cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.11588/duerer.online.68b6e7973a40a
title: Scenen aus dem Leben Albrecht Dürers, https://d-nb.info/gnd/1281037109
DOI: 10.15468/dl.9rvhyc
title: Occurrence Download

description: A dataset containing 48897 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Oxalis perennans"
 ]
}

 The dataset includes 48897 records from 74 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0019154-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.30031528
title: A Meta Analysis of TOE Factors DrivingOrganizational Adoption of Artificial IntelligenceAcross Industries

description: Documents from the meta-analysis.
DOI: 10.6084/m9.figshare.30031528.v1
title: A Meta Analysis of TOE Factors DrivingOrganizational Adoption of Artificial IntelligenceAcross Industries

description: Documents from the meta-analysis.
DOI: 10.15468/dl.qfh6d7
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Baruna socialis"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0019161-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.28847492
title: Skill training synergistic muscles project

description: The aim of this project was to investigate if the short-term learning of a motor task is mediated by changes in the common synaptic inputs to motor neurons of synergistic muscles. Participants performed fifteen trials of a force-matching learning task, from which two trials were analyzed (pre-learning and post-learning). Motor units were decomposed from high-density surface electromyograms using this algorithm and tracked across trials. Motor unit discharge behavior and common synaptic oscillations across the delta, alpha, and beta bands were calculated and compared between pre- and post-learning.For further details, please refer to the <b>READ ME</b> file.
DOI: 10.6084/m9.figshare.28847492.v2
title: Skill training synergistic muscles project

description: The aim of this project was to investigate if the short-term learning of a motor task is mediated by changes in the common synaptic inputs to motor neurons of synergistic muscles. Participants performed fifteen trials of a force-matching learning task, from which two trials were analyzed (pre-learning and post-learning). Motor units were decomposed from high-density surface electromyograms using this algorithm and tracked across trials. Motor unit discharge behavior and common synaptic oscillations across the delta, alpha, and beta bands were calculated and compared between pre- and post-learning.For further details, please refer to the <b>READ ME</b> file.
DOI: 10.6084/m9.figshare.28847492.v1
title: Skill training synergistic muscles project

description: The aim of this project was to investigate if the short-term learning of a motor task is mediated by changes in the common synaptic inputs to motor neurons of synergistic muscles. Participants performed fifteen trials of a force-matching learning task, from which two trials were analyzed (pre-learning and post-learning). Motor units were decomposed from high-density surface electromyograms using this algorithm and tracked across trials. Motor unit discharge behavior and common synaptic oscillations across the delta, alpha, and beta bands were calculated and compared between pre- and post-learning.For further details, please refer to the <b>READ ME</b> file.
DOI: 10.15468/dl.t7ytxc
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is "
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0019162-250827131500795/datasets/export for details.
DOI: 10.5281/zenodo.15127714
title: Gene-specific substitution rates for the Vespertilionidae (Chiroptera: Mammalia) mitochondrial genome, with the description of three new mitogenomes

description: Data belonging to:
Borges, M. S., Salles, M. M. A., Oliveira, E. F., Magalhães, F. M., Silva, D. C., Oliveira, H. F. M., ... & Domingos, F. M. C. B. (2025). Gene-Specific Substitution Rates for the Vespertilionidae (Chiroptera: Mammalia) Mitochondrial Genome, with the Description of Three new Mitogenomes. Journal of Molecular Evolution, 1-10. https://doi.org/10.1007/s00239-025-10265-5

- annotation_data.xlsx: annotation details for the three newly described mitogenomes- *.fasta: alignment files for each newly described mitogenome- bats_mitogenome_mcc.tre: phylogenetic tree produced using BEAST- *.log: log files for each BEAST run- info-runs-beast.xlsx: detailed results for each BEAST run
DOI: 10.5281/zenodo.15039728
title: Gene-specific substitution rates for the Vespertilionidae (Chiroptera: Mammalia) mitochondrial genome, with the description of three new mitogenomes

description: Data belonging to:
Borges, M. S., Salles, M. M. A., Oliveira, E. F., Magalhães, F. M., Silva, D. C., Oliveira, H. F. M., ... & Domingos, F. M. C. B. (2025). Gene-Specific Substitution Rates for the Vespertilionidae (Chiroptera: Mammalia) Mitochondrial Genome, with the Description of Three new Mitogenomes. Journal of Molecular Evolution, 1-10. https://doi.org/10.1007/s00239-025-10265-5

