diff --git a/week5/community-contributions/day3 - vectorizing_subtitles_from_llm_engineering.ipynb b/week5/community-contributions/day3 - vectorizing_subtitles_from_llm_engineering.ipynb
index 5076f8f..5ce3eba 100644
--- a/week5/community-contributions/day3 - vectorizing_subtitles_from_llm_engineering.ipynb	
+++ b/week5/community-contributions/day3 - vectorizing_subtitles_from_llm_engineering.ipynb	
@@ -24,7 +24,7 @@
   },
   {
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-   "execution_count": 62,
+   "execution_count": 63,
    "id": "ba2779af-84ef-4227-9e9e-6eaf0df87e77",
    "metadata": {},
    "outputs": [],
@@ -39,7 +39,7 @@
   },
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+   "execution_count": 64,
    "id": "802137aa-8a74-45e0-a487-d1974927d7ca",
    "metadata": {},
    "outputs": [],
@@ -59,7 +59,7 @@
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+   "execution_count": 65,
    "id": "58c85082-e417-4708-9efe-81a5d55d1424",
    "metadata": {},
    "outputs": [],
@@ -72,7 +72,7 @@
   },
   {
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-   "execution_count": 42,
+   "execution_count": 66,
    "id": "ee78efcb-60fe-449e-a944-40bab26261af",
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    "outputs": [],
@@ -85,7 +85,7 @@
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-   "execution_count": 43,
+   "execution_count": 67,
    "id": "730711a9-6ffe-4eee-8f48-d6cfb7314905",
    "metadata": {},
    "outputs": [],
@@ -143,7 +143,7 @@
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+   "execution_count": 68,
    "id": "7310c9c8-03c1-4efc-a104-5e89aec6db1a",
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    "outputs": [],
@@ -154,7 +154,7 @@
   },
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-   "execution_count": 45,
+   "execution_count": 69,
    "id": "cd06e02f-6d9b-44cc-a43d-e1faa8acc7bb",
    "metadata": {},
    "outputs": [
@@ -164,7 +164,7 @@
        "217"
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-     "execution_count": 45,
+     "execution_count": 69,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -175,7 +175,7 @@
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-   "execution_count": 46,
+   "execution_count": 70,
    "id": "2c54b4b6-06da-463d-bee7-4dd456c2b887",
    "metadata": {},
    "outputs": [
@@ -215,7 +215,7 @@
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-   "execution_count": 47,
+   "execution_count": 71,
    "id": "78998399-ac17-4e28-b15f-0b5f51e6ee23",
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@@ -233,7 +233,7 @@
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-   "execution_count": 48,
+   "execution_count": 72,
    "id": "763e51ff-5787-4a56-8176-36b7c5796fe3",
    "metadata": {},
    "outputs": [],
@@ -246,7 +246,7 @@
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-   "execution_count": 49,
+   "execution_count": 73,
    "id": "99fe3a37-480f-4d55-be48-120588d5846b",
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    "outputs": [
@@ -267,7 +267,7 @@
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   {
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-   "execution_count": 50,
+   "execution_count": 74,
    "id": "057868f6-51a6-4087-94d1-380145821550",
    "metadata": {},
    "outputs": [
@@ -308,7 +308,7 @@
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   {
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-   "execution_count": 51,
+   "execution_count": 75,
    "id": "cfb855dc-1610-4aaf-8e5f-68c26ce640a5",
    "metadata": {},
    "outputs": [],
@@ -323,7 +323,7 @@
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-   "execution_count": 58,
+   "execution_count": 76,
    "id": "b98adf5e-d464-4bd2-9bdf-bc5b6770263b",
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@@ -340,7 +340,7 @@
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+   "execution_count": 77,
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",
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interface.\\nBut fi...\",\"Video: 60617163\\u003cbr\\u003eText: And already that wraps up day two.\\nNow that you have built that solution.\\nAnd congratulations on tha...\",\"Video: 60616423\\u003cbr\\u003eText: So I hope you've just enjoyed yourself experimenting with different LMS locally on your box using th...\",\"Video: 59170227\\u003cbr\\u003eText: Welcome back to Google Colab.\\nHere we are ready to explore the wonderful world of Tokenizers.\\nSo, uh...\",\"Video: 59169985\\u003cbr\\u003eText: So I hope you enjoyed that whirlwind tour of Google Colab.\\nHere's just a little screenshot example o...\",\"Video: 60616927\\u003cbr\\u003eText: It's time for our first LM experiment at this point.\\nSo some of this you may know well, you may know...\",\"Video: 59673721\\u003cbr\\u003eText: And here we are in JupyterLab for the last time, and we are looking here at day five, the last day\\no...\",\"Video: 59508055\\u003cbr\\u003eText: I'm so very happy that you've reached this epic moment in the course and that you're hanging in ther...\",\"Video: 59670259\\u003cbr\\u003eText: It's remarkable.\\nBut you are now at the 95% point.\\nThere's 5% remaining of this course.\\nUh, maybe it...\",\"Video: 60616623\\u003cbr\\u003eText: So we're now going to start week one of the course when we are going to be looking at exploring fron...\",\"Video: 59472383\\u003cbr\\u003eText: And welcome back to the week six folder.\\nWe're now at day two, which is the second and final stage o...\",\"Video: 59670171\\u003cbr\\u003eText: So as the very final step on this part four of day two of week eight, we are now going to build an\\ne...\",\"Video: 59297721\\u003cbr\\u003eText: And so now the time has come to talk about the most crucial aspect of Rag, which is the idea of vect...\",\"Video: 59297599\\u003cbr\\u003eText: Well, that was a sneaky detour I took you on in the last one.\\nI hope you enjoyed it though, and I ho...\",\"Video: 59507635\\u003cbr\\u003eText: Look, I hope you're excited.\\nYou really should be.\\nYou've been through 80% of the course and it's al...\",\"Video: 59669375\\u003cbr\\u003eText: Here we are for the day.\\n2.1 notebook.\\nAnd don't let it be said that I don't ever do anything for yo...\",\"Video: 59297733\\u003cbr\\u003eText: Welcome back to JupyterLab and welcome to your first experiment with the world of Long Chain.\\nLet me...\",\"Video: 59670369\\u003cbr\\u003eText: It is terrific that you're hanging on in there and making such great progress with this course.\\nAs w...\",\"Video: 59166281\\u003cbr\\u003eText: And with that, amazingly, you completed day one of week two already and that gets you to the 15% poi...\",\"Video: 59671567\\u003cbr\\u003eText: Well, the first thing you're going to notice is that I don't have a notebook open for you.\\nAnd that'...\",\"Video: 59297593\\u003cbr\\u003eText: And welcome to continuing our journey with Hrag.\\nAnd today it's time to unveil Liang Chen.\\nSo first,...\",\"Video: 59166461\\u003cbr\\u003eText: And welcome back to the lab.\\nHere we are in Jupyter Lab and we are going to go into week two.\\nAnd we...\",\"Video: 59167007\\u003cbr\\u003eText: Well, how fabulous is that?\\nI hope that you are as wowed as I am by our new airline, I assistant and...\",\"Video: 59508121\\u003cbr\\u003eText: The moment has arrived.\\nHere we go.\\nWe're in fine tuning.\\nWe do fine tuning.\\nTrain.\\nThere is also a ...\",\"Video: 59295579\\u003cbr\\u003eText: All right.\\nAre you excited to see how this goes?\\nLet's give it a try.\\nSo in this next section, I cre...\",\"Video: 60620375\\u003cbr\\u003eText: And with that, we've reached an important milestone.\\nThe first week of our eight week journey is com...\",\"Video: 59472491\\u003cbr\\u003eText: Welcome back.\\nIf you are following along with me in JupyterLab, as I hope you are, then you will nee...\",\"Video: 59472425\\u003cbr\\u003eText: Welcome to week six, day three.\\nToday is going to be a day that you will either love or you will hat...\",\"Video: 59508057\\u003cbr\\u003eText: Actually slight change in plan.\\nI'm going to wrap up the day.\\nDay three at this point, and say that ...\",\"Video: 60619577\\u003cbr\\u003eText: And for the final piece of background information, I wanted to take another moment to talk about API...\",\"Video: 59170291\\u003cbr\\u003eText: Welcome back to Colab and welcome back to our business project.\\nSo again our assignment, we are due ...\",\"Video: 60619651\\u003cbr\\u003eText: I mentioned before an AI company called vellum.\\nWhen we were talking about the different questions, ...\",\"Video: 59473191\\u003cbr\\u003eText: And you thought we'd never get here.\\nHere we are in Jupyter Lab, running our fine tuning for a front...\",\"Video: 59170297\\u003cbr\\u003eText: And here we are in Google Colab, ready for fun with models.\\nSo first we do the usual Pip installs an...\",\"Video: 59167015\\u003cbr\\u003eText: Welcome back to Jupyter Lab and welcome to Day Five's Lab.\\nAnd this is going to be lots of creativit...\",\"Video: 59170043\\u003cbr\\u003eText: Let me enthusiastically welcome you all back to week three of our LLM engineering journey.\\nIf you en...\",\"Video: 59473147\\u003cbr\\u003eText: Well, I'm very relieved.\\nI've got that behind me.\\nNo more human testing for me.\\nWe'll have one final...\",\"Video: 59166453\\u003cbr\\u003eText: Welcome back and welcome to our continuing JupyterLab experience.\\nUh, I'm hopefully going to keep yo...\",\"Video: 59166915\\u003cbr\\u003eText: Welcome back to the wonderful world of JupyterLab.\\nAnd here we are in week two.\\nDay three.\\nUh, bring...\",\"Video: 59667365\\u003cbr\\u003eText: Here we are back in Colab, looking at the week seven, day five of the Colab notebooks and I'm on a\\nT...\",\"Video: 60616845\\u003cbr\\u003eText: We're on the home stretch.\\nThis is the final step in the environment setup, and it's an easy one.\\nIt...\",\"Video: 59295459\\u003cbr\\u003eText: And welcome back to More Leaderboard Fest as we go through some more leaderboards.\\nBut this time we'...\",\"Video: 59471979\\u003cbr\\u003eText: So we now turn to the parts of the problem, which is perhaps, let's say, not as glamorous as some\\nof...\",\"Video: 59503705\\u003cbr\\u003eText: And so now we talk about quantization the q and q Laura.\\nQ stands for quantized quantized.\\nLaura.\\nAn...\",\"Video: 59472505\\u003cbr\\u003eText: So the good news is that this is the very final video about data set curation.\\nYou were probably fed...\",\"Video: 59669217\\u003cbr\\u003eText: And welcome to the next part of visualizing the data.\\nAnd just very quickly to show it to you in 3D....\",\"Video: 59671221\\u003cbr\\u003eText: I gotta tell you, I don't like to toot my horn a whole lot, but I do think that I've done a great\\njo...\",\"Video: 59503703\\u003cbr\\u003eText: Well.\\nHello there everybody.\\nI am so grateful that you've made it through to the start of week seven...\",\"Video: 59473201\\u003cbr\\u003eText: Well, before we do a postmortem on what happened, let's just quickly look at the standing the rankin...\",\"Video: 60622463\\u003cbr\\u003eText: In this video, we're going to set up a full data science environment for Mac users.\\nIn the next vide...\",\"Video: 60619299\\u003cbr\\u003eText: Well, I hope you found that both educational and enjoyable.\\nAs we went through and learned so much a...\",\"Video: 59295607\\u003cbr\\u003eText: So to revisit then the solution that we built in the previous day and talk about the metrics.\\nAs I s...\",\"Video: 59297575\\u003cbr\\u003eText: Well, welcome to the final part on rag.\\nAnd this is the session where you go from being a rag expert...\",\"Video: 59507687\\u003cbr\\u003eText: It's time for action, everybody.\\nWe've set up our colab.\\nHere we are, week seven, day three.\\nWe've g...\",\"Video: 59671441\\u003cbr\\u003eText: And welcome once more to our favorite place to be Jupyter Lab, the Paradise for a data scientist exp...\",\"Video: 59673431\\u003cbr\\u003eText: And here we have it.\\nThe user interface is completed.\\nThe extra notification came through on my phon...\",\"Video: 59473137\\u003cbr\\u003eText: Let's get straight to it.\\nSo the place where you can see everything that's going on and get knee dee...\",\"Video: 59166421\\u003cbr\\u003eText: Welcome back to the radio day in the lab.\\nMore to do.\\nLet's keep going.\\nWhere we left off is we had ...\",\"Video: 59295599\\u003cbr\\u003eText: Welcome to the Jupyter Lab for day four.\\nIt's going to look very familiar because it's actually I've...\",\"Video: 59669631\\u003cbr\\u003eText: Here we are in our favorite place to be in JupyterLab, ready for some coding and a lot of coding tha...\",\"Video: 59673663\\u003cbr\\u003eText: But wait, there's more.\\nWe need to add some more to the user interface just to make it look more coo...\",\"Video: 59506929\\u003cbr\\u003eText: And we return to the hugging face open LLM leaderboard.\\nThe first place you go when selecting your b...\",\"Video: 59504785\\u003cbr\\u003eText: So at this point we're going to talk about hyperparameters.\\nAnd we're going to introduce three of th...\",\"Video: 59505337\\u003cbr\\u003eText: So we're now going to look at four bit quantization, the rather remarkable effect of reducing the pr...\",\"Video: 59271655\\u003cbr\\u003eText: So here we are on Hugging Face's main landing page at Hugging Face Core.\\nA URL you know.\\nWell, since...\",\"Video: 59472883\\u003cbr\\u003eText: Okay, time to reveal the results.\\nIt has run to completion.\\nAnd here it is.\\nSo a moment to pause.\\nIt...\",\"Video: 59673639\\u003cbr\\u003eText: And welcome now to the code for our user interface, which we will find in this Python module.\\nPrice ...\",\"Video: 59472463\\u003cbr\\u003eText: So last time we looked at a humble linear regression model with feature engineering, and now we say\\n...\",\"Video: 59297595\\u003cbr\\u003eText: So by the time you're watching this, hopefully you have played yourself with vectors.\\nYou've created...\",\"Video: 60619149\\u003cbr\\u003eText: So we're going to start our exploration into the world of frontier models by playing with the famous...\",\"Video: 59297735\\u003cbr\\u003eText: And at last the time has come to see rag in action.\\nAfter all of this talk, and here we are.\\nWe're i...\",\"Video: 60616407\\u003cbr\\u003eText: And now over to my Mac people.\\nAnd I have news for you.\\nIt's exactly the same thing.\\nYou go to a fav...\",\"Video: 59170235\\u003cbr\\u003eText: So here we are in Google Colab for our first collaborative session on the cloud using a GPU box.\\nOn ...\",\"Video: 59472067\\u003cbr\\u003eText: So we've covered steps 1 to 4 of the five step strategy.\\nAnd that brings us to step five, which is p...\",\"Video: 59472011\\u003cbr\\u003eText: Welcome everybody.\\nSo in the past I've said quite a few times, I am excited to start this this week ...\",\"Video: 59295553\\u003cbr\\u003eText: Welcome back.\\nIn the last part, we gave our GPT four and clawed the challenge of converting a simple...\",\"Video: 59297773\\u003cbr\\u003eText: Well, I hope you're eager with anticipation for this session in JupyterLab as we finally get to see\\n...\",\"Video: 59295583\\u003cbr\\u003eText: And here we are back in JupyterLab.\\nIt's been a minute.\\nWe've been working in Colab for last week, a...\",\"Video: 59507329\\u003cbr\\u003eText: Okay.\\nIt's moment of truth time.\\nI have just taken our class tester.\\nYou remember this class?\\nUh, it...\",\"Video: 59295429\\u003cbr\\u003eText: Continuing our investigation of benchmarks, and this will become more real when we actually see some...\",\"Video: 60595637\\u003cbr\\u003eText: Here we are back in the Colab, which has been running overnight for me and probably for you too, I\\nh...\",\"Video: 59668027\\u003cbr\\u003eText: And so here we are at the home page for modal.\\nAt modal.com spelt model not not model which is confu...\",\"Video: 59295527\\u003cbr\\u003eText: I'm so happy to welcome you to week four, day four on our journey to LLM Engineering and Mastery.\\nHe...\",\"Video: 59295377\\u003cbr\\u003eText: Just before we go on to some of the more advanced metrics, I want to mention for a second something\\n...\",\"Video: 59666211\\u003cbr\\u003eText: So before we try our new model and one more recap on the models so far and keep notes of this so we\\n...\",\"Video: 59170107\\u003cbr\\u003eText: And once again, it's that moment when you take a pause and congratulate yourself on another day of\\ns...\",\"Video: 60616833\\u003cbr\\u003eText: So I realized that day one of week one has been a pretty long day, and I assure you that the other,\\n...\",\"Video: 59472413\\u003cbr\\u003eText: Wonderful.\\nWhere we left off is we had just created the Get Features function, which builds our feat...\",\"Video: 59297561\\u003cbr\\u003eText: And would you believe at this point you're 55% of the way along the journey?\\nUh, it's been a while s...\",\"Video: 59669211\\u003cbr\\u003eText: Well, we took on a lot today and we seem to have been successful.\\nThese red icons that you see on th...\",\"Video: 59166981\\u003cbr\\u003eText: Welcome to week two, day five.\\nThe last day of week two where a lot is coming together.\\nI am so grat...\",\"Video: 60619227\\u003cbr\\u003eText: And now let's move to Claude from anthropic, my favorite model and typically the favorite model of\\nm...\",\"Video: 60620395\\u003cbr\\u003eText: Welcome back to Jupyter Lab, where I want to show you the assignment, the homework exercise for you\\n...\",\"Video: 59665127\\u003cbr\\u003eText: Well hi there everybody.\\nI'm not going to give you my usual song and dance about how excited you are...\",\"Video: 59668923\\u003cbr\\u003eText: Well, welcome back to Jupyter Lab for what will be an epic finale to our time in this platform.\\nAnd ...\",\"Video: 59504887\\u003cbr\\u003eText: Well, here we are again in Google Colab.\\nIt's been a minute since we were here, and welcome back to ...\",\"Video: 59170165\\u003cbr\\u003eText: Welcome, everybody to the last day of week three.\\nWeek three.\\nDay five.\\nWe're here already wrapping ...\",\"Video: 60617251\\u003cbr\\u003eText: Congratulations are definitely in order.\\nYesterday was a mammoth first day on this course and you go...\",\"Video: 59166951\\u003cbr\\u003eText: All right, back to the lab.\\nBack to our project.\\nTime to work with tools.\\nI am in the week two folde...\",\"Video: 60619619\\u003cbr\\u003eText: Well, day four was an information dense day.\\nI do hope that you learned some something useful here, ...\",\"Video: 60616663\\u003cbr\\u003eText: Well.\\nHi there, this is time for PC people to get set up.\\nSo all you Mac people out there, you don't...\",\"Video: 59508175\\u003cbr\\u003eText: So I'm taking a moment now to explain that the training costs of optimizing a model for this course\\n...\",\"Video: 59670087\\u003cbr\\u003eText: And welcome to part four of day two of week eight.\\nUh, there's a lot happening this week, and I have...\",\"Video: 59506713\\u003cbr\\u003eText: Hi everyone.\\nSo the reason I'm so fired up about week seven is that this is the time when we actuall...\",\"Video: 60620169\\u003cbr\\u003eText: Hopefully you found this super satisfying to be able to have this nice business result and have it c...\",\"Video: 59295435\\u003cbr\\u003eText: Well, just before we wrap up, let me introduce this week's challenge and talk about what we're going...\",\"Video: 59297609\\u003cbr\\u003eText: Last week, we worked with models that were able to speed up code by a factor of 60,000 times, which\\n...\",\"Video: 59507489\\u003cbr\\u003eText: Continuing our adventure through hyperparameters for training.\\nThe next one is pretty crucial and it...\",\"Video: 59295549\\u003cbr\\u003eText: And welcome back to our challenge again.\\nAnd this time we are working with our beautiful prototype.\\n...\",\"Video: 59665129\\u003cbr\\u003eText: And now let me make this real for you by showing you some, some diagrams, particularly now looking\\na...\",\"Video: 59169991\\u003cbr\\u003eText: Okay, so that was your introduction to Hugging Face.\\nAnd now I'm going to turn to a different resour...\",\"Video: 59472027\\u003cbr\\u003eText: And now the time has come to curate our data set.\\nAnd the way we're going to do this is we're going ...\",\"Video: 59472307\\u003cbr\\u003eText: Welcome to week six.\\nDay two a day.\\nWhen we get back into the data, we look back in anger at our dat...\",\"Video: 59508289\\u003cbr\\u003eText: So here we are now, back in the Colab, in the same one that we kicked off in the previous day.\\nIt's ...\",\"Video: 59472333\\u003cbr\\u003eText: Thank you for putting up with me during my foray into traditional machine learning.\\nI think it was u...\",\"Video: 59295431\\u003cbr\\u003eText: Now I want to take a quick moment to give you a flyby of five different ways that llms are used comm...\",\"Video: 59673449\\u003cbr\\u003eText: Well, I have to tell you that I'm a little bit sad.\\nThis is the beginning of the beginning of the en...\",\"Video: 59669389\\u003cbr\\u003eText: Well.\\nHi there.\\nSo you've made it to day two of week eight, and I am super grateful that you've been...\",\"Video: 59170057\\u003cbr\\u003eText: And so at the beginning of this week, we started by talking about hugging face pipelines.\\nAnd you us...\",\"Video: 59166949\\u003cbr\\u003eText: Welcome back to making chatbots.\\nLet's keep going.\\nSo for the next part we're going to beef up the s...\",\"Video: 59473019\\u003cbr\\u003eText: Welcome back to an action packed time of of training.\\nSo now, after waiting about five minutes when ...\",\"Video: 59297585\\u003cbr\\u003eText: Before we move on, let me show you one more time this fabulous slide that describes the simple three...\",\"Video: 59170255\\u003cbr\\u003eText: And welcome back to us continuing our journey through the model class in Hugging Face Transformers l...\",\"Video: 60614589\\u003cbr\\u003eText: So we're now going to run a large language model directly on your box using a platform called llama,...\",\"Video: 59297601\\u003cbr\\u003eText: I'm not going to lie, at this point you have every reason to be impatient with me.\\nWe've been yammer...\",\"Video: 60616629\\u003cbr\\u003eText: And welcome back to team PC and Team Mac as we come back together again for a quick video.\\nIn this o...\",\"Video: 59297749\\u003cbr\\u003eText: It's always welcome back to JupyterLab, my favorite place to be.\\nAnd now we are, of course in the we...\",\"Video: 59170135\\u003cbr\\u003eText: Welcome.\\nIt's week three.\\nIt's day four.\\nWe are back on the adventure in open source land, back inve...\",\"Video: 59472017\\u003cbr\\u003eText: And this is the first time that we'll be coding against our big project of the course.\\nWelcome to Ju...\",\"Video: 59507017\\u003cbr\\u003eText: Welcome to Colab.\\nWelcome to the week seven day two Colab.\\nAnd just before we try our base model, we...\",\"Video: 60619883\\u003cbr\\u003eText: And now we've arrived at an exciting moment in our first week.\\nThe conclusion of the first week is w...\",\"Video: 59508297\\u003cbr\\u003eText: What more is there to say, really?\\nTomorrow is the day for results.\\nA day that very excited indeed a...\",\"Video: 60619247\\u003cbr\\u003eText: We're going to spend a little bit more time with GPT just to try out a few more interesting things.\\n...\",\"Video: 59504769\\u003cbr\\u003eText: Without further ado, we're going to get stuck into it.\\nTalking about Laura.\\nLow rank adaptation.\\nAnd...\",\"Video: 59170233\\u003cbr\\u003eText: Welcome back to our continued exploits with Tokenizers.\\nWhat we're now going to look at is what's ca...\",\"Video: 59671231\\u003cbr\\u003eText: And here we are back in the Jupyter Lab for the fast approaching conclusion with a really great proj...\",\"Video: 60620397\\u003cbr\\u003eText: Well, that's a fantastic result to have now arrived towards the end of week one and having completed...\",\"Video: 59170093\\u003cbr\\u003eText: I'm delighted to see you again.\\nAs we get started with day three of week three of our adventure and ...\",\"Video: 59473089\\u003cbr\\u003eText: Welcome back.\\nSo hopefully you are still impressed by the GPT four mini results.\\nThe frontier model ...\",\"Video: 60395261\\u003cbr\\u003eText: Let's keep going with our project to equip our LM with a tool.\\nWe just created this piece of code to...\",\"Video: 60617259\\u003cbr\\u003eText: I'm excited to introduce you to your first exercise, and I'm looking forward to seeing what you make...\",\"Video: 59507313\\u003cbr\\u003eText: And it's this time again, when we look at the podium of how our models are performing across the boa...\",\"Video: 60619721\\u003cbr\\u003eText: Now it's time to talk for a minute about tokens.\\nTokens are the individual units which get passed in...\",\"Video: 59295451\\u003cbr\\u003eText: I know that everybody.\\nIt seems like just the other day that we were embarking on our quest together...\",\"Video: 59166919\\u003cbr\\u003eText: And with that, it concludes our session on tools.\\nAnd at this point, you are probably an expert on t...\",\"Video: 59295441\\u003cbr\\u003eText: Okay, so welcome to our leaderboard fast as we go through a ton of essential leaderboards for your\\nc...\",\"Video: 59295541\\u003cbr\\u003eText: And welcome back.\\nYou've just seen GPT four zero spectacularly failed to work on our hard Python con...\",\"Video: 59473101\\u003cbr\\u003eText: Welcome back.\\nSo about ten minutes later, maybe 15 minutes later, the run has completed.\\nAnd how do ...\",\"Video: 59507423\\u003cbr\\u003eText: So you may remember eons ago when we were building our data set.\\nAt the end of that, we uploaded our...\",\"Video: 59295545\\u003cbr\\u003eText: I really hope you've enjoyed this week.\\nWe've got tons done.\\nWe've experimented with all sorts of ne...\",\"Video: 59472503\\u003cbr\\u003eText: Welcome back to Jupyter Lab.\\nLast time, we looked at some silly models for predicting the price of p...\",\"Video: 60614591\\u003cbr\\u003eText: The mantra of this course is that the best way to learn is by doing, and we will be doing stuff toge...\",\"Video: 59473021\\u003cbr\\u003eText: Welcome to our favorite place to be to JupyterLab.\\nHere we are again now in day three.\\nIn week six.\\n...\",\"Video: 60617255\\u003cbr\\u003eText: I'm now going to talk for a bit about models.\\nA term you often hear is the term frontier models, whi...\",\"Video: 59667829\\u003cbr\\u003eText: Well.\\nHello there.\\nLook, I know what you're thinking.\\nYou're thinking I peaked too early.\\nLast week ...\",\"Video: 59505329\\u003cbr\\u003eText: Welcome back.\\nYou may, like me, have just gone off and got a coffee while things loaded back up agai...\",\"Video: 59669049\\u003cbr\\u003eText: So what you just saw was an ephemeral app, as it's called, which means just a temporary app that you...\",\"Video: 60619439\\u003cbr\\u003eText: This now brings us to an extremely important property of LMS called the context window that I want t...\",\"Video: 59668181\\u003cbr\\u003eText: And so it gives me great pleasure to introduce to you the project that I've lined up for you this we...\",\"Video: 59472441\\u003cbr\\u003eText: Welcome back.\\nSo we've been doing the thoroughly distasteful, unsavory work of feature engineering.\\n...\",\"Video: 59507785\\u003cbr\\u003eText: Well, I'm sure you're fed up of me saying that the moment of truth has arrived, but it really has.\\nT...\",\"Video: 59295587\\u003cbr\\u003eText: When I left you, we had just created this simple user interface for converting from Python to C plus...\",\"Video: 59166465\\u003cbr\\u003eText: Welcome back to the JupyterLab on Gradio day, so you'll remember where we left off.\\nWe'd written two...\",\"Video: 59473071\\u003cbr\\u003eText: Hey, gang.\\nLook, I know what you're thinking.\\nThis week was supposed to be training week.\\nI set it a...\",\"Video: 59295423\\u003cbr\\u003eText: Welcome to day two of week four, when we get more into leaderboards so that by the end of this, you'...\",\"Video: 59297723\\u003cbr\\u003eText: So I know what you're thinking.\\nYou're thinking, what's going on here?\\nWe're on day five.\\nWe're on d...\",\"Video: 59166947\\u003cbr\\u003eText: Well, thank you for coming along for week two, day four.\\nWe have lots of good stuff in store today.\\n...\",\"Video: 59666831\\u003cbr\\u003eText: Take one more moment to look at this very nice diagram that lays it all out, and we will move on.\\nNo...\",\"Video: 59295493\\u003cbr\\u003eText: And welcome to week four, day three.\\nAs we are about to embark upon another business project which w...\",\"Video: 60616855\\u003cbr\\u003eText: Now I know what you're thinking.\\nWe've been building environments for so long.\\nAre we not done yet?\\n...\",\"Video: 59506611\\u003cbr\\u003eText: So in a future day, I'm going to be training, fine tuning a model and creating a fine tuned model.\\nA...\",\"Video: 60616493\\u003cbr\\u003eText: I'll just take a quick moment to introduce myself to convince you that I am actually qualified to be...\",\"Video: 59166317\\u003cbr\\u003eText: And welcome to week two, day two, as we continue our adventure into the realm of LMS.\\nUh, so today, ...\",\"Video: 59295439\\u003cbr\\u003eText: So I'm aware that there's a big risk that you are getting fed up of leaderboards, because we've done...\",\"Video: 59472421\\u003cbr\\u003eText: And welcome back to our final time in Jupyter Lab with traditional machine learning.\\nIt's almost ove...\",\"Video: 59472137\\u003cbr\\u003eText: Well, well, well, it's been a long day, but congratulations, you've made it.\\nWe've gone through and ...\",\"Video: 59297693\\u003cbr\\u003eText: So at the end of each week, it's customary for me to give you a challenge, an assignment to do on\\nyo...\",\"Video: 60620143\\u003cbr\\u003eText: So we're going to make a call to GPT four.\\nOh, that's going to ask it to look through a set of links...\",\"Video: 60619501\\u003cbr\\u003eText: I welcome to day four of our time together.\\nThis is a very important day.\\nToday we're going to be lo...\",\"Video: 59297743\\u003cbr\\u003eText: And welcome to day five.\\nFor reals.\\nWe're actually in the proper Jupyter notebook.\\nThis time we're i...\",\"Video: 59166847\\u003cbr\\u003eText: Well, they say that time flies when you're having fun, and it certainly feels like time is flying.\\nU...\",\"Video: 59170223\\u003cbr\\u003eText: Well.\\nFantastic.\\nIt's coming up to the end of the week, and that means it's coming up to a challenge...\",\"Video: 59170037\\u003cbr\\u003eText: So how does it feel to be 30% of the way down the journey to being a proficient LLM engineer?\\nTake a...\",\"Video: 59295609\\u003cbr\\u003eText: You must be feeling absolutely exhausted at this point.\\nAnd if you are, that is okay.\\nYou have done ...\",\"Video: 60619281\\u003cbr\\u003eText: Well, I'm delighted to welcome you to day three of our eight week journey together.\\nAnd today we're ...\",\"Video: 59472429\\u003cbr\\u003eText: And continuing on our strategy to solve commercial problems with LMS, we get to step four, which is\\n...\",\"Video: 59167009\\u003cbr\\u003eText: Welcome back.\\nIt's time to make our full agent framework.\\nI'm super excited about this.\\nIt's pulling...\",\"Video: 59166481\\u003cbr\\u003eText: And here, once more we find ourselves in our favorite place, the Jupyter Lab.\\nReady to go with weeks...\",\"Video: 59670933\\u003cbr\\u003eText: I realized my enthusiasm for this project is a bit insane, but I have to tell you that I am very sat...\",\"Video: 59670073\\u003cbr\\u003eText: Okay, it's time to complete the Rag workflow in our Jupyter Lab on day 2.3.\\nWe've got this function ...\",\"Video: 59673595\\u003cbr\\u003eText: That concludes a mammoth project.\\nThree weeks in the making.\\nIn the course of those three weeks, sta...\",\"Video: 59297603\\u003cbr\\u003eText: And I'm delighted to welcome you back to LM engineering on the day that we turn to vectors.\\nFinally,...\",\"Video: 60614541\\u003cbr\\u003eText: I am delighted to welcome you to the first day of our eight weeks together as you join me on this ad...\",\"Video: 59667357\\u003cbr\\u003eText: Let's now see our results side by side.\\nWe started our journey with a constant model that was at $1....\",\"Video: 59667841\\u003cbr\\u003eText: Now, look, I know that I went through that very fast, but maybe, uh, you're still, uh, blinking\\nat t...\",\"Video: 59472007\\u003cbr\\u003eText: So I hope you enjoyed our first bash at Scrubbing Data, and that you are now looking through the cod...\",\"Video: 59507435\\u003cbr\\u003eText: So I'm now going to talk about five important hyperparameters for the training process.\\nAnd some of ...\",\"Video: 59509185\\u003cbr\\u003eText: So this is where I left you looking at this satisfying chart on training loss and seeing the trainin...\",\"Video: 59473159\\u003cbr\\u003eText: Welcome to Jupyter Lab and welcome to our experiments at the frontier.\\nSo we are going to put our fr...\",\"Video: 60619447\\u003cbr\\u003eText: I want to take a moment to talk about something that's very fundamental to an LLM, which is the numb...\",\"Video: 59166353\\u003cbr\\u003eText: Well, congratulations on leveling up yet again.\\nYou've got some real hard skills that you've added t...\",\"Video: 60619123\\u003cbr\\u003eText: So what we're now going to do is we're going to look at some models in practice and start to compare...\",\"Video: 59295363\\u003cbr\\u003eText: Well, another congratulations moment.\\nYou have 40% on the way to being an LM engineer at a high leve...\",\"Video: 60619289\\u003cbr\\u003eText: And now we'll go a bit faster through the other models.\\nWe'll start with Google's Gemini.\\nI have the...\",\"Video: 59472873\\u003cbr\\u003eText: So it's quite an adventure that we had at the frontier of what's capable with Llms today, solving a\\n...\",\"Video: 60619429\\u003cbr\\u003eText: Let me talk about some other phenomena that have happened over the last few years.\\nOne of them has b...\",\"Video: 59295601\\u003cbr\\u003eText: So it's time to continue our journey into the world of open source and understand which models we sh...\",\"Video: 59170025\\u003cbr\\u003eText: And a massive welcome back one more time to LM engineering.\\nWe are in week three, day two and we are...\",\"Video: 59166443\\u003cbr\\u003eText: And welcome back everybody.\\nWelcome to week two day three.\\nIt's a continuation of our enjoyment of r...\",\"Video: 60620025\\u003cbr\\u003eText: And welcome back to Jupyter Lab, one of my very favorite places to be.\\nWhen Jupyter Lab sprung up on...\",\"Video: 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interface.\\nBut fi...\",\"Video: 60617163\\u003cbr\\u003eText: And already that wraps up day two.\\nNow that you have built that solution.\\nAnd congratulations on tha...\",\"Video: 60616423\\u003cbr\\u003eText: So I hope you've just enjoyed yourself experimenting with different LMS locally on your box using th...\",\"Video: 59170227\\u003cbr\\u003eText: Welcome back to Google Colab.\\nHere we are ready to explore the wonderful world of Tokenizers.\\nSo, uh...\",\"Video: 59169985\\u003cbr\\u003eText: So I hope you enjoyed that whirlwind tour of Google Colab.\\nHere's just a little screenshot example o...\",\"Video: 60616927\\u003cbr\\u003eText: It's time for our first LM experiment at this point.\\nSo some of this you may know well, you may know...\",\"Video: 59673721\\u003cbr\\u003eText: And here we are in JupyterLab for the last time, and we are looking here at day five, the last day\\no...\",\"Video: 59508055\\u003cbr\\u003eText: I'm so very happy that you've reached this epic moment in the course and that you're hanging in ther...\",\"Video: 59670259\\u003cbr\\u003eText: It's remarkable.\\nBut you are now at the 95% point.\\nThere's 5% remaining of this course.\\nUh, maybe it...\",\"Video: 60616623\\u003cbr\\u003eText: So we're now going to start week one of the course when we are going to be looking at exploring fron...\",\"Video: 59472383\\u003cbr\\u003eText: And welcome back to the week six folder.\\nWe're now at day two, which is the second and final stage o...\",\"Video: 59670171\\u003cbr\\u003eText: So as the very final step on this part four of day two of week eight, we are now going to build an\\ne...\",\"Video: 59297721\\u003cbr\\u003eText: And so now the time has come to talk about the most crucial aspect of Rag, which is the idea of vect...\",\"Video: 59297599\\u003cbr\\u003eText: Well, that was a sneaky detour I took you on in the last one.\\nI hope you enjoyed it though, and I ho...\",\"Video: 59507635\\u003cbr\\u003eText: Look, I hope you're excited.\\nYou really should be.\\nYou've been through 80% of the course and it's al...\",\"Video: 59669375\\u003cbr\\u003eText: Here we are for the day.\\n2.1 notebook.\\nAnd don't let it be said that I don't ever do anything for yo...\",\"Video: 59297733\\u003cbr\\u003eText: Welcome back to JupyterLab and welcome to your first experiment with the world of Long Chain.\\nLet me...\",\"Video: 59670369\\u003cbr\\u003eText: It is terrific that you're hanging on in there and making such great progress with this course.\\nAs w...\",\"Video: 59166281\\u003cbr\\u003eText: And with that, amazingly, you completed day one of week two already and that gets you to the 15% poi...\",\"Video: 59671567\\u003cbr\\u003eText: Well, the first thing you're going to notice is that I don't have a notebook open for you.\\nAnd that'...\",\"Video: 59297593\\u003cbr\\u003eText: And welcome to continuing our journey with Hrag.\\nAnd today it's time to unveil Liang Chen.\\nSo first,...\",\"Video: 59166461\\u003cbr\\u003eText: And welcome back to the lab.\\nHere we are in Jupyter Lab and we are going to go into week two.\\nAnd we...\",\"Video: 59167007\\u003cbr\\u003eText: Well, how fabulous is that?\\nI hope that you are as wowed as I am by our new airline, I assistant and...\",\"Video: 59508121\\u003cbr\\u003eText: The moment has arrived.\\nHere we go.\\nWe're in fine tuning.\\nWe do fine tuning.\\nTrain.\\nThere is also a ...\",\"Video: 59295579\\u003cbr\\u003eText: All right.\\nAre you excited to see how this goes?\\nLet's give it a try.\\nSo in this next section, I cre...\",\"Video: 60620375\\u003cbr\\u003eText: And with that, we've reached an important milestone.\\nThe first week of our eight week journey is com...\",\"Video: 59472491\\u003cbr\\u003eText: Welcome back.\\nIf you are following along with me in JupyterLab, as I hope you are, then you will nee...\",\"Video: 59472425\\u003cbr\\u003eText: Welcome to week six, day three.\\nToday is going to be a day that you will 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Five's Lab.\\nAnd this is going to be lots of creativit...\",\"Video: 59170043\\u003cbr\\u003eText: Let me enthusiastically welcome you all back to week three of our LLM engineering journey.\\nIf you en...\",\"Video: 59473147\\u003cbr\\u003eText: Well, I'm very relieved.\\nI've got that behind me.\\nNo more human testing for me.\\nWe'll have one final...\",\"Video: 59166453\\u003cbr\\u003eText: Welcome back and welcome to our continuing JupyterLab experience.\\nUh, I'm hopefully going to keep yo...\",\"Video: 59166915\\u003cbr\\u003eText: Welcome back to the wonderful world of JupyterLab.\\nAnd here we are in week two.\\nDay three.\\nUh, bring...\",\"Video: 59667365\\u003cbr\\u003eText: Here we are back in Colab, looking at the week seven, day five of the Colab notebooks and I'm on a\\nT...\",\"Video: 60616845\\u003cbr\\u003eText: We're on the home stretch.\\nThis is the final step in the environment setup, and it's an easy one.\\nIt...\",\"Video: 59295459\\u003cbr\\u003eText: And welcome back to More Leaderboard Fest as we go through some more leaderboards.\\nBut this time we'...\",\"Video: 59471979\\u003cbr\\u003eText: So we now turn to the parts of the problem, which is perhaps, let's say, not as glamorous as some\\nof...\",\"Video: 59503705\\u003cbr\\u003eText: And so now we talk about quantization the q and q Laura.\\nQ stands for quantized quantized.\\nLaura.\\nAn...\",\"Video: 59472505\\u003cbr\\u003eText: So the good news is that this is the very final video about data set curation.\\nYou were probably fed...\",\"Video: 59669217\\u003cbr\\u003eText: And welcome to the next part of visualizing the data.\\nAnd just very quickly to show it to you in 3D....\",\"Video: 59671221\\u003cbr\\u003eText: I gotta tell you, I don't like to toot my horn a whole lot, but I do think that I've done a great\\njo...\",\"Video: 59503703\\u003cbr\\u003eText: Well.\\nHello there everybody.\\nI am so grateful that you've made it through to the start of week seven...\",\"Video: 59473201\\u003cbr\\u003eText: Well, before we do a postmortem on what happened, let's just quickly look at the standing the rankin...\",\"Video: 60622463\\u003cbr\\u003eText: In this video, we're going to set up a full data science environment for Mac users.\\nIn the next vide...\",\"Video: 60619299\\u003cbr\\u003eText: Well, I hope you found that both educational and enjoyable.\\nAs we went through and learned so much a...\",\"Video: 59295607\\u003cbr\\u003eText: So to revisit then the solution that we built in the previous day and talk about the metrics.\\nAs I s...\",\"Video: 59297575\\u003cbr\\u003eText: Well, welcome to the final part on rag.\\nAnd this is the session where you go from being a rag expert...\",\"Video: 59507687\\u003cbr\\u003eText: It's time for action, everybody.\\nWe've set up our colab.\\nHere we are, week seven, day three.\\nWe've g...\",\"Video: 59671441\\u003cbr\\u003eText: And welcome once more to our favorite place to be Jupyter Lab, the Paradise for a data 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leaderboard.\\nThe first place you go when selecting your b...\",\"Video: 59504785\\u003cbr\\u003eText: So at this point we're going to talk about hyperparameters.\\nAnd we're going to introduce three of th...\",\"Video: 59505337\\u003cbr\\u003eText: So we're now going to look at four bit quantization, the rather remarkable effect of reducing the pr...\",\"Video: 59271655\\u003cbr\\u003eText: So here we are on Hugging Face's main landing page at Hugging Face Core.\\nA URL you know.\\nWell, since...\",\"Video: 59472883\\u003cbr\\u003eText: Okay, time to reveal the results.\\nIt has run to completion.\\nAnd here it is.\\nSo a moment to pause.\\nIt...\",\"Video: 59673639\\u003cbr\\u003eText: And welcome now to the code for our user interface, which we will find in this Python module.\\nPrice ...\",\"Video: 59472463\\u003cbr\\u003eText: So last time we looked at a humble linear regression model with feature engineering, and now we say\\n...\",\"Video: 59297595\\u003cbr\\u003eText: So by the time you're watching this, hopefully you have played yourself with vectors.\\nYou've created...\",\"Video: 60619149\\u003cbr\\u003eText: So we're going to start our exploration into the world of frontier models by playing with the famous...\",\"Video: 59297735\\u003cbr\\u003eText: And at last the time has come to see rag in action.\\nAfter all of this talk, and here we are.\\nWe're i...\",\"Video: 60616407\\u003cbr\\u003eText: And now over to my Mac people.\\nAnd I have news for you.\\nIt's exactly the same thing.\\nYou go to a fav...\",\"Video: 59170235\\u003cbr\\u003eText: So here we are in Google Colab for our first collaborative session on the cloud using a GPU box.\\nOn ...\",\"Video: 59472067\\u003cbr\\u003eText: So we've covered steps 1 to 4 of the five step strategy.\\nAnd that brings us to step five, which is p...\",\"Video: 59472011\\u003cbr\\u003eText: Welcome everybody.\\nSo in the past I've said quite a few times, I am excited to start this this week ...\",\"Video: 59295553\\u003cbr\\u003eText: Welcome back.\\nIn the last part, we gave our GPT four and clawed the challenge of converting a simple...\",\"Video: 59297773\\u003cbr\\u003eText: Well, I hope you're eager with anticipation for this session in JupyterLab as we finally get to see\\n...\",\"Video: 59295583\\u003cbr\\u003eText: And here we are back in JupyterLab.\\nIt's been a minute.\\nWe've been working in Colab for last week, a...\",\"Video: 59507329\\u003cbr\\u003eText: Okay.\\nIt's moment of truth time.\\nI have just taken our class tester.\\nYou remember this class?\\nUh, it...\",\"Video: 59295429\\u003cbr\\u003eText: Continuing our investigation of benchmarks, and this will become more real when we actually see some...\",\"Video: 60595637\\u003cbr\\u003eText: Here we are back in the Colab, which has been running overnight for me and probably for you too, I\\nh...\",\"Video: 59668027\\u003cbr\\u003eText: And so here we are at the home page for modal.\\nAt modal.com spelt model not not model which is confu...\",\"Video: 59295527\\u003cbr\\u003eText: I'm so happy to welcome you to week four, day four on our journey to LLM Engineering and Mastery.\\nHe...\",\"Video: 59295377\\u003cbr\\u003eText: Just before we go on to some of the more advanced metrics, I want to mention for a second something\\n...\",\"Video: 59666211\\u003cbr\\u003eText: So before we try our new model and one more recap on the models so far and keep notes of this so we\\n...\",\"Video: 59170107\\u003cbr\\u003eText: And once again, it's that moment when you take a pause and congratulate yourself on another day of\\ns...\",\"Video: 60616833\\u003cbr\\u003eText: So I realized that day one of week one has been a pretty long day, and I assure you that the other,\\n...\",\"Video: 59472413\\u003cbr\\u003eText: Wonderful.\\nWhere we left off is we had just created the Get Features function, which builds our feat...\",\"Video: 59297561\\u003cbr\\u003eText: And would you believe at this point you're 55% of the way along the journey?\\nUh, it's been a while s...\",\"Video: 59669211\\u003cbr\\u003eText: Well, we took on a lot today and we seem to have been successful.\\nThese red icons that you see on th...\",\"Video: 59166981\\u003cbr\\u003eText: Welcome to week two, day five.\\nThe last day of week two where a lot is coming together.\\nI am so grat...\",\"Video: 60619227\\u003cbr\\u003eText: And now let's move to Claude from anthropic, my favorite model and typically the favorite model of\\nm...\",\"Video: 60620395\\u003cbr\\u003eText: Welcome back to Jupyter Lab, where I want to show you the assignment, the homework exercise for you\\n...\",\"Video: 59665127\\u003cbr\\u003eText: Well hi there everybody.\\nI'm not going to give you my usual song and dance about how excited you are...\",\"Video: 59668923\\u003cbr\\u003eText: Well, welcome back to Jupyter Lab for what will be an epic finale to our time in this platform.\\nAnd ...\",\"Video: 59504887\\u003cbr\\u003eText: Well, here we are again in Google Colab.\\nIt's been a minute since we were here, and welcome back to ...\",\"Video: 59170165\\u003cbr\\u003eText: Welcome, everybody to the last day of week three.\\nWeek three.\\nDay five.\\nWe're here already wrapping ...\",\"Video: 60617251\\u003cbr\\u003eText: Congratulations are definitely in order.\\nYesterday was a mammoth first day on this course and you go...\",\"Video: 59166951\\u003cbr\\u003eText: All right, back to the lab.\\nBack to our project.\\nTime to work with tools.\\nI am in the week two folde...\",\"Video: 60619619\\u003cbr\\u003eText: Well, day four was an information dense day.\\nI do hope that you learned some something useful here, ...\",\"Video: 60616663\\u003cbr\\u003eText: Well.\\nHi there, this is time for PC people to get set up.\\nSo all you Mac people out there, you don't...\",\"Video: 59508175\\u003cbr\\u003eText: So I'm taking a moment now to explain that the training costs of optimizing a model for this course\\n...\",\"Video: 59670087\\u003cbr\\u003eText: And welcome to part four of day two of week eight.\\nUh, there's a lot happening this week, and I have...\",\"Video: 59506713\\u003cbr\\u003eText: Hi everyone.\\nSo the reason I'm so fired up about week seven is that this is the time when we actuall...\",\"Video: 60620169\\u003cbr\\u003eText: Hopefully you found this super satisfying to be able to have this nice business result and have it c...\",\"Video: 59295435\\u003cbr\\u003eText: Well, just before we wrap up, let me introduce this week's challenge and talk about what we're going...\",\"Video: 59297609\\u003cbr\\u003eText: Last week, we worked with models that were able to speed up code by a factor of 60,000 times, which\\n...\",\"Video: 59507489\\u003cbr\\u003eText: Continuing our adventure through hyperparameters for training.\\nThe next one is pretty crucial and it...\",\"Video: 59295549\\u003cbr\\u003eText: And welcome back to our challenge again.\\nAnd this time we are working with our beautiful prototype.\\n...\",\"Video: 59665129\\u003cbr\\u003eText: And now let me make this real for you by showing you some, some diagrams, particularly now looking\\na...\",\"Video: 59169991\\u003cbr\\u003eText: Okay, so that was your introduction to Hugging Face.\\nAnd now I'm going to turn to a different resour...\",\"Video: 59472027\\u003cbr\\u003eText: And now the time has come to curate our data set.\\nAnd the way we're going to do this is we're going ...\",\"Video: 59472307\\u003cbr\\u003eText: Welcome to week six.\\nDay two a day.\\nWhen we get back into the data, we look back in anger at our dat...\",\"Video: 59508289\\u003cbr\\u003eText: So here we are now, back in the Colab, in the same one that we kicked off in the previous day.\\nIt's ...\",\"Video: 59472333\\u003cbr\\u003eText: Thank you for putting up with me during my foray into traditional machine learning.\\nI think it was u...\",\"Video: 59295431\\u003cbr\\u003eText: Now I want to take a quick moment to give you a flyby of five different ways that llms are used comm...\",\"Video: 59673449\\u003cbr\\u003eText: Well, I have to tell you that I'm a little bit sad.\\nThis is the beginning of the beginning of the en...\",\"Video: 59669389\\u003cbr\\u003eText: Well.\\nHi there.\\nSo you've made it to day two of week eight, and I am super grateful that you've been...\",\"Video: 59170057\\u003cbr\\u003eText: And so at the beginning of this week, we started by talking about hugging face pipelines.\\nAnd you us...\",\"Video: 59166949\\u003cbr\\u003eText: Welcome back to making chatbots.\\nLet's keep going.\\nSo for the next part we're going to beef up the s...\",\"Video: 59473019\\u003cbr\\u003eText: Welcome back to an action packed time of of training.\\nSo now, after waiting about five minutes when ...\",\"Video: 59297585\\u003cbr\\u003eText: Before we move on, let me show you one more time this fabulous slide that describes the simple three...\",\"Video: 59170255\\u003cbr\\u003eText: And welcome back to us continuing our journey through the model class in Hugging Face Transformers l...\",\"Video: 60614589\\u003cbr\\u003eText: So we're now going to run a large language model directly on your box using a platform called llama,...\",\"Video: 59297601\\u003cbr\\u003eText: I'm not going to lie, at this point you have every reason to be impatient with me.\\nWe've been yammer...\",\"Video: 60616629\\u003cbr\\u003eText: And welcome back to team PC and Team Mac as we come back together again for a quick video.\\nIn this o...\",\"Video: 59297749\\u003cbr\\u003eText: It's always welcome back to JupyterLab, my favorite place to be.\\nAnd now we are, of course in the we...\",\"Video: 59170135\\u003cbr\\u003eText: Welcome.\\nIt's week three.\\nIt's day four.\\nWe are back on the adventure in open source land, back inve...\",\"Video: 59472017\\u003cbr\\u003eText: And this is the first time that we'll be coding against our big project of the course.\\nWelcome to Ju...\",\"Video: 59507017\\u003cbr\\u003eText: Welcome to Colab.\\nWelcome to the week seven day two Colab.\\nAnd just before we try our base model, we...\",\"Video: 60619883\\u003cbr\\u003eText: And now we've arrived at an exciting moment in our first week.\\nThe conclusion of the first week is w...\",\"Video: 59508297\\u003cbr\\u003eText: What more is there to say, really?\\nTomorrow is the day for results.\\nA day that very excited indeed a...\",\"Video: 60619247\\u003cbr\\u003eText: We're going to spend a little bit more time with GPT just to try out a few more interesting things.\\n...\",\"Video: 59504769\\u003cbr\\u003eText: Without further ado, we're going to get stuck into it.\\nTalking about Laura.\\nLow rank adaptation.\\nAnd...\",\"Video: 59170233\\u003cbr\\u003eText: Welcome back to our continued exploits with Tokenizers.\\nWhat we're now going to look at is what's ca...\",\"Video: 59671231\\u003cbr\\u003eText: And here we are back in the Jupyter Lab for the fast approaching conclusion with a really great proj...\",\"Video: 60620397\\u003cbr\\u003eText: Well, that's a fantastic result to have now arrived towards the end of week one and having completed...\",\"Video: 59170093\\u003cbr\\u003eText: I'm delighted to see you again.\\nAs we get started with day three of week three of our adventure and ...\",\"Video: 59473089\\u003cbr\\u003eText: Welcome back.\\nSo hopefully you are still impressed by the GPT four mini results.\\nThe frontier model ...\",\"Video: 60395261\\u003cbr\\u003eText: Let's keep going with our project to equip our LM with a tool.\\nWe just created this piece of code to...\",\"Video: 60617259\\u003cbr\\u003eText: I'm excited to introduce you to your first exercise, and I'm looking forward to seeing what you make...\",\"Video: 59507313\\u003cbr\\u003eText: And it's this time again, when we look at the podium of how our models are performing across the boa...\",\"Video: 60619721\\u003cbr\\u003eText: Now it's time to talk for a minute about tokens.\\nTokens are the individual units which get passed in...\",\"Video: 59295451\\u003cbr\\u003eText: I know that everybody.\\nIt seems like just the other day that we were embarking on our quest together...\",\"Video: 59166919\\u003cbr\\u003eText: And with that, it concludes our session on tools.\\nAnd at this point, you are probably an expert on t...\",\"Video: 59295441\\u003cbr\\u003eText: Okay, so welcome to our leaderboard fast as we go through a ton of essential leaderboards for your\\nc...\",\"Video: 59295541\\u003cbr\\u003eText: And welcome back.\\nYou've just seen GPT four zero spectacularly failed to work on our hard Python con...\",\"Video: 59473101\\u003cbr\\u003eText: Welcome back.\\nSo about ten minutes later, maybe 15 minutes later, the run has completed.\\nAnd how do ...\",\"Video: 59507423\\u003cbr\\u003eText: So you may remember eons ago when we were building our data set.\\nAt the end of that, we uploaded our...\",\"Video: 59295545\\u003cbr\\u003eText: I really hope you've enjoyed this week.\\nWe've got tons done.\\nWe've experimented with all sorts of ne...\",\"Video: 59472503\\u003cbr\\u003eText: Welcome back to Jupyter Lab.\\nLast time, we looked at some silly models for predicting the price of p...\",\"Video: 60614591\\u003cbr\\u003eText: The mantra of this course is that the best way to learn is by doing, and we will be doing stuff toge...\",\"Video: 59473021\\u003cbr\\u003eText: Welcome to our favorite place to be to JupyterLab.\\nHere we are again now in day three.\\nIn week six.\\n...\",\"Video: 60617255\\u003cbr\\u003eText: I'm now going to talk for a bit about models.\\nA term you often hear is the term frontier models, whi...\",\"Video: 59667829\\u003cbr\\u003eText: Well.\\nHello there.\\nLook, I know what you're thinking.\\nYou're thinking I peaked too early.\\nLast week ...\",\"Video: 59505329\\u003cbr\\u003eText: Welcome back.\\nYou may, like me, have just gone off and got a coffee while things loaded back up agai...\",\"Video: 59669049\\u003cbr\\u003eText: So what you just saw was an ephemeral app, as it's called, which means just a temporary app that you...\",\"Video: 60619439\\u003cbr\\u003eText: This now brings us to an extremely important property of LMS called the context window that I want t...\",\"Video: 59668181\\u003cbr\\u003eText: And so it gives me great pleasure to introduce to you the project that I've lined up for you this we...\",\"Video: 59472441\\u003cbr\\u003eText: Welcome back.\\nSo we've been doing the thoroughly distasteful, unsavory work of feature engineering.\\n...\",\"Video: 59507785\\u003cbr\\u003eText: Well, I'm sure you're fed up of me saying that the moment of truth has arrived, but it really has.\\nT...\",\"Video: 59295587\\u003cbr\\u003eText: When I left you, we had just created this simple user interface for converting from Python to C plus...\",\"Video: 59166465\\u003cbr\\u003eText: Welcome back to the JupyterLab on Gradio day, so you'll remember where we left off.\\nWe'd written two...\",\"Video: 59473071\\u003cbr\\u003eText: Hey, gang.\\nLook, I know what you're thinking.\\nThis week was supposed to be training week.\\nI set it a...\",\"Video: 59295423\\u003cbr\\u003eText: Welcome to day two of week four, when we get more into leaderboards so that by the end of this, you'...\",\"Video: 59297723\\u003cbr\\u003eText: So I know what you're thinking.\\nYou're thinking, what's going on here?\\nWe're on day five.\\nWe're on d...\",\"Video: 59166947\\u003cbr\\u003eText: Well, thank you for coming along for week two, day four.\\nWe have lots of good stuff in store today.\\n...\",\"Video: 59666831\\u003cbr\\u003eText: Take one more moment to look at this very nice diagram that lays it all out, and we will move on.\\nNo...\",\"Video: 59295493\\u003cbr\\u003eText: And welcome to week four, day three.\\nAs we are about to embark upon another business project which w...\",\"Video: 60616855\\u003cbr\\u003eText: Now I know what you're thinking.\\nWe've been building environments for so long.\\nAre we not done yet?\\n...\",\"Video: 59506611\\u003cbr\\u003eText: So in a future day, I'm going to be training, fine tuning a model and creating a fine tuned model.\\nA...\",\"Video: 60616493\\u003cbr\\u003eText: I'll just take a quick moment to introduce myself to convince you that I am actually qualified to be...\",\"Video: 59166317\\u003cbr\\u003eText: And welcome to week two, day two, as we continue our adventure into the realm of LMS.\\nUh, so today, ...\",\"Video: 59295439\\u003cbr\\u003eText: So I'm aware that there's a big risk that you are getting fed up of leaderboards, because we've done...\",\"Video: 59472421\\u003cbr\\u003eText: And welcome back to our final time in Jupyter Lab with traditional machine learning.\\nIt's almost ove...\",\"Video: 59472137\\u003cbr\\u003eText: Well, well, well, it's been a long day, but congratulations, you've made it.\\nWe've gone through and ...\",\"Video: 59297693\\u003cbr\\u003eText: So at the end of each week, it's customary for me to give you a challenge, an assignment to do on\\nyo...\",\"Video: 60620143\\u003cbr\\u003eText: So we're going to make a call to GPT four.\\nOh, that's going to ask it to look through a set of links...\",\"Video: 60619501\\u003cbr\\u003eText: I welcome to day four of our time together.\\nThis is a very important day.\\nToday we're going to be lo...\",\"Video: 59297743\\u003cbr\\u003eText: And welcome to day five.\\nFor reals.\\nWe're actually in the proper Jupyter notebook.\\nThis time we're i...\",\"Video: 59166847\\u003cbr\\u003eText: Well, they say that time flies when you're having fun, and it certainly feels like time is flying.