cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.21947/2229252
title: WFIP3 MRR2 / Raw Spectra, Barge

description: This dataset includes raw Doppler spectra recorded by the Micro Rain Radar. It is designed for advanced users to perform their own processing of the MRR2 data.
DOI: 10.5439/2229368
title: Measurement of particulated matter (PM1, PM2.5, PM10) using a PM sensor during the SAIL campaign in Gothic, CO and Mt. Crested Butte, CO

description: We deployed another PM sensor (Modulair-PM, QuantAQ) to measure the mass concentration of particulate matter (PM) for three size cuts at both the main site (M1) and supplementary site (S2) of the SAIL from 14 June 2022 to 14 June 2023. The instruments provide the mass concentration of PM1, PM2.5 and PM10. Mass concentrations were calculated based on measurements made with a nephelometer and an OPC. We used Quant-AQ's algorithm [please see their documentation here and the references within] to determine the mass concentrations reported. Here, we present the time series of sample relative humidity, temperature, pressure, and the mass concentration of PM1, PM2.5 and PM10. We also present the size distribution of the aerosol particles within a diameter range of 0.35 - 40 micron, measured by the OPC of the pm-modulair. However, we encourage caution while using the size distribution data, since it is operated only with the factory calibration. Abstract and description of the campaign can be found here : https://www.arm.gov/research/campaigns/amf2022ssb.
DOI: 10.57841/casdc.0003229
title: 基于摩擦耗散的石墨/WC-Ni干摩擦下磨损定量及预测
DOI: 10.21947/2229424
title: WFIP3 - BLOC site - CU Profiling Lidar (Windcube v1) / Raw data

description: This dataset is from WFIP3 BLOC site WindCube v1 Profiling Lidar / Raw Data from CU Boulder. Please note that the .sta files are in human-readable text, while the .rtd files require some processing software that is not easily automated. We plan to process the .rtd data following the campaign, but if you wish to try it sooner, we can make it available upon request.
DOI: 10.21947/2229425
title: WFIP3 - BLOC site - CU Profiling Lidar (Windcube v1) / Reviewed data

description: This dataset contains reviewed data from the WFIP3 Site BLOC WindCube v1 Profiling Lidar from CU Boulder.
DOI: 10.21947/2229427
title: WFIP3 - BLOC site - CU Profiling Lidar (Windcube v1) / Reviewed data

description: This dataset contains reviewed data from the WFIP3 Site BLOC WindCube v1 Profiling Lidar from CU Boulder.
DOI: 10.21947/2229428
title: WFIP3 - MVCO site - CU Profiling Lidar (Windcube v1) / Raw Data

description: This dataset contains raw data from the WFIP3 Site MVCO WindCube v1 Profiling Lidar from CU Boulder.
DOI: 10.15485/2229438
title: Carbon flux measurements from chambers collected between July to October 2022 at Old Woman Creek, Huron, Ohio.

description: This dataset contains carbon dioxide and methane flux measurements collected via chamber sampling at Old Woman Creek National Estuarine Research Reserve in Huron, OH. These data were generated to understand temporal and vegetation patterns associated with wetland carbon cycling. Specifically, this dataset intends to answer how carbon dioxide and methane fluxes change monthly and hourly across sites with vegetation and without vegetation. Data includes chamber measurements that were measured in both sites with vegetation and without vegetation and that were collected hourly, for 12 hours, and monthly, for four months. The file soilrespiration_data.csv contains these data, and the metadata file (soilrespiration_chammetadata.csv) and location metadata file (soilrespiration_locationmetadata.csv) have information on locations where the chambers were placed and sampled in the wetland. Data processing was done on raw methane fluxes (Flux_CH4) to remove the influence of ebullition (Flux_CH4_ebullition) to get a diffusive flux (Flux_CH4_diffusive).
DOI: 10.25505/fiz.icsd.cc2hnhh5
title: CSD 2313607: Experimental Crystal Structure Determination

