cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5066/p9zwln0b
title: Hawaii Island airborne detection of fungal pathogens of Ohia, 2016-2017

description: This data release includes metadata and tabular datasets that document (1) Austropuccina, Ceratocystis and Myrtaceae qPCR (quantitative polymerase chain reaction) DNA detections in Passive Environmental Samplers (PES), (2) wind speed, wind gust speed, and wind direction measurements collected at two sites in the Kahuku Unit of Hawai'i Volcanoes National Park (HAVO) where paired PES were located, (3) localities, sites and elevations where PES were located, and (4) Genbank accession numbers for Austropuccinia and Ceratocystis DNA sequences amplified from samples collected in a subset of PES. These raw data were analyzed and reported in the manuscript &quot;Environmental Monitoring for Invasive Fungal Pathogens of ??hi?a (Metrosideros polymorpha) on the Island of Hawai?i&quot;.
DOI: 10.5517/ccdc.csd.cc2cz95v
title: CCDC 2203857: Experimental Crystal Structure Determination

description: Related Article: Wen-Juan Wei, Hong-Qiang Gao, Ming Fang, Yun-Zhi Tang, Yen Wei|2023|CrystEngComm|25|1333|doi:10.1039/D2CE01419J
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.cc2cz96w
title: CCDC 2203858: Experimental Crystal Structure Determination

description: Related Article: Wen-Juan Wei, Hong-Qiang Gao, Ming Fang, Yun-Zhi Tang, Yen Wei|2023|CrystEngComm|25|1333|doi:10.1039/D2CE01419J
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.cc2cz97x
title: CCDC 2203859: Experimental Crystal Structure Determination

description: Related Article: Wen-Juan Wei, Hong-Qiang Gao, Ming Fang, Yun-Zhi Tang, Yen Wei|2023|CrystEngComm|25|1333|doi:10.1039/D2CE01419J
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.cc2cz98y
title: CCDC 2203860: Experimental Crystal Structure Determination

description: Related Article: Wen-Juan Wei, Hong-Qiang Gao, Ming Fang, Yun-Zhi Tang, Yen Wei|2023|CrystEngComm|25|1333|doi:10.1039/D2CE01419J
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.cc2cz9b0
title: CCDC 2203862: Experimental Crystal Structure Determination

description: Related Article: Wen-Juan Wei, Hong-Qiang Gao, Ming Fang, Yun-Zhi Tang, Yen Wei|2023|CrystEngComm|25|1333|doi:10.1039/D2CE01419J
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.cc2d2w1f
title: CCDC 2207294: Experimental Crystal Structure Determination

description: Related Article: Ross Davidson, Yu-Ting Hsu, Mark A. Fox, Juan A. Aguilar, Dmitry Yufit, Andrew Beeby|2023|Inorg.Chem.|62|2793|doi:10.1021/acs.inorgchem.2c03934
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.cc2d2w2g
title: CCDC 2207295: Experimental Crystal Structure Determination

description: Related Article: Ross Davidson, Yu-Ting Hsu, Mark A. Fox, Juan A. Aguilar, Dmitry Yufit, Andrew Beeby|2023|Inorg.Chem.|62|2793|doi:10.1021/acs.inorgchem.2c03934
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.cc2d2w4j
title: CCDC 2207297: Experimental Crystal Structure Determination

description: Related Article: Ross Davidson, Yu-Ting Hsu, Mark A. Fox, Juan A. Aguilar, Dmitry Yufit, Andrew Beeby|2023|Inorg.Chem.|62|2793|doi:10.1021/acs.inorgchem.2c03934
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.cc2d2w6l
title: CCDC 2207299: Experimental Crystal Structure Determination

description: Related Article: Ross Davidson, Yu-Ting Hsu, Mark A. Fox, Juan A. Aguilar, Dmitry Yufit, Andrew Beeby|2023|Inorg.Chem.|62|2793|doi:10.1021/acs.inorgchem.2c03934
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.cc2d4qr1
title: CCDC 2209083: Experimental Crystal Structure Determination

