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3,494 results for “modified”
Supplementary data release for "Cosmology and modified gravitational wave propagation from binary black hole population models"
<p>We release the data products associated to the paper <a href="https://arxiv.org/abs/2112.05728">"Cosmology and modified gravitational wave propagation from binary black hole population models", </a><a href="https://journals.aps.org/prd/abstract/10.1103/PhysRevD.105.064030"><em>Phys.Rev.D</em> 105 (2022) 6 </a>.</p> <p>The data can be used in conjunction with the code <a href="https://github.com/CosmoStatGW/MGCosmoPop">MGCosmoPop</a> to reproduce the results of the paper. </p> <p>The data product contains the following folders:</p> <p>* injections_GWTC3: injections used to analyze the GWTC3 catalog, generated with the code <a href="https://github.com/CosmoStatGW/MGCosmoPop">MGCosmoPop</a> . Injections are available separately for O1-O2, O3a, O3b for minimum SNR of 10, 11, 12 (folder names are self-explicative). Each folder contains a file named selected.h5 with the injections. For loading them, refer to the tutorial of the code <a href="https://github.com/CosmoStatGW/MGCosmoPop">MGCosmoPop</a> .</p> <p>* mock_BPL_5yr_GR : mock data for 5 years of aLIGO observations, with fiducial cosmological model set to General Relativity (see the paper for details)</p> <p>* mock_BPL_5yr_MG : mock data for 5 years of aLIGO observations, with fiducial cosmological model set to a modified gravity model with modified gravitational-wave propagation (see the paper for details)</p> <p>* injections_mock : injections for analyzing the mock datasets above</p>
Changes in soil moisture and temperature modify the toxicity of sodium selenite and sodium selenate for Folsomia candida (Collembola) Willem 1902
<p>Effects of sublethal concentrations of selenite and selenate were tested on parameters of mortality, reproduction, growth, and oxidative stress parameters of <em>Folsomia candida</em> (Collembola) in case of different climate scenarios. The standard 20°C and the increased 25°C temperatures were combined with three different soil moisture conditions: drought, standard water content and increased water content.</p>
WaterGAP2.2d model derived Potential evapotranspiration and Renewable water resources variables with standard and modified PET calculation methods
<p>This data set is produced as a part of the ''Improving the quantification of climate change hazards by hydrological models: A simple ensemble approach for considering the uncertain effect of vegetation response to climate change on potential evapotranspiration" journal publication (in preparation). WaterGAP2.2d global hydrological model with two different settings; 1) with standard PET method Priestley-Taylor (PT) and 2) with modified approach (PT-MA) (please refer to the publication for more details on the method) used to derive the data set. The bias-adjusted GCM-derived (GFDL-ESM2M, HadGEM2-ES, IPSL-CM5A-LR, and MIROC5) climate data under RCP2.6 and RCP8.5 emission scenarios were used as the input. The model-derived potential evapotranspiration and the renewable water resources variables are available from 1981 to 2099 on the monthly scale for each land grid cell (spatial resolution: 0.5 degrees x 0.5 degrees). The data files are in the netCDF format (.nc4). </p>
Low dose rate radiation induced secretion of TGF-β3 together with an activator in small extracellular vesicles modifies low dose hyper-radiosensitivity through ALK1 binding
<p>This is a collection of results from all clonogenic assays on T-47D cells used in the manuscript "Low dose rate radiation induced secretion of TGF-β3 together with an activator in small extracellular vesicles modifies low dose hyper-radiosensitivity through ALK1 binding". </p> <p>T-47D cells were subjected to various pretreatments: low dose rate priming (0.1-0.3 Gy/h for 1 hour), small extracellular vesicles from irradiated or control cells, irradiated or control cell conditioned medium, MMP/ADAM inhibitor TAPI-2, recombinant TGF-B3, inhibitors of ALK1, ALK2, ALK5 or TGF-BRII, iNOS inhibitor 1400W, recombinant FKBP4, recombinant MMP14 and combinations of these. All pretreatments except low dose rate priming was administered for 24 hours. </p> <p>After pretreatments, cells were seeded to colonies and irradiated with 220 kV x-rays at a dose rate of 22.5 Gy/h or gamma rays from a Co-60 source at a dose rate of 20-25 Gy/h. </p> <p>Colonies were cultured for 2-3 weeks before fixation and manual counting. </p>
