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412 results for โSeptemberโ
PheKnowLator Human Disease KG Benchmarks: Instance-Standard Relations-OWL (v2.1.0 - September 2021)
<p><strong>PKT Human Disease Knowledge Graph Benchmark Builds (v2.1.0)</strong></p><p><strong>Build Type: </strong><i>Instance-Standard Relations-OWL</i></p><p><strong>Build Date: </strong>September 01, 2021</p><p> </p><h3><strong>Important Build Information</strong></h3><p>The benchmarks were originally built and stored using Google Cloud Platform (GCP) resources. For details and a complete description of this process, can be found on GitHub (<a href="https://github.com/callahantiff/PheKnowLator/tree/master/builds#readme">here</a>). Note that we have developed an archive for the builds on Zenodo. While the original GCP resources contained all associated files, due to the file size upload limits associated with each archive, we have limited the uploaded files to the KGs, associated metadata, and log files. The list of resources, including their URLs, and date of download, can all be found in the associated logs.</p><p>Details on each of the files generated by the build process can be found in the file associated with this directory (<a href="https://zenodo.org/records/10065431/files/PheKnowLator_HumanDiseaseKG_Output_FileInformation.xlsx?download=1">PheKnowLator_HumanDiseaseKG_Output_FileInformation.xlsx</a>).</p><p> </p><p>๐จ <strong>AVAILABLE FILES </strong>๐จ </p><ul><li>Available KG benchmark files are zipped and listed below.</li><li>For additional details on what each file contains, please see the associated Wiki page ๐ <a href="https://github.com/callahantiff/PheKnowLator/wiki/September-01%2C-2021">here</a>.</li></ul>
PheKnowLator Human Disease KG Benchmarks: Class-Inverse Relations-OWLNETS (v2.1.0 - September 2021)
<p><strong>PKT Human Disease Knowledge Graph Benchmark Builds (v2.1.0)</strong></p><p><strong>Build Type: </strong><i>Class-Inverse Relations-OWLNETS</i></p><p><strong>Build Date: </strong>September 01, 2021</p><p> </p><h3><strong>Important Build Information</strong></h3><p>The benchmarks were originally built and stored using Google Cloud Platform (GCP) resources. For details and a complete description of this process, can be found on GitHub (<a href="https://github.com/callahantiff/PheKnowLator/tree/master/builds#readme">here</a>). Note that we have developed an archive for the builds on Zenodo. While the original GCP resources contained all associated files, due to the file size upload limits associated with each archive, we have limited the uploaded files to the KGs, associated metadata, and log files. The list of resources, including their URLs, and date of download, can all be found in the associated logs.</p><p>Details on each of the files generated by the build process can be found in the file associated with this directory (<a href="https://zenodo.org/records/10065431/files/PheKnowLator_HumanDiseaseKG_Output_FileInformation.xlsx?download=1">PheKnowLator_HumanDiseaseKG_Output_FileInformation.xlsx</a>).</p><p> </p><p>๐จ <strong>AVAILABLE FILES </strong>๐จ </p><ul><li>Available KG benchmark files are zipped and listed below.</li><li>For additional details on what each file contains, please see the associated Wiki page ๐ <a href="https://github.com/callahantiff/PheKnowLator/wiki/September-01%2C-2021">here</a>.</li></ul>
PheKnowLator Human Disease KG Benchmarks: Instance-Inverse Relations-OWL (v2.1.0 - September 2021)
<p><strong>PKT Human Disease Knowledge Graph Benchmark Builds (v2.1.0)</strong></p><p><strong>Build Type: </strong><i>Instance-Inverse Relations-OWL</i></p><p><strong>Build Date: </strong>September 01, 2021</p><p> </p><h3><strong>Important Build Information</strong></h3><p>The benchmarks were originally built and stored using Google Cloud Platform (GCP) resources. For details and a complete description of this process, can be found on GitHub (<a href="https://github.com/callahantiff/PheKnowLator/tree/master/builds#readme">here</a>). Note that we have developed an archive for the builds on Zenodo. While the original GCP resources contained all associated files, due to the file size upload limits associated with each archive, we have limited the uploaded files to the KGs, associated metadata, and log files. The list of resources, including their URLs, and date of download, can all be found in the associated logs.</p><p>Details on each of the files generated by the build process can be found in the file associated with this directory (<a href="https://zenodo.org/records/10065431/files/PheKnowLator_HumanDiseaseKG_Output_FileInformation.xlsx?download=1">PheKnowLator_HumanDiseaseKG_Output_FileInformation.xlsx</a>).</p><p> </p><p>๐จ <strong>AVAILABLE FILES </strong>๐จ </p><ul><li>Available KG benchmark files are zipped and listed below.</li><li>For additional details on what each file contains, please see the associated Wiki page ๐ <a href="https://github.com/callahantiff/PheKnowLator/wiki/September-01%2C-2021">here</a>.</li></ul>
