cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5517/ccdc.csd.cc2bq4qy
title: CCDC 2166240: Experimental Crystal Structure Determination

description: Related Article: Xiaoju Tan, Kun Zhao, Xuefang Zhong, Lan Yang, Yiming Dong, Tianmi Wang, Shengping Yu, Xiaoxiao Li, Zhigang Zhao|2022|Org.Biomol.Chem.|20|6566|doi:10.1039/D2OB00964A
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.cc2bxkjc
title: CCDC 2172403: Experimental Crystal Structure Determination

description: Related Article: Xianglin Yu, Zhiliang Tang, Kun He, Weina Li, Jun Lin, Yi Jin|2022|Org.Biomol.Chem.|20|6654|doi:10.1039/D2OB01234K
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: 10.14469/hpc/11024
title: Catalytic and Computational Studies of N-Heterocyclic Carbene or Phosphine-Containing Copper(I) Complexes for the Synthesis of 5-Iodo-1,2,3-Triazoles. Table 1
DOI: 10.14469/hpc/11025
title: Catalytic and Computational Studies of N-Heterocyclic Carbene or Phosphine-Containing Copper(I) Complexes for the Synthesis of 5-Iodo-1,2,3-Triazoles. Table 2
DOI: 10.14469/hpc/11026
title: Catalytic and Computational Studies of N-Heterocyclic Carbene or Phosphine-Containing Copper(I) Complexes for the Synthesis of 5-Iodo-1,2,3-Triazoles. Table 2
DOI: 10.14469/hpc/11027
title: Catalytic and Computational Studies of N-Heterocyclic Carbene or Phosphine-Containing Copper(I) Complexes for the Synthesis of 5-Iodo-1,2,3-Triazoles. Table 3
DOI: 10.14469/hpc/11028
title: Catalytic and Computational Studies of N-Heterocyclic Carbene or Phosphine-Containing Copper(I) Complexes for the Synthesis of 5-Iodo-1,2,3-Triazoles. Table 4
DOI: 10.14469/hpc/11029
title: Catalytic and Computational Studies of N-Heterocyclic Carbene or Phosphine-Containing Copper(I) Complexes for the Synthesis of 5-Iodo-1,2,3-Triazoles. Table 5
DOI: 10.26060/mpdp-c561
title: S-map - a new soil spatial information system for New Zealand 2021 (deprecated)
DOI: 10.5517/ccdc.csd.cc2bz99y
title: CCDC 2174070: Experimental Crystal Structure Determination

description: Related Article: Jun-Nan Li, Zi-Jie Li, Liu-Yu Shen, Pinhua Li, Yicheng Zhang, Wen-Chao Yang|2022|Org.Biomol.Chem.|20|6659|doi:10.1039/D2OB01053D
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.cc2c0wx6
title: CCDC 2175608: Experimental Crystal Structure Determination

description: Related Article: Jian-Ting Sun, Xin Li, Tian-Yu Yang, Min Lv, Ling-Yan Chen, Bang-Guo Wei|2022|Org.Biomol.Chem.|20|6571|doi:10.1039/D2OB01196D
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.cc2c0wy7
title: CCDC 2175609: Experimental Crystal Structure Determination

description: Related Article: Jian-Ting Sun, Xin Li, Tian-Yu Yang, Min Lv, Ling-Yan Chen, Bang-Guo Wei|2022|Org.Biomol.Chem.|20|6571|doi:10.1039/D2OB01196D
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.cc2c2qpw
title: CCDC 2177368: Experimental Crystal Structure Determination

description: Related Article: Jessica C. Neville, Michelle Y. Lau, Tilo Söhnel, Jonathan Sperry|2022|Org.Biomol.Chem.|20|6562|doi:10.1039/D2OB01251K
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.cc2c8wr9
title: CCDC 2183291: Experimental Crystal Structure Determination

description: Related Article: Zhi-Mei Fu, Jian-Shan Ye, Jing-Mei Huang|2022|Org.Lett.|24|5874|doi:10.1021/acs.orglett.2c01782
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.cc2bck09
title: CCDC 2156050: Experimental Crystal Structure Determination

