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	<title>Anchorage Farm</title>
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	<description>Registered Romneys</description>
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		<link>https://www.anchorageromneys.com/2026/03/2420/</link>
		<comments>https://www.anchorageromneys.com/2026/03/2420/#comments</comments>
		<pubDate>Mon, 16 Mar 2026 22:11:54 +0000</pubDate>
		<dc:creator>Stephen Shafer</dc:creator>
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		<description><![CDATA[The post preceding this one is the second part of a white paper I wrote about recessive Romneys.  The first part was published on line in the Dec 2024 Ramblings, but sad to say, Ramblings has since gone dormant. The article is in the middle of the on-line Ramblings.                [...]]]></description>
				<content:encoded><![CDATA[<p><span style="font-size: medium;">The post preceding this one is the second part of a white paper I wrote about recessive Romneys.  The first part was published on line in the Dec 2024 Ramblings, but sad to say, Ramblings has since gone dormant. The article is in the middle of the on-line Ramblings.<a href="https://www.anchorageromneys.com/wp-content/uploads/2026/03/Rosa-and-2038-26-2.jpg"><img class="aligncenter size-medium wp-image-2421" alt="Rosa and 2038-26 (2)" src="https://www.anchorageromneys.com/wp-content/uploads/2026/03/Rosa-and-2038-26-2-300x225.jpg" width="300" height="225" /></a>                                       Here&#8217;s Rosa, age 10, with her lovely ewe lamb 2038-26</span></p>
<p><span style="font-size: large;">https://americanromney.org/wp-content/uploads/2024/12/December-17-2024.pdf</span></p>
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		<title>Recessive Romneys part 2</title>
		<link>https://www.anchorageromneys.com/2025/09/recessive-romneys-part-2/</link>
		<comments>https://www.anchorageromneys.com/2025/09/recessive-romneys-part-2/#comments</comments>
		<pubDate>Tue, 09 Sep 2025 19:41:03 +0000</pubDate>
		<dc:creator>Stephen Shafer</dc:creator>
				<category><![CDATA[Uncategorized]]></category>

		<guid isPermaLink="false">http://www.anchorageromneys.com/?p=2352</guid>
		<description><![CDATA[                                                                                                              [...]]]></description>
				<content:encoded><![CDATA[<p><a href="http://www.anchorageromneys.com/wp-content/uploads/2025/09/Sylvie.jpg"><img class="aligncenter size-medium wp-image-2357" alt="Sylvie" src="http://www.anchorageromneys.com/wp-content/uploads/2025/09/Sylvie-300x225.jpg" width="300" height="225" /></a></p>
<p>                                                                                                                                                        &#8220;Sylvie&#8221;                    photo by Stephen Shafer</p>
<p>      The December 2024 issue of Romney Ramblings carried part 1 of a white paper about recessively-colored Romneys.  This part 2 was to have come out in the next issue of Ramblings.  That is now months overdue; so, I’m putting the article on our Anchorage Farm web site.  It addresses why there so few registered recessive Romneys in America and what can be done to better that.  After all, it’s here they first (thanks to Morris Culver) took hold, opening the door to registering colored sheep of traditionally white breeds.  Ours is still the only country in which natural-colored Romneys (whether extension-dominant or agouti-recessive) are in the same purebred registry as white ones.</p>
<p>     “Natural color,” today sought-after by many breeders, now has a foothold in some traditionally white breeds.   Most such breed associations, however, do not register it. Romneys, Border Leicesters and Lincolns are the ones I know of.  The others direct traffic to NCWGA. </p>
<p>     As the proportion of Romney breeders who cultivate color in their flocks grows, many still don’t see the differences within “natural color” between “recessive” and “extension dominant” that were described in part 1.  Recessive color genetics get lost in the shuffle.   The show ring has a strong influence on that process.  </p>
<p>     Recessive Romneys generally don’t stand as tall nor have the body length of the extension-dominant sheep that now comprise just about all (but not all) the Natural-colored Romney class at larger shows. Also, most recessive lambs aren’t as dark as some extension-dominants.  Breeders focused on major shows thus prefer extension-dominant.  </p>
<p>     Another hurdle in selective breeding for recessives is that as Romneys age, it’s hard to tell the larger and darker ones apart from extension-dominants. Characteristic white markings like small “teardrops” may be hidden by facial wool. <span style="text-decoration: underline;">Early post-natal inspection (photographs strongly recommended) is a must for any breeder who has natural-colored Romneys of both genotypes that may have interbred.</span><i>                      </i></p>
<p>     The language of genetics is not an incentive to everyone to go deep on sorting out where coat color patterns came from.  Just reading part 1 and part 2, if you’ve got so far, probably felt like a flashback to high school biology with Mendel’s peas and terms like “alleles” “genes,” “loci,” “dominant,” “recessive,” “heterozygous,” “this locus,” “that locus,” “carrier frequency” “autosomal” “Punnett square” etc.</p>
<p>       Fundamentally, though, all<i> </i>that’s really needed is to understand that natural-colored Romneys can get their coat color pattern by two different modes of inheritance, recessive at the agouti locus or dominant at the extension locus.  A breeder can’t weave shadings in fleeces to taste or forecast a the coat pattern of yet unborn lamb lamb without attending to the difference. <span style="text-decoration: underline;">Good treatments of this topic are listed at the end.</span> </p>
<p>     Another reason  people shy away from recessive is that it can be slow and imprecise to figure out which two of the alleles recessive at the agouti locus to the dominant Awt are being expressed<i>. </i>On-line chat group help from world authorities like Margaret Howard and Dee Heinrich is no longer available.  Maggie is still ready and willing, however, to field individual inquiries at tawandafarms53(at)att.net.   Fortunately, these two and colleagues have published a guidebook, now in its fourth edition, which is referenced below.  </p>
<p>     Romney breeders have it relatively easy when trying to nail down color alleles. Within the several dozen described at the ovine agouti locus, only five are now well-established in American Romneys.   <span style="text-decoration: underline;">Light blue</span> (Albl) has a lighter and more extensive display than do the others.  <span style="text-decoration: underline;">Intermediate blue</span> (Aibl) has been discerned only in Moorits, which are both scarce and prized.   The next three get increasingly darker in color value, displaying less and less white going from <span style="text-decoration: underline;">dark blue </span>(Adlb)to <span style="text-decoration: underline;">midnight blue</span> (Ambl) to <span style="text-decoration: underline;">self </span>(Aa).  A breeder confident he or she is working with recessives can learn to categorize very young recessive lambs simply as “lighter” vs. “darker,” or on a self-styled scale like 1 to 5.  This can even be done by taking notes without photos.  Photos are much better; they allow reconsideration and review by a group. </p>
<p>     The ewe lamb below, 1937-24 BBR Tw, is on the light blue end of the Romney range.</p>
<p> <a href="http://www.anchorageromneys.com/wp-content/uploads/2025/09/p738R-side1.jpg"><img class="aligncenter size-medium wp-image-2354" alt="p738R side" src="http://www.anchorageromneys.com/wp-content/uploads/2025/09/p738R-side1-300x225.jpg" width="300" height="225" /></a></p>
<p>                                                                                                                                                                                   Photo Elizabeth  Shafer</p>
<p>     By contrast, the ewe lamb pictured below, 1945-24BBR Tw, is as about dark as an agouti recessive can be.</p>
<p> <a href="http://www.anchorageromneys.com/wp-content/uploads/2025/09/ewe1945.jpg"><img class="aligncenter size-medium wp-image-2355" alt="ewe1945" src="http://www.anchorageromneys.com/wp-content/uploads/2025/09/ewe1945-300x225.jpg" width="300" height="225" /></a></p>
<p>                                                                                                                                                                                      Photo Elizabeth Shafer</p>
<p>     Maybe the worst impediment to wider acceptance is that recessive Romneys are hard to find.  They are a heritage genotype within a breed that is itself not prevalent in America. Only a couple of places in the country could sell four good recessive lambs now and still have some to keep. A number, however, could let one or two go to introduce agouti color alleles to a white flock or to tease out alleles that are are latent there. </p>
<p>     There was to have been in the same Ramblings a paid advertisement giving contact information for all the breeders in ARBA that I know are actively working with recessive color.  That’s now appended to this essay.  Contact me to fix omissions. sqs1(at)columbia.net.  In making the list I’ve been heartened to learn that some ARBA members not listed are bringing out homozygous color in their flocks,  not always deliberately, but serendipitously.  The gene frequency of agouti recessive alleles in American Romneys is clearly higher than I had thought six months ago.  These flocks are another potential resource for recessive breeders.  It is possible <i>sometimes</i> to be quite sure a mature Romney is “recessive” based on inspection. Other cases may be too uncertain</p>
<p>     Small exchanges among active recessive Romney breeders are a good step.  We in ARBA need to promote what we cherish and to work with each other cross-country. Near-future imports of semen that will meet ARBA criteria are unlikely, though there are a couple of rams in Aotearoa (New Zealand) that qualify.  Consequently, we “recessivists” need to keep on the lookout at home and elsewhere for reports of any apparently white x white union that left a surprise colored lamb.  At Anchorage we’ve had two such over the years.  In both, the parents had a common ancestor.  Such surprises won’t necessarily be suitable for breeding, but some will.  I encourage anyone who knows of one to contact me, especially if the union was not consanguineous or only distantly so. </p>
<p>     This paper about recessive color in Romneys does not pretend that recessives are better for every breeder than extension-dominant. <span style="text-decoration: underline;">That statement is wholly untrue</span>. It does appeal for recognition, appreciation and conservation of agouti-recessive genetics that without such attention will be submerged by extension-dominant.  Seeing the difference is crucial. Closing words about agouti-recessive alleles in Romneys borrow from <i>South Pacific</i> “Once you have found [them], never let [them] go.”</p>
<p>     This  photo of spun yarns from a recessive flock in New Hampshire is a good sign-off.</p>
<p> <a href="http://www.anchorageromneys.com/wp-content/uploads/2025/09/walkeryarn.jpeg"><img class="aligncenter size-large wp-image-2356" alt="walkeryarn" src="http://www.anchorageromneys.com/wp-content/uploads/2025/09/walkeryarn-580x434.jpeg" width="580" height="434" /></a></p>
<p>                                                                                                                                                                   Photo by Theresa Walker</p>
<p><i>     End-note on the spotting locus</i>, which got only a few words in part 1: spotting, the wild card, is confusing. Even Dee Heinrich’s research and presentation (in <span style="text-decoration: underline;">Beyond the Coat</span>) does not make the operations of this locus and its possible interactions with the E and the A loci easy to understand and explain, at least not for me.  Spotting, however, should not scare anyone away from recessive color, any more than from extension dominant color. If a breeder’s goal is to eliminate it, Dee has set out guidelines, though not a sure quick path. Spotting need not be a detriment. It may be an asset for some breeders, even a fixture as it is in the <a href="about:blank">Zwartbles</a> breed.   It complicates the task of identifying agouti allelotypes when it prevents wool pigmentation just where an agouti genotype does the same.</p>
<p>&nbsp;</p>
<p><i>References</i></p>
<p>(on paper) Dee Heinrich, Margaret Howard, Christian Posbergh and Melissa Wubben <span style="text-decoration: underline;">Beyond the Coat of Many Colors: Combining the Art and Science of Sheep Color Genetics (</span>2021) To buy, contact Margaret Howard 935 Lichens Road Montague CA email enquiries to tawandafarms53[at]att.net</p>
<p>(on-line)   <a href="about:blank">https://americanromney.org/color-genetics/basic-info/</a></p>
<p>Wendy Allison four articles</p>
<p><a href="about:blank">https://www.colouredsheep.org.nz/2021/11/22/genetics-how-do-we-get-coloured-sheep/</a></p>
<p><a href="about:blank">https://www.colouredsheep.org.nz/2021/12/10/moustaches-fangs-and-nose-rings-colour-pattern-and-co-dominance/</a></p>
<p><a href="about:blank">https://www.colouredsheep.org.nz/2022/02/12/why-a-brown-spotted-lamb-is-like-the-holy-grail/</a></p>
<p><a href="about:blank">https://www.colouredsheep.org.nz/2022/03/01/genetics-breaking-the-rules/</a></p>
<p>Daniel Godfrey with Wendy Allison</p>
<p><a href="about:blank">https://www.colouredsheep.org.nz/2023/11/12/the-dangers-of-extension-dominant/</a> </p>
<p>&nbsp;</p>
<p><i>Acknowledgements</i> First and foremost, Margaret Howard for her vision, leadership and hard work getting recessive Romneys back into view after a near-total eclipse in the 1990s.</p>
<p>Margaret Howard and Dee Heinrich for a multiyear tutorial to many breeders, not just of Romneys, who wanted to learn more about color genetics in sheep.</p>
<p>Maggie and Dee for reading early drafts of this paper.  All mistakes are my own.</p>
<p>Appendix list of ARBA memers interested in recessive color</p>
<p><span style="font-size: medium;">        A search for ARBA members who deliberately breed for recessive color built the startup list below.  <i>Disclaimer</i>: There is no authoritative body that certifies a given Romney as “recessive,” no registry, no touchstone, no seal of approval.  It’s a judgment call, grounded in attention to the genetics of coat patterns. The more the parties know about the coat pattern genotypes of a sheep’s ancestors, the more definitive the call can be. Looking at a mature natural-colored Romney is not always reliable.  Reading a pedigree for BW and BB suffixes is even less so.</span></p>
<p><span style="font-size: medium;">       The difficulty in discernment is due to the high prevalence in American Romneys of “extension dominant” color.  This can mimic very dark recessive patterns and will hide the white displays that betoken certain other “recessives.”  In breeds without extension dominant (e.g. Icelandics, Shetlands in America), calling recessives is relatively easy. Not so in Romneys.</span></p>
<p><span style="font-size: medium;">       As compiler, I hope this starter list will stimulate interchange among listees and get them fielding many inquiries from off-list. I want it to grow, and welcome comments or questions to sqs1[at]columbia.edu regarding additions for the next version.  The counts by sex pertain to homozygous recessives; where no figure is given, the latest count was unavailable at press time.</span></p>
<p>&nbsp;</p>
<table width="594" border="0" cellspacing="0" cellpadding="0">
<tbody>
<tr>
<td valign="bottom" nowrap="nowrap" width="221">
<p align="center">contact e-mail</p>
</td>
<td valign="bottom" nowrap="nowrap" width="189">
<p align="center">contact person</p>
</td>
<td valign="bottom" nowrap="nowrap" width="44">
<p align="center">state</p>
</td>
<td valign="bottom" nowrap="nowrap" width="38">
<p align="center">ewes</p>
</td>
<td valign="bottom" nowrap="nowrap" width="52">
<p align="center">rams</p>
</td>
<td valign="bottom" nowrap="nowrap" width="51">
<p align="center">bb?</p>
</td>
</tr>
<tr>
<td valign="bottom" nowrap="nowrap" width="221">
<p><a href="mailto:lists@barinagaranch.com">lists(at)barinagaranch.com</a></p>
</td>
<td valign="bottom" nowrap="nowrap" width="189">
<p>Marcia Barinaga</p>
</td>
<td valign="bottom" nowrap="nowrap" width="44">
<p>CA</p>
</td>
<td valign="bottom" nowrap="nowrap" width="38">
<p align="right">21</p>
</td>
<td valign="bottom" nowrap="nowrap" width="52">
<p align="right">6</p>
</td>
<td valign="bottom" nowrap="nowrap" width="51">
<p align="center">yes</p>
</td>
</tr>
<tr>
<td valign="bottom" nowrap="nowrap" width="221">
<p><a href="mailto:tawandafarms53@att.net">tawandafarms53(at)att.net</a></p>
</td>
<td valign="bottom" nowrap="nowrap" width="189">
<p>Maggie Howard</p>
</td>
<td valign="bottom" nowrap="nowrap" width="44">
<p>CA</p>
</td>
<td valign="bottom" nowrap="nowrap" width="38">
<p align="right">0</p>
</td>
<td valign="bottom" nowrap="nowrap" width="52">
<p align="right">0</p>
</td>
<td valign="bottom" nowrap="nowrap" width="51"> </td>
</tr>
<tr>
<td valign="bottom" nowrap="nowrap" width="221">
<p><a href="mailto:melissaecunningham@yahoo.com">melissaecunningham(at)yahoo.com</a></p>
</td>
<td valign="bottom" nowrap="nowrap" width="189">
<p>Melissa Trojanoski</p>
</td>
<td valign="bottom" nowrap="nowrap" width="44">
<p>CT</p>
</td>
<td valign="bottom" nowrap="nowrap" width="38">
<p align="right">10</p>
</td>
<td valign="bottom" nowrap="nowrap" width="52">
<p align="right">2</p>
</td>
<td valign="bottom" nowrap="nowrap" width="51"> </td>
</tr>
<tr>
<td valign="bottom" nowrap="nowrap" width="221">
<p><a href="mailto:olympiafarm@att.net">olympiafarm(at)att.net</a></p>
</td>
<td valign="bottom" nowrap="nowrap" width="189">
<p>Anne McIntyre-Lahner</p>
</td>
<td valign="bottom" nowrap="nowrap" width="44">
<p>CT</p>
</td>
<td valign="bottom" nowrap="nowrap" width="38"> </td>
<td valign="bottom" nowrap="nowrap" width="52"> </td>
<td valign="bottom" nowrap="nowrap" width="51"> </td>
</tr>
<tr>
<td valign="bottom" nowrap="nowrap" width="221">
<p><a href="mailto:oakcreeksheep@yahoo.com">oakcreeksheep(at)yahoo.com</a></p>
</td>
<td valign="bottom" nowrap="nowrap" width="189">
<p>Melissa Wubben</p>
</td>
<td valign="bottom" nowrap="nowrap" width="44">
<p>IA</p>
</td>
<td valign="bottom" nowrap="nowrap" width="38">
<p align="right">18</p>
</td>
<td valign="bottom" nowrap="nowrap" width="52">
<p align="right">3</p>
</td>
<td valign="bottom" nowrap="nowrap" width="51">
<p align="center">yes</p>
</td>
</tr>
<tr>
<td valign="bottom" nowrap="nowrap" width="221">
<p><a href="mailto:kimberly@livingsky.com">kimberly(at)livingsky.com</a></p>
</td>
<td valign="bottom" nowrap="nowrap" width="189">
<p>Kimberly Thiessen</p>
</td>
<td valign="bottom" nowrap="nowrap" width="44">
<p>ID</p>
</td>
<td valign="bottom" nowrap="nowrap" width="38">
<p align="right">13</p>
</td>
<td valign="bottom" nowrap="nowrap" width="52">
<p align="right">4</p>
</td>
<td valign="bottom" nowrap="nowrap" width="51">
<p align="center">yes</p>
</td>
</tr>
<tr>
<td valign="bottom" nowrap="nowrap" width="221">
<p><a href="mailto:orrweaver@verizon.net">orrweaver(at)verizon.net</a></p>
</td>
<td valign="bottom" nowrap="nowrap" width="189">
<p>Sister Chrysorrimonii</p>
</td>
<td valign="bottom" nowrap="nowrap" width="44">
<p>MD</p>
</td>
<td valign="bottom" nowrap="nowrap" width="38">
<p align="right">6</p>
</td>
<td valign="bottom" nowrap="nowrap" width="52">
<p align="right">2</p>
</td>
<td valign="bottom" nowrap="nowrap" width="51"> </td>
</tr>
<tr>
<td valign="bottom" nowrap="nowrap" width="221">
<p><a href="mailto:windsweptsheep@gmail.com">windsweptsheep(at)gmail.com</a></p>
</td>
<td valign="bottom" nowrap="nowrap" width="189">
<p>Sue Posbergh</p>
</td>
<td valign="bottom" nowrap="nowrap" width="44">
<p>NJ</p>
</td>
<td valign="bottom" nowrap="nowrap" width="38">
<p align="right">9</p>
</td>
<td valign="bottom" nowrap="nowrap" width="52">
<p align="right">1</p>
</td>
<td valign="bottom" nowrap="nowrap" width="51"> </td>
</tr>
<tr>
<td valign="bottom" nowrap="nowrap" width="221">
<p><a href="mailto:maryiselinfineart@gmail.com">maryiselinfineart(at)gmail.com</a></p>
</td>
<td valign="bottom" nowrap="nowrap" width="189">
<p>Mary Iselin</p>
</td>
<td valign="bottom" nowrap="nowrap" width="44">
<p>NH</p>
</td>
<td valign="bottom" nowrap="nowrap" width="38">
<p align="right">7</p>
</td>
<td valign="bottom" nowrap="nowrap" width="52">
<p align="right">2</p>
</td>
<td valign="bottom" nowrap="nowrap" width="51"> </td>
</tr>
<tr>
<td valign="bottom" nowrap="nowrap" width="221">
<p><a href="mailto:theresawalker@comcast.net">theresawalker(at)comcast.net</a></p>
</td>
<td valign="bottom" nowrap="nowrap" width="189">
<p>Tim and Theresa Walker</p>
</td>
<td valign="bottom" nowrap="nowrap" width="44">
<p>NH</p>
</td>
<td valign="bottom" nowrap="nowrap" width="38">
<p align="right">7</p>
</td>
<td valign="bottom" nowrap="nowrap" width="52">
<p align="right">0</p>
</td>
<td valign="bottom" nowrap="nowrap" width="51"> </td>
</tr>
<tr>
<td valign="bottom" nowrap="nowrap" width="221">
<p><a href="mailto:windingwicksandwool@gmail.com">windingwicksandwool(at)gmail.com</a></p>
</td>
<td valign="bottom" nowrap="nowrap" width="189">
<p>Marianne DiTaranto</p>
</td>
<td valign="bottom" nowrap="nowrap" width="44">
<p>NH</p>
</td>
<td valign="bottom" nowrap="nowrap" width="38"> </td>
<td valign="bottom" nowrap="nowrap" width="52"> </td>
<td valign="bottom" nowrap="nowrap" width="51"> </td>
</tr>
<tr>
<td valign="bottom" nowrap="nowrap" width="221">
<p><span style="text-decoration: underline;"> </span></p>
</td>
<td valign="bottom" nowrap="nowrap" width="189">
<p>&nbsp;</p>
</td>
<td valign="bottom" nowrap="nowrap" width="44">
<p>&nbsp;</p>
</td>
<td valign="bottom" nowrap="nowrap" width="38">
<p align="right"> </p>
</td>
<td valign="bottom" nowrap="nowrap" width="52">
<p align="right"> </p>
</td>
<td valign="bottom" nowrap="nowrap" width="51">
<p align="right"> </p>
</td>
</tr>
<tr>
<td valign="bottom" nowrap="nowrap" width="221">
<p><a href="mailto:anchorageromneys@gmail.com">anchorageromneys(at)gmail.com</a></p>
</td>
<td valign="bottom" nowrap="nowrap" width="189">
<p>Rhonda Jaacks</p>
</td>
<td valign="bottom" nowrap="nowrap" width="44">
<p>NY</p>
</td>
<td valign="bottom" nowrap="nowrap" width="38">
<p align="right">13</p>
</td>
<td valign="bottom" nowrap="nowrap" width="52">
<p align="right">3</p>
</td>
<td valign="bottom" nowrap="nowrap" width="51"> </td>
</tr>
<tr>
<td valign="bottom" nowrap="nowrap" width="221">
<p><a href="mailto:applewoodacre@yahoo.com">applewoodacre(at)yahoo.com</a></p>
</td>
<td valign="bottom" nowrap="nowrap" width="189">
<p>Regina Embler</p>
</td>
<td valign="bottom" nowrap="nowrap" width="44">
<p>NY</p>
</td>
<td valign="bottom" nowrap="nowrap" width="38">
<p align="right">0</p>
</td>
<td valign="bottom" nowrap="nowrap" width="52">
<p align="right">1</p>
</td>
<td valign="bottom" nowrap="nowrap" width="51"> </td>
</tr>
<tr>
<td valign="bottom" nowrap="nowrap" width="221">
<p><a href="mailto:crazylegsfarm@gmail.com">crazylegsfarm(at)gmail.com</a></p>
</td>
<td valign="bottom" nowrap="nowrap" width="189">
<p>Norma Johnson-Glacy</p>
</td>
<td valign="bottom" nowrap="nowrap" width="44">
<p>NY</p>
</td>
<td valign="bottom" nowrap="nowrap" width="38"> </td>
<td valign="bottom" nowrap="nowrap" width="52"> </td>
<td valign="bottom" nowrap="nowrap" width="51"> </td>
</tr>
<tr>
<td valign="bottom" nowrap="nowrap" width="221">
<p><a href="mailto:ash.florafaunafarm@gmail.com">ash.florafaunafarm(at)gmail.com</a></p>
</td>
<td valign="bottom" nowrap="nowrap" width="189">
<p>Ashley Lovett</p>
</td>
<td valign="bottom" nowrap="nowrap" width="44">
<p>NY</p>
</td>
<td valign="bottom" nowrap="nowrap" width="38">
<p align="right">5</p>
</td>
<td valign="bottom" nowrap="nowrap" width="52">
<p align="right">1</p>
</td>
<td valign="bottom" nowrap="nowrap" width="51"> </td>
</tr>
<tr>
<td valign="bottom" nowrap="nowrap" width="221">
<p><a href="mailto:aceinthehole07@hotmail.com">aceinthehole07(at)hotmail.com</a></p>
</td>
<td valign="bottom" nowrap="nowrap" width="189">
<p>Ace Vandenack</p>
</td>
<td valign="bottom" nowrap="nowrap" width="44">
<p>OR</p>
</td>
<td valign="bottom" nowrap="nowrap" width="38">
<p align="right">12</p>
</td>
<td valign="bottom" nowrap="nowrap" width="52">
<p align="right">3</p>
</td>
<td valign="bottom" nowrap="nowrap" width="51"> </td>
</tr>
<tr>
<td valign="bottom" nowrap="nowrap" width="221">
<p><a href="mailto:kelly@oviesariesfarm.com">kelly(at)oviesariesfarm.com</a></p>
</td>
<td valign="bottom" nowrap="nowrap" width="189">
<p>Kelly Bell</p>
</td>
<td valign="bottom" nowrap="nowrap" width="44">
<p>OR</p>
</td>
<td valign="bottom" nowrap="nowrap" width="38">
<p align="right">22</p>
</td>
<td valign="bottom" nowrap="nowrap" width="52">
<p align="right">2</p>
</td>
<td valign="bottom" nowrap="nowrap" width="51"> </td>
</tr>
<tr>
<td valign="bottom" nowrap="nowrap" width="221">
<p><a href="mailto:sclambscapes@gmail.com">sclambscapes(at)gmail.com</a></p>
</td>
<td valign="bottom" nowrap="nowrap" width="189">
<p>Maria Rooney</p>
</td>
<td valign="bottom" nowrap="nowrap" width="44">
<p>OR</p>
</td>
<td valign="bottom" nowrap="nowrap" width="38">
<p align="right">35</p>
</td>
<td valign="bottom" nowrap="nowrap" width="52">
<p align="right">5</p>
</td>
<td valign="bottom" nowrap="nowrap" width="51"> </td>
</tr>
<tr>
<td valign="bottom" nowrap="nowrap" width="221">
<p><a href="mailto:blacksheepdoc@yahoo.com">blacksheepdoc(at)yahoo.com</a></p>
</td>
<td valign="bottom" nowrap="nowrap" width="189">
<p>Sarah Vining</p>
</td>
<td valign="bottom" nowrap="nowrap" width="44">
<p>WA</p>
</td>
<td valign="bottom" nowrap="nowrap" width="38">
<p align="right">6</p>
</td>
<td valign="bottom" nowrap="nowrap" width="52">
<p align="right">2</p>
</td>
<td valign="bottom" nowrap="nowrap" width="51"> </td>
</tr>
</tbody>
</table>
<p>&nbsp;</p>
<p>bb? “yes” means the recessives include moorits</p>
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		<title>Breeding sheep for resistance to worms</title>
		<link>https://www.anchorageromneys.com/2025/01/breeding-sheep-for-resistance-to-worms/</link>
		<comments>https://www.anchorageromneys.com/2025/01/breeding-sheep-for-resistance-to-worms/#comments</comments>
		<pubDate>Wed, 01 Jan 2025 19:40:04 +0000</pubDate>
		<dc:creator>Stephen Shafer</dc:creator>
				<category><![CDATA[Uncategorized]]></category>

		<guid isPermaLink="false">http://www.anchorageromneys.com/?p=2224</guid>
