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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57626</MJD>
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<dataEOP><pole type="prediction"><X>0.2383</X>
<Y>0.4024</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.24079</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57627</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2389</X>
<Y>0.4004</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.24161</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57628</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2394</X>
<Y>0.3985</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.24240</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57629</MJD>
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<dataEOP><pole type="prediction"><X>0.2398</X>
<Y>0.3966</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.24323</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57630</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2403</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.24413</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57631</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2407</X>
<Y>0.3927</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.24513</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57632</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2410</X>
<Y>0.3907</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.24625</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57633</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2414</X>
<Y>0.3887</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.24744</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57634</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2417</X>
<Y>0.3868</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.24869</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57635</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2419</X>
<Y>0.3848</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.24995</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57636</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2421</X>
<Y>0.3828</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.25119</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57637</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2423</X>
<Y>0.3808</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.25239</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57638</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2425</X>
<Y>0.3789</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.25353</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57639</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2426</X>
<Y>0.3769</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.25459</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57640</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2427</X>
<Y>0.3749</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.25560</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57641</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2427</X>
<Y>0.3729</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.25658</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57642</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2427</X>
<Y>0.3709</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.25756</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57643</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2427</X>
<Y>0.3689</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.25858</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57644</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2426</X>
<Y>0.3669</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.25970</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>0.2425</X>
<Y>0.3649</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.26097</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57646</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2423</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.26241</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57647</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2422</X>
<Y>0.3609</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.26404</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57648</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2419</X>
<Y>0.3590</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.26584</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57649</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2417</X>
<Y>0.3570</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.26773</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57650</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2414</X>
<Y>0.3550</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.26962</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57651</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2411</X>
<Y>0.3530</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.27142</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57652</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2407</X>
<Y>0.3511</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.27308</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57653</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2403</X>
<Y>0.3491</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.27459</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57654</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2399</X>
<Y>0.3471</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.27598</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57655</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2394</X>
<Y>0.3452</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.27728</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57656</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2389</X>
<Y>0.3432</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.27857</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57657</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2384</X>
<Y>0.3413</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.27989</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57658</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2378</X>
<Y>0.3394</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.28128</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57659</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2372</X>
<Y>0.3375</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.28274</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57660</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2366</X>
<Y>0.3355</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.28429</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57661</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2359</X>
<Y>0.3336</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.28588</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>0.2352</X>
<Y>0.3318</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.28749</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57663</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2345</X>
<Y>0.3299</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.28909</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57664</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2337</X>
<Y>0.3280</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.29065</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>0.2329</X>
<Y>0.3261</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.29215</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>0.2320</X>
<Y>0.3243</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.29359</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57667</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2312</X>
<Y>0.3225</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.29495</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57668</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2303</X>
<Y>0.3206</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.29627</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57669</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2293</X>
