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Dataset results
517 results for “October”
SG - October 2024
<p>Measurements of SG (Global) in October 2024</p> <p></p><p> Light Pollution Laboratorie <a href="https://data.eelabs.eu/api/lpls/SG">info</a></p>
LPL5 - October 2024
<p>Measurements of LPL5 (Tejeda) in October 2024</p> <p>Gran Canaria</p><p> Light Pollution Laboratorie <a href="https://data.eelabs.eu/api/lpls/LPL5">info</a></p>
An undescribed species of Dimitshydrus sp., resting underwater. Photographed by Yanagi in the Shikoku region on October 29, 2024.
<p>Supplement of : Yanagi & Akita, 2025. Discovery of the Larva of Morimotoa gigantea S. Uéno, 1996 (Coleoptera, Dytiscidae, Hydroporinae) from Kochi, Shikoku, Japan, with Ecological Knowledge of Japanese Subterranean Diving Beetles. Gekkan-Mushi: A Monthly Journal of Entomology (647): 40-50.</p> <p>Supplementary information, Photo S2</p>
Fig. 1 in Abstracts of the Immature Beetles Meeting 2019 October 3-4, Prague, Czech Republic
Fig. 1. Most participants of the Immature Beetles Meeting 2019 during the
FIG. 3. — Paraduslia talimaae n. gen., n in Arthropods from the Lower Devonian Severnaya Zemlya Formation of October Revolution Island (Russia)
FIG. 3. — Paraduslia talimaae n. gen., n. sp.; A, No. 35/701, 18 × 9 mm; B, No. 35/703, 20 × 16 mm.
epicPCR sequencing data, October 20th
<p>Samples:</p> <p>Rhodo100dilWWMocksBC10e8SM16S<br> Rhodo100dilWWMocksBC10e8SM16S<br> Rhodo100dilWWMocksBC10e8SM18S<br> Rhodo100dilWWMocksBC10e8SM18S<br> Rhodo10dilWWMocksBC10e8SM16S<br> Rhodo10dilWWMocksBC10e8SM16S<br> Rhodo10dilWWMocksBC10e8SM18S<br> Rhodo10dilWWMocksBC10e8SM18S<br> RhodoMocksBC10e7MC16S<br> RhodoMocksBC10e7MC16S<br> RhodoMocksBC10e7MC18S<br> RhodoMocksBC10e7MC18S<br> RhodoMocksBC10e8SM16S<br> RhodoMocksBC10e8SM16S<br> RhodoMocksBC10e8SM18S<br> RhodoMocksBC10e8SM18S<br> RhodoNoMocksBC10e7MC16S<br> RhodoNoMocksBC10e7MC16S<br> RhodoNoMocksBC10e7MC18S<br> RhodoNoMocksBC10e7MC18S<br> RhodoWWMocksBC10e8SM16S<br> RhodoWWMocksBC10e8SM16S<br> RhodoWWMocksBC10e8SM18S<br> RhodoWWMocksBC10e8SM18S<br> WWMocksBC10e7MC16S<br> WWMocksBC10e7MC16S<br> WWMocksBC10e7MC18S<br> WWMocksBC10e7MC18S<br> WWMocksBC10e8SM16S<br> WWMocksBC10e8SM16S<br> WWMocksBC10e8SM18S<br> WWMocksBC10e8SM18S<br> WWNoMocksBC10e7MC16S<br> WWNoMocksBC10e7MC16S<br> WWNoMocksBC10e7MC18S<br> WWNoMocksBC10e7MC18S</p>
SOUNDEPTH - Bibliography (Update October 2025)
<p>This file features a comprehensive bibliography of sources and studies related to my MSCA research project (Horizon 2020 – MGA MSCA-IF – Grant agreement No. 101019781 – SOUNDEPTH).</p>
Readme files in 16,000,000 public GitHub repositories (October 2016)
<p>Format</p> <p>index.csv.gz - CSV comma separated file with 3 columns: <repository name>, <flag>,<readme file name> For example: src-d/go-git,s,README.md</p> <p>The flag is either "s" (readme found) or "r" (readme does not exist on the root directory level). Readme file name may be any from the list:</p> <p>"README.md", "readme.md", "Readme.md", "README.MD", "README.txt", "readme.txt", "Readme.txt", "README.TXT", "README", "readme", "Readme", "README.rst", "readme.rst", "Readme.rst", "README.RST"</p> <p>100 part-r-00xxx files are in "new" Hadoop API format with the following settings:</p> <ol> <li> <p>inputFormatClass is org.apache.hadoop.mapreduce.lib.output.SequenceFileOutputFormat</p> </li> <li> <p>keyClass is org.apache.hadoop.io.Text - repository name</p> </li> <li> <p>valueClass is org.apache.hadoop.io.BytesWritable - gzipped readme file</p> </li> </ol>
Sets of mutually similar public GitHub repositories (October 2016)
<p>The format is JSON, the list of lists. Each list is the group of very similar repositories (Weighted Jaccard Similarity threshold 0.8~0.9).</p>
Programming language keyword frequencies extracted from 16,000,000 public GitHub repositories (October 2016)
