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Response of Lake Baikal periphyton to nutrient enrichment at 10 sites across a land use gradient: Results from a nutrient diffusing substrata (NDS) experiment
This data set contains results of a study on the response of benthic algae to experimental nutrient enrichment in the nearshore of Lake Baikal, Russia. Nutrient diffusing substrata (NDS) were deployed at 10 sites across a land-use gradient (from town to forested) during August to September of 2015 . Four NDS treatments were used at each site: 'control', 'added phosphorus', 'added nitrogen' and 'added nitrogen and phosphorus'. NDS tiles were left in the lake for 32-33 days. After retrieval, benthic chlorophyll a levels from all sites were analyzed as an index of periphyton biomass (data in file periphyton_chl_a.csv). Taxonomic identification of algae was done at 4 of the 10 sites (2 developed, 2 undeveloped); cell counts are presented in file 'periphyton_abundance.csv'; biovolumes were determined for the most common taxa and are presented in file 'periphyton_biovolume.csv'.
Trophic interactions of fiddler crabs (Uca spp.) with black mangrove (Avicennia germinans) detrital matter as a result of mangrove encroachment; 2018 and 2019
Woody plant encroachment is reshaping communities in both terrestrial and coastal environments, but little is known about its effects on basal consumers. We used interactions between fiddler crabs (Uca spp.) and the encroaching mangrove Avicennia germinans in Gulf of Mexico salt marshes to explore trophic interactions between basal consumers and encroaching shrubs. Fiddler crabs were collected from wetlands in Galveston, Texas in summer 2018 and 2019 and used in a series of food preference and food quality trials. Through these trials we collected data on the relative attractiveness and quality of black mangroves and smooth cordgrass (Spartina alterniflora) as food sources for fiddler crabs.
Murphy Dome: Moss (Hylocomium splendens) biomass results from a moss transplant and leaf litter manipulation experiment in three pairs of adjacent black spruce and birchs stands.
This dataset contains moss (Hylocomium splendens) growth from individual moss shoots within moss transplants in black spruce and paper birch stands. 10 mosses were marked with PVC beads in June 2013 and then each moss segment was measured in the field in June and September of 2013, 2014 and June and August 2015. All samples were harvested in 2015 and their dry weights were calculated. Moss biomass from other time periods were estimated using allometric equations. The data was collected in three blocks (A, B, and C) of adjacent black spruce and paper birch stands at Murphy Dome (access via Cache Creek road).
Murphy Dome: Moss (Hylocomium splendens and Pleurozium schreberi) biomass results from a birch leaf litter and leachates manipulation experiment in a black spruce stand.
This dataset contains moss (Hylocomium splendens and Pleurozium schreberi) growth from individual moss shoots in a black spruce stand. 10 H. splendens and 5 P. schreberi were marked with PVC beads and measured in September 2014 and then each moss segment was measured again August 2015. All samples were harvested in 2015 and their dry weights were calculated. Moss biomass from other time periods were estimated using allometric equations. The data was collected in the spruce stands of block A only at Murphy Dome (access via Cache Creek road).
Urban heat island conditions experienced by the Western black widow spider (Latrodectus hesperus): extreme heat slows development but results in behavioral accommodations
Herein lies data on urban h eat island conditions for black widow spiders across the CAP study area. It also includes data on the development speed and behavioral responses of spiders reared in the lab at these UHI temperatures. The urban heat island (UHI) effect describes the capture of heat by built structures (e.g. asphalt), resulting in elevated urban temperatures. The UHI is a well-studied phenomenon, but only a handful of studies have investigated trait-based shifts resulting from the UHI, and even fewer have attempted to quantify the magnitude of the UHI experienced at the microclimate scale. Here, using a common urban exploiter, the Western black widow spider (Latrodectus hesperus), we show that the UHI experienced by spiders in July in their urban Phoenix, AZ refuges is 6 degrees C hotter (33 degrees C) than conditions in the refuges of spiders from Sonoran Desert habitat outside of Phoenix-area development (27 degrees C). We then use this field microclimate UHI estimate to compare the development speed, mass gain and mortality of replicate siblings from 36 urban lineages reared at temperatures that reflect urban and desert habitats. We show that extreme heat is slowing the growth of spiderlings and increasing mortality. In contrast, we show that development of male spiders to their penultimate moult is accelerated by 2 weeks. Lastly, in terms of behavioral shifts, UHI temperatures caused late-stage juvenile male spiders to heighten their foraging voracity and late-stage juvenile female spiders to curtail their web-building behavior.
