cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.25919/tv9h-jv56
title: Parkes observations for project P595 semester 2023APRS_02

description: We propose to continue the PULSE@Parkes project in which high school students from Australia and around the World use the Parkes radio telescope in a remote observing model to observe and analyse pulsar data. The data from some PULSE@Parkes observations are used to support the space missions, other observations supplement the P456 Pulsar Timing Array project and the remainder were chosen in order to make a detailed analysis of pulsar timing irregularities and intermittency.
DOI: 10.5281/zenodo.7927195
title: THE GROWTH IMPACT ON COMPANY VALUE: EVIDENCE FROM THE E-COMMERCE SECTOR

description: The data contains financial information on the companies from the e-commerce industry worldwide over the period from 2017 to 2021 (panel data for 173 companies).<br> The list of variables:<br> 1. Current trading multiples (EV/GMV, EV/Revenue, EV/Gross Profit, EV/EBITDA, EV/EBIT)<br> 2. Control variables: Dummy_Dev (1 - developed country, 0 - developing country), Dummy_Ind (1 - primarily marketplace, 0 - primarily retail)<br> 3. Breakeven point (Dummy_GP, Dummy_EBITDA)<br> 4. Growth of financial indicators (GMV, Revenue, Gross Profit, EBITDA, EBIT)<br> 5. Gross Profit margin, EBITDA margin, EBIT margin<br> 6. Standard deviation of forecasted revenues (G_stdev)
DOI: 10.5281/zenodo.7927194
title: THE GROWTH IMPACT ON COMPANY VALUE: EVIDENCE FROM THE E-COMMERCE SECTOR

description: The data contains financial information on the companies from the e-commerce industry worldwide over the period from 2017 to 2021 (panel data for 173 companies).<br> The list of variables:<br> 1. Current trading multiples (EV/GMV, EV/Revenue, EV/Gross Profit, EV/EBITDA, EV/EBIT)<br> 2. Control variables: Dummy_Dev (1 - developed country, 0 - developing country), Dummy_Ind (1 - primarily marketplace, 0 - primarily retail)<br> 3. Breakeven point (Dummy_GP, Dummy_EBITDA)<br> 4. Growth of financial indicators (GMV, Revenue, Gross Profit, EBITDA, EBIT)<br> 5. Gross Profit margin, EBITDA margin, EBIT margin<br> 6. Standard deviation of forecasted revenues (G_stdev)
DOI: 10.5281/zenodo.7927187
title: IHME Raw Life Brazil's Life Tables Datasets

description: Raw data sets for life tables in Brazil between 1950-2020, originally from the GHDx website.
DOI: 10.5281/zenodo.7927186
title: IHME Raw Life Brazil's Life Tables Datasets

description: Raw data sets for life tables in Brazil between 1950-2020, originally from the GHDx website.
DOI: 10.15482/usda.adc/1528995
title: Data from: Demographic parameters shift over time among artificially selected Drosophila melanogaster: a case for or against lifetime reproductive measurements

description: Drosophila melanogaster is a fruit fly pest found around the world. This insect responds plastically to variation in temperature and has been known to be locally adapted to different locations across the globe, with varying maximum and minimum thermal limits. Artificial selection can be used to create adaptive responses in a laboratory setting, which can be used to mimic a range of thermal responses. Previous research has shown that within 30 generations of selection, naturally caught D. melanogaster from North Carolina, USA, can produce populations with both increased and decreased responses to cold stress as demonstrated by the chill-coma recovery trait (Gerken et al. 2016). This dataset expands on cross-tolerances to reproductive capacity and includes data from the four artificially selected D. melanogaster populations and two control populations. Egg production and total lifespan were measured in a laboratory setting at five different temperatures. Two data resources are included: full egg production and longevity for each fly assayed. This study was used to establish how selection for cold tolerance can affect reproductive capacity and longevity.
Resources in this dataset:


Resource Title: Oviposition (egg laying) data for entire lifespan
File Name: Full_egg_data.csv
Resource Description: Egg laying (oviposition) data for entire lifespan for 6 populations of Drosophila melanogaster. Fly_ID is a unique identifier for each female fly assayed. SelectionLine is the specific replicate line and SelectionRegime is the overall increased (Resistant) or decreased (Susceptible) cold tolerance parameter (or Control, no selection). Treatment is in degrees Celsius and is the temperature at which the female was put to lay eggs. The remaining columns represent each day of egg counting. The first count was on day 6 after introduction to the temperature assigned, and counts were conducted every 6 days until the female died or until day 210.


Resource Title: Longevity (in days) for Drosophila melanogaster populations
File Name: Full_longevity_data.csv
Resource Description: Longevity data (survival) for 6 populations of Drosophila melanogaster. Fly_ID is a unique identifier for each female fly assayed. SelectionLine is the specific replicate line which includes the overall selection regime of increased (Resistant) or decreased (Susceptible) cold tolerance parameter (or Control, no selection) and the specific replicate for each selection regime (1 or 2). Treatment is in degrees Celsius and is the temperature at which the female was put to lay eggs. Longevity_days is the total lifespan of the individual female fly. If the Longevity_days is set at -9, the fly outlived the maximum days of 210 and was not counted in overall survival parameters.
DOI: 10.6084/m9.figshare.22806743
title: BM1

description: BM1: HLApollo flagship benchmark dataset
DOI: 10.6084/m9.figshare.20405502
title: DistractionData-Anon.csv

description: Distraction Data
DOI: 10.6084/m9.figshare.20405502.v1
title: DistractionData-Anon.csv

description: Distraction Data
DOI: 10.6084/m9.figshare.20405625
title: DistractionData-DescriptionsOfVariables.pdf

description: This is the description of variables for the DistractionData.csv data file
DOI: 10.5281/zenodo.7927209
title: Carbon Emissions Metals&Mining

description: This dataset contains financial and carbon emissiona information about Metals&Mining companies.
DOI: 10.5281/zenodo.7927208
title: Carbon Emissions Metals&Mining

description: This dataset contains financial and carbon emissiona information about Metals&Mining companies.
DOI: 10.6084/m9.figshare.22806494
title: FateMap Paper datasets #3 (Goyal et al., 2021, Biorxiv)

description: Datasets from: https://www.biorxiv.org/content/10.1101/2021.12.08.471833v1.full <br> All gDNA barcode sequencing datasets, both raw fastq files and processed data. <br>
DOI: 10.34943/78de0464-24c8-4397-89dc-70f3617881c6
title: Fraser River Delta Upper Slope Acoustic Doppler Current Profiler 300 kHz Deployed 2023-03-16

description: The RDI Workhorse Monitor ADCP 300 kHz (15551) was deployed on 2023-03-16 at Fraser River Delta Upper Slope. This site is located on the upper slope of the Fraser River delta, where depth is approximately 100 metres. This device is a Acoustic Doppler Current Profiler 300 kHz. Acoustic Doppler Current Profilers (ADCP) are hydroacoustic instruments, similar to sonars. ADCPs measure current speed and direction at multiple predetermined depths simultaneously. ADCPs use the Doppler effect of sound waves that are scattered by particles in seawater over a depth range. It was deployed on a fixed platform. Data from this deployment were archived and made available through Ocean Networks Canada's Oceans 3.0 digital infrastructure, with quality assurance and derived data products following established practices.
DOI: 10.5281/zenodo.7927211
title: A Gaussian Process Regression weights file for the Zundel cation

description: Trained weight files for a kernel model of the potential energy of the Zundel cation, to be used in an example of the i-PI interface of the librascal ML library
description: This is not meant to be a very accurate model, and only serves as an example
DOI: 10.5281/zenodo.7927210
title: A Gaussian Process Regression weights file for the Zundel cation

description: Trained weight files for a kernel model of the potential energy of the Zundel cation, to be used in an example of the i-PI interface of the librascal ML library
description: This is not meant to be a very accurate model, and only serves as an example
DOI: 10.15139/s3/eayrc4
title: Food Insecurity Among Black Households in the Mississippi Delta

description: Over 38 million Americans experienced food insecurity in 2020 and a disproportionate number of those people, over 21 percent, were Black Americans (USDA, 2021). While Black people across the country experienced food insecurity at disproportionately high rates, the Deep South’s prevalence of food insecurity continues to outpace much of the rest of America with three of the top five food insecure states (Mississippi, Louisiana, and Arkansas) comprising the Mississippi Delta (Henchy & Jacobs, 2020). There is a paradox at play in the Mississippi Delta region regarding its role as one of the top agricultural producers in the country but simultaneously home to some of the food insecure communities as well. Food insecurity is associated with a number of poor health outcomes including, but not limited to, decreased cognitive performance in children, increased anxiety, and depression in non-senior adults, as well as higher rates of diabetes, hypertension, and general increased rates of poor health (Gundersen, 2015). Black households in the Mississippi Delta experience a series of social determinants that contribute to the high prevalence of food insecurity in the region including poverty, racial residential segregation, social isolation, and lack of access to nutritious foods. Food Insecurity and its complexity of confounding factors leave researchers with a significant task to find leverage points at which community leaders, policy makers and other actors in the socioecological framework might reduce food insecurity in places with high food insecurity like the Mississippi Delta. This report recommends addressing food insecurity in the Delta through improving the local structure of information flows by offering education programs to boost enrollment in social welfare programs underutilized in the region.
DOI: 10.6084/m9.figshare.22191400.v4
title: FenFit CT Segmentations and Tabular Data

