cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5517/ccdc.csd.cc2fw53m
title: CCDC 2260430: Experimental Crystal Structure Determination

description: Related Article: Md. Mahbubur Rahman, Pengcheng Gao, Qun Zhao, Roger Lalancette, Roman Szostak, Michal Szostak|2023|Cat.Sci.Tech.|13|5131|doi:10.1039/D3CY00717K
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.cc2g3tw9
title: CCDC 2267801: Experimental Crystal Structure Determination

description: Related Article: Daniel Ejarque, Teresa Calvet, Mercè Font-Bardia, Josefina Pons|2023|CrystEngComm|25|4798|doi:10.1039/D3CE00608E
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.cc2g3txb
title: CCDC 2267802: Experimental Crystal Structure Determination

description: Related Article: Daniel Ejarque, Teresa Calvet, Mercè Font-Bardia, Josefina Pons|2023|CrystEngComm|25|4798|doi:10.1039/D3CE00608E
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.cc2g6g05
title: CCDC 2270316: Experimental Crystal Structure Determination

description: Related Article: Kaushik Chakrabarti, Alice Spangenberg, Vasudevan Subramaniyan, Andreas Hederstedt, Omar Y. Abdelaziz, Alexey V. Polukeev, Reine Wallenberg, Christian P. Hulteberg, Ola F. Wendt|2023|Cat.Sci.Tech.|13|5113|doi:10.1039/D3CY00881A
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.cc2ft0x6
title: CCDC 2258378: Experimental Crystal Structure Determination

description: Related Article: Daiki Matsumoto, Chiaki Tanaka, Masaru Fujibayashi, Sadafumi Nishihara, Kiyonori Takahashi, Takayoshi Nakamura, Tomoyuki Akutagawa, Atsuko Masuya-Suzuki, Ryo Tsunashima|2023|CrystEngComm|25|4793|doi:10.1039/D3CE00429E
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.cc2gkzbc
title: CCDC 2281393: Experimental Crystal Structure Determination

description: Related Article: Daiki Matsumoto, Chiaki Tanaka, Masaru Fujibayashi, Sadafumi Nishihara, Kiyonori Takahashi, Takayoshi Nakamura, Tomoyuki Akutagawa, Atsuko Masuya-Suzuki, Ryo Tsunashima|2023|CrystEngComm|25|4793|doi:10.1039/D3CE00429E
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.cc2gjcr4
title: CCDC 2279856: Experimental Crystal Structure Determination

description: Related Article: Daiki Matsumoto, Chiaki Tanaka, Masaru Fujibayashi, Sadafumi Nishihara, Kiyonori Takahashi, Takayoshi Nakamura, Tomoyuki Akutagawa, Atsuko Masuya-Suzuki, Ryo Tsunashima|2023|CrystEngComm|25|4793|doi:10.1039/D3CE00429E
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.cc2gkz89
title: CCDC 2281391: Experimental Crystal Structure Determination

description: Related Article: Daiki Matsumoto, Chiaki Tanaka, Masaru Fujibayashi, Sadafumi Nishihara, Kiyonori Takahashi, Takayoshi Nakamura, Tomoyuki Akutagawa, Atsuko Masuya-Suzuki, Ryo Tsunashima|2023|CrystEngComm|25|4793|doi:10.1039/D3CE00429E
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.23646327.v2
title: Improving and Extending STERGM Approximations Based on Cross-Sectional Data and Tie Durations