<Y>0.3188</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.29758</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57670</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2284</X>
<Y>0.3171</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.29891</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57671</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2273</X>
<Y>0.3153</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.30032</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>0.2263</X>
<Y>0.3135</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.30185</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57673</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2252</X>
<Y>0.3118</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.30355</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57674</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2241</X>
<Y>0.3100</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.30544</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57675</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2230</X>
<Y>0.3083</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.30753</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>0.2219</X>
<Y>0.3066</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.30976</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57677</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2207</X>
<Y>0.3050</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.31206</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57678</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2195</X>
<Y>0.3033</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.31432</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57679</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2182</X>
<Y>0.3017</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.31645</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57680</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2169</X>
<Y>0.3000</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.31842</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57681</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2156</X>
<Y>0.2984</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.32023</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>0.2143</X>
<Y>0.2969</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.32193</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57683</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2129</X>
<Y>0.2953</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.32356</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57684</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2115</X>
<Y>0.2937</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.32520</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57685</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2101</X>
<Y>0.2922</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.32688</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57686</MJD>
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<dataEOP><pole type="prediction"><X>0.2087</X>
<Y>0.2907</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.32861</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57687</MJD>
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<dataEOP><pole type="prediction"><X>0.2072</X>
<Y>0.2893</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.33039</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57688</MJD>
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<dataEOP><pole type="prediction"><X>0.2057</X>
<Y>0.2878</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.33221</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57689</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2042</X>
<Y>0.2864</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.33403</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57690</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2026</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.33583</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57691</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2011</X>
<Y>0.2836</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.33759</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57692</MJD>
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<dataEOP><pole type="prediction"><X>0.1995</X>
<Y>0.2822</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.33929</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<dataEOP><pole type="prediction"><X>0.1979</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.34091</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57694</MJD>
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<dataEOP><pole type="prediction"><X>0.1962</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.34245</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57695</MJD>
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<dataEOP><pole type="prediction"><X>0.1946</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.34392</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<dataEOP><pole type="prediction"><X>0.1929</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.34535</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<dataEOP><pole type="prediction"><X>0.1912</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.34678</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57698</MJD>
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<dataEOP><pole type="prediction"><X>0.1894</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.34826</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<dataEOP><pole type="prediction"><X>0.1877</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.34978</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57700</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1859</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.35144</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57701</MJD>
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<dataEOP><pole type="prediction"><X>0.1841</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.35326</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57702</MJD>
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<dataEOP><pole type="prediction"><X>0.1823</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.35526</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57703</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1805</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.35743</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57704</MJD>
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<dataEOP><pole type="prediction"><X>0.1786</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.35971</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57705</MJD>
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<dataEOP><pole type="prediction"><X>0.1768</X>
<Y>0.2669</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.36201</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<dataEOP><pole type="prediction"><X>0.1749</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.36425</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>0.1730</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.36636</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>0.1711</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.36830</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57709</MJD>
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<dataEOP><pole type="prediction"><X>0.1691</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.37011</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>0.1672</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.37182</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57711</MJD>
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<dataEOP><pole type="prediction"><X>0.1652</X>
<Y>0.2614</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.37351</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57712</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1633</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.37522</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57713</MJD>
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<dataEOP><pole type="prediction"><X>0.1613</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.37697</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57714</MJD>