description: Raw de-identified patient geometry files used in FenFit paper
DOI: 10.5281/zenodo.7924809
title: MUSES Fractional Vegetation Coverage (FVC) 8-Day Global 1km SIN Grid in 2000

description: The MUltiscale Satellite remotE Sensing (MUSES) product suite includes products with different spatial and temporal resolutions for parameters such as Normalized Difference Vegetation Index (NDVI), Near-Infrared Reflectance of Vegetation (NIRv), Leaf Area Index (LAI), Fraction of Absorbed Photosynthetically Active Radiation (FAPAR), Fractional Vegetation Coverage (FVC), Gross Primary Production (GPP), Net Primary Production (NPP). For more information about the MUSES products, please refer to this website (https://muses.bnu.edu.cn/). This dataset is the MUSES global FVC product at 1 km spatial resolution and 8-day temporal resolution. The MUSES FVC product is provided on a Sinusoidal grid and spans from 2000 to 2019 (continuously updated). It was generated from the MUSES LAI product at 1 km resolution and other ancillary information using the complement to unity of the transmittance of light through the entire canopy in the nadir viewing direction (Xiao <em>et al</em>., 2016). The MUSES FVC values are physically consistent with the corresponding MUSES LAI values. The MUSES FVC product is spatially complete and temporally continuous. This dataset is the MUSES FVC product in 2000. <em>Please </em><em><strong>click here</strong> to download the MUSES FVC product <strong>in 2001</strong></em>. <strong>Dataset Characteristics:</strong> Spatial Coverage: Global Temporal Coverage: 2000 Spatial Resolution: 1 km Temporal Resolution: 8 days Projection: Sinusoidal Data Format: HDF Scale: 0.004 Valid Range: 0 – 250 <strong>Citation </strong>(Please cite this paper whenever these data are used)<strong>:</strong> Xiao Zhiqiang, <em>et a</em>l. (2016). Estimating the Fractional Vegetation Cover from GLASS Leaf Area Index Product. <em>Remote Sensing</em>, 8, 337. If you have any questions, please contact Prof. Zhiqiang Xiao (zhqxiao@bnu.edu.cn).
DOI: 10.5281/zenodo.7924808
title: MUSES Fractional Vegetation Coverage (FVC) 8-Day Global 1km SIN Grid in 2000

description: The MUltiscale Satellite remotE Sensing (MUSES) product suite includes products with different spatial and temporal resolutions for parameters such as Normalized Difference Vegetation Index (NDVI), Near-Infrared Reflectance of Vegetation (NIRv), Leaf Area Index (LAI), Fraction of Absorbed Photosynthetically Active Radiation (FAPAR), Fractional Vegetation Coverage (FVC), Gross Primary Production (GPP), Net Primary Production (NPP). For more information about the MUSES products, please refer to this website (https://muses.bnu.edu.cn/). This dataset is the MUSES global FVC product at 1 km spatial resolution and 8-day temporal resolution. The MUSES FVC product is provided on a Sinusoidal grid and spans from 2000 to 2019 (continuously updated). It was generated from the MUSES LAI product at 1 km resolution and other ancillary information using the complement to unity of the transmittance of light through the entire canopy in the nadir viewing direction (Xiao <em>et al</em>., 2016). The MUSES FVC values are physically consistent with the corresponding MUSES LAI values. The MUSES FVC product is spatially complete and temporally continuous. This dataset is the MUSES FVC product in 2000. <em>Please </em><em><strong>click here</strong> to download the MUSES FVC product <strong>in 2001</strong></em>. <strong>Dataset Characteristics:</strong> Spatial Coverage: Global Temporal Coverage: 2000 Spatial Resolution: 1 km Temporal Resolution: 8 days Projection: Sinusoidal Data Format: HDF Scale: 0.004 Valid Range: 0 – 250 <strong>Citation </strong>(Please cite this paper whenever these data are used)<strong>:</strong> Xiao Zhiqiang, <em>et a</em>l. (2016). Estimating the Fractional Vegetation Cover from GLASS Leaf Area Index Product. <em>Remote Sensing</em>, 8, 337. If you have any questions, please contact Prof. Zhiqiang Xiao (zhqxiao@bnu.edu.cn).
DOI: 10.5281/zenodo.7923809
title: MUSES Fractional Vegetation Coverage (FVC) 8-Day Global 1km SIN Grid in 2001

