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11 to 20 of 718 Results
Audio PhD Dissertation of Nicholas Gardella | Responsible and Equitable Use of AI Code Generators in Computer Science Education
Apr 21, 2026 - School of Engineering and Applied Science
Gardella, Nicholas, 2026, "Audio PhD Dissertation of Nicholas Gardella | Responsible and Equitable Use of AI Code Generators in Computer Science Education", https://doi.org/10.18130/V3/VM1IPO, University of Virginia Dataverse, V1
This is the archival audiobook version of the PhD Dissertation of Nicholas Gardella, Responsible and Equitable Use of AI Code Generators in Computer Science Education.
PreMo: A Clinical and Vital Sign Dataset of Very-Low-Birth Weight Infants from 4 Neonatal Intensive Care Units
Apr 21, 2026 - Center for Advanced Medical Analytics (CAMA)
German Mesner, Ian, 2026, "PreMo: A Clinical and Vital Sign Dataset of Very-Low-Birth Weight Infants from 4 Neonatal Intensive Care Units", https://doi.org/10.18130/V3/KCBTMS, University of Virginia Dataverse, V1
PreMo Deidentified export of vital signs and REDCap clinical data for the PreMo 4-NICU study of very low birth weight infants Please additionally cite the corresponding manuscript Vital signs, demographics, and clinical events for low-birth-weight infants from four intensive care units Ian German Mesner, Doug E. Lake, Sherry L. Kausch, Katy N Krahn...
RAISE (Retrofitting Allocation using Income & Spatial Equity): A Tunable Strategy for Household Retrofitting Allocations
Apr 20, 2026 - Department of Computer Science
Kishore, Aparna, 2026, "RAISE (Retrofitting Allocation using Income & Spatial Equity): A Tunable Strategy for Household Retrofitting Allocations", https://doi.org/10.18130/V3/BHIB7J, University of Virginia Dataverse, V1, UNF:6:1Z/FcgeIHU7PJ2+7ISL3Dw== [fileUNF]
The dataset includes both the code and output data for the research work on the retrofitting optimization framework called RAISE. RAISE is designed to allocate state retrofitting budgets to households in a way that maximizes energy savings while ensuring a balanced distribution of funds across counties and income groups. The input folder contains t...
Cascading_Effects_of_Defeat_Behavior_and_Outcomes_Dataset
Apr 18, 2026 - Department of Biology
O'Connor, Clara, 2026, "Cascading_Effects_of_Defeat_Behavior_and_Outcomes_Dataset", https://doi.org/10.18130/V3/YMTSS6, University of Virginia Dataverse, V1, UNF:6:Px97iI7ZrlsQxmhZ0CF5jA== [fileUNF]
Data used in the analysis of the paper entitled "Cascading effects of defeat: Age-independent loser effects alter partner behavior". Behavior and fight outcome data for focal and partner forked fungus beetles (Bolitotherus cornutus). Each row distills data from one 2.5 hour fight video.
The Life of Saint Mary the Egyptian: Toward a Digital Critical Edition of the Old French Version T with English Translations
The Life of Saint Mary the Egyptian: Toward a Digital Critical Edition of the Old French Version T with English Translations
Apr 17, 2026
Cantrell, Loren, 2026, "The Life of Saint Mary the Egyptian: Toward a Digital Critical Edition of the Old French Version T with English Translations", https://doi.org/10.18130/V3/U2SCIX, University of Virginia Dataverse, V1, UNF:6:aE6LTsWFyDmlvQ7NdmIpWQ== [fileUNF]
Source files and code for the digital dissertation The Life of Saint Mary the Egyptian: Toward a Digital Critical Edition of the Old French Version T with English Translations, including XML data, scripts, and documentation.
Replication Data for: Thermal Transport in γ-InSe: Bulk Single Crystals and Thin Flakes
Replication Data for: Thermal Transport in γ-InSe: Bulk Single Crystals and Thin Flakes
Apr 11, 2026 - Department of Electrical and Computer Engineering
Tonni, Farjana Ferdous, 2026, "Replication Data for: Thermal Transport in γ-InSe: Bulk Single Crystals and Thin Flakes", https://doi.org/10.18130/V3/TJTASK, University of Virginia Dataverse, V1
This dataset was created to document experimentally measured thermal and thermoelectric transport properties of layered metal chalcogenide thin films under controlled conditions. It includes temperature-dependent in-plane thermal conductivity, sample thickness, and supporting structural and compositional characterization data. The dataset enables a...
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...
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"
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