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</time>
<dataEOP><pole type="prediction"><X>0.0604</X>
<Y>0.2605</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.09402</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2015</dateYear>
<dateMonth>12</dateMonth>
<dateDay>31</dateDay>
<MJD>57387</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0588</X>
<Y>0.2611</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.09267</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>01</dateMonth>
<dateDay>01</dateDay>
<MJD>57388</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0572</X>
<Y>0.2617</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.09131</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>01</dateMonth>
<dateDay>02</dateDay>
<MJD>57389</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0555</X>
<Y>0.2624</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.08994</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>01</dateMonth>
<dateDay>03</dateDay>
<MJD>57390</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0540</X>
<Y>0.2630</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.08860</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>01</dateMonth>
<dateDay>04</dateDay>
<MJD>57391</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0524</X>
<Y>0.2637</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.08731</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>01</dateMonth>
<dateDay>05</dateDay>
<MJD>57392</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0508</X>
<Y>0.2644</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.08608</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>01</dateMonth>
<dateDay>06</dateDay>
<MJD>57393</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0493</X>
<Y>0.2652</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.08491</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>01</dateMonth>
<dateDay>07</dateDay>
<MJD>57394</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0477</X>
<Y>0.2660</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.08380</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>01</dateMonth>
<dateDay>08</dateDay>
<MJD>57395</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0462</X>
<Y>0.2667</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.08271</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>01</dateMonth>
<dateDay>09</dateDay>
<MJD>57396</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0447</X>
<Y>0.2675</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.08162</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>01</dateMonth>
<dateDay>10</dateDay>
<MJD>57397</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0432</X>
<Y>0.2684</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.08048</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>01</dateMonth>
<dateDay>11</dateDay>
<MJD>57398</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0417</X>
<Y>0.2692</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.07923</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>01</dateMonth>
<dateDay>12</dateDay>
<MJD>57399</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0403</X>
<Y>0.2701</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.07785</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>01</dateMonth>
<dateDay>13</dateDay>
<MJD>57400</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0388</X>
<Y>0.2710</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.07631</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>01</dateMonth>
<dateDay>14</dateDay>
<MJD>57401</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0374</X>
<Y>0.2719</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.07463</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>01</dateMonth>
<dateDay>15</dateDay>
<MJD>57402</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0360</X>
<Y>0.2728</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.07285</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>01</dateMonth>
<dateDay>16</dateDay>
<MJD>57403</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0346</X>
<Y>0.2738</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.07105</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>01</dateMonth>
<dateDay>17</dateDay>
<MJD>57404</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0332</X>
<Y>0.2748</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.06928</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>01</dateMonth>
<dateDay>18</dateDay>
<MJD>57405</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0319</X>
<Y>0.2758</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.06760</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>01</dateMonth>
<dateDay>19</dateDay>
<MJD>57406</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0305</X>
<Y>0.2768</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.06603</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>01</dateMonth>
<dateDay>20</dateDay>
<MJD>57407</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0292</X>
<Y>0.2779</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.06459</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>01</dateMonth>
<dateDay>21</dateDay>
<MJD>57408</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0279</X>
<Y>0.2789</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.06324</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>01</dateMonth>
<dateDay>22</dateDay>
<MJD>57409</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0266</X>
<Y>0.2800</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.06195</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>01</dateMonth>
<dateDay>23</dateDay>
<MJD>57410</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0254</X>
<Y>0.2811</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.06067</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>01</dateMonth>
<dateDay>24</dateDay>
<MJD>57411</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0241</X>
<Y>0.2822</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.05935</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>01</dateMonth>
<dateDay>25</dateDay>
<MJD>57412</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0229</X>
<Y>0.2834</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.05798</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>01</dateMonth>
<dateDay>26</dateDay>
<MJD>57413</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0217</X>
<Y>0.2845</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.05654</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>01</dateMonth>
<dateDay>27</dateDay>
<MJD>57414</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0205</X>
<Y>0.2857</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.05504</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>01</dateMonth>
<dateDay>28</dateDay>
<MJD>57415</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0194</X>
<Y>0.2869</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.05350</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>01</dateMonth>
<dateDay>29</dateDay>
<MJD>57416</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0183</X>
<Y>0.2881</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.05195</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>01</dateMonth>
<dateDay>30</dateDay>
<MJD>57417</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0172</X>
<Y>0.2894</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.05040</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>01</dateMonth>
<dateDay>31</dateDay>
<MJD>57418</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0161</X>
