cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.13623965
title: snpnetcox_map.tsv

description: mapping of disease phenotype and their IDs
DOI: 10.6084/m9.figshare.13623965.v1
title: snpnetcox_map.tsv

description: mapping of disease phenotype and their IDs
DOI: 10.6084/m9.figshare.13623959
title: Training and testing samples of three urban catchments in Beijing

description: This file included the training and testing samples of CNN model in three urban catchments (LSH, QH and BH catchments). Detailed descriptions of the data source and format are available in Zhao et al (2019) .Zhao, G., B. Pang, Z. Xu, D. Peng, and L. Xu (2019), Assessment of urban flood susceptibility using semi-supervised machine learning model, Sci Total Environ, 659, 940-949.<b></b><i></i><sub></sub><sup></sup><br><b></b><i></i><sub></sub><sup></sup><br> <br>
DOI: 10.6084/m9.figshare.13623959.v1
title: Training and testing samples of three urban catchments in Beijing

description: This file included the training and testing samples of CNN model in three urban catchments (LSH, QH and BH catchments). Detailed descriptions of the data source and format are available in Zhao et al (2019) .Zhao, G., B. Pang, Z. Xu, D. Peng, and L. Xu (2019), Assessment of urban flood susceptibility using semi-supervised machine learning model, Sci Total Environ, 659, 940-949.<b></b><i></i><sub></sub><sup></sup><br><b></b><i></i><sub></sub><sup></sup><br> <br>
DOI: 10.15468/s4bg5k
title: GASTRODIA AGNICELLUS

description: This dataset contains the digitized treatments in Plazi based on the original journal article Hermans, Johan (2020): GASTRODIA AGNICELLUS. Curtis's Botanical Magazine 37 (3): 385-395, DOI: 10.1111/curt.12354, URL: http://dx.doi.org/10.1111/curt.12354
DOI: 10.5258/10.5258/soton/d1400
title: Dataset for: Microplastics in fish and fishmeal: an emerging environmental challenge?
DOI: 10.5258/soton/d1400
title: Dataset for: Microplastics in fish and fishmeal: an emerging environmental challenge?

description: This dataset supports the publication: Thiele, C. J., Hudson, M., Russell, A. E., Saluveer, M., and Sidaoui-Haddad, G. (2021). Microplastics in fish and fishmeal: an emerging environmental challenge? Scientific Reports, 11, [2045]. https://doi.org/10.1038/s41598-021-81499-8
DOI: 10.5281/zenodo.3630701
title: Supplementary Materials for "Simultaneous single-shot radiographic imaging using a laser-driven x-ray and proton micro-source"

description: Simulation Data Repository, please read the contained README file in the contained simulation/ directory. This directory contains a copy of the used PIConGPU source code, version 0.5.0-dev-60ad9eb85 and analysis scripts. The PIConGPU source code is archived including its complete git history (git version 2.17.1) in source/picongpu.tar.gz with the input parameter template inside in share/picongpu/examples/Wneedle . Generally, PIConGPU source code is available via https://doi.org/10.5281/zenodo.591746 with its public git repository being maintained on https://github.com/ComputationalRadiationPhysics/picongpu . The two simulations’ exact input is modified accordingly in the directory input/ inside: 2D_a0-45_Z-10_ppc-20_002_light.tar.gz (p-polarized; along X) 2D_a0-45_Z-10_ppc-20_003_light.tar.gz (s-polarized; along Z). “Heavy” simulation data (checkpoints in simOutput/checkpoints/, full-resolution field and particle output in simOutput/bp/ ) has been stripped from this archive and are archived on NERSC’s HPSS tape archive. Analysis scripts are provided as Jupyter notebooks (DensityPlot_polX.ipynb and DensityPlot_polZ.ipynb) and depend on the following software: - adios 1.13.1 python bindings with enabled c-blosc transformations<br> - numpy 1.17.1<br> - matplotlib 3.1.1<br> - PIConGPU post-processing helper modules located in each simulation root directory under “input/lib/python/”<br> <br> The detailed conda environment can be found in the README.
description: This research used resources of the National Energy Research Scientific Computing Center (NERSC), a U.S. Department of Energy Office of Science User Facility operated under Contract No. DE-AC02-05CH11231. A. Huebl acknowledges support by the Exascale Computing Project (17-SC-20-SC), a collaborative effort of two U.S. Department of Energy organizations (Office of Science and the National Nuclear Security Administration). We acknowledge all contributors to the open-source code PIConGPU for enabling our simulations.
DOI: 10.5281/zenodo.3630700
title: Supplementary Materials for "Simultaneous single-shot radiographic imaging using a laser-driven x-ray and proton micro-source"

