Mathcad Professional 14.1 <description/> <author>David Lim</author> <company>Parametric Technology Corporation</company> <keywords/> <revisedBy>David Lim</revisedBy> </userData> <identityInfo> <revision>5</revision> <documentID>AC6E0827-15D4-4202-B06C-19E9C610DD52</documentID> <versionID>A396040B-285F-4F37-881C-9696EB6743F6</versionID> <parentVersionID>00000000-0000-0000-0000-000000000000</parentVersionID> <branchID>00000000-0000-0000-0000-000000000000</branchID> </identityInfo> </metadata> <settings> <presentation> <textRendering> <textStyles> <textStyle name="Normal"> <blockAttr margin-left="0" margin-right="0" text-indent="inherit" text-align="left" list-style-type="inherit" tabs="inherit"/> <inlineAttr font-family="Arial" font-charset="0" font-size="10" font-weight="normal" font-style="normal" underline="false" line-through="false" vertical-align="baseline"/> </textStyle> <textStyle name="Heading 1"> <blockAttr margin-left="0" margin-right="0" text-indent="inherit" text-align="left" list-style-type="inherit" tabs="inherit"/> <inlineAttr font-family="Arial" font-charset="0" font-size="14" font-weight="bold" font-style="normal" underline="false" line-through="false" vertical-align="baseline"/> </textStyle> <textStyle name="Heading 2"> <blockAttr margin-left="0" margin-right="0" text-indent="inherit" text-align="left" list-style-type="inherit" tabs="inherit"/> <inlineAttr font-family="Arial" font-charset="0" font-size="12" font-weight="bold" font-style="italic" underline="false" line-through="false" vertical-align="baseline"/> </textStyle> <textStyle name="Heading 3"> <blockAttr margin-left="0" margin-right="0" text-indent="inherit" text-align="left" list-style-type="inherit" tabs="inherit"/> <inlineAttr font-family="Arial" font-charset="0" font-size="12" font-weight="normal" font-style="normal" underline="false" line-through="false" vertical-align="baseline"/> </textStyle> <textStyle name="Paragraph"> <blockAttr margin-left="0" margin-right="0" text-indent="21" text-align="left" list-style-type="inherit" tabs="inherit"/> <inlineAttr font-family="Arial" font-charset="0" font-size="10" font-weight="normal" font-style="normal" underline="false" line-through="false" vertical-align="baseline"/> </textStyle> <textStyle name="List"> <blockAttr margin-left="14.25" margin-right="0" text-indent="-14.25" text-align="left" list-style-type="inherit" tabs="inherit"/> <inlineAttr font-family="Arial" font-charset="0" font-size="10" font-weight="normal" font-style="normal" underline="false" line-through="false" vertical-align="baseline"/> </textStyle> <textStyle name="Indent"> <blockAttr margin-left="108" margin-right="0" text-indent="inherit" text-align="left" list-style-type="inherit" tabs="inherit"/> <inlineAttr font-family="Arial" font-charset="0" font-size="10" font-weight="normal" font-style="normal" underline="false" line-through="false" vertical-align="baseline"/> </textStyle> <textStyle name="Title"> <blockAttr margin-left="0" margin-right="0" text-indent="inherit" text-align="center" list-style-type="inherit" tabs="inherit"/> <inlineAttr font-family="Times New Roman" font-charset="0" font-size="24" font-weight="bold" font-style="normal" underline="false" line-through="false" vertical-align="baseline"/> </textStyle> <textStyle name="Subtitle" base-style="Title"> <blockAttr margin-left="0" margin-right="0" text-indent="inherit" text-align="center" list-style-type="inherit" tabs="inherit"/> <inlineAttr font-family="Times New Roman" font-charset="0" font-size="18" font-weight="normal" font-style="normal" underline="false" line-through="false" vertical-align="baseline"/> </textStyle> </textStyles> </textRendering> <mathRendering equation-color="#000"> <operators multiplication="narrow-dot" derivative="derivative" literal-subscript="large" definition="colon-equal" global-definition="triple-equal" local-definition="left-arrow" equality="bold-equal" symbolic-evaluation="right-arrow"/> <mathStyles> <mathStyle name="Variables" font-family="Times New Roman" font-charset="0" font-size="10" font-weight="normal" font-style="normal" underline="false"/> <mathStyle name="Constants" font-family="Times New Roman" font-charset="0" font-size="10" font-weight="normal" font-style="normal" underline="false"/> <mathStyle name="User 1" font-family="Arial" font-charset="0" font-size="10" font-weight="normal" font-style="normal" underline="false"/> <mathStyle name="User 2" font-family="Courier New" font-charset="0" font-size="10" font-weight="normal" font-style="normal" underline="false"/> <mathStyle name="User 3" font-family="Arial" font-charset="0" font-size="10" font-weight="bold" font-style="normal" underline="false"/> <mathStyle name="User 4" font-family="Times New Roman" font-charset="0" font-size="10" font-weight="normal" font-style="italic" underline="false"/> <mathStyle name="User 5" font-family="Times New Roman" font-charset="0" font-size="10" font-weight="normal" font-style="normal" underline="false"/> <mathStyle name="User 6" font-family="Arial" font-charset="0" font-size="10" font-weight="normal" font-style="normal" underline="false"/> <mathStyle name="User 7" font-family="Times New Roman" font-charset="0" font-size="10" font-weight="normal" font-style="normal" underline="false"/> <mathStyle name="Math Text Font" font-family="Times New Roman" font-charset="0" font-size="14" font-weight="normal" font-style="normal" underline="false"/> </mathStyles> <dimensionNames mass="mass" length="length" time="time" current="current" thermodynamic-temperature="temperature" luminous-intensity="luminosity" amount-of-substance="substance" display="false"/> <symbolics derivation-steps-style="vertical-insert" show-comments="false" evaluate-in-place="false"/> <results numeric-only="true"> <general precision="3" show-trailing-zeros="false" radix="dec" complex-threshold="10" zero-threshold="15" imaginary-value="i" exponential-threshold="3"/> <matrix display-style="auto" expand-nested-arrays="false"/> <unit format-units="true" simplify-units="true" fractional-unit-exponent="false"/> </results> </mathRendering> <pageModel show-page-frame="false" show-header-frame="false" show-footer-frame="false" header-footer-start-page="1" paper-code="1" orientation="portrait" print-single-page-width="false" page-width="612" page-height="792"> <margins left="86.4" right="86.4" top="86.4" bottom="86.4"/> <header use-full-page-width="false"/> <footer use-full-page-width="false"/> </pageModel> <colorModel background-color="#fff" default-highlight-color="#ffff80"/> <language math="en" UI="en"/> </presentation> <calculation> <builtInVariables array-origin="0" convergence-tolerance="0.001" constraint-tolerance="0.001" random-seed="1" prn-precision="4" prn-col-width="8"/> <calculationBehavior automatic-recalculation="true" matrix-strict-singularity-check="false" optimize-expressions="false" exact-boolean="true" strings-use-origin="false" zero-over-zero="error"> <compatibility multiple-assignment="MC12" local-assignment="MC11"/> </calculationBehavior> <units> <currentUnitSystem name="si" customized="false"/> </units> </calculation> <editor view-annotations="false" view-regions="false"> <ruler is-visible="false" ruler-unit="in"/> <grid granularity-x="6" granularity-y="6"/> </editor> <fileFormat image-type="image/png" image-quality="75" save-numeric-results="true" exclude-large-results="true" save-text-images="false" screen-dpi="96"/> <miscellaneous> <handbook handbook-region-tag-ub="157" can-delete-original-handbook-regions="true" can-delete-user-regions="true" can-print="true" can-copy="true" can-save="true" file-permission-mask="4294967295"/> </miscellaneous> </settings> <regions> <region region-id="78" left="6" top="33" width="366.75" height="94.5" align-x="85.5" align-y="42" show-border="false" show-highlight="false" is-protected="true" z-order="0" background-color="inherit" tag=""> <math optimize="false" disable-calc="false"> <ml:provenance expr-id="1" xmlns:ml="http://schemas.mathsoft.com/math30"> <originRef doc-id="36FCE4C3-960E-4728-AFC3-AF6D5431009F" version-id="DA124863-7F50-4A73-8AE9-007EABAE2A33" branch-id="00000000-0000-0000-0000-000000000000" revision-num="502321236" is-modified="true" region-id="0" href="C:\Documents and Settings\David.Lim\Local Settings\Temporary Internet Files\Content.Outlook\DBCA0NEV\GSW_1002_v2_0_System_Stability_DNV_RP_F109 (2).xmcd" xmlns="http://schemas.mathsoft.com/provenance10"> <hash/> </originRef> <parentRef doc-id="42FD7ECC-8C96-41D2-9548-544E02336F3D" version-id="19DB5A9D-D115-497E-826F-C6F30D0C23B0" branch-id="00000000-0000-0000-0000-000000000000" revision-num="502321356" is-modified="true" region-id="0" href="C:\Users\David Lim\Desktop\SMath\GSW 02 v1_On-bottom stability_113mWD.xmcd" xmlns="http://schemas.mathsoft.com/provenance10"> <hash/> </parentRef> <comment xmlns="http://schemas.mathsoft.com/provenance10"/> <originComment xmlns="http://schemas.mathsoft.com/provenance10"/> <contentHash xmlns="http://schemas.mathsoft.com/provenance10">6d90e7e417040ae2963b8c142484779a</contentHash> <ml:define> <ml:function> <ml:id xml:space="preserve">val_find</ml:id> <ml:boundVars> <ml:id xml:space="preserve">val</ml:id> <ml:id xml:space="preserve">vec</ml:id> </ml:boundVars> </ml:function> <ml:program> <ml:localDefine> <ml:id xml:space="preserve">lst_vec</ml:id> <ml:apply> <ml:id xml:space="preserve">last</ml:id> <ml:id xml:space="preserve">vec</ml:id> </ml:apply> </ml:localDefine> <ml:ifThen> <ml:apply> <ml:lessOrEqual/> <ml:id xml:space="preserve">val</ml:id> <ml:apply> <ml:indexer/> <ml:id xml:space="preserve">vec</ml:id> <ml:real>0</ml:real> </ml:apply> </ml:apply> <ml:return> <ml:matrix rows="1" cols="2"> <ml:real>0</ml:real> <ml:real>0</ml:real> </ml:matrix> </ml:return> </ml:ifThen> <ml:ifThen> <ml:apply> <ml:greaterOrEqual/> <ml:id xml:space="preserve">val</ml:id> <ml:apply> <ml:indexer/> <ml:id xml:space="preserve">vec</ml:id> <ml:id xml:space="preserve">lst_vec</ml:id> </ml:apply> </ml:apply> <ml:return> <ml:matrix rows="1" cols="2"> <ml:id xml:space="preserve">lst_vec</ml:id> <ml:id xml:space="preserve">lst_vec</ml:id> </ml:matrix> </ml:return> </ml:ifThen> <ml:otherwise> <ml:for> <ml:id xml:space="preserve">ii</ml:id> <ml:range> <ml:real>1</ml:real> <ml:id xml:space="preserve">lst_vec</ml:id> </ml:range> <ml:ifThen> <ml:apply> <ml:lessOrEqual/> <ml:id xml:space="preserve">val</ml:id> <ml:apply> <ml:indexer/> <ml:id xml:space="preserve">vec</ml:id> <ml:id xml:space="preserve">ii</ml:id> </ml:apply> </ml:apply> <ml:parens> <ml:return> <ml:matrix rows="1" cols="2"> <ml:apply> <ml:id xml:space="preserve">if</ml:id> <ml:sequence> <ml:apply> <ml:equal/> <ml:id xml:space="preserve">val</ml:id> <ml:apply> <ml:indexer/> <ml:id xml:space="preserve">vec</ml:id> <ml:id xml:space="preserve">ii</ml:id> </ml:apply> </ml:apply> <ml:id xml:space="preserve">ii</ml:id> <ml:apply> <ml:minus/> <ml:id xml:space="preserve">ii</ml:id> <ml:real>1</ml:real> </ml:apply> </ml:sequence> </ml:apply> <ml:id xml:space="preserve">ii</ml:id> </ml:matrix> </ml:return> </ml:parens> </ml:ifThen> </ml:for> </ml:otherwise> </ml:program> </ml:define> </ml:provenance> </math> <rendering item-idref="1"> <element-image-map> <box left="1.5" top="0.75" width="365.25" height="93" expr-idref="1" xmlns="http://schemas.mathsoft.com/worksheet30"/> </element-image-map> </rendering> </region> <region region-id="104" left="384" top="39" width="98.25" height="152.25" align-x="405" align-y="48" show-border="false" show-highlight="false" is-protected="true" z-order="0" background-color="inherit" tag=""> <component