cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.4231/5dvh-kv88
title: Chavas and Peters (2023, BAMS): Static energy has important conceptual benefits for explaining how our atmosphere works.

description: &lt;p&gt;Excel file for Figure 1 and MATLAB code + data for Figures 2 and 3 of the manuscript Chavas and Peters (2023) submitted to Bulletin of the American Meteorological Society (BAMS). Project abstract: Potential temperature and static energy are useful quantities for understanding the properties of air in our atmosphere. While both concepts are used widely in the climate community, static energy is used relatively little in the meteorology community, a contrast that is evident in both American Meteorological Society journal publications and in introductory textbooks. Here we highlight this contrast and emphasize key conceptual benefits of static energy. Static energy is an intuitive and tangible quantity that describes changes in temperature in terms of conversions among different forms of energy. This intuition can help explain basic atmospheric science concepts, such as the dry adiabatic lapse rate, to the introductory student and the established scientist alike. Bridging this gap between the weather and climate science communities is important as these communities must work together to understand and predict changing weather patterns in a warming world.&lt;/p&gt;
description: Excel file for Figure 1 and MATLAB code + data for Figures 2 and 3 of the manuscript Chavas and Peters (2023) submitted to Bulletin of the American Meteorological Society
DOI: 10.4231/4mag-jn90
title: Salt Stockpile Inventory - January 24 to 27, 2023- INDOT Lebanon Salt Facility

description: &lt;p&gt;&lt;iframe allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" allowfullscreen="" frameborder="0" height="315" src="https://www.youtube.com/embed/Pcj_3vDup6s" title="YouTube video player" width="560"&gt;&lt;/iframe&gt;&lt;/p&gt;

&lt;p&gt; &lt;/p&gt;

&lt;p&gt;Indiana Department of Transportation is evaluating the use of LiDAR technology to monitor the salt stockpile volumes. During the 2022-2023 winter season, technology was implemented to capture preseason and postseason volumes at over 120 stockpile locations statewide. Images are used to support the LiDAR digital surface models to validate the volumes. Scans were performed each time the snowplows returned to restock in order to determine salt use throughout the storm.  This time lapse shows 21 images collected during the period January 24&lt;sup&gt; &lt;/sup&gt;to 27, 2023.&lt;/p&gt;
description: This visualization shows RGB images, LiDAR images and estimated volume of the salt stockpile at the INDOT Lebanon Salt Facility throughout a winter storm.
DOI: 10.4231/f2kn-br43
title: Time lapse of weather, road speeds and INDOT trucks during a winter storm from December 22 to 25, 2022

description: &lt;p&gt;Indiana Department of Transportation has installed telematics on approximately 1100 snowplow trucks to monitor truck deployment.  This timelapse shows the location of those trucks during a winter storm and integrates doppler weather and highway speed data.  The blue circles are the active trucks. The dataset contains sample data of a route of one truck.&lt;/p&gt;

&lt;p&gt;&lt;u&gt;&lt;iframe allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" allowfullscreen="" frameborder="0" height="315" src="https://www.youtube.com/embed/JLz7SxeE-Qo" title="YouTube video player" width="560"&gt;&lt;/iframe&gt;&lt;/u&gt;&lt;/p&gt;
description: This time lapse shows interstate traffic speeds, doppler weather data, and telematics data from Indiana Department of Transportation trucks during a winter storm on December 22 to 25, 2022.
DOI: 10.4231/7gsh-5m42
title: INDOT Snowplow Dash Cam Video Timelapse during a December 22 and 23, 2022, Winter Storm.

description: &lt;p&gt;&lt;iframe allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" allowfullscreen="" frameborder="0" height="315" src="https://www.youtube.com/embed/KMQEQhVYPmQ" title="YouTube video player" width="560"&gt;&lt;/iframe&gt;&lt;/p&gt;

&lt;p&gt; &lt;/p&gt;

&lt;p&gt;This video provides truck dash camera images and location at one-minute intervals synchronized with a time-space heatmap of connected vehicle probe data speeds. Approximately 600 images are shown in this video over a 24 hour timeframe between December 22 and 23, 2022.&lt;/p&gt;

&lt;p&gt; &lt;/p&gt;

