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1 to 10 of 742 Results

Code for modeling WASH components by RTMB Apr 6, 2026 - School of Engineering and Applied Science Fang, Bin, 2026, "Code for modeling WASH components by RTMB", https://doi.org/10.18130/V3/ED1WNW, University of Virginia Dataverse, V1 The repository contains two R code files: data preprocessing and model/prediction/evaluation files.
A global dataset of household-level water, sanitation, and hygiene (WASH) predicted conditions Apr 6, 2026 - School of Engineering and Applied Science Fang, Bin, 2026, "A global dataset of household-level water, sanitation, and hygiene (WASH) predicted conditions", https://doi.org/10.18130/V3/O58DEE, University of Virginia Dataverse, V1 The dataset includes GeoTIFF raster layers representing the predicted probability of each ordinal class. Files are named using a standardized convention that encodes the WASH component and ordinal class name.
Data for: Mechanistic insights into laser-generated surface nanomorphology from physics-guided, explainable machine learning and molecular dynamics simulations Apr 3, 2026 - School of Engineering and Applied Science Valavanis, Antonios S.; Gurevich, Evgeny L.; Shugaev, Maxim V.; Zhigilei, Leonid V., 2026, "Data for: Mechanistic insights into laser-generated surface nanomorphology from physics-guided, explainable machine learning and molecular dynamics simulations", https://doi.org/10.18130/V3/XCKLVR, University of Virginia Dataverse, V2 Data for: Mechanistic insights into laser-generated surface nanomorphology from physics-guided, explainable machine learning and molecular dynamics simulations
Data for: A Physics-Regularized Machine Learning Approach for Predicting Time–Temperature–Transformation Curves in Alloys: Application to Uranium-Based Alloys Mar 30, 2026 - Materials Informatics Group Garg, Sunidhi; Jishnu Bhattacharyya; Vineet V. Joshi; Sean R. Agnew; Prasanna V. Balachandran, 2026, "Data for: A Physics-Regularized Machine Learning Approach for Predicting Time–Temperature–Transformation Curves in Alloys: Application to Uranium-Based Alloys", https://doi.org/10.18130/V3/EXJA3W, University of Virginia Dataverse, V1 The data in each sheet is described below: 1. Data_train: Training dataset used for all the ML models 2. Data_test: Test dataset used for all the ML models 3. Data_virtual: Dataset having the principal component (PC) values of U-Mo-X alloys absent from train and test set and is the input to predict the TTT curves for these U-Mo-X alloys 4. Data_cal...
Particle Image Velocimetry for Bio-Inspired Vortex, Fin, and Boundary Interactions Mar 26, 2026 - School of Engineering and Applied Science Zhu, Yuanhang; Ormonde, Pedro C.; Liu, Leo; Pan, Yu; Westfall, Elizabeth; Han, Tianjun; Zhu, Joseph; Zhong, Qiang; Bart-Smith, Hilary; Dong, Haibo; Lauder, George V.; Moored, Keith W.; Quinn, Daniel B., 2025, "Particle Image Velocimetry for Bio-Inspired Vortex, Fin, and Boundary Interactions", https://doi.org/10.18130/V3/UL6CJE, University of Virginia Dataverse, V2 Particle Image Velocimetry for Bio-Inspired Vortex, Fin, and Boundary Interactions.
Data for: An Active Learning Workflow for Predicting Misfit Volume in Body-Centered Cubic Refractory High-Entropy Alloys Mar 23, 2026 - Materials Informatics Group Liu, Shunshun; Balachandran, Prasanna V., 2026, "Data for: An Active Learning Workflow for Predicting Misfit Volume in Body-Centered Cubic Refractory High-Entropy Alloys", https://doi.org/10.18130/V3/AD6H08, University of Virginia Dataverse, V1 Data for: An Active Learning Framework for Predicting Misfit Volume in Body-Centered Cubic Refractory High-Entropy Alloys. This repository contains relaxation trajectories for all BCC HEA crystal structures, and 11 template SQS structures.
SUPPLEMENTAL MATERIALS for "Free testosterone independently predicts metabolic syndrome severity in U.S. adolescent girls aged 12 to 19 years" Mar 18, 2026 - School of Medicine Burt Solorzano, Christine; McCartney, Christopher; Pannone, Aaron; Kim, Su Hee; Gurka, Matthew; DeBoer, Mark, 2026, "SUPPLEMENTAL MATERIALS for "Free testosterone independently predicts metabolic syndrome severity in U.S. adolescent girls aged 12 to 19 years"", https://doi.org/10.18130/V3/WCIKL0, University of Virginia Dataverse, V1 Supplemental analyses for "Free testosterone independently predicts metabolic syndrome severity in U.S. adolescent girls aged 12 to 19 years"
Replication Data for: Blue Light Enhances Background Current and Dopamine Sensitivity of Carbon-Fiber Microelectrodes During Fast-Scan Cyclic Voltammetry Mar 6, 2026 - Department of Chemistry Donarski, Eric, 2026, "Replication Data for: Blue Light Enhances Background Current and Dopamine Sensitivity of Carbon-Fiber Microelectrodes During Fast-Scan Cyclic Voltammetry", https://doi.org/10.18130/V3/CSSH1Y, University of Virginia Dataverse, V1 This dataset contains both raw and processed data that demonstrates the potential for visible (blue) light to produce a photocurrent and enhance dopamine detection during FSCV experiments.
Supporting data for manuscript Dulko et al., 2025 Mar 5, 2026 - School of Medicine Dulko, Elzbieta, 2026, "Supporting data for manuscript Dulko et al., 2025", https://doi.org/10.18130/V3/BADMP8, University of Virginia Dataverse, V1 MATLAB table including spike times and ECoG from all single-unit recordings.
Replication Data for: Parasite defense covaries with reproductive timing, not with resistance Feb 28, 2026 - Department of Biology Gibson, Amanda, 2026, "Replication Data for: Parasite defense covaries with reproductive timing, not with resistance", https://doi.org/10.18130/V3/U3KH8P, University of Virginia Dataverse, V1, UNF:6:bzgkjimjwRmjowJUc2zG+Q== [fileUNF] Data for the manuscript "Parasite defense covaries with reproductive timing, not with resistance"

