cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.22897118
title: Snow survey 25.01.2023, Akkayin district, North Kazakhstan region

description: This shapefile contains results of the field snow survey from the territory of LLP "North Kazakhstan agricultural experimental station" located in the North Kazakhstan Region, Kazakhstan from 25.01.2023. <br> Snow thickness was measured with a metal ruler with a 1-mm scale and the density of snow was calculated with the use of the weight snow gauge VS-43M. The actual snow density (ρ) was calculated from the mass (m) of snow, the snow depth (SD) and the area of the VS-43М weight snow gauge cylinder (S).
DOI: 10.6084/m9.figshare.22897118.v1
title: Snow survey 25.01.2023, Akkayin district, North Kazakhstan region

description: This shapefile contains results of the field snow survey from the territory of LLP "North Kazakhstan agricultural experimental station" located in the North Kazakhstan Region, Kazakhstan from 25.01.2023. <br> Snow thickness was measured with a metal ruler with a 1-mm scale and the density of snow was calculated with the use of the weight snow gauge VS-43M. The actual snow density (ρ) was calculated from the mass (m) of snow, the snow depth (SD) and the area of the VS-43М weight snow gauge cylinder (S).
DOI: 10.6084/m9.figshare.22897205
title: Snow survey 25.02.2023, Akkayin district, North Kazakhstan region

description: This shapefile contains results of the field snow survey from the territory of LLP "North Kazakhstan agricultural experimental station" located in the North Kazakhstan Region, Kazakhstan from 25.02.2023. <br> Snow thickness was measured with a metal ruler with a 1-mm scale and the density of snow was calculated with the use of the weight snow gauge VS-43M. The actual snow density (ρ) was calculated from the mass (m) of snow, the snow depth (SD) and the area of the VS-43М weight snow gauge cylinder (S).
DOI: 10.6084/m9.figshare.22897205.v1
title: Snow survey 25.02.2023, Akkayin district, North Kazakhstan region

description: This shapefile contains results of the field snow survey from the territory of LLP "North Kazakhstan agricultural experimental station" located in the North Kazakhstan Region, Kazakhstan from 25.02.2023. <br> Snow thickness was measured with a metal ruler with a 1-mm scale and the density of snow was calculated with the use of the weight snow gauge VS-43M. The actual snow density (ρ) was calculated from the mass (m) of snow, the snow depth (SD) and the area of the VS-43М weight snow gauge cylinder (S).
DOI: 10.6084/m9.figshare.22762094
title: Data from: Trophic niche segregation in a guild of top predators within the Mediterranean basin.

description: Diet data used for the analyses of trophic niche partitioning among three species of owls living in sympatry across the Mediterranean Basin. <strong>Location:</strong> Mediterranean biodiversity hotspot. <strong>Taxon:</strong> Northern long-eared owl (<em>Asio</em> <em>otus</em>), Tawny owl (<em>Strix aluco</em>), Eurasian eagle owl (<em>Bubo bubo</em>).
DOI: 10.6084/m9.figshare.22762094.v1
title: Data from: Trophic niche segregation in a guild of top predators within the Mediterranean basin.

description: Diet data used for the analyses of trophic niche partitioning among three species of owls living in sympatry across the Mediterranean Basin. <strong>Location:</strong> Mediterranean biodiversity hotspot. <strong>Taxon:</strong> Northern long-eared owl (<em>Asio</em> <em>otus</em>), Tawny owl (<em>Strix aluco</em>), Eurasian eagle owl (<em>Bubo bubo</em>).
DOI: 10.6084/m9.figshare.22762094.v2
title: Data from: Trophic niche segregation in a guild of top predators within the Mediterranean basin.

description: Diet data used for the analyses of trophic niche partitioning among three species of owls living in sympatry across the Mediterranean Basin. <strong>Location:</strong> Mediterranean biodiversity hotspot. <strong>Taxon:</strong> Northern long-eared owl (<em>Asio</em> <em>otus</em>), Tawny owl (<em>Strix aluco</em>), Eurasian eagle owl (<em>Bubo bubo</em>).
DOI: 10.6084/m9.figshare.22879004
title: fasta files

description: fasta files of 149 assembled genomes Neisseria meningitidis collected from Suzhou
DOI: 10.6084/m9.figshare.22879004.v1
title: fasta files

description: fasta files of 149 assembled genomes Neisseria meningitidis collected from Suzhou
DOI: 10.6084/m9.figshare.22897406
title: gbk files

description: gbk files of 149 assembled genomes Neisseria meningitidis collected from Suzhou
DOI: 10.6084/m9.figshare.22897613
title: <strong>Gene flow, mating patterns and inbreeding depression in </strong><em>Roupala montana</em><strong> var. </strong><em>brasiliensis</em><strong>, a neotropical timber species</strong>

