXY+R9wqehOen8qp+E7eK50eZZ5JPLaThV7nHBpPCSTrqkltBD5ssL+btbH bIzzVqV3YSZt6xqAjjaed2ijJORjBJ9qpSTPr00MEAYoy5eI/wAIz3+vWs/WtSbUNQSGJFkRWKRl uct3b+lbei6W2nsuZd9ywO7jrx0pSfKM1NW0m5jsYoTFtwA8KKOOmOK4nWJpL7WnghXPljBkXoGx zXYavqk9pDujAneNdinPKnHJrB0fR5Iw653STnczY+7nsaXMorUqXQzo9Jitt/O5G5zjk1bjtba1 USBW8zkLhscdqtapaS286hyVQ8bo16U9NLmdgm0eWSB5hHU9aSkmjNs2vD3jK5026VLNmtZbhBud eFJH4Y/wr0HxhpureAfDqXtzNbk61CVmS1vUkluBncGZQMhADgj1FeR6tqIsbuOJIlLeXtVc5x6/ TNXLHVpdQjmSEea6RfO0kn3I+6r/APWrSO2ptzWVkjJvLSFoY5IHaYu254wwJUen1BFS3N5aWckL qE8tgCUfuCBlfzrEmvpmuD8iwKSVxH/WorqbdFGjLlUzjjn/AOvSZHXU3mkjLPsPkrszvOCetWbW dbizuS0azSbVBeQ/d+grn7SYNGwwDngDPStGwgRQ5LkyMenbFJk3Op8J+GbvxZJHaWZVriL/AFcL EBmB9B3r6H+F+l6/4J02DV1tIDcCU2yzNh2bjGAp7/Wvmzw/rEnh24ju7d2TUIX3Rup+6MYr3z4V /Fy3xv1q2hnuI38z5DjePQJ03U4mXO09UffPgVdQvtLtbrWXVbIWo3JPGsflezHuPevnT4weOPDP g74gL4r8O6dFeToy2uq2bQo8FxAOrJn+P3rp/C3xd1P4p+H9Y0Sae10GylgZY5pAHO0DoSSMHFfI urR30Wo3MU1/iKN2QMoADAZGacpOKvE7KEKc4NT/AK9D0D4z+MvB3xstUXRfD9jpatEv+lRx7J1Y cbSBxXzTqvh698NXzW/E5AyGhOSB2rsrPSb63vpToqtIFGZY5ORJ7in381s7mWRZILmIYnhlGGrH mlzXPQcacqfJONmupe+F/wC1B4k+FtnLY20FlfWMsflvHfQ7iAQed3XNetQ/HjwV8UNGs9P1a6uP DN2LZxNONzpLIFOxVwcAkccj2rxWLQ/DevWKI58piMFlGCi9fXk5rkda8DCxknawnaW3UblEgG44 7V0RqdDznRabcJH0/wCHvEkWnau+kreW9zLCvn2F00gUqCoJkznG4Efd+ldBq3xK8CeItK8QaJq9 y7GZlMMgLFGl2gPJ6/eycfSviCPVNQsGRtssZUkgc9DW5pniSSGHzGRJ23biG689qfmSrLdHda7q nhm/t5rCcbL5YhDDequDujyFdh33rj6GuCt/EF7ZRi0leRY0JKbWIH1FGo6xY314ZngYY6FOMHj8 x1q9Z6pot/tXUWcjJCtF8vHap1L0myfTZpLq8AX5twydx/nUcumytJxBtV22jj71Z081vYXBl0+4 add3yg1tQ+Pt6xrNBGJFAwyjpUSvfQ1Sje0mWbXQXmXyAv2cKdxLjk/Ss/xBobWygGf7QuzKk8YF WrjxR9sQSyS/dOMBMYrH1bWbe8ClXyQuMHP5VPvG7dBQaWpzbOY5gUjPy9yepresbdryHeJPK4yQ x4z61m3DLNGqoyrk4JYVas76LTYhKNtzOG+VGyVH4dzWpwxtcr6tczWsJYBlDKVDE4De4pvh6xja 3T5mkuLjIEat1qG7a81qbzZIpXB+ZWCHaPp6Vp211qAs44LfSWDwjCzBcH15oeg9XLY1JLGSx0WZ 2jCLu2bt38hVKO4t7eyK7JHuNvDIcms6zF/It19ud1yQqo3brzW2t8LCxgRQqFAGLBfmY+lU5dBX 1MO1xfXQe5cuFG1Y/wDGuol1K8kihga9MkduAEXd8ka+gFYNxp8eoXbuI2jeTpt45qxYeHovMkju DLv6Etnr/wDqqEHLqasfiW5htZo/NV7ftGzZ2++PWr+jfEC90W3uni1GW3+0R7Dbwnhx6HHQVgye G7VZpFeRki+6CDxmqEdqtmxFpMEO7btf7v503qNx0Oo1jWNQ8VTIL2aFkhQBUhPt3PUmm29nEsKq ijP90rzWB5jNOFeFixHDQd/firEOqXFptWGQSleqzDBJ9Kl6jj5mm0AjkLR7kIHrkfjV2O48iFo5 h+8YZDZ4rGt9d8zzhsaNSMnAyBWrbtbXEkf2V97KuWZiPT0NRextpsj6G+AMkNt4DhWR5Gknv3mn WNtxECYAAUdNzcZPWivJPDPi3WdBsUitpPJst26SGEY80Z6Oc8jPNFaKRySpTb0PdNEk13XrHWLa 8S1lecRXXlRWzyN5R4aRXP3cDgZHbiugTxR4TtfDayxanfC4s12wqC8STsPk4OPmbk8cg181aX8f vEmgtHFY6hNDHsEDNGqrL5QAGzcOoAHB6g812Vn8dfC+maBq1lpnhWa1luGzHdSyrPJDnaSAzHPO DyPWtvZz7E+0jfc9S1TxN4l0PRre+03R5ILWCEWxvpAIY5WY/wCsdMliwyRuOP1r1DwZ8L9Vk01N JXx1qEb6vGJLcWUEYimBGXOcE7VJxjPevIpf2sfDreE200+Hb5Yrox/bJWSJ3IDKSFJbJyB3xW7o /wC1J4D028u5rKx8SaFbqVOn2vkQXMMZx8zbTMvlkn+6elV7OQuePQ9utfhL4tkSBIfHuoxXQAHk XECPEzoNpG0KOBj1r5l/buh8WaOvhjSfFEumTTwRSvBcWMbI8qlhkuCTg+mOK9h079uvwO1vMl/p niKC8WUyotqkBiYMBk4aboTnjtnrXzB+1j8ZdE+K2taRLodnfWkdvbMkpvlUM7Fycja7cAYH4U1T nfYOeL7GP+yP4q07wj8bdD1bVpFhsIFlEkjcKhaNkBb2y2TX11+0b8S9F1+BtU8MzXGp65oKsk8t vb+ZZtbygeZFLMcKuNqkc8HHFfBfwt8UW3hPxILm+luI7KaJ7W6ltYleZbdwBJ5asQN5AwCTxnNe y6j8S/DN9NeQ6GNb8H6CtxDc2Xh+1iju7WWVDxLcCSUAtgA7QpGRzRKnK+xFOST3OL+I3hnxH8Vr G38RWmiS6b4Y8i5GmReYJpJRGd8gJ6lcljzwADjpmvDVUWsCNvxMOEPp719V+Dv2htH8F6XNb6ra ahqt5pxlt9PjWOOKCexnDi4jlUPw5ZwQRuwBgYr5j1SzkXUnk2JGjHeq84QdgvqPr6VHs59inNW3 Ppr9iseFtYm1zRdYvLjS9YYJc2OqWtw0UsZyFdeDhskqQD3r6h8eeOPF3wO1ezludSTx9pOVUC4I jvoV9CvRu/OO1fmr4c1I6Ddx3cBdbiNshlPH+RXsmvfHptRgZUW8u0aPl7sgsrYxkYJ45PFQ41Fp YyU1d3PWvFX7Xmoahbawum3TR2mouy3EF4oJiQcKinryOOK8O1z4l3GvWRiGIoFO/wDdk4yDwCK8 41bVBqEzvt2sxycAAZ/CqlveMsIjc8KcjaOv1rKVKpLoPmj0ZpX2oC5kMjHc0h5PpVG6uAI2xt2E 8Y7e9C3ibnLJwRwMdKoXJZ02xcEHjdSjRmuguaJOuoRxrtEhcHowPQVUYTXU0jeYUi/hUmmNHKpj ZCgb+Kpdu1yxOST0q/Yy7D5oj41jhg+dvMIORn1pVunkZWY7UUHaFHemqF2sMZB5+lR7dkhK9M8c 0vYzbvYLx7li0+1XlykUMO8k4Clc5+tdZoGl6f8Aa40vVlUSsArxrlV69fxrlvD+saj4fvhd2Vx5 E4DoJFHIVhg/jitVb6zt7dIUuL2dSys+QFBA6jAPr3qXQn2Jur7j/FGnppt19nhmV5FBcyI+4N6D j0rK86OSOMySuSBu+RcY4967iHUPCU2mW9tLbXtpP5mZZIYo2ynPOS4Jbp7VxuvLDJfs2nidbEEi LzsB8ds4yKPYTvsac0X1KtrcfaI3iMiiQ8KGGRjr1rOs5bmxvze20hneLIMQydyng4HtXQaRpOg2 4nfVDfTP5BaFIY1CiY9A3zfd/Wu18IeJvDHhu0Nkmn3Ea3Ea/aLpo45JA4GSEBYAAn8a1VKX8o+a Pc8puNtu0l/buzQscTw+oPf6io9BnXSdRmhQkxXAEqNxg966LxlcWGoXwu9JiaDc372ORQqyD1OC ea4v+y7qPUBNE8aQq25IyxOB6dOlVGjLXQbnHubkV8mm37QPt+z3TZjZTjY3cUeMTLF4bhMgKHzA EBA4GDnmqt1YPcM5wrIwB54Kn24rKv8AS9Sv8JLcRtEn3QWPP14pRoyvdoIziup0ngG387RUKja7 SsxduigVga1dS6H4oupQcNMu1gvcMBnFb/hTUW8N6SImhjmu43dkOTsYEcK3tnmufudKvdQulmnk iMrNl2GfXtxS9jNSvYFKPc2PC+kmBm1W9RvKb/UoegXP9ea6G3v47qZpNio8IJ45z6f0qnJeK0cU KqzRxoEAPHTPb8ar3jxw6bcLb7kupjgE8KB9etS6M29UHOr7mZbxt4l14JkrbWvLn37/AK11yfZr WNEDBFXq3dh161yWl2p02xKRANOxyxJIU/U9TUwt/OdpLs/aX/hViQq/hUTw85vbQHUj3Ne61S1u m+zWscl9c5wkceMHuST06U/7Ne3wQFkslYn5Y23Nj3NY0HmQsdgWNWHO3r+FaEV88MKg/Mw/lUyo 1ErRRDlHuTN4Rs0+x3KfvSWPmqxJIrOs7eDwzrUOoQIshtpVnNvcDMcgB6MO4q/DrVxHHIgIVWOf lNYesfbNTuGcPGmRjqc/yqqdKsnqinUTXKJ438QReJfE97q6WkOmJcyF/ssH3YyeoHoPSsOQ/IrK oIfgDPWrcmhzSMCXjyfvcn/ClXR51ZSJFwo9T1/Kuj2c+wc8e5Xji2sgPyjHPFbVq2JI8ALtPJY8 YqounzhmJaPJ+v8AhVmS1laMBNuSOck9fyqfZT7DU49y+8JV4ZgfMWTrzj8KvRa5Jp7IsXyliN2e q/Q1kW8EsbAeZkelXLyxhnUEGRHHO71NL2U+wm4vqehaH8TZNJTNkQZQ24tIxYf98nv71LpPiiDU bt5dSRrxi24RqcKM9zivK47WSHjfuz15xV+ylkt8nuwwcGs5UanYcaipu8Wes6P4muYby+aygXyp PlzvCleOMHvWH4ijfUtl1HJi/LlJC2Du9jXJ2+pLHs3GRgp+6OP61O+qQtcvLHHJHnlQTnFEadVP Y644pW5ZF/R4GGoRRxKol5/dt3NWdQE0dxJE8yh05APIB9Ky21iCZlaSFy4cFXU4Kgdcc9aSbXFe /J2vPa9f3mA+fQ46ir9nPsHtIdy6t5HAoZ41uivG0jjH1pJtPstbVmjsVt1XlVi4J9Saz21S2kY7 hIgOQdqj+Wa1tH8QafprQs0EzhR8wGOfTnNP2dTsVGrB6N6HL6j4VgjQNFNIrMfu96rL4dt/KiZZ pSwbaw2jj6V3mpeJtL1LzJXtphMy4XbGoC/T5q5kaiun3U5tlZoZRtPnKM4Peq5Kj6Ck6S1TJ9P+ H97eSReSz+RJwGKd/StKL4R3N00xFzIpjwf9V19aueFfF1roLLJK95IFHCqBtH5tWpcfFTdqS3cM EhQJsMbkAN+Gaj2dW+xvCWGteT1OY1T4c32lsv2GRtQaVSWjZAAnvXOT+HfENnBNPNafuIcb5Ao2 j0r0H/hajRyyPFalgx+7J9cnkGs/X/iA+u6Xc2skPkLLyEjA2596ahV/lJcsK72djzuC4aEssl1E 6OcmNo+n41teFZNBsrrzdQglmA5AzlR71nfZU3AkZPar9qtqF/fQb2z/AA/TpVezn2OOM4Re53kP iTSnkjnjWOG1Y4WMHnb9PWrd94h03yd0CNBIvIU4O7PGa85l+yMYz5X3Tnb2x6VFO0ZbdFvRugXP AFL2Uuxv9aS2ZpareWVxaQLb487efNZupPasoJ5+oIjvtjBztAqMK21dxyd5bNaIut0hEi7IWXBd VywrR05JWsc/tYyldsTesUwSFisvHzMxprXF2+VNw4Oc8nNPkay25CS+bkHdnqPzqnJKrMxbdt6K uelZ+yn2NPaxWzHy25RXU3Dy7RvK+9LtjtYftEIEpOMnOdp+lVUhzM0jHAc8qPSrEPlxrtAJ59Kf s59ifaR7klrMt1OXhVoW4y3v9K0fsYMw3r5obJ6YPNUkvPs8oeMYOMHdVptYaTHmJnAxgD+tL2c+ w1OHViR2/wBnmwY3YdB5YAx9amksnuIZC9nsLA7JMhfzqSz1a0iB8yKQnOQRz/M1b/4SC0KgGOVx jlWUY/Dmp9nPsaKVL+YzYI7n5Yz5kO3H3pTs6UVb/ty23Y8qRo+mGA4/WitFCfYPbRXUl0vS4GjL bVlkJYc9B71Bc2kfPlsGZn2gd+OtOjWWxhXy2AWVcnep4JpkijyrcyNs3NuLL2Ar1Dxy+10jwwRq mWyGYfStG3VTlW+dupLDIrBt5h9okm4KFggJ6/5NbKXIjhG4kerccCgRHeW8UbIy26ytnbt9c+9c 1r4C3Q24A29FBGPbmuqimQyB3z0+SPv9a5jxOxbU2ztzgdPpQBDocSy3LBk3gKTj+tdRLKtukci4 KYyAP7uK5jQ5VhklkOPMVcpnv6/pV2W9eG1JGGRxhVPbPXH60gE1O9+3TROqqGh+Yt688CodYVLp YWjIYbS2O6+o/OkjkFurBV3D+Inn8q2dD+G3jPxPZ/2jonhHXNVsZCyLc2OmzTxEg4IDKpBIpXGc kvHAzmpVbaD3rU8S+DfEHg2aGPxBoOpaHLOC0KalZyW5kA4JUOoyBnt61jbiPakIVm9aZuGaazev JpAhZulMY/Oee1P24XPar9vYvFJG5j3IR3GBzUV7DJbL5TDEeSVOKAKRx2pKb2qWBdzZIyB70AN/ iwOa0rjRXht1b7z43NjoBVTT1EmoQKeAzjH510EsbxxyCdthCNjnsD0oAwfJiWz3knzc8LVqO0L4 Z9sYI4UDmnGMLp8TuqhGmxu74HWr0FuNQlVIlZbZT80vQkdlFAFSEQREmSVCVPTuakvJn1CSIxW7 fZ4+FyMDNbS2NtEoWOEI3TeoyR9ay768eRlhhfDgkDtz3NMDPlM0kxt8gc5O3nn0q0NDlkOWRgcd znNSwwtbeRJEpTszHqx7mtCWcwzKAN4wSSeuMUAcvqcfk7QeOOBWYw6V1EnhPX/EVjqOr6VoWp6j o2mr/pmoWtpJLb2wxnMkiqVQf7xFcsfvCgGP/hB709oj5Bk6hWC1GvDe1XI8NptyQOjp/WmIpKAc HtUiL++XvzS2sZlkAC7gOSB6DrTFfbIxxnnpSGXh5cdu7sw3k4C96qrmc7j0FMZt5CgZY9a07exm jRXIVB1XdzQBWhjEjENx7+lC2rtIQOV/vVZvNNmtSGkb7w7VVSQqMbjSGMkyTwOBQFp7buxrq/A/ wl8b/Ehm/wCEW8Jaz4gjUlXm0+ykliQgZwzgbVOPUjqPWkI46RtvHeouvPeup8dfC/xd8N7tIPFX hrVfD0shPl/2jaSQrJjrsZgA34E1y3rT9AsL3o4pq/NTu/SgByrUi1EuM1NFg4yKAJRCWw2MGlEj