hide-arguments="false" clsid-buddy="01350081-1122-11DB-9380-000D56C6051A" item-idref="2" disable-calc="false"> <inputs/> <outputs> <ml:id xml:space="preserve" xmlns:ml="http://schemas.mathsoft.com/math30">vec</ml:id> </outputs> </component> <rendering item-idref="3"/> </region> <region region-id="92" left="510" top="69" width="115.5" height="12.75" align-x="586.5" align-y="78" show-border="false" show-highlight="false" is-protected="true" z-order="0" background-color="inherit" tag=""> <math optimize="false" disable-calc="false"> <ml:eval placeholderMultiplicationStyle="default" xmlns:ml="http://schemas.mathsoft.com/math30"> <ml:apply> <ml:id xml:space="preserve">val_find</ml:id> <ml:sequence> <ml:real>0.2</ml:real> <ml:id xml:space="preserve">vec</ml:id> </ml:sequence> </ml:apply> <result xmlns="http://schemas.mathsoft.com/math30"> <ml:matrix rows="1" cols="2"> <ml:real>0</ml:real> <ml:real>0</ml:real> </ml:matrix> </result> </ml:eval> </math> <rendering item-idref="4"/> </region> <region region-id="117" left="510" top="87" width="115.5" height="12.75" align-x="586.5" align-y="96" show-border="false" show-highlight="false" is-protected="true" z-order="0" background-color="inherit" tag=""> <math optimize="false" disable-calc="false"> <ml:eval placeholderMultiplicationStyle="default" xmlns:ml="http://schemas.mathsoft.com/math30"> <ml:apply> <ml:id xml:space="preserve">val_find</ml:id> <ml:sequence> <ml:real>0.3</ml:real> <ml:id xml:space="preserve">vec</ml:id> </ml:sequence> </ml:apply> <result xmlns="http://schemas.mathsoft.com/math30"> <ml:matrix rows="1" cols="2"> <ml:real>0</ml:real> <ml:real>1</ml:real> </ml:matrix> </result> </ml:eval> </math> <rendering item-idref="5"/> </region> <region region-id="146" left="510" top="105" width="115.5" height="12.75" align-x="586.5" align-y="114" show-border="false" show-highlight="false" is-protected="true" z-order="0" background-color="inherit" tag=""> <math optimize="false" disable-calc="false"> <ml:eval placeholderMultiplicationStyle="default" xmlns:ml="http://schemas.mathsoft.com/math30"> <ml:apply> <ml:id xml:space="preserve">val_find</ml:id> <ml:sequence> <ml:real>0.4</ml:real> <ml:id xml:space="preserve">vec</ml:id> </ml:sequence> </ml:apply> <result xmlns="http://schemas.mathsoft.com/math30"> <ml:matrix rows="1" cols="2"> <ml:real>1</ml:real> <ml:real>1</ml:real> </ml:matrix> </result> </ml:eval> </math> <rendering item-idref="6"/> </region> <region region-id="157" left="510" top="123" width="120" height="12.75" align-x="591" align-y="132" show-border="false" show-highlight="false" is-protected="true" z-order="0" background-color="inherit" tag=""> <math optimize="false" disable-calc="false"> <ml:eval placeholderMultiplicationStyle="default" xmlns:ml="http://schemas.mathsoft.com/math30"> <ml:apply> <ml:id xml:space="preserve">val_find</ml:id> <ml:sequence> <ml:real>0.45</ml:real> <ml:id xml:space="preserve">vec</ml:id> </ml:sequence> </ml:apply> <result xmlns="http://schemas.mathsoft.com/math30"> <ml:matrix rows="1" cols="2"> <ml:real>1</ml:real> <ml:real>2</ml:real> </ml:matrix> </result> </ml:eval> </math> <rendering item-idref="7"/> </region> <region region-id="153" left="510" top="141" width="115.5" height="12.75" align-x="586.5" align-y="150" show-border="false" show-highlight="false" is-protected="true" z-order="0" background-color="inherit" tag=""> <math optimize="false" disable-calc="false"> <ml:eval placeholderMultiplicationStyle="default" xmlns:ml="http://schemas.mathsoft.com/math30"> <ml:apply> <ml:id xml:space="preserve">val_find</ml:id> <ml:sequence> <ml:real>0.5</ml:real> <ml:id xml:space="preserve">vec</ml:id> </ml:sequence> </ml:apply> <result xmlns="http://schemas.mathsoft.com/math30"> <ml:matrix rows="1" cols="2"> <ml:real>2</ml:real> <ml:real>2</ml:real> </ml:matrix> </result> </ml:eval> </math> <rendering item-idref="8"/> </region> <region region-id="80" left="6" top="147.75" width="306" height="308.25" align-x="71.25" align-y="162" show-border="false" show-highlight="false" is-protected="true" z-order="0" background-color="inherit" tag=""> <math optimize="false" disable-calc="false"> <ml:define warning="WarnRedefinedBIUnit" xmlns:ml="http://schemas.mathsoft.com/math30"> <ml:function> <ml:id xml:space="preserve">G</ml:id> <ml:boundVars> <ml:id xml:space="preserve">M</ml:id> <ml:id xml:space="preserve">N</ml:id> <ml:id xml:space="preserve">table</ml:id> </ml:boundVars> </ml:function> <ml:program> <ml:localDefine> <ml:id xml:space="preserve">mvals</ml:id> <ml:apply> <ml:matcol/> <ml:id xml:space="preserve">table</ml:id> <ml:real>0</ml:real> </ml:apply> </ml:localDefine> <ml:localDefine> <ml:matrix rows="1" cols="2"> <ml:id xml:space="preserve">m_min</ml:id> <ml:id xml:space="preserve">m_max</ml:id> </ml:matrix> <ml:apply> <ml:id xml:space="preserve">val_find</ml:id> <ml:sequence> <ml:id xml:space="preserve">M</ml:id> <ml:id xml:space="preserve">mvals</ml:id> </ml:sequence> </ml:apply> </ml:localDefine> <ml:localDefine> <ml:matrix rows="1" cols="2"> <ml:id xml:space="preserve">n_min</ml:id> <ml:id xml:space="preserve">n_max</ml:id> </ml:matrix> <ml:apply> <ml:id xml:space="preserve">val_find</ml:id> <ml:sequence> <ml:id xml:space="preserve">N</ml:id> <ml:matrix rows="2" cols="1"> <ml:real>0.003</ml:real> <ml:real>0.006</ml:real> </ml:matrix> </ml:sequence> </ml:apply> </ml:localDefine> <ml:for> <ml:id xml:space="preserve">ii</ml:id> <ml:range> <ml:real>0</ml:real> <ml:real>3</ml:real> </ml:range> <ml:program> <ml:localDefine> <ml:id xml:space="preserve">min_offset</ml:id> <ml:apply> <ml:plus/> <ml:apply> <ml:plus/> <ml:id xml:space="preserve">ii</ml:id> <ml:apply> <ml:mult/> <ml:real font="0">4</ml:real> <ml:id xml:space="preserve">n_min</ml:id> </ml:apply> </ml:apply> <ml:real>1</ml:real> </ml:apply> </ml:localDefine> <ml:localDefine> <ml:id xml:space="preserve">max_offset</ml:id> <ml:apply> <ml:plus/> <ml:apply> <ml:plus/> <ml:id xml:space="preserve">ii</ml:id> <ml:apply> <ml:mult/> <ml:real font="0">4</ml:real> <ml:id xml:space="preserve">n_max</ml:id> </ml:apply> </ml:apply> <ml:real>1</ml:real> </ml:apply> </ml:localDefine> <ml:ifThen> <ml:apply> <ml:equal/> <ml:id xml:space="preserve">m_min</ml:id> <ml:id xml:space="preserve">m_max</ml:id> </ml:apply> <ml:program> <ml:localDefine> <ml:id xml:space="preserve">p_1</ml:id> <ml:apply> <ml:indexer/> <ml:id xml:space="preserve">table</ml:id> <ml:sequence> <ml:id xml:space="preserve">m_min</ml:id> <ml:id xml:space="preserve">min_offset</ml:id> </ml:sequence> </ml:apply> </ml:localDefine> <ml:localDefine> <ml:id xml:space="preserve">p_2</ml:id> <ml:apply> <ml:indexer/> <ml:id xml:space="preserve">table</ml:id> <ml:sequence> <ml:id xml:space="preserve">m_min</ml:id> <ml:id xml:space="preserve">max_offset</ml:id> </ml:sequence> </ml:apply> </ml:localDefine> </ml:program> </ml:ifThen> <ml:otherwise> <ml:program> <ml:localDefine> <ml:id xml:space="preserve">p_1</ml:id> <ml:apply> <ml:id xml:space="preserve">linterp</ml:id> <ml:sequence> <ml:id xml:space="preserve">mvals</ml:id> <ml:apply> <ml:matcol/> <ml:id xml:space="preserve">table</ml:id> <ml:id xml:space="preserve">min_offset</ml:id> </ml:apply> <ml:id xml:space="preserve">M</ml:id> </ml:sequence> </ml:apply> </ml:localDefine> <ml:localDefine> <ml:id xml:space="preserve">p_2</ml:id> <ml:apply> <ml:id xml:space="preserve">linterp</ml:id> <ml:sequence> <ml:id xml:space="preserve">mvals</ml:id> <ml:apply> <ml:matcol/> <ml:id xml:space="preserve">table</ml:id> <ml:id xml:space="preserve">max_offset</ml:id> </ml:apply> <ml:id xml:space="preserve">M</ml:id> </ml:sequence> </ml:apply> </ml:localDefine> </ml:program> </ml:otherwise> <ml:ifThen> <ml:apply> <ml:equal/> <ml:id xml:space="preserve">n_min</ml:id> <ml:id xml:space="preserve">n_max</ml:id> </ml:apply> <ml:localDefine> <ml:apply> <ml:indexer/> <ml:id xml:space="preserve">rm</ml:id> <ml:id xml:space="preserve">ii</ml:id> </ml:apply> <ml:id xml:space="preserve">p_1</ml:id> </ml:localDefine> </ml:ifThen> <ml:otherwise> <ml:localDefine> <ml:apply> <ml:indexer/> <ml:id xml:space="preserve">rm</ml:id> <ml:id xml:space="preserve">ii</ml:id> </ml:apply> <ml:apply> <ml:id xml:space="preserve">linterp</ml:id> <ml:sequence> <ml:matrix rows="2" cols="1"> <ml:real>0.003</ml:real> <ml:real>0.006</ml:real> </ml:matrix> <ml:matrix rows="2" cols="1"> <ml:id xml:space="preserve">p_1</ml:id> <ml:id xml:space="preserve">p_2</ml:id> </ml:matrix> <ml:id xml:space="preserve">N</ml:id> </ml:sequence> </ml:apply> </ml:localDefine> </ml:otherwise> </ml:program> </ml:for> <ml:id xml:space="preserve">rm</ml:id> </ml:program> </ml:define> </math> <rendering item-idref="9"/> </region> <region region-id="154" left="510" top="159" width="115.5" height="12.75" align-x="586.5" align-y="168" show-border="false" show-highlight="false" is-protected="true" z-order="0" background-color="inherit" tag=""> <math optimize="false" disable-calc="false"> <ml:eval placeholderMultiplicationStyle="default" xmlns:ml="http://schemas.mathsoft.com/math30"> <ml:apply> <ml:id xml:space="preserve">val_find</ml:id> <ml:sequence> <ml:real>0.6</ml:real> <ml:id xml:space="preserve">vec</ml:id> </ml:sequence> </ml:apply> <result xmlns="http://schemas.mathsoft.com/math30"> <ml:matrix rows="1" cols="2"> <ml:real>3</ml:real> <ml:real>3</ml:real> </ml:matrix> </result> </ml:eval> </math> <rendering item-idref="10"/> </region> <region region-id="82" left="6" top="465" width="307.5" height="192.75" align-x="24.75" align-y="474" show-border="false" show-highlight="false" is-protected="true" z-order="0" background-color="inherit" tag=""> <component hide-arguments="false" clsid="01350091-1122-11DB-9380-000D56C6051A" clsid-buddy="00020820-0000-0000-C000-000000000046" item-idref="11" disable-calc="false"> <inputs/> <outputs> <ml:id xml:space="preserve" xmlns:ml="http://schemas.mathsoft.com/math30">A1</ml:id> </outputs> </component> <rendering item-idref="12"/> </region> <region region-id="86" left="6" top="669" width="39.75" height="12.75" align-x="21.75" align-y="678" show-border="false" show-highlight="false" is-protected="true" z-order="0" background-color="inherit" tag=""> <math optimize="false" disable-calc="false"> <ml:define xmlns:ml="http://schemas.mathsoft.com/math30"> <ml:id xml:space="preserve">M</ml:id> <ml:real>0.25</ml:real> </ml:define> </math> <rendering item-idref="13"/> </region> <region region-id="87" left="78" top="669" width="47.25" height="12.75" align-x="92.25" align-y="678" show-border="false" show-highlight="false" is-protected="true" z-order="0" background-color="inherit" tag=""> <math optimize="false" disable-calc="false"> <ml:define warning="WarnRedefinedBIUnit" xmlns:ml="http://schemas.mathsoft.com/math30"> <ml:id xml:space="preserve">N</ml:id> <ml:real>0.0046</ml:real> </ml:define> </math> <rendering item-idref="14"/> </region> <region region-id="83" left="6" top="699.75" width="190.5" height="18" align-x="67.5" align-y="714" show-border="false" show-highlight="false" is-protected="true" z-order="0" background-color="inherit" tag=""> <math optimize="false" disable-calc="false"> <ml:eval placeholderMultiplicationStyle="default" xmlns:ml="http://schemas.mathsoft.com/math30"> <ml:apply> <ml:transpose/> <ml:apply> <ml:id xml:space="preserve">G</ml:id> <ml:sequence> <ml:id xml:space="preserve">M</ml:id> <ml:id xml:space="preserve">N</ml:id> <ml:id xml:space="preserve">A1</ml:id> </ml:sequence> </ml:apply> </ml:apply> <result xmlns="http://schemas.mathsoft.com/math30"> <ml:matrix rows="1" cols="4"> <ml:real>0.10666666666666666</ml:real> <ml:real>6.75</ml:real> <ml:real>0.54666666666666663</ml:real> <ml:real>12.666666666666666</ml:real> </ml:matrix> </result> </ml:eval> <resultFormat