description: Phenotypic and Genotypic data. Data are from a progeny test and from field collected material as well as 9 SSR loci.
DOI: 10.6084/m9.figshare.22897613.v1
title: <strong>Gene flow, mating patterns and inbreeding depression in </strong><em>Roupala montana</em><strong> var. </strong><em>brasiliensis</em><strong>, a neotropical timber species</strong>

description: Phenotypic and Genotypic data. Data are from a progeny test and from field collected material as well as 9 SSR loci.
DOI: 10.25345/c5zk55x1m
title: MassIVE MSV000091977 - Characterization of Mauritia flexuosa and Euterpe oleracea
title: This is a study of characterization of Mauritia flexuosa and Euterpe oleracea by LC-QTOF/MS
DOI: 10.15468/gmdsks
title: An update catalogue of biting midges of the genus Culicoides Latreille, 1809 (Diptera, Ceratopogonidae) of Mexico and their known distribution by state

description: An updated catalogue of Culicoides of Mexico is presented. It includes 86 species with their regional distribution and corresponding record references, known immature stages and associated pathogens.
DOI: 10.6084/m9.figshare.22898369
title: mob_he

description: MOB Histology data used in tutorial and in article
DOI: 10.6084/m9.figshare.22898369.v1
title: mob_he

description: MOB Histology data used in tutorial and in article
DOI: 10.5517/ccdc.csd.cc2bkg0d
title: CCDC 2161723: Experimental Crystal Structure Determination

description: Related Article: João Honorato de Araujo-Neto, Adriana P. M. Guedes, Celisnolia M. Leite, Carlos André F. Moraes, Andressa L. Santos, Rafaella da S. Brito, Thiago L. Rocha, Francyelli Mello-Andrade, Javier Ellena, Alzir A. Batista|2023|Inorg.Chem.|62|6955|doi:10.1021/acs.inorgchem.3c00183
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2bkg1f
title: CCDC 2161724: Experimental Crystal Structure Determination

description: Related Article: João Honorato de Araujo-Neto, Adriana P. M. Guedes, Celisnolia M. Leite, Carlos André F. Moraes, Andressa L. Santos, Rafaella da S. Brito, Thiago L. Rocha, Francyelli Mello-Andrade, Javier Ellena, Alzir A. Batista|2023|Inorg.Chem.|62|6955|doi:10.1021/acs.inorgchem.3c00183
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2bmh3l
title: CCDC 2163679: Experimental Crystal Structure Determination

description: Related Article: Hongliang Li, Liu Liu, Guanghui Gou, Xuelei Xin, Jun Li, Haji Akber Aisa|2023|Phytochemistry|210|113647|doi:10.1016/j.phytochem.2023.113647
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.6084/m9.figshare.22898501
title: mob_3d

description: 3 gene spatial transcriptomics data
DOI: 10.15139/s3/2gcv4n
title: The 5 R's How-to Guide and Case Study (2023)

description: The 5 R's is a five-question framework to help us understand the broad “system" around an area of work, such as a Vision Zero or Safe System-related initiative, to inform strategic planning and action. This guide and case study are included in a five-part series of systems thinking tools, adapted and applied to support road safety interventions for more effective VZ planning and implementation. Utilizing these resources, stakeholders can establish a firm foundation and deepen their understanding of the system (of policies, norms, funding streams, equitable/inequitable processes, etc.) underlying their road safety outcomes. Systems thinking is an approach to problem-solving and understanding complex problems by analyzing the patterns, dynamics, relationships, and feedback loops among various elements of a system. In these set of resources, researchers from the Collaborative Sciences Center for Road Safety (CSCRS) have developed systems thinking-based content and guidance materials to strengthen the implementation of Vision Zero (VZ) and Safe Systems approaches. These tools and resources introduce the systems thinking framework, and provide guidance on using systems thinking and collaboration tools to support VZ planning and coalition building efforts.
DOI: 10.15139/s3/b7gb58
title: Goal and Action Alignment Mapping How-to Guide and Case Study (2023)

description: Goal and Action Alignment Mapping is a mapping tool that allows people to see how they are embedded within a larger system that includes shared goals, illuminates win-wins between themselves and partners, and can help motivate action and change. This guide and case study are included in a five-part series of systems thinking tools, adapted and applied to support road safety interventions for more effective VZ planning and implementation. Utilizing these resources, stakeholders can establish a firm foundation and deepen their understanding of the system (of policies, norms, funding streams, equitable/inequitable processes, etc.) underlying their road safety outcomes. Systems thinking is an approach to problem-solving and understanding complex problems by analyzing the patterns, dynamics, relationships, and feedback loops among various elements of a system. In these set of resources, researchers from the Collaborative Sciences Center for Road Safety (CSCRS) have developed systems thinking-based content and guidance materials to strengthen the implementation of Vision Zero (VZ) and Safe Systems approaches. These tools and resources introduce the systems thinking framework, and provide guidance on using systems thinking and collaboration tools to support VZ planning and coalition building efforts.
DOI: 10.5281/zenodo.7551770
title: One Model to Rule Them All: Cross-Language Detection of Malicious Packages for NPM and PyPI - Dataset, Models, Malicious Packages List