description: Temporal exponential-family random graph models (TERGMs) are a flexible class of models for network ties that change over time. Separable TERGMs (STERGMs) are a subclass of TERGMs in which the dynamics of tie formation and dissolution can be separated within each discrete time step and may depend on different factors. The Carnegie et al. approximation improves estimation efficiency for a subclass of STERGMs, allowing them to be reliably estimated from inexpensive cross-sectional study designs. This approximation adapts to cross-sectional data by attempting to construct a STERGM with two specific properties: a cross-sectional equilibrium distribution defined by an exponential-family random graph model (ERGM) for the network structure, and geometric tie duration distributions defined by constant hazards for tie dissolution. In this article we focus on approaches for improving the behavior of the Carnegie et al. approximation and increasing its scope of application. We begin with Carnegie et al.’s observation that the exact result is tractable when the ERGM is dyad-independent, and then show that taking the sparse limit of the exact result leads to a different approximation than the one they presented. We show that the new approximation outperforms theirs for sparse, dyad-independent models, and observe that the errors tend to increase with the strength of dependence for dyad-dependent models. We then develop theoretical results in the dyad-dependent case, showing that when the ERGM is allowed to have arbitrary dyad-dependent terms and some dyad-dependent constraints, both the old and new approximations are asymptotically exact as the size of the STERGM time step goes to zero. We note that the continuous-time limit of the discrete-time approximations has the desired cross-sectional equilibrium distribution and exponential tie duration distributions with the desired means. We show that our results extend to hypergraphs, and we propose an extension of the Carnegie et al. framework to dissolution hazards that depend on tie age. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.23646327
title: Improving and Extending STERGM Approximations Based on Cross-Sectional Data and Tie Durations

description: Temporal exponential-family random graph models (TERGMs) are a flexible class of models for network ties that change over time. Separable TERGMs (STERGMs) are a subclass of TERGMs in which the dynamics of tie formation and dissolution can be separated within each discrete time step and may depend on different factors. The Carnegie et al. approximation improves estimation efficiency for a subclass of STERGMs, allowing them to be reliably estimated from inexpensive cross-sectional study designs. This approximation adapts to cross-sectional data by attempting to construct a STERGM with two specific properties: a cross-sectional equilibrium distribution defined by an exponential-family random graph model (ERGM) for the network structure, and geometric tie duration distributions defined by constant hazards for tie dissolution. In this article we focus on approaches for improving the behavior of the Carnegie et al. approximation and increasing its scope of application. We begin with Carnegie et al.’s observation that the exact result is tractable when the ERGM is dyad-independent, and then show that taking the sparse limit of the exact result leads to a different approximation than the one they presented. We show that the new approximation outperforms theirs for sparse, dyad-independent models, and observe that the errors tend to increase with the strength of dependence for dyad-dependent models. We then develop theoretical results in the dyad-dependent case, showing that when the ERGM is allowed to have arbitrary dyad-dependent terms and some dyad-dependent constraints, both the old and new approximations are asymptotically exact as the size of the STERGM time step goes to zero. We note that the continuous-time limit of the discrete-time approximations has the desired cross-sectional equilibrium distribution and exponential tie duration distributions with the desired means. We show that our results extend to hypergraphs, and we propose an extension of the Carnegie et al. framework to dissolution hazards that depend on tie age. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.23646327.v1
title: Improving and Extending STERGM Approximations Based on Cross-Sectional Data and Tie Durations

description: Temporal exponential-family random graph models (TERGMs) are a flexible class of models for network ties that change over time. Separable TERGMs (STERGMs) are a subclass of TERGMs in which the dynamics of tie formation and dissolution can be separated within each discrete time step and may depend on different factors. The Carnegie et al. (2015) approximation improves estimation efficiency for a subclass of STERGMs, allowing them to be reliably estimated from inexpensive cross-sectional study designs. This approximation adapts to cross-sectional data by attempting to construct a STERGM with two specific properties: a cross-sectional equilibrium distribution defined by an exponential-family random graph model (ERGM) for the network structure, and geometric tie duration distributions defined by constant hazards for tie dissolution. In this paper we focus on approaches for improving the behavior of the Carnegie et al. approximation and increasing its scope of application. We begin with Carnegie et al.’s observation that the exact result is tractable when the ERGM is dyad-independent, and then show that taking the sparse limit of the exact result leads to a different approximation than the one they presented. We show that the new approximation outperforms theirs for sparse, dyad-independent models, and observe that the errors tend to increase with the strength of dependence for dyad-dependent models. We then develop theoretical results in the dyad-dependent case, showing that when the ERGM is allowed to have arbitrary dyad-dependent terms and some dyad-dependent constraints, both the old and new approximations are asymptotically exact as the size of the STERGM time step goes to zero. We note that the continuous-time limit of the discrete-time approximations has the desired cross-sectional equilibrium distribution and exponential tie duration distributions with the desired means. We show that our results extend to hypergraphs, and we propose an extension to dissolution hazards that depend on tie age.
DOI: 10.5281/zenodo.8298583
title: FloodsNet_WorldFloods-USGS-Sen1Floods11

