<?xml version="1.0" encoding="UTF-8"?><EOP xmlns="http://www.iers.org/2003/schema/iers">
<version>
<product>BulletinA</product>
<date>2016-03-03</date>
<volume>XXIX</volume>
<number>009</number>
</version>
<metaFileName/>
<headerLine>
<headerLineDate>
<sYear>Year</sYear>
<sMonth>Month</sMonth>
<sDay>Day</sDay>
<sTime>Time</sTime>
<sMJD>MJD</sMJD>
</headerLineDate>
<headerLineEOP>
<product source="BulletinA">
<sX>X</sX>
<ssigma_X>sigma_X</ssigma_X>
<sY>Y</sY>
<ssigma_Y>sigma_Y</ssigma_Y>
<sUT1-UTC>UT1-UTC</sUT1-UTC>
<ssigma_UT1-UTC>sigma_UT1-UTC</ssigma_UT1-UTC>
<sdPsi>dPsi</sdPsi>
<ssigma_dPsi>sigma_dPsi</ssigma_dPsi>
<sdEpsilon>dEpsilon</sdEpsilon>
<ssigma_dEpsilon>sigma_dEpsilon</ssigma_dEpsilon>
<sdX>dX</sdX>
<ssigma_dX>sigma_dX</ssigma_dX>
<sdY>dY</sdY>
<ssigma_dY>sigma_dY</ssigma_dY>
</product>
</headerLineEOP>
<headerLineUnits>
<product source="BulletinA">
<X>arcsec</X>
<sigma_X>arcsec</sigma_X>
<Y>arcsec</Y>
<sigma_Y>arcsec</sigma_Y>
<UT1-UTC>sec</UT1-UTC>
<sigma_UT1-UTC>sec</sigma_UT1-UTC>
<dPsi>marcsec</dPsi>
<sigma_dPsi>marcsec</sigma_dPsi>
<dEpsilon>marcsec</dEpsilon>
<sigma_dEpsilon>marcsec</sigma_dEpsilon>
<dX>marcsec</dX>
<sigma_dX>marcsec</sigma_dX>
<dY>marcsec</dY>
<sigma_dY>marcsec</sigma_dY>
</product>
</headerLineUnits>
</headerLine>
<data product="BulletinA" source="BulletinA">
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>02</dateMonth>
<dateDay>10</dateDay>
<MJD>57428</MJD>
</time>
<dataEOP>
<nutation type="rapid">
<dPsi>-93.92</dPsi>
<sigma_dPsi>0.30</sigma_dPsi>
<dEpsilon>-9.99</dEpsilon>
<sigma_dEpsilon>0.04</sigma_dEpsilon>
<dX>-0.184</dX>
<sigma_dX>0.119</sigma_dX>
<dY>-0.106</dY>
<sigma_dY>0.040</sigma_dY>
</nutation>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>02</dateMonth>
<dateDay>11</dateDay>
<MJD>57429</MJD>
</time>
<dataEOP>
<nutation type="rapid">
<dPsi>-93.82</dPsi>
<sigma_dPsi>0.30</sigma_dPsi>
<dEpsilon>-9.75</dEpsilon>
<sigma_dEpsilon>0.04</sigma_dEpsilon>
<dX>-0.201</dX>
<sigma_dX>0.119</sigma_dX>
<dY>-0.095</dY>
<sigma_dY>0.040</sigma_dY>
</nutation>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>02</dateMonth>
<dateDay>12</dateDay>
<MJD>57430</MJD>
</time>
<dataEOP>
<nutation type="rapid">
<dPsi>-93.93</dPsi>
<sigma_dPsi>0.30</sigma_dPsi>
<dEpsilon>-9.75</dEpsilon>
<sigma_dEpsilon>0.04</sigma_dEpsilon>
<dX>-0.207</dX>
<sigma_dX>0.119</sigma_dX>
<dY>-0.092</dY>
<sigma_dY>0.040</sigma_dY>
</nutation>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>02</dateMonth>
<dateDay>13</dateDay>
<MJD>57431</MJD>
</time>
<dataEOP>
<nutation type="rapid">
<dPsi>-94.14</dPsi>
<sigma_dPsi>0.30</sigma_dPsi>
<dEpsilon>-9.92</dEpsilon>
<sigma_dEpsilon>0.09</sigma_dEpsilon>
<dX>-0.198</dX>
<sigma_dX>0.119</sigma_dX>
<dY>-0.080</dY>
<sigma_dY>0.090</sigma_dY>
</nutation>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>02</dateMonth>
<dateDay>14</dateDay>
<MJD>57432</MJD>
</time>
<dataEOP>
<nutation type="rapid">
<dPsi>-94.33</dPsi>
<sigma_dPsi>0.30</sigma_dPsi>
<dEpsilon>-10.13</dEpsilon>
<sigma_dEpsilon>0.04</sigma_dEpsilon>
<dX>-0.187</dX>
<sigma_dX>0.119</sigma_dX>
<dY>-0.081</dY>
<sigma_dY>0.040</sigma_dY>
</nutation>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>02</dateMonth>
<dateDay>15</dateDay>
<MJD>57433</MJD>
</time>
<dataEOP>
<nutation type="rapid">
<dPsi>-94.44</dPsi>
<sigma_dPsi>0.30</sigma_dPsi>
<dEpsilon>-10.29</dEpsilon>
<sigma_dEpsilon>0.04</sigma_dEpsilon>
<dX>-0.173</dX>
<sigma_dX>0.119</sigma_dX>
<dY>-0.075</dY>
<sigma_dY>0.040</sigma_dY>
</nutation>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>02</dateMonth>
<dateDay>16</dateDay>
<MJD>57434</MJD>
</time>
<dataEOP>
<nutation type="rapid">
<dPsi>-94.50</dPsi>
<sigma_dPsi>0.30</sigma_dPsi>
<dEpsilon>-10.43</dEpsilon>
<sigma_dEpsilon>0.04</sigma_dEpsilon>
<dX>-0.158</dX>
<sigma_dX>0.119</sigma_dX>
<dY>-0.072</dY>
<sigma_dY>0.040</sigma_dY>
</nutation>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>02</dateMonth>
<dateDay>26</dateDay>
<MJD>57444</MJD>
</time>
<dataEOP>
<pole type="rapid">
<X>-.02205</X>
<sigma_X>.00009</sigma_X>
<Y>0.34634</Y>
<sigma_Y>.00009</sigma_Y>
</pole>
<UT type="rapid">
<UT1-UTC>-0.013426</UT1-UTC>
<sigma_UT1-UTC>0.000018</sigma_UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>02</dateMonth>
<dateDay>27</dateDay>
<MJD>57445</MJD>
</time>
<dataEOP>
<pole type="rapid">
<X>-.02243</X>
<sigma_X>.00009</sigma_X>
<Y>0.34846</Y>
<sigma_Y>.00009</sigma_Y>
</pole>
<UT type="rapid">
<UT1-UTC>-0.015220</UT1-UTC>
<sigma_UT1-UTC>0.000017</sigma_UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>02</dateMonth>
<dateDay>28</dateDay>
<MJD>57446</MJD>
</time>
<dataEOP>
<pole type="rapid">
<X>-.02321</X>
<sigma_X>.00009</sigma_X>
<Y>0.35074</Y>
<sigma_Y>.00009</sigma_Y>
</pole>
<UT type="rapid">
<UT1-UTC>-0.016986</UT1-UTC>
<sigma_UT1-UTC>0.000025</sigma_UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>02</dateMonth>
<dateDay>29</dateDay>
<MJD>57447</MJD>
</time>
<dataEOP>
<pole type="rapid">
<X>-.02414</X>
<sigma_X>.00009</sigma_X>
<Y>0.35278</Y>
<sigma_Y>.00009</sigma_Y>
</pole>
<UT type="rapid">
<UT1-UTC>-0.018722</UT1-UTC>
<sigma_UT1-UTC>0.000022</sigma_UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>03</dateMonth>
<dateDay>01</dateDay>
<MJD>57448</MJD>
</time>
<dataEOP>
<pole type="rapid">
<X>-.02472</X>
<sigma_X>.00009</sigma_X>
<Y>0.35442</Y>
<sigma_Y>.00009</sigma_Y>
</pole>
<UT type="rapid">
<UT1-UTC>-0.020380</UT1-UTC>
<sigma_UT1-UTC>0.000023</sigma_UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>03</dateMonth>
<dateDay>02</dateDay>
<MJD>57449</MJD>
</time>
<dataEOP>
<pole type="rapid">
<X>-.02462</X>
<sigma_X>.00009</sigma_X>
<Y>0.35600</Y>
<sigma_Y>.00009</sigma_Y>
</pole>
<UT type="rapid">
<UT1-UTC>-0.021904</UT1-UTC>
<sigma_UT1-UTC>0.000023</sigma_UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>03</dateMonth>
<dateDay>03</dateDay>
<MJD>57450</MJD>
</time>
<dataEOP>
<pole type="rapid">
<X>-.02400</X>
<sigma_X>.00009</sigma_X>
<Y>0.35779</Y>
<sigma_Y>.00009</sigma_Y>
</pole>
<UT type="rapid">
<UT1-UTC>-0.023526</UT1-UTC>
<sigma_UT1-UTC>0.000055</sigma_UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>03</dateMonth>
<dateDay>04</dateDay>
<MJD>57451</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0235</X>
<Y>0.3597</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.02521</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>03</dateMonth>
<dateDay>05</dateDay>
<MJD>57452</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0228</X>
<Y>0.3617</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.02696</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>03</dateMonth>
<dateDay>06</dateDay>
<MJD>57453</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0224</X>
<Y>0.3638</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.02884</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>03</dateMonth>
<dateDay>07</dateDay>
<MJD>57454</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0222</X>
<Y>0.3658</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.03086</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>03</dateMonth>
<dateDay>08</dateDay>
<MJD>57455</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0222</X>
<Y>0.3677</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.03302</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>03</dateMonth>
<dateDay>09</dateDay>
<MJD>57456</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0220</X>
<Y>0.3695</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.03530</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>03</dateMonth>
<dateDay>10</dateDay>
<MJD>57457</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0218</X>
<Y>0.3713</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.03765</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>03</dateMonth>
<dateDay>11</dateDay>
<MJD>57458</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0215</X>
<Y>0.3731</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.04001</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>03</dateMonth>
<dateDay>12</dateDay>
<MJD>57459</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0212</X>
<Y>0.3750</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.04230</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>03</dateMonth>
<dateDay>13</dateDay>
<MJD>57460</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0209</X>
<Y>0.3769</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.04449</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>03</dateMonth>
<dateDay>14</dateDay>
<MJD>57461</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0205</X>
<Y>0.3787</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.04658</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>03</dateMonth>
<dateDay>15</dateDay>
<MJD>57462</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0201</X>
<Y>0.3805</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.04856</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>03</dateMonth>
<dateDay>16</dateDay>
<MJD>57463</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0196</X>
<Y>0.3824</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.05042</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>03</dateMonth>
<dateDay>17</dateDay>
<MJD>57464</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0192</X>
<Y>0.3842</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.05222</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>03</dateMonth>
<dateDay>18</dateDay>
<MJD>57465</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0188</X>
<Y>0.3861</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.05401</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>03</dateMonth>
<dateDay>19</dateDay>
<MJD>57466</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0183</X>
<Y>0.3878</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.05583</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>03</dateMonth>
<dateDay>20</dateDay>
<MJD>57467</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0179</X>
<Y>0.3896</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.05769</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>03</dateMonth>
<dateDay>21</dateDay>
<MJD>57468</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0173</X>
<Y>0.3913</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.05959</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>03</dateMonth>
