cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/39b34nz3h9.1
title: Data for: The Effect of Rich-Oxygen Microwave Leaching of Extracting Vanadium from Converter Vanadium Slag

description: In this paper, the comparison of microwave heating leaching (MHL) and electric heating leaching (EHL) and the mechanism of rich-oxygen microwave leaching of extracting vanadium from converter vanadium slag were investigated. The comparative studies of leaching showed that the vanadium leaching ratio reached 45.76% in 20 min using EHL, but it can reached 95.78% under the same condition of MHL. The MHL mechanism analysis by XRD and SEM showed that the decomposition of the spinel in the converter vanadium slag can be accelerated by the MHL. In addition, the MHL can reduce the granularity and also make the surface of particles become more porous. In general, the leaching of converter vanadium slag by MHL is much more effective than that of EHL in the pressure leaching process. The kinetic studies of MHL and EHL showed that the activation energy of vanadium MHL and EHL were determined to be 15.57 and 48.53 kJ/mol, respectively. The MHL process followed the diffusion control and the EHL process was controlled by chemical reaction. The results showed that the MHL can shorten the process time, improve the productivity, reduce the cost and improve the product quality. Therefore, MHL of converter vanadium slag is an green production technology ensuring economy and feasibility.
DOI: 10.5517/ccdc.csd.cc12dtw5
title: CCDC 995437: Experimental Crystal Structure Determination

description: Related Article: Ranjeesh Thenarukandiyil, Babulal Maji, Joyanta Choudhury|2019|Inorg.Chim.Acta|487|419|doi:10.1016/j.ica.2019.01.002
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.cc1ntdd8
title: CCDC 1543750: Experimental Crystal Structure Determination

description: Related Article: Saul H. Lapidus, Adora G. Graham, Christopher M Kareis, Casey G. Hawkins, Peter W. Stephens, Joel S. Miller|2018|J.Am.Chem.Soc.|141|911|doi:10.1021/jacs.8b10638
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.cc1ntdf9
title: CCDC 1543751: Experimental Crystal Structure Determination

description: Related Article: Saul H. Lapidus, Adora G. Graham, Christopher M Kareis, Casey G. Hawkins, Peter W. Stephens, Joel S. Miller|2018|J.Am.Chem.Soc.|141|911|doi:10.1021/jacs.8b10638
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.cc1ntdgb
title: CCDC 1543752: Experimental Crystal Structure Determination

description: Related Article: Saul H. Lapidus, Adora G. Graham, Christopher M Kareis, Casey G. Hawkins, Peter W. Stephens, Joel S. Miller|2018|J.Am.Chem.Soc.|141|911|doi:10.1021/jacs.8b10638
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.2531609
title: Dataset for "Depletion-induced seismicity at the Groningen gas field: Coulomb rate-and-state models including differential compaction effect"

description: Data package used for the article of Candela et al. : “Depletion-induced seismicity at the Groningen gas field: Coulomb rate-and-state models including differential compaction effect”.
DOI: 10.5281/zenodo.2531660
title: Scenario divergence of sea level rise

description: This file contains the underlying dataset for figures in Hinkel et al. (in review). The dataset contains probability density functions of mean and extreme sea level for a set of tide gauges from Gesla-2 (Woodworth et al., 2017) for projected regional sea level rise from two emission scenarios RCP2.6 and 8.5 as presented in the IPCC-AR5 report (Church et al., 2013). Based on the temporal change in overlap of the pdfs for both scenarios, a year of divergence is diagnosed for each tide gauge station.
DOI: 10.5281/zenodo.2531661
title: Scenario divergence of sea level rise

description: This file contains the underlying dataset for figures in Hinkel et al. (in review). The dataset contains probability density functions of mean and extreme sea level for a set of tide gauges from Gesla-2 (Woodworth et al., 2017) for projected regional sea level rise from two emission scenarios RCP2.6 and 8.5 as presented in the IPCC-AR5 report (Church et al., 2013). Based on the temporal change in overlap of the pdfs for both scenarios, a year of divergence is diagnosed for each tide gauge station.
DOI: 10.5523/bris.10i96zb8gm0j81yz0q6ztei23d
title: Genome-wide association study of lifetime smoking index in a sample of 462,690 individuals from the UK Biobank

description: This study is a genome-wide association study (GWAS) of lifetime smoking index (a composite of smoking initiation, heaviness, duration and cessation) in a sample of 462,690 individuals (both smokers and non-smokers) from the UK Biobank. This identified 126 genome-wide significant, independent SNPS.
DOI: 10.21415/mwat-d323
title: FluencyBank CSAL Corpus
DOI: 10.5517/ccdc.csd.cc1pl1s3
title: CCDC 1566485: Experimental Crystal Structure Determination

