cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5517/ccdc.csd.cc27f4qk
title: CCDC 2068218: Experimental Crystal Structure Determination

description: Related Article: Aaron D. Nicholas, Leah C. Garman, Nicolina Albano, Christopher L. Cahill|2022|Phys.Chem.Chem.Phys.(PCCP)|24|15305|doi:10.1039/D2CP01996E
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.cc27f4pj
title: CCDC 2068217: Experimental Crystal Structure Determination

description: Related Article: Aaron D. Nicholas, Leah C. Garman, Nicolina Albano, Christopher L. Cahill|2022|Phys.Chem.Chem.Phys.(PCCP)|24|15305|doi:10.1039/D2CP01996E
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.20186285
title: pbmc.h5ad

description: PBMC dataset for openproblems.bio
DOI: 10.5281/zenodo.5902893
title: Dataset for: AutoSourceID-Light

description: This is the dataset used in the paper AutoSourceID-Light (<strong>paper</strong>) for Training, Test and Validation sets. AutoSourceID-Light (ASID-L) is an innovative framework that uses computer vision techniques that can naturally deal with large amounts of data and rapidly localize sources in optical images. The dataset is made of 3 fields images taken with the MeerLICHT telescope: _20200601_191800_ (Omega Centauri globular cluster), _20210401_173445_(Fornax galaxy cluster) and _20210910_022724_ ('empty' CDF-S). For each field, 2 files are provided: the optical image (_red_cosmics_nobkgsub.fits) and the catalog of EDR3 Gaia sources that match the location of the fields (_GaiaEDR3_cat_SNR_redimage.fits). If you use the dataset, please cite the appropriate DOIs. Code available at <strong>https://github.com/FiorenSt/AutoSourceID-Light</strong> (Zenodo repository)
DOI: 10.5281/zenodo.5902892
title: Dataset for: AutoSourceID-Light

description: This is the dataset used in the paper AutoSourceID-Light (<strong>paper</strong>) for Training, Test and Validation sets. AutoSourceID-Light (ASID-L) is an innovative framework that uses computer vision techniques that can naturally deal with large amounts of data and rapidly localize sources in optical images. The dataset is made of 3 fields images taken with the MeerLICHT telescope: _20200601_191800_ (Omega Centauri globular cluster), _20210401_173445_(Fornax galaxy cluster) and _20210910_022724_ ('empty' CDF-S). For each field, 2 files are provided: the optical image (_red_cosmics_nobkgsub.fits) and the catalog of EDR3 Gaia sources that match the location of the fields (_GaiaEDR3_cat_SNR_redimage.fits). If you use the dataset, please cite the appropriate DOIs. Code available at <strong>https://github.com/FiorenSt/AutoSourceID-Light</strong> (Zenodo repository)
DOI: 10.17909/t9-9gm4-fx30
title: TESS Eclipsing Binaries ("TESS-EBs")

description: TESS-EBs is a catalog containing locations, ephemerides and basic light curve properties for eclipsing binary stars found in data from the Transiting Exoplanet Survey Satellite (TESS).  Prša et al. 2022 discuss the selection criteria for eclipsing binary candidates, the detection of hither-to unknown eclipsing systems, the determination of ephemerides, the validation and triage process, and the derivation of heuristic estimates for the ephemerides. They also present statistical properties of the sample and qualitative estimates of completeness. Instead of keeping to the widely used discrete classes, the authors propose a binary star morphology classification based on a dimensionality reduction algorithm. The catalog will continue to be updated with new sectors of data as they become available. The deliverables presented here are curated by the TESS Eclipsing Binary Working Group, an open group of professional and citizen scientists.
DOI: 10.5281/zenodo.6685648
title: Molecular Models of hematite, goethite, kaolinite, and quartz surfaces

description: Molecular models for hematite, quartz, goethite and kaolinite surfaces according to different terminations.
DOI: 10.35077/tab
title: MOp BARseq Brain XC118