\\nU...\",\"Video: 59170223\\u003cbr\\u003eText: Well.\\nFantastic.\\nIt's coming up to the end of the week, and that means it's coming up to a challenge...\",\"Video: 59170037\\u003cbr\\u003eText: So how does it feel to be 30% of the way down the journey to being a proficient LLM engineer?\\nTake a...\",\"Video: 59295609\\u003cbr\\u003eText: You must be feeling absolutely exhausted at this point.\\nAnd if you are, that is okay.\\nYou have done ...\",\"Video: 60619281\\u003cbr\\u003eText: Well, I'm delighted to welcome you to day three of our eight week journey together.\\nAnd today we're ...\",\"Video: 59472429\\u003cbr\\u003eText: And continuing on our strategy to solve commercial problems with LMS, we get to step four, which is\\n...\",\"Video: 59167009\\u003cbr\\u003eText: Welcome back.\\nIt's time to make our full agent framework.\\nI'm super excited about this.\\nIt's pulling...\",\"Video: 59166481\\u003cbr\\u003eText: And here, once more we find ourselves in our favorite place, the Jupyter Lab.\\nReady to go with weeks...\",\"Video: 59670933\\u003cbr\\u003eText: I realized my enthusiasm for this project is a bit insane, but I have to tell you that I am very sat...\",\"Video: 59670073\\u003cbr\\u003eText: Okay, it's time to complete the Rag workflow in our Jupyter Lab on day 2.3.\\nWe've got this function ...\",\"Video: 59673595\\u003cbr\\u003eText: That concludes a mammoth project.\\nThree weeks in the making.\\nIn the course of those three weeks, sta...\",\"Video: 59297603\\u003cbr\\u003eText: And I'm delighted to welcome you back to LM engineering on the day that we turn to vectors.\\nFinally,...\",\"Video: 60614541\\u003cbr\\u003eText: I am delighted to welcome you to the first day of our eight weeks together as you join me on this ad...\",\"Video: 59667357\\u003cbr\\u003eText: Let's now see our results side by side.\\nWe started our journey with a constant model that was at $1....\",\"Video: 59667841\\u003cbr\\u003eText: Now, look, I know that I went through that very fast, but maybe, uh, you're still, uh, blinking\\nat t...\",\"Video: 59472007\\u003cbr\\u003eText: So I hope you enjoyed our first bash at Scrubbing Data, and that you are now looking through the cod...\",\"Video: 59507435\\u003cbr\\u003eText: So I'm now going to talk about five important hyperparameters for the training process.\\nAnd some of ...\",\"Video: 59509185\\u003cbr\\u003eText: So this is where I left you looking at this satisfying chart on training loss and seeing the trainin...\",\"Video: 59473159\\u003cbr\\u003eText: Welcome to Jupyter Lab and welcome to our experiments at the frontier.\\nSo we are going to put our fr...\",\"Video: 60619447\\u003cbr\\u003eText: I want to take a moment to talk about something that's very fundamental to an LLM, which is the numb...\",\"Video: 59166353\\u003cbr\\u003eText: Well, congratulations on leveling up yet again.\\nYou've got some real hard skills that you've added t...\",\"Video: 60619123\\u003cbr\\u003eText: So what we're now going to do is we're going to look at some models in practice and start to compare...\",\"Video: 59295363\\u003cbr\\u003eText: Well, another congratulations moment.\\nYou have 40% on the way to being an LM engineer at a high leve...\",\"Video: 60619289\\u003cbr\\u003eText: And now we'll go a bit faster through the other models.\\nWe'll start with Google's Gemini.\\nI have the...\",\"Video: 59472873\\u003cbr\\u003eText: So it's quite an adventure that we had at the frontier of what's capable with Llms today, solving a\\n...\",\"Video: 60619429\\u003cbr\\u003eText: Let me talk about some other phenomena that have happened over the last few years.\\nOne of them has b...\",\"Video: 59295601\\u003cbr\\u003eText: So it's time to continue our journey into the world of open source and understand which models we sh...\",\"Video: 59170025\\u003cbr\\u003eText: And a massive welcome back one more time to LM engineering.\\nWe are in week three, day two and we are...\",\"Video: 59166443\\u003cbr\\u003eText: And welcome back everybody.\\nWelcome to week two day three.\\nIt's a continuation of our enjoyment of r...\",\"Video: 60620025\\u003cbr\\u003eText: And welcome back to Jupyter Lab, one of my very favorite places to be.\\nWhen Jupyter Lab sprung up on...\",\"Video: 59170055\\u003cbr\\u003eText: Welcome to the world of Google Colab.\\nYou may already be very familiar with Google Colab, even if 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+7lSz06O286L5trcRSKqTJwHzn3fcEyrguSg/JzwpBVTpiL+yAsd8m74o0WWv5xzjCWdKG/Y3pdIuXjjfE0OUUnvety9taFARFPCistF6XnntH8zvf/KFSGtV6yBFmJ34wS+Yu/5zv/n5BRMRbUEBz9Vx+9NPvzwZZalzKUpPkYqq1fZ6W4ev1njcXJSuOysgMspNWQKohN56TcfsZ80sFIUmMUvio4xUXKq06+cX8PR3quumunty2NVaKhLzUOvgrHRtReFFEfCi7qEoAt7d9p6QqKgUWDn++ptSe8+30bFK69Y8587t8WpCHvWW0yMLeIqg1H6U8Yq/DqSuo6hbpX8rus5F4PmFaB2DgJf4FqIjBCAAAQhAAAIQgAAEIAABCGwi0NICnoS6a6/7s03729Lsseujp2yK95z+FfPrP/xlUsBpJOApbVJ1w2Sg4Hez9Z9w2KY7PtMKMirqL6OLWlFdSvW7xNaIU/qqxMOkAt4tt99tBcj6EXhP2mtXT9ipJf5FEfCcKHbV986aNNzQXF09urAIPB37kjdKIO02X//Uu736Y//zhN29tEzXnvz8Y73UUNUkCzbVd1NdwO/blNXTPvsdTzDcZqslNW/qoIAXlU0cAU+CkCIAa5l3/Py3fzZKLZbBxVOftOc0Ac+Nr14E3gdtXbyX2ki3WuNRhN9LrdCsqMhn2hpswaZUXr+JRC1Anzj3h+aCy35pfvOjz5kPffIb5mablvyzH3xiMk1UfYICnv88SlG9yka3yV13/6ftY85837HWOGWizmHQxEKimcxIZGIRdQ+FCXiqK/gyG22qeX7ZMg7WHlRk3XNsHUUZS7imCEmlxMaJwNN5Dn1u7Qi8G26+1ROUEfD4vQoBCEAAAhCAAAQgAAEIQAACeRFoaQFPUBXlJDHoW599zyRj1Xh7oa2RpfRHV3i+noCnlML3nfk185Orf2e+9smTzf8+8bF110qOqKrR9Zajj7AF/18w5Tiln77plE95qbuXf/sMr7h+UgFPgqJqoykiyV8DT1FPz7Mpkiro/xorEiYV8Jxxwg1XnOcJjWpKg1Vk4NIlNoXWRpuFNdUM/Ohnvm0+/eETPIHru58/1TPicO0NJ53tmT0EXX11HbmeqpaYq/XmF2LUX+dTLTaljzqh6MYrv+hFh0VlE1XAu+7Gv5tjT/7kZKprcN6f+/ol5ovf/slkarUi8ORW6uoE/vlvd5hXv/V0r4bd8/b7n8nuznxBx+2+86NqCngShZ9mTROOOPgZ5j1vmRp5plTrHR+5zRQhrtaaKHpNUZmKuFSa5xteeYhX59Df/AKexMqbbdp0MDVbTsj/tIKi3IUVmXfiBz/v1TN0UaGq1/dsG+0n8xEJeFH3UCMBT/fp8e/5lLn73mXmgi99yCyYP2fKuJUS/IQDXm9e8aLnTtZz1AG6X8U3KOC99LBne/eGWrAGnuoFPmyNYJQi75oz4thlx+29enoIeGF3PZ9DAAIQgAAEIAABCEAAAhCAQFICLS/gOfMJpYuqxpVe+i++4teeCPGZj5xgDrCGCWoSMSRWnXz8xAu+UjmVInmRjTb65x3/8aKgXvuygxqug1JDlVJ57XU3mX2ftId5/rOfYhbOn2vuuX+Z+eGPr7WOmhvM509726TJRVIBT4NQWurXf3ClOcUKO898yuPNcisaffyc73n14y61IsQC68iaVMBzxgsSelSz7l9332/O/ML3PbHm6t/8yfz46x8z21kBTQJovbahf9Dsd+TbvPTLBZaBXxhRH+dCe+TBz/KcXXWcxLJPnPdD885jX+q53aop5VNpnO9726s90xGlvSod15l8yCVUIpAEKglhj9lhu0hsogp42i9vOfUc85sb/mrkUPp0ayyiNZUhx29v+JuXvvm8/Z5sPvnBCZMJOfXKMOXLNoV5iU2pVTqzItPuX7bCq9/2GMvwltv+7bm6arxKdVarNx4JYUojfodNtVW6tCLcVMNRdd/k9BuMLK21HhIQVXNPAtQvrPgarCfoF/CcaCoB+HBrkiJRVKLzByzjg579P9YN+CgjoVg1DV/xwgnhTKKp9sevr/+rFykpAS/qHvqITVG97sa/mV9eNGEw4x+Lov6+aZ2WP/2hE6z78tS6k9ovSllWpN39djyfP/3tXnr2dy++xqvVeJG9x5XKrtRauc4+5yXv8MYmwVvGLNfd8PcpLrRyP5aorD6KkB21nL9m7y+5Hn/rs6ohuDMCXtLfQvSDAAQgAAEIQAACEIAABCAAgVACLS/giZDEui9/9zKjqKVuG9mlVFjVu3quTb1zTcKBCve7JidKRcmp+L9e6J3rZRhxCT5ypL3kqt9Y4eleo8gkRZTta9Mrj7bXVOSYa2kEPF3nG+dfZcWcX3s1vyS0KDpQNdW233ZL7xJJBTz1lbOmjDv6rOj4WGt68O4T/s/0WkOKN7zrbKO0Rok0tcw8/HyUZql0S0WPOUHO/7lqsn3hmz/2BFKlHCt6S8YJSil1TWYEn7ImEL+wqdASBXewUWeKbnTCq0TRY+2YxHqvPXbyahpGYRNVwNM4JMyq7pvWVaLumr71tp5dl60RuK051IrCL33BfpOpnX/7512eiKvowte+7PleDUHxkhh17e9u9kQgCU8HPuvJ1vX3SM/RVq3ReOSWKwdcz9XVrvNuOz3SHGsZRDVLcQ7Jz3nGPuacj7512hYOptBqnF+163+nFW41d6WvSqQ8/jWHT7qsSjhV5OEq66IsQfDoVxxsDU/u8oxiZJoSdQ9984Kf1RXwDjnqFPOf/y6recvJ/VfpvPr8g2d/w4qid3sCvJyZ32LdlM/8/PfNhXbNDrZ1ApW6LSFfbsXj4+OewYsEWImtV//wbE9kVZPw+kUrlt5u56A0bu37N7/uheZ/95mIuiUCL+zpx+cQgAAEIAABCEAAAhCAAAQgkJQAAl5ScvSDAAQgAAEIQAACEIAABCAAAQhAAAIQgEABBBDwCoDMJSAAAQhAAAIQgAAEIAABCEAAAhCAAAQgkJQAAl5ScvSDAAQgAAEIQAACEIAABCAAAQhAAAIQgEABBBDwCoDMJSAAAQhAAAIQgAAEIAABCEAAAhCAAAQgkJQAAl5ScvSDAAQgAAEIQAACEIAABCAAAQhAAAIQgEABBBDwCoDMJSAAAQhAAAIQgAAEIAABCEAAAhCAAAQgkJQAAl5ScvSDAAQgAAEIQAACEIAABCAAAQhAAAIQgEABBBDwCoDMJSAAAQhAAAIQgAAEIAABCEAAAhCAAAQgkJQAAl5ScvSDAAQgAAEIQAACEIAABCAAAQhAAAIQgEABBBDwCoDMJSAAAQhAAAIQgAAEIAABCEAAAhCAAAQgkJQAAl5ScvSDAAQgAAEIQAACEIAABCAAAQhAAAIQgEABBBDwCoDMJSAAAQhAAAIQgAAEIAABCEAAAhCAAAQgkJQAAl5ScvSDAAQgAAEIQAACEIAABCAAAQhAAAIQgEABBBDwCoDMJSAAAQhAAAIQgAAEIAABCEAAAhCAAAQgkJQAAl5ScvSDAAQgAAEIQAACEIAABCAAAQhAAAIQgEABBBDwCoDMJSAAAQhAAAIQgAAEIAABCEAAAhCAAAQgkJQAAl5ScvSDAAQgAAEIQAACEIAABCAAAQhAAAIQgEABBBDwCoDMJSAAAQhAAAIQgAAEIAABCEAAAhCAAAQgkJQAAl5ScvSDAAQgAAEIQAACEIAABCAAAQhAAAIQgEABBBDwCoDMJSAAAQhAAAIQgAAEIAABCEAAAhCAAAQgkJQAAl5ScvSDAAQgAAEIQAACEIAABCAAAQhAAAIQgEABBBDwCoDMJSAAAQhAAAIQgAAEIAABCEAAAhCAAAQgkJQAAl5ScvSDAAQgAAEIQAACEIAABCAAAQhAAAIQgEABBBDwCoDMJSAAAQhAAAIQgAAEIAABCEAAAhCAAAQgkJQAAl5ScvSDAAQgAAEIQAACEIAABCAAAQhAAAIQgEABBBDwCoDMJSAAAQhAAAIQgAAEIAABCEAAAhCAAAQgkJQAAl5ScvSDAAQgAAEIQAACEIAABCAAAQhAAAIQgEABBBDwCoDMJSAAAQhAAAIQgAAEIAABCEAAAhCAAAQgkJQAAl5ScvSDAAQgAAEIQAACEIAABCAAAQhAAAIQgEABBBDwCoDMJSAAAQhAAAIQgAAEIAABCEAAAhCAAAQgkJQAAl5ScvSDAAQgAAEIQAACEIAABCAAAQhAAAIQgEABBBDwCoDMJSAAAQhAAAIQgAAEIAABCEAAAhCAAAQgkJQAAl5ScvSDAAQgAAEIQAACEIAABCAAAQhAAAIQgEABBBDwCoDMJSAAAQhAAAIQgAAEIAABCEAAAhCAAAQgkJQAAl5ScvSDAAQgAAEIQAACEIAABCAAAQhAAAIQgEABBBDwCoDMJSAAAQhAAAIQgAAEIAABCEAAAhCAAAQgkJQAAl5ScvSDAAQgAAEIQAACEIAABCAAAQhAAAIQgEABBBDwCoDMJSAAAQhAAAIQgAAEIAABCEAAAhCAAAQgkJQAAl5ScvSDAAQgAAEIQAACEIAABCAAAQhAAAIQgEABBBDwCoDMJSAAAQhAAAIQgAAEIAABCEAAAhCAAAQgkJQAAl5ScvSDAAQgAAEIQAACEIAABCAAAQhAAAIQgEABBBDwCoDMJSAAAQhAAAIQgAAEIAABCEAAAhCAAAQgkJQAAl5ScvSDAAQgAAEIQAACEIAABCAAAQhAAAIQgEABBBDwCoDMJSAAAQhAAAIQgAAEIAABCEAAAhCAAAQgkJQAAl5ScvSDAAQgAAEIQAACEIAABCAAAQhAAAIQgEABBBDwCoDMJSAAAQhAAAIQgAAEIAABCEAAAhCAAAQgkJQAAl5ScvSDAAQgAAEIQAACEIAABCAAAQhAAAIQgEABBBDwCoDMJSAAAQhAAAIQgAAEIAABCEAAAhCAAAQgkJQAAl5ScvSDAAQgAAEIQAACEIAABCAAAQhAAAIQgEABBBDwCoDMJSAAAQhAAAIQgAAEIAABCEAAAhCAAAQgkJQAAl5ScvSDAAQgAAEIQAACEIAABCAAAQhAAAIQgEABBBDwCoDMJSAAAQhAAAIQgAAEIAABCEAAAhCAAAQgkJQAAl5ScvSDAAQgAAEIQAACEIAABCAAAQhAAAIQgEABBBDwCoDMJSAAAQhAAAIQgAAEIAABCEAAAhCAAAQgkJQAAl5ScvSDAAQgAAEIQAACEIAABCAAAQhAAAIQgEABBBDwCoDMJSAAAQhAAAIQgAAEIAABCEAAAhCAAAQgkJQAAl5ScvSDAAQgAAEIQAACEIAABCAAAQhAAAIQgEABBBDwCoDMJSAAAQhAAAIQgAAEIAABCEAAAhCAAAQgkJQAAl5ScvSDAAQgAAEIQAACEIAABCAAAQhAAAIQgEABBBDwCoDMJSAAAQhAAAIQgAAEIAABCEAAAhCAAAQgkJQAAl5ScvSDAAQgAAEIQAACEIAABCAAAQhAAAIQgEABBBDwCoDMJSAAAQhAAAIQgAAEIAABCEAAAhCAAAQgkJQAAl5ScvSDAAQgAAEIQAACEIAABCAAAQhAAAIQgEABBBDwCoDMJSAAAQhAAAIQgAAEIAABCEAAAhCAAAQgkJQAAl5ScvSDAAQgAAEIQAACEIAABCAAAQhAAAIQgEABBBDwCoDMJSAAAQhAAAIQgAAEIAABCEAAAhCAAAQgkJQAAl5ScvSDAAQgAAEIQAACEIAABCAAAQhAAAIQgEABBBDwCoDMJSAAAQhAAAIQgAAEIAABCEAAAhCAAAQgkJQAAl5ScvSDAAQgAAEIQAACEIAABCAAAQhAAAIQgEABBBDwCoDMJSAAAQhAAAIQgAAEIAABCEAAAhCAAAQgkJQAAl5ScvSDAAQgAAEIQAACEIAABCAAAQhAAAIQgEABBBDwCoDMJSAAAQhAAAIQgAAEIAABCEAAAhCAAAQgkJQAAl5ScvSDAAQgAAEIQAACEIAABLnY+nEAACAASURBVCAAAQhAAAIQgEABBBDwCoDMJSAAAQhAAAIQgAAEIAABCEAAAhCAAAQgkJQAAl5ScvSDAAQgAAEIQAACEIAABCAAAQhAAAIQgEABBBDwCoDMJSAAAQhAAAIQgAAEIAABCEAAAhCAAAQgkJQAAl5ScvSDAAQgAAEIQAACEIAABCAAAQhAAAIQgEABBBDwCoDMJSAAAQhAAAIQgAAEIAABCEAAAhCAAAQgkJQAAl5ScvSDAAQgAAEIQAACEIAABCAAAQhAAAIQgEABBBDwCoDMJSAAAQhAAAIQgAAEIAABCEAAAhCAAAQgkJQAAl5ScvSDAAQgAAEIQAACEIAABCAAAQhAAAIQgEABBBDwCoDMJSAAAQhAAAIQgAAEIAABCEAAAhCAAAQgkJQAAl5ScvSDAAQgAAEIQAACEIAABCAAAQhAAAIQgEABBBDwCoDMJSAAAQhAAAIQgAAEIAABCEAAAhCAAAQgkJQAAl5ScvSDAAQgAAEIQAACEIAABCAAAQhAAAIQgEABBBDwCoDMJSAAAQhAAAIQgAAEIAABCEAAAhCAAAQgkJQAAl5ScvSDAAQgAAEIQAACEIAABCAAAQhAAAIQgEABBBDwCoDMJSAAAQhAAAIQgAAEIAABCEAAAhCAAAQgkJQAAl5ScvSDAAQgAAEIQAACEIAABCAAAQhAAAIQgEABBBDwCoDMJSAAAQhAAAIQgAAEIAABCEAAAhCAAAQgkJQAAl5ScvSDAAQgAAEIQAACEIAABCAAAQhAAAIQgEABBBDwCoDMJSAAAQhAAAIQgAAEIAABCEAAAhCAAAQgkJQAAl5ScvSDAAQgAAEIQAACEIAABCAAAQhAAAIQgEABBBDwCoDMJSAAAQhAAAIQgAAEIAABCEAAAhCAAAQgkJQAAl5ScvSDAAQgAAEIQAACBRIYH99oBkfGTfvsWWZoZMwMDI2Znu5209Ux23S2zy5wJFwKAhCAAAQgAAEIQKBoAgh4RRPnehCAAAQgAAEIQCAigdGxcTM8utH0D42aYSveqc3raff+XDcwOnkWq+mZnq52+9OGmBeRLYdBAAIQgAAEIACBZiKAgNdMq8VYIQABCEAAAhCY8QQk2g1ZsW5geGxStPNPupaA5//cL+YpWm+2/oIGAQhAAAIQgAAEINDUBBDwmnr5GDwEIAABCEAAAjOBwPCoFexsSqyi7EasgNeohQl4QTGvu7PNptnqZzZi3kzYLMwBAhCAAAQgAIGWJICA15LLzqQhAAEIQAACECibgKtjp2i7MVvfLmqLI+AFxbwOWytPgl6P/SEyLypxjoMABCAAAQhAAALlE0DAK38NGAEEIAABCEAAAi1CYHB43AwOj3opsnFEOz+epAJeELEi8iai82ab9jZMMFpkCzJNCEAAAhCAAASalAACXpMuHMOGAAQgAAEIQKD6BJxz7KBXz27MxAi0qzu5rAQ8/wU8J9tNabY42lZ/XzFCCEAAAhCAAARajwACXuutOTOGAAQgAAEIQCBHArWcY7O8XB4Cnn98Mr7oUpotjrZZLhvnggAEIAABCEAAAqkIIOClwkdnCEAAAhCAAAQgYEyYc2yWjPIW8Pxj9TvaEpmX5SpyLghAAAIQgAAEIBCPAAJePF4cDQEIQAACEIAABDwCSo9dNzAayTk2S2RFCnj+cS+c22E2Wq+Nttk23bZ9FiYYWS4q54IABCAAAQhAAAIhBBDw2CIQgAAEIAABCEAgIgHnHDtqxbuFczrN8jWDEXtmd1iZAl7/oK3lNzpuFJmHo212a8qZIAABCEAAAhCAQBgBBLwwQnwOAQhAAAIQgEBLE6jlHNtmFawl87taSsBbNK/TbFDEoRXwgs052vbY2nmzpe7RIAABCEAAAhCAAAQyJYCAlylOTgYBCEAAAhCAQLMTiOocu+XC7pYS8JbM7zTr+msLeP41d462PZ2zTXvb7GbfDowfAhCAAAQgAAEIVIIAAl4lloFBQAACEIAABCBQJoEkzrFbL+o2y1a3TgptVAHPv45ytO3pbjeeqNeOmFfmHufaEIAABCAAAQg0NwEEvOZeP0YPAQhAAAIQgEBCAmmdY7dd0mMeWDmQ8OrJu5VVAy+JgOefJY62ydecnhCAAAQgAAEIQAABjz0AAQhAAAIQgEDLEFD9toEha8QwMm5GxqbXcosDohUFvLUbRszomLWiTdkk5nXbenm9NjpPUXrUzUsJlO4QgAAEIAABCMx4Agh4M36JmSAEIAABCECgtQk459ghK9qNWffYrForCnhr1o9kylBr4Rxte7smUm0R87LaoZwHAhCAAAQgAIGZRAABbyatJnOBAAQgAAEIQMAjUMs5Nms0ZZlYzLFRaxK91llH2CLb0gVdZtW64cwFvOAccLQtclW5FgQgAAEIQAACzUIAAa9ZVopxQgACEIAABCBQl4AzoRgcHrPi3VghpCTgrVg7aDZmF9QXadw9XW1e2mnRAp7mu7JvKHcBzw/BiXn6E0fbSNuDgyAAAQhAAAIQmKEEEPBm6MIyLQhAAAIQgMBMJ5DEOTZLJmUIWhp/Kwl4/vVS5OHcnnZPQMTRNsudzLkgAAEIQAACEGgGAgh4zbBKjBECEIAABCAAAY+Ac46VgCNDBZlSlNUQ8IolL+FSkXiqw6cIxC5rgqG/Q8wrdh24GgQgAAEIQAAC5RBAwCuHO1eFAAQgAAEIQCAiAZlQTNS0G5tM31w0r9NssDXgyhTwiqoJF8TUqhF4mndH22zT1z8yBYnqAfZYAwzHBROMiDcWh0EAAhCAAAQg0FQEEPCaarkYLAQgAAEIQKA1CIQ5xy6c22EGh6ywZ51ly2pL5nd60WBZOttGmUuZAt7yNYNRhpjLMVHMOyTmddvIvK6OiWg9xLxcloKTQgACEIAABCBQAgEEvBKgc0kIQAACEIAABKYSGLd1zYZHN9oou1Ev0s7+Z8MmAW/IincDVsQrq0nAUxrv6FixLhatKuDNs/Xv1KKad0jM67Cp1hL0euwPYl5ZdwrXhQAEIAABCEAgCwIIeFlQ5BwQgAAEIAABCMQmkMY5VmKORL4Ng6Oxr5tVBwl46/qLT+MtS8DbdkmPeWDlQFb4Yp8n7ZrjaBsbOR0gAAEIQAACEKgQAQS8Ci0GQ4EABCAAAQjMdAJZOcfGjcbKgysCXh5U658zy6hLiXmdm9JsMcEodh25GgQgAAEIQAACyQgg4CXjRi8IQAACEIAABCISkNHEiP3pHxwzI2PZ1KyLUg8t4vASH4aAlxhdoo5ZCnj+AeBom2g56AQBCEAAAhCAQMEEEPAKBs7lIAABCEAAAq1AoJZzbJbzrudImuU1ws4lQUmiZNFOuK2aQluEcYnf0ZbIvLA7gM8hAAEIQAACECiSAAJekbS5FgQgAAEIQGAGEwhzjs1y6hKxlAYpF9iyWqsJeFsu7DZlutAumtdpNgwUV3PQOdr2drcbRelhglHWncZ1IQABCEAAAhAQAQQ89gEEIAABCEAAAokIxHWOTXSROp0UHTXHGlmsXjec5WljnSuvlM5Gg2hvm2Xm9XZ4rqouyrF/aNRsLMAIt2wBr6yUZa2Hc7Tt7Wr3hGPEvFi3CgdDAAIQgAAEIJABAQS8DCByCghAAAIQgECrEEjjHJslIwl483rbzcq+mS/gtVn1qNsKdnO62zyhbtTa747amoJDI+Pe3/faaETVFuwfGjODw2O5iHmzZhmzdEG5EXhLF3SZVVawHZP9cMltqY1G1Bog5pW8EFweAhCAAAQg0EIEEPBaaLGZKgQgAAEIQCAJASfaSUhStNeAFYrKbjNdwBPrThvpNdemb0o8GxweNxsGRz3xqlYNPPHotQJfZ3ubPWbcrOsf9US9rCLzNJ4l87tKTaFVBODKvqFKCHj+sThH257O2aa9bXbZtwbXhwAEIAABCEBghhJAwJuhC8u0IAABCEAAAmkI1HKOnWdTVtXW2TpkZTcJSottTbQVa4dKG4p4KBouK0HTiXaKqNP/HrYRduutaDc6NjXirJGJhcS+DisiKTqxbfZsLyJPP2mNNhDwpm6zrRd1m4fWDE4TSFUrr8eKrp6oZ0VVGgQgAAEIQAACEMiKAAJeViQ5DwQgAAEIQKDJCYQ5x86xwoRqgVVFwCs7IkwCnrI5FRmXtElwc2mwTrRTKmwjwS2qC63OrZpt3TYyTKKeS7FNIuZVRcAr00TDv8bbLukxD6wcaLjsONomvSvoBwEIQAACEIBALQIIeOwLCEAAAhCAQAsTiOMcWwXnV/9SlW2qkCYiUSwl3HXZKC1FyIWJdv55RxXw/H2CYp4i+xThF1XMq0LEYxTRrIhbOUk9QL+Yh6NtEavENSAAAQhAAAIzjwAC3sxbU2YEAQhAAAIQqEsgjXNsFerO+SdWtqATV8DrtmmVEu3041JbB62IFrclEfCCYp6iKZXmqTRbV9ewkTmEBDy57pZpGqK01WWrB+Piyvz4tNGIEvM88bZDPzjaZr5AnBACEIAABCAwQwkg4M3QhWVaEIAABCAAAUfAmVBIqFHUVdJWNQGvbEEnioDnmUvYaDsZUozYWnZOuEtjLpFWwPOvv8QonU+ptjK/kFmG9klwfGULeEmi3pLu87B+7W2zzII52YiZEvM67B6RoNdjf2brL2gQgAAEIAABCECgBgEEPLYFBCAAAQhAYAYSyEq0C4o9ZRtH+MejFNoVa6cbCRS1nPWENL9op6g2Lz3WCqeNItzijDlLAc9/XY3b1eOTg61fzCtbvE0b9RaHb9ixiqSUUcXqdcNhh8b+XBF5E9F5ONrGhkcHCEAAAhCAwAwngIA3wxeY6UEAAhCAQOsQUD2zISsUDVrBSAJM1k1RUFtZ0awKaYyamwS8lX1DmQljcXlJSJM5RF//iFFUljOMyEO0848tLwGvkZg3MrrRRorNKi2Ftgo1+ByfompBek62m9JscbSNe3dyPAQgAAEIQGDmEUDAm3lryowgAAEIQKCFCMQxocgCS9l15/xzWDK/06zdMGJGbWpqGU1CzlwbiSVhUymnzuU1q0i7enMqQsALinlzrOOuDDckDK/rH/X+TJMGHHe9skxbjXvt4PF+4TbtuaL2l/FFl9JslY5t14EGAQhAAAIQgEDrEUDAa701Z8YQgAAEINDkBJTaODg86kXb5S0WBVGVnbYaFPAkJkV1Us1i2RUJpnp2Eu5Uu2zERj2usqmURa5D0QKeuEk0koi3YWDUzOtt98wvhkete+6gTQ+2DPJuZafw+ucXpfZhnjxwtM2TLueGAAQgAAEIVJcAAl5114aRQQACEIAABDwCco6VW6kMEIZHxoz9z9La0gVdhQtW9SarCLwiBDwn2smMQv9b9ezWD44aRUV1279bs36k0PUoS8Dr7d48V0UdupRhpRG76MO8xDyvrqDv+oUCD1xsfm+HF4E4YFPVy27O0ba7s93WziMyr+z14PoQgAAEIACBPAkg4OVJl3NDAAIQgAAEUhCQKJLWOTbF5Wt2LUo0izLuhXM7vHp/EjezbhKonKGDE+08MwpftFlZolIVBDw/76CYJ3FTImeWYl5Rdeei7CPtO0W/VkHA849X0bHrB0a8yFAcbaOsJMdAAAIQgAAEmosAAl5zrRejhQAEIACBGUxAzrGeMGAj7RbO6SzVoKEe5kXzOr00yizFmaRLmoeQIqHIcwG1IogiHoOinX+sLq00DzfSRkzKELOiXlNi3hybXiwDBqXZSoCW0JU2xTjq9ZPupTj9qnQP+McdrE/pHG0R8+KsLsdCAAIQgAAEqksAAa+6a8PIIAABCECgBQhICJPAoYglv3NslSLd/MuQh2iWdJlVi2zU5hOnjYTqtmKTRDv9SLTzfiJE9ZVVl60MMSvJNRW5qH5KtR0bnxCnN9jovCTmF2UYR9Tbl2Wbp9Qal4TTpQu6zfI1gzWH7Rxte2yabbtNeaZBAAIQgAAEINB8BBDwmm/NGDEEIAABCDQ5gSjOsYryGbBiRxQhqUgcZRfw9881zVi89Fc5elrxbsS62DrhLo64hIAXfeeJlUtJllAtIxZF50XlnWato48y2pFKVV3ZN5Q6qjDa1aIdJbF0sX1mrFg7FNpBtRt7NkVJ4mgbiosDIAABCEAAApUhgIBXmaVgIBCAAAQgMJMJxHWOVaF8pR0qYqlKTemRKpy/zqbRlt3iijp+0U5svfTYFE6+rSbgyayirz+9YUcSMS/uWue5N6vkxOzmqShSiXJx07n9jraIeXnuGs4NAQhAAAIQSE8AAS89Q84AAQhAAAIQmEYgrXOshDJF1WQhmGS5PElSKbO8vv9cUdIq29tmTbqlZiHa+a+v9VFK8cq+4bymWPO8ZaxBXsYZzgiks73NS7OVq7Ai9IKReVmlS2exUMFac1mcM+05stgTztG21z57FKU3W39BgwAEIAABCECgMgQQ8CqzFAwEAhCAAASanYBMKIZHFdk14cKZpiWNqElzzSh9yzJuqDW2eqLF5tprbZ4QpEg7pcimNVIIjgEBL8qOiXaMargpwm9er4Tr2fY+sgYig5tdf6tSezGs1ly02WZ/VNYRitLu5Gar+oWqn4eYl/2acUYIQAACEIBAXAIIeHGJcTwEIAABCEDAR8DvHJtWtPODLSs9M2xxqzQuF721Zv2IF62oenZzbfSQRBalLCv9OGvRzs9H11wyv6uucUAYy6SfZxFtFffaRaZOa/0kHHVbwwWJehJgO9pneX+mNSyJO+9aom0Zax42bqXcK3IxLz442oatAJ9DAAIQgAAE8ieAgJc/Y64AAQhAAAIzjEA959gsp1mWOBQ2hzjF8sPOlfZzRSnOnzNRK1DjkoC63op2o9aUoohW1hqVIeBlHeEVdX2cmDenu83WXpwQ8RRNqXuwjKaU7AV2zxWdNh02V0UoDopNysjfsOvocyfm6U8cbaMQ4xgIQAACEIBANgQQ8LLhyFkgAAEIQGCGE4jiHJs1girW2io7hdBF2slBVtFZ4zZHVhF4ZQg6ZbFoJQHP3VNL5neaDdY4pd2mdUo4UpqtUtUl5hUl2GosVUoh9z9vxGfthpFCWej6uge77b2oNcEEI+vfAJwPAhCAAAQgMJUAAh47AgIQgAAEIFCHQFzn2KxBbr2o2zy0ZnBaQf+srxP3fEULixLKujvbvJ8uK+BItFEkliLvyjCR8POSI+lyu0ZFtlYV8PwC1eY6h+2e+cWQjTxTynTQ/CLrdSmDfZQ5aB+u7BvKNWU8bBwyvuiy96gYIeaF0eJzCEAAAhCAQHwCCHjxmdEDAhCAAARmKIG0zrFZY1m6oMusXj9ceFRN2DwkFqxYm7+wqBRZJ9xJtPN+fCmCZaWwtqqAN2oF07xqrIXtOd0Lq9YN1xSoJBa5+oeqAyfhXdF5eYh5UZyPw+aSx+cS+5etLlZIbjQPmWD02DqGzr0YE4w8Vp1zQgACEIBAqxFAwGu1FWe+EIAABCAwhUCWzrFZo1Va3Lp+62hbUr2vevNpJKakZeAZUyiCx4p3I7aWnRPuaokxZaWw+udYdDSirl1GFJhq4JUp4EWNMNP+keirPZSHmFdWLcBG91UV7oMwMU8mKHN7OqyouhFH27QPSfpDAAIQgEDLEkDAa9mlZ+IQgAAEWpeARDvV0FJ0mwSiqjalhyo1sKyop3pcshYW/aKd0mKVHitDiigOsmUIaK0o4OXtchp2DyaJ+nQuxZ3tbV6arWroDVkxPE1kXtkcanGqkrFMvXX0ommtqNpn6/R1bBJZe6zQSmRe2M7ncwhAAAIQgMBmAgh47AYIQAACEGgJAjKhmKhpN1E7rarpqf7FqGK0j8a3aN6EoUCayEC5ec61UTmKtIsr2pUtoJV9/TIi8MoWk9OkiCpCTWYL83rbPeF+eNTWUBxM5mRbNodaD+uqGmv4x6oIPAmNff0jU6aAo21L/PplkhCAAAQgkBEBBLyMQHIaCEAAAhCoHoFGzrESoQZs0Xt/TbWqzaCq9baSihibjQfavCgoRdo5QTUp+ySRWUmvVatfq5hYJF3zrFhnFWnpDFGci7Hbg1HF6CzE66yYuPOUIejGnYMiFyXUy2ikXvOcbDtwtI3LluMhAAEIQKB1CCDgtc5aM1MIQAACLUEgqnNslBfKsoEpskZRQyv7hsseypTrKzLQvos3fBl3HSTauZpkEk+0PnqJj5IeG2XSUWujRTlXkmMQ8JJQi98nTQRevatpP/Zao4XuztlehF4UMU/p43433Pgzyb6HottkGrHORsVWtcX9wgRH26quJOOCAAQgAIEyCSDglUmfa0MAAhCAQGoCzoTCmR1EPWG9lK6o/Ys4TmmmC+Z0VFLA0/zrCQYS7ZQaqygn/W/Vs1tvRbtRa0qRdZOgsmb9SGaCYNzxlSEglhFxpQi8QUVM+lyA47JKenwRJg26hp4JigJTmq1cbLVvg5F5Zax3GLdm+DIiDTe/o62+1KBBAAIQgAAEWpUAAl6rrjzzhgAEINDEBLJwjq1qdJt/WSQqbLWw2yxbPVip1aolINUS7TwzipwddLM21IgLOo0wEfda7viyBLykdeOSztP1095aMr/LLF9TzH2wOdW73TO/kJGMokaV9l12ynYtlmWnN0dZX0VQPmTXL42BiK4jMc+L6LViq6L0MMGIQp9jIAABCEBgphBAwJspK8k8IAABCMxwAhKCRuyPRIQR6yKbtim6bdHcTrNi7VDaU+XaP6vaX1kO0hXNX2NdfPUyrZ8uGxmjKMgiRDv/XMoW8GSGsmrdcKERgK0o4C22NSvLuFe11xVNKsMVPXe6bI22B1cNpBaisrwfq5jW659fXgKsxDw52ioNWpGTiHlZ7irOBQEIQAACVSSAgFfFVWFMEIAABCDgEQg6x2aNpYriWHCOZUR4hXFWDTyv7pZ9g+6XEYgV7spIrdQ4FX1UVmSYrl9GCm8ZAl6ZQmlVUskl5klIVJOYp3qOSrVNG1UWdr+FfV7FZ4R/zEV9WeIcbXvsFwqIeWG7hs8hAAEIQKAZCSDgNeOqMWYIQAACM5hAI+fYrKet6KnVNoosj9psWY21TOHEPweJF6ppp2g7iReqE7ZibfqUuLScyk4fLCP6qdUEvKqku/sjybz7obvNdLa3eWm2zgCjDDEvD4OPtPelv38Z+9U52vZYg5J2a1BCgwAEIAABCMwEAgh4M2EVmQMEIACBJiYwbu1Mh0c32miWiUguuZsW1aoijjWab1z3xizZOdFOKYRyjfXSY209sHGrUixd0F1YTbJGc1IBfwmKA3ZsZbQy9lAZgkgZ83Tr6cQymZWU2STgBVN5VadSDrZyi5aoPTxq08htmn/etR8dh6rWyfSvkyJ21cpyyVWtvJ5NBiWYYJR5B3FtCEAAAhBISwABLy1B+kMAAhCAQGwCSZ1jY18opEMzuDcWPUalu6neV1C0k4Dnb1VJPy5bHChD2CpLwCvL7beM+dZ6dLjaj6ttzcNaTWKaZ7BgI1Ul6rmovDzFvLzqy2X5rC07StY/Fxxts1xZzgUBCEAAAkUTQMArmjjXgwAEINCiBLJwjs0aneq46QW4r7/cyJ5G8/JqzVlhIM/oFTHQdbptuplSAJ3wEBTt/OOsStoeAl7Wd0Xt85VR68+NpCoCXpxxSMyTuYLuqTzFvDBRsZjd0fgqZaSZR5m3X8zD0TYKMY6BAAQgAIGyCSDglb0CXB8CEIDADCaQtXNs1qi6bWqoUqvqRdRkfb0k58trjBLtXLSQxAYV5N9gDSkaiXb+8ZfhvlqLn0QVvXznKXA2WrcyTDTiCElJ9lytPmULeGWusV9IlBgXV/DX/SWBXHXZlGYr4wulomcRmVfGXoi7p6pusqH5SMzrtA7DMsDA0TbuCnM8BCAAAQgURQABryjSXAcCEIBAixDI2zk2S4xFuSOmGXOWBfwl2ik1Vil++t8SEdZb0S6JiUcZqaP1BDy9cJdVH61oAU/rNn9Ohyc0jIza2n+2bqSE17zNE8oUYcqOsnT7LotxaP0kuik6T+YXQ/YeVP3GqMJ58B4oIkI3zfNLfauSbh91HrqnN47bo62oh6NtVGocBwEIQAACRRBAwCuCMteAAAQgMMMJOOdYCQsPrS7fmTQO7qqkgtYbc63C+XHmV0u088worPiTplVFwFOEYrcVRMoU8JwIk4Zno77+2mpaz5GxjVaw22jWD4x6UZSqWSgjj3X9NrIr5brWG0fZAp5KMEqoLLNJwMtyHBLnJai79VMUrKLz4oixRdfIjMu/GWr0BecUdCfXFwS6z/QnjrZxdwDHQwACEIBAlgQQ8LKkybkgAAEItAiBes6xVRF14iyDBLyH1lRbdIwbweIEH++l04oEcvfNQrTzc61KYfosIxTj7Bt3bJ4cNrsAt9loyc1rWMuV1XFQiqeiKrOOyitTwCvbabiotXYp7RJjo4p5ee6/JPdDsE9eJQCyGFu9czT6nSART6m23p/22UqDAAQgAAEIFEkAAa9I2lwLAhCAQBMTiOIcW/VokFr4m0F0jCoyetFocsG0EVn9VsSRcDdoU/TyaFlHIyUdY9kCXtbikouYFF+lVTpDEX9UVi0Bz/Fz9dZcVFet/klYS8BbsbYcobsqIpXGMWijV/O6p9y6uPXtbG/z0mwbrWFVDSLcXJqhRp//fogTMai6jF32eas5IuYlearQBwIQgAAE4hJAwItLjOMhAAEItBCBuM6xzeDqGly+ol7K02ybYEqX/1wuSkvC3ZBNn/REO/sTJw0vydiyqAeW5LrBPnrh1hqu7BvO4nSxzyEOo1ZoUx2zNM1FKnW0TdQmlClHvbpojQS84N6YY8enqDy3L5Km2ErAW24jVctoVblHixb7JcZq7eb1yi17tk2PtlGYg2NeurS7v8uMjIyyF5rtS52kEYM42kbZDRwDAQhAAAJpCSDgpSVIfwhAAAIzjEAa59iyo6GSLEVVhKhGYw8KB5tTK2dPRmlJ9ElaCD8JN0WdVeWOJAAAIABJREFUJHHkTHKtRn3iRMxkfW2dL42Ap7Grv+qgqa7dgKImI0RMRhXw3HwlBMk0obtzIuUvanqmn1eZAt6ieZ1mgxU0k4qPWa17mc7L/jqIuu9cVN5iy6bKJQCqEj0ZdQ9k8SWUxDx9odLdae/t9llmtv6CBgEIQAACEMiAAAJeBhA5BQQgAIFmJ+BMKFSMP40IpJfMrWykzjJrZNEsLWnERZHz00uwnGKVsiWxx6VWFi3a+edctnmEX5xauqC86LAkAvCEC+mEE7Ai7eKuY1wBz79u6jshLti6epsiuqIIY2UKeEVHvtW7t6sS7eYXZLtsPTaZmSjCMso6Fvnc0rUaRQ8XPZYo18tacJR217HpnsPRNsoKcAwEIAABCDQigIDH/oAABCDQogSyEu2C+KLWa6sK9ipHDUrgUUSIi5zaYNPn9KKeRmTNinuVuJXpJBxVwGu3qbGqSyfhLK2pSBoBzy98OtOEKMYXcY1UstpnOo8EPLkMl73vy9xntXi66FMZlugZ4dZRgnBVxLxm+32Qt+DoHG0R87J8QnAuCEAAAq1DAAGvddaamUIAAi1OQM6xSs+Tm6UEBPufubSqRMtEnVzVogb1Uu6EFY1N6Y7jtuDVbPsfff0jUaeV+3ESpBbMKa/2nH+CZYpLjQQ8vyGFapbJHTZutF2thcxCwPOfV+NUVKAzvljXPz1dtUzGVYl8q5qAFxTR3ToqXVrmF4qoVm3GsoTPqj1bozwUixQcnaNtjxVf221aNA0CEIAABCAQRgABL4wQn0MAAhBoYgJxTSiymGqzFS3XnIt8aavF2Ak9Lq1SIo/EHqXNqulFXWYEq9eVY9RQa8x6OS8zddU/pjLTOyV8KbVZqbCu+WsUhhlSJLnnshbw/GNwopCL5pLYr33Y6gJe2bUWa+2TRg6vWkel2ztRNkndwyR7099HIv+iuZ3WvXgo7akK6V/mGusZ0mMjdD1Rz64dDQIQgAAEIFDz398bbQMNBCAAAQjMHAJliHZ+es1QUy642ooaXLthZFIwK2I31BLtVJi+VupblaLd/GzKFHWCAt7KvqFSIo2cgKe1c7XtXI3CtM609fZhngKeu6YEWqVvK9VPEaAS9MoySyhToHU8dL/KMKJKYlRUwwVX91BfEMjBtigxryp1MqM+z6vyu8vvaIuYF3X1OA4CEIBAaxAgAq811plZQgACM5yARB+JBYr20Qtama1KtdGicpDLZVQH0KjnrPmt2aQ7YZvpslEWUWuhVSnazT+vqqQUlukOqohTCSMSuSTiFZGyWISA519nXU/ildLutWeLNkyowj6r4nMtSbRzUMxzbrZ5fJ0fVWBM80zNsm8Vx+scbXutmK4oPRxts1xxzgUBCECg+Qgg4DXfmjFiCEAAAh6BvEwo0uJtxrpHqmMmcULF4PNoXiSKjWTSS1i/vYYnglixNU6rSrSbf8xVqU1WdASlM6RQiqKEj1G7eYpMby5awNOaa61XrB20YuVmU5WiIrmqsPerGE2WxjFVz2lFVc7rbbduyLO9L3422DRw/ZmVmCeBUefLKxI1zvMzyrFpeEY5f9pjnKOt7kGl2iLmpSVKfwhAAALNRwABr/nWjBFDAAItTEAvzIPDo15x8rIKk0fBn7eTX5QxxDlGqY96mc3SJMLVQZNwN2QjJF3kUtKX46qIZX6uRQtn9da0COMUl/KsmmISP1TzThGvHbbOV7fdP3JJLaoVLeDVqg3mIrm0v534k5fzaRVSaBvVmytq3YPXyWrfaz/7HYldVF7a9Swqsjkr/s32ewtH26xWnvNAAAIQaB4CCHjNs1aMFAIQaEECzjnWS1mz7rF5OcdmjbbZXtyySo/zmxe4OmhZuI5qfbJ6Wc9yrasyJkXO9A/Wrh+Ydr5BQwq/uYjOXbSYVsY1GxX3l/ijdHCZrDjjC0WyJhWqg+tVprGAfyxKr1QElN+sJO3eSts/D1Ff6+miLLWeacS8PMaXllmj/mWbGaWZm8S8+dYVvM0uIJF5aUjSFwIQgEC1CSDgVXt9GB0EINCiBEas6+PaDcNehE8zNqWkqlXpZbcRxzQF6v3plFmLdv4xV1EUlXA2aOu+xU0HznpPZ536pv2giKQ53W1epKurbVdr3K0u4PmZOOML53y6rt9GKdro0zStKgJe3mn2SRjlLTgFxTyJ1/qdFHVNq1C7MCrXquyzqOOtdZyLIJxlJqKCcbRNQ5O+EIAABKpJAAGvmuvCqCAAgRYjIOdYpcUO2Eg7Y2tqqS7Ryr7hpqVQFTe/OADj1NnSy54icro7J2qguSiVPNOakxSsjzP/JMdWpcZVVuNQmqSEO6XFSqiQAB22pllFb8bhX7RomETgdlxcVJ6iiEftFxNxm64tgTaL5+Elt99tbl252v6sMbsvWWh/Fk38ucWi0GFlLRKHXjDkgKJrjWodJlyW2+0zb6P3u6qRYUuzCWLN+DsrKJ5vZetUBp2iZXzRZZ9pWjscbdPedfSHAAQgUD4BBLzy14ARQAACLUqgnnNs0S9meeBXVNqiuZ226P1QHqfP5Zxh9Y9cVJYcR7VGqkeoVMEwgSerwVYxha8qkZZpoqO0ruovQwpFvsZ1I24VAS+piOai8nqsiCCn3rjGF1nwlXB3yR13170VJeIdscsODYW8qkSbukmUKZBpTXS/uEjLWmvabL8DquhAG+d3RxTeSgHvsQKsxDwcbePQ5VgIQAAC1SGAgFedtWAkEIBACxCI6hwbJiY1A6o4EW1VmE+tem7OuECinf63orKCNdCKGnsVXTDzMP9IwjOukOgv2q91dYYUScTYLASmuHMuIwIvqYDnn5vf+MKZuoSlY6qP6usldfk97fc3eRF3Udqp+z6hrohXlXqPbh4SbBbYmmdZRCZGYVPvGLemekbKzMSJeYpkVQpnkeYuaeZRtQjLuHORANnRPisyb4l5E2s0sU7UzYtLnOMhAAEIlEMAAa8c7lwVAhBoIQJJnGNV70wvuEpRatbWbCKkS1EVd0WX+EU7pciGCQ15r1MZQlHYnKoiKrqIkrCai5sNKdo8U5gs1jXLFM8w3u7zogW8rMUif201zUnlA+oZX6TZY3HEO41DkXinPnWfmsug59mqdcOFRdyG7YUquuL6xTxvXW39wzXrhzMzNAljkubzZvt9FZyrBMiR0Y3efRS3SczrsEK5BD1FyiLmxSXI8RCAAASKI4CAVxxrrgQBCLQIgSycY5s9nUdLXUXThXpbUILCgt4OT7ibbf9DIl4W4k6WWz5JHbIsr1/rXFURFRuJGS6KUlF6zpBC65ulS2oW0Wlx1qpoAS/PdfZH5Y2N27qDAeOLpELVrQ+vNqddf3McrN6xSqU9YtcdpvWrmqNqlX9H6Hm60JZQUP1DNbeuitDL6r6LvbAhHfI2BMl6vMHzZSlAKiLPRVC2b1rDvMfP+SEAAQhAIBoBBLxonDgKAhCAQEMCMqEYtt9+9w9NuPSlbXqpVXpUM9WQC845blpjWmZJ+rvC5Yo6UHqzWtkpaY3mUTVXx6wjs5KsofrUitJyaxvHkCLJ9csQVmeSgOeYS/Tp2pQu64wvFE00YSoy2/T1j8RanrC6d41O9t3D9p/2cdXuvTR1H2OBTHiwUo7XbhjxRHOtoSKatY7O8KfsiGb/tMqsJ5gQ75Ruune2WdxjHlw1kLlA6jnZbkqzxQQji9XiHBCAAATSEUDAS8eP3hCAQAsT8DvHZiHaBVE2Ww254Pir6urn0ij1UqkUL1eLSy9xVTfeqFqUSFVefF2dtD4rGDhDChdtl3caehkMyhDwervbItfXSvtrwRlfyCTB6j9euvNaK+DFid561WXXJh5GMwh4Va/ZViti0Z86XSUxr6q/q6Ju4CgGFlHP1eg4HG2zoMg5IAABCKQjgICXjh+9IQCBFiNQzzk2DwxVK5oed45FvVREGdfm2mezJ9MoJboGTQuqFmUTnFuWaVJRuEU5pgrMJNoppVAupxsGxzxRNokhRZT5Bo+RKLF0QbdZvmYwSfdEfWa6gOeHotqUit5SixO9lUbAC5pZlCHShm0MlSjYMGAjvu2XEFVsYc+FoJgncyA9k8uYT5XTkaOsbRnj9zvaEpkXZZU4BgIQgEA2BBDwsuHIWSAAgRlMIKpzbNYInKlCkqLUWY8l6fnKjCKMKtr556aokRVrB2NF+iRlk6RfFUXdsBf1JPOM0kcCsSK0VLdwZGyjUXRIWSnn2jcIeFFWLf4xEmdHbRieRFkJFUrpU3Nup/Wi8tIIeMEIvDLSpMNIVa0mn3+8cQVPHa9ah71d7d5pVIpCkbNFifBVj2YM2wtlj9852vba+1PPYUwwwlaMzyEAAQgkJ4CAl5wdPSEAgRlMIIlzbNY49EKjNM/V1vmwWVvREWMSdfQS2N052xPhXMRO1BfBKgpk/rUv+0Wt1j4sUkjwG1JofV3Ujsa12EYkIeDl86RI4wSbdkT6IkPmB/5UaL/xhUuBD0ZuxXWg9Y8zKODlaeKRlE/V0un980iTkirWEuUlzmvdw4TapPz8/Yr+PZXFmKs6fudoq9/DEtsR87Jebc4HAQi0OgEEvFbfAcwfAhDwCDgTCvcyWAUsVUpBTcqjCCdaiTquSLrSsvTCp6jFqKJd1QUy//iqaAziitWP2ii4vJo/mlJpdhLu/NcrI43VP9eiI02LTqFN6gSbxX5oJFr70zDlHj1go/R070vcTWpisfuShebUp+4zZehlCpj1GJYV+RplTbVfkhiPBM/thFqlUOcp5lVZDA3jrXtgKxsBvGx1cSn8YWPyf+4cbWUUhZgXhxzHQgACEKhNAAGPnQEBCEDAEni4bygT99isYTbzi4VY5FWbx0Vi6cVO/7uWqJNkLaookPnnkdWLcRI29frkFbW4Oa2ubbJuYSNDijIFDQS8zbvjppVrpm2VfawolrRJwOu3dQ3DaqMFI7fW9Y+al/7o57EvG6x/pxOUKWDWmkDcFNXYEFJ2yKP8Q1DMc9HVcYxNak2rbPE/JWrTTI71ztG2x0bIt1tHYhoEIAABCMQngIAXnxk9IACBGUhgrXWvrGKtubzEkaKWMMvUs1qinV7iwl7s48w1TepXnOskPda5rVYprVoCy6Bdh0EbGZdFm6iFNSHMxommLFpE88+1aPGwjAi8sIgqCXc3rZou3jlO+yxeaJIIeXHNGiTIaKzzetvNbXZM77z6D2Y84tasFX2n8euLCKUGrrOmEVVois5eMKfDrOyrZnmFPFP93frOsbURtc5jdnEl1ipCL4mYV8Vnapw9lteXZHHGkORY1crr2VTTEhOMJATpAwEItCoBBLxWXXnmDQEITCEgo4oqvgwpkmGjfSupyotj3G2TNg1YL2suPVYva0pxzlq0888pS8ExLqsox1fxxb1WjbIoc/Ef4zekUDRlkjUu2kjCP/6ir12GgKcX7nrPoSvuW2YeHAhP4dump9sc8oitY22PNCnaen7ctbbPfOS6P5uN9v8k5NUTeeqJdxqsInOtj0ZlvuSpYkqvf1GLqik37feD/T0eJVrTP9ZmFcDcHPIUS2PdqCkOljg+f07npNt0ilPRFQIQgMCMJ4CAN+OXmAlCAAJRCIzbt7Mq1pCpekRYFLZJ0oDdvFU3p9/WtPJqE2YU4dVozFWvJ1TFdK+kaccuolLF6jUviUMS75LULtSalukg3MoCXlTxzt13cUU8CXhr1o8k3he67q0PrzY/uvNuc7uNEJxlN9u4VfEk5OlHwt0Ru+xgdt9iUd1HQxYidZRnZdRjqphK7x97kmd+1LnXO85fD1Ff9rgU27AI7TzSfdPOJU5/PXtWrRuaUhM0Tv+qHDvPflnpfpdUZUyMAwIQgEAVCSDgVXFVGBMEIFAKgRVrhrw0nCq1iVpHnWa5HVuztqhpwF5UiRXs9DM0KvdBK9rZnyRpUWlYlfHyGWe8ZaaK1hpnXDHBGVJonbOMqFTUzyrr2JxUAIyzBsFjixYPqxKB92D/oLni/mWx0R2y3dZmm97uSP2ydjmWucVsW35LTqdHPX7nSC6nWaeJR5p4g4OqFhHoH2oVvgQJinnOrbqWmBf191PaNcujfxVYZzWvLezzm1TarGhyHghAYCYTQMCbyavL3CAAgVgEqloHT4LSirVDpQgTsQDWObhRhIPfXVTCi5c6mSIKK4vxpknZy+L6YefIWtAIu17Y51HS+Vy0nYQHt85Zi7NlrlvRa1K0gFcvyjKs7l29vRMnCi9PcdQZI0hMHh6tn34Ztw5f2D2T9vMqp02mLZuQlk2wvzPDUTS3oi/7h0aNzHCc0F/1L2wa8ah6yYeoa6kUWt3nuNRGJcZxEIBAKxNAwGvl1WfuEIDAFAIqmK9UlKo1vTwOKI20gBTSPOYerDFURdHOP++q865axEijl0hF50kc6bBF9yXMKk02rwi5MrkUHf1XFQHvq3f+J/Ej4/U7PzpS3yLSk/0RW202PE8ij0yNXPRvFmm8kSYb8aCqCYr+YUcR9CNOM/PDgk7FQ/aZpBT+KpbPiDL5Zq/f5+Yod9ol87uiTJljIAABCLQ8AQS8lt8CAIAABByBUZs+W8VUVUW/KHKgr3+kKRdLL01yTNTLUnfnbO+l2NUnykvMSQMqaU23NNeM07dqAmPQWEMRL2KoFMWRsY2Fic9lihpFCzytJOAVnTKu/SzRWcKOSirI4XTh3E5rclSdKOiiBeM4z6dmEZWc+6wi82RipS/wJNwWXbIhDtvgsVWOxIwzL+0Z/RuBBgEIQAAC4QQQ8MIZcQQEINBCBKpYB69Z02Qk5OhFeE53m2m3RcXX2+grRbVUUbTzb/G4Nd2Kvj2qVnR9ok5jl42uG/FcBPXfaQ0pkjAts05ZKwh4ozbFXamH/lZEBJ5SHMuKkHLP3q6ONu8LFKV9j1pRuuyWZ1px2rlVzfCj0Xyc2Kh1dW7nEm2bRcwrOnU/7d6o15/6d3mR5bwQgMBMJICANxNXlTlBAAKJCaxZP+xFh1WpNVOh6qCzqNImVUB8CyvwPLRmsCmiG6oumOqlUzWDJJKV3Vw6dK8dk9yCvRqG1oCkjFamcFB0+q7bo4oOK4K3IirLEvCKSKEN26+KApSA56LyyhZ4yhQ1w1hVLUK40XiDX4bod60cbOfY/a4/x8YnIjAl6lUtMq+Z/l0Qtme0n6l/F0aJzyEAAQhMEEDAYydAAAIQ8BGQACERr2pNKVOr7biqEP0RZONEOxd9JdEuKOQULXCkWT8XUbbcCo5VbGXXmPIbUuilVgLtgt6O0qKk3BrVE5mKWMMi97ciRCUkaR2ca3beQl49tnmbWFThXpRQsnRBty2vMPE8cKmXEnicU3YRIqrbx1Vg0uieaqaosEZp91p3F5XnrbVNs+0fLO8LiiDzqn/RFPW5S/27qKQ4DgIQgAACHnsAAhCAwDQCVa2DV7WohmkvNzYFqVH0VdXSPsO2ftF1t8LG4/+8rBc3CYc9VjiqZUhRhZS+MmsX5i3gSbRR5KVqSEogl3AncWFl37AnKM3rnYgYkpjqN1+Is68aHVsvuvHB/kFzxf3LYl/mkO22Ntv0dof207wXWxMfuXCX1eoJZn7jC42tqKi8YM3JsrjUu26VowODY4763PKvte4zV8O1SOE2OPZmqTUYtj+pfxdGiM8hAAEITCVABB47AgIQgECAwEOrBytXp60q/1h3rqIq/K2USS8CJYI7blXGH3WzVz3isShRw29IodqFenEN1kETUwlYazeMlBohWmZqserv5RGd43dsljAnkUjrUEvElcggBr1d7ZlHhjUqlh83Cm+bnm5zyCO2jnQrav/p2hIqy2pRBDOthwRV/Uhc3WDT2/MSd8qOwG20DlWPDvSPPWkKalXEvJliYLF4Xpf3xQQNAhCAAASiEUDAi8aJoyAAgRYisGrdsPcCXKVWVtSVGHgvjJteTodsfTOXNhanJlCZ40+yjnlHVCUZk79P3lEuEmpdSrQT7RqZj1SBV5nmI1kLeJqLIgrriaaN7qdgZFgW6bVhYsEV9y0zDw6Ep5zHEe+036vw3Ijj+BsUd/KIiCxzn4c9tyR2LrKOvWVGTIaN0X2exVglWGo99IWWnOLlYluU0UkzpSo3WhPq30XdsRwHAQhAYIIAAh47AQIQgECAQFXr4BWZ1umP/HEiglL3kjrIJo12KGtzVj3lVy89WZuC6IVWtdU6rWBbq45ho7Uo0wHWjavMyKQs5u+PdhR/mZTUu9+iCltZpddGmV9YOu0+ixeafZYsjHVLxxHPYp04xsESaFSna836kRi9jHXennDhdsYXWQipGoCEXRuE6aVKV60lZVXGPLIeq/aqnp1uvYfsPZxHOrv38majbbdaWJ47c1brpXTkpQu7sjod54EABCDQEgQQ8FpimZkkBCAQh4BSnx4useZSvbEqrVNpinmlZmUt2gXnkYfoFGdd4xxb9ZTfrFJ8axlSJBFqy3SAdevqzAVW2wjaoltYhFqj8fjvO4l2UfhHFfDcddOm18aJMJSQF4zGiyvcuXGXKcq6MUjoabeRVmlcn4NCapoorTR7Le/7osw6lHHnlueXNC6lWlHMSqnOuj5i3Ps/Lpuijqf+XVGkuQ4EIDCTCCDgzaTVZC4QgEBmBJatGvCiHKrUFs7psC8DGzONvFCUiGpmqQaNUmJdce6kkXaNeFUhzTLqepYpBkUZY1qWftFIgpFS/dI4HFfhxb3Ml9q4AqYzgWmUJhsm+sm4Im5tuGB6rWq1RalhGUfAi7J/ox6TdZRU1Ov6j8tyb/uF1LHxZMJOI+fUJPPLsk+VxcXgPIsyhspDzKv6F0xR95TSrXWP0yAAAQhAIDoBBLzorDgSAhBoIQJVrIPnvczaNJ01NgovTVPUlVK75nRP/MNZ0QFK9clDtPOPM8+IhzQ8avXNoj5S1mPyny/Ji7Kr16SokEaGFEnGXaaBhBtv0Gxg+V3rzS3XLDfL/71hckpb7jjHbLnTHLPnAVslmWbdPhJ5Rq3iX8vgw9/Jpcl22Pt4xEb6NkqTbTTALMTKOOm1ZQp4aaPf0i50XHE26vVcenBne1ss0xFF3+r3U97P66jz8B8nUWxdf7lmNlHHXXQNOYm3ShmdY58V+lMCrgR01ZWNU09W80vy/I/KpcjjqH9XJG2uBQEIzBQCCHgzZSWZBwQgkCkBCVpKV61SSyMquVRJ1efRi0QWUVdx2Sgdrsdev4wUx7hj1fFF1hyMO744UUF+Q4qw2mpxx+GOr0Kqo/a4c+e99ov/niLcBeclIW/PA7a0Yt7cpFOe0i9MwBMfvbhrjFHTZPMW8Nz5/VFhwyNjXhRuME0/bcRnUshVEIbzFkuCUZFhtdMkPK1YOxhb9Em6BnH6FS2KxRmb/9iya8i5CFx9mSIxb1D33eD0+67e/JqFc6P1kTC/pa3lSoMABCAAgXgEEPDi8eJoCECgRQgM2X9Qx01PKwJNnDpyTrRzbqJxjQmynk8WUUNZj6nR+ar8ohzmRBk0pPCcg22qbF6tCinHeikeWT5iLvrEbZGnuf+xO2Qi4tUyFvDXF1S0VNR01SiDz+Ne8osKGoM/OqgsAa8Khg1Fpqy6dEtFSCtCq5bxRd4O1FH2X71jqjw2/5jTfBmWhk+tvkHnYlfGol6t27LFx6zmr3+XLLQptDQIQAACEIhHAAEvHi+OhgAEWohAFevghb1IT/tm3wo3tSJqyljGZnvxCGNdBkN3zVqCWTDKMotIr6hzDKavRu2X9XHXf+Mec8+tfbFO+/KzHhfr+FoH+yMi47jJJr1wHgKefyxufyllX/URe6ygVEbaZlhkY1J+cfrpOaBo7DQ1IuNcT8fqWSn2Lt1Sa6Co8Nn2gyXzu8zyNYNxT5n78dr3VR1bcPJVqK1Ya0GiiHkumreKXzDG2WTUv4tDi2MhAAEIbCaAgMdugAAEIFCHwMN9Q16qaZVavTpyeiFR1IZetPvti17eEVdJmWTlnpr0+nH65VX7Ks4Y6h3rF8ycIYXWX+tehmDrT1/NYn5JzqGad7/92j1ebbk4Tam0aWviKdVTRjBqLk1WaxG3tlXUcecl4N1y6+3mH7fe4Q3jZUcc5glJmptS71WrS1F5eblg15p73umrUXiXna7oXwNFco7bTSUxNa+9FYVJrWOaqURCM9RjdTVLu2z6fdvs2fa5PuFQrfqZ+qzP1hps5rblwi7TbtOHaRCAAAQgEI8AAl48XhwNAQi0EAFFMKkgd5Wa/yXJqztmRRv96OXaE+1yFA2y4FCU818WY41TZy6L68U5hwS8LWwkjl7mnSFF2Wtfdvqc6t6tuqc/dqSU6uHtf9yOcfBPHhtMk62V8pjoxCGdshbwzr/kMnPBjy6fdtU9dtvF7LH7Lub41x7pmd04kdKl+eUtIlVFwKtKzTmJqe65FJZqmce+a3TOsLT+osfT6HrN9HtI89D93ml/30tIV9Ozfq39t0ne919ea0b9u7zIcl4IQKAVCCDgtcIqM0cIQCARgSrWwVOE3YI5HVOEG30rX0VHwlrQqyyKBcdbxYgSF2nZYQU8RS88tHqwMmtftunHD0/+u2UyK7aAp3WPm0YbrDEoB1obrOYZVBTRshLwFHF3wSWXm3/cNhF1V689aa/dzftOPtHbay7is7PDRvvaqCClduYlJJTlfuvnUPa+9o/FiWTrBka8yEj9PpCIL3FVa5HXOkTZ080Q1ebmUXZUZRSe9Y7R2IdHx0y3vf9GxvTFXflrH3c+1L+LS4zjIQABCGwmgIDHboAABCDQgMADKwdK57P5hXm29wIt1zql9xZZkykrCFUUxerNrSp13fw11UbG9LI+ZgasU2jVXkLLNv0oQsDzO/pKrNM6qBUdfZSVgHfkUcdGurV1L+y6y87mI+995+Tx/tROCQl5RB+WXYdSc1y6oLsyNedqmXr4jS9cFHaRac5uQ1QhWjLKZm62Wqz+OQXH7tZeglgziXn6ElICNA0CEIAABOJB4CnLAAAgAElEQVQTQMCLz4weEIBACxEoqw6eXph7uybqaimqwqVLScDTS22WjpZFLmeV3P/C5l3mi57fjMTVVAtGWpYtbgT5aTxr1o+UFhEoAa/N3jdjVuSM2xpF4LlaVHpJrufkXHRR/CwEvA+c9snQyDvH0UU2vvRFh3q18YLNFdbX32cZEVT2nqqaMUMjkcxvgCCziwEr9OcZHRncA81S37SZfgfVus96rPC12tZADAp7+mKvt7vNRshOOBgXleYe91mr46l/l4QafSAAAQhMEEDAYydAAAIQaEBA7oN6CSqi6WVR9ezm2H+EuxdhXTuYHttMaai1uFUpJS1sXVXX7SHr+FhUalocQ4qq1XEqW1BUDbyVtgbeuBW5465XLQHPH/kqUarWvej2j1eP0gp8EjCLaGkFPKXOfvD0T0Ueqj81+eLvfKluP380WBbptRKFynC/dROsShSuG0/Uez4YmZVHdGRwExT9rIy8eQMHFi22Jx1nrX6KWgszsJjmRD9ijY0Gxwo1n2k0Z/vPHLP14p4ssXAuCEAAAi1FAAGvpZabyUIAAnEJ5F0HzxXBV3Fq/cNbET7rrWjXKD027ct7XAZZH98skRqadxGilN8IQcKT1j9KXcOq1ZySuFC0S6l/b95yzUPm1l+s8GqCxRHwgi60esHX/ajzKIrFpck2ug88sc8K780i4NUzrag3R7+A9+H3vsPsufuuDR8LWaXXlp0mrnWd0zM94inrZ2LU88UVNLUOXZvmoAgtPVvyiMorM1o5Kjt3XNWem3HGH1XAdef0R2Vq/atgfKIvKRfb3xU0CEAAAhBIRgABLxk3ekEAAi1CQNE8y6xRQJbNCTZKydP/rpeWV++azfSyVGsOcV9CsmQf91x5jtXVA5QhRRThNjh2RWMomqEo44QwdnoxVh2mKIJX2LmSfn7hKbfEFvAUfeevM5hkLYoW8DRepVOu7JuaSheVWxoBz6XR/uWaaycvt/WOO5itd9qh5uXdFw76MG56bdl1FasWrZWGR1BUldgu9/I4Yne9/aX9KFFmxdqhqFuwtOPyfKbnPak0gnZVxDzq3+W9Szg/BCAw0wkg4M30FWZ+EIBAagIr1gx5wkSaNi2txdYn0rfhSYuNN1MUW5BbM6UAZz1Wv1Ck1OioEV619l7RaZth+79Wgf2wPll/vv7+QXPlOXdaES/amQ86YSfz6N0XmE6bAqvIJAlMSRydi47UKlPA26Gj3ey5xeKagPc+4Nlm7wP2ryvkKfpGP1HTayVYLLcp7GW1os1JwuaZVfkBJ6pmFZVVtWdRI45pRLCw9cnz8yy/uHN1Pbvsc69ttiLzJqK+k/57JM68t7Bp8dp/NAhAAAIQSEYAAS8ZN3pBAAItRCBNHTy9AOqFtUcvrZ5AMGYG7T+U07ZmjiJoJifarF5M/e6lTrRLIhT5903VUqmrEBEoEfGBO9ebK6yI16jpZfgl79rNLN1xTioR1V2j6LXIU8Ab32q+0c/o47efRNh5y31m5D/Lzfpb7jZ7b7u12Xu7revi3XrHR5uDjjum7udx0muzEqySPm+zFvCTjkP98jDUcGuh309KGY8bIenmE6U2W5q5Z9U3SxEsqzFFPU9evzf17NIXGCoboC8qh+y/TxRFnfb3U615Uf8u6mpzHAQgAIH6BBDw2B0QgAAEQgjopWbVuuipQZ7osynSRClKnmhnf7JIVWq2F6ZaaJvJBTCNMKN56qVIL0dx06Sj3JRVS1urQrqhX3BRTbxbrlk+BaWYPeUF25olj+o187fvyewlNc0+ibLWwWPyEvCGD3isFe8WTBvSxo02MtEWwx//78Pm+X0bzeJVAw2HHSbiuc6Om1xTJWwrEsj/nCw7Ak/7adSGc5aZFu5Y5f3c9BuQDI/GMz6oQvp8lPsob4ZRxpD0GDFW6+vPzygnaH6SVNCtN0dF/C2Z35UUAf0gAAEIQMASQMBjG0AAAhAIITBqv5VebtNoGzW/Y6VLjYxiRJAUftGCQdJx1utXdmRN1PkoYmPpguhpfH5DCl1D9eny3Adyfsy6RmNUNsHjik4jrTXOWlGAblyqNZjXeqQV1OIyz+J6Rx517JTL1hPvdNDYqBXWrJDVbtPtFvR0mSfdeG+oiNconbbW3vGn10owU0RYnHsvLsMox6vOoItIinJ8nsdkFQ0cNkZ/rTSXXhlmfNEsEeFV+JIhjH+9z4tmnIeYR/27pKtPPwhAAAKbCSDgsRsgAAEIRCBQqw5e0aKdf5h6ydpmcY95YGXjSJgIUyvlkGaq4RdFJHN7QSKEoi3T1DeMsyAa20O2RliW0Z1xru8/tgqisqtZJsFBkY+KoEpbazAKjywEtSjXccdkcb1bbr3dfPD0T3mnbCTebRy30XdjY8bYuoLzuztNR1ub1+fAn94eOuTXnvXR0GP8B9z48GrPzbfdRkrKiXu2/fOxc+bFOkeWB0vA6x9MXqs0y7GUUY8vKOKs67dfSNio8mBrlrpyzexAW9azXv/WUK1E3Zed7W32eTo+6WYb9/cO9e+yfCJwLghAoFUJIOC16sozbwhAIBaBNeuHvX+0KgWnt6vdpsjO9kQT/Z0EmzzqxYQNsJlEsOBcio4mCGPZ6PN6nF0hcLkJFyES1RpjlfZAFVJ6JXIssKlmMrEYtimfirgr4t7MQlCLs0ezut4HTvuk+fvqZVbA26Pu5ceteDduX9rnd20W73TwTv962P6sbDjsqFF4N6xYZW6w4p2/OeFgo33QvmSHR5ilnZ2FC9VL5nca1UCVmFh2K7Men1uLeb3tnpizflM9V8clypccZfPT9Zvp946fVx71D5OsxzQzLvuMlcCt2nlhYh7175IQpw8EIACB6QQQ8NgVEIAABCIQGLEvcLMUgmKb6sIowqcIYaDR0BbOseldNhqiCvWZIiCcckizFD13L30blAq7KfLEb0ih9NiiRKJajCUw1IuKibsmWRxfVs0ytyYSF3RP9FnRpcj7s+gXbCfgrfj3OjN2x3qzceXwtOVr22Wuads1PHrtoz+/1PxhbKp45j+ZBLx5nR1e+mywhUXhRRHwLr7nfnN//3SnWRv4Y9rsFyZjmyLxdpjfa16+0/ZenbyiBLUqRZZVJZ03aEKiFGN9qVWmW3DUZ1eV1jPqmHVcXgYWccYQPNafah3FzZj6d2lo0xcCEIDAZgIIeOwGCEAAAhEJ6AWlqBfHKEPy6vlYB7k1VqxotlaFdMuozFzxcEUQKC1TYu6AIlAycBOOOoZ6x+mlflBRoBUYi8ZYZG1Df71BrYlEVjVFCa3smy5opWXdqH/cWolpx6K5d/yn3/T9dU3oqdr3XWxmb1G/cPw5/73J/GtgjVm1eq3d14NmcHCi3md3d5fp6e423VYUHVhnRcIaITZhtfDCBLx64p2uL6Zt9v/JRMK1nRbOMa/b/VGeOFuEcC3BZ8XaaqSoVzF6zD3HuzrazHp7/ykavVaKbegmLeCAZnagrXrqbxQxb56NjHZRpAUsN5eAAAQgMGMJIODN2KVlYhCAQNYEHlo9WGhUT9j4m9lRrxnGXrQhRdh61/q8zLS6WuMpQvDQumjezt3XHwGpfaVC6UULeGJRZPTh2B3rjPnXBi86LUprJOK99Y5rG56iv29dXQEvLI22kYB334YBc8m9D9S9tkQBudMGIymPeOS2ZscFczyh1qVzhpksRGFU65giBemwMSpdftW64Ur9DtKY9UWSan+O2MhXRVmpZe1eGsYmyufN8Dun3jyqKN7WG6srLaG94O5PRarPt89lCb40CEAAAhBIRwABLx0/ekMAAhUl8Me/3GbW2RfEJ+21q5k/tzeTUerlSREGVWp6wXxw1UBo/ZkqjdmNpayi3GEsnCFFb3e7re8z6tX30QtqGaJQ2FjLKGzfaEx5igz+1GWJdsHU8btuW23+fcdam87X5qW477TrQrPTbovCEGb2eVEC3vjDQ2b0+lWT6aVRJjBria1f99QlNQ8NE/BGhoZM38OrEkXgNTKxaBR9p4Eq4nVWDQHvKVssMk9Zutiby+Y6lO3esznrCLCi1jTKGhYhjkcZR/CY4JcIzvjCE/Xss9NffiDJ+bPq08wOtFX9XRm2NtoL+qJlrv1dKkMaGgQgAAEIpCeAgJeeIWeAAAQqROD+ZQ+b1739DPPkvXcz69b3G/33OR97q9lu6y1Sj1KGFTKzqFKrWg20OGyqNHZ/tJ0zpJAYoKzBKkdu6AVpjo1GW23F5Sq0rNdU6yLDGNVMVBRHLXdfCXfnnfWXyel7Dqa+tMsDD3+0OfDwHXLHk7aQ/4MPrDEPPrh2cpzbbLPAbLPtwmnjHvn9Sq/mnasP5z9g7dqptewWLNgsYNaLwrtq5d1GP41a38MrzfCm1Fr/cY1q4G2946PNQccdU/e059x6V8Nr1hPw1Omtu+80pa9L4ZN4O25v2izSa4uuaxi2QasUDegfa73afMG0Shlf5BUpGcZOn1c9DbXeHKq2D6OwDh5D/bsk1OgDAQhAoDYBBDx2BgQg0NQEbvvXvd74d3vMI70/z/j89z2x7qgXH+j996lnfNX787RTXp96nqrt8/DaifpQVWnN+lIiflUYu0v/6rCpl40MKar68lxmymite0CpXllE3LgoyFppsv7rnnfmzeau26fWgQsKeDpe0XhvevcTcr1tk+6Rm/58j7n5ponnWLBtbUW8ffZ55BQhb/iyB73DnIA3ODhg1q5dY4aGphtB6LgFCxban0WmnqnFnf2rzefuu7khm/HhYbNq+cNTjlm0qt88+cb/1u130LFHm613qi+cZing+Qfh6rKlTa/Nyuk3i01XdI3FOGPWPb+uv7FTr55TishTJJai8rIQWOOMUcc2Uxqqf27ud1RVvqSJy13H6wsYlTagQQACEIBAegIIeOkZcgYIQKAEAi7STsKdRLw3v+5F5vDnPc289X3neOKdIvDUdNyRr/+AufqHZ2eSSrvMpqv6gntKmPnUS1bRnS4qlLKcaP011Fy0XZiTb56poVF51Tquai/2aZ0y9bKql3w1Rew0WperL73bXH3pf6ZhkXAjkSDY8hbxkkTgXXH538wyX9Rdvb1w8CGPmxTx/ALehg39ZvnyZaFbqKur22y11Tam87Btah7rjCzqnUj3zODAoFm7YuXkIY0MLMLEO50kTMDTNdVquQkHI/Dq3Rt6xsghNUl6bZWiW8VisRXKVlTsCyRxj+vsGhRYtTZFmEPFHWfoTVXQAVX4oivtVLew9Rupf5eWIv0hAAEITBBAwGMnQAACTUlAkXbz580xx7/mcNNnU2VdnTv9vdopJ/zf5LyUUnvUS55n9n9a+gicqtXBq3J6Z9jGKtKJVkKXIkCUYqeXYaViShyqJQ7UGnfWqaFhbOJ8njTyK841oh6relgSuJUqF7UFTSlqpcnWOtdJR/+y5iVqReC5A9908t651cWLWy8tqnjnxi4Rb8t1bWbsjvXeX42MDNmU2/omEEE4EvG2f/0+NZmFReFpjXSvqB6eRLx60XdKm937gP0bRt65AUQR8OR8W+sLkygCnruOP5VTfxc1+ktfjnTb58Wa9eW7fFf5i5okwrX3AmKfyRJYXVRe3sYXSccZ9TmW13FV/t0Tdc5iTw28qLQ4DgIQgEBjAgh47BAIQKApCUiUe7cV6eZZg4prr7vJm8PhBz3d/Omvt5szPvc9L+LOtXO/+WPvfx7/2hemnquEibUbyn+h80+kWQtc6wVuq4XdZpl1982ruVRMiXeK9IgqDgXHoygIRXWFRerlNY9G561ScXu9kCtwSiYTYc2fJhtXUK0XfadrNhLw8ozCiyPgqd7dlVf8PQzRtM+PecMzjIvAu/fexnXrap389kc+YA457MU1r9tIxHMCnjo+pmeheeZtU9OW9fdb77hDJOHOXTzMxELXrCXg+U0s4gKMk15bJYOYqhowZFWfzUU7Kno2SbRk2D6ocgRj2Nib9fe7m5fWdOnCrrBp8jkEIAABCEQkgIAXERSHQQAC1SLgGVU8YXdz4823mhc+/xnmtjvv8YQ8CXcHvvwkr+adS6PNUsAbGhmrnBtpM39Dn8fLid+QQiYUSsVUfbuo0Xa1dnocYaroO6VK6x9FaNAxitSLmr5ci2e96LswAU+fn/31Z+eyRHEEvLjRd27AT7D18PZ8oNPWvFtt+mzdO7u9I7frH7rBXP/QjebcL/2gYZ+gqYUSWRU9s0PXAvP8JTuYnXuzcfa9z7qEX3Jv/QjCegLeEY/c1jxiTk/kedc60EV/Kb122D7Tawn7Vbrng06vqSafYeesIwOD0ZJD9rmdhfFFlOdShlgyO1VWAmlmA0pwIurfJYBGFwhAAAINCCDgsT0gAIGmJCBR7gv25/rLz51Mn3XC3QO27p0+k/usnGhlZHHae95gnrzXrpnMtWp18Kr6chcFdpbik5fyZiPtnPGBhLusaitl/aIahU3UY7Iyjoh6vUbH1asbFkyTTbs2jQQ8f7RYrbHmKeCt7BuKJBR/7Su/TYRbzrSH7/EY89D195hVqyccZyWwRRHyLrjrEnPfhvvN29/xfrPLro8Nvb4i8v41sMZLOX/p9jvnkkraKApP15WjrER417br7TZHPmq70LFHPSAoGMmAZdCKRmp6rsrNuApRt1WNAM4zSlHPEj3P9TM2ns74Iklqf9Q9lOdxzSo8+pksntflOYnTIAABCEAgGwIIeNlw5CwQgEDBBGROIcFOEXdynVU79cyveVF3L7RmFt+5+BrzRxudp6bUWedSm8UwH7Yv6YroqkqTuDTHvmyu7BuuypAijyNtge4khhSRB+c7sGpur/45pGWYhEe9PsG6hptT42Z5abVpIyHddcMEvHErvNQTtfIS8OIYnSQR8LTXJTgd96ZnmTu+8Me6rrO11ua/6+8zF/77R95Hhxx6ZN002lp9vVTn7vxqwdUS8cZXb/Ci/pRCKwFvVneHecSS+ZmKd8G5BtNrO+y8lc5ZBQFP5jCDtmanExezvGfTnKsIYcwvsiZ1Fk5rrpOGUZq+VXq2J50H9e+SkqMfBCAAgdoEEPDYGRCAQNMSkGGFhDylyyrSTm6znzvtbZlF2tUDIyFiXX916uAVUUsur02S1IlWkQnOkELFz5VmlSZFNmx+VWZcpVS/iZSvTk+sS5sm22hNyhbwfnbFFeauO+40d9155+Qw99xjN/Os5x1kdnzMzmHbyUQV8LTvJGQpyk77W2KW6uCd/o6TzEt3OiL0OjrAL95VTcAbvG7C1favu84yNzy82ki427imf9q89v77g0Y/c0893HTsnl0EXi2AfnOFoVH7bJHwbP8ss0kcXr1+OLOI4qzmUrQwpi9SFJHnjC+0Nlojf5Rmrbk1qwNtlhHqWa15nPOoHumW1sCCBgEIQAAC2RFAwMuOJWeCAARKIHDuty41P7rqt+YRNgovK6fZsGlUsQ7elrZItCLw8hSxwrgk+TyOE61e3vTi5lJkvWLnBUZC5lGvLwmzYJ+quGW6aMheu0b9VlCViJfXfmxkYuGlXtaJwEtrYvGvO+4w533mszWXzaXu7rTzzub4E9/ecGnDBDyJSF4NOHsWby6+cEIJeFdcfpH5x69vMEc8+kUNr3O/TZm94N+XTOkfNYXWnTjrCDyJdoPXrZo27vH77jN/edSomTU+4bIrMxQ50Eq487fuI55seuxP3k3iycjoRtPRLvnUeHXy9MwJE4vyGFdVBagyhUV/xKRbm3pCa5WcuuPsj6r+zok6B+rfRSXFcRCAAASiE0DAi86KIyEAAQhMEnhg5UClaKgO2oAVTYoUtLIAEBbZ5jek0PWyTMOMO/6qRkPEEUHjzjnK8S6FW2ul9Vk0t9PkfX/cddtqc95Zf6k5vHrmBzr4TSfvbXbaLZkJQyPxTuf2194LE/HqmVhMCndWuKolfsrEYp8nPsoT8H525SVeRNa+W/2PNXXYzmw/9xGTPGRY8d/195v7++/3xuUi+CSIhZlYBKGmEYg33nK/d7pZe25nRu/t94S70XunPzvHHrSutoOboprH1pvZg/8yEuzr1bAsIhLPnxLtUsG7bFqt6jdmYawQ5d5yx1RVgKqCA7Y/YlJO4YrI7h8anRRam9UIolnH7d/X+l2gaHkaBCAAAQhkRwABLzuWnAkCEGghAlWrg5c0FbUKS6bowRVrh6ZEtnhRP/Yf/kqXUtRLLZfIosdeVZFUL3qLrYArhkU1v7Aqoclf/D+OG2ua8Z535s3mrtut8BNos/VGb2PXJFb5W9rou3ce/+aGww1G/jUS8W768z3m5pvunTyf0mQVcaborkZRiwcf8jizzbYLPVHuzce9IlZKpfq85MUvMwfbGnhxBKi4hfQl2o3/8E9m4y1THWbHlg2Zkd12NuNbLPF+XNs4MGzGl62dytaKeJ0jdzWc36LvHp9m+4T2rSVOBcWidf35p9fqmksXdJvlawZDx1zkAWFfvhQ5FnetzTU3J+oX6qft/9n7EgC5qjLrr7q6eu90d/aE7CshhLAqSNgRUEQQRDZZVHRmHGVwRn4ZcXRAUQR13EYcNzZZRFRA1qAou7InIUD2PelO73tXd1X3f8+r3OpXr95y31b12nx35hnSddfz7nude+p83xFEcLnIE9vRE520FyrYuH3uVPosdB38bi+Ns4FFoXHn8RgBRuAfGwEm8P6x7y+vjhFgBEJCoLN3SDsER6UUW4XlBwepbANxIXPb4b+LGbJmtp4ou/0i1KqxPfwDvtFN1ixM1o2Zg599g7ZmJJ4ZgeeXvEPOu5WPPuaKwEPlf7n632jBokWm7R57ZDXtberSjClANiJU1q5I9R3q4D407txAX7v+v1xBeOvP7iWQ/VXlIsxZqJRUiDw3TqMg79JfeThvTuk2YbAzOLq+5IqjsyRejvpO17I03UTDA7nhs/qOww6ltXumcM/w5QK+ZEAxqr5c3RSHysUg6FXmH9V5Ye5G4wvkyesQOQSLEf6sgqVZnbFuYMH577zeeW7HCDACjIA9Akzg8Q5hBBgBRsADAlHLgxdFNYQqrFC2JYRKAgUupWHmTlOdk1k9P6GEfsZVaasnG7rv/JvWpOfOv2t/li0/QFwzqPayo1W6Mq2jNw3B/bHLBVboUGNjPjwo2cQRXpBiGcLotLPniGuu57WjoZP6DnXMcu+dduYH6fQzz8wZW5/L8Y67X6Xdu/NVhMbJTp1WJ9xjD8n+GGPBQOArX/sKbVifcdt2Kvrcd3olmZPCFfceh3Hcd7tiRd6NiJDG4bZ89ZMk8dJbmk27xRxjPeZh0mhQumQ61V53jtOyPX+uSopLtXBZIq5MirqZlFSVtXdHy2U8yu9DPb74/YJ3AhxsEWJbCNWkm/trVbfQ79Eg5qzvA+R2vQih5cIIMAKMACMQLAJM4AWLJ/fGCDAC+wkCUMsUQvHkBs5iJhR3M0/U1Su5ZMggTDiiXKKscsS9b3phM7Xf9hINrsrkHTMrNZe9V5nIwz2qKCvRFFsgVlXDmHFgLoZzJ4g8lIQIv4YKDyS7X+JOYuiVwEP77/7kf7VujLkC+4UpAopVPjw5tl55J38mCTw8M+vXvU3f/97XLe/5wkVL6Av/8VXLzyU5iwpm5IYqgZc651bTMYZ7RD6ynsxajaX/nDPJjsCjvo1ZUwuz9mGF0XrJPxZWeG1UQynHStoGqQgGoS9VkyDzipHL0PIhNPlgrBtYcP47N3eb6zICjAAjoI4AE3jqWHFNRoARYARyEGjuEDmdxDf6USn11QlCqJAkBqIyLz3pAAdZOMnisCsNKTQyr6pUc9GNcolqLipgVrGhibZ+9j6lEDEo8iZ896OWUBvdft0qIqEMSwrCr1j7MAzCww+B95Nf/pQQfg2i2k79g7x4xgLDCrOiJ/Dk54/+8YG8qgsXHUSLFh+k9FhJghqV9fNUIfCG73tFy3tnVuwIPOTES5abm4poqQyTjRQbarScf5gEnp+8kpKsxcT9hteCKIOCzEkBqXSTA6yEEE/8/ivWc666FDMlJZ4f7Gv8LsIa8IUDfndGJcTWC4Gsikeh6nH+u0IhzeMwAozA/oYAE3j72x3n9TICjEBgCEQtD15UFREyxKxKHJb6RN5AMyWXarhaYDfPY0dRnGdy1U7qvOb3Wsio6gHUTIlnDJP1ejAHWYV0bsXKEantt4p4oEnrVQm8EXEDZCo7zVFW/M//3fZ/gYeFmxF4Hrd0XjNJ5GGM3oGMcs6JQLJS36GtHYGHz3uWv8d06sUk8IIKWw0ivDaqRFlUTX30m0mFCJP7Hao8mXd1UJB5xSxhfAlRyPXgfTF1fGUhh+SxGAFGgBHYbxBgAm+/udW8UEaAEQgaASgr2roL5/zpNH8cROqECq+QbqRWc9K7lIJUQrgSwjCtHDbHSvhvFOfZ+h8PUGqNcPzUkUdOewWfT/vTv2mhzCB+ESrrJkzWrv9iK4aCIl/0a1Qh8KR5Rkzk3wP5hH0/Z8EC+uwXrs6Bq2nTSmra/FQehNUN82jKvNOoZvx8x9sXJoEnB5d7A7msnEwAfBF47z1WyNTMHUJjg9YKvDBNLILO7+YnvBaK1gERbj0g3p9RKnDpbe1K2romF3u+bu6jvEcweEkPD/tWTvpZ+1g3sOD8d37uPrdlBBgBRsAeASbweIcwAowAI+ARgZQIvdkrwmijVKZPqKTdrf1FmxKUA8gzBFMKN4YUY0HNAVCLld/N7obuOfUHmkIKrJGTk6nsB4fVyZ8+lqZ+5lhX90llY7lxLVXpz22dMHIV/uR/vk+bNmywnQoIL9wGKCGlCk/vQtvTtkkQdyupt32zbT9T5r2fpsw/zXEsEDuFCDuHohLPdExsGivnWj8EXt/p76fhxk7T9Zb0WptYhBU+i4mEuYfl/gThC8UXMLVTzsLMAGrvVNrepdjtc+K3fhTVyMY1ef0yAfcIex7XYErcI6FELaQqb6wbWOCLRGDPhRFgBBgBRiB4BJjAC1vE04sAACAASURBVB5T7pERYAT2IwSilgevGP/wNxpS4FDqNvwSJAFK1PI8Gbdy1JQRcJyF2ywIORACVgpHPXGH+4UCV9qKS8zDF/08wmu7f0U4AGMfoEypOIymVhzuqcs37s11aJ16cAVNW1ZRcHJr4/r1dOv3f5A3LpAE7priTvy3PoR2/sKFOeq71U9do4yBE4lXCAWenCyezZRgJOFWi0M58oYZnWvtCDz0k260/qJDM7LYI+6zQYUXG+6hWP9GU8zCVN9hQK/Ej/INFhX1JBFIPLwzzZ7fKCrdopwPVH8P/ObjxDqhyINCOV6Cd1pKSw2gmqrAzX7Q1x3rBhYThakS9jcXRoARYAQYgeARYAIveEy5R0aAEdiPEOjoGcwSFVFYdqEIJhxspKMfyARJ2jkRSFYYIdSpUhAD7d3RNrKIWp5BSeAB17hQPaYtVDqaOmxfWKfMlefGkVZlb6/q+CWt7vxVhkwU4xnn8v4pP1Im8kDcvXFfLnkn5wAS77AL6y2JPJW8VyrrMdbRk3iSMAWBl96Xe1CG0Jqp7za9equj8s443rwj/tkynLYYBJ6elDc61/Zf+wcaeUuEcVsUqzx46YnjaXDFMVorI4kXT26kkVRPXo+lS6ZT7XXneLmFym0KmcfRKbw2iko3GN1AZVUIBajyTTOpGGTKA0m4IjwUxhd2hjR+5hzW+8vPnNy05fx3btDiuowAI8AIuEeACTz3mHELRoARYASyCEQtD17YRJhMyg7yzqjC8bMtcCBsqCmLRP4+u3WEEZ7pBzc9gQcM9WF2WZJJsEwIrZXEkhwvSAJvZePnqCn5RnYpVmTilPLD6LSpP7Zd8mPXNVLjWwOOsHzgG1MtSTyolvZ2OPfhOIihwu5tm+kHt3xPU9sBU31QY4bAy4TQGkNnN7/2U7dDEXLizT/yX0zbqRB4nbF3qatkHY0bXkx1Iwe6Hl82kAo8M1WtfB7673qZum9/yVaZlG4T5PxgbhhocsXRNDxxQnZuw+29NNLRRyUDGyk+0punSKu57mxKLDnA81pUG/pVbqmOY6ynNxCRX4pMGFceyl72Oke0GysmC2Eo2fCYlwt1WbVQpsL4Avld8bswqBDnsYKt1f7Bvw3g4MyFEWAEGAFGIBwEmMALB1fulRFgBPYTBKKWBy8MIkxvSIHbijBXO0MKr7e+2Pn7VOYdBr4q41rVgQNt23/8Tvs4IQ6VQ8I9UXM/FTKILMlkkTorKAJPT96N66ygcV2VmgKvo6aPuurySTQ7JZ4qeSfxsCLxglQt6fc/9v2bq96mx/74aF5OPChPPnT2WXTCaWfk3C4r0wqV+37I+28xrWZF4IG02xF/WCPujAVE3sz0h12TeXYEnhwDxFPqKw/R8JpdpmSxrKdX4unVd/q51lx8AMXefIfwrMkwbKjuCkHcyXkU2zhCH16LfdUizCKCIohU9p1TnUKEGDvNwenzQijZjOpJfKHnlNPQad6FUtE7zcPr55z/zity3I4RYAQYATUEmMBTw4lrMQKMACNgiUBT+4Bj7rFCwheU6kBz8NuXyBsKAygNwjxEBhnuFCbeUSMaYWKBAsIDBfmZVEKZx3/3PCpfPsMXVDJsdsaOBpqxc3y2LxgeIB8cys4ZbbRzZnvOOJfOfiFv3D1rBujxrzS6ns8nH5qT1yYIAk/mdpRqQhDXdrhCOVMq2BZjHkc/BJ5VLjwzAg/k3dqEOeGnB2jp0DWuSDw3ajTkwpPh2pqZh4Vx6sicyZR8z3sptT1juFM6q1K7KlZk1HhWWLreHB4bFCOXqNlUQeQBf6g7wwzbdAuTmz3htu+g6oetRjfOU6onocoD8YzfmV6ML8bK70Gr+8T574LawdwPI8AIMALmCDCBxzuDEWAEGAGfCLSJvG34x3pUip/DZxCGFF5xGCtOtDhg4Z6rkGResVBth0Nq/90vU8svX9SaYE4qCdbLlh9AE777UdVhLOs9tPoUOujt/JBGPYGHxl3j+untpaM50g6p+yQtr/9UTr9u1XeyMfLhHXZRfU5ffkJo9c+AG7WpFenkxrzCCLQqgadK3sn+3ZB4bsmatFDiIR+eyPmvEU9GIi928HQqufBIih1sHQpbbAIvKs+4PpxSTxDhy5RCmClYPfh4V3f3Rc8ZVz/fYuUrlaq8SvHlF/a+W1VeUF/A+X65e+iA8995AI2bMAKMACPgEgEm8FwCxtUZAUaAETAigG/bYWYRlYIQHKif3Di6yqT0IC8QJuikNgpjrWPFidYPQRoEbvqQThB22H87P/cbSq/ZrR0YVQi8INR3WMuG+y5TXpKexDPLhfers7cq96WvCFOLD944NY/AaxVhh25IVpnfsUyQotj/bp2Ui6nAe7EslwxVAfJ9g79UqaYpwAagKBLvBdUy8tYujcQbvu/VLJFXffnRNLBwCqWXTHPsptjvgqg4v5qFqkJpm3FGzeQh9ar0crwJNhWigo/dGtwSz37wsGqrD4WGgrIX6SdEmgOrErUUDW4xKRfvTuRs5MIIMAKMACMQHgJM4IWHLffMCDAC+wkC+Ad5S2cyMqtVDR3CYaFGOL+CsBgS7qX9SMbt4pAe9IJV5x30uG77A0GKw5hbgsftOMb6UhkmD+5GkrXjmt9R8s2deWYVxn6CIu+6nv01Ne1e6WpZehLPGEbrlcDDBIxhtCBZO3qGlAg8vaOqNA5wtah9la2Sz/sJoVXJgbcj/pCW985tQT68memzHZuBCOkb8BYOKDuHKgmkU3VFXLsnTg6eKnn3HCfuo0IQIdg+hs82tXvXSKUXXFFVMA1iPrKPqOBjt6YohaLK/V9RVpI1vjBTUI51AwvOfxfkU8Z9MQKMACNgjgATeLwzGAFGgBEIAIHGtn5H4iSAYZS6yCTvLhPOhfmkYqEMKZQmaqg0VtQHhU7grldH2oV0Yl4dt72UDac13oOgTCtkv00PfIW6Uttd3+q/HbNJaxM2gdfZax/iB1xBFEFxCuLOS74q/eK1nJGiTxCH+tLTtonCdKH1or6T81NR4QVB4OnxkKGg+JkVkVcskjxqBJWq+rGQ4bWFMIdw/VIxaRDVUFSpygPxasxrONYNLDj/XRA7l/tgBBgBRsAeASbweIcwAowAIxAAAlHLgze5vpxau0bztMnwQKneCoKwCAC2vC6iZhBhtsZCKAX1RKuqOtJIIHXf+Tdt+mXCqMKvWYURh/53niNcrYPvut4GMLUYWjCHTpv645y2QSvwzMgho6NskKHi2jMmFGZGAg+L3PTqrdTbvlkJq0ES/xcbotdWzKXuiXU0Kz2NZqenZ/9EJ3oTi7FG4EkQJOmEPHnI6YZQUBn+XczwR6ilJtVViC9A8h2UlW5ggJXwRYwTEa0fDl+C4B0PtWNY4bWFeP/5hXAskIzYZ+XinVEtvkSA8QWeAZB6+LdEmGZRfrG1ao/8dwithgM5F0aAEWAEGIHwEGACLzxsuWdGgBHYjxBAOAwOWlEpSDI+OJQmmAnIECvpjKeSI61Y63B7YC3GPHFIRqgQCNKgiz6s2W0uQkmIhDEv4zr9EnjjD/5InomFVwLPzMTCqBqT4ccJcWAeEiHvQRJ3ekLKisBTJfHaSjo08m7d+5Zq5J2xgMz7eP9Z/xAEXg5ugrgA8STNGfB8+Q3b9fpsYq+MF+/P5gikRfCaa06GbOLdj7yYTiHLbrCCchWEU5cwsYhqGQskox47GQ4NBV5S/N52a3wRhfvA+e+icBd4DowAI7A/IMAE3v5wl3mNjAAjEDoCUcqDJ0MDsWi3JFDoQDkMMFacaIPOAWUMk9WrkVTvSSGJB0ng9aVbqF9cbgoUeCeteCSvyRv3dtAb93W46Uqra8x/h5/J0EOoFxEmK40p8Dy4MbZwMxk7BZ7sx06J1xhv1qpZkXeyD5B4lyc/rK0RZK2dAq+3u516u/Mxra6tp+raBlIJoS2UactoTrdSsdQRTcnoN6zZzf2TdcMk6N3OJ4j3TNDhtXieRBpDzQU3qqVYDrR+8JApJPBFYG1VRpUnv3QrxnPgdi21gnyU5jNu23J9RoARYAQYAXUEmMBTx4prMgKMACNgi0Ax8+BJhRGIChAUQ6kRSpTGQlGJhbkNxsrBK4j8SrhnWC8SmweVhy2IA7/K/ZUEHup2Dm2n1EifSjOtzpRll9C4paeb1n/sukZqfEs9dNFMfYeO64WCC2o7kEJeHGWVF6OrqKqARE683vZN1LT5qWxrKO+2HjiVdi+eqTT0nOHp9PnSc7Xn+63Sm6mrZF1Ou8FkP3W0Ntr21b+rjFbUfY9mzjnItp4bQxDZ0ZZ1PbRVXH/5Y1NO33MWVdNJH55KcxfXWI6JezZROFlCPQwiG0RRWKSr2SRUiFilm+SzUtChvHjfZL4oQN7HtOe8j6p5+Xwu31fzYoZge5248XefJLQrhTIVKsqk+PLBzPjC63hBt+P8d0Ejyv0xAowAI2COABN4vDMYAUaAEQgIgZaupEbEFKrIfF5wksU/9nuFUyQOvDjs4u9TRD6axnZ1MqRQ87YbR5UEKfZc/aiSZD5CkK1BKyQLReANNW+j7ufuzt4GVRJvXOksGn/CpykxabblLVQl8aYeXEEfvHFqTj8gKOTzAGw7ChjW7lW59VzZa4TLbfl8/Fyq7ZwoHGhzXWhVyDuMtfvB8TSwu5zOv+w6WxLPLYH3l4cb84g749pA5H3ymgWWS5ah9OWJuLJzrVVnewfeobVdv6fmZH6+xqXjPkJL687N20MIBzTLZej2HvmpH5aiVu+Iivn19rtzH4+Su6sVvmNhjsa525GO0vgCYebpYZECoC9VFHWq3X7G7x7Of+fniee2jAAjwAioIcAEnhpOXIsRYAQYAUcECpUHTxJAVYK46xPqFCtDirF4iJHqmyjkn7K74V5UKPrQ5rBUYbjnSIJeCMVS17O/plTLqAutXThtaayKquITqXLygTTu+I87PktO4bRG5Z3RURYEDApwLlTRG0u4GfPXlX+k7fE9bppodRfHZ9B5nR/U/luvwtu7e4tjX1Df7XloQrbev391lIw1NnZD4P3qlo20dX2v4/ioYEfiGXO/qTjXmg26tvP3grz7g+18JpUfSCdNvi5bB3upVKjVCrl3zCaINcPgoF08z2EVL+G1uDfNnQNZw5Gw5uan3yAU0n7G99JW5fe1nnyVxhdRUOVx/jsvd5zbMAKMACPgDQEm8Lzhxq0YAUaAEchDAMmnwzIQ0LtnwoQCyd6d8nmNlXxyRiDHwuFL5vpxOuTrQ5uDCpO1e/T8KAPdPtJGFZ5sDyIPBWaEyJWVEORdoqRK+1ntcZfYqu+McwCRZyyHXVSv/QjYIkk/CBejkrEYJIxXAu+bNT9zC71WPyHMVK7p/LT2352xd2lt4haR7848551+ACN5h8+OOeFccZ1nOg9VAg9hs7d9Z5OrtZx01hQtpNZYrEgiPZGHLy76xWVV/rL3RlPVnVl9PYkXlRxv2MOFUgLq8w8OpUWopiC+zfKujQVl91hwoDXuQS+44lmAihuKY3nPksKgpxgmVQj/hfEMF0aAEWAEGIHwEWACL3yMeQRGgBHYjxDY3dof6Gqlmx4O6yApQNylRGJ+lTJW8skZ11JIEkoFR7M6uC8V4oBtFWanD5OFo2Ch8nh5UQZ6xQDtrEg8fIaQUv1edUveWc3LSIqaOcoWwymzmASexOreVWdQ5QHWii0z8g5tZ8xeQh+7/CumkKsSeF/99CpXW2mIBkgEb9J7fvnrnHYHjZxFB9YuE+HPKWor3Ugbyx/P+XxB8gO0NH2mRt7qnWv1xAXCZv/a/E1X85EkHpxAQYjYkYOuOvZYGe9vkOBOXxJ47N60mTG81uhcHlZYb5BrGGsOtPJd2VDjzfkY9wxqvGIaX4yvLddyuXJhBBgBRoARCB8BJvDCx5hHYAQYgf0IgSDy4BkNKZyUJlbwjpV8csb54wCNENAouxyaYYuDFAgFKHgwf6/3zc/jUgz1kBWJpyfwgiDv9M8FSA07BWoxjAi8Kn+CUODJPfO9Gy6hiulJjcRrOKonu5XaX6khkHfIeWdVrMJojeGsZu3dqu+ExYag7jq1rmZ/eB3NPnt9TrfDVR0UE+xVLeWr82TF9/R+niYOL9SMYGDM0JdMZZP8u1Hf6Qc+cdKXadHEQ2hAKPsGCpjP1AzTYhOJZuG15UL1ZffFhZ93V1Btx+IXV0HNWSoppSoPXx7huQhblcf574LavdwPI8AIMALOCDCB54wR12AEGAFGQBmBTpE03wvxJMkfqEpABASl2po+oZKCVgUqg+GxYlCHGY/DKzXTO0QaFWFuVJJKg7moVAzlmZwenGn1BYqQ/qrprkJmzZYqiQTgrJo7sBD5w4xz9eoaGjSB52K75FS1I/Cccp6pGFfIwbqpUSjvktmxjQReqrJdyDdBOoxQKZU7kngT0gs10x5J5MHI5xfrLvQEA0wtVsy40DKE1FOnHhsVWk1rNU09KaQ5nAt1YrENPuwgHYsOtGHMWb4Doc7DM4HLLCza4/bMNkP/k+qtvxjw2z+3ZwQYAUaAEchFgAk83hGMACPACASIgNs8eDLUEsot/APbypDC6xTHQjiqcW1jRTkI1QFyDiG82UkR5vX+uW2nJ66Gd/XTSNcQjXSPGjmUHFBJsVrhWjwu/HxFfg01pDGFFzVjsfYQ1Gp7O9w5P3txoRV8FX0ocTSdmD4yx5ESCjyvxY7Ac1qTkcAbFuQbIv2Nwf4lsRHqju3ImaKewEuX9dKwuGKCNQKBh1JBdVRJmbyHZgVKPJB4KCCb1vc+SGs6fq+NPSwIJzfqIxB4x8+8UCOoVI1gUlu3UWpbxsyl4oTjvMKf10468aqmTAhsYIuOgO342jLxBVOJ5oRaKHWX23WpmEG47TPs+mHOWR8WXSL+0i/+nRGk8QXnvwt7d3D/jAAjwAjkIsAEHu8IRoARYAQCRAAHxsZ2+wO83pACQ4dJ/oyFcFQj/F4Segd4C2270t87HIZwECpkjiqndSJstXqIqPXV1mzVtt7ufHJgagPFl4xz6s7X514JCKOjrBfViNd8dL4WLBp7IfC2xXfT3ZWPKA+NtSE32i2xzwuiaVDLfaW9R/pS9Otf3kA7t72j3JesaJcDT2VNegJvCKSZxQyEBkj7ZDDWRsOxzH/rCbyhmr3az/QEHv7eQLMt1zQ+tYDe23dV9nPpPIv3SAmAEkWVyEMevAsWfV2YESUdCbyeO35N6X3EnX5y8dmzNCKvdI71nFVukErosko/QdaRxkgwp5E516A4DpIQ8jvfsWCCpF9jIX/f4YsNfFkIpT+UlHhneHm/6ueP3H14Z3NhBBgBRoARKAwCTOAVBmcehRFgBPYjBJo7kto/jo1FMz4Q/3gOS21nBjH+YY3x2rutE9tH8dZE7RAmw2TlvQNpN0647lm5NRYNU6jt1nVTSpywQdy19Y3mQTPOqWp8Fc06Zm5oU8VhXxUfO0dZLxMsVrJ9FbLLbD0qJJ4k7qAM+/jAWXR49dys2k8qDp/50wP01BO/sSTQrLA0utBueLg3W3WcIAi7xEF//OIETVhcZtqFzIE3CGbHoozQsPi/UTWoJPEkgSfVd2bNa2gKJYQWz6roVXiSwJN13RB5UOCdNPtiWxUlFHe9d97tuC1B5NVc/nHHelYV8A50+jLIc+ceGxpJRWPOtSAIIY9T05p5zUPpZ0y/bfHswsG1uXM0rNxvn07t9ao8hMD6IWE5/50T2vw5I8AIMALBIsAEXrB4cm+MACPACJA+D56ZIQVCZd2EdfmBFIosr+52fsb12zYqob8gQGVeQqNSshiGEXa4Ilw2/W63FtK7tbWF+oecSdswSTyVHF765yOovI8SI1UyraS1k0rauiixYafWdGjhDO3P1MKZrrexn5yTVqG0euIO/Ngl/R+i2enppmo/kAH33/4N2r71bU1BpuJXrVffta4bpJdv6chZt96MBCTegg9XmxJ5P75pA+3cMEr8GcEbJvHeE5e+gMRb8avfaT+yI/CcwmjhTLtQXLLcv+PSvHsniTxo8hDiK6JA8woIvFPmXGxJnKmSd7JjrySe13yKrjesywZWpKI+hyu6LFZ47Vh0oC12zlc83/hiShpf4EsXpIZQ+TdKqVC4ThZEMxdGgBFgBBiBwiHABF7hsOaRGAFGYD9BAIeX/sFUlviBWybIH9WcSkHDFDU1m8r6ihn6qw+T1dxwxb0zc6QspmGEGYbpd7q0fHe7O1upb9CZvJN9PJ/YTleeNkp+qNwflTogOKEE7BeOnsZidJQNg9R2IvBA3JUK0i4uyDurAjLPDZHnVzUFJR6IvO3xPZqaCBGg2IMg7malp9Fxg0do5B2K1fp2CPLugTtv1NqjOBF55192Hc2ccxD9/ZZ2alsn4q8NRU/gyY/ec019DomXFAnv3lzbRX/4wRZLLM0IvIVnNVPDuQ9m5rkv/51ZB24JPCcXWoTWAh4jkXfBrLtoUp11HsPOG76psvVz6lRfdonrcNpiKUjtFqdKKso8nHCs9aPscg20aFBsMszLnMMwsPAyD7TROw8jH6+T8QXnv/OKNLdjBBgBRsA7AkzgeceOWzICjAAjYIkAEkX3i9xAZsRPoWGLiprNzbqLcRAzC5O1I12LZZRghWPq5TZBHCdpV2ebG6hpZfe7dNLxR9Ky6f5ydhkHBYGHos8R6MVR1tVidJXt1HAg78r//rZS1+nx42jw6KVKdZ1IQ6dO9MTmH/pf1Ig7FBB3xmI3Fki8l575Pe0S+fCsiDwo7xA6C/LOTHknx0uUxmgola/l+8AvJmen1IUvKUSd3/9gM+2yUOEZCbwpCxN0xtV19E7Vt7R+giTw9g68Q39tdibbhB+DIPJiGs5Las+hQ+rP04wazMIZB555jpLiclu8qPCK4aLstC4QuQj1bO1S+3KgGOG1+OIH6SvMvjRwWl+xPo9irkPjvbNSVHL+u2LtGh6XEWAE9mcEmMDbn+8+r50RYARCQ8AqD15oA9p0XEw1m9f1FpIcswuTtZt/1FQyIPCc8t6ZrWdTsoWeL9tO3/pQftih1/uHdnqFot5R1krR6Gcss7ZWBJcb8k72q6rE80rgmRGbf3i9P2dZB04rpSXTRt2DVcZ66Znf0Y6t7+QQeQcI4m76rAMFeXdetv/Hr8yYR5gVMwUe6iGUdqG4UJqFWkcIj7Xy98ea6OXH8vvT58CT5B3qbyu/m/ri230RePoceHINqiQe6k+rOojOX3D9PrXjiClJ5ZXAQ/91X/2yq+2N56Vc5EyFG25Uip85IbS1eh+hH2Z4rVfjnGJhXEgDC69rlGQycuVBkadX5U2uL6dS8XMujAAjwAgwAoVDgAm8wmHNIzECjMB+hADcIRGCEoUyFvMChX2wAflWUSYOlRWlQrGRCZP14sbnJ+eZfm9sacqEO27ZmzkMzZ08TPXVIyJ/odoOGt7VT7g2Nu9Ra2Co9cXdD9Ijn77OU1urRjjwI68S7iXCyBFOlxJYF6qA4GruHMjL5VT2t7W2YbNW8+v/4DGOU1ch1fSdSOIOP8P7AsohEHdG8k62AYn3kcMrNSLP7VjoQz+eNByAYcVGnWmFcZFWBB7qSRXerv7cd93ODT2aEs9I5E1cOEKHfrCKpi4aJSKbE89RS+J5bVjpQmucgxsXWn1bFRIPzrMnTc7sfahGM++EfIdOL+Gzci5uw2gxB4T4RsnhOog5Yf8hp2hZIi72e0rb70Gmlhhr6SIK+UWV48vLoYLe+CIupKtJQeZJUtZv39yeEWAEGAFGQB0BJvDUseKajAAj8A+MwENPPE/vbNxOpxx3BB21fLHvlUJl0NZdOFc5uwlnnPnKhLNiNOajCu6kunJq6UoqJdNW7XP0AFmikUp+cxNijm3C4dfrIRTEnSTtzNYAEg9knhORJw0s3BB46e1NlN7RpA37QOebdMP/flsVRtt62G847IMgRUHInVd8/EwIex4KJuPYlY+95KlbFRWeajicGZGGSX3z0S56d8+oU6vVRP/zzFo6YUmtrVuq3SL14792bwe98wdrt2I7Ak/mwtMr8OzG7acOGoh15lSRCjz80CyM1in/nZn6zjgHozMtPodhxaTyJTS5Ykm2ulSZ9Q2kqVa476JIxWghCbwohoIGmastjPBa1Rx9nh7+kBoVI1VEEEvB+6NGkN0wv+DCCDACjAAjUFgEmMArLN48GiPACEQMga6ePvrolV+low49kI46bAn95LY/0KXnn06Xnvd+XzNNCQVHlAgzKBOQ16kYRIpXIIPM3adXg4G0CypHkp85vr5ZhMj1ZpR3TuWwuWlHEg8htCoE3uALq2noxTXZIbvSA9Q1PEALJk6lqoNn0+QLT6DqZXOcppT3uT5/G/AdEk6GUGio5sxyPaBDA7NwutINO7Jus27HUyHwrEhDOZYVcYfPVck72dfNF0ygqbX+FI2Yz6vf7aDGtwc0V1Yz50k7Ak+G0coceCqYdlMjpWKjXybIHHho27l1NrXvmSj+S64rRgfM66aG+TtMux6fWkDv7btKZVilOnhPwFlTKt/0oc27b72dejdYm3TYDeA2hFbFwVlpQQFWahC5Abv7hgJX0crwWuQihAoVyjwVB1Tj0qKYN9AJ/iBJUaexgv4c+RBBQHJhBBgBRoARKCwCTOAVFm8ejRFgBCKAwNMvvEEnH3uYNhP895+ff51u/NKntL/vamyhT1x9E932/WvpgKk4SHovTe0DkSHMcPiKiqmGKqJ+c/fpCSWo7XA49BImazdfr3N0Ut6ZjXnyMvuQbLjQbthsTnTI/vrve4qGd+TmJ2tO9VByJKUReLLM+cZlyiQeCB6EypaJPFd6ctSLIqZpZCetHv4b7RV/yjI5NoOmiOuQkqNVt45Wz4xc9UPgqZhZWBF4dsQd5moXNmu1aOD+q080uMLErDLcZ9vXDxEMHVCMRJ4KgQcX2haZBE9hRpLE6y3ZRtsr7tGIBwLv1AAAIABJREFUux1/PYG6ts3RWo/ExF4X3HacMqG2DfO207xTn88h8oIm7zAOQmhhaNErwr31Be+S9PPPU+/Tz2aca13ypm4JvLDIMoVbY1lFVV3qdQw8I1B04UKeNRB5bkLux6KaLWxMvd4LlXac/04FJa7DCDACjEDwCDCBFzym3CMjwAhEGIEHn3yBrvvWz+l2QdBBdYe/P/3ca/TDb4yqOK676Rf0HvHZ2Wes8LUShFbiIBKFYuYIGoV52c3Ba+6+oMNk7eboNS/U02vchx4hlHbuFGvmAGG0za/tprY+83BIM/IuOZyi5nQPVSbK6IC68TlLdSLxpHIG5IaVqhHKz0ZBZKuUp9IP5BB3Zm1OjX9UI/NUCtQtCIXUk7Z+CDwvCjwn4k6u47JfuHMORjsQa2ctr9By4vkp+hx4IF2NRJ5KCC3GVw2jlXMdogHaW/Eord6xntbecXl2CQmqoEqq01RYAyVdlNap9Y74zD00f3Y5LUh+gCakF/pZtmlbu9DV1NZt1Hvn3VpuuoxzrRqRV37CcVQhLjclisSOm2fZzVqNdb2G10Yx7NgOh7DzvPq5B05t8QxMHe/vveM0Bn/OCDACjAAjYI4AE3i8MxgBRmC/QuCmH99D74pcd1DX3Xjtldp/X/WVH9LK+76TxQGqvLt++6SmwvNToPiCmUUUylhKli3xAnGAMB3VEEzpdIqDPwwTggqTtbt/XsK2vKjv5BxUVXg4HOrD0JDvbuA3f8pbilTfgbwDiWcsSx/6at7P9I6y0gjBCiPVQ//dqe8rPyaqJJ5ZGKIXB1o5MTcEHtSIIM0Rsu6EEfr3SuAtmBynL585Thk7s4qt6wbp5Vs6cj6SRJ4M8E5ZfA8hTSxkY6OZhd3EJoociXt2xOjOO3NdLEvADtiQY5ddNkxz5vhasmVjp9DVnjt+Telt27X2ksgbEeG+mmrRole36jt0o/rchINCfq+ZPKrlnnMuep2nPoQZv0+hjLQKrx1rDrRj8XeyvI8wIqmvyf994fU+cztGgBFgBBgBdQSYwFPHimsyAozAPwAC54p8dz8SarvzxJ9/e+Qn2opOu/CLdO3nL8mG1SIvHn4mP/e6bCh/WkTeuSiUsfptv9NBthBhsnb3DyRjgzjIIL+gavFD4Knkwuvd0kE739mVc9C1C501U9/JtUwS+fAmX3QCAWdJSrkx/7BygtVjpaK8M2J7SenVjnBbKXK8mlgk33sQDU+osx0XpibAyszF1KrhO3uG6FuPdjuux1hBKuPuvDJXOem6I9EAYbRt64bymuK9gXE0tZkhR57Mf2dspKLEA3lXLvq9444YbduWmwcS+GE8K6Jm9uwRuvxylzGsiqAgdNXJkVpP4qFbjezctwQjkefWfVZO0+m9p7icwKp5+aIisMFFR8bwWijbjekQxpoD7VgM+ZX3lPPfBbm7uS9GgBFgBNwhwASeO7y4NiPACIxhBEDMQW2H8FnkuTtHhMgiTBYOtHc+sJJ+94sbtNWhHgi+p3SqPK/Lbmzrd50vyetYTu1ALrQLRaCbvEJOfYb9udWc5YEyIUgAqDLg+lssgw63h20v4bMSZ6cwWlnvrY3radvqPTS/PJPHsfeWu7O3SppW4Ad25B0+rxamFod+/0qNvHND3MnBnFQxyHn3JxE667YsE/nwnHLiQQGXEgo4oxLTSxitU/47qUpEaCVUtwMi56Jq8ZL/Dn0HSeD1PPkzev7XK2gkXiU6FpeuxEW0N4gpfWhtw6IEvfca6/x7yInXJb7AMKbFqy2N0Tixl2S54YZc9R1+7kTgoU5YKjwnExI574FnnqOkuPQFHJ7EKD57NiWOW0Glc2arboNsvWKp3ewmiv2diJdQlzCxKGaxCq/1km+zmOvA2GPZwGKi+LcEfgdzYQQYAUaAESg8AkzgFR5zHpERYASKhADy3e0WJhWfvfxsuksQdrgOXDCLviFCaUHo4b/hRIvw2XM+cJxvJ1osM0p58MaikYV+znoVGMg6hFQVIkzWabuqqMz0fbhxnzWOrUrggYh4cdMmuv3vf6U1e7bTp2/flbcMq7BZWRF442B85OPXa1h7IUidXHphWLFGXF6KkwrPLu9j2d/WUrytS3lYK/WdJO4kuVlbVZqXd09lkGKE0JZtvZ3KxSVL86459OzDGTOf4bIJNLKP/AWBl94XQov9MHVpOZ3y1UlKocF2a3/mmRjhMhYVAu+EE0YIV9DFTe455MRLiXBa/CnDapHvrnL+HBp/0HyNiOwVORjduqqCmK2tSlC7yKHqVBpjfdRU0pdTbcpwFU0dySVhnfpx+tzK3MOpXZifyxBUEIsDQ2kNb9V0C2HOS7VvN3tNtc9C1OP8d4VAmcdgBBgBRsAaASbweHcwAozAfoMA8t+Nq62mXXua6ZU339WUdginhZkFCgi9bvGzk1ccrpF5QRSowzp7i6takOsYiyE7ODjiYIYi3QmR3y5KKkInksq4j/yE0DrlwJNj6XN5tby+nt750i+y04DqzizfHSpkwgEzxB0IO4QxmuXBU302nHKKucl9ZxzTicADuVa6z2DDbL6qJJ4ZeWck7iS5aWacoYKVVwLPq4lF5ZtXU2nHm3lTA4n39qsnU8vuudpn6drFpCfwZNisqjmH3dotCTxBYKWFgs+uhEng7e1QM11xuq+j7sxxjcSzy9+m7wt7q1yoFDt6rH9vgLhbFW8R5F2/6TSmDFfS8vTEwIg8p+fYCYswP5dq7HKhCMMXDWbhtWGO76XvsZrSQv4eHi9CzbkwAowAI8AIFAcBJvCKgzuPyggwAkVA4Lpv/1JLjo7QWZB2cJutramiaz93cWiziVIevLGWNBsH2ZqKDIHXKUK3oHLyogIL7ebu69jt4dYrgVdfPUKHz1MLzTQqZtaenQkPtyoZ0wJB3IkKkrhD3SoRQjv3xlGHULdYOjlDhk3gOYX96cNpdzXuoZdXvUG7mxq1ZY6UJ2ikooymLVpAh3/oDJq2eAFZEXcSF68EnpcwWhBEv/qEdRir1b2yIu+M9d9+5SQtnLZ06eepbHYJTVicf2j3Q+RFkcCbPqGSdreak2Ju976sL8M+q8qFOlOByHNytgZ5tzKxQ2k6pw3NDITEi3r6BbxnkDdRe2eJ3xuq5jFKIIZQaaz9LtZDwPnvQtgQ3CUjwAgwAi4QYALPBVhclRFgBP6xEIACD4o7ONKGWaKUBy+MA2qQ2BnDZJOCtKssi7syiQhyPip92YVqWrX3EkarYmAhxzPmrLIi8EAuAHMcfYf3Ke70c5YmFio4mNVxwiZMAg+H5KqKuK2SSc750W//gBrfXqf9daRUxIzi0hXgNPfgxXTul66i7v5Ulkju7NhJnR2j4ckgD2bMeo+rHHhymG8+2kXv7kkpQ33zBRNoaq27MFJj2KzTYFg3jT+Mupb9j21VJSIvLdxbh/cRTyUz6ZnnZ5uG0MrcfnYDjgUFnnH++vxtUIlBLWY0YkAbp3DVO8sy+1S1BEHiuU0ToDq3oOoZzUf04bVQbKuqH4Oaj1M/Y1ENL9fE+e+c7i5/zggwAoxAuAgwgRcuvtw7I8AIMALU0pXU1GNRKFFVUkg32SqhuOsTBy49SRJ10rFChLtVCOLGLuTNeO/be4je2JJLEtntDzfqO/RjdI3ce+8z1HzfM9khssSd4H/sVI1+wmcxmFMYqxcHWrkIpxBaVQLv0e/+mPas32gKvxEnqPHO/I/PCdJuJ23f+jJ1debmFoSKESrfmnEH0LJDz3X1yMONFko8FRLvP8+spROW1JLbcM/av57oak4ypLrj+L8otdMTedkclUMvUCz1omn762/+VxG3XZPzmQqBF4aJRaHMI4Ap1HjVglw2U4rZmRs8WbrdMmzW6gYhnPb0lPeUEGMh3NOKYMReAtYy/UJUwmvHqoEF579Teg1yJUaAEWAEQkWACbxQ4eXOGQFGgBEQDqARyoNXX52gpHCHjIL5gyR4oFrC4RmknVmYbFRJR7m3vYZDqZJ4bsk7zAsHV4Q66ZO6b73uDhp4e7uW3w7RZk7hyH7Vd5iHE7np1cRicmwGvT/+UdvXi8p9ef2PT9DrjzyR148dwTl/xcFUNss8zFISeELMqJWDl3+E6upnuHoNOoXTgrxbMi1BIC3cEHhxkfOuSuS+29xcRluyVznNnZQU16B2zROXvkgCr2/W5TQ45wrldQD7ysRuGup/jgYGtmr7zazcfu8ZtG3HVPGRCAWOZUJ0nQi82bNH6PLL3SkPVSaOdxCIlUIaIZgpF6Em6xYpA8zyfLpV38l1+1HhARfkPGvuTKrAWPA6KgSjVD9CzY1Q217xu8aNU3TQixqrBhbIzThhXHnQcHB/jAAjwAgwAi4QYALPBVhclRFgBBgBLwgkhUNeIQ+FdnPUEqSLw3VHEY01cCCsKCsRCpRSjURyOkxF3T1X5QBpdU9A4m3Zi/uR78aJNqqus8b+MadJdRmCR6ob+9Zuo1Vf+KUWKutU/Oa+k/0blYBm43pR4Tmp7zCOCiHzi3+6OmdKTsrEdHqQ+vs76KjPHGMKoZHAG1fnXoknOwaRpy8HTivViDtZ3BJ4CJ+9646HBXlnfQAHmXflCW3ZMbwSeFoHyfuoZGSHaW5F/bquv/mKfX/NkHgJ8X4aEl8yWJUw1HcYS1Wx6fTsePlcEnnYszCRgWrbSODBtGJVvNVL98LQYoJmauGlOJHwXvoMso3ZlxV2/Rc7vNbP74sgcfPSF9yRZVoEL+25DSPACDACjIB/BJjA848h98AIMAKMgCMCQSdGdxzQogIOOw01xVFTaAdkQSCWiW/xobTTh8narccpj5pXLIJsN7Whghrb/blXwtxCFqjuGnIjC11PF6HHCEcG3sBaqi63CCVe31vbLPsLQnknO1c5XDeN7KQ/pR9QXt+pQnk3RSjwnIoTgbdn3UZ69Hs/1rpxIu7kWP397cIhdYimHzGDDjhiZt4UjAQeKvgh8ezW6JbAu/vH36Ed777mBJumyJMknmcCzxA2a+ZuLCeydftUuuO+M8RfBTkZG2+rwAuLvMNcVNxfjeBtf3Ezde5oF1eH9lHdzHpxNdCs981zxNmsAt6R0uHTmLutWARe1PO1GfN9qgKP9wPaIsR2UHzJZpWTULU/1XoqX2qo9lXoepz/rtCI83iMACPACOQjwAQe7wpGgBFgBAqAQJTy4IFsahLKLKuwtqDhkG6yOMSDSEIeIjdjQwFSKdR67d254X1Bz9Nrf293N9H2VJsgyFIiPCvTy3nTlnntzne7zKFUKC0TcersHRQh3Om8PnvXbKVeExJv8kUn+B5f34Fq+J0qiadK3mEOehWi2aIQPvvGo09kTDwUQoql+g59uSHwUP/YEz4fKK7ozA2B9+uf3aaRd7FBNQWXJPGQ8yomgHQbQhvrv8VyvcAb90bvdozKWjjtzuWmBB7CZmFcMWdO4DBmO3TK16gfGcTd9he32E5m2QWHa2Se2yLfzyDO9M61b5YUR4Hn5CTtdn1B18f8NCW3+LLCS5E5CfHORHgtiDy3v6PcjBt1QtRqLXgX4J2jfUnBhRFgBBgBRqBoCDCBVzToeWBGgBHYnxDoFCGrXg8YQeM0YRxyLIl8czZhan7HxCEdBxWEykJt50fdUEzVoB0OIO5+t2cNvdOzVyOBcPjTE5Mg8QpJ5IGAgFpRJsavrSoVBJ55Li2/99dNezfqRKuceMtKjtZUdyrKO/3crEguYLXq0Sfphd896pgLUPY3ONhLuFAsCTycbQUjYAxTnjn7PTRrznvdwOZY147Au/+dVdn2g8kk/fmxlTReEBOTWt917FdW+NQJrbRgsiDNxXr63eTAszGt0A9uRuSVlB9Lr7x2gvZ+kgXkXZjEnRxHVem75jevZRV3TmC6JfH0Rhq9296gvc/dRv073tTCantGhJuquAbmHEgdJ36EknOWOA2f/dxPCG3UUxgYHWiVQTGpWIjw2qjjaYUf57/zs7O4LSPACDACwSHABF5wWHJPjAAjwAhYIhClPHh+FQt2t9lrmKzT1nFDAjn1FcTnIO5wyWIWOonPltRMpv9adGoQQ5r2oc8naAxLDvJg62cBxbx3RgdjSXICq2fuf4Reefhx5aWNBQJvbXMj/ffzK3PW1NrcKojHjHp1Qm8HLWrZSxP6+xzXDRXeZ04U+fAEedSp6EKrdapI4MkJ6Im8WNmxVF9/YlFyhoLASwkll53BD8Jl1/zmdUfs9BXckHj4sgJ5xl7/yT9T7/Y3c8aB8KmZRo0kQOQ1XfFlpbn4MbGAiVCbUD87md4oTSSESlYOtH6GkqYXNeJLKJg+IU9rUF94jVUDC3whB2MkLowAI8AIMALFRYAJvOLiz6MzAozAfoIAFDl+c6QFBVUYIamSGMEc9fnWgpozVINRUJNhPVDefWPDn/MO12bKK1QKg8STxhRlIkwW+ZvM8glGJfQtjAO26r6SKjU9cSexenvD2/SX7/w0p6tyKrHsOuoEnhl5h8Xs2bVndE0jwxQbGaSjd2xXIvG+df4eSh35Q+qtPkQVctcEnuwYe7qq5nhKVK4oCoEHB9qkIHbtCLznv5P73KuAgrx4yy44QqWq5tq85e5/o9YN5rkKO2mQUrFRExoVEm/KcCWdnpplO/7zJXfRC+IylmOHL6XDao+i6s4DleZf6EphG0LI8FooyVEGBqEmT7lKAaHHJOz5hok/578LE13umxFgBBgBdQSYwFPHimsyAowAI+ALgajkwcuEaZUJh9JRNYeXhY2SSP7DZJ3Gj1LY0cWv35M3XS1Jv8A1nTZ3eA0qnFaPOUKycaC0UsZAMQHVDgirYhbstY6eobx5Npb0Ey59OTQ1PtCpgsAjGskxTWmPDdLmeC91lAzR6k/ekDde2UgJmRF5egLP0oW2SCG0VuQdFpdD4OEHLki8m677IKXnfcLdHnKpwNPfgDJB3jU0nKSFo4fxRYDd5gKB1yfyRVoprVTy3ln1v+KLpyjt65bnbxNhs7fbOkW3xnLf210nfYQ6RUitlbm0nfpue2wV3Ru/xnZuUAWeP3gzzRpZrrSGQlYqZHqFIMJrw/jyrFB4Q0nN+e8KhTaPwwgwAoyANQJM4PHuYAQYAUagQAhEKQ+eHyML6aKXEAc7EEggksIOr4pK4m9j6Kx+6+AwmbIg8FDvnsMv9rzT9JirEhs4LFaIXG8gz4pZjDkXQdo9UbbbckqHphrID5EHMrWiLJMPELnDQJzL+wLy7vVExjEUpefdrbT55jvz5hIfEWowiuf8XJpY6PPfVextpsrmFpJ/okHHwUuob+JEGpg8Kds+bBOLrz33JL3d0mSKaR6Bh1qCxEM47TE7t1veh5GyCXTD/95KpYIF1pPA79yVGUf+OfGQapq0vIaWXDol25ediYXdXkxUX0RVVXO1HHi4f7iPRjfWsPayk8rXD4E3631zlZxp3/6WMJER5KUVGYe1D9EwdcVyn+md19+lGYOA+NS39UveYby4eAzSwgfnovQtkSPxvDgH+90/+vDaobRwU3eRTzYqv8fcYpCIl9Ck+nK3zbg+I8AIMAKMQAgIMIEXAqjcJSPACDACZgiA7Grr9qd6CwpZt0YWelIERg04VNuFmgU1T9mPVD+0dhXXidaOwEuUltCQjTHIVxaeQgfVjpIcKhjJ0E8vmKtgVrX+XUq0tlCirUWbztD4iTQ0YSL1LQouZE6vbHqibJdQ3Q04Ln3qcAWdMXiAYz19BS0EUxCWwEzmA8TYIDB3DSSpWSiXtlZmTChQEmJT49r07Tuod922vLHMSLzS+jQt/OAirW7D2ne0y67sPvE4mnTUmb4MLN7uX5s3xEGVS7MutHbqOzQ0JfD29Xjm5h3af0l32pF4pWBsqmikfIL2869/7xtZAq95VY9G2rWsHsXQODGQeBqRl7yPYsOZvlXLSMlMqqi5OId0lorTQhB5TrnewibwYFqx/Z6rBX9nT+BJPPXhtI1X/KdmagHFLUjrabFqWppsoMnDVZbwf7v0NMdbk3EhhmNwpuqXUrn5FR07CLlCmPlcnabuJbw2Skpyp/XpP+f8d27Q4rqMACPACISLABN44eLLvTMCjAAjkEUgSnnwVB0X9QfogcG0RtzZqczCut04LE0cV07NncUlQM3CZ+WanRR4bsJoJXE3JBR9XhOo496Nry0zxQykXd3fns+5XRt21NHjL82ijTvrtJ+nq2topLSUTrqghOYsjdHcgxEf6r7IXHwvpZvpzdJ25Q5USTwz4k4qQvtLR+jFtk6NwCsbn6aSstzhS8XGqiopobaHn6Wmh57Jm5s+nHbaogW04lPn0Fur/kDT/vKsprxTKZP+48dUOm+pStVsnfYNO+hvsVepsWdXTrvyumrChfLe8ctpBi0mOM7+9t1R11njQN1d3dTT3WM6/sKuIVrYba7QPO6UE+mDZ71fU3Rt/XsHPXfNZqU1QJF3/LcTghT8jVJ9WWmk7AKqFOo7qH26+nLnVAgizylXY9gE3t5nb6PWF0T4rMHN2gnEPkpR/ISLqFRcKNNGqmhe+ThBZpdq+THN3tlWOe+MY4HAIyj79hF4yIm3QlxRKVEhxFTDa8eqgcX42nLNUZ4LI8AIMAKMQPERYAKv+PeAZ8AIMAL7EQLNIu8cwm6KXZzUWQi/rBYhbDg4O+VaK9Ra/IT9BjVHOwIvLkJoQdJCLWdWnAg8OyLK6/zNHGDrXno+q7iT/f7w/mVZ4k4/liTx8LNP3BD3ROKBLAYJ9L+0znYZ6VQ/xUuFAkxXzhicTlNFEn6zIvGCOgvKR6ORR6NwXv1zV4dGiMQSI4LAs37uxok4waRQ4UGJZyTyFi08kA7/0Bk0bfECbRp9T9xNnX/8hdItqaysE2sqo8rPfE2ZxHvth/fTuoWNlJxmfWAGiVczvpbGxydS067xdN/buY6l+sklk0lqaxFusibFjsD78reu18JYG9/ooSevWq+0XlnpuFvm0aSD25RJPJB3FJ+lqSeNIbv6gcMk8pzckv0QeCpOtCDw2l683dMXJJOP+wRNPv4TOfdIhnpClQpCWx/qeU/8i7QjttrxngouVXuf6cNyo6TCixohZhdei88m1VWI3LPOCmTHG1PgCpz/rsCA83CMACPACNggwAQebw9GgBFgBAqIQEfPoHCxEwmFilzM3PBwOC4TxB0O7TjwYZ6FDJN1gsRt2K9Tf14+twuh1RJ824S/WYXQGs1AzBxlvcwVbYykhJnyzoq8k2P6JfFAyrxVJhRcQ3vzlgHSLjXQRsPiT2MprRhPM8um54XSSuIOexWhstinxhyMIO9WdrRrBDQIvHj1MJXWWDCr+wYGiYeQWmM5fKieGkZGpXvd136M0qlBGhzsE7nBzNVr8XiCyspEFj1B3qHE5x1EVZ/5b8fbqELejYBNEVxkRUWdSCqfoLe2pbSrpDpG8Rpz0s+KxLMi8C759BU0e95c7V3w1L9toN2vdzvO3Vjh3JXCuTYtcuylXrQNp5XkHdqrGq+MklOlmisovmSwIs5VJy4di+3qG11oB6ifkuJCqSNrAxYVE4ugCTz9OuQXMvgZiLyv06lKsIDAM37fFBUCL8qOrjLlBMhTFKTPwHsIXza0dxc3DYTSjddVAqE+WRhYcGEEGAFGgBGIBgJM4EXjPvAsGAFGYD9BIEp58JDzqV0Qijj44qBeJVxL+8RBOEgCKcjbWsx8R3IdtgSehQOpbGs0sdATd8AcZFTQZiDGvF4TH30w55YgZBaXXRmJC0K3piZbxa0SD+TBzxMb89Y2JIg7kHdO5dKeaVQz8RCNjMOB2I64k3092d5GTUNDWhvkFCtRIPAQTluHjP2GMjddTfPEhZL8029pUFyygMjLIfHEHkgkykTesEReP7U33W+71M2Pv0RvNr5MnYflz0FriNBKHfeP7VZWXkc9pWl6YZVQIHaUCL9dQRY2lIhQ4Xwi0iyU1ozAk+QdhsR74a7jX7c1VbBaVDYfHiqAyBM58WKCzEOuO8KFkjg2pznGSwmCUvWLg6CIvIwzd7mjOmrNb16jzh0dtJd2CeIuX0klAg1pnCDyKmhUNapqYIEceDvuvTowBZ7ZfZHK6y8nT9SIOSfS0ywtQFQIvEI60Dq9o+w+lwZElYK86xdpKLp68x25/fQfdlvOfxc2wtw/I8AIMALuEGACzx1eXJsRYAQYAV8IpMSpaa8Io41CgaINCc9xCA6LQApynVFx8LMKowWOwNOMhNOHz8pDNEgDVUdZrzjqVYswrKja8G5OV1d9b4VS16m6+mw95MP75NctSCaT3rDeX5blEniq5B26W7Hyh3TwybfQxOmHWiru9MNK9R1+5obAQ/0JIuefsdgReGbgIZQ6beJGXHbq+VQuLqvy56u+R9s/aUjSJysbyDv8GBQdCLuSqnp6bfsA7diamTt+XjpeSKcS+SQelHg9XT1CPZhRAX1wV192OrPmzqHjTj1RU97Jsv7Xe+ntuxr9E3hKuyxDGLoh8GS3fok87BMYnjiZ5Gygt+jPv/kj1e3ImHxYFRB5k+kAqptZT8suOEJp9ZjD2m8e74nAO/i6Z5XGkJVuTpwm1JvYKxmFqsxxZ+wkygReMRxoXYFsqIx8fSjlMDty6V7rZ1y/bRtqRAqAfUpCv31xe0aAEWAEGAH/CDCB5x9D7oERYAQYAVcINLUPBK60Up2APkwWbWCSMFZCepzy9qli4Lfe291N9I0NfzbtxuzAu6RmMv3XolO1Q1Chw5NBSgyIENMBoe4zEngq6ju5yOHyChquGA2juuH3+USXFa7A5LaKTVlSC2GzgwZzBrt7cuKff6QRSId8+FGl52ZVbw+t6s04pWK/o8Sq0o4htKhXKVgNmFroi57A6/vZf1N689u2W8gLgQf13RZxWRF4I6n88F9J4JULFV5LIkl/+WvuPamcLnIPCuD0+cv0Ez9UkEzH107SfnTcqSeZrqnQBB72a1LsVVUFnnGIyi6fAAAgAElEQVTSXok8qZKyexeCvPtRyVdo3PbxNOOFhY4kXnJmH11xwdXKrxs8Jz0v30Ubn/iZchtUNMt/59SBPgcetju+eDAj8qJM4EVBke2Es/5zmcMVP0MoLdTEwB0pABAG7qSGdDNWkHU5/12QaHJfjAAjwAj4R4AJPP8Ycg+MACPACLhCoBh58HAQqxEhsjg4wE0Wyi8thLOq1FF14mpxIVaOUs4jKxLPeOAFeffNZadrxJ3M1zYoDBcKVaSBBHKEBUngwZkWl0rBPrujclNWWZQU5J1ZzjurvqDA04iKxRfTlMWXOA6pJ/DA38XExhkpHbY1sZCdGgm8QeTo+9tttKctQ9od8cJuGt+aCZ2sKm/QLmMJmsCTOe+M40gCL5GoorQI233w2VROFeTES4wDSYA8ZrnmKgdNnELXH3e6I5ab7m2mNbfvKZgCDwRe30Ca/D4jbok8hHlXCEKlo8c8pyGAuqrknBy8QOLNFJex7B0cR2/HxlOrcIGdTNOz4bTzZ5TT6cfU04KZ5vnE5BzeuPVfqHe7tSmJfrzqWYfS3Eszz4ebsj22iu6NX5O7XwxEXkZRnJsDL0outFFxoFXB3SpEG8RxJi1A5vcyiLxiuLxbrYHz36ncXa7DCDACjEBhEWACr7B482iMACPACGjfuIPEK0SB6gsHBBmuqc+zFiVCTBWLKDjRyrmCxENOvHd6Rs0Z9ATepXMOpcvnHaYRd8XKKyhdPTetXkdla1bRhL27s1D/efUS+stbB1FMSHAQSmcsMWSw31eMCjw3BB662FLXTc8kMzj1d2xUvd1U17aTlr36e61+9YRlNO/YmxzbmhF4ILAqpjqbx+gJvN5kO7Wve4ySW1/KjjlvXTvNF5e+1FVNo4TOPdeKwLNzorVT4Jmp7zC+nsADiXfA44fTd6tfzE4NafhKx2dCnTUlovh/KPKWTFAj79Cub90APfn59VqortuSkwNPsXFQBJ4cTpXIw3OSEPu9q8+cwHs8dh/hsiog8wZ3HKARd4M7ZmSrIZR2igil1RcQef/6sal5XennsOWuqxxJPK/knRzYyolWKvJQD/kj9SYWUcl/h7lFzYHWbouDnK0UX6BZKTzt3GsVH51QquHfDvUihJYLI8AIMAKMQHQQYAIvOveCZ8IIMAL7CQJQl7R0hpcHD4d15IurKEOunRHqhUGChepLGllE6Vt/u20QBSda4/xA5EkST+bpu2T28qISd3KOUHi8u/JP9OqDj9PBk+po2aTRXHZPCwLv6dWCwNtH3kGplldE+5jYT3onWtRxS+AN1Q/T3QNbtO7dEHjLXvkd1bXvyk5rmQijdSp6Ak+fl7CkbMRRhScJPJB3feLq+uv3coZraOmnI1/ckzcFPYlnFnZo50KL53XHyr/ThkdeoM1X5JtfqBB4k7oOoMNfOkqb13eqXqD1pa3afyemjOYqBBaXHnI4XXHo4ZoTqYrKDYTabe97zROBd9wt82jS8lHzE6f7hs/xfHeKJP9Bv4+ciDwn91snAg9z3/2dq0yXOIvm5/3cjMTTq2XRAKYWvdvepL3P3ZbTHsTd5OM/QdWzD1OB1LbOt0tPs/wc/L2mXhX/hxx5F6ZuoVkjy32PGUQHY+3LJzfhvtIxGO8FfNkXhMOyV8w5/51X5LgdI8AIMALhIcAEXnjYcs+MACPACFgiEEYevNFwnBJl8qi+WuScEuSe15xThb7FVgehh//8KK3bsl5cG7JT+vDJZ9LiuQtp8bxFoU9TOsrCybdHEKY4dAXtKOtlEX/90U+pddPm7FwuOmi21k3JcIyeWXUwrVy7OKdbKxIv3ZAbKurWiRZqmad699Ab8TZlAk+vvpOTVCHwUPfOvU1aE6OxiBOJBxMLhM129u2h3jfvp3THzjzY9WG0+g8njpun/dWMwDNT3+ldiN944Fl69+EXqOkDpZSclhua7ETgIQfegk0H0tz1uUTRH8vXUe1pGffcpSJkdumkjOpL5pLEfzsReSDwXvv5blp1Wz5pabcfJx5STcd/J5+4ctrDIPAQxhrWs2NF5DmZZxjDZ43raPnNuTnKO/3n+jBa/c8/e/6UnHBav/n/nLC1+txKiQcCD/kTZ40cQmeUf5Lmxw/VCKUo/K4YKw60EnMv4b54TpHyQqa9KEZ47eT6cvE+U0uV4HX/cTtGgBFgBBgBdwgwgecOL67NCDACjEAgCLR1D2o5b4Io0hxBO5AL8sjNAUtz8hMHhQ6hehkLxehEu27zerrll9+3nTpIvGuu/EIoyzM6yiJn0LbHN2mJ+GWpmVdPtfPzc6WFMiFdp3s3bCIQeJgTnD1RTp49haZVVlJ5KqP0+uL9H86bhpHESw0JFc74cVQiyEkUty60aCOJmUdLd9KWrrccl25G3qGRKoH3ZHsbNQ0NaQQeiDK9ogskXmnNMJUYIsNKReW6eJxadr1MPZueNiXvMAcrFZ7MiWck8IzqOz1xp39e4UI7MDVGez+Yq8KzI/BiJQmqqKijkx8xV1JN/n/Wbqly78Ix1yrEW4a0/unqDdSyOmMMolK8qO/QLxTBeDeGReDJuRuJvIR4B+J9bPXutCPwkiJ0tvU351nCUkcNVEfjTT//3r9nCHVtXwmXUju1tAruXusgJ9722Gp6oeSubBeLyw6jIwcuoRnDh2g/k/sFocY94guKYirDxpoDrZ/UD8UKr0XU/dTxlV63FLdjBBgBRoARCAkBJvBCApa7ZQQYAUbADgEcfhAq5rXoSQA/5ghjTcmgd6JVIe8kvkGTeGaOsnue2kKN4ipByKmJ9efCfzqsoETe/VdlktTjwD2kS2R13qR5VFeXCa289S/vo03NE3O2oZ7AGxYc8+Bgpm5iVib81q36Dm1A4MGcoFzkgnr8qU/Sm4efa7n1Z236O+EyFlUTC7RrHByklR3tWnAwctKZhWSCyMMlyxE1tTR5pIx++/jHHR9LMxIvEa+guurpOQo8PXmHZxY5paCoAQFiJItkHjyjCs+OwCsT6rsjXz6GGlrzCaLEzFJquKjOcS1yLw8MIlfjUI4bpiTwugZ76NkvbqTONblGGfFYvhuxV/IOE4VSs7lzoGCOnHpyBOoy4/oleD+MfYU2xsyJ5+4X30u4rIpZCK2sq1fhFYq8dNwQ+ypY3YvRFA1xzXShGESem5BU1fWGVc/KwMLLeIUkUTn/nZc7xG0YAUaAEQgfASbwwseYR2AEGAFGIA8Br3nwvITJOsE/fUIl7W7td6oWic/1uY+uvO6zrubkl8TD2CBfzBxl1//0derZ3KHNBwc2KwVRoUg8qb7DfPQKPPz92K45NH2uWEdDJjTKisTTk3fauibX0LwjEvTJr4/mVVO5AcBjvFAXAT8ovbauvpP2rruHts/PJz3MiDs5xtz3fYtqJmbUQCpFknhmIa3G9qfVN9DUsowk72dPfEyle62O0dQCYbQYb2T2Eio79XwqnbdUq1ddkSHuJNlutT9e++H91LFxZ04orZULbVyo745+4xRT8k4b89hKcVUprwVzrK4QLrA6UiZRPkhNfXupN5VR3+24O0k77snN3xkXbhklsRLyYlphnBxIo70dGZffQhYQzLgnZaXmpJRdDjw/BN7px9RpzrQohSYv7fBVyTGnVzFCvVjItAFeQlILuZ/0Y6k4HLudmzG8Fvir5LR0M06dSK8BxTsXRoARYAQYgWghwARetO4Hz4YRYAT2IwQa2/q1HENORU8coa7bMFmn/qNoDGE3ZyhVfvWH39NDIu+d23LNp652nRNPbwpi5iirJ+8wHyNhZpxjIUi8tY+vpLWPP6UNrScUp3TW0dTODGEwTZB4IPJQ9CTesMiPNyKuVCo399EJHxikM74+XRlyvUoU5Ig+f9aah89U7gcVVR1ojZ2CxNuQGqAtPeYE9ZREgpZX12TJO7R3Q+DJ8aDIa2gdoOOWfoZmn38pNbZnSCipbnPjRCxJvM7D4oQLxajCm9A+mQ7eeQTVNluHZtuFz1qBrydlmns7aXf/NktDCZB5KOOWxWnBEXOpck8jxV/9E5XszpiVyDI8fS6NTJ9H6aNOdbznCDWU2DlWDrCCVL8NC9dVkBZV5aU5ROYGeot+VPIV0xHtCDy78Fl0pifwirV2s0VJ0r1ZwWypGCGeY8mBNky1YJjYc/67AF8w3BUjwAgwAgEiwARegGByV4wAI8AIuEGgpSupKXKsSlBhsk5zCvOA4TS2l89BOJ571ZWewuxgbPHhU9TIIyP+ZnnCEDaLS1+cCDzUPfzmk70sXbmNkcAbFgQauGI9gafvDGTepr0T6C8bFovccVOpROSCk+XomdtpxrhOOvDCaVT9gQMd52CW483osNnTspq2vPifjn2hglfyTnaOw/7qvV1iXYM5401JlOUQd/JDLwSebPuZM+4nEDGdfUNZpaZVfjm7xbdv2EEIqYUaD3nxcA13j1BN7VSak1pOEzqmmJplyD7rLxxHZbPyHW2VABeVQAzsHFwnlHViXLFxsH9sS0czTX/mRapsbbesBiIvdfZnbLspFollVL+ZmV08RvcRlHjGYkfg2YXPoh9J4AUZZql6j+3qeVWNgbCuEQQoiFAngxSv81RRB3rtO4x2hfqCLMjwWs5/F8ZO4D4ZAUaAEQgGASbwgsGRe2EEGAFGwDUCVnnwcHiqrizVlFPISxV2aBLGqxSHrnaRPH4sFBCOF/77p5XUi2br+cWNP7FdJkIgcQgtE7iAfAHJahXy+Pr/ezqvL7sQWll52vvnEq6wip7AAwkjNFwaXlYEnn4eFXXjqFJcxgLyzo7AszJnQD9QNeFQCDxlAYmHUNre1jWWMPgl79CxW1LIK4F3xILzacXSC6lO7E+EtHkh7uz2w+D2Ieq4rytbxSo02C95hwH2Dm6n5Ei/lj8QzC+2EJ4BwcvkF0HexfaRo/P+mFF9WhUnEq9YIbRWe8RI5N2UvJbWCzWevlgReFbus/q20sQC9xIhi61d0XgHG82C3L6n9E7HQTvXjrW8rX4MLNzijvpBhNci3B9pD7gwAowAI8AIRA8BJvCid094RowAI7CfIJAcSmcPbCA/QBhBqWQMNwwbjrF2INq8fSN9++f/49mp0orAg3oEibtxL1TDlK0IPKl4s7p3cKZd9M+Hh3Zr9TnwQJwJCkZTxYRB4NkRd3KBdoqepnV3U2/LmhwiD4YVIO/c5LyzAtMtKfTaxt8SLjcFRM+lJ3+TptYv0XLdhRkG2vtCH/W+0J+nwHOb885ufTuS67SPQeDBpVb7b2wk8f/a3pZEXm8Xxfq6s11Ne/FVWxUeKqaPPMU0nBYYTqorTg48pz2iJ/IeSP6acOnL7u9clf1rOQkzE+E6W0H2Dp7zZ5TTv35sqtbOq+LNzR51UxdfksD4xo2juVn/QarCZP9jyYG2mMpKY3gtHI4HbBT/+vvH+e/cPC1clxFgBBiBwiLABF5h8ebRGAFGgBHIQaBJ5MoCaVclFEp9wpkS7pRmjplhw1ZolYCf9YBw/JQwsJDEgtu+jASemaOsSp/dm9ppw/+9kVdVr3iz6yfsMNq//PBWat64WXNihbMsCDyU5dtn2y6vYdYM08/rP7+CyhaOOtaqEHeyIxzkoSothsrTiZwxW6yqCi/ZmhD4ipyBneOovnoaTZ4ymxbOW0DzFr1PZQv5quNlXSoDdqZaqCvdqlXVE3j4O0gBuCyjaGG1e3fldNmwbhM1rN/sOMzgv3wrr46bvGuOA7io4IZkMRJ5q5Nvaoo8qPBKXjyDygVp50TcyanpHWjxDoJbdJcIvY5CCdokYlTV7N+51hiOHwW8rOYQFbLRLZE6UeSZRRsujAAjwAgwAtFDgAm86N0TnhEjwAjsRwhAbYdDm12YZiHgKFSenqDW8s9f/VdPRKfMgadXPEpnULcuflYEnpEws1pz2ASeVOFhPiBdZBiwnQrPKnw2sWAiNVy1QluKG+JOrr2YIYLSoMAqDNrs/uxuW0uPvHy95XZN9ZXQYKtwLu0H8VIhyLtRcw8Z2rr80ONp+aEnBLXl8/opBIFnFaarEXmpQRppa6a+4TIaEBdK26o+al+VMQxZWrWNllZvM12/mQoP+6q+pvBhpF7GNcuR9+PfNNKmnUmKv7OGSlr2ape+pA48mNJLlmk/0pN3+HvUSCkvz4zKRg/CuRZ7ZCCZVlaTqcwrrDpRyy+L5xkGLRlH7LRmLGT8vcf578LaDdwvI8AIMALBIMAEXjA4ci+MACPACHhCAKGa3RFQXeAAiaLPUeZpQQVq9IM7fkBr1mfC/NyUaz/zBTryoIO0cGU3zqBWY5iF0BoJM7O2YYfQyjGlCs+Yl29+0xSqSVbkTK20vJxqp0wyXSrUd5WLJ2lEg8wN6Ca8rljqKiwG5HRHz5DrkGuQeAil3dP2dg4mwwNx6t2ewc5I3uFnetXalKmz6fQzLnOzRZXrFpPAwyRTPb3U0z2a0xA/0xN4ciEn1q2iyWWdOesyI/CKRfJi3FoRMupFHWok8r780V9S99Y9tvfwA9edR8efsTCnDkippAhvdPNMKW8UDxXd5o10O4Q+vDOZEnlekWtU/KlSxpIDbVS/GBvdt3HtvQj8cR8g0i4XvxsnjCtXuRVchxFgBBgBRqAICDCBVwTQeUhGgBFgBCQC+jx4xUSlmCGOXta9q3Ez/fePv+PKiXb54gPp61ddE6gxiBmBh/U4OdGGbWKhxxSGFuue/BOldE6i1QPlNLWzPkvi2ZF3E/7tOJpwyFRPxJ1+HmERTk77B4fozt4hT4pN9J0h8dZSU8c7muKue1u5ULE0aORdWWl+njNj2GlYSjwNz+4XKBZ/PQ+CkeFpItmcyLE4MqoMdMJJfj4w3EfNQzu0v1op8FLCpKOnXSjthtM53bYLBV7bPgWe/gMjiWdG4OEdVFUR18jWQpYg8s+BELn1/O9prr39yWGRDmGYunpHsSlPxKi8rITqajLuzmdffz4dsHRmdpkIWXVDYoWJTyFzEWIsKMKqxX0HkaTiXBs2uRgktmMhNYUxvBah3Aj95cIIMAKMACMQTQSYwIvmfeFZMQKMQMQR2NXYQgdMHc0H5nW6yCMVZsJ71XnhIDVFEAJRmIvKnKEEe/jpR+nuRx6yra6F+on/wZ/XXPkFWjB7gSvSz2kue57aQriMxYnACzt81jifdNNOevf1t2nt47kuocsmHU7jdpRQoiJfcdFw1kE06Zylvok7OZfpEyppd2smvLKQxQ85AuUgjE2gOoSz7O8fvI2aGs3DQuWajAQefn7ZFf8V7JJjuylR/lgOKWs2wMjQmZ5IPGliYUXgdTTvI+8MBN7uJztpYG8q7xmblOigk+pXZ6cYJQIviPxzD37tftq9dqe2vhKROgzvHOScHLYRlelJvLBCVt1uuk3rtlN7Wyd1tXflEN7zF82ihgnCmmNindsulevrnWutDBeKqeRVXsi+im5yK7rtO4z6eNYRWouwXy6MACPACDAC0UWACbzo3hueGSPACEQQgYeeeJ7ufGClNrPamiq68dorfRN5LV1JLZyz2GVyfbnmiusmV1ix5gzVTKUw/rjjwT9oRJ6xyGT7CGfFer74yatp8bxFoUx3/U9fp57NHTl92xF4C//pMKqd3xDKXKw6dSIIBje00NDGFq05DtJTzzvYlRuvymKKpcBDeGLfQH6uJ6c5g9ipEXsMxB1yRWEf3Xn7152a5Rk/oEGgKjxB3sUSjzqqPOVEvZB40sjCjMAbEGrGgT4ROjsi3lnp0RDa/sYh2r2yK4sPnsGsW634qT4nnhmBV6yE/9XiHiPvl9f0AbvW7qCHvpbvWuxE5B31sWMIFwqejebOgUC/XHDcqLoKbS2dtGm9IO9aOzUsYHpj9nvgyGOWhUriyfdPbVWp9v7Bc9crjJ3kPirWHnGDpaw7luYq54x7j70ojWq8rJvbMAKMACPACISLABN44eLLvTMCjMA/EAJdPX300Su/Srd9/1qNtPvJ7Q/Sg4LQW3nfd3ytEuF9OKQUuwTtPBjmekAsNNSUiUNvktZtXq+ReOu2bNCUdjj4wW8V6sazTjqTPnyKUCGFXIwkHuaA8TO+r6OlGOQdRlfJxSQVMJg7yIyg83F5zUXn99ZBUTKUVs8vJl2JjTkSV735DK1681nH6Zgp8AIl8EofoVjJHmUCDxP2QuLtHdxO6ZKBvNBjTX0nS1qEu+5jV3ZBfdeU/x6TRJ5ehWfmQgvcQXx7JdIcb4xFBah5EV7udb+/cv9LhMuq2BF5n33g37VmxQ4LXfnH57PTtyPwUKkQJB7G0UKqxZ6AKgzu7PgdCUIdmQCi8PvSab9FzcDCab74nPPfqaDEdRgBRoARKC4CTOAVF38enRFgBCKMANR2CJU96rAldNTyxfTgky/QK2++Szd+6VPZWZ924RfpX684h84+I+PQ6aUMDA5TW3fSS9NA20CJAvIGrrhjociQTKOjLA57qbSROgt/RfpwWoTQCWZDO2yiwLQCee8KrbyTq7ZzbgybuJNzUCERw7hLqgSNFXEn56RM4IG8FaSWXn0WGIEXfy2b884pTFuPpZYTL/Uh1/B2xXZR50BPTrscAm+fCs+KvJMN8TSgXDD5WRo64hRKH3Vq3lyKReC5JXiNE//JR7+nhCuIvBgNCGK/VdTPkKBf+N1m7U98ITGQuoRS9HGlvoKs9MqLazTlnSzaFyAI/7V5hRaKxMOc9EYheKd2QQEaAcW60z0o1vvOaV52n8PMRRpa+emH2zICjAAjwAiEhwATeOFhyz0zAozAGEVAKu2OOvRAOnDBLPpfobT73S9uoN2CzLvpx/do/y0LSD6o8KDK81qikgdPEjkIox0LBWGhUM4kxOE3CEfZoNYMIg9Y4iDcL8IvQd45EXfJ7SKMevsgdb8wSpaUzSyj8lllVLui1vfUcCgzKlcKRdzJyXsNZfW7eLO16/t0Iu5k3UgQePvUd5iTGwIP9UcGP+0aSijD1jXvpK40SKdM0RN4/SLquu2NHhrY0a3U98VH7KLKiz5ralbgdJ+UBvBQye++VCXwBFKCwGvTZihViUd/rJ2OuaA9J+x6cORmGqZDPKzEfROEzr760pqchthXCJ+1+woE+fCOet8y9wP6aCHztKILGdau6lzrY1jPTceCgYVxcRPF71T8XuDCCDACjAAjEF0EmMCL7r3hmTECjECREPjJHQ9RV3cvXfu5i7UZIFQW5bNCaQfF3Q+/cZVG7KGA7DvmQ5+ltX+93ddsmzuSWphfMctYMbIAMYbDfpVQDPaIUE+EU0Utb58bV9/u57tziDuzPTDhovGCzMs3mlDdL3p1kz5ZvIrro+oYTvX8Kp2c+rf63CrHmR4HOJ867aHGxq208om7HKehhU8rKvBa/0iES18qRarGqsUi7Pms/KFiZT/P/rAQBJ4+byHy4qG8+cwu7c+29VJXJ/4ymKRYZ+ZzqzJSVUsf+eIKjSBAjjMU/f5TVUo63gCXFZA6oFuojr2qdtUIvFHyTj+9ax7ckiHKxP/o91+hSDyYViD3nb7gC5EhBQXzaWd5V527vEXZ6pIUc+tc63U8r+3GmoGFXCfw5fx3Xu86t2MEGAFGoDAIMIFXGJx5FEaAERhDCDz9whtUW11JUOChQHV34MLZdM7px9J1N/1C+xnMK2R5vyD1bt+XF8/rMjt6BrWE3cUuULW1i7l4PcyGOX+ZEwmOoMiTBQIDpdA5s1TWqM/RZ1e/5Z5WGtyhpnj0Q+IBu7rqhEYsaZgJE4JCq1eKpbAyhmZKAhj7CMSdGxyUTCxMCLzTzriUpk6dk90KfeuIdn7XfieByJv5xdw6xSTw5Ez+cOuom2zeCnq7KNaXq8YDcScsc2ninPF03Nnzs02MRB7yb/nJRafyXJrV8Zub0SkHHsJlY5QhPY0FIbTYjyBNoMSWJN7wyCE0SDd7XZJyO33uO9koqgSemQNtsb6McAJ4LBpYcP47p7vKnzMCjAAjEA0EmMCLxn3gWTACjEBEEYDC7jxhXIGw2XHCdRY58T5x9U106fmn06XnvZ9A9t352yc1As9PiUoevHpB8iRT6gn//axZtS0OQ0hmbjRXkE607d1qBJjqeEHVc0pMj7DZ1nszIXWqxQuJJ0NEkZevTWDlhrBSnZdKPb9unypjmNXBPqkQ+wekJUhESQB7MS1QCaM1KvCmTJ1Np59xWXZqKuSdrGwk8aJA4L3zShO9+2qT69ux4sPzaNIBNXntJAmTiINQHSx4fjO/DrBWLrSjC90lCDyd8ce+D2Ys7afzb9izT/GUIdbxjIJjB5FXCBWeHwKvkHnwgI18jkG6G4s+HUCvcJzuS44617reqAE0GIsGFng/40seLowAI8AIMALRRoAJvGjfH54dI8AIFBkBhNOifPbys7MzAYkHJR7+XCJCab8kQm3hSuunpET47F4RRlvsEiUjC0k84TBrphhTVbm5xfTu+AZaXdJGa8QlyyWpBbRseDwdMjJBuTuoGVu6kjlmBvrGu7+9R7kvWRF58SZerDYHPX69QrGIBOVw7S1WwXxA0hTaJAUH/3rhWAz1YRDuuk8+cSc1NW6zhFELQdOZAOjVd27IOzlADonn0cQCfXnJgacPodUv2FaFZ4LMxOnVOeo7M/AQylopHEf7REh8pwhp1ZuAhLlnrdboZswHv3Y/7V6707RJjDaa/lwaWBj3i3StpZLLqD91sWNot5t5GusaCTzNxVv8D5SQTqXQIbT43YRi50Br5lxbqH2kx2ssGliMry0Xjr+c/85p3/PnjAAjwAgUGwEm8Ip9B3h8RoARiCwCZuq7V4ULrR/HWbvFNrUPhHpYUwEapBi+hS+WkQXUSzhE4LCmYkzhpHJTWbOsszrWSneXbswh7oztQeJ9e+i9St3aHeJU8t5ZDeKkwrMiPoPESgkAQyXtcF0R18JWC1FkqGyFIIWQXzLIPW1H4ukJGWPo7I7viIDK9eqr7xC+pMK3lKPjt+cAACAASURBVB770i7ae+AAzaZ2ujq2ikSmKqopiSsRLRhtJH24kHUdoT7wvppW5Fbzrh56/uGMg6pTUSHv0Ic0k0iUxsTzn9BUVCBrwiZggnourHLhmRF4H71+N808eECDzixnIn4OIm/cuL9qhg0gnp1yNDrdB7PPjTnwwD3HBIGnMlahCTzsj6Rwn1VRzgLTjHK7tGD7SI/vWDSw4Px3Xp4gbsMIMAKMQOERYAKv8JjziIwAIzBGEHhl1Tq6S4THnrLicM1pFuWzn/gIHbVcZJgPoUQlD970CZW0uzU/5CuEJWe71JMtbg6sIMk6e70noJcTAHl3bdnLSktUJfEQRjU4lDYNCfRD4NUeW2PqTOukWPQbKugEzt7VceptilHv3lwVR/XkYZp8SJoaDhDmI8K8IEgizWxO2EsIuUaoLEhgOAGHQUpbhdOCwDv88BPooIOPy5ve+s/kz/itAzPP2uSWUnFlQthA2jXGRkPD3zq7nd46u0P77PLYazQn1k5VgsSbHivX3IVlbkOre+RFfQc11qS6CqEMzhBNxqJC4oG8O/DIKaahs8b+9LnoMDZI/LAJGKc1Ou15/efPbnmXXrzjGWqckcnNWdmWpqq2Lpq4MVetqSfvUA9fmljlHE3SExoONeJy815UnbfRhRbPzohOPWrVz/xFs2j+4oyRU6EKFM1IAaBCLso5yX0k8UOe2bBTCJjl6isURl7HgTJ6Ur13kySv43I7RoARYAQYAfcIMIHnHjNuwQgwAvsJAg8++QJd962f0zlnrNAcaP2GyTrBhsMFSLxil0KG/+gNBaCsAAZuDmjI2YeD7YAgavyUD5Y/7qq5Colnl/MtSAJPEncgq+wOqEGRnQBq8+pdtGXN7ixmnVtLNOLusPdYqxNrpo7QER+JhUrgSSz0ewl7DOqdMIlDkHkoyHe3cO4CSzMGSeDtnThEIO6aJ6by9t3cd8to8rpMuKC+3PerLSJHWkaxdcnIqzRHqPHKR0DilWm500DimUU+jgydKSR4013tb1RWxc0sJ54b4k5OzMxMImwiLwiyZVt7C4G8297Rqi2lt72HhvoHaWhAKk2TNGFjM33o8A10zAXteffBjsAbGHlCqw8cpPOqijJZ9WaP9A7SupfX05SyKq1JT2qQuoaStKs/14jE2F+h1XcY349ScnQfxbXfL2Ga+IxFAwvOf6f6xHA9RoARYASKjwATeMW/BzwDRoARiCgCCKHtFlfYxJ1cPpQBLUXMUSbnUYgE3Pqk437ykgWRsw857xA667bcNPge25x4diYbQRB4euJOJcQOOcaQC8+PAgXE3dP3vJJD3iW7BHmUyqiOUD7wkXNp2gEzTOGcMDNG044PPg+fHRY4vE8cV16w/H9Wbrsy/93TK7pMiTsANkwjJLK/adgd8nwl1bfGszg+cMfWrMEBfviJktdoliDx6kdKqZ5KNXIPRF5aEHkIOx0ZnibCZkXorAfyDv2rEnhunxur+nYKK9zD2sqEFl7v531hHBvkGXJDejXCAXn36zdesIUgFtugfT6nvp0+efhreXWtCLzUyMdFAPXH8+q7fe7NJgfibnhvr2AbMyRjV2dPXjWQeLtNiLxCm1fIvThBPMNWalA3exDv5WphZoMSBpFXiN+fbtarUpfz36mgxHUYAUaAEYgGAkzgReM+8CwYAUaAEdAQiEIevDDdXeXhUzs8CTJJJZ+R3daQRKAfdZVb9Z2cD4wtLkkvtJyeXT5BPwTezCsm04TFVUo5AvWTw8ESueC8Yg7y7pf/mTF1kcVI3smfW5F4CZEHb8aJSaqe4pwkX+WVoEpmqBgVrB5amTfklJL5NCU+X2Uq2Tp2ysuf3mlN3qEDQavso+8y3elJvN/ctiUnH1xCkE/T021aOO0VNKqGTJQcIBw7Z9BA/6G+yNpCE3gqId56xS5yKfoho4Gv37yMNz6d+zyYb5SdQkGXCZM+ae5m7dIXKwLPzIV2x5oW+ts962nnW62aKi8T8kr0ngsX0tEXqaV20Mi7LZlwbH3p7emnYfF+EPRv9sdQ463rzigLUYpB3mFcOwdaVw+nrnJYzrUgotuFkt4qLNrrfMNsx/nvwkSX+2YEGAFGIFgEmMALFk/ujRFgBBgBXwggxw9CQotZwnB3dcrP5nW9QairvBJ4mPNjyQ9YTh1zm1JfQY3CnMSsuHWhlQf2RV+b6SmpvR2x5IS/GXmXFuKdwW5r10IzEk+SFQdf4i9UXJW4k+uyC78Dcbd66ClLCKaUzKP3V/yLE0TZzzG3UkGsgKDWl+1C7XTHM/ahiUlB4BnL8Q/ViPx3oznw8Pms/mE6oWOEZoo/UeqkCq9uAsXFJckJfAaiy01Yuhy/GASeqsJKvz4/Kio/zsh3vf58NmzWaXNIFR7q3XDyn3KqxwURm07nEtrDI4cIMvfmnHq//c8XNeLOWLJEnvjgozceQ9OX2rtUp9/aaz3dkWHq7U2K+Yz+DgKJl5pWXfCcd/pJ+nl3Od0buZeQB65HmKb4NU4ZawYWeFdNbqhwgok/ZwQYAUaAEYgIAkzgReRG8DQYAUaAEQACODzAlKHYJYhDiDQTwCE5yLxNRmz8zjUsAg/ztJubqgpPr7Spel811R5b62l7QMVSlohTV5/7/fWLax/MCZvFBIb6RfJ9cdmVT37uqpyP/RJ4UtWITt0QU1YE3lMDt1LTsLObqhsSz4rAu3dLF23aLFxVLSKIxSeUztHfZaCbLXLibTq7VXOhRblkd4pmD+QSPpLAk2DHJ8+gkooqjcjT3F1Fbkm3xEShCTwvOc78EnlW90rlAVNT38me+oRibpf2F70KD8+2FvasS15oRt79z1l/dJySfE9c9t3jaNLiBlN1IsJmRxA6a1Gs1IAlc+spVl3mOIewKrhxoPU6B+x3EIVwrfbqgBzGl19e16PajvPfqSLF9RgBRoARiAYCTOBF4z7wLBgBRoAR0BCISh48P0YWMsytShyG+gQhqZKfzc/t9zNXjBsmgedkHNFyTysN7jBXo+mJOxzwy2aW0cSL7dU1djiC7EDuJy/5vq478yd5XasQeEYVnlQbTV6W1pxpVYs+dLJLENxuTUvMQmhVyTs5R5B4J6RzTTrKqkWOOUOxIoVuXttGw4KDG2oyX7UVgVfdE6MNl2RUU2bkHX7eQAmhwovn0H+SxBt6vIlKt/VRan2Plh8vftoUKllQTfGFNbbwF5rAUwlztpqwV8WhVb5Cp32pkvsuv48Miacn8JC3ELGww/sIPDfKO6s54r3xzWc/amrWYKe+MyMT5RixydVUIq5iFS8OtF7n6se5diwaWDTUlBHmzYURYAQYAUZgbCDABN7YuE88S0aAEdiPEGhsE7mIgkkR5hk1Lwdbv46yXifrN2m4VwJPxYkWxhH9gsS0I5yMJJ6RuAMufsk79OGVkPnz3a9oxhXGokLgwZVW70yLOcAtddLBagSefk/5yZkIAqClK5nNIdeU3kRPJX+qvOUO6RWGEuk4VcbGaZe+xBNTqbJBOL3uK3YEHqpYkXhQ34HE05ehimHqmTpE/cu7LMk71IeJxfhYQhhWCN8KJEUTZaRziFIPiTDe5lGVZImIeI6LDZYSL5jY/GpKnDHFksjzmx9OGdx9Ff0QeHrs8e5SVfx6zQsJ19nntqxzu8R99Vvp+pPfFcq71VQCBk/cr8Hhj4vg6UO0S1+Q8+6BL7/kepyjL1pEJ3/iIGH8UZpD5NkReEYy0Tho/ODJrucRVAMv6sz/z953wElVne2/W2a2984uVdrSRGNXoqLYUGyoWBKjX6ppmva3BXtJTKL5Ur4UjS2iIjYssZeo2EWBBZZeFlhYlu11tvzPc2bPzJ07t5x7Z2Z3Fs4xE2DnlPc8597Z333med8n0rW1RB5qh8qkakf6uyjSmN2ML85NoWSWPqyaQkAhoBBQCAwPBBSBNzzOSUWpEFAIHEAIgGjAA+hQNidGFtFylHW730idaN260NqZWGA/skQo0mlbl7UGitKLlDoQd1nHZVLKqBS38ISMc0OSDAWBFy3iTmweSkhtyq1d3TsxLqcniQ5uTwtgmEwplJ1YZHgWablnUJK3zNAYAfXvntgSrH9nROJpHWixgCDv8PeiiY102S5zxaJIoeXkL/s/X20nS9VlMzLhXt874WnOSPVD48rOH44zJPEGk8DDeUfLZRT7ykhNYi+kDlvXNENqZidLL3aq6IyEwBuVW0DfOPQ4jr8dgfjhomr66PF1ru79a144i48T9SI7WC3OptV1IUYo2okFmWj25dFQEXjRvjbcgAkM0wdUalZE3nAzsFD179xcDWqMQkAhoBAYWgQUgTe0+KvVFQIKAYVAGALxUAfP/9DkpT2NJgW7NA+G2EAk6qhIL4FInWhXJNTTtd5PHIdhZWAhJpOpO+fUkMFxoJoBbpQs0STwBEkw5RLjtOFgHarEqF5T+lTmf7f/UgrGrzeHp5nmJ1aYjgWJl5ZeTumMQAJhqG1IoRUNghconjqYJ0FvU7AXTCxA3PWwV2dukLA7bFQDzWowJ/VL+r2USn4VDZR3/c09lMD+g6No72LjOoUhtRX/OCPM6CJaBN57K77gcc2aEZ5uHMQjgdfqi8RNWn8oQkGVnsJS+U2IPChk25jZiBs3W2c18ILRzRo7ib4+djL/Aa9P2Nlrur5M7Tuzi/HsP0+kzVuD5B8+Zw5LmUHelBSesjsg1NRck351rP7ngTMaIgVeLBxopW5+g07idw3qFsLwAoZTWrzcfEHiNpZojAMpmctSaFVTCCgEFAIKgeGDgCLwhs9ZqUgVAgqBAwSBLl9vVB9k3cKG1Bo8UOsdLGPlKOs2Tju3VzFvz+Jn+V8Tp05mr8qQ5ZySeHd3H0Ez+u3r0enJxdoPnubr4k/uoHvQNModM5WyDzvHlVOoU8zc1JIycqAV63bss0690qfQgrTKKOmn0SeFklvAIpPVTPQyow2oT2G64MY5FXH5nvcX6fecHazZpSdqtARe1scTKOvjiSFQdpXXU05JM1XM2EbtzJWzvT1IOCazenNoqZ40ysvMpzRvUKGHdNqcorNMCTzsH+QdVE4sKy+sNZKPmhJC3Wt9JV10dEq7KYGnN7Do294ROu9qRsxU8UxNw4aYcs8tp2SWTqs1uoiEwNu6exe9z4i7bbtrw9Y8bsYhYWSe2/Rumesf19Y7S9dxwhTX1WnzKwNY6JWZMvOJPjIEXk9Ce2DK5P50/vfLDjmWRucV8r/bre+GwOvq6qTmVsYKzw1Pe//+Ed+h1JRUys3ODSPyzAwseKAZHkoam8f/2vB4+Jc6eRdHRyFshH8sHWidnLe2r5FzLa5h1JOrazL/0svterEap+rfxQpZNa9CQCGgEIgdAorAix22amaFgEJAIeAagZ31uodw1zO5H6it3zZYjrJuozVze+2rWkO+m+4ynDbpwnMpmb1EkyXxZMk7zMtJuuwU5uC6nDY8cTtfyp/m6CdUejWkSumx5xNesWxuDT+MTCwQp10dPL2JBUiUyWf0UWJukKSKhgIRpF3P0nB3zcRJHkqc5KWiS3NDlE4g8Lw1+VT4zNGmcGf0MKYtv448s0JrkAkCTwwEkTcivzwwT/6I74QReFARfbyvk96oYUYSNtnxtdRFXQnBTl0HtdG1e/wOtPqW0p9IpRRU0Aj1nbbfqq299LeGUFJhfHsinVbvpQkdweL1xf84lKUJJjMSz8devYapwDLX5mOvv2RI3OnHXjLnDBpdUsZ/DPIoK93jymDFLKb1VXX08uLVtJ6ljYoGBSiuwXGVhXT6/Cl07LEj2ZcUXa7IYjMjC6ahpJ7EdurXEbGIoSzfS9+aOYfSekt4SFBs1TWxdGcTctUpgQfybu8+v+GJ99wVYdDMmzyXRmSP4D8vKiyhtNRU/nco8vAZ36P9QNKMholF1+4U2nWD+e+lvIu9FAsibzAcaGWua6M+Wufa3j528j39rly+3a4f6ThV/y5SBNV4hYBCQCEw+AgoAm/wMVcrKgQUAgoBWwTioQ4elA+egVpZqd4kni4Ua0dZW2BMOhgRU9033Un9VWttp/Tccl1AkQcS77HkDbQyMZjuKCaQqXlntFhK40b6+B+/NiXutGPGL7iRMkdNsY3ZbQe3Nb/M0mgRR1czU3j1hKdplpaX0xnnhhKSk07rpaLRiTy9NBrEHV//tw3UVx2q6NPjkz49lVJ+mRuodfb82/8IU91px3j7GNHj87MqiYX15P16kMTTE3jooyXxMnO+RnmFR3AyStTyg/su9nzXSpYzK9EEiQf1XU9pF1Pf9YYp8PTkHabVEnidCf1U5+2n92t66IMdoao+EQKIvB/X+BWEr89OpHU1+2j9pr2c5IJKEKc6d04lzTstVLFqtgVZ8k6Mv+6y/+F/jUTtZxQLyLs/3vyuKdI4FxDpC+85mfJH5kiciHGXR794n7Y1Bs8U5J0vqdl0vtOOTqbSwkRK7SmhEe1zOIG3p9GYnMUkTmrgack7jqkBgTciq4zmVZ4ZiK+8bBTHAcQmzhqq1zAykanvdv8zhTpX2btGp05LohF3+pWG0WrDoa4cMMxn6dgeJq/F70mk15qRodHCJdJ5cI+X5gfVw5HOp8YrBBQCCgGFwOAgoAi8wcFZraIQUAgoBBwhAKKspd2alHA0ocPOeMDNZg9uKcmoReZjDyV9rlQqDpd13V3v/idL3okFtSSe6yAMBrZuW01bFt/B3+lnT8YmApeQkbEk8WRNNYwwuP/a55iScKchPEYknl59N/ZkH+WV+2udock6hVqdhwx5h/FceTXRQx5G4rVu66CVj6+hjn5zoqWf3X9picmBpQWJB5ojiTm+GrWyvHKeTpue/TUqKTmSqXH6eEqwtj6k3szCam9FGYm056AmqmZqLi2BB+IO9e7gPKtvIn1WkHd4/zcfhxNEIBwEUQMSr2/5TtqQ2k0JOf6zAZmTNCDO62W8DajMX/5wFk0ab2zggTFIm130+suObp9RJaV06Zy5USXw7Mg7ESAwgPvmtXfOppET8l3VwcNcgsSTJe/E+iDxZnrPsiTwnLjQ1tXvpu5uv9IyobCVKUc3GZ6FVoXn9aZQUYFfDQgVpBACamvkNX2UTo1L5W3Ro03imamrHV1og9AZRGMTM6vBPY9yALLOtYMQmuESqv7dUCGv1lUIKAQUApEhoAi8yPBToxUCCgGFQEwQGKo6eEj1y0hL5sohpNGB8Kll7oXx3qDmgvqhmZGeqHXXO1DvTjbuBFYXz3vL9bLdbfuJlOPVj95CTVtW+5UttqOCHWb+apGD3vJdI60nZUXi9TK+GUq8no4E0pJ3xdN7qXiGPyVTkHdGtRXld+HvaZY2azSPMM9IPCuDtrY3UiurE7evr8ZwSV93D/Wzaz+bFfvXNi9LpfUUNTJyy7jun1Dh5eYfToVFR1ATuxY7WM01fQOJ98GeDtrebqyKQ/+R6cl08djswNC+znbq3WMcr3b+vj2MwGHus9tT/Cm425r76PE1xoYhYtyWZesJ3UvSUgIEHt6DQgckF15Q47EMQUsS79/3/ZlG7Q39rPhgsr9umlVDKu3kURWB+9euv937P7pgiV2XwPsgrXBv3vy7OTRxWhH70sSdocU7m7fS61vf4KSouM85fmylQycl08xJwVRlbXCT+0+n7hbrWppPXbeMalZZKzdl1HfadbUkHlR4/rP2YyEUefwea8um7bdaXz9GYJfdkUZp042JbunDYR3jwYFWJl6jOqz4nQQiD8Ygbq8rmbXd9slhX9Dh94FqCgGFgEJAITC8EFAE3vA6LxWtQkAhcIAgAAXEYBJnIp0RD6BI/xHEw3BIX8IloTWL6Jr/TVdXSTRUeNpagfs2VdFn9y/kD8doIEFkW6xUeNFIVbRKp519yeF00qWHh2xTGBTgh3D8zM6Au7ExKbyyZhUfu7t5D5VkF/O/F7M/xd+1E3f8j7/Wl0zjZ8CesnFfVU/yK+98/V3U0h+sjybmgWlFMuPd9ASep5IRXZXGqiYxdmLZBK7AS69ltc0+8buvps2/2DBEEHnb21h6a52/rhhIu1HsofrYYuO0tp7d26m/y7o2JlJoG9m8zcn+i23R6m7a3mJedK92VQ11NvvnLGHpdKnJQaLJj5mfuMPfQYKCjPjnH84LSbP0VNdQ8rPvUevnzCnDoH0wKZesiDyYWpxy+OGUzOaHWtGq9a7dQHjpW0JhPiVNHk+vvFVLLz+1WuaS4H2EccMZF0yhcy6Zxurw+QkNpDvLmqg88MUWSsqrpvHjtvOx6zb7ly/IZS/GX3rZFwtZ3mSuZtY2btzSX0pFzSdbxiujwmtuaaIWGFdgT8dtpMSi8HqQ+kWQTntY+aE0aUQlM7VgacQD9wfvB/V1WRa1vZxAux/tME6ttYg6Wio8fKGUxkgmpKPHc8N1ZGZgIX43IX6YqBiR+kOxt0KmGERsqikEFAIKAYXA8EJAEXjD67xUtAoBhcABhECs6+DhARK17aCy87HcTpAr3SztT9u0RhbxDL1QQOx8f7mpaYVd/HpTC7v+2veNTD52vLeEu826IfBiZWihd8V1skd9X7jTalNqjYg7XFv6NFKkxOnJaRB3K3f4yTujVpxVTNMrpgWIPCfqO8ynJfDWjm6ihFQ/q2pE4gnX2YrsrJBQkD6bcd4rlpAVflBLae/spqRkL/Xq8qVTz19gSubJnoMdiQfl4LZmPzlqR951NrVTbdUO/9Ko4cUe6HNSPZywC2LmJ/BES2TP+wvmTaO5p1RyIgLkXe4fllBrRzt/mbVtBan0xHF+wwp9kyHw+vbuo573P7GFadnyRlqyWl5VhNqE4pz+/NR8Pr+T2owg7zY3ttMRh66i/DzzlGzMW5DmDSHxhOptdOOltvsCiffRonWmSjxB4MmSd9oFT5p1Js09eA6v2eZjqrEERrCLtmlei79258CHmGGNPJPoxy0NvX9sN2nQAQoxrA1ldTw3mTiNnGvNzEtivVdV/y7WCKv5FQIKAYVA7BBQBF7ssFUzKwQUAgqBiBBAPZ02poaLdgs65yXa1iGTeTCJdnxu54NacPf9T5DvyWddTeGGwLNy5wV5hxeoIhAfdu6j2qBjReAJV9y6plBXUleAmQwSxg0g7j7e/Tl9Vrec97yg4hv8T33h/jdWv0V7WuTUdCdVzuYknlMCz58KytRECe1UX9hFCblB5QlIPNTD62Hur2h761r4n0XpaYxw8ZNB/hL/TJhkQuB5Nu+j9Lc2URpLzfV4C1j9uCAxpIUpuZKpvBb6ayK6bXYk3ta6NlpUZa28w9pa9R0lQ2KXQGPz0gNKO54LOqDA08e65B8XURIj75Juf5yr8ewIPIw3I/FQB+/7886mHqaONFInyZJ3fI1NDVTTlCBF4vFU0YG0UYwVBJ7Ya0ZqEksx9DDVVA//HNaTLYK8Q//TTlomdZwjsvyur2hOCDwxBqYWNcwIRZ9Sm3tYJ61PfkMqBn0nEHjz557Pa67qjRdA4InmlMizI/Davqymtq/WhYSTcfBEypg5KfCzeHag1QbuJE6o9ZBa6/UkmV5brg7SwSB8cQfTDdUUAgoBhYBCYPghoAi84XdmKmKFgELgAEEAxhH7WqJHtGiJFVkDgWgqtmJ9bHCibXzoKWpf9LSrpZzUwbMi7sTigsDDv5GppBM3WsYYKwIPixop4NwAtnnHTtrCXv4/d9HY8hE0YXQ5TT9oFL3X/Ro9sukhw2mvnHAFzS28hKfl2Snv9BNAiXfylNmuCDxB1qwtYXXsNASedg0Qec1trdTCXinMxaEwI0i4oJ8ZgVf469f5NH0JGYz0YfYS7CHdzIUyGiQeauL1NdWHpdQm5hTQXe9upa3b7T83UPuON3CTjGxFG53rdxBFJq2oiaZV4Ams7r/3PMq/dwl51/sVfE2tbZYKPDHOKJ0WCrwzjjzClMDzMeVdP1PgyTQQeGhLqpKoptk6PVBb9w1j9AQeh4Zhgy8x0lOSQ8iWzQ1t9MDyrYGQBIHXy1j6Pg1giYy5T2IptKIhlTaLzYWGzxAY24xpukxma5Z93vzvC/Tmey+6mgcE3sXzLqD65q6wtGEtgScmlyXyzAg8I+JOH7gg8oZLCQfEuY+l+cqmXeuvLTjXgiR2Mt7VYQ8MUvXvIkFPjVUIKAQUAkOLgCLwhhZ/tbpCQCGgEDBFIFp18HjdM5YaJVIZQd45eVAYUZBGO+uta2/FwzEiXbObqe+aH3nKVTgyCjwnJCgcaDc8cTuPBfW9oDCSbbEk8KCAq2vqDFMUycaGfv96dikn7UTjLq+M7GjzMYVbVz21Z9dRz0zjenEgtyZlTKfvl/+K3lzzlpNled/p5dNo8udjqWepfZ0vMblWbWVF4KF/Q+s+amjzE0GoX1YwkFLoqdxAXvbSt5wHPiPPlgaqb+umisKx/G0o8ND0abRibDTSac2A+97SL7kJR3+dvXmFlrzDfGOYAg98Ey5VKM60dfC0CrSHv38ET51FE4ROTV14PUGjGH97th8j0UDgzT2KufYy8kuvwHOivsN8gsCTUeFp06ox1ojA014/WiLvhTW76M1Nwf3OOeF95jrcw2ssGjUPY0Q9Hj9xJ1R4+CxBTcGxUSDwNm2tpvv//QezS8Ly53fe8HdTUt+IwNNiYpVaa0TgNbyyjHy7rQ05xPyekgKqvHg27Wb1Mocq1VQGUCMDC5lx+mtrMJ1rVf07Jyek+ioEFAIKgfhCQBF48XUeKhqFgEJAIRCCQF1jF3+wddNQywnEHR6yUBzebfFsKNuQzmumKHITWyzGiILntacucDW9FYGnJe6AI4qRy5CgX/72Eh6LUwVerEwsEEuk56kl70Dc4QEWD9ggLza1Dai62Dp9ua2GJB7IzF42ILunkE5MmufqrC7KOY+672l0NFaktdYc101tddbOypt2bwzMDRIvk6mmcmd/RomF4UqwrOtepVaWZpmY6KUR+eWBcYLYF4ntdgAAIABJREFUAkljpGLLe/x5R/HLdgaBJxpMLfqbDdLwUxJpy3ssfVEUaGQD8tI8/KX/uPG7krIO7IzFe4tmj6CMFz8KCWkfM1IAiQVVmVV7/NhS2l4YNOq47rL/4e7Eneye6mRfLmibmWmF2fy7d7ZQ10DZgfs+9Bh2a8pkJh9ZPbS9LHgNpDCV3eyZ42jB1Ck0vbjINHxgkcUw+tnLK/g1jK3uqm2k0SO30FGH+0lfs4Z7JTWFXSMDabRCpTmuOXIFHtb856O/p83bQlNS7a4ZqO9OOWEe+0xIMTSWaXi8ixoe9xPBHez+TtNcL2JuI0WekYlFd+1eanz1Q7uQQt4vOWoq9U8a52jMYHfGOULRBmftSBpwhNITqdv43RIr51pV/y6SU1JjFQIKAYXA0COgCLyhPwMVgUJAIaAQMEWgsbWbk0VOmijCjoeAaLjeZafjoZ6ZXMSgHp+Tfdn1FQ9Su665mfqr1tp1D3s/ZckjYT9zS9yJiUQaLVc1MW5CRoOXObKSxl/8a8fxyw6AMYmRYYnMeEHeiYd2EBiCyNzZwRxN+0KVmkYknlAeNbW30PSkw+kQ7zEyS4f0ueTIBeTEhRaDQeD1j2eGLQtSmTJywLzBZGWtCg9d9qTsoI2TXmcpphkhIyo+qqGRH9fwn5XljaA0b7iDLMgvkb6r5bYyf307eaZMd7x3uwG//2ADratvDekGRR51+cmxhBw/sbXzvc3UuTeoYizNTGE1/4IutPp1/GfuV+ctOpHt9YVQAq/b52NphH4nVKumTaOF+m7WjEM5gdfOYtSb6DhJn8WanR0+2rPLv3ejNNrtZR0hxJ2Is2hEJqUyYg5tWlER3XHi8ZZ7uPGt1QSRZWtbJ61dv5vKR3TQ/LODilSzwSDxxhVm87c9qIXWPp3yumbYQSb1vhsVHtR3+NzMYp/xZk6vn81ton0GDHQauyDy2cUtSD0tkVd+VwZzBR6w3x6Ifs/DL0jtQ3QSqtmCb5zpaNxgd45FndhYOtemsHR5ELaqKQQUAgoBhcDwREAReMPz3FTUCgGFwAGCgGwdPJAiSJHlaaRMxQLiTv8w7BYyEIIpTELWyFR48d5Q382NE61efRcpcafFacPjt1F7zRqu1rEj8GJN3iEuELJG6Yp2Z4tadw8998JA7a4gcSfGadV32rl8MzdSf26QKBK1v/a2+hVLV2b83G7psPdhZlG4M9eRCg9EReLPchix4KXWbR22JF5tw05q7+7g5N1bxcZquWOr99Fx1Q2m5J02cH1abazSaKv3ttIfloWn+upBbFi7hxrW+M1DcH+XZobW+zM7lIuYC+03+pqp76n3w1IbZUg8QeDBvOLSOXP5Mmakcvdz1q6/RjEKFd5H2xPpo5ogIblqQgtX3ukb1HfF5aGOqXYkHgg8tOVfBevgnT9vJ1WUWys7MaYiL4NSWTptQfIIytk32/G1bzXACYn37ct+RuNGT+Kuux7GzOqdXld0ddO1exvpqKWJ7GVO7JazWpFaZV7a9CSa9qdcHqZQkblR34kU5+w5R5G3tDCqOEVzMicGFk7XjYVzrap/5/QUVH+FgEJAIRBfCCgCL77OQ0WjEFAIKARCEOhhOWt7WBqtWXNSk80ttCA+8jK9rG6afWF8t2tEa5woet69YjX5brpLalqteUU0iTvt4ptYLbzW7au5esms6cm7JN9GSvaF1pHrSp8jtSerTiB5+cM1S6uWbXjIv//ppbRh2w7D1OGG7npq8BkbDehVeMI8oK7F3//01AupLGmkbCi8HxR4aF2/baC+ajliufTWYmoKZriaknhJTPoD9Q9SJJe3fUov5z5hGhsIvAv2pBkq74wGadNqvecuoLT5Fzvat2xnOxJP1C7b/u4mrsIrYeq7VAv1nXZdGFikM/Vd9ssfD7jU+lNJRbMj8UDgJVw4myvvROMGNK2+sGvLqQJPzAcS77HP+wNGFkibrZoYqkpEXyPyTsyBdNqL2cuowYF22dqdVLs7VHEoQ+JlpXioJCedpibOpY7GPNkjle4HEu/N/75omk47dtRE+s43gqQ5Pg/wuaRVWAvyTiw6/54kqqg2NwURJJ42dVarItu1rIoaP3emihZEf9qMUGdaaSAGqSNqihoZgERzeVHHFu6xrUwJb+SKLLueqn8ni5TqpxBQCCgE4hMBReDF57moqBQCCgGFQACB3Q2dYQ+2g0HcaY8AyrZ4LyaOeKHk6WAPOKil1Ve1hnoWP2uZTiuUd7Ei7gSGqM9X99EztPHNxYZXtta0AsRdavvrYeSdGNjJSLxIiDzE4vUkhSlujALDgyMUJr7efvrxXX8yvSutCDwM6j5hRWCsIPAa2pqZsUcPHeI52nEarSDwMGnv2m5bJZ73l7lUdlS2YZ2v2g/2EV4iLtRwS69Io9Jj8ylzVBpV1aykD9e8Ry9+uZTvwetJoSkV02gqe53Jsmc7nzYn+MwAQ1pt/iWXUdLZF0WslP20djV9xl7rGlfR+qaVfMm5oy+mkVnl9EJVaEqvMBtB2jNIt5H9CbT2jXXS5N0vfziLJo0vIk91DTex8NfHMzbsaO1oZ2pgH9tfkGDNTk+n9keuD1PuCQJvxboNtHpDkLQe3dpBk3pY7bVU5yl//7c8jdav9htNLDs0vD4dUmaROmvVnr9wvuHbb22uo7+/vpKl0IZ/qXHkYQ2m9fCA1L49mXTu+NOpPG1kTL8UAZG3eWtoTbwjRk6i1s3rqIW9Wjevp7LZc7kCr/SEuSH1B8/Y4VdmaltFdQLNv8dP/hu1lIs8dPy3wvHEZ0jXqvW077M1vE6mrCGFqBEoHGktD2qI3ozUwMJp2FpXZDfOtbhVQTiKe9bp+qq/QkAhoBBQCAw9AorAG/ozUBEoBBQCCgFLBLR18CJ1lHULNR6wY1VU221MRuOM1GUg8dB6B/6E4i5xaiUlX3guTwfFGKQfQ9WAlGUZcwqnMesLnaM2HhpUd5mjgiofkHeZTX+3nb7HM47acr5v28+oA66hDLZns5pXGANcQNzhTyijkI698M/mcTkh8ERtq9bOdurwdTom8IqziunkKeGph77n25garzugyEuc5KHESV7ynO2vWwcSupaR4fomakYi9RyqRO35b9u5kbbvCnfTzc7Mo1EjxlH69h3UetuNrs6h8MmlHGM0I/WZzKRXvnIrI+/WmHY9acwkGpl2LK3bU8TPEkor4ZR65qRSOou9qjfU0dJX1lD1xr2WSwryTnTK+f0S8q7z1/+zM+wQY/rOP5aSLpzF7jUfewVre+6s3c4Uni/TqvVB8xCMGZOaRleWj2TmDymUl50tTeQlTR7PUqXH0/qqOnrmndX0XPemgLlFNrsOUtj1n8nche2coa1UeHPv/Y8lXiDyKlhtPKTV1uxIpZqdadTVmE11uzPooe+fROnMrADnPlht3QN/4KSdvgmiDGRe2ewz6bHmNnqsxdzhGUQeXtr20bw+ujQrgy7NDq0RKfq0fVlN7SvWBYgjGSJvOBB4QmUYqYGF02tAEHlOnWtV/TunSKv+CgGFgEIg/hBQBF78nYmKSCGgEFAIhCCAenZdvt6oOMq6hXa4GFkIJ1orcgoYaIm7SBx6neBpRiCJOWTJO9HfLYln5ZpohUs0CTysA1fjfW0Njgk81L8ryS52Aj3vC+XJnsYggYcYQEwbEXdNLL131brPbdcAkVdx8222/cJIk8pplLXwDv5joXLEfS6bGreybjNd+cpt1NUbahpiFEhuWh+tuPKZMHJS3xck3tJXw8nAeadW0rzTKsOmFio87RvCsAMEjVG6eN3fr+ZkH5xcU72sriYjsJavXU93/N8/TF2urxhRQWPT0vkyZcxgQkaN5z3ntEBYj1etpifYK+wMcA1a5bSzAVYE3uV/e5P2dtg7j4LqQoYx3IyL0r08jEd/eLJh3TnHF5LEAKjt1j9wr2lPQZShQ+bYCfTAvCtoZbc7YvHlcuP7EgRe21d+NaBWtWlF5A0HAi8WBhYSRxro4tS5FvGiBp5qCgGFgEJAITB8EVAE3vA9OxW5QkAhcAAhAAIvGo6ybiGTJcbczh+tcXb1+oaCuBN7s0tDztn7K8cwuE2nNSKzhBLRjNC0IvA6ettpV6e5s6s2hRabFA/nvl4fHUdnSNfAM1PfyQCHPdc1dXJHWLFXoS7Ujpcl78QYqPDGPOlXeco2vQOtUNSksRpXLcxJFUpQq2anvNOPhRLv3hNulg1Pup8RiYfB+lRd/KzxZ/PJN6kiMLcgkk/5zjUEkguErllzQuIlH3cEJRbmB6aKFYH33fvfpi6mTJUh8VIYeVealcJITUZssqN97EdzeMq2kzqU0oei62imvBPdtAQefvaL+T+g1KJSV8uZEXiYTO9Ca0XkCZUu1LDFl5/lKpbBGBRLAwun8cs416r6d05RVf0VAgoBhUD8IaAIvPg7ExWRQkAhoBAIQ8CoDt5gwiTUSlaGGoMZj9VaIwrSaGd9qDJpKIk7ESvUXk3MydeIqEhhNe9Q985Nayr8reNhQg3oBJe3P/mM3v7EXJVm5kLbO2Y34aVtHmaMgrp6U7Jm0A8qfkVvrnnLdg+RkHeYHPhDcIW1rVSXK6s/o+YBh1zboAY6jGYEXgYj8mSanrzTjhGpy/iZ2bXyr5Uv0X2f/1tmqZA+1x51Dl0y+SLH4+wGgMRLf/GjQDptyH4Y1jRlFO396XmG1/3Nf/4brdm4iRG6iTy11yp9XZB4SKcdUVxkGJaevEOnWBF4L3yxmV5gZhZode2sDiMzHNI3qO6yvcnc5RdNKBSfuvpUbkbQwVSXsWy73nqRdr31kuUSegLvZ/OupJTCEkpKkXMl1k5uReBpVXjaMUZEnnCgTZs+gTJmToolRBHNPRgGFk4DtHKuxee+qn/nFFHVXyGgEFAIxBcCisCLr/NQ0SgEFAIKAUME9rV0M1VObB/27KAvzk3hRddli5DbzRer94UTLYgyJwRVrOIR80Kt0cke2GGwoW+REHitOd+jXs9BjsIHRj6mHkLtP5AIskogNyo8vfoOgQoC76bKe2hq9sG0u3kPraxZRXtawovno7/btFkBCurc5aR7eIqq1V6dqu+0oB+RVmpbD8+KvNPOJdJqocSDIk97z81a9ENq6jZ2/LW6CGKlwhNrgsjbsvE/tC5pwEij+xLyTayghKmjeNpeF68xGLqXC6/2q05BIoHAA7kgVGpGe0FNPKTTXjJpciCVNoGp7aC4Q807o7ZyTx3d+M67YW8lR5hCW72rgX7/0pch80KR1zVA5GWnGBs+zPvaWLr8+Ik8hRZ4aGsBOrqJJTp/ceMPLHtplW6iIwg8T1YOebJzJVYI7WJF4KFnwyvLyLe73nBeLZGHnOPkknzKOeUYxzEM1oDBNrBwui+9cy1+H+YzkyfVFAIKAYWAQmB4I6AIvOF9fip6hYBC4ABBAMQDFDlD2eDw2saK/MPQIJ4b4uxmKcd4QAZBNVg17uwwQdomFGA4S33LaPqbqeus3bxO02gRB2ohiZprTkw7Nu/YSQ8++4JpSDs7aqizL6h+9M3cSP254QXxQeBdP/G3nLzTNxB5ohWzWndu6t2J8VqDiiQo79qtr18z0wq7M8D70yZ+jXKy8qljyePUs3oV9azx7yP1/AX8z7T5F8tME9Ink51VOiOCQPQItdaMh5zPIyZd8a3HHcdgN2Bd4kp6ybuI1g8Qd9r+E3qn01xG5E3sm86uuST28rDrroffA4v/8zo99YpfdapVgQmVmnDKNVr/gtPmEF6y7ezFS8K6gty3u/bNXGjFZFoVnkwsE8ty6RdzD+FqUHyWprKUaXxGNbfbp03LzK/vY0fgCaWbMDbB+L8cczptLCyj9PLRjpe0I/AwoRWJh/dBjGWPKqYR82YNadkIu80PlYGFXVz693Gd43Mwk9WdHDCMdjqF6q8QUAgoBBQCcYSAIvDi6DBUKAoBhYBCwAwBkGZ7mfptKJuRw+tQxmO0ttY9NV6IOxEn6gh6PUn8YV3f3NS/E3PIEnh6MgsEgpEa0O5M7VJpRT08PXnX1N8emPqsqT+gcSlT6QzvTLvlXL0vroNepjoRzrJQQLYz51MrAtqIwBub3Udjs8Prs21uTqDNzf7USLSRZeOYM60zJaTM5rCXbKZgw8P3+1vW00VLr5UZZtgn2gQeyLv70q6zjQdE3jWdd3FyBuQxav3d/8zL9NgLr/Kx+jRO/Az7RnE8I6MDpwSeXoWHmntQ+1kReFYGFtoN/+6l5bRuV6MtBoK8Q0dt6qW2dpkdwWy7iK6DLYEHjFGXT3N5bygopb8ee4ZjAs/KhVYfd3ftXmr7cl2YGs9TUsBSZifSqMoKZnDSzd2ycR3E22c59jPUBhZOr4V8VoMRxjGqKQQUAgoBhcDwRkAReMP7/FT0CgGFQJwhsIM9mFRv3E5Zmel0+MHRrd1Tu6/D0NlxsCCIZ8WBNlUWaYdQW9k50Q4WbmIdK/ximUKrJe4EmWWlBpTBBUo8EHlbduwK6z6mvIxOPOIw+qz/Tapq/oo+bP6Imvs7KDOjnN0XFTSi5Eh+PiDX0M7wHBw1Ik97HTQzxaqWoJQh8LT173JT+unQInu16Rd1zE21K8GWwFtVu4uqdtfSk18F0y6nlpTStNJSuujgQ2xhx/WDVNSyP55n29esQzQJPFnyTsQiSDz8G+e09M036d8vvhpInRXXgzZ2bVql9n2nBB7mvOHtd2lVXR2f3o7Am8bcbu848XhpnO2UeFryDpMaOVLHgsizI/BwDkhZ1pdFgApv18FHSe8fHWXUdzIT4syLcoKO0QKXeCPy4snAQgZXVf9OBiXVRyGgEFAIxD8CisCL/zNSESoEFALDBIHnX/2AHnnqVTrpuEPpzfe/oMNnTqZrf3RJ1KLf29zFUkPtCYWoLaibKB5r/hjVuLNzoo0VPnbz6h9Mtf3dEHjPbUjhU1SMu4omFJeFLW9E3IlOUI9EywUTRJ5oIO607Y8dr9D6vlADC7yvJw4mJJbQT9NOs4PQ9H3Ml87SxLBnM7UOSMseJjWyMg4QCjxZ8k4EBBIvK/8gUwXer1/9DyfvrNqtp5zGyLzwc9SOwT4Pe+RK6uztYKSLsWvrWTlfC1nmhSa/8UhOai+9t2Cxa4z1A6/KONPxXFd33MXTadGQPvvMa29wVR6alQst+vivGb8izw2BhzWEoYU/ldBPXumbU/JOOx5Enr6ddejYkB9ZfQ6goxGRtzXlbT7H6K4THWFuR+AZKR+xQObYCXT1aZdJr3V3YS7NSIlOfTXsH8o7/Rcw8UbkxaOBhdmBoZxEEathq5pCQCGgEFAIDH8EFIE3/M9Q7UAhoBCIEwSOOvMqevr+W6m8tJC5WLbT/G8vpB9+6xw6+7TjohJhPNTB0xpERGVTLiexM6cwUri4XCqqw6zikkmjXbsviX7zaUYgpr7ELOpPzOb/Pn3qTDpj2iGcAIBSC+REY6vPME2QFzhnNcnwfqyaGXmH9YyUP25JPF7fiRGSMHmxMqgQxG4H69fK0oeNGgi89as20KmT+qhXl7GekMTiZsacickDjJNugq4SYwJShrwTU1mReCAgsdcLltxB79WEuwH/vPhMmpQ6wnBfIPHa81rp3hNujspxv+RZxOveOW1ChSdcrU+68mp+fSZ2dlFCZyf1tXUSY1j5tP35OaxwICMd0oJuqKI+3l3XXEVjRo52ZaiDdNoNjfX0yFerQhTNIO6QNjvdxOHW6V7N+mPvMBOAIZBVq8v+L21IeoPvUWtwm9MzhkYxIi+3N5QYNJpr3QN/oNbN602XMSPwymbPpbLZZ9L/q2ugld3mnxHTvR66NDsjauQdArVLTY0HIi8ev8yyupaAKX4nqKYQUAgoBBQCwx8BReAN/zNUO1AIKATiBIGpJ3yLqt55KBDN86+8T3956Dl67YnfRSXCLmbMUN/cHZW53E4Cg4gOVoDeTe00t2tqx9kRd6IvisTD9MNK1RONeJzOYRVXkm8jZTb93XTKuz9Jp+qGoLNlf4KX+pKKQvoDnxvPPItGZBVZ1nqLdTr0+t5a+mOnv76ZUUP9MX3tLfT7aeqpNCGpVApWK4Wh2QR48M5ixdxTWD1CXB/6enjVH2wlX20VTZ9uTNJhXhB5nszQ9xMT2Q+zJ1NHysiQpZ2Qd2LgM9+8ImQOsU8oB1vZvbdiz2a69KXrA31A2oG8s2vjckopf9JYSs4MEmJ2Y8zevzf1OkPTCpn5Hu17hRORII8fYym0Tz3wb0oYIO04vv5LI9D6QeJxMs8f95Tx4+h3v/wRV1y6NX+QUWPK7MVNHzOFmZirMWkzrcx4MDA1bhUjd14QeTPar7QMoWXzOlr/wL2mfcwIvENv/7/AmBVd3bSyi51VS9CMBvXupqd4okrciQWzmVu0jzGWVkpZ9B1KIi/Wn59uriurMXmZXn7PqaYQUAgoBBQCwx8BReAN/zNUO1AIKATiBIHzmeIOKbNInRXtlAW/oGt/fCnNPta+xpXMNnbWBx0+ZfpHu4+dOiLa64n5nD6s4SEQTrRDRTSa4WDn5GuWShsk7waYjQRGang15B37cQJjPoRz509OPM0wrVbEBZKkMDvFVgXk9jxf7v6SXvZ9ZTqcE3isad0v8W8ZFZ4wqEA6Jerc2TmJGgUhVIpdLCUdDq8gjD544iuq395E55zTbpqeGsBPR+JlpGeTLymbWtKnBZZDzbuFr73iGMKLDp7Ja+IJshoTiNqFYrJr3vozvbntA/7Pf4z6Lv8TiBon1bLUy+xSyvCk8X7ZB49xHJN+gJv0WZEG+6DvPwGlZPK1v6eFK7+gqoRe25j6y4s5iXfTj75HU8cfxPFBHTKOj427sH5yjOtkhOhQfD6ASAGBbKR+1ZN32riF+hDK2r6BSgoyJJ6VCk9bi1KsNeF/rqGssRNtzyNWHfAZ2cKMfmS/fHH6uyEacQ/V70G3sav6d26RU+MUAgoBhUD8IaAIvPg7ExWRQkAhYIMA0lPf+mB5WK/J40fR5INCFTCDCSYUd8+x14P3BV0i/8oUeGhXsVTaaLShroM32MoDtw9n8fqAJWMeASVeavvrlOzbxC+ZYNpsv5+k0ZN3mgsLRBQe7scXldJPZ59uecnFMs34R20PW67N+TvG6OgJPAz6c8blhmNl1ZdO7rMMlkacnpJMm9bW0dv/9ptLnHsuM4sRDInFZEmMQ01KTaDUlHRmyuFXRu7LOiYw4smvlocYVjiJ6/Xvfceynh/mAok3szPPNG1WrJfHapOVZZYHlk/KSKWM8XIqR7OYnRJ4wlEWRhR/bXuRT+v7+T3MiXQFrUxup6VJvbQ+IeiQmciujST2XyL7T9sW3ncHJ++0TXxGOCF0ZQxNnJyXk75W9SdXpP+LmpK3WN87DBLgI4i86W1X2KbTGpF43OR3gPQXCw41eYc4UFuurqnTcXq0298VTs5O9B1KAthpvMnsoIvzIlfdOl1X9VcIKAQUAgqB2CCgCLzY4KpmVQgoBGKMgCDGsAwIvUeXvEZ3XvvtqNWbcxs+FHd3XPedgANttAk8KHGgThjKFkviR+wr0oexwSYaZc8D6hsUFEfqn10DkQcS797/rqR1jQPpT8n+endWTZB4oiaeWV+3D8qma2/8hL+VsOlT+uG0dsZuMXVUMitsnxKs2SfGcndRHXkg3tMTeOiLGndWBhV2mFi9D3Lp06dXUu3mBq76AYGHBpMIM6MIMV92cUaAvMPPtASeSJ/tbmsgX1tjWAiJnlTyZuRSktevjEMDqYJ4Xv72ty3r+Yn+uz5bQ9uadzPlXbj2LoPNX5iWG1DeaQOIVIUnS+BxkgjmE4xdE2mxN+15jr587Ss68s/3UaunPhDWHxO9ISQezj2B/edh/01PSKYFlEqTFpxNvZeeZXicohYiahyiXqiJxwcfi1R2s/qQkVxLMmPNUkSt1HdG8wpFXpZvNE1rtU6lxXh9Oq2WRIdpBWreDaXyjn926BxoZfDU94n0d4fMmsPJwAKp5rkshVY1hYBCQCGgENg/EFAE3v5xjmoXCoEDGoEb7r6fsjLTo+r46hZQKAPv/tNjdNUV5xL7gKVHGLH4v7f/hBtbRKPFQx28WBpZROvhK9Ypom7P0q7+ldG8P1n8IKuB5WxFkBenVvpNLcxa1OoE7ttBCZ/7laaicQJP29Jz/WTeQJMl8LT139pZyqObdFk75PZua6RlT67g5AHUKmfOC41dT+RBtYSGP1MyvJSaGXR31BJ45z3yIHU07KI+HzNmsGgg8tLyygj1yPyGBf0shdafRmvVumobqWu3nxjs8HVRWw9US/7cyqL0vAAZiPmgTtO2lJJcSillZ+KyyZhYaPcjlklpHkOHr7mDRr+2hL2eNlz9ZUbWiYbrfnq/h2YlFPJ7AKRvwmv/ZASdccotjgYKN6gq2zp9pv0+f3YtvfSv8BTv0dOK6PhLptGY6SxdN0bNTL0Fp9ltA26zTpZm3wfQOfQbU/dlo7l2vfUiJ8RBWBd+/Qwny8W0L66ZLFb+QO9A62ZR7e8SXC/tXdakruwaw83AQtW/kz1Z1U8hoBBQCAwPBBSBNzzOSUWpEFAImCAAhdub73/B01azGYkXD+3Tr6p5Km1WRhp9Y/4pUSPvsDcoWWobrAmBWGMgW2TcSRzRIu60a0IpuLsxNBVrRdVeWrm6nh5bUk3TpxTQjCl+YvXSCyY5Cdd1X1kHSrHA+j276C//dV5HDeN7Gcfxp4tCDRG0gdvV45PapIa827q7kg/JyaijG47aFj5cR+IZ1d/CICjw3BhUSMVr0AnGFdXLtgbemTWriwoLB4qM2UyqJfD0NfBO/+OdtuSdmD6ZqfBS80oDqjG9kYVRGFoCzypMXHMgHUR9RPSNlMBbl7iS7ku7znBZ1DeEuku7Hl+TkXcT1/6cfN4mOu/HQRMOq9hBlYKgSmH/lST4SbXUt/9FqV5/DTm9CYmYS5iVGPV7+Lq22my/AAAgAElEQVS3aOeavcwowaxiIKsZyIi8y++a7faSshxnRpzLpM+aTXxQz2yannwKf1u2HqDTWnMxAUM3qROFsmw84ncLlM8wgbFTZ9rN6+ZLGLs5Y/l+cW4K+3LA4TdAsQxIza0QUAgoBBQCESGgCLyI4FODFQIKgaFE4PlXP6C/PPgsJ++ipXAbyv3Irj3UdfB4EfZk9gDNDAQibbEg7kRMeFAWD7Mg7kDagbwza3cvPIZmTI2OUtIKlxEFaSRrRvLaGmYGURVe71EGd5Rx+98LzQm8iIlYRt41vfs+bd1TyRxdQ91wv5i8jqqmrSCvR0c2a0g8IwfMyZ5S+nXBWZwAGqwURz2BN3myjyore2QgDlHgdXhHBlxot334NP172dv0bn++1Dzo5GHptN6MPN4/mgQe5hMGEkLhFymBhzn1TrRiDaj9jGobFq/9Fk1smkMfFD1A113+hjQuTJTF4x+V4K9v2v3S37laMSfDb2Bh5TYtPl/QD58FN57+OB/jYeOtCDz0iRWJZ5Z++V72QmlM9B1HdZ1Io9lLv18zghPj4zENNOLPJAsEgQ3SSVO9SRERefFaX9Vo66r+netbSg1UCCgEFAJxi4Ai8OL2aFRgCgGFgBUCazdupx/f8Ef60x0/HVLjiqE4JTywQkUwVA0Pz0jLqWvqch2CUFjxB2tW16+DpUdGu+FhECqgDz+vpWtvXSY1/WCQeEhBBglrVaNL4NPX76PLHnhAKnZ9p4MKS+nHJ5gbWcBQQ+DvZoEVi+upqabbcOiuwnp6+biP+Htp3hZWJ05zvWb7lVR6Ag9KsV8XnEkje4ticj2Y7VFP4KHfccd1UVGRvQpPKPD06rsP/nApbelPpUf6g+YRMhhnFI+lqSWldNup1gYkmEtWgSfW7e9iJii4zdgr2ZdJyZk5lJifSMkHBVNWZWLU9hEkntakwmyOwz6+n1WxS6OlFTfS7xZslF4KZC5eOZRNOQk5nMATDaQMT0ntDroJG02Mfo/9+h1a90Ut/0yQIfAwz/EXT+UptdFsZjVE3abQIjZB4GlxyUofuL9NHHoHo5apU9wGQxUozHDcEnmIsYP9/h0KB2OneKr6d04RU/0VAgoBhUD8I6AIvPg/IxWhQkAhoENgR+1euuLqu+mc02fR2aceG3gXdfDiJY02loeGh9V9Le7Js2jE5vbhTxBTeIhGTbNYEHdif1BKrFpTTz+89l1HW441iadVBuoD06eOej299L3HrB1dzTZ32pSZdNoU8zpqqZ5EppBLkjLU0K+x4vkOatoYbsyg7QcV3vLJ6/mPQki8ARWeIPBEyuW4hBL6Scqpjs4qGp1FDTztXIWFvTRrljE5qe0nCLzmtKnUk5zD34L6bvuHz/C/P9w3grYy0kq2peaW0h1nnkvTSstsh/S0dlL7xlrbfiDuCC9NS/UVUnJ/SiDN1XOYl5N5ThtcfH+fch2t7P3SlJCe0Dud5nZfQp+tGEXV2W/x1w9u3UEHrZYvBcD4N0MCL3ivJ7Hadx5e58woRXLLyj30yPVvB+oCYpydAk/MvfCFi5zCYtrfyqQhEgJvVvOthmuapaKDxCrITqE9rMRAPLWoG+tYbM4tkRePykWzbUKlit+DqikEFAIKAYXA/oOAIvD2n7NUO1EIHDAIoMbcX1nqrL5NnjCa/t8PL97vcYiHOnhWJJTRAWiJO9kaTZEeJFQ319++jD5ZvsfxVC8/Oc/xGNkBRmliZqlvaSl99MrqL+nZ5eEF9+3W+/ullzOC1JyUcVvLqXFXP618ppmRQjqjCoOAXjruQ6ot3MfqmPlYXbtWfw+40rIXCDw0pFwexMi7n6YGybvmddXUvJ692J8t69dR1oSJlD1xEmVPYC/2p1nb3NFLWwwMDk7Ms3ZhXHrPf8OmBIk3eXJPiBIPxhVaZ9r0EeWE1FlB3mESLYHnVIV34zFH0axj5E0F2jYwRVmbOQnT38ZUhDpxa2Kvl7zdhczflSnbcAYDxhlOSDw/AeSlbl8fPVf7CK1JWEHrk1ZSJ3VQDytFmpyexkk7kHcT+6bT7rYeenNzW4DAO2XJPjplSYPdJRx4XxB4WTMOp567f244ThhYpLEUyZYOH1flifbuolX07uNV/J/Yt7j2jAw+9JN/884To2ZqYVUD06kLrYhTr74zAgdEa1YaCM5ejg0nr6JkFiF9iDYdo+FA6yYWJ0TecDOwUPXv3FwRaoxCQCGgEIhvBBSBF9/no6JTCCgEFAKGCNQ1djEFiX2KX6zgE+mpdqm8Q0HciT3jYeusi1/gTotOWyxVeFBEICUQqcPi4dHL1HBGqcTJSf2UndFH3/zXI462cO4hBzP13UxLAk/UEatvtleaaRdf8VIvNW1hZJwEgYdxIp1WqPASGHmXlJ7Jp8TZgLibkFQaWGL1vfdw0s6sgcybcs0vw97+184ORt6Z3xNXlKXS2LQkw2mNVHiiI2riwdRCm1JbX59EidmFlM2cfvVNS+DhGtyWkE4P9tgr6o5P2EeXHXMijTr6fOmztlLhGSnvMLG3q4AS+4LOucHadf2UdKi1Eg99M9n1i/v6qR0P0av7HjOMdWzKdDop+xIalzo98P6iVU0BAg8/dJJGKwi89Ltvof4Z1oYzuKeQVosmviwIIfB4Sm4CVx8aGXzoNxTNNFo70tyNCs9Mfaffh9aht5cVyPT19LtS30pfnA47uv08criMaXcZIg+q5TR2/UfDJTdacZvNg98xpfny6t9Yx6PmVwgoBBQCCoHoIKAIvOjgqGZRCCgEFAKDikBjazdXUwxVs3uQGUriTmDy2FPV9OSz61wReJfOnxQzZ1qhtutl5JUZcac916z0XtpQV0t3/ec1qeOeXFpC159xKu1rNiartJMgHcxpGt1797N6dl1t0gSeWK973CrqOWg1JZWMpe68UXRY1kiq6CkKcRK1I+/EXFoSD6q7B3fJpQJakXgfPPEV1W9vksK4cFQOnfO9I/g9qE/ZFASeIIcEgfxuf56hqcVoploDeTcmoZNGHn2eIwIPwZqReP3N4WSmnrzTbjaRiTW9hckEJZ6R+YG4p5H2/oetv6TNXSttsfp20V0BEg8EHhpq4KEdtLqDpdLutJ1D1MDLmn4YZfzGOFXUaBLtffbiA1/SW4+t4t1AZAkCT/yb1/ADlgZkfzQJPG4AxEggGLSYNSdutNPbrqDc3rG2GGo7YP+5rIYpjIii4crqaHGLzrFwoHUTmxWRJ9JR7b64crNutMegxl8+q9enmkJAIaAQUAjsXwgoAm//Ok+1G4WAQuAAQWCo6+CZpYLFA3EnLgEQeE8wAg8px1aGEUaXTKwIPOCWzeoS4eG5qd0nVQNQqPDW7KrlqbRra3ebXuVQ3uHV0ZVgqb4TEzitZcjTZ5kCzw2BhzWPn/EM9Y09nLE3R3CVVDtLdxVkkRV590FDNm3vSKHtnUHl2GlHlNK3b/0e2Snv9GBZkXhGhhb68QUjc+jYBQdzIggP9CgUD0JG7GPXJ8/yNFoovJxed9MuuIFyRk5x/CkGEg+mFiKdVq++Q9psck9WiPLObJER87P5W8IFWBAaCezabWYGOn+rvVaKvBPzCxLvjc2ttKetl7vQ1qds5m/LkHjI8t06LY3yf/Mbmpg43jE2+Ez64MnV9PKDX7LPAr8hBlKhcT7ahvOEayd+rH0vmgSeVn1rtREZJZ4b8k6siXuvi6U/42yhqERabZtB6rljsCMYIKvqjmAJR0ONiDwQn8PFwELVv3N03KqzQkAhoBAYNggoAm/YHJUKVCGgEFAIBBHoYemze1ga7VA2kD+7WRF0kBTxRNwJTEDgPf4MS8VkAeqe1W1hizaBp0+VzWH1p2ob5FRjCBa18NJS/IQDiDyQeKIuHhR3lWWlnLhD8zGBXEu7vfoOfeGIu6+lO4zMMANo6xd9tI29eGuus8VR3+Hr05+h/jk/5D+GC24POxgoulDrbs19vwubbxsj7Z7cVWS6jq+gmPJPPpRGHu/MKfTWcawOn0lDOm31sq1hajwQd5OOGU2Fo3JDRorUP6GoxH5eucO58UF2RSVNv9CvTnPbQOT1sldfXS97+c8psY+lxWpSZu3mTmKutJmVXl4zDWn6niS/Ugv7erNpEb3ZvMhuirD37xz5YqAO3l5G3i1jJJ5oIPFQE8/I1ALE3fsXF9C0g8+jucmnOV5XDEAK7XtPVlESr2HIy/6ZXvNQIqJfLz43GITRNLHQXvN2m0FNvKbkLbQt5e1A15yeMZTDFHeju060G275Pu77BqbihuLQLo0/ooUcDIa7axsrK2Ck/nQwTdS7aok8TA73dT35G/VFozBhITtjqFBVUwgoBBQCCoH9CwFF4O1f56l2oxBQCBxACOxmBNBQPkigiD3qKKV6E3kcg2VOIXvEK6r20nW3LeNqG6jwnLRoEXh4+INCC6myKPiPlEtg5cZtUSjxrPYhq7wTczg1Iwko8DCBwzTa0cVrWHooq33H1HdoIDNwNs1MiWikvoPqbhl7WbWGglJK9Hgoe3QRTb18tvQRn5jnITtji57uJ0PmS/Yak3JahRrIrrZOH615e3HAiVY2KCP13cY9VbSpropeX704MM2cKRfSuKKpdFDxVNOpezb2UC97uWkg8FImeLhJBZxaPUwCJxSG128/082UvB7eSTmXhJlZ6CcDmYcX2mvz8ymf1SyckDCervH+yNW62kG3zXuSK+zEJ4GdQhLnOvHQUoKJRbTcsqF862SfAZ3ss2Aom9Hnj5mRzmDF6eYzcbBiwzog6hEjfpfEU+qxEQaq/t1gXhlqLYWAQkAhMLgIKAJvcPFWqykEFAIKgaghMJR18LSKO5FqF7WNRXGiuQuWUiJ7moE6ykmLhomFwAjEHQwqtGQryJEmlo7oxmCjd08jU1T1UHZ5Bnky/DWOnBJ3Ags3hAKvgSdaWyOTMpnX89JiPmpSE42eOznwI6QsQuXlSU6gly+7POR47JR3onNDfgklev0YVBw/VVqJNyY1ka4cYVzgHcRdjy+UvBPrJXsuIkHkaQ0dhAGJSJHGA/T7/7qJ9m1bLXXZGZF3f3vnJk7emTWQeN8/4RbDtyMh8LKnpFDOtFSuzBQKLWEK8b2qU6T2o+8EU4vvFN/Ff6x3pDWaEMKhNPZ/U5InREzeievsv4+voqX3f8mXE8Yd+LvVPXjF3bNp5tHlfEzd4y0B8k/EnDQ3mNItAwxUZi2MsHZz38vML9PHzkl1KIg8u5hk9hXrPqLuK9LI8eUDaszFK5GHOosF2c6uzVjjp+ZXCCgEFAIKgeggoAi86OCoZlEIKAQUAoOOANRcIPEGs2lJKdRQSmXqsnh25HNjZDF9SgH95qZjXcNqRdyJSZ0SZ63MXGH3RzXUVtMcFldGRTaVHFVBmSzF02nDgyjEiU6KsnMXWlYLL9BkSLwkD836aaFheCAMPvzBt7myRQgln9hZFFLvzmhgR1oGdaZlBgg89Dl6oXzqqj6Ntq+XmWww8q6vz5w0E3FkZd1OedmHcGUWyDt9w55Qg6r6ncVcjWfV9OQdVHd/f/cmqaM0I/HcEHiC1Eo7MoW6/SbBIa2mt4r+sftadkb+1FKzNnpPAZ2wajKNqQs977xZJ1P7kX7DBZB4e9jr7aa1vB5edfZbgenSGKE7wzuRp8y6qXmnjQvngHtNnNPD171FW1cFU79F3TuRLqsdC+XdmOnF1PtSF/WxFxNX8taj23vChCTyXGOekq2dEwqu+uahTcE0q19qdA1npSfzH8daXT3UDrQyN5vewAI44mcg8tq7esLMbGTmjFUfVf8uVsiqeRUCCgGFwNAjoAi8oT8DFYFCQCGgEHCFAGoF7WX1eAajGZFSw0E1AWwW3vkhffaVfL02t+o7GeJOnBWIM/5gbED+6M8T5N2mJfZKLhB5B11gnlZpdJ3IFtXXjg1Jo2Vv4EG2n6XT9nUwZ1qjlpLOUmezaPSh5vWYPr7qO1wpiWtqS5uXQODZNSMCb8o3T6ScMcV2Q/n7egKvu+PXUuRdMisviDpq3tTbqD/BHG+h/OqoXUvbq1fQxveWhMRl5jhrp7zTb86IxOvb10e+z+TJfeHCCpVoyimphvht6lxJ99ddx84p6OKqN+m4/K1jw4g7MVm5129A0XTeTPJV5EmdkdtOQXIlkRFmoTUeUQ/v3cdDSdpA3bsBElmQd75726h/fdDtWzjigmjWZuXLknhOTWPc7t9qHJRk+OLFyglXOx4lEmAwgXRqqM9iUbYhXhxorXCDetLIwCJoZpMcN0Seqn8XiztHzakQUAgoBOIDAUXgxcc5qCgUAgoBhYArBGJdB8+OlHJqguBqkxEOwoPXVf/vHVq+cq/tTG7IO4GRkwdcPER7PUm8/ptVkyXvxBxOSTwolNJTzR/mW7e2Utu2Vj59xqhMyhztl2aBxKv6Tx8n3EDiBGoM9jDSSKTUMtUdyzelnDKmqJprbaoBAg8N8y1rzKb3661r34n9alNo8TPZNFp9DTyrtNmqtdn01HMjaXV1qMLxovOy6dIF37W9poQaD4pVuH1aOdO+XrU4pN6d7eQDHb53/C1hNfG6P+2m/gbrWmuckEKK+YBjLurfJbOXWdPWwINqCk2kg1qRd96ENCry+FNR0WJJ4on70UwdifW3rNxDW9lLS+SNnl5EE2aW0jnfPYSTW233sJRZDXmnxQS4BYwuBsSoMiQeFHh7mPHPUDa3ZFkG+5xAyjuU33bXsdP9xZsDrVH8WtMmo/fjhchT9e+cXn2qv0JAIaAQGF4IKAJveJ2XilYhoBBQCIQggDpVnd1BhUi04LEj7sQ6ZqqEaMURjXlEmug/Hq2ix5ZUG07pxrRC1IpKZE9uqGfnxD1RjIU6yKqtuPdDxxCMmz9FOp3WLI7d79XS7vdrDdcu+3opTZ07mnZs9tFHT1vHP4qp7qyUd2KBmpeW0o6XXuD/lDGvEOMai0ZQQlKQHHRL4HW2nWe415vvnhpG3Gk7JiaOo9sXzqJpU+wVgyBAMlI9jLTFPWtMrDlV34lYzFJpu14zJ4tAwIFMFIqqhDxGKh/urydo1vQmFiIF9dI3jqHRe4xTpDFXVlI+ZbOXtkWbxNO6qepVd05uIuCSvo2R1Hc1MWz8jrVmDRwmCBOk1aJf8tXplDjRmACVTV11Equbvn41XZ8rY45YkVTx6kAr8MXZoaacDPkaK4xkz1rVv5NFSvVTCCgEFALDEwFF4A3Pc1NRKwQUAgoBjgBql4E8ilaTJe7EekjBxMONnZIsWvG5mYenjLE6RY0DOMGdduXqej4V6t3NmGpOPBitpyUKhHmB07jwkFeUY63G2f3hdl73zmlzosJDHIXswbROk4q98bENAdWddm3orUBuIHUQpM+4S8ZzRd7WL/p4TTxRFw+KO7xkiDvt/EKF54TA6ysfRS0agxIZAk9vYGGmvrvwimNsoU9IyGOqwTxpEg/XjjCEMDJ/+dVT823XNOvw2wtCU3TRD6m0qIenVeJBccdJJw1uMuQd5nuzaRG92bwoJIQxrObd5W8fxx2F+03khSJ9VjvQV55LTecf4nq/2oEyqjsnC4m6dzDT4Ne7BYuH+0LUx+sbn8RIPON6eLh3shh5NtQ1Q53W3zTCLdokVbw70DpNOwZm0cZI9vrFNSZKNMiOUf0UAgoBhYBCYPggoAi84XNWKlKFgEJAIRCGQLTq4Dkl7kQgskqyoTy6aBVIjwZxp8XBrh7WxqeqDE0rZLCccc3RMt14H20cZuQd9u5XGvWHpIAKEk96MYuOzeuqac19vyNZB9rU4hJKSk2lvSw1tXuAYJEh8K4oS6WxaUHVnhGBd8tvplLVWntTEEHgYVvPPWGs4jPasr+umJcR8CxVszOooI02gSfWBonXt6mHk+28fttAATcQd4n5iZZps/r4/7nnOtrctTLw4+NXTaITqoLuwvr+hcnllJJo7Pi79ycnRnTpREt1pw+i+6qgWYxRuqxR0JzgZoRf3oMFYa7T6I/PWKijZGrP1VA91ST4v2RAq+gvoAoqiAgrMTiaZQ8ESZXJvsiBI2urRE1P/SaGQy3VSFJ8B5vIU/XvonKbqEkUAgoBhUDcIqAIvLg9GhWYQkAhoBCQQ6B2X0dIQXW5Uf5ebok7scZwePhCrHZkmRVm0SbuxFoF2V6untQqobRxuEmfFeOdEHiiLpdR2qwg7qC40xbtF+ugLt5Bl/rNCaLRRCrtPZsqLKfz5OSQNyc30EeQeHYutHryDhNoCTyQNah1t/AuOTMQLYG3YH4l4SXbhMkFSB2Rgh0LAk9cvwlsc43bu8hX7ycMrWrdWe0BZhZQ4QkSz4rA09e+08/bfuSYgDOtLG6iHz67QByhhICMGYyT+bUEnhjnJ/LY9cIIUKs6hnn/yuOp0npnUhnDGBB3Tyd9ZBhqeX8+HdU3MWIiL5LPQjMMI/mMxBcseZneEBWwk7MajL7RSPEdLCIP5wuVrWoKAYWAQkAhsH8ioAi8/fNc1a4UAgqBAwiBvc1d1M1USLINDxJIKUWaDcbh4TcSZ0EoOhpau02JKNm4YtnPTYxaJ0urgvhu47Z7KBwsAk8QiV/cvjywFWFuoK2Rpt2nr5sRjz4fdba10+6xm/lbReVlVFxRRlOP/JpbSPg4KPEW//sdeuWT8Bp8UNyl5jHizpMStkblSdOo/XBjAg1psyfmeUOUd2ICEHi9PU/yNEjs94lnR3LTCpmmJfDQ34kKT8wPFStPa2R18b7/8Nkyyxr2MUqhxT2Oex3qKFzD0WxCiXfTk8YxFzPTirSkdEb8GpO/iMUNgSfIoiRG/BilIT/70jNh25w8oZIqJ8qTq0YEnpgUKjs0s/p43r9mh6RPCpUlzgIKVrNzWJL4Ie1I2Gd7ROf3HuWaxJNJ3bcNwKKDUGSjS0t7j1RdUCfKxEhii2SsnYGFk7ljSeSp+ndOTkL1VQgoBBQCwxMBReANz3NTUSsEFAIKgQACsnXw8OCbzlQreGCKBnEnAsjN8FAXq+IebYIgmkdsR5Zp18IDFpQ9wAl7gutiJASn2T6EuQbOz6gNFoEHbDa9XkPb397J02RFmqXZnlsamjh5J1prbgO15TUG/g0ib+qRhzIyb0RER3jX716hFZ+uDcwhFHc4Hx6jRhU4eWIpXfeL03jftxtCjTXGMPMIbcqsNihBBu2tP4sR0P53ZGrfiTkSEsoYWRNMD3VD4Im5MhnB88bqxfTs54ssFV5GoM6ZciHNmXph4C1/0X1vVO9zs8Pc+s6TNGF5qHGD1rACsaDhvPSl5JwSeEJ151e3hRKSIO6efelZ02tu8oTJdP01N0hdk1YEHibAjrpamjg5qVXjpTFVKAg80cT15WGsH/q2sS9LOg2+bJEl78S8bkm8aJUTsAPRCZEXSXqqXRzReN+JgYWT9WJB5EHlmcN+H6umEFAIKAQUAvsvAorA23/PVu1MIaAQOEAQ6PL1kpWbaayIOwEvHqo9TL4Uz0YWoqi3XapdpCnFTi45O9zcmlggBicptHiABnm3492dIa6kRnvRk3fooyfwxLgTzpsbFRJv7TpjN1ykieEheML4Erru537yzknDNYEzwDXR1Hg9I5iq+HB5Ag+paqEkZSQEHtbeVFdF9793M7c0hVpLtgn1nVY1Codqs/Rs2Xll+qV/vJnSP95i2dVv9DBQf0/DeMnWwLNT3d157x20dn2Q7DULRpbEg4kFXkato6mROpqbAm/hGgxsiQlDs64opYy5oa7EQmUJUlyfNm+VNmsF6k9758ocT0ifwVa7yRB58e5k7sbAwsnBRJPIU/XvnCCv+ioEFAIKgeGJgCLwhue5qagVAgoBhUAIAjvrO8IQiTVxJxYcLFVHJEeOh7A0pk4wc4AcTOJO7MPOAKR1exNtWrLa8bZLjqqgkqPlUkCFK+qOd3bR+te2Wyq/jMg7BGdG4OG9C3/yHcfx6wesqa6l5174kvREHlR3lZNL6TuXHjlQb0wuRVTrWCrUlX29q6i7cyFfWpbA06vvMDZSAg9zbNxTRf/8702c8DKrPajF6HvH30IHFU8N1LN0k+796QvP047qatrJ0pdHTJxE5ZMmDfxpbk4hYvDUNFDOM19KnTNPzWaMBdRoXSPkXGitVHdY1E55pw9MlsQzUuE176mlni5jYg9ETGJJIvV7E8gzIZ3yrh4TsjTS+JHKDOIY6dItHT5+vzlV34lJj+ybQEf1T5TCXXSSqcPnaELJzn7TFg+/nvVpz6jBWc/KQMRC5SwZnmW3wVIIRoPIU/XvonHiag6FgEJAIRDfCCgCL77PR0WnEFAIKASkENDWwRss4k4bWCwKo0ttXLKTWaH0oSDuRMg4p3yWvlrXZEwIoJ8bJ1oZ9Z3+Gtn531204bUaUzRR8661Mag60na0IvCQShtpTTy7IxZmEJ5k45poWrxBnsDMoZmZh+gJA0Hiof7dU89bE6BG5B3WiQaBh3ler1pMr7N0WpwT9tfbG55+in4g7yaWTuOkkNm+rPADcffpC0tNu4DMO+cXv7I7Asp5ejl5dgTTqO0GcHLy0sOpuSjLtE6anepOrPHNq75ht1zY++fOPZfOnWvtGty3rod67mvnYz+pradSXxt1dPi/KPEkJvJXhkeTOszUd54y5m7MzquPlSRNHh9K4gmzGD1Rc0f3847jFwOcqvBARvlY8b6hKneQwdLZs9JQ77GXmtr9afgljMCrbeh0jUGsByIVXbaeXzRicUvkQQVflBteGzQaMak5FAIKAYWAQiB+EFAEXvychYpEIaAQUAi4RgBpgO1M3RGLGncyQQ32Q45MTPo+IwrSSCgVocjLZrWCjBQhbuZ2O0Ybk9kcTki8cfOnUObIHMtwtAo0KILw4JfBCKB3r//EdFwHM6uAYYVRsyLw0D8aKjwZfKFoRP0nfX00bU1D3CdW5AVIvK9WvkI33Wm+ohl5N21KId2+8OsyoUr1gRIPJN7mvblRqvUAACAASURBVFWUDMILZhADXjXjiqYS6t7NHH2wa5OK5373W664E62jt4safK3U2ResIZia6KWDKqfTFdfdZhuzExKv6byZlDCmgJ9XFzfS8avRRMM1is8yKCStzsup+k67iUf++qjtnrbes5eeeXYL5SX209dSjbunJydTRmYyU98x8o41rsQbMLrI/vFopsbL4D8XBJ6YRRDPd/U8zz+HrJxtzQJ1SuAhXbWFEWeDkVptFrOWoOpmhSfx+WP1JYbtIcW4QzQNLJyE6pTIU/XvnKCr+ioEFAIKgeGLgCLwhu/ZqcgVAgoBhUAAAX9B//5BKVpvBPtgpRlFcuRIYcPDK8gqqHuQytXNzDeGsiEm1CqzSx+zI/EyKrIJqbNW5J2Z2lCkQH/yf6upbVurIRwNe/Ya/rw7tYMayoxr1IkBg0XgCfIECh+hxvMyohbqNKdppTfc8hqtWr1dt+fUEMMKPSC3L5xF06aE1j6L1rUFRR7OaebomVSSNYlfL5GYVOjJu52d9SHEnT7uTnZ9/eCGu2lq1hj+Vtvy9/ifGYfMCukqQ+KBvPNV5AXGQZWVkephphTM1ZillmrrVdrdF7K174zOwY7A+2jJLvpoSS31dzLyrqWX8vxeHOGN8XYZBV7KzAs1DwABUzq/jNJOL+KKs7xMY7XtH5NeIjjqonGjD/nSh+SUwIundFXgk8MUgcIlGWY+TvYerXvLap5YGVg4iV2WyMvPSmFYDjDHThZQfRUCCgGFgEJgWCGgCLxhdVwqWIWAQkAhYI7AbpaGZPfAGyv87GrMxWpd2XmFKyf626mwZOeMRj8nykXUxGuraaZW9sKfaCDtQN5ZEXeizh366+tPiT3gwX7TV3tp06INhtsyI/D2le4iX5p1+ttgEngieJCVIEx6WLogDF6c3herVtfRjbf6SSqZFkvyTrs+7rNcti8YeOxlqdduCOgd1Wvp+d/fE5h2U/sumS1SweRiurRkDKUlhafppR9yXIDMQ008mFroU2rhOOsrzw0h78TCICkKs1MY8ZrIlcSNLMVZprlJnxXzXnf19VQ5sdJwmZrVLbTk1uC9cFIzq68IUxEtuQbObcBhF5PklaaQN82vwtO2iQ8dTOms/mYHI/GManCCwEPzK/f8RB5SpmWaGwJvT2P8pKviix988YQG528oguOJyBts0w+rM7cj8lT9O5k7RvVRCCgEFALDHwFF4A3/M1Q7UAgoBBQCHAFtHbzBhsSsxtxgx6FfT9TRghLLxx6Ke5jiTutEW/fkw7R38SNhYaZPZQ/d7FV00eUx28L2VVVUv76a3nn0Cc4NoFVMnUIjp02loxdcEPG62r3bkZbFrHYSHpx3VzPjDAMSz4jAkyHvsInBJPC0e0adO6+HOSTb1MYzAxok3hNL1jAlnrH6UIwbLPJOm/oM0kOo1to65cw7RLzaund2yjsxJq+jl7zs/vn6nMk0Lq3MEDJP6SjKPeNSx9etODMMhFINClkQWKiRZqfIioTAs1LgLbl1PdWsDqpROYEn0UrGpof0QirtlEcP4TUXcS1CIaVX/upNLEDU+B17gynTRks7NbGIBzWZfh9aB1onn1cSRxGVLvGoLNcTeVAXg/YtzjPJ8Y4KEmoShYBCQCGgEIgXBBSBFy8noeJQCCgEDngEmlvb6a8PPUfVG7bR4YdU0mXnz6HszNAHQiuQmthDIkiYoWpDVSvIaL9GD4OokQZyQKhgti78GbVXfWUJF0i80bf+IeqQLr7xZqqpWs0FPAnsicxIIXbBbTdxMs9p0xpU2BF3Ym6tEUTN6gba+e6ukHRavQOtLHmH+QeLwBN107p5TbXgfeB3wPTyFE2nZBfiB4mHl74tmF/JUmYLY5Y2K9bTElzYl7hW8HPUccQ1ZKasNLp2/vrd/+E/Rs27XV37bC8vQd6hIwi8vORMyvNkGY5zSuKZ1brTptVanVksUmj16jtsVJbA06rwkiDGY8R88V+mBs5MpKtjTmGMUEP19HTSR2F4gvyDY29jW7AmITrhc8ybnETn9x5FFVRge36iA9bOYoo3Mydu6Ymi2NEopVe4c8dDmQMnCukowiI1lSDyoFzEZwLUq6opBBQCCgGFwP6PgCLw9v8zVjtUCCgEhgkC37r6bjpi5mQ6+7Tj6NElr9GnX66lp++/VTp61I/a12LuaCo9kcuO8fCwoyWvoExASpZQ8WhVgjLknYAh2iSeIO8wP1fbsP/rERI8HfZOSTytSgsGAE5TR7Vk16bXd/Bodr9fSzCx2Ovx/7stT95ttKi8jE48/0yXV5TcMJwr3HwFcWe0Z+DMU08dkl1yEcSuF+rB4UytiFhh3oEUTZn0Q0HgyajvMthnSiZ7iQYCD81MhYf3tOm0ZsgI8rGfXfdaUlLbX5DKRqo10c+ticXkCZPp+mtuMAxP1L7TvilL4GXkeigr38MUdCwNlsGGz57iv0wJWwdnlpsJN1a/gcdTCR/SjoRQMrWVEc54GbWkfan03fQTaBRz8ZVtuI5gGNE84P4qOy6W/azcywWRh/UH0wVWu994+lLK7BxwnxSw+ndQmaumEFAIKAQUAvs/AorA2//PWO1QIaAQGAYI7KjdSyDwXn/id4Foz//2QjrpuEPpqm+dI7UDFECvZXXwhqqBbAAPNVQqQEF24KEYMRgROXggW/m3vxumzVrhVnjhN6OSTqsl77AeUp9QwN7KFfJnzy62PVIzgwrbgQYdRM08fRrj4v/9p+PpTjhvLhVXjHA8TmaAVmUJIxAZZ81I1XgycUWjj6jZaEVKateRIbtEf0HgydS+K2kNVfTKEHhYp+jK60xhgLouPcVf78zKYVZMIIgcfLYgFVV/X7tJo7Wqf2dE4I3t6qNxXfZ16UDeZbMXM1flLeOMIsqYa25sIpSGcE5+pPt92s7UeGj7WjtN6xsmN6RSxmflvN+owky65OsTpS65of581geJaxzEu50D7VARefGYcmx20CiBkAzWWDWFgEJAIaAQ2O8RUATefn/EaoMKAYVAvCEAsg6psmtZqmwWS5G949pv8z9PWfAL+ujFvwbChQLvhrvvp9c0pJ7dXuoau1itt6FxVtWnqNrFGq33nZBXUAm+PyfUOVM2jsqn35TtatgPNe+e+vUtYe95GIGH+nxm7eiLLjCtiec2jVJmI35yITlQs2tPzU565xl/wX2ZFkvyDmQEFCdQGcqQQNp441mNpyUl3ZhvCDVeF08jNq4hJxxo7Qg8vfoOGMoSeEYqPC0xbKa6s7qutGRXqyZFes26NXTXfXfKXJK8j5X6Du8bEXi5PcyJtt3+cxVOtFDhiWakvtMHGqxplkQPdLxHnzVuNyXvUjbmUebWAq7sE0SmLInHFX/sfulk10Y8NKcGEX7y3cP37SRl3O1encbndp1IxyUzIlTVv4sURTVeIaAQUAgMHwQUgTd8zkpFqhBQCOwnCEBZd87ps2j2sYfQ86+8z1NlH7zvWsLPvzn/FJ5CK9oVTJX3jQtO5X1lWmNrNyc1hqLhQbQoJ4X2MBJxMJoT4k7E07DkUdr9xEO2xfGN4o9UhffhE0/Rh08+FTa1HYGHAXoV3mAVfBfpqVA1IvVOlsQzI++qPU/z/U/yne/qEoELK+q+ySrTrBaJNzWeNv1ZW8PPDVCC7Gpu7+ZpmtomTCycEng5eel08GGj+FRWKbR4X0/gOVXdme3ZTGkoS+LZkXdY14jAw89lVHgg70Diodmp7/R7xD29r62D/vHaGmofUx/2GZW6KT8wBKngcKwVRheXzJpgm06Lz+YG9vtBRqnq5ppzOsatIhDXUlYa0o97TdOvncZi1D8eDSyM4kxnqdEoD6CaQkAhoBBQCBwYCCgC78A4Z7VLhYBCIE4QgOruxzf+byBVVvtvkHl/Yco8reIOSj2o877BiD2ZNtR18JDK40Y5JLM30ccNcSfG1j/1CE+fRbqx0xYpgfeHcy80XBIkGVQlVo6bgsADgYGi5XZ10Zzuzaq/IE1SGHmGVFXEWvXx5+z1Rdgw1LybeuShIWmzIO3Wef3EnbYV9FZSQe8UKTIvUmUa1v3PkkT2grNAaLvom4k0b8HgqHqMcDYzqYj0DIXiDfPoFUtIo7WrgadX4M34GnOZzfeb6sgSeJGq7sww0KZVir2BxENNvLXr1xoOO3fuuXTu3POkYL1vwXLDfoe29VKexfcjwoXWMyGd8q4eI7WWttOi/66j7fWtnJyDAYZdDUthdHFcZRkdNbHUcj0YRtQ1dTr+8mL3xj7avSn087JkXAKVHBRZymYkikC9E6tM7UenhxEPNV1lYs5j5B1+H6imEFAIKAQUAgcGAorAOzDOWe1SIaAQiBMEkD67k70OZ2YVaJ9+VU1vvvc5XfujS/i/kUZ7DlPgibp3qIv3wyvOpcMPniS1gx6WPjtYCjijgPJYTaMOVtsqFmlaovA7HmrdFjUHebdvySOE+m5OW6wIPJAcUNLYEXiCuLSq8ed0T076+/GXd3Pdm7iaE3f1SeEOrtp1QeQd0/lr01BkjBys9rF+dQL96dZky61OPTiBLrgsgUZO6HHlVOsER23fSPcms65QGqLOmkg93VG9lh66eyE1+FpNp9ASeFr1XWqil0akGLufdvr891X212bRiONOcFTrTmYv+j7+e8LDVMc4t6BhDYg80SZPqKTKiZWOpjdT4WESs3RaqO/yjsjhyjvvxAxH64nOdz8TJMX1KjurCfEZ8tvLjyI4kXf3GKfIWhlGGM0N4m7FG720R0feib7FjMSbcXKSayLPyIHWKWixJPKGg4EF8FL175xeNaq/QkAhoBAY3ggoAm94n5+KXiGgEBjmCOgJOhB8SJuF6q6ltZ1mMxMLQe7JbnU3M7KwU27IzuW0H2qm4WEymk6HQsWDP63cOGVirXvyYWp8+lFXaWSxJPAQu9mZ4SH1rreej0raqAxGdkQBlDMQMCJd24p0fCHDT0rLNCMSLxqEpRF5d1T6M4SXttX4KgmvU2+ZTxOn+tV4LdUraO/Lj1PHhlVhWyg4/WIqPONima0Z9nFqUmG1UHL1TvKs2xnSpeOsw0L+rVVRCpIHJN7/3XEtdfZ1G07vYSR3fkcvack7dNSr75CS2aozeNg25QJqzaqgygovTSyzJk9dgzgw0ImBh5O1lty6nmpWhxOcODu0bFZLDmQeWsWUTJp+eYVr4k7EpSXwxM+Eyg6qYSvh8MILD6OsdD/WOGNtqqysYYRYE+TdG/8INTAxw+7k7ya7IvGcEopWZyeIPKiTYY4SqSLPKV5Orqto9sWlWJqfFs0p1VwKAYWAQkAhEOcIKAIvzg9IhacQUAjsXwiAoCsvLeSbamYE3U9YOu1DrP6dvgmDC9HXCQpDWQdPpLYhjTbSFos6b22rvqSdt/7CFYE36pbfU8a0ma63pXegFRPh4TOR/Z8RgQcM8JB2DXOijZfaVYhb1DQzU/wsS73NVnmnB3Ji9/k8nVYYc/B7xMB11MkB/GRB0FCgwrOG5ufcYTk8dcIkGrPgPGpd8xVtfeZRS8IEE438yR2UPmG6dEjRSAUWi4G4S3vhszDyTrwPEk9P5AkVK1ScMLnYsHoF3fvwnZRa0xy2h86KbDorIzOQNosOZd58SktKCfRt7ewjveCrnRF3mxiBpyV3Z01OoaLs2Kb5IRU9h9VHRHNicrBr55dUu+tLWv75Q4F9lZbNpLIRM2njS8cGSDzcp1wtqyPSQN7NXzhB+hqw6mhE4In+nDhk/8P6RsT5tecdyrvqzxh9UTsylakVgYtdc0LeibmcknixIsii9TtjuBhYqPp3dlezel8hoBBQCOx/CCgCb/87U7UjhYBCIA4RQH2759hr9qyv0TfOn8Mj/OvDz1NWRho3rXj7/S94/Ts40or0WrfbgIkFSLyhaHjILWG1lmqZCtBti9ZDmNn66y482fQh2GxM+tSDafStf3C7JT7OzIUWep4kRj7oFTN4XgepN2LKFLrw9psjWjsWg8VDuJHjqRP1nTa2S/oWR62+n7bmnQx5J+JIT6ynJkZ6JKHEF87AxhNGlsSLpkkFyLvs3y+1PVbfxBHU8ot5Yf0ymYtvmjeJK7WWN2yimzc8QjnLagL9mo6p4H8f2eSji6qa+N9lyDv02zR5PrVljwxbczBIvHUb+mn79kTysMODO3EPu38mHEQ0cbxfNadvL79wNSfvrFpB17W09cNSTqTrSfSj5pfSUfPLbM9BtoMVgYc5ONk/oADUlwEQBJ7oBzV0ekoyTy8GiSejjG7bvZb++3hBSNpsYnIqJXpSLbeAdNo53wuS5Xb7jTVBJr5Iwp5BWpqlFZvFOVwMLEBY45xVUwgoBBQCCoEDBwFF4B04Z612qhBQCAwBAoK4AykHok6rqIP6DmmyaEbvuw0XDyt7mwbHCdYoRrduh7Em7kSs/etXUfV1P3VUzD1S9Z1Y20yFJ5xogQEe0rUqnwtuu4lGTpvq9nKI6Tgjgwsz0wqrQPzqJqITem6itHa5eo92GxPqOyfkXX9fHyX3tVBGyj6q78vmZ2GkutKunTZ+Go366Z2m4UTbpEKWvBMBmZF4epOLx3e8Q0/Vvhu2jx83ldOY9dtDlHeodSfq3WkHmJF36FOYlUhfr7QmguzO1Ox9EHcvv9pP6zcGe/AacpwEJxrPSLwzTk0IIfJkyDvMlswmOfvc/6WcguncoRYtmqSddk8wsdi217wuoegbuC4ZM8cuWYKJBV76Ju5PELaof2hW2gDE3d5Vz9Gu6naqWn6ZIczeLEZiWhB5TlR4bh1onV4fWrMTJ3VTYWChT0N2uvZg9C9kzsLYo2oKAYWAQkAhcOAgoAi8A+es1U4VAgqBQUbg+Vc/oB276sKIOxEGHGbR9MReNMIcyjp4uUwV0NndK21kASIBqUBQZUA1AwVhLGv4QbEAN9rNDz0gBXWkte+0i5ip8EDgoaHGlXbvQ0HetW9poo6tftWVthUcP8oULzxEQg0Ctc8XvYsNXWfNBiezzEoohEC0iDRaqYOx6SQIPKTNgsSTaX0+plxlwZSkb6O9vVnUTX5VkZ0az0yFFwuTiqzfLTVNmzXbo1E6reiLdOiMVA+rG+YzNfDo3rWVmv6zKDB9Y3u4UYIVeScGxkKFB/Luj381N6XhZ8carq+fXuUn8WTIO6S1CxUsZr/yu+/IXEIR9dlW10KL3lsvPYeoj/etEydRYbbfIdiooW6ll91ovYzt0xNZIO+2vXU3H7Z98yz+MmtWJN50ZmgxY45cmnQkDrTS4Gg6OiXyhoOBhap/5+ZKUGMUAgoBhcDwR0AReMP/DNUOFAIKAYVAGAL7Wro5iTYUzYmRhSA4ullBeBhUxJK4E1iIh7ltyz6hbTf93BKiaJJ3YiEtiQeFDBQ+aEj309a2GgrybvvDKxl5F14PTcRecPxIMiPysBe41FYlPkWf9zxpe+mBWMEYECti37Eg8K4uNFYUGQXY1+1XroLAa+lLo5b+YIF4KzWe3tQC9djymSNztK9rp+o77R73/eP7pmeCveWke3gqt5XyqG35e+TbtY3qNm3hc7Wxenet2RW0p/xo2/NGh8pyD39Fq9mRd2IdfnZQtjIm7oJzvqINa66xDAH3JCeVNTfkIV/7FuEV6yarwhNxjCrMpO+fNpXgNmyWLgpVNH4ncDXogNEF+jbvWhMg7zCfHYGHPmYknhMCT8QzGJ/32vPyOzJ7+O8ZszqJsarPF+3rJpWlwOMzRjWFgEJAIaAQOLAQUATegXXearcKAYXAAYIAXPjwID4UTRSTtzKyEPXAok1wyOxXX6cPzrTtVV/xFxrq3eFVdNHlMtO56oOHxK+ee4befuQJTtwlwcSCkQXgCyqmTqGjF1wQkjbbunUVtW6rClmrdNZFrtY2G2RH3olxaaOzaeTl5sYNm9KeIaTR4iHZqNi+SJcFmYL0P22LJwIPce3szQ+Dy0yNN+lPS/0ECUtX9DLTAFz/0SYoYFqBl5vW/PN51DNphOVQIwME7QDsb0tdL32+qTNo8NH9ISX4Pgybt9/DSD1vKLEX7TTa+/7SF5I2a4cLuPKC/8/eewDYVdVb478pd3pN75OQhDRKQlEpUSSPIAoSBATp+PD5HiD6fP4fUTAqUsL7fO8hKH4qIoggCBFQBAl/iiYUQUgo6QmpJJM6vd4p317nZs/sOXPKPu22+e3vu4bM7LPL2ufevLPu+q1V/iDVjH/Q/t5U3ovm8ZKhwsOcuiQeyLtLPnmksUwnlZk58RWfvyBs33nqB9Swu1+dqkPgwROvoGLMIKi9EHijhE/qvnr/Pqlu5+z2e6hOy4sTSnHzF0dR+/O5rU339+x/p4sU92MEGAFGILsQYAIvu86Td8MIMAKMgIFAqn3wxg0vpt0H2wadRiqJO3UxqSqRsvP5s/OEAnFXu+KxQeSd3EvZpDk07bIfBr7rdck7OZETiSc98FAaaybp1HJZq0Wf09Jfphl0Uyih9eR/1y3M/kViRSy3nYYV7TOmtyLw8HMrNd7cX/zZIO9QBg5SIIoWhMBzKqNV14q9JQIQEqmlMgBAqmVfW99C7+0QpcbdOymn/XHXbfYWXSjkb/2hFl/4mH2pp+tgSgdd9Z15zMqif6cZR7xn/NhIdD3cASS6EVqCm9amnXX2XUY6bTLaynV7CC+7Zud7ZyZhcf3IysGEGba7/tGrjATsnsNeejoEHsazUuHpEnjponDrv88TQR/40gtfOGRKgAX73yXjXchzMAKMACOQfggwgZd+Z8IrYgQYAUYgFARqD7X1q2RCGVF/EJiAq15LkriLd/dSo1AGhq1M0l9Zoqd5fV6v99NfKrOk6lAdo0gotgpieQNM5kHebX54idZU0y69hcpqjtLqa+508K876OBfd3q+dsIVR1HJ5ErL62QKbcKjK1EiiwfmLoeq7uHds+jk9u96XofdBTKF1msJbXXhXirIS5TSmgm8bXkjaVv+KON3p3Ws6fPGAwt0wn3PRV4G7sf/TuKjS+DJ/lJJCz4LHo3tnShzj9O+hm5asWazFnknx5IkXpgltH8WoRUIrvDaRpaeTpUVotxb3Logk+S9aZDNVpJRZYIgZbT76tbS/vq1JP8cWTWbRlXPJvmn3T6sSDyrwArz9QiuQAptp3jT5Yg3X50ooVXb/vefMoIr0GR4Dj6XX33xO66Q5hdXEV5qu/ROvXJOfNYVHSaHXSdKQgczkVco1pfuARbsf5eEG4OnYAQYAUYgTRFgAi9ND4aXxQgwAoxAUAQONHYYHlypaFLFEBeJuDAsx3MxHoqkmicVa1LnTKbKQkd1KMvfZNmxF/JO7mvud/7gC1av6js5iZMf3oHctfR68a0kCTxcg3JZB3ETndR2M43ome1rD3YXQYXnhcDL62roU99JDzyQdq8UzqHth4k7da7J3fvo9Pha+tTnP0NVZ15kGwIR1qaCKPB0SmjN65SqO0jT1JCLJ1++1fOWeku/GaoHXlACr1IQeDKoApuRJexOG/OrwHv5nVsM8s6ugcT79HF6ZL0X4BEoBK80EJNQhUIdKptK4OFnILJyBTP0/tuXUv0h+8Aa9DUTeKOOyKEzvqrnbQh1JxoUb+nUJJGHfxuQ2Auy2oXPTdnyQTIOryhM2fw8MSPACDACjEDqEGACL3XY88yMACPACESKQCp98CRphQ2aHxwj3bTm4FaKN81LtbvJUjZdnz88bCNEAGWLG35zs23ZrN0C/JbTbrzlVe09mTseueQUy2uB7+slt9Keng+MkAo0pyTXKMg7zLlpbQ7t+fGd2im0o0t3UU9HovQbKbQb88bRg6WfdsXn2HmzaOnVJxlqQztzfNdBNDoEIfCcQizMU0ORBZWqVN2B6KoQ9yf2t2rDS/TuxleEd6PGgpUu8MT7wqkLvF3k0NsvgVcSe5DGjXiQhlejdLRfdYc9o6lltebp/XjguZF3co4wSTx5frKcG3/HFyloUhltJvDkOkBkuanwzAServoOcyQ7gdbLDaeGz4D4bGiNDyA9vYwVZV/2v4sSXR6bEWAEGIH0RoAJvPQ+H14dI8AIMAK+EeiIdxtG+sls0uMtofqglBqVO+3brHgLEyPV5w7lwu0eVJAwV2//aC2984tv+1J/+FHhhUngmUMc9tIaQ4knGzgSqHzUgIuoyDs5Z9um9QaJ59QKi3qpopqoSITOtu/YTB29+fR2zlQt8i63sJgKRo2nGeMq6HsXHCU8tAoGqNXCvLcw1rB/+b+eh/RSPitVd1aJpnjfvLfxYdp7cCsdavbG4I0ZXkMnHXO557XbXeCXwCvMW001Y75JFeWitNs0OCg83MNW5bRjxs6lz55zl6f165J3ctAwSDx8eVImVG5QkIGAVRvOD+QPgnO2vPE47X3vScv9NNRNojWrLjNUeVYqNJXA+6d/yafRU0WtvGZLVQKtzvKAXUx809AoiDtZQo77wS7dV2fMKPqw/10UqPKYjAAjwAhkBgJM4GXGOfEqGQFGgBHwhYBVkISvgVwusgpnSFVQhO7+zMmMutfZ9bMLqPA67l4RWrH/tcdcS06txkUyrdd0WisCr7njILWIl7mVFg6nMvGSTVXgSeLHSnGJYIuDeWvFK5F4OS5vDo2ho2hC07m+iEqvmPbsXE+HfrGUGusSKivZQNwJ/o0qBXknW+/IGtr65ir6QcUXXaeR5J3s+J+fny3KRCuEyqggMjVe/obdVPHff3Rdm9pBR31nVm3ZTfDym7cbe4OysqFVj8QTvBGVFefSpz/m7q/mZWPXfVNvfjmmoQIVrN1Zp32T9uxZbTuVQTTLcIfDLJ/X8ll43b2y6hYv2zH6njZvieGN56eh/BPllYeE352Tzyi+KCgtitGKn188KAlanVeGWpiJPIRYHHtWKR1zhkiq8dhSnUDrtFzgFxc3tlpq7JTu63HroXTHvQkM8UUIN0aAEWAEGIGhhwATeEPvzHnHjAAjMIQQiNoHTyWtzOmbfPtEqAAAIABJREFUqQiK8HK0UIIAnzB8jhIPxOEkkCJ1Fi+nklO7fQYl8Dq7WqmudZcrjNUlE6ggv4RA4Mlyaah9ULatG1CSMNnvTzrtfv8gdX8wmDQs+NKRruvR6QASr/vxpY5dcybMpPwvLqYnV26ix5/7u2NfM3mHzlDh3ShIPLSigtzI1HheSDwd7ztJvkKx63Z+IPDQQB9Aqdba0SNID3uoimI5AosE2RA2gXfXT3to0xb30zdSg0E6ivVOO4LoovPeo+ee+YbrhbKs9uxzf0zDRx7j2l/t4FV9J6/1o8LTJV/V9QGT+nV/pH1ChYeyYSd/ShB5Rkiv+J+SUTPo5C9bl867AZQuCbR268S/CXXNnSJsZ3A4SroQeex/53aX8e8ZAUaAEchuBJjAy+7z5d0xAozAEEcAaqgmUQ4UdsODGMgXkFYgbVqFObr5wR+kAB4K082sXGJRXS5KHQU+QYI1dAIqrLBf0ZMoXVvRk0iBnJ+76PCf5xnkHV5oiZJTQTwIgkQnb9MPgSdDLHTJO7mfGZ87hWZ8PpF86zdZGA/FRZsb6OB9a6jzvQO2t2nRbSdR3tH9yr8g93P3609Rj3ipDcRd7kmLKHfiTOPHd/5xLW3Y3UjdTYeop72duttb+7rnVwwjkHe5qLe1aPf/6yf6fgrSIyo1Hkg8eOLFNu62XEf8yHHU9K3PO0Llh/iRBJ4cWKrxOrt6qa0zcZdCcYcSREncyb5hE3gbN/fSj+91fmeAuDMSkA+L9b5+bQ4dOU14I+5eTavefoBqHZR4WPdxx19FCxd8tc8PUJfw//1LF/u+Tb94+qPa1zqVzOoMsv3FpdRxYIPByBr+fw5wAsc5Z3+XqsbNGpAyrjMP+qRbAq153TrqQOltin/vUpFWWy5Ugvi3lRsjwAgwAozA0ESACbyhee68a0aAERgiCEThgyfVZm7hDHhYKxYEX50o50rHFoRglGbncaHU8EJebe9dRw93O6vAFrw2hQpXvtdPAon/yhOVam4prrjAD4HXuq2Bdv3mA9rbuNHTMR26eg1dfNz/BjJ5h+qu/abXjXJFkANO6q8wSTy3jf7zz9/o90JzkiZZDKQSePLXUavxzCQeyLuuGeOo7YP3jJfaio86hgpGj6bqmgmGSlBHdadev2rdb6m+acegnRuKUdFkaIkVxmETeJjDjsRL+NklVILyCCV5N2A/gsQDkWdu8LybJ8i7sePmGr9KKEbxhUVcK204GQQeSj79nKG615a96+nAB09R2/71fWWZ3RYKNFwz6fTFVDp65mF1acxIOUfQgy6piS98QPjii6V0a/hMrxal7/sbOrSWBuK0UuDf3tlt7MdNuao1qEYn9r/TAIm7MAKMACOQxQgwgZfFh8tbYwQYAUYAiorauvZQgPCqNpPqnn31eg9EoSzSwyCGGkSEbdSLoAndFsTnToe8M4iCHc30iUdbqYAGKrxA4kGG50SQ+AmxwJzrf/EK7d+4VRcGWveJ5dQwbC+dPOVKOkW8nNrj61cN+vXsEWNo5h6RcirIO9kSZY4IELAv54uaxJPn+8W7VlqW0ekAZEXg4boo1XjmdcX37aWml16wXC7WkS9YlIq5c6l3+hydLQ3os/WjFbRNvKya0xlOHj+fpohXFA0k3rPP9/aV0yY87PpVd9OnEn32zITyLkiT9wfSomWaq914URJ4fpSTbvuWqbTGGcogj8PMZ8momVSzYPGAIdAPhBxIzdaOLkNp7UbkIYG2Q5B+qsec27qS9Xs1wEJ3TokBQkOaxf51MNAd264fvFvZ/y4oinw9I8AIMAKZiwATeJl7drxyRoARYAS0EAjqg+eVuFMXNaqq0FA0uD3YaW0k5E4yZVAnqRcPtHhYhdrFKqTBbWm65J0cZ/rvtlDNzvJBJJ5TSa0f9Z2c7/+8dDrNfuMMqjg0xm0rtPbjy6lx+F6j38SqYw0VnlVbc2AP3fLqc7bjfWVZAc09UErF+bEBfQzfMRCVNjdN6R/Pdl2jnw6yFBGKmgv/d6WfIYxr7Ag8OWCUajzM0SiIuy5B4Fk1YAt4oRxFyx81mipOP8PzXu1UeHIgSaCBbJYVmVGo78wL//BDot0f5RkEUefhPYK8C0rcmeeRaa5xUZdrp0CLisCT9ykIoyiIMBB5xr0hSErYJAw/ahE1OyjmQGKVF8eMvsDCaU3pnEBrFWCh+8bwQ2bqjq32Y/87P6jxNYwAI8AIZBcCTOBl13nybhgBRoARGIQAfHr8+NBJ4g6lQfXNcV8lQvCZaxMPmu1CdZGOTSeJdsfaBioVD6cQo6AkuWx4IVWNKvK0nd9230E7etdrXwMV3lGP7qZhNHbQNQmFzOCSWr/qO0wAAg+t4uBomv33hZbrbBxWS7umv9dH3slO/9/pLw3q70be4YKb/ztRczm2rHIQiSdTQHHvmS25wlbhgdSCMghlg7IU7ul/7CK8/DQ3Ag9jRqXGs1PeSdUd7mFzqR9KavHy0uoat9Pq9Q87XqKWsM6deRlVlk/yMoXnvijthxosKmLLakEyzdWqrHbN1icIL69tzpQLCC+rFkbJrJf14L5BmWiBUCvj3wAnv1D5PsL4dupEnc9bL+sLs69TgIXuPFETefgSqbJ04BceumvjfowAI8AIMALZgQATeNlxjrwLRoARYARsEUA66KEm/TJWmbaHBzK3hzY32NPZ8whrd3poe/8VUYZ4IKEetFKDHXPaaC0iz6v6TmJqV0orf6+W1E679BYqq0kESvhpksCT14LIq6wbLXztEyWtIO7smpnA0yHvPvlaDn3y9f5yRisSL0EAYX54mPXTeDGRShtWMq1MXzWrKteLAIv/EkEWXtu5J0wgvHRb2Go8K/WdWXVntbZhF1+mu+S+fiDxUEpr5YenDnbSsVfQxFFTBTkaN4Igwm6yrBXjJtOLTO5DklwxkdyBL0tUksuPCs8qwEItma3fuJa6d26iztf/3AdlwUmfo7yJ08UrnMRm8xl5SWBV+6pf/CT2UEj76sOxdAjzPsIZjq4qCs1uQt6TsGjAfd/S7hDT7GEjw8oLDRU4N0aAEWAEGIGhiwATeEP37HnnjAAjMEQQ0PXBC+LvZgelfJjTKVNNxXFYJdE27GunNX/bZyi/3IzJdUg8JM7KtFmve5y3czpNf7WDmnessby0+oij6MR/vdNzEIF5MDOBhxTRBHHpvmIzgXfR0/e7XmQm8IpEGe04ocSzagi4SPiZJRYTBoEnkyRBKEGdanXOMonWdTNKBx31nXm8sNR4ZvUdMJMEqNt9XC7KaGOinNZPgydevSDzVCKvSqjtqipq+jzvVHWWXzWv1dpkOWnCgy0cksQPBrhGftbhNpXBNvvq1tIrq27RHvK0eUtoVPXsAf3VktlDv/kRde/aZDte3oTpVHAyyLzoiDyoVfG+ATHlZI0gQx6QUI6+hUicFkpmnH+6NS92Cl7WLsfF/d8oyouDEtjsf+cFfe7LCDACjEB2IsAEXnaeK++KEWAEGIEBCOwXQRJxm/SDKIg7OXnYyoawjxUKLDQodyQOb72wh2o/atH27XMj8YIQePNzF9H83POoefsHg0g8eN5J4qBKpCfqpmNaYSgJPGF7ZZR3CmsvrWb2wNNR32FgM4GHnx1RNcJ2TjUcIe9i/wo89V7XSV/1QuL95+dn08xxFVq4WXUKqsZTE2d1VHfqGvyU0Zr3ULytftC22iZXDfiZU8mpF+Ck71rQBFYvc+r2lXsEqQjvON1SWivyTi2Zbf7d/ziSdwPO84vfiIzEwzwykdctvEItKe0WMdoyuVwXy2T1g1JckmxRzOlFwWg3f0z4JowUnrLcGAFGgBFgBIY2AkzgDe3z590zAozAEEGgvrlTJAUOVKhESdypsIbhLRTVMSGJtlSQeHiwhGLkvTcP0MbVhzxP98kv1theEwaB57YgqXCKd8HHzVkZYzXWmzt+Qys/fMAgLQ8L3dymNH5/0bz/oUnVc/v6InH2iQ2DU2fNg9XsJLr89wNLwaqLSggvp2aEiVw+k3oumKpNsMrx1JAKELa6zc0Pb4Yg7VA2G4S8k2sJosYDgdex5j1t1Z26/yAEXvnqWoo12JdFxiuLqGlufziKLDlFkitKTrt0ZJ7KYqNIYNW9F3T7qQQjFGe79n9gEHn76weXZY+smm143qnKO/Me2x77X23yTq6x7D/u1V2ur37qHt2CfdB3hCifxZ9hKNF8LdjhomSl4wYh8tj/LuxT5/EYAUaAEchMBJjAy8xz41UzAowAI+AJAdUHTyXukBgI0/coU2LTOcgCCrxyYdIOpQxKKV9+dJsnXGXnmjmVVDNnoNpI/i4ZBJ6cC4odJBUeaup0Lf/FNSAwK4QpOgjMm/4039PerRJodQk8TCRDLOSkOgQe+lb9n1Op6mOjB/mN2S3eKqTC00ZFZ3jibRAv+SeuB2kH8i4M4s68Hq9qPOyxa71Qab67ui9h1sse/RJ4buSdXIOZxMPP1TJmXdJZehbi/vZK/HnBI6y+VmW1arCFVViFOWW2e+dGavv9XZ6XBF88lNNG3XTCK7AGfJGDf2uQVotmF3QR9Xqtxk92Oq6891HarotDtVBZ497gxggwAowAIzC0EWACb2ifP++eEWAEhggCXaJ8FiWDeHjCQ4CT91fYkERdnuRnvTJhF8RViSif2n2wzRjmb7/f7mc4qhxZSMd+ul9lZB7k9q4rfY37nfwHPV8nyR+QIiBorZpVKemOutX02Kpvas1nRd7hQi8EnrmMVofAyz1qOBXffhLBW2qYSDh28+KyC6nQ2mSKO+mq8eS9XL/9I6p97i++Vu2HwFPJu3hvHcVpcAltjKoollNtrMmKxOsvsUx4o9mlnEpFGt6vDcJLLMovHHwB6HKRWlaLLwrs1m+VMtv52p8HBFZ4WV/UKjx1LSClkJAKr0rpAaj+Xk2glQRWXKgvrfp62WPQvqm0eZA+ge2d8Am09uKU+2P/u6AnzdczAowAI5AdCDCBlx3nyLtgBBgBRsAVgV7x1AhCx+1BwXUgjx3SKchCqkUQjCBVasMrCgw115b36mj7mgaPu+vvHnYZrfS/87Mg7BMEV4cgPFCypjYnUkuHxAN5d/KUKweUzsrxvRB4uObyx3KoZpfIus3tojKR2FgaK6CSPOswC/Qvuu0kyjt6uDGdLOGzUhzqhFT4wTUV19j5xlmRsIce/a2vJXpNoc0XSaIV79aKkJM26qBa1zkLaQzl5RRT47FjqEukfZqbNPtH+TbK/VWCC/svKcw31Ft2hLTrAtKgg7msViUrncqCm//7Wt+rTyaBJxdpRVbaJdDqEpu+AdC4MKoAC42p+z7H8CVXmXjJwA8zwZsvPs9HVQ9+3+jOwf0YAUaAEWAEsgcBJvCy5yx5J4wAI8AIOCIAkgrqj1S0ccOL+1RuqZjfye9PlvhuEN53URF42PNvu++gHb3rtbY/KWcmXZb3ba2+Tp3UktoCUS4L8k5Hffnq1gdpp1Dk7ax/t294J+JOdtINsZD9x096hxbdN5bGbKqgwrxEoAhaLKeQSnIrKJbb/9CqknfqnqXyB4b62Bv2iL3qhFQEBjhJA5hTXOVZSkJeLkMNstBdml/1XW59nRZ5J9cBEq9z8lgyB1uo61TJSnmW8MoLM7lWF5eo+qk+aNgXzhLkjR1BmWkEHnBTwysQrtMtlHZ2CbTmvslOE04XhbiKgzkchP3vono38riMACPACGQeAkzgZd6Z8YoZAUaAEfCFAL7dh7olFU2q3JLtWwXiQ5YNg7y0ejjEw5HoZigT/ZbQOnngSby3966jFT1PaZF4fkpn7c4ViZEgCND2N3RoeeMFuUd+sPJZWnvQWZVVXFJHE2r6wy5OWj6FjvrzuEHTgsirnjvLKJt1arIMDn1wn5tVh0H2k07XgpCVHmJ2Z9n40gvUtW+v1rLzR42mitPP0Oqrdhr2123U2rvV83UlOVPo0KcmO14n1WhQyWbzWcryyVzx4bNPKBrtPhszkcCTByyJZySotsfx789ANbB6I6Av/DhjhwlbKBRb1+6mtnV7Btwvw88/3vN953RBsgIsdBdtReRVlbL/nS5+3I8RYAQYgWxHgAm8bD9h3h8jwAhkFQIf1R6gex94inaLP0W1Gd22+BoaP2aE1h7xQHRAEDipaCAe4sKHL5klcKrPnVPZsCy3hGIrihALM95OoRZBymbN8wwkL7sN4seqpDaK++Gip++3HdZM3hXl59O4skTZbNU6kUS7vj+Jdut5B2hMbBp9tvprtuPJcuG4uL/hv4VySxDVdn5qUew3GWPKcAOcYSxfMM6i/d9/PE2PbxjsezetOZ/O6a2hGbnDbJfml7zDgOWvrLL0vHPDAZ54TafNc+wmfeDgjQZCBySek2+c25zp+Hu1ZDZHMDbwrbTzAPSTQCv3nIoSWhVvNZBDEs9uakp8HtOHe2n9zU+KLxvI0i9w+BeOp7CIvGQHWOjej1I1XiSsBdBA9HJjBBgBRoARYASYwON7gBFgBBiBDELgqm8spQXzj6fTT5lHDz2xnF5a+Q49cd8tVFHWT3o4bWdvXXvkCiyr+ZF2igeRevFQHnXTJe7UdUifrdV/32944XltTv53dmNBkSdLalEyW5Mzy+u0tv0lBmrKsPTgAvnj9hAddCFOpbTTZ73UN7xK3jnNeVbV9TS2YPqgLlZ+fqr/n266adD9Rnm9fJBXS0nXHNhET215ntYc3Ew9grSEd5y59cbjNL2jmL6VM5AwA3EXEy+UzvptRa+87OtS8SlAradZqymtfOCcfON8LSANLjKnzGJJ0ocN/21+b/oNscibMJ2KL/r3lO1YvjfVUnb5ueQUPrPz1j8ZqjucPbg83Nsg8syteNZYmnjzOYH2l8oAC92FFwoQhosEX26MACPACDACjAAQYAKP7wNGgBFgBDIEAajvQOC98OiP+lZ809L7qFyQd4uvv0RrFwhuQOJdshseUKvLCowSzqiaVQmWl7lksunfntlF+3a3al96zGmjqWpUehiMq2o0O9Wh9BlLhkrNXE47bMRWGj4yUXpZXVQsXnrEs1mFB0IY6iwnPz+p5MI9n+zSbe2bx6WjJHsSnlj979sv/unrfVeC2EODz5hVmz18Gn3/ZHsFo5+1+iXwMFf7aZ8eNKUke+xUaNLnEOrDTCZlrVJmVTASBBdUhzjv/rRaP2W0xV/8BuVNPNLP8Xq6Ju/DOBW+2Eb5W/v9VfE5lDO9gJo+WUjxKf3elhjYXCLaLKwLZDu47G06+Ie3B8yfK0i8PHFRt0h26DEReUFJvHQKWLIDHcrFKvFvJzdGgBFgBBgBRsD4d1SkElr/X3yMDyPACDACjEDKEVh48bfouqsW0bmfOZUam1sJf3/jmXv71gVSDz9bLkg9nVJaPBQizCIVbYxI0dsrvJ7C/lfHKaDC6z4lAbby2V209yN3Ei8dyLt1K5YZD8XwmTrprIsNLz+3UmWn1EuvmOn0hyJv7YFaWt/7OxpW2UzF+TGdywb0+fKoH5NV8qrTQLI82s7/0PMiknSBlepOTv391+4RHoObB5Ic4vxRYmenxvveSdfTnBGDFYx+t3Ng649ownbvXmS7at6mEVO+1Tet9EgD+aiTjm2XyOt3H8m6zsv7rZ/gyjO8HEFSd+/cSG2/v0t7ucki70p+2TiAuMMC8UUIVHO4F9G6BIHX+pWKQWvHPiuFtQJCPCRxu/HSX9juUXy8Ca9SQeSZFKcTbjqbSmYP9s/UAStdAiyc1lopvqjAOrkxAowAI8AIMAJAgAk8vg8YAUaAEUhTBEDYXXDNEmN1IOjQrhYKvEWCzAOhJ9sNN99NC049bsDP7LaUSh88BFk0tXaF6k0G5Q5Kc6EqBAEQRpNle9vX1NP7bx2wHLJyZCHVzKlKmfJu//a1tH7lMjqwY51B3oEgkA/NIybNopmnnk8ja2Y7wiEfoJOZ8nn/vn7lmNezum7iT4wwDq9njX1CwQILqahLh73uyaq/neoOfVE6+4PXf2I7jZ0aL2wV3oeH/oNmv3e25+2+8clf0tzcR4zrrEpJdQY0J/KC0EnnFtY+O7dv0CLxUkXeyc8hnIf5Sxo7Eg/nJlVwex57i7Y//HfXL3jyE5Zwff54QVR46RZgYXUfj6oqFKSoYC+5MQKMACPACDACAgEm8Pg2YAQYAUYgTRFYv3kHPbTsBcPFG+q6a4US7+m/rKSfihALSehh6Qi1QMPvdVrtoTZLzyyda4P0QfkYHu6ghgra/PjceZ0zofbJp3de3zfAN7ByZFHKiDvsYcXDPzSIOzSoXfCwbEVinHrJza4kHsaQ/n9QZkYd/OCXwMsX7NsNNT/VUmnZnbNUbzW2oozcwlTL6w0Scn8n1Z2c6vENz9HjGweHVqhLAVFppcb7/Tk/Dm3Fm3t+SFXbiz2p8NYe8wz1VFXRjPwlokw0XwRx5BLKm/0ScAh+qCgpMMpN1TLM0DYZwkBWPnBeh03ssz/Mo+PVP1Pn638eNAw87wpO/lxSymZRMouXbLjfcN85lap3LCgmvOzapst+4eh5p16XIAsTP+kSleVHPvwvXmE1+o+qKqKDjdEnc/tanLgImI4ZZo+Z33H5OkaAEWAEGIHMRYAJvMw9O145I8AIZDkCTz3/Ku3es99Q1kF59+u7FhtEntn3Dr54V1x4phFsodNS5YMH37JiQYjViYd2v016n3UaXlhdvh/+dedPlGAK5WBb3LUsVXfMIP0keWd4TImHOyu1izq+Lokn/f+iLjX1SuChZA4PsfC/unpkcAIqXQMuQEjD6wqJq07lzzoEnjx/sxrvwiM/QxfOOCvI7dd3bW3vMsJr9rufo4qGgeWLHUIN22kiSFdOXEbVRzfR7IIlVF18NDWK9y+It/LeYMma6RpyIUtmQRSjDDZoU33j5GcRymq7d24ShN30pJB26h4qvnOo76/YK5oOEdt4u30qsiyfdfK8M+OIqTH/sU9c69kbMRMCLNj/Lug7h69nBBgBRiD7EGACL/vOlHfECDACWYIAUmbLy0tp0ZmnGKQd/O5mTa+hf7vyXELZ7G7xdzSU1Oqq79A/VT54kjzxE2Shep/ZGd1Hdexe/KuiWgPGRdnsa4/eZhB3vTbJo1bzn/ftRMmiW1NLTUHyhu1ViPlXtTwnXs4KMvQDJdBXFnx4IfDAC6vJMIFk30vm9cv7Gj/XIaTV8AodLFQ13vnTwyPwMDdUeM20jirqxwol3nFUuH80NTcLFacg52Tb0LaF/li/nDa2b6FcqqRvXPFLmjLhqEFLLxMq0iBknvQ6dEo31cErjD5+SmZbu+qotbu+b/qSvCoqya8etBy1fBiK2VSEs6jqO7PfnRt+LdeUU/cR1v6XZv+7hOddolTWrUr6uD9cKwhw4bVnCv9wWk8mBFiw/53bHcW/ZwQYAUZg6CHABN7QO3PeMSPACKQ5AvC+qxDJskt/8gh9bN4sampqMcpmQeA9IFR4J86daewAf0cCLfp6aR3xblE25F8F52Uuc1/4+YDA0yWHwgyoCLJuSW6BOGsQihrd9QeZU70WysO/PXwr1W5do6V0Ua+FH96s+edrL0WWDkeR3rqncxM9V2/v4YZFInESeHcpT+3zSj9D80r9q8f2rtlO+9buGIDB8V/6lFBXxgxCW0141QYqYEdZutws5ncLHZFTeVHgqcuDGu+yOZ+jz09Z6Pn+sdtmc+9a2tx7q/Hr7Tua6O9P9dKMoql93f8kiLtEK6A8GilI2XzxyqVrL72DptUcM2jYAkHiDQ+gyFNVaqkqk/ZaMnugYysd6NhmeydNKplrSeSlkrAEgVf0UptBsLspgM0bcyqjtQuwMHveWYGFElo1FEMnyCcTAixGVBYaHoHcGAFGgBFgBBgBiQATeHwvMAKMACOQJgiAkIOfHbzvlt13i6Gye3P1eiOgAgo76XV32+JrAq84VT541eUF1CJKX3W81qIIqAgKnNcH9KDzqQTmz2/UJ+HUeRFqMf/S73paSpQltc/W3UO18YEpqlic4Wsl/qdHsKNmxY1f9R2Iu/efWDGIvJNgHHPhfDr1ytMpmUEeXpNX1YPzS+BhjD9f+BPhdwjCMh4aYQkS7+87HqSf/e6PNvcXyLtRgrjLM8g72aIi8TB+KkIu/JTM7mhZNUB1h7W3NLZRS1O/txx+1rxHlFVvrKaPn3EMTZg6ug9DlbAM80zdPijKXmmnAkHi+VH/ORF4B5e9TQf/8Lbl9H2ed4Lk7TLZV5pDLKSyDgM5hSaBvG8XJevtimLUbe/J/D373yUTbZ6LEWAEGIHMQYAJvMw5K14pI8AIZCkCkrh7S5B11wmiTibM4u/jhOcdfO/Q0A9N/j0IHAeEcbda6hZkLC/XggAzHqwcEmOTEVDhZc3mvon1xUSiaacWEel3LkkWSjXJk3dc4nco0i2jVSfAQ/MwQbiCTMNew1Qdmkk8hFQYYRwWk5xVdT2NLZjuee8g71685WHX60bNnkTn3nGlQW5F7XXoR3WnbsAthdZuszKFNgpy6/ZHbqT3d/yNBBVCPeIlW36OMN/vrRLEXdGgZU2ddDRdd9lSy+UGLaeVg8rQkqjJLT8ls2byrrNDkKqCvIt3Wgf81K6KU+3qLoPEw0tt6pmGnfJt/jyoFGEaeS+0UvyZJtf3lVUHJwKvde1u2nXbM47jSs87fE70HCbyJtx0NpXMHujDiEGkShEqQav06XQPsEC6Oj5/uTECjAAjwAgwAgP+Pe4VjSFhBBgBRoARSA0CIOmgrIOPnSTukrESkEJNIZire12rk++QfOBKVkCF17Wr/aNUqNkRmMkm8OR+JZEYdkktSLx9XcIb7XBIhfn/GhkTmybKZj8TKXkn9wgS78wfXG6U1HZ3h18mHUR1Z75P/ajwvnfS9TRnRD8JGha5tW7He3THI4sHLDGhlsoxSqDjDv8Xpp0KD4ON7QkWbiEXJMsqobCMgtzyo8iF3908nlv3AAAgAElEQVSO1tUDMNv3UX8ohN3n0ubnOqi5tseSxFMJqyh8AFUf0E5B3qkJtF4+R5088DCOkwpPnUcGXUB9N+bbZzsuQd7rqj9eJgRYsP+dlzuL+zICjAAjMHQQYAXe0Dlr3ikjwAgwAn0IpMoHz+rBKV187rzeHpKUiXf1hpI0ifEqSmMENRrIMnOqY6oIPEkO4IEy8RDc7RWqQf0lSbm5cT1taVpPezo395XVgrQDeedHdScneuSi2z2v8egL5tPRoqRWegCGFXARVHVntZHvv3YPrT24mc5cNTh5evOYPbRlbG3fZWbyTv4iDDXekysfJrxkyxX3LghZlFfiLjFVOw7YypnzL6Ez519qeU7DxIWFRpRJOC1szzg/JbNyJ2b1Xd3+Rlvlnbp7qcLDz77w1TMGlNPKflGU1QI783tfTaH1ckJOKbRynJ23/ona1u1xHbZEkHfH/tf54n7LIQR6ONkymHHBZ3apUIMHSUR3XWDADux/FxBAvpwRYAQYgSxFgAm8LD1Y3hYjwAgwAk4I9Ah1TG1df7lbMtEaKYy5QVChQcFSIAIadEzHk7lGL3Mh0bRQ7MGKdNMZB2QADNWLCpxx8EvgeQ2xsFuzqiLzG+ShkrUIUjGTlDp4ufV5//EVhu+dn3bJY98xLlMJn0afSlVJ8kShKM17uo32Pbyd2rs6LLcJEu+nZz1HduSdelEQNZ5K4JkTSYMQeGGV0ar77Cdx8oySSh0fTitw/ZTMquOsb3y5768ona0/oF+OuvrXCX+88UeMpvP/9QzbWzysslo7haGaRKv7PnNT36njuCnxhn/heBp+/vF979XykoQ1g1WprDqu/JKkWJSn4ssI9E/Hxv536XgqvCZGgBFgBNIDASbw0uMceBWMACPACCQdgVT54CHIQnoZIX0TKZyZbubgN7lVKtF0cFi3YhmtX7nM831y6iU308ia2Z6vs7vAT9kgxpLER1gqPrv1BSHwFiy5lEbPqTGGBuEDr0M/5KzZvzA08MVAsTsbKXdDwiutravdIPHq2hv7pijKL6Ri8ao8djjFb6zQmtqvGg8E3tOvPZIogxaqO7ViNt0IPAkEiEYoyuDt2CiUW15IZL/3vnoIKoFnFVrhdGCSwEOfG/7rMtezDaI8xBcTsfwcW1Ks5JeNlL/V2rPPvLCuKfnU+hW9e1G9FkSeuUnizvxzfL7Ao69V/JsCL0unf1Pwb1AsL1ecfU8kpdWuB+PSAZ85wysKgw7D1zMCjAAjwAhkIQJM4GXhofKWGAFGgBHQQQBlRy2CPEtmk4QVHq78KtaSuV4vc8lSMxCSIOScml911oqHf0gHdqzTXpafBFqdwRPEgEgU1kg09btXnXVY9fn/f/Bb29RZtzFlGa3aD8rIipL02CuUd/nipdt6ZuRrk3gY04saD+f6l7cepUde/I0lCZauBJ7Ezuteh1cUEPzl/Coy5bwqgadbPiuvVQk8q0ALu/uiTCidSwrzPb1f8RnmFDaEuXRIPKfgCt37WLefWiqLLwqabcKSZIAFCEoQlVGoZHXXbNWvXKxJBj4FGYevZQQYAUaAEcg+BJjAy74z5R0xAowAI6CFAB5GDzVZl+BpDeChkwx9gNqlVXiolRTlEUoos62B1EByYEfc+kE/qN/f/u1raeUjt2rBFhV5JydXPQDtFC9RKtHsQAibwMM8cq9OibzJ2Gvhl93DDsy4dJ1bTN3ipdt01Hiqr9+FPzjTcmg3Au9/vvNn2yWFFWLhtmd1r/hCA9595ha0ZNY8nkrg6YRXqNf7JfDkPSw9Nu084/yE8+R9GDeUeOZgCxB3UN51HxFzO4bQf69+zprLpc0+rGbSD19qpVoRzv53od8SPCAjwAgwAlmDABN4WXOUvBFGgBFgBLwhkAwfPDvCakx1Uco8+Lyh5L23mnwJlaF8GFTLZd2ULW6zuinxoibv1PVZeQDKvUaRiOmGTVgltFbzWAVcJEthKNV3naLsr1PcVC3iT9li4qYrE9GcBYjntGgd9w9zg23Q760UavL9jFRX6Td2+yM30vod71uOb+cwNnXS0XTdZUstrykQHNrw3vACLHQ2LktNUX6pEjhhlMya51dDLLwo8NQQC4zpRYGnrkEqheNdPaR6WUaxVx3so+wjU88xh0whxs+sAixkyXyJKMXFFxJhhPX42RvK0aEQRCAMN0aAEWAEGAFGwIwAE3h8TzACjAAjMIQR2F/fQfFup6xIf+C4Kc0QZFHX3GmpePE3Y/pdJR+I4bMF5UvYZVpQ46GcVvrigbQbMWk2zZp/ftLBUMtM4S2FYBJzSEVvw0YivEwtZ9LZoa43CIEnQyycFiRVSiAnewWRBrIyGSEs8L6rX9NOcQd5kB2R54fAAwaqQg37BalnVVp5xdLPWkKGTxarYnIn9V3YCbS6N5ckcHAvy/dsGCWz5vlbu+poR+tq48dePPA2P9dBzbX9n9U6HnhOe5cELUpNkeTqx+tRF9tU95MELT6DoaJFsyuFlve8TrptFPti/7soUOUxGQFGgBHIHgSYwMues+SdMAKMACPgGYEofPCkSgkP+lC0WJnEQ7UF4tDNK87zhtLoAllOGxOKj1ZRllUviLxsbiAs4d0EZc/+hv7SbBB3vTueEU/Mm2y3n3PUv1NO5ZGhwfPIRbd7HsvK/85uEJB4UMmgHRB79Zto6mWR9Zfv1e5enZc3QI3X+Z/l1DvTfykjCHfcx/AUsyI+1u14jxBoYaXEg8umWph67aV30LSaYyz3kiryTl1MlSDbS0QqdJf4fMJ9HEU5JVR4vS9vosK/7qdu8X6RrW1sAR06vpzaxw0MMGje002b/9JvOeCWQqt7o8j7GGpsqIWTcR/rri3sfiBoR4hgCPl57Jakrar37Mqrw14jxkMiOUJWuDECjAAjwAgwAlYIMIHH9wUjwAgwAkMYgTB98GTZpI7SLKHYig1SaWXLUYDMKirIEwRml2F8DwN8HVP4TNy/WkKKAA+Y5Us1T1fdBur94H+1thUmibd3zXZ68ZaHteZFp1GzJ9E/fc891RN9Va87JK/qhnloL8ai4+/q6uisG7x5Ro6O9ZMAQRR48t4FGV9VlhhTls+alwoSDy9zgwrvjPmX0JnzL7WFIR3IO7WMFJ9RpUUxreAHL2fb9WEttd73AnV2t1KP0Cd2xbsHkYQg8nafM8IY1kze4Wdf+OoZNGHqaC/TDuqr+t3Fu3oN0qhLEHlek3kDLSKJF+PfG5R+Y38gyXC+OspZL+m2YWyH/e/CQJHHYAQYAUYgexFgAi97z5Z3xggwAoyAKwJQmewTZbRBmlSaYQwvybIJwi9mBGlYmccHWVOqrrUjMaH+QLgFCB835Ueq1u51XuypTDwIW5WQyrPd++zVnhRMYZJ4uqW0uuSdndedWmaqeh56xdOu/47OTnq0vp7OvreXxm3RH7VU+OGVCSUemh8CT5JZ5hAAnfRWM4l33qkJ4q4pp5dAQ3YetvcqE9I8eN4VUmr9vuTZmktmdQI99E+ESJJ38pquHvHZ1yusBGxIvHcmVFLt6oFJ4WGQd1IljftV/exVy2rTIczBC7Z2fe2ChUBgSqWb9MezGyOZQRfwh2X/uzBOnsdgBBgBRiA7EWACLzvPlXfFCDACjIA2An598Nx87nQWgIeo6rICgnIrk8tpVSzM3m8qDlaBDzo4pVsfnZAKKO/ymjcZnlMo0dNtuaf8TLeraz83JZ4ueaeTMCvJj3rh7RhmKSLUdzvjcTr++V46frnrlgd0gAqvZ0Y+xW+s0L5QklYgm6FQsiqBD5vY0l5cBB11UmalxyMUtSgj9tPM5J06Boi89lZx34jxZetq66WDBfn092GVfT8Lg7yT6mC7L1tUL0Azeetn36m8RhKzTupn6Y8XF/e7m/pQBhTB41NHved17/APHVk1sHza6xjcnxFgBBgBRiC7EWACL7vPl3fHCDACjIArAiAcUB6n2/BQ5KUEyW1cnYcstzFS+XsdckddnyQM4KsUJtGTDAx0iUqspefVfzOWBDUJHnxBCOm0nImfo7CDLUDk7Vu7Y8D0R18433U5qjILiiQrMksdRFX7IMkyDP+0/9q3r2+Kf/kPPQzlBSDwvPjf6ZBZ6n511HhuINfv2UrbV71EDbXbBnStHDOZauadTlVjp7gN4fv3XpJXgxJbLb9cTt1bnX0MOzviFBckHsItZHtjWAVN/9zxRupskGanRLMbU/WAsyuZDrKeqK9VS4R1EmW9qA+t0m3D2A/734WBIo/BCDACjEB2I8AEXnafL++OEWAEGAFXBEDegcTTaarySofQ0BkTfeTDZXtnt6FsyITmxfPPvB+vD5fpgAcecOFvBxWS2wMxQit6d/65b9mCwzOIPBBgbqRWFASeH/zsSkjdxlKJHnOJotu1Vr9XCbyxm3vpHA8CxZFHFWup7yQxC4N/L2Xw8r3r5o1nt+93n/3VIOLO3BdE3rGf/Wc/0NleoxKzXolWqdhCua2Xaxu/85CvPRQuOIYKFxzr61p5UZAvSbwQW4EWGeLFUEzCnsFr0rkslYU1AM7W7XNO3gv4XAuD5BxWXmh483FjBBgBRoARYATsEGACj+8NRoARYASGOAJQgSFJ06kFIat04ZXlSeifzj5xeBiuEIbv+eJPr2SHioVXRYwujmH3s/N+c5rHTODJviAuXUtqK6ZT7tHfDHsb2uMFIXfUSfBwD48tHcLTaXEqgYd+uiTe7qlEs7/vHnQgSYigISte1Xg65J3EpXh4DbWOucD4a834Ipo8IZEA7KdJlWGQc1E90RpF6SvIPLfml8DDuBW3X+42vO3v7fzuvAwYVH3oZa6gfb2oKu3mkiXiuWLjOkppYAzCEFYQQbwD2f8u6Onz9YwAI8AIZD8CTOBl/xnzDhkBRoARcEVgb127o9cVHmjCUBO5LgQPqyItECmmBxo7XNVaOuOF1Sfs0mG5Luw3lp8TioIjrL1iHKeQCrd57Ag8XAcckVlgV1KbSgWeX9WdHR7AECm12LJfhY70wFPnAIkHPzy7UIu3FxK9fWYO/eeoUY5HFQbZoU6g642Hktntq152u43oYJ3whYsnyoYPxE6kg+Il26c+XkV4eWmp2m/Hi+9Sx4vveVnqgL5+Cbyw95vuZbVu/n5eD8DLfs1BF169EvGF0CgRYMGNEWAEGAFGgBFwQoAJPL4/GAFGgBFgBAxyDuWrsoURUBEE1rAfPIOsBddKBSJUSlBZuJWBep0vDJWM1zmd+uuEVDhd39uwkRBiYdecSmpTQeCFpbqz269Up+mqtdRxXm1pIbzsGsItZIPqbs+0RKLrKaWlxsuqJWu/Le3WZYh/u/+7jrdrh1C0HaqPD+qzoeTaAT+DGu/K88e43vqp3q9TgIXr4kUHrwSeJFLjXQgiCceLUV1nupXVSqK8V8h7o1Bv4/OwUnzRArsJNzylQjsm1MZeQkDY/07nncB9GAFGgBFgBJjA43uAEWAEGAFGwCj7QakQHj5KxMMKHliCltQFhVWSSMlS/jkRHZ1x+F25hxgE2XOilLHAeEBMVSKvl5AKt73KEAu7fqCZ8ixKanOO+nfKqTzSbfhQfp/M0sAgARfmMlqdzdup77yGrujMZffesfLGc1Pf2ZF3mGNH4bnUljfeE4kXRsmsDgbSAgA+glZll35LaL164AXxu9PZp+yjvncaW+NaZcRextftmyz/VK8KO69BF0hjx73KjRFgBBgBRoARcEKACTy+PxgBRoARYASMNFSQeHi4TwZZpQt5IuyhMOmkVqoUiMl6+LbCH6qaooI8Q4npZt6uc35OZbTq9QNKapPofxeW95sOFmoflEzDqN4LMb2js5Mera/XnuriqiqaVFAwoL9UZaF0OWoyWp3Y7I3nRuCpZbPmDZvLaOXv7cppU6HktQu50EmhtTrgkmvOoPwj3FWGuDYVCdf4jIbXI5rfMnHtG9vUMRWfl+q/DToKO7zX8Z53+3eV/e/83gV8HSPACDACQwsBJvCG1nnzbhkBRoARsEXAKA8SSgok6qVTkw9pIBjDIJbc9qaWy6YiEVeWgyUeiDtDL9c1799PSIUbhvL3Pe//D1HjJtfusqQ275hvUrxkmmv/IB1U5dDBxs6U3O+S5PFyT+uSeFbkXbJUaHbnonrjvbviefrw7Zcsuzqp73CBHYGH3y25YXLfmEHUjkHuLXltv1orr6+M0k8Zbd6U0VT6FWFoqNFSQVaqy5JlpkGDHDS2anQBcQjVGhTLOiEiuuPq9vOisDOr98xBF+x/p4s692MEGAFGgBFgAo/vAUaAEWAEGAEDAbMPXjrBkowyqYTar8BVKZEsXMJ8IF/5WvOAZZ96cpkRUoHkRChEQFRGVbarS+IVzP0PGjZ+jqEEjYqoTZXqzuqe8RtwYeeJNzEWMzzvVOWdLOssEKEwqSIr1b1Djbfz3Vdo7WvLjTRic2tq6aLmln4vTvPvnQi8K74wxkinxf2M+zpIymxY73GzOq31hdXaYRa65J30XIvK/80LFsn6TJGeoelwT6sKOzf/PYkPbCpAPMrPOfwd9gncGAFGgBFgBBgBNwSYwHNDiH/PCDACjEAGItDY3GqsuqKsRHv10gdP+4Ikd8TDDwg2lADWC7++sJpaEtUoxm0Xfnfp0hJqwJihxEOZs9cG4u7V1wYHIADLI6cW06knl9LI0XmRq/wcy2mVsll5xiB3wlQfhqG6++uT7xrw18wcTZNn6ZU06pyXLDEN2/swFeWFOvtFCe1H771idO0S72W1uRF4Vh548nqU0Z592gijjDQdiB11X2oZccPaj6j1vhccofJC3g2vKEi5X6l5M6riEn6A5nPWuU/s+oT5xUaQdajXuins7PDJFRcCHwRYsP9dWKfB4zACjAAjkN0IMIGX3efLu2MEGIEhhgCIuzt/8gi9tXo94b8XfeZUWnz9JVoodMS7jQffdG/wEyoUiqIDjR2BiSc8DErft1SUy+pg7aeEeMfOTgJ5t3PnYKIT4+GBUz5Uf+miapo0MTnqD6TTEl6HW86ksy0hkA/pXnzi7LDUKYl+tnmHcfn0gkrjJdu2dbX0mzuWWw79qfOOJbzCaGGnhoaJXxj7M4+BFFqUTWPfKNmXajw3As+cQquOe86nRxJIPLeU0Cj2ozOmSmod+mAXtW/aM0iNB+Iu/4jRVLjA/b5KKL8KyE+ysc56w+gj1WkocQ3jXORnPz4X0s3qAXh5VSDKMtzCGIdXhHG/8RiMACPACAwFBJjAGwqnzHtkBBiBIYPAvQ8+TY1NLQZpBwLv6m8spQWnHkfXXrVIC4PaQ22WpW1aFyexU1AVhiR13IzFk7glx6mkMi3ehQCCuCtx+chjhwaRd9JnrkchTOSkTiTe2q2dtHbbYCLwgk+XRgoPHm5hju+3FNItUXdTZwPdXfeB5R7OKp1I++9eR9vX73Xd4xXfXhiaIk8GXOiY41stTPUzdCvnc91YhB3UIAuUmaKBUHYi8OzKZ/HeyBP/c9onqujkE/rJ1wiXH2hoWcYNz1GzF5ruwEE//3TnCaOfVKeVCZUZ7kk/pfrq5x8Sb9O9qaXTTa1djuppfC6PGVac7lvi9TECjAAjwAikCQJM4KXJQfAyGAFGgBEIAwEQdiDrTpw70xjuo9oDtPDib9HyR39E48eMcJ0CKjQEWWRCkyScF5WWSup4uS5d8NBRoFiVzeKBsldUK9qpViZOjNElFw0btM1b7q+jdRbknex4viDxoiTy1ORUL4SUm+rux4fep83xRttjPbingTqFF98RTzVT2e4u1+MPk8RTU0y9kBUo0ywpzCeECPghSVw3GXKHd5/9FTXUbjNGlWq8+qYu8cXDYLxbc8fRzqLBX0KAuMO1cUFKqyEWIS819OFUpZYXsjbZATdhblxVILqRWuq86VoKroONfC/HBTkNewarz1/2v9NBkvswAowAI8AISASYwON7gRFgBBiBDEUA5BwIOyjtrrjwTLr2ynNpqSifbRJ/v23xNX27uveBpwwiT/2Z05YzicRLPCAVaHnESdVKlIENybiVpIG7HQF554/6VWO5gt0AwYEHRxB4Tk1V4UF198Nf12ttZ9bkGC35crVWX7+dpDLNzdvMTXWH+d3Iu6a6Vmqub+tbqg6JB1+8K79zpt/tGdftX1Pbdz28sfBgP2HeOCPF1KlcUO45T5C0bn0DLTCCi1USD8ODaN65p33ATHbkHZI7DVJa/E/N+CK68vzwfAkj2KrlkFJl2iXen26ej5lMZKmbVwlqNzWxH/uAZJ2dl3mkB2JCTdw14LMYKmN44HFjBBgBRoARYAR0EGACTwcl7sMIMAKMQJohANLu/GuW0AN3LaZyEVQB0g4KO0nq/Vr8XCru8DP0feOZe7V3kUkknttDXqaVy+ockkzMNSe2wvvud4/VUU3DQQJ5V19YTHUFeuVZp4hAC6TTorkp78xrjFqJh/kkWdvS3p/eqK7DTXWHvk5ls3KsPVsPDthe6UddNPXpgSm+VmfkV4UH4m7vlo3UU9xAXcN2Dhg6r1148h1xEo2cMt0ymVdnzzr3Uyr71O/ZSiiplWq8uAiROVjfRSDu9uefQG154wcsT5bM9gjiTnrnZZL6zgprNeTCKoFZJutmirrS7X5SQx/s3s/S489vgI/bGpL9e7WUWE2gHVVVKIjr3GQvh+djBBgBRoARyFAEmMDL0IPjZTMCjMDQRuClV1fRiyvfodtu/GeDtHv6LysNwu5cEVpx09L7DHBUxd2c066iNa884Am0TCTxUDoowyhA7FUIdQOUOulqeu7pQEydsT+k8nYIwgOllu3bG2nXczvowNrByrltlcNoe+Vwx+lkGe0TL7fQMvHy2r57dRXNnhJtGIa6Z6ne0VHdyb24qe/Qz0zg4Wc6Kjw/oRbbX95MDV3rBhF3ZuyHD5tAc4+5oE+lFUaqrtfzTWb/3/yhlnbt7jCmhDpNNrVkVv7sii+MockTipK5vEjmUktMVSVlJvndeQXGrqx2KOwZKlv8W4XPcG6MACPACDACjIAuAkzg6SLF/RgBRoARSCMEkDKL0thrrz6Pbrrjl3T5BQvpKUHiwfsO/43S2tNFeAX+G+Teus076J5bb/C8AxitQwGRCU01Osd6oeDI9HJZN9yx50qRyrv1/g+o6cN6am4WZF5Tt+1lq0eNp4aiEsvfSwXel5bsc5vW8vfJUOHJiWVJLdRKUC+pxK3T4r+291XHvZnLZ2Xn0W+1E15OzWsZLci7utgbQnln78Wnzje8egKdeNyFhpcWiGndPfs6zDS4aNuudvrtk7VGQAXKZEF4yJJZLA9ls0idzQbyToVbKs9QbokvH3LEy84/LQ2OKZQlqGW1veKQoSx1K5cPZeIUDoI9Vgv7B26MACPACDACjIAXBJjA84IW92UEGAFGII0QQDgFymdRLlsh/pTls1DejRNqPCTSrt+03VMKrdX2QOI1tnRmRDqtfChC0uqBxg4j2TLbW+1vhYJrVxPlCIKjta2bDh5yDl2wI/GCEnjA+Xe3jEoK3FKJFxMeiFAfNgsli1vTKZ+1I/Aw9jH3unsCLvnNFW7LMH7fsq+Ztr7xDnWOt07BtRtk5oxTaFrNJ6its5vqmjKDWNcCxKHT31c1UVEsl5595YARVgHSDuRdthF3KgQokR9VVUT4HIN6uLOrJyiMaX89vowYWVlk+CAiSEkqqdN+4T4WGBN7rBbKOy6d9QEeX8IIMAKMwBBHgAm8IX4D8PYZAUYgMxGAB97LooT2DhFaoXrb3XDz3XT6/ONp0ZmnhLoxEGEHGtrTlsSTPngy7Q8BAEUFeVlZOisPFg+8tKeFdj6wxlAokfj/wGHXbmdiB754746eMOj+yBQCT/V9A7ksy4jdDPGfbd5Bz7UM9Jgzg9DRFqdDtdaKODcCz0sJLXzvdrb/wfN7NE8QWcfP+zcjbbZQ/Hc2loaroKillFCmlRbFhBegtQeiZzDT9AIZbAEFXryrV4T0xKi9s0cQWnHXIJo03ZLrsiQh3y6IabynsWc0L2m1rpOkSQeQd8MrCg2PUm6MACPACDACjIBXBJjA84oY92cEGAFGIIUIoBz2p6J09rqrFhl+d1DhLRJ/XiZKZRFkcZUonV123y2GIi/sBhLvoFC1OSVihj2n23iq/5m5XFamtWZjKZYksTb8/D1q2DJQGdba4lxGC0ytVHg3fmu0AbffElpcG6UCz87rTvrB6RBabiW02IOVB55OkIUXAu+DP/7Nk/oOe5QpwhMRalE9zygRrygpyEpCSxI6caE8axBqLLl3O584t8+JTPm9lfebGvgAEg+l09nU7NJ1ZVltp/D4VO+BTN47vlSqEuXvTN5l8iny2hkBRoARSC0CTOClFn+enRFgBBgBLQTWCw87qOvgcXetIO/UhFmEVqB8Ft/n333b12nm1IlaY/rp1NUtEiIbO9OCxNNJ4My2JEMzibXl1jcsj7G2Nu54vOZQiy9dVE2TJib8mPwSeLMmx2jJl6v93Fau1+icdaJPTJTUdhqKJaumQ+Ad3NNAne0DS3J1PPB0y2exrvde+JNrcIUdKJLAw+9VQgtqPEl0uQKqdNhSW09b9iZI4IXHTvZyaSR9E+9ZKO26LJN3MalbamskC4t4UOzZiYTORvJSpmnbeZXqpNVGfCyhDQ/VrFQWhjYoD8QIMAKMACMw5BBgAm/IHTlvmBFgBDINAYRVgMC78fpL+oi7VO4h1SSefOiDMgMPfm6KQLeHxFRi6WVuqHOg4EBpHcIbkDpb+/A6yyE6BYF16JCzUuevk6Yb16rkHf5+y/11tG6bMwFoNWkUIRZeEmaxJqnmAYEHbzxz0ymjxTVmFV6Y5bMYPywCT+4PhBYIggYRcKHrl7b83W20/L3tgzCaOrqSFh4zmaaOqfJye4bS10v6aLYQWnYKNDtAJXmJzwEd78dQDiaCQUC4lxXlU50ISXLzKlUTxb3c46E6eDcAACAASURBVBEs29eQ5YKcxb3tp910569o5rRJdPn5Z/i5nK9hBBgBRoARyDIEmMDLsgPl7TACjED2IQC/uyhKYoMglQoSz6lc1m0vXh+S3cZL5u/l2s2EZf2KXVS/4iPHpRwSgRZxwWMh2dHcQOCZyTv0Wbu1k374a/fABvN4YZfPygd8SVjqYu5WUqujwlO98NzUd17TZ7GPsAk8jCmJaje/NCjufvbCu65wgsj7t4VzXfuF0cGuZFZn7ExW48kzc1IbWmGAe7xKJJgipTYjCS1BZvlJmpVltdLr1O3LG537J+o+Qcg7rA3//ssv8a4TqfMnHjujb8lQ3t8sFPi7xJ/nnTWfLhMkX7r93wpR48vjMwKMACMw1BBgAm+onTjvlxFgBBiBkBBAQiI88fAwFXVLKHPyhf9Tl+90Qjz0jhDm4R1CuWelzop6D17HB6lRKhQqKCm0KjFzUuCpc3V29lJXvBcZF31EXsW0Spr05Tm2S/Kqwvvu1VU0e0qiBDdok0RtnjB7r2+Ouyos7eaTxE69UPioqjSdNFqMCRKvd00jTXzMnsz04nunrnPvlg30Uf2LnqHKFam74yd93PDAs2qSvMQ9g5Jas7JJl7yTYyeDxNMpmXUDKhPVeF7Uhnb7l4SWG2nrhl8yfy+VxEECWMrEvwdQnKa7CjEoeaeeC8g62GWgIWkeNhpQ55WXFtNioc5/6dVVtPSeh2n5oz9K5nHyXIwAI8AIMAJJRoAJvCQDztMxAowAI5BNCIDEQwkUSLEomvQ+0y2XdVsDCI5KUc6UI8gxEDt+PMPc5gjj96rnW7PwArNb57bb/649HdQ64rjESyRbzh8vXoOTaNXBdEm8MMk7v6o7OxBUVZpK2oLEQznt5rh14izGO6t0In22bBJtW1dL29fvpb8+mVCtQXE3edYYAnkXpL3z9r2eLy8QqqujZlzjel2C2BkccPGz5auF312D6/Vqh38749jIymnDILHUtWaKGs/N787LAamkLe5xO/9HL2NG0VeqBnvFh1C9KPUO2uRneYFIYwbRr1s6HnRe3evDJO/UOd96dwOVi5AqeN2C0EOIFbxx0a4WIVaXX3gmnX6KNcGvu3buxwgwAowAI5C+CDCBl75nwytjBBgBRiBjEMADFNQQYTW1XNZKSRR0njBUIEHXYHW9V8+32t+upfYdTdpLyRVPvYLHo5rvfFxL2eZUTovQigs+XRqK8i4s1Z0VEPJB30rRByIPr+dadhqXTotV0PSCSoO4i7rt2f0W7dnzlvY0buo780DY97DyhCoS78+Nu+u0SmfN40ShwgtSMusGWDqr8eS+o1ABg6yuFAmn8rzTqbw0SgsDkNXYN76YCKLYdbuvvPwe5HmJ8PiLqqGs9s6fPGJ44yJ9/rZvf8X482s3/dhQ4EGdh8R6qPZOnDdrQNltVGvicRkBRoARYASSgwATeMnBmWdhBBgBRiDrEWgUqgqoxYI2qcqxSyYMOr68PqHWyU+bVF1zSIXuPr2o8DDmmAWTaNKZky1LLO3mBJG3Vgm2AHEXVpMBDF697rzOL887XdQ6UBuuX/8kHTy0y3UrIO+qRtbQ5HFnufY1d5CqtN+/tpGeeXur5+txwY8u/5Sv66wuCqNk1mrcQ4WPGz8u7ppNxd1z0i6p1q/fnVfg002FGCV5p2KjhnvAUzBV6uqoyTvs+d4Hn6Y3V62ju2+9gXYLkg4J9TNE0AV88E4QHnlQ4o0TJN6C+cfTQ48/T4vEzzkEw+s7ifszAowAI5CeCDCBl57nwqtiBBgBRiAjEQDp1mSR/qmzmbDLZfXnjAkyq8M1CVFnPD997EIqdMfS9cLDeEWTymnMZbNJllg2CZ+3tg7ntFrddXjtlwqllCRRsGfcq6loZpXlpm3PUP3+wWmwcm35gmSuqJ7oi7yTY2DOX738Pq3ddYhQ9u61LTymhhYeO9nrZYP6h10y25a3hg4VPkHt+WsHzVXdcQGV9cyhscWJII5UqrMkeRyFmtjqUNT3FkIu3FJeAx+szQDyc6axtTMppb1qOXGyiXoom0dUFhlhMlG3869ZQgi0kKWy8L8DoQcvvKWHlXkP3LXYWAZUeCD02Bsv6lPh8RkBRoARSA4CTOAlB2eehRFgBBiBIYOAVxIPD5sVogQqJh58DjZ2apV2hgkmHriqRckT1IPJJLPsQip25x6k3XmHBmxxXPcwGtcz3HbbIPGQSutUTmv2vUuWMsZq0VJ1l2zMsRbpxYUHbhAqyVTq2BGILW17aO/+d6i5qT9VGKq7svLxIrBiLpUWjw18y3/rob9Srtg09t0tgme80HhBCbwoSmY/KvmBJXFnBmpcyxIaETtGKPJi1NIeF6/kEtZhk5ZeboRUhlykUuGMfZeX5CeNuE18lhYmhbzDpkDSIW322qsWGXvE39Euv2Ahgdxbdt8tRhktGsptF178LXrjGe+em17uNe7LCDACjAAjkBwEmMBLDs48CyPACDACQwoBHRLPLWU1mYAlm8xSQypUJdgfC9+gPSbyTsXhnPaPOxJ5IPHQ6lckiCAo7opqKmwDK1R/uGSQWVIZBAIJ+06lT1eyS2olkZMsFZb5/bP83W20/L3tBoGJc4AST1eMFyTIwm/J7P7XV9EB8TK3kgljKOfTH1B86tvaHxEg8cp6jxLBHsnziIvS705746JjKlRpqSQtVWySUVYr/+3Iz8v1ciyB+0qlHYg8eOH9Wijunn7+VWPca688t298WW4rFXmBJ+YBGAFGgBFgBFKKABN4KYWfJ2cEGAFGIHsRaBVlikh6tWqSwEJiIvyKUknkyPXJB+72zujKK+1CKqC6+1ORXqKsG4nn545KxgN3KlV3dphIhRLuwaiUWWqJdIMoL0+m4k/dtyTw1PudDqvx3O4Zvx54fu6rlp17aMfjz9kuqYfaKJ67h4qv2EX5k9vclt73+6mNjxn/nQyPuGR/IaADggx76EIKbIQJ3EjYjeXnJF3daodBlARmqsg7uVeo6zYI8g7+dyDy4IUHvztZWivVd/fc9nUOstB5k3AfRoARYAQyAAEm8DLgkHiJjAAjwAhkKgIgw/CwKJU+8oEnLhRYCL1IB+JOxVYq0vCzsMkWp3AON+Wd+fyjIPESpGrMOK/Orh7HW651474Bv48NLyW8rJpaPplq1Z3V+mRaK+7RsImNdCMtUUarNpTToqwW70M7YtFP+azfklk38g5r78zZTb057cY2vJB48MQb1nGhcV2U/ovJVnZ6/behrDhfJKTmh15OnC6KQzs8wi6rTTV5Z7VPM4EHlR488O4RYRfcGAFGgBFgBLIDASbwsuMceReMACPACKQtAjBQrxMhEUh8LYjlGqWTyfSa8wMMVCSFYq0odwxKMrqFVPwjtoneFi+v7autn/V6iWt/N+UQiLvWTfstx4kNK6GSI0cNIPKSlSjsujGNDmGWuEqlZZ7wV0xleIJ522YVnvw9vPlAYFoFXHhV3wVRNW7//bPUuqvW8bQ6cj8c8HtdEq9IpNOOb/3egGvDVuP5URxq3JqhdwmbwHT73Ah9AwEGxJnjiwr4b/pNq01H8g6QgKwDiXfi3JlGOi3+jtJaqPO4MQKMACPACGQHAkzgZcc58i4YAUaAEUh7BJoFcdfoM6E2FZsL+jCulss6kZY/L3nW1/aOj0+nE8Qr7CYVafCpU1WIDa9vpfihVtfpKj8xmYpGlglT9wLqjPek3OvOdcFKhyDkkxzGzt/Qyzqi7Puz5atpy96GQVP0BVwoajyv3ndB3jM66jss2kzg5dW0UsmV/eEfTtjJMlq1Txhklhwj3gVvx9SVSXu9b3CvVoovK8Igs6IsQ/e6L7f+alkt/k2ClYNuQ9gSAivwfknHhrJZpNKCtJOltOm4Tl4TI8AIMAKMgD8EmMDzhxtfxQgwAowAI+ARga7unpSkzHpc5oDukozxGjygS+J48b4z7yMqAk/Oo6oQD736oRZ5h2vxYDtpwXTqLi9Ke6Wl1b2hBm14KaNWSYFUpCl7uc/tlHh9ARdCjffVBcfQ1DFVWsP6xUwd3C60wrwAM4GH35cv0VOwWhF4cny/arxMUp9ZHWYQjzgElEDNVifK7qG0zrSmltU2CEsHtz0UFeRRlUhMT1fyLtPw5/UyAowAI8AIeEeACTzvmPEVjAAjwAgwAj4RyEQSD+WFw8oLDWWNW+mvXUiFHVx+y2cx3tjuYfT5jk/4PAm9y0BqdGw5QHtXC98xjUuAFbzUUHY84nNzNK5I3y4gMEFQ6JC3mUjibKmtF0o8+Uoo8qaOrhSvKvriydNJt/w3DNUi5l73P/dr3QxREXiY3KsaT3oc4rPBi4pLa6NJ7iTPEfvQUREGUVsmeWuu00klIoKX7PYO30CZYuw6IHdgBBgBRoARYAQiQoAJvIiA5WEZAUaAEchWBJ7+y0p6890N9LFjZ9C5nznV8zZB4tUJbzkEWWRKkwSNU5mYH7+3dCfwcD4H/7zGIHPgjybDSMznZlV+WTJ9pOGJl8ktQWoUOBr+y3OH151b+EcmYaGjSAuTxAlC4On44KkhFm7nkOy9u60nWb+HGg9epW4hF2Gee7L25jaPVCKWiLJiKG/VL2vKBZmPPXNjBBgBRoARYARSjQATeKk+AZ6fEWAEGIEMQuBr372HKkqLacH84+mnv36SZk6bRLctvsbzDkAGHWzsyDgSb1h5gVDaQKXR1bdnt5AKJ3DSuYRWrvuAIPDQ7IIOVNWduleEWlSeNMXzvZFuF6jpmqo6J8i5J3uP+7d10fpX2umA+FNtIybn08zTimik+NOqSUWaOaFXLZkNK1lYl8DryqmjbvFSm04J7biWJVTcra8KtVPj4ecVoowSLezU4mTfF3bz2e1dpnTnCAyyde/4PKs8fL4oqy0Wyjsm79LlzuR1MAKMACPACDCBx/cAI8AIMAKMgBYC6zfvoJuW3kfL7rvF6A+z7AuuWUKLhArv2qsWaY2hdgKJVy8ekECIZUpTAx5AXODBLmiyrt8Qi3PaP07jeoZHCl38YAs1vLGtbw482JP4/wi4sFLdmReT6WW06n5kSS387VBaW1oU0yqrjvSANAZf8UDzIOJu0DkJAm/+VWW2oyUUaflGoi4aSgmhUFKJbI2lOHbR9cDDIOYyWjcCz4v6zrxIVY2H8lKEs4S996DYRXW93HtrRyI53OoLjKjmTvW4eI9XlxUSPvO5MQKMACPACDAC6YIAE3jpchK8DkaAEWAE0hABpNmVizS7E0W5LAi8G26+m5Y/+qO+lb61er1B6v36rsU0fswIXzsAKYAHxExqIysLKSbKK8NI1vVTRpsM/zucR+vGfdS6af+AowFxByKvR5jdgchzatlE4GGfIDRg2o+9p3tQBdarQ97J84Maz4nEQzkxCByc/966dsPnMMymm0KLOXuojeK5e4zpCz51kAo/dch2KUVds2l86/cCLVWqLfPzcqmhpVOUVGfOlw6BNi4ull9aFMbyqE182QL7g6HQuGx2KJwy75ERYAQYgcxDgAm8zDszXjEjwAgwApEjINV1J86dSU1CaXerKJOtEETewou/RYu/dimdfsq8vjWA1Ftw6nG+/PDkIFDyNAnfoXRvakgF1DhQaYRB5Pyx8A3ak2dPQphxSYb6Ts4pS2jxd6m6g3oS/w0SB6EVVi1bSmjl3nDWUOHh3AtjudQR1zP7T9U9vU6UzKJs1ktDOe0s8TI3tWQWvB32j3CPsEm87b9/llp31WotGSQeymnLvve+bf8wyDsMLj3fEHLg5g+ntfgM6oSS0mrhAwnyDv5wuiEXGbTFQUtFCS0Up9wYAUaAEWAEGIF0Q4AJvHQ7EV4PI8AIMAJpgMDSnzxiKOouv2DhgNUgwOKnDzw1QIX30BPL6aPaA7T4+ksCrTzdSTyrkApZWqiTVOoEDrzwoMTTIfGSSd5hzaoHnkyYlXux88XD77MhxELu02zaLw3voyKyAr2RDl/85PfrfQ1z3verBlwn00nVstEEmekc7uFrcnGRFxJv0oVnUe7kQ9SWv5bqCp8wpgRpV9w9m4Z1XOh3CX3X4ZwRYoImPd+8JtUGXkQKBzB/vsn7HuffKL5wyfTkXStocd4gKrkxAowAI8AIMALpiAATeOl4KrwmRoARYARSjMDV31hq+NqNEyTevYKwe1OUyn5MqPFuFCQdfgfFnfS9A9lXUV5K1155buBVpyOJB5IKpYOdhuKqa5DqSCaV4gE/aAqpUzktymZPiE+P3PfOfIjxDw9QiyiltVPbGb54opnVWMkon93edIi2N9eJV0K9WFM2zPjzk2OnBr4XMYAsnbRTHRWLB32U1Da2dqYVmeFHfScBO1V44clQC6e0UZXIAoFtp8T0cxA6JB7Iu9KJY/0Mr3WNPHs7vzudpFqtidK0k9PZq0EPsEAIW4mZCkjwMTaissgI6+HGCDACjAAjwAikKwJM4KXryfC6GAFGgBFIIQIg5dB2C2UdSDv44MHrDmW0IO7w32h41AHJhz74XRitpb1L+EylvpxWLZcFcYcHebsmH/ax9jD8sUDkqW2cIO+iDqww701NWd3+4iZCoIVdk6W1XYc98So/MZliw0vDuB1sx3ho01sGeWfXPjlmaiAiz6y4XPPiMtr/4Vrav3WdMeXIKbNo5BGz6ZgzLjCCDUDyQZWUDi0IgYcy2qNOLzaCKuBx6JYyqwZcBCWwVezgiYdy2gOvr+r7ccmEMVQiSLuRJ/WX8EeBNxRmIGabxfvZ7X0PnNCyhcjCXlAqrqMuzRYSMyh5B8uJsP79i+J+5jEZAUaAEWAEsgcBJvCy5yx5J4wAI8AIhIYASmLhd3edIOuk0k7+bM0rDxjzINQC/njwyQu7wWsKirZUtYSyKt9T2qSbYidVe/Ezr5m8AnmHQIv4oVbb4VBeBwyqT55CvRXFfqbVugaqu4c2/0Orb01ZNV0+/UStvrKT6vcG8uq9F56gtYK8c2qf/sp36Yg5x2iRHp4W47NzEALv6AXFdPI5FZ7ufalSzQZ/NCflmd1xZAuRJUuGQdzqktGqErOptSuwCtnnLe/7MjWgxM8g+HfxKqFKv+LCM+ny88/wMwRfwwgwAowAI8AIaCPABJ42VNyREWAEGIGhgQB87k4QpBy87ZAyu+y+W4yNQ2UAUu+NZ+5NChBQ8xxq7BCJn0mZzpgED3MVwsA8Jsqo/IRTyMTGeJf+A3Dyduc+k1vJaMPrWx1JvOGnHEGjJ1cJFWI4SkSrFbsp78zXeCHxQNyWCfN6pCJDSfnKL3/Yp7hzQ+9T19xMU2YfLczvYwb5HKYazW1u8+/9EnhQUh53ZilNPkmo7zy+8VR/tKCekF73G0Z/rL9SKM/yxHvfj5ou073xgn4BIb0SM4nEDUreyfsO/zbCagJfal139XlGartsIPjwO8T5fkz8/NzPnBrG7cpjMAKMACPACAxRBJjAG6IHz9tmBBgBRsCMAB40kCg7c9okoyQWDX53KJFdMP94enHF2/SxebOSqjJASeaBhvakkHhWIRV+75IqQQKCCAjbG8zvenSuk/sHeeFGPkGNpzaUy8qSWTwUwzMwipTWv+3ZQn+r3aKznQF9Lp92AtWUJ/zxrJpaLi2J232iXPav993qaS6QeOOmzzH2n8qSWj8EHu5XEmT5yVeU0ojJ/hM4owy48HQYHjoHJa/UqTJRjReWBYBK4up8jng4otC7hkXeqQt7690N9NNfP2n8G4pQp/VbdtJNd/ySrhBhUDPEz/ClGMKhpKo99E3xgIwAI8AIMAJZjwATeFl/xLxBRoARYAScEZAKAajtfn3XYuMBQzYoC6DIQx+Qd6efEq33lNVKu7p7fKnhdM/dLaRCdxxzPz+leH7nCnJdVMoZXR8tL2v3qr6TYzv54VmlrOK6x7/jPVUZvniniXLaoGouL5jY9dVNoZWlzxDc9Yj/MafQ+llLJqnRcP6VgnCXqks/+zVfk0n7l4RrmEEsEtMucT81Cj9Tr2rOMM7AaYwoyDt1PvxbCsLugmuW0KKz5tO5Z55i/LsKhR78Y6WqPep98viMACPACDAC2YcAE3jZd6a8I0aAEWAEPCFws3iggI9dOpf2REHieQmp8ASo0lka/Pspx/U7p+51yVDLyP2HVVJ566rlutsb1O/meQsH/UySrOb1IbDCzffObiEX3p4IgEGLKuBBBwQdFZ45fAQBFrPEK6wm1WhO5FDz7nZq2d0xaMrRJ1SGtQzbcaIm2dNdjRf151OZ8BEtKcwX5ejxUMJ9wrghYI8wvKKQcO9H2e598Gl66rkVtEiUzCLFXaryZOAFvhR7aeU7NHN6zYCS2yjXxGMzAowAI8AIZD4CTOBl/hnyDhgBRoARGBIIhEni+Qmp8AuyVLik2hdNXb+d6q6texe1d3/U17W64ON+t913XZgKp7AIPDVht0Ekx/aafBaDEHizF5xPc8RLNqnwRJopQjGS2VY80EwHtlnPKUtmpToKZbPzryoLfXlOARcf/nEvtewZTN7JRYw6vpKiIPIkea2TtBoUkHRV40VNXkrc1P0jXVwmVQfF1c/1RQV5BHuDqMk7rO0M4Rd7+7e/0kfOwY7ichF0ARX708+/Snfc8zAtOPU4Yxsg8x4Q6ndujAAjwAgwAoyAGwJM4LkhxL9nBBgBRoARSBsEQOLVNXVSXHjj+WkypCJfqC+gukpWaZckMUDggMhJVbNT3dV1/p3wsmpFeeMJRF5x3gTfy1Z98XTTLa0mC4PAk6ojp7MIk8DDPmS6J0Q/yfZFNJN45pJZrC8q8k6eoVXAhRt5J68tHVtIR3x+tO97z3yhV7+7xzrq+oaYk1dER+X7S1hOJzUeytsTYR2dg8jr0IA2DYQvTRAS0mwE3HQlbV65DCgBq8piUW1v0LhzTruKZGI7fgl/2dOFlywCLs4XpbUP/PjbNHPqROM6lNXCZzYVFhVJA4QnYgQYAUaAEQgFASbwQoGRB2EEGAFGgBFIFgLw6Too0mm9knhhhlT42atX4sDPHE7X2Hm97W5bNkB1ZzfG2OIvBCLxVF84vySWXwIPSbRXzfiYkTAMEs0tZTRsAq+PjCrKE2W1+cb8bkEhYZ7/fqHCW/9KOx3a0W3sX6qgQNyhbHZkgNAKL+uU9+BbD++kxl3t2peGReJJIt0tJfmDrjYCcbem23qNFxVWE15eW6rVeGER6V73Lfsno2zfam1IlsZ7P5kNJN0VQnEH/zuEWVz19Tto+aM/Mog8+Mlee+W5fcu56c5fGTYWi0RfbowAI8AIMAKMgBMCTODx/cEIMAKMACOQcQiAxGts7TKM592aJA064z1GCWOyVHdW68ID7Ajhv4SE1iBKNLc9q7+3SliVv9cl72T/oCQexglSuuc3xOKMidPpnGkzDfWjThlrEAIPSbSjjphte0TyfnQjkbycsVtfSRx1C+Vqqt8De//RQAdXNxhL7vYgRp1yzigqG+ffn8/O79CMHci7Ja173CAlqPF+WDrOtZ9Vh1So8VL9BYKKg/qZbFXC7gtUm4vKheoPZ5/shrJYKOuaRBAUXtddfR6dcFh9ByKvoqzEWBI88RaKcluU0MInjxsjwAgwAowAI+CEABN4fH8wAowAI8AIZCwCUDLZkXgqcYUkxHZBmqVDk0q0HCGFirqEzcnrz6ls1g4nlNOOK+73d/OLp9/ky+1Nh+ihzf/wNC38ru761Nmekoz3fbiW/nrfrZ7mkZ3VEAu7AXAPDCsvICS/Rn0P2CkvfW0uhItk6WxOZytRRxt1NexPjFpYQjnKyzxVED883URkXfJOri0IiZdMNZ6u8jCE49UeAu8BqFGjDLlIFXmnggAiTya7PyW875BQe9uN/9zXZelPHjHSadkDT/vW4Y6MACPACAxpBJjAG9LHz5tnBBgBRiDzEYCiqEkEEagtmSEVfhGEKgSm6lF48Tmp7uR6P2y+29fSw1DhYWK/iiAvKjwQFyidHVPoPdH0lV/+kPZvXecJI3OAhdvFuqowt3Hsfh/1+H7W9f7Pd1D3/h2CvBMEnmgyC3SAq6Ug8vJGDlYjHf1VbwolryWjX2j80POWbikZ69sXD5NFrcbDZyFKSOuE310qAyTsgI2KyEwH8s6855deXWUk09596w3Gr2Rp7bL7bukj+TzfgHwBI8AIMAKMwJBCgAm8IXXcvFlGgBFgBLITAUniyYfBXCHviIIYCxu9IOWkdmvRIS+RNrun7Q++toNAizDSaQ3y5rASDaWdXkrp3Eg8qO7g9Xbp1BNoYql3rzIJzOPfuUQbo5FTZtFpX/mudn/ZMYqSWvk+gMIP6tNUlo2rgHRtfoc+ePDAIIx0STwvBJ7X9F943qmBFboHGUSFJ+eIjMQSXxLg8+BgY/ICe3RxM/eTRCYU1c0B05orhd8d1H3p2K4SabRSkfemUON9+2uXcnhFOh4Ur4kRYAQYgTRFgAm8ND0YXhYjwAgwAoyANwTgcZebS4bHVyqTXr2tmowH7PLimCAcOwIpZHRUd3Jtfspn5bVhEnhyTN0SRxVbu3JaEDeTBGl3yugjqKZsmNfjGNAfpbRrX1zmqsTzS96ZCRyvRKbV5rwSV4EA8nhxy73X06Y9n7e9CkSekxJPl8CTScMg8XVVZ99t2W0bWuG2zT9UHOHWRev3YarxolT4am3GRyeZ1hwzEnL9Bb1UlRWIstw8H7Mn75K33t1A6zdtp9NPPY6Vd8mDnWdiBBgBRiArEGACLyuOkTfBCDACjAAjAARaRUgBPMUyrYF0qRYPns3t/shHHdWdikm6EXhYmyQvcH5eE1r/tmeL8dCeJ3A8edQRoRO4dqEWIO5GisCKOQuC+wICAxCZ8Af0Qjyp55qOJbNyfR3P/4o6lt9PH5Z8z/HtaVbj5YpSWnjj6SbR+lW1+imflRsJi8DDeEHVeJIE6xXySy+q1nT6zJSq1PZOBA/FqXcAq2u9Uihuh4mAIFzLjRFgBBgBRoARhxhtZQAAIABJREFUyFYEmMDL1pPlfTECjAAjMEQRyFQSz48nnBfVXboTeFifH7N9iUFMPLgno2waZB5aWKSd+W2aIC8KqKU9Ll56Ma3AoEKUDaKlU8msurfG/zjF+OvuwiupPW+y66dTjnDH6xX/L6diBOWKl1uIhVe/O/MC0oXAk+uShHZjayeByNJpfj5DdMZNRR8QkVAmg5ivb3HGAOTdiMoi4/ODGyPACDACjAAjkM0IMIGXzafLe2MEGAFGYIgiAAXXocYOI+Uzk5okIdo7u41SYKfmVXVnHstviEUUJbTq2rwQMYk025ihuHPDKxPvgw5RFu6mQErnklkVc0ngteXW0J6iq7SOQ9IxuRNmklP5bBjEVboReABI9TJ0SysOAwOtQ0lyJ9zf8LRDQ1mt2c9R7js/j5V3ST4ano4RYAQYAUYgBQgwgZcC0HlKRoARYAQYAXsEGptb6eWV79Cbwido0WdOpROPneELLnhfHWhozzgSD8qTSkFKoVmVwPlV3ZlB3N22jNq7P/KM7RFliQTFKJtU3xTG7FV1stw0Ewz6/WLltsd0Lpk171kSePi5rgoPfUHinfif/0RUnW9ZWi397vx6psl1+g2xwPVhltBa3StuarwEiVtIXtR6fu/JVF1n5Q/I5F2qToPnZQQYAUaAEUgVAkzgpQp5npcRYAQYAUZgEAIg7y64ZolB3M2cXkNL73nY+O9rr1rkC62u7p6MSGC02pxVsENQ1Z15Hq8qvLHFX6DivAm+zsLPRVZhBPKh3Ys/lp+50+WahMqwwFDiyXCWTCiZNeOnEnj4nS6JN7b9AZr4v4+KsuKYUUra2BrvG9qv353d2fpR4V1UWE14Rd3s1Hh+AjuiXmtU46sp41DcVpTki7JZVt5FhTePywgwAowAI5B+CDCBl35nwitiBBgBRmDIIvDU86/SW6vX0203/rOBwUe1B+jqbyyl6wSBd64g8vy0TCbxJEEBdRG8oAqEIi1MxVlb9y7a0/YHLViTTd7JRUlPOBBY+cLsCiRmpiUNawHs0EktK0Z5NcisTCsbNhN42K5TOW1R9zaqjr9CZVOGUem1PyFVldnQEqdyQd6Ekdqrwu5VhTcnr4h+WDou6PF6ul5V48UEeYX3Q5ifCZ4Wk6LOpUX5fWW1KVoCT8sIMAKMACPACKQEASbwUgI7T8oIMAKMACMgEXjp1VV0+inzjL/iv596bgXdfWt/mebTf1lJP33gKVr+6I98g5bJJF51eQEVF+RRq0iorRfERdgNJB5SaZ3KaVNF3qkk3ojKQsrkcwx6biCwRoiUTSOsQ/g7tgt/vExqLfdeT91bVlkuGUSeGmxRHf9rX7/ChV+mwjMThD5aWXG+4XvYEe82iKuw23dbdtOa7nbXYVNB3slFgdAdKd4PueLPffXt4n2RYWafrujad4iJcuHh4n2AvXNjBBgBRoARYASGGgJM4A21E+f9MgKMACOQRghAYbfw4m8ZCjuUycq/g6wbP2ZE30rR57bF19CJc2f6Xn2PSLQ4KIiPeIY87Kped0gWrSgdWEbpGwibC0HkWZF4CK1IZYPCqEwoblo7uoQCMY/w3I602d6hw1kYYQYyZbZTEFelRbGM8zvr2vwOtf7sa55vpYr/frXvGqjPSgpxL3QTSosRUuMW7uB5QnGBmxIvleSdJHIRcNLd05OR94KfM8E1TN75RY6vYwQYAUaAEcgWBJjAy5aT5H0wAowAI5CBCKzfvIOW/uQRo2xWknb4e5PwwgNhJ9u9QoGH5tcLT46TKSSelded9H5rEUq8lvbuDDxtb0u2C+sI2/fM26qS39sqZVb1AVQ94ZK/Om8zdjz/K+pYfr/2RSX/dg/lTzvO6G917mEFWNgtCESeuYG8Oyq/WHsPYXa0Spr1klQb5lqSPRaIW5SOc2MEGAFGgBFgBIYyAkzgDeXT570zAowAI5BiBEDcvSgSZyvKSuhN8d8P3LW4z/dODa+4Cj54V5/nO5HWvE14ykHRlW7NLWFWeqHBBw0+cNnaEr539j5vCYIzZqivOrsyq5TUy5k5pczqJPV6mStZfXVJPEneqepDK7WdJDizPdTEjcB3S6pN1vlGMQ8UuFKBGsX4PCYjwAgwAowAI5ApCDCBlyknxetkBBgBRiALEYDn3fpN2w1lHcpkL7/wTJo5dSKNE+WzCK/An3A6mjFtEi2+/pJQEUBZarNQs6VLU0tFnRR2IG6GCV88GPhH4YmXajycSCt1bVbKtFSvPaz5vaTMSuImk8hMlNNCiWfliZc3dR7B9w7KOyvFmRXGmUpm6t4vMonY7YyzUY1XLvwO8ZnAjRFgBBgBRoARYASImMDju4ARYAQYAUYgZQggdXb3nv0GgXfvg0/TT3/9JF1+wcI+sg4ltuVCnaf64YW5WKjYmlrDD4bwskb50I1roAzshrGXRoORf6FIpT0gfP2ywQ9OkjWdwturQZyJzp4kdmGnkWrAH1kXP8SkqkLLpJJagAhFHhqIO1kui79L0qqxtZOgrtNp8pqW9njWlJn7KRnPFjVeUPKuUVgx3CksGW4UX/5A5c2NEWAEGAFGgBHIdASYwMv0E+T1MwKMACOQgQggrAKkHAi8t1atM3YA3ztQV3jQUv3vot5eKkk8+aDtl3Dw83AfNZ5+xpf7wFm0iYACr02SmQi30CVAvc6RjP666kOrtUCFVilI3TyR0umFCE7GvrzOEeS+9kuIe11jMvoHwQGkbnVZAXWJLwSiCPqIev9ByTu5Pqi877jnYbpCqLsvP/+MqJfN4zMCjAAjwAgwApEiwARepPDy4IwAI8AIMAJmBBBI8dRfVtIT991C/3h3Ay0VD1dIoT33M6ca/ncPPbE89HJZt1NINokXJskgjfxBXnVlSMKuPA/GIYGEl5JZt3s56mAHt/mD/B4kZJUgndBQ4h6EjAUO8EnE+yLTfBIlGZsj0oeDkm9lovwUHnL1LfpKxiBnGMa1laUxka4bXtkslHj4dweKbnw5ZKXohh8rrBpYqRfGCfIYjAAjwAgwAlEhwAReVMjyuIwAI8AIMAIDEIASAmSdGk6RThC1CuUXHpajbkFVd1brS4Q+FGRUqINV0m5Q7GX4RSYl9fopmXXDKYox3eYM+ntdvzsv82RiwEUUQTWZpMbD51iJCKmJor0lvjBCaNLi676UIIkFsfey+PtPBbmHL48QlHTtledGMTWPyQgwAowAI8AIhIIAE3ihwMiDMAKMACPACDghcNPS+4xfw+suKj+7ME4AJF6jUKpo2tB5mjJMtZnVxG4plZ4WG2FnqS4qEP59BxvDL3mVBEiH8NJLdz84WSKJktewVWIy7ARHme4ltfCug1oOydBOAS5+bksZcIE50l2lGgWJqWKWzmo8ITY0voQoKoiGvFNxAFkHRd5u8Se+UCJxk6DMdvmjP2IFnp83GV/DCDACjAAjkDQEmMBLGtQ8ESPACDACQxcBlCedOHdmRgCAMtQDDe2hknhBPd50gYuaANBdh12/ZK1P9YMDaaMTiBF0b16ulyWzIC2iJtfSvaQ2iM+bF8yhzkR6c1NbegZcSLWgXx9IXSzSUY2H98GIyiLC2qJuUOFd9fU7aPHXLu3zxDv/miW06Kz5xt9lue0GUW574rxZdJn4GZfVRn0qPD4jwAgwAoyALgJM4Okixf0YAUaAEWAEhgwCIPEOinTXIB5cAEtNVsWDedDxdA5AKq+QzFovfMTSpUWpNrPbY7LIIS8Yp6K8NR1Li1MRuhG1CtbLfaD2TYWPZbqo8eRnZH5erl/4PF/30LIX6KnnVhgkHr5celMEKT1w12KDvLv6G0tpnAhYgi8ryL6HHn/eUOZxYwQYAUaAEWAE0gEBJvDS4RR4DYwAI8AIMAJph0BXd0+gEs9kqe7sgKsSRvBIJE21Ai0VJKaKCUonK0oSyis/Cbdh3pipIDHl+lXyKl3uCZwHiO1kN+lD2dia+mCHVJLMqVbjpYK8k/caymhvuPluI9jintu+TqefMo+W/uQR4+8g82QDoQfrh0xRkCf7vcTzMQKMACPACCQXASbwkos3z8YIMAKMACOQQQj4IfFSTVip8KaSHMA6JFGSavIsWaW7drd2Mktm3d5e8p5IlR9cuqgBVa9E3J+pKLOuKIlRofCCxFkkQ51rd2+kQo2XSvJO4nCVIOfQxo8daYRXoJR2mUhHV31aP3H2tQahN1Mk1HJjBBgBRoARYARSjQATeKk+AZ6fEWAEGAFGIK0R8ELipVp1ZwWkLM+LIjDCibACFjHhO5ZqckKuUZYWI6AEacPJImxSUTLr9oZKFYmWakLZjIsacBFFkIjdOWBeBDb0ipsxXcrck6nGSwfyDuWyN4twpbtvvcE4poeeWG4k0S6+/pK+Y0Op7Ysr3h6gyHN7b/HvGQFGgBFgBBiBKBFgAi9KdHlsRoARYAQYgaxAoEc8aMMTLy585axaOqnurNYny0hBXIWddmqer7gwTySK5hvlqqkoj3S74aB6Ah7JIDRTWTLrhoMsqYVXYkNrtAo0SZSlg9rMCpdkEpqpVoO63RdRq/Fioqy/WoSJJNPzzm3P+P1Nd/7KKJNddOYpRncQfAsv/pZRXnvisTN0huA+jAAjwAgwAoxA5AgwgRc5xDwBI8AIMAKMQDYgABKvThBgHfGeAdtJR9WdFd5Rp1yqaqZkkGNB7qkEyRgzlHhREJrpVDLrhpMkNP9fe/cTI1d55nv8pbqquun/QM8NEyZkESKbFZA7RpEwG2YwRIpkc00kRK4TW+NsDCYskNK5Riyi+MZILMAEb8LITqxESAFhS5EGjGAWsXWjcSaE1TUashhycTJKG9zVf9xd/3yf5zRvp9xUV506f99zzvdIKGBXnT+f99iKf36e94mrpdYGViv1tqlJUOjqYavi4pwM7Hp4Z9cmrmo8De9umhw2JUV27Dj9xlnzbzLQ4vDsfq8ST/fH00CvsyLPsVvmdhBAAAEECihAgFfAReeREUAAAQSCC2ir3fJqM5UJs8Hveu2bcQUInSFNWvuJDWpjA82llaZZWmkN+vVNP+9iy2y/h1urQKuKQyMWi6iN+z1PmJ+3+zZGbWGNXRic4dcnymq80eGyvGMVv5dO5XPHfnravC7TaRek+u5bD+/whldwIIAAAggg4JIAAZ5Lq8G9IIAAAghkQmCl3pIWsOu8FtG0J5sOCqaVRjNSBaOVhFFURGWlArGbU+cggygtktxPbdD13+zzUQ91SHtYRhgXa9FotiNpL05jH8owz9/53Siq8cZHymZSpmJzIIAAAggggEA4AQK8cH58GwEEEECgoAJaVTS/5G5LYK9l0RBvSvaCu05a2YIOdOgMOTTITHOKZthXMOw0ULXQwGpIQl0N77JuEXaPwCT3GQy79r2+b58jTCDr2uCOoF5Bq/Em5PcZNeBAAAEEEEAAgfACBHjhDTkDAggggEBBBTS4WnB4X69+y6J/sB6pDg08KdbuIRd1m2G/+43z522V1KB7wcXVlhzns/Y7d9D1jbqisd99JvHzdsBFkD38NACslK/zfn0lNfU4TpNBq/EI7+JcDc6NAAIIIFBEAQK8Iq46z4wAAgggEJlAHkI8DWz8DJ6wlWbVSjJTXCNbJJ8nGnQvOJenzPp85E0/NmhLbRb3/vNrZAdclKXSUsO4fhWWeQwyO638VOMR3vl9u/gcAggggAAC/gUI8Pxb8UkEEEAAAQS6CiyvtrxW1KwetuLq44VV02xd7foYthJJ9/zT0DKvh5+pqXlqme21jnay8LAEtr2Cq6DVi1l7h/wMuMhjRWa3depVjUd4l7U3m/tFAAEEEMiKAAFeVlaK+0QAAQQQiFzg2IlT5u2zvzMT46PmsX0PmW13bAl8DQ3xakt10+6efwU+b1JfXKugGpZwrvGZwRxZHkgQxM9WXEnB1WfaH4sS0HS62eCq17vhp4IzyFq49h1df52mqr/ON+4fGddkY9cMOu9nYzWeTjMelYpeDgQQQAABBBCIXoAAL3pTzogAAgggkAGBk6+9ZT7601/Mnod3mIv/dckcPPSC+d/f/4657567At+9Vq/Nza9kNsTbGE7Z/67LxNp52esvD/t4DbK4GwcQ5Llltp/LxsrEQVts+50/az+vwZUGVXbAhZ8q1qw9o9/7tdV4JQk39b3gQAABBBBAAIF4BAjw4nHlrAgggAACjgvc/8hT5sTzs+aWm2e8Oz39xlnzklTkHe/4sSCPoCHepdpq332ygpw7ie/YYKYtaZ3+u7bLattsUQ8bzNQbrVxMmQ2zjnZ6caVcMvrveW+n7mdl28p1Tzz9tVKUKsSNLprZzUyNGA3yOBBAAAEEEEAgPgECvPhsOTMCCCCAgEMCH/15zlyUf7bcdquZlJbZfU8eMbse3G52yj/2OHTkZe9fD8/uD3XnzVY7s3+Yty2CQ6WSachzbGwTDAWTwS/byrOSJFZLKzJ1OMf7//lZHrvfnTHXmdpy3eh01iIfOmlWK/E0xPMz4CJvVmu/PoYJ7/K2sDwPAggggICTAgR4Ti4LN4UAAgggEKWA7nV3SirsPi/VdhriaZXdb39/wau4O/PKc+uX0pBv9/5nzG9+dSz05bMY4q1Vm5XXK6s0nOg3wCA0lMMnsC2zNWkfXpU24hsnqqYlFZZFbCfWZepsKdYKPPXQAE99inbYfRL1uTXkHqnqr52KhLwN+acYFas23C4PlYq2/DwvAggggAACqQgQ4KXCzkURQAABBJISOP/e++al46977bJ6aJWdts0e2LvL7JA2Wq3C03+3x8bW2jD3qSHeJwt1qWRze7KFbY2syrTRjW2AG/eBC+ORle/aKbPaKrqxqqqIoaatytwYXnYO+9C94LQKrQjHZoNMrNNaqJdvD8K7IrzpPCMCCCCAgGsCBHiurQj3gwACCCAQqYBW330kQyoOf++fvPOeevOcuSjDKzS004o7baXd840HzJ7d9xsdbPH2r/99PeyL4kbaEmronniuhnh2cmav/cxsZZ6GWbrHX54PP1NmbRupHWCAx1r1mb4f9Wa+W2r9vh959iC8y/OveJ4NAQQQQMBlAQI8l1eHe0MAAQQQCC2gIZ0edljFoWf/2au623bHFu/H9ee1Kk//9+47t3rBnv1s6It/egIN8S4vNaTd0K3WukGmqq4FfcOyB1wjt0MtOltm++3tZoNP3Rcvry2Ta0Flxdded36C4Kh+PaV1HjttdVHWvN9gF+uh75H+msnLBOeK/D5wg7RO0zab1lvIdRFAAAEEiixAgFfk1efZEUAAgQIK/A/Z407baXWQRdKHVmwtrzaTvuxnrmcraOqyr5sOZfDb+mi/l7fQqlfLbK/FshN7dX+8vO0DF6R12u6Lp2Z5ayG1VZeDVKGqh1bijVTXWrGzXr2q4Z0OrCjp2NmAR21x2Twtf2HyvccfjfwvSgLeEl9DAAEEEEAgMwIEeJlZKm4UAQQQQCCIwHkZVrFNKuv0uPDBh+bIj3/hBXhacffE00fNrPxB0v58kPMP+p2aVOJpBU9ah62qClpJZ0MrrSbMw0RWPy2RvdbK7h84JOFGHkIr9Zgcq3iPHHQCcd5ajIOEmZ3vjAZ402NVrxIvq9Wao8NlMzlaDhXeWRPdl/TIiz83u752r7d1wcZDQ740/oIlrd+TuS4CCCCAAAJ+BQjw/ErxOQQQQACBTAloQKf73+lxeHa/9792/zvv32Uq7WPSLrtT2mmTPjT4Wkh4cmfQKrNuNrbSKusTWQdpme33jthzZbnSKmyY2WlUlQEg0+M6lTXbLcZRDS3J8oALDe90LaM8NKTT35/1L1X092e7bYH+mE4H14nhD0nAd+DbO6O8LOdCAAEEEEAg0wIEeJlePm4eAQQQQKCbwGkJ5zSg073uOgM6DfAO/egnZs/DO7y97tKs8kgyxLNDKHoNqgjyJtlwY06GdGRpj68ow8zPhlZrlVb99kgL4h3nd7RKbHI02nvvDK002MzSO2JD6kbzaqTt0YPsKxjnevs998RoRdqAy34/PvDnNk4J12BvQf7RQE/DPP1vrZLmQAABBBBAAAFjCPB4CxBAAAEEciOgf9h7Vlpk9eg2jEKr8i7KRFo7wCLtB9fqpHlpqY3r6NyD61Kt7nuvu0HuJ2x74SDXiuKzUVaZdbufuM8fhcHGc8S9hlmrTox7DbMy4CLu8K7fu/zOuXfNS8dfN6+9/IN+H+XnEUAAAQQQKIQAAV4hlpmHRAABBIoj0LnnXRaeenm15e01FvVhQ4gkpmAG2eA/6uf1c74oW2Z7Xc9Wb8nw4cD7yPl5nrCf0fucHq96p9G9Gf0OMwlyXW2pvVGml7q+D1xSg1o6w3XdO7HebAdhje07aYd32lqr08H/4d7/7rXR6l++aLXefffclWrldGzgnBgBBBBAAAEfAgR4PpD4CAIIIIAAAnEK6B/eP5Y2VA18ojhsUKVtukm1cq7teVaVdsO60dDQpSOultl+zxh3ZVu/6/f6+birzLpd27bUuhps2jbiJN9hF/cKTDq803DunbO/M/qXL9o++//kv/9OWmjtFgjaSqtbIuiwIf3s3fK/WmHNgQACCCCAQNEECPCKtuI8LwIIIICAkwLN1lUzN78SKsSzoUy90fYmxMZZUdUN0bYGujS4II2gqtNmbf/BileJ50qVlQ2qllbSmYqqeyfqPbg08CPNsNVWbOp7k/YkYw3hR+WdTfL46tcPrIdyW2+79ZpLa9XdwUMveG20dtDFjkeeMsdlkrj97yTvlWshgAACCCCQpgABXpr6XBsBBBBAAIEOgWarbYLuVWc3x08rlLGPkXZg1vlCJdUy2+8ldinYTDOo6nRKO0Ts9p4E/bXXb/39/nyav4ZL0k49OZZ8eKc2GtLpcKH7tn/lmoEVuqfpw/ufMbMHv+m1ztpjt/yYTq7dGPb5deZzCCCAAAIIZFWAAC+rK8d9I4AAAgjkUmDQEM+2h1YrpcDhX9SQWlE0MzlsGtIafDnGIR2b3XdaLbO9HPWedA84NZlfbiQ+kVXXZEoq3yrS6qyVb0lXZ3azSdtE72l6rGKGhq7zTFyYkpuGiYZ3M1MjRoPmtA4N67RVVttoD3//O2brl75gTr56xrwtrbUnpNrOHtpCqwHemVeeYy+8tBaL6yKAAAIIpCZAgJcaPRdGAAEEEECgu4DfEG+tiqni7XOnLbOuHWmEIy5VAHZbD12vYQlbkwzRsmCi73KSFXA2KFuVdvOaBKquHbbNOO4BF2vvxnCq4V2nvVbjXZSQbucD95gnnj5qdn3t3muq7/Y+ecTcfdft3mALDgQQQAABBIomQIBXtBXneRFAAAEEMiGgId4nUhXUkL3xuh22FdKlfcR63WcS4YwrLbP9XrAkp/a6OCShm4/dKzCJFnDXA03rY9dOh8LEETJah/JQqd8rm8rP6xRaHVix88Ht3vXtMItXZT+8yfHRVO6JiyKAAAIIIJCmAAFemvpcGwEEEEAAgR4CbRnXeUmm03aGeJ2DKtJoxQyyYDawiivEc7E9tJ+ThjPaUrtwJb5BEq7sd9fPwv58Z1WcusTR0urSfoR+XPTd1sESZamUi7Jq0/XwTm20XVar8HT6rE6n1fZahlf4eWv4DAIIIIBAXgUI8PK6sjwXAggggEAuBDTEqy03zfJqU6aZlo1WKmm7rLbNZumIaxprVqqpuq2VvfeoK6w09NHJt0m36kbxPsZ572vvYNmp6bd+zaIccJGF8M666N54p984a275278xf3/HFirv/L4wfA4BBBBAIJcCBHi5XFYeCgEEEEAgbwJahdduy1CIxYYTAwiC+Nrqp6gCSFvZF9X5gjxT2O/Y6sGoBinEFQqGfc5Bv28DK63EiyKszlo14maBr1ZtNiXUv7wYbOhGRQZV3CDncLVtdtD3hM8jgAACCCBQJAECvCKtNs+KAAIIIJBpAQ2qFhzccH8Q1Cgq5mzo5dLk3UEMun02ioApa+2h/cyiCiPVdqQ6FGkLar97j/Pngw640PBOB1aUdOwsBwIIIIAAAghkToAAL3NLxg0jgAACCBRZIA8hngZwMxIkBJkAGkUA6Or7Y9uMg1SdZWWoyaD2YfY3tPvH6TWDVqwNer9Jfb5zwIWf/QI1wNSp0IR3Sa0Q10EAAQQQQCB6AQK86E05IwIIIIAAArEK5CXEmxqtmEFaR/PQMtvvxQgSUNqKrLiGhPS75yR+3rbU1pbrRvcM7HcEcex3Ttd+3m+4OTpclkEYFddun/tBAAEEEEAAgQEFCPAGBOPjCCCAAAIIuCCwtNI080sNF24l1D34aW/MY8tsLzR9Xt3rrCX7HvaaNNw5tbWW8dZqPy+RbRHuN/SjCOFdp1evARcTEpLrrzEOBBBAAAEEEMi+AAFe9teQJ0AAAQQQKKjAskyi1dbArB+99n8rWhjTuZa9KutsmKUDHrQisyiHbYvVbdy6DXRZay2tyuRmf5V6eXHTXye2ys66EN7lZXV5DgQQQAABBNYECPB4ExBAAAEEEMiwQL3ZNh/XVo0Mpsz0Yfd/+3hh1TSl8kyPIrTM9ls0NZi4vuINYNC17nTRoMb+WL/z5O3ne7molX2H8vbc/Z7Hulypt+TXD5V3/bz4eQQQQAABBLIkQICXpdXiXhFAAAEEEOgioGHF3PxK5kM8rSrT4Ra6KX9lqGTyNGU2zIvbOV12qFSSiaolk+f97vxadVYh6nc0BMZlrf1ah1ZwIIAAAggggEC+BAjw8rWePA0CCCCAQEEFmq12LsILbYGcmdIJtS3veTjWBKyLhrV/kbD2asYrLqNaV22p/dz0iDdddW5+tbAVidZT24dHJcjkQAABBBBAAIH8CRDg5W9NeSIEEEAAAQcEaovL5rfvvW8mxkfNtju2JHJHWQ/xbMvs0krLCyFWG23Zyyz7gzrCLn7nPoD67xUJObVNtJX1vumQMJ1DPFrtttcyWuS2YsK7kC8UX0cAAQQQQMC1zmgsAAAgAElEQVRxAQI8xxeI20MAAQQQyJ7AhT/80Tz74s/NlttuNRc++NB7gBPPzybyIFkM8bpNmbXDCq5KSNVrEmsiqClexIaaGmTq9FU97I8Vea+3bsNN1gZYVIxOaNYQuCiHDvSYmRox2lLMgQACCCCAAAL5FSDAy+/a8mQIIIAAAikJ7H3yiHls30PrlXcHnz5qbrl5xsw+/mgid9SW0OuSDLZofDoMIpGLBrxIvymzOol1uFLMirNe03nttFXdL1An0Rbp6NwTcGNQ1zmNVQPOvLcar/36GSa8K9IvAJ4VAQQQQKCwAgR4hV16HhwBBBBAIC6B+x95yqu409BOj4/+PGf2aai3d5fZ+eD2uC57zXmzEOL5nTLbK8hKBDPhi9gQSjtkLy9uHkLZ8FMr84rSaqwDPCZHq55Lrwm89p3Jc5WiXf+yDHzhQAABBBBAAIH8CxDg5X+NeUIEEEAAgYQFDh152QvvDkhgZ4/Tb5w1L504Zc688lyid6N7gi2vNhO9Zr+LdWuZ7fcdnTCqoUyeAxk16FeRuNHJthprG2XeK84GDXK1SlEnsmqVYt5aagnv+v2Owc8jgAACCCCQPwECvPytKU+EAAIIIJCygFbc7ZAqPA3rbBWe3tJXv37AvPbyD675sSRu1aUQb9CAqtMn722jaxWJFammq6/vd+f3/Rg03PJ7Xlc+F/T5/FYzuvKcfu6D8M6PEp9BAAEEEEAgfwIEePlbU54IAQQQQMABgWNSbXdKqu6Of9pKq1Npd+9/xgvwJmUybdLHwpWmWUh5oqvfltleNmECwKTNB7le0ICq8xprVYrBAsBB7jXJz9oKQ71mr3bifvekeylq+23WKzgJ7/qtND+PAAIIIIBAfgUI8PK7tjwZAggggEDKAjbEu2/7V8w7Z39n9nzjAbNn9/2p3VVaIV6Qltl+IZ62Rq7UW9Ie6VZ78KCLq4HM5FjF+1ptqWFauvFdiMMOeNDBFnmwiXKd7f55SyvZbKmtyJRZHVhR0n7pBA5t+//Zq2eM/uXDt1L+vSuBx+USCCCAAAIIOC9AgOf8EnGDCCCAAAJZFjj/3vveEIttd2xJvHW2m1vSIV5cFXMaCmq405JJu/NSWZjFaaNx2eh51abRbGOz4RdBVm1GqkNmWoLepMK7zgriCakY1n09/1H+IiKpITxZ/j2fe0cAAQQQQCAuAQK8uGQ5LwIIIIAAAo4KLEt1lrYjxn1oy6y2dGrAphVhcRzaGjlcKZm52mqmQjxbDaYDFuK20bbRsJV9cazdZue0VYQaNsdpo2twqea+zehw2UyPr1VpJnHoXzocPPTCNft1nv/9BaOhnm4JwIEAAggggAAC6QgQ4KXjzlURQAABBBBIVUBDvNpS3YTs2Oz6DFG3zPaDimL/uH7XiPLnk7xfu++gDjKpS0We64e93yT2qrN7BrrcUjshAbW+L0keulfnrq/de027/7Gfnja1hSUz+/ijSd4K10IAAQQQQACBDgECPF4HBBBAAAEECirQlPbTufmVSEM82xa6Um/LNNVGYrJJBj9BH8oOZNAtzDRQS6oqbm16b8UsrTTln3gqIYOadH4vyWDTXte21K422rJnoFut2GmEdxc++NBrl9VhO/bQLQA01Hvx8He9rQA4EEAAAQQQQCAdAQK8dNy5KgIIIIAAAk4IaIh3SdpPowiTkmiZ7YW2FlRVJTisy4ALt6rN4trvzu9L1BlUJRms+r0/2wqdRruvBqva6q2t2Glcv5tRGuGd3oe2yp6UwRVHf/jE+m3tffKI2XrbrVTf+X2Z+RwCCCCAAAIxCRDgxQTLaRFAAAEEEMiKQLPVDrUXmA1AXNhTzO6f5lK1mSvTT21r85BMM02yArDXrwOXhpGsVXFWvEq8uPbe8/N7Qlrhnd6bVts98fRRM3vwm+bzn7vJHPnxL8xF+THd+25ShllwIIAAAggggEB6AgR46dlzZQQQQAABBJwRCBripdUy2wsu7Wq3zntLoy2030tl7ymJfeaysk72PtN+n6dk0uzYSLJ73m1cIw3xnpXgzpuefedWc2DvLsK7fr+o+HkEEEAAAQQSECDASwCZSyCAAAIIIJAFgUFDPFcqlrrZamXXzOSwacjghstLye3FZ+/FVrtVpK3XlbbMTqckpuBmLbxLe+20/Xt0eCgLv1VwjwgggAACCCCQggABXgroXBIBBBBAAAFXBdoyllb3xGvI3nibHS61zPZznJaKJm0Z1RDt6uaP1O80A/28SxWALoZoNjx0ca/CTi8bUMd9nzrUZGZqxGj7NwcCCCCAAAIIILDp/we/Kgc8CCCAAAIIIICAFdAQ75PFutHJnBuPtFsMg6xSkm2sWZn4ah3tHnSy5LIvXvwhZ5JrEeRd2fgdu6diXFOVCe+iWCXOgQACCCCAQDEEqMArxjrzlAgggAACCAwsoIMOlleb699zuWW238Ot3Xs51LCOftdwZW+5fvfZ7ed1CmzcQ0iyFt51hpza3qphW5TDP2wYXh4qBVkyvoMAAggggAACBRMgwCvYgvO4CCCAAAIIDCJQk/3jliTEm7g+/oBnkPsK8tnrZX8xfQ6tNKvL3nhRHbaleLji5n53fp/TBrRR++j1tZVZ9wOck/bsrPZ+qI++P9qOHfb9Ibzz+1byOQQQQAABBBCwAgR4vAsIIIAAAggg0FNAA5ellaapLSc/DCLqpbEtkfo8Syut0KfPYktxr4eOw+fGiarXjp2n9+fKasssXPlrdeogLxLh3SBafBYBBBBAAAEECPB4BxBAAAEEcivw0Z/nzPt/+KO57567rnnGd869a7Z86QvmlptncvvscT2YhhULOQjw1CeqIRM27AoT5sS1XmHOqz42dFu40ghcMReVc5hnieO7dt9APfegLbWEd3GsCOdEAAEEEECgGAJU4BVjnXlKBBBAoFACGuDteOQpc+aV59bDuvPvvW8OHnrB+7HJ8dFCeUT1sHkL8cJUhmV5vzs/70PYtuCoK/n83HPSn7H7KmqI56eltiJTZm+aHDYl3UyPAwEEEEAAAQQQGFCAAG9AMD6OAAIIIJANgUNHXvZu9PDsfu9/j/z4F+aiBHtHf/hENh7A0btcltZB3SMtD4eGVFMyvGFIghXd18zv3mxJDHxwxdeGVOrTbEkvtY/D7jX48cKq7+/4OK2TH7FTh/tVYer+iDfoIAzCOyfXkZtCAAEEEEAgCwIEeFlYJe4RAQQQQGBggfO/v2A0xNOKOz2++vUD5sXD3zXb7tgy8Ln4wrUCGuLVluqm7S/PcZ5Pq+lGqkNeiNfq8VCdraV52M/N78KshVRV2TNQBpr02Tcwq5Nm/Vp0+5y+F9PjFe+nugXBo8Pl9Z8Pcx2+iwACCCCAAALFFiDAK/b68/QIIIBArgW0jXb24DfNhLTMavvsb351LNfPm+TDaTXW3PxKrkI8rRy7VOse4uV1vzu/74yfYR1FDO86/ezzd7bUjo+UzaRM4OUILqB/GXPqzXPm8Pf+af0kWlG968HtZutttwY/Md9EAAEEEEAgYwIEeBlbMG4XAQQQQMC/wOk3zpp/kz/8aYA3OTFmDnx7p/8v88m+AhriXaqt9qxa63sShz6wWevnoHudOfRIkd6KthxrJZ52gXZWmtkf14tpe7XfVuRIb86Rk2m1ou6tqMM/SqWS0VCPI7yA/mWMBnYH9u4yJ197y7z96383J56fDX9izoAAAggggECGBAjwMrRY3CoCCCCAwGACdpiFBngMrxjMzu+nm632plVrfs/h0ue00m5GBg3My8Rd3desSPvd+V2Hzko7/c5Nk1XPSoeccKxNOf5v0yNGg02OaAT09/Ld+58xL8oepv9LtkbQ8I5p4tHYchYEEEAAgewIEOBlZ624UwQQQACBAAJPPH3U1BaXC1utoVWI+offbXfdHtv+f3kL8Wy7aEkSmJV6ywvzilxV1u2Xna1WNOYq4d0GoAkZjELlXYDfrPt85dhPT5uXjr/ubYuwZ/f90V+AMyKAAAIIIOC4AAGe4wvE7SGAAAIIBBfQ4E5br4o6vOKghJeTUn14y9/+jfnZL980j+17KLY/+GqI94kMgWj4nFQafFXj/6YN8PRKK/W2KdLACr+6drCFttMurTSpvvsUbkr2uxuTfe84ohfY++QR7y8j7r5z6/p08eivwhkRQAABBBBwV4AAz9214c4QQAABBEIIvHPuXa9aQ9tni7hX0vn33jcnJbQ7Ki1neugffPfJH4C1euW+e+4KIbv5V9sywVX3xMtyiGf3u9PQbrXR9vZ8uyrPRRXeX9fdGtl98HQCa0uC26Ib6bsyKoNQOKIX6Nz3Tv9SZs83HojtLyOiv3vOiAACCCCAQDQCBHjROHIWBBBAAAHHBHRK4e0yoXCnbHxexEMDTN3o/fDs/vXH11Dv0I9+Yo7HuH+UhniXlxpe62nWjs2mqOo+eMOVkje4oSXPV+Sjl9FItZSr/RD9rrNWId4o+yZqVSJH9AIX/vBHb4q43ffO7m2q+5qyD1703pwRAQQQQMBdAQI8d9eGO0MAAQQQQMC3gP6hVve707bhPQ/v8L6nlSob/5B7SDaA3yrBpv2M7wsM+MHLiw2zvJqNoQbaMqtVZJrNbTZFdbPgakCWTH+8X5CplXkT11e8oLPebGf6Wf3evIZ3M1MjRoefcMQjoH8ZoUdn5bD+Xjchk8XjqiaO50k4KwIIIIAAAuEECPDC+fFtBBBAAAEEUhfQ8O5pCebu2/4Vr1X2nbO/84K7YydOmbfl3197+Qfr93j+9xfMyVfPrLfWxnnzNanEW5T90Vw+7H53fqaorg1uKHsBVTMHe/35XRc1unGi6rUU99sPcG1vvIq3L97SSvaqMP2a6Ofsu1MeovJuEDc+iwACCCCAAALBBAjwgrnxLQQQQAABBJwR0Em7u75273o1yu79z3gBnbaX6b9rxZ1tpdXW4kmpXDnw7Z2J3P/CFRlwIPvJuXis7eVWkVCq7g2r8HPY4Q0LVxre9NW8H4MEnNZikMAvq36Ed1ldOe4bAQQQQACB7AoQ4GV37bhzBBBAAAEEPAEN6TSg06DO/rcN8LSlVgO+Cx986O0J+HkJ9b73+KPedNqkDhdDvDAtsUFCraSso7xOmOe8TjpKp2TvwIpU5OVt78C4wzv9NfuvUjn70X9d8qpqt37pC1EuK+dCAAEEEEAAgYwKEOBldOG4bQQQQAABBKyAts12buZ+v+x995a00HYeGuDpYUO+pPW0pXJeWmrTPjR8mRyreLehLb5Bh1KECbfSNvBzfR1IMTlaHag6sdt5bVCal7bjuMM7NdRfz8d+etoL7rTd/bF9D5mdD9zjZ9n4DAIIIIAAAgjkWIAAL8eLy6MhgAACCBRPQIM6bZPViY16nHztLa+11oVpjcvScqpDItI6og7dtMpM94ZryX5489ImfDUnA2rDVCd2W1sbBma97bgigypukmmzJZ1ckdChYd6+J4+YV2UfyySrZhN6PC6DAAIIIIAAAgMIEOANgMVHEUAAAQQQcF3g1JvnzIX/+E9vyqwOsZiQVtlZaZl15dDppB/XVr2Jr0keawModLhCI/LhCnY665w8V9ZDvKjDO7vGUYenSb47eq00wju9rgZ4Ok36//zqGAFe0ovO9RBAAAEEEHBMgADPsQXhdhBAAAEEEAgjoKHd/5UqvIvyB38dbLFn9/1hThfLd3WC69z8SmIhXlyhVCdOEteIZTE+Pands25Iqsy03TWOINJWLOol47pGHEajw2Vvsm7ch4Z1+utW977T4+Kf/mJOvXHW7Hpwuzmwd9f6hOmtX/6i2XbHlrhvh/MjgAACCCCAgGMCBHiOLQi3gwACCCCAQBiBd869a468+HNzXFpoXWib3exZmq22uVSrB96Dzo+RBkbT41WjHY+XF4Pvd+fnWvqZtam2ZS+c0pAyK0fSU2O1YlHbauNe/yj8x2U97Z6JUZyv2zl0aMXTR172Bs1su+t2c8vnbvI+pkHdFtkHT38dazBvwzwN6HUgjYZ6HAgggAACCCBQHAECvOKsNU+KAAIIIICAUwJxhnhptWxWZeqqhoa15bpZqbed8u52M2k52ZZm3RNR26pdPCYkaNTKyiQO3avy5C/fNEcPf/czU2ftz3WG8rovngZ42+7cmsTtcQ0EEEAAAQQQcECAAM+BReAWEEAAAQQQKKpAHCGeVndNj1WNDk1YWmklTluWNlQdbqGTd9O4vt8HTvs+7fWvyHCThStNv7edyOeSDO/sA134wx/NoR/95JrWd22r3b3/GfOiBHudbbN7JcB7jAAvkXeBiyCAAAIIIOCKAAGeKyvBfSCAAAIIIFBQAQ3xPpG200YEbaeu7EWXVmWb31fIlXZf277bkCo8Vyb5phHe2XXTdtpD0k77j9u/YnbK3nc6UVqPzkE059973xw89II588pzDLbw+8LzOQQQQAABBHIgQICXg0XkERBAAAEEEMi6QFvG0l6SKa5BQzw7hKEiLay6B10r6TG3XRZA72lmcthoOHV5qeHMErkScnaC2Em+aa9dmuFdtxdEq++O/vCJ9f0sNeB7WH5szzcecHJAjTMvOTeCAAIIIIBADgUI8HK4qDwSAggggAACWRTQEK+23DTLq4O1U9pqN91zrrbsTlBm12B6rGLinO46yFq7EpR1u+e0qwJ178LR4aFBOGP/rFbj6TALnSZtq/Mmx0fN4dn9sV+bCyCAAAIIIICAWwIEeG6tB3eDAAIIIIBA4QV0YqzfEG9taETF+f3m0q56sxN59eXSwRFXHR2Sq+up+wcmuX+hTinW8G6k6lZ4p2ule+BpiCe36P27Dq0gvCv8b5EAIIAAAggUVIAAr6ALz2MjgAACCCDgsoAONVjoU01nQzFtu2xGsH9e3B5pVZi5vh/fRvckKyo1vJuZGjE6UMPl48IHH5rP3zzDnncuLxL3hgACCCCAQMwCBHgxA3N6BBBAAAEEEAgmsFmIp9VkE9dXpGKqJPvmubHfnd8nvF5aNPXetQquLnvjxX1kLbyzHrZiUAM2DWjjqBi0NuWhUtzLwPkRQAABBBBAAIHQAgR4oQk5AQIIIIAAAgjEJbAxxEuyOiuuZ9JqL20TXVppyj+tuC7jBZyTo1XZF7BudH/ALB5xVVkS3mXxbeCeEUAAAQQQKLYAAV6x15+nRwABBBBAwHkBDbrmZYqrDb6urLZkj7TBBl249pBxV8al1a4bh7OtWtR98XTtwx6Ed2EF+T4CCCCAAAIIpCFAgJeGOtdEAAEEEEAAgYEEGq22t5F/Vva78/NwGiRpJd5qI9rpuWkPzPDz7IN+JqrAk/BuUHk+jwACCCCAAAKuCBDgubIS3AcCCCCAAAII9BTQQRVz8yum7egE1SDLp3u9TY1WzJC01Uax19uknGu4UvLO1coTlOCqlQae+lhBJulWxPgG+T573gV5U/kOAggggAACCKQtQICX9gpwfQQQQAABBBDwLZDHEE8fXqvmRqpDgYO3uKr5fC9Mgh/UkHLQASYa3t00OWxKOhWDAwEEEEAAAQQQyKAAAV4GF41bRgABBBBAoMgCTWmnzdr0WT/rFbT1Nar2Uj/36MpndI8/nearlYb9pvmODpfN9HjFlVvnPhBAAAEEEEAAgUACBHiB2PgSAggggAACCKQpkNcQzw5s+Hhh1Wi1Yb8jqYm2/e4jjZ/38+yEd2msDNdEAAEEEEAAgTgECPDiUOWcCCCAAAIIIBC7QF5DPA2mZqTdc36599RVG/bpfnD9qtBiX4yULtDZOqxTaq92ZJ4T0mqrVY0cCCCAAAIIIIBAHgQI8PKwijwDAggggAACBRVoy0SDS7VV0/BRrZYlon5tsUHbbbNk4Pde7SCQSvmvwzsI7/zq8TkEEEAAAQQQyIoAAV5WVor7RAABBBBAAIGuAnkO8XTq6mqjbWpSjWcPwrvuvxCsi3qNjVB5x28XCCCAAAIIIJAvAQK8fK0nT4MAAggggEBhBS4vNszyajNXz6/VZdPjVe+ZaksNMzm2NoxB22Y720Vz9dAhHkYDT53my4EAAggggAACCORNgAAvbyvK8yCAAAIIIOCYwEd/njOn3zhrtt11u9l2x5ZY7y6PIZ6CTUtwNypVZYtXmtdU48WKmbGTa9A5Okx4l7Fl43YRQAABBBBAwKcAAZ5PKD6GAAIIIIAAAoMLnH7znHnp+Otm14PbzSkN8e7cag7P7h/8RAN8Y0FCroWOltMBvurkR+1+eC3Z70///VKtbvTfOdYEhMSrUqTyjjcCAQQQQAABBPIsQICX59Xl2RBAAAEEEEhZ4P5HnjKvvfwDMzk+amqLy2bfk0e8EG/28UdjvbO8hHh2Iq1OWF1aaRmdPDsl01XnZHBHM2eDO4K8EBrezUyNGHXiQAABBBBAAAEE8ixAgJfn1eXZEEAAAQQQSFFAA7sdEuD95lfH1u9C22k1xHts7y6zU6ry4jyyHuKNjQx5wxg+XqhfE9ZVZdqqVpxpqHdltRUnodPnXqtMHCa8c3qVuDkEEEAAAQQQiEqAAC8qSc6DAAIIIIAAAkYDut++977Z+cA9nsbu/c+YXV+71+zZff+6zjvn3jVHXvy5OfPKc7GLLUvApQMfsnb0mzRr22o1wNOgsmiHff7yUKloj87zIoAAAggggEBBBQjwCrrwPDYCCCCAAAJxCBx69p/NqX/5tRfO3XLzjBfoaYinbbT63/b46tcPeJ/R1tq4Dw3xakt1k5Vt4yalRXa4UvIq73rtdVfUEI/wLu5fMZwfAQQQQAABBFwUIMBzcVW4JwQQQAABBDIqcOzEKXPhgw+9f44/P+uFdvpjOsDC/reGenuljfatBCrwLKPuFzc3v+J0iHed7ucmLaGNZtvMyxCOqz7mVOh3bpyompY8n9/vZPTV8m6b8C7Lq8e9I4AAAggggEAYAQK8MHp8FwEEEEAAAQSuEdCwbuuXv2gu/Md/mrfP/s6rvNPj5GtvmZ/98k3zd59W4X3v4DfN1i99IVE9DfEuyfAHFye4hq2mmx6rmIrsjafDLfwEf4nCR3SxigyquEHCStpmIwLlNAgggAACCCCQKQECvEwtFzeLAAIIIICA2wKn3jzn3eAu2QPv4NNHzUWpttMqvKM/fMKbQvu+VOZtue3WRFpnu0k1W20J8Xq3piYtHDa8s/fbb9+8pJ8ryutpeKcDK0o6dpYDAQQQQAABBBAooAABXgEXnUdGAAEEEEAgLgEdUKHVd//z4R3m2R//wqvCe2zfQ9cMsYjr2n7P61KIN1ItmcnRqqkt181Kve33ETb93GaTa0OfOMUTjA6XxaicaHinYbMOY9kiVaKdezemyMClEUAAAQQQQKDgAgR4BX8BeHwEEEAAAQSiFDj/+wvmZ6+e8Srtdj243eyUf/bJfnevSittEgMr/D6LCyFeXBVzVWmlnR6vynTahtEptVk+NLybHq8k8gi6b6O+v+9I6KwBnu7VePedW73qUQ4EEEAAAQQQQCBtAQK8tFeA6yOAAAIIIJAjAQ09NLA7evi7ie9xNyhjW8bS6p54DdkbL+kjrvDOPkdZWk51uMXSSlP+yWaINyHTeNUp7uO0tH2/dPx1s1Vau/9h+1fM30top5WkJ2XPRteC57gtOD8CCCCAAAIIuCtAgOfu2nBnCCCAAAIIZFJAq5dcqrbrhagh3ieLdbPaCN++6mexdGrslARTSQyciGpvPT/PFfVnkgrv9L41dH5C9mv81jceMDtl78bz0jp78NAL3gAW2z6rgd5Hf/qLV1GalXc76jXhfAgggAACCCCQrgABXrr+XB0BBBBAAAEEHBC4vNgwy6vNWO9EAzWtitOwsLbciPVa9uQaGM7I8IdGs20uLyVzzbAPlmR4Z+/VhnjbtPpOWmhnZUryfffc5YV7WlGqPz4xPuq12GpLLfvihV1lvo8AAggggAACgwoQ4A0qxucRQAABBBBAIJcCNQm4FqXlNI4j7Wq46bFkqv7C2qUR3nXe81e/fsAL6rT6To+H9z/j7eV4YO8u779Pv3HWG8zCvnhhV5rvI4AAAggggMCgAgR4g4rxeQQQQAABBBDIrcDClaZZiLg6zpX96OLedy/sS6GDN0aHh8KeJvD3j/30tNcmu/XLX/Qq7o68+HOv0u7w7P71c2p7re6NR4AXmJkvIoAAAggggEBAAQK8gHB8DQEEEEAAAQTyKRBliDc2MiSDGCpmToZlNFMYlrFxhfR+xkbK5uOFuhP3o/cnncVmcizd8E7v48If/mg+/7mbvD3u7D54Z1557po97/ZKO+3dd91uDnx7Zz5ffp4KAQQQQAABBJwVIMBzdmm4MQQQQAABBBBISyCKEM/VirfrpcpNQ8XLMryjLnvjpXloeDczNWK0StGl4+SrZ7z972Yff3T9tk6+9haTaV1aJO4FAQQQQACBggkQ4BVswXlcBBBAAAEEEPAnsLza8kKuIMekTJodqZbMpVrdtGTSrWuHC229a/sCDjsX3ula6bCKl06cMieen/WWzoZ3x+W/GWDh2tvM/SCAAAIIIFAMAQK8YqwzT4kAAggggAACAQQ0xKst1Y3fDE6nvupebnpo+HfVvexuXSHNwRr22uWhUoBVSeYrxyTA04EV2lKr1XiEd8m4cxUEEEAAAQQQ6C5AgMebgQACCCCAAAII9BDQvevm5lf6hnhpBmJBF1Dv+caJqllttE0t4uEdm91TFsI7e++1xWVzUcK7rbfdGpSY7yGAAAIIIIAAApEIEOBFwshJEEAAAQQQQCDPAhriXZJBFJu1w2YxvLPrpVWDU9LyOyT70OlwizirBrMU3uX5febZEEAAAQQQQCB7AgR42Vsz7hgBBBBAAAEEUhBottpd97Srlkte2+zClYa5Ii23WT3i3revIgHhDVLt53LbbFbXjvtGAAEEEEAAgfwLEODlf415QgQQQAABBBCISGBjiDc2MmTGRspe5ZpW6Urn6EMAAAVaSURBVGX9iGtyroZ3OrCipGNnORBAAAEEEEAAAQQGFiDAG5iMLyCAAAIIIIBAkQU0xPtEAruR6pC5fnjI2UmzQddIn2ni+oo3hKPebAc9zfr31Gl6rEJ4F1qSEyCAAAIIIIBAkQUI8Iq8+jw7AggggAACCAQSaMtYWt0PTyvvNtsXL9CJHflSWSrmZqRibl4GW4RpCx4dLkt7ccWRp+I2EEAAAQQQQACB7AoQ4GV37bhzBBBAAAEEEEhRQEO8y0sNs1LP7r53vfjCDuaYkMEY2pLLgQACCCCAAAIIIBBegAAvvCFnQAABBBBAAIECC1xebJjl1WYuBTTEu1EGT6w22qYm1Xh+D8I7v1J8DgEEEEAAAQQQ8CdAgOfPiU8hgAACCCCAAAKbCtSkEm9xJZ8h3nUyd0JDPCk49PbFu9pnVgfhHb9QEEAAAQQQQACB6AUI8KI35YwIIIAAAgggUECBhStNszBAlVrWiCalJXa4Uuq57x/hXdZWlftFAAEEEEAAgawIEOBlZaW4TwQQQAABBBBwXiDvIZ7uabfZ5N0pmTQ7NsKed86/pNwgAggggAACCGRSgAAvk8vGTSOAAAIIIICAqwJL0ko7Ly21eT00wJuSary52qppttb6aafHq2ZUfpwDAQQQQAABBBBAIB4BArx4XDkrAggggAACCBRYYHm15e0Xl9ejWi55oZ2GlVp1Vx6SjfI4EEAAAQQQQAABBGITIMCLjZYTI4AAAggggECRBerNtvlYqtR0+EMeDw3xZqaG8/hoPBMCCCCAAAIIIOCcAAGec0vCDSGAAAIIIIBAXgS0xXRufiV3Id5Q6Tpz02RVKu9KeVkqngMBBBBAAAEEEHBagADP6eXh5hBAAAEEEEAgaoHTb5w1tcVls/XLXzTb7tgS9ek/c75mq20u1eqmlZNSPMK72F8ZLoAAAggggAACCHxGgACPlwIBBBBAAAEECiNw5Me/MAsS3k2Mj5pTEuR96+Ed5sDeXbE/f15CPMK72F8VLoAAAggggAACCHQVIMDjxUAAAQQQQACBQghc+OBDowHeiednvef96M9zZt+TR8yuB7cT4vl4AwjvfCDxEQQQQAABBBBAICYBAryYYDktAggggAACCLgl8M65d82pf/m1OfrDJ9ZvzIZ4h7//ncTaaT9ZqJuG7I2XpaMiU2Zvmhw2Jdn7jgMBBBBAAAEEEEAgeQECvOTNuSICCCCAAAIIJCSgAd1F+WfLbbd6V3x4/zPmuFTg3XLzzPod6J542k6rP57E0Za98C7JdNqshHgj1SEzPVYhvEvi5eAaCCCAAAIIIIDAJgIEeLwaCCCAAAIIIJBLAa24O/nLN72BFbMHv+lV2GlY99KJU58J8e5/5Cnz1ivPJeagIV5tuWmWV5uJXTPIhUaHy2Z6vBLkq3wHAQQQQAABBBBAIEIBArwIMTkVAggggAACCCCAAAIIIIAAAggggAACUQsQ4EUtyvkQQAABBBBAAAEEEEAAAQQQQAABBBCIUIAAL0JMToUAAggggAACCCCAAAIIIIAAAggggEDUAgR4UYtyPgQQQAABBBBAAAEEEEAAAQQQQAABBCIUIMCLEJNTIYAAAggggAACCCCAAAIIIIAAAgggELUAAV7UopwPAQQQQAABBBBAAAEEEEAAAQQQQACBCAUI8CLE5FQIIIAAAggggAACCCCAAAIIIIAAAghELUCAF7Uo50MAAQQQQAABBBBAAAEEEEAAAQQQQCBCAQK8CDE5FQIIIIAAAggggAACCCCAAAIIIIAAAlELEOBFLcr5EEAAAQQQQAABBBBAAAEEEEAAAQQQiFDg/wNLBAPbsKL33wAAAABJRU5ErkJggg==",
