cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5517/ccdc.csd.cc2dz1v9
title: CCDC 2233421: Experimental Crystal Structure Determination

description: Related Article: Meng-Yang Chang, Chi-Ruei Guo, Chin-Huei Ho|2023|J.Mol.Struct.|1285|135478|doi:10.1016/j.molstruc.2023.135478
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.cc2dz1wb
title: CCDC 2233422: Experimental Crystal Structure Determination

description: Related Article: Meng-Yang Chang, Chi-Ruei Guo, Chin-Huei Ho|2023|J.Mol.Struct.|1285|135478|doi:10.1016/j.molstruc.2023.135478
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.cc2dzfvp
title: CCDC 2233793: Experimental Crystal Structure Determination

description: Related Article: Xiaohui Wu, Ruicheng Wang, Wen-Cheng Chen, Bo Liu, Qingdan Yang, Shaomin Ji, Yanping Huo|2023|J.Mol.Struct.|1285|135408|doi:10.1016/j.molstruc.2023.135408
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.cc2dzyzb
title: CCDC 2234293: Experimental Crystal Structure Determination

description: Related Article: Hannah E. Straker, Lynn McMillan, Lina Mardiana, Glen R. Hebberd, Elle Watson, Paul G. Waddell, Michael R. Probert, Michael J. Hall|2023|CrystEngComm|25|2479|doi:10.1039/D3CE00041A
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.7860766
title: RISKRES project database

description: RISKRES projetc database containing the reactions to seismic events in Europe in 1200-1755 AD
DOI: 10.5281/zenodo.7860765
title: RISKRES project database

description: RISKRES projetc database containing the reactions to seismic events in Europe in 1200-1755 AD
DOI: 10.5281/zenodo.7860758
title: Digital Twin of a Multi-Arm Robot Platform based on Isaac Sim for Synthetic Data Generation

description: This data set is required by the following repository<br> https://github.com/AISciencePlatform/icra2023_synthetic_data_pretraining_for_robotics
DOI: 10.5281/zenodo.7860757
title: Digital Twin of a Multi-Arm Robot Platform based on Isaac Sim for Synthetic Data Generation

description: This data set is required by the following repository<br> https://github.com/AISciencePlatform/icra2023_synthetic_data_pretraining_for_robotics
DOI: 10.5517/ccdc.csd.cc2dzz0d
title: CCDC 2234294: Experimental Crystal Structure Determination

description: Related Article: Hannah E. Straker, Lynn McMillan, Lina Mardiana, Glen R. Hebberd, Elle Watson, Paul G. Waddell, Michael R. Probert, Michael J. Hall|2023|CrystEngComm|25|2479|doi:10.1039/D3CE00041A
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.22688263
title: The data needed for the experiment

description: Road network data as an important geospatial data is widely used in intelligent transportation, location services and other fields. With the development of social economy, the application of various fields to the quality of road data and the current situation of the higher the requirements Based on the representation ability of graph neural network, this paper proposes a graph matching model. The model starts from geometric features and realizes self-adaptive path through similarity expression of different feature Path matching.
DOI: 10.6084/m9.figshare.22688263.v1
title: The data needed for the experiment

description: Road network data as an important geospatial data is widely used in intelligent transportation, location services and other fields. With the development of social economy, the application of various fields to the quality of road data and the current situation of the higher the requirements Based on the representation ability of graph neural network, this paper proposes a graph matching model. The model starts from geometric features and realizes self-adaptive path through similarity expression of different feature Path matching.
DOI: 10.5281/zenodo.7747825
title: A multispectral UAV Imagery dataset of wheat, soybean, and barley crops in East Kazakhstan

description: This study introduces a dataset of crop imagery captured during the 2022 growing season in the Eastern Kazakhstan region. The images were acquired using a multispectral camera mounted on an unmanned aerial vehicle (DJI Phantom 4). The agricultural land, encompassing 27 hectares and cultivated with wheat, barley, and soybean, was subjected to five aerial multispectral photography sessions throughout the growing season. This facilitated thorough monitoring of the most important phenological stages of crop development in the experimental design, which consisted of 27 plots, each covering one hectare. The collected imagery underwent enhancement and expansion, integrating a sixth band that embodies the normalized difference vegetation index (NDVI) values, in conjunction with the original five multispectral bands (Blue, Green, Red, Red Edge and Near Infrared Red). This amplification enables a more effective evaluation of vegetation health and growth, rendering the enriched dataset a valuable resource for the progression and validation of crop monitoring and yield prediction models, as well as for the exploration of precision agriculture methodologies.
description: This research was funded by the Science Committee of the Ministry of Science and Higher Education of the Republic of Kazakhstan, grant number AP09259379.
DOI: 10.5281/zenodo.7747826
title: A multispectral UAV Imagery dataset of wheat, soybean, and barley crops in East Kazakhstan

