cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.25403/upresearchdata.23684628.v1
title: Demographic, farm characteristics, crop improvements and profitability levels at Exchange Irrigation Scheme

description: Dataset for a dissertation titled' Impact of smallholder irrigation revitalisation programme on the Exchange Irrigation Scheme in Kwekwe district, Zimbabwe'. Chapter 1 dataset focused on the components and sub-components of the Smallholder Irrigation Revitalisation Programme (SIRP). Chapter 3 dataset focused on the Exchange Irrigation Scheme map and the selection of the sample size and stakeholders for focus group discussions. The data summarises the number of irrigators who were sampled from each of the four irrigation blocks using a multi-stage cluster sampling procedure (using proportionate and simple random sampling methods). A total of 134 irrigators, were sampled from a sampling frame of 982 scheme beneficiaries. On the other hand, a total of 25 stakeholders were chosen for focus group discussions. Chapter 4 dataset presented figures on the demographic characteristics and farm characteristics as well as the level of satisfaction with the services that were offered by SIRP. The challenges faced at the Exchange Irrigation Scheme as well as the target market were presented in chapter 5 dataset. The crop improvements and profitability levels were also presented in the same dataset.
DOI: 10.25403/upresearchdata.23684628
title: Demographic, farm characteristics, crop improvements and profitability levels at Exchange Irrigation Scheme

description: Dataset for a dissertation titled' Impact of smallholder irrigation revitalisation programme on the Exchange Irrigation Scheme in Kwekwe district, Zimbabwe'. Chapter 1 dataset focused on the components and sub-components of the Smallholder Irrigation Revitalisation Programme (SIRP). Chapter 3 dataset focused on the Exchange Irrigation Scheme map and the selection of the sample size and stakeholders for focus group discussions. The data summarises the number of irrigators who were sampled from each of the four irrigation blocks using a multi-stage cluster sampling procedure (using proportionate and simple random sampling methods). A total of 134 irrigators, were sampled from a sampling frame of 982 scheme beneficiaries. On the other hand, a total of 25 stakeholders were chosen for focus group discussions. Chapter 4 dataset presented figures on the demographic characteristics and farm characteristics as well as the level of satisfaction with the services that were offered by SIRP. The challenges faced at the Exchange Irrigation Scheme as well as the target market were presented in chapter 5 dataset. The crop improvements and profitability levels were also presented in the same dataset.
DOI: 10.5517/ccthc1p
title: CCDC 759532: Experimental Crystal Structure Determination

description: Related Article: S.A.Aldonin, P.A.Abramov, A.V.Virovets, M.H.Sokolov, V.P.Fedin|2010|Koord.Khim.|36|643|
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.cc1pz954
title: CCDC 1578246: Experimental Crystal Structure Determination

description: Related Article: Neha Kathewad, Shivpal, Nandha kumar, Rajarshi Dasgupta, Moushakhi Ghosh, Shabana Khan|2019|CSD Communication|||
description: Related Article: Neha Kathewad, Nandha Kumar, Rajarshi Dasgupta, Moushakhi Ghosh, Shiv Pal, Shabana Khan|2019|Dalton Trans.|48|7274|doi:10.1039/C8DT04471F
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.cc1pz965
title: CCDC 1578247: Experimental Crystal Structure Determination

description: Related Article: Neha Kathewad, Shivpal, Nandha kumar, Rajarshi Dasgupta, Moushakhi Ghosh, Shabana Khan|2019|CSD Communication|||
description: Related Article: Neha Kathewad, Nandha Kumar, Rajarshi Dasgupta, Moushakhi Ghosh, Shiv Pal, Shabana Khan|2019|Dalton Trans.|48|7274|doi:10.1039/C8DT04471F
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.cc228xfq
title: CCDC 1915193: Experimental Crystal Structure Determination

description: Related Article: Zhengtao Li, Tullimilli Y. Gopalakrishna, Yi Han, Yanwei Gu, Liu Yuan, Wangdong Zeng, David Casanova, Jishan Wu|2019|J.Am.Chem.Soc.|141|16266|doi:10.1021/jacs.9b09780
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.cc21trd1
title: CCDC 1901583: Experimental Crystal Structure Determination