<Y>0.2906</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.04887</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>02</dateMonth>
<dateDay>01</dateDay>
<MJD>57419</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0150</X>
<Y>0.2919</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.04739</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>02</dateMonth>
<dateDay>02</dateDay>
<MJD>57420</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0140</X>
<Y>0.2931</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.04596</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>02</dateMonth>
<dateDay>03</dateDay>
<MJD>57421</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0130</X>
<Y>0.2944</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.04458</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>02</dateMonth>
<dateDay>04</dateDay>
<MJD>57422</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0120</X>
<Y>0.2958</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.04323</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>02</dateMonth>
<dateDay>05</dateDay>
<MJD>57423</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0110</X>
<Y>0.2971</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.04188</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>02</dateMonth>
<dateDay>06</dateDay>
<MJD>57424</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0101</X>
<Y>0.2984</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.04050</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>02</dateMonth>
<dateDay>07</dateDay>
<MJD>57425</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0092</X>
<Y>0.2998</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.03902</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>02</dateMonth>
<dateDay>08</dateDay>
<MJD>57426</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0083</X>
<Y>0.3012</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.03740</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>02</dateMonth>
<dateDay>09</dateDay>
<MJD>57427</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0074</X>
<Y>0.3025</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.03560</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>02</dateMonth>
<dateDay>10</dateDay>
<MJD>57428</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0066</X>
<Y>0.3039</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.03364</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>02</dateMonth>
<dateDay>11</dateDay>
<MJD>57429</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0058</X>
<Y>0.3054</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.03154</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>02</dateMonth>
<dateDay>12</dateDay>
<MJD>57430</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0050</X>
<Y>0.3068</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.02938</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>02</dateMonth>
<dateDay>13</dateDay>
<MJD>57431</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0042</X>
<Y>0.3082</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.02725</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>02</dateMonth>
<dateDay>14</dateDay>
<MJD>57432</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0035</X>
<Y>0.3097</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.02522</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>02</dateMonth>
<dateDay>15</dateDay>
<MJD>57433</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0028</X>
<Y>0.3111</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.02332</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>02</dateMonth>
<dateDay>16</dateDay>
<MJD>57434</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0021</X>
<Y>0.3126</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.02155</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>02</dateMonth>
<dateDay>17</dateDay>
<MJD>57435</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0015</X>
<Y>0.3141</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.01990</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>02</dateMonth>
<dateDay>18</dateDay>
<MJD>57436</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0008</X>
<Y>0.3156</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.01832</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>02</dateMonth>
<dateDay>19</dateDay>
<MJD>57437</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0002</X>
<Y>0.3171</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.01676</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>02</dateMonth>
<dateDay>20</dateDay>
<MJD>57438</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0003</X>
<Y>0.3186</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.01518</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>02</dateMonth>
<dateDay>21</dateDay>
<MJD>57439</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0009</X>
<Y>0.3201</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.01354</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>02</dateMonth>
<dateDay>22</dateDay>
<MJD>57440</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0014</X>
<Y>0.3216</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.01183</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>02</dateMonth>
<dateDay>23</dateDay>
<MJD>57441</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0018</X>
<Y>0.3232</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.01005</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>02</dateMonth>
<dateDay>24</dateDay>
<MJD>57442</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0023</X>
<Y>0.3247</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.00822</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>02</dateMonth>
<dateDay>25</dateDay>
<MJD>57443</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0027</X>
<Y>0.3263</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.00636</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>02</dateMonth>
<dateDay>26</dateDay>
<MJD>57444</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0031</X>
<Y>0.3278</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.00450</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>02</dateMonth>
<dateDay>27</dateDay>
<MJD>57445</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0035</X>
<Y>0.3294</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.00267</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>02</dateMonth>
<dateDay>28</dateDay>
<MJD>57446</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0038</X>
<Y>0.3310</Y>
</pole>
<UT type="prediction"><UT1-UTC>0.00090</UT1-UTC>
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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>-0.0041</X>
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<UT type="prediction"><UT1-UTC>-0.00080</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>-0.0044</X>
<Y>0.3342</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.00244</UT1-UTC>
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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>-0.0047</X>
<Y>0.3357</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.00403</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>-0.0049</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.00559</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57451</MJD>
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<dataEOP><pole type="prediction"><X>-0.0051</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.00717</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57452</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0053</X>
<Y>0.3405</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.00881</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57453</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0054</X>
