class: center, middle, inverse, title-slide # A Data-Driven Approach At Characterizing Heterogeneity In Neuropathy Assessments ### Luke Johnston --- layout: true <div class="footer"> <img src="../../common/au_logo_black.png" alt="Aarhus University", width="160"> https://gitlab.com/lwjohnst/neuropathy.clusters </div> --- ## PURPOSE: Get feedback, comments on two issues: - Analysis implementation - Extracting key results --- class: middle, center # BACKGROUND --- ## Diabetic neuropathy: Major complication without strong definition -- - Many assessments: - DN4, UENS, TCSS, mTCSS, Monofilament-based, MNSI, Heart rate variability, Sural nerve conduction -- - No consensus on assessing neuropathy --- ## Study objectives - Are there specific groups of people who share similar assessment responses? -- - Are some assessment tools better at capturing features of neuropathy? -- - Based on above, could we simplify what assessment items to give and use the responses? --- ## Study and measurements - Cohort: ~13 year followup of ADDITION-DK (n=526) - Measures: 8 different neuropathy assessment tools (105 total items) --- ## Rationale on statistical analysis <table class="table table-striped table-condensed" style="margin-left: auto; margin-right: auto;"> <thead> <tr> <th style="text-align:right;"> ID </th> <th style="text-align:left;"> A1 </th> <th style="text-align:left;"> A2 </th> <th style="text-align:left;"> A3 </th> <th style="text-align:left;"> A4 </th> <th style="text-align:left;"> A5 </th> <th style="text-align:left;"> A6 </th> </tr> </thead> <tbody> <tr> <td style="text-align:right;font-weight: bold;"> 1 </td> <td style="text-align:left;"> absent </td> <td style="text-align:left;"> present </td> <td style="text-align:left;"> present </td> <td style="text-align:left;"> present </td> <td style="text-align:left;"> present </td> <td style="text-align:left;"> absent </td> </tr> <tr> <td style="text-align:right;font-weight: bold;"> 2 </td> <td style="text-align:left;"> absent </td> <td style="text-align:left;"> absent </td> <td style="text-align:left;"> absent </td> <td style="text-align:left;"> absent </td> <td style="text-align:left;"> present </td> <td style="text-align:left;"> present </td> </tr> <tr> <td style="text-align:right;font-weight: bold;"> 3 </td> <td style="text-align:left;"> absent </td> <td style="text-align:left;"> present </td> <td style="text-align:left;"> absent </td> <td style="text-align:left;"> absent </td> <td style="text-align:left;"> present </td> <td style="text-align:left;"> present </td> </tr> <tr> <td style="text-align:right;font-weight: bold;"> 4 </td> <td style="text-align:left;"> present </td> <td style="text-align:left;"> absent </td> <td style="text-align:left;"> present </td> <td style="text-align:left;"> absent </td> <td style="text-align:left;"> absent </td> <td style="text-align:left;"> absent </td> </tr> <tr> <td style="text-align:right;font-weight: bold;"> 5 </td> <td style="text-align:left;"> absent </td> <td style="text-align:left;"> present </td> <td style="text-align:left;"> present </td> <td style="text-align:left;"> absent </td> <td style="text-align:left;"> absent </td> <td style="text-align:left;"> absent </td> </tr> <tr> <td style="text-align:right;font-weight: bold;"> 6 </td> <td style="text-align:left;"> absent </td> <td style="text-align:left;"> absent </td> <td style="text-align:left;"> absent </td> <td style="text-align:left;"> absent </td> <td style="text-align:left;"> absent </td> <td style="text-align:left;"> present </td> </tr> <tr> <td style="text-align:right;font-weight: bold;"> 7 </td> <td style="text-align:left;"> present </td> <td style="text-align:left;"> present </td> <td style="text-align:left;"> absent </td> <td style="text-align:left;"> present </td> <td style="text-align:left;"> present </td> <td style="text-align:left;"> present </td> </tr> <tr> <td style="text-align:right;font-weight: bold;"> 8 </td> <td style="text-align:left;"> absent </td> <td style="text-align:left;"> absent </td> <td style="text-align:left;"> present </td> <td style="text-align:left;"> present </td> <td style="text-align:left;"> absent </td> <td style="text-align:left;"> absent </td> </tr> </tbody> </table> --- ## Groups by row: Hierarchical cluster (HCA) <table class="table table-striped table-condensed" style="margin-left: auto; margin-right: auto;"> <thead> <tr> <th style="text-align:right;"> ID </th> <th style="text-align:left;"> A1 </th> <th style="text-align:left;"> A2 </th> <th style="text-align:left;"> A3 </th> <th style="text-align:left;"> A4 </th> <th style="text-align:left;"> A5 </th> <th style="text-align:left;"> A6 </th> </tr> </thead> <tbody> <tr> <td style="text-align:right;font-weight: bold;background-color: lightblue !important;"> 1 </td> <td style="text-align:left;background-color: lightblue !important;"> absent </td> <td style="text-align:left;background-color: lightblue !important;"> present </td> <td style="text-align:left;background-color: lightblue !important;"> present </td> <td style="text-align:left;background-color: lightblue !important;"> present </td> <td style="text-align:left;background-color: lightblue !important;"> present </td> <td style="text-align:left;background-color: lightblue !important;"> absent </td> </tr> <tr> <td style="text-align:right;font-weight: bold;background-color: lightblue !important;"> 2 </td> <td style="text-align:left;background-color: lightblue !important;"> absent </td> <td style="text-align:left;background-color: lightblue !important;"> absent </td> <td style="text-align:left;background-color: lightblue !important;"> absent </td> <td style="text-align:left;background-color: lightblue !important;"> absent </td> <td style="text-align:left;background-color: lightblue !important;"> present </td> <td style="text-align:left;background-color: lightblue !important;"> present </td> </tr> <tr> <td style="text-align:right;font-weight: bold;background-color: lightblue !important;"> 3 </td> <td style="text-align:left;background-color: lightblue !important;"> absent </td> <td style="text-align:left;background-color: lightblue !important;"> present </td> <td style="text-align:left;background-color: lightblue !important;"> absent </td> <td style="text-align:left;background-color: lightblue !important;"> absent </td> <td style="text-align:left;background-color: lightblue !important;"> present </td> <td style="text-align:left;background-color: lightblue !important;"> present </td> </tr> <tr> <td style="text-align:right;font-weight: bold;background-color: lightblue !important;"> 4 </td> <td style="text-align:left;background-color: lightblue !important;"> present </td> <td style="text-align:left;background-color: lightblue !important;"> absent </td> <td style="text-align:left;background-color: lightblue !important;"> present </td> <td style="text-align:left;background-color: lightblue !important;"> absent </td> <td style="text-align:left;background-color: lightblue !important;"> absent </td> <td style="text-align:left;background-color: lightblue !important;"> absent </td> </tr> <tr> <td style="text-align:right;font-weight: bold;background-color: lightblue !important;"> 5 </td> <td style="text-align:left;background-color: lightblue !important;"> absent </td> <td style="text-align:left;background-color: lightblue !important;"> present </td> <td style="text-align:left;background-color: lightblue !important;"> present </td> <td style="text-align:left;background-color: lightblue !important;"> absent </td> <td style="text-align:left;background-color: lightblue !important;"> absent </td> <td style="text-align:left;background-color: lightblue !important;"> absent </td> </tr> <tr> <td style="text-align:right;font-weight: bold;background-color: lightblue !important;"> 6 </td> <td style="text-align:left;background-color: lightblue !important;"> absent </td> <td style="text-align:left;background-color: lightblue !important;"> absent </td> <td style="text-align:left;background-color: lightblue !important;"> absent </td> <td style="text-align:left;background-color: lightblue !important;"> absent </td> <td style="text-align:left;background-color: lightblue !important;"> absent </td> <td style="text-align:left;background-color: lightblue !important;"> present </td> </tr> <tr> <td style="text-align:right;font-weight: bold;background-color: lightgreen !important;"> 7 </td> <td style="text-align:left;background-color: lightgreen !important;"> present </td> <td style="text-align:left;background-color: lightgreen !important;"> present </td> <td style="text-align:left;background-color: lightgreen !important;"> absent </td> <td style="text-align:left;background-color: lightgreen !important;"> present </td> <td style="text-align:left;background-color: lightgreen !important;"> present </td> <td style="text-align:left;background-color: lightgreen !important;"> present </td> </tr> <tr> <td style="text-align:right;font-weight: bold;background-color: lightgreen !important;"> 8 </td> <td style="text-align:left;background-color: lightgreen !important;"> absent </td> <td style="text-align:left;background-color: lightgreen !important;"> absent </td> <td style="text-align:left;background-color: lightgreen !important;"> present </td> <td style="text-align:left;background-color: lightgreen !important;"> present </td> <td style="text-align:left;background-color: lightgreen !important;"> absent </td> <td style="text-align:left;background-color: lightgreen !important;"> absent </td> </tr> </tbody> </table> --- ## "Groups" by variable: Factor analysis <table class="table table-striped table-condensed" style="margin-left: auto; margin-right: auto;"> <thead> <tr> <th style="text-align:right;"> ID </th> <th style="text-align:left;"> A1 </th> <th style="text-align:left;"> A2 </th> <th style="text-align:left;"> A3 </th> <th style="text-align:left;"> A4 </th> <th style="text-align:left;"> A5 </th> <th style="text-align:left;"> A6 </th> </tr> </thead> <tbody> <tr> <td style="text-align:right;font-weight: bold;"> 1 </td> <td style="text-align:left;background-color: lightblue !important;"> absent </td> <td style="text-align:left;background-color: lightblue !important;"> present </td> <td style="text-align:left;background-color: lightgreen !important;"> present </td> <td style="text-align:left;background-color: lightgreen !important;"> present </td> <td style="text-align:left;background-color: lightgreen !important;"> present </td> <td style="text-align:left;background-color: lightgreen !important;"> absent </td> </tr> <tr> <td style="text-align:right;font-weight: bold;"> 2 </td> <td style="text-align:left;background-color: lightblue !important;"> absent </td> <td style="text-align:left;background-color: lightblue !important;"> absent </td> <td style="text-align:left;background-color: lightgreen !important;"> absent </td> <td style="text-align:left;background-color: lightgreen !important;"> absent </td> <td style="text-align:left;background-color: lightgreen !important;"> present </td> <td style="text-align:left;background-color: lightgreen !important;"> present </td> </tr> <tr> <td style="text-align:right;font-weight: bold;"> 3 </td> <td style="text-align:left;background-color: lightblue !important;"> absent </td> <td style="text-align:left;background-color: lightblue !important;"> present </td> <td style="text-align:left;background-color: lightgreen !important;"> absent </td> <td style="text-align:left;background-color: lightgreen !important;"> absent </td> <td style="text-align:left;background-color: lightgreen !important;"> present </td> <td style="text-align:left;background-color: lightgreen !important;"> present </td> </tr> <tr> <td style="text-align:right;font-weight: bold;"> 4 </td> <td style="text-align:left;background-color: lightblue !important;"> present </td> <td style="text-align:left;background-color: lightblue !important;"> absent </td> <td style="text-align:left;background-color: lightgreen !important;"> present </td> <td style="text-align:left;background-color: lightgreen !important;"> absent </td> <td style="text-align:left;background-color: lightgreen !important;"> absent </td> <td style="text-align:left;background-color: lightgreen !important;"> absent </td> </tr> <tr> <td style="text-align:right;font-weight: bold;"> 5 </td> <td style="text-align:left;background-color: lightblue !important;"> absent </td> <td style="text-align:left;background-color: lightblue !important;"> present </td> <td style="text-align:left;background-color: lightgreen !important;"> present </td> <td style="text-align:left;background-color: lightgreen !important;"> absent </td> <td style="text-align:left;background-color: lightgreen !important;"> absent </td> <td style="text-align:left;background-color: lightgreen !important;"> absent </td> </tr> <tr> <td style="text-align:right;font-weight: bold;"> 6 </td> <td style="text-align:left;background-color: lightblue !important;"> absent </td> <td style="text-align:left;background-color: lightblue !important;"> absent </td> <td style="text-align:left;background-color: lightgreen !important;"> absent </td> <td style="text-align:left;background-color: lightgreen !important;"> absent </td> <td style="text-align:left;background-color: lightgreen !important;"> absent </td> <td style="text-align:left;background-color: lightgreen !important;"> present </td> </tr> <tr> <td style="text-align:right;font-weight: bold;"> 7 </td> <td style="text-align:left;background-color: lightblue !important;"> present </td> <td style="text-align:left;background-color: lightblue !important;"> present </td> <td style="text-align:left;background-color: lightgreen !important;"> absent </td> <td style="text-align:left;background-color: lightgreen !important;"> present </td> <td style="text-align:left;background-color: lightgreen !important;"> present </td> <td style="text-align:left;background-color: lightgreen !important;"> present </td> </tr> <tr> <td style="text-align:right;font-weight: bold;"> 8 </td> <td style="text-align:left;background-color: lightblue !important;"> absent </td> <td style="text-align:left;background-color: lightblue !important;"> absent </td> <td style="text-align:left;background-color: lightgreen !important;"> present </td> <td style="text-align:left;background-color: lightgreen !important;"> present </td> <td style="text-align:left;background-color: lightgreen !important;"> absent </td> <td style="text-align:left;background-color: lightgreen !important;"> absent </td> </tr> </tbody> </table> --- class: middle, center # FIRST ISSUE: ### Both methods data-specific, with fixed groups. ### What is *likelihood* individual will be in group? --- class: middle, center # My idea for implementation: ### Run methods on resampled sets (4-fold CV, x 25) --- <table class="table table-striped table-condensed" style="margin-left: auto; margin-right: auto;"> <thead> <tr> <th style="text-align:right;"> ID </th> <th style="text-align:left;"> A1 </th> <th style="text-align:left;"> A2 </th> <th style="text-align:left;"> A3 </th> <th style="text-align:left;"> A4 </th> <th style="text-align:left;"> A5 </th> <th style="text-align:left;"> A6 </th> </tr> </thead> <tbody> <tr> <td style="text-align:right;font-weight: bold;background-color: lightblue !important;"> 1 </td> <td style="text-align:left;background-color: lightblue !important;"> absent </td> <td style="text-align:left;background-color: lightblue !important;"> present </td> <td style="text-align:left;background-color: lightblue !important;"> present </td> <td style="text-align:left;background-color: lightblue !important;"> present </td> <td style="text-align:left;background-color: lightblue !important;"> present </td> <td style="text-align:left;background-color: lightblue !important;"> absent </td> </tr> <tr> <td style="text-align:right;font-weight: bold;background-color: lightblue !important;"> 3 </td> <td style="text-align:left;background-color: lightblue !important;"> absent </td> <td style="text-align:left;background-color: lightblue !important;"> present </td> <td style="text-align:left;background-color: lightblue !important;"> absent </td> <td style="text-align:left;background-color: lightblue !important;"> absent </td> <td style="text-align:left;background-color: lightblue !important;"> present </td> <td style="text-align:left;background-color: lightblue !important;"> present </td> </tr> <tr> <td style="text-align:right;font-weight: bold;background-color: lightblue !important;"> 6 </td> <td style="text-align:left;background-color: lightblue !important;"> absent </td> <td style="text-align:left;background-color: lightblue !important;"> absent </td> <td style="text-align:left;background-color: lightblue !important;"> absent </td> <td style="text-align:left;background-color: lightblue !important;"> absent </td> <td style="text-align:left;background-color: lightblue !important;"> absent </td> <td style="text-align:left;background-color: lightblue !important;"> present </td> </tr> <tr> <td style="text-align:right;font-weight: bold;background-color: lightgreen !important;"> 7 </td> <td style="text-align:left;background-color: lightgreen !important;"> present </td> <td style="text-align:left;background-color: lightgreen !important;"> present </td> <td style="text-align:left;background-color: lightgreen !important;"> absent </td> <td style="text-align:left;background-color: lightgreen !important;"> present </td> <td style="text-align:left;background-color: lightgreen !important;"> present </td> <td style="text-align:left;background-color: lightgreen !important;"> present </td> </tr> </tbody> </table> -- &nbsp; <table class="table table-striped table-condensed" style="margin-left: auto; margin-right: auto;"> <thead> <tr> <th style="text-align:right;"> ID </th> <th style="text-align:left;"> A1 </th> <th style="text-align:left;"> A2 </th> <th style="text-align:left;"> A3 </th> <th style="text-align:left;"> A4 </th> <th style="text-align:left;"> A5 </th> <th style="text-align:left;"> A6 </th> </tr> </thead> <tbody> <tr> <td style="text-align:right;font-weight: bold;background-color: lightblue !important;"> 2 </td> <td style="text-align:left;background-color: lightblue !important;"> absent </td> <td style="text-align:left;background-color: lightblue !important;"> absent </td> <td style="text-align:left;background-color: lightblue !important;"> absent </td> <td style="text-align:left;background-color: lightblue !important;"> absent </td> <td style="text-align:left;background-color: lightblue !important;"> present </td> <td style="text-align:left;background-color: lightblue !important;"> present </td> </tr> <tr> <td style="text-align:right;font-weight: bold;background-color: lightblue !important;"> 5 </td> <td style="text-align:left;background-color: lightblue !important;"> absent </td> <td style="text-align:left;background-color: lightblue !important;"> present </td> <td style="text-align:left;background-color: lightblue !important;"> present </td> <td style="text-align:left;background-color: lightblue !important;"> absent </td> <td style="text-align:left;background-color: lightblue !important;"> absent </td> <td style="text-align:left;background-color: lightblue !important;"> absent </td> </tr> <tr> <td style="text-align:right;font-weight: bold;background-color: lightgreen !important;"> 7 </td> <td style="text-align:left;background-color: lightgreen !important;"> present </td> <td style="text-align:left;background-color: lightgreen !important;"> present </td> <td style="text-align:left;background-color: lightgreen !important;"> absent </td> <td style="text-align:left;background-color: lightgreen !important;"> present </td> <td style="text-align:left;background-color: lightgreen !important;"> present </td> <td style="text-align:left;background-color: lightgreen !important;"> present </td> </tr> <tr> <td style="text-align:right;font-weight: bold;background-color: lightgreen !important;"> 8 </td> <td style="text-align:left;background-color: lightgreen !important;"> absent </td> <td style="text-align:left;background-color: lightgreen !important;"> absent </td> <td style="text-align:left;background-color: lightgreen !important;"> present </td> <td style="text-align:left;background-color: lightgreen !important;"> present </td> <td style="text-align:left;background-color: lightgreen !important;"> absent </td> <td style="text-align:left;background-color: lightgreen !important;"> absent </td> </tr> </tbody> </table> --- ## HCA results: Likelihood of group membership <img 