PheKnowLator Human Disease KG Benchmarks: Instance-Standard Relations-OWLNETS (v2.1.0 - September 2021)
<p><strong>PKT Human Disease Knowledge Graph Benchmark Builds (v2.1.0)</strong></p><p><strong>Build Type: </strong><i>Instance-Standard Relations-OWLNETS</i></p><p><strong>Build Date: </strong>September 01, 2021</p><p> </p><h3><strong>Important Build Information</strong></h3><p>The benchmarks were originally built and stored using Google Cloud Platform (GCP) resources. For details and a complete description of this process, can be found on GitHub (<a href="https://github.com/callahantiff/PheKnowLator/tree/master/builds#readme">here</a>). Note that we have developed an archive for the builds on Zenodo. While the original GCP resources contained all associated files, due to the file size upload limits associated with each archive, we have limited the uploaded files to the KGs, associated metadata, and log files. The list of resources, including their URLs, and date of download, can all be found in the associated logs.</p><p>Details on each of the files generated by the build process can be found in the file associated with this directory (<a href="https://zenodo.org/records/10065431/files/PheKnowLator_HumanDiseaseKG_Output_FileInformation.xlsx?download=1">PheKnowLator_HumanDiseaseKG_Output_FileInformation.xlsx</a>).</p><p> </p><p>๐จ <strong>AVAILABLE FILES </strong>๐จ </p><ul><li>Available KG benchmark files are zipped and listed below.</li><li>For additional details on what each file contains, please see the associated Wiki page ๐ <a href="https://github.com/callahantiff/PheKnowLator/wiki/September-01%2C-2021">here</a>.</li></ul>
PheKnowLator Human Disease KG Benchmarks: Instance-Inverse Relations-OWLNETS (v2.1.0 - September 2021)
<p><strong>PKT Human Disease Knowledge Graph Benchmark Builds (v2.1.0)</strong></p><p><strong>Build Type: </strong><i>Instance-Inverse Relations-OWLNETS</i></p><p><strong>Build Date: </strong>September 01, 2021</p><p> </p><h3><strong>Important Build Information</strong></h3><p>The benchmarks were originally built and stored using Google Cloud Platform (GCP) resources. For details and a complete description of this process, can be found on GitHub (<a href="https://github.com/callahantiff/PheKnowLator/tree/master/builds#readme">here</a>). Note that we have developed an archive for the builds on Zenodo. While the original GCP resources contained all associated files, due to the file size upload limits associated with each archive, we have limited the uploaded files to the KGs, associated metadata, and log files. The list of resources, including their URLs, and date of download, can all be found in the associated logs.</p><p>Details on each of the files generated by the build process can be found in the file associated with this directory (<a href="https://zenodo.org/records/10065431/files/PheKnowLator_HumanDiseaseKG_Output_FileInformation.xlsx?download=1">PheKnowLator_HumanDiseaseKG_Output_FileInformation.xlsx</a>).</p><p> </p><p>๐จ <strong>AVAILABLE FILES </strong>๐จ </p><ul><li>Available KG benchmark files are zipped and listed below.</li><li>For additional details on what each file contains, please see the associated Wiki page ๐ <a href="https://github.com/callahantiff/PheKnowLator/wiki/September-01%2C-2021">here</a>.</li></ul>
PheKnowLator Human Disease KG Benchmarks: Class-Standard Relations-OWL (v2.1.0 - September 2021)
<p><strong>PKT Human Disease Knowledge Graph Benchmark Builds (v2.1.0)</strong></p><p><strong>Build Type: </strong><i>Class-Standard Relations-OWL</i></p><p><strong>Build Date: </strong>September 01, 2021</p><p> </p><h3><strong>Important Build Information</strong></h3><p>The benchmarks were originally built and stored using Google Cloud Platform (GCP) resources. For details and a complete description of this process, can be found on GitHub (<a href="https://github.com/callahantiff/PheKnowLator/tree/master/builds#readme">here</a>). Note that we have developed an archive for the builds on Zenodo. While the original GCP resources contained all associated files, due to the file size upload limits associated with each archive, we have limited the uploaded files to the KGs, associated metadata, and log files. The list of resources, including their URLs, and date of download, can all be found in the associated logs.</p><p>Details on each of the files generated by the build process can be found in the file associated with this directory (<a href="https://zenodo.org/records/10065431/files/PheKnowLator_HumanDiseaseKG_Output_FileInformation.xlsx?download=1">PheKnowLator_HumanDiseaseKG_Output_FileInformation.xlsx</a>).</p><p> </p><p>๐จ <strong>AVAILABLE FILES </strong>๐จ </p><ul><li>Available KG benchmark files are zipped and listed below.</li><li>For additional details on what each file contains, please see the associated Wiki page ๐ <a href="https://github.com/callahantiff/PheKnowLator/wiki/September-01%2C-2021">here</a>.</li></ul>
