cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5517/ccdc.csd.cc2987lf
title: CCDC 2123084: Experimental Crystal Structure Determination

description: Related Article: Zhenxing Cong, Mengmeng Han, Yuanyuan Fan, Yunhao Fan, Kai Chang, Leyi Xiao, Yufeng Zhang, Xu Zhen, Qianqian Li, Zhen Li|2022|Mater. Chem. Front.|6|1606|doi:10.1039/D2QM00284A
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.cc2987mg
title: CCDC 2123085: Experimental Crystal Structure Determination

description: Related Article: Zhenxing Cong, Mengmeng Han, Yuanyuan Fan, Yunhao Fan, Kai Chang, Leyi Xiao, Yufeng Zhang, Xu Zhen, Qianqian Li, Zhen Li|2022|Mater. Chem. Front.|6|1606|doi:10.1039/D2QM00284A
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.cc29x8zh
title: CCDC 2142347: Experimental Crystal Structure Determination

description: Related Article: Eugene A. Katlenok, Anton V. Rozhkov, Ruslan R. Ramazanov, Rashid R. Valiev, Oleg V. Levin, Dmitrii O. Goryachiy, Ilya V. Taydakov, Maxim L. Kuznetsov, Vadim Yu Kukushkin|2022|Inorg.Chem.|61|8670|doi:10.1021/acs.inorgchem.2c00321
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.20092316
title: Gene sequences for beta-tubulin, calmodulin and 28S: Aspergillus luchuensis Strain C7

description: This data contains the DNA sequences of beta-tubulin, calmodulin, and 28S-rRNA in Aspergillus luchuensis Strain C7, used for phylogenetic reconstruction and taxonomic analysis of the strain. <br> Also, a concatenated alignment of these genes with closet phylogenetic neighbors is available for reproducibility. <br> All files are in _txt_ format and they are easily readable with any plain text reader.
DOI: 10.6084/m9.figshare.20092316.v1
title: Gene sequences for beta-tubulin, calmodulin and 28S: Aspergillus luchuensis Strain C7

description: This data contains the DNA sequences of beta-tubulin, calmodulin, and 28S-rRNA in Aspergillus luchuensis Strain C7, used for phylogenetic reconstruction and taxonomic analysis of the strain. <br> Also, a concatenated alignment of these genes with closet phylogenetic neighbors is available for reproducibility. <br> All files are in _txt_ format and they are easily readable with any plain text reader.
DOI: 10.5281/zenodo.6657526
title: Gallinago gallinago decontaminated gx

description: .
DOI: 10.5281/zenodo.6657525
title: Gallinago gallinago decontaminated gx

description: .
DOI: 10.5281/zenodo.6656847
title: Promoting extinction or minimizing growth? The impact of treatment on trait trajectories in evolving populations - Data

description: This is the dataset used in the manuscript "Promoting extinction or minimizing growth? The impact of treatment on trait trajectories in evolving populations" by Raatz &Traulsen. The code used to generate the data can be found at https://doi.org/10.5281/zenodo.6656842.
DOI: 10.5281/zenodo.6656846
title: Promoting extinction or minimizing growth? The impact of treatment on trait trajectories in evolving populations - Data

description: This is the dataset used in the manuscript "Promoting extinction or minimizing growth? The impact of treatment on trait trajectories in evolving populations" by Raatz &Traulsen. The code used to generate the data can be found at https://doi.org/10.5281/zenodo.6656842.
DOI: 10.21985/n2-jqgh-5e96
title: test
DOI: 10.13020/146x-1412
title: Historical National Boundaries

description: Historical National Boundaries displays global national boundaries for the following dates in history: 1800, 1914, 1918, 1939, 1945, 1970, 1990, 2000. Boundary changes associated with World War I (1914 - 1918) and World War II (1939 - 1945) can be viewed by turning off all other layers and toggling between the two. Data for each layer comes from a variety of sources, including historical atlases and the Library of Congress website - https://www.loc.gov/maps/.
DOI: 10.34681/mp5j-sp45
title: Family Structure and Functioning in Neglectful Families, 1991-1993

description: This study identifies differences in family structure and functioning between neglectful and similarly situated (low income) non-neglectful families. The study specifically looks at: the relationship between family coping skills (e.g., problem solving, conflict resolution, communication, emotional expressiveness, cohesion, leadership, use of power, negotiation) and adequacy of parenting, the relationship between drug and alcohol abuse and neglectful parenting the role that men play in neglectful and non-neglectful families. The investigator also looked at the effects of race, chronicity of neglect, and personality factors. Study participants were recruited from the Georgia Department of Family and Children's Services by caseworkers who found them to meet NIS-2 definitions of neglect, were verified as neglectful upon investigation, and had at least one child between the ages of 5 and 18 living at home. Similarly situated families who had not been reported for neglect or abuse were selected from those same counties for a matched control group. Data collection efforts involved: caseworker interviews, home administered questionnaires, home interviews of 103 neglect and 102 control families, in-home videotaped interactions of 92 neglect and 95 control families, and follow-up interviews in some cases.
DOI: 10.34681/gam0-q535
title: National Family Violence Survey, 1976

