cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.7017638.v1
title: spherical collision survey differentiated density

description: spherical collision survey differentiated density
DOI: 10.6084/m9.figshare.7017584
title: Digit ratio data US women college athletes and throwing - Lombardo et al.xlsx

description: Digit ratio and sports behavior data used in "College-aged women in the United States that play overhand throwing sports have masculine digit ratios."
DOI: 10.6084/m9.figshare.7017584.v1
title: Digit ratio data US women college athletes and throwing - Lombardo et al.xlsx

description: Digit ratio and sports behavior data used in "College-aged women in the United States that play overhand throwing sports have masculine digit ratios."
DOI: 10.25380/iastate.7017491
title: Productivity and diversity of annually harvested reconstructed prairie communities database

description: This data supports an accepted article that will be published in <i>Journal of Applied Ecology </i>in Jan 2019.Matt Liebman (mliebman@iastate.edu) is the corresponding author for the article. <br>Productivity and diversity of annually harvested reconstructed prairie communities database was compiled to test whether the long-term maintenance of biodiversity can be achieved alongside substantial productivity in fertilized mixed-species prairie. Using this database, we report how NPK fertilizer application, precipitation, and time affected the species composition and productivity of reconstructed prairie communities harvested annually as biofuel feedstocks over a nine-year period. Three main datasets were used for the analyses conducted, each encompassed a part of the full picture. First, we used prod_pre_div.csv to evaluate the relationship between productivity and precipitation. We also used this file to run the Analysis of Variance (ANOVA) on productivity, species richness, Simpson’s evenness and Simpson’s diversity. Results of this analysis are shown in Figure 1 and figure 2 of our article. Further, we used species _cover.csv for the ANOVA on the cover of individual plant species, cover of functional groups-i.e. C3 grasses, C4 grasses, the non-leguminous, the leguminous and cover of forbs partitioned by flowering time( see Table 2, Figure 3 and Figure 4). For creating a complementary picture from changes in species composition over time and treatment, we used species_proportional_cover.csv for multivariate analyses- i.e. non-metric multidimensional Scaling (NMDS), Multi Response-Permutation Procedure (MRPP), and the matching of ordination method (see Figure 5A and 5B). Usage of these datasets has no copyright or proprietary restrictions other than citation of the paper.
DOI: 10.25380/iastate.7017491.v2
title: Productivity and diversity of annually harvested reconstructed prairie communities database

description: This data supports an accepted article that will be published in <i>Journal of Applied Ecology </i>in Jan 2019.Matt Liebman (mliebman@iastate.edu) is the corresponding author for the article. <br>Productivity and diversity of annually harvested reconstructed prairie communities database was compiled to test whether the long-term maintenance of biodiversity can be achieved alongside substantial productivity in fertilized mixed-species prairie. Using this database, we report how NPK fertilizer application, precipitation, and time affected the species composition and productivity of reconstructed prairie communities harvested annually as biofuel feedstocks over a nine-year period. Three main datasets were used for the analyses conducted, each encompassed a part of the full picture. First, we used prod_pre_div.csv to evaluate the relationship between productivity and precipitation. We also used this file to run the Analysis of Variance (ANOVA) on productivity, species richness, Simpson’s evenness and Simpson’s diversity. Results of this analysis are shown in Figure 1 and figure 2 of our article. Further, we used species _cover.csv for the ANOVA on the cover of individual plant species, cover of functional groups-i.e. C3 grasses, C4 grasses, the non-leguminous, the leguminous and cover of forbs partitioned by flowering time( see Table 2, Figure 3 and Figure 4). For creating a complementary picture from changes in species composition over time and treatment, we used species_proportional_cover.csv for multivariate analyses- i.e. non-metric multidimensional Scaling (NMDS), Multi Response-Permutation Procedure (MRPP), and the matching of ordination method (see Figure 5A and 5B). Usage of these datasets has no copyright or proprietary restrictions other than citation of the paper.
DOI: 10.25380/iastate.7017491.v1
title: Productivity and diversity of annually harvested reconstructed prairie communities database

