cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.34740/kaggle/dsv/4810185
title: TI-AWR-6843-AOP Gesture Language Data
DOI: 10.6084/m9.figshare.21818442
title: The genome of Cynoglossus semilaevis

description: The genome optimization of Cynoglossus semilaevis
DOI: 10.6084/m9.figshare.21818442.v1
title: The genome of Cynoglossus semilaevis

description: The genome optimization of Cynoglossus semilaevis
DOI: 10.6084/m9.figshare.21639635
title: test

description: A typical dataset which consists of 16 instances ranging from 5 operating rooms with 40 cases to 30 operating rooms with 240 cases .
DOI: 10.6084/m9.figshare.21639635.v6
title: test

description: A typical dataset which consists of 16 instances ranging from 5 operating rooms with 40 cases to 30 operating rooms with 240 cases .
DOI: 10.6084/m9.figshare.21639635.v5
title: SCAP with laminar flow operating room

description: A typical dataset which consists of 16 instances ranging from 5 operating rooms with 40 cases to 30 operating rooms with 240 cases .
DOI: 10.25919/k41n-je66
title: Parkes observations for project P1101 semester 2022OCTS_10

description: We propose to carry out fortnightly monitoring of a very active repeater, FRB~190520, with the Parkes UWL system. Our current observations show that FRB~190520 is not only the most active FRB that can be observed with Parkes, but also shows extreme rotation measure (RM) variations and unique behavior at 2 to 3 GHz frequency. This makes UWL the ideal instrument to carry out in-depth studies of this repeating FRB. With this program, we expect to detect a large sample of bursts from FRB~190520, and in collaboration with the FAST telescope, we will study the local environment, emission properties, fluence distributions, and polarisation properties over an extremely wide bandwidth with high sensitivity.
DOI: 10.6084/m9.figshare.21820026
title: SCAP-MLOR

description: A typical dataset consists of 16 instances ranging from 5 ORs with 40 cases to 30 ORs with 240 cases.
DOI: 10.6084/m9.figshare.21820026.v1
title: SCAP-MLOR

description: A typical dataset consists of 16 instances ranging from 5 ORs with 40 cases to 30 ORs with 240 cases.
DOI: 10.6084/m9.figshare.21804048.v1
title: Supplementary materials: Feeding spent hemp biomass to lactating dairy cows: effects on performance, nitrogen metabolism, milk components and quality, methane emission, and blood parameters

description: This is a supplementary materials for a manuscript titled "<strong>Feeding spent hemp biomass to lactating dairy cows: effects on performance, nitrogen metabolism, milk components and quality, methane emission, and blood parameters", </strong>submitted to Journal of Dairy Science.
DOI: 10.6084/m9.figshare.21804048.v2
title: Supplementary materials: Feeding spent hemp biomass to lactating dairy cows: effects on performance, nitrogen metabolism, milk components and quality, methane emission, and blood parameters

description: Spent hemp biomass (SHB) is the byproduct of the extraction of cannabidiol from industrial hemp (hemp). Despite its excellent nutritional value SHB is still illegal to feed it to food-producing animals. Assessing the effects of including SHB in the ration on lactational performance and animal health is one of the critical steps to implementing SHB as a feed for dairy cows. Our study revealed a low palatability of SHB but no effect on overall performance; we observed minor effects on inflammation and metabolic status of the animals and no effect on nitrogen metabolism or enteric methane emission. Our findings suggest that overall, SHB is likely a safe feedstuff for dairy cows.
DOI: 10.5281/zenodo.4015559
title: wild_expression: gene expression data on wildlife hosts of emerging infectious diseases

description: Publicly accessible data and code supporting the manuscript: "Host gene expression in wildlife disease: making sense of species-level responses"
DOI: 10.5281/zenodo.4015560
title: wild_expression: gene expression data on wildlife hosts of emerging infectious diseases

description: Publicly accessible data and code supporting the manuscript: "Host gene expression responses in wildlife disease: making sense of 'null' results"
DOI: 10.5281/zenodo.4606961
title: wild_expression: gene expression data on wildlife hosts of emerging infectious diseases

description: Publicly accessible data and code supporting the manuscript: "Host gene expression in wildlife disease: making sense of species-level responses"
DOI: 10.5281/zenodo.5204652
title: wild_expression: gene expression data on wildlife hosts of emerging infectious diseases

description: Publicly accessible data and code supporting the manuscript: "Host gene expression in wildlife disease: making sense of species-level responses"
DOI: 10.5281/zenodo.5120932
title: Supporting code and data for REBA (Rapid EOO-Based Assessment)

