1 to 10 of 54,576 Results
May 7, 2026 - Center for Advanced Medical Analytics (CAMA)
Kausch, Sherry, 2026, "Replication Data for: Modeling Heart Rate Patterns to Quantify Neonatal Opioid Withdrawal Syndrome", https://doi.org/10.18130/V3/RLOW6S, University of Virginia Dataverse, V1, UNF:6:Q1kdLvKSzbc3fN44Nn0s2A== [fileUNF]
Anonymized data set for replication of study findings. |
May 7, 2026 -
Replication Data for: Modeling Heart Rate Patterns to Quantify Neonatal Opioid Withdrawal Syndrome
Tabular Data - 6.3 MB - 32 Variables, 19576 Observations - UNF:6:Q1kdLvKSzbc3fN44Nn0s2A==
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May 7, 2026 -
Replication Data for: Modeling Heart Rate Patterns to Quantify Neonatal Opioid Withdrawal Syndrome
Plain Text - 3.7 KB -
MD5: 0d6aaa993c34e4cddcb1f56dc5d2c89c
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Apr 30, 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, V4
Particle Image Velocimetry for Bio-Inspired Vortex, Fin, and Boundary Interactions. |
ZIP Archive - 8.7 GB -
MD5: 7f71f09ad2ba7b306f5f01f6c57b620d
PIV and force data for "Ormonde, P. C., Zhu, Y., Quinn, D. B., & Moored, K. W. (2026). Rather than drafting, vortex capture dictates efficiency in three-hydrofoil schools. arXiv:2604.19121” |
Apr 30, 2026 - Biocomplexity Institute & Initiative
Mortveit, Henning S.; Adiga, Abhijin; Baek, Hannah; Bhattacharya, Parantapa; Eubank, Stephen; Machi, Dustin; Marathe, Madhav; Porebski, Przemyslaw; Swarup, Samarth; Venkatramanan, Srinivasan; Wilson, Mandy; Xie, Dawen, 2024, "Synthetic Population for Washington, US (ver. 2.4.0)", https://doi.org/10.18130/V3/PNGMRJ, University of Virginia Dataverse, V2, UNF:6:i+YB7Rre5h9cv3VjPNxfew== [fileUNF]
The synthetic population for the state of Washington is constructed to be statistically indistinguishable from the real population at the spatial resolution of a US block group as measured by the US Census on selected demographic variables, which in this case are age (AGEP), household income (HINCP), household size (NP), race (RAC1P) and hispanic (... |
Apr 30, 2026 -
Synthetic Population for Washington, US (ver. 2.4.0)
Tabular Data - 97 B - 2 Variables, 8 Observations - UNF:6:i+YB7Rre5h9cv3VjPNxfew==
This is a lookup file that defines the different activity type identifiers (integer) supported in our v.2.4.0 synthetic populations, along with the activity type verbiage so that when looking at location assignments or the population network, it is clear what activity the person is doing at that time. |
Apr 30, 2026 -
Synthetic Population for Washington, US (ver. 2.4.0)
Adobe PDF - 521.2 KB -
MD5: cf835bbb5dcd9b87ad3ee3efe17a1336
This document is a data dictionary to explain (generally) what the different files in the synthetic populations represent, as well as the column definitions. |
Apr 30, 2026 -
Synthetic Population for Washington, US (ver. 2.4.0)
XZ Archive - 100.8 MB -
MD5: 59d3814e29a09b69013156752414cd30
wa_activity_assignment_day.csv.xz contains the activity sequences for the synthetic people in the synthetic representation of Washington. This does not contain the locations where these activities are performed -- wa_location_assignment_day.csv.xz has the mapping of activities to locations. |
Apr 30, 2026 -
Synthetic Population for Washington, US (ver. 2.4.0)
XZ Archive - 3.1 MB -
MD5: 5c165562db01a49835e4371ad92a4cc9
wa_activity_locations.csv.xz is a list of activity locations (e.g. places where people go outside of home) in our synthetic representation of Washington. |