&lt;p&gt;Link: &lt;a href="https://youtu.be/KMQEQhVYPmQ"&gt;https://youtu.be/KMQEQhVYPmQ&lt;/a&gt;  &lt;/p&gt;
description: This shows a time lapse of an INDOT snowplow during a winter storm, along with a heatmap with highway speeds, color coded by mile marker and a map representation.
DOI: 10.4231/691j-5a92
title: Evaluation of Integrated Management Strategies on Soybean Sudden Death Syndrome (SDS) Root infection, Foliar Symptoms, Yield and Net Returns

description: &lt;p&gt;Sudden death syndrome (SDS), caused by &lt;em&gt;Fusarium virguliform&lt;/em&gt;e, is one of the top yield-reducing diseases of soybean. Methods for managing SDS are limited, but the adoption of resistant cultivars is a common strategy and the implementation of cultural practices such as strategic tillage, crop rotation, water drainage and adjustment of planting date can reduce SDS disease pressure. In addition, two seed treatments are registered for use for SDS, but there is limited Indiana specific data on theses. The objective of this research was to assess the effect of integrated management strategies that includes cultivar selection, seed treatment and seeding rate on SDS root colonization, root rot, foliar symptoms and yield in Indiana. Our goal was to determine the economic impact of these integrated management strategies in order to provide growers with a cost-effective management program for SDS.  &lt;/p&gt;

&lt;p&gt;The project dataset includes all the raw data and field trial information from this research that is now part of the published work Brown, M. T., Mueller, D. S., Kandel, Y. R. and Telenko, D. E. P. 2023. Evaluation of integrated management strategies on soybean sudden death syndrome (SDS) root infection, foliar symptoms, yield and net returns. Pathogens 12 (7). doi.org/10.3390/pathogens12070913.&lt;/p&gt;

&lt;p&gt;The dataset includes the raw excel files from each of the three field research trials. Each field file include basic field information, plot and treatment map, basic summary table of the data collected, raw subplot and whole plot data of disease ratings, yield data, and weather data. In addition the final data that was merged and SAS code is also included. &lt;/p&gt;
description: Abstract: Three soybean field trials were conducted in Indiana to evaluate the integration of seed treatment, cultivar selection, and seeding rate on sudden death syndrome (SDS) root infection, foliar symptoms, yield and net return.
DOI: 10.4231/kz5w-dc21
title: Modeling N2O emission from the pan-Arctic terrestrial ecosystems

description: &lt;table id="infotbl"&gt;
 &lt;tbody&gt;
 &lt;tr&gt;
 &lt;td&gt;
 &lt;p&gt;Nitrous oxide (N&lt;sub&gt;2&lt;/sub&gt;O) is a potent greenhouse gas with radiative forcing 265-298 times stronger than that of carbon dioxide (CO&lt;sub&gt;2&lt;/sub&gt;). Increasing atmospheric N&lt;sub&gt;2&lt;/sub&gt;O burden also contributes to stratospheric ozone depletion. Recent field studies show N&lt;sub&gt;2&lt;/sub&gt;O emissions from the Arctic ecosystems have increased due to warming. To date, the emissions across space and time have not been adequately quantified.  Here we revised an extant process-based biogeochemistry model, the Terrestrial Ecosystem Model (TEM) to incorporate more detailed processes of soil biogeochemical nitrogen (N) cycle, permafrost thawing effects, and atmospheric N&lt;sub&gt;2&lt;/sub&gt;O uptake in soils. The model is then used to analyze N&lt;sub&gt;2&lt;/sub&gt;O emissions from pan-Arctic terrestrial ecosystems. We find that both regional N&lt;sub&gt;2&lt;/sub&gt;O production and net emissions increased from 1969 to 2019, with production ranging from 1.2 - 1.3 Tg N yr &lt;sup&gt;-1 &lt;/sup&gt;and net emissions from 1.1 - 1.2 Tg N yr&lt;sup&gt;-1 &lt;/sup&gt;considering the permafrost thaw effects. Soil N&lt;sub&gt;2&lt;/sub&gt;O uptake from the atmosphere was 0.1 Tg N yr &lt;sup&gt;-1&lt;/sup&gt; with a small interannual variability. Atmospheric N deposition significantly increased N&lt;sub&gt;2&lt;/sub&gt;O emission by 31.5 &plusmn; 3.1%.  Spatially, terrestrial ecosystems act as net sources or sinks ranging from -12 to 700 mg N m&lt;sup&gt;-2&lt;/sup&gt; yr&lt;sup&gt;-1 &lt;/sup&gt;depending on temperature, precipitation, soil characteristics, and vegetation types in the region.&lt;/p&gt;
 &lt;/td&gt;
 &lt;/tr&gt;
 &lt;/tbody&gt;
&lt;/table&gt;
description: This dataset contains the main codes and data for the N2O emissions quantification from pan-Arctic terrestrial ecosystems on a process-based biogeochemical model.
DOI: 10.15468/dl.twqmzg
title: Occurrence Download