description: Shared here are code and data to support the manuscript: "Using publicly available data to conduct rapid assessments of extinction risk." Raw data (North American plant occurrence records) were harvested from GBIF using the R package <strong>rgbif</strong>. Subsequent data manipulation, cleaning, and statistical modeling was conducted using the codebase documented by the project GitHub repository, which is also archived here. <strong>plant_rapid_assessment-v1.1.0.zip</strong>: An archived version of the GitHub repository files, including most project data, analysis code, and relevant outputs. <strong>gbif_data.zip</strong>: This ZIP archive contains the key project data files that are <strong>not</strong> uploaded to the GitHub repository (because of file size considerations). Once decompressed, contains a "gbif_occurrences" subdirectory, which holds all raw GBIF occurrence records for each species queried, and a "gbif_cleaned" subdirectory, which holds the cleaned, derived GBIF occurrence record dataset (for all species). Note that the directory is ~13 GB decompressed.
DOI: 10.5281/zenodo.5120933
title: Supporting code and data for REBA (Rapid EOO-Based Assessment)

description: Mistaken incomplete upload that did not include data files external to the GitHub repository.
DOI: 10.5281/zenodo.5120938
title: Supporting code and data for REBA (Rapid EOO-Based Assessment)

description: Shared here are code and data to support the manuscript: "Using publicly available data to conduct rapid assessments of extinction risk." Raw data (North American plant occurrence records) were harvested from GBIF using the R package <strong>rgbif</strong>. Subsequent data manipulation, cleaning, and statistical modeling was conducted using the codebase documented by the project GitHub repository, which is also archived here. <strong>eveskew/plant_rapid_assessment-v1.0.0.zip</strong>: An archived version of the GitHub repository files, including most project data, analysis code, and relevant outputs. <strong>gbif_data.zip</strong>: This ZIP archive contains the key project data files that are <strong>not</strong> uploaded to the GitHub repository (because of file size considerations). Once decompressed, contains a "gbif_occurrences" subdirectory, which holds all raw GBIF occurrence records for each species queried, and a "gbif_cleaned" subdirectory, which holds the cleaned, derived GBIF occurrence record dataset (for all species). Note that the directory is ~13 GB decompressed.
DOI: 10.5281/zenodo.5781324
title: Supporting code and data for REBA (Rapid EOO-Based Assessment)

description: Shared here are code and data to support the manuscript: "Using publicly available data to conduct rapid assessments of extinction risk." Raw data (North American plant occurrence records) were harvested from GBIF using the R package <strong>rgbif</strong>. Subsequent data manipulation, cleaning, and statistical modeling was conducted using the codebase documented by the project GitHub repository, which is also archived here. <strong>plant_rapid_assessment-v1.1.0.zip</strong>: An archived version of the GitHub repository files, including most project data, analysis code, and relevant outputs. <strong>gbif_data.zip</strong>: This ZIP archive contains the key project data files that are <strong>not</strong> uploaded to the GitHub repository (because of file size considerations). Once decompressed, contains a "gbif_occurrences" subdirectory, which holds all raw GBIF occurrence records for each species queried, and a "gbif_cleaned" subdirectory, which holds the cleaned, derived GBIF occurrence record dataset (for all species). Note that the directory is ~13 GB decompressed.
DOI: 10.6084/m9.figshare.21814705.v1
title: Electronic Supplementary Material 2 from Age-dependent genetic variation in aggression

description: Supplementary Tables and Graphs
DOI: 10.6084/m9.figshare.21814705
title: Electronic Supplementary Material 2 from Age-dependent genetic variation in aggression

description: Supplementary Tables and Graphs
DOI: 10.20372/eiar-rdm/qvr22b/h1eoik
title: SARI_NPKS_crop response dataset.tab

description: :unav
DOI: 10.20372/eiar-rdm/qvr22b
title: SARI_NPKS_crop response dataset