Data for a publication "Amino-Modified ZIF-8 for Enhanced CO2 Capture: Synthesis, Characterization and Performance Evaluation"
<p>Data for a publication "Amino-Modified ZIF-8 for Enhanced CO2 Capture: Synthesis, Characterization and Performance Evaluation".</p> <p><strong>Versions of dataset:</strong></p> <p><strong><span>V1: </span></strong><span>First dataset regarding the data used in the article.</span></p> <p><strong><span>V2:</span></strong><span> The dataset </span><span>was newly reorganized</span><span>, containing the </span><span>data,</span><span> that </span><span>were used</span><span> for the published article. </span><span>More information can be found</span><span> in the README file.</span></p> <p><strong>Article abstract</strong></p> <p>The urgent need for sustainable and innovative approaches to mitigate the increasing levels of atmospheric CO<sub>2</sub> necessitates the development of efficient methods for its removal. In this study, we focus on the new, innovative approach for synthesis and functionalization of metal-organic framework (MOF) ZIF-8 in one step at room temperature to enhance its capacity for CO<sub>2</sub> capture. Specifically, we investigated the impact of four amino-compounds, namely tetraethylenepentamine (TEPA), hexadecylamine (HDA), <a title="Learn more about ethanolamine from ScienceDirect's AI-generated Topic Pages" href="https://www.sciencedirect.com/topics/chemical-engineering/ethanolamine">ethanolamine</a> (ELA), and cyclopropylamine (CPA), on the <a title="Learn more about chemical structure from ScienceDirect's AI-generated Topic Pages" href="https://www.sciencedirect.com/topics/materials-science/structure-composition">chemical structure</a>, size, surface area and porosity, and CO<sub>2</sub> capturing of ZIF-8 powder. By varying concentrations of the amino-compounds, we examined their influence on the ZIF-8 properties. Our findings demonstrate that each amino-compound and its respective concentration exhibit distinct effects on the characteristics of ZIF-8. Notably, the ZIF-8 sample functionalized with the highest presented concentration of TEPA exhibited significant improvement in CO<sub>2</sub> trapping efficiency, with a 33.3% enhancement. Moreover, least concentrated samples with added HDA or CPA demonstrated notable improvements with enhancements of 46.6% and 18.6%, respectively. These results highlight the potential of simple synthesis and functionalization techniques for MOFs in enhancing their CO<sub>2</sub> capture capabilities. The findings from this study offer new opportunities for the development of strategies to mitigate CO<sub>2</sub> emissions using MOFs.</p>
Data for a publication "Argon plasma-modified bacterial nanocellulose: Cell-specific differences in the interaction with fibroblasts and endothelial cells"
<p>A dataset containing data for the published article "Argon plasma-modified bacterial nanocellulose: Cell-specific differences in the interaction with fibroblasts and endothelial cells".</p> <p> </p> <p>For more details, please read the <strong>README - Description of data and analysis informations.txt</strong> file.</p> <p><strong>Dataset versions:</strong></p> <p><strong>V1:</strong> The first dataset containing a majority of the data.</p> <p><strong>V2:</strong> Dataset contains all the data mentioned in the article in the appropriate file formats for long-term preservation and accessibility.</p>
Modified half-hourly FLUXNET dataset for 10 Boreal forest sites (CA-Obs,CA-Ojp,CA-Qfo,FI-Hyy,FI-Ken,FI-Let,FI-Sod,RU-Fyo,RU-Zot,US-Prr)