- annotation_data.xlsx: annotation details for the three newly described mitogenomes- *.fasta: alignment files for each newly described mitogenome- bats_mitogenome_mcc.tre: phylogenetic tree produced using BEAST- *.log: log files for each BEAST run- info-runs-beast.xlsx: detailed results for each BEAST run
DOI: 10.5284/1135459
title: Digital Archive from an Archaeological Evaluation and Excavation at Sam's Lane, Blunsdon, Swindon, Wiltshire, 2018 - 2021

description: This collection comprises databases, reports, images, and GIS data from an archaeological evaluation and excavation at Sam's Lane, Blunsdon, Swindon, Wiltshire undertaken by Cotswold Archaeology in between September 2018 and February 2020. Two Late Iron Age crouched inhumations were recorded, and a Roman period cremation cemetery was uncovered.
DOI: 10.15468/dl.akz3ap
title: Occurrence Download

description: A dataset containing 5078 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Stephanomeria exigua"
 ]
}

 The dataset includes 5078 records from 143 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0019163-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.9fnyt9
title: Occurrence Download

description: A dataset containing 120978 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Boraginales",
 "Geometry POLYGON ((-17.62504 -34.81917, 51.13387 -34.81917, 51.13387 37.34999, -17.62504 37.34999, -17.62504 -34.81917))",
 "HasCoordinate is true"
 ]
}

 The dataset includes 120978 records from 416 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0019134-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17036977
title: Agentic RAG Red Teaming Bench v1.0.0

description: Snapshot matching the Hugging Face release. JSONL prompts, attacks, and evaluation artifacts. See Related identifiers for the canonical HF record.
DOI: 10.5281/zenodo.17036976
title: Agentic RAG Red Teaming Bench v1.0.0

description: Snapshot matching the Hugging Face release. JSONL prompts, attacks, and evaluation artifacts. See Related identifiers for the canonical HF record.
DOI: 10.15468/dl.hz6j3u
title: Occurrence Download

description: A dataset containing 400 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Stephanomeria elata"
 ]
}

 The dataset includes 400 records from 28 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0019165-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.adkk4d
title: Occurrence Download

description: A dataset containing 270 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Capparis spinosa ovata"
 ]
}

 The dataset includes 270 records from 34 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0019167-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17026/ar/kyrhkj
title: Archeologisch vooronderzoek plangebied ‘Europakwartier-Oost’ te IJsselstein, gemeente IJsselstein
title: Ruimtelijk advies op basis van inventariserend veldonderzoek door middel van boringen (verkennende fase)

description: IVO-O
DOI: 10.15468/dl.kxcxzt
title: Occurrence Download

description: A dataset containing 132 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Hoplostethus cadenati"
 ]
}

 The dataset includes 132 records from 19 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0019168-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.xmhz3t
title: Occurrence Download

description: A dataset containing 349056 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Falconiformes",
 "Country is Brazil",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 349056 records from 71 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0019113-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17035529
title: Data for Changning TRL location
DOI: 10.5281/zenodo.17035530
title: Data for Changning TRL location
DOI: 10.15468/dl.yqf8x7
title: Occurrence Download

description: A dataset containing 573523 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is France",
 "DatasetKey is Observation.org, Nature data from around the World",
 "TaxonKey is Lepidoptera"
 ]
}