description: Related Article: Andrew S. Wills, Simon Coles and Michael B. Hursthouse|2004|University of Southampton, Crystal Structure Report Archive||1173|
description: An entry from the Inorganic Crystal Structure Database, the world’s repository for inorganic crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the joint CCDC and FIZ Karlsruhe Access Structures service and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.25505/fiz.icsd.cc2hnhk7
title: CSD 2313609: Experimental Crystal Structure Determination

description: Related Article: Andrew S. Wills, Simon Coles and Michael B. Hursthouse|2004|University of Southampton, Crystal Structure Report Archive||1172|
description: An entry from the Inorganic Crystal Structure Database, the world’s repository for inorganic crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the joint CCDC and FIZ Karlsruhe Access Structures service and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.25505/fiz.icsd.cc2hnhl8
title: CSD 2313610: Experimental Crystal Structure Determination

description: Related Article: Andrew S. Wills, Simon Coles and Michael B. Hursthouse|2004|University of Southampton, Crystal Structure Report Archive||1170|
description: An entry from the Inorganic Crystal Structure Database, the world’s repository for inorganic crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the joint CCDC and FIZ Karlsruhe Access Structures service and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5281/zenodo.10360319
title: Dataset for "Ferric-iron-bearing silicates at the base of the mantle transition zone"

description: Single crystal X-ray diffraction raw data supporting the results of the manuscript.
Powder X-ray diffraction raw data supporting the results of the manuscript.
Powder X-ray diffraction processed data supporting the results of the manuscript.
Submitted to Journal of Geophysical Research: Solid Earth.
DOI: 10.5281/zenodo.10360320
title: Dataset for "Ferric-iron-bearing silicates at the base of the mantle transition zone"

description: Single crystal X-ray diffraction raw data supporting the results of the manuscript.
Powder X-ray diffraction raw data supporting the results of the manuscript.
Powder X-ray diffraction processed data supporting the results of the manuscript.
Submitted to Journal of Geophysical Research: Solid Earth.
DOI: 10.21227/k66a-xz05
title: Coil,Transformer and IPM motor

description: For coil dataset，the shape of one data is [160,160,5]For transformer dataset，the shape of one data is [400,400,5]For IPM motor dataset，the shape of one data is [180,180,5]The first five layers consist of input device property information, while the sixth layer represents the FEA magnetic field distribution results.When using, please note to split the dataset into two parts, with x being transformed as follows:X = data[:, :, :5]X = np.transpose(X, (2, 0, 1))X = torch.from_numpy(X), and y being transformed as follows:y = data[:, :, 5]y = torch.from_numpy(y)y = y.unsqueeze(0)
DOI: 10.25919/rt63-mw33
title: National Bushfire Intelligence Capability (NBIC) Stage 1 Collection

description: The National Bushfire Intelligence Capability (NBIC) is providing national awareness for bushfire hazard and risk. It recognises that disaster risk reduction requires an informed shared understanding of bushfire hazard and risk across the disaster Prevent-Prepare-Response-Recovery (PPRR) continuum. The NBIC approach is unique in that it was conceived and is being implemented as an integrated socio-technical system to ensure that data design and relevance is optimised and to support longer-term climate adaptation decision making. 

NBIC Stage 1 achieved the generation of bushfire behaviour maps that consider future climate over a range of timescales using the best available and readily accessible data. This data collection comprises a set of demonstration outputs that show bushfire hazard severity potential and various layers that are used to calculate it. These include draft input mapping rasters for slope and fire weather potential (baseline and projected). 

The NBIC workflow uses a powerful cloud-based digital platform to enable the rapid co-development, testing and delivery of national extent products. NBIC Stage 2 will build on this work to produce more refined outputs of bushfire hazard, incorporating ongoing advances in data and science to support medium- to long-term decision support needs. 
 