numeric-only="true"> <decimal precision="3" show-trailing-zeros="true" radix="dec" complex-threshold="10" zero-threshold="15" imaginary-value="i"/> <matrix display-style="auto" expand-nested-arrays="false"/> <unit format-units="true" simplify-units="true" fractional-unit-exponent="false"/> </resultFormat> </math> <rendering item-idref="15"/> </region> </regions> <binaryContent> <item item-id="1">iVBORw0KGgoAAAANSUhEUgAAAekAAAB+CAYAAAAA2unYAAAAAXNSR0IArs4c6QAAAARnQU1B AACxjwv8YQUAAAAJcEhZcwAADsMAAA7DAcdvqGQAABS6SURBVHhe7Z2LtaMgFEWnn9STflKP 9aSfDJePXhEU/L0Q9l6LGVH+4jli8uK/DwAAAHwlmHRH/Pv3zwYAAGgDFLsjMGkAgLZAsTsC kwYAaItjiv1+fR7/Hp/X28dXGT5PbxL/nk+7/Rz8oVKy9UnZT/PvTqr6cQamvY/X57bqPEmT vr3vX8AlfT44B5P8zTwBgO/hgEkH0y0Ru/fn9fDpdgtkrj7Zf0Rwa/pxInYczhb1dZYmXdH3 wdxY3dnYyzjhfC/G4ugcXOEP5gkAfA/3rKTPWrkkyhmeO1bkMWe1rxYj9v9udL79K2m5yTph nM9EjHLvCTt0vpdjccocXOPmeQIA38Oo2CI0TsT9XbsIg8S9OEzHp31FYmfTRHl1vnE7rHBU +RYnimN+XZ/kjR4HXtYPw1bZuq8PXVhIJ2HWXvWEIYkbk9lwHCC0YUbU9/frEbU1Gv+Nxpw/ RgnseT+wuoz6nJwThqKxsG2pm4P1Y7A1TwDgV1GK7QRIa/Dw8kKhhcgKjBefSOyyzNLpx43K mGeCFgloaFR0zIqobrDlwn6slW2P6T76bV2P7/ssv+nfogsLXL2jgOuwnXkk5JmxODehrebQ MPi+Ldud5/wx0jjjDGXsRPdZtlNzwrZjeyyq5+DOMSibJwDwa8wVW0xQCdYrFoXxTt+LiRa7 NeJ0Or52TIuYEKUVgZytRAJX9UPIlW3L8Mbpg4hqto2ereNnEto1I+p7WAXO27Q0jVVOHqOA NcQo/1rIlhn12RLPCbsrVc7SpJP1NDxPAOB7iBV7XAFMd/6CEya3YpDtm0zabitziNLmheui flgyZdsyJoEPWGMZO7CkTHxdnVrYx7BSdkzIMyPZdz9OY39cvLyqc8dIY9MWn6sMsz5n5sTI +lhUz8FL5wkA/BqRYhv8ikLrxVxAlJAlBT5BnE7H144Fc1IrEp12Vdiu6EcgUXZo6yikJo09 nuif/sLTnY8xt016+LxmbZv215m04cQxWiDpT/pMOjsnCseidg6aHF8/TwDge1iatBWRSACt gDiBH4NJ8xQDtfE1wXSiFvI9B2+8yTL0MW3MYZ9ZTYxp/bGQbsHRfrh2P5LKmChb0OXrfF6s l3VIOUqYF+wwxxVCGybUeNt2zc+V7kN49Js1pAVnjVEGMbf8wK0Q9Tk5J2ROFY5F7RwUTp8n APCrJEy6La5eYcwfl5+MiPKVjY8IBgDncvkq9+Z5AgDfww8otqx4rlllvIeXWWn5yNnY1VTB ivFEMOmruG4O/sU8AYDv4RzFTj0yHMMdj+kyjxW/FhH1+9sbzskh/vxcfytXzMG/mScA8D2w rOqIYKYAANAGKHZHYNIAAG2BYncEJg0A0BYodkdg0gAAbYFidwQmDQDQFih2R2DSAABtgWJ3 BCYNANAWKHZHYNIAAG2BYncEJg0A0BYodkdg0gAAbYFid0SbJp34aczxp0l3/AxpNq+pJ/s2 qy2kjfolGy5ux/uKF2PYPtT1/T08P48XPzAK0BqYdEccNml5PeStOi9mlzDTsM+aVc1vW2/k rS4vhXqt5A4z3SbcAJSVKy+JkVexyitXT20GANwCJt0Rx0xazOfiVzJGJF8BOXttY2WbSvIe fS3kJcYcUVLH25i5NecL3+QGAJeDSXdE0qSD4L+MOZlj1p/sPpf24ZaE1tBC/n9Ps6K228Eo otVdXOYrmEpIJ2VsGKGUkXj8/H49ZnnFyF0btynLq1bCpYT+mlXr7A1hBWYvbXDp/QpebhJU 3un4tG+sL9NG2095I1dhH7ba4OpzaWbjFdJJ2P1RAQCsgUl3RBDUiZRpapOS43pbrTxjoxjj cZkqPjOBvMkIsaEGZL82ilqTLskr+xNVZwj98/3ZMNAlyxX9YG5qbHYpK5ifLdePX0EdbzkP 5mbqVeTUK22wx0Jd0lfdT98ePwblYwYApWDSHbE0aUMs+DYeTNUFJ76RECfzaQHPHEvFE8SG GrjDpHN1Z1nrewly06LMePH9rnHFWm7SAfuZdIlZ59pg61rOh+oxAoBdYNIdEUR2Riz4Nh5W SJrvMGlrJlMjFivAVQrz3m7Sqi3TClZwYz49kag36YA169Vvd2faYOtazgcZo9STDgA4F0y6 I4pM2ov1aFLG2JwWx480o7hd7WWMaiueIG8CUq+qp+qz0LK8dY+7Dbo/BX1LYsdvXu98DI6Z dBGJNpjK0vMhboOJP0PEHpO5dkEbAToDk+6IpUk7AXb71WppFFkTlGKLeel9Y1zCw6w+7bb5 f1ZmXIeKrxmstCF3/IgJbOaV9tWUq/sTxsCFudltIeVEK1Z9HkIwaeRb2y4epffMzosOmw1K tEHIzIdg6i6EfHr8zI1F1U0UAMRg0h0RBLUVqle0ZyDGc3ulP0Q0fn9yDgF+CEy6I1ozabsS u/ORqV0xplenUEb8eX715/sAMAOT7oj2TFrIPII9HfWZL+wGkwY4F0y6I9o0aWgJTBrgXFDs jsCk4XL4TBrgVFDsjsCk4XrUt7vlM36+3Q1wCBS7IzBpuIXNP3MDgFJQ7I7ApAEA2gLF7ghM GgCgLVDsjsCkAQDaAsXuCEwaAKAtUOyOwKQBANoCxe4ITBoAoC1Q7I7ApAEA2gLF7ghMGgCg LVDsjsCkAQDaAsXuCEwaAKAtUOyOwKQBANoCxe4ITBoAoC1Q7I7ApAEA2gLF7og2TXr4PP89 zb8e+4alht+u9PXtN+O9+/WScq70+6Nd3M67K14qvTGWw+th2sJruKBtMOmOOGzSw/PmF/iL yGsRDqJfYHK3t7WERtpvzU/dGO0ieq/06TcmJWP5NsP4+Px7PD8vzBoaBZPuiGMmLaKrV0nX MzwT9RUJ/v1tLaaV9pubhEOr30uMOaK0jvfweWHW0CiYdEckTToI3cuIsjlmddnuc2kfVgGd aYT8/55mlWe3g0BGq5q4zFcQ05BOytgwACkj9dg1Eub3y4hvKNOmj9u6Xo/cCLi0fuUo5qTz LcbCE9JJqHk83Ez7pR1TO4sIfRumOmdtWWGrH9PxaV88lpv4+fd4pdtz+1wAKACT7oggJBMp 09TiLMf1tlrdxQI5xuMyVXwmfuvias1rrEwxq1fK9mUa3sPgBTJq6yrOFHXawdxUuHIyY2Hb EOqtqcvQUPvFtIr75ctZ3Ki5hhSw0g8pK5ifbntFHW9z4/A0N5frK+mb5wJAAZh0RyxN2hAL nY0HU3XBiU4kQMl8Wrgyx1LxBGLSs9VKIMobVj/ztJViKTcNygTGhZatazkW2baV0FD7q/up +xb1s4hcPwLjirXCpOWmcdOcFXfOBYACMOmOCOIyIxY6G59WdxPfadIO17ZRvOO2bjKtoKaV k8HWtRwLaVtylV9CQ+2/3aRz/QjjY9ss275PG3W8X/Llu6oGGG6cCwAFYNIdUWTSXqRGcTYr C6dBsXFEcbvKyQj0VjxBVvxmeYfPSxUi3+QN++tMzuBXafM8mbFI9Oep2rFKQ+2ve9xt0OXG dZSS6Md8LpSb9G5OGUtp5wVtg+7ApDtChEfChBMet1+tEqzw+P1KqcYv1vh9Y1zCw6y67Lb5 f1ZmXIeKh8eKKaQNi+NxWc7MXNyElbZuI2WrMQhkxiIIuQuJfElaar+UV2Myqm/jXHChuAuW RD90H0IwaZ6zsVwym586bDbo+Fi6utfHT1b6mDhsgUl3RBCSVhChqxN4OA0xHgb/ANs3OdOT E4A8mHRHtGbSRsZ4ZPgX2BVjenUKpWiTnp4yPF/Dx35Mrlbf+XuhKZ+7YQpxvVo3QT1xsh8N 2HI5f78CJt0RQRTaQoTpgOCkHpWOoYEbgNvbrz7zhQMokzaGHD7LDqvnt/zAStHHCdH5GF6J Mv1n5erpx7gPmgeT7ogg7gBwNcqkw43W7DsW6vgG2nDDN86nFbMPxpz5eOg3QbE7ApMGuIul CQdjdUZabtLO5M1q2vwf/m5byooNGZP+TVDsjsCkAe5CP+72j6iF8TF1hUkbxIBnK3H1aNtE Pk/Zln1jGr8PmgfF7ghMGuAexsfRYpryW+aJPxezxmv2FXmpWUXHf8se8qfKbOL7FlAEit0R 7uLllAMAtAKK3RGYNABAW6DYHYFJA3wh2T+z45E1YNJdES5+AABoAxS7IzBpAIC2QLE7ApMG AGgLFLsjMGkAgLZAsTsCkwYAaAsUuyMwaQCAtkCxOwKTBgBoCxS7IzBpAIC2QLE7ApMGAGgL FLsjMGkAgLZAsTti26SHz9OnmV6DdwauXFek3j4H+8ahPQXan2PkpxcBfpPztSbNtfVg0h2x btLq/bYNmdf4SsDqKyTckBT0c3jecKEDwGHGa1X0zOld69cuJt0Rqybd8Kry2pW0u9gxaYBv J75W71pJXwsm3RFZk47fwjPO6rDalKDMLJjb62mPbV4E2gy3jNEcf44vyHdhq/yzTHpclUuQ l/Wru3EbNupYvITf3NXP8tn6XJqHHoCQToKtFwDypHQpda0Gk1bH9PWVuh6DJnhtC2FZho/L 9qaOeHLX/waYdEeEiZMkmmhmh52EwV+cAYn5qAukyBhDeilbb/vDMwZzcQzTpC7kHJOWtnlz NbyH0I5wodvIBvMxE4ZXuEjlmK7Lb9s2hHpr6gLokZwu2Vh0/bj4qDez6z11PYb0JoRCJM9o tDqPYXipPLqslI5krv8CMOmOqDLptXh8bIvSvHpFqcKWaZ21kg4r4fldrrsIi4uXPoSL2pRv 7jkctq5lv6TtNXfVAF0T68csHl+rK/HM9bgo3yC64Mpw+Z3WGNMNF3eUJ6kjufoKwKQ7IkyO JPHktIaZuRgSE3mV0rymztKJqznLpB3+Qty9up3u9KdVtMHWNd1hB3a3HaBH1nRpca2uxDPX Y1IT/I338Hqa/VKGOW62x3JLdCRXXwGYdEdUmXSYZGEmRivE5aRcQadfzWvqfJiJXFqu56zH 3S/VqOE57Z9f6AVYIYnzOPMe767DDUk8Hib+VO0AAM2KLi2u1bV44fVocWlDnXalPNZpKNKR TH0FYNIdkTdpP/F9GCePnXxhf7gL9BN2tm8Nld4Y8PilMD3JNWJSY/kurE5mb4g2zBLqCzK+ WIW4H/Mx0GWFx1flNwJSdmJs9HjqsnQfdt5tA3RDUpcc+lodt72BTnGfZ3E95rXtbVfRY0Td SGt9E03L60j2+t8Ak+6IMHEAAKANUOyOwKQBANoCxe4ITPogs8dscYg/xwIAOA6K3RHBUAAA oA1Q7I7ApAEA2gLF7ghMGgCgLVDsjsCkAQDaAsXuCEwaAKAtUOyOwKQBANoCxe6IHk16GN9C U8+RvHAXb3uezueqcgHqwKQ74ohJz37qzoeKX7b7G+yr5Px2LUfywr281dvGzkSVO/2kpApf fwHAL4BJd0QQlz08mxOk9/QquWqO5IW/YHhmfgv+IPlyhwavCWgRTLojujLpirfMLDiSF/6G q85ZtlxMGu4Bk+6Inkx6eKq31ozEb8NSb6xR/UvnrcT+hOiv/FSoHrd4DFPUpq8j+WpSM971 c7SgndlyTfqq+uLyXTyee6exY/69zQ3JgydIXwcm3RF/atK3rk4zr4qcIWm8iM0ErSTvFkGA +T3vs7EGnTQ2M+a5158eIleu2b97Qufm3lnUzb/34F4P+zD9OX/84CiYdEf8nUmLKJ27mlpF hG9LsHPiWJK3hEvEF4TkSlob36nkyj1g0nfMjZI63nIDIub8+gzM068Fk+6I0006CMHracu1 Sew+V8/DKoQz6FD3v6dZUdvtICDRXX9c5iuITUgnZWyIo1m1J9OEss3KYfY2K502kXfxsnhJ o/LNvvkb8q6I5Jg2E1JstWE57p6QTsLemw/dl5V+jdSmryRt0m6MErvzFLYzXW6lSYfy1+Ze hrPnn2DHUJ4YFZ6XP51/nYNJd0S4WPawFKSUaepVhxzX20roYgEZ43GZKj4Th7z4WCRNtr0+ b07EknmXTwIGc/Ngs0o5QXxsmb6dufIN4TzkQpqVNthjoS417ro9vv+Lrm2ixy0awyS16es5 x6TL23ncpKPyV+ZGmnPnX+At/ZbvXxQ59V/NP8CkO2LdBNZZXUmHa9zGXR0huGzRBZrMpy/s zLFUPEFOxFfr8WTzinkrMVx8v2ZcMZSLZDW5Nti6luMufZmtavai+1LSr6L0TvR1m8eQGn/F mklX9bewX+lyxeDW2zmjsK4sF84/+5l0iVn/1fzrHEy6I8IFtIdykw53zpr7TTopDmv1ePLC Mq0kphWE4PrmTEO2t0VSi1kq5Mm0wda1HPecmVVTMG4zatNXkutXtSkUtjNd7s0mfeL8y2HN evXb3X80/zoHk+6IbRPIU2TS/iIeBc3cebtsTkimIqK4XQVkBGwrniArDjpvppxVYfGrFX14 nr5MJMN5yIVVEm0wlaXHPTF2TxuRdob9ejtDwbjNqE1fSe4cyf7fNWnDSfPvEH8x/zoHk+6I IhPIsBQkd2G6MtVdtL0w/X6VZ/ziid83xiU8jAjabfP/rMy4DhUPj90SpEVc5w31uaCT5gzA IWWovgq6vyGYNPKtWReP0h8m0QYhM+5BVMvbIqJpBHcsQ4+b6tc4/rXpD6L7E52nOpMub+dx k9Z15efeNolzv3P+za4/HTYblGiDcNr8gxhMuiPCxbKHqlXDXyPCsLe9R/L+EPNHqtvUpr8C MZ4rTl263BqTBtgPJt0R3Zi03NXvbe+RvM2gHzHqbYd8Nlnzd7O16a8Ck26F9fkHczDpjujG pOXC3/149UjeNnCPOp0w6u22kcewV/QjVy4mvZffnH/XgUl3RD8mnfncrIgjeVtBG89V5nY3 0o8rbq5y5WLS+/nF+XcdmHRH9GPScoe+/8I/krcNflEkrzLNXLmY9H4w6Row6Y7oyaSN0+7/ fPJI3ib4QZG86pxly8Wk94NJ14BJd0RXJi0X/+oPM6xxJO/3Y//MTObC4/UZ1HbLOnnVt8vz 5WLSe/nF+XclmHRH2IvBhD00KUjDa/8d+pG8cC/vYfkzmWewWi4mDfeASXdEdyZteA/735F7 JC/cxfszmPN0PlvlYtJwD5h0RxwyaZ9XBzQKesH9qVAUuADgBjBpAACAr+Tz+Q/l4dQhWi6a igAAAABJRU5ErkJggg==</item> <item item-id="2" content-encoding="gzip">H4sIAAAAAAAA/+xWP2hTYRC/l+SlSc0ziTXRVIcgBcXNpw5CaaKxg2AopKWL0KHpRxNJ8tI2 agWHFCdBQXDSRV3c3VzEuoidWhdBu6Q4OVmRgot53t33JflaQavWQZrf47773n3f3b37/ty7 EAAYSKNIvdz3YOurzQpxCAg2UqCcH5m8LPI1lkAOaRCV0l774UuAus+e+AywYNpWlcf96r3H 9oQBpvxoz3sVBOTRktTwB202ECCn5DCYGR8dnrlQE2WDTYTIjC6wkPbw1ICYyYnpolMxeeAU aU85eSnzsexMOxD/XKF6zpmX330RqQcFuXYkWWo80shN5C7yw8jTchgKoJYHPKFWdBZHVw/t ldFZWnRhGZ0VkdGFKbqoDcjrYWibIuzjrwth1BmnPOlQnHIgQt+I4o6ENAdxa46hxlnsX0J6 juS6NBunjpREplQUlRrroIus0fLELequLEcbj5/2r8EWDIEXmm4Q/JrM0L8zwsvD702XPEq4 XfxX+IbU1KiL3YUcOPjUIAnDUEE+C9e3poKfIg5m+85TLliA08aR6Gr0Xh2s8Vdmvz63ce3o cbHx1vBif1Elkgx6J7+C27nf8k3AdGno8WxX74Xx6znbxZ/430n8jX9aBsrjtCf0i6RfJ+X8 bi7YHTCxfioEAW71yfPQC1h5MbVOR7uDs7jEiElBXHWnoMinJwyyTvQqlaJ2yqhoe4b0xd18 Qu9qtzCLlWYSqYC5oIRPEs5jO43c5vHq+ieYxyP6esJN1IeyicX3Y4mO9qpv4x/avkFs7PbS ifxK9MkdeDSwbL5pVUMBdYN0BNRyPbhPWEpJ/i4lRxupk4wPSv5RydcV/6p4q9iMpPlqkjP8 R2+inUGfrER51yNrVxLoav+PFXpMVehxWcPGaLsPSM1YR/OgNprQRun9OwAAAP//AwCyk3U6 UwwAAA==</item> <item item-id="3">iVBORw0KGgoAAAANSUhEUgAAAIMAAADLCAYAAABNliBnAAAAAXNSR0IArs4c6QAAAARnQU1B AACxjwv8YQUAAAAJcEhZcwAADsMAAA7DAcdvqGQAAAW2SURBVHhe7d0BcqM4EEbh3Mfn8X18 npwn92HoRvwWbUEgtXhp+X1V2kkCM+uyXhQnqMjXABTEACEGCDFAiAFCDBBigCiG7/vX8PVl 4z58Tx+Y3r/7e8Pw8xhufvxruD1+po+Z+Twbt8dQHal8D/fx+PxP4ZqqleFneNyWE/b9mCfX jt2GqQGb2PK2B1Li2TXh0/9D8dSDUv53yy8T9lk+f3aPE/2Y56daFeZhc/fzuC1XCaQWXjM8 V4fnqjBarABPFsOxz2hWhit7fQFZXgMs52aaRK0C4zl+3COZv3xM799ZKdJ6jcEn/nUVmCa+ 8Vlcv4BsrB4TXkBm0IjhWp6hMU4f5Tm/LHuQOB8xQIgBQgwQYoAQA4QYslpcHlj72Y6Zfr4z nWej+gFhQAwpPS8ZuPp6UmTRVD/p88sHK+cSQ0aNSwCt60ZN/tPi9rnEkFGc/BjHBlaG3rx8 dlf7S7Z4NOvXh4ghoz+tDNMLya29J8SQUZz8GMeL30MwxJDS1ncTZfPQ8+CuEAwxpFX//KBe FUIMi70mz9GKw4+Vty/LHiTORwwQYoAQAyRNDIw3jfKcX5Y9SJyPGCDEACEGCDFAiAFCDFmV vQk+gZtXLCt+nWL9UjcxpHRgD+RM8RBDX/60n8HOn/8sHw6IIaM4+TGOhXoVIYb+HNgD6Tdt W2x0IYa+7F4ZykYXm+Qw1EfFj5W3L8seJCpx8mMcq1gZOrT13UTY9rZADJ2yiZ2W/M09kAvE gJ2IAUIMEGKAEAMkTQyMN43ynF+WPUicjxggxAAhBggxQIgBQgxZ+WXrcfJ8bF2+bu9pYD9D N7YuYUfh3A3EkNGhzS3E0Lc4+TGOhdcvE2thEENGBzbERn6H2JVziSGjQytDNO2Q4gVkL+Lk xzg2EUNntr6bKK8R5oMWSjXz05eJdjjEkNbeDbH1efHcJWKAEAOEGCDEACEGSJoYGG8a5Tm/ LHuQOB8xQIgBQgwQYoAQA4QYsvLL1uPk+dhx+do3xJTzV/ZLEkNKW5ewG152RrURQ0aHNreE cDYQQ0Zx8mMctXLsZnscbLLHsRYGMWR0ZEOsn1sd2/iSQQwZHVkZmuGwB7IfcfJjHLWXUNZX EWJI6cCG2PL+/IvQ2RDbpb0bYk197sqXkxExQIgBQgwQYoAQAyRNDIw3jfKcX5Y9SJyPGCDE ACEGCDFAiAFCDFn5pelx8nysXL6eLc7lQlVnti5hR8vNLFzC7s2RzS0ew75ziSGjOKExjsB/ U34531eGxV6HJ2LIqLmvcT0GP/9+1waXlRaIIaUjK0M85iG1zyWGjOIExzhqzVWE3dEdObAh 1kMJ566EQwxp1Ztc68ltbIj1AOZz119bEAOEGCDEACEGCDFA0sTAeNMoz/ll2YPE+YgBQgwQ YoAQA4QYIMTwMX7ZADMihg8wbXuzQQxwrAwQYoAQA4QYIMQAIQaMnt9alsFvosFviAFCDBBi gBADJE0MjDeN8pxflj1InI8YIMQAIQYIMUCIAUIMqf1+JVJ3crGJrgb3dOrI3k2uL/d/2kAM qe1fGYihe3/7MrEWBjGktieGpelG4u2/QwypHY9h+ju8gOwQMUBaMYSbgtodYquZ5/dNdGh9 k2uIoawEz3NX7jE98uPl7cuyB4nzEQOEGCDEACEGSJoYGG8a5Tm/LHuQOB8xQIgBQgwQYoAQ A4QYuhcvVK1f8iaG3rUuYXMbHzh+4y1mrAyYxN+LHRDDx5heSN42NkwSw0f4PQRDDN3bF4Ih ht75dw/jJIfRisOPlbcvyx4kzkcMEGKAEAOEGCBpYmC8aZTn/LLsQeJ8xAAhBggxQIgBQgwQ YvgkftGKDbEou5yI4ePZngaLYP6zfDgghu7Vtwsmho/md4Vb3PmNGD7U632j59HaIe3HytuX ZQ8S/wVWBggxQIgBOxEDhBggxAAhBkiaGBjnD3+u/b/AMAz/AAirhhFtNyi4AAAAAElFTkSu QmCC</item> <item item-id="4">iVBORw0KGgoAAAANSUhEUgAAAJoAAAARCAYAAAAliLUMAAAAAXNSR0IArs4c6QAAAARnQU1B AACxjwv8YQUAAAAJcEhZcwAADsMAAA7DAcdvqGQAAALJSURBVGhD7ZcNcoQgDIW9j+fhPpzH 83gfyosIIYa/lXXajt+MHRUSkkeI28W9vDzAW2gvj/AW2ssjvIX28gj3Cm23bl1WZ/fwXGVz ZlncgssYujdbGOqluB58G/83QPOwVim23dk1xNId/wx8nKv1q38LoQNoalGhaDuex41COwun JwFsbJg3VJyc0np4z9+xZ1pLCO/ZrYnzN+N9fnXzBYWY7iN1AG0tyjRsB/0909F657VQ/KBQ ss64Gd8xzxdH56p2zkHBppDFOIeLDmBUC06P7UAesdDoZFPHCKLDCZ6DozSe3nUVEM0Rttwu 3uMECf8E/8zhYuvBVnSj3a6ZPeJeawEqPiQtbY4cjjnZWuc8XNkarMPPoJDDsBaMPtv+PFhH u1btZkPwPBESNQhO9x0LZfPOgsIzK65sE5NP2uQzKDEmxQB4xwVpiut9tsWvaENjPLdwz3UK OWf2Pi4ReuBYKxYov3QDVQcwrAWj17acR07+6cRGsoKy0kE8oXcKTTzXxvjGATFXigHGxPX+ G90sUtKGYsoLAsJrsXFa4yOUfI1pkdNr25uH+I2WTm46sSB0Hipd3D9UaHTPToyYqyaJgkgG