description: Long-range projection mapping of ~10k neurons in MOp using BARseq. This is part of the BARseq dataset used in Munoz-Castaneda et al., 2021 (doi.org/10.1038/s41586-021-03970-w). For information regarding BARseq technology, see Chen et al., 2019 (doi.org/10.1016/j.cell.2019.09.023)
description: Sequencing-based projection mapping
description: DATASET METADATA: title:'MOp BARseq Brain XC118', GeneralModality:'anatomy/morphology', Technique:'BARseq' SPECIMEN METADATA: LocalID:'XC118', Species:'mouse', NCBITaxonomy:'NCBI:txid10090', Age:'56-63', Ageunit:'Days', Sex:'Male', OrganName:'Brain', Locations:'Mop upper limb area' INSTRUMENT METADATA: MicroscopeType:'Spinning disk confocal', MicroscopeManufacturerAndModel:'Olympus IX-81, Crest Xlight v2' IMAGE METADATA: Number:'1,2,3,4,5,G,T,A,C,DIC; ', displayColor:'(0,1,1)(1,1,0),(1,0,1)(1,1,1)(0,0,0);', stepSizeX:'0.65', stepSizeY:'0.65', stepSizeZ:'7'
DOI: 10.5281/zenodo.6761816
title: Generating spatiotemporal patterns of linearly polarised light at high frame rates for insect vision research

description: <strong>Electrophysiology dataset for the work presented in:</strong> Supple et al., (2022) Generating spatiotemporal patterns of linearly polarised light at high frame rates for insect vision research. J. Exp. Biol. 225, jeb244087. doi:10.1242/jeb.244087 <strong>Analysis code available at:</strong> https://github.com/jacksupple/Supple22_JEB_PolDevice_DataAnalysisScripts Download, select all, and extract files. Navigate to the assembled folder to re-run the analysis code. <em>Argynnis paphia</em> butterfly intracellular photoreceptor traces are located in "\Photoreceptor_data". Results of the analysed data are found in "\photoreceptor_results" <em>Calliphora vicina</em> blowfly extracellular lobula plate tangential cell (LPTC) recordings are located in "\LPTC_data". Results of the analysed data are found in "\LPTC_results". "\DualDLP_Stim" contains parameter files for the rotating dot stimuli, which are used during analysis.
DOI: 10.5281/zenodo.6761815
title: Generating spatiotemporal patterns of linearly polarised light at high frame rates for insect vision research

description: <strong>Electrophysiology dataset for the work presented in:</strong> Supple et al., (2022) Generating spatiotemporal patterns of linearly polarised light at high frame rates for insect vision research. J. Exp. Biol. 225, jeb244087. doi:10.1242/jeb.244087 <strong>Analysis code available at:</strong> https://github.com/jacksupple/Supple22_JEB_PolDevice_DataAnalysisScripts Download, select all, and extract files. Navigate to the assembled folder to re-run the analysis code. <em>Argynnis paphia</em> butterfly intracellular photoreceptor traces are located in "\Photoreceptor_data". Results of the analysed data are found in "\photoreceptor_results" <em>Calliphora vicina</em> blowfly extracellular lobula plate tangential cell (LPTC) recordings are located in "\LPTC_data". Results of the analysed data are found in "\LPTC_results". "\DualDLP_Stim" contains parameter files for the rotating dot stimuli, which are used during analysis.
DOI: 10.5066/p91w73on
title: Wetland vegetation and elevation of Arcadia Marsh, Michigan (1995-2010)

description: Vegetation sampling and elevation data were collected to characterize the sedge-grass meadow of Arcadia Marsh, Arcadia, Michigan (USA), a drowned river mouth wetland near Lake Michigan. Wetland vegetation community data were collected by quadrat sampling in 1995, 2002, and 2010 and topographic data were collected via GPS and LIDAR positional data in 2010.
DOI: 10.35077/tag
title: MOp BARseq Brain XC117