<dateDay>22</dateDay>
<MJD>57469</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0167</X>
<Y>0.3931</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.06151</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>03</dateMonth>
<dateDay>23</dateDay>
<MJD>57470</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0161</X>
<Y>0.3948</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.06344</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>03</dateMonth>
<dateDay>24</dateDay>
<MJD>57471</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0154</X>
<Y>0.3966</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.06536</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>03</dateMonth>
<dateDay>25</dateDay>
<MJD>57472</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0147</X>
<Y>0.3983</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.06725</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>03</dateMonth>
<dateDay>26</dateDay>
<MJD>57473</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0140</X>
<Y>0.4001</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.06910</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>03</dateMonth>
<dateDay>27</dateDay>
<MJD>57474</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0133</X>
<Y>0.4018</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.07091</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>03</dateMonth>
<dateDay>28</dateDay>
<MJD>57475</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0125</X>
<Y>0.4035</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.07265</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>03</dateMonth>
<dateDay>29</dateDay>
<MJD>57476</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0117</X>
<Y>0.4051</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.07432</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>03</dateMonth>
<dateDay>30</dateDay>
<MJD>57477</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0109</X>
<Y>0.4068</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.07595</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>03</dateMonth>
<dateDay>31</dateDay>
<MJD>57478</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0100</X>
<Y>0.4085</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.07755</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>04</dateMonth>
<dateDay>01</dateDay>
<MJD>57479</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0091</X>
<Y>0.4101</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.07919</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>04</dateMonth>
<dateDay>02</dateDay>
<MJD>57480</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0081</X>
<Y>0.4118</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.08093</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>04</dateMonth>
<dateDay>03</dateDay>
<MJD>57481</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0072</X>
<Y>0.4134</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.08282</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>04</dateMonth>
<dateDay>04</dateDay>
<MJD>57482</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0062</X>
<Y>0.4150</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.08492</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>04</dateMonth>
<dateDay>05</dateDay>
<MJD>57483</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0051</X>
<Y>0.4166</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.08723</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>04</dateMonth>
<dateDay>06</dateDay>
<MJD>57484</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0041</X>
<Y>0.4182</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.08972</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>04</dateMonth>
<dateDay>07</dateDay>
<MJD>57485</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0030</X>
<Y>0.4197</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.09231</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>04</dateMonth>
<dateDay>08</dateDay>
<MJD>57486</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0019</X>
<Y>0.4213</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.09490</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>04</dateMonth>
<dateDay>09</dateDay>
<MJD>57487</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0007</X>
<Y>0.4228</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.09740</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>04</dateMonth>
<dateDay>10</dateDay>
<MJD>57488</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0004</X>
<Y>0.4243</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.09974</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>04</dateMonth>
<dateDay>11</dateDay>
<MJD>57489</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0016</X>
<Y>0.4258</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.10193</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>04</dateMonth>
<dateDay>12</dateDay>
<MJD>57490</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0028</X>
<Y>0.4273</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.10399</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>04</dateMonth>
<dateDay>13</dateDay>
<MJD>57491</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0041</X>
<Y>0.4288</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.10598</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>04</dateMonth>
<dateDay>14</dateDay>
<MJD>57492</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0054</X>
<Y>0.4302</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.10795</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>04</dateMonth>
<dateDay>15</dateDay>
<MJD>57493</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0067</X>
<Y>0.4316</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.10994</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>04</dateMonth>
<dateDay>16</dateDay>
<MJD>57494</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0080</X>
<Y>0.4331</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.11196</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>04</dateMonth>
<dateDay>17</dateDay>
<MJD>57495</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0094</X>
<Y>0.4344</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.11403</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>04</dateMonth>
<dateDay>18</dateDay>
<MJD>57496</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0107</X>
<Y>0.4358</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.11613</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>04</dateMonth>
<dateDay>19</dateDay>
<MJD>57497</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0121</X>
<Y>0.4371</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.11824</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>04</dateMonth>
<dateDay>20</dateDay>
<MJD>57498</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0136</X>
<Y>0.4385</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.12035</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>04</dateMonth>
<dateDay>21</dateDay>
<MJD>57499</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0150</X>
<Y>0.4398</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.12243</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>04</dateMonth>
<dateDay>22</dateDay>
<MJD>57500</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0165</X>
<Y>0.4411</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.12444</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>04</dateMonth>
<dateDay>23</dateDay>
<MJD>57501</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0180</X>
<Y>0.4423</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.12638</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>04</dateMonth>
<dateDay>24</dateDay>
<MJD>57502</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0195</X>
<Y>0.4436</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.12822</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>04</dateMonth>
<dateDay>25</dateDay>
<MJD>57503</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0211</X>
<Y>0.4448</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.12998</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>04</dateMonth>
<dateDay>26</dateDay>
<MJD>57504</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0226</X>
<Y>0.4460</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.13166</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>04</dateMonth>
<dateDay>27</dateDay>
<MJD>57505</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0242</X>
<Y>0.4471</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.13331</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>04</dateMonth>
<dateDay>28</dateDay>
<MJD>57506</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0258</X>
<Y>0.4483</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.13495</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>04</dateMonth>
<dateDay>29</dateDay>
<MJD>57507</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0275</X>
<Y>0.4494</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.13663</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>04</dateMonth>
<dateDay>30</dateDay>
<MJD>57508</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0291</X>
<Y>0.4505</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.13841</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>0.0308</X>
<Y>0.4516</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.14033</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>0.0325</X>
<Y>0.4526</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.14240</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>0.0342</X>
<Y>0.4536</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.14463</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>0.4546</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.14695</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>05</dateMonth>
<dateDay>05</dateDay>
<MJD>57513</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0377</X>
<Y>0.4556</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.14929</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>0.0394</X>
<Y>0.4566</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.15155</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>0.0412</X>