Code for modeling WASH components by RTMB

Apr 6, 2026 - School of Engineering and Applied Science

Fang, Bin, 2026, "Code for modeling WASH components by RTMB", https://doi.org/10.18130/V3/ED1WNW, University of Virginia Dataverse, V1

The repository contains two R code files: data preprocessing and model/prediction/evaluation files.

A global dataset of household-level water, sanitation, and hygiene (WASH) predicted conditions

Apr 6, 2026 - School of Engineering and Applied Science

Fang, Bin, 2026, "A global dataset of household-level water, sanitation, and hygiene (WASH) predicted conditions", https://doi.org/10.18130/V3/O58DEE, University of Virginia Dataverse, V1

The dataset includes GeoTIFF raster layers representing the predicted probability of each ordinal class. Files are named using a standardized convention that encodes the WASH component and ordinal class name.

Data for: Mechanistic insights into laser-generated surface nanomorphology from physics-guided, explainable machine learning and molecular dynamics simulations

Apr 3, 2026 - School of Engineering and Applied Science

Valavanis, Antonios S.; Gurevich, Evgeny L.; Shugaev, Maxim V.; Zhigilei, Leonid V., 2026, "Data for: Mechanistic insights into laser-generated surface nanomorphology from physics-guided, explainable machine learning and molecular dynamics simulations", https://doi.org/10.18130/V3/XCKLVR, University of Virginia Dataverse, V2

Data for: Mechanistic insights into laser-generated surface nanomorphology from physics-guided, explainable machine learning and molecular dynamics simulations

Data for: A Physics-Regularized Machine Learning Approach for Predicting Time–Temperature–Transformation Curves in Alloys: Application to Uranium-Based Alloys

Mar 30, 2026 - Materials Informatics Group

Garg, Sunidhi; Jishnu Bhattacharyya; Vineet V. Joshi; Sean R. Agnew; Prasanna V. Balachandran, 2026, "Data for: A Physics-Regularized Machine Learning Approach for Predicting Time–Temperature–Transformation Curves in Alloys: Application to Uranium-Based Alloys", https://doi.org/10.18130/V3/EXJA3W, University of Virginia Dataverse, V1

The data in each sheet is described below: 1. Data_train: Training dataset used for all the ML models 2. Data_test: Test dataset used for all the ML models 3. Data_virtual: Dataset having the principal component (PC) values of U-Mo-X alloys absent from train and test set and is the input to predict the TTT curves for these U-Mo-X alloys 4. Data_cal...