<Y>0.3421</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.01058</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>-0.0055</X>
<Y>0.3437</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.01252</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57455</MJD>
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<dataEOP><pole type="prediction"><X>-0.0056</X>
<Y>0.3454</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.01464</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57456</MJD>
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<dataEOP><pole type="prediction"><X>-0.0056</X>
<Y>0.3470</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.01695</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>-0.0056</X>
<Y>0.3486</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.01936</UT1-UTC>
</UT>
</dataEOP>
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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>-0.0056</X>
<Y>0.3502</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.02180</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57459</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0056</X>
<Y>0.3518</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.02416</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57460</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0055</X>
<Y>0.3534</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.02638</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57461</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0054</X>
<Y>0.3550</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.02841</UT1-UTC>
</UT>
</dataEOP>
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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>-0.0053</X>
<Y>0.3566</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.03030</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>-0.0051</X>
<Y>0.3583</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.03207</UT1-UTC>
</UT>
</dataEOP>
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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>-0.0049</X>
<Y>0.3599</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.03379</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57465</MJD>
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<dataEOP><pole type="prediction"><X>-0.0047</X>
<Y>0.3615</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.03550</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57466</MJD>
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<dataEOP><pole type="prediction"><X>-0.0045</X>
<Y>0.3631</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.03724</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>-0.0042</X>
<Y>0.3647</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.03904</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57468</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0039</X>
<Y>0.3663</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.04090</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57469</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0036</X>
<Y>0.3679</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.04281</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57470</MJD>
</time>
<dataEOP><pole type="prediction"><X>-0.0032</X>
<Y>0.3695</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.04475</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57471</MJD>
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<dataEOP><pole type="prediction"><X>-0.0028</X>
<Y>0.3711</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.04670</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>-0.0024</X>
<Y>0.3726</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.04863</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>-0.0019</X>
<Y>0.3742</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.05051</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>-0.0015</X>
<Y>0.3758</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.05233</UT1-UTC>
</UT>
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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>-0.0010</X>
<Y>0.3774</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.05408</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>-0.0004</X>
<Y>0.3789</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.05576</UT1-UTC>
</UT>
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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>0.0001</X>
<Y>0.3805</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.05740</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57478</MJD>
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<dataEOP><pole type="prediction"><X>0.0007</X>
<Y>0.3820</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.05903</UT1-UTC>
</UT>
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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>0.0013</X>
<Y>0.3835</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.06069</UT1-UTC>
</UT>
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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>0.0020</X>
<Y>0.3851</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.06244</UT1-UTC>
</UT>
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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>0.0027</X>
<Y>0.3866</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.06433</UT1-UTC>
</UT>
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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>0.0034</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.06641</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>0.0041</X>
<Y>0.3896</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.06867</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57484</MJD>
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<dataEOP><pole type="prediction"><X>0.0048</X>
<Y>0.3911</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.07109</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57485</MJD>
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<dataEOP><pole type="prediction"><X>0.0056</X>
<Y>0.3926</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.07359</UT1-UTC>
</UT>
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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>0.0064</X>
<Y>0.3940</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.07606</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57487</MJD>
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<dataEOP><pole type="prediction"><X>0.0073</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.07842</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>0.0081</X>
<Y>0.3969</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.08060</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57489</MJD>
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<dataEOP><pole type="prediction"><X>0.0090</X>
<Y>0.3984</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.08260</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57490</MJD>
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<dataEOP><pole type="prediction"><X>0.0099</X>
<Y>0.3998</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.08444</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57491</MJD>
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<dataEOP><pole type="prediction"><X>0.0109</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.08618</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>0.0118</X>
<Y>0.4026</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.08788</UT1-UTC>
</UT>