description: This study introduces a dataset of crop imagery captured during the 2022 growing season in the Eastern Kazakhstan region. The images were acquired using a multispectral camera mounted on an unmanned aerial vehicle (DJI Phantom 4). The agricultural land, encompassing 27 hectares and cultivated with wheat, barley, and soybean, was subjected to five aerial multispectral photography sessions throughout the growing season. This facilitated thorough monitoring of the most important phenological stages of crop development in the experimental design, which consisted of 27 plots, each covering one hectare. The collected imagery underwent enhancement and expansion, integrating a sixth band that embodies the normalized difference vegetation index (NDVI) values, in conjunction with the original five multispectral bands (Blue, Green, Red, Red Edge and Near Infrared Red). This amplification enables a more effective evaluation of vegetation health and growth, rendering the enriched dataset a valuable resource for the progression and validation of crop monitoring and yield prediction models, as well as for the exploration of precision agriculture methodologies.
description: This research was funded by the Science Committee of the Ministry of Science and Higher Education of the Republic of Kazakhstan, grant number AP09259379.
DOI: 10.5281/zenodo.7749411
title: A multispectral UAV Imagery dataset of wheat, soybean, and barley crops in East Kazakhstan

description: This study introduces a dataset of crop imagery captured during the 2022 growing season in the Eastern Kazakhstan region. The images were acquired using a multispectral camera mounted on an unmanned aerial vehicle (DJI Phantom 4). The agricultural land, encompassing 27 hectares and cultivated with wheat, barley, and soybean, was subjected to five aerial multispectral photography sessions throughout the growing season. This facilitated thorough monitoring of the most important phenological stages of crop development in the experimental design, which consisted of 27 plots, each covering one hectare. The collected imagery underwent enhancement and expansion, integrating a sixth band that embodies the normalized difference vegetation index (NDVI) values, in conjunction with the original five multispectral bands (Blue, Green, Red, Red Edge and Near Infrared Red). This amplification enables a more effective evaluation of vegetation health and growth, rendering the enriched dataset a valuable resource for the progression and validation of crop monitoring and yield prediction models, as well as for the exploration of precision agriculture methodologies.
description: This research was funded by the Science Committee of the Ministry of Science and Higher Education of the Republic of Kazakhstan, grant number AP09259379.
DOI: 10.5281/zenodo.7860751
title: A multispectral UAV Imagery dataset of wheat, soybean, and barley crops in East Kazakhstan

description: This study introduces a dataset of crop imagery captured during the 2022 growing season in the Eastern Kazakhstan region. The images were acquired using a multispectral camera mounted on an unmanned aerial vehicle (DJI Phantom 4). The agricultural land, encompassing 27 hectares and cultivated with wheat, barley, and soybean, was subjected to five aerial multispectral photography sessions throughout the growing season. This facilitated thorough monitoring of the most important phenological stages of crop development in the experimental design, which consisted of 27 plots, each covering one hectare. The collected imagery underwent enhancement and expansion, integrating a sixth band that embodies the normalized difference vegetation index (NDVI) values, in conjunction with the original five multispectral bands (Blue, Green, Red, Red Edge and Near Infrared Red). This amplification enables a more effective evaluation of vegetation health and growth, rendering the enriched dataset a valuable resource for the progression and validation of crop monitoring and yield prediction models, as well as for the exploration of precision agriculture methodologies.
description: This research was funded by the Science Committee of the Ministry of Science and Higher Education of the Republic of Kazakhstan, grant number AP09259379.
DOI: 10.5281/zenodo.7815318
title: Land Productivity Dynamics (LPD) maps based on approaches recommended by the United Nations Convention to Combat Desertification (UNCCD) for the Brazilian Semiarid Region (BSR).