<Y>0.4575</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.15366</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>0.0430</X>
<Y>0.4584</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.15557</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>05</dateMonth>
<dateDay>09</dateDay>
<MJD>57517</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0448</X>
<Y>0.4592</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.15731</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>0.0467</X>
<Y>0.4601</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.15890</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>0.0485</X>
<Y>0.4609</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.16041</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>0.0504</X>
<Y>0.4617</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.16189</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>0.0523</X>
<Y>0.4624</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.16337</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>0.0541</X>
<Y>0.4631</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.16487</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>0.0560</X>
<Y>0.4638</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.16637</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>0.0580</X>
<Y>0.4645</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.16789</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>0.0599</X>
<Y>0.4652</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.16938</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>0.0618</X>
<Y>0.4658</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.17085</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>0.0638</X>
<Y>0.4664</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.17226</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>0.0657</X>
<Y>0.4669</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.17358</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>0.0677</X>
<Y>0.4674</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.17481</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>0.0697</X>
<Y>0.4679</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.17595</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>0.0717</X>
<Y>0.4684</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.17701</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>0.0737</X>
<Y>0.4689</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.17801</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>0.0757</X>
<Y>0.4693</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.17898</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>0.0777</X>
<Y>0.4696</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.17996</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>0.0797</X>
<Y>0.4700</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.18102</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>0.0817</X>
<Y>0.4703</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.18218</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>05</dateMonth>
<dateDay>29</dateDay>
<MJD>57537</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0837</X>
<Y>0.4706</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.18347</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>0.0858</X>
<Y>0.4709</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.18491</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>0.0878</X>
<Y>0.4711</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.18645</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>0.0898</X>
<Y>0.4713</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.18805</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>0.0919</X>
<Y>0.4715</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.18963</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>0.0939</X>
<Y>0.4716</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.19112</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>0.0960</X>
<Y>0.4717</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.19246</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>06</dateMonth>
<dateDay>05</dateDay>
<MJD>57544</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0980</X>
<Y>0.4718</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.19363</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>06</dateMonth>
<dateDay>06</dateDay>
<MJD>57545</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1001</X>
<Y>0.4718</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.19466</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>0.1021</X>
<Y>0.4718</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.19560</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>0.1042</X>
<Y>0.4718</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.19650</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>0.1062</X>
<Y>0.4718</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.19741</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>0.1083</X>
<Y>0.4717</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.19834</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>0.1103</X>
<Y>0.4716</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.19929</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>0.1124</X>
<Y>0.4715</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.20026</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>0.1144</X>
<Y>0.4713</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.20123</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>0.1165</X>
<Y>0.4711</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.20217</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>06</dateMonth>
<dateDay>15</dateDay>
<MJD>57554</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1185</X>
<Y>0.4709</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.20307</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>0.1205</X>
<Y>0.4706</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.20389</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>06</dateMonth>
<dateDay>17</dateDay>
<MJD>57556</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1225</X>
<Y>0.4703</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.20463</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>06</dateMonth>
<dateDay>18</dateDay>
<MJD>57557</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1246</X>
<Y>0.4700</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.20529</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>0.1266</X>
<Y>0.4696</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.20586</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>06</dateMonth>
<dateDay>20</dateDay>
<MJD>57559</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1286</X>
<Y>0.4693</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.20638</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>06</dateMonth>
<dateDay>21</dateDay>
<MJD>57560</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1306</X>
<Y>0.4688</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.20688</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>06</dateMonth>
<dateDay>22</dateDay>
<MJD>57561</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1326</X>
<Y>0.4684</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.20739</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>06</dateMonth>
<dateDay>23</dateDay>
<MJD>57562</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1345</X>
<Y>0.4679</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.20796</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>0.1365</X>
<Y>0.4674</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.20864</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>0.1385</X>
<Y>0.4669</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.20944</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>0.1404</X>
<Y>0.4664</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.21038</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>0.1424</X>
<Y>0.4658</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.21143</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>06</dateMonth>
<dateDay>28</dateDay>
<MJD>57567</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1443</X>
<Y>0.4652</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.21254</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>06</dateMonth>
<dateDay>29</dateDay>
<MJD>57568</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1462</X>
<Y>0.4645</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.21366</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>06</dateMonth>
<dateDay>30</dateDay>
<MJD>57569</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1481</X>
<Y>0.4638</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.21471</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>07</dateMonth>
<dateDay>01</dateDay>
<MJD>57570</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1500</X>
<Y>0.4631</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.21566</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>07</dateMonth>
<dateDay>02</dateDay>
<MJD>57571</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1519</X>
<Y>0.4624</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.21646</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>07</dateMonth>
<dateDay>03</dateDay>
<MJD>57572</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1538</X>
<Y>0.4616</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.21714</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>07</dateMonth>
<dateDay>04</dateDay>
<MJD>57573</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1556</X>
<Y>0.4609</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.21772</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>07</dateMonth>
<dateDay>05</dateDay>
<MJD>57574</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1575</X>
<Y>0.4600</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.21827</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>07</dateMonth>
<dateDay>06</dateDay>
<MJD>57575</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1593</X>
<Y>0.4592</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.21883</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>07</dateMonth>