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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>0.0128</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.08958</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>0.0138</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.09130</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>0.0149</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.09306</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>0.0159</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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<MJD>57497</MJD>
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<dataEOP><pole type="prediction"><X>0.0170</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.09668</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>0.0181</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.09849</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57499</MJD>
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<dataEOP><pole type="prediction"><X>0.0193</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.10028</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57500</MJD>
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<dataEOP><pole type="prediction"><X>0.0204</X>
<Y>0.4132</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.10201</UT1-UTC>
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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>0.0216</X>
<Y>0.4145</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.10366</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57502</MJD>
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<dataEOP><pole type="prediction"><X>0.0228</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.10524</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57503</MJD>
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<dataEOP><pole type="prediction"><X>0.0240</X>
<Y>0.4169</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.10672</UT1-UTC>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57504</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0252</X>
<Y>0.4181</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.10813</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>0.0265</X>
<Y>0.4193</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.10950</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>0.0278</X>
<Y>0.4205</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.11086</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>04</dateMonth>
<dateDay>29</dateDay>
<MJD>57507</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0291</X>
<Y>0.4216</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.11227</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>04</dateMonth>
<dateDay>30</dateDay>
<MJD>57508</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0304</X>
<Y>0.4228</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.11378</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>05</dateMonth>
<dateDay>01</dateDay>
<MJD>57509</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0318</X>
<Y>0.4239</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.11542</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>05</dateMonth>
<dateDay>02</dateDay>
<MJD>57510</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0331</X>
<Y>0.4250</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.11723</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>05</dateMonth>
<dateDay>03</dateDay>
<MJD>57511</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0345</X>
<Y>0.4261</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.11920</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>05</dateMonth>
<dateDay>04</dateDay>
<MJD>57512</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0359</X>
<Y>0.4271</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.12129</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>05</dateMonth>
<dateDay>05</dateDay>
<MJD>57513</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0373</X>
<Y>0.4281</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.12340</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>05</dateMonth>
<dateDay>06</dateDay>
<MJD>57514</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0388</X>
<Y>0.4292</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.12546</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>05</dateMonth>
<dateDay>07</dateDay>
<MJD>57515</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0402</X>
<Y>0.4301</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.12737</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>05</dateMonth>
<dateDay>08</dateDay>
<MJD>57516</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0417</X>
<Y>0.4311</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.12911</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>05</dateMonth>
<dateDay>09</dateDay>
<MJD>57517</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0432</X>
<Y>0.4321</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.13066</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>05</dateMonth>
<dateDay>10</dateDay>
<MJD>57518</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0447</X>
<Y>0.4330</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.13209</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>05</dateMonth>
<dateDay>11</dateDay>
<MJD>57519</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0462</X>
<Y>0.4339</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.13344</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>05</dateMonth>
<dateDay>12</dateDay>
<MJD>57520</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0477</X>
<Y>0.4348</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.13477</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>05</dateMonth>
<dateDay>13</dateDay>
<MJD>57521</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0493</X>
<Y>0.4357</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.13611</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>05</dateMonth>
<dateDay>14</dateDay>
<MJD>57522</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0509</X>
<Y>0.4365</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.13747</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>05</dateMonth>
<dateDay>15</dateDay>
<MJD>57523</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0524</X>
<Y>0.4373</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.13886</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>05</dateMonth>
<dateDay>16</dateDay>
<MJD>57524</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0540</X>
<Y>0.4381</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.14026</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>05</dateMonth>
<dateDay>17</dateDay>
<MJD>57525</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0556</X>
<Y>0.4389</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.14167</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>05</dateMonth>
<dateDay>18</dateDay>
<MJD>57526</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0573</X>
<Y>0.4396</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.14304</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>05</dateMonth>
<dateDay>19</dateDay>
<MJD>57527</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0589</X>
<Y>0.4404</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.14437</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>05</dateMonth>
<dateDay>20</dateDay>
<MJD>57528</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0605</X>
<Y>0.4411</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.14562</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>05</dateMonth>
<dateDay>21</dateDay>