description: Although soil and agronomy data collection in Ethiopia has begun over 60 years ago, the data are hardly accessible as they are scattered across different organizations, mostly held in the hands of individuals (Ashenafi et al.,2020; Tamene et al.,2022), which makes them vulnerable to permanent loss. Cognizant of the problem, the Coalition of the Willing (CoW) for data sharing and access was created in 2018 with joint support and coordination of the Alliance Bioversity-CIAT and GIZ (https://www.ethioagridata.com/index.html). Mobilizing its members, the CoW has embarked on data rescue operations including data ecosystem mapping, collation, and curation of the legacy data, which was put into the central data repository for its members and the wider data user’s community according to the guideline developed based on the FAIR data principles and approved by the CoW. So far, CoW managed to collate and rescue about 20,000 legacy soil profile data and over 38,000 crop responses to fertilizer data (Tamene et al.,2022). The crop response dataset (N=1,686 observations) is extracted, transformed, and uploaded into a harmonized template, consisting of 76 variables. SARI NPKS crop response data. Reference: Ashenafi, A., Tamene, L., and Erkossa, T. 2020. Identifying, Cataloguing, and Mapping Soil and Agronomic Data in Ethiopia. CIAT Publication No. 506. International Center for Tropical Agriculture (CIAT). Addis Ababa, Ethiopia. 42 p. 10.13140/RG.2.2.31759.41123. Tamene L; Erkossa T; Tafesse T; Abera W; Schultz S. 2021. A coalition of the Willing - Powering data-driven solutions for Ethiopian Agriculture. CIAT Publication No. 518. International Center for Tropical Agriculture (CIAT). Addis Ababa, Ethiopia. 34 p. https://www.ethioagridata.com/Resources/Powering%20Data-Driven%20Solutions%20for%20Ethiopian%20Agriculture.pdf. The Coalition of the Willing (CoW) website: https://www.ethioagridata.com/index.html. TERMS: Access to the data is limited to the CoW members until the national soil and agronomy data-sharing directive of MoA is registered by the Ministry of Justice and released for implementation. DISCLAIMER: The dataset populated in the harmonized template consisting of 76 variables is extracted, transformed, and uploaded from the source document by the CoW. Hence, if any irregularities are observed, the data users have referred to the source document uploaded along with the dataset. Use of the dataset and any consequences arising from using it is the user’s sole responsibility.
DOI: 10.20372/eiar-rdm/4imwzg/hvfahx
title: OARI_NPKS_crop response dataset.tab

description: :unav
DOI: 10.20372/eiar-rdm/4imwzg
title: Oromia Agricultural Research Institute (OARI) NPKS crop response dataset

description: Although soil and agronomy data collection in Ethiopia has begun over 60 years ago, the data are hardly accessible as they are scattered across different organizations, mostly held in the hands of individuals (Ashenafi et al.,2020; Tamene et al.,2022), which makes them vulnerable to permanent loss. Cognizant of the problem, the Coalition of the Willing (CoW) for data sharing and access was created in 2018 with joint support and coordination of the Alliance Bioversity-CIAT and GIZ (https://www.ethioagridata.com/index.html). Mobilizing its members, the CoW has embarked on data rescue operations including data ecosystem mapping, collation, and curation of the legacy data, which was put into the central data repository for its members and the wider data user’s community according to the guideline developed based on the FAIR data principles and approved by the CoW. So far, CoW managed to collate and rescue about 20,000 legacy soil profile data and over 38,000 crop responses to fertilizer data (Tamene et al.,2022). The crop response dataset (N=1416 observations) is extracted, transformed, and uploaded into a harmonized template, consisting of 76 variables. Oromia Agricultural Research Institute (OARI) crop response dataset. Reference: Ashenafi, A., Tamene, L., and Erkossa, T. 2020. Identifying, Cataloguing, and Mapping Soil and Agronomic Data in Ethiopia. CIAT Publication No. 506. International Center for Tropical Agriculture (CIAT). Addis Ababa, Ethiopia. 42 p. 10.13140/RG.2.2.31759.41123. Tamene L; Erkossa T; Tafesse T; Abera W; Schultz S. 2021. A coalition of the Willing - Powering data-driven solutions for Ethiopian Agriculture. CIAT Publication No. 518. International Center for Tropical Agriculture (CIAT). Addis Ababa, Ethiopia. 34 p. https://www.ethioagridata.com/Resources/Powering%20Data-Driven%20Solutions%20for%20Ethiopian%20Agriculture.pdf. The Coalition of the Willing (CoW) website: https://www.ethioagridata.com/index.html. TERMS: Access to the data is limited to the CoW members until the national soil and agronomy data-sharing directive of MoA is registered by the Ministry of Justice and released for implementation. DISCLAIMER: The dataset populated in the harmonized template consisting of 76 variables is extracted, transformed, and uploaded from the source document by the CoW. Hence, if any irregularities are observed, the data users have referred to the source document uploaded along with the dataset. Use of the dataset and any consequences arising from using it is the user’s sole responsibility.
DOI: 10.20372/eiar-rdm/ftckt8/ge5bfr
title: ICRISAT_AfricaRising crop response dataset.tab

description: :unav
DOI: 10.20372/eiar-rdm/ftckt8
title: ICRISAT_Africa Rising crop response dataset