l07E2fx/v4UhhYI2FNPVD2IrdSBQ3qDPOprqa0CLC522HxaaJ3Qt7jQX7cFCO0XPPttprr6Z rAtifqFjwTbpaJ2JAVRQtPHGFGMU28+hcSUvvkbvJ6cHXQfQp4VOn+1nn04CwokTSqKJ0+Xn mHjyap0BASc7s4XiUX3wMV5c5zt/euLcMKYJEG3yjT67I8Q51jwvNi/Eu6rqKdoAHiO3C4V5 XNwOfviaNynpADQtemna9uehFNrfYmZn4OQ/HSaTfZbm8C0dqgzk8ecLzWebWvwk9s0633i/ A3WJ2hfgU+brUGUwjzmFFlusdj2RfOGT9utAMXwzzqd0GM/jH3S0l9+Pcz8fVBwQKuaxAwAA AABJRU5ErkJggg==</item> <item item-id="5">iVBORw0KGgoAAAANSUhEUgAAAJoAAAARCAYAAAAliLUMAAAAAXNSR0IArs4c6QAAAARnQU1B AACxjwv8YQUAAAAJcEhZcwAADsMAAA7DAcdvqGQAAALASURBVGhD7ZeJkYYgDIXtx3rox3qs x35YEjkeEBA8mN0dvhl3VK7k+Qj/LnoyGcA02mQI02iTIUyjTYbwzGjHptdl1dthn6vsWi2L XuhSiu/VbptaKa5Hcyvz18L9aK1ybMe2nrE0x/8GJs51098tl+hANGhRg3XKPlR/Hg+M5ozT ksCht9X26zInUlqP3uM7eOa1EuEJ817ZAbKQH1KK6TGpDkSDFhX8ZpT06ZxvTEVr7XeFMM+u ksq4KxCGDH5ROU3/9XFgnUQxvkOmA9GrhUB1I3bk4Y1GgZ5HiXUpTQJuDu3hXZOBuE8yFsf5 e1exYH7mFMiPx/VobFLCU2Eo7rKRzNwbriVzpQ3mGK3l+tEVxQkV/g0EHYg+LWTqFb89D6ho ueP3zQaPibCoVnC+b1go6ucMRc9grugjhjn5I7ugkjZJBHqHYpbFDWtfi1/RhtswN3uPOtm1 ovEmriR0y7mWNyhe8gBRB6JdizJ1o9XyiImPTvqQYKhss/sd+sRoyXOtDT8ckfRNhSR6xWUh vSEqlLThmGJDkPBSbMhVew+luXq1kGB9Kk5qzSP5jRZ2btixhN39vCDdDzIa38OOSfqKSZIh woCsEuVAPlUK2nBM+fj7H+heRRPn6tYi534eMfk/A7Zq4dzxYgON5kSPju3QVxYBqiD1F367 REQf4wJBGxejF9v04XYhL/efLtF65LRQNkOnFgJXRrt3dDIkXLJDWbRkd5k+yu+8WkWgZMM4 tcOOzebANjSXe2d2j+9r2yTx/Jj4Q7vqyOK5OTOVznhXUT1BGwJjxHHWmOeF42geiO0pJR0I SYtWMP6iHm3zCkb7W7xZGZD4p8PL9FTRRr7SoUpHHn/eaCbbcDy8xLFv2hTeb+AKUzsB7vK+ DlU683jHaHh0ZNeI5AtH2q+DzPBlnKN06M/jH1S0ye9H6x/WHDNyp/GjmwAAAABJRU5ErkJg gg==</item> <item item-id="6">iVBORw0KGgoAAAANSUhEUgAAAJoAAAARCAYAAAAliLUMAAAAAXNSR0IArs4c6QAAAARnQU1B AACxjwv8YQUAAAAJcEhZcwAADsMAAA7DAcdvqGQAAAKrSURBVGhD7ZeJjcQgDEXTT+qhH+pJ PemHxY4Bcx9D0MyKJ2WVhMv+fJzZQ202C9hG2yxhG22zhG20zRI+M9ot1XmcSt70XORS4jjU AZcQeC8uamolux7MLfRfAvvBWvXYLjEQxzA6zlOqJrmGCHQgbnlqzceSTI/tz+MDoxnjtBjt VvKkfl3m5OTWg/f8HXvGtWLhLWTIdUbT1GIaJtThAY0Cug0kWRzbmceaitbar0ZinqgiXYIJ AwbPG+mSUsmlFY3wYpxDqTLPr2hERx7WaBAoute4FCZhbnbt7l2TgbBPMJaPs/emYrH5kccs djxfD8YGJTwUBuI+UwHq/KBbaYMMNW14jt5aph9cXpysws8goQPnNaN15MEqWnz64cTjHDwR FJUEx/uGhbx+/BPIzOVtopsTN9kEFbSlRIB3fLPTRtO5ymdci9Gwf04bbOO50T3XiXL2xmfX fdayBuVXJtCakd4zWqt+4acTNpIZivbCYU/oJ0YLnkttfOOAoG9oKqDJaJfOjV61CpXVBmPy DQHzpWLj1Np7aFnrLaO15hH8RnMn151YgCoPLgj3i4yG98wIQd9kkmAINyCqRACYixsDrrpY GW0wJlO5HOMbNFbRfsxoGqpafG5/sYVGM6J7n23XNy0Cq4LQv/DbBWiuaEBCGxOjFVv3wfZE XsI+dK5bocUMbxmtNY/YaChccEJRtOB06T7Cnrz4RDuoGtIlLnZiozl4GzeXeadPj+1LbSkj 2TGhgWNRYqGeeM+kegltAB4jH0fGdPkZYB4W26fkdAB4DC2O4FTHtueRMNpvMbMycPyfDpOB DZwc9Fs6FOnI4+eNprN1n8pJ3PqfBV143wGrX+kLMMp8HYp05jHHaPzTEV0rks980r4OMMOb ca7SoT+Pf1DRNt+PUn/O/kVanqAN4wAAAABJRU5ErkJggg==</item> <item item-id="7">iVBORw0KGgoAAAANSUhEUgAAAKAAAAARCAYAAABaWaf9AAAAAXNSR0IArs4c6QAAAARnQU1B AACxjwv8YQUAAAAJcEhZcwAADsMAAA7DAcdvqGQAAAL4SURBVGhD7VeLsYQgDLQf66Ef6rEe ++GRCLKEIKCeN/fGneFG+SabTTgn9+LFF/EK8MVX8QrwxVfxCvDFV3FNgKt18zQ7u4b3QyzO TJObqBnDz2YJQ72onkd7G/8bwPPorLZti5F2gJ2450fhz5yt66LxFAQ/AaudfSyGg+DsHPmR /I77cUGAMVA9AiSjw7wh0SJq51E/9sE7n3UgoiBUjMFqzQnbbkDL1tOQ/Gxg8RGfgwJEfih5 Jym4QT+eqYC981pQ9ikq2GKA1C1baxwv1jqbrY8in9x82dgTyGy/B2WFTzhXAQE1sQ34sQuQ 1czkhw1pE8iQNJ76uoTFc8RaXLc/p+DnxmPJpwbn0VqRgZJUslsVk/ePpqkBCja3RNjiLO5D fdlecR61zH64Ke6Awg/iFgGq+/f7ARWwrBZUIXgPPIhJDYTzc8dB2bwoNHoH0WVBTHtykKNR YkwjkPow2LoAva92W6cKkEG2Kdmd4YAzHkOfwzPyx/1ifdWe7axduNj0BSo/iMsC9PGoJWnd jxz5FUwBBqGFGCXsmXtFgOL9aAwDRxBzpdgIXQJcvG+h64ioxX8sNTmscca25kKhczSbEa3x EfScdV6APjaN6trjh/gPmDI6ZTJhy9TNWHp+SID8DAIRc1UnSRBpQVGhCCQ6FAa1kixa2yHA Gmdsa7m+FfR64M5VwE8JsJWcrbMjyo+QUOXQrtzQBwUYSc+u/zRXJxCqJs0/yFJCtQJ6HnoI ZCicRdv3PfwcHlf8NXBO79XVg5bAzgqQ1u3LhP0RvX6UAmTihLqZNJF1fo7ZM/IoG0L1DM0s kMnFHjiGoot9Pqv2uWFME9i+Rgq7JCUjKgiJW8He5sessqpwRkDbcR2ek3FH+4DNV1Hjh3Do ax3l7aHZ2++HIsDfwp0Vowf5X5ObQaK42Zmn+WEM+PHzAvTepiv3w1j9x4sv4J8BV8ujm+Qs nuOHMejHPQLEq6ZoTzhfuQJ/BiSST9r/FD/jfvyDCvjid+HcHys4qYf+GyoUAAAAAElFTkSu QmCC</item> <item item-id="8">iVBORw0KGgoAAAANSUhEUgAAAJoAAAARCAYAAAAliLUMAAAAAXNSR0IArs4c6QAAAARnQU1B AACxjwv8YQUAAAAJcEhZcwAADsMAAA7DAcdvqGQAAALPSURBVGhD7VaLscQgCEw/qcd+rCf1 pB+fEI2IPzRe5u6NO+NNEgVhXfA2s7DwApbQFl7BEtrCK1hCW3gFz4R2arNvu9Gne6/iMGrb zAZDKXxWh5uSorgf+Fb21wHXwV612Eg81PajsHvu2ojoGgLjwe6kd5+j9Jw8arb9eTwQmj8o SQIQtFvXJU6K0n7wnX4j77hXXkSnVgMxTEAlpmfgPMQ5Hspy1yGOpm1nHu90tGFxMWT8AAlR ZzyU7Zj+w1WVaef0ot3M/jioAUQxzkHCA8cTgZdsO/K4hYaqRfKdQ3AC785RmA/fRALCNcyW 2t3P4fDj4GkLh0H2A1tWaafeI3uIuygmF1tLbC1uvB/4Fvny62BEcZIOPwMZHhJI1pRQtJXn QTpaWv2Hds7pRkiqIxyfBRtF67yg4J2IKzrE4BMP2QfF5rioAPCNHnZVaAiIIVOtESrc4BzN zT1TnvA7s7dxsdAdrr1ugdKRN8jykMBy1yqoIiq25TxixFcnHCQRlOYO8KAh6SdCY++1OXpw ALaWiwrQLzRY0xKaRYkbjCkWBBCfi42iNd+Dti/L42g3a9hK82D/0ULlhooFXBV5VQ08vyQ0 fCYVw9ZmkwRBBIOkE6WANQKhlbjBmFJ7iK3WZcoHNNbRaoctKqQCWraDQrNwXYvmFJP2otA8 6dG1HdbmDxPiI75blWzzlRCFyHDjY7x92DU4n8lLkX2kV44EeR4uwNw9xWJoQWI7dnUiMhWO pLHqsmvUXXk11btu6IY6SMUmPugcFZf/ZqvnXuvmckK6bbiAHSlOMDgSlq549yx7GW4ANEZq R/eJOAI/JLanKPAAIgj7w5DvKbOV55ER2m9hZmegiP86TAYIcHLQn+Khio48fl5oNttwVU7C eWhjG+9ngN2vdgOMYj4PVXTmMUdo9OpIxhvJF660rwOI4ZNxvsVDfx7/oKMtfD+M+QO/ejpm tfIrwAAAAABJRU5ErkJggg==</item> <item item-id="9">iVBORw0KGgoAAAANSUhEUgAAAZgAAAGbCAYAAAD5r4b7AAAAAXNSR0IArs4c6QAAAARnQU1B AACxjwv8YQUAAAAJcEhZcwAADsMAAA7DAcdvqGQAADyySURBVHhe7Z1N2qSqsoWrd3q3d3t7 BjWJO4kcyJ5BjsfemUvOJy8REBggICqaYeZ6n8cqfzBA1LUE85M/bwAAAOAEYDDG+fPnD09g MNPj/Xi+wkLG61nfBgDoBsplHBjMGUzvx+P5blnI6/l4w2MAOAaUyzgwmPFMjx7zcCb0t21C AIA2UC7jwGAGMz3ef3N3eT3ff7me/6bG0+pGAwCsAuUyDgxmJKVWyev9/CvGstw+PTLTAQB0 A+UyDgxmHK/n3/djCguCa6X8USunx580DbVuFjsBAHqAchkHBjOSZQuFTEd3meXLaMEAsB8o l3FgMIPJ3sE0DQbvYAA4BJTLODCY8ehfkdUNBr8iA+AoUC7jwGDOwJmH/B1M5R0M/g4GgOMs lItuMBG1x/R6Pxd/kOZuzj8P9y/9+kbS0nIJlab2NBh/Iuom/TJVrx/1JMkxK33qrW3MZ55o ff1eZDCrdWCAQ+dQEbu/1K/IaH86x+5/dI0BcJxEudhclIjmy95c0htYDKn4Qxvq73Y3b2Ic FahrYhnH3fzP9X0ZEoxmUio7lbUkQK1tChawmpmew3UG01kHZ3LFOSzB5/XDxw7AFzIrF3UV LG6wtAUj3Qea1/PpTMCZQ+Hpnvu6sz7uGhRn4jJoAe81GN9SWvWx1hNua5uGyria0TiuMxhH bx3UIIPYvfOF5xAAcAlRubgF0eoCopu3sJ2NITw9JuLg0pPY5C9Ra/g43sTmcvQYjBcmEWIR f2lZ6XV8DCRAE/3vt8Wy5eLEy1kahvJriVihLg4gx5BAJufqaAqtPiqftAClrPPxB8Nm83bL PfUTq8TH5Kl1bRC079+9rburzyEA4AqicqXCTkiXg1//XxKbgmqKMeQGpdf33NySXvL1+/QY DJGJOotdKAuLTBA+EZxkW9iP50WctIlQbCVaDqqrQlVkZKKpp/WdI7LPzHxeuI7CMczzIvI+ f53V5OrYH55LV60ffdyzYbwmeutWxhtRWkfbufYcAgDOJzUYJSiMumFrRpEbgxcINx+UYrvB OKJo7DQYQZ7aiwLqoeOexTlsC/mLuNOkY/ce0wgk/wQunz6mwjwRWjpcUrdtUZUr9SMtiNax enOZ62ltqse69hwCAM5nVq5wI6c3Id30/sZeNxh/o5OgTeonnrsMxuGFi/btUYVcnPyybynM x+CCbhAnJdQZfcd0VgvGoctXm2fmVkxsvTD99RPTrtTH8BaM5HvSOQQAnI9SLhFEfVPONzaL SEEY6UV+XMs3tYiCh02nsF/O8u8OQnk69vXlnMUpLWtDnLQIJdt83tFEnPnqYtAxdRVrAMcM xlF4cOirn8m1HucTsvrJFNp39zsY4tpzCAA4n0y56D70ghan+Y6f+8QZMSQ/SbJZfNPt8/sZ LyT6A4JznrmIubQLVVjuT8QYtJ6FRmKGifPPyhTFWK/XYhXWJXlR2pbYpkJ5FCnrzFxW7kKM 81RkakmUypsJf7F+nAAndeCPI27vOSAS8XrFrHLdOQQAXMHCYFrM5nGctMtmO0f33w21CC4U KxFSAAC4G1G5/jxTESsv01PtSldJB6/p+XYP37s5uv9u+Ik4aw2cDAwGAHBXWLnIPLShtJdf 7z//++dSkbUBmeu15kLAYAAAdyUazJ7/wfnAYAAAd+WPNgua37IMzgcGAwC4K4nBEFuXwbnA YAAAdwXKZRwYDADgrkC5jAODAQDcFSiXcWAwAIC7AuUyDgwGAHBXoFzGgcEAAO4KlMs4MBgA wF2BchkHBgMAuCtQLuO0DeYTn68Z+7Voe7jjS74abhD+Jl7vNwH9+eLr6PHYd+6q+cn1V/iS 9QKV5hP1u1pnNzjvNwQGY5y6wdDNffzDo6DABz5q2o8YRs+5J1EP6TaZkqaW3/L6k+EWigY2 Pd5/XVk+M2xCZ52ZPu/3BAZjnJrBjBw6ARTYMizDwXFwNtNrFrtNJaMQp3T90ai0TxqTqNAS oIEJadv6SLAn0VsXFw/H8e3AYIxTNBi6WUrNebo53PopDDxGN7MMQtZ1Y/fsr2/UOC9PiG7a cnNeUV5HHMiMJi7f3F3zmHzZl/mpp/8WfC72P/XOZQsx6JhiOUtld/SIJafJ9t107nS3F00q Pz7m5fXnhz338dJQTzZgOjer57XjnI6oM4nJU3IsnecddAGDMY7cBBq+OZI7mJiFgm9EvqH0 /JoI9uwvaTJhSm703pvzivI6aF4EJIlL+1NZnaA8yzmRUC2qWeFF6qgYeSHX+cTB9Gpl5/mO fJN0284di7QUKttWvv5oPRlM2K5EW6/n81Ol95o4WmeUj8Rym9xDBq8OrJ130A8MxjheBJYG U7xRFzdUYb5Fz/48H25UPU/ky2s08wjzLbbsL0+5ej2nq5e3JYgsouHc9ExNYaWyKVFc+F1e 9pVyR/J0erm1zeWSvF/J0tbqRYzE7y8i7eaDWq8bjIPz6jinB+tMWjnl4+goJ+gCBmMcEShN 9QbovTlr9OzP8+FG1fNEvrxGM48w36Jr//BUzCKXPrm6x173tFsX/zWhoe3HWzDE/ESeDgVe KTsfX0e+eTq9vLpNPcVnaWv1MhuMKy0JuDOA6flY3S+B81o7p8SIOgtpk7iUFAYzChiMcWoG U+qiqN6Qi5uzQs/+PN8hUj008wjzLTr2T+sqExxeT0JVLnNXVwnFOfAOJhKeuHV+zbL31HOe Ti+3tgXx1i0EnbZ2/dGL/LiW9xGh9yTdbjV4P32chXlhd51N72c8cAqj6sGBLrJxwGCMUzIY vlnk5o8EUeAbTs+Hm47iNO+anv2fcf0fJ6oPmeebeN5H97/XuaK8vOCFTk9S9mR7Jl4cPxWe Kk7ojv+KjPLLytAqe7HMGnk695Ouo65zp/N29ZDU0eL6U/u7SU7bLNTp9vn68GX0Rk/M6fqu CUqzp87SulnG7DzvYBUYjHHkJsjBU9bJ0NMxKrjKyOsv7eL6MDjvQ4HBGKdmMO5OcE9heNI6 BX4KbrUOwKjr7zU9366xYgOc9+HAYIxTNxii0EXQotR9ECeDZvWR8pJw3kRkPn4+N15/prnR eb8RMBjjiGAAAMDdgHIZBwYDALgrUC7jwGAAAHcFymUcGAwA4K5AuYwDgwEA3BUol3FgMACA uwLlMg4MBgBwV6BcxoHBgM+SfVYlTGf8sTv90eXzQ391Wcubv5+WHz/+0r8bKJdx5KIG4DM4 g7lAUOlDmZ/W7VfXN+WuqY9vAcplHBgM+CznC+rr+XlziTiTaX+qHwazBSiXcWAw4LOcLKj0 uZta/PgpnMZnb2ppKuvjV5kbMfPP96fAYLYA5TIODAZ8ljMF9fV+6jFkEly+YgJsFqV0tTSV 9W5eusDYaFrGVh1yAgazBSiXcWAw4LOcKKgk5LWmQvLZfPqoZuGHBbU0nfu2usLqrRgYzBag XMaBwYDPcp6gUiuipvF5C4N+zZUbQi3N+r7OdBaD+GdUDQgGswUol3FgMOCznCWo1LKofx6f TEILfM1gSmna+7rjCfdUHi/FpSt2k8FgtgDlMg4MBnyWswS1Hfc8g/FQmvaQ0zUDhMFsAcpl HBgM+CwnCap64V7k7HcwdFwrA4yV38PAYLYA5TIODAZ8lpMEdeUluzcA9UuwWndVMU3HvokJ laG/z4HBHAPKZRwYDPgs5xnMalgyB77+VUsirIv7ltIQhfW+W8zfT2vmQlD6ZTIYzBagXMaB wYDP8kGD+TAwmONAuYwDgwGfBQaTAoPZApTLOG2DcRf7yovKcVBepZeld8cdV/Wvto3A3T1Z F1AVf574uqEPSO45Z0l+BUGN3U+Uh9qm16/VKQzmJ4DBGKduMCQkvaIDmrAwXmXUWxHD6DnX 9IupkG6TKWny/P59//PPv7wlR95ppHrryrD2R4zEv/+8K2HN8N//+0+hjK4+/udh+4HEEDAY 49QMhn7bjwepgXT8qihCT99XOnuvWew2lYwkTv2J/fV8vieqt8ScOw3mzi0Y6y1eQ8BgjFM0 GBKA0kUehUGeQt3UcxeTSLh4U3gilT9Wk3lGi87efIQzy+kg8+WYMa7/Wwhafkw+z+VPZNXT fwuu+/2tnblsIQYLtJSzVHaHrvsanCbbV++3WudzHflJ8nPpk3QzbDDufy5zvB5hMGAGBmMc ueE1LKqLK18JRyJea6I578eiG4RqnqdYkiYTqE35CGeW00HzIgB6Pe9PedQFcK1V6M2s9zhr eCHX+UxOqGN5S2Xn+Y58k3TbzhmbhBQq2eb2rVSKGIzk5U0bBgNmYDDG8aKwNBh/M2fkQrRJ mLSY1eZDrDxuvrzG3v053Uo5BRZJJajESj7VenV4cxGRXp9qcRgqmzKShR7nZV8pdyRPp5db 21wuyfu8fNuqwTh4HzJOGAyYgcEYRwRLA4NpzLt/+WmdlYHmZb1jculc66FlIi1j8Caz4Tir zK2Y2HphKmXfVD+Vel3dplpVSVpXjqXKMonBOKR+/sJgQAAGY5yawSy7yBwtEWnB6VaEW8fK 4+bLa+zdn9O1y5nWTSbSvJ7EvZzXWhcZQ3EOvIOJhFaKzq9Z9u76qdRra1swPN2qmre1fkWW f0olxFmtRAd+RfYTwGCMUzIYFoDFU1S4uTk9CZNabj5xzem4eyPOUzb0ROqWH08Vyz157spH OLOcvODEMcSTScqcbM9NgmIqAW5BT99dCVtQflkZWmUvlllDhjTvp+uo65zpvF09zHVUbsHM P0bI66yU3pctGRr5zi0Y6wU3BAzGOP4mXp6mrqdt0A+1KFChBcYJatIdCIP5CWAwxqkZDF/o i6dHsAt+em+1Dn6ZMYL6mp5v16iagcH8BDAY49QNhih0s5Qodb3EyZBJfaScZNQ3MZdP1c8Z gtpjMPF4G8dWS9Pcd+4ibJUBBnMcGIxxREAA+AznGUzzp9xs/MEc2CxKDwG1NK19aZu7pzqO CePBHAfKZRwYDPgsJwmqE/7rR7T0821jm8GIlseBchkHBgM+y1mC2o7LvwxU2+lHLbkx1NJU 9w2tmYf8Aq55XGRGlVZTcz+ggXIZBwYDPstZgloTcA+ZhDaUmsGU0rTW0xAGE2XKZtN6B+OO u/izeRjMFqBcxoHBgM9ynqCS4GeeETnLYErri1TfEcFgtgDlMg4MBnyWEwWVWhENgS+/R1Fs fAdDBlPsOitQfv9CwGC2AOUyDgwGfJYzBbXVTeby1b8Eq3VXFdNU1nO3mBiHSrOgdcytbSAH ymUcGAz4LCcLKnVF1eKzIdD1r4wgrIu7lNIQtfXUuuH19fcv9dYLAYPZApTLODAY8FnOF1T6 exMzmu0MqP2dORjMFqBcxoHBgM9yjaBOj8+bzGvVXAgYzBagXMaBwYDP4gQ1XIN6OkNj6Xtl z+SDZddBY9uU8qYfAuTH3v77GaCBchlHLmoAALgbUC7jwGAAAHcFymUcGAwA4K5AuYwDgwEA 3BUol3FgMACAuwLlMg4MBgBwV6BcxoHBAADuCpTLODAYAMBdgXIZBwYDALgrUC7jwGAAAHcF ymWcdYNRn/IY+gkLH9eH1PMDqH3pthMe1+PA/gCAa4DBGKdtMDSeRhBZFu07CC6ZlS5zfdjc Im4f+SBhPoAUAMAWMBjjNA3mNqaiqIw2uAsaS+RWBw/AbwGDMU7VYGI3U5iiSuuv3yrzETN6 +gGXVkVdm9eakbntD2cUsSyN+FuGrW3jzOm515kAAFcAgzGOCHaRhfCnLQL/qXHqgtr6nkbS U2w9HzYnTCz0vRZBBqMNZZ/BzMeDFgwAdoHBGGeTwbSWF2a0Qu++aghaPbVaMMcNxuNf9m98 hwMAuAwYjHFEsIvkws9ir5YvMpiuRpEw8h0Mt2RgMABYBQZjnE0GI11Hotgk5n+fvvvqLIOh PP86ke+Ny2VUcaV8e0jMCgBgDRiMceoGM7+HoGluFJAZyHp5uvcthXRdC5XemUd8gV8zA5dn 70t+JpYxNy1/TH5fPT/ju8VCPjAXAEwDgzGOiCkAANwNKJdxYDAAgLsC5TIODAYAcFegXMaB wQAA7gqUyzgwGADAXYFyGQcGAwC4K1Au48BgAAB3BcplHBgMAOCuQLmMA4MBANwVKJdxYDAA gLsC5TLOaIOBYQEArgJKYxwYDADgrkBpjAODAQDcFSiNcewYTPnrxmNRX4jmjPJli6x/Afoo NCjbZw7/inM+kw+nDe4PDMY4+w2hzOh446AhAvT4M1TOnvFoGmwdDM0ioS6+XXfjMAwwmK8C BmOcnzGY3ET2mkpkw2iZZET7M9qIK9ejf5C16fl06e9qMNuOFS2Y7wMGY5xLDCaMfDmFp0ga I1+eKON4+Vrw4/yeLiy1TxJP1rnJtWSS5RA7GWxMD36m9vflVQOm0dQqG+1LI3KGxc0U68Vv KrNBdEMLrNlFFvPceC4uOecwmF8HBmMcvpHdNIplvFkwWFhYSPQ8ia+kyQRGRscksVoVVsIL