cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.4231/93az-1k22
title: Fire design of SpeedCore walls and CFT columns

description: &lt;p&gt;This computer program was developed to simulate the behavior of composite walls and columns subjected to fire loading. The program is based on the fiber analysis method and the fundamental axial force-moment-curvature-temperature relationship of the member cross-section. For composite columns, only uniform heating (from all sides) is considered. For composite walls, uniform heating and one-sided heating are considered. Additionally, for composite walls, there is an option to simulate the whole planar wall length, or a unit width wall segment taken from the complete wall length. Two versions of the tool were developed compatible with Matlab and Octave softwares. A Graphical User Interface (GUI) was developed for the fiber model with the main aim of enhancing its usability and giving designers the ability to better manipulate the inputs and visualize the results. The GUI was developed using MATLAB App Designer. The user interface was designed with the ability to run the model in multiple ways depending on user preferences and input and display the results as interactive plots.&lt;/p&gt;
description: This tool is developed to analyze the behavior of the SpeedCore walls and CFT columns under fire loading using the fiber-based section analysis.
DOI: 10.4231/pyz7-v839
title: Dataset: A Case Study of the Importance of Publicly-Funded Research to Coastal Regions

description: &lt;p&gt;This dataset includes information on peer-reviewed publications that were submitted to the National Sea Grant Library (NSGL) between 2001 and 2015. The data includes title, author(s), year of publication, and journal in which each publication was shared, as well as the journal impact factor for the journal and year of publication, extracted from the InCites database, and number of citations (citation index) collected via Google Scholar in 2016. &lt;/p&gt;
description: Dataset for Behl et al. (in review) in which we conduct a bibliometric analysis of 6,500+ peer-reviewed publications generated over a 15-year period by the National Oceanic and Atmospheric Administration’s (NOAA) Sea Grant program.
DOI: 10.4231/34tj-s109
title: Estimation of the Probability Density Function of Random Displacements from Images

description: &lt;p&gt;This is the data sets that used to develop, verify, and demonstrate the use of Image-based Probability Estimation of Displacement (iPED). iPED is an image-based algorithm to find the probability density function (PDF) of particle displacements from a sequence of images. iPED does not make any assumptions about the shape of the particle intensity profile or the PDF of the displacements. We compare iPED&rsquo;s performance with the previous correlation-based method for both Gaussian and non-Gaussian particle intensity profiles undergoing Gaussian or non-Gaussian processes. The datasets present here can be used to reproduce the figures and analysis reported in the paper.&lt;/p&gt;
description: We introduce a novel approach to Image-based Probability Estimation of Displacement (iPED) which is direct estimation of the PDF of displacement of racers within images. Data sets to reproduce the plots and sample images are available here.
DOI: 10.4231/02rb-9p04
title: Post-Earthquake Fire Simulations: Videos of The Analyses

description: &lt;p&gt;This project focuses on the post-earthquake fire analysis and fire resistant design of steel buildings with moment-resisting-frames (MRFs). Steel building structures are designed with special MRFs to resist earthquake loads in high seismic zones. The post-earthquake fire behavior of these structures is analyzed by: (i) first subjecting to seismic ground motion records scaled appropriately to represent design-basis and maximum-considered earthquakes, and (ii) then subjecting the earthquake damaged building to realistic compartment fire scenarios of different durations and intensities. The structures are modeled and analyzed in 3D using ABAQUS, while accounting for various sources of material and geometric nonlinearity and potential damage modes.&lt;/p&gt;