		<description><![CDATA[&#160;                                      Trish and Gordon Levet with Stephen,  Anchorage Farm 1999  photo E. Shafer                                                                         Writing and video by or about Gordon Levet Breeding Sheep that have a high immunity [...]]]></description>
				<content:encoded><![CDATA[<p>&nbsp;</p>
<p><a href="http://www.anchorageromneys.com/wp-content/uploads/2025/01/Levets1999.jpg"><img class="aligncenter size-large wp-image-2225" alt="Levets1999" src="http://www.anchorageromneys.com/wp-content/uploads/2025/01/Levets1999-580x394.jpg" width="580" height="394" /></a></p>
<p>                                     Trish and Gordon Levet with Stephen,  Anchorage Farm 1999  photo E. Shafer</p>
<p>                                                   <span style="font-size: medium;">                     Writing and video by or about Gordon Levet</span></p>
<p align="center"><span style="font-size: medium;"><b>Breeding Sheep that have a high immunity to worm challenges</b></span></p>
<p align="center"><span style="font-size: medium;"><b>Gordon Levet, Wellsford NZ</b></span></p>
<p align="center"><span style="font-size: medium;"><b>November 2024</b></span></p>
<p><span style="font-size: medium;"> </span></p>
<p><span style="font-size: medium;">     First an overview of worm challenges and the role of the immune system.  In feral sheep and in all mammals, worms have always been present.  In sheep there are six main worm species.  All cause ill health and stifle growth with some deaths occurring.  By far the deadliest is Haemonchus Contortus, commonly known as the Barbers Pole worm – BP worm – because of a red spiral in its entire length – blood.  It is the only one that sucks blood, with each worm sucking a mil of blood a day.  So, 500 worms would remove half a litre of blood every day.  Females produce 10,000 eggs each day.  It is truly a killer worm.  The natural habitat of feral sheep are the arid hills and mountains around the Mediterranean, Asia Minor and the Rockies of North America.  In small mobs, they would browse on brambles like wild roses and numerous small plants and shrubs.  They would only ingest worm larvae when grazing on grass around streams and other moist areas.  Their immune system evolved to control the low worm challenge animals face.  Worms play an important role in nature because they are one of the first to stimulate the immune system into action.</span></p>
<p><span style="font-size: medium;">      Now fast forward to our present farming methods.  We have changed the diet of sheep from browsing in small mobs over huge areas.  Now we farm sheep in big numbers on small areas of lush pasture where scientists estimate that one kilogram of herbage would contain 10,000 worm larvae.  For hundreds of thousands of years, the immune systems of sheep have been ‘programmed’ to control very low worm challenges.  So, our modern sheep now have a far greater worm challenge to face, probably a hundred-fold increase or maybe a thousand-fold, no-one knows.  So, we need to breed sheep that have a quicker responding and stronger immune responses to control the greatly increased worm levels.</span></p>
<p><span style="font-size: medium;">      Farming in a warm, wet, humid environment in NZ that favours all parasites fungi that produce toxins that kill sheep and cattle i.e. facial eczema, diseases like pneumonia that causes 94% to 96% of lambs in autumn to have lung damage that results in deaths every year, always 2% to 5% and in some years, higher.  I have also had a major worm problem where the deadly BP worm is the dominant species.  However, on the positive side, these are the ideal conditions to breed sheep that have resistance to all these health problems.</span></p>
<p><span style="font-size: medium;">      In the 1980’s I became aware that some lambs were more affected by worms than others, so believed that genetic factors could be involved.  I had already succeeded in breeding sheep to be resistant to footrot and scald in the previous 30 years, by the simple method of ‘culling the worst and breeding from the best’.  So believed the same selective breeding may succeed when applied to the worm problem.  In 1986 I discussed this subject with a parasitologist, Dr Tom Watson who agreed that it would be possible to breed sheep that were resistant worm challenges.  He provided protocols to be followed to begin this long-term mission, which some thought would take at least 25 years.  These protocols were to drench all ram lambs, then about 8 weeks later, take a dung sample from each lamb, send them to a laboratory for worm egg counting – faecal egg counting or FEC for short.  All lambs were then drenched.  The whole process was repeated a second time to achieve greater accuracy.  These egg counts indicate roughly the number of adult worms present.  When the egg counts become available, the average count for each sires’ ram lambs is assessed.  Over the years, I have used 10 to 12 sires.  In the early years, the average worm count varied greatly with a five-fold difference between the best and worst sire.  This variation was an early indication that progress was possible.  It was then a simple matter of using the best son of the best sire to mate with the second-best sires’ daughters.  Conversely, the daughters of the best sire would be mated with the best son of the second-best sire.</span></p>
<p><span style="font-size: medium;">      Four years after I started a very long journey, our NZ Department of Agriculture set up a national programme for ram breeders to join to breed for worm resistance with the same protocols I was following.  It was called Worm FEC.  About 30 joined with different breeds.  But many left within 5 years when it was realized that it was all hard work, costs and no tangible financial rewards.  Over the years, the membership wavered between 25 and 30.  In recent years there has been renewed interest in the genetic solution as drench resistance has become an increasing problem.</span></p>
<p><span style="font-size: medium;">      In NZ we have had a national breed programme since 1967 which with the aid of computers ranks all animals in a flock for many traits. This programme is called Sheep Improvement Limited or SIL.</span></p>
<p><span style="font-size: medium;">      Worm resistance is scored by  DPF (Dual purpose Fecal Egg Count) which I do not fully understand.  I believe the figure is a combination of the sheep’s individual faecal egg count – FEC, the sire’s FEC, together with the dam’s sire and the siblings FEC.  In other words, the historical background of FEC.  The figures generated are a minus figure for those that are more susceptible to worms and positive figure for resistant animals.  Thus, a sheep with -300 would be moderately susceptible to worms whereas sheep with a positive figure of 300 would be moderately resistant.  Those that have a figure over 700 would rank in my opinion as highly resistant to all worm challenges.  SIL also ranks all animals for all traits which is within the flock ranking.  There is also a national ranking of rams for those that are breeding for worm resistance.  It took me 26 years for my flock to reach an average of 296.  This figure was compromised because of using an outside sire which had less resistance.  The rate of progress increased rapidly to reach a DPF of 749 nine years later in 2020 when no outside sires were used.</span></p>
<p><span style="font-size: medium;">     In breeding for resistance, I did the opposite to best practice to minimize a worm challenge.  My aim was to give lambs the highest worm challenge possible.  Then the first FEC would reveal lambs that were resistant to this high challenge.  I would also indicate those that reacted the earliest.  For example, the 2019 born ram lambs – 399 – that had never been drenched had an average FEC of 3733 in the first FEC.  The highest 25550, the lowest 105.  There were only 13 under 500, 6 were by a sire who had only 28 sons tested.  The second test 4 weeks later average was only 122 with 70 nil counts.  This led me to claim success in my long mission.</span></p>
<p><span style="font-size: medium;">      What does all this mean for breeders who wish to breed for the resistance trait?</span></p>
<p><span style="font-size: medium;">      There is now semen available to ‘short circuit’ the long process of starting from scratch as I did.  Let me explain.  Using the semen from a ram with a DPF of 700 over an average non-resistant ewe should result in progeny varying from nil to 700, averaging 350, a figure that took me more than 26 years to reach.  I would rank the progeny of this ram as having moderate resistance which would require less drenching. Using another ram having the same DPF of 700 and the progeny should have an average DPF of over 500.  Now use a ram with a DPF of 1000 over the daughters of the second ram and the average should be around 750 which took me 34 years of long hours, much costs to achieve.</span></p>
<p><span style="font-size: medium;">      However, this is all hypothetical.  The only certainty with genetics is uncertainty.</span></p>
<p> **************************************************************************************************************</p>
<div><span style="font-size: medium;">More about Gordon, the studmaster at Kikitangeo for seventy years. <br /></span></div>
<div><span style="font-size: medium;">This ten-minute <a href="https://www.ruraldelivery.net.nz/posts/Kikitangeo-Romney-Stud">video</a> is a good introduction. </span></div>
<div> </div>
<div><span style="font-size: medium;"><a href="https://www.ruralnewsgroup.co.nz/rural-news/rural-management/managing-sheep-drench-resistance" target="_blank" data-saferedirecturl="https://www.google.com/url?q=https://www.ruralnewsgroup.co.nz/rural-news/rural-management/managing-sheep-drench-resistance&amp;source=gmail&amp;ust=1735843313371000&amp;usg=AOvVaw0oXcQNL8Lx_a6MF__bAMaC">https://www.ruralnewsgroup.co.<wbr />nz/rural-news/rural-<wbr />management/managing-sheep-<wbr />drench-resistance</a> article by Gordon</span></div>
<div> </div>
<div><span style="font-size: medium;"><a href="https://www.farmersweekly.co.nz/news/treasured-ewes-go-under-the-hammer/" target="_blank" data-saferedirecturl="https://www.google.com/url?q=https://www.farmersweekly.co.nz/news/treasured-ewes-go-under-the-hammer/&amp;source=gmail&amp;ust=1735843313371000&amp;usg=AOvVaw0gcxGmO_PGckOMQm1Q5tEe">https://www.farmersweekly.co.<wbr />nz/news/treasured-ewes-go-<wbr />under-the-hammer/</a>  anticipates the centennial dispersal sale.  There the Giddings family  bought a Kiki ewes and  rams to start the Kikitangeo South Stud in Aoraki at which KKS 7084/22 was bred.</span></div>
<div> </div>
<div><span style="font-size: medium;">Gordon Levet  received The Royal Society medallion and citation in 2009 for services to NZ agriculture and Beef + Lamb NZ’s Industry Innovation award in 2016.</span></div>
<div> </div>
<div><span style="font-size: medium;"><a href="https://primarywool.co.nz/news/gordon-levet-of-kikitangeo-stud-wellsford-wins-the-primary-wool-co-operative-sheep-industry-innovation-award/" target="_blank" data-saferedirecturl="https://www.google.com/url?q=https://primarywool.co.nz/news/gordon-levet-of-kikitangeo-stud-wellsford-wins-the-primary-wool-co-operative-sheep-industry-innovation-award/&amp;source=gmail&amp;ust=1735843313371000&amp;usg=AOvVaw1YnHWuQ8K9NXzZfOWTXwSV">https://primarywool.co.nz/<wbr />news/gordon-levet-of-<wbr />kikitangeo-stud-wellsford-<wbr />wins-the-primary-wool-co-<wbr />operative-sheep-industry-<wbr />innovation-award/</a> 2016</span></div>
<div> </div>
<div><span style="font-size: medium;">Husquavarna North Island Farm Forester of the Year 2019</span></div>
<div> </div>
<div><span style="font-size: medium;">Massey University Innovation Award 2019  <em>vide</em> <a href="https://www.youtube.com/watch?v=rEfq7YkxGWQ" target="_blank" data-saferedirecturl="https://www.google.com/url?q=https://www.youtube.com/watch?v%3DrEfq7YkxGWQ&amp;source=gmail&amp;ust=1735843313371000&amp;usg=AOvVaw3P8uVrtYzF2nTkMa5QhIJi">https://www.youtube.com/watch?<wbr />v=rEfq7YkxGWQ</a><br /></span></div>
<div> </div>
<div><span style="font-size: medium;">It&#8217;s been a signal  privilege to know  Gordon and Trish for the last 25 years, to talk about roses and  Dame Kiri as well as sheep and worms. We hope to pass the Kiki torch on in America.</span></div>
<div>
<p><span style="font-size: medium;"> </span></p>
</div>
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		<title>Greenhouse Gas Balance Sheet for Anchorage Farm</title>
		<link>https://www.anchorageromneys.com/2023/10/greenhouse-gas-balance-sheet-for-anchorage-farm/</link>
		<comments>https://www.anchorageromneys.com/2023/10/greenhouse-gas-balance-sheet-for-anchorage-farm/#comments</comments>
		<pubDate>Fri, 20 Oct 2023 20:31:47 +0000</pubDate>
		<dc:creator>Stephen Shafer</dc:creator>
				<category><![CDATA[Uncategorized]]></category>

		<guid isPermaLink="false">http://www.anchorageromneys.com/?p=2090</guid>
		<description><![CDATA[                                                                      Greenhouse Gas Balance Sheet for Anchorage Farm A greenhouse gas (GHG) balance sheet for a farm with livestock has three main entry categories – carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O).  CO2 is the GHG that by any credible calculation accounts for the lion’s share of the recent rise in global average [...]]]></description>
				<content:encoded><![CDATA[<p>                                                                      <span style="font-size: medium;">Greenhouse Gas Balance Sheet for Anchorage Farm</span></p>
<p>A greenhouse gas (GHG) balance sheet for a farm with livestock has three main entry categories – carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O).  CO2 is the GHG that by any credible calculation accounts for the lion’s share of the recent rise in global average surface temperatures. Its physical capacity to prevent heat from escaping the planet’s surface as infra-red radiation is the standard to which all other GHGs are compared by the ratio called global warming potential (GWP).</p>
<p><a href="http://www.anchorageromneys.com/wp-content/uploads/2023/10/flir2.gif"><img class="aligncenter size-medium wp-image-2099" alt="flir2" src="http://www.anchorageromneys.com/wp-content/uploads/2023/10/flir2-300x199.gif" width="300" height="199" /></a></p>
<p>The photograph by Environmental Defense Fund is meant to catch your eye.   It uses Thermal Infrared Hyperspectral Imaging to visualize as a black cloud  methane emissions from a natural gas withdrawal facility unseen by the eye. Its relevance to  this essay will emerge  in   section 2, on methane.</p>
<p>Emissions of all GHGs and of other atmospheric pollutants are supposed to be reported by large companies in three categories referred to as scopes 1, 2 and 3.  Scope 1 (<span style="text-decoration: underline;">direct</span>) includes emissions under the direct control of the reporting company’s management.  An example is gas and particulates emitted from the stacks of a plant that makes cement or steel using heat from combusting fossil fuels. Another is tailpipe emissions from the fleet of delivery vehicles (think Amazon). Scope 2 indirect are indirect emissions such as stack gas from an offsite fossil-fueled station that generates and transmits electric power to a reporting company like Google. Significant scope 2 indirect emissions can go un- or under-reported by large companies. An example is fugitive emissions of methane between fracking well and gas-fired generating plant.</p>
<p>Scope 3 indirect emissions are the hardest to delineate and track.  These can be <span style="text-decoration: underline;">upstream</span> (related, say, to the manufacture of equipment that will be used by the reporting company or to employee business travel) or <span style="text-decoration: underline;">downstream</span>, like tailpipe emissions from vehicles running on gasoline or diesel.  It’s important to avoid double-counting, equally important that nothing is hidden or effectively disowned. Who, for example, is ultimately responsible for tailpipe emissions of CO2 and other pollutants? These are usually booked by EPA under “transportation.  The oil companies that sell gasoline, diesel and jet fuel don’t take responsibility for those products under scope 3 indirect.  Exxon (https://corporate.exxonmobil.com/-/media/global/files/advancing-climate-solutions-progress-report/2023/2023-acs-progress-report-executive-summary.pdf ) speaks of achieved or planned reductions in scope 1, scope 2 and “upstream” emissions but is silent on scope 3 indirect downstream. Who would expect otherwise? Manufacturers of single-use plastics similarly deny responsibility for what their products are doing to the waters and biota of the living earth</p>
<p>Households, of course,  don’t market a product; so, household “carbon footprint” calculators don’t have scope 3 downstream emissions. For example, the EPA household calculator <a href="https://www3.epa.gov/carbon-footprint-calculator/">https://www3.epa.gov/carbon-footprint-calculator/</a>  combines emissions from heating with gas or oil with those from operating a vehicle and with waste management, all three being under direct control of the householder.  The calculator does register scope 2 indirect emissions from electricity generation.  Scope 3 indirect upstream is not in this calculator. Theoretically, this could include the energy costs and pollution due to manufacturing and delivering a vehicle or a new water heater or furnace.</p>
<p>A farm that markets a product could be said to have scope 3 indirect emissions downstream, for example methane from animals sold as breeding stock.   Oil companies don’t report the climate-breaking downstream emissions from their products. The end-user (Amazon, in our earlier example) is tagged with those emissions under scope 1.   It would be absurd for farms to act differently. The emissions of a ruminant after a shift from Farm A to Farm B would theoretically be reported by B in its scope 1 accounting for as long as the animal is there.  I say “theoretically” because there is no policy in the USA under which individual grazing operations must now report even guesstimated emissions of exhaled methane. Nor, in my opinion, should there be.             </p>
<p>                                                    Section 1 Carbon dioxide </p>
<p>The table below shows CO2 emissions attributable to livestock farming at Anchorage Farm circa 2014 with about 45 brood ewes. Scope 1 emissions are in regular type and <i>scope 2 indirect in italic.  </i>Scope 3 indirect upstream emissions are marked with an asterisk. The figures in column C are approximate.  </p>
<p>A ton of each of the three major greenhouse gases, when dispersed in the atmosphere, blocks the return of infra-red energy to space from earth’s surface to a different extent. Each thus contributes to atmospheric and global warming to a different extent per ton.   It is conventional to express the global warming potential (GWP) of methane and of nitrous oxide relative to that of CO2, as a CO2 equivalent, or CO2-e.  The GWP of methane relative to that of CO2 is highly unsettled.</p>
<p>In this table and the one following, units of CO2-e equal units of CO2.  CO2-e/FU is a term from Life Cycle Analysis meaning emissions expressed as CO2-e per functional unit (FU) of production. Examples of FU in the wider literature include kwh of electricity generated, mass unit of cement, kg of carcass weight, kg of table-ready meat, bushel of grain, or grams of complete and digestible protein.</p>
<p>Small farms do not report GHG emissions to any regulator under any of the three scopes.  Thankful that we don’t <i>have</i> to, we can for self-analysis organize our GHG accounting as if we did.   In the table below, reflecting conditions about ten years ago, the biggest single entry would be  indirect scope 2,  “Barns electric nonsolar.“  This shocking usage was due to several months during lambing of 24-hour incandescent lighting and almost year-round use of ventilation fans. Merging for a moment scope 1 and scope 2 shows that heating, cooling, lighting and ventilation of buildings accounted for 26.5 tons of CO2, more than half the total at that time. Using feed we had not grown ourselves (scope 3 upstream indirect) explained almost another 12 tons.</p>
<p>&nbsp;</p>
<p align="center"> </p>
<p>&nbsp;</p>
<table width="609" border="0" cellspacing="0" cellpadding="0">
<tbody>
<tr>
<td valign="bottom" nowrap="nowrap" width="37"> </td>
<td valign="bottom" nowrap="nowrap" width="167">
<p align="center">B</p>
</td>
<td valign="bottom" nowrap="nowrap" width="95">
<p align="center">C</p>
</td>
<td valign="bottom" nowrap="nowrap" width="61">
<p align="center">D</p>
</td>
<td valign="bottom" nowrap="nowrap" width="95">
<p align="center">E</p>
</td>
<td valign="bottom" nowrap="nowrap" width="84">
<p align="center">F</p>
</td>
<td valign="bottom" nowrap="nowrap" width="71">
<p align="center">G</p>
</td>
</tr>
<tr>
<td valign="bottom" nowrap="nowrap" width="37"> </td>
<td valign="bottom" nowrap="nowrap" width="167"> </td>
<td valign="bottom" nowrap="nowrap" width="95"> </td>
<td valign="bottom" nowrap="nowrap" width="61"> </td>
<td valign="bottom" nowrap="nowrap" width="95">
<p>CO2-e/FU</p>
</td>
<td valign="bottom" nowrap="nowrap" width="84">
<p>lbs CO2 /yr</p>
</td>
<td valign="bottom" nowrap="nowrap" width="71">
<p>tonnes</p>
</td>
</tr>
<tr>
<td valign="bottom" nowrap="nowrap" width="37"> </td>
<td valign="bottom" nowrap="nowrap" width="167"> </td>
<td valign="bottom" nowrap="nowrap" width="95"> </td>
<td valign="bottom" nowrap="nowrap" width="61"> </td>
<td valign="bottom" nowrap="nowrap" width="95"> </td>
<td valign="bottom" nowrap="nowrap" width="84"> </td>
<td valign="bottom" nowrap="nowrap" width="71">
<p>CO2-e/yr</p>
</td>
</tr>
<tr>
<td valign="bottom" nowrap="nowrap" width="37">
<p><i>1</i></p>
</td>
<td valign="bottom" nowrap="nowrap" width="167">
<p><i>Barns electric nonsolar</i></p>
</td>
<td valign="bottom" nowrap="nowrap" width="95">
<p><i>33400 kwh</i></p>
</td>
<td valign="bottom" nowrap="nowrap" width="61"> </td>
<td valign="bottom" nowrap="nowrap" width="95">
<p><i>0.9 lb/kwh</i></p>
</td>
<td valign="bottom" nowrap="nowrap" width="84">
<p align="right"><i>30060</i></p>
</td>
<td valign="bottom" nowrap="nowrap" width="71">
<p align="right"><i>13.7</i></p>
</td>
</tr>
<tr>
<td valign="bottom" nowrap="nowrap" width="37">
<p><i>2</i></p>
</td>
<td valign="bottom" nowrap="nowrap" width="167"> </td>
<td valign="bottom" nowrap="nowrap" width="95"> </td>
<td valign="bottom" nowrap="nowrap" width="61"> </td>
<td valign="bottom" nowrap="nowrap" width="95"> </td>
<td valign="bottom" nowrap="nowrap" width="84"> </td>
<td valign="bottom" nowrap="nowrap" width="71"> </td>
</tr>
<tr>
<td valign="bottom" nowrap="nowrap" width="37">
<p><i>3</i></p>
</td>
<td valign="bottom" nowrap="nowrap" width="167">
<p><i>Mgr hse elec nonsolar</i></p>
</td>
<td valign="bottom" nowrap="nowrap" width="95">
<p><i>11600 kwh</i></p>
</td>
<td valign="bottom" nowrap="nowrap" width="61"> </td>
<td valign="bottom" nowrap="nowrap" width="95">
<p><i>0.9 lb/kwh</i></p>
</td>
<td valign="bottom" nowrap="nowrap" width="84">
<p align="right"><i>10440</i></p>
</td>
<td valign="bottom" nowrap="nowrap" width="71">
<p align="right"><i>4.7</i></p>
</td>
</tr>
<tr>
<td valign="bottom" nowrap="nowrap" width="37">
<p>4</p>
</td>
<td valign="bottom" nowrap="nowrap" width="167">
<p>Mgr hse nat gas</p>
</td>
<td valign="bottom" nowrap="nowrap" width="95">
<p>1080 ccf</p>
</td>
<td valign="bottom" nowrap="nowrap" width="61"> </td>
<td valign="bottom" nowrap="nowrap" width="95">
<p>11.7 lb/ccf</p>
</td>
<td valign="bottom" nowrap="nowrap" width="84">
<p align="right">12636</p>
</td>
<td valign="bottom" nowrap="nowrap" width="71">
<p align="right">5.7</p>
</td>
</tr>
<tr>
<td valign="bottom" nowrap="nowrap" width="37">
<p>5</p>
</td>
<td valign="bottom" nowrap="nowrap" width="167">
<p>Truck towing vet runs</p>
</td>
<td valign="bottom" nowrap="nowrap" width="95">
<p>455 mi</p>
</td>
<td valign="bottom" nowrap="nowrap" width="61">
<p>37.9 gal</p>
</td>
<td valign="bottom" nowrap="nowrap" width="95">
<p>22.6 lbs/gal</p>
</td>
<td valign="bottom" nowrap="nowrap" width="84">
<p align="right">857</p>
</td>
<td valign="bottom" nowrap="nowrap" width="71">
<p align="right">3.9</p>
</td>
</tr>
<tr>
<td valign="bottom" nowrap="nowrap" width="37">
<p>6</p>
</td>
<td valign="bottom" nowrap="nowrap" width="167">
<p>Towing shows sales</p>
</td>
<td valign="bottom" nowrap="nowrap" width="95">
<p>1500 mi</p>
</td>
<td valign="bottom" nowrap="nowrap" width="61">
<p>125 gal</p>
</td>
<td valign="bottom" nowrap="nowrap" width="95">
<p>22.6 lbs/gal</p>
</td>
<td valign="bottom" nowrap="nowrap" width="84">
<p align="right">2825</p>
</td>
<td valign="bottom" nowrap="nowrap" width="71">
<p align="right">1.3</p>
</td>
</tr>
<tr>
<td valign="bottom" nowrap="nowrap" width="37">
<p>7</p>
</td>
<td valign="bottom" nowrap="nowrap" width="167">
<p>Truck no tow no grain</p>
</td>
<td valign="bottom" nowrap="nowrap" width="95">
<p>4145 mi</p>
</td>
<td valign="bottom" nowrap="nowrap" width="61">
<p>345 gal</p>
</td>
<td valign="bottom" nowrap="nowrap" width="95">
<p>22.6 lbs/gal</p>
</td>
<td valign="bottom" nowrap="nowrap" width="84">
<p align="right">7806</p>
</td>
<td valign="bottom" nowrap="nowrap" width="71">
<p align="right">3.5</p>
</td>
</tr>
<tr>
<td valign="bottom" nowrap="nowrap" width="37">
<p>8</p>
</td>
<td valign="bottom" nowrap="nowrap" width="167">
<p>Tractors diesel</p>
</td>
<td valign="bottom" nowrap="nowrap" width="95">
<p>130 hrs</p>
</td>
<td valign="bottom" nowrap="nowrap" width="61">
<p>43  gal</p>
</td>
<td valign="bottom" nowrap="nowrap" width="95">
<p>22.6 lbs/ gal</p>
</td>
<td valign="bottom" nowrap="nowrap" width="84">
<p align="right">972</p>
</td>
<td valign="bottom" nowrap="nowrap" width="71">
<p align="right">0.5</p>
</td>
</tr>
<tr>
<td valign="bottom" nowrap="nowrap" width="37">
<p>9</p>
</td>
<td valign="bottom" nowrap="nowrap" width="167">
<p>gas Mowers</p>
</td>
<td valign="bottom" nowrap="nowrap" width="95">
<p>100 hrs</p>
</td>
<td valign="bottom" nowrap="nowrap" width="61">
<p>100 gal</p>
</td>
<td valign="bottom" nowrap="nowrap" width="95">
<p>19.6 lbs/gal</p>
</td>
<td valign="bottom" nowrap="nowrap" width="84">
<p align="right">1960</p>
</td>
<td valign="bottom" nowrap="nowrap" width="71">
<p align="right">0.9</p>
</td>
</tr>
<tr>
<td valign="bottom" nowrap="nowrap" width="37">
<p>*10</p>
</td>
<td valign="bottom" nowrap="nowrap" width="167">
<p>Grain to producer gate</p>
</td>
<td valign="bottom" nowrap="nowrap" width="95">
<p>18 tons</p>
</td>
<td valign="bottom" nowrap="nowrap" width="61"> </td>
<td valign="bottom" nowrap="nowrap" width="95">
<p>505 lbs/ ton</p>
</td>
<td valign="bottom" nowrap="nowrap" width="84">
<p align="right">9090</p>
</td>
<td valign="bottom" nowrap="nowrap" width="71">
<p align="right">4.2</p>
</td>
</tr>
<tr>
<td valign="bottom" nowrap="nowrap" width="37">