description: Simulation Data Repository, please read the contained README file in the contained simulation/ directory. This directory contains a copy of the used PIConGPU source code, version 0.5.0-dev-60ad9eb85 and analysis scripts. The PIConGPU source code is archived including its complete git history (git version 2.17.1) in source/picongpu.tar.gz with the input parameter template inside in share/picongpu/examples/Wneedle . Generally, PIConGPU source code is available via https://doi.org/10.5281/zenodo.591746 with its public git repository being maintained on https://github.com/ComputationalRadiationPhysics/picongpu . The two simulations’ exact input is modified accordingly in the directory input/ inside: 2D_a0-45_Z-10_ppc-20_002_light.tar.gz (p-polarized; along X) 2D_a0-45_Z-10_ppc-20_003_light.tar.gz (s-polarized; along Z). “Heavy” simulation data (checkpoints in simOutput/checkpoints/, full-resolution field and particle output in simOutput/bp/ ) has been stripped from this archive and are archived on NERSC’s HPSS tape archive. Analysis scripts are provided as Jupyter notebooks (DensityPlot_polX.ipynb and DensityPlot_polZ.ipynb) and depend on the following software: - adios 1.13.1 python bindings with enabled c-blosc transformations<br> - numpy 1.17.1<br> - matplotlib 3.1.1<br> - PIConGPU post-processing helper modules located in each simulation root directory under “input/lib/python/”<br> <br> The detailed conda environment can be found in the README.
description: This research used resources of the National Energy Research Scientific Computing Center (NERSC), a U.S. Department of Energy Office of Science User Facility operated under Contract No. DE-AC02-05CH11231. A. Huebl acknowledges support by the Exascale Computing Project (17-SC-20-SC), a collaborative effort of two U.S. Department of Energy organizations (Office of Science and the National Nuclear Security Administration). We acknowledge all contributors to the open-source code PIConGPU for enabling our simulations.
DOI: 10.5281/zenodo.4455953
title: Multiseriate cortical sclerenchyma enhance root penetration in compacted soils

description: Accompanying data for 'Multiseriate cortical sclerenchyma enhance root penetration in compacted soils'
DOI: 10.5281/zenodo.4455952
title: Multiseriate cortical sclerenchyma enhance root penetration in compacted soils

description: Accompanying data for 'Multiseriate cortical sclerenchyma enhance root penetration in compacted soils'
DOI: 10.5281/zenodo.4450881
title: Discrete Element Model for subglacial till: code and data

description: This is a permanent archive of the code and data for the Discrete Element Model, Sphere, developed by Anders Damsgaard, and used for simulations of deforming subglacial till. File is compressed in the tar.bz2 format. The Sphere code and documentation can be found at https://src.adamsgaard.dk/sphere/ . Run sphere/python/MyVisualization.py to generate the figures in sphere/Images/.
DOI: 10.5281/zenodo.4450880
title: Discrete Element Model for subglacial till: code and data

description: This is a permanent archive of the code and data for the Discrete Element Model, Sphere, developed by Anders Damsgaard, and used for simulations of deforming subglacial till. File is compressed in the tar.bz2 format. The Sphere code and documentation can be found at https://src.adamsgaard.dk/sphere/ . Run sphere/python/MyVisualization.py to generate the figures in sphere/Images/.
DOI: 10.25345/c5321h
title: MassIVE MSV000086742 - P. putida predation sensitive vs predation survivor
title: Comparison of P. putida type strain crude extract with P. putida type strain phenotype evading myxobacterium C. ferrugineus predation.
DOI: 10.6084/m9.figshare.13623989
title: Identification of Variants (rs11571707, rs144848, and rs11571769) in the BRCA2 Gene Associated with Hereditary Breast Cancer in Indigenous Populations of the Brazilian Amazon

description: Describes the raw genotype data of the BRCA1 and BRCA2 mutation profiles of Native American populations and their potential association with increased susceptibility to breast cancer.
DOI: 10.6084/m9.figshare.13623989.v1
title: Identification of Variants (rs11571707, rs144848, and rs11571769) in the BRCA2 Gene Associated with Hereditary Breast Cancer in Indigenous Populations of the Brazilian Amazon

description: Describes the raw genotype data of the BRCA1 and BRCA2 mutation profiles of Native American populations and their potential association with increased susceptibility to breast cancer.
DOI: 10.6084/m9.figshare.13623971
title: Raw Data.xlsx