description: The MUltiscale Satellite remotE Sensing (MUSES) product suite includes products with different spatial and temporal resolutions for parameters such as Normalized Difference Vegetation Index (NDVI), Near-Infrared Reflectance of Vegetation (NIRv), Leaf Area Index (LAI), Fraction of Absorbed Photosynthetically Active Radiation (FAPAR), Fractional Vegetation Coverage (FVC), Gross Primary Production (GPP), Net Primary Production (NPP). For more information about the MUSES products, please refer to this website (https://muses.bnu.edu.cn/). This dataset is the MUSES global FVC product at 1 km spatial resolution and 8-day temporal resolution. The MUSES FVC product is provided on a Sinusoidal grid and spans from 2000 to 2019 (continuously updated). It was generated from the MUSES LAI product at 1 km resolution and other ancillary information using the complement to unity of the transmittance of light through the entire canopy in the nadir viewing direction (Xiao <em>et al</em>., 2016). The MUSES FVC values are physically consistent with the corresponding MUSES LAI values. The MUSES FVC product is spatially complete and temporally continuous. This dataset is the MUSES FVC product in 2001. <em>Please <strong>click here</strong> to download the MUSES FVC product <strong>in 2000</strong></em>, <em>and <strong>click here</strong> to download the MUSES FVC product <strong>in 2002</strong></em>. <strong>Dataset Characteristics:</strong> Spatial Coverage: Global Temporal Coverage: 2001 Spatial Resolution: 1 km Temporal Resolution: 8 days Projection: Sinusoidal Data Format: HDF Scale: 0.004 Valid Range: 0 – 250 <strong>Citation </strong>(Please cite this paper whenever these data are used)<strong>:</strong> Xiao Zhiqiang, <em>et a</em>l. (2016). Estimating the Fractional Vegetation Cover from GLASS Leaf Area Index Product. <em>Remote Sensing</em>, 8, 337. If you have any questions, please contact Prof. Zhiqiang Xiao (zhqxiao@bnu.edu.cn).
DOI: 10.5281/zenodo.7923808
title: MUSES Fractional Vegetation Coverage (FVC) 8-Day Global 1km SIN Grid in 2001

description: The MUltiscale Satellite remotE Sensing (MUSES) product suite includes products with different spatial and temporal resolutions for parameters such as Normalized Difference Vegetation Index (NDVI), Near-Infrared Reflectance of Vegetation (NIRv), Leaf Area Index (LAI), Fraction of Absorbed Photosynthetically Active Radiation (FAPAR), Fractional Vegetation Coverage (FVC), Gross Primary Production (GPP), Net Primary Production (NPP). For more information about the MUSES products, please refer to this website (https://muses.bnu.edu.cn/). This dataset is the MUSES global FVC product at 1 km spatial resolution and 8-day temporal resolution. The MUSES FVC product is provided on a Sinusoidal grid and spans from 2000 to 2019 (continuously updated). It was generated from the MUSES LAI product at 1 km resolution and other ancillary information using the complement to unity of the transmittance of light through the entire canopy in the nadir viewing direction (Xiao <em>et al</em>., 2016). The MUSES FVC values are physically consistent with the corresponding MUSES LAI values. The MUSES FVC product is spatially complete and temporally continuous. This dataset is the MUSES FVC product in 2001. <em>Please <strong>click here</strong> to download the MUSES FVC product <strong>in 2000</strong></em>, <em>and <strong>click here</strong> to download the MUSES FVC product <strong>in 2002</strong></em>. <strong>Dataset Characteristics:</strong> Spatial Coverage: Global Temporal Coverage: 2001 Spatial Resolution: 1 km Temporal Resolution: 8 days Projection: Sinusoidal Data Format: HDF Scale: 0.004 Valid Range: 0 – 250 <strong>Citation </strong>(Please cite this paper whenever these data are used)<strong>:</strong> Xiao Zhiqiang, <em>et a</em>l. (2016). Estimating the Fractional Vegetation Cover from GLASS Leaf Area Index Product. <em>Remote Sensing</em>, 8, 337. If you have any questions, please contact Prof. Zhiqiang Xiao (zhqxiao@bnu.edu.cn).
DOI: 10.25914/f01x-b211
title: Magnetotelluric Broadband Surveys of Australia
DOI: 10.25914/31br-q319
title: Magnetotelluric Broadband Surveys of Tasmania
DOI: 10.25914/be5s-at41
title: Magnetotelluric Broadband Survey of Western Tasmania, 2016
DOI: 10.25914/mrx9-r791
title: Magnetotelluric Broadband Survey of North-Western Tasmania, 2016
DOI: 10.25914/3erf-dn38
title: Magnetotelluric Broadband Surveys of Western and North-Western Tasmania, 2016
DOI: 10.25914/080v-2z48
title: Magnetotelluric Broadband Survey of Western Tasmania, 2016 (packed raw time series archive)
DOI: 10.25914/ekv8-my29
title: Magnetotelluric Broadband Survey of North-Western Tasmania, 2016 (packed raw time series archive)
DOI: 10.15482/usda.adc/1528996
title: CameraTrapDetectoR Pig Model