description: This data supports an accepted article that will be published in <i>Journal of Applied Ecology</i>.Matt Liebman (mliebman@iastate.edu) is the corresponding author for the article. <br>Productivity and diversity of annually harvested reconstructed prairie communities database” was compiled to test whether the long-term maintenance of biodiversity can be achieved alongside substantial productivity in fertilized mixed-species prairie. Using this database, we report how NPK fertilizer application, precipitation, and time affected the species composition and productivity of reconstructed prairie communities harvested annually as biofuel feedstocks over a nine-year period. Three main datasets were used for the analyses conducted, each encompassed a part of the full picture. First, we used prod_pre_div.csv to evaluate the relationship between productivity and precipitation. We also used this file to run the Analysis of Variance (ANOVA) on productivity, species richness, Simpson’s evenness and Simpson’s diversity. Results of this analysis are shown in Figure 1 and figure 2 of our article. Further, we used species _cover.csv for the ANOVA on the cover of individual plant species, cover of functional groups-i.e. C3 grasses, C4 grasses, the non-leguminous, the leguminous and cover of forbs partitioned by flowering time( see Table 2, Figure 3 and Figure 4). For creating a complementary picture from changes in species composition over time and treatment, we used species_proportional_cover.csv for multivariate analyses- i.e. non-metric multidimensional Scaling (NMDS), Multi Response-Permutation Procedure (MRPP), and the matching of ordination method (see Figure 5A and 5B). Usage of these datasets has no copyright or proprietary restrictions other than citation of the paper.
DOI: 10.6084/m9.figshare.7017392
title: 3D Point Cloud Data to Quantitatively Characterize Size and Shape of Shrub Crops

description: This repository contains necessary codes and raw data to extract size and shape traits of blueberry plants for a research study
DOI: 10.6084/m9.figshare.7017392.v1
title: 3D Point Cloud Data to Quantitatively Characterize Size and Shape of Shrub Crops

description: This repository contains necessary codes and raw data to extract size and shape traits of blueberry plants for a research study
DOI: 10.6084/m9.figshare.7017371
title: Elibariki Mwakapeje Figure6 Dataset Case Control study from Risk factors for human cutaneous anthrax outbreaks in the hotspot districts of Northern Tanzania: an unmatched case–control study

description: <i>Bacillus anthracis</i> is an aerobic, Gram-positive and spore-forming bacterium, which causes anthrax in herbivores. Humans get infected after coming into contact with infected animals' products. An unmatched case–control study was conducted to identify the importance of demographic, biological and/or behavioural factors associated with human cutaneous anthrax outbreaks in the hotspot areas of Northern Tanzania. A semi-structured questionnaire was administered to both cases and controls. The age range of participants was 1–80 years with a median age of 32 years. In the younger group (1–20 years), the odds of being infected were 25 times higher in the exposed group compared to the unexposed group (OR= 25, 95% CI = 1.5–410). By contrast, the odds of exposure in the old group (≥20 years) were three times lower in the exposed group compared to the unexposed group (OR = 3.2, 95% CI = 1.28–8.00). Demographic characteristics, sleeping on animal's skins, contacting with infected carcasses through skinning and butchering, and not having formal education were linked to exposure for anthrax infection. Hence, a One Health approach is inevitable for the prevention and control of anthrax outbreaks in the hotspot areas of Northern Tanzania.
DOI: 10.6084/m9.figshare.7017371.v1
title: Elibariki Mwakapeje Figure6 Dataset Case Control study from Risk factors for human cutaneous anthrax outbreaks in the hotspot districts of Northern Tanzania: an unmatched case–control study

description: <i>Bacillus anthracis</i> is an aerobic, Gram-positive and spore-forming bacterium, which causes anthrax in herbivores. Humans get infected after coming into contact with infected animals' products. An unmatched case–control study was conducted to identify the importance of demographic, biological and/or behavioural factors associated with human cutaneous anthrax outbreaks in the hotspot areas of Northern Tanzania. A semi-structured questionnaire was administered to both cases and controls. The age range of participants was 1–80 years with a median age of 32 years. In the younger group (1–20 years), the odds of being infected were 25 times higher in the exposed group compared to the unexposed group (OR= 25, 95% CI = 1.5–410). By contrast, the odds of exposure in the old group (≥20 years) were three times lower in the exposed group compared to the unexposed group (OR = 3.2, 95% CI = 1.28–8.00). Demographic characteristics, sleeping on animal's skins, contacting with infected carcasses through skinning and butchering, and not having formal education were linked to exposure for anthrax infection. Hence, a One Health approach is inevitable for the prevention and control of anthrax outbreaks in the hotspot areas of Northern Tanzania.
DOI: 10.6084/m9.figshare.7017365
title: Distribution of anthrax cases per village in the hotspot districts of northern Tanzania from Risk factors for human cutaneous anthrax outbreaks in the hotspot districts of Northern Tanzania: an unmatched case–control study