description: Excel sheet data contains age, sex, WSLs in 30, 90 and 180 days follow up
DOI: 10.6084/m9.figshare.13623971.v1
title: Raw Data.xlsx

description: Excel sheet data contains age, sex, WSLs in 30, 90 and 180 days follow up
DOI: 10.15468/cpenfw
title: A new species of the genus Pareas (Squamata, Pareidae) from Yunnan, China

description: This dataset contains the digitized treatments in Plazi based on the original journal article Liu, Shuo, Rao, Dingqi (2021): A new species of the genus Pareas (Squamata, Pareidae) from Yunnan, China. ZooKeys 1011: 121-138, DOI: http://dx.doi.org/10.3897/zookeys.1011.59029, URL: http://dx.doi.org/10.3897/zookeys.1011.59029
DOI: 10.34740/kaggle/dsv/1866714
title: US counties COVID 19 dataset
DOI: 10.15468/sbqfsq
title: <strong> From the frying pan: an unusual dwarf shrub from Namibia turns out to be a new brassicalean family strong&gt;</strong>

description: This dataset contains the digitized treatments in Plazi based on the original journal article SWANEPOEL, WESSEL, CHASE, MARK W., CHRISTENHUSZ, MAARTEN J. M., MAURIN, OLIVIER, FOREST, FÉLIX, VAN WYK, ABRAHAM E. (2020): <strong> From the frying pan: an unusual dwarf shrub from Namibia turns out to be a new brassicalean family &lt;/ strong&gt;. Phytotaxa 439 (3): 171-185, DOI: 10.11646/phytotaxa.439.3.1, URL: http://dx.doi.org/10.11646/phytotaxa.439.3.1</strong>
DOI: 10.25966/02c0-ts79
title: MODIS Cloud Regimes and Cloud-Precipitation Hybrid Regimes (MODIS-IMERG)

description: Cloud regimes and Cloud-Precipitation Hybrid Regimes are derived via k-means clustering, with MODIS C6.1 2D joint histogram of CTP and COT (total 42 bins) and IMERG v06B precipitation histogram (total 6 bins) in 50S-50N and 15S-15N domain.

By the relative weight between cloud and precipitation, there are 4 kinds of regime sets for each tropical and extended domain:
1) Cloud only (42 bins),
2) Cloud+Precipitation with weight 1 (Cld42+Pr6x1; 48 bins),
3) Cloud+Precipitation with weight 3 (Cld42+Pr6x3; 60 bins),
4) Cloud+Precipitation with weight 7 (Cld42+Pr6x7; 84 bins; equal weight).
DOI: 10.6073/pasta/911dad35624be8a378a6f9bc48674242
title: Landscape Flowering Phenology Field Data for Sites in the Vicinity of Crested Butte, CO

description: This dataset represents field observations of reproductive development (flowering phenology) in 135 species of flowering plants collected at 12 field sites in the vicinity of Crested Butte, Colorado starting in 2019. Sites were visited approximately weekly from early May until early August, and all species in flower were recorded in 25 segments along a 50m transect at each site, and species were recorded if they were within 1m of either side of the transect. Datasets included in this package are 1) cleaned field observations of flowering phenology, 2) taxonomic identity of all recorded species, 3) spatial data representing the location of the center of each transect segment, and 4) spatial data representing the segment polygons.
DOI: 10.5281/zenodo.4456051
title: Fraunhofer IML dataset

description: The dataset is produced within the Safelog project and is used for the evaluation of the developed algorithm which estimates the location of humans in the warehouse environments.
DOI: 10.5281/zenodo.4040555
title: Fraunhofer IML dataset

description: The dataset is produced within the Safelog project and is used for the evaluation of the developed algorithm which estimates the location of humans in the warehouse environments.
DOI: 10.25345/c5zb8p
title: MassIVE MSV000086743 - N2 methanol extract MS1 agilent C18 column
title: wildtype and acox-1 c elegans extract ran on reverse phase 28 min method on Agilent C18 column
DOI: 10.5066/p9j7i9nw
title: Electron microprobe and 40Ar/39Ar isotopic data from west-central New Hampshire

description: This dataset accompanies planned publication 'Unmixing multiple metamorphic muscovite age populations with powder X-ray diffraction and 40Ar/39Ar analysis'. The 40Ar/39Ar and electron microprobe data are from samples adjacent to a lower greenschist facies shear zone in western New Hampshire. The geochronology coupled with the electron microprobe data provide a petrochronologic framework for the rocks studied in the manuscript. Sample collection was supervised by Ryan McAleer, Gregory Walsh, and Peter Valley of the USGS.
DOI: 10.5281/zenodo.4456059
title: Swisslog dataset