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<dataEOP><pole type="prediction"><X>0.1593</X>
<Y>0.2590</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.37875</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57715</MJD>
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<dataEOP><pole type="prediction"><X>0.1573</X>
<Y>0.2583</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.38056</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57716</MJD>
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<dataEOP><pole type="prediction"><X>0.1552</X>
<Y>0.2576</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.38237</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57717</MJD>
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<dataEOP><pole type="prediction"><X>0.1532</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.38416</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>0.1512</X>
<Y>0.2563</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.38590</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57719</MJD>
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<dataEOP><pole type="prediction"><X>0.1491</X>
<Y>0.2557</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.38756</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57720</MJD>
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<dataEOP><pole type="prediction"><X>0.1470</X>
<Y>0.2551</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.38913</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57721</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1450</X>
<Y>0.2546</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.39062</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57722</MJD>
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<dataEOP><pole type="prediction"><X>0.1429</X>
<Y>0.2541</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.39201</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57723</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1408</X>
<Y>0.2536</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.39335</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57724</MJD>
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<dataEOP><pole type="prediction"><X>0.1387</X>
<Y>0.2532</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.39465</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>0.1366</X>
<Y>0.2528</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.39596</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57726</MJD>
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<dataEOP><pole type="prediction"><X>0.1345</X>
<Y>0.2524</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.39733</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57727</MJD>
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<dataEOP><pole type="prediction"><X>0.1324</X>
<Y>0.2521</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.39879</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57728</MJD>
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<dataEOP><pole type="prediction"><X>0.1302</X>
<Y>0.2517</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.40039</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57729</MJD>
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<dataEOP><pole type="prediction"><X>0.1281</X>
<Y>0.2515</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.40213</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57730</MJD>
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<dataEOP><pole type="prediction"><X>0.1260</X>
<Y>0.2512</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.40402</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57731</MJD>
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<dataEOP><pole type="prediction"><X>0.1239</X>
<Y>0.2510</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.40603</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>0.1217</X>
<Y>0.2508</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.40810</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57733</MJD>
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<dataEOP><pole type="prediction"><X>0.1196</X>
<Y>0.2507</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.41014</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>0.1175</X>
<Y>0.2506</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.41210</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57735</MJD>
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<dataEOP><pole type="prediction"><X>0.1153</X>
<Y>0.2505</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.41393</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57736</MJD>
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<dataEOP><pole type="prediction"><X>0.1132</X>
<Y>0.2504</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.41561</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57737</MJD>
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<dataEOP><pole type="prediction"><X>0.1111</X>
<Y>0.2504</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.41719</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57738</MJD>
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<dataEOP><pole type="prediction"><X>0.1089</X>
<Y>0.2504</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.41874</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57739</MJD>
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<dataEOP><pole type="prediction"><X>0.1068</X>
<Y>0.2505</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.42029</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57740</MJD>
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<dataEOP><pole type="prediction"><X>0.1047</X>
<Y>0.2506</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.42188</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57741</MJD>
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<dataEOP><pole type="prediction"><X>0.1025</X>
<Y>0.2507</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.42352</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57742</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1004</X>
<Y>0.2508</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.42518</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57743</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0983</X>
<Y>0.2510</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.42685</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57744</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0962</X>
<Y>0.2512</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.42849</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57745</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0941</X>
<Y>0.2515</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.43008</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57746</MJD>
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<dataEOP><pole type="prediction"><X>0.0920</X>
<Y>0.2517</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.43160</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57747</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0899</X>
<Y>0.2520</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.43303</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>26</dateDay>
<MJD>57748</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0878</X>
<Y>0.2524</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.43436</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>27</dateDay>
<MJD>57749</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0857</X>
<Y>0.2528</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.43561</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>28</dateDay>
<MJD>57750</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0837</X>
<Y>0.2532</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.43679</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>12</dateMonth>
<dateDay>29</dateDay>
<MJD>57751</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0816</X>
<Y>0.2536</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.43793</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>12</dateMonth>
<dateDay>30</dateDay>
<MJD>57752</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0795</X>
<Y>0.2541</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.43907</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>12</dateMonth>