<p>11</p>
</td>
<td valign="bottom" nowrap="nowrap" width="167">
<p>Trucking grain to us</p>
</td>
<td valign="bottom" nowrap="nowrap" width="95">
<p>720 mi</p>
</td>
<td valign="bottom" nowrap="nowrap" width="61">
<p>60 gal</p>
</td>
<td valign="bottom" nowrap="nowrap" width="95">
<p>22.6 lbs/gal</p>
</td>
<td valign="bottom" nowrap="nowrap" width="84">
<p align="right">1356</p>
</td>
<td valign="bottom" nowrap="nowrap" width="71">
<p align="right">0.6</p>
</td>
</tr>
<tr>
<td valign="bottom" nowrap="nowrap" width="37">
<p>*12</p>
</td>
<td valign="bottom" nowrap="nowrap" width="167">
<p>Hay to producer gate</p>
</td>
<td valign="bottom" nowrap="nowrap" width="95">
<p>37 tons</p>
</td>
<td valign="bottom" nowrap="nowrap" width="61"> </td>
<td valign="bottom" nowrap="nowrap" width="95">
<p>282 lbs/ ton</p>
</td>
<td valign="bottom" nowrap="nowrap" width="84">
<p align="right">14148</p>
</td>
<td valign="bottom" nowrap="nowrap" width="71">
<p align="right">6.4</p>
</td>
</tr>
<tr>
<td valign="bottom" nowrap="nowrap" width="37">
<p>*13</p>
</td>
<td valign="bottom" nowrap="nowrap" width="167">
<p>Straw to producer gate</p>
</td>
<td valign="bottom" nowrap="nowrap" width="95">
<p>5 tons</p>
</td>
<td valign="bottom" nowrap="nowrap" width="61"> </td>
<td valign="bottom" nowrap="nowrap" width="95">
<p>100 lbs/ton</p>
</td>
<td valign="bottom" nowrap="nowrap" width="84">
<p align="right">500</p>
</td>
<td valign="bottom" nowrap="nowrap" width="71">
<p align="right">0.2</p>
</td>
</tr>
<tr>
<td valign="bottom" nowrap="nowrap" width="37">
<p>14</p>
</td>
<td valign="bottom" nowrap="nowrap" width="167">
<p>Truck hay and straw</p>
</td>
<td valign="bottom" nowrap="nowrap" width="95">
<p>650 mi</p>
</td>
<td valign="bottom" nowrap="nowrap" width="61">
<p>54 gal</p>
</td>
<td valign="bottom" nowrap="nowrap" width="95">
<p>22.6 lbs/gal</p>
</td>
<td valign="bottom" nowrap="nowrap" width="84">
<p align="right">1220</p>
</td>
<td valign="bottom" nowrap="nowrap" width="71">
<p align="right">0.6</p>
</td>
</tr>
<tr>
<td valign="bottom" nowrap="nowrap" width="37"> </td>
<td valign="bottom" nowrap="nowrap" width="167">
<p>Total scope 1 direct</p>
</td>
<td valign="bottom" nowrap="nowrap" width="95"> </td>
<td valign="bottom" nowrap="nowrap" width="61"> </td>
<td valign="bottom" nowrap="nowrap" width="95"> </td>
<td valign="bottom" nowrap="nowrap" width="84"> </td>
<td valign="bottom" nowrap="nowrap" width="71">
<p align="right">17</p>
</td>
</tr>
<tr>
<td valign="bottom" nowrap="nowrap" width="37"> </td>
<td valign="bottom" nowrap="nowrap" width="167">
<p><i>Total scope 2 indirect</i></p>
</td>
<td valign="bottom" nowrap="nowrap" width="95"> </td>
<td valign="bottom" nowrap="nowrap" width="61"> </td>
<td valign="bottom" nowrap="nowrap" width="95"> </td>
<td valign="bottom" nowrap="nowrap" width="84"> </td>
<td valign="bottom" nowrap="nowrap" width="71">
<p align="right">18.4</p>
</td>
</tr>
<tr>
<td valign="bottom" nowrap="nowrap" width="37"> </td>
<td valign="bottom" nowrap="nowrap" width="167">
<p>Total scope 3 indirect*</p>
</td>
<td valign="bottom" nowrap="nowrap" width="95"> </td>
<td valign="bottom" nowrap="nowrap" width="61"> </td>
<td valign="bottom" nowrap="nowrap" width="95"> </td>
<td valign="bottom" nowrap="nowrap" width="84"> </td>
<td valign="bottom" nowrap="nowrap" width="71">
<p align="right">10.8</p>
</td>
</tr>
<tr>
<td valign="bottom" nowrap="nowrap" width="37">
<p>15</p>
</td>
<td valign="bottom" nowrap="nowrap" width="167">
<p>Total  rows 1-14</p>
</td>
<td valign="bottom" nowrap="nowrap" width="95"> </td>
<td valign="bottom" nowrap="nowrap" width="61"> </td>
<td valign="bottom" nowrap="nowrap" width="95"> </td>
<td valign="bottom" nowrap="nowrap" width="84"> </td>
<td valign="bottom" nowrap="nowrap" width="71">
<p align="right"><b>46.2</b></p>
</td>
</tr>
</tbody>
</table>
<p>                                                                        Table 1.  CO2 accounting circa  year 2014</p>
<p>&nbsp;</p>
<p>               Table 2, below, synthesizes approximate figures from mid-2023.  A major change from earlier is that electricity, now generated by wind and solar instead of gas, is “supplied by” Green Mountain Energy; that is, Green Mountain sends Central Hudson a kwh for every kwh Central Hudson sends us.  Electricity from wind and solar is not cheaper to the end-user than that from gas, but the process of generating it is almost emission free.  The figure I used for emissions related to wind and solar reflects the energy cost of building the facilities, running them and eventually dismantling then recycling or disposing of them.   It’s really a scope 3 indirect upstream item for Green Mountain Energy. I charge it to us to be conservative.</p>
<p>Table 2  is based on usage figures from the first 6 months of 2023 with one future possible change– reduction of imported  grain– grafted on  and one actual change, a 25% reduction of ewe flock size.   It reflects the significant decrease in scope 2 indirect CO2 emissions explained in the paragraph above.  It also indicates a big drop in scope 1 direct CO2 emissions from the farm, due to having installed heat pumps in the manager’s house in late fall 2022.  (I am surprised that Manager’s house electricity was down so much.  The improvements in heat loss from last fall’s insulation upgrade could be the reason. Barns electric is also much lower, probably because the lambing period with 24-hour lighting was unusually brief in 2023.)</p>
<p>&nbsp;</p>
<table width="648" border="0" cellspacing="0" cellpadding="0">
<tbody>
<tr>
<td valign="bottom" nowrap="nowrap" width="43"> </td>
<td valign="bottom" nowrap="nowrap" width="175">
<p align="center">B</p>
</td>
<td valign="bottom" nowrap="nowrap" width="89">
<p align="center">C</p>
</td>
<td valign="bottom" nowrap="nowrap" width="61">
<p align="center">D</p>
</td>
<td valign="bottom" nowrap="nowrap" width="101">
<p align="center">E</p>
</td>
<td valign="bottom" nowrap="nowrap" width="79">
<p align="center">F</p>
</td>
<td valign="bottom" nowrap="nowrap" width="100">
<p align="center">G</p>
</td>
</tr>
<tr>
<td valign="bottom" nowrap="nowrap" width="43"> </td>
<td valign="bottom" nowrap="nowrap" width="175"> </td>
<td valign="bottom" nowrap="nowrap" width="89"> </td>
<td valign="bottom" nowrap="nowrap" width="61"> </td>
<td valign="bottom" nowrap="nowrap" width="101">
<p>CO2/FU</p>
</td>
<td valign="bottom" nowrap="nowrap" width="79">
<p>lbs CO2-e</p>
</td>
<td valign="bottom" nowrap="nowrap" width="100">
<p>tonnes CO2-e</p>
</td>
</tr>
<tr>
<td valign="bottom" nowrap="nowrap" width="43"> </td>
<td valign="bottom" nowrap="nowrap" width="175"> </td>
<td valign="bottom" nowrap="nowrap" width="89"> </td>
<td valign="bottom" nowrap="nowrap" width="61"> </td>
<td valign="bottom" nowrap="nowrap" width="101"> </td>
<td valign="bottom" nowrap="nowrap" width="79">
<p>per year</p>
</td>
<td valign="bottom" nowrap="nowrap" width="100">
<p>per year</p>
</td>
</tr>
<tr>
<td valign="bottom" nowrap="nowrap" width="43">
<p><i>1</i></p>
</td>
<td valign="bottom" nowrap="nowrap" width="175">
<p><i>Barns electric GM</i></p>
</td>
<td valign="bottom" nowrap="nowrap" width="89">
<p><i>15000 kwh</i></p>
</td>
<td valign="bottom" nowrap="nowrap" width="61"> </td>
<td valign="bottom" nowrap="nowrap" width="101">
<p><i>0.2 lb/kwh</i></p>
</td>
<td valign="bottom" nowrap="nowrap" width="79">
<p align="right"><i>3000</i></p>
</td>
<td valign="bottom" nowrap="nowrap" width="100">
<p align="right"><i>1.4</i></p>
</td>
</tr>
<tr>
<td valign="bottom" nowrap="nowrap" width="43">
<p>2</p>
</td>
<td valign="bottom" nowrap="nowrap" width="175">
<p>Barns electric direct solar</p>
</td>
<td valign="bottom" nowrap="nowrap" width="89">
<p>3000 kwh</p>
</td>
<td valign="bottom" nowrap="nowrap" width="61"> </td>
<td valign="bottom" nowrap="nowrap" width="101">
<p>0.2 lb/kwh</p>
</td>
<td valign="bottom" nowrap="nowrap" width="79">
<p align="right">600</p>
</td>
<td valign="bottom" nowrap="nowrap" width="100">
<p align="right">0.3</p>
</td>
</tr>
<tr>
<td valign="bottom" nowrap="nowrap" width="43">
<p><i>3</i></p>
</td>
<td valign="bottom" nowrap="nowrap" width="175">
<p><i>Mgr hse elec GM</i></p>
</td>
<td valign="bottom" nowrap="nowrap" width="89">
<p><i>5000 kwh</i></p>
</td>
<td valign="bottom" nowrap="nowrap" width="61"> </td>
<td valign="bottom" nowrap="nowrap" width="101">
<p><i>0.2 lb/kwh</i></p>
</td>
<td valign="bottom" nowrap="nowrap" width="79">
<p align="right"><i>1000</i></p>
</td>
<td valign="bottom" nowrap="nowrap" width="100">
<p align="right"><i>0.5</i></p>
</td>
</tr>
<tr>
<td valign="bottom" nowrap="nowrap" width="43">
<p>4</p>
</td>
<td valign="bottom" nowrap="nowrap" width="175">
<p>Mgr hse nat gas</p>
</td>
<td valign="bottom" nowrap="nowrap" width="89">
<p>100 ccf</p>
</td>
<td valign="bottom" nowrap="nowrap" width="61"> </td>
<td valign="bottom" nowrap="nowrap" width="101">
<p>115 lb/Mbtu</p>
</td>
<td valign="bottom" nowrap="nowrap" width="79">
<p align="right">1150</p>
</td>
<td valign="bottom" nowrap="nowrap" width="100">
<p align="right">0.5</p>
</td>
</tr>
<tr>
<td valign="bottom" nowrap="nowrap" width="43">
<p>5</p>
</td>
<td valign="bottom" nowrap="nowrap" width="175">
<p>Truck towing vet runs</p>
</td>
<td valign="bottom" nowrap="nowrap" width="89">
<p><i>nil</i></p>
</td>
<td valign="bottom" nowrap="nowrap" width="61"> </td>
<td valign="bottom" nowrap="nowrap" width="101">
<p>22.6 lbs/gal</p>
</td>
<td valign="bottom" nowrap="nowrap" width="79"> </td>
<td valign="bottom" nowrap="nowrap" width="100"> </td>
</tr>
<tr>
<td valign="bottom" nowrap="nowrap" width="43">
<p>6</p>
</td>
<td valign="bottom" nowrap="nowrap" width="175">
<p>Towing livestock</p>
</td>
<td valign="bottom" nowrap="nowrap" width="89">
<p>1200 mi      </p>
</td>
<td valign="bottom" nowrap="nowrap" width="61">
<p>100  gal</p>
</td>
<td valign="bottom" nowrap="nowrap" width="101">
<p>22.6 lbs/gal</p>
</td>
<td valign="bottom" nowrap="nowrap" width="79">
<p align="right">2825</p>
</td>
<td valign="bottom" nowrap="nowrap" width="100">
<p align="right">1.3</p>
</td>
</tr>
<tr>
<td valign="bottom" nowrap="nowrap" width="43">
<p>7</p>
</td>
<td valign="bottom" nowrap="nowrap" width="175">
<p>Truck no tow no grain</p>
</td>
<td valign="bottom" nowrap="nowrap" width="89">
<p>3000 mi</p>
</td>
<td valign="bottom" nowrap="nowrap" width="61">
<p>345 gal</p>
</td>
<td valign="bottom" nowrap="nowrap" width="101">
<p>22.6 lbs/gal</p>
</td>
<td valign="bottom" nowrap="nowrap" width="79">
<p align="right">7806</p>
</td>
<td valign="bottom" nowrap="nowrap" width="100">
<p align="right">3.5</p>
</td>
</tr>
<tr>
<td valign="bottom" nowrap="nowrap" width="43">
<p>8</p>
</td>
<td valign="bottom" nowrap="nowrap" width="175">
<p>Tractors diesel</p>
</td>
<td valign="bottom" nowrap="nowrap" width="89">
<p>130 hrs</p>
</td>
<td valign="bottom" nowrap="nowrap" width="61">
<p>43  gal</p>
</td>
<td valign="bottom" nowrap="nowrap" width="101">
<p>22.6 lbs/ gal</p>
</td>
<td valign="bottom" nowrap="nowrap" width="79">
<p align="right">972</p>
</td>
<td valign="bottom" nowrap="nowrap" width="100">
<p align="right">0.5</p>
</td>
</tr>
<tr>
<td valign="bottom" nowrap="nowrap" width="43">
<p>9</p>
</td>
<td valign="bottom" nowrap="nowrap" width="175">
<p>gas mowers</p>
</td>
<td valign="bottom" nowrap="nowrap" width="89">
<p>100 hrs</p>
</td>
<td valign="bottom" nowrap="nowrap" width="61">
<p>100 gal</p>
</td>
<td valign="bottom" nowrap="nowrap" width="101">
<p>19.6 lbs/gal</p>
</td>
<td valign="bottom" nowrap="nowrap" width="79">
<p align="right">1960</p>
</td>
<td valign="bottom" nowrap="nowrap" width="100">
<p align="right">0.9</p>
</td>
</tr>
<tr>
<td valign="bottom" nowrap="nowrap" width="43">
<p>*10</p>
</td>
<td valign="bottom" nowrap="nowrap" width="175">
<p>Grain to producer  gate</p>
</td>
<td valign="bottom" nowrap="nowrap" width="89">
<p>9 tons</p>
</td>
<td valign="bottom" nowrap="nowrap" width="61"> </td>
<td valign="bottom" nowrap="nowrap" width="101">
<p>505 lbs/ ton</p>
</td>
<td valign="bottom" nowrap="nowrap" width="79">
<p align="right">4040</p>
</td>
<td valign="bottom" nowrap="nowrap" width="100">
<p align="right">1.8</p>
</td>
</tr>
<tr>
<td valign="bottom" nowrap="nowrap" width="43">
<p>11</p>
</td>
<td valign="bottom" nowrap="nowrap" width="175">
<p>Trucking  grain to us</p>
</td>
<td valign="bottom" nowrap="nowrap" width="89">
<p>360 mi</p>
</td>
<td valign="bottom" nowrap="nowrap" width="61">
<p>30  gal</p>
</td>
<td valign="bottom" nowrap="nowrap" width="101">
<p>22.6 lbs/gal</p>
</td>
<td valign="bottom" nowrap="nowrap" width="79">
<p align="right">678</p>
</td>
<td valign="bottom" nowrap="nowrap" width="100">
<p align="right">0.3</p>
</td>
</tr>
<tr>
<td valign="bottom" nowrap="nowrap" width="43">
<p>*12</p>
</td>
<td valign="bottom" nowrap="nowrap" width="175">
<p>Hay to producer gate</p>
</td>
<td valign="bottom" nowrap="nowrap" width="89">
<p>37 tons</p>
</td>
<td valign="bottom" nowrap="nowrap" width="61"> </td>
<td valign="bottom" nowrap="nowrap" width="101">
<p>282 lbs/ ton</p>
</td>
<td valign="bottom" nowrap="nowrap" width="79">
<p align="right">14148</p>
</td>
<td valign="bottom" nowrap="nowrap" width="100">
<p align="right">6.4</p>
</td>
</tr>
<tr>
<td valign="bottom" nowrap="nowrap" width="43">
<p>*13</p>
</td>
<td valign="bottom" nowrap="nowrap" width="175">
<p>Straw to producer gate</p>
</td>
<td valign="bottom" nowrap="nowrap" width="89">
<p>5 tons</p>
</td>
<td valign="bottom" nowrap="nowrap" width="61"> </td>
<td valign="bottom" nowrap="nowrap" width="101">
<p>100 lbs/ton</p>
</td>
<td valign="bottom" nowrap="nowrap" width="79">
<p align="right">500</p>
</td>
<td valign="bottom" nowrap="nowrap" width="100">
<p align="right">0.2</p>
</td>
</tr>
<tr>
<td valign="bottom" nowrap="nowrap" width="43">
<p>14</p>
</td>
<td valign="bottom" nowrap="nowrap" width="175">
<p>Truck hay and straw</p>
</td>
<td valign="bottom" nowrap="nowrap" width="89">
<p>650 mi</p>
</td>
<td valign="bottom" nowrap="nowrap" width="61">
<p>54 gal</p>
</td>
<td valign="bottom" nowrap="nowrap" width="101">
<p>22.6 lbs/gal</p>
</td>
<td valign="bottom" nowrap="nowrap" width="79">
<p align="right">1220</p>
</td>
<td valign="bottom" nowrap="nowrap" width="100">
<p align="right">0.6</p>
</td>
</tr>
<tr>
<td valign="bottom" nowrap="nowrap" width="43">
<p>15</p>
</td>
<td valign="bottom" nowrap="nowrap" width="175">
<p>Total scope 1 direct</p>
</td>
<td valign="bottom" nowrap="nowrap" width="89"> </td>
<td valign="bottom" nowrap="nowrap" width="61"> </td>
<td valign="bottom" nowrap="nowrap" width="101"> </td>
<td valign="bottom" nowrap="nowrap" width="79"> </td>
<td valign="bottom" nowrap="nowrap" width="100">
<p align="right">7.9</p>
</td>
</tr>
<tr>
<td valign="bottom" nowrap="nowrap" width="43">
<p>16</p>
</td>
<td valign="bottom" nowrap="nowrap" width="175">
<p>Total scope 2 indirect</p>
</td>
<td valign="bottom" nowrap="nowrap" width="89"> </td>
<td valign="bottom" nowrap="nowrap" width="61"> </td>
<td valign="bottom" nowrap="nowrap" width="101"> </td>
<td valign="bottom" nowrap="nowrap" width="79"> </td>
<td valign="bottom" nowrap="nowrap" width="100">
<p align="right">1.9</p>
</td>
</tr>
<tr>
<td valign="bottom" nowrap="nowrap" width="43">
<p>17</p>
</td>
<td valign="bottom" nowrap="nowrap" width="175">
<p>Total scope 3 indirect</p>
</td>
<td valign="bottom" nowrap="nowrap" width="89"> </td>
<td valign="bottom" nowrap="nowrap" width="61"> </td>
<td valign="bottom" nowrap="nowrap" width="101"> </td>
<td valign="bottom" nowrap="nowrap" width="79"> </td>
<td valign="bottom" nowrap="nowrap" width="100">
<p align="right">8.4</p>
</td>
</tr>
<tr>
<td valign="bottom" nowrap="nowrap" width="43">
<p>18</p>
</td>
<td valign="bottom" nowrap="nowrap" width="175">
<p>Total rows 1-14</p>
</td>
<td valign="bottom" nowrap="nowrap" width="89"> </td>
<td valign="bottom" nowrap="nowrap" width="61"> </td>
<td valign="bottom" nowrap="nowrap" width="101"> </td>
<td valign="bottom" nowrap="nowrap" width="79"> </td>
<td valign="bottom" nowrap="nowrap" width="100">
<p align="right"><b>18.2</b></p>
</td>
</tr>
</tbody>
</table>
<p>                                Table 2.  Projection of CO2 accounting for 2024, to be compared to that in Table 1.</p>
<p>&nbsp;</p>
<p>From these approximate figures it’s clear that as to reducing the farm’s positive emissions of actual CO2, we’ve made good steps, more than a 60% reduction compared to a few years ago, even if there is no future decrease in grain feeding.  The sector that has changed the least over the last ten years is in scope 3 indirect, the upstream emissions associated with growing, gathering-in and transporting grain (corn, oats, soy meal), hay and straw. Can we tighten the belt in that area without compromising animal health? It is theoretically possible.</p>
<p>CO2 associated with the operations of an established farm (as opposed to “land use and land use changes”) is presents relatively few problems in accounting.  Methane and nitrous oxide, which together far outweigh CO2 as farming-related GHGs, are much harder to grapple with. Methane looms larger for a farm with livestock.</p>
<p>                                             Section 2 Methane</p>
<p>Most (say 80%) of the methane (CH4) emissions from a pasture-based ruminant livestock operation are from enteric fermentation. Some are from composting barn litter or manure and a smaller proportion from manure dropped on the grass. My first go at methane accounting for our farm used the COMET model developed at Colorado State with the USDA.   COMET predicts the changes in GHG fluxes in a particular farming operation as it changes practices.  COMET had and still has an exhaustive and exhausting method for reckoning CH4 emissions. It required entering the makeup of nutrient intake month by month for two age groups.  Through my own fault, the nutritional entries I made and all the analyses returned are lost for good.  I had written down for 60 head a figure of 5 tons CO2-e/yr for methane, presumably based on GWP100 of 28-34. That cannot have been right. The emission mass must have been underestimated. </p>
<p>Not ready to re-do CH4 in the very demanding COMET model, I sought estimates in the literature for how much methane “a sheep” emits per year.  The biggest determinant of that quantity is how much the sheep eats, measured in dry matter.  The makeup of the diet is also important; on grain, less methane is produced, but not a huge amount less. Breed doesn’t seem to matter.   From three independent papers* I got estimates for “the average sheep” derived by different methods.  These agreed reasonably.  They were, per sheep per year, as follows: 8.4 kg, 8.36 kg and 10.4 kg.  The unweighted mean is about 9 kg CH4, which I will use.</p>
<p>Using a round number of 50 head for the flock, this returns 450kg CH4 for the year.  With what I think is the appropriate conversion factor, the GWP20 of methane (= 86), that equates to a jaw-dropping 38.7 metric tons CO2-e.  Using the more popular GWP100 yields 12.6 metric tons  CO2-e.  Static stockpiling of barn litter for later application to fields adds (figures from long ago) another 2.3 metric tons under GWP20, (0.7 by GWP100).</p>
<p>(*)  sources and calculations</p>
<p>(1)  <a href="https://www.teagasc.ie/news--events/daily/sheep/measuring-methane-from-sheep-systems.php">https://www.teagasc.ie/news&#8211;events/daily/sheep/measuring-methane-from-sheep-systems.php</a></p>
<p>10-35 gm CH4 /d mean circa 23 gm/d                            8.4 kg CH4 /sheep/yr</p>
<p>(2) Small Rum Res 27 (1998) 131-150     used 22 gm average “all sheep”</p>
<p>18.4 lb/sheep/yr * 50 sheep  = 925 lb/                          8.36 kg CH4/sheep/yr</p>
<p>(3) Goopy JP. Woodgate R, Donaldson A Animal Feed Science and Technology 166-167 (2011) 219-226</p>
<p>Assume a mature sheep consumes 2% of body weight per day on a year-round average. Assume average weight in flock 75 kg dry matter intake = 1.5 kg DM/d  * 365 d/yr = 548 kg DM/yr/sheep * 19 gm CH4 /kg DM =  10.4 kg  CH4/sheep/yr</p>
<p>&nbsp;</p>
<p>                                                                    Section 3 Nitrous oxide</p>
<p>            We have only once in thirty years put on any synthetic nitrogen fertilizer; that was one application of urea on the main park probably ten years ago.  Thus, N2O emissions from the farm now are associated largely with stockpiling barn litter outdoors for 6-12 months and spreading that quasi-compost on pastures.  Manure dropped on the grass is not very important.  My estimates of N2O emissions made 5-6 years ago came from working with COMET and with Prof Mary Schwartz at Cornell.  She observed that our then method of handling barn litter was not a good composting process and was likely to emit CH4 and N20 to excess.  I estimated the N20 emissions from the farm as 12.3 tons (probably metric tons, I don’t remember) CO2-e.   The GWP used for N2O is 273; accordingly, the actual estimate must have been 0.045 tonnes. In the years since, we have improved practices a bit by going to two windrows instead of one pile. The process is still too anaerobic.   For a 2023-2034 figure I will use 10 metric tons CO2-e, as the flock is these days at least 20% smaller than it was ca. 2010-2017.</p>
<p>            With the figures above for CO2, CH4 in CO2-e and N2O in CO2-e we can go now to a three-gas balance sheet.</p>
<table width="391" border="0" cellspacing="0" cellpadding="0">
<tbody>
<tr>
<td valign="bottom" nowrap="nowrap" width="135">
<p>Gas and source</p>
</td>
<td valign="bottom" nowrap="nowrap" width="113">
<p>GWP CH4 = 86</p>
</td>
<td valign="bottom" nowrap="nowrap" width="143">
<p>GWP CH4 = 28</p>
</td>
</tr>
<tr>
<td valign="bottom" nowrap="nowrap" width="135"> </td>
<td valign="bottom" nowrap="nowrap" width="113">
<p>Tonnes CO2-e</p>
</td>
<td valign="bottom" nowrap="nowrap" width="143">
<p>Tonnes CO2-e</p>
</td>
</tr>
<tr>
<td valign="bottom" nowrap="nowrap" width="135"> </td>
<td valign="bottom" nowrap="nowrap" width="113">
<p>per year</p>
</td>
<td valign="bottom" nowrap="nowrap" width="143">
<p>per year</p>
</td>
</tr>
<tr>
<td valign="bottom" nowrap="nowrap" width="135">
<p>Actual CO2</p>
</td>
<td valign="bottom" nowrap="nowrap" width="113">
<p align="right">18.2</p>
</td>
<td valign="bottom" nowrap="nowrap" width="143">
<p align="right">18.2</p>
</td>
</tr>
<tr>
<td valign="bottom" nowrap="nowrap" width="135">
<p>Methane ent ferm</p>
</td>
<td valign="bottom" nowrap="nowrap" width="113">
<p align="right">37.8</p>
</td>
<td valign="bottom" nowrap="nowrap" width="143">
<p align="right">12.3</p>
</td>
</tr>
<tr>
<td valign="bottom" nowrap="nowrap" width="135">
<p>Methane compost</p>
</td>
<td valign="bottom" nowrap="nowrap" width="113">
<p align="right">2.3</p>
</td>
<td valign="bottom" nowrap="nowrap" width="143">
<p align="right">0.7</p>
</td>
</tr>
<tr>
<td valign="bottom" nowrap="nowrap" width="135">
<p>N2O composting</p>
</td>
<td valign="bottom" nowrap="nowrap" width="113">
<p align="right">10</p>
</td>
<td valign="bottom" nowrap="nowrap" width="143">
<p align="right">10</p>
</td>
</tr>
<tr>
<td valign="bottom" nowrap="nowrap" width="135">
<p>N2O SNF</p>
</td>
<td valign="bottom" nowrap="nowrap" width="113">
<p align="right">0</p>
</td>
<td valign="bottom" nowrap="nowrap" width="143">
<p align="right">0</p>
</td>
</tr>
<tr>
<td valign="bottom" nowrap="nowrap" width="135">
<p>Total</p>
</td>
<td valign="bottom" nowrap="nowrap" width="113">
<p align="right">68.3</p>
</td>
<td valign="bottom" nowrap="nowrap" width="143">
<p align="right">41.2</p>
</td>
</tr>
</tbody>
</table>
<p>                 Table 3.  GHG accounting in metric tons CO2-e for CO2, CH4 and N2O, by GWP used for methane</p>
<p>&nbsp;</p>
<p>When methane and nitrous oxide are brought in, the benign-looking “carbon footprint” in Table 2  turns horrendous.  This is made much worse by my insistence on using GWP20. Assuming (for an average year, not 2023) that 50 sheep are sold for meat at an average of 60 kg live weight yields a footprint for meat produced of 68.3 tonnes CO2-e /3000 kg = 22.8 kg CO2-e/kg live weight.   If we assume 35% of live weight is edible, that’s 65.1 tonnes CO2-e/ 1000kg edible meat.  How does this compare to figures in the literature?  A back-adjustment of methane GWP is needed for that.</p>
<p> Every report on meat I’ve ever seen that comes out of agriculture uses GWP100 for methane. A value of 28 is often cited, (though there is no consensus). <span style="text-decoration: underline;">None uses the GWP20</span> of 86, though stern critics of animal agriculture will.  Conceding for now to GWP100 lowers the methane component of the farm’s GHG profile from 40.1 kg CO2-e to 13.1 and so drops the GHG profile from 68.3 to 41.2 tonnes CO2-e per year.  Table 3 displays the CO2 equivalents for each gas comparing GWP20 (value 86) to GWP100 (value 28).  If the farm produces 1 tonne of edible meat per year, the GHG footprint of that reckoned with GWP100 for methane is 41.2 kg CO2-e/kg edible meat.  This is not way off from one external estimate for “lamb” from Our World in Data. <a href="https://ourworldindata.org/carbon-footprint-food-methane">https://ourworldindata.org/carbon-footprint-food-methane</a>. Theirs is 40 kg CO2-e/kg edible meat. Their figure is derived from the meta-analysis of Poore and Nemececk in Science 2018 June 1.</p>
<p>Calculating the GHG footprint of meat is tortuous and bedeviled by sources of disagreement besides what GWP to use for methane.  Functional units range from live weight to 100 grams of protein, with many assumptions fluctuating in that conversion.  How many servings of 100 grams protein will the “average” lamb or steer yield?</p>
<p>Might this farm, despite its emissions as calculated by me, be a carbon sink?   That is, might the annual drawdown of CO2 here (largely by trees) exceed its GHG emissions reckoned in CO2-e?  It depends on what GWP is used for methane and on how much of that the annual CO2 flux is likely, under current management, to stay behind as carbon for ten, twenty, fifty years in vegetation (living or dead but if dead not decomposing) and in soil (mostly that of pastures).   </p>
<p>A forest stand evaluation of the farm was done in 2017 by a team from the Black Rock Forest.  They reported on five separate 1/10 acre plots in which every tree was inventoried and measured.   Projecting their observations to the 30 acres of woodland, there are about 6000 trees with total dry above ground biomass (agb) of around 2700 metric tons.  Total carbon content in trunks and branches is about half that.</p>
<p>Estimates vary widely on how much CO2 is taken yearly into the trunk, branches, roots and soil around roots of a tree. Important determinants are species and above ground biomass.  The latter is related <em>t</em>o species and age, but also to soil quality and local climate.   Drawing on the concept of an average tree as we did of an average sheep, one <a href="https://onetreeplanted.org/blogs/stories/how-much-co2-does-tree-absorb">web site</a> <strong>states</strong> “the average tree absorbs an average of 10 kilograms, or 22 pounds, of carbon dioxide per year for the first 20 years.“ Thus, 6000 trees would hold onto 60 metric tons of  CO2/year in wood above ground.</p>