v2gICWeMocWstMxlmI3gNU1BuCimpKM0er795O8FtafcNUr1shavV3RduqcvfN1gJM+t52Le 79xzDoP5dWAwxvE39ZkG44iisjYfBEXPE/lyjdZ+HTG9IaknbILTifj5yWuUF8WaXiWtoY4p yVPTOoaIN9ZS3Oow1NMzxkkNJjuujnorwunOOOc7jjUAg/k+YDDGkZtzFMV4TYE5IjYZ+VPv rpjyNF0oY0LbYIjjLRhH6xiK9D3Vi5nqqWhy3fWWoeutOV85tny5CFowvw4MxjgiLqMoxmsK zCixIYI5iIiE9wC822rM6f1UGUwP2eafmKP4upg+/LrBMJSP1XcwgXoXmWO13ipwurPPOQzm 14HBGOd8g/ECTesek54PNzyldyIRuz2cGD9iFwgJ0bzPWhcIw8Kk9yekVeKnx5QvL9MkQqRj qvWxFbAmWmRKq4pcQh+7qpdmPWwTXaJuMCr/TediTnfuOXfpeo+VW7ch5tr5ArcBBmMcuelG MToeAADUgNIYBwYDALgrUBrj3Mpgku6vfOp4LwDGgXMBDACDMY6IwihGxwMAgBpQGuPAYAAA dwVKYxwYDADgrkBpjAODAQDcFSiNcWAwAIC7AqUxDgwGAHBXoDTGgcEAAO4KlMY4MBgAwF2B 0hgHBgMAuCtQGuPAYAAAdwVKY5zfMxj11WT+qm6+bBFfRl88PT+O5if7vwx8tv97gMEYZ7Qh jI43FvoMvB5/hMqql3d8QyuOD3NjQl38gubOwwXAYL4BGIxxfspgchPZayoRP25Jl1btHhNm DxvGSXFMz6dLf2eD2Xa8aMF8DzAY41xiMDTY09+nEzL/9EijQ8qTpB6mNxnGlwXACzgtyyBh 1bHrE1S3V9JCkXVuci2ZZDkITnzC5TRKtNT+vgxz2fT+RWhfq6NahhZY36iWG7sTLzvvMJhf BQZjHLmxR7GMN4sSi0QQ6nk+CC/Ni6Dr9bw/iZsTkWePKHhxEv3w4qXy0OKcL3NesxG8nLj5 TRRT0kl5ZL795O8FVeexFak/iqHnw+YivYI712ndYCRPVY9kHKtlmPc7/7z3Hq8HBvM9wGCM szSEYxTj5YJSmhdYvJSYEZyuU6TztHq5tS0gT9PJEzOn8+tl8vrkRbSmVUlrqGNK8tS0jiFC JliOWx12eHrGOKnBZMfVUW9FON1Z533H8QZgMN8DDMY4clOOohivS2jCEy/f+DSvhMYJ4V8n JlUB1uRP11qkcsHKlyOhLMVyatoGQxxvwThax1Ck74k+6ZoKU7GOu+stQ9dbbT7U4bHzjhbM rwKDMY4IyyiK8TqEJr3pldBQGl5PT6w9Qq0Fixb9ewDejfNrCeX0fqoMpods80/LUehcTB9+ 3WAYysfqO5hAvYvMsVpvFTjdFecdBvOrwGCMc77BeHGmdY9Jz4cbndL7BSc6flucnCg/KH2y vUOok1iSPhhPmOTl8by8TJOIkI6p1sdWgE5bgkxpVZFLzHUW64PnW4K6TXCJusGo/LkudXlW yhDSnX/eNxxv7IoL8cGtgcEYR262UYyOBwAANaA0xoHBAADuCpTGOLczmFKXSpw63guAceBc gA8DgzGOCMIoRscDAIAaUBrjwGAAAHcFSmMcGAwA4K5AaYwDgwEA3BUojXFgMACAuwKlMQ4M BgBwV6A0xoHBAADuCpTGODAYAMBdgdIYBwYDALgrUBrjwGAAAHcFSmOcawwm/6y9+mqxiS/a 5uUDANwBGIxxrjEYDX26PXynir9lhW9WAQD2AYMxzuUGA1MBAAwCBmOcSwxGTIWGwA3beerp kwojUk5hkCoaVVIGrOoeQnltf216cb7djcfrG1ORK47FkQyFzGXXA3754+rKDwDjwGCMI0I0 imU8EepcwP3WNrPIsyDyvnp+bXTLnv11+eb0cQRFHgFxWV45ztq05IpjcdC8jDSZxKX96Tic 2TzbOQFwF2AwxqkL4j6K8Vjo9hiMIxfP0nyLnv15vlK+fPkIzfzDfIst+7Mx0rlQ6zndoGMB wAAwGOPAYGS+Ur58OSDHWZuKNPMP8y269g8tHe4ao3kVl7oo/4ZWDwBfAAzGOE1B3EExHgsg DKadf5hv0bE/v5OJ74yUwVCa+D5mQ/0DYBgYjHGagriDZbz5BfMfJ2z6JX/h3XmGfjmt54OQ UpxmkJ79n6p8j/dD5lmYddnDe43dXHEsvJDUMU9yXMn2YDwA3BgYjHFEhEYxOh4AANSA0hgH BgMAuCtQGuPc3mBKXUJxutm7hm86FgAuAAZjHBGwUYyOBwAANaA0xoHBAADuCpTGODAYAMBd gdIYBwYDALgrUBrjwGAAAHcFSmMcGAwA4K5AaYwDgwEA3BUojXGsG8zoeACA7wHKYBzrhjA6 HgDge4AyGMe6IYyOBwD4HqAMxrFuCKPjEekn7Y3An4mpfA6mtQ2AHwYGYxzrhjA6Xt+n8Qcz Pfiz+nVkOOSSibS2AfDbwGCMY90QRscjNrdgyCB2q7sfu2U1O7RgANgMDMY41g2hGE8El4YA Dtu3+MUmg6G8/u4dnGseGIynkOf0WK4rHVMc2jg3GF7O0gDwg8BgjCNCN4rz40mXkZvCKJO+ 26vfBHoNxsc92nLw5Y3ZsWGF0THZKNSQxuqYZJn343kpB5mWzFPso+UD4L7AYIxzviEcoxgv EVwiE/EVegzGm4vPu2eqtyQqZZseYV9tMKlZUEuH4+ptwXh03r3HDcC3AYMxjojUKC6JVzSY /if5j7ZgwrLPn+b3GMzeLjsAvgsYjHEuMYQDFOOFp/go2tQakK6lDnoNhqG8dr+DIVKDSfNu GIw2kmSbf68TW0yrv1AbBZX1qNm2OC/+/M7Lx8+XwX2BwRinKOAHuCReMBjZtuX9C5uR7Ner zId+RaYEjfJblN1NbI7ZDwLiMen12nDCumvc5b64c5d0X+bLnbyeD5iRQWAwxhFBG8Ul8ZIn egDqUItRG0q+3Mv0wPVmERiMcS4xhAMU48FgllCduJbQxO+NXJ1Rq0haa2vdh1376i6s0LVn Jb7Dvy9zad0kBqLXUYyYf1jWrcbHc3pPIZPY4pR8pRyUDg1GU8BgjCM3zijOj0fi49ctusbY eGRbPn2zIc1C6cU11BGrIW1rHXvfvl50aX5O79NoYyhxdnxHMDBOEq4B3pUXGy0YZxwyH1so yTpf5tdriuUEtoDBGIdvZDeNwnq874WEWL+3EUH0gi2CW6ZnX72+lr7GufFzExFjIJoGIw8k qoVE2+Wa44kL13OM4BNAGYwzWsCtx/tefttgvBF4tIk0DSYgpkIhaH5ZVz3HCD4BlME41g1h dLzv5XcNxrmCeieXpm8azPSc40rXGL1viZXlysHzHWUAHwHKYBzrhjA63rcSX0w7QYzz+sW2 6gbK6dlXzz9Venn6n+OTOcxdVMTY+GViOje53Tzq5Xw0j2SZ3t34Zf0+L5axsC7GBiaAMhhH brhRWI8HrmGaoMTgfKAMxrFuCKPjgfN5OXORn/wCcCZQBuNYN4TR8X6W6k+4b/Ju4e7lB6cA ZTCO3KijsB4PAPA9QBmMY90QRscDAHwPUAbjWDeE0fEAAN8DlME41g1hdDwAwPcAZTCOdUMY HQ8A8D1AGYxj3RBGxwMAfA9QBuNYN4TR8QAA3wOUwTjWDWF0PADA9wBlMI51QxgdDwDwPUAZ jGPdEEbHAwB8D1AG41g3hLHx/OfhfUxjnxhJPjmf0doGwA8DgzGObUMYG+/1fESR5s+vr3wC fhjTo2M8lprptbYB8NvAYIxj2RCI0fEi3CqYx/toQgaxW919q2l1HBG0YADYDAzGONYNoRhP BJcGjArbNw8ERTF6WjCcrtOIFuguOTeFQs4DWs3rSscUB+3KDYaXszQA/CAwGOOI0I3i/HjS ZeSmYBB+NMONJuBaJWvi7OMebTn48kYD1MbGRhHKLaaRbAv78byUQw/fS7GPlg+A+wKDMc75 hnCMYrxEcIlMxFdx6VdaL3oI3p6pblaVssXhe7XBpGZBLR2Oq7cF49F59x83AN8FDMY4IlKj uCRe0WD6n+SnR19r55QWTFj2XWM0v8dgNrbWAPhSYDDGucQQDlCMF57io2hTa6DnfYqDTCPu 5+KsvrynvHa/gyFSg2HTmgteNxhtJMk2/14ntphWf6E2CirrUbP9HPN7L38M+TK4JzAY4xQF /ACXxGPBFYGgqc8AkpfrPHWKy6Ffkal8yQkWZXcTm2P2g4B4THq9Npyw7hp3uTf5+7Z8uRP9 M3dgAxiMcUTQRnFJvOSJHoA21GrUhpIv9zI9cM1ZAwZjnEsM4QDFeDCYJVQnriU08XsjV2fU KqKuQ5kPyYp07au7yELX3vD4bpknaqnNLbfHk873+k+y/Tszv4+k1esor1iGsKxbjo/n9J5C FrHVKeWT8lI6NBrNAIMxjtw0ozg/Xi5ECjYe2ZZP32xIs0h6YQ11xEpI21rH3revF1yan9P7 NJT+ePy5VTGv82npHE/vZz0DTzAxThWuAzGCZgvGGYfMxxZKss6X+/VyZWjWI/gEMBjjePG9 k8GAMiLGhBZpL/AitmV69i0Jf76+Rm/Z/DKd77iOWw6yb53cRMQYiKbByENJbEn57XLd8cSF 6TlOcDVQBuPITTQK6/G+l5sbDBsJrdd50npqmcxmUYNNQR2kNpGmwQTEVCgEzatQgZ7jBFcD ZTCOdUMYHe97ubfBUItjzifMU+vCz6znwS0RHXdO3zQYZ2Bxk3SNkdn5wtDK96O3DOByoAzG sW4Io+N9K/GltBPDOK9faqsuoJyeffX8U6WXJ/85PplJ2uLoKhu3YGibE39nMPF/EvdCN1aJ WBY30W5MjBvKtFj2LSS/TkxQlbmwLsYGHwfKYBy52UZhPR64hmmCCoPzgTIYx7ohjI4Hzufl zEV+7gvAmUAZjGPdEEbH+1mkm2kx3ei9wjccAxgKlME4cpOOYnQ8AACoAaUxDgwGAHBXoDTG gcEAAO4KlMY4MBgAwF2B0hgHBgMAuCtQGuPAYAAAdwVKYxwYDADgrkBpjAODAQDcFSiNcWAw AIC7AqUxDgwGAHBXoDTGgcEAAO4KlMY4MBgAwF2B0hgHBgMAuCtQGuPYMxg/YNX5gzpdlQ8A 4CxgMMYxYTDTIwi9Hy6X9ofwAwDWgMEY5/MGo8ZgZ9CyAAD0AYMxznUG443Db5cBouYWC0/s KmIwapsei10NOhXHfed1LuZzHm+dpmWMsEzzsk8MMY/nvpofAMAEMBjjiKiOohwvbaVMD0rz cFbCS1mLRYwoiH9iBBRH5ikdzSvjkiC0TzQJvY9jeqp9dCwpj9tjmgr7Sn68AQBgABiMcS4x mKy1kC57sc8NprisWhMyzetT8ScT8zH8/t58nGE8Q+BsH296WSullh8AwAQwGOOIcI6iGG+i rqtRBjO3NCIFg+E8XStmej7ceorhtrv5GLe0j5iR5FHLDwBgAhiMcS4xGBFuUfcg/l7bG4bC 6GXf1RZbGfLrs6JZ+LSSJ7dQFu9WZpN7qp2nh6yv5AcAMAEMxjjXGIyDBd1vm9+/eKR7iswg zgfxn5d1qyKs8+7ijUSnCby49RIX3o95Yd6HTUdaLmHSLrLIDwBgBRiMcURURzE6HgAA1IDS GAcGAwC4K1Aa48BgAAB3BUpjHBgMAOCuQGmMA4MBANwVKI1xYDAAgLsCpTEODOb3mOKncADY youvHytAaYxj3WBGx/t5+FtsYR74P579tgpJ/ubrBFx8+eLSp4EyGMe6IYyO99u85m+xAcf0 fjzU1x2+iOSPjE9gMlJvUAbjWDeE0fF+GnzqJmF6nCvCn8WZp/400miMXEtQBuNYN4TR8X6Z 7xbUjTiB3D6+D31SKP/m3Rjqn0g6kN+Z3X/UDWfAYaAMxhkt4Nbj/S70/TV8Gdpz8tP9VnKz 22V+5W6x+cOto7FRh1AG41g3hNHxfhb6aKclUf0gNHqppa5CKo82lHy5l6KZ0Hk/5WDpgeUs 8+oHymAc64YwOt7P4p6K8TVoofD0HQx4kqGzaTvVmcxzIt1FRvOuRbhIU0cPyy0Gkg/VHfMP y3GYb7f8eE7vKWQSu9AkXykHpVOn+bwWjC/Dpy8pKINx5KIchfV4PwsMJsXVx9xKmEXcryPz cMtcX/OTuhd1mp/T+zTaeCroFiTNu33ldDRbMKqc0SySdb7Mr9e0bFG4dGf+XBkGA1YZLeDW 4/0q/KQMg0lIf/QQWiQ8r7t/vJn4qtPra+nL5CYixkA0DSaYkW4h8bkM9wVPXLi8DK58ap8z 0MfwKaAMxhkt4Nbj/Sq5iAHCiXD8e47zDUYbvD4f+bkpnSve390HFILmVahAWoaz/w6GKJXz aqAMxrFuCKPjEXyzLu/Qc+AnUC1Kn+lW+Nwxn0Qrjy35x26kcw0mLVNuBg2D0V9ekK4x9/98 Ll05eF7FdHn1d4354/P3mRxPjkqTtaRgMKDJaAG3Ho+FlmJeIrbeUHb9LQMJ38AiXmcwB45Z WD32Vh778vfvV9zkMo7zTkz1S389/1Tp4zW10iUV07kpHh+ZRVgXzSNZdsZUMIBYxsK6Pae5 ua8r019nXvn1A4MBq/iL9HcMhtgstiR4e2+kXU/z/olxj1BUIeEaGrDBrmMWOo+9lceh/H+T 19OZJt0XBZPkd1UFMyFTuuqSqgGDMY51QyjGEwGhp7uwfcuFvslgKK8jf6Coxa44L0/cbuIy 6S4LWSfp/bp4o0uMp3/qfTiRqNYLpc2PmUxHPZlTXHnKljwWT8ryhB1izdvndfOxyaKPyVPz Kb987M081LEu6kUy4uUsDUggg3FtN74Wk8vE1R09XJVaKzAYsIrcuKM4P54S5CBWXsD6TaDX YHxcJVR7iGKnu27UMSTCLXnlNzoJr96WxeCEarlYL257Iu5zehaOIMLzvOy3bFFMTow4DqWT mHqfeMy0QPnM5+a1OlSAL1fMr5nHfKyyzPsl+ZfqjuZPQMq0mE7McxDeYOh/d82o60SvTw1G 1+vngMEYR26CUVwSLxEQIhOlFXoMxouzCMT6VH0y1mWtzRPJckFks/yWQlpYTuKQIMxCz3B6 LdiFeSK0dDis27b4ILO0apL953JIC6RaRwmVc7mSB0H5zAYZtvH8XG80rZz6n0SMJK1/Nx8q q2wwsxF9ChiMceSmG8Ul8RbiQjdFKjYtegyG8CbTH7fIQuwK80SynIksb1OCLzRjEGm9LP6q W8etzTNzKya2XhhfzrkFVRf/mLZ0HAnZsct+HXnUDWYtTzAbjK9HeqCY1E+dlwbjzsV8kj4G DMY4lxjCAYrxWDSUCOkn7A56DYahvE59B8OpsuVcZL3AxxvcHS9vK8Zo1IvsJ3B6LdiFeSG0 IPT+aT3WxH96P2MBKYwqb5H02PvykOXStkrdgQR6kR+rhetPTN3DpqMrzkg9wmCMc4khHKAY T26AOGVi2CIIJU+9dwjdTG1VrODFzefnngBl3hnWI66nsqt0wRCkWymWUR8zr9OxtbDKOrU+ 4vaJ/Vvz/o9Jz1MYarm55aR+KE0Wb5GfmxbH5g0jbk9i+m35jw+SYy/mQXWkj58mKZteX6iX LK/fI6/ztB5lNZ0DP5/Vs1yfSUv2c8BgjCMXziguiceCsfYk/IP01Iv+wz0jWBGrX+JQndN3 z4z4NAzGOJcYwgGK8WAwZTrrZf2XXNfxcoYnXwgG13Cszl/vyV0/VoDBGOcSQzjAMp7ucuno sonTtxtSo14A+FJgMMYRAR6F9XgAgO8BymAc64YwOh4A4HuAMhjHuiGMjgcA+B6gDMaxbgij 4wEAvgcog3GsG8LoeACA7wHKYBzrhjA6HgDge4AyGMe6IYyOB978dwz40xOwHzt/CwNlMI51 Qxgd7+cx+Jf8H2X3Z4CM89oybPIOXHwLf80PZTCOdUMYHe+3ealvkQH+49TH936m5qW+hnwG k4G6gzIYx7ohjI730+BLwgk8FPC3ugvjDHTDV8Y3Y+B6gjIYx7ohjI73y3y/oG7AiWM6vsnn iV+RDp81ypd3cWYXIHXDfdhhoAzGGS3g1uP9LvTZdXyjzHPyk/0ecsPbaYClbrH1MXj28vl6 hDIYx7ohjI73s9CHQK2J6oeg8W6sdRVSmbSh5Mu9FM2Ezv0pB0wPLZ/9iCyUwTjWDWF0vJ/F PRFjsC2h8OQdDHiSwdZoO9WZzHMit1+4Hv0Xq+fBuB5P/yXvNVOIg7mptHod5RXLEJb14GqP 5xQ/tR+70KR8Ul5Kp071eS0YX4ZPXlZQBuPIBTkK6/F+FhhMStIFNQu4XxeMhOtrfkqfWxX6 yZ3SktmkQ0MX0a1Imnd5yClptmBUWaNZJOt8uV80EFjeonDpzvy5MgwGNLFuCKPj/Sr8lAyD SUh/9CBGQWgD8eYzV91sRnEdmXfHGDy5iYgxEE2DCWY0t6T8drk3eOLC6HIThZbaYPQxfAIo g3HkAh2F9Xi/Si5ggHACHP+Wo8Ng2EhofWY6E7VM1oWWTWF2quSc5OendL54f3cvUAiaV6EC qcGc/XcwRKmcVwJlMI51QxgbzwuDj6mf9E6Enz4lLxIx/TR8HSxOV2WcHPNJtPLYkn/sQlo3 mLk7SBkM5eVnEnEvkpQrTZ8LdbKsv74gXWNkdvF8klFmZXB59XeN+ePx90WtJabSZC0pGAyo MlbAbcfTT3QkFvpGOQdvKLvMjISvfKfv4jqDOXDMwuqxt/LYlz9fD7SfyzjOu+uj+NLfxaYW S/yfCsvmEdKFmCX4PHAM9aAR44ZW0GLZxS4YQCxnYd2eU93c15XprzOv/BqCwYAm/gL9DYNJ YEGoPa1lkODtvYmSp9Ze/NPiHpGoQqI1NGCDXccsdB57K49D+f8ur6drKZEBFkyS31cVzIRM 6arLqgQMxjjWDaEYTwSEnuzC9s0XOcXoacFwuk4jKqHFrjgvT9xu4oPQ3RWyTtL7dfEmlxiu ZcZ1wD+VrdQLpc0riUxHPaVTXHnCljwWT8nydB1izdvndfOxyeL81N5+wi8fezMPdayLepGM eDlLAxaQwdCv4eh6TC4VV3/0gFVqrcBgQBO5cUdxfjwlyEGsvIBtNAFq8q+IjY+rhGoPUex0 1406hkS4Ja/8Jifh1duyGJxQLRfrxW1PxH1Oz/UQRHiel/2WLYrJCRHHoXQSU+8Tj5kWKJ/5 3LxWhwrw5Yr5NfOYj1WWeb8k/1Ld0fxJSLkW08n5DsAbDP3vrht1rej16T2j6/YzwGCMIzfA KC6JlwgIkYnSKi59IrZLvDiLOKxPVbPSZa3NE8lyQWSz/JZCWlhO4pAYzELPcHot2IV5IrR0 OKzbtvggs7Rqkv3nckgLZM3QPZVzuZIHQfnMBhm28fxcbzT1Xye/hRhJeg7cfKiwssG076Oz gcEYR266UVwSbyEudEOkYtOC+pN7NMabTH/cIguxK8wTyXImsrytUOZmDCKtl8VfdOu4tXlm bsXE1gvjyzm3oPT+WV6StnQcCdmxy34dedQNZi1PQMwG4+uSHiom9cOYpcG48zGfqI8AgzHO JYZwgGI8Fg0lQvoJewW6SeJ+Ls7qy3vK69R3MJwqW85F1gt8vLnd8fK2YoxGvch+AqfXgl2Y F0ILQu/PBjxnVhH/9C/c1z9bkh57Xx6yXNpWqTuwIHnw4joUY/ew6ejKM1CXMBjjXGIIByjG k4s/TpkYVpCumnlaE7sA3UhdCXO8uEle8aemzrAecT2VXaULhhDLKnewPmZep2NrYZV1an3E 7RP7t+b9H5OepzChezBRD0qTxVvk56bFsXnDiNuTmH5b/uOD5NiLeVAd6eOnScqm1xfqJcvr N8nrPa1LWU3nwc9ndS3XaNKa/QwwGOPIRTOKS+KxYHSawy/RUy/6j/aMYEGofpFD9U7fPTPg 1TAY41xiCAcoxoPBlOmsl/Vfcl3HyxmefB0YXMexen+9J3cNWQAGY5xLDOEAy3i6y6WjyyZO 325IjXoB4EuBwRhHBHgUo+MBAEANKI1xYDAAgLsCpTEODAYAcFegNMaBwQAA7gqUxjgwGADA XYHSGAcGAwC4K1Aa48BgAAB3BUpjHBgMAOCuQGmMA4MBANwVKI1xYDAAgLsCpTEODGYc6afl t+A/8zLvqj77siveKPJyAWALGIxxYDBjKH/ifg/0afTw3TR81BOAJjAY43ydweweu+U4+1sw CpgKAN3AYIxzicGIaD7DqIgPP9LiFJ76abRBaQGkQ7JuhPIZMfrkRP/749jiF7sNppAvTz2x oiFt7FajESrXzkGMrefb+fD6xlTkzGNwJAPNcdx5AK3H5PM8dN2BjwGDMY7ceKNYxstFY17m m5rFRc/vMwgvLEEMd6HKGUbs8zH7y7PPYCTfXMj91jaqzFJOEt3V/XvOgS5Xfz4+TX1acuYx OGg+nM9kPe9PeTizsTByFtgFDMY49Rt/H8V4fGMrwcgFoDS/AXlq7Z1YhErk5WQR6m/F7DMY h853UYYV8vS9+3O6lXOgY+Vx8+Uj7I3N6VaOQWDTovOv1vfmA8wCgzGOiO4oivHyG3mLMHRy vAXjWAiOPOWGxRVgMPP5r01FOmMv4HQrx+D+5ZZObD3Legd1Sf5tPHAA88BgjNO88XdQjFcU kDVhILTAd4g97X/4HYxqsYQ+/l75gcHYM5j0nCiDoTS8Xv1qD9wOGIxxmjf+Dpbx5heqvntC v2DV80EMKN0ekRacKez+FRkLk5SVpiBGPcQumK3lV/XjhE7nvx6mXrdtY+w5B08Vy9Xprnx6 OPMYeCE7p26S40m2bzjXwAwwGOPITTeK0fEuhcUGT7MA3AUYjHFsG8zGLrKjwGAAuBUwGONY Nhj/9wte8PX8OZCB+bIvuktK3SxxMmpIdyxzzjccAzgVGIxx5IYdxdh41LcuQqLnAQAABmMe GAwA4K7AYIwDgwEA3BUYjHEsG0z8uenf+XtTx38WCwD4FmAwxhlpCMToeAAAUANKYxwYDADg rkBpjAODAQDcFSiNcWAwAIC7AqUxDgwGAHBXoDTGgcEAAO4KlMY4MBgAwF2B0hgHBgMAuCtQ GuPAYAAAdwVKYxwYDADgrkBpjAODsYYeNmCeSqNbvqbn+zl95sM5I/O+4jjOysMPI5FNpZMF TgFKYxy5KUYxOt7v4QymQ6Cmx6NoOlfyOjI8deDK4xhR3nX6zh8YA5TGODAYa6wL1Ov5eXOJ ONH+u1O0P3IcB8rbBwzmSqA0xoHBWGNFoGiUx9r2OAJkY1iDWprK+vhF60bM6bFjGIXWcRyA y7sSd1d5u4HBXAmUxjgwGGu0BOr1fj6y4Zwjbj8xATaLUrpamsp6Ny9dSk3hpn02DaPQOo79 RDNcE/jN5d0CDOZKoDTGgcFYoyFQJIy1R+/poYSVBmcr/DCglqZz31bX0qZWQes4DtLTgiHO a8XAYK4ESmMcGIw16gJF4lkTxVxY6ddNuYjX0qzv60znuSKaG95ttI7DbXQtKLd9ov/9tbRF