<dateDay>31</dateDay>
<MJD>57753</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0775</X>
<Y>0.2546</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.44025</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>01</dateDay>
<MJD>57754</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0755</X>
<Y>0.2551</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.55848</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>02</dateDay>
<MJD>57755</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0734</X>
<Y>0.2557</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.55709</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>03</dateDay>
<MJD>57756</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0714</X>
<Y>0.2563</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.55556</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>04</dateDay>
<MJD>57757</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0694</X>
<Y>0.2569</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.55389</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>05</dateDay>
<MJD>57758</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0675</X>
<Y>0.2575</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.55212</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>06</dateDay>
<MJD>57759</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0655</X>
<Y>0.2582</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.55029</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>07</dateDay>
<MJD>57760</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0635</X>
<Y>0.2589</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.54846</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>08</dateDay>
<MJD>57761</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0616</X>
<Y>0.2597</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.54668</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>09</dateDay>
<MJD>57762</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0597</X>
<Y>0.2605</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.54502</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>10</dateDay>
<MJD>57763</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0578</X>
<Y>0.2613</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.54347</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>11</dateDay>
<MJD>57764</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0559</X>
<Y>0.2621</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.54203</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>12</dateDay>
<MJD>57765</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0540</X>
<Y>0.2630</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.54064</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>13</dateDay>
<MJD>57766</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0521</X>
<Y>0.2639</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.53924</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>14</dateDay>
<MJD>57767</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0503</X>
<Y>0.2648</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.53779</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>15</dateDay>
<MJD>57768</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0485</X>
<Y>0.2657</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.53628</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>16</dateDay>
<MJD>57769</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0466</X>
<Y>0.2667</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.53472</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>17</dateDay>
<MJD>57770</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0449</X>
<Y>0.2677</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.53314</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>18</dateDay>
<MJD>57771</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0431</X>
<Y>0.2688</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.53158</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>19</dateDay>
<MJD>57772</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0413</X>
<Y>0.2698</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.53006</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>20</dateDay>
<MJD>57773</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0396</X>
<Y>0.2709</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.52861</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>21</dateDay>
<MJD>57774</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0379</X>
<Y>0.2720</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.52725</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>22</dateDay>
<MJD>57775</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0362</X>
<Y>0.2732</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.52598</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>23</dateDay>
<MJD>57776</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0346</X>
<Y>0.2743</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.52481</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>24</dateDay>
<MJD>57777</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0329</X>
<Y>0.2755</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.52371</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>25</dateDay>
<MJD>57778</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0313</X>
<Y>0.2767</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.52266</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2017</dateYear>
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<dateDay>26</dateDay>
<MJD>57779</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0297</X>
<Y>0.2780</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.52162</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2017</dateYear>
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<dateDay>27</dateDay>
<MJD>57780</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0282</X>
<Y>0.2792</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.52054</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>28</dateDay>
<MJD>57781</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0266</X>
<Y>0.2805</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.51939</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>29</dateDay>
<MJD>57782</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0251</X>
<Y>0.2818</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.51811</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>30</dateDay>
<MJD>57783</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0236</X>
<Y>0.2832</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.51670</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>31</dateDay>
<MJD>57784</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0221</X>
<Y>0.2845</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.51514</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>02</dateMonth>
<dateDay>01</dateDay>
<MJD>57785</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0207</X>
<Y>0.2859</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.51346</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>02</dateMonth>
<dateDay>02</dateDay>
<MJD>57786</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0193</X>
<Y>0.2873</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.51172</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>02</dateMonth>
<dateDay>03</dateDay>
<MJD>57787</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0179</X>
<Y>0.2888</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.50996</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>02</dateMonth>
<dateDay>04</dateDay>
<MJD>57788</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0165</X>
<Y>0.2902</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.50822</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>02</dateMonth>
<dateDay>05</dateDay>
<MJD>57789</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0152</X>
<Y>0.2917</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.50653</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>02</dateMonth>
<dateDay>06</dateDay>
<MJD>57790</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0139</X>
<Y>0.2932</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.50491</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2017</dateYear>