description: The dataset is produced within the Safelog project and is used for the evaluation of the developed algorithm which estimates the location of humans in the warehouse environments.
DOI: 10.5281/zenodo.4382268
title: Zagreb dataset

description: The dataset is produced within the Safelog project and is used for the evaluation of the developed algorithm which estimates the location of humans in the warehouse environments.
DOI: 10.6084/m9.figshare.13621169.v1
title: Speedtest Open Data - Four International cities - MEL, BKK, SHG, LAX

description: This dataset compares four cities broadband internet speeds:- Melbourne, AU- Bangkok, TH- Shanghai, CN- Los Angeles, USGeojsons of these 2* by 2* extracts will be added shortly.This unpacks, geospatially, data summaries provided in Speedtest Global Index (linked below).<br>Histograms, and data visualisations will be provided.Data Sourced from - This is an extract of Speedtest Open data available at Amazon WS (link below - opendata.aws).<br>AWS data licence is "CC BY-NC-SA 4.0", so use of this data must be:- non-commercial (NC)- reuse must be share-alike (SA)(add same licence).This restricts the standard CC-BY Figshare licence.<br>
DOI: 10.6084/m9.figshare.13624082
title: Higher cognitive reserve is associated with better working memory performance and working-memory-related P300 modulation

description: This study aims to examine how two levels of cognitive reserve, as evidenced by reading syntactic skill, modify performance and neural activity in a two-load-level (high vs. low) working memory (WM) task. Two groups of participants with different reading skills, high and low, were obtained from clustering analysis. We collected the P300 event-related potential component during the performance of the WM Sternberg task. <br>
DOI: 10.34683/sr1070
title: StoneRounds Case: SR1070
title: Foveal Hypoplasia

description: StoneRounds Case SR1070 was diagnosed with Foveal Hypoplasia likely caused by mutations in the gene: PAX6.
DOI: 10.6084/m9.figshare.3761562.v1751
title: Online Labour Index: Measuring the Online Gig Economy for Policy and Research

description: Data repository for the data underlying the Online Labour Index. See http://ilabour.oii.ox.ac.uk online-labour-index/ for details.
DOI: 10.6084/m9.figshare.13624082.v1
title: Higher cognitive reserve is associated with better working memory performance and working-memory-related P300 modulation

description: This study aims to examine how two levels of cognitive reserve, as evidenced by reading syntactic skill, modify performance and neural activity in a two-load-level (high vs. low) working memory (WM) task. Two groups of participants with different reading skills, high and low, were obtained from clustering analysis. We collected the P300 event-related potential component during the performance of the WM Sternberg task. <br>
DOI: 10.25345/c5tj6r
title: MassIVE MSV000086744 - 01212021_Chelomics-versus-native-metabolomics_benchmarking_data
title: The chelomics approach was compared to the native metabolomics approach on culture extracts and purified standards (siderophores and domoic acid).
DOI: 10.5281/zenodo.4455607
title: Data_Appendix C_Biomechanical Basis of Human Movement

description: Sample Kinematic and Kinetic Data Subject: 50-kg woman<br> Activity: Walking sampled at 120 Hz; one cycle from right foot touchdown to right foot<br> touchdown<br> Markers: Head, R shoulder, R elbow, R wrist, R hand, R crest (IC), R greater trochanter<br> (GT), R knee, R ankle, R heel, R fifth metatarsal (met), and R toe<br> Stride events: Right foot touchdown (RTD), left foot touchdown (LTD), and right foot<br> toe-off (RTO)<br>
DOI: 10.18112/openneuro.ds003481.v1.0.1
title: Pragmatic Language
DOI: 10.18112/openneuro.ds003481.v1.0.2
title: Pragmatic Language
DOI: 10.17632/mpkwt7fmp6.1
title: Data for: Monte Carlo Model Validation of a Detector System Used for Positron Emission Particle Tracking

description: Geant4 Application for Tomographic Emission model of the ADAC/Phillips Forte dual-headed positron camera used for positron emission particle tracking experiments at the Positron Imaging Centre. The data folder contains all imported geometries and material definitions. The mac folder includes the geometric and digitizer model of the system, as well as the phantom and source descriptions used for model validation. Output files are produced in the output folder. Please use the 'Run_Forte.mac' file to set the appropriate paths to macro files and to begin the simulation.
DOI: 10.17632/36pdh4r43p.1
title: Data for: Loss in Weight Feeding, Powder Flow and Electrostatic Evaluation for Direct Compression Hydroxypropyl Methylcellulose (HPMC) to Support Continuous Manufacturing

