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README.md
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---
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license: cc-by-3.0
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---
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| 1 |
---
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license: cc-by-3.0
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---
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+
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+
This is the YODAS manual/automatic subset from our YODAS dataset, it has 369,510 hours of speech.
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This dataset contains audio utterances and corresponding captions (manual or automatic) from YouTube. Note that manual caption only indicates that it is uploaded by users, but not necessarily transcribed by a human
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## Usage:
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Considering the extremely large size of the entire dataset, we support two modes of dataset loadings:
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**standard mode**: each subset will be downloaded to the local dish before first iterating.
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```python
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from datasets import load_dataset
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# Note this will take very long time to download and preprocess
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# you can try small subset for testing purpose
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ds = load_dataset('espnet/yodas', 'en000')
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print(next(iter(ds['train'])))
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```
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**streaming mode** most of the files will be streamed instead of downloaded to your local deivce. It can be used to inspect this dataset quickly.
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```python
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from datasets import load_dataset
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# this streaming loading will finish quickly
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ds = load_dataset('espnet/yodas', 'en000', streaming=True)
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#{'id': '9774', 'utt_id': 'YoRjzEnRcqu-00000-00000716-00000819', 'audio': {'path': None, 'array': array([-0.009552 , -0.01086426, -0.012146 , ..., -0.01992798,
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# -0.01885986, -0.01074219]), 'sampling_rate': 16000}, 'text': 'There is a saying'}
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print(next(iter(ds['train'])))
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```
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## Subsets/Shards
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There are 149 languages in this dataset, each language is sharded into at least 1 shard to make it easy for our processing and uploading purposes. The raw data of each shard contains 500G at most.
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Statistics of each shard can be found in the last section.
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We distinguish manual caption subset and automatic caption subset by the first digit in each shard's name. The first digit is 0 if it contains manual captions, 1 if it contains automatic captions.
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For example, `en000` to `en005` are the English shards containing manual subsets, and `en100` to `en127` contains the automatic subsets.
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## Contact
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If you have any questions, feel free to contact us at the following email address.
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We made sure that our dataset only consisted of videos with CC licenses during our downloading. But in case you find your video unintentionally included in our dataset and would like to delete it, you can send a delete request to the following email.
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`xinjianl@cs.cmu.edu`
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## Statistics
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Note that there are no overlappings across different subsets, each audio can be included in the dataset at most once.
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| Subset name | Hours |
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|------|--------|
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| 66 |
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|aa000|0.171472|
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| 67 |
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|ab000|0.358342|
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| 68 |
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|af000|0.880497|
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| 69 |
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|ak000|0.250858|
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| 70 |
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|am000|0.924708|
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| 71 |
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|ar000|289.707|
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| 72 |
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|as000|0.548239|
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| 73 |
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|ay000|0.0342722|
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| 74 |
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|az000|3.8537|
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| 75 |
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|ba000|0.0210556|
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| 76 |
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|be000|48.1537|
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| 77 |
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|bg000|46.8375|
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| 78 |
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|bh000|0.0127111|
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| 79 |
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|bi000|0.0125556|
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| 80 |
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|bm000|0.00214722|
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| 81 |
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|bn000|27.064|
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| 82 |
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|bo000|0.746211|
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| 83 |
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|br000|0.729914|
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| 84 |
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|bs000|9.36959|
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| 85 |
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|ca000|74.1909|
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| 86 |
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|co000|0.0418639|
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| 87 |
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|cr000|0.00584167|
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| 88 |
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|cs000|167.604|
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| 89 |
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|cy000|5.20017|
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| 90 |
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|da000|27.4345|
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| 91 |
+
|de000|3063.81|
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| 92 |
+
|de100|4998.11|
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| 93 |
+
|de101|4995.08|
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| 94 |
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|de102|955.389|
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| 95 |
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|dz000|0.06365|
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| 96 |
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|ee000|0.0411722|
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| 97 |
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|el000|126.75|
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| 98 |
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|en000|4999.73|
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| 99 |
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|en001|5032.69|
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| 100 |
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|en002|5039.9|
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| 101 |
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|en003|5001.4|
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| 102 |
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|en004|5054.66|
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| 103 |
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|en005|4027.02|
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| 104 |
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|en100|5147.07|
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| 105 |
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|en101|5123.05|
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| 106 |
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|en102|5117.68|
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| 107 |
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|en103|5127.3|
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| 108 |