description: This study was conducted in 1976 at the University of New Hampshire. 2,134 respondents were interviewed in a nationwide sample of 960 males and 1,183 females. The purpose of the study was to ascertain methods of conflict resolution within the family. Information was gathered regarding the following areas: resolution of conflicts between spouses and between parents and children, including detailed information on the development of conflicts resulting in violence, resolution of conflicts in respondent's childhood family, family power structure, marital closeness and stability, personality, and stress factors.
DOI: 10.6084/m9.figshare.20092529
title: Dataset: Can leading a physically active and healthy lifestyle prevent gaining the freshman 15?

description: Weight measurements for N = 525 freshmen students at Oral Roberts University. Weight change measured at 6 months and 12 month intervals. Male encoded as 1, female as 0.
DOI: 10.5281/zenodo.6652343
title: SuperDARN data in netCDF format (2019-Nov)

description: 2019-Nov SuperDARN radar data in netCDF format. These files were produced using versions 2.5 and 3.0 of the public FitACF algorithm, using the AACGM v2 coordinate system. Cite this dataset if using our data in a publication.The RST is available here: https://github.com/SuperDARN/rstThe research enabled by SuperDARN is due to the efforts of teams of scientists and engineers working in many countries to build and operate radars, process data and provide access, develop and improve data products, and assist users in interpretation. Users of SuperDARN data and data products are asked to acknowledge this support in presentations and publications. A brief statement on how to acknowledge use of SuperDARN data is provided below.Users are also asked to consult with a SuperDARN PI prior to submission of work intended for publication. A listing of radars and PIs with contact information can be found here: (SuperDARN Radar Overview)<strong>Recommended form of acknowledgement for the use of SuperDARN data:</strong>'The authors acknowledge the use of SuperDARN data. SuperDARN is a collection of radars funded by national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, Norway, South Africa, United Kingdom and the United States of America.'
DOI: 10.5281/zenodo.6653266
title: SuperDARN data in netCDF format (2019-Oct)

description: 2019-Oct SuperDARN radar data in netCDF format. These files were produced using versions 2.5 and 3.0 of the public FitACF algorithm, using the AACGM v2 coordinate system. Cite this dataset if using our data in a publication.The RST is available here: https://github.com/SuperDARN/rstThe research enabled by SuperDARN is due to the efforts of teams of scientists and engineers working in many countries to build and operate radars, process data and provide access, develop and improve data products, and assist users in interpretation. Users of SuperDARN data and data products are asked to acknowledge this support in presentations and publications. A brief statement on how to acknowledge use of SuperDARN data is provided below.Users are also asked to consult with a SuperDARN PI prior to submission of work intended for publication. A listing of radars and PIs with contact information can be found here: (SuperDARN Radar Overview)<strong>Recommended form of acknowledgement for the use of SuperDARN data:</strong>'The authors acknowledge the use of SuperDARN data. SuperDARN is a collection of radars funded by national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, Norway, South Africa, United Kingdom and the United States of America.'
DOI: 10.5281/zenodo.6652120
title: SuperDARN data in netCDF format (2019-Dec)

description: 2019-Dec SuperDARN radar data in netCDF format. These files were produced using versions 2.5 and 3.0 of the public FitACF algorithm, using the AACGM v2 coordinate system. Cite this dataset if using our data in a publication.The RST is available here: https://github.com/SuperDARN/rstThe research enabled by SuperDARN is due to the efforts of teams of scientists and engineers working in many countries to build and operate radars, process data and provide access, develop and improve data products, and assist users in interpretation. Users of SuperDARN data and data products are asked to acknowledge this support in presentations and publications. A brief statement on how to acknowledge use of SuperDARN data is provided below.Users are also asked to consult with a SuperDARN PI prior to submission of work intended for publication. A listing of radars and PIs with contact information can be found here: (SuperDARN Radar Overview)<strong>Recommended form of acknowledgement for the use of SuperDARN data:</strong>'The authors acknowledge the use of SuperDARN data. SuperDARN is a collection of radars funded by national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, Norway, South Africa, United Kingdom and the United States of America.'
DOI: 10.5281/zenodo.6654686
title: SuperDARN data in netCDF format (2019-Mar)