IRP RECC report results
<p>This is the set of results for the 259 model runs of the ODYM-RECC model that were used for the report "Resource Efficiency and Climate Change: Material Efficiency Strategies for a Low-Carbon Future. Hertwich, E., Lifset, R., Ali, S., Pauliuk, S., Heeren, Tu, Q. A report of the International Resource Panel".</p>
TF-IDF Results for EarlyPrint 1666 Texts
<p>The results of Term Frequency–Inverse Document Frequency run on a subset of <a href="https://earlyprint.org"><em>EarlyPrint</em></a><em> </em>texts: the ones published in 1666 that are currently available as part of EEBO-TCP Phase I. <a href="https://earlyprint.org/notebooks/tf_idf.html">The full analysis that produced these data is here</a>.</p>
UniDAM results for APOGEE dr16
<p>UniDAM results for APOGEE dr16 + Gaia dr2 parallax + 2MASS/AllWISE photometry.</p> <p>Parallax offset of 0.052 mas is used for Gaia parallaxes</p>
SWAT+ simulation result used in "Smart renewable electricity portfolios in West Africa"
<p>Shapefiles and simulation results from SWAT+ used for the paper "Smart renewable electricity portfolios in West Africa" by Sterl et al., who used it to infer the interannual variability of river flow seasonality across West Africa.</p>
Patient-reported outcomes predict return to work and health-related quality of life 6 months after cardiac rehabilitation: Results from a German multi-centre registry (OutCaRe): dataset
<p>This is the resulting data set from the prospective observational study (available cases at the time of follow up monitoring) OutCaRe, that is the basis of all results presented in the article "Patient-reported outcomes predict return to work and health-related quality of life 6 months after cardiac rehabilitation: Results from a German multi-centre registry (OutCaRe)".</p> <p>OutCaRe is a registered study (https://www.drks.de/drks_web/navigate.do?navigationId=trial.HTML&TRIAL_ID=DRKS00011418).</p>
Server room CFD analyses results
<p>Files included in this dataset contain transient records of the most important variables of results of 9 scenarios of Poznan Supercomputing and Networking Center testbed CFD analysis.</p> <p>Modeled testbed included server room equipped with two heterogeneously occupied racks (with each server modeled separately) and one roof-mounted cooling device. Setup was examined virtually for three servers power usage scenarios (50%, 75% and 100% of maximum value). For major part of active servers the power usage was changed respectively in each scenario, while some of them preserved daily-averaged values (inactive devices are also included). For each power usage level also three different air conditioning temperature setups (24, 27 and 30 Celsius degrees) were tested. The most relevant information about the model can be found below:</p> <p> </p> <ul> <li>server room dimensions along x, y and z axis (with one of the corners placed in the origin): (4.86, 4.00, 3.00) [m]</li> <li>racks dimensions: (0.6,1.18,2.1),(0.8,1.18,2.2) [m]</li> <li>racks position (translation from 0,0,0): (1.4,1.95,0), (2.08,1.95,0) [m]</li> <li>first rack equipment (position [-], size [-], airflow [m<sup>3</sup>/s], power usage (50%/75%/100% scenario) [W], flow orientation [-]): <ul> <li>0, plug, -, -/-/-, -,</li> <li>1, plug, -, -/-/-, -,</li> <li>2, 4U, 0.0, 0.0/0.0/0.0, y,</li> <li>6, 2U, 0.0, 0.0/0.0/0.0, y,</li> <li>9, plug, -, -/-/-, -,</li> <li>10, 2U, 0.05, 230/345/460, y,</li> <li>20, 2U, 0.025, 90/90/90, y,</li> <li>22, 2U, 0.05, 450/675/900, y,</li> <li>24, 4U, 0.12, 1000/1500/2000, y,</li> <li>28, 2U, 0.05, 230/345/460, y,</li> <li>30, 4U, 0.12, 1000/1500/2000, y,</li> <li>34, 2U, 0.05, 400/600/800, y,</li> <li>36, 2U, 0.05, 400/600/800, y,</li> </ul> </li> <li>second rack equipment (position [-], size [-], airflow [m<sup>3</sup>/s], power usage (50%/75%/100% scenario) [W], flow orientation [-]): <ul> <li>0, 3U, 0.0, 0.0/0.0/0.0, y,</li> <li>3, 3U, 0.0, 0.0/0.0/0.0, y,</li> <li>6, plug, -, -/-/-, -,</li> <li>7, plug, -, -/-/-, -,</li> <li>8, 3U, 0.0, 0.0/0.0/0.0, y,</li> <li>11, 