description: This dataset contains the model weights, architecture, and class label dictionary for CameraTrapDetectoR pig-only model version 1. The model architecture is a FasterRCNN object detection model with a ResNet50 backbone. This model identifies and counts wild pigs in camera trap images. It also includes categories for non-pig detections (animal, human, or vehicle), and a background class. Additional information about the R package and the training data can be found in the package's Github repository: https://github.com/CameraTrapDetectoR/CameraTrapDetectoR
List of Resources:

pig_v1.zip is a folder containing the model architecture, model weights, and class label dictionary used to deploy the pig-only model version 1 in CameraTrapDetectoR
DOI: 10.6084/m9.figshare.22191400.v5
title: FenFit CT Segmentations and Tabular Data

description: Raw de-identified patient geometry files used in FenFit paper
DOI: 10.5281/zenodo.7927051
title: Processed data for neurodegeneration vs tumorigenesis analyses

description: Processed data for neurodegeneration vs tumorigenesis analyses.
DOI: 10.5281/zenodo.7927050
title: Processed data for neurodegeneration vs tumorigenesis analyses

description: Processed data for neurodegeneration vs tumorigenesis analyses.
DOI: 10.6084/m9.figshare.22806917
title: HHCW Master Data Sheet

description: This spreadsheet includes all data used in a work stress study involving home healthcare workers including: ELISA data associated with participant cortisol levels, subjective stress levels associated with occupational stress exposure events, airborne pollutant data participants were exposed to, etc.
DOI: 10.25919/se1h-8505
title: Parkes observations for project P1194 semester 2023APRS_02

description: Among nearly 2000 unidentified gamma-ray sources detected with the Fermi Gamma Ray Space Telescope, there are potentially many pulsars. The ultra-wide frequency coverage will enable us to detect MSPs with steep spectrum and avoid difficulties caused by interstellar scintillation and dispersive and scattering smearing. We propose to revisit highly ranked pulsar candidates that remain unidentified. Such a pilot survey will help us designing future searches of the coming 4FGL gamma-ray source catalog using the UWL. We select 11 targets and request 12 hour time in total.
DOI: 10.6084/m9.figshare.20224099
title: The nomenclatural history of <i>Phormium colensoi</i> Hook.f.

description: The complicated nomenclatural history of <i>Phormium colensoi</i> Hook.f. is reviewed. The name and a very brief validating description, both attributed to Joseph Dalton Hooker, were published in 1848 in an article by Le Jolis. The brevity of the description does not affect the validity of the publication, and the name is here accepted as validly published. Indirect references to gatherings by Banks & Solander and by Colenso are discussed to identify original material. Plants seen during this study at localities close to those visited by Colenso have a diverse range of phenotypes, and Banks & Solander specimens also seem to show more than a single phenotype. A lectotype is therefore not designated at this time. Possible synonyms for <i>P. colensoi</i> are also discussed. <i>Phormium cookianum</i> Le Jol. is the name currently recognised by New Zealand botanists, but this has not historically always been the case. A Le Jolis specimen at Kew is designated as lectotype for <i>P. cookianum</i>. The possibility that <i>P. cookianum</i> is a provisional name, and is therefore invalid, is rejected. <i>Phormium forsterianum</i> Colenso is a validly published synonym, but is superfluous and illegitimate. <i>Phormium hookeri</i> Gunn ex Hook.f., commonly regarded as a subspecies of <i>P. cookianum</i>, may not be sufficiently different from phenotypes of <i>P. colensoi</i> to justify the same rank under that species. The conclusion by New Zealand botanists is that European writers on <i>Phormium</i> were greatly misled by the limited material they had to hand. An open question remains as to whether some or all the original specimens of <i>P. colensoi</i> and <i>P. cookianum</i> might be of hybrid origin. Until the necessary taxonomic work (genetic and population studies) has been done, the nomenclature of <i>Phormium</i> species should be regarded as an open question rather than being decided purely on publication dates.