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<UT type="prediction"><UT1-UTC>-0.01288</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57441</MJD>
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<dataEOP><pole type="prediction"><X>-0.0107</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.01452</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57442</MJD>
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<dataEOP><pole type="prediction"><X>-0.0111</X>
<Y>0.3293</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.01622</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57443</MJD>
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<dataEOP><pole type="prediction"><X>-0.0115</X>
<Y>0.3310</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.01794</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57444</MJD>
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<dataEOP><pole type="prediction"><X>-0.0119</X>
<Y>0.3327</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.01967</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<dataEOP><pole type="prediction"><X>-0.0122</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.02138</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57446</MJD>
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<dataEOP><pole type="prediction"><X>-0.0125</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.02305</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57447</MJD>
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<dataEOP><pole type="prediction"><X>-0.0128</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.02466</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57448</MJD>
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<dataEOP><pole type="prediction"><X>-0.0130</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.02622</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57449</MJD>
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<dataEOP><pole type="prediction"><X>-0.0132</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.02773</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57450</MJD>
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<dataEOP><pole type="prediction"><X>-0.0134</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.02922</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<dataEOP><pole type="prediction"><X>-0.0136</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.03074</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<dataEOP><pole type="prediction"><X>-0.0137</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.03233</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57453</MJD>
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<dataEOP><pole type="prediction"><X>-0.0138</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.03404</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57454</MJD>
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<dataEOP><pole type="prediction"><X>-0.0138</X>
<Y>0.3496</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.03592</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<dataEOP><pole type="prediction"><X>-0.0138</X>
<Y>0.3513</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.03800</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<dataEOP><pole type="prediction"><X>-0.0138</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.04026</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57457</MJD>
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<dataEOP><pole type="prediction"><X>-0.0138</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.04263</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57458</MJD>
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<dataEOP><pole type="prediction"><X>-0.0137</X>
<Y>0.3564</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.04503</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57459</MJD>
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<dataEOP><pole type="prediction"><X>-0.0136</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.04735</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57460</MJD>
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<dataEOP><pole type="prediction"><X>-0.0135</X>
<Y>0.3599</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.04954</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57461</MJD>
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<dataEOP><pole type="prediction"><X>-0.0133</X>
<Y>0.3616</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.05156</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57462</MJD>
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<dataEOP><pole type="prediction"><X>-0.0131</X>
<Y>0.3633</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.05342</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57463</MJD>
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<dataEOP><pole type="prediction"><X>-0.0129</X>
<Y>0.3650</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.05518</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57464</MJD>
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<dataEOP><pole type="prediction"><X>-0.0126</X>
<Y>0.3667</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.05688</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<dataEOP><pole type="prediction"><X>-0.0124</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.05858</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<dataEOP><pole type="prediction"><X>-0.0120</X>
<Y>0.3701</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.06032</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57467</MJD>
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<dataEOP><pole type="prediction"><X>-0.0117</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.06211</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57468</MJD>
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<dataEOP><pole type="prediction"><X>-0.0113</X>
<Y>0.3735</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.06397</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57469</MJD>
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<dataEOP><pole type="prediction"><X>-0.0109</X>
<Y>0.3751</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.06590</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57470</MJD>
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<dataEOP><pole type="prediction"><X>-0.0104</X>
<Y>0.3768</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.06786</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<dataEOP><pole type="prediction"><X>-0.0100</X>
<Y>0.3785</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.06983</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57472</MJD>
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<dataEOP><pole type="prediction"><X>-0.0095</X>
<Y>0.3801</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.07179</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57473</MJD>
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<dataEOP><pole type="prediction"><X>-0.0089</X>
<Y>0.3818</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.07370</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57474</MJD>
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<dataEOP><pole type="prediction"><X>-0.0084</X>
<Y>0.3834</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.07556</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57475</MJD>
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<dataEOP><pole type="prediction"><X>-0.0078</X>
<Y>0.3851</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.07735</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57476</MJD>
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<dataEOP><pole type="prediction"><X>-0.0072</X>
<Y>0.3867</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.07907</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57477</MJD>
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<dataEOP><pole type="prediction"><X>-0.0065</X>
<Y>0.3883</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.08076</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<dataEOP><pole type="prediction"><X>-0.0058</X>
<Y>0.3900</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.08243</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57479</MJD>
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<dataEOP><pole type="prediction"><X>-0.0051</X>
<Y>0.3916</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.08414</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57480</MJD>
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<dataEOP><pole type="prediction"><X>-0.0044</X>
<Y>0.3932</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.08595</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57481</MJD>
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<dataEOP><pole type="prediction"><X>-0.0036</X>