<dateDay>07</dateDay>
<MJD>57576</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1611</X>
<Y>0.4583</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.21943</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>07</dateMonth>
<dateDay>08</dateDay>
<MJD>57577</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1629</X>
<Y>0.4574</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.22008</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>07</dateMonth>
<dateDay>09</dateDay>
<MJD>57578</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1646</X>
<Y>0.4565</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.22076</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>07</dateMonth>
<dateDay>10</dateDay>
<MJD>57579</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1664</X>
<Y>0.4556</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.22146</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>07</dateMonth>
<dateDay>11</dateDay>
<MJD>57580</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1681</X>
<Y>0.4546</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.22215</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>07</dateMonth>
<dateDay>12</dateDay>
<MJD>57581</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1698</X>
<Y>0.4536</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.22280</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>07</dateMonth>
<dateDay>13</dateDay>
<MJD>57582</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1715</X>
<Y>0.4526</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.22340</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>07</dateMonth>
<dateDay>14</dateDay>
<MJD>57583</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1732</X>
<Y>0.4515</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.22392</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>07</dateMonth>
<dateDay>15</dateDay>
<MJD>57584</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1749</X>
<Y>0.4504</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.22437</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>07</dateMonth>
<dateDay>16</dateDay>
<MJD>57585</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1765</X>
<Y>0.4493</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.22474</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>07</dateMonth>
<dateDay>17</dateDay>
<MJD>57586</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1781</X>
<Y>0.4482</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.22507</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>07</dateMonth>
<dateDay>18</dateDay>
<MJD>57587</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1797</X>
<Y>0.4471</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.22537</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>07</dateMonth>
<dateDay>19</dateDay>
<MJD>57588</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1813</X>
<Y>0.4459</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.22568</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>07</dateMonth>
<dateDay>20</dateDay>
<MJD>57589</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1829</X>
<Y>0.4447</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.22606</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>07</dateMonth>
<dateDay>21</dateDay>
<MJD>57590</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1844</X>
<Y>0.4435</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.22655</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>07</dateMonth>
<dateDay>22</dateDay>
<MJD>57591</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1859</X>
<Y>0.4422</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.22718</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>07</dateMonth>
<dateDay>23</dateDay>
<MJD>57592</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1874</X>
<Y>0.4410</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.22798</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>07</dateMonth>
<dateDay>24</dateDay>
<MJD>57593</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1889</X>
<Y>0.4397</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.22890</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>07</dateMonth>
<dateDay>25</dateDay>
<MJD>57594</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1903</X>
<Y>0.4384</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.22990</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>07</dateMonth>
<dateDay>26</dateDay>
<MJD>57595</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1917</X>
<Y>0.4370</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.23092</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>07</dateMonth>
<dateDay>27</dateDay>
<MJD>57596</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1931</X>
<Y>0.4357</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.23189</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>07</dateMonth>
<dateDay>28</dateDay>
<MJD>57597</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1945</X>
<Y>0.4343</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.23277</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>07</dateMonth>
<dateDay>29</dateDay>
<MJD>57598</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1958</X>
<Y>0.4329</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.23352</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>07</dateMonth>
<dateDay>30</dateDay>
<MJD>57599</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1971</X>
<Y>0.4315</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.23416</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>07</dateMonth>
<dateDay>31</dateDay>
<MJD>57600</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1984</X>
<Y>0.4301</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.23472</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>01</dateDay>
<MJD>57601</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1997</X>
<Y>0.4286</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.23524</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>02</dateDay>
<MJD>57602</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2009</X>
<Y>0.4272</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.23579</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>03</dateDay>
<MJD>57603</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2021</X>
<Y>0.4257</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.23640</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>04</dateDay>
<MJD>57604</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2033</X>
<Y>0.4242</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.23708</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>05</dateDay>
<MJD>57605</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2044</X>
<Y>0.4227</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.23782</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>06</dateDay>
<MJD>57606</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2055</X>
<Y>0.4211</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.23861</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>07</dateDay>
<MJD>57607</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2066</X>
<Y>0.4196</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.23941</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>08</dateDay>
<MJD>57608</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2077</X>
<Y>0.4180</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.24020</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>0.2087</X>
<Y>0.4164</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.24095</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>0.2097</X>
<Y>0.4148</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.24164</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>11</dateDay>
<MJD>57611</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2107</X>
<Y>0.4132</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.24227</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>0.2116</X>
<Y>0.4115</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.24283</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>0.2125</X>
<Y>0.4099</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.24335</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>0.2134</X>
<Y>0.4082</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.24384</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>0.2143</X>
<Y>0.4066</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.24436</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>0.2151</X>
<Y>0.4049</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.24494</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>17</dateDay>
<MJD>57617</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2159</X>
<Y>0.4032</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.24563</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>18</dateDay>
<MJD>57618</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2167</X>
<Y>0.4015</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.24648</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>19</dateDay>
<MJD>57619</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2174</X>
<Y>0.3997</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.24751</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>20</dateDay>
<MJD>57620</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2181</X>
<Y>0.3980</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.24870</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>21</dateDay>
<MJD>57621</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2187</X>
<Y>0.3963</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.25002</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>22</dateDay>
<MJD>57622</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2194</X>
<Y>0.3945</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.25137</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>0.2200</X>
<Y>0.3928</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.25269</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>0.2205</X>
<Y>0.3910</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.25390</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>0.2211</X>