description: Related Article: Yu Fang, Shangfeng Ren, Chen He, Huiqi Han, Jin-Biao Liu, Fumin Liao, Min Yang|2022|Org.Biomol.Chem.|20|6550|doi:10.1039/D2OB01165D
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: 10.5281/zenodo.7020346
title: Predicting Patch Correctness Based on the Similarity of Failing Test Cases

description: Dataset for the paper "Predicting Patch Correctness Based on the Similarity of Failing Test Cases" Tool name: BATS
DOI: 10.5281/zenodo.7020345
title: Predicting Patch Correctness Based on the Similarity of Failing Test Cases

description: Dataset for the paper "Predicting Patch Correctness Based on the Similarity of Failing Test Cases" Tool name: BATS
DOI: 10.5281/zenodo.7020394
title: Ubergraph edge list

description: Normalized edge list of Ubergraph using bioregistry
DOI: 10.5281/zenodo.7020393
title: Ubergraph edge list

description: Normalized edge list of Ubergraph using bioregistry
DOI: 10.23645/epacomptox.16897780
title: invitrodb v3.5

description: This new release of the ToxCast database, invitrodb version 3.5, and reflects an update from the release of invitrodb version 3.4. Invitrodb version 3.5 is the backend data source for bioactivity in the new CompTox Chemicals Dashboard, to be released imminently.<br> <br> Science Inventory, CCTE products: https://cfpub.epa.gov/si/si_public_search_results.cfm?advSearch=true&showCriteria=2&keyword=CCTE&TIMSType=&TIMSSubTypeID=&epaNumber=&ombCat=Any&dateBeginPublishedPresented=07/01/2017&dateEndPublishedPresented=&dateBeginUpdated=&dateEndUpdated=&DEID=&personName=&personID=&role=Any&journalName=&journalID=&publisherName=&publisherID=&sortBy=pubDate&count=25 <br>
DOI: 10.23645/epacomptox.16897780.v4
title: invitrodb v3.5

description: This new release of the ToxCast database, invitrodb version 3.5, and reflects an update from the release of invitrodb version 3.4. Invitrodb version 3.5 is the backend data source for bioactivity in the new CompTox Chemicals Dashboard, to be released imminently.<br> <br> Science Inventory, CCTE products: https://cfpub.epa.gov/si/si_public_search_results.cfm?advSearch=true&showCriteria=2&keyword=CCTE&TIMSType=&TIMSSubTypeID=&epaNumber=&ombCat=Any&dateBeginPublishedPresented=07/01/2017&dateEndPublishedPresented=&dateBeginUpdated=&dateEndUpdated=&DEID=&personName=&personID=&role=Any&journalName=&journalID=&publisherName=&publisherID=&sortBy=pubDate&count=25 <br>
DOI: 10.23645/epacomptox.16897780.v3
title: invitrodb v3.5

description: This new release of the ToxCast database, invitrodb version 3.5, and reflects an update from the release of invitrodb version 3.4. Invitrodb version 3.5 is the backend data source for bioactivity in the new CompTox Chemicals Dashboard, to be released imminently.<br> <br> Science Inventory, CCTE products: https://cfpub.epa.gov/si/si_public_search_results.cfm?advSearch=true&showCriteria=2&keyword=CCTE&TIMSType=&TIMSSubTypeID=&epaNumber=&ombCat=Any&dateBeginPublishedPresented=07/01/2017&dateEndPublishedPresented=&dateBeginUpdated=&dateEndUpdated=&DEID=&personName=&personID=&role=Any&journalName=&journalID=&publisherName=&publisherID=&sortBy=pubDate&count=25 <br>
DOI: 10.25810/5dxz-xm93.52
title: Latin American Newspaper Coverage of Climate Change or Global Warming, 2005-2022 - July 2022

description: The Media and Climate Change Observatory Data monitors 126 sources (across newspapers, radio and TV) in 58 countries in seven different regions around the world. Data is assembled by accessing archives through the Lexis Nexis, Proquest and Factiva databases via the University of Colorado libraries. More information may be found at: http://mecco.colorado.edu.
DOI: 10.6084/m9.figshare.3761562.v2320
title: Online Labour Index: Measuring the Online Gig Economy for Policy and Research

description: Data repository for the data underlying the Online Labour Index. See http://ilabour.oii.ox.ac.uk online-labour-index/ for details.
DOI: 10.6084/m9.figshare.20610123
title: buteo_buteo_zanfona_1.fasta.gz