PheKnowLator Human Disease KG Benchmarks: Class-Standard Relations-OWLNETS (v2.1.0 - September 2021)
<p><strong>PKT Human Disease Knowledge Graph Benchmark Builds (v2.1.0)</strong></p><p><strong>Build Type: </strong><i>Class-Standard Relations-OWLNETS</i></p><p><strong>Build Date: </strong>September 01, 2021</p><p> </p><h3><strong>Important Build Information</strong></h3><p>The benchmarks were originally built and stored using Google Cloud Platform (GCP) resources. For details and a complete description of this process, can be found on GitHub (<a href="https://github.com/callahantiff/PheKnowLator/tree/master/builds#readme">here</a>). Note that we have developed an archive for the builds on Zenodo. While the original GCP resources contained all associated files, due to the file size upload limits associated with each archive, we have limited the uploaded files to the KGs, associated metadata, and log files. The list of resources, including their URLs, and date of download, can all be found in the associated logs.</p><p>Details on each of the files generated by the build process can be found in the file associated with this directory (<a href="https://zenodo.org/records/10065431/files/PheKnowLator_HumanDiseaseKG_Output_FileInformation.xlsx?download=1">PheKnowLator_HumanDiseaseKG_Output_FileInformation.xlsx</a>).</p><p> </p><p>๐จ <strong>AVAILABLE FILES </strong>๐จ </p><ul><li>Available KG benchmark files are zipped and listed below.</li><li>For additional details on what each file contains, please see the associated Wiki page ๐ <a href="https://github.com/callahantiff/PheKnowLator/wiki/September-01%2C-2021">here</a>.</li></ul>
Data from: Parentage of 920 gray-sided voles (Myodes rufocanus) born in a 3-ha outdoor enclosure between September 1992 and May 1994
<p class="MsoNormal"><span>This dataset provides the estimated birth location, sex, assigned parents, and estimated birth and death dates of 920 gray-sided voles (<em>Myodes rufocanus</em>) born in a 3-ha outdoor enclosure in Sapporo, Japan between September 1992 and May 1994, as well as captureโrecapture data for 30 trapping sessions.</span><span> We introduced 22 males and 25 females from several natural populations into the enclosure in late September 1992. Individuals in the enclosure were captured using live traps every two weeks until late April 1994, except for periods with deep snow cover. The location, body weight, and reproductive status of each vole were monitored throughout the study period. Complementary trapping was performed within the home ranges of breeding females to mark juveniles as early as possible. Upon first capture, each individual was marked by toe clipping for subsequent identification, and the cut toes were used as DNA samples. For each individual, candidate parents were selected based on female reproduction history and capture points, and then parentage was determined using genotypes at 3โ5 microsatellite loci with the CERVUS program. The results show that individuals born in the enclosure (<em>N</em> = 920) were derived from 215 litters, among which multiple males sired 51 litters. We used this database to elucidate the promiscuous mating system and inbreeding-avoidance mechanism of the gray-sided vole and to develop a ne</span><span>w method for estimating the frequency of multiple-male mating. This dataset will contribute to future behavioral ecological research on this and other small mammal species.</span></p>
Dunyvaig Castle 13th September 2021 LARGE
The penultimate day of the excavation. This model was made before some final slots were inserted to ascertain the level of the floor and wall depths. 785 cameras with Canon EOS80D. Focal length 50. F11, ISO320. Shutter 1/40. Created in Agisoft Metashape. Large version. Total faces: 13,464,375 Dense cloud 202,017,386. Medium quality. Source: Objaverse 1.0 / Sketchfab
Measurements of meteorological parameters and subsurface water temperature in the hypersaline Dead Sea in September 2015
Open the record for dataset details and reuse information.