YKtyKeswT7ybvxrq/h/8LvF/xX1Ga08IeGtQ8QXEKhpfscJZYgem9vurntkjNIo45o9vPY06Ndw4 Fd18Qfgz49+E9vC3i/wlqeg287+XFcXduRC7kE7RIMqWwCduc4BriFk2ZIo0YD1hIYZ4PWn4JY45 X1xUTzs/c0ecw6cU7D0JZIdqYwC5PBqMn5eRg4prSsy9ajMjdCaAuSxqrdabgxyYBz6VEcjvShul BJZ85schR+NQvNuBGMUxmyaaaYXJFm2qFI49ae0wbFQspApqr3xSsGpZjuFjyNu4GomkBVsdc03G Kaf1oGNqVDjOR1qIAU5st7DtTES+YijtxULN83FDRnsc0RqSfcUAKvRc04Me9J0YChl9KYhzKKaY 8dacM/SnKpPfNSMaDQG56UpU596Np9KAF465pQwpOcUdKYD87mp646dKiXPWlY80hkjKvGGoqDnN FMDoZG8y2QiTenByfao5Zo5pgztlFTA29KYsv2eLaAAinIUnNU0uAokYjcW49qBFq1jjmhcDhiSR 61asZAuRNlpt2FUjg+9Z0cM1t84GRw3Bp6XRmk3MsgI5+UdKBG6VWFyOWZlya5fWpN9/ITXRae1x 5ZMcKoO8kp7euK5fUi32yTe25t3JFAh9iOp75wAatLGJl81pFKqeI2J5rPhxs645/GpwZItpb7pG QD6UgJZJGjV03YXHAYV94/8ABMX41eJLrxc3wxd7U+F7XTrvU41WD995xli6vnp87cY9K+CJpWkB LZyP84r63/4Jbtu/aSvvT/hHrr/0dBWdT4WaR3PMv2wvjb4k+Lnxb1ay8QNatD4b1G+0yw+zQ+WR CtwwG/n5jhBzXhJfmvSPi5dPpXx88Z6hGoklt/E97OiHOCVu3bB/Kv0jP7Sdj8SP2J9X+KXjvwZY a1bWV4ufD8bt9nnlS7jjg3l85USMjMCCMA8HoVzcqVkFuZu5+Ty6ZeGx+3GzuPsOdv2nym8vd6bs YzViz0ybUZUSCJndyERIwSSx4AAHUmvvX4Cf8FGvEnj74r6F4L8WeF/D6+Fdfu49Jht9OtpEa2Mr eXEuGdldNzKrAqODkYxgy/Hj4veHf2I/ihd+F/hV8PdFs9bv1XUr3XNTRrhkWVmIgt0DKY0AHQNt /wBnjNHO72sHKt7nxBNZ3tndR2NxFJbzxgErMhRlPBGQeen86j8TxH7DEzcMjEc4BOfav0efxvZ/ tmfsj+Odb8T6FYWHivwvbzzx3lohADRQ+eGjYksgcBlZNxHfPTHyN+zN8Z9R+BPxK/tzTNNs7251 C1GkNFdFwojkuIWLjBBzmMY/GqUm09NULlsz55sdPutUu4rSytpry6lbbHBbxl3c+gUck1Nq2j6l 4duDaanYXWm3JUMYLuFon2nodrAHFfqR+3Z+1Jq37OPjHQ4vCXh/Rm8TatpubjXtQt/NlS2SV9kC AEHG9pG5JHzHjJyOX+Anxy0f9vzw34g+GHxR0PT4/EUFk15YapYRFTgMFMqAk+XIjNGcBsOCRgAE GOd25raFcqva5+eHhDTVuLg3MnIi+6Pf1rq7/wAO6vrti/8AZWi3+phG2ySWdq8oj4zglQcHpxXr /wCyL8Bf+E4/aNvfAWvxebp/hqa6m1fYSBKLeUReVnsGkKg99u7HqPdPGX7THx203xze6Z4A+HVz 4c8DaTcPa2FqvhqZ/tESNtDk7QAGxkBAAAQMkjJtz1siVHqz4K0zQXvFD3e6OGJiqxNwc55z6c1u KBbxqFUKq8FR0r7q/a+8FWnxG+BPhn4wP4ebw14pZ44NXs5IXichiyHerAHKyKNrEZKv1PFZ/wDw Tq+MV7p/ieb4ZJZ2raffPday92S3niQRQptAzjbiMds8mjn93msHLrY+Hb3UorW1eQ8yY+UHqTWS NNe1jSXAaVv3jlj+OBX6L+Iv26tH+CPxa8T+EdF8BR3HhrTrq5iubq1byrq71HzQZpWYjbt3ecvI JPykEAYrE/YL/aAji+JWt+Dp7GK0sfFWoXerW07uTKlwQrCI9sFEbtndj1o53a9h8qva58CiaW6V gA3mE7gDxtqtcTPcOIRlQOJWHXntXr/7U2ua5rX7Q3jgatp8VlrseoGCZbcHytqKqI6gknDoqsM/ 3q+0f2zvj7qngP4MeGvAmoafYv4m8U6Mv9rQKXC2SbUU7ATknfvUE/8APNuBRzbWW4uXc+P/AIW/ tka98CvhP4o+HmnaHpuo2urrK0N7PlXtXliEbkqBiUYVSA2MHOcjgfNLfer9VPhT8eNU+N37Gfxk h1HTLTTl8NeGr3SYPspYmVF01/nbcTzx2r4u/Ye/Z+s/2hfjVDp2tK7+HNIgOpajGpI+0KrqqQbg cgOzDJHO1Wxg4IUZJXbVhtPRHiWjeEtd8SRSSaRouo6okbbXaytZJgp9CVBxVOZpLSOe0lhaKYPi RZAQysvBUg9Dn1r7l+Lf/BRzXPA/i678KfCXQdA0LwdoczWVsXs932jYdpZVVlVIyR8oAzjknnA7 Ga88O/8ABQ79nXxTrVzoFjovxa8Iw+a11ZrtWb5GdACSWMcgjkUK5OxhkH1OdrVrQOVbJn5x2tz9 ld2xyVKjn1pkbfMxr9Mv+CW/xu1LxDot78MpdPtY9M8P2cl/DeoW86VpbnJVgTjA3noOwr4V8K/E S7+Enx8bxhYWsN9eaRq9xcR29wSI3O91w2Oe/aq5ndq2wuWyTucbounsx+0uCFz8rEcVeuY33iJH y7NkZNfoR+314tm8dfs3fBzxNd26Q3OtLBqMlvBkojzWayMozztBY4zXB/8ABOHwVofiD4jeJ9av dPt9S17RdNWfR7O6K4MjMQ0gBzgrhF3fw+aT6Uuf3eaw+XWx8ea54L8UaTYf2jqGh6laWPy/6VcW rrH833fmIxzXMnLV+hC/tw/FjwD8QfsPxe8KIvhi4d4r7R20kRyCI8EwF2AkAyPvMwYHqM5r5L/a P8UeAvGXxLn1P4b+H7jwz4akt41+wXESRsJhnewVZHAByMAHt0FCbe6BpdDL/Z++H9r8VPjV4P8A Cd9K0VhqeoRxXLKSGMQO51BHQlVIB7Eg19z/ALYX7YniP9mvxlYfDP4aaNpOgabpmnwu08loHA3j KJEmQqqqjkkEkk9Mc/nv4L8Sal4C8WaN4k0iQRanpV3FeW7tkrvRgwDAEZU4wR3BIr9DL744fsz/ ALY2kaaPibF/wh3jGGAQ/arh3tzEeciO6UGNowzEgS46n5etRNaptXQ47WMr4D/tleH/ANpLwx4l +Hvx/bw/ZWUtp51vq9wy2kcp3BdvzHCzKWDqyEcA8cZPwn8XPDOheDfiRr2i+GNaXxHoFnP5dpqi Oji5TaDuBT5TySOPSvrr4q/8EzZ18NS+JvhJ4th8baX5RmisJmjaaZAM/uZ4z5crHsMJ7E9Kl/4J h/GjVfD/AI7m+FX9mW4sNUnudTnu5d4uIpI4FXYBnGP3YzkZ5NJNRTlEbu9GfCC07bzXuH7TWtSe G/2vfG+rQxrLLYeJGukjfO1mSQMAcdjivsL9pP4tX3xz/wCCc9h441Kxt9OvdU1KPzLW1LGNPKvp YRjcSeRGD9Savm203JtufmWrc8irkMJ217F+x38bdS+Bvxms9R0zT7XUZdajTQ5VuywEcc1zCxdd pHzDyxjPHJr9AP2tv2pNK/Zj+KmhSaZ4Ts9a8UavawS6nf3ORLFpqTMohiI6MxE+CTgEAkN0olJq VkgjFNXPyfMeK/RPT/E2ofs9/wDBNvQNd8FTLpOva7eK1zqUca+bvlmk3OMgjcI4kjBPQDjmvnT4 uftXXfjP9o/S/iz4c0ZNIvdNghS3s9Sb7Qm9FddzbduRh+mR0r7c8e/tVeNfDX7GPhT4p2cGkt4n 1S4ijnjlt3NthnlU7UDgjhF/iPeom27aFRsrn5sfED47fED4paJZaT4u8U32v6dZTtcwRXhVikhG 0tuxuPHABJAycda5m28F+IbzTDqMWhalLpoUubtLOQw7R1O8LjH416bYftEarL8fpPiv4h8PaL4i 1OZzJNpdxb4tGcQCJGUNvKlSqMD1yvUZr2vwz/wVA+JkfjCxm1jS9Cn0AzKLnT7O1eNlhz83luZC QwHTORnqKvVbInTqz4y8setHl9ea+xv+Clvwt0HwH8XtH1bQ7KLTh4gsmuLy3gQLGZ0k2tIAOAWB XOO6k9Sa6r9lXwL4T+BH7PWp/tA+LdKj17VmlaLQbKZRiMrIYVK5Bw7ybsvg7UTI6nJz+7cfLrY+ JdS8G67o9il7f6LqNlZPjZc3NpJHG2eRhiMHNY7KN3tX254b/wCCmXjGbxYIvHOgaHq3g28fyrzT ra0IeOFjglCzsHwP4XBDYxkZyOD1LwH8Lv2iv2pvB3hr4TaXeeHvCeqRKdUjlVw6yI881w6B3fYD CqKoBCg4wvq1Jr4kKy6Hzjo3hfVvEskqaTpV7qjxAGRbO3eYoD0J2g4qpeafPp9xLbXVvLbXEbbZ IZkKOh9CDyDX6M/Gr42fFX4O+LpfAnwV+Gs+i+DNC228d1a+H5rn7ZJtBdw20qVycZ5ZipYsc4Dv jh4duv2mP2O7z4h+KvCcnhf4k+Ft3nPLZSWzzxxlDJ8rgMY2jbeOoVlIB61HP3K5T83HhPUfrS7S vJXirf7lY1O4lu+ajeQY+QZ/CtiCq0gLcjFPXD9MdKekLspIj+pNKlqWkJb5QPSgCJmPTjNMn+6D jFPWIxsXUhvY1HPIZFwR0oEQ7iKk3ErUOc1NGm4dDTA6zw78KvG/izTE1HQ/BniDWdPkYqt5p+lz zxMQcEB0QgkHrzWl/wAKD+Jx5/4Vz4tGP+oHdf8Axuv0A/Zv+I2qfCP/AIJy3fi7RorabU9KlupY I7xGeIk3gU7gpBIwx6EV4en/AAVE+L0i5GleFD3/AOPKf/4/WPNJt2Rdktz5tPwD+J+7/knPi0/9 wO6/+N08fAP4nNy3w58W/T+w7r/43X3x8C/2nvj38evBHizxPpMngLTbTw6G8+G8sLsvLiJpPl2y kdFxzS/Cv9qH48fFj4M+LviPYSeA7LTPDf2jz7O5sLvzpfJgWZtpEpXkMAMnqKXPIOVHwOPgF8Tm /wCac+LB/wBwO6/+N0q/AP4nc/8AFufFo/7gd1/8br6Mf/gqR8Wl6aV4V/8AAKf/AOP0xf8AgqZ8 Wuc6V4V/8Ap//j9VefYPdPnk/AP4ndR8OvFn/gjuv/jdH/Cg/id1/wCFdeLD/wBwO6/+N19D/wDD 0r4udf7J8Kkf9eM//wAfr27xJ+078e/DP7POkfF2eTwFNo2pGIR6fHYXf2hN7soyTLt4K+tJykug WR8Ef8KD+Juf+Sc+LP8AwR3X/wAboX4CfE7/AKJx4s/8Ed1/8br73+JH7UHx4+GnwQ8KfE69k8B3 mleITbiCyt7C7E8XnQvKu4mXbwEIOD1NeKH/AIKkfFrcB/ZXhXH/AF5T/wDx+hSm9kFkfLHib4e+ KfBEdu3iPw1q+gJcFhC2qWEtsJSuNwXeozjIzj1FYHFfol/wVEupdb8A/CO7lCrLcm6ncJ90FooC ce2TX56TWpiB5q4y5lcUlZ2K+BxxiinKpxnNFUIvSTLHH5bdCcnH8qZbqGkYgfKOelQSNuA3HJJ5 46UiuVbbnaCc/SgRq3CLHa71lxnquaS3Y7y1sjKvTfJwKhwjWrFiHcndu6UrXJgt0YNuLc4z0p3F c1Y4JBlhcMrOOdoAH5Vyl9lriTLbjuOW9a04tUZVbHI6Dd2rImYNIx9TQhD48BBnrUk0qsq4XHHN QK5UgAZJHerMVrJJIF24OOc9ABSGivtZsAkgGvtH/gl/odxb/Hy7vzbTLbtoV1GJih2E+bBxu6Z9 vavjxrXa5ALAxgP8314FfTXwd/bl8c/AnwLb+FfD+leHb2xjnlmD6hbXDzbnbJyUmQY9OKiSbjZF xtfU8f8AjrY6jpPxp8dm4sZo47rX794vNjZfMU3MmCueo+lfXeh6JqB/4JW+KbH+zrpL1tRQi08l vN/5Cdufu4z0GenSvnL43/tQeLfjx4q8Oa94j03R7S60NSLaPTIZUjbLh8vvkcnlR0I4r2P/AIel fFmTeY/D3g3Cj+Kyuzz/AOBVQ1JpaFK2p84/s16Pfz/tEfDjyrG4k+y+KdLNxsiY+SBdx538fLjB 6+hr2v8A4KbWd3F+0pLffZ5ltDpdnGLjYfLL4c7d3TOO1cD8If2wPGvwT8Y+NfE2h6XoV1qPiy5+ 1ahDqFvO8UTeZJJiIJMpAzK33i3AH4y/tCftseOP2kfBtl4Z8TaV4fsbC01BNRSTSbeeOUyLHJGA TJM424lbjGcgc+rtLmuTpax9JfsU2WoH9j/45R3NrdLLNp955SyRMGkBsHxtGPmB9q+OLOzurPxd pC3MbW7pf26mGRCrL+8U8g+386948Kf8FPvid4b0LTNHj8P+EpLPT7WK0id7S68wpGgQFj9pwTgD OAK8j8XfFu7+MnxZi8U6rHaWuq6nqdrJLBZI6xLtMaDaGZiOFHUnnNON03cG1pY+iP8AgrNY3I+I 3gm9NtN9jOkvCLjYfL8wTMdm7puwQcdcVnf8EvvhrqUfxC134lahG2n+FdI0ye2/tC4GyKWZipYB jwVRFcse2V9a+g/21/2uta/Z38faBocPhvR/E+h6ppZuprXU0bcsqysoKsCRjA5BU+xHf40+N/7e Xjr40eGm8MR2lh4R8KyKEm0/RwyvcIP+WbyE/cP91QoPfNZxUpQskXKydz2/9hP4hafqf7XPxC1V pUii8ZvqFzYhsqWZrr7QqgHnmPecdflrA+MX7Vf7QPwV8baj4b13xTcwXFvM628j6LZBbqIN8ksb eRhlYYPHTODggivkPw7qGt2etWOp6de3Gk3NnIs9tdW7FHiZTkMpHOc19seHf+CjPjW00O3s9e8O aL4ivIVAF9KrQs5A++6Lld3+6FHtVuGt0rkKWlmzyP4mfHj4/wDxG+HyW/jC6vIfBuryqsc11o8F ulw0ZWQbJFiUnHyng4OD1wa7n/gnP4cax/aAhvVhmlT+zbqNrplJXdhTtz0B9q4v42ftQeN/jxHD aa/cWtrpEMomi0zT4fLhDgEBySWZjgnq2OeAK0vgj+134v8AgH4Tu/D/AIf03Q7yzub1795NSgme QSNHGhAKSoNuI17ZyTzT5XytJAmr3OV/aD067s/jZ8QJp7WaGGbxFqJjkkjKq4+0yHIJHPB7V57o fjSXwD4g0vxFp0qx6jpt1Hd2654MkbhhkDtkc+or0X9or9rbxd+0Lb6Ro+rafo9o+nySSxyaXDLG QXAB3b5X7KOmK8aXw7DDEPMdpZepf0P0rSN7ak6X0P0e8ZfBDTPjj+0l8Jvijo0Ak8L+JNOj1fU2 Ax81siPHvOAcsGhjIP8AcPpivi/9qr4yW3xi+M/iLxDb3Imsobj7LprLgr9miO1CMdmwz/8AAzXe +Av2vvF/gH4H3fw402Czmtmt7m2t9Tk3i5tkm3FgmDgEFmIOOCfavnP7Hp8kO4HYx+Uhn5B71nCL T1KlJdD7U/Y307UG/Y4/aHE1jcxzXmnX7QRtCwaUNp0gXaMfNntiuO/4JbeLLbwd8dPEPhjV1On3 