description: Distribution of susceptible anthrax cases in the most prone areas for anthrax is crucial for rapid disease transmission
DOI: 10.6084/m9.figshare.7017365.v1
title: Distribution of anthrax cases per village in the hotspot districts of northern Tanzania from Risk factors for human cutaneous anthrax outbreaks in the hotspot districts of Northern Tanzania: an unmatched case–control study

description: Distribution of susceptible anthrax cases in the most prone areas for anthrax is crucial for rapid disease transmission
DOI: 10.6084/m9.figshare.7017359
title: Coffee_Farm_Inventories

description: Database of shade tree inventories conducted in coffee farms in Pu'er and Xishuangbanna Prefecture, Yunnan Province
DOI: 10.6084/m9.figshare.7017359.v1
title: Coffee_Farm_Inventories

description: Database of shade tree inventories conducted in coffee farms in Pu'er and Xishuangbanna Prefecture, Yunnan Province
DOI: 10.6084/m9.figshare.7017356.v1
title: Clean raw data for: Developmental instability in a population of forest-dwelling olive baboons (Papio anubis)

description: Clean (outliers removed) raw data for: Developmental instability in a population of forest-dwelling olive baboons (Papio anubis)
DOI: 10.6084/m9.figshare.7017344
title: Fractal laser modes data and evaluation tools

description: Software for theoretically modelling fractal laser modes; raw data of experimentally measured intensity cross-sections in fractal laser modes, and tools for evaluating these
DOI: 10.6084/m9.figshare.7017344.v1
title: Fractal laser modes data and evaluation tools

description: Software for theoretically modelling fractal laser modes; raw data of experimentally measured intensity cross-sections in fractal laser modes, and tools for evaluating these
DOI: 10.6084/m9.figshare.7017356.v2
title: Developmental instability in a population of forest-dwelling olive baboons (Papio anubis) [raw data and supporting figures]

description: The Excel spreadsheet contains the raw data (females-raw, males-raw) used for visual and statistical inspection and the clean data (females-clean, males-clean) following visual and statistical inspected. <br>The PDFs include scatterplots (for visual inspection) and report on statistical inspection of suspicious data points that resulted in the clean data.
DOI: 10.6084/m9.figshare.7017356.v3
title: Developmental instability in a population of forest-dwelling olive baboons (Papio anubis) [raw data and supporting figures]

description: The Excel spreadsheet contains the raw data (females-raw, males-raw) used for visual and statistical inspection and the clean data (females-clean, males-clean) following visual and statistical inspected. <br>The PDFs include scatterplots (for visual inspection) and report on statistical inspection of suspicious data points that resulted in the clean data.
DOI: 10.6084/m9.figshare.7017326
title: Flow diagram functions STB SDP160

description: Flow diagram to understand the new functionalities added to STB.
DOI: 10.6084/m9.figshare.7017326.v2
title: Flow diagram functions STB SDP160

description: Flow diagram to understand the new functionalities added to STB.
DOI: 10.6084/m9.figshare.7017356.v4
title: Developmental instability in a population of forest-dwelling olive baboons (Papio anubis) [raw data and supporting figures]

description: The Excel spreadsheet contains the raw data (females-raw, males-raw) used for visual and statistical inspection and the clean data (females-clean, males-clean) following visual and statistical inspected. <br>The PDFs include scatterplots (for visual inspection) and report on statistical inspection of suspicious data points that resulted in the clean data.
DOI: 10.6084/m9.figshare.7017326.v1
title: Flow diagram functions STB SDP160