description: .......
DOI: 10.6084/m9.figshare.20610123.v1
title: buteo_buteo_zanfona_1.fasta.gz

description: .......
DOI: 10.13026/92ks-sq55
title: A large scale 12-lead electrocardiogram database for arrhythmia study

description: This newly inaugurated research database for 12-lead electrocardiogram (ECG)
signals was created under the auspices of Chapman University, Shaoxing
People's Hospital (Shaoxing Hospital Zhejiang University School of Medicine),
and Ningbo First Hospital. It aims to enable the scientific community in
conducting new studies on arrhythmia and other cardiovascular conditions.
Certain types of arrhythmias, such as atrial fibrillation, have a pronounced
negative impact on public health, quality of life, and medical expenditures.
As a non-invasive test, ECG is a major and vital diagnostic tool for detecting
these conditions. This practice, however, generates large amounts of data, the
analysis of which requires considerable time and effort by human experts.
Modern machine learning and statistical tools can be trained on high quality,
large data to achieve exceptional levels of automated diagnostic accuracy.
Thus, we collected and disseminated this novel database that contains 12-lead
ECGs of 45,152 patients with a 500 Hz sampling rate that features multiple
common rhythms and additional cardiovascular conditions, all labeled by
professional experts. The dataset can be used to design, compare, and fine-
tune new and classical statistical and machine learning techniques in studies
focused on arrhythmia and other cardiovascular conditions.
DOI: 10.5066/p9b593dz
title: Spatially-Explicit Predictive Maps of Greater Sage-Grouse Brood Selection Integrated with Brood Survival in Nevada and Northeastern California, USA

description: We used a hierarchical Bayesian modeling framework to estimate resource selection functions and survival for early and late brood-rearing stages of sage-grouse in relation to a broad suite of habitat characteristics evaluated at multiple spatial scales within the Great Basin from 2009 to 2019. Sage-grouse selected for greater perennial grass cover, higher relative elevations, and areas closer to springs and wet meadows during both early and late brood-rearing. Terrain characteristics, including heat load and aspect, were important in survival models, as was variation in shrub height. We also found strong evidence for higher survival for both early and late broods within previously burned areas, but survival within burned areas decreased as annual grass cover (i.e. cheatgrass, Bromus tectorum) increased. This interaction effect demonstrates how invasion of annual grasses into burned areas, which has become prevalent in Great Basin sagebrush ecosystems, can lead to maladaptive habitat selection by brood-rearing greater sage-grouse. Understanding these complex relationships aids wildlife conservation and habitat management as wildfire and annual grass cycles continue to accelerate across western ecosystems. These data support the following publication: Brussee, B.E., Coates, P.S., O'Neil, S.T., Casazza, M.L., Espinosa, S.P., Boone, J.D., Ammon, E.M., Gardner, S.C. and Delehanty, D.J., 2022. Invasion of annual grasses following wildfire corresponds to maladaptive habitat selection by a sagebrush ecosystem indicator species. Global Ecology and Conservation, 37, p.e02147. https://doi.org/10.1016/j.gecco.2022.e02147.
DOI: 10.6084/m9.figshare.20610393
title: Figure 1.zip

description: Raw CoSMoS data related to Figure 1.
DOI: 10.6084/m9.figshare.20610393.v1
title: Figure 1.zip

description: Raw CoSMoS data related to Figure 1.
DOI: 10.5281/zenodo.5589610
title: IWTomics ETn example