description: Related Article: Lian Wang, Zhenhua Wen, Yulin Xu, Youming Zhang, Jingsheng Miao, Zhanxiang Chen, Kai Li|2023|Mater. Chem. Front.|7|873|doi:10.1039/D2QM01163H
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.cc2d4qs2
title: CCDC 2209084: Experimental Crystal Structure Determination

description: Related Article: Lian Wang, Zhenhua Wen, Yulin Xu, Youming Zhang, Jingsheng Miao, Zhanxiang Chen, Kai Li|2023|Mater. Chem. Front.|7|873|doi:10.1039/D2QM01163H
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.cc2d4qt3
title: CCDC 2209085: Experimental Crystal Structure Determination

description: Related Article: Lian Wang, Zhenhua Wen, Yulin Xu, Youming Zhang, Jingsheng Miao, Zhanxiang Chen, Kai Li|2023|Mater. Chem. Front.|7|873|doi:10.1039/D2QM01163H
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.cc2d4qv4
title: CCDC 2209086: Experimental Crystal Structure Determination

description: Related Article: Lian Wang, Zhenhua Wen, Yulin Xu, Youming Zhang, Jingsheng Miao, Zhanxiang Chen, Kai Li|2023|Mater. Chem. Front.|7|873|doi:10.1039/D2QM01163H
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.21890718.v1
title: Data from: Contrasting effects of fungicide and herbicide active ingredients and their formulations on bumblebee learning and behaviour

description: This dataset contains data collecting during a Proboscis Extension Reflex paradigm experiment on the effects of fungicides and herbicides on bee behaviour. <br> Fungicides and herbicides are two of the most heavily applied pesticide classes in the world, but receive little research attention with regards to their potential impacts on bees. As they are not designed to target insects, the mechanisms behind potential impacts of these pesticides are unclear. It is therefore important to understand their influence at a range of levels, including sublethal impacts on behaviours like learning. We used the proboscis extension reflex (PER) paradigm to assess how the herbicide glyphosate and the fungicide prothioconazole affect bumblebee olfactory learning. We also assessed responsiveness, and compared the impacts of active ingredient and commercial formulations of both compounds (Roundup biactive and Proline, respectively). We found that learning was not impaired by either formulation but, of the bees which displayed evidence of learning, exposure to prothioconazole active ingredient increased learning level in some situations, while exposure to glyphosate active ingredient resulted in bumblebees being less likely to respond to antennal stimulation with sucrose. Our data suggest that fungicides and herbicides may not negatively impact olfactory learning ability when bumblebees are exposed orally to field-realistic doses in a lab setting, but that glyphosate has the potential to cause changes in responsiveness in bees.
DOI: 10.5281/zenodo.7554325
title: Data Archive: Local and Global Order in Dense Packings of Semiflexible Polymers of Hard Spheres

description: Data archive corresponding to the publication "Local and Global Order in Dense Packings of Semi-flexible 2 Polymers of Hard Spheres" by D. Martinez-Fernandez et al., Polymers 15, 551 (2023); DOI: https://doi.org/10.3390/polym15030551. Please see README.txt for instructions on how to access and read the files from the crystallographic analysis based on the CCE norm descriptor. All snapshots have been generated and successively analyzed by the Simu-D software.
description: This research was funded by MICINN/FEDER (Ministerio de Ciencia, Innovación y Universidades, Fondo Europeo de Desarrollo Regional), grant numbers "RTI2018-097338-B-I00" and "PID2021-127533NB-I00" and by UPM and Santander Bank, "Programa Propio UPM Santander"
description: {"references": ["Ramos, P.M.; Herranz, M.; Foteinopoulou, K.; Karayiannis, N.C.; Laso, M. Identification of Local Structure in 2-D and 3-D Atomic Systems through Crystallographic Analysis. Crystals 2020, 10, 1008. https://doi.org/10.3390/cryst10111008", "Herranz, M.; Mart\u00ednez-Fern\u00e1ndez, D.; Ramos, P.M.; Foteinopoulou, K.; Karayiannis, N.C.; Laso, M. Simu-D: A Simulator-Descriptor Suite for Polymer-Based Systems under Extreme Conditions. Int. J. Mol. Sci. 2021, 22, 12464. https://doi.org/10.3390/ijms222212464", "Mart\u00ednez-Fern\u00e1ndez, D.; Herranz, M.; Foteinopoulou, K.; Karayiannis, N.C.; Laso, M. Local and Global Order in Dense Packings of Semi-flexible Polymers of Hard Spheres. Polymers 2023, 15, 551. https://doi.org/10.3390/polym15030551"]}
DOI: 10.5281/zenodo.7554324
title: Data Archive: Local and Global Order in Dense Packings of Semiflexible Polymers of Hard Spheres

