cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.4231/v168-xw88
title: Aerial imagery of the Purdue Agronomy Center for Research and Education (ACRE) - 1976

description: &lt;p&gt;Aerial imagery from 1976 covering the Purdue Agronomy Center for Research and Education (ACRE) (4530 US-52, West Lafayette, IN 47906; latitude / longitude in decimal degrees: 40.4698, -86.9927) and surrounding areas. The data were obtained from the USDA Natural Resources Conservation Service, Lafayette Service Center, 1812 Troxel Dr., Suite C3, Lafayette, IN 47909 in June 2017 and consisted of three individual images that were scanned at 400 dpi (dots per inch) and saved in TIFF format. These original images are provided in the folder labeled &ldquo;Original_Scans.&rdquo; The images were georeferenced and projected using the Georeferencing tool in ArcGIS 10.6 and using as the standard base map the 2013 IndianaMap Data imagery from the same area that had previously been reprojected into the Indiana Geospatial Coordinate System NAD_1983_2011_InGCS_Tippecanoe-White_(m). For accurate georeferencing, stable and visible benchmarks such as roads, intersections, driveways, railroad tracks, culverts, etc. were used as control points. Sufficient control points (usually about 15) were added so that the spline transformation could be used for each image. The three individual images were then mosaicked into one georeferenced image using the Mosaic tool in ArcGIS 10.6. This mosaicked image, in the Indiana Geospatial Coordinate System NAD_1983_2011_InGCS_Tippecanoe-White_(m), is in the folder named &ldquo;Georeferenced.&rdquo;&lt;/p&gt;

&lt;p&gt;This data set was produced as part of a project funded by the Office of Agricultural Research and Graduate Education at Purdue University.&lt;/p&gt;
description: Aerial imagery from 1976 of the Purdue Agronomy Center for Research and Education (ACRE), West Lafayette, IN.
DOI: 10.4231/74kh-8x07
title: Aerial imagery of the Purdue Agronomy Center for Research and Education (ACRE) – 2013

description: &lt;p&gt;Aerial imagery from 2013 covering the Purdue Agronomy Center for Research and Education (ACRE) (4530 US-52, West Lafayette, IN 47906; latitude / longitude in decimal degrees: 40.4698, -86.9927) and surrounding areas. The data were downloaded from the Indiana Spatial Data Portal (ISDP) (https://gis.iu.edu) and consisted of 20 individual images available in TIFF format that were already georeferenced in State Plane coordinates. The 20 individual images were then mosaicked into one image using the Mosaic tool in ArcGIS 10.6. The mosaicked image was then reprojected into the Indiana Geospatial Coordinate System NAD_1983_2011_InGCS_Tippecanoe-White_(m). This reprojected image was then used as the standard base map for georeferencing other aerial images of ACRE.&lt;/p&gt;

&lt;p&gt;This data set was produced as part of a project funded by the Office of Agricultural Research and Graduate Education at Purdue University.&lt;/p&gt;
description: Aerial imagery from 2013 of the Purdue Agronomy Center for Research and Education (ACRE), West Lafayette, IN.
DOI: 10.15468/dl.qpj9te
title: Occurrence Download

description: A dataset containing 47 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 Botrychium multifidum",
 "Year 2000-2024"
 ]
}

 The dataset includes 47 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0059541-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.4231/gkyx-g476
title: Chronic Exposure to a PFAS Mixture Resembling AFFF Causes Decreased Body Size in Northern Leopard Frogs