description: This artifact complements the paper "One Model to Rule Them All: Language-Independent Detection of Malicious Packages for PyPI and NPM" submitted at ESEC/FSE 2023. In particular: "Labelled_Dataset.csv " contains the data used for the features evaluation, models evaluation and models training The .pkl files are the best-performing classifiers obtained after the models evaluation "Malicious_Packages_Discovered.csv" contain the list of malicious packages discovered during our real-world experiment
DOI: 10.5281/zenodo.7551769
title: One Model to Rule Them All: Cross-Language Detection of Malicious Packages for NPM and PyPI - Dataset, Models, Malicious Packages List

description: This artifact complements the paper "One Model to Rule Them All: Language-Independent Detection of Malicious Packages for PyPI and NPM" submitted at ESEC/FSE 2023. In particular: "Labelled_Dataset.csv " contains the data used for the features evaluation, models evaluation and models training The .pkl files are the best-performing classifiers obtained after the models evaluation "Malicious_Packages_Discovered.csv" contain the list of malicious packages discovered during our real-world experiment
DOI: 10.6084/m9.figshare.22898564
title: mob_100d

description: 100 genes for mob spatial data
DOI: 10.15139/s3/r7wgid
title: Causal Loop Diagramming How-to Guide and Case Study (2023)

description: Causal Loop Diagramming clearly depicts how multiple factors in a system may interact to cause an outcome (e.g., road traffic crashes), and are used to help better understand and disentangle the complexity surrounding specific problems or issues to inform action planning. This guide and case study are included in a five-part series of systems thinking tools, adapted and applied to support road safety interventions for more effective VZ planning and implementation. Utilizing these resources, stakeholders can establish a firm foundation and deepen their understanding of the system (of policies, norms, funding streams, equitable/inequitable processes, etc.) underlying their road safety outcomes. Systems thinking is an approach to problem-solving and understanding complex problems by analyzing the patterns, dynamics, relationships, and feedback loops among various elements of a system. In these set of resources, researchers from the Collaborative Sciences Center for Road Safety (CSCRS) have developed systems thinking-based content and guidance materials to strengthen the implementation of Vision Zero (VZ) and Safe Systems approaches. These tools and resources introduce the systems thinking framework, and provide guidance on using systems thinking and collaboration tools to support VZ planning and coalition building efforts.
DOI: 10.15139/s3/5hziwq
title: Balance of Petals Diagramming How-to Guide and Case Study (2023)

description: Balance of Petals Diagraming is a systems thinking tool used to brainstorm and document what, specifically, is needed from stakeholders to support an initiative, such as a Vision Zero or Safe System-related initiative, as well as what about the initiative brings value to each stakeholder. This guide and case study are included in a five-part series of systems thinking tools, adapted and applied to support road safety interventions for more effective VZ planning and implementation. Utilizing these resources, stakeholders can establish a firm foundation and deepen their understanding of the system (of policies, norms, funding streams, equitable/inequitable processes, etc.) underlying their road safety outcomes. Systems thinking is an approach to problem-solving and understanding complex problems by analyzing the patterns, dynamics, relationships, and feedback loops among various elements of a system. In these set of resources, researchers from the Collaborative Sciences Center for Road Safety (CSCRS) have developed systems thinking-based content and guidance materials to strengthen the implementation of Vision Zero (VZ) and Safe Systems approaches. These tools and resources introduce the systems thinking framework, and provide guidance on using systems thinking and collaboration tools to support VZ planning and coalition building efforts.
DOI: 10.34683/sr2429
title: StoneRounds Case: SR2429
title: Retinitis Pigmentosa with Ataxia

description: StoneRounds Case SR2429 was diagnosed with Retinitis Pigmentosa with Ataxia likely caused by mutations in the gene: ELOVL4.
DOI: 10.34683/sr2065
title: StoneRounds Case: SR2065
title: MIDD

description: StoneRounds Case SR2065 was diagnosed with MIDD likely caused by mutations in the gene: MT-TL1.
DOI: 10.15139/s3/xjemfj
title: System Support Mapping How-to Guide and Case Study (2023)