description: Maps of the land productivity dynamic (LPD) based on approaches recommended by the United Nations Convention to Combat Desertification (UNCCD) for the Brazilian Semiarid Region for the period 2001-2015. LPD from Trends.Earth (TE), LPD from the Joint Research Center (JRC-LPD), and LPD from the Food and Agriculture Organization – World Overview of Conservation Approaches and Technologies (FAO-WOCAT LPD). In addition, TE-based LPD with climate correction based on Rain Use Efficiency (RUE), Residual Trend Analysis (RESTREND), and Water Use Efficiency (WUE) calculated using the procedures described in the second version of the Good Practice Guidance for SDG Indicator 15.3.1. The annual LCLU maps from the MapBiomas project at 30 m spatial resolution for 2001 and 2015, and the 16-day MOD13Q1 NDVI dataset from 2001 to 2015 were used as inputs. ********************** A total of seven GeoTIFF files in Geographic Tagged Image File Format (GeoTIFF) format are provided at 250 m spatial resolution. Coding for the LPDs. Value Meaning -32768 No data 1 Declining 2 Moderate decline 3 Stressed 4 Stable 5 Increasing Funding: this study was undertaken as part of the Satellite Desertification Monitoring Program in the Brazilian Semiarid Region [Grant Number 403223/2021-0] supported by the CNPq. It also had the support of Capes, through Notice no. 28/2022 – PDPG Social Vulnerability & Human Rights [Grant Number 88881.705050/2022-01].
description: {"references": ["The Good Practice Guidance for SDG Indicator 15.3.1 version 2.0 is available at https://bit.ly/3knel9r. Communities: Remote sensing"]}
DOI: 10.5281/zenodo.7815317
title: Land Productivity Dynamics (LPD) maps based on approaches recommended by the United Nations Convention to Combat Desertification (UNCCD) for the Brazilian Semiarid Region (BSR).

description: Maps of the land productivity dynamic (LPD) based on approaches recommended by the United Nations Convention to Combat Desertification (UNCCD) for the Brazilian Semiarid Region for the period 2001-2015. LPD from Trends.Earth (TE), LPD from the Joint Research Center (JRC-LPD), and LPD from the Food and Agriculture Organization – World Overview of Conservation Approaches and Technologies (FAO-WOCAT LPD). In addition, TE-based LPD with climate correction based on Rain Use Efficiency (RUE), Residual Trend Analysis (RESTREND), and Water Use Efficiency (WUE) calculated using the procedures described in the second version of the Good Practice Guidance for SDG Indicator 15.3.1. The annual LCLU maps from the MapBiomas project at 30 m spatial resolution for 2001 and 2015, and the 16-day MOD13Q1 NDVI dataset from 2001 to 2015 were used as inputs. ********************** A total of seven GeoTIFF files in Geographic Tagged Image File Format (GeoTIFF) format are provided at 250 m spatial resolution. Coding for the LPDs. Value Meaning -32768 No data 1 Declining 2 Moderate decline 3 Stressed 4 Stable 5 Increasing Funding: this study was undertaken as part of the Satellite Desertification Monitoring Program in the Brazilian Semiarid Region [Grant Number 403223/2021-0] supported by the CNPq. It also had the support of Capes, through Notice no. 28/2022 – PDPG Social Vulnerability & Human Rights [Grant Number 88881.705050/2022-01].
description: {"references": ["The Good Practice Guidance for SDG Indicator 15.3.1 version 2.0 is available at https://bit.ly/3knel9r. Communities: Remote sensing"]}
DOI: 10.6084/m9.figshare.22688320
title: Tables Response Variable and Tools.docx

description: Data base from the beavior about the use of the variable response and tools of the Lean Manufacturing methodology
DOI: 10.6084/m9.figshare.22688320.v1
title: Tables Response Variable and Tools.docx

description: Data base from the beavior about the use of the variable response and tools of the Lean Manufacturing methodology
DOI: 10.6084/m9.figshare.21341766
title: Metagenome and 16S rRNA sequences

description: NCD:C6_1,C6_2,C6_3 HFD:CH10_3,CH10_5,CH13_5 HFD-L:HL10_1,HL10_2,HL13_3 HFD-H:HH13_1,HH13_3,HH13_4
DOI: 10.6084/m9.figshare.21341766.v1
title: 16S rRNA sequences

description: NCD:C6_1,C6_2,C6_3 HFD:CH10_3,CH10_5,CH13_5 HFD-L:HL10_1,HL10_2,HL13_3 HFD-H:HH13_1,HH13_3,HH13_4
DOI: 10.5281/zenodo.6757693
title: Tundra soil viruses mediate the responses of microbial communities to climate warming

description: The dataset of this study contains the information of metagenomic data, environmental factors, GeoChip data, vOTUs table, mOTUs tables, and the viral and microbial sequences.
DOI: 10.5281/zenodo.7420595
title: Tundra soil viruses mediate the responses of microbial communities to climate warming