description: &lt;p&gt;Per- and polyfluoroalkyl substances (PFAS) occur in the environment as mixtures, yet mixture toxicity remains poorly understood. Aqueous film-forming foams (AFFF) are a common source of PFAS. Our objective was to examine chronic effects of a complex PFAS mixture on amphibian growth and development. We tested toxicity of a five-chemical PFAS mixture summing to 10 mg/L and that accounts for &gt;90% of the PFAS in AFFF-affected surface waters: perfluorooctane sulfonate (PFOS, 40%), perfluorohexane sulfonic acid (PFHxS, 30%), perflurooctanoic acid (PFOA, 12.5%), perfluorohexanoic acid (PFHxA, 12.5%), and perfluoropentanoic acid (PFPeA, 5%). We also included treatments to determine whether PFOS drove mixture toxicity and whether PFOS and mixture components act additively. We exposed Northern leopard frog (&lt;em&gt;Rana&lt;/em&gt; &lt;em&gt;pipiens&lt;/em&gt;) larvae through metamorphosis (~120 d) in outdoor mesocosms. After 21 days of exposure, larval body condition fell ~5% relative to controls in the 4 mg/L PFOS treatment and mixtures lacking PFOS. At metamorphosis, the full 5-component 10 mg/L PFAS mixture reduced mass by 16% relative to controls. We did not observe effects on development. Our results indicate that toxicity of PFOS and other PFAS mixtures typical of AFF sites act additively and that PFOS is not more inherently more toxic than other mixture components. The data structure is described in detail in the data dictionary, above.&lt;/p&gt;
description: We exposed Northern leopard frogs to mixtures of PFAS reflective of AFFF sites and found stage specific effects, including reduced body condition at day 21 and decreased mass relative to the control.
DOI: 10.4231/t1kn-3t16
title: A Critical Review of the Purdue Amphibian PFAS Ecotoxicity Research Studies (2017-2022): Identification of Screening Levels in Water and Other Useful Resources for Site-specific Ecological Risk Assessments

description: &lt;p&gt;With the goal of aiding risk assessors conducting site-specific ecological risk assessments at PFAS-contaminated sites, this dataset synthesizes information on the ecotoxicity of PFAS to amphibians produced by the Purdue University ecotoxicology research group over 6 years, in 9 amphibian species, and across 14 peer-reviewed publications. These studies consisted of spiked-PFAS chronic toxicity experiments with PFOS, PFOA, PFHxS, and 6:2 FTS that evaluated apical endpoints typical of ecological risk-based decision making (survival, growth, and development).&lt;/p&gt;
description: This dataset includes data from several studies used to develop PFAS toxicity reference values for amphibians.
DOI: 10.4231/f75x-1n34
title: Automatic 4D flow MRI Segmentation Using the Standardized Difference of Means Velocity

description: &lt;p&gt;We present a method to automatically segment 4D flow magnetic resonance imaging (MRI) by identifying net flow effects using the standardized difference of means (SDM) velocity. The SDM segmentation method was validated in 4D flow MRI measurements of &lt;em&gt;in vitro&lt;/em&gt; flow phantoms, &lt;em&gt;in &lt;/em&gt;&lt;em&gt;vivo&lt;/em&gt; Circle of Willis datasets, and &lt;em&gt;in vivo&lt;/em&gt; aortas.&lt;/p&gt;

&lt;p&gt;Here, we provide the velocity fields obtained using 4D flow MRI in the scaled &lt;em&gt;in vitro&lt;/em&gt; flow phantoms.&lt;/p&gt;
description: We provide 4D flow MRI velocity measurements in two in vitro flow phantoms of a cerebral aneurysm. One phantom is unscaled (1-to-1), and the other is scaled by a factor of two in all dimensions (2-to-1).
DOI: 10.4231/80rv-x686
title: Methane emissions from land and aquatic ecosystems in Western Siberia: An analysis with methane biogeochemistry models

description: &lt;p&gt;Western Siberia contains extensive wetlands and aquatic ecosystems, contributing a significant amount of methane (CH4) emissions to the atmosphere. However, estimates of CH4 fluxes over the region are poorly constrained partly due to the uncertainties from the inundated area data. This study applied two process-based biogeochemistry models (Terrestrial Ecosystem Model, TEM; and Arctic Lake Biogeochemistry Model, ALBM) to quantify the emissions from land and aquatic ecosystems separately over the region within the period 2000-2021 using different inundation datasets. We use two wetland data to drive land methane modeling and three inundation data to drive lake methane modeling. We conduct different simulations to compare emissions over the region using these datasets. This study is among the first to investigate methane emissions from the whole landscape and make the quantification from land and aquatic part separately in the region. This study highlights the importance of dynamic wetland and aquatic area data in quantifying regional and global methane emissions.&lt;/p&gt;
description: This dataset contains the main codes and data for the methane emissions quantification from land and aquatic ecosystems in Western Siberia based on biogeochemical methane models.
DOI: 10.4231/bb7m-hn65
title: Weakening cooling effect of northern peatlands on the global climate system during the 21st century