description: 2019-Mar SuperDARN radar data in netCDF format. These files were produced using versions 2.5 and 3.0 of the public FitACF algorithm, using the AACGM v2 coordinate system. Cite this dataset if using our data in a publication.The RST is available here: https://github.com/SuperDARN/rstThe research enabled by SuperDARN is due to the efforts of teams of scientists and engineers working in many countries to build and operate radars, process data and provide access, develop and improve data products, and assist users in interpretation. Users of SuperDARN data and data products are asked to acknowledge this support in presentations and publications. A brief statement on how to acknowledge use of SuperDARN data is provided below.Users are also asked to consult with a SuperDARN PI prior to submission of work intended for publication. A listing of radars and PIs with contact information can be found here: (SuperDARN Radar Overview)<strong>Recommended form of acknowledgement for the use of SuperDARN data:</strong>'The authors acknowledge the use of SuperDARN data. SuperDARN is a collection of radars funded by national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, Norway, South Africa, United Kingdom and the United States of America.'
DOI: 10.5281/zenodo.6653972
title: SuperDARN data in netCDF format (2019-Aug)

description: 2019-Aug SuperDARN radar data in netCDF format. These files were produced using versions 2.5 and 3.0 of the public FitACF algorithm, using the AACGM v2 coordinate system. Cite this dataset if using our data in a publication.The RST is available here: https://github.com/SuperDARN/rstThe research enabled by SuperDARN is due to the efforts of teams of scientists and engineers working in many countries to build and operate radars, process data and provide access, develop and improve data products, and assist users in interpretation. Users of SuperDARN data and data products are asked to acknowledge this support in presentations and publications. A brief statement on how to acknowledge use of SuperDARN data is provided below.Users are also asked to consult with a SuperDARN PI prior to submission of work intended for publication. A listing of radars and PIs with contact information can be found here: (SuperDARN Radar Overview)<strong>Recommended form of acknowledgement for the use of SuperDARN data:</strong>'The authors acknowledge the use of SuperDARN data. SuperDARN is a collection of radars funded by national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, Norway, South Africa, United Kingdom and the United States of America.'
DOI: 10.5281/zenodo.6654835
title: SuperDARN data in netCDF format (2019-Feb)

description: 2019-Feb SuperDARN radar data in netCDF format. These files were produced using versions 2.5 and 3.0 of the public FitACF algorithm, using the AACGM v2 coordinate system. Cite this dataset if using our data in a publication.The RST is available here: https://github.com/SuperDARN/rstThe research enabled by SuperDARN is due to the efforts of teams of scientists and engineers working in many countries to build and operate radars, process data and provide access, develop and improve data products, and assist users in interpretation. Users of SuperDARN data and data products are asked to acknowledge this support in presentations and publications. A brief statement on how to acknowledge use of SuperDARN data is provided below.Users are also asked to consult with a SuperDARN PI prior to submission of work intended for publication. A listing of radars and PIs with contact information can be found here: (SuperDARN Radar Overview)<strong>Recommended form of acknowledgement for the use of SuperDARN data:</strong>'The authors acknowledge the use of SuperDARN data. SuperDARN is a collection of radars funded by national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, Norway, South Africa, United Kingdom and the United States of America.'
DOI: 10.5281/zenodo.6654247
title: SuperDARN data in netCDF format (2019-Jul)

description: 2019-Jul SuperDARN radar data in netCDF format. These files were produced using versions 2.5 and 3.0 of the public FitACF algorithm, using the AACGM v2 coordinate system. Cite this dataset if using our data in a publication.The RST is available here: https://github.com/SuperDARN/rstThe research enabled by SuperDARN is due to the efforts of teams of scientists and engineers working in many countries to build and operate radars, process data and provide access, develop and improve data products, and assist users in interpretation. Users of SuperDARN data and data products are asked to acknowledge this support in presentations and publications. A brief statement on how to acknowledge use of SuperDARN data is provided below.Users are also asked to consult with a SuperDARN PI prior to submission of work intended for publication. A listing of radars and PIs with contact information can be found here: (SuperDARN Radar Overview)<strong>Recommended form of acknowledgement for the use of SuperDARN data:</strong>'The authors acknowledge the use of SuperDARN data. SuperDARN is a collection of radars funded by national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, Norway, South Africa, United Kingdom and the United States of America.'
DOI: 10.5281/zenodo.6654428
title: SuperDARN data in netCDF format (2019-Jun)

description: 2019-Jun SuperDARN radar data in netCDF format. These files were produced using versions 2.5 and 3.0 of the public FitACF algorithm, using the AACGM v2 coordinate system. Cite this dataset if using our data in a publication.The RST is available here: https://github.com/SuperDARN/rstThe research enabled by SuperDARN is due to the efforts of teams of scientists and engineers working in many countries to build and operate radars, process data and provide access, develop and improve data products, and assist users in interpretation. Users of SuperDARN data and data products are asked to acknowledge this support in presentations and publications. A brief statement on how to acknowledge use of SuperDARN data is provided below.Users are also asked to consult with a SuperDARN PI prior to submission of work intended for publication. A listing of radars and PIs with contact information can be found here: (SuperDARN Radar Overview)<strong>Recommended form of acknowledgement for the use of SuperDARN data:</strong>'The authors acknowledge the use of SuperDARN data. SuperDARN is a collection of radars funded by national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, Norway, South Africa, United Kingdom and the United States of America.'
DOI: 10.5281/zenodo.6654539
title: SuperDARN data in netCDF format (2019-May)