<Y>0.3948</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.08790</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57482</MJD>
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<dataEOP><pole type="prediction"><X>-0.0028</X>
<Y>0.3963</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.09004</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57483</MJD>
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<dataEOP><pole type="prediction"><X>-0.0020</X>
<Y>0.3979</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.09237</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<dataEOP><pole type="prediction"><X>-0.0011</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.09486</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<dataEOP><pole type="prediction"><X>-0.0002</X>
<Y>0.4010</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.09744</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57486</MJD>
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<dataEOP><pole type="prediction"><X>0.0007</X>
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<UT type="prediction"><UT1-UTC>-0.10000</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<dataEOP><pole type="prediction"><X>0.0016</X>
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<UT type="prediction"><UT1-UTC>-0.10244</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57488</MJD>
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<dataEOP><pole type="prediction"><X>0.0026</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.10471</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<dataEOP><pole type="prediction"><X>0.0036</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.10679</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<dataEOP><pole type="prediction"><X>0.0046</X>
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<UT type="prediction"><UT1-UTC>-0.10872</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<dataEOP><pole type="prediction"><X>0.0056</X>
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<UT type="prediction"><UT1-UTC>-0.11055</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57492</MJD>
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<dataEOP><pole type="prediction"><X>0.0067</X>
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<UT type="prediction"><UT1-UTC>-0.11234</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57493</MJD>
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<dataEOP><pole type="prediction"><X>0.0078</X>
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<UT type="prediction"><UT1-UTC>-0.11412</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57494</MJD>
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<dataEOP><pole type="prediction"><X>0.0089</X>
<Y>0.4142</Y>
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<UT type="prediction"><UT1-UTC>-0.11594</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57495</MJD>
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<dataEOP><pole type="prediction"><X>0.0101</X>
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<UT type="prediction"><UT1-UTC>-0.11779</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57496</MJD>
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<dataEOP><pole type="prediction"><X>0.0112</X>
<Y>0.4170</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.11969</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57497</MJD>
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<dataEOP><pole type="prediction"><X>0.0124</X>
<Y>0.4184</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.12162</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57498</MJD>
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<dataEOP><pole type="prediction"><X>0.0137</X>
<Y>0.4197</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.12355</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57499</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0149</X>
<Y>0.4210</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.12545</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57500</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0162</X>
<Y>0.4224</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.12731</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57501</MJD>
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<dataEOP><pole type="prediction"><X>0.0175</X>
<Y>0.4237</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.12910</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57502</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0188</X>
<Y>0.4249</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.13081</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57503</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0201</X>
<Y>0.4262</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.13244</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57504</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0215</X>
<Y>0.4274</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.13400</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57505</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0228</X>
<Y>0.4286</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.13552</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57506</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0242</X>
<Y>0.4298</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.13704</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>29</dateDay>
<MJD>57507</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0257</X>
<Y>0.4310</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.13860</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>30</dateDay>
<MJD>57508</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0271</X>
<Y>0.4322</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.14026</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57509</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0286</X>
<Y>0.4333</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.14206</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>02</dateDay>
<MJD>57510</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0300</X>
<Y>0.4344</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.14402</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57511</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0315</X>
<Y>0.4355</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.14614</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57512</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0331</X>
<Y>0.4366</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.14836</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>05</dateDay>
<MJD>57513</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0346</X>
<Y>0.4376</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.15062</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>06</dateDay>
<MJD>57514</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0362</X>
<Y>0.4386</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.15281</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>07</dateDay>
<MJD>57515</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0377</X>
<Y>0.4396</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.15485</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>08</dateDay>
<MJD>57516</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0393</X>
<Y>0.4406</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.15671</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>09</dateDay>
<MJD>57517</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0409</X>
<Y>0.4416</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.15839</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>10</dateDay>
<MJD>57518</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0426</X>
<Y>0.4425</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.15992</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>11</dateDay>
<MJD>57519</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0442</X>
<Y>0.4434</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.16138</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>12</dateDay>
<MJD>57520</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0459</X>
<Y>0.4443</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.16282</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>13</dateDay>
<MJD>57521</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0475</X>
<Y>0.4452</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.16425</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>14</dateDay>
<MJD>57522</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0492</X>
<Y>0.4460</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.16571</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>15</dateDay>
<MJD>57523</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0509</X>