<MJD>57529</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0622</X>
<Y>0.4417</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.14680</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>05</dateMonth>
<dateDay>22</dateDay>
<MJD>57530</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0638</X>
<Y>0.4424</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.14791</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>05</dateMonth>
<dateDay>23</dateDay>
<MJD>57531</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0655</X>
<Y>0.4430</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.14895</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>05</dateMonth>
<dateDay>24</dateDay>
<MJD>57532</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0672</X>
<Y>0.4436</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.14995</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>05</dateMonth>
<dateDay>25</dateDay>
<MJD>57533</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0689</X>
<Y>0.4442</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.15096</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>05</dateMonth>
<dateDay>26</dateDay>
<MJD>57534</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0706</X>
<Y>0.4448</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.15202</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>05</dateMonth>
<dateDay>27</dateDay>
<MJD>57535</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0723</X>
<Y>0.4453</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.15318</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>05</dateMonth>
<dateDay>28</dateDay>
<MJD>57536</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0740</X>
<Y>0.4458</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.15451</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>05</dateMonth>
<dateDay>29</dateDay>
<MJD>57537</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0758</X>
<Y>0.4463</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.15602</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>05</dateMonth>
<dateDay>30</dateDay>
<MJD>57538</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0775</X>
<Y>0.4467</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.15774</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>05</dateMonth>
<dateDay>31</dateDay>
<MJD>57539</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0793</X>
<Y>0.4472</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.15962</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>06</dateMonth>
<dateDay>01</dateDay>
<MJD>57540</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0810</X>
<Y>0.4476</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.16161</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>06</dateMonth>
<dateDay>02</dateDay>
<MJD>57541</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0828</X>
<Y>0.4480</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.16363</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>06</dateMonth>
<dateDay>03</dateDay>
<MJD>57542</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0845</X>
<Y>0.4483</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.16556</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>06</dateMonth>
<dateDay>04</dateDay>
<MJD>57543</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0863</X>
<Y>0.4486</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.16732</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>0.0881</X>
<Y>0.4489</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.16886</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>06</dateMonth>
<dateDay>06</dateDay>
<MJD>57545</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0898</X>
<Y>0.4492</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.17019</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>06</dateMonth>
<dateDay>07</dateDay>
<MJD>57546</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0916</X>
<Y>0.4495</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.17134</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>06</dateMonth>
<dateDay>08</dateDay>
<MJD>57547</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0934</X>
<Y>0.4497</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.17235</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>06</dateMonth>
<dateDay>09</dateDay>
<MJD>57548</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0952</X>
<Y>0.4499</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.17327</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>06</dateMonth>
<dateDay>10</dateDay>
<MJD>57549</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0969</X>
<Y>0.4501</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.17412</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>06</dateMonth>
<dateDay>11</dateDay>
<MJD>57550</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.0987</X>
<Y>0.4502</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.17492</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>06</dateMonth>
<dateDay>12</dateDay>
<MJD>57551</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1005</X>
<Y>0.4503</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.17568</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>06</dateMonth>
<dateDay>13</dateDay>
<MJD>57552</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1023</X>
<Y>0.4504</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.17640</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>06</dateMonth>
<dateDay>14</dateDay>
<MJD>57553</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1041</X>
<Y>0.4505</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.17709</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>06</dateMonth>
<dateDay>15</dateDay>
<MJD>57554</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1059</X>
<Y>0.4505</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.17774</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>06</dateMonth>
<dateDay>16</dateDay>
<MJD>57555</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1077</X>
<Y>0.4505</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.17833</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>17</dateDay>
<MJD>57556</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1095</X>
<Y>0.4505</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.17887</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>06</dateMonth>
<dateDay>18</dateDay>
<MJD>57557</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1112</X>
<Y>0.4505</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.17934</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>06</dateMonth>
<dateDay>19</dateDay>
<MJD>57558</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1130</X>
<Y>0.4504</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.17976</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>0.1148</X>
<Y>0.4503</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.18015</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>06</dateMonth>
<dateDay>21</dateDay>
<MJD>57560</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1166</X>
<Y>0.4502</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.18054</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>06</dateMonth>
<dateDay>22</dateDay>
<MJD>57561</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1183</X>
<Y>0.4501</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.18097</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>06</dateMonth>
<dateDay>23</dateDay>
<MJD>57562</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1201</X>
<Y>0.4499</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.18147</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>06</dateMonth>