<Y>0.3892</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.25498</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>0.2216</X>
<Y>0.3874</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.25593</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>27</dateDay>
<MJD>57627</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2220</X>
<Y>0.3856</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.25677</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>28</dateDay>
<MJD>57628</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2225</X>
<Y>0.3838</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.25756</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>29</dateDay>
<MJD>57629</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2229</X>
<Y>0.3820</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.25835</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>30</dateDay>
<MJD>57630</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2232</X>
<Y>0.3802</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.25919</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>31</dateDay>
<MJD>57631</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2236</X>
<Y>0.3784</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.26009</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>09</dateMonth>
<dateDay>01</dateDay>
<MJD>57632</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2239</X>
<Y>0.3766</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.26106</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>09</dateMonth>
<dateDay>02</dateDay>
<MJD>57633</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2241</X>
<Y>0.3747</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.26208</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>09</dateMonth>
<dateDay>03</dateDay>
<MJD>57634</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2244</X>
<Y>0.3729</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.26311</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>09</dateMonth>
<dateDay>04</dateDay>
<MJD>57635</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2246</X>
<Y>0.3711</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.26413</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>09</dateMonth>
<dateDay>05</dateDay>
<MJD>57636</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2247</X>
<Y>0.3692</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.26511</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>09</dateMonth>
<dateDay>06</dateDay>
<MJD>57637</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2248</X>
<Y>0.3674</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.26602</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>09</dateMonth>
<dateDay>07</dateDay>
<MJD>57638</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2249</X>
<Y>0.3656</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.26685</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>09</dateMonth>
<dateDay>08</dateDay>
<MJD>57639</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2250</X>
<Y>0.3637</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.26760</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>09</dateMonth>
<dateDay>09</dateDay>
<MJD>57640</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2250</X>
<Y>0.3619</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.26830</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>09</dateMonth>
<dateDay>10</dateDay>
<MJD>57641</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2250</X>
<Y>0.3600</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.26898</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>09</dateMonth>
<dateDay>11</dateDay>
<MJD>57642</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2250</X>
<Y>0.3582</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.26969</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>09</dateMonth>
<dateDay>12</dateDay>
<MJD>57643</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2249</X>
<Y>0.3564</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.27048</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>09</dateMonth>
<dateDay>13</dateDay>
<MJD>57644</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2248</X>
<Y>0.3545</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.27141</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>09</dateMonth>
<dateDay>14</dateDay>
<MJD>57645</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2247</X>
<Y>0.3527</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.27253</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>09</dateMonth>
<dateDay>15</dateDay>
<MJD>57646</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2245</X>
<Y>0.3508</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.27388</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>09</dateMonth>
<dateDay>16</dateDay>
<MJD>57647</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2243</X>
<Y>0.3490</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.27545</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>09</dateMonth>
<dateDay>17</dateDay>
<MJD>57648</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2241</X>
<Y>0.3472</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.27723</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>09</dateMonth>
<dateDay>18</dateDay>
<MJD>57649</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2238</X>
<Y>0.3454</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.27914</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>09</dateMonth>
<dateDay>19</dateDay>
<MJD>57650</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2235</X>
<Y>0.3435</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.28109</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>09</dateMonth>
<dateDay>20</dateDay>
<MJD>57651</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2231</X>
<Y>0.3417</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.28298</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>09</dateMonth>
<dateDay>21</dateDay>
<MJD>57652</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2228</X>
<Y>0.3399</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.28476</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>09</dateMonth>
<dateDay>22</dateDay>
<MJD>57653</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2224</X>
<Y>0.3381</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.28641</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>09</dateMonth>
<dateDay>23</dateDay>
<MJD>57654</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2219</X>
<Y>0.3363</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.28796</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>09</dateMonth>
<dateDay>24</dateDay>
<MJD>57655</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2214</X>
<Y>0.3345</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.28943</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>09</dateMonth>
<dateDay>25</dateDay>
<MJD>57656</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2209</X>
<Y>0.3327</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.29089</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>09</dateMonth>
<dateDay>26</dateDay>
<MJD>57657</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2204</X>
<Y>0.3309</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.29237</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>09</dateMonth>
<dateDay>27</dateDay>
<MJD>57658</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2198</X>
<Y>0.3292</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.29390</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>09</dateMonth>
<dateDay>28</dateDay>
<MJD>57659</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2192</X>
<Y>0.3274</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.29549</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>09</dateMonth>
<dateDay>29</dateDay>
<MJD>57660</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2186</X>
<Y>0.3257</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.29715</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>09</dateMonth>
<dateDay>30</dateDay>
<MJD>57661</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2179</X>
<Y>0.3239</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.29884</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>10</dateMonth>
<dateDay>01</dateDay>
<MJD>57662</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2172</X>
<Y>0.3222</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.30053</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>10</dateMonth>
<dateDay>02</dateDay>
<MJD>57663</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2165</X>
<Y>0.3205</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.30220</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>10</dateMonth>
<dateDay>03</dateDay>
<MJD>57664</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2157</X>
<Y>0.3188</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.30381</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>10</dateMonth>
<dateDay>04</dateDay>
<MJD>57665</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2149</X>
<Y>0.3171</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.30536</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>10</dateMonth>
<dateDay>05</dateDay>
<MJD>57666</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2141</X>
<Y>0.3154</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.30687</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>10</dateMonth>
<dateDay>06</dateDay>
<MJD>57667</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2133</X>
<Y>0.3137</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.30834</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>10</dateMonth>
<dateDay>07</dateDay>
<MJD>57668</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2124</X>
<Y>0.3121</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.30979</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>10</dateMonth>
<dateDay>08</dateDay>
<MJD>57669</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2115</X>
<Y>0.3104</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.31124</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>10</dateMonth>
<dateDay>09</dateDay>