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fvaS5AkSZ/+9F0Y45deejkajUWj8UwmGwoFS0pK0ukMx3G6Tm/rGYTM0zoeMMdxdrvNZrNls7loNI4xc0bEgTHGGGHMaJrKshzHYZZlDUPL5/MulzMYLF2+fClCKJVKWSxSVVVVUZGPYZi9e/flcsQ0kSAIuq6Pj2wmxAwEAggN0fAmkUiMZ0EwDMOyDMtyhBh0VjtB4BmG1TSNlpZCCLEsJ4p8UVExxkjXjXA4TAhhGDEUCqmqPjYWyWSyuVzeNE2fz0uI+ZWvfPHaa6+56O/GxeZrCPkaQpPdCnBRSZKkqprd7kDvZ7xIkqTruqbppmkghFmWZVnOMAxFKWiaqqoqIURVNY7jdJ3kclmLxZpMpkRRHJ9uUtf1eDxeXFycTCZHR0d0XUfIpEOJMpnM/v0Hjx8/YZpEVdWioiJB4NF7tZtUQeDz+TzHcQjhRCKJkOl0ukRRNE2iaUZ3d3cul8tms4lEMpfLYszouq6qGh0WlclkamtraHciLQxFnyDQ8VfZbFYURa/XEwiU0Mm2W1uPGwbBGLtcrmw2p2k6x7E8b+F5juf5TCY7f/78Z599LhgsXb/+tkl7ewCYTAQhZKIPPv7ECCF01rqLAPxPXBXhRKFQiEajNKMaIeRyuX7yk5/8/ve/f/nllwkhjY2NX/ziF4uKij7J2ktTKBT66lf/t6oqW7du7+vrFQR7Mpncv/+AaRKGYURRyGZzDMMQQlMUTDpVttVqLS8v6+rqzmQyPp/3/bQEzLLseFcGwzC0GqOua6IoMAxDCGu1Svm8PHPmzFOnTj3++BOjo+GBgQFdNxobp5aU+Ovr69ra2lVVxZix2Sx2u13TDEmSCgU5Fos1NNTzPE9rzjAMy/MczYCXZbmsLOTz+ViW7enpmTlzhtVqzWSyQ0NDPT3diURSkiRRlLxerygKIyMjpmmyLGu3O0RRDAQCRUXeZDKZSCRN0/zc5z67evWq+fPnQZIWuCJNnTqloaG+o6PTYpEMw0gmkyyLU6k0xoxpokJB0TSNxgkMw5rmexiwPVEAACAASURBVP2NhBDTJLFYzDD0np5eOggKY2y1Wgghvb19hJh9fX20IlwiEec4jhAjkUhomu50OhBCyWTaNMnx460ulxMhpOtGMpnAmLFYJI5jZVlRVWK321VVSaVSoihqmmq327q7e/L5PMaY5wUaM2iaRsco6rre2dmJEE3KYukkM7Rrgra5UChkszlZlkVRTCaTuVyePhahA8fpPlVVS6eNWCzu9/t7e3ucTndr64m1a2/meX4S3yMAJodYhP1LzEIEsf7TF2MthSwBJLgnq13ginelhRMzZ8588cUXz1i4evXq1atXn77E7XZ/+9vf/qidnH3tpWnHjp2bNr1ZVVU1f/784eFhv9+fz+e7u3sURREEnmEYmmzAMAxCJs1h0HV9dDQsy7IkSclkSpYLCBGGYSVJHB+PRJMQeJ4TBNF4f34DWS643eLw8PBvf/v7bDbrcNgVRYlGY+l0ZsqU+tLSUobBw8Mjg4NDhAguF+/xeO+6684tW7YePXosHI4YBhkdHbHZrAghh8OZzWb9fj/HscPDIzzP33bbuvnz5/X09NBK+cXFvmQyGYvFM5msLCvZbBZjRlUV2qGh69roaLhQKAQCAafTSSfw+vSn7546dcokvhcAXFClpaUzZ86Ix+PDw8MYMwjhdDpLexMRQrqu0ZGBpokI0RmGM02Dht+0x08QBKfTyXEsz/Msy3Z2drnd7sHBoXxeVpSCqiqlpQGWZUdGRkyTsCxLCJ3yBRGiW63WbDabSqXo+EmMGZvNxvMcrSLFMDiVSmKMGYbRNM0wSDyeNAxDFAVV1Wg3I00eVVUVY+z1erPZrK4bpkkIMRmGMU1SKOi0yhzGiGE4mmvhdDpjsbjFYikUZI7j6SHy+ZyqKqZpchwriqJhGCMj4Xy+MDw8kkqlLvFnQABcEFIAWUpR9B3E2xH7/pA/NWbmh5mKOzADMTa4UK60cOLqpKrq/v0HQqFgZWWFxSIRQgYGBiwWi8PhUFUtn8+xLIsQ5jhEiMlxPELIarUkkynDMOx2e1FREe3HSKVSLMvZbDaMGY5jaWojrfJutVoVRVFV1W63u1zOaDTW19fvdDpqa6tZliOEWCzWwcHB1tYT6XQ6FAoFAoEbb1x5zTWLQqFgRUWFy+WUZdnj8bAs29fXpygFn8+XyWSy2SwhpFDIi6JEJ6u6/fb17e3t27Zt1zSd45i2tk5FUUpK/Iqi8Twfj8cMQ/N43F6vjw6i4Hk+Hk9omi5JUjBYqijq+PgNAK5IkiQtXrxo//4D5eXlsizv3buPENNqtei6zvO8qqocxxoGYRhkmpgQGkswNA+B53lCiKoq6bQyc2ZzKFS2ZcuWysoKlmWnTm3IZDJjY9Genl6bzcowTD5fkCRJEDhN0w1DLykpCYWCnZ2dPC9gzFRVVTgcjlwuJwhCKpXGGCuKKkmCquoIEcMwWJZNJpOGQex2Kx1ySeutGYZBiGG12oqKfCzLpNMZXTfoM4tCoYCQYZoEIUznrbNaLdlsNpVK0/rUhmFYLFYaRSCECCEcxxkG0XXD5/O63e6+vv6uri7omQRXJ4wxKr8N6Vk09BoSXAgLppFHepap+jQuvX6yWweuZBBOXAkikYiu6z5fEULI7/dbLJbi4uJMJpPL5UzTLCnxDw0NsiyHEDIMg+YzyLJiGIbb7WYYprS0hOP4TCbT1aVqmk4IkeU8y7IzZjQbhjE0NMJxvCzLbreb4ziv1yuKfDgcYVnW6XTRWCKRSGia5nDYDYOMjIwsXLjw3nvvWbBg/nhhpUwmwzCM2+0uLQ1omhaNRn0+rygKGKNEIhmNxurr60tLS6dNm1ZfX+f3F2/ZsvXAgYP79r1LC7+Wl5fPmTNHEPj9+w8qSiGdzlgsFlEUHQ67LBdYluU4rr6+LhDwd3f30pEYAFzBFi9e9MILL2/dujWRSGazadqBQOe9IcRQVdpBwTAMliTRMIgkSdlsBiFGEARVVTVNFwQhmUwlkymM8ehoOJVKI4QIIVarJZ+XXS6X1+ttb+8wTcIwnKIoHMdGozGMGUEQZFnx+Yo6O7t0XU8mE+Xl5VOmTOnt7YlExmRZIYTQZxmSJKbT6Ww2J0kWXdcNg4iiSOewYxhWUZSenl46Dxct4kSIqWkaxphmfCGEBYEvLi5iWS6RiL/fQYoVReF5nqaBmSYixDBN5PV63W4XQohhMMb4Kp8qGFzNsOjF9V82vS0oN2BqaSx4saMGe1sQhhgbXEAQTlwJCCFbt25raZlJ/+twOKZNa0QI5XI5hmEWLlzwz//8K4fDQQtUY4wFQRgbC9tsNkHgy8rKM5ms1+u1221FRUVjY1Gr1Wq12gKBQGlpoLe3z263iSJfVlZNnyxqmtbfP1AoFCRJymTSoijE44loNCqKIsfxhUKW49gDBw6sXHnD6UVaHQ6Hz+c7fPhIaWmJKAq0mKPdbtc0LRgsbWqa7nS6Ojs76+pqdV1/4oknDx8+UlZWls/Lo6MjNpstk8lGIpHKyspYLBYKBVVVZVkmk8mUlgYYhsnn85HIWH19XW9v3y23rC0rK5uMNwGAi0SW5SeffHpoaLCsrMw0jVwuyzDvZRoYhkEIkSSJYVia71RU5Eul0jzP53JZjBEtb0A7K8LhSCaTZVnGajUZholGo4SYpkk4jk+l0uXltOITslotTqcDY6zreiQypusaz/OiKMyZMzsejw8ODhYXFxuGwXEcxohhGJfLabXSmtEmz/MMw9jtNp/P29PTS+ecUVWVdlbQ2WzoROy0si1CiGUZmoqtqkpxcZGuG3SoFe1i5XneNEmhoAgCTeUiGDM8z/l8PkLMZDJRUuIfG4vKMoQT4CrGWugUE5doPUpwJYJw4kpQVFS0YsXynp5el+u/JVolk6lly5beeecdp061vfvufotFomUfZVkuLQ0mk6m6ujq/379v37sIIbvd7vP5UqlULBZ3u13R6FhnZyfP84ZhyHKhp6e3uLhI07RkMplOZ3ieI4REo7F8Pp/JZD0eNy0mizGWJEtlZdWpU20dHZ319XXjjVm+fFksFjtx4oTH4ykvL08mEwjhdDo9ffr00tJgKpVKJlNTpjQcPHjor3/dOHPmDLfbHY1G8/mcz+dTFOXEiRN0ZgzDMDBmAgG/0+ns6+t3OByGYfh83hMnTl577TU337wGxjmAK9s77+x98cWX6upq2ts7BUGik0DTgUCCINBsZkEQstmcIIg2my0cjshyASGs6wYtp0YnpqCDjhAyVVVRFJoMTehQqHA4HI1GaaLFeE4zyzKEGHRhOp2mzwtKSkqSydR9993T1dXz7LPPpVJJjBlVVREyNU13Op2Kog4Pj9hsVlrQmcYAtCAsrSJNE7roIQghqkoQ0hBCFotVlvPZbIbGKoWCzPO8ohQQwoQYhYJMMyisVpuiFBKJeDqdqqqqcjgcs2e30NxxAAAAFweEE1cCq9U6deqU7dt3uN0ul8tFF2azmd7e3iVLrmlsbFyxYnkkMubxuGVZ5jiOPmvcsmUbx3HTpk21WKSBgcHu7h7TJLpuNDVND4fDJSWBuXPniKLU39/f399PkxwIIaaJnE6HJFny+TxCOJ+XaRolyyJFUS0WS3V1VW1t1e7de+bNm3t6ONHUND2fz/M8v3nzm7FYbHBwsKysrLGx0ev19vT0DA4O3XnnhoULFzzzzLN2u51OXm61WmgpGFEUBUFUFKWurnZ4eEhVVZ+vaMoUn91uT6dTo6PhQKBk/frbVq68sba2ZjLeAQAuns7OLo/HnU5nBwcH/X6/rmvJZIrmEggCnfpNk2U5FCoLBksHBgYxZmU5Z7FIimLSQm0YY4bBLMvSgrCaZjAMq+sGen+OF9MkiqJjjDVNz2TSgiBijAqFgizLHMfncjlZlrPZHEJmNpuNxWLvvrv/9tvXv/baa3Z7GcNgVdUYBguCoCiqpmkcxzEMY7NZZVmm1xCWfa+OEx3szTDs6SlPNKdc01SLxZfJZERRHJ/Ym2EY+kxEUVQ6Y43dbquvr62rq3M47E6ns62tvaioCPKwAQDgYoJw4gpx881rotHYX/+60eVyWSxSoVBIJlO33bZu3bpbMca33npLKpXas+edmppqi8Uiy/LAwOCcObNVVctkMtXV1WVlZbW11W1tHQsWzPd4PAcOHGhubqZ7ZhgmkUjG44mRkdFCQeZ5wWKRaJFHmolBiFkoyKqqyLLscDhCoZAgiLSo/BmNnD9/3vTp0267bd3Y2FhHR2d/fz/tSSgp8d9227pVq1YKgpDPy7SqPUKotLQ0Fosnk0m3281xrKbpFRXlR44cDQRKLBYLxri2tqavr2/u3LkbNnxq/vwzJ+4B4IqUz+cFQaQ50IIg2Gy2ZDJpsVgUpSDLBdMkFovV5/M6HA7au5jP5ywWC8aIDjJkGJZlGYSQrms0tNB1jeOY02euxJgRBJYQUxRFwyAsy3IcizFTKLxXj6G4uJgQwnF8cXGxrhv9/QOBQKC+vv7o0WOVlRWEGJlMNpvNxmJxu91usVhKSvw9PT1utyubzRUKBdo7Qfs9NE2llanxe5Bp0gkujeHhEYZhpk1rnD9/3u7dexRFSaVS+byMEDJN0+v15PN5TdOqq6v9/mJZLpw8eWrRooVr166Z1PcHAACuOhMPJ3bt2nXs2LGenh5VVWtra5ubm5cuXXoeWwbOic1m+/KXvzhjRnNPT08ikXS7XZWVlQsWzKfVUaqqKr/whc+XlpYODQ3RO4YFCxbMnNm8c+fuF198ieM4OnB57dqbb731lqeeetrr9dLdFgqFkZGRRCLhdrtGRkYIMRFCbrcnECjJZrODg0PxeBwhlE5n7HZ7XV19c/P0QCBAX0jnzf1gO6dPn4YQWrZsKSEkmUyqqlpcXDw+QolmV9N/FxUVhUIhXdfb2ztyuRydtbeurpZh2Ndff4PecyxZcs0tt6yFWAJcPRwOhyzn6YzyCCGfz2eaZi6XD4dlu92m6/qiRQu/9KX77HZ7LBZra2t7/vmXZs2aEY8n33rrLYZhOI4jhOi6TggrCLyqavl83jTfm5GGXh8sFgvGTC6XdbtdDoczl8sZhq6qiqZpdA+jo2Ea57Msy7LM0NBwNBr91KfWd3R0dnZ2apquKMr7edKmy+UKBALxeKKysqKzs2t0NMzzHC30ZBgGxgL9yr/fbcLQmS4xZgkhDMOcOHGyo6NT1zWbze71eum8ExaLtb6+rlAoWK3W+vo6OvJq3ry5q1evpDWmAQAAXDQTCSc6OjoefPDBPXv2nLF84cKFjzzySH19/floGDhnPM9fe+01HzUVdHl5+Ze+dJ+qqvQmgP76trS03HjjDaOjo6Zp+v3+xsap70+a/V4GF02BKCsLIWSOjY1xHPZ43LFYlOc5v99vt9u7u3vi8Vh9fcPixYt8Pg/LcoVCIRKJqKr6sZ8EhmHG45ZxU6dOzefzkUjE7/cjhEKh0p6eXkVRCDG9Xi/HMSMjI6IoNTU1CYJoGFp//8D+/QdaWmY5HDBaGlwVpk6d8thjaY/HrSgKrcdaXFzMsnGfz1dc7Ovr658+vVFVVY7jgsHgwYOH0+k0zV7w+bzpdJp+U+hMcLquY4zo7Tu9d6c39PQfHMcZhimKgiAI2Wwml8vTjAtZlkVRcDoduq6l02mEzJKSQCaT+fSn7+7o6PrP//xPjuMDgYCmaSMjwxzHGoYei8UIMRRFsdtt9PkFHVJFCOF5QVFUmhOFMWJZ1jAMnucQwoVCQdd1QgxVVTFGmpZMp9Mul8tqtS5durSurpYOdLz//q8QQjweD316AgAA4CI753Ail8vdc889fX19paWld9xxR2VlJcdx3d3dGzdufOedd+65557NmzfT1EBwCRIEgd6mUzzPNzc3NTc3nb6N2+0+fvx4KBSUZTmZTLrdLp7n4/G4qmqSJGGMRVGSZZnex/j9fkVRTJPoulYoFDRND4fDw8MjX/nKlxsaJhJYNjc33XffF/7whz+lUim323PqVFtvb6/dbmtpaZk2rXHv3n35fF7XCSGkuXk6Qiifz7366mvV1VXr19/2Pzs3AFwe5s2be9dddz755FNut3toaMjtdmuals1mKyoqenv7dN04dqy1tfVkT09PoVAoLQ1arZbOzk7TRLSsgiCIPM9pmub1esbGooWCYpro9K4JQeBpoVU6gqi19cR4nwadY1vX9UKh4HA46PYIYU1TaZnahoY6v9/vcjkJMWW5EI/Hy8pCLpdrYGCgpKQkHk+4XE6r1ZLNZiwWqVBQETJpDIAxZlmG5zldNwghmoYMQ6dPNziOfz9xixBCUqm0z+etra1GCCWTiZqaar/fT9MtAAAATIpzDif+6Z/+qa+v7+abb/7Vr351eiXQBx544Otf//orr7zyy1/+8qGHHjqvjQQX1dy5c1544cWhoWGLRert7QsGSzVNSyZTdrvd5XKl02lRFBKJZElJiWmaqVRq2rTGm2++SZYLW7duu+66JTab7bbb1n3qU7cTQnK5nMPhOKdf+kQi4XK5Zsxo7uzsSqfTyWQyGAxOndpQXV0djca6urppoVg6h53dbrdabaWlgZMnT61bR2h9SQCubDzP33PP5wKBkm3bdhw/fryjo1MQBJfL2d/f73A4brzxOp/PNzg4ePToMZZlRVGoqak+cuSY0+lIJFRaIjYWi0uSSLObaC8fLfr0fg60Qb+yDMPQjgifz4cxJsQYGQlzHMPzfCqV1jSNYVg6N6WmqT6fDyGUTmemTJlSX18nyzLLMk6nY3BwgGEYQRD8/mKHw9Hd3YMxcjpd+Xye9o2k02mWZelMmnTybFpzVtffK/dkmiYtUf3+F9zM5fKjo2GGYcLhyJw5syGWAACAyXXO4cS+ffs4jvv5z39+eiyBEBIE4ec///mmTZv27t17/poHzr9sNnvkyNGRkRHDMIqLi5ubm4qLi+mqfD7f29tHCFmz5qYXXniBlnAJhyOEkOrqKk3T8vk8yzKRyBjHceFwGCHkdntaWlq+9a0HFEX5/Oc/h5ApimIsFnviiScHBwfpBFVTpjTceOMN4yWnzqKnp/fJJ596++0tTqfDarVEImOdnZ2LFi2oqalhGEZRCgghRVHy+XxfX5/b7W5oqKezZKiqms/nPzRbA4Arj8Viue22dbfcsnZgYKCrqzufz+/bt2/z5rdWrFhOr8yjo2GbzVpUVNTd3XPttdcsWDA/HA4nEklaT6msrCwYDEQiY7FY3Ou10nggHI7ous4wDCGGJEkYo1gsXlJSwjA4GAyapinLcjKZorNDWCwWr9fn83kNw4hGYxaL5PG49+8/0NbWPjYWKS0N0CFVDQ0Nuq4PDQ3LcsEwiN9fHI/HZ82a2dBQn8tlVVWXJNFudxiG/thjT8TjCdM0GIYxDEKTs8fRRCk6vR0hJBwO7979js/n/dKX7lu69LpJeQsAAACMO+dwor29va6u7kPHqTscjvr6+ra2tvPRMHBB9Pb2Pf30X15//Q2bzcYwTC6XW7r0uptuWj1v3tzdu/c888xz27Zt4zheEPiWlha73e5wOJPJeF1dXTBYevjw0bGxMb/fjzFjtVoaG6cihEdHR1esWMbzPM/zdFq6w4ePPPvsc0eOHC0pKZEkMZ/Pb9mytbOz6777vnD6OKsPUlX1mWeeffnlVywWSzyeoAuDweCxYydKS0srKysNg2QymUQigTFWVfXAgYPpdLqiooLOgwvDpsHVhmXZqqqqqqoqhNDQ0HBFRfn4U558Pi+KIsuygiDIcr6pqam6umr69OkHDhxcvfrGsrLy4eHhXbt2l5aWyrJMa7I5HI5oNFYoFHK5HM/zqqoWFblDoSAtt4AxZlkWY0aSJJ4XDMPI5XIIofLyMofDEQyWPv30X/fseSeRSAwODmqaXlLib2hoKC4umjGjWRCE9vaOUChUWVlxyy1rV61aSbsyxhFCGhrqf/rTnw0MDBmGbhgGyzKEjFetNU2T8DxPp67TNM3hcM6ePeuBB/6fmTNnQNcEAABMunMOJzweTzQa/ai10Wj0g8m14BKRy+WefvovO3fuGq/4pOv68eOtpmm+887e559/4dixY6IosSxbU1Pd29ubzeauu27J9u07eJ7nOH7atKmqqrS2ntR1raKiXFGUZDJ19913rVx54/ghDMN4/fU3Dh06PH/+XIZ5r1hTKBTcunVbIBD4whc+f5bmtbd3/OEPf6SplrR5spwPh8MYo+HhkYqKipGREdM0RVHAGHs8nrKyUDQapdMAL1myhOOg6jG4epmmefocuON1nzCmq5AoiqIo2GzWRYsWrVx5I01/Gh4eHhoajsfjLpeLTtegKEp/f39j47S+vr5gsNTj8dB+SIQQHfU0Njbm8dgNQ582bXpVVSXHsfv27U+l0n19/ddcsyifzx86dLi/v7+3t8800bRpjZIk8jz/la98+fOf/2wgEPjQEYkMw/yv//XpI0eOdXR0xGKxvr5+l8sZjUZTqfR47VqaHU6vAEVFvhtvvGHWrJkX5dQCAAD4GOd8B9bY2PjGG29s3rz5xhtvPGPV22+/HYlE1qyBmt+XqCNHjr7++hsLFswbf5DPcdzUqVNef30TLcdUW1tLhxOMjo76/X7aB/W5z/2v/v7BHTt2iqKoqtqKFcvtdntNTXVxcXFdXe3ChQvGJ81FCA0NDWUymYqKivFYAiEkCGJZWVlfXx/Ndvio5h08eCifl8ePixCy2+2EoO7u7p6envLy8vb2Dq/XEw6HTRMVFxdjjK1Wa3t7x9y5c1asWHb+zxcAlw+/vziVSpkmwZhBCDmdzr6+PpfLoaqqzfbely4eT+q6XlZWhhCyWCwej+fYsWNlZaHW1hPJZNLlctHCTVVVlbqurV696vjx4x6Pp1BQ8nnZarUghH0+byqVSiaT1dVVgYBf1/Wuri6Hw24YGi294HIJDQ0NDMOeOtV25MjRRCKp69pNN62+++47g8HgWdpvsViqqipHR0fmzZtz/HjrwYOHCXmvzhwhRBRFmj6haZrPV+JyOaEaLAAAXDrOOZy45557Nm3a9I1vfOPBBx+8++67RVFECKmq+vTTT//4xz/GGH/uc5+7AO0EExSLxbq7e9xudygUHBkZsVqtkmQ5fQOMUS6Xi0QioVCIvpssy/p83t7eXpvN1tnZ9cAD37z55jVLl16XTCY9Hk91dVVlZeVHHS6VSu/atXvevLlnLLfZbISQ0dHRurq6D30hQmhgoD+dTldUlJ++sKTEH4vFeF7Yv39/KpVyuZzV1dUY41Qqnc2+N9aiqqoqFAqd+7kB4Moxd+6c48dbT506VV9fzzBMRUVFLBbr7Oysq6srLi7q7u4ZGhoeHByYM2fu8PBwXV2tIAgLFy547rnnHQ7n4sULh4dHBgYGMUapVMbr9Xz5y19cu3bNX//6zNGjx2bMaD527JjdbhdFMZPJEkIcDkdDQ313d8+yZUvr6mq7u7tVVRtvSTAYdLvdgUDJkSNHVq9euXjxopkzZ1it1o/9E+bMmf3SSy97vd4ZM5qDwdDw8PC77747MjJqmsg0zVwux/Ocz+ctKyv71Kdunzt3zoU8nQAAAM7BOYcTS5cuvf/++//1X//1oYce+tu//Vv6wInm9SKE7r///uuug8S4S8KpU6d+9rN/7Orq7unpxRi1tLRUVpa/P63Ef8lksrquiqI4PgihUChEImOJRCKTyZgm+t3v/mPt2ptXrVq5fPmyjz0o7fegyZrjEonk4cNHNE3t6+sLBAKLFy+68cYbLBbLGa/lOIFhsCzLZ9x58Dzf2Nh4002rfv3rf50/f67L5cYYZzJZVVWtVmsmk/H5vB/8uwC4qlRWVt5ww/UIoV27djudDkKIoiiNjY3xeOLVV18LhyMsy1ZXV2ez6f/7fx85evTYF77w+fnz5/2f//Ot/fsP7Ny5i+cFj8edy2VvvfXmu+6687rrlkiStHr1KkLI7t17qqqqUqlUJpNVFOW229Z96Uv3NTVNT6VSPp8vFov9y7/8OplMnt4Yq9VaU1MzPDxy3XVLPvhw4aNce+01X/7yF3/7298NDAza7TbTJDU1NS0tsyKRsa6ubp7nHQ5HSUnxbbfddtddGz5JfAIAAODimMhw8x/84AfLly//yU9+cvz48cHBQYSQJEmzZs367ne/e+21157vFoKJ6Ozs/Pa3v7t37z6fz+fxuHVd27t3754970iSWFlZ4fG4BUGkW6qqOjoadrnc+XzearUQQiKRMTrXVTqdcTqd8+bNa21tNU0zECg5S78EVVYWWrr0ura2dlotyjTNgYGBd999t6enj2GY3t4+wzA2bnx2/fp1f/d3f3tGQn9FRVkwGIzF4rSEi6qqhmHk83mHw9HSMnPhwgWPPfa41Wqlccj4eK2hoUGPZ8bpA64AuDpdc83iysqK2bNbaPAQCJQ4HPbf/OZ3O3bsmDZtallZxZQpdRgzuVzu9dffcLvd9933hbVrb25qmr548aKxsTGHw1FWVtbc3DT+bZo3b67fXzx16pTR0bCmaU6no6WlZe7cOTT72el0IoRUVeV5PpPJntEYWoX2jJTrs2NZ9tOfvnv69OltbW3RaMxut4VCoQUL5vM8f/LkqUgkgjEOBAJTp06B7zsAAFxSJpi9unjx4hdeeME0zZGREYRQaWkplNe4pPz614++887ehoZ6On7JNE2GYfv6+lVVfeqpvzQ3NwUCJbW1tdlsdufOXU6nK5GIp1KpXC5nsUiJRNzhcOq6JghCfX2dz+cpKvLu2fNOY+PUjw0nLBbLggXzt2/fIUkiwzCDg0MnT56KRqOiKLrd7mAwgDETi8Weeea5QCDw7W8/cPpra2pqnE6n1+ttbW3VdaNQKJimWVxchDHT3NzU0FB/6623vP32lhkzmsZjoZGR0VgsPmfO7At0GgG4vJSVldHUCELISy+9/Nprb+zZs8c0UTgcGRwczudzTU3TbTZbdXVVf39/LBbz+XzjFh6jxwAAIABJREFUtaE+VGVl5dm/9RzHTZnSsGvX7mAw4HA46UJN07q6utevv62y8twyHDDGM2fOmDlzxhnLIesaAAAuZeccTqxcufL222//6le/ihDCGJ+RXffQQw/19/c//vjj562B4Nyl0+n29g6Xy0VjCYTQ2NjYyMgox7GKopWWlnR2dp061Xb8+AlVLbAs73Q6MUaGQaLRMY7jdV1XVSWTyYZCoebmJppU7fG4R0ZGz35cRVFOnDip6/qaNasPHz62b9+edDqVTmcFgbdaLdlsNhIZCwQCPp+3t7fvr3/duGbNTQ0N9Sz7XtL27NktGzbc8Zvf/BZj7HK5i4o4hMxsNu9y2Y4fb122bOkdd9yuqurmzW+63S6eF7LZbDab/epX//fixYvoHgzDiEajgiC43W6Ib8HVbMeOnb/4xT8X///s3Xd8VeX9OPDnrLtncvfNuJkkJGSwdwZB9hCioihUERSrtcXV1mp92Wm/ttZRWn8qguJClE1lSYBAEJARErL3vrm5e575++PYNA0QkhAIyPP+Kzz3jM8dJPdzzvN8PlotTdMmk4HvZF9aWoqiaEZGukKhKCg4cv/9ywZ09+BqsrOzOjtte/bsDQ8Pk0ploVDIZrPl5GTfffei7v/dffN6vXV19TabTS6XR0ZG6PX6648KgiAIumkGnE6UlpZOnjz5ao9evHixtLT0+kKCBo+iqLKy8pKSktbWVpZlWZZBUSwQCPr9AbFYjOO4328zm81ms6mry37u3HmFQjFr1l0oihQXX2xoaNDp9DabjaZpiqKjo6OmTJnUXfaXL9HYx6mrq2u+/nrbnj17OY6jabq1tVWhUFgs0UVFJ9XqMIIgOI5zOJyBQFAgEDidLre7ZNasuePHj7NYoiMjI/1+P9/njqbpqKjozs7OUCio0WjU6jCTybhjx860tFHz589bu/axzMyMlpZWv9+v0YQnJSXxhee9Xu833+y7dKmM734llUpzcrJHj86EfbKhOw3Lsl1dXYWFx3U6rdlstlotgUAQ/KeUk9Pp9Hq9HMcCAIaqtrJEIlm58iG+k31XVxefEkyfPk2j0fRn9zNnvv/mm30HDx5CUZRl2Zyc7PT0tLlz53T30KBpurT0UktLi9/vDw8PT01N6e68CUEQBN0K+vvnJCsrq/vnLVu2HD58+PJtXC5XZ2en0WgcmtCgAbJarZ999sW2bdsBAC0trV6vB8PQsLCwUCjkdrsVCnkgEGQYJhgMSqVSs9lcW1vL95OWyaQZGelyudztdksk4pqa2rS0UaNHZ3avbeAzAb1eBwAIBAJHjhytqam12+18wpCbmxMMBj///IsTJ4o0Go3X67Xb7S6XOxQiMQxHkB/uEyAIYFnW5XIKhSKGYRiGRlH0wIEDFEVbLNEJCfEOh7Ourj4YDJpMJqVS4XZ72trahEKhzdbp8Xg3bfp4zJjRRqNx1qy7AAA+n6+o6OTZs+cKCo7I5bKTJ0+dPn1aLpfL5TKJRMpx7J49e599dt38+fOG7f2AoJvL5/Pt27f/0qUyr9d78uR3FEXJ5TIMw/x+n1gsAgCIxeL6+oYRI0YEAv7c3Byj0TBUpxYKhTNn5s2cmTfQHcvKyvfs2VtSUjJhwjixWELTVENDw5EjR2mazs9fCgBwOp2ffPLZl19uFQqFBEEEAoHs7KypU6f0pzIEBEEQdHP0N52orq7u/tnlcrlcrituJhAInn322SGICxogiqI+/fTzb77ZN3p0pkKh8Pv9Fy+WdHV1+Xx+gsAZhnG7PR6PhyDwlpbWlpZWiUTS1WVvb7c6HA6LJVqtVicljRAKhfwuAAD++wcAgOPY6uqaCRPGjxs3zuPxbNiwcceOnRqNRiqVBIOhXbt2X7pUptNpDx48xK+YFAgIiqJIMsSybG1trUQicbncAoGA47hAIIDjRCAQQBBULpcJhQIURQmCcDic5eWVJBliWcbj8Vy6dIkkKaFQYLFYgsFgIBBEEKSw8Pjvf/+n1177o0wms9lsmzZ9vGfPXrVaJRQKz527UF9fL5VKwsPDOzqsFEUmJycbjYYzZ77PzMyANWShO0EgENiwYeP27TvMZrNAIPB6vQ6Ho6WlNSEh3uv14jiuUCj4zN5qtTqdzmXL7rsViiMVFBz5/vuzmZkZfGw4TkRFRSEIWlJSOn36NK1Wu2XL1h07dmZkpKtUKgAAw9Dl5RUMw6hUqszMjOEOH4IgCAKg/+lEeXk5/0NSUtKKFSt+/etfX3EzfkbN0IQGDURJSen27TvGjMnkV0PGx8fX1dXb7Xav14dhGE3TACAIAgwGQ2RkZFNTU1NTE8uyarU6MjLC6/U2NTUHAoGxY8cIhUKtVpOZmXny5CkcxyiK8np9kydPysqaHh8f9+WXW3ft2j16dGZ3N7qYmOjCwuMSicTn8zkcDqPRgCBIIBDo6rLjOOZyeVAUsCxH0xTLsizL0jSFIAiGYVKplCRJkUjMMDRFUY2NjSNHjqRpyuv1chxgGCYYDNXXN4RCQRwnSJIUiUSffvqZWCz+7W9/8/XX2/fvPzBu3BixWNLS0mK1WgUCgmFYghBoNOGhULCysioxMeHo0WPTpk2F6QR0Jzh2rHDbtu2jR2fIZHKO4+rr60OhEIKgFEWlp6c5na6GhkaWZVEUjYmxTJw4oWcz++ESDAY7Ojp0Ol2vlU4Gg66g4Mj8+fO8Xl9ra2tCQgKfSwAAMAxPSIg/f/6CVquF6QQEQdAtor9f/bvnvcyePTs9Pb1XiU9o2LW0tAiFQj6XCAQCHR0dYrE4LEztdrs5DuE4DkURtVoVERHh8XgdDodCIe/qspNkCEEQmUwmFAoqKiqMRqPb7br77sWJiQnFxRfPnj0PABAKBUeOHE1JSUlMTCgvr4iIMPfsbC0QCGNjY0pKSj0ej0qlIgiCpmmfz4eiiMvlZlkWQTCRSETTNMty/HIOghCEhak1mvCuLjuGYXymQRA4x7ESiUSpVFqtnRKJhGEYt9sVFhYOAKBp2mQydnXZv/7669raGqfTRdN0a2t7RIS5paUVwzCCwAEAPp8vPDxMKBSFh4ddulRmsUS73e5hekMg6KYqKyvXajUymRwAgCCI0WioqanRaMIbGhpjYrJiY2OMRmN5eXlubu5TTz1xtVJOHo/n/PkL7e3tNE3rdLoxY0Z3f4/vG993aKD4BjWXX4HiR0iSbGtrO3Lk6LRpveuPazThnZ2dFEXBirEQBEG3ggHfSfjggw9uRBzQdaJpuruISnNzc11dvcUSjSBIR0cHSZJ807dAIGC320OhEMtywSCpVqtUKnVbW7tCIScIAgCkuLh4/vy5gUDgmWee9/n84eFqgsADgRCOE++9935zczNFUb0ySYqi7HZ7aeklr9drsUQLBAKn09nR0cFxgGVZBEEIgsAwFMeFJEljGA0AIpFIIyMjKYoKhUIAcDTNhEJBghAgCCIUCqVSKcO0kyQJAEAQNBQK0jSj1WpDoZDdbidJsqmpmWU5mUxSWVmVnJzk8XiEQkEoRAoEBMdxFEUJBAKRSIQgwOv1SqXSYXgzIOimc7vdYvF/Jy/FxMR4vd5z5y74/f6qqiqNRuNyuR566MGVKx+6WjWnurr6L77Ysn//AYlEgqKoz+fLzc2ZOTNv/PhxVzspSZKHDxeUll7yeDxyuTwiwjxjRm7/l89JpVJ+XhYA/1PKie9ioVarbTYbAABFe1dp40ssMAwD0wkIgqBbAZyY9COh0WicTmdFRQVJkg0NjQxDB4NBHMc5DqjVYQQhEImELS2tHAcwDBcIBFqtBgBgNBr5xtL19Q1SqUQmk9XU1B86dMjr9arVKhzHVSp1eDja1WVXKpXffLMvKSmpu5u1z+erqKisqalpb28PBIIkSTY1NXk8Xp/Px3EcxwEEQXEc5e8b4Dih1xsUCnldXT1FkdXVNRRFeTweFEUBQDAMVSoVfFlbgUAYEWF2Ol1+v18kEkkkEoVCwTBsXV1dKBTi11pQFOnz+f3+YHFxsUAgEApFFOXDcQzwM7oAQBBAkmRa2qi4uLhhe0sg6CYSi8V8Es5DUTQtLU2r1RUVFY0dO2bs2DFRUVHjxo29vBs9z+fzffHFluPHT0yYME4o/KG3/YULF2ia1ut1V2w9EQqFNm786NNPP1OpVEqlAgBQUHCktrZu0aKFlzeOuCIURVNSRh469K1er+u+TsEwTE1N7bx5c+PiYvmCci6XS6n8n5skTqczKSmpu5clBEEQNLxgOvFjwHFcR0e7SCT69tvDYrHEZrORJNnZaVMo5CRJ6fV6h8NhMOiCwaDFEo2iKEVROp2upaU1LEydkpJCUWRmZsbhw0dsNhtNUxRFchzndLo6O21yudxg0KvVqubmVoNBHwwGPR63Xq+zWq2lpZdKSkpIkkJRVCgUSqUSvrMERZE4jnMchyAcy3IYhsXExDAMq1IpTSZja2urw+FAED9BEDiOURSNIAgAXCgUIgjC7fa43a6UlJTOzs7i4gsKhcJisXAcV1ZWRlEUiqIikYhhGH4XlmV8Pr/H45VIJPyFTKUSAwCQJOl0Ov3+QGpqalxc7HC/ORB0M8TFxe7bt5+/Q8iP8Kn10qVLfvKTlRbLNRpQXrhQvG/f/u5cAgBAEERyclIf/SuPHj32xRdbUlJSZDIpjuMCgcBiib5w4QKO4/Hxcf28MZiXN6OxsWnbtu06nVYqlZEk2dnZOWXK5EWLFgoEgri42EWLFh48eCg9fVR388qOjo7OThtsXglBEHTrgOnEj8G5c+fffnu9XC6PjrbU1FQzDMNxgKZpp9Ol0YTRNBUeHtbVZacoOixMrVSqPB5Pa2ur2WwyGAwAAIIQdHY2OZ3OzMxMt9tFUQxJkgRBoCjqdDr9fr/BYMAwjGGYmJiYoqKi0tJSq7WzoaGRYVipVBoKhcxmk9fL35dgEAQQBC4QCH0+H4IgFMX4fH6FQg4A0Go1JEkRBCEWi4PBII4TGIYJBAKPx+t0uqqqqhMT4+PjYxMTE48fPy4SiUOhkMPh8Pv9TqcLx3EEARTFL7QQUBSFooDjOBzHfT6/QCDgF5G3tLSyLCMUiu65J3/t2seG+52BoJskK2t6RUXl0aPHYmJiFAoZTdOdnV2NjY05OVnXzCUAAO3t7RKJRCT6n3sXCIKq1eqr9a+8eLFEq9WqVEqapvkRFMXi4+P37z8wa9Zd/fy6L5VKH330kfj4uMrKKqfTKRKJIiMjsrKm8xUUCILIz18SCoW6m1f6fD6Px7N69aqpU6f05/gQBEHQTQDTiR+Dkye/U6mUGRkZBQVHRCKxTCazWm0EgXMcZzJFOJ0OqVSOICiOYx6Px+Vyt7d3+Hz+UChIkmRbWzs/S0omk6alpWzbtoMkgxiGdU9KFggIm81GEASCIFpt+PPPP/vll18dPPitQCAgSVKlUoWHh4WHh6vVqq4uO44TPp+PZTkAgFwuJ0lSIuEzB0wikVy6VE7TtMUSHR4e5vcH+PUeKIrZ7V1Op3PixAkdHVaPx3viRFFWVlZiYuKxY8elUqlQKGpsbBIKhaFQiGVZgiD4srOhUIhhGP6rjMfjiYiIiIyMUKvDAgH/ggXzV616+GrzOiDoxycsLOyhh5bL5fLOzs6CgiMAgJyc7MWLF86dO6c/u1+tSSWCXPkhmqbdbnfPqgw8vrifw+Hof+RisXjOnNlz5symafryZdmRkZFr1z6WkZHON68MDw9LSkrqLiwLQRAE3QpgOnHbYxims7MzPDzc5/MBAMxmk0Qikcvlzc0t/DppgsBra2sXLVqIosilS2W1tbUIgmIYJhAIvV5fXFyMxRKdlJR46tQZv9/PcQDDCBxHGYbBMAxBEIqiOY71er0Yhn3++Za7715sNBpGjUpFUaSmps5oNPBrHmiaFovFBCHAcZym6ejoKL6hhM1mdbvdbrcYQZBRo1JFIpFCoSAIgVIp6H4K/HqHhQvni0TiYDBgsVgSExO0Wu2XX26trKzau/ffcrnc7/cDAPi13XzraxRFOA4IhQK1Wu33+xEESUwcMXp0RkRExNixY26FmvoQdDOZzeYnnni8vb19yZK7RSKRwaBXKBT93Fen0/n9fpIMdc8pAgDwkx75/pW9YBj2nwrU/4OvB9094eqaOjo6WlvbAoGARqOJibFccRulUjl79qx+HhCCIAi6+WA6cdv7z7VDhKKo+voGvtOtRqMRiUQNDY0KhZyfaJSamrpv376qqmqlUiEQEMEg6XQ6GxubEATEx8fX1tbX1NSKRCKXy6nRqO12J0VRLMvQNM0wDAAoQRCjR6enpo46f/48X/I1IWFEQ0Njdzmp/3ShwqRSqVQq8Xp9UqlUoZCzLG212qZPn/7oow9zHFdUdJIkyV7f9d1ut8vlOnDgUFNTU25uTnt7h0gkMhgM99+/rK6uftKkiS+99Nvq6hqBgLDbHRzH0TTNd9IgCEyn04WHh8vlcn496KJFC2E1J+iOhSCI0Wjsf22lbunpaTNn5p0+fTolZSSOE+CH/pW148ePGzt27BVPFBUVWVR0sldrbau1c/r0aVFRkdc8YygU2rZte3l5BX8vBQCwePGiuXPnJCYmDDR4CIIgaHhdO53YuXPngI5oNpvHjBkz2HigAcNxPCwsrLi4ODw8zGKJ9vl8/O0CHMelUumkSZNQFJ0+XXX06JFz584nJiZ0z2Kqr29oa2s7ceIkgqA0TRMEfvx4EQBsZKQZw3CrtZNhGJpmUBSVy+UREabk5JESiSQ5OfnIkSNtbe0TJoyLi4tramrW6bQYhuE4wTC03+9PTEyIibH4/QG3203TNIbhEyZM/Pvf/6rX651OZ1pa+pkzZ5RKBYKgAIBQKNTe3tHa2goA+Pbbb2NjYy5cKMYw7Jtv9j3//LNz586JjY2JjY2x2+2/+c3LHo9HIBAEAgGOLx0FgEKh1Gg0oRCJYVhsbMyhQ98uWXJ3SsrIYXszIOh24PP5UBTtORtQoVDcffdijuMOHy5QKOQoino83smTJ02fPi0hIf6KB8nKmt7Q0HjmzJmoqCiFQsEwtNVqq66unjx54tX6WvD4Yk3bt+/46KPNcXGxkydPIgjc7fZ8++1hj8fzk5+siIy8djYCQRAE3TqunU6sXbt2QEdctGgRTCdusrFjx3z11ddqdZhEImltbeN7wNnt9qSkEWFhquLiErFYdOFCsVar7c4lfD6/0+kUi8Uul0skEpnNJpqmCgtPcBzidLq1Wq1QKOzq6sJxLDo6mmVZnU4vk/1w1T8xcQSG4RcvliYkxAEAampqCYLw+71CoQjDMJlMZjKZJBIJAFxra1t1dc19992j1+sBACqVatmye4qLi6ura8LDNRiGtLZ2OBxdHMfFxcWFhYV5PN7W1rYJE8ZHR0efPn1m7NgxOp0OAHDvvfeQJLl377+PHi2kKIrjOKFQIJPJ1WpVV1eX3x9ITh4hkYgBAIFAYHjeAwi65VEUVVBw5Ny58/zUQZVKlZU1PSMjnb+1mJyc9Pjja8aMGd3e3k5RtF6vS09Pu2JNJ57FYuEzkP37D/Brq7Kypk+dOjk/f+nVdvF4PPv27a+oqLTZbOfOnWcYRiyW8DOjlEplRkbaiRNFFkv0Qw89eAOePQRBEHSjXDudWL16da+R8vLyY8eOAQAyMjLi4uJQFK2trT179izHcY899tjs2bNvSKTQ1U2YMP6pp3769tv/AAAIBERFRQWG4bGxMRpN+PnzxePGjTWbzQAgYvF/y7T7/T6+qlIwGKAoEgCQnJwsFAoPHy7weLx+fyAxMcFkMlVUVHIc5/P5o6Ii+fsJAACpVOz1erOypp86dVooFPC9tEeNmjB9+jSCIOrrG7777pRcLg+FQlOmTJ42bWrPxaDLlt2HYfjHH2/2eDynT58RCoUqlVoiEfM1psLCwnAcb2/vyMhILyg4kpc3g08nMAxbuXJFTk52TU3tzp27vv32cH19g8Ph6OrqwnEcRdHvvz/X2tqGYWj/J4tD0B2FYZjNmz/96KOPDQa9UqlkWa64uHj79h2/+MXTixYt5LcJDw8f0CqFUaNSDQZ9bm6O2+3WaDRmsykiIuJqG3s8nvff37Bnz16TyeTxeCorq2QyWXFxcXx8fESEGQCAophOp21oaOQ4Dq60hiAIuo1cO5145ZVXev6zrq5uzpw5UVFR//rXv9LT07vHy8rKHn/88U8++WT58uVDHuXtorvQ0M23aNHCxMTEsrKyysqqqqoqjuNqa+tiY2M1Gs2sWXe1tLQgCBIKkVLpD0VaKIpGUYRlGY4DAoGQX9wcGxvr8XjkcoVarTp//gJFURiGicWStLS0iIgIfhsAgNvtveuumY8++sjcuXPa2toYhtHpdKNGpWo0GpqmS0svTZw4gS/6FB0dHR8fhyBIz5dlyZLF8+fPrays/Pvf37bZOt1uj8fj6a4eI5PJ6usbYmIsGIa5XK6eO5pMJpPJNG3a1IcfXlVdXSORSFiWEQiEOI7Z7V1NTU0TJ07U63XD9Rbc7vj3l1+aMtyxDLPu2XR9bwMAuI1eqzNnvt+4cVNKSopG80NXbINB39jY9P33Z1NSUvpTTPaKhEJhcnKSQCDgF0T18YIcOHBw167do0dnSiSSuro6kUhoNBo6OzsRBNFowvl7FBiGkyQZDAZhu+ubgP8Msyx7G32MoZ6G8SvHLYJhmOEOAfrBgJdiv/baax6PZ+vWrampqT3Hk5OT33vvvZycnD/96U/vv//+0EV422BZ1ufzDeOH22QymkzGGTNyAQCBQMDhcCiVSn5dssvlEgqFdrtdIhH/5+80x7JcMOg3GIxyuSwUCvEHCYXIuXOnTJkyubGxye12FxYev3ix1Gg0dG9AkmRdXV1a2iipVJqampKamtIdgMvlAgBER0dFR0d1X1x0u91XjNZoNPJf/b1eH0mSvV43t9vDn5E/Zk8Oh0MgECgUCo/HI5VKMQxlWQ5BUJlMVlNTc/ToscmTJ13fC3lHYxjm8tf8TkNR1DX/SPMpx230Wn3//fcSiaTnf3YAgE6nPXasMDk5Sa1W9bFvH/ivpCRJUhTV95bnz18IDw/DMIxvb0/TTCgUksvlNTW1UVFRBoMeAOB0OmJiLPxcLOhG49+7YDDY8yMB3Rb4987v99/h83tJkrzmpR/o5hhwOlFYWGg0GnvlErzExMSoqKiTJ08ORWC3HxRFFQqFXC4f7kB+0HPWgUqlevTRR95//4P29nalUkkQAgA4n88nEgnS09O6Y/Z6PaFQaNSoUampqfxbPGXK5I8