description: Data archive corresponding to the publication "Local and Global Order in Dense Packings of Semi-flexible 2 Polymers of Hard Spheres" by D. Martinez-Fernandez et al., Polymers 15, 551 (2023); DOI: https://doi.org/10.3390/polym15030551. Please see README.txt for instructions on how to access and read the files from the crystallographic analysis based on the CCE norm descriptor. All snapshots have been generated and successively analyzed by the Simu-D software.
description: This research was funded by MICINN/FEDER (Ministerio de Ciencia, Innovación y Universidades, Fondo Europeo de Desarrollo Regional), grant numbers "RTI2018-097338-B-I00" and "PID2021-127533NB-I00" and by UPM and Santander Bank, "Programa Propio UPM Santander"
description: {"references": ["Ramos, P.M.; Herranz, M.; Foteinopoulou, K.; Karayiannis, N.C.; Laso, M. Identification of Local Structure in 2-D and 3-D Atomic Systems through Crystallographic Analysis. Crystals 2020, 10, 1008. https://doi.org/10.3390/cryst10111008", "Herranz, M.; Mart\u00ednez-Fern\u00e1ndez, D.; Ramos, P.M.; Foteinopoulou, K.; Karayiannis, N.C.; Laso, M. Simu-D: A Simulator-Descriptor Suite for Polymer-Based Systems under Extreme Conditions. Int. J. Mol. Sci. 2021, 22, 12464. https://doi.org/10.3390/ijms222212464", "Mart\u00ednez-Fern\u00e1ndez, D.; Herranz, M.; Foteinopoulou, K.; Karayiannis, N.C.; Laso, M. Local and Global Order in Dense Packings of Semi-flexible Polymers of Hard Spheres. Polymers 2023, 15, 551. https://doi.org/10.3390/polym15030551"]}
DOI: 10.5281/zenodo.7682587
title: Polymorphism and Perfection in Crystallization of Hard Sphere Polymers

description: Data archive corresponding to the publications "Polymorphism and Perfection in Crystallization of Hard Sphere Polymers" by M. Herranz et al., Polymers 14, 4435 (2022); DOI: https://doi.org/10.3390/polym14204435 Please see README.txt for instructions on how to access and read the files from the crystallographic analysis based on the CCE norm descriptor. All snapshots have been generated and successively analyzed by the Simu-D software.
description: This research was funded by MICINN/FEDER (Ministerio de Ciencia, Innovación y Universidades, Fondo Europeo de Desarrollo Regional), grant numbers "RTI2018-097338-B-I00" and "PID2021-127533NB-I00" and by UPM and Santander Bank, "Programa Propio UPM Santander".
description: {"references": ["Ramos, P.M.; Herranz, M.; Foteinopoulou, K.; Karayiannis, N.C.; Laso, M. Identification of Local Structure in 2-D and 3-D Atomic Systems through Crystallographic Analysis. Crystals 2020, 10, 1008. https://doi.org/10.3390/cryst10111008", "Herranz, M.; Mart\u00ednez-Fern\u00e1ndez, D.; Ramos, P.M.; Foteinopoulou, K.; Karayiannis, N.C.; Laso, M. Simu-D: A Simulator-Descriptor Suite for Polymer-Based Systems under Extreme Conditions. Int. J. Mol. Sci. 2021, 22, 12464. https://doi.org/10.3390/ijms222212464", "Herranz, M.; Foteinopoulou, K.; Karayiannis, N.C.; Laso, M. Polymorphism and Perfection in Crystallization of Hard Sphere Polymers. Polymers 2022, 14, 4435. https://doi.org/10.3390/polym14204435"]}
DOI: 10.5281/zenodo.7682586
title: Polymorphism and Perfection in Crystallization of Hard Sphere Polymers