description: **Test upload to create DOI. Version 2 will have full data described below.** This represents the WorldFloods, USGS, and Sen1Floods11 flood training data as part of the FloodsNet data set.
DOI: 10.5281/zenodo.8298584
title: FloodsNet_WorldFloods-USGS-Sen1Floods11

description: **Test upload to create DOI. Version 2 will have full data described below.** This represents the WorldFloods, USGS, and Sen1Floods11 flood training data as part of the FloodsNet data set.
DOI: 10.5281/zenodo.8298840
title: FloodsNet_WorldFloods-USGS-Sen1Floods11

description: **Test upload to create DOI. Version 2 will have full data described below.** This represents the WorldFloods, USGS, and Sen1Floods11 flood training data as part of the FloodsNet data set.
DOI: 10.5281/zenodo.8299592
title: Bibliographic data and thesauraus files

description: <strong>Data for “Seeing beyond the frames we inherit: A challenge to tenacious conservation narratives” (published in <em>People and Nature</em>)</strong> Stephen M. Chignell and Terre Satterfield ------------------------------------------------------------------------------------------------------------------------------- This repository contains the following data files used in the above publication. Detailed information about how these data were collected and analyzed can be found at the journal website. Bibliographic data downloaded from Web of Science (raw text file format) Can be imported directly into <em>bibliometrix/biblioshiny </em>or <em>VOSviewer </em>software Bibliographic data downloaded from Web of Science (Microsoft Excel format) Can be imported directly into <em>bibliometrix/biblioshiny </em>software “Thesaurus” file created to disambiguate author names in <em>VOSviewer</em> software “Thesaurus” file created to disambiguate publication keywords in <em>VOSviewer</em> software “Thesaurus” file created to disambiguate author organizations in <em>VOSviewer</em> software
DOI: 10.5281/zenodo.8299593
title: Bibliographic data and thesauraus files

description: <strong>Data for “Seeing beyond the frames we inherit: A challenge to tenacious conservation narratives” (published in <em>People and Nature</em>)</strong> Stephen M. Chignell and Terre Satterfield ------------------------------------------------------------------------------------------------------------------------------- This repository contains the following data files used in the above publication. Detailed information about how these data were collected and analyzed can be found at the journal website. Bibliographic data downloaded from Web of Science (raw text file format) Can be imported directly into <em>bibliometrix/biblioshiny </em>or <em>VOSviewer </em>software Bibliographic data downloaded from Web of Science (Microsoft Excel format) Can be imported directly into <em>bibliometrix/biblioshiny </em>software “Thesaurus” file created to disambiguate author names in <em>VOSviewer</em> software “Thesaurus” file created to disambiguate publication keywords in <em>VOSviewer</em> software “Thesaurus” file created to disambiguate author organizations in <em>VOSviewer</em> software
DOI: 10.5281/zenodo.6047543
title: Optimal Control of Renewable Energy Communities with Controllable Assets: consumption and production profiles

description: consumption and production profiles for cases I and II used for computing simulations in Optimal Control of Renewable Energy Communities with Controllable Assets
DOI: 10.5281/zenodo.6047542
title: Optimal Control of Renewable Energy Communities with Controllable Assets: consumption and production profiles

description: consumption and production profiles for cases I and II used for computing simulations in Optimal Control of Renewable Energy Communities with Controllable Assets
DOI: 10.5517/ccdc.csd.cc2fs56m
title: CCDC 2257550: Experimental Crystal Structure Determination

description: Related Article: Ryoga Hojo, Katrina Bergmann, Seja A. Elgadi, Don M. Mayder, Megan A. Emmanuel, Martins S. Oderinde, Zachary M. Hudson|2023|J.Am.Chem.Soc.|145|18366|doi:10.1021/jacs.3c04132
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.cc2fs57n
title: CCDC 2257551: Experimental Crystal Structure Determination