<p>This set contains half-hourly driving data and observations used in the simulations described in gmd-2018-313 (doi:10.5194/gmd-2018-313). Originally, this data is part of the FLUXNET2015 dataset (doi:10.17616/R36K9X). We have quality checked and gap-filled this data to suit the simulations.</p> <p>The upload contains site specific csv-files, a data header that is common to all files and a README. The actual data contains half-hourly values for:</p> <ul> <li>gross primary production (GPP, mol m<sup>-2 </sup>s<sup>-1</sup>)</li> <li>evapotranspiration (ET, kg m<sup>-2 </sup>s<sup>-1</sup>)</li> <li>air temperature (air_temp, degrees celcius)</li> <li>air pressure (air_pressure, Pa)</li> <li>precipitation (precip, kg m<sup>-2 </sup>s<sup>-1</sup>)</li> <li>specific humidity (qair, kg<sup> </sup>kg<sup>-1</sup>)</li> <li>wind speed (wspeed, m s<sup>-1</sup>)</li> <li>CO2 concentration (CO2, mol mol<sup>-1</sup>)</li> <li>shortwave radiation (shortwave, W m<sup>-2</sup>)</li> <li>longwave radiation (longwave, W m<sup>-2</sup>)</li> <li>potential shortwave radiation (mpot, W m<sup>-2</sup>)</li> </ul> <p>The sites (named by their FLUXNET identifier) and the years of data in this set are:</p> <ul> <li>CA-Obs (Saskatchewan) 1999-2006</li> <li>CA-Ojp (Saskatchewan) 2004-2006</li> <li>CA-Qfo (Quebec) 2003-2010</li> <li>FI-Hyy (Hyytiälä) 1999-2006</li> <li>FI-Ken (Kenttärova) 2003-2010</li> <li>FI-Let (Lettosuo) 2010-2012</li> <li>FI-Sod (Sodankylä) 2001-2008</li> <li>RU-Fyo (Fyodorkovskoye) 2002-2009</li> <li>RU-Zot (Zotino) 2002-2004</li> <li>US-Prr (Poker Flat) 2011-2013</li> </ul>
EVO-NANO modified PhysiCell simulation run with 10K vasculature agents
<p>PhysiCell modifications:</p> <p>- added CSC</p> <p>-added vasculature</p> <p> </p> <p>this run:</p> <p>Cell cycle speed increased to 1/10 (default is 0.0432/60 = 0,00072)<br> snapshot is taken each 180 minutes (of simulation time)<br> There are 10000 vasculature agents with 100 branches<br> oxygen secretion rate for each fasculature agent is: phenotype.secretion.secretion_rates[0] = 10<br> </p>
EVO-NANO modified PhysiCell simulation run with 50K vasculature agents
<p>PhysiCell modifications:</p> <p>- added CSC</p> <p>-added vasculature</p> <p> </p> <p>this run:</p> <p>Cell cycle speed increased to 1/10 (default is 0.0432/60 = 0,00072)<br> snapshot is taken each 180 minutes (of simulation time)<br> There are 50000 vasculature agents with 500 branches<br> oxygen secretion rate for each fasculature agent is: phenotype.secretion.secretion_rates[0] = 10</p>
MAR-M-247 creep assessment through a modified theta projection model - Figures 2 and 5
<p>These two programs provide a way to rebuild the MAR-M-247 creep data presented in the paper:</p> <p>G. Maggiani, M.J. Roy, S. Colantoni, P.J. Withers, MAR-M-247 creep assessment through a modified theta projection model, Materialia, Volume 7, 2019, 100392, ISSN 2589-1529, https://doi.org/10.1016/j.mtla.2019.100392. http://www.sciencedirect.com/science/article/pii/S2589152919301887)<br> </p> <p>In Paper_Figure_2.m two coefficients of the paper itself are corrected and a comparison with what written in the paper and the corrected value is provided. One typo error for theta 1 at 982°C and 140 MPa where 6.9 must be 1.9. The other is for 1038°C 50 MPa theta4. In the paper it is written e^-11 while it actually should have been e^-10.</p> <p>Paper_Figure_5.m more decimal values are provided for the coefficients a, b, c and d that are used to rebuild the theta values.</p> <p> </p> <p> </p>
GLM2_modified and Results as used in Ma et al: Global rules for translating land-use change (LUH2) to land-cover change for CMIP6 using GLM2, Geosci. Model Dev., 2020
<p>Code modified GLM2, scripts and result as used in Ma et al 2019, Ma et al 2019, Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2019-146</p>
A Modified Doyle-Fuller-Newman Model Enables the Macroscale Physical Simulation of Dual-ion Batteries - Dataset and Software
<p>This dataset contains:</p> <p>- all the raw cycling data of the three-electrode cell used to gather the experimental data for the model validation (VMP data, exported with EC-LAB);<br>- the specific, processed data used in the model validation step (0.2C discharge, 5C discharge, EIS data);<br>- the COMSOL dual-ion battery model (version 6.0). IMPORTANT: activate the "Electric potential at the positive electrode current collector (only for EIS)" boundary condition when simulating impedance spectroscopy, and deactivate it when simulating charge/discharge curves; the charge-discharge profile can be modified by changing the duration of the test, the C-rate, and the conditions set in the "Events" section.</p> <p>Update: Fixed the model to work also in the 6.2 version of COMSOL (Substituted Dleff with Dleffxx in the modified weak expression of the cathode mass conservation equation). Download the new version!</p>