2taZttkuR5bNNE4fy8HByUZ2+iVkaJ/wVB+KXhXRNO0Wz0HwfLaadbx2cMk1ndF2SNQiliLkAnAG cAV86fET4zeIviR8Wr34jXLw6P4kubmG7WTSN8KQSxIio0e52ZSPLU/ePNLlk7p9R8yVrDvjZ8It a+B/xI1nwtrNncW/2W4cWlxMhC3dvuPlzI2MMGXHTocg4IIr7X/YP8O3XwJ/Z7+KvxW8VxyaVpV/ ZIthFdJsa4WFJcMoOCRJJMkadMkHrkGvOfDP/BT/AMbW+iWlj4t8I+HfGdzabfKv7qIwykgAb2Ay m4+qqv0ryP8AaC/a/wDiB+0YkVnr9zb6d4fhl82HRdLQx2+4cKzkktIwH944HOAM0NTkrNAuVO6P dP8Agk3f28Pxk8X2byBbmfQfMjjIPzKlxEG59t68e/sa+VPiN4K1vQvix4k0C70y6TWI9VuIfsaw sZHPmNgoMZYMMEEdQQR1ql8N/iV4h+EPjLTfFPhW/bT9XsmJSTaGR1Iw0bqeGVhwQf0IBr6p1r/g qN8S9R0uOOy0HwxpurtH5b6pFaSySJ7xq8hUHPOG3D2p2kpXS3FpazPS/wBszQdSsv2RvgXZ3VjP bXmn2FnHeQzQMHt3WwRWV16qQwwc9DxXzp8A/gz8WPFbT+OPhjM0N1oMpWS5t7pIJVJTcVVCfnBX jbgg5wa2fF3/AAUN+I/jj4Y3fgfV7DQbmxvLBdPudR+zT/bJQFAMhbztnmNjJOzGSeBXlHwl/aJ8 cfBPXINQ8J61cWkKyeZPpsjs1ldHG397DkBjjv8AeHYilFSUbDurn2N8D/219b+KvivRfhx8S/CW l+M7PWLmOwN0tmBIhchfMkiIKMB1YqFwAT2r5a/bC+FWj/CH9oPxN4c8PsF0iMw3EFv5hdrYSxLJ 5RJ54LHGedpXOa9mvf8Agpd4ljiub3Rfhv4T0fxHcriTWBEzuSerY4JPpuYj1zXyT4u8Va3478S6 hr2v38uo6tqExmubqQDLse+AAAOwAAAAAGBRGLTvawN6WPRf2atD+HviD4qafpPxLuJrbw7eRtCr wu6H7QzKsWWQEquSck8DvXc/tu/styfAjx6s3hjQ9R/4Qe6tI5Ib1t9wkcoyJEkk/hORuAOODx0O PnBbWNsnLHj1r63+Ev8AwUe+I/w58P2uh6rZ6f4vtLSMRQXOoM6XYUcBWlU4cAY5ZS3qTRLmTugV rWZ2/wDwSq0XxzZ+L/El+Yb61+H82nnzDcKy20955ieW0eeGYIJMleACAf4a539mfxFoF5/wUn12 70eRI9L1HUtZWyZeUlYrK5KkZAVtrsOgwQBjgVzPxp/4KH/Ev4oaFc6Lp62Xg/SrpTFP/ZW83MqH 7ymZjlQf9gKeoyQa+V/DviXVPB3iKw1vRL2XTtW0+dbi1uoTho5FOQR2P0PBHB4pKDldvqF0rWPY v21vDOp+H/2ovHkV9ZTQtfaibu1JQ4nilAZGQ4+Yc447gjqK+mPGnhXWtJ/4JW+GdKvdJvrTU474 yvZTW7rMqNqM8isUIyAUZWzjoQa4D/h6f8TX0WGCXw34Vn1eIYXU5LWYkerBPNwG+hx7dqw7L/gp l8XYvCVzoV/a+HNa+0JcRzahfWc32l1lZyR+7mRBtD7VAQABVHPUrlk0tNgvFXPn34O6fdaj8UvC i2ttNctHqtpK6woX2oJ0yxx0A9fevsD/AIKgaXdTfHjQr5bSeSyh8M24e4WJjGh+13XBbGB1H5iv mL9nT4/eIf2cfHV14j8N2emX19eae+myR6rFJJEI2kjkJASRDuzEvOcYJ49Pavib/wAFBPiL8XPA eteEdX0Twxb6bqkIhnlsrW4SZVDK3ylp2AOVHUGqknzJoItcp8ytE9xcRxW8bSySMFREUlmJOAAO 5zX3/wDFDR76T/gmz4AsxY3Ml2l3But1hYyD95cdVxmvhvwp4qu/AvjLQvEllDBJfaPfW+oW8dwC 0TSRSLIocAglSVGcEHHcV9R/8PTvitzjw94NI/68rv8A+SaJqTasNWtqZ3/BPv4PeG/iJ468V6z4 o0pNdh8MWK3Fvo0yB1uJnLYJQ8PtCEbSMZdfSprn/gof8XtW8QjR/DugaJYW9xN9mtdCtdLaZ1yc CLBOWbt0HPYdK8F+GHx48W/B/wCI03jHw3cw22o3Bf7Tbyxl7edHbc0brnJXOOhBGBg17l4s/wCC i3ijUdPuZfD3gvwx4U8Q3alJ9ftLbzLrlSCyFuje7bv60nFt3tcL6HoX/BVaznk8XeBrhIJGgj0+ dXlCEopMq4BPQE1e0PTbv4+f8E37bRfDUX9oeIfC13m40225lfypnfCr1JMMoYAdSCBzxXgnxq/b s8d/HvwDN4T1/SvDtlp800c7SabbTpNuRsgAvO4xnrxXnHwT+PvjP4A+I5NV8I36xGcBbuxukMlr dKM4EiZHIJOGBDDJweTlKD5UuqG5K5zHg/wTrfxG8YWXh7RNPnvtXvJhDFaqpLA5wS391RySTwAC TX0j+zP4V1b9mb9tjw34f8bR2tjdyiSyaSK5SSM/aInWBgwPG59gAbB+bkCtzWP+CnHi9rO5bRPB PhvQtcul2zaqsbyuT3YKcZOeRuLD1Br5I8QeKtZ8WeJbzX9W1G4vtavJvtE17M5MjSZzuz2xgYA4 AAAwBV+9LcnRbH23+1d+0P8AtEfAv4u63p0Xia4svC9zctPo1wdHsnhe3c7liWRoCS0edhDHd8uT nIJ8f8U/tP8A7RfjT4a6tPrGr6hd+B75Dp97ef2Dax28glDLs85YBgnBGVYEHHIJFdl4A/4KUfEH wr4dg0bxHpGk+M0gQIl5fb47hwOnmMuVcgDrtBPUknmuE+OP7b3xD+Omjz+Hbw6foPhqXb5mm6XC VEwVgyiSRyzHBA4XaOORUKL2aKb03PnqZWZVJwB2AFIVKqi54J5qzt2Rjcct3qBX3OMkYBrczJVz tIxgdKicFunBNSs21TlgfTmoGkz0pDQ1YzwgPWq19GI2A6nvV2Paz7i+MVnXjbpDTJIBWj5e1VI/ +vWeg+YfWtPG7GKYI/QnwD/yiq8R/wDbz/6XrX54FnjPykgV+iXgX5f+CV3iT/t4/wDS5a/PFtpU k9ayp7v1Ll0P0E/4Jx/8m8fGn6Sf+kj0z9jkf8YE/G73Gqf+m6Onf8E4f+Td/jT/ALsn/pI9N/Y4 5/YJ+N//AHFP/TdHWUt36opbI/Pry8DHOaasfJxT93QYr139mn9mnxH+0h41GmaYGsdFtWV9T1iR Mx20Z7D+9I3O1fxOACa6G7aszPJIwF+8OK/Qr4uLu/4Je+CQP71n/wCjpK2PFnwz/Ys+F+tzeF/E VwTrenqsV1/peoTuHwM72h+QP6qMYJxgdK5v9qj49fBXWf2X7f4c/DbXvPFld232SwNtdDZEjszf vJkGcZ7nPNYuXM1ZF2tck/atz/w7v+C/b5tL/wDSGavz8ZvlB/iFfpT4d+OP7N3jr9nX4feBPiTr 32ptHsLMy2Qt76MxXMUBjPzxIM43OOCQc15p8XrP9juP4ZeJD4KlY+LRZv8A2YN2p/6/+H/WfJ/3 1xTjJx0aBq+tzqv+CmEzQ/C34MsvXyp//RFvX5+m8eXAKj0r9Av+CmGf+FW/BnAyfKn/APRFvXwA kLsyErtGfSqpfCTLchWPLcminYIkx1OeKK0EQed8/PPelVgsmWORVZmOQRTfmzQIutc7s46t1qNp AAB19aqgnPtUvBye9ADi3PHSoW+8alwWPpjmom6mmiSRVyoOORWnYt+8USMDyCTnqKzgpI45qSOO RVJDbRjOf6Uii/qQaOQOrhldQrbat2MUXlKAAc9WzyKxmkd4QgBYZznP6V9C/s0fsheKv2gNPvtX N/a+FvBlmzJPrmoJu3MBl1jTI3bRjcSyqPXORSbUdWCuzxeeFdkrqxK9Avr2q7a2CwxxxhlVnHI6 k+9fY+sf8E89L8S+Gbqb4X/FLRvGd7Y/62yUxEOy5OzzYpXCMcYAYYz1Ir5E1jSbnR9TnsNRtJrG /s5mgnimBV4pFJDKR6ggiiMlLYbTW5z+s6aLORZ1+dSfnXtWLeRLFN+7O5CMg19yeCP2BZtW8D2v iX4leNbH4cabdAMlveqnnbWGV8x5JEWJjwdvzHHBwemf8RP+Cb1zH4Nu/Evwy8cWHxCs7dTIbW3R RI6quWETxu6SN32/KcHAycZnnje1x8r3PiVWPIr179m/44w/s9eNLvxNL4Ys/F6XWnyWC2V5KI1i ZpYpPMBKPyPKx0/iPNea+FvCGt+NvEFvoegaVd6vq9w/lxWdpEXkJzjoOgHcngd6+stS/wCCdet+ A/gP4q8d+ONaXTtX02wa7ttDsAsoUjtNL0zyOEz/AL1EmtmSk90N+OH/AAUO/wCF2fDzW/DV58NN OsLnULcW8eqG/wDOltwHDZXMIPb1HWvknQrVbzUERxkAbgPXFUEje6mSKJWlkdgqqoyzE8AADqa+ 3Phb/wAE6L/TfDlt4p+KfjjTPh1azL8llOUaRQw+USyvIiRt32jfxwcHIB7tND1kfNscIwCRjtj0 qbhRknAFfTHxW/Ye1bwx4Hu/F/w/8TWXxI0W3RpnjsFUTeWBksmx3WXA5IBB9Aa+Lr7V7m9+++1f 7q8CrUk9iXFrc6y41iztuGmUn0Xmsy88VwKjLFGzNjhjxXPQ2N1ecRRMw9cYFaMPhO5bG+SNB37m mFjNg1CS3kMgb94zbi3rVmTxFdyD/W4+grVh8L2ysN7tIc49BVptHs44WxAquAevejUDmG1ScZxK /PXBNV2nZskBifpWoqKOigfhTZiFhcj+6aQ7HPtmkpT3pGHSqJCpDjYuKjqWTCqo9qAH2sfmzop6 d6tXEKwzKBwCc1Hpy5uB7A1YuubpBSGSSMgXgilWMN24p0w+XGKkXpUlETRIMk/pTm+ZflWn464o 9qQEAt2zuDYP6UqvtIDjafXtU9NdQ6hSARQBDcYW3Z+uOlZDZJzWjfDyYdobhv4aoDmqQg702nYo ZTTAdbv5cyt3BrZjkePBU/erCb5TWpZ3PmQqOrDikxFmRpJmyxyabJGFX5Cc9+Kf/jR60iiEh+p6 ihlLRkE4NTN3ooEU442XOfw4pzbl79fSrdJtHFAyFUDLktzTljXbyaftHHFG1aAImAyACak8lVUZ 3A0bBSNkggk0AKVQr1OaYEjXrkilEfU5pDH70DHxxpKcKpNOe22DpuPoKarMi4BxSrI6YxzQIi+T d9ys+6O6ZscCtKQlmztxmsy4/wBYfrTAjXhh9a0du1R1qhCu6ZMetamfbvQI/QnwCv8Axqv8Rj/r 4/8AS5a/PCZQqn6V+iPgNh/w6y8Rnt/pH/pctfFM3wF+JjQkp8PPFThhkEaLcnP/AI5WUN36mkuh 9j/8E4P+Td/jR/uv/wCkj1x/7GP7THws+FvwR8VeCviG95ImtahO0trDaPLHLbSW8UTKWUgjO1x6 16Z+wP4G8R+B/wBn74wweI9A1PQZp0keKPU7OS3aRRaOCVDgZGfSub/YV+HPw11P9nLxx4z8d+D9 P8Q/2HqNzNJPPaLNOLeK1ikKJkj/AGiBkcms5WvK41eyJP8AhPf2Hh/zKN1/4D3v/wAdpnxC/bT8 GeEfhrafDz9m/Q7rT73VJmi+0R2jpJA0hA/dBiXkncnAY52gDHOMWf8Aho/9j3/ok8//AIIrf/49 Wj4d/a+/ZY8C6mmueG/hneafrdqrG2ng0a2jkVipGA/mnbnOM+5pfJhfzK/gL9lD4Yfs/wDwrk8b ftDmPUNa1R1K6e88rG3ZufLURsGllPVzyBg9gWNNvHX7D/fwndf+A99/8dr5Q+Onx28VftH+Pjq+ sM7KX8jTdItstHaxseI41/iYnGWxlj7YA9l0v9jfwn8NfDVhrXx2+IUfgie+j8238O6dF9o1DZ6t gNg56gIwHQtniqt1kxXXRHozfED9h2Mgnwndgjp/o99/8drlvi541/ZG1D4ZeI4vBvhu5tvFMtm6 6bO0F2Ak/wDCSWkK/mKyrX9k34P/ABot5rT4PfFp7zxLHGzQ6J4mt/Ie5IGSEbYh6f3VbHfA5r5W 8XeD9Z8B+INR8N6/ZS6bq1hKYbi1mHzIw/QgjBBHBBBHBpxs+rE2feX/AAUuYr8Lvg1gZ/dTZ/78 W9fn6Wl7HFfbP/BQD4o+EvHvw2+ENt4d8QWGtXEFrLNPDZziR4FaKFR5gHKHKsNrYPyniviXdTpu 0RSauNMp3x5XlaKDH84bNFaXRNzPbPalIpw+50z6mljj8w49s1QEfPNCszDHalZdrEA0Qg9cUASr DI6tIB8o61B/FU3mHkc1B3FNElkSeXwenXjrR5j3CBFxs3cVCVLvjFW7XTZ7iJnRcIpxk8ZNIaLt nZlcOw7jAHSve/HH7S+oa3+zboPwq0fR00PTdMmSe6vLe6LG+wzyMrpsGAZHD9TygrwKHSZnjH73 aemCOOK2/B/gnxL4z8Tad4f0G0k1DU9SmEEEMJzuJ6k+gAySTwACT0pO3UpXPd/+CfWna/qn7T2g 3Xh9pks7WCaXVZFz5YtihBV/UFzGAP7209q9V/4R3Q/jF/wUm1C3tlS60Wz1MXVwinKSS2tsnmZw eQZ48Ed8nPFaPxO8WaF/wT9+DsXw48GXMV98VPEMIudY1lVBa2UjG71XjcsSdvmc8n5vKP8AgnF4 hhb9qLTIrhts93p17FGSwzJJs8w9TknajH8Kx3vMvtE1P27PiBf+Mf2gdc06WeRtN0Ly7G0t9x2p +7VpGx03F2bn0CjtUv7AHxEvvBv7QVhoiXMo0rxGklrdW+/EbSLGzxSYP8YK7cjBw569K85/a11S PR/2kviFbTowk/tWSQ8cYcB1P5MKt/sX3H9vftS+AoLRGLfa5JmyOixwSOx/JTV2Xs/kTf3jZ+M3 jTU/2Qf20fiBq3hLT7QXE6u9ot3GzQxi7jjmd1UEZ2szgDO0EY6DFe0/Cn4keJvit/wT9+OPiDxb rNzrmry6heIbi5I+VBaWeERQAqKCSdqgDJJxya8N/wCCimqWWsftQeKbdGZZbGCzgZsAhm+zRvgf Tfj6g16b+zP/AMo1/jX/ANhK+/8ASSyqGlyp+ha3aPnz9hvw/p/iX9q74fWOpxxy2q3c10ElAKmS G3lmi4P+3Gn411f7fXxA8Q65+1B4ostRuJBaaJ5djp1oxPlwRNFG5ZV9XLbiepyB0Ax8+eCfF2p/ D/xdpHiTRZ/suraXcpdW8hGQHU5AI7g9CO4JFfd3in4ufs1ftiafp2pfEW61D4b+ObeEQy3dqjES gDO3zRG6OgOcbwrjOB71K8ZcxC1Vjg/+CYfjDW7D4/XOh29xM+j6pps8l7bbiY90e1o5SP7wJ259 HNeS/HDwfo/hv44ePLbTRHJYW+t3iwRIAI4V85vkUDsv3fwr7w8L+G/hX+xz+z9q/wARvAkl3rd/ rVsINN1bVh+/vHcnylRSibYsgyHCjcqZy3ymvzlvr66vLy4u7yRrie4kaWWSQ5Z3JJYk+pJzRD3p