<p>To empirically gauge annual CO2 sequestration in soil is notoriously hard. Chambers, Lal and Paustian in J. Soil and Water Conservation (2016) 71:68a-74a wrote that “prescribed grazing” could put <span style="text-decoration: underline;">carbon</span> into soil at annual rates ranging from 0.17 Mg (metric ton) to 0.44 Mg per hectare.  Converting the midpoint of that range into CO2/acre returns 0.44 metric tons CO2/acre/year. [To convert mass of carbon  to mass of CO2 , multiply by 44/12.]</p>
<p>In an earlier paper Conant, Paustian and Elliott 2001 Ecol Applic 11 343-355 estimated that improved grazing by itself would add carbon at 0.35 Mg/ha/yr.  This equates to 0.5 metric tons CO2/acre/yr.</p>
<p>We not only employ adaptive paddock management on perennial pasture, but also fertilize by spreading stockpiled barn litter and sow clover into pasture. It is therefore reasonable to attribute 0.5 metric tons CO2 sequestered /acre to at least 17 acres of the 20 acres grazed in 2023.  This makes 8.5 metric tons CO2 sequestered in pasture soil.  [Note that all commentators hold that annual additions can’t continue at a given mass per year, but at what point the marginal returns begin to fall or a ceiling is hit no one can say.  It is likely to be above a soil organic carbon proportion of 3%.] From soil sampling, we estimate that these 17 acres hold about 500 metric tons of carbon in the top thirty inches.</p>
<p><strong>              </strong> Table 4 below shows that the farm may be a carbon sink, marginal with GWP20 for CH4, but significant with GWP100. Put another way, even using GWP20 for methane, the figures make a case but not a proven one that this farm is “carbon neutral.”  It only gets there, however, because of the trees.</p>
<table width="388" border="0" cellspacing="0" cellpadding="0">
<tbody>
<tr>
<td valign="bottom" nowrap="nowrap" width="169">
<p>Gas and source</p>
</td>
<td valign="bottom" nowrap="nowrap" width="113">
<p>GWP CH4 = 86</p>
</td>
<td valign="bottom" nowrap="nowrap" width="105">
<p>GWP CH4 = 28</p>
</td>
</tr>
<tr>
<td valign="bottom" nowrap="nowrap" width="169"> </td>
<td valign="bottom" nowrap="nowrap" width="113">
<p>Tonnes CO2-e</p>
</td>
<td valign="bottom" nowrap="nowrap" width="105">
<p>Tonnes CO2-e</p>
</td>
</tr>
<tr>
<td valign="bottom" nowrap="nowrap" width="169"> </td>
<td valign="bottom" nowrap="nowrap" width="113">
<p>per year</p>
</td>
<td valign="bottom" nowrap="nowrap" width="105">
<p>per year</p>
</td>
</tr>
<tr>
<td valign="bottom" nowrap="nowrap" width="169">
<p>Actual CO2</p>
</td>
<td valign="bottom" nowrap="nowrap" width="113">
<p align="right">18.2</p>
</td>
<td valign="bottom" nowrap="nowrap" width="105">
<p align="right">18.2</p>
</td>
</tr>
<tr>
<td valign="bottom" nowrap="nowrap" width="169">
<p>Methane ent ferm</p>
</td>
<td valign="bottom" nowrap="nowrap" width="113">
<p align="right">37.8</p>
</td>
<td valign="bottom" nowrap="nowrap" width="105">
<p align="right">12.3</p>
</td>
</tr>
<tr>
<td valign="bottom" nowrap="nowrap" width="169">
<p>Methane compost</p>
</td>
<td valign="bottom" nowrap="nowrap" width="113">
<p align="right">2.3</p>
</td>
<td valign="bottom" nowrap="nowrap" width="105">
<p align="right">0.7</p>
</td>
</tr>
<tr>
<td valign="bottom" nowrap="nowrap" width="169">
<p>N2O  composting</p>
</td>
<td valign="bottom" nowrap="nowrap" width="113">
<p align="right">10</p>
</td>
<td valign="bottom" nowrap="nowrap" width="105">
<p align="right">10</p>
</td>
</tr>
<tr>
<td valign="bottom" nowrap="nowrap" width="169">
<p>N2O SNF</p>
</td>
<td valign="bottom" nowrap="nowrap" width="113">
<p align="right">0</p>
</td>
<td valign="bottom" nowrap="nowrap" width="105">
<p align="right">0</p>
</td>
</tr>
<tr>
<td valign="bottom" nowrap="nowrap" width="169">
<p>Total</p>
</td>
<td valign="bottom" nowrap="nowrap" width="113">
<p align="right">68.3</p>
</td>
<td valign="bottom" nowrap="nowrap" width="105">
<p align="right">41.2</p>
</td>
</tr>
<tr>
<td valign="bottom" nowrap="nowrap" width="169">
<p>CO2 seq  trees above ground</p>
</td>
<td valign="bottom" nowrap="nowrap" width="113">
<p align="right">-60</p>
</td>
<td valign="bottom" nowrap="nowrap" width="105">
<p align="right">-60</p>
</td>
</tr>
<tr>
<td valign="bottom" nowrap="nowrap" width="169">
<p>CO2 seq  pasture soil</p>
</td>
<td valign="bottom" nowrap="nowrap" width="113">
<p align="right">-8.5</p>
</td>
<td valign="bottom" nowrap="nowrap" width="105">
<p align="right">-8.5</p>
</td>
</tr>
<tr>
<td valign="bottom" nowrap="nowrap" width="169">
<p>Net GHG emissions</p>
</td>
<td valign="bottom" nowrap="nowrap" width="113">
<p align="right">-0.2</p>
</td>
<td valign="bottom" nowrap="nowrap" width="105">
<p align="right">-27.3</p>
</td>
</tr>
</tbody>
</table>
<p>Table 5. Net GHG balance for three gases, including CO2 sequester in trees and pasture soil.   Two values for methane GWP are used.</p>
<p>Anchorage Farm, with half its area in woods, is not typical of US farms. The woodlands here provide ecosystem services that, estimated as net flux of CO2-e, probably outpace on a per acre basis most farms that produce food (meat or non-meat) or fiber.  Only a tree farm managed in a <span style="text-decoration: underline;">truly</span> sustainable way and with the bulk of its harvested mass becoming structural timber can hope to do better on CO2-e accounting. </p>
<p>Is that a good argument for re-foresting all the world’s farmland?  No. Farms produce food.  Tree wood is not food for most macro-organisms except fungi.</p>
<p>Is it a good argument, then, for reforesting all land used in ruminant animal agriculture and using the remaining cultivatable land to grow beans? No, again.  To sustain good soil for growing food and to make bad soil better requires maintaining the stores of carbon and nitrogen in good soil and replenishing them in bad.  There are few ways to do this today, now that the world has run out of guano laughing out loud.  The worst is by combining aggressive tillage and synthetic nitrates to boost primary vegetative production. Even in careful rotation among forbs and legumes, this mines the soil for carbon and nitrogen, since harvest takes away carbon temporarily stored in above-ground stalks and foliage.  In so doing, it cuts off from the in-ground vegetation (roots) the supply chain of carbohydrates that photosynthesis created in the leaves to be shared with the roots and with the soil around them. Leaving land bare in winter lets carbon escape from soil as CO2.</p>
<p>A big improvement on the above convention, with less (but seldom no) need for synthetic nitrates, comes with no or minimal tillage combined with cover crops that keep living roots in the soil year-round.</p>
<p>A further improvement substitutes animal manure and or compost from ag residue/food waste for synthetic nitrates as fertilizer. This desirable change is limited by supply of manure and compost.  see Gaudaré  et al Nature Climate Change 2023  https://doi.org/10.1038/s41558-023-01721-5</p>
<p>A large proportion of the world’s land that is not tundra or ice-covered is climatically or topographically unsuitable for growing human food crops.  Here the most practical way to conserve good soil and heal damage is through <span style="text-decoration: underline;">improved</span> grazing, with emphasis on <span style="text-decoration: underline;">improved</span> intended.  Grazing systems, mostly with cattle, have proven in small experiments to add carbon to soil. See Machmuller MB et al Nature Communications April 2015  <a href="https://www.nature.com/articles/ncomms7995/">https://www.nature.com/articles/ncomms7995</a> and see Stanley P et al Agricultural Systems 162 (2018) 249-258.   Allen Savory and his disciples have documented observationally that short-stay-long-rest intensive grazing can restore vigorous plant growth to arid land that’s been almost barren for decades or more. </p>
<p>To sum up<i>, conserving and improving soil through the interaction of photosynthesis and grazing animals is such an important ecosystem service that arguments about the climate effects of methane emissions from ruminants should not erase it</i>.  I don’t share Allen Savory’s vision that vast tracts of desertified land worldwide can soon be brought into carbon-neutral food production with millions more cattle, but he could be right. I am sure that the world needs <span style="text-decoration: underline;">holistically-managed</span> grazing animals to save our soils.  From ruminant grazers, enteric fermentation methane is inescapable.  “You can’t have one without the other.” Grazing animals provide complete high quality dietary protein and, <span style="text-decoration: underline;">properly managed</span>, build soil. No other food-growing system can do that beyond the small-farm scale without importing fertilizer.</p>
<p>This essay began as GHG accounting for one small farm with livestock.  It has now become an apology for keeping domestic ruminants when all authorities agree that making worldwide annual human-controlled methane emissions stop rising or actually decline is the fastest way to slow the rate of global warming. (Why humankind theoretically has this leverage through methane is addressed – and I hope explained – in one of my several blogs on methane http://www.anchorageromneys.com/2019/09/methane-manifest/).</p>
<p>“Apology” here means not “I’m sorry for the mistake,” but, to paraphrase a dictionary, “a formal explanation or defense of a belief or system, especially one that has widespread opposition.”            </p>
<p>A frequent defense for raising domestic ruminants, with which I struggle, is that the carbon atom airborne in a molecule of enteric fermentation methane is “not new to the atmosphere.”  It had been in the atmosphere as CO2 before being incorporated by photosynthesis into cow fodder, as part of the short-term global carbon cycle.  That much is true.  The argument continues, and I agree, that this “biogenic” CH4 is part of the short-term carbon cycle that has been processing Earth’s methane exhalations for millions of years, keeping atmospheric concentrations stable at least in recent centuries.   Methane released from the natural gas delivery system, on the other hand, has been out of the short-term carbon cycle for millions of years and is in that sense an alien intruder. That, too, I buy.</p>
<p>A conclusion I can’t credit is that “biogenic” methane, being in a natural cycle, doesn’t increase the power of the GHG-spiked atmosphere to block outgoing infra-red, thus warming the planet.  The unwelcome reality is that the atmospheric methane-processing system must deal with all the CH4 it sees as best it can without regard to whether the gas came from a peat bog, a drowned forest, a coal mine, a gas compressor station, a dairy farm, a landfill, hooved ungulates on the Serengeti Plain, a rice paddy or a termite colony (to name a few sources, some under human control and some not). </p>
<p>There is no special handling for the fraction of human-influenced methane emissions released from domestic ruminants. Accordingly, the total of all annual human-influenced methane releases must stop increasing. The sector whose annual releases are highly likely to be rising far more than those of any other is fossil fuels, particularly natural gas.  Worldwide withdrawals of the latter were up 25% from 2012 to 2022 (3.343 bcm to 4.175 bcm).  There is no reason to think that planned and unplanned releases as a proportion of total shipments declined over this time.  In contrast, one tally of world cattle population shows a 6% decrease over the interval.</p>
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" /></p>
<p>&nbsp;</p>
<p> <img alt="" 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1vuuqcxeqv/rLqxG2YDMy4i7ctRnTmvL5s5+eZlvFJInS6DTcLXvvntisCHDvT898rHPHX8QwFm6g4L6g7QPvrutzbmN095Z0PBZOrmn5BJWkwTFxpf/UzxXZONTmij5j/Xn08Wo5+Qsbbnz9R5JmfOqluLxCSxzkcydMBdJxcht4DQgUioLbt6DU3FOFYuZnmRIpP+M3wtSCz4qtw/zLNi/ZPrsX6m1oNyuevQuNb8nDbXlU1xHUohKbr+kAYulqM81D5fHnL3X3j3b/m37w9ElI+5HjbhqtfFmHVGKnELrYt1eyB/L9DkdhSTj9A+t25uDJUFQQ4FHQytxSGlWur7nrJOpMho6ni0vfcJEek67DBm/mFNk6tYbIxDslVnRZsqW+PY+/YRaXTKH4TQhmqpEelQQBD0JbQJaSJU/sll6oa6SUuXssnzBSBG+nQAi9BpWc4EExNk/7r/ksQ0lH75usUkZbJJbas/EQ5D/lKfhXIxHy2pK3cDg/vGRaRTg6+gDSl+g014+eMRmlh1P7EYfvmfb60sSkJzkJ6n/MU4d/xD5UMBWHIO0DQeKQuuj3Fsk5PiiqPHOLRh0e3CnKNjZYS0J7HDi8XqZ9vzZ+q7nzNn5ZBX/Xy/bzG58MuH3rVQW3b1GpqKcVO5lEBjKTLpPyNnXHPf82H6ndLPnHpz16Fxrfk5ba4rmxJoLIWk6PpTCUtT+31T+JQ9SMz8XjSAbz379KGg8zXkMa12Kg7++xLTMvvl6+aeWCf9cW3S+IcOn5s0pSlylTq3pMwnKTKaMh7j2PuEiHQTdn75USwxxiFb49j7DhDpEGix4A2phDPmH5IiTCETOT+4iH4B/YFo8gn2F6zUfsX8jP0NqE8m/X7HfHJi5Cplkx2bpOqu506CqZuAlMkmtc2+jMQm9tR668pNGpHOnehSD86acGwivv4CL8EsYDaPjz8R+wdkPlnwxyO2YcAzUhZOX0Zjh0iCR8qC67+zMXMof2MQIlgx4qv7jOcBR+137m9wmsYQfV2sfrY9f6bOBzlzVqq1l//s3L6lRApeCmtoKsZ15Xzte51PXIpMLmUindrPHDxzifS41vycNofK+vNb3Tyfsq9sk0iHrJxie7rQ/KnbhDXw9a96UfG0o47MDvgp9eSu4ynEDXXn7LFRPnc86uTEr6dpPQ7xmiY+EvO7T13vQviEnpuCScp4jGPvk4tdap9T3v+2ZWtce98BIo3O+ROUv5FNfSFzNhqpL1juwpizCIyrX7E2+ycksRM6f3xiUZtjm/IUgUYZH5+UQAL+xq7OlCdXVpranEtKYv0Hcbvm+i8W3/mP24sf/2ytLa79Y/376w5WcjcwoXcidhiV8h7l+lvFfGNj+IXmFG36pQ9bRD78k1X9Tvgk0pfvYcY/JU2XL6OpgVJi739o4YnVnbKoNpli+++ljIeei/Tmz5eB0OHUYvWz7fkzRZ5zNwvDHu4NI3P+oZBvZpkyThqDcayhqRiHyoVM2OuISm5fc8dVt2+YZzXhkNPPHDxz1qFxrvk5bfbLxvaounwKSdHlU+bWuraHSHTKQS7qi2mk5ZmoDyldU1JmNfUrpgBKxSF375Y7HnVY59STS6BSlCOp73sKPil9SRmPcex9Up7rj1FKn1Pe/9x6YjiOa+8bJNIhc2R92jMuwhkDITTZxLRCOQMxrn7FBNFvY4qA6TIxIh2bMFOfF+tHXT0pY5BSJrWdKXKUUhfeg9e+5Z21Qevq6ljqRDp1wa7rX8y8NHRfE6nTJFZrlzVB0mTZ30T5pHOY8U9ZFIeV0XHUnXK40aS5Dx1eYNy0Gacmy7HDi9S5ORfDlH62PX+mzA25hCtFBkLPzcULdcTkP7ctOW1IXUNTMfbL5cQySZXJtjaBubg2YZDbzxw8RyHSqXN/jszktB1l/c1wzGc49j74zx92n+PPn/g9xxoOcx3+6o8ERNUZGnA91ucQpr51YGxfmIpD7ljnjkedfOTUk9oXeda0EOnYGKfMkbnY5a6NTe9/27I1jr0vDjyDRBodCwWYkNzSqYtl2yCkDPooi+K4+hUTxLY3gjkTTM4iFutHXV0pcpBSJrWtbfQ/tJHB8yXCLqKe77Xn7rZJiNKsNdQk0oMj1UTqtMmwdnuoI3W6fEqMgDYWk1EWh5QN9jDyn7IhrjPH1ocR+vBCb1I1trHDi9S5eRz9bHv+TJ1ncvqSIgOh5+Y8Q+6PzX+5bclpQ+oamoqxLhfS9sWsrXL76r/nKVZXdZvv2CF/HQbD9DMHz5R5Q+ob55qf02Yp6+9LUwhl7H3w2+H3OZUM+3Nk6n0pOIRy3ubKVwo51G1JHfuc+QH1545HHT459aT2pe5dTgnamOoKOk7T7hxMUuetXOxG2Sv5Y922bLVNpIENUirXEumQwMtpZOpi2TYIqZs1PRg5bRhXv2J+wn4bgXPOB3midQqrYV6mlOcN80KlvlQ54xRraxv99xdFEOi66MypC1TOBqZuU9yGabffXmwWH3bQATFYq+s4RBgmiqk2OZUNqk+wtXZZb5rqyofM5oYZ/5QN97AyOq66U+TJN1kXfDXB1mSkbjx0+brgIYvVz7bnz9QXIUceUrAJPTfnGXVzhr8JzG1LThtS19BUjKVcyMw5RqJxr9+emJntYqe/GrafOXimzBtLkUiHzLlv+OTFURNnX95j/sq56a9CBx9tkmgZC38fmXPIgzr8Q4jYAXPqfi9nfiCRDqfzTNmzpIxHSj3+XBFbD1KeOyoBrpu/2pattve+si9qJNJNuaV1B0c5idEApghBbNBHGdDUTUDu4Mba7Pv4pZClpoUzBcechVdvZo5+7hnVrSkT+ST6SIcC9jQtOpNGpHM3CsPISuieEKmDyZoEFfPlKUTqkA7k1DPfVlUf2hT5UWZTNtzD+Einvqex9z902BSLk5C6uPmbr1BQMd803ifZJx7/W4XOFFBHRharn23Pn6nynrMOpGATem5OhFG5f9w+0jm5Z3O1ZiEMRiGXucTYf19yCNGwYzzqYUGqvEq5HCLt49fmmp/T7mFJNJ6Ru97lZKnYVSQa/UgJJNiEqb9mkEhfUgtXyp4u9X1PWSdS9uwpa/449j4pzx2FdzXJbAp2ORwydy5oapteKxqJNCrxhUXC+OuNVd1i6S/osQA6/qZhFHOK0KKB79rYBPiDG5uQYimgUl6inEWn7fr0s3MD+8S08cOMUwwLX2ZjWgi/Pn/iiG0e/PFd6qbdw0yMMcxTrvuyABL85W/cUjTlLvZJ3Y9+ckfx7suvqh4XIpy5ASVQ2TBRu9sk0v7zY1qT1PcqlPLkN37t8OowIpbmCkTilD84oXjOaedUmI8S2Gkc/RznfNfWIp+66fKf588tMblI2WzntiVnM5N6GJ0yX6BMKGr1285+eXHqSc9KraKIpYHTFaUcqNU9OBdXXU8b/UwFJIdIo85xrfmp7fVJNCz2PvWBt0c10VJ/SvpF3ZbYQZSUHSWwWGrffRnRiozYfja2r4kdcqXuE3LmB7Sprfk6p57Uvghmk0qkx7H3ycUOGObKRN37kFtPTCaG6UvKfB8l0qgklFtaNr+4XvdC+p1q2gT4G0PUOylEuomotZ1HOmUCjglTSh11ZfxFLTYZxw4R5Dm5L0xTH3xZSsnhqOvLedlC45tCpFNz6/ljGdNUpi5Uw2i6RpGb0DhDdrR/eWh+0PKG9+y7t91e+aPXBb7xNdmx8R82j3SbRNrfwMc0YaHNZV0aQC1DwOwpTzq0OowIzV3aBBByevzRR/UdXtT1O4VIjKOfOXmk25DhYeasFGxCbUtJc6bvGyaPdGwOz5mb2yTSIXL52Q+/o8+NKWU8/XelyULF3+vEDv/184cd47b6mYKFv8lNWYfGteantLctv+PUcfXXjrpD9HH7safMBbEDfr8O/5At9t6n7oNy5ofU/UmKbOTsc1P7Is+dVCI9jr1PLnb+HIPfU/dK/riPQ7ba2vtqGUki0j6QfmfrXsjUzV5oUpokIo22+ilGBCMfg9DkFyJjKeaoeGn22WuPgZPZnAkmZcJqIpkgKXWbG38TiHrqNia5L0ys3f7LEiMmkPGjn/pEW61PrPBdHYH1x7dObkOTS8omzR/LFLlIGX9/oUgJ2iLYaH/82Dj413XbEORKRyMNYawPRUACf3LH2mLt+k222qaNgI9B3fjnmOYNK6MpG+zQHFt3IBMq2xRNVz9fguVJcLzQ4YW/4QJ2n/nclyzmqc+pG59x9LPt+TNVpnPkIUUGQs/N6VuqCXRuW3L62RaRbpNchiyMvvHZKwbWTf+QJzVCtYxbLq4ynz7zhWcW99631VbTtJ6mymWsnD+esXXIx6+tNT/WzrZINJ7jj40OsKjb4WujQ2tMWyQaMn7rv/2ggOtMLJVV6N2O7WlC+Op9UUy+UwlUzvyANqXsT2KykVtPal/q3uVRlHop+KRgktqHtvc+qc/VY5bS55Qxzq0nBce29r760DqJSKPDIcIgQNRtaENEChPYC37/eEMA97S3I7z/+z92TbU51uCOIrxST85ApG4C/DplAXzu7z69eNaxv2EfveWuu4tLrvzUQL7hOiLkaxJQBybKZx3768Xhv/y44pEPP9gSvC133mMx+8q/fNuSkBBGKcKUIsR1ZXwtMxZWv+/X3vCVgbRRTcQnZ5xS2h7CE4cYpz//xOKwX3qcreJHP/5Z8eV/vrW48cvfKB7/848stEbPJ+KQW4wdxgEfELzQ+Nprl51fkXLdVn+RBnl9/ateVL0LaA+eI8/Avf7mDljDtPERh7h2QM7wLskhAL5LGf9QVHKND+pDmVvMQo9nwAT7+i/eZIOS1Wk+c8cFzxNSXLeoa1Kny+NZdYdXuBY6DMEzTj7xuAq70NzTpL0eVkZTN9j+uKEfeGd+68lHVtBee8OXK1N4jXfTpijk5yi4150U+4HhpLyOqu6P92L2s835M0WOUSZHHlKxCT27qW+yjkIu/vbv/7EiZKinTiZy25LTz9Q1tAnjEGnAvIgghymfRzzsoAHTb//d0nMd5rePfvr6vkO9pnm8rg25uI6jnyn4DLMOjWPNb2prKNjnS076vZTu2TIv/qNn9q2joQMpvR5g7X3vRz5d/OcPf1w9I7QWhEi0WO2kNu6tZ59ui+p3ReRbz/UoI3sUOciUZ6BtkkUn9bko549jjqtj3XySMz+gDSn7k5Q+5dSTSwYnVSMN3Nre++Ril7s2No31OGSrrb2vxjmZSIcmIgGgiSD5k3bj5GlMN7XJ+CQQaUyiP1u7vm8DU9fH2Alg02FFXZ2LQaTrLAiaxjZ2epr7wqRMtDl4+mPjT6RNz4P8a7/dOiIdOljy6/XvDQX88+/x37/UBSa0kYvhGpPh2P2hSR735M4h2Ej89ObrGh+XgreuIKYNGlZGUzfYOeOhtcToQ2xc/IOh2D3+AY7g1HR4sdj9zHnfpT+x+BZtLfKp2NQ9L7dvTRYmuW3Jkfs2iHToQCk2r+jroXcB8+hTn31a0jqNumLrVag9ubiOo58pOKXMi/57MY41v66tMQvIlD6G3uuQ+2BTXSGlR86+oK5uIa+j9DPFMi30fP9Qrmn+SyVQOfMD2pS6P4mNc049qX2RZ04ykUYfUt7x1L1PLnaoN1cm6sY6t55UmcjZa0nbQuuKPC+ZSDcNTtMmOJT/zgdNtGx+dNhJINKY0A775ccW2jwrJBSpATIw0V1k/oqpV2wyCW1sU4UpVnfTdSysp/7pnw2c4ofuSQn2lfvCpLa9jhD494dektjmVeQWgW+0D1bT4hSrM3RvbFIclkgDA2wwTzvrzwcsJ+rwrTOJSx0PlAuRuiaCFhrD1HZg8/SqN14QfZ+gofrkpX/W6H85rIzmbLBTJnjZ5OtDyhiR9jURGIcm7XJo0xk7vFgK/Wxj/kyV5Rx5yMGm7vmpm/jYWpPblpx+LlUiDUzxbp1+ztv7tI7Drleh+3JxXSwijbYPsw61vebXyfkoBFPqrFuDU9YDva77bUx9B5vmECHSdYfKTbkoORwAACAASURBVPfi3fbTnabOV7LeH37s86tbmvZmqQQqZ37Ag9van+bUk9oXAWbSiTT6kSLrKBfb++RihzpzZaJOhnPryZGJNva+csCYRaRDLwG+iwUtwMM+dNVni3/4p5v6Nuw4NX/Kk55QvOa0P67McGKEJHexyhmI1E2ArlP8i6SPn/zMDdVCjQn5Vw//5eKZT39qVpRRjddt//XDPhIAof/Fxz6q+PVffYLxrXlan/mSCGOOMOVMwqGyWAzeffnfFP/+/dv7NiiY8GGKp8e26Vk545TbZrww77rsr/sCVaEO8Rd9xm8fZU3BQn5KILEfv+bzUbnVZC+m5aqr85ce9+ji3DNPC44pZPPiD/1N8S+3/FslDyILr3rxH2abdvsYov6PfOq6gXFEORlLRHt+zglPy4V/oHzIbK9JuxzaWOWcyON9uub6L9lx1O+T4Jf6fg4ro7lzFtr7Vx/8ZHH9F24amEv0WGuZixHp0GFM0+FFaDGMaemWQj/R7lHnz1QBz5GHXGzq2oC5DGupDtKHslhLMX8gwrp28wjVk9uWnH6mrqFNGI+bYMr8q+cCwe/VL/nD7GBmdZvv2L5o3P2MyfEw6xDqbGvNr2vfOIm0zA+YX/13SAIx+mbhup1tEmlpC9YmuJj9+Gdr+9YnvUfBXuqU554wtGzqPmi5azocTSVQOfMD2tHW/jSnntS+1L3Loyj1UvBJ6UtuH7R8jbL3Gea5KX2OzU+hPUgsaFkKjm3vfbHfWLbTfFI6xDJEgAgQASJABIgAESACRIAITCYCvrVRzqH0ZPaYrSYC40WARHq8+LJ2IkAEiAARIAJEgAgQASKwJBDQmrvcNFpLogNsBBFYQgiQSC+hwWBTiAARIAJEgAgQASJABIjAuBDwzXWplR4X0qy3CwiQSHdhlNlHIkAEiAARIAJEgAgQASJgENAxNprSPhIsIkAEmhEgkaaEEAEiQASIABEgAkSACBCBDiGgMz+kZsLoEDzsKhFIQoBEOgkmFiICRIAIEAEiQASIABEgAkSACBABIuAQIJGmJBABIkAEiAARIAJEgAgQASJABIgAEchAYFGINDNuZYwQixIBIkAEiAARIAJEgAgQASJABDqMwLJly5Zc77OINAnwkhs/NogIEAEiQASIABEgAkSACBABIkAEEhBok5APEGmS5YQRYBEiQASIABEgAkSACBABIkAEiAARmBoEckn2soWFhZ1T03t2hAgQASJABIgAESACRIAIEAEiQASIwIgIxIg1ifSIAPN2IkAEiAARIAJEgAgQASJABIgAEZhuBHxiPQKRrnf4pnn4dAsRe0cEiAARIAJEgAgQASJABIgAEVgqCDRrj9s3wMbzIkS6nyyTIC8VUWE7iAARIAJEgAgQASJABIgAESACRCAHgUHCPTzJ9oi0I86LRpiXXlTznHFhWSJABIgAESACRIAIEAEiQASIABEYFoHhee2wT7T39Qh2egMMkTa0eWf6DX0tzCS+Qz9nJFh4MxEgAkSACBABIkAEiAARIAJEgAhMOgKxAGAD/RuW5lZ5q+srWDY/H4naHSDLJMSTLoJsPxEgAkSACBABIkAEiAARIAJEoBsIBAl4Ismu01YPEmmPOI9Kmo0bdjdGh70kAkSACBABIkAEiAARIAJEgAgQgV2CwM4ikQnXtGaAXCdU5+5xBZfNqzzSqaRZk+PUe3YJmnwIESACRIAIEAEiQASIABEgAkSACHQeAU2UU0l3H7luINY2aveO+flG7g3STLLceTkkAESACBABIkAEiAARIAJEgAgQgalAAEQ4Rq4rUl3DlgeI9LDEmWR7KmSKnSACRIAIEAEiQASIABEgAkSACEwsAtkByUxPm4h1nZbaEulU8lxLlhvdoOkjPbFSyIYTASJABIgAESACRIAIEAEiQASWJAINhtV1WuQqGnd9h5JItal/2Y4d9abdA8S5jxP3E2RqpJekdLFRRIAIEAEiQASIABEgAkSACBCBziAwqJFWrNoj2DHtdR2pdj7Sikj3keEAaW6LLLdVT2ekgR0lAkSACBABIkAEiAARIAJEgAh0FIEY4U2FJZjKSpHruuf4hBp81hLpithW5Nn9kEJ4U8pIx5gKK3WIWY4IEAEiQASIABEgAkSACBABItA9BOr4ZUqAMI1WCvkeINYlqW4i1As7F+xjlm3fvsPQaftjI3kOdcgnxoOEvHsDzx4TASJABIgAESACRIAIEAEiQASIQD8COQrYbOwUAY6lvWoiye65prIaLbX0wZp2b9caaa/FurNCmochy2MFLRtl3kAEiAARIAJEgAgQASJABIgAESAC40Jg3PwvRdtc9Q2BwUB8y0BjOu1VM6ku2XRd4LJt0Eirj0+e7e81gbebAWK07nEJJuslAkSACBABIkAEiAARIAJEgAgsFQTGTZyb+1kfvbuWKBuC65uKh8q67wz1BicuCbm0ZdkD27b3fKTNt1UqrAAPHgSIkbuXivCyHUSACBABIkAEiAARIAJEgAgQgV2FwOKS53AvGyN2g+sG0l+B/6aRasup7cdquLc+sM3+igrEcVqa1Q9OjzQ3glYWS/Gp3lWDzOcQASJABIgAESACRIAIEAEiQASIwOgItEOgw9bL0boDt4nWWPs1+73sJ9A9Dbb+Hj/PLJuB/rm63RJsaKPLjzzLku/773/AXOpXh/cKNwQgM5cqZ+sa2+8oEKOPI2sgAkSACBABIkAEiAARIAJEgAgQgTEjMDy3S1TIDtF+X8Pc7wdtYmpDAx2w/PajdfuE2lppmz/+92hiRabvufc+W3WUPJfEuTZSd0LHhwc/oXIWIQJEgAgQASJABIgAESACRIAIEIFWEcjncOmplHMbmhNkTMr2yPVCkFjXkWprvg2FcXkOMDMzUxHrZUZzvazPQTq3JyxPBIgAESACRIAIEAEiQASIABEgAlOHQB6BHoI8txWbuj7W2MCY+KQ5Nmjz8/NG4VwU27ZtL5bNGNNvQ6aFWZNIx9DjdSJABIgAESACRIAIEAEiQASIQEcQyCXQSeWTAlkPB3BQS51Arivf6prH6n7h523bdtiYYtBGW+00NdLDDRjvIgJEgAgQASJABIgAESACRIAITBMCSaTYdrg/CNcABh5xTq+3HTQHyHUDsa4j1H6b8fvWrdutQtqafZNItzNYrIUIEAEiQASIABEgAkSACBABIjCpCKSR3TQCnVKXxN5KKRvCtD+wWDPqFbFOJNR1bYJWevv2HcXMLDXSkyrnbDcRIAJEgAgQASJABIgAESACRKAVBOJktoFAK+1zXT2jkubUTsbIdZ+muoZUu5RXC4FHmnTRCwvFvffdX8zNzlEjnTooLEcEiAARIAJEgAgQASJABIgAEZg2BIYm0SWBbiLP8boH0aytD6msMj+WFNckmK7TUuP5IXNvSSd99z33FrNzsyTSmWPB4kSACBABIkAEiAARIAJEgAgQgalAoJno1mihGwi0zb8sjLMGodrrqTy5QZPcNCh1pNon1Lp9PULd69edd91dzC2nRnoqXgB2gggQASJABIgAESACRIAIEAEikINAmyQ6RqD7ntVHmAfZc55GWrFq9WNTvukQodZk2n++M/XuVX7n3feYqN0MNpYjayxLBIgAESACRIAIEAEiQASIABGYeASySXSNFrqJQFfPqLhyjzTHtNa5APcT55L0lv/Ukeoms+9+a3Bpt6tw8513FXNz1EjnjhHLEwEiQASIABEgAkSACBABIkAEJhaBNkh0HYEe1Dw7EppCnFPKoK4mbbMMSq+MIb8RTbUm1D3/aDS6qs22X8y8QaRnZ+kjPbEvABtOBIgAESACRIAIEAEiQASIABHIQWAYEj1g6hzwgw5pn+ueFYvsHetPNHiYV0Ff4LAaLbWQ6QH/aPBwTcSNSfemLVsYtTs2SLxOBIgAESACRIAIEAEiQASIABGYBgRGJdGNWmhlvh16Th9BNUQcn0HynYmyR4o1wQ5prX1CXafZ7q9npti5oJm0Me3eAtNuaqQzR4vFiQARIAJEgAgQASJABIgAESACk4dAPZEORNo2XNcnv/79mghDa1t73UBV5ZGuSUXVR6wj0DYGEhOSrp7jl8fvNpOWT8RL1XO/77Q4h9tO2D5aIs2o3ZP3ArDFRIAIEAEiQASIABEgAkSACBCBHATGQaKd5naQhPc9Swi2F5x7sD2pua+k1/05sAbItblsv1PVhgg12DRIvh+Zu2fq7Z4n96LdmzbfWaxYvoJ5pHMEkGWJABEgAkSACBABIkAEiAARIAKThkC9v7LXk4gmWurxSXT1vSGaNjAXCLanfe5vQ3oQsias+4KKlQUHCHPZFqeJds/t/7dsbxVQrEeeF5SD9DLjHw0zbxDpuVlG7Z60d4DtJQJEgAgQASJABIgAESACRIAIJCOQrI0egUQvLCy49hhN8MLO8mf8qiN1+b7Rugfes6PkuV8h3UeOdZhuTapnls1UGuqZmZkBMu2bekthORDAv6hv48YtxfK55dRIJ0sgCxIBIkAEiAARIAJEgAgQASJABCYMgTCR9kyyvTzRfmAxrYkWbizfgURDU7tixfJixmhtQVKX4gftXDDt3LZtewHtsrRTzLqdJbjWWDuM7PVlpabd/Lxpk/GRZvqrpTjEbBMRIAJEgAgQASJABIgAESACRGB0BIYx6a4j0YjQVWmeTdMcMV0ooOldudJoaEuz6dFbPd4ahExDcw4yjb+CkyXXlRa952AN4i2a9k2bDZGeYdTu8Y4SaycCRIAIEAEiQASIABEgAkSACCwSAqnaaD9AmDS3LjK31ULDH9poeFetWmk10ZP0ge/z1vsfsJpp33daInqDT1eHAzA9L22/NxjTbgYbm6TRZluJABEgAkSACBABIkAEiAARIAKJCCRpo1NMuq3/cs/fWUj0wvxCsWLlCuMvPJvYoqVVbPv2HdbMe2bWmaJrU29rzm0OCTSRRhmQaUukVzBq99IaTbaGCBABIkAEiAARIAJEgAgQASLQAgK52uigSbcl2s5XuO+vIZnzC/PFbg960MRpowVaaKXvu+/+YtaYacM1WjTT7l+Ye5ugadBKI1p3ae4NM/Z1GzcVc3OM2t2CiLIKIkAEiAARIAJEgAgQASJABIjA0kEgVRvdaNKtSDR6Jv7R0NTCX3h+fr7Yc4/dl06nh2jJ3ffcW8wicBj+lObpTjMtpupeeHDz6/pNm4vlyxm1ewi4eQsRIAJEgAgQASJABIgAESACRGDpItCONro/sjeINAgnNNH4eceOHcXee+25dEFIaNmdd93ttMtGCw3NNEy3hUhLxG6dTgsa6o2b7ixmlzPYWAK8LEIEiAARIAJEgAgQASJABIgAEZgcBEJE2k/pHNNG6/K2rP3PaKMNiYY2et74SO+91x6TA0qgpXfedY81TYdW2uaWtjbeKKgjdpt+i7+0wQA+0iTSEz3sbDwRIAJEgAgQASJABIgAESACRKAfgVG00fZez6TbambNH0n/BBKNFFLbt28vVu+z10TDv3mLSWVlNNJCptEZ+EHDf1oCjTkf6dJf2uCwfgNNuyd60Nl4IkAEiAARIAJEgAgQASJABIiAj0AukS6zOtlqhEg3aaNRBtpomHZPA5GGNnrWRO4GcRatNDyjhUhDC4+UWMt2Oi01iDSDjfG9IwJEgAgQASJABIgAESACRIAITBECOWbdOlJ3kzYaZBLXXeqrwpp275g3RHrvCddI33mX9Y22AccMT7ZE2mikxYxdInbbSN44aDCa+A2bthRzs4zaPUWvDLtCBIgAESACRIAIEAEiQASIQNcRGCTS/UHDwAirMioota+N9usREo1/JdjYtGikQaAdiQaZNkHHRCXfc5U2Jt8utzSJdNffMPafCBABIkAEiAARIAJEgAgQgalCIGrWrUk0ej5ApHukW3yjoY3GxxFop5lG5O75HfNTYdo9Y8y6oZV2pt3464i01dYv6wFkddLmexBpW94U8pJjTZUssTNEgAgQASJABIgAESACRIAIEIFOIDCqWbcwQ78e/I5rViuNyN3GRxrBxvZdvfdE47pp850u2Bh8pM0fp5VWaujy4MF+hzhs5p916zcxj/REjzobTwSIABEgAkSACBABIkAEiAARUAjkEOlUbbTUKdpoF2zM+EibYGPTQKRdsDGnkZaAY5JDGr8jWnmPSC8r1q7bWKxYuZwaab55RIAIEAEiQASIABEgAkSACBCBaUBgaP9oy6r7zbrLr0p/YUMoYdpdpoGaRiINy22kvnKm3SV5Nqi4qN2ikTZEer0h0itIpKfhfWEfiAARIAJEgAgQASJABIgAESACvSBZFRYq0Jjyjw5F69Zm3fZ6qbIWs273r4vcjb/bt+8o9tt3sk27N26CafesNekWs24btVvIsw3VXZJpl2C7WLcBpt2M2s3XjQgQASJABIgAESACRIAIEAEiMPEI5AQaGyTS4SBjrk53zf4xwcZAol36q/livzH6SN/+v3cU37ntR8WJxz55bGOz0fhIzxoSDdNuS6RNsDETYaz0kzaaaPu7T6Q3GyLNYGNjGxRWTASIABEgAkSACBABIkAEiAAR2FUItOkfLW3WRBpm3SDSzkd6weaRHieRvuCDny5u/NqtxUcuPLM4cP/VY4HREWn4SLsgYyDOJuRYH5EWXF0maWikSaTHMhislAgQASJABIgAESACRIAIEAEisKsRGIZIS+7oSussaZ88s270Rcy6XforF7V7/333GUs31xiyespZ77B1H/OUw4qzX/r7Y3mOzQltonZDKy2BxoAFPnCLBrGuUmEBG/MliPTcclOe6a/GMiaslAgQASJABIgAESACRIAIEAEisMsQGCbQmBDpkH+01kbbFMqlWbcLOrZzrET6vR+/rrjmxq9X2F196RuKPXZb1TqWQqRnbA5p5ydtGbRNdQUm7TJFmytV9O61SH+1gj7SrQ8GKyQCRIAIEAEiQASIABEgAkSACOxqBBqJdEagMT9at/hH43sXaAwaaZf+qm2N9Ldv+6HN53zuuz9e3Hvf1gpC+Ek/5YhfLB6y/96tmnmDSNv0V8a8e8Zon0GknVd46SddEullxm9aonevsemvVlAjvasFnM8jAkSACBABIkAEiAARIAJEgAi0jcDwRLo+7ZVoqtFWkGhn3t0ukT7r7ZcX3/n+j7Lg2N1op8867TmGXP9C1n1+YZ9Iu1zSiNrtPvLjIJFeSSI9EvK8mQgQASJABIgAESACRIAIEAEisAQQSCXSpfuzbbEz7faIdNkXSXslXZO0V9DY2qjdJv3V/vuN7iN9w1duLi68/JosBB91yIHFha9/ycjm3hs2Go20SX8FrTQ8o10KrB6Rhmm3Jddl5HL87DTSJNJZA8bCRIAIEAEiQASIABEgAkSACBCBpYhA+0RaiDYYt5h1G610y0QaWIJMX/qJ64r77n8gCu2hj3tE8ZbXnDwyicaDaol0mT8a7Nq6SpNIR8eFBYgAESACRIAIEAEiQASIABEgAhOHwFBEuvQIdtpno30FYcQfL380vh+XRlqARt7oPzVm3k1kuu0I3uttBG4TtdvTSFt/aMui0bqdxQy01GU+aQQbo0Z64l4PNpgIEAEiQASIABEgAkSACBABIjCIgE+ktX+zjbpdhebu3QvCGEp9VU+kjY+0yScNUt2WabfuieSOrhvftqN3C5G2EbsNWUbAMZh2k0jzDSMCRIAIEAEiQASIABEgAkSACEw5AqPkkI6lvhJSKRG7x0mkX/6mS4r//vGa2tE699XPGznAmK58WCK9fAWjdk/5K8XuEQEiQASIABEgAkSACBABIjDtCIybSFuz5jJi9ziJ9LEvelPjUD3/955WnHLi0a0NZ4hIW3vu0i+6zrSbRLq1IWBFRIAIEAEiQASIABEgAkSACBCBxUFgGog0ckif/RdXWAARlfsVJ59QPPrhBxVXf/6m4mN/90X7PQKNIVp3Wx8S6baQZD1EgAgQASJABIgAESACRIAIEIEJQ2AaiLRE7j7l2UcXzznuqL4RWGOCgl34wasL/Puxi85qbXRIpFuA8v3vf3+xZo2zxz/33HOjNZ533nlVmQMPPLA4/fTT++657rrrim9+85v2u2GuRxvAAkSACBABIkAEiAARIAJEgAgQAYPANBDpxRjIRiKNvFf2Mxi1m6bd3mjddNNNxY033hgl0iDdmjiDVD/pSU8qTjjhBFsjSPT3vve94qyz3GkJyu+1117FSSedlHR9MYSIzyQCRIAIEAEiQASIABEgAkRgMhEYN5Hupb8ab9TuXY1+Y7AxEun04Ugl0n6Nn/zkJ+1XQpQvvPDC4qijjrJ/8Vm/fn1x6aWXFmeccUbx4Ac/uIhdT28xSxIBIkAEiAARIAJEgAgQASJABAa10pOY/mpXj+OwRJp5pL2RGpZIgxj/4i/+otVI+6RZHgGt9THHHFM85jGP6SPV/nUh36MI0T333FP84Ac/KI444gj775577mn/8jtiQDngu8D5gHMi1wWujdwfcI/EPeF07gn32GMPb8//n0X13X/+oDj88MMdxUDq6PKTn0d6wd4+Pz8/ljzStnl9JwC9ti6rNMSjMKX+e4VIz87O2gDdyCdd5ZFu0EiTSLdApGG2jY+Yet92223FVVddVWmffaK87777Nl5vg0hDsO+//3774uBfCAb+duk74I7+7r777n0YbN26tTPfrVy5slNjHpLxLssBZH2FyXHYtXff7y8WY3zXpXdf95dy4NZBygHng67LAQ5RH3jggU7uCWVdwJ4QyibZF0/jugAS2L/mbbXE0H73wFbLDfB7H5EGaTWEUcirJrG4ZH8HwzT/uDzSwxPpOoLcHi12NeUQ7joi7dJeSX2AwGGEutes21iQSI9IpLUmWqpaChrptoVxEuvbvn37JDa71TYvX7681fomsbKuywFloCi6LgN4bykHlAPKgVvBujwfCJmaxLW8rTaDAELZNM2fQaLaI8g2L7IhgSDV6UTa6KuV9jqHSO8q0pw6nnXkupZIW0aO/znyTCIdQTrHtNv3c9ZVx3ygY9dTBYLl6hHo8mIpqHDz3O1NEzfO3DhzLuitEVwTeKBCIu20kl3+kEj3iLSQQksTQxppkGdDInHNJ9L4bmFhZzG/YEy7d+wo9t93HytWS404x2RdiPX6jZuLubm5YnZm1mjrDTIgzcuM1t4n0jvNoURJqqmRDqBbR6QllZUEC0Nwsbvuumsg5ZVUyajdMdEd/3Vumrhp6vqmiUSaRJpEmkRar7Y8XO324So10s4smRppp5EeJNIgwm7GsIRYEWkwakuo8WVl3u2INPbbQqTHv7sfzxNApDE/CpHGu+K6b/4YYr1z54Ij1wNEeoX5btKOD8aDoa01lUjrHNLSnMc+9rFV1G58xzzSYxyohKpJpEmkSaQpA5QBN1mSQHWbQPFAhQcqQIBEmkTaysHsjPORtoxZEWerfe79bok2/tgvS/NwlDGaaDmQWDDXRiPSyglZ7e1j1LTe/1nZoCdwBSkiRHqmNHu3+CDIGFzDFZE2yBULJal2GmkS6WSYYY4teaGTb2LBRUOARJqbZ5IoygBlgERaFiGuCZwPuj4fkEh3lUj3CHKMSFeaZwTUKom05dvKvLvykTbfzRsNfzqR7pHmGFEelTz0E+04ue5ppBGte1kVtRvtEAtvi50i0mvXbyqWr1hOjXTKYEG7jA/SW/EzGQhw08RNU9c3Teg/NZHURFIO3JrFNYHzQdflgESaRLqOSAtZro/c7fykrW+00ciKeff8/EKxY35Hsd/qvQPkwBHncZPmVFbSI9eDxHrDpi3F3KzxkRZtPYKyGdJszblL5b0l1SqMtyXSxhycpt2pI8ByE4UAN03cNHV900QCRQIlkzYPVEikOR9wPiCR7i6RrkyzzWugTbtjAcdwHcRZm3eLnzR8ze1fo5Xed5+9yuVmCPIctu7O5xxxxXNVp0+qN26+0/hHu2B8NiCfTfXlgo4Zpmzvm9GM2vxOIp0/RLxjghAgkSaRJpGmDFAG3KRNIk0iTTkgkSaR7gaRhqQ3pcBqJtI9M3CYcIfMu6VukGiU2bFjvthn7z3T8jYHSHNbGuug33QCucbzN2+5y0TtRsRuHdkeRFp8pJ2pOz7ynLXrN5q1lT7SE0QN2dQcBEikuXkmiaIMUAZIpGXd4JrA+aDr8wGJNIm01ayCLBrSWBFYRTatthlaaEOQK0LuRe/GtZ5WGkR6R/GgB60qVhp/4YGPR5zbIs2pfGCAXAeI9dZt24r779vq0l8Z026baxt/rAbaEGgEGzMB1vA9tNLoAzBcs25DsWLFSpp2pw4Gy00WAtw0cdPU9U0TNVDUQMmsTY00NdKcDzgfkEh3mUj3NM2NRNqmuOpptEEa+6N3A8Me2Zbo3SDTq415dxUNvCTQKcRZNL0pZUNMRMiya3nzpyLWZVG0H9poMelG+10fTL+hjsaxgiHSLuuXIdAlkca1tTZqN4l0DHNen1AESKRJpEmkKQOUATeBk0iTSFMOSKRJpEmk8Rb4RFr7SVtNtJcGS9MABBwDkZac0tDUiok3uOnee+1u668jxaOS5lRKEiPXuI6+brnzHkOOnS+0za1tSLPTRstfMOnewUKPSBfFmrUbi5WrVlEjnTooLDdZCJBIc/NMEkUZoAyQSMvKxTWB80HX5wMS6W4TaQk4NqCRxotRRuS2P4ItGyIpZLinlZY0WMgj7VS6NoK3+YBMQyuNKN577L6bMXmeq7TTmqjnMIlaMl5qinPqAjEWjTWCo23btr249977rSk3TLpFky4BxWagha4IteunJdcStdtg5NJf0Uc6ZxxYdoIQ4KaJm6aub5rQf2oiqYmkHLiFi2sC54OuywGJdHeIdEWI+/btjhxXcqA0rdYHuPw4It0zBZe0V/q6/a40pRbzbtxntdMwDzf1WV/qsl4pi/ukbXVEOcVEG3XoVFS6m6JNMPLsEQAAIABJREFUtmVKE/MqUJghyOg/NM/QRFstdJk3Wsi000i7J9iP/FP6Tpd23iTSE8QJ2dQhEOCmiZumrm+aSKBIoGTq5IEKiTTnA84HJNJdJ9KOHPtEutI4lyxXiLTTYPe00DqCt9NEO/NoCTwmxBlkGnxZApZV0b+t/7UzCy8jeikT8MFw3nkaacfQrUm3/dH5OIuZtvVvtr7Prv94mphyW1N0lEfm6NI/2plwO7K+s0x/ZQm31dS7PNrUSA9BznjL5CBAIk0iTSJNGaAMuDmbRJpEmnJAIk0iTSIt5so2V7Klm0Js7S/VR8y7xYTblhV1smGhljSDGOt7Si00yjqC3SPhlqyX6mG5ZeB+XVkG3dCRuW26KgkSVtYhz678nksyXZFqROUuny33W3LtrNZd1O7yOnJN70RaMFNwjQk2RtPujIFi0clCgESam2eSKMoAZYBEWlYurgmcD7o+H5BIk0hrIt0z4S61uVYD7X7umW6r70qtrfhF27I7VaosF9q6JNjOtNtqta1G12mcK1Pv0nxc5uc+Qq5+8bXS/aS5p8Xuc5u2Lt4q4rZ7sgkKhu+cZroy/y7NtcXk3RRSRLzUVJf+4k7Dbauwpt8g0ozaPVnckK3NQICbJm6aur5pQv+piaQmknLgFg6uCZwPui4HJNLdItKOEA+mhEJ+ZJ2mqq+MLe7Ic5+vdOlP3Qs85kyhnWa69xwblAv3l+ptd83TfJdkVD+jb3tftqF5y+/8uP37NEGWaz0T736faUln1SvnzL7FzBu+3vbeMo+01VZbMu6IOvJIL1/JYGMZ1IxFJwkBbpq4aer6pokEigRK5mweqJBIcz7gfEAiTSLtSKAi0o4390ybi5nKt7ki4oZIir+zfYuszXYv2Jj4PIu/tCOigXpKzW5lRm0f3Ht2FWRs0F06TD/KM4IqkJhlur12VaRamZWjIkeWHeEXv2j4PfdMwqWe8rFiLm5M1yX9Fa6s27C5mDPRyZeZDg0eV0wSY2JbiUAAARJpEmkSacoAZcBNjiTSJNKUAxJpEmkSaUekEVTL+UjbT0WkSzNu7ffsvKhtIdFGV6S6tNjuaZZBuHuabPG57ifhPbI7QD/L56bS0srM2yPeVZoq275eZ7QW3plnA4deePIqUFkVpbvUTlsfaUe8zRFEdeiwZj1Nu0lApxgBEmlunkmiKAOUARJpWea4JnA+6Pp8QCLdPSINmdfEVHyBZ2fn+s2+DakUwlvlfVbm3CDbWstc+VKDOJc+0JVPtIr+LWbS8I3u98kuCbWYkGtWn8VNekS5p4G2va4ieFfm2aWPd6V5tn7UzmfaEmVjtg0zbjlskAjnO5e5NF4uajeCjbmf74BpN/NIZ40WC08QAtw0cdPU9U0T+k9NJDWRlAO3cHFN4HzQdTkgkSaR7hHp2f6I2+X+vhe9etCc20X4dgVFC+1SX/V8ooWMo1yV9gpE27tP6ISrr9SEK81yTCutg46JdtmR5x5R0fmk7UFA2U4XbMyVq7TUpfZa0mXhXhsPrTTrFrPzKp2WuchgYxNECtnUfAS4aeKmqeubJhIoEiiZOXmgQiLN+YDzAYl0N4m0Jr5CHl36K4nI3SOyfVpj5YNcmWcbYikpsYRYVybfRqsrabFAbhGsqxcF3JmIO39mFcxMbe8HNNaNW/9+jbMu2iPQvWdqLTRyQVtibU27jbG20TLbIGkILGYv9bTSpVW7vVZp10tt95q1NO3OZ2e8Y2IQIJEmkSaRpgxQBtyUTSJNIk05IJEmkSaR7ifS0Cz30ls5FW1P22wJpQ4GVkXyNtpqQzxFO11pocs80g9atbKYm5spJFf1UiMO8/PzxY4dC8X9Wx9wqbDKPNGinQaZ1ibccl0IupDutes3FcvnGLV7qY0v29MSAiTS3DyTRFEGKAMk0rKkcE3gfND1+YBEmkR6XERazLh3322VIdCGjU/AZ35+objvvq0mfnfp/2xINT4k0hMweGzi+BHgpombpq5vmqiBogZKZlpqpKmR5nzA+YBEmkS6n0gPb9otZtgw87bm3ObfPXZ/0MSQaFkb503b77nnfmvqbc28bRRvZ/ato3jTtHv8vI1PWGIIkEiTSJNIUwYoA9RIUyPdW5x5oNLtAxUS6W4S6XDU7uGDjUmgMckbvTC/s1i5akWxasXyJcYE0pqz9YFtxdat24qZ2V5eaedTXfpMl/7RVlttv3MHEAw2loYvS00oAiTSJFEkUZQBygCJNIk0ibTexnR5b0AiTSLdRvqrKmK3IZMLxjx6fud8seceuxezpWn0pNEGHAjcefc9xeyyWUOmEdG71EYj4RdSYzH91aQNKdvbBgJdXixpztmToK7LATVQ3dZAcS7gXKDXU84H3Z4PSKS7R6RDaaRctGpE7S4/Zb7oKop3LzWzjVTtUj85LSw0sgjWhQ/MuRF4a8eOHcXqffZqY+u+aHVs2nynCZA2Z4OMSS5pYGQjddtgZCaqt82kjZzTDqA16xm1e9EGjA8ePwJdJ1BAmJumbm+aKANunuFcwLmAcuDeBa4J3Z4PSKRJpDEPLDNkscqfbL9wkbrdjyYVlNHQysd+b4hk33eGQINbzy/M2+9BpPddvff4N/ZjfMLGTVsckTYa6FkcMljL7jLZdJkqy5wauGjeJVbrNmwu5lbMmfzUsazXY2w4qyYC40KAm2dumrh5pgxQBkigZI3hmsD5oOvzAYk0ifQAkVYk2s6Vlk+rPM/2eo9sW8po/zN/DLEEiUb0631XT7ZGeuOmO22gNJBpaKDxx3YbZt7QSJu+2hzTJl2Yw3CZ8ZHeUCxfyfRX4+JxrHeREeCmiZumrm+a0H9qoLqtgZJpmHJAOeB84N6GLu8NSKS7RaTDelLn/4sczxJ5u6eN7uWUdny5Z9LtOHZp2m000fjAxNtYPBfbtm0r9t9vn0Xe9Y/2+PVGu7xihSHFJgOW5L+eMT7Tts9lcDFLqsvDBpBqBhsbDXPevcQR6PJiyc1zTzi7LgckUN3eOHMu4Fygl2rOB92eD0ikSaRdJGpHpIUcV4Rb+0aDSZtySG8lHykHcmlJtCkDbTS00vvvO+FEeqMx0zbaaGilK3xE+2x9pB0OCKi205izO430xmI5yDdNu5c4I2TzhkKg6wSK2gdqHygDlAESaRJpEun+LUSX9wYk0iTS1uUZfsAg0qVZtwQRq4iyJdF4b0Agnf90VQY6WkTrNqpoXAOJ3jFviPTqCSfSmwyRnp1zpt3IKQ3VtEt2ZaJ2l/7jCNJmtdNGDW++Wrt+E4n0UAyNN00EAl1eLLl55uaZMkAZIIEigfIXa2qkqZEWTeREbOTG0EgEx5Ko02OofklVOWja7TSrPpFGo+EDLJ+eybf7Rsi0XLf5o01xkGn8jP32NGikMT8CGxu52wYYA5m2fNr9g+/sL85PnER6SYk7G9M2AiTS9I+FTHVdDrhxpgzgPaAcUA4oB26X0eU1gRrp7mik6/yjKyI9V/pIV+y5F7nbEWntL+18o0G1rTbakGeYfFvTbuMvjYOJ/SY8avcGE7Ubh0yI2O3Sg8EEXnJKu0MD5yNdsmrTdxLptpkb61tSCHR5sZSB4Oa525smbpy5ceZc0FuWuCbwQIVEujTpXVK7tV3bmK5opENEunTzdRppRaQtSS4v2jRXEqm7JM56hKwmGvmjoZU2fxaMj7TVSE9BsDGrkYaPNJKAGYwscbZpsHqHDJL+ygYbW7uxWLlqFX2kd+0rzKftKgS4aeKmqeubJhJpEmkSaRJpvebycLXbh6vUSHdbI11HpF3KK/ex/tCKQGvfaLnutNE9LG2wsSkg0i7Y2GxJosvUV86eu0r51SPSy4q1JtjYipUrSaR3FbHjc3YtAiTSJNIk0pQByoCbd0mguk2geKDCAxUgQCLdZSLd0zr7Guk+Il2mvLKaaSHUKo80WKU17S4DbiFq97g10mtMaqp1G+4sDn38I8ZGJJD+CuskonaDODs/afhIG7P2Mo+0fC/m8cgjvWIFifTYBoUVLy4CJNLcPJNEUQYoAyTSshJxTeB80PX5gESaRNoeqBiyCFnAR5t1+0HGQJidb7RTWbvo3b0o3s5XGkR6PBrpG75yc/HRv/tisXbDlopQHPvUw4vnP/tpxYH7r26VZDgiPeeCjZVm3S5VmPl/mf5K/KNh8o3P2vUm/dVypr9qdSBY2dJBgJsmbpq6vmlC/6mJpCaScuDWJa4JnA+6Lgck0t0g0k2BxnKItJh1u1RXTi3tTL/Nn9JP2hLpMeSR/sg1Xyg+Zkh06HPA/vsU733rK4s9dlvVGulYb/JILzem3RWRNuTZ5L2yftLGdts+x6XE6n1IpFuDnxUtRQS4aeKmqeubJhIoEiiZm3mgQiLN+YDzAYl0d4m0+Ef7RNr3j/ajdZeW3n3aaDHrlsBtO0zU7jbTX93+v3cUr3jzpY3U4smHP7447zUnt0Y/QKTnELW79JGGGbcJOeYCjgl/tsHMy6jd5sk2arcxB19mTheUm3lrbWJFRGBRESCRJpEmkaYMUAbcNEwiTSJNOSCRJpEmkW4k0iVrdibc/dRQzLpxv5h02/RX8JHesb148H7tmVq/9+PXFdfc+PUoh7j60je0ppVet8GQ4jnnI+3SX4mPNEy7e00RU3iUcemvSKSjA8UCk4kAiTQ3zyRRlAHKAIm0rGBcEzgfdH0+IJHuKpHuBRqrI9K+f7SO1q3Num0qqNKsG/mjFwyZxtzaJpF++ZsuKf77x2ui5OPcVz+veMoRvxAtl1LAEmmkvzIEuaeVRmfFR9rlkTYe1FVO6TU2ajd9pFPwZZkJRICbJm6aur5pogaKGiiZuqmRpkaa8wHnAxJpEmlrslySxaZAY3VE2gYeK1Nf2XzSxn9627ZtrRLpY1/0piTW8fzfe1pxyolHJ5WNFQKRXrFihfWDnjH+0XhXnFc4TLtxEEEiHcOQ16cMARJpEmkSacoAZYAaaWqke4s7D1S6faBCIk0i3Uyke5prq4X20l7pQGP4GUR6fmG+sHmk992nFRaR4h8tD2rTT9r6SCOP9AzySEuQMUuj7cGD6a3zlzYByHCYgJ+dRprpr1oZeFay9BAgkSaJIomiDFAGSKRJpEmk9Q6ly3sDEmkS6SwiXb442j8aX8FH2hJp6yM936pp99du/o/ivHd/IolUPPrhB9ro3W18xLTbmnWDMNu/2jnakWftI00i3QbyrGPJItDlxVIGhdqHbmsfIAeUAcoA5cDNiFwTOB90XQ5IpEmkNZGORuxuINKWTJvrINI7Wswj3ZT2KkQ4brjyba3wEOSRnjN5pEGkEZdbBxuzDzApsEikW4GalUwKAtw0cdPU9U0TCRQJFA/VeisW1wSuCV1fE0ikSaRTibRzhXaRu62VN/4Hhln5R4+HSJ/7ro8XX7/ltmSq8d63nlE8+uEHJZevK1hLpMs+O9ycz7SYvFMjPTLsrGApI8BNEzdNXd80kUiTSJNIk0jrdZoWKt22TCCRJpGuJdJe6itrwow/Ng2W8522vsHmT5X+ylxpWyN91tsvL77z/R8l04sL/t+pxRMe/8jk8rlEWvpsDxFM/xGMTA4ZkP6KPtIjQ88KlioCJNIk0iTSlAHKgJuhSaC6TaB4oMIDFSBAIt1NIt2XElpF7e4z7c4m0i5iN0h1m6bdOT7SjzrkwOJ9b2vHR1o00nhHJHI3fKRJpJcqy2O7xo4AiTQ3zyRRlAHKAIm0LDZcEzgfdH0+IJEmkW5PIz0eIo13dI3xV167YUuUJ7ShiZaHbNi4pZidQ8RuEuko8CzQDQS4aeKmqeubJmoi3VzHuYBzAeWAByo8UKFGGjIADSrMkaf548yxe59J0kj744J0WDfd7Hym99htVXHisU8ey9CRSI8FVlY6yQhw88zNMzfPlAHKAAkUCVRvJaeJf7cP1qiRJpGeBI205h43fOXm4oav3mK/2t0Q6fNec/JYqEmMSC8zuaV3GlN2+kiPBX5WuhQRIJEmiSKJogxQBkikSaRJpPUepct7AxJpEulJI9K7il+QSO8qpPmciUGgy4ulDBK1D93WPkAOKAOUAcqBmxG5JnA+6LockEh3k0hL1G07EbYWbGw86a8Wi2QIkfbzSEuwMWqkF2tk+NxFQ4CbJm6aur5pIoEigeKhWm8J4prANaHrawKJNIn0Us8jrUmD7+st15YhoXPLnzoiLbmzQaRdAmlzFrHTJpQuXB7pFeb3upa23EhWRwR2JQLcNHHT1PVNE4k0iTSJNIm0XndpodJtywQSaRLpVCKtqaHNIa3il42aR3pX0c4cwl1LpMsJFOmjq4/BAnWTSO9KVsdn7XIESKRJpEmkKQOUATf1kkB1m0DxQIUHKkCARJpEWhPpZeYXIbX2X0MO+34vX5sQkcZ3C+YvIqBjv/3g/VYH9/m7ijSnkow6cr1+4+Zibm6ugGn3jMEB5ZBHWj4k0qkIs9zUIEAizc0zhLkLqS6aXloSKBIoEmn3hnBN4JrQdTkgke7GnmCQvPYIchaRhhbamDC7+lwd9s8CNNSGSJt/5xfmix07dhT777uPnWeXGnGOkRoh1hs2mTzShkTPziCXdEmkTU5pWHPbMstKlXz5DzXSMWR5feIR0JsmeVGwiMgnNY+g3IM63MSxMIBNUxncp5+rb0ZdTT4guA/Xpf2h8n79uoxPol784hcXmzdvrppw6aWXFgcffHB0rP/0T/+0uP3226tyT37yk4vXve51ffellPnLv/zL4utf/3rffW9605uKI488srYNfpuloNz3rW99q3jb295We/8b3vCG4rDDDov2cVoLkEiTQJFIk0jL/Mb5oNvzAYk0iXQzkQYRdrOF3XuCPOOPR6RBLp15N7TSC8W2bdsqIj2peykQacyPSG8FIm337SDQHpEWLX6PSC+nj/SkDjrb3YyAJtKhzQOIdIgU61qtiYci3zK54PRNPrEyMBWpMyXB5KTrkjqbFjvd7rpyooUN9fu6664rPvCBD9hHpRBpIchCnoXYajKdUkZI9KMf/ejioosuKq644ori2muvte34zGc+EyXSL3vZy4oTTjghSeylj6tXry4uv/xya3rU1Q83zt3eOJNA9d58aqSpkYY0dFkOSKRJpPEOzMyCLJaKJUWcnfa5mUjbMiDQhkjb/ai5Ae+UaKTz91rhwGExzXa9/7Ny5s5oDIg09usw65Z9/TIos0xftUaaRDoDVBadbARksZSFw9dsXnzxxcWBBx5Y20m5L6RpPeeccywBlpetqQxezPPPP39AE4sHP+tZzype8IIXDLRByLcmm1IIhPK4446zv+L5IY0s6n3hC19or/ufHCKt6xbSre8HAU4pgzYIRmjbqaee2ndf20T62c9+tu02tNaHHnroZAvyiK0nke72xplEmkRaTyGcD7o9H5BId5VI9whyHZHG99A+VybcOroYrqmAY1WwMesjvVBs35FKpHukOUaUR9z6eAqsOLm2RHoWPtIz9l68KzPGzNtZhRpUjJa6anOppV63wfhVL5+lRnrUwZqE+xfTpFcTL2AVMgv2MYyZ64pZbx3RhOZSiDReCBBTfHRbmoi03NOkaT3rrLMsUY2VwcsoRNrve51GGu29/vrrreZYiKduO8yVYQ59yy23VGbNgomQyJe+9KXFM57xjJGItOALze6HPvQhW9fPfvaz4owzzrA/g9SvWbPGapabymA89FihrZ/4xCesubj0r+49EtlN1UiL5luw7rL2AZhy49ztjTOJNIk0iXT/6tLlNYFEmkS6kUiHAo4pP2lcdkHGFqzZNzTS+LvD/N1v9d6BbZwjzuMmzak8rKfFHiTWGzffafyjZ5yftPmLQ4WZZU4ZVRFpo522pvE2J1ZRWCJtyjL9VeoITHi5HE0kuppirptSRmALmQTnQKrNdUHq5PcQ0fQ1kXh58GIIOcVzm4g0ymqSeskll1jt9ec///nKLNrXxqLMQQcdVHzuc5+rylx99dX2ZMsn0uLH7E74Bl9odxI2Y01nxEcabRKSLH3W5tL4GQTcx8nHOEcOpH5NklGftAPk9rvf/a7VtjeVEZNs/1AlhRz7h0D+c3T/NMkXLXeXN00k0k46ui4DlAPKgcyTPFjr9nxAIt1dIi2aZp9ID0buHjTvBnEO+UmLqyGI9L777FVOM0OQ57bSQscVz9WW0SfVm7bcZYl09Y5YwixxlYxWGgHISp9x+FEDj3UbNlktNol0Dpub4LI5BCrFXDeljIZrVCKtzXXrglNpoumbTGstbwqRvvLKKytN62WXXWa7snbt2lptbKgMtMIgkSGNdE40abT9jjvuqJ4t2mafSINs33zzzZWWOuQDnSMHbRJp0UjDR3rTpk1V0LMUCwX/MAa/h8zBffNxkihqpCkD7u0hgeo2gSKR7u1GunywRiLdDSINaW+K3K19pJuINPapQh6lTtFK4/eKSO+YL/bZe8/aeEB91ClAmtvSWAf9phPINZ6/5c67rVm3fkdc+ivxkbY/Wk01InuTSE8wIR626TkEqk2TXp8E5RAnudc31w1h4JscH3PMMX3Fcoi09muGBlRIstYK+9rYUBmfSOsGgeQecMAB0YBn4i+tSS2ehZdda9hFu6s1uKMS6bbkAFGzxRw85Gsdi9wtuPljrIOP+b7bck+XN00kUE4Kui4DlAPKAYk0iTQQIJEmka7kYM6RQftRZFP8pCUYry3jpcGy1pKOVVofacQMetCDVhUrVywf3J57xLkt0pzKhQbIdYBYbzVRx7fe/0Bp1o1o3c58uy9zDrprUmDZ/NL4Y/5du35jsXyOUbtTx2Liy+UQ6TY1kaMS6ZC5bmgw/Db7m+fFItLHH398X+RvnQLqjW98Y/GEJzyhVrZ8Eo2Cn/70py35lkBnvrk0NL6SqmpUIp1idZBbRmuStYl4akTuunvkAMH3ue46iaImMp1IY9HUi24s3ZxsCOqi/+vUdCmp7kITgXbv8NPs1aXjC9VDOUiXg4lf7Bs6QDnothyQSHeZSPdMtq0c1BFpmyu6p9HWabAs5y7zR4NqStAx6ydtyPRqY95dRQMvCXQKcRaf45SyoelN1m3X8uZPtcaXRdGHzcas20bsLk27XR+Mj7Qx57as2v7fBBuTXNLl7+vWb7LWXjTtjqE+JdcnlUiHzHX9IdHktM43Nkak9QYaP3/4wx9uxbT72GOPrTbn4qutzdzPPPNM95IimoGavEKaaD+VUyj1Vp1mVjBrkgONo5DwOj94TVhjZfRhiNyng4/hWfiI1rrOaiHUPtwXIvPSXxLpwAnxlMxpqd1IkYG6DWZKurlQ0EAd5FDe61CqO1xLSZFXR4DqAhb62JBAdZtAiTxQDrotByTSJNKYC3wirc277cGwlwZLrydQUCN/tI3xgz/mZ1knwU333mv3SpMbWqNHJc2p636MXOM6+rrlzntsyish0eIL7Q7CPXW6+hU/rl23qVixYgWJdOqgTHq5HCLdlkmv1jIO4yMdI4UYkzrteY5G2iekmCC0rzECiR188MF9ptShYGN+GQQb80/Y/EjfEv1b5EsCkOGl9vsm13QZa2ZSknDU4ZNaX25zibSuU+oKEd1QCrDXve511eM1mdZtEsKur0v9dff4/tEheSWRdghw4xzfOMvmMpQFAG4HcE3AOwfCG5JJWIFccMEFffnK/bgGkGk5NPPfyViKPEllF8pmEHp2aK2iHMTlYNLX+JT2Uw66LQck0t0m0hJwbEAjjcmjjMhtfwxE73a+0pIGC3mknUoXgcjwqSJ4G3/pPXbfzRBMp+HFRxP1lHlK74dD5etzSNfXjntEYz1vCPS2bduLe++936zrLkq3pIsVog8S7fbXpg/loYGkwLLPN/1H1G5qpHNGdMLL5hDpXHPduhzDGrJhiHSdua7UW0eicT2HSONF0NpORPQ+5JBDaiOX6zzNTdrYU045pUq9JW3W4wAf6t/5nd/pC2ImJFKX832IxdzTzxOtiYD0IVdsxXS6Kbdzbp2LWT5FG7mY7Rv3s7lxjm+cgZF+d+oi8iPVm1hN+OnmdE74UO76VCIdSpGHDQrINt5NEOeLLrqoj9DX5aPXskU5iMvBuN/FpVA/5aDbckAi3R0iXRHivonH5ULWkalF2QPNch+B7dNK9wcvc8ocyTvdwxTfW+00rpv67F61rFdIrE5UU+cWlWKiLQQ9NK9W5uUg8aUWWQgyyLB148K/ZUYfsRatfKKtD7RYijrMLKm2nNrllS7M+QGJ9FJY1XZhG3I1kTFzXTQ9pYx0sY5IhzSRuKfJXBfXm4hmG0Qa2mWtPZZ+YKN79tln28lCJqOQNlbKYOPip3BCXaLpws86GrhspDWx98VEiLy+T5e55pprrL9K7qZJnhnL7bwLxXbkR5FI07Q7JgP6HdWHZDrIISxHbr311ioiPt4xLKza9QSZAmRO8N/fXCLtp8jz/bfxuz5o9LMU+C9O7lww8ou3BCuIycESbHLrTaIckEj7B/CtC9kSrzAnY8oS70q0eSGfYxBZn0hXftAly3UaaUdVJUq37yvtNNHOPFoCjwlxxv4YtFyIchX9u9Tsomb7KEvWhcAPhvOu85kOa6RdPfYamq8ItGijhWDb9dSUxbsgxFoCjLm6kUNatOkmFS3yZlsi7a7ZSN47EWyMPtJRIZymArlEGn2PmeumlkG5XCLdZK6L+mJE099Y+ubb2vdRfBRFGwuTbE2UtRz4k3DIT1mXqfN/lDIhX8pqMqgRQLQNn9CCKCeC+Jebpm5vmiAjOTIQMh3Whyqh61pEteVE6PCoycrBn2t0vaKFTSkTemWaCJS8fz4p1VpqRO5HfAIsvjJHoE3Pe97zKmKNOQPvtM7ljjIPechDbJ71XCKNfuh5xJ8ntAZd5qum9SpHDqZp3dN9IZHOmw8oB9OHADXSXddI292lJYWyf7R+zqHo3aV5t5hw486qHCybQaBLzbS8KaKFlvVLm4KLVtfWU94wcL9uEKmPAAAgAElEQVRWV2e8fv0xjnoxh4SaVxrl0hUS3/eR6j5faKd9ttdtQ/sJ/sysOVxAWjBE7TY+0jTtzhioaS/aBZNe8ScWH2MZU23aDeIAk2yZMLQPsn+f3B8ro81MZILR8qTvlxM8/x5dXsr4/tF+3dw8pxPpauJUE3zI7EhPvvq0VcuCHjvITJ35Ut09+F4OS3w5CclS3akt7k2VAU2SfbNlSa0WmgPlgA5k80Mf+pAt4rtkCAEWQpw6l0o9Tc9PKRMjUL5rhx/8TlLgycZDHxJIv2EBguuS712+11pt4BAaqzofaZ0iD+PuW6DIM/ShYB22qXJQ5yd+5JFH2qpD1/UzcVhSF9sA5WIuIymHt6E2aPmrwyAmB6lyOcnlUuVgkvsYa3uX5YBEmkRaE2nRPFf7XauBdjS3Z7qtvoMmFlro0i/aljWa2SpVVpkSS/bK7ntDRJ2bsatXTL0rrXf5vU7BpQi1v2b2k+YeyVWhgkqNdBltuyTJYo7tonG7DB22rjLVFVphTbuNzbY8A1ppp20v67LlXdov/MhgY7HZtkPXu27Sq7XG02T2w01TGpGu21z4GkFrBtQ3W8sCsNOa0qfU408rTRGbUacsIk0boCYilSoDMgdoshsiyX775QBOa6P974T45BDplHtSyqC9sY1znTm2pJIDScOzMPbSN2iYoWmWj8SJEJItv2sijeB7ekzlXt+qJZQizx9/bWGEg4ZjjjmmccVKkYMmP/FQKj15oN9HTaSb7vMbXOcqpP3GQ3KaulTH5CC1nkkulyIHk9y/lLZ3WQ5IpLtFpB0hHkwJhQBa1aF8n3k1bsBdjjz3iLbjw/KdCzxWkmqrme49x5pBl9fd83ukvK8t5T09M3L19gY0wYPvtpif99+nCbJcsd9Vfs/uW2ljZcJtibXTZkvf7L92z9dvLm7vtxppk0fa5M5m+quUmZdlJg6BnMWyTlM9cZ32GsxNU5xEiclsnVkzIiaLya72idVQY6MPEgBSHKvHlykZIyFocl3IG4hXUxtRHoHlDjzwwKC4pspAiKDE4hT4BEoaoLWK0ECGyHbTu5VCxFLKyDNS5oLQgYaPie7vOeecY8dFiLNv6l3XP+SB75349zY4ckAjJnehFHnaGgHkWwdb/OAHPxjcMEk7UuQgFNyxboylXi0jom3OGZtQPXXBK3W9Mc12CP8UOZj0OT/W/hQ5iNUx6de7LAck0iTSjgQqIu1YZc8K06iPtRWdXa+MVrfPss65CVdRsN2a1vOXdkQ0UA9IqhB0e4cjqNWaKEbfg+7S4WmnXEKrQGKlhlmClVWkugwWJpVUmmdHr8tDBUearRm4U1Mrq+5Se2206RK5G3Vt2HinycdttNvmpsHjikmfKdn+ziPQ5cUyZ/M87YISkwMQkltuuaXydQ2ZNSOyuh/c6dRTT62gk4UhVk9Ia6gDXQk50OTs/PPPt8++/vrriw984AP2mT6JaLKiSN04+xpOpK7TJsy+ZjFGavwYBjmayRQLmZQyqUS6z8zLbjLcKi4HAIiu/4xnPKMvsJikpIrFcvC1rNpPDM8ImfD7KfJQh+8usKuIdKx/IdP6YYh0SspF4IV3IMeyQc9vsblg2udC9C91PphmLLosByTSJNJ4t50r22zvNa+IdGnGrc2sXbZoyyqFZFak2n2ttNcg0z1NtvDifhLuSGqfb7a0RMy/E2lpZSHoEW/RQLtm9zqjtfDOPLvMFS1RuctAZULEHeEGwTb/lpp2rW1fu8HkkV7OPNKVIL3//e8vkN4En3PPPTe6jmDj+c1vftOWgzbo9NNP77tn1OvRBrBAIwJdXiwFGG6a4hpp7Z+KDbpPXMX3UoimbOKFEEnADUy4uBfmvnX1XHbZZQP+0rgPf3VKM/gaX3vttXYYEUhKk3htQi3+100+2DkyoMk0ni2mzfjZJ8I6WrU+VEBZTR61+XOTr7PIbEjD6b/oKWX0PbG5IBQwUPog/tF6fFG3HGZoU29E9tafupzxoVR7+r6mFHkifxqDttJf6XaF/MTFB17a6r8T8n3IRzqUe173uS6VoeAL2cH6LO+FLxMpBzUxOejCkpozH0wrHl2WAxLp7hFpvMdaX4qfnRzM9VsxGRJZxd8RX+k+kgz+29MyV1pkEGdLVuV+7WftSLgln4pgiwa7j4RXE06qOlpu6LfssuTaflWaZZeE2WqSy7ZoCzDxmZZI3H25ok0tor2GW7gfl2jNemPaPUfT7r614qabbipuvPHGKJHGBuJ73/teIRsnkPC99tqrOOmkk2x9o16f1gVsV/ary4ul4MxNU5xI60BTmgDffPPNlZYam/SPfvSjliSHUoNBq6g1hKgHxADf6Xre8573FAcccEDta+D76gqJ00GmfG00FiSYf9d9RpEBTej0c+u+l7kPWkMd/EkTtJhJbix3PJ6RUkbjEZsLcJiiNf5yL8bxwgsv7PN/D2UL0Cnx9HOBvT5UOPPMM61GMESkYynyIEu5bgN+W1LmX79/2k/cJ9IpJvuaVDdpknOJdChNYIxMx+QgBZ9JLzPKfDDpfZf2d1kOSKRJpHtEerYKAOZop/tUgccUsXYXRIvcK2et8cpgXKLFrQKPmfJV2qsyQJfU30/s8W1JvhWHjhlL98WrKcmyI8+9maqP+No4YY5MOys0V0601M6cuzTrRovKAs5aHPf1PjOz7kAB6a9WrlhJ0269OKQSaWyujjrqKPsXn/Xr11uNzRlnnFE8+MEPtpuvUa5Py4K1mP3o8mIpuHPTFCfSPokSralv1nzRRRcVt99++4BIiy8zLmgyFqqnyZdZNjiaeMCkGGblOn+x3wA857jjjquNDD6KDPhmyfLsJiIbCgAW87WWepsIek4ZH6PYXBDSSKMO32Q+N5icxl7q8n2xJc1eKIhdXYo83b+UiN0oP6wc1AX3ygn61ZR6UfqSYtotGml9SKPfl5jFQ0wOFnO92lXPHlYOdlX7dsVzuiwHJNLdJNJ4r7Rvck8ORHvcI7K9AGOWOduPjdRtI3DbX6z5tq0Tf0ofZ4nmLdZ1uHdB+UML6Xb+zP2+0vLe9z3blmv69Gucdckege5pxLUWekaidZdpriQ6t7vPdsx+ZhDxu/p5topWjijk+DBqd2B8Uoi0T5qlmvPOO89GTn3MYx7TR6pzrws5j0gQL0cQ6PJiKdCkbpr+Z+P24uNfu2uiZOrn9l9enHzUXtE2x+RAFpSYWbMm0uIzK4RSp0dqqqeOSEswMU0KJA0brmki7ZuaAwC059hjjw1ikSoD/s06grPW9MVIse6/mKFrM2loNUP+2Hh+HXHXbUsp4/clJgMo75ts6U1HeIF239aVk3vktFub38t3/sZGP6cp9ZqUiz1b1zesHGjTavjN46PlVLsa1L2MMZnBfaEy/sFKLLBZrC0pchCdUCa8wLByMOHd7mt+l+WARJpEGi+DloOd0NJqn2Sbqsr5OQ8EA6siebsUWHJbpYU2BBs/P2jVShN8Febjyg97CU0iOIDesWOhuH/rA047XabIqrTTpRYaHeztDUpiX/p34x5opJfP0rS7b2hTiPRtt91WXHXVVZX2WSoQIr3vvvuOdL0NIr1t27Zi48aNxUEHHWT/XblyZbFixYpOfQfh37x5szWlxb/oPzYR/nfr750p/vYbm4vdd9+92Lp1q33x8TLh56X63cP2XV489ee2Rvu22267JY35t3+yszjtQ+uX0DQXb8oTH7GyOP/ZM1EZT5GDvffe274j+uNv4jWBg0/w/vvv36eBhn80TFf9hUPXg3kD8od777zTRHs0sobn4i+0bbBowQfE+IlPfGKBuQRy+IMf/KAyM7/kkkusLMPyRUd2xs8hGYcMxN79++67r9iyZUv1fI0DTLHXrVtXPOQhD7EL5JVXXmn9VIXQ6/nlrrvusn3zDxNQH8pffvnlturPfe5zVeC00047zWrdoanVpO3pT396n+ziXVy1alVfmd/8zd+073RsrgPOoXe/S9+lyIH/1vl+4pADrClaewx3BYyNyMGDHvSggXdAHzi9613vsm5Q2oT8He94R/GoRz1q4CAlZPngH6Rok/B3vvOdBd7lujWPcrC5SJGDad8zdFkO8P5iru/inlDWQewJN2zYULsnnNZ1Af3COos9CORA9iptEWkx4959t1Wm7lJlG9/KLWqJ+fmF4r77tprM0c7cu5lIo6m9QGkk0jVDl0KkJ0Ejff/99xc//vGPi8c+9rHFT37ykwKbGyyg/ncrVu1W3PivPy0e9rCHWfN0TK7YrGLDtFS/22/vVcXuO9bE+2bIBjQn2KDdcccdtl/Awf/ue2vnild8bMuivsy5Dz/i4cuLNz/9vmjf9txzzyQ5AAYv+/DG3GYsavkjf26FxSAq4xE5gNyD5GGRxUIgGhu9YUeqIwkABrL8xje+sdhnn336iPT73ve+imxKCiMApOt57Wtfa58jn3vvvdfKpfaBhnkqiCUINN5HId7aHxUyjTZrogHiGZJxkJzQu6+/w/NDvtvwvcbJ7f/8z/9YnKHJ8TVaofkFOOoo0+jvAw88UGBe2mOPPexiLh98h7L6IAPPwbP1fAVZBkmSD+q75557on1D+4B56N3v0ncpchA6ABF/f4wJDnse+chH9sn0ySefbNcKkQOQZMQZkQjzMl7iH41yKK+JNA6hDjnkEDtGOnUa7oUvNN4JyPvdd99dQA78MnJI81//9V+N8wHl4A576BGbD5r2DNNwb5fl4Od//uftfqhuTzgN4xvrGzCAjNftCad1XZD9PfbAwMAR6eFNu8UMG2be1pzb/LvH7jhInQwSLWvTvGn7Pffcb7XSjkxrc279MyJ4lz7k4NPIIw2NtDmgYPorRQdSiDSKj+oDHbt/VzGUu+5fKP7PW360qx7XynOe9MhVxUdefnC0rlTzrW/+9wPFS65YF61vKRWANvaK0x4SbVKqGd+/3L61eOEHfhatbykVaEsOQv6x2qwZGjc5vfXNXLVGGIEHfW20X89DH/rQRj/qUDAm8aEVIh8y7W4KYpYqA0tpbNtuS+pc0PZzl1J9lIN4vISlNF7jagvloNtyQNPubpp2h6N2Dx9sTEy/LYE2fxbmdxYrV60oVq1YPq6pa6z1bn1gmzns317MzOq80uLyVea7tpbd7uDBRvI2/yL9FYm0NzR1RFpSWUkwsVGjcsfuH6vEqMpJpIuCRLooukykMSFqjbB+92DWDM0oJkwJEiVkWspBYybR+5vqAZkLBTY77LDDgibVUv+nP/1p+yNIuibmch3+yzC7rotwyY1ztzfOIieUA8oBZIFy0G05IJEmkW4j/ZUQaZuC05hHz++cL/bcY/di1uynJvGDA4G77rm3mF1mXDuNRl3HTJH0V5J3ukyCbcus2bDR7Q0NEDqq9yRi0FqbU4k0HjhqnujY/a11qqEiEmkSaYhHl4m0BPryXxNMi9AG6+nRj7iMeyRqct0GRdfjlwmZQPvtECIfqt8uYmYBaCuP9K6YcxbjGdRIk0BB7igHlIOuywGJdB6R7vnMukBTVUTqwELmUiq5ctgXyEd/bwN4mTL6etOaKPfiHlnnq1zPZcRpfb/sCfzv/GegvpkZFQiszBddmXorVujiXrs80RKATNoPc24EHcM+ZfU+8eCvi7H+pz5z85a7LClGBG8dfMzmni5DeZf66mpfCI30ipUrSKRTQYY5tmieUu9Z6uVIpEmku06k0X99+oifQ4uRvyjqE1m5llKPlKmiYtp0C+E0D6GozNr3uIlAS5uogSKBgixQDigHlAM3K3b5QIVEOp1Ihw7OIT9yuK339z6ucsBeV0fooN7nC033Yu2vi4jtp20M6UqXGbLYF8ekItKgyy5Hsnzs/cZvuO87pL8y/80vzNvvgcm+q3sxTJY69wm1b9PmOx2RNgciszhkcFm6qo/Fy/Tb7RHd1+s3binmVsySSKcMOLTH+Ej6j5R7JqEMiTSJNOS0yxrpSXhPR2kjCVS3N84iO5QDygGJdB6R1ppE3OlrI7W2UMiKLuO0fvWmrk0Htnie//xQG3qRl93OPna4SiKdRqQldoof2BAYw+VLH8aIVZsO1ojMGwgaKuPju4Qh1glctUBAQ5+m54s7WZ27F1JnvvCFL6xkIUqkFYm2bbGipPI82+v2q166R8ujzR9DLF1Q0gVDpCdbI71p8102UJo9wDAHBzb1l2S8grLD9FlyTOMgAp+16zcWy41fOE27R9mlTvi9JNIk0iTSE/4SR5pPAkUCRQKVR6CmeUbgfJA2H9QRzpgrD2RHyoQCWfqyJWX975vuFfKFMr41E0hTHTkTcp6T2zcUl6MuX7vOLw+y97rXva7qls4BL18ivsfBB9cHjg3d4wfk9AmqxhGEEqkq/Y+vsfWvCzEWEi3P1Gn/LrvssoqognghErqkr0R9mkhLUFIQcHzkd8mI4BNdkb1Q+j9pK/pwyy232LSY0k9N5N/whjcUiL8S9tx1VnCQA4m8LeVAHuVnkGdt0o1nWzNn8weaaJF1Y9ldIOXu/vvtM9FT5wajXUZEf3BkeUegmYbpuiXV5qNNvPE7onbbe+gjPdFjP1LjSaRJpCFA1EiP9Bot6Zu5cU7bOGMQ3/uFu8zfO5f0ePqNe8XRexevODquCaAcpMvBRAlAZmMpB3E5ECJTRyJBUERbHNJYgmgeeuihVrMl2RbqhgnBJH0tspDo0POhyQSJk+f7RBLkDG6IdWQ6RyOtnw8SqIltiAQL8UNfNZH277v11lur9HhNZBp9ExKrSXodQcZzdbm6umNE2g9AinSXRxxxhMVc+giifOyxxzozYENIdd/RDrkuhx0SywTvn8a1bvw/97nPWYyk/+JbLRYPIdNupCcUMp9KpIUcV4Rb+0aDSVvf7N6XFck2hFpiyEAbDXnbf98JJ9KbjJm2eWehlZaDBiHQ+v116bFg4j1TrFnHYGOZS9D0FSeRJpEmkZ6+91r3iBvn+MZZ8CKRnu53ocu+sTKynA/i84FPdnwSeckll1hNqpBk0dDq3OggSHWm3VJOTHR9Io3nS5m6lIggaEKihVgKqa+rFzKQQ6RDGlHddq1x1n33ibRul9zTpG2tm4VS7pFnNZHtGJEGtpqUgkgffvjhljD7GOM76Tue+ZWvfKXYvHlzRaT7CZgj3VIehyIf/OAHB7TGIHPnn39+8fWvf73SNut66iwetAYd99cFRrMuz+UBgDbX7tdGg0Tjqc4fuIrpgt/xB4FOjaYW10Cid8wbIr16won0ZkOkZ+fKDC1wCy+jd5s+W610Gc/GhbRxPuJr1jH91XTvGhJ6RyJNIk0infCiTHCRnI3zTzfvKK7517snqrcPXT1XnPjEPRvbnEqgSKQnauizG5sqBzHf2BBBCm1adTntQ1vXcCmPsmiDH6U3dJ+0NeZvSyLdQy8mB5gzNWmDv6kmQCCqIC3i/yzjdf3111eaVhBp0SLKk1GH1s5ec801A5pjXxsKEi/16ACXn//85/ueZVPxKI3ke97znuKAAw4YEJlRibQ2b8ZBAj5iUgzSj1SMIIBaIy2E/2Uve1kVZ0iTSamn6YX2teOhstIOENSmOmNE2tcyS33adFr6J9/J71pjfdxxx1UkWerUGnPRWvt9gfyFLB1QTtoSSqepDzAkINqgaXcvD7I1X1b+0fB3lk/P5Nt9I2Rarrv5DrG3XNYQtGcaNNLAHmPlSLQ7cNAfiQtrXaYNXus2OC02Tbuzl+PpuYFEmkQa0kzT7ul5p0OLcmrvplUOYhtnwYdEuihwmPLTTeEAOKlytKvLPXTfuQIHKrFPihy04RuLdtTV0+TDWnfoVXdPXaTgJhxSD9ZSfGNDm33fnDalHr+9vnZTrvtaxlC5Ov9d/YwmORD/WE2kX/CCF9io976PrH/gojXEuEd/fHIGUgnT4JB/rJDkkDZaDlfE9BfPAGnHR2up60haDpHW+GJc8RHTYSF0Qgzld19jrYmjJtIhQu7Lgb4X12IEWcYsJgMxIo1nScRs32QbY3L77bfbgwKMMfDQ7ZLy6Ovxxx9vD0pCJBqyfMoppwR9mH0iLbhJ3WLeL2MuuOnxwkEKDjUGP4pIz5U+0lKo1DzjV0ektb+0840G1ZZDO5h82+jjxl8aWvL9Jjxq90YTtRvvEPyi3aGmCxZoNdGm36KVrjA1fV+3YbOZG+gjHVt7p/o6iTSJNAR8WgkU+payeZ7mlzx14zzNcpAqAyTSRfGeGzcXl/zj5ol6JV759NXF/z1mdbTNMTlI8Y2VIDR1JFI2r9iI+0QADcRG/IILLhjIIyvPrguw5N8j5fXm+eKLLy4OPPDARhxS5oMU31h5bsisWYIqpdQTamyd+bAu65s+p2gs5f6YHGjTatwTIpHwU9ZaaqlbEyjdXtSpNbdieuv3H3VeeeWVxbXXXhscR7QFY6y1z6IN1bLQBpFGA/zDCiGSQh6F3MkBSptEWgOgtcGakEsZGf/Q4YMPZAqRrnxkvdSU+oAF9daNk7zrGGeMqX+g4B+iSNA4EFPMHUi1K4Rd0u5qKwR510VjKtYs0j7IxGtf+9oBGZK0TXb+UERam3XbwxqJ1G1q8A97rCYa+aOhlTZ/FoyPtNVIT0GwMauRho80koBBM43o3SoFlsYC3681pt0rV66kRjq6+k5xARJpEulpJlAk0nn5g6f1QCW2cZYpnkS620Q6xTf2oQ99aEUuQiTy6quvtuKkiY6Ua9JYiia0KcCS1nJqYiby2xaRzvGNlWfrAwDp7zD1aPLmR37WWzHfF1Y/X4h83dYtNh+EDimEGIHc+AG/5Dm+xlC0xxI8TMYfPrdPeMITgs3zA5QBg3POOafymcVN0DY+7GEPGzioEZKLMm0Rab+R+gDjec97no0a3fTBWLRh2q3lwtdMa5Ia00ajnhQi7UiUM+sVkhsLtoayuq/QSOOjI3rLQYu0A23xD7dA1sT/Xg7e0AbfdQDtq3yXy1RrwxJpl/LKfWyd5b/yu9NGOw20azt+7mFpg41NAZF2wcZmS000LIt60bqBAbTS8sGYrGPU7sb3vxMXSaRJpCHo00qg0LfYpkle9Nvu2F6c/w+TpYl73EEritc9oznAR4oGSjCYVjlIlQESaRLpmG/s2WefbTfW4hONzaykocF7hGi5iPCLyMRCMuALi3uE/D3zmc+0Zp3+x09LhLp9E2PcE0q3g+/HSaRjprhaYyjayRCRjtWDfqRopLUGGuTpE5/4hNXgNQWZErxT5gMx7dVjpEkkfsZHyAz+1YTptNNOK+AjKwck+l5fG621kajnwx/+sNV0ahPetWvXVmbVfo5iaaMmlBK12ZexHNPu0CY4RIp1uVBgsbaCjdX5VTcFZgv1IYVIh9ZN6bsEc8O4VWmjSiIrZULpr5oCx+lDmMsvv9zKlY+1JsmYh8S8X2RevxM4rEHk+P5Pr72+RrqPSNtf3ByHj+2jyiMt1yypNN8javc0aaQRtRsaefhJu8MUROh2eaTdEYP74BrySK+gaXfoNevOdyTSJNKQ9mklUOhbyqYJ5b753w8UL7li3US9/E98xMriitNCflC9bpBIp8sAiXR3iXSOb6xsMOUeTSKhLTzooIP6/FWxgdbau1DKG7yxUp+8vXpjDE03/BBDvrZIk4NPW0Q6xTfWnyj1Jl8iMw9TD+oN+T6HUhlp3HFfyOQ3NKHH1oTKL7K06RSi65MklNMHKtoKQac/8iNAa220T9h1fmC0HYcw+E4TaZDkI488stKUSvvq8hxrDEYh0kKIm3yVQ6S5Kf2VWA/UyYqQT12Hf1gSI/e+DKQS6ZAc4tkIPudHWhdcfRnR4xaSRcwFOn1WLL2ZkHjUhfuaUrRhvuj/KCJtyGKlce/LHe2idYsJOPop2mjU5TTgvSjektZr+/bxaqTvuW9rsdb4Iz/64QeNbY+GPNLLl8+VJt2lb7SN1N2zSgCPxgGCYLdug4naPbecpt1jG5UJqJhEenoJFMQvlUSRSE+vHKTKAORlWuUgtnGWqZpEurtEWubLGPmDb6zdXJrdFUgQPppEgkhgsynvnQ5WJAREIur6WwSr4VCaR1yXeyRnK54pbQRxRE5jCQAFEg//2cFIvb0npc4HMd9Y3XbpY0jjllNPaMuk79dmu9ondtOmTTblED5N5uBSf2w+ENNO3R5NIiWPs6QoknZpv3k5+AgFKdMkzPfHFrNtn5Bqbaz4Z+v2aaIJuTjmmGOCO9AcIu0fVKDCmA9yiEjjvpDvvz4c8d87pBcL3eOT6BRzax+IFCIdkgHUI6mn/Dr9QzD9vjZRAcwFMo/48hmyipDnN40jygySaNSeSqQHg4y5VFdOLe1Mv82f0k8az9ph/o4rajdI9CvefIkh0luK5//e04pTTjy6CdKhr21AHmkEGxPTbvhH4489UHOaaGiptVbaBhsjkR4a86m4kUR6egkUBDR10zStBAoYxDZN8iJTI00iTSLdbSKd6hsrAYEwd2gSKSa7vnYK5A4pgeSTmprID7AEn0vxkxTCqM15JRBVeBPtnp66JvgbnDrz2ZAmumlzlGuGqzGu6zNIl8Yq5icbWxNAYLQ/qvQHJPLCCy+0kZiF5ISCzklaKyFXmlzKQYvU6RNpWBWgPzpnsZTFoQoOEEAEtRZT442+43DF15hKmRwiPRWb3EAnUoi0JU1lxGY5mBJ/5DpcJM+wLiffhe7R5UTD6Y+bTonnPz9Ud585tvdQ0TLbvimNtO8f7Ufrlmq0NtoSa4nabUy7bR7pfdvLI33DV262UcOPOuIXivd94rrihq/eYpux+26rigv/36n23xu/emtxzFMPKw7cPx5oMkWWHZGGj3SpjUbUbsklrQKOoS4x67fprwzxZvqrFISntAyJNIk0RJtEenrlIGfjPK1yENs4y/ROIt1tIg05SPGNDWmiEVlXNrG4LtpKCRaFjZcm3X/xF39RmeZqDbJsqNEWHRVaNNN1+WVFhqGx81Mv6TuACWIAACAASURBVO1Lznyg7wuZz+aSaNSXa4aLe3wtZ11gsdS6Y/NBnTZSE7C6MjYdkNHOyZhqvENpzHx5E41jqH5dd0hOgVWdxlTGkkQ6LdjYpG/5Q1YpMSLtUl5ZmtgLYlYGGcO3QqTxs5h0u/RXzkf6wfu1Q2hBoi+8/JqkIThg/32Kj174p0llY4XWb0Qqq+Um/ZUj0jrgXOUnbdFxgddQZo2J2g1zcBLpGLpTfJ1EenoJFMQ2ddM0rQQKGMQ2TfJ6UyM9vQcqqTJAIt1tIp3iGwutsA4CJlpS0RZhgwmSo6NKw6dS+zOGfExBgMTXVTatISLtb0d801aYdretkQ75xmpT3FiUbGlzrJ6YH7T4QGstfCjQUqgejVvKfOBr+0LaSF1GNFQhTXCdtlGT2x5R6QUzkvrr6taHLkJuYttVEumuEumeuTZkJKSRFiIthBu/90frLuuAD7Uy614w5dok0l+7+T+K8979iZgo2+uPOuTA4n1ve2VS2VghIdIzhiBr8+6ext6R5x6RnjFEeiOJdAzYab9OIk0iDRknkZ5eOUg9TJlmOUjZOKP/JNLdJtIx31iJpttEIiUgmGikIVdCNHXUXwTk0vVccskldpMGf+e6AEuI9K3JNkjRzTffXEUHb8tHOsU3Vvt++/skMa1OqSfkGxuq2zfXDuXoRjtiJDrncHUa938k0iTS0DpjHsF8p/NHh4i0H61b/KNt0C1zaIg0WPML860SafhEP+eMP69ev0Mf94jiBaVf9O3/c0fxkc98objv/gfs9ROPeXLxipNPaOVV7Wmkkf7KaaSthh6K+tJPWqJ3i+Z+rU1/xWBjrQzApFZCIj29BAoymUqiSKSnVw5SZYBEmkQaMvCeGzcXl/zjZKWBe+XTVxf/95i4WWHsQCXmG9vkmyp7AImojE1YKOqvRN3V2mbcCyKNHNV1AZbqIgXrNFttRe2e1P1MartjcpBazySWI5EmkW4m0v2BxjSR1qbhEq1eiLTNI92CjzRItPaJBom+8PUv6XvVvn3bD4uz/+IK+x18pd/y6ucVT3j8I0d+Ha2PNPJIzzgirf3TUXkVvdvGXHNO045Ir6Bp98joT3AFJNLTS6BIpN2Lmbppomn39FompMoANdLdJtIpvrGxg6lYVF3xsw2lPfJNdWVrUef36pOimH9szpowwduaaNNT54NoRRNYgESaRFoT6dxAYyLylY+0+cJG7W4h/ZWOzi3PucAEFguR5LPefnnxne//qHoDX37S8cVzjjtqpDcS6a/mjL+z09T3gs1JpToNlnUnN19YIr2SRHok4Cf9ZhJpEmnIMDXS0ysHsY2/nsOmVQ5SN84k0t0m0k7rIOlO3JsR8o2tI7yxqLr+daknFL1X3sthIgU37Uty5oNJ39/UtT91PpjG/pNIk0gPR6TdXCimzuMg0rf/7x0mzdWlfa9dKpF+8uGPL857zckjvbK1RFqZdztFtNPak0iPBPf03EwiPb0EClKaummaVgIFDFI3TdRIT++BSqoMkEiTSE/P6h7uSeqaMM04pM4H04gBiTSJdC2RLu245fAuFGjMRqs2f8ZBpPG+Xf35m/p8oEOaZl9zDfPvs176nJHTYNURaelzL590L+DYujLSN6N2T+NsmdgnEmkSaWqk3ctCIk0iTSJNIp24dE5sMRLp9MPViR3khoaTSOcR6b+7+d7ip5t3TJQoPPdX9yj238MEylIf7d/cHpHeWSCfNEh1G6bd0twmH+gUH+phB0uItE17ZfNHO/PufiLtapdDBhLpYdGeovtIpKeXQEFMUzdN1EhPrxykysA0H6ikaqBIpEmkp2h5D3YlZz6YVixS54Np7H8ukQaJ/OmmySKSD913rnjo6rna4dP5wGNjfOpl64p//ZGLED0pn6vOOKB4/EHLs4h0auqrfo30eIj0mg2bi1POekdf+w8tg4mtNdfWbthSXTvmKYcVZ7/091sZmmGJtI13YQDsJa5rpTmsZFIQIJGeXgJFIu3ewtRNEzXS1EiTSJNIT8raPWw7SaTT14RhMV7K9+US6WmM4k8i3Ut/JcHGcog07kF5ROweh0Ya5t3v++T1Sa8RonZfc+kbksrGCoWItDXntv+52BniG2010st22mBjmFNJpGPoTvF1EmkSaYg3NdLTKwc5G+dplYPUwxQSaRLpKV7ubddy5oNpxaLL8wGJdJ5pNzXSRgdtda2OROLPuIk0NNKIyo3PsU/9/9m7/yA5ruuw9xf7GwAJECBhgapI1g8XtU5CSaTNJIKcMKYJvXosVhzrVUUFR5YdWjYo0JV/DFc5Vc/hY1yVOBGSP15ZkCHTikX/QJFVsZ0qPf5hqORiIsM/yJJtOWFgukQzEk0usPhJgwSw3F28e87t293T27Nze3d2d/r0dygIi5meme6eM7396XPuufe63/rd0/m80XKfNBa7xQP61O//qfvkD36/+1Q2x/R6j1eDIe3LvH0puzakBNLr3d12ng+k7QKqyUmTVUCRkW524mw1Drp84hx/W6UCymIGKu6D1Diw8xt+5ZakxoHlfZAaBxYvrAFpIF03RnqUMtLVY095zHTdvNLDOlaVIS1QjnNJFxnpEqQ9piUbf86jn4z0sD6Blr4OkAbSZKTDl5fSbruVCV0+cQbSxS/n1Dho6a/zpNVOhbRcVPvjl68lveaoLPT33rfd/b33zwxcndQ4ANI2K1Qo7R7t0u66L/BTv/1VJ9NjSfb5/e++c+B3fC0LDIJ0nPsrTpEYIT01yTzSa9nfZp4DpO0Ciox0+JqmnjQBaSBt8cQZSDeHtDRYev3ycqt+z99529iqDZaIg+ZxYPF4QEaajPR6M9LF9FcbM0Z6qw68dZAud+3uB+nJCcZIb9VnNhLvC6SBNBlpMtLxYERp9xvu81+9MhLH5tSV+MwDu91nHtg1cPHUTCSl3c7HAHFAHNiMAyBtH9LPPLbffWB/b9fyNk1/NfCX2QYtsDqk43Rifh5taUDmbzJeXEq7yUhv0AfSlpcF0kAaSANpIB32AICyWcoZ4zu1OoU4IA6sHg+AdDchHZuF6bFQulB7DI6Pj2vjsHjTRmKxqZiXd5wrudpsrMhIL+szlpaWhjqPdNlP/SaVipgdprV6IR3mkC4y0iVIj/kdqD3Xbrp5PxUXY6SH+Sm08LWANJAG0kAaSAPpGANkIrmgIrFAHNiMAyANpPtCWtLW2RRPmnEtpbHlx9iQTBAp48zlz1ohvVmzLjcBdz9Iy/7yfcVCt25JRsu/5UKD/8fZcxfd1BRjpFvI3+GtMpAG0kAaSANpIA2ki9+rZKSBNBnp8H2weEHFerOxutLupIz0qpCWabCKY2QTSG8WmlNl1A/XfSGtFxX0GkMo6wbSqbu6G8sBaSANpIE0kAbSQBpIl896LAIqbl+XS/zJSJORLmektXw7E3LIOFf+Haq9wxzSFUjLfcvLN93Ssi/tXlx0d+y9Tb9iowbnQZqLsD5/8bKbmJhwY9ukpFuyzzIFlpR0h32SQ1q20f9HRnrQnu3I40AaSANpIA2kgTSQBtJAuvfEz2JlApAG0qtDOmRfcxCXIJ2Pnw4DhLPy7gBpuTgVId1WPgmkZbxzhLQiWhPQveOjb/qLB3K/LDd37oIv7aZrd1s/86GsN5AG0kAaSANpIA2kgTSQBtLVE0uLlQmdL+32H/LYeGikFcRcgrNmn4t/1zUcC2OGJRu9rI3Glv0T1gfp0AW7ehuU2e4//rmUOm8gpQhpWRtpxCb7Z5s2Fovr57PQpUZjsm/OzssYaSDdYDfbWxRIA2kgDaSBNJAG0kAaSANpIN27Bx558px74ZUbrTr5rx8jXQBZNmY1SNd17lZvl8q78zHS/r4lD+p0SBdoHgTl9e70XmgPxnWRkS7KumNpt1xtiOOjY8dugbRMfzU5OeG2+Y0Z/A7r3SKeP5J7AEgDaSANpIE0kAbSQBpIA2kg3V1IRyz379wdxknr2GhpY52Vdy8tLbvFpUV3+57dNc7J5lweEWYWuF7J3guXrrjxsXGfjc6y9Vn5tlxYqGs0JtsvkJ7w2WsgPZLE3ZyVAtJAGkgDaSANpIE0kAbSQBpI24V0uXN3OSM9qOGYzhvt4VydT1ogKaXd+sdnpffetivbeWvAc311d3MINUgLV1F98fIbftxzmF9b59jW8dHZfFdZRloy1LIv9LlAuvnnY/EZQBpIA2kgDaSBNJAG0kAaSANpG5CevXOypnt20ZF7dUgXZeBSwh3HSceMdT6ntL9Dx0j7ZRYXl9xtu28NwBx0q1lkWIXRte+fgGt5/8tX/ibPRiuk/S2+Xvl1pWO3ZK7lOefOX/QZaUq7B33kph8H0kAaSANpIA2kgTSQBtJAGkh3BNI+szo+ETCotxI2BYqSixUgRzxnd+VZaXlMl9OstEB60W3fPuOmfeOtFbcKnIeF5lScrcB1DayvLyy469duZNno2K1bpr+SfZRloHU3hbHS+p//++z8BTc5QbOx1M/C5HJAGkgDaSANpIE0kAbSQBpIA2nLkC4yzToNWj9IS1MxQWNpfune7t0y9VWB7di9WzC9x5d3593AM0CnwDmUUK99DuqI5bDmq99yWGeLyvpf8mXdOoe03y/xj7BZfg5zSAc4x7LuuL7nfNdumTKLMdKD9rrhx4E0kAbSQBpIA2kgDaSBNJAG0t2EdHmctGaiK9NglfeK+FogrV285T//cyzxFpvu3rUzB2gdn9aL5lSSDcK1wthv6+UrV3VsdAS0THEVM87hokAmbt0nWfdumUra//vsOZn+agpIp34oFpcD0kAaSANpIA2kgTSQBtJAGkjbhnRsOLYiIy2bnXXk1h9Fy16KK7PScRosmUc6AFM7ePubYFqy0lLqfcvOHR6YIcMrtzLUm1iqXzY7aSx25Y3kOTFjLc3RFhbedm++eU3HRUs2WsZFy/uNbQvrPCagzn6WfPnNbUW2Wy8G6Bhp37Wb6a+afKT2lgXSQBpIA2kgDaSBNJAG0kAaSNuBdA7ink0KOFZIZ52pcyxnMC4gXZSClxuMxcf1vixbG8u75bU0Oy3Zav96OpY6e924bD4sW+elri/FTinRjkCvk1ksxdZlshLzmAmXjLNsv/6ddemW5WV/5M3F8imvQmm3vo5fPman9SX93WeltNuPC6e0256Pk7cISANpIA2kgTSQBtJAGkgDaSBtHdIBx1VIa8my/6+cgQ7DluW+Igtd7uAdMtGhPDo2HotwFkwLP2PDsrz7dywHV5zq/FIlTK9s590sI52BN5uaSqRbbgwm6xgz5AppvwaK5wzWeke2b3R8tGajwzRX2mRMIZ3BPFxFANLJ2jS8IJAG0kAaSANpIA2kgTSQBtJA2j6ktdA6y8DK1uo457ru3Vl5dyzh1mXjct6UimbNKhf7LGah5Z4A7ALh+fji4FW9rXh+nwz1IIaVS73F0UVmuXifmKUOuA4XE+QWs9NxfeLz9fGb4eKCvl6Gfin59il3vW/unO/aTUZ60Mdj+3EgDaQlwv/4m9fdj37htVYF+33vnXFPPfrOgev89ttvD1xGFnj+5Rvux794LmnZUVnoe98z7b746e9YdXWko2TqzWocpMbA57/6hvv8V6+k7q6RWO4zD+x2n3lg18B1SY2DXzx1yX3uK5cGvt4oLfDYg3vcTx3cM3CViAOnHWZTbsSB88cCe8eDPBOZEgR+GYtxEMuQU3bBI0+ecy+8ciNl0ZFZ5pnH9juZRzrCcOWKFZAOY6ELIPdmpWPpdilTLZlZyUJn46L1+R6b+VRZ2ZRYAcihtFuz2jq+OOvMHUu9s/eO69cD8tI/qlnpXjQXWeyeKax1iHeWQc4yyZqh9usau3Hn5d9q5Jhtln9kcNY19qXd2TZni+jz5XXk5QXSU9M0GxuZ4N+KFQHSdgEl8ZR60mQVULIPUk+egbTdCyqpMWDxxDn+Xkk9Flg8cY77gDhI/51AHABp+d5YjIMuQbofpqWJVnmaqh6saro44LmAdnBwvC+WeCuqNTNdYFyniJLnZ3nn8Fgl860rVrxegdTsaJ2tw+ouChcBem4ZoGMGOT5WlHj3jpnWcu/YUEzhnU15lV8wKKa+Cq8VSrpjV++5c+fd5DRjpLfCryPznkAaSEswAmm7cZAKKMtxAKAAVJOLalxQsQkoLqiUxsYmnoUC6XZnpJMgHdxcNNXyWdiYYc6f77O65ftCzXbMWMfnFuOlQxa35nWyTuB5A684BjnLQOdNxlYOl66P2KxGvDejXKxXnnWO5dnZq+j80C6AX/7rmeZKd0dWyl161zHf3fum70iuSM/eV7t2T/lx1n6DShXuid8uFjOxB4C0XUBJgKYiCkjbjYPUGADSNjNQ8RdVahxYPHEGUMXpCnGQXqVk8YIKpd1h7K40w0q5tb20uz+kBY/jxS7IIZ2VcZfHPYdR1MrL2JQsR3VWsV1krwXTRSY7grMX4RGpNV27s/dNZWle5l2Bd8xAh9UuNqachdfMss4frRufl4Jnm6r7RjL3elFAx0iHbLTP5ecXHebmpbR7GkinfJmsLgOk7QIKSIdvbWo2ktJuu5UJqTFg8cQZSBe/vYmD9IurXFCxeWENSHcP0lVMF9NfTfROP+WxGMGbj5UulXOHJG2RZS5PmxXHQOdjomOGOevSra9XAnZ4btHAqxfOqenoeGwvoFxkoHWr8+yx3u/BHMc75+OnS+XcqmQ/pLvozh06lsfsdXw3KQWXbZHXeF1Ku6cYI23VyEnbBaSBtOVMJJBOP3G2HAcAKj0OAJRNQHFBhQsqsgeANJAuID3e23E7+4rkZdclWOtD+TjnsGDMQoepr4ox0XnjMXGpz/4rorNsbvl5OYNLY7LLY54HZaXLTcdidjngufiul+eTVrdn66mdurPlYpY6jOvOyr0F3lqGHsZUa6m3NPHOpgkLj93Mmo2RkU4Cp9WFgDSQtgwoIJ0OKMtxAKTT4wBIA2k5FhAHNuMASHcT0lXAFnEQO3Jnf8cS7/h3aQxyXp7tH4tTYoWpswpgSqOxOC2WJnhjw7II76yJV08zsxKweruID8pM92acy04rAB3K0mNzMFlGy7mz6axCabcv1s5KuMPjlS7ecR+UMtqx3HvuLKXdVn2cvF1AGkhbBhSQTgeU5TgA0ulxAKBsAiqeFDBGOn24j8WhHkAaSMuxoBwHN7O5knM4ZJnXmH3VhHO5VDvOL+3RHDts5VloX/IsP2+fmXYTE2NufLw0DjtZJhu/oIyRX1xcdteu3+iZR7oo+fb7qFTCrRnorFRcftbO5P7vs/MX3eQEpd0b/4mN8DsAaSBtGVBAOh1QluMASKfHAZAG0mSkw0kbkLZZmdC1ZmORIHlDsA2CdCzj3rljxgPaa7wFtyXfhfutt677gu6Q3c7LvKWSG0i34BMcgVUE0kDaMqCAdDqgLMcBkE6PAyBtE1BkpIsTri4fD8hIk5HuzUivvbQ7lmFLmbeWc/u/b9m5vTWIjkeEJb/uV69e095nWuatXbxDCXh5qqtyszJKu0cAsKOyCkAaSFsGFJBOB5TlOOjyiTOAAlDl8w1KuyntblJua/HCWhcz0uXGXcNoNhaz2wpoadG1dNNNz0y5manJUeFNo/W4fmPBXb++4MbGi3mlQ5m3YDqMmQ6dycPPNBtrtHttLwykgbRlQAFpIN0kBiyWcgJpIA2ke8/junxhjYx0NzPS9ZBe+/RXecduP0h62ZdHL91ccrfestON+4xuG29yQeDK31x149vGPaalo3eWjZYJv/w2STdvHTOujcqY/qqNn/GGrTOQBtJAOny9mEeaeaSBtM0xkfEXaJcBxQUVLqjIHgDS3YN03TRSYTxwqRFY7NItmVdtw118X0Lf6zDvc2xAJs265Cbl3NJ4a3Fx0e25bdeGWWUzXvjipSu+QdqEQjnOJS37KJZxx6mxfPF33nxtbp6u3Zvx2Yz0ewBpu4CSwEst4/vjb153P/qF10Y6Vqsrd997Z9xTj75z4DqnnjwDaSANpIG0HFCIA+LAahwAaSAtsb3NYzE21tKTqBzS8uOYjnmON4W1Hzfcc58HtNh6aXlJ7xdI792ze+D52CgvcOHi5QBpn4Eel4sMWtldTMGluPbbrRnprF35ufOX3MTUhJ+fetCs16O85azbuvYAkAbSEkBA2m4cpF5MsRwHqRdTABSAsgqoeKKQejywODY27oMuHw+ANJBeAekSovU7otnokH0u5nUusB0z1pqn9rAUREv367172p2RvnDxijZKE0wLmnVctFra/yRzSPtt1fHSfrqwsA+3ublz593kNNNfrQuibX8ykLYLKInN1JMmIG03DlJjAEiTiZQYAFDEAXEQzuwsXlgD0t2CdH2eNIz/laZzBZSLRlrFnNFi6qKkOxjbY9L/J5louUmJt6/sdgsLC+6O229rNYnmfXZ5asqj2A/zjg35xvyY6by0OxsjrYzWrt7OQ7olpd1PPPFE0ofz+OOPJy3HQsUeANJ2AQWkQ5ynZh8o7bZbmZAaAxZPnOPRPvWCCpC2CSjioDjv6fLxAEgD6dCJOkA64jgHd3lstJQv++Vkeqt4y5HtJamI9stINlqy0nfsbTmkL/gybZ+Nlqx0vn9i9lky0lk5tzRUu+nL2UNG+oKbFHy3qbT72Wefdbfddps7cOBA/sGeOHHC3X///W52dhYjN9wDQBpIS8iQkbYbB6mAshwHXT5xBlAAqnxakHo84IKKzQsqQBpI65BnGQcskM7KumMTsSIbLYiWI4cA0idgszLvUO4cSr6lyZg8JoheXPKQ3tNySF/0kB6fCKXdMqe0pKbDZFfF1FfatVv2iU/D+20/O3+xfZCW7HQ183zmzBn35S9/2R09erQhI1kcSNsFFBlpMtJNYgBI2zxxBtJAGkj3nut1+cIakO46pENmtQppzUxXM8+K7PDdiZiO3ySdP9o/JpiWn+U7ZSEjLRcaZd9o524ZD62YVk+Hv7I5pVXRliA9Pz/vjh8/vgLYMHnwHgDSQNoyoGTbUk+aKO22W5mQGgOUdjNGWo4ZxAFxYDUOgHR3IN1vfHQO6YlsjHSkQpZ5DnAOZd3lDHVsvqXZaI9nKfnW0m4/XlrKvG9vedfu875rt2TppWN3mB5MSuDjnNLhooE2Houq9tveyoz0yZMn9SM/dOhQrkS574033nCHDx8eLEeW6NkDQBpIA+nwlQDSQBpAASirgIq/+CntTr+4avF4AKS7DemYYdY4KEFakZw9qNNc9WSjSwOnFdmyDwOmpcx72Y+R1oy0gWZjmpGWMdIyCZjfRwpnnQYru7jgf4zTX2mzsbMX3PTMTLvGSMsvAxkn/fzzz+cg3L9/P4he4wUCIG0XUBISqSdNjJG2GwepMWD5ggoZ6fRjAWNjyUjLsYA4sBkHQBpIy/e7Cukw5VW46Xjo7O/47zg2Ov47ZKOLfanNxgxAOjQbG88QnU19Feq5s2ruYh5pQfbZtnTtXqMReVrCHgDSdgEFpMMXIBVRZKTJSFvMQMVfA6kXVACUTUARB8UJUervBIvHAyDdZUgXWedVIZ1NeaWZ6QjqMAtWlrWWTt6+tDtruCVduzczI/1nZ/7KfePMK+6Ds+9xH5p9b4J00haR6a/k96R07ZZtDeOkZYy0n/Irm0c63h/L42Ue6amp6fZlpOt2SV0TsrRd1+2lgDSQlm8AGWm7cZAKKMtx0OUTZwAFoMpnOanHAy6o2LygAqSBtBwPpHxZYkFu5bLuYl7pcNQQMFez0eUu3mGstEB6czLSn/+NZ91vn/qD/JD2se+7xx399MeHArkA6YnQbCwr6w5Thfn/z6a/iuOjJRstt7PzfvqryRZOf1Uu6457j/LutcURkLYLKImI1JMmIG03DlJjAEjbPHEG0kAaSPeeH3X5whqQ7gakP7B/ogYFpYx0IqTjtFhhqquQlg6l3/6/bJy0QnoT5pGe89D91NH/tGK7Pv9vjrj3v/vOtSGo9Kx5P4/0pC/tziHt8eznvdJx0j7lrEuGKbGKWyshHTPP0qn7K1/5ijYdk+mvXn75ZffQQw+te0d27QWAtF1AAenwbU49aaK0225lQmoMWCzlBNJAGkgD6bgHgHR3IR0bjSkIS5Cujo+uduvOKr2zuaRDeXcs6xZES8fuRf9no6e/kpLun/mFL65g2md/9pGhlHgLpCeka3c2RlrKuH3LsdBwLPpZm5lnc2H5NdGu3b4cfJvfKb0t2UZYk+US7hMnTuRNxijtXtuHBqSBtEQOGWm7cUBGOv1iCpCmyZQcD4kD4sBqHABpIL0qpDM1a9a5QsNwX7BGLOnW6a9kjPTi227f7XvWBpHEZ1XLuuVpO7ZPu1/6+cfc/jvW/97nznsUT4Qx0mH6qzhGWkq7i5WMpfDabEwgPdUySAue77//fjc7O+vk549/PNTGM490YiRWFgPSdgElH3UqooC03ThIjQHLF1TISKcfCxgbC6TlWEAc2IwDIN1VSBdl3f0gXR0fHcu6tYy7VNatTceysm7JRi/7x+R37LAgLSXcp772p+6WHTPuoB8Dfdb/+9iTv+Ven7/kPv6xA+53v/Z1d+7CFUX0z/zE/+U+eu93rw1AlWcppGX6Kw/kIistGxvHSId5pP0I6nxO6Tnt2t2yMdKy3VLWvW/fPv1bAC23gwcPugMHDgxlZ6a8iJSTP/300/mid911V8/c1tXHH3/88Z6XLU/htZXju4G0XUAB6fCVS0UUpd12KxNSY4BMJICSYwZxQBxYjQMgDaS1ZDnD4mqNxvpBWifHyqa+0vmk/fjphYWFoUC6Wr6902P6zbeuu4/cM6toFlzL7aq/L/6cYraUZQTSU1NTOg56zI+Plu9KGBUupd1yIcIQpFN2yEYvI6Xkn/jEJzQzLrfyvyOijxw5ouAXNL/44ovu6NGjumz135JZ37VrVw/EN3r94+sDaSAtsUBG2m4ckJFOv5gCoACUVUDF3/mpJIzhrgAAIABJREFUxwMy0jYvqABpIL06pIvMtWahK9NelRuN6VhpD+mlZT9GekjNxo7+u19x3/iLV3oI9EMHP+I+8883vgeWjpGWeaTHZB7p2GRMGd0D6W2+AZlcTJCLESEjbWT6q82Cp7xPzIRHKMt9x44dcw8//LDC+uTJk7o60ggt3uRxyZjLn/LP/V5vs7YHSNsFlMRQ6kkTkLYbB6kxYPmCChnp9GMBgLIJKCBdnFV1+XgApIF0I0hnX5vy+Gi5S8ZIh6ZjMkZ6aWil3Z/86WNatl2+HfzohzUbvdG3WNqtZd3SYEz/ZIOjtb9YwHN5jHRrIS3ZX7nFkmjJAD/33HN547GN3tny+rE0W0rK//zP/9zdfffdeWl5FcqyfMw6P/jgg1qOXka4PC7btNnl6fK+QNouoIB0OBKknjRR2m23MiE1BshIk5GWYwZxQBxYjQMgDaTLkB7YsXsVSCum/ePatXtI80jXNRR7/7v361zRw5jiajUfyjzSE34eaYG0uLncbEzvsALpmPmVTSrjebO7dp8+fdqdOnUq/0yqZd5VFEdI33PPPTq2Gkiv/XLHfe+dcU89+s6BL5B68mwVUEAaSDeJAVnWamVC6rEAQAEoq4CKvzBTK1SoTLB5QQVIA+lUSIeh0KFNt1Z5y/8JKPPx0cOHtIx9/vxv/H/u1O//qTYTk+Zi3/zW6+4P/uSM+5F/+oD/8/3ud//7191Zn7WWMdI/9LGPDLRA6gJ9IV3MdiUzg2lGOpa8tzIjHcFczUJvJqTlvb/85S/nY54jqiOeRyEjffXqVffSSy+5e++9V/++9dZb9U/1vpsTO90PHDufGmcjsdy97550P/2R+YHbtn37dp1fXKoF5O9bbrnF7dy5c8V9f3F+2j32m2+MxLalrsQ975pwRw+cH7htu3fvToqDly7MuEd/7VLq24/EcsSBcylxIP0X6r77dfdZjQP53td996v3/db/3O6e+qPFkYjv1JX41N+fcJ95YNfAY11qHMg++NIfvp369iOx3I/+g0n3Uwf3DDzWEQcvaz+WlOMBcfCys3g8+NCHPuS++c1v9j0nrMaGxTj48Ic/7P7yL/+y7zlh+ffCD//it9z/mCtJaiSOeKuvxH/6wUV397t3VH7n/ZX+W7ftr152H/zgBzXz2pORrkx9pSXMlY7dOjbY/5dPf+VXZZgZ6X5b9vtf/1/us7/8X9xb1270LPLB2fe6Y34e6WHc+kE6jocO73FTm5HFiwwy/VXrxkhLZldgtHfv3jwjvdnNumQM9BtvvNFTSl4eFz0KY6QlsK9du6YHCvlbvjDyp3rfmwvb3IGf//YwYnDTXkMy0sc/uWvgtskX/caNG27Hjh3u+vXrWqYh+6B63598a8n9xK+262LC93znlPvcP7914LbNzMwkxcHX//ei+xdPzm3aZziMNyIOnEuJg2nfCKPuu193n9U4kGNB3Xe/et+T//2a+8JzV4cRnpv2Gj95/y0K6UHHutQ4+MJzb7pf+r12XVh89Pt3KaQH/c4jDq474uCaIqCrxwM5J5QOy/3OCau/FyweD+Sc8M033+x7TliOjR/7wpz7+rfadWHx1z69x83eKfMhF+e7166VzoEXbiio1w/p0LFbvk/DKu1e7RdntaN3XPbz/+bIUMq+I6TFCrFzt4yRNgdp2XECVcmsxtt9993nHnpo4zu6xfeL46PL5dmSEY/rQdfujT2HpLTbue99z7T74qe/Y+COTi3js1rSKzsotazXaol/agzIvrIaB6kxQGk3pd3yPSAOiAOrcUBpdzdLu3Ua6HgrTX+1voz0aED6sz4j/SGfmV7vrVOQXu/OGsbzy/NAy+tVMc880sPYy/WvAaSBtH7nGCufdEEFSKdfTAFQAMoqoOJv09TjAWOkbV5QAdJAuu8Y6cal3ZsLaTmGVbt6yzjq3/n8/z0UcHQG0tUmX+W99/jjjw9lZ3bpRejaTdduy5lIMtLp0x5ZjgMy0ulxAKBsAgpIF2d2XT4eAGkg3WZIS+Mx6ewtc02/7137/bRYw+vm3RlIl+dr7hJ4N2pbgTSQtgwoIJ0OKMtx0OUTZwAFoMrnD2Sku12hAqSBdJshvVEWktftDKRlLHJ16qiN3LHWXxtIA2nLgALSQLpJDFDaTWk3pd3hrIfKBJuVCUC6m5CWSZt0+iq5DW2M9PCnv9pKc3Wua/eBAwe2cn+beW8gDaSBdPg602yMZmNAGkABaSAdT/AsHg+ANJAe5Xmkq7jK8V95YJtM6DzkW2fmkZ6fn3fHjx93jIceTgQBabuAkghJLeOz2q25STYSSANpiyfO8TdF6rGATKTNTCRxUJwzdXmoB5AG0qmQLiNWfi53/l7vPNL9gDwc2RSv0gTcfSGdZfFl8mh5PZ1f2+8M+Xnu3IV2zCMt5dwpN3Cdspd6lwHSQJqMNBnpeFSwekGlyyfOAApAlX/rc0GFMdI6f3DizeKFNUHg0tJS0h545Mlz7oVXbiQtOyoLPfPYfveB/RPVHG5taXdEoSysuPU4jMgdBGl5fNn/kX0pv2P33b6ndhdsFppT938/XJ87f1GTT/L9GBMw65+x8LKaAG8xpFN3Dss13wNAGkgDaSANpMMeICNNaTdxEL4LFgEVj3NdvrBGRpqMdDkjPRDSMqzaIzJgOCBb/1uWDLWHtP97aXnJLS4uujv23qZfsVGD8yAZRVjPX7jkJiYm3PiYh/RYgLRcWND//L9v3lwOuL7pf85Q3ZqM9KCdwONr3wNAGkgDaSANpIF0jAEAxQUVIG33eACkgfTqkBYIh/jX8mXBs/xXgbRMOR3Ku8Nc0gsLCzmk1y6SrX2mQHpqaspno8cU0vJdCZcPeiHtH9VtLkq7pzyu23b5YGv3tal3B9JAGkgDaSBt98Q5fraU9Ha7pJc4KE7dyEhT2t3p0m7/VRgbFyxmZcslOIfs8+qQ1mUE0FmJvJR3y3cqZqSbI6m+cdggmvYf/5xtQMMVEUjL70kp69bybtk/kpWWivdSRhpIN9yx1hcH0kAaSANpIA2kyUgXv+0p8ae0W6LBYhyQke5qRroAssR2HaQ1C53lYENzsV6QlhuO5c3GdIz0snt7MRXSBZoHQXm9/uqF9mBcK6QnZIz0mGab5bsSx0jHodKyTuVmY2fn/bjqqUky0uv9sNr8fCANpIE0kAbSQBpIA+nyuQwl/kBa4sFiHHSz2VgipOsajpXGScvDocmYL232/0lmX/4s+j+379ldw6EA541Gc6rDClyvhPX5i5fdhM9ESzZa/ug4aF/GreOis+S9ZqdLU28ppH0Wm9Lu1E/A4HJAGkgDaSANpIE0kAbSQLr3JI+MNJC207U75FIjaMsZ6ZUNx1aWdwuc68ZJC6LlwoRAeu9tu7Iv0BrwPKxpoQcnnvMveRXVFy5dUUjnVRuyTr6xWGg6Fl5Yxk+Xb2fnL3hIt2yM9OnTp92pU6dqScv0V82lD6SBNJAG0kAaSANpIA2kgXT1LJKMdDunv5q9c7ImC9wc0oLk2HBMYiOWd0eQ55BeXHK37b61J1vbVyQ1aB5Wxrp23HQCruX9L11+w3ftLkFaN0AgHcdIh+Zrem+WlW4lpI8dO+YefvhhNzs721yNPGPFHgDSQBpIA2kgDaSBNJAG0kAaSPfugbZmpAdC2o//HfdozAFbwmYcJy2IjnjOhk7nWWl5TJfz/5Mx0jL91fbtM27ajxdecavAeVhoTiXdClzXwPq67zp+7a3rYforP0ZaO5sroiUD7QEtzcZ8gzW5X7LSsg2SuZ47d953+p5uV2n3E0884Y4cOeL27duXug9ZbpU9AKSBNJAG0kAaSANpIA2kgTSQtgzpomRby5f7QVrnii7GNZenwYqwlmmvRJWx6ZiOk/aY3uPLu/Nu4BmgU+AcM70py9aRJmI5rPnqtxzW2aKyDZKNjmOjZf3DNnhAy/hoTUnrP/XiQYS03H/23AU3Nd0ySJ84ccLdfffd7sCBA4P2FY8n7AEgDaSBNJAG0kAaSANpIA2kgXQ3IV0eJ62Z6Mo0WOW9Ig3HBNJa5i3/+Z9jibfYdPeunWEO5krX7/ga60VzAm10kUG4lsdlWy9fuapTXsm/BdOSfQ7Z6PhHrxkU48uzjLT4eu7sBTc9M9OujPT8/Lw7fvy4Yzx0aiitvhyQBtJAGkgDaSANpIE0kAbSQNo2pGPDsRUZadnsrCO3/ljTvTuMlY7jpGUe6ZDSlUZkcss7ePvx0rfs3OFLnify7HQZ6k300hfjpc7Zqa8nMI4Z6yUP6IWFt92bb17TcdH5vNH+xWJDsTEP6jBGOoyT1k7l8nM2Tlom3A7TX7Ws2ZiUdve7gevUcCqWA9JAGkgDaSANpIE0kAbSQBpI24F0DuKeTQoNx8qdqSNWdQxwdguQLnfv7p3CKm86lpVSxynF5H7NTku22r+ejqXOXjcitpyojuOwq3GXUqItz8lRW3mBvLxclslKzPNGYR7IOke0/B2z0Nm80fF5ISMd3kFv8a9s7HRW591OSDenIs9YbQ8AaSANpIE0kAbSQBpIA2kgDaStQzrguArpfBx0ptwI6ZDBLrLQ5Q7eIRMdyqNj47EIZ8G0sDxCOe/+nZWDB+QHoBZZ55XtvJtlpMOFAC3p1vmeo4FDVlnHN+vY57D98nAs5dZSdJ03OiBbXiCMhQ5Yv5lNfyWvI/i+KdvuH2tlRhoWD3cPAGkgDaSBNJAG0kAaSANpIA2k7UM6lisLIhW08l9ME5e7d2fl3bGEO+A3W0BKnQXQAuPyc7IstCwbgF0gXLGe6TY+ZcXz+4yrHiSfcmdu7Q2WvU+keXzvfNxzhukc1dKVO3vv+HzFdahaD127s8fH9f5Q5j3nm421rrRbNujkyZPupZdeyvfrXXfd5Q4dOjRoP/N4zR4A0kAaSANpIA2kgTSQBtJAGkh3C9JFCXeWzdUMdPhZM9HZvFf5fVnWNo6L1vtvhqy0PiebEisAOZR2hzmjSmXisdQ7Kx+Pe7wH5KV/VLPSvWgustg9w6Y1I53N+axjnbMMta5myEyXO3LHMdyajfbZ5wLiWaZas9BZF+/wEprxFki3rmu3IFpuZTjX3Yea0/YAkAbSQBpIA2kgDaSBNJAG0kDaFqQDiFdOCSXzI5enqepZRhcPcOwZK52VYedl4BHVmpku3kebcmljshLIM5RX36f8Hj17PluH1SUTxnFXn9czZVX2YGwSFrLN4c64jrG5mN4n5i+VectYb31uNo+0Pt9fOAjLSkb6vJucbmGzsbqmYtKEjGZjaXguLwWkgTSQBtJAGkgDaSANpIE0kO4gpIMqi9Jmnz4uNwFT/HpI9jQG05rtmLGOzy3GS4fxxjWvk2V28zJqfePivfMmYyuHS9cDJ680L3AbXrIYLx3GTBdZZnmhgOUA/jguWsY9F5lo7SqWvUrYP/qYz6bHeaTldc6dv+QmfHfybX6DVl6uaG6yTXlGPzAD6bXtfiANpIE0kAbSQBpIA2kgDaSBdFcgLU21whhpveWQzkq7y+OewyhqXShmo3NUlxqGhey1YLrIZEeJ9iI8IrU0NjuuR/a+qSzNy7wr8M6nqdL1KzamnIUP5dmyHwK0dTdkjcqKLt1ZabeOkQ7w9rn8/KLD3Dyl3WvTp6FnAWkgDaSBNJAG0kAaSANpIA2k7UFatqgMU/k5dO2e6C37VgSHsc75vM+lcm7NypayzPm4aYGzYjU+vzzOOiBcX68E7PDcDNSxhLys+kbOKqCcl3XrXVkWOgOzlmdn65JnnrXOO+wPhbIv25blIqo1GS+PbQvTeIWu3dJsLPz8upR2t20eadk4mo01irBVFwbSQBpIA2kgDaSBNJAG0kAaSHcJ0uO9HbezTS+6V68s5w4dvsOCcXxzaDBWjInOG4/5u/NprwTalefFPR1eL8N3KbM8KCtdbjoWs8sBz8VnmMM6vIVCOU6DFZfLs9RZ9jrMIZ1NmRWS7Pn0WeFl4mM329lsbHiE5JVkDwBpIA2kgTSQBtJAGkgDaSANpG1Cugxf+TmfRzoCtgTZnk7epTHIeXm2DBWOnbczWOcl3z6rG6fFEtxKs66iC3iRne5pZlba5b1dxAcNlO7NOJc/uQLQxXuWs9AyF3Qc9yz7QrLM2iRNAR2wrGgulXrLz3l2Pct2z51tYWk3/B3uHgDSQBpIA2kgDaSBNJAG0kAaSHcN0pJZLkqxdet1qqoAYAVluRlY3snbZ6s9PGN2Os9CZ/NIb5+ZdhMTUj5eGoc9XL6s69WWlpbc4uKyu3b9RpgKK5snOmantXt3qYQ7Ph6BHtF9dv6im5xoSdduaSb2iU98wj399NN9dx5du5vHFZAG0kAaSANpIA2kgTSQBtJAGkivFdKxjHvnjhkPaK/xFtyWlpbdW29d9/27s/HPMo+0v5mEdAs+j1auIpAG0kAaSANpIA2kgTSQBtJAumuQjtnoYoxyaml3XE7KvLWc2/99y87trUF0/KSX/LpfvXpNS721zFu7eIeybkq7W0nbzV1pIA2kgTSQBtJAGkgDaSANpIG0TUjXd+1ee7OxWPqtgJYZmZduuumZKTczNbm5iBnSu12/seCuX19wY+PFvNJhTHU2ZjobH63ZapqNDWmvG3kZIA2kgTSQBtJAGkgDaSANpIF0lyC99umv8o7dfpD0si+PXrq55G69Zacbz0qj20YkuSBw5W+uuvFt4x7Tfsx0zEbLhF8Wpr+S8dEpN8ZIp+yl3mWANJAG0kAaSANpIA2kgTSQBtL2IF03jZTOhzxWagSWzRedT0NVTM2sGWed4irr7C0ZWWnWJTcp55bGW4uLi27PbbuaI2SEnnHx0hXfIG1Cm4zFuaRlH2mnbm1G5rt660zaMud02EFz83TtHqGPcGtWBUgDaSANpIE0kAbSQBpIA2kg3RVIy1jgUkOwHNLCZT8VlM/Qxpui0UOy5z6Z/sr/b2l5Se8XSO/ds3trIDOkd71w8XKAtN8v43KRQSu7sym4srmk/VWD0M07g/S585fcxNSEn5960KzXQ1pJXmb09gCQBtJAGkgDaSANpIE0kAbSQLqDkC4hWrdek62h+VjReEzvKu5TR/v/PCwF0dL9eu+edmekL1y8oo3SBNOSgZb/NA8vZd6SkfbbqnNM++nCdA/5f8ydO+8mp1sy/dXoEdTGGgFpIA2kgTSQBtJAGkgDaSANpG1Buj5PGrpRyxzPPR261crFnNKSdC2XdAdjh7mlJRMtNynx9hXPbmFhwd1x+22thtG8zy5PTXkU+0R9nP96zI+Z1m2WZmMyr7agOrvYIKieO9eS0m7GSG9cbAJpIA2kgTSQBtJAGkgDaSANpLsF6YjjHNzlsdEiaa9Fmd4q3uJygktFtF9GstGSlb5jb8shfcGXaftstGSl44UGF7PPOkY67AdpqHbTl7OHjPQFNyn4prR746A66q8MpIE0kAbSQBpIA2kgDaSBNJC2D2kd8izjgH1Gulyu3ZuNFkTLvhBAFiXdodw5lHxLkzF5TBC9uOQhvaflkL7oIT0+EUq7ZU5pSU2Hya68pwOitUmbZqd9Gt7fdXb+IpAedehu9PoBaSANpIE0kAbSQBpIA2kgDaStQzpkVquQlq2WMcDx1jM2Wh7LMB0f1/mj/X2Cafn57bffNpGRnpyc1H2jnbu1wVjWkC32HJP79ApDaLbWKkhLefcnPvEJ9/TTT/e1JdNfNWc3kAbSQBpIA2kgDaSBNJAG0kDaDqT7jY/OIT2RjZHO9Rwyz4rqrKy7/O/YfEuz0R7PUvKtpd1+vLSUed/e8q7d533XbsnSS8fuMD2YjCWPc0qHiwZhjHSmar/trYJ0cyLyjJQ9AKSBNJAG0kAaSANpIA2kgTSQtg3pzMkhI12CdLmsW6e50g7dYV9UQa6ZaJk/WrLS/r9lP0ZaM9IGmo1pRlrGSMskYH4fKZx1GqxiP8Tpr7TZ2NkLbnpmhjHSKeC0ugyQBtJAGkgDaSANpIE0kAbSQLqbkA5TXhVwln+uzEZn02H5x0I2Wv5e1my0NhszAOnQbGw8Q3QYEy03mf4qVHMX80jLY2fb0rXbKmJHYbuANJAG0kAaSANpIA2kgTSQBtKWIV10nq5mpHsgHWZPViTLTUEd7spwHR6TUme5X7p2W8pIS9du2dYwTlrGSPtpr7J5pOP9sTxe5pGemppuV0b62Wefdc8//3ytQRkj3ZzmQBpIA2kgDaSBNJAG0kAaSAPpjkDaY1EwLbe6bt2xrFvAHDt1R1SXu3iHsdICaRsZ6cnJidBsLCvr1r0jDcay6a/i+OiYqT4776e/mmzZ9FfSdAwwNwdzv2cAaSANpIE0kAbSQBpIA2kgDaRtQPoD+ydqTvtLGelVIV0sJ5lXwWOY6iqkpeVv/S8bJ62l3f6PiXmkpdlYLO3Wcm6BtEg61L6HKbGKmzYb8+OqWzWP9LFjx9zRo0eHJ8mOvxKQBtJAGkgDaSANpIE0kAbSQNoupGOWWUFYgnR1fLSkYHu6d2e7RAGdTYOlsI5du31pt84jvbfl80hfCPNIS2m3NhmTrt0u/lzERd6129/VSkifOXPGPffcc+7w4cMdJ/BwNh9IA2kgDaSBNJAG0kAaSANpIN1dSMe5o/Osc5aNluyz3CKk5edY0h2mvwpjpPfdvmc4MPGv8mdn/sqd+tqfuLnzl90tO2bc//Mvfzh/7atvXdfHfv/r/0vv+6GPfcR99N7vXvd7nzsfssvjWVl3KO/Oyt9LiWhf+J1PhRWmv2pZRpox0uuOlZ4XANJAGkgDaSANpIE0kAbSQBpIW4V0kWWWLazLSEdIl6e9iuOjy2Xd2nSsVNa97J8wTEgLkJ/4f3/THfzoh9077tijkP74/3Eg/2Ae/bnPuatvXXMf+7579b6Pfs93u/e/+8514yhCesxno2N5tw6Q9tcRwhjpMI90GdJz2rWbMdLr3vltfgEgDaSBNJAG0kAaSANpIA2kgXQHIC1DfjMsrtZorK5bdxwfLbgMWWnJSC8NFdIC5QM+w/ypH3pgBa8E2Z/95f/ifv0/HlVgD/NWZKRl+qswj3QYFR7KvCOkt/lx05Kll33YSkgzRnqYYeMckAbSQBpIA2kgDaSBNJAG0kC665CujI8uTXtVHmMtiBZUR0jrPNJDGiP9sR/7OffZn33EfWj2vSvA89Rvf9V9w5d9H/tXPz5cDPlXm5cx0jKP9FiAtI6Tjs3FdDrpgOeVkG7Z9FeMkR5u7ABpIA2kgTSQBtJAGkgDaSANpLsF6aaNxuLeycdI+zu0a/cQp7/aMkif95D2019JWbe4uTxGWu+IkM46lxcZ6ZZBWqa/6ndjWqzmyAbSQBpIA2kgDaSBNJAG0kAaSAPp+o7dodmYgjIv6/ZZ6Q2C9Pvfvd/t3LFdP4xyszHJSP/2qT/oGRM9rGZj8/0grYgON50Jq+2Qbk5FnrHaHgDSQBpIA2kgDaSBNJAG0kAaSHcY0tmI4NCdO8wfrfNFV+aP1nmldXz0xkG6Goe/+6s/r3cJpH/9v/5ez8Of/MHvrx1P3VR//SAdx0OH17sZ5pKWacD8f9K1e2q6ZRnppjuG5VffA0AaSANpIA2kgTSQBtJAGkgDaZuQLo9vlqxybDbWU9rdGNJ+jLTvZC2gHnZp91ZCWkq6BcthnLQ0HAtjo4E0oq7dA0AaSANpIA2kgTSQBtJAGkgD6fZD+ukj73Czd072bMggSKdOfaWozDPSQDrMI92y6a/w8HD3AJAG0kAaSANpIA2kgTSQBtJAGkjLHlittFvLmrOO3dYz0jooPMvg98tIA+nhurR1rwakgTSQBtJAGkgDaSANpIE0kAbSWw3pb37rdXf1rev5ByHNxt7/7jv133K/PF6+yWPDmFM6jpEul3YD6daxdvNXGEgDaSANpIE0kAbSQBpIA2kgDaS3GtKbL6Hwjp2B9OnTp92pU6dq9zPTXzUPPyANpIE0kAbSQBpIA2kgDaSBNJAG0kWzMZMZ6WPHjrmHH37Yzc7ONlcjz1ixB4A0kAbSQBpIA2kgDaSBNJAG0kB6EKQ3utnYVlGtLiOd0rW7dWOkn3jiCXfkyBG3b9++rdrXpt4XSANpIA2kgTSQBtJAGkgDaSDdfkg/89h+94H9Ez0bMqhrt+J5RKa/2ipkrRXSrZtH+sSJE+7uu+92Bw4c2Kp9bep9gTSQBtJAGkgDaSANpIE0kAbSNiEtJco6xZXchjaP9LLSe2lpaajzSJc/gXydK4FZzOs8PJJFSI+Pj8su8vNIj9mcR3p+ft4dP37cMR56OMEDpIE0kAbSQBpIA2kgDaSBNJDuMKQF2tsKcJcRKw/FuaZFz8vLy/pnrZDuB+ThyKZ4lSbg7gdpVXV287tH59HW6cH8P+bOXXCty0hLaXe/G7huHoJAGkgDaSANpIE0kAbSQBpIA2kgHZHbC2lf+J0ltGUPNYH0ZqE5VUD9cN0X0vLCiumA59ZDOnVHsVzaHgDSQBpIA2kgDaSBNJAG0kAaSHcL0hGFysS6jLTg2SNSHqtCWu5bXr7plpZ9affiortj722680YNzoM0FGE9f+GSm5iYcONj476s2+8ZQfO2sfD0MqRv+ox0hupWZqQH7RAeb7YHgDSQBtJAGkgDaSANpIE0kAbSXYe0QDjsAwVxCdJxnLU2JcvLuwOk33777RzSzRQyOksLpCcnJ3NIyxjpsPn+Pw/rmzeXA65XQHrK39eCywdS0v2JT3zCPf300333OqXdzQMSSANpIA2kgTSQBtJAGkgDaSDdAUj7TRwb93MleygGMZfgrNnn4t+asZb/9M5s/LQs4zPRUt4tjcaW/WPrg3RpEHJp9w+iaf/xz6Ua9AYsipAe81iWhmO6f2RQtAwdL0Ha7zm/zQHVISPdEkg32Bcs2mAPAGkgDaSBNJAG0kAaSANpIA2krUK6ALJs4WqQzjPP0lArg7R6u1TenY+R9vcteVCnQ7pA8yAoN6AKqTqFAAAgAElEQVRM7aK90B6M6yIjLd26t+Vdu+XFY4W37rsSpM/OX3STU5PtyEivd4fy/Po9AKSBNJAG0kAaSANpIA2kgTSQ7i6kI5b7d+4O46R1bLTPyMby7qWlZbe4tOhu37O7BhoBzhuN5lTjFbheCevzFy+7iXE/Rjpm67VDd0B1GdJycSHeFNK+HLwVpd2pO4nlmu0BIA2kgTSQBtJAGkgDaSANpIG0XUiX55IuZ6QHNRyTxwXO5fLuOE5aSrv1j89K771tV7bz1oDn+uruZqBRsac/pYrqC5eu+PHRY1rWLX/Uy348tC63LbzwWFnU/t9AOn1/m10SSANpIA2kgTSQBtJAGkgDaSBtA9Kzd07WZIGLOaJXh3RRBi4l3HXl3THDrGOk/TKLi0vutt23BnQOutUsMqyMde37J+Ba3v/S5Td81+4wNlohrTeBdBwjHUrd9d5sO8/OX/AZacZID/rITT8OpIE0kAbSQBpIA2kgDaSBNJDuCKQFix6NOWBL2NRss2ShPZDlVte9Wx4rstIC6UW3ffuMm/bjhVfcKnAeFppTcbYC1zWwvr6w4K69dT1Mf+VLu8XL2q1bM9Ae0NJszDdYk/slKy3bIOCeO3feTU1NU9qd+mFYXA5IA2kgDaSBNJAG0kAaSANpIG0Z0kWmWbOu/SAtTcUioLO/e7t3O50/OmI7du8WTO/x5d15N/AM0ClwjpnelGXrLBaxHNZ89VsO62xRWX/JRseSbln/sA0e0FnmWSAdZv3ygM4gLY+d1a7dLYP06dOn3alTp2r30mZOfzU/P++OHz/esx5Hjhxx+/bt0/vOnDnTM1VXdd2effZZ9/zzz+uy+/fvd4cPHx702W/I40AaSANpIA2kgTSQBtJAGkgD6W5CujxOWjPRlWmwyntFGo4JpLWLt/znf44l3mLT3bt2KkT7oXi9aE7F0CBcy+OyrZevXPU4DmOhBdOC5pCNjn/0mkG+PQWknZs7e8FNz8y0KyN97Ngx9/DDD7vZ2dnUfTn05SKiZV7ruvWIiI6wFjS/+OKL7ujRo7ou1X+fOHHC7dq1yx06dGjo6zroBYE0kAbSQBpIA2kgDaSBNJAG0rYhHRuOrchIy2ZnHbn1R9Gyh2TEsPwdstJxGiyZRzqkdLWDt78JpiUrLV28b9m5w5c8T+TZ6TLUB7mk/HhfjKeMxa68kcA4ZqylOdrCwtvuzTevaSm3lHTHTHpsKDYmWegc1GE7Fdexa7ffJ2H6q5aNkX7iiSdcOfPb5AMZ1rIC4StXrvSF78mTJ/WtyjCWCwAHDhzQP+WfZbkI863YLiANpIE0kAbSQBpIA2kgDaSBtB1I5yDu2aSA47yhVinTqmOAs1uAdFEKHqe9Kj+u92Wl1LG8W56n2WnJVvvX07HU2evGZeV5cd36QTmlRFteozwVVXkzYzZZl8lKzPNGYR7Isv2SeZZMtGahs3mjI6ZDRjq8g97iX9nY6azOu52Qluzt3XffrSDdqpusw7ve9S7NMr/55pu6GgcPHszXqQpleTxmnR988EEtCa+iWS4QlF9js7YNSANpibU//uZ196NfeG2zwm4o73Pfe2fcU4++c+Brvf322wOXkQWef/mG+/EvnktadlQW+t73TLsvfvo7Vl0dmeMw9WY1DlJj4PNffcN9/qtXUnfXSCz3mQd2u888EKcd6b9KqXHwi6cuuc995dJIbFvqSjz24B73Uwf3DFycOHA652nKjThw/lhg73jQ25F4cCRYjIOIvsFb79wjT55zL7xyI2XRkVnmmcf2O+naLbc6qApkq5DOM86ZciOkQwa7yEKXO3iHTHQoj46NxyKcBdPi5diwLO/+HcvB9X1UpaV1XNnOu1lGOghdS7r1xzDGOZZp6/hmHfsctl/eLZZyaym6LO//i+OjQwl3wPrNbPorBbdm6sM82q3MSMfs7WaOh65+OwTKAuiI4VjKHUu961AcIX3PPffo2OmNhvS1a9fct7/9bXfXXXe5V1991XfT2+527Nix4r7FbTPuH//7syNzAEhZke/5zin3rx98a+C2Tflyi9dee829733vc6+//rqb8eMYZD9U73vx7IT7zK9fTnnrkVnm3ndP6j4YtG233nprUhzIPvjJL10Yme1LWRHiwLmUONi5c2ftd7/ueGA1DuRYUPfdr9538utj7lf/YCEl/EZmmR/7yJQ78gO7Bx7rUuNA9sEXf//6yGxfyoo88tEZhfSg33nEweuOOHjVl5x293jwXd/1XXo+1O+csPp7weLxQPaBnBf3Oycs/1745PFX3TdeG9zAKuU4tVnLfO6fjbu/+67t+hn/9V//dc154uvu/e9/fz7Fk45zztPExVrG8u5Ywt0Dc69QRbPAuNzxO8tCy7IB2AXCFetZejg+ZcXzyy/WYIeVO3PrdFWxSVj2GvG983HPGaZzVEtX7uy94/MV16FqPXTtzh6XuaZvyrRgfsE532yslaXd/fbtZuFaIP23//bfdg899FC+KjFLLfeNQkZ6wbdyv3Dhgrvzzjv172nfVU5+eVTvu7404f7hv21XJlKycP/hn44N3DYJ8kuXLrl3vOMd+rdsv1yNr973jb927vBTFxt8Zbd+UUHkL/wTN3Db5JdiShz82as33af/8/zWb1iDNSAOnEuJA4mBuu9+3X1W40CuOtd996v3PfVHS+5XvnatQRRu/aI//n3bNSM96FiXGgdf+sNF98v/LVRateX2E/9op0J60LGOOLikF9VSjgfEwSVn8Xgg54SXL1/ue05YjQ2LcSDnhOfPy7RF9eeE5d8Ln/ql19yfvrrUlkOhrueTP7LD/Z2/NaO/8y5evFhznnhZmxzL8bAo4c6yuZqBDj8Xpdul+7KsbRwXHabGKk2VFVpbZ8AOpd2a1daMbsg456XeWfl43Lk9IC/9o5qV7kVzkcXuGTatQ7yzOZ91rLO+s28KJj+HzHRe/p2Va8eSd79QCeJZpjobLx4y3PoSWvotkG5d1+5RiGYZA7179+6+kGaM9MZ+SpT0OpdS0iufQmoZn9WSXtkHqeWclHbbLfFPjQGLpZzxaJx6LLBYyhn3AXGQ/juBOKC0W743FuOgS6XdAcQrM+oyP3J5mqqeZXTxgOeesdJZGXbReCyUQofMdPE+2pRLG5OVQJ6Np66+T/k9euSQrcPqmgjjuKvPKwM5PlaUePeOmY7TWRXLhbLvWOYtY731udk80pqtVowHqMs80pPTLWs2trFES3v1alfuQf+ma3fafk1dCkgDaYkV4iAtDlIBJfvU6gUVAAWgmlxU44KKTUBxQaU0NjbxhAtIt3uMdBKkg5uL0mY3lo9tzp/vIRnHO2voaM120WwsALkYLx0gWvM6WWY3L6PWNy7eO28ytnK4dH3EZtcI8kZiKt1ivXJUl8rK5YUClgP447hoGfdclITH18neNpaL+9L1OP2VPHLu/CU34buTb/Mb1KoBAJLxfemll/KdKuOAN3vqqOp81tWpsJhHOvEovYbFAFQaoGTXpiLKKqCanDyTkQbSAApAyTGDOCAOrMYBzcbC2F1phpVya3uzsf6QlqZa48UuyCGdlXGXxz2H2aIVyjEbnaM6q9guMsuC6SKTnSWlKwgvsLuCn9n7prI0L/OuwDufpkrXr9iYchY+lGfLftCN132RNyrLu3Rn2WkdIx3g7XP5+UWHufkWlnbXlU3X3ZfyBWEZ5+jabbdbM5AO3/DUbCSQBtIACkBZBVQ830m9uGoxExn3QervBIvHAyDdPUhXMR3HAo+PT/SWfXtURiDn8z6XyrlDk+0iy5yPpRY4Z2Og8zHRpe7fsUxaxkb3jsnOQB1LyHOUpaaj4xMKKBcZaN3qHMZ5eXY2xjvPPOs46jBmWqHsy7aljDuiOnY4v7ktTOMVunZLs7Hw8+tS2t3GeaTrmopJp+zNajZmCeBAGkhLPJORthsHqSfOluOgyyfOAKr4jU0cpFcpAWmblQlAGkgXkJZmY8XxsdxJO0KyWs4dOnyH58QsdJj6qhgTHZ8jy+XTXgm0K8/LGVwak10e8zwoK11uOhazywHPxTaV55PWCwHZeoZmY2G5PEudZa/jdFnyXO2HlpV1x7LzfDot/2Arm431AzOQXhvvgbRdQElEpCIKSNuNg9QYANI2T5yBNJAunx2kHg+AtM3jAZDuJqTL8I14lK7dsVw7/zuWeMe/S2OQc1T7x+KUWBHWecm3z+rGabEEt9Ksq+gCHkrEw3jmUjOz0gFqRcZ6Vdr0ZpzLixaALt6znIWWuaAV1lra7Yu1fZZZm6RJYzF9qMhKZ1Xt+lieXc+y3XNnKe1emz4NPQtI2wUUkA5f1NQsFKXddisTUmPAYiknkAbSQLr3pK3LxwMgDaR7IS2Z5WJ6q5CiLbLNCspyM7C8k7cvA/fwjNnpPAudzSO9fWbaTUyM5XNVjxqbZIz84uKyu3b9RpgKK5snOmanBdPlEu74eAR6RPfZ+YtucqKFXbtHodnYqAXFWtcHSANpy5lIIJ1elWA5Drp84gykgTSQBtJxDwBpIL1RkI5l3Dt3zHhAe4234La0tOzeeuu679+djX/2qJabeUi34LNpzSoCaSBtGVBAGkg3iQEy0jQbk3ghDogDq3EApIF0L6RjNjr7u0FpdyzDljJvLef2f9+yc3trEB2htuTX/erVa1rqrWXe2sU7lH2Xu3ibKe1ujVBbsqJAGkgD6fBlpbSb0m4ABaCsAorKBCoTqpnIlNNUi2Pluzb9lXzO5cZdw2g2FhuNKaBlRualm256ZsrNTE2mhNXILXP9xoK7fn3BjY0X80qHMdXZmOlsfLRmq/W+cOGhVc3GpJmYzNX89NNP9/0A6NrdPDaBtF1ASTSkNpah2ZjdOEiNAcsXVCjtTj8WWDxxjr8ZiQPioOsVKmSku5mRrof02qe/yjt2e0wu+/LopZtL7tZbdrrxrDS6uUa29hlyQeDK31x149vGPaalo3eWjZYJv2RqLEvTX23trrb37kDaLqCAdPi+pp48k5EmI01Gmow0Gelw3OSCis0SfyDdPUjXTSMVulVL1+7sFku6s27acaoqzWZn/8VO25KRlWZd+piUdfumY4uLi27PbbtajaSLl674BmkT2mQsziUt+0g7dWszMt/VW2fSljmnQzvzufkWdu1u9ac0gisPpIG05UwkkE7PQFmOg9SLKUAaQAFpIB1P1SweD4A0kJb43uaxmM+frHcU5d9CxfL80YpGD8me+zygBdtLy0t6v0B6757dI6ic9FW6cPFygLTPQI/LRQat7M4mm86myvJXDUI37wzS585fchNTE35+6kGzXqevx4YvyTzSw93FQBpIWwYUkAbSTWLA4olz/I2RWuJPJtJmJpI4KM6dunxhDUgD6RWQLiE6pJmDrGP5dkB2gW0lo/7P/+dhKYiW7td797Q7I33h4hVtlCaYlgy0/KebLWXekpH226pzTPvpwsI+3ObHSJ93k9Mtm/6qDtLz8/Pu+PHjjjHSzZENpIE0kA7fG0q7Ke0G0mSk5VhAHBAHVuMASHcL0vV50jD+d3zcly0Linuy0cWc0sHLQdDxdbTMWUq7fSZablLi7Sue3cLCgrvj9tuaI2SEnjHvs8tTUx7FfgYs2TdyG/NjpnWbs+ZiiursYoOgulXNxk6fPu1OnTrVd5cfPHjQHThwYIQ+knasCpC2CyiJwNQsFM3G7MZBagxYvqDS5QxU/E2UGgdkpIG0xAxxYDMOgDSQDp2oA6SDCf1/Walyz9hoRbaUdIfxwLpstpw8RxHt/y3ZaMlK37G35ZC+4Mu0fTZastL5/onZZx0jHfaDNFS76cvZQ0b6gpsUfFso7W4HW0dvLYG0XUAB6fB9S0UUGWky0mQiAZQcM4gD4sBqHABpIK1DnmUcsEA6y0YLErWUOUI5y1SHbHQAdL5MBm9pMiaPCaIXlzyk97Qc0hc9pMcnQmm3zCktqekw2ZXv2h0QrU3aNDvt0/D+rrPzF9sH6X4U7Td2evToOlprBKSBtEQkGWm7cZCaibQcB6kXUwAUgLIKqHjmkXo8ICNt84IKkO46pAOWq5DWbHM18xzHRmsmuncuap0/2t8nmJaf5XeshYy0HB9l32jnbm0wJphWT2eQDrTOBom3E9LPPvuse/7551dodP/+/e7w4cOjpdQWrA2QtgsoCb/UkyYgbTcOUmMASNs8cQZQxS9iLqik/04A0jaPB0C6O5DuNz46h/RENkY6HiJLWA5jp3sz1LH5ljwmeJaSby3t9uOlpcz79pZ37T7vu3ZLll46dofpwaQEPs4pHS4ahDHSmar9trcyIx0zz9Jg7Ctf+Yo7dOiQO3PmjHv55ZfdQw891AK6jtYqAmm7gALS4buWevJMabfdyoTUGCAjTUaajHQ4bgJpIG01DgSBcR7kQWfkjzx5zr3wyo1Bi43U4888tt/N3jlZjHsurV0cCq0XVEqQLpd16zRXPdnoYoy0vJRmomX+aMlK+/+W/RhpzUgbaDamGWkZIy3zRft9pHDWabCKjHyc/kqbjZ294KZnZto7RvrEiRN5FprS7rV9j4E0kLaciQTS6Rkoy3EApNPjAEDZBBSVCVQmyB4gI93tjHQ/SFebjAmdy+OlQzY6gDpkpCUbXexLbTZmANKh2dh4huhs6iut8ZYND43ZCkhvc2d9s7Gp6el2QVrwfP/997vZ2VknP3/84x/XD5bpr4B0dQ+knjxbzUTK/kgt66W02+4FldQYANIAymoGKv5uSP2dQGUCGWmJGYtxAKS7DOmiVLuake6BdDbllWamI6hL80iLKrW0O2u4JV27h52RnvNTUZ07f2UgbD44+56By6QuINNfyfmSdO0WOIdx0jJG2jdiy+aRjvfH8niZR3pqqmWQlh0iZd379u3TvwXQcmP6q9RQ6V2OjLRdQAHpEOupJ89WL6gA6fQYsHjiHI/4qXFARtomoIiD4twn9XeCxeMBkAbS8k2Q8mWJBbnVdeuOmWsBczUbXe7iHcZKC6SHm5E++u9+xX3jL14ZCJvP/uwj7kOz7x24XMoCAdITodlYVtYdpgrz/59NfxXHR0vJt9zOzvvpryZbNv1Vys5gmfQ9AKSBtEQLGWm7cZAKKMtx0OUTZwAFoMpnBKnHAy6o2LygAqS7AekP7J+ogUApI50I6TjlVZjqKqSldSos+S8bJ62QHvI80gLpD3ogf+qHHugLmo/92M+5oULazyM96Uu7c0h7PPt5r3SctK/d1vUIU2IVNyCd7k2zSwJpu4CSoE09aQLSduMgNQaAtM0TZyANpIF07ylcly+sAenuQjpmmRWEJUhXx0dXu3Vnld7ZXNLZGOmsrDs2blv0XbuHOf3VVkF6Qrp2Z2OkpYzbtxwLDcein7WZeda1WzPSfh5pXw6+zV9d6G3JNmJslEZiKbfHH388ZTGWKe0BIG0XUEA6BHrqSROl3XYrE1JjwGIpJ5AG0kAaSMc9AKSB9KqQztSsWecKDcN9IZJiSbdOfyVjpBffdvtu37NuX8nY6FNf+1P3u1/7unvHHXtWLdv+td/5qvvY992jmWv5e723c+c9iifCGOkw/VUcIy2l3cWrx1J4WSZMf9UCSK935/D8/nsASANpiQ4y0nbjgIx0+sUUIE2TKTkeEgfEgdU4ANJdhXRR1t0P0mHu6DC9ldxiWbeWcZfKunWZrKxbphFb9o/Jxer1QvrqW9fdjxz9j+5N/3fT2yd/8PtXLQNPeT2FtEx/5YFcZKVlY+MY6TCPtB9Bnc8pPadduxkjnbJ/zS4DpO0CSoI2FVFA2m4cpMaA5QsqZKTTjwWMjQXSciwgDmzGAZAG0lqynGFxtUZj/SCt02BlU1/pfNK+zHthYWHdkP6zM3/lfuYXvrgmb33wA+9xx/7Vj6/pufFJAumpqSkdBz3mx0fLdyWMCpfSbrkQYQTSq5V5U9rdPIaAtF1AAenwfUhFFKXddisTUmOATCSAspqJjGcHqRfWgDSQtnpBJY7rTTljfuTJc+6FV26kLDoyyzzz2H63stlYKSO9KqSL5TQLXZn2qtxoLM4nvbS85HQe6b23rWsfbDWk532zMZ1HekzmkY5NxpTRPZDe5huQycUEuRgRMtItnP6q+kkJro8cOaJTYnFrtgeANJC2nIkE0umZSMtxAKTT4wBA2QQUkC7Ojbp8PCAjTUZ69Yx0BdLZ16Y8PlrukosRCmkdI700lNLurYZ0LO3Wsm5pMKZ/ssHR2l8s4Lk8RtoMpE+fPu3+/M//3B0+fLiZIlnaAWkgbRlQQDodUJbjoMsnzgAKQJVPdchIp1cpWaxQAdJAugzpgR27V4G0Yto/LpBeHMI80lVIS7m2NBLrd/v1//p7+UPDKO2WeaQn/DzSAmlxc7nZmN5hGdLz8/Pu+PHjjtLu5lcGgDSQtgwoIA2km8SAxRNnIA2kgXTvuVGXL6wBaSCdCukwFDp0HtMq76wZWTE+emMhPaiBmMwjHW8bCulitiuZGUwz0rHk3UxG+syZM+7LX/6yO3r0aHNJdvwZQBpIA+lwEGCMNGOkgTRjpOVYQBwQB1bjAEgD6b6Qrkx9pSXMlY7dOjbY/5dPf7WBGelRgXQcDx3OFG9qM7J4kUGmv2rdGOl+zcYOHjzoDhw40HEWN998IG0XUBINqWV8dO22GwepMWD5gkqXM1BkpMlIk5EmIx33AJDuJqR7poQuNRvrKe1uDOnQsVtQPYzSbonRR3/uc+7lb89puDaB9OP/8ofdR+/97uYIKj0jlnbLdyR27pYx0uYgva69xJNX7AEgbRdQQDqEeyqiyEiTkSYTSSbSaiaSCypcUJE9AKSB9PAy0sOHtMSojJX+/G886w54GH/qhx7oKzcp7X700P/pDnzPd7v9d+xZt/CA9Lp3YTdfAEgDacuZSCCdXpVgOQ5SL6YAaSANpMO5EN3bbZb4A2kgPeqQluPP0X/3KzLZtfvQKs3Gfu13vuo++7OPrLpME9l1CtInTpxwc3Mh9S+3++67zz300ENN9hfLZnsASANpy4AC0kC6SQwAaQAFpIF0PEG0eDwA0