description: This example contains two region datasets "ETn fixed", "Control" and one feature "Recombination hotspots content". In particular, the region dataset "ETn fixed" contains 1296 genomic regions of 64 kb surrounding fixed ETns elements (32-kb flanking sequences upstream and 32-kb flanking sequences downstream of each element). The region dataset "Control" contains 1142 regions of 64 kb without elements, used as control in the test. The regions are aligned around their center (i.e. around the ETn integration sites). Recombination hotspots measurements are associated to each "ETn fixed" and "Control" region. In particular, this feature is measured in 1-kb windows, so that each region is associated to a recombination hotspots curve made of 64 values. The measurement used is the feature content, i.e. the fraction of the 1-kb window that is covered by recombination hotspots. Data have been collected and pre-processed by: R Campos-Sanchez, MA Cremona, A Pini, F Chiaromonte and KD Makova (2016). Integration and fixation preferences of human and mouse endogenous retroviruses uncovered with Functional Data Analysis. PLoS Computational Biology. 12(6): 1-41. Fixed ETn positions come from: Y Zhang, IA Maksakova, L Gagnier, LN van de Lagemaat, DL Mager (2008). Genome-wide assessments reveal extremely high levels of polymorphism of two active families of mouse endogenous retroviral elements. PLoS Genetics. 4: e1000007. Recombination hotspots data come from: H Brunschwig, L Levi, E Ben-David, RW Williams, B Yakir, S Shifman (2012). Fine-scale maps of recombination rates and hotspots in the mouse genome. Genetics. 191: 757-764.
description: {"references": ["Cremona, M. A., Pini, A., Cumbo, F., Makova, K. D., Chiaromonte, F., & Vantini, S. (2018). IWTomics: testing high-resolution sequence-based 'Omics' data at multiple locations and scales. Bioinformatics, 1, 3."]}
DOI: 10.5281/zenodo.1184681
title: IWTomics ETn example

description: This example contains two region datasets "ETn fixed", "Control" and one feature "Recombination hotspots content". In particular, the region dataset "ETn fixed" contains 1296 genomic regions of 64 kb surrounding fixed ETns elements (32-kb flanking sequences upstream and 32-kb flanking sequences downstream of each element). The region dataset "Control" contains 1142 regions of 64 kb without elements, used as control in the test. The regions are aligned around their center (i.e. around the ETn integration sites). Recombination hotspots measurements are associated to each "ETn fixed" and "Control" region. In particular, this feature is measured in 1-kb windows, so that each region is associated to a recombination hotspots curve made of 64 values. The measurement used is the feature content, i.e. the fraction of the 1-kb window that is covered by recombination hotspots. Data have been collected and pre-processed by: R Campos-Sanchez, MA Cremona, A Pini, F Chiaromonte and KD Makova (2016). Integration and fixation preferences of human and mouse endogenous retroviruses uncovered with Functional Data Analysis. PLoS Computational Biology. 12(6): 1-41. Fixed ETn positions come from: Y Zhang, IA Maksakova, L Gagnier, LN van de Lagemaat, DL Mager (2008). Genome-wide assessments reveal extremely high levels of polymorphism of two active families of mouse endogenous retroviral elements. PLoS Genetics. 4: e1000007. Recombination hotspots data come from: H Brunschwig, L Levi, E Ben-David, RW Williams, B Yakir, S Shifman (2012). Fine-scale maps of recombination rates and hotspots in the mouse genome. Genetics. 191: 757-764.
description: {"references": ["Cremona, M. A., Pini, A., Cumbo, F., Makova, K. D., Chiaromonte, F., & Vantini, S. (2018). IWTomics: testing high-resolution sequence-based 'Omics' data at multiple locations and scales. Bioinformatics, 1, 3."]}
DOI: 10.6084/m9.figshare.20610252
title: Honor Killing Database v.1.0

description: We developed new dataset of suspected honor killings worldwide specifically for this project. We focus on honor killings here due to their more visible nature: honor killings in particular “are intended to be public statements, to restore honour to a family, to shame individual women, and to deter other women from resisting cultural codes of family and community” (Hellgren and Hobson, 2008, p. 386). Furthermore, murders, due to their violent nature, are thought of as more serious and “newsworthy” crimes and thus more likely to be reported to the police and by the media (Marsh, 1991; Chermak, 2002, Hart and Rennison, 2003; Chermak and Gruenewald, 2006; Siegler et al., 2008; Tarling and Morris, 2010; Gruenewald et al., 2013).
DOI: 10.6084/m9.figshare.20610174
title: Figure 2.zip

description: Raw CoSMoS data related to Figure 2.
DOI: 10.6084/m9.figshare.20610174.v1
title: Figure 2.zip

description: Raw CoSMoS data related to Figure 2.
DOI: 10.6084/m9.figshare.20499906.v1
title: Soil and foliage chemistry data from Pinus radiata forests in New Zealand – S90 trial series