2U, 0.0, 0.0/0.0/0.0, y,</li> <li>13, 2U, 0.025, 69/69/69, x,</li> <li>15, 3U, 0.0/0.0/0.0, 0.0/0.0/0.0, y,</li> <li>18, 3U, 0.15, 1350/2025/2700, x,</li> <li>22, 2U, 0.05, 161/161/161, y,</li> <li>24, 2U, 0.025, 69/69/69, x,</li> <li>26, 2U, 0.0, 0.0/0.0/0.0, y,</li> <li>28, 2U, 0.025, 23/23/23, x,</li> <li>30, 2U, 0.05, 258.5/258.5/258.5, y,</li> <li>34, plug, -, -/-/-, -,</li> <li>35, plug, -, -/-/-, -,</li> <li>36, plug, -, -/-/-, -,</li> <li>37, plug, -, -/-/-, -,</li> <li>38, plug, -, -/-/-, -,</li> <li>40, plug, -, -/-/-, -,</li> <li>41, plug, -, -/-/-, -,</li> <li>air conditioner max. cooling capacity: 10 [kW]</li> <li>air conditioner airflow: 0.533 [m3/s]</li> <li>air conditioner inlet center: (3.76, 1.3, 3.0)</li> <li>air conditioner outlet center: (3.76, 2.8, 3.0)</li> <li>ventilation airflow: 0.0252 [m3/s]</li> <li>ventilation inlet center: (2.8125, 3.6475, 3.0)</li> <li>ventilation outlet center: (2.95, 0.605, 3.0)</li> </ul> </li> <li>domain cuboid cavities (start point, end point): <ul> <li>(0, 0, 3.0), (0.72, 4.1, 3.27),</li> <li>(0.32, 0, 3.27), (0.72, 3.78, 3.5)</li> </ul> </li> <li>domain cuboid obstacles (start point, end point): <ul> <li>(3.61, 0, 0), (4.86, 0.44, 1.89)</li> <li>(0.32, 3.78, 0), (0.72, 4.1, 3.0)</li> </ul> </li> </ul> <p> </p> <p>The dataset contains records of below variables:</p> <ul> <li>temperature from four virtual probes placed at the same locations as real sensors in the testbed: <ul> <li> (1.8, 2.12, 1.42) - close to inlet of a server from the first rack</li> <li> (4.8, 1.65, 1.5) - close to air conditioner wall-mounted control panel</li> <li> (2.5, 2.09, 0.95) - close to inlet of a server from the second rack</li> <li> (2.8, 0.65, 0.75) - probe distanced from both racks and air conditioner, imitating "neutral" point</li> </ul> </li> <li>surface-averaged temperature at inlet of each server</li> <li>surface-averaged temperature at outlet of each server</li> <li>surface-averaged temperature at air conditioner inlet</li> <li>surface-averaged temperature at air conditioner outlet</li> </ul>
Supplementary data for 'Results of the third Marine Ice Sheet Model Intercomparison Project (MISMIP+)'
<p>Datasets and model datasheets provided to the third Marine Ice Sheet Model Intercomparison Project (MISMIP+)</p>
Results of the 2nd International Competition on Software Testing (Test-Comp 2020)
<p>This archive contains the results of the<br> 2nd Competition on Software Testing (Test-Comp 2020)<br> <a href="https://test-comp.sosy-lab.org/2020/">https://test-comp.sosy-lab.org/2020/</a></p> <p>The competition was run by Dirk Beyer, LMU Munich, Germany.<br> More information is available in the following article:<br> Dirk Beyer. Second Competition on Software Testing: Test-Comp 2020.<br> In Proceedings of the 23rd International Conference on Fundamental Approaches to Software Engineering<br> (FASE 2020, Dublin, April 28-30), 2020. Springer.<br> <a href="https://doi.org/10.1007/978-3-030-45234-6_25">https://doi.org/10.1007/978-3-030-45234-6_25</a></p> <p>Copyright (C) Dirk Beyer<br> <a href="https://www.sosy-lab.org/people/beyer/">https://www.sosy-lab.org/people/beyer/</a></p> <p>SPDX-License-Identifier: CC-BY-4.0<br> <a href="https://spdx.org/licenses/CC-BY-4.0.html">https://spdx.org/licenses/CC-BY-4.0.html</a></p> <p> </p> <p>To browse the competition results with a web browser, there are two options:<br> - start a local web server using<br> php -S localhost:8000<br> in order to view the data in this archive, or<br> - browse <a href="https://test-comp.sosy-lab.org/2020/results/">https://test-comp.sosy-lab.org/2020/results/</a><br> in order to view the data on the Test-Comp web page.