+2nz06DG9XicSiQKBQHt7x8yZecuW3RseHn75SSmKcrlcCIJc8dFeNBpNU1Mzf4lUrQZ8yXmGYRAEBIOBvLwZY8eOufw4bW3t339/DsexiAhzKBTif5MoFAqRSETTVHl5xYIF8wf5kt3ZgsGg1+vFcVylGuQ3yx8Nh8NxzavjKIr283N+i2BZTqVSXt6MRaFQsCw76Cfi9XqDwaBQKOz7Vx+fQqhUaj4As9mckBDf3t6u1WpxHAMAiMVit9vldLrGjx/XKxiapm02G8uyPVd/QdfP5XJRFCWRSGBZ7duO3W5nWVYul/OVV+5Yfr/farUOdxQQAINIJ2ia7uMqVDAY7J4SA906MAxbseJBmqY3b/6EomiKohiGi4+PB4DT6XT82gmHw1ldXbN48aKxY/+7kj4yMnL16lWxsTENDY3BYFAsFi9cuGDGjNywsLDrjyopacQ33+xLTU2Ji4utq6tTKpV8KVi5XO52e8aPH8cvnOiFv70rEAgNBgMAHEXROI4hCBoIBIJBxOl0Xn9gEPTjIxKJSJK8fJyiqIE2fKQo6syZ7+vr651Ol0gkjIiIGD9+XN+7CAQCDMO6AxAIBHFxcSzLNje3BAJBvpNmR4c1P39pVtb07r1Ikjx48NDZs+f4m0Uoio4bNzYnJ1skEl35NBAEQdBwGHA6kZqaWlRUdPr06XHjev/9OHPmjNVqnTJlyhDFBg0lrVb79NNPZWVNb25udjqdJpPJYDCcPn2mra2Nr/uenZ2VmZm5dOndvVpQ6XS6++9fBgAIBAJD22c6Jye7urpmz569Gk04y3Iul7O6ukYqlWVlZS1ffv+0aVOv8kQ0GRnpR47wteqR7quVwWCQ4zi1Wj2EEULQj0ZMjMXhcPb6X+xwOP1+f0xMTP+P4/P5Pvpo85YtX8rlcrFY5PF4XS7XPffkr169qo+WLwiCxMRYjh8/ERUVyTerMZmMIpGQpmmCiEhMjDcYjCNHJvdMFTiO+/zzLzZu/MhsNqnVagRB7HZHQcGRxsamVasevrx/NjQIlC8UDLIioRD9TwchCIKgQRjwb+RZs2YVFRU98cQT69ev75lRnDlz5oknngAAzJw5cygDhIaOSCSaOHECABO6RzIzM1pbWxcsmI8giMGgNxqNfRRUGdpcAgAgk8lWrXrYbDZVVFQyDEOSJIZh06dPy8nJ7uO7gtFoTExM2Lv33263u7uOUzAYdLvdSqUyPj5uaIOEoB+HSZMmzp075+DBQ3FxsUqlkmVZh8NRU1O7bNl9aWmj+n+c3bv3fPXV1xkZaUqlCgBAkqTN1rVjx06DQb9s2X197JiTk11f33Dq1GmLxSKXSymKcrncOI4/+eQTc+fOufyGw6VLZRs2bBw5Mrn7LqVarQ4LC/v88y/S09MmTpxw2Rmg/uI4zlpcX1t4MeQNEAQhEArCR0RETk4mJHf0zBkIggZtwOnEqlWrDh06dOzYscWLF6empiYkJAAAqqurL168CACYNm3aqlWrhj5M6MZAEMRsNpvN5uEKQKFQ3HvvPXyXDLFYLJPJrrkLgiCPP76mpKT04MGDSqWSb7Lh8/lUKvXSpUumT592E8KGoNuOVCpdseJBqVTa0dHRfUNyypTJd9+9GOv3lWmv11teXhEVFcnnEjyVShkZGVFRUenxePpYQWE2m++/f5lEItm5cxc/kpubk5+/ZM7w/MpOAAAgAElEQVSc2Ve8fFBRUSEWi3vNeFSrVQqForKyEqYT16O5qPzMP/diUoFAKWGEgkDI1Xqqyt1sS7lvGiGGGQUEQQM24HQCRdEPP/zw3XffXb9+fUlJSUlJCT8ul8ufeOKJ1atXoyg61EFCP3IYhmm12v5vr9Pp/vGPt/72tzcuXSovLb1EEJhGo33wwQfuuWfpkCzqgKAfJZ1O9/jja9ra2hYuXIDjuMGgv+LypD50dtoOHy4YPTqz17hKpTx8uODBB5f3vSA7Li726aefys9fYrN1SSQSk8nYR6MYr9crEl3hq61IJPJ4vAMKG+op6PC2n6uRGtRivYJhGIIgCIIQh8vrDxerLHpL9gBuVUEQBPEGM/1ULBb//Oc/X7NmTU1NTW1tLUEQMTExMTExcHncLcXv93d0WBEE6HS6vgt3BIPB2+6902q1f/rTH61Wa2trG0mSOp0uMjKi/xdZIejOhCAI379lsLsD8J8ilT3xI/3pPYdhWFRUVFRU1DW3lEqlodAV1o6HQiGpFFYiGjxHXXvLdxWGzDiK+W81ZEIslITLnbXtAKYTEAQN3OBXs0kkklGjRo0aBX/13HJ8Pt+ePXvLysoPHy4AAOTm5owZM3rGjNxeOYPT6Txw4GBNTS1fsikxMWHGjNzbq6u0Tqcb6OVVCIIGTa/X5+bm1NTUKJXKnuN2uyM3N4fvHTE4LMtevFhSU1PjcDgVCnlMTExsbKzf77fZurr77gEA3G6Xy+XiJ9lCg0P6QiiGoTgGmP9proKLBJQ/xLEcgsKW5BAEDcwg0wmfz7dr167Tp087HI7s7OwVK1YUFhaOGTNmyFfrQgNF0/RHH23euvWr6Oio0aMzOA7U1NQUFBxpbW3Lz19SVlZutVoRBEFR9Ny588eOFRqNBr6hxIEDBysqKh9+eKVeP/jvBBAE/YiJxeL09LSCgiNSqVSn0wKAAAA6O23NzS333JM/6PYFFEV99tnnGzZslEgkEok4GAx5vd57770nP3/p119vi4qKCgtTIQjidLoaGhrz85desy4t1AdCJGAYlmN732JiSAoT4jCXgCBoEAaTTnz//fePPfZYW1sb/0/+tvVrr71WX1+/cePGMWPG9Lk3dGN9//3ZLVu+TE9PV6l+uHyoVCqVSuV7771/4UJxaWmpWCzmOK6mphbDsJycbJ3uh0ULERERBQVHNBrNo48+MnzhQxB0S5szZ7bL5dqwYWNNTa1IJPJ6fcFgYMWKB+fOnTPoYx48eGjjxo96FnFyOp3btm2/9957nnzyiYsXS/gbrTk52Xl5M+bPnweb2V0PZZTWPC7B0+4QqP+b/rEU4+/yxkbBm70QBA3GgNOJ1tbWlStXOhyOvLy8uXPnrlu3jh/Pycl5880377vvvmPHjhmNxqGOE+qv6upquVzenUvwRCKRy+U+deq7vLwZAoHQ5/O63e6WltbKykqlUsG31RQKhdHRUc3NzQ6H4xbs3uB2u8ViMfwaAUHDSyAQPPTQg2PHjq2rq3M6nSKRyGAwjBqV2qtfTf/RNH3u3Hmj0dhz4qJKpYqNjWlpaVm0aMGcObNXrlzBsqxOp+1P8Teob1K9KjzR3Hq6UuiT40oRIuRod9Dd0hU5Kck8IXG4o4Mg6LY04HTi3XffdTgcjz322MsvvwwA6E4n1q1bFxkZ+fOf//ydd975wx/+MMRhQv3m8/mFwt5/11taWhwOR0JCvEAgBAAEg6GWllaDQV9TUxsRYbZYLPxmUqm0oODIypUrbp10wufz7d9/oLy8IhQKIQhiMBhmzsyLjR1A1y0IgoYWgiAjRyaPHJkMAPB6vcFgsD+LsK/GbreTJHn57xy1Wl1QcGTJkrt1Op3FEn1dEUP/KyYvHRcJmr6vaD1VhaFo5KTksERTbF6GSAWzNQiCBmPA6cShQ4dEItELL7xw+UP5+fl//OMfT548ORSBQYMkk0mDwVCvQY/Hi2GYWPzDUmwM++F9FwoFHo+nezOKorOzsy7PRoaLz+d7//0NO3fuMhqNcrmMJCm+jfecObMnTBg/3NFBEDQE+k5FridRga4GxbDorFR5kiEyL41AMJVJKw6TwZcagqBBG3A60dbWFhsby0+P6YXviVZRUTEUgUGDlJiY6PF47HZ7zw4MHo+HYWiNRsP/Uy6XxcXFdnR0IAjC9liQ197eFhFhvnWWYh8+XLBz567RozOk0h+umUVEmC9dKsNxPDk56fYqQgVB0BWp1WqBQGC323tWcAIA2O327Oys66kWBfUNExFSk1oikQx6DT0EQRBvwC3noqOj29vbr/ZoS0vLoCuaQ0MiMzNj+fIHSkpK6+rqHA6Hw+Goqam12Ww6nV6r/SGd4Eu/e71ep9NJEDgAXCDgr6io7Oy0ZWdn3TrdGy5dKtPr9d25BAAAQZC4uJiDBw9VVlYNY2AQBA0VHMfHjBnd1tbW3t4BwA9XN5xOZ21tXWxszIAaXEIQBEHDYsB3J0aNGrV169Zt27bdfffdvR7at2+f1WqdNGnSEMUGDQaGYQ89tFyr1RQXX2RZFgCg0Wiys6fX19fX1NTGx8fzd7QjIyMsFguKos3NLZ2dNo7jZszIffzxNbfOJCKKovx+/+WXzYRCEY7jLpfr8l1omu7s7AQAaLVaHB98TxUIgm6mGTNybTbbe+99UF9fL5GIQyHS5/Pde+89S5b0/isDQRAE3YIG/JXrqaee2rNnz3PPPWe327szCqfTuXv37t///vc4jq9du3aog4QGRiQSLV68aO7cOTabDQCg1WoJgigoOILjR4uKTiqVSo7jXC5XTk72tGlTtVqt0+lUq9XR0VFyuXy4Y/8vHMdxHKeo3m1xGYZhGKZXS75QKLR//4Hz5y8wDAMAwDBs4sQJWVnTB11tBoKgmwbH8QceuD8jI6Ompqary65QyKOjo9PT02AlNwiCoNvCgNOJ+Pj4v/zlL88999zLL7/829/+FgCwcePG9957DwCAYdjLL78M+2TfClwuV2Njk91uV6lUEolEpVJlZ2dFR0enpIzs6LCiKGow6MeOHRMZGTnckV4VgiAWS3Rh4fGoqKie86/a2tqysqbHxFi6R1iW/eSTzzZs2CAQCBAE4ziOYah9+/Y98sgjP/nJChQd8Iw+CIJuMgRBUlJGpqSMHO5AIAiCoAEbzISQJUuWTJgw4fXXXz9z5kxjYyNN0xEREWlpac8880xSUtKQhwgNVEHBkWPHCg8d+hZBEI7j8vJmTJkyOTs7KybGEhNjGd7YBiQnJ7u+vuHUqdOxsTEymZSiaKvV2tDQOHv2rJ5LdC5cKF6//p8Yhre1NQmFAgRBQqFQeHj422+/k5GRPnp05jA+BQiCIAiCoB+3Qc4vN5vNb7zxBgCApmmapnvNPIGGUVHRyVdeedVkMk2cOF4kEgeDwbKysoMHDyEIkp2dNdzRDYzZbF627D6xWLxr125+JCcne9GihfPmze252ZkzZzweL4ahEREmBEEBABzH2e32UIgsLDwO0wkIgiAIgqAb53qXq/IT3IckFOj6MQxz9OgxrVaTmJjAj4hEooSEBJblCguPT5o08YoVfm9l8fFxTz/91JIld9tsNolEYjIZL293VV5e4XA4kpJG8LkEAABBkLCwsIqKykuXLt30kCEIgiAIgu4gg8wEKIpqbm7mCwddTq/Xy2T9ba7p8Xg+/PDDU6dONTQ0BAIBi8WSkZHx+OOPdzdJgPrParUGAgGDwdhr3GDQHzx46IEH7r8R/aRJkqytrevs7BSLxTqddshLmOM4HtPnNK1QKISiaK81EgiCYBgaCvXu6AdBEARBEAQNoQGnEzRN//73v9+4cSNFUVfbZvv27ePGjevP0fbu3fvcc885nc7ukba2tqKioo8++ujPf/7zkiVLBhreHY4kyYKCI5mZGb3GCQIHANyI79aVlVXbt+/Yu/ff/DqN6dOnRUdHzZp115CfqA9Go5Gm6WAw2HPSXTAYpCjq1mnJB0EQBEEQ9KM04HRiw4YN7733nlAozMjIEIvFV9wmOTm5P4cqKyv72c9+hiDIE088MX/+/OjoaJIkq6qqPvjgg3379j377LMjRoxISUkZaIR3Mr6CU2trq1Kp7Dnu9fqys7PCwnpPE7pOra2tX3yx5cyZ78eMyZTJZAzDtLS0FhQc8fsDTz75BN/g4iaYNGnixx9vbm9vV6vVYrGI44DX6/V4PBqNdvz4fqW1EARBEARB0OAMOJ34/PPPTSbTtm3bIiIirvPcb731FkVRX3755fjx/22dptPppkyZ8oc//GH9+vVvv/32v/71r+s8yx1FqVRGRUWdPPldeHh49zIJiqLq6xtSU1N1Ot3Qnu7o0WPHj58YN24sX8gVx1Gz2cRx7BdfbJkzZ3Z8fNw1j2C329va2kOhkFarMZvNvSYssSzrcDhwHO+VHfUybtzYBx64f+fO3TiOVVXV0DSlVCppmo6KihzypwxBEARBEAT1NOB0oqGh4Zlnnrn+XAIAcOHChdmzZ/fMJbo9//zz77//fnFx8fWf5U4zf/7czs7OgwcP6fU6sVgSDAY6OqzZ2VmLFi0Y8tsFDQ2NGo2mZ1MIAEB4eDiG1TY0NPSdToRCoZ07d126VHb4cAEAIDs7y2AwzJ8/l/9oBQKB/fsPXLxYQtM0AEAmk2VnZ40enXnFJhJyufzBB5czDPPxx5+wLCMSSSiKNplMwWDw4MFDOI5PnDhhCJ81BEEQBEEQ1G3A6YRcLu//Muu+Wa3WhISEKz5EEITFYuGbOkMDotPp1qx5NC4utra2zu/3i8Xi+fOjc3NztFrtkJ+LJEl+VUZPCIJgGHbNdRpbtnz54YebYmIsEyaMx3HMZus6deq03W5fs+ZRhUKxceNHW7d+ZTKZFAoFyzIlJSW7d+9Zt+7nCxcuuOLRYmNj4uPjwsPDMzLScByXSqV6vU4kEpWVlREEkZqaMlQfWgiCIAiCIKinAacTeXl5hYWFK1asuP5zjxgxoqys7IoPkSRZX18/ZcqU6z/LHUitVufnLwUAhEKhG1oZVqVSeb3eXoMkSZIkeXk5155qa+tqamoTExMMBgM/otGEK5WKgoIjI0YkarXaLVu+zMhIUypV/KN6vb6hofHs2XMZGelRUVGXH5Bl2cbGpuTkpF6lqywWy4EDB+fNm5uRkT745wlBEARBEARdxRWmjvTtl7/8ZXFx8bvvvsswzHWee+3atfv37//mm28uf+h3v/sdRVEPPPDAdZ7iDneju0ykpqbYbF0Oh6N7hOO4urr66dOnJSf/0B+dYZjOzs6mpqZgMNi9WV1d3bFjhXr9/yxsIAhCq9XU1taVl1eo1aruXIIXFRVRWHi8rKz8ipEEAgGKoi6vDSAWixAEcbvd1/M0IQiCIAiCoKsZ8N2Jo0ePrlq16vXXX//444/HjRtnMpl6TZ0HAKxbt64/h5o/f359ff1jjz02a9asBQsWREZG0jRdV1e3efPmM2fO5OfnjxgxoqampucucXHXXt0L3TRTpkx+4IH7P/30M51OK5craJrq7LSlpIzMyclWqVQsyx47VnjiRFH3xKeUlJF33TVTqVQGg0GCILq7znUjCEEwGEQQ5PLmFQiCikSiqyUGIpEIRVGS7D3DiiRJjuOGvBUGBEEQBEEQxBtwOvHUU0/xP3i93rq6uitu0890wmw28z/s2bNnz549vR7dunXr1q1bew22tLQMIFboBhMIBD/5yYqYGEtp6SWn04nj+JQpU9LSRsXGxjQ0NGzbtmPz5k/MZnNkZCSOY263u7DweGNj05o1jyqVSpIkaZrCcaLnAf1+n1KpxHH8SksvOJIkr5YYYBhmsUQXFZ2MiDBj2H8/1c3NrTk52TeieR8EQRAEQRAEBpFOvPbaa0N17kmTJg3VoaDhQhBEXt6MvLwZFEVhGMYwTFVV1YYNG3fs2NnW1hYIBGUyGUHgCQkJKpVKq9Xs3fvvESMSJ06ckJ2dVVFRkZAQD8AP9abcbpfN1jVyZDJN01999XUwGBCJ/jt5yWq1kSTZx+2pGTNyGxubTp78zmKxyGQSkqQ6OjpaW9seeGBZWFjYDX8hIAiCIAiC7kgDTicefPDBoTr35TcfoNsXQRAAAKfT+cUXXx4/fsJoNLa2tsXHx3k83qampkAgOHbsGLFYotNpKyur5s+fN23aVJZlL1y4oNFocRxzuz3t7e35+UunTZtKUVRJSenBg4diYixKpYJhmK4ue0ND48MPrxwxIvFqAZjN5uXLH5DL5Q6Ho6DgCAAgL2/Gww//JDc356a9CBAEQRAEQXeaAacTENSHoqKThw8XjB6d0dnZheMYjuNyuYwg8NLSS5GREQaDQSQSe71ejuP49RUajYYvBxwVFbVs2b15eTOEQqFQKFy58iGFQtHa2sonBjk52XPnzpk/f17frTNiYixPPfXTjo6OpUuXSKVSo9FwtcbtEARBEARB0JAYcDrRd2s5tVqt0+n6WVCIJMm+N0BRFMdhwnM7aWhoVKmUQqFIICAYhuU4DkEQkUhEELjD4TQYDKFQUCKR8FlBZmZGZmZGKBQKhUIKhaLncbRa7Zo1j1qt1vz8pQKBwGDQ99rgalAUNRqNRqPxhjw9CLol+f1+v98fFhZ2xT6PEARBEHRDDfjL+pw5c665jUKhGD169MMPP5yXl9fHZjEx11ggu2jRovXr1w8sPmhYhUIhfnV1WJg6OjrK5XIplUoAAIZhNE0Hg0GrtTMhIb7nLvztiCseTafT6XS6Kz4EQRAA4OzZc0ePHnM6nQAADMMyMtJzc3OkUulwxwVBEATdQQacTqxevbqkpKSoqAgAIJPJIiIicBxvbGx0u90Igixbtszj8dTX1xcUFBQUFKxbt+6ZZ5652qEsFkuvEZIk29vbWZbFMCw7Ozs9fQCtx1wu14YNG0pLSxmGSUpKeuSRR67YB7qxsfHJJ5+84hHuu+++5cuX+/3+ZcuW9Xpo9OjRr7zySv+DuWMplQq/3w8AkMsVBoOhoaGBphmpVBIMBvx+/7lz52fNuis7O2u4w4SgH4OCgiMFBUeKi4u1Wi2OEx6Pu6DgSE1N7erVq2BGAUEQBN00A04nfvrTn86aNUun07366qvz5s3rvrd+4MCBF198sbOzc8OGDRiGnTp1as2aNW+++ebSpUsvTxt4x48fv3yQJMm9e/e++uqrLMuuWrWqn1G53e5f/vKXDocjOzsbw7CCgoIXXnjhL3/5i0aj6bWlTCa76667eg3abLazZ8/yM2RaW1sBAKNHj+657xU7MUOXGzlypMfjsdm6IiMjRoxIEAiI5uYWu90OAJqUNCI1NXXhwvn8/QoIgq6H3W4/evRYZWVVWloaP6LVavR6/a5duxMS4ufNmzu84UEQBEF3jgGnE6+//npHR8fu3bszMzN7js+cOdNkMt11111vvPHGs88+O378+N/+9rdPPvnkmTNnrpZOXJFAIFi8eHFsbOyCBQvWr1//s5/9rD977d+/v6Wl5fe//z3/lzUrK+u5557bs2fPypUre20ZFhbW6+4Ex3G/+c1vxo8fn5ubC/7T2mLVqlWRkZH9DxviZWZm3H//fZ9/vsXr9SiVKoFAqFDIA4HAk08+cc89+TCRgKChUlFRefhwweTJE3sOSqVSnU5XVlYO0wkIgiDophlwOnHq1KnIyMheuQQvJSUlJiZmy5Ytzz77LABgypQpAIDa2tpBhJWWlpaUlPTll1/2M504cOCAxWLpvkqXmJg4cuTIb7/9dsWKFX3XAgIA7Nixo7m5+a233uL/2draimGYyWQaRNgQiqL5+UsjIyNramr5+W/p6WkTJ04YO3bMNd+IAXG73SUlpVarFUVRvV6fmZkhEAiG8PgQdIvzeDw4jhNE74+9RCLxer0Mw2AYNiyBQRAEQXeaAacTHR0dKpWqjw34RYEAAJlMBgDgZ9IPglqtrqqq6s+WFEW1tbXNnz+/52BqamppaanH4+m7IpDVat28efNPf/rT7gvnLS0tCoXigw8+OHnyZCAQsFgsS5cuHTt27OCexR0Ix/GpU6csWrQwEAhgGHYjvuWXlZVv27b9wIGDYrGY47hgMLhgwfy7714cE2MZ8nNB0K1JLBYzDMOyDIr+T9pAkiGhUAhzCQiCIOimGXA6kZaWduzYsfLy8qSkpF4PVVVV1dfXT5z4w813vqRsRETEIMKy2Wznzp274lrqyzkcDgBAr4k0fBbhcDj6Tic+/fRTk8mUnZ3dPdLa2upwOC5evJidnU3T9PHjx1999dW1a9des6QVy7I+n49l2f7E/GPFcRz/g8vl4n8IBAJDe4qurq7Nmz+5cKE4MzODLwnl9/sOHDjocrnWrHmUT2KhQeA/ugzDdL93dyyapmma7nsblmU5jhvG10qr1UyYML6+vtFs/u+tVIqiWlraZszIvWmBMQzDnxd+bG47/Ic8GAxSFDXcsUADw/+69vv9wWBwuGMZTqFQqPtbBzS8BpxOLF68+NixY4888sjf/va37swBAHDmzJlf/OIXHMfNmzcPAFBeXv7iiy8iCJKVddUyPp999tkVx7u6uj799FOv1zt79uz+hOTxeAAAvRqWSSQSAIDb7e5jx/r6+sOHD7/00ks95+FYLJbk5OSVK1fyl9WXLVv2i1/8YtOmTVlZWfwxr4bjOJqm4e9lAADHcTfudfjuu1OFhcfHjBmN4zj/VUYoFI0YkfDtt4czMzOmTp1yg857h7ih793tgk8V+t6G32AYXyuNRpOYmHDsWGEoFNJowgkC93h8jY1NkydPnDRp4k0OjGXZO/xKyu0Lvne3L4Zh+D+Cd6xrXveBbpoBpxPLli0rKiraunUrX7KJ7x1RX19fV1cHAJg1a9bDDz/M/0DT9PLlyxMSEq52KH6JxdVEREQ899xz/QlJLpeDy66C85Os+q6W+NVXX+n1+jFjxvQc7LVaQyKRLFiw4P/9v/9XV1eXkpLSx9FQFBUKhXd4G2aWZUOhEN+6bkgO2NjYWF5e4XA4ZDJZVFRUampKV5ddrVb3ep0JglAqlXa7/Q5//a8HwzAkSfIf4+GOZZhhGHbNyUL8NYjh/bzdffdimUx24ULx0aPHAADTpk0dOTJ5/vy5g7snPDgkSfLrNODipdtOKBRiWRbHcYIghjsWaGCCwSDHcQKB4A6f1ji0azKh6zGYntNvvPHG9OnT/+///q++vr6+vp4f1Gg069atW758Of/PkSNHLly48PHHH+/jOE8//fQVxxEEsVgsd911Vz8LAfFrOXrdiOBvWYSHh19tL4/Hc+LEiXvvvfeaH0eDwQAAsNvtfW/Gf4e+w8u9UxQVCoXAtRK5/mBZdteu3efPXzh+/IREIgmFQoFA4IEH7mcYRiAgLv/7RxA4juN3+Ot/PYLBIJ9OwNcQw7BrtpdGURRBkGF/re65J3/27FkrV67w+/1arcZgMNzkxtgcxzEMA//r3XZCbr+1qs1rc8vDlNo4k1TX15JI6FbDT/LpownsHQJBEJhR3CIGk06gKLp06dKlS5d2dHTU1tYGg8H4+PiIiIieb+q///3vax7n+eefH8TZLycQCAwGQ1lZWc/BsrIyuVzex8KJQ4cO0TTNF4ft1tTU9Omnn86dO3fUqFHdg11dXWCwi0CgQTt2rPDvf38rJiZm0qQJCIICAOx2+5dfbh0xYoTL5eY4lh/kMQzj8XhhC23oDiSXy/k7tBDUT62nq1pOVTQUlgIMBRyInpQcPsJsyUlD8Tv6UjcEQYM2mHSim16v1+v1QxXK9cjLy/vkk0+qq6vj4+MBAC0tLSUlJYsWLeojbS0sLIyKiuq12ttgMJw7d66rq+tPf/oTfw+RJMndu3frdDrYhuJmYln2u+9O6XTaqKj/vuxhYWGxsbE4jo0alVpdXRsfH8e/vyzLVlZWTp8+LTMzY/hChiAIug10ljY2nyx31nVo0ywcCnAMd7faW05VAg7E3nWFEvAQBEHX1K90Ij8/HwDwxBNP5Obm/u1vf7vm9uvWrRtQEMePH7948WJdXR1JknFxcaNGjepjAfcVzZo169ChQ7/73e/4FGLPnj1qtbq7dGxBQcFHH320aNGiRYsW8SMej6eqqmrWrFm9jkMQxMqVK//5z38+99xzkyZNCgaDhYWFVqv1pZdewvHrSr2gAXG73X6/Pyys91y18PCwEyeKHnhgmUwm++67UwqFgq+uM3nypNmzZ90iyS0EQdAtq/VMVVdFc1iimV/3gqCI3KgGHNtV2WKakChSwklrEAQNWL++IhcVFQEAli5dCgD461//es3t+59OVFVV/epXv+KP39PEiRP//Oc/97GMuxelUvnaa6998MEHu3fvZlk2OTl51apVGo2GfzQYDNpstp4dMM6fP89xXHJy8uWHmjNnjkQi2bFjx1dffSUUCuPj43/5y1/yK86hm4Yvm3P5zSV+ZMyYMXl56tTUlI4Ovo2dbty4sfD2EQRBUN9IbyDk9ovCFL1+u4rDFc3fVcTkZcB0AoKgQehXOnHvvfcCAPiv1K+99tpQndvn861cubKhocFoNObn50dHR+M4Xltbu3Xr1pMnT65cufLAgQP9X96nUqmeeeaZKz40e/bsXjVnp02bNm3atKsdKisra6C3R6ChpVAoRCKR0+nQ6f5nNprD4czOztLrdREREbGxMMeDIAgaAJZmAAAo1nu9PoahAACGgmU3IQgajH6lE2+88Ub3zw8++OBQnfuNN95oaGiYN2/eO++807PI4C9+8Ysnn3xyz549b7755q9//euhOh10G8EwLDMzY9++/SqVujuj8Pl8NTU16elpZrN5eMODIAi6HQlkYhRDSV9QHPY/HT9DvhAAQKyCbUAhCBqMoVkPsG/fvtra2vT09MmTJ/d/r1OnTuE4/te//rVXwXKBQPDXv/51//7933333ZCEB92OcnNzOjo6NmzY2NAglUqloVDI7XYvXLjgnnuWwsJwEARBgwx4IyAAACAASURBVIDimDre1PJdpSRMBvAffpGyFONu6ozNy5CbwoY3PAiCblODSSf279//+uuv5+Tk/OpXvwIAvPTSSxs2bOAfWrp06RtvvNHPviqVlZXx8fFXLHEol8sTEhIqKioGER7040AQxIMPLh81alR1dbXN1qVQyCMjI8eNGwsb1UEQBA1a1LSRvg5nzYFzuFyIEhjCIrQnYBqfGDszA7lsEhQEQVB/DDidKCoq4vte82sP6uvrN27cqFar77vvvn379n311VczZ85csGBBfw6lVqttNtvVHrXZbGFh8ErJHQ1F0czMDFj+FYIgaKgQYmHKvVPVMfq28oaAwyNRycOi9KZxCeIw2L0EgqBBGvCliH/84x8AgFdeeeWFF14AAOzbt49l2aeffvqll1769NNPURT95JNP+nmo5ORkm8124MCByx/69ttvrVZrSkrKQMODIAiCIKgPmJCInDpyxD2TUx7OTVmeFTdrNMwlIAi6HgNOJ8rKyoxG4+rVq/kFDydOnAAA8P0coqKi4uPja2tr+3molStXIgjy1FNPbdq0KRQK8YMkSX788cdPPvkkgiAPPfTQQMODIAiCIAiCIOimGfBkJ6fTOWLECP5njuPOnj0bFRWl0+n4EblcXl9f389DZWVlrV27dv369b/+9a9/85vfmEwmAEBbWxvDMACAtWvXTp8+faDhQRAEQbepUCiEoihBEPw/WZZFUTibH4Ig6FY34HQiIiKiqamJYRgMw06cOGG32/Py8rofbW1t7U4t+uPFF1/Mycl57bXXSkpKmpubAQAikSgjI+P555+fOnXqQGODIAiCbjsMwxQWHj937rzT6URRNCwsLCxM7XA47XY7QRBms2nGjFz+ehMEQRB0CxpwOjFx4sTNmze//vrry5cvf+eddwAA3enEpk2b2tracnJyBnTAyZMn79ixg+O4trY2AIDRaIRlQCEIgu4QLMt+9tnnH3zwoVarUSqVNM1s377DbndERJgSExNpmj5y5Ghtbd38+fPGjBk93MFCEAQBAMA333zz9ddfFxcXW63W8PDw2NjYnJycRx55pFfng3fffffVV199+eWXH3vsseEK9eYYcDrx5JNPbt++/a233nrrrbcAABaLZdasWQCA/Pz8oqIiAMAjjzzSn+NYrdaTJ0/q9foJEyYAABAEgRefIAiC7jQXLhS///6G5OQkvV4PAGhoaHA4HGKxCMcJhUKhUqksFktJSQmO4wkJ8QqFYrjjhSDojtbV1fX444/zK4dxHFcoFG1tba2trYWFhR9++OGmTZuSkpKGO8ZhMOBpqZGRkTt37szLyzMajZMnT/7www9xHAcAOBwOmUz25z//OTc3tz/HOX/+/Nq1a1955ZWBBgBBEATdUCRJ3rRzlZSUyOVyqVTS2tpWX99QXV0rFAr1en1TU1NnZycAAEXR+Pj4gwcPXbpUdtOigiAIupzX67333ntPnDgRFxf34Ycf1tTUXLx4sa6u7osvvsjIyGhubn700Uc9Hs+NDsPj8ZjN5qysrBt9ov4bTBu7ESNGbNq0qdfgpk2bTCZT/5fNZWRkiESi6upqj8dzxU52EARB0M3U0tJy+HBBc3NLMBhUKBQjRyZnZ2eJRKIbelK73W6328+cOVtf34AgiNPpFIvFMpmcIASBQJDfRigUCgQCu91+QyOBIAjq2x//+Mfy8vKRI0d+/fXX3d9dCYKYOnXqF198MX/+/KqqqvXr1/OtFO4oQ1M0Y9++fbt27Tp58mT/d9HpdO+99x6GYS+++GJ3lVgIgiBoWFRVVW/YsHHz5k8vXSpraWk5ffr0X/7y+j//+a7b7b6h5y0rK6+qqnK7PVFRkdHRUQqFwufzdXXZgsEgf+sbAMBxHMMwvSYlQxAE3UwdHR18a7VXX3318uvgMpnsZz/7GQBg9+7dwxDcwFmt1gMHDlit1iE52mDuTuzfv//111/Pycn51a9+BQB46aWXNmzYwD+0dOnSN954A8Ow/hzH6/WuXr36zTffPHbs2PTp0w0Gg1Ao7LXNunXrBhEhBEEQ1H8URe3YsfP06TPjxo3t/gUeEWHes2dvZGREfv7SG3Req9Xq9/txnJBIxPzNbalU4vF4nE43iqIqlYrfzGbromk6KirqBoUBQRB0Tbt27aJpety4cZMmTbriBrNnz3755ZcBAH6/XyKRXL7BX/7ylzfffPP111+///77e45PmTKlvr6+rq6u+6JJc3PzO++8c/LkyebmZrVanZSU9NOf/nTixIkAgFWrVn3zzTcAgOrqarPZnJKSsn//fn6vmpqat99+++LFiw0NDUajccaMGWvWrOm5Mnnz5s0vvPDCP//5T5lMtnr16mAw+M//z96dB0ZVnQ0DP3eZfZ9MZiazZd8I2UlC2LIQQCCAAkoUBaFFStW3FrWttVq16vtq+aRabWtdCrjQIlSqUEUIJGEJhFUI2ZfJnplJMvt+l++Pq2MMiwmERTi/v2bunHvunQnM3Oeec57nr39duHDh1X84Yw4nqqurV61aBQCYPn06AMBoNG7atEkmky1btmzPnj07duyYNWvWggULRtPVunXrmAdms3n79u0XbQPDCQiCoGvNaOzYtWt3Zmb68JtBAoFQq9U0NDQGg8FQLYjx1dnZ1d5uTEpK7OrqksvlXC5HJBLZ7Y6hoaGICLVCEUZRpMUy2NzcfP/9y+Pj467FOUAQBI1Gc3MzAOAyJdH4fP64ZHBqampauHCh0+mUyWQJCQlms3n//v0HDhzYtGlTSUnJrFmzlErlli1bJBLJPffco1armb3+/e9//+pXv/J6vTKZLDo6uq2t7Z133tm+ffuWLVuysr6XFq+lpeXvf/87giCpqalMDoyrN+Zw4q233gIAPPfccytXrgQA7Nmzh6KoX/ziF2vWrFm5cuXUqVM/+uijUYYTr7zyyliPDkEQBI07m80GABAIhCO2C4UigiAcDkdYWNi1OG4gEMAwLDMzg8vlhlZaa7UaDodDEMThw0dQFC0omJGTM+mee5bCHOIQBN1ATJnm6zBM+tJLLzmdzv/5n/95/PHHmTmff//7359//vlXX321pKSkrKxs/vz5W7ZsCQ8PDyU06u3tffLJJwEAf/7znxcvXgwA8Pv9//u///vOO++sXbu2oqJCIBCE+v/Tn/60aNGil19+eRyXLo85nKivr4+IiFizZg3zlEmVtWjRIgCAwWCIi4tra2sbZVf333//WI8OQRAEXbFgMNjU1GwymQAAKpUqKSmRGY5gRtgJgggtVwi1BwBcOA11vMhkMgAATdM5OZMSEuLdbg+KIkKhsLe3V6lULVxYyuPxtFqNwWCAsQQEQTdWZ2cnAOA6VDU4f/48AGD58uWhL+QHH3zQZDKN+H4ebsOGDT6f7/nnn2diCQAAh8N57rnn2traysvLP//887KyslDjsLCwDRs2jO8X+5jDCZvNlpiYyDymafrUqVMGgyFUCVskEjHRGwRBEHRT6enp2bZt+3/+8xkTQpAkuXTpkjvvXKjT6QwGfVFRYXu7MSoqctgetMlkSktLFQqFBEGcO1fb1dXldDrDwsImTEgel1t0sbEx8+fPO3TocFpaqlQqZRZLOJ1Os9lSVrZs5sxRpR2HIAi6DkJ1Ea71gaKjo/v6+n71q1898sgj+fn5CIKw2exnnnnmMrscP34cQZBQLBEyb9688vLy48ePDw8nZsyYMe43icYcTuh0uq6uLpIkMQw7cuTI0NBQqCo2AKC3tzcUWvygs2fPXuZVmUymVCqv3V0xCIKg24fb7f7oo60VFZVZWZlisQgAYLfbv/jiS7fb/fOf/0wmk2VmZlRUVKIoolar2WyWx+NpbzdmZmYUFRU6nc4PPvho27ZPeDwem832eDzTpk3NzMwoLZ1/lWfFZrMXLlzg9XqPHKkODw9ns9lut8tsttx1150lJTPH431DEASND5VK1dbW1t7efpk2x44dGxgYSEpKio2NveIDvfTSSw8++GBlZWVlZaVcLs/Ozp4yZcqcOXMiIyMv2p4giM7OTpqmU1NTL9pgRAgUWm4xjsYcTkyePPnDDz/csGHD8uXL33zzTQBAKJzYvHlzX19fUVHRKLuaO3fuD7YRi8VZWVmrVq0aHrRAEARBY3L8+Ikvv9yTmzuJy+UxWyQSaVraxD17vpo0KXvmzOJ58+aSJHn27LkDBypQFKUoatasktmzZ02YkLxp05ZPP92ZkZEhlUoAADRNGY0dFRWVUqk0KyvzKk8sMTHhJz9ZFRsbw9S7kEqlCQnxhYUFPB7vat8zBEHQ+MnKyqqurj516tSlGtA0/dBDDw0MDGzZsmVM4cSIyqEJCQmVlZV79uzZt2/f0aNH9+7du3fv3j/84Q+rV69+/vnnL9ydIAiSJFks1oMPPnjR/mNiYoY/vRZ36sccTjzyyCM7d+5844033njjDQBAVFTUnDlzAABLly6trq4GAKxevXqUXa1Zs6a2tpbZSygU6nQ6HMc7OzsdDgeCIGVlZU6n02g0VlRUVFRUrF+//vHHHx/r2UIQBEEAgO7ubpFIFIolGBwOVyIRd3V1AwBwHL/rrjunTZu6YEGp0+lUKBRRUZECgaC3t7ejoyM2NoaJJQAACIJGRhrcbvexYzWZmRlXf25arXb58vvAxRZvXCgQCDQ3t5hMJhRF1Wp1QkK83+8fGBjg8XhyuXz0pVQhCILGpLS09K233vrqq6++/vrr9PT0CxucPn16YGAAx/G8vLzRdxsIBPr7+0dsZLFYpaWlpaWlAACz2bxz587XX3/93XffZYYpRjTmcrkajaanp+exxx4L5de+zsYcTuj1+s8+++zll18+f/58dHT0Sy+9FJpMJhQKf/e73xUXj3a268MPPzxnzhylUvnCCy/Mnz8/9DOwd+/ep59+2mKxvP/++xiG1dTUPPTQQ6+//vqSJUuioqLGesIQBEFQMEjg+EUqAuE4zqy3ZoSHh4eHhw9v0N9vqqionDJlZJ71sDC52+12Op1XU13OYrEYjR02m00ul8fGxvzgD2FHR8cnn+zYtWs3hmE0TQcC/ri4+PBwBZO0hM/nFxcXZWdn3XrrtimS8tncHCEX41yTjL0QBP2gtLS0goKCysrK3/72t5s3b1YoFMNfJUmSWd5QWFgoFI7MksdgvpoGBweHb/ziiy8oigo97erqevDBB2UyWaiCglKpfOihh0wm09/+9rdLpTtKS0vr6enZvXv38uXLh2/fuHHj/v37f/3rX0+bNm3Mb3gsrqSMXWJi4ubNm0ds3Lx5s0ajGdOdoQ0bNphMpl27dmVmfm+4fNasWRqNZvbs2Rs3bnziiSdyc3N///vfP/LIIydOnIDhBARB0BWQy2Uul5umKQT57luapmmn0yWXyy6zI/M7d+EFOrNl+K/gmJAk+dVXe48fP7F//wEcxwmCKCmZOX36tBkzpl8qGLDb7R9//M/Dh49kZ2eJREKfz3foUPXu3btjYmJzcyfRNN3f3//f/37x1FO/njNn9pWd1U3IM+jsrKp19g7SFA0AEIRLDNNTRNprkrcXgqDL27Bhw9y5c8+cOTNr1qwXXnghLy9PqVQSBFFfX//888+fOXNGIpH83//936V2Zy5it27dWlZWxkQj586de+GFFzAMI0mSaaPVaru6uhoaGrZs2bJixQpmY1dX1549ewAAaWlpod7sdnvo8RNPPPHVV1+9+OKLSqVy1qxZAACapnfs2PGnP/1JJBJlZ2eP+0cxwpWEExel0+kAAGfPnuXxePHx8aPZpaamRq/Xj4glGCkpKdHR0du2bXviiScAAFOnTgUAjD4FLQRBEDRcenp6fv7ktra2mJhoAJjrddpo7Jg8Oe+io/YhSmV4YWGBxWIZMWphtdoMBoNYLB4x63eU9u7d9+qrGwwG/bRpU3EcDwQCdXV1+/aV/+//vpSfP/miuxw9emzfvvK8vFxmPKSjo7O3tzcmJsZsNnk8Hr1er1Ao2trajh49lpWVOeJsb2Y0RSPoxSMoz4CjfsfhnppGoUqG8zhkIGg+Z/QMOGJmZ4YlaK/zeUIQpNFoPv3009WrVzc3N//sZz8DAMhkMqfTSRAEAECtVm/cuDEiIuJSu8+ePVur1RqNxmnTpmVmZtpstrq6umnTpqWkpJSXlzNtUBR95plnfvOb3zz11FN//vOfNRqN0+lsbm6mKGrx4sVTpkwBADBZMSwWy4IFC9LS0l566aWkpKRnnnnmxRdffPDBB1UqlVar7enpMZlMPB5v06ZN12Ep2riFE+DbNSgGg2Hbtm2jaW8ymS4/tM1UVgIAMMNGHo/n6k8SgiDoNhQVFclcpp88eUomkwIAbDZ7VlZmbm5OXNzllgzq9Xq1Wl1dfVQg4PP53xRCMpvN/f39q1atHOWINE3Tw8ccPB5PTc1xnU4bHR3NbGGz2QkJCV6vb//+A3l5uRfttqurWyqVhOZWDQwMCgQC5mfVbnfo9QAAYDDoKyoqS0pm3vzhhLW1r/9Mu3fQQREUVy5Up0eHJelGjMx0HjzfW9MUPjES+3ZJCV8hGWjowji4NFqFscbzFxyCoNGIiYnZt2/f9u3bd+3aVVdXZ7VaIyIioqOj8/LyHnroIT6ff5l9JRLJjh07/vjHP1ZXVx89elSr1a5fv/7hhx9+7733hEJh6HvvgQce0Gq17777bktLy9mzZ8PCwvLz85cvX15aWsp8ReA4/vLLL2/YsOH8+fNisZjZa82aNbm5uX/5y1/q6+vr6+t1Ot2cOXMeeeQRrfZ63Hq4ki+j6urqzZs3XzhWMDQ01NfXd/kbXcOlpaUdPHiwoaEhKSlpxEvNzc1Go3Hy5G/uUTEpZZkBEAiCIOgKzJkzW6vVRkVFmUwmmqZVKtWkSdmpqRMvvxeCIEuXLvZ4PJ9/vksikbDZbLfb7Xa7V69+sLi4yOfzXWbf/v7+qqqDXV3dbrdbLpdPnJgydeoUFovV09O7f/+B7OwsphlBEG1tbWazxeFwWq1WDEPvvPPOpKTEEb0Fg8HQQm2apkNPURQNzRPAcRaO4y6X6wo+n+upt6ap+1ijubaDIxGgKGKqNTbvPj7x3oL4udng24iC8AUcPYMCtQwbtjwdQRGRJqyj6nzM7Cxp5GjTskMQNI5wHC8rKxteyeFS1q5du3bt2uFb9Ho9k8poRLMRW4qLiy+/FPnee++99957R2xMT09/++23L7PX/ffff41KSI85nDh16lRZWRkzrHOh2NjYxx57bJRd3XnnnQcPHly9evVrr70WihwAACdOnPjlL39J0/T8+fMBAA0NDU8//TSCIAUFBWM9WwiCIChk4sSUiRNTxrqXQqFYt25tdnZWV1eX0+kKC5PHx8enp6ddfmiitbVt69Z/Hjx4SKFQsNns2traHTv+vWTJ4lWrVjLzo5hggCCI06fP1NfXC4VCABCSJMrLD/h8/sLCgsLC733ny+Uyp9MFAA0AgiAIi8UiSYKm6UAgwOd/M5RPkgRBEMzK7JuWZ8DeXdNkazcpUwxM8CDShrnMttqtldIoVfgEPdMs4PYDmr5w7TXOZQMAAk7vdT5tCIKgSxlzOPG3v/2NIIhHHnlkxYoVX3755bPPPrtjx47o6OgTJ0489dRTM2bMSE5OHmVXZWVl1dXV27dvZ1I2MaPeRqORKREyZ86cVatWMQ8Igli+fPkol2RAEARB44vH4xUUzBh9+2AwuHPnf2pqjufkTAoNKTgcjk8/3anTafPycgsLC8xmC4/H6+zsqqurV6tVHA7H4XCIxeLc3OympmYURSdOTBmeOyUtLS03N6ezs8tg0ANAoyjS399vNpsFAuHQkNVut0skkq6unsLCgvj4uHF+/+NqsLGn73izKisGDJvaJFRKvRb7YGN3KJxg8dgAACpIjtidDBLg26ACgiDoZjDmFN3nzp2TyWRPPvmkVqstKyvDcby3t1elUs2fP//tt9/etGlTVVXV6HvbuHHjG2+8odfrjUbjgQMHDhw40N7erlAoXn755b///e9MmwkTJvzud7975ZVXxnqqEARB0A1hNHZ8/vmu2Njo4XUkxGKxRhNx/nxdeHi4Uqk0Go2BQMBisfD5PA6HEwwG7XaHTCZlsTgxMVEVFZX19Q3D+0xOTsrMzGhrazt9+kxV1cHTp894vT6Px+v3+xsbG6urjx06dLijoyM7O0ulUl33dzwGfocH47IuHNth8bl+u3vYUw5fIfaYbTT9vfRZbpNNn58shsmdIAi6aYx5dKK/vz85OZn5hRAIBElJSWfPnl28eDEAID8/PzIy