description: Flow diagram to understand the new functionalities added to STB.
DOI: 10.6084/m9.figshare.7017356.v5
title: Data: Baboon Fluctuating Asymmetry

description: The Excel spreadsheet contains the raw data (females-raw, males-raw) used for visual and statistical inspection and the clean data (females-clean, males-clean) following visual and statistical inspected. <br>The PDFs include scatterplots (for visual inspection) and report on statistical inspection of suspicious data points that resulted in the clean data.
DOI: 10.6084/m9.figshare.7017254
title: Machine Learning Materials Datasets

description: Three datasets are intended to be used for exploring machine learning applications in materials science. They are formatted in simple form and in particular for easy input into the MAterials Simulation Toolkit - Machine Learning (MAST-ML) package (see https://github.com/uw-cmg/MAST-ML).<br><br>Each dataset is a materials property of interest and associated descriptors. For detailed information, please see the attached REAME text file.<br><br>The first dataset for dilute solute diffusion can be used to predict an effective diffusion barrier for a solute element moving through another host element. The dataset has been calculated with DFT methods.<br>The second dataset for perovskite stability gives energies of compostions of potential perovskite materials relative to the convex hull calculated with DFT. The perovskite dataset also includes columns with information about the A site, B site, and X site in the perovskite structure in order to perform more advanced grouping of the data.<br>The third dataset is a metallic glasses dataset which has values of reduced glass transition temperature (Trg) for a variety of metallic alloys. An additional column is included for majority element for each alloy, which can be an interesting property to group on during tests.
DOI: 10.6084/m9.figshare.7017167
title: Nothobranchius furzeri sites

description: List of known N. furze sites studied during 2008-2016 by Reichard lab team.
DOI: 10.6084/m9.figshare.7017254.v2
title: Machine Learning Materials Datasets

description: Three datasets are intended to be used for exploring machine learning applications in materials science. They are formatted in simple form and in particular for easy input into the MAterials Simulation Toolkit - Machine Learning (MAST-ML) package (see https://github.com/uw-cmg/MAST-ML).TEST<br><br>Each dataset is a materials property of interest and associated descriptors.<br><br>The first dataset for dilute solute diffusion can be used to predict an effective diffusion barrier for a solute element moving through another host element. The dataset has been calculated through DFT methods.<br>The second dataset for perovskite stability gives energies of compostions of potential perovskite materials relative to the convex hull, again as calculated through DFT. The perovskite dataset also includes columns with information about the A site, B site, and X site in the perovskite structure in order to perform more advanced grouping of the data.<br>The last dataset is a metallic glasses dataset which has values of reduced glass transition temperature (Trg) for a variety of metallic alloys. An additional column is included for majority element for each alloy, which can be an interesting property to group on during tests.
DOI: 10.6084/m9.figshare.7017254.v3
title: Machine Learning Materials Datasets

description: Three datasets are intended to be used for exploring machine learning applications in materials science. They are formatted in simple form and in particular for easy input into the MAterials Simulation Toolkit - Machine Learning (MAST-ML) package (see https://github.com/uw-cmg/MAST-ML).<br><br>Each dataset is a materials property of interest and associated descriptors. For detailed information, please see the attached REAME text file.<br><br>The first dataset for dilute solute diffusion can be used to predict an effective diffusion barrier for a solute element moving through another host element. The dataset has been calculated with DFT methods.<br>The second dataset for perovskite stability gives energies of compostions of potential perovskite materials relative to the convex hull calculated with DFT. The perovskite dataset also includes columns with information about the A site, B site, and X site in the perovskite structure in order to perform more advanced grouping of the data.<br>The third dataset is a metallic glasses dataset which has values of reduced glass transition temperature (Trg) for a variety of metallic alloys. An additional column is included for majority element for each alloy, which can be an interesting property to group on during tests.
DOI: 10.6084/m9.figshare.7017137
title: Numerical simulations of a fluid sphere undergoing precession

description: We provide a dataset of numerical simulation of fluid flow in precessing spheres.Some include magnetic field to asses whether the flows are dynamos or not.The dataset includes the simulations from papers linked in refereces below. Please also cite them if you use this dataset.<br>We cover a wide range of the parameter space, pushing towards planetary values to the limits of current super-computer capabilities.<br>We include a python notebook (jupyter) to work with the dataset.<br><b>WARNING: </b>the first<b> </b>version of this database had some errors and inconsistencies. Please use the more recent revision.<br><b></b><br>
DOI: 10.6084/m9.figshare.7017254.v4
title: Machine Learning Materials Datasets