description: Related Article: Andrey N. Usoltsev, Moneim Elshobaki, Sergey A. Adonin, Lyubov A. Frolova, Tatiyana Derzhavskaya, Pavel A. Abramov, Denis V. Anokhin, Ilya V. Korolkov, Sergey Yu. Luchkin, Nadezhda N. Dremova, Keith J. Stevenson, Maxim N. Sokolov, Vladimir P. Fedin, Pavel A. Troshin|2019|J.Mater.Chem.A|7|5957|doi:10.1039/C8TA09204D
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.cc1pl1t4
title: CCDC 1566486: Experimental Crystal Structure Determination

description: Related Article: Andrey N. Usoltsev, Moneim Elshobaki, Sergey A. Adonin, Lyubov A. Frolova, Tatiyana Derzhavskaya, Pavel A. Abramov, Denis V. Anokhin, Ilya V. Korolkov, Sergey Yu. Luchkin, Nadezhda N. Dremova, Keith J. Stevenson, Maxim N. Sokolov, Vladimir P. Fedin, Pavel A. Troshin|2019|J.Mater.Chem.A|7|5957|doi:10.1039/C8TA09204D
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.cc1pl1v5
title: CCDC 1566487: Experimental Crystal Structure Determination

description: Related Article: Andrey N. Usoltsev, Moneim Elshobaki, Sergey A. Adonin, Lyubov A. Frolova, Tatiyana Derzhavskaya, Pavel A. Abramov, Denis V. Anokhin, Ilya V. Korolkov, Sergey Yu. Luchkin, Nadezhda N. Dremova, Keith J. Stevenson, Maxim N. Sokolov, Vladimir P. Fedin, Pavel A. Troshin|2019|J.Mater.Chem.A|7|5957|doi:10.1039/C8TA09204D
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.cc1pl1w6
title: CCDC 1566488: Experimental Crystal Structure Determination

description: Related Article: Andrey N. Usoltsev, Moneim Elshobaki, Sergey A. Adonin, Lyubov A. Frolova, Tatiyana Derzhavskaya, Pavel A. Abramov, Denis V. Anokhin, Ilya V. Korolkov, Sergey Yu. Luchkin, Nadezhda N. Dremova, Keith J. Stevenson, Maxim N. Sokolov, Vladimir P. Fedin, Pavel A. Troshin|2019|J.Mater.Chem.A|7|5957|doi:10.1039/C8TA09204D
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.cc1pl1x7
title: CCDC 1566489: Experimental Crystal Structure Determination

description: Related Article: Andrey N. Usoltsev, Moneim Elshobaki, Sergey A. Adonin, Lyubov A. Frolova, Tatiyana Derzhavskaya, Pavel A. Abramov, Denis V. Anokhin, Ilya V. Korolkov, Sergey Yu. Luchkin, Nadezhda N. Dremova, Keith J. Stevenson, Maxim N. Sokolov, Vladimir P. Fedin, Pavel A. Troshin|2019|J.Mater.Chem.A|7|5957|doi:10.1039/C8TA09204D
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.cc1pl1y8
title: CCDC 1566490: Experimental Crystal Structure Determination

description: Related Article: Andrey N. Usoltsev, Moneim Elshobaki, Sergey A. Adonin, Lyubov A. Frolova, Tatiyana Derzhavskaya, Pavel A. Abramov, Denis V. Anokhin, Ilya V. Korolkov, Sergey Yu. Luchkin, Nadezhda N. Dremova, Keith J. Stevenson, Maxim N. Sokolov, Vladimir P. Fedin, Pavel A. Troshin|2019|J.Mater.Chem.A|7|5957|doi:10.1039/C8TA09204D
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.cc1z184f
title: CCDC 1818464: Experimental Crystal Structure Determination

description: Related Article: Yue Yu, Ruiyang Zhao, Changjiang Zhou, Xiaoyi Sun, Shizhao Wang, Yu Gao, Weijun Li, Ping Lu, Bing Yang, Cheng Zhang|2019|Chem.Commun.|55|977|doi:10.1039/C8CC08558G
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.cc1z186h
title: CCDC 1818466: Experimental Crystal Structure Determination

description: Related Article: Yue Yu, Ruiyang Zhao, Changjiang Zhou, Xiaoyi Sun, Shizhao Wang, Yu Gao, Weijun Li, Ping Lu, Bing Yang, Cheng Zhang|2019|Chem.Commun.|55|977|doi:10.1039/C8CC08558G
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.cc202w66
title: CCDC 1849807: Experimental Crystal Structure Determination