r/NjqbKhvNuAwVwJlMY4MBhr1ASKWhb1biUSVi2YNYMppWnv68oTzmkeL8Wl6+p2ah3HnJeM XMqGUezuK9NtMN3l3Urt/IEzgNIYZ7QhjI73e9QEqi1c5xmMZ13o2wY4syLA0oKJ2bv07nrq 1ex+g+kt71ZgMFcCpTEODMYaFYFywtv8G47O9yjFND37stC3BbnrvcbacRQNpiNuoN9gOsu7 GRjMlUBpjAODsUZFoFbfGSghJpEudv/U0nTsm5hQGfq7llXBXjsONhhlcJTvhq6sLQbTVd7N wGCuBEpjHBiMNeoGs6pbQZyTv1nJBbuUhiis991i/nz2iDalX022dhyxHDJt6MYiMxpd3s3A YK4ESmMcuSFHMTre73HAYD7MOIPJzO8kYDD3B0pjHBiMNWAwMBjQC5TGODAYRSJuTijccVyv Fb9sML7O/TWUdY0tus70tM+QVsur89QJ9frF+6EzDeaqa/JT1/52YDDGkZt0FKPjXYeI2w6x Gir+/77/+effMK/49593abUl/vt//1kvo6Hj6Cqvg4yIrun0HL8qf3zqzt//PLp/lLBKvLb8 r/uW5fhtYDDGGW0Io+Nthm7Ivf0ru7pnaj/r3UvlCfgnWjDX0ttF9no+35Mrd9qqqhmMO38b fvXWJr+27tOyuAoYjHEuMRgR7qf/lc/j4X96OoUnQ/ljP5nfDeVz5I/ntMEU56WV4ya+y+en ynmdpPfr4vFIDKkDJ1q8vPgkCgzmKjYZjPuf/gB17hIbaTDqupJrrnhticGobTqvjutOpmWM sEzz8XqXEOrXhGv5XQwMxjhy4YxiGS8X5XmZL8pwkc7z+wzC3wTzTbGLeGNJGfU8TaFs/DQr eclNT/ME3ah6WxYjqwO5YX35Kb7bVlI9GMxwthqMnDcvpu48DzEYL+xSDjaxeA/4/OYyynUT rq/ECHquOwftE8un93HQqJ/Jtc8r3fJ8T76mqbCv5McbLgUGYxwvnGcajCO5EWQ5XLS1+Q0k T1gdU/VpS5ezNk8ky/6GjCLA29L8eFszBiFx3P+zoszAYIaz3WAc4fxyC2CEwTSvi+zaai2H cq1edw4yMR/D7+/NRx1Pto83vey+qeV3MTAY48jFMYpivPwi5+VxBkN4k0lvpM3octbmiWQ5 u+lrx9CMQVAcWnb/l+5UGMxwdhmMQ661vyMMxtVHct22rq3Wcu91R1CerowTf8mAYrjtbj7G Le0T8oqtq1p+FwODMY5tgwkXf7zZ8os+g/Y/9R0Mp8qW1U3OUNeBetoTQS3GUPuFm/6FX5Fd Rv+vyPJPyvhzHLudErb+iiwIt8SK1wEvZNdWa7nzumPS8qfvlhzZ9f1UO8/fb6vkdzEwGOOc bzDhYub1JP7zsn7RSBenfzJ0y0euVLrQ07upE11O93Qq886wHpXyy00pXQix3ME85nV5HWRp 9Hr37/e0YLwAJkMjGzqOnvLGc7sQ6cp5qq5vkFwL6QOSvrbysszLhWuKy1C47gKJabr95nsm v759nfgYbtLHtsjvemAwxpELZxSj430tfHPmokVUBOqWBuOZnurp2LTBeJLybmaHwYDdQGmM Y9tg6OlpbqqvdpHdiR8xmNf0fLuG6oxxg1mUdzMwmCuBwRjHssH4LgDdHfAtBkNm6esp77qo ClSPMMcui0Y91dI09527TVplqLUIEk4zGN0d1HeddJV3MzCYK4HBGGekIRBj45FoiFjo+W+m bjDVn1czZFqhftgscuMiamla+9I2d047RHPIeDA70Xnzw4h+aV0B48HcHxiMcWAw1qgIlBP+ 60e09PO9hjBkRMsRVA02BSNa3h8YjHFgMNaoCVRbuKi7R7cy6Ck+N4Zamuq+Qagf3D3ppkb+ /vysi/racfg83XlefEJnAxRjtQXTW96twGCuBAZjnLGGMDYeCx/Fc2Ih3y3r6fq4NzWBagsi 1ZU2lJrBlNK01v95uDwpUxb+lti7cnedm9ZxuBjh+pHz7K+BjUbQ1Q3XW96twGCuBAZjnJGG QIyO93vUBYrEtqabNZPQtIxky/oiG96ttI7DbfQtmLjdm06/Zncax4bybgMGcyVQGuPAYKzR ECgS34bAl9+jKGppKuvJCIpdZwU2vc9oHUfRYPpjT9TiCvMtznn/QsBgrgRKYxwYjDVaArXW vRREk0S6+BRfS1NZn4i9SrOgVeYSjePgPJU5kvl1dmWRIcb9XJz6jwm2lncLZ8YGOVAa48Bg rLEiUNS1U9sexDn5O5BcsEtpiNp6EnheX2gRBXa1BmrHEcshU2+LRO9DU71M57VeCBjMlUBp jCM35ChGx/s91gWK/n7DjIY5o9j7s+PicbDBnGgAB8rbBwzmSqA0xoHBWKNPoOhdw6d17DVA rBfHcaLBjCjvOjCYK4HSGAcGYw0nUKEO9VTSLPpu1vPYh7N2Q2OkjMp7Pg597FnX2KLrTE/r hjSyvJpl15ybYDCXAaUxjtwUAABwN6BcxoHBAADuCpTLODAYAMBdgXIZBwYDALgrUC7jwGAA AHcFymUcGAwA4K5AuYwDgwEA3BUol3FgMACAuwLlMg4MBgBwV6BcxoHBAADuCpTLODAYAMBd gXIZBwYDALgrUC7jwGAAAHcFymWcosHIJ9OffrCpx8OPKjjRELpumYa75eF0wzwAAHwCGIxx lgajPpnOnx2fl9lMwmfT5/m+EQcBAGA0MBjjLA3GkQ/6pI2kNg8AABcDgzEODAYAcFdgMMaB wQAA7goMxjhLg3m9n3/9Oj9s7bz8mPQ8+Yt/0Y8hYgEAnwAGYxxvJDhNAID7AeUyDgwGAHBX oFzGgcEAAO4KlAsAAMAJvN//D3xJz4uN7FGwAAAAAElFTkSuQmCC</item> <item item-id="10">iVBORw0KGgoAAAANSUhEUgAAAJoAAAARCAYAAAAliLUMAAAAAXNSR0IArs4c6QAAAARnQU1B AACxjwv8YQUAAAAJcEhZcwAADsMAAA7DAcdvqGQAAALbSURBVGhD7VeBkYQgDLQf66Ef67Ee +/FJAEkgQFCPufthZ/xRSEiyLOF+OScmBmAKbWIIptAmhmAKbWIIngnt2M51Wc/t8N9V7KdZ lnOBxxh8N7uf0qIYD9Y29q8H2kGsVm7Hua0up+5cbsHmuW426qeQ8GBxbKvjXL1PEWXf/joe CC0IR1MAbKi36xInRSkejNMx8o2xOPERfr0xCouo5vQEKQ8WNpbxAyianlpbvp11jOloWrsW hHV2k3Sj3RBSXMfK+XXj6+OEboLl+A4yHlLYmLfrLfl21HEJDRJ1bdKrFBYhJz7OxzGVgNAm 8aV+13voWGR9RLze3EPigW/SwtPTB3lnJGFMe32Hmli8HC1u3HrOhsUKdvCwPEmHfwMCDxw2 3lavsYyar74O0tHchlLO980nTwvxm4Rm+K4IxOyCoOCbiIttYlwTNzkklcxJLR3G6GZLQnN+ Nh64Ym6t32gVbnCO1ubfKU++ZuZv85JjuliXQOlTSFK82i5EjsWuVEXbt1wHB786YSOJoDIh Xyf0idCS79ocFlqag08uKoBWaC2bDCVuMCcvBP8A8VJuFK35HmjWAptr3zpR89XWkfxGiyc3 nliAVzZKF94HCQ3fyYlJbMUiQRDRIetEACSODKqEVuIGc8o3IY2RorxB9zpaO3+yb90o++pi S/8M+K5Fa+KkDRRaIJ1d29FW3kzIj6wt/XZh6xD7FgRuQo4X2dYG54W6wn9xAO2Vo4HMQwJ2 ADtR8b13dSKAuES9SFpyuqyNuU5e7aTARkY/s5MTm61B56i4wpg9PZetnysKCez4RrPu6EUD DyfK5buK7AncAGiO1I/E4BzBOkpxa1DgAQUo5aWAzldfhyC038KbnYGC/3R4GU+6SwGf4qGK jjp+Xmi2Wv3Vp8Sxb6dtvJ8Bdr/aDXAX7/NQRWcd7wiNXh3ZM6L4wpX2dQAxfDLPUTz01/EP OtrE9+M8/wAJfSr4Pn8ongAAAABJRU5ErkJggg==</item> <item item-id="11" content-encoding="gzip">H4sIAAAAAAAA/+xdB1wUx/efvTvgjnoUEcRy4Kmg1KOK0sVGUwRLLIhwFKUoHIpRlCgm9qix RU2MGhR7iyj2FhNQIyrqzxiJWBKNJrGgxiTKf2Z2b+9ud+8O/JHf7//7yDtmb/bN+76Z9+bt 7MyWwxQAQMA0CCZjnOfBrUCRJ5c7AEQymITZKXFjxspTFJgD4mHqCUGhfNnaEwAUC2SjnsAv A5nZeFxuSO0byXgWAKQaAsDnhQEvqIeUNxTJMFyIqkTViSIGD4qc0E8hzyawAlOkRJ1hBpMJ FhXKJ8TL0zNzcwxwgQ9Cp+amkDwB5nWnzTDMzxgfnltItjoaJiPIiKftiEH6YMqCsuthRdl8 ABzhfiFPZacY8nmAZ4qdZEXXFKZQ5GWOKVDIyfYFwmQB1Mks0Elj31zpHAvSOeZi0jkWtHMs SedYWJHOsUTOsZYhtcWWGEkoddlg40yh08ILUlMnIzeRBUjOCLJVHNSohOUAuMHvyRBVAJU8 g/mGBmgagKJxWfKIrEx5jgJjYGkUoawJb2FMVF+wvLVud5s6wKBgwAdvGkTAUI1HqLdTDHBD 0f6bBlQjSQ0t9D9Fr2F6o5Za6N2ieJALPwogAZEgB37ngcnMoUAn2QID+phHY8Fi4Es4Wd6w /KQYmA0+Y9BGXdaznVtX+fOrBByJQTHFi4C1o3rleJvfpLoRWQEeoW5PY3EJTa5JO71N/c1J /079yvG7hd5NgjMsMBjOA7qRUy44JUCTJqFadCDiwRwBzw8w1t40UBxEVlgG8gzDgS+cKPWH cx1vtG+AZj2BAG0bUHz+I0kt/jnL9PG0Yf+Jdja1/D/VVqIYdXI0oZzd4R6f3zIvfNcJzQvb Un3YDn6j4QH1uRE1OogAuaQ0AeSKDi3izAG5JoEhgFcraHSwBmhJA0ArgOYKALSGyQ4me5jQ 5ACtQ52oelDqAPMSQC7VgmDqCJMUpk4wdYapC0zOMLnA1BWm9jC5AnIN5A6TB0yeMME1F17d egNyHekLkx9M/jAFAHIdGQg0z33BcD8EplCYwmAKB2h+AkAv8O6dI5tzXojGA4mQPGMcJ4t7 q8t+4e5OzwsBn+QRIA5kwVnh25IxNS9E6tB3Y3E9qe8h0Po8MA6MwX4Y1+T60bwUjYGCJtSP ZI8PJfMEnhlng/HQD2PA2Lepv8nzQtRepaVvqH5D36hdyuMf7TOP/3ft2HgXiFBO8ShCY6yA OjaPk1+9kcAIPOpHZo+Rp6Zm5qRLvL1l5LwCRgXfmIx95rGPxviYzJS83PzcNIUksjBFniWR eXp6S4bk5o3Lz5DLFTjUwjPT0gJI9UjEfRAqcQ8A9d33TOCIXs15DZqmGmuaQMf4rVlrn76K yxBvXSwE3brsve4JedsAeW5D5aGAPBb7AvJcNxqQ5zJ0ZRGd6+D0CJ/vVgLy/PYlIJ11V0Ce j8QwpWTkZea75xdkZWVOTM4h+QjbK3liZqokOhNdwlPKMnyB6y/ef+jQ7p5VBMqDh6aq8VFp rZ55nS77eVfOX1nj7iD+ZAW03/XVDmR/DSCPaVQ+AOWFsGWGBuC9uPNGJ6AeQ+iIOvi9S3AC a72N+348wtAmSf4DFI7bkEygNhyHjQ0i0NpkDeRaglrYW4vmYT+L7HErrfDWGm93YsxhvA2C JVHwI7WrtepO+WUoLxTLLcBbJ7w1xyuf/RjzPeZ4wV77AcfFIoLsdiMiAiTDc1UmHKfz4Pb/ m4RIr4SNHgkCzqAO83RLiPRI8ODMT187LHVKuMLzaYDOWgR6JVBL9UmgNY6+lvroleip16ch OtuRwWFLNlWeTOsQ6rXFWEc73NV1QCkLIgHys+GsKx/O+2Lh9yT4HY/nIclwFkgi6JhrNILX ZARZB69RiPaCtnB2AtcVTlKnjq4dO3omufQY4azcGeHSXuAITydtNcqHx8tTR2oKOcHhv51K yN1TUw/cR1JdYMOcmFIMbZSoP1yfwBVIEuJ3lShrpnZHOFMVKxlObk64NDQJQt3h8sYFQdVx miAGIgSeoAM1KyPbplkfbppalSEhKhV+oBtaNdGVKvEsMAtpB8+A8DzotIG0v8cIN2W2vaAd KEXrPbqM9JWaQHuwES0GlQxYiRoe7rUXdASb0KlSXYKhBYv5gjK08ktCXKXf3Ehdql2qFPkO 7YQmubUXuILNaFmZ5KaOUocw5IPAFrSEVK8I+UqzLpKjqg76i1bgA7aidSpdoRLNgLJwdnCW Yq0KPlSfVOXn7djPUoafpSo/78B+lmr4Warh553Yz1K2n6Uaft5F+Vmq6Weppp+lTD8Hgd2U 36Qsv0lZfpOy/SYEe9DyEMrcwtcUAHjeIFGb2xyXIL6Bkl/fwm8OPiIC6PDzVxRbsFYLf7sW /hYt/B1a+Ku18Hdq4W/Twv9MC39eE9ujTf9ezDdk8T/Xwv9MC3+eFv6XWvi7tfC/0sI/qoU/ Vwu/opnasw/zjVh8Mk6ESv5SS8sVJitMgGA55otoflrasQ7HOgDBfsr/W0n+H5QeOj43a+Hv 1sLfxck3BtzHhQmr/WQ8myr5NXgh1UEpb6bJN1HyzVV8uEEXUBl8Rr0WLP+Q8S9W6RkN8MVV Ut6S1c6tmnG7xtLS1sQW6lmF+VZq+kk/L6fkRZz+sdbSThtVe5LhnJr2Qyst8ujKMB5nhJp8 O8yHrQqwtAyVhEo05bn4e0h+Ty3ydlz1OrH02GK+S6Pr5WrnJzwr2C+w52WenSRukrCUFHmO wmuJ0BMsoa0EwEDQvsEMzhU9QSdovxtMYSAFfsh74l5YBmmyZGqSsTU56dAkozVZMTV5szV1 1qHJm9ZkzdTkw9bUVYcmH1qTDVOTL1uTuw5NvrSmVkxNfmxNMh2a/GhNtkiTj+6+6wA1+ejt u9ZMTRx911GHJlXf2TE1cfRdFx2aVH1nz9TE0XfddGhS9V0bpiaOvvPQoUnVdw5MTRx9561D k6rv2iJNfrr7TgI1+entu3ZMTRx9J9WhSdV37ZmaOPrOWYcmVd91YGri6DtXHZpUfSdhauLo O08dmlR958jUxNF3Pjo0KfvOFKDFOKB7TcrQ0a7BiLOnTEFHFU7GxjkycDIaJ1XhvNm4Tgyc N43rpML5sHEuDJwPjeuswvmycW4MnC+N66LC+bFxXgyc0p9C4IzWTeHJqUuEbTUxhEMDH4TD E3QqJSuGZzw4NYlIzkopyEpWZObmLBG6amJ4tg0mgLyWlAIK4DYZ1pWJn+MidViArmjWFJEh TxkniZBnZS0RdmWoaN1gDFVkwIamgHEwDCJgLgt+SAUC0K2Y37BEKNFAEQb8BgPqthi69KOU dS02hLLODFnDBpGarAQMh0E3ksa4FQsgpjMDI2gQQkwByIMf5MIU6qYnQrgXG0GEOwNh1GDK QmjW1Qou9cXoFsb4rOScZEVu3mRJgrxQsUTox3CJb4MYRIJCMB57NAd7NRffd5WABKi8ECgo lSKoXgBAn9xc2KHtGR3apkEA+uCblsouNYcHCJw895Un4zs0XkxfGfDF0Fd9YRUoDDJh1emw Si8aLVNHy9hoSw60jEZ7q6O92WgrDrQ3jfZRR/uw0dYcaOVhZgwPHDjJ7ZczvkDBjCUDng2M pX4QMR72ntKxYnjIwOCPzswZJ0+lIpcZ/HYw+KNxXeNgvams2DUF/uggjZUXKPKSs1gHKdEW HqToImYBvqmerBbzoBjACHPSjDACNBhCeRQI2WrSIhCAQiA2VyFnhQDPGIZALL57L6fETUB3 tA6LK1BgXzgxAK1gHXG4RereEIDAYoMGpgWEgQG0YABUnUcPNEp/90D+TshUZMlZ/uZbQH+j C7kK+rY+QvTEiFwF8hQTYY8RyAyV3ZYgCC2whiTn5aCIII8kd4Y5JvCgHAJBebBxyqBQP4IW CofCpEIsAujegyWUSQZjcPMGQcnJOBeDOzkTuiUb+nAAzE3ETVJJoGBIh0MZOg/5gdH4XtEs uHo7jh5TgV7Hty29VgntwCp1N1LfSHqDUAwT0KD5sHvR01gnCCFMAPj+wgN/Q71oFUnde+8j CZJ4unv6+vrB8hjYvcFBEh93T2Mg5IFYSU9c6OmN1jsEnH5aIzbi+KEiZbnMRwTLjWE5DwgJ EOFFAHsqK1Nlvels1BiUbYALCCH4woG8pWnVFoBp8DtFaAuTygRb2sTlwiGmy9VKzObzwIAo vgBdHEBsR/Cg1uIYekahLY+8pTo8IjdHAc9ySQmTx8vzR7oXZmdtW3w29pSnOPJl379n3nPr v2ZPqLDTgxnfLPxm/dTj334qta38155NiX+9jL6UEF4msc1yve798vMed/KOdDDad2rlmk39 dz4N7yZ96NBnZOmP/nHXtw+e80Ebu57JpRYr6w8ePezs/1Fxvzmr4kun/DQ+PXpP0MJFeR0W fXnpzwDeWd+JnYtfF5ufLxj4g93DOYsD7lRGXLvHL9/VbmjQb/derZTeXvTVwRC/2G39I4Qz 9x5fUvOo7FXvSttw96qKLs/dv+w2Z935YScTXtnvuj9K7nvRt6xW8tRkvtWpXaZzki6kS+zd fjrW4/M5j25cHZZ1+ObCPQun+o06F3uiwWb085D71pfPTR8+nYdu9vIZ/iq9uunn4zCHuh5d iEjKk2fle7ijbcnHF8ae8jT96PdZR2ZeLBp46ZRdp4kepYsiPDYUgTrn6RlODjccHt6I+8bQ +JCw5MvfX24OerNj3qu6pT9LbFdtMTx1OyLkbEbdxKBj02dUzvpyUyfh8MLxH26YcmNf0uEB Fzf0PO/lUNq33HOZlcXs63GH43eEp16sFF/qH3nDZ4x0+qbFE5KudVj5uf0tv+jLz23jr/mP 3vFxWWXD3lOe5z6POzF9p+u9SEGO/9LozLtj1pV53Bl0ZFGZfEtN++p9B15dfU1wGTpu8nLb mTA3FwUHTIoMebbcQ20bA8+q6fI8FCGm52KMT0nEoXVF6yYtuu6fcsg5csyeszsOvQARa9qE ffPFpbU3rt27M9P/ux9trqyOMhvmusbIbK78vPvs/Y+num5yKPu+b9uvXbPqvmn104NCu8qv Flj/2O/b/IFFHa8smrV9303J1X3drjj+7npzVIV0bNC8PkPuX37pcjvyYbfOxrwA7sbHXsq+ eAEemLs6kEcDq/FeqNmPhkXlOviLj7a+P33ooyO7Ux9a2i/mP2zVZXdWx/j4u3371bi7/ZYX Fj9R0W3JIA8D4y8jPQzef7jOuc0XRJv6Sx1SJGGr38w2r7jk7jLwCb/3YttyEBFV5P13gHcP 7x5Tfv5t7+z3u6w0OXn7YNLhxMdBbS2uzz4ddnP6D79PnXjjZUmvJ8KBtncOhpw6eezQswdd JlWXm04oCVr08dd+W/5at7TyxZkP7U7KrPYPnZHyR/a5whLpiKejU05fdLm/4P6ZtHUDrs8W zyny6G1ZFtT240rxlKLSSz8Oc84ddGB+6QCTiKop/X3LpT4TfVy6lqyc0/lerWh9QYcX9rsv B0/rXPSxk2PdRweTqqe/OfPdZ2ZfBbVen7dgm+O1i9PzKyqOZ+zZ/PLuCcmNrxK6ruh66NNp Zl/ktbq2o7zbr/03xvGrxwu7xFT8K3Dr6vOX2o4rvrTT/Ob2seO2ZtSZvR7ebc2ks7+k1Pk6 X0l678SkwJhd62dd+8ImadSJFQ77ep+9ujPM5eieGTttJw4v3VKaNDO8/+1K44MDdmT5tt50 XpLS++Wax+9V1GzO+W7Zz86zP3Q9WGObYnu2YLftupQzPcCA0LnSOUHdox7bmTnOXT17CdGl NlgULjws+Dr6eF7y3mqXrBPTn7s8yP1+Q4ZDx4j3nvA6j5H3e/Lk9KJPel19bfTFFX9J7o+H u0958+ejV7npHqPWBDXIj+4fLK/8dV2A573ahj+e//jj9LrXzx9a/J407ZOcI/Nbd35z80LS 0b9ef2yx+SPrnzcW/vXr1kk7k468/m1ryPT3H1QfPXvxeMnLfiWzJhXHHenjOoMf+Mcd4tia XiG9Ti8Jdbw/sSznbDWv/TlxQV2bf/nVWZsPO2Nw2D+o/MCL8OBlp3c/O+W5p3jkmYyZEzYR 7bccMTV5uWnCrdo1cTE/dCyJHTHFf2BW9wNBMZIjViuq0ma7repj87WVQcCZS4OO7RadWXg5 qNPpPeNWmHa3znI9sun0OMltn35rTbeFVs160Vcw7dMK4YytbjcUawvNeo/clFNn7SDab7De /GlRtJt3bcSgOU4rqoLnlmU+LpJGtK6snW8RM2J438eKYpdn33d0LYn6adGpyWabQkpM70yc suI7J4fKTp8eUPzW8Ux06ryYVY5zrVqX97ldfbq2tbVw4N12Xg9mTPq06KOycY/5c68d/Et0 YvmhC3GCjx0rVi19CgYei644teKl597b+/03pJSMHJa2os/giTfvnbZvtyBz9KwXwWdsPltv eab2zl/mhmbLh/pd6BcidNz6KHnI6KDQidu2PLQzyfgkIWnvKqeXc3aFl3/EL/8wblL50sI0 54XipE2vwOGc7w+bJX73aX+LB+PH8CyEX00Xe8RuaGtcnSx4+d72Po57xq44aPtb4WcTzk5v XfHNraM9yzNG3DoqsJ+aad/30cZzRtmX+9R8L7FYGTzD8NSynLDTedPd1/+yxXZ14L0zL2JW HyLadNz645y+U3Oe7a15sbThs/JvJviPiDt1Z3BW6bao8sCH8VW18TP3mr/skDXuvYw2HZLL pFu7P9y4teLB2L8biobs/W3U0QfyqwVt/Y/Mtwg6E+PhvXbbiDiPT/Z7VF8vy+wTeO+i99qM X79Nj3b+tdL+67/C44oEPS/OD9xVdrf+gHV6x+PSkp1bzp0wtHW/1fds4ZrKC3NMpzj2H+2T UL9sSei5RKOTUSuL5yweNfGXwYWBCw5mLY0NnBfpeyW629ZQWZLH0r0FK+MrbUZu/unyoegj aQ73XR7OKF5yxFSU4r369PKZvQp2l83/Mv3gaB8jUdGecckD83cd2F7jMWLfSV6ZfNQHfXIs 2tc8nFYhcJIITgVkXOhTFbd5a+vaK98djo3b6b2xFVE9xsNJ8lIRM2HklJ4FB31q3G9lziux zPETZdvfvDVH3L7k54ubB3uE39lzdMc99333XQbdfy35Kq/NlRsdxkxITJr5Q17OF7s/dcl4 9NnV11WD7cPTZi85GPLhHK+pC6xmt1v3+UGx2a19Zwc8rf/wWP+0fgcWuUlP1twKfPDldYmT Vf7HS8p+23onHSr4znHV8AnWVif7RO0wzLyX0tEodv9n879J6bl0440FreQP6q1kU1d1W3Ns 7JOtM5dJV884NKXufo1Dtcv0EsnpqivrZbdmCwsnDIje3t3pcWfXqNTJf7u12jj5e9+kyAd2 /a9ZxoT77HROk8XVBS5LV9QnpvHvjJ2W5lmWvGSyY1vBluOreu/bkjnYN9583NbfXoVX5fW+ dG7cxmWJCVcU6V7jPoq0H7rn3pW5h0+MTR7zbWbarLhBL/Oqtrvl3YxfuyhR5FmYFtLnypHQ MM+ye6uH1djcueKzLe/F1Cs72s3jfx7xq1PkyW//XDbr+06H5L4nK9q5jtr8FDqs5uSlwotD xkY9HPLTT8Oz/QI+vHtxhvuk/qXVO0quu/epFj9XxC0pNXM7+Azdl2CfAs0uLlpbDnMOBPns tvopkJy0MM/i1CQmxvikp03JyxmThLm5lw+KF3e+Obt6ew2/5K6vmV+IdOCjX812uArdP0o+ +mnmoRWfVVqnyGq9Mra0EQY+WDZh1YnsA48Whsbbxs653iN11+gZC3P9f22VvjjKOaazNN7Z 3WtlnnmX/p+sqZ6b8Kp4R8CGjwffddqwMezbQ9V9XxYUffFkNTH1a+mRMeIpV4D98gGrGva+ DmgzJ92jg+3INwPD8q/PMnBef+bcrY6rt0QLqoYfPHj6R9p0gucGtM9qNYljjstUwJzmqciT 0Jj0MYHMaZOK7Hm6J1FMTcw5jIqucmny4tLBDAIVXRc1OiQGRBngl04M4GckVFRjjNdJcO00 n7F2QgXk84tijecXzfDTfKZwmwoscN4Sr7/EsJl/b35yKWbMgJAkzO+K+d3wdgbmFKtuS4FO aLEOXIkPYMkJgfLthplYugRvO0PpNEw/hXRRyzvTWu6HuKjlY4BEgl7TR8945cO1JrlmjcF3 KFCSwDI5fmqLfArKGe5HggjgDcsiQC/8tgJcUwqA4Acg7WJx7QM+eiJvlYmPMBW23QgMJR+l Any4DaMukDQvUQ+ZaaVBkRG9/oFq1WpvDK+F3m1qiYkW0kZiOte8UcLXL/L/gArxG3Rh1PPF WfAcOwhf88zG11En40vlafRlaPX7PdzkjM65gHxvCL0D0pg2IE/9QOUN4FktF99fyqYuMjet PQFv8bsA6IkkAdX5POr9swH4xk4+PM964vcKG0t2b/H+VTeYRnQg8//++29N/10A9fd10Wwe vYqGnnZBV83R7HMqII+SEkBOZ9F7MGhKuBSQ78OsAeQF4Z1A830YNEPqLxkgiZLn5EyWDFBM lkQr0M0p8sgQ0zNbbd/txeQxifqHvJoOTMVkFe0pMfrNoXyslexEfe/I6En43UEBpQ3tK+c3 CzoDUNsOtlwK8JsPgD+BjyRNcSlC8AkhjnwTDEE5U14lOEGgnIjmETxUE8oJCDOKx8P3D/jY NKSpC0G2g7mniSd16pdAHrQVVOI7CrrlW+h/mVL/2w1oof91QiNEcXFxc6pUzS7eluCwOn/+ /GZsUgv9j9O7s6LrCW4b/bfb0Fgie4UcPha9O13UQrpI0ATZRLzkUz4t9N+fzniCQEbSRcqI R+3WdVG0qYQm5uhSroz1aRo1pSf+GxQN+1yBH1/Leyt8y4jTTET/7C2RCtCdhFSg+uMkgt7g DKGWb2SVBCKc49G5ZqG3V0X9LojmF8rkCn8xRklN1sBQgNmk5Sgn9Bm8vCUiW6iFWqiFWqiF WqiFWugfo2aZa+q7/9XOHoA2HZT3vxZYoDuO5INm2u5/1YOJhP77WkjHXzwxIC914V+mAgSP 5zRocj76HxbtzCCnznB93z+nA/xyHtLtWLMyEmlxIwDgusOGytB9NfTtTpAtRHfc0PNXf6qt z0kdBK77bx6gfneZ5PIafXftGf4/HI2/G/c28mh18U/Lkz3xhLojTF/FEydkZsvzJbHySZL4 3Oxk9jMApL/4LDzRJLyA1qNvn6znxVu204Chl9kPylLt/gqG/nKh/MvWp7mPfhMWvb0lM0Y/ 14WaGgGPG6UkWSIDvXCJFzDQaJM2nbr2lXWlaK0L/1sYIGvGuuZrrYtcBns3Y11fYY1RwIRV 1zFcMqYZ66rVatf9Zu8vI0JbXZZEc/eXp9a6Aonm7q+hhLb+SiF091fTj0v1cQ8dd6a4pjBg jp+u8HSXQTkBTCKKH4x70VONk4453SFHiZ1LYf0orDHF30f+NqinkZrsD1rqMcGW+qpJuhOk pC9D6zD8LIiXr0prIt16Hw2tiazWJ1KtD1DDcrc+kaP1iVpan8hqfaKW1idytD6Tbr1SVskP oPheGrVlUjb4q0ly25DJYUMmbYMPQytpg4+aJLcNmRw2FNE2+GnYUKTFhiKWDUVabCjisKFI iw1FLBuKtNhQxGHDYtqGAA0bFmuxYTHLhsVabFjMYcNi2gZ/hlYTanxRSXLbsJjDhlLKBi93 Tw0bSmkbND1WStngqybJtEEpWcGS5LaglGVBqRYLSjksqKAt0DwaKrRYUMGyoEKLBRUsCyoo C7wYPVtBWSBTk+S2oILDgvOUBTJGH5ynLdD013nKAm81SW4LzrMsOE9bwJQkLfBUk+S24LyG BWLMq4Pl6ClV8s15IVwRCDQsqaMs8WL0RR1liZeaJLcldSxL6mhLujMkmZbUabGkTsMS7vlx 08+XzqAatAJuWvRx76vms63BSGxnLD2P4OO3YlBJJpZR/SKBAKh7WmXDv3/OtwEKjXO+LW4B H6zCnlP9YIIxboN6C5rTjwqiFbjIqQ+1SemVe9gr9C8yaHiD9I9Sg9LD7QhtHnYh1Dws82m0 hwU6rRToXPW4wtpVnibb6AgscBTEALO31qw+b3tbvHIPreJramqA0m5DShrxSA0op34dAO2T skY0X7mkJPlCfHSGihzBY6AkUkJZo7q0SOsVicdqNWhijLCkDa4Z5ax56H97aqudgPEGaH8Z UrpFnJZy1atusW4LFUTj5Fwbqa+62T1mQ3vMRo/HbP4jHktspNy0RsptaqTcq0bKOTWyR6OI 5u4pZ3imIXvKWWdP9SWc6XOSEhtM93Kwnl4OpntZiY2nsfF6sPEsbBqNTdODTWNh36ex7+vB vs/CLqSxC/VgF7Kw62nsej3Y9SxsOY0t14MtZ2GraGyVHmwVC1tLY2v1YGtZWGUsWvOeAe0j 9jNqxNbEtoIjlxLrqhWL6mylNsaRWBd4rCuxiVqxyFYXtVFBiZ1GY6fpwU5jYTfR2E16sJtY 9lbT2Go99laz6n1FY1/pqfcVC+tEKLFOWvuXxKpGKCU2isZG6cFGMbBP6bh6qieunrLiCnGV 9Sq0YhGOoMv/vTMLWS+KYrLeeqA9nlGtqnhXYV1prPZ4JrHMeH5Gx3O9jngmscx4fkbHc72O eCaxzHh+RsdzvY54JrHMeH5Gx3O9jngmscx4fkbHc72OeCaxzHh+RsdzvY54JrHMeH5Gx3O9 jngmscx4fkbHZL2OmCSxCgYWzSiVc8uJOrGquadqlqXE2ujB2rCwzjTWWQ/WmYUNprHBerDB LGw8jY3Xg41nYdNobJoebBoL+z6NfV8P9n0WdiGNXagHu5CFXU9j1+vBrmdhy2lsuR5sOQtb RWOr9GCrWNhaGlurB1vLwj6lsU/1YJEk92yW/Na94lSO4eRorv0OKxfFhsX2Q9/K8cOYarsj oRw/nAjl+GDC2XZHulyFjaKxUXqwUSysgsYq9GAVDCzX+MGNVY0fSqwrjXXVg3VlYUNpbKge bCgLm0BjE/RgE1jYLBqbpQebxcIW09hiPdhiFnYpjV2qB7uUhS2jsWV6sGUs7GEae1gP9jAL W01jq/Vgq1nYuzT2rh7sXRb2Dxr7hx7sHyysKaHEmhK6sUhSEyuhsRI9WCTJNfaY6hx7jHSM PY5E08YeFSl/GWAAwP8VGbcrAZD/7XKuFi0t1ELvNjXnGyncVMq71Uo9NYdOAuTDz1iAnveh ybk5NLdQC7VQ89E64ARE+F079OGBobyhPG9Ml0OU3wRYI+wMk3YtPt7KXCL+76tF1G/T9DMM xs9noH2kH+3zqX0erPeGgarcGA4bUlEwqYZnjr/IH7FE91KFPDGVX4rnMqMJC8wjMM+VHCUp Ho+Dx8e8/ho8AYecAQfPkINnxMETcvBEHDxjDp4JB8+Ug2fGwTPn4Flw8MQcPEsOnhWDdxT9 czdIvTg+IvAaypJP9CE6in/+n4B7zA8pifqmN5YneIb4ly5DKD4PyvCxBhQbfAplQJUagkjc X2SpEdxDHxHcN8ao3lAPgWX5sDwU9yO5x4d7hvSeAO4Z0XsGcE9I7xlq4Iw0cEINnIjCHQHh uFVhsG6fUHIbiv2Atk4wT4BYzJHiPFlqg7e3QtDWPVSEtRhQWnqFkluVFkkTtBhiLYgbRpUR GANAW5YWsg4xhxYjqi2xoWEU5m20CCktCaHkVoeW4oE4L+TQIqIsehxCblV12qhpsdGpBf93 IKzljxByq02LAeDDkccYR8KqTxE9CTmC/2GFEe4LwNFCE0o3CA2jJNRbotFCkKrWryotKKZM sRYejqmeeLQMo/xKFCdjFGm7mrbj6ZzajpL/HQ22jP0hS811llroLBXrLLXUWWqltfQa7KNa eAhkEO1hLgFMg8ez6jMCpli4OlV+gnlWoNyQoCwHWCsA84RimIAahYN20Bq+AO+gJSty8j1Y gQEebnjwm7xgJKIAIsw1xN/kwvZ3fEjB5SpIF7aGSaUcDl34nZVe5PmphZqBWslQ9BWTXiaA rYwHd1NhD/B5YegfRLWWrT0Byw3tZD1ht4W2Rq63JzGtSUwbtRIH9RK4/38AAAD//wMAeLal lZ6YAAA=</item> <item item-id="12">iVBORw0KGgoAAAANSUhEUgAAAZoAAAEBCAYAAABBp2PjAAAAAXNSR0IArs4c6QAAAARnQU1B AACxjwv8YQUAAAAJcEhZcwAADsMAAA7DAcdvqGQAACwSSURBVHhe7Z0BduuoEkT/ft56vJ+s J+vJfvJpUNsIIRm6Cxkydc9RZl4sO9fVDUhKovzvlxBCCBkIFxpCCCFD4UJDCCFkKFxoCCGE DOV0ofl+/O/3f4/v7V9Hfr7+XT5OCCGECCcLzffv17+wkPzvEf7vSFxk/ne9EBFCCCFCdaH5 +foKC8z37yMsJmdrCc9oCCGEtFBZaH5+v77SAhIvn/37Cp858n6huV6oCCGE/Dc4LjQ/X7/b OhP//9///v1+VVaa9jOasHD9CwuWXGorN65ChBDy5zksNPEsplgQ/lVWGl46I4QQ0kKx0Hz/ fhWLSlxQKpfPeEZDCCGkhd1C8/P1qFwmq3+vhWc0hBBCWtgWmvysI/+R5uJsRM9svh+vz50u NvxhAEIIIbUfBpiA5yLGjRs3btyW3uKcHj9OhsoRQghZFy40hBBChsKFhhBCyFC40BBCCBkK FxpCCCFD4UJDyJP0o/jSd3GTn8nPb8UEIftVgZP7Byau94u/v6aexeNXj0XiLaXk8fptpQhB I70Y/xs/TobKETKcbfLd3WZp+z2x2q2XrMitnfT1rn7Z+Xq/sCCeLlJXj+kixAWG3AsXGkLC tBzPHmqTfliAHrBZWc6Y8km+/LfyZr+wAJ7+AvSbx87+thQhI+FCQ8h25nI6QZ9Qu/Hsc6u9 mHyd3dlGWuAOu17ul11SOywa7x97PNJ7la33/RJiRfot/jd+nAyVI2Qkd11Oil+nsoCUl+Za 90sLXd378Nh2NvP4TqsLL6GRO+FCQ/7z1Cfd/OwgbIDDf/RCI8R9T9zyx46vKZfjeFZD7oEL DSEXl87imcHJbPyZS2clYcHY7Zvzeqxn8SIEjYyJ+N/4cTJUjpCxpKP7/UScuDpj6Cb+ZFv+ vZPim/xK636R8NipX/bYdunstefV4kUIFi40hAjbWU252EAXmoCcBelZxNVrt+93/n2W/WNp YXm+zuGsiZBxcKEh5Ml2ZlNs2KP+bcKX165cynp97mS/5y9bpm3ndvVYJH9/5U+lETIO6bn4 3/hxMlSOEELIunChIYQQMhQuNIQQQobChYYQQshQpl9ouHHjxo3b+luc0+PHyVC5VVjNl/xd 2ItkJrjQAOHgJrPAXiQzwYUGCAc3mQX2IpkJLjRAOLjJLLAXyUxwoQHCwU1mgb1IZoILDZA/ M7izW5mUd/fd3bEYe2+WC85u21Ljat+Lx/Lbt9z2vsYh72MMN9RCedbk/H5ucP5q7+u9/C5f Jz1/xFuTrxv/Gz9Ohsqtwmq+70gD63hPLLnJ4+O7c+RLoxs7uPUGk8LVvuePfWe32k/3Axsx 2O5kVC+Or0Uifs66wDh6TRG/P9P7sng+n7fd767yOilzLjTT87cWmu/fr6+vyqQrRz3vjqwy 9AjR3L0yMPIJp/x3ztW+F4/9/OzejwzYEYPtTsb04lW+JVf7vnmdePRtuOmnu9eUv9X7P9/f O+e4oJTvI7g+vsL75hnN/Pypheb76zf0XWrKvPNiQ1Y7fY8OsqKh05HiyVbrcJl0dq9xcXp/ tW/r6ziOPmdC8oRzSy22/3+Efba+eFsOVK8pf633S2Tf3QNh34c89+I5TuQ9xv/Gj5Ohcquw mu8VP+GILvZbHDSvI6Wfr8fJEdXGySCzcjz6SoNBLxHkXO3b8jrPiWDESLuZEb14Sy1kEgxn M49wFB4fkX3PjuLBvab8td4vKc/YX3+3KD2HC83k/J2FJjScHNLp/z8bNvx/PPI5J00MuGZF Dbbm19kmi9rrr8SqC83xMbkEVO+nuC+w1xLB5Y/1/g7p71wwLOyvf6bnYPNMaD9yoQGwmu8p oRmfY03Q0/Lw+aZLBwE9Oyib9mOXDzpe5zho10PyhHNDLXomVwXWa8Jf7P0n8rn9977OnK7y tiCvGf8bP06Gyq3Car5nyKWDfZ9tR5WPN5cOKqRGPrn00YIcge2+MXzxDdGrfXteRwbt2US0 CEN68Y5aSPa7xy4m1wJ3rwX+ZO9vXP3Z70R71r1woQHyNxaa0GyVSwRx0OyOmHpIDWydvOVr 6xFWPOK9eJ2rfdteZ9xgu5NRvTi+FkWvHI7U3+Hptb/b+/Lv3VNDrseXGtf7XGiALL/QxKPJ MChkKweWHDFtTXw/22A9eG2fr32u9h7OHsvfd9hGDLS7kfcxhsG1iKSziPjY7ih9IH+49+NC qe/tudVyTc/nQmPi1bRXzfIqhr2xMb6E+GEvkpnQfvzDC42wLTYnS3U8zQyPe49aOLjJLLAX yUz8Nxaa76/fx7+wmBxO0QNyWvx4/OY/L2+Fg5vMAnuRzMR/YqGJv4AVr8GWl8XCmc4jPCZn NLVFqBMObjIL7EUyE/+BheYn/QJW/PG/8sf90sKT/7SGB/Hlxo0bN27HLc6R8eNkqJyLsMCk X8Da/1y53E4ifctm/3kPEN/B0BHD7I7MEAMdMajjlKaIAJ/3LYoLyvaje2Hxef6Wb/WSmg02 JQY6+mGGGOiIQR2nNPUHKJfN9Hsv6WfE/4V/P7KfPos/1gz6wXE2JQY6+mGGGOiIQR2nNHUH mJ+5BOKikt/rJ37fBvcLSmxKDHT0wwwx0BGDOk5pag8w+w3ZsOk3+vPbfJe/LYv6YYDZoSOG 2R2ZIQY6YlDHKU1XCDCHTYmBjn6YIQY6YlDHKU1XCDAH4bs/00o/Dac/ho2AjhgsjuVZdLpk uz/7nun7hawzexGFvF78b/w4GSq3Cj7f7TY51ZvkpeZEQMftU07MjpWfcpRbICEu3eawztun nLAXMaijJ81h+Ip8P3bfrfl2Dfni7Z+Q7YCO2z+cmB2LwT16YPfDOuewFzGoozXNodiL/BnM vttPv40qcg4dMZgds8F9x8DuhnXewV7EoI5G07GYA/wQvoKP+TsQJXTE4HN8/D4eYych1hnD 33cc34uCOhpNx2IO8ENYfeVoYvampOMeq6NOQP/kbuLy30ED/C9nSMc9Vse7elFQR6PpWMwB fghvwd835XbdN7uu2st4x+0boGGzNu5wx+2yxuccX5crTh3Cfp6BPzxD9uI17MUd6mg0HYs5 wA9h973+xqEU+tWwsu8HBnej4/7ecrafrBme48/P9nhwPNv3DWbHbHAL9QGeJkjP4GYvSrbs xUtu6kVBHa1pDsVe5M/g8tUjm7LZpBleIzvwqcEdaHZMfD/uHtyBHsewb7qzdz9mx2JwR+Ln gnPuFz4X78snnzecNbAX97AXK8S+G9+Lgjo60hyHq8gfwO+bjh5ioXU7DJoPDu5Ii6MQ9qt+ /j13OOrRW939PRbH+i/JHT8fJ6ZsEoiunZ7yOj7Yi8Idjn+9FwV5rfjf+HEyVG4V7vH99OBu 43XZop/76i6TgC3L4Y7xKHI7DpYj487BzV58wV504uxFQR3vSrOL+4qM4R7f+Qe3HPWkxvz+ /TJcr7iv7iHLR3FZo5HhjtngfuXZDnsxwV4E4OxFQR3vSrOL+4qM4Q7f56lted23kdGOZ6fk PdznaL8NyGhHGdyaoedSxUjYi37+C70oqOP4rjQwPEAwK/jSEcPsjswQAx0xqOOUpisEmMOm xEBHP8wQAx0xqOOUpiLHjRs3btzW3+KcHj9Ohsqtwgq+dMQwuyMzxEBHDOo4pekKAeawKTHQ 0Q8zxEBHDOo4pekKAeawKTHQ0Q8zxEBHDOo4pekKAeawKTHQ0Q8zxEBHDOo4pekKAeawKTHQ 0Q8zxEBHDOo4pakvQPmt5e0nHt79Qln+C0nGXz4TfL4lHf4dQB31poFxs/+GeInN0ZDX07// l+XcOcavXfu6mLoPzxAwZmyO58T7cDmdSmyOfTX0etscM057EZepOmIrDsIToPzGbX7bhNPf aN3du2e7AZ7zt18RNPt3gnOUrF7NGR0/OLh780oD6EO/jf2cpI9fH1X3oRmCxgyuF4XgAeq/ nPG96Pce1YvITNURWXEY9gD3k+Dx3y9+vr93QcbGMIbrKviOdv9eYI7SoLucxNF2m4+SfsfO vOLg8p2B+XOsOXa+jwtGZogaM7jxEgg1RfReyR296PUe04sBYKbqCKw4DnOAh0kwnco2hSbP NaYLGzge/zegHI+TS3LUIzkP3Y5deW2PPWSxkSM5W67+HCuDG1j3sRkWGMeMP0MluaZ64i7h CmNzxHj7c6wtNNhM1RFVcSjWAD2ToJz2Wga24C94YqpJ/Izt+xuvrD7n2JWXTARh4DzCUbkQ n3t1xHmCP8fj4EbWfWiGBdYxA+vFDHHxXBItuStHj/eIXsxBZKqO+IoDsAZoHjS7a8/9oAYO csIpQTkK0TO8Xr454nvS69iT13FfGWT93r2OR/7IQuMYM/4M68T3gmjEwG05BqzeI3qxxJup Oo6puBNzgKbLALLPp6/bb3guY7wB5lhwHGB2uh078vJMBDn+HCuDG1j3kRm+kH0+ecnnjJDt Ar14xOY9pBcP+DJVx1EVd2EOMF7WyQfA+yCtf1M8BzZwDP6twBxzDpfRfHQ79uQlE8FuX9tk 7s+x4gis+9AMN7xjZkgvRoI7qBnvyPGFzXtILx7wZaqOoyruwhOgXFfUo9R3p33y+O7hMBlZ MkUOnB7/HpCOkThx958RXGFxbM8rLSzPxw9HoG34c6wPblTdx2aYHt89bBgz8F7cQBw0KqNz zLF6j+rFHNRBxZiKO/EFuE0o4TVqp7L6OWmKuM9uy49I2pHn4jjz9wFz3M5ikN94VWyObfVO yMDa9v1ErZ/ZpW0/D2HqbvNryxA1ZuR5EC7z9GFzbOxFkLfNcePMAZypOoIqjkXlVmEFXzpi mN2RGWKgIwZ1nNJ0hQBz2JQY6OiHGWKgIwZ1nNJ0hQBz2JQY6OiHGWKgIwZ1nNJ0hQBz2JQY 6OiHGWKgIwZ1nNJU5Lhx48aN2/pbnNPjx8lQuVVYwZeOGGZ3ZIYY6IhBHac0XSHAHDYlBjr6 YYYY6IhBHac0XSHAHDYlBjr6YYYY6IhBHac0XSHAHDYlBjr6YYYY6IhBHac0XSHAHDYlBjr6 YYYY6IhBHac09QVouZVHes5HbgVxwOL/Hqjj7jYVn72/lCmvp3+/uzvH+LVrXxdT9+EZbve4 83jaHM+J9xVzOpXYHPtq6PW2OWac9iIuU3XEVhyEJ0DLje001BkWGuuN+d6Bc0yDaef4wcHd m1eqtX1xdOX4nKSPXx9V96EZysT0fGy7b5zBE9eLQvAA9V/O+F70e4/qRWSm6oisOAx7gNL8 eXDlvyuEwfP4+o6Tp3Fs+wq+w+DfyDDH2LC2G1SW9Dt25gVw9edYc+x8HxeMzPDn+3s3+cTJ 1DAh4XoxEGpqHbdX3NGLXu8xvRgAZqqOwIrjMAcoE8mu8dPR93lo4fGH7P9uv2tgA6fbvx2Y Y0CO3NRT/h/dlM105bU99pDFRo7kbN7+HCuDG1j3sRkWyHMNkv4MleSa6ok52FHG5ojx9udY W2iwmaojquJQrAEej7BSaHo6W/L6WwtXTfEef8ETvf49oBwTr2a0Zlaj17ErL5kIwsB5hKNy IT736ojzBH+Ox8GNrPvQDAusBxnYXkzEgx9DPc+4K0eP94hezEFkqo74igOwBtg78bwGSdqP C00rwSucGTyC2yqD+7ivDLL+mvtz/CMLze77NX1ge/FFfC/WQVxwW44Bq/eIXizxZqqOYyru xBxgx+lrWq2P2x2D+5Su0+8+YI7R6dWcKccPfY+mIy/PRJDjz7EyuIF1H5nhC9nnk5d8zgjZ 7t6LnXtyVGzeQ3rxgC9TdRxVcRfmAOOP6+UDoCVIwT6wBdjAMfu/B+uYO33QsScvmQh2+9pq 7s+x4gis+9AMN1B/3hdPcLcO4oI7cnxh8x7Siwd8marjqIq78AQoR9h6lNp+2jfJQhOw+b8H 5yjNmZ0JHCZwOxbH9rxSjZ+PH45A2/DnWB/cqLqPzTA9vns45NirihwvOd4FMGd0jjlW71G9 mIM6qBhTcSe+ALcJJbxG7VS2PrnMs9Cc+/uAOsajt82x+ajtPTbHnnqnRTJ52xZHV4673Mp+ w9Td5teWoUyk6v7a+nOU50G4zNOHzbGxF0HeNseNMwdwpuoIqjgWlVuFFXzpiGF2R2aIgY4Y 1HFK0xUCzGFTYqCjH2aIgY4Y1HFK0xUCzGFTYqCjH2aIgY4Y1HFK0xUCzGFTYqCjH2aIgY4Y 1HFKU5Hjxo0bN27rb3FOjx8nQ+VWYQVfOmKY3ZEZYqAjBnWc0nSFAHPYlBjo6IcZYqAjBnWc 0nSFAHPYlBjo6IcZYqAjBnWc0nSFAHPYlBjo6IcZYqAjBnWc0nSFAHPYlBjo6IcZYqAjBnWc 0tQXYN+tPOI9iWTfxv1r2Hz7PNOtIey3e7E51qndigRx+w+bY2eOwvM2G/152hwzTutoeB8V bstwe46l7u4Mq9h9atyRo3fuced4Macg5kVBHUdU3I0nwL4b231Dbitu8e3yjDeulKJPsNCE 5vzaqcrgsnvlDM8xkAbQh3K8qGPv+zjjjgyFlOM8C43Hp8b4HP1zjyvHyzkFMy8K6oivOAB7 gOXdSMt/FxjuPFuj37fTM9Kyzzmupsz5kT98nSFHReCmbKe/3t47TftzrDl2vo8LbunFUPNH ONqY5ozG6VPjjl70uo7pxQBoXhTUEVxxDOYAZSLZTXpXp9PZae7dk0+Xp9IwAVzgb8o6cuSm