description: Three datasets are intended to be used for exploring machine learning applications in materials science. They are formatted in simple form and in particular for easy input into the MAterials Simulation Toolkit - Machine Learning (MAST-ML) package (see https://github.com/uw-cmg/MAST-ML).<br><br>Each dataset is a materials property of interest and associated descriptors. For detailed information, please see the attached REAME text file.<br><br>The first dataset for dilute solute diffusion can be used to predict an effective diffusion barrier for a solute element moving through another host element. The dataset has been calculated with DFT methods.<br>The second dataset for perovskite stability gives energies of compostions of potential perovskite materials relative to the convex hull calculated with DFT. The perovskite dataset also includes columns with information about the A site, B site, and X site in the perovskite structure in order to perform more advanced grouping of the data.<br>The third dataset is a metallic glasses dataset which has values of reduced glass transition temperature (Trg) for a variety of metallic alloys. An additional column is included for majority element for each alloy, which can be an interesting property to group on during tests.
DOI: 10.6084/m9.figshare.7017137.v1
title: Numerical simulations of a fluid sphere undergoing precession

description: We provide a dataset of numerical simulation of fluid flow in precessing spheres.Some include magnetic field to asses whether the flows are dynamos or not.The dataset includes the simulations from papers linked in refereces below. Please also cite them if you use this dataset.<br>We cover a wide range of the parameter space, pushing towards planetary values to the limits of current super-computer capabilities.<br>We include a python notebook (jupyter) to work with the dataset.<br>
DOI: 10.17633/rd.brunel.7016849
title: Performance and Radiation-Tolerance of Honeywell LOHET-II Hall-Effect Sensors

description: MICE, the international Muon Ionization Cooling Experiment, is a project to design, construct, operate and test a cell of a muon ionisation cooling channel that may be used for a future Muon Collider or Neutrino Factory.<br>The object of the MICE experiment is to take a beam of muons created from protons from the ISIS accelerator hitting a titanium target and to show that it is possible to create a narrow intense beam, using detector techniques from particle physics.The MICE Muon Beamline[1] can be set to deliver beams of either positive or negative muons. This is achieved by physically swapping over the current leads for each of the conventional magnet power supplies. Ensuring the actual operating polarity of the beamline is correctly recorded as a manual step was at risk of error or omission.We have deployed a simple system ("POMPOMs", [2]) for monitoring the operating polarity of the two bending magnets by placing in each dipole bore a Honeywell LOHET-II Hall-effect sensor (SS94A1E) that operates past saturation at nominal field strengths, and thus returns one of two well-defined voltages corresponding to the two possible polarities of the magnet.The environment in the experimental hall is monitored by an AKCP securityProbe 5E system integrated into our EPICS-based controls and monitoring system. We read out the beamline polarity sensors using a voltmeter module, and translate the output voltage into a polarity (or alarm) state within EPICS whence it can be accessed by the operators and stored in the output datastream.This spreadsheet contains the data from the LOHET-II sensor initial characterisation, radiation-tolerance testing, and in-situ performance monitoring[3] programmes.<br>1. "The MICE Muon Beam on ISIS and the beam-line instrumentation of the Muon Ionization Cooling Experiment" Journal of Instrumentation (2012). doi:10.1088/1748-0221/7/05/P050092. J.J. Nebrensky and P.M. Hanlet: "POMPOMs: Cost-Efficient Polarity Sensors for the MICE Muon Beamline" TUPD90 at DIPAC'11 - 10th European Workshop on Beam Diagnostics and Instrumentation for Particle Accelerators pp. 518-520 (2011)3. H. Nebrensky: "Routine POMPOM sensor test procedure" (2013)<br>This material forms part of the MICE Miscellaneous data, DOI: 10.17633/rd.brunel.5024885 ( <em>Construction/Beamline/Other/PerformanceAndRadiationToleranceOfHoneywell_LOHET-II_HallEffectSensors.zip</em> ).