description: Data archive corresponding to the publications "Polymorphism and Perfection in Crystallization of Hard Sphere Polymers" by M. Herranz et al., Polymers 14, 4435 (2022); DOI: https://doi.org/10.3390/polym14204435 Please see README.txt for instructions on how to access and read the files from the crystallographic analysis based on the CCE norm descriptor. All snapshots have been generated and successively analyzed by the Simu-D software.
description: This research was funded by MICINN/FEDER (Ministerio de Ciencia, Innovación y Universidades, Fondo Europeo de Desarrollo Regional), grant numbers "RTI2018-097338-B-I00" and "PID2021-127533NB-I00" and by UPM and Santander Bank, "Programa Propio UPM Santander".
description: {"references": ["Ramos, P.M.; Herranz, M.; Foteinopoulou, K.; Karayiannis, N.C.; Laso, M. Identification of Local Structure in 2-D and 3-D Atomic Systems through Crystallographic Analysis. Crystals 2020, 10, 1008. https://doi.org/10.3390/cryst10111008", "Herranz, M.; Mart\u00ednez-Fern\u00e1ndez, D.; Ramos, P.M.; Foteinopoulou, K.; Karayiannis, N.C.; Laso, M. Simu-D: A Simulator-Descriptor Suite for Polymer-Based Systems under Extreme Conditions. Int. J. Mol. Sci. 2021, 22, 12464. https://doi.org/10.3390/ijms222212464", "Herranz, M.; Foteinopoulou, K.; Karayiannis, N.C.; Laso, M. Polymorphism and Perfection in Crystallization of Hard Sphere Polymers. Polymers 2022, 14, 4435. https://doi.org/10.3390/polym14204435"]}
DOI: 10.6084/m9.figshare.22185862.v1
title: Beyond Simple Trend Tests: Detecting Significant Changes in Design-Flood Quantiles

description: The text files contain AMF data of USGS basins File names include the USGS site number AMF record end year is 2015 with varying start year for all basins
DOI: 10.6084/m9.figshare.22185862
title: Beyond Simple Trend Tests: Detecting Significant Changes in Design-Flood Quantiles

description: The text files contain AMF data of USGS basins File names include the USGS site number AMF record end year is 2015 with varying start year for all basins
DOI: 10.25345/c50p0x15f
title: MassIVE MSV000091374 - Dataset Zaupa et al, whole-larva proteome from 7dpf fed zebrafish larvae and non-fed siblings.
title: Whole-larva proteome from 7dpf fed zebrafish larvae and non-fed siblings.
DOI: 10.5281/zenodo.7679700
title: Internal gravity waves generated by subglacial discharge: Implications for tidewater glacier melt.

description: Additional data used in the paper titled "Internal gravity waves generated by subglacial discharge: implications for tidewater glacier melt", submitted to Geophysical Research Letters, that is not already contained in the GitHub repository.
DOI: 10.5281/zenodo.7679699
title: Internal gravity waves generated by subglacial discharge: Implications for tidewater glacier melt.

description: Additional data used in the paper titled "Internal gravity waves generated by subglacial discharge: implications for tidewater glacier melt", submitted to Geophysical Research Letters, that is not already contained in the GitHub repository.
DOI: 10.15468/qp8aqx
title: Range and Regularities in the Distribution of Earthworms of the Earthworms of the USSR Fauna. Perel, 1979

description: Checklist based on the earthworm fauna of the USSR published by Tamara Perel in 1979. This monograph presents a taxonomy used by earthworm researchers in Soviet Union and countries of Eastern Europe.
DOI: 10.5281/zenodo.5784287
title: Homogenized anisotropic thermal conductivity on microstructure of binary composite with thermally imperfect diffuse interface