<Y>0.4468</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.16718</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>16</dateDay>
<MJD>57524</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0526</X>
<Y>0.4476</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.16866</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>17</dateDay>
<MJD>57525</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0544</X>
<Y>0.4484</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.17013</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>18</dateDay>
<MJD>57526</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0561</X>
<Y>0.4491</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.17157</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>19</dateDay>
<MJD>57527</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0578</X>
<Y>0.4498</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.17295</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>20</dateDay>
<MJD>57528</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0596</X>
<Y>0.4505</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.17425</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>21</dateDay>
<MJD>57529</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0614</X>
<Y>0.4512</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.17545</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>22</dateDay>
<MJD>57530</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0632</X>
<Y>0.4518</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.17657</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>23</dateDay>
<MJD>57531</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0650</X>
<Y>0.4524</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.17759</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>24</dateDay>
<MJD>57532</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0668</X>
<Y>0.4530</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.17856</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>25</dateDay>
<MJD>57533</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0686</X>
<Y>0.4535</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.17950</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>26</dateDay>
<MJD>57534</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0704</X>
<Y>0.4541</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.18046</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>27</dateDay>
<MJD>57535</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0722</X>
<Y>0.4546</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.18148</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>28</dateDay>
<MJD>57536</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0741</X>
<Y>0.4551</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.18262</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>29</dateDay>
<MJD>57537</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0759</X>
<Y>0.4555</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.18389</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>30</dateDay>
<MJD>57538</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0778</X>
<Y>0.4559</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.18529</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>31</dateDay>
<MJD>57539</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0796</X>
<Y>0.4563</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.18681</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>06</dateMonth>
<dateDay>01</dateDay>
<MJD>57540</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0815</X>
<Y>0.4567</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.18840</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>02</dateDay>
<MJD>57541</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0834</X>
<Y>0.4570</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.18996</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>03</dateDay>
<MJD>57542</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0853</X>
<Y>0.4573</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.19143</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>04</dateDay>
<MJD>57543</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0871</X>
<Y>0.4576</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.19274</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>05</dateDay>
<MJD>57544</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0890</X>
<Y>0.4579</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.19389</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>06</dateDay>
<MJD>57545</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0909</X>
<Y>0.4581</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.19490</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>07</dateDay>
<MJD>57546</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0928</X>
<Y>0.4583</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.19581</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>08</dateDay>
<MJD>57547</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0947</X>
<Y>0.4585</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.19668</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>09</dateDay>
<MJD>57548</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0966</X>
<Y>0.4586</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.19756</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>10</dateDay>
<MJD>57549</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0985</X>
<Y>0.4587</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.19846</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57550</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1004</X>
<Y>0.4588</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.19939</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>12</dateDay>
<MJD>57551</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1023</X>
<Y>0.4589</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.20032</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>13</dateDay>
<MJD>57552</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1042</X>
<Y>0.4589</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.20125</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>14</dateDay>
<MJD>57553</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1060</X>
<Y>0.4589</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.20215</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57554</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1079</X>
<Y>0.4589</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.20300</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>16</dateDay>
<MJD>57555</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1098</X>
<Y>0.4589</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.20378</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>17</dateDay>
<MJD>57556</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1117</X>
<Y>0.4588</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.20446</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>18</dateDay>
<MJD>57557</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1136</X>
<Y>0.4587</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.20506</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>06</dateMonth>
<dateDay>19</dateDay>
<MJD>57558</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1155</X>
<Y>0.4586</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.20558</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>06</dateMonth>
<dateDay>20</dateDay>
<MJD>57559</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1174</X>
<Y>0.4584</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.20603</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>06</dateMonth>
<dateDay>21</dateDay>
<MJD>57560</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1192</X>
<Y>0.4582</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.20645</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<dataEOP><pole type="prediction"><X>0.1211</X>
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<UT type="prediction"><UT1-UTC>-0.20689</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<dataEOP><pole type="prediction"><X>0.1230</X>
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<UT type="prediction"><UT1-UTC>-0.20738</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<dataEOP><pole type="prediction"><X>0.1248</X>