IT-RAD weather radar data collected on 5 September 2015 during an exceptionally intense hailstorm in the Gulf of Naples
<p>On 5 September 2015 a violent hailstorm hit the Gulf and the city of Naples in Italy. The storm originated over the Tyrrhenian Sea dropping 7–10 cm diameter hailstones along its path. The event was observed by a dual-polarization Doppler C-band, namely the Monte il Monte radar operated by the Italian Department of Civil Protection, being part of the Italian radar network (IT-RAD). </p> <p>The dataset is composed by high-resolution polar volumes of the following radar parameters: Uncorrected reflectivity Z (UZ), Corrected reflectivity Z (CZ), differential reflectivity (ZDR), uncorrected differential phase shift (PHIDP), co-polar correlation coefficient (RHOHV), Doppler Velocity (V), Doppler Width (W). The scan strategy is based on inverse elevation mode (from the highest to the lowest elevation angle) with variable PRF. The different phases of the event were well captured by the weather radar of “Monte il Monte” (lat = 41.9394 °, lon = 14.6208 °, altitude = 710 m) which, at the time of the event, was affected by a differential bias (on ZDR) of about 0.8 dB to be algebraically subtracted from the measured quantities. The user should be informed about some spot regions of missing data that might be present in the radar variables, especially on the V and differential phase. This is caused by the thresholding approach applied at RSP level on the signal quality index (SQI) to compensate for W-LAN interferences.</p> <p>The dataset, consisting of 44 raw radar data volumes with 5 minutes sampling rate, is provided in a proprietary format (“Datamet”) that is manageable by using the python code named read_datamet.py that is available at <a href="https://zenodo.org/record/4897245">https://zenodo.org/record/4897245</a>.</p>
Meteorological Data from Kardamyla, Chios: September 2024 Baseline Measurements for the MUSICA Project
<p>September 2024 marked the transition from the intense heat of summer to milder conditions. Significant rainfall was recorded, including one day of heavy precipitation, while temperatures remained relatively moderate. The data provides insights into the climatic behavior of the region during this month.</p> <h4><strong>Temperature:</strong></h4> <ul> <li>Average temperature: <strong>23.9°C</strong>.</li> <li>Highest temperature: <strong>32.8°C</strong> on September 5.</li> <li>Lowest temperature: <strong>14.1°C</strong> on September 25 and 26.</li> <li>Days with temperatures ≥ 32°C: <strong>3 days</strong>.</li> </ul> <h4><strong>Rainfall:</strong></h4> <ul> <li>Total rainfall: <strong>62.8 mm</strong>.</li> <li>Days with rainfall > 0.2 mm: <strong>3 days</strong>.</li> <li>Day with maximum rainfall: <strong>62.2 mm on September 11</strong>.</li> </ul> <h4><strong>Wind:</strong></h4> <ul> <li>Average wind speed: <strong>6.5 km/h</strong>.</li> <li>Maximum wind speed: <strong>53.1 km/h</strong> on September 10 and 13.</li> <li>Dominant wind direction: <strong>Northwest (NNW)</strong>.</li> </ul> <h4><strong>Conclusion:</strong></h4> <p>September exhibited milder temperatures compared to the preceding months, with significant rainfall on September 11 distinguishing it from the dry summer. Winds remained steady, predominantly from the northwest, emphasizing the seasonal shift.</p>
Dataset: HowFaster.NET - Global Ranks - Edition 1 - September 2020 (full month)
<p>A distinction is made between the level of abstraction for:</p> <p>- Autonomous systems;<br> - Continents;<br> - Countries;<br> - Regions;<br> - Cities;<br> - ZIP codes;<br> - Time zones;</p> <p>Data is provided in CSV and JSON formats.</p> <p>Filename format.</p> <p>edition.[value-edition].[value-label].[value-type].[value-format]</p> <p>possible [value-edition] content:<br> - integer from 1..</p> <p>possible [value-label] content:<br> - as;<br> - continent;<br> - countrycode;<br> - regionname;<br> - cityname;<br> - zipcode;<br> - timezone;</p> <p>possible [value-type] content:<br> - global_ranks;<br> - local_ranks;</p> <p>possible [value-format] content:<br> - csv;<br> - json;</p> <p>Example names:</p> <p>- edition.1.as.global_ranks.csv;<br> - edition.1.as.global_ranks.json;</p>