description: This dataset contains supplementary data and utilities of the publication "A diffuse-interface model of anisotropic interface thermal conductivity and its application in thermal homogenization of composites" (Yang, 2022). We performed thermal homogenization on microstructures with three types of inclusion geometries, in which ones with oval-shaped and fiber-shaped inclusions were read from characterized/generated digital microstructures, and ones with irregular-shaped inclusions were imported from the phase-field additive manufacturing simulations (Zhou, 2021). Si-Hf-N was chosen as the composite material system with β-Si<sub>3</sub>N<sub>4</sub> as the sole matrix phase and HfN as the sole inclusion phase. Direct homogenization method with the linear temperature BCs (see Supplementary Note 3 of the publication) was adopted. This dataset documents homogenized anisotropic thermal conductivity of corresponding microstructure as a tensor with normalized interface thermal resistance varying from 10<sup>-8</sup> to 10<sup>12</sup>. Voxelized digital microstructures and utilities for visualizing the overall thermal anisotropy are also attached. Properties Value Dimension Description \(k_\mathrm{(i)}\) 90 \(\mathrm{W~m^{-1}~K^{-1}}\) Thermal conductivity of HfN inclusion (Li, 2020) \(k_\mathrm{(m)}\) 180 \(\mathrm{W~m^{-1}~K^{-1}}\) Thermal conductivity of β-Si<sub>3</sub>N<sub>4</sub> matrix (Li, 1999) \(\ell\) 5 \(\mathrm{nm}\) Diffuse interface width \((X,Y,Z)\) (500,500,500) \(\mathrm{nm}\) Simulation domain size <strong>Notice:</strong> The digital microstructure has been voxelized, which can be loaded by default as a 200x200x200 numpy array (see utilities.ipynb). In order to perform the homogenization, interface smoothening is required, i.e., to generate diffuse interfaces. In this work, we smoothened the interface by operating transient Allen-Cahn calculation with finite timesteps. See Supplementary Note 4 of the publication for more information.
DOI: 10.5281/zenodo.5784288
title: Homogenized anisotropic thermal conductivity on microstructure of binary composite with thermally imperfect diffuse interface

description: This dataset contains supplementary data and utilities of the publication "A diffuse-interface model of anisotropic interface thermal conductivity and its application in thermal homogenization of composites" (Yang, 2022). We performed thermal homogenization on microstructures with three types of inclusion geometries, in which ones with oval-shaped and fiber-shaped inclusions were read from characterized/generated digital microstructures, and ones with irregular-shaped inclusions were imported from the phase-field additive manufacturing simulations (Zhou, 2021). Si-Hf-N was chosen as the composite material system with β-Si<sub>3</sub>N<sub>4</sub> as the sole matrix phase and HfN as the sole inclusion phase. Direct homogenization method with the linear temperature BCs (see Supplementary Note 3 of the publication) was adopted. This dataset documents homogenized anisotropic thermal conductivity of corresponding microstructure as a tensor with normalized interface thermal resistance varying from 10<sup>-8</sup> to 10<sup>12</sup>. Voxelized digital microstructures and utilities for visualizing the overall thermal anisotropy are also attached. Properties Value Dimension Description \(k_\mathrm{(i)}\) 90 \(\mathrm{W~m^{-1}~K^{-1}}\) Thermal conductivity of HfN inclusion (Li, 2020) \(k_\mathrm{(m)}\) 180 \(\mathrm{W~m^{-1}~K^{-1}}\) Thermal conductivity of β-Si<sub>3</sub>N<sub>4</sub> matrix (Li, 1999) \(\ell\) 5 \(\mathrm{nm}\) Diffuse interface width \((X,Y,Z)\) (500,500,500) \(\mathrm{nm}\) Simulation domain size <strong>Notice:</strong> The digital microstructure has been voxelized, which can be loaded by default as a 200x200x200 numpy array (see utilities.ipynb). In order to perform the homogenization, interface smoothening is required, i.e., to generate diffuse interfaces. In this work, we smoothened the interface by operating transient Allen-Cahn calculation with finite timesteps. See Supplementary Note 4 of the publication for more information.