description: Long-range projection mapping of ~10k neurons in MOp using BARseq. This is part of the BARseq dataset used in Munoz-Castaneda et al., 2021 (doi.org/10.1038/s41586-021-03970-w). For information regarding BARseq technology, see Chen et al., 2019 (doi.org/10.1016/j.cell.2019.09.023)
description: Sequencing-based projection mapping
description: DATASET METADATA: title:'MOp BARseq Brain XC117', GeneralModality:'anatomy/morphology', Technique:'BARseq' SPECIMEN METADATA: LocalID:'XC117', Species:'mouse', NCBITaxonomy:'NCBI:txid10090', Age:'56-63', Ageunit:'Days', Sex:'Male', OrganName:'Brain', Locations:'Mop upper limb area' INSTRUMENT METADATA: MicroscopeType:'Spinning disk confocal', MicroscopeManufacturerAndModel:'Olympus IX-81, Crest Xlight v2' IMAGE METADATA: Number:'1,2,3,4,5,G,T,A,C,DIC; ', displayColor:'(0,1,1)(1,1,0),(1,0,1)(1,1,1)(0,0,0);', stepSizeX:'0.65', stepSizeY:'0.65', stepSizeZ:'7'
DOI: 10.6084/m9.figshare.20043353
title: Characterization of experimental cattle populations from Argentina with a low-density SNP genotyping panel

description: The folder includes: - raw SNP array data of 45 cattle samples from the Angus, Hereford and Argentinean Creole herds at Balcarce Station; - 25 cattle samples from the Argentinean Creole herd at the Leales Station; - 117 cattle samples from the Argentinean Hereford Association.
DOI: 10.6084/m9.figshare.20043353.v2
title: Characterization of experimental cattle populations from Argentina with a low-density SNP genotyping panel

description: The folder includes the raw SNP array data of 45 cattle samples from the Angus, Hereford and Argentinean Creole herds at Balcarce Station and 25 cattle samples from the Argentinean Creole herd at the Leales Station.
DOI: 10.18430/m37vid
title: X-ray diffraction data for the the crystal structure of L-leucine dehydrogenase from Pseudomonas aeruginosa (7VID)
DOI: 10.35077/tan
title: MOp cell typing using BARseq

description: Cell-typing by in situ sequencing of cell type markers using BARseq2. This dataset is part of Sun et al., 2021 (doi.org/10.1038/s41593-021-00842-4).
description: in situ sequencing
description: DATASET METADATA: title:'MOp cell typing using BARseq', GeneralModality:'spatial transcriptomics', Technique:'BARseq' SPECIMEN METADATA: LocalID:'XC-wt2', Species:'mouse', NCBITaxonomy:'NCBI:txid10090', Age:'56-63', Ageunit:'Days', Sex:'Male', OrganName:'Brain', Locations:'Motor cortex' INSTRUMENT METADATA: MicroscopeType:'Spinning disk confocal', MicroscopeManufacturerAndModel:'Olympus IX-81, Crest Xlight v2' IMAGE METADATA: Number:'Sequencing images: 1,2,3,4,5,G,T,A,C,DIC; Hybridization images: 1,2,3,4,5,6,GFP,YFP,TxRed,Cy5,DAPI,DIC', displayColor:'(0,1,1)(1,1,0),(1,0,1)(1,1,1)(0,0,0);(0,1,1)(1,1,0)(1,0,1),(1,1,1)(0,0,1),(0,0,0)', stepSizeX:'0.34/0.65', stepSizeY:'0.34/0.65', stepSizeZ:'1/7'
DOI: 10.5281/zenodo.6780261
title: Automated inference of sequences of operations in RESTful APIs with deep reinforcement learning - replication package

description: This directory contains the replication package of the article entitled "Automated inference of sequences of operations in RESTful APIs with deep reinforcement learning". Please note that this is NOT a real publication or scientific report, but a project created for the purpose of learning the basic concepts of research by emulating the process of creating an article.
DOI: 10.5281/zenodo.6780260
title: Automated inference of sequences of operations in RESTful APIs with deep reinforcement learning - replication package