SG - September 2021
<p>Measurements of SG (Global) in September 2021</p> <p> </p> <p>Light Pollution Laboratorie <a href="https://data.eelabs.eu/api/lpls/SG">info</a></p>
LPL4 - September 2021
<p>Measurements of LPL4 (Isla de Corvo) in September 2021</p> <p>Azores</p> <p>Light Pollution Laboratorie <a href="https://data.eelabs.eu/api/lpls/LPL4">info</a></p>
Dr. Sarvapalli Radhakrishnan, then President of India, felicitating Dr. P. L. Vaidya, on the occasion of the conclusion of the Mahฤbhฤrata project, 22 September 1966
<p>Dr. Sarvapalli Radhakrishnan, then President of India, felicitating Dr. P. L. Vaidya, on the occasion of the conclusion of the critical ediition of the Mahฤbhฤrata on September 22, 1966. After 48 years & a critical study of 1259 manuscripts, the project was completed in 1966.</p> <p>After V.S. Sukthankar, S.K. Belvalkar was appointed as the general editor on April 1, 1943. Upon his retirement, P. L. Vaidya was appointed as General Editor of the project in 1961, while R. N. Dandekar became the joint general editor in 1957.</p> <p> </p>
Processed model output and observational products used in `Observed winds crucial for September Arctic sea ice loss'
<p>Processed model output from wind-nudging experiments used to investigate Arctic sea ice loss. Also includes processed observational data shown in the manuscript.</p> <p> </p> <p>For further details, see </p> <p>Roach, L. A and Blanchard-Wrigglesworth E. (2022). Observed winds crucial for September Arctic sea ice loss. Accepted at Geophysical Research Letters</p>
Supplementary data to Analyzing and Modeling the Spread of SARS-CoV-2 Omicron Lineages BA.1 and BA.2, France, September 2021โFebruary 2022
<p>ZIP folder containing supplementary files to the article entitled <em>Analyzing and Modeling the Spread of SARS-CoV-2 Omicron Lineages BA.1 and BA.2, France, September 2021–February 2022</em> and published in Emerging Infectious Diseases with doi <a href="https://dx.doi.org/10.3201/eid2807.220033">10.3201/eid2807.220033</a></p> <ul> <li>Script_EID_1.R is the R script analysing the data_EID1.csv screening test data file (Figure 1 and Suppl Figure F1, and Tables 1 and 3).</li> <li>Script_EID_2.R is the R script analysing the data_EID2.csv screening test data file (Figures 2, 3, 5, and Suppl Figure F2, and Table 2).</li> <li>Script_EID_sequencing_raw.R is the R script analysing the data_EID_sequencing.csv sequencing data file (Figures 4, 5, and Suppl Figure F3).</li> </ul>
Sell AMX Pitch (September 2017)
<p>Auyon (Alex) Rahman’s pitch to sell AMX to the members, faculty and stakeholders in attendance at the Student Portfolio Investment Fund at the University of Maine, that manages $3.2 million of the University’s endowment.</p> <p> </p> <p>Auyon (Alex) Rahman was able to secure majority votes, and his motion to sell AMX passed.</p>
September 2022 OCFL Community Meeting
<p>This month's community meeting included:</p> <ul> <li>Updates on ocfl-index project</li> <li>Discussion on purging files from an object</li> <li>Discussion on <a href="https://github.com/OCFL/extensions/pull/57">NNNN-flat-direct-clean-storage-layout</a> and extensions generally</li> </ul> <p>Full notes can be found at: <a href="https://github.com/OCFL/spec/wiki/2022.09.14-Community-Meeting">https://github.com/OCFL/spec/wiki/2022.09.14-Community-Meeting</a></p>
ScienceDex guides
Understand access before you commit
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Allen Brain Atlas
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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
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