kC6DZB+6re/6r7hM9ODbkd/4uNDyUbL+3QG0oLoXbt2uUOHDuX79+TJk/pz+b5BO5/Hwx4A0kAaSIfvAqXdlHZbPHGOv+tSx8qTibSZiSQOirO+LleoAGkg3QZIb4XROgNpaTZ25MgRt2/fvp79LPcz/VXz0APSdgEl0ZB68kyzMbtxkBoDli+odPnEGUABqPKZQerxgAsqNi+oAOluQlombdLpq+Q2tGZjw53+qrlghvuMfvNIm2s2duzYMffwww+72dlZID2EGALSdgEFpMMXJBVRZKTJSJORprRbjhnEAXFgNQ6ANJAe1Xmkh0Cadb1EP0jL/oo3E/NIy5zRzz33nDt8+HC+YadPn3aXL19mnPQaQghIA2nLmUggnV6VYDkOUi+mACgAZRVQVCZQmSB7AEgD6VRI5xlsHzfyc3kKrY2YR3oNhBnqU/pCOsviy+TR27ykdX5tvzPk57lzF+zMI13dm5R5p8UXkAbSlgEFpIF0kxgA0kAaSIdzB0q7bVYmAGkgXYZ0RKF85xXOHocR0IMgLY8v+z9LS0ta+bfv9vVPQZUml41Z6tz5izoccnx83M8j7feM/hkLb6ZZaSOQ3pjd191XBdJAGkiH7z+l3ZR2A2kABaSBdDwjtHg8ANJAuhGkZVi1R2RAdUC2/rcsGWoPaf/30vKSW1xcdHfsva3VmJq/cMlNTEy48TEP6bEAabmwoP/5f9+8uRxwfdP/nKG6lRnpVn9KI7jyQNouoCTcUhvL0GzMbhykxoDlCyqUdqcfC8hE2sxExtOP1OMBcWAzDoA0kF4d0oLmcLTQ8mXBs/xXgbS/yyN6WSG97IEpv2MtQFqOj2M+Cy2Qlu9KuHzQC2n/qG5zUdo95XFdzt+PIPaqqyTTXb300kv53XfddRdTX63xcwPSdgEFpMOXIhVRZKTJSFvMQAGo4pdj6rGAOKAywWplApAG0hLbY+OCxaxsuQTnkH1eHdK6jABaIe3/+CfYgnRAtO4fyUpLxXspI916SNfNGc080mtUtH8akAbSljORQDo9E2k5DgBUehyQibSZieSCChdUFFAeBzIGNPVm8Xgg+JNxvSm3R54851545UbKoiOzzDOP7Xcf2D+xYn3KzcLqIC1PkOxzXsJdfoI8Vmo4Fsq6/fRXOkbaZ6QXjWSkJ2SM9Jhmm8OFhtCyOw6V1p9LzcbOzvtx1VOT7cpI95svmnmk1/YdBtJA2jKggHQ6oCzHAZBOjwOLJ87xtyNxQBw0+Z1gsTIBSHc1I11kmvWCSk1GWiFd13CsZpy0ljb7/+SChPxZ9H9u37N7bRAZkWedv3jZTfiLTHKhSf7oOGhfxh3GSsc0vSSpi/mwFNK+HLxVpd1AergRB6SBtGVANTlporSb0m6LJ87xNwZjY9OHeRAHlHbL98ZiHADp7kI6ZpqrkF7ZuXtwebdmrv3/BNGSmRZI771t13CBssmvduHSFYV0/h0RL/vGYmVIy74q387OX/CQbtkYaUq7hxtZQBpIA+nwnQLSQNriiTOQLn5nkpEmI93k4qrF4wGQ7gakZ++czKexKo6AxdRW5Yx0KqRjxlqS1rG1Vg7pxSV32+5binHXw6XKhr+aXAy4dPlvfNfuEqT1XQXScYx0aL7WekjLBtBsbHgxBaTtAkqiJDULRdduu3GQGgOWL6gAqPRjAaXdNjORXFDhgopmIhkjrRlU62OkB0Ja4sCjMe81nVUuK5ZL46QjnrO78u7dOj66lJWW/bl9+4yb9uOF23i7vrDgrr11PS/r1s7mimgZJ+0BLc3GfIM1uV+6emtHcy/suXPn3dTUdLtKu9v4AY3yOgNpu4AC0uGbl4ooMtJkpC1moAAUgCqfg6ReWOOCis0LKkC6yxnpomRb46AfpGvGScdpsCKsZdqr4udwYULmklCGg0MAACAASURBVN7jy7vzbuCjjJ/SuoVs9Bs5omX94zhonTdaU9Lqab140APpsx7S0y2E9IkTJ9zc3Fy+G+677z730EMPteQjG63VBNJA2nImEkinZyItx0HqxRQgzdhY+R4QB8SB1TgA0kBaYrsK6UHl3WW5xO7d+rf851EdS7zF4Lt37WwNpgXRl69c1XmjBczSZEyyzyEbnXXsziAds/cFpJ2bO3uhfZAWRO/atatn3mimv1o7zoE0kLYMKCANpJvEAIACUFYBRWUClQk5oJj+qqOl3RIBYZz0ioy0ppeL70hd9+5+WWnp4N3TeMyPl75l5w5f8jwxsqBe8oBeWHjbvfnmtXxcdJg3OpRuh++KQLrAtHYqlwx1HCft92OY/qplzcaka/eRI0fcvn37evTI9FdrwzSQBtJAOnx3KO2mtBtIA2kgHY6HlHbbrEwgI92djLTauDIXdA+k5YKKd2LtOGkt7+7t3t0vKx3fR7LSYV5p38m7NM+0ji1Wp8dy8ArYa/iycr3rjVOeiqq8RPn+OFtVBLBmnLN5osdiFjr7d29Jd7jwoLdsPxWQDl3LWwnpY8eOuYcfftjNzs4C6bXZuedZQNouoOSDTh0PR7Mxu3GQGgOWL6hQ2p1+LABQNgEVf/GnHg+IA5txAKS7DumA4/IUTxGtdeXd5SmztMGWZLQzEEtZdHw8Nh6T++IfYXNYJvydv35m02j8VDSnkqfAcPYMuSbgoazjmyXr7G86Djr7W36WP2He6FjSHZYN1xP8c+M80vIcbTYWsvCthPSZM2fcc8895w4fPpzv09OnT7vLly8zTjo1ykrLAWm7gALSIdBTEUVGmow0GWkykXLMIA6IA6txAKSBdJjSKYwH1ltiVloWVfSKkLPnxPHS+ljWxbuMZ1k0QjlCPF82f6yYUmqtqO7NTIeO2mHTwt+K5NKY54hoeSyWdMfSdh0SnTUZEy9rB2/p2p3JX7LYkmUPXbv9PNJtLO1O8eLjjz+esljnlwHSQFq+BGSk7cZBagbKchykXkwBUADKKqDiyU7q8YCMtM0LKkAaSK8G6aZZ6XLjsTKmIzpj1roO62EcdsGwFVXo2UNVXPcv5y6RLstCxwsFimoRslaXF5np2JE7bncAdLasLhoy2RHSobTb312CdCu7dndev0PcAUDaLqAkTFJPmoC03ThIjQEgbfPEGUAVvzC5oJL+OwFI2zweAOluQVotWCNUmR+5NiMdnJnfInbLL1Et8a7D9AqQZyXhPeuSvU8V1MU6l5Rd654iy1yscAnBpaeXxzaXM9OxnDs+v4xo2QYZ6x2xHeaO9q/vcR1vmpGeblmzsSEakpfyewBI2wUUkA5f8dSTZ0q77VYmpMYAGWky0nLMIA6IA6txAKSBtMT22Nh4b0ftUnl3GcE5aqWcuaTpOkzn46WzabH6vc4K3FfhLgsMMnQUXPbcnix1BdC6aARx9rw4ZjqOidZ/Z125w9vHseBFs7H4OnH6K/m3jJGemJr0uF5rUToUbf0eANJAWoKYjLTdOCAjnX4xBUABKKuAiicrqccDMtI2L6gAaSAdIC0NtrIx0hlc67LFBaTDQuXxzgGWBXrDYyVwaw10OPL0Irz6nBKlSqhuBKwKvHNYa4l38Ur5/aV1C/eVNV+sXz79lY6RDg3GypCem2/hGOlGO5aFB+4BIG0XUPLhp540AWm7cZAaA5YvqJCRTj8WACibgALSxelQl48HQLp7kK5CNkJ6fHyit+x7YFZ6DZhWombdvisZ7dDFayW0B8JllQXKgJZ37p0GKxvvXEp3R0SHjHTRSE23VO/LSsV91+44Lro8nvr1c+fb12xsPTuY567cA0DaLqCAdIj31JMmSrvtViakxgAZaTLScswgDogDq3EApIF0AelxhWJ+q6C2vjS7mFu6B+grMtO96A4duurRHDPZ+mhP87HV09M95dz5oivHTQ/KQsfHdb7rWMmdpbEDpHvtVO4ELmOkaTbWcV0DaSAtXwEy0nbjgIx0+sUUAAWgrAIqnuqkHg+oTLB5QQVIdxPSPej1/yjioHfsc093bX1SgaS8PFsz1yvvL88xXZRyV8ZWZ9np6vrEV+sdaTxooHSxEnWdvHMgl95TrV4q5S5Pk7Wsc12VmpXlK9UL/PJ2thbSTzzxhG7e/v37dT7purmlO+7j5M0H0nYBJUGQetIEpO3GQWoMWL6gQkY6/VgAoGwCCkgXp0VdPh4AaSAt34RyHKxo6j2oxDtoc0XzMb07b9IVvm/9QB3BHrO7/WCdjJkKgPN5o0vgrwN0eZ1DV+4C71raLVlqee2eeaTHfDfvgG5pNjY52bKu3ceOHXMPP/ywbsBzzz2nkJab4Jq5o5uEXFgWSNsFlHy+qYgC0nbjIDUGJF6sxkGXT5zjb4XUOADSQFpihjiwGQdAuruQLmO1Nw5WZqXLy9aWeAeB9paG+7vybt4r5oiOoq28V/46YRx13S11Huk6POvL12Sg9X2y8c/xeeX3iU8pxkhn25aXfAd06/RXbYN0BHM1Cw2kmyMaSId9ZnVsLJAOn28qoqzGQSqggLTNE2cgXfxuTD0WUOIPpCVqLMYBkAbSEtsr42D1Eu/VMN3TqTvDdPBxnEIqHIPryrZrJ40qZcQHyUaRXDOUusgs15d/l9ctLwHPM9JZ0zF9897pr8qN0xTSZ1vYtfvEiRPu7rvvdnv37s0z0nLfrl273KFDhwbtcx6v7AEy0kDaMqCAdHpVguU4AFDpcUAm0iaguKDCBZV6QK1+WmzxeLC8vOyWlpaSPPDIk+fcC6/cSFp2VBZ65rH9bvbOyb6rI3itu6CyWol3DuMVnbejNVdmmiOSq6BuhOoGO3UQnqu4rxtXrSovzU0dN1dKu/Mx1HmrcRcy0lMtK+2WHXHy5En30ksv5bv3vvvucw899FCD3c2icQ8AaSBtGVBAOh1QluMASKfHgcUT5/j7jjggDpr8TiAjbbMyAUjXQ7qaWdbjZiU7XM1M5yjWxG1/TPdAvFLBvTIrPajJWNVwvSnpFUAulXDHZ1aXCVNdhXmiy4/F0u6bMv1VpmqdRzobO91aSMPg4e0BIA2kLQOqyUkTpd2MkbZ44hx/W6SW+ANpMtISM8SBzTigtLvbpd1lSI6Pj9dgov8Y5vy5q4E5EdQK8Lqa7OxNaku+69a2OjdVaZnyNFWrATpmoavNxsJzsvL07IKCIHvbzWIftbZr9/AYySsBaSANpMNxAEgDaSANoORYQBwQB1bjAEgDaeWhB2E9pDM8Vuu8EzLTiuOeJmM1KI/LZPzKsZvXUK/RZaVy7CrS+0+NFSe2DvujrqnZcnW9dKrpYlnt2j016XGdSv81bh9PG909AKTtAkqiLjULZbVbs+yD1HJOIA2kARSAsgqoeBaS+juBjLTNCypAGkjLsUDiQP70vw3OTAdyr1LOnVdo14M6h3fNSvTr4F1dtF9Wu378c28H7/JY6PK6KKqzB8tjpPOpsLJtDl27z7djjHScN3oQR5n+atAeWvk4kAbSEhVA2m4cpJ44W46D1IspQBpIA+lwngCkgbTVOOj6GOkIaclIr55Hrcd0FcB1mF6B5KzkezU8l4WSmt/tB+bya/U0IVsxr3SxZCzt7sV5MV673DwtPOtme5uNNeciz+i3B4C0XUDJZ56KKCBtNw5SYwBI2zxxjsf+1DgAUMSBVUDF70KXL6yRkSYjXYb0YNimYVpepx+oe96jlKWO38dUNKdKrhfXRfm2rmOfMdVyf+zKHd8nlHurl3uarmmzMWlM5m80G0v9VAwvB6TtAgpIhy9u6kkTpd12KxNSY4CMNJlIOWYQB8SB1TgA0kC6Cuk1YTrIWW8rxhbXlHuXGdWzfE+D7pXduvshu+/UVbnOi3dcLWvdW8Yd0J0vLzNhxQx2udlYaZtbCWkp864r4e53v2EDD2XTgDSQlkAiI203DlIzkZbjAEinV6eQkQbSciwgDmzGAZAG0nWQHjamg7P7j43Ovbti8urskdQZsHpnvspdNKjkuwzo8rqUER32SXV9bvZslxlIz8/Pu+PHj9cCeyjaXOVFzpw5455++ml38OBBd+DAgXzJeH+8o4r/Z5991j3//PP68P79+93hw4c3elVrXx9I2wWUfOCpiALSduMgNQaAtM0T53jgT40DAEUcAOnwrbFYmQCkgXQ/SA/GdOBxbZa4T3Y6/v5JQXUdUpplpFdnVB2e8/WLXbsrMI/zSPu23Pl2l7elVZA+ffq0O3XqVN+9VIXsZqg0Al7eq/z+EdFHjhxx+/btc4LmF1980R09elRXq/rvEydOuF27drlDhw5txmr3vAeQtgsoIB1CPTUbSWm33cqE1BiweOIMpItfecRB+sVVLqgAaasXVGg2Frp295v+avCY5VUyzaVMcl8EZzXhg99nfSSK2eWkzt5axl2X3pYN0jmv+kJ6anq6XdNfjVIJt6zLfffd57797W+7u+++O89Inzx5Uj/9MoyPHTumj8uf8s+yXAR5hPf6QqfZs4E0kJaIISNtNw5SM5GW4wBAAagmF9W4oEJpt8SLxTggI01GWmJ7UBykIXdA6faALHVZKyvmk25GmXxccz8097xXbDi2Ivtc3BEQLlno7Jl9IB3mkZ6yAenNBnY5iyw/lyFdhbJ8DHH5Bx98UMvQq2iW9d+KrDqQtgsoMtJkpJvEAJC2eeJMRpqMdPkkMvXCGhlpm8eDQYCq+sViHJCRHgxpiYM0TMuSaaCOsZX+ug013WfxFeOl+4yrjtNfhTbd4bYapMM80hdsQHqzx0hLxvmNN97IxzVXIV2H4gjpe+65R8dUbzSkFxYW3IULF9ydd96pf0/70oMpf9Wket/1pQn3D//ta8OJ1k16le99z7T7D/90bOC2SZBfunTJveMd79C/ZfvlJKJ63zf+2rnDT13cpLUfztt8z3dOuV/4J27gtu3YsSMpDv7s1Zvu0/95fjgrt0mvQhw4lxIHEgN13/26+6zGgZSw1X33q/c99UdL7le+dm2TIng4b/Pj37fdfeaBXQOPdalx8KU/XHS//N/eHM7KbdKr/MQ/2ul+6uCegcc64uCSIw4uaElrV48Hck54+fLlvueE1d8LFo8Hck54/vz5vueE5dj41C+95v701aVNOpIN522e/JEd7u/8rZlVY1zioF9pd3ktmqF3cHMxfe2aRmLN3qf/fqptMtYHzuVXCVNdhSmterc/+1clIx2XaRWkR2WMdHlcdHWH33XXXVrOPQoZ6WvXrmnJuazTq6++6rZv366/QKv3LW6bcf/4358dzrd3k15F8PCvH3xr4LbJL4TXXnvNve9973Ovv/66m5mZ0f1Qve/FsxPuM79+eZPWfjhvc++7J3UfDNq2W2+9NSkOZB/85JcuDGflNulViAPnUuJg586dtd/9uuOB1TiQY0Hdd79638mvj7lf/YOFTYrg4bzNj31kyh35gd0Dj3WpcSD74Iu/f304K7dJr/LIR2cU0oN+5xEHrzvi4FUFVFePB9/1Xd+l50P9zgmrvxcsHg9kH8h5cb9zwnJsfPL4q+4bryVIbJOOdSlv87l/Nu7+7ru2rxrjsg9SIB3frxl0g5QbPSe1S/egHdDgoyrQHZ5Ut771018VFwxaBem47za7hHvQZyaPV+HMGOmUvbb2Ze5774x76tF3DnyB1HGRVptMyQ5KLeNjjLTdEv/UGJB4sRoHqccCi2Mi44EyNQ4slnLGfUAcpP9OIA4o7ZbvjcU4oLQ7rbS77iS7EY71BdaA6oFn92tfoIrn8iutBultYwWeW9u1e9Bu20pgVyFN1+5Bn9b6HgfSzklZ8xc//R0Dd2TqybNVQMkOSj15tnpBJTUGgLTNE2cgXRwmU48FXFCxCSguqDQHFJA+51545cbAc61RWuCZx/a72TsnV12lpmPlqy/WHNTxFYrU89pfI21v95Z5D05V9+/aHa4HxMdbD+ny/MvlXbmVczHXlXIzj3RaoK9lKSANpCVuiIO0OADS6RdTABSAkmMLcUAcWI2DpoAC0kB6tfP04WC4vq570GvXjofWlR2M5rptKr9fPnXWgK7drS7tlrHKX/nKV3RMsqD15Zdfdg899NBaXNbp59C1225JrwR2KqLISNuNg9QYICMNoCQGLJ44k4ksTnNSjwfEgc3jAZBm+is5GjSNg0FQGoTeQc8fhceLrt3F2gya/qrVkJbNlE7Yhw8f1i3eytLuUQiAta4DkLYLKCAdvhWp5ZyUdjNGmkwkkJZjBnFAHFiNg6aAsnhBhTHSw4d02SBtQ3WRfV6ZyTYJacHz/fff72ZnZxXSH//4x/Xzk7mZH3/88bV6srPPA9JA2nImEkinVyVYjoPUiykACkBZBVQ8ySEjnX5x1eLxAEiTkd6IjPRqiBo1WPcrCU/p2i3b2fox0rIRUta9b98+/VsALbeDBw+6AwcOdBbEa91wIA2kLQMKSAPpJjFg8cQZQBW/Hbmgkn48sJiJjJHQ5TgA0kB6syFd55PNwnX/cdQr16pTkF4rGnneyj0ApIE0kA7fC0q7Ke0G0mSkyUiH4yGQtlniD6SB9ChAOtVj/cDdBMjreS+Tpd2pO4Tl0vYAkLYLKImA1DI+mo3ZjYPUGLB8QaXLGSgy0mSky2cDqccDIA2krV5QYYz0xo6RTtPH6C1lPiN98uRJ3evSpbt6k7HS73rXu+javYa4BNJ2AQWkwxciFVFkpMlIk5EmE0lGmox0PJWyeDwgI01Guk0Z6TWwZs1PMQ9pmav54Ycf1iZj1ZtMf/Xcc8/lHbzXvBc7+EQgDaQtZyKBdHpVguU4SL2YYvHEmYw0GWky0r0nd10+HgBpIA2k67FnHtKDprca9HgHjZy0yUAaSFsGFJAG0k1iAEiTkSYjTUaajHRx+mixxJ/Sbkq764AEpJ94gumvkujcuxCQBtJAOnwnKO2mtBtIA2kgDaSBNJCOe+CRJ8+5F165sYaz6617yjOP7Xezd06uugJNKxO2bms2753NQ1pKu48ePVq7R2UarC996Ut9H9+8j6F97wSk7QJKojG1sQzNxuzGQWoMWL6g0uVSzvhbKTUOLGag4j4gDtJ/JxAHNBuT743FOCAjTUa6kxlpaTa2e/fu2oZizz77rLty5UptI7L20XZz1xhI2wUUkA7fpdSTZzLSZKTJSNs8cQbSxXkFF1TSfydYPB40zUQCaTLSm6uSrXs38xlp2bUyDvq+++7rwbQg+vnnn6ese42xB6SBtOVMJJBOz0BZjoPUiykWT5zJSBe/HImD9OOBRUBxQaV5JtJiHJCRbh4HayRGq57WCUjLJyJTXc3NzeUfzs6dOynpXkeoAmkgbRlQQDr9xNlyHACo9DiweOIMoMhIl0+Tunw8ICNN1275LjSNg3UwozVP7QykW/OJtGRFgTSQtgwoIJ0OKMtx0OUTZzLSZKTLpyOUdlPaPT4+nnyGavHCGhlpIF33BQDSyYcFFizvASANpC0DCkgD6SYxQGk3Y6QlXogD4sBqHDTNRAJpxkh3RU1Auiuf9JC3E0gDaSAdvlQ0G6PZGIACUFYBRWUClQmyB4A0pd1riYMh02MkXw5Ij+THMvorBaTtAkqiL7WMj+mv7MZBagxYvqBCaXf6scBiBir+JiYOiIOuV6gAaSANpOttBqRH36wjuYZA2i6ggHT4yqWePJORJiNNRpqMNBnpcNzkgorNEn8gDaSBNJAeSZC2daWANJC2nIkE0ukZKMtxkHoxBUgDKCANpOP5nMXjAZAG0kAaSLfVrCO53kAaSFsGFJAG0k1iwOKJc/zFk1riTybSZiaSOChOwbp8YQ1IA2kgDaRHEqRtXSkgDaSBdPj2UtpNaTeQJiNNRpqMNBnp4ozW4oU1pr9q3nSurcZpst6MkW6yt1g23wNA2i6g5ENOzULRbMxuHKTGgOULKl3OQJGJJBNZPuVJPR5YBFTcD10+HpCRJiNNRpqMNAwe4h4A0nYBBaTDFyX1pImMNBlpMtJkpMlIk5EmI01GOu6BR55kHukhkmOkX4qM9Eh/PKO7ckAaSFvORALp9KoEy3GQejEFSANpIA2kgTSQBtKj65aNWjMgvVF71vjrAmkgbRlQQBpIN4kBIA2kgTSQBtJAGkgbx0/N5gHp7n3mQ9liIA2kgXT4KlHaTWk3kAbSQBpIA2kgDaSHQoxWvQiQbtXHNTorC6TtAkqiLLWxDM3G7MZBagxYvqBCaXf6sYAmU0x/JccC4sBmHNBsjGZj8v1uGgejo5aNWxMgvXH71vQrA2m7gALS4aubiigy0mSkyUgDKDLSZKTJSJORJiNtmj61Gweku/eZD2WLgTSQtpyJBNLpmUjLcZB6MQVIA2kgDaSBNJAG0kMhRqteBEi36uManZUF0kDaMqCANJBuEgNAGkgDaSANpIE0kB4dp2zWmgDpzdrTxt4HSANpIB2+1JR2U9oNpIE0kAbSQBpIA2lj2EnYHCCdsJNYZOUeANJ2ASWfdmqjKZqN2Y2D1BiwfEGF0u70YwFNpmw2mYq//VOPB8SBzTho2mTKYhwsLy+7paWlJBI88uQ598IrN5KWHZWFnnlsv5u9c3LV1WkaB6OybRu5HkB6I/eu4dcG0nYBBaTDFzcVUWSkyUiTkSYjTUaajDQZaTLSZKQNw6fPpgHp7n3mQ9liIA2kLWcigXR6JtJyHKReTAHSQBpIA2kgDaSB9FCI0aoXAdKt+rhGZ2WBNJC2DCggDaSbxACQBtJAGkgDaSANpEfHKZu1JkB6s/a0sfcB0kAaSIcvNaXdlHYDaSANpIE0kAbSQNoYdhI2B0gn7CQWWbkHgLRdQMmnndpYhmZjduMgNQYsX1ChtDv9WGCxuVD8zUccEAddr1Bp2mTK4vGAZmPONY2DLvgJSHfhU96AbQTSdgEFpMMXJvXkmYw0GWky0mSkyUiTkSYjTUaajPQGgGPEXxJIj/gHNKqrB6SBtOVMJJBOz0BZjoPUiylAGkgDaSANpIE0kB5VtWzcegHpjdu3pl8ZSANpy4AC0kC6SQwAaSANpIE0kAbSQNo0fWo3Dkh37zMfyhYDaSANpMNXidJuSruBNJAG0kAaSANpID0UYrTqRYB0qz6u0VlZIG0XUBJlqY2maDZmNw5SY8DyBRVKu9OPBRabC8XfuMQBcdD1CpWmTaYsHg9oNkazsTqFAenRsWmr1gRI2wUUkA5fxdSTZzLSZKTJSJORJiNNRpqMNBlpMtKtosxQVhZID2U3du9FgDSQtpyJBNLpGSjLcZB6MQVIA2kgDaSBNJAG0t3zEJDu3mc+lC0G0kDaMqCANJBuEgNAGkgDaSANpIE0kB4KMVr1IkC6VR/X6KwskAbSQDp8HyntprQbSANpIA2kgTSQBtKj45TNWhMgvVl72tj7AGm7gJJQTW00RbMxu3GQGgOWL6hQ2p1+LLDYXCj+2iYOiIOuV6jQbMw5mo3RbKyOckDaGHA3a3OAtF1AAenwLUo9eSYjTUaajDQZaTLSZKTJSJORJiO9WQoZnfcB0qPzWbRqTYA0kLaciQTS6Rkoy3GQejEFSANpIA2kgTSQBtKtosxQVhZID2U3du9FgDSQtgwoIA2km8QAkAbSQBpIA2kgDaS75yEg3b3PfChbDKSBNJAOXyVKuyntBtJAGkgDaSANpIH0UIjRqhcB0q36uEZnZYG0XUBJlKU2mqLZmN04SI0ByxdUKO1OPxbQbMw5LqhwQcXqBRWajdFsTGK7aRyMjlo2bk2A9MbtW9OvDKTtAgpIh69uKqLISJORBlAAyiqg4olM6oU1LqjYvKDSFFAW44Cu3UC6DnZA2jR3N27jgDSQtpyJBNLpmUjLcZB6MQVIA2kgTWk3pd2UdlPavXHuGNVXBtKj+smM+HoBaSBtGVBAGkg3iQEgDaSBNJAG0kAaSI84XjZg9YD0BuzULrwkkAbSQDp80yntprQbSANpIA2kgTSQBtJdEFDvNgLp7n3mQ9liIG0XUBIgqePhaDZmNw5SY8DyBRVKu9OPBRbHRMZflsQBcdD1ChXGSNNsTL4DTeNgKOAY8RcB0iP+AY3q6gFpu4AC0uFbl3ryTEaajDQZaTLSZKTJSJORJiNNRnpU1bJx6wWkN27fmn5lIA2kLWcigXR6BspyHKReTAHSQBpIA2kgDaSBtGn61G4ckO7eZz6ULQbSQNoyoIA0kG4SA0AaSANpIA2kgTSQHgoxWvUiQLpVH9forCyQBtJAOnwfKe2mtBtIA2kgDaSBNJAG0qPjlM1aEyC9WXva2PsAabuAklBNbTRFszG7cZAaA5YvqFDanX4soNmYc1xQ4YKK1QsqTZtMWTweLC8vu6WlpaSz+UeePOdeeOVG0rKjstAzj+13s3dOrro6TeNgVLZtI9cDSG/k3jX82kDaLqCAdPjipiKKjDQZaQAFoKwCKp7GpF5YswiouA9SfydYPB40BZTFOADSdO2uYx2QNozdjdw0IA2kLWcigXR6JtJyHHT5xBlAFb9BiYP044FFQAHp5oCyGAdAunkcbKRDRuW1gfSofBItWw8gDaQtAwpIp584W44DAJUeBxZPnAFUcWJCRjq9SomMtM0KFSANpMlItwyro7y6QBpIWwYUkE4HlOU4ANLpcQCkGSMtxwLiwGYcUNrtHJAG0kB6lGXasnUD0kDaMqCAdDqgLMcBkE6PAwBlE1CU+FPiL3sASAPptcRBy2izptWltHtNu40nAWkgbRlQQDodUJbjAEinxwGQBtJkpMO5IaXdNisTyEg3v6DSBS0B6S58yhuwjUAaSFsGFJBOB5TlOADS6XEApG0Ciow0Gem1ZCItHg+ANJCmtHsDQNnVlwTSQNoyoIB0OqAsxwGQTo8DiyfO8fc7cUAcNPmdQEaajDTzSHdHR2Sku/NZD3VLgTSQtgyoJidNzCPNPNIWT5zJRJKJLJ800LWbrt3j4+PJ55EWL6yRkSYjTUY6+RDA/1mjKAAAHKpJREFUgoP2AJAG0kA6fEuANJAG0jYzUGSkizMBIA2kgfSyW1paGnR6rI+TkU7aTSYWIiO9yR/jiRMn3NzcXP6ujz/+eM8anDlzxj399NN9H3/22Wfd888/r4/v37/fHT58eJO3ILwdkLYLKPl8U0+a/vib192PfuG1LYnBtb7pfe+dcU89+s6BT08t5wTSQBpIA2k5oBAHxIHVOKBrN127JbabxsHAEy0DCwDpTfwQBcHve9/73OzsrL6roFpuEcMR0UeOHHH79u1zsvyLL77ojh49qstV/y3P37Vrlzt06NAmbgWQjjvbKqCAdPiEgfRk8nHF6gWV1BgAUADKKqDiQSD14qrFkt64D7p8PGgKKItxQGk3kK47KQLSyaeKw1/w9OnTTv5EKJ88eVLfpAzjY8eOuQMHDuif8s+y3Pz8vDt+/LiL8B7+GvZ/RTLSZKQlOqwCCkinVyVYjoMunzgDqOL3H3GQfjywCCgg3RxQFuMASDePg810yVa9F5Deqj3v31fg/MYbb+QZ6SqUZdVi1vnBBx+sRfMTTzzhDh48qNDezBuQBtKWAQWk00+cLccBgEqPA4snzgCqOKsgI51epWSxQoWMNKXdcjRoGgeb6ZKtei8gvUV7Po51Lo+RrkNxhPQ999yjY6er2Wcgnf4BMjbWue99z7T74qe/Y+BOSz1pIiNt94JKagwAacbGSgwAaeKAOAi/WoG0zeMBGWkgXXfyDKQHkmL4C1Qz0fEdRiEjffXqVffSSy+5e++9V/++9dZb9U/1vpsTO90PHDs//J2zga9477sn3U9/ZH7gtm3fvt29/PLL7u6779a/b7nlFrdz584V9/3F+Wn32G++sYFrPPyXvuddE+7ogfMDt2337t1JcfDShRn36K9dGv6KbuArEgfOpcSB9F+o++7X3Wc1DuR7X/fdr973W/9zu3vqjxY3MGqH/9Kf+vsT7jMP7Bp4rEuNA9kHX/rDt4e/ohv4ij/6DybdTx3cM/BYRxy8rP1YUo4HxMHLzuLx4EMf+pD75je/2fecsBobFuPgwx/+sPvLv/zLvueE5d8LP/yL33L/Y27bBh69hv/S/+kHF90Hv3P133kSB026tw9/LUfvFYH0Jn8mdeOg4yqMwhhpae1/7do1PVDI3/KFkT/V+95c2OYO/Py3N3nvre/tJCN9/JO7Bm6bXHW8ceOG27Fjh7t+/XpeylK970++teR+4lfbdTHhe75zyn3un986cNtmZmaS4uDr/3vR/Ysniy706/uENufZxIFzKXEwPT1d+92vOx5YjQM5Fsj2DjoePPnfr7kvPHd1cwJ4SO/yk/ffopAetG2pcfCF5950v/R77bqw+Oj371JID/qdRxxcd8TBNdflOJBzwoWFhb7nhNXfCxaPB3JO+Oabb/Y9Jyz/rvixL8y5r3+rXRcWf+3Te9x3v3Nq1d95EgdAuveXMJAe0klJystIY7FTp0656pRX8bl07U7Zi2tfhtJuSrsleoiDtDigtLvbYyLjkTY1DijttlnSSxwU5xxd7pnQdGysxeMBpd2UdtcJBEiv3WWNn1mdQ1peQEpBYtdu+TfzSDferclPAFBpgJIdmnryzBhpxkhLvFiNgy6fOAMoAFX+5Zr6O8EioOJ+6PLxAEjTbEy+B03jIPkEvcULAukWf3hbuep07bYLKCAdvlmpJ01W5xNPPXEG0mQiJQYAFHFAHITfHTQbs3k8ICMNpOvcBaS3UqMtfm8gDaQtAwpIp1clWI6D1IspFk+cyUiTkSYj3XuS1uXjQdNMpMULa0AaSAPpFsN11FYdSANpy4AC0kC6SQwAaZsZqPh7t8uA4oIKF1RkDwBpSrvXEgejZpeNWB8y0huxVzvwmkAaSAPp8EWntJsx0kAaSMuxgDggDqzGAZAG0kC6HndAugPo3YhNBNJ2ASXxkjo+1mqTqSbZSCANpAEUgLIKKDLSZKTXAihKu8+5F165sRGn3xv2ms88tt/N3jm56us3vaCyYSs7Qi8MpEfow2jTqgBpIE1Gmox0PGZZvaBCSW/6RTWLJ84xvokD4qDJxVWLF9aaAsri8YAx0s1L/NvkmrWuK5Be657r+POANJAG0kAaSIc9YPHEmUwkmcjyaU5qlZJFQHFBpTmgLMYBkG4eB12gEpDuwqe8AdsIpIE0kAbSQBpIxxiweOIMoIqTByCdPiWixQtrZKQZIy1Hg6ZxsAH8GLmXBNIj95G0Y4WANJAG0kAaSANpIF38zrYIKCoTqExYC6AsXlgjIw2k64QGpNvh1pFbSyANpIE0kAbSQBpIA+nyCYpFQFGZ0BxQFuMASDePg5HDywasEJDegJ3ahZcE0kAaSANpIA2kgTSQBtK9Z30WKxOalvQCabp2d8FCso1Auiuf9JC3E0gDaSANpIE0kAbSQBpIA+nqKSaQBtJDZsfIvhyQHtmPZrRXDEgDaSANpIE0kAbSQBpIA2kg3bsHHnkSSI+2Yoa3dkB6ePuyU68EpIE0kAbSQBpIA2kgDaSBNJAG0p1CUGljgXRXP/l1bjeQBtJAGkgDaSANpIE0kAbSQBpIr5MVrX06kG7tR7e1Kw6kgTSQBtJAGkgDaSANpIE0kAbSW6uSrXt3IL11+77V7wykgTSQBtJAGkgDaSANpIE0kAbSrUbNOlYeSK9j53X5qUAaSANpIA2kgTSQBtJAGkgDaSDdVRMB6a5+8uvcbiANpIE0kAbSQBpIA2kgDaSBNJBeJyta+3Qg3dqPbmtXHEgDaSANpIE0kAbSQBpIA2kgDaS3ViVb9+5Aeuv2favfGUgDaSANpIE0kAbSQBpIA2kgDaRbjZp1rDyQXsfO6/JTgTSQBtJAGkgDaSANpIE0kAbSQLqrJgLSXf3k17ndQBpIA2kgDaSBNJAG0kAaSANpIL1OVrT26UC6tR/d1q44kAbSQBpIA2kgDaSBNJAG0kAaSG+tSrbu3YH01u37Vr8zkAbSQBpIA2kgDaSBNJAG0kAaSLcaNetYeSC9jp3X5acCaSANpIE0kAbSQBpIA2kgDaSBdFdNBKS7+smvc7uBNJAG0kAaSANpIA2kgTSQBtJAep2saO3TgXRrP7qtXXEgDaSBNJAG0kAaSANpIA2kgTSQ3lqVbN27A+mt2/etfmcgDaSBNJAG0kAaSANpIA2kgTSQbjVq1rHyQHodO+//b+/+Xe0o2gCOL9FKMIggWKUQsRACFhYigqAIVpaKja0odioIFiFFKi0FSSGWEksLsdG/IIUgSAq1sLIQCwvRTubCXPZuZs/OZn/MTPZz4eU1957deZ7vM/vsfM/Z3XPkTYk0kSbSRJpIE2kiTaSJNJEm0kT6qE5EpI9a+YV5E2kiTaSJNJEm0kSaSBNpIk2kifRCrWh2cyLdbOnKBk6kiTSRJtJEmkgTaSJNpIk0kSbSZa2k3OhEuhz7pkcm0kSaSBNpIk2kiTSRJtJEmkgT6aalZkHwRHoBvCNvSqSJNJEm0kSaSBNpIk2kiTSRJtJHdSIifdTKL8ybSBNpIk2kiTSRJtJEmkgTaSJNpBdqRbObE+lmS1c2cCJNpIk0kSbSRJpIE2kiTaSJNJEuayXlRifS5dg3PTKRJtJEmkgTaSJNpIk0kSbSRJpINy01C4In0gvgHXlTIk2kiTSRJtJEmkgTaSJNpIk0kT6qExHpo1Z+Yd5EmkgTaSJNpIk0kSbSRJpIE2kivVArmt2cSDdburKBE2kiTaSJNJEm0kSaSBNpIk2kiXRZKyk3OpEux77pkYk0kSbSRJpIE2kiTaSJNJEm0kS6aalZEDyRXgDvyJsSaSJNpIk0kSbSRJpIE2kiTaSJ9FGdiEgftfIL8ybSRJpIE2kiTaSJNJEm0kSaSBPphVrR7OZEutnSlQ2cSBNpIk2kiTSRJtJEmkgTaSJNpMtaSbnRiXQ59k2PTKSJNJEm0kSaSBNpIk2kiTSRJtJNS82C4In0AnhH3pRIE2kiTaSJNJEm0kSaSBNpIk2kj+pERPqolV+YN5Em0kSaSBNpIk2kiTSRJtJEmkgv1IpmNyfSzZaubOBEmkgTaSJNpIk0kSbSRJpIE2kiXdZKyo1OpMuxb3pkIk2kiTSRJtJEmkgTaSJNpIk0kW5aahYET6QXwDvypkSaSBNpIk2kiTSRJtJEmkgTaSJ9VCci0ket/MK8iTSRJtJEmkgTaSJNpIk0kSbSRHqhVjS7OZFutnRlAyfSRJpIE2kiTaSJNJEm0kSaSBPpslZSbnQiXY590yMTaSJNpIk0kSbSRJpIE2kiTaSJdNNSsyB4Ir0A3pE3JdJEmkgTaSJNpIk0kSbSRJpIE+mjOhGRPmrlF+ZNpIk0kSbSRJpIE2kiTaSJNJEm0gu1otnNiXSzpSsbOJEm0kSaSBNpIk2kiTSRJtJEmkiXtZJyoxPpcuybHplIE2kiTaSJNJEm0kSaSBNpIk2km5aaBcET6QXwjrwpkSbSRJpIE2kiTaSJNJEm0kSaSB/ViYj0USu/MG8iTaSJNJEm0kSaSBNpIk2kiTSRXqgVzW5OpJstXdnAiTSRJtJEmkgTaSJNpIk0kSbSRLqslZQbnUiXY9/0yESaSBNpIk2kiTSRJtJEmkgTaSLdtNQsCJ5IL4B35E2JNJEm0kSaSBNpIk2kiTSRJtJE+qhORKSPWvmFeRNpIk2kiTSRJtJEmkgTaSJNpIn0Qq1odnMi3WzpygZOpIk0kSbSRJpIE2kiTaSJNJEm0mWtpNzoRLoc+6ZHJtJEmkgTaSJNpIk0kSbSRJpIE+mmpWZB8ER6Abwjb0qkiTSRJtJEmkgTaSJNpIk0kSbSR3UiIn3Uyi/Mm0gTaSJNpIk0kSbSRJpIE2kiTaQXakWzmxPpZktXNnAiTaSJNJEm0kSaSBNpIk2kiTSRLmsl5UYn0uXYNz0ykSbSRJpIE2kiTaSJNJEm0kSaSDctNQuCJ9IL4B15UyJNpIk0kSbSRJpIE2kiTaSJNJE+qhMR6aNWfmHeRJpIE2kiTaSJNJEm0kSaSBNpIr1QK5rdnEg3W7qygRNpIk2kiTSRJtJEmkgTaSJNpIl0WSspNzqRLse+6ZGJNJEm0kSaSBNpIk2kiTSRJtJEummpWRA8kV4Ar8Smd+7c6W7dunU+9LVr10qE0RFpIk2kiTSRJtJEmkgTaSJNpIl0ERmpYFAiXUERckOIEv3uu+92jz32WPftt992P//8c/fBBx/k7mK11xFpIk2kiTSRJtJEmkgTaSJNpIn0aoLR2I6IdEMF++qrr86iffPNN8+j/vTTT7vnn3/+7H97/hBpIk2kiTSRJtJEmkgTaSJNpIn0ng5S01hEuqZqTMSSkuabN292ly9fviDXe6REpIk0kSbSRJpIE2kiTaSJNJEm0nu4R41jEOkaqzIS0/Xr17tXXnnlwqfPa4v07du3u48++qh76KGHuv/++6+7dOlS98ADD3T//vvvYX4Xcg659xkc7XdHq3kq36PVPJWveXDprAfqB8c6B+gH6XmvH+gHR1wT6gcX5/2NGze6q1evNmRP24ZKpLflu+re9/hE+tdff+2+/PLL7uGHH+7++eef7sEHHzwT6fDffoeBeeBY0A/0ROcF50brA2ska8JjrgnD7aVXrlxZ1W9a3hmRbqh6Nd0j3RA2oSKAAAIIIIAAAggggAACqxIg0qvi3HZnNT21e9tM7R0BBBBAAAEEEEAAAQQQqJcAka63NsnIavke6cawCRcBBBBAAAEEEEAAAQQQWI0AkV4NpR0hgAACCCCAAAIIIIAAAggcgQCRPkKV5YgAAggggAACCCCAAAIIILAaASK9Gko7QgABBBBAAAEEEEAAAQQQOAIBIn2EKssRAQQQQAABBBBAAAEEEEBgNQJEejWUdoQAAggggAACCCCAAAIIIHAEAkT6CFWWIwIIIIAAAggggAACCCCAwGoEiPRqKO0IAQQQQAABBBBAAAEEEEDgCASI9BGqLEcEEEAAAQQQQAABBBBAAIHVCBDp1VDaEQIIIIAAAggggAACCCCAwBEIEOkjVFmOCCCAAAIIIIAAAggggAACqxEg0quhtKM+gbfffvv8n5cvX+4++eSTuwDduHGj+/33389+/8wzz3TvvPPOhdd8/vnn3Y8//nj2u9dff717+eWX79pHzjglKvPTTz91n3322fnQqfzCH/vxp3L88MMPu7///vtsP9evX+8ef/zxkwzCH2/evFki5bvGvHXrVvfDDz+c/z6V35DTMMc//viju3bt2tk+xuZRf+A4Z8ZY7Q0mh0H/Nakcv//+++7rr78ePU7CH/rzJOb43nvvdVevXt075ZPH+dg8nmKQ0wuGx9OpvrE3lJw+NdUPp3pBf/t+fleuXOk+/vjjvVO+MN6e/bA/V0IQtRwHOb1grX7Yn2811D9OhuEcTfXpqV6w1lwqdUDkMJjqBTlzaapflMp/2KfvdX2YwzGn727JIWf8NWo9ZJHqeaEvPvXUU8l1dJgr77//fnJ9uSWf+2XfRPp+qWRFeYSDsi/O4d+PPPLIhcVcOPAfffTRc3kOr3niiSfukukoUmOSOTVOCSwh5i+++OI835jDSy+91L3xxhvnIYUmG/M6lWcUqdSiI3DsL5JTrEswCDH/+eef5/nGHPoNPi6IYl6n8gwngd9++y35hkzMry+cNYh0DoOwILp9+/Z5XqfyHDtGoki/+uqryZNkifrHMUM+L7zwwrnQR8npv9mTy+DUMTJ2jJXMPY69Zj88dYykcg1jl54Xe/bDML/++uuv854YhaP0m4s5vWCtfhjOK/1zzfBcW+qYWKMXrD2X9maRw2BqbZQzl4bnxBrOh2v2wxyOOX13y/rnjL9GrUOPe/rpp0fPsYFVWGuHn/C6b775pnvuuefO1gohxrfeeuvsd2EdGXpHTXNly/qsuW8ivSZN+0oSGC5mhguGsFFcIA4XPKcWz8PBalk0pSCEhhl+ovQO5SH8bbgIvJeT4dg+apiaOQu80NifffbZC284RDanRLo/T8Knt7WeDIYM+m+mhDxjHql3lFsU6eG8i8d+P79cBqd6Qc3zfqpPzemHc0Q69Jhffvml+KfRe/bD0GeffPLJ8/4R2ZYW6RSDLfph6jwaj5vaeuKSXtDnueTcWvq8OGQwpxf0Yx/OpXtZO5RisWR9GGNOzaWpvrt3vmvkGWIeq/Ww5sM3q8Pfw/ngtddeu3ClWjh+wu/CFZQ19sm963Qv4xHpe6Fmm1kEhp+ypSRybJE8R6RzPrWcFfiKLx5KUOpTgrFFcu7iOedksmJKs3aVquNQoE4J81Rto4C/+OKLZ5eC17Zo7EtyvAohtWgKrxsT5vtBpIdzeQ6DqatTUm/AzJqkO714ST/M7QW1ylNEvFU/jIvV+EbNUKx3KvHkMFv1w7E3pFO9djLIjV+wpBf0Q1sylzZOcXL3QwZz1kZx5/d6NdtkcDu9YEk/HMrjqfP+1Bpi63TXyDNnPZwS7VNX68WrxHJunduaUav7J9KtVq6RuFMH/lhDS53scxpHSlJqwpNa/KakaEwqphbPNd8LFeswrPlYXVMLiVOCHf8W/j/cY1+zQAwZjNV17FLMKZGO99LXfEIc5jCHwaleEHvHd999d/5MgbHnEpTsDUv74VQv6B9v4XK+/q0kJfPuj711P+wvGseerVGaxVb9MM6v/tyPC+XaWCzpBacEas65tfQ8GMY6Z200dm6dOtZK59wff2k/jPs6dW6sYX24Vp5j82PqGSLh/Bg+bQ5rzHgZd+DS/3dYe4WfGs8ZNc3ZVCxEuvYKNRzf2H2Lc04WOSJd8/2RqXuDQ0nnnOxzF8+pRVQN0yd1X+xaIh3YBHmK98rXKtIpBnMkcmzOpOob31ip7TKt1P37cxhMiXRgET+RqPFYWKMf5vSCmi9n3rof9t+Ii8dBbW+obNkP+9IQe0MQ6HC7S00ivbQXhNzWmEslz48pBnPWRiH21FxqRaTX6IfxvDh8Bk9K1ofPqNmr9mvlOVXr/psK4b9TD/jdK+ejjUOkj1bxnfI9teidc/nSlEhP/X2ndJPDnFr0bnFpd39xUculzacup1rj0u6xJxUHFqVOnMPJMMZgzmXNc0S6xmNi7BODOQymRHooCqUv5Ust5lIyM6cf5oj02HMGSvbCqd60Rj+M86N///2YbJVisXU/TOWV4lIq/1N9bE4vWOvcWorDWD+c0wty+ltOvyjBYK31YYufREfea9c67rfG83+JObbnmER6T9oHGWvqQJ7zQI1T+5oapyTuqRPYVg8bmxp3TyZTJ/rU4vleHzYW8xpbjO2Zd3+sKQa5D9qaI9LhtTXdEzm12MllcOp4T90LW8sDyKb61Jx+OHV8j90jW2r+x3Gn4l6jH44d+7UcC1O9YIt+GPiP3S5TYk6s0QvWnEu1McjtBVNzKfe4K5H/Wv1wai5NjbN17lPjr11rIr11Rcf3T6TLsb9vR05dsjRMNvXY/9TDgk41o5xxSkDOvdQ89fVXqac1n1o4BAb9S3jCPmv43tCcT4LGvu4ldUly7sKhJpHOYZD66qf+1/f05+/UwiG+Nl4CVsNVCTmXo+UyONULhnWfWsTs2Rdy+lRuP5ySiFq+6qjPd69+mLqcPz58rPSxkNMLtuyHNVzWvUYvWHsu7dkHwlg5DKZ6Qc5cqlmk1+iHORxzxtmy/jnjr1HrwKL/FZPxKr3abu3aknXpfRPp0hW4z8aPJ7pUWsMDe+qL6MM+xhbEc8bZG3H/YTf9sVOCG8Q3/owtdqYWz/191CDR/QXDkP3wcuu4eIyvG1vwtijS/QeA9DkMGcTFfnjNqQeFjYl06lio5STafxBen8HwDaMcBlNyPJxLNcjDnD6V0w9zekENefdrvWc/TPEuLdF798PhMZd6c3bvc2IYb41esPZc2ptDLoNTvSD3vBJym+oXe+e/Vj+c4jhnnC0YzBl/jVoPb3Gr5fy/Bdsa90mka6yKmBBAAAEEEEAAAQQQQAABBKolQKSrLY3AEEAAAQQQQAABBBBAAAEEaiRApGusipgQQAABBBBAAAEEEEAAAQSqJUCkqy2NwBBAAAEEEEAAAQQQQAABBGokQKRrrIqYEEAAAQQQQAABBBBAAAEEqiVApKstjcAQQAABBBBAAAEEEEAAAQRqJECka6yKmBBAAAEEEEAAAQQQQAABBKolQKSrLY3AEEAAAQQQQAABBBBAAAEEaiRApGusipgQQAABBBBAAAEEEEAAAQSqJUCkqy2NwBBAAAEEEEAAAQQQQAABBGokQKRrrIqYEEAAAQQQQAABBBBAAAEEqiVApKstjcAQQAABBBBAAAEEEEAAAQRqJECka6yKmBBAAAEEEEAAAQQQQAABBKolQKSrLY3AEEAAAQQQQAABBBBAAAEEaiRApGusipgQQAABBBBAAAEEEEAAAQSqJUCkqy2NwBBAAAEEEEAAAQQQQAABBGokQKRrrIqYEEAAAQQQQAABBBBAAAEEqiVApKstjcAQQAABBBBAAAEEEEAAAQRqJECka6yKmBBAAAEEEEAAAQQQQAABBKolQKSrLY3AEEAAAQQQQAABBBBAAAEEaiRApGusipgQQAABBBBAAAEEEEAAAQSqJUCkqy2NwBBAAAEEEEAAAQQQQAABBGokQKRrrIqYEEAAAQQQQAABBBBAAAEEqiVApKstjcAQQAABBBBAAAEEEEAAAQRqJECka6yKmBBAAAEEEEAAAQQQQAABBKolQKSrLY3AEEAAAQQQQAABBBBAAAEEaiRApGusipgQQAABBBBAAAEEEEAAAQSqJUCkqy2NwBBAAAEEEEAAAQQQQAABBGoksESk/wcPeM4sfqPalQAAAABJRU5ErkJggg==" /></p>
<p><a href="https://www.statista.com/statistics/263979/global-cattle-population-since-1990/">https://www.statista.com/statistics/263979/global-cattle-population-since-1990/</a></p>
<p>Rice growing and ruminant agriculture at least have signaled awareness and taken some potentially corrective action.    In ominous contrast, the fossil fuel sector acknowledges no such constraints and projects steeply increasing annual withdrawals of natural gas for years to come.</p>
<p>&nbsp;</p>
<p>&nbsp;</p>
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		<title>Ecosystem Services at Anchorage Farm</title>
		<link>https://www.anchorageromneys.com/2023/10/ecosystem-services-at-anchorage-farm/</link>
		<comments>https://www.anchorageromneys.com/2023/10/ecosystem-services-at-anchorage-farm/#comments</comments>
		<pubDate>Fri, 06 Oct 2023 17:02:12 +0000</pubDate>
		<dc:creator>Stephen Shafer</dc:creator>
				<category><![CDATA[Uncategorized]]></category>

		<guid isPermaLink="false">http://www.anchorageromneys.com/?p=2088</guid>
		<description><![CDATA[                                                                                               Ecosystem Services at Anchorage Farm The Millennium Ecosystem Assessment (MA), a major UN-sponsored effort to analyze the impact of human actions on ecosystems and human well-being, identified four major categories of ecosystem services: provisioning, regulating, cultural and supporting services. 1. Provisioning Services When people are asked to identify a service provided by nature, most [...]]]></description>
				<content:encoded><![CDATA[<p>                                                                                         <span style="font-size: medium;">      Ecosystem Services at Anchorage Farm</span></p>
<p><span style="background-color: #ccffcc;">The Millennium Ecosystem Assessment (MA), a major UN-sponsored effort to analyze the impact of human actions on ecosystems and human well-being, identified four major categories of ecosystem services: provisioning, regulating, cultural and supporting services.</span></p>
<p><span style="background-color: #ccffcc;">1. Provisioning Services</span><br /><span style="background-color: #ccffcc;"> When people are asked to identify a service provided by nature, most think of food. Fruits, vegetables, trees, fish, and livestock are available to us as direct products of ecosystems. A provisioning service is any type of benefit to people that can be extracted from nature. Along with food, other types of provisioning services include drinking water, timber, wood fuel, natural gas, oils, plants that can be made into clothes and other materials, and medicinal benefits.</span></p>
<p><span style="background-color: #ccffcc;">2. Regulating Services</span><br /><span style="background-color: #ccffcc;"> Ecosystems provide many of the basic services that make life possible for people. Plants clean air and filter water, bacteria decompose wastes, bees pollinate flowers, and tree roots hold soil in place to prevent erosion. All these processes work together to make ecosystems clean, sustainable, functional, and resilient to change. A regulating service is the benefit provided by ecosystem processes that moderate natural phenomena. Regulating services include pollination, decomposition, water purification, erosion and flood control, and carbon storage and climate regulation.</span></p>
<p><span style="background-color: #ccffcc;">3. Cultural Services</span><br /><span style="background-color: #ccffcc;"> As we interact and alter nature, the natural world has in turn altered us. It has guided our cultural, intellectual, and social development by being a constant force present in our lives. The importance of ecosystems to the human mind can be traced back to the beginning of mankind with ancient civilizations drawing pictures of animals, plants, and weather patterns on cave walls. A cultural service is a non-material benefit that contributes to the development and cultural advancement of people, including how ecosystems play a role in local, national, and global cultures; the building of knowledge and the spreading of ideas; creativity born from interactions with nature (music, art, architecture); and recreation.</span></p>