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<UT type="prediction"><UT1-UTC>-0.20798</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<dataEOP><pole type="prediction"><X>0.1267</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.20871</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<dataEOP><pole type="prediction"><X>0.1285</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.20957</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<dataEOP><pole type="prediction"><X>0.1303</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.21054</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<dataEOP><pole type="prediction"><X>0.1322</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.21159</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<dataEOP><pole type="prediction"><X>0.1340</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.21263</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<dataEOP><pole type="prediction"><X>0.1358</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.21362</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<dataEOP><pole type="prediction"><X>0.1376</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.21450</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<dataEOP><pole type="prediction"><X>0.1394</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.21524</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57572</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1411</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.21586</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<dataEOP><pole type="prediction"><X>0.1429</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.21640</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<dataEOP><pole type="prediction"><X>0.1447</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.21692</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57575</MJD>
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<dataEOP><pole type="prediction"><X>0.1464</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.21746</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57576</MJD>
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<dataEOP><pole type="prediction"><X>0.1481</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.21807</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57577</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1499</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.21874</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57578</MJD>
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<dataEOP><pole type="prediction"><X>0.1516</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.21949</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57579</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1532</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.22028</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57580</MJD>
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<dataEOP><pole type="prediction"><X>0.1549</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.22110</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57581</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1566</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.22194</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57582</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1582</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.22275</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57583</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1599</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.22354</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57584</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1615</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.22427</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57585</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1631</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.22495</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57586</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1646</X>
<Y>0.4440</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.22557</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57587</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1662</X>
<Y>0.4431</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.22614</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57588</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1678</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.22670</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>20</dateDay>
<MJD>57589</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1693</X>
<Y>0.4413</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.22730</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57590</MJD>
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<dataEOP><pole type="prediction"><X>0.1708</X>
<Y>0.4403</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.22797</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57591</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1723</X>
<Y>0.4393</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.22878</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57592</MJD>
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<dataEOP><pole type="prediction"><X>0.1737</X>
<Y>0.4383</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.22971</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57593</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1752</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.23077</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57594</MJD>
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<dataEOP><pole type="prediction"><X>0.1766</X>
<Y>0.4363</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.23191</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57595</MJD>
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<dataEOP><pole type="prediction"><X>0.1780</X>
<Y>0.4352</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.23307</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57596</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1794</X>
<Y>0.4341</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.23420</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57597</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1808</X>
<Y>0.4330</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.23525</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57598</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1821</X>
<Y>0.4319</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.23619</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57599</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1835</X>
<Y>0.4307</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.23702</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57600</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1847</X>
<Y>0.4296</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.23776</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>01</dateDay>
<MJD>57601</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1860</X>
<Y>0.4284</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.23844</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57602</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1873</X>
<Y>0.4272</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.23912</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57603</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1885</X>
<Y>0.4260</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.23983</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57604</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1897</X>
<Y>0.4247</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.24058</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57605</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1909</X>
<Y>0.4235</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.24139</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57606</MJD>
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<dataEOP><pole type="prediction"><X>0.1921</X>
<Y>0.4222</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.24221</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57607</MJD>
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<dataEOP><pole type="prediction"><X>0.1932</X>
<Y>0.4209</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.24302</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57608</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1943</X>
<Y>0.4196</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.24376</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57609</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1954</X>
<Y>0.4183</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.24440</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57610</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1964</X>
<Y>0.4169</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.24492</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57611</MJD>
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<dataEOP><pole type="prediction"><X>0.1975</X>
<Y>0.4156</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.24532</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57612</MJD>
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<dataEOP><pole type="prediction"><X>0.1985</X>