description: A dataset containing 4650 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Observation, Human Observation, Material sample, Material citation, Specimen, Living Specimen, Occurrence evidence)",
 "Continent is Europe",
 "OccurrenceStatus is Present",
 "TaxonKey is Bromopsis benekenii",
 "Year 2000-2024"
 ]
}

 The dataset includes 4650 records from 128 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0059543-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.4231/9c8x-h052
title: Raw Data and Results from Automatic Murine Cardiac Ultrasound and Photoacoustic Image Segmentations

description: &lt;p&gt;The purpose of this project was to apply deep learning via implementation of U-Net to automatically and more efficiently segment the anterior myocardium of murine cardiovascular ultrasound and photoacoustic data in order to calculate radial strain and oxygen saturation. By doing this, segmentation time improved 300-fold and the deep neural network used was able to perform segmentation on both healthy and infarcted myocardium. The results of this project show that deep learning can be used to extract physiological parameters from ultrasound and photoacoustic data in less time to monitor cardiac health. The content in this publication includes raw data and results from running the deep neural network on the validation set of the ultrasound and photoacoustic images.&lt;/p&gt;
description: Accuracy and dice scores from cross-validation reported in the cross-validation results spreadsheet. Radial strain raw data and results reported in strain results spreadsheet. Oxygen saturation values reported in sO2 results spreadsheet.
DOI: 10.4231/28gb-5023
title: Promoting Inclusive Design and Deployment of Connected and Automated Vehicles for Older Adults Through Education of Engineering Students

description: &lt;p&gt;The development of connected and automated vehicles (CAVs) holds promise for reducing traffic crashes and maintaining mobility among older adults. Challenges remain, however, in ensuring that CAVs are accessible, acceptable, affordable, and otherwise inclusive for older adults. The objective of this project was to increase graduate students&rsquo; awareness of and sensitivity to these issues, using a framework of experiential learning. The project provided an opportunity for University of Michigan (U-M) students enrolled in a graduate course on human-centered design and engineering to be involved in all four aspects of experiential learning &ndash; exploring, engaging, reflecting, and communicating &ndash; to meet the project objective. The project involved several primary tasks: 1) completion of a research synthesis on older adults and CAVs by the project team; 2) discussions between the project team and older adults themselves (termed community engagement); 3) presentations by the project team to students in the class on the project background, findings from the research synthesis and community engagement, and an industry perspective on older adults and CAVs; 4) implementation of student classroom projects on older adults and CAVs as part of their regular course curriculum; 5) development of posters by the students highlighting their classroom projects; 6) presentation of the posters by the students in a formal poster session at the University of Michigan Transportation Research Institute targeted to U-M faculty and staff, representatives from industry, and other undergraduate and graduate students; 7) evaluation through pre- and post-surveys of students to measure changes in knowledge about older adults and CAVs; and 8) development of a set of recommendations for future efforts to train and educate students in this area, as well as the design and deployment of CAVs themselves.  The project dataset includes the reference list of documents/websites reviewed during the literature search (.docx), field notes from older adult nominal groups and focus groups (.docx), voting results from older adults nominal groups (.docx), coding tables from older adult focus groups (.docx), pre- and post-data from surveys of engineering students (.csv), and data dictionaries from surveys of engineering students (.docx).&lt;/p&gt;
description: Inclusiveness of CAVs for older adults via literature review, older adult outreach and graduate student experiential learning. Data include: reference list, outreach field notes/voting results/coding tables, student survey data/data dictionaries.
DOI: 10.15468/dl.hcxkbq
title: Occurrence Download

description: A dataset containing 263 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Thymelaea velutina",
 "HasCoordinate is true"
 ]
}