description: &lt;p&gt;Northern peatlands store large amounts of C. Model projected fate of the C stock has significant uncertainties due to the insufficient processes of N cycle in current peatland biogeochemistry models. In this study, we incorporate adequate N cycling processes to a Peatland Terrestrial Ecosystem Model (PTEM) to simulate C and N dynamics of northern peatlands during 15ka BP-2100. We estimate that by 1990, northern peatlands accumulate 408 Pg C and 7.8 Pg N since their initiation and their greenhouse gas emissions of CO2, CH4 and N2O have a radiative forcing (RF) of -0.57 W∙m&lt;sup&gt;-2&lt;/sup&gt;. During the 21&lt;sup&gt;st&lt;/sup&gt; century, mineral N content in northern peatlands will increase, resulting in more net primary productivity. With increasing greenhouse gas emissions, the cooling effect of northern peatlands is weakening under warming conditions, primarily due to increasing CH&lt;sub&gt;4&lt;/sub&gt; emissions.&lt;/p&gt;
description: This dataset contains the code, run directory and outputs for Peatland Terrestrial Ecosystem Model v 2.3.
DOI: 10.4231/vte5-gn79
title: Acoustic properties of non-native clear speech: Korean speakers of English

description: &lt;p&gt;The dataset was collected to examine acoustic correlates of non-native English clear speech produced by native Korean speakers. In other words, we aimed to explore how native Korean speakers would produce English clear speech in comparison with native English speakers. All speech samples were obtained by having participants read an English word-list with three repetitions within each speaking style. &lt;/p&gt;
description: Each .csv file provides information about Speaker Group, Speaking Style, and Voicing (for some models) that are used as fixed effects, along with dependent variables (i.e. each acoustic parameter).
DOI: 10.15468/dl.h9j688
title: Occurrence Download

description: A dataset containing 2670 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Scarus dimidiatus"
 ]
}

 The dataset includes 2670 records from 81 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0059539-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.4231/vafp-dw68
title: mHealth hyperspectral learning for hemodynamics

description: &lt;p&gt;To demonstrate its versatility, an experimental model of vascular development is used to extract hemodynamic parameters via statistical and deep-learning approaches. Subsequently, the hemodynamics of peripheral microcirculation is assessed at an ultrafast temporal resolution up to a millisecond, using a conventional smartphone camera. This spectrally informed learning method is analogous to compressed sensing; however, it further allows for reliable hypercube recovery and key feature extractions with a transparent learning algorithm. This learning-powered snapshot hyperspectral imaging method yields high spectral and temporal resolutions and eliminates the spatiospectral tradeoff, offering simple hardware requirements and potential applications of various machine-learning techniques.&lt;/p&gt;
description: A small sampling of hyperspectral data enables spectrally informed learning to recover a hypercube from a red-green-blue (RGB) image without complete hyperspectral measurements. Hyperspectral learning is capable of recovering full spectroscopic resolution
DOI: 10.4231/k3d7-2698
title: Source Data for Organic Optoelectronic Synapse

description: &lt;p&gt;Optoelectronic devices can detect and store visual information, making them attractive for future bionic eyes or automated vision systems. Here, we present a photonic organic synapse based on photon-modulated electrochemical doping. We measured the photonic characteristics and synaptic-like functions of our devices to demonstrate how they work. We also used experiment to support the mechanism of the synaptic behaviors of our devices. These experimental results are included in this dataset, which is used to support the manuscript &#39;Organic Optoelectronic Synapse Based on Photon-Modulated Electrochemical Doping.&#39;&lt;/p&gt;
description: Source data for manuscript 'Organic Optoelectronic Synapse Based on Photon-Modulated Electrochemical Doping ' ( 10.1038/s41566-023-01232-x)
DOI: 10.4231/b5tq-5z89
title: COVID impacts on human-animal relationship and mental health

description: &lt;p&gt;Data (without imputation) used in the analysis for the paper, titled: Temporal patterns of owner-pet relationship, stress, and loneliness during the COVID-19 pandemic, and the effect of pet ownership on mental health: A longitudinal survey, published in the PLOS ONE. &lt;/p&gt;

&lt;p&gt;We conducted a longitudinal survey to examine the temporal patterns of owner-pet relationship, stress, and loneliness during four phases of the pandemic: 1) pre-pandemic (February 2020), 2) lockdown (April to June 2020), 3) reopening (September to December 2020), and 4) recovery (January 2021 to December 2021). We also investigated the effect of pet ownership on stress and loneliness, by considering a set of a priori causal assumptions. In addition, we hypothesized that the differences in the levels of stress and loneliness between dog and cat ownerships were mediated by the owner-pet relationship. A total of 4,237 participants (657 non-pet owners, 1,761 dog owners, and 1,819 cat owners) completed between one and six surveys. &lt;/p&gt;
description: Trend in human-animal relationship, stress and loneliness during COVID pandemic
DOI: 10.4231/pf9s-4g38
title: Row Selection in Remote Sensing for Maize and Sorghum

description: &lt;p&gt;This repository is to provide data and R scripts using in the processing of doi: 10.3389/fpls.2023.1202536.&lt;/p&gt;