<Y>0.4142</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.24559</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57613</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1995</X>
<Y>0.4128</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.24573</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57614</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2004</X>
<Y>0.4114</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.24577</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57615</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2013</X>
<Y>0.4100</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.24579</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57616</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2022</X>
<Y>0.4086</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.24589</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57617</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2031</X>
<Y>0.4071</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.24606</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57618</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2039</X>
<Y>0.4057</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.24643</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57619</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2048</X>
<Y>0.4042</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.24701</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57620</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2056</X>
<Y>0.4027</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.24778</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>21</dateDay>
<MJD>57621</MJD>
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<dataEOP><pole type="prediction"><X>0.2063</X>
<Y>0.4012</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.24868</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>22</dateDay>
<MJD>57622</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2070</X>
<Y>0.3997</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.24967</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57623</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2077</X>
<Y>0.3982</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.25074</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>24</dateDay>
<MJD>57624</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2084</X>
<Y>0.3967</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.25174</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>25</dateDay>
<MJD>57625</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2091</X>
<Y>0.3952</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.25257</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>26</dateDay>
<MJD>57626</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2097</X>
<Y>0.3936</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.25328</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>27</dateDay>
<MJD>57627</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2103</X>
<Y>0.3921</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.25387</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>28</dateDay>
<MJD>57628</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2108</X>
<Y>0.3905</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.25443</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>29</dateDay>
<MJD>57629</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2114</X>
<Y>0.3889</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.25494</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>30</dateDay>
<MJD>57630</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2119</X>
<Y>0.3873</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.25552</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>31</dateDay>
<MJD>57631</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2123</X>
<Y>0.3858</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.25617</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>09</dateMonth>
<dateDay>01</dateDay>
<MJD>57632</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2128</X>
<Y>0.3842</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.25694</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>09</dateMonth>
<dateDay>02</dateDay>
<MJD>57633</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2132</X>
<Y>0.3826</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.25777</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>09</dateMonth>
<dateDay>03</dateDay>
<MJD>57634</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2135</X>
<Y>0.3810</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.25869</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>04</dateDay>
<MJD>57635</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2139</X>
<Y>0.3794</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.25958</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>09</dateMonth>
<dateDay>05</dateDay>
<MJD>57636</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2142</X>
<Y>0.3777</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.26052</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>09</dateMonth>
<dateDay>06</dateDay>
<MJD>57637</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2145</X>
<Y>0.3761</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.26139</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>09</dateMonth>
<dateDay>07</dateDay>
<MJD>57638</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2148</X>
<Y>0.3745</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.26225</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>08</dateDay>
<MJD>57639</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2150</X>
<Y>0.3729</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.26310</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>09</dateDay>
<MJD>57640</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2152</X>
<Y>0.3712</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.26399</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>09</dateMonth>
<dateDay>10</dateDay>
<MJD>57641</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2154</X>
<Y>0.3696</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.26486</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>11</dateDay>
<MJD>57642</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2155</X>
<Y>0.3680</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.26580</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>12</dateDay>
<MJD>57643</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2156</X>
<Y>0.3663</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.26679</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>09</dateMonth>
<dateDay>13</dateDay>
<MJD>57644</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2157</X>
<Y>0.3647</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.26785</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>14</dateDay>
<MJD>57645</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2157</X>
<Y>0.3630</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.26904</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>15</dateDay>
<MJD>57646</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2157</X>
<Y>0.3614</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.27043</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>16</dateDay>
<MJD>57647</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2157</X>
<Y>0.3598</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.27196</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>17</dateDay>
<MJD>57648</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2157</X>
<Y>0.3581</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.27364</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>18</dateDay>
<MJD>57649</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2156</X>
<Y>0.3565</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.27543</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>19</dateDay>
<MJD>57650</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2155</X>
<Y>0.3548</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.27721</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>20</dateDay>
<MJD>57651</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2154</X>
<Y>0.3532</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.27887</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>21</dateDay>
<MJD>57652</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2152</X>
<Y>0.3516</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.28031</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>22</dateDay>
<MJD>57653</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2150</X>
<Y>0.3499</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.28157</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>23</dateDay>
<MJD>57654</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2148</X>