8qOPPpoxY7Q3sVAUXbJkyZIlS0wmU1tbm8/ni4uL0+m+txztiy++GOtJQhAEQcN5vd7a2vP9/f0kSYaHh2dkpF9qRlBLS+uxY8dMJjNBECqVMj8/PyHhu5Fht9t9/PiJ7u5uj8crl8vi4+O1Ws2FnQwNDQEAhELRiO0ikSgYDLpcrjvvXGi32/fvP2AymQKB4MDAgMfjiY+PT0hIAADgOIvNZg9Pg8hYuHCBwWDYtWt3ZWWVwRAZHq7w+fw0TRmNRrfbJRDw161bO2/e3Kv5oK4DFMdo8iIJdmmSQr+/ulo/Jdk75LTUdoo0cpzPIf1Bt8XuGXBMLJuB8+DoBARBN4sxhxNisXh4hqWkpKTjx4+HnsbExHz99ddXcB4qleomv58EQRD0I9XV1fWvf32ye/d/ORwOiqJer3fOnNnz58+7cB32oUOHy8v3HztWI5NJURStqrK1txuzs7MWLCgFAPT393/44cf//e8XYrGYxcLdbk9GRnpcXOzixXeN6IfFYgEASJLAsO/VziMIknlVo9GsXbsmMTFh06YPjMZ2rVYrk8mioiKZxE00TQWDwQuTGyIIkpmZ0dDQcPTosdLSuUzGW5/Pl5aWiqLI2bO1YrH45i+MLdTICX8w4PKyhd+9QSpIeu1uUYR8eEtJpDLujmycyw56/D01TQAA/ZTkifcWROTAqb8QBN1ExhxO6HS6s2fPGo1GphhHcnLyv//978HBwbCwMACA0+kMZXeFIAiCbjiv17t1678qK6tycrKZTK82m+2LL748e/Zsaen8tLS0CROSmUvw/v7+8vL9DQ0NOTmTvh0ipjs6OgAAsbGxiYkJn3yyo7x8f07OpG8v9GmjsaOq6qBGo7njjjnDD2ow6AsLC7q6uvX64Rn5aLPZnJaWygyMyOXyxYvvomn6b3/7e1ZWJhOBMEwm8/Tp00JpZEcYHBwSiYQAIF6v12az+/0+Docrk0lFItGIcrM3J0WiLnZWZnvFOVm0kisWAAQEPX6b0ayfnKTOihnRWBYbIYlSeSz2mFmZbCFXEC6BhbEhCLrZjDmcKCsrO3PmzN133/3444+XlZUlJSVRFPXuu+8+/vjjx48fP3XqVGpq6rU4UQiCIOgKnDnz9RdffJmbO4nH4wMAurt7WltbOzo66urq6+rqpVLpvfeW3X33ErlcfvbsuYMHD+XnTx423RSJjDQcP34iISGexWLt2PHvtLS0YYMGiEajsVqtp0+fGRFOKBSKiRNTqqoOoiiqVqswDPP7fW1txoyM9BH5mgoKZjQ2Nh0+fCQ2NkYkEhEEMTAw0N5unDZtakzMyHCCoigURVksFkmSra1t3d3d7e1GFEUoio6JifZ4vMOXaty0UBxLWJSHsrDm/55AEAQAmqZBVGFqzOxMrlR4kfYYKlTLhOrLFS+HIAi6gcb8zbts2bJDhw7t2rVr+/btZWVlU6ZM0el0b7zxxptvvklRFACASccEQRAE3Qx6e3v5fD4TSwwNDbW2tlosFoPBMDQ0pNFo4uLi/v3vTwmC+NnPHhocHBQIBCOmJwGAiESiwcEhs9mMIIhMJrFabQMDFo/Hy2LhfD5fLBY7nU6v1ztibtLChQsIgmhoaKysrMIwjCCImTOLS0pmjshUq1Ao7r//PoFAYLVaKyoqAQBFRYV33DFn4cIFoTbBYPDQocN1dfVDQ0McDsdiMTc0NDkcdqlUqtfrMAwjSbK/v7+vr39wcOiafZDjiSsRpCyboZ+S7BlwUCTFk4skkeGwLB0EQT9SY/7yYrPZf/vb306cOGGxWJinW7ZsWb9+/dmzZzUazUMPPbR06dJrcJ4/DhRFhaop3Z6YkBIAcJt/Dj9GzN+Opmn4t6Npmqbp0bT8UXxWwWAQQRDmHXV0dPb09ERERCAIgiAIRVEymTQxMeGTT7bPmDEdRdFgMOh0OlEU5fF4oTEKkiRQFGU+lqam5r6+/q6uLhaLRVG03+9XKsNlMtmF334Yht1999Kenp7Zs2e5XK6wsLCYmGgMwwKBwIiIRavVrlu3tqenZ/78eVwul8Nh+/2B+voGhSJMrVYHg8EPPvho69Z/hoXJhUIRQRB9fX0ej8fr9Wm13wQ/wWAwGAxGRUWaTCav1xuqnH2TE+rChLrvEjRd539OzD8J+LP14wX/dqFLDuiGu5J7IQiC5OTkhJ4mJibu3r2bJMkL7mndXiiKcrlclyrwd1uhaRouofmRIkkS/u2CweAP/kemKOom/Hfe39/f2to2NDQkEAh0Ol18fByCIDwez263WywWmqYHBgbYbDZzCeLxeFksls/n4/F4NE3X1tY2NDSeP183ODjIYrEwDNPptBqNhiRJs3lALpfx+fzIyMivvtqnUMjVajUTbPj9/o6ODrVa7XK5LlohWyAQJCYm+Hy+ysqqzz/f5fV6EQRRq9UFBTMMBv3wlmKxmMViffnlnubmlsOHjwAApk6dotPpJBLxBx98mJycLJNJv+2T397ezuVyu7q6MAwHgKYoOiEhXqvVlJfvv+uuRXq9/sIzgUZgwgmfz+f3+2/0uUBjw/zt3G738NQ4t6FAIDDKWz/QtTZuQ6tjjSXMZvPRo0dVKlVeXt54ncONhaKoWCwWiUYmRrytBINBu92OIAizNB/6EfH5fC6XC8dxqVR6o8/lBrNarcOXBV8U5IaLdwAAIABJREFUiqI31b9zmqb37t1XXX20srIqGAwODQ15vb6cnEklJcUcDofP51dUVLrdHhRFKYqSSiVOp0uv10VFRTIzlNhsdnX1sXPnzoWHh5tMJqlUShBEZ2dnaupEBEFnzy6ZPXuWTCYLBAIURQqFQubzoWna7/fjOKurq2toyJqcnMRsbGxsMhqNNptNKpXGxcVpNBEff/zPnTv/o1arhEJhMEicO1drs9nmz5+XkzMp9BYoitq587OtW/8VHR09dWo+iqI2m4PJRhUertBoIkItfT4fQZA0TeXm5gkEfARBRCKhXC73eDwdHZ0CgfDm+bvczOx2ezAY5PP5fD7/Rp8LNDZDQ0MURYlEIg6Hc6PP5UbyeDxms/lGnwUEwDiGE2N15syZdevWpaWlwbISEARBV+nEiZMvv/x/BoNeLpedOHGKy+Wy2ayqqoMnT54iCCI8XCESidxuj9PpdLtdbrc7KSlBr9cxl90ej2dwcPDIkepp06bgOF5be76hoRFF0WCQOHu29u67l9xzz91hYWEkSUZGGqKjo/v7+3GchWFYMBjQaDTx8fEDAwP9/f3JyUnBYPBf/9r27rvvs9lsLpfr8/mmTMn3er01NcezsjJDd1v0el1dXR2LxUpKSgxtbGho/OCDD4dXwlapuGKx6JNPdsTFxQ5/s1wuNyYmurW1lc/nDl+u7XK5CgsL5HK4ZBmCIOi6umHhREZGBpfLbWlpcTqdt/kdfQiCoKt05Ei1XC7j8wVVVYfCwuTMlyqPx7fZrAQRFAqFSUmJVqu1u7unrq4eAFooFMbGxgIACIJobGyKjY31+XzMwFRu7qSYmBiXy0XTZGtre15ebnx8HNMSAJCUlJCWNtHhcAQCAT5fIBIJaZo2Gjt6eno9Hk95+f7339+UlJSkVisBQACg+/r6yssPaDQRw7/nEQSJjY3Zu3ffnDmzJ03KZjY2NTUBAFAU9fl8XC6X2cjj8QQCvt3uGP5meTyeSCTyeLzksGJwfr/faOzIzs6GQxMQBEHX2Q0LJ5RK5TvvvPPzn//86aef/uMf/3ibD9hBEARdMY/HY7VaFQqFydTP4XBCF+4IAvr6+hMSEjo6OgwGfVJSUmJiYkSE+uDBw0Zjp1wuJwjSarUWFMzw+fytrS3MXiiKKZXhSmU4AMDhcPn9/r6+vj179nZ2dp47V9ve3p6SMiE2NpbL5ZrNloaGhoaGBo/H88Ybf25tbe3q6tbpdGp1qCYpolKphEKB2+0OBoPDp5BxOFwcx5nFJxRFVVZWbdv2SW9vn9HYERUVKZVK4+PjmPIUYrFocNDKpIgN7a5QKKRSSWdnJwCAz+d5PF6LxVJSMnPRou/yQUEQBEHXx41MS+dyudasWfP6668fPHhwxowZarX6wqBi/fr1N+TcIAiCfiyY9CYoinq9vuFJjSiKQhAExzEWi+XxeAmCwDAsJSWFpmmKotPT0yUSSUSEesqU/P/85/O6uvMX9uz3++12+zvvvHfkSLVWq+HxuEND1iNHqq1WW2RkZFtbG7MYOisrKyMj7cSJkwcPHiopKR7eA4oiAoGgtbXN5XKH1lIDACiKJEmSGYXYs+erV1/dAADw+XxarcblcnV397hcrqysTD6fLxKJFIrw2trauLhYPl9AUaTFMtDV1fXLXz4WEaHu6Oh0OBxisTgqKrKoqFAmgzOdIAiCrrcbGU6sW7eOeWA2m7dv337RNjCcgCAIujyBQMDn8+12O4qiNP3d/B+SJGmaRhDE5XK1tLRYLBYEQZiF1JmZGU88sT6UQiMuLtZms7tcLqHwuzJqAwMDPp+vvb2jsbExN3cSimJ6vY7FYvX09Jw5c7ahodHlciMIkEgkXq+3o6NTo4ngcDh9ff2JiQksViiqQSQS8YXJsvr6TAUFM6KiIgcGBmpqjhsM+rAwOZMsSyqV8ni89najTCbTaCL8/sB9993X09OzZ89XGIZRFFVQMCM3N/eee5YywxcEQfwoqtdBEATdqm7kV/Arr7xyA48OQRD049Xf33/+fJ3FYuFwOFqtNi0t9YsvvuTxeF6vl5kXRJKkx+PR6XS9vX02m43L5aEoSlF0T083RdETJ04Yno5v8uS8RYsW7tq1Ozo6SiIRUxQ9NGTt7OwsLZ3vdDqjoqJQlGmMJCYmKhThNA0aG5tQFEgkUpFI6Ha7v/76rEaj0em0bW3tGRnp4eHhoc7FYkl6elp7u5HNxkUiUSAQtFgs7e3GkpJinU539OixiorKKVPyWSyWRqMxGjsCgQCfz8dxrLm5eXBw8N57y+69d1kwGCwtnW+xWLhcrlarMRgMobIYMJaAIAi6scb8LXz27NnLvCqTyZRK5SgXQtx///1jPToEQRB06NDh8vL9VVUHBQIBQRBer3fBgtJFixZ88skONpvT1tbO5/MIgmBWVHd0dIjFIhYLd7lcNA0CAUIiEfv9gYGBgVAOJS6Xu3LlA1KppL3dGCpNXVo6LzIy8oknfjV5ch4AgCRJq9Xq8XhwnEXTFEEQOp1OIpEw0YtMJu3vN7HZbJ/PZ7PZQuGEw2EfGBgoLZ1PkuTu3f9lNhYVFc6dewdT99rj8aAoymKx3G43RZFardZms/l8fi6Xq1AoHn304TvumMNisVgsVmrqRGZ3kiTNZrPb7QkLk0skkuv84UMQBEEjjDmcmDt37g+2EYvFWVlZq1atKikpuaKzgiAIgi6usbFp377yxsamKVPymREGp9O5b195cXHRq6/+35Ej1VVVB5uamqVSKVOAQqFQsNlsk8ns939zja5SqY4dq6mvb5g+fVqoW6lUunLlCpvNdu+9ZTiOq1RKoVDY3NwCAAgEAi6Xu7Gxsbm5BUEARdHBYJCm6eETqxAElUplNE1JpRJmpQSPx/V6fQ6HY8mSxQ8+uILD4SxefJfFYuHz+RpNRCiSEQqFJEm2txs7Ozu7urqYu1Eej4epf7dw4YLQKAQAgKbp6uqjVVUHfT5fRUVlYWFBZGTkvHl3qFShxd8QBEHQ9TbmcGLNmjW1tbXV1dUAAKFQqNPpcBzv7Ox0OBwIgpSVlTmdTqPRWFFRUVFRsX79+scff/zyHbrd7s8///z48eNWq7WwsHDFihWHDh3Kzs5miitBEARBwx09evT48RM5OdkAfHOdLRKJkpOTdu3aXVIy88knH3/00YcbG5vMZjOO42+99ddDhw7L5TKtNoIkKRYL9/sDLS0tYrHEarVe2LlUKmXSxba3G8vL9/f29oWFhVVXH2UCEo0mghl/aGhoDAaDJpNFJBKHLvdZLLyhofG++8qWLFnc1dVls9mlUkl0dHROziRmgXhsbExsbMyII8bFxWZnZ+3bV06SlFarZXoLBgMtLe0DA4Mmk0mtVocaV1RUPv/8H5TKcJVKnZWV2dfXd/Tosf7+/p/8ZJVSqbwGHzYEQRD0w8YcTjz88MNz5sxRKpUvvPDC/PnzQ5n79u7d+/TTT1sslvfffx/DsJqamoceeuj1119fsmRJVFTUpXo7efLk2rVr+/r6mKcGgwEA8MorrxiNxk2bNmVnZ1/Je4IgCLp19feb5HJ5KJZgiEQiNpvd29ubkZHO5XLT09MAACRJbtjwGofDGT4jCMdZJEnabPZgMHipQ+zff6Cq6mB19VGRSGixWM6dq0VRNCYmBsdxv99ntVplMimCIAAgXV09EomYw2HTNG2320Ui4Zw5swsKZoz+7cjlcqlU0tXVrVarvF4viqKBQNDhsKemppjN5pMnT82fP49p6XA4Dh06rNVq4uPjmS1isVihUFRUVBoM+uXL7xv9QSEIgqBxhP5wk+/bsGGDyWR6//33FyxYMDwL+KxZs/7xj3/s27dv48aNAIDc3Nzf//73JEmeOHHiUl319vauXLmyr6+vpKTktddeC20vKipyOBzLli0LhRkQBEEQg0n/euF2BEFomh6+ZWhoSCgU0DTFZJId8VKoVNwITU3NVVUHW1paJ0/OmzhxYnFxUVxcLIIgHR0dRmNHX59Jr9dHRERwOGySJAwGnUwm5fP5EolEoVDceeedRUWFY31HanVEenqaVqvl8/n9/SaxWDRx4sSsrEyZTGqxDISatba2lZfvDwsLM5nMvb19drsNAJrFYkVERLS1tY/IHAVBEARdN2MenaipqdHr9ZmZmRe+lJKSEh0dvW3btieeeAIAMHXqVABAW1vbpbp6++23rVbr2rVrn332WTAsJ+z69ev1ev1jjz325ptvvvTSS2M9QwiCoFuYUqmsrj46YqPNZrXZ7AAAv98fSoZBUVRkpKGzs8tkMslkMg6HQ1GUx+MZGhpSq9U6ne6i/Z84caKm5nhu7qTQAIhMJiMIwmazZ2SkR0dHi8XCgYGh+vr6hoaG8HBFXFyc2+12OJy9vb3z58/l8/ljfUcYhsnlsokTJ3q93szMDIGAj+MsAABN0yj6XeA0ODhoNpvPnj1nNHYAAKKiIkUiUUJCPJfLJUnS6/UOL7wNQRAEXTdjDidMJhMzs/ZSmCqnAAAmf7nH47lUy/Lyci6X++tf//rCl5YuXfryyy8fPTryJxOCIOg2N2lS9gcffNjR0REZaQAA8Xg8dXX1zc0tBBE8cqT6zJmvp0+fNnXqFAzDZDKZWCxRqyPEYnFjYxOzO1NzevLkPJXq4osNzGaLVCoZPpmKy+XSNM3n83k8LlOKTqVSer2ezs4uo7HDYhlAUXTWrJIHHlheXFx0Be8oIkJttztIkhgeigQCAYfDqdFomKcURVVWHuzr62ez2TqdFkVRj8fT09Pr9XqVynCtVnMFYQwEQRA0LsYcTqSlpR08eLChoSEpKWnES83NzUajcfLkycxTJqXspW6AAQD6+vpiYmIumlUWQRCtVtvY2DjW04MgCLq1paWlPvHE+hMnTh47VsPlcltaWnp7+2JjY9LSUt1ud1tb+7595Y8++vDixXex2ezU1IkHDlRMmJCclJTodntwHMMwtKWlLSoq6lLZkBAE+f6cKaBUKhsaGgBAQjEGTdNut3vFivtnzix2uVxyuTwpKfGKc7bm5uYUFhacPHkyOTmJzeYAAPx+X11dQ3Fx0aRJ36yga2horKioSExMdLtdTKEJPp/P4XBaW1uHhoZKS+cPL6MBQRAEXU9jDifuvPPOgwcPrl69+rXXXgtFDgCAEydO/PKXv6Rpev78+QCAhoaGp59+GkGQgoKCS3UVGRnZ399/qVd7enpC96UgCIIgBoIgpaXzExISUlMnlpcfaGpqmjmzOCYmisvlAQCkUimfzz979lxOziS9Xj9nzmyTybx16z/FYjGfz/P5fHa7o7R0/pIld110AQYAQK1WWa1WmqZoGthsdpfLSZKEXq8/d652YGCgtva8y+Wy2x05OZPmzZs7YUKyz+fjcDhXM9EoLCxsyZLFKIru21fO5PTzeDyzZ89aunRJaDC8vb2dx+PFxmoqKiopihIIhBiGBgJBn8+n1WpnzYJJySEIuk3RNJ2Tk/Pss88uXLjwRp3DmMOJsrKy6urq7du3MymboqOjAQBGo7G9vR0AMGfOnFWrVjEPCIJYvnx5KAXHhVJTU7dv3/7pp5/eddddI17as2eP2WzOz88f6+lBEATdDhIS4hMS4js6Oq3WocTExOEvabWagwcPFRTM0Ov1XC539eoH09JSW1parFabWCwyGAyTJ+ddJhP35Ml5DQ2NJ06csNns9fUNJElSFIXjLLlcRtPUyZMnURRlsznHjtWkpExQKMLEYvHVv53k5CSt9uczZkw3mUwIgqhUqvT0NGbGLMPn82EYplSGz5xZ3NnZGQwGjcaOqKjIyMjIEUW4IQiCbjiz2dzfb/L7/eHhCoPBMDx30bjbtm3bDc9dNOZwAgCwcePGGTNm/PGPfzQajUajkdmoUCjWr1+/fPly5umECRMWLlz4s5/97DL9PProo7t3737yySeHhoZCEYXNZtu1a9eLL76I4/i6deuu4PQgCIJuEx6Ph8MZmaCJKTLtcrmYpziOT56cx1S2Ho3IyMipU6fs3bvv9OkzzO7Mkui+vj6Xyz1//ly9Xg8AsFqtO3f+Z2BgYOXKBy46Z3WsxGLxtGlTL/rS11+fPXCgorGx0ePxYBimVCrValVGRjqfz29oaGDOB4Ig6Gbg9Xo//XRnU1NzRUUls2XZsnsWLJh/mcn/V8bpdP71r389efLk4cOHx7fnK3Al4QSKokuWLFmyZInJZGpra/P5fHFxcTqdbvjQ+RdffPGD/cTFxb366qtPPvnks88++/vf/x4AsGnTpnfeeQcAgGHYs88+m5qaegWnB0EQdJsQCoU+n3fERooiA4HA1cw+8nq9/f19MplULBYjCMJms0mS7OjocDodLS1tTIEguVyemjpxz56v0tPTxlRoYqz27SvftWt3bW2tVCrt7zdxuRyj0ZiQkJCVlelyuaxWW0rKhGt3dAiCoNGjaXrr1n999NHHMTEx+fl5GIbb7Y7PP99ls9keeuinYWFh43gsj8dTU1MDAEhOTq6rqxvHnq/AlYQTISqV6lKL+UZp8eLFeXl5GzZsOHHiRGdnJ0EQOp0uLS3t8ccfv3CpNwRBEDRcQkL8f/7zmVqtkkploY2dnd0FBTMSEi450fQHnT17jsPhyeUKPv+bOVH9/SY2mw0AMjQ05PN5mXUafD5fJBJ1d3df5bu4FI/Hs23bJ1u2fFhbe54pbWGzWWUyqVAoqq2tZUYqli+/Ly8v9xqdAHQtBD3+gNvHlQgw9lVdgUDQTaipqXnLlg9SUiaEZmCGhcnFYuH+/QeSkhLvuuvOcTyWSqXavn07AODQoUPLli0bx56vwBX+Zw4Gg93d3ReWRmKoVKrhc14vT6vVMpXvCIIgCOJSlZUgCIKg4U6dOl1XV89msz//fLdMJjcYDGq1cmhoyGQyL126+GpSWTgczoGBAan0u0xNNE0hCIJhqNls8vkCTDgBAMAwLBi8JvXjCILYsuXD9977R3d3V1RUJIZhXq8Xx1ksFkculwFAi0SiX/zi0cLCAibRE3TzG2rp6z5S77O7maeSSGXk9BSubLRXCxB08zMajSwWKzxcMXwji8VWKBTt7cYbdFLXw5i/hQmCePHFFzdt2hQMBi/VZufOnTk5OT/Y1ezZsxcvXhxaX4Hj+PBfhd/+9rednZ0ffvjhWM8QgiDolldevv8Pf3hJJpOq1WqSJEwm8+nTp1NSJuTl5a5b97Pp06ddTecKRRhJkiRJslgsZguO4wRBEgSl10ewWN+kZKVpyu12M5Uoxt3p02f+9a9tBoNucHCAqSnB4XC4XK7JZMrLyyHJqMjIyMLCAjabfS2OfhMKev1uky3g8nElAoFKOspb+2SAcPUN+WxuFp8jUEk54mtfnYOmfQ4PTVIciQDFvlt+aqnrbC//eqC+ix8mxth40BfoP93q6h1KXjqFr7jCFMMQdLPx+Xw4jg+v28Ngs1k+n++GnNL1MeZw4v3333/nnXc4HE5GRsalcoMkJyePpqvz589PmTLlUq+eO3fu/PnzYz09CIKgW57ZbD506LBOp42LiwMAREdHEQTR399fX9+Qnz/56lcyTJmSLxQKTSZTZGQks0UoFLJYLIqiZDIZny8AAABAt7d35OXlpqSkXOXhLqq5uVkoFEqlMpqmKYpi8qJwuVw2m22z2fh8AY7joWjn1kbTdG9NU+/Jlu7qBmZLVGGqYXpKWIL28jsONvV0VNZ2VNUyT/X5Saq0aF1+EoKNQ5IZMkD01DTZO8w+m4vF5wojZLq8xIGGbtPZdjJAAABQDFOlRWlyEzA2TgaIrkN1g409YUl6ZpUlBwj4YeKe4018pSR58SWvBCDox0Uqlfr9fpIkMOx7F9hut/vyNaB/7MYcTvzzn//UaDSffvrpFS9RH16JYtu2bQcOHLiwjd1ut1gsERERV3YICIKgW1h9fUNlZdXUqd+l0sZxXKfT2e32hobGkpKZV9wzQRAVFZU1NccjIw01NTVDQ1aZTCYWi9xuN4fDRhAERdGOjg6aBlarNSsrMz09Ta8f53QlDI/Hy+GwZTJpZGSk3W4P1cjDMMzn8zmdrjvumH2p0hm3mN6appo3dwnCJcqJBozNJryBvlMthDeAIIg8/pJT2uydltavTg/Ud4Yn63EBhwoStnZT99EGIhCMLk6/ylMivIH6fx9p2XOKLxfiPA4ZIDqqatv2nLT3DEl0Co6YD1DE7/B0HW2I7x6YsHSqo2eg4+B5ZYph+F8MZWECtczZO0T4gjj3togMoVtecnJSQcGMpqbm+PjY0BiF1WobHBy6tZNGjDmc6OjoePzxx68m3VVLS0vosd1ut9vtF23GZrOfeOKJKz4KBEHQrcrhcHA4nBF3vwAAAoHgUt+oo7R9+463335HrVanpEwAAGltbTGZTEzd69LS0tzcHI/HYzabmdIQOTmTYmKir9EIvlAo8Pn8QqFQpVJ1dHRQFC0Q8DEM83h8vb39S5bcVVxcdC2Oe7MhfIG+k62CcIk0+pvEJ2wRNyxRbznfyRbxZHERl4qpeo42mM8ZlRMMAEUAACiHLTaEIygyUNcVkRXLlY55xQIZJAANmElWXdX1rV+dCk/WsYXfTFJgC3k9R+s5YoEkUomgCACAJxNyZYKW3cfDErU4GwcAYOyRMQOLywY0HXD7YDgB3RqUSuX06dNomj5z5muFIgzDcIfDYTKZ7r23bMqUW7mW2pjDCZFINPpl1hfV0PDNcG1SUtKKFSt++9vfXrQZj8eDC+wgCIIuxOVyg8EgTdMjLiUDgcDVZLNoampuaGiMj4/XaCLAN7+LUzo7u+vq6n7726fmz5/L1JegaRoAwBw6VN1i3CUkJLhcrsHBwcTEBAzD+vr62tuNwWCQxWLNnFl03333qtXqa3Tom4qr39pVXa9MMQzfiCBAoJL4HR6/w8OVCC7ciwwQbrOdpxAzsUSIQCXtPtYYWZQ6+nCCpunBxp7e400+uwfQNEfCV2XEDDb2CpTSUCwBAAg4PYSfIAcdfoc71DlXLGCJeLa2flV6DACADBLotwtvvj3PIACAxbtdFsBAt4Pi4iK5XB4eHj4wMEDTdFxcbGrqxKKiwlt7cuaYr9dLSkoOHTq0YsWKKz5kKBv6HXfckZ6efjXJ0SEIgm5D0dHRBEGYzWaVSkWSJEEQHA4nGAxYLAMxMdFX3G1DQ0N19dH8/O8K3uE4KyYm2uFwMOMhzMbrM8UoIyP9gQfu/+ijj3U6rUKhEIvFYrGkr6932bJ7/ud/Hrm1f5iHI/1BAABywc01ZgvhC4KLLWMmA0GapjEcG7kXhoX6HKX28q+/3lzOEfO4EiGCIoONPa1fnuIrxBzZ98IYKkhiXBYVIAjf9zpncdkBt0+sDdPnJw219Eqj1aSfCHp9NAA4l+0225UpkSz+OJRBhKCbR0ZGekZGejAYDAQCAsFFAv5bz5jDid/85jelpaVvv/32T3/6Uwwb+VU1Ju+9996FG/fs2dPW1paenn6ZVdoQBEG3s9jYmNWrH3zrrb9iGI6iCIoiBEESBLFgQeml1mGTJHn27Ln29nabzS6RiOPj41NTJ44IDJxOJ5fLvTAnCY/HdTgcV3aqRmPH4cOH+/r6/X5/eHj4pEnZmZkZowlIUBS9//77wsMVX399liRJAIBWq8nIWDV79qzbJ5YAALCEPAAA4QvgnO/9XhNePyIVcEQXT4jC4nFQHCM8/hHbCV8AAMARjTa/k73DPFDfJdErhBFyZotAJXX2WXuONoSnGATDMjIhOEoRJAAAQb+3zpsMBllcNs5ja3ISOg/XObqHAKDdZhtN0Sw+JyxJp86KHeXJQNCPC4vFun2+rMYcTlRVVf3kJz/ZsGHDBx98kJOTo9FoLgwq1q9fP8revvrqqw0bNhQVFT311FMAgGeeeeb9999nXlqyZMnGjRuvMmKBIAi69SAIotPpDAZDbe15m82GIKhCIWfWMFw04Z7P5/voo60ffPAhn8/n8bher8/j8TzwwP333Vc2vD2fzw8EAhfu7vf7mVStY3Xy5Kldu3YfO1Yjl8swDD9x4sTHH2/96U9X33tv2Wi+2zkczsKFC+bNm2uxWAAA4eHht+EMWKFaFlWU1nu8iSPSI9/OXKKCpLvfqsmOu9R9fQRDZTHqnmONPKWExf12KhFFO7oshukpYkP4KI8+2Nzbf6ZNnf69IS9RhIzF57h6h8LiNeDbyJArFZDegDBCxh4W4QQ9fr/dK4lUAgBUmdGqtOi2vWcInx/BMKFGTlOUu9/aU9Mki1GjFwykQBA0StOmTevp6bmx5zDmr+ZHH32UeeByudrb2y/aZpThRHV19apVqwAA06dPBwAYjcZNmzbJZLJly5bt2bNnx44ds2bNWrBgwVjPEIIg6NZms9kOHz6CYdjChaUul4sgSIGADwA4cKBi0qTsuXPvGNH+v//94uOPt6amTgwLC2O2DAwMvvfe+7W1tTExMQiCqNWqadOmxsbGer3egYFBhSIstK/L5bLZ7HFxY76FbLfbv/jiy9ra2pycbAT55o61yWR6771/xMbG5udPHmU/OI7fzln+UAyNLk4jvP7+M+2CcDHGZgV9AY/ZppucFFmQepkd9VMnOHuHOirP8cIlLB6bChKeQac6LTqqMBXnjPaOacDpZfHY4ILRJKFKhuCotc0k0ilwDk5RFBUkOWI+4Qv6rE5ACwFAAi6vs3sgema6Kj0aADBY322p7YgqmIhgKBkgcB4b57GDLl/rnlPKlEh1ZsyVfT4QBN0MxhxOvPLKK+N17LfeegsA8Nxzz61cuRIAsGfPHoqifvGLX6xZs2blypVTp0796KOPYDgBQRA0QkND4/79B/LzJ7PZ7OHDC0qlsq6ufkQ44fF4amvP6/W6UCwBAHC5nF6vd9eu/6anp+I4brXa6urqZ84sfuCB+z/+eGtkZKRcLkUQ1G53GI3GRYsWTp6cR1FUIBDw+XxisRhFf7hwwflIqp1cAAAgAElEQVTzdeXl+/Pz80KxBABApVKZTKavvz47+nACkkapku7KF6hkbpOVpmgBhhmmTjBMm3D5etJsITflnmlibZjNaCL8QRRDI7LitHmJkm+HJmiK9g44/H5bQCoWhEsuOtCBsXEySF64HeeyZHEajIN3VzegGEqRlDY3IXPNHJzLsraZeo41AgC0uQkRmTHRMzNwLhsAYO+04DwOR/q9eeRsEY8t5No7zTCcgKAftTGHE/fff/94Hbu+vj4iImLNmjXM0yNHjgAAFi1aBAAwGAxxcXFtbW3jdSwIgqBbhsPhwHH8woLQAgHf6XSSJDl8KpHFYtm//0BmZkZoi81mNxo7fD5fMBjUaLRyuYyiyLq6OpqmV6y4XywW1dXVHzhQAQAoLCyYMmVyQkLCn/70xrFjNXa7ncvlRkYaiooK58yZHaoFcVFDQ0McDofNHnmRKhKJBwcHr/ITuN2INGETlk6lSDLo9rOFPAQd1Wp4loAbMzsTABBw+3Aue3iNamfvUOPn1V6ba/DrDhTDdPlJ6vRo7eQk9PsV7sTasKDHH3T7WILvMoYFfQGf06ubkqRMiYwqSA2VsROqZQCAoNuXuCCXIim+Qjy8CDfhC2Dsi8xowtg44b3IFDsIgn5EbuQ8VJvNlpiYyDymafrUqVMGg0GpVDJbRCKR0Wi8YScHQRB0s+JyuSRJUhSJohgAIBgMGo0dQ0NDfX19ZrNl377ygoIZl8kY29fX193drVQqvN5vSkagKJaQEH/o0OGcnEl3373U6XQuX34fQRAqlfL06TMff/zPffv2ud0ePp9HEMSpU6cPHjzc2tr205+uvuhSDQaLxSJJEgB6xNpukiRun+WJ4wvFsOEX6KPHFnzvH4N30Nn02bHemia+WqpIi8IR1Nbe33O0IeDyxc7JGt5SkWKImZXRUXFOYlByJHwAgN/pdXRaogtT1WnROI8d/v0MtgAAloArEVzk3x5LwCX8QQAA4Q8GHB7CH8Q5LLaYT3iDwxPOQhD0YzSqcGLp0qUAgJ///OfFxcWvvfbaD7Yf5doJnU7X1dXF3Eg7cuTI0NBQSUlJ6NXe3t5QaAFBEASFREdHzZgxvaenV6vVuN3uM2e+bm1t5fF4Npudx+O98sofa2vPr1q1Ui6XAwDCw8OLi4taW9tCgwkej4fD4Xi9/ujoKKHwm8tTFMWEQgGz6FkkEjEpvPv6+iorq6qrqwFAYmKimYxMbrfbZDJ/9tkujSZiyZLFlzpJvV4fDAaHhmxyuSy0kaLIgYFBg0F/jT4ZaDS6jzX21DTJE7Q0QuMsnMViSQxKjMUabOpRZcQIVdJQS4yFJy6ajHPYbrOtp6aJ2Rg/Nzt2TjY+xmIRshg14QtazncE3H5nzyCCIDRN88LEpD8giVKN59uDIOi6G1U4UV1dDQBYsmQJAOD//b//94PtRxlOTJ48+cMPP9ywYcPy5cvffPNNAEAonNi8eXNfX19R0W1R9BSCIGhM9Hp9UlJiVdVBgiD6+vra2tplMrnL5UxKSszKykQQZM+erxSKsJUrVwAA+Hx+aurEiopKHMelUolAIEBR1O8PeL3e+Pi44ZORKIoekXCptvb83r3lg4ODarU6lN1VIBDw+TwWCzcaOzwez6XWUSQlJS5bds+nn+5MSEgIC5MjCOL1epqamqdMyZ82beo1+2ygH+bosvDChCiOMhl4GXyVpPd4ky4/aXg4AQDgSgQT7pnm7rdGFaUBmuaFiUQR8gsXZ/+gsHhNRHbsuY8qOCI+VyIAGEr6/M7eAa6I73e4x+FdQRB044wqnLjnnnsAANHR0WBcl2I/8sgjO3fufOONN9544w0AQFRU1Jw5cwAAS5cuZQKY1atXj9exIAiCbiWLF9/FZrOPHas5cKAiEAiQJJmUlJiUlMiUTIqMNBiNHQ6HQywWB4NBDMMkEkl5+X4Wi8Vi4QRBDg4O5udPTkiID3Xo9/udTqdWqx1+FJvNxmLhACAjpiex2WyapmmadjgcUun3rj5DUBS9774yFEW3bv0niqIYhgWDwTlzZi9cuECn012DjwQaFYqkyACBskb++qMoimAYU5hiBARBhBHyUOmJKzwuReEcliJRh2IYRVEAALaAE5akpwnSdKZNMykeY992WYAh6JYxqv+9GzduDD0ex6XYer3+s88+e/nll8+fPx8dHf3SSy8xOcWtVqtQKPzd735XXFw8+t7sdvv7779//vx5kiSTkpJWr14dHn7x1Noej6esrGzExqysrOeee26sXUEQBN0QbDZ78eK7DAbDgQMViYmJCkWYWCwODSCIRMIDBypWrHhAJBL961/b3nvvHxpNxOTJk10ux9CQ1WazpaenYRhGECSOswAAXq+nrq5h9uxZkyZljzgKc+U3Ynk3RVE0DcAlylyESCSShx76aXFxUV9fn8/nUyqVCQnxV1bCAhovKIay+BzSN7IwNkkQFEFyrtkyBs+AkyKosEQdRyIg/QEaAJzDRhDgd3q7qhviF+RK9PB3FoJ+rG7wzYDExMTNmzeP2Lh582aNRjOaRIQhDofjN7/5jdVqLSwsxDCsoqLi17/+9auvvqpQKC5s3NvbCwDIysoa/qrBYLiCriAIgm4guVzO5/PDw8PE4u8lWSIIqrCwgMXC6+sb3n33/eTkJJXqu+npNputuvpYcnLysWM1XC6Xpmmfzzdv3ty7717KLJkIiYyMRBCg0UQ4nc5QnlmKIj0er0AglMvlEomEKZ93KQiCxMfHxcfHjd+bhq6WPDaio6oWl/HRYamWnF2D+vwkaYz6Gh2UJsiemqbwZD2CAJz73boLFMMAADRBXaPjQhB0HVxhOOF2uz///PPjx48zl90rVqw4dOhQdnb25e9UjdIVjIN/9dVXPT09L774YlpaGgCgoKDgySef3L17N1PRYgSmduBPfvITvf4iywHH1BUEQdANpNFEzJxZ3NjYOCKcMJvNarVKrVafOHGSy+UOjyUAAFKpNCJCnZGR9uCDK0wmE4IgarV64sSUC7/AJ05MWbZs2T/+sXloyAoAEImEJElaLAN8Pr+oqGDWrBIA/Qhp8hJsHebWfac5ciFXzA8giHfQqUjSa3ISrixz1GhwxHxtboLLZB1eNhsAEPT4tLkJTNooCIJ+pK4knDh58uTatWv7+vqYp8x9/VdeeYUpa52dnX3Zvb8TCPxAqmkURZnpTz9o7969UVFRTAAAAEhISJgwYcL+/ftXrFiBXLBirLe3F8MwjUZz9V1BEATdQFwuNy8vd//+AywWW6fTYBhOEMGuru7+/v5169biOO5yuS6aMZbL5QYCwby83Mv3j+P48uX3slisw4ePVFUd7OjopChKJBJNnTp14cIFyclJLpfr2rwzaCSaoq1t/c7ewYDTy5HwpVEqse4Kx8xZPE7y0qmomDPU2oejGIvFksdqNDkJimSds2fQM+BAUIQXJhZprmqxxAhsEU+kCes73caVCkNluakg4ewZVCTreXLR5XeHIOhmNuZwore3d+XKlVartaSkZN68eaEkTkVFRa+//vqyZcsOHjwYERExmq6Ytd2XsWjRor/85S8/2E8wGOzr6ystLR2+ceLEiefPn3c6nWKxeET7np4esVj83nvvHT161Ov1RkVFLVmyZNKkSVfQFQRB0I1VUjLT6/WePn2msrKKxWIFAoGiosKysmUzZkwHAPD5fK/Xa7FYPB4PhuFisZAZx/D7fULh5Woqh0il0jVrfpKXlyOVSvbuLWexWBKJuLOzs7KyisvlDl/MDV07ZIBo3lVT/2k1xsIwDovwBSOyYuXxmphZGej3k3HRNO2x2D0DDgRBeAqxIPzipQbZAq6hOFU9NREngEgmwXlsz6Czfvvhxs+OMQ20uQkibVj0zHSu5Js61kGvv7emydE96Hd4OCKe2BCuzU3EuWMoIRJVnOa1OrsO1fHkIozLIn1Br9Wpy0+OKcn44Z0hCLqJjTmcePvtt61W69q1a5999lkwLCfs+vXr9Xr9Y4899uabb7700kuj6SoqKmrElkAg0N/fT1EUhmGFhYXp6emj6cdqtQIARtRnZS79rVbrhTFAb2+v1Wo9d+5cYWEhQRCHDx9+4YUX1q1bN3fu3LF2NRxFUR6PZzQnfAtjVm0CAJxO5409E2ismJSRFEXBvx1BEMMTaF4URVE0Td8kn1VxcVFKyoQZM6bb7XaZTGYw6MPDw5lxg2CQaGpqOneuls1m0fT/Z+8+4+OqzoSBn9vL9KLpoy5Z3VW2BcaywYBNM2BCd0wCCSEbdjdhTSCbEF42CeWXvglZYBNIARJKjAHDgo1tbIML7rIlW73PaHqf2+/7YYwQcpFkZORy/p/se2fOOTMjae5zzznPA/LzvWaz2em0h8OR3I6I8bQvy/KGDRsPHWpevLgx9+eR5/mdO3clk8mvfOUmr9cjiuJZ8lacr7o3HGh9/WNDoZ0yaRAEUVUQ7Qv07WiRUNXdMG34YXwi07PhYDaU8O/pAAA4ZpfovFbPgspR64tyZFlGUAQwWFbi5WDqyKsf+Xa16QuspJ5VAUj4I/2ftCZDsfKbGjACFxLZ9rc+6d/aTBlZnCYlXuLf/cTX1FVy7RzaNK64FAAAcFBw9SzKrk/2htK+CKal7OVOZ2OlTCHw52dCVFUFAGSz2TFXeZzfOI7LvRXQlJtwOPHBBx/QNP3973//+FM33XTTz372sx07doyzqY8++uj4g4IgvPPOO4899piiKHffffd42sn9GRq16jeXPCSRSBz/+MLCwsrKylWrVpEkCQC49dZbv/vd7/75z39ubGycaFMjqaoqiiLP8+MZ8/lNVVX4PpyjFEWBn52iKMOB8cnkvsPOnvfKaDSOTNiaG5jP59u3b59OpxfFsE6noygyEom0t7fr9Ya77vpqbW3NOMd/5MjRf/5zTU1NjUajkSQJAIBhWFlZ6a5dn3g8bq/3K/DH5oySMnykbZCxGXA9PRzoUhatmOUCTd2mWg9G4AAAWZDa39jp39Gq9VjM1R6gqil/1L+vMzUULbl+7smqzsmyLMvy0L7O3q3NlkoXRpGyqgAAcD2tK7Z1bzyoL3NYa/O7Nx3o29ZsLHcOT0cwNl3/zqMogxdfVz+BF0MgpJkVWvlw2yBAkHDrAJ9Mm6u8jjklCDaB/CsQAECSpNzv4wVLFEcnKIOmyoTDCZ/PV1xcTFHU8acQBHG73UePHv0iAyJJ8vrrry8uLr722muffvrpf/3Xfx3zKblUJNlsduTB3ERBLgX7KKPaZFn22muvffbZZ7u6unIJYcff1EgoilIUNSmb0c9duasKBEFOuFwbOpvJsiwIQu7HeKrHMsUwDBtVze14uZ1UZ/nv+549e/fs2XvllZd3dXUFAsGenl4AgNvtSaWSjY0LR03DnkIkEqEoymq1jDpus+X5/UMAAAzDcndnoDMhEUyF9ndbq73456t/sBYDhqAopzB6BgAwdKTT/3GrpdJDsBQAQFVUMc4BRW375850X8RU5rTPLLZUuIcr0PE8rygKjuMEQUjhNKPX0NrPfc0RBJHVsVIkQ6goH0jqXRZGx448a/RYxVgW4eTxT1DEOocCOzsSnQF7XRFGk4ooZ3yxo/t7cATLb6z+Iu/SBSV3V54kyTH/Up3f4I7Ws8eEw4mCggK/33+yswMDAyfb4jwhdXV1FRUVr7766njCidw9uVGzB7l5huHMhqfmcDgAAJFIpKys7LSbyl1Djxl1nN+G52cu8PfhXMRxXC6cgJ8dhmFjJqpGURRBkLP8vRoaCtjtdo1G4/F4SJLS6bQkSdrt9vb2jnQ6Pf7BE58adXy4ojaO42f5W3FOE6gkimH45z8CWZblJJ/NCGIgxeQ7UAwVQinGoGENx67sw60DwcO9OEMiAKT9USkj9G9prrtzccmVs3IPkCRJURSSJFmWxRGMoMnjP2KcIjGAoqIa2NdlrfSOfoBRG9jXVXX9ReP/9DsO9MTa/Ll0sQAAQBJ0kYMgiWRnAF9Qc+bySp1neJ5XVZWiqAv87g+CIDCiOEtMOJyora197bXX1qxZc8MNN4w69d577wUCgYaGhkkZmclkamtrG88jSZJ0OBwtLS0jD7a0tOh0uuN3O/T19b300ktXXXVVbW3t8MFwOAwA8Hg8E2oKgiDobJarh93S0jI0FOjt7cNxXJYlrzcWiUTS6fT427FYLIIgcFyWpj83GxOPxyyWU22iVRRl//4D7e3tkUhUr9d5vd76+jlw6nKiGIvOPbc8HYgRzLFrx2Bzb6TdJ2Z4IZlJDIR1DlPN7YsUQULwY/eqs+Fk8HAvbdQQGhqogNTQ1mnulC8abh0wl7tMRaOLS5B6VsyMXq6mqkDK8pSBRXHMPbecj43+mVFlBQCA4uO9QS5meS6aYq36UVeArEU/sPNo8ZIZMJyAoHPUhMOJ+++/f926datXr45EIsMRRSwWe/vtt3/yk5/gOH7fffd98WGFQqF9+/aNvxb1kiVLXnzxxfb29tLSUgDAwMDAoUOHli9ffnzY6nA49u3bFw6HH3/88dwsoSAIb7/9ts1my5WhGH9TEARBUyKdTm/fvqOvrz+RSJjNpsrKylmzZh4/o2Iymbq6uvr6+kwmU36+BwAEABCPJ/r6+pubm6+/fvk4u6uqqrziist37dpVU1ONYce+NXw+XzQamz697mTPEgThpZf+/sILf9ZqtSzL8LyQSCSWL79u1aqVJpPptF73BYo2aPQeq29vB6llCJYKHOrx7WlXZAUBQGs3cvF0rGsoE04655RJ2WMbc7ORJIpjhIZWgSqLEk4SAACNwzh0oMsyzXN8OGEudUqckArEtLbPduCkfGHHjGJLmYux6DESz0SSlPFzsxDZSMrbUKGxjXfVnCxIAAD0uD0SCIENn4Ug6Fw04XCitLT0qaeeWr169SOPPPLjH/8YAPDCCy8899xzAAAMwx555JGRd/1P7eWXXz7h8XA4/NJLL6VSqaVLl46zqSuvvPKDDz74r//6r9x1/7p160wm03C+182bN//lL39Zvnz58uXLCYJYtWrVH/7wh9WrVzc0NHAct23btkAg8KMf/ShX4+LUTUEQBE2tUCj05z//dd26d4xGA0XRmUwmHo/feecdd955+6gb/1VVlQMDAwRBjphcVQWBLyoqSiZT8Xh8nNsntFrt8uXXSZK0des2s9mEYXgymUwkEt/61jdnzZp5stwyGzZ88Je//LWmptpqPVYeIZVKvfPOuxqN5p57vg5v0ExI0ZIZQjLbuWEfRpHBwz2yKGEEzph1bJ4BQRFapwm39mM0KXJ8JhBnbQZZkFACAwCIaV7rMNEWHQAAQRCcIYTkCTIQmstcNbc1Hnr5QyGeIbUMQAAXz/DxdPGSmYYCGwDAObOkd1szRuJahwnFMUVR0v5oyh+dtnzeyBLXp0ZqaARDxSzPgM9VmchNjMBKdhB07jqdMnY33njjvHnzfv7zn+/evbu3t1eSJI/HU1dX98ADD1RUVIy/nf/4j/84xVmPx7N69epxNmUwGJ588sk//vGPb7/9tqIolZWVd9999/B3GMdxoVBoOIvrsmXLWJZdu3bt66+/TlFUaWnpQw89NFwE49RNQRAETSFVVV9/fc369Rvq62czzLHLr3A48tJLL9tsedddd+3IB5eVldbU1OzZszcYDJIkpShKNptxu91er2f79h2Dg77x78auqqo0m++urq4aHPTxPJ+XZ62pqZk5c8bJFk1JkrR//wGn0znyj6dWqy0pKR4YGPD5fJOyy+7CQemY6lsXWqu8nR/sH9h5VJOnJ3UsqaVz+6oRHKX0GjHNlS+rb393N5/MiBlOTPNShhOzotZl5iJJDMdIHaOICkaeoFIEgiClS2drHcbg4T4unkYQYK302uuK7LUFuQe46stm3XNloKl7YOdRlMBkUXbPLS+6dLqnoXL8rwLFMVORffCTNsaqJz4NQlRFTfQFCxfV6t3j2usIQdBZ6HTCCQCA2+3+1a9+BT7NU3Z6a2H/7d/+7YTHEQQpLCy84oorxv9VBwAwGo0PPPDACU8tXbp01ERHY2NjY2PjaTQFQRA0hXw+n8/nKy4uGo4lAAAWi9ntdjc1HVq2bOnIzbIoik6fXofjeDabzWazGIbpdNr8/Hyapnt7+8asrTGKw+G48cbRW+ZOJhaLCYJgMhlHHTeZjJs3f7h8+XUwnBgXVQ0090bbfdloiqBJjd1oKXZiJM7aDCj+ua9vjMSTA2H7rBJTqTN4uNe/tyOU7gcAkFpa5sTg4d5sOEkZWCHNnayWNoIizlmlzlmlsighCDJ6RwSCFDTW5FXnexdU8YkMpWP1Hgt7khp5p+BdUJ3yx3o+bGIseoIlZUHKhpKOWcVFl00f/x4MCILONqcZTnz2fBzH8dNs5MEHH/yCvUMQBF1QgsHQ5s0fNjTMH3XcaDSIohiNRm022/BBi8VCEIRWq62trVEUZXhzhd/vX7So0WYb7+a005Bby3R8hancgTETZ0EAAEVW2t/ZffiVrYSGIllakRU+ntY6zKqiyLw0HE4osgIUReYlvceitRmYCo+9rkhIZiMdPlkQaIMWo0gVKOlgPHSkv/rmS/Jq8k/db66KxQmxVj1rPf2sJLHuoWBzn6qo+vw8mRNJLUMbNJ6GCs+8aVqn+bSbhSBoyp1mJNDX1/f73/++ubm5s7OTpumSkpK5c+d+85vfzJWAgCAIgs6E3IW4qo6usperuzfqMp2iqOrqqs2bPzSZTEbjsRvJ6XS6s7Orvr5+ZOAx6YxGI03T4XBkVEaNcDiyaFGj0zl6KzB0vKH9nc2vbDUV21nrsc9OEeVgc6/GZswE43qWFDOCkMyqsqIqKh9LaewGjMQBAJH2wYFPWt0NFcm+oJgVkgNhAIDObcEoXOMwniJaOKP6Pm7x7WkfOthN6RhFUflERuc2u+dPc8wonpLxQNB5oLm5+Yknnjh8+HA6nZ42bdo3vvGNqdrrezp/Vp5//vnHHnts5PY7n8+3bdu2559//te//vWSJUtO9sRnnnlmon3de++9pzFCCIKg85LL5Vy0qLG/v9/j8Yw8HgqF8/PzzebRt3iXLVsaCAT/8Y9XDAYDwzA8z8Vi8WuuufrGG68/o+PEMGzu3Pr33ntfp9O53c5cUqloNNrZ2XnJJRefRiSTSCQOHTocDAZRFLXb7TU11Sx7bu/clbICgqG5AOCEgs29lEEzHEsAAFACM5e5EgNhFYBI26DMS7kFQrIgUQZGzIotr39c9ZUF2XACJXDGqKENrJjmTEU2oCKEhspEk2J6aoqXx3uDvj3t8d6AvbYgt99DUZRY5xCKY3qP9YvMeEDQ2SkTTmZDcUmQGLNO5zQj6OQnn2hpaVm2bJnRaLzlllsYhnnnnXfuvffeBx988GRbCc6oCYcTe/bsefTRRyVJWrp06T333FNWVqYoSltb27PPPrthw4bvfOc777777vC25lEee+yxiXYHwwkIgqBhFoulomLa1q3bKIrOy7MAgKiq0tfXHwgEGhrmH7+IiGGYu+/+Wm1tzdGjR/fu3ZfNcna7nWGYpqZDDQ3zjy9bNokaGxeGQqHm5paPP97OsizP89ls9tZbb7nhhglHMs3NLW+8sXb9+g0Mw6iqynHcsmVLb775K4WFBWdi5GeUIsuDn7SFmvuENAcAoA0aV32ZpcIzKtWVqqhcPEPpR5ddJ1hKazdaF9X1fHiQi6VlQaL0LKllHNOLCB3dtfGAscAGUARRVQAAgiCkliG1xxpBwqkTXtOIGR6nyTNxuTMs2Nw7dKDLVlcEPu0ERVFDsX3wkzb79KL8BbAeNnT+kDixc/2+WPfQwK7W3JGyq+YULq7TOiY5QfbPfvYzFEXfeuut/Px8AMD9999/8803//KXv7zjjju+/ARCEw4n/vCHP0iS9K1vfetHP/rR8EGbzXbxxRc/+uijzz333G9+85tf//rXJ3zuI488cvojhSAIggBYvvy6TCb7l7/8lSAIiqI4jluw4OLrrrt2wYKLT/h4giBqaqp3797T3NxiMhlpmlm/fv0rr7x6ww3Xr1q1ckIZLyYEw7Cbb/5Ka2vb3Ln1kUhEr9fn5+fX1tbkCv6MXzAYfP31f+7du7ehYV6uDnc2m9m6dZuiKP/yL/edWytsVUVte+uT5tc/Yix6Wk8riho60texft+Muy4ruuxzBQERBKAokqsT97kWVKCqqs5jZi169/xpsiBROpZgj5W3Yy36SIfPe1GlLMlCmiM19MhnZuOpkZunhWS2f/sRIZBEFIBimNZhdM+v0LlGT3ApssxFUnwqyxi1lEFzelEHF00RGmpUcmAURQmGykZSp9EgBJ2lVLVt3a7WN3fpvBbH9GIEQ4RUtmvjQT6Rqb5lIW0cb/348di7d++iRYtysQQAAMfxW2+9defOnQcPHrz00ksnsaPxmHA40dTUhOP4CXdRP/zwwy+88ML+/ftP9lw41QBBEPQFMQxz111fbWiY39vbm0gkzGZzaWlJQcGp7tO/+eZbb7+9btasmVqtNnckmUy89dbbJpNx5co7z+hoy8vLysvLvkgLO3fu2rJl67x5c4fTfjAMW1NT9f776xsa5jc2LpyMYX5Jgi29za9/ZC51MuZjUZDWbkoORoLNfeZyt8E7Yp8JgrA249CBLp3bAkZchvPxlKqoOE2gOMaYRodSGE2IGd5QZC+6tK7/4yOmMmeukLaiKImeoL220D7j2NoBLp5uf2PXwI4j2jwTrWVkUfLt60j6IqVXzRlZ5C50pL/vo2Yxww/sanXPLWet+oLGGp1rwhldERQFo7flAwCAoipwXz50Pol2Dx15Y4e5xMlYjv160kYtoaX7dxw1FTuKL585WR2Jorhq1ao5c+aMPNjf3w8AYJjRs5pfggmHE6FQqKCggKKo409RFFVYWNjX1zehBt99991NmzZ9+9vfLiwsBADs3bv3l7/85dVXX33bbeg7cv4AACAASURBVLdNdGwQBEEXAhRFKysrKivHVecnHo93dnYVFBQMxxIAAJ1OX1BQ0NHROf5idlNlcNBnNBpGpRCkKFqr1Q4MDEzVqE5PtN1HaujhWCJH6zT793XkVRd8LpwAwDmzOOWLxLqGDF4rgmMAAD6RiXUNlV1Vb/DYFFlRFXXUXIEiyhhFEDRZdnU9UEHXpoMEQyIYKmUEZ32ZZ/604VChd8th3842U7mL1rK5NW9apzl4uBenScNdtlzhav++zt5th0NHB7R2o72mMBtJBpq6uWhq2vL5ugnWiNDYDFwio0oyMiIbrMSLUobX2EdnE4agc1dyIIziGGPWjjyI4Thj0ib6Q5PYEUEQo+7s9/T0vPzyyw6HY/bs2ZPY0ThNOJwoLy9vbW2VZfn4CWtBEHp6eoqLx5ulQZbl73znO2+++SYA4K677sod5Hl+06ZNmzZt2rhx47PPPgsrp0IQBH0R4XBk06bNs2ePvitmMOg3b/5w5co7z/JwQpZlBDnBDWwURSdaOmPK8ckszozer4IgAKdJIZUdddxU4vReXIWgyMDOVowiVEmWJbl06ezSpbPTwZhjZnF6KKZ1frYaW5akbChhuGw6AEBjM9bc3uicVZIKxGVBZMw6S7l7eMezxIvx3gBr02PUZ4NBUETnsXZvbipeMsNQYJN4cWDn0Uj7oHWaO/cAnCVpo9a3v5M2aWtuO2nhphNyzCj2tPQPHeo2FTtxCgcAiFk+2u7Pv6RmzMS1EHQOkXkRxVBw3LUrSmAyL525ft95552HHnoolUq9+OKLJDneQvWTaMLhxDe+8Y3777//qaeeevjhh0edyqV7Wrly5Tib+sc//vHmm2+6XK6HH364pKQkd3DevHmvvfbaj370o3feeee11177yle+MtERQhAEQcMwDAWfZpIdKXdkojsZvnx5edZEIqGq6si7S7IspVKpM5rr9kzAKUKRThACyaKMUyfYFu+cVWIqsnvmV2QjSYwmaSObHoo3vbxZlZVY91Copc9c6jLk56EYJqS5xEDYPX+ae960Y33RpH1Gsf1EwxDTnKqoODP6miO3MopPZgEAycFw70fNturPXesjKKK1mzKhxOiNGWOhTdqSpbMQDOnd1px7pRIvFjbWll41O9cpBJ0fKB0rC5IiK7kpvmFSRiCPy6wwKTo7Ox988MHt27dPnz79l7/8ZUXFuGatJ93Y4URuJdaw+vr622+//Xe/+92BAwfuuOOO4uJiVVU7Ojr+/Oc/79y584477li1atU4+37xxRcxDHvppZfKyj5bWYuiaENDw9/+9reGhoaXX34ZhhMQBEFfhN1uv+yyS1tbWw2Gz60qCYVCl112qcNxwgvOs8isWbPmzz/c3t5RUlKMfJpj9OjRtoULL5kxY/pUj25i9B4rH89KvIBTn13K88msxAk6z4mXD9EmrXN2KQBAzPDNr27r2nhAYzeRGprUM7RBI6Sy/TuOkjrGPbfcXOYqumw6Y9KesJ1hiiwHDvcED/cm/VHCQDN6janAnpumkCUJAHDscj8rAgAwcnSQg1E4AEDK8qcIJxRZRo8LU03FjrqVl3rmTctEkgiCsHkGc6kTp6fgNioEnTnGEqdrbnm826/Ptw3fAeES6WwsZS51TXp3L7/88g9/+EOLxfL73/9++fLlU7iiZ+xwYt68eSc8vnXr1q1bt446uGbNGkEQTpbZaZTOzs7i4uKRscQwh8NRVlbW1tY2nnYgCIKgk6Fpes6c2Rs3bqJpxuVyIgiiqurgoK+/f+D222+j6QncY54SxcVFCxdeAgDYuXOXwaBXVTUWi190UcPSpVfa7Wd7LDSKfUZRQWNN//Yjem8epWMAULOxdKIvVLZstrXCc+rnDuw82r3xYF51/vDtfE2eMdrht1Z6S66cbci3shb98UssRpFF6ejanUfX7uATmWw0KXFCqj8ixLPmMidt1GYDcc/8abnkToSGAgBIvEASn7ulKnMiYkSIE8USiiz793WGmvv4ZAYjcI3D5Gmo0IzIJUWwlB0WrYPOa6xF55pTClQ11NJHG7UohgppLhNKlF8z1zmrZHL7Wrdu3erVqy+//PJf//rXU75mdexwYu7cuRNq0ev1jvORuUzkJzubSqVG7b2DIAiCTsPlly9JJBItLUe2bt1G0zTHcZdcsmDJkksvv/ykVUfPKpdeujg/P7+6umpoKICiqMNhr6+fM/7vmrMHwVAV1zcQLJUJJXI56d1zyx3Ti0uunJW7nZ/yReJ9IS6aIrWMzmMxFny2miva4actupFLgxAEMRbY/Ps6yq6qH1nt7mT4RKb17V2H/7HFmO/QuSyxvkAmnGCMmlQgpqqKxmbKBGLly+flQgWdy1xwSXWgqcdcRg9HKYokp/xR+/Si41coyYLU8s+P29Z9wpi1hIZRJHlgV2uiL1h02YwxIyUIOp945lfQBg1j1mWjKaCqBsZmmeZ2z5uG4pO5slRV1Z/+9KelpaV/+tOfzoZtxmNfr69Zs+YM9V1bW7t+/fpDhw7V1NSMOtXS0tLT0/Pl582FIAg6/+A4fsstN3d1dS9ceEksFjMajUVFRUVFhVM8rIkoLS0pLZ3ke3tTgrHoam5dmBqKFV1ah6Aom2c4tkNaVbs3NwUO9QzubsMoQhFl56wSQ35eyZWzcJpUZFnM8sfvdkAJDMGx3G6HU/Ptae/fceTIGzukNM/HM7RJK4syTuLpYBxF0FBLv7HIPu36Bp3byicylJ7FCNx7cZXEi8GWPq3NiJK4lBXS/qhzdmnBwtFf2QCAwU9a29/Zbalw0/pjmfX1bkuopQ/FMENBHtwgAV1QrJVea6VXkWRZlM7QD3/uOrm2tvb4ncz33HNPaWnpmej0FKby9v9tt922fv36r3/960888cTIyGH79u0PPPAAAGDFihVTNzoIgqDzSlFRYVFR4dSOAQIAAATROkyjSuT69nbs+9N6vcvsnF2CIKiqqplQwre7HcWwsmvqUQzDCJyLJKUML3ECimOkhtbYjQBFVFkmjgszRgkd6e/7uCXaMajJM2RAXJGVeHdAkWWcJnX5Vopl0r6IkBGOvLH9yBvb3XPLTSXO/Euq86rzUQIjtbSQ4nJ1J/KqvIWLak+Y2jXcOsCYdbReA1RVVVUERREUMRTaej9q9l5SZas+9+qXQ9AXhOLY5M5IjNTd3Q0AaGpqampqGnXqmmuuubDCiSuvvPLuu+/+4x//uHLlSpvN5vV6CYLo7e0dHBwEAKxYseL666+fwuFBEARB0JdBVf37OhmzTuex5g4gCMJa9aqsRLv82UiSNmqz0eTgnnZaz2IkoSqKLEjGAhtt1rrqy/Ve66mbH/ykLdjSZyl3x3qC6VCcYGjKqJF5ESEwKSum+iMSL+jjmbzqfAQBaX/Ut7c9E4zX3LrQUu42l7mERLZyxcW0UTNcfnsURZaFFCeLUuBQj5TlgQowitDajRq7CcVQPp6Z5LcLgi54V1111VlVeGeKNyc89thjCxYsePzxx1tbWwOBQO6gy+V68MEHb7rppqkdGwRBEASdUaqsiFlBkWQxy9MmzaizlFE7sKu1+PKZ8Z6g/0CXwWMV0hyhoVACU0Qp0uHDB4iSy2dpbKeqBCdlBS6WYiw6FEUlXkQAglMEQABKYEKKI1lKygqUntV7LLlkTQRLk3q264MD1gqPe940BEEoA0sZ2FN0gaBoYiCc6A/JvIjTJIIAKZyMdvqtFR5VUTACboOEoPPc1P+SX3HFFVdccUUymezs7OR5vqSkxGKZWLlNCIIgCDq3JPpD/duPZIJxRVZUWYn1DBGa0ZfsCAYAAKqsBJq6NVaDzmWKdg5JvJgcCAMAtE6TmOGNpY5Td5SrdIFhqMQLpIYRdZzI8cSnGVrFNKeqiiyKqvrZUwiWogxMvCcwXMXi1DLBuJjMcpGkvtCGAAQAQGiBmOEDTd0FjbVal3l8bwkEQeeqqQ8ncnQ63fTp51gGcQiCIAg6DZF2X/v/7Qkc7GKtepTAhTQXaOqldAxtrBhZkkJIcO655ZSe5eJp2sCSOtZWVyRlOFOxA8VRgqX8B7r5SOrUfeEshRG4kOZxhsJpgtSxEsfz8YyqqrIgoSYtqWUwikCAOvJZKEGIWWG8L6fNl4kkDYX2bChBGjQogQIFABUooqwCVe+Gtwgh6DyHjv0QCIIgCIImiSLJPZubgs29eTX5WqeZteqNBTZrpSfRHwq1fLYYWubFRF+Qteq1ThMAIDd7gCCA0NCsVU8btShBIODzQcCJoBhqKXenAzFZlBEEwXBUazfpvXkEQxpLHIZCG0Zgeo8F+3S+QlGUbDiZ8kVTQ9Foh09VxuwB8MkMrWfNJU6N3ZgJxFKDkZQvQmgoQ6HNmH+O1QaBIOg0jD070djYOH369N/+9re5/86cOfP2229fvXr1GR4YBEEQBH1GFMW9e/f19PTE4wmj0VBUVDRz5gzsuOrLZ7/EQLj7wyZrpRdBPrujZypxZoKJeLcfwzFCQymizMVTBQtrS66YheIYbdKGjvTl4ophQjytqqrGNnbFCc9FlSl/pP3/9kqcmAknKV6SJVlXYDMU24AEkj1BVVZyGyeEZDbSNhjp8ElZQeaFQFNP2VX1xZfPyGWzzYQS/r0dqaGozEu0SZtX5bVUeBAEwQhMlmTGoqMMGkOhTeLE3KtID8Vy5fAgCDq/jR1O+P3+aDQaCoWsVisAIBAIpNPpMz8wCIIgCDomnU7/5S9/e+WVV7VaLUWRHMenUqk77rh95co7zv7C3qMIyawqK0Iykw0lEBQhNDRr0aEYaq30yCWOvKp8RZQIDa11mp2zSnLJlOzTizre25vsD2ldFgRFAABihot2D5Uuna335o3ZI04TlTctMBY5wq0DfR+1xLqHGIuOMjLZUEJK8ba6osRAONY1RLBkpM2X8kUAhjhmleRVevkU1/XBfinL196xKNEfan9vr293G2XQIDgmprJH3the9ZUF5VfX69xWWZC4RJrWa1iLPtepLEpcLA1XOkHQhWDscGL+/PkbNmyYNWvW8A7pv/3tb2vXrj3FU/bt2zc5o4MgCIIgAN58863XX//n9Ol1RuOxLEaRSPTvf/+H2WxaseLGqR3bRKX90fRQLDEYwQlMVVVVUU0lDnOpS5EUrcNUcUPD8flYbTUFs+6+Yqip27+3A2cpRZLFDF982fTSZbNRbFyLljES9zRUeBoqqm9d6NvTHu8NxofCKE2YC+wF8yuDzX2Bg92RDl8mlNDn57F5BkO+DcFQ2sBi5a6uTQetlZ6hpp7AoR5bXdFwj5lQouXVbTqX2TmzpOyqOR3v7zXk22ijFkERIZWN9wS8F1U6Zp0PxQchCDq1scOJJ5988uGHH965c2ckEskd4ThOFMUzPDAIgiAIAgCAeDze2tpWUFAwHEsAAMxmk9frOXy4edmypSx7qjSmZ5VMKBE81INROIGilEkLAJB5Kd4TUCUFJTBrheeEtR0QBClYVGsqddrrCrPRFE6TWocpryofIyecTwWnCO9Fld6LKuPxuCiKLMvSLOu9qNIzv+LAXz7g45m8mnwEQYYfTzAUwVJDB7t7tzXb6wpHRi+sVZ+NJEMt/a45ZeXXzsVIPDkYGdjVqsqKLEquOWWuueW5NVQQBJ3fxv5L5HA4nn/++eH/ut3ue+6559FHHz2Dg4IgCIKgTwUCwU2bNs+ZM2vUcZPJtHHjplWrVhYUnDNFl/37OvwHuqxVXv/eToCihIZCSYzUMsEjfcWXzfBcVHGK5+o9Vr1njIp1pw1BEYzECYYcGUvkqEBNDUZUFWAUMeoUpWO4eFpVVFLLVK64ODkQpgyaSOtAuHUg0NRNsFSgqbtgUa1hHCuyIAg6d034xsbKlSvnzJkziSMQRbG/v19RlBOetdvtWq12EruDIAiCzi25C1z1BBmG1EWLGr/04XwhqaEYadAY8u0AQTND0UR/OHecNmiMxQ5T0RhFJI4ncQJOEeC4GOA00AaNmOFVVR2OKIRkNtodiHX6Y+1+FaiBA4S+MI8xfvalrCoqiqLg085DR/s71+/TOs3O2aUYgXOxdPBQD5/MVt7QoHXC6hMQdN6acDjxxBNPTFbfkiT95Cc/eeGFF06xdOqNN96or6+frB4hCIKgc47dblu8eFF3d49Opxt5PByOms0Wm802VQM7DaqioCiCIMCYn6dzGE0lLkWUMJpM9AZ1n0/cdGpCKtv38ZF4b0DKCiiO6dyW/IurGItu7GeenLXCE60rTA6GdS4LAEBIZkNH+mJdQ6zNoPPkDe3riHb7JUE0Ftk1eQYAgKqCbCTpqi/PhR9cNBVq7tO7LbpPt1/TRg2pZ/x7O7QOU+WNF32RsUEQdDY7/TJ2H330UVNTU1dXlyAIJSUltbW1jY0Tu0v0pz/96bnnnqMoasaMGQzDnPAxlZWVpz1CCIIg6Dyg0+mqqiq3bNmq1WqGk4IEAsH+/v6bbrrxZF8fZyfGpBVS2dwMAEYSjJkAACiSLHE8bRrvVDyfyDS/sq1322HGqscZUhXlwd1tib5g2dX1xsLTr/NgKnHmVeUP7GrlYhlSx8S7hxL9IWORw+C16lwWhRMiHb6UL4pgKGPRAVmN9QTsdUWuOaW5pyf6Q/07jzpmFef+m3uNKIqyeYaUL6LIMnoOZvWFIGg8TiecaGtre/jhh7dv3z7q+Pz585944omysrJxtvP3v//d5XKtWbPG4/GcxjAgCIKgC8S1114Tjyf+9rcXGYahaSqb5TiOu+uury5deuVUD21irJX5se5AciDM5hlSQzEhlZVFiY+nbVX5lvKxvwoVWfHtbjv6xvaB3W1au0nKChqrntDQGqcpcKgXp8npdy0ZZ64nAICqqClfJJkJoBimselZq6Hw0jqdyxxs7k0ORjLBmKnEaS5zMSYtAMBc7lYBCB/pDx3uVQUJwVB3Q0XBJdWGAhsAQMoKif6wKiuqpES6B4VkVhZlFENxhkKAmqHJTDihtU1g+gWCoHPIhMOJdDq9atWqnp4ep9N50003FRQU4Dje2dn52muv7dixY9WqVevXr9doNONpqqen54EHHoCxBARBEHRqNE1/7Wur6uvndHd3x2Ixk8lUXFxcVVWJouO9dD5LmEudtpoCMcN3bTjAxVMogeVKyA0d7O75sKn82rkoftJb+IokH3ljx9G127loCgEIn8imh2J8ImMstGtsBr3X2r25qXjJjNz1/ZiyoUTX+gODW5pzkwbuueWmYkfholprpdda6U0H4wAALpamjce+0DESt1UXaO1G/4Gu4itnOWYUG4vslJ7NhOLdm5pS/mj35qZMKJEOxmVBpPWsqgAunpZ5UZZk2qBhLFpbTaH34kqMOP1lERAEnZ0m/Fv9q1/9qqen5+qrr/7d735HkuTw8e9+97vf+c531q1b95vf/OYHP/jBeJrS6XRwmzUEQRA0HhiGTZ9eN3163VQP5IvKX1jj39eBEpilzI2SGMHSWodR5qUjaz7W2Azei6tO9kT/3o6ja3cYCuwAIFKWxxmK0jPZSBJBENqoIRkSAMAlMmNXyQZASHGd7+zx7e4wlTk1Rp2qgnQgNrinnU9kqm++BMFQgiEBAMqonY0IwBmS0rMFi2qNBTYAQCacbHn948FP2jQOk2N6Yc+Hh9L+GGvVqioQOV4WJJQkJEGkjZpEX2hgV5uY4squgfshIeh8M+H7Ort27cJx/Be/+MXIWAIAQJLkL37xC4Igdu7cOc6mlixZsm3btokOAIIgCILOXanBiG9fp2tumXNOqb2uyFzqJLUMY9GxVkOwpU9VTpDBKifcOsCYtIxZCwBQcomuEIQ2aBL9IS6SlARJ5sWUP5oaiimyfOox+Pd1+Ha0GUsduRLXKIFpbEZLmavtnd2Du9v6Pmrp+uBAciAcbOkXs8Lws1RVTfmj+QuqdJ+maer/qLlv51HzNJfWbsQZijRoKAPLxTMpXyQbTqlAlTmBNmgJlmKtBmOBLdrlTw6Gv/h7CEHQWWXCsxOtra2lpaWj0mvk6HS6srKyo0ePjrOphx566JprrnnmmWfuueceDO7QgiAIgi4A2UgSAEDqRu8gJ3WMlBXEDE9qT1z6jU9kCJbCCJygyXQwTjI0QACCoQBFkr5I9nAvl8jsf36Dt6GC0rMFjTWn2Jad6A+TBnZUFTwUx4RUdt8f14tpjjSwMifw0VT3xoOWaW6dyywLYnoobpnm9l5UmXtiyh/t3LBfiKUDB3tQHMUokoumaAOriBIXzyAYosoyoaUxEk/5IlKll9RRvVsOWcrdbJ4BLnmCoPPJhH+fTSZTKBQ62dlQKGQ2jze39JYtW+6+++6f//znf/3rX+vr610u1/FBxfe+972JjhCCIAiCzloIisiCmOoPK7KMUQRt0BC50tGKmjt70ifiWG7aQeexSpyQCScpPYNiuJQRhpp6UBxzziw2Fju4eDrY3Msns+XXzDUWfraPQlXU4OGeaNcQH0v79nVw0bTWYwYEAACIWSHa4eMTmWinP941pHNbJV7U2A3mCneiL5SNJHOTElqn2TO/wlZTAABI9IdaXvsodKQfQRAVAEWShXgWYAifzKoqQHGMoElCSyuSzMVSlJ4NHx0EiBrrDnSs3xfvDbrnTbPVFhxfMg+CoHPRhMOJysrK9957b/369ZdffvmoUxs3bgwEAlddddU4m7r//vtz/0ilUl1dXSd8DAwnIAiCoPOGKiuBw70YSfTtPIpThKooOpeFzTMYC2xcLG0qceAMebLn6l2WwV2teo/KmLVqkQ1B0XhfUBYkIZXROC326nxDgQ1BEZwiaB0bPNTDmLS5cEJVVP++juZXPxr45ChOk5SWljJCKhBFMGCd5sU0aPhIX7wvhCKoIiuElkn6I6qsJAfDOEUaC21iVpi2fF7JFTMZkw7B0FyDXR8cCDb3aWwGIcWRGhoAQLJU6OigIkusSStxAkCOVdqWOSETSgAAaCNLaChZkgKHunu2HKr/l6s9809VBRyCoHPFhMOJVatWvf/++/fff//DDz986623UhQFABAE4R//+Mfjjz+OIMjKlSvH2dSTTz450d7PcoqiyGOtWD2/DVc3v8Dfh3NR7rNTVRV+dqqqqieqwHw8+F7l3ij4YzN+vVsPt63bpcgKhmO0UYNRhJDIJAZCXDSliFJeXeHwX9Hj2WYWRbv9wcO9hoI8xqIn9BrKpIm2+1ACy2+YRpt14NNPBCCAzdNnwolMLEVq6I539+z73/fSgTht1CAomo2kSC0DECzZG8YIXGPWx7oDGrsx3htEVBUAhNaziiSLWYGx6hP9IZwlVUWlTFoFqECWAQDJwQgXT+s8ltxWDYKlEBRBcQynMCEp8mme0FCKIMuipIiyxIuqoiIoIvGSIT9P77biFIHiwcHdbZZK78lWdkFjgpccp/hlgb5kEw4nGhsb77vvvqeffvoHP/jBD3/4Q5fLBQDw+Xy5n+n77rtv4cKF42zqzjvvnGjvZzNZlpPJ5CkqfF84VFWNRqNTPQrodMiyDD87URQlSTr1Y2RZhj/nwwRBEARh7Mdd8BRB6tt9lDCxrM2IUHi8cwjFUARFxYwgcFz5zRcRXsOpfqgoYJ1fwonC4M42BAFABXkzi1wuo393u4SDbDY78rGiImWz2fBQMBtMHHhpk4qjpJEljCwAAGMJPp4m9ZSY4kPN/VmHQVbkdDghpjkERVEKkxVZRYACgCRKhI5ODYQj/YGRA4sPDvV83Gyt9lI2HR3TJYeihJZGcQygKEKgqqKoKgpQkI2kUAJVZAWoasoXZfL0tE0vKpKYlTAj3b3tsHl2obHMecbe7/NcOp1Op9NTPYqpJAjCOG/9QGfa6eyF+s///M/Fixc/+eSThw4d6u/vBwDQND1jxowHH3xwwYIFkz3CcwaGYQaD4YSb1C8coijG43EEQYYr10LnCo7jUqkUjuNGo3GqxzLFYrEYQRCnfgyGYQiCWK3WL2dIpyEej2cyGYvFMioL3+RKpVKJRCKRSOj1+ry8vDHftwtcoj8UPtBrrfRSOkY7U2vy2sQUr0iSqqg6l7l4Xo0ub4zNh1arNb+2LHFNMBtJ4hTB2oyKJG9s6qNQnGTZkY9UErxGo3Hku9oPDWoMWiHDiwAZ/oAICxEfCOuL7RlfjKQoRIdo7QYEQTJDcYkTFEEGiqLICheII2adqqishmUBSWoZnCYAAHhSJgiCJCmSpehaOqb1i1khORDGaQJRgGtuGW3UxHuCoZY+BENkTJZ5gTJpMRxHJBWkRNZmUGk1QRAaijmbf4nOWpFIRFEUnU6XWyFywcpkMsFgcKpHAQFweuEEAOCiiy5au3atqqo+nw8A4HQ6T3tDVTqdfuuttz755JNoNLpo0aKvfvWr27Ztmz17NsOMznoBQRAEjWn37j2bN3+YSqUAAAiCVFZWXHHF5WciSkyn02vWvHHo0GEMw0iSxHH8oosaLrlkAQwqTkaRFAAAgqIpXyQdiEu8iCAAp0napAm09I6Z3TUHpwhzmWtEm3JBY83Qvk5zOTO8jVvmxVinn9Kzg7vbw0cHMIYEGf5z93FRBMURQkNp7AbXjJJIly+vsiAbTXPBuJjMAhUBKAAykFQh6YugGOrf15F7HmvVFyys0TpM3oaKSKefLLCRWtpWWyjxornMFTrUnY2mWauO1LGx7oDGYSR0TLzTj9Gs3m1FCDQTTmAEzubpZUEEABzbgw5B0GnZsGHDf//3f7e1tZEkWVVV9b3vfW/OnDlTMpIvlKkNQZDcYqfTtmfPnnvvvTcXkwAA8vPzAQBPPvlkd3f3Cy+8MHv27C/SOARB0IXmww+3/PjH/89iMdtsdoLAk8nUtm0f9fT0fuMbd09uRCGK4p///NdXXnnV6XSaTCaCwEOh0AcfbPz61++68847YMaeE2LMWld9mW9vR6I3iDMkRhAAUdPBRPBwr3veNErPSJyA0xObTUJxrLCxVubE+5hbTAAAIABJREFUwKEeJk+Pk3g2mgq19CmCPNTUEz7SH+8PERqa0tIyJwLtiPt0KpA5wTGn1FFXPNTUnY2nJU6QRFkFCIKoQEUABgCCAkWVFTkdiGVCcVUBgabubDhZfMVM+/Si/u1HUATV2AwoRaiyyoWT3ourEQzt33kUp4loh58yabLhJG3U8kkOQREEIARDyaIkcEJ6IOK9qNKQnzfJbzEEnR1ULgi4ISDzgLYirBcgE67zNqZ169Z985vfrKqq+uY3v8nz/CuvvLJixYq1a9fOmDFj0vsa01Qmfh4cHFy1alU0Gl2yZMlVV101nMRp8eLFv/nNb2655ZatW7c6nXBVJQRB0LjE4/EtW7a6XM7y8vLcEbPZbLfb3n9/fXFx0YoVN05iX7t2ffLqq6/V1FSzLIvjOEmSJpNJrzf88Y/Pz549u6qqchL7Om9QehbDsdDhXq3TRBk0uYM4RXCxVKTD98nv1lF6ltDQ9rpCx8xidNzlmMxlLpTAaJM2G0kqkhztCqA47pk7jbHqAQA4Q/r3dqBOs5jl0Xia0rMAQWRBlHlRSHJapyl/UU02mmp+/WNFkICqogiCoKiqqBhNAFWVOIFkGSHFq7KqsRtZqz7U0ofRxPSvXqYq6tDBrv4dx4pNeS+q9DZU5NUWuOrLerc2Rzr8lIGldAxr0iV9kcRAmNTSQAVSho+2DdrrirwNFQRzQa/Vgc5Pclbtf0tNtKmBrbkDSP4K1H0VYN2T289TTz1VUFDwzjvv5CaE77zzzgULFjz99NPPPvvs5HY0HlMZTjzzzDPRaPTee+995JFHwIicsN/73ve8Xu+///u//+53v/vpT386hSOEIAg6h7S1tX/wwcaGhvkjD9I07XDYjx5tVVV1EicNWlvbDAaDXq8fuW3dbrd1dXW1trZONJxQVXX//gOHDh0KhcIURbndroULLzGZTJM12rMHazOweQYhxSmSguKoIslcPENpmPRQPNw2qPdahUSmZ9PB8uXzK25oQLHx3tE0FtqNhXaJE/s+bvbtbS9YWD08y2EssPPxTKTDZyyyYzgWHwgjCBBSHKWjC5bOKLx8Bobj066fD1R19zPvkjpG5kRVUTCKQDBEyooYSaqqgiBA4gQAAIIiOre558NDJVfMyr+k2j69qPjymUIySxk0Orc5Fx64500z5NtQAsvG06xJCwCgjBqCpfhkNtblNxY5nHPKCi6pyavynpn3GIKmkKp0vwp6/qFqCxHrXBVgiBRXB95RxThS8nVAjbcy25g4juvo6LjnnnuGF5e63e7S0tLOzs7J6mJCpjKc+OCDD2ia/v73v3/8qZtuuulnP/vZjh07vvxRQRAEnaOSySSKosfvzmQYRhAEnudpetKWqqfT6RO2RtN0MpmcUFOKorz22utPP/0/Op1Or9dJkhSJRJuaDt144w0nDEv6+/s7O7sikYhery8uLiosLDy9lzAlFFE2lThwmhSSWYkXEQRBCVyRFYZASZbS2ozAZuRiqda1O0zFDueskuNbENNcpMOfDScwktDYDKYS5/CWCZwmpKxAsPTIFVM4S1oqPXwizUVSjEVLG1hZkAoX1boX1+jK7ARLAQAwAvdcVHn0rV0yL3DxLIIAIc0psoRiKEARnKFUFSCfxjY4TQEAhBQHAKD0LKVnRw8RAI3dSBs1weZeRscgOEawlLXSK6Y5VVHLr66vvnW8GSAh6NyiJtrV7peAoRKhrAAABABAWoBJpw59CHTliPe6yeoIRdE1a9Z4PJ7hIxzHBQKBxYsXT1YXEzKV4YTP5ysuLj5hXgIEQdxu99GjR7/8UUEQBJ2jWJZVFEUUxVGboXmez61HmsS+NBoNz3PHH+c4TqvVTqipPXv2Pv30/5SXlw1vxpMkcc+ePRiG5ed7R7amKMrbb6/bu3ffli1baZrmef6SSxZUVVVef/3yM5rAahJhJAEUdXjPQHIgHOsZ0jrNmWB8+HqdNmpJgybcOnB8OBE62t+98WDfxy04iSuKqkhy2VX1JVfOZMzHkgoqsoKio+c0aIPGWOQ0Ftnc86ZhJM7mGQzevEQyMTKzudZhyr+4qmvjAZkXEBSVeRHBUBUAhRMUQSJYenjb9LFd1CcvtwcAQFCk+PIZYpob3NPOmvUodayYXdHiupJlcFckdP5K9yAIDqjPJbdEUBJQFjXdPYlbykiSrK+vz/37n//8p9/vf/PNN3me/9rXvjZ5nUzAVIYTBQUFfr//ZGcHBga+4D5vCIKgC0pJSfHixYs6O7uKigqHD0qS6PcPLV165fFXmV9EWVlpLBZPJhMM89nN6UAgyHFcWVnZhJrat2+/0WgY+Qcfx4lp06a9//76Sy9dPG/e3OHjW7Zs/dWvflNYWLhgwcUoiqqqOjAwuGXLVoIgbrjh+i/+or4Eeo+FS2aHt1xLvIhimCLJsihTus/eSYIh00Mx//5OPpEhtbTOZdE6TCl/tGvD/lBLn3NmMUrgAAA+kencsE8WxdrbF6E4BgBgTFoxy+fKxn3Wq6qKGc4yzeO96KSL0FAcc80r79ywXxEkIctTOg1AgMSLCIoiKAqAKmV5YNICAFJDUe9FlTrXGMs2dC5L1c2XGPJticGwzIsEQxkK8tzzKygdTNsInb9kDqB4blric1ACyPwZ6vOhhx7KZrOKotx2223FxcVnqJdTm8pwora29rXXXluzZs0NN9ww6tR7770XCAQaGhqmZGAQBEHnIqvVOmfO7M2bP5Qk0WazEQSRSqV6enobGxdedtmlk9vX3Ln1K1bc+Prr/3Q6nWazCcfxaDTa19f/ta+tqq6umlBToVDIYBiddYqmaYqiQqEQACCVSm3fvqOnp3ft2jez2QxBELlNIAiCuN0uSRIPHmy67LJL9Xr9ZL26M8deV1TYWNO//YihII/UsQgAEi9yoYS52MHaDcMPS/mjXCzl292GErgiSa76cnOZS5Vl/94O2/Si4T0wlJ41lzo71+93zSnPbUWwVnicc8pinX5DoT33KFVVU4MR+/SiMfcqOGeWVN28YPfv3kYxjIsmAYJgJI4ZaURRcZpI+2Okjs0MxTKRZN3KaRg1djpg1qovu6YeACDzYqh1INTSd+jFzQiGsla9a2653g3LE0HnHdIAFAGoEkA+f4EtpQFpOMlzvqjW1lYAQEdHx+233/7Vr351zZo1Z6ijUxg7nHjzzTcn1KLb7R5ngtf7779/3bp1q1evjkQiwxFFLBZ7++23f/KTn+A4ft99902oawiCoAvcsmVLKYrasWPnhg0fAAAWLWqsrq6+7rprbDbb5HZEkuRdd31Vq9W0tBz5+OPtl112qdlsXrHixiuvvGKiG74xDFOUE5RckGW5r6/v5Zf//u677zU1HcrLs/h8/nQ68/776+vqauvqanEcBwBYrdZNmzbffPNXzolwAmfIacvn4zTZ/n97AABSVkAxlHWaLRXu4emjRH8wfHTAUuFxzipBcUxV1JQvOvhJq96bRxk0o95eUsvgJJ7yR3PRAptn8MyfBlQ1cLCb1DEARYRExlZbaK8rMhbaxxyezmU2FtqNRfZsNKUoCqFhUKCmAjEumor1BGRJzr+4yjW3/ISbOk5GVdWuTQebXtxM6hhKxwAFDH7SmugPeeZNc80tn8B7B0FnP30FyFsAku2qtnj4V1UVooCLoIbJzHcXjUZzWwaG97CVlJTceeedTzzxRFtb20SniL+4scOJiV7TL1++fJzhRGlp6VNPPbV69epHHnnkxz/+MQDghRdeeO655wAAGIY98sgjtbW1E+oagiDoAoei6JIlly1YcPHKlXdkMlmr1WK1Ws9QFQitVnvTTSui0ejKlXfq9TqbzXZ6W73dbteHH24pLi5CRqRmDwaDPT29f/zj8+l0OhQKsyzNsgyKonl5eQCoTU2HtFpNLh8uhqEAgJEJps5yrFVfc1tj4aLaTCihAjCw82jfx818IoMaMYAhQjI7dLBHazfY6wpy65cQFNE6TYosp3xR2niCfc8IiqojSuC55pRp8gzGQns2nFBkhbXqrZVeS/mJk1RKvBgLDHHRNKGhtHYTimEAQWiLPpdkNkfrNofb/U6bYebXL2etBoyc2LqGSNtg04ubDfl5WsexVF061RrrGgIIYiyys3ln6pYtBH35EDoP2C5WgYpED6qUGSA4IiYRbggpvBmxzh/7+eO2f//+O++88/nnn7/iiiuGD+ZKVU7uutZxGvuPwje+8Y1RR44cObJ161YAwIwZM0pKSlAU7ezs3Lt3r6qq995779KlS8ff/Y033jhv3ryf//znu3fv7u3tlSTJ4/HU1dU98MADFRUVE3olEARBUA5N0wUFBV9OXwzDGI1GnU532i1cfPHFHR2dhw4dKi8vIwgSABCPx7Zs2YqiaHV1dXd3t0ajZVkmEon09w/k5eW5XE6dTjs0FCgtLUFRLB5PLFrUmJdnnbzXdMYhKKJzW3RuCwDAUu7S2AyJvtDArlYAgCLKereFtuhw6nN7nRmzbuhglyLJxiLHyOOKKEu8MLwVO8dQYDMUjD0fFevwh3d3De5ozf3X21DB2gyKLHOxFGP6bAc8oiJyVrDXFupcp7M8KXSkn2Cp4VgCAIAgwFBg8+1uc8woyofhBHR+QeyNgDSplBXhwwCoiK4EGKuBbSFAx14fOH7Tp0/Hcfzvf//7cDghCMLatWuNRuOUJLsbO5x49NFHR/63q6tr2bJl+fn5//M//zN9+vTh4y0tLd/61rdefPHFO+64Y5x9S5KE47jb7f7Vr36V+68kSZOYxxCCIAg6+xUVFV599VUoim7cuImmaUmSUqmU1+u1220URXV393i9HgRBLBZLNBoNh8MWi5mmGVmWOY5DELSzs2vmzJl2+9grec5OBENVXN+QCSWKLp2uSLKqqr0fHuJT2VEPQ1GUYGgxzaX80eFLc1VRY11DnvkV5rIJZy5J9Ib6P2xOdgXzqvMJlpQFOdod6N9+xFzminX5EWCnjDoEATInxnoCjhlFzjnjXT4hpLKx7gAXTWEkrnWY+HiG1Iz+ZkdQBGcoLpqe6LAh6OyHmOoQUx1QRKAIANeciS7MZvO3v/3t3/72tytWrGhsbOR5/q233uro6PjDH/6AjbsC5iSa8FbsJ598MplMvvbaazU1NSOPV1ZWPvfcc4sXL3788cf/93//dzxNzZ49+6abbrrllltyE9Y4jucWwkIQBEEXlDlzZpeWllx22aXBYJCm6XA48swzz7rd7nA4Aj6dwQcA5OXZUqmU7/+zd+fxUVb34vg/51nnmX1PZrIvhAQSdtkhAVFRFETQUq1yra29evVeRW3rUtufbb8Wl/ryXuvV2+q1du9FrQptgaJo2EEEEghZyL5OJrOvzzzPc35/DI0hQEhCIIGc91/JmZnznNnn85xzPp+ODoqitVrtyZPV4XBk+fIbbrvt1ku0oOuyUVv1aqseAKSo2LL7hBiK9qvnIEZi2WXFWoe5+qP90Z4gp+WxgmP+sGNGfvaSKecs/jCwzkN13qpW2+QsjucAgOEpQ4aVohCvE7JLS+p3HAXUSdGUIskZ84uyl0wZ5M7p7uPNTZ9VtOw9SbO0IsnOawqCrW4pnjj7mliWh7puiiCuJBQ7sjMS/TzxxBNOp/M3v/nNL37xC7VaPWnSpJdeemn27NkXvuUlMOR38q5duxwOR79YIqmgoCAzM3Pwtefcbvcbb7zxxhtvzJgxY926dStXrryY6XKCIAjiymU0GufPP53Nb9++/QghikI6nTY7OysQCOr1OgCgadrpTE1Pz6ipqUlJSVmxYkV2dtaCBfOHWuliLGMEzpBlbz9UqzJqkzXmAEAWpUCL21KQVrhmvr04y13dGvOEKIbWpBhTpub0XUc0SLIoxXqCvFl7Rj5ZAI3d0PFl/YLvrcleMiXs8ktxUTDpjDkpvSMZWKDF3fjpMXdNW+q0HJpjMYaoJ9hd3abEE8a8VIb96ieHGIlLUVHrGLEiwQQx3lAUdffdd999992jPRCAYYQTkiT1LXzTTywWUxRlkF399a9//eCDDz766KPDhw8fPnz4hz/84YoVK9atWzd37twr/TwTQRAEMWw2mw0AfL6A2WyyWi3Nzc0MQ6vV6lgsZjQaOI7VaDTf//53Fy5cMNojvSSyy6ZEe4INO46qTFpW4KS4GPOGMxZMyr1uOkVR1qIMa9EFUr5ekCxKAJDc6t0XomkAUBLyIHdf9NN+qLbzaIO9JDv5HY4QCGZdSnFW696TrqMNtkmZjMABIDEY8dZ35iybZi1Kv1CXBEFcAYYcThQXF+/du/fgwYO91fh6HTp0yOVyLVgw2M/3qVOnTp069dlnn92/f/9