 The dataset includes 573523 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0019159-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.26969014
title: code&data(CBA)_r2

description: The compressed <b>code&data(CBA)</b><b>_r2</b><b>.</b><b>zip</b> file contains 7.py files, 1.ipynb file and 3 folders.The <b>Main.ipynb </b>serves as the main file for the calculations, which provides step-by-step explanations and results for distributed execution.The remaining 5.py files are stored in the <b>lib folder</b>. <b>CBA.py</b> includes three functions, named Calculate accessibility, Calculate congestion, and Pareto_optimality. In the <b>Main.ipynb</b><b>(or Main.py)</b>, we use real data to call the functions from <b>CBA.py</b> to reproduce the main experimental part of the paper (Section 5). Additionally, we have incorporated <b>CSA.py</b> and <b>twoSFCA.py</b>, which represent the CSA model and 2SFCA model for comparison, allowing for a method comparison and analysis.The remaining four .py files are auxiliary to CBA.py:· <b>access_demo.py</b> defines an Access class that is primarily used to organize and manage demand, supply, and cost data, while providing various methods for calculating accessibility.· <b>fca.py</b> provides the concrete mathematical calculations and accessibility models, implementing the actual accessibility calculations by focusing on handling demand-supply data and calculating weighted accessibility.· The functions in <b>helpers.py</b> serve as auxiliary tools for the Access class in access_demo.py, mainly for handling and standardizing input data, as well as performing some additional calculations.· <b>weights.py</b> is mainly used to generate different distance or time weighting functions, which are applied in calculating weights for spatial accessibility models.The <b>data</b><b> folder</b> contains the three original csv files required for the calculations in this paper, including the demand points (<b>chi_demand.csv</b>), the supply points (<b>chi_supply.csv</b>), and the cost data (<b>chi_dist.csv</b>). To ensure data privacy and prevent potential data leakage, we processed the original data by removing sensitive spatial location information.·<b> </b><b>chi_demand.csv</b> stores the ID and population of each demand grid.· <b>chi_supply.csv</b> stores the ID and power (supply volume) of each charging station.· <b>chi_dist.csv</b> stores the travel time cost from each charging station to the demand grids.The <b>r</b><b>esult</b><b> folder</b> contains the results obtained by using the provided functions, with specific correspondences annotated in Main.ipynb.
DOI: 10.6084/m9.figshare.26969014.v2
title: code&data(CBA)_r2

description: The compressed <b>code&data(CBA)</b><b>_r2</b><b>.</b><b>zip</b> file contains 7.py files, 1.ipynb file and 3 folders.The <b>Main.ipynb </b>serves as the main file for the calculations, which provides step-by-step explanations and results for distributed execution.The remaining 5.py files are stored in the <b>lib folder</b>. <b>CBA.py</b> includes three functions, named Calculate accessibility, Calculate congestion, and Pareto_optimality. In the <b>Main.ipynb</b><b>(or Main.py)</b>, we use real data to call the functions from <b>CBA.py</b> to reproduce the main experimental part of the paper (Section 5). Additionally, we have incorporated <b>CSA.py</b> and <b>twoSFCA.py</b>, which represent the CSA model and 2SFCA model for comparison, allowing for a method comparison and analysis.The remaining four .py files are auxiliary to CBA.py:· <b>access_demo.py</b> defines an Access class that is primarily used to organize and manage demand, supply, and cost data, while providing various methods for calculating accessibility.· <b>fca.py</b> provides the concrete mathematical calculations and accessibility models, implementing the actual accessibility calculations by focusing on handling demand-supply data and calculating weighted accessibility.· The functions in <b>helpers.py</b> serve as auxiliary tools for the Access class in access_demo.py, mainly for handling and standardizing input data, as well as performing some additional calculations.· <b>weights.py</b> is mainly used to generate different distance or time weighting functions, which are applied in calculating weights for spatial accessibility models.The <b>data</b><b> folder</b> contains the three original csv files required for the calculations in this paper, including the demand points (<b>chi_demand.csv</b>), the supply points (<b>chi_supply.csv</b>), and the cost data (<b>chi_dist.csv</b>). To ensure data privacy and prevent potential data leakage, we processed the original data by removing sensitive spatial location information.·<b> </b><b>chi_demand.csv</b> stores the ID and population of each demand grid.· <b>chi_supply.csv</b> stores the ID and power (supply volume) of each charging station.· <b>chi_dist.csv</b> stores the travel time cost from each charging station to the demand grids.The <b>r</b><b>esult</b><b> folder</b> contains the results obtained by using the provided functions, with specific correspondences annotated in Main.ipynb.
DOI: 10.6084/m9.figshare.26969014.v1
title: code&data(CBA)_r1