description: Related Article: Louis Frentzel-Beyme, Marvin Kloß, Roman Pallach, Soma Salamon, Henning Moldenhauer, Joachim Landers, Heiko Wende, Jörg Debus, Sebastian Henke|2019|J.Mater.Chem.A|7|985|doi:10.1039/C8TA08016J
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.cc2brs30
title: CCDC 2167802: Experimental Crystal Structure Determination

description: Related Article: Shisi Tang, Jiayu Xu, Xu Liu, Yan Zhu|2022|Chem.-Eur.J.|28|e202201262|doi:10.1002/chem.202201262
description: Related Article: Shisi Tang|2024|CSD Communication|||
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.cc2c1v09
title: CCDC 2176510: Experimental Crystal Structure Determination

description: Related Article: Jie Tang[a][f] , Chong Liu[b] , Chenyu Zhu[a] , Keju Sun[c] , He Wang[a], Wen Yin[a] , Chuting Xu[d], Yang Li[d] ,  Weiguo Wang[d] , Li Wang[e] , Renan Wu[e] , Chao Liu* [a], and Jiahui Huang* [a]|2022|CSD Communication|||
description: Related Article: Jie Tang, Chong Liu, Chenyu Zhu, Keju Sun, He Wang, Wen Yin, Chuting Xu, Yang Li, Weiguo Wang, Li Wang, Renan Wu, Chao Liu, Jiahui Huang|2023|Nanoscale|15|2843|doi:10.1039/D2NR05921E
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.cc2c9w1m
title: CCDC 2184230: Experimental Crystal Structure Determination

description: Related Article: Haley M. Carlson, Sydney R. Smith, R. Adam Mosey|2024|J.Org.Chem.|89|1160|doi:10.1021/acs.joc.3c02334
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.10565384
title: Dataset for the Active-Learning Global Optimization of Ni-Ceria Nanoparticles

description: Dataset to perform the active learning global optimization of the following Ni-Ceria nanoparticles CeNi3O5, Ce2Ni2O6 and Ce3NiO7. The zip file contains three main folders with the regression datasets, input files, and scripts used for each of the methods discussed on the manuscript "Active-Learning for Global Optimization of Ni-Ceria Nanoparticles: The case of Ce4-xNixO8-x (x=1,2,3)" submitted to the Journal of Computational Chemistry.

Please feel free to contact me at lizandra.barriosherr@ucalgary.ca for questions related to the use of this dataset and scripts.
DOI: 10.5281/zenodo.10565385
title: Dataset for the Active-Learning Global Optimization of Ni-Ceria Nanoparticles

description: Dataset to perform the active learning global optimization of the following Ni-Ceria nanoparticles CeNi3O5, Ce2Ni2O6 and Ce3NiO7. The zip file contains three main folders with the regression datasets, input files, and scripts used for each of the methods discussed on the manuscript "Active-Learning for Global Optimization of Ni-Ceria Nanoparticles: The case of Ce4-xNixO8-x (x=1,2,3)" submitted to the Journal of Computational Chemistry.

Please feel free to contact me at lizandra.barriosherr@ucalgary.ca for questions related to the use of this dataset and scripts.
DOI: 10.17615/ykbw-cb47
title: Session Laws Passed by the North Carolina General Assembly During 1866/67-1967, Identified by Machine Learning as Laws Likely to be Jim Crow Laws (plain text format, single file) version 2

description: This corpus was created for a text analysis project called On the Books: Jim Crow and Algorithms of Resistance. On the Books focused specifically on the laws passed during the Jim Crow Era, which is defined for this project as the period between Reconstruction and the Civil Rights Movement (1866-1967). In addition to creating the corpus, the project also used machine learning to identify discoverable North Carolina segregation statutes during the Jim Crow era. This corpus contains all of the laws identified as those likely to be Jim Crow laws in a single file in plain text format. This is version 2 of the data. This work is licensed under a Creative Commons Attribution non-commercial 3.0 license: https://creativecommons.org/licenses/by-nc/3.0/
DOI: 10.17615/ek4q-hd91
title: Session Laws Passed by the North Carolina General Assembly During 1866/67-1967, Identified by Machine Learning as Laws Likely to be Jim Crow Laws (plain text format) version 2

description: This corpus was created for a text analysis project called On the Books: Jim Crow and Algorithms of Resistance. On the Books focused specifically on the laws passed during the Jim Crow Era, which is defined for this project as the period between Reconstruction and the Civil Rights Movement (1866-1967). In addition to creating the corpus, the project also used machine learning to identify discoverable North Carolina segregation statutes during the Jim Crow era. This corpus contains all of the laws identified as those likely to be Jim Crow laws in a single file in plain text format. This is version 2 of the data. This work is licensed under a Creative Commons Attribution non-commercial 3.0 license: https://creativecommons.org/licenses/by-nc/3.0/
DOI: 10.17615/nrzm-p576
title: Session Laws Passed by the North Carolina General Assembly During 1866/67-1967, Identified by Machine Learning as Laws Likely to be Jim Crow Laws (XML format) version 2