<MJD>57670</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2105</X>
<Y>0.3088</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.31271</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>10</dateMonth>
<dateDay>10</dateDay>
<MJD>57671</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2096</X>
<Y>0.3072</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.31425</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>10</dateMonth>
<dateDay>11</dateDay>
<MJD>57672</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2086</X>
<Y>0.3056</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.31591</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>10</dateMonth>
<dateDay>12</dateDay>
<MJD>57673</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2075</X>
<Y>0.3040</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.31773</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>10</dateMonth>
<dateDay>13</dateDay>
<MJD>57674</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2065</X>
<Y>0.3024</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.31977</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>10</dateMonth>
<dateDay>14</dateDay>
<MJD>57675</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2054</X>
<Y>0.3009</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.32199</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>10</dateMonth>
<dateDay>15</dateDay>
<MJD>57676</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2043</X>
<Y>0.2993</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.32433</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>10</dateMonth>
<dateDay>16</dateDay>
<MJD>57677</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2031</X>
<Y>0.2978</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.32680</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>10</dateMonth>
<dateDay>17</dateDay>
<MJD>57678</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2019</X>
<Y>0.2963</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.32916</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>10</dateMonth>
<dateDay>18</dateDay>
<MJD>57679</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2008</X>
<Y>0.2948</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.33138</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>10</dateMonth>
<dateDay>19</dateDay>
<MJD>57680</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1995</X>
<Y>0.2933</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.33344</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>10</dateMonth>
<dateDay>20</dateDay>
<MJD>57681</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1983</X>
<Y>0.2919</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.33532</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>10</dateMonth>
<dateDay>21</dateDay>
<MJD>57682</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1970</X>
<Y>0.2905</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.33708</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>10</dateMonth>
<dateDay>22</dateDay>
<MJD>57683</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1957</X>
<Y>0.2891</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.33875</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>10</dateMonth>
<dateDay>23</dateDay>
<MJD>57684</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1944</X>
<Y>0.2877</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.34039</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>10</dateMonth>
<dateDay>24</dateDay>
<MJD>57685</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1930</X>
<Y>0.2863</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.34203</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>10</dateMonth>
<dateDay>25</dateDay>
<MJD>57686</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1916</X>
<Y>0.2849</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.34377</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>10</dateMonth>
<dateDay>26</dateDay>
<MJD>57687</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1902</X>
<Y>0.2836</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.34554</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>10</dateMonth>
<dateDay>27</dateDay>
<MJD>57688</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1888</X>
<Y>0.2823</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.34733</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>10</dateMonth>
<dateDay>28</dateDay>
<MJD>57689</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1874</X>
<Y>0.2810</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.34916</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>10</dateMonth>
<dateDay>29</dateDay>
<MJD>57690</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1859</X>
<Y>0.2798</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.35088</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>10</dateMonth>
<dateDay>30</dateDay>
<MJD>57691</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1844</X>
<Y>0.2785</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.35262</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>10</dateMonth>
<dateDay>31</dateDay>
<MJD>57692</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1829</X>
<Y>0.2773</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.35429</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>11</dateMonth>
<dateDay>01</dateDay>
<MJD>57693</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1814</X>
<Y>0.2761</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.35589</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>11</dateMonth>
<dateDay>02</dateDay>
<MJD>57694</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1798</X>
<Y>0.2749</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.35737</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>11</dateMonth>
<dateDay>03</dateDay>
<MJD>57695</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1782</X>
<Y>0.2738</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.35884</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>11</dateMonth>
<dateDay>04</dateDay>
<MJD>57696</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1766</X>
<Y>0.2727</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.36030</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>11</dateMonth>
<dateDay>05</dateDay>
<MJD>57697</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1750</X>
<Y>0.2716</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.36180</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>11</dateMonth>
<dateDay>06</dateDay>
<MJD>57698</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1734</X>
<Y>0.2705</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.36333</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>11</dateMonth>
<dateDay>07</dateDay>
<MJD>57699</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1717</X>
<Y>0.2694</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.36496</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>11</dateMonth>
<dateDay>08</dateDay>
<MJD>57700</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1700</X>
<Y>0.2684</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.36677</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>11</dateMonth>
<dateDay>09</dateDay>
<MJD>57701</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1683</X>
<Y>0.2674</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.36883</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>11</dateMonth>
<dateDay>10</dateDay>
<MJD>57702</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1666</X>
<Y>0.2664</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.37114</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>11</dateMonth>
<dateDay>11</dateDay>
<MJD>57703</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1649</X>
<Y>0.2655</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.37367</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>11</dateMonth>
<dateDay>12</dateDay>
<MJD>57704</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1632</X>
<Y>0.2646</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.37628</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>11</dateMonth>
<dateDay>13</dateDay>
<MJD>57705</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1614</X>
<Y>0.2637</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.37884</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>11</dateMonth>
<dateDay>14</dateDay>
<MJD>57706</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1596</X>
<Y>0.2628</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.38139</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>11</dateMonth>
<dateDay>15</dateDay>
<MJD>57707</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1578</X>
<Y>0.2620</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.38370</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>11</dateMonth>
<dateDay>16</dateDay>
<MJD>57708</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1560</X>
<Y>0.2612</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.38589</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>11</dateMonth>
<dateDay>17</dateDay>
<MJD>57709</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1542</X>
<Y>0.2604</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.38787</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>11</dateMonth>
<dateDay>18</dateDay>
<MJD>57710</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1524</X>
<Y>0.2596</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.38971</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>11</dateMonth>
<dateDay>19</dateDay>
<MJD>57711</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1505</X>
<Y>0.2589</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.39148</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>11</dateMonth>
<dateDay>20</dateDay>
<MJD>57712</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1487</X>
<Y>0.2582</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.39326</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>11</dateMonth>
<dateDay>21</dateDay>
<MJD>57713</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1468</X>
<Y>0.2575</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.39506</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>11</dateMonth>