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bWweS8uRJwLz7ngcSBTzn8nPCk0JAFY74cytwzLThixJddtjlPYFwprDhcFMo7QazZwZiiEJqv3rh1S0LVEQFPF82ms8f3fxb8+sffsVrruI2ksPssOO+Yv717wfNTy9rONqiAp7L4/bHH5875rLUseTSk1NRudrea/PwxfXHjUXhupMiIqOqKUsAldDbrGmbnW0xC7nQJGZJfFQhFRcq7fYLC3j6N+V1U949VdjVXMqJuYet4KxwbbnwfAQ83zXkI+Ddb68JiYoKgVXF33BTaO+l1h2rsG6Nc/r0KUFOyAMPOcVbwJODUutRhVfCeSB1HrluFf4td51z4IWFaG2DgJf5EmJHCEAAAhCAAAQgAAEIQAACEFhDYEILeBLqbr71TzbsbyOz7dOevNaiOPKUb5hbfvuXMQGnlYCnsEnlDVMBhXA12/ABh22448utIKOk/ip0EefqUqjfVTZHnMJXJR5mFfDu/Mf9VoBs7sB73g5PC4SdOPHPR8Bzotj13/vcWMENjdXlo0ty4GnbN79fAmmv+fYXPhXkH/u/HZ8RhGW69vzXHRSEhionWbQpv5vyAl5kQ1ZP/uJ3AsFw043nxl7UUQHPl00aAU+CkByAccU7fvrLPxmFFqvAxYuft906Ap7rXzMH3nE2L96+1ukW1x85/Pa1QrNckS+3OdiiTaG84SIScYA+f84l5rJrfmZ+8f0vmePPOM/cZsOSf3Lx58fCRLVPVMALH0chqtdbd5uq677yJc8xnz3mIFs4pZHnMFrEQqKZipGoiIXvGkoS8JRXcD/rNtU4z7WMo7kH5azbxeZRVGEJ1+SQVEhsGgeejrPHq+IdeL+77W+BoIyAx/cqBCAAAQhAAAIQgAAEIAABCBRFYEILeIIql5PEoAu+eOQYY+V429vmyFL4o0s830zAU0jhMZ/9lvnhDb8y3zrjk+aFz31m07lSRVTl6Drk3W+0Cf9fv9Z2Cj/94BFfCEJ3r73wtCC5flYBT4KicqPJkRTOgSfX02tsiKQS+r/DioRZBTxXOOF31301EBrVFAYrZ+C8uTaE1rrNkppyBp501oXmzBM+HAhc3/3y0UEhDtfed/jpQbGHaFVfnUdVT5VLzOV6Cwsx2l/HUy42hY86oej3P/pa4A7zZeMr4N36+zvMQZ88YyzUNTruL337KvO1C384FlotB56qlbo8gX/66z3m7R85Jchh95qd/29sd1d8Qds9Y+stYgU8icIvsUUT3rjby8yRh6ztPFOo9ZZP2nQtIS5uTuRekytTjkuFeb7vrbsHeQ7DLSzgSay8zYZNR0OzVQn5bisoqrqwnHmHHfflIJ+hc4UqX98rrNtPxUck4PmuoVYCnq7Tg4/8grn/P/PNZV8/3syaOW2tfiskeMdd32sOeMOrxvI5agNdr+IbFfD23fMVwbWhFs2Bp3yBj9pCMAqRd80V4thmy82DfHoIeElXPZ9DAAIQgAAEIAABCEAAAhCAQFYCE17Ac8UnFC6qHFd66L/yulsCEeKsEz9sdrUFE9QkYkis+uTBjQd8hXIqRPIK6za6+55/By6od+732pbzoNBQhVTefOufzYuet6153SteYGbPnG4eeHC+ueQHN9uKmn3myycfOlbkIquAp04oLPXbF//IHGGFnZe/4FlmgRWNTj37e0H+uKutCDHLVmTNKuC5wgsSepSz7p/3P2g++5WLArHmhl/80fzg258xT7ACmgTQZq2vf9DsvM+hQfjlLMsgLIxoH1eFdp/ddgoqu2o7iWWf/+ol5uMH7RtUu1VTyKfCOI859O1B0RGFvSoc1xX5UJVQiUASqCSEPfUpT/Bi4yvgab0ccvTZ5he/u92oQulLbWERzakKcvzyd38Nwjdfs/PzzRnHNYpMqFKvCqaca0OY59qQWoUzy5n24PyFQf62p1qGd/79vqCqq/qrUGe1Zv2REKYw4o/ZUFuFS8vhphyOyvumSr9RZ2ncfEhAVM49CVA3WfE1mk8wLOA50VQC8F62SIpEUYnOn7aMX/uK/7PVgA80EoqV0/CAvRvCmURTrY9bfnN74JSUgOe7hk60Iaq3/v6v5mdXNArMhPsi19/5ttLymcd/2FZfXjvvpNaLQpbltHvQ9ufLp3w0CM/+7pU3Brkar7DXuELZFVqrqrO7vPljQd8keKswy62/u2OtKrSqfixRWfvIITtqOX/LXl+qenzBF5VDcGsEvKzfQuwHAQhAAAIQgAAEIAABCEAAAokEJryAJ0IS68797jVGrqVe6+xSKKzyXb3Kht65JuFAiftdUyVKueSU/F8P9K7qZRJxCT6qSHvV9b+wwtN/jJxJcpS9yIZXvtueU84x19oR8HSe8y693oo5twQ5vyS0yB2onGqbb7ZRcIqsAp72VWVNFe5YZkXHZ9qiB5/68FvMVFuQ4n2fON0orFEiTVwxjzAfhVkq3FLuMSfIhT9XTravnP+DQCBVyLHcWyqcoJBS11SM4Au2CMRNNhRaouBTrOtM7kYnvEoUPcj2Sax32HarIKehDxtfAU/9kDCrvG+aV4m6S5atsPnsemyOwM3MHlYU3vf1O4+Fdv717n8FIq7che/c73VBDkHxkhh1869uC0QgCU+v3un5turvPkFFW7VW/VG1XFXADaq62nl++lZPMgdZBr7FUlyF5F1e9hxz9kkfWWcJR0No1c9v2vm/1wq3GrvCVyVSHvyOvcaqrEo4lfPwMVtFWYLguw/YzRY8+VdQKEZFU3zX0PmX/aSpgLf7gUeYf/93fuwlp+q/CufV58edfp4VRe8PBHhVZj7EVlP+7JcvMpfbOdvN5glU6LaEfFUrXrVqVVDgRQKsxNYbLjk9EFnVJLx+zYql/7BjUBi31v2H3rW3eeFzGq5bHHhJdz8+hwAEIAABCEAAAhCAAAQgAIGsBBDwspJjPwhAAAIQgAAEIAABCEAAAhCAAAQgAAEIlEAAAa8EyJwCAhCAAAQgAAEIQAACEIAABCAAAQhAAAJZCSDgZSXHfhCAAAQgAAEIQAACEIAABCAAAQhAAAIQKIEAAl4JkDkFBCAAAQhAAAIQgAAEIAABCEAAAhCAAASyEkDAy0qO/SAAAQhAAAIQgAAEIAABCEAAAhCAAAQgUAIBBLwSIHMKCEAAAhCAAAQgAAEIQAACEIAABCAAAQhkJYCAl5Uc+0EAAhCAAAQgAAEIQAACEIAABCAAAQhAoAQCCHglQOYUEIAABCAAAQhAAAIQgAAEIAABCEAAAhDISgABLys59oMABCAAAQhAAAIQgAAEIAABCEAAAhCAQAkEEPBKgMwpIAABCEAAAhCAAAQgAAEIQAACEIAABCCQlQACXlZy7AcBCEAAAhCAAAQgAAEIQAACEIAABCAAgRIIIOCVAJlTQAACEIAABCAAAQhAAAIQgAAEIAABCEAgKwEEvKzk2A8CEIAABCAAAQhAAAIQgAAEIAABCEAAAiUQQMArATKngAAEIAABCEAAAhCAAAQgAAEIQAACEIBAVgIIeFnJsR8EIAABCEAAAhCAAAQgAAEIQAACEIAABEoggIBXAmROAQEIQAACEIAABCAAAQhAAAIQgAAEIACBrAQQ8LKSYz8IQAACEIAABCAAAQhAAAIQgAAEIAABCJRAAAGvBMicAgIQgAAEIAABCEAAAhCAAAQgAAEIQAACWQkg4GUlx34QgAAEIAABCEAAAhCAAAQgAAEIQAACECiBAAJeCZA5BQQgAAEIQAACEIAABCAAAQhAAAIQgAAEshJAwMtKjv0gAAEIQAACEIAABCAAAQhAAAIQgAAEIFACAQS8EiBzCghAAAIQgAAEIAABCEAAAhCAAAQgAAEIZCWAgJeVHPtBAAIQgAAEIAABCEAAAhCAAAQgAAEIQKAEAgh4JUDmFBCAAAQgAAEIQAACEIAABCAAAQhAAAIQyEoAAS8rOfaDAAQgAAEIQAACEIAABCAAAQhAAAIQgEAJBBDwSoDMKSAAAQhAAAIQgAAEIAABCEAAAhCAAAQgkJUAAl5WcuwHAQhAAAIQgAAEIAABCEAAAhCAAAQgAIESCCDglQCZU0AAAhCAAAQgAAEIQAACEIAABCAAAQhAICsBBLys5NgPAhCAAAQgAAEIQAACEIAABCAAAQhAAAIlEEDAKwEyp4AABCAAAQhAAAIQgAAEIAABCEAAAhCAQFYCCHhZybEfBCAAAQhAAAIQgAAEIAABCEAAAhCAAARKIICAVwJkTgEBCEAAAhCAAAQgAAEIQAACEIAABCAAgawEEPCykmM/CEAAAhCAAAQgAAEIQAACEIAABCAAAQiUQAABrwTInAICEIAABCAAAQhAAAIQgAAEIAABCEAAAlkJIOBlJcd+EIAABCAAAQhAAAIQgAAEIAABCEAAAhAogQACXgmQOQUEIAABCEAAAhCAAAQgAAEIQAACEIAABLISQMDLSo79IAABCEAAAhCAAAQgAAEIQAACEIAABCBQAgEEvBIgcwoIQAACEIAABCAAAQhAAAIQgAAEIAABCGQlgICXlRz7QQACEIAABCAAAQhAAAIQgAAEIAABCECgBAIIeCVA5hQQgAAEIAABCEAAAhCAAAQgAAEIQAACEMhKAAEvKzn2gwAEIAABCEAAAhCAAAQgAAEIQAACEIBACQQQ8EqAzCkgAAEIQAACEIAABCAAAQhAAAIQgAAEIJCVAAJeVnLsBwEIQAACEIAABCAAAQhAAAIQgAAEIACBEggg4JUAmVNAAAIQgAAEIAABCEAAAhCAAAQgAAEIQCArAQS8rOTYDwIQgAAEIAABCEAAAhCAAAQgAAEIQAACJRBAwCsBMqeAAAQgAAEIQAACEIAABCAAAQhAAAIQgEBWAgh4WcmxHwQgAAEIQAACEIAABCAAAQhAAAIQgAAESiCAgFcCZE4BAQhAAAIQgAAEIAABCEAAAhCAAAQgAIGsBBDwspJjPwhAAAIQgAAEIAABCEAAAhCAAAQgAAEIlEAAAa8EyJwCAhCAAAQgAAEIQAACEIAABCAAAQhAAAJZCSDgZSXHfhCAAAQgAAEIQAACEIAABCAAAQhAAAIQKIEAAl4JkDkFBCAAAQhAAAIQgAAEIAABCEAAAhCAAASyEkDAy0qO/SAAAQhAAAIQgAAEIAABCEAAAhCAAAQgUAIBBLwSIHMKCEAAAhCAAAQgAAEIQAACEIAABCAAAQhkJYCAl5Uc+0EAAhCAAAQgAAEIQAACEIAABCAAAQhAoAQCCHglQOYUEIAABCAAAQhAAAIQgAAEIAABCEAAAhDISgABLys59oMABCAAAQhAAAIQgAAEIAABCEAAAhCAQAkEEPBKgMwpIAABCEAAAhCAAAQgAAEIQAACEIAABCCQlQACXlZy7AcBCEAAAhCAAAQgAAEIQAACEIAABCAAgRIIIOCVAJlTQAACEIAABCAAAQhAAAIQgAAEIAABCEAgKwEEvKzk2A8CEIAABCAAAQhAAAIQgAAEIAABCEAAAiUQQMArATKngAAEIAABCEAAAhCAAAQgAAEIQAACEIBAVgIIeFnJsR8EIAABCEAAAhCAAAQgAAEIQAACEIAABEoggIBXAmROAQEIQAACEIAABCAAAQhAAAIQgAAEIACBrAQQ8LKSYz8IQAACEIAABCAAAQhAAAIQgAAEIAABCJRAAAGvBMicAgIQgAAEIAABCEAAAhCAAAQgAAEIQAACWQkg4GUlx34QgAAEIAABCEAAAhCAAAQgAAEIQAACECiBAAJeCZA5BQQgAAEIQAACEIAABCAAAQhAAAIQgAAEshJAwMtKjv0gAAEIQAACEIAABCAAAQhAAAIQgAAEIFACAQS8EiBzCghAAAIQgAAEIAABCEAAAhCAAAQgAAEIZCWAgJeVHPtBAAIQgAAEIAABCEAAAhCAAAQgAAEIQKAEAgh4JUDmFBCAAAQgAAEIQAACEIAABCAAAQhAAAIQyEoAAS8rOfaDAAQgAAEIQAACEIAABCAAAQhAAAIQgKQ0u04AACAASURBVEAJBBDwSoDMKSAAAQhAAAIQgAAEIAABCEAAAhCAAAQgkJUAAl5WcuwHAQhAAAIQgAAEIAABCEAAAhCAAAQgAIESCCDglQCZU0AAAhCAAAQgAAEIQAACEIAABCAAAQhAICsBBLys5NgPAhCAAAQgAAEIQAACEIAABCAAAQhAAAIlEEDAKwEyp4AABCAAAQhAAAIQgAAEIAABCEAAAhCAQFYCCHhZybEfBCAAAQhAAAIQgAAEIAABCEAAAhCAAARKIICAVwJkTgEBCEAAAhCAAAQgAAEIQAACEIAABCAAgawEEPCykmM/CEAAAhCAAAQgAAEIQAACEIAABCAAAQiUQAABrwTInAICEIAABCAAAQhUQWB05SozPLra9A+Nmkm2A73dnWaK/eno0P/RIAABCEAAAhCAAATGCwEEvPEyU/QTAhCAAAQgAAEIeBAYHl1lhkZWmcGhlWbECnhxrWdyh+me3GmCP7s6PI7KJhCAAAQgAAEIQAACVRJAwKuSPueGAAQgAAEIQAACORAYGllpBqxgJ+Fu5arVqY4oM96Uni7702m67P/gzkuFj40hAAEIQAACEIBAKQQQ8ErBzEkgAAEIQAACEIBAfgRWWZFu0qRJZsXAiOkbHDUpNbumHZGYN9k68gi1zW+uOBIEIAABCEAAAhDIgwACXh4UOQYEIAABCEAAAhAomEA4n92wddrNnj7Z9A+utDnu4sNkXXcUIjvVuutGrcqn/ZK2Dw+DUNuCJ5XDQwACEIAABCAAAU8CCHieoNgMAhCAAAQgAAEIlE1AobGDw1Z0s8JbNJ9dMwHPGvNMzxoXnZx02q/fhtd2WnudBLnJnR3B/w8ON3LkrfaMuCXUtuzZ53wQgAAEIAABCEDgcQIIeKwGCEAAAhCAAAQgUCMCEuwGh0cT89mFBTyJc91WnJPTTgLdkHXlSaDTT1Sgk8A31ea86+3usKJeh82Zp20l8o2mEvMIta3RoqErEIAABCAAAQis9wQQ8Nb7KWaAEIAABCAAAQjUmYALjZXYNmwdd7757CTgWe3N5qybFLjr5NKTsy5NiKzEPAl+cupJ/JMjL6hga/syutLTmmfhulDbKfY4XZ32oDQIQAACEIAABCAAgVwJIODlipODQQACEIAABCAAgWQCEtlG7M9AINq1zmEXPpry2Ulsk3uuywpv2r9vYDSVaNeqdzq+nHwS4lQkw7n4fEXBGVO6TIfdT/n2qGqbvA7YAgIQgAAEIAABCPgSQMDzJcV2EIAABCAAAQhAoA0CLp+dRLGVvjY7e75eK6hJtJOwpv0aIbYrzYypXV5FLLJ2Wa4+JxbKpTdo3YHOndcsb54EPLXlVlRUo6ptVvrsBwEIQAACEIAABNYmgIDHioAABCAAAQhAAAIFEFilqq+jEtyS89mFT+/y2Uk8UzEKl89OTr2w8OdbhTaPoSnUNuiPxMTJjVBbJySG+xQV8KLnpqptHrPBMSAAAQhAAAIQmIgEEPAm4qwzZghAAAIQgAAECiHg8tmpIESa0NhoEQoXuirxrpnbrUwBLwrr8VDeTtu/1WOhwBLoZC7sG2w48Fo1qtomEeJzCEAAAhCAAAQg8DgBBDxWAwQgAAEIQAACEGiDgPLDSYDrt6KVCx31OZyKPSjXnJxtcrilLUJRpYAXHp/G4dx5Pdad5/LyyaXXTHyM8iHU1mfFsA0EIAABCEAAAhOZAALeRJ59xg4BCEAAAhCAQCYCymc3YCu+KiecQkglpunv+rdWTc41VXtVPjuJW3LaSfBKU/HVHb8uAl54vOqTil9IkOvsUM6+RqitHIm+Yp6OR6htpmXJThCAAAQgAAEIrMcEEPDW48llaBCAAAQgAAEI5ENA+ewGrUA3bIU7iW7RGhTK/abKq1EBT8465bELF6HotyJfNJ9dll7WVcBzQqbGruIXGrtESznyXBGMNIIlobZZVgf7QAACEIAABCCwvhFAwFvfZpTxQAACEIAABCCQC4E0+ewk4Lncb75FKNrtZN0FvOj45D6U81Bhw3LpuTx/CkH2bYTa+pJiOwhAAAIQgAAE1jcCCHjr24wyHghAAAIQgAAEMhOQmCQXnRxycoz5Ngl4EqfUJOBp/0Cgsn8W1eoq4PUPWn4JopwYyZnX290RuPQGrbPRufMItS1qxXBcCEAAAhCAAATGMwEEvPE8e/QdAhCAAAQgAIG2CUTz2fke0FViVb62ydZdpuMs77fVZ1M4ynzPFbddHQW8OTO6Td9AOgYKtXVFMHptEQwJp8qbJwFU+QV922Zzp5ilfSNmig3X7bICYYfsejQIQAACEIAABCCwnhBAwFtPJpJhQAACEIAABCDgR8CFxkogUk67FBqRCRehkLgkoUnCncJC1dJUofXrbfOt6ijgzZ3Z3baI6YRRiXqrrR1PRT7kaGwljEoEnDer1yxYMhgAI9S23dXF/hCAAAQgAAEI1I0AAl7dZoT+QAACEIAABCCQOwGJdkFxhTVikO8JnDsscIhZl53cYXFFKKb1dgWiEQJe+wJeeG5c3rzA5WhDbcVewqvmIRxqq5DcuTN7xgS86PxS1dZ3xbMdBCAAAQhAAAJ1JYCAV9eZoV8QgAAEIAABCLRFQM44OeTS5rNzRShUOTXIz2YFoyEbFqs/m+Vnc2GbCHjdQRhrmiqzvpMsMXVqT1eQN6+zo8OG1zZCbfuHRq14OslsYMN3Fy4dSjwcVW0TEbEBBCAAAQhAAAI1JICAV8NJoUsQgAAEIAABCGQjoLoTy/uHA7ddmvxpXZ2TTI/NvybRTkKRRL/AaeeZz04CnsS+Zf0j2TqeYa+6htAuWTGSin2GoQdzJN5yRmrO3FwvXjGcSjwk1DYLffaBAAQgAAEIQKAKAgh4VVDnnBCAAAQgAAEI5EIgnM9ulc1JN7W300hA8mnhfHZy1rkqqL6iXfgcEvAUpul7bp/+JW1TRwFvo9m9ZtGyocIFvCgb8Z81dfJYPsOgArDCpT0FWHc8Qm2TVh2fQwACEIAABCBQFQEEvKrIc14IQAACEIAABDIRkCgzYn+i+ewkyM2Y2mUFpOGmx+21IptcW932T1eEIm2107iDVyXgDSonnHUL1qVVJeAF82pFPAmoCoHWHCvUNgiBtqHUTpxtFgIdx49Q27qsKvoBAQhAAAIQgIAIIOCxDiAAAQhAAAIQqD0B5bMbsGJVq9DYOAHP5bOToKNKsRL9GtVn04XYJgGqSsALCnNYLnVpVQl4zfi7IiRy1vXaEGkVv1DevLSibTjUVsfqssIgDQIQgAAEIAABCJRJAAGvTNqcCwIQgAAEIAABLwIKhx0eXW2FllHvfHbKYzdr2uTAhSWHnXKjScCTWOcKUaRxYHl1dM1GQThuivDdNMdutq1CaOso4C1cOti02Ece4447hk8Owri8ec7FmTbUNsi/tyZsWnNPgwAEIAABCEAAAkUTQMArmjDHhwAEIAABCEDAi4DLZ6eqohLd0jSJd9N7u6yI1mWLGDQqz6YpQpHmXHHbIuA1qMiBt2DJYLs4U+8/zc67XHJpqgBrziT0ylEnQU7rRUKvXHpphF6dVw7PGVO7rWCcuuvsAAEIQAACEIAABLwIIOB5YWIjCEAAAhCAAASKICDnU5CfzIonEk7StGgRCrmppvZ0VSIg+eTfSzM2n23r6MDbbO4U89CiAZ/u57rNjCldwfHSCHjhDsidp7WjvHmdHcqP2Ai1lZjsK+ZpPlxotgQ9Qm1znWIOBgEIQAACEJjwBBDwJvwSAAAEIAABCECgXAI++ezieiSRpce6phoFChr5zAKXXSif3SZzes38xeU7wBDwGjNWpYA3asOu88gH6EJtFRLt8ua5IhijK2254iZt7sxus7zfukdDlW8JtS333sLZIAABCEAAAuszAQS89Xl2GRsEIAABCECgBgSUz06VUhvFI1Ya+7/ezRWhUD47iSFDVhzRcfQT54yqSkBCwKtWwCvSjai5daKxRunWXzRvXlIBDxdq29vdZbq7JpkO/QMNAhCAAAQgAAEIeBJAwPMExWYQgAAEIAABCPgTaDefXY+tGNoIZ2wUofDNZ4cDz3+Oitiyqhx4RQp4YU5ajw0xr5E3b9AK0s6dN29Wr1m0bMiG3yYr1FS1LWL1cUwIQAACEIDA+k0AAW/9nl9GBwEIQAACECiNgJx2ykEmwS1LPjsnjKjDyj8WOPZC4Yg+A5GAVEUVVAk7EpEWLRv26WYu25QlWvl2VqGnErGqKGIxZ0a36dPaS7lefMcWt53G63LdKdRWjrqlfSPBuvUR8cLHJNS2nZlgXwhAAAIQgMDEIICANzHmmVFCAAIQgAAECiHQENpGAxfSxjb/XJoCBr22+qcEEFUCleDhRLu04kd4YElhjIVAsAdFwGswmDuzpxIBLy7/XFFzHXdcjX3erJ7AKapwb61hFVWRmJ1WVCTUtsyZ41wQgAAEIACB8UMAAW/8zBU9hQAEIAABCFROwIXGxuWzU/jqI0sGm1btdPnsAteSzSsWV4Si3QFKyFmyYiS1A6rd81YhXtXNgVcFAzdvEs8eWz5c+ry780fHrrx5EqZViVbuOgl7uma05n2r2urYhNq2e2WyPwQgAAEIQGD9IYCAt/7MJSOBAAQgAAEIFEJAop0cds5R1Owkce63aBEKVwBAxSjSCBm+A6vKiVWFeIWA9/iqqMp56XrQ1TnJzJnebcO3h9ZZqgq1ndrTtSano9ymcq0qr+No6muAUFvfOwHbQQACEIAABNY/Agh469+cMiIIQAACEIBA2wSGbHL+tCGtTjxbZZW5KUGi/04j8SJNEYp2O46A1y7B7PtXEUbselu1gCfH3bQpXWaxdQG2aroe5D7ttWG2ypsnR54rgjG6Mrn4RfjYhNpmX6vsCQEIQAACEBiPBBDwxuOs0WcIQAACEIBAzgRUgGJ4VHnoGvns0uahk4AhR1iHVSi0r44hh1FaUaLdYVVRzEB9rqKAQ90ceHKhzZpWbiEPt16qqj7szj/FCnIKl1X4dpqm66ZRvKUz2M05VNPmzdO+Or8rqtFlw3ZpEIAABCAAAQisXwQQ8Nav+WQ0EIAABCAAAW8C4Xx2Eg7StDEn0RrxQU4iiXcrBkfNgM33VVWrUtSSC6zMCqxVjjVufiVGzZjaVWolXtePzeZOSVVAJe/1KQFP4a3L+tMJeOF+yMHoKjHrWIPWBevceWnCzV04r/LuqV+aFxoEIAABCEAAAuOfAALe+J9DRgABCEAAAhDwJiBnz4j9ScpnF3fAcBEKhcjqGI1iFg3H3sypk4OQwIkq4JXtAkPAe3yVls0+en3MsOGzassHRr2vxVYbSiB3zjxX8MU3pF3Vnaf0Ph7O60Jte2zIrlx6HfoHGgQgAAEIQAAC444AAt64mzI6DAEIQAACEEhHQPnsJKplCY0Nu4L0d4l1QZif/bNoESPdKBtbS0ixWqLps07AslvZLrA6Cng+eeDynpcqCohEx1CkeC0xLyheYUXzqdZRJ7HcCfBxobZJ4byE2ua9AjkeBCAAAQhAoBwCCHjlcOYsEIAABCAAgdIIhPPZSWyToJWmPZ6XqxF655w/SXm5plnXj8w9ebmQ0vTZbZu3EypNHxDwOszU3s7UeeDSMI7btg4CXpliqq7PbuukkxAnYU+hsrrO5X5VqG2aa6DLXrA9Vhgk1LbdVcj+EIAABCAAgeIJIOAVz5gzQAACEIAABAon4PLZqXCEXHJpm0QBuXskDEgEkCgg516aIhRJzp+0fcqyfRrxIsvxW+0z0QW8qua/yuq3bj1UWTxlak+Xded1mM6ODuvOy56LklDbvO8IHA8CEIAABCCQLwEEvHx5cjQIQAACEIBAaQTkiFO1yceWD6UW7eJybEm0c/nssgxCImAVIZThvuZRTCDL2LVPXYtYSOCabCvEjqxcnbq6cBoWVQl4VRbPcHzmzuw2S/tGUgneadj6bOsKy8y0lYB1X5AA74pgpBHi3bkItfWhzjYQgAAEIACB8ggg4JXHmjNBAAIQgAAE2iYQzWc3b1aPWbxi2Es4cEUo5LRT6N2QFQCDfHb2J02Vy2aDqIOQUpWIVEcBTyyUN82Jd5pzObQUEi2nZh5zHhVPJfosWZG9EmuWCyRwj1YQuhvuq8TbRcuGChVIfdm4e4KqQrtCGNrXXetJofBx5yHU1pc+20EAAhCAAASKI4CAVxxbjgwBCEAAAhBom4ALjW1Ue103n52cP8v7bdisFeNiH7yt80rVJyXayaEjh13gtGuyfTsdlkC4wYxus3DpUDuHaWtfVeDstWMtW0RyAt7CpYO5C2PNgMTlXXOh0BJunGATLjji8htqPShnWp5iXlXuxypFWzc3EvDKnPtWF0mcmBguRiMhdzDkzksr5BJq29Ytip0hAAEIQAACmQkg4GVGx44QgAAEIACBYghItFPom6s02eosrUQcl8/OhdEVIdqF+1aHYgJVugDLdmG5uV9pQ2Nd/kJVKHVFDZKEmbzFPAlpcmqVXcSkDgJe2fkPW90TkvoSFz7vCtVo/aRthNqmJcb2EIAABCAAgWwEEPCycWMvCEAAAhCAQK4EFBqrh2g55OSM8m0q2jDJPpHLnSfXlUQ7PYS380Due+647ZLEg3aO7bPvRBHwuqyzcs70bjPZho9q7eSRv9CFWyrM1lcEDM9JVQVEqhIO3dgliM2b1WsWLBn0WaKFbpNWRFff5cjT3EsE1r3DvTjIIvgTalvo9HJwCEAAAhCY4AQQ8Cb4AmD4EIAABCBQHYGGyDYauO3SOl9cPrvpvV2BiKOH7kaYbfpj5Ulgkzm9Zv7i6oQMCVuzbBL/RcuG8xyW17GUe+yx5cOp59Lr4HYjFwYpocW1FYOjZsCGROfVnKCjnHLdXY0w276B0eDPJEdfVQJeVed1zNOKZnnNVdxxnLCbNYxdArheAshVJ2HPCbk+8x/tD6G2Rc40x4YABCAAgYlIAAFvIs46Y4YABCAAgUoIhPPZSWxL28J5rPR3iXWKeOu0otViKxzVoZUdRhodc5V5+JSPULn30oqxreYtXHhEf3c561RVNC58Os814EItJRh2dnTYvInW6TfYPH9iVUKazqvroM+KmVW0KkXj6HiVA3KKFfXzuB9o/qf2dFl3Xkcw/+0UQJFLUutI61bioKrk0iAAAQhAAAIQSEcAAS8dL7aGAAQgAAEIpCKgMLQR++OTzy7uwC5PmR5644pQVBkyGtdfiVhL+0a8quKmAum5cZVuqLwEvLWFs4ZQG1d4pGgBL4w83KewMyscZikhbVQhmDk6An2mvUwOcf3JUzTzGW+rbYrKB6j577HuPBWI6bVFceTIc7k1JcoltZlTJwfCthNZCbVNIsbnEIAABCAAgXUJIOCxKiAAAQhAAAI5E3D57OSyy+LGcpVEXREKHUcCYNyDcpWOs2YCXququDmjjj2cXIBV5CNLqgicNPaggq7NReYqyCZVC65KuAo7s8JinvotYWeiCXhFiWZJ6yXu87JckO7FguZczVU8bpY3r9VaJdQ2y0yzDwQgAAEITEQCCHgTcdYZMwQgAAEI5EpglXWWDI+qcES2fHbO3RQ4XNaIIGmKElSddy4Mc86M7iBnWpYE+HlNSlWFNLIIeGGxdsQ6mQKx1tPBVpWAF56nsJjXY51Z/TaMNUl4zGue3XHEoVVob97nix5vmg1ZlQhVdvXduHFVsSbCof0SdAdtURXnznN5E5UfcvGKYS9nLlVti16xHB8CEIAABMYrAQS88Tpz9BsCEIAABCol4PLZ9Q9ZscqGOKZt4dxmeugdsmG2WYtQ1EnAq0JAiLKvu4AXFu3k0Ewj1obHWgfW0f5oXaspZ5quDa1pnxDLtNdPePsswmk754vuW5brzafPEtAHrIg6mOGe5HP8pG2iodZyZCpvoxg9Yqv0JhVCiR6fUNsk4nwOAQhAAAITiQAC3kSabcYKAQhAAAJtEZDTTqGscvvowTRtU7J7uZQaSeEbuc2C0LM2H7aLrn6aZpxVFxRQXxVCu3BperEgzTjjtm3lPtR8y6mluZeIoeqx7VYMrqOAJ+eVHIQab6NwQVdQ/MD9e5aQ8qR5qTrvYp3mIY3TLYlru5+PVTTWOrBrP5wLNItDl1DbdmeE/SEAAQhAYLwTQMAb7zNI/yEAAQhAoFACymcnQUIPnBvO7DHzFw+mOt/juaIaVRflRgmcdvZ4ebWqHUjhcdTBjVRVJdxoKKdzWU634oXEjD4r/GbNixi3VuokHKl/zUJZdQ0on6M4OEeW3Hlp3VjNrpeq5tv1p07zUDWLuDlyeTpV3EbrQCGy4dyJWhNZ1gKhtnl9g3AcCEAAAhAYLwQQ8MbLTNFPCEAAAhAohYBcdnLEDVvhTmKL/d+x5huq6ooR6GFVjiOJdhICiwolrDpsLjwxdUjoX5UjMRBy7FwbK9ZNta4j57KU266Iua+TcKQ14JP/0Ana4pOXmFe1aFUnAb2q8PFWN+e4Kr3h3IkKt5ZLU/fJrMIuobalfD1yEghAAAIQqJgAAl7FE8DpIQABCECgegK++eyahac5p5UKUKgQhYSJrHnNstCYOXVyIBT2WaGo6haIl1acWbJipLKulC2ouLxfzn2o0NgyCjnUTcBLyz0vMa+qqsNugVclGEcvMN2H5lqXcBUVmFtd7AodV9+W9cffE8aK+OjeYVMM6P7pimBkEb4Jta3s1suJIQABCECgYAIIeAUD5vAQgAAEIFBPAnLEyfEhscU3n11YoIgWoQhy2dkfFaPIEg7WDqU6hK26/kuUmTG1yyxaNtzOkNraN62QlPVkzmkp4VZz32lzHEq4860im/W8br/xLuCFxx8U9ujtNN1dnYEbSxzF1Odaqtp1VrUD0HFUjs0507tt/sehdpdWrvunfcHweNqBzqAf7t6aNe0Aoba5TicHgwAEIACBCgkg4FUIn1NDAAIQgEC5BFw+O7k7siTTl2Ai4a7DWkbkGinLaZVEqQ5hq2ERYda0yZUKeD6hnElMm30eriA7slLh0Y8LTWULamWfL4mZhFM5L7NcW+7YrvDBNFu1VHnShkcfLxrTTMzzDW1P6n/Wz6s+v+t3XKhq1jHluV87If6uGIrLmzdoX7w4d56PuBsdB6G2ec4sx4IABCAAgbIJIOCVTZzzQQACEIBAaQRcaGxQNMI++IXz2fl2IizYSLiTOLF4xXAhOc18+xTdrg6uN9enOoTxSdgalIOrzeq+YVFSBRhcTsNm4dFyQo6qUrE9dxltfRTwwtxcaGUjn+DjYl7YiaVt5s3qrTRstC4CXp2E/PA85hViHM6bJ3HX5VDMWhgmHGordjQIQAACEIBA3Qkg4NV9hugfBCAAAQikIiDRTg6NgUC0S1/pVQ+JymOnsEj9hPPZTbYhalOskLN4eXXhoXEw6hY6V7WgkYewJSFS8z/NhnXK6aNCFFpPrdxlE13AKzKUNCreuBBbzUeVed/qIFi7e0KdQunD9yndDx5ZMugVDu17s3dOTV2jEni1Dtw9P22orZvDpX3DwTUvt1+XFQhpEIAABCAAgboRQMCr24zQHwhAAAIQSE3A5bPL6sQI57PrsUnU9SDYcO2tLdjUyekWhqSH2Y1n95r5iwdTsytih6pzkmUV0sLrQH9XjkQVBvENCdV55fIsq5hIHkJlnvNfpIAXXe9Te7qs2NIRhNmqPWZF9bTCTR5j1zrZYEY98s4p15xeOJTlAPXhV9a9SfdmOWRdqK0TeMUjKdRWoccK2Q7n7STU1md22QYCEIAABMomgIBXNnHOBwEIQAACbRNYZVWS4VHlHxsN3Ha+Akv4xM5hJRFAf5dYF+Qza+HaK+thNAugqkWzcJ8l5Cxcmq/jJg2TNE6kqGjXTl7DNOdNM55m205UAS/MQ8KNOOgeIDHPOSXLEvPqJOrnHTqexxqtwh0cvreHQ237h0ZjxbykKrlUtc1jJXAMCEAAAhDIgwACXh4UOQYEIAABCBROIJzPTkJblvZ4dcOGayeLWFNEOFiWsUT3Kcv95NPXvHJe+ZwrbhsfIU05r4JwOSsAaT0Fee1sBeF2ms952zl+dN86CngLbKhkmU3XtNxTCmsPFzxQzjwJNnKjZRH4fccQVCK2a0nFO6puuu7qlp+z6rx8Lo9iUInWuqvlyAtSLITWRdoquVS1rXqlc34IQAACE5cAAt7EnXtGDgEIQKD2BCSojNifrPnsNMDgAdsKNQqvUiiVhBqF3I7aCqJZWh0fkjUOVQBd3m/ztLUpQmVhEt2n6r5INFAI3PKB0bW65gqSaD0MaV3Z8Ni8Cl3oRHLyyK0TPW8eTOOOgYC35vqOEdBcSKVCbVeuaog2Cm1OCqdMO1dVC1Th/tZJxHf9SnK3peXd7vaPv8RpFK2QeC9Bbnn/SKZ7AaG27c4I+0MAAhCAQBoCCHhpaLEtBCAAAQgUTkDimtwRWUNjnePCuavCRSjycOJULU41m4A5Ng9XnxWs6iDgVd2XsKgSriKs+Xe5sfIWcjQvzYTDoi6augl4VYRx+whoTsxTJWFXubRZOGXauSpbtG3Vvyr4J/GqY14+12fn2NS6CMQ8+92j7x2JelnuD4TaJq0GPocABCAAgXYJIOC1S5D9IQABCECgLQLhfHazp3ebhxYNpD5eOI+Zch7JXRXks8v4INaqA2nDrVIPJuMOdXpQrlpYkqii6rFqTrRLqiCbEftauyHgTcl0/bbDXsx1zS+zDiqf5hxYqlyah5hXduGSZmPUi4t5s3pN2SHMScwl5uftdE06Z5rPXV5TVckNF0ZxayNrYST1gVDbNDPBthCAAAQg4EMAAc+HEttAAAIQgECuBFw+O7lgJKy4liY8VcnRp9hQSDnt9BCWJZ9dlkHVLSTMjaHs/Gut2FUharjE9RJm9HcJd6pMmofr0ned+LjBfI/ls13VQmm0j1U4wNpZ93mIeXWZgzpVww2vizqG9Yb7F1dkQ98n4G0fJQAAIABJREFUEoX13eKEXjnz9B2T1eFMqK3PHY1tIAABCEAgiQACXhIhPocABCAAgVwI6MEnCE+y4bFyN8S1JLdGOBxS+w8ON5x2WR+qsgxMOfWmWIeXkubXqaV1IhXZ93ZElTT9iqsgqyqkHfYJfMbULrNoWblzNNEFPIk1ZTvA8lprwb3Fuja7uzqDnHm+odZ1qfxa1/uSiv7MX1xuYZM09xCfa9aFYOuFke45bm3oe4xQ2zS02RYCEIAABNolgIDXLkH2hwAEIACBpgTS5rOLPozLCaEqoa4IhdxUTrQr01kVHqAcG7OmTS5dHEpaZuFqnEnbFv15kWKiy3HonHZxzsuq5shHDMiTfV3cX25MVQh4eYeOO/eVBGBVsh0etRWKBxsvHeLEGuXEXNo3krkoTl7roey159NviV1zZ/aULur69M1tkzYlgnP69nZ3BC69PMKwXajtZPtdp/s4DQIQgAAEINCMAAIeawMCEIAABHIj4EJjA1ecTQhu9bZUTS6SaVO6AoeDRDs5HiQC6v/LyGHm01mXM6lurhI9+FXhOotjFlT+jakM6sO32TaumrDWhctv2KyCbFXhhM7FtWSFXz62dnho3zoJeFWJNUUyCIvFEmuc8yrs+K1LiGheTsR212R4/7jw1DyPn8exklzfrc7h1kcgwE1u5FSUy1xFmLK+YAqH2urvHaqMQYMABCAAAQisIYCAx1KAAAQgAIG2CDTLZ5fmoOH8ZXIh9NswSIk0KkaRJUQpzbmzbKuwMCU9r1PfqhJQ4vjlJSa6kGmJdq4wiR6Ok1pVLBDwyndblRXCKrEmXOTAiXkqvLNwafX3grydiEnXmM/ndXQFRvudpwDrcirqfqXmXjRkTfEg7a7bCoN6kSWREDHPZ9WxDQQgAIH1mwAC3vo9v4wOAhCAQCEE5IpTKKtccc3y2SWd2D3s6MHEFaHQA48eiOvmbouOJU2xjSQOeX5eRRGBvAW8cJ7DdirIVhHOWXYYc5Hus7TrsirXoxxUfQO2GI4V+8tqYTGvxwosK+z5y87FGR1rWUJmGsZ1dAVG+1/UPVPuQwl5+n6Te3PQfmcGOWDbqIyuY+n7UfdFQm3TrES2hQAEILD+EEDAW3/mkpFAAAIQKJRAI/fcaPAQkjU8KCzOyL2mY6kS7ejKx2Nt6yqOheFWIRr4TG5dnIFpxRxtr+q+yiuldaFCFO2GTBf1YN5qHvJyHvrMtbapm4Cn/pRdOKTKHHQS8ubN6g3uYRJXlDPPVdYuU1DUWqjjfbNO6zPumirLqRt1b7q8eRLz0n6Xunt8pz1oj9JM2FQFhNr63jHZDgIQgMD4J4CAN/7nkBFAAAIQKIRAu/ns1CmXIyhwItjQWD24JOWz0wP58v5yHTVpAaZNfJ72+Fm3r8tDvBM2WlUkdRVkp1vhTttLIO6zwl3aB9ooq8seviX4J4kHykW376Y7ZcWZej8EvPIFPK35x2xF6HbXTerJtjtEBSD9vwQVhTxOsotaYl47+dDS9CnPUNA05221bV1fdLg+VxHi64qk6DtRhXhc3jy9sEgSfZvlFCTUNq8Vy3EgAAEI1J8AAl7954geQgACECiNgB4gRuzPQFCEIltImhNm9HCi0CGXu8zXUVVXcSw8CXKLaZzL+sspVuC7AOokfsY54MJrQ3/XmpDbLuzA9B1rnHB3+fyGeKemh1133DdvslMpQt5EFvDKHrub5yqFq1bVjsWj27rylDdv5apGcQMJ1EXlzazCcZp0rVY5N0l90+cK8ZXQWuV93K0Tib66J7rcinFVj30FR7lBlTsv+JOqtj5LgW0gAAEIjBsCCHjjZqroKAQgAIFiCLh8dlnCecJiiXJBSbQL57NrViW01UjqKo6F+6yKqFOsiLfYOn/q1OoUsqZQL+UyDLswJ1tRTaJd4MLMKWfZXcv/bS6zwt3dKx5YayrCAp774Pinvt1sO+PJhU2ZHsDLDCOt03xXKeBVVUTCN+ehy/fpHFdym8qdl5eY5+N4LWzRtzhwHUXFcHfrdP2oX66Yk1IJ6OWXC7V1ayXLyy2q2lax8jknBCAAgeIIIOAVx5YjQwACEKglgVU2Afbw6Opc89lpoI0cee0LM1UJAWkmq5XzJs1x8t5WjhI7vYHTp+om940eQBU67aoxZhF0k8Zx3L0XrCPeaZ84AU//XqSIN9EFvKm9nUHYcpnNCcVlntOdy9cRFe5bEWJe2pyTZbAqK79cO2OpS8qBuDG4Fx9y0fXal2O6l4rpclswxacSd9wxCbVtZ7WwLwQgAIF6EEDAq8c80AsIQAAChRJw+excgvWsJ5PzTLl7FBqmnFMS7eTgyyME0vVJDy4bW/GnzpVo69rHqt2L4SIlHRaShESFyOblNIquW+W7C4fNhj/vtG6/laHiKO6zZ07fwpyw9TuyXgIt9ytbSEnjIGomaOYFIpj7CgS8Kl1eEvDklMoaghkV81z4ZNrrpY6OYF93Yl7rL8tx6lL0x6fv4rmhzffovmvdS5F2nMyE2vqQZxsIQAAC9SKAgFev+aA3EIAABHIj4PLZ6Rf/pX0jmUIWXc4yiXbK0SOxLqkIRR4DGA8PVnXsYyCwWlGhTBeUhCEVonCirlsfEpeKLkby5ttObLrcJODJbRonhly+46fzWKbrHKNs11GSgBet7rvKwsg7fNNByOJGy2MS5PRsVSwlj3M0O4Ycr2pyRbXTXGEDCaDdXZ1Bzrw+e0zlD/UR86pi32rMdexTuL9lX6vtrA/tG+6v7rlBYSh7v5eAPGi/l5VjUaKez3qJ6wuhtu3OEPtDAAIQKIcAAl45nDkLBCAAgVIISGBTeI1+mXdVGWdPm2zDb1Z7h1VGi1DoocAVosj6cJB28HUqxtCs73UMvyor/NjlappmBQetCeccClcClbg0aNdiEWGzmpNW7jv3wCvBKm7NFlXUomxRoJmAJ/FE+dbUn75BOwf2GtbcOMeXHv4lEuUpsFYh2JTNO3ovUE4yhTZmDWmMu7e40MnG/HXYFy/2pYmdw7iiBm7/vITEtPfpVtvXsU/h/tbRtZhFENV6UaGUaN68dnLaEmqb55XAsSAAAQjkSwABL1+eHA0CEIBAqQTkMJJAMmyFO/3Crvxn0eYTVqk3+noI0Bt9V4Qiz0IDaaHMmdFtBmzoZVHiT9r+xG2vPsol004IUx79CB+jyBBOJ+zKbac14pxczcKnixA3wmOto4BXdjGBsICn+ZFoIidkUqEQ5/iaMbUrcPAozFkiVFiATbs2qxLwNrDX4cKlQ2m7m8v2SQ7Idk8SFvM0T04oj95zir7WsoyjaDZZ+hTex+d7sd1z5Lm/TwELd11LoHcFU/QyT/eDdr6nCLXNcyY5FgQgAIH2CCDgtcePvSEAAQiUTiBtPrtmrqxwvjK5lFwITju/6OcFYzw8XPk8UOXFI81x8kzqH3Zj6u9JwlC4n0U7cHwEvNV2YYdF7WUDi4Muvucpe5t9N90pDVbvbcsM6ZRIMsk+tSv8TQ/vCuXUHKUR4rSfrjcJ+HLlZQ2xlYCnfrQbTuoN2m5YdTGZMkX8qNMqLOYV7XZNMydu2zo6lMPjqLvAGGUuV7peGKV5qaXveAn6urblqnNrppWbM2mudZwp9njueu/QP9AgAAEIQKA0Agh4paHmRBCAAASyE5CoJoeMHs71y3eapge/TTeYYh5+bCCoCKq38/rRcVzl2DQP/GnOnXXb8RDeVFeRMQ8BTw9nQY6lNRVks7gxxUfPdkUJOkkCXvBgaQW8geEBs3DFw2stxSf1D5stBobNrs/c1+y67b5Zl2nsfmUIeE58n2oZD1jn7fL+kVwKyYRDbNMmya9CwCsrZLzZApGoovyieRbx8VmMUTFP+yy1ayDPUF6ffrTaRtfBomVDqcTkds+ZZv+6C4zRsbSbc9WlPYiG2qqwVdbUGLrFTl7zO4Vy5CLmpVmBbAsBCEAgGwEEvGzc2AsCEIBA4QTi8tmlPalzUM2yuZr0y7Ue9vVgntalk/a87W4vZ82c6dWFxvn0v64iox5MH1s+nPrB2YlCEu5czsN2BIEyQipbFbHQel+w7CHrWBlYZzq3XzpgZtvcYmpbztvWfGDnE3ym3GuboqqiumtZzkYJ7hJVFdom52w78xQ3qLBApDxseshXReFWD/pFOy7j+llV5VvXlzqIVK4ittaE3Jiu0niVTuq6VukOr6F2BTGvm0FOG+Wd69GFZuv+0Tu58TLP3UeyvsxTiPe82T05jZjDQAACEIBAMwIIeKwNCEAAAjUh4EJjGwJbfD47n65K/Oqxv5TrTbsLe1RFTj3w5/2g79OfrNsUJYRk7U90v6rD95qNI00BkHAYtROF8hJ3dexpVmxabMXEotpx915g7l7xQOzhFy5/yAqRg+t8NsteW89atraol6eIl/e6DSoLW1HV5baTo3GsQI0NoS1CwAtDcxUvlftQD/oqfBEXgleFgFeGSNxq7ebhds3j2nBrTvf7RgGTLiu2yn3auOdnFWWy9i1vwSlrP5o+/Fjn2MbWITh/8br3h7zPlcfxin5ZFHbeqr9p3bfaR47rWbZgFg0CEIAABIolgIBXLF+ODgEIQKAlAYl2wQP4GldcVlyP/wLeERwimqusruGercZb9xCnurpMkgqAuIIlEnjlqFIBg7xEu/B8lhHeeNfyf5vj/3nhOstIue6WDTby3UVb2H0X/iwvES8PAU8CiK5ZzZEqSOuBOk58LzuPl5vTuIIKEvCUb1BOvbKaxCr1ZZkNH62i5THX7fa7WeEUl//MCa/6nklyUbbbF7d/0YJTu/0cDw7v8BiVb1WCbFHpCKL3bb0skDtP19agfeHh8uO2cuDKMa/rkQYBCEAAAsUSQMArli9HhwAEILAOAYXGKvdclnx24YOFnTn6xVoOOx07Lh9TGWJK3lOdJETlfb4sx6tjGFZccQ2X/0iVCfXA3zfYCKUu0plTZEXc8FzFiXj/W3xf7HQ2E+/cxp978xVZlsFa+7STA6/hnuoMnLM+c1S2gOcGGg6x1b/pfqY+y5lXpsu36DyLrRZD2RWHm/XF5zpzL3hcZdKshUp8L46qhdWkflbt3EzqX/Tzqr4Lo7kWW+XN3ciGz3ZZwY8GAQhAAALFEkDAK5YvR4cABCAQEGgUixgN3mRnFU1cDixXXEC/TAfFBTyOWVe3WKvlUUVIXtrlWkeXoOOmtdGoQNgQhLRO5LYrK+F+mQKHRLzL5t8ShNMO2Zx30aIVmtck8U7b5FHUIq2AJzeQXFIuRDZNwZCqBLzwdRIVhxRiW1b+tSrvEXUJE03rditDzKtrhW63buvev+j3UF1yLcqRp98/nBCs32f0vaJIgk1soSwaBCAAAQgUTwABr3jGnAECEJiABML57OR0ytqcaKdfmPXLsysuoGOmrRynN+QqblCWgJN1zG6/tA+m7Z4vy/5yRvTZnGRlCRZJfZRoNmPK5OABa5VdINFQ6qT98/687BxhEvKuuPdKc/dDfwqchqqSON0Kma5gRdL4yhLw3HUt4U79VGicjxAf7X8dBDzXJ/XFWCew8m3qXiWxuOj8axLwRm3cbpmuPzfeuuTAbMdN5oqAuEIGEo+zfLfUeV3GXfNVOdqS7j9xn9f15ZsL0Va+RV0LNAhAAAIQKIcAAl45nDkLBCAwAQhIxBmxP+3ms9Mvw1PsW2696dYv73qwD5JK2z/baePpoUXjHA9hv3Vxcrhw6qlWEFIYdYddOAuXDrWzXHLZt2wBT52+8a7LzI13XxZcOxLK0gjWeQl4i5YNxTptw5V+dU2364ism4DnCmqIvcJbXf61okI2qxx/cM1ZoXzJimry77kLNA8XouZLoquKzujPlauaFyvxuTHU0Zkc7ncdHG0+HLXNuHiRRf473+lkOwhAAAJtE0DAaxshB4AABCYyAYklcn+0ExrrxCq5phRGp9YIubXhsVYQzKvl8aCXV198jlNX50G471UWBwmLQWFnpkQrVQNctKy46q8+86dtqnhQHhPw7PnlBqtawHNuO11/rtJvXo6xKgWs6BpQXwbl4Iq8aHAur+6uzkzVLVuttSrH347zzff68dlOLxHyzD2o+64Lk+zs6LDfQStNv82ZGVd5uFn/6pgb1PV1PHyv1OU7xmf9aZsNZ/UEL9xoEIAABCBQPAEEvOIZcwYIQGA9IrDKhmsNj6oqZHv57PQQ0WN/4dWDkkQ7Pdg70S5rjrwkzHqTL4dFHYSdpL66z+v8IKg+lu2OcKKdWzNxORDLzD2XNI9zZ3abpX0jqUS0pGP6fP7Jy98UbCY3a9kCntxHClWfLCetdaHpT7loFSab97VdpYAVnQf1RUJPs5cO4YT4cojKqdxuVdSkc/qslazbVFlAI9znZsJp1nGF94sWMXAhtq1eLNVdIBtvFWjrdI03W1P6nu5QvgIaBCAAAQgUTgABr3DEnAACEBjvBFw+ux4rgD1qwxKzPoSHi1AoRFbuPd8iFHkw1PklLsxfPJjH4Uo5hgSgMpPipx1UGXmwNG8SC3q7O4K8hwq7TMqXttncKeahRQNph5P79lXN39d+fpy5b+FdgXg2stJC82xxVWhvWnrRWnvvMustTY/WKGzQHYQwO1dkXm67uJPW6eE+jZim60YvL1yIbdZrvKr1pbmQo9K+dwlEyCpbWSK5r5jnUxW3Sl51cU76MqjCxezbN22nkOt5Nr8uDQIQgAAEyiGAgFcOZ84CAQiMUwJy0rgiFFlyyOlhRg+qEl/0i26Qy87+6OE+bRGKPBDW3dEWHWNdcsw1Y1+U2yRa5EDuTAkFvuKxHvoWLh2sZI2FWVVV5ONfC+4yX7/luFQCXjT/nYS7m5atLd65se0y8y0mLORJFHDVfrVNWcVi6iTgZRXTXK5L3R99HF7h9aVzKged73WRxz3UHaMu7KsQeFqJeWW7ktPOad2/U8LjKer7JS2zVtvr5ZJSNtAgAAEIQKAcAgh45XDmLBCAwDglsGTFcPBQqaZfVOXoWWJDAls1PZA60U7bVV0JNPrAm9XtUsUUVpljzne8eYmi4YrD+ns766YsV04SoypFDol43771eC8H3pbztjUf2PmEYDj3Dd4RCHf3D93RcngKGPvI5p8z28/eca25KpN9lXyjcLIKeO44rvCFnM5qPoUvqhCvXH+LDF1Nuq7Cn1dRKCZ8ft2rnKtNOfNUAEOCatXFPZoxrMu8+czxeCjkNIcCFj5TyTYQgAAEciOAgJcbSg4EAQisjwT0EPnY8kY1z1a5c8K5yeSsU1GL/qHRVPm3yuA3ntwH4jEeHmDaEWxcwngJvsqJKHdmEFbdZvGSqpxv0TVcdZjhsuF/ms9cfUTLSyvqvDvqv3u03F6pnpTvSQKehIpTn3TdWg6wdoWsNPcB8R21fSgyTNe3P3m64R5/CdIZFE/os/kD466JKgW8Mue52RzUKd9l+H4tN6XmzVUlrsIh2YxZlWvG91py242HF1gb2fDZLjvfNAhAAAIQKIcAAl45nDkLBCAwTgko/92CJQ0BT825rfT3hsuuIbzoYaXMfHZZcdY9vCk6rvEQQpQltFrz4NaPwqkHbHhstHpn1jnWfnVxZlVd+VgP6wuWDBpVpv2XzYmnvHhqctxtZX923XbftTB/Y8GRsc47rUPltZN4p7xnKmbjMus9pWd7876NTh07TpnCzvoq4DmY4YqoEoWU/zFc+MLNbzvXStZ9XbGSKsWpOuabc/dDXScqtuPyHPo4KrPORZr96pIf1KfPdbmPN+ur7oebbDDFZyhsAwEIQAACORFAwMsJJIeBAATWXwKP2KIPekhzD0sa6WQr2qmKohxTSQUF6kRmvFXgE7u8QlSLmgdfV2NcBVmtnyJyIVYtnDnWCq2T8LKsv3XYeVFzkzYXYNR9pwdUXfcS6yTaSZSIa6dsfu3YP5fpfqyTgFe0oOVCbMOCkHJvVVWspQ5OLt1TVFl8sc3VWpcWtw6co1J5IvWyqyoxr1FkpicQ9cdD0xpTBECaStpljksvoTaY0V3mKTkXBCAAgQlPAAFvwi8BAEAAAkkE5KxT7js9QKpJsEvKg5d0zCo/r7sgFmVTpqMpy7y0CnOSYCrBQU4UicBluTSrFs4cx8BpaB/aq8qHlUZUckUrdJ132v/oTwl2Pg6rcFGLNNVYs6y38D51EvDKFLSccKVq3itseG3wIqXNsPO0c1F17jn1t44VVZO+X6oU88aTA308uM8loOv7jwYBCEAAAuURQMArjzVnggAExikBvf1WMQs9II6HnGxJmOsuiEX7nyVENYlBnp9HXTCu8vC03s7gNH2DDaemjxCUV7/q4syp+nrxzcumOftF3yXmhsXfDRyRq+x/mrnt4uYIAc+YMgU8zYHL/6aQWlX5VoizXNHhENu8rqfwce4cHTB3rRw0s6ZONkvXOEu37ew123WVH0oo8UQu0eVWxKxDS5uTL3Al2/tk7+SGM89VIS7ClSw+4yGnnJvH8eCW33BWT/A7EQ0CEIAABMojgIBXHmvOBAEIjFMCEu4eXdrIgzce3oonYfYN+Uw6Tlmf1yUctNl49aClMCI9RMttpzUil6bydVUV+lS1cBZ+CJVLY9GyakL8ksRqOZgU1icB7wfzLzTXLvxOpmUdFfAGrWs3z5yGzTpVNwdemaGJ0XBIrflwzrW8q21LuLt0aHEg3ql12TWjAiKuScTbr2dOqUKe7uUSvupQxCRgYu+Fqkq6cM33pe/FpHumQu1nTO2y12Kjkq3mT2PLU8yre065MK+6i40SjiXaq6APDQIQgAAEyiOAgFcea84EAQgUTODmX91m/n7vA+b5Oz7DPH+Hp+V6tvmPDYw5chSWt7RvpPSQrbwGJNFCuWvqlDep1djqGvYkAUGCgQSgHusg6beCXR4VZPOY57rkeqq6H3ECXjisWUKrmzMXQpuFf1TAc9U3sxwrzT5ZBbyBKy42g1dess6pup6xnel90/5m8jO3T9ONYNuyC0pobUmQiROHnYDtCl9ontsJsZV49+n+h9diEhXw3IcnTt20NBFP4y9LLPZZEHmE9EYLlwyO2Mrc1sXczvy5vuu7e7F101f1YsWHodtGczsyujpwlNax9djvPuUTpEEAAhCAQLkEEPDK5c3ZIACBggi886OnmSdssmEg3n3n8p+YXV76HHPwO/fO7WyPLhsKXFVqs62jaMSG1db1F+ukQWd1SSQdt6jP69ZfJ4Cq+rBCY/Uz27pOHrGJ0fN0i7TLsy7VFqvMFeby0Sl82bmzJBDILRktPnPf4B3mmwuPzIT9vfNONVv2NkQvuaLuXvRXc/uCv6x1rN23OCDTsVvtlFbAG7n7DrPipGMS+zH92M+kFvHKnmcfl6krfKFceQqLzlI8IU68k+dIzqNmYfFliXgSqPUyqS6CVN6uMc3f1J6uIERaYqwLsc0q5iXl50u8MErcoO5io+Za7moaBCAAAQiUSwABr1zenA0CEGiTwIPzHzV//Mvfzd/++R+zy8ueGzjt/m7/fvRp3zRXfvPE4Oja5tX7H25uuOT0QNTLo+mBf/mafEd1dYSlGWddxB3fPlfdX1dBVs7FIRtSLdEuHLZWtwdpca3Lw2qVc6f8iXJKya2lOUtySH5jwZHm/qE7fJdlsN1TerY379vo1ODv9yy5w/z4v5eYe+2fcTn0tp61nfnoDqekOn6rjdMIeL7inTtfWhGv7Hl2+dN8C6S44gm6hhWa2ScR16PwxbF9D42FzTo2ihqcZNWlZgKewmlPmrZZbvPc7EBl5x1MGlCRIartinlVu4GT2EU/r8v9u1m/FSqtl1k0CEAAAhAolwACXrm8ORsEINAGgT/c/g9z2pe+Z97+plebGTOmBX8/76wjzENWsDvn/B8Ef3dNgt7/PfvpZq/XvrSNMz6+65AN43GhWo0HgW6zYEkjL954bHV/ux9lWkV/nWjnU0G2joU2qmAWdy1IZFi4tDx3ogttdrkT5bpaPjDi5Y7M4sJz7juJd1/869GNnFAJRTAOfdbJZpvZ6cNUo3zTCHjLTzzajP7tzlS3qzQiXtkOvKwVjqNCkHJVNit8Eee+E8BG2q9JgauvWbtq5papWGfZuGzmSX0s6z7onJUK4/QNkx5PL97q5jqPm3etPfLfJV0RfA4BCEAgfwIIePkz5YgQgEBBBD5yzNnmldZ1t/drXhKcwf3/07fa3CiE9rfXnjN2ZuXDUyhtWNRrp1urrJ1m/uJG8nK1jWb3BIJemZVF2+l/dF+FActJVpfk50ljK+vBUA9OLmRLz+Z6uI+GWsb1tY6FQZIKOCQxz+tzCYmPLS/+WnEP6JPtHGrO5JpVfkI54dKEu6cR8aLinZj5CHja7isv/2HbiH0FvGY575I60LvP/mbKm/xCf8vOgZdXvjWFAqr4TFwVVBWt0E+0qeKtWisBTwUt9FNUS1vxtah+hI9bhSNQgr3WgsKk5YrsH2rcs6PuyrzDe4vkmcfaLrJ/cjVvZAU8GgQgAAEIlE8AAa985pwRAhDISOCcC642f7NFKk4+4r2B604uOwl0M6dPDUJmjzjkreaVL9kxOLrCag+xgt+NNow2rxbOg1eWoJRX36PHGU8PM+q7hIq0QowvOz0AKqxOYo8eiuXYkuCTRpytI8+6JLgvUkjU3GlthF2SYVE6awVjiXg3LbuoZThtOO/dWbcfZe5d2nC3OVeKRP9WLY9wWl8BL4v7zvV9zsVXe11KVQh4EhIk1ObR5LidZteSHF0ut+V3+ha1EPBWx4ZJu74ULeBp7av6ddqKr3mwanaMqh2BrhKxXsKokq0rJqN7ed0q9raahzq+EAr3V9+VyvtKgwAEIACB8gkg4JXPnDNCAAIZCSxb0W++e+WN5ivnfT8oUrGZzW93061/NudbEc9VoJW4p6Y8eHLl5SngKVm4c/LUUbBJg9UnAXya4xW9bd7hT+EKsvq7HBty22VNBu8e/utU2bdI0TPNfEvs9s2F4LvOAAAgAElEQVQ35ntcOVT0EKm5U147iXZxgqu2a0fkkZAXzYmnnHeuYIX660JnXd99BTxt364Lz1fAW3zAXr5o19nOR8CrIr9YVnE2CUQ4xPbCFYvMeUsXriPUabyrE8Kkixbw6nbPqWINtJpLl/NQ9wm5K+WaVB7bwTXFqJLWQZWfF/nSI49xqXiFfgeiQQACEIBA+QQQ8MpnzhkhAIE2CMiFp3bwOxoPpN+54gZzsxXxvviZj5g3vffT5pVW2JO4d9qXLzJ7v+5l5sB9dm3jbGvvKmfWY8sbee/0cKBfYuvkfkgzUD2kbmxzk4XDgtPsX/a2eQiOGrNz2jnRLqmoge8465izSA9YytWVl0PJl0V0u7ycgGKsUEe57SS4+sydBDw5qpatKUCTdQyt9rvugYvNj+yPa0F+NLvYkhx42n43W5m2neq0E13AK8qV6+by8mGF0C4JriP5KTWn+lP3D/f3ZmujaAGvbmGWuj71nehyxRZxrWU9pr4/NrSh/JoziXlZqhFnPXeW/epewEIsxZQGAQhAAALlE0DAK585Z4QABNog8C7rqjvwza8ZC5WV8+4H1//SnG0FPOfQW7a8z/zfjs8Y26aN062166j9xT9cuKLuv2QnjbsuRQ6S+qnP2xEcg2T3CpG14k+/ddkF4XE5uzDa6Z/P+LNskzXJf5ZztdrHV2SKO4ZzSkq4E2OJkT45Cd2xymCAgNcQtMoO5ywrJPKNy+4LlpN0WbkrG9nvjFlpHXgtaliYootY1EWgd9da3QTF8P0kfH+OOvPqJubVzckYvS9LzN5kgyl5f01wPAhAAAIQ8CSAgOcJis0gAIF6ELj6x7ear9iKs8p3p6ZKtCcf+T7z/B2eVkoHF9rKs3qDr1b3MJckIOMtj18awdRVkJVwF5ecPolNls/T9C/L8dPuk4drMe0547bPEuoYnj8Jrj5uu7hzB8fp7TRLVozkMZTYY4wHAS9rEQsN2DeEVk7LMt1XOp/LcVbY5NoDH9v3kLlr5eMFjHQuhWWryY0XF0q7bWevOWnaZkV2q3Y53bJc54UCCh08ziEtUU/uXN0furs6g5x5us/oftNKmC26z3UWQjV2Vf6dO7OnaAwcHwIQgAAEmhBAwGNpQAAC446Awmb//q//midsPNfs9dqXmifYXHhltSUrhoNf8tXkANHDW9UhilnHPt7y+CUJpk70CRc0SOPWysrR7af+KU9i1jx67Z4/un8Vrqi4MfiGsTq3nYQA5bPL42G6DBFzPAh4I3ffYVacdEzqJeZbhVZzV4WA1z+4cp1qo6kH6bGDc+G5TSXgjdo12oiWnrROiO2JUzc123UV61LKKzTdY/hem5QlqHp1JrJRkii2dnqFjkDMW94/Grz8KVvMq3sBC/3eoFBpGgQgAAEIVEMAAa8a7pwVAhAYpwQkKkjEUytDHCgS03jrf9yDjYQDPVD0dncED1pO9ElTQTYvxnVzNNYlrDcpjNUVKJlsc2hJcJUgntf8lbHG1yliYVUdiTo+YyijiIUrdrDwmCNM3+23t6ycGr0WfNx3Vd0LiyiO0uxecOfogPl0/8NjH8u55ZzY7h9lytO8n73RFmbr1bZwiw3XL1L8qdsLA82HikTU5QVGeC7TiGJhMS+oSDxiHcAlCcXqs+ZVRX/yTvOQ1/fcBjN6gu9bGgQgAAEIVEMAAa8a7pwVAhAYpwSGR1eZR5c2ClnURSDJinK89d85BvVgLJedy4vmchhV/eCY5iEx65yl3U9hvVUXKomrlinhVU67sFtSlWTzbmU5w866/Shz79I7g+47ISdJwNt61nbmozuc0taQm+UXjLoZJQio4MOSE44yK/92p/37apvQv/Wppx/7GTP5mdt79a+KiqhVCFgunNY58MJwXNis2MvxpfuTRD6xH7LfG3mLeRvZIkSLlg15CcVek9jmRnXrT3g4WV+uhCsSS8xzL4j0e0BRrW6pGKLjVP9cpe2iGHBcCEAAAhBoTgABj9UBAQhAICWB+Y8NjLlYxlMhiLhhbjS7J8hblSQ2pESU++Z6KJ5qH4ol4kl88K1CmntHWhywjiHJWp+PLa92fsMuOAkbmkfNpx6GJdoVufbKSggfduHpob/Dw4F36LNONtvM9hPI+v9hzMA9xiy6Zu0FOGe7DjNnd5uTbauGoOCE0ck299+IFRni3IzLTzrarPr7nUEfxyqr6i+hlka8025l5BqMXnpVrW0xvsYsWyt1girOxjW39js7rJNLxXPsT17iTx3E+fCYN5s7xTy0aKDMW673ufIQF8sQ88q6X3mDi2wo4XojK+DRIAABCECgOgIIeNWx58wQgMA4JSBBRA9iarNtLpiRlauDcKnx2LI6E8oYqwtlUiGKHitIyMUiF8SCJWsnlC+jLz7nqMKFlNSvpLyBSfvn8bm4qEJpFcKr1tC8Wb2lrBkn4vkIeGnEO4l2UeHOzYtEOJVSmLKNMc86oTsQ8CTaJSXiV0680bvvNENXXTJWWbV7WysmbrOt6dln/9TTXoWAl4cok3qgdgcVRFAOsDQFO8Lij86p4hvthNiWua59GNVZeCrCaa5j6oWNCjroO2mF/f7XS6V2xVmXTmCx/R2jjk0vX2ZP765j1+gTBCAAgQlDAAFvwkw1A4UABPIioAcvFStQk6NIAlNdf+FOGnMdKwcGOdMsU/1ItJMY4cIr6xxeFFfpMIl/0Z+XmScsPBYXwunCnG3AeWXhfmU6lSTiXf+fS8y/lt0Z6yxU2OxuWxzg7bz77+kN512z1qkCCla0W2XjY6c+3ZhND4tY6TwXmBMkpvY8HvaZRoxIynPo2Y1Um0nAq0LMb1eo1/66t0kMUYitiiWkYS1IdSlQ4yasXSapJj7lxkXfl13ItK4dtf6hhoCeJaVD3QtjSbiWcEmDAAQgAIHqCCDgVceeM0MAAuOUwJBNau3cF3o4kLtowZJGXrzx1uryxt+3gmwVea/SzGmZYpFPv/RAKJGgiPxyced38yiBQg+xCpOVOFFleN3iDe4x5/efZ+7tvGOtLm+9cnuzjf3ZfeQtPii9txGDBwf/Zn7/4J/XPp8V73xDZgMhwIbN/u+M+NNKuAvMd7YF+ezW6HZz97RJ8O1P1hZO4K9juPySSfnbkqp8Zu1Pq/2qutbyGqtYy1k8zeaCdC4uX+GnboJZXkyKWCdl9k3z4vKz6r4rp2WaNAF1dsRrbja0KRk0RhoEIAABCFRHAAGvOvacGQIQGMcEwrl+xkseuTjcVQqQOrccWuFCBgpDapUTre4POHVzCJbhsIwWTHCJ3sOiT1VuqTN7jzT3d9/Z0g0jIe+wwVNzuxvlVfn2nvev3SUXmivdbqWFK74uhNYJeNpjm3PzGYpzikmMTXIVSSSRCLXMViEtq1Up4CkXmEKV82phB+RKW10kSTgtU5TyGaPuM1qDdUwlUcY9MI5R1GmZNKc6RlVh4T5zrOI8m2wwxWdTtoEABCAAgQIJIOAVCJdDQwAC6y+BR231P4lNanUXlZJmoUzRSWKPBIFpvZ1Bt/oGG4ndfQsZVPUwlsTQfV43h2CRD/rOvTnZCrG6FuIKJjguVTyYSryT605CcVI4W54iXh4CXth9pwfnoOCEFUjktgsHycYJeO268KJr/XFxqTO4TuNCPrXO8ha1kq65qkThou9BYeF0eNS6WO09MhpiqzBGrYs8RcQk3q0+nz198pjbrJ3jFLFvHfrmI+YVkasvT57K9zd3Zk+eh+RYEIAABCCQgQACXgZo7AIBCEBAOfCc26CO1UfTzFDRhQ6i+dAk9ijpd5KoEjeGuoT8NuNbNzE371A7V+U07Jr0Cc8tW9i8bvJF5rrui4Jp8hHwtF1eIp4YSTRIU+Qgup4WX2vMY9c0wmQl3MlxF9fKEPDC53XipAv5dIUYyhbwqiyaUFZYerTqqe6ZjndZffD9HqlzNfaqqhU3Y+cKvvRObuRAdM48hVNPscJsXfPpzrDpGJx47bsu2A4CEIAABPIngICXP1OOCAEITAAC+qX7seWNvHf6hVzJnRcuHZ958PQwKGdNnuFPTrRTonb9XaKdy4fWzvIoOiF5O33TvnULJctSMTOOgQQaN5eaxzR5nXS8okXiaJ8PnrbH2D91WgfeSlsp2qed02eVszZbOwKeOCus/MErV5oHLh8NxLtWrWwBz/UlWvRitb1/BO68hLDShZdeYB697MJ1hjR12x3Mhvu+3Uzb7tle9Kss4lCFo0vXsZzLWhsSfdT6VG14jQvcC1qBG8kNuXDpYOJ6LbALTQ9dpsM8zfh0DUkIdzkQta/Cp1XlPum6T3OevLYl/11eJDkOBCAAgfYIIOC1x4+9IQCBCUpAVR/nLx4cG72S9D/82EAtf/FOmqI8XW2uKq/cBAqNDX5yfsissiBCEsu6uTH1kDhvVrZqneEche0KsBI9Bq3wl/daiJuPezruMGdNOXLsIwl4ul59Hop3H35L20Ut0gp42l7rpre7Y0zofvj7q8yia5JWW3wOvLxDaFv1whW9kLCkJnFX+fKirPvu/Esg3PXfdXvLQUnI2+LELyQOPC9hOvFEMRtUVdnZdUUvjHQ9Sbx1+SbTVrHNMu5m+9Q59LNKp2YaxmKoYlidHY0CES50WmKtz30rzbmybishVBWvaRCAAAQgUC0BBLxq+XN2CEBgHBNYaCvPOjdE2Q6jPLG162oLVx4dshVHnXBX1INHncO18g5ZzWOe0wie0XBnOaqSCov49LHMkL9w+Kz6VoWAp1xRC5Y8LvDHMQpXXpb7Va5elwuyVQXa8LHKcOAtWTBoli58fCxbbDt7neHIeaq1o0IGcUUv/rbPLj7LJNjGR8Sr8jqrQ0imHG9ygPfYMEwJv2o+RRK8JyHFhnUWyfJ8OZUCSaZNXZ5Q5bmc2tMQ9OXQG7RV7+PyIGY6ScadlN9yIyvg0SAAAQhAoHoCCHjVzwE9gAAEximBJSuGAweEmgSK1fYX76QQsroONW2YUVh8kOgQhMcmVJDNa+x1FkvbFUPzYhQ+jk94W1iElQCbR7hzuA9FJ/4Pn2sdAS8Qlgp04E16yFrhHh7rgkS1WVO3MIuXzY2dTrlUxcNdN81yCEar0MYdrMgqtBLu/vrzR2LHMGtej5GQN3ujxkO9xjNq7wMaS7ToxW2Hfdj03dnaeRc9yZNOOKNlOK3LI7ZkRXlVb10fqyjIEuUTrcAbLZIQV2ikiHuLjllnkaxujuhmc9DMxRjNg1iV41LpE2ZP7y5qCXFcCEAAAhBIQQABLwUsNoUABCAQJqBfpiXiuYcY5bJpJ3F9lXR9RDGJU84ZIHedkqqXJdqF2RSRsy9P9tGH6zyPneVYzQpIOLddWEySeFeEc7LMqpmlCXgS7jr/bCaFxDs3P3KsjIxuYpNaPcdWodgscKeJs4p/JFXsdcfwceFFBby8wmdv/9l867pLzun5rJ03DkS8sIAXXqOj/7jD3HfsYUaBdxJRbYovr5bkwiuyunJSB6u+vluFxeszpS9wedV0j9Y1naVgUBIH97nmQk6xZf3li6lJfawiX2FSn+I+96lcXaWYN8eKd5pnGgQgAAEIVE8AAa/6OaAHEIDAOCWgvEOPrilcUec8QD54m4liEh4UEjett/HLu8K0FO7nQv18jp33NnV+YNRY07oZ8+YTPV5UnHWOmclWkPUVk9rtY9mCS7iIRZC3SeKRRx0L7xx4VrybNPm6plgk4MmRJuFqSudeZlrP5oE7N63g/d/TjRm4pzn9sIA3ZRtjNj+83Zkyxle8c2eSiPfkLWeYIevAjboJw0UrlN5L/ZVA7OOIfMaVNzUdTJX3gKoFPN8CHs4J6QpfFBViW+cXKnVOtxBe3GmdgloD7p7qKkLr3lJULsSNZvfYat6NUG0aBCAAAQhUSwABr1r+nB0CEBjnBB6xhSycmDVeHhbikAcPA9a5saRvJHALySmUdwXZvKbax62Q17myHKeZ4y3LsfLYRy4UOXAkKmlek0I38zhn9Bhl5yw7s/dIc2/nHUE30gh4XlVoE8Q7nVOs1aQZBs6z4d0DJ16W1krEcwJez9b5iHetwmZb9f31735qooDn9pew5JLhq3ptM2FVVWnn7feO2NOW6egMdyDPfG8rHho0fQ+t63Lc+HmzWi6TLNeSCznu7uocy1Gal9hTZoGatNdP3V6mNOt/O05BzW3j+9oVkhlNXSW8FVfdyjbZYEpa9GwPAQhAAAIFEUDAKwgsh4UABCYGgceWDwcPRGqzp002KuLQLKdVnYnIlTXT9l/iTpA4u4A8aHmNv+5uR1WpHFDoWs7Vd7Pwc/nWtK9CvrU2q3BPli26hivROrFIlWhbNW/3Xde1sWGzOnanXZxan5Psf1yBG/376lWbGjO6R5YpDPZROK2q0kbdeHO26zBzrDbYtZVnbGpCD9K679zhtnv+hmaTrWes4wBqVbzCcZJAEBde20rAKzOnYhiZr/staaLv++Ejpu/h5iHKT9lzIzN9s/iiAe24WcNhmKp4qorBclS3EzZf1xdXeYqtSfPZ7ueuKEm7oc5OzHOuS+eKbeeeLwe+KuTSIAABCECgHgQQ8OoxD/QCAhAYpwT08LPUutbU9GClX3YXW1FvvDQJd+rz1N7G2/vHlg3VQnhK4ldnZ4XEBWlFWhtVNOUq1AOcy7fmdKsqc1TpYVoukzJzRLpceIEZzioXrQS8rVdubw4bPDV5umLcdzq8REL9uXJNsQyJ4GEBTwdePfy+5OOn3KJZ7rmUhxnb/BeXPZBpV83vK/Z/8joCXjiEttWBx8Jr7UaaJwlKSQKeK5qRqcMZd2pXiJbr7v5rFnidfdqmPWbL12+8zrZ5uQ+jYk+fDfHWC6i0Yl5d78VZnIpeE5PzRkW9kIoWNskaQj3LvtjTmqNBAAIQgEA9CCDg1WMe6AUEIDBOCQyNrBwTJSSc6E31giXJyd+rHG644qhEBlfZbsOZPWaxLcrRrgugjLH5FN0oox9x50ibzyiPfrqwZwl3eiAM51vLu0rkv+9YYG656E7zwJ0L1+r6Tgdsa7bYfiPzZPsTba0S7+cx/mbHkBPv7KlHthTwvJ13Oknnn8wkW7hCTWOS4y4Ik5XoFOpErICnghYrn5vrcNcXAc9BceG1EkN3vObnTd1h7YQctjMBwQsP+6Ima/XbO77+n1Snj3PiKeec7tt5Or2dMKl1m6bSaVHiUypITTau4j6cpd9lVC5vR8zbcFaP0f40CEAAAhCoBwEEvHrMA72AAATGMYH5jw2M5XGSG2GhLWzRTshKESicaBfOgRZNqF+n0M8kBnVOnF6m8yMsxjYLe27XNRSeiwuOvHkd4S46VxLydnrLdutMYVXJ/+WMlRvvitXfWatPEu7kvNtm1fZJy23s80lWwOvsui0Q7+RUkuMurrkiFuHPVk9AAa/vzr+Y/xz3cW++bkNVod3282cHeb0kVskdFs7ZVlXetXbCVx/541Kz4E9LU7PY/qAnrbVPkWN3hS96rFCpluTayiukODUUjx3q/B0R7n7ZQqPLh9g7uTO4tpLmWPdtl4bAAzubQAACEIBAwQQQ8AoGzOEhAIH1n8CjNuxUYphanUQwPVzp4aC3u/Ew1je4Msht10xcLPtBop2VUee+Fu2ocG47ua9cQQrNa7PQt7wesn3EOzenbz/lFes48aoS8NwDa1bXlMYk4UZFXUZX/9EsH/5dYpjhRBTwdtpvi1j3rm8Ybfh+8KQTzjDTtnt2IJRKxHP3MCc2KKyv397P8irE4Hsvaid8Na37zvVpo+fOMuHCFgO3/TUQXRRC7Nq8F+3oOwTv7ZxrSykWVq5aZZb3ry2i6kDtOhK9O5Nhwzp9F7fqvgTZkdHVpadc0LUlx+WMqV22cJWKGz3uxnffJfp8nq1AS4MABCAAgfoQQMCrz1zQEwhAYJwSULji8v5GHryqhaVoKKWExRU2F5tPWGyeTq2ip7LufS1CrHKhsJNtqLbmVevO1+nZbn8UMnvLxXd5T+uTVvaZ975zazPnpj+N7SNhc2CrJ5i+PV5oRp72RO9jtbthVkdkWCgVb4UWDq/+w1gIbat+jVcBL2sRi+1tEYsNt5redD0+8OmPmf67bveaSifeRTcOC0rKa7jEhvuXXSimnfyWWQU8lwtv4W9uM4/an7i1JVYbWhGvCCFPQk+QJ9UK2BJ09H2iFwb6Tqn6+67VglJhiEX25ZrvPdJrcRawUR2KgETneNCmBpFA3mNf/s2YMrmAUXNICEAAAhDISgABLys59oMABCCwhkA4D14VwpITGvSApb+PiQ02IXmaVud8RtFxFO1yS8Mtbtu8ErtrPiUahEOfs+S+alfAO3HPS72RvGxkodGP2qZPnTO2X6cV8Fbah3614W2eaJZ+/E3ex2xnw7TXZLQISFQondT9jcTuxAp446CIxZIFg+avP38kcXzRDXbaY3PTMV1OreaVfn1EvGbiXfh8uk8pX6euDYUAxjnDUg/Ac4esufeyhs+6bs2cc6fp/9/84H+bCXj6bOoTNzFb7Lub52jSb+ZCbF2VUx3BVbdOf7Ti9hhP32V5fVfkRTPseu2xYbY0CEAAAhCoFwEEvHrNB72BAATGIQElsJ+/eHCs55vNnWIeWjRQ6EjcG3M5I3psgulm+c/SdqIObgDfPpfB2bcv0e3aLbLhQjYlUrgH5HacJJrXx2x15CzHSOO+e+vgv80Wq/rHcEQFPFdhVBuUJeL5VsANM5do11Qo7brWTOp4uOXSiIosq1dtaszoHlmXU9P98i5ioROldeHNmtdjXrX3Fl7rSznx5MR79LILx8akfHf6mbffO7z5OHdVIHDbEEDnDFPl57RVVL1PajfMmn+uHQFvdEW/6Z3067FuthLwtFHRIp7riIRx8eiwX0ZpCl+k4Z1127q/4HHj+n/23gNOsqpMG3+7q7uqc+6ZnpwjDDMgQRREZcmCRHVBzN9/zbi7foo5obJGXMO6q5gIBkBUJCt+OiAISpgZZpgAk2e6p3MO1eF/nlt9qk/duuHcW7eqbvW+5/crmul77gnPObeqz1PP+z5hH+ccET5bIlSXXBgBRoARYATCgwATeOFZCx4JI8AIFDAC7cJ5FmoQlEzJGycYjJxDCGcSue2GRRgTiDs/iiy7PgolbxDGH2ay0Q+OZuWXEbLpUUVpt66Z7EldAg9hs28e3Z8yhKqGMqpuKDd+B7JlUrArKsGCcNqhi1+e1SffKQcgriG/GkIBtZWrRUeoqPRexzGnEXhZUN9hANkg8NCuLokH8m7ja1oo1+GK6K+9dyS5l6QyzM70IqgNhueodzCulZLA3KefENrJMZGaYXAnRaMJ9R0KDEHd3hYWX3UBVS4SpHGWi3wPhlILzxFyqQ2Njtu6B2d5OMnmMzEbydUY0U+Yx4kw9Zbp9+5cYsJ9MQKMACPACDgjwAQe7xBGgBFgBAJAAIc6qD9Qgna/03GQDWAKRhMgBFCgQAp78UOS5WpOurmyzDkLgbvZHTiIMftVDqFvXQLPrL7DvWYCb0qwd+Yoy/b//lAQU7RtA+ROc20ZHeuZUcmqzxQMAfDselInupB4WFfZ3lT8ImFZOz8rc8wWgYfBupF4S46rpSXH1RnzMhNqWZms0ij6U9dTXrIzvQhKlZeJktUPgQf1XXH8pSSBJ7aycAQV7scu2RFypcIzh3/KPIVI5yDDm/EzKPx191XQn8G6/XqtF+Zx4ovChuqo1ylxfUaAEWAEGIEsI8AEXpYB5uYZAUbgfwcCIAG6+keNyUIlVymIsM6+Md+TV9VYOPwgcXg2iB3zAL3mC/M9wQBuDDPZ6JbcXRJIOCQFFf7sBKkuoWjVhg6BZ6W+Q1sqgVcMSYcFgZcLFZ4kfKB4Qf4uFDxTGalXBYlHkactw2kNAm+ihabiwYfNqmuUTQIP/SAnXm/7DPEp+5bEnfy3HaEWwGNu2YRO+LxqegFVmDReyGRMmRCVfsJo4x37qLx8T3LIeIRAUroReLhh3b+9I5Oput5rRYyrN8nPEoQ35zrENsxf7qgYZaKMdl2gDCvA6RmfY1wYAUaAEWAEwoUAE3jhWg8eDSPACBQoAuPiRHVMhNGi+E2gnQjni4g/mhOJo4PIfeYVTr9j99pPEPWlK2u3yO0WtmJFhKquplBnyUNtLtQpOIjh8O9HWalD4KnGFepaNCyooti0iyH6x8OBPHhqMRN4bYPjdEy8UDbMKct4aYH73PoyEfY4qR8m67XXyIzbLm5trDxduKTGvan6vPYp6mebwNMdUq4JPC/9mY0XMjG9yNQM5qXftdHg0cTnhE4p6nuCIpGBZFXjGRLFwSskWTfbBJ5u/jaJf7n4bEMIPb7sAqGazfe9XId066ylVZ2wGVioY2wSeVPxOcaFEWAEGAFGIFwIMIEXrvXg0TACjEABI9AmjCxk2JxufjZzCCVUdlAGjU+7deYDjjAfKlQ8dA+Q+cBQHZskGkuFCyvW1+xqmovxGbkThfoMpJKf4uZCa0XgRYUKtXFBdSr54EDg/WHvgCDuJtKGN6cyYhB5cyu9qUHUMFkk2m/vHc06oSYHnytlTVgIvEyJLS970k355dSWqgrD+6xX0wszcTj64M00+tCPUrqMrDiRYue+g0pWnmQ5FF0Sb9nFc+jgL25PaSNMBJ6f/G2qKnJiMnsOwrncj172rloXn/2Nwk3ZKhTcb5tB3gcMDdU0F0aAEWAEGIFQIcAEXqiWgwfDCDAChYwAXD4RpoVSJ8JPRkWmcasQPUnaIU8Q/l87eX6OwMkV+RDEdMJ6UFNVX1Jtl1G4ZoZgZRoa7abCsyLwVPUdhg/iBUSaOdfc3tecTL87foPrDEHk/dOyKtd6IBZAbKm4e1FsuXagUSFXz1BYCDydkFYN2LSqBEF8+DG9UPsd3/M0Df3XBxzHCyKv8r3fsazjFE5bOS9Gc06upar5ZbTjGyZyUAiiBO9FqRpW62FkW4GXiapXzVUoHUWmIwkAACAASURBVITx/ugpD6UN+k6mNVobLEeV/BCgORoaxcQXPiAXuTACjAAjwAiEDwEm8MK3JjwiRoARKFAEEBLZM5AI5zT+OBfhJz3C3EIW/A4hsgglGhLqD5B9I0KRFbYS5txyZqwySSqfDdyxxpKYBVnV0TeaVzWlnGMQasWffuwR2r+t3RI2cw48s/oONxkEnpEbboZ+iIv/f/SUTbTlldZqJXNndiQeDu3Yt1Fx8LRSOeY6pA6mIUMjwbkI2+3VsBB4uSRIsdbAN5McoxJPL6YXst+2p59wJe9k+04kHuoMHBmhwSMzIbVzBXGnlvbHn6EO8Uq2p2Fggbq5MLHAGoyKz69Mv5gArjI3JQwvMg2xDTMxpq5tmA0sQM4iBx4XRoARYAQYgfAhwARe+NaER8QIMAIFisCYUNx1iDA9FEmYwJ0WhA6IOxxOcpn3zC+MYc4tZ55TrpROTliqhiOqmjIMY1OJCrMTq5/94UTifXxou9Gkalxh7iMiwohVAq9PkN4//vC7PA3l7GWVyXBaKAthGIPwZCcHX6xFLnLSyYkwgedpST1VzlRNateZm+kFrscObaEXvvEBGihJVyfNG+23bNqNxHOa/ODBo3TgjvuTVUoE2TWukQBv8VUXUOWieZ5w9Vo5G0YRM89zceILLvHC56qXkoky0Es/mdbNBn6ZjkneX18VNUhVLowAI8AIMALhQ4AJvPCtCY+IEWAEChiB1q5hQd4VG6RdhfgWOy4OH7lykA0KtiDUWkGNxa2dfKkYzLkLrcijsB3Qggpz3Lf1GCGk1qzGe9X6Srrk6I6kaYXV2mFvyfyOXtV3sj3kwnvd2pq0MFmnvQICD2R6rnJLho3AAykP3scrGeL2/MnruVTgGbkNhdGP33yObnOyM70AofGPH3+Gju3ZatvEvJF+siLyKt7zbduceG7jUVV4OgReLtR3GHM2Va2qMhJK5mFB5OnmKwxKGei2LpleD3Ou2Tl1MePvGC6MACPACDAC4UOACbzwrQmPiBFgBAoYAbjsQWEEpV1ZtJgGh0WobAjDZN0gDvPhQh071BYg0/qG/JkzuOFgvi6NEaCohDoE62xHiiC8EaQJDp5hKNk8cMv51X79ToruOmQ7XZXA2ztvLv3uygs9QYO1Rl71/3NyoyczkFyrIcNC4Ml8gCBLZT566cL6YmsPvdjWk4L/uRuXeloPVA4iJ52XTjM1ZPHSl1T79RzdR5vv/D6N7d/henvV+CitHuxMqQdTi9h573S9167C/l/dR0OHWsmNwMsVeYdx5ir/qFRG4ksxqNixf/HTzsVW10DK92IEcGOunxkvQ8YemyMMLLgwAowAI8AIhBMBJvDCuS48KkaAEShQBJAPqHs6D16uyaUgIcs14eF37NkKp1PHI9V2qjECyDu7A6S8F+QJErTnilx0wzBXa+pE4pUK9RRUqWOrF9Jdl59v6TprngeIJ+TOgx8iktyDFN0wJ2Y40+qWXBFqcjy5UgFZ5cBT96s5HyCelyM9/fTV3/2DpqaxNGN47glLCETeHU/8POXSVS//Z0u4c01G5OO5+suPPmWQZ/GDL4jn3t1CwkqJV/P1x3S3q2W94cOtdOiO+0QIrXUzTaefSM3ilYuS6zXHnKDKw/tpdQVC5ouT6SjMX6AUwpdPYU5TAaK0ToTQcmEEGAFGgBEIJwJM4IVzXXhUjAAjUKAIjMYnksnVc0EuZQumfIWmep0PDnVz68qotXvE662u9eUhC/nVrIwR3BoI2/ojpBeK0GyFUap4lO48RBW/fyJNjVeyYQl1nncKja1aSLdv63WEEMQdiALwJRPiPypv4ofAGxHkeq7UsHh+oBLKNMG/2x5TCTxp5CHzDCKs2+zq+V8PPStUd71JR2A8P1ANw9lUlm0HfyrMCQ5Rc215WvfrFx5Pn73yiym/D9JUwm2+uA4CD2Qa5peLsv8ZYd7yzJ+oaGyIJo4d0O7ypN4jKXUzJfBkfrhD2/cbajy15Iq4k31CSVst9ni3cF7PR1FdhCfE5pXGFwi3hXvqsZ7gPw+CnGeYjaJgXoEvH7kwAowAI8AIhBMBJvDCuS48KkaAEcgBAk89+wIdbuuk177yRKqpqgisxyOdw8m2gso7FtjgNBsKs0LAPIUgFReqmynID4TI+iVhwpZLUIdU2rFrB72weyZM8LKLLtfcMXrVVNfgrcdGaOuxGQdO2YIMk4XSzkxAyTqqkYVOzzpz12lHt06Q7rCDw0epvftZ4WprIm3qN9Hy+acQ9GAgtODA62Tk8dBz++ihLfvTplAsUl2B+Oge3EdbD/w0eT1WErEk8VDhM1feQMct3GDUzTWBl2vyA+o7Oc/4gfQQ2iKBnZUqz6zCy5TAC5O7apjGopqPYB1ASAfhUKz7rPupF7b8qOocmmpjBEy5MAKMACPACIQTASbwwrkuPCpGgBHIMgKf+I+bCZKeakHc/fHRp+ljH7jGIPKCKB19o4ZiCyVXYYtBjFttI2zkk9P8gsAYB1KEDoGMkKSdHXnkBetc5YnSGZMT8XH3vb+mu++927KZtavW0sf/9RM6XbjWUddKJfCswmSdGrv6+FrXvtQKQRJqOh0H1d++I/enEXeyf6iQsF83rLiYiiNzXInmD9/yZ8eh/3XX59Ou15RHqaZiJpwu0hyn2HFDVDJnnObVzafyaEKlt7J0PZ02eQktKVqnA09GdYLCVncQksADSTpmQeDNrEcqkafmwss0Bx76CJO7aq5JVJ21wvOA0M/YNPkE8yhd4wud9oOsk4t8pH7Gi/fhloZ05a2ftvgeRoARYAQYgewgwARednDlVhkBRiBECBxu7aD+gSFau3KxMaqnnttJ3/3x3fSTm643/v3bBx6l7/7kN/TQL74WyKjhdimNCwolFNVq4oWiHgTGYyJ02Wt4JEjKKhEqBOUSCFcnQwq/GwMHtfbeEdd8eX7b93KfXe6wL33zi0J194JrUx/70Mdp3erMCBo1jBfk021bewwSCmo7KGc00ot5zn+HieWacAiCZLIj7yTZKRdsUoC3qOV8qiyfZ7uGduo7eQPCZvuG09V5sVKhwqtJHOgrXt1rEHeylJWW0fz6BYlwXDEomPcsLlpLb458jCaRK+5QYk8VLVxLxYvWuu4v3Qq5VFPK8FmMDe8XY60Co9Eh16FKVZ4Mo83EhVZ2lst5u00wVzke3cZhvi7HhTybMBrC+ztC2WWIrc77i9c+vdbPZtoHr2Mx14+Jz0KEIHNhBBgBRoARCC8CTOCFd214ZIwAIxAAAjd+53baueeAEWaGJPg/FqTdbx58jBA++8WPzrgCXvGuT9NbrjyXXn/+GRn3isNCV38iNLCQQlHNEw9C2ZYxmBoNeFGmyAT/ONjhIOUUcqjRtWuVMGEoc2ipeat0yTs50UxJPBywcbhGEnoQp08cGDReXopX9R3a9rJHvIzFrm6mDsRW5J3MCaiSnYkcgQljjyXz7Ek8mfvObrxW6jtZd9mcaoqeKYhWhbyT15bPWZHMpwfF6jl3ttLiw0XUUNSS1lXx6ZdSRLwyLbkkj1QCD7kw40ODNNmunwfvtIGjFFv9Mip797czzj2Jeecyj6PTOoGI7xfO3+OCtA1TsXKglblIIyJWHOZDeOUiD6gdLmH+mwDvk8iBx4URYAQYAUYgvAgwgRfeteGRMQKMQIYImJV2fUKFh1x3IO9A7N31w5mQMajwngSpd/27MuxVKInEQVaaKuCAjUNFNkwWMh6oSwOFoh60IqbMU0MdhMhClYEDXDbUdlZwhinXERREOJzJ/FBOYbN2WyOTcFooAFUlnMwt+Ie9A1putBiT19x3ch65Nj7IRPGHnHf7jz6QXAKnnIAqgVdR1kJL519guXRO4bMHO/9MeNmVhadPUc2mMeMLEDNdU19ZTw1VDTTv8CidfcdMjr4qqqOqorq0JqHGK3lDQvnst+TaUViG0BoEniCspoQCb0qDxEMI7bqWxTTn374v3ncSOcUyUYLhywCou8NAmoU1BNQpHyq+sKmIlRhrgZyPw+JzIB8htmF2p2+ojiX3qt/nk+9jBBgBRoARyC4CTOBlF19unRFgBPKIwC13PmSEzkJV93cYVohQ2lNOXEenbFxD577pw/SfN3wwGVb7glDpfeLGH6aQepkMvb1n1AjdQbFSBWTSdq7uDfNBQ8XALl+fVNuBTJGGFCDvchlGlakSK8i1xgG2ubYs6dD4lvde66t5Lyo8rAH2EQ7NMi8k1sLsIGpnaCEHOKcyIkJny2hupT93xFwn3cecd3Ttob8dTDc9uGqNNckm59re/YxhWqFj5qESeLh//fK3W65pJgTe+vcoRiPjIoRWuH5K04b6aDWt662kc+/vT+u3pWip5VgyJfFy6aaMCUgCD18CSOWWDom3cMFKWnrWVVSy8iQDB/klQlSEJQ+NjhtfJHgh48JEmoUpt6fcZOb3N6c3N2l8gS918DndP5Qbd26MKZcKUq9v8FhXhMNzYQQYAUaAEQgvAkzghXdteGSMACOQIQIg8EDMHRHE3WvPSByikOsOyrvviZ8oUnEHcu9tH7qRHg4oD17PwJih8jL+YBeqp1ERNujXzTRDGHzfLkOPwu7ohwmq+fpkiBIUMyCNQBYFYUjhB0i7vHN+2griHokT3Ga/fNOXfDV52UWXkZs77QxZgbC1SUPpgjVwU8KByGsbHE8q8jbMidEcQdr5Je7kBI3xlEWoZyDua85eb/r849+m7V0vGmpcq3LV6vPJisgDIdfT/xy1djxt4GVze7JJM4HXLJxpm+vTzXicQmidFHjl8yZo2aXjNCVIO4qnY1c/UUpv/BPR3HYxz9JSKoKl7XSxU+HhcibhtFCiYR2DfKb7i1LXqXpqhsSQYbRSgaeu51RfB+GVUmIVVLdkPW1600ct1x5EEwhemZ9NlzwKC2mGPYc8acd6Rrw+Flmtb1YY63SGtYDpRaX4kgdh/fjMznaIbZiIWBUjmLTMEQQeF0aAEWAEGIFwI8AEXrjXh0fHCDACGSAA8g657b79xeuSDrNQ2aG8922X0tsFYXftVecZijwQe6cKdd61V5yTQY8zt+IgABIPxVD/iENCjwh/KrRSKEYWUDmOC7YDh2yptgsDYRo2ElSaavz69/aus2571InAk2GyUDnCBdK8BiBXy8TzkCsiTc5FJ8zabd4615/v2E2fe/w7IkRP1BbsgB2Bh7bWN66kz77iA0azM3m6iugvz3zflbiTY9El8JxMLJwIvMaXxWnOJkHU2MhW17ZGBIGnKHYUEs+JwMP4d57/Vdq2PZX8On59Ex2/vtkRajzrXf1jgRB4nYK4G7MRHFWJPSyJvC3330wDx/ZrK+ZOuOAdVDdvmeuWkesO8sjJNdWLusy10wwrhDWHW6ZflpiJ1UzCne0gDrOBBdSIcPHlwggwAowAIxBuBJjAC/f68OgYAUYgQwQQKvs+QdZJc4pHHnuGfnP/ZiN8Fqq77/30t9TfP0hnC4VeEAYWcrgIteroTYSe2YV4Zji1nNwe9vBfHNpw8IBb5pAgjPKptrNakLCtvcyjdcfv7qK7773b1x4yE3ggkRAqLN18QUTYhQbmikgzTyxXROpn/yqUd517tAg8jPHNx11E7zrpYoOMkkosO/dZq8XSJfBwr1MYrZ2JxYLTJqjmOHuTkfO2lNDLn58ZmcGFCRJPxOGRHYH3fEcl/WrXXHp+ciUVRdMVPyDx3nTlOlsiLwgF06jI5tc1IxZ0fA7mTRYZ7+E7HvoJHd2/x/WZ0SXv1Iawjon3soRr6qBQDatGC7jeIIwj2qc/U1wHkcUKuQ5H151KkDlbZYgtcqZarYfumPL1PuRnfMiPCmUoF0aAEWAEGIFwI8AEXrjXh0fHCDACGSIAwu7Gb99mEHbzW5qMPHdBKu2chtfaNZxU0jgl185wilm9PUwmDHKiOEwj/EwSRlA7xoSyC8WcWy2r4Gg2HpbQNwxXuuL+8rd3ZkzgqWGyCJGFYsUtrNFPmJsmzI7VQIAg91Q2w8Hv2Hk/3bErYT4BBV6RkNvY4QElToJ8I/rVxd9KqSdz4OnMWzcHHtp6sbWH/uvh5yyb3Xbwp9Q3vD/lWqwkQgtWdVDs9IjlPWWTxfTWRyLUgvBZtYh5FUejBoFXKV5qAXn3mcdXJH5VWUdFVelGF7L+DZ8+05LEA4GXSfimF/IOY4mK6c2LCHJNhGA/t/lB2v+MiBm2KLUtS2nJia/VUt7Zra1qtIA6UgUGhR7CPFUHaZ39kY06Ycrrqc4vG59V6nq4qSR1sA5zXtkmoWzFezoXRoARYAQYgXAjwAReuNeHR8cIMAIBIHDLXQ/Tz+540HCgfcuV5waqtHMaHsK8kE8HBcQJVBUjIidbIZWwHDikIQWIOxyqQNQhv50kSMIa1oW1lmGruTTPsNtjILFGkOdJYOfXxOJNl15Jb3vDG3yFKudLSZSLft9wz3VJ2LFH4XQ5NDRGYyNx6u8ZNq6VlZdSTLxq6iqSe9ecD8/sQuv0fqHrQivbsAul7R3aR88f+lmyK5B3TdEiikTaqPIqoaizKC3jMfqXOxLvb+ZSFItRtXChrS2uN5xrEUq8TSXvcIMLgYcqViRepoS4U9isHdZVgkBbJNRxMvS75+he6m3dm6wO4i7ooppeTIgchMiHGAYCL6wmDEEoM53WEF8+QJEncxfKfHle3tfDih2+cGhpKA96C3N7jAAjwAgwAllAgAm8LIDKTTICjAAjAASgSuqdznsXFiLM68rkKvTQblzyEIuDE8hQHJrU0DJ5X76UXTp4StWb1bh17g+yjqqe+dI3v0gv7H5Bu3npinrXj37uO1Q5X7m8ctGvSuCBtBvoHaaR4UTeSyO0VPxHPexX15VTtSDy1Fx4cjF0w2hVAm/JvPOFSmue63pCiffQln30YltvSl1J4tWUR6mmIkpT3T2CMeqhmn9Nz4sF8q58KkIbt08Yr7QiFGvzSlcm5w5ny089ttwg8ZKlvsUyhFZtC+G0N3z6VSnNZ0LgeVXfyY5BcKyMluZF4Yu9i9xk5eI9cDQ+kVPHVKvNFMa0CrnOLafmLvRifBFG7LDGULDDmIQLI8AIMAKMQPgRYAIv/GvEI2QEGIECRQCHLRmyl28izC+EuT4YYZwgJUDYVYqQNWlIAfLOSemQj3HqYpqN0C7dvs31QCSDjJChxm4qPBnqCQIKa3H9hz5Oa1et89u9cV++jFEyDb10mrQ0r0CdUUHedbb2JUg7FBNxp7YTFevR1FJrhNGay/aXfuyKsyTwFrXokXdqgyDyXmwTJJ1SFjT20x1P/IK2H9qWJPAiC4uSKjyEzdZNlhrkHYodgVdV0kjVJU0pbV95zwkp/y6au9R1fqigqvAyJWLhNjtgY1rhNBgQkFVCPF2ZJwE18rshF9vExBRVVyQcU51ML7SA9VkpTIpiOYV85RqVxhcgwKC4HRafU/jizuqzKsyfUfhcQA48LowAI8AIMALhR4AJvPCvEY+QEWAEChiBI52J0DmUfBEXmcKXK9UAkqODuIOTLMJjvRpSYJwdfUJjY0rJlen8M70/TDmjzC6wO3btoC/f9KW0KYLkM8ghcQXhjwjf+5gg79atzoy8Q0fZJNKc1iqbz58k8JLk3TRJpLMXocS7/9ofWA7dTYmHNVq+4ALhGzE3022acv/zh7bStt/cSpP/eMb4fdvVcWpfGk8Sd2rlt9yZcNuWJToqDBcm5lBRw0x+u1/tnGsYV8hSXF1Hkep6sa/E3nIhxWBogRcK5gulkN8ceIVK4Kmh7xIHJ9OLQDeD0lhYSagwGGtI4wuYKoFslaY0Er58kYw6e6GhOiY+ezn/nQ5WXIcRYAQYgXwjwARevleA+2cEGIFZjQAIJZBRKGEKpfQCejYVZKqDqVTbDYswWT8lrPjicAnFTN9QIpwyn8VKCQoS7+57f22E08owWRB2qgFDUOQd5g6iFfkh3QwvgsYpk9BLnbG88ffXGcq7URE2C+ITHJ4Ol1zfV0/3fOLbtl3A1GJwuFW4LLem1Gmu30RzGxZRLDqX/D4zTvMa/9XdNCFesjx2dg/99ezUsFtcU1V4BnnXIUJu54vw2PIZh1kzgSfVd8Ks1lAugegEmWdFeJoJvEzMSPwSeHguoL7LlwJPukeb3Z3tTC90iGOdPW2uk4tckn7GFaQDrZ/+1XuwJvgiCkSeVErib4CI+GIqLJ8D5jnivREqUy6MACPACDAC4UeACbzwrxGPkBFgBAoYAeTAQ0gNSpgOGV4ghYIMJUiH14R6JGIQRsghBAIiU0InrPiGKXza6gAu12L7zh30xDNbDCJFLZdddLmX7eJa146McL0xwwrZUP4lwr2FQ6gIQfvQQ9+g+/72eHKUOMjrECkrDq+gd5x2OZ112Ubj3tbWfdTWul/83G/8nNuyhFrEK/FzaQoKeDbHBduaDQIPHY1e+ZaU/g4sG6GDy0fSiLyLH5qgFS8WU3QsoeIpWpE6zhQCzyL3neHaO00gQPGp4qYSeJnmusyEwKsQBB7CaPNRdAwa8D4Dp1qQREOjcIWeIDPhl+nYw2oWZFYoZjrPoO6XIbYwvjCep/FJYYQypvW+ENQY3NopEc/dHEHgcWEEGAFGgBEoDASYwCuMdeJRMgKMQIEioObBC+vhxw3aoAgoHL5xkHEzpHAbj931sBqFhC10CmqL9t5Rioq8TSCA4iKvFhySc2WykS+lpA4Jorv3pHK0VJAmcXEoB7l9z18205ee+X6yCV0C79ynzjXIO7wefOBnBmlnV0DinXf+DKmWbQJv7DNfoqnnnY1OkkYaFb1UVCUUevV1KeGzmItB4O1dIhgwcS1qTxYY7r0mIk8l8CRJ5deN1a+JBZ7hlomijL9k0N1f5npe1KMqaWQVyul3DLgvTGpidR5BPtuZ4ON0L5THINtBsI6NC0OmEWtDpmz1b9cuvkiDSQoXRoARYAQYgcJAgAm8wlgnHiUjwAgUKAJQk7R2jxijx0EXf8TLfxfKlBKJ45F3atTzkDFnSRThZhAdCCfKVG1nNZCgiEbPk9S4wcsBXKM531VAROCwOy5yNPnJM+i7Y+VGqGXycXgFcdgzEM9o76kh3+a9/Oe7n6PvPn8rjVRN570Uz43woaXh4sTzb1VOfuFkauhvoCVr51LLSW2O5J28XyXxsk3goU+zCs88D9UJt+i4tRQ5fz1NHXyBpg4liL/i0y+looVr6fL/u117+xhEnvgPfn71C6+m5SvqDdWSOYejdoNKxU5hZDHmMVqwToREVo1NZbR3/IwV92Ri3KG6pQZhehFWlXM281v6XTfzffgMaOtJvBdUxPBFVnFezUjk+OrhcCxIPC6MACPACDAChYEAE3iFsU48SkaAEShgBNoF8QUlBMqcukT+r6BDm7INjzx86IQEYiw4OOKb/Wyp7azmm8lBN9v45du5UQ1ZxlzzuQelo6afsM/SQ91UejjVORXzGTptmesSZhK6K4kQkFUg7sxj3992lP77jjtpoGeYBmODNBFJzeN4ONKaRuRJ8g4Dr193iGrn6ed+lCReLgi8yed3EPLh2SnxgIkRdr1+LUU/93Hbdfjk5/9C27Z3uK6TWuH49U1005dfaxAeCAtFAQkNItZv8aPCWyOS/Pf1ppp1+O3f631B5J0DZom8bFDcTvpW3IYxVDVTYxOv6+Gnvt0a4n0FX3BBmY51QToJN8d1P/073YO/SUqEKpALI8AIMAKMQGEgwAReYawTj5IRYAQKGAHkvMEf5sZBvTpq/IHuh7zIJwQ6YY+JfGARkQ8sYihV8nEY8Uo05gpTHfyCHouanw1qO6wHwmTzMRZ1bn5ceUHcVfxtnyV5J9vuvXwTxRfW28LoZ94gPjFe7GeEGY9MG9Kondz28L10oK2V4EDbJUwsUEZLR42XWoaLRuhwSSvBtGLFkRWG8g6lqKyfGtYfouq6Ck9bYOOmV9EZp5+d1Rx46oDMphbyGvZZyRsuI7ryUtfxX/qmX7vWUSvc8Okz6fj1zYYKDSHyIDqwFsgtmknItxcSr0F897KkvjxvyulMw4ZVPDM1vciXAY3TpglClelpU/qorOOSq6ol5WdnJntcZ5iIVm9pKNepynUYAUaAEWAEQoIAE3ghWQgeBiPACMxeBEbGJoXiKXGYN/6QF9+694gDaCEVJ9IFcwJxVypUHvkKy5RY+iFpcrEOuVSuSPUjlB1W65HLsVhhCyIGB0c7U5TxgRGaEK/RtoTSrmhsnCoO91GZcPGt7RhyXC4nEs9L6K4k7tz28+YtT9OjW55Jjunovs6U8Y0Xj6eo8epbG6misyqlTsm8XdS8rJhiZaWetiJUeFde9o6cEXhycFDkTU7nxQNx5wXXbdvb6ZOf36w1T0neqZWxd7CvpWFm/5D/3I0g8QbEPrQLp40KUWGVeFUIq9zGGqQQsA+F1pqQz0o65I+fpv2YXoTxC5Kw5j5V18RL6LEkq8vFZyqUraPiSwMYYemq373sBXxuN4gvFbkwAowAI8AIFA4CTOAVzlrxSBkBRqBAEUC+MZk/LmyGBrqQmg041FxgUm0XBlUhFI7D4rBjpZTSnWs26vlRnXkdBw76UCjhAGgV5inby8VYnMbuREgM7mmlicFUoqTkWH9Kc3P29xpknl2xI/HciCbsaZAByE3lRtyhb4TN3v7wfSnD6O8ZMsJoUZBmLdXPN1G19mADlQ7PHJqr1m+hppZar8tt1H/fez7nmcC77Y6dyb42rG+kE45r8tW3vMkPae4UTouwWRhXQHlnLureVcOaoVjyS3KAyDOTeCDvYsYKJnKXguSA8Us+ihvhnemYdE0vUG+uyJ8ZthyueK5BcoXh88duLfw8I2gLezwR+hwxQmwzIaytxlZbWWq853FhBBgBRoARKBwEmMArnLXikTICjEABI9AmjCykcUMYVQxu0EriEYnQcZjAoRaHZhyasmFI4TYeu+vZPuz6usIfxgAAIABJREFUHVe23BtVIlUNk3UaZ74xMhSCIszanMfMiryLdA9RUTw9N5wbidfxwdekQWCXe0/FEPsZ+1pnT5vVd7LDztZeGhPPiR2BBwWeqsKb94o9ntV3si8vBN5HP/cYbd2eqhCU7Vxz5Rq65qo1vrZ3JuYgv7hzR0qfIO6cilXOvxniNWLkyfvvsR20pbiLtoqXLBsmG+ia8ZV0wlSj5zkGGcLquXNxQyY5I73252R6EdYvnxDW2y3SVIQ5r2ymn/lq6DNcbPE5jFQcmc65SWCHNefCCDACjAAjUDgIMIFXOGvFI2UEGIECRgCmAfiDG8Xvt/H5mj4OblB2VYjX0PTBIWwKN4mNWSmYL8zM/QbtkKuGySJEG+ojHdIJ48p3zigrLEZbe5Ihsyp2ZvWdes2JxBs6bWmasYWZ/FExdFIs2u2hL996s+32AokXR9ibTY2mXS3Glbd87Fz6y99+4Hub6hB4W57voOs//1fXPqDG+4/PvNK1nrlCJgSe186c1FbbIl10ffRvhnstwg0RfmgOOwSR9x/x0zx1m+/nJR8h71amFwhbLhNf3mRiIOIJeM3KmZJjmt34rha0yYZZMYn3fxDXfkJsgV2xjEf3PUO+kRFgBBgBRiCXCDCBl0u0uS9GgBH4X4sACBYkXkcBkVAk/grvcwgDzDdQOHQg1xTGigKCAyRepsnjsz2vsKpEggrDU00VpALSK6ZBk4le+wcWICU6+2ZcPfue25fWTPHgKBUP2jt/xsTzNPdAr2X3dgSe8D8wiB2oSEH0QMniN/TOicDDoIZ6h6lXKAityhXHnUdnXbbRuPSzn3zBK4TJ+m4Eni55Jxv0Q+LlmsAbgVOnyUxkS1GnIO+eTOICTgLEBAjUSbHoKrnhlcTLlnpWd9EzcU/W7cOunqr8iohcgBOTyOc65ossynQsVvcHTY5lY4zZymGIsap5DMfGhXp4JGFUpFOg5GsWDrRcGAFGgBFgBAoLASbwCmu9eLSMACNQoAjgj+qO6RxK+SZQnCCUqiSptpPOpbjHSyLufC7T/MZyOtKZyEMWpqKOq4RuNYZWUpT4OT71ZpqkE4yXuZjDZEE6ZRI6BZITuY9UAi2XOIEUaK4tS5oC2Knv3Ag8jHnxjg7LoVsReHViztjXw0IJC0dZ3YOuHTZuBB5wluuE3HgoUWFUAbOKj735nclmn3v2z/Tcs3/xvAQ6LrROYbN2HXoNp82lM6ldHsMLY/dbTgd7TSqMVCLPC4mX75DzOSLvXGffqLbC1vNG0rwB2IP0wZdPUHwFEcKp2bVttbAqrtUB5+Jz0yrE1i0nJPY1Pge4MAKMACPACBQWAkzgFdZ68WgZAUaggBFo7RoW6h+R3F4cKuc1hIdkAkGERNmVIi8ZlCoyv445JMcIJRP1wu6gG9acSMZBvPdJKqWPOO7isamvGETejLqiyAiRRaiUbpisUwdmAi0fjxRCt2Qy/EwIvNr2IUtnWkngqUpS7GeQDnbut15xcCPwSkVuqbiNGkYl8NCvHxXeuedfS6uWrbQ1sfCqvlPnf98vL9GGI5cEk5Ua7bbIbrqtZI/jeA0iT/wHP6HAFEIyunHsVK2ceFZ597TBCaCi+qwE0JzvJqRB0KjY0yB/oMjOhrGClwEWggNtro2VzMYX+LICa2b+PK+vihLUgVwYAUaAEWAECgsBJvAKa714tIwAI1DACHQIFQWMBlDCkAcPf7yDkCsVSiEd182whqeatwQOTEEorILealWl19PExLOu4WeGmqLyJsH0npA0Cgl6LPlWKaqkhJV5BeZbNDZOkWlHV7v52xF4o6cvo8irV1FE7O2JiSmDtENIOBREQYWu3/bwvXSgrdV2aewIvMVzW+iacy5Kua+1dR899MAt2ssM8q6lZakR4j4uvhWwCgOG2+xtdyYcZxFSinBS3TxZN376FdrutCDwjvWkOgdrT8RjRatwXTv1nV3TIhLUIPOunVxFbxpb6UqK59PlNAxku8TRiqh1Mr3wuLS+qufS4MPXAMVN+crRh72D97vqihLjJ9T0+AJDKo/niPDZEvF7LowAI8AIMAKFhQATeIW1XjxaRoARKGAEQCL0T+e9y0VYjRVUajgm1Fxe86jlm/jRWX6QGlA6QrUWllJMW6g88lHLxPpyjFgbHLpAsmBtpBIvG3PAYby9d0Sb0Al6DGr/dgo89AkTi6NH99O8eUssh2BF4AHHqWtPof45NQYxLVWLdu63fue2v+0o3f7wfba3qyG0aqWrz7mQlsydl3afLomH0NmNm84y7nck8AR594u7dgkmNLGnsLdQzDnhrCbgJYw2lwSeFYnklcCT8wWR9/eyy1xVZHZhu373jZf7gsqd6aVPu7pOSkAr04tMQ9R1xpzP/IA64wtLjj5pfFEuvrCDAhXvi9UVHD6rs4ZchxFgBBiBsCHABF7YVoTHwwgwArMWgdH4RDLvWK5z90Bth8T9OFB4dS1VFyTsByaMNd+ukVYbuKzo/JRcXLKOzNEFbgVEk6qQmpw6gcboK1l5HvK9jqqSyorAaz2wl5776yPUtv8lxDymYHDiiWfQiSedafxO5sBLhkiK343Mr6Oeyzel4RY0gYcOnFR4VgSelfpODvTAvr/RkcO7aefOLTQ4mMjhGI1WChVhKUVKojS3ZYkg7l5lKO9ksSLwJEl/i1Dgff9n21L2lF1OODNYQRB45aMHqXzsYNo6xCM1NBxdROMlta57u33/duo4sCNZ76yLr0lT+/kl8NDofaMXGGGEeG9E6R9Kz42Yz2dFhtF3C+OIfBZdJaCaiw3jzcQhVWe++f4iwm2Muf6cdxuP8Z4iQvurxJdcUN9zYQQYAUaAESg8BJjAK7w14xEzAoxAgSIA5YvM+5X4Zj4qDqOjWZsNCATkKcIf6gidMV4m90avncMIAPl0/Dp3eu3PT/2gTEJe3HkgrfsVaxZ7HhIMK2BWgTBGyKCwD3DQNZRi4ldOiqiRqQc896dzQ77DjNUQ8vGBERp6cSYU9cFf3ExtB/fNTGNiIhH/qZSWlsV02avfQC0HeykiwDRwFOwnCNBeQd7FF9anwRDUvjA3bEfimQk8O/Kut+cQbXvu7rTxtrZ1Jn+3evUJtGHT5Wl1VAJPVddC7fvDW7cnQ2jNN7oReV4IPCtlVvXQNiqd6HPciiDy+iuOt6yzY/Nd9MKjd6VdA6Z1C9bS2jOuoOYl643rmRJ4shO5P4DjoHDzhFED9lMuTTrME86mg6nO+4Ss4yd9guqQmg3TC+zhuUJJLD9TvcwnV3XzbYBiN0+YV2BsXBgBRoARYAQKDwEm8ApvzXjEjAAjUMAIqHnwkIMGTqBBGBNISNSk/fgdDvJqGGGm0BVC0vBMD3Yg7l7clU7eSexWrF5MXog8SeBJ0g7tyDBZt/WAO+04vdmtmufr+c4dZQ5LlHnw0sg7OTMLEm9lZQu99cRLUsKS7cg7NJNN993NW56mR7c8k7IOKoF3xgkn0pknnJS2TnbkndWC1tQuSCPxQOCBvCwRpBNy/OF5l+S6mgPPboPYEXleTCzMBF5D/1+196MVibf5ti+kqO7UxlIwvfqTBonnl8Czc6JFHxWxxBcfIJ7w//kKNw8LAZQJkSjDN4M2vfBDKmpvzIAq5trAQnfYTbUxQ4nHhRFgBBgBRqDwEGACr/DWjEfMCDACBYxA72A8mZstyD/ujfBAhIKJb9WHRO435LbLRg6ibKmYgl5Sv4nDn/rrVuru7HUdTn1jLZ3yig2u9VChLHKbUIndilRkRhkXpgq6JVsEHogflKAcWXXnI+tZEYibv/cjETb7J/umYB06HU5bLH6WCEXp4rr59OaTXk/xBXUE51kr5Z1sEOQ2iEOQ5tkqIPLUOQ4IQu2VG0607e6xP3/b01BUEk/OBz9V4k5t8MI3/k6rfTWU+4T1TXTDJ0/Xug+V1Bx4Oso7c8N95cclw2nN5F18oDuluqFaLYlRJFpu/P4MQeI9tLzU1YXWajJuLrSSeMJexTqqBgDa4GRYMd9Euxx+UERikKYXmZCKGS6L9u25dGjWHpSoiM/HYkMSzoURYAQYAUag0BBgAq/QVozHywgwAgWNAHICdfUnwmZxKIIDbI8g9fwUHGahEqksixiKrgFB3OGQqes06afPTNVtfvr0c48fl19d8k6Ox4nES6xNsbHGoyM/obGxnxrrYudMajfHbBF4OPwG6cjqdY2sjEa++86305TIE2nOeZfWtjh3lih58d59261a3TsllC/aspOKtwrDB6VMblhNUyes0WrbqpKVY6paDznvDu5/0nP7G0+8nBbOW2oo7tyMaLY830HXf15fEYfB/PX3Vxhtq2GkToOUBF7JeC/VDD/veT5ShaeGzYK4Gx/ssVp6Q3FYXFpGsYZ51LR4HdW++b10fdQbjnbqO6vBY34wxMH7LPC2ypPnedKaN4BwHoF7aIapDzS7s60WtBOvqnKMT0z6cg3PlxGULpZh/azE+36zUP9zYQQYAUaAEShMBJjAK8x141EzAoxAgSIwLg4rMu+d3xAgkC8g7kD+ITwW6psgw3DdoEVOqO6BMU9KMrc2g77u9XDX1dFLf398q+dhnHz6BmpomknGL/MOggCRa1M0eYuRAw/FzpnUruNsOdHmOzm+WdFzeOcL9Nuvf9WAASSeQeSZC1x6SyNUJA6gajnl4kvolItfr7V2ZsdUEHeR23+fRt6pjcW//G++iDw3As+r+g5jAgm5evXptGDxqUaorJMLrZyDFxLvxk+/gk44rsnoB21HBd4IIwWBZffFgMTUzrRCZ2G6ql9Bd3/5aqPqaNdRmoyPuN4mSTyo8I4uneuJxHNT38nOzaSvVJDhulcHb9cJWVTIp4GGOpxs5czMxPQiSAW7n7Vxuyff77F248N7L3LgcWEEGAFGgBEoTASYwCvMdeNRMwKMQAEj0NY9kiTcdEM91QT1bqqbbEMT9oMT5u81V59b3js7TKUKT3X5NYczFtMWihZ9xGgiIkhXJ9MKcz/ZMrHIZj44nf1nVgA+dc9v6al7EuGeiOwqFid7w5lXsEYmE9q05r0QeGq+NpB3pR/7hs5wyQ+JFySBh+cfZId0Kn7lWR8wxq1D4KGeG4m3YX0jwbgC5J1aZBgp8sBZEXkqwZUJgQdX2tu/8VGyU97ZLRJIvI2XvJ/WnXkFbSnq1CLxdMk743m1CbsOMhTUaQOGJQQzF+OQhFdMpIOQanKndAO5GJPWm4NNJa+fQZn05eXe+qqo4bzMhRFgBBgBRqAwEWACrzDXjUfNCDACBYxAj1CvQb2B4hTqicMzlHbIbYeDJMJvoYTJpdrOCuawHkzUsXrN1ffQPY/62lFYl3++5rWG2s4p72CUPiJIqS3GOkq3VLcOsxU+i36xt5pry4Qa1F3p5DZOP9eNnI0iJLFnIBE+DgLvH7//XdJR1iCqLBoeGUv9bVm0SKjv9BV4ksDzQt7JYXgl8YIg8MzEnRyLVwJP3gdjC3MBeWcm7sx17Ig8jK+hOipMHkYpEwLv6SefpGfEa7htr+ftVFJZR2/44v3GfSDxthZ3WebEu2Z8JV0zscpT+24qKjeC01NnFpWtHH4zbdPP/bkch47pRVjDU1Vsgw479rNuVvfAPKvEpGIOqm1uhxFgBBgBRiD7CDCBl32MuQdGgBFgBFIQANEDEg/FykxAGlKAvENOO+OV5xxI6gS8kmP5WH4c8JpqYgaxoFO8EHhGwn/xHyjFoA479+IztEjVsqLzk4nDocJzKpNTJ9AYfUVn6L7r5PJQbh6k3EMg8BBu/LQg7/5y592G4s5coMIBcTcuPCysyvHnXUyXvOVyLRyS+dqu/7pj2KxVY8iJN37jv2v1g0pu4Y9OIbR2xJ3s3C+Bpz14m4pmwgrvTQjHgzFIpgTek488aJn3TmfMV9/0uE41z3WcjBLuOrqVtve30Y6BY0a7xSKy+8SG+fTGhSfQ8mhTxiZC+SbZJVhOuSM9A+rxBjulo9/0Ex67z6h6GBWCcKueIwwsuDACjAAjwAgULgJM4BXu2vHIGQFGoEARgDtsxzSxZCYyVEIPqq58q+2sIC4E9QPG7YWg0iHwQNjhMIuCdZEcHAg8nYJQ2rJiEUorAHQi8HJB3mG8OGC2945k1fTEDhfseyi3gGNcPA8vPLuNfv3VdMIS5N3AiDPZ2XTahbT2nIvpVevcD6ZyzqUX/ovOkqXV8aLCczNSMRN4khhWQ2WtBqk60eqG0PqarMNNKpE3JUjXjr5RKhs5SOVjB311tbOrjv74nfdp5b4zd9BcXUfnfCGhwAu6gMAD6aG6NYO0A3kniTtzn8DmRGGw8aZFGzMi8lR1Y9Dz8tIeyLJq4cTb3Z8992a38ZhNLybE+wIIU6ngdbs/19fD+hkJNX+dCKHlwggwAowAI1C4CDCBV7hrxyNnBBiBAkagtWvYIIDKhPqoQSjFUIZEeKxTGGaYposwHKhuwkgwSpzcFFAqnk4EHg7SUm1nFf6qS+ChPxBX5aW3G860ViWbYbPm/rzgE9Tek7kcoS7F/u8UxI/cQ7/52lfoyK6ZEE8d8g7jWnvdd43hNVUXu5J4Bqn2P78muuUeX1OauPp1NHHNxVr3IoRuaGSChnZtpYmXtovX88bPyPL14nUc7WqKUF/vYSOcuRg57kSrMsedUwfHb7yMausWGlXyReDJ8YFYgdIVBWq84tY/a2GjVpIutLd/6HTP9+IGEHin/5+vU9Xi9b7ud7rJrJAGeXfD7j9q9YN1/fqJF9AJdS3ajr5qw27hu1qDCKCSkwoxgOY9NSFNL0BEoeDzErkZs+m87mmA05XDqlKHWhYpMLgwAowAI8AIFC4CTOAV7trxyBkBRqCAEcBhF4dfHDxwKOkbjIcqTNYN2kIwsvAyRrOJhTlM1o6olCYWbnjJ66qqBoo8vFAm6QTjlcviphALciySjIBzsjT5MDvCqk606HtgeNI2bFaObfEV11HFwtXJoa5bUEp42ZVcE3jHbvokje553nI4kxNxOrJ8HvVuWJ9ibHKwq5X++uJzdKi7LXnfwvq5tKihhc4/6ULasGkmXDjfBJ5KVIDoqYofpKL+fSIUWrgJOwsnaVLk9JwcmKT9f1hAwx0VtOXwW6lzok+8IYppi1eR2Cs6Zf38ZbTpI7frVPVcB27WceEcDsdflC/s+oOt8s6q8XVVc+gL68818pjqOPqqbYSFOMMeA9mO/KthKSDHQfCXii9EdE0vcjn2sOaJbRIO8nhmuTACjAAjwAgULgJM4BXu2vHIGQFGoIARwOFDqo9wSARBFKYDkhu0Vrn73O7J9XUvY+zq6KW/P77VUNqBZAP3gDBXNwfUk0/fQA1NtZ6mNr+xnI50Dnu6JxuVcQgeEcRENvMrGqSOUHxAuQi1jCRCMB8rHKQbLXLejcSdGaCKBato8ZUfSoPm8lMrbOECgTf0Q5Fr76cJx1uvRVeBNy7UdmM//LylYYlU3KHvsbEx6qosoaOveZUxlF8+9WAKcWce34lrzqQrX/02Wrc4QfaGgcBTzUgwptrhbRSbEkScKIL7siTyxruEakqs8YG/LDTIO5T2rv+kbQN/mpkySLwSZxIP6rvm6vqsEXjqM4KwWby8livmbSC81LBjmdsU6RTsCkggvB+p4bte+w6ifhjNGJoFEdUlQnrxualjehEEDl7aCCNm2EstDeVepsF1GQFGgBFgBEKIABN4IVwUHhIjwAjMfgRG4xNGCCoKwmjLxWEtnzmGvCJeCGPWHaMM69y5Yz9t27o3oYbSAMSr+k42icMncoa5KZQ0hpBRlWwqa0DcoX0nd16zAk9OBkq8X375K44EHvLeNb38Isv5n7k2Rs01iRA7c4Eqc+TmzAi8I5tOoGPbD9DWOzenNL/hyjNpzvrFNPe4JTT0P58l2rcjhcAD0aCSw3L9J8bHqFWcqz8+edhxPcvLaylSkshf9bGrbzRIvEwIvN3HjtLuY610//PPpvR7wXGbaNWcFvGa57q/zG7C8obqoW0UnewT8038RiXyrMg71OkbuJ/a+u+mQ/H2mX4dSLyKaBktbZpHVYvW0cp//pTrWP1UwH4ZHB43DCm8qu9kf1DhfWr1PyW7nyHyIgYB1T+UaN9czOo/P+MP4p58hNq7jdsuv6md6YVbe0Ffx3t8tzCqwhd1YSkx8XdG43S4e1jGxONgBBgBRoAR8I4AE3jeMeM7GAFGgBEIBAGpwkq4/EXpWI+eY2ognWfYSCGM2c2pEARfpSCZMBeoXEA2PfHoFuru7HVFxy95h4ZzGbrqNJGgFT7AEaGCIO+AJTB1ypGoqmjM49xxOE6b7/oNDR3aTUOHdxuXobirWLjKlriTbTiF0cq8dHTe/3FdY6sKT7/sFNqyM+E6aldefpLIy9b9rLGvoDxEMYg78b9WORRx/WjnIfp+7Rjti6UrzqLRCorGKtO6+9n19/km8L71yP20p73VcR4g8i48/kTHOnYEHm4qGe+lUhESWyHCaiWRN9Y7QW1P1VPnjsaUdkFqoRxq/SANTY5Q53gfDU9Nvx8KEtAcTiuVd7hn5Zs+mZX8d2gbzyqMErCPr37af5ju7SddbYmjJJxw0axQzYVCVuchCJubqo4rrtn0QpKwOvPNtE5YDSzwfo8ceFwYAUaAEWAEChsBJvAKe/149IwAI5ADBPoGhuhPjz5Nv3ngUTrlxHX05ivOoZoq+zA93SFBhQWiA6UQTCHM84IKoq0nPy6muhibwzRx+IsK4g7KJRzKzYdmtCvDae36WLF6Ma1Ys1h3CGn1wnIwB4FZJsi2TJ0cpYIRuOoQdxIQJ2XPX3aMUEe/fXihE/huBN6oeObGfvQbitz+e09ruLcvTn+ev9L1nldOPUAlZVGqX9homFNA0elEZPYMdIk16KLHmqror+KlWy474xp6yzlvFXkCp1JCk93u1yHvZBsrm1voutdekNbkn7rH6E/d8YQBh/iPnN9r6kvpNfXWLpcgqw7eeMRoy1C5CkIzYhJKjozupmOd3zbqgMgbnkyQeJHaiNEX7kHIrCzZVN8l3pfLkqkOvBJ4Kw5U04qDNcZQ37n4VOPnxOutQxitlGNwae4VuVHzreLy4ubttveCuK6rrEZf0vSiLJqQgo6IvIvZNr1w++IoCAz8tNFQHSOJg5/7+R5GgBFgBBiBcCDABF441oFHwQgwAiFG4G0fupFO3bSWXnvGSXTLnQ8ZI/3i9e/KeMQ4nMm8d14MFzLuOKAGwqIkc5qODGXCwR+kHdxPkX/KTR2GNkHkmdV4mRB3cpxecvMFtFSWzWTqlKgSd1LB6MWVWA1PNA8QCjy8/BSnEFo15LTk+q9T8dZdWl3Eh8fogfK51FmVIGScCgg8lMrGaiqvq3TNo9jadVjsyUROxK+ubXFrPnl97eIN9OV3ft0TgXfftmfSQmbdOvzga85PhtPuHZ6gHx8dSd6CvFpFCoEnL7x9XhktK09l5/of7af+xwYMUgWKPLvgQpXEk+0VVxVTVIRFTyKn3vQvs03eoRs1zFuXwANxd+5jC5LkHdpZVtGQxGxckHh2RB6eKShYK2KJ/Hf4kiefBJ6O2s1t/wR93a9BhDTSybbpBdavVGzwviF/719B4yXbAxGLLxS4MAKMACPACBQ2AkzgFfb68egZAUYgCwj8VijtThaE3YKWJjrc2kEf/OR/0l0iIb0s577pwwaBd4qok0mBGqCrP6Ew8XsoyaT/TO8tBPMNkIxQCIE08EMyZYqR1f1QkMCRMt8HPNUR126eu/ZM0e4Xie57cIZued15RXTShlLasD6SdJT1g5OTEjETAs/JxELN+1e0ZaehwtMh8e4hEfbpQt5JA5RTx+9PwtG0osWVwNvXuidZ30zgTQqjB5g9qCUiyCxZ7v7cQ54IvA/88sd+loq+/ca3k5m8Q0N2BB6umUk8SeAVIyTWhUcAidfbfz+NjiWwMRN4La+8gvDKdlHVZzoEHog7vMxFJfBwbXJNCcU/ak8GA595wnAASsVRkR8vlyGg6ti9qN2yvRay/UwNIrJtehHGz8US8aDOEQQeF0aAEWAEGIHCR4AJvMJfQ54BI8AIBIjAC3sO0BXv+jR9SRB0rz//DMK/QeA99IuvJXsBwfdHEVL7nzd8MKOecThr7U6oWcIaduM0wTAe7jBeNUwW/0ZYZ49QO4alZKp8C3IeTuFxN3130iDvZDGUUwhjBAEhlFArVxB96H0zZJLXcbkZMPz6ySGvTZJT+Cwas1I/Rm67xzacdnLDajp87ZX0x8/fZjsWSdzBsRgKRKnAww018xuMcFqnYkXggbibHJgU5J31ncVVRQQizwuB50d9J3uHCu+WgXTCyYnAW1pWTO+YPxMyKgk8c9hscn+J/7FS5YHIiy6PUePxlVQ8dw1VLlzneV8cfXhv8p555yzTuh/7vbm2TOQmTbxHu7nQQnn3nl+kj62utJzqxctcnEg82Xd774ihGkZuSRQ7wwutCfmoFEY1WZAGEdkwvQhyfD6WzPIW7J+6Kuf3oaD64nYYAUaAEWAEsosAE3jZxZdbZwQYgQJDACGyL7x4kJ56ZkeStHv5695rKPCgyEOBKg8qvMd//72Mc+G1C+OKOCwaRSmEnHLqcoaNdJQhnWqYbKlgnMKgdlNx01G+5eqxsSLwoLr71vdmqJQkcQeCysSwrHIh8XZN7qF7xx+g3VMzKjPM7aLI+XRS5VpaXbzSUPFZlfa+Cdr8gjdjFyf1HfoAIQE1ilWfIPLUMnHNxcY/t96xOc1xFr83E3fyXpXAK6+vIryciiTwDlRE6ZeLGwjk3USXe/6/InEev+fbf9RW4Pkh8OKjwzQ+OkINh1+kBf2dyWnE56+hoVMvocmFay1DaGVFNSceCLzBxxMhtE4Fl81EXuUrqmjZBU1CsTzmmE9Qbbf/xW4CcTfwUk9ad1XL6whEXvWKmXx65kpWz6mTCu9rX0nkuTMpMiNuAAAgAElEQVQXs/pOvW4XTmvVtySbcG1wZCLrudwwzmw6VTvvAvur2ficBLb43MALn8eZKB6zMT6/WMn7YF4BlT8XRoARYAQYgcJHgAm8wl9DngEjwAgEiADUdh99/9X0dpH3TobJfuLGHxo9qHnvzhEE3k9uuj5J6vkdQs/AmGGkgFIIOeXM8wzDYSWRMyqS4iYrc7GFSe2mYmc213DaPyU7j1DpriNUfs/fjWrx1fNpfM18Gr74ZL/bLnmflROsVN5BbSeNA8zEndqxHYn3zbHvpBF36n0gwD5S8UFaPL7cdh5eQmmdct/JDvwoiswEnh1xJ/s4fupJqqUu4586BJ7MgQcTi0drKrXIO9nXj868ixqurtUysfBK4A33ddNIf4L8aunrpEUKgSf7H1+whgYu/6gtqaaq8EYPjFLPrxK46BSVyJv/lnpqXF1HUKRNG/s6NgHybvd/P+PaDYi81e8WtsEWBV9QgPjo7JuRQW7vb6Mbdv8xrbZd6GxLTORBjNg7f9qp8GS+tm5BWJqL4fwr3u9ANg2MjBt5VIFJd99+2nd4M/X0H0i5ZemCM6muejHV1yxxxcNcISyGO3JcZlWk5wm53JCp6UWYvpxRp9pUGyPsGy6MACPACDAChY8AE3iFv4Y8A0aAEQgQARBzD4twWYTJPvnsCwZpB8UdCL0fTxN2cKVFmC1UeZm60YK8A4mHEhZzAy9w5ot0xEEJjnpQFcQFu2SnmMCBbK5wkpShyl7mls26IM6QoN6JjABxB9IO5J1dAYmXCZFnXj/kunvgoSmDuENIKF465br3FtHqlTPSKjfyDm1KB9MPRN5nKPHsipsSr6m6mF61Ti+/kx/nXUnguRF3cvw1U120gZ40/qlD4EkXWuS/i7cmyHydcn71FXRR7ZVU+YpyKhcvt+KFwOtvP0rjYzNmFXYEHvqMCxKv79KP2Hb/+eWVyWv9d3bQ0D5v4ezYVetvmEPiaU+GszrNVZe