description: Related Article: Roan A. S. Vasdev, James A. Findlay, Anna L. Garden, James D. Crowley|2019|Chem.Commun.|55|7506|doi:10.1039/C9CC03321A
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.cc23fbws
title: CCDC 1949245: Experimental Crystal Structure Determination

description: Related Article: Kosuke Oki,  Masayoshi Takase,  Shigeki Mori,  Hidemitsu Uno|2019|J.Am.Chem.Soc.|141|16255|doi:10.1021/jacs.9b09260
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.cc23fbxt
title: CCDC 1949246: Experimental Crystal Structure Determination

description: Related Article: Kosuke Oki,  Masayoshi Takase,  Shigeki Mori,  Hidemitsu Uno|2019|J.Am.Chem.Soc.|141|16255|doi:10.1021/jacs.9b09260
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.cc24hr2h
title: CCDC 1981336: Experimental Crystal Structure Determination

description: Related Article: Guanghui Wang, Zijun Zhou, Xiang Shen, Qi Yu, Sergei I. Ivlev and Eric Meggers|2021|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.cc25wfh0
title: CCDC 2022362: Experimental Crystal Structure Determination

description: Related Article: Tim P. Schlachta, Jonas F. Schlagintweit, Markus R. Anneser, Eva-Maria H.J. Esslinger, Maximilian Muhr, Stefan Haslinger, Fritz E. Kühn|2021|Inorg.Chim.Acta|518|120228|doi:10.1016/j.ica.2020.120228
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.cc23w6bk
title: CCDC 1962558: Experimental Crystal Structure Determination

description: Related Article: Vedichi Madhu|2020|CSD Communication|||
description: Related Article: Vedichi Madhu, Arun Kumar Kanakati, Samar K. Das|2020|New J.Chem.|44|10781|doi:10.1039/D0NJ02028A
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.cc288wfw
title: CCDC 2093908: Experimental Crystal Structure Determination

description: Related Article: Christian Marvelous, Lucas de Azevedo Santos, Maxime A. Siegler, Célia Fonseca Guerra, Elisabeth Bouwman|2022|Dalton Trans.|51|8046|doi:10.1039/D2DT00356B
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.cc2bbvj2
title: CCDC 2155384: Experimental Crystal Structure Determination

description: Related Article: Zhuofeng Xie, Yuyang Dai, Manling Bao, Zhongtao Feng, Wenjuan Wang, Chunmeng Liu, Xinping Wang, Yuanting Su|2022|Chem.Commun.|58|5391|doi:10.1039/D2CC01254E
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.cc2bbvl4
title: CCDC 2155386: Experimental Crystal Structure Determination

description: Related Article: Zhuofeng Xie, Yuyang Dai, Manling Bao, Zhongtao Feng, Wenjuan Wang, Chunmeng Liu, Xinping Wang, Yuanting Su|2022|Chem.Commun.|58|5391|doi:10.1039/D2CC01254E
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.cc2bjpdz
title: CCDC 2160991: Experimental Crystal Structure Determination

description: Related Article: Amine Garci, Seifallah Abid, Arthur H. G. David, Marcos D. Codesal, Luja Đorđević, Ryan M. Young, Hiroaki Sai, Laura Le Bras, Aurélie Perrier, Marco Ovalle, Paige J. Brown, Charlotte L. Stern, Araceli G. Campaña, Samuel I. Stupp, Michael R. Wasielewski, Victor Blanco, J. Fraser Stoddart|2022|Angew.Chem.,Int.Ed.|61|e202208679|doi:10.1002/anie.202208679
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.cc2fyry3
title: CCDC 2262936: Experimental Crystal Structure Determination

description: Related Article: Tsubasa Kinugawa, Takashi Matsuo|2023|Dalton Trans.|52|9499|doi:10.1039/D3DT01471A
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: 10.26050/wdcc/ar6.c6pmmimil
title: IPCC DDC: MIROC MIROC-ES2L model output prepared for CMIP6 PMIP