description: 2019-May SuperDARN radar data in netCDF format. These files were produced using versions 2.5 and 3.0 of the public FitACF algorithm, using the AACGM v2 coordinate system. Cite this dataset if using our data in a publication.The RST is available here: https://github.com/SuperDARN/rstThe research enabled by SuperDARN is due to the efforts of teams of scientists and engineers working in many countries to build and operate radars, process data and provide access, develop and improve data products, and assist users in interpretation. Users of SuperDARN data and data products are asked to acknowledge this support in presentations and publications. A brief statement on how to acknowledge use of SuperDARN data is provided below.Users are also asked to consult with a SuperDARN PI prior to submission of work intended for publication. A listing of radars and PIs with contact information can be found here: (SuperDARN Radar Overview)<strong>Recommended form of acknowledgement for the use of SuperDARN data:</strong>'The authors acknowledge the use of SuperDARN data. SuperDARN is a collection of radars funded by national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, Norway, South Africa, United Kingdom and the United States of America.'
DOI: 10.5281/zenodo.6655021
title: SuperDARN data in netCDF format (2019-Jan)

description: 2019-Jan SuperDARN radar data in netCDF format. These files were produced using versions 2.5 and 3.0 of the public FitACF algorithm, using the AACGM v2 coordinate system. Cite this dataset if using our data in a publication.The RST is available here: https://github.com/SuperDARN/rstThe research enabled by SuperDARN is due to the efforts of teams of scientists and engineers working in many countries to build and operate radars, process data and provide access, develop and improve data products, and assist users in interpretation. Users of SuperDARN data and data products are asked to acknowledge this support in presentations and publications. A brief statement on how to acknowledge use of SuperDARN data is provided below.Users are also asked to consult with a SuperDARN PI prior to submission of work intended for publication. A listing of radars and PIs with contact information can be found here: (SuperDARN Radar Overview)<strong>Recommended form of acknowledgement for the use of SuperDARN data:</strong>'The authors acknowledge the use of SuperDARN data. SuperDARN is a collection of radars funded by national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, Norway, South Africa, United Kingdom and the United States of America.'
DOI: 10.5281/zenodo.6633650
title: SuperDARN data in netCDF format (2005-Oct)

description: 2005-Oct SuperDARN radar data in netCDF format. These files were produced using versions 2.5 and 3.0 of the public FitACF algorithm, using the AACGM v2 coordinate system. Cite this dataset if using our data in a publication.The RST is available here: https://github.com/SuperDARN/rstThe research enabled by SuperDARN is due to the efforts of teams of scientists and engineers working in many countries to build and operate radars, process data and provide access, develop and improve data products, and assist users in interpretation. Users of SuperDARN data and data products are asked to acknowledge this support in presentations and publications. A brief statement on how to acknowledge use of SuperDARN data is provided below.Users are also asked to consult with a SuperDARN PI prior to submission of work intended for publication. A listing of radars and PIs with contact information can be found here: (SuperDARN Radar Overview)<strong>Recommended form of acknowledgement for the use of SuperDARN data:</strong>'The authors acknowledge the use of SuperDARN data. SuperDARN is a collection of radars funded by national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, Norway, South Africa, United Kingdom and the United States of America.'
DOI: 10.5281/zenodo.6654644
title: SuperDARN data in netCDF format (2019-Apr)

description: 2019-Apr SuperDARN radar data in netCDF format. These files were produced using versions 2.5 and 3.0 of the public FitACF algorithm, using the AACGM v2 coordinate system. Cite this dataset if using our data in a publication.The RST is available here: https://github.com/SuperDARN/rstThe research enabled by SuperDARN is due to the efforts of teams of scientists and engineers working in many countries to build and operate radars, process data and provide access, develop and improve data products, and assist users in interpretation. Users of SuperDARN data and data products are asked to acknowledge this support in presentations and publications. A brief statement on how to acknowledge use of SuperDARN data is provided below.Users are also asked to consult with a SuperDARN PI prior to submission of work intended for publication. A listing of radars and PIs with contact information can be found here: (SuperDARN Radar Overview)<strong>Recommended form of acknowledgement for the use of SuperDARN data:</strong>'The authors acknowledge the use of SuperDARN data. SuperDARN is a collection of radars funded by national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, Norway, South Africa, United Kingdom and the United States of America.'