8k22s+pcTLZV4BlFWlu7SbEXivefna1NMK9C2G3kn+x/90YzBhfwdiOaYyJXp5BAtc7nB8OKPT95MHT37HbfAprXXeCbxwhYO6kRsuu1/r9fN4bUwP3IzFNFZN6/jyLQ+3rdaRD5FLowAI8AIMAKzAwEm8GbHOvIsGAFGIAAEkO/ulrsepi9+9J30lCDv4D6LsFnkuntE5Lz7jSD1LhV58fDz2qvOo2uvOCfjXsdEgvKO3kSYYFjVYk6TzHXCbqk+iYrDLXLb6bjJhkElaMbQjfgEeVfz9d9p7S8o8vo/fIlWXXMlKGyGRDgeClQ9//Gtcdq6Y0JL5aS2parwdMg73JsIzS0yQkA/VPp+RxIP9a1caUHeNQt3Ut1iR8o43b/j14/Stjs3G2SmrsuuVOHpEHjo+8ZoF+2bLBF57zQZU3HPt+bfnnCVFCxw0/9tdIVAl8BD2OxAR2tKe6vbD1LttFOuVUdDp1xCw6e+3nIMKoEX6xymAz9OD2l1GvySt9dR1YooRSNVhvGLVJzZ3fP0Rx5xxQIVRkRo8MioUAX299ITLTuoq6yfLnv/J+kf4+NUFhOOndMK1PlCQbc4GqVXVs4QkbhfzYmnhs/a5byzG9TYR6ppam2qSg9fTKB/u/Byta1ndtxKfQMHjPoyP6XdLvJK4sGFV1f1qAV6hpXyYfbkxfQi15+HOnCCCG6sielU5TqMACPACDACBYAAE3gFsEg8REaAEcgNAsh/B3MKKD6gsquuqqCzzziJrr3yXGMATz23k/rF79esWJRx6Kw6ozZhZAFiIKxqMSf0DcWBUKpk2yQC/VSJQ610kx2eDjvW2RluZJlOG0HWeWn/TmptfZHu/eNvk0TZ2We+jpYtWU3Ll6whL+SdHJdfJV59ddRYP+w/hOO9433e1FEqLt/9RjEh591N8e9owYXnLCLCFKFqWVW0kv41+n6t+zKppEuSqwpPEMXfe93nPHcLEm/FypjhJOr4DP1/n6HdJRN0w/98RJvAe3/jJ2lVbL0nAg9j0HGhNavvcN8ph3e5zr/zfTdb1lEJvIaaCWr/0yB1iJdOqVhaSkvekchTV1JcaeR9g+IMaigQeWZCFTnvVMMKuz5a29tEGzP5FfesmqB9r9+YrF4WjdH8OXONf8vlW1RaapB4IPPMJfYO/dBg871WBJ6bwYtsA+SdGjKLZwouv8a4RRpFq52nS+KF8fMIBBly1Hl5/9fZZ7p13EwvwvZZg3mB9EQoOBdGgBFgBBiB2YEAE3izYx15FowAIxAAAo889gz9cfM/DMJu7crFhgrvxu/cboTKZrMgMTsOpChhC1lym7dVnii3e3SvS1MKqbZDuDEUi15Lvg996nh/cMvXae+BXUa+PhQzAbFs8Wp6/8FFVLnPOyHQ9T/v1oYGhChIAoTwxgWmkoB93795x1d2CgIPhhX3TjygPQ7sHxmW9r3YTdr3ea04MjlEo+I1NjVM8aJhmhCkYayonGLFFVRbkjCnQcG6QIkIfFSFp52RhdM4Tr3m1bThlCbqvOd2mnhpe1rVyPL1FP2nq6hk+XHGtce+sJm+03mD69QkeYeKUoGHENrKV1a43uumwrNS360Z6qKa7g7Xtq1UeGYn2uqKCSoVufQH9465KvGaXlNJzeKFMjJWLAj8ciOEVlVE4X1TVeG6qe+gumvtOJYyl74F1bTzivXUG00lFctjMZrXPDctjPxNdXVpJF7pf/RR8U5rMxY34KxCaHVyzyHn3bMvWLsjSyKvSHwdNSkecpVDRj68E9e92W1YxrPQIAj+9mmFuOsNOaiALxwyMZgIaoh2phdhVHs3VMeMdBNcGAFGgBFgBGYHAkzgzY515FkwAoxAASMAJUnvYEL5FMYQHDdovRgyuLWF637CZJ3azUfYldV4JHmHazL/m1VI5qefaKDGhrkUE2F8XoqbCs+KnDK79OaawEP/yGGIAmfai0rO9zJlrbq94x3UNzHjoArVHwg8tcyLiST/5dXCsTgRmg2y2Lw2f/jcrXRse6pBgN0A5qxfTBd/6a1UGik2wj5RRv9wR7J6TBB35nLsK4kx3t9/Fz0gXuaCnHcro+sM5Z0sIPAGu9toON5BxVWph/TGsxZR41mL09r51iP305721BBZWUk1rsDvGuPDdEbvYeofn6J+JycTUdeKwHv7vDJaVj4T4lwSmaKayhmSGGq8IUHmqXnxVOJOjmtwJEK1FWVpOfAkEY216h8apyf+7Q+Oe8KsvEPlpz54mnGPmcDD78oEidfSlFDiyQIl3j/Xp7rXRn47TCXi5adYEXggqvrFvnHKubZXGFbAtMKt4LuCYvGGoxJ5rzn14263kZ98ka6NZlghbCG9qukFMMZ7bJsgmXWMVjKEQvt2kIoG0c+FEWAEGAFGYFYgwATerFhGngQjwAgUMgKj8Ymk0yEOTeUi5MXKfTCscwxKNaiqwhDOGVSYlG7YZDbxVck79GPkfxOHKvMB/axD5YQXyvx53lwj7Qg8s5JRVSyZk8JnSuC9d/RDnmBE/1JVmQ0C79jYARoVqju1qKo//B6HW6zHonKB90SZY547HRIP5N0/febNngmQ7p/3UvygvoorPjJIva17jamVtAhZm01Z+JbjqWJpbcpVOxJPJfAkeSdvPDLqrM40E3hm9Z1sR6rwdDdKXEAyNFJCUKWpjrDq/dKJ+pH3PmiELFuFjvb09Rr57tRy+LQFdOS0hcavrAg8/L6laY6RE08tCKU158RzC6PdubCddi1KKBlXH2yiNYeaafz15TQhXuYCoqpTmNw45VzUJfBk25LIAzpL559Ji8XLqfhxbNZdUz/1whjSq86jSiiakeYBBZ9fOqYXfnDwck+JWPQ5gsDjwggwAowAIzB7EGACb/asJc+EEWAEChiB1q5hI8wJZAvy6BzrmcnPFPZp1Yn8OjisjAjlktcSVJisU7/5DgVDzrsf3vqNtCGaiSRUUAm86qpaqq6u04bUbGahYgvSDsoyMyEgQ6D3dCSUPH94uNl4oSDnmG658Lwiuki8vIbQuinw4p2DhJdaShsrCS+3YlbeyfoSd+CTdNudjjFsLl1EZSKs1qm0Pb+ftgpTC7MaD8TdhivPpLnHJYhXr4YZg48N0eBjeioulbwz1sqBwMP1xW/bQGWLa1KmtfvYUbpv27MpajwQeJVdR2mtCJttEuo7tYwKjDrj9vn8VALPjryT7emSeCDv+ocipBuq/4wwsJBqIzOR56S+w7jMBN7RkUQoOPLhLW48hRorZpSPViq8ohfiFP1Kf9rWuef0HXTPK15I+/1UWRFduOgkujC6Ke0aVFNuztl/evJLbo+A5XUQeceteA2tWXqWoVq0S0sQNjU49kB9VbhCelWAJV7I0wjVN8g85OtzwtjXAnq4CekA6gRmXBgBRoARYARmDwJM4M2eteSZMAKMQAEj0CHUFiBYUObUxQylia7jZb6n7SdEVSq/QOCMjE1aJqQPcl46B+Ig+1Pb+uNf7hG5FX+f1ryqPpMXVQIvKoiDpsYW7WFJBZ5UHIKgAnHnpGTsif+N+safTFECfukTb0j2GSmq1CLykP8OxSuBZ5cDD6Td0K5jFO8aspx/aUMFVaye40jkHRzdaX2vUP1NIS+YIKTM/hLIizcnmh52qr0ISkWvBB5ulWG0bv117NuWrILQWXP4rHo/VDgop3zl1Y5kwsDBXtq7+W+09Yn/MeqXWhz8nUg8SeCBvHtNfTQldNZqPm4k3vBokdi7iX2li6U0sUjkgEvMWxJ5+w6nhz/L8NnxImGKUToiQoX3EIi7AfFTLbHSBAmyqvFKWi1eKB+ZMydtWmouPCjuQNxJ1Z1aGeQdtSRCi1cVz6XrylNDx6HAQ74/p+JVgae2tXTBmbRmyVlUXQG32yIjZBzEkxr6qZOHr3xfqqPw8FL9LxwcJ2dx0TBMEgr1ngH/Rjte+/RSH2HPw1DeKV9kuZleeGnfT10QnsCNCyPACDACjMDsQYAJvNmzljwTRoARKGAEQLQg5xGK1UEgzFPTDVEFoYQcYzBPADmJQ2NQYbJu+EDViDyDTjml3Nrwe/3jX/wXy1utFHhL+krordtnlFJewmgnLz+Vom86XRvbI8N30cjEYWEqUGwYWciy/6Vmuu3m1yT/XUSlFI2k5vxSJ3Tde4to9coEWeLFhRb1gQHy0a1UXGhB3vU+sU8L7tqXL7Uk8azUd1JxVyQIC3W+5o4WxdZo9e1WSZd0UtsZOxCnnl/0OTY91HOM8EIpjonVaRDPk0XSrYiYJxSGeNagm2t57RJaduFy4z5VFdT2+EFqe+JQss89e2+ngcEE2VUsntdYQ3qIp1VOvOp//7EWcWeeXHksXbkriTtZVzcfW/+L3bT7v59R9u4Mkffiwf1puEoCb6BkmHomd9HugRkHZexoqTeUBB4aaChfT6cv+rQlgYfrUon3tTdsdiXv5IBUEk9XMZwJgafmwJM5R8uiESP0EzlZsZ2QGgEGS1ZfJIG4K9+fSt7JuQwvqaNsEHlhUwSaN5OTgYWd6YXbe0im1/FlYInIw8mFEWAEGAFGYPYgwATe7FlLngkjwAgUMAJqHjw/irZ8Tt0tN5EM5cQBEaG2OCTmmkjLJynqRODhcDzW20sTwh1zciwRNv2llxKhekXFEVqwMEG4OBUIjUDWjHzsUhpc3qKFrSTv0K4VkahL4qnknRzjN8e+Q7unUhVMduM3CDyBwXUl76fVxSuNcFld8k62aUXiqQSeJO4MIksQE1bzVcdXE2lMcaZ1w9/uuh8CD2255cKT6ruiqCDEGxM5t1QCD3sBewK/UxWG5UtqaNFbNxhqtloR9g4S8+mfPEsDh1IJQ5B3IPHUEhUhnRHx/JoLsIXCbd3ZV9Bx4pWt4iUf267vP00DL6WSSyDj9too8KC+ay3alkLeGc+feFkReLgGEu/ul82QfeZ53zf2LN3XPkMkJq/X2ZMpF5ZuNMJpsT+rK0pd86A6udA6rYOdC610962IlRjv0wi/NBsylAhVIMi70l5ndSD679so3ouEkjCoks/3cLc5JFJfxFxVk6rpBdqE+tysfHTrS/c63gNaLMh33fu5HiPACDACjEA4EWACL5zrwqNiBBiB/2UI4BAscx7JA3Z7b+HkwbMysoBqplKo7WQop1UOtlwtM1R/KFA65rrYEXhTcRE23dsjyLvUdT67u5nwQmmIxCgmkuhHLBxpJVEDkmZ01Tzq+/AlWlMbnjhER4d/naxr5cqKiyDxNj9yHB3YmwgVLC2uE8RQIpQQOe9WrRDJ+KeVd+aOdUk87I1/jb6flk+JxkTpfXyvbdis3eQQTlt7+rKUy30THTQw2TWjQFNSt+WSwEOIop3xgtNiOSnxQOCBvIs0RAziFgVknR1xp/az+tOvTP7zwK+306Ag77B/zCorVYUnb7Ai8Qy12NK19Op3fUpr7/mtBAIPocC6z68ViWcVQvv4dScbobNP96SbrzgReKUC929t+AYdV7PRckrvH/ypr6l+p/KtRsijbqjoMztuFcYces7IckCb1l5D9TX2BjnYUtXlpQRTBnyxpKo1G/68z9O8giTxdIw9PA0uwMp+zKfM4bVBm15gD4FU5MIIMAKMACMwuxBgAm92rSfPhhFgBAoYgXZhXIGk1yhO4ThhnKJUR8RFOGS+wmSdcPFzwAoKZ7MDrUG4CMXdaEciDNKqvOvIElo+UmkQeCgqiacSd1J51ffvl9D4mvlaQ1bVd7jBUFEJAsgiCjPZHsi8joOn0cY1y2xJO3PnOiTep2o/ZJB3MpS6497nteZgriRVeFLt2TPeQYf6Wy3nlCsCT9d4wWnCMLYwl8N/nFF2yb1g7CmT4s6qXUngqWGzhoLT2AOpRF7rsUcJL1mswmkXrzmeXvH2T2Q9XydUyRinLoGHMZtJPLMLbVd5Pz19djkdXdpq5L0zF0ngRYQStiSSqj6sLC6mU+s20WfXfy3tPkN9F3/O1z6GCu+qmpM9zdULiedG3slBS8MIpHXAlzAo8e0dVPJil6d5xWvLqH+Tfh5Pp8bzmcfUbdJ+9qdsUyofgza9gIpTfnHlNn6+zggwAowAI1A4CDCBVzhrxSNlBBiBWY4AcrQh/xAKcrbl073OK9Q4wFSW4aBbTENiDjhoh8mEIwgyxSsmsr6VicVIe1syZNau3fccXUYbx2aSwlcvXGIZGumFvENfLw38Z0qXRrJ/DfIHNy2v+qAnGJATD8YW5pDaiyLn00Ul5xsHTBBH2PcwrRja3e6pfVm5es0cmrtxvkEeY++1DrZR30SnZVt2ikNZWceJVmeQIMVgBOBHgefU/q7PP2ZcBnmHPvCcWeXAs2pDEnhbvvl42mVJ5BlE4HRaOoTT4iWJPKnCa162jtaLkNl1mzZR93OP0WTnISrqPpLS5tTyU4hWnKoDlWsd7JNxMU+vOTOREw/htPInVHi76w5TZ1kfdZUlHGM7XzefWgWBZ+evq+a/Q32o7xpKEoTer057KG3smRJ4b6w92fNcdUg8XfIOEzLnHDRU4f9vrxFWDLJf7g/XhRMVus5aqlPNsY5uXsCMO/LZQFDhvUGaXjSJHIZojwsjwAgwAozA7EKACbzZtZ48G0aAEShgBJAPp6s/EU6Zz5BPLxAi3Au5kkoFcQciwS7puZc2s1U3nwoONYzWTX0n539udQud2lVPC48k8khFa2qppLo2CY90nfWKlyWBh4O52ZLVomGvBJ7b2FTlil8Cz8g/dXwLxVY2Jwme/nv3Utea3vTuY8VUIhxSJ0sToafmEqQLbbYIvLZbn6fBfb0p6kIdAk/mwIPb7O7bXhAq0BlVWbRmxtlTiMsMclAl8iROc1++kOaevijxz67DFDv4Dxo7dtBxmadedqmIBV/gthUcr/sl8MyN7nxpF3315ptSfr31tM1UNP1cqWGzqFQaEco/AKKUeqHGi0473H5m3VfTwmgzJfCubjiFRoTBj+pmqgMecuLtO7w5LaQWjrPLxMtLMSvKVNMKEP6Yvi6RF4SphZewYi/zDKpu0OG9QZhe4PNOOjEHNU9uhxFgBBgBRiD/CDCBl/814BEwAowAI2AgMC7CZ4+JMFoUXWfXfEBndpMdFIqnUZEQf65IWC7z+OVjXG59Orkqut2b6fWX9u+kH976DaMZHfXd+bUtND9abqiCQKwhvHXR0TJafOk1FF89Xztc1mrcaQQeWAtB2OSDwFPNCbwSeKo5Rbkg7ypWz6GJ3QMUf0CoG/cMUs9lkxRfaL1yRbUlVFRTmnYxKPUdGg6awANWILL2P7CXDj60N7GXhBRqaGIiZR4lYi3LBelUaiKeFr7leOo7PEEHH2ylcaH2NZfi2IQgieMi32JCfmdF5CUJPEHeFf3jN66GILKPTEk8KBlH45OeFXhWq28m8ba+7BHhbFKaJPFwDx6J0hKxR4rsyTvUywaBd03jqYYjea6NflSs4PiKdA5S8WjlOov9USz2Gt6bnELwgyDwMglRzfS92+1+NxMnt/udrkvTC3xJBox1TS/whVqzcKDlwggwAowAIzD7EGACb/atKc+IEWAEChiBtu4RQ8mWzUOBX3gQhoo8PdJN1hwmO0ccGGC84ZRLzW/fQdyX77BkSeINKW6YWGczXidW1tOm8jrLEOSTbvivjKEwE3gYAw7iOiHPQSvwVKdWXQLP7CoLQCpWNVOsqIJGv/NSCj7tH5iOBbVCTajxiufEKD7VTeMkzESKWmm0NBESWUXrqKpoPbUU+XdWDYrAk8QdTGDkM7f3J1uozSUfGYi8GkFCoUB9NxptoIGDwxQfGLMk8CREZc0jSRIPv1OJvOZTpxV4f7/bCJl1yyeowr5tfFXaKjSvXEFz4IbiUkDgDY1M0Jj4oiCIAhLvd4/cSzv37qaXVj9Ng9XTrrVlFVRcUWnkvCsW5J18PpHzrkqQIuZiFUK7e6KVvjXyoK9hXld2Hr2ycakIux7Veh59daJxkzkk1IrAk81AjQell/plg9pFEARekASuxvQ9VcF7GPIEdvePebrPa2UvphcgPOE0zYURYAQYAUZg9iHABN7sW1OeESPACBQwAghBhRsdipWzaz6mJsNkpZssxmdF0uHQBzVeUIfsoOcKVQlIKplnMOj2ddoDiffLr19PbeMjadXnRctooyDu5kQSIbNWJQgCr3vsb4SXLAaBh1xqwoDEqdRHTyO8gixmpamdiYUcI5RRWEPz/oOJxcTtrYbyTi1jC6Zo6NQpSyWeyORF8eYumoqJfI0KeafeDyIPJB7IPK/FCO0VLpDHetLXWqctK+IO97WOjdHmbYdo0d3u7qOSxCtetdQg71DcCDzUMZN4+B2IvOWvXkaNjYdpZMcTRls6BF58ZJQG2tvpxdZJ42UuzSuX03EXnOtI5GXzveWWF39At7z0QyqLxcQr8eyBlCqaJrUlgWnl1mtF4OH+bw2LvI+TbTrLnKyzqnguXVd+vmFglG8lszkk1InAkxNQn1GoeWVEfhAEXj7V026LCLIMz3qfUE3mouiYXtRXRQ03Yy6MACPACDACsw8BJvBm35ryjBgBRqCAEQC5BDMLlDrxDTpCU70mbg9i+jiQ4GBSFi0WoVSC9NIg5sKet08N1wwCI79tPP3J9xi3gsQ7NoGQ6SnaWFaXPPA6tRsEgTc8cYiODv86pRsdImZe+eVUHrGJSfUJhlmlZlbhuRF36La0oYKqmprT1HfqkAYFiTd0mkpQToK+o+L2Qeo95R6aLLYnW0DirSz+lK8ZggjxSuDZEXcYAMi7h3q6jbGUHxqkpic7qPxwulOtHOzQggqaKq2mxs5UNc5wWyrRaTW5yoXp7baI/HeLyp82TCsQ0gflplOoZ/+xdhofTaQFQHno2YRJj1V59QfebUviQT3bMxDPmirtDX87N2VI2JdTJmMXlcjD3K+cfy1dtfBay7n4UeFBfbcq0kJ+9oyvzelwkxWJ2PDnfVrdSEUvfgKnvhNaaEy40WZSwuzKnk91IMxGoP5DyOyA+NsBfz/gyw2o4WEoxYURYAQYAUZg9iHABN7sW1OeESPACBQwAlCvdYgwVBQc5BGumu3QHBUuI6RR9As3TzVkTwdSHCbKBemXy/HqjEvWCUtewZd+fBP179tl5NmyCzuzm1cQBB7aPjJ8F41MHE5240bglUUW0Pxy/+GkdvPBIb9ZHO5VkgsqPEnc4T6ZA9CuDajv6MlE7judMiyIvNGpDoqJe1AOfvOXrrf5JfG8kDHYnyADnJ67B7u7qC2uGE4I/Br+1kFlgsyrUIg8EHedpzbR8MJKWvCDLqoRIaFqTrzRrmGaFCG5TqVU5MNTzS1Q94R/PZ2KHv6ucZtBaIn/TIg8fFaupFJ5p/ZhReAdLo3Q36tidCRaQvWLUgniN27cRG/ceKLhyp1NAu+OQ7fQHYdvSQ7VisCTF6HOO6npJPqPTd9wdAr3QuJJ8i4MbqtWzyTmXv1sK5X2elOTTjWUU+mZSwxVOcglnTB9857MVMnq+nBnWCFoAws/wzGbXpSLvxu4MAKMACPACMxOBJjAm53ryrNiBBiBAkagFYdrweyAVGkQYanS2CKbU5KqH/SBPFt+VH9hOHw6YZTvvIIS4z33/ZZevP+3hlJCugTqGEjMe+1FNO+1rwtsG6gknhOBly3yTk5EVfsAo+K+ETr0p92uxB3uB3lX2lhJI99+MS181g4o5LuLU0LFhtJ73jbqO/95V1wRSuslJ97Yz3dRjVDHdP5ou9F28fGNFNnQSNF/Xp3Sl1Qh4pduJNXPjqWSlGqop90EQODB1KJCkHhqcVPhmQm85Veup6pFtUkCD21h3+C9CuMwhzZ3HzyUNiQzgffb+gqDuJOlrKaGymtr0u777pWvp4VVjb4IINeFna7w2e0fpu39W4x/YU2cjBkQOivVT6jfP2SdOkCHxJPkncSzWoT65/NLEKwp8qd19qXmdCsRoeA1z7XqwmnU69vYQlpeknsAACAASURBVBMiJBhqbuRPhTGGHVZ2DYf5i6F8f6aYMcN4aiujxpdwXBgBRoARYARmJwJM4M3OdeVZMQKMQAEj0CESmEOFg4JQGByk/CgX3CDAIRVhr1JtNzSaeZL4MIc6AY9cjw8HKqgogTPWVGK86+Zv0IBIoO/FQCIo9Z26L2Q+PDsCLxt578z7EmvSK/JHASPsc3nA7318L8W7rMNDETYL11mQdyhD1yWIF50yTAkHV1l0CTxdFd7E1k4CeTe5rZNKxDM2LpOBKX2WChKv/Jo1yecPxJ1b7kg1fFY25UbgVf9jmGqeHibkwqudNrSQ904IVdSYMM1xKjKMVpJ3qCsVePh/dd+o5iJDPX000teX1rRK4JnJO1nZrMLD70sFqfSps8+j41vm6Syx7zpSiYd5ISekOSvk+uoT6LPrv5bSvlT24pd25NR9Y88a99wXf874iXx3CJe9MLoppS0Q2DGhZMZ+yFdxGoMXEg/k3bgIIVeLzKeK3yEtw4iLChT1cp1jzgvuYVF1q2MG+QrMuDACjAAjwAjMTgSYwJud68qzYgQYgQJGAAq4/umE2GY3wCCmlUmYrFv/+XZ6Dcv41ByCViGR/Xt30e6bv5kMFXUzkFj1zn+l6mWpyi23uXq5Xhpro87B/SlEMci7v5fupn+Il1peFl9F8ycaaP5ko5cuLOviQF8rFEdOyhzkxVMLiDtz8aLAMxN4x973CI2ubNeay6bi2x3rgbwb+cTjyTp2BF5EEGrlJzVT2ZdON9SuL92fuGfv9M9lF5xO9SsXUv2qRcm2nhscoOcGU3PX6RJ4aKSxNN2VEiTeuHCltQunBYGnknfGYKYdaPG/VsQv9v5wbx8N9vSmYSUJPITN/q4hQb6aS1VzM5WWxVJ+DQJvddNc+sJ5F2itU6aVHuj6uZFTbEqJMl5fcwIdV7PRtmkdIs9tXCBesKb4DMhXcRsDSDyYWjiF01qRd+p8zI6qMneb1ZzzmWPObQ3CSC421cYI+HJhBBgBRoARmJ0IMIE3O9eVZ8UIMAIFjMBofCIZvhTUAUFVgiF0E4dTP2GybrCGwenVaYwY35jAV0f5Idu5rW+QtoyO0daxhCpmQ7SUTohF6ZqadALCrGrEQdxOPSlJPLf8c9km7zAnHJJHBJEkcTlS3En3lM041VphCiLvZPHyU1SjhlJx2IT7ciYq0/j9bfo58EwKPJ0ceHKOTgSembzDPWYCD8QdnsUJ8RAaz+HJ5bStI6HKsisnfeAqg8jzo8BDmwihtVLgqf2ByJucdr+Wv69dFaPV165IH9aLT1LRS08Zv7fbu2bzCtRVXWjt1HeoZxVGCwIPZjqfP/f8rKvwMAYvuQvNAKlEnq7KTLYBFSoUm9l4b9Z9TnUJMxB5pSaH5bhQ3JlVd079qrnbhkZnTBjUe8Lixm41D12sdLEPoh4UzTI1QxDtcRuMACPACDAC4UKACbxwrQePhhFgBBgBA4EjncPGz0xDdLIRJuu0RGHOV4Rxu6lL1LmBtLu+o8dxR97YVGeQeaqqEaQdkraDoNEpQ397iF645+60qkHnvHMaC4gDRHpCCWOlurO7d55Q4l0y+nKdaRp1rBxWg1BtTuwecHShVQeoKvBGVhyj9vf/SXv8TgTe8McfN8Jm1SIJPDNxhzqDbV00MRqn7a9KV6qZByRJvCBz4LlNuuWVDYSXZZlW4Xkh8B4WDrTykfivuel57mQ/TgSeNLVwG3um1+c3liffg/22Jd+78R6sm1fUTKT77TuT+6D6hgLcyV04k/at7gWpLfPk4b1TTeeQ67QHXuYWNnIRbrTNIu0GF0aAEWAEGIHZiwATeLN3bXlmjAAjUMAIqHnwcJg8KowtdAkhTFsmWMfhEYchKDoyUTjpQokDfX1VlNqnnXR178tVPRyqKwVZ5ZYk/qPt3UnFndPYEO723UXNdEp1mfYh3dweDoGZKtAyxU8SmztH21yVd+a+dJR4VsSdbAekxdBI5vkXdcNoVQLPi/rOLQfe4CW/T1sGEHgoUnEnK4yPjNHQsYSRRvuSEfFKOE87FZB4TzZVprnQFgn2w+nZRh68hc+NpbjQuvWF65s+stK+WtdhKvrHb2wVeAihVXPg/X3PhMhzmGjuoHgGf1tvHT6L63YhtFDgofz6LW/XGX5GdTJR4Jk7lu85MTFvKJ+dwkXzQZ6Zx5tPV1UQeRWxEkHmRYw9DQVjjTBlUF2qM1rYAG8Om4EFpob3ceTA48IIMAKMACMwexFgAm/2ri3PjBFgBAoYgd7BuHHQQ9FVKIGsgyGFNAOQxF2uYVBdRXPdt1t/OgSjjvIOvIwQOxiKImGsSF9uTCjx/BTd9fXTtu49IHzLRD66n8U309FIl+5tyXr/MnSh5T1OxJ28AWHNyIEXRNigDokHB1o40XrJfYexriz6JFUVrbecJ0wr4uIlS/F0qCx+Ym7m0ndgxk1Wl8CrEznxFrz7UnqoZ8ZB1y0HHvqdK3LfrXhgmAYOJlS9OmXlmxZQ1eJyx6rFPYcpdvBpGmk9kFZPJfCeEuRd90CCfAOd+XdBdj9ZYf+sWJlYqEq/bBN42XLTlmpomNrYEXn5JM/kIobl/VtVMA4Kgh8htl6+xNLZ55nU0fksyaR9P/fiyzO853JhBBgBRoARmL0IMIE3e9eWZ8YIMAIFjMDI2KRQZSVUOW555dSDIcKPcDjMZfiTGeYwEFJOS+8WHnfh4VTTBLUtSdwh3NTMy9y3IN1cQWcL+snLp9Oulzo4LPdW9NLPxjd7uS1Z16zC0yHu5M2Z5P36+fPb6RfipZbJY6N05bFmWj9SRceNVlnO5+D7f0zDK2ZINLdJu6nvJIEHVQ7CZbE/JgXbYGViMdorwn17Z8wodAk8jPHs//w3YWQxY2YhCbzhwSEa7Oqm+Eiqq2zlwAC955xzaODAMO35xWG3aRrXdcg71MP7DtSTnc88msyJp3awv7uEnnh0T1qfXg0s0IAk8I6b25J1Iwv0BRUT3L+zUYBbwo21xCClVEVevskzjK2xJhYaxRtwAuGJfY7wUDcFYzbWy65NjA1j6ps2nMpl33Z9wbW+BN8scWEEGAFGgBGYtQgwgTdrl5YnxggwAoWMwLhgh471JAg8uzx4iUNgxDhII8cS3E5zESbrhqsb4eh2f7avO+UtslPf4UwENRVIGQtBlTFkmQ/P6/hBYKHk03kSe+iF6pfokfgOr8M36ksCzwtxJzvykpdQ3rP1WDt98v/92XasU0KxQ6OT9KndS5IkXvHKSoqsrKKyi1ooUrGHnuz7lPZcndR3aGTqV7tp7PZdhkII4bKyBE3gwZ12uXhJEg/ERveRozQ6ZKGuO3CQin9xJ7W319Kr3nYtRcvLafjvY1QTraKaRusQVl3yDvNLEngmomt42xaKH2ujYzteoCcff4aKSkqoSKgAi8srkrhY5cAricWoek5z2ppIUhTmDrnIgWfksxQhnD0DCdOabBWZ900l8ppry/JKnoG8rBaKWLcUA9nCxNyu+lmiEp/4ogrEZz4/78L2OYf3gpYGZ9VsrtaN+2EEGAFGgBHIHgJM4GUPW26ZEWAEGIGMEGgXBB7C79RcO2EJk3WaWBiVCep4kWdqWBz+rJxo4Th7W/+MOipB3EFNla64M2NwTXWlpTOt2yaQ4avZJgzcxrG7bh89MpaqZnO7R15/Ba2hs6PrDRLZyXnXqj3zfnn0rwP02F9n1gD3LFpUSosXRemMV1SRG3ln7uOGV59FG0zEEEIVX+p+mvZM3eA6RSfyThKWfU+1Uee/P5rWVl/RuLF3ZBH+kFQkksH5VeBJAg/twZX2jh/cTKMnbUrtVxB3RQcPUcdvdlB7R23yWv38eQaJBwKvNlZF1Q2VdPY1pySv2xpW2CBkJntA2vU/8nBK7a7OboPEk6VY9A8iz+xCC/Kufl5CwQpSRg2VxPsfyHP8Ptvhs+gfaxoTIeW5eh5VIg/9t/eO5C1UNNdzd3v4rN6rVcMLfD72D4kvr8bTw9Td2v7/2XsPOMmqMv3/7a7OOc1MT855hjCASBIFAQVWwgyIAorxv6sromtARX6KsqILyoqy7qoIIoiSkSQISM4zwMz05Jw651jV1f0/z60+1adu3XBu1a3qmu73+Clnpuvcc895zq3b3G897/sm+36mFbCAU7FK/G7jxgqwAqwAKzC+FWCAN773l1fHCrACh7EC7d0i0b0oPoGGhwU4UArFf6T3CvjkFZKkU4ZkK+emeq5OjjcAvLu7e4z8dsjXBbedCmCc5pYowMsUvbaW76LnPDrwDHeU0Or4ocV0ZN+CGEdM+LEBwsvcAufkE16yScfTe5t66M9/Gc3vZqU1QN6doX9QXp63MLGHL14TM5xapKB++H7Cy9xqs1YTXlbNymmoFrFoR5Y9Ae+sWp4ANEXt/UB5xtu7j+im3orI59ytqQDvr9f8gA7W1QnAH1/EYveeydTbWxA3nIR48o25K6fR52843+201utQnGpw3eFl1QDxtm/dRa0tkYrOgHiHykrpEQEQ0dSqs7ie4FoE85RpAGSY8JqVRwoH3tEJzdXLQdhbzCHdjlh8DhCSjDvPWDnM1GrUXjRLVV+3nIDShY7zpxvkZVp1XIR9w83MjRVgBVgBVmB8K8AAb3zvL6+OFWAFDmMFAO8GQmEjTDY/N/PBnSq1W565sdwWON4KxYOOOUwMD4P3CHj3+5ZOGvIA7uRaEgV4gBY1Iu/UWFfu7S3rpDsH411kVnuVPeJMNEJGhVZqDryhrSIH480jJUdtNjproQj9FhAve1GOESLe1Bim39xmn3tQDrMpsIt2FO6mqipvD6qXLF9GnxAv2RK9PiVksXIayjx49RSk/ix7RxAAHl5ZQrtgeZj2HBnrNnT6bKASbeXCmbRvw0a69/s/NNyhZoBnB+8wbm5BAVVNnxZzikQhngSvTTv3xznv1BOEwiEB4yIwEyAPrbumnIqOPZlu2Tla+EM9JpJrMpJLUPjxaMWUqfSDMz6SltvGWEEs6X5DASOAmBLxAshL55c1AIgDwkXrR0GZZDfLS5VX+SVIuvLkparQSTKa1Ygv+aADN1aAFWAFWIHxrQADvPG9v7w6VoAVOMwVAMDrEfntssTDbL74j/N28XB3OLRMCy9SNTMnqZduqlB4mH5T3053tHcnJHGiAA8nSxQoJTRRm4NQfOQ/Bx9yHNIM7mRnWYVWB97F7MVVRXSoeJj+/Nc2Cgv93doLOWupObtdOPCyPEM81YWnOvDczon35TWDvzs5ff55zZM0ab3z9RMQDtrCxkifHUd00XC5+7rlHFHEAu3Ve+6lV/9ybxzA6+nJpz17pzguacr8eXHvf+4n59HAtCJ6QAC2TSNOOdlpqaiwfOGiubS0pjLmOAnw9j7yOA2K8Fmr1tnXKZzD1k7EN1ZMptrKpfSr19bazhcg75iZ0+nGj51rhLSmI+eZn1WRda4t2cecCxIAC/nxikU+Pqw7HQ4z3AMAEMeyCJLUI5Eqr8Y1Kb6IycMXXqYCIV72wq1vpoUa43OCe1o2/sKNFWAFWAFWYFwrwABvXG8vL44VYAUOdwXqW/sMF0oiDzNjuXanPHNjOS95boQ/IQk6HsTMbiqnKrROc0+0Ci3GBPBs7QqmBVDYrQF79sLgJnola0tcF4A7AAU47uBOVJvqvgt+qdPT9sKJd9+0ATp4UK9y8gN5z0bHr6oSD+oeQmkTAXiywnPeSE40p1xbm7N66Gc5e+nib++imeudHYiFDd30zuImaqsI0Zzh+FBXKxHV8Fk7gKe67xDaDOiPe4dsADM5IoS1sCYW8tUfVUED76913DuAvO+duCraB07W7PZm2v+3x+OOg+uuq7/LcbxNcyuoqziPTl96Gv1z1wHaUF9PGxvqo8egYAWqzp4wd6YAMtnCkZedUigjTwwXWr9wP1vlyPR0cXvs7FSNWX7JkGqQBwg0ljn4VMmSgWRqnjy4GOFm9zNPXqYVsEDORlQP5sYKsAKsACsw/hVggDf+95hXyAqwAoexAoA6eABBA3RCmGU6XCjJSgY3CeBHZ29mOQYlkCkS87PLJWguZKGjRTLuO4wP50s6HDZOa5HOo7/Qy3Qo0Gp0NXIBjhTxMIM7vD81XEULNq+iut0huu8hAWw6Im6yC0TV0SXZAVoaCLjK94/cAdo0Z1jL9aMCvJKSbCopcR9fTkAFeG7AVAV3CGHUCSn8aWAPbcmOgLsT7mqkE+9qslz7K5dOolcvnUwnfelB4/2K4RyqIOeQ4IoFM+iYKy+OjvfzCyJ/N4fQ1m2aZfy8SIBNFdypE8kWexIQlWEDZVWiOmweHerupf5wmLK/PVrQwm7TVIgHwBKqW0+Nb8Y76Fp7ItePUzswuZjwQgPEm1IWKWJhbhJs4T6I+4patVUtduF2Pt33AbLhevYT+OicWwccylBRjJeK+wV+x9S39etMN+V9/AhlHi0Q4q+LMRPu1+oG4HOBHHjcWAFWgBVgBca/Agzwxv8e8wpZAVbgMFYALjGENKFluqtNlTlTCjPIOY2GVmUbOaWQXwq62j2kf7upjdYH9eDjyrxc+umk2PBCr5cc4FlQhEun2/WjzlMW94Bb5cniN2gvNRnuTytwh+MA7975n8W0ScA7tOG98YUYlgjX1AUCEjmBvPd6g/TCUcMU0qgkqQI8nLO2Vv+hVQV4eAC3CslMBNxJDT+buylu2zHe8Xc2GEUZ9q0spv1HRIAVWtnWJlp580tUMJxNtWRfPdIM73AsCljs31hnCfCc4B2OlQAPf+/MK6aOEUelDsDDMQinvXDxXMO9agXw+oJ91Bfqc/0IqAAPnT95/CWWx5hDWtWqrakIk7S7NlwXlGQH3N+7xBceOuGrqQB5uFbh4moUBVYyoekATS/zVDXDPQ5AOFEAnGkFLKpK86nAgxvZi27clxVgBVgBViCzFGCAl1n7wbNhBViBw1iBA/XNdOvtD9Eb72ym6bU1dP3Vnzf+TKYhB15LZ9AYIlNdbVbr85KAPBl93I6VVQrxcKo6qXRCoHQgnh/wDmtwqozrtka/3pdhehgPjrPtoUZ6PbA16saT5wG4mzZUTTd9pzzm1FYAT3b4Tn6BJcQLBoeorTVMfz0lrAUuZA48OW4yAE/N9ZUMuJNzsQN4Q4IS2IGC6t3b6ehbH6Vp7RH4GQ6MFtrAv9WwWVVs2xDaHXMsnXdZorIpikGg5eaPhtoNiAokjfmlxs91AR76/ulfTrMFeDruO4xhBngrp6+glTNWxF3OdiAnVSDPrfKpX5838zhurlCr8/oJ8uyK+6RqvW7jpmofki14kWmgEzoCKHL+O7crit9nBVgBVmB8KMAAb3zsI6+CFWAFMkCB1Z+/lr78mQvotJOOpjvvf5ruvPfvdN/vrqOykqKkZnewJeJmyTRXm9uixrKQhZozCm4LcwikLgy1C6cFuDsiP48uLRt1VLnp4fQ+Hp4LhKMJrrB0NwmvCvKEo0oAHQmMneZx3W1tUeed7OcE8ODE+25BoeWQDfUhbYDXlNVGL+aui46jC/DMVWhlmCTC0ZH0HteLbqisnS5eAN7i5/9OeMk2Z7iQBvtFDsQB8RIQb+ln/sOoNmvXrKrQVhYFaH1dJITWrmVniVxy4tpFGxRrDwuy2BMQIaM5oiKwRgitHPd7JxxNq6bXxDnwWnsHaF/baPjszAr7vFxeAF5vv30OM79BntcCJ359XpM5r/zdkC3E6BaubZ2Qb/O88RlAFddMSXuQ6nBe3PfwewD3Pbjx4HbXSU8xlvdqq2stR6xjsgB43FgBVoAVYAUmhgIM8CbGPvMqWQFWwGcF4LbbsmMflQo4d9yRiwn/vuKqG+jpe26Mnul7N/zOcOB96Yrzkzp7c+eAUWgBLROqleouJt0hv3ggQ7J7uNmgFx5k7cLRMg2GjsV8zK4zhLAij5IbwKvbFaQf/aE97jJwAnjojLx4CKc1NwC8vwgHnk4VWhwrXXhecuCp4bMYA64uuNJQnAPXCiCvzsO707WvA/DguAO4q9mzIzpUJIQ2HnQtuPQ6Kpkd70iTByKM9mBdnchRmGXMff6kfHFPmkT1rfZhxQGxB9li0Vj7oIiNHhyxBjadtpiyTp7u+NGe3jhAM5oGjD5HT6mh42dMpvxFNdT86uO0vblTvLpEyPWQ8VJbmQBDMyvyqFzAErWhCq25WYXR6lZG9QvkpRoc2Ynsx3nlfUQ6jr2EifqRc073d4NbP8y/SoQUI+drqpta8AJfYLjlFtRxb6d6zur4+AKiosQ+BD+dc+FzsQKsACvACqReAQZ4qdeYz8AKsALjTAGEyT705Et02smrjD+/8++fpA+Jv595yTfotUdvja72TRFKC4j3lAL1EpECoX5wB6BlWvJsp/XA3YAk+3A2pbKpIMpcUdbuvHhom1RekDH5njCfGpF/Kh0PrHbhorqaWLnvoLMbwLNz4W0eDNFTS8IC/NiHmqr7KF14ulVof/zBU2nl5EnRIaQ7U/da0b121SIW8hhora7rxDt+HQPv0C9SxMIaurlBvJsvvDgK8M5aVm7Au8dei4TEmpuEd/LngH4S4DVfe5rtMgHujq/rFPAuEspvzLkgj6oLC4yw3Ddy91FbQQ9l5WCt8QBPHrN8SmEU4pndd+gzuXQyfXhZ/Dy85qSTQObPa180qtZKMLxy6mxaOW2243bqfgZ0rwndfn6HZcqcn3CX4YsM/P5wy/fmd8453bVb9RsLlxv2HnoBiKHZgbx0fzHlpiO+dMHvWm6sACvACrACE0MBBngTY595lawAK+CTAm++u4VuuOUuul+ExqI9LAAeIN4fbr6aEEL7qTVn0nkfOTl6NkA95MI77qglCc9AzYOXad/+Oy0q1a4yFUQhZMyriyrTEpGn2l2pk+dNZw6fuLbRctuHUQ1hpAqt3XXxx6L4kOODq3Povne7tQEexp45M5c2Tl5PG5qsK72iz4pJkwihsxLeqeAO7w8Ix2EioYZ2a9uc1UM/y9kb8zY0HxbkBMVAzGGzsiPCZ+1ayazltOCyH9m+jzXd+/0f0s531tNpi8uMfo8LgGd24ZnhHfrJENqVK4fphTWnG8VKzJAH8G71881x55cA742cfdSaJUL8RRVbElsLiDc4ZA/sAfGyqgtp89z4oi92OfC85oa7++0X6G4B79CQFwxfIgyJDcAerJw6iz656gO2IC+dzi9VVFQMLhWFbNpE1XE/mxoe7wbyxjLlgXnN6fryx05r1cmI3ysqAM203xs15flGeg1urAArwAqwAhNDAQZ4E2OfeZWsACvgkwLPvrzOCJe9fPUZxoj49zMvraXrv/05A+b9WrjzVMfdldf8ki4XUC8ZgIeHz/q2SGXATEs07iRrxM2Cqob+hkHhYaVYhMnmiofeZPKWZZqb0Suo0L2kdcCdHAt5uJo6+h3dOnYAD2O4ufDMAC9roci79bViaqwP0x13NRuQxa0B3n3y41VGt/WNTXSPqMaqgjyAuxXCcfcJAe/QVHDXueUhI9y0bPH5BsDyE+DhXGYXngrwPnbd1+OWVjucRwUUcfzYtaO++4DlW+q6nrjtbqra+gKF+iP3CQnxUHE2S4TMImzW3LD+6klD9OEPD9MtCz9shBOjSZBnB+/Qp7akkA7md9KOQMvosCMQL5wdX41YdgoLmpb/0XmW6zl96Wk0pSw+rFY3N9z6g3sEuHuB1h+Khag4GfYB9yPsPSDlT865zBLipQqkOW6weDPVjjOd8GKdz77bOvx6H27AARHa7vfn0+v8zE5GzCeTKvUCTtdW2X8B4HW93J8VYAVYAVYg8xVggJf5e8QzZAVYgQxWwAB0F51l5MFDg+MO/wbg6+zuNf4NoJdsIYsmAcGQnydTqrvqbomfbgW1Smoy4E7OHW7GoKjy2z+SX1B3Tanq5zdQ9ALu5Jp08o05Arx+QUcaY3OgqXqZAV7OVUWUvSjHyFu4d1+Q/u92e0cdxlHhnds+yOuld/sjBHCnNqNiY9lCGi5dSFmzznUbytP7KsSTAG/hP2OLVmBAp9BZ9YS1p3yc8JINUAGAAyHAgHBiJQbIbn/8LgrVj8KrV94O0StvW7vhZk7NphOPyaHB4l5j2F8u+LDxJ+4vBsgT23jes00xYbPy/AU5AQHwiujpvG3xugQEICtAOHT8NRAS8w7lBih/brnxUptd+Cz66AK87zx6pyW8U8+jgrz/PDse4qUapNldSLhWUYwg1ekG7EBepv1eySQ3oPxcwBVYIl4IiUexoaBw8I51yxc5XwEUubECrAArwApMHAUY4E2cveaVsgKsgM8KIJz21394kG4X4bOywZ33GVHMAsUtAO1OO+WYqFsvmdO3dweNEFG0THu4cVqXH1BKrSjrlmDci8ZjHaZlnqtfQDERcCfnIquzOj2cOgE8jDPsAPEkwIPzLnCOqHwq4B2aCjBeeqWbXn6lJ0YegLtZM/Po5BNLXLdYAq6Bls0GuAu3bY07BvwOtAruVoC87JXx7jjXEzl0eDi7iR4ONBvOL4TQmgGejvNODi8BntzXgHCeAiDATabqFjy0hzqeuDtuVvsOhmnfoVHYAHg3c1rE9dfWP0AbsovpgenHxOrdPEAXPBcfOotOcN8V5ORYAzzxfu6sCursEwUtQkEaElVNzS0gKtMWr5oS82M7951xPlFhUzqQ7SRXw2bd9m220OPkN4M0Y/8gLZw0Neo2LfnU8VTxvtlibrPSXok13QUkzCAPxS4qRSGEdOTgdNsfuecN7c5OYJ1x/O6D3xnIkYfPok7BC7/Pbx4P80EOPG6sACvACrACE0cBBngTZ695pawAK+CzAqg6++XPXBB136FohQyVBchDBVq/Wn9wiFq7IqGoFeI/2P3O3+XXPM3jJPpgigckPCgBUPhdbEDOUYbi+p13KlEtkwWK5gqUiYSf6UDE+57rofvFy62Zc+KhCu2FywoNaAd4pzY/nE8IuNQnXQAAIABJREFUf5QPswC9/c//f7ZTjAF46JUCiIdh/17QaoC27GcfpIIXHhbhstmuIbPmSU8/9RJaeOalRoVls/PU7Nwyu/Dc9gjvPzb7ffSPXhDN0Xb8xk5RuKLL+AFgj8yNJ913rVm99HbuAcvhs0VxmIB4AeLZ5cMrO21W9FgneIdOOg68c397vc5S6RMP9tIsAfBkqykpperiUgPkYo24Lqo+eyLlfuI4rfH86jRWIaNqBVZcp60iB1+y1ZiT1cTvgh7Jzkc9Xi1gIe+3eB9frnmp+OvXnKpK80XhDc5/55eePA4rwAqwAoeDAgzwDodd4jmyAqxAxikgw2NRzAJVaQ8KYDdNADsUrEhFGxThszKXHB7a80U4WruoTpvpzWvOPjXpOh6IACxS9UAJ4JNJrpNEIZYf4E5eR7rA1c2FZ3Vd/vm6+Pxmsl8yMFV1HHaKzwRCoofW/5yo0yLEc+SERqio+D/12sqaeY7v4bRSzx1P30X1L/7F88cV4azzPvxJmnTSxy3zgZkBnp0Lz+7E5R/9JOWJ6qwPbNlFD2zdFe2mAjz5w+rCfFFFNs/IU4jcdzsDrZbDSoCHN/uCfdQXiuTlUxsAHsJmV85YYZn3TvbVrQqrA/DM8A7nqCoqMQCeEVKNJtYGx2TFjasp/8gZnvcr0QMAhrp6QzQY1kgCmehJHI5TnWW47wJIjVWIqNffGSmQw3ZIwOSWzoGY+4a8/+YKt6lboRC/5wp3avTa9XtwHo8VYAVYAVYgIxVggJeR28KTYgVYgUxXYPP2vUbVWbjsvnzF+TGVZ1M19wZRyALAIdPAk9N6deeKfsgvJF1GcN2lCtyp89Wpupqq/TSP67Vqr5/gTs5FNxdX3a4g/egP7drSfP8zFbRsbp5tf+mea+nUr8LpFCo89PK/Oc6td6hDOMtEeKv4POVm5VNudoHRP/uk/9Fek05HVc93/vNCnUOMPgBXiD4FLJv3ieuoZPYKy2Ot9ksX4kl4Jwfe1NxGm1raDZCnAjxUnK0oiDgmA2JiYF3IvfeUVQ48aDjiwFMnHAoDTkXy8U2aMZXOvuQiLS10qsLqhM+e9MaAETZr1RbUTFU0j4A83Hsq0wjxUlXARktk0QnOW4SEAt4V5edQcUHA0MDPlAW6cwFMxL53CqCZSc0tTyDmjLkX5AUEAB00gHsqf4chZ+JkAfC4sQKsACvACkwsBRjgTaz95tWyAqyAjwqoIbM+Dms7FMKb8ICF5mdxiFTP3WmucFugoiwefvwoTOF1LZmUTxAPiDUiIblbHipAG4QXo8Epk0iorJ1ORtVF8fCOHGtuTRfiucE7nAf7jzBCHYDnluNveO+jNLzvsbjph4b6qXeok0LD1lWRi7LLqPjIH1BW+SK3pWu/rwK27X/6PnXv3eh4rAR3COcUPIVKZi2nBZf9yPYYJ+Das+5Fymt+MO7YntAxVHT0yYbzzq71PLGZ8LJrgAdP5m4z3GrmZgXw1D7Lj19Fy4+Pzblndx6d60IH4H3715FwYKsmAZ68DkUwrQF3C46aQTU3rUmLE00nTFj7okugIz57/QgDVQr6pCr3qNv0JEz0877mdk6d93VdwmpYcirz5OF3QIXIW8iNFWAFWAFWYGIpwABvYu03r5YVYAUOYwV6+gepYyRsVs3Fk+lLsipkoT4c+g2hvOihU7TBy3jJ9nVK2J+OB2qvLkCs97rbhHNrdzzwWzonl9Z8qNjReafq5QYx3MCdHMsK4AHedYSdK9zi+M5px9GCRf8v4W0cahXhu22jBSOgp+FYmyXC6/ZsoO13XWs7dgBMdgTcyU4LLrV336GPHcDL732aCsTLrvUXnUED4mXXgtuaqf2Wlxx12JXTStuzW+L6oIiFU7v4yi9o6wtnZqlwhznlqVx/cA9957E/2Y7p5L5DCG1VUWn0WBQICY+EsQLELH/9m8Z7qXai6RTq0BYtgY5ODkA111uqdcDUxzqc2E4+r85AXD9wMwK0oXKt39oh3yfmxI0VYAVYAVZgYinAAG9i7TevlhVgBQ5jBZCTqLkj4h7y+jAxlsuGowKhRHAPIkQWecEQIjuWeZakHro539Kln9WDdDrAnVyfTsiinRZw5NUJkLdMgDuncFm74+0ghlrQRMelaQZ4uvAO89o6qVJAvPfR2ZVf8bTlAHeDOwZpWIF3GEAtlpF7bB71dtXFQTyEyuJhH4471dDmBu8wvhXAK+74DeWEdrrOfzB3HvWU/6ttv7ZfvkSh7daVaHEQXHivZe+jtuy+6BhZAljkTLGvFOzFfYdBdR2hTjnwvAA8AEM1Dx0q01aLohalRRFQ4jeEwZiZULRBx9GdLpAHkN/UkXkVaJMpNKKmO8DvPXwZZ2Fedf3Mqh1qyvONzwc3VoAVYAVYgYmlAAO8ibXfvFpWgBU4zBWob+0z8mIl4pQaq6VLAIXzp6qibKJrS7RwRKLncztOdSumE9yp8xorN5DZgQeoJfMiSuCrk1PKDPA6Bhttw2bN+wGAt3VSFR1d/BHx+qjbdhnvA96F3rLOr2audhuYn0P9OZup/qW/UO++jQbgM4M7jKkD79DPDPB04Z1cmBPEc3PhAeA1UQ+9lTNajbZwTqXhNsI9ytwmTZ9KH1p9rpamspPu59MpjFYn/508nxXAK/3U+423cc8FxME1CCe0XwUndFyGnkTz2Fm3UIgcVgV5PaLIkBp26/HUcd29ziXZ83k53qqAhZfj5TUERx7y5CVT8AL3jdqqQq+n5/6sACvACrAC40ABBnjjYBN5CawAKzBxFGgWFfAAM9AyqQCD1Q6oFWXxPnK76QCYdO5mIsUTUjk/uBURxpcrXthnPOT5BQp05z1WAA/uQ1zfcKZIeJkI8FUBnpP7DrDA7IJ5dNn8qEyfnfzfWpINPBVfZVUeaFXttvSkQiqdmksNW9+l5m3vxZwDOe/sClZYTUYFeIHQDirp+F+tOaNTqL+Fhgb7aNP2TurujRC3yYs/ScXVK6mk5gjj304QDwAPxSzQ3srZT521AcoWIX2AC6jwq4I8r847uQisD9U9dQoafOfRO2n9ob1x67cDeNPLq6gwN1KcQzYngKfOSbqI/aiSrQsptTfWY0fdQkPmYVNRRCfT7sfq53iKcAbWi0JSfjSZJw8htsGQ96q/+cLJXi3ypXJjBVgBVoAVmHgKMMCbeHvOK2YFWIHDWAE8MHaNVOezyi2XCUszwt7Eg7esKIvQ2anCLXCwZTTULhPmiTm4VRZM5zxVxx2KSIwV7Byripi4ngcEtMS1kwi4U/dKVqHtDXcYhSusmhngtRQV0Ktzpke7frTi32lq3kLHSyAoKpuaw2bVA1SAFylQISrfCuaVf2aBL/urAjxd9114sJeC3aOuua6eIdq6J1IhVjZAvHkn3WD8ExAPBS3M4bQS4OUuqKHKK0+mxv0HqenAoegYsirnomOPti200vjn5+P0LV4xm4pXzjF+rlsVGX2RC+/utS/EQTwrgGcF7zCGGeBV3bSa8o+cYXkNJAOZ1QG9rDEV96NkAaKf4aFegG0qtLAbM1VgMdGCF8gLCYjMjRVgBVgBVmDiKcAAb+LtOa+YFWAFDmMFBsS39bJSp8wth3w6mdDw8IWQRzyUmHOVAc74GXbm53pV55ef4+qOpYIAVC3MFQBUpwqs7vhe+40FGIYG5eKhdEDkeewU4YnJwsvhjq00vOEX5AXgvTp7GrUUj4al6YTROrnvoLsB8AS0E38Y4E6uC6G0OeKVbFPhT3nzt1yHM8M7ecDbdfEhwCrEQz+APBXiASAMf2iBYy4v6cKFq1TNH9ezfjftvuaPtvMtEhBv7vWfNnJ9wtGH+4lus3LiySq0hbl5omhFSZzzTo6tAry8I6dTtahCa9VCTXuob9OLNNi8V+yv4jgU5ujCpacYL9021nk4E9HYam3yi5tkwkMz7XeaXGc6cs7Kiuw4p1thJ85/p/vp4n6sACvACow/BRjgjb895RWxAqzAOFZgSISsyTAe/Ad/oXjAdarQmA4pdHK14cEMcKpPJPDOtDYWwAoaWDl4MiG3IfJ89Yt98jO3ld2eqxqYIU+y18nQ+p9Tb9tbWg48M7zDud0AHopWhMXLqQFgAeKZw6DHAuDZwTvM3wrg4edmiKeu1a1qsNpXzZu29srfUvf6PbayDVIfDWZFQhVrb/wgLVh+YUL3DeTFk23K43to7j8O2YI72U+tQmvnvgO4w8vczCCv9JRLKXfSbNfLOJniCK6Da3Tw+96spk7wmuctU6urp3OP5GcFoeN2+iHNAb4Y4MYKsAKsACsw8RRggDfx9pxXzAqwAoe5Ak3tAwYMG8vwT7UyqE64YzocDIlua7pdH06hd5mQxD0djiBZEEC9dvwGCbge9jY+QAV1t1leGjKE1gre4YBkAJ4Ed0gRh8dss6MwqzKb8o7LS/SSjR7nxYE30L3fyHln1ewAHvrOPfEn0Zx46rFeAJ48LrR5L+347h3CjhivSX9WG/VntcdML3zkEHXdGKLKwaV0Yv/3k9Kr5T/uo+C7o6HD5sHUcGe47+p/nkd1WX+L6TbU10Xz6ipp/q6ZtnNRQV7xSe4QD9AKaRHSnetSLgDnRzEKVDn3s6l53noHBrUqr/pRKMLPNcix4NJu6w6mdY/gBkWOPDgaoR++/MJ9BKHrkwXA48YKsAKsACswMRVggDcx951XzQqwAoexAghFlWGz6X6wkO6KIuH86xWhu7pJ3DPBWWa35emCi7o5s8aqiITUx6+QOiu9ZS4pvKeGVOLfqQCH63qeoHU9T9Kiplaq7umj6t6Iswv57tpKimhzTaXtncCtiIWVAw+umEhl2WEjtNSqiAVOOBYOvL72bbZrdQJ4KGwxZfGlcccmAvA2nnedMY7MB2gUuhDcqDvrUNR1Zz5R3+UCXlwece6e0HcN1QwtS/ju7QTx5F51X1ZOb1/xUtw5hkMDNNTdGv35sW8vp6r2ctu5AOQV1c6lqg9d7givxirnpJx4qqGZLsgbyy+k3C6oRK51tzF13zfnyUPVauQJ5cYKsAKsACswMRVggDcx951XzQqwAoexAv3BIWrtGjBWUFEcyRuW6tBUCe5QmALnQo4er3nKxhpM2W15KuEidINmXqpWjvUDfbJJ7a10Vq8fc35E2T9Vyfxva/yq5dZjTnbXsJv7DgMOtQ5R6K1I7rhRICV+PlKZVZ5UDcuM/iwFOfDye5+mAvGya3YA72BTmA6Jl1Nb+bHH4t72CjVQsKLpntiiFYBcgHfBYefqnq1PRe53aMlCvIF391P3H1+Lc+NVffYE6jq6l55bfpelFOGuFhELHZsr0A3iYaBpZ11BZdPnGS4qfPFirnzsVUe/f3Wl676sgjwUNoIW6ucPn8cq4QZEtfJMaolW6fV7DdAPjrwSkXsSWnFjBVgBVoAVmJgKMMCbmPvOq2YFWIHDWIFB8RV8owijRQP0yEfRA+HKS0VTKwzagRfd86bbLag7LzwY1ZTl+/rg6DXEWJ3rWOXkk3PwE2jqgDt5XqcKlM/uaorZztPmTtLdXjoU3EZPtP8qrr8TwJPuu6H+XhoeGA07zcovpOyCouhYwaf7o5Vl7WCgFcDLPTaPsqsEvUqyqdAzENpBJR3/azliqL+FBvtH3WNqpy27Q1QfWkg9eYvijs0Nt1BJcCsdc258wQmv4MkK4Klhs+aqwOpkOv9LhC8eKSyNolWHkw+ntRIJztM/hj5LcAVatXDbaIVd9f0znznRcRdR0KJo2SlGQQ4AGDPISxdAs5rkWITsq44ygDzp4jZ+l4kvO8aygI+VRpk2r8kV+aJacvL3jiRvPXw4K8AKsAKswBgpwABvjITn07ICrAArkIwCDW39kXw4Ik9OZYn/rgUZ7olnWSTS9sPhl6kJyrEPfj1EJwPu5PWQilxwVtda72CbqNI6mnOsKFBBRTmVBpBC0nZZ7TiR69QLuJPjG1UsCwIxD/AAd2Z4J/vPrSiiz62aozW9x9tuEZBqe0xfzBFuOTOu+WjFv9OUoekUbtxvOTYgXl5lDVXWlFP3pgHq3OjsGDIDPL/y32FyZteinQvProBFV88QvdZwHIUC1Y46TplxHK1cfGxMH68Ab9f37qDeDbHFK9qzd2ntnxpGiwOSdeFZnXRz9t9oY9YjAuBZT8kO4M3fOdMxJx5Gq7rwu8ag5nBSAKyq0nzxhYyzA1FLpAQ64fdHqSgwNBaFkMyhodAdOTEzpaq6ej/G79pMmBeMd7VVo5WyE9hyPoQVYAVYAVbgMFeAAd5hvoE8fVaAFZiYCrR2BQkPf2iATw3iAdDGOKItkDncE2GyfiY2T1euOe0FKx3hekNuwUQTyfsB7uR0/MxBt6erlfZ0t9EL9Tuiqz139hwqzu2g8HC3pVQ1+XNo2ZSlUajQv6eT2l/cT/17u2L6F8wqpYLZZVRxyozozxMBd/Jg1fm3q63HAHe72ntdt/NzR8+muZXFrv3MTjwzwKvNXWAUrpjUVhDjujMPHBDkAfAhq0A8SNfMoOCbQRpusy8AYAZ4frnvMC+rsOPijt9QTmhnnB7mEFpdeJdTUEW54lVWUhkD8ZIFeKg2251d77pv6GAGeIuCq2lxaLXWsbqdXsq5ieqHNscBXRyP4hXD/dafl8q2Mjpu7QrH00iAJzvh+ikX4AwFCgCHmjsHkr5/665T7ZcJ7jJoAR2QZgC/w3Af9vP3TiK6qMck+7sh2fOrx0MnhBlzYwVYAVaAFZi4CjDAm7h7zytnBViBw1gBwLV2URUPLdmQSxW66FSUTVQ2P0MzE52D3XGJugOldrnCPRYSuQh1i3o4zd+vHHR3bnvTgHdqK8sL08qayHWTlx2g6nxr8FVTXE01gSMMcNf+on3lTowDkDf9U8uNxOoAAnCq9PQ751SzWr/q/Pv92t1a8E6Oowvx0B+FLdAwV1zvACiAd1PzFlK4o4WGxMuqZQvSYBSoEJRBwvLs8moKiJcTxFMBnp/wTq4BVSlx3anNKpxWrULrFDZrXnteyXQK5ERcPzOnzqNZ0+Ybf/cK8MwhtFZVZ83nlmG1qEQbOmIUkqYC4D2Q80Xq3NlD3bt74rZ/ygcnkZ0DD53dwmjNAE+eAJ/1CuGgRthusikKnO4pdu/5+WVBIudXj0GKhT7xpVShgFSGHr3+V8ZNZI5+fUGWyLnNx5SLnLfYM26sACvACrACE1cBBngTd+955awAK3AYKwCHQvNIsu9EnW3pAndS5kyuMuj1QdaPoh52l1+yoBOuuzu3vxU3vArv5Jt2EA+hdUN/FZDvkHu4FsBW2fwKmvnpZQkVN1Gvj0nlBXTPun22YbN2mnkJp5VjmEOVke/OKmxWVicFtLPKjxaYPMPIi2dVlRbngpbhMlHM5Dj/nTNuhT8A8sqyI2Gr3T1dtPWN31J3byRGtKH4XNc7YLYAd/kC4KntpGPOMByI2CsvoZ/JALzOZyIONVTgRPMC8HZt6abd4vXc3xqiy/jQv0yhOYtLaK54oe3bXUd3v/A1S3gnD5pzYREVz7TeQyeAhxx4eFk1uX/4QgYONBS8SSfIQ6j8gIDYfqRIcL2YXDqoaQzkPRCHjCXIw32+WuRH9XKdJ6uD0/E1AnJCG26sACvACrACE1cBBngTd+955awAK3CYK1Df2mfka/IKfIxcY8J9JB8WpQspHXKMdYVVuzXCCVMonA1uuaBSCe7k3BKBI+q6rJx3eP+kaaPFGNT+VhAv+6CAVfeGhUtPFG3IsnZ8GJVXxf8ZYEX8H5x4tZctS+oywkP85+9fm9AYXlx4OAGAyaD4AEl4YXbfmddnNynpwpPvozrtkBJSO+2YkpQBACeAh2u1TDh2hsUacZ/IzcmibWvvoAN1f6Lu3EWWRSvMayysWBC37BWLjqEq4TpMJE/ixvOui46n68DrvUwE214eNtyP2chbKK61Bf3uIbQAd889Uk+7t8Y76uQk5iwqpoVHtNGbr99M7Vl7xbVskwAPBwyFac6aUkuI5wTwSk+5lHInzba8fHANYm9kfjW1aFBnb0ikSbAPzU7oQ2I6CM7jLnGeRFMH+DEHjGEHysYa5GVCiLGqMe6P+AxwYwVYAVaAFZi4CjDAm7h7zytnBViBw1wB5E0CfEObVl1IB1usAY1cJh5GAO7wsJROl4cqc6KhqqneKrdiIOkAd+YHtXpRqMRre+HQjph8d/L4maUhmlUaG2apjl2Sk0+lufnRH2XdP0TD+4cpmwToDYxWXUUHJ7BVe+lSIy9eou3N+jZ6uM662qfbmKhM66U6rRmehPZujZ4CYakSTLqdF+/nzoqv4CqP8xpqqnM+9TNtDqFVr1VU9JT5xCQM2b/xT/TuxlcNiGfX4LxD7jsZOqv2Qxjt3BkLEgJ4Pet30+5rRivauhWxCB81RB0/i62wnS0MSKuyP04LRR48gC8r5gZ494cbR/M+Omna2f06zVr6PPVkNVBw2OUzFw7RnIvK4yCeHcDLqZlFZR+4zPb0dg64dIErXJst4veIXQVlL9diMn3d0gaoesCtmC7HIFy6mVLAIldUnp0kKtByYwVYAVaAFZjYCjDAm9j7z6tnBViBw1gBPLwi4TeaUx48WVHWeBARubL6R6DfWCwd0ATNnLNrLOZiPqcVBDUXZUiXWzFRp6Kd+25F9QCV59u7eeJceP89msOuIFBqSKXjSKs4ZXpMUQuv+/rGoTZ6ZFN6AJ7ZvQaAJwtU4LPi4MWKW1amADwJ6Z0gB2DIgYN1tGHzaxQOxUN/WbTCbu+SAXgYU4V43VmHaDDLGpoh513fLwYt3WEf673byAWGLySsvoy47b+2Ozrv5Nq6u9qop7udCksbaeryv1H3UGzOyDgNhsVnSDjxln99UvQtuyq0bvAOA7g54FIN8vyqvu31c27ur5sGQnUoYt9RyCnZ4k1Oc082v2yyuqjHQyPkwOPGCrACrAArMLEVYIA3sfefV88KsAKHsQIDobBwT0QKEpidAgBPBXnZxkMuoFO3gH1jHSaFeeIBrFhAPLdQ1bHYFkCzNlEYBDolU03Vj7kn+uD443VPWZ7eLnxW7Ty1cMQ595qAFK+P4qvCnNKYUFmn9SUL8F490EKPbRnNVeZFS68OPHP+sbYtdTEFKryce6wBHgqoIFxWtwjN3oM76EDDThGWKkJSR0JsddebLMDDeQDxGu95nno37CErF56sOgtnrPm+dULfNVQzFAnVlmHCiCqUudIQNqvmu3NaV8OhXdG3J8+oE1bmx91lEBBv0vH5NPmESAEYK/edDrzDsbqgPhUgL5Pyu3nNxSf1gCsNv9vsnJjum+ncI5MKWFSKYie4Z3FjBVgBVoAVmNgKMMCb2PvPq2cFWIHDXAEZNitzuHUKRx5cbkUC3PWKBxs/qqL6KVEkvxuSgg/4OawvY8EN0y/Cs/JFPrx0J5M3L8BcYEF3gakAeMW5ZdohdsnmwQPAe1wAPC/uN6mNV4CHzwygF9x2cKx1btukK3Ncv7EEePi8hwR0xmdfNxQSAG/foZ3GOpBTy6iuC9ehhvDIgVddUU2lIrzQDxB/8J4nqS7vrqimyHcnW0DwirBS0FiFd+omqIDrxms3EUJo3VpwoI/aWuuj3YrLmmjKkiepm9wB8pQP1giIV0Dv3/oBKt3WHh0DxSoA7+xy3pnnZBdevVXA5G1b62jhomW0aPFoXkk/QR7gqF976Ka12/vqlydufdX35RctBaJyrd8gL5MAJ9Y8WYTP5ghgyY0VYAVYAVZgYivAAG9i7z+vnhVgBQ5zBWQePDzYVQkAhQTvyA8EIKH7MJ9uCTLJ1RAFBYJgwAUylvkB1X3wWhVXHmsH8NxCaHF81IH3unDgvTZshMwC6MgQWp3rJFkHHvbgK4+8mxDA81LEQg0rR544fFYGG/bRsIA6XltWvsgXN2Wm7WGpCFPE3pQISA8AA1DfPhJK72XuL7/9dLQ70uJnC6CDFhYw0K6VlVTSysXHGk7aooIAQTs/WnN2HW3Nu59aArEQVQV4dvBOPT/m9b3PvyMu3AiQdGoyfFbts/h995IoHeEK8YrnFNFnP3ULTabFSS3ffG384qbrBLiLB8kLFy2lc85dE4V5foA8fAbgYEOxjLFuyf5OwH0b90yAvN4Bfxx5bnn50qkZAHttlXtF8HTOic/FCrACrAArMDYKMMAbG935rKwAK8AK+KIAQofgpMADDFprVyQENJNbouGhqViTGiqL8EM882fCA22iD492AM+tiAW0BcCDHoBDgz8fLXiRToAH5+GvXttBW5vdHVTq9TC3oog+t2qO6yUiXXfY6wHxyhdh5hJCDfX3Urhxv+sYskNosI9Cg/20NbiZsgsihT6mVi2jaVXLY8bwu4iFzHOHNaCKrrmIhe4COrpaacPWt2O6G3kOUb22R+RM7BugtoI8ai8cTZwP9115aZXvAE9OAiBPQjzc1wCq8GXE4tBq3WXRtV94N5Kv0ahYK1LW2YA8O4AnT9RH7QLldcSdt4DK6bRTP0snnKo/J6vJqw4vOO5u/vmPXNd41de/75sjz1zExfXkKeqQbNVtdVoYK5IbUTjQkwR5mVTAAmASX9BxYwVYAVaAFWAFGODxNcAKsAKswGGsABxS7T1Bw3VXIcIBkdR7LItU6EiZCQ+OVjnupKtF5hXUWUuq+gBeIGG517nYVaHFPJ3y4JXlCSyRlz8aRnmfiFs8QJSTlScAkX7lwznfPT4pSXBtbGvpMSCel+bmvpP7HRC6Ssed1X7ruPAA7nr720TYaj81DxyiV5ufiJnqio5Smj3pGMoVlVzRVnzs30TIuPeKwub1R4BPXkyeO3MhDi+aoe/6LW9RZ3ekcEOFAHbz2rqpsj+SV1OgXGFki3wZAJA3vHIVFc2JVK7124FnNe9EzwGAJxsq1hp5/sSNcshUw8UcQotj4MDTaSecemHSAE+GsL7+1jta8E7Oywzx8HPVUSpzAbqtw2veObeUOXlyAAAgAElEQVTxEn0/FXlR/QB5mVQxHb8LACa5sQKsACvACrACDPD4GmAFWAFW4DBWAO6S+rYIHMBDXL5wrCQSTpdOCWS+Pj/yZ3mdt3xYzBUgx1y9Eg99UyoKonp6HdvP/sm4UhJx4U0rKovNf7ZfOLsezBIAL+Is02nJhs/iHDJ0+L2DHfT7dXt0TktO8M6pGAneA8QwQ1IniAd419ETqZKrwrvCtg6q3rWPito7o3MuL55qQDyAmqoTr6DJH/iM1nrMndQ1YK5qaKgTwGt4cTS/m6HtrBIqmV0SNwfkw8upe9eAd3atSDgMs7NzqOP9J1OouiYtAM+4n4k8hV7DdFWAJ9cDkLdr0n7aXhPrsMxvEqGJu8uptKPA6KoL8C761Pdo5pzR3HSJbKx02X7y0jWeD7eCePJ3ACC4TjETwGBUMR9rx7ZuBVrPIokDJMhDuDm+3PKSExbO2aaOfq28kInMzcsxNSJvLH53cWMFWAFWgBVgBRjg8TXACrACrMBhrkCTKAgRCg8ZoACV6po6Mq9AhCrxWMxTuq3cctwlm4vJz0sp0dxpe0Ro5J3b37KcilUuvKq8IsoPxLo7igIVNK1uGu1/erfWkpItXiFPogKpXW099OyuJtrV3ms7Bzt4h30uEgAI45lBrRzMDuDh/XBHCw2Jl9pUeLelcx1t7VpnvA14N3PdRss51pTPMz6XEpKs+N4LWnrKToAxMkE/XLbmZgXwdty1nXr2WsM4QLwpJ9fGgLzclmYqefmfAgyGBfgZvXcEsgMUENdFfm5+TH48QLycaVNSnj/Nam1gjLsa8SVFJGUAWkXxMFWK19wpEbeguQptW1EnrZ0rKsxatHB4UDjzwlTSnk8nNDdT9XTrfuqhM2YvpYs/fY2nfbTqjPX9/fEH6J6/3uN5rHPOXU3n/Is9+JOOPCeQlymAKtGCPV5EM4M8hGUHReVmu5bMFyhe5qXTF9kxsFcoNsONFWAFWAFWgBVggMfXACvACrACh7kC7d1BI08UWiYBKCdZ0zVPXXAn55pJ+flQmRE5Dd2S8VvpbAfx8BA4syREM8QLzQ7ezSo+2gjXrK9roQN/dIYafsE7zMcqbBIgzwzxkPNubmWx5SUm4QWAFypT2lVW1XlIB8iT7bXNf4zkvBsBd/i5E7zD+7mBAqounx4FeMWzjqK5l//S9Y6juwYVcnXv6aadd293HRsd5n1ygQHxAO/KX3vJOGbr/lGgUV2GcN1YYKDmleu5YLVRuRZwNFVNXZsVuDOfFyBv7uQh8SUGGXnw0JzgnTx+cDAorpFhmpF3kE7u2Oe6HD/cdzgJ4OzPfvpDWr9xg+s5rTrc+r9/djzOzX2W6BcECU3W4SCEqnaJQhrpcAKqmuBLL7tw47F0iZulggu1ukw/jYHf+8PjsQKsACvACmSWAgzwMms/eDasACvACnhWAPAOEA8tkwCU00JSPU+v4E7ONR1uEN0NxoNtjwAkTk4Rp7EA8V6o30F7RI4zgDtZVRZh1x+onU/zy4eF8y4QM0RN/tzov9Xzt7+4n9pfFEnxlAZwV3HKDCqYXaa7JNd+yeTD0nEdmSegW2DiYOtGevSNH8bNf8baDTFhs+YOfUM5lJNXQX2hCDAtyMmhmnnvo1Vf+K2lFtIViEqwOuF+AA2oRItQyLd+tNZVX7UDIF6gaR/tf04UjhiN/I0ZY9GMLFo0IzZ0D+AucORK6l+ylFIZBg/AhSIdB1vCtG5X7HXqtNCj54r74YFu+vmt62ydd+bjC4p6BJztoppQr4B49oVM/IJ3OD/Cty+7bI1RaCOR5gbw5JhW+eCQFxBFETLBrT1WTkCnvIGpDOv1uteYC3LgcWMFWAFWgBVgBaAAAzy+DlgBVoAVSIMCB+qb6a13NouE8b102smraHptjW9nBeBpHgmbxUMvWiqdMX5MPFUV/uRDGVxXcF9ZhR06zV8+uO268zXq3XSQ+jZF8p3JVn3hMVS9+hhqCjVS06BIoKW0ZYWx1UeT1ckPmCj1qGtqorqWJgPc6TacPxhKb1GURIp3eIVe6vp1XUhvb7+X8FKbk/suNJxNXeFI1chsEYqanRUbonzXyf9BaxYfTRctOdroo+a56xQwzkshGkDP1lcbaM+zBz25NXOnipx2O7a4Xg7Vgs+esMwE0KZMpuwPf8g4FjnqEoXMTieXAO/lTcMxIbOuExYdTlsZpu88/QS9sHGva/ea2nwqKhKh1p1t1ClecOHVhPpijkPYLApXJJv3Th0UgPyTn1w9UibEdZpxHXQBnjxQBXlwn6GlEsDqrCgT8o7Kqs6Yr3TkAa72iy/GvHwOddabSB+kxcAcubECrAArwAqwAlCAAR5fB6wAK8AKpFgBwLsrr/klnf+Rk6mrp4/+eO/f6f7fXecrxGsQhSwQaplJlVSdZDUSuOcFfCu4kUgVRqv5Bbccoq5H1lHLO9YunM4ZwhF0whANHFdG2YXxroilAuL5BfJkQYdEYGwibjSzHmNRLRggS9cZpEKvRCGSrgPPCuChaAVe5qbCO7xnBfDem3UCrZ91Ii2rrqUbTv8XI18fnLRegbM893s/eccIaYUmuA+4ubqCoX5q62yiorygyHPnfgM0Qzycq2/1GmPOgB1ofhdEAEBu6himlzd7t6ghlPZbr9xBA/2icEG7cLEOxOc7Ky3PobyCbMovQK4/UXFXUH84004qyqdj83KMf6OdcOpqd4ES6IEQ+YsuuTCBIyOHeAV48kSAZuVCW5lbscchzDzhyWkeOBb5UO2mJn934v3cQLbhTkwkfYHm0rW7Ta7IF3k0uYCFtmDckRVgBViBca4AA7xxvsG8PFaAFRh7Bb7309/Tkvkz6fI1ZxqTufP+p+lOAfGeuudG3yaHXGmospcJjgadRSXitLIa1y9wJ8feeun/iYclEvmY4s8GeLfl4tE38mrLLSFeTc4kOrUs4k5KpskqlV6qcPoB7uScnSqcJrMut2PdoJpTZVm3sc3vu51L9tcFeGZ4h+PtAN7aUwsN6HbjMV+k+YNHJAwLUG224aXRirPQB/cBwAe7/H8NLRHwmB8IUV6eHiBTw2kRkt11/oVR4Aj4YbiWgiKvWF/Il8qdGO+FjcJdbBPe67bX/7P9D25dou+rhUZQsfa5T39RwMlBSiXcwrX3hzv/RI89er/2PNWOiQI8jAE4L3e9KD8n5Wu1W2CilYYTEkzzoPw8kXOuNJ8GhPvYLkee5lBJd8sRn7PJlZEKydxYAVaAFWAFWAEowACPrwNWgBVgBVKsgBng4XRnXvINuvorl9JpJ0VC6JJteNCEAwYt1fnlkp2rPH5adaHIbxUbqqY7tt/gDufd9+O/GSGzucKNExI5yNRmhnfyvYK51qHQfkA8L5DTT3An12ZVUEJ3f5Lp5xTWWizcUnAOyeqayZwHx+rm39IFeJ0ibHZQhM+qTQV4wwKYDRd10Nr3V9G6E6qj3eaW19BHhy8xXl6bGeDheFlwApQGeeTU1t3bQd097QTKZgC8nBEoDXIlDszCnzbt3PdH7HpmgCe7Y3+KC3J9AUIAeA++NpQQDHy54R16Tyk24qapCvDQ974LPyUgF1xqIhRa5KFM1BnpdF5c5y+8tpZu/vmP3KYX975bFVq3AdUQUasceXbg121cr++nKpWC13mo/aUTD/CutCjHcLWm6hpwmyecuRUihJYbK8AKsAKsACsgFWCAx9cCK8AKsAIpVuDhJ1+iZ15aS7/88ZXRM1n9LJlpwC3Q0hkpZJGJD0VWawNo9Bp2p4IqhO/5lXurt+4g7b/+UWOacOCFBdNQscebX7eutpkjqqHmVBZZbl2y4bQ6VVKl8wluKzj1/Az5GqtwbCtXXCoAJTYN16COblZFLMwhtFbuu8j1FKkgOVTYIf4RgexmgFdbXE6FOZFQ1K8M/ZgW0grt24EVwJMHw+EH2DYkiMzQSBRpV0sD9YR6jC75At7l5ZrspoB4otiGVTthGSpiZlF27WTqOvEUS7A1CoREiHwS+fGwN/e+bGGF1VBmb3c9PVb/hEbPSBczwLv3gk8ZPwe8KRMFBIyKuwLo+HW/wbioLNrY3k+/uOk62rZ1k/Zc0TEZ9x2Ot6pwPRYgD3kA+8SXT5mQa05ugLmAhVoQqUeEZMOZmS7AieIVmA83VoAVYAVYAVZAKsAAj68FVoAVYAVSrABy4MFxh5BZWbxi8/a99BWRF+9pH8No61v7jNxXCL0sFP/RP9YJyt1k9VIkIVUAR85Ruu+Mh3lhQIIBTz6kHRA575D3zq7ZufDQf3XVxW4yOL5v50aTD5XI2QUI6hdYUCfjJR9dUos0HaxCNQkopePOT0CJ0+oCPPT92xs/oEOtddHZmotYoOIsXmrLzhIFLLJzYuAd3v/91xbG9KvIL6LKglEQ7AXiOQE8eRKY6nCtBBtbqC3YSaGsyPUM912+GeDhDRuIJ8Nohz70QeqrrHZ0psniIhguEfiVDMDDORMNob1oyZF08dIjY/ZHzY+WyFrMnw8AQ1QPlvdoLxDvqq9/nxYtXubpI/f3xx6L6V8m3IUnnn6mJYiSIerpyJEHWN/SmRm55qRAcCcOhIbirm15DSA/HgokpTK8Ws6lRuRJxHm5sQKsACvACrACUgEGeHwtsAKsACuQBgVuvf0hAsi7/urPG2cDwLvhV3fT7Tdf7dvZm8WDEEBHxN2RJ9wdA76NnYqBzE4Hq3OkGtzJcyL3nWwyX/hIoUZKBuB9oPSDNCl3csLymZ0yfuZ/05mUbpVWnbF0++Da7RFhiwAIeQJGI7/joCmkWXcst35ews2tXHgz1m6govZIkjYzwBM+NlEcQYS/iTDVIRE2K9uhGYX0+EUzYqZmBngLhlfQlcM/dpt+9H0UsXBr4ZZWomCQmrJ6o11zA/0CEAhHHSxm5mYB8QDwlhxbS2EB8HTdswAQcBIBinjJj4dr/+l3QtTabTE3t8WK959vf5zqmhs0eootEkAtPHKN/eDkM2n5pFrL41SQp+PctDu5VX5LN4i3cNFSOufcNZ7gHcDdU489HjcN5FZDaPWZ55xNZ51zjuU0VZDX0RtKWRhxvSjAlEnNDSqmC3DiI1lbVZhJ0vBcWAFWgBVgBTJAAQZ4GbAJPAVWgBUY/wp0dvfSZ666wXDgHXfUErrzvqfo+u98gY47crFvi0eeni7xoIWGynUIqfXbseTbZMVATiGa6QJ3cj0qwDPyh4nX4IjpbvNFIpn5TPtE/04OvGTDaBFiBpiFfUTieQCtdOZjSjfAk/AZ+5KOdcJt0yvC4nQdjGaIp7rwzAAvGjpb2hzzsTG77/CmGeDhZ4m48EoW7jHO1b1tdsw5hweCNNQqAJ5oPRSi3qyQcOSFRb7HAWG2y6JcxI1bNWHdy1LK1J5y+lQqPudUY2+83lu85scDSHl9ywDtavTuQEIV2t7sQ/SDl57SumXJ6r3LaqbQD085y/UYeX9KtGiHXYGYrVvqRDhtXUxhC+S7W7hoWQy4e/it+CrZ5x0bC4Vv/cXNtGPbNsu1SICHN+cvXEhf+tpVtmuWYcTIDernZ3KsHL5Om+ulCBTmjy+h8EVDKgqe5It7PcKsubECrAArwAqwAqoCDPD4emAFWAFWII0KANyhnXbyqmg4rV+nV/PgZWJuIfM6rR6W0g3u5JxiAJ74IZiFrEQ7lgAPYcZ4kINWfj48615zVrmydI/10g/rKxl5GMZxANHpyIvlFeBhboB4KGohw2klxJM58GTYrFz/kALwHlsznepnxudMtAJ4ukUtgj1rKdizjvoOjTrrcO6BlnIKtpYbME+67/BzCfDgvgtkiUq1I9kec8RFH+fEU114uTl08g/PT8oNKfOsFQroATceAJhdk7kQn11vAxcdLrDTVkZy521sqneFeJgTwosXV03WgnfytMnkjAOMR7oDhGF6aQB3VvBOjrF4Whl9+2PLyAnewc+IfVYBrJMTT46t5oLz416USJVtL1ol0tdL4SA/rgOnOQIOwrnKjRVgBVgBVoAVUBVggMfXAyvACrAC40SBIfFEKMORdMJTM2HZAERt3UHhAMo2HGapynXmtlY1Bx76qpVoxyKEVoZpFYmHuF7xkN8+UmHYbR1+v+8lxDTRc0toi0qfKEyCyosI77Or/PnafYeip5qxrIRmLCtN9NRGwZegKACTKCwEyEMDxAtseJG21L0VM5fhvF4azu8lhM2icIUVvMMBqEJrbjphtH1tj1E4VG8cGkZRl9YBenXHaEjiCfMLDJDX9FBsGHd7TquAVvHwDG48wKyAjCMX42aVldJQIIdmnLKQZp04L2Gt1QN18uNJ92dbN9G6XfoQ7+i5YaosGT2bG8RDqCJCZq896cyE1qaCvJ7+kIBy7oU37PKsOU3gp4/U0ZaDkXBtpzanShQH+ufvbbtEoqUjhU3U9m9XfZUWLFrkNnzUOY2OyeQDlMUZvEJM1wkm0SGZ35vqddAfDBtw1qtLVZ16VWm+UQWZGyvACrACrAAroCrAAI+vB1aAFWAFxpECTSLvXUgkb4OToLIkj5o6MjcPnnyIR1JwPPAkEpbn19apVWgxJiIKpQPPCeA5VaHFOF6LWEATACxALQCskIjjLRB/R76tsWhuDrX9Oxro9affowM743ONHX/GEYSXXbNzW1q5k/bXddFr99XT/jpBcyza+9fU0vvXTPUsEc7lBAt1BpTXMXKoPfbPB+i51x6OHhau3kcHjmqmQzPtc1lZue/kAL8cesh2Ciq829MQpJfWd9PeRhEqi9hvhc3MqMyhVQVlVPDGfFHgposqiw5RRzhA9QPlOsujwNSIrid/43St/l46SVcXtEOeNZUpqdWIdSGeGd6pc/nrpnfp3s3vxkwPIbOfOfoYWikAHu4/yTQ1P6Vb9V04pOEy1c3tqAvvMP/GhgbK6Wmg+d2xa5VrA6DFBQIHoNp0XHhq/2QLe+De0i/ucYnC82T2yu7YRMCqeSwJ8uAoTub3GgC2ZW7KVCycx2QFWAFWgBU4bBRggHfYbBVPlBVgBVgBdwWQWF46GvAA0NDeb1lp0H2k1PVQIRUe2OVDTurOqDeyUyXaN79u/XDvV/47M7iDEw3ujURCuvRWq9fLCXAB3OHl1KbPm0Kr//WMmC6q+8qqEIA5Pxjg3X3XbXedMNx4a66Nre7qdlAyAE8FNp3icydBxA9fEsUTWkZccRWHaGDVE7bTKAjk0tQSa5DmFEIrw2Yx8IsC3AHemduwWvgjHKZZwSz6hFIld3v3ZOoOF8Qdh+IbaDK0FgBv5cdXUfnMSjc5E37fnB8PA00qLxCFeGILHOxqyLLMiYecd3On2OepdJpYMteA1bg6YMtLaPpm4br7mXDf6bZ9e/caXed1v0Mlg6PFU+TxuG7h1rZS66Zbf617mmg/nfVaDepFA8+TSvAA6QjXBatOp1FBHr5U8+JWRI7CyeL3NzdWgBVgBVgBVsCsAAM8viZYAVaAFRhHCiCnVGtXxHWXjvBHL9KpkEqGyhoQpCjHKLiRCU3mwkMEIeCidKl0zhimLRfHhsbl1ZZTdqF1jqKanEl0atmHtJbklPcPD4FWIENrYB86IaQMIXeqO6mxrY5efvM2OtAQD++GG46k4cYjY84sIZ5uBV01N5YuvJMn9ArxrNanIxuAUyR5fdgy1FeFeL2n3WY5pBO8wwFOAK+7MRIiCefd3c9EilM4tmDEwTmzU0C8vNFrtnswn7b3TLE9tCSnnxb8++qUwjt5cjU/Xp9w5CL3YzruC364rqwEdAJbqrvQbevc8t6Zj5cAr3iw3dKFpxawMB+bCMCTY3gFeekukOOmM973si8646FPIiAPLuwK4aDnxgqwAqwAK8AKmBVggMfXBCvACrAC40iBQfFNf6MIo0WDswQt2dCwZOVRwY05x52Xqn/JzkPneITStjzwNvVvPmSAKyFntKkQL1l419OwmfqbN4tw2QggQ96squXnWU5xLB90AdPycgPUOVLd+Lm11wlw9y61N3dRe8lk6iidQuVdDVTR3Rid+3D3FBreFVvJc+6iWvrcN87RKsQBEFAsrt22riDdfMk6nW2L6eMlnNauGqjdSb0UWbl38zq6b8s66j/6cRqqjDjyZHMKm5V97MJnVffdT+6OHddWLOHAMy5mYdS7JDuHZonqsmprDJYbwFoNYS0V8G72uSdS2YdPNUK4k8nn5WUTpUMTf7qFonoZ166vW5h4sufA9YxzqPc+L5/pz/7mNU9TkAAPBx3R/nzcsakCePJEOiAvUm06P85h6WmhPndOR9oJef/AZ8nJkYfiFTJHoM/L5OFYAVaAFWAFDnMFGOAd5hvI02cFWAFWwKxAQ1u/8bAtH6TS4WKx2gVzIQa7HHcIW2ruHMioUN+Oh9bS4LZ6anlnf8zScr+6ivYu6aLmwSbLC8/NeQdw17rxIQHvthjrNUORmhXn06SV58eM7WdYl9dPiwrTAO+a2uvo+ar3UXNeVdxQAHmzDq43YJ6EeAC0AfF/cDKe/8UP04z59m4vOaAMG37stj1G3rtE2lX3HK11mC7Ak9dylgAPCJf1CrMuD55pBKbWFBcbx5rqB8TNVSd81i501nbhcOGJiNSTBgN0EpI8igZ4bIBqE7yTY5Rf+10jkX6pcJrCFYfwfLe5awnv0knCFBRaQH68VObHhFM5HYBShgkjZQDcm+bwYDtJDjeAJ9fhBPLwxUChcPcC0mdKw70Ars905BvFueCyQ7MCeTXidyL048YKsAKsACvACpgVYIDH1wQrwAqwAuNMgVbxUISHxLFyt6mOO1lZ1Al4IKF7j0ggH0Ty/Qxpbto1hRqpyQTxlhUud5x9sGUL7XnmBktwpx5YNHkJzT796uiPxlIf6YbatOcduq/uV/TKlBMoJK4tp7Zyyz8MiJfVU0sknHjhEeLjVtRCjinPmQzAW3PtAq3qtHhILhLhsHYP7WrYNyASrue9be/QK7vuoH3t8UUCTpz7aTpJvMxtG22gW7KvMX4MOIVml2fLrfqsdOBpu+/kZIbgwBN7Jwy638rPI/ABgFVzMQPZvfhTl1LOnNnGP9Xw1q4+ke9PhOqnsqn7EnEt5Ypw5cGUAMR05mKDjlgL4E23gKE6QNQrwEMRi4GBiAvbiwPPaxEL3f23cp0lU+1V97xe+6EiNX5PpbMqrhXkBFCvrbIveuN1XdyfFWAFWAFWYHwpwABvfO0nr4YVYAVYAeMBBMUs0NLp3vIK7uRWZUqor/nS8asICB7Ssjq30/pHf2S4iXSaCvHwYIkk6IBH6W4yB9+tr9xID+WVi/kP0ZDGGo4QEK9cQLyhnWeK+GAB8kTTBXjoi1xUt359vW3VWTcddMNosTeNvW303oFD0SFnV9TQ7MoaoxKwWkkSHe5Z+zVLcKfOZ2bFkXTJql/ETREQ74mse2h71gYDiCGUEXATXE02J+ed7JMwwBMDZA3m0HBbH323ME9U37VXUYV3steDf3uHNm+tp23bIxWHP3a2yHco/rzgX45y2w7P76t5EHGwBIgIOQdA9POzkIq8Z04Llu4z3AvgbpRg2O4YrwCvv7+fmhojIe1mgAd0jMqmVl+oJJP/TmeDVZCH/nb5I3XGSkUfODHxe9OPAhZe56eCPJyfw2e9Ksj9WQFWgBWYOAowwJs4e80rZQVYgQmiAJxszR0RB0Y6XAWJgju5HWqYZiZtUbJFQORDGfR54Tef8Bx6KMNpEy204JeWAJkffvO3xnC6AA994cQr3zE1WtTCqiKt3RxxzqvPejXhJegAvD1tzfTi7i20v6MlDmjAJXfWkuV0zNQF0fd04J2csB3Ew/uAePJPXBvLc46gueHldHroYq31hoOHqK/9cfLqwOtuz6fQQD4F+wI0Ze0amlmyl2ZVN9BJC0edhIHZs6jg1FOizjtMaNOWerrhpidj5maERqOaKRx84v+u/o+P0NLFEVDrR7MLbcY5y0R+MKOwSq8/rl0v+ej8XptakdluPV6LWGCOcOHl9DTEFbGAbgKHin2L/SLh3676Ki1YtMiP5bmOgb2tFAUaesUXTakMjXadiKmDX1/YeD2v2h+/M8pFvsRcVFHixgqwAqwAK8AKWCjAAI8vC1aAFWAFxqEC9a19xsN1KnMNmauKIkm719xgkB7jVIkw2qYR6Jgp2wH4GQyFqV+sy0sz67L3rfupecNDXoaI9l36iduNXEiyqENCgyR50ONdG+juhkgxCS8AD/nwZr2THQV4Xh14j/xuV8I58NxCaF/YtZle3LXFWFNAwDrpjMTeAU5JF86simq6fNXJ9LIImUXYrJfmBPHMD+2oxBwaRK63kBboRRVaXYAX7A9Qa32JOCXWFsm7NW3P540/hweCNBwM0mXnv0dLvvyBuOX95MYnDdedXUMtjGzkOBQ3m2993T+I55abUMJx3OMSyUmorifdDjw4jjFvNVTTrfCDVxce1rcktJkaNr0Zs3XYK7HrMWHT6YR3cjKAZQghVh2uifzu8PJ5dOqbSUU1OP+dX7vK47ACrAArMD4VYIA3PveVV8UKsAJCgWdfXkfPvLQ2Totvf/kTVFZSNK41QlEIALXIg0letDKtH4s2Ayo/wtkywf1g1sar881Ol6b1DyUM8GaddjWVT1tKqEo4VsVIbmp6idZ17IrK45YDT9Xx5OefiVak9QLwEPr9qChi8eq9o6GtXq5dpyIWcN79ad3L0eEA8GBIilQdji8wAYhX336tl9NH+37ztGe1j5NFDnr6Q0ZVYqcGF95TL/6VXlovyso6tNb6Ygr2R6pRC1QpAF4W5fVPpZqGc+KO+sx1AZq7IpKfD83KeWd3KoRlgg1d/fWzaNHC5J14MoTQLR+ZDHO2KrAxvOEADW84SEP3vGVMO2vFNOU1PaJImr882Bd42AjNBiAuDC6k8uElMZIaDizxWYdDTi2ssflgJ/3skTrta2nxtDL69seW0d8fe4yeeuzx0WtdCZ+dv3AhIQOJGeUAACAASURBVO9dupx3chIyLB9FPGRoNECebk5AbRE8dExnAQu3aeF3IT5P3FgBVoAVYAVYASsFGODxdcEKsALjVoHO7l7asn2vsb6unj769R8eNP5+/++uG7drlgtDaFJXbyQP3uSKfAP+JOtwSAW4k/NNNlw1FRuq63xz02XTn69IeHoIo518hKhMW16gXbUy4ZPZHPiFfY+KnGNt0XcHhStRtxLpyY9vjDrwrvzZZdpTk5VBb7o4HsC7DeIWPnv9sw9Hh8BzckCEq+GzAReZVQsO9lIO3U8FOa1up457366ohd1AABoVIrwQ83LLx7V5y4N05xP2UGfUeYezReAdWnX9OZQ/MNVyCirE+/QXb/e0Xgx/1Irp9IOrz04qNBIONQAVFOPRyUem5seT8DN8zcMGvLPVWcC8wI/PMwBehQhZTCUc78jaTPsCj1BndsTxaeQ+BCgemdzy0DfjQJ7MF4diIdKVqRtKK+GdunaAPLQyUUADoGzuggVpB3dyPghPLxXuZrUCrbqHqSpW4nQxpyPVhM6HCdfGZAHwuLECrAArwAqwArb/DTMsGsvDCrACrMB4VwBuvBtuuYv+cPPVNL22ZrwvlwYEZJEPpahi2ice2ryGgkqR3ACVH2JmygOUuhY3d46uLskCvEkrz6d05+lSdfhq0yvU0rEj+qNhAR8GNSsGS4DnxX2HE8nKuzvf66D7rtuufYn1ixDUIy4tocfvHQVbZ1+0jBYun2S8zKGzoChqyKzViboHWkQRka00pegN7XnIjl4BnjwO8BhgCYn+nSqV/v6B+2nn3s2W86rfXT7y81F4Z+e+kwPMWZ5Fn/1RgFCw4iHxSqTd98fPiST83qvGSrcwnMOJ5EbD8YWiwEbXNx8wYKzbf93CkVd4wwWOVYgTWb96DODdxtz/ihkGkGbQBIvLhhbTisFvxfSzglqbDnQSQN4W4cizaucdO4PwsmtjeR+RcwKcRI63zpEvmNS5jhXIy5QvkFCdGACfGyvACrACrAArYKcAO/D42mAFWIFxr8CB+ma64qob6Jbrv0pL5s8c9+vFAvEAW9/Wb6wV4Wh4uLV6YHISQxdQ+SFoKnP1JTM/qwde6AJNUUES4cNwtDjBgmRDaIunLDHCoN0cWcms0+lYALyunoMUHOyLdsP1FdaAeCfdnkNeilfIExjwSoSRoiDLfddt06pG23Cwi7rLW2m4YNByOQuXTaLuU9uNzwJAgQyXhSPIyekFgNcdbKFZpU94ljhRgIcTSZhRmBcw9h5aWLXbHnyEdu4TgHUY+fMirluEzbbWl4oxRpPhu8E7OTZceO/sejdhgHe+qEp74ceOMj4jABIIBbWbuzyndN3p9HXaBDjvaOPBaAiiW9Xn3COnU/lNq405+t2s4B3OkSuuv5CF29MK4qnXASrwSochQmpViAfX3RLxcmpq6Krfa/Uynk5V7XSDvExJ4YDiHgCc3FgBVoAVYAVYATsFGODxtcEKsALjWgGE0a75/LV0+UVn0eWrzxjXazUvTubBA6DAg4FukQi4f/DgnZebbThh/Mhx5ya81zm6jefX+yo4A/iBLnjAgiZwR+mEJScD8FDEAk060txAiF/rxjgS4D7es4/uqt9IHd2xIYmuEC9USBe/WkWr/9X75878kL+/rsvRibf7QCOFK/ps4R3Wg7DU7PP6afK00hjgmqkAT+6lWqlUzYsm38f1+NLatfS351+PhgF3tYqCGKNRz7Z576yulw99PJvai95LCuBdICCevIYAY9Gs5i6dhvg84V6TTBu6581ovjuMM1opF+HR1iPjmigQLrygjxV05Zleyfuc5UntAB46W4XTqtcBQCfuy/gyBuG1XppV6KqX4/3q6+Velg6Ql0kFLJDuIocr0Pp1qfE4rAArwAqMSwUY4I3LbeVFsQKsgFQAzrv3HbWEvnTF+RNOFLh2ZBJ4HYeBrISIB5p0gTt1UzIhvMt8kcjw4yyhCR6eEw3vSySMFvnvED6LpuNa8esCV0ElroO63jb679YNAhj0UndffFEJq8q0eXlFtKbyGDqven5C07Kq1ImBXrsv/vz3/+Vt6qOI29SqSZADl2T/GV2UL5xhUwTEk80N4CEHXmvf/rQ78MxrieRFi4Smdot9kYAVRTgkHHvujUjBhi1vDtOWtyIZUuC8s8t5Z6WXnwBPjm8OCUY1VAmj/MjPifPY5b1TK+WajW8G1L3kOKKPH5vQdWp3EIpVIO+dVXMCeHYuPHUct4q1dnPKlEINqPrb1NHvGuKsriOVIA/u74IRp6ivF4HHwXAt1lYVejyKu7MCrAArwApMNAUY4E20Hef1sgITSIFb73iYHnziRfryZy6IWfVpJx097qvQYsFwaLR2DRhrd8rxM9bgTm5OpuQhUi+WClERskgAn14RJptIXi45Vk/DZtr77A3an77S7vk0f943jP4Dpxca4Yh4wEvWpeQ2AZk8X3UYAnDd2llH67tbKSTCaK0gnjpuTqBAJKmfRrdMOcntdLbvYx7IFea23sf/WkeN971Ox2Z1xY311nAp1Wfl0yHKjzolQ2dFqraWi0Tx5ZWRh2U3gIc+rb37qLboAc/r8VKFVmdwgAxAPIRvC4+ZUeDAyiH73F+GCK9EWrIA7+r/+AgttXC0qRVHUWXVD9edur7B8//Hcbnm0Gl0Nqp9irlkP/hviUhle8yGnJ9Fi1aonVBGBPMw58BT+5wY/L3WXLyCPN3KvlonT7ATroEpAuDJ9A5eh5HQukCElftVtTZT8q9iTVUiXy03VoAVYAVYAVbASQEGeHx9sAKswLhV4OEnXyLkvzO30045ZkLkwhsMD4nKpRGAB7cLmgpEMgXcyf3JlAcpzEeCLKM6qTAyqRUTE/3A7HnmBupttC44IMec9+6FVNazgPJLa2NPsyCXsj9aQu1TI5VE/W5yvVYOQzx015Tl0zW73qLtoUjyfFSlHQz3ideo860gr1LAsALKzSmkKytX0MI8WUTB+2zhisnLDTjmbRzcWU+7fvgADQi46tQeGaqmgwLioYXnB2loQTDGhQcHm1uutNrSIgHDf+JpIcnkv7M7EWAjHvKxT5h3aFCEygqIZ87BmCzAqz2qkW646UlP65Wd7/i/KyyPUx2D+EwZQLp30DU/nu4k3AAexsG1bEA7XAvhYQOmASYGfAZ4duGzODPO7xR6rwvwpC6Aubh3urmDEco8IK6bdKREcLp+vaRzsBvHDPLgSE20JVvkKdHzmo8rF18WScjq15g8DivACrACrMD4U4AB3vjbU14RK8AKsAJRBZoEwAsJkCdhHcLVJKxBp7EIlbXbHqfqhOnaUjPIwgM/HqxkRd9k52HnxCtun07z31tN2TkF8fBu5KQANgOzAtT7Bedk9V7mKCvtwhHUKUKu7cCCDG/+79b1UYhndZ4FuWV0dsmspOAdxjXyMBZECiBYNcC73t89TXt3KIneHBYuId5Qpchb+L5IMY5Z8yqNPwFUjKIWAujYtcuOPkn43fbTX9Z9XUvemRVH0iWrfqHVV6eTWlBGDTktFhqh4qssbqCOde2FiUGN6x6IwP6f3Pgkbd5arzO9aB8UsJD579QD8blC/kjkjZQACXuMzxagkhWE9HRi0VkH4MkxZVg1/o1rPl0AD+xQXG0Udqh6M3/Tx6m7bQf1tO2MkWDKvDOouHI+lVRZh6XLawEh1laViwGqukTuPKeCLV4199rf7zBemR8ymbQPiYT0el23Tv+a8nzjvseNFWAFWAFWgBVwUoABHl8frAArwAqMYwXau4PGQ7MMXYLbBC2TwJ2UH+4iP2GZl22F46tMwAQ8zJurvaYiNx9AnnTj5ewK0bTnjqHcwgrbKYc7kPOMKNQ+SPVF3TS0NI/yFhZT8TmTvCwz2tdrhWE85Da2R9x224IdxusJUdxCto8WzzSgXTKuO3UhKnC2WmDPb5+i8K4GbYCHMSTEGzxOFLuoCkcBHt5zKngwq6KaLl91sjGNvW3vuEI8v513En71B8MCzITj5MBe4toFHFKv3du+H6bdG+2hpJWuCJ/FS7ZPf/F27etryaJa+s43PhLTXwIWwFG7EHQnCKl9ctHRC8BT7zl5R82g3OvPs9TWy/nVvnYOvIC40IbF/yyK0IqqzgM0ONBJ1f9c7Hjaecf8qy3Ec8oVh89wS+eAVuGdRNftdpxdbku349zeT9RNnimVebE+/J6R7lC39fL7rAArwAqwAhNXAQZ4E3fveeWsACswARQAvBsIhY0QWiSOxwN+nwABmdqmVRfSwZaIQyodTX3wg9vLqsrrJOGMQEVfB9NMUlMt+26r7fFD/UMUbgoa7yP8TuIYQLyBnIjDqvjsSdogzyu4kxNDfkKrKqJJLdzhYAl+rJyPA8+8SwPPvGccrevAQ1/kxMMLDRBv5rHxTkY8QAOEAeRiv1V4p0735V130D4B8/a1vxv9sd/gLlIdM4+2Pn+v4agqmbaEymcus1XNXCgC8/cC8eYsz6LP/igQM/6mLfVGNVo3J54VvMM9B/BR58sCNbef3efQ7VozV6F164/38aUBXXwsVXz2BKO6a6LnNp8LRSw2DN8b8+PynHwjZHdYbIwVwOvr3G/0n/TiEa5Td4J4xr1CyZUo9U/FFxGuEzV1QBhvv/id1C9cl6loOvdz9bz44qZQ5Bf1I0VCMuvJFd/OTBIVaLmxAqwAK8AKsAJuCjDAc1OI32cFWAFW4DBXAAAPuaaQJBvhtGOZA8lNSsCyNuEaTHWYlxeQlcriGvnP9BFeVk2Fd+b3+wOD1FAcKciAVvHV2ZS3qNhRXln1U+bKctsL9f1UamA1D5l3r6kjksNRbdJ9ByC9e7s9/LQa9zdD06I/vvhnK+jFXVviukk33tyqSfTxI05IGbi10x/X5oHXH6A9r9wfBYlq35knXEizTlhtebh0YBWKzzpg/ZZ3wkYxCzcnnhW8U0/woIB4AHlWzRw2K8GjW042q7HUwgxegfHwhgOiEu1o5VdAMgBvq8qz4HZoBsC7/1+NvydzbnUtv9y3lhqpjlZOj69CW5GbT2WBvCiIl8cN9DTRUHiAivZMoeK9U7Q+mm4QD4OoIab4CkC6aLVOkIJO6XIB6hb4QM45aNQpQovHsmEecJ9zYwVYAVaAFWAF3BRggOemEL/PCrACrMBhrkB9a5/xEJspbgMnOVH1FaGCqXJoeAF3cp6pLK5R9NtOytkVn6vMCd7Jee0pa4+R0g7iORWo0L20U+2csZqHGrarvt/1vTsJoYhGcZGWXupoGy2k4bYeCfDOvmgZnX1xxM32wq74wiKnzltiJJRH3ja/XFluc8P72Kt37/kRteypoyErm9bIIGUzltLKi6+xHVKCG3TA/P/x5wjIs2rmsFmnecKRJ914VrnupOsuWc0i12yuCP+3zudmN0fpwkM6Qwf5jMPhtJx6y0XUOqsmZjjpZEQVby+5+bb1ttEt+9dFx1ohAF554UHLqU7KK6SC7EiuQYTOBnubKLe9mCrWW+e3sxqkuHIezT9Wr3ou9CwXhS7wBY6fhUN0rmm1j91n2us4uv3dQN5Y3Nes5o7CHtgjbqwAK8AKsAKsgJsCDPDcFOL3WQFWgBU4zBVo7QoaUEw6Y2Rl2kxcVqocEYmAO6lPKotr2IXPDjYGaXjAOczMDPAw38m/Hg2xlCDCygm1n1pof1ZLzCUwY7iaZlC15WWRqtxVTtegOeRPFtzY/e+/jykC4CWMVgK8X927Ruvyh0MLD9d+FVqwO6nMY/fmnT+khp0btObmBvEwiArCZKVOCfLUXHdaJ3ToJK81uHvVStfJjKu6CQHSANR0Wtudb1DBvW+7du38f+dS8aqZVGJR2FnNJWdVIMRq8Cu3Phv3YzPEw7gyFH9mQSScOyTy3mU1hD3BO3miI874L9d1yusAYZr4PQCnF3KhenU4ap3IoZP8/Fq5apMd2+14O5CXLkeg2/wmi/DZHCQ55cYKsAKsACvACrgowACPLxFWgBVgBTJcgYeffIn+eN9T1NndS5+66Cy6fPUZnmaM/FkIp0PDg4JaxdLTQGno7Fa8wOsUkgF38lx+z0ldgx3AC+1zd5VZATy48AqXlBg5D61yegHcvZa9lQ5k2Yeerg6/Pw7kAQTlCMuSX3BGZx+lW0fdQ1TKbfzmHTGH9wu403hwNJzYaWwAvK/+4FRauNxb8Q8UWijKzzE+R1Z5EnXWY9dHutbW/+MvtP2F2LxpbuPqQDyZDy1f5Pvye/521XHd5u3lfdVNaC4wYx5nQFjvmgXoy9l4kArve5ty6w7FnSq0bCr1rTmGBpdPM0JoK8QrX8bUmnrr5uZD2Oz2vlhHrBxqZtVbNEu80FSAl58doMl5RTR0sJfK1s3wIkm0r04YLTqbAbx05CFHqheXYUKTHDkIDvCCEUdrMuMkc6wK8nr6BqlCwPl6Dw7eZM5tdyycoLVVhakYmsdkBVgBVoAVGIcKMMAbh5vKS2IFWIHxo8Cb726hG265i3754yuptKSIPnPVDXT6yavoS1ecr71I5MCTxQAqS/OoTwC9VIWoak/KpqOslpvsQxUe+uHmK8jLNnL+4UEVhQkSaamsVGgF8FBxdqgzPqzWPHdLB96FtTR59VTLwgGAd/cHXtOSwAzxxuLhG3n3QoPDlJuTZeyfzN0oc+CpC9GFePnXfsIzvJPnkSAJlxGqOydb1ESGNmNd3eIz+dJNl2rtjbnTSV+/S+s4CS+gqR/QRp1/OsCuTmjrgb74Aj2FI248gDtAO9kATrLEhxv3hemFzuGLKvixgohW7jvzpgDkgRMivFe2L076GO156vda+2fVacq8M2jK/DNdj7cKFXWqWOs6YAIdcD+G5um4Vtymh/2EExGfaTjU/YbybudX30du2irxe5kbK8AKsAKsACugowADPB2VuA8rwAqwAmOkwA2/upum19bQ5WsiD2kH6pvpzEu+QU/dc6Pxc90mK7umKkRVdx46/ZIpZIEHMuQtA1xIFtypc0U4Z0N7f9LQxrx+qyIWiQC8bBF9hYfj4rMnU/5HrK+L/w48piN/tI8K8VLlQgy+Ej+nwMyFVLJgqZGza2BwiOC6U+Hr4M566v3d03FrAcTraO2nAQHD4nQW8GDyRcdT+bnHeNLAqjPceMUFuaIybEi8vFd0lq61XAERAA+wtr2v3k/7Xn0gobk5FbVI5fwDgkalOwzTKbRVuu90RMQeoKxzeISm1QjQb+fCU8ezgoiPN+ygJxp2RrtlievDruG86rX80eq5tGjXk9TTNnq8zvxlH10HHmC4nXvRDPJkqLWXeej0BUREKHqmFFGSX/DIPRmr3IAAiZgLN1aAFWAFWAFWQEcBBng6KnEfVoAVYAXSoIAMlQWkW7JgFt1+89V06+0PGdDu+qs/H53B9274nfF39Wdu02vuFInSxcNTqkCM2/m9vJ+oS9CPYg1283R6APayNnPfwM4QFf+uK+bHTgAP6bpg4GnP76cO8YpUTI0k7B8SKcKKz55ExefEh4fel/2qY9is3Rq+Gj7HeEu6z6STM5k149jwvq3U99ebLYcxUkEhrOyKb1FfzTxLd4yVC08dDDBvQITI5YtQ4gJRDAGt7D8vT3ba0ePNRSJ03Z0IZYTjBo47FWQkCvCCHe1UPf1Yqpo+CiZnnPMx13XKnHvgWG5hqepg+IwBkKuOSNeTpaADrnsAXkBECV46xf2tS7gLnZqsMIwCIaoht1S4PMtEiKdd21aXRU/cl03b6yJ9AMyPn9FJpyzooFdn1NPzNQ2xh4rxsgqyKUtAWtnw2c22AHir2reJvIfxQFpHNt0ceAhHb+pw/gIiJlRdVGXVzTmoM0/0wRczEljrHpPKfipQlL878DlON8irEbrg9zI3VoAVYAVYAVZARwEGeDoqcR9WgBVgBVKsgIR3MlR2zeevpau/ciktnj/TCJv9g4B50nG3efteuvKaXxouPN2Gh3TkwkNLlZtMdy5u/byGWqUS3Mm5ohJtUIQipyL02FyJ1qkCrQR4e8vbDXCHME5RWDLa7ACeV/edHFB14flVQdIO3kkXIdaDdeHfxR//Gg1PW2h5yXR+9063Syn6ftHnz6CcebXa/XU7IkS7rCjP1Y2HXGsIk7MqKIJzeQV4AHehjg5jmvnhGioIx0Lb0oWLaNnXvum6DOkoA5DD/cEuLFgCSzjWEAKpCyxdJ5BkB/mFBOa1vyNIHQLi2TWsAQBvUI1hHensBPB+eV0gCu7k2Bcub6QZ5QPGP1+e2kCvTKun3AgnjmlZJYEoxAMsBZlGAQnZ4MA7JWuIdr79G89KeKlCay4I43Qyt8qtnic6ckCm/d6xKmABdy2qH6PYR7quc+gCsMuNFWAFWAFWgBXQUYABno5K3IcVYAVYgRQr8L2f/p6WCFgnQ2UROrtk4Ww6/6yTDIB33FFLYvLeLf/gFbTxn7drz0rNgwc3WbpdBtoTFR11XYLpAHdy3l6hopf1oq8Z4jkVsWgu7ab+HAFRLKI3UcQib1FxzOlfy9pKr2dv8zolo//xQwvp/cOLjL97gQB2J7OCd2YXoTwWAA92w/yLrqLAzMgczM3NiWdomyJ4J+eC+SMZPp7BzSGlukUevAC8voZ6GhqIwCM0K4CHn+tCvNEQyoAxf3M+MFlkA0AjU8IfzdcBwEuP+DwcErkJ4URVW9R1Z7hUrR16dgDPDd7hPAB4eGVnDVOOA8TLxkTEBa1OAQAPrx1v/Y/nMFrd8NlEq7/6CfIiFdDzqVGkIciE5pRrVX4eSkRYa6pBHioDTxKFpbixAqwAK8AKsAK6CjDA01WK+7ECrAArkEIFECar5rS7QkA7hMjiZ3hvtXDk3XL9V+m4IxcTClv8+g8PGiG2ug0PrrIwhLkioe4Y6eoXKRqBh71RSKGeO53gTp4XD7PFIvyxTeQsS1VTIZ5VGO2AgHZdhf3UFxBFLiyMRrkLi6jyqjlx0/ML4GFPEIqdTPGGvr/8gsL7R2FijkgXZnYRygUYphSkKhMOvELhxLNryIk38Mx7FN41GsYYmDtFOO6mUP7pR6Zqu+LGlYnx+4R7B3nEZLgpIIBbrryOfXW04d7rHeda2Dad8g5WUrh/FIJ0F4ncaXlhyhmOhbZyIF2Ih/6ALAPN3XRwZxvt395Czfs6KFc4B4/80DwqnFxCldPL06ZlIidCCG2P+FzguoFDMOLizDL+beW6U89hBfAQNnvLdbG5yY6f2UHHz+yMmd7ekm66Z1Ekh11AXM+BQDwkzK6IFEwYFpNSAd5XZhxNC4sqjWO9QDxdeIdxky1AE3GZwoEsQpQTdF9iDoUCiKXy/unlmoEjFrnn/n/2vgQ+sqrM/ktSqSydpJN0uju97xvN0iAoq8PWLCOb7OCgqIjKpqOoIDPuKA7OfxxEHBEFQVEREARlacSFRQRpdnqhm96XdNKdfa8k/3te5VZuvbzl3lfvVVW6v+uvDJ2667nvvfzueef7jldKAJXIi8qtFy+GMA8ujAAjwAgwAoyALgJM4OkixfUYAUaAEcgSAk4E3er1W+jSz3zHcqKtEh+E2pqYWGDqjYIQ6xfxiboKtywt13GYSUKV0NiaThbhEFglDju5yFOEA1+NUFlhTlEW5MSLbRC52/7UTYldwum0V5g4lPZQX3GCugoTVgggVGl2IZEbeYe5hkXgBckDONi0hwZWr6Mh8XOor4cGm3cl4RvsoIL+nZTo73CFUxJ4ICsrPn9blLCH1rfMzVYuDub9woDDJOfXG/d9i9q2rnKcy/SVZ1PZnqk0NGAz6BgqpL7SJtpT+zL1lO9wbDvtA6eTTl68Nc9tojXPb7IIr2S4aYH1vJCE7YQZ42nRkbOobmZ1aHiF3RFcaHGLIDeedZl5qO7UsZ1caK+5cDSxcs2RWxyn/KsF62lLZaf1XTw+ZGEHsk4W5MOLlcfSQo/nl1XTNTMOSetPh8QzIe/QOYhkKL3aRF67TEqFeIFRXhIT+Q8TnuHWTmPkm3mSyXyidOvF3xTsDxdGgBFgBBgBRkAXASbwdJHieowAI8AIRIQA8t8dKkJkJSGH8NkTjnmPpbZDQc47mFqgtHV0WQRekNIiwsugJPAKHwrSbxRtYGTRKdQeCOeThCNIBTiSRpGHTmcNUyeUkXTz1amfaR2EBe75n43U/nZ7SnGnklpq/06hs/L7sAg8JH3vEq6r9hBLt3X2P/uiRdzJMtjRSkOdybxtsgwNdNBg9zrHLnCdJtVUghQ54gMUPzJpqJGvBdendLaEUglKVxgBtAtDDR3VopMKD6q7Ga+cYy15SMRMDw2mx00XDsYFYZVMgL9t2iOOJJ6OCu+5X79Gu4XiDpjHxDokQYx/SzWbxP3ICw7MWxLPrsLDniDnnJNiVa5HV32H+m4EXroKb8hS4qUVYWoRryqmhMK8q+o7tW7HnvXC1OLJUSG1k+cup8nzkm7kJiVMxXVQMgsKPpDB+RKCHcQRN+javfYKL6pilmsPF0aAEWAEGAFGQA8BJvD0cOJajAAjwAiEjgCIux8Kl1mZ3w4EHgg6hMuuEAYV8vuzTjk6Lf9d0ImATNjTnlSQIRyyWRB6fqFlQcfKtB0OnVCxgMCJC+VdPuTfyhZm9hDhtkd2UecfGy1IVVIL/3YzrbDjH4aJBfYEBITOIdxO3mHeIO8G2tMJPMzTi8RDiC04j9j78pvAk3sGbHCtyr1CQnyEIDrllnO6R+wk3sKnr0lVG+xPD99WyTtZyY3Ee99tP3G9JSV5B7IL91u/YvIg88clw5yTijIo8Y66MHuhybrPkmSetTit3d1DneJZJ0vSHKVgFBGJ78XW0EQHBRQcZx+7P52Fm1bVQ+fsn7wPnYok8RBCO4rAw1i18RSB50be6a7VpB7Iqh5xXYb54gPXBa5tOBK3CmWf/Znw5op0V94yodyrnllKE2Y7h3qbrCeMupk8y8Mi8kCUTxIGFlwYAUaAEWAEGAETBJjAM0GLUURBnwAAIABJREFU6zICjAAjEAICTsSd7FY6zOLfKrEXwrCCrBtM5ZWrFqGovULdpkPGhDG2SR84iCNUtkTknXM6HJr0FWZdVRUYZr+yL+kI6pVrqvuxRivkqm96ySizCq85BVHhTRuqpXMHj0h1q2vkgZBZfGRB+DEIoER7i4icHU3god5g304RYrvTcQkgYKr+5QxxQ5yad4SzvFaHBLnllh9Mhl/3WjnE/NV4ksSbsOF9hI8sKoHnRN6hXnfZdto+/dFROLoReE2bW+iF+163QmbBz7m5y8qwWnyPegilXXTUrChug0B9SqMN5DTDHBsFYaVweFafqbDa4fx4buQd6joReE757+yTBYn3wvQG2l49OjS8ZEIJLaqooROqZtE8ET6brQKyyiSU22Re0p0YBCmczlc+toPeXDEcJq90hHsAL4smzR1H+y+fRJPmVZgME3rdMBy1MyXyQH7C/IYLI8AIMAKMACNgggATeCZocV1GgBFgBEJAACGycJt1ymEHw4rbhCrvikvPMs5xpzO1huYe64BrJTaPC9dJcejKl6I6diLpPw44UeecM1l7mKFo6rjqunVChIMePu8v/DttKxgJafVb+zkDh9N0mpCqhmsmXlzkm0ur76HHrTbJPGojIZhOIbTqHAY6XnWd0rhjTqPJJ33Qyr3lZwjht66wvjd1Z0UOsTJxz4Ho0AlDbr1gjTXVvs4W6+dgn8iBKMJlC4fSjRXs63FS4TkReNifd/+xhd56ZoM2MQrVEJLMDQgy5vQvvD8sKAP3I1V3qvJRdtYr5tgmXlKoRJ6Vo1DkJ6wW7F2iX4QkO5vSOhJ46NcthFZdwPhqQSBO6qD18WROPOtemBin9y6bRbOKq0SYtQhFD5BHzg7Syt0ttHJP8tpQy5SyUjqktpqmlCfVXXheNLb2aIVxB90IvHz460820Na1CPdPGoioRRJ48nfHf3JOzki8sPOZqmYXHdbzKaGFNcwr8FKECyPACDACjAAjYIIAE3gmaHFdRoARYATGOAJQYsAVEwffWpFnLh8IMpXAUkNl60V4UUNLtAdPk+3UJbB0+3Rbt1974CIdhf3qqt9vpd30QuFaLRLPTt6hHz8n3mdX7aBJiR6qe+tNKxQTZ3gkz48jDna4DDRsdp2ylwoPJhYybK9Y5BNDSKqbWswEkyB1ZbisSX47OY5ULEHFhpyUbgRS/8OdlPj9CAGE9p2bN2lNF4YWzRNeTqtrJ/CkQ+7Pv/LUKEMUv0FknrzzbjhOm6zw6zPI95JA1Q1PVseQhgydPf2OhLCTAy3a6xJ445PGsqlSsl8VVS+rsVxY5XWM0GoYS+A6Mik7unos4m5H94gbsVN7EHmnzagX6RJKhfLau67J+E51ETIL5V0q5FpUAsmrXvf2+/XC/zog02EDtce1XyJeRuC6CbPI5zlejOkQeXVCGYlnKhdGgBFgBBgBRsAEASbwTNDiuowAI8AIjHEEoA6AAggFCbRlyFkulqUm/YeCBgYb6iEP+azau5JGFvlQoNyAagKYZVpAPiC3nwyXNekviBus2r9XOC3CZg8fXJimvJNt3da/ubGd7n3mHevwfmBvCy3tSVcF4ZBaW5FUAw3sEbmx+p2dfN0IPLuBRTLUWJicuJAvJlia1FUJ10zvGxiUQInltgYnAq+vtYX6W51DkNV12Ak81cRCEoggV0CW/+67fzWBIK3uxV853lLJ6hJoq+5poMbXOqjp9SQxWXfgOJp4UAUtuWSy0Ryk6i4IgaoOJIk0kDlOqshbvlFE695OJ1h0wmhnzhkt66s6exqVDmMl5yD3Av82ec7d8c5GbbymChXeR/abFfmLml9/8Y20OUkiz0qbCJZa/ALKPLUglHb/5WZ7r71wj4ow1MDfGfwtjKLoEHl4wVFfWxbF8NwnI8AIMAKMwF6OABN4e/kG8/IYAUaAEVARABnW1JokUJDTrVscYsJMbq6DNg44OPhDCYFDOA5STmqqqA9aOnO11wmqfpP92A0qgqjIwsrFByJPLdOHJjgSd7IODuV2Nc+9f1tLm5s6LEUnQiv362qmAwSJZy9pJJ6LCs+JwCuavoDKLvj3Uf1hLiDxMGw21Hgg3MpFIn4oa8LKG6kSOPY1OBF4AEFHhWcn8JZ89lqqWrjIcsXF9aeqXH9/89+C3AZWmzNECK3XGmTHIO7w8SrH3DzXIvP8SiaqO7e+pcs1+CWEsMt7MogKD+GzdvVd0cIKqjiw2nL3lQYn6lwwPl4M9Itns1seRVn/D1t3+irv1L5xn5w7bxqNLyj2gzbw91J959SBNBBRTVDUerlQ4WX6AkQXKHlv4KfdhAmk8YSqEt2uuB4jwAgwAowAI5BCgAk8vhgYAUaAEdjHENi5p9sKm0P+HRwuEMaVrWJCYOVjnj4khG9q69XKcaRiarJuv70wcYP168v0e5XARMjs82t2WiQaSA8c0kHeORF4GEeSeEN9PTTYPDrRvZ3A23FkIe08uXbUFMcnZtPM3uOoemCOuIa9lWym67PXl2ovL2ORTMdwWoMbgTfQ00M9u7zJMJXAg/rugM9/0XJndVqDdKANsgYQeLLINSC3W8ewCy+++9u161OKO78xvEi8bO6Dmp/OxI22pHSIJk9JX2XBhDgVHznBIk/xzPVSfakYOuVRQ+jsH7Y5G724YYt7c0p5GZ06NTqlmxeBh3lZ5L4oIBMHxUNiUBFU54LAy3ZqBkkQq0Qe/vaCtOXCCDACjAAjwAiYIsAEniliXJ8RYAQYgTGOAAgoHOblwSKMkFA/SIIQWGEnG/ebo873pmG90qW0WITfIv8gnBgzLbpusJmO49ReJsRHnqdv3vdPi5RQQ+OQA+/ELneSoUKEjeKDYje1UAm8tR8qoc6FlZ5LAJF3YNfH0lRgwNgtr5wJHmGGy+qM66Qo7P74CMnZneil7kSf+PSKUPNuKhYGDCWCCEl+kgSJLNLEAuTd+758vaW6cwtzXfPcJlrzvF5uPXWMCTPG01EXHpQ2rj0kddvLbfTMF97VWX6qjhOJZ2oWYjSgrfKIs+gIZm5KvLOX7qLp45NqZifyDsq7okXJaxiqWeQe9VNvquPbVVtuphVe6y20klEO0cfmz84EFs+29vBZe2XVwMJubJPtMNokEVwSeU5AJ8BUIg9yZeDChRFgBBgBRoARMEWACTxTxLg+I8AIMAJjHAEcDNuHVXdTJ5TR9t3dka0oCHGnTibTkNWwF6Yb1hvUoEJnvn5mEjp9BK0DAhPGFI+t3ExPvLLVsZuL2zZ6dl9fXZ72PRR5Q329VDhXEB4zFtDzS3+hPT1J4qGBVDC1dcGoxTxvYnPJ69a44DwQLlvde0DWHW9lOGW3IHuaf91qGVls62iyyDu1DAkZ09DAgEXOxMVSJ/YlyYDusu3UftxamnvWWTTz4P0twsgpbFPtK0gY7ZEXHEh1M6sd90mu4Y7D/0kDAdjUs5880OrXnq8vSLi59oVkq2gPDV79Jol8eAXCnXbEkAVNjj28m04+rptKkykeU0USdyqpaaLcdcqPF4TAQz9QvR1cU02HTHDer6AYyXYmBB7aABOLWBRl6YmTaL8TJmU6Be32URlYaE9AVMT9AQMLLowAI8AIMAKMQBAEmMALghq3YQQYAUZgDCPQK9Q7UnVnqijTXXamxJ0cJ1v5inTX5Rd2rOb3sytodMfwq6drptGwfpAa3h0Sn0HaJX6iHHBiEU2eW0CT55m5H0pCslyEfjUL99Sfrlhl5b5zKn4qPDuBhz6KFs+3Pq+X/4xaYxv9IEj7/oDOj1rhtFY/ghiorkA+MZg09Puq8bqLGgjEXU8sGZYKpSRUhZIsquk9kPDJZlFJn3s/soLqt1V5Dg8iDyTelHglVX51CtUeXmsZpOgabTRtbqHnf5MkL3WKk/rO3g5mFc998V0qEosBiWfzL/AcBiq82e8bH3rOQZ212eskDVOKLUJY53pS28uwXx0S1W1uan6+m1em56zUWY9Uvx1SGx2B5xdCqyrw1DnjOr/iR++xfmVi4qGzbrc6ui9gMhnDry1yIU4STuJcGAFGgBFgBBiBIAgwgRcENW7DCDACjMAYRgAhjzube6wVhH2gkcQdCJAwDmWYX//AoG/oWba2wyvsWK7dyVE37Pn5KRNfXzFAbzwlFFouZZIg8Q4EmadB5KkhjFDf9QkC+Gu/+afnkk7o3EmTB5LXmL2oYbT4rqCuloqPfi+1FG2gN8bdGQiqY9q+kdZOmk44uYvKiiDvdoxbYf0TZIvM5Wcnm0oTk2lq1/JA88qk0Q3P/Iy63u6kjz15jFY3/7hoC335snO1VHf2DnVJPB3yDn2rxhUgLFCsPIk+Kxns6aYFxzTRkuVdlvoRbcoX7C8+B2hhEEWlkbDWmLbzsbxnwgubL6JXm1vpme1NaTnk/NabawLP8rYBievA4E6aO46O/9RcK8QbeEWZZ1LiFJYBkB/uXt/DwAkGPFwYAUaAEWAEGIEgCDCBFwQ1bsMIMAKMwBhHoLGl1yLGwgrHdErUHQZEONyBNMqm0YbXvHGYrxM5lBqHnXxRN5sHUDk3LwJvxY/7U4o7vz048fKYK4nnREjKZPz/ee+Lfl27GlrUVpSI6y4ZiijJO/z3ppI/02bxCVJUFZ5sD1KuVuQe6xX5Hu3qKUnegWBIhhmOqO6cxg+DxGt8Kz034MSl9a5LfaNxA13/t59Z3yPc8BMr3k+zG+oc6787uZH+fNBq2iB+XrDoWLp4yfFBICSQeMiHt3tL66j2IO4WHTnLNWzW3sDuPAsKD0SemxoPxN1A6x4a7O2hKfNeoSlzX03rsmz+/lT3rxfllMiT+Sxxzbi9nIgy7BchtK+2tAiiOUmI6UQnSwLvsgWzA10Tuo3cwmhlDj4nBebxn5xDk+aNOA9XCBIPoeuqiYju+Lr1sm1g4TQvmFdAyc2FEWAEGAFGgBEIggATeEFQ4zaMACPACIxxBKBMgtMhCKnJ1aUpRZ7psqLM9Ya56IaLms47k/qSPJMmG8gxBZOAbObocgst9lPeOa37Q99NV4NI4qs/AeIrkbYukHogYh5buYXgQutXEE4LJZ7qTIsQWhB3CJktFD9lyYTAgyvtLPFxKkliIN3IAcq7vuJdIpU8UUIzvjNoOO2mP6+jrsZOx7mVTxxHs46bP+q7e99+mu5dNUJm4j7Fvhz32hIrp5ksG+ubCB+oai0X4LrZ9J1/+bjftvh+DzJPEnmLjprlW99ewU7gye8twlQsBpjLVYC869+1nQrHJUROP6L6Ga9R/UznkN4Z19yYUxIP65A5/nB/tIpconI7cG9UCGKmQzxX/cwqjAEdbnDHOxut/yoaNkCQ++7WH+pNipfQB6a7k8VB56K227W+g57+8YZRXckcfHayUarv7A1UtWPYRF4uDSzUdSL/Ha4hLowAI8AIMAKMQBAEmMALghq3YQQYAUZgjCOAnE572pMOihPFgQJ5zUwcUqMm7lR4/cJFs70VIM/A+SBfWlR57vzW5BYK9ssvpZsd+PWD75EX78DlRRZBBIUd8qe5rQsHz/LSInr0pc1aBJ59/Jl1FXTx+xc6TisqAg+DgWyFGg/XfevQdtpa+qRFTGpyd6n5zm37Nx1IrTqduzpo81/Wa9Wfeew8GjdpRI102gP/6diuUJz7pQIrqW4arRx89Jxvao0ZZSU3Ak+OKcNq+/sF+diXzD8oy9zTn6F54tPxUjV1io+9LPrB76Ocunbf0jQFRBP2pDSun3dQexBbRdXIQjWDGHBwt7a+F/93ypTJNKU8+pxrTiSeU/47N/JOXarMAwniHSRpGIRoqXiulQ4T+UHxz7Qdbtn62rJMu+H2jAAjwAgwAvswAkzg7cObz0tnBBiBfReBhAif3SXCaFGqRUhPr1CT6BySdEiesFENQjCGPQf0pxo5dAhlWi7DemUoK1SUsgRR38m2n7ql3CLueoT7KXKPuRVVEXnTgyuNYb74mAU0c2KlY7soCTwMCMJl/Lg4bR1aSZsGXtYKQbRPdErnciobmKy17lX3vUbdA81CbdZDiaGRfICxglIqLaqm4sL0g7xK4rkReBgYxN1wWjlH0j0fCDzM88GTfIwxBrfTQH8b2ZO6Lb/922n47nmonvq3jxBQCKed+Zn0OlobEkEl3A+ThIIZSjjku+sTz9Goyx+27qQd3SPXE64FXBNQZgpz4lTB78+aPZVqY9nLtwYS780Vu0QIf1Jxaifw9l8+ifZfrnf/yGcuTETw7IXKORN8nZ6ZUe+Vvf8S8YydIFIwcGEEGAFGgBFgBIIiwAReUOS4HSPACDACYxyBBmFkARUSQr9KhLKqRYTVuhWVuANp5EXyhA0LCEYQSz0il1muCg5/pfEiax5QbVl5sASJl6uCHEr2OQQh8JKhmUSnX11GldMGfcOAUR+EKnIAbtrVTvc+8442BF7qO3SSCYFnN7FQJ6Veu3Bm3VPyGrWVvpHMx2Z4SemG0a5/+k1q2L7OExsQeZXFU1J11HBaNwIPhAjCEXHfSuLGng8tXwg8rzDawYHtNDjQRUOJdMWoVN/ZgWu4bXbar/JBhSeNKkAsoVSWJ/OaZSOc3k7iYVypzgSZiGfURQtnUF08rvViRvsmNqj41lO7aJz424KQYqju1Hx3Bt1YVWWOVfx3UHMkqJa7xVxy+XcEz23kwOPCCDACjAAjwAgERYAJvKDIcTtGgBFgBMY4AlCMgJCSudxUYwa5NJX8yIa7qhOkOPRgHrlQvDkZVIRl/JHJ5eM0B9PwWRB3SAI3IAR3MoxWZ07J0MGYRVSs29GqReL5kXdy3GeqvqIzhbQ64xOz6cCujzm2k260al6y5pLXCR9cUyAkTULHdQi8XT2raN39a7TWYSfxlpx/kNXOTuBJ1Z2TeYHMhybDKPOFwMM6/nbtemp6fST/H/LfDQ01i2tuDw0NJKyPLDWLNtGhn/+lI25920qp+eGRPG4TTr3IMrXIRfEyqkg+L4ojNWKQa97R1WMp8VbuaUnBMKWslGaPL6f3T6uzwmdNUyOEiWcUIat47kGRh/vAlCiFUrKxtSeQ8jYsXGorS6xQay6MACPACDACjEBQBJjAC4oct2MEGAFGYIwj0NU7IA5BSQXMpOqkqkomG8chFfmHcCDts1w8080Msrl0qb6AeipbBYfPKqGUcFq7F+GZrfk5mXvous8mlTpQcYkUasNOAiYEHtYoc8pBjblqS4uVD29zU4fj8o9eMoXw0SlBVHhuDrTIVei0f5LAw3ykOYRULfnN0Y/AA3m38qXfUdWm/fy6Sn2vknh1SycT3GmliUVqfmKfMEe3ItV4B0ycQ9886qPaY2ejIki83W90UkwsBktIJJJ5AVUCr2ahIO+uTZJ3WLOTw6oaShs2gbe76B3aExtRTC7oPdURGmlUkTRYcA41l0YMZUKxG6Whhdfe4ZmJnI9wGjclusK6JpxUwuH1LYnSgVEO005jJJXDpSJtxEjocVhzMekH+Vyt3JVcGAFGgBFgBBiBgAgwgRcQOG7GCDACjMBYRwD5hJoEaYeihhc5qc5yudZMnXJN5q4qDr1yLk2dUEbbd3ebdB16Xbu5h18IrQyXBYliDx21O9HqTFYmmi+OJfNTbWhoSyPxoLpzy3fn1f/r5T+j1thGnSmQnbxT9w8KUyd1nUrgyUEsUwUNNZ6ficWfd91IvWsKjAg8zKEiVm/lxJMEHtYBFZ6uQjDRO0SJviE6a/uFNHNgplC4DdHiY0upbnaMJopProq8Rt76+U566SfbBDEn7pnBpHsxCLzqeeupZtFmy7TCr6imFmEReO+UPEbrxMepzBcknkrkVZUXGxlVSKUe+g4a9umHidf3UJy1d/fTeDFvEIkg252I0UzG8GoLpVyvePmjk1s1yBxMHGvxQqZMqIabxTMhVwXPmEmCwOPCCDACjAAjwAhkggATeJmgx20ZAUaAERjjCOzc022pYqCWQGgPDp25Vtw5QYq8ayBkEDoVRTE158gHYw07gdewfpCeun10Xj5J3CVzp41Gb9LcAlr+yeB5maQbZ1sXQrINk8q5bKYOiWcn76Q6CmHhfvkJ3636xaiRgRMO2W7utH7qO3R435ZLqGrjEmMCD6YWZUU1FoE385Bplhvw3ze/Q59Z8RPfy72jaUCQd0RHdB1FR3YfNUpVCBIPZF62iTwZ7ggCR+5Hou83lOj/jbWmROse66Nbwibw/lF+S5rqzm0eR3ZfQwvGLbWIKL/ryqkPiQPuDRBq2SDRVMWZSnR19vT75i998uEN9OTDG0ctZd6iajrpzNk0b3GN1pZl6xlpJ/JgMGQvuUzDIOcCRXt1RfYMRbQ2iSsxAowAI8AIjDkEmMAbc1vGE2YEGAFGIDwEmtp6U+6q6BVhqlGRZJnMOqoE5GqosIk5B+bTKQ6KmbgiZoIH2iJEtFUYj6gqM3sYLfLcJVVc7qOdeHmMJs/LLC8TcETIHhQ3YZEULUUbLCXe5pI/pyaPfHfjB+bQrN7jUr+TY/cLRaluqHd3UQPtGLfCERSEB6PY1Xt+6ju0CUrgoW1NXKxLkHez3jMtRVa/0biBrv/bz1w3T5J30/tn0AVt6TnhUnnzhBoPtPfRl1ZkjcSTBg/254lK4A32dFPfrm3at0HnS9UEEg8lUxMLXfIOeeQgzjyi5xqq6JmnPVd7RVMSLfBAww1xDVcK5Z2qOJMvKYpFeC2eG07Prh999xVav2Ykp57TPEDkffpLB/tOES8YGkTIajYIS0zG6yUM1IA9goDNpYFFjSDv8JKBCyPACDACjAAjkAkCTOBlgh63ZQQYAUZgL0CgWyiW2sSBbrI4cOU6LNQNzijyKWUSKgyCAmJAkH65Kk4kolThdXU1iVxjgiDp60pNr7i4jIqLy6m8vC71u0zVd/a1yzBDt/DVMLECKVIhlKPYRxB3pqF6XiQeSBsQAlKNN6VzOZUNTPac/lutD9Jbbb+z6kz/6znGS60rnUtzjp9PxbXlaW1B4iEn3htNG9N+D/KuvnMGHSmUdzMSMx3HG8mhl3Tc/eDXkgRYVAWYgVh2U6upBB7m0NewjQZ79ULRu1+ups5/VlPNyRcRQmiDFq+wWbVPrAXMJ9yKaxPz6X1d1wQdMtUO+4GQVi8SLeNBRAeWs7gIG5UOuWqfqqOrmh/v2o+NEOV+c/Aj8XKZc87JsRbhxLvFy6pcvpxCntmY5RzEhRFgBBgBRoARCI4AE3jBseOWjAAjwAiMeQTUPHg4eOciV5MOiGE6v2ZC3Mm5IqdSvLgoJ864cg5OJGJTw2v08l+ep9VPHu0KK4g8kHjTFo3LKHTWbQDs1XhhAOKV6F9nz73qyD0MGtYo+/Yi8VCnunAKTR5YRomOCb5KIhhY/KXx21bXE199P5W0TjRa5rRpB9Cs47xVXiDyUBo3Jmjmi+/V7l+q8Rb9SwktfH80ebjcVHf2SfZ0np36lYkKD+q7bkHgHXX3k4I49w8FdQPnsSpvIs4iPS3DDUF6KhH77+28miYMLNDG3F7x1RVP0871G2jnuxstVaxlZiD6P+CEY2nZ8uMD9+vUEC88ULxeMMh7CKG93/3qi77KO/s4n/7iMtdw2jCf10GBUYm8YkGc7WzOnYEFtrq+tizoUrgdI8AIMAKMACOQQoAJPL4YGAFGgBHYxxGQqjuop6BQyKWqzG0rkoqOEuEimDTdCFJkUnmExWWaT8/JBTbInDJpo6oSsbaO5jfpvvuushRDKL1bT6W+bf86aoiiyncoPv2PdPrFV9GUqcsymYJrW+wX8j3h4Aqswwqjk2FyBaJjqEbDUtSAyOuJNaStpzQx2VLdyRx/cGz2C5lGCC1KSUsdTXztX7SxRQ68RSccSuMmVWi1WfWXHlotPiZFqvE+9J260MKcMb5U3enmeOvr/k+hBnwrNXVdEq/httk045obadzCA0SOwGJLYeYWCuqFixeBJ0NmEw65Nu2mFrrYg7SzyDtB3NmLdA8GWXjSJz5G9fPm6HbrWU/XQALXxI6N7fT9b748irDUmcj3fjYSyq7WBzkI0qytq1+nm0jr4O9ahVBMdwm1tG6IfdgTwrU6oaok7G65P0aAEWAEGIF9EAEm8PbBTeclMwKMwN6FQFtHFz38xHP09DMv02EHL6ErPnKm0QKRBw/GFfng1Oc1cYQgNQrXXFMyyNSgQge8bDrjus1HKkzgOBoXB8Tv3nyEIzaJtvk00JZUDpVMT3fc/Njlf9FZbuA6IL/KS2KBiBb7oFLhFSRcNvAChhtK8rc/MeRJfsGFtrF3dRJrAxJv6fKjafzkkdBmv/k+c1cHNQkVXpByyXfrxJ4UWeGVfoSkX/9yT0z6Ghx4k/p6vpLWNUg8GFq4hdMONh9NtUfeltZGKj1N8i56hc/CwMRyaHZ5wAQNo73ri//pB6OlxgOZd9LlH6NJc2b71veqIPdE91kpTSugOsRzDaS4rlWQmwoPpFm/cMwxDWvPaOEujfGio1jkBAQpi2dRUhmcXUde5CPEvnBhBBgBRoARYAQyRYAJvEwR5PaMACPACOQYgXMu+wqddeoxdPxRB9NNt95L0+rr6LqrLtaeFVQsONDkAynlNWnTEN8oiDt1flAEgvw0JRS1N8anIg7JIGJgGvHscz+lV16+y7jrg99zKeETZVEVWkEUOSCWq0RILhReuE7DUt0FWTOUPF7klxpGi/5B4lVt3M81nLZ3fCOVLBqiIxdebjSd333N22jAqzM40h5wQpkV5gzyt1WopEyvYbmnIP6DtHci8TBnEHl2Ei9WfiiVVn/PdUnJPYlphdU6EXiWCk48/KBc9cIhCIH3+P/91FF557QYWKcUCqLpnM9cTpVTZxhf55JkNt1T1XXWmgMAEUXnPoMr7UlnjlYNIj9nu7iu7EYwRhd5SJVVNaLdsTZbRF6d+FsBwpkLI8AIMAKMACOQKQJM4GWKILdnBBgBRiCHCKxet5luuOkOeuCnL9YaAAAgAElEQVSOb1izgBrvXEHoXXnpWXTmKe550NQpgxjZ054MTQUp1SxCBfPh4GWH1cQ4Ihn2GLMUIF3io3MYNd1GU0LRtH+3+moOv9J4kZXb6Y+PfJZ27njVeIj6KcvoX0//vnE70wY4OMuwR93wZZWAzSd3ZIRPw1HSTfmlmllInEpFPjx8rMhMGeJc3UhVQnV33KQbTOGkTAg81Y1Whge3dfVZBKlOCUsJ6UbiqXOIFV9AsfgFvtOS5BUqqsYM9oa7i96hF8f9IPVrqM5QZNi510CmIbQInX38x+4Owm5jzVw0jy78/Cet55YuwYRrEi7QQXJCqgSenNNIHkB3RSLquhF4MI1obM2eA63XvuFvmv2ZI81E8PzEC5DOHg+bbt+rz78CHHklMepfm2swAowAI8AIMALuCDCBx1cHI8AIMAJjCAEQdJ/5j1voCkHQHbZsMdkJPCzl4cefpR/e9RA9+Wt31Yq65EHBKsgE39VCldObyI/QJ/u26IT4hmFQoXs5ZDtMTBJacLCUB1IclHe19NDPbj9Wd9qj6kUdRqsOWBoXarryuK9aCsQSDtcgMfIhDM8OmiQksR6n8FGVxMO+ob6dFJ9YspiWVp1Nk0qXGO9dkBx4chC7E60u+aWq7sLMJQZnWpREf/JnYeFSoUTbX4u4swMHlRMUV17kF3LguRlVeG2EKYGHvHevrtB3dlXH/ujN37ReQOgoC3XNQ9zW5kTgybpSnWg39JDfOxF4uXSgdbpPJ4tnpJuBhbz28dMkDNzkhkUuwIki/QMXRoARYAQYAUYgDASYwAsDRe6DEWAEGIEsIbBtZxMhZBZhslJ1d9KF19KN111mEXqpg5XD77ym2CjMIZCzCARYiTgEt4iw2nwrUvmE3E5uB/d+ERIYprmBFwY4YOPgFyQs1ARbr1BgqAARAn37j/QNE+xjZ5PAw9heoX5RkUQmeJvUlYQR1Gv266BjaC291fY72tLxljBtSM8qtrTqg7R0/Igbq8mYqAsX2mdFHjzTUjc7Rsdc6myUIdV4Tg6vMpdhhwhhzkdCVcXBj1xdWXkrQYnnZFThheepbbcYwW0SPmvv+JRPJg0tVHLV7hAelqGLF4En5+WWH8/JxCIfDH7kvHXnojrWhu3Ejr8TCFfnwggwAowAI8AIhIEAE3hhoMh9MAKMACOQJQSefu4VWv3OJnpIqOxkmCwUd/j3nd+/LjUL5MJbvGAWnXXyUVozg8MmVCteJJlWRxFXQihSg1CcyVxVUee581oODn3jRP6tZuGyGlWRikK30DjkmursTtD/3fb+wFPINoEnJyrDnGXII5REMOOISgkTGCCfhmp4MMLPcW3KtUQZ+hvEyEINn3Vall2NhzpQtCGvWpiqu6j2Qu1Xkjf4Ha4pFBDeIFt/E/u00RRM1XfoXMe8wm0Sy5YfR8uWH5/6WhLFMucgcvZhLUFCZp3GvPZj/kpBNT8eCOm5i6rp0186eFR3+eRAazoXiTNSLniFYptcPAi3xzy4MAKMACPACDACYSDABF4YKHIfjAAjwAhkCYF77n+SKivHkXh4p4XJQoV3lsh5h9BalEs/exNd+dEP0mEHLdKaGcg7kHgodpJMq4MsVZJ553DAkiRJLlxJsVwQN3VVSWfcsIt6YPciTmRewB/copfv0GmeuSLwMBesE7m7EKIXFhkR9l7o9ifXgmsz6XQZbV4tUxWel/rOvkaEBlePw76QlSMs31V3XnsEohj5F9W12HPhebUPYl6B/jIh8C79r286TgmGHRVC0YV8agidDytXqY4KT05Ihh9/9j8PpSmzK0YZfyC1AO4B5O/LdQma5kBeM/i7iOvf1ORFXTfc02MijJYLI8AIMAKMACMQBgJM4IWBIvfBCDACjECWEICy7r0HL7EcZ0HaIWwWSjv8+6OCtJsqQmvbRZ48/N7EibZP5L1rGiaipKoLv8u3ggNZiVBpofT04XCV20MiyE63/EpBsFMVhchz53dAh7IjJg7zf3v2jrx1oXXDAWsFedc/fJ0ViUT8YalegmCfSRs1LBhEUXEsO2vRJfFMyDt5DQIPrAX3W74a2/jtmRpmChUh1oKQczzbQOKtK3mM9sTWuXYTRHknO8skB54TgSeNF3Cf9CeGRI7IcNWqP/ruK7R+jZ678RVCeXfgsjorR1+SrE6kSC78/egW/+4RDsW5LpmYMoXhWIscgvW1ZbmGgcdnBBgBRoAR2IsQYAJvL9pMXgojwAjs/QhcM2xgsUa4z8KoAjnxYFaBnHgwuNgu/l1ZUW7927Q0CDdTKCeyldvNdH4ynBTtogxNNJmXzEHnR7T59YnDIpQ1WKOJolC6T4L4ChJGmwv1ndtagzii+uGaje+dXFl1zTrCmp+bqQWIu8XHltJE8VOn4PrDdagqCHWMIXT6znYdOW9V2anmLJTKKhB5IPFA5qGAtENZMPwz6LyDutDWz51Np3zq42nDytyQ9rVUlif3NSziW4fE+/QXl9G8xTXWuE75BmGss7utNxLnb9O9kCY/pu3U+pLIw32BHJC6zsDoA0Y8eEnBhRFgBBgBRoARCAsBJvDCQpL7YQQYAUYgAgRA0N0miDoQc8hxB5XdVvHf7xUKO4TL/sdNd1ihs2eKT6YFii+o2mRCb5Bk+VBUZ1nMD3nn8mVuYahN5PqQmwuHQ5CoJkWSeOve/Sfdf//V2k1PPe37NGXqMu36YVRUc/rhMGwPTZOqvF6h3gkaurbljSba+sZueuFXa1NTPvyihTT9gAk04wBzYttt3X6GGzj4V4v8V1DhhEWw+O0BFHlN4oOyRBB3ukUq1dxUkH7GELrjZKuenzMrQlF1HF4znW8QIwtpYCHHlgYiuB/wjLAXSXzblXBB575+dbOlxHvy4Y2pLuaJfHfzFlfTSWfOcexWNYGA62qYquSg65DPkrBSHATJtwrzCrwQ48IIMAKMACPACISFABN4YSHJ/TACjAAjECICkrh76dXVKbMKdA/DikMFeScVdqiHEkRxZ58uyCOEl6FMnVBG23d3h7gi865kWCJ+qsYG+TA3uRoczkDQBAnl9SOATBADwQKlx9atr9Cvfn2lb9Nsk3fy8Fssct6BKPYjKREqDRWbThixXCyIuxfuXUtb39ztuv7p+0+g875zpC8+ssJb69bT0vnzRtV3Ut25derl7qo9kQgrOqnu3IZzUrBFMbVnnko3VTjmxOO0hpH3FIguPwLYbtjhd01qTcChkkkuPDt5J1MG+N0zI+GeRZYbshPRF3T+Ju1KxD07obKEOkRqAz/8TfoNUtdyVB82xQnS3usekMpHP8fauvEl1gsxLowAI8AIMAKMQFgIMIEXFpLcDyPACDACISEAkg7hsdJlNqRufbvp7R9IKdukWUQu8uD5KR3CClv1BUSjQqk4IJYJEs/EidZvfRrDulaRxNKf/nI7vfTinaPqHfyeSwmfbBYTskudFw6+ULDoGEKAvLv/y3/XWpYfiQfS7rePr6C31707qr/zT11OV1xwmkWQmBAU2SKLtAAYrqRehyYh6Wt2JmjTniE6aEacZtQUWPnkwiq/uP1O2rxho2N3M+fMpmNOPJZmzXVWgUmlGpSdJqYb2QgR1lHiqeSdU8isDsbqdYaXMZmG9uuMqdaRz0PktXTKj2faXyb1ozbTUFWHbkQecqTCcIQLI8AIMAKMACMQFgJM4IWFJPfDCDACjEBICCCXXZXIY5eLIlV3UR9+nNaGw2e5UE1AOQE1oJuLJ+bWJ8jGfEiSjvBVkEy6Ib3SORehwFG5lCYJibjovz+yMXSuTRzmqwQ2fVY4rHloMMaQykL8N1RIbm6Q/3P6IzpTStVxI/G+duv/ORJ3aIjrE/NZNGcOnXvKckdlnt8k8iXPnxrKrKMeXbWjn363sptW7xgxjQEtUVhEtLi+mM5YVkpLphT7Ld/1+03vbqBf/uQurfYf+sSlaSSeX/ivTqfZCBFGTjwYW+x8d2PalJYtP46WLT8+9TupiDQlItVOs6WUtGMrw0Xx/FYxzYUqMFsvetQUD+pzDqHEE4UDLRdGgBFgBBgBRiBMBJjACxNN7osRYAQYgTGOQJNIPg7CJYiyLJOlm+SByzeTDR0nWrdDXiaYebUNI5dc0LkFVXZ5jSfVVdJBVK3793vXpOW70533ud8+Ii0nnht5ByICa0JqwsHh/IT7zZ9LX7vqU7pDpdVTHWtbRbijGykZqHOfRkH2BuTdd/7Q7tozBEZQGV33r5W0cHKwfF/fvv6rRsuVJJ6TUYVRR7bKkpDHr7OVt1Cdgl/uPpO1qS6q2SLzqyuKqac3/eWKiqlfyKnJ+vzq4rnc0NKTlfvLybEWCkS83OHCCDACjAAjwAiEiQATeGGiyX0xAowAIzDGEYCCoF2QCjiQTBT5e3a19Ea6oiDEVr6ZbAAnEJ9ORAwIE6jQYuKnXx6rKIDWzaHlNPazhfdYv545dKD4HKQ1PRBtcF4MojAc3NWZGqNAYFYwbsS98ZGVG2jtjhZav6s1RaQtnFJNi8Rn3Vff1JqbvRKMLY64eJH1a4TM4mMvUnXnFIqYCYmHcZJqvFhafsdAC9FsFITs8iPv1KGLhBrvW2fX0kwRVmuST84rbNZtaQin/fRnPmGpdU3CfzWhGt6b4qypWNXcfVCrhVnkM8jK1dmVCDXk2T5PPAvdnnPy+sMLoqiJ6ySe+PvVEyaUvn2pRJ4k/n0bcQVGgBFgBBgBRsAAASbwDMDiqowAI8AI7O0IqHnwcBhr7uiLJI+SdE7FQT+I0kVH9ZatvYITbacgPtVcYFHmuTNdV5IkLRbJ7eEy7J2vDKTdc8PEnX2cowYvoaPFx6kENeQY6uwji7gbNk+x991bU0KffWxl2q+h9gIZIUm1mrt3UXV5XKhGzdVf//7I6Vbf53/2i2ljpFR34vr0MgX+6lWfDBRKKwfDfVAjwp0zcd31ux7UUEZTsuvDd+zx6z59b8S+/PHzU42IL1P1HQYEbh+/8jKqmzo9MoWVxA1GCE7KTyNgPCrDrAX3p06ux0zGlDklkZ8uaEi73/g6z2XpAByWa67TnKIysPBbv/we187kas5/p4sX12MEGAFGgBHQR4AJPH2suCYjwAgwAns9AggR3NmcVC1UCxUUlFRh5poLi9iKklw03WSEvYHkQd4nFNP8YqbjBamvo/C5t+ha2lLwum/3Fw3cnFLkqfvZJkg4k2vFIu82tLiO19OfoIbWbtrc3UP3btuVVk8l2Erv2GF9N3l8mTGJBwIPphVfv/XHqf6LBDlEYj91VGTniVx4+GRapOuu6racaZ9oH9QMAW2R8w4f03LuoeX00fdXWc38yHm4zT7zp79oDyH3HXtz9PHHClMLPXda7QEcKkaZTy7MkFndNco8jGETaCaqN5VUBploYjqis85c5HBV54UXDPW1ZTpT5TqMACPACDACjIARAkzgGcHFlRkBRoAR2PsRaBRhs/0DgxYRVSIMEVpc1FEmSIRF3MkxoXrrFoSZCWFkMl+TusgXGC9Oho0iB1Qmpg0m45rWlYfm4ljBKGJFl7yTY4LEWxQ/RCiHYtbhW8cIQZ2vH3mHupuaRvKuOZF4qAOyreT27VbXJWIP6sebmb+AwJPhs1LZB3JINy9dWAQe5h82UZQpOWSqvlP39+7LakUotTAxEcpIr/xrJgSePZz5mBOyQ+DJdUnlWBj55HKZoxLrCdu0QxLFXuZDTs+rqPLjOamiTZ+XmdSHGROMhLgwAowAI8AIMAJhI8AEXtiIcn+MACPACIxxBBAuhoOYDO9rbM0sD54kEkD0dImPjrLJD0LkDrNyOgn1Rq4LCDwc1gYF64P8T0750nI9R3V8uyGEV9is27wXFC+jjxX+T+BQvIE30xV19nFaunpFnqy+tF/fu61BqPFGX4vlP00q8FDGC8KoulzP+VE60YLA+92KpyzSzvTaDJPAw/xVYiXotaSjttS5HjMl8OR6xgvXaBCteK7Y7w0dAg9ut2ivmoig72wTeBhTGpDgv/3UhW4YS6LWlOzS2TPTOjKfaCbrkUStToi+HyZhvfzIpoGF05pgXiEdeU33hOszAowAI8AIMAJeCDCBx9cHI8AIMAKMQBoCyJO2pz1JlGRyEApiUKG7FflgZAGypUIQiVhnofiHDD3WXUMu68kchCARvpI4QXsqhYXCcVSsWwg06cLESCitdgeiInLeDSmGFU5tVfWd/N5NhVfyh91UtDNJ9pUKFd5kTRUeTCxO+vhSuv/Jp+hnD/5RW3WnzjdsAk/2jeubXmqxiPSBAcEsDpfYzDKKzXRXGUqyPIxQ3DAIPHU9UKeCwMeapMLRj8Cz5ztUsc8FgSfHT5JWo9fjdx9kqor06z/o93iGgWjtEHuj7o9ff2GvJ4zwXpNQXr/1Bf2+TuSPte5hLowAI8AIMAKMQMgIMIEXMqDcHSPACDACYx2BhGBnpPtskFAkKNLgvBqWmsIJT5kkPFekmSQnQXbiwIucfA3C8VA39DIfrhFg2Fz+Nt2R+KwgibxnlMw9Jsg3wSUNDvtgeJlaePUWlMBDnzet2zyq68IdvVT6xxGzhbmTq9JIL7fr59t/O9cy9Wjv7qfzPpNuYqG7P1EQeH9ZMUTdTzdZUwBZijI13kMzSkccNSsunpZG5KmqO6wnjOswTAIPa3AL23QzsQDJ7KWK/NAnLqVZc+foblXo9UzCUKUT7JC4gaIykMh0gaqDKq4hr7x0cu1QRiL3paly1Wuusm+EocKt1jQ/Hv7+lIq2ILFzUXDPTmIDi1xAz2MyAowAI7BPIMAE3j6xzbxIRoARYATMEGgQRhY4lJmEqspDavHwoS7q/HQgzZraekMhK3TRcXNbnVAVp/audCda3T5zWQ/hs38vuoegrAOJN6L1GpkViDscqhM2ki8ogecXPouRnRR4+L1bGG3xynYqfqXDmvSciZViPQXW9etEZGEPP/6/76equeNTxMPXbv0/envdu8Zbcd/3/8u4jVuDv/61gEDeDexxJh6ml/TQ+ZN3pppLEk+qoMI2A/j2H9po9Q7zEPXFU2L05Q8kTSycij3X3z0/vpM2b9iYqoprDfsHQx03InLmnNn0b5d/NDTsM+lIzePmFFYr1a72XJFbO7tpW1fSJGRaeRlNH5cfpgdqmLDTMy0TYxQTnP3m4daXDF2VpkImY4ZRF67FE6r0wvjDGI/7YAQYAUaAEdi3EGACb9/ab14tI8AIMAJaCCD/FkwZdEJVwzao0JqgqBREHajbt72e3xoRTtfXH65jb9C5mrST+e9SCjuhroPKDkUNl3UiUnJB4D27p5XwcSqSxJtVV2l9DeJEzZsmHUwvvOkomri4Jq0LuxOtH4bdwhl3UOTjK7Uxnud/8DS64OzT/ZqP+v7nPy+gje+4k3eyAVR4500aIfFmXD6HimaURaLqWrWjn77zhxEjEd1FXf+BSloypdizuqpee+2Nd+jO235q1bcbVbh1kmv1ndO8ZPinanIhyVU1n+E/GvfQP5qaHZf2vroaet/EWl2oI63nZKoi86ImHWx9ZLshzU7Oo1+Ekuuo/XJtcAQCETnwuDACjAAjwAgwAlEgwAReFKhyn4wAI8AIjHEEoF5A0nkU5MFzClXFYRthTggnDeJEmilEOByjRG1kgXFK40Uif5f7odVEqZjpusNsbzewKCoSvQtSCgRLMnzRfbTABN4GQV74OBu7KfCcQmjVGS6hcpq+foC2vrnb+rXMoYa1HHfpEqqZX03TD5jguChdEm/bjgai/gTVj6twBefrX/4c7b9kkdZWgbzbtKmAenf3UW+fyHlna4UtiVMhxbAposws66ELJjdYe4SceKUXTNMaJ0glUxWen/rOPgdJCL2zZj3dfusdo4wqnOacj+SdnCf2BLnkikX+s/7EIBWIZ6QknaC4e3Bz0jHZq0wrL6VzZkW3p37jq9+rYbVwJoe6endbX6ghs7rz0c2Ph/DVxtbcpTOorSyxHJi5MAKMACPACDACUSDABF4UqHKfjAAjwAiMcQT6xOGzadh91ik8NEqDCl3ooMwYJ8i1ZqEWjKKYrDHquUSxPtnnd2MnpbpPhsuCKBoaFTJrn0NQAk8nB56TCy3G9yPwTj9kNp1+SDIv2t/vXWMRzAsOnUxzl020ct35qYb8SLz1GzZTdUmJ+JT6bokOibdxI9HddxdSe3MvJXwUTSDyygvw/0RH1bTQUdWtlqurPR+e78QMK+jmwjMl7+Q0pErt3XUb6LFHVtA7a51DmRE2e8yJx+Y0750OdHixgfB+FJh2yJyEt6xar9PcqpNPJB7mUy0UZXiJAaftMAxStIGwVZSEIsyDnO5nfD9xfKnI4TqSLzLoWEHb4YUXXhxwYQQYAUaAEWAEokCACbwoUOU+GQFGgBHYCxDYuafbUsQgPBT5xKDKMyG1ooYAh7U6kWuocZhoDGs8mcsvJg5hCH3TSdCePDgm5xKGgUBYa/HrZ2dBF91d9DlqKnjbqloMpdeQIEYLYlY4o1seOdT9UuJJv+5dvw+SB88rfFYOdPtlx1n/KfNnwcEVCk0QD7WVces77KnfHv328RUEMk/Ni9cpQnftIbN+APiReMh79+jDfZQQRA95qB3lOJLEQz68C+t3WkRB6dETKHZEekiw37xMv/dT4oG8++AhZb6hs+q49j3Cd3Cq3bh+I73xxtq0+27m3Nk0byBGhbvbqGhPm9XNQG0VDU6oosSCGabLiax+UiUWS5FcFeIFQ3lJjH7y5gba1N5lNG4+kHjYI9w3vf2D1CYMJWRKBSzEKd+f0QIzqOyWHy/XL1LwN2OSIPC4MAKMACPACDACUSHABF5UyHK/jAAjwAiMcQRgEAEnWbj6QelWKFgqEFVqPqdcLxFqh7DcX/3y3PmtVSqJchVi5jc/9XsQd68VNVFDYTf1FKyldYM3j2peTjGqLIylOc/KSkHVd7K9jgqvR4SpNrQmk/xvFjnn7t22y3OJn//AMlo0pYa8TB1AsIBQQXg4VKa65c1Va+ir3/5/utVT9ZYuXkjfuOHzru2u/5LImyjMT5Ig63UfpwIqKSikz83caDWoWz6ZKo+tE4SKPzGpN4JzLeTEg6nF71Ym9wQFpB3IO7+cd/Ye8SIAKiqnsHR7LrnC3a1U8o8kwexW+hdMzymRJ3P6wcDATvrjufKD1Un1HRSTJuWaJfNMqodaV5pv4MWNXbmqG84a6oQcOgNhh3xzUhkIlSDwBtmYiwLFb3VF8kUBF0aAEWAEGAFGIAoEmMCLAlXukxFgBBiBvQABKJe6xOGtShyQysTBqFkQBMh1l08lLPdXqSzMNJcfch9VlcfFARImIJqMTJYBBXn3ZPEWKhomZAeEHK1jcA1toO+NmgkUedUFIgOb4kI7Y+hAunhgdF3TZQxo5MKTJJ6b+6wcE+TdftNqhftj3CKdce26KSclMYH90T3o/+bBR+i+3z1qukSr/gP3/Ni13b9f3Zv8zoDAQ/VKEUorCbzSo8W6T5wklF/FFolnQkwGWlAGjVTzCi+iO6XO29VCvU+/pjUiFHl9hy/VqhtmJT9XVmlaYeUshKpV3G+Dmo+GXJlaSCWh18sadS9xH+XyeScJRYT+I+dg1A7obtcPyETpghvmNcZ9MQKMACPACDACEgEm8PhaYAQYAUaAEXBEYFCQClA2gAyBWkY3nDSbcEJtBe4DKpEgBepCEJR+pI9J334HepO+oqi7QpB3jUXJ8GjsryydQ84kHkJqa0DiCfLhmKEP03v7PhTatHyVeGJviubU0CMrN4jPxlHjypx3Xqo7p8l6Kaac6n/lxv+mt1avDbRutzDaVS810O13Vyf7NCTwygSx+sVZm6ymIPAQRquGO8q8a4EmHFEj0/sCyrvSF9+21pV8FvlPLNtKPKnoBN5uBJbddRbrsQhxsSC/UO5cEHimSmIQ4tJ1FcpWU5Wh/67q1cA9PVkYWCT/Hvjnu9Tr1axWnUijAFUgF0aAEWAEGAFGICoEmMCLClnulxFgBBiBMY4ADs3I6QYlE5KY9/SJcD+hbsqnAgKuTJCLpkYWarhsFCHBOEwidxRysLUKdYrfQT0bmGLNa8ua6YXELksF5FZ2Df3e+moXPWL9HEcLaf/Bw+j8oU9ZCjcnlWLfzibqfHUt9Tck3V/VMu6ghTRumbcjK4g8eykQ11zBOO9wNByWkTcN5EkQ0koqJv0O/Odc8snAW3T+B0+jC84+fVT7NAIP3yY0GKrhXhBGe/2szda/qq9bkNZ3Mu9aUU7NBuyLlaSQiQFC/IW3UvnucO2KJdOguJ/8UOr+1yMC75VJQ+QGxfXjFzJvJ/AwBp4P1pqw7R5htdkk8KTqsV9ch7rKVBWv5L0U/F40wd6priTw8DcLzwSkfDANlc9kDtjO+tqyTLrgtowAI8AIMAKMgC8CTOD5QsQVGAFGgBHYdxGQefAQYlosLEqDHOyiRA/qjxqRc0jXyAKHPKgJsR4oC6MOCcaB1ikvVpSY2PtW1/zf3a8HIhMPGphABw3UWcTDeLGmIoG7NIPofHUNdb7mrE6zwlQ7BmhzooJeL5xKuwoqrenNm15CJx9RTfNnBEv4rhKwfgSKH9aqmYIb2ZoJgecWQgsC74nHErSpsS45RRA5fuzU8GLmlfbSv03elVLf2deohgkHITb9MNP93m5UoWMIg76d8t5J0guqUa8Q1N737SfMLcbrTtG4nqmS0InAk4OC9JFmMU4KQ0ngFWx7lwq3p7vzDk6dS0PT5hrP36mB6ZrcBpUuscgz6UeKhzJxpRNpsIHnAUq2DTfwnJ8gTJW4MAKMACPACDACUSLABF6U6HLfjAAjwAjkCQIPP/4sbRMqqcMOXkKHHeSthlKnDAUDwlNNibJsLhtGFjube3yHlHnuQCphTbpkgm/HPhVkmB1yCGY7vExdM4icnxevCbycD/eNXDcyR9aWZ9+k1pdXO/a5a0+/cK9MZ6R+GcoPu5UAACAASURBVDs0rS6IvCvPrzeaU1j5Cu2D2h1E1e+jyIEHAm/1Pxvob28r96OmCu+MidvpsMVxqrh4uit2ao4yE+Wb0WZ4VPYyqvAbI/bOFip+Z6tjNYRyg/hyc0iOMow2ee0VW2pPXfJ/a2c3Pbh5u+eSQaBhv+xrOnvmVJr91D2CvNvg2H5w6hwaOPTEjIg8uU9hqtXcXGL99j2T75F7zsnAAvc19qzDMuNIBHqBoTMvjC9DiXXqcx1GgBFgBBgBRiAIAkzgBUGN2zACjAAjMIYQOOeyr9Di+TOtzw/veoiuv/pDdObJR2mtAGTXnvZkov0wHV+1Btes5GdkIdUlYea505xaqpqXo6NpXzr13RRqd8fDIfAwh6HGPdT8xPOO+cmcyDu0aRAKvKeK0glkXRIvTNWdG4YyJNfuvBmFC60k8Nq7y+mVDTOSU0JoM6LUPZR4VcUddKlQ3825YT+dS8FSIskw42woaHWNKrwm70Xgod2IGk/AZZOuBSXwNm7toU3beuiv/2hJTW3WtFKaPb2U/uV91Sl34yCKzwc2baNtXd4vGaTJBZYDIm9Gyw664NU/aO1x/xmfCETimea705qMUklee3j2Rp1KANd4rxjHiVjNhjKwtrLECqnmwggwAowAI8AIRIkAE3hRost9MwKMACOQYwQeeuI5evqZl+mWb11jzQQqvJMuvJae/PX3aFr9cOiexxwTA4O0qyVJ4PkRZblaKsJUceC1G1mohE82wmX91q+aDERJpHgZOoRJ4DU//ryV8w7htCCcpKKxVYTMtnW6uxWvEAReY1MXFTbtSkG2/PSFdNIZC10hzETN5bcv9u9x2K8WYdlQeUG5JtcVxMjCzcACY2JN9/3gFSvp/p72Mnp900xrKggRHbLlRUO2tEKRBA7k3YEzNtM5XzjEd1mbirbT5qIddEzfeyzCCyokhPlFqQQNKxTTj8CTi3dS4wUh8EDaqcSdHVy4x15+0TSqmxDzxd2pgo4Kb2RNIqxWbNi5/3iQpnWMzinpNgETEk9e4+gLzsVR5+hM5mWMUVdvdCq4icJAws9oSSoD8TNsVSpecOF65MIIMAKMACPACESJABN4UaLLfTMCjAAjkGUEQNC99Noai5xDqKydwMN0brjpDmtWN153mdbsGgWB1y+IPIQI4XwCMiyfCows4sVFafn5QGKVxouGD4zuZFK21+GUQy6sOeg46gYl8CYPltHJiSTBJMuunydNLlAkkYIQ4S0NyRxUTqW5qYOef34zdRcUj/p6xuQ4nfn182ja0mE1mqgRNIdaGJgmQ2qLxXXVl3IYNcmF50beqQq1Z/+0hd56cac13YbWEnp3V60goitGpj+sxCsr7aBpExqpfnwvnXj2Apo4TamjLBak3TPxly3izl5A5J0gzEigVLIrDMPAK4hRhdu4Tjnw3Ora1XimBN7PH9hpKe+citW3+D8r757Yiw+fXW8p8oIUExIPyrs57cnrQjfsHuG0iTMv951aWCSr70C2CvLZFxfP67DJM2lgoZNKAdMKOz8eCN5JgsDjwggwAowAI8AIRI0AE3hRI8z9MwKMACOQJQTueWAF3fPbJ+isU44WCqhuuu7KiyzF3Uc/exPd+f3rUoo7/A5htQ/c8Q0tFR4UGl29A6lDj0wSnqVl+Q6D8FTkHsK8ZH60XIbL+k5YVAgzdM3EUfeJ2GZqKOzWmWJaHWliof5SJfDwexyi4WC5o6nfsf+Vz62jlt1Jt9k9BeWj6kysAelaSFOXTqezvn5+CqNcqidV1aQ0g9BR4rmRdzKkUHXyfebh9bR1cxvt6kwqXVF2t05O/XdZSQeVlyZx6ywvpHMu3o8W1Y0m8H5R9ogjcWcH+pKe0+mAkpmWclJVGBpfFMMNgFGVuP+GBMOFvQort2TZH/9uNKVCEb0I59GBI/enrkpngtPeoZfyDsQdXlj020J0oybxkPdu7t3fsKYqw2rhGu1l3CHX5afCw/0lc/ghPUIuStjkWSaEJP5ewJQHf98yMXuB6zNUu1wYAUaAEWAEGIGoEWACL2qEuX9GgBFgBLKEwHIRGgtSrqoinRyB4g6KvCsuPSs1E5B6+Pdhyxb7zg6HG5B4pioH345DrDB1Qhl19w0QlBB+YVQhDptRV0kyJ56m8DLtUBpk9Ii16ygjdxZ00ZPFW0yHIdXAAo3dnGfdwmc3rNlJG9Y0pMZ1IvCqxonDdEWRVWf+IbPp/BsvCJUQMl600gBh2iA/cG1BEQVTi7dWraW3Vqe7757/wdPogrNPdxxK9mHPobZGqBIfuPdtGtflTag0TowRPiifO3J+GomnS97JiX2o+zRaVDSdqsrjGbmFSsI8CkWfbhitCvbgohlUcXDSmVWHnPzGLRsd9wrPEYgfnchI5MX7yDlmxiv2QeBMay/Tysto+rgyKnrpKSr655/SvgZJBTIxIchEr3DXgUNPoIHDTnRcU5gvDTK5l2TbMMwlJHmXyfWn5sdDiG9HAIU5XiBBoc6FEWAEGAFGgBGIGgEm8KJGmPtnBBgBRiBLCBx+2hX0wqO3ERxn777/SWrr6KIPn3cyHX/UwaPy3l0qCLzrrrrYMrbwK32JQWpqHcmDB7dC3bAuv74z/V6qz8rF4am9q1+LxMp0zDDbB1WPZGLMYarCO6l/BtUPjVbM2RV4wMWJwEPY7CvPr0+DzY3Aq6lKhmmDODnja+nhtEFw734jQT1vpodQ11xUEqQrS4GKg3oyj5d+WLbfHv+3UCau3S1Udp0iTF2QeBMb00PUQdpBedc1biRB/sIJFfT5o+Zb60DY7C/LHtVaU/ztKoqvGk8T7p9HtUPVVptDLhxPtYviVDqr0Eg950ZIak1Es1L8hbeoaE+bVu2B2irqO3ypVVeGP3f2wEXbea+c1HfIYAbyzlK8eRiJfOWa2VpzClLJicBDPzJUGP/t9vx1IvBkyHZxLBzFZZA1ubWRc4OCDSYXus6+6A+EOghovFzC36hMi1SSFg8rU036rBP59/B84MIIMAKMACPACESNABN4USPM/TMCjAAjkCUEEBZ71qnH0LYdjXTJuSfRdmEwcPUN/2up8v4p8uLdeufv6ISjD6F2QexVCpUeCDzdsnNPt3WgdTOM0O0nzHpS/YNDX4E4Cfb1D1CPcCEcawWH2NrKOA0IZZefU2NYxhy6JJ4beQeMdQg8rO3d1enqu24qdsyBV1MZE+rRopSr6GHnH0H4BCkg7pp/JXLX2cg72VfNRXEKQuTJnHzoB2o8v+T/fnnhoL77f8+vC7LElApPV31X+839qUSQd7LUDo6nuPgfCkjT+v1Lae5p5VQ5z1tJ5EdIBlqMRyMdEk8l72RX6l45qfHsBJ5byKzT1OBKi08UxY3Ak2Nhr7A2kNx2ktFO4GV7r4Lioe5Ve1fCl5CLUk2ohvjqvKyy7p3asqBL53aMACPACDACjIARAkzgGcHFlRkBRoARyF8EoLz7sgiXVR1mET4rybqUwcXkCVqhs+pKQVYgTBNGCWVC7dYs/p2r4mTWgPAlHAKjdHeNer0gR+ES6hYCrBKWOuGyfvP1CqeFacVBA3WOyjvZr3ShVcdxUuA9/fvX0qbSRiWUKEiGyqpFDaGVv7/i/s/5LWPU982/6rXIO79Sun8RTf32aGWhXzt8n1R4xVyT8UviBHnGvHJrPSJCix8VnyDltEX1dLr4fLvidt/mdvIODSqEqrJiaFxa2yKxLcf9x0RXNZ4kTnCfZTOHGkwtYu9sdVTj+ZlWuKnxVAIPqjsUhKjqlFwSeHJ+1pyH1aqSSFYJPOQGxYuBTMJLdbAIs47MEel130RJ3qlrkc9bv3sYz+wJVcFUvWFix30xAowAI8AI7BsIMIG3b+wzr5IRYAT2YgRAzIG8Q067k0QevCvFzzOFkQXKPSKUFt+bqO2coMIhEGoESUzsEs602S6q+szuYihVE/lmsGGKEQ6NFYIYAtYyhEsaKYBcaBO/D8skQJ3ba0VNqX+CuNMpfeK6anlitNGA3YVWJfD6qZDaC5zdGuFCay+mBB6Udztu0DfpyITEkwQJDvgqceynulPXmCmBd+B+g77hs07knZxD/eDEUZiDF7rktzPTcjPK8EJUjuoa1LnmUAe58VASC0bciv3aQgmKfJNYm1RVSQKvWPwSvB3CZnVLlAQe5hD/0fVaU5EmF9b8xf9JE4tskVxakzSspOakU0OgpYttgdgvhM0abJfhDEaq2/Pj4e+gfdxK8eIFeHNhBBgBRoARYASygQATeNlAmcdgBBgBRiACBEDM3XbXQ7Rd/PzWdZdZRhWr12+xwmY/KEJpK0VC9IcEsXfLt67Rcpv1mmKvCE+V5Nik6hLrv6MgkpzmgEMUSC2QW16OpPU1pbSzuScCpLPbpaqcgaum37qzO7v00ZxIPLsKTxJ4XuSdk/oOI5kSeO+e0W4Mx5Qby6jsgGAHcJnDCyocEEPVFcUilBuqOz031kwJvOoDttEz8Zdd14ycdxO+dYDr904EHiovOquCDru42iK2oLwFQaE65xqDnCcNpMILxjxPPrOb/vpCS9IYwnB+mTjR6gwVe/h2Kty+QaeqVQcOvPFZC2jgrE+IlyyFnkpe7U5zXFGSxlAaIr8piDJds56wp+718ojz34WNNvfHCDACjAAj4IUAE3h8fTACjAAjMMYQAHEHZd3Tz65MU9vJZcjvQegdL3Le4WcYZfvupLKpRoRldQslQjbyzalhTFA/eJGGE0Ui8WahzMgXg41MMAdhggMr1rK7rTdrZGmQOTuReLv29FNvf5IWAYGnknfIVzikyFhKigtoUm2x49AmBJ5u6Kx9oExUeLIv3BNl8SKx5hGiWwfLTAk8vxDaigdmUOUDzkY18aHilJGF01xPvWOSCA2MCzKoyLqvTAwGdNaeqzogY/CsKBQ/r/jaKk+zCrc5RmliIcfUVeHJ+oXnfJJqlyyxckg2CtOhbL1giXof8TegRqgnEwODWX1x5LQuNT+ezNWHF0e4lrgwAowAI8AIMALZQIAJvGygzGMwAowAIxAiAk8/9wq1t3emwmRD7NqzqyZBJEFdhANVcVFhpPnmgrisZpNYjApzVemBXHjlJTGCe6SOYUJUc9Ltt/PVNdT52tpUdZB4mxMV9Paa3bR7zSbHbrzIu6lLp9NZXz9fd3gKor6Tnc/9faX2OGpF9TqFqquyPKZlRqL28cnfvxpo7B+fscxq55UDb8rFR7n27ZQDT638kftnWHnu4LoLAqXXUhb2ZyV0MRAgGo1UUwes5+8vt9Hjf9udV+GzchkF296l4t//RGNVRIMfvJxqFy+2SNZ+QXRVj4tTh3jh4RTyqdVhnlSCGhnXHtYCjmxcqXSBHh3Kms0pyxdL/fh7KNThXBgBRoARYAQYgWwhwARetpDmcRgBRoARGOMIIEQQB0J5qILKI+ySictqabzQcsnNZnhvmOuXeavsYcLSMGEsrmvdlh768x/X0bu/eDQNKhB31cJ1try00CK8nEIYz/z6eTRtqX6es2wTeHJf7PuFaxDXoj1Po9u18t/PraO1uzuMLqWFEyro80fNt9p4udB6EXhu4bMgShCSecZdU9JUd6brMlpQFio7GY8gBPqeBxtoy7YerVDaWdNK6SPn1GdhtiNDeIXTDk6dQ6XHnELlcxdYJL9UH8vQbpPrMKuL0hhM7le+rgsYg1wsFcpbLowAI8AIMAKMQLYQYAIvW0jzOIwAI8AIjHEEoMbZ054k7RA21NDSE6oaBwQWDkOZ5DlKKiOKrXmOlVBamZfLK3dask7cUkCNlVBGVZ3282t/Sdve2jrqDsAhGPUQ9qcagJqq79Bxtgg8zBe57kA8uuW6k3uq6wB6+X0v0lCPULe1dKVjJBRHhdXlVFCabvAh1XeyspsKz43Ac1PfCWFt0tl0gAghtPai4xJqb7PykcdH9TNl4XyasihJQEZd1DyFbg7Pdz+4k7Zu77WeZ25mFrkg71Rsil56Kg2qwalzqWL+QksR7UbuqyGfIJTHSlitnwlHvqwLBB7w58IIMAKMACPACGQLASbwsoU0j8MIMAKMwBhHACSLNIlAbiyZAyjTZclwJJPk/15jShMIL8OLTOccRnt7uKwf4aiG/2Ft+Vyc1IQPffU+2u5A4mEdRSJUDuQJrrEg5B36yAaBB1UQwpoR0udHpKrOp17kSfeDL9FbK96k/1sy3X1LBZFXVF9tff+5I+fTorqKtLqbirY7utE6OdA65b5LEqkCf2sPkl07EXj4varuUtVR9smDuFv56GjyTtYDifeBz18V6WVscs/AlfaZF1uoSCwwIS5GmaYRxB1cZ2dPd3ZPjnQBLp1LErk/ARLZP6w5qWYrFgpqqKgFO5vHBUpPmMK4ka3q1PG3Y7yoj/B1HRzCXjYMnWIW682FEWAEGAFGgBHIDgJM4GUHZx6FEWAEGIG9AoHGll4rxxIIGpRMiCTVZVDnsGYCoMnB3aTfsOri4AlnXVO1IciTWmGYAPVXq3BmVLwgwppaRv2oCi0n05GX7vs74eNUkAj+uI8cQ/udflggpVCUJhaSbAXRaKpkkuRJW1eflVNOLe03PkSJVdtTv/rR4mn0blW5Iz7z+hJ0/bWnuu6PE4lnN7FwIu8QLouw2YTC69QuKqb3faHG81pQHV07bITyH/77Vtqxdp3vtRQliSfvMR2yVZ2oJMdAZraJtAH5ploL+myThDJcXZEOoS+Rfi36blbEFeSzDaRkm3i26Ra0GyeepXiegsTLFkGJe6a+tkx3mlyPEWAEGAFGgBEIBQEm8EKBkTthBBgBRmDfQKBFuFFC7SBDmBC6ZVoyyXNnMhYOdnVVJVbyfZMDockYpnWDmHM4jeEXYmY6r0zrm6oJnUi8w84/wsodV1UeLFS4+40E7bgh6ZRsUqbcWEZlB7gnopdEEMwcgpIDwAfEq2oE0b9qG3Xc+LDjVJ+cVpv2+5O27bH+XXr2YVQmPl7lmfjLBDJvc9EOqxrCaBEyC/IuLv6nlpiI/lNVd/K7936hmiYsSq/rNKZTeKqf8s7eTxQknszXl0neyHxUrclrEUSVnQzWveaDhEHr9h20XlBSUh1PEq/4XVjqcK/1IN0D7mkujAAjwAgwAoxANhFgAi+baPNYjAAjwAiMcQRA3oHEw8F9cnVpKqRWd1kyXBbhh5mo93THwzwRYlUgCBTMO1eKtShIS5nvD+vKpZom7D1VyS5T4tVUhVe6fxFN/baz4i0T1Z0X2QWSEorTxot+qHsZp9Wr+cUVRu12r+mjF29uSWsjjSqEmHbUPaFL3qkdSuIVIZr/+5GrjeaHyoecdgodcvopxu3sDSQRBHLL9NpxGlwlhUyVlxkvxtZBmKS9VK0hHDzXYbVyz3TzRfrhquYUjVKlPH5csaX848IIMAKMACPACGQTASbwsok2j8UIMAKMwBhHICFO/LtEGC3KxPEl1CzII7/cbahbKnIaVYkDT1h57kxhlAYZYYfq6swjbIJLHVPm+wvr8KuzHllHJSUzUTo5jaljPOA21+1f7qKeN/3zfHmRd1HuGQiGkg0NtPXLv00z7tDFXkeFZ+9LJfFUowp7vSDknewDe/bWEyvoHw/90QrxNi2X/fj7pk3S6gcNmdUZNJdqPBn6inmG/RIi1wSlJH7DNh1SCUooZ+0h3jp77lenTvz9w73MhRFgBBgBRoARyCYCTOBlE20eixFgBBiBvQCBhuYeKy8UwtSQD88rmb9K8kDBkkulWPIQHnN1bAx7a7J1OM5EsRZ0zUFz+JmOJ4kTU5WhXzhtzUVxqrmoZNR0oiQl1cF6hHFF38P/tH5lSnYFIfAwDsiGrU900yu/aU0ZVeD3XQUJGlo8REvOqKClC8abblFafeS+a3hnHSGfod1Z2K/jTAi8MNVpbvOUOTuhXsyWGi+M0FI/3PG9NINAvkC8DMiGUjlbe4Zx4uIFUph/fyrF3z6ZB1YHX67DCDACjAAjwAiEhQATeGEhyf0wAowAI7CPIAAVG8wXoKorE4RYs/i3veDgWS6MGnAwzCc3WKn4MCWETLfWyYXVtA/T+iBUi2PmJgsm4+Qiwb9UGQYJu0ZIrb04EXeSxMC++Y3z+8dXpbo845QlJvCl6sJ5FiReMpS1wCLEdUmTIASenSz50/oG2ra2WxB3gzS0JF0ttyxRQ8sS6Tn4dBd5xyc/m6oKww8UXYLyA5+7iqYsmq87lFXPKbegUQcBKuMZUj0ubjkRR6HsklPCOJVlxVqOxwGWMaqJ6i4cJtnlNLdskHfquDJnK36XKfnK5F0YVxv3wQgwAowAIxAUASbwgiLH7RgBRoAR2EcRgEIDLoZSHSJDaiUcMvwQeaicnEhzDZskhKIgFuXacxUqLFWGIFl1QptN9iIXpKScnwwjBOGFtemSXTrr01HdrVnXSCDu1qxvGtXlonl1BCJv0fyJOsNZdSSBh/8GzQWyK2km4R96akLgqTnhYHwA3B6Pb6OdhT2+cz2lbyrVD5q5bKoEHgaQBKWOGs9UgZck44utZ0xQcxFfEFwqqCHeUTi6ZpvgUpcZJtllhy/XOUmlojdpSGOuNGTyLugdw+0YAUaAEWAEwkKACbywkOR+GAFGgBHYRxDo7R+wwlBRJlWXpEJSJVnQL/JftQmCD6qifC1hh6bpkEDZwiKZxD2Yk6vTHMNyzg1j/WETlDLhvZfqDsTd758YUd25reMLVx6jTeI5OdBCiQfCy4941SXwgBVMCqAUk2HuuuQd1lg/WEqn9E0z2jaE0O5Yu25UG0uNJx4HXs8EEwIvlwSXneyqrii2HGElQWoEmK2yJAajVtLqzDHsvH9SLQn1djYMjNzWqCoNTV7i4JkKVTkXRoARYAQYAUYglwgwgZdL9HlsRoARYATGKAI793RbiqGayrgwphigYpEZH3mGTA5EuV46DnJ1VSXU25+ZY2UulWluGIZFUObj2iTplonySj3Eexlw6JJ3ch9MSLzmf7tt1PZhXtg7L8WanwutJJOLBZGrmra8GttDr8aajW47UxJv5SOP08pHH3ccwytceMrC+fSBz1/lOzcZwo2w3LAcRveU/JaaS+5PG7um91wqS+xHZQNLfecUVuhpWPes74QNKsi8fzGxeZkoDfNxbVBiw0kWpb0r4ZqfFdctyLvSOJN3BpcOV2UEGAFGgBGICAEm8CIClrtlBBgBRmBvRqCprddylK0WByAQd355w/IZC6wBCiHT0EwZipurcFk/TDNxr5QkWb6uLRMiR0d1B2wRNnvzD5/xg3nU97oknpMKT3bmpljzU9955Qu8q3S98VrQ4NKeeUbt7GG0amO3cGGd/HeZ5EJ0WkB30Vu0fdw3PNdWKki8aV1f1Vq/vK6CqPFy6Sats7hM11YzrAgGNvlWZCi2074liccSwv5wYQQYAUaAEWAE8gEBJvDyYRd4DowAI8AIjDEEQOwUFpJwoR2ywv5kSO0YW0ZqulCaQWGhKpbc1qKGyyJUuEdgkc/FJNwwn1yDdTA1WRv6M6lvqr6T8z3j5CVWTjyd0n7jQ5RYtd2xqgyplQYXsSVTqfKGs1y79VrbzsJukfvOeRy/eZqaWuxYs47+8P9u9ewWz45CwTBjbfUL/NV3Jvvmtx5876S6c2tnQuKBNIfTNUIt27rEs0GDsAp7bTrrD1JnZG0xkT+uXyvvYNgh70HmrdPGaW1SNRgT6nIujAAjwAgwAoxAviDABF6+7ATPgxFgBBiBMYQAQvwaW3uTB/CaUmpo6QnVWCAXUMjDpldIpTSpGGuKw+S8i4UDY59rqNhYXZvM+edFKjiZOfhdY5f9+4N+VVy/v+N/ztZu60XiyZDa4iXTqPS6Mxz71MlRGCR8Vg5mSuChnQ6Jh7XN2X8RnfXFa1zzx8kQTvQZVl5NHeWdHWiE1Nb2nqe9pzI8E2kGcM+5ma7AhKNEKJh1XhxoDx5xRal+xTBejq5jhZhU4ZJrA7mM65PJu4gvJu6eEWAEGAFGwBgBJvCMIeMGjAAjwAgwAiDwdjYnnSwnVAnDBI8cQmMJrWQ4VXwU0aVDkuT7Ot3C9PLJgCMohjJBPvIZ2s0EJJEAsqEvoa+WzBaBhzUjnLbnwZdGqfGguis/571Ud9hsS+lqJ0wkMYs1S6MKJwyzTeBhDiDxkA/PydQC3x9y2in0njNOsYhl3Hf2/Ykqb9q28q9TT+xt40ttXttvjNu4GUGo1yuUemOx4NobLwhImKTYHV3HIjEp9wB7M3F8iVCYc9jsWLwuec6MACPACOztCDCBt7fvMK+PEWAEGAENBLbtbKLKinKqEh/d0tjSK0JoB62wRChNcIjbG4okumDIgVBhhMSBYBhLBh1u+2AnDsaq6s5tfSpxgDogl4Pm8YuSwItvvMtawkD1MuujUyQZ1NbVR/2JIeu+Q/5JL8Wo7DcXBJ66JphbyALDiimL5qct2Z5jrULcc7g2TUlXPxyDqO9kn6YqPNnOrliT1+VYU/E6YWs38MDfgzCMgfz2Marvi0WuO+S8Y/IuKoS5X0aAEWAEGIFMEWACL1MEuT0jwAgwAmMYARB3H/3sTTStvo62iv/+8Hkn0yXnLNdaEVwJQdrh8F1ZHhvzefDURUsVBn6HNUJl4hYGpwVWnlWCcQdy/uHA7RUGl2fT1pqOVAahMpxKvZRpXh2GTeAVtbxK5a9+1nHI3tmXUp/4+BVJwOJnV++AlWdNtwQ1sQgSQqs7J7WeSgbhXlPDSge3dVtVCypjVFCVdA4NUkxy39n7D0rgyX5AwEJtiAIToITIH7q3FPwNgKNrkOsyXzAoL4kJt9ng11a+rIPnwQgwAowAI7B3I8AE3t69v7w6RoARYAQ8ETjpwmvpzu9fZxF4ksy78fpP0GEHLfJFDgna97T3WrmCJleXpkJqfRvmeQWZdys2HEKFsEwToiTPl5cycsD+QVkIomRvIRPUUGeo07DGoHt3861/ozXrm4y3c9G8WKKWRwAAIABJREFUOvrCVe9Pa1cmiLuYIPD8Stey73sq8mQ4MFSFWJ/J3j0e30Y7C5Nh7ybF1IXWpG+1rpqnENdl685u6trQQUPto5W9hdPKCB/TkksCT+4d8oai7E3Eeeq+EyHq8ViRtsmF6f5FVR+KzypBQHJhBBgBRoARYATyHQEm8PJ9h3h+jAAjwAhEhEBbRxeBwHvh0dtSIzz8+LP0w7seoid//T3fURNCvbVLhNGiIGdQm8jD1avhuujbcQ4ryEO2Gi4LtVqRCK0CWTKWVXhOefykAYRfDrUcbon20Pa9A7GMHF3YuyBkyZp1jXTzD5/RHl9W/MKVx9Ci+RNT7XTJO9nAicSTyrt+QZDg2gQJpGPeoU4+iBPtKX1TqX7QnCgzBQ3qNCigcB2CdB1Y1UaFnUniTjxmXEvR4kojRV4uCDwZQouwZ5mfEQRl9bi4peztEPs5lgvWAmVhszDrwIsA9QUIVNomeSdzgUOleEbg2WFaVq/bTIvnzzRtxvUZAUaAEWAEGIGMEGACLyP4uDEjwAgwAmMHAZBzd9//JIG4u+qjH6QzTz7KIvBu+dY1aQcR/O7KS8+iM0852ndxDcLIAmSCJIfGap44mQvOLV8aDngIOR1LbpHq5jkRk/L7qMwCfC+ekCr4GYxId+Eg+dRMVXh29Z1X2Kzb8hMiJ163UOLJgmsTCqGuXpgFDKQ1U/Or6RDMJiReNsg7NWxW5vIDeSdVd5YLr/i/QcGcDwvXRsFmQuJlOwee170l1w4X2rFAdDldr15Os/a8hvn48iMoeQcsrv6PW6hd/C298brLLAW7vUDRjuL0XUiPPu6GEWAEGAFGYB9EgAm8fXDTecmMACOw7yFwzwMraNuORrrk3JPon6+toe/84JeW8u42obbDQQOHEFlA9P3p2ZUWsedXkIerRSgvUMYiiWfiwCqJIB3TAD/csvW9PET7GTmATKiuiFvTwn7m42HbCTOp3IKSySvXnZsDr84+6JJ4mYTO2ucBFd5gzTJLQahjVGFCUuqQeNnIe+dEbg219dPA6vZR21JUmPyVkxoPefGKllTpbKVVZ33VBdp11YpTO79CZQNLtdtKh2CYjkBV6FbGAtHlNHedlxp4rsAECAQ01Id2AlobzAgqImcf5pZJeUn8Lb1J/C09bNliukK89JImUPh7e89vn6DDDl5i/d11I/kyGZvbMgKMACPACOybCDCBt2/uO6+aEWAE9jEEDj/tCnrgjm+k1ABnX/YVelD8G2q8c8V/q4q7p597hR567BktAg8wWsn0O/sshcxYUnPJA6iTssnt8kC4WFV53CK58jk0TCUmTZRnXoqafLplpPJsQITsyZBSv/mBTKitjFvXqSlJ6UfiOZF3mE/lX471m5bj94m5H6XKAy+3SEmsT6dIklI37x+caVFejTVbP+sHS61w2WWJWp3hMqojyS176LaqvrMPgJSUhS5qPJOceEFUeKYGFqb3kd3NNZ+fLUHIfrsTr8wDmNFFlEFjvKwoF8rWsAoIu7sFYXfXcD7Z5ULF/oMbP0OL582g1eu30DU3/K9WWoqw5sP9MAKMACPACOy9CDCBt/fuLa+MEWAEGIEUAnCaXSTy9ZwlwmLvEWG0UNi9F6oBEUqLcrU4YFwlFARTRSjQTbfeS1eK3x9/1MHaCCL3UVNrz5gg8STR4adKc1u8bJ+v4cIyHNiE/FHXKsmVfCUp5fw6e4IpeiS5YmIAAXyQE2/NuqbkT2FuAdIOue4WzU/+tJcg4bPoo1AwVSCrOo/7qzFJrIZl5mu4d5VQFYIId1KyJl5MkopexUmNZ6rC21b+deqJve03lPV9aWI/mtb1Va26QcgtteN8V+PJXIw9ffrEsv3ZAlUpFLNw98620hf3Vd34UsIzPOyCl2FSgYe/t98aDq3F748QL9De+stdYQ/J/TECjAAjwAjsgwgwgbcPbjovmRFgBPY9BHCI+MWwSgDk3CXnLKeHn3iOfnjn7+h+ocTb3rCbbhP/jZw+l5x3shF5J9FUSTwcZOuqSkToWLCDXhQ7pKrS2kRy9R7h5Bm05KPS0CQc2G/dmYSc+vUd9Hu5vqCmFKOJknikbpnxjXdRifiYFKyNhEIQCqX2Y/9i0jStrhPJ2VzQR82F/al6NYPFVDOUDJvORlFdZt2cgXUIPMxVqvEGBAMkSaDYe82Ugzokngl5F9YzQYadQiFmop6Neg/DXB9ML0DiZnN9cv4xyQBHAJgMnYW5xSphcnHC0YdYKSpA7CGMFup2hNZWin/j76yO23sE0+QuGQFGgBFgBMYwAkzgjeHN46kzAowAI2CCAA4S14jE2willcUK9bGZWJj0aa8LZ1qprJEkXq8gytwO7JmMZdI2U1Wa01h7+/qc3DNNMA+zrtw/qHbCyqPlur7+56gg8fyo6Q/FjiQqPspoWbohtJZZg2ClBgVxhxBfu5GF0aDDleX6diZ66I2+1jTyTu1vzsA4mis+URbpVOoVru6W/85rXjGRG0/AZeXGMyXw0C/CafeU3D9KjQfirmxgP6rtPU8LFp31aXWkVAKJXiNCPRPigjAN+TYdy6++nIt0Cfarr/M91IbIQweDkiAu0TpjyDrZIO+kqztCZ0HM4d9Q4iHvLJTv8oUZ0lVMnTLRyp133dUfYhLPZCO5LiPACDACjAAxgccXASPACDACezECMKR4SHy+dNXF1ipB4N05nKdHEnr4twz9CQMKlcRDf9XikIbSIlRv2S5+DqVhzAfrg3JKxwU0jPHUPrKRWwohj3DKzEVIZpiqQjfsUyGdLetosPvXvls0FBcmCEUzfeuhgg6BJ0NmoWCVpXf2pdQnPpmWd4s6aVNxl6VYg6rPLWSxWqjx3pOoyXQ4x/Ym+eB0FXjqQEk1HlH88DrjkOMwFmyyviDjJQ1KiiNVi3rNK2rznqjXlw3yDvhJAg/mULLc8N2fWiq8QwWhB3d3Se7he6jxkMrixi99PMhlwW0YAUaAEWAE9lEEmMDbRzeel80IMAJ7NwIg5/D2X7rjTRO57VDgOnu3yIG3RIT4oMg8PWGj4UbitXb1ZyXvEQ5tcBiEMiYbueqiPsQ77Y8cMxvrk4d407xxmVxXUagm3eZTGttGA12/8iS51La6JJ5fGC2UTVDcQXmnlkzCZ2U/CJldWdxi/dOu8HPCIWwST+ZL608Mku59H4TAw1riM8upbvF4y+0VKrFs5FbLZr7BbBD1Xs+YqJ23sb4q8SIkJn62ihc9YZl4FEPFKIxrogybVXFD/lgUONIiHQVIuwd++k3LFAr/Vt3ekYsWBhdM4GXyV4LbMgKMACOw7yHABN6+t+e8YkaAEdjLEcAh4qVXV1suspK4U5cMcg/F6bswobGTeNL1tamtN9IDtkr8IFl6Ng7zwC1qpYrcm2yoCp2ug2SC/bhFkMAgI6qSDdWdfe4F3Tdbv3Ij1JzWOlT2BS0InFR4UnXnpIoLS333p/iuUfMDtgQ1nqL2Uysd0l8dSl48acZgGvI8uK2b8DEtRYsrqXB8MWUrt1pY+eBM1xm1Wk2dj1TeRv28VscM08SjNF5kqb9xr2WzQPWOl2QoUN+BzLO7wEv39xuv/wSH0GZzc3gsRoARYAT2AgSYwNsLNpGXwAgwAoyAigDIOyjv8qFAWbRbEHb9w4SBJPGiCMdUVRxR9K+DpyS5onJwzabqzmm9URMX2VTdpdZny3nnFNLqSOBp5sSzu9GqRhX2fsPIfYc+ETq7QXycihVyKv7PiTwMQ4WXqRrVVIVXOK2M8JElTBLICb9cG7xErcaTyslc5S6VJh4VQkGNlwVBcl6Wl8TEy4Zk6oZcF7wwu1So4Vf8+nupqdz284fpxVdW0V0ifQUXRoARYAQYAUbABAEm8EzQ4rqMACPACDACxgg4kXggasIMy8o1saWCEsUBX5ISfcIQBCGzIF9yVXDAHi/y4oWZ90/2GRe59sK8LnQwkuo7ta4XySXrDRXOICq5UGcIAok3bsvPrZ/SqMLeUFXeNQxtJXxkmVwwnfDRLS/HmqlFcZx1auemNjyhb5LuMGn1JLEEdV8m16iJmUVBZYyKllSNmq8Mbw3b6TQXoeRumyGdhmEM0iGeCWGUqAl6kzkGJSorxbMJfw/yqSCUVuaeRdjs1Tf8r5UPb/E88QzhwggwAowAI8AIGCDABJ4BWFyVEWAEGAFGIBgCIC3auhKEwyZKpiodOQup2MoHYktFJqyDsBpOCqfGsHJDBdvF9FZh7aEkJxGWC+In28WJwMMcEHgHktIpR52co04YbRqZtPlFoj2vUMnGu6wuoLgbEB9pWAHS7qmB+x0hmCQIvAMLD9ci8pzCZ506TYXyCtJNUsJBCDxJWoe1hyDxEEo71O5+PdiVd07rk9dWl7i2MiW5cmnm4nZP4NpCWHsYueOiePEQxr0M0hSh0UiHgJBsr5QI+UjeAQOQdjd85ycWHMiFdwuTd2FcGtwHI8AIMAL7JAJM4O2T286LZgQYAUYgNwiAhJIkniTfgiiucpEnzRQxHK5rRQL1/gTIS3MH3pyEkxouUqqAgoQMq8RWkGvAcKqu1d0IPNnAK2+cH4EniVyYK/hdAysEcbdLUd25TRhE3vKicz2Xr0vgoRO7wYUpgSeJ3CgMTkDkgcSTefGguCuoEnnNlJBZv+tANZto7ugj1e1XbbuzZyU19LyS+tXk0oOpvvQQynVIqd/68H2mYcNQKoIk88JHZx5R1dFRVOYreadignDaqHPPRrUH3C8jwAgwAoxAfiDABF5+7APPghFgBBiBfQaBNuEyCDUFCggg5DoyOTgmCYOYUGMEy4+UbaCRSN0k3HQskJMqhkHUVyqxlS3XULd99yPw0C4VUqso1fB7LwLPJKz79cEX6A3x0S0HCCUe1HhuxYTAk31YuflEOa5nopbxi7xO0Q7EfC7DunVwA0lVVR4f9dwAcbei4WrHLkDiHTv9UzQhtiwn6lCddck6OiSXU39hKWlN5hq0LojK8eJ5OihkeOo1BxViufhbwoURYAQYAUaAEdjbEWACb2/fYV4fI8AIMAJ5iABCJduHVWlJAqiE9rT3uqpjsARJFOVbuKwOvLqH5LGgunNar5r/rFXsq2eYm0XAFlkH8HwICdYh8LBmu1LNLQeeNFNBG5DVfsSWV9is17V1olDhueXF8zKx8OoTROUFZTN89yasEHGdeyfMOlIViz5x/T22/Upq6B1R3aljqXkQJ8UPppPqbw1zKpH1ZaLGi9JUKLIFio6lG2+3SMlQLEg9OM5yYQQYAUaAEWAE9gUEmMDbF3aZ18gIMAKMQB4i4ETiQY2FPFpqURVpaGP/Pg+X5jglmQDfKVw0aML2fFu7V56wfFLdpeFmc6H1wzTlIhu/gIYK0pPQByFgTdV3cn5eKrzmgj5aWdzit5RR3x/SX00TC0us0G817LdhYD01DK636mMfxwkSdnxiNtUMzjEeIx8a4F58s+1Oen7nj60ch/bi5ER84PiP0UHVH8+H6fvOwU+NJ3PnDYnF+xHuvoPlqAKIyrrxJTkanYdlBBgBRoARYARygwATeLnBnUdlBBgBRoAREAioJJ4keFSSLgghks/AJtUxcaH+6fv/7b1rkF3Vmaa5lJnnZCrvgGxuZWiX6UBElQGBRbsHmJiBEuCyYyQHeMI2JUp0qSJmBAImwtOWS7R/eKxAzPgHIEx0t3EhW20XE4awNFNlLirojgJF11hlBLiqEWGIMhBcLYGUqUzlXbPefbSSnUfnsu9n73OeZWcgZe691vqetc9RnDe/73sXs8/ClFrmOTa3t1pOnXmPMWgWnouxVD7fjJ6xfoljrsRLlWmG7ef3k7n7Ih/rzT131b03iBOt/+bRhZK5fO4071tOAPrgxOvmscM7Fi/Ta1Q/c33kzuz6fXNx6TpzZvdnIsfQihtd2awrG5ZzrhuLAm0NZW/NmTu8vnhFGa7kdM7GovccZcYWNXvSz9zF0NPdVZSjYJ8QgAAEIACBRAgg4CWCkUkgAAEIQCAqgVoinlwj1dNo1n6wDlKGGHXtVtznSoFdjEUsCW7GzQkHx2cq55j7GOffNMtm/u9mYXk/d6WzrqeaTFkUozLWmvXz2/fB8cU1PjXQY86z/bzSEvC0UFARzy/euQ0q6+6ZmX9vlI2mnmNdVrmr58i7pvd/SVzEe/fXU+bAo0fMe/84teRczvrDPnO2/Vr1tdFA51XropeO/NC8fPQvvR+5UtlmMeraImXh+eMetBmT/bZvqHtWk3ILjnwAMW5EvIsBj1shAAEIQKDwBBDwCn+EBAABCECg+AQkZilDxJXL9ltji+nZeS+bqR2HsrX0oboTYpydWzC/Ozqd/2MMIOJ54l3Pf2fTmM7z4lFmodwvFeOhsemavf/etH3wJNy9NVkxbqkeI7+/0wyWomUSNcrAc+s064dXT7zbO/3vvSkk4Ol1ecKKePUcXHXdn/T/X4md8S+2vneKcFc9uYS8P952VqQ1d71x5ZL7JOJ122yuZjHqpvXn74u0ZqtvUjbzaTb7d25+IXSWaKv37tZHvMvLSbAPCEAAAhBoFQEEvFaRZ10IQAACEFhCYMpmayk7TZlM+rPcBvVfZei1y3AN5pWRJidexTg7Z7MMTxp6tEOc7kO2i1Euw2FceFvOwPbEMwtvmWX2y41q4c7vwHrUCnTKbuq1ItyH4zNLTCsk3j362/GGIXWf95embBWk0yO4aAYR8NziEvKqx+/PD9Tc23+a/N+97/t7wbk/y5SjlkmJymnX9P2vsY8viHjnFokq4vkFvCUxWiFPf68Xo9YtooDn77+pzNGBvlJhXLzdWZfsvw1nDPd658OAAAQgAAEIdCoBBLxOPXnihgAEIJBDAsrwOXR0yivVU6+tFfYDWzuIeH4jjmr31VEr4hVK4Grw3NTrdRfUhTeHj+QpW6qUzpY8MxW/uOycMccmZzwROoh454lkn/yFWdb3XmgR75PLfs+ssU60SY+XZ582L8/u9cT06pLZaife6rXjZuEd+KsjXtlsmLHqq6Ohy2mdgKfXpYbfKVjf0euxXrlw0QS8Wq+9opnmSCAfHSyFeSwWr93z5PPmc5euNOeetSLS/dwEAQhAAAIQyBMBBLw8nQZ7gQAEIAABr0zPL+LJEVNN5o/YbKYijiBGHEUXuJwgoHOSqOUXRNyZVTiUbLZhReAq4mh2Tn6n3bv3vx8sxN53TfeZT3jXDlqTk6DltH9kxbszrYiX9PhvC39rBbynG2ah1TJ/0D7i9sL7y7W/jRTOv9nzL0LdJwGvlkDpn6RexmGRBDwJzaWeZV5maK2sSSc6qzfesZxmOiuDd9j+kiPq2P/Sq2b7jp+YdV+42qy/cU3UabgPAhCAAAQgkAsCCHi5OAY2AQEIQAACfgLVfZqUpaZRJBHPn3UXxJm0lntrEZ4KJwLIwEFZaY1GUR0w/cJcM6MKZant/3Da/N37E1aMDnaCYbPw0sq+k0D56/m95vkjv2i6cWf+4C83vbi0xnOljTKiZN+5dcJk4SmDcu/7m82b4//gZdk1GosZh/a6BXvxmb2rzHVnPRglvEzv0fOqX3xM21L9ZuX5ilHO2D32HpWDz9h+jnkZ6i+pZzLuGDs2aR7audvsf/Gg2bL5ZrP6kgu9Kd9+75C59a7tRo/Byn95vrltwzqz8jO2zyUDAhCAAAQgkFMCCHg5PRi2BQEIQKDIBPRh6ee2dEnjlq9cHynzoZaIV5RS0yBZd7XOt9Ijr+wZeuTpg3StvUYtw5Ng4LIqj9ref7Uyg/L07EugVAmfehY2EyjdvmVa8V8PHbfmD8ZIDwkSoxPxzmoiWKQh3vkFyn1jvzAvzTy95AjKL69e8vf5M98282e+Y6rLTfMu4LkMyv/2wd+bJ969PfBj5rLxbjj7++a07ksC39eKC6OK5K4/ZxA35SziSkq88+/14Otvedl4W27/uhka7Dc3bvy2+Zb989obrvLEvDvufsA8ct8WM2x/xoAABCAAAQjkkQACXh5PhT1BAAIQKDCBh360x4yNT3gfklyGwzr7AWmTzW4IO6pFPH0A7yt313X8DDt/0tdHFbX8+1BpnwSuCSsYTUwFTOFKOpAm80mgVGmbSu+i7lHlfbWMHzIOpe5yfqMK9S2sVRZc7+b/858+9H4kgaunWz3WbAZXk2wv7/qRA2b4jJfqltF+tuvz5mL7leRwPf3c8+Z64HW/f44pv3yF6Xn/3JrLzVkRb+biX3pCnhO4ZGJxxolPR9pemhl4Eo1Vvu1/3p5+73bz/vSBwHs9q2+VufnCH3jl382yMANPmvCFcd87HCc9E9W9OhPeasPpZO4zYN9f0hwbbObduM3Mu/aqy8w1V1/uZd7d+/2/Mmuvv9KsvKDiMs2AAAQgAAEI5I0AAl7eToT9QAACECg4AZUkSaxbbRuHa0jEu+6r3zBPP/q9SI3E64l41Y6frcZWz8Ahyr6iZtFEWSvMPWHLgpvNndeyYZeNVG1U0Swe93Mn4Lm/S8RTnV6Q6sQrP7HcDK146ZSlkhbutECtnn7vz79unn3z/zH9e78cKNzJNT+vZONZkex/O3tHZHfTtAS8Rq+loCKeK531C4Ef2SxZ9evMy3CiehL7amU2njKQ+yM4Moc5B/XF23rPD8y2LRs9tyRl5d1265fNNVeuWvw3694Hf2qGhgbM+puuo6w2DFyuhQAEIACBVAkg4KWKl8khAAEItD8Bufz90n4gusL2FVIp0tbtD5srrHinP7uhkloJed4HpghDIt5HthH77MkPzM3MBCIsEfkWJxDM2H5T9QwcokzuLzXNQ++/qGXBzWKPmzXUbP6wP0/i2VIJ7b7fHV+ytMpp1TdOffEayT7/9g9OD7vl0Ne7HmmzVlGsLmM+8u4Js+//fc/MmenA80rE+4Pf+wOzqvf6RbfQesYJ9SZ999dT5om73wu8pv/CL3z3LHP2Z/tOuTfIs/XSkR+al4/+Zd11Lx75N+aS0T9b8nMJXMqSVVl1HswfknhmqwFknY2n18aKkT7PXCTtsfXeH3qinMQ5jWf3HTC7fvaUVz4rcW/z1vu90loJeBL3tn3rzxf75qW9N+aHAAQgAAEINCKAgMfzAQEIQAACkQmoDEnlRlesusicc9YK70ORGoVLxNOHoXPt9zRcFt4//ZedkddSE/nDY9OLIp7L3gpiEBF50SY3Jpl1V28pGXi0svdf0ll3teIM03Q/rbP0C7Fxe/PVEvC0b4kiMgtQOW69ktq0Bbxm2YUv/828OfTOlBk/8bvAqJedecj8T2s/t3i9e22GLcP8xdb3zHv/OBV4XXdhLRfasNmdEvKqR7Vw5/+5M3+Q8BS2xDp0gA1ucG0F0spI1vOiktY5+8CqN2eQfo5h43OvvR6p3BkM9bqTK63LuFPbB/0b9c3bvuZli+/YdueiYKd/z3Y99rR54Lt3ZLAzloAABCAAAQg0JoCAxxMCAQhAAAKRCBx87U1PqHv84e949+vvagwu0U7f1/Bn3K2xH4x2+kS9KItKxFOJmNwVNVxWWNYinhNBks66q8ckjQybIPzTyrqrtbYEkRHbFy+KWPnCr944ZcrLLj8/SIjeNVGMKppNXl1G679eJbUSQtQbzz9UPnvlJ5c3mzryz4M8R889POfNP3tiOpCI12N6zXDXJ8zVG5f2LPOXYTZzQnUBRcnCq5V9p/6K6uOWxfuCc2GemJqN3A8yyoE6AfGEfU+MKzgHWX/Q9h9V30v1/4va97LWOlmLd9qDssZ/bEU5/fv0qv136x5bLrvz/m+ZZ59/wbzymzfMDp9YJ/FO5hfbvrk0CzMIM66BAAQgAAEIJE0AAS9poswHAQhAoEMISLBTn6D77Ycd/fcdm8Hwiv3eLbYsSeWz6oV3jW0Qrn54e57aZ5557leegJfEUMaLDBQ0KiJTyXw4Pp16Typ/NtrYxKyZOikkJhFTsznCZhQ1m6/Rz7PIuqu3fhCRyd37N3/9snnv3aN1Q/njL37WnH3OaN2fuzhLNsso6Qymell4bjOupHb2pE/Jp/p7zNc+PRzn2BrGOWyzqDT03NYz5HjjhQXzpv1yQyLe8RNjdctply8bNvrSOO+yLnO+/fIPJ8qG4RumF95Zf9hn/njbWYtLtiqTMwnzmjAH36oemUnH2QrxznFWqazKZmVkscn2v1ttW0B8/kubvF9IucxxXSunWn9/vDDnxLUQgAAEIACBpAkg4CVNlPkgAAEIdBABlRtJpFMJrcqRnOvsbVa0+5ztg6dMPH1PPfEk5Pk/GMXF5BfxKr2uelMV8fzZaOp9lUYpWTMmlaymslfKNhPEEaHZhDV+nmXWXb3tVZxRy2ZscsZz/awe775zxPzib34dKLqzzh4xX/zSxadc26yUNNDkTS76q38eM29NVoTmWkPllxIxJKj9z+cPmfNOimxJrO3mcH3gghhyVAt4/n1IyPMPJ9y579US8NzPwmapBcnEW/XVUbPqax+Ls60StfxMwsYZ5ZzbJc6Sfc8+zfYRzKpsthlr/TullhB7rdmSGyqt1S+eXJZ5szn4OQQgAAEIQCBtAgh4aRNmfghAAAJtTEClSH9hRbr/+tcPmWFbPqshw4oxm9WwxTYBT3vINGJ8ctZbRkLFaVbckrgmsSKp0cpstFoxBGnMHyV2f9P6LEoPm+2xkVDRLPOueu7qTDyX5aesu7SdRN+0GW+P/na8brjnDfSYOy79hCdUBi01bcbO/dzFGaQX3Qcvd5sPfjtn3jlYEUx7lp8wXbYqtruSuNd0NBLwdHMj44x6kysb713bE8/1xVPG3dn2yy/c6V5XAn3Usk5L2G4K4OQFSWep+dd1An49YTvoHpO4Lk6cvaUu7726Swp2Tob+zVLWuHrd6RdNKpuVmYX64am3KwMCEIAABCCQBwIIeHk4BfYAAQhAoGAE5Np30PYKUladsvDW2ZJZ/VlDWXcytnAOf2mH5hfxnOhen9eAAAAgAElEQVSj7yUh4uUhG60Wv6SzcLLIRovyHPideF2fL/W7O/DCm6Gn+7M/v9oTkc4YLpusehf6N6mS2urxKSveKevOiacSNpIo5XWis/oJNjNYmHh/mfnnv62odONjs2Z8/NSMwfLQiaZCXjMBz8Xu+tMlJZ6GKbkO/dDEuMFl4yUltuXBtKcWDhenWhoEceTt7+1ZdCqOgTeVW51o93tWwPNc03GfTYUzk0IAAhCAQHQCCHjR2XEnBCAAgY4joA81yrBT36Bv2gw7ZSq4slm50CqfQv/Vz1xGXhaQaol4QUoG6+3NZZd0WWUlCUElDQZ+ceuIzTyKOsJkaUVdI+59En2cuPUf/8PfRZru8//q0+Z//O8v8JrwJyHuRtpEk5ucGBKnRDqMuOsX77S1aZu5evjQTM1dNhPxPvvFbjN6drCMKicYT9hs2aiGCIrT9fVLyx017hm7rMO4Dq55FSkdH2eoIYdlmQzVy2odsq9jxZLnoUw8/fuWZLuHPMfL3iAAAQhAoFgEEPCKdV7sFgIQgEDLCOx6fK951vYDUradTCqqh0wtNJR914qRlIjnPizHEReyjF/iVqmnIjSG6cvnhB6VbkrUCnNvlvG5tVwG0vbv/W3ovSrW8887zfzR9X9Y18ChFTHVWjNMz7rq+x0jleLW6h3ov75avHM/O/S7aTNTo++gfl5PxBuxwt3FVsALM5wArXuaZQlWzxtGpAyzp7SulYNrvzXbCVLKXL2HqK/vtGJpNK96V44OlK3B0Pwp7ylFEO9awYw1IQABCEAAAmEIIOCFocW1EIAABDqUgMS53bbfncpi85yZoA+OysbRcNkvUzP6MFnfSMAdaSvLK+M+VmEzdNz1SZUax91/0PsPfTBm1P9uwZo+2P83HcoHUxmprtU9KqMtwvCLW0GE2Sj9C/95b4+Z+GCpa6zYNMrC6+o5YXprGOWGyb6r5h+21LSZwUlez9cJs0EF81Y56sbl538WnWCJeBeXKvdDAAIQgAAEKgQQ8HgSIAABCECgrQj4RTx9mFwx3GuzkRqLeEUVtPwH57KvGvUWK7JIqVid+6zEECfK1Xt41SBfPfLl8OqyC4si4LmYwpxpmJLxetl3bt1GIt7y05cqp3HEO7deUHErrFCdtze2WuJWrT0WLcOwVgyuTFpPS6n7VKE4b2fDfiAAAQhAAAJFIICAV4RTYo8QgAAEIBCKgJwoPxyb9kQe15/phP1Lda849yGzFaYGoQIKeHEjl8p2ECmF4Yc/eM6jIZFDTRfn509NxZMgJNFO4p0bZ509Yr74pYsDkszPZY36xbnstbB9/TzH2V83LnmViDc+NndKOa3caUvLjVHZrIwrgva9a0a0URahew1rjjHb79F/rs3mzePP3ZnWysZLy2U6aw56eY5ap9m+crjS6qz3yXoQgAAEIACBIhFAwCvSabFXCEAAAhAITECN1A8dnVostRy1bp8acjOVOYUErbJ1/ZQgMDW7EHjevF/osndcD7+iZ91V83YCnr7vsuxc03wJPYq3VontqsvOM5ddfn7ej6/m/pypisRK58br3FwPj82EFrSCCHhuIxLyZqY/fn0Mnbtgfm+1FWcCGlaEBe5KZCemZj2Di3bIRqvFoFY2nnO9TsqhNyz7pK6vnFmvkRjJgAAEIAABCEAgOQIIeMmxZCYIQAACEMgZAQk7h20mnsvYcW6m+vCsksNj1gUz7+YNUZA60UNx689F63XXKOYXfvWGOfBCxTBFw4l2Okf9uZ4DZtHKZ2sxcKKdfqbsLZlVRBlhBLzq+T/52XnzyYvnoywb+B4nWCqBsmRFoKIYygQO0Hehy8Zzr9UogmyUddO6x7339FA2mxZi5oUABCAAgQ4mgIDXwYdP6BCAAAQ6gcDc/IIV8SrGFsq6U0mXPiwfssJeO4p3itN9iFZ8czbWj6xDbTsNGVm89+7RxZBcpk+9vnh//MXPmrPPGS08gkqGVsnr7aeyWWWoRRl5F/Dca1XxakRxb43CpVX3SJiVS63elz6yJjz1ROhW7S/ouoh3QUlxHQQgAAEIQCAaAQS8aNy4CwIQgAAECkRAIt4y+7/J6TkvG63ozfAboVdftP7eHi+7UFmGLuuw3QRLiXgfvD+2xKhCjrOmqvddu4h3/mdW53/6UNlM29JvCXlRhOh//Ek50iv4D29OXwx2z6xKSV02XpyMw0iBZnCTvz+nSqN7bUn/cH/ZCrPRxdkMtl1zCcS7VpFnXQhAAAIQ6CQCCHiddNrECgEIQKCDCbhMPFdO224inhM6dMTKWPI3+m/HWCVg/ee/e838f7/87ZKn2vXF+8Qnh4363hU9807nqlhnrTGL63+ngF0PNYk+ErrCGjv8894eM/FBOHfQtMtnnQhULdYp1hGbpVbqiRZrHt/26vX2a/Q6zmMc2pPKnNXzTq+9KGP3U/vMNVeuMsOD/VFu5x4IQAACEIBAxxBAwOuYoyZQCEAAAhCQiKdy0tmTzqUVF88er8Q2rACSJ5rOjbRR5o6LtegN8l2jf39fNPXF849P/4vTzUUXfMITtuRIXNRRMXQoNewB585+bHLG64sXZoTJwhv45IL59Jq5MNOHujaI+2qQ5zzUoi26OIgxR1FiVbbvcH9PZPFOR/DQj/aYZ577ldmy+Waz+pILW3QqLAsBCEAAAhDIPwEEvPyfETuEAAQgAIEECcihVMYWTsQrsvOjhABl16l0tDrrrhaySsP8sjU/CC/2JHgEkabyu3YGEVyDCEKRNpLRTWGyJl2sYctMJ95fZtQPr1kmXtriXRhx2WUkxikfzugIay7jXHaDvAbzno03aH/5MXzS3Tsu07ffO2S2bn/YrLzgPLNpwzqy8eIC5X4IQAACEGhLAgh4bXmsBAUBCECgfQnog96ux542w0MD5k9uXBPpg55EPDWLlwig4YStD8enC9NA3gmP6nOnvn5Bh8v+KZKzZ5CMpVrx+8WeqI6tQbkmdZ0TbeZtlqjONWhmqOunpirGIGKuf7+NTC3SLpt1zrpBRFn/nt19RcoojZrxm8dsvCGbGSqROemx6/G9ZvcTz5lH7tuy5L19z5PPm932a9C+7+/4PzYnvSzzQQACEIAABApBAAGvEMfEJiEAAQhAQAT0Ie77O3ebTbd+2Rz8zRvm2edf8D7onXvWikiAJHTI2EKjksXUa8WPfJdduqy7su19Flb0cJCiCmKRIMe8yWWiSYALWyKqpV3/tKBZijG3G+v2ipBc8sxHwoiy/kWdSBTFuVUZeRPvV/riDZy5YL+sI0hKI4lMOserCGJ0mIzKWsidsCunZb1HRTEuSeoo0xLv3P7Gjk164p1+WfOQfb9/x/73QpuZ94x9v7/lK9eb9fYXNwwIQAACEIBAJxJAwOvEUydmCEAAAgUlsOar3zA7fYKdPtzpQ93jD38nckSninhlTzyRiJK3ETXrrlYcErZkjqBMryMTs3kLddF9VILFmN1f0Ey0eoE4ASWvGVtJ7i/vwlaSArJ7jnXuYTMPs3roR22ZqQRkPXtxhTcJtEPLS/Y125oy+BEbi/qGpjkk4N159wNG/73lpuvM2huuMsrMU588vf9rSNx79fW3zDlnnuGV3TIgAAEIQAACnUAAAa8TTpkYIQABCBSYgD6ouQy7Gzd+22zbsnHxA5s+4N1kv3eb7ZmkD3lRhwS7cZvhpeHEhTyJeElk3dVjo1JEOZkesn0B44oLUflX35ekUOmf25VKjx+fzY1Aq7N1fcSSECpdvHnK2PKfgQQoGR/oDKJkVNZ7xuKYeST13FbPk1YJt7KFT7O9LLPuA6j+mf293WnhWpy3uh/euH2f13v/jm13eiYXB61wd8fW+71/B/RvwBWXrvT65jEgAAEIQAAC7U4AAa/dT5j4IAABCBSYwNZ7f2j2H3jFPGYz7FRSpSbnGhLx3FBZ7Y9tT7w4WXiaq5aIF6eUMSnsaYlZ/v3FLe9LKtawRhVR1k0y+yvK+v57sthLkpl9ceNN+znzm3lIIGylIJ322fpfK1HKpcOcpfoqrhjp89oMZDlcPzytudqKdFtu/7qXeecX8/SzO2y23nqbqadrGBCAAAQgAIF2JoCA186nS2wQgAAECk5AAp563VV/eJNY5+979wf/wwbzT/9lZ+xo8yTipZl1VwtUGCfQ2KBrTOAEj7BOqlH24souW9lPzIlZaYsv4uMyDyemZs3EVPal4f4sw7T7t2UhAjd75rJ0QHbl0nrdpCFaVl6XvZmLd46xfkFzz4M/NddedZn3i5sNd203V6y6yGz607WLx6B/J/RvxLrrr2x2NPwcAhCAAAQgUGgCCHiFPj42DwEIQKC9CbjMCmXebfvWn3vlU8rK2PWzpxbNK5SRoeviZuA5kn4RT2LACvvhdWomuqlAlBNKwswg+rplMzaZbX8tJ2ZlXbYc1QE1Clt3jzPVKFnDCvVEi9vbL+hekjCNCLqW/7q0M9Hq7amv3GWG+8tWsMxWtGyFEJ5WNp47u57uirFJ1kPlsdfZvqcqnR0aWG7GJ46brff8YDEjW/tx11T/UifrvbIeBCAAAQhAIAsCCHhZUGYNCEAAAhCIROBWm23xXZt18Q8vHvTcZ+U4q/HsvgPm+4/83Ot9pP5I39x8s1n5mU9FWqPWTXK1PHrS2MGJeOo3JSfUNEdaH8TD7Nl9aM/C2dP1adP+WmVA4HqnZeE+3Coxy3/+WYqWTkRrVc/BrPsApl0i3Ox1nGQ2XqvFOxfrwdfeXOx5ut1m4mmolNYNfU/XOHOLZoz4OQQgAAEIQKDIBBDwinx67B0CEIBAmxNwAp7KZeVAK7HOZVoo8+JV+8Etrb5Hk9aFVqKOhsua8oSmlBxbO6l/lzhm0dsv6Msji5JHl5klEThJ84agMfqvq7AveSWXabktt1rM8sebRbmyM4PJMquy1tn7fwkQ1XG5JJMM61Ddqsy7es+0XMf1ZuzKZ/e/9KrZbM0syL6L8i7APRCAAAQgUEQCCHhFPDX2DAEIQKDNCUick2mFRDtlVkjIk1D3zPMvZPphTaWzEvHUK01jdKDk/feoFWGSbJCfhcAQ9pFxfeLm508kHm+WWWBB407LMTQPPdlqMUir56ATu7utCNSqrMpa8fqz05LMpFW8cmc9Yd8k0hL3gz7D/uuU/Tg6UDbHbDbxMeuyHXTIkVoOt11yrsjZcO0Srr36cjM2PmGetf8ePGDLa5PMvs5ZyGwHAhCAAAQgsIQAAh4PBAQgAAEI5IaAPqApy2J4aMB887aveW6DyrpT6ayy8PY8tc/b69oMm5XPWQHr0NGpRRHPZdocGpuOLeI5EWXGlueq/1tW/dDCHHga8abVcD9MXLWudWKbRIwkMqnSEsnixunuT7ofXx5KhBuxcWJbjxWnkjzfPLhV13ueJS4Gjbe/t8eKkZVfUuR16Jc7MrbQvwtrb7hqiZlRXvfMviAAAQhAAAJJEUDAS4ok80AAAhCAQCwC+lC2236tsx/K9MFMQ4Ke32021gIxbpaId9gKdk5gU8ZcX7k7lgjQKuOGKBiSKIcsUrxJGBFkUaYa5Sxr3aN4VVIrUWtmbiHStC7DLYveiZE26LvJ9T2MY3CRd7HSzyhIvEP9JfsM9MRFy/0QgAAEIAABCKRIAAEvRbhMDQEIQAACzQm4rDtduWnDulwIdrV2PTe/YEW8j11Do4paRci6qxW/61kXtq+W4h22pceqyMtTSWWzJ7MiSJUj9YnLY4lws3hdH8Ao2WRRXwvN9pTmz+O48jpzjqzdmuPwaGQYg3gXhyz3QgACEIAABLIjgICXHWtWggAEIACBGgQk4Mll1mXd5RlSXBGvSFlotc4hrKiVJ6OKKM9V2Cwrf8msDCKS7JMYZf9h73F9D3WfhNog+8+LeUPYWN31TmwNKkwXUaz0s6nOxkO8i/rkcB8EIAABCEAgewIIeNkzZ0UIQAACECgwgWoRz4lU/uy86vCKmnVX65hcLM1KJYsudLjYnaglIxMZmtQTtdxz0IxLER59d3aNRK289/cLw1nC9OnWdVWi68TUfN1b2+WZdtl4XV1dRo6zDAhAAAIQgAAEikEAAa8Y58QuIQABCEAgRwTqiXi1BI+iZ93VE/EkeMilV+Yb/lH0LLR6j1kj8aZdhB1/7I162sUpt83Ry/iU59YZOFSXejuzj2W2DryRiJvX2Kr3pXJ2lYerjycDAhCAAAQgAIHiEEDAK85ZsVMIQAACEMgRgQWbkiVji1lrcKHhyks/HJ82Mr1wPbZmrSlAXh1m4+B0mWnzNtajk5VyUWf+oHjVS63dhjOmkIgjswf/GTsG7RSzy9SqdcZBS06LxsMZehyZmLEC9cdnPG2dosfsc170IfFuxUifkQjLgAAEIAABCECgWAQQ8Ip1XuwWAhCAAARyRKBaxKtkJvVacWfeCnrdthyvcUlejkKJvBXXA01CZcmWIkrYcW69kSfN8Y0u+0zijswMopg+5Di8mltzfeJczI3KxYsWW639tusZu+zYnu6udjgmYoAABCAAAQh0HAEEvI47cgKGAAQgAIEkCUjEG5ucM5PTc15GlsrwekvdXrbOsary0iTXzctcErFGB8redn53dLqtxTvHXILW4PIeMzk1t5h9mJfzSGMfTvjpsmmX6vFXXTadxpqtnlMZtStGeo1e3+3wXCPetfqJYn0IQAACEIBAfAIIePEZMgMEIAABCEDAEzZ6S5WMrEn7dcZw2fteo6b4Rcfm7/1WtrHr7+1aWqmzcgKtDC3GJmZtyXCPd+btnHXod+LVc63ehyonLaLLbtDXmysF17kqq3RoeanQ2bSId0FPnusgAAEIQAAC+SaAgJfv82F3EIAABCBQIAIS7I5aYceJPRLx2rHE0u+q6+/95voAStxptx549Ywb/GKPeh+206jEVrLZpJV+cBrqfShBq12Fy1qGJH7htmgmFnKZPWO413Sp+R0DAhCAAAQgAIFCE0DAK/TxsXkIQAACEMgbAZUXjp9sdu/PXmqXskMn6tQT6VzM7ZR96ESdetmF7ShcNnPWrSXu5e21GHY/rp9jvYxK1wtQLrUyMcn76O/tMcP9PbHEu4d+tMeMjU+YTRvWmeHB/ryHzP4gAAEIQAACbU0AAa+tj5fgIAABCECgFQT8Ip4yllbYDJipmflC9w6TMCdRR6WyzUwMnDtrO8Q8PFAySl6SaNPInKNdxFrFoZg1mmWb+c0eiuzQ6hyVZ+fUz7Kx02xFrC15GYnNrm3Fe49bc9CWd7tzjLuPXY/vNbufeM5s2XyzWX3JhUumO/jam+ad9w+bz9nvI/DFJc39EIAABCAAgcYEEPB4QiAAAQhAAAIpEKgl4smp9cjJEtsUlkxtSidahCkHdqLIvC0r9ZfZprbJhCeOIsgp5tHBsif4KYvrRMEqauPG3EzkTPiIEpkuTsw99qDz2P9wyJqsSGxPcrz93iGzdfvDZuUF5y1m40m8u+PuB7zvvWL/vGPbnWblZz6V5LLMBQEIQAACEICAjwACHo8DBCAAAQhAwEdAH1Qf2rnbjB+bNOu/cv0pGSdhYPl74um+UZfZVCARr1n5aDMezcoSm93fip+7mJVh5Xq/hdlHs/LTMHNlda3chIf7y545RZT+ha4XYFHKS8U1brm3KyOemJrNjVlNGuKd/xlUNp4Eu+pMPL1v3nrXdvPYw98hEy+rFy3rQAACEIBAxxFAwOu4IydgCEAAAhCoR+Dg62+Zrff8wGy5/etet379ed0NV3kZJ1GHnDtViuiGRLxu21g+7xlafqMKZRM2Kh9txqYogpYy6EZs9pKcR+NmVi3v7fbMHnT2ee+XltT5uEzNIvQ/dIKl36Cj2XNc6+euXDwPzrxpi3eN+IzZX3hc99VvmMetgHfuWSuioOQeCEAAAhCAAASaEEDA4xGBAAQgAAEInCSw9d4fmtWXrjTrrr/S+46ySvSh9OlHvxfrQ6lEvLGJGbNwsqRSgklfudscGpvOZZllGplFFUGrxxPG8ujWGqWUstkLp55zbbP7svq5EywlKCdV/loEx9akBEt3Ts6ZV6Jgq55vlW7329dY1kPvke/Yrx8/9rSXtbzzvi3e++aeJ583Q9b0Yq39BQi98bI+FdaDAAQgAIF2JYCA164nS1wQgAAEIBCIgDJH3AfM7Q/+1LvHy8A7OVROu9t+GJWIF2dItDp0dGqJiCdRq5khRJw1w94bxqgi7Ny6Pq9urRIs5dh5bGouUvloIxYuQ0v9D/PUCzANwdLPwTm2tkrQqncmSYt3/nX0fJ8+VClDnpiaj/ISCX2P+i2uGOkzEouzGK7FwC9fPOi9b+rrQltSe5H9kli356l95sFHfm6uveoyMzw0YJ557lfmge/eEesXIFnExRoQgAAEIACBIhBAwCvCKbFHCEAAAhBInID7IPrM8y94c6v0S0N9nB6xWST+MjBl4W3bstHLzosz8iziRTGqiMIibeEozJ78mVNpC6l56gWYVamrK1PNQ484l224zCpezdx1wzxD1de6DER9P6msxnr7qbyWejMT77SPzf9uh3n1N2/U7HWn99QbN37b7Lz/W4tmFg/9aI8ZGlhu1t90XRys3AsBCEAAAhCAgCWAgMdjAAEIQAACHUlAHzTXfeFqs/7GNZ5pxX6bUSLhTk6LGhLs3KgurY0DbG5+YUnWXZoZQUH36faQlQGBy0qbmpm32UpzQbeZ6HVOSJRJhcwqshjO6KGVWWlxTUnCcspDj7hWPG86a/VA1Fmn0QPRPb893V1hjyT29TKy2P3Ec2bL5puXmFlssL/8uGLVRWbTn65dXENZzcrSi9NHNPaGmQACEIAABCDQJgQQ8NrkIAkDAhCAAASCEzj42ptm890PmL0ny2KVOXK3Fe4k4Dk3RWde4f6uMjC5LyYxqkU81x8u7Syw6r0naVQRlosyolRuOG9Li7MuLXUGE63IDHNlxK1Yu1VZgFlmOtZ7xuWsm7VY7HogSiRWWe2Jkz0ww75W6sXUCvHO7UXvi/plxxU2K1ni3P6XXjWbt97vtRpwLQmcscWObXfGcvOOy4v7IQABCEAAAu1CAAGvXU6SOCAAAQhAIDABfbBUryZl32now6d6Nbned+7DqYQ+ldLeduuXzTVXrgo8f5ALa4t4ytiZzsTkoZUilp9P1qJSHjIes87+y3q9es+/M0eRmCVBLe3hBDQJd1msVyseJ172luI7G2v+ku11d5oVvlsp3vnjVOayWgvssiYWet/09w9V9p3eQ2VswYAABCAAAQhAID4BBLz4DJkBAhCAAAQKTkB9ms6xQp1zn3Xh+A0u0gixWsSrCA69qYp4aRtVROGUhajmF7GSzIaKEq/ukbAj51CZEKjMMqnsrOr95M0JNysxMQ/lyv6zSEIwl3innnddemhyNp7dd8D7JYhrPaAy210/e+qUfqI52zbbgQAEIAABCBSKAAJeoY6LzUIAAhCAQBoE1LtJJbIq/dpjHWfffv/wkj5Oaazp5lxYOGF74k2bWVtKqiHBZYX9kK6y0qSzhvIm5pwqcPR4YpbMPpIcFTOFknUGncvMHTTo/tMUL52IlVVvw6AxO0OJknVt1XnP29dAkiNNpnH26QwuFG5YIw25JI8OluIsn/q9LuNO76PKvKs2A0p9AywAAQhAAAIQaHMCCHhtfsCEBwEIQAACSwnU6mm3xrrMqsxLZhYa6unkd6FNm2G1iOeylJIs/cvaqCIKM9cfLskSy7yKOaeKlyVrpjFj1C8tiVGEuNMwesi6JDvKWWmPEpWDCqtD9nqdZxGGhLtx26IgrmN3EWJljxCAAAQgAIGsCSDgZU2c9SAAAQhAoGUEJNDtthl2/swQlcn+6y9t8pqxy7hirf1qxZCINzY5ZyanK66sTsSL23zfOXDOzqmR/lzi2U5Js+rUuJPKjvSfd9bmIFGehaTiVlafMlenZ7NzFY4Sr7unIlaXPMG2kQtykcS7ODy4FwIQgAAEIACB5gQQ8Joz4goIQAACECg4gWpn2epwVPq1/qbrMs26q4dUWTlJiXjO3TaPpaONHiknQk3NRHMOdeJIXPEz68c+rviWlPiZddzOkVjrRukHWOS4XR9Eve6rS4kR77J+ElkPAhCAAAQgkG8CCHj5Ph92BwEIQAACCRBQQ3W5yGZZFhtn22MTs+aY7demEUXMcj3Gytb58vBY8j3G4sQW9F5n8nDCZiaGySRzpaNp9NILuve410UpA3UOr0mW4caNI+z9Uc7OiXdFE6n9bGq5844MlMxAXzHKZsOeM9dDAAIQgAAEIBCNAAJeNG7cBQEIQAACEEiVgMpdx62RhYYrDwySkVbUbKR6MIOKWX6DAAmgSRsjpHrYNSYP46JahH53Qfkpe/L0obIt955tajhSMScpJ9o7MOg+k77OCfUztgS42xrZ9JW7k16C+SAAAQhAAAIQKDgBBLyCHyDbhwAEIACB9iVQLeJJ2Ji3Dq1HrEBVazghJ0nzizzQbSZQJdVHLQ+x+vfQTMxyWYq6px1ESxd7kFLiZs9E3s4yyH4U9ydH+zzBngEBCEAAAhCAAASqCSDg8UxAAAIQgAAEckzAL+Jpm6O2tE7DX1babtlntY5D/fxGrBvnobFpM2dFTDeK4K4b5/FyGZXVZgftlmlZi5Fza60uA29X8e6M4bLp6e6K87hwLwQgAAEIQAACbUwAAa+ND5fQIAABCECgPQhUi3iurFRilkrtJGgUzbAhyslUMu16vfJKlRoq7pItuVS/u6KXzDbi4XoaqrRSsfba3oYqHZ2Yal5mGoVznu6pGLGUvFgnp+etc2vZ296RYzPmxMc6bp62HHovToxFvAuNjhsgAAEIQAACHUUAAa+jjptgIQABCECgqAQkXki0cMNlIenvRTWqiHIWTuzosqqWjAskbnbK0JnL2GDBKledeuZ6HYyd7A3ZDueOeNcOp0gMEIAABCAAgWwIIOBlw5lVIAABCEAAAroRXrgAACAASURBVLEJOBHPfehX1pn+3ElijjN3UPbVtM3Caycxp9ED4ncWtrYmbWHcEPQF4X/eJdy2S8ZlyWZUnjHca7rsa5gBAQhAAAIQgAAEmhFAwGtGiJ9DAAIQgAAEckRgfsHY0sEFL/NMZbPt2A+sFm6/gCXBUlloKqc8YUVMfz/AHB1VYlup7nfXrqYdtYD5y6b1vFcE3FLhBUyVvqufJeJdYi8TJoIABCAAAQi0PQEEvLY/YgKEAAQgAIF2IyATh0NHp6yIVYnMZaW1ayZeI8MG1w+wXbKyqp9VOdGODqoH3Jz9ml/8sTMukStxuwqY7rnW2fqNS5yAWW3sUZTX+aAtgx4+aUZTlD2zTwhAAAIQgAAEWk8AAa/1Z8AOIAABCEAAAqEJzNlUPL9gV2n23+OVF/rFjtAT5+wGl3El4wplYNUa7ZqF6OJqdKbtKmA2O1NlZCoDU9WnR47NFsbEZMg6KSs2BgQgAAEIQAACEAhLAAEvLDGuhwAEIAABCOSEQLWI11euuJN+OD7dFiKexCnFFCSzUALmiL1ezrztIGCGid1lqknImpmzNdYFH2FEySLFnqV4N3Zs0nsKhgf7C/40sH0IQAACEIAABBwBBDyeBQhAAAIQgECBCVSLeK5nmBxriyrmuJJZlUgq806GFUFGdb+0IPfk7RrFfvpQObRBR71S27zF12g/7Rx7VuLd2+8dMvc++FNz8LU3jV42t3zlerP+xjVFegzYKwQgAAEIQAACdQgg4PFoQAACEIAABApOoLaIV140uihSeJVSYPV8m13S8y1oDI365QWdo1XXxTWniCqAtSpe/7pxz831BFRfSInXQUXfLGJXqW+/fa6zGDdu/La59qrLzKYN67zlNt/9gPkj+/e1N1yVxfKsAQEIQAACEIBAigQQ8FKEy9QQgAAEIACBrAhIxPvI9r+btaYGGk4QqTY/yGo/UdZp1vcs6JxFFLKSKgV1br3d3cu8foh5ErLqnZ8TLpN4Vl3pcR56Qao/34qRPqP4shgP/WiP+eWBV8zO+7YsLrf7qX3mnXd/tyjoZbEP1oAABCAAAQhAIB0CCHjpcGVWCEAAAhCAQOYEFmz60WHbA65axJP5w/jxucz3E3RBJzbOzC4k5qjqTA5OWCZ5d2lNSrj0805jzqDnGeY617cxyZJvN2fULM4w+693beWZ7s1MvFPPu+u++g3z+MPfMeeetWJxWxvu2u5l5K2/6bokwmIOCEAAAhCAAARaSAABr4XwWRoCEIAABCCQNAGJeB/ZEsJpK4ZpxC1NTHp/1fNVxJaS5zCbhsgYxhAh7Vir53eZgrPWeCINkdGVIzdy8M065qxERn8WZpg+iknwcK+5nu6uJKYLNMeux5426n+35favL17/7L4D5i/u+YF5+tHvYWYRiCIXQQACEIAABPJNAAEv3+fD7iAAAQhAoA0I6IP1q6+/ZT53yYWZfZCWI+nkdCXrzokZUzPpiGRRjyirLLGs1gnDISthNat1wsSua7M4E2Vhqp9iUCfjsDHUur4V4p32US3g6T1H/fB2bLvTrLbvOwwIQAACEIAABIpPAAGv+GdIBBCAAAQgkGMCux7fa3b97ClzjS1j2/3k8+a2W7+cmSukX8STmLHClvQpM29scralxJygOGezBccmZs28nAdSHspGG7GZfodsifHcyT6BKS9Zd/pKv7uSPYcZI6fdtIfOXs628zbuNDL9wuzflTbrnqzMJhzvtDMRS7bX3WmWc5aZd469BLs7rGHFtVdfbs498wzz/Z27zTprXOHMLMKcEddCAAIQgAAEIJBPAgh4+TwXdgUBCEAAAm1AwPWlciVs+pB9q+1JdZt1iMzKFVJlqeMnBTtncOCJJ1Y4a8Uo93SZ0cH0SmYbxSQzAYmYErFUstuKkUXmWb24nMHD4bGZTETT6n20MhvQGWVIME1DwJZ4p553XXKuaNHQ+80e+0sCvc9IvFt5wXkt2gnLQgACEIAABCCQBgEEvDSoMicEIAABCEDAEtj/4kHzkM2EecTnCqm+VNt3/MT7nr/ZfJrA/CKe1hkdKJllVmjIKgPKxebEq1Y6hLZKRPJnnmWVdVjrmVI2mspKdQYztvdeVqNV3P3xOQG7ZEVkxZ9U5md/b48nSjMgAAEIQAACEIBAmgQQ8NKky9wQgAAEINDxBOQMWS3Wbd3+sMdl25aNmfGpFvGcuYNKSk+kXMEq8WbYioZKTlJZb1LCSVR4foODNLKxqveVB/HKvyeXBTkxNWcmptLPRKysV7YmJa3LfPTHn6SIOWTLsiVMMyAAAQhAAAIQgEDaBBDw0ibM/BCAAAQg0NEEXA88ldG6cfC1N829D/50SWZeFpCqRTwJD33l7kSzkarjcKWLabnMRuXmsrHSzkSsuOyWrVA2m4lYFpRHViJmpf9cj/eMtbr3YC0RM85ziXgX9GnjOghAAAIQgAAEkiCAgJcEReaAAAQgAAEINCCwwfa9u+LSlYsN5fe/9Kr5/iM/Nzt9pbVZAZy0vd9UOutGmj3Z3NzKcsvCrCEKQ5eJmGRJZRZso8RafY8TMbtt/7Y0MiPTfLaSiF8ipit91fmHyURFvEviBJgDAhCAAAQgAIEwBBDwwtDiWghAAAIQgEAEAmoq78pmJeSpN943N99sVn7mUxFmi39L2iKehBGJN0n3Gosfee0ZkhaaJIypz1xvKdlea2nHn2SWXJrCaNIcwvZmHLHl4MoqZEAAAhCAAAQgAIEsCSDgZUmbtSAAAQhAoKMJKPPu4G/eMNdcdVlmBhb1gMvA4EPb/27hZP+75b0yN+gxcR1K89bvLegDV4lf5g7TsUo9XfxpuZ0GjSfsda7UN26fuqxKc8PG1+x69ek7fajSp69eX0D1cFQvP5WdMyAAAQhAAAIQgEDWBBDwsibOehCAAAQgAIGcEFBPskNHp04R8aJmYrl+Z+q1p95iRRvq17diuNcctSW/Ufbv+v1lZQ6RNN+44mvc+5OOJ+x8TnycteK2ngF/Sa3EuxUjfUZnzIAABCAAAQhAAAKtIICA1wrqrAkBCEAAAhDICQGJeIdtJp5zhnWOoWEy0VzJqLK44mbwtRpLVBEqbBlmq+Ost77OUploysxUr8SgfeGKLl76eaj81/8su2eip7srr8fGviAAAQhAAAIQ6AACCHgdcMiECAEIQAACEGhEYG5+YYnwVhFjer1ywmaZaEUtGW3EI2wZaLXg0w5PW5iYXPmxBD+VZrfDcDEdn54z+jPiXTucKjFAAAIQgAAEik0AAa/Y58fuIQABCEAAAokQqC3iqSdY/XLYSslsyfYMq983LJHNtWAS59C6zNZO1stE8wt9EjuDZqu1IJxIS+p8K30B6wtzSRuARNpoSjcpG3XFSG9Ks7fvtGPHJs2z+w6Y1ZdcuNjrU0Y+r77+lrnmylXtGziRQQACEIAABFImgICXMmCmhwAEIAABCBSFQLWI57LravV0C5OhVZT4a+2znpuqKxlVhqJEznYdjUpj21m8K9ks1DNsP8QuNb9jhCbgXLe3bdloJOjdtPHbZv1Xrjfrb1wTei5ugAAEIAABCECgQgABjycBAhCAAAQgAIFFAhLxPrIZV7O2N55GdU84f8lsO2ad1XoUqoUqZ9YxZo0O5Dbb7qO6pFjZiXJj1QjTJ68onOQyOzpQQryLcWDKuLv1ru3mtg3rzCuvvWnGrYgnMY8BAQhAAAIQgEB0Agh40dlxJwQgAAEIQKAtCSxYBwMZW1SLeDOzC6Zc6rIls3P2q3gus3EOy/VEm5qZX2JwEGfOIt3rSopLtqxUf27XzMPBvh4zbMU7RnwC+1961Wzeer8ZHuw3jz38He+/DAhAAAIQgAAEohNAwIvOjjshAAEIQAACbUtAIt5H1pRg2op2GiolHVzeY47ZclFlnnXacFloErCOTsx0nICp8xaDT5zsCXfICrxyMG6nMWSfcWVbMpIhcND2vLvxz/6d1wfv6Ue/l8ykzAIBCEAAAhDoYAIIeB18+IQOAQhAAAIQaEZAYt1yW1I4a91Fj9nMu9Ns6aT+fGSic0Q8fxnxpO15d8ZwuW0z0Oo9DzJ0UNlspWz6hBV0K39u5lLc7PnKy88R75I9CX/fu4O/ecMM2ey7Lbd/PdlFmA0CEIAABCDQYQQQ8DrswAkXAhCAAAQgEJaAykblRKrhSin1504Q8VzprF+squ4JF5Zn0a53Pf/0DLisu+reiEWLyb9fxLvkT2/7gz81B23vu533bTH+fnhrb7gq+cWYEQIQgAAEINAhBBDwOuSgCRMCEIAABCAQh4CcVsd9pbNq8t9tnTol6tiErLYcjVxWnZDZ6QxOHyobW21dWDMLZRX293an8vxKwFLmmUpIO2lIsLt7+8Pm/u/esdj37tl9B8yzz/3K/FubhUcvvE56GogVAhCAAASSJICAlyRN5oIABCAAAQi0MYFqEU8Clxw71Q+tnUQ857JqW75ZYWrWzEuhqjPUG7DXGntIyGx0XREfi6Cx6bq+cpc1PikOA53t6cO9RqXBaYz9Lx40W62IJQFPXw/4xKw01mNOCEAAAhCAAATanwACXvufMRFCAAIQ6GgCKuXS8Pdf2vX4XrP/wCveh2pGOAK1RDyVmRZJvGkUcZTS0EaZeuHo5uPqKCXCKrMdWl7yhMwZ2yMxz6Nyxr2mx2aQZjH0fqM+cNu2bMxiOdaAAAQgAAEIQKBNCSDgtenBEhYEIAABCFQIuEwYvwvihru2m2uvusysv+k6MEUg0K4inrLIRgcq5gwTU/OhyLheeUesc2/eBaykBUw3nwQxldROWLOTsPxCwY5xsRNoe7rTybyrtTWVlN648dvm7//6oRg751YIQAACEIAABDqdAAJepz8BxA8BCECgAwhc99VvmNs2rDNqoK6+VBLwJOjRiyn64cuNVWKVG0XPQkti/xKwVtjMrqO2V2AR3VmTEOD82XsVx9roz1jSd2Yp3smFddx+vWPFO2UBr7505WIWsAS9TuuLl/RZMh8EIAABCECgEwkg4HXiqRMzBCAAgQ4jsOfJ580zz7/glcw+9KM9Zmx8YklJbYfhSCzcahGvkoXWU6hyWvW7U+lnUn3sopTgJnYgMSbS2Y3YXnbqZ+icZqNO5ww+Sra/XF56A5asuHqazQ5MK/NOgt29J51X9Wf9ckBf6n+nbF/98kBGDtt3/GSxL55KahHyoj5l3AcBCEAAAhDoPAIIeJ135kQMAQhAoOMIKONFWXjKulMp245td5rVl1zYcRzSCHhqppKJ53wekhSC0tivf04ntk3NLJgxn8Nu3HWj9JCLu2ac+5PIPqy1vptXIl5cUTBOfBLv1POuS84VKQ29x9xqM3uvsWKdv9+mW27PU/vMPVa8e/zh73ii3cHX3zJ3bL3fe09iQAACEIAABCAAgSAEEPCCUOIaCEAAAhAoPAE5QqqkTR+09SG6E8ZDO3ebHz/2tBfqLV+53mz607WphC1x5tDRqUURr1KK2Wuzr+Jnc6WyYTupKxdVqat6+iU9XBZat2UhAStPpaT+WNMS79wacnkdHaz0FWxFWXF/b49dv5T08dacT5l3es3pPUbZda5E3/XAq/7FwRr7S4Wd920hCy+T02ERCEAAAhCAQPEJIOAV/wyJAAIQgAAEAhCQmYV6391265dTE7ICbCOzS+R8+fa7v/OygVx20DpbxrfJ9gJMY0jEO2zLL+dPpuLluR9clplhw7YsNany3CTPTQKjhDUNZVCmKTC2qqx4yLLXWWc99Nrb/cRzXsm+su30vrPygvOWZObtf+lVs9lm4GFskfXpsB4EIAABCECguAQQ8Ip7duwcAhCAAARCEOg084o77n7Ac9lV83wNJ+I5M48Q6AJfOje/sKT/nRNulOHWiuyrWhuXoCa32cNjM4tiY+AAI16YdpZb2G21QlCTYCiHWo0sMhJbJd65s1CJ7DlnnuFl4X3+S5uWmOYoU0/ltuu+cLVZf+OasMfH9RCAAAQgAAEIdCgBBLwOPXjChgAEINBJBCReqYT2ilUXtXX2nYQBDYkGcr7U8PfjciLeY7aEOC0H3noiXlqlqkGf41a7o1YMPkpettvM3ELQbSd+XSvEO38QWQiorRbvqg9NAp4/006vTf1CQeWzDAhAAAIQgAAEIBCUAAJeUFJcBwEIQAAChSQg58e/uOcHnhPkN205aVrCVSvhOAdMOe1q7Lz/W2ZoYPmicYff6VKZecr8uebKValtOW8iXqtFKwfa9d1rVUaiMg+H+8vWsGPGyLijVWOgr9sM9KUjZo4MlOzc2ZfNNmKpvni/tCX8et2ptFa9OB+x4l07vhe16pliXQhAAAIQgEAnEEDA64RTJkYIQAACEGhrAuqxde3Vl3vleOq/9exzv/IEAgkHu5983vuzE/G23vtDr6x23fVXpsokLyJeRSzq8VxmWylaOditEhOz7PsX5MFK2kREBrPDA2XTbzMd8zjU8+4Z+7q8yPbCW2t7UTIgAAEIQAACEIBAWAIIeGGJcT0EIAABCEAgRwScw6W/RE/ulnsf/Z63Syfibdl8sxkfn/BcabPK/lmwhhYytpi1Bhca6oO2YrjXCmnpOL9WH0vees/5RTz1g5ueXfCExbRH3jnM2pLio5ZDVCMNiXcrRvo8Z2EGBCAAAQhAAAIQaFcCCHjterLEBQEIQAACHUNAPbVcrzvX78/fX2uPzcJTee051hFTxhb+ktq0IdUS8SRezVtR78hEOuKVstxGB0tGhrhpO6xG5Scxc8QaanRb0SlNU4dRW1Ja6uny1nAOwVH3nMZ9jkPUPbqMxp7urjS2x5wQgAAEIAABCEAgNwQQ8HJzFGwEAhCAAAQgEJ/A7qf2mYO/eWNR0FN/vFb32pKINzY5Zyan5xYDlLCkESfzqhatVpWoRj25tLLj/KYdWWT5RY3f3RelxBfxLi517ocABCAAAQhAoEgEEPCKdFrsFQIQgAAEINCEgLLxVv7L870ed+qHt+tnT5mnT5bTthrekWOzp4h4yrw6ZMtso5ZP+mNyTq/jx2eNXG+LMpIW8YomYrpzKttnYXSwbCamZu1X4/NDvCvK080+IQABCEAAAhBIigACXlIkmQcCEIAABCCQAwJymd20YZ3ZZXvdaeTNeXfMls0em/o4E0/iVV+5O7aIl7QIlvVROvFRJb8ztidc1OHMISYs42YiWNQ10rzPCXMyHKmXOViyZcdn2F6KXWp+x4AABCAAAQhAAAIdQgABr0MOmjAhAAEIQKAzCEjA++WLB80tttedhLw8jvHjc2bcZ94QR3xTDzVlbUnLUYZfHvu8BT2DuOKbc9xVv7u5k8YhQdfO03U6U/VJ1KjuDyixV+XXiHd5OjH2AgEIQAACEIBAFgQQ8LKgzBoQgAAEIACBjAg8u++AZ1ax8jOfymjFaMskIeIVtVS0EbGoMcURQaOdYPp3VcfU39vjmZMwIAABCEAAAhCAQCcSQMDrxFMnZghAAAIQgEAOCFSLeC6D7PBYc8fUvnKXGbYurkUtFW0m4ikDbXq2fhmp/35x6C3l12k2zqPmSotVVtzf2x1nKu6FAAQgAAEIQAAChSaAgFfo42PzEIAABCAAgWITkAB31PbFc6Mi2PR4pZP1ykCjOJYWjZLKSEesMNdt+71Vl5G6WFz5sP6u3nlJGIHkkZNKpBHv8ngy7AkCEIAABCAAgSwJIOBlSZu1IAABCEAAAhA4hcCkdYyVALVUxCtZ4Wp6iYgnwWpoeftmm9V6NOqVxkYttS3a4zdkRUwxYEAAAhCAAAQgAIFOJ4CA1+lPAPFDAAIQgAAEckBAIt7YxIxZOFHZTMXQodcT9lQ+GcSdNAdhpLKFahGvU8Q7Mu9SeZyYFAIQgAAEIACBghJAwCvowbFtCEAAAhCAQLsRUMnsoaNTS0S8FcO95pgts1UJ5XEr8qlvXicO1wtOJccDfT1mbHLGTM0stCUKOQqfbs+93NPVlvERFAQgAAEIQAACEIhCAAEvCjXugQAEIAABCEAgFQLVIp4MGgZtCeWkFa6O+HrlpbJ4zicdHSiZfiveHbMi5tjkx30Dc77tUNurZBf2ehmYDAhAAAIQgAAEIACBjwkg4PE0QAACEIAABCCQKwJz8wtGTrTKNJPb7JFjs2Z0sNTRGXiujLadWbjS4J5uMu9y9YJkMxCAAAQgAAEI5IIAAl4ujoFNQAACEIAABCBQTWBqZt58dNJdtVP6vlUzcG60JVtOemhs2nOaFYvTh8pmenahbTLxEO94/UMAAhCAAAQgAIHGBBDweEIgAAEIQAACEMglAZeJN3/S2cIJVxL2OqEXXiOhzgl73bbU9MPxGU/YK+pAvCvqybFvCEAAAhCAAASyJICAlyVt1oIABCAAAQhAIBSBahFPwpWMLdop+6wWkKAZh9UOtaHg5uDikhUg1fOuS84VDAhAAAIQgAAEIACBugQQ8Hg4IAABCEAAAhDINYEFm4F32JaPzlqXWg2JeCohnbd/b0djCxk4KD45zk5MzTc9GyfiKRNPJiBFGf29PV5vwyzH2LFJMzzYn+WSrAUBCEAAAhCAAAQSIYCAlwhGJoEABCAAAQhAIE0C1SKe1pIr6zKbuXXkZJ+8NNfPau6Bvm7PvCOsGLe8t9sMLS95LGbmFrLabuR1Bm2Mw/b80h4S7P7hpVfNM8/9yux/8aC33GMPfwcRL23wzA8BCEAAAhCAQOIEEPASR8qEEIAABCAAAQikQUAi3tjknJmcnlucfri/ZHpLHxs8pLFuVnPGLYcNm7mXVVzV6wzZM1OsaQ2JdnuefN48+/wL3hKrL13pfW3d/rBZ/5Xrzfob16S1NPNCAAIQgAAEIACB1Agg4KWGlokhAAEIQAACEEiDwJFjs0tEPIlBfeVuL2vNGV6ksW6aczohMm4MQXvnpRlLo7nTFu+09tvvHTK33rXdbNl8s7nmylXedjbf/YA596wVZsvtX1/cHuW0rXoKWBcCEIAABCAAgSgEEPCiUOMeCEAAAhCAAARaSmBsYtYcsz3i3IibvdaqYFw/PxntJlUK7Iw+Zm0pbZ56BI7YklmVB2cxJOLdYUW7dV+42oyPT5hnbDbeI/dt8UpnlZ33/Z27jboFStTbtmWj918GBCAAAQhAAAIQyDMBBLw8nw57gwAEIAABCECgLoHx43NmfHK2sCJemtlyEvFGbKlqtzXEUFbfiRZ6W8hgdnigbPptn74shzLsbtr4bS8j7+lHv+eJdLse32t2/ewpT8zT35/dd8B8/5Gfm8dtXzwGBCAAAQhAAAIQyDMBBLw8nw57gwAEIAABCBSQwEM2u+nnNstJAskttueYK2NMI5RqEc+ZQBwey3c5bZrinZ9zqzMTJd6tGOkz6s+X9ZBwt8GW0l6hHnirLvKex81b7zc77/+WWfmZTy1u5/Nf2mT+/q8fynp7rAcBCEAAAhCAAARCEUDAC4WLiyEAAQhAAAIQaERAGU5vv/s7r9fYfuv+ufWeH5h1N1xlNm1Ylxq4ahGv4sga3sk1tQ1WTdxX7jLD/WVryDFjpmbSd4yN6mwbl4cTKXu6u+JOFen+g6+/ZV597U2z9vorvfsl5l179eVLTCz0jG7f8RMy8CIR5iYIQAACEIAABLIkgICXJW3WggAEIAABCLQ5gTVf/YbZebI8UaE6Q4EHtt25JOspaQwTth/eUdsXzw0nkn04Pm3m5ltYP1oVaKsy4iqiZsnrszdje+OlPVot3lXH57Lx9tpSWjdciS3OtGk/DcwPAQhAAAIQgEASBBDwkqDIHBCAAAQgAAEIeATk/qmMu7X2yw1nGqA+ZGmOyel5T6ByQ2Wbpw/1mvHjs+a4/VmrR6vEu6U8ykZi58RUejzyJt4pficku2dQ4p2e1ZUXnOeZWDAgAAEIQAACEIBA3gkg4OX9hNgfBCAAAQhAIMcEXJmsMwVwYp37u9u6xBKV0a62/cjSHBLxxiZ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59506507\\u003cbr\\u003eText: Well, I realized that was a whole lot of theory, but I hope it gave you a good intuition that will\\nb...\",\"Video: 59671315\\u003cbr\\u003eText: Okay, so here we are, back in Jupyter Lab, ready for the next use of a frontier model, and see this\\n...\",\"Video: 60616895\\u003cbr\\u003eText: It feels like 100 videos ago that I told you that we were going to have instant gratification with o...\",\"Video: 60619275\\u003cbr\\u003eText: And we will conclude our expedition into the world of frontier models through their chat interface b...\",\"Video: 59472693\\u003cbr\\u003eText: Friends.\\nI am absolutely exhausted.\\nI am exhausted and a little tiny bit traumatized.