OQ5aJINw3KBgA9qkZB0qiLoBlXbyKvFl2jLcGtzIrShlVSR35NOumX7NIpDE7fSpGZWjYA8iok3Z ZQeOx70hnMeuQR68VUurpPJkCtyRiuo1CzLQuRxwckVxt1CEVyTzRYZQPrS0UUyQ6U9vvU3bnBpz /fNIaLFpMIWLbcnGKkkn8yZZMdO1MtVXY2eTUrJHGR82SOq4oAJLxmx8lSLfOFz5eRRtDMMDHemN lcqp/CpGO/tID+A0xtSbPC1CwVfvmkdk6jn6UwJjqT84UUfbJG/iVfwqsuf4RxR5DMfmoAJpjI2W bP0qEsOwNT+T7Zp/k5PSi4FdWyKF+7jNWvI9qX7OOR2pXAqlT60+Nmhbj9Km+zp3pRAlHMBNHqA2 jcOamW5WReGAPvVb7OvoKXyVFK4FneMHJ5qRWyKp7AD1p3THJpXAt96Krbj/AHqXcfU0XEWPSiq+ fekz6mjmC5Yz796RmGOtV80uKVwuTb155o8xfWoio4pPlo5h6kplX1pvnD0puRjpSbh6ZouA7zc9 qqvbbmJJqzuA7UbhRdgQRW4jcMMkirG5vpTdwpd1F2Fj9C/AWT/wSv8AEeTzm4/9L1q2v7Sn7Xsd tGI/hBbuAoAJ0W55GOv+uqn4BP8Axqt8Rn3uP/S9a8Sb/gpR8a7eFVXUNHAUYH/EsT/GsUnJvQ12 sez+I/2jP2tNQ8M6xban8JLe10+a0mjuJho9ypjiKEO2TMcYBJ6Un7G//Jhvxs+mqf8Apujr0n9k 39obxj+0J8C/inqPjCe0nudPgmggNpbCEBWtnY5A6815t+xv/wAmG/Gz/uKf+m6Ok+qsPzPz5yAa Xiky3fpRx0JrYxPpf/gnv4Y0zX/2h4dR1SEXMHh3S7nWkixkGSPYqHHcqZNw91FdZ8I9N8P/ABqH xX+PvxfivPE2l6HIhj0O3lZfMeQ4jjJBBEaAxqACBySc4wfI/wBkT4wWvwS+Oeh67qOP7FuQ2m6k zDIW3lwC59lYIx9lNer+KPEWvfsF/HPxXoVnpln4n+H/AImhFymk6iN1te2bltmGwQGTc8ZOCCOo ORjN3uWrWF+JPhL4e+Pv2f3+N3wq0O8+HWs+GdXis77T47p3QsWj2SROTw6mWIgrt/iyMgGqH7bm rQ/EHwL8EPiRPbpF4h8SaHPDqcsaBFmkt2iXdj/ekk/DaOgFUfFHxy179qq48LfB3wN4N0rwJ4av NQVl0nShlXk5LTSsFUbEXc5AX+HJyQMN/bu8XaJH4r8K/C/wy/naL8O9O/so3B5aS5YJ52T3I8tA f9vfSW6HpbQ+YA3rSkhulH40BR1zWpFgHail9sUUBYpxt1qTzNuNvBFU953YpWbFaEkxkGc9+9MM wFQ80u0896dhEokDcd6F+8KZGevFPj+8PrVIDTs7RriaNdo2jBc/5710sUflZQ7eeQpPH4Vlaeki xqvmfKRjpV0R7Z1w+VUelIZK6m3zIFURuB93sfWv0w/Yl+AI8E/Bn/hO9J+w3vjrxHYs9jcX4YW9 lEx+RDtBY5IDNgc4CggDJ/ML7ckjGOaQomcBRxx/Sse9vDIwghbKK+5W71Mo8ysmVF2dz9AfGf8A wTb+JHjzWr7WNZ8daHfarfSma5u5knLux6/wcDsAOAAAOBXzTdeHdb/Y/wD2nLWJbi31HVPC15b3 EslsWEVxHJAkjxjcARmOUoT7mvKdO0hY1V5WVmJzuJ4HtWwsce1SW5HpxSjF9WF+x96/Gz9l3w3+ 21fW/wATvhj4t0+z1a8tY4tR0+/BAMiAKpl2BnjkVcIQVYEKpBxyZPgv8AvC/wCwTb6p8RPiT4rs dR8SNZtbWGm6cTzuwWEQfDSOxULuKqqjcT1yPg+01CbT7hJLSd7edfuyROVYcYOCPbNZ95dXPiLU pJJppJlHEk0jFmb8T16VPs3a19B83WxV+J3i7VfiV498Q+LtShK3OsX0t26qSyRhmJCKcchRhR7A V+ofwc/ZB17wV+yR43+GVxrmm3Gp+KJ5ru3vYlkEMKywW6AOCM5BiJ4HcV+aN4qR6bOuMKIyMD6V 52fvGnKF1ZMUZW1Z1HxO8B3Xwt+IWv8AhK9uYby70e7e0luLcERyMpxlc84+ten/ALHP7PU/7Q/x es9NuY3/AOEY0zbe6zMpK/uQfliB/vSMNvrjcR92vCB61q+H4RNqC5GQqljziqs7WFfqfY37b3xt g+I3xKXwxociL4W8KA2VvFBgRSTjAkcAcbV2iNfQISPvV82zLv4BwT6CqEbKqsFkAZTgc84qVbwN wSAV55OKcVyqwm7u4lxGy7XCcL1wcE/hVc3Ak3ryMc7W4IpLrUEMeGZQcUxdUtlU7mVjjuM1QFne PKWRX28c47+1PhvEYghskdvasO7vLcsWhDKx5+UkCqZvHDbgTu6ZpXQWZ0dxeBop1BzkHFchqOPM YD2q295cOuzdhfSqbQkn5jk1N0UkUqVVOcVbW1A6ml8gDpzRzIfKVVjLYpGzuOavMo25x2qiRuY4 pp3E1YtWowp5pZG3TtjpRBH+7GaSNd0xHai4rEjMzDH4ZqMQt0L1YCBaOKjmKsQfZlPU5pwhVeAM VLTGzmi4tA8sUbaXlqApPHSgAIxQKXaelLtNTcBo+bPBo296fsOOtJt7UAN78Uc9hzT9oycUAL9a BDdpxk0o+lL8p/ipcgcZBoAbj2o/Cl8zB6cU7cW7UBqNH5UhFO2buoxTth7igBgHFKMZ5p4hbPPA p/kfKcYJpD5SL6CnKrNx0p/klMEjI/Q0SfNwq80yuUjaHnB60fZyp4qeNdqDI+b0pGbcQCdp9jnF MqxD5BC9aYFZTgc1ZG3pkmkKr5mRyKQWRDtbuuPem+SzZ61abG75hUnGzhvl9KLhYomMrjjI9qcy k/djq1tU85pjJu4HQ+lAWR+mf7LfgWy+LH7A7+CJtbt9Dk1aa6iNw4WQxYut+dhZc52+o6155cf8 Er9PkUKPi7Zrj10tT/7cV8EtGYRlQWbPc1Xv2LbM8HFTGLvoxt9z9R/hZ+xz4t+DXhjXfD/hb45a XZ6XrWftsc3h6GYvlChwzTkr8pPSn+CP2O/Fnw6+Hev+CNC+OGl2vhvXPO+3W8nh+GR382IRPh2n yuUUDjp1r8t7dv3CgMAakG7oT+tJxfcSatsfff8Aw6zsP+iu2f8A4K1/+SKraj/wS8sLLT7m4/4W /pieTGz7rjTljjGBnLN552r6nBxXwYVGOKTn/wDXStLuK67EkkflyOgdX2kjcpyD7ivszw8o/a8/ ZJn0Fv8ASviT8M4/PsCeZb3TsYMY9SFXbj1jj/v18Zc4wduK9B+A3xm1X4B/EvTPF+kx/aTbborm yaTy0uoGGHiZsHGeCDg4KqcHFU0CZ9Efs42Fv+zD+z74h+OOrxJ/wlGuK2jeEraUZPzZDT7T2yrH /diIz89fH2oX89/dz3dzI1xcTu0ss0hJZ2Y5LE9ySSa9d/aZ/aWv/wBovWtHkXRofC+gaPa/Z7HR bWbzYoiTl3yEQZOFGAowFA9a8XXO3BJ+lCXVg+wu4Hvz9KdhiBgZHc00jHbAoXPUNxTEOaMKcLlq KFbvmimMyO+aUjPtSbWPQH8qUI2cFeK2uZCqucYp64HeoyrqeBT1LLnjqO5pXGPUYjz60Rn5hg4O ajkby4x+tRxyBmAzTuI1V1S6tWO8cg8nHemrq87SMRgs3A3VA0hkjVGbjue5+tM2r3OfxqeZAaEl pJcbZJZ0ckZ2ggVDHBHI0kkbeWoOF9abZsn2oHAPX+VOvJEFwdo2/Sjm0A6HSYF8gSyHeQP4z/Kl urpRKjB9qk4PtXM/ae24gfWkMy/WlzAblzfJNNtSQrCBgt3PtVu31i2t4xGGwo7KK5f7QvpSfaBS 5gOlvvEEU1vJGitlgRzXN+QPWk+0Un2jtRzAOEI9zVi2ka1bfH8px3qp9o96PtPvSuI0X1CeRdrS celQtIx6k/nVTz+lKJjRcZZzRkVW873pfOwKLj1J91Jycc4qH7SOmaDcD60rlWZNuOaXmofPWkEw 7NQFmT9OppDjtVc3Bz1xS+Z6tQFmSTcRniqOfmOKnuJQsZ+bNUlm5zWkSWjUhz5a45pIj+8NQrcA RjJpkM3zHBxSA0OKRmGMDBPpmqnnbec5+tKs21s7R9aguxbVeMsB+dHHoMVU8/uf507zhxQFiwTn GKTf6jNQGVR06/Wk831GKB8pZ85dvvQZOuOtVPOUZAOKBMOgOaegcpcG5eGHP1pzbffHSqnnFu9N 887s559aB8pb43YHI96XjcCNpFVfOz3oWYdDzQOxcXGfuZP50rFVxhBn2OapmVP72PoaQTBcfNSA tlivA4P+1UnLKCRz3qo10rnJfmg3SkADkD3ouBZ3BWwR27VKZjtAJzis/wA7uD+B6U77Vu4PP40C L0bOeQm5e1J5w6MMZ7Zqj9q2+uaBdjjIXOaAuaG4tj+WaXd0OQrD0rP+2e+KT7V+IpBc0V2dScE0 1mRWLbgD6dqy2m5yGpBcEdRTFdmo0kbc7sfhTBMqk4LYqh9qVRycfhQZgx4bigWpe84N3p63Ax61 niQEcnNKsyr04pBqaPnA9Kasrc4GPpVETDOc4NL5/YEmgepZa4+brVK8k8xxmpPPGMfzqldSjzMd KqO5LRfhK7AMVIrLVYTKqjnGBQswYnBpMLFnA7E03aT3qDzcn0HtQJ9vO7NAWLHApVcev51X87OM mjz07EUDsWfqcUhIHoar/aPxpPOXrnFICyWHXpS7h1zVXz88daBIuM9KALXDd+aKq+dz/jRQI65v hpqx6T2Y/wCBv/8AE1E3wv1hv+Xiy/7+P/8AE16lRXz312sfuP8AqhlfaX3nlP8AwqzWf+fmx/7+ P/8AEUf8Kr1n/n5sv++3/wDiK9Woo+u1h/6oZX/LL7zyab4U61IABc2P4yP/APEUyP4S60rAm5sf +/j/APxFeuUU/r1YP9Ucr7S+88o/4VXrP/PzZf8Afx//AIij/hVOs/8APzZf9/H/APiK9XopfXa3 cP8AVDK/5ZfeeW2/wv1iGTcbiyxjtI//AMRSTfC/WZJCwuLEZ/6aP/8AEV6xZ2c2oXkFrbRtNcTu sUcajlmY4AHuSaW9s59NvJ7S5iaC5gkaKWJxhkdTgg+4INP67WsL/VHKr2s//AjyL/hVes/8/Nj/ AN/H/wDiKP8AhVes/wDPzY/9/H/+Ir1erd1pN5Y2dld3FvJDbXqNJbSsMLKquUYr6gMrD6g0vrlY P9UcqW6f/gR47/wqnWf+fmy/7+P/APEUn/CqdZ73Nj/38f8A+Ir1irVrpd3fWl7dW9vJNb2SLJcy KMrErOqAt6Asyj6kUfXKwPhHKlun/wCBHj3/AAqnWP8An4sf+/j/APxFH/Cq9Z/5+bH/AL+P/wDE V6vRR9drD/1Ryv8All955R/wqrWf+fmx/wC/j/8AxFH/AAqnWP8An4sf+/j/APxFer0UfXawf6o5 X/LL7zygfCrWv+fmx/7+P/8AEUf8Kr1n/n5scf8AXR//AIivV6KPrtYP9Ucr/ll955QPhXrI/wCX ix/7+P8A/EUf8Kr1n/n4sf8Av4//AMRXq9FH12qP/VHLO0vvPKP+FU6z/wA/Nj/38f8A+Io/4VVr Xe6sf++3/wDiK9Xoo+u1u4/9Uss7P7zyj/hVWsjpcWP/AH8f/wCIo/4VTrHe4sf+/j//ABFer0Uf Xa3cP9Uss7P7zyn/AIVVrH/PxZdP+ej/APxFJ/wqrWf+fmy/7+P/APEV6vRR9drdxf6pZZ2l955N J8KdadNoubH8ZH/+IqBfhDrY63Ngf+2j/wDxFewUU/r1YP8AVHK+0vvPJf8AhU+tAcXNjn/ro/8A 8RSL8J9bX/l5sP8Av4//AMRXrdFH16sL/VHK/wCWX3nk6/CnWu9zYn/to/8A8RTh8K9ZH/LzZf8A fx//AIivVqKX12sP/VLLO0vvPK/+FW6z3ubHP++//wARSf8ACq9YZcG5sv8Av4//AMRXqtFH12sP /VLLOz+88pHwr1lRgXFj/wB9v/8AEU3/AIVVrX/P1Y/99v8A/EV6xRR9drB/qllnaX3nlH/CqtY7 3Fjj/ro//wARR/wqnWB0ubL/AL+P/wDEV6vRR9drB/qllnZ/eeUH4V6z2ubL/v4//wARS/8ACq9a 5/0mxx/10f8A+Ir1aij67WD/AFSyztL7zyg/CvWu1zY/9/H/APiKT/hVetf8/Njn/ro//wARXrFF H12sH+qWWdn955T/AMKr1jqbix3f77//ABFH/Cq9ZwB9osf+/j//ABFerUUfXawf6pZZ2l955T/w qvWe1xY/9/H/APiKP+FWaz/z8WP/AH8f/wCIr1aij67W7i/1Syzs/vPKf+FWaz/z82P/AH8f/wCI o/4VXrP/AD82Q/7aP/8AEV6tRR9drB/qllnaX3nlI+FmtD/l5sf+/j//ABFIfhXrPX7TY/8Afx// AIivV6KPrtYP9Ucs7S+88o/4VXrP/PzY/wDfx/8A4ig/CrWT/wAvNj/38f8A+Ir1eij67WD/AFRy zs/vPKT8K9Z7XNiP+Bv/APEUf8Ks1r/n5sv+/j//ABFerUUfXawf6pZZ2f3nlH/CqdY/5+LEn/ff /wCIpP8AhVWtf8/Nj/38f/4ivWKKPrtYf+qWWdn955N/wqnWuv2qyB/66P8A/EU9fhXrI63Nif8A to//AMRXq1FH12sL/VLLOz+88q/4VbrH/PxY/wDfx/8A4ik/4VZrX/P1Zf8Afb//ABFerUUfXaw/ 9Uss7P7zyj/hVmt/8/Vj/wB/H/8AiKik+EutyPu+1WP/AH8f/wCIr1yij69WF/qjlnaX3nlP/Cq9 Yx/x82P/AH8f/wCIpP8AhVWsf8/Fj/38f/4ivV6KPrtYf+qWWdn955R/wqvWf+fmy/7+P/8AEUf8 Kr1n/n4sf+/j/wDxFer0UfXawv8AVLLO0vvPKV+FesZBM9if+2j/APxFH/Cq9YGcXFj/AN/H/wDi K9Woo+u1h/6pZZ2l955SPhXrQH/HzY/99v8A/EU3/hVWtE5NxY5/66P/APEV6xRR9drC/wBUss7P 7zyY/CnWT/y8WI/7aP8A/EUv/CqdaH/L1Y/99v8A/EV6xRR9drB/qllnZ/eeTj4U6znP2mx/7+P/ APEUV6xRR9drB/qjlnZ/eFFFFcB9mFFFFABRRRQAUUUUAej/ALP/AI20vwD8SrDV9cgsrjSLdWmm W7sxcvuRS8fkg/dlLqoVsgAnJ4zTv2gvHGlfEL4kXms6Fb2drpNyiTxR21mtvJvdQ8vn4+/KJC4L ZIOARxivpT9h74WeD/HPwr1e+8QeGtN1i8j1qWFJ7y3WR1jEEBCgntlmP4mvoj/hnj4Zf9CJoX/g En+Fd8KM501Z6H55jM+weCzGcpU5OcVy9Ld7+p+T1vO1rcRTIFLxsHUOoZcg55B4I9jX0T8dvjH4 Q8ZfC3QdB8P2GjW2r6aY4L2S10kQqwZPMkNm/wDyziExcMMAtkEcZz9sf8M8fDL/AKETQv8AwCT/ AAo/4Z4+GX/QiaF/4BJ/hVxw04ppPc46/FGBxFWnVnSleDutV+J+TVfRnwI+MXhHwb8L9f0LxFYa