description: The compressed <b>code&data(CBA)</b><b>_r1</b><b>.</b><b>zip</b> file contains 6.py files, 1.ipynb file, two folders and 9.csv files.<b>CBA.py</b> and <b>Main.ipynb</b><b>(or Main.py)</b> are the main files <b>CBA.py</b> includes three functions, named Calculate accessibility, Calculate congestion, and Pareto_optimality.In the <b>Main.ipynb</b><b>(or Main.py)</b>, we use real data to call the functions from <b>CBA.py</b> to reproduce the main experimental part of the paper (Section 5). The remaining four .py files are auxiliary to CBA.py:· <b>access_demo.py</b> defines an Access class that is primarily used to organize and manage demand, supply, and cost data, while providing various methods for calculating accessibility.· <b>fca.py</b> provides the concrete mathematical calculations and accessibility models, implementing the actual accessibility calculations by focusing on handling demand-supply data and calculating weighted accessibility.· The functions in <b>helpers.py</b> serve as auxiliary tools for the Access class in access_demo.py, mainly for handling and standardizing input data, as well as performing some additional calculations.· <b>weights.py</b> is mainly used to generate different distance or time weighting functions, which are applied in calculating weights for spatial accessibility models.<br>The <b>data</b><b> folder</b> contains the three original csv files required for the calculations in this paper, including the demand points (<b>chi_demand.csv</b>), the supply points (<b>chi_supply.csv</b>), and the cost data (<b>chi_dist.csv</b>). To ensure data privacy and prevent potential data leakage, we processed the original data by removing sensitive spatial location information.·<b> </b><b>chi_demand.csv</b> stores the ID and population of each demand grid.· <b>chi_supply.csv</b> stores the ID and power (supply volume) of each charging station.· <b>chi_dist.csv</b> stores the travel time cost from each charging station to the demand grids.The <b>r</b><b>esult</b><b> folder</b> contains the results obtained by using the provided functions, with specific correspondences annotated in Main.ipynb.
DOI: 10.15468/dl.mdc6cg
title: Occurrence Download

description: A dataset containing 98360 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is SWG Coastal and marine invertebrate observations"
 ]
}

 The dataset includes 98360 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0019166-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57967/hf/6395
title: agentic-rag-redteam-bench
DOI: 10.15468/dl.rn46ky
title: Occurrence Download

description: A dataset containing 13017 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Poa pilosa tenuis, Poa plumosa, Poa poiretii, Poa punctata, Poa senegalensis, Poa tenella, Poa tenella, Poa tenuiflora, Poa verticillata, Eragrostis multicaulis, Eragrostis damiensiana, Eragrostis damiensiana, Eragrostis damiensiana condensata, Eragrostis damiensiana condensata, Eragrostis feroliniana, Eragrostis insconsicua, Eragrostis insconsicua, Eragrostis niwahokori, Eragrostis peregrina, Eragrostis pilosa multicaulis, Eragrostis pilosa condensata, Eragrostis pilosa damiensiana, Eragrostis pilosa damiensiana, Eragrostis pilosa multicaulis, Eragrostis pilosa condensata, Eragrostis pilosa condensata, Eragrostis pilosa damiensiana, Eragrostis pilosa nana, Eragrostis pulchra, Glyceria airoides, Poa suzumeokatabica, Eragrostis cilianensis, Briza caroliniana, Briza eragrostis, Briza eragrostis megastachya, Briza major, Briza major, Briza megastachya, Briza megastachya, Briza megastachya, Briza oblonga, Briza purpurascens, Calotheca purpurascens, Eragrostis argentina, Eragrostis articulata, Eragrostis articulata, Eragrostis cilianensis, Eragrostis cilianensis, Eragrostis cilianensis leersioides, Eragrostis cilianensis megastachya)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen, Machine Observation)"
 ]
 }
 },
 "Continent is Europe",
 "Year is greater than or equal to 1980",
 "Year is less than or equal to 2024"
 ]
}