description: Project: Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets - These data have been generated as part of the internationally-coordinated Coupled Model Intercomparison Project Phase 6 (CMIP6; see also GMD Special Issue: http://www.geosci-model-dev.net/special_issue590.html). The simulation data provides a basis for climate research designed to answer fundamental science questions and serves as resource for authors of the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC-AR6). CMIP6 is a project coordinated by the Working Group on Coupled Modelling (WGCM) as part of the World Climate Research Programme (WCRP). Phase 6 builds on previous phases executed under the leadership of the Program for Climate Model Diagnosis and Intercomparison (PCMDI) and relies on the Earth System Grid Federation (ESGF) and the Centre for Environmental Data Analysis (CEDA) along with numerous related activities for implementation. The original data is hosted and partially replicated on a federated collection of data nodes, and most of the data relied on by the IPCC is being archived for long-term preservation at the IPCC Data Distribution Centre (IPCC DDC) hosted by the German Climate Computing Center (DKRZ). The project includes simulations from about 120 global climate models and around 45 institutions and organizations worldwide. Summary: These data include the subset used by IPCC AR6 WGI authors of the datasets originally published in ESGF for 'CMIP6.PMIP.MIROC.MIROC-ES2L' with the full Data Reference Syntax following the template 'mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version'. The MIROC-ES2L climate model, released in 2018, includes the following components: aerosol: SPRINTARS6.0, atmos: CCSR AGCM (T42; 128 x 64 longitude/latitude; 40 levels; top level 3 hPa), land: MATSIRO6.0+VISIT-e ver.1.0, ocean: COCO4.9 (tripolar primarily 1deg; 360 x 256 longitude/latitude; 63 levels; top grid cell 0-2 m), ocnBgchem: OECO ver.2.0; NPZD-type with C/N/P/Fe/O cycles, seaIce: COCO4.9. The model was run by the JAMSTEC (Japan Agency for Marine-Earth Science and Technology, Kanagawa 236-0001, Japan), AORI (Atmosphere and Ocean Research Institute, The University of Tokyo, Chiba 277-8564, Japan), NIES (National Institute for Environmental Studies, Ibaraki 305-8506, Japan), and R-CCS (RIKEN Center for Computational Science, Hyogo 650-0047, Japan) (MIROC) in native nominal resolutions: aerosol: 500 km, atmos: 500 km, land: 500 km, ocean: 100 km, ocnBgchem: 100 km, seaIce: 100 km.
DOI: 10.5281/zenodo.8272682
title: Meshing strategies for 3D geo-electromagnetic modeling in the presence of metallic infrastructure

description: Accompanying data to journal article Castillo-Reyes, O., Rulff, P., Schankee Um, E., Amor-Martin, A. (2023) Meshing strategies for 3D geo-electromagnetic modeling in the presence of metallic infrastructure. Accepted for publication in Computational Geosciences.
description: The research leading of this study has received funding from the Ministerio de Educación y Ciencia (Spain) under Project TED2021-131882B-C42. All petgem simulations have been performed on Marenostrum supercomputer at BSC. The elfe3D computations were enabled by resources provided by the Swedish National Infrastructure for Computing (SNIC) at UPPMAX partially funded by the Swedish Research Council through grant agreement No. SNIC 2021/22-883.
DOI: 10.5281/zenodo.8272681
title: Meshing strategies for 3D geo-electromagnetic modeling in the presence of metallic infrastructure

description: Accompanying data to journal article Castillo-Reyes, O., Rulff, P., Schankee Um, E., Amor-Martin, A. (2023) Meshing strategies for 3D geo-electromagnetic modeling in the presence of metallic infrastructure. Accepted for publication in Computational Geosciences.
description: The research leading of this study has received funding from the Ministerio de Educación y Ciencia (Spain) under Project TED2021-131882B-C42. All petgem simulations have been performed on Marenostrum supercomputer at BSC. The elfe3D computations were enabled by resources provided by the Swedish National Infrastructure for Computing (SNIC) at UPPMAX partially funded by the Swedish Research Council through grant agreement No. SNIC 2021/22-883.
DOI: 10.5519/qd.mf8zsgs8
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (12645 records)
DOI: 10.6084/m9.figshare.24006267
title: Supplementary Material for: Refining a multifaceted model of perceived utility of genomic sequencing results