&lt;p&gt;Please note that the type of all the video files is Quicktime (.mov), and they can be opened using different media players such as, VLC, PowerDVD, and Adobe Flash Player.&lt;/p&gt;
description: This repository archives the videos of the simulations of the designed structure to different earthquakes and post-earthquake fire scenarios.
DOI: 10.4231/rna2-wj54
title: Wabash River Baseflow Dataset 2015

description: &lt;p&gt;This dataset contains geochemical and isotopic data which were collected in the autumn of 2015 longitudinally down the Wabash River from its headwaters in Fort Recovery, OH to its confluence with the Ohio River near New Haven, IL. The following data were measured: general geochemistry (standard suite of cations and anions), stable isotopes of water (&lt;sup&gt;2&lt;/sup&gt;H and &lt;sup&gt;18&lt;/sup&gt;O), chlorine-36 (&lt;sup&gt;36&lt;/sup&gt;Cl/Cl) and strontium isotopes (&lt;sup&gt;87&lt;/sup&gt;Sr/&lt;sup&gt;86&lt;/sup&gt;Sr). Each set of isotopic data is collected in its own individual excel spreadsheet and each spreadsheet is accompanied by a ReadMe in pdf format.&lt;/p&gt;
description: This dataset contains the geochemical and isotopic data from the 2015 baseflow sampling campaign in the Wabash River watershed.
DOI: 10.4231/1tzx-br43
title: Structural attributes derived from Google Street View imagery, Louisiana coastal zone

description: &lt;p&gt;When developing plans for flood risk mitigation, one of the first hurdles local and state regional decision-makers must clear is gathering data on what assets actually exist on the ground in their jurisdictions. Even in areas like Louisiana&mdash;where significant effort has been taken to study flood risk since Hurricane Katrina struck in 2005&mdash;property data sets are incomplete, fragmented across agencies and jurisdictions, and obsolete. This data set, funded by the Andrew W Mellon Foundation, uses automated image processing of Google Street View pictures to extract building attributes relevant to flood risk, such as the foundation height and type, square footage of the building footprint, number of stories, and usage (e.g., residential, commercial). The classification and inference of these attributes were produced using machine learning methods for the purpose of developing structure-level estimates of risk that have been incorporated into a data viewer and decision support system. Risk estimates are derived from these building characteristics and hazard estimates from Louisiana&#39;s 2017 Coastal Master Plan. &lt;/p&gt;
description: Structural attributes relevant to flood risk (foundation height/type, square footage, number of stories, building type), produced using machine learning for automated image analysis of GSV images.
DOI: 10.4231/7bzn-gm13
title: Orthogonal polynomials relative to a generalized Marchenko–Pastur measure

description: &lt;p&gt;A number of Matlab functions are provided that allow the computation to full double precision of the three-term recurrence coefficients for orthogonal polynomials relative to a generalized Marchenko&ndash;Pastur probability measure. They implement three different approaches, one based on modified moments, one based on a modification algorithm, and another one using discretization. The results produced by them are consistently the same.&lt;/p&gt;
description: A set of MATLAB scripts related to orthogonal polynomials relative to a generalized Marchenko–Pastur measure
DOI: 10.4231/6bar-6w02
title: Population-specific brain atlases for early-to-middle adolescent collision-sport athletes

description: &lt;p&gt;This repository present population-specific brain atlases for early-to-middle adolescent (ages 13-19) collision-sport athletes, based on the MRI scans from the longitudinal database of Purdue Neurotrauma Group. The brain atlases were developed in an effort to facilitate multimodal neuroimaging studies, specifically to minimize bias introduced in spatial normalization, improve sensitivity of voxel-wise statistical analysis, and therefore better clarify the mechanisms that lead to traumatic brain injury in adolescent athletes, which is one of our long-term commitments to this vulnerable population. Image processing software including &lt;em&gt;FSL,&lt;/em&gt; &lt;em&gt;ANTs&lt;/em&gt;, and &lt;em&gt;Freesurfer&lt;/em&gt; were used to create the templates (T1-weighted and DTI) and semantic labels (cortical and white matter parcellations). To scale and speed up the atlas creation, we established a high-throughput high-performance computing workflow which integrated Open Science Grid and Purdue Community Clusters.&lt;/p&gt;
description: Population-specific brain atlases for early-to-middle adolescent collision-sport athletes in the longitudinal database of Purdue Neurotrauma Group, including cortical and white matter parcellations, a T1-weighted template, and a DTI template.
DOI: 10.15468/dl.pgjjxq
title: Occurrence Download

description: A dataset containing 1657413 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Tracheophyta",
 "DecimalLatitude is greater than or equal to 30.0",
 "DecimalLatitude is less than or equal to 35.0",
 "DecimalLongitude is greater than or equal to -100.0",
 "DecimalLongitude is less than or equal to -95.0",
 "HasCoordinate is TRUE",
 "HasGeospatialIssue is FALSE"
 ]
}