Particle Image Velocimetry for Bio-Inspired Vortex, Fin, and Boundary Interactions

Mar 26, 2026 - School of Engineering and Applied Science

Zhu, Yuanhang; Ormonde, Pedro C.; Liu, Leo; Pan, Yu; Westfall, Elizabeth; Han, Tianjun; Zhu, Joseph; Zhong, Qiang; Bart-Smith, Hilary; Dong, Haibo; Lauder, George V.; Moored, Keith W.; Quinn, Daniel B., 2025, "Particle Image Velocimetry for Bio-Inspired Vortex, Fin, and Boundary Interactions", https://doi.org/10.18130/V3/UL6CJE, University of Virginia Dataverse, V2

Particle Image Velocimetry for Bio-Inspired Vortex, Fin, and Boundary Interactions.

Data for: An Active Learning Workflow for Predicting Misfit Volume in Body-Centered Cubic Refractory High-Entropy Alloys

Mar 23, 2026 - Materials Informatics Group

Liu, Shunshun; Balachandran, Prasanna V., 2026, "Data for: An Active Learning Workflow for Predicting Misfit Volume in Body-Centered Cubic Refractory High-Entropy Alloys", https://doi.org/10.18130/V3/AD6H08, University of Virginia Dataverse, V1

Data for: An Active Learning Framework for Predicting Misfit Volume in Body-Centered Cubic Refractory High-Entropy Alloys. This repository contains relaxation trajectories for all BCC HEA crystal structures, and 11 template SQS structures.

SUPPLEMENTAL MATERIALS for "Free testosterone independently predicts metabolic syndrome severity in U.S. adolescent girls aged 12 to 19 years"

Mar 18, 2026 - School of Medicine

Burt Solorzano, Christine; McCartney, Christopher; Pannone, Aaron; Kim, Su Hee; Gurka, Matthew; DeBoer, Mark, 2026, "SUPPLEMENTAL MATERIALS for "Free testosterone independently predicts metabolic syndrome severity in U.S. adolescent girls aged 12 to 19 years"", https://doi.org/10.18130/V3/WCIKL0, University of Virginia Dataverse, V1

Supplemental analyses for "Free testosterone independently predicts metabolic syndrome severity in U.S. adolescent girls aged 12 to 19 years"

Replication Data for: Blue Light Enhances Background Current and Dopamine Sensitivity of Carbon-Fiber Microelectrodes During Fast-Scan Cyclic Voltammetry

Mar 6, 2026 - Department of Chemistry

Donarski, Eric, 2026, "Replication Data for: Blue Light Enhances Background Current and Dopamine Sensitivity of Carbon-Fiber Microelectrodes During Fast-Scan Cyclic Voltammetry", https://doi.org/10.18130/V3/CSSH1Y, University of Virginia Dataverse, V1

This dataset contains both raw and processed data that demonstrates the potential for visible (blue) light to produce a photocurrent and enhance dopamine detection during FSCV experiments.

Supporting data for manuscript Dulko et al., 2025

Mar 5, 2026 - School of Medicine

Dulko, Elzbieta, 2026, "Supporting data for manuscript Dulko et al., 2025", https://doi.org/10.18130/V3/BADMP8, University of Virginia Dataverse, V1

MATLAB table including spike times and ECoG from all single-unit recordings.

Replication Data for: Parasite defense covaries with reproductive timing, not with resistance

Feb 28, 2026 - Department of Biology

Gibson, Amanda, 2026, "Replication Data for: Parasite defense covaries with reproductive timing, not with resistance", https://doi.org/10.18130/V3/U3KH8P, University of Virginia Dataverse, V1, UNF:6:bzgkjimjwRmjowJUc2zG+Q== [fileUNF]

Data for the manuscript "Parasite defense covaries with reproductive timing, not with resistance"

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Find and cite data across all research fields.Choose LibraData below to share and archive your data

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