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<dateDay>07</dateDay>
<MJD>57791</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0126</X>
<Y>0.2947</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.50333</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>02</dateMonth>
<dateDay>08</dateDay>
<MJD>57792</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0113</X>
<Y>0.2962</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.50174</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>02</dateMonth>
<dateDay>09</dateDay>
<MJD>57793</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0101</X>
<Y>0.2978</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.50008</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>02</dateMonth>
<dateDay>10</dateDay>
<MJD>57794</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0089</X>
<Y>0.2993</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.49830</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>02</dateMonth>
<dateDay>11</dateDay>
<MJD>57795</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0078</X>
<Y>0.3009</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.49638</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>02</dateMonth>
<dateDay>12</dateDay>
<MJD>57796</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0066</X>
<Y>0.3025</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.49433</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>02</dateMonth>
<dateDay>13</dateDay>
<MJD>57797</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0055</X>
<Y>0.3042</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.49218</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>02</dateMonth>
<dateDay>14</dateDay>
<MJD>57798</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0045</X>
<Y>0.3058</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.48997</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>02</dateMonth>
<dateDay>15</dateDay>
<MJD>57799</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0034</X>
<Y>0.3075</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.48773</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>02</dateMonth>
<dateDay>16</dateDay>
<MJD>57800</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0024</X>
<Y>0.3091</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.48551</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>02</dateMonth>
<dateDay>17</dateDay>
<MJD>57801</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0014</X>
<Y>0.3108</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.48332</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>02</dateMonth>
<dateDay>18</dateDay>
<MJD>57802</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0005</X>
<Y>0.3125</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.48119</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>02</dateMonth>
<dateDay>19</dateDay>
<MJD>57803</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0004</X>
<Y>0.3143</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.47912</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>02</dateMonth>
<dateDay>20</dateDay>
<MJD>57804</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0013</X>
<Y>0.3160</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.47711</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>02</dateMonth>
<dateDay>21</dateDay>
<MJD>57805</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0022</X>
<Y>0.3177</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.47516</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>02</dateMonth>
<dateDay>22</dateDay>
<MJD>57806</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0030</X>
<Y>0.3195</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.47324</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>02</dateMonth>
<dateDay>23</dateDay>
<MJD>57807</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0038</X>
<Y>0.3213</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.47133</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>02</dateMonth>
<dateDay>24</dateDay>
<MJD>57808</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0046</X>
<Y>0.3231</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.46937</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>02</dateMonth>
<dateDay>25</dateDay>
<MJD>57809</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0053</X>
<Y>0.3249</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.46733</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>02</dateMonth>
<dateDay>26</dateDay>
<MJD>57810</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0060</X>
<Y>0.3267</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.46519</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>02</dateMonth>
<dateDay>27</dateDay>
<MJD>57811</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0066</X>
<Y>0.3285</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.46294</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>02</dateMonth>
<dateDay>28</dateDay>
<MJD>57812</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0072</X>
<Y>0.3303</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.46059</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>03</dateMonth>
<dateDay>01</dateDay>
<MJD>57813</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0078</X>
<Y>0.3322</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.45823</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>03</dateMonth>
<dateDay>02</dateDay>
<MJD>57814</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0084</X>
<Y>0.3340</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.45592</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>03</dateMonth>
<dateDay>03</dateDay>
<MJD>57815</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0089</X>
<Y>0.3359</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.45362</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>03</dateMonth>
<dateDay>04</dateDay>
<MJD>57816</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0094</X>
<Y>0.3377</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.45153</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>03</dateMonth>
<dateDay>05</dateDay>
<MJD>57817</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0098</X>
<Y>0.3396</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.44952</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>03</dateMonth>
<dateDay>06</dateDay>
<MJD>57818</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0103</X>
<Y>0.3415</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.44755</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>03</dateMonth>
<dateDay>07</dateDay>
<MJD>57819</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0106</X>
<Y>0.3434</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.44568</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>03</dateMonth>
<dateDay>08</dateDay>
<MJD>57820</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0110</X>
<Y>0.3453</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.44384</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>03</dateMonth>
<dateDay>09</dateDay>
<MJD>57821</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0113</X>
<Y>0.3472</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.44198</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>03</dateMonth>
<dateDay>10</dateDay>
<MJD>57822</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0116</X>
<Y>0.3491</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.44014</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>03</dateMonth>
<dateDay>11</dateDay>
<MJD>57823</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0118</X>
<Y>0.3510</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.43820</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>03</dateMonth>
<dateDay>12</dateDay>
<MJD>57824</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0120</X>
<Y>0.3529</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.43617</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>03</dateMonth>
<dateDay>13</dateDay>
<MJD>57825</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0122</X>
<Y>0.3548</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.43407</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>03</dateMonth>
<dateDay>14</dateDay>
<MJD>57826</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0124</X>