Further information about NBIC is available at https://research.csiro.au/nbic/
DOI: 10.6084/m9.figshare.24791445
title: Data for colorplots in Fig.3

description: Data for colorplots in Fig.3Fig.3(a): Ne9_Dfield0.070-0.110_eps4.0-8.0_flux0.00_theta0.770.npzFig.3(b): Ne9_Dfield0.070-0.110_eps4.0-8.0_flux0.00_theta0.770.npzFig.3(c): Ne18_Dfield0.070-0.110_eps4.0-8.0_flux0.00_theta0.770.npzFig.3(d): Ne18_Dfield0.070-0.110_eps4.0-8.0_flux0.00_theta0.770.npzMore details in README-Fig3.txt
DOI: 10.6084/m9.figshare.24791445.v1
title: Data for colorplots in Fig.3

description: Data for colorplots in Fig.3Fig.3(a): Ne9_Dfield0.070-0.110_eps4.0-8.0_flux0.00_theta0.770.npzFig.3(b): Ne9_Dfield0.070-0.110_eps4.0-8.0_flux0.00_theta0.770.npzFig.3(c): Ne18_Dfield0.070-0.110_eps4.0-8.0_flux0.00_theta0.770.npzFig.3(d): Ne18_Dfield0.070-0.110_eps4.0-8.0_flux0.00_theta0.770.npzMore details in README-Fig3.txt
DOI: 10.6084/m9.figshare.24791604
title: Data for colorplots in Fig.4

description: Data for colorplots in Fig.4Fig.4(a): Ne9_Dfield0.097_eps5.0_flux0.00_theta0.770.npzFig.4(b): Ne9_Dfield0.097_eps5.0_flux0.00-3.00_theta0.770.npzFig.4(c): Ne9_Dfield0.090_eps4.0_flux0.00_theta0.770.npzFig.4(d): Ne9_Dfield0.090_eps4.0_flux0.00-3.00_theta0.770.npzFig.4(e): Ne9_Dfield0.070_eps5.0_flux0.00_theta0.770.npzFig.4(f): Ne9_Dfield0.110_eps4.0_flux0.00_theta0.770.npzFig.4(g): Ne9_Dfield0.070_eps4.0_flux0.00_theta0.770.npzFig.4(h): Ne9_Dfield0.110_eps8.0_flux0.00_theta0.770.npzMore details in README-Fig4.txt
DOI: 10.6084/m9.figshare.24791604.v1
title: Data for colorplots in Fig.4

description: Data for colorplots in Fig.4Fig.4(a): Ne9_Dfield0.097_eps5.0_flux0.00_theta0.770.npzFig.4(b): Ne9_Dfield0.097_eps5.0_flux0.00-3.00_theta0.770.npzFig.4(c): Ne9_Dfield0.090_eps4.0_flux0.00_theta0.770.npzFig.4(d): Ne9_Dfield0.090_eps4.0_flux0.00-3.00_theta0.770.npzFig.4(e): Ne9_Dfield0.070_eps5.0_flux0.00_theta0.770.npzFig.4(f): Ne9_Dfield0.110_eps4.0_flux0.00_theta0.770.npzFig.4(g): Ne9_Dfield0.070_eps4.0_flux0.00_theta0.770.npzFig.4(h): Ne9_Dfield0.110_eps8.0_flux0.00_theta0.770.npzMore details in README-Fig4.txt
DOI: 10.6084/m9.figshare.24791613
title: Data for colorplots in Fig.5

description: Data for colorplots in Fig.5Fig.5(a): Ne9_Dfield0.090-0.100_eps4.0-6.0_flux0.00_theta0.770.npzFig.5(b): Ne9_Dfield0.090-0.100_eps4.0-6.0_flux0.00_theta0.770.npzMore details in README-Fig5.txt
DOI: 10.6084/m9.figshare.24791613.v1
title: Data for colorplots in Fig.5

description: Data for colorplots in Fig.5Fig.5(a): Ne9_Dfield0.090-0.100_eps4.0-6.0_flux0.00_theta0.770.npzFig.5(b): Ne9_Dfield0.090-0.100_eps4.0-6.0_flux0.00_theta0.770.npzMore details in README-Fig5.txt
DOI: 10.6084/m9.figshare.24791628
title: Data for colorplots in Fig.6