<Y>0.3483</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.28265</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>24</dateDay>
<MJD>57655</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2145</X>
<Y>0.3467</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.28364</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>25</dateDay>
<MJD>57656</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2142</X>
<Y>0.3450</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.28452</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>26</dateDay>
<MJD>57657</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2139</X>
<Y>0.3434</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.28539</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>27</dateDay>
<MJD>57658</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2136</X>
<Y>0.3418</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.28634</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>28</dateDay>
<MJD>57659</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2132</X>
<Y>0.3402</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.28738</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>29</dateDay>
<MJD>57660</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2128</X>
<Y>0.3386</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.28849</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>30</dateDay>
<MJD>57661</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2124</X>
<Y>0.3370</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.28971</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>01</dateDay>
<MJD>57662</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2119</X>
<Y>0.3354</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.29098</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>02</dateDay>
<MJD>57663</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2114</X>
<Y>0.3338</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.29221</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>10</dateMonth>
<dateDay>03</dateDay>
<MJD>57664</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2109</X>
<Y>0.3322</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.29342</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>04</dateDay>
<MJD>57665</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2103</X>
<Y>0.3307</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.29455</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57666</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2098</X>
<Y>0.3291</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.29558</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>06</dateDay>
<MJD>57667</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2092</X>
<Y>0.3276</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.29653</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>07</dateDay>
<MJD>57668</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2085</X>
<Y>0.3260</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.29731</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>08</dateDay>
<MJD>57669</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2079</X>
<Y>0.3245</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.29801</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>09</dateDay>
<MJD>57670</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2072</X>
<Y>0.3230</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.29870</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>10</dateDay>
<MJD>57671</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2065</X>
<Y>0.3215</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.29941</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57672</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2057</X>
<Y>0.3200</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.30028</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57673</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2050</X>
<Y>0.3185</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.30133</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57674</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2042</X>
<Y>0.3170</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.30265</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57675</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2033</X>
<Y>0.3155</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.30416</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57676</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2025</X>
<Y>0.3141</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.30593</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57677</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2016</X>
<Y>0.3126</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.30781</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57678</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2007</X>
<Y>0.3112</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.30969</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57679</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1998</X>
<Y>0.3098</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.31151</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>19</dateDay>
<MJD>57680</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1988</X>
<Y>0.3084</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.31321</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57681</MJD>
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<dataEOP><pole type="prediction"><X>0.1979</X>
<Y>0.3070</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.31474</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57682</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1969</X>
<Y>0.3056</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.31605</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>22</dateDay>
<MJD>57683</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1958</X>
<Y>0.3043</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.31723</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>23</dateDay>
<MJD>57684</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1948</X>
<Y>0.3029</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.31838</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>24</dateDay>
<MJD>57685</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1937</X>
<Y>0.3016</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.31946</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>25</dateDay>
<MJD>57686</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1926</X>
<Y>0.3003</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.32053</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>26</dateDay>
<MJD>57687</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1915</X>
<Y>0.2990</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.32160</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>27</dateDay>
<MJD>57688</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1904</X>
<Y>0.2977</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.32264</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57689</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1892</X>
<Y>0.2964</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.32375</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57690</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1880</X>
<Y>0.2952</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.32490</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>30</dateDay>
<MJD>57691</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1868</X>
<Y>0.2940</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.32608</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57692</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1856</X>
<Y>0.2928</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.32730</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>01</dateDay>
<MJD>57693</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1844</X>
<Y>0.2916</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.32848</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>02</dateDay>
<MJD>57694</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1831</X>
<Y>0.2904</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.32962</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>03</dateDay>
<MJD>57695</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1818</X>
<Y>0.2893</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.33076</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57696</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1805</X>
<Y>0.2881</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.33188</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57697</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1792</X>
<Y>0.2870</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.33301</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>06</dateDay>