description: This corpus was created for a text analysis project called On the Books: Jim Crow and Algorithms of Resistance. On the Books focused specifically on the laws passed during the Jim Crow Era, which is defined for this project as the period between Reconstruction and the Civil Rights Movement (1866-1967). In addition to creating the corpus, the project also used machine learning to identify discoverable North Carolina segregation statutes during the Jim Crow era. This corpus contains all of the laws identified as those likely to be Jim Crow laws in a single file in plain text format. This is version 2 of the data. This work is licensed under a Creative Commons Attribution non-commercial 3.0 license: https://creativecommons.org/licenses/by-nc/3.0/
DOI: 10.17615/rhqn-aq45
title: Session Laws Passed by the North Carolina General Assembly During 1866/67-1967 (plain text format) version 2

description: This corpus was created for a text analysis project called On the Books: Jim Crow and Algorithms of Resistance. On the Books focused specifically on the laws passed during the Jim Crow Era, which is defined for this project as the period between Reconstruction and the Civil Rights Movement (1866-1967). In addition to creating the corpus, the project also used machine learning to identify discoverable North Carolina segregation statutes during the Jim Crow era. This corpus contains all of the laws identified as those likely to be Jim Crow laws in a single file in plain text format. This is version 2 of the data. This work is licensed under a Creative Commons Attribution non-commercial 3.0 license: https://creativecommons.org/licenses/by-nc/3.0/
DOI: 10.17615/r18t-wp92
title: Session Laws Passed by the North Carolina General Assembly During 1866/67-1967 (XML format) version 2

description: This corpus was created for a text analysis project called On the Books: Jim Crow and Algorithms of Resistance. On the Books focused specifically on the laws passed during the Jim Crow Era, which is defined for this project as the period between Reconstruction and the Civil Rights Movement (1866-1967). In addition to creating the corpus, the project also used machine learning to identify discoverable North Carolina segregation statutes during the Jim Crow era. This corpus contains all of the laws identified as those likely to be Jim Crow laws in a single file in plain text format. This is version 2 of the data. This work is licensed under a Creative Commons Attribution non-commercial 3.0 license: https://creativecommons.org/licenses/by-nc/3.0/
DOI: 10.17615/36y2-0y50
title: On the Books Training Set

description: This file is the training set that was used to train an algorithm to identify Jim Crow laws. It contains laws that are labeled as "Jim Crow" (jim_crow=1) or "Not Jim Crow" (jim_crow=0). The source of the determination is also provided.
DOI: 10.17615/drgb-b583
title: Codes and Datasets for paper “After Desperate Times, Still a Desperate Measure?: Pandemic and Post-Pandemic Engagement with Preprints in the Biology and Health Science Fields" Master's Paper

description: These codes and datasets are part of the master’s paper “After Desperate Times, Still a Desperate Measure?: Pandemic and Post-Pandemic Engagement with Preprints in the Biology and Health Science Fields.” These code and datasets inform visualization and analyses about the number of preprint manuscripts on two preprint servers, bioRxiv and medRxiv. The code and datasets also inform visualizations and analyses about attention to and trust of the preprints on these servers. Although the datasets contain some data from November 2013 – June 2018, the focus of the codes is the data from July 2018 – December 2022. 

The folder contains datasets: 
•	Identifying metadata for the preprints posted November 2013 – December 2022 (folder data/contributions).
•	Identifying the number of times per month each preprint’s abstract was viewed and the number of times per month each full-text PDF for each preprint was downloaded, for each month that each preprint was available online (folder data/usage). 

The folder contains codes for:  
•	Downloading metadata for preprints (preprint_details.Rmd)
•	Downloading usage statistics for preprints (preprint_usage_first_adaptation.Rmd, preprint_usage_second_adaptation_use.Rmd) 
•	Cleaning usage statistics for preprints (identifying_missing_preprints_from_download_w_altmetricsdimensions.Rmd, preprint_usage_second_adaptation_use.Rmd)
•	Downloading citations to preprints using the Dimensions Analytics API (preprint_citations.ipynyb)
•	Creating figures to visualize the data (figures.Rmd) 
•	Statistical tests to analyze the data (statistical_analyses.Rmd)

The folder also contains notes about downloading data about citations to and altmetric citations to the preprints, although this data could not be shared publicly.