description: Although soil and agronomy data collection in Ethiopia has begun over 60 years ago, the data are hardly accessible as they are scattered across different organizations, mostly held in the hands of individuals (Ashenafi et al.,2020; Tamene et al.,2022), which makes them vulnerable to permanent loss. Cognizant of the problem, the Coalition of the Willing (CoW) for data sharing and access was created in 2018 with joint support and coordination of the Alliance Bioversity-CIAT and GIZ (https://www.ethioagridata.com/index.html). Mobilizing its members, the CoW has embarked on data rescue operations including data ecosystem mapping, collation, and curation of the legacy data, which was put into the central data repository for its members and the wider data user’s community according to the guideline developed based on the FAIR data principles and approved by the CoW. So far, CoW managed to collate and rescue about 20,000 legacy soil profile data and over 38,000 crop responses to fertilizer data (Tamene et al.,2022). The crop response dataset (N=5,517 observations) is extracted, transformed, and uploaded into a harmonized template, consisting of 76 variables. ICRISAT_Africa Rising crop response dataset. Reference: Ashenafi, A., Tamene, L., and Erkossa, T. 2020. Identifying, Cataloguing, and Mapping Soil and Agronomic Data in Ethiopia. CIAT Publication No. 506. International Center for Tropical Agriculture (CIAT). Addis Ababa, Ethiopia. 42 p. 10.13140/RG.2.2.31759.41123. Tamene L; Erkossa T; Tafesse T; Abera W; Schultz S. 2021. A coalition of the Willing - Powering data-driven solutions for Ethiopian Agriculture. CIAT Publication No. 518. International Center for Tropical Agriculture (CIAT). Addis Ababa, Ethiopia. 34 p. https://www.ethioagridata.com/Resources/Powering%20Data-Driven%20Solutions%20for%20Ethiopian%20Agriculture.pdf. The Coalition of the Willing (CoW) website: https://www.ethioagridata.com/index.html. TERMS: Access to the data is limited to the CoW members until the national soil and agronomy data-sharing directive of MoA is registered by the Ministry of Justice and released for implementation. DISCLAIMER: The dataset populated in the harmonized template consisting of 76 variables is extracted, transformed, and uploaded from the source document by the CoW. Hence, if any irregularities are observed, the data users have referred to the source document uploaded along with the dataset. Use of the dataset and any consequences arising from using it is the user’s sole responsibility.
DOI: 10.20372/eiar-rdm/9yaiis/wrcwib
title: GIZ_ISFM_crop response dataset.tab

description: :unav
DOI: 10.20372/eiar-rdm/vfxiws/carcqg
title: ATA_balanced fertilizer_crop response dataset.xlsx

description: :unav
DOI: 10.20372/eiar-rdm/vfxiws
title: ATA_balanced fertilizer_crop response dataset

description: Although soil and agronomy data collection in Ethiopia has begun over 60 years ago, the data are hardly accessible as they are scattered across different organizations, mostly held in the hands of individuals (Ashenafi et al.,2020; Tamene et al.,2022), which makes them vulnerable to permanent loss. Cognizant of the problem, the Coalition of the Willing (CoW) for data sharing and access was created in 2018 with joint support and coordination of the Alliance Bioversity-CIAT and GIZ (https://www.ethioagridata.com/index.html). Mobilizing its members, the CoW has embarked on data rescue operations including data ecosystem mapping, collation, and curation of the legacy data, which was put into the central data repository for its members and the wider data user’s community according to the guideline developed based on the FAIR data principles and approved by the CoW. So far, CoW managed to collate and rescue about 20,000 legacy soil profile data and over 38,000 crop responses to fertilizer data (Tamene et al.,2022). The crop response dataset (N=886 observations) is extracted, transformed, and uploaded into a harmonized template, consisting of 76 variables. Agricultural Transformation Agency (ATA) balanced fertilizer trial data. Reference: Ashenafi, A., Tamene, L., and Erkossa, T. 2020. Identifying, Cataloguing, and Mapping Soil and Agronomic Data in Ethiopia. CIAT Publication No. 506. International Center for Tropical Agriculture (CIAT). Addis Ababa, Ethiopia. 42 p. 10.13140/RG.2.2.31759.41123. Tamene L; Erkossa T; Tafesse T; Abera W; Schultz S. 2021. A coalition of the Willing - Powering data-driven solutions for Ethiopian Agriculture. CIAT Publication No. 518. International Center for Tropical Agriculture (CIAT). Addis Ababa, Ethiopia. 34 p. https://www.ethioagridata.com/Resources/Powering%20Data-Driven%20Solutions%20for%20Ethiopian%20Agriculture.pdf. The Coalition of the Willing (CoW) website: https://www.ethioagridata.com/index.html. TERMS: Access to the data is limited to the CoW members until the national soil and agronomy data-sharing directive of MoA is registered by the Ministry of Justice and released for implementation. DISCLAIMER: The dataset populated in the harmonized template consisting of 76 variables is extracted, transformed, and uploaded from the source document by the CoW. Hence, if any irregularities are observed, the data users have referred to the source document uploaded along with the dataset. Use of the dataset and any consequences arising from using it is the user’s sole responsibility.
DOI: 10.20372/eiar-rdm/ztvv17
title: ARARI NPKS crop response dataset