f/vKXzZs3b9q0adOmTVlZWevWrVu7di0pY0cQBDEOZWdn3Xbb6r//fevUqSWFhRMTCeno0WOyLEejUY5jFy5ccNttqxcsmD/aw7xUOK1q8h2LTHmpgRZ3zBfmdYLOaXFeM4EbuQJwrMAhmpKiYr92KRoHAE435KVTSaFOr2DW9jsfqLYbBavemGV3VTYliw9ijPNvmJF/0yyaJYudCOJqMOR38g033LB3794HH3zw9ddf7xtRHDp06MEHHwSA6667bkgdUhQ1b968efPm/fSnP925c+df/vKXrVu3bty48cUXXywtLf3tb3871BESBEEQVxaMsc/ni0ajVquV4ziapteuvS0ajW7btt1oNAiCKjc3p6enZ9Gim1euXFlUVJiRcbGn58c4RuAyF06+dP0jmjJk2zsP1UkpJpY9vbwbYyXQ4s5aPNmQaRtGn1hWFFnut3oKABACVs1nL51S4rREe4KIptQ2vSHTTtGjkM6SIIhLYcjhxH333bdjx47y8vJbb721uLg4WSmjrq6uoqICABYtWnTfffcNcygMs2zZsmXLlh05cuTxxx+vqqr69NNPh9cVQRAEcUXAGO/Zs3fXrt3RaBQAEEITJuSvWHGT0+l84IHvTJ8+raWlNRwOWyzmgoKCmTNnjEpK9auSY86EYHtP575abYopmdkp2hNMmZqTXTZlaDukMe6qaOo+0RzzBLsrmiLuAKcReMNX8xtSTFQkWWMznK/2BUEQV7ohhxMURf3v//7vm2+++frrr1dWVlZWVibbdTrdgw8++O1vf3vYn/VVVVWbN2/evHlzXV0d/HPWYnhdEQRBEFeErVu3/exnL9jtNpvNRtNMMBjctWt3V5fr29++T6/XX3/90Ka7icFjNarcldeYslOj7V4plqBoOu2agrQ5Bfr0IVTwwBif2nq44nc7eb3AawVZlgOtbgAw5TuS/SiK4mvsylw4yZibeqHOCIK4Ug1n2aIgCI888sj9999/6tSp+vp6lmVzcnJycnKGVzKisrJyy5YtH3/8cUNDQ7Jl6tSpq1evXrly5ZWbR5wgCIK4IJfLtX//gczMzNzcnGSL2Wyy2aybN28pKJiwYsVNozu8qx4jcFlLStRqdSIaZ3ju7HVKF5SseG3MsmtSjACgTTPTHNd1pD4RiSciIsXScX/YMSMvZ+lUVhhUbiiCIK5Ew98FpVarS0pKSkpKht3DT3/60y1btjQ1NSX/zc3NXb169erVq3NycobdJ0EQBHGlqK6u+eyzzxcsOGMiWq1W2+22kyerSThx2Qz7t37PyVZWzSdjCQBAiLJOTFMZ1V1HGjgNby3K0NgNjpn5Grtx5AZLEMSYM/xwYvfu3RUVFQ0NDaIo5uXllZSUlJaWDqmH119/HQBSUlJWrVq1evXqKVOmDHswBEEQxAAURTl5srq1tTUUClkslkmTipLJWEdXKBRiWZam+38TCYIQCoUwxiRp+BgXC0RYNde3BVFI5zDHveGMBUUFt8wZrYERBHE5DSecqK2tffLJJ/fu3duvfe7cuT/72c+Sm7MH484771y9evXcuXPJ1jqCIIhLp66u7vXX39y6dSvHcVqtjmHopUuXLFgwf+nSJaM7MLVanUgkFEWmqDMKIMTjcbVaTWKJsY9mGSzjs9tlWaZIEliCGDeG/G4Ph8Pr169vampyOBxr167NyspiGKa+vn7Tpk379u1bv3799u3bNRrNYLp68cUXhz5ggiAIYgg++eTT//qv1z77rNxgMMTjotfrmzSpqKLi2I4dn+j1+lmzZo7i2PLz8xYvXtTS0pqR8VU5M1GMu1zd+fl5oziw0YIxDnf6Ij0BwFiw6LQO8xiPqbQOU9wfkRMSfWbFazkq6kjFa4IYN4YcTrzyyitNTU0rVqx47bXXOO6rKc5HH330oYce2rJly6uvvvrUU0+d7+Zr164FgAcffHDp0qU///nPL3i4DRs2DHWEBEEQRNKxYxVbtvz11Kn6nJxsnU4HALFYrKamprCw0GQy7t69Z3TDibS0tClTSj777PN4PG6zWRmGCQZDjY2Ny5ZdW1Y2tNWzV4GYP1z3ty8i3f62AzXJlomr5uQsnSqYdaM7sAGkTstNn1/YcfiUMcvOagWEcSwQ8Td25SybZp10ldcGIQii15DDiQMHDjAM8/LLL/eNJQCA47iXX35527Zt+/fvH+DmySVSa9asAYCXX375gocj4QRBEMSw7dmz99ChLwKBYGbm6d92KpXKYrFUVh6fM2eO1+sNh8ODnE++RFauvEWtVh88eGjHjk8AoKysdPr0aatW3WIymUZxVJefnJCqP9zXtLPSkGlzzMgDgLg/cupvX8T9kZI7yxiBu2APo4LXqwtumUOxTOOnx5ITKRjj/OUzJ5CK1wQxngz53V5TU5Ofn588y9WPTqebMGFCdXX1ADe/4447ACCZu2njxo1DPTpBEAQxSIqidHV16XR6AOi7ZkYQVAihWCwKALIsj9r4AACAYZjly28oKyu9++674nHRZrOazeNxkUx3ZXP99iP24ixWfTrJkmDRsRpV42eVtuKs9DkTR3d4A9A5zVPvWZpdWhzpCVI0pbbq9Rm2YeScJQjiyjXkcMJkMrnd7vNd6na7B/4meOWVV3r//sY3vjHUoxMEQRCDpCgKAKjVAgDE4/E+pYEQQhAKBQVB0Gq1ozfAr6hUquzs7NEexWgKtvewar43lkhiVKxKJwRbe2BsZ0iiGNqU5zDlOUZ7IARBjI4hp1QqKipyu93bt28/+6JPPvnE5XJNnjx5JAZGEARBXBSGYUwmkyxLRUWFHo+ndyIiHo/H42IwGJo+fRpJrDdGyKJEs/TZ7RRLy2Li8o+HIAhi8IY8O7F+/fpt27Y9/PDDTz755Lp163ieBwBRFP/0pz89//zzCKG77757kF0dO3ZsgEtNJpPdbk/2TxAEQQwJxtjn802YkP/++x+kp6cnEon6+nqVSoUQ1dPTo9VqvvWt+5YsKRvtYRKncTohERUxhn6ZnBKROK9Xj9KgCIIgBmXI4URpaekDDzzw+uuvP/XUU88884zT6QSAjo6O5HmvBx54YPHixYPs6sYbb7zgdfR6/YwZM+69995ly5YNdagEQRDjkCzLe/fuKy/fFY/HMVZSU1MqK4/bbLaMjIxQKBQMhhYvXnjXXXfefPMKmj7H6XBiVFgmOFOn5YY6PNo++VXDLn8iKloK0kZxYARBEBc0nMQLTz/99JIlSzZu3FhZWdna2goAKpVq2rRp3/3udxcuXDj4fr797W9XVlYmcz1ptdr09HSGYZqbmwOBAEJo3bp1wWCwsbFx586dO3fu3LBhw2OPPTaM0RIEMbLigUikJwAY1FY9OW861mCM//CHP7711v+mpNgtFgsAIIRYls3Pz500aZJarU5Lc86dO8doNI72SIkzGLLs1qKMtgM18UCE12sQhWKBSNwbKv56qSmf7EkgCGJMG2Yet/nz53/44YcY446ODgBwOBzDKLXzb//2bzfccIPdbn/uuedWrFjRu4R3+/btTz/9dHd399tvv03T9IEDB+6///5XX311zZo143yvHkGMrkQk3rDjqK+xK5kXP212gXmCM3PhJE4rjPbQiNOOHz/xq1+9XVhYmJqakmyx2Wxms/n48RP33//t6dOnje7wiAHkXjtVYzN0HWuI+SMIwFKQZpucmTo9b4xXsiMIgriotNAIoeRip+F56aWXurq6Nm/ePH369L7t1113ndPpvP7661955ZXHH3989uzZP/zhDx966KFDhw6RcIIgRosiy9Uf7ju19bA+3ZpSnK0ADjR3tx+qi3T7J69bTHLMjxEnT54UBKE3lkiy2WxarfbkyZMknBjTEEqZmpMyNUeRZKxgmiPvKYIgrgzD/7TavXt3RUVFQ0ODKIp5eXklJSWlpUMrYnrgwIGMjIx+sUTS5MmTc3Jy/vznPz/++OMAsGDBAgCor68f9mgJgrhI7qrW2r8eshVlIJryt7jigQjGgBNy5e8/06ZZcpdOHe0BEgAAwWAomRm2H7VaCASCl388xDBQDNnTQhDElWQ44URtbe2TTz6Z3PPQ19y5c3/2s59NmDBhkP10dXUNvH7X5/Ml/0hmRo9EIgNc2e/3v/3228ePH5dlubCw8Jvf/KbNZjvflRsaGn7zm980NDREo9HMzMxVq1YlI5bkUdatW9fv+jNmzPjRj340iPtEEFctf3M3q+YBQfeJ5lC7h9HwFE0rshL1h2v+ss9elKl1jK8yxmOTIKjicfHs9nhcFATV2e0EMeISkbi/yRX1hhgVq00165zjsS4hQYwrQw4nwuHw+vXrm5qaHA7H2rVrs7KyGIapr6/ftGnTvn371q9fv337do1GM5iupkyZUl5efvLkycLCwn4X1dbWNjY2zp07N/lvMqVsenr6+boKBALf//73vV5vWVkZTdM7d+783ve+98ILL1it1rOv3NjYuGHDBq1Wu2zZMp7n9+7du3HjxrvuuutrX/saALS3twPAjBkz+t42MzNzMPeIIK5iUlSkWMbX6Ap1eNV2Y2/VW0VMeOs7Gz45WnxnKVnkPery8vLC4bDP5+t7siYYDAQCgfz8/FEcGDFOuKtaGndWtOzhWaLvAAAgAElEQVSpomgKK4rzmgJjdkrOsqmsQNK+E8RVa8jhxCuvvNLU1LRixYrXXnuN47je9kcfffShhx7asmXLq6+++tRTTw2mq1tvvbW8vPyb3/zmz3/+897IAQAOHTr06KOPYoxXrFgBACdPnnz66acRQgMsptq2bVtbW9tPfvKTKVOmAEBpaekTTzyxZcuW9evXn33ld999l6Kol156KSUlBQBuv/32Z5555o9//OPy5csNBkNbWxsA3HfffRkZGYN9UAhiHOC0KjEYxYrC6YTeWAIAFEnRp5minmC0J6i26kdxhAQATJ8+7fbb177//gc5OdkmkxEA+Xy+hobG225bPWvWzNEeHXGVC7S463cc9VS3pUzNZngOYyXc7ev4ok4WpcLb5pHTDQRxtRpyOHHgwAGGYV5++eW+sQQAcBz38ssvb9u2bf/+/YPsat26dXv37t20aVMyZVNOTg4ANDY2NjQ0AMANN9xw7733Jv+QJOmuu+4aYBnV9u3bs7Ozk7EEABQUFEyaNOmTTz655557zv78qq6unj59ejKWAACappctW3b8+PG6urqZM2e2t7fTNH0xW8wJ4qpkyk1NROKhTo8uzdLbKEVFRZLVNn3bgZqCW2aTcGLUMQxzzz3fMBj0tbV1O3d+BgBlZaULFy5YtWplvw9tghhx7QdrXMcabJOzkmccEKI0NiOiqGB7T7CtR59+jvUCBEFcBYYcTtTU1OTn5+t0urMv0ul0EyZMqK6uHnxvr7zyyuLFi1988cXGxsbGxsZko9Vq3bBhw1133ZX8d9KkSStXrvzXf/3X83WSSCQ6Ojpuvvnmvo3FxcXHjx8PBoN6/Rm/byRJuummm/otr3K5XACQ/K5ta2vT6/VvvfXWvn37otFodnb2mjVrZs2aNfg7RRBXJVO+o3DVnC/f3h7zhnitAAjJ8YQYjlkL0zm9Gjq8NMeO9hgJAACtVnvXXXd6vd51676GMU5JsZvNZPE6cclhjIOdXpVZ13f2EgDUJl3bwdq0ORNJOEEQV6shhxMmk8ntdp/vUrfbPaTvLYqi1qxZs2bNmq6urvr6+lgslp+fn56e3ndK4W9/+9vAnXi9XgAwGAx9G5NRhNfr7RdOMAzTG6gkdXZ2bt++3WKxJGOM9vZ2r9dbUVFRVlYmSdLu3bufe+65Bx544II1vBVFGXiz+HigKEryj2CQ5JC5wiQL2yuKMsBzl3HjtI6K+u6KJsQzAMCqGH1eitZpDjR1p1yTp6jpq+N5lyQp+WgMQFEUjPFYvr8Mw6SlnZ5lvXTjlCQJABKJxFh+KIhzSr7I4/H4BV/tg6TIcjwakxVZFPsnA8BYCQWC5EUyUjDGABCNRs9+qMeVWCyWfCiIUTfkcKKoqGjr1q3bt2+/7rrr+l30ySefuFyum266aRjjSElJ6V19NFTJTyhBOCM3olqtBoBAIDDwbffu3fv6669Ho9Ef/ehHLMsCQHZ2dlFR0fr165OTFevWrXv00Ud//etfl5aWJvs8H4xxIpGIx+PDuxdXE4wxeRyuUIqiDPzcZa2YwZm1vrpOwabntCpZTPgau2KeUP6UuQkpAdJlG+klpChKb2B8PsnvsKvydR6JRDo6Ov1+v8lkcjodPH/hHbQXfNkQY5YsyyMVTgAAUjHxYIS3aM84RDwhJSRKYMmLZGRJkpSM58etRCIx2kMgThtyOLF+/fpt27Y9/PDDTz755Lp165LfNKIo/ulPf3r++ecRQnffffclGOdAkiuvotFo38bkRMEAOaba2tp+8YtfVFZW5ufn/8d//EdWVlay/d///d/7Xk2tVt9yyy3/8z//09DQMHny5AGGQVEUz/P9oprxJvmrAiGkUpGUlFcYWZZFUUy+jAe4WvrMAo5hORXfsb8m2eKYPSF1Vn7K9NzLMszLgaZpmr5A4v/kDOpV9n7HGO/Zs3fXrt3JTRcAcP311y1ZUjZt2nmLioiiKMsyTdNkY8YVJx6PK4rCMEzyVNqISJmU1bmnRokkeMPps29YwaGO7owFRfaJGYxAXiQjI3lWnuO4C35SXd3I5v6xY8jhRGlp6QMPPPD6668/9dRTzzzzTHLLckdHR/L0xgMPPLB48eKRH+aAkvkQ+01EJKcsLBbLOW+yffv2N99802AwPP7444sWLRr4FZmamgoAHo9n4GEkf0MPMknu1ap3fmacPw5XolgslgwnLvjc5cwvzpheEFo1L+6PcHpBm2oaTApIjLEYiFIMxWrGeqhJ0zRFUQNfh6IohNBV9jrfvXvP//t/P3M4UmfPvkalUkWjkSNHjkiSpFarz1dOG2MsyzLDMFfZQ3Fl8dR1eOraY94Qw7OaFJNjRt5gfrhLkqQoCsdxA0+8D0nOwmLRHar5eD9v0HAalSIrMW8odXpu7nXTDVZSl2bExONxjDHP84OZPLyKIYRIRDFGDKeM3dNPP71kyZKNGzdWVla2trYCgEqlmjZt2ne/+92FCxeO9AgvjOO41NTUqqqqvo1VVVU6na7fxomk3bt3v/baa9dcc80jjzySLJDXq6Wl5fe///1NN91UUlLS29jT0wMDVr0giPGGEThj9mBXJ8oJqXVPlbuqVU5IAMCq+bTZBb25X4gxQhTFzz77PCUlZeLEickWnU5fXDz52LFjWq126tQpFwyxiFGAcf0/jhx99xNGxbJqHstKPBjNXDhpwk3X9M3AdtnQLFO4ep4h0+at74x6QwzPalNMjpl5WgdJBkAQV7PhhBMAMH/+/A8//BBj3NHRAQAOh2N0A8Rly5b97ne/q6urS9Zpamtrq6ysXLVq1dmjwhj/+te/Tk9PT9ay6Hdpamrql19+2dPT8/zzzyfnEEVR3Lx5s91uJ2UoCGIYFFmu/su+6o8PaO0GTidgRYl5w407K6bevTT3+umjPTriK21t7du2bZ8+vd+6JuR0OkOhkMvlSs7TEmOKq7Lp6LufGDJsmlRj8htNiifaD9UhRE25ZynNDfMr/mJQDJ02Z2LanIkYY3LmmCDGiYv6rEEIjZH6DDfccMOOHTt+/OMfJ0OILVu2mEym3tSxO3fufPfdd1etWrVq1arGxsbOzs68vLw33nijXye33HJLenr6+vXr//u///uJJ56YN29eLBbbtWuXy+X6wQ9+wDCj8LlMEFc6V0VTzUf7LQVpKuPpxTBqqyHY6XVXt1oK0w2Ztt5rxnwhd3VbzBNEFKW2GeyTM2meZJ69fGKxGACwbP9FMhzH7tz52b/8yzlKghKjzlXZzOvVWsdX64gYnjXlpjZ+VpGxoMhaNJpnwUgsQRDjxzB/IkuS1NXVdb78XCOyLujYsWOCIAxQuq4vg8GwcePGt956a/PmzYqiFBUV3XfffVbr6RTXsVjM7XYnN2d3dnYCwKlTp06dOtWvk/nz56enp994441qtfrDDz987733eJ7Pz8///ve/nyyxRxDEUPnqOzmd0BtLJGlTTJ2HT9mLs3rDCXdVS+OnFa37qli1CmMsReNZi0tyr5/eN94gLimDQV9WVup2u/utpA+HI2VlpUaj4Xw3JEYLxjjmDXK6/vkAWDVPMVS0h2RlvSpgCRA5m0mMdUN+jUqS9Nxzz/32t78dIONbW1vbxY0KMMb3339/Zmbmn//850HexGg0PvbYY+e8aPny5cuXL0/+PW/evI8++mjgrkpLS0tLSwc/WoIY4+R4IuoJIppSmbQ0O5LfTFjBcX9YFiWVSXvOlRViKMao+p/wRggYgRNDMQBIROPu480nP9wXaOuxF+cwAgsAUkxs/6JWkeUp31gy9rduXx0cDofZbD506AuTydSbLiaRSDQ3t8ycOTOZ8YIYe84xBYAxBgxA5gauaKIXd+2EcDNOhIDRIn0+SikFRtv/anIMSxHEGQGRrU3EaBryD4tf/vKXb731FgBkZWUNu1JEr7179/7617+ur6/v1+7xeDo6OqZOPW92QoIgBiMRjTftrPCc6gSMAYCiKWtRRsbCSRcfVGAFtx+s6TxSL4sSACCEjNkpWWUlnPaMX/+MipXFc6QGl+MSo2LbD9a2H6yt/evBcJeP06qwJOvSbTqHiVFx5nxHy+4qx/Q85+yCixwqMRgIoVtuudnv9+/Zszc1NVWlUkWj0Y6OjtLSxbfcsmK0R0ecA0JIbTd0HWvQOs19VxaJoZgiKxo7iQCvVDjaCQ2/Uzp3IsGGKR7JMaVjG/JXo9y7ker0hC0Vqkauw4ocAACMaGScDClliNWN6sCJ8WvIPymS0wWvvfba6tWrL/LYhw8fXrdu3fmKsOTl5T3yyCMXeQiCGM/khFT9wd5T277UOsy8TlAUHPeHW/dVx/2RiavmnOu05hA0fnr06Ds7BKteMGmAphKhWPsXdZGewOQ7FvVNUqnPsMUDUSkm9p2jiPlCkpgQw7Gj736isRnUNoOiKCq9OtITwhgQBdoUE82xjJoLuXwXM0hiSHJysu+9d31GRkZLS0uymsSyZUuvu27ZxZ85Ii6R1Kk5oQ6Pr9FlyLQlU6WJkbivvjPvuunGXPKsXbHatiiucmSZARSX/JhGmgzc9RnwZpT3LwBA+w7T3Z9S0RospCCKBTmkuMpRqB7lfRNIREGMhiGHE83NzZMmTbr4WAIA3njjDUmSHnrooXvuuefvf//7s88++9577+Xk5Bw6dOjJJ59cvHhxUVHRxR+FIMYtV0VT7d++sBZl8P9cXa0yqDmN6sR7u22TM80Thp9HIdTp7T7Roku36pyn8z+q9BrBqGvYccSUl5q58KuCj6nTcrOXTGkqP27IsPJaQQEs+sKBtp6CFbNCnT7BrDXmpIihKIUQxTKCWRvtCVIMpbEZEYUQQnDu/VnEpZKenv4v/3KPLMvBYFCv15PksGOceYIzzRtCCLUfrGXUnJKQ5Xgi+9qp+SuuocZ3gbMrF465cbQT1JlA9VkmSvGgyYRIG4g+oBjWsxuFahVz8T+TxFiBT4H27ViTjTJWjdLAiXFtyOGEIAgGw8jsyauoqDCZTE888QTDMOvWrXvuuefa29vnzp27YsUKs9l8++23X3/99Ze/KB5BXDV8DV28TuDP3KkpWHRMq9vX2HUx4YSvsav9UK1jZn7fRkbNCSadr76rbzjBCFzh6nmshg93+doO1ABA2uyC9LmFGqfpxPP/Z853KAmZEXhZlABjQIjVqhRJkaJxmucSkbhgIWfaRgFN02SzxJUibXaBKSfFMTM/6gkyKk5jN1gmpo9KilhiRKCET3GVg2lG/wsYDXaV4+yvgxSk3Z8n9NOYPjPMiBFASIFADZB9M8RoGPInTllZ2T/+8Y9wOHzxNVA7OzuLioqSsbVGoyksLDx27Nhtt90GAPPmzcvKyvrd735HwgmCGDYpGj9nrlWKYxKR86ZSGIxEJE6zzNmJIGkVK4Zj/RpVRs3kOxZFe4L5y2cCQghB677qjiOnfI2ucHfAmGXn9WpNijHmC6uMGkShYFuPOd8ZaO1JmzPRNonUeyGIC1DbDGobSb11taA4AEDQf8sZwhLYFyGax9E2jBDQ/XNUYFoNiojkKNAjVuacIAZpyBPZTz31FM/zDz/8cDB4sUno9Hp9MnlrUmFh4cGDB3v/zc3NPXr06EUegiDGM0bgpfg5tkErosSq+YvqWcUpCRmU/kuRZDFxvp4Fi848wam26hp2HG3ceSwRjlsmOAWTNuYLdZ9oRggJJm2o0xftDjA866lrs03KyFk6VWU8K5MJQRDE1QsLqSh1KURd/S+IdQHFg5ACtIAwBnxWvCHHAVGYuqjPdoIYngvPTvz85z/v17J48eL3339/7ty5ZWVlGRkZHNc/C+SGDRsGc+z09PRjx441NjZmZ2cDQFFR0fvvv9/T02OxWAAgGAz6fGQXJkEMnzHbLgajYjDaNzN91BOU4glDlv0ie3bMyg93+TQpXy2JkeOJmCdsHLDn9gO1LXtPppRkI4aKeoKRnqDGZqBoGgMYMm2CWec51WEtyihYcY2tOEtt1V/MIAmCIK44iOLANk/p/ARRDAjpQHOgxCHSimPdlH0BIAZpc2TLfCrcBKqvlptiRUJxF6SWIUT2zBCj4MLhxMsvv3zOdp/P95e//OWcFw0ynFi3bt2RI0duv/32xx57bN26dYWFhYqi/OpXv3rssccOHjx4+PDhkpKSwfRDEMQ52adk5y+fWb/9S63DxOnUgHHMHwl1eotum2+5iI0TAKBNNWtTjU3llbFAWGc3IpYWQ/FAW0/m4snOawYqPelv7labdRRLA4AhO0WKJ0LtHkbN+xpdNMdgDAU3zy68bR7JcUkQxLiF7AupyU/g7v3Y9TlCFMYKlVKKcu4G61wAAN4i6Yo59x5gGVCnYsSAFELhZmSbByllozx0Yry6cDixcePGS3Tsr33ta7t27dq8efOmTZvWrVuXLEr9n//5n6+99pqiKABw7733XqJDE8R4QLNM4ep5KpPWV9/Zur86bXaBYNJOWD4zY+Gki8kS62voavqsIhaIyNFE3BdxV7Xwek12WUnqtJzspVMHrjonxUXEnj55xusE26RMXifEA5FEJC5Y9FmLJmXMn0S2XxOyLB8/fqKpqSkQCBiNxokTJ+bn5432oAjiskEo9VpknonTV0AigFgD0mQB99X2mIRtKQZaiFXhnt0AgOyLkC4HnCuQ+qLOExHEsF04nPjGN75xiY7Ncdwbb7xx6NCh7u7u5L/vvvvuhg0bjh075nQ677///rVr116iQxPEOMGq+Qk3zZJiiYmr51EUEiz6i0z54mty1f71oKuySZtqzlw4WYzFKYY25qY45xSkz554zpvICcnf1B3zBBFDywlZin+1C5xV85aJ6UpCVuSaybcvHHhmgxgnYrHY7373h9/85rcqlSpZTW/evLmFhRPXrLmNZc+RWoAgrhpYjkOsCxIBxJtBZUemcxfzRYhOWMt41RI27+sgRYC3YFaPeg4prnKU8GPOhHT5YLkGUSTBF3GZjPJLDSF0zTXX9P47ceLELVu2JMsnjeKoCOIqw6hYfZplRLpq/vy4q6LRVpQJFILTyWG1ntr2riMNzhn5FHP6navISsQdiHlDMW+488iplj1VyemQmC8sJ2S12aAyfpUaLtDhSZ83yZSXOiIjJK50H3308e9//4fi4mKrNfmixe3tHZ9/Xq7T6VasuGmUB0cQIwRHuyB0CuIeYLWgzkC6POzeD65yLMexqxzZFwFnQI7rkb7gfD0gVot4CwCA6IP6d5TWvwJnAloFcgSLPpS5GnLuAoZksyAuh0GFE8lZggcffHDp0qVn78w+2yD3TpwPiSUIYmyK+cMxX0iTYkrGEkkIIZ3D1Fx+PP/GmYYMGwAE23rq/3EkHog076mKuHw0y1omOk25qQhQ2O1vP1jbsuuEfWoOp1VhWY72hGL+cNHqeYKZrHEiIBAIVFWdzMrK/GcsAQDI6XREo5EvvzyybNm1PE8S1xBXPNz5Kbj34q5yTPEIJ8A2X8EYsISCp7DgAMtsiHuw5yiIAchaO0BEcbq31o+Vtu3IMqM3RSwW/dDyMebMVNbtl/7eEMTgwom9e/cCwJo1a+D8O7P7ushwgiCIsUmKxNsO1FgL0/u1UxwLAFJUBIBIt7/6o/2dX57SZ1g1Nn2k04toylXRhCjKlJuqsRvT5xe176/m1Lxg0gKAISvFOSvfXpJ92e8NMRZ1dnZ9+unOWbNm9ms3my2SJHV3d6en93/5EZdOPBAJdXoT4bjKpNE5LaQ63ojAnsPK8Y1InQa2eQjRGGOIdkDXZ4i3gOO606dqaB54I3iOYM4AuglnF/n5StyDw82gzexbbgJxBqxJQ4FaLIURM5QqYViCWDcWfYgzAG8DiiwvJAZlUB8Nd9xxBwDk5OTApdyZTRDEGMdqVGmzC8LdgX7nh6W4mLwUAFr3nuw4VGsrzqIY2t/sZtS8YNaKQSriDmhTTayaF0xabao5fX6Rc1Y+w7MDb90mxhuMMQCc/eMp2ZK8lLgMFFlpKT/eVdnUtr862ZJdVpK5aLKlIG10B3YVwN17gDOBNjf5L0IIaBWWIxiskAghNrk8SYFECNMcBE+hSCtozl/QM96DXeVg7h+BA2MAwEj0wKDDCeyrhI5/YCmcXG2FWB2kLkXG4iHfQ2L8GVQ48corr/T+fel2ZhMEMcbxerXaqu+qaBQsWoo6XQQTYwi3e7NLS7SpRoxxoNUtWPXJTRRYVgADYGA1qmBbjyHTlixyhxgKyzJZ3USczW63lZWVtra2aTRn/Abyer0Wi9lqtY7WwMab5vLjX761Tec0p07NoThGisQ7vzwlRUWKoU25ZJvTRZDCIPqBP/OVrEgYMSjaDlIQWC2IPgjWgByH4CmgGKBVOPValFoK6Fy/2VDyo1jp3wwKAMYxN8Q9gBgkpPQ/6JmwvwpaP8LeCiw4keUaEL3YVwmJICgJZJ5+UXeZGAfIxCVBEEOQubg46g11HqnXpZhogVPERKjLZ5+clVVaTNG0nJAUWaFZJhGO+VvcgQ5P3BuSYiKjYgFjRZIBQFEUKSbyhqHMvxPjhslkys/P2717j16v1etPZ8b0eLytra233rpSEISBb06MCDEYdVU26ZxmffrpH6CsRmUuSHcdb1KZtCScuBhYkQEAgDqjleYAIVBkwAokQthzDEebgBYQI2BGj6Nt+MRLlBREGbeeo0chlUopxaGG/ruuw+0QbsYY4+7eZLK5KP2W82zOxrhjO3iOYmPJ6blBWoVZI/IfB1rAxhKSJIoY2IVfH2+++eZQO/3Od74zrMEQBDHW6dMsE1fNFYyaSE+w7UBN2uwCY05qxoJJ5nwHANAsw6i4qDfob3YFO70URcliAmMsBqIYYUVWAONAU3fa7AKyZII4n1WrVvp8/vfee1+n0yUTxQaDwTvv/PqNNy4f7aGNF4H2nrb91SlTs/s2IgRqqyHqCSYi8eQ0IzEMiNUCrYJEAAT7V62sHqnTwV+DGBX2HYXgcaTIGAJYjiMNBYoMmgzsO46sc0E4K5ZjNGCaAl2fY4oHVQpCCIMCoSbsO4Z4EwhpYJmNAHC0A7r34kQY5d97jsrZMTckgiA4+64zRAhhwYk7ttFZa0GTeYkeEOLqcOFw4rnnnhtqpyScIIirmD7NUnxnmRiOFa1ZwGlVvF7d91Jjjr1q025FljUpJoQQUCji8mMFAwJfQ5cYiNhLstPmTFRb9aM1fmKM0+l099//rRkzpjc1Nfl8frPZlJubO2PGdJL077JRRAnOlWUxuYhRFiUSTgwfosBUgjv+AbwZ8ebTjXICIRosM+We4yh8CskSpgWEEyCkAMViz2EwTcFd5Th1KTo7nABAjutBCkOgFrr3AM2DHEMqJ2LUkFIK9OkJPSQ4gFbh5k3IOhtMU/r1gOUIdpWfo8wFrQIAkKMj+QgQV6MLhxPPPvvsZRgHQRCXgiLJUU9QDMcEk1Zl0CSLYWMFY4wpmrrgzQfAaVTcuXZRWwrSdemWntp2MRSlWYblOV4rUByDWIrXCRkLizMXFpHFEmOWLMsURQ2URuay4Dhu/vx58+fPG91hjFucXg0AYlTkdWesLpOicYrWsxoSS1wceykVaVMa/gS8ERgNyHEQvchxPbLNV6r/G4VOYEaNaB4oA/BmoDigOBB9gGWQY+fukGIh83Yq3KBocyHUgBCNIy2gyUD0mYsDk1Upwo1nhxPA6JB9EY66EHvGiR4kR8C+CDPaUf5EIMa8C4cTZKqBIK5EGOPOL+vbD9bIopRclaSxG3Vp5mCbJ9oTEKNxLCt6h9mY79CnWQ2ZthE7rqJIUdE2KUOKiMk8PIJFp0uzMCqu+0RzdlnxCB6LGCkY48OHv9y3b7/H46FpOjU1dcmSspyc7FEeFjFK9GmW7NKSji/quMJ09M8iM1JcDHX5MhcX0yxZRj8EWI5DzwEINYDow4wO6XLBOhdy7qb0hThYh0QPMFpQpyHrPMwIlGEiDtUjOQK89Z97rAEYDQ41It4C3PkndZWY4j4IoXro3oMpDgVPAaUCzgza7DOuhjgsxc6ODRBvxrwVPF+AygL/XAqFsQLhFqTJBsExQg8GcdUiHwoEcXVqP1h74L8+Vpt1gs1gL86KuAONOyti3pAxOwUoiLiD4U4PVkCbYsy9frohy562qGhEjktzLKIpQ4aN16mluEgxDMVQABDzhdJmF9A8yWI+5iiK8vvf/+FXv3rbbDYZjSZZlnfv3tPc3Lx06ZLFixeN9uiIUUAxdPbSKVJc7DxSr7boaZYRY2K025+5aHLmwkmjPborCU6EcMNvccuHiDMCI2A5Bk1elHYjyvkG2OYh25nzb1IYAEBlgYAXYxmh3ux5CMlRZJ4G2gnnPVDLx7j+16DLB+s8hBBGDPYcRd27EMWB2vnPK2GQo4gznLMHlLYcRC927we1E1EqrMRRtANZZoHzxt6REMT5DDOcCIfDH3/88cGDB71eb1lZ2T333LNr166ZM2eStBsEMRaI4Vj7oVqNzWDMSUm2KLLCqDg5IckJCQBAVkx5zkQ4xupU3lMdHYfqEqKYWjYCEYUmxZi1aLLreBOvVzMqLtmIMY64AlqHmWyZGIO++OLwr371dlFRYUrK6VdLdnZWdXUNRVGFhRPtdvvANyeuSqbc1MLV87Sp5nCXT5FlHc8al03LWDCJ05JCMUOAO7bilo+ReSowOgBAAFiKQMc/MKOj8u/td2XEqDGtAlqH9Pk4UAesDmgOsIzEADBqZFuMzjM7gWPdEKwFTQ5SnX4Lg2BHNI0RjSItveEEjrQg21xkKDz9r5IARewtcoc0WSj3Lqyy42hHsu4EmKYgx7Le+hgEMYDhhBNffPHFd77znY6OjuS/mZmZALBx48bGxsZ33nln5syzaqkQBHF5BVvdrXtPpkzJ7m2JugPhLq/aogt3+RCF1DYDAHBaVbjLrzbp9FnWQIvb4A7oUs3n7XRwKJpyzi5oKj/ure/QppppnpVjYrDDY/ee8OkAACAASURBVC5wps8tvMgNG8SlUFFRaTAYemMJAEAI5efnfvbZ5wsWzL/22qWjODbiMov5Qr5GVzwQ4bQqfYataM18rGApJpK918OA5SgEakCTlowlkhCjxppsFG3HMRdS9YvVETIW444d2FBAsXqI92CsAFaATqDUayHzXFlik6Lt2FUOljlfdSSkYkMJeA/jaAeEW4BiQPRA3IPSV4ImC3srwL33dP+MBswzkG0eUCyoM1D+N0GOovxvAmtAjPq8RySIMw05nGhvb1+/fr3X6122bNlNN920YcOGZPuSJUteffXVr33ta+Xl5Q4HWWZHEKMpEREBoO/KIimeoFgGKEqRZK53eyVCNEtLMdFoSmk7VGuZmX3x4QQApE7LnfvIqrYDNS17qpItmQsmpc2ZaC/OuvjOiRHn9Xp1uv6p6GmaEQTB6/WOypCIyw9j3La/uuPwqba9JymWUSTJOXuirSg9q6yExBLDFPcCVvptbgYAxBmwqxxl3gb9wwmAlMUo3ATNHwBvUYR0SokqcS+deRtkrkH0+Z8FLANA7y4XAACgkKkYACMlBiob0CrQT0TW2cg6G3d9jl3l2HsMODPQDIgBaN+KM9dQefcAxQEAogUgK02IIRpyOPHmm296vd7vfOc7yYxPveHEhg0bMjIyHnnkkddee+2nP/3pCA+TIIihSKZekWIiK5z+BqJoChQlWUiu7xSBomBE04g+nfFppAbgmJlvm5SZf9OsuD+sMmg0KSZGRXZNjFEsy0qSdHa7JEkcx13+8RCjovPL+oO/2KJJMabOyKMYGis42OZuP1CNKCp7yVmJgIjBQDQAYIz7bX3GWO699KxbCJC7HnQTIFhDxT1Aqym1E9kXnaPcRN9b8RZkXwRiD3CWvn0hVgeG2ZD/LYpRnc4YG++B7t0QqIPecnWqVKyyo+b3sL4ApSy+uDtMjF9DXniwY8cOlUr1ve997+yL1q5da7fb9+3bNxIDIwhi+PQZ1oz5RaE2TzK3EgBwOkESpUQwxqpVspgsywqKJMtigtepxGAMAHjDSE5tMwJnzLKnTMkxZNlJLDGWZWVl9vR4JCnRt9Hn88diseRaVuKqhxXc8UWt2qIzZtmTxSUQhXROi9Zhdh1vTkTioz3AKxNvAYpHcXe/ZhTvQfbFSHCe80aI5lHqEjThO1Tx96mi/6Cybh84lgAAUGcAb8bBBiyLvW1Y9OJoJzIWU7ypt/oEDpzEXZ+DNvuMcnWcEXgz9p8Yxl0kiKQhz050dHTk5uby/Dkm3RBCaWlp1dXVIzEwgiCGjxX49LmFiiS7q9s0Nj3FMqBgVsVhWdGkGn31nYyKQRQV84UNmXaVVec71ZW9dIrGOQIrnYgrzoIF8ysrj+/bt7+gIF+r1WGs9PR4a2trb799bUlJ8WiPjrgcot6QFEsI5v5r3gSzrm1/9YSbZpFaMcOAKAass3HnPzCjAiEdIQpjDPEuFG5G6TcD2//RBqzgnoPYdwKJPZjikZCKbPNAnT6YI6GMW5EUVTp3YM6IaBWWwhD3oezbIXXJGdcU/UBzQJ3124/WgOi/iPtKjHdDDieysrI6OzvPd2lbW5vTee6AmyCIyyl1ei7NMayaT0TiyboTkyemSaLU9FklzTG+pm6aprRpFppnek60ps8tzFo6Bcg+6XHJarV+/evreJ7fvHkLRVEYY4zxnXd+/Y471pJC1OMElmUAAOqsMtgUBQDJRZLDo8iKv9kV84QomlLbDTqn5cK3uZrYF6KJD4H3KHTvxhSPFBFs85FtIXIu739NLOOmP+NTv8a0ABQDiqwoMSpYB2k3I1PJBY+DBAfO/xZlnAyRVpBCiDODLg8s1yDqzJlhWoVlCTDuX6pSSZwugE0QwzLkcKKkpGTTpk0ffPDB6tWr+120detWl8s1bx6pY0oQlwmWlZg/zKr53pSsfdkmZ1onZYjBaNGaBYJJywgcVnD+8pkhl89b0xYPRhGiWC2vSzWnzswDng6FQpf/LhBjQW5uzr//+0MrVtzU3d3NMIzD4cjOzhr12tjEZcPrNYhCiXBUdeaKRzESS5tdIJjOOo8+OMH2nrq/H2789BhCCDB2zi7Qp1tzrp3K68dLyiCEKEi/GczTIGUxinuBM4A6A7Q5cNabC7sP4LpfYWBAjuJAEwCAOhO3b0NYAW3OOaYyzj4WpwfnDRe4kiYTQIa4G1RflRPFSgKJbqQlqTKI4RtyOPHwww9v2bLliSee8Hg8vRGFz+fbvHnzT37yE4ZhHnjggZEeJEEQ/cX84ebPK/3N3cn902qLLmPBJENW/zwhCCFer+798kYUMmTaDJm2tFn9yyHFYrERGRhWsK+xK+zyyaKkMmnN+Y7e7eDEWMZxXFFRYVFR4WgPhBgFjIo1Zqe0H6pTGbW9eZxkMRFodlsK0oRhlYuJByI1Hx3oOHzKWpTBaVQYcLQn0Hn4VCIcm/z10nGVMxqp0y+4Zgn3HMJiCOQIcCYQ0gEwSEEl7kNN/4ccyyjrnIFvPljaPJTzDdz4e4wTiLcAorEYhHAD2BcjO6lZSQzfkMOJ/Pz8F1544Yknnnj22Wd/+MMfAsA777zzy1/+EgBomn722WdLSi48K0cQxMWI+cMn/m9X654qtd3IqnklIXdXNkV6gtlLpoxuMtZ4IFK75WDtXw9RFIVoSk5ImYsmZy2abC3KGMVREQRxQVmlJRF3oGHHEZVJxwicHBdj3nD6/KLc66YNb56q44u61n0n7VOzaYYBAARIsOgRTdf9/XDq9DzbZLLL/0z+ShDdoMn5amMDpUeIhVAdeI/ACIUTCCHIWgM0B4Fa7Co/3Zi2gspYBfw4W4dGjKjhlLG77bbb5syZ89JLLx06dKi5uVmSpPT09ClTpjz22GOFheTMFkFcci27q1p3V1knZzH86bew2mboqW2nWcac52CE0UnuiRVcu+Vg/bYvrQVpnEGNEJLiCdexRlmUOJ2gT7eOyqgI4ooji5L7RHOoy5cIx3ij1lLgvAxvH06rmnzHIlNeqr+5O+4Lczq1Ls3snDVh2AuTgu0elVGTjCUUSQm0dMd8ITkhh7u8Ve/v5nSCIdN2wU7GETEAFNt/kzQjAFAQ6x7B4yBaQFl3QNyNM1aBHAPeijQZ58xaSxCDN5xwAgDS0tJeeeUVAJAkSZIkleqrHTwVFRVkgoIgLh1Flv2NLrXd0BtLAABCoE+zNu8+kb10iqUgbVQG5mvsqv3rIUtBGm/UJFsYnjVPcHYdrdenW0g4QRCDEfOHqz/cV7/9CCvwNEcnomLqtFxrUUbO0qln1ikbeYzAZS6cPFK9yQkJJXdyJ+TuqhZvfQcjqGiOkuNS5+FTgkmXc+3UcTdvGevGwVqIe4DRIE0G6PK/uojRgJLA/TZJy1EAwLTurI6GKxHC4UaIe4DVInVG3x0UBHExhhxOfPLJJ0uXLv3q9gzDMKc7CYfDL7744ttvv93c3DxiAySI8SrmD0dc/kQ4pjJpdWmWZDJ4AJCioiLLZ++9Tk5KiKEYYBxxB6KeYMwf8bd0J0IxKSoKZq11UqZtUuawf5FIsUSg1R0PRDititMJiVAsHojwerXWYeK0AgCEOr0UTfXbyokoJBi14U7fwJ1jBbtPtgZaumO+MKcTdA6TbXIWzQ3zfAdBXKkwPvW3Lxp3VtqLs5J7GDCGYIe3/UCNyqhxnrXlaSzj9epENA4AgVa3t75DYzNQLAMYi2zUlO90n2ylWNqQbR8/e6tw12fQvVvpKgeKByWB7PNBm40ybkWMBgDAWII8X4DoxqwJUQwGjKQYxHswb6P1BSMzAPcB6PpU6fwUIQpjBdkXI9NUcF7fP/sTQQzdkL+t77vvvrfeeqtvRJG0devWZ555pr29fTwnFkwmWBztUYym3rs/zh+Hi6TISuOnx3pOtrYdqEm25CydklVaYsxJAQCKYzCAkuhfxlgRJQBIROIVv98Z9YSadlZEvSFEU1q7UeswSVGx+uMDhbfOLVg5pzcy6Wvg5677eHPLnhPN5ScAQAxEeKMm5g3zejUgSJ9X6Jw1wTErX5FkRKGzM5YATSmyrCjK+VZgywnpxJ/KK/9UjgAAIYpCiKYKVs4tvG0erxMG+6iNqEG+gMnrvBd5KEZEsL0n3O03Ztl790MjBDqHKRGOdh5tSJ2RN+Lpti7d15a5wHnyg71htz/qDXFqVTKWiPvDWqdZbdEBTTXvOpE5bjZWYe9RcO2C0CmwzkUUgzHGMRe49mCMqZy7AABs83HTJqAYFG0DRANWADAIDsq+EBsK4VzP0ZCeO+w7Dh3bIXASzNcAowKcwOEmcJUDliB95Qje08uJfOyMHUMOJ1iW7RdRdHR0/OAHP/jb3/4GANOmTXvhhRdGeIxXCFmWA4GAKIoXvurVDmPc09Mz2qO4grXuPF773l5Nqkk/IYViGSkSb9xd6Xd7s5dP1zhMAEDpOd8hN9LxvVMNGGNvdTuj4Q6/sz3a5dekWzBLAQUUR/va3CAwxvxUys9X/F851rH2GbnnO7QkSb3PnSLJsZ6gGIrF3IHuY02+xi4hzRTvCYbqfBFfCDDWZlkEm77zeGPD5xUl31pG80w8Egv6Av1mFcIevzbX6vF4znlEjHHde/tO/nGXIskszwFNgaJI8UTFHz+NK4m8lbNG5jEdClEUJal/tNaPLMvkdd4rHo/H46Rw8gjoqWtp3H3cNiUrEomccQFHB9xeV1vniO+Mikaj0Wh0ZPtMouyazOVT6z88GPOHFQXLHlkWJZVFx1k0CaSAokhSwtXaiezjImks3/IPuucLRVcEMREg+TtBi7g03F0V5yqxygE4k3d+nWn9P6TKwUADQoATIMdFtjAR10H8HB81oVBo8Nm9+Za/sz2HJN0kEBUQIwAAyEoxcdxxMEpPAs40Uvf0chJFkUQUY8SQw4nf/OY3d99993333ff2228vXrz4nXfeeeGFF0KhkE6n+973vrd+/fpk1ZtxiKZpg8Gg043cGscrUCKR8Pv9CCGLheSIGKZIT1DsCFhyHFrHP2tUazV6m7G7sjmc05VVMgEA6EVTxY6Au6bNmGXntIIUE7uONvoauniTJhGIMVo+1uULdngMWXaaZVghHqx3WbJSTU4bjiQSnUGr9RzbGGKxWCgUYhjGaDQCgPtka+uu41JUbD1QzfJcsLVHZdFGw56e6jY5IQkCDxiL3rA1x6kzGbz1neFaV/GdpcElHa6KRtMEJ0JIjiWkeCIRieGolH1N0dkHlUWpZU+Vq7Kx7oN9cU+E4ZhYOIRoitereY1aDEWDVe3qlZx6WEkqL4bP52PZC8z+0zSNEDrnIzmuhEKhWCzG8/w4/+gbKbIxyLKsoFH3+ybFgqRWqy0WS++sxcXz+/2JREKtVqvV/X/QB1rcvqaumDfManid02KdmHaOWUcAOZ6IeoK0ilMZNOdcRWn9+rWpE7O+/OXWcJeP16tZDa9NMQkWHQAossIyrMVmHRdvIjmmdMSx3oGEMx5qrEoD916NcCuyWAEALN/GtgLsPZbcMgGsDllmq6yzEer/s8rj8SiKotPpeH5wrwcprHTEsT6N6zcAPhN6DqiF25HpSlpH1ysSiXR3j+Q+dWLYhhxOzJkzpzeiyM3NraqqAoAVK1b8+Mc/TklJuQQjJIjxJdjmbjtQ45ie17cRIUpt1Yc6fTFvqKn8uL/J1f5FHa8X3Cdboz0BWZSwjG1TcyhAoQ4Pb1KH2r1iMBbu8qkMGkbFYoRCnR5FkgBQtCeEZQWdmfQ9uS8i6PFrLHqsN3hPdTT840j3yVadw2QvzOz4si7qCUY8AZVJw2p4WmZlMSHFEonaTnNemtqq09j0LXuqCm6Znb1kiiLJzeUnpFhcUSDi8rJqlXN2AWfQ9DuoIsknP9hbu+UgQijk8oGiSKICGBiOkWJiPBhhVXzHl/Vht//yhxMEMVoEqz5tdkHMG1SZzgjP4v6wKdt+GZK2YQU3fHLUXdXScbiOFXhZlKR4ouDm2bnLpvbUtCd3T/E6QbDqY75QsO30lCMjcGlzJqYUZ/WLOhCF0mZNCDR11/39C3txJuoTI0W6/c7ZBfr0cXHiCSsSAJydPen0A6L8cy6UYpFjGXIsg0QQIxoxIzZvg5UEAPRPGwWAKAYDgExWVRAXazg7HXsjiqqqKqfT+fzzzy9btmzER0YQ45MsSnJCivlDoACr4Rk1n1wtTdG0kpBPbNrdsqdK5zCnTsv1N3XFfOGIO4hoChQcaOiMBaKgKKEuL1YURZJjnpAYiHJalRiO+hu73VWtcjwR94faD9Y4rilIlpHCCu44XNdxqK6xvFKW5dSZee40W9jld9e0WQszEIJEJC6LsiLJiGXkuCSGYqyap1gGEIr7wlFvSG3VYQAxHGv6/Lg21chrBbVV72tycRqVtjhLkZTuyuby/+8Plolphmy7Y3qepTAdIdR1rLFm8wFrYXr3yVasYIZjEU0psoJlheJZRFNYkWURsCiP9hNCEJeP7v9n786e5LrOA8F/3zl3zZt71r4XgCrsIECQ4CIuImnKsinTliXZktsT4+mJ6JlRdEyE/TDzFzhm/GB7/DAx0Z6OsHu6x57uli2LWimJlEiJAgkSBEAABFCoKlShlqzKrNzz7uecbx4SBAEQIilxAUjc3xOZyOVkJgp1v3O+ZbiY6stunFwomcZbpdjkVVtBvTOwf+pjmFO+cWLhjf/wXGa8f+jQjt6rBS334nePrR+70K22rKyj2UbU9RvzZcZZ3/6pVCGthPAudpZfOHP433x+4uGbNIYau39nd6O+9eZKZrxPt02S0t1qt1drEw/tSfXnPup3dDtA3QEtBVELrOt3XeM2ATDrHeczeubD/aZRTwPTIe6CeX0rp7gLAGh+IjOdEreVX7NxytWIIo7jqampD3VJicSdK3KDtVfnvEprudxAzjKjJTNj95qfxEGkqs3yidrA3gk9ZTaXN2vzG1Y25fRnO+t1xplbbatYAAEB9Ta9SClumkHbE34cZ4L0cMGttGIvOvZ/fvfQv46mHjsAAJd/dubEv/9hqj/Xt3tckAwa7sKbayRlerjYu5jghiajGBhqphZ1fN2xenO4EREQZRgFbbfyxlLYdBeePc41rbFc0U1t9L6dViHdXK5svL7Ada2xtBn7UXutNv/94/v/6NHtnz/cWCibWdvMpmQkEECR4sAYZzIS3NA00/DrndxkvzOUv6VfSCLxsUKGO37rHhHGl547ZTgW17XYD0UY7/+jR4cP73jvx39ARJunLlnFdGb47etLK+cgYxunLo19Zo/TlwWA5qVNGUsllXADY6IfAKxCprWytXHqUv+eiV4u07Uyo6Xtn7ubG/ryi2d6t4wemZ16dP/U4wc+8nd0u0AoHID1H5JZwremxZGMoLPAxr4A6emP/vU1yO6EzRfAGgDtSiNvIAHuJRz9LXImP/I4NfFp997hxIkTJ256u2EYf/qnf/rnf/7nX/nKV/7mb/7m2sTZQ4cOfWgLTCTuGCTV3DOvrB69YBczUce3SunYD92Nhgii4vYRr9LKTQ3ottFe3Qrafme1qqJYCRn7sRISOQME1LiKJXIGBIyDEjLoeCiJGSiFCppeerjYt3Ms7PqVM8u5qUERRuXXF9MjxexYnxCCokgzdcsy5r7zGupadqxPxTJseySUigUpAxCZxqOOr4QUQcQ4667X3c2mu9ks7R4bPrQ96viNhbIAqM+v56cH3c2mkbHNbEp4ITe1/NRg2HJP/8MLhe3DYcfvNYjknOspU/ghoeq9CyKSUioprHzaGUjCicSdxco7+7726OCBqe5GM/ZCu5DOTw3ktw19DEcTsRdGbmC9NTemR8VSRlL4EagrNa9Bs2ukLW5qYccXQaxZOgBkhgvrxy6MP7DrneEEABRnRjKjJWco31goq1AYWdvM3REV2G8beBjdVVj6R9BzoKdBhhA22PBjMPa7gB9HR2wcfoK8VVj7Lhh9pKWQYgqq2P8gG/sdSBrFJj6w9/5L/IUvfOHd71CpVL72ta9de8va2toHWlQicUfaurB68Xuv9e0ak5FoLm50NxoEpGK5eXKxuVTd8fm7iahbbsR+wDQe1Ltc1zrrdRULxjkpxTSNUKoYQAEgkAIiglgqAkYYtrp2IZ2fHjRzqcj1L3zrZbfSrJ69HDTd0syoKEah7zdXtmQYMYWapXXXa53BXGe11l6tRa6vpAparmYZTONKStH1mc4JsFOuCy/KjpYK00MAIGMBDO1Spr1WB6JOuZEeKgAActa6XDWzKUSIuv78916zCo6MBQBoaUOzdBkLGUuQCqSSfiz8yEintn8u2ZhI3Ik0Ux+++0M+iyBFW+dWWivVoNE1HCs73mdOFm+4j7oSMFwXt4gg6pRryBmRunK3WDKNM13vrNWKMyO9cIJpnGk8coObvroI4gvfeuXi9141synN1Fsr1aXnTk09dteu37vfKqQ/3Hd6e0JmwLY/huxO6MxDVCPusNQo9j8Axse1Y6Kl2Y5/TZkd1JlncYuYzUbGYOBhsIc+pgUkPtXeO5x46qmnPoZ1JBJ3MlIUtt3Nk5c4Z2Y2BQAqFl6t41VbyBkgI1IbJxdVLL1auzA1ICLp8baWMjGKgyBChhQrpmm9/UuucSkkEXFDByJmaExjpECzdN3SO+v11VfmhBu0LletfLq72agvrLtbLaYxt9bWLEPTdRGKoFknqVDXnIG87prt1ZoSUkVx7IVM43YpS0SaqaOGkcYiL2gtV4z0BNc1ACClGGdBy+ca7y0p6LiMs+q5Fc3Uo64///3jw/fs6G40s+P9qUKmztDMOkHLRVIKkRlaqi89cGDbnZQLkXi/6vX6G2+crlQqjLHh4eHDh++2LOtWL+p2p4Sc+/axc//8C802dNtUsQg7/shDu8ae3H9tWyfDsTRLjzr+tf0PkGGqlAFkxtVRGBonqXqTENhbZyZKKSXUL2s8dflnZxZ+cLxv9/jVSTKxF13++RnNNvb+4cMfw8HLbQE59t8P/ffDDRHbx4bbOPKbCL9JSrB3lGUnEh/Ee/99+tu//duPYR2JxB2rNre28tK53kW2UoqdXspN9LuVlhKysGMYEcOOlx4oWAVn5eh5UEpKxXRmZlMyFsgQEbiuKZQqFkSAnEmliJRmaHrakrHgGgdkWkoPGp3OeiNouhQLJVVzcYMIZCh002hdrmqW7owUkaGmaalixttqtdfr6YF81wtVJFQkkCNypmJhFzPImfDCzEjRr3WF3wYmetFOdrRopu32yhYCCC8QsVRCyJj8ehsRjbTFGEPGnOF8t9K0sqnqmeXYD1WsgpaLiEopK5/ODBe5wbc9cVdm5I7o+pJ4/06ePPWd73z3+ed/4jgOEbmu+9RTv/3FL/7e9u2/dJRKAgBWjp4//82jxe3DVzORIjdYe+k8aCz/1Ueu3g0Z9u+ZuPyzs2Y29XbOEmLQ9q2MraevBB5W3mmvVIlUdqykO1diOXejOXpkNjc58M5Xl7GoXyynBvPXTqXUU0Z2vN+rtvyt9h1SkH37wCSWSHzYkr9SicStVJtbW/zhieqbl1P9+ex4aev8anOpEjS73Y1meqjQG18tY8UtXU9boJSZcbxq28zYyDD2IqYxYAw5s7J27EUqlowzGceKmGaZpIjruvADADDTFuisu9lsXtqQkdBtMzWY41zrlOturU1S6SkDgABQCSnC2CpmoO7GXgCE3NSc4QIiRi03aHlmLpUZKTGN1S+WEYBpXLN15LyzXuuU61HXR8Zi19NSdtwNwo6PRETANBa2PeGFUpKVdwbvmq7NrZKg5nJF+CEyZAyBcwDgBt/5xQemHr/rFn83idtMuVx+5plvv/HGGw8+eL+m6QDg+96LL/4sjuN/+2+//kkcfEGKbjqu4UN+Fam23ryc6steW9VgOFZmrORvtb1Ky5l+u1hi9P5d3lb7zW+8pK3XDNuUsYi6wfj9O+tza92NemawAAwzI6X26lZrueIMFWQsYj8M6l230tz25EHnZoFB2PKUlGbmxkMkI51aOza3/XOHknAikfike1/hxJe//GUA+PrXv/7444//1V/91Xve/8/+7M8+6LoSiTsASXX5xbPlEwvc0BuXNmQQMY3LWHQ3miKIuaEDgPBDFcVWMc0YQ42bOTvVn4s6ftB07YITtjzN0pWUKpYyiMxCOlXMtFe3lAhlLLihKyGUJJKyW2ki5y40YzfgGpdRHDZc3bHtYkZGImy5sRcJPwIFMoiyoyUpZOyGKoqd4QIoIgCucyNth+6aZhmlXaPVs5c1xzTTFiFE3cBwNG5q7ZWaVchopmY4plIUtj0GQABM55qpE5EIIjNjx37UWd0iqdprNSubsib6ABnTmBQyaLphx4/cgPE7dCBm4pd55ZVjP//5S/fff4SxK/37bTu1d++eH/3oxw8++MCjjz7y7g+/fbiV5tqxOXejKcLIzKSKO0dHDu/o7R18FMKuLyPRy6K8lpG1N09c2v4bh+CaxkKMs9nfua84M9JarviNruFY6aHCwL6pyy+9Wbuwuv7qRW7qMopH753t2zWW6s+tv3px9MisXczs+tKDo/ftvOkCeiHTW5UX1yAFV2cvJBKJT7L3FU4cPXoUAL70pS8BwF/+5V++5/2TcCKReD+6m835Z48zxHZzS0+ZvY5Mfq3DdE6KwranlBJ+2LdrzOnLkVJOfy4O4+LMCAL07Z4gUl6t05wvE1B6KF+bLyNie3VLM3UVC6uYVrFUQmVGMgAQtX2/0UUGyJiZc5ihCT8O2356uGhmU1HHRwTNNhhnzvRgdqyvcno59gKS1Ly0iQDAkHGmp21uam6l1d1stVe2Uv05pmtmLiX8KPJCKSQgxJ7vDA3nxkqd9bpmaF69E7Y8kEpGMRBolqmZhpGxm0sVkiTD2Jkeujrejuka47yzVmsvV6Kub6Ttd/v4EneYjY3NfD53NZboMU0znU6Xy+VbtapfVXO5AukEtQAAIABJREFUcvG7r24cn7eKGaax2AsXf3xi2+fu3vOlz3xEU+rwlyXqE/X++Mb7M+zfM9G/Z+LaG7d/7tDAvsmx+3YGLdfIprKjpexYX9j2dv7u/Zqp26VMr27qpsyco1lG0OzYxeuqrv2GO3pkNunelkh8CryvcOIP/uAPAGB6ehoA/uIv/uKjXVEicceIun7Q7AKgM5jvFSPqtmGkrc56jZQCgHR/LtWXzYz1IUNknJt61A26Gw1nIKenTRkKIDX95MHpJw5a+VR3o9HdaMooZhovH59fP35ReHFuIg+IpChseZptIJAI49gNNSJu6gQUu76ZdQDByNrF3WN6yrRtGwBEEMZ+hADc0AFBxVLFMvZCpmlRFLSXNoAIOZIiksQMXpwa8aotkoqI8tODZsYuv75glzJGGAk/BEQzbSNniBi5gd2XIaXiMGKadsPVDDc0ZCz2QiWSAXaJ6yilblqz26u6+fjX82uQsbj045OV08v9+6eunr9FXX/xRycyI8Xp90rw6zVo/lXDbCNja7bhN90bWrgGLW/g0HSq//1Onc+MFDMj1zWDMrOpdx56vBPjbOiu6csvntEsIzNUBIZEFNS7ndXq5CN777iOsYnEp9H7Cif++q//+up///Ef//FHtphE4s4SuwFJMtPm2xdJiGbOUbEkqQzHLM4MG5kUABCpzlqdcb7/X3027Phrr1xABCIYf2D36P2z/XvGAeDawuXi7GhjcbPZ2PC22oAYe4EUkpQCzpQiiGIZC24ZuqX7ja5SYOXTiEz6kW4ZRNBZ3/JqHUTs7WuqWCopgQAQlRSkoLvZVFK55QYgZkdLpZ2juYn+ypllEcaZkVKqlCUpMqMl4UcAiIzrKYMUcYNJIVUsvWrbb3l2xo79UPjR1WpOAAAikgo5T44mEjcYGOhvtdpECvHt9Bgh4m63OzBwkwrg21B7ZWvpp6f7d49fm8tnpG1nIF+fW598dP8vy/Grz5fXX53zah0g4obWt3t89MisZr2v0wxkOHhg+vILZ7qOmR7MQ6/ZWtvtrtWLe8bs0vsNJz6I4XtmDvy3T2ydWym/Ns8tXUZCCbn7iw+8ZwSVSCQ+ET7kUuzz589HUXTgQNLeMZF4b8zSkaEIhUHXpBwQyUhkx/tGjsyuHj2vmTpqTAbx8OEds184Mv7QnrDtbXvirrDjW3knM1oyrrkWdytNr9pWSumWPrBvQrf0Xt5Ue7UWuzUzYwOiigQzNQSUkQiF4Lpml9IM2dC9OwTJ6sklTde9rRaRMh1bCqGUUkoBIuNIBIhoZExSpKdMI2X275u0C5lekoaRtqJOwA1NMzVSnGks9kMgIlJWzhFhHLY8GcaKKGx5djZlZqzQDTpr9dxkPzevzFGK3UBGcf/usY8ulTzxCXX48OEzZ87OzV2cmdneiyikFOfPX/jsZx89dOjgrV7d+xK2PADQ0zd2U9VTpoxF7IXX9j66avPUpeUXz1TfvGwXMkznsRusvHSueWlzzx881JsF+Z5G7pnZ/8eP1ebWNl5f0CxDRkJE8cRj+8Yf2/fB39T7gQy3/cbB/j0TI/fOhC3PSNvpkUJhahDukBaxicSn3YccTvzJn/zJyspKMsYukXg/DNu0cg7TubfVMhyLaVwJGXUDq+gUdwzv/cOHpz57oLvREH5oFdKF6cH0cBEArJxj5Zwbnirs+AvPHu+WG2vH5gCAgKyMw22juH04doOg6eq2SYqYxpAzUIAG05hOioy0HXb96Yf3bX/qnojE2Gd224Z1+Wdn14/Pe5tNAOpuNgDgyqapUsgZN3W7PxO1/Oxon1dtAyD3NBnEfq0zdGg69kK30jLSll3I1ObWScjMYAE5M/NO7AYiJDvvAGLfrrH0SCF4/nTsBq3L1VR/FhmTYew3uqP379z5+w9+3F9G4rY3PT31+OOPIeIvfnE0m80QUavVfuSRh59++ndKpU9GT2GmcwAgQXj9GGKSCgC4fpMQOur6Ky+9WZ9f7989fuXiuy+b6s9dev5UbqJ/6rH3tXmHDLf/5t2lnWODd00HTddIW+mhojbkyI83Seyd6VKJROLTIWkUm0jcMumhwvQTB8snFnTHkpHorNUyoyWr4EipMmN9djGTKmV7iUzvTkk598wriz8+mZvoH7p7GwMM2n759QURhJnBggjjzkYdOYYdDwg0U9fSNoKK3EBFIvbDbF+6NrfOfniCF+zhQ9s5aowzxpkisnIp1uhCGPfSsQhREclYhA03aHk8ZUw9uMerNJVUjPPxB3cP3jW9/tp8Z73Wi2omH9krw7ixsBF1/aBcR84Nx+KGXto1WpoZZTofv39X7cKqu9UiSSqOSMG2z919z//0W2aS6ZS4mUceeXhycuKuuw5UKlXG2PDw0D33HB4cHLzV63q/0sPF0SOz3XLDLmVkGHNT54YGRF6t3bdn/KbJS82lysrR80N3bbt2I19PmalStr5Qfp/hRE9+aiA/9XZWWKvV+pjDiUQi8WmVhBOJxC2jWcbQ4e0rR885/XmrkCrOjACBX2sPzoyMP7j7hqpTr9raOHXJq7ZULO1SZvCu6exYX++Pts6vzv/geP/usV6hBQDYxfTofTPLPzm9dmwuM1qMu4GMYiUIgESEstllGovd0Mo72544aPdnAaA2v17+5/mF7MvCj+IgIklW3ondUDf1KFbc4DIWoAgAEFFGgmK5efLSrqfv3/XFB4QX6o7VaweZmxwI297s7xxhnNt9GRXLzlqtXa435tcv/MvRvtlxq5S2ck7v2ig70adZ+sapxZ1ffDAzXEgPFvr3jF9NfEok3mlycnJycvJWr+LXlCplzLwz9+1jumOFTTczVmKGxjU+sG9y9MjNu6xGHZ8xxs0bf1nrKVP4kYzFDS2VSFFtbq270ZCRsIvpvp1jxs0SqBKJROJDlIQTicStNHZkFr7+VPnEwurR871bJh7aM/6ZPaXZ0WvvtnV+9dJzJ8vH581sChmGnaCxuDF4YHrikb2I2FmtaZZ+NZboMTOp4o4Rq5hBJFLEDT3V7wACEJFQQcNFjWcnB+y+LACEba8xX46anvTjzGCBW7pbaXVWqnZfVsRCSQmhkkIhQzOb0m1ThJFmG9nR0ubppdLOsfRw4bqXvrbfiw1mNtW3e7w1M7L0/GndsYxM6tp9VmbwbU8emn3qnqRfZOJTr7G44Te6hmMCAyVla6kiwrh/91hxdqy4Y/imD+EGj4Ows1EHQN02zWyq99MjY8E459eXGPn1zvwPjs9//zg3OOM8DuLxB3aNf2b34IHpmz75ByT86CNqbptIJD5ZknAikbilEMce2DV41/SOzx+OOr6ZczLDhRu258O2t/T8qa1zqwN3TTPGAIAIOms1AEgPF0qzozISNy1c1my9b+coM/XauRWv3jVSpu5YyJmMhAiisOtbWbtXAl6fW/OqLc2xVCyYpZsp00iZ7dUtv96xC2kRRFIQ48zMpTRTF2EYu2FuYmBg32T5+PzQoW03hBM3IEVrxy5svL6gmXr55GKqmLZL2dxEH9M1APCq7fRQwS5lZSz8eldFwio4SVunxKcPKbr84pnauZWpzx6I/TDqBjIW3NS75bq7WSeid7bBDdve+usL3NAvv3CGGToCFHcMF7YNcdvorNftUvbCM69wU3cG84P7pwDh4ndeXXrhdP/u8d6JhBSidmGVpLJyTm7yQ2t+5dc7K784112vizDmhpabHBh/cPf76RibSCQ+rZJwIpG49fSUWdg29Mv+tHZhbfXlC0MHt7G3xsciQnqkWDm9nBvvL82OmtmUCGJS1Es3uiryQiNru5WWVcwqwKDRba/VmMaRM802AVBPmQBAUnn1rhJSS+sqFgQEAJpt5icH6gsbow/scvqyF3/wurfZjN0g6gbc0HIT/SP3zmgpU7OMqOO/+7u79PypN/7Dc6n+nJlNNS5tiCBsr26FHa+wfdirtoozIyP3zqwePV9545KSau3Y3OiR2cxIafqJu6z8jRXnicQnl7fVCjt+ergIDHXHutofmTEWtjy/1kn1XdezVQl54V9eXjt6nhs613UjbaHGG4sbYSeQUWw41uapxerZy8ILYy8Yunv76L0zCz860b/77ewmrmn5bcMbJxc1Sx+5d9ZIW+nhYu+n/tfmVprnv3l07ZULqVKWW4YM4tWXL7SWKrt+/4HkgDGRuGMl4UQicbsLGl3N0tn1XV8Q0cxafr0DAMWZ4eG7t/cqua/ewa91Yjcszoysv3qxcnbZzKb0lMF0TQQRKamZuopiQAYASkglJDJGkoyMzbUr/ywwXeO6lipmHvxfvmxk7UvPndJti+nMzmeyYyXUOADIOH73Uoduub51biU73pceLhKR5pid9Xp7ubJ56pJXbe34/D2j9826lfbJv/9xqug4A4WBvRPdzcbGicWg2d37hw8nxxSJT43YC9eOzQ3sm7jhds021o7N7Xz6Prg+nKieW1n40Yn+PeN6yjKztrfV7qzVSFHtwqrumOl9U8ix+uYKIkqhLn731fVX5hSpwbuuy2vyt1reVvv0P7649MIZABh/cPfw4R2j9878Gh1aSVHl9NLZf3xx49RidqIfNZ7qyyJDZyS/fnzezDn7vvbI+3meqOv7tY6MZaov+2naMiAVQ+1V6i6ie1kRMWcch58E++Y5bLcLGVDUAC2Neua975xI/HJJOJFI3O6QM1L0zttJAXIGAJmR0sC+ybVjc2E3sHMpYhi1Pb/e3fPlz1g5J2x7TON2fxbfmm0Ru0FnrSZj2TuIYLrGOCOpZBTrKYMbV+IWKSQA9UoyBvZOrR2d698/qV0TPPjNrozk1Yrwm2ouVcqvzQ8d3gYAiJgdLTkDueL24cZCeejQtrv+uyfKr108+59fEH4YtFjQ8q2ck5vst/Ppyy+eLWwb+pUa1yQStzPNNkePzAbNrn59WpAMo9Ejs9o7Dg06azXdNnoRdWHbUHa0VNwxrITcOLEAyPSUWT6xoKeM2I9i1weGrbUaKFr52dnR+3cZaQsA/FqneWkzaHnpwdzwPTtkGNcvrq/84ty9X39q7IFdv9LihR9d+NbL57/1StDokFTty9X6xfXCtqG+XWPc1DMjRW+r5dc7dvHdrkplGF/6yRuN+fLqKxcAYPTIbH5qYOKRfe/sfP2JQ9KHS/+gFv9fkC4RQbChlMDSN2D6X7GJ3wP2gU6EPgrkl2n9WfCutPUns4TDT2Jm+61dVeKT673DidnZ2ff/dJ7nfYDFJBJ3IiVV7fxKa2UrbHlGxs6O95VmR2vnVzvletT1rZxDQoowjr3w2iwFUhS0us7gleyCyc/uT/VlN04uBi0PiMztw317JoYPb1/52ZterZOdGAhqHTPv9MZHMJ0jYmlmxK20hBfqtkFEMozNdNrMO1cm6hEEja7uWAP7JwFg6NC28Yf3rB29kJvsM9IpJaRXa7sbjZ1P31fcMfIu7y72Aqbza8cYc12zi+nYK+i2WbuwdvG7r1XfvJwZLokgVkJ0y42w6w/snbBLmdZy5SP4vBOJW8Ppz+kpc+v8qplLXz0bIIJuuZkd73f6bpxOrWJ5bU0UN3Xb1AEAgQFi49JGryuDDCIjbREBxUoJ0bhcQc7GPrNbM/T2arWz2WA6N3MOYwwtPT89iAw3TixkxkuVhTW31k4Xsn3Tw/mpd222S3TxB8fP/8vLmdGiu9lIDeS4rqlYNJc2eyO69ZSxdmxu9un73i2cIJr7zqsXnnk5M1Ls3zfJGHYrzY3XF7ytzt6vPvw+5/HdvsrP0dJ/BmQkPDAKkNmJFFHrHJ353xAkTH7tnYUxt5K/AYv/iaovQWoUmAUUQ/0EhDUY+x0sJDs4iV/He4cTrut+DOtIJO5MMhIXnnn5wrde0VMmN3UViaDtpgcLbqVpODY3NBFEA/sm0wP5+sX14sywnrIAQArRWqwM371j6OC23vMg4sD+qYH9U712rlcTkIK2Z+ec1EC2yaC9WmMaJ0WklDNcnH7swOgDu5rLlbDpDh7cPvfdY/XFctT0MEMkVdjxmcannzg4cu8MABhpe9fv3W+kzNbK1uKPTogwzoyWUoU0APmNbqr0S68hNNtUsQRFcH1dhwwF0/jq0fPN5YqRTr2VR67rKbO7VjPTtuGYkRd+JB96InErIMPJR/YJP6qeW7H7s0go/CBoeYP7pyYe3vfO7CMza8d+eMPPTtQNvFpbhDEyVLEgAi1lykjKOFaxBM5UENcuriGiVXDq82XhRVJIJPJrHc3WNdMwMvb8s8e9rXb1wgpojBGO3jubHevb/vm7b3pN37i0sfyT00s/Pd1eqRIR1zUZRFzXmK6Z2VTY8YUfiVgUdwxXTi93Vmt2MV2cGXlnc4j6wsb5fzla3D5slzIAQESmY9FwYeHZ48XtwxOP7P2wP++PkYqpeRaAQ7CO1jCw3nu3wR5GIKq/wUr3we208a/WfwjVl7B4EN6ap0jmADXPArcwtwtY0q0r8St773Di+eef/xjWkUjcmS7/7OzcM68UZ0fsfLp3S/n1hZVfvDm4f7p3LEBE3la7s14r7BiunLnMDY0xJsJo7L6dI/ftJEU39Gq8oQk9NzQpZaovZ2ad3MRA5IWcc90x3WrLKqYH75q+mmk9+tCuV/+v77prDW+jCQBM5zu/cGTv1x69eoWR6stNPXbgjf/0UyObypeyVi5FAPM/eN2rdmZ/977s6M3HEuenBobv2eFuNq8epACACCO/0dFSxtL3T6eHCu5mE4h6l1PImJ4yw7aHGvuANaOJxO2mODOilHI3G83FzfbqFgDkpwd1x0oP3aQ3WnFmdPjuHa2Vrdz4lXxCGYny8fnYDw3HisOI65oIhXBDZEhAwFF3TOGGBLA1twaKAAkUoMa6m0232rJKGa7xuOuH3SDVny/uGRNhbDq2X+uUj88DwK4vPnDDGrbOrSz++OTGiYXIDVJ9eRmLoOViB7mhc1Pnpt5Zq2VHS1vnV8OO37i0iQhKqOkn7tr2xMHs+HVpkK3LVa5rVjENAH6t3VquSiE7azXNMs7+1587Q/kbumN/ksQtIKEgRm6/FUsAAAA3yVuFrZdp+DdunzwiEh76q8oexmtmsyMiOBNU/hGNPY3ZmeseEHeofoL8MqoIzD4sHgL7lzYOSdyx3juc2Lnz5rN1EonEByQjsXVhNT1YuBpLxF6khLSLWRHGIow1U0dEpz8nvDA9VNz9lYeCWkdJFba63Y3m6tHzvT5IuYn+iYf33jTNIDNSkn4Uu4HuWM7glbJHGYrGpY30yHUBQHqkeO//+sWw1oVG2Gs9mRku3LBjuvTTM/W5tbH7d17denQG8xunFo20tf+/eeymp/mZkVJxZmT91bk4jO28wzQedf3OWm3y0f2F6WEASA1kM6OlqONfbUeDOpex8KqtwnTySyvxadNY2GgsVaxCemgoH9Y7XrV18u9/vPTTN8bv3zVwcFvf7KhVTPd+lDIjxaGD29aOzcVd38o7hNha3GgtVwb3T7dWqzpC7EXIkRTJMGY6122Dc64X02HbF0GEnDHDICGJCIFAQdTyiAgJVCzaK1uR63fW69nRkpm2U6Vse3Wru9lMD+ZJ0erL5zbfWPZq7ebihnCD/n2T1bOXYxHqtuUMFVqXNrrrjcx4HyhQUm2eWvJqrfHP7Om1p4u9cO3lC8KP9v3Ro9cWRcgw4oaGiH6ts3Vu1a22dNsw847wotbS5sKzryuh+veM37Iv5gMgYAAAUgBefyZDhADANJDv0f7u44TCVUTIb2zsS9wCABDd6251l2n5G6r8HOppQo1EB/sewP4HceizH9NyE58QSSl2InHLBM0uSWVc8xtX+GFnrZYqZTtrtdLMyNW6ZyOXIqWyI6WhA9Pl1+e3zq3ULqzafdm+3ePdjcbGicXuRmP3lx96Z9JR3+6x6ScPLv30TH5qwMylECHs+O2l6sRDe4YPbXvnkpzBfH7nzbs9Bi3X22o5w4Vr0xgYZ5mRUtByva2205+76QO3PXnIcKzK6WUlZS/+GT60ferxA92NJgBouu705zprNSWkZhuIGHV8krT3qw/38qwSiU+N1kq1sVDOTfZbOWflF+fbK1UVC6XI32qXX1+wS5mJh/YO7pucfvJQ72d54uG9dim7eepS0OgoRcINUeMDd02ZGbtxaSNoekBXmjQwjXFDl2Gs2baMBLcMTddQ40Gzy01dxVLGAqUyHSv2QgBwNxtEyiqmYy/0tzrpgXxrpTr56H7N0o/9zbeWfnom7vqALOr63NS6lRZJFbRcK+8gY1YhDQy75bqMBRDEQTj2md356SvVF3rKLM2Orr1yoX/3+ORn919977pjiTASsVh/7aJXbSmpoo7fy54qzo7ULqxplt63c7TXXuITxsgDT6GKgOLrbpceOeOMCJADyRuDjVtFswGAZHjD9g+qiADgmjCDpE/L/0zVo1C6F7jRuwm6CwQE9iDmdn+Mi07c7pJwIpG4xZDe7tokwkgEkVtrR22vPl8u7Ro1MykA6DVlQsTYD9devtBYLJd2jvUeojsmt42lF87YhfTurzx0wxEB17Wdv3s/1/WL33sVAQCBCLY9eXD7bx5GzjvrNca5VUhz4yb/FJBU7fVa0HCZxtKDhdgP147NvXP7ULP1tWNzM0/d+8vCCcbZxMN7R+/b6dfaO5++zy5le21nmMbHH9jVWCznpwa5oXXLDaVUZ7XGND72wK69X3k4SXZKfMq0livrx+cHD0yvvXK+uVDWHBM1Rm5ICIioIrF1fqW9Uo26wb6vPaI7lpIqPZS3C/usnMNM/ZX/41vNy5XNU5c6azW7kLYKTtDyQCpgQIAiiOxCWoQx07hm6iQkAEOGMoyBCBkCURSEQEQESsi4G5i5FNc1M213qg0klLF4/f9+du7br9p9GTNTDNte5PoiiLsbDd2xSFHQ6MpYarahWbpumsSYXUgLPwZBMoo10yBFbrXlVZrttdrxf/fsxhuLo/fuHDq4TQQRN7TSzomVX5xzN5tM40bKAiQZiqgbRB0/Mz6w/OLZmaeOZEaKt/pbelfeKjXOULiF3AB7GEv3ALcRGfQdoeX/QmEDtAxyC4hAehDWUHiQGpEbL+LG86insXA3ZmchOwPIiQjCKoRbyAywhkDvnVETNc9CZx6iBnEL4g4AQlgHzYbUKA5+Fs2bp5X+CrQ0WINQf52sAvgViLtAArUUhU20R2D9++ryPxHTMT2J9giVn8XsDIRVoBhkjIwTaFD5OToTkIQTiWsk4UQicctYhTTTeND2zLwDAH6t01gox14Ytj0gqL55ubO2lZsaHLxrOmy6Tn/OzDv1+fWVo+cHDkwBQNj2ahfWuptNUOQ3Ouf+6ReAOPXYgRuGYVk5Z99XH554eI+/1VaKUqWMXcwsv3imeWmTiACAcT54cLq4/7o4obNeW/zhicXnTvX+d/TIbHqoMHxoe+QG196NFIVNN3bD+sU1r9IUsbTyTn5iQEsZ3XIjaHb1lOUM5s2MzQ3N7ss25sutlQUSyu7LlmZHhw5tXzl6Xkly+nNWMR3Uu8jYyOHte//wETOXDNlNfNrEXsR13phfr18sA0MgEt2QGZwUMI3JSLibzdyR2cs/O1vYPqSnzI2TizISAICImm3U59a9ShMHC3ZfhoTSLUO3jMgNgmaXGZpu6nEQMURAiF1fSYIgAkkEAAhA0Et5AiAAAIKg6aLG0sNFxjk3dOGGrcWNhR++bmRsIGiv1RCRpCJCRIq6ASIh54Ak3FB4UcDc/OSAVUw3lzar51bCrl/aPdpeqm6euiTDOPZDt9yonl06/R9/WpoZ6ds7sXV+VbOMxoV1QjKNFEmphJJxnB7IhW3Pr7UAQATRrfx63ota+Re4/M/UOE1MB6YzptPQk1Dcj9wGPc12/g+08gxtvQLcBmBAMYFGosK4Des/oKBMpEDPYGqMTf8R9D0AtWMUVKjyMwDAwUexeBgHH1Irz9DC3yO3QTOhs6TcFZYeh+xuAIDyj1X1ZZbZrtDQ3TbxDOmfB/O6ghMiBfXXqXUOwxoxA1OjMPAwmkUAgqgJUYP0PBh5HH6Cuouw+j2I28QtJKXiBkgBeoaaZ4FiIKlkhHoOohqRhO4SSB+EB1oKtBSoWK19n43+9ocQ2yQ+LZJwIpG4Zbiu9e+ZWD16Xk+ZRtquL6y3VmtARAoMx9BsM2h5wRuXYjfkBt/5xfsZZ71EBd3Q3Y3G5unl5vIm1zjTGJHqrNdP/8MLfr2z5ysP9eooZCQqp5c66/Wg6SKHVH9h6OC0lUud/S8/v/Tjk5mRopG2FFHQcFdfPrfj6SODj15pRe83unPPHCufWCjtGjUcm5RyNxrl1+bNvENSmLlU7wzEr3ebS5tupenXuy/9798AjnYuo6WM0syIkqqxuNF7trH7dw7snSzMji4++/ql509xjQMDGcmpz+6ffvzAff/z0+Xj8zIWvTyo/j0TU48fuLZuO5H41GCctVdqQaMjIwFIUVeCIiWxNwAGAZSQJJSVd5aef6O5tGn3Za1Cmms8aHsbr88TANM0BNBMAwwARK/SZJxZ+TQpEH4ECFEoZBgTEXLGGJNKIgAAIyUJUbeN2PWBiJQiAr/eBcLMSDFqeTKOF547GbU8IPDDyMjYyFjsBoCgCFApAgAlAJCIGMfs2IBdymopk3Hu9GfbK1vCC5tLmyIQMoyICFEBQxGJ8snF1mpt8OB00OgwgzHGZSyAOBBYeSfVlw27ftT0xh7cdXVS+G1IrX6P5v4dtOfAyCMAxV1iBiz8HSyZYJVA+JDZBvYITH0VgjoyTt4q+Bugj0B3AVUI3CYAiNsQ1uXlb+L6s0QCM9uhdC+ShM6i2nwRKy/S2vcAAGRIoktxBzRbuauIOpXuQyVh48dy9duop00RYbCFlX9Wo5/DqT9Cqx8AiCQsf0Mt/B3qOaWlIKhCWAFnUuX2IihQIW2+BKXDLDUKY08DagAE6UnsLhEaKCNSAoIqhFXEK5zhAAAgAElEQVRABswALUPti0gRASJqAEhGAVUEqIFmUussLP1/MPNvgL3bGNPEnSMJJxKJW2n8M7uDZvfNb7wU+2FraVNGkmnMdiwRCRnGXOORFzaXNg//j7819sBuAOj1WfLb3frihldtGSlbs3UAYEFMSmm2vvzC6exY38xT90Yd//w3jy786ISMZez6MhL+Vrs0M6qn7fZKpW/PeGowzxgDACvrmGnrwjdftidLpZkRACi/dnH1lQuD+6eujOLmzO7P+c3u5huXnMF8e+10Zqxk553axfXOep1xpmIhEAFUqx0UZobXjs15W63xB/dmx0tSyOZydeUX5/MT/e5We2DfZC+FKQ6i8vF5GYq9X3148OC0v9WZ+e17zHzaLqSR3U4N2hOJD09zaVMKwQyNRQIUKSGVIghjACCpiBQ39NbSJtO0OFjXTINbAQBkR0tG2paRIKLMcNGttDQvjP0obLlSKlCq176p1x6NlCQgQECGyBkTUkl15eURZChIEgD0TiZJKL/Wit1AT5mGYws3ICIZCiWU8CN6646oiAAQATlXinrpUjKO2uu1gb0T6ZFi0Ohqlt5arkReoIQCIGQIjIFSAECK3M3G2ssR0xgyJsJIxhIZQ8Cg7YUtz8ilSCgjY/+yhMlbjqI2LP8jtM9DZgaQAQBGbejOExBKTtIHzYHGKYpdNvQ4jDwJhXtg+R+xcRIbZ4AE8BSQQpKEnMIKcoNaFRz6DTT7r7xA2gFkavm/QlBDUAoIVYxAFEWAGrXPkwwwqICexqACyIjnVcrROvMwvwbChx3/PVj9sPUqLfwdZHaSkcPWGeouKtRw61WqvkwyQKufVIxr31Wag5WfUdjA4SdRRSBjCKtkFDBqg/QIOCIH5KgCgAiQQVQH5GAUEBGYDnELmMUK+9Xqt1n/A1i8+1Z+MYnbRhJOJBK3EtP4zqfv698zMffMK+crbSMNdjGj20bkRzKMSSnN0gGxtH24N4EuN943/sCulaPn26tbIo57lRVEJIWwi1l/q+MM5BuLG+5m48K3jl167qSWMtqXq0bGRkTG+ebpJUBkGhNhHLb9wvZhM2MDgF3KasuV7mqtF06012p2wbkSSwBIIWrnVuvz6zKIVSyUkOtHz6POSUpnsBg0OkSADAE4qXDrzLLu2HY+EzS7+al+pvHceF/Q6Ky8cmHbE3ddLYfQLaM0M7Jy9E0jYw3etc0upHNTg+yTWIWZSLw/3lY79sLcWP/WhRUSSkkJ1Ls0J2SMiECBEqq72YzdABnmJvq75boIIr/esUtZZEy3NM0yirOj9bm1sOVqtqFzHrZcKWMUAKSIgHF25XoXQMWyd6hwhSIZRoCI2KvGAkRUUimpYi8ozY6m+rO1uXUiAgZxEAEAKQAiAALoHaEA50wRAVDQcK1ciiHLjvUBQONiOez6vVcBRGQMERQAKfXWy5FdzDQvbSopgYBIIUMiClte1AkG9k5MPXbg9t1KaJ2F+ikwSr3PloBAtFGzQIQgA7AGwR4GAIxb1L0E838PI2WovARAwDQQiuIOIMPeG1Yh+GVgBorrxv6iu0r+JiCnKx85AiIBIEmUCrw1UhEyDVADPQtoAwDolgrWceVbQJJN/L7aOgZGAe0BaJ5R7Tm0B5GZ4MbglQE5BFU0CqRlUMVUfRmYjv33Q9SicAuMArYvkBIAAMiIGShD4JZCjqiBEsR470SaesV+WoqcbeBeAncFknAiAQBJOJFI3HqIxZmR/n2TCz86wQ2td9xvOBY4FgAEjS4pit9KKdYda+jwjgvfOaZiAQpAkVRShsLI2FYuFbRcd6u5+OyJuW8f86otEQuGqDuWklL4sQgiRCBSUpAIRWupQkINHZxGjQMAMzThXxkbJyPB+NtNSNrLW42FjVR/Pmh0chMD+ckBt9q6/PM37VwWkEXdwMynGUMAQM78Wjt2A6uQkrEQUayZBgBww4jdQAYxvFXWQYrqC2Wv0n7jPz7v/PAEAGz7jYNTn92fmxz4uD73xCdMvV6vVrdM0xwcHLBt+1Yv51fmVlprx+YGD05rlr569DxIuLLnD71onACB6VyEMRAxTTNzDiCSVO5mU0QCiGQomsuV2AuEH5NSSkgAlLHgpsZ1XYQxKEKNYSRQ06RSqBTTGOOcFCkhiAiRAQIgklJc40SEHFUk0DZIqdZShaTqjcIkAMYZIhABvdUxGhkyjUshGSIBiEigxhlnmqkDR0AERQDINIaIQECK3oolUMWSoHewAQjAdIaAKBXqqGIVub6ZuY2/06gOjPdiCQACEaAMATSEAIARaiAj4DoCo+4imn0w/+/BHiF/A2QIMgJu4ZXHKgAOwkMuSHaxF6cBUOxCWEVQRByQGAhCeiu0QkXEhA9AFFQJNRZ3iOvAdIAIYg9EBxb+Tl3+JyLFiKRw0d8E5CA8gA6EdSQBIIkQ/A1ABowrIox9Wv0OIKe4jXGbZNB7OSKJQIAMSDFEAElMA4pAdIkQVQSMI3ACIOA3drJK3MGScCKRuC2k+rNKEUbiuluJ4jDUTasXElRPLzcvV4NGtzg5VG65ADJoe0bKNBwzVcoiZ2Hbj9o+kSTRuwYASaCU19sv1GwDFMlYkFJBswukKmeXuan1750EBBnF2lsT68xMKn4rtFBK+fWOnraYxpVQmqkjZ2YmpVmGW+nEYUSShBdqtsE4QwBERI4iFAQUtrwIfNQ5KIEAUikRRLEbelvt5uJGt9oCAiufMrOpVF925ei5sOVOPLzPGczZxaxmJSm5iSsqlco3v/mtcrn805++AABPPPH44cN3f+5zT2raJ+lXGJECAGTYv3eis15vLm0CgIwEEJFUgKhZuoolIFg55+3JM5yZGbu9XNUMzau2CYhxTkpxXVNxLGMFiIxxAGAMpVRM4xQrUpIB6o6ppywlJNNY0HJlJAgBFaHGgHElFSkFiAhAQlZOLxORDGOk3jkE0JUsKbpyuAAkY0kA3OAkCYjMbMrbarZXaqgxEcSIqEgB0NWd7Ct6oQWRV2mRUqgAekGNxjhDUsQs7je6m6cuTT124OP+Vt4n5Ap1kAGILkZNVBGENWIcRIAA6K0ArBBRL6MJtDTZwyh8jGoAvbMdBUoCECgByICAhI/dJWAmmUUkgmAT3MsABBCDAgJ19VMnIIZIFAMAAiERuJc1va2YCSBAuqBZFDZAuKAipSR6a6ACRHalOy2pt7oJ05UIT0kGjIgg2CQl4Jq56wQEJEEEgECkUAlCjbiBDEDPguiSUiQFi+qw9i1Eg4IaSg/eMcIicQf6JP1bnEh8ivXtHh+9d+bSc6e0tK3bBgCQUkHTNZ3U6JHZzGjp3D/94uK3j+lpS7cNr9GOuwHqnCIlgkiEMdM1AAqbXakUAqLOUCpkrFfZ2Ws0S1IpqUgSKgCOsRcB0ubpSyIUmqV5Wx1EIEUAUJwZvvi9V8Oma+YdFQgiYjqP2l52rGQVM1KI+txaUG/HfsQ0zjgTfkREuqUDIgACougG7eWqX2kHTZfpzMw7MhSd1Vr7crW5uBG2PWQMOSKiUqp2YTVsF5nOz/3T0fLJxcED01zn/Xsmxh7YnQQViWaz+fd///88//xPpqam7r33HinF3NzF55//ied5X/7yl2716n4FqWJm9MisX+vYpYyVd5zBvIqFt9UhYpyh5liaZQT1jp6xtZQRdvzO6pZmm4BIQkZdX3AmIgGAYPbyjogAgSEokpHghgaAjDNShAxIAuqMGRpylIHUHZMZmowlQ1RAoCQQIEPiXNO4EkqGsRISEdHgEBGJt8otAK9sn/faVRORkFrKjONQxkRSNZcqmqkHTRdIUS8+IZKxYBonQAAkuLLLroR8+ykJlCTOiJsG07mKJWOss17/+L+U98seAW4hAHirQAqYDswE6SEopZDJoDcrkIgAAYIqkoDsrPLKGNcQgCIfGCISECEgIAfgIHxVew1U3DtJIBK9K/4r0RwSAfz/7d1JcF3HuRjg/+/uM94ZF8PFSBAQARKEJtIcNA+WLNmRTDt6ju2yYyd2VbJJ6i0cl73Izs7CXqSyyDJ2pVyVqpdNXiqW/FLSsyVbyntPsmVLtihKIimJ4gCAIHCBO52x+8/iXICDZIqEJYIC/2/B4r23edA85+Dc/rv/7iYDIovFAEU2jwWJUGLaFKINWiMSpQF2U+U0UgqUAGUBCQCYbCs9AlpLWCMgIjCISCbNHvmIhmA9o42QEiJAFARElAiSJGzQIRKQyou0RQAQLQEBvPafzNLLMPE1MXDfZl4ddh3gcIKx64LlObd96zPBUvPMy8cszxaWNKl2iz4KHNo/VT8+f/TJl6pTw045BwRxIxC2lQYxIgpLoRCd5YYOEtIGBHbTDAhAm+ybGwgIgVJDaQpCEAJo0iZFxISi+T8cE