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|en104|5126.33|
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| 109 |
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|en105|5097.65|
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| 110 |
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|en106|5131.47|
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| 111 |
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|en107|5135.6|
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| 112 |
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|en108|5136.84|
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| 113 |
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|en109|5112.94|
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| 114 |
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|en110|5109|
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| 115 |
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|en111|5118.69|
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| 116 |
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|en112|5122.57|
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| 117 |
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|en113|5122.31|
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| 118 |
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|en114|5112.36|
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| 119 |
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|en115|5112.27|
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| 120 |
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|en116|5123.77|
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| 121 |
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|en117|5117.31|
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| 122 |
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|en118|5117.94|
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| 123 |
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|en119|5133.05|
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| 124 |
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|en120|5127.79|
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| 125 |
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|en121|5129.08|
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| 126 |
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|en122|5130.22|
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| 127 |
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|en123|5097.56|
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| 128 |
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|en124|5116.59|
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| 129 |
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|en125|5109.76|
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| 130 |
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|en126|5136.21|
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| 131 |
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|en127|2404.89|
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| 132 |
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|eo000|12.6874|
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| 133 |
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|es000|3737.86|
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| 134 |
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|es100|5125.25|
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| 135 |
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|es101|5130.44|
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| 136 |
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|es102|5145.66|
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| 137 |
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|es103|5138.26|
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| 138 |
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|es104|5139.57|
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| 139 |
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|es105|5138.95|
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| 140 |
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|es106|2605.26|
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| 141 |
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|et000|14.4129|
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| 142 |
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|eu000|19.6356|
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| 143 |
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|fa000|42.6734|
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| 144 |
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|ff000|0.0394972|
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| 145 |
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|fi000|212.899|
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| 146 |
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|fj000|0.0167806|
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| 147 |
+
|fo000|0.183244|
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| 148 |
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|fr000|2423.7|
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| 149 |
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|fr100|5074.93|
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| 150 |
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|fr101|5057.79|
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| 151 |
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|fr102|5094.14|
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| 152 |
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|fr103|3222.95|
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| 153 |
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|fy000|0.0651667|
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| 154 |
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|ga000|1.49252|
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| 155 |
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|gd000|0.01885|
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| 156 |
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|gl000|9.52575|
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| 157 |
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|gn000|0.181356|
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| 158 |
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|gu000|1.99355|
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| 159 |
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|ha000|0.102931|
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| 160 |
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|hi000|480.79|
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| 161 |
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|hi100|2.74865|
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| 162 |
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|ho000|0.0562194|
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| 163 |
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|hr000|25.9171|
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| 164 |
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|ht000|1.07494|
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| 165 |
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|hu000|181.763|
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| 166 |
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|hy000|1.64412|
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| 167 |
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|ia000|0.0856056|
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| 168 |
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|id000|1420.09|
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| 169 |
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|id100|4902.79|
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| 170 |
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|id101|3560.82|
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| 171 |
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|ie000|0.134603|
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| 172 |
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|ig000|0.086875|
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| 173 |
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|ik000|0.00436667|
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| 174 |
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|is000|5.07075|
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| 175 |
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|it000|1454.98|
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| 176 |
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|it100|4989.62|
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| 177 |
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|it101|4242.87|
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| 178 |
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|iu000|0.0584278|
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| 179 |
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|iw000|161.373|
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| 180 |
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|ja000|1094.18|
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| 181 |
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|ja100|2929.94|
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| 182 |
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|jv000|1.08701|
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| 183 |
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|ka000|26.9727|
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| 184 |
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|ki000|0.000555556|
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| 185 |
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|kk000|3.72081|
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| 186 |