description: This directory contains the replication package of the article entitled "Automated inference of sequences of operations in RESTful APIs with deep reinforcement learning". Please note that this is NOT a real publication or scientific report, but a project created for the purpose of learning the basic concepts of research by emulating the process of creating an article.
DOI: 10.18164/495eb10d-d423-432a-980f-264ef287d45b
title: Great Lakes Water Quality Monitoring and Surveillance Data
title: Données de surveillance et de monitoring de l'eau des Grands Lacs

description: Water quality and ecosystem health data collected in the Great Lakes and priority tributaries to determine baseline water quality status, long term trends and spatial distributions, the effectiveness of management actions, determine compliance with water quality objectives and identify emerging issues are included in this dataset.
description: Les données de qualité de l'eau et de la santé de l'écosystème recueillies dans les Grands Lacs et dans les tributaires principaux afin d'établir les niveaux de base, les tendances à long terme et la distribution spatiale, d'évaluer l'efficacité des mesures de gestion, de déterminer la conformité aux objectifs de qualité de l'eau et d'identifier des problèmes émergents sont incluses dans cet ensemble de données.
DOI: 10.34681/fns0-yx36
title: The Maltreatment of Children with Disabilities and Child Maltreatment in Substance Abusing Families, 1991

description: This study examines the incidence of substantiated maltreatment among children with cognitive, physical, emotional or learning disabilities, with specific attention given to the relationship between maltreatment and disabilities. It also investigates the incidence of child abuse and neglect among children in substance abusing families, and the relationship between child abuse and familial substance abuse. The data were collected from a nationally representative group of 35 Child Protective Services (CPS) agencies, which were asked to provide information on all cases of substantiated maltreatment over a four to six week period in early 1991. The Archive distributes 5 data files for this study which provide information on a total of 1,249 substantiated maltreatment incidents. A case-level data file includes demographic information on the children and adults involved in each case, information on the timing, type, and reporting of maltreatment, data on the relationships between the individuals involved in each case, and case status. A second file contains caseworker assessments of children with suspected or known disabilities, as well as information on the sources and reliability of those assessments. An estimated 14.1 percent of the children in the study were identified by caseworkers as having one or more disabilities, using the definition found in the Americans with Disabilities Act (P.L. 101-336). A third data file contains substance abuse information for each adult in the study suspected of substance abuse. In addition to the three files mentioned above there are two files the which the Archive distributes which are restructured versions of the case-level file, in which the unit of analysis has been changed to represent an individual involved in a case.
DOI: 10.6084/m9.figshare.13295831.v11
title: Autism Spectrum Disorder and Asperger Syndrome Question Answering Dataset 1.0

description: <em><strong>RUS</strong></em> <strong>Последнее обновление: 23/05/2022</strong> Набор данных предназначен для разработки русскоязычных диалоговых систем (чат-ботов, вопросно-ответных систем и т. д.) о расстройствах аутистического спектра. Источник текстов: https://aspergers.ru Проект реализуется победителем конкурса «Практики личной филантропии и альтруизма» Благотворительного фонда Владимира Потанина. <strong>Состав набора данных:</strong> 1. original.json: оригинальная версия датасета 2. multiple.json: версия датасета с несколькими вариантами ответа 3. short.json: версия датасета с укороченными ответами 4. half_sized.json: версия датасета содержит 50% собранных данных 5. no_impossible.json: версия содержит только релевантные вопросы 6. impossible_question.tsv: список нерелевантных вопросов (используются для создания шумов в данных) 7. crowdsourcing.tsv: результаты краудсорсинга 8. age_dataset.tsv: набор данных для определения возраста пользователя (можно использовать для кастомизации моделей) <em><strong>ENG</strong></em> A dataset for question-answering used for building an informational Russian language chatbot for the inclusion of people with autism spectrum disorder and Asperger syndrome in particular, based on data from the following website: https://aspergers.ru. <strong>The dataset has several versions:</strong> 1. Original version 2. Half-sized version (50% of the original data) 3. No impossible version (a version without irrelevant/impossible questions) 4. Short version (a version with shorterned answers) 5. Multiple version (a version with several answers, all the other versions contain only one answer to each question)
DOI: 10.18164/48f3a45e-851a-45c7-96fd-959a6fb485a9
title: Great Lakes Areas of Concern Monitoring and Surveillance Data
title: Données de surveillance et de monitoring pour les secteurs préoccupants des Grands Lacs