description: Related Article: Ryoga Hojo, Katrina Bergmann, Seja A. Elgadi, Don M. Mayder, Megan A. Emmanuel, Martins S. Oderinde, Zachary M. Hudson|2023|J.Am.Chem.Soc.|145|18366|doi:10.1021/jacs.3c04132
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.cc2fs58p
title: CCDC 2257552: Experimental Crystal Structure Determination

description: Related Article: Ryoga Hojo, Katrina Bergmann, Seja A. Elgadi, Don M. Mayder, Megan A. Emmanuel, Martins S. Oderinde, Zachary M. Hudson|2023|J.Am.Chem.Soc.|145|18366|doi:10.1021/jacs.3c04132
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.cc2fs59q
title: CCDC 2257553: Experimental Crystal Structure Determination

description: Related Article: Ryoga Hojo, Katrina Bergmann, Seja A. Elgadi, Don M. Mayder, Megan A. Emmanuel, Martins S. Oderinde, Zachary M. Hudson|2023|J.Am.Chem.Soc.|145|18366|doi:10.1021/jacs.3c04132
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.cc2fs9m5
title: CCDC 2257687: Experimental Crystal Structure Determination

description: Related Article: Ryoga Hojo, Katrina Bergmann, Seja A. Elgadi, Don M. Mayder, Megan A. Emmanuel, Martins S. Oderinde, Zachary M. Hudson|2023|J.Am.Chem.Soc.|145|18366|doi:10.1021/jacs.3c04132
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.cc2cmyzy
title: CCDC 2193931: Experimental Crystal Structure Determination

description: Related Article: Tong-Kai Luo, Xiang Zhong, Qing-Yun Zhang, Xiao-Feng Chen, Hui Xu, Yan Peng, Sui-Jun Liu, Zhao-Bo Hu, He-Rui Wen|2023|CrystEngComm|25|4873|doi:10.1039/D3CE00523B
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.cc2cmz00
title: CCDC 2193932: Experimental Crystal Structure Determination

description: Related Article: Tong-Kai Luo, Xiang Zhong, Qing-Yun Zhang, Xiao-Feng Chen, Hui Xu, Yan Peng, Sui-Jun Liu, Zhao-Bo Hu, He-Rui Wen|2023|CrystEngComm|25|4873|doi:10.1039/D3CE00523B
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.cc2g41m9
title: CCDC 2268010: Experimental Crystal Structure Determination

description: Related Article: Jinling Chang, Qianxi Ouyang, Xiaogang Peng, Jiao Pei, Linlin Zhang, Yutian Gan, Hanli Ruan|2023|Bioorg.Chem.|139|106745|doi:10.1016/j.bioorg.2023.106745
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.cc2g41nb
title: CCDC 2268011: Experimental Crystal Structure Determination

description: Related Article: Jinling Chang, Qianxi Ouyang, Xiaogang Peng, Jiao Pei, Linlin Zhang, Yutian Gan, Hanli Ruan|2023|Bioorg.Chem.|139|106745|doi:10.1016/j.bioorg.2023.106745
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.cc2g41pc
title: CCDC 2268012: Experimental Crystal Structure Determination

description: Related Article: Jinling Chang, Qianxi Ouyang, Xiaogang Peng, Jiao Pei, Linlin Zhang, Yutian Gan, Hanli Ruan|2023|Bioorg.Chem.|139|106745|doi:10.1016/j.bioorg.2023.106745
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.cc2d62b1
title: CCDC 2210372: Experimental Crystal Structure Determination

description: Related Article: Xue Bai, Xu Han, Yuxin Wang, Ange Zhang, Yanli Yang, Ying Lu, Shuxia Liu|2023|Inorg.Chem.|62|13221|doi:10.1021/acs.inorgchem.3c01393
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.8299627
title: Using sea level to determine the strength, structure and variability of the Cape Horn Current

description: This is the data used in the paper ('Using sea level to determine the strength, structure and variability of the Cape Horn Current').
DOI: 10.5281/zenodo.8299628
title: Using sea level to determine the strength, structure and variability of the Cape Horn Current

description: This is the data used in the paper ('Using sea level to determine the strength, structure and variability of the Cape Horn Current').