<dateDay>22</dateDay>
<MJD>57714</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1449</X>
<Y>0.2568</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.39694</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>11</dateMonth>
<dateDay>23</dateDay>
<MJD>57715</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1431</X>
<Y>0.2562</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.39886</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>11</dateMonth>
<dateDay>24</dateDay>
<MJD>57716</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1412</X>
<Y>0.2556</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.40081</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>11</dateMonth>
<dateDay>25</dateDay>
<MJD>57717</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1392</X>
<Y>0.2551</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.40269</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>11</dateMonth>
<dateDay>26</dateDay>
<MJD>57718</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1373</X>
<Y>0.2545</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.40445</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>11</dateMonth>
<dateDay>27</dateDay>
<MJD>57719</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1354</X>
<Y>0.2540</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.40609</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>11</dateMonth>
<dateDay>28</dateDay>
<MJD>57720</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1335</X>
<Y>0.2536</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.40760</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>11</dateMonth>
<dateDay>29</dateDay>
<MJD>57721</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1315</X>
<Y>0.2531</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.40890</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>11</dateMonth>
<dateDay>30</dateDay>
<MJD>57722</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1296</X>
<Y>0.2527</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.41012</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>12</dateMonth>
<dateDay>01</dateDay>
<MJD>57723</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1276</X>
<Y>0.2523</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.41124</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>12</dateMonth>
<dateDay>02</dateDay>
<MJD>57724</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1257</X>
<Y>0.2520</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.41223</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>12</dateMonth>
<dateDay>03</dateDay>
<MJD>57725</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1237</X>
<Y>0.2516</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.41316</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>12</dateMonth>
<dateDay>04</dateDay>
<MJD>57726</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1217</X>
<Y>0.2513</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.41403</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>12</dateMonth>
<dateDay>05</dateDay>
<MJD>57727</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1197</X>
<Y>0.2511</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.41496</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>12</dateMonth>
<dateDay>06</dateDay>
<MJD>57728</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1178</X>
<Y>0.2508</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.41611</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>12</dateMonth>
<dateDay>07</dateDay>
<MJD>57729</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1158</X>
<Y>0.2506</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.41730</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>12</dateMonth>
<dateDay>08</dateDay>
<MJD>57730</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1138</X>
<Y>0.2504</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.41869</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>12</dateMonth>
<dateDay>09</dateDay>
<MJD>57731</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1118</X>
<Y>0.2503</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.42023</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>12</dateMonth>
<dateDay>10</dateDay>
<MJD>57732</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1098</X>
<Y>0.2502</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.42184</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>12</dateMonth>
<dateDay>11</dateDay>
<MJD>57733</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1078</X>
<Y>0.2501</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.42344</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>12</dateMonth>
<dateDay>12</dateDay>
<MJD>57734</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1058</X>
<Y>0.2500</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.42499</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>12</dateMonth>
<dateDay>13</dateDay>
<MJD>57735</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1039</X>
<Y>0.2500</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.42652</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>12</dateMonth>
<dateDay>14</dateDay>
<MJD>57736</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1019</X>
<Y>0.2500</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.42794</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>12</dateMonth>
<dateDay>15</dateDay>
<MJD>57737</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0999</X>
<Y>0.2500</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.42922</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>12</dateMonth>
<dateDay>16</dateDay>
<MJD>57738</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0979</X>
<Y>0.2501</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.43045</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>12</dateMonth>
<dateDay>17</dateDay>
<MJD>57739</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0959</X>
<Y>0.2502</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.43165</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>12</dateMonth>
<dateDay>18</dateDay>
<MJD>57740</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0939</X>
<Y>0.2503</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.43291</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>12</dateMonth>
<dateDay>19</dateDay>
<MJD>57741</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0920</X>
<Y>0.2505</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.43416</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>12</dateMonth>
<dateDay>20</dateDay>
<MJD>57742</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0900</X>
<Y>0.2506</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.43544</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>12</dateMonth>
<dateDay>21</dateDay>
<MJD>57743</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0880</X>
<Y>0.2509</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.43671</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>12</dateMonth>
<dateDay>22</dateDay>
<MJD>57744</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0861</X>
<Y>0.2511</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.43799</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>12</dateMonth>
<dateDay>23</dateDay>
<MJD>57745</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0841</X>
<Y>0.2514</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.43922</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>12</dateMonth>
<dateDay>24</dateDay>
<MJD>57746</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0822</X>
<Y>0.2517</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.44043</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>12</dateMonth>
<dateDay>25</dateDay>
<MJD>57747</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0802</X>
<Y>0.2520</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.44151</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>12</dateMonth>
<dateDay>26</dateDay>
<MJD>57748</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0783</X>
<Y>0.2524</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.44257</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>12</dateMonth>
<dateDay>27</dateDay>
<MJD>57749</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0764</X>
<Y>0.2527</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.44352</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>12</dateMonth>
<dateDay>28</dateDay>
<MJD>57750</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0744</X>
<Y>0.2532</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.44445</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>12</dateMonth>
<dateDay>29</dateDay>
<MJD>57751</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0725</X>
<Y>0.2536</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.44540</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>12</dateMonth>
<dateDay>30</dateDay>
<MJD>57752</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0706</X>
<Y>0.2541</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.44644</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>12</dateMonth>
<dateDay>31</dateDay>
<MJD>57753</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0688</X>
<Y>0.2546</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.44753</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>01</dateDay>
<MJD>57754</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0669</X>
<Y>0.2551</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.44878</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>02</dateDay>
<MJD>57755</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0650</X>
<Y>0.2557</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.45014</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>0.0632</X>
<Y>0.2563</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.45162</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>0.0613</X>
<Y>0.2569</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.45320</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>05</dateDay>
<MJD>57758</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0595</X>
<Y>0.2575</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.45490</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>0.0577</X>