description: Water quality and ecosystem health surveillance and monitoring data collected to complete assessments of beneficial use impairments of Areas of Concern (AOCs) and to track the effectiveness of remedial measures and confirm restoration of beneficial uses are included in this dataset. AOCs are geographic areas in the Great Lakes that were identified in the mid-1980s where significant impairment of beneficial uses has occurred as a result of human activities at the local level. Remediating AOCs contributes to the sustainability of local communities and of the Great Lakes region, and is a joint commitment under the Canada-United States Great Lakes Water Quality Agreement (GLWQA).
description: Données de surveillance et de monitoring de la qualité de l'eau et de la santé de l'écosystème recueillies pour compléter l'évaluation de la perte d'usage dans les secteurs préoccupants, pour évaluer l'efficacité des mesures de remédiation et pour confirmer la restoration des usages. Les secteurs préoccupants sont des zones géographiques des Grands Lacs, identifiées dans le milieu des années 80, dans lesquelles il y avait une perte significative des usages due aux activités humaines locales. La remédiation des secteurs préoccupants contribue à la durabilité des communautés locales dans la région des Grands Lacs, et est un engagement conjoint en vertu de l'entente Canada-É.U.A. sur la qualité de l'eau des Grands Lacs.
DOI: 10.6084/m9.figshare.20161934
title: ChAdOx1 NiV vaccination protects against lethal Nipah Bangladesh virus infection in African green monkeys

description: This dataset contains all the raw data from the manuscript ' ChAdOx1 NiV vaccination protects against lethal Nipah Bangladesh virus infection in African green monkeys'.
DOI: 10.6084/m9.figshare.20161934.v1
title: ChAdOx1 NiV vaccination protects against lethal Nipah Bangladesh virus infection in African green monkeys

description: This dataset contains all the raw data from the manuscript ' ChAdOx1 NiV vaccination protects against lethal Nipah Bangladesh virus infection in African green monkeys'.
DOI: 10.35077/tap
title: AUDp cadherin and high-level cell type marker expression using BARseq

description: In situ sequencing of cadherin and high-level cell type markers in the auditory cortex using BARseq2. This dataset is part of Sun et al., 2021 (doi.org/10.1038/s41593-021-00842-4).
description: in situ sequencing
description: DATASET METADATA: title:'AUDp cadherin and high-level cell type marker expression using BARseq', GeneralModality:'spatial transcriptomics', Technique:'BARseq' SPECIMEN METADATA: LocalID:'XC-wt1', Species:'mouse', NCBITaxonomy:'NCBI:txid10090', Age:'56-63', Ageunit:'Days', Sex:'Male', Genotype:'Strain_Name=C57Bl6/Agouti/Swiss', OrganName:'Brain', Locations:'Auditory cortex' INSTRUMENT METADATA: MicroscopeType:'Spinning disk confocal', MicroscopeManufacturerAndModel:'Olympus IX-81, Crest Xlight v2' IMAGE METADATA: Number:'Sequencing images: 1,2,3,4,5,G,T,A,C,DIC; Hybridization images: 1,2,3,4,5,6,GFP,YFP,TxRed,Cy5,DAPI,DIC', displayColor:'(0,1,1)(1,1,0),(1,0,1)(1,1,1)(0,0,0);(0,1,1)(1,1,0)(1,0,1),(1,1,1)(0,0,1),(0,0,0)', stepSizeX:'0.34/0.65', stepSizeY:'0.34/0.65', stepSizeZ:'1/7'
DOI: 10.25921/gw16-1j77
title: EK80 Water Column Sonar Data Collected During FK190106-20190124-221004
DOI: 10.35077/tar
title: cadherin expression and projection mapping in MOp