LcapqRkt7KS50kTBQqGSM3jAfvIvOEYUYJUhieAMfbP/AAzx8Mv+hE0L/wAAk/wo/wCGePhl/wBC JoX/AIBJ/hRHDTg7phi+KMFjKfsqlKVrp6NdD8nridrq4lmcKHkYu2xQq5JzwBwB7Cvbf2bfgj4R +NU13puseKLnR9eEh+yWNvEGM0QTcz5IwMc96xf2qPD+meFfj14p0vR7CDTNNtzbeVa2qBI0zaxM cAdMsSfqTXS/sO/8nCaT/wBel1/6KNckIpVOV66n2GNxEqmVyxVCTg+XmW3a9up1Wqfs7/BLTtYv NFm+L0ljq1tO9rKl1bqFilRirKxIA4II+8B715p8a/2bPEfwZjg1KWaDXPDVywFvrNj/AKskjIDr k7Ce3JB7HtXM/G7/AJLR4+/7GDUP/SmSvpD9jLWH+KXgPxt8Ldfka90k2YmsxLljbhyVYL6AP5bq Oxye9aJRqScLWZ51Spi8uw8Ma6zqQ05oyS2dtYtJbX2Z87fBHwLovxI+I2naD4g1tdA024Dlrosq lmCkrGrN8oLHuf54rK+JvhnTfBvj7W9E0jVU1vTbK4MUF9GQRKuAeo4JBJUkcZBr039nf4O+BPij rVz4b8UeItS0nxU1y8NlYWMe5ZkjjZ5CXMbKCNjdWGccV53r/gFoPi/qPgjSZGndNdk0a0kuCNzk XBhQsQMZPGcCsnH3FoevDExljakedpRivdast/iT69uxx9FfVfiT4O/AX4X64ng/xb4n8RTeJAkf 2u+s0VYLZnUMuV2NgYIbHzcHk1xXjL4A+GfhP8TtP0zxl4s8zwfqEM09vqWkoZLhVUfIJE2MASxA +XcCOeOlDpSRNLOMPWsoxlqm4+6/eS/l7/meUeKPAPiHwTa6XPrulT6WmqQm4tBcYV5IwQN23O5e o+8BmsCvvD9qrQfhbqFj4TbxV4l1bTLqHR2GlR2luXW4TC7TIfLbBJ2+nWvGf2Z/gL8Pvjfp89jq XiXVbPxZCJLh9Ns4wEFsrIok3tEVzucDG7PtVyotT5Is48LncJ4L63iINJb2i7bvby01fRnzrXq3 7O/wr8NfFjxTqGneJvEq+HLe3s2nhO9EaZgQCAz/AC4UZJHUj6E13fir4L/Bnwn4Y8UWknxAvL3x xo1vIPssckcdtJdBWIhUGIl8EbWw3Xjg5AZ+zZ8BPh18btMNlfeJ9WtfF8SS3M+m2kYEaW6uqBw7 RFTkuvAYnnpSjTamk7P5mmKzOlPB1KsHOCWnNyu6vrez6eZ8+61ZQabrN/aW10l/bW9xJFFdR/dm VWIDj2IAP41TrW8J+F9R8beJNO0LSYPtGo38ywQx9Bk9yewAySewBr6S1j4K/Av4T3A0Dx34z1i/ 8T7F+1DSI8RWhYZBwI25wQcEk4wdozis4wcteh6GIx9LCSjSleU2r2iru3ey2R8r1v6n4B8Q6L4V 07xJf6VPZ6JqMhitLqbCicgZyqk7iMfxYx717D8Rf2cfDfgC58P+Jf8AhNINU+G2rXsNv9stctfx I6O5bYEKsAIzz1yQNgr3f4qeHvhNdfAX4d2uu+KdYsvCsOf7Kvre2LTXHyH76+WccZ/hFaxovW/Q 8uvndOLouhFyjN2fuvonp/iv07HwRRVrVY7SHVLxLCV57FZnW3lkGGeMMdpIwOSMdhXqnwC+AT/F 59W1bVdUXw/4Q0VPM1DU3AJGAWKJnjIUEljwoxwcgVhGLk7I93EYmlhaTr1naK/rbueQ0V9O6b8O P2d/HWrQ+GfD/i3xFpetTOILPUNQiVre5lPCggovU9AdmSQB1ArybWPhfB8N/i6PCnj+6m03TIJs XN/YoXLQFSUljG05B47ccg8g1bptanJRzKlWcocsoySvZxabXdLr8j07wj8Dfh34P+Eui+Ofilq2 qodcY/YNN0kDds5KsflJJwN2cgAMBya8d+Kdn4Js/Eyp4BvtTv8AQ2t1dn1VAsqTEtuQYVcqBt5x 1z1r7I+M3h/4TXnwb+Gdv4j8U6xp/hyC1xpF5a2xeW5TykGZF8s7Tt2noOtfBt4sKXk62ztJbiRh G7DBZc8E++K0rRULRSR5OS1p41zxFSU73ejVo2u0rabq2uu+56B8FfgV4i+OGvSWWjrHa2NthrzU rjPlW6np7sxwcKPxwOa9lvPgf+zv4bvP7G1r4qalLrSMY5JLJVNurjgglYJFXB7F61PE2qSfBX9i nwzZ6KfsuqeMJN95dxgK5jlVnfnHXyxHH9Ca+QKHy00la7KpfWc1nUqKq6dOLcYqNru2jbbT67I9 7+L/AOybrPgnTYfEXhG7PjjwlcJ5qXunR+ZJEmCdzqm4FMA/OvHHOK8EruvCPxw8ceBfC9/4c0TX pbTRL4OJrNoYpVIddr7S6sUyOu0j1610nwC+AT/F59W1bVdUXw/4Q0VPM1DU3AJGAWKJnjIUEljw oxwcgVDSm0oI76dWtgKM55hUTjHaSWrXmrb9NNzyGt7wInh+Txdpa+KnuI/Dxl/01rT/AFoTB+7w ec4r3/Tfhx+zv461aHwz4f8AFviLS9amcQWeoahErW9zKeFBBRep6A7MkgDqBXhfxM+HOrfCnxpq HhvWUUXdq3yyx52TRnlJF9iPy5B5FJwcfe3RrRx1LGOVC0oSts1yu211/Wh6p+0/8IfBvw58P/D/ AFnwY1+9j4ktZrzdfy7mMYS3eIgYG04lORXgVfT/AO1l/wAkX/Z9/wCxfP8A6TWVU9P/AGe/h94i /Z91Tx5ofiXVr/V9K09HvrRkEcMN55aNJF80QLKC/VSQfU1pOnzTaj/Wh5mAzBYfA0p4mTk5SlG+ /wBtpXZ82UV7V+zX8J/Avxf1ifQvEniHUdK1+eTGm2djHkXCrG8khLGNlXATuRn3rhviR4P0/wAD /FTW/DaXMz6Zp+oNa/aJcGTyw2CxwMZx6CseR8ql0PajjaUsRLCq/NFX2e3ddzjqK+tdb/ZW+Fr/ AA507xzpHxEvbbwvJcHztR1KD78KmRHWKLy0cymRAoBHQMcHineHf2b/AISfGrw7qcXwz8UasviP Togxj1YAJIT90uvlghSQRuQ/LnkHgVr7GWx5f9vYTlc2pcqdm+V2i9ve7HyRU1j5BvLcXRYW3mL5 pTrsz82PfGa+mfDfwi+Aum60nhTxF481LVfEs0gtXu9MTyrGGY8bEcowOGONxJXjnHIryv8AaE+D M3wO+IUmg/amvrGaBbuyuXUKzxMWXDAcbgysDjrgHAziolTlFcx10MzoYmt7CKkm1dXTV13Vz074 w/Bv4Z2HwFtfiB4Dk1aWO51BbWNtQl4Kgur/ACbQeqV8zV9reB/DfhvxP+xPoEHi3xAfDeg2+qTX NxdpHvkfbPMBHGvOWYnjAPQ8GuV0f4B/Bz4zWV5p3w08W6na+KrWEyxWmtD5LgDuRsU89CVJ25yV radPms421R4eBzSOEjVp4hzkoTkuZptJJ2V2fOXgHQdP8UeNdF0jVdTTRtOvLpIZ7+TG2FCeW54H pk8DPPFdJ8efh7ofwx+IlzoXh7XV1/T44Y5PtG9HaN2BzGxT5SRgHjswrY+Dfwx8J+IfiBf+EviD rGoeGtUW6TTrOC0iLtLdmXyzEx8twvOOTge9Yfx6+Hdj8KPixrvhXTrm4u7Kw8jy5roqZG3wRyHO 0AdXI6dAKx5bQvY9uOIVTHqlGb0je1vdeq1Uutr20OAor6L8P+C/2dtD06w/4SLxvret6lcwxyTf 2fatFDblgDgjy2OVzg/Meh4zxXPftGfAOw+Esega34b1eTXfCWvRGSzuptpkQ7VYBmUAMGVgQQB0 IxxyOm0rjp5pRqVlQcZRcr2cotJ27XPFaKKKyPXCiiigAooooAKKKKACiiigAooooAKKKKACiiig AooooAKKKKACiiigAooooAKKKKACiiigD6Q/Zt0/443fge/f4Z6hbWmhDUXE6TfZsm48qLcf3qk4 2eX044+tesf2L+1t/wBBmw/Kx/8Ajdc1+xz+0B4D+FHw11XSvFGttpuoT6vJdRxCznmzGYYVDZjR h1RhjrxXvH/DZ/we/wChsb/wWXf/AMar0qahyK87fM/Lczq46OMqKngozjfRum3f59Tyz+xf2tv+ gzYflY//ABuj+xf2tv8AoM2H5WP/AMbr1P8A4bP+D3/Q2N/4LLv/AONUf8Nn/B7/AKGxv/BZd/8A xqteWn/z8f3nme2zH/oXR/8ABTPLP7F/a2/6DNh+Vj/8bo/sX9rb/oM2H5WP/wAbr1P/AIbP+D3/ AENjf+Cy7/8AjVH/AA2f8Hv+hsb/AMFl3/8AGqOWn/z8f3h7bMf+hdH/AMFM/P343Q+Lbf4oa1H4 6mjuPFS+T9ski8vaf3Mfl48sBf8AV7Og/WvQ/wBh3/k4TSf+vS6/9FGuQ/aU8ZaP8QPjZ4k1/QLs 32k3htzBcGJ49223iRvlcBhhlYcjtW1+z7+0BpXwN+2XE3gi28RatJLug1JrsW8tuhTayKfKc4P1 FcEXGNW7elz9DxEK9fKPZwp+/KCXKrRs2vO1rdjjfjd/yWjx9/2MGof+lMlfSn7Jujn4J/Cnxh8V fEamzt7m1EWnQSrte4VclSuevmOUVfXaT0INcpd/tceB7jVZ9W/4UboL6xLM1y15cXUcrGZmLGRs 2wJbJJznOea8s+Mn7QXiv42XcX9szx2ulW7brfSrMFIIzyAxBJLNg43E+uAM4qlKFNuad2cdShjc woQwVSl7OGnM2020uiSvvbdnRfsdzyXX7TXhOaVi8sjXrux6kmznJNcz8SbjU7P9ojxbdaKkz6tb eJ724tfs8ZkcSJdO6kKAc4K5/Ct34AfHvR/gi1xdXPga18SawZjLa6nJdCCa1UxlGRT5TnBBPcdT S+PP2io9a+JGkeNvCXhOy8F61ZNNNLJG6XP2qaXO6WT92mThm6565qbx9mlfW51Sp4r+0Z1I0fcc OVNtWbV3qr3s722PUb743fC/4yXcNh8YPBd14c8TKiQPrdjvQpxwzjh1GG4VlkAzXjn7RXwU/wCF H+OY9Kt746npV7bLeWVy+N5jLFSr443Ar1HBBB46D0e6/aW+GfjK+t/EPjT4Ux6l4viC+bdWl40c Fy6gAM6ZAPAAw4fAGMmvI/jV8YtV+NnjI67qUEdlHHCttaWUJJS3iBJC57kliScc57AACqkoyjq7 v+tzly3D4mjiIqFOVOnZ80XJSjfpyat237K3Q9m/bl/5pl/2A/8A4iov+Cev/JaNa/7F+b/0ptqo 3H7Sngbx14R8N2fxE8A3HiLW9BtxbQXVrftbpOoCjL7SCM7RkcjOSMZxWd8Df2ntD+CNhdLafDu3 1DU5ppsaodQEU4t3ZWEBbyGLAFBznkjOBVc0Paqd9Dl+r4z+yZ4BUW5q63jZ3bd1r+djxLxQxbxN q7MSWN5MST1Pzmvoz/gnr/yWjWv+xfm/9KbavGvjF8QNG+JXiqHVtE8JWvg63W2WGWytJRIssu92 aYkInzEOB0/hHPp6L8B/2n9H+B+hLBH8PbXVdbPmJJrS3wt55InYN5Z/csdoKr/F2FZ03GNS7eiP WzKnicTlkqNOk+eSta60+d7fcyL9iG4s4P2g9I+1FRK9rcpbFv8AnoYj099u8fjXmnxitdRs/it4 vi1ZXXUBqty0vmdSTIxBHsQQR7EVe8cfE611j4hWvinwhoEHgM2gia3tNPkV1jlQ58wEIoJJ7Fe3 evZZv2rPAXjmG3v/AIhfC211rxLBGsZv7WRVWfA4LA4IGf4SWA7elC5XHkvsyKixVDFLGxouSnFJ xTV4tNvvZrXWzPmu90HU9N0+yvrvT7q2sr5S9rczQssc6gkEoxGGwQRx6V9LfHz/AJNL+Df4/wDo tq8r+Nvx81X4zT6fbNYW+g+HdMXbYaNZH91DxjJOBuOOBgAAdAMnPY+FP2h/CeofCfSfA3xF8H3H iS10aUvYXVldmBwvzYVsEHgMV4OCMZGRkkeVc0U9wxUcXUjh8ROl70JXcU03ZprrZN6q+p8/V9a+ CUk1D9gXxdBouTeQ6i0l+kJw5QSws5Pt5QUn/ZU18v8AirUNM1XxJqN5o2mNo2lzzM9vp7TmbyEP RN5AJx7/AK9a7j4G/HvWvgfrF1NZQRapo98oS+0m5bEc4GcEHB2sMkZwQQSCDxiaclGTvs9DrzLD 1cVh4SpR9+MozUX1trZvb9Lnnmk215eapZ2+nrI9/LMkdusJw5kLAIF984xX0p+39Pbv8UtAhyr6 nDokQu3T1MshUH36np0YUy0/aS+Fng/UZPEHhH4RxWXilvmimu7stb274xuRBkLj/YCE+orxdviZ c658UY/Gfiyyi8Tyvdrc3djOQkVwowBF91gq7QFHBwBVe7GLine5zRWIxWLhipUnBU4ysm1eTdtN G1bTdvc9z/aW/wCTavgf/wBeI/8AREVfLNfTXj39r3w1468Cy+GpfhPYW8UNlLaaZK2oLINOZ4yi yRJ9nGCvykAEfdHIr5lpVnFyvF3Ncmp16OHdPEU+V80nune7b6N9z7A1DSZ/j1+xfoI0RDea/wCD p9k9jCN0rRxqyYVepJiaNx67GAya+P2UqxBGCOCDXb/CX4w+I/gz4j/tbw/cqvmAJc2c4LQXKDor jIPGTgggjPXk17rcftTfCnxJcf2t4i+Dlnca85LSyRmJ45W/vMSo3Z/2gfxqny1Em3ZnLTji8rnU hTpe0pybkrNJq+rTTtpfZnkngP8AZ817x18NfEnjZbm20nSNIQukmobkS72gmQRsAeVwB0wWbbnI OPZPBKSah+wL4ug0XJvIdRaS/SE4coJYWcn28oKT/sqa8s+Nn7TWvfGKxt9Gisrfw14WtiDFo9g2 VYj7vmNgbtvYABR1xkZrK+Bvx71r4H6xdTWUEWqaPfKEvtJuWxHOBnBBwdrDJGcEEEgg8YIyhGVl ta1xYjD4/F4f2lRLnjOM4wv0j9ly6t99rnnmk215eapZ2+nrI9/LMkdusJw5kLAIF984xX0p+39P bv8AFLQIcq+pw6JELt09TLIVB9+p6dGFMtP2kvhZ4P1GTxB4R+EcVl4pb5opru7LW9u+MbkQZC4/ 2AhPqK8bi+KE+r/FRPGvi7T4fFcklz593YXBCRTrt2iPlWCqBgDg4Cil7sYuN73NUsTisVDFSouC pxlZNq8m7aaNq2m7e57R+1l/yRf9n3/sXz/6TWVafwFRpf2Nfi2qKXYTTMQoycCCIk/TAP5Vz3xQ /az8PfErwL/wjr/C2xsWtbRrTS7tr9Zf7OUhR+6XyBjhFGAR90elcZ+z/wDtFah8DbjU7ZtMh17Q NUUC702Z9mWAI3K2GA4JBBBBGPStOaHtL30a/Q82ODxkssVF0rThPmSbWvv826bS3tqXP2M/+Tk/ B/8A2+f+kc9c5+0d/wAl38c/9hWb+der6X+194W8E+IoL/wb8JNH0ePcTdS+aouZUKn5I3Ef7oZI zwwIGMDOR5T8ZfixpnxW+IVv4ntfClv4fTy0F3Zx3AmF3KJHdpXby15YMFOQfujntUS5VT5U7u56 GHji6mYvFVKLjFw5dXF6pt9Ge0+Kf+Uevg//ALCsn/pXdVm/8E9WP/C5taGeP7AmOP8At5tqn1f9 