 The dataset includes 1657413 records from 259 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0059446-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.4231/ezdx-xt41
title: SNP datasets and passport information of sorghum accessions from Ethiopia

description: &lt;p&gt;Phenotypic data collected from field trials, genotypic data generated through genotyping by sequencing, coupled with agro-climatic data of sorghum accessions from Ethiopia were used to conduct comprehensive germplasm characterizations. The datasets were also used to implement genome-environment association (GEA) studies to explore the genetic basis of adaptive traits and describe insight into the Ethiopian sorghum germplasm, which is important in the world sorghum collection. &lt;/p&gt;
description: Agro-climatic information, phenotypic and SNP datasets were generated for 1628 Ethiopian sorghum accessions and utilized for a study on germplasm characterization and genome-environment association studies.
DOI: 10.4231/b1ka-gz57
title: Summer Science Program in Biochemistry - Characterization of the Cdc14 phosphatase homolog from Botrytis cinerea

description: &lt;p&gt;&lt;b&gt;The Research Project in SSP Biochemistry&lt;/b&gt;&lt;/p&gt;

&lt;p&gt;Cdc14 enzymes have been reported to be required for normal plant infection by several plant pathogen species. In the SSP Biochemistry program, research groups of 3 participants each purify and characterize the Cdc14 homolog encoded by a different plant fungal pathogen species. Each group is initially given the gene sequence for the putative Cdc14 homolog from a phytopathogenic fungus. Their overall goal is to determine if this protein would be a suitable target for development of a novel fungicide to protect crops from pathogens. They first use bioinformatic tools to generate a hypothesis about the function of the protein encoded by their gene sequence. Then, they use a recombinant plasmid to overexpress their protein in &lt;i&gt;E. coli&lt;/i&gt; and purify it using nickel affinity chromatography. They characterize steady-state kinetic properties and substrate specificity of their enzymes and compare the results to previously characterized Cdc14 from the model fungal species &lt;i&gt;Saccharomyces cerevisiae&lt;/i&gt; (ScCdc14), for which structural information is available. They then design an assay to test inhibition of their enzyme by a series of compounds originally identified as &lt;i&gt;in vitro&lt;/i&gt; inhibitors of ScCdc14. They choose the best one, perform computational docking to predict how it might bind to the homology-based structural model of their enzyme&rsquo;s active site that they previously generated, and finally hypothesize about ways to optimize their inhibitor structure to improve binding and specificity by taking advantage of known features of Cdc14 substrates. In the end they conclude whether or not the active site substrate specificity is conserved enough to justify using the ScCdc14 structure as a model for designing inhibitors to their enzyme. In this publication, the biochemical results and the homology based structural modeling of the Cdc14 homolog from &lt;i&gt;Botrytis cinerea&lt;/i&gt; are presented.&lt;/p&gt;
description: In SSP Biochemistry, high school participants conduct group research projects to characterize the Cdc14 phosphatase homolog from a phytopathogenic fungus and explore its potential as a novel antifungal target to protect crops from disease
DOI: 10.4231/3gen-d590
title: Summer Science Program in Biochemistry - Characterization of the Cdc14 phosphatase homolog from Aspergillus niger

description: &lt;p&gt;&lt;b&gt;The Research Project in SSP Biochemistry&lt;/b&gt;&lt;/p&gt;