description: The dataset of this study contains the information of metagenomic data, environmental factors, GeoChip data, vOTUs table, mOTUs tables, and the viral and microbial sequences.
DOI: 10.5281/zenodo.7438318
title: Tundra soil viruses mediate the responses of microbial communities to climate warming

description: The dataset of this study contains the information of metagenomic data, environmental factors, GeoChip data, vOTUs table, mOTUs tables, and the viral and microbial sequences.
DOI: 10.5281/zenodo.7438349
title: Tundra soil viruses mediate the responses of microbial communities to climate warming

description: The dataset of this study contains the information of metagenomic data, environmental factors, GeoChip data, vOTUs table, mOTUs tables, and the viral and microbial sequences.
DOI: 10.5519/qd.8yfe5jak
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (578 records)
DOI: 10.5517/ccdc.csd.cc2dzz1f
title: CCDC 2234295: Experimental Crystal Structure Determination

description: Related Article: Hannah E. Straker, Lynn McMillan, Lina Mardiana, Glen R. Hebberd, Elle Watson, Paul G. Waddell, Michael R. Probert, Michael J. Hall|2023|CrystEngComm|25|2479|doi:10.1039/D3CE00041A
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.cc2dzz2g
title: CCDC 2234296: Experimental Crystal Structure Determination

description: Related Article: Hannah E. Straker, Lynn McMillan, Lina Mardiana, Glen R. Hebberd, Elle Watson, Paul G. Waddell, Michael R. Probert, Michael J. Hall|2023|CrystEngComm|25|2479|doi:10.1039/D3CE00041A
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.cc2dzz3h
title: CCDC 2234297: Experimental Crystal Structure Determination

description: Related Article: Hannah E. Straker, Lynn McMillan, Lina Mardiana, Glen R. Hebberd, Elle Watson, Paul G. Waddell, Michael R. Probert, Michael J. Hall|2023|CrystEngComm|25|2479|doi:10.1039/D3CE00041A
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.cc2dzz4j
title: CCDC 2234298: Experimental Crystal Structure Determination

description: Related Article: Hannah E. Straker, Lynn McMillan, Lina Mardiana, Glen R. Hebberd, Elle Watson, Paul G. Waddell, Michael R. Probert, Michael J. Hall|2023|CrystEngComm|25|2479|doi:10.1039/D3CE00041A
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.cc2c7xq8
title: CCDC 2182360: Experimental Crystal Structure Determination

description: Related Article: Dawid Drozdowski, Katarzyna Fedoruk, Adam Kabanski, Mirosław Maczka, Adam Sieradzki, Anna Gagor|2023|J.Mater.Chem.C|11|4907|doi:10.1039/D3TC00401E
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.cc2dzz5k
title: CCDC 2234299: Experimental Crystal Structure Determination

description: Related Article: Hannah E. Straker, Lynn McMillan, Lina Mardiana, Glen R. Hebberd, Elle Watson, Paul G. Waddell, Michael R. Probert, Michael J. Hall|2023|CrystEngComm|25|2479|doi:10.1039/D3CE00041A
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.cc2c82vl
title: CCDC 2182519: Experimental Crystal Structure Determination

description: Related Article: Dawid Drozdowski, Katarzyna Fedoruk, Adam Kabanski, Mirosław Maczka, Adam Sieradzki, Anna Gagor|2023|J.Mater.Chem.C|11|4907|doi:10.1039/D3TC00401E
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.cc2f1hgg
title: CCDC 2235765: Experimental Crystal Structure Determination

description: Related Article: Ruijie Mi, Zhiying Ding, Songjie Yu, Robert H. Crabtree, Xingwei Li|2023|J.Am.Chem.Soc.|145|8150|doi:10.1021/jacs.3c01162
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.cc2f136t
title: CCDC 2235385: Experimental Crystal Structure Determination

description: Related Article: Dawid Drozdowski, Katarzyna Fedoruk, Adam Kabanski, Mirosław Maczka, Adam Sieradzki, Anna Gagor|2023|J.Mater.Chem.C|11|4907|doi:10.1039/D3TC00401E
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.cc2dpgcy
title: CCDC 2225160: Experimental Crystal Structure Determination

description: Related Article: Mingoo Jin, Satsuki Matsuura, Hikaru Yamamoto, Motohiro Mizuno, Hajime Ito|2023|Eur.J.Org.Chem.|26|e202201468|doi:10.1002/ejoc.202201468
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.