&lt;p&gt;Abstract: Remote sensing enables the rapid assessment of many traits that provide valuable information to plant breeders throughout the growing season to improve genetic gain. These traits are often extracted from remote sensing data on a row segment (rows within a plot) basis enabling the quantitative assessment of any row-wise subset of plants in a plot, rather than a few individual representative plants, as is commonly done in field-based phenotyping. Nevertheless, which rows to include in analysis is still a matter of debate. The objective of this experiment was to evaluate row selection and plot trimming in field trials conducted using four-row plots with remote sensing traits extracted from RGB (red-green-blue), LiDAR (light detection and ranging), and VNIR (visible near infrared) hyperspectral data. Uncrewed aerial vehicle flights were conducted throughout the growing seasons of 2018 to 2021 with data collected on three years of a sorghum experiment and two years of a maize experiment. Traits were extracted from each plot based on all four row segments (RS) (RS1234), inner rows (RS23), outer rows (RS14), and individual rows (RS1, RS2, RS3, and RS4). Plot end trimming of 40 cm was an additional factor tested. Repeatability and predictive modelling of end-season yield were used to evaluate performance of these methodologies. Plot trimming was never shown to result in significantly different outcomes from non-trimmed plots. Significant differences were often observed based on differences in row selection. Plots with more row segments were often favorable for increasing repeatability, and excluding outer rows improved predictive modeling. These results support long-standing principles of experimental design in agronomy and should be considered in breeding programs that incorporate remote sensing. &lt;/p&gt;
description: Remote sensing data evaluates all row segments of a plot, but the repeatability of traits from different row segments has not been evaluated. We evaluated which row segments provide the best repeatability and yield prediction of remote sensing traits.
DOI: 10.4231/8k7w-nf84
title: Code and Model results for Soil organic carbon is a key determinant of CH4 sink in global forest soils

description: &lt;p&gt;This publication contains code and data of a biogeochemistry model, TEM-SOC, that includes a function related to soil organic carbon (SOC) for the estimation of global forest methane soil sinks. You will find four files when downloading the bundle: (1) One file (TEM_for_tutorial.zip) contains C++ codes and a compiler for default TEM model, (2) one file (TEM-SOC_code.zip) contains C++ codes and a compiler for the new model, TEM-SOC, (3) one file (TEM_compileandrun_guide_manual_Liu_Oh.pdf) is a guideline for the model, and (4) another file (TEMDEF_TEMSOC_output.nc) is model outputs of global forest methane oxidation from 2000 to 2016 from the default (TEM-DEF) and new (TEM-SOC) model.&lt;/p&gt;

&lt;p&gt;Soil organic carbon (SOC) is a primary regulator of the forest&ndash;climate feedback. However, its indicative capability for the soil CH4 sink is poorly understood due to the incomplete knowledge of the underlying mechanisms. Therefore, SOC is not explicitly included in the current model estimation of the global forest CH4 sink. Here, utilizing in-situ observations, global metadata analysis, and process-based modeling, we provide evidence to support the notion that SOC constitutes an important variable that governs the forest CH4 sink. A larger CH4 sink was observed with increasing SOC content on regional and global scales. The revised model with SOC function better represents the field observation data and estimates a 39% larger global forest CH4 sink than the model without SOC function (24.27 versus 17.46 Tg CH4 yr&minus;1), further narrowing the gap between bottom-up and top-down global soil sink estimations. Our results highlight the indicative capability of SOC for the forest CH4 sink, suggesting that the effect of SOC needs to be incorporated into the estimation model to better understand the future CH4 dynamics and to constrain the global CH4 budget.&lt;/p&gt;
description: This dataset contains code and model results for the paper 'Soil organic carbon is a key determinant of CH4 sink in global forest soils' by Lee et al. (2023).
DOI: 10.4231/qs1j-6j77
title: Genetic and environmental variation in alfalfa forage yield from variety testing experiments conducted in North America between 1986 to 1999