<Y>0.3567</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.43196</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>03</dateMonth>
<dateDay>15</dateDay>
<MJD>57827</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0125</X>
<Y>0.3586</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.42989</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>03</dateMonth>
<dateDay>16</dateDay>
<MJD>57828</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0125</X>
<Y>0.3606</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.42779</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>03</dateMonth>
<dateDay>17</dateDay>
<MJD>57829</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0126</X>
<Y>0.3625</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.42579</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>03</dateMonth>
<dateDay>18</dateDay>
<MJD>57830</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0126</X>
<Y>0.3644</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.42387</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>03</dateMonth>
<dateDay>19</dateDay>
<MJD>57831</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0125</X>
<Y>0.3663</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.42198</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>03</dateMonth>
<dateDay>20</dateDay>
<MJD>57832</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0125</X>
<Y>0.3683</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.42016</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>03</dateMonth>
<dateDay>21</dateDay>
<MJD>57833</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0124</X>
<Y>0.3702</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.41846</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>03</dateMonth>
<dateDay>22</dateDay>
<MJD>57834</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0122</X>
<Y>0.3721</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.41677</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>03</dateMonth>
<dateDay>23</dateDay>
<MJD>57835</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0121</X>
<Y>0.3740</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.41508</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>03</dateMonth>
<dateDay>24</dateDay>
<MJD>57836</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0118</X>
<Y>0.3759</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.41326</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>03</dateMonth>
<dateDay>25</dateDay>
<MJD>57837</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0116</X>
<Y>0.3779</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.41128</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>03</dateMonth>
<dateDay>26</dateDay>
<MJD>57838</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0113</X>
<Y>0.3798</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.40911</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>03</dateMonth>
<dateDay>27</dateDay>
<MJD>57839</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0110</X>
<Y>0.3817</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.40681</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>03</dateMonth>
<dateDay>28</dateDay>
<MJD>57840</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0107</X>
<Y>0.3836</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.40441</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>03</dateMonth>
<dateDay>29</dateDay>
<MJD>57841</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0103</X>
<Y>0.3855</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.40199</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>03</dateMonth>
<dateDay>30</dateDay>
<MJD>57842</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0099</X>
<Y>0.3874</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.39969</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>03</dateMonth>
<dateDay>31</dateDay>
<MJD>57843</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0094</X>
<Y>0.3893</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.39758</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>01</dateDay>
<MJD>57844</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0090</X>
<Y>0.3911</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.39565</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>02</dateDay>
<MJD>57845</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0084</X>
<Y>0.3930</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.39386</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>03</dateDay>
<MJD>57846</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0079</X>
<Y>0.3949</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.39225</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>04</dateDay>
<MJD>57847</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0073</X>
<Y>0.3967</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.39072</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>05</dateDay>
<MJD>57848</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0067</X>
<Y>0.3986</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.38927</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>06</dateDay>
<MJD>57849</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0061</X>
<Y>0.4004</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.38773</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>07</dateDay>
<MJD>57850</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0054</X>
<Y>0.4023</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.38614</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>08</dateDay>
<MJD>57851</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0047</X>
<Y>0.4041</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.38443</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>09</dateDay>
<MJD>57852</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0039</X>
<Y>0.4059</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.38260</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>10</dateDay>
<MJD>57853</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0032</X>
<Y>0.4077</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.38069</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>11</dateDay>
<MJD>57854</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0023</X>
<Y>0.4095</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.37877</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>12</dateDay>
<MJD>57855</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0015</X>
<Y>0.4112</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.37690</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>13</dateDay>
<MJD>57856</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0006</X>
<Y>0.4130</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.37507</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>14</dateDay>
<MJD>57857</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0003</X>
<Y>0.4147</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.37342</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>15</dateDay>
<MJD>57858</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0012</X>
<Y>0.4165</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.37188</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>16</dateDay>
<MJD>57859</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0022</X>
<Y>0.4182</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.37045</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>17</dateDay>
<MJD>57860</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0031</X>
<Y>0.4199</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.36910</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>18</dateDay>
<MJD>57861</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0042</X>
<Y>0.4216</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.36779</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>19</dateDay>
<MJD>57862</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0052</X>
<Y>0.4233</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.36644</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>20</dateDay>
<MJD>57863</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0063</X>
<Y>0.4249</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.36502</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>21</dateDay>