5aVr5Xe+Jv/Fy61Zg/dWbttYurx/UeffMmrFqWt4mYQNzv5oWphqGp59so7C/UTC04plwQxSiGkNGFskiQFQiHsghs1gySIutnZAMqz42ZAAIuvnSgO9QhLSsdKoxg0KN/xSnljzNnX3jWxRiniVztpkDhF7/RLb7Xm6zP/4u4L067YDejXv/7N008/s2/fpxynO3pWLJYcx3nttcP79+8bGxvb3OpduXyt4vcW5185rnxb2ipbk03aUsepVfJs37PzTtIKSJtguaVslYSJTo2OkiwhRqcapQAiSo1JNSohlCQiMmS0oTDJJkCbOMsvIiDSYZJGqbSljlKvp5B0YkAAIjLZQwKFQG1M1glAhlACpcbobgbOuvOvs9auNnbec3vywVIzDWPShgyAQCADBISIBNkwC2TJXEQAqFy7ezhEoaS0pEm1tJW0ZBTG4KgL98e87pR2yW1PmDf/KxgNYMBAahJpNCAI0Z3rQEBZbhiakDrzEC2hVewOMIisHS+ys0GkUTqgO0CAlBAKUj6mTTSme9KyYBGzAYUspOsu+JvNpiAQoE22NR6ZhFBiGgGlWfDW3WQEDEI3mFv/S3eVYFyrM15wpbO0u27QAmQQBZABMBoFQLRshC0oBZOiDkFYJCxIO3Tm7zA4bZKGGHn8Gl8Tdl3ZOuHE6urqT3/608OHD2utd+7c+a1vfauvr29jha/qUIx9VHoma/f/4Guv/8/nl4/NkzHKs/O1yuiduwZun3zlJ0/nBird7SnqzeW35wvDPeFyK24Gxhg0RoepMQalkNmXh0AiQcasfTFlrYusC4oQERWSITBEhlCInomBwYNT7Xrz9G+O2Khmv3b/zi/eURiqLr91OmqFncUGCuiZrHnVIhEFy03bdwnI6ymG9abwpFBSR7GOUqeYQyUp1WAIbSmUQAIdpWQMILgFP1hpR82OUBIMKNeiRMetIAliHSbStS3flkqG9aZQItdXOvaL3/XNjA3cun1zrwvbXMeOHe/r61uPJTJDQ4PPP//Cvffe8wkKJwBx8tG9aZi8++yraRC35uukjTFGCImE4Wo76YTSUVEzkLbtlnPKd8J6S4dxd4BRSQNkuTYZQ2RMaizXSbvpkd10FkQEQ9mjwCn7cTP0q8V8reL2FjuLK2mUhMstoYCIpGMZrU2ku0tCEQCQSQmwuzPFevYLZhHBekRBBIjbHrgl7YSnlt5wCn642pK2NFpTdxj0fJM1a6FarpXNCLd8J41ikxghEaUAbUyqwRgUQtlWYfj63cAOhQV9d8Cx/0ZkEIBIS0BAMlkiV9Y+X4sBAACA0CRkEiMUmhRRZgMIBm2UFgAQEUoHUVAco7RB5SANAM35HLEsMsmm1K9dhe7znADQIJARgsgIQJA26BhQEqXZye8ORnRX8Fr7l7C2JWr3w7UKExAhCuqmPXUnyhgiFJZHaKGJwOkXVhHCBTJNVD4pD4UFcQPcQbN6BI//dzP4kJDX8ewX9jHbIuFEo9H4/ve/X6/X77//finlc889973vfe/HP/5xb2/v1Ra+qkMx9tHK9ZX3/bvHdZwGy01hKbecE1KE9ZZJtVPorsgeNwMU6OQ9y7Mbp5aqUyOWb7fOLNffXtBpCoBkNHYndwrSGrrJCmQ0EYEQIJREiSYxKMEp5+JmQAQohF3w5OTAu8/+sXb7ZO32ibG7Z8bunknD5Ozhd1/8L/8n7sROxWSLz5hUp1HSv3useWapeWbZ8mzhKBPETtFPOqFQEi0hpcq+yizHIm2SIEzCuDjSm0aJ5Vkm0cpzjNFRM9BJd0InGUKlvN5CsNQUSkrfXjlxlsOJG1yn07kklgAAIYRlWe12e1OqtGFeJT/71fv6ZkbffuYPjVPnDIGfc3Sik3YEiFEQSNfKeu6dsq88h8hE7UACamPcgh+utAAg68U3iU6iCLvNRRSIwlZCCp2kpGnb/bfseHz/wsvHzr15qjjcq6O4efKc8l3Ls4Egboc6SsgQCkQE5TlJJyJjspFMRAQBYM43PgERs7YtICAURnr7d40c/buX7ZyXBjEKAQAoRJZRKZQgAjLG8mw77+Vq5eBc02jtFHwiSoI4MaFO0qy9nAaxdC2Vc8Y/fWvf7m2bdmGuAKEN3hDmJ9FEEJyF5ZeJJAoFOrog2IL1uI4AIG0KtMHyKFv8LmmByoFwIG2C8sAbAB2CTkAVUHkg65AKAH3+QN3oDJAQEAgQINul0AAIAi2yHKju2Mf6aBCRUECAlHZ7krpJTt3Dnp/ivRYyIgIKMBql6E6UB6FQeEZ4iATSNUEocjWsHqB3/gdaebDy66NVIBCcflh9HZd+C/33fuyXgV2vtkg48fTTT58+ffqHP/zhLbfcAgD33Xffd7/73aeeeuqb3/zm1Ra+qkMx9nGQtsrXKudfi+6AecZog0JksxSkpYojVb+3GDU6yrV0MwEy2aKTiAgCkRAAyRhhKRSQxikIAQAm1sJS0pZSKUTUSXcKuOXZ0rNbC/X1H65ca3DPTXv/zaMLr75z+qU3paWac0t2we+bHOzZMVi5aXD5rdNho9OeW44SbeUdu+DF7dD2XWmpbtcXYhJE0EbQlBsoR42OP1ASSsWdEAhIGyHQZCkYibY8G1FYOcekWtpWcvEm3OwGVCgUwjC45E2tdRzHxWLxA//J9Uy51vCB6YU/vjO8f4oIgnpLR0m02jFaK89uzdX93pLXk2+fXUXZToOYUqN8G1OtXAulMGkqbQsRpWMBkI4TlIIAlWfpROtE+30lqeSOz+7d8cie0YPTJ5790+rJxXee/aOwVH6gPLR3sjVfXz42T2SiRkfYynJsaaukHQF0M5NAogA0RsNFaU6oHMtoA0i12yZACq8nL5Q898bJbI5WtjIsCARE5SiT6N5doyjEnd994q0nXzr5/GG3khdKViYHg3ONlXcXopUOEQkLLM+e+PRtM391l1fJb+J1+VBo5QAQ7SKoAiQtsvKoQwAJIAgNQDZlvbsFefcPAgANVhGFonCJgMAEaOVJlBElgFib2CCADIIAFNQd8KCsrU9EWcpTtsgFkAFUQEQoIEtaRYnCAVrfTTzLiZJZphSaGEgYQ0KuBzrdqPD8WEoWqBCSyCbhZ4s2+WCVBQIRYdIAAZh0SMdABEKt/SSDRCAsRAs671Ewf72u8suuhS0STjzzzDPj4+NZAAAAU1NTMzMzv/rVr77xjW8gXnqHX77wVR2KsWvAKfjKs8PlVrbXtXIsk2oyJg2TwnDVzruQdQ1a6JZy4UobjCEDJLqLMgoBVs7xekvG6NaZulQSAJxiTlpWGsY6SZXvWBfMeBZSXjAREwAAEcfu2d27a2Tkzl3hSmvu5WNn/3SiZ2oQUUhb9M1ui5vBainnVvI7//nB1/7m+dUTC9n8PjzfDYbZ4iZOOVcYrkarHafkZ3lTpI20ldEGtfH7Sk7JBwCUonl6qTTSm/3v2I1senrq5z9/cnS0ncvl1t98772T99137/T01CZWbMN0nKZhYhX8/ECZDKVBlI3O6Th9+5lXCkM9/bPbwpV2GsRJEC288nYSJkKglXN8KrTmV4gSIJCW1FEiXbs4WvV6igigk1R5TnGkpzW/kv0gt5Sb/sLBNIxHDu78x//8t73TI3bRk7a18u5Z0qBcGxCFJe2iB/N1JMgWgSVjAAWtt4hRCIWks4jfWDm3UCtLKZTroBBGGyASWbd21kI1JG3LJBqkAAK35E9//sC5Iyd7dgx1A4YdQ327x5aPzq2cPDvx4K1j9+weuGXcLV/XsQQAQG5MDD5Ey3+g4i4wEcg8qA6lLVgLInA9guhOVRAGDIBAp4dUHq0SNN8G5ZEzgMkqCAtMnE12AemsTdMWIjuNgIACEFEnhlAgrR+ayCAKRGGEAG0AJCGiMdmivN2I0BhUHiBSkgCAlLi2JPH5TLb1oGJ9Ysbapj8EqEDlLhiXMih9MBrSNtglSNvdYjogpwekh0kH7DKo63QLQnZtbIVNo5IkmZubm52dvfDN2dnZer3ebDavqvBVHYqxawMF1m6dCJabzTNLYMjrKRRHqp3F1Xi17ZZyaxMcyYS6tncyP1hBJQGItM7GKHJDPfv/+vP3/McvTz6y1yl40lF+bzE3UEGFaRinYYwCnbXvcmNM2omySRqX8HtLg3smtz946+xX7xs+MLX05umkHZIhk6RRK4w70fj9Nw/vm/Z7CgSgk/TC/bNQCkSwPKcwUMnXKnEr0HEqHSWVsnIuGSOU9KpFv7+UJU6YRPvVQhon5fGBa3CG2fXs3nvvefzxx1555dUTJ04sL9cXFxdff/3IiRMn9u/fV6vVNrt2G5Gth5atdIQCrZyrHEsoKR1LOVbcDoQUuYFyaby/unOksmMIEYzW0rELQ73FkaqyrWyfCunabjnfv3vb4J7J2p7J4QPTA7eMu+VCGsb2BXs4KNeu7Zmc/Mye1ZOLlGqvWhjae5PlOzqIdBDpRMeNTm6gDEKgEpD1UGc73YnunhEmNYBACMqxK+P9w3fP2MVc3Al7dgy55bxOdbamk9EGDEnXQiBpK2WpkYPTfn+pb9fojs/tW3l7vjlfjztR0gmTTkRAe771mbu+91fb7p39BMQSACAcqD0ApRlYPUxphJCC9MEAgqDuWVtbYBeRCAhBIII/REkbiEBYYPngj2K0AGmT3AFIViFugLBBOiA9BBCUGhAEElAgGTAaMFtPqztuQNlohrBIuggCpIsqB6oAKo/Cgu7CUgRg1uZD2EBIAIiEa1lPmbV5GbC2SSESZHvVCRIKUGaFwMRoIpA5M/lN6JwEk0LaoqRDSQtUHpwqAFB8DkozWJrelMvCrhNbYXSiXq8DQKl0UWScDYLX6/VLRsMvXzgMwys/1CWIKAiCG3wEw5hur3ar1drcmmwxhena9FfuXnrj1MnfvalsO2oEaZzaBQ+VrJ9cTNpB1Az6bt+uk3T4npnVU4vB/GrWtdm7a2Tff/hCtm1tadcQSTz1m9ct1yKBVt4zqcmWi7ErOa01EDRPnuu9bZs3WrnMFRRlt3bXdErm9D+8kb1T2zu5Y/9k34HJVqvVe9u48/e/T4M4bgXSkigFGIo7kXSU8KxzR087Jb88OdCaqydh4vT4+aFKe6Hh95WaJ8+Fq23pWEQULDYsz979L+/3xnqu/b2UpqnW+vJljDFExPd5kiQAkKbpx3oqvvzlL5XLpaNHj2UzBWq12h13HNy/f98n9/xbPbnWb99yqvkL94FuL6wO3jElpJh77URxtKpyDqXGqfiopIkpqDdRCJOa8k01u+DGragw1NM6s2QUxnF8/iBn6tXZMWeweMnJGbhzR2e1deYPx51yTthK5V1A4Q2Ui9t63aJv590zLx4NlhqYSKGEkIJIgQAdpdkkYGFLVNL2nf5PTRYm+1PSUStoLNT792yf++2xeKVNhoRA4VioRNyO8oPlOIzy2/sinURBMvLwLNnYOLE497tjAFDbOzlx27bR+2Y770tju67Z01iJpLGwcUSuvGryUyg8kzZleHatZZ4lGkkQhgjI6dc9d4vwBDaOkonJH0RA8ibAqUAwD6U90HwDpCeCBSMUgECQAg2hNGhJE3Yb+igRDAERIQlJKodpE4Sd5HcLu4DBe6BK1D4JuUEZL6FuGeEiCjIJqQJYRTQRqSJFS5i2SCpMA0RhhI1GA2kA7G5ZZ5VJ+ZQ0iFIUiuLV7iJPKEEW9Pi/jof/lSzsUWd+Lud/AdEiWGWSeUgCiOdQ2kn5YApVuOa/j2EYnp9szjbVVggnsnGDSzZJ9X0fABqNxlUVTtP0yg91CWNMHMdCbIUBn78QEWWBGfsI9R2Y9Lf1VHaPxI2Oyrkm0eFyK1puGWOK2/smvlCTrrXw4rGF3x0TtrKKnvSsyQcOjj9yq130u5cDYej+Xcbohd+/LR3l5mwyunlqOT/cE3c68btB1Oz07h7rvX0cc9blr6A3Upl84kDtzqlota1c2+srOuVcnCaQJtW94yMPzB7/379FKYw2kGqTaGWrkXtnRj9z6+rRubgVWhW/vHPI7y9VpoaNMadfOLL0x/dyQz1JJ0zjJOlEhdHq6KdvHnpwNkpiuOb7rhpj1gPjPyf7DuP7PKO1/tAA7C9hWdZjj/2zJEmWlpYcxymXy4gXtaE/cSo3j66eWlx642RusEf5tkl0WG935ld2PHGwMj0kf/366ReOZCX7b9++66v3rJw4u/r2vJV37ZwrXStuhX17to8+uHv58Kl3/+8f3J6CyjlAEDc60Wpn8N6dquJfcnNa1dzY527zhkrthVUdxoXxvuJEX/vUstdXsAseABYn+tIwtvJecaQnidNwsdlZXHUKXm6wZBd9IkzaYf/eicknDoRh6A2XJw7tO/a3LzpFvzBUaRkT1ttGk9GJ1NrKe7WDU+Wpoeqe8fVqDN63q7c9MfTAbgByK3kr76ZA6SfuN8idgqGbRHXOUX2i8XtTPgAodPsNtXoYdQeEWGtWSbCLRhWw/Q6ZmOyKKdycFmaMO6Rzk8aqCt0yqiTbb6nWm6rxJ0yWiUgkdREtYDgnKCCUwqQkLKDUCC9LTkLpE6VkV5PeB6LBJ2F7dIAAAAcqSURBVEB61tlnrKUXyB8HlFrljLdNe9uNVQS0tDOkC7vtxkui+aaaf0qZBIUyThHTFpAmlIQKQQsQJB3tbUMUqbcN43MkPBGeRtIAGqQb9X8uGvwqxQm4u2Bil5W/zZn7X6J5GNI2EJDwo8EvJQNfojC69lfjE/0Q2GK2QjhRKBQAIAgu6uTodDoAcGGu7ZUUzufzV36oSwghbNt23Rs61TuLqRDx/SuxsL+cOz5YHR+88B0ylGUKZS/7doyM3T0TLLekLf2+Umm8H+VF8a07NVrsq/TPbGsvruo4cct5YcukHUUrbUCwSn7v7Fh14qIf8edrA37hg38p9v315ysTg2f+6a2o3gYAp5wbvnN6+yO3K9eGO2fSIDapvjAZo9hfmRvubS+sZAtG+dXS2IM3b+KqkUKID+0XyMYhb/DfdwBIkkRrLaW0rI99w0HXdbMH+BbgbnPVZz910vdOvvB69s7gp24af+CW0XtnhJKVsf7Jh28P6y1hSa+v5PXkG+8tnnrhSNwM5l8+Xp0esQve8F07S9v6+24aKQ31Lh89kwYxANg7hvpv3tY7OwYfNE7uDrnloV4AyNZ0ap6tv/v3r5569rDIliECmPzcXjvvpFFKhtCSlBIIAxrmXz5e2zuZ6y8N3zPj93ZH6Xd89lPl0b6lI6fiRidpx2G9RVpbOccp5/pv3V4Y6S2MVi8Zrnddt1DdEhn23iT4/x7nfyGDM2LpH0BYettXsf2OTFYpbYHKmdx0OvY1sHyMzoFwyB2g3Pja9nUXKPQB3NUNxElrFNg+Kc8+jSuvIMWkYxA+mA4AiM4JAEmUUulm3XtXWL7fWGXLsrA0rvvvwGiRAMHtp9LNYJWyh5cAsACgPALRoh56FM79BoI5bBzGtAHxEqqCsSrGH6PyzaZ4C5gY7DIIG5dfxGgRF58Dk1Blb9pzEIa/6OAFz8Oxz6cDd4n2UQznjKqgNyTyN11UgN2QtkI4US6X4X2jB9koRLVavarC2bjEFR7qEojoeV4WkNywkiTJegtu8POwafL5ntqHrGicz+d7Rz8g4zwMw1arpZT6SK7dnq8/tOfrD6VBnMaJW/Qvaty87/D5fH5gcsRoEzU6TtHb9H3rlFLyw+oghEBEvs9brZbW+qO6bW4o+d352vTYzscOBMtNy3dyA2W3dD4+L16cc5ufyQ/uGo+bQfyVwC54dsFbb6kXH94LD++N26GQ8qp2kdda7/jigYkHbqV2AgR+b7EwXEWBRhsdxlbOBQAyFK60kq/Ebjln5y4Nngt3zk7cOWu0zjbk3uCJ+KTKQ8+/pXARwi+jUOAOgH3RJdtgj1p+BgZm1l6szYfXIQRzlDTQroA3CMIKlpfBGNd1HacEPR+29Uo+D9XtMHoPxKsUnIGkiU6VvEElbcD3NQKHD1K4CNHXQXro1Wz5QT0m+TxUr4tVfbPn8GbXggFsjXDCtu1arXbkyJEL3zxy5EihUHj/bIfLF0bEKz8UY+zylGcrz/7wcgAAIKS4zleKZOyjJZQsjfWVxq5om1REdIq+U/Q/8NP3t/WvCGJhuJol9J6vlRRi7Wgo0OspXH5zsk2P/zcRun3gfny73K41lKUL+e0fQavZLuFazPPnj4bo9oPb/5f/NHZD2SLdCQ899NDx48ePHTuWvTx9+vRrr7328MMPf2DYevnCV3UoxhhjjDHGbmRbYXQCAB555JFf/vKXP/jBDw4dOoSITz31VKVSeeyxx7JPn3vuuZ/97GeHDh06dOjQhxa+/KeMMcYYY4yxdVsknCiVSj/60Y9+8pOfPPnkk8aYXbt2ffvb3+7t7SaRh2F47ty5bEb1hxa+/KeMMcYYY4yxdVsknACAcrn8ne985wM/evTRRx999NErLPyhnzLGGGOMMcYyW2TuBGOMMcYYY+za43CCMcYYY4wxtkEcTjDGGGOMMcY2iMMJxhhjjDHG2AZxOMEYY4wxxhjboK2zstP1oNPpENFm12IzpWkaBAEiNhqNza4LuzpxHAdBIKUU4kbvZUjT9EqKERHf50EQxHGcpukN/uj7JOp0OtmFu8Ibnl0/giAwxiBiFEWbXZfNdIP/968rHE58ZCzLWlxc3OxabDIiyloVKysrm10XdnXWr93y8vJm12XzSSkvXwARLct67733rk19rlvZbYOIiLjZdWFXxxgDAHztPomya7eyssLXzrbtza4CAwBA7lJijDHGGGOMbcyNntXAGGOMMcYY2zAOJxhjjDHGGGMbxOEEY4wxxhhjbIM4nGCMMcYYY4xtEIcTjDHGGGOMsQ3icIIxxhhjjDG2QRxOMMYYY4wxxjaIwwnGGGOMMcbYBnE4wRhjjDHGGNsgDicYY4wxxhhjG8ThBGOMMcYYY2yDOJxgjDHGGGOMbRCHE4wxxhhjjLEN4nCCMcYYY4wxtkEcTjDGGGOMMcY2iMMJxhhjjDHG2Ab9f9OysBbfeH7MAAAAAElFTkSuQmCC" width="80%" style="display: block; margin: auto;" /> .footnote[Focusing on HCA for time.] --- class: middle, center # SECOND ISSUE: ### What are common responses by group? --- ### This is 50 rows of what results look like: <div style="border: 1px solid #ddd; padding: 0px; overflow-y: scroll; height:350px; "><table class="table table-striped table-condensed" style="margin-left: auto; margin-right: auto;"> <thead> <tr> <th style="text-align:left;position: sticky; top:0; background-color: #FFFFFF;"> ClusterNumber </th> <th style="text-align:left;position: sticky; top:0; background-color: #FFFFFF;"> Questionnaire </th> <th style="text-align:left;position: sticky; top:0; background-color: #FFFFFF;"> AssessmentResponse </th> <th style="text-align:right;position: sticky; top:0; background-color: #FFFFFF;"> MeanPercent </th> </tr> </thead> <tbody> <tr> <td style="text-align:left;"> Cluster: 1 </td> <td style="text-align:left;"> MNSI </td> <td style="text-align:left;"> Ankle reflex: Present with reinforcement </td> <td style="text-align:right;"> 0.8977778 </td> </tr> <tr> <td style="text-align:left;"> Cluster: 1 </td> <td style="text-align:left;"> TCSS </td> <td style="text-align:left;"> Ankle reflex: Decreased(present by reinforcement) </td> <td style="text-align:right;"> 0.8977778 </td> </tr> <tr> <td style="text-align:left;"> Cluster: 1 </td> <td style="text-align:left;"> HRV </td> <td style="text-align:left;"> E:i (expiration inspiration): High </td> <td style="text-align:right;"> 0.8107937 </td> </tr> <tr> <td style="text-align:left;"> Cluster: 1 </td> <td style="text-align:left;"> mTCSS </td> <td style="text-align:left;"> Tingling?: No </td> <td style="text-align:right;"> 0.7972152 </td> </tr> <tr> <td style="text-align:left;"> Cluster: 1 </td> <td style="text-align:left;"> UENS </td> <td style="text-align:left;"> Neurotip section 1: Normal </td> <td style="text-align:right;"> 0.7894309 </td> </tr> <tr> <td style="text-align:left;"> Cluster: 1 </td> <td style="text-align:left;"> MNSI </td> <td style="text-align:left;"> Do you ever have any burning pain in your legs and/or feet?: No </td> <td style="text-align:right;"> 0.7872358 </td> </tr> <tr> <td style="text-align:left;"> Cluster: 1 </td> <td style="text-align:left;"> TCSS </td> <td style="text-align:left;"> Ataxia?: No </td> <td style="text-align:right;"> 0.7855172 </td> </tr> <tr> <td style="text-align:left;"> Cluster: 1 </td> <td style="text-align:left;"> MNSI </td> <td style="text-align:left;"> Do your legs hurt when you walk?: No </td> <td style="text-align:right;"> 0.7803376 </td> </tr> <tr> <td style="text-align:left;"> Cluster: 1 </td> <td style="text-align:left;"> MNSI </td> <td style="text-align:left;"> Ulceration foot?: Absent </td> <td style="text-align:right;"> 0.7726740 </td> </tr> <tr> <td style="text-align:left;"> Cluster: 1 </td> <td style="text-align:left;"> MNSI </td> <td style="text-align:left;"> Ulceration foot?: Absent </td> <td style="text-align:right;"> 0.7726740 </td> </tr> <tr> <td style="text-align:left;"> Cluster: 1 </td> <td style="text-align:left;"> mTCSS </td> <td style="text-align:left;"> Position sensation: Normal </td> <td style="text-align:right;"> 0.7721547 </td> </tr> <tr> <td style="text-align:left;"> Cluster: 1 </td> <td style="text-align:left;"> UENS </td> <td style="text-align:left;"> Neurotip section 4: Decreased </td> <td style="text-align:right;"> 0.7600000 </td> </tr> <tr> <td style="text-align:left;"> Cluster: 1 </td> <td style="text-align:left;"> UENS </td> <td style="text-align:left;"> Neurotip section 2: Decreased </td> <td style="text-align:right;"> 0.7569231 </td> </tr> <tr> <td style="text-align:left;"> Cluster: 1 </td> <td style="text-align:left;"> TCSS </td> <td style="text-align:left;"> Temperature for foot: Abnormal </td> <td style="text-align:right;"> 0.7544304 </td> </tr> <tr> <td style="text-align:left;"> Cluster: 1 </td> <td style="text-align:left;"> TCSS </td> <td style="text-align:left;"> Upper limb symptoms?: Yes </td> <td style="text-align:right;"> 0.7446667 </td> </tr> <tr> <td style="text-align:left;"> Cluster: 1 </td> <td style="text-align:left;"> DPN </td> <td style="text-align:left;"> Amplitude: Low-mid </td> <td style="text-align:right;"> 0.7406803 </td> </tr> <tr> <td style="text-align:left;"> Cluster: 1 </td> <td style="text-align:left;"> DN4 </td> <td style="text-align:left;"> Pain in area may reveal hypoesthesia to touch?: No </td> <td style="text-align:right;"> 0.6948315 </td> </tr> <tr> <td style="text-align:left;"> Cluster: 1 </td> <td style="text-align:left;"> UENS </td> <td style="text-align:left;"> Vibration on great toe: Decreased </td> <td style="text-align:right;"> 0.6471795 </td> </tr> <tr> <td style="text-align:left;"> Cluster: 1 </td> <td style="text-align:left;"> MNSI </td> <td style="text-align:left;"> Have you ever had an open sore on your foot?: Yes </td> <td style="text-align:right;"> 0.4088889 </td> </tr> <tr> <td style="text-align:left;"> Cluster: 1 </td> <td style="text-align:left;"> DN4 </td> <td style="text-align:left;"> Do you suffer from pain in your feet?: Yes </td> <td style="text-align:right;"> 0.2711111 </td> </tr> <tr> <td style="text-align:left;"> Cluster: 1 </td> <td style="text-align:left;"> DN4 </td> <td style="text-align:left;"> Pain feels like painful cold?: No </td> <td style="text-align:right;"> 0.2320000 </td> </tr> <tr> <td style="text-align:left;"> Cluster: 2 </td> <td style="text-align:left;"> mTCSS </td> <td style="text-align:left;"> Foot pain?: Yes </td> <td style="text-align:right;"> 0.5133333 </td> </tr> <tr> <td style="text-align:left;"> Cluster: 2 </td> <td style="text-align:left;"> DN4 </td> <td style="text-align:left;"> Pain feels like electric shocks?: Yes </td> <td style="text-align:right;"> 0.5093333 </td> </tr> <tr> <td style="text-align:left;"> Cluster: 2 </td> <td style="text-align:left;"> TCSS </td> <td style="text-align:left;"> Knee reflex: Decreased(present by reinforcement) </td> <td style="text-align:right;"> 0.4174359 </td> </tr> <tr> <td style="text-align:left;"> Cluster: 2 </td> <td style="text-align:left;"> TCSS </td> <td style="text-align:left;"> Ataxia?: Yes </td> <td style="text-align:right;"> 0.4150000 </td> </tr> <tr> <td style="text-align:left;"> Cluster: 2 </td> <td style="text-align:left;"> MNSI </td> <td style="text-align:left;"> Do you ever have any burning pain in your legs and/or feet?: Yes </td> <td style="text-align:right;"> 0.3059259 </td> </tr> <tr> <td style="text-align:left;"> Cluster: 2 </td> <td style="text-align:left;"> DN4 </td> <td style="text-align:left;"> Pain caused or increased by brushing?: No </td> <td style="text-align:right;"> 0.2794203 </td> </tr> <tr> <td style="text-align:left;"> Cluster: 2 </td> <td style="text-align:left;"> DPN </td> <td style="text-align:left;"> Velocity: Low-mid </td> <td style="text-align:right;"> 0.2385185 </td> </tr> <tr> <td style="text-align:left;"> Cluster: 2 </td> <td style="text-align:left;"> MNSI </td> <td style="text-align:left;"> Do your legs hurt when you walk?: Yes </td> <td style="text-align:right;"> 0.2350000 </td> </tr> <tr> <td style="text-align:left;"> Cluster: 2 </td> <td style="text-align:left;"> Monofilament </td> <td style="text-align:left;"> Light touch under foot, point 4: Abnormal(≤1/3) </td> <td style="text-align:right;"> 0.2112821 </td> </tr> <tr> <td style="text-align:left;"> Cluster: 2 </td> <td style="text-align:left;"> Monofilament </td> <td style="text-align:left;"> Light touch under foot, point 1: Normal(≥ 2/3) </td> <td style="text-align:right;"> 0.2088623 </td> </tr> <tr> <td style="text-align:left;"> Cluster: 2 </td> <td style="text-align:left;"> MNSI </td> <td style="text-align:left;"> Monofilament great toe: Normal(8-10) </td> <td style="text-align:right;"> 0.2086842 </td> </tr> <tr> <td style="text-align:left;"> Cluster: 2 </td> <td style="text-align:left;"> UENS </td> <td style="text-align:left;"> Neurotip section 5: Normal </td> <td style="text-align:right;"> 0.2084291 </td> </tr> <tr> <td style="text-align:left;"> Cluster: 2 </td> <td style="text-align:left;"> MNSI </td> <td style="text-align:left;"> Do you ever have any burning pain in your legs and/or feet?: No </td> <td style="text-align:right;"> 0.2000000 </td> </tr> <tr> <td style="text-align:left;"> Cluster: 2 </td> <td style="text-align:left;"> UENS </td> <td style="text-align:left;"> Extension great toe: Normal </td> <td style="text-align:right;"> 0.1996101 </td> </tr> <tr> <td style="text-align:left;"> Cluster: 2 </td> <td style="text-align:left;"> UENS </td> <td style="text-align:left;"> Neurotip section 3: Decreased </td> <td style="text-align:right;"> 0.1966667 </td> </tr> <tr> <td style="text-align:left;"> Cluster: 2 </td> <td style="text-align:left;"> UENS </td> <td style="text-align:left;"> Neurotip section 1: Absent </td> <td style="text-align:right;"> 0.0333333 </td> </tr> <tr> <td style="text-align:left;"> Cluster: 3 </td> <td style="text-align:left;"> MNSI </td> <td style="text-align:left;"> Has your doctor ever told you that you have diabetic neuropathy?: Yes </td> <td style="text-align:right;"> 0.2966667 </td> </tr> <tr> <td style="text-align:left;"> Cluster: 3 </td> <td style="text-align:left;"> Monofilament </td> <td style="text-align:left;"> Light touch under foot, point 1: Abnormal(≤1/3) </td> <td style="text-align:right;"> 0.2555556 </td> </tr> <tr> <td style="text-align:left;"> Cluster: 3 </td> <td style="text-align:left;"> DN4 </td> <td style="text-align:left;"> Pain feels like electric shocks?: No </td> <td style="text-align:right;"> 0.1720000 </td> </tr> <tr> <td style="text-align:left;"> Cluster: 3 </td> <td style="text-align:left;"> Monofilament </td> <td style="text-align:left;"> Light touch under foot, point 3: Abnormal(≤1/3) </td> <td style="text-align:right;"> 0.1293333 </td> </tr> <tr> <td style="text-align:left;"> Cluster: 3 </td> <td style="text-align:left;"> HRV </td> <td style="text-align:left;"> Root mean square of successive differences for hr: Mid-high </td> <td style="text-align:right;"> 0.0720000 </td> </tr> <tr> <td style="text-align:left;"> Cluster: 3 </td> <td style="text-align:left;"> mTCSS </td> <td style="text-align:left;"> Upper limb symptoms?: No </td> <td style="text-align:right;"> 0.0525490 </td> </tr> <tr> <td style="text-align:left;"> Cluster: 3 </td> <td style="text-align:left;"> HRV </td> <td style="text-align:left;"> High frequency (?): Low </td> <td style="text-align:right;"> 0.0512000 </td> </tr> <tr> <td style="text-align:left;"> Cluster: 3 </td> <td style="text-align:left;"> TCSS </td> <td style="text-align:left;"> Ataxia?: No </td> <td style="text-align:right;"> 0.0482270 </td> </tr> <tr> <td style="text-align:left;"> Cluster: 3 </td> <td style="text-align:left;"> TCSS </td> <td style="text-align:left;"> Ankle reflex: Normal </td> <td style="text-align:right;"> 0.0477778 </td> </tr> <tr> <td style="text-align:left;"> Cluster: 3 </td> <td style="text-align:left;"> UENS </td> <td style="text-align:left;"> Extension great toe: Normal </td> <td style="text-align:right;"> 0.0475789 </td> </tr> <tr> <td style="text-align:left;"> Cluster: 3 </td> <td style="text-align:left;"> Monofilament </td> <td style="text-align:left;"> Light touch under foot, point 1: Normal(≥ 2/3) </td> <td style="text-align:right;"> 0.0400000 </td> </tr> <tr> <td style="text-align:left;"> Cluster: 3 </td> <td style="text-align:left;"> MNSI </td> <td style="text-align:left;"> Vibration perception at great toe: Decreased </td> <td style="text-align:right;"> 0.0346667 </td> </tr> <tr> <td style="text-align:left;"> Cluster: 3 </td> <td style="text-align:left;"> mTCSS </td> <td style="text-align:left;"> Tingling?: No </td> <td style="text-align:right;"> 0.0315447 </td> </tr> </tbody> </table></div> --- class: middle, center ## How to make sense of this data? ## How to extract meaning?