George Mason University Dataverse
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Heated Condensation Framework (HCF) Algorithm and Analysis Data
No full textThis data was generated by Finley Hay-Chapman and modified by Briah Davis for use in research concerning land-atmosphere interactions. The data consist of single-column model output from the single column model version 6 (SCAM6) model within the larger Community Earth System Model. Outputs consists of various atmospheric and land surface variables. Boundary conditions were generated from the variational analysis product available for download at https://adc.arm.gov/discovery/#/. This specific model consists of output from May 1, 2012 to August 31, 2018. Time in the dataset has been converted to datetime64 format and filtered between 11 and 23 LST. Additionally, the data has been filtered for times when the sensible heat flux (SHFLX) and latent heat flux (LHFLX) are positive. Finally, the interface and midpoints pressures are calculated and appended to the DataArrays using the sigma level information provided in the original output. Note: Data were obtained from the Atmospheric Radiation Measurement (ARM) User Facility, a U.S. Department of Energy (DOE) Office of Science user facility managed by the Biological and Environmental Research Program
Aerosol Composition during Dust Storms and Wildfires from the IMPROVE Network
No full textThis dataset contains daily observations of PM10, PM2.5 and chemical composition measured by the Interagency Monitoring of Protected Visual Environment (IMPROVE) network. In addition the raw IMPROVE data, local dust storms and wildfire events are identified in a separate column based on the method described in Tong et al. (2017) and Zhao et al., (2015)
Code and Data for "A General Framework for Regression with Mismatched Data Based on Mixture Modeling"
No full textThis file contains code and data for replicating the simulation studies and the analysis in Sections 7.1 and 7.3 of the paper
Slawski, M., West, B.T., Bukke, P., Wang, Z., Diao, G., Ben-David, E.
"A General Framework for Regression with Mismatched Data Based on Mixture Modeling", to be published in the Journal of the Royal Statistical Society Series A (2024+)
Blanchard et al. 2024 RPPA intensity values
No full textRPPA intensity values used in the publication titled "Signaling dynamics in coexisting monoclonal cell subpopulations unveil mechanisms of resistance to anti-cancer compounds" by Blanchard et al. 2024. https://doi.org/10.1186/s12964-024-01742-
Social and Environmental Justice Implications of Flood-Related Road Closures in Virginia
No full textVirginia Road Closures data supporting manuscript submission, collected and processed from Virginia Department of Transportation data portal (SmarterRoads.org) for the time period September, 2019 - January, 2024
DEMend: Automating hydrological correction of Digital Elevation Models for enhanced urban flood modeling
No full textThe DEMend Toolbox is designed to automate the process of hydrological correction for Digital Elevation Models (DEMs). It incorporates existing, publicly available datasets, such as road networks, stream networks, and bridges/culverts, to identify and remove obstructions from DEMs. This improves flood modeling and hydrological analysis by ensuring accurate terrain representation for water flow analysis
Deformable Object Tracking Dataset (DOT)
No full textThe Deformable Object Tracking Dataset, DOT, is a large real-world dataset for tracking deformable objects with little or no texture. The key technology is to use UV fluorescent markers to provide features for correspondence tracking while maintain the object's original appearance. DOT has about one million video frames of four types of deformable objects: paper, cloth, rope and hands. For each motion, DOT provideS 2D videos with and without markers from multiple viewpoints, 3D models of the deformed object, and tracked ground truth correspondences in both 2D and 3D
Replication Data for: Identifying the Mechanism of Interaction Between Soil Moisture State and Summertime MCS Initiations In Weakly-Forced Synoptic Environments Using Convective-Permitting Simulations
No full textThis archive provides access to model data and analyses scripts used in the study: Identifying the Mechanism of Interaction Between Soil Moisture State and Summertime MCS Initiations In Weakly-Forced Synoptic Environments Using Convective-Permitting Simulations.
The archive consists of 3 main directories:
1. Data: All WRF data used in this study, in the form of wrfout (.nc) files and example namelist information used for WRF/WPS. Each file is organized into experiment group folders. 2. Records: Tabular data that documents Control, PB-1 individual case locations and times of MCS initiation in WRF, and NoMCS cases. 3. Analysis: Jupyter notebooks (.ipynb) used to create figures produced in publication, text file (.txt) listing the modules/version numbers used in jupyter, and python code (.py) detailing the method used in placement of PB-1 experiment in WRF
Multi-Modal Passive Perception Dataset for Off-Road Mobility in Extreme Low-Light Conditions
No full textThis dataset contains multi-modal passive perception data, including thermal, event, and stereo RGB cameras, IMU, GPS, and LiDAR for ground truth, to enable off-road mobility in extreme low-light conditions
Global Navigation Dataset
No full textGlobal Navigation Dataset (GND) contains multi-modal robot perception and action data across many university campuses with multiple traversability labels (open space, obstacles, stairs, off-road, and roadway)