description: Data for colorplots in Fig.6Fig.6(a): Ne8_Dfield0.070-0.110_eps4.0-8.0_flux0.00_theta0.770.npzFig.6(b): Ne8_Dfield0.094_eps5.0_flux0.00_theta0.770.npzFig.6(c): Ne12_Dfield0.070-0.110_eps4.0-8.0_flux0.00_theta0.770.npzFig.6(d): Ne8_Dfield0.094_eps5.0_flux0.00-5.00_theta0.770.npzMore details in README-Fig6.txt
DOI: 10.6084/m9.figshare.24791628.v1
title: Data for colorplots in Fig.6

description: Data for colorplots in Fig.6Fig.6(a): Ne8_Dfield0.070-0.110_eps4.0-8.0_flux0.00_theta0.770.npzFig.6(b): Ne8_Dfield0.094_eps5.0_flux0.00_theta0.770.npzFig.6(c): Ne12_Dfield0.070-0.110_eps4.0-8.0_flux0.00_theta0.770.npzFig.6(d): Ne8_Dfield0.094_eps5.0_flux0.00-5.00_theta0.770.npzMore details in README-Fig6.txt
DOI: 10.26186/149046
title: Enhanced Oil Recovery Potential Basins

description: This dataset shows the key Australian petroleum producing basins ranked by their potential for CO2 enhanced oil recovery (CO2-EOR), based on a study completed by Geoscience Australia in 2020. Basin rankings result from the assessment of six parameters: the API gravity of the oil, temperature, pressure, reservoir quality (porosity, permeability), nearby CO2 sources and existing infrastructure. Higher rankings indicate greater potential for CO2-EOR. For further information see: Tenthorey, E., and Kalinowski, A. 2022. Screening Australia’s Basins for CO2-Enhanced Oil Recovery. Proceedings of the 16th Greenhouse Gas Control Technologies Conference (GHGT-16) 23-24 Oct 2022. Available at SSRN: https://ssrn.com/abstract=4294743 or http://dx.doi.org/10.2139/ssrn.4294743.
DOI: 10.6084/m9.figshare.24791520
title: 13 PCGs.rar——Mitochondrial13 protein-coding genes used for selection pressure analyses.PCGs.fas ——The concatenated dataset of mitochondrial PCGs used for phylogeny

description: 1.The dataset (13PCGs.rar) can be decompressed into 13 protein-editing gene files, opened using the MEGA software, and used for selection pressure analyses. 2. The dataset (PCGs.fas) used for phylogeny.
DOI: 10.6084/m9.figshare.24791520.v1
title: 13 PCGs.rar Mitochondrial13 protein-coding genes used for selection pressure analyses

description: The dataset of mitochondrial 13 protein-coding genes were used for CodeML and BUSTED analyses. The file can be decompressed into 13 protein-editing gene files and these files can be opened using MEGA software.
DOI: 10.6084/m9.figshare.24791634.v1
title: Source data for the project entitled "Altered DNA methylation within DNMT3A, AHRR, LTA/TNF loci mediate the effect of smoking on inflammatory bowel disease"

description: In this study, we aim first to assess the association between cigarette smoking and the risk of IBD through a prospective cohort study in the UK Biobank. Then, we evaluate the potential causal association between smoking behaviors and smoking-related DNA methylation with IBD by performing MR analysis, and finally validate the associations via genome-wide methylation and colocalization analyses.These are the source data for Tables and Figures of the manuscript. Each one has been labed as "Source data for figure/table xxx". If you have any question about the datasets, please do not hesitate to contact us.
DOI: 10.5281/zenodo.10360428
title: Plagiarm The Study Investigates How R&D Can Mitigate The Influence Of A CEO'S Masculine Image On Leverage

description: Plagiarm The Study Investigates How R&D Can Mitigate The Influence Of A CEO'S Masculine Image On Leverage
DOI: 10.5281/zenodo.10360429
title: Plagiarm The Study Investigates How R&D Can Mitigate The Influence Of A CEO'S Masculine Image On Leverage

description: Plagiarm The Study Investigates How R&D Can Mitigate The Influence Of A CEO'S Masculine Image On Leverage
DOI: 10.6084/m9.figshare.24770919
title: Datasets of efficient isolation and long term storage of genomic DNA from the leaves of some tropical trees