<dateDay>24</dateDay>
<MJD>57563</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1219</X>
<Y>0.4497</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.18206</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>06</dateMonth>
<dateDay>25</dateDay>
<MJD>57564</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1236</X>
<Y>0.4495</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.18277</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>06</dateMonth>
<dateDay>26</dateDay>
<MJD>57565</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1254</X>
<Y>0.4492</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.18358</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>06</dateMonth>
<dateDay>27</dateDay>
<MJD>57566</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1271</X>
<Y>0.4490</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.18448</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57567</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1288</X>
<Y>0.4487</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.18541</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57568</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1306</X>
<Y>0.4483</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.18630</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>30</dateDay>
<MJD>57569</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1323</X>
<Y>0.4480</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.18707</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>01</dateDay>
<MJD>57570</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1340</X>
<Y>0.4476</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.18767</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>07</dateMonth>
<dateDay>02</dateDay>
<MJD>57571</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1357</X>
<Y>0.4472</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.18809</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>07</dateMonth>
<dateDay>03</dateDay>
<MJD>57572</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1374</X>
<Y>0.4468</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.18832</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>04</dateDay>
<MJD>57573</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1391</X>
<Y>0.4463</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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<MJD>57574</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1408</X>
<Y>0.4459</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.18845</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57575</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1424</X>
<Y>0.4454</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.18851</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>07</dateDay>
<MJD>57576</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1441</X>
<Y>0.4448</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.18862</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>08</dateDay>
<MJD>57577</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1457</X>
<Y>0.4443</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.18884</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>09</dateDay>
<MJD>57578</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1474</X>
<Y>0.4437</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.18912</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>10</dateDay>
<MJD>57579</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1490</X>
<Y>0.4431</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.18939</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>11</dateDay>
<MJD>57580</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1506</X>
<Y>0.4425</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.18968</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>12</dateDay>
<MJD>57581</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1522</X>
<Y>0.4419</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.18991</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>13</dateDay>
<MJD>57582</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1537</X>
<Y>0.4412</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.19006</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>14</dateDay>
<MJD>57583</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1553</X>
<Y>0.4405</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.19012</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>15</dateDay>
<MJD>57584</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1569</X>
<Y>0.4398</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.18998</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>16</dateDay>
<MJD>57585</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1584</X>
<Y>0.4390</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.18970</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>17</dateDay>
<MJD>57586</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1599</X>
<Y>0.4383</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.18934</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>18</dateDay>
<MJD>57587</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1614</X>
<Y>0.4375</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.18890</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>19</dateDay>
<MJD>57588</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1629</X>
<Y>0.4367</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.18852</UT1-UTC>
</UT>
</dataEOP>
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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>0.1644</X>
<Y>0.4359</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.18821</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>21</dateDay>
<MJD>57590</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1658</X>
<Y>0.4350</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.18809</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>22</dateDay>
<MJD>57591</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1673</X>
<Y>0.4342</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.18812</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>23</dateDay>
<MJD>57592</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1687</X>
<Y>0.4333</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.18841</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>07</dateMonth>
<dateDay>24</dateDay>
<MJD>57593</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1701</X>
<Y>0.4324</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.18889</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>07</dateMonth>
<dateDay>25</dateDay>
<MJD>57594</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1715</X>
<Y>0.4314</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.18947</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>07</dateMonth>
<dateDay>26</dateDay>
<MJD>57595</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1729</X>
<Y>0.4305</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.19014</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>07</dateMonth>
<dateDay>27</dateDay>
<MJD>57596</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1742</X>
<Y>0.4295</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.19079</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>28</dateDay>
<MJD>57597</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1755</X>
<Y>0.4285</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.19133</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>29</dateDay>
<MJD>57598</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1768</X>
<Y>0.4275</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.19164</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>30</dateDay>