<MJD>57698</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1778</X>
<Y>0.2859</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.33428</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>07</dateDay>
<MJD>57699</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1765</X>
<Y>0.2849</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.33560</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>08</dateDay>
<MJD>57700</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1751</X>
<Y>0.2838</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.33702</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>09</dateDay>
<MJD>57701</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1737</X>
<Y>0.2828</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.33855</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>10</dateDay>
<MJD>57702</MJD>
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<dataEOP><pole type="prediction"><X>0.1723</X>
<Y>0.2818</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.34028</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57703</MJD>
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<dataEOP><pole type="prediction"><X>0.1708</X>
<Y>0.2808</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.34215</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57704</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1694</X>
<Y>0.2798</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.34407</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>13</dateDay>
<MJD>57705</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1679</X>
<Y>0.2789</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.34605</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57706</MJD>
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<dataEOP><pole type="prediction"><X>0.1665</X>
<Y>0.2780</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.34794</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57707</MJD>
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<dataEOP><pole type="prediction"><X>0.1650</X>
<Y>0.2771</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.34971</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57708</MJD>
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<dataEOP><pole type="prediction"><X>0.1635</X>
<Y>0.2762</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.35135</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57709</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1619</X>
<Y>0.2753</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.35288</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57710</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1604</X>
<Y>0.2745</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.35426</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>19</dateDay>
<MJD>57711</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1588</X>
<Y>0.2737</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.35560</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>20</dateDay>
<MJD>57712</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1573</X>
<Y>0.2729</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.35693</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57713</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1557</X>
<Y>0.2721</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.35821</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57714</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1541</X>
<Y>0.2714</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.35949</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57715</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1525</X>
<Y>0.2707</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.36067</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>24</dateDay>
<MJD>57716</MJD>
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<dataEOP><pole type="prediction"><X>0.1509</X>
<Y>0.2700</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.36179</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>25</dateDay>
<MJD>57717</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1493</X>
<Y>0.2693</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.36288</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57718</MJD>
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<dataEOP><pole type="prediction"><X>0.1477</X>
<Y>0.2687</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.36387</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57719</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1460</X>
<Y>0.2681</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.36485</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>28</dateDay>
<MJD>57720</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1444</X>
<Y>0.2675</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.36572</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>29</dateDay>
<MJD>57721</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1427</X>
<Y>0.2669</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.36652</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>30</dateDay>
<MJD>57722</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1410</X>
<Y>0.2664</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.36724</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>01</dateDay>
<MJD>57723</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1394</X>
<Y>0.2659</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.36787</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>02</dateDay>
<MJD>57724</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1377</X>
<Y>0.2654</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.36848</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57725</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1360</X>
<Y>0.2649</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.36908</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57726</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1343</X>
<Y>0.2645</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.36972</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57727</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1326</X>
<Y>0.2640</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.37045</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57728</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1309</X>
<Y>0.2636</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.37139</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57729</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1292</X>
<Y>0.2633</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.37249</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57730</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1275</X>
<Y>0.2629</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.37374</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57731</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1258</X>
<Y>0.2626</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.37513</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57732</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1241</X>
<Y>0.2623</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.37664</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57733</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1223</X>
<Y>0.2621</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.37819</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57734</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1206</X>
<Y>0.2618</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.37965</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57735</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1189</X>
<Y>0.2616</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.38099</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57736</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1172</X>
<Y>0.2615</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.38223</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57737</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1154</X>
<Y>0.2613</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.38340</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57738</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1137</X>
<Y>0.2612</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.38458</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57739</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1120</X>
<Y>0.2611</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.38574</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>18</dateDay>
<MJD>57740</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1102</X>
<Y>0.2610</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.38689</UT1-UTC>
</UT>
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