Data archive for "Modified rice bran arabinoxylan as a nutraceutical in health and disease — A scoping review with bibliometric analysis"
<p>v1.0.0 Release with the publication of the paper on PLoS One</p> <p>Ooi, S. L., Micalos, P. S., & Pak, S. C. (2023). Modified rice bran arabinoxylan as a nutraceutical in health and disease—A scoping review with bibliometric analysis. PLOS ONE, 18(8), e0290314. https://doi.org/10.1371/journal.pone.0290314</p> <p><strong>Full Changelog</strong>: https://github.com/sooi10/RBACScoping/commits/NetworkAnalysis</p>
A modified decontamination and storage method for sputum from patients with tuberculosis
<p>Sputum sampling is a cheap and non-invasive method for diagnosis Tuberculosis. A modified method is devised to enhance handling capacity and minimize risk of contamination in culture.</p> <p>"22_samples_TTP_GU_method_comparison_dataset.csv" is a dataset for comparing standard method and modified method of sputum handling and storing procedures before being cultured in MGIT. MGIT is used in BD BACTEC 960 MGIT system which generates "Time to positive" hours for a culture to growth and "Growth Unit" for estimating the amount of growth.</p> <p>"348_samples_TTP_GU_modified method_dataset.csv " is a dataset for applying modified method on selected 348 sputum samples for culture in MGIT. The dataset contains "Time to positive", "Growth Unit", "ZN smear grade", and "Duration of frozen:.</p>
Relationship between decay resistance and moisture properties in wood modified with phenol formaldehyde and sorbitol-citric acid
<p>This dataset contains measurement data from the following publication: Belt, T.; Kyyrö, S.; Kilpinen, A. T. (2023) Relationship between decay resistance and moisture properties in wood modified with phenol formaldehyde and sorbitol-citric acid. Journal of Materials Science, 10.1007/s10853-023-08874-w. Small samples of Scots pine sapwood were modified using different concentrations of phenol formaldehyde (2.5, 5, 10, 20 and 30% resin solids content) and sorbitol-citric acid (5, 10, 20, 30 and 40% resin solids content) and then exposed to brown rot decay by <em>Coniophora puteana</em> and <em>Rhodonia placenta</em>. Sample masses and dimensions were measured at different points to determine their weight gain, anti-swelling efficiency and moisture exclusion efficiency due to modification, their mass loss due to decay and their moisture content at the end of the decay test. Fluorescence images were collected from decayed and control samples after the decay test. Further details on the experimental procedures can be found in the publication. </p> <p>The "Sample IDs and measurement data.csv" -file contains the sample IDs and all measured dimensions and mass data for every sample. Areas A<sub>dry0</sub>, Ad<sub>ry1</sub>, A<sub>wet</sub>, and A<sub>dry2</sub> are the cross-sectional areas of the samples in the dry state before modification, in the dry state after modification and before leaching, in the wet state during leaching, and in the dry state after leaching, respectively. Masses m<sub>dry0</sub>, m<sub>dry1</sub>, m<sub>dry2</sub>, m<sub>RH85</sub>, m<sub>wet</sub>, and m<sub>dry3</sub> are the masses of the samples in the dry state before modification, in the dry state after modification and before leaching, in the dry state after leaching, in the conditioned state at RH 85%, in the wet state at the end of the decay test, and in the dry state after the decay test, respectively.</p> <p>The "Fluorescence images" -folder contains fluorescence images collected from the samples. The image files are named according to the ID of the imaged sample, followed by additional tags. The samples modified using phenol formaldehyde were imaged using both green and UV excitation, and the file names contain the tag "green" or "UV" to denote the used excitation wavelengths. For all samples, the sample ID (and the excitation tag) are followed by a number to differentiate replicate images collected from the sample. </p>
Enhanced Westermo dataset - Transformed and Modified for Test case Selection and Priorotization in the context of Continuous Integration and Reinforcement Learning.