description: A soil and foliage chemistry dataset from the national S90 trial series located in <em>Pinus radiata</em> forests in New Zealand. The dataset underpins two existing publications by Ballard et al. (1971) and Jackson and Gifford, (1974). The dataset is made up of soil and foliage samples collected from 128 plots in mid-rotation (10-20 year old) <em>Pinus radiata</em> forests. The soil and foliage chemistry testing methods are detailed in Ballard et al. (1971). Contact: Loretta Garrett (loretta.garrett@scionresearch.com) <strong>Acknowledgments</strong> Thanks to R Ballard, DS Jackson, GM Will, and HH Gifford (New Zealand Forest Research Institute, Ltd) who did the research and publications using the data and leaving a hard copy legacy of the data that could be later shared. <strong>References</strong> Ballard, R., Jackson, D.S., and Will, G.M. (1971). Correlations between <em>Pinus radiata</em> foliage nutrient concentrations and soil tests in New Zealand. Paper presented to 15th IUFRO Congress, Section 21, Florida, 1971, 6 pp. Jackson, D.S., and Gifford, H.H. (1974). Environmental variables influencing the increment of radiata pine (1) Periodic volume increment. New Zealand Journal of Forestry Science 4, 3-26. <strong>Disclaimer</strong> We make no warranties regarding the accuracy or integrity of the Data. We accept no liability for any direct, indirect, special, consequential or other losses or damages of whatsoever kind arising out of access to, or the use of the Data. We are in no way to be held responsible for the use that you put the Data to. You rely on the Data entirely at your own risk.
DOI: 10.6084/m9.figshare.20499906
title: Soil and foliage chemistry data from Pinus radiata forests in New Zealand – S90 trial series

description: A soil and foliage chemistry dataset from the national S90 trial series located in <em>Pinus radiata</em> forests in New Zealand. The dataset underpins two existing publications by Ballard et al. (1971) and Jackson and Gifford, (1974). The dataset is made up of soil and foliage samples collected from 128 plots in mid-rotation (10-20 year old) <em>Pinus radiata</em> forests. The soil and foliage chemistry testing methods are detailed in Ballard et al. (1971). Contact: Loretta Garrett (loretta.garrett@scionresearch.com) <strong>Acknowledgments</strong> Thanks to R Ballard, DS Jackson, GM Will, and HH Gifford (New Zealand Forest Research Institute, Ltd) who did the research and publications using the data and leaving a hard copy legacy of the data that could be later shared. <strong>References</strong> Ballard, R., Jackson, D.S., and Will, G.M. (1971). Correlations between <em>Pinus radiata</em> foliage nutrient concentrations and soil tests in New Zealand. Paper presented to 15th IUFRO Congress, Section 21, Florida, 1971, 6 pp. Jackson, D.S., and Gifford, H.H. (1974). Environmental variables influencing the increment of radiata pine (1) Periodic volume increment. New Zealand Journal of Forestry Science 4, 3-26. <strong>Disclaimer</strong> We make no warranties regarding the accuracy or integrity of the Data. We accept no liability for any direct, indirect, special, consequential or other losses or damages of whatsoever kind arising out of access to, or the use of the Data. We are in no way to be held responsible for the use that you put the Data to. You rely on the Data entirely at your own risk.
DOI: 10.6084/m9.figshare.19938780
title: Development of Scanning Acoustic Microscopy System for Evaluating the Resistance Spot Welding Quality

description: Scanning acoustic microscopy (SAM) system (TSAM-400) was designed and developed for evaluating the quality of resistance spot welding (RSW) joints of 1.5 mm-thick SUS 316 stainless steel sheets under different welding parameters. Indentation and nugget information (diameter and shape) were used for evaluating the RSW quality. SAM A-scan signals were used to calculate the indentation. The nugget diameter was determined in the C-scan image. Internal information (nugget shape, splashes, and defects) was visualized in the B- and C-scan images. In addition, the spot weld area was treated to examine the surface topography effect. The nugget diameters of treated and untreated areas were measured and compared to conclude that the surface topography effect can be neglected in the quality evaluation by SAM system. By implementing TSAM-400, some specimens were successfully tested with a scanning area of 55 × 15 mm<sup>2</sup>, and a scanning time of 33.5 s corresponding to a B-scan frame rate of 4.5 Hz, and a resolution of 0.1 × 0.1 mm<sup>2</sup>. Finally, the good input parameters for welding two 1.5 mm-thick SUS 316 were determined by analyzing the results from TSAM-400.