R3Fexua4PfbQIznbpOTPsVJHUz/UGZuhEB5/yP43Ol7i96kxNsf0mHwNz9wzpBdBboo6IisO wxpgPF2tFPvdRCinvHdeTrF5zrjQiLfdqWRojjIRhIHz+E5DJz7XkKc/x2MdrX1bY3Qvvv4+ Sdrv0wsNwqfG6BwVz9wzohdzvPOioI64igOxBugZsPG5xi69pyknXGiAl82EkTke95U8+ycm f44LLzRhsX7llfb76EID8qkxNMeC+FyD+IheLLG6KeoIqjgWc4DdlwFyQui757bT7WvynG+h kSa0TIZnjMzRMxHk+HOs1NHVt3tGZpiOcI/b/RkmUD415HW6+MDc0+14oGVOsc+LgjpiKg7G HKAcYe+uK/ZMzmFfy8gOdPuaPHveyxF/U5bIQLL71Biao0wEu31tk7k/x4qjq2/33NOLwo2L YRN2nxr35SiEfQ3iQ3rxgM1NUccRFXfjCVCOcvSIpue0z/O3sS2+/Z49jXvE35QFMrAcRzo1 xuaYJqLn44cj0Db8OdbraO3bknt6UeBCU3L33DOqF3M886KgjiMq7sYX4DahhNeonco+PxeP QLb9wuZpUJtvo6cAcLU5niMDSQcViuE5xoGlOeZHn+24crys49n76MPm15Ohkh6boRcTdp8a Q3MEzT2uHM8cgPOioI4jKu5G5VZhBV86YpjdkRlioCMGdZzSdIUAc9iUGOjohxlioCMGdZzS dIUAc9iUGOjohxlioCMGdZzSdIUAc9iUGOjohxlioCMGdZzSVOS4cePGjdv6W5zT48fJULlV WMGXjhhmd2SGGOiIQR2nNF0hwBw2JQY6+mGGGOiIQR2nNF0hwBw2JQY6+mGGGOiIQR2nNF0h wBw2JQY6+mGGGOiIQR2nNF0hwBw2JQY6+mGGGOiIQR2nNPUFeHYbiAuet124855DnZ7R0X7f IV+me+SeTtE72xC3/rA53ltvm2PGaR0N76PCbRluz7HU3Z1hFbtPjTtyjPdDk327cn/hzvFi TvG6Keo4ouJuPAH23tguBWqfwAWLb5dnvPOwFH2ChSY059dOVQaXLz9leI4Bb71dOV7U0XpD xpI7MhRSjvMsNB6fGuNz/Hb/XX5Xjpdzit9NUUd8xQHYAyzvRvrm7qSHW8fb6Pft9Iy07HOO qylzfuSP5mbIURG4Kdu5v97+HGuOne/jglt6MdTc8zf6Yb2oOH1q3NGLXtcxvRgAuCnqCK44 BnOAMpHsJr2r0+ntMeffkBe6fbs8lYYJ4AJzpm+QIzc9ivMyNkdMvf05Vupo6oc6YzMUwuPO v9HvzzDH71NjbI7pMfkangOfIb0IclPUEVlxGNYA4+lqpdjViVAaIwTp/RvyQq9vl+eTGRca 8bY7lQzNEVRvf47HOtr6oc7oXkT8jX5kLyJ8aozOUZHLbXfNO0eu5xSPm6KOuIoDsQbYU+zj vhL6PQPH1pQTLjTAy2bCyBxR9fbnuPBCExbrV15pv48uNCCfGkNzLIjPNYiP6MUSq5uijqCK YzEH2HH6+snB3eP5Yr6FRjK05HXGyBxR9fbnWKmjqR/qjMwwHeEet/szTKB8asjrdOGqYeiJ 3XPb6HY80DKn2NwUdcRUHIw5QDnC3l1XvAhSGmO3742Du8fzScs+5/ibskTysvvUGJojqN7+ HCuOpn6oc08vCjeOlybsPjXuy1EI+xrEh/TiAZuboo4jKu7GE2D7jximxnw+fjgiacfi2+6p 9DTuEX9TFsjAchzp1BibI6be/hzrdezvhzr39KLAhabEWkPr3+Uf1Ys5VjdFHUdU3I0vwG1C Ca9RO5Xdf06C3vbdHY30YfPt8IxHS+o5x+CWgaSDCsXwHAH1duV4Wcez99GHza8nQyU9xoUm pzFHwHgWXDmeOYDcFHUcUXE3KrcKK/jSEcPsjswQAx0xqOOUpisEmMOmxEBHP8wQAx0xqOOU pisEmMOmxEBHP8wQAx0xqOOUpiLHjRs3btzW3+KcHj9Ohsqtwgq+dMQwuyMzxEBHDOo4pekK AeawKTHQ0Q8zxEBHDOo4pekKAeawKTHQ0Q8zxEBHDOo4pekKAeawKTHQ0Q8zxEBHDOo4pekK AeawKTHQ0Q8zxEBHDOo4pakvwLPfzq2w+y3Yu2/v0uEpRNe7HevIrTZSZq8N8RvZNsfOHIVn 3fvztDlmnNbR8D4qjM4QUXt5Dox8DCOacMPm2FfDeJsadTfU3OaYcTGneN0UdQRWHIcnwPb7 DaWm2O1rDNTi23VfpHhDSCn6BAtNaE7+KWcjF3XsfR9nDM0QVHtYL8othZ5jNt1eyBjbgfG9 mLvbGNWLCDdFHVEVh2IPUJotD678d07xWAz+rvtf9XgqLfuc42rKHP4p5+3/rNQcO9/HBUMz BNV+VC/KRP+5haazhqEXva5jejEAcFPUEVRxLOYAZSLZNX46azkLTRpT9/c0abdvp2fiTeO+ wd+UdeTITY/ivIzNcXuMf8p5j+NrW2vvz7CCvA9LYCeMzTE9Jl/j/pv55tTmFIyboo4DKu7H GmA8Xa0U+3wwvEL19Givb7+nMONCI952p5KhOcpEEAYO/5TzHvvXttce3YvxgDG85icXGmuO yf1TOV7PKR43RR2xFQdhDbC/2OHxcIT7CPt4Ar2nKSdcaICXzYSROR73lTz7DzD8Of6RhcZR +2G9GF7XklmN23IMxOcaFskRvVhidVPUcUDF/ZgD7D59fYWcVu+bvkdjulwx30IjTYga2MLI HD0TQY4/x0odTf1Q555eTHlaaz+iF4Vjje3clWMi9ITBe0gvHrC5Keo4puJOzAHGo5p8sbgI Mu6bP9YSep1u3x7PJ3Y/wd+UJTKQ7D41huYoE8FuX9tk7s+x4mjqhzr39KKv9vhe3JAaW1bn CvfkqIR9Dd5DevGAzU1Rx0EV9+EJUM5M9Ejr+rRPQs6OaA8TUTsW33ZPpadxj/ibskAGFujo URmbY1pYno8fjkDb8OdYr2N/P9S5pRedtYf3YsR24HDGLTlu8E85fwhfgNuEEl6jdiq7+1w8 Ctn2vX0St3redEnlDTKQdFChGJ7jdnCRcrzvoOLJZR3P3kcfNr+eDOVt+Gpvc6wQDw4377Ch FhnB5tiYI2A8CzbHjTMHkJuijqCKY1G5VVjBl44YZndkhhjoiEEdpzRdIcAcNiUGOvphhhjo iEEdpzRdIcAcNiUGOvphhhjoiEEdpzRdIcAcNiUGOvphhhjoiEEdpzQVOW7cuHHjtv4W5/T4 cTJUbhVW8KUjhtkdmSEGOmJQxylNVwgwh02JgY5+mCEGOmJQxylNVwgwh02JgY5+mCEGOmJQ xylNVwgwh02JgY5+mCEGOmJQxylNVwgwh02JgY5+mCEGOmJQxylN3QHG2yi03FJmxtt+XJGe Y7kthDvTgngvJ3F3ZpdzW47P22z033Zo9hxHZyj383r6bltvP8pzYOS3TPHeLyXD5tjXi97a 2xwzLuZJVF+qI7DiOFwBPu9/9H4SWepGhgEt/ucXmm/Y3xTPuSPHlOHd97U7A5/j0AzDxPS1 e0gm1k8u1nl+6T52xiF8YHwv+mvvyvFynsT1pTqiKg7F34jSdO8GQLlPy3Pq9PsavnYY5I8w yqc4owlNihrQOcNzjIPLdjNNZfYch2ZY/I1+6UnLXZxhGRY+MtF/bqHp70Wvqz/HE0dgX6oj qOJYhgWYI5PObpDceFmq+2uHxx+y/42OpyQHeT3vpF0yNsftsYceyf3NHMdmuEeO2vUIvgdc hhnyPiwFPWFsjpja+3OszZPYvlTHARX3MybAPfHUttIYdwyc3q/9+psQV817jT/TI3IE6bkM VTI0R5kIwsB5fKfw4nMN7rPnOLoXX8h+Nmd0him/sH1wobHm6Km9P8freRLRl+qIrTiI0QEK 9gF2ZGhThgnyNX7SfrMsNEJ8L6ABPjLH477SI/1Zzp7j0F7MMV42E4ZkGL+xbRu/NW7LMWCt vT/HxnnS0ZfqOKDifu4IUCbwWmNYMu327fjaz6O1YusdUPKcMYSsjRNOSbdjR46eiSBn9hxH ZpgjeVon9VEZHmts564cE7ba+3NsmCedfamOYyru5JYA4xFQfg2yJfQ63b7mr93TvHv8mZ4R 3C1CFYbmKBPBbl9blrPneE8vSna2sSIMy1BqvEIvHrDV3p9ji6OvL9VxUMV93BNg2CucLehR mecU0eJr+9rzLTTevymeMzbHlN3z8cMRaBuz53hLL8qkCjjKxWIfGzVuyXHDWnt/ju/nSW9f quOIirtxBRiPLF6XmF613iaayult3Pf2gXP2tWuein0w2RwrnObrZ3yOMrDUPT/6bMfmWGFQ jja/vl6USVQnVAuwDONZKj5DwebYmCOo9jbHjTMHcF+qI6jiWFRuFVbwpSOG2R2ZIQY6YlDH KU1XCDCHTYmBjn6YIQY6YlDHKU1XCDCHTYmBjn6YIQY6YlDHKU1XCDCHTYmBjn6YIQY6YlDH KU1Fjhs3bty4rb/FOT1+nAyVW4UVfOmIYXZHZoiBjhjUcUrTFQLMYVNioKMfZoiBjhjUcUrT FQLMYVNioKMfZoiBjhjUcUrTFQLMYVNioKMfZoiBjhjUcUrTFQLMYVNioKMfZoiBjhjUcUpT d4DxNgpt9+iJ9yQKXy9uxa02WrH5nt2u4or0HMttIdyZFiByK7ktx+dtNvrv4zR7jma/jjHT tW8FaIb5bWhAfSjYHPt60Vt7m2PGRR1RfamOwIrjcAX4bLyWgfD9mVuzByw34NPif36hweRW ckeOKcNJJskBOZr8esZM1/iqA8tQJspnvbf72FkGRwWLY18v+mvvyvGyjri+VEdQxbH4G1Ga rm3QIPqy37f0a/ANg+rx9T3HGQ0ot5LhOcbBZbuZpjJ7jna/xjET6dn3CCrDn+/v3WQYJ3fw BNlOfy96a+/P8cQR2JfqiKk4mGEB7shOc++efGTC2w2Id5fEwuMP2f/dfuf4M1VwuZWMzXF7 7KFHcn8zR7tfz+LRs+8RXIYF0g+gGbLb0dCL3tr7c6zVEduX6jio4j7GBHiOnPLeeSngeOSV int26/XX34S4at5r/Jke8eZWMjRHmQjCwHmEo2DBeglt9hztfusvNJIjaJ3pduwd04qn9v4c r+uI6Et1HFNxJ6MDrBEbxdilQ5syTJAvrbkWGsGTW8nIHI/7So/0Zzl7jna/xRea3fdr/Izs xRJr7f05vq+jty/VcUDF/dwR4JHwnF2jtNPt23GanY4qjltLA+fIc8Zgz62k27EjR89EkDN7 jna/njFjGV8v8BlKLVe6jFtiq70/x5Y6+vpSHdEVh3BPgCXhOcaVu9s3/lhhPjBafXuad48/ 0zPsuZUMzXG7dPba15bl7Dna/Vp7UOjZ9wg6Q+SfE1eG9uIBW+39ObY42twUdcRWHMQ9Ae7x NKvFV85U9Gi6/fR0voUGOcjH5piyez5+OAJtY/Yc7X6dE+MkC43UfFfyUFfL+CgZ24t7rLX3 5/i+jt6+VEdcxYG4AoxHFq9LTK9abxONTi6n+/Vj89185OtXTrnrk+AECw0wt5LxOcrAUnfb pRabY4VBOZr8WseMAPA2OVaoX1a21bXE5tjYi6Da2xw3zhzAfamOmIqDUblVWMGXjhhmd2SG GOiIQR2nNF0hwBw2JQY6+mGGGOiIQR2nNF0hwBw2JQY6+mGGGOiIQR2nNF0hwBw2JQY6+mGG GOiIQR2nNBU5bty4ceO2/hbn9PhxMlRuFVbwpSOG2R2ZIQY6YlDHKU1XCDCHTYmBjn6YIQY6 YlDHKU1XCDCHTYmBjn6YIQY6YlDHKU1XCDCHTYmBjn6YIQY6YlDHKU1XCDCHTYmBjn6YIQY6 YlDHKU1dAcabJ24/8bC7DUSNs1tG9GHzbf/atVtt9N4aQp4DI79NhfceFRk2R0MNn/7993GC 5hiI98SKLh3+F5j9YiYdeUyTIWYMl9gc+1y8tbc5ZlzUHNWX6oisOAxzgBLcc+Lb7mt1MRFa b4JXYvFt/trhPX3tHpJm/uTgDrk+Gy9ljFprhua4kQZQf34KLkchzxKDye95cNaWy0wZosZw yfhe9NfeleNlzXF9qY64igOxBtj3N8RlksxDLv/dTr9vx9f+kT/gnCGLqaEJXE2ZU/jI4Prc QtNZwzi4fDddhOUogO40nGP3a+z/qTLsrH8Hd/Sit/b+HE8cgX2pjqiKQ4E1ogyKs8Tksd2E nU57LQF3+zq+tiyeetTUAyzTnKt8DYzNcXvsEZ4Tvo5st9T6lOSTXDB3HBbsfi2T9GQZAsdw SbejoRdThvba+3Os1Rzbl+oIqjgWf4CJq6Pt49lOCviOSdz+tWW/d5NBHVSmimQbmxExqjeG 5igTQRg4j3DWK8Tnvp1Yj6BzFFKWtrqW2P0aFprJMkSO4ZKhvZjhqb0/x+uaI/pSHTEVBwNp xN33a44gm/Supozvafe8diCZlohPeF3EwBZG5njcVwZZ/9HvkBwD0Q+waNv93i80s2VoHkcN jOzFEmvt/Tk21tzRl+qIqTgYf4BS5DenfcDT7m5f49eWolsHkT/TOscBZmdkjp6JIGdUjnHQ A3K0+1kWmg9nCBzDJSN78Yit9v4c39fc6qaoI6jiWLwBNv350Xg0ni9GLaHX6fY1fW1pXJuf 4G/KE2SAIUZ2YGiO4rnb1zYpDctR3AE52v0aenC2DIFjuGRoLx6w1d6fY4ujzU1RR1DFsXgC lKOuXS5hcJzlJNcg9WgsHq0ZA7X4dn9taWTAkQUW3BGkMDbH5Pp8/HAE2saYHEXnQxPkk5ZJ Z74MUWO4ZGwv7rHW3p/j+5p7+1IdcRUHYg1QCi3P3W96lLENkt3A2D4n+90+iZ997Zpnalxt Ygs2xwrxqHbzDhtoXEdsjj05ysBS9/zosx2bY4V4BKwun12sz10mzzByVn8fNsfGXgTV3ua4 ceYA7kt1RFYchsqtwgq+dMQwuyMzxEBHDOo4pekKAeawKTHQ0Q8zxEBHDOo4pekKAeawKTHQ 0Q8zxEBHDOo4pekKAeawKTHQ0Q8zxEBHDOo4panIcePGjRu39bc4p8ePk6Fyq7CCLx0xzO7I DDHQEYM6Tmm6QoA5bEoMdPTDDDHQEYM6Tmm6QoA5bEoMdPTDDDHQEYM6Tmm6QoA5bEoMdPTD DDHQEYM6Tmm6QoA5bEoMdPTDDDHQEYM6Tml6b4Dp9hDXt1q4vs2F2Tfe7qHnXkItrnXgmXa7 v8fmeF2bKs/bbPT7o3OM98SKLh3+F5j9Wuu5u0UJb0Gzp8/FW3ubY8ZFzVF9qY7IisMoA0Td cLCGBno1eb+7WV7p28TznmHt763F9QyT4xkG9xYsjr03MkwZ2r2hOcp9w4CTo2Dya67n/iaM MctPTJAZ695U0197V46XNcf1pTriKg7kGKAeKWAnttANv4+v7zdnCfvBdfy3p+DH1zqlyfUc V1NW6XBvpN/xfW12xMFlOwpXoDkGH9C8+GRoL0p+uwlIntPfj7gMO+vfwR296K29P8cTR2Bf qiOq4lDOA6wvOPW7Nm/baWLhtR4yaNJrnu52GFzH/eXr2GgdGI2uF9gdz8ANaqXbsaE2L7bH Zvl795tPcvEtfjl2v/f1PJ7BpPfQe1dxWIZd9e+j29HQi97a+3Os1Rzbl+oIqjiW9wFqGPaJ 7nU57ro5WwaXveBtk3Wr6xX+piz5/ELTNfHJRBAGzix/7z4nHShhshzai9v3Z179d5H3BagM UQtfjaG9mOGpvT/H65oj+lIdMRUH0xTg1vSmpgqTTjlYpl1oOlyv8DdlyVoLzXFf8e/PEp9j IvpZClswtBcD0TN8jXz7VIY99e+l19HjYq29P8f3Nff2pTpiKg7mMsBtgcmL2nvp7Gz/alM0 nBLLc228L3SX6wXyHCyfX2haaqOgJiV8jkrIc+dnw+7XX89jpm3AMuyofy8je/GIrfb+HFtq 7utLdQRVHEs1wMoCg+FNQ8Svm1+rPBbHXvDewW0fSP6mLOl1f0+3Y0NtnshEsNvXliU+RyW4 A2bI23pxG48f7cWe+ncytBcP2Grvz7HF0eamqCOo4ljKAONRPXyBUd5POPL19ci3dippL3jv wOBCU/KuNi9Sds/HD0egbeBzTKB+hP+WXoyLdv/ZoILMsL3+fYztxT3W2vtzfF9zb1+qI67i QJCN+J5y8t4mpN0ktH0ueNUmJ5PvdkQYXzNs119fKV3bgWZ66u7D5nhWm1qOMrDUOz/6bMfm WGGmDFt78bkfZvLBcFZ/HzbHxl4E1d7muHHmAO5LdURWHIbKrcIKvnTEMLsjM8RARwzqOKXp CgHmsCkx0NEPM8RARwzqOKXpCgHmsCkx0NEPM8RARwzqOKXpCgHmsCkx0NEPM8RARwzqOKWp yHHjxo0bt/W3OKfHj4QQQsgguNAQQggZyO/v/wFgvMoBS1ozagAAAABJRU5ErkJggg==</item> <item item-id="13">iVBORw0KGgoAAAANSUhEUgAAADUAAAARCAYAAAB92+RQAAAAAXNSR0IArs4c6QAAAARnQU1B AACxjwv8YQUAAAAJcEhZcwAADsMAAA7DAcdvqGQAAAE/SURBVEhL7VVRssMgCPQ+nsf7cB7P 430oq/iCBtO06ftopjvjTCqC7AI28A3xI/UtuDOpwhQDh4CVOLfNCeZMJPn1YRTiWO+PTG5w m+N8JnOq+1hprFROzZA8VjlxjJGDa7wKJKWJVnJ7YQulPyI1TyOstQEDqULERJK4U4mcxFFs 0ZfxGkSwTaxWkUPtBuJblXpuO1JZDw1BJUgSh3JIyvE7CcS1HYBKHIoHUrPw2r7wc0jpJUN5 t/3nlbK9P60F4znuU1IYBdcOYaeZ6smPqsu3JnOO1Ot4jZTkc/BQYUwWpFpgVCubIfyvSkH5 szOFpBcmAXx3r59x0B6de32Z2CWgM8zrt6gERN24tzkfoG2ppEZ1uyNItO9JffdS27JvoIto /4N0DzGroP1+ew5V7nt6+VCpu+BH6ltwQ1LMDweQy1g1mekcAAAAAElFTkSuQmCC</item> <item item-id="14">iVBORw0KGgoAAAANSUhEUgAAAD8AAAARCAYAAABq+XSZAAAAAXNSR0IArs4c6QAAAARnQU1B AACxjwv8YQUAAAAJcEhZcwAADsMAAA7DAcdvqGQAAAFnSURBVFhH7ZXhEYYgCIbdx3ncx3mc p334ANHQJOu++tHVe9d1ESgPYDl4sT74t+qDhyWCdw4cXSGxiaXtPsIi5ktV9/AQrQ0sn0ls Cg40TtYC0QuTWFhL9GxsA9A5bla4SAlCSZxBAlp6WT6TWClMy0IxCC3GDj5CSgELoBe6EZ72 qtnljmw6ZflMYhOyxKbz2cerEdnC453GZR3zGXyupt74qHjSVCDtq5MjWT67sVgYetWMvUxH IDbp/hAewxgoLzaDL8qV5YX7SyWpRQAa1oIf+dixa74aPhcLJ5qe5UgY8Kh6Zo7Cn9ct8AnH Xcw9fO9vw6O4WvhR8Td1HjNQ73L8xvXkmWeobv9SLJ3HAD50vwwBUkHXqvtiD3+nls88Vnee fYq/xFb4tWLFoQgdd+FpoUHHjkqOV7Ov2NrEB7lZdlEDT6JpYf9sbzr/NlV4F9s6nH1+opiA QDTM2eenqsL/c3+mAH64qdrSZsjpDgAAAABJRU5ErkJggg==</item> <item item-id="15">iVBORw0KGgoAAAANSUhEUgAAAP4AAAAYCAYAAADai0DOAAAAAXNSR0IArs4c6QAAAARnQU1B AACxjwv8YQUAAAAJcEhZcwAADsMAAA7DAcdvqGQAAATDSURBVHhe7ZlrdqMwDIWzH9bDflgP /2Yv2Q8j+YFlWbItkrSnRN8ceqaAZOna15DmcTiO83W48R3nC3HjO84X4sZ3nC/EjS/w3Jbj 8XiIx7I9012O83dx4ws8t/XI/sZN4DT7vrrxnVvgxh9QGd9xboIbf4Ab37kjbvwBbnznjrjx B7jxnTvixh/gxnfuSGP8fS1fXa3789jW7aiX/X6sjxV+wrUl34u/S5B7Fp4n8dyOJY33WEkW el6LVQg90FwMNHO5Dv108n/W+FlLwtn3cn6zIFH3kBBjcYykYzo60iiUeWxje/npNdLnZI8i U7HKuAlcH3KN8bDq084F9caoR01bfn6gs9EjlfGDYUgC/nscvG4kbxSiWPj11yIsUIEgXpMH mt/GsTU7CIa55M0oj1PVFBYTv59OHrv/LbRaVufEmiJiD1rsvlc59lXOqYN5O/138tOvRQtz PcrM6iONmwhxZJ29qI80F3T81kMUTVvh/KhOo5bF+GDSdneCxU+e+PVOGXluG5gTmheaw+Lw 2swTE/PsoQZavN34IQ/8Q+EaPRPtDg3g2FrAB5C0rGuIG890D1Ox9XyOiXnm33ho/rR44aji DT02TMUq4yZ2XK+S9gGrPhFxPWVUQ2raaucpSp2GNXwaPxTfe13ABoTrqtHg/hWKx7wzCyfm wdrpDgkNmoxf7u/ttPJEoeB84/sQqpZ1XdiDph2/dyo2zck0adGuqCWaqdGMIeUPOUotlh45 plg2bgCMgeEYJ7Zi1SfB66rAOqR1GOoTtNXOU9Q659fwaXwUozZK2Tnx/D+luWzY0DyJp+dn Jjbfn8eNMUbjgyDn7UFAWQRtotQF0QXFTjrxQ0mmjc+16i1snmMmtvsKLBDHgKcVDhP07Ouj 58c5jU89S48ce2wZF6Krh4LUh1WfDJ+LCthspBo1bWc079Wp9capjX+KlCDm4aJnuGHjoPD/ NLoWxyl5gLNhm/FjD/Whi97mna31VXQt5xc272EcC1oaX2Mt9Yzy58+ktpw1V2LPz8I7PBTS rRjXTr9dnwyfiwL4QHraA1ov4x77dfJ4DfYZnwui79QZalgsEp/6O9mRZgupjA9gHP7NYZk2 /g6bRD1OyCEIH86/zfgwERee+OI4U59hI00Pw9iyGc/Cx+gbrZcf68kGnO+xwRxbxg1rk81P 3Ytdn4y2nnp/KNS0HWverxPj9TkqFOMnIeunfm38YXPpSc0Ll+I47etLqmciFpFff7D+dnHo vRgW4Qto48d608cT1FJ5WiBtjkEsmMbcG3njq/JL9PLDtbIY53tsMcZW4xbEeb6iT0KaTzx3 noJa5b99CNqONB/UObuGifEjwahkVzwbaoTOG0U88m1l4Pp6efJiM7CLkerKmKxJvLfpgsfT ceimpYwPwp3nqtx4Px//Q/QWbZh4rI/Uks6d5Wo9SLGJ3tOnCxmrSM7qAZr8qs5Ap84hI316 4yYkc7xDnzxe46FcK9dN0hbRzgP9OufXcGP8HpJgV8GvVaxzTnk1vgHFfldzE7xTS8cJGNaw yfiQuX31uMBzh8/zL+R4Nb4h7MQXd/zLvEdLxwkY17DR+Ai+Tvy0ST4JGvC3+rmbls7vYF/D F4zvOM7f5jj+AyFyI0PcV1TMAAAAAElFTkSuQmCC</item> </binaryContent> </worksheet>