<MJD>57599</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1781</X>
<Y>0.4265</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.19177</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>31</dateDay>
<MJD>57600</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1794</X>
<Y>0.4254</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.19178</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>01</dateDay>
<MJD>57601</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1806</X>
<Y>0.4243</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.19165</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>02</dateDay>
<MJD>57602</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1819</X>
<Y>0.4232</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.19148</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>03</dateDay>
<MJD>57603</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1831</X>
<Y>0.4221</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.19130</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>04</dateDay>
<MJD>57604</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1842</X>
<Y>0.4210</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.19114</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>05</dateDay>
<MJD>57605</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1854</X>
<Y>0.4199</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.19109</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>06</dateDay>
<MJD>57606</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1865</X>
<Y>0.4187</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.19115</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>07</dateDay>
<MJD>57607</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1876</X>
<Y>0.4175</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.19130</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>08</dateDay>
<MJD>57608</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1887</X>
<Y>0.4163</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.19155</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>09</dateDay>
<MJD>57609</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1898</X>
<Y>0.4151</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.19180</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>10</dateDay>
<MJD>57610</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1909</X>
<Y>0.4139</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.19205</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>11</dateDay>
<MJD>57611</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1919</X>
<Y>0.4127</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.19230</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>12</dateDay>
<MJD>57612</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1929</X>
<Y>0.4114</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.19251</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>13</dateDay>
<MJD>57613</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1938</X>
<Y>0.4101</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.19269</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>14</dateDay>
<MJD>57614</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1948</X>
<Y>0.4089</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.19295</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>15</dateDay>
<MJD>57615</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1957</X>
<Y>0.4076</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.19321</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>16</dateDay>
<MJD>57616</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1966</X>
<Y>0.4062</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.19351</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>17</dateDay>
<MJD>57617</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1975</X>
<Y>0.4049</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.19387</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>18</dateDay>
<MJD>57618</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1983</X>
<Y>0.4036</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.19441</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>19</dateDay>
<MJD>57619</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1991</X>
<Y>0.4022</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.19513</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>20</dateDay>
<MJD>57620</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1999</X>
<Y>0.4009</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.19594</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>21</dateDay>
<MJD>57621</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2007</X>
<Y>0.3995</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.19693</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>22</dateDay>
<MJD>57622</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2015</X>
<Y>0.3981</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.19795</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>23</dateDay>
<MJD>57623</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2022</X>
<Y>0.3967</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.19894</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>24</dateDay>
<MJD>57624</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2029</X>
<Y>0.3953</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.19988</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>25</dateDay>
<MJD>57625</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2035</X>
<Y>0.3939</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.20072</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries><time><dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>26</dateDay>
<MJD>57626</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2042</X>
<Y>0.3925</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.20137</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>0.2048</X>
<Y>0.3910</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.20193</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>28</dateDay>
<MJD>57628</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2053</X>
<Y>0.3896</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.20242</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57629</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2059</X>
<Y>0.3881</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.20284</UT1-UTC>
</UT>
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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>0.2064</X>
<Y>0.3867</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.20327</UT1-UTC>
</UT>
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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>0.2069</X>
<Y>0.3852</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.20368</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>01</dateDay>
<MJD>57632</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2074</X>
<Y>0.3837</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.20410</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>0.2078</X>
<Y>0.3822</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.20457</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>0.2083</X>
<Y>0.3807</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.20505</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57635</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2086</X>
<Y>0.3792</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.20560</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57636</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2090</X>