 The dataset includes 263 records from 27 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0059542-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.4231/4f5s-5c18
title: Effects of PFAS on amphibians and echinostomes after a 21-d exposure

description: &lt;p&gt;PFAS are ubiquitous in the environment and have detrimental effects on the health of humans and wildlife, including immune function. Host-parasite interactions may be impacted by PFAS in the environment. Here are the results of a 21-d laboratory PFAS exposure on northern leopard frogs and parasite-infected ramshorn snails. We found differences in host parasite load when parasites were exposed to PFAS.&lt;/p&gt;
description: The effects of a 21-d exposure to PFAS on larval northern leopard frog susceptibility to parasites and parasite infectivity.
DOI: 10.4231/kh94-qh07
title: Tolerance and avoidance responses to novel saline conditions in an invasive treefrog

description: &lt;p&gt;Salinity is an environmental stressor for anurans, as their highly permeable skin makes them prone to osmotic stress when exposed to saline conditions. However, certain anuran species have colonized areas near saltwater habitats suggesting an ability to acclimate to saline conditions. Here, we evaluated tolerance and avoidance responses to saline conditions in adult Cuban treefrogs (&lt;em&gt;Osteopilus septentrionalis&lt;/em&gt;), an invasive anuran distributed throughout Florida. To examine salinity tolerance, adult frogs were maintained in two treatments simulating a freshwater (0.5 ppt) or brackish (8.0 ppt) environment for six weeks. Every two weeks, we submerged frogs in brackish solution to quantify individual weight change as a measure of salinity tolerance. We found that frogs maintained in brackish solution over time significantly lost more weight at weeks two and six when compared to week zero, suggesting that salinity is an environmental stressor for Cuban treefrogs. Yet, exposure to salinity over a longer period of time may change their physiological response to saline conditions as the weight change at week four was similar to the pre-exposure period at week zero. Since salinity appears to be a stressor for this species, we investigated avoidance behavior towards saline conditions by offering individuals a choice between freshwater or brackish environments. Our results showed that Cuban treefrogs chose freshwater environments more frequently and may thus avoid saline ones. This study reveals that a non-native species can use physiological and behavioral strategies to respond to salinity, a condition with dehydrating effects, potentially allowing them to expand their newly established ranges into areas that other anurans may not be able to colonize.&lt;/p&gt;
description: This study evaluates tolerance and avoidance responses to saline conditions in the Cuban treefrog (Osteopilus septentrionalis), an invasive anuran distributed throughout Florida.
DOI: 10.4231/xaxh-8n13
title: Statewide Analysis of Winter Storm After-Action Report for December 22nd-24th, 2022

description: &lt;p&gt;This after-action winter storm report provides agencies with the ability to quantify winter storm impact and can be used to make data-driven decisions for future winter events. It can also be used for training purposes.&lt;/p&gt;

&lt;p&gt;This report looks at mobility and impact of winter weather events statewide using connected vehicle data, weather data, snowplow telematics, and dash camera imagery during a storm that had over 700 miles of traffic operating at below 45 mph statewide.By combining all these data sources agencies are able to visualize the impact on interstates and representative operating districts to aid in redeployment strategies.&lt;/p&gt;

&lt;p&gt;The dataset contains a pdf file with charts of vehicle data, weather data, and snowplow telematics and a csv file that contains data from Indiana Interstate Congestion as roadway miles operating at below 45 mph.&lt;/p&gt;

&lt;p&gt;This after-action report is for the period of December 22nd - 24th, 2022. Complementary reports for other reporting periods can be found at &lt;a href="https://doi.org/10.4231/ACMF-JY72"&gt;10.4231/ACMF-JY72&lt;/a&gt;.&lt;/p&gt;
description: This report shows the statewide impact of a winter storm on December 22nd, 2022, using connected vehicle data, weather data, and snowplow telematics.
DOI: 10.4231/cad0-2985
title: Statewide Analysis of Winter Storm After-Action Report for January 21st-23rd, 2023

description: &lt;p&gt;This after-action winter storm report provides agencies with the ability to quantify winter storm impact and can be used to make data-driven decisions for future winter events. It can also be used for training purposes.&lt;/p&gt;

&lt;p&gt;This report looks at mobility and impact of winter weather events statewide using connected vehicle data, weather data, snowplow telematics, and dash camera imagery during a storm that had over 280 miles of traffic operating at below 45 mph statewide.By combining all these data sources agencies are able to visualize the impact on interstates and representative operating districts to aid in redeployment strategies.&lt;/p&gt;

&lt;p&gt;The dataset contains a pdf file with charts of vehicle data, weather data, and snowplow telematics and a csv file that contains data from Indiana Interstate Congestion as roadway miles operating at below 45 mph.&lt;/p&gt;