&lt;p&gt;Cdc14 enzymes have been reported to be required for normal plant infection by several plant pathogen species. In the SSP Biochemistry program, research groups of 3 participants each purify and characterize the Cdc14 homolog encoded by a different plant fungal pathogen species. Each group is initially given the gene sequence for the putative Cdc14 homolog from a phytopathogenic fungus. Their overall goal is to determine if this protein would be a suitable target for development of a novel fungicide to protect crops from pathogens. They first use bioinformatic tools to generate a hypothesis about the function of the protein encoded by their gene sequence. Then, they use a recombinant plasmid to overexpress their protein in &lt;i&gt;E. coli&lt;/i&gt; and purify it using nickel affinity chromatography. They characterize steady-state kinetic properties and substrate specificity of their enzymes and compare the results to previously characterized Cdc14 from the model fungal species &lt;i&gt;Saccharomyces cerevisiae&lt;/i&gt; (ScCdc14), for which structural information is available. They then design an assay to test inhibition of their enzyme by a series of compounds originally identified as &lt;i&gt;in vitro&lt;/i&gt; inhibitors of ScCdc14. They choose the best one, perform computational docking to predict how it might bind to the homology-based structural model of their enzyme&rsquo;s active site that they previously generated, and finally hypothesize about ways to optimize their inhibitor structure to improve binding and specificity by taking advantage of known features of Cdc14 substrates. In the end they conclude whether or not the active site substrate specificity is conserved enough to justify using the ScCdc14 structure as a model for designing inhibitors to their enzyme. In this publication, the biochemical results and the homology based structural modeling of the Cdc14 homolog from &lt;em&gt;Aspergillus niger&lt;/em&gt; are presented.&lt;/p&gt;
description: In SSP Biochemistry, high school participants conduct group research projects to characterize the Cdc14 phosphatase homolog from a phytopathogenic fungus and explore its potential as a novel antifungal target to protect crops from disease
DOI: 10.4231/df06-7c69
title: Summer Science Program in Biochemistry - Characterization of the Cdc14 phosphatase homolog from Cercospora zeina

description: &lt;p&gt;&lt;b&gt;The Research Project in SSP Biochemistry&lt;/b&gt;&lt;/p&gt;

&lt;p&gt;Cdc14 enzymes have been reported to be required for normal plant infection by several plant pathogen species. In the SSP Biochemistry program, research groups of 3 participants each purify and characterize the Cdc14 homolog encoded by a different plant fungal pathogen species. Each group is initially given the gene sequence for the putative Cdc14 homolog from a phytopathogenic fungus. Their overall goal is to determine if this protein would be a suitable target for development of a novel fungicide to protect crops from pathogens. They first use bioinformatic tools to generate a hypothesis about the function of the protein encoded by their gene sequence. Then, they use a recombinant plasmid to overexpress their protein in &lt;i&gt;E. coli&lt;/i&gt; and purify it using nickel affinity chromatography. They characterize steady-state kinetic properties and substrate specificity of their enzymes and compare the results to previously characterized Cdc14 from the model fungal species &lt;i&gt;Saccharomyces cerevisiae&lt;/i&gt; (ScCdc14), for which structural information is available. They then design an assay to test inhibition of their enzyme by a series of compounds originally identified as &lt;i&gt;in vitro&lt;/i&gt; inhibitors of ScCdc14. They choose the best one, perform computational docking to predict how it might bind to the homology-based structural model of their enzyme&rsquo;s active site that they previously generated, and finally hypothesize about ways to optimize their inhibitor structure to improve binding and specificity by taking advantage of known features of Cdc14 substrates. In the end they conclude whether or not the active site substrate specificity is conserved enough to justify using the ScCdc14 structure as a model for designing inhibitors to their enzyme. In this publication, the biochemical results and the homology based structural modeling of the Cdc14 homolog from &lt;em&gt;Cercospora zeina&lt;/em&gt; are presented.&lt;/p&gt;
description: In SSP Biochemistry, high school participants conduct group research projects to characterize the Cdc14 phosphatase homolog from a phytopathogenic fungus and explore its potential as a novel antifungal target to protect crops from disease
DOI: 10.4231/8rg5-fn11
title: Summer Science Program in Biochemistry - Characterization of the Cdc14 phosphatase homolog from Claviceps purpurea

description: &lt;p&gt;&lt;b&gt;The Research Project in SSP Biochemistry&lt;/b&gt;&lt;/p&gt;