<Y>0.2582</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.45662</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>0.0559</X>
<Y>0.2589</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.45831</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>0.0541</X>
<Y>0.2596</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.45996</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>0.0523</X>
<Y>0.2604</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.46148</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>0.0506</X>
<Y>0.2611</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.46285</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>0.0488</X>
<Y>0.2620</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.46404</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>12</dateDay>
<MJD>57765</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0471</X>
<Y>0.2628</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.46516</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>13</dateDay>
<MJD>57766</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0454</X>
<Y>0.2636</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.46622</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>14</dateDay>
<MJD>57767</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0437</X>
<Y>0.2645</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.46732</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>15</dateDay>
<MJD>57768</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0420</X>
<Y>0.2654</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.46840</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>0.0404</X>
<Y>0.2664</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.46949</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>17</dateDay>
<MJD>57770</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0387</X>
<Y>0.2673</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.47061</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>18</dateDay>
<MJD>57771</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0371</X>
<Y>0.2683</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.47174</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>19</dateDay>
<MJD>57772</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0355</X>
<Y>0.2693</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.47284</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>20</dateDay>
<MJD>57773</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0339</X>
<Y>0.2704</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.47393</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>21</dateDay>
<MJD>57774</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0324</X>
<Y>0.2714</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.47497</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>22</dateDay>
<MJD>57775</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0308</X>
<Y>0.2725</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.47591</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>23</dateDay>
<MJD>57776</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0293</X>
<Y>0.2736</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.47678</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>24</dateDay>
<MJD>57777</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0278</X>
<Y>0.2747</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.47757</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>25</dateDay>
<MJD>57778</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0264</X>
<Y>0.2759</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.47829</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>26</dateDay>
<MJD>57779</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0249</X>
<Y>0.2770</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.47900</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>27</dateDay>
<MJD>57780</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0235</X>
<Y>0.2782</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.47964</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>28</dateDay>
<MJD>57781</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0221</X>
<Y>0.2794</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.48030</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>29</dateDay>
<MJD>57782</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0207</X>
<Y>0.2807</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.48105</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>30</dateDay>
<MJD>57783</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0193</X>
<Y>0.2819</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.48191</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>31</dateDay>
<MJD>57784</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0180</X>
<Y>0.2832</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.48296</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>02</dateMonth>
<dateDay>01</dateDay>
<MJD>57785</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0167</X>
<Y>0.2845</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.48414</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>02</dateMonth>
<dateDay>02</dateDay>
<MJD>57786</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0154</X>
<Y>0.2858</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.48547</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>02</dateMonth>
<dateDay>03</dateDay>
<MJD>57787</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0142</X>
<Y>0.2871</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.48680</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>02</dateMonth>
<dateDay>04</dateDay>
<MJD>57788</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0129</X>
<Y>0.2885</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.48820</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>02</dateMonth>
<dateDay>05</dateDay>
<MJD>57789</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0117</X>
<Y>0.2899</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.48955</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>02</dateMonth>
<dateDay>06</dateDay>
<MJD>57790</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0106</X>
<Y>0.2912</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.49082</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>02</dateMonth>
<dateDay>07</dateDay>
<MJD>57791</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0094</X>
<Y>0.2926</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.49206</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>02</dateMonth>
<dateDay>08</dateDay>
<MJD>57792</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0083</X>
<Y>0.2941</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.49329</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>02</dateMonth>
<dateDay>09</dateDay>
<MJD>57793</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0072</X>
<Y>0.2955</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.49450</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>02</dateMonth>
<dateDay>10</dateDay>
<MJD>57794</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0061</X>
<Y>0.2970</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.49568</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>02</dateMonth>
<dateDay>11</dateDay>
<MJD>57795</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0051</X>
<Y>0.2984</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.49687</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>0.0041</X>
<Y>0.2999</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.49811</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>0.0031</X>
<Y>0.3014</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.49930</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>0.0021</X>
<Y>0.3029</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.50046</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>0.0012</X>
<Y>0.3045</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.50154</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>0.0003</X>
<Y>0.3060</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.50252</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>-0.0005</X>
<Y>0.3076</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.50346</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>-0.0014</X>
<Y>0.3091</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.50439</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>-0.0022</X>
<Y>0.3107</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.50531</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>-0.0030</X>
<Y>0.3123</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.50626</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>-0.0037</X>
<Y>0.3139</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.50720</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>-0.0044</X>
<Y>0.3155</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.50819</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>-0.0051</X>
<Y>0.3172</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.50927</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>-0.0058</X>
<Y>0.3188</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.51047</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>-0.0064</X>
<Y>0.3205</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.51181</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>-0.0070</X>
<Y>0.3221</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.51342</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>-0.0075</X>
<Y>0.3238</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.51517</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>-0.0081</X>
<Y>0.3254</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.51705</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>-0.0086</X>
<Y>0.3271</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.51897</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>-0.0090</X>
<Y>0.3288</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.52093</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>-0.0095</X>
<Y>0.3305</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.52283</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
</data>
</EOP>