<p><strong>Overview</strong></p> <p>This repository contains a modified version of the existing, recently published dataset, Westermo. The initial dataset was gathered at Westermo Network Technologies AB, located in Västerås, Sweden. It encompasses over <strong>1 Million verdicts</strong> obtained from testing embedded systems, collected over a span of more than <strong>500 consecutive days</strong> of nightly testing. The dataset has been transformed and tailored specifically to cater to the research community, particularly for addressing challenges such as regression test selection, identification of flaky tests, and visualization of test results. The original dataset can be accessed through the reference provided in <strong>[1]</strong>.</p> <p>The Westermo dataset offers valuable historical information regarding the execution of test cases and their corresponding results. It serves as a valuable resource for evaluating and comparing different Test case Selection and Prioritization (TSP) techniques, enabling researchers to identify test cases that are more likely to fail during subsequent executions. Test cases in the dataset are characterized by attributes such as execution duration, previous last execution time, and the results of their recent executions.</p> <p>This dataset offers valuable historical information regarding the execution of test cases and their corresponding results. It serves as a valuable resource for evaluating and comparing different test case prioritization and selection techniques, enabling researchers to identify test cases that are more likely to fail during subsequent executions. Test cases in the dataset are characterized by attributes such as execution duration, previous last execution time, and the results of their recent executions.</p> <table align="left"> <caption><strong>Table 1: Dataset Overview</strong></caption> <tbody> <tr> <td>Test Cases</td> <td>1855</td> </tr> <tr> <td>CI Cycles</td> <td>15,197</td> </tr> <tr> <td>Verdict</td> <td>1,036,818</td> </tr> <tr> <td>Failed</td> <td>5.03%</td> </tr> </tbody> </table> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p> <p>However, the diversity and multitude of the features in the dataset can be irrelevant to some TSP approaches. This led us to perform a dataset conversion, where we customized Westermo to have the same features from Paint Control and IOF/ROL, two widely used datasets in Reinforcement Learning based TSP approaches.</p> <p>This conversion required the combination of multiple variables and generating the target ones. When it comes to generating the “LastResults” and “Cycle” values, further analysis was required and the data handling needed an in-depth understanding of how the nightly testing was conducted. This led us to investigate what a CI cycle is in their context, and we followed their definition of a session, stating that “a session is when we run a suite of tests on one test system with a certain software version and testware version”. When splitting the data according to the 9 different systems used, we were able to generate 9 different sub-sets that fit the CI context.</p> <p> </p> <p><strong>File Format</strong></p> <p>The compressed .zip file contains 9 files, each one corresponding to each of the 9 systems. The datasets are available in CSV format, with the semicolon (;) serving as the delimiter. The columns included are represented in the table below along with their descriptions.</p> <table> <caption><strong>Table 2: Parameters of the dataset</strong></caption> <thead> <tr> <th scope="col">Column Name</th> <th scope="col">Content</th> </tr> </thead> <tbody> <tr> <td>Id</td> <td>Unique numeric identifier of the test execution </td> </tr> <tr> <td>Name</td> <td>Unique numeric identifier of the test case</td> </tr> <tr> <td>Duration</td> <td>Approximated runtime of the test case</td> </tr> <tr> <td>CalcPrio</td> <td>Priority of the test case, calculated by the prioritization algorithm (output column, initially 0)</td> </tr> <tr> <td>LastRun</td> <td>Previous last execution of the test case as date-time-string (Format: <em>YYYY-MM-DD HH:ii </em>)</td> </tr> <tr> <td>LastResults</td> <td>List of previous test results (Failed: 1, Passed: 0), ordered by ascending age. Lists are delimited by [ ].</td> </tr> <tr> <td>Verdict</td> <td> <p>Test verdict of this test execution (Failed: 1, Passed: 0)</p> </td> </tr> <tr> <td>Cycle</td> <td>The number of the CI cycle this test execution belongs to.</td> </tr> </tbody> </table> <p> </p> <p>The implications of this conversion are important as it can help the previous works to re-assess their approaches and have more data for training and testing, as well as opening a broader data spectrum for future researchers in this field to find ready-to-use, rich datasets, on which they could evaluate their approaches and contribute to the TSP community. This also addresses the limitations in the field discussed in the systematic literature review <strong>[2]</strong>, stating that future research on TSP techniques should focus on collecting data from more recent subjects in a CI context with varying failure rates and larger execution times, as reproducible studies with appropriate datasets are needed to develop a usable body of knowledge regarding TSP over time. We believe that this conversion of the Westermo dataset is our contribution to alleviating the gap for the RL-based approaches.</p> <p>The original dataset can be found <a href="https://sites.mdu.se/aidoart/results/open-source/test-results-dataset-westermo">here.</a></p>
Data from: Nutrient identity modifies the destabilizing effects of eutrophication in grasslands
Nutrient enrichment can simultaneously increase and destabilize plant biomass production, with co-limitation by multiple nutrients potentially intensifying these effects. Here, we test how factorial additions of nitrogen (N), phosphorus (P), and potassium with essential nutrients (K+) affect the stability (mean/standard deviation) of aboveground biomass in 34 grasslands over seven years. Destabilization with fertilization was prevalent but was driven by single nutrients, not synergistic nutrient interactions. On average, N-based treatments increased mean biomass production by 21-51% but increased its standard deviation by 40-68% and so consistently reduced stability. Adding P increased interannual variability and reduced stability without altering mean biomass, while K+ had no general effects. Declines in stability were largest in the most nutrient-limited grasslands, or where nutrients reduced species richness or intensified species synchrony. We show that nutrients can differentially impact the stability of biomass production, with N and P in particular disproportionately increasing its interannual variability.