description: Although soil and agronomy data collection in Ethiopia has begun over 60 years ago, the data are hardly accessible as they are scattered across different organizations, mostly held in the hands of individuals (Ashenafi et al.,2020; Tamene et al.,2022), which makes them vulnerable to permanent loss. Cognizant of the problem, the Coalition of the Willing (CoW) for data sharing and access was created in 2018 with joint support and coordination of the Alliance Bioversity-CIAT and GIZ (https://www.ethioagridata.com/index.html). Mobilizing its members, the CoW has embarked on data rescue operations including data ecosystem mapping, collation, and curation of the legacy data, which was put into the central data repository for its members and the wider data user’s community according to the guideline developed based on the FAIR data principles and approved by the CoW. So far, CoW managed to collate and rescue about 20,000 legacy soil profile data and over 38,000 crop responses to fertilizer data (Tamene et al.,2022). The crop response dataset (N=432 observations) is extracted, transformed, and uploaded into a harmonized template, consisting of 76 variables. ARARI NPKS crop response data. Reference: Ashenafi, A., Tamene, L., and Erkossa, T. 2020. Identifying, Cataloguing, and Mapping Soil and Agronomic Data in Ethiopia. CIAT Publication No. 506. International Center for Tropical Agriculture (CIAT). Addis Ababa, Ethiopia. 42 p. 10.13140/RG.2.2.31759.41123. Tamene L; Erkossa T; Tafesse T; Abera W; Schultz S. 2021. A coalition of the Willing - Powering data-driven solutions for Ethiopian Agriculture. CIAT Publication No. 518. International Center for Tropical Agriculture (CIAT). Addis Ababa, Ethiopia. 34 p. https://www.ethioagridata.com/Resources/Powering%20Data-Driven%20Solutions%20for%20Ethiopian%20Agriculture.pdf. The Coalition of the Willing (CoW) website: https://www.ethioagridata.com/index.html. TERMS: Access to the data is limited to the CoW members until the national soil and agronomy data-sharing directive of MoA is registered by the Ministry of Justice and released for implementation. DISCLAIMER: The dataset populated in the harmonized template consisting of 76 variables is extracted, transformed, and uploaded from the source document by the CoW. Hence, if any irregularities are observed, the data users have referred to the source document uploaded along with the dataset. Use of the dataset and any consequences arising from using it is the user’s sole responsibility.
DOI: 10.20372/eiar-rdm/ztvv17/b6ydtt
title: ARARI NPKS crop response dataset.tab

description: :unav
DOI: 10.6084/m9.figshare.21820103
title: datasets.rar from Sensitivity analysis of large body of control parameters in machine learning control of a square-back Ahmed body

description: Active drag reduction (DR) of a square-back Ahmed body is experimentally studied based on machine learning or artificial intelligence (AI) control. The control system consists of four independently operated arrays of pulsed microjets, 25 pressure taps and an explorative downhill simplex method controller. Two strategies, i.e. asymmetric and symmetric actuations, are investigated, with 12 and 9 control parameters, respectively. Both achieve a DR by 13%, though with distinct flow physics and control mechanisms behind. A model linking the control parameters with the cost is developed based on Taylor expansion around the K-nearest neighbours of the smallest cost obtained from the AI control, resulting in a substantially reduced deviation between measured and predicted costs, especially when involving a large number of control parameters, compared with that based on Taylor expansion around the optimum cost. Sensitivity analysis, conducted based on the model, indicates that the control efficiency, i.e. the ratio of the power saving from DR to the total power consumption, may reach 55 and 78 for the symmetric and asymmetric strategies, respectively, given a 1–2% sacrifice on DR. This efficiency greatly exceeds that (26.5) obtained by Fan <i>et al</i>. (Fan et al. 2020 <i>Phys. Fluids</i> <b>32</b>, 125117. (doi:10.1063/5.0033156)), whose independent control parameters are only three.