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|kl000|0.00575556|
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| 187 |
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|km000|3.98273|
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| 188 |
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|kn000|2.36041|
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| 189 |
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|ko000|2774.28|
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| 190 |
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|ko100|5018.29|
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| 191 |
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|ko101|5048.49|
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| 192 |
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|ko102|5018.27|
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| 193 |
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|ko103|2587.85|
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| 194 |
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|ks000|0.0150444|
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| 195 |
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|ku000|1.93419|
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| 196 |
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|ky000|14.3917|
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| 197 |
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|la000|7.26088|
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| 198 |
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|lb000|0.1115|
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| 199 |
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|lg000|0.00386111|
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| 200 |
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|ln000|0.188739|
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| 201 |
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|lo000|0.230986|
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|lt000|17.6507|
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| 203 |
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|lv000|2.47671|
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| 204 |
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|mg000|0.169653|
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| 205 |
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|mi000|1.10089|
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| 206 |
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|mk000|5.54236|
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| 207 |
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|ml000|13.2386|
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| 208 |
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|mn000|2.0232|
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| 209 |
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|mr000|7.11602|
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| 210 |
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|ms000|28.0219|
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| 211 |
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|my000|2.35663|
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| 212 |
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|na000|0.0397056|
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| 213 |
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|nd000|0.00111111|
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| 214 |
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|ne000|2.34936|
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| 215 |
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|nl000|413.044|
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| 216 |
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|nl100|2490.13|
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| 217 |
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|no000|129.183|
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| 218 |
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|nv000|0.00319444|
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| 219 |
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|oc000|0.166108|
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| 220 |
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|om000|0.148478|
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| 221 |
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|or000|0.421436|
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| 222 |
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|pa000|1.58188|
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| 223 |
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|pl000|757.986|
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| 224 |
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|ps000|0.9871|
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| 225 |
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|pt000|1631.44|
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|pt100|5044.57|
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|pt101|5038.33|
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| 228 |
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|pt102|5041.59|
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| 229 |
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|pt103|3553.28|
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| 230 |
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|qu000|0.748772|
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| 231 |
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|rm000|0.192933|
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| 232 |
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|rn000|0.00401111|
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| 233 |
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|ro000|99.9175|
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| 234 |
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|ru000|4968.37|
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| 235 |
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|ru001|627.679|
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| 236 |
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|ru100|5098.3|
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|ru101|5098|
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|ru102|5119.43|
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| 239 |
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|ru103|5107.29|
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|ru104|5121.73|
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| 241 |
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|ru105|5088.05|
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|ru106|3393.44|
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| 243 |
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|rw000|0.640825|
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| 244 |
+
|sa000|0.354139|
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| 245 |
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|sc000|0.00801111|
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| 246 |
+
|sd000|0.0768722|
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| 247 |
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|sg000|0.000472222|
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| 248 |
+
|sh000|0.250914|
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| 249 |
+
|si000|4.2634|
|
| 250 |
+
|sk000|30.0155|
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| 251 |
+
|sl000|22.9366|
|
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| 253 |
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| 254 |
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| 255 |
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| 256 |
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| 257 |
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| 258 |
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| 259 |
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| 260 |
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| 261 |
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| 262 |
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| 263 |
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| 264 |
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| 265 |
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| 266 |
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| 267 |
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| 268 |
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| 269 |
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| 270 |
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| 271 |
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| 272 |
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| 273 |
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| 274 |
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| 275 |
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| 276 |
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| 277 |
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| 278 |
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| 279 |
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| 280 |
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| 281 |
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| 282 |
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| 283 |
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| 284 |
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| 285 |
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| 286 |
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| 287 |
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| 288 |
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| 289 |
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