szwvqngdvCg+EGnw6Kiubez/ALRVoYJG3HzFj+z4yGdm+pNcn8Af2mtJ+BeiyRJ4BttY1qRpA+si +FvM0LFD5R/csdoKA9fwrTmhzxfNseW8LjpYDFUPYNSqSk0uaO0nfv0/4Y8Y8SsV8S6qQcEXcpBH ++a+nv8Agol/yUTwv/2Cm/8ARz15XdfGbwpd/F5PF7/DTTTov2YxSeGzcKYZJCCDKX8nG7Jz9zt1 rpPj1+1JpXxx8O/Y5fAFtpWroyCHWGvhcTRRhtxjX9ypAOfWs04qElfc9KpTxdTGYWt7F8sE+bWO nMku+tra2+R0uuf8o/8Aw/8A9hxv/R09eY/sq2eoXn7QHg3+zlkMsV2ZZWTPywhG8wk9gVyPxx3r p/h/+1Np/hH4S6f4C1XwDZeKNOgnklna+u8LKrSM+FTyjsYFhhsnp0540Lr9q7Q/CGkX1p8MPh7Y +DL+9i8qXV5JvPuEBPRMr26jLEZ/h4qrwbjLm2scqpY2nTxOGjQv7SU2pXja0ur1v52sV/Gd7aah +3NbS2TK8A8W6fGShBHmLLCsnT/bVqzv2stJuNe/as8Q6ZaBTdXs+n20QY4Bd7W3Vc/iRXLfBT4v aX8LfE15reteErfxleSNHNbSXlwI5LadX3+armNzuzjng8Zrf+N37RWn/FjUtO1jS/BVt4U8R2t2 l3JrEV0txPOUULGGPlIfl2rjJP3RxUuUZQd3q3c6aeHxVDGU1CneEKfJzXW+jva9+ltjtvHngf4K /s/31r4Z8TaVrnjXxKLdJ724t7k20EZYZAUBh9cc8EZPYa/7U1zpF5+zZ8KptBs5tP0eSVmtbW5k 8ySNPLOFZu5rB179p/4e/EOG01bxx8LI9a8W2sIiFzb3zQQTkdN4HOPZg+O1ZvxG/az0/wCJHwv/ AOESvfh3p9rPDEEsr23ugI7IgjBih8r5flG3Afp3rRyhaSTWu2h5dLDY+VXD1KtOblCV5NyVtU1e Kvtr2T6anztRRRXEfehRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRTdQkl8vE itIqj7pPOc9c1zWvacdWhMLfID0J5/CsY1YyZ+YLjZN/7v8A+Tf/AGp09FePXXw/JmUjjnPvTB8P zmUlhtbpmui9P+Yr/XWP/Pj/AMm/+1PZKK8Xb4e+XEY1dW4zjrj8aoN4Auh8hVQG9OcVS9m/tDXG kX/y4/8AJv8A7U93orwC68A3rPGuAwyTwfStrRPCMtvdRlo9nlnfuPI4GcfpTapr7Q/9dF/z4/8A Jv8A7U9lorndN09rqxkkKAEFh6dB/wDXqhHYGNMbDlecFevv+dRLlik77iXGnfD/APk3/wBqdjRX ITaM0xUbuD03H7vGTUc3hlpNywnc7cfM2APwrH2iE+NO2H/8m/8AtTs6K4iHQZ4edrYPyg9SD7VJ b6PceZIGK5Xnocn2pe0iL/XX/qH/APJv/tTs6K5ePQVXG4sr9lA4NMHhpmuQ8jfu2GNpXPbOapTi V/ro/wDoH/8AJv8A7U6uiuRbwu0jEYWTjCsOlbvhHwP/AGpf+XcRKUB+bkggfh71UZwbs2JcaNu3 1b/yf/7U0aK67/hUWnupKNNF9HzgVz/izwMfDa25iuJJFmJA8zAxj3FdcaUJaKX4Gr4wa/5h/wDy b/7Uo0VmNZ3DIPmcr/vD/Cq0lvP1LFseuDW/1T+9+Bl/rr/1D/8Ak3/2puUVz/2efBUY/KmGzmb5 sDd/u0fU/wC9+Af66f8AUP8A+Tf/AGp0dFctNpcjqAetZl14MjueZN34U/qf978A/wBdP+of/wAm /wDtTvKK88XwJaqwJQYz3FSjwTZLwYVIzzx0pfU/7wf66X/5h/8Ayb/7U76ivl7xJpKXGtXaxOqR hyBv4xg/SqmkWMcmoW8bruw45z70fVP734FPjO3/ADD/APk3/wBqfVlFcWvh1NqkwrngbvWnf8I2 qsCsXHtT+p/3vwJ/11/6h/8Ayb/7U7KiuKbRkUY8vB9KRtFWPGQrf0o+p/3vwD/XT/qH/wDJv/tT tqK4ltLRM/KpH+zzUQ0+JuQGB70fU/734B/rr/1D/wDk3/2p3dFcGbGJeg5+lRvawqOuPWn9T/vf gH+uv/UP/wCTf/anoFFecutpGvMig96aj2IYjzlB60fUv734D/10/wCof/yb/wC1PSKK87PkBcLK p7kY5qNQjYxt59qPqX978Bf66/8AUP8A+Tf/AGp6RRXny2u7gAMKmWx8zPyil9T/AL34C/12/wCo f/yb/wC1O7oriI9LaVuF4A9KsLocjjpin9T/AL34D/10/wCof/yb/wC1OvorlF0Ft2Opx6Uf2Ewx levfFH1P+9+H/BD/AF0/6h//ACb/AO1OrorC0yG90eZJbS4ktpB0MbEVc1aa/wBcwL2VZz6lAD+e KPqf978A/wBdf+of/wAm/wDtTRornf8AhH/9gH0pf+EeOM7M0vqf978A/wBdP+of/wAm/wDtToaK wU8P8ZKY/Cn/ANgKedv6U/qf978A/wBdf+of/wAm/wDtTborEXw2rdBz9Kcvhts4z+lH1P8AvfgH +un/AFD/APk3/wBqbNFZP/CNtyM4/CmN4ccYG8D8KPqf978B/wCun/UP/wCTf/amzRWC2hmNjukX 8RRHokknKFWH+6aX1P8AvfgH+un/AFD/APk3/wBqb1FYv9jSgEeXu+gNQPpEw/5dc++aPqf978A/ 10/6h/8Ayb/7U6GiuQutJfa2dNDkdO9Vrbw8ZJM/2Ov0H1o+p/3vwF/rp/1D/wDk3/2p3FFYFr4a /erINJeOQdJAw4rqdJWeFtt5pa38PQxXHOfow5BpfU/7w/8AXTS/1f8A8m/+1KtFbVx4e8Pahzb6 PPpMvcNIJI/8RVC68LSWrDZEk8Z6GM8/iCKf1P8AvfgL/XT/AKh//Jv/ALUqUVah8LySDJiKnPTc KkPg07dyo2frVfUv734D/wBdP+of/wAm/wDtSjRV5fCsu4Dy3496sQ+GZCwxC2PqKX1L+9+Av9df +of/AMm/+1Mmiuij8LsORbseemcVZi8Plcf6MxxR9S/vfgP/AF0/6h//ACb/AO1OUoru7fSvLwWt 2AH0oo+p/wB78Bf66/8AUP8A+Tf/AGpxC2t4zMpjVyyYL9vb8arxae/meZLGFOCTtOdvvXd3HhLx do9qDe6NK4UnJh2yDHTPyknH4Vzsklxb3SwtHBCrjlQpXb7c818o+aL1R+cKhbVmDNpklxCxWMGP qHHB/Kq81nFIoVRk9G9a6ORriLcjxmFMcNjgjuap283nXDw+U2E5DbCFPHr3oVRSIlS6GP8A2aFh XZEvzDPTmpF01ZIi7jO44G0cA/X8a3o7WVY1Q4XJ4kIGc+9I1nHGpMsTb48kMDwfwodTl1D2XKtz mbrSUW5V5YcS8oFyOnSoo7Ix7sJtOMMzN/SuskVbeGS4MfmDGQGwdvrWe8MF1skwwcHaNnTbyaOf m1MZU2tStZxvb2E0awyYZGyG5IJHWqdnpMrRgBiSy475rooY5JJtgjYGQhd23OBgcClvLeO3tzOb n91uCblT7p/D6/pTlWlOy7GTi5LQwf7Nm2bGBcMN/XByO1N+yyK3mENux0PbmrckcFxOZYtQLcFW gCnOc/4VoS2O6ZUFypwMbsdD16VDbuZx5m2jIgkuYpowrCQdfQVJJMcf6phJnk9R9c1dupPOktpV uEcj5GGMcDpjAqGa+hjUQlByMghuSPeo3ZfM46bjbZpIXaR4mIIJDYz2qdblVhKsrt8hIb+lUlvD NDm2fMcfA2n8hTf3si7pN0QVcbmPU1eq3BVnElhcKqyEHGM7Qo/L2qWDWH02SUWs00Pm9QHAPXua ijUCBsSAY6MGqrHGn752KykgbcDn8aabjqivbSOiXxhqqw5j1O4Ru5kAbFV7rxFe6hD5Nze+bGjF lVowcHjnp0rH8kRqiuNrbDyxPzAsKkdEhjaRj5gwG2hue/FbqrUurMr2k7ljzpY2Dnyim7G0p/8A qpLjUlWRRHbwZJ427sN+pqC62QqOQiyjcGBzj8apZkiutrMZYUUsG3Efgfc11wr139o0jGUtmaEl +Y8M9mmDyhSQ5Prxikk1S1t4zNcxhEPQK/zfliufvLXUWLDzJFRjlRG2SBjv/kVmXNre72WSKTfn gtkY9+a76cqt/eqG0KV3rI173xzZpKkdlZySSdWM5GB7cVC/ia6unztjsznkKrMAPyJ/rWRHNPaw O6hZFYZMpO3v0BxzVZbqaJs7FjB5Hl/MT+Nd3tG92dcaUTVuLzUpZP3dyrIzbQQMKR3IyAay7q0e 7tZfOurpZlk2bVcBSuPrms6a4l2NHhleQ7yZRx/MVM0l0zxxuwZ+2DkEH09KfM+4+WCexy2oeBZb i9YxTOiMfndxkfWr2i/DlmmEyXazPBy/A2qR755/Gusgl8mQqZWIK/MjdP06c1XjjiikxBAeHx8v BOT1xjn8aXNKxSpwepqR391bxkzjzF27F+YfeC+g9TWjb61GbdCUyzcFVY5B+lY0n2n/AJaLsdWB EhUHfzxkemKgvxLazSJH+9VhkzOm3nrjFCq23Zk4U5Ox1dreW18WWGdUcHDBmwc+lXJNHuphuWNn jz/BzmuHgtZFU7bf5JAMnk4P51pwX2s6PbrHaMzrG3IIJ69uv8qmVeS2MJUv5WdB/Yt0md0Ei+mV pn9lTKp3DaM9x1q3pPii7uoAjxTW8ygk8kr+ZqSx8Va7HcK0kObb+CRWDg+xFc6x0lfmiczbjuZ3 2V41JwpT6Cq8kShSXTj/AHQa66TxAduZJY3BGNvljj8MU23vvNXL2tsyFuN8K4P+NT/aST1iR7RM 4G6tNPm3CQqpx/GnQ/nVVbbS4kfCROykZLIR/I16JHFbXbP5mladIVbDEQMmB6fKwH6VDJpejshc eGo7jsRBcMhH55rSOYUb2tqaKUb6Hnjrp7MWiXGeeYicfrVy1k06WTZtUnHJ2EV2cek6KIy0nh3U YEYdRfqV/LZmiPQfC8khWKyvxIDn/j4Rjj6ECtfrtL+YdvMwbWKzfaI1IXpn3rSisoWbGMH/AAq3 GvhiK/jtZft1mzMAzlFYJ6E47V7DY/Ae31CzS5tdbSWOQblYxk8fnWyxFOSvctQk3Y8ajsUUnA49 qtLaq3G3Ar1m7+Auowwube6t7kKMhOQx+ma4qTRJLORop42jdSVKsMY9a3jOM/hdwlCUdzAhsuwU fjVtbNQR8qsP7prWXTA556e1SrpoC+3uK1IMVbKPum36mpE08NyB8vetX7GN338nFTfZ12jDHjqM UAZH9m9lGxfpQulOGBycdTxW4bVOcHI+lOFp33HkccVPUoyP7JfdjqPpTl0eQ5A2k59K21t/lHf+ f41KtqST0XA5wavzAxI9FboxGfpT10XnnAPrW15aKoyTn60q7B/HgY70mwMb+x1OD19R60o0VSCP LHXuDW0WjUAtOgB7FhxT1aOTO2VGx1IYU0SYX/CPxYx5CufU0o0zylAW2OO20Cttsqy/I0g/2SKs w7pFxt24/vdaegzBj0vzAB5O3PqKc2ilDgxL/vCui8ggc80C2LAhWAH+11qeoHKzaPIPuhVx6DNQ R6XKrEGcDtt2c5rrpLU7DjDZ+opkVmyjmM7u5znNWIwrXS5d3+tX/gS4rTj0obQN4yPatmGFVz8p zjrVnykVANzA57880DML+w2cja+D71PHoJ5HmMSOvSt2OJF68k9Bg1chijbDfMT06U0M5kaCzbf3 j5+gp58Ou3AZsf3s11QgXPQ1PHGi9uaBHJR+HGXktkj+9Vq18Osrclea6lYvM6Lx/eBqdbcHjqe5 YUgObTRPKXn5qXy4YX+eKTHstdVHZjj7p9OKtR2cYJLJ9floJOVgjt2YZiyPdaK7CPT7dpAPLG4+ oooEeEaT+0rqq4EtrFKvrk8Vvz/tAeG9UjK6xoUU4K4ZioY/nivmOOVyzAfKF+nNSeT5uNgPTkL0 r5+yluestj6WXxp8LtVjXdZtaFv+ee4BfooOP0qpc+G/CGsR50jxV9h5+WO7h3IfYng187QW7TKQ Ny44ppvrqwaIxyvjOMCsp0acugpa7o+gv+FZauqmO11PTdRizuLRXQDnnoFYcfnVLVPh74li+7o1 26nDM8IEn/oJNeNL4v1i1ZBFdSBM8Lk1vaX8Xte037l9NHKDxuJxXI8HTexPLFrU6y+0uXT4Y0ud PvIghYHeGUNnr1FZslrBM2EaSF0Yk7j90Ee31qa3/aS8R2P7ueVblRwyyqXH15rZh/aE06+Xbqvh vTbs55LRBe3XpWP1KS+GQlFXuY8c09r5KD7ifIcHdlvfnqKRfNhmmPlo42HJVR8rdsDsPauot/H3 w91aNDNpM1jITkGzuCMH6Hj9Kauk+DNXkeS08S3Fl5nG26iUgfiprKWGqJnNKi27xOOV9sgadUWZ zubag+6B69uaIW3TR4BkfOd2R0/DtXdyfC17i4aew8QaXqBYLt3OYjx6gg1hXPw58TadM6nSbi4i zu8yyxMD74XJ/Sn7Ka0aMVh5LdHLllhlMzw/ebaAvXHrikupPKuupZwMbWT1pviCy1HSZI0urO9D uT8727rj68fzqrb6tHNG3lygPghlbgj3rP2bWqRl7OUXohy2O4u9u4TH3VK4GfrT1tfOj2hXZFGG JPBOabDeKrJGXVUfLcHJIpjRwNMH+0TEtlvvfdx3pTi3uVOjpdofb28FrKxSKQgHPHIpxxezbgXt kUBwuzljjkH0FMaye6jJivmjlYglCuBSyafNbsQZ927HGeM/Sp8jJRa0a0HM2xY4jL54TJEYbH86 jcSRsspwo2YY7h8vOTj14qX7HAZS7Al9o2gH9agkmS0bE+WXOQFPf2p3tsJXYWMMccZaRXlfadrE evT8RUi3lvaqyj5pMYCnPHr9aWPcs8eyRpImBXJJyCarQwxwzSSPH+6c7RuJzmtFeW41r1JIUa4L SC5Maf3HHJNSalI1xLGm8h1I3+Y3y7cc4qAWgzuQmN87m54OP6UefI18QW2RLje3XIHXAzzVK62Z n70dUyO6t7Xy7c3CxvFGCADkA+vHYVE2kQTW8b+UozklVGBjtitN5orplE1uVDFnRQM985PtUTeY twfLCRq3UrgnFVGrJfaNVOa6mWuiWMMcRkjEUoHzIxOW/wDrVLaaZZiQyW6qJXyu7A+X8KurEJ8z TSM0YIHlyYxz3zUhWKEHy2XeVLBc8gZ61TrTfUXtpXuU7W2ig89zBCXmOwOBn8P8ac1rbNJI8EXl tGoYz7sjjsAOnFLHcXHlrDGI448hnJHQfXvTxps8nlIFBOBlEOOMnBP+FL20trlqtNsrX0Zu7OEK WCYyygAFWHUj86S3tVaT5Y2klYDcGZeQMnJ9OlW7yz3SRMkiRHGQvfIHOcduKqQQqZJyJIym0BmX GV4//XTUr7kSlqE80EjRPM0gkjO4GFiuRnBB9qsXGsQSTRGHgomRGV25xTJLeFQW8mQSOuA8hyu4 c9BVe4sbiYn7GxHlqMsULAfh/jRKz0M7tlqDVUhuZfM8xI2UFWVgwye9MV7i0nfyZ3nV1+YBOE9D 