description: Introduction: Research on the perceived utility of genomic sequencing has focused primarily on pediatric populations and on individuals and families with rare genetic diseases. Here, we evaluate how well a multifaceted perceived utility model developed with these populations applies to a diverse, adult population aged 18-49 at risk for hereditary cancer and propose new considerations for the model. Methods: Participants received clinical genomic sequencing in the Cancer Health Assessments Reaching Many (CHARM) study. Semi-structured qualitative interviews were conducted with a subset of participants at one and six months after results disclosure. We used an approach influenced by grounded theory to examine perceptions of the utility of genomic sequencing and analyzed how utility in CHARM mapped to the published multifaceted perceived utility model, noting which domains were represented or absent, and which were most salient to our population. Results: Participants’ discussions of utility often involved multiple domains and revealed the variety of ways in which receiving sequencing results can impact one’s life. Results demonstrated that an individual’s perception of utility can change over the life course when sequenced at a relatively young age and may be influenced by the resources available to them to act on the results. Discussion/Conclusion: Our findings demonstrate the relevance of a multifaceted perceived utility model for a diverse adult population at risk for hereditary cancer. We identified refinements that could make the model more robust, including emphasizing the overlapping nature of the domains, and the importance of life stage and personal resources to the perception of utility.
DOI: 10.6084/m9.figshare.24006273
title: Supplementary Material for: Refining a multifaceted model of perceived utility of genomic sequencing results

description: Introduction: Research on the perceived utility of genomic sequencing has focused primarily on pediatric populations and on individuals and families with rare genetic diseases. Here, we evaluate how well a multifaceted perceived utility model developed with these populations applies to a diverse, adult population aged 18-49 at risk for hereditary cancer and propose new considerations for the model. Methods: Participants received clinical genomic sequencing in the Cancer Health Assessments Reaching Many (CHARM) study. Semi-structured qualitative interviews were conducted with a subset of participants at one and six months after results disclosure. We used an approach influenced by grounded theory to examine perceptions of the utility of genomic sequencing and analyzed how utility in CHARM mapped to the published multifaceted perceived utility model, noting which domains were represented or absent, and which were most salient to our population. Results: Participants’ discussions of utility often involved multiple domains and revealed the variety of ways in which receiving sequencing results can impact one’s life. Results demonstrated that an individual’s perception of utility can change over the life course when sequenced at a relatively young age and may be influenced by the resources available to them to act on the results. Discussion/Conclusion: Our findings demonstrate the relevance of a multifaceted perceived utility model for a diverse adult population at risk for hereditary cancer. We identified refinements that could make the model more robust, including emphasizing the overlapping nature of the domains, and the importance of life stage and personal resources to the perception of utility.
DOI: 10.6084/m9.figshare.24006273.v1
title: Supplementary Material for: Refining a multifaceted model of perceived utility of genomic sequencing results

description: Introduction: Research on the perceived utility of genomic sequencing has focused primarily on pediatric populations and on individuals and families with rare genetic diseases. Here, we evaluate how well a multifaceted perceived utility model developed with these populations applies to a diverse, adult population aged 18-49 at risk for hereditary cancer and propose new considerations for the model. Methods: Participants received clinical genomic sequencing in the Cancer Health Assessments Reaching Many (CHARM) study. Semi-structured qualitative interviews were conducted with a subset of participants at one and six months after results disclosure. We used an approach influenced by grounded theory to examine perceptions of the utility of genomic sequencing and analyzed how utility in CHARM mapped to the published multifaceted perceived utility model, noting which domains were represented or absent, and which were most salient to our population. Results: Participants’ discussions of utility often involved multiple domains and revealed the variety of ways in which receiving sequencing results can impact one’s life. Results demonstrated that an individual’s perception of utility can change over the life course when sequenced at a relatively young age and may be influenced by the resources available to them to act on the results. Discussion/Conclusion: Our findings demonstrate the relevance of a multifaceted perceived utility model for a diverse adult population at risk for hereditary cancer. We identified refinements that could make the model more robust, including emphasizing the overlapping nature of the domains, and the importance of life stage and personal resources to the perception of utility.