description: Loss in Weight Feeder for six different HPMC materials (3 grades and 2 types) run at 3 different feed rates
DOI: 10.25612/837.1jvvr7vdngd1
title: Small Business Pulse Survey Data

description: Data from a survey measuring the effect of changing business conditions during the COVID-19 pandemic on the United States’ small businesses.
DOI: 10.3886/e112301v1-73660
title: Data and Code for The Labor Market Impact of Immigration: Job Creation vs. Job Competition

description: This paper studies the labor market effects of both documented and undocumented immigration in a search model featuring non-random hiring. As immigrants accept lower wages, they are preferably chosen by firms and therefore have higher job finding rates than natives, consistent with evidence found in US data. Immigration leads to the creation of additional jobs but also raises competition for natives. Which effect dominates depends on the fall in wage costs, which is larger for undocumented than for legal immigration. The model predicts a dominating job creation effect for the former, reducing natives' unemployment rate, but not for the latter.
description: Personal probability weights provided by IPUMS are used.
description: Prime-age (25-65) high-school dropouts that are non-institutionalized and live in households in urban areas (MSAs) in the United States.
DOI: 10.3886/e120402v1-73661
title: Replication Data for: A Look Ahead at the 2020 US Elections: The Role of Candidate Diversity in Political Participation

description: These files contain the replication code and data for the article "A Look Ahead at the 2020 US Elections: The Role of Candidate Diversity in Political Participation" published in the AEA Papers and Proceedings.
DOI: 10.17632/3g95ns5rpj.4
title: Data for: Development and application of dairy-based sustainable livelihood security index in the districts of West Bengal, India: A tool for dairy development planning

description: District wise data base of 18 states of West Bengal on 17 indicators
DOI: 10.6084/m9.figshare.13624202
title: GM and mutagenesis_Merged file_OpenAccess1.sav

description: This data contains variables pertaining to attitudes to plant biotechnology such as GM and gene editing. It also contains variables pertaining to food perception and environmental attitudes.
DOI: 10.6084/m9.figshare.13624202.v1
title: GM and mutagenesis_Merged file_OpenAccess1.sav

description: This data contains variables pertaining to attitudes to plant biotechnology such as GM and gene editing. It also contains variables pertaining to food perception and environmental attitudes.
DOI: 10.5281/zenodo.4456126
title: r-process abundances in neutron-rich merger ejecta given different theoretical nuclear physics inputs

description: This data release contains nucleosynthesis predictions for the r-process abundances presented in Côté, Eichler, Yagüe, Vassh et al. (2021) for compact object merger ejecta based on the publicly available simulation trajectories of Rosswog et al. (2013). All ejecta for the merger scenarios considered here are very neutron-rich (Ye ~ 0.016-0.11). Calculations were performed with the PRISM code (Mumpower et al. 2018) which accounts for nuclear reheating (here with a reheating efficiency of 50%). Results are reported for several different theoretical nuclear physics inputs but all calculations make use of the GEF fission yield prescription (see Vassh et al. 2019). All abundances are given at 1 Myr (10^6 years) post-merger. Please see the README file for more details and references. When using these nucleosynthesis yields, please cite this Zenodo data release (Vassh et al. 2021), and refer to Vassh et al. (2019) and Côté, Eichler, Yagüe, Vassh et al. (2021) for further details on the nuclear data applied as well as Rosswog et al. (2013), Piran et al. (2013), and Korobkin et al. (2012) for further details on the merger ejecta trajectories.
description: NV and RS were supported by the Fission In R-process Elements (FIRE) topical collaboration in nuclear theory, funded by the U.S. Department of Energy. TMS and RS were supported by the U.S. Department of Energy SciDAC collaboration TEAMS (DE-SC0018232). TMS was supported by the Los Alamos National Laboratory Center for Space and Earth Science, which is funded by its Laboratory Directed Research and Development program under project number 20180475DR. MRM was supported by the US Department of Energy through the Los Alamos National Laboratory and by the Laboratory Directed Research and Development program of Los Alamos National Laboratory under project number 20190021DR. Los Alamos National Laboratory is operated by Triad National Security, LLC, for the National Nuclear Security Administration of U.S. Department of Energy (Contract No. 89233218CNA000001). This dataset is released under Los Alamos National Laboratory report number LA-UR-21-20444.