9ag02zvDK0dwI0duGcgjr0wK2riIx28YhVWlbq4HzFemG7CpfKlY06bGAJ5Le782Uq4b7oQHO41d m8QXNjuV4vMQYxjO5D6elalvYSXLfJGsTRHLlCGwfTmiLRYprppI4xJ5Zw7BgCSRnIX1qvdtqEVH VMh0fWJrhnRH8w4yy+XgjjvWnPdLBqEMMO0SMm4qwKds5Gax7r7R5gKFrb/lm6qNoI7ZI6mprG2i uriL7QkjfLhZDncuePyFZNR3CyeiNdtZkjYxiJZYtuVk4J649Kh8wRyYkj8h9u4sDxz796f/AGHc WcxdJla3VPMXII3ZOMe9PNkxsfMuLcyljhSr7c5FY8yW4ckluQJpMd0zSDc5YbgdvyntxXofwu8f yeH7pNDvneS1J2pKRxG3Ye+a83s5LmLMRtmKx87t3Dey8/yqyYXa3NwUaN3+bbnGzB7VtGu49dBx lJM+tLWYfK6k4PeuW8f+BYvEcLX1n+6vowS+0cSj/Gub+GXjC51CzWzupFaaFMqefmX3969Gtb5W HLc/Svbo1LpTiepGXtFqeAJpzws4d23LxtIxQtrKeVkytexa94HtdUuTdxTGB36qigjPrzWO3w2P lOY735gMhWjxuP8ASvVWIhbV6mDpNvQ86WGRjgtnHqKl2MrEBsA8dK1ms4Y7h4bu8h0+dXKCG5SR Cf8AaDbdpH40jaYn/LO7s7oj+CO5QsfwzmtlqrmTi4uzMFoZFyMjJ+tRt58ajDKCO1a17Dd2+caX cSL7Dj+dZj3F6rELo90wA6lG/pTdhIDcTIu5mUE9881Xa+uuNjJ6fWnSXl15ZL6VKhJxlgR/MVWn vtqkLazI/wDu5qbs1SFk1bUI2+aCMjscZpI9S1GYgeRG/tt6VLF9ukUbreTHVSSB+FPazumzIYJk J7B1NTr3DREMkN9KSHtE+b+HgVBNot1LHgWit/uSACrktteIuf8ASEH+4Gpn+mKQDHK4x1aHB/Sj lJuYUnhXU2w0UDIc/wDPxx/OtfR4/EGjzIZbaO4tG4KeYCQfrWrab1XMlvKp/wBw4p5uMq6mE5/2 kNVYDWtrhZuXt2i45yRU6NCrE7AOOp6ViafqOnXxc2k0F0Y+HWE5K/XmtLzk27TBKB3wtaoixbjk RlyCuPTNWLW7t7KRXuIY7tcY8sl1H/jpFZwvkXO2C5Ix2j6fSrcFxHJEp+yzqSe60CsdTp+t+Fbx TFcWc2myt/y2jEkqL9cnP6GtU+DbW8gFxpWqW2pbjkKpw3+friuKkkG0OfMT5edyj8qZFqEtncrN BdtBIMFZEGD+hosNSNTVIrjSGIurG7CjncsRI/MVRj8Q2ajI85Nv8O3n+dd94S+PWr6K4t9Ve21u yI5jnjAfHsw6j61tax4s+GXjKPfMsvh7UWGfMhhDoT74/wDrUwUub4jy1vFWnouXNwTn+5T4/Gmm c48/j/pkSK6RfAOq6xIW8Mahaa9CDgCFlWT8VPNVtS0HxB4bONU06S3b+9JFtH8qlpk69DJj8Y2T L+7+1Jk/88Cc1ND4wt2YlGn46lrdv8KfDqb7juQjHXAAzV6PUE8vqcjqAODT1H6iQ+LYmbDNjH8R iYD+VaEPiqzfP+kxMP8AcIIqh/bVqqkMOfQqcUR+IrEMCfLI9Sn/ANagNEasfieyZcC5hz3yCDRV I+I9IbHmNAx75TJ6/SimK5876h8P442DHTZE6nfEpOay28J28DYEskch42ypgg17bdaLDcMoaWVX znKvgD8qzbjwjbTSZaWeQ5yWZgf6V5UsG0vdZ3Kunujx638K3ILIDHJk5GOKz9R8F3qruSEkbsgg g4r2ybw5Z/KAvQ/extP6VUm8Ow8qN/r96sXhasdmWq8Op4Hc6Tc26lZInXgndt+7WbGzRjYyDdwd zHqK9xm8LlM/OR2BI61mz+Dw6nKQuePvpzR7GpFaxK9rSfU8Zv40m27dyc9u9OkKxxq2CTtxzXqG ofD+OZWK2obPUKcHpWXdfD/baYME6Mp4wM1K5o7xHzJ7M8+FvLPNgfIufuir6NuXCMwde1bjeEZ4 RuMmM/8APRMfrTY/CV4srMrRyfLzhsVLkmUovoZKaheQ8pdSxkHqGNa1n468RafGGtdTuI8HpvI/ HrVT+x7sQOZIJBjIyvNUL6U2dv5ZhdcY5K1EXruN8yO6sPj34x03Cy6jJcxnjEhyD+fWtOH9oK5v EVNV0TTb9c4bzbZD/IV5XJIGhjyvI5BNRWNkZIpOTh2PXtWnLF6szcmeuL8TvA+oZa+8G2scm371 szRY/I4FNsdS+HV8qzBdW0qWUZ2xzrIqj2BXP615LqEP2e1nYH+Ajd056Vc0/SUjs4135ITGeh46 Vm6cHqJ67nrA0XwxdqrWnjOSGQcKLu1BwM9Plaq954G1G4mWbTPEWi367cfNKYXHuAy4zXmBhSMh T8zN/dHSnsWVoxG7KfbisnRgwaUt0ehP4D8Vk+bLYNdk4DfYbiOUsBwOFYnrzWVqWn+I7Ztk3hq+ RGfJZrZ+o9ABXKw63f2eQLuYY+7hzWhb/EjxDpysbbVLhcDH+sI/rU/V432HGELbFuS6udNmD38E tlHu8xhJEV+lL/b1h5sc8t+uwSf6sqOfQCpbf42+Jo1RZrgXIA/5aqG/nVm8+L7XUUYutI069BGS s1pG2PzWo+rq5m6MN0Vp3stqTwzO/I+VcbqtGOzmMQlY7kH3lGCuPf696VfibodwoW48J6a2eMxx NH+qMKvQ+I/BMqHzPDRtlbG4W95J2+pNRPCvozKdCMndMzYrZ4vnlmWbf83z9QPrU0km4N5cY3Nn MirwR3xWkbz4e3TACHVLQDqYrtWJz25Wo1i8HpJmPxDrEMY6RSQxyKPyIrL6u2EsOtLFAWrNiJ2A jGdxccKcdRUE1vF9oCx/ONgBXB/nWnNa6LPdbofEsUqDpHcWzJnPrj0qOTQ3b5rXXtOmHGE3lefx FR7Ka0aMpULbIqm0aS6SNmBG1d659Peia3e7YbwUhb5iyggEA4FJa+G/EC3hdrrTpYc52x3SZP68 dTWpFpfiW3kxHYR3iLgh4JFYH0B57VDoT6GaoS3sVI42uJoo5Y42UgL5uCMdh9R7VFJpzbQPIaJW y5D9z34x+prVtbXxNcTEXGiXNvGpyrBR1J7c0sq6np801xe6ddXKn5RtjZn+uBWfs6iewvZu+sTN XT7j7PFPtdrcPypYHH1PertjbywySyxSNFFjDKqkFwOcEnqDTD5qyGIW9/ErfcluITgZ7U60vtqt C10xGcnKn8xUSU1uivZuPQljdGmjuRZySRyEqQFPT1HpzSSLEuoMkSTKSp6jGBjqPeqy6paysuL3 BDfdwccdxVy91ZGtgWnbzQ5Rcn76+oqLSsUoSZn215M98IXtyN+VPncLj3NaTRwvbmCO2KOmR5sY JJPrn0rM/wCEg00XCRNKF2tgryT07VXbxRbQSKlpOrlmJCu+Pwq1z9iYwlq2jQAX5AzvHGBlJZRn OPYcCtWxt4rqMTTPtXcd4ZcHjjI9RXMTeKL1YRuidhnG3YNob0zWpY+KpJlVLx4VBOfJAyxP9Kaj J6tExWux0Fx5S3UZ35hIKxk8gnHIqC6mlhPm7DEYxtwScc96yo/E2ntCUusRTByAScYHepYtZstQ WRrdi+wbWZJcj6D0FZNSlujobaWqL9iJb2Wf/RWZNgAce/cVJHp8rXIWMYlh+XyZOA4GepJ61kw6 5At4LeGSSEFwRK3fB5/DtVqTULuZhDbo15J5hP7vrjselT7KTewlGL1tqbFncyWl4s0MPkXEYAMu /C57ivY/CuupqlmhWRWlAw6g9G9K8k0Pw/4g15zEdNuDbsAx3LtUNnrkivWvB3w1XRLj7ZKCtyww VDkivSwvtacrW0NYRd7o6uHe+MnIIwcCqjJd2N1iQ77fOVb1rZj0xFGMsp9iazPE32fTtNlee6aN lHyrvzk/SvZvrY6LGf4m0a28VaZ5LRr9ri5idmI6diR2rxu8hvdFvGgvtOaCYNzIDlcfWvWtJvlC KzON3vSeKNKtfEmnmHeizrzGxx19DXTTm4aGMoqovM8xUxzKSQ4PYgfyNCxsMqs06p1H75hn680k 1hcaVM8N1gY5G0EZqg1xGjlh8z9CWPP8q70cLTTsbHm3lvjZfz7m5+eQt/OpVv7lSGF07Z65wRWO LhFVSiHI/T/69WfN3IpZVK56Z/nTHqan9rXb8v5Mm44G+GNsfmKnj1eSNsPb2kmB0NrH/QVjRyQR qyE88c5zUi3K8hWI9Dihgb8muW8sY83RdIUKOv2d1J/Jx+lVf7R0luJtKtVXf/yzllTP/jxrKaNZ 8EyBm/2u1Ry6Wko685zxiqA6Nv7Gum3LYSxAj/lneOf5imtb6I8eH+2Kx4O2YH9CK5yHSSsobO1R 93DMT+hrUt2G/BkLEH+JMUIRJYeFvDWnmR7G1vLRn4aSNYcv9cVe/s3RhHvl1PVoj3QW0bj8wwpi wPJ/qtoJPdaVrOYqd5BOegOKoCrI2hRsX/ty/RAMbZNNBP6PTlm0VhmPxAA2Puz2MyfqAajaGVl/ 1K5B6bhz9eOlPXS5HPmNBAi9Pl5/pQAq6fZ3DDy/EmmsevzrOv8A7Tp3/CPjnbrekynPa5wP1Ap0 Og2r4ztVs9MVMmg2/wAzbFPb5aNAsV49BuFPy3elSLnHy38X+NW4fB9/dfLDBZzOepivYiPy3c1F NpMKxny42L+yio4NHhkuAZLQBv7zoBzT0BvTYs/8IPrljdLJBZFZV+7JBOm4fQhq9C8L/Ej4h6FC Le70+bxDp+MG3voxIQPQN/jmuEi8P2qspW1jyST8ijJq5b6dFG4KJIj9trEY/WkTZdEevWug+Cfi grR3GjX/AIQ1du6xERlvY42n9K5zxV+zprugq8uk3y6pB1wgKuPqv+FclZ31xa4Cy3IbJAQzHH16 10ug+N9b0Vj9mupdn9yR94/I0tRq/XU4ibRPEWmymOSBg69VdCM/pUax6qg/fWMTj0Mf/wBavZrX 4tC6t/J1bSJJW/ikt2Az78jNW5NJTX7fzNAvpd33mgnbBHtU3HZHiC2cE7L9p0qNTnaWRiKK9W1C x8SadEBd2DFV+8yxhxj6gUUcwmux4w0Shj+/VSfU4zUciuuF3qRjn5sUyaxJ5WUFh71UaxeTDbx1 J5PWqLuTSwScHcDjnrVeTfkfNls0yaxfCKCp7nnmozYyx9yD6ZqRA29m5OCTxmo2jcdySTxmpPst wmfmJb6dKSSG4bHTb7CndgQeU/DYGetGxuCMgnk1P5Vxj59qj1xStDJHhskA8UbgU5ICV+ZEYdye RVSTSbeRm32qktxuXkVssrdCQxHcDg0xWcRr8gz61DjF9CoyknoznJNBtBH8sUkBHHyHr71Tn8KR TqT5xJPaVAc11TSSBTmMfSk8x9n+pJxzWEsPTlrYv2011ODu/Ayzc+RE+3oNuKoyeASEJ+x7cckR vXpLEP8A8s/fpQsZPIQAHrmp+rU7bl/WJep5BrHgNri12RwXCMzDP8QxUX/CK3EMexHZAOPmjNey LGFKjp1zk8U2Ty9mQOCaxeF7Mr6w5a2PDLrwzerkqY2Xtg4qn/Y1+rjFsz7eCVOa9ymt4mYrsjwf pWRfRWoMZeCML0PIGRUPCyt8RftU1qjyJbG58tS1s4Cg4BXnNUZY5A8oMLY3YPyd69fms7KQgR/u 8rgYPU1ENLs49u6QOxOT3rP6vUjsCrQ21PLBbhVQFApxxkVSuo0DbFGCO4New3UemEKWEDH7pZ+O K5rWrHSo8SrFDIp5wpA9aydOrF6o15qctmeaXEb28akZbnH1qXbIsatk85BHWty+1Lw9IscUtpJE d38Jz/Wned4eaFkS8lg53biuaLvsCsnuc/ud19GFVy0gLBsgg8c1uXNvpzCM2+qD0O5MA+lZklog 3Fb6KVxxg9TVpMJNFAtK0mQ7EDpzT0vpozhs/jTgsj7wDE3GBhsAH8aih86LClN4UcsDmqcSVorl 6aaSZF8tyo7nOKjXUNTsXBjuJPLJwPmNRtdRIoYhlXjO0Zpq6lErbJNybf7wpq/Yp69ToLfxVqVv CrC7c7eOWNbFv4ovvJJ+2TFmOSRIRiuSj1O2mhC7VHrnvVlLi3bZ8wCkc1lKL7AvU6GT4ka7YSNs vbhgOPmkJzzRb/G7xBbsAW81e29QcVz00cBzskyMYyxqr5kX3cgnPqBQkuqCykdwvx01xf8Al0s2 Cj+KBf8ACrUXx21B4V+0aVp7Drta2U/0rgWULkjHIxgc1RkXytxDEleOlHLF7ofLbZnpU3x4tWf9 94W0eZyRuc2y5Ix0zjpTo/jFpFyuZfCOjyt3zbgfyryAxGTllO7PJxVm1tfLZmByrdOKcqcbbEa7 HsEfxh0Qp5f/AAh2nsmc8bv8at/8Le8Mx7dvgrTmYEZ4bP1zmvHGbyegbH0ot5FaNtxJYntSdOKW wbM91j+MXhl7ZlbwXpsg64aMHn61Ztfjlo9jzD4Q0yAdQFgUV4dCwSEEj73NSrMJgcMCc4xU+zj2 LTPdV/aIsvMJTw1Yb/XyF/nU8f7St7b7jbaTaxAf3IwDj8K8Jtf3smBjg496tszQyDafY0nFLZFn uA/ad1neVa1iKk1Ov7SuryA7YVAP9wDIrwVbgSNzhTzVvT42BI6AHJNXyoiTPYrj45a9qEflrcMm 73pIPEWo6vhrmZ55ByATXnmkpG87gjJABUY9a9Y8D6Cj+Vc35EFupJAlO1nPYAU+V3Qr6alyx1y4 uAqvKYX9JMitqHUJI12mQMfXdmq959le4cBlkU8jjOKsWsdr5PCK7e4rrsjBJolvJv7YhWGXKleV kUbiD6fSuM1ixlsbp0ljJLNz3/Gu5t7i0Rud0YH93+VY/iWdbi4EoYNC6gHIwQQe1dFOXQiSuzl7 W4Kr8z888dx9asK29Qd+McAZ61H9stYcn5AFHJbipY9Rt+AFTnkGui1jBlmCFJn+827GSOKvQWLM p3D8Kzxqsca5TCA+lN/t7f8AKrnI7UCszVXSVZvmLf8AATUqaXCTlw2B331kLqkzqW84oOgX/GoG vkyfOuD79aF2Y7I6SeG1jjK+eY1A6rJiqK3NjatldTlDD+EuDn9K5O+vLMTZCmUemTVQ3iSLstra RD3wpYZ+tMZ3U3iBSg8i7Y474zS/25Nt4my2B/BXFhrlv9UkmOmAnWtS3ju5GQrG23GCDxSCxJrG oX7XaSwTeUQMHaPvH0NS2vi7VeGkC7ehwvyj8qi/s66vZGXyZoweAwGea0o/AzzwqGu5EwvI2CjU VkNt/HFxIuSiqFODxVq38XY3MZMnGRtXg+1QJ4Jit/ka5lYEc8Cp7bwfb2/zGSdz1xgUAPbxE8zZ kdkRh/dNW4PEFqrZZmK9Bu6Uy28O2NxgSCYn+6w6VpWfhGwjQhQ7En7shyMetFmIqf8ACRxwxhxN gj3xxmrcHipZM+XGG+mSa04dB0+1jKraq3/Ac1pW+mwRqGjjjQ+y4qkNFCz1SWRdzWLAMeCT0rVi