</p> <p><br> Contents:</p> <p>index.html directs to the overview web page<br> LICENSE.txt specifies the license<br> README.txt this file<br> results-validated/ results of coverage-validation runs<br> results-verified/ results of test-generation runs and aggregated results</p> <p><br> The folder results-validated/ contains the results from coverage-validation runs:</p> <p>- *.xml.bz2 XML results from BenchExec<br> - *.logfiles.zip output from tools<br> - *.json.gz mapping from files names to SHA 256 hashes for the file content</p> <p><br> The folder results-verified/ contains the results from test-generation runs and aggregated results:</p> <p>index.html overview web page with rankings and score table<br> design.css HTML style definitions<br> *.xml.bz2 XML results from BenchExec<br> *.merged.xml.bz2 XML results from BenchExec, status adjusted according to the validation results<br> *.logfiles.zip output from tools<br> *.json.gz mapping from files names to SHA 256 hashes for the file content<br> *.xml.bz2.table.html HTML views on the detailed results data as generated by BenchExec's table generator<br> *.All.table.html HTML views of the full benchmark set (all categories) for each tool<br> META_*.table.html HTML views of the benchmark set for each meta category for each tool, and over all tools<br> <category>*.table.html HTML views of the benchmark set for each category over all tools<br> iZeCa0gaey.html HTML views per tool</p> <p>quantilePlot-* score-based quantile plots as visualization of the results<br> quantilePlotShow.gp example Gnuplot script to generate a plot<br> score* accumulated score results in various formats</p> <p><br> The hashes of the file names (in the files *.json.gz) are useful for<br> - validating the exact contents of a file and<br> - accessing the files from the witness store.</p> <p> </p> <p>Overview over archives from Test-Comp 2020 that are available at Zenodo:</p> <p><a href="https://doi.org/10.5281/zenodo.3678275">https://doi.org/10.5281/zenodo.3678275</a> Witness store (containing the generated test suites)<br> <a href="https://doi.org/10.5281/zenodo.3678264">https://doi.org/10.5281/zenodo.3678264</a> Results (XML result files, log files, file mappings, HTML tables)<br> <a href="https://doi.org/10.5281/zenodo.3678250">https://doi.org/10.5281/zenodo.3678250</a> Test tasks, version testcomp20<br> <a href="https://doi.org/10.5281/zenodo.3574420">https://doi.org/10.5281/zenodo.3574420</a> BenchExec, version 2.5.1</p> <p>All benchmarks were executed<br> for Test-Comp 2020, <a href="https://test-comp.sosy-lab.org/2020/">https://test-comp.sosy-lab.org/2020/</a><br> by Dirk Beyer, LMU Munich<br> based on the components<br> git@github.com:sosy-lab/sv-benchmarks.git testcomp20-0-gd6cd3e5dd4<br> git@gitlab.com:sosy-lab/test-comp/bench-defs.git testcomp19-84-gac76836<br> git@github.com:sosy-lab/benchexec.git 2.5.1-0-gffad635</p> <p><br> Feel free to contact me in case of questions:<br> <a href="https://www.sosy-lab.org/people/beyer/">https://www.sosy-lab.org/people/beyer/</a></p> <p> </p>
Antimicrobial resistance monitoring results complementing the EU Overview Summary Report on AMR in zoonotic and indicator bacteria from humans, animals and food in 2017/2018 - Ireland
<p>This dataset contains AMR monitoring results in animals and food at the isolate level pursuant to Article 9 of Directive 2003/99/EC and to Annex, part B, of Commission implementing Decision 2013/652/EU. In addition, the dataset includes any other results from isolates than the ones mentioned in the Commission implementing Decision 2013/652/EU. The quantitative minimum inhibitory concentration (MIC) data from dilution methods are included. REPORTING AUTHORITIES CONTRIBUTING TO EACH DATA COLLECTION: AMR_2018_IE_20200204: >> The Food Safety Authority of Ireland</p>
Antimicrobial resistance monitoring results complementing the EU Overview Summary Report on AMR in zoonotic and indicator bacteria from humans, animals and food in 2017/2018 - Sweden
<p>This dataset contains AMR monitoring results in animals and food at the isolate level pursuant to Article 9 of Directive 2003/99/EC and to Annex, part B, of Commission implementing Decision 2013/652/EU. In addition, the dataset includes any other results from isolates than the ones mentioned in the Commission implementing Decision 2013/652/EU. The quantitative minimum inhibitory concentration (MIC) data from dilution methods are included. REPORTING AUTHORITIES CONTRIBUTING TO EACH DATA COLLECTION: AMR_2018_SE_20200204: >> National Veterinary Institute, Swedish Zoonosis Centre</p>