description: Correlating gene expression to projections in MOp using BARseq2. This dataset is part of Sun et al., 2021 (doi.org/10.1038/s41593-021-00842-4).
description: in situ sequencing
description: DATASET METADATA: title:'cadherin expression and projection mapping in MOp', GeneralModality:'Connectivity and spatial transcriptomics', Technique:'BARseq' SPECIMEN METADATA: LocalID:'XC116', Species:'mouse', NCBITaxonomy:'NCBI:txid10090', Age:'56-63', Ageunit:'Days', Sex:'Male', Genotype:'Strain_Name=C57Bl6/Agouti/Swiss', OrganName:'Brain', Locations:'Motor cortex' INSTRUMENT METADATA: MicroscopeType:'Spinning disk confocal', MicroscopeManufacturerAndModel:'Olympus IX-81, Crest Xlight v2' IMAGE METADATA: Number:'Sequencing images: 1,2,3,4,5,G,T,A,C,DIC; Hybridization images: 1,2,3,4,5,6,GFP,YFP,TxRed,Cy5,DAPI,DIC', displayColor:'(0,1,1)(1,1,0),(1,0,1)(1,1,1)(0,0,0);(0,1,1)(1,1,0)(1,0,1),(1,1,1)(0,0,1),(0,0,0)', stepSizeX:'0.34/0.65', stepSizeY:'0.34/0.65', stepSizeZ:'1/7'
DOI: 10.35077/tax
title: cadherin expression and projection mapping in AUDp sample 2

description: Correlating gene expression to projections in AUDp using BARseq2. This dataset is part of Sun et al., 2021 (doi.org/10.1038/s41593-021-00842-4).
description: in situ sequencing
description: DATASET METADATA: title:'cadherin expression and projection mapping in AUDp sample 2', GeneralModality:'Connectivity and spatial transcriptomics', Technique:'BARseq' SPECIMEN METADATA: LocalID:'XC97', Species:'mouse', NCBITaxonomy:'NCBI:txid10090', Age:'56-63', Ageunit:'Days', Sex:'Male', Genotype:'Strain_Name=C57Bl6/Agouti/Swiss', OrganName:'Brain', Locations:'Auditory cortex' INSTRUMENT METADATA: MicroscopeType:'Spinning disk confocal', MicroscopeManufacturerAndModel:'Olympus IX-81, Crest Xlight v2' IMAGE METADATA: Number:'Sequencing images: 1,2,3,4,5,G,T,A,C,DIC; Hybridization images: 1,2,3,4,5,6,GFP,YFP,TxRed,Cy5,DAPI,DIC', displayColor:'(0,1,1)(1,1,0),(1,0,1)(1,1,1)(0,0,0);(0,1,1)(1,1,0)(1,0,1),(1,1,1)(0,0,1),(0,0,0)', stepSizeX:'0.34/0.65', stepSizeY:'0.34/0.65', stepSizeZ:'1/7'
DOI: 10.3886/e119933v1-122082
title: Replication Files for "Using Synthetic Controls: Feasibility, Data Requirements, and Methodological Aspects"

description: Probably because of their interpretability and transparent nature, synthetic controls have become widely applied in empirical research in economics and the social sciences. This article aims to provide practical guidance to researchers employing synthetic control methods. The article starts with an overview and an introduction to synthetic control estimation. The main sections discuss the advantages of the synthetic control framework as a research design, and describe the settings where synthetic controls provide reliable estimates and those where they may fail. The article closes with a discussion of recent extensions, related methods, and avenues for future research.<br>