<p><span style="background-color: #ccffcc;">4. Supporting Services</span><br /><span style="background-color: #ccffcc;"> The natural world provides so many services, sometimes we overlook the most fundamental. Ecosystems themselves couldn&#8217;t be sustained without the consistency of underlying natural processes, such as photosynthesis, nutrient cycling, the creation of soils, and the water cycle. These processes allow the Earth to sustain basic life forms, let alone whole ecosystems and people. Without supporting services, provisional, regulating, and cultural services wouldn&#8217;t exist.</span></p>
<p>               In regard to Anchorage Farm, the easiest dimension of the above four to pin down is <span style="text-decoration: underline;">Provisioning.</span> (Caution! the term “extracted from nature” in that paragraph strikes a sour note.) Our farm grows sheep that will go directly into food channels; also, sheep that will grow elsewhere before entering food channels; and purebred sheep for breeding.  We sell wool to a specialty mill.</p>
<p>            Of the <span style="text-decoration: underline;">regulating</span> services described above, our farm uses no chemical herbicides and no neonicotinoids, which makes it a good space for pollinators such as bees, wasps, butterflies and flies.  We have observed and documented over a hundred species of native plants (trees and wildflowers) in the woods, in pastures and their edges, and around the dwellings. There is also a thriving population of non-native plants considered invasive such as Autumn olive or Purple loosestrife that pollinators frequent.  We are working to supplant non-native invasives with natives that keep a better balance. Milkweeds abound for benefit of Monarch butterflies (which to everyone’s dismay are scarce here).  The <a href="https://www.inaturalist.org/projects/anchorage-farm-saugerties">Anchorage Farm Saugerties Project at i Naturalist.org</a> gives a pictorial convenience sample of what grows and lives here.</p>
<p>            The roots of trees on the rocky limestone slopes stabilize and reciprocally nourish soil through their roots.  Their fallen leaves armor the soil against splash erosion, which helps to stem sheet and rill erosion that worsen old gullies and lead to new ones. We have partly filled some pre-existing gullies with wood from fallen trees and branches.  Loss of soil from unwooded slopes is minimized by a year-round cover of perennial grasses, forbs, and herbaceous vines (some of which are invasive non-natives like Black swallow-wort).</p>
<p>            The meandering Sawyer Kill erodes its banks every day, more when in spate after heavy rains. Year after year we see tree roots along the stream getting exposed, and big trees in the water. The best strategy is to keep planting trees, shrubs and smaller plants along the banks.  That all new plantings should be native is now our rule. It’s not that native plants hang onto soil better than non-natives, but they provide food for insects that the aliens don’t.</p>
<p>            Carbon sequestration in the woodlands and grasslands of this farm, estimated by simple models (link to GHG accounting essay) roughly balances GHG emissions. In a micro-cosmic way this contributes to climate stabilization, if not improvement.  We found good soil here when we came and work to keep its carbon level high, improving it if possible.  Good soil is a precious resource fast disappearing from the earth.</p>
<p>            <a href="https://www.soilassociation.org/staff-bios/graham-harvey/">Graham Harvey</a> writes in <span style="text-decoration: underline;">The Forgiveness of Nature</span> (Jonathan Cape, 2001)</p>
<p><em>Grasslands are the unsung purifiers of the earth’s atmosphere. Everyone acknowledges the role of forests in cleaning up the air and stabilizing climate systems, but grasslands store as much carbon in the organic matter of their soils as temperate forests and far more than tropical rain forests.  Every acre of park, every patch of green space between city buildings, every sunlit meadow is contributing to the survival of the planet, taking in carbon from the atmosphere and locking up some of it safely in the soil.</em></p>
<p>Harvey’s rhapsody is accurate as to storage <i>in soil </i>worldwide<i>, </i>though hectare for hectare forests store more total carbon (including above ground vegetation) in each of the three strata of latitude.  <a href="https://netedu.xauat.edu.cn/sykc/hjx/content/ckzl/5/10.pdf">https://netedu.xauat.edu.cn/sykc/hjx/content/ckzl/5/10.pdf</a></p>
<p>For a more quantitative appraisal of grassland see Bai and Cotrufo Grassland Soil Carbon sequestration: Current understanding, challenges, and solutions Science 2022 <a href="https://www.science.org/doi/10.1126/science.abo2380">https://www.science.org/doi/10.1126/science.abo2380</a></p>
<p><span style="text-decoration: underline;">Culturally</span>, this small farm is  inspired by the work and writings of Sir Albert Howard; Robert Elliott, author of the <a href="https://www.soilandhealth.org/wp-content/uploads/GoodBooks/The%20Clifton%20Park%20System%20of%20Farming.pdf">Clifton Park System of Farming</a>; Sir R. George Stapledon (1882-1960); Beatrix Potter; Henry Beston; Chauncey Stillman (American supporter of the <a href="https://www.soilassociation.org">Soil Association</a>); Wendell Berry;  Charles Massy; James Rebanks.   We strive to keep their practices and their ethics.</p>
<p>            Go back now to the six major services mentioned on the web site home page.</p>
<ul>
<li>carbon drawdown through woodlands and grassland soil</li>
<li>encouraging biodiversity, with priority to native biota</li>
<li>safe space for pollinators</li>
<li>production of high-quality high-protein food</li>
<li>production of high-quality natural fiber–wool</li>
<li>preservation and improvement of healthy soil, “the gift of good land” (Wendell Berry)</li>
</ul>
<p>If farming ceased here and the pastures filled in with locally prevalent invasive trees, grasses, forbs and vines (irresponsible “rewilding”), only the first of the services above would continue apace mostly courtesy of the arriving trees.  Biodiversity declines, however,  where  everything is woodland. It is greater where woodland and grassland, however weedy, coexist.</p>
<p>If farming ended but existing pastures were mowed once a year, the first three services named above could abide.  If we got rid of livestock, giving the pastures over to a mix of organically-grown tree nuts, lentils and small grains, the first four services would be kept. [None of the three crops provides a complete protein, but they can when combined.] Fertilizer would have to be brought in.</p>
<p>Only with sheep on grass pastures, however, could all six services be delivered in a complete circle centered on good soil.</p>
<p>                                                                                                                      “To me, this is all”</p>
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		<title>Book review: Apocalypse Never</title>
		<link>https://www.anchorageromneys.com/2021/03/book-review-apocalypse-never/</link>
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		<pubDate>Tue, 16 Mar 2021 20:25:02 +0000</pubDate>
		<dc:creator>Stephen Shafer</dc:creator>
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		<description><![CDATA[ Review by Stephen Shafer of  Apocalypse never:  why environmental alarmism hurts us all by Michael Shellenberger   New York, Harper 2020      Michael Shellenberger can’t be dismissed as a standard-issue climate change denier.  He acknowledges scientific evidence that average global surface air temperature is going up.    He recognizes that fossil fuels under human control have had, [...]]]></description>
				<content:encoded><![CDATA[<div><span style="font-size: medium;"> Review by Stephen Shafer of</span></div>
<div><span style="font-size: medium;"> <span style="text-decoration: underline;">Apocalypse never:  why environmental alarmism hurts us all</span> by Michael Shellenberger   New York, Harper 2020</span></div>
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<p><span style="font-size: medium;">     Michael Shellenberger can’t be dismissed as a standard-issue climate change denier.  He acknowledges scientific evidence that average global surface air temperature is going up.    He recognizes that fossil fuels under human control have had, and still have, a big role in that rise.  He does deny, however, that efforts to radically lower CO2 emissions in the next few years are justified.  He argues that the rate of change in air and sea surface temperature and the effects of that change are greatly exaggerated by “apocalyptic environmentalists.” The exaggerations, in his opinion, are fomented by persons phobic and confused about nuclear fission; indifferent to poverty in the developing world; and, he speculates, using maladaptive defense mechanisms against an unconscious death wish for humanity.   </span></p>
<p><span style="font-size: medium;">     Shellenberger’s be-all and end-all is continued economic development for the whole world, with the lion’s share to lower-income countries.  This is constrained of course by resources and sinks.  A good ideal fifty years ago, it is incompatible now with what most climate scientists say must be done to arrest global warming unless methods of energy conversion can be deployed that don’t release greenhouse gases (GHGs).   The author allows that renewables (principally wind and solar with some hydro) are good on GHGs but argues they can’t power the scope of development he calls for.  Consequently, he stakes everything instead on the “peaceful atom” or in some situations, natural gas.  Anyone who says “No Nukes” or “Leave it in the Ground” or “Circular Economy” or (worse yet) cites Garrett Hardin’s lifeboat analogy must in Shellenberger’s  view be irrational about  nuclear power or care nothing for  people in  low-income regions or both.  The introduction (p. xiii) sets out the dialectic thus: “[The book] makes the moral case for humanism, of both secular and religious variant, against the anti-humanism of apocalyptic environmentalism.”</span></p>
<p><span style="font-size: medium;">     Near the book’s ending (p. 270) the author uses “if” and “might” to make his polarities look subtle.  The implication is not lost.  He writes<br /></span></p>
<p><span style="font-family: Arial, Helvetica, sans-serif; font-size: medium;">If the climate apocalypse is a kind of subconscious fantasy for people who dislike civilization, it might help explain why the people who are the most alarmist about environmental problems are also the most opposed to the technologies capable of addressing them, from fertilizer and flood control to natural gas and nuclear power.</span></p>
<p><span style="font-size: medium;">     The “environmental problems” Shellenberger refers to are not limited to rising global surface temperature and its sequelae, To him, a worse environmental problem is low potential for rapid economic development  in much of the world.   For that problem his practicable solution is processes extant now that can convert one form of energy to another very rapidly in a small space.   Prime among these is “atoms for peace.” (p. 280)  A distant second is natural gas.</span></p>
<p><span style="font-size: medium;">     The author can’t see a rational basis for anyone’s opposing nuclear fuels as a solution to both widespread poverty and long-lived atmospheric pollutants like CO2 and N2O; so, he psychoanalyzes the opposition.  He presents his finding not as a declarative nor (as in the excerpt above) in hypothetical “if … might” terms, but as a rhetorical question ripe for a “yes” answer. “Could a similar hatred of human civilization, and perhaps of humanity itself, be behind claims of environmental apocalypse?” (p. 270)  Shellenberger conjures up   from Ernest Becker’s “denial of death” his personal  insight that “apocalyptic environmentalists,” especially  those who act out die-ins and carry pretend coffins, have an exaggerated fear of death, stoked  because the prognosis for life on earth as we know it looks worse to them than to the him.  Indeed, he regards “apocalyptic environmentalists” as “lost souls” who believe the false doctrine that emissions of GHGs are now a net detriment to the living earth and who “derive psychological benefits from climate alarmism.” (272) .  The authors writes<br /></span></p>
<p><span style="font-family: Arial, Helvetica, sans-serif; font-size: medium;">Young people learning about climate change for the first time might understandably believe, upon listening to [Sarah] Lunnon {of Extinction Rebellion] and [Greta] Thunberg, that climate change is the result of deliberate, malevolent actions. In reality, it is the opposite.   Emissions are a by-product of energy consumption, which has been necessary to people to lift themselves, their families and their societies out of poverty, and achieve human dignity.  Given that’s what climate activists have been taught to believe, it’s understandable that so many of them would be so angry. (272)</span></p>
<p><span style="font-size: medium;">     Whose reality, please? Most people would agree that the industrial revolution did not begin with a plan to heat up the planet. Most “apocalyptic environmentalists” will concede that we would not live as we do now without a lot of fossil fuel burnt or processed in the past.  That said, nearly all climate activists, even those not engaged with Extinction Rebellion, do believe that energy buyers and sellers in the last fifty years have <span style="text-decoration: underline;">knowingly</span> encouraged the release of now intolerable quantities of GHGs to the atmosphere in pursuit of corporate profits. This has been deliberate. <i>vide</i> <a href="https://iopscience.iop.org/article/10.1088/1748-9326/aa815f/pdf">Supran and Oreskes</a>, 2017  Whether it’s malevolent or just reckless endangerment  is a matter of opinion.  </span></p>
<p><span style="font-size: medium;">     Three pages later, Shellenberger reprises the defense of economic development as practiced around the world.</span></p>
<p><span style="font-family: Arial, Helvetica, sans-serif; font-size: medium;">The picture promoted by apocalyptic environmentalists is inaccurate and dehumanizing.  Humans are not unthinkingly destroying nature.  Climate change, deforestation, plastic waste and species extinction are not, fundamentally, consequences of greed and hubris but rather side effects of economic development motivated by a humanistic desire to improve peoples’ lives. (275)</span></p>
<p><span style="font-size: medium;">     This is humanistwashing,  Shellenberger’s own  variant of greenwashing.  Oil companies like Shell, Exxon, Texaco and Chevron were not motivated by humanistic desire when they plundered Nigeria and Equatorial Guinea and Ecuador.  See <span style="text-decoration: underline;">Crude World</span> by Peter Maas</span></p>
<p><span style="font-size: medium;">     The author contrasts activists people motivated by anger in what’s to him a fallacious cause with those called  to what he sees as the authentic cause of civil rights.  (273)</span></p>
<p><span style="font-family: Arial, Helvetica, sans-serif; font-size: medium;">As such, when we hear activists, journalists, IPCC scientists and others claim climate change will be apocalyptic unless we make immediate, radical changes including massive reductions in energy consumption, we might consider whether they are motivated by love for humanity of something closer to its opposite (275)</span></p>
<p><span style="font-size: medium;">     In summary, Shellenberger believe that activists who say that to be recognizable and stable thirty years hence the world must reduce CO2 emissions radically without relying more on nuclear fuels are lost souls following false gods.  For a rebuttal much better than I can do,  let&#8217;s turn to the  words of  someone who may be thought by atheists or adherents of non-Abrahamic religions  to serve a false god, but by few humans a lost soul: His Holiness, Pope Francis  in the 2015 encyclical <a href="http://www.vatican.va/content/francesco/en/encyclicals/documents/papa-francesco_20150524_enciclica-laudato-si.html"><i>Laudato Si</i></a> .  I call your attention especially to paragraphs 59, 104 and 161 among those reprinted here (italics added).<br /></span></p>
<p><span style="font-size: medium;"><em>59. At the same time we can note the rise of a false or superficial ecology which bolsters complacency and a cheerful recklessness. As often occurs in periods of deep crisis which require bold decisions, we are tempted to think that what is happening is not entirely clear. Superficially, apart from a few obvious signs of pollution and deterioration, things do not look that serious, and the planet could continue as it is for some time. Such evasiveness serves as a licence to carrying on with our present lifestyles and models of production and consumption. This is the way human beings contrive to feed their self-destructive vices: trying not to see them, trying not to acknowledge them, delaying the important decisions and pretending that nothing will happen</em>.</span></p>
<p><span style="font-size: medium;"> </span></p>
<p><span style="font-size: medium;">66. The creation accounts in the book of Genesis contain, in their own symbolic and narrative language, profound teachings about human existence and its historical reality. They suggest that human life is grounded in three fundamental and closely intertwined relationships: with God, with our neighbour and with the earth itself. According to the Bible, these three vital relationships have been broken, both outwardly and within us. This rupture is sin. The harmony between the Creator, humanity and creation as a whole was disrupted by our presuming to take the place of God and refusing to acknowledge our creaturely limitations. This in turn distorted our mandate to “have dominion” over the earth (cf. <i>Gen </i>1:28), to “till it and keep it” (<i>Gen </i>2:15). As a result, the originally harmonious relationship between human beings and nature became conflictual (cf. <i>Gen </i>3:17-19). It is significant that the harmony which Saint Francis of Assisi experienced with all creatures was seen as a healing of that rupture. Saint Bonaventure held that, through universal reconciliation with every creature, Saint Francis in some way returned to the state of original innocence.<a href="http://www.vatican.va/content/francesco/en/encyclicals/documents/papa-francesco_20150524_enciclica-laudato-si.html#_ftn40">[40]</a> This is a far cry from our situation today, where sin is manifest in all its destructive power in wars, the various forms of violence and abuse, the abandonment of the most vulnerable, and attacks on nature.</span></p>
<p><span style="font-size: medium;"> </span></p>
<p><span style="font-size: medium;">67. We are not God. The earth was here before us and it has been given to us. This allows us to respond to the charge that Judaeo-Christian thinking, on the basis of the Genesis account which grants man “dominion” over the earth (cf. <i>Gen </i>1:28), has encouraged the unbridled exploitation of nature by painting him as domineering and destructive by nature. This is not a correct interpretation of the Bible as understood by the Church. Although it is true that we Christians have at times incorrectly interpreted the Scriptures, nowadays we must forcefully reject the notion that our being created in God’s image and given dominion over the earth justifies absolute domination over other creatures. The biblical texts are to be read in their context, with an appropriate hermeneutic, recognizing that they tell us to “till and keep” the garden of the world (cf. <i>Gen </i>2:15). “Tilling” refers to cultivating, ploughing or working, while “keeping” means caring, protecting, overseeing and preserving. This implies a relationship of mutual responsibility between human beings and nature. Each community can take from the bounty of the earth whatever it needs for subsistence, but it also has the duty to protect the earth and to ensure its fruitfulness for coming generations. “The earth is the Lord’s” (<i>Ps</i> 24:1); to him belongs “the earth with all that is within it” (<i>Dt </i>10:14). Thus God rejects every claim to absolute ownership: “The land shall not be sold in perpetuity, for the land is mine; for you are strangers and sojourners with me” (<i>Lev</i> 25:23).</span></p>
<p><span style="font-size: medium;"> </span></p>
<p><em><span style="font-size: medium;">104. Yet it must also be recognized that nuclear energy, biotechnology, information technology, knowledge of our DNA, and many other abilities which we have acquired, have given us tremendous power. More precisely, they have given those with the knowledge, and especially the economic resources to use them, an impressive dominance over the whole of humanity and the entire world. Never has humanity had such power over itself, yet nothing ensures that it will be used wisely, particularly when we consider how it is currently being used. We need but think of the nuclear bombs dropped in the middle of the twentieth century, or the array of technology which Nazism, Communism and other totalitarian regimes have employed to kill millions of people, to say nothing of the increasingly deadly arsenal of weapons available for modern warfare. In whose hands does all this power lie, or will it eventually end up? It is extremely risky for a small part of humanity to have it</span></em></p>
<p><span style="font-size: medium;"> </span></p>
<p><span style="font-size: medium;"><em>106. The basic problem goes even deeper: it is the way that humanity has taken up technology and its development</em> <i>according to an undifferentiated and one-dimensional paradigm</i>. <em>This paradigm exalts the concept of a subject who, using logical and rational procedures, progressively approaches and gains control over an external object. This subject makes every effort to establish the scientific and experimental method, which in itself is already a technique of possession, mastery and transformation. It is as if the subject were to find itself in the presence of something formless, completely open to manipulation. Men and women have constantly intervened in nature, but for a long time this meant being in tune with and respecting the possibilities offered by the things themselves. It was a matter of receiving what nature itself allowed, as if from its own hand. Now, by contrast, we are the ones to lay our hands on things, attempting to extract everything possible from them while frequently ignoring or forgetting the reality in front of us. Human beings and material objects no longer extend a friendly hand to one another; the relationship has become confrontational. This has made it easy to accept the idea of infinite or unlimited growth, which proves so attractive to economists, financiers and experts in technology. It is based on the lie that there is an infinite supply of the earth’s goods, and this leads to the planet being squeezed dry beyond every limit. It is the false notion that “an infinite quantity of energy and resources are available, that it is possible to renew them quickly, and that the negative effects of the exploitation of the natural order can be easily absorbed”.<a href="http://www.vatican.va/content/francesco/en/encyclicals/documents/papa-francesco_20150524_enciclica-laudato-si.html#_ftn86">[86]</a></em></span></p>
<p><span style="font-size: medium;">113. There is also the fact that people no longer seem to believe in a happy future; they no longer have blind trust in a better tomorrow based on the present state of the world and our technical abilities. There is a growing awareness that scientific and technological progress cannot be equated with the progress of humanity and history, a growing sense that the way to a better future lies elsewhere. This is not to reject the possibilities which technology continues to offer us. But humanity has changed profoundly, and the accumulation of constant novelties exalts a superficiality which pulls us in one direction. It becomes difficult to pause and recover depth in life. If architecture reflects the spirit of an age, our megastructures and drab apartment blocks express the spirit of globalized technology, where a constant flood of new products coexists with a tedious monotony. Let us refuse to resign ourselves to this, and continue to wonder about the purpose and meaning of everything. Otherwise we would simply legitimate the present situation and need new forms of escapism to help us endure the emptiness.</span></p>
<p><span style="font-size: medium;"> </span></p>
<p><span style="font-size: medium;">161. Doomsday predictions can no longer be met with irony or disdain. We may well be leaving to coming generations debris, desolation and filth. The pace of consumption, waste and environmental change has so stretched the planet’s capacity that our contemporary lifestyle, unsustainable as it is, can only precipitate catastrophes, such as those which even now periodically occur in different areas of the world. The effects of the present imbalance can only be reduced by our decisive action, here and now. We need to reflect on our accountability before those who will have to endure the dire consequences.</span></p>
<p><span style="font-size: medium;"> </span></p>
<p><span style="font-size: medium;">171. The strategy of buying and selling “carbon credits” can lead to a new form of speculation which would not help reduce the emission of polluting gases worldwide. This system seems to provide a quick and easy solution under the guise of a certain commitment to the environment, but in no way does it allow for the radical change which present circumstances require. Rather, it may simply become a ploy which permits maintaining the excessive consumption of some countries and sectors.</span></p>
<p><span style="font-size: medium;"> </span></p>
<p><span style="font-size: medium;">225. On the other hand, no one can cultivate a sober and satisfying life without being at peace with him or herself. An adequate understanding of spirituality consists in filling out what we mean by peace, which is much more than the absence of war. Inner peace is closely related to care for ecology and for the common good because, lived out authentically, it is reflected in a balanced lifestyle together with a capacity for wonder which takes us to a deeper understanding of life. Nature is filled with words of love, but how can we listen to them amid constant noise, interminable and nerve-wracking distractions, or the cult of appearances? Many people today sense a profound imbalance which drives them to frenetic activity and makes them feel busy, in a constant hurry which in turn leads them to ride rough-shod over everything around them. This too affects how they treat the environment. An integral ecology includes taking time to recover a serene harmony with creation, reflecting on our lifestyle and our ideals, and contemplating the Creator who lives among us and surrounds us, whose presence “must not be contrived but found, uncovered”.</span></p>
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