mmPymMKT/D14qzHaIyjgDj/PFWY7ZBIME7/XtigQxITIoyRkdQRWrYyT2syTQzeXIn3WXqKhWHd2 IPfmpVt2UghxjPpzQLY7zRfiZqNttjvW+2Q4wWPDf/XorjFjLAbjwaKVkTZ9DEb4N+KCvGkZP/Xz D/8AF1FN8GPFLf8AMIA/7eIeP/H6+kPtJ5wAarzXjLxio5i7nzgfgz4tUHGkdeuLmH/4uo5PhH4w jXA0bcf+vuH/AOLr6Q+3HuDimLepjBRs0uYk+aj8IvGDKQNFbP8A18wf/HKX/hUHjHb/AMgRueub qD/4uvpP+0F6Dio/tzN3p3GfN0nwe8Z8D+xAwx3uof8A4uq8nwc8a8kaOdx/6eoMf+h19LteSHvm k85mHWlzAfNY+DfjRlGdFJb/AK+oP/i6X/hTfjZhxo+D15uYOf8Ax+vpdWb1xT2+pNFwPmA/B3xy mT/Yqn/t7h/+LqpJ8I/HMbMT4f35PH+nW4/9nr6lk3KCO+artGfrUgfLEnwr8dxghfDTN/2/W4/9 qVFJ8M/HrMQvhlgPX7dbf/HK+qPJbn5aEjCkZWjUZ8jS/Db4lqxYeDmlGeP+Jha/n/raib4Z/E5o 22+CyGzx/wATC1x/6Nr7CEadQDg+nNOKce1GoXPjNvhH8Tp2BfwVESD3v7b/AOOVUu/gb8Sb3hvB sMQ/vLqFvz/5Er7W+VScjNM8xRzzn3od+o+ZnwbJ+zL8UJWBXQWg5426jb8f+RKh/wCGYfiuzEjS 5k3dT/aFtx/5Er7084N9aPM645HWo5UHOfBf/DLvxR2tv0iZ8kD/AJCNv/8AHaT/AIZL+Id1/r9E YoP4TfW+f/RlfefmEcUm9utHKg52fB0/7I/jeNVK+Hi5U8f6ZbAn/wAiU1v2UfHW5XPhln4wy/bb Uf8AtSvvHeW4701s0cqHzs+Arj9k74geWfL8MsX38A31rjH/AH9qq37K3xLhjxD4UTryTf2uf/Rt foP2NRle2KnkQ+dn52H9lL4ol5CfCnysc/8AIQteP/ItV1/ZQ+K6qVHhhguCAo1G0/8Ajtfozs7U +NGQ5CbvqM0+VBzs/OL/AIZL+KhXB8LE9/8AkI2v/wAdqW6/ZY+K93Isn/CJ7G2hWxqNpyR3/wBb X6Myb5NoK9PQUwW7f3aXIh+0Z+dlv+yv8V4dv/FLZ+uoWn/x2rkf7L/xVVefCaA+1/af/Ha/QoQu cDHAqRbc9xxR7JD9qz89R+zL8VlAI8Io7d831p/8dqrJ+y38VGl3DwbHt7g31rn/ANG1+jkahRjp +FSoR3x+VCoxD20j85F/Zh+J4wG8Ep77dRtR/wC1ahvP2V/ifM8jR+DXCnoBqlr/APHa/SRdh7L+ VSeWmOgpexiHtpH5s2/7JnxNjhWSTwozbv8AlmmqWu4fX95itG3/AGVviLwD4PmwP+onaf8Ax2v0 W8pP7opRCnpQ6EWHtpH56r+yd4/m4fwvIg99Rtf/AI5Va4/Y1+IbNvh0UAYyFN9b5Ht9+v0S+zoe 1At0H/66aoxQ3Xkz864P2OviZGnOigHPAF/b/wDxyiT9jz4oBgYtCGf+v626/wDfyv0W8kdBnFO8 v3o9jEXtpH53Wv7IPxRtemjKD3/0y25/8iVq2v7JvxAVWa68PmZv4dl/bDH/AJEr7+2DvR5aen6V P1eDD28j4Eb9kXxttBXwy+7q27Urf/45Ulv+y745FwVXw1H7B9RgI/8ARlfe+1emP0pFtoVbIRQ3 rtp/V4j9vI+K7L9nH4iWsYC6BBCQMAx3Nv8AzL1r2f7P/jpShn0Vnwec3kB/9qV9h8etKMU/YwJ9 tI+Wbf4HeKbfJGguT7XUA/8AZ6nX4SeMY/ueG/zvIP8A4uvqH+VG2tPZxI9oz5Ym+E/jsq3leHFR +zfbIOP/AB+sO++AvxAvpA82ktIRjaPtkAx/4/X2J3FGPWqUUthc7PjI/s5+NnyDoa4Y5w13Af8A 2pU8X7OvjRf+YIB/29wf/F19jNx0Ipu4/wCzVCu2fIcf7PPjfHzaUoGfu/aIT/7PVhf2e/GCj/kE DJ5P+kw//F19a7jxkCgS7u360CufJ/8Awz/4u/6A+T/19Q//ABdPP7P/AIrYf8gbr2NxDj/0Ovq4 SdPlo8wemKLhc+UI/wBnfxSmNulFTnn/AEiDH/odWo/2f/FkDArYSH/ZW5hGf/H6+oTdKh+YYFH2 +Hjmi4XZ80r8DfFA66Pn/aNxD/8AF1Yj+CvileBo6gf9fMP/AMXX0eupRHjmj7ZF6tVXC7PnT/hT 3i1DldKBI6f6TD/8XTl+E/i/dtbRvxF1D/8AF19DPeQL13E+1MbUIG4AkJ9hRzD5j5+b4P8AivJx pH3uT/pUX/xdSL8J/FaqAdIzj/p6h/8Ai696k1C2gUvLN5C5+9IcD9amhvLaaNXjuA6N0ZeQaLiu z59X4S+KxIzf2Ufp9ph/+LqU/C3xXGuU0ZmboP8AS4cf+h19CLJDuP7ynq8TNw+aLhc+eV+GvjNR 8uhknH/P1D/8XViD4deM+N+hlcf9PUP/AMXX0Gu0rw2Kf8o6tj8aLsdz5/8A+FfeMI2AGjZHXP2m H/4upv8AhAfGTBcaTs9T58J/9nr3pWVejZFSqwK0czFc8Ntfh74r2jzNNI/7bxHP/j1Xo/h54j2k nTyG/wCu8eP/AEKvaFkHFP3+q0XA8c/4V94i2/8AHhz/ANdo/wD4qivZVI44Iop3EZhjHpUT2qt2 qwzComkOazKK8lpGQACwqJrHdjEhqw7+hqlcPtRjzn2NAgbT0HV1IHYjNMXT03cMp9qoNeMzgbmA /wBrmrMUzY4pAT/Y06fyNO+wJx8xpizH0xUySN3NAxPsYHQtQ1uf7xGKmVzQX60WAptbnHDc1C0M q9Tmr+/1HNI2G6Ln6GgRnjzORu59M0MrLg1fWME5KgGnNCp4xzQBjvI6sAKVZnOBtP5Vr/ZkGDtp yxqvQYosIyv3mc4JqNo5G/hNbe0dMUm2iw7mJ9llb+E1ILOTvGxHfmtZsCkyaOULmV9lkXrG1O8g n/lm35VpbjRk/jRYLmb9mBP3WB+lO+zL3U/lV7n6Uu407BczvKRc5GPwpyxxZ4q9u6cUhx6UAU/J iJz8tP8AKT1FWML/AHf0o2J3AoAr+SPY0eQvNWdq56UmwHtQBX8r0NOCH2qby1z0waPLH+TTEQ+W fSjafSpvL/CjYfWkBFg/3RTse2KftP4Uu00wGYFP4oAIzxml20AH0/Wj+dKR7UmOO/5UAKOnWnU3 IWjPPWgB9LUak49qdQA5aUU3n1oAPrTAduo3e9IE9/0o2eppALvI70eZ9Kawx2qNmPakMe0j9gD+ FRmaTPTFM3H/APVR97qaBjmkY1EWYd6m2/Kaa0Z9Mn6UAReY57kUbm9TTzG2MbTSeS2fun8qBmbr fiGy8N6Xcalql/Fp9hbruluLmQIiD3J964bwn+0b4A8ca0NJ0bxXbXWos2yOCRJITI3ohkVQ5/3S a4n9p61TUvGXwl0TWBjwrqGtsL9ZDiOWVQnkRv6hizjB/SrX7Xmg6TH8D9Uv7iKOzvNLeCTTLmNd kkM3moqiMjkZBI47c9sjVRWl+pm5PW3Q9b8S+NtM8G6TLqeuahbadp8RAee5cKoJ6AepPoOawvAf xu8H/EySZPDeu2uoywn54NrRSAZxnY4ViM9wMV5F42tZPE3xu+CumeK482M+nTXv2WbHlTagsQJD L0JUhSM9zjvg+4a54B8M6t4i0TUdUsbF9bspC2mzy4SZWHJCYILAYzjkCpsktR3b2PJNY/ar0XRf jvc+HL7WNOtPC1jp8i3Nw0TmRdQWUo0RbB4AB4A/E16140+KHhf4d6XFqXiTVrXSbWbmEzEl5eMn Yigs3BHQHqK8nOlxyfttNE8ETbvB/mFWQEE/aOv1p2h6bBr/AO2V4mTXo1muNH0W2bQoZzkLGwUz Sop6MHZlyOxP1q+VfgRdnqHgL4weD/idDNJ4X1e11Z4eZIk3RyoucZMbgMBnvjFdmtwNuWhx+NfP 3xk0q10X9pD4RahpCrB4g1K4ubW9WAYNxZhF3GTHXaC2M+nfbx6F+0VNe6X8CfGs+ml1u002QB0O GVDgOQexCFvyqOXVW6jvucL8ZPjf8HfGHhfxB4S1PxBp+oXotZnhgzK0XnojGPEyjy9wYDA3dcV1 H7LEkFv+zt4NmnZYo47J2eR2AVQJHJJJ6AVV8J+FvD1n+yrDBpVtby6fN4Ya4J8sYlkNsWaRhjli xJOeQa8b8SXVzZ/sC+GBDNNbWdw1vb380JIZLZrlg/TsTtBHfOO9acqa5V3Ju07s+g9D/aO+GXiT xL/YGmeLNPudTZtqJ8yxyN6JIyhHPsrGvSFKyKGXBUjIK9DXIap8PvA154Ag0LUdL05vCkEUflwz bVgRRjYwbjB6fMDk56811mm2Nrpen21pZxeXaQRLFDGvIVFACgH6AVk7dC9epyfj74yeCvhSsJ8V +IbfSJJhujgZXlmdc43CONWbGe+MVP4F+MPgn4nXUlr4Z8Q22sXEcAuZIoQ4ZIycAsGAwc9jz7V5 P8E4LTWv2kvjHqOsKtx4gsLm1tbJZly1vZ7G2+XnoGwpOPY8bubPgOxt7X9sz4iLbwx24k0CzkYR oF3MTHljjqT61pyrYm7PQfHvx8+HPwt1NdP8SeKLXT79gCbVEknlTIyC6xKxQEf3sVtw/FDwlN4K l8Xw6/Zz+GoV3SajC/mRpyAQcAkEEgEYyM149+xVp9pqngzxL4hv40l8Y6hrd0mtSyfNNG6sMQkn kKAcgdPmNR/CTQ9Osf2lvjF4a0mCNvCktpaT3lgg/cRXciDcqr0G4Fycdxj+EAPlWq7Bd6Html/E zwvrHgmbxfZaxDceGoY5JZNQVW2KsZIc4xngg9u1XPBHjzQPiNov9r+HNTi1XTvNaH7RCGC71xkf MAeMivkyHxZefDf9nr4ifDCNml8R6TrJ8NaXG0gEk8N85aB/UExvMR/uDkdvrH4e+D7T4f8AgnRP Dtmq+TptpFbFh/y0ZVAZz7kgn8amUUhp3Oi3UUhb2oqCjOb61G2N34U/8KY36/WpGRuu7gVRu4wI ye1aD9DVK6jaSMoBQMwiw80E8n2rQhX5cDNVxprLIpLcd8jpWhDbkDgZHTrQIFGexAqWPOcdqctv 68VMsW2gBopdmRgVIF7Yo20AReWd3Wl2EYFSFaKAG7cUU6m+9MQdKDQfejikAn1oopfpQA32xR60 owep2/hSZ7frQAm3pRS803PvTAXb70mzv1pNw55pA3vQAu0UbKN3zUu6gBCtG2gtmigBNtG3FOpP p1oAaU70cfWlNHPpQAm2jaeaXHvzRSATGaFWl/SjNMBu0568Uu09jR5g/Gk85F70ALhvXNO59Kia 5RV6jrSfbEGM0ATBumRQ201UbUEX+lNXVFbgCgC35Y4wSKd5fox/Oqi3Tt34p6ks3JH50hk5DL3z Sbm79KYe3NO7UDHeYRzSF2pACe3FLjn1pAJk0xmOKf8AhimldxwKBjGzilVWbAGKcLdvYfWp0hKn +GgREsTt/CKmSEjg8YqVR8vSnbd1UK5H5eOhp20/Snr9OaXjHPNAjl/iB8OtC+J3hubQvENmLywk YSLtYo8Ug+66MOVYc8+5ByCRXAaX+y/oy6vpl54h8T+J/G0GluJbGw8QagJ7eFx91ygUb2HTJ49R Xs+M9qeo61Sk1ohWRxnxM+FPh/4saPBY65DMslrKLizvrOTyrm0lHR4pB0PA9RwOOBXPeC/2f9J8 NeKLXxJq2ua94x12zjaKyu/EF2JhaKww3lKFABI6scmvVeKBRzNaBZbnmPxG+BOl+PvF2n+KINc1 vwx4hs7ZrP8AtDQ7hYnlgJJ2PuVs4JOPr3wML44+AeheOotEuJ9R1jTvEOjQLBZ+JNPu/L1AKBg7 5MYfdyTkfxNjGTXpu2l2nGKOZhZHmXw9+Auj+A/Elx4ln1PVfFHieaPyTrGvXHnzRxf8848ABF+g zyRnBxWr4B+EWjfDzTNe0+ye71C01q8mvLuPU5/PBaQYZBwPlx65J7k13G38TTlpXYWR4ZD+yToN rb3el2fivxdYeFbkPu8OW2qlbRdwIIGVLbcnO3dyeuRxXU+AvgD4f8D+AtR8GyXureJvD98ChtNe uVnWFCPuRBVUIufm4HDcjmvS/ehfU1XM2HKjw+0/ZK8OrFa6dqHiXxVrHhW0kWS38M3+pb7FNpyq FQoZkU9FJ49673XPhTo3iDx94a8Wzy30OoaBHJFaW9tPst2Vxg70xzgHsR2zkACu3pNvtScmFkfN /wAW1+FOpfFa5kv/AB1f/Dnx5p8Ecc+oWN0bL7TAy7lVmdTHKAOOOcgA9AKxP2WdJsr/AON3xF8S eHbzUNZ8MpbW+mx65qc7zS6lcAK0sm9sZ5U9AFwVxgECvpzVPD+l68ipqmmWeoov3Vu4ElA+m4Gr lnZ2+n28dvawR28EYwkUKBFUewHAqubSwuXW55N4n/Zt0fVvFOoeItB8ReIvA+qalzqLeHb4QR3Z x990Kkb+p3DHJJ6nNdb8MPhX4f8AhJos+naDDMzXMpuLy9vJTLc3cp6ySuep69MDk4HNdngNnODT fKQ9OtTzNqw7Lc8z179nvwx4k+Lmm/ES6l1BdXsfKYWccqC0mkiDiOWRChYuofghhjaPfPp/Jpoh xnB/WlEZ45/WldsB6Ej6UUCNscNiikMobew6UhQ1IeKb+PNAEWzORmmtDu//AFVPg/Sm4I+tIZB9 nA7YpRCBUpz6Um0jvQIYEo20/wBaT3oASil/nRigBpH503+VPNNamAnak/ClyKTNIAx+NJ2pGYUn mehoAWjNM3d+1N8ztQA/PpRmo/MHSkaQZxnn60AS7qbuHrUZkFMeTbyeKAJyw6UzzFqs04pjNyKA LfnJSfaEFZ08mzPNU2ujuxjNA7G210i1G+oIvQmsNrg+rfSmNI23rQBuf2mvbrSfbzz3rDV3ZhjJ +lXFZtn96gC/9uc9KVrqXINUY5MHkc+tT7iVwM0ATNdOvU0z7c2eDUDs3Qnio9pPTvQBaN4x+tJ5 7evFRxxsf4ak+zs3O0igCJpX/vHNRSTMO5/Grq2Zb7xxS/YEJ5JJoAyJJnDHk1E0sjYyWNb32WMY +Xn6UjQIcYG3tQBz+2Rm43VctwwPQ59xWn9nT6/zpy26tk5oAWFFZeevcVOsKg/dJ9OaiWIL0PP1 pct/fJxQMtbVxjGaZgA8EflUau1DHsaBk2cc8Cm5yf5UwD0qVY+lAgwW705Yz64NPC/jS8jNAhAG Wnq5HemeY3BxUbM55wKALIY+uRS59apMz+mPoakR/UkUCLdKvTkVGrDHXNP+9TAfSr9aYMdqXIHr QA/jil3D15ppfbwQT+FQtPzjYfyoAsbh9aWqZuDjO0003RzjBoGXsr16UqketZpuzwMc0q3W3OcA /WgRobwvek8zHO7NUftQOCOfxo+0Z6UAX/tAXOcfnULXwHY1U8wk9M0mFbtSGXVvx3XA+tO+1L1J I/Cs8KE5OQPrT94bpnNA7F9bhWHBqVH3dP5VnLIV7YqaOZj9KBGilSD0qoshx1pwmPrTEWu+KKr+ caKYH//Z