description: &lt;p&gt;The yield dataset contains forage yield data from over 700 alfalfa variety tests conducted by researchers in the US and Canada from 1986 through 1999. Some trials also measured forage quality and stand; these data are also available in PURR. The data were aggregated from the Alfalfa Variety Performance Database originally compiled in 2000 by Daniel W. Wiersma and Wayne G. Hartman (doi: &lt;a href="https://doi.org/10.4231/PHKH-4334" target="_blank"&gt;10.4231/PHKH-4334)&lt;/a&gt;. The database was used to analyze long-term trends in genetic improvement of alfalfa yield and agronomic performance across a broad range of environments.&lt;/p&gt;

&lt;p&gt;The yield file contains cultivar-specific yield data for each harvest within a year. It is organized by Trial, and includes trial-specific spatial (state, latitude, longitude, elevation), and temporal (year of trial, harvest number, harvest date, planting date) details. Finally, when available soil type and statistics are also provided. A companion dataset in PURR contains the characteristics of these alfalfa varieties (doi: &lt;a href="https://doi.org/10.4231/FMY9-6966" target="_blank"&gt;10.4231/FMY9-6966)&lt;/a&gt;. &lt;/p&gt;
description: The dataset contains data used to analyze genetic and environmental effects on alfalfa yield and agronomic performance. Data were compiled from alfalfa variety tests conducted by University researchers in the US and Canada from 1986 through 1999.
DOI: 10.4231/966q-6f95
title: Clustering in Machine Learning Pattern Formation of VO2

description: &lt;p&gt;We have trained a convolutional neural network (CNN) machine learning (ML) model to recognize images from seven different candidate Hamiltonians that could be controlling pattern formation of metal-insulator domains in Vanadium Dioxide (VO&lt;sub&gt;2&lt;/sub&gt;).  This trained CNN was then applied to experimental data on VO&lt;sub&gt;2&lt;/sub&gt; taken via scanning near-field infrared microscopy and via optical microscopy.  &lt;/p&gt;

&lt;p&gt;The html files are interactive 3-dimensional plots of the full 7-dimensional that visualize the output of the last fully connected layer of the CNN from the training sets.  The plots also contain the high and low confidence predictions from experimental data. &lt;/p&gt;

&lt;p&gt;The included codes contain the architecture of the ML model, the symmetry reduction operations applied to binary images, and the criterion for assigning high or low confidence to the ML classifier predictions.  &lt;br /&gt;
 &lt;/p&gt;

&lt;p&gt; &lt;/p&gt;
description: Codes used in "Deep Learning Hamiltonians form Disordered Image Data in Quantum Materials" https://arxiv.org/abs/2211.01490 and the resulting visualizations.
DOI: 10.4231/pqft-7g59
title: Genetic Parameters and Multi-trait Genomic Prediction of Grain Yield on a Plot and Ear Basis in Temperate and Tropical Maize

description: &lt;p&gt;Yield gain has been a primary objective of maize breeding programs for the last century. Advancement in phenotyping tools, genomic methodologies, and data analytics strategies provide plant breeders with new tools to assess germplasm merit of experimental testcross hybrids, but more work is needed to integrate these systems into modern plant breeding schemes. The objective of this study was to assess genetic parameters and perform single- and multi-trait genomic prediction of grain yield and yield components in three testcross populations of either temperate or tropical descent. Two cross validation scenarios were implemented. In the first approach, five-fold cross validation was used with equal representation of each heterotic group across the five folds. In another scenario, training and testing sets originated from separate heterotic groups to evaluate prediction accuracy across heterotic groups. Where models were trained and tested on different heterotic groups, prediction accuracy was best when Iodent inbred lines predicted Non-Stiff Stalk inbred line performance due to the genetic similarity between these heterotic groups. Many yield components including ear area, ear length, and kernels per ear were more heritable and more accurately predicted based on single-trait genomic prediction than grain yield per plot or ear in the temperate and tropical populations. Multi-trait genomic prediction of grain yield per ear and grain yield per plot resulted in improved prediction accuracy in comparison to single-trait genomic prediction where secondary traits were known in the testing set. The integration of high-throughput yield component assessment with genomics could improve yield prediction in breeding programs. &lt;/p&gt;
description: The objective of this study was to assess genetic parameters and perform single- and multi-trait genomic prediction of grain yield and yield components assessed through ear photometry in three testcross populations of either temperate or tropical descent.