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</pole>
<UT type="prediction"><UT1-UTC>-0.20609</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>0.2093</X>
<Y>0.3762</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.20657</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>0.2096</X>
<Y>0.3747</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.20699</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>0.2099</X>
<Y>0.3732</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.20733</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>0.2101</X>
<Y>0.3717</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.20762</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>10</dateDay>
<MJD>57641</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2104</X>
<Y>0.3701</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.20787</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>0.2106</X>
<Y>0.3686</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.20812</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>0.2107</X>
<Y>0.3671</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.20841</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>13</dateDay>
<MJD>57644</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2108</X>
<Y>0.3655</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.20888</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>0.2109</X>
<Y>0.3640</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.20951</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57646</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2110</X>
<Y>0.3625</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.21034</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>0.2111</X>
<Y>0.3609</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.21140</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>0.2111</X>
<Y>0.3594</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.21268</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>0.2111</X>
<Y>0.3578</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.21413</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>0.2110</X>
<Y>0.3563</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.21559</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>0.2110</X>
<Y>0.3548</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.21697</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>0.2109</X>
<Y>0.3532</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.21827</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>0.2107</X>
<Y>0.3517</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.21944</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>0.2106</X>
<Y>0.3502</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.22056</UT1-UTC>
</UT>
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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>0.2104</X>
<Y>0.3486</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.22156</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>0.2102</X>
<Y>0.3471</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.22251</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>0.2100</X>
<Y>0.3456</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.22348</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>0.2097</X>
<Y>0.3441</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.22457</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>0.2094</X>
<Y>0.3425</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.22582</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>0.2091</X>
<Y>0.3410</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.22716</UT1-UTC>
</UT>
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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>0.2087</X>
<Y>0.3395</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.22849</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>0.2084</X>
<Y>0.3380</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.22983</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>0.2080</X>
<Y>0.3365</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.23115</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>03</dateDay>
<MJD>57664</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2075</X>
<Y>0.3350</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.23245</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>0.2071</X>
<Y>0.3335</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.23367</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<dateDay>05</dateDay>
<MJD>57666</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.2066</X>
<Y>0.3321</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.23478</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>0.2061</X>
<Y>0.3306</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.23580</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>0.2055</X>
<Y>0.3291</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.23670</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>0.2050</X>
<Y>0.3277</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.23753</UT1-UTC>
</UT>
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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>0.2044</X>
<Y>0.3262</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.23833</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>0.2038</X>
<Y>0.3248</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.23920</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>0.2031</X>
<Y>0.3234</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.24020</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>0.2025</X>
<Y>0.3219</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.24133</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>0.2018</X>
<Y>0.3205</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.24283</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>0.2011</X>
<Y>0.3191</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.24444</UT1-UTC>
</UT>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57676</MJD>
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<dataEOP><pole type="prediction"><X>0.2003</X>
<Y>0.3178</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.24628</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>0.1995</X>
<Y>0.3164</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.24823</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>0.1988</X>
<Y>0.3150</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.25009</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>0.1979</X>
<Y>0.3137</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.25193</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>0.1971</X>
<Y>0.3123</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.25362</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>0.1962</X>
<Y>0.3110</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.25517</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>0.1954</X>
<Y>0.3097</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.25665</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>0.1944</X>
<Y>0.3084</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.25803</UT1-UTC>
</UT>
</dataEOP>
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<timeSeries><time><dateYear>2016</dateYear>
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<MJD>57684</MJD>
</time>
<dataEOP><pole type="prediction"><X>0.1935</X>
<Y>0.3071</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.25942</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>0.1926</X>
<Y>0.3058</Y>
</pole>
<UT type="prediction"><UT1-UTC>-0.26079</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>0.1916</X>
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