\\nAnd you are so...\",\"Video: 59670121\\u003cbr\\u003eText: So it's business time right now.\\nWe are going to build a Rag pipeline to estimate the price of produ...\",\"Video: 59295619\\u003cbr\\u003eText: Welcome back to the the moment when we bring it all together into a beautiful user interface.\\nBut fi...\",\"Video: 60617163\\u003cbr\\u003eText: And already that wraps up day two.\\nNow that you have built that solution.\\nAnd congratulations on tha...\",\"Video: 60616423\\u003cbr\\u003eText: So I hope you've just enjoyed yourself experimenting with different LMS locally on your box using th...\",\"Video: 59170227\\u003cbr\\u003eText: Welcome back to Google Colab.\\nHere we are ready to explore the wonderful world of Tokenizers.\\nSo, uh...\",\"Video: 59169985\\u003cbr\\u003eText: So I hope you enjoyed that whirlwind tour of Google Colab.\\nHere's just a little screenshot example o...\",\"Video: 60616927\\u003cbr\\u003eText: It's time for our first LM experiment at this point.\\nSo some of this you may know well, you may know...\",\"Video: 59673721\\u003cbr\\u003eText: And here we are in JupyterLab for the last time, and we are looking here at day five, the last day\\no...\",\"Video: 59508055\\u003cbr\\u003eText: I'm so very happy that you've reached this epic moment in the course and that you're hanging in ther...\",\"Video: 59670259\\u003cbr\\u003eText: It's remarkable.\\nBut you are now at the 95% point.\\nThere's 5% remaining of this course.\\nUh, maybe it...\",\"Video: 60616623\\u003cbr\\u003eText: So we're now going to start week one of the course when we are going to be looking at exploring fron...\",\"Video: 59472383\\u003cbr\\u003eText: And welcome back to the week six folder.\\nWe're now at day two, which is the second and final stage o...\",\"Video: 59670171\\u003cbr\\u003eText: So as the very final step on this part four of day two of week eight, we are now going to build an\\ne...\",\"Video: 59297721\\u003cbr\\u003eText: And so now the time has come to talk about the most crucial aspect of Rag, which is the idea of vect...\",\"Video: 59297599\\u003cbr\\u003eText: Well, that was a sneaky detour I took you on in the last one.\\nI hope you enjoyed it though, and I ho...\",\"Video: 59507635\\u003cbr\\u003eText: Look, I hope you're excited.\\nYou really should be.\\nYou've been through 80% of the course and it's al...\",\"Video: 59669375\\u003cbr\\u003eText: Here we are for the day.\\n2.1 notebook.\\nAnd don't let it be said that I don't ever do anything for yo...\",\"Video: 59297733\\u003cbr\\u003eText: Welcome back to JupyterLab and welcome to your first experiment with the world of Long Chain.\\nLet me...\",\"Video: 59670369\\u003cbr\\u003eText: It is terrific that you're hanging on in there and making such great progress with this course.\\nAs w...\",\"Video: 59166281\\u003cbr\\u003eText: And with that, amazingly, you completed day one of week two already and that gets you to the 15% poi...\",\"Video: 59671567\\u003cbr\\u003eText: Well, the first thing you're going to notice is that I don't have a notebook open for you.\\nAnd that'...\",\"Video: 59297593\\u003cbr\\u003eText: And welcome to continuing our journey with Hrag.\\nAnd today it's time to unveil Liang Chen.\\nSo first,...\",\"Video: 59166461\\u003cbr\\u003eText: And welcome back to the lab.\\nHere we are in Jupyter Lab and we are going to go into week two.\\nAnd we...\",\"Video: 59167007\\u003cbr\\u003eText: Well, how fabulous is that?\\nI hope that you are as wowed as I am by our new airline, I assistant and...\",\"Video: 59508121\\u003cbr\\u003eText: The moment has arrived.\\nHere we go.\\nWe're in fine tuning.\\nWe do fine tuning.\\nTrain.\\nThere is also a ...\",\"Video: 59295579\\u003cbr\\u003eText: All right.\\nAre you excited to see how this goes?\\nLet's give it a try.\\nSo in this next section, I cre...\",\"Video: 60620375\\u003cbr\\u003eText: And with that, we've reached an important milestone.\\nThe first week of our eight week journey is com...\",\"Video: 59472491\\u003cbr\\u003eText: Welcome back.\\nIf you are following along with me in JupyterLab, as I hope you are, then you will nee...\",\"Video: 59472425\\u003cbr\\u003eText: Welcome to week six, day three.\\nToday is going to be a day that you will either love or you will hat...\",\"Video: 59508057\\u003cbr\\u003eText: Actually slight change in plan.\\nI'm going to wrap up the day.\\nDay three at this point, and say that ...\",\"Video: 60619577\\u003cbr\\u003eText: And for the final piece of background information, I wanted to take another moment to talk about API...\",\"Video: 59170291\\u003cbr\\u003eText: Welcome back to Colab and welcome back to our business project.\\nSo again our assignment, we are due ...\",\"Video: 60619651\\u003cbr\\u003eText: I mentioned before an AI company called vellum.\\nWhen we were talking about the different questions, ...\",\"Video: 59473191\\u003cbr\\u003eText: And you thought we'd never get here.\\nHere we are in Jupyter Lab, running our fine tuning for a front...\",\"Video: 59170297\\u003cbr\\u003eText: And here we are in Google Colab, ready for fun with models.\\nSo first we do the usual Pip installs an...\",\"Video: 59167015\\u003cbr\\u003eText: Welcome back to Jupyter Lab and welcome to Day Five's Lab.\\nAnd this is going to be lots of creativit...\",\"Video: 59170043\\u003cbr\\u003eText: Let me enthusiastically welcome you all back to week three of our LLM engineering journey.\\nIf you en...\",\"Video: 59473147\\u003cbr\\u003eText: Well, I'm very relieved.\\nI've got that behind me.\\nNo more human testing for me.\\nWe'll have one final...\",\"Video: 59166453\\u003cbr\\u003eText: Welcome back and welcome to our continuing JupyterLab experience.\\nUh, I'm hopefully going to keep yo...\",\"Video: 59166915\\u003cbr\\u003eText: Welcome back to the wonderful world of JupyterLab.\\nAnd here we are in week two.\\nDay three.\\nUh, bring...\",\"Video: 59667365\\u003cbr\\u003eText: Here we are back in Colab, looking at the week seven, day five of the Colab notebooks and I'm on a\\nT...\",\"Video: 60616845\\u003cbr\\u003eText: We're on the home stretch.\\nThis is the final step in the environment setup, and it's an easy one.\\nIt...\",\"Video: 59295459\\u003cbr\\u003eText: And welcome back to More Leaderboard Fest as we go through some more leaderboards.\\nBut this time we'...\",\"Video: 59471979\\u003cbr\\u003eText: So we now turn to the parts of the problem, which is perhaps, let's say, not as glamorous as some\\nof...\",\"Video: 59503705\\u003cbr\\u003eText: And so now we talk about quantization the q and q Laura.\\nQ stands for quantized quantized.\\nLaura.\\nAn...\",\"Video: 59472505\\u003cbr\\u003eText: So the good news is that this is the very final video about data set curation.\\nYou were probably fed...\",\"Video: 59669217\\u003cbr\\u003eText: And welcome to the next part of visualizing the data.\\nAnd just very quickly to show it to you in 3D....\",\"Video: 59671221\\u003cbr\\u003eText: I gotta tell you, I don't like to toot my horn a whole lot, but I do think that I've done a great\\njo...\",\"Video: 59503703\\u003cbr\\u003eText: Well.\\nHello there everybody.\\nI am so grateful that you've made it through to the start of week seven...\",\"Video: 59473201\\u003cbr\\u003eText: Well, before we do a postmortem on what happened, let's just quickly look at the standing the rankin...\",\"Video: 60622463\\u003cbr\\u003eText: In this video, we're going to set up a full data science environment for Mac users.\\nIn the next vide...\",\"Video: 60619299\\u003cbr\\u003eText: Well, I hope you found that both educational and enjoyable.\\nAs we went through and learned so much a...\",\"Video: 59295607\\u003cbr\\u003eText: So to revisit then the solution that we built in the previous day and talk about the metrics.\\nAs I s...\",\"Video: 59297575\\u003cbr\\u003eText: Well, welcome to the final part on rag.\\nAnd this is the session where you go from being a rag expert...\",\"Video: 59507687\\u003cbr\\u003eText: It's time for action, everybody.\\nWe've set up our colab.\\nHere we are, week seven, day three.\\nWe've g...\",\"Video: 59671441\\u003cbr\\u003eText: And welcome once more to our favorite place to be Jupyter Lab, the Paradise for a data scientist exp...\",\"Video: 59673431\\u003cbr\\u003eText: And here we have it.\\nThe user interface is completed.\\nThe extra notification came through on my phon...\",\"Video: 59473137\\u003cbr\\u003eText: Let's get straight to it.\\nSo the place where you can see everything that's going on and get knee dee...\",\"Video: 59166421\\u003cbr\\u003eText: Welcome back to the radio day in the lab.\\nMore to do.\\nLet's keep going.\\nWhere we left off is we had ...\",\"Video: 59295599\\u003cbr\\u003eText: Welcome to the Jupyter Lab for day four.\\nIt's going to look very familiar because it's actually I've...\",\"Video: 59669631\\u003cbr\\u003eText: Here we are in our favorite place to be in JupyterLab, ready for some coding and a lot of coding tha...\",\"Video: 59673663\\u003cbr\\u003eText: But wait, there's more.\\nWe need to add some more to the user interface just to make it look more coo...\",\"Video: 59506929\\u003cbr\\u003eText: And we return to the hugging face open LLM leaderboard.\\nThe first place you go when selecting your b...\",\"Video: 59504785\\u003cbr\\u003eText: So at this point we're going to talk about hyperparameters.\\nAnd we're going to introduce three of th...\",\"Video: 59505337\\u003cbr\\u003eText: So we're now going to look at four bit quantization, the rather remarkable effect of reducing the pr...\",\"Video: 59271655\\u003cbr\\u003eText: So here we are on Hugging Face's main landing page at Hugging Face Core.\\nA URL you know.\\nWell, since...\",\"Video: 59472883\\u003cbr\\u003eText: Okay, time to reveal the results.\\nIt has run to completion.\\nAnd here it is.\\nSo a moment to pause.\\nIt...\",\"Video: 59673639\\u003cbr\\u003eText: And welcome now to the code for our user interface, which we will find in this Python module.\\nPrice ...\",\"Video: 59472463\\u003cbr\\u003eText: So last time we looked at a humble linear regression model with feature engineering, and now we say\\n...\",\"Video: 59297595\\u003cbr\\u003eText: So by the time you're watching this, hopefully you have played yourself with vectors.\\nYou've created...\",\"Video: 60619149\\u003cbr\\u003eText: So we're going to start our exploration into the world of frontier models by playing with the famous...\",\"Video: 59297735\\u003cbr\\u003eText: And at last the time has come to see rag in action.\\nAfter all of this talk, and here we are.\\nWe're i...\",\"Video: 60616407\\u003cbr\\u003eText: And now over to my Mac people.\\nAnd I have news for you.\\nIt's exactly the same thing.\\nYou go to a fav...\",\"Video: 59170235\\u003cbr\\u003eText: So here we are in Google Colab for our first collaborative session on the cloud using a GPU box.\\nOn ...\",\"Video: 59472067\\u003cbr\\u003eText: So we've covered steps 1 to 4 of the five step strategy.\\nAnd that brings us to step five, which is p...\",\"Video: 59472011\\u003cbr\\u003eText: Welcome everybody.\\nSo in the past I've said quite a few times, I am excited to start this this week ...\",\"Video: 59295553\\u003cbr\\u003eText: Welcome back.\\nIn the last part, we gave our GPT four and clawed the challenge of converting a simple...\",\"Video: 59297773\\u003cbr\\u003eText: Well, I hope you're eager with anticipation for this session in JupyterLab as we finally get to see\\n...\",\"Video: 59295583\\u003cbr\\u003eText: And here we are back in JupyterLab.\\nIt's been a minute.\\nWe've been working in Colab for last week, a...\",\"Video: 59507329\\u003cbr\\u003eText: Okay.\\nIt's moment of truth time.\\nI have just taken our class tester.\\nYou remember this class?\\nUh, it...\",\"Video: 59295429\\u003cbr\\u003eText: Continuing our investigation of benchmarks, and this will become more real when we actually see some...\",\"Video: 60595637\\u003cbr\\u003eText: Here we are back in the Colab, which has been running overnight for me and probably for you too, I\\nh...\",\"Video: 59668027\\u003cbr\\u003eText: And so here we are at the home page for modal.\\nAt modal.com spelt model not not model which is confu...\",\"Video: 59295527\\u003cbr\\u003eText: I'm so happy to welcome you to week four, day four on our journey to LLM Engineering and Mastery.\\nHe...\",\"Video: 59295377\\u003cbr\\u003eText: Just before we go on to some of the more advanced metrics, I want to mention for a second something\\n...\",\"Video: 59666211\\u003cbr\\u003eText: So before we try our new model and one more recap on the models so far and keep notes of this so we\\n...\",\"Video: 59170107\\u003cbr\\u003eText: And once again, it's that moment when you take a pause and congratulate yourself on another day of\\ns...\",\"Video: 60616833\\u003cbr\\u003eText: So I realized that day one of week one has been a pretty long day, and I assure you that the other,\\n...\",\"Video: 59472413\\u003cbr\\u003eText: Wonderful.\\nWhere we left off is we had just created the Get Features function, which builds our feat...\",\"Video: 59297561\\u003cbr\\u003eText: And would you believe at this point you're 55% of the way along the journey?\\nUh, it's been a while s...\",\"Video: 59669211\\u003cbr\\u003eText: Well, we took on a lot today and we seem to have been successful.\\nThese red icons that you see on th...\",\"Video: 59166981\\u003cbr\\u003eText: Welcome to week two, day five.\\nThe last day of week two where a lot is coming together.\\nI am so grat...\",\"Video: 60619227\\u003cbr\\u003eText: And now let's move to Claude from anthropic, my favorite model and typically the favorite model of\\nm...\",\"Video: 60620395\\u003cbr\\u003eText: Welcome back to Jupyter Lab, where I want to show you the assignment, the homework exercise for you\\n...\",\"Video: 59665127\\u003cbr\\u003eText: Well hi there everybody.\\nI'm not going to give you my usual song and dance about how excited you are...\",\"Video: 59668923\\u003cbr\\u003eText: Well, welcome back to Jupyter Lab for what will be an epic finale to our time in this platform.\\nAnd ...\",\"Video: 59504887\\u003cbr\\u003eText: Well, here we are again in Google Colab.\\nIt's been a minute since we were here, and welcome back to ...\",\"Video: 59170165\\u003cbr\\u003eText: Welcome, everybody to the last day of week three.\\nWeek three.\\nDay five.\\nWe're here already wrapping ...\",\"Video: 60617251\\u003cbr\\u003eText: Congratulations are definitely in order.\\nYesterday was a mammoth first day on this course and you go...\",\"Video: 59166951\\u003cbr\\u003eText: All right, back to the lab.\\nBack to our project.\\nTime to work with tools.\\nI am in the week two folde...\",\"Video: 60619619\\u003cbr\\u003eText: Well, day four was an information dense day.\\nI do hope that you learned some something useful here, ...\",\"Video: 60616663\\u003cbr\\u003eText: Well.\\nHi there, this is time for PC people to get set up.\\nSo all you Mac people out there, you don't...\",\"Video: 59508175\\u003cbr\\u003eText: So I'm taking a moment now to explain that the training costs of optimizing a model for this course\\n...\",\"Video: 59670087\\u003cbr\\u003eText: And welcome to part four of day two of week eight.\\nUh, there's a lot happening this week, and I have...\",\"Video: 59506713\\u003cbr\\u003eText: Hi everyone.\\nSo the reason I'm so fired up about week seven is that this is the time when we actuall...\",\"Video: 60620169\\u003cbr\\u003eText: Hopefully you found this super satisfying to be able to have this nice business result and have it c...\",\"Video: 59295435\\u003cbr\\u003eText: Well, just before we wrap up, let me introduce this week's challenge and talk about what we're going...\",\"Video: 59297609\\u003cbr\\u003eText: Last week, we worked with models that were able to speed up code by a factor of 60,000 times, which\\n...\",\"Video: 59507489\\u003cbr\\u003eText: Continuing our adventure through hyperparameters for training.\\nThe next one is pretty crucial and it...\",\"Video: 59295549\\u003cbr\\u003eText: And welcome back to our challenge again.\\nAnd this time we are working with our beautiful prototype.\\n...\",\"Video: 59665129\\u003cbr\\u003eText: And now let me make this real for you by showing you some, some diagrams, particularly now looking\\na...\",\"Video: 59169991\\u003cbr\\u003eText: Okay, so that was your introduction to Hugging Face.\\nAnd now I'm going to turn to a different resour...\",\"Video: 59472027\\u003cbr\\u003eText: And now the time has come to curate our data set.\\nAnd the way we're going to do this is we're going ...\",\"Video: 59472307\\u003cbr\\u003eText: Welcome to week six.\\nDay two a day.\\nWhen we get back into the data, we look back in anger at our dat...\",\"Video: 59508289\\u003cbr\\u003eText: So here we are now, back in the Colab, in the same one that we kicked off in the previous day.\\nIt's ...\",\"Video: 59472333\\u003cbr\\u003eText: Thank you for putting up with me during my foray into traditional machine learning.\\nI think it was u...\",\"Video: 59295431\\u003cbr\\u003eText: Now I want to take a quick moment to give you a flyby of five different ways that llms are used comm...\",\"Video: 59673449\\u003cbr\\u003eText: Well, I have to tell you that I'm a little bit sad.\\nThis is the beginning of the beginning of the en...\",\"Video: 59669389\\u003cbr\\u003eText: Well.\\nHi there.\\nSo you've made it to day two of week eight, and I am super grateful that you've been...\",\"Video: 59170057\\u003cbr\\u003eText: And so at the beginning of this week, we started by talking about hugging face pipelines.\\nAnd you us...\",\"Video: 59166949\\u003cbr\\u003eText: Welcome back to making chatbots.\\nLet's keep going.\\nSo for the next part we're going to beef up the s...\",\"Video: 59473019\\u003cbr\\u003eText: Welcome back to an action packed time of of training.\\nSo now, after waiting about five minutes when ...\",\"Video: 59297585\\u003cbr\\u003eText: Before we move on, let me show you one more time this fabulous slide that describes the simple three...\",\"Video: 59170255\\u003cbr\\u003eText: And welcome back to us continuing our journey through the model class in Hugging Face Transformers l...\",\"Video: 60614589\\u003cbr\\u003eText: So we're now going to run a large language model directly on your box using a platform called llama,...\",\"Video: 59297601\\u003cbr\\u003eText: I'm not going to lie, at this point you have every reason to be impatient with me.\\nWe've been yammer...\",\"Video: 60616629\\u003cbr\\u003eText: And welcome back to team PC and Team Mac as we come back together again for a quick video.\\nIn this o...\",\"Video: 59297749\\u003cbr\\u003eText: It's always welcome back to JupyterLab, my favorite place to be.\\nAnd now we are, of course in the we...\",\"Video: 59170135\\u003cbr\\u003eText: Welcome.\\nIt's week three.\\nIt's day four.\\nWe are back on the adventure in open source land, back inve...\",\"Video: 59472017\\u003cbr\\u003eText: And this is the first time that we'll be coding against our big project of the course.\\nWelcome to Ju...\",\"Video: 59507017\\u003cbr\\u003eText: Welcome to Colab.\\nWelcome to the week seven day two Colab.\\nAnd just before we try our base model, we...\",\"Video: 60619883\\u003cbr\\u003eText: And now we've arrived at an exciting moment in our first week.\\nThe conclusion of the first week is w...\",\"Video: 59508297\\u003cbr\\u003eText: What more is there to say, really?\\nTomorrow is the day for results.\\nA day that very excited indeed a...\",\"Video: 60619247\\u003cbr\\u003eText: We're going to spend a little bit more time with GPT just to try out a few more interesting things.\\n...\",\"Video: 59504769\\u003cbr\\u003eText: Without further ado, we're going to get stuck into it.\\nTalking about Laura.\\nLow rank adaptation.\\nAnd...\",\"Video: 59170233\\u003cbr\\u003eText: Welcome back to our continued exploits with Tokenizers.\\nWhat we're now going to look at is what's ca...\",\"Video: 59671231\\u003cbr\\u003eText: And here we are back in the Jupyter Lab for the fast approaching conclusion with a really great proj...\",\"Video: 60620397\\u003cbr\\u003eText: Well, that's a fantastic result to have now arrived towards the end of week one and having completed...\",\"Video: 59170093\\u003cbr\\u003eText: I'm delighted to see you again.\\nAs we get started with day three of week three of our adventure and ...\",\"Video: 59473089\\u003cbr\\u003eText: Welcome back.\\nSo hopefully you are still impressed by the GPT four mini results.\\nThe frontier model ...\",\"Video: 60395261\\u003cbr\\u003eText: Let's keep going with our project to equip our LM with a tool.\\nWe just created this piece of code to...\",\"Video: 60617259\\u003cbr\\u003eText: I'm excited to introduce you to your first exercise, and I'm looking forward to seeing what you make...\",\"Video: 59507313\\u003cbr\\u003eText: And it's this time again, when we look at the podium of how our models are performing across the boa...\",\"Video: 60619721\\u003cbr\\u003eText: Now it's time to talk for a minute about tokens.\\nTokens are the individual units which get passed in...\",\"Video: 59295451\\u003cbr\\u003eText: I know that everybody.\\nIt seems like just the other day that we were embarking on our quest together...\",\"Video: 59166919\\u003cbr\\u003eText: And with that, it concludes our session on tools.\\nAnd at this point, you are probably an expert on t...\",\"Video: 59295441\\u003cbr\\u003eText: Okay, so welcome to our leaderboard fast as we go through a ton of essential leaderboards for your\\nc...\",\"Video: 59295541\\u003cbr\\u003eText: And welcome back.\\nYou've just seen GPT four zero spectacularly failed to work on our hard Python con...\",\"Video: 59473101\\u003cbr\\u003eText: Welcome back.\\nSo about ten minutes later, maybe 15 minutes later, the run has completed.\\nAnd how do ...\",\"Video: 59507423\\u003cbr\\u003eText: So you may remember eons ago when we were building our data set.\\nAt the end of that, we uploaded our...\",\"Video: 59295545\\u003cbr\\u003eText: I really hope you've enjoyed this week.\\nWe've got tons done.\\nWe've experimented with all sorts of ne...\",\"Video: 59472503\\u003cbr\\u003eText: Welcome back to Jupyter Lab.\\nLast time, we looked at some silly models for predicting the price of p...\",\"Video: 60614591\\u003cbr\\u003eText: The mantra of this course is that the best way to learn is by doing, and we will be doing stuff toge...\",\"Video: 59473021\\u003cbr\\u003eText: Welcome to our favorite place to be to JupyterLab.\\nHere we are again now in day three.\\nIn week six.\\n...\",\"Video: 60617255\\u003cbr\\u003eText: I'm now going to talk for a bit about models.\\nA term you often hear is the term frontier models, whi...\",\"Video: 59667829\\u003cbr\\u003eText: Well.\\nHello there.\\nLook, I know what you're thinking.\\nYou're thinking I peaked too early.\\nLast week ...\",\"Video: 59505329\\u003cbr\\u003eText: Welcome back.\\nYou may, like me, have just gone off and got a coffee while things loaded back up agai...\",\"Video: 59669049\\u003cbr\\u003eText: So what you just saw was an ephemeral app, as it's called, which means just a temporary app that you...\",\"Video: 60619439\\u003cbr\\u003eText: This now brings us to an extremely important property of LMS called the context window that I want t...\",\"Video: 59668181\\u003cbr\\u003eText: And so it gives me great pleasure to introduce to you the project that I've lined up for you this we...\",\"Video: 59472441\\u003cbr\\u003eText: Welcome back.\\nSo we've been doing the thoroughly distasteful, unsavory work of feature engineering.\\n...\",\"Video: 59507785\\u003cbr\\u003eText: Well, I'm sure you're fed up of me saying that the moment of truth has arrived, but it really has.\\nT...\",\"Video: 59295587\\u003cbr\\u003eText: When I left you, we had just created this simple user interface for converting from Python to C plus...\",\"Video: 59166465\\u003cbr\\u003eText: Welcome back to the JupyterLab on Gradio day, so you'll remember where we left off.\\nWe'd written two...\",\"Video: 59473071\\u003cbr\\u003eText: Hey, gang.\\nLook, I know what you're thinking.\\nThis week was supposed to be training week.\\nI set it a...\",\"Video: 59295423\\u003cbr\\u003eText: Welcome to day two of week four, when we get more into leaderboards so that by the end of this, you'...\",\"Video: 59297723\\u003cbr\\u003eText: So I know what you're thinking.\\nYou're thinking, what's going on here?\\nWe're on day five.\\nWe're on d...\",\"Video: 59166947\\u003cbr\\u003eText: Well, thank you for coming along for week two, day four.\\nWe have lots of good stuff in store today.\\n...\",\"Video: 59666831\\u003cbr\\u003eText: Take one more moment to look at this very nice diagram that lays it all out, and we will move on.\\nNo...\",\"Video: 59295493\\u003cbr\\u003eText: And welcome to week four, day three.\\nAs we are about to embark upon another business project which w...\",\"Video: 60616855\\u003cbr\\u003eText: Now I know what you're thinking.\\nWe've been building environments for so long.\\nAre we not done yet?\\n...\",\"Video: 59506611\\u003cbr\\u003eText: So in a future day, I'm going to be training, fine tuning a model and creating a fine tuned model.\\nA...\",\"Video: 60616493\\u003cbr\\u003eText: I'll just take a quick moment to introduce myself to convince you that I am actually qualified to be...\",\"Video: 59166317\\u003cbr\\u003eText: And welcome to week two, day two, as we continue our adventure into the realm of LMS.\\nUh, so today, ...\",\"Video: 59295439\\u003cbr\\u003eText: So I'm aware that there's a big risk that you are getting fed up of leaderboards, because we've done...\",\"Video: 59472421\\u003cbr\\u003eText: And welcome back to our final time in Jupyter Lab with traditional machine learning.\\nIt's almost ove...\",\"Video: 59472137\\u003cbr\\u003eText: Well, well, well, it's been a long day, but congratulations, you've made it.\\nWe've gone through and ...\",\"Video: 59297693\\u003cbr\\u003eText: So at the end of each week, it's customary for me to give you a challenge, an assignment to do on\\nyo...\",\"Video: 60620143\\u003cbr\\u003eText: So we're going to make a call to GPT four.\\nOh, that's going to ask it to look through a set of links...\",\"Video: 60619501\\u003cbr\\u003eText: I welcome to day four of our time together.\\nThis is a very important day.\\nToday we're going to be lo...\",\"Video: 59297743\\u003cbr\\u003eText: And welcome to day five.\\nFor reals.\\nWe're actually in the proper Jupyter notebook.\\nThis time we're i...\",\"Video: 59166847\\u003cbr\\u003eText: Well, they say that time flies when you're having fun, and it certainly feels like time is flying.\\nU...\",\"Video: 59170223\\u003cbr\\u003eText: Well.\\nFantastic.\\nIt's coming up to the end of the week, and that means it's coming up to a challenge...\",\"Video: 59170037\\u003cbr\\u003eText: So how does it feel to be 30% of the way down the journey to being a proficient LLM engineer?\\nTake a...\",\"Video: 59295609\\u003cbr\\u003eText: You must be feeling absolutely exhausted at this point.\\nAnd if you are, that is okay.\\nYou have done ...\",\"Video: 60619281\\u003cbr\\u003eText: Well, I'm delighted to welcome you to day three of our eight week journey together.\\nAnd today we're ...\",\"Video: 59472429\\u003cbr\\u003eText: And continuing on our strategy to solve commercial problems with LMS, we get to step four, which is\\n...\",\"Video: 59167009\\u003cbr\\u003eText: Welcome back.\\nIt's time to make our full agent framework.\\nI'm super excited about this.\\nIt's pulling...\",\"Video: 59166481\\u003cbr\\u003eText: And here, once more we find ourselves in our favorite place, the Jupyter Lab.\\nReady to go with weeks...\",\"Video: 59670933\\u003cbr\\u003eText: I realized my enthusiasm for this project is a bit insane, but I have to tell you that I am very sat...\",\"Video: 59670073\\u003cbr\\u003eText: Okay, it's time to complete the Rag workflow in our Jupyter Lab on day 2.3.\\nWe've got this function ...\",\"Video: 59673595\\u003cbr\\u003eText: That concludes a mammoth project.\\nThree weeks in the making.\\nIn the course of those three weeks, sta...\",\"Video: 59297603\\u003cbr\\u003eText: And I'm delighted to welcome you back to LM engineering on the day that we turn to vectors.\\nFinally,...\",\"Video: 60614541\\u003cbr\\u003eText: I am delighted to welcome you to the first day of our eight weeks together as you join me on this ad...\",\"Video: 59667357\\u003cbr\\u003eText: Let's now see our results side by side.\\nWe started our journey with a constant model that was at $1....\",\"Video: 59667841\\u003cbr\\u003eText: Now, look, I know that I went through that very fast, but maybe, uh, you're still, uh, blinking\\nat t...\",\"Video: 59472007\\u003cbr\\u003eText: So I hope you enjoyed our first bash at Scrubbing Data, and that you are now looking through the cod...\",\"Video: 59507435\\u003cbr\\u003eText: So I'm now going to talk about five important hyperparameters for the training process.\\nAnd some of ...\",\"Video: 59509185\\u003cbr\\u003eText: So this is where I left you looking at this satisfying chart on training loss and seeing the trainin...\",\"Video: 59473159\\u003cbr\\u003eText: Welcome to Jupyter Lab and welcome to our experiments at the frontier.\\nSo we are going to put our fr...\",\"Video: 60619447\\u003cbr\\u003eText: I want to take a moment to talk about something that's very fundamental to an LLM, which is the numb...\",\"Video: 59166353\\u003cbr\\u003eText: Well, congratulations on leveling up yet again.\\nYou've got some real hard skills that you've added t...\",\"Video: 60619123\\u003cbr\\u003eText: So what we're now going to do is we're going to look at some models in practice and start to compare...\",\"Video: 59295363\\u003cbr\\u003eText: Well, another congratulations moment.\\nYou have 40% on the way to being an LM engineer at a high leve...\",\"Video: 60619289\\u003cbr\\u003eText: And now we'll go a bit faster through the other models.\\nWe'll start with Google's Gemini.\\nI have the...\",\"Video: 59472873\\u003cbr\\u003eText: So it's quite an adventure that we had at the frontier of what's capable with Llms today, solving a\\n...\",\"Video: 60619429\\u003cbr\\u003eText: Let me talk about some other phenomena that have happened over the last few years.\\nOne of them has b...\",\"Video: 59295601\\u003cbr\\u003eText: So it's time to continue our journey into the world of open source and understand which models we sh...\",\"Video: 59170025\\u003cbr\\u003eText: And a massive welcome back one more time to LM engineering.\\nWe are in week three, day two and we are...\",\"Video: 59166443\\u003cbr\\u003eText: And welcome back everybody.\\nWelcome to week two day three.\\nIt's a continuation of our enjoyment of r...\",\"Video: 60620025\\u003cbr\\u003eText: And welcome back to Jupyter Lab, one of my very favorite places to be.\\nWhen Jupyter Lab sprung up on...\",\"Video: 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59166461\\u003cbr\\u003eText: And welcome back to the lab.\\nHere we are in Jupyter Lab and we are going to go into week two.\\nAnd we...\",\"Video: 59167007\\u003cbr\\u003eText: Well, how fabulous is that?\\nI hope that you are as wowed as I am by our new airline, I assistant and...\",\"Video: 59508121\\u003cbr\\u003eText: The moment has arrived.\\nHere we go.\\nWe're in fine tuning.\\nWe do fine tuning.\\nTrain.\\nThere is also a ...\",\"Video: 59295579\\u003cbr\\u003eText: All right.\\nAre you excited to see how this goes?\\nLet's give it a try.\\nSo in this next section, I cre...\",\"Video: 60620375\\u003cbr\\u003eText: And with that, we've reached an important milestone.\\nThe first week of our eight week journey is com...\",\"Video: 59472491\\u003cbr\\u003eText: Welcome back.\\nIf you are following along with me in JupyterLab, as I hope you are, then you will nee...\",\"Video: 59472425\\u003cbr\\u003eText: Welcome to week six, day three.\\nToday is going to be a day that you will either love or you will hat...\",\"Video: 59508057\\u003cbr\\u003eText: Actually slight change in plan.\\nI'm going to wrap up the day.\\nDay three at this point, and say that ...\",\"Video: 60619577\\u003cbr\\u003eText: And for the final piece of background information, I wanted to take another moment to talk about API...\",\"Video: 59170291\\u003cbr\\u003eText: Welcome back to Colab and welcome back to our business project.\\nSo again our assignment, we are due ...\",\"Video: 60619651\\u003cbr\\u003eText: I mentioned before an AI company called vellum.\\nWhen we were talking about the different questions, ...\",\"Video: 59473191\\u003cbr\\u003eText: And you thought we'd never get here.\\nHere we are in Jupyter Lab, running our fine tuning for a front...\",\"Video: 59170297\\u003cbr\\u003eText: And here we are in Google Colab, ready for fun with models.\\nSo first we do the usual Pip installs an...\",\"Video: 59167015\\u003cbr\\u003eText: Welcome back to Jupyter Lab and welcome to Day Five's Lab.\\nAnd this is going to be lots of creativit...\",\"Video: 59170043\\u003cbr\\u003eText: Let me enthusiastically welcome you all back to week three of our LLM engineering journey.\\nIf you en...\",\"Video: 59473147\\u003cbr\\u003eText: Well, I'm very relieved.\\nI've got that behind me.\\nNo more human testing for me.\\nWe'll have one final...\",\"Video: 59166453\\u003cbr\\u003eText: Welcome back and welcome to our continuing JupyterLab experience.\\nUh, I'm hopefully going to keep yo...\",\"Video: 59166915\\u003cbr\\u003eText: Welcome back to the wonderful world of JupyterLab.\\nAnd here we are in week two.\\nDay three.\\nUh, bring...\",\"Video: 59667365\\u003cbr\\u003eText: Here we are back in Colab, looking at the week seven, day five of the Colab notebooks and I'm on a\\nT...\",\"Video: 60616845\\u003cbr\\u003eText: We're on the home stretch.\\nThis is the final step in the environment setup, and it's an easy one.\\nIt...\",\"Video: 59295459\\u003cbr\\u003eText: And welcome back to More Leaderboard Fest as we go through some more leaderboards.\\nBut this time we'...\",\"Video: 59471979\\u003cbr\\u003eText: So we now turn to the parts of the problem, which is perhaps, let's say, not as glamorous as some\\nof...\",\"Video: 59503705\\u003cbr\\u003eText: And so now we talk about quantization the q and q Laura.\\nQ stands for quantized quantized.\\nLaura.\\nAn...\",\"Video: 59472505\\u003cbr\\u003eText: So the good news is that this is the very final video about data set curation.\\nYou were probably fed...\",\"Video: 59669217\\u003cbr\\u003eText: And welcome to the next part of visualizing the data.\\nAnd just very quickly to show it to you in 3D....\",\"Video: 59671221\\u003cbr\\u003eText: I gotta tell you, I don't like to toot my horn a whole lot, but I do think that I've done a great\\njo...\",\"Video: 59503703\\u003cbr\\u003eText: Well.\\nHello there everybody.\\nI am so grateful that you've made it through to the start of week seven...\",\"Video: 59473201\\u003cbr\\u003eText: Well, before we do a postmortem on what happened, let's just quickly look at the standing the rankin...\",\"Video: 60622463\\u003cbr\\u003eText: In this video, we're going to set up a full data science environment for Mac users.\\nIn the next vide...\",\"Video: 60619299\\u003cbr\\u003eText: Well, I hope you found that both educational and enjoyable.\\nAs we went through and learned so much a...\",\"Video: 59295607\\u003cbr\\u003eText: So to revisit then the solution that we built in the previous day and talk about the metrics.\\nAs I s...\",\"Video: 59297575\\u003cbr\\u003eText: Well, welcome to the final part on rag.\\nAnd this is the session where you go from being a rag expert...\",\"Video: 59507687\\u003cbr\\u003eText: It's time for action, everybody.\\nWe've set up our colab.\\nHere we are, week seven, day three.\\nWe've g...\",\"Video: 59671441\\u003cbr\\u003eText: And welcome once more to our favorite place to be Jupyter Lab, the Paradise for a data scientist exp...\",\"Video: 59673431\\u003cbr\\u003eText: And here we have it.\\nThe user interface is completed.\\nThe extra notification came through on my phon...\",\"Video: 59473137\\u003cbr\\u003eText: Let's get straight to it.\\nSo the place where you can see everything that's going on and get knee dee...\",\"Video: 59166421\\u003cbr\\u003eText: Welcome back to the radio day in the lab.\\nMore to do.\\nLet's keep going.\\nWhere we left off is we had ...\",\"Video: 59295599\\u003cbr\\u003eText: Welcome to the Jupyter Lab for day four.\\nIt's going to look very familiar because it's actually I've...\",\"Video: 59669631\\u003cbr\\u003eText: Here we are in our favorite place to be in JupyterLab, ready for some coding and a lot of coding tha...\",\"Video: 59673663\\u003cbr\\u003eText: But wait, there's more.\\nWe need to add some more to the user interface just to make it look more coo...\",\"Video: 59506929\\u003cbr\\u003eText: And we return to the hugging face open LLM leaderboard.\\nThe first place you go when selecting your b...\",\"Video: 59504785\\u003cbr\\u003eText: So at this point we're going to talk about hyperparameters.\\nAnd we're going to introduce three of th...\",\"Video: 59505337\\u003cbr\\u003eText: So we're now going to look at four bit quantization, the rather remarkable effect of reducing the pr...\",\"Video: 59271655\\u003cbr\\u003eText: So here we are on Hugging Face's main landing page at Hugging Face Core.\\nA URL you know.\\nWell, since...\",\"Video: 59472883\\u003cbr\\u003eText: Okay, time to reveal the results.\\nIt has run to completion.\\nAnd here it is.\\nSo a moment to pause.\\nIt...\",\"Video: 59673639\\u003cbr\\u003eText: And welcome now to the code for our user interface, which we will find in this Python module.\\nPrice ...\",\"Video: 59472463\\u003cbr\\u003eText: So last time we looked at a humble linear regression model with feature engineering, and now we say\\n...\",\"Video: 59297595\\u003cbr\\u003eText: So by the time you're watching this, hopefully you have played yourself with vectors.\\nYou've created...\",\"Video: 60619149\\u003cbr\\u003eText: So we're going to start our exploration into the world of frontier models by playing with the famous...\",\"Video: 59297735\\u003cbr\\u003eText: And at last the time has come to see rag in action.\\nAfter all of this talk, and here we are.\\nWe're i...\",\"Video: 60616407\\u003cbr\\u003eText: And now over to my Mac people.\\nAnd I have news for you.\\nIt's exactly the same thing.\\nYou go to a fav...\",\"Video: 59170235\\u003cbr\\u003eText: So here we are in Google Colab for our first collaborative session on the cloud using a GPU box.\\nOn ...\",\"Video: 59472067\\u003cbr\\u003eText: So we've covered steps 1 to 4 of the five step strategy.\\nAnd that brings us to step five, which is p...\",\"Video: 59472011\\u003cbr\\u003eText: Welcome everybody.\\nSo in the past I've said quite a few times, I am excited to start this this week ...\",\"Video: 59295553\\u003cbr\\u003eText: Welcome back.\\nIn the last part, we gave our GPT four and clawed the challenge of converting a simple...\",\"Video: 59297773\\u003cbr\\u003eText: Well, I hope you're eager with anticipation for this session in JupyterLab as we finally get to see\\n...\",\"Video: 59295583\\u003cbr\\u003eText: And here we are back in JupyterLab.\\nIt's been a minute.\\nWe've been working in Colab for last week, a...\",\"Video: 59507329\\u003cbr\\u003eText: Okay.\\nIt's moment of truth time.\\nI have just taken our class tester.\\nYou remember this class?\\nUh, it...\",\"Video: 59295429\\u003cbr\\u003eText: Continuing our investigation of benchmarks, and this will become more real when we actually see some...\",\"Video: 60595637\\u003cbr\\u003eText: Here we are back in the Colab, which has been running overnight for me and probably for you too, I\\nh...\",\"Video: 59668027\\u003cbr\\u003eText: And so here we are at the home page for modal.\\nAt modal.com spelt model not not model which is confu...\",\"Video: 59295527\\u003cbr\\u003eText: I'm so happy to welcome you to week four, day four on our journey to LLM Engineering and Mastery.\\nHe...\",\"Video: 59295377\\u003cbr\\u003eText: Just before we go on to some of the more advanced metrics, I want to mention for a second something\\n...\",\"Video: 59666211\\u003cbr\\u003eText: So before we try our new model and one more recap on the models so far and keep notes of this so we\\n...\",\"Video: 59170107\\u003cbr\\u003eText: And once again, it's that moment when you take a pause and congratulate yourself on another day of\\ns...\",\"Video: 60616833\\u003cbr\\u003eText: So I realized that day one of week one has been a pretty long day, and I assure you that the other,\\n...\",\"Video: 59472413\\u003cbr\\u003eText: Wonderful.\\nWhere we left off is we had just created the Get Features function, which builds our feat...\",\"Video: 59297561\\u003cbr\\u003eText: And would you believe at this point you're 55% of the way along the journey?\\nUh, it's been a while s...\",\"Video: 59669211\\u003cbr\\u003eText: Well, we took on a lot today and we seem to have been successful.\\nThese red icons that you see on th...\",\"Video: 59166981\\u003cbr\\u003eText: Welcome to week two, day five.\\nThe last day of week two where a lot is coming together.\\nI am so grat...\",\"Video: 60619227\\u003cbr\\u003eText: And now let's move to Claude from anthropic, my favorite model and typically the favorite model of\\nm...\",\"Video: 60620395\\u003cbr\\u003eText: Welcome back to Jupyter Lab, where I want to show you the assignment, the homework exercise for you\\n...\",\"Video: 59665127\\u003cbr\\u003eText: Well hi there everybody.\\nI'm not going to give you my usual song and dance about how excited you are...\",\"Video: 59668923\\u003cbr\\u003eText: Well, welcome back to Jupyter Lab for what will be an epic finale to our time in this platform.\\nAnd ...\",\"Video: 59504887\\u003cbr\\u003eText: Well, here we are again in Google Colab.\\nIt's been a minute since we were here, and welcome back to ...\",\"Video: 59170165\\u003cbr\\u003eText: Welcome, everybody to the last day of week three.\\nWeek three.\\nDay five.\\nWe're here already wrapping ...\",\"Video: 60617251\\u003cbr\\u003eText: Congratulations are definitely in order.\\nYesterday was a mammoth first day on this course and you go...\",\"Video: 59166951\\u003cbr\\u003eText: All right, back to the lab.\\nBack to our project.\\nTime to work with tools.\\nI am in the week two folde...\",\"Video: 60619619\\u003cbr\\u003eText: Well, day four was an information dense day.\\nI do hope that you learned some something useful here, ...\",\"Video: 60616663\\u003cbr\\u003eText: Well.\\nHi there, this is time for PC people to get set up.\\nSo all you Mac people out there, you don't...\",\"Video: 59508175\\u003cbr\\u003eText: So I'm taking a moment now to explain that the training costs of optimizing a model for this course\\n...\",\"Video: 59670087\\u003cbr\\u003eText: And welcome to part four of day two of week eight.\\nUh, there's a lot happening this week, and I have...\",\"Video: 59506713\\u003cbr\\u003eText: Hi everyone.\\nSo the reason I'm so fired up about week seven is that this is the time when we actuall...\",\"Video: 60620169\\u003cbr\\u003eText: Hopefully you found this super satisfying to be able to have this nice business result and have it c...\",\"Video: 59295435\\u003cbr\\u003eText: Well, just before we wrap up, let me introduce this week's challenge and talk about what we're going...\",\"Video: 59297609\\u003cbr\\u003eText: Last week, we worked with models that were able to speed up code by a factor of 60,000 times, which\\n...\",\"Video: 59507489\\u003cbr\\u003eText: Continuing our adventure through hyperparameters for training.\\nThe next one is pretty crucial and it...\",\"Video: 59295549\\u003cbr\\u003eText: And welcome back to our challenge again.\\nAnd this time we are working with our beautiful prototype.\\n...\",\"Video: 59665129\\u003cbr\\u003eText: And now let me make this real for you by showing you some, some diagrams, particularly now looking\\na...\",\"Video: 59169991\\u003cbr\\u003eText: Okay, so that was your introduction to Hugging Face.\\nAnd now I'm going to turn to a different resour...\",\"Video: 59472027\\u003cbr\\u003eText: And now the time has come to curate our data set.\\nAnd the way we're going to do this is we're going ...\",\"Video: 59472307\\u003cbr\\u003eText: Welcome to week six.\\nDay two a day.\\nWhen we get back into the data, we look back in anger at our dat...\",\"Video: 59508289\\u003cbr\\u003eText: So here we are now, back in the Colab, in the same one that we kicked off in the previous day.\\nIt's ...\",\"Video: 59472333\\u003cbr\\u003eText: Thank you for putting up with me during my foray into traditional machine learning.\\nI think it was u...\",\"Video: 59295431\\u003cbr\\u003eText: Now I want to take a quick moment to give you a flyby of five different ways that llms are used comm...\",\"Video: 59673449\\u003cbr\\u003eText: Well, I have to tell you that I'm a little bit sad.\\nThis is the beginning of the beginning of the en...\",\"Video: 59669389\\u003cbr\\u003eText: Well.\\nHi there.\\nSo you've made it to day two of week eight, and I am super grateful that you've been...\",\"Video: 59170057\\u003cbr\\u003eText: And so at the beginning of this week, we started by talking about hugging face pipelines.\\nAnd you us...\",\"Video: 59166949\\u003cbr\\u003eText: Welcome back to making chatbots.\\nLet's keep going.\\nSo for the next part we're going to beef up the s...\",\"Video: 59473019\\u003cbr\\u003eText: Welcome back to an action packed time of of training.\\nSo now, after waiting about five minutes when ...\",\"Video: 59297585\\u003cbr\\u003eText: Before we move on, let me show you one more time this fabulous slide that describes the simple three...\",\"Video: 59170255\\u003cbr\\u003eText: And welcome back to us continuing our journey through the model class in Hugging Face Transformers l...\",\"Video: 60614589\\u003cbr\\u003eText: So we're now going to run a large language model directly on your box using a platform called llama,...\",\"Video: 59297601\\u003cbr\\u003eText: I'm not going to lie, at this point you have every reason to be impatient with me.\\nWe've been yammer...\",\"Video: 60616629\\u003cbr\\u003eText: And welcome back to team PC and Team Mac as we come back together again for a quick video.\\nIn this o...\",\"Video: 59297749\\u003cbr\\u003eText: It's always welcome back to JupyterLab, my favorite place to be.\\nAnd now we are, of course in the we...\",\"Video: 59170135\\u003cbr\\u003eText: Welcome.\\nIt's week three.\\nIt's day four.\\nWe are back on the adventure in open source land, back inve...\",\"Video: 59472017\\u003cbr\\u003eText: And this is the first time that we'll be coding against our big project of the course.\\nWelcome to Ju...\",\"Video: 59507017\\u003cbr\\u003eText: Welcome to Colab.\\nWelcome to the week seven day two Colab.\\nAnd just before we try our base model, we...\",\"Video: 60619883\\u003cbr\\u003eText: And now we've arrived at an exciting moment in our first week.\\nThe conclusion of the first week is w...\",\"Video: 59508297\\u003cbr\\u003eText: What more is there to say, really?\\nTomorrow is the day for results.\\nA day that very excited indeed a...\",\"Video: 60619247\\u003cbr\\u003eText: We're going to spend a little bit more time with GPT just to try out a few more interesting things.\\n...\",\"Video: 59504769\\u003cbr\\u003eText: Without further ado, we're going to get stuck into it.\\nTalking about Laura.\\nLow rank adaptation.\\nAnd...\",\"Video: 59170233\\u003cbr\\u003eText: Welcome back to our continued exploits with Tokenizers.\\nWhat we're now going to look at is what's ca...\",\"Video: 59671231\\u003cbr\\u003eText: And here we are back in the Jupyter Lab for the fast approaching conclusion with a really great proj...\",\"Video: 60620397\\u003cbr\\u003eText: Well, that's a fantastic result to have now arrived towards the end of week one and having completed...\",\"Video: 59170093\\u003cbr\\u003eText: I'm delighted to see you again.\\nAs we get started with day three of week three of our adventure and ...\",\"Video: 59473089\\u003cbr\\u003eText: Welcome back.\\nSo hopefully you are still impressed by the GPT four mini results.\\nThe frontier model ...\",\"Video: 60395261\\u003cbr\\u003eText: Let's keep going with our project to equip our LM with a tool.\\nWe just created this piece of code to...\",\"Video: 60617259\\u003cbr\\u003eText: I'm excited to introduce you to your first exercise, and I'm looking forward to seeing what you make...\",\"Video: 59507313\\u003cbr\\u003eText: And it's this time again, when we look at the podium of how our models are performing across the boa...\",\"Video: 60619721\\u003cbr\\u003eText: Now it's time to talk for a minute about tokens.\\nTokens are the individual units which get passed in...\",\"Video: 59295451\\u003cbr\\u003eText: I know that everybody.\\nIt seems like just the other day that we were embarking on our quest together...\",\"Video: 59166919\\u003cbr\\u003eText: And with that, it concludes our session on tools.\\nAnd at this point, you are probably an expert on t...\",\"Video: 59295441\\u003cbr\\u003eText: Okay, so welcome to our leaderboard fast as we go through a ton of essential leaderboards for your\\nc...\",\"Video: 59295541\\u003cbr\\u003eText: And welcome back.\\nYou've just seen GPT four zero spectacularly failed to work on our hard Python con...\",\"Video: 59473101\\u003cbr\\u003eText: Welcome back.\\nSo about ten minutes later, maybe 15 minutes later, the run has completed.\\nAnd how do ...\",\"Video: 59507423\\u003cbr\\u003eText: So you may remember eons ago when we were building our data set.\\nAt the end of that, we uploaded our...\",\"Video: 59295545\\u003cbr\\u003eText: I really hope you've enjoyed this week.\\nWe've got tons done.\\nWe've experimented with all sorts of ne...\",\"Video: 59472503\\u003cbr\\u003eText: Welcome back to Jupyter Lab.\\nLast time, we looked at some silly models for predicting the price of p...\",\"Video: 60614591\\u003cbr\\u003eText: The mantra of this course is that the best way to learn is by doing, and we will be doing stuff toge...\",\"Video: 59473021\\u003cbr\\u003eText: Welcome to our favorite place to be to JupyterLab.\\nHere we are again now in day three.\\nIn week six.\\n...\",\"Video: 60617255\\u003cbr\\u003eText: I'm now going to talk for a bit about models.\\nA term you often hear is the term frontier models, whi...\",\"Video: 59667829\\u003cbr\\u003eText: Well.\\nHello there.\\nLook, I know what you're thinking.\\nYou're thinking I peaked too early.\\nLast week ...\",\"Video: 59505329\\u003cbr\\u003eText: Welcome back.\\nYou may, like me, have just gone off and got a coffee while things loaded back up agai...\",\"Video: 59669049\\u003cbr\\u003eText: So what you just saw was an ephemeral app, as it's called, which means just a temporary app that you...\",\"Video: 60619439\\u003cbr\\u003eText: This now brings us to an extremely important property of LMS called the context window that I want t...\",\"Video: 59668181\\u003cbr\\u003eText: And so it gives me great pleasure to introduce to you the project that I've lined up for you this we...\",\"Video: 59472441\\u003cbr\\u003eText: Welcome back.\\nSo we've been doing the thoroughly distasteful, unsavory work of feature engineering.\\n...\",\"Video: 59507785\\u003cbr\\u003eText: Well, I'm sure you're fed up of me saying that the moment of truth has arrived, but it really has.\\nT...\",\"Video: 59295587\\u003cbr\\u003eText: When I left you, we had just created this simple user interface for converting from Python to C plus...\",\"Video: 59166465\\u003cbr\\u003eText: Welcome back to the JupyterLab on Gradio day, so you'll remember where we left off.\\nWe'd written two...\",\"Video: 59473071\\u003cbr\\u003eText: Hey, gang.\\nLook, I know what you're thinking.\\nThis week was supposed to be training week.\\nI set it a...\",\"Video: 59295423\\u003cbr\\u003eText: Welcome to day two of week four, when we get more into leaderboards so that by the end of this, you'...\",\"Video: 59297723\\u003cbr\\u003eText: So I know what you're thinking.\\nYou're thinking, what's going on here?\\nWe're on day five.\\nWe're on d...\",\"Video: 59166947\\u003cbr\\u003eText: Well, thank you for coming along for week two, day four.\\nWe have lots of good stuff in store today.\\n...\",\"Video: 59666831\\u003cbr\\u003eText: Take one more moment to look at this very nice diagram that lays it all out, and we will move on.\\nNo...\",\"Video: 59295493\\u003cbr\\u003eText: And welcome to week four, day three.\\nAs we are about to embark upon another business project which w...\",\"Video: 60616855\\u003cbr\\u003eText: Now I know what you're thinking.\\nWe've been building environments for so long.\\nAre we not done yet?\\n...\",\"Video: 59506611\\u003cbr\\u003eText: So in a future day, I'm going to be training, fine tuning a model and creating a fine tuned model.\\nA...\",\"Video: 60616493\\u003cbr\\u003eText: I'll just take a quick moment to introduce myself to convince you that I am actually qualified to be...\",\"Video: 59166317\\u003cbr\\u003eText: And welcome to week two, day two, as we continue our adventure into the realm of LMS.\\nUh, so today, ...\",\"Video: 59295439\\u003cbr\\u003eText: So I'm aware that there's a big risk that you are getting fed up of leaderboards, because we've done...\",\"Video: 59472421\\u003cbr\\u003eText: And welcome back to our final time in Jupyter Lab with traditional machine learning.\\nIt's almost ove...\",\"Video: 59472137\\u003cbr\\u003eText: Well, well, well, it's been a long day, but congratulations, you've made it.\\nWe've gone through and ...\",\"Video: 59297693\\u003cbr\\u003eText: So at the end of each week, it's customary for me to give you a challenge, an assignment to do on\\nyo...\",\"Video: 60620143\\u003cbr\\u003eText: So we're going to make a call to GPT four.\\nOh, that's going to ask it to look through a set of links...\",\"Video: 60619501\\u003cbr\\u003eText: I welcome to day four of our time together.\\nThis is a very important day.\\nToday we're going to be lo...\",\"Video: 59297743\\u003cbr\\u003eText: And welcome to day five.\\nFor reals.\\nWe're actually in the proper Jupyter notebook.\\nThis time we're i...\",\"Video: 59166847\\u003cbr\\u003eText: Well, they say that time flies when you're having fun, and it certainly feels like time is flying.\\nU...\",\"Video: 59170223\\u003cbr\\u003eText: Well.\\nFantastic.\\nIt's coming up to the end of the week, and that means it's coming up to a challenge...\",\"Video: 59170037\\u003cbr\\u003eText: So how does it feel to be 30% of the way down the journey to being a proficient LLM engineer?\\nTake a...\",\"Video: 59295609\\u003cbr\\u003eText: You must be feeling absolutely exhausted at this point.\\nAnd if you are, that is okay.\\nYou have done ...\",\"Video: 60619281\\u003cbr\\u003eText: Well, I'm delighted to welcome you to day three of our eight week journey together.\\nAnd today we're ...\",\"Video: 59472429\\u003cbr\\u003eText: And continuing on our strategy to solve commercial problems with LMS, we get to step four, which is\\n...\",\"Video: 59167009\\u003cbr\\u003eText: Welcome back.\\nIt's time to make our full agent framework.\\nI'm super excited about this.\\nIt's pulling...\",\"Video: 59166481\\u003cbr\\u003eText: And here, once more we find ourselves in our favorite place, the Jupyter Lab.\\nReady to go with weeks...\",\"Video: 59670933\\u003cbr\\u003eText: I realized my enthusiasm for this project is a bit insane, but I have to tell you that I am very sat...\",\"Video: 59670073\\u003cbr\\u003eText: Okay, it's time to complete the Rag workflow in our Jupyter Lab on day 2.3.\\nWe've got this function ...\",\"Video: 59673595\\u003cbr\\u003eText: That concludes a mammoth project.\\nThree weeks in the making.\\nIn the course of those three weeks, sta...\",\"Video: 59297603\\u003cbr\\u003eText: And I'm delighted to welcome you back to LM engineering on the day that we turn to vectors.\\nFinally,...\",\"Video: 60614541\\u003cbr\\u003eText: I am delighted to welcome you to the first day of our eight weeks together as you join me on this ad...\",\"Video: 59667357\\u003cbr\\u003eText: Let's now see our results side by side.\\nWe started our journey with a constant model that was at $1....\",\"Video: 59667841\\u003cbr\\u003eText: Now, look, I know that I went through that very fast, but maybe, uh, you're still, uh, blinking\\nat t...\",\"Video: 59472007\\u003cbr\\u003eText: So I hope you enjoyed our first bash at Scrubbing Data, and that you are now looking through the cod...\",\"Video: 59507435\\u003cbr\\u003eText: So I'm now going to talk about five important hyperparameters for the training process.\\nAnd some of ...\",\"Video: 59509185\\u003cbr\\u003eText: So this is where I left you looking at this satisfying chart on training loss and seeing the trainin...\",\"Video: 59473159\\u003cbr\\u003eText: Welcome to Jupyter Lab and welcome to our experiments at the frontier.\\nSo we are going to put our fr...\",\"Video: 60619447\\u003cbr\\u003eText: I want to take a moment to talk about something that's very fundamental to an LLM, which is the numb...\",\"Video: 59166353\\u003cbr\\u003eText: Well, congratulations on leveling up yet again.\\nYou've got some real hard skills that you've added t...\",\"Video: 60619123\\u003cbr\\u003eText: So what we're now going to do is we're going to look at some models in practice and start to compare...\",\"Video: 59295363\\u003cbr\\u003eText: Well, another congratulations moment.\\nYou have 40% on the way to being an LM engineer at a high leve...\",\"Video: 60619289\\u003cbr\\u003eText: And now we'll go a bit faster through the other models.\\nWe'll start with Google's Gemini.\\nI have the...\",\"Video: 59472873\\u003cbr\\u003eText: So it's quite an adventure that we had at the frontier of what's capable with Llms today, solving a\\n...\",\"Video: 60619429\\u003cbr\\u003eText: Let me talk about some other phenomena that have happened over the last few years.\\nOne of them has b...\",\"Video: 59295601\\u003cbr\\u003eText: So it's time to continue our journey into the world of open source and understand which models we sh...\",\"Video: 59170025\\u003cbr\\u003eText: And a massive welcome back one more time to LM engineering.\\nWe are in week three, day two and we are...\",\"Video: 59166443\\u003cbr\\u003eText: And welcome back everybody.\\nWelcome to week two day three.\\nIt's a continuation of our enjoyment of r...\",\"Video: 60620025\\u003cbr\\u003eText: And welcome back to Jupyter Lab, one of my very favorite places to be.\\nWhen Jupyter Lab sprung up on...\",\"Video: 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        "                            \n",
-       "var gd = document.getElementById('6e775494-6bdd-4cf4-ab4f-18f0e647109b');\n",
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@@ -4174,6 +4174,14 @@
    "metadata": {},
    "outputs": [],
    "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "1440654f-590f-4781-bd1c-abfc6ca6edf1",
+   "metadata": {},
+   "outputs": [],
+   "source": []
   }
  ],
  "metadata": {