Jornada Basin and Experimental Range Mesquite Herbicide Project (JERHM) Connectivity Modifier Data, 2023
This dataset includes plant community composition, plant litter, soil depth, and shrub interspace fetch distance data collected in 2023 as part of the Jornada Experimental Range Herbicide Mesquite Project (JERHM). Data were collected to characterize plant community and ecosystem resource (plant litter, soil depth) responses to the use of Connectivity Modifiers (ConMods), which are used to reduce bare ground connectivity, alongside herbicide application to reduce honey mesquite (Neltuma glandulosa [=Prosopis glandulosa]) encroachment. ConMod and control (rebar-only) arrays were installed on 16 paired, 5-hectare plots, with one plot within each pair randomly selected to receive herbicide treatment in 2021 to reduce N. glandulosa abundance, or left untreated for comparison. Approximately 6 months after herbicide application (spring 2022), 12-unit ConMod and control (rebar-only) arrays were installed on experimental plots within 8 randomly selected N. glandulosa shrub interspaces (n = 8 arrays per plot, 4 per array type). Data were collected in the fall of 2023 at the end of the second growing season following array installation. There are no immediate plans to continue data collection.
Daily aerosol emissions changes in 2020 due to Covid19: modified SSP2-4.5 to account for sector activity level
<p>Daily aerosol emissions estimates for 2020, modified by the country-specific impacts of COVID-19 lockdown. </p> <p>This repository holds the netcdf files for aerosol and precursor emissions projected by the scenario SSP2-4.5, from the Scenario4MIPs database (<a href="https://esgf-node.llnl.gov/search/input4mips/">https://esgf-node.llnl.gov/search/input4mips/</a>), modified by the country and sector activity levels associated with lockdown for 2020, with observation-based data up until the 5th of July and a fixed estimate thereafter. This is the daily equivalent of <a href="https://zenodo.org/record/3951601#.XxYBsihKhPY">https://zenodo.org/record/3951601#.XxYBsihKhPY</a>. </p> <p>Funding was provided by the European Union’s Horizon 2020 Research and Innovation Programme under grant agreement nos. 820829 (CONSTRAIN) <a href="http://constrain-eu.org/">http://constrain-eu.org/</a> </p> <p>see <a href="https://github.com/Priestley-Centre/COVID19_emissions">https://github.com/Priestley-Centre/COVID19_emissions</a> for more details.</p>
Fall Detection Dataset Modified - Unicomfacauca
<p>Modification of the original TST Fall detection dataset (available at <a href="https://meet.google.com/linkredirect?authuser=0&dest=https%3A%2F%2Fwww.ieee-dataport.org%2Fdocuments%2Ftst-fall-detection-dataset-v2">https://www.ieee-dataport.org/documents/tst-fall-detection-dataset-v2</a>) in order to more accurately represent the event of a fall, and also adds a class related to people standing.</p> <p>Source Code Repository: <a href="https://github.com/CristianChilito/Fall-Detection-System-Unicomfacauca">https://github.com/CristianChilito/Fall-Detection-System-Unicomfacauca</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.