description: System support maps are used to understand the role an individual or organization plays in a system, their responsibilities or objectives/goals, needs for meeting each responsibility, resources used to support needs (and notes on whether these resources are helpful), and wishes for being better supported or better supporting the system. This guide and case study are included in a five-part series of systems thinking tools, adapted and applied to support road safety interventions for more effective VZ planning and implementation. Utilizing these resources, stakeholders can establish a firm foundation and deepen their understanding of the system (of policies, norms, funding streams, equitable/inequitable processes, etc.) underlying their road safety outcomes. Systems thinking is an approach to problem-solving and understanding complex problems by analyzing the patterns, dynamics, relationships, and feedback loops among various elements of a system. In these set of resources, researchers from the Collaborative Sciences Center for Road Safety (CSCRS) have developed systems thinking-based content and guidance materials to strengthen the implementation of Vision Zero (VZ) and Safe Systems approaches. These tools and resources introduce the systems thinking framework, and provide guidance on using systems thinking and collaboration tools to support VZ planning and coalition building efforts.
DOI: 10.5519/qd.omrvykpi
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (31 records)
DOI: 10.5066/p9ll7e8y
title: Shakemap Atlas Composite Dataset for the Conterminous United States from 1906 to 2020

description: Composite of Shakemap Atlas ground motions (PGA and PGV) and intensity calculations at a scale of 10km. Time history at each grid cell and maximum observed/estimated hazards are provided.
DOI: 10.34740/kaggle/dsv/5709886
title: NSE-Scripts-Data
DOI: 10.5517/ccdc.csd.cc2bpyss
title: CCDC 2166056: Experimental Crystal Structure Determination

description: Related Article: Hongliang Li, Liu Liu, Guanghui Gou, Xuelei Xin, Jun Li, Haji Akber Aisa|2023|Phytochemistry|210|113647|doi:10.1016/j.phytochem.2023.113647
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2bsg7v
title: CCDC 2168457: Experimental Crystal Structure Determination

description: Related Article: Yalu Zou, Hongbin Chen, Xingqi Bi, Xiaoyun Xu, Hebin Wang, Menglu Lin, Zaifei Ma, Mingtao Zhang, Chenxi Li, Xiangjian Wan, Guankui Long, Yao Zhaoyang, Yongsheng Chen|2022|Energy Environ.Sci.|15|3519|doi:10.1039/D2EE01340A
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc294w8m
title: CCDC 2119850: Experimental Crystal Structure Determination

description: Related Article: Svetlana V. Klementyeva, Claudio Schrenk, Andreas Schnepf|2022|Inorg.Chem.|61|11787|doi:10.1021/acs.inorgchem.2c01501
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2c10ct
title: CCDC 2175715: Experimental Crystal Structure Determination

description: Related Article: Tushar Verma, Pankaj Verma, Udai P. Singh|2023|Microchemical Journal|191|108771|doi:10.1016/j.microc.2023.108771
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2cmv84
title: CCDC 2193816: Experimental Crystal Structure Determination

description: Related Article: Shuang Su, Xue-Qiong Yang, Ya-Bin Yang, Zhong-Tao Ding|2023|Phytochemistry|210|113651|doi:10.1016/j.phytochem.2023.113651
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2dhqbz
title: CCDC 2219641: Experimental Crystal Structure Determination

description: Related Article: Shu-Yi Li, Kun Wang, Jia-Wen Wang, Shu-Cong Fan, Peng Zhang, Quan-Guo Zhai|2023|Inorg.Chem.|62|7069|doi:10.1021/acs.inorgchem.3c00476
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2dhqc0
title: CCDC 2219642: Experimental Crystal Structure Determination

description: Related Article: Shu-Yi Li, Kun Wang, Jia-Wen Wang, Shu-Cong Fan, Peng Zhang, Quan-Guo Zhai|2023|Inorg.Chem.|62|7069|doi:10.1021/acs.inorgchem.3c00476
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2dhq9y
title: CCDC 2219640: Experimental Crystal Structure Determination

description: Related Article: Shu-Yi Li, Kun Wang, Jia-Wen Wang, Shu-Cong Fan, Peng Zhang, Quan-Guo Zhai|2023|Inorg.Chem.|62|7069|doi:10.1021/acs.inorgchem.3c00476
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2dhqd1
title: CCDC 2219643: Experimental Crystal Structure Determination

description: Related Article: Shu-Yi Li, Kun Wang, Jia-Wen Wang, Shu-Cong Fan, Peng Zhang, Quan-Guo Zhai|2023|Inorg.Chem.|62|7069|doi:10.1021/acs.inorgchem.3c00476
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2dy53n
title: CCDC 2232561: Experimental Crystal Structure Determination

description: Related Article: Zhikang Chen, Wuchao Zhao, Conglei Liu, Liuying Jiang, Gang Fu, Yuetao Zhang, Hongping Zhu|2023|Polym.Chem.|14|2344|doi:10.1039/D3PY00301A
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.