<p>Origin</p> <p>16,000,000 repositories on GitHub as of October 2016, classified with github/linguist and parsed with Pygments. Token.Keyword tokens were filtered and MapReduce-d. Fuzzy duplicate repositories were discarded.</p> <p>Some languages, e.g. Haskell, are parsed wrong, resulting in <strong>many</strong> keywords. Still they were not removed since we are not familiar with such languages.</p> <p>Format</p> <p>Triples [language name]\t[keyword]\t[frequency]</p> <p>Tabs and new lines in keywords are escaped as \t and \n respectively.</p>
PERTEMUAN 9_ 1 OCTOBER 2022, PENGENDALIAN BAHAN BAKU_AKUNTANSI BIAYA_UNIVERSITAS GRESIK
<p><strong>Capaian Pembelajaran Mata Kuliah (CPMK)</strong></p> <p><strong>Setelah</strong><strong> </strong><strong>megikuti</strong><strong> </strong><strong>perkuliahan</strong><strong> </strong><strong>ini</strong><strong> </strong><strong>mahasiswa</strong><strong> </strong><strong>mampu</strong><strong> </strong><strong>mengetahui</strong><strong> </strong><strong>dan</strong><strong> </strong><strong>menghitung</strong><strong> </strong><strong>pengendalian</strong><strong>: </strong><strong>biaya</strong><strong> </strong><strong>bahan</strong><strong> </strong><strong>baku</strong></p> <p> </p> <p><strong>Indikator</strong><strong> </strong><strong>Pembelajaran</strong><strong>:</strong></p> <p><strong>1. </strong><strong>Karakteristik</strong><strong> </strong><strong>bahan</strong><strong> </strong><strong>baku</strong></p> <p><strong>2. </strong><strong>Pembelian</strong><strong> </strong><strong>bahan</strong><strong> </strong><strong>baku</strong></p> <p><strong>3. </strong><strong>Penilaian</strong><strong> </strong><strong>persediaann</strong><strong> </strong><strong>akhir</strong></p> <p><strong>4. </strong><strong>Metode</strong><strong> </strong><strong>penilaian</strong><strong> </strong><strong>persediaan</strong><strong> </strong><strong>bahan</strong><strong> </strong><strong>baku</strong></p> <p><strong>5. </strong><strong>Latihan</strong><strong> </strong><strong>kasus</strong><strong> </strong></p> <p> </p> <p> </p>
LPL14 - October 2022
<p>Measurements of LPL14 (Ilha das Flores) in October 2022</p> <p>Flores</p><p> Light Pollution Laboratorie <a href="https://data.eelabs.eu/api/lpls/LPL14">info</a></p>
LPL12 - October 2022
<p>Measurements of LPL12 (Ilhas Desertas) in October 2022</p> <p>Madeira</p><p> Light Pollution Laboratorie <a href="https://data.eelabs.eu/api/lpls/LPL12">info</a></p>
LPL17 - October 2022
<p>Measurements of LPL17 (Isla de Tabarca) in October 2022</p> <p>Alicante</p><p> Light Pollution Laboratorie <a href="https://data.eelabs.eu/api/lpls/LPL17">info</a></p>
LPL8 - October 2022
<p>Measurements of LPL8 (Timanfaya NP) in October 2022</p> <p>Lanzarote</p><p> Light Pollution Laboratorie <a href="https://data.eelabs.eu/api/lpls/LPL8">info</a></p>
LPL4 - October 2022
<p>Measurements of LPL4 (Ilha do Corvo) in October 2022</p> <p>Corvo</p><p> Light Pollution Laboratorie <a href="https://data.eelabs.eu/api/lpls/LPL4">info</a></p>
SG - October 2022
<p>Measurements of SG (Global) in October 2022</p> <p></p><p> Light Pollution Laboratorie <a href="https://data.eelabs.eu/api/lpls/SG">info</a></p>
LPL3 - October 2022
<p>Measurements of LPL3 (Madeira East Coast) in October 2022</p> <p>Madeira</p><p> Light Pollution Laboratorie <a href="https://data.eelabs.eu/api/lpls/LPL3">info</a></p>
LPL5 - October 2022
<p>Measurements of LPL5 (Tejeda) in October 2022</p> <p>Gran Canaria</p><p> Light Pollution Laboratorie <a href="https://data.eelabs.eu/api/lpls/LPL5">info</a></p>
LPL1 - October 2022
<p>Measurements of LPL1 (Teide NP) in October 2022</p> <p>Tenerife</p><p> Light Pollution Laboratorie <a href="https://data.eelabs.eu/api/lpls/LPL1">info</a></p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.