description: Data of DNA quality, quantity and yield was provided. Data of Band percentage also provided separately.
DOI: 10.6084/m9.figshare.24770919.v3
title: Datasets of efficient isolation and long term storage of genomic DNA from the leaves of some tropical trees

description: Data of DNA quality, quantity and yield was provided. Data of Band percentage also provided separately.
DOI: 10.6084/m9.figshare.24770919.v2
title: Data obtained from Efficient isolation and long term storage of genomic DNA from the leaves of some tropical trees

description: Data of DNA quality, quantity and yield was provided. Data of Band percentage also provided separately.
DOI: 10.20372/aau_rdr/wkywgv/13u23y
title: S final.xls

description: :unav
DOI: 10.20372/aau_rdr/wkywgv/cc7b0x
title: AP final.xls

description: :unav
DOI: 10.20372/aau_rdr/wkywgv/vflvdd
title: Overall Index.xls

description: :unav
DOI: 10.20372/aau_rdr/wkywgv/zwe9xa
title: Stability final writing data.tab

description: :unav
DOI: 10.20372/aau_rdr/wkywgv/a6fwlb
title: Social Capital final writing data.tab

description: :unav
DOI: 10.20372/aau_rdr/wkywgv/dcowin
title: IFA final writing data.tab

description: :unav
DOI: 10.20372/aau_rdr/wkywgv/ibnth4
title: AC final.xls

description: :unav
DOI: 10.20372/aau_rdr/wkywgv/jacbxj
title: IFA final.xls

description: :unav
DOI: 10.20372/aau_rdr/wkywgv/nnwypa
title: SC final.xls

description: :unav
DOI: 10.20372/aau_rdr/wkywgv/osidrt
title: ABS final.xls

description: :unav
DOI: 10.20372/aau_rdr/wkywgv/mohh5a
title: Asset Possession final writing data.tab

description: :unav
DOI: 10.20372/aau_rdr/wkywgv/o76htp
title: ABS final writing data.tab

description: :unav
DOI: 10.20372/aau_rdr/wkywgv/pmxb0p
title: AC final writing data.tab

description: :unav
DOI: 10.20372/aau_rdr/wkywgv/r6miw2
title: Agri inp & tech final writing data.tab

description: :unav
DOI: 10.20372/aau_rdr/wkywgv/zxlpqx
title: ATA final.xls

description: :unav
DOI: 10.20372/aau_rdr/wkywgv
title: Rural Household Resilience to Food Insecurity in Majang Zone, Southwestern Ethiopia

description: The data is collected at the household level to measure resilience status and its determinants
DOI: 10.20372/aau_rdr/wkywgv/0etvrd
title: ORCID numbers of the authors.docx

description: :unav
DOI: 10.20372/aau_rdr/wkywgv/jcrilm
title: Questionnaires_FGD and KII guides.docx

description: :unav
DOI: 10.20372/aau_rdr/wkywgv/u2iygm
title: Overall Index.tab

description: :unav
DOI: 10.20372/aau_rdr/wkywgv/yfxe7q
title: Ethical Clearance Letter.pdf

description: :unav
DOI: 10.6084/m9.figshare.24792222
title: Additional file 1 of Metagenomic comparison of the faecal and environmental resistome on Irish commercial pig farms with and without zinc oxide and antimicrobial usage

description: Additional file 1: List of total MAGs and associated antimicrobial, heavy metal, and biocide resistance genes. The excel tables include sample IDs, binned MAGs per sample, taxonomic assignment, and found resistance genes on binned MAGs.
DOI: 10.6084/m9.figshare.24792222.v1
title: Additional file 1 of Metagenomic comparison of the faecal and environmental resistome on Irish commercial pig farms with and without zinc oxide and antimicrobial usage

description: Additional file 1: List of total MAGs and associated antimicrobial, heavy metal, and biocide resistance genes. The excel tables include sample IDs, binned MAGs per sample, taxonomic assignment, and found resistance genes on binned MAGs.
DOI: 10.26188/24562789
title: Austin Health OMOP Dataset

