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1 to 5 of 5 Results

A predictive machine learning model for cannabinoid effect based on image detection of reactive oxygen species in microglia Feb 4, 2025 Jeffries, William W, 2025, "A predictive machine learning model for cannabinoid effect based on image detection of reactive oxygen species in microglia", https://doi.org/10.13021/ORC2020/AJXIK0, George Mason University Dataverse, V1 Code used in support of paper "A predictive machine learning model for cannabinoid effect based on image detection of reactive oxygen species in microglia"
Aerosol Composition during Dust Storms and Wildfires from the IMPROVE Network Apr 29, 2024 Tong, Daniel Quansong, 2024, "Aerosol Composition during Dust Storms and Wildfires from the IMPROVE Network", https://doi.org/10.13021/ORC2020/EOL1WJ, George Mason University Dataverse, V1 This 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 b...
Replication Data for "The Mason-Alberta Phonetic Segmenter: A forced alignment system based on deep neural networks and interpolation" Oct 23, 2023 Kelley, Matthew C; Perry, Scott James; Tucker, Benjamin V, 2023, "Replication Data for "The Mason-Alberta Phonetic Segmenter: A forced alignment system based on deep neural networks and interpolation"", https://doi.org/10.13021/ORC2020/PDSAP7, George Mason University Dataverse, V1 These are the TextGrid outputs of the alignments run during the evaluation process for the MAPS paper. They are separated into train, validation, and test sets. The results from training and running the Montreal Forced Aligner (MFA) are also provided. The tar file for MFA contain...
Road density, road features, and in-vehicle PM2.5 during daily trips taken by Washington, DC metro area commuters May 11, 2023 Krall, Jenna R, 2023, "Road density, road features, and in-vehicle PM2.5 during daily trips taken by Washington, DC metro area commuters", https://doi.org/10.13021/ORC2020/9EA00H, George Mason University Dataverse, V1, UNF:6:+x5TcYrmAs3MUZthKeXuRQ== [fileUNF] This dataset was used to conduct all analyses in the working paper, "Short-term associations of road density and road features with in-vehicle PM2.5 during daily trips" by Jenna R. Krall, Jonathan Thornburg, Ting Zhang, Anna Z. Pollack, Yi-Ching Lee, Michelle McCombs, and Lucas R...
Temple Data: Jomon and Yayoi Jan 28, 2021 Temple, Daniel H., 2021, "Temple Data: Jomon and Yayoi", https://doi.org/10.13021/ORC2020/LYETXQ, George Mason University Dataverse, V1, UNF:6:q4fveHZTnahwEHrJmjLK2g== [fileUNF] These data include long bone measurements for adults, cross-sectional geometric properties of long bones for subadults, and data regarding linear enamel hypoplasia formation for a series of individuals that was collected using a measuring microscope. The data are associated with...

A predictive machine learning model for cannabinoid effect based on image detection of reactive oxygen species in microglia

Feb 4, 2025

Jeffries, William W, 2025, "A predictive machine learning model for cannabinoid effect based on image detection of reactive oxygen species in microglia", https://doi.org/10.13021/ORC2020/AJXIK0, George Mason University Dataverse, V1

Code used in support of paper "A predictive machine learning model for cannabinoid effect based on image detection of reactive oxygen species in microglia"

Aerosol Composition during Dust Storms and Wildfires from the IMPROVE Network

Apr 29, 2024

Tong, Daniel Quansong, 2024, "Aerosol Composition during Dust Storms and Wildfires from the IMPROVE Network", https://doi.org/10.13021/ORC2020/EOL1WJ, George Mason University Dataverse, V1

This 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 b...

Replication Data for "The Mason-Alberta Phonetic Segmenter: A forced alignment system based on deep neural networks and interpolation"

Oct 23, 2023

Kelley, Matthew C; Perry, Scott James; Tucker, Benjamin V, 2023, "Replication Data for "The Mason-Alberta Phonetic Segmenter: A forced alignment system based on deep neural networks and interpolation"", https://doi.org/10.13021/ORC2020/PDSAP7, George Mason University Dataverse, V1

These are the TextGrid outputs of the alignments run during the evaluation process for the MAPS paper. They are separated into train, validation, and test sets. The results from training and running the Montreal Forced Aligner (MFA) are also provided. The tar file for MFA contain...

Road density, road features, and in-vehicle PM2.5 during daily trips taken by Washington, DC metro area commuters

May 11, 2023

Krall, Jenna R, 2023, "Road density, road features, and in-vehicle PM2.5 during daily trips taken by Washington, DC metro area commuters", https://doi.org/10.13021/ORC2020/9EA00H, George Mason University Dataverse, V1, UNF:6:+x5TcYrmAs3MUZthKeXuRQ== [fileUNF]

This dataset was used to conduct all analyses in the working paper, "Short-term associations of road density and road features with in-vehicle PM2.5 during daily trips" by Jenna R. Krall, Jonathan Thornburg, Ting Zhang, Anna Z. Pollack, Yi-Ching Lee, Michelle McCombs, and Lucas R...

Temple Data: Jomon and Yayoi

Jan 28, 2021

Temple, Daniel H., 2021, "Temple Data: Jomon and Yayoi", https://doi.org/10.13021/ORC2020/LYETXQ, George Mason University Dataverse, V1, UNF:6:q4fveHZTnahwEHrJmjLK2g== [fileUNF]

These data include long bone measurements for adults, cross-sectional geometric properties of long bones for subadults, and data regarding linear enamel hypoplasia formation for a series of individuals that was collected using a measuring microscope. The data are associated with...

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