 The dataset includes 13017 records from 220 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0019171-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.48597/mgg2-excu
title: Aerosol light scattering at Appalachian State University, Boone (NC)

description: Measurement of Aerosol light scattering at Appalachian State University, Boone (NC)
DOI: 10.48597/nnzf-jy55
title: Aerosol light scattering at Appalachian State University, Boone (NC)

description: Measurement of Aerosol light scattering at Appalachian State University, Boone (NC)
DOI: 10.48597/nrez-7mhf
title: Aerosol_absorption_coefficient at Appalachian State University, Boone (NC)

description: Measurement of Aerosol_absorption_coefficient at Appalachian State University, Boone (NC)
DOI: 10.48597/nsq3-gcz2
title: Pressure at Barrow

description: Measurement of Pressure at Barrow
DOI: 10.48597/pk3m-6fn4
title: Aerosol light scattering at Appalachian State University, Boone (NC)

description: Measurement of Aerosol light scattering at Appalachian State University, Boone (NC)
DOI: 10.48597/pkun-bjjb
title: Particle_number_size_distribution at Pallas (Sammaltunturi)

description: Measurement of Particle_number_size_distribution at Pallas (Sammaltunturi)
DOI: 10.48597/pqqk-ue98
title: Aerosol light scattering at Appalachian State University, Boone (NC)

description: Measurement of Aerosol light scattering at Appalachian State University, Boone (NC)
DOI: 10.48597/pwr4-mnrb
title: Particle_number_size_distribution at Pallas (Sammaltunturi)

description: Measurement of Particle_number_size_distribution at Pallas (Sammaltunturi)
DOI: 10.48597/q43c-kktv
title: Particle_number_size_distribution at Pallas (Sammaltunturi)

description: Measurement of Particle_number_size_distribution at Pallas (Sammaltunturi)
DOI: 10.48597/qd9t-exu8
title: Particle_number_size_distribution at Pallas (Sammaltunturi)

description: Measurement of Particle_number_size_distribution at Pallas (Sammaltunturi)
DOI: 10.34740/kaggle/dsv/7743415
title: ⏳ endoflife.date database (duckdb)
DOI: 10.48597/qsfy-k727
title: Particle_number_size_distribution at Pallas (Sammaltunturi)

description: Measurement of Particle_number_size_distribution at Pallas (Sammaltunturi)
DOI: 10.48597/r4sz-6mu9
title: Aerosol light scattering at Appalachian State University, Boone (NC)

description: Measurement of Aerosol light scattering at Appalachian State University, Boone (NC)
DOI: 10.48597/r5e9-cmz5
title: Aerosol light scattering at Appalachian State University, Boone (NC)

description: Measurement of Aerosol light scattering at Appalachian State University, Boone (NC)
DOI: 10.48597/r5wy-369c
title: Aerosol light scattering at Appalachian State University, Boone (NC)

description: Measurement of Aerosol light scattering at Appalachian State University, Boone (NC)
DOI: 10.48597/rwyu-vf2t
title: Particle_number_size_distribution at Pallas (Sammaltunturi)

description: Measurement of Particle_number_size_distribution at Pallas (Sammaltunturi)
DOI: 10.48597/rx3b-jrvu
title: Particle_number_size_distribution at Pallas (Sammaltunturi)

description: Measurement of Particle_number_size_distribution at Pallas (Sammaltunturi)
DOI: 10.48597/s5ph-gjvz
title: Particle_number_size_distribution at Pallas (Sammaltunturi)

description: Measurement of Particle_number_size_distribution at Pallas (Sammaltunturi)
DOI: 10.48597/s6pn-ch3f
title: Temperature at Barrow

description: Measurement of Temperature at Barrow
DOI: 10.48597/tezm-p5av
title: Aerosol light scattering at Appalachian State University, Boone (NC)

description: Measurement of Aerosol light scattering at Appalachian State University, Boone (NC)
DOI: 10.48597/ts3y-re8x
title: Particle_number_size_distribution at Pallas (Sammaltunturi)

description: Measurement of Particle_number_size_distribution at Pallas (Sammaltunturi)