&lt;p&gt;This after-action report is for the period of January 21st-23rd, 2023. Complementary reports for other reporting periods can be found at &lt;a href="https://doi.org/10.4231/ACMF-JY72"&gt;10.4231/ACMF-JY72&lt;/a&gt;.&lt;/p&gt;
description: This report shows the statewide impact of a winter storm on January 21st, 2023, using connected vehicle data, weather data, and snowplow telematics.
DOI: 10.4231/wz91-pf09
title: Statewide Analysis of Winter Storm After-Action Report for January 24th-26th, 2023

description: &lt;p&gt;This after-action winter storm report provides agencies with the ability to quantify winter storm impact and can be used to make data-driven decisions for future winter events. It can also be used for training purposes.&lt;/p&gt;

&lt;p&gt;This report looks at mobility and impact of winter weather events statewide using connected vehicle data, weather data, snowplow telematics, and dash camera imagery during a storm that had over 300 miles of traffic operating at below 45 mph statewide.By combining all these data sources agencies are able to visualize the impact on interstates and representative operating districts to aid in redeployment strategies.&lt;/p&gt;

&lt;p&gt;The dataset contains a pdf file with charts of vehicle data, weather data, and snowplow telematics and a csv file that contains data from Indiana Interstate Congestion as roadway miles operating at below 45 mph.&lt;/p&gt;

&lt;p&gt;This after-action report is for the period January 24th - 26th, 2023. Complementary reports for other reporting periods can be found at &lt;a href="https://doi.org/10.4231/ACMF-JY72"&gt;10.4231/ACMF-JY72&lt;/a&gt;.&lt;/p&gt;
description: This report shows the statewide impact of a winter storm on January 24th, 2023, using connected vehicle data, weather data, and snowplow telematics.
DOI: 10.4231/ffcn-hm31
title: Analysis of Winter Storm After-Action Report for February 16th - 18th, 2023

description: &lt;p&gt;This after-action winter storm report provides agencies with the ability to quantify winter storm impact and can be used to make data-driven decisions for future winter events. It can also be used for training purposes.&lt;/p&gt;

&lt;p&gt;This report looks at mobility and impact of winter weather events statewide using connected vehicle data, weather data, snowplow telematics, and dash camera imagery during a storm that had over 80 miles of traffic operating at below 45 mph statewide.By combining all these data sources agencies are able to visualize the impact on interstates and representative operating districts to aid in redeployment strategies.&lt;/p&gt;

&lt;p&gt; &lt;/p&gt;

&lt;p&gt;The dataset contains a pdf file with charts of vehicle data, weather data, and snowplow telematics and a csv file that contains data from Indiana Interstate Congestion as roadway miles operating at below 45 mph.&lt;/p&gt;

&lt;p&gt;This after-action report is for the period February 16th-18th, 2022. Complementary reports for other reporting periods can be found at &lt;a href="https://doi.org/10.4231/ACMF-JY72"&gt;10.4231/ACMF-JY72&lt;/a&gt;.&lt;/p&gt;
description: This report shows the statewide impact of a winter storm on February 16th, 2023, using connected vehicle data, weather data, and snowplow telematics.
DOI: 10.4231/rjys-vn71
title: Statewide Analysis of Winter Storm After-Action Report for March 2nd-4th, 2023

description: &lt;p&gt;This after-action winter storm report provides agencies with the ability to quantify winter storm impact and can be used to make data-driven decisions for future winter events. It can also be used for training purposes.&lt;/p&gt;

&lt;p&gt;This report looks at mobility and impact of winter weather events statewide using connected vehicle data, weather data, snowplow telematics, and dash camera imagery during a storm that had over 250 miles of traffic operating at below 45 mph statewide.By combining all these data sources agencies are able to visualize the impact on interstates and representative operating districts to aid in redeployment strategies.&lt;/p&gt;

&lt;p&gt;The dataset contains a pdf file with charts of vehicle data, weather data, and snowplow telematics and a csv file that contains data from Indiana Interstate Congestion as roadway miles operating at below 45 mph.&lt;/p&gt;

&lt;p&gt;This after-action report is for the period March 2nd - 4th, 2023. Complementary reports for other reporting periods can be found at &lt;a href="https://doi.org/10.4231/ACMF-JY72"&gt;10.4231/ACMF-JY72&lt;/a&gt;.&lt;/p&gt;
description: This report shows the statewide impact of a winter storm on March 2nd, 2023, using connected vehicle data, weather data, and snowplow telematics.