Antimicrobial resistance monitoring results complementing the EU Overview Summary Report on AMR in zoonotic and indicator bacteria from humans, animals and food in 2017/2018 - Latvia
<p>This dataset contains AMR monitoring results in animals and food at the isolate level pursuant to Article 9 of Directive 2003/99/EC and to Annex, part B, of Commission implementing Decision 2013/652/EU. In addition, the dataset includes any other results from isolates than the ones mentioned in the Commission implementing Decision 2013/652/EU. The quantitative minimum inhibitory concentration (MIC) data from dilution methods are included. REPORTING AUTHORITIES CONTRIBUTING TO EACH DATA COLLECTION: AMR_2018_LV_20200204: >> Assessment and Registration Agency of Food and Veterinary Service of Latvia</p>
Antimicrobial resistance monitoring results complementing the EU Overview Summary Report on AMR in zoonotic and indicator bacteria from humans, animals and food in 2017/2018 - Spain
<p>This dataset contains AMR monitoring results in animals and food at the isolate level pursuant to Article 9 of Directive 2003/99/EC and to Annex, part B, of Commission implementing Decision 2013/652/EU. In addition, the dataset includes any other results from isolates than the ones mentioned in the Commission implementing Decision 2013/652/EU. The quantitative minimum inhibitory concentration (MIC) data from dilution methods are included. REPORTING AUTHORITIES CONTRIBUTING TO EACH DATA COLLECTION: AMR_2018_ES_20200204: >> Agencia Espaola de Consumo, Seguridad Alimentaria y Nutricin >> Ministerio de Agricultura, Pesca y Alimentacin</p>
Specific monitoring results of ESBL-/AmpC-/carbapenemase-producing bacteria and specific monitoring of carbapenemase-producing bacteria, in the absence of isolates detected complementing the European Union Overview Summary Report on Antimicrobial Resistance in zoonotic and indicator bacteria from humans, animals and food in 2017/2018
<p>This dataset derives from the specific monitoring of E. coli producers of ESBLs/AmpC/carbapenemases, as well as the specific monitoring of carbapenemase-producers (voluntary reporting), in the absence of any isolates detected. This dataset contains only data when Total units positive equals zero '0'.</p>
Antimicrobial resistance monitoring results complementing the EU Overview Summary Report on AMR in zoonotic and indicator bacteria from humans, animals and food in 2017/2018 - Cyprus
<p>This dataset contains AMR monitoring results in animals and food at the isolate level pursuant to Article 9 of Directive 2003/99/EC and to Annex, part B, of Commission implementing Decision 2013/652/EU. In addition, the dataset includes any other results from isolates than the ones mentioned in the Commission implementing Decision 2013/652/EU. The quantitative minimum inhibitory concentration (MIC) data from dilution methods are included. REPORTING AUTHORITIES CONTRIBUTING TO EACH DATA COLLECTION: AMR_2018_CY_20200204: >> Ministry of Agriculture, Natural Resources and Evironment - Veterinary Services</p>
Antimicrobial resistance monitoring results complementing the EU Overview Summary Report on AMR in zoonotic and indicator bacteria from humans, animals and food in 2017/2018 - Iceland
<p>This dataset contains AMR monitoring results in animals and food at the isolate level pursuant to Article 9 of Directive 2003/99/EC and to Annex, part B, of Commission implementing Decision 2013/652/EU. In addition, the dataset includes any other results from isolates than the ones mentioned in the Commission implementing Decision 2013/652/EU. The quantitative minimum inhibitory concentration (MIC) data from dilution methods are included. REPORTING AUTHORITIES CONTRIBUTING TO EACH DATA COLLECTION: AMR_2018_IS_20200204: >> Icelandic Food and Veterinary Authority</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.