<MJD>57864</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0074</X>
<Y>0.4266</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.36349</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>22</dateDay>
<MJD>57865</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0085</X>
<Y>0.4282</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.36188</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>23</dateDay>
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<UT type="prediction"><UT1-UTC>0.36013</UT1-UTC>
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<timeSeries><time><dateYear>2017</dateYear>
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<UT type="prediction"><UT1-UTC>0.35819</UT1-UTC>
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<timeSeries><time><dateYear>2017</dateYear>
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<UT type="prediction"><UT1-UTC>0.35609</UT1-UTC>
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<timeSeries><time><dateYear>2017</dateYear>
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<UT type="prediction"><UT1-UTC>0.35392</UT1-UTC>
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<timeSeries><time><dateYear>2017</dateYear>
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<UT type="prediction"><UT1-UTC>0.35183</UT1-UTC>
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<timeSeries><time><dateYear>2017</dateYear>
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<UT type="prediction"><UT1-UTC>0.34984</UT1-UTC>
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<timeSeries><time><dateYear>2017</dateYear>
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<UT type="prediction"><UT1-UTC>0.34802</UT1-UTC>
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<timeSeries><time><dateYear>2017</dateYear>
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<UT type="prediction"><UT1-UTC>0.34627</UT1-UTC>
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<UT type="prediction"><UT1-UTC>0.34463</UT1-UTC>
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<UT type="prediction"><UT1-UTC>0.34304</UT1-UTC>
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<timeSeries><time><dateYear>2017</dateYear>
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<UT type="prediction"><UT1-UTC>0.34146</UT1-UTC>
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<timeSeries><time><dateYear>2017</dateYear>
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<UT type="prediction"><UT1-UTC>0.33984</UT1-UTC>
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<UT type="prediction"><UT1-UTC>0.33818</UT1-UTC>
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<timeSeries><time><dateYear>2017</dateYear>
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<UT type="prediction"><UT1-UTC>0.33652</UT1-UTC>
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<timeSeries><time><dateYear>2017</dateYear>
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<UT type="prediction"><UT1-UTC>0.33487</UT1-UTC>
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<timeSeries><time><dateYear>2017</dateYear>
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<UT type="prediction"><UT1-UTC>0.33320</UT1-UTC>
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<timeSeries><time><dateYear>2017</dateYear>
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<UT type="prediction"><UT1-UTC>0.33151</UT1-UTC>
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<timeSeries><time><dateYear>2017</dateYear>
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<UT type="prediction"><UT1-UTC>0.32987</UT1-UTC>
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<timeSeries><time><dateYear>2017</dateYear>
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<UT type="prediction"><UT1-UTC>0.32842</UT1-UTC>
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<timeSeries><time><dateYear>2017</dateYear>
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<UT type="prediction"><UT1-UTC>0.32719</UT1-UTC>
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<UT type="prediction"><UT1-UTC>0.32612</UT1-UTC>
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<UT type="prediction"><UT1-UTC>0.32505</UT1-UTC>
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<UT type="prediction"><UT1-UTC>0.32395</UT1-UTC>
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<UT type="prediction"><UT1-UTC>0.32292</UT1-UTC>
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<UT type="prediction"><UT1-UTC>0.32188</UT1-UTC>
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<UT type="prediction"><UT1-UTC>0.32079</UT1-UTC>
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<UT type="prediction"><UT1-UTC>0.31956</UT1-UTC>
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<UT type="prediction"><UT1-UTC>0.31825</UT1-UTC>
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<UT type="prediction"><UT1-UTC>0.31676</UT1-UTC>
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<UT type="prediction"><UT1-UTC>0.31515</UT1-UTC>
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<UT type="prediction"><UT1-UTC>0.31349</UT1-UTC>
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<UT type="prediction"><UT1-UTC>0.31193</UT1-UTC>
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<UT type="prediction"><UT1-UTC>0.31049</UT1-UTC>
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<UT type="prediction"><UT1-UTC>0.30920</UT1-UTC>
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<UT type="prediction"><UT1-UTC>0.30801</UT1-UTC>
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<UT type="prediction"><UT1-UTC>0.30688</UT1-UTC>
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<UT type="prediction"><UT1-UTC>0.30579</UT1-UTC>
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<UT type="prediction"><UT1-UTC>0.30466</UT1-UTC>
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<UT type="prediction"><UT1-UTC>0.30345</UT1-UTC>
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<UT type="prediction"><UT1-UTC>0.30220</UT1-UTC>
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<UT type="prediction"><UT1-UTC>0.30095</UT1-UTC>
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<UT type="prediction"><UT1-UTC>0.29973</UT1-UTC>
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<UT type="prediction"><UT1-UTC>0.29851</UT1-UTC>
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<UT type="prediction"><UT1-UTC>0.29731</UT1-UTC>
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<UT type="prediction"><UT1-UTC>0.29620</UT1-UTC>
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<UT type="prediction"><UT1-UTC>0.29519</UT1-UTC>
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<UT type="prediction"><UT1-UTC>0.29437</UT1-UTC>
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<UT type="prediction"><UT1-UTC>0.29367</UT1-UTC>
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<UT type="prediction"><UT1-UTC>0.29310</UT1-UTC>
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<UT type="prediction"><UT1-UTC>0.29259</UT1-UTC>
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<UT type="prediction"><UT1-UTC>0.29205</UT1-UTC>
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<UT type="prediction"><UT1-UTC>0.29149</UT1-UTC>
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<UT type="prediction"><UT1-UTC>0.29083</UT1-UTC>
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<UT type="prediction"><UT1-UTC>0.29005</UT1-UTC>
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<UT type="prediction"><UT1-UTC>0.28919</UT1-UTC>
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<UT type="prediction"><UT1-UTC>0.28826</UT1-UTC>
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<UT type="prediction"><UT1-UTC>0.28712</UT1-UTC>
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<dataEOP><pole type="prediction"><X>0.1083</X>
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<UT type="prediction"><UT1-UTC>0.28584</UT1-UTC>
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<dataEOP><pole type="prediction"><X>0.1103</X>
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<UT type="prediction"><UT1-UTC>0.28451</UT1-UTC>
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<dataEOP><pole type="prediction"><X>0.1123</X>
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</pole>
<UT type="prediction"><UT1-UTC>0.28318</UT1-UTC>
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