&lt;p&gt;Cdc14 enzymes have been reported to be required for normal plant infection by several plant pathogen species. In the SSP Biochemistry program, research groups of 3 participants each purify and characterize the Cdc14 homolog encoded by a different plant fungal pathogen species. Each group is initially given the gene sequence for the putative Cdc14 homolog from a phytopathogenic fungus. Their overall goal is to determine if this protein would be a suitable target for development of a novel fungicide to protect crops from pathogens. They first use bioinformatic tools to generate a hypothesis about the function of the protein encoded by their gene sequence. Then, they use a recombinant plasmid to overexpress their protein in &lt;i&gt;E. coli&lt;/i&gt; and purify it using nickel affinity chromatography. They characterize steady-state kinetic properties and substrate specificity of their enzymes and compare the results to previously characterized Cdc14 from the model fungal species &lt;i&gt;Saccharomyces cerevisiae&lt;/i&gt; (ScCdc14), for which structural information is available. They then design an assay to test inhibition of their enzyme by a series of compounds originally identified as &lt;i&gt;in vitro&lt;/i&gt; inhibitors of ScCdc14. They choose the best one, perform computational docking to predict how it might bind to the homology-based structural model of their enzyme&rsquo;s active site that they previously generated, and finally hypothesize about ways to optimize their inhibitor structure to improve binding and specificity by taking advantage of known features of Cdc14 substrates. In the end they conclude whether or not the active site substrate specificity is conserved enough to justify using the ScCdc14 structure as a model for designing inhibitors to their enzyme. In this publication, the biochemical results and the homology based structural modeling of the Cdc14 homolog from &lt;em&gt;Claviceps purpurea&lt;/em&gt; are presented.&lt;/p&gt;
description: In SSP Biochemistry, high school participants conduct group research projects to characterize the Cdc14 phosphatase homolog from a phytopathogenic fungus and explore its potential as a novel antifungal target to protect crops from disease
DOI: 10.4231/dfb0-f030
title: Nitrous oxide emissions and field-level nitrogen balance of maize and other field crops: Data for meta-analysis

description: &lt;p&gt;This is a compilation of field research data measuring nitrous oxide emissions from 55 different field crop experiments reported in 66 different publications. The data are mostly maize in the Corn Belt, but also include other crops and regions around the globe. All studies reported crop yield as well as N&lt;sub&gt;2&lt;/sub&gt;O losses. Experiment dates range from 1993 to 2017. Map illustrates observations for which multiple non-zero N rates were monitored -- this is the restricted dataset used to determine the generalized relationship between N&lt;sub&gt;2&lt;/sub&gt;O and N balance (where N balance is N inputs minus N removed). The dataset includes a total of 805 separate site-treatment-year observations, with up to 87 different variables for each observation.&lt;/p&gt;

&lt;p&gt;This dataset contains yearly management, production, and N&lt;sub&gt;2&lt;/sub&gt;O emission outcomes - along with other explanatory variables - drawn from temperate-region field crop experiments. Data subsets include: 1) maize in the North American Corn Belt on silt loam soils as published previously by McLellan et al. 2018, 2) additional observations for maize in the Corn Belt on silt loam soils, 3) maize in the Corn Belt grown on soils of other texture classes, 4) maize in the Corn Belt fertilized with livestock manure, and 5) other crops and regions. Yearly observations are averages of 3-4 replicates for each treatment-site, with measurement variability included where available. Most observations and explanatory variables originate from published data in peer-reviewed publications; some gaps were filled with data provided by field researchers, and weather and soil data gaps were filled using publicly available datasets.&lt;/p&gt;

&lt;p&gt;The data are used in the following publication:&lt;/p&gt;

&lt;p&gt;Eagle, A. J., McLellan, E. L., Brawner, E. M., Chantigny, M. H., Davidson, E. A., Dickey, J. B., et al. (2020). Quantifying on‐farm nitrous oxide emission reductions in food supply chains. &lt;em&gt;Earth&#39;s Future&lt;/em&gt;, 8, e2020EF001504. https://doi.org/10.1029/ 2020EF001504&lt;/p&gt;
description: Dataset for meta-analysis establishing generalized relationship between N2O emissions and field-crop partial N balance. Quantifying on-farm N2O emissions for food-supply chains.