description: The Austin Health Dataset is an OMOP dataset based on records held at Austin Health.The data is derived from an Electronic Medical Records System held in Cerner.While the data is not open access, researchers can enquire about access subject to ethics and governance approvals.The dataset is based on Version 5.4 of the OMOP Common data model.Specifications of data model:https://ohdsi.github.io/CommonDataModel/cdm54.htmlCitation guidance here: https://ohdsi-australia.org/EMR2OMOP.html<br>Data custodian: Dr Graeme Hart, Melbourne University<br>
DOI: 10.26188/24562789.v1
title: Austin Health OMOP Dataset

description: The Austin Health Dataset is an OMOP dataset based on records held at Austin Health.The data is derived from an Electronic Medical Records System held in Cerner.While the data is not open access, researchers can enquire about access subject to ethics and governance approvals.The dataset is based on Version 5.4 of the OMOP Common data model.Specifications of data model: https://ohdsi.github.io/CommonDataModel/cdm54.html<br>Data custodian: Dr Graeme Hart, Melbourne University<br>
DOI: 10.26188/24562789.v2
title: Austin Health OMOP Dataset

description: The Austin Health Dataset is an OMOP dataset based on records held at Austin Health.The data is derived from an Electronic Medical Records System held in Cerner.While the data is not open access, researchers can enquire about access subject to ethics and governance approvals.The dataset is based on Version 5.4 of the OMOP Common data model.Specifications of data model:https://ohdsi.github.io/CommonDataModel/cdm54.htmlCitation guidance here: https://ohdsi-australia.org/EMR2OMOP.html<br>Data custodian: Dr Graeme Hart, Melbourne University<br>
DOI: 10.26188/19932020
title: Electronic Medical Records National Data Asset

description: Data from hospital Electronic Medical Record (EMR) Systems is being transformed to an international gold standard Observational Medical Outcomes Partnership (<b>OMOP</b>) Common Data Model (CDM).Tools, mappings and experience gained will be made openly available, and a community of practice and a roadmap for continued national implementation will be built. The Data Asset will significantly improve the quality, accessibility and feasibility of EMR data warehouses by streamlining data governance, consent and ethics. We will convert three existing data warehouses from Queensland Health, Austin Health and Western Health so that they can be accessed through a common interface. Learnings from the <b>Cerner</b> conversions will then be applied to the conversion of other data warehouse platforms including the <b>EPIC</b> EMR system which will be investigated in collaboration with the Peter MacCallum Cancer Centre and the Royal Childrens Hospital.The dataset is based on Version 5.4 of the OMOP Common data model.Specifications of data model:https://ohdsi.github.io/CommonDataModel/cdm54.htmlIntegrated Data Governance, Digital Health, and the Common Data Model (OMOP-CDM)DOI:10.21203/rs.3.rs-3479039/v1Citation guidance here: https://ohdsi-australia.org/EMR2OMOP.html<br>
DOI: 10.26188/19932020.v2
title: Electronic Medical Records National Data Asset

description: Data from hospital Electronic Medical Record (EMR) Systems is being transformed to an international gold standard Observational Medical Outcomes Partnership (<b>OMOP</b>) Common Data Model (CDM).Tools, mappings and experience gained will be made openly available, and a community of practice and a roadmap for continued national implementation will be built. The Data Asset will significantly improve the quality, accessibility and feasibility of EMR data warehouses by streamlining data governance, consent and ethics. We will convert three existing data warehouses from Queensland Health, Austin Health and Western Health so that they can be accessed through a common interface. Learnings from the <b>Cerner</b> conversions will then be applied to the conversion of other data warehouse platforms including the <b>EPIC</b> EMR system which will be investigated in collaboration with the Peter MacCallum Cancer Centre and the Royal Childrens Hospital.The dataset is based on Version 5.4 of the OMOP Common data model.Specifications of data model:https://ohdsi.github.io/CommonDataModel/cdm54.htmlIntegrated Data Governance, Digital Health, and the Common Data Model (OMOP-CDM)DOI:10.21203/rs.3.rs-3479039/v1Citation guidance here: https://ohdsi-australia.org/EMR2OMOP.html<br>