cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5517/ccdc.csd.cc2bntc6
title: CCDC 2164958: Experimental Crystal Structure Determination

description: Related Article: Kristina A. Lotsman, Konstantin S. Rodygin, Irina Skvortsova, Anastasia M. Kutskaya, Mikhail E. Minyaev, Valentine P. Ananikov|2023|Org.Chem.Front.|10|1022|doi:10.1039/D2QO01652D
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.cc2bntd7
title: CCDC 2164959: Experimental Crystal Structure Determination

description: Related Article: Kristina A. Lotsman, Konstantin S. Rodygin, Irina Skvortsova, Anastasia M. Kutskaya, Mikhail E. Minyaev, Valentine P. Ananikov|2023|Org.Chem.Front.|10|1022|doi:10.1039/D2QO01652D
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.cc2bntf8
title: CCDC 2164960: Experimental Crystal Structure Determination

description: Related Article: Kristina A. Lotsman, Konstantin S. Rodygin, Irina Skvortsova, Anastasia M. Kutskaya, Mikhail E. Minyaev, Valentine P. Ananikov|2023|Org.Chem.Front.|10|1022|doi:10.1039/D2QO01652D
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.5691575
title: Dataset for the paper "Universal attractors in language evolution provide evidence for the kinds of efficiency pressures involved"

description: Dataset for the paper "Universal attractors in language evolution provide evidence for the kinds of efficiency pressures involved"
DOI: 10.5281/zenodo.6022460
title: Dataset for the paper "Universal attractors in language evolution provide evidence for the kinds of efficiency pressures involved"

description: Dataset for the paper "Universal attractors in language evolution provide evidence for the kinds of efficiency pressures involved"
DOI: 10.5281/zenodo.5691574
title: Dataset for the paper "Universal attractors in language evolution provide evidence for the kinds of efficiency pressures involved"

description: CORRECTED Dataset for the paper "Universal attractors in language evolution provide evidence for the kinds of efficiency pressures involved"
DOI: 10.5281/zenodo.6023285
title: Dataset for the paper "Universal attractors in language evolution provide evidence for the kinds of efficiency pressures involved"

description: Dataset for the paper "Universal attractors in language evolution provide evidence for the kinds of efficiency pressures involved"
DOI: 10.5281/zenodo.6028260
title: Dataset for the paper "Universal attractors in language evolution provide evidence for the kinds of efficiency pressures involved"

description: Dataset for the paper "Universal attractors in language evolution provide evidence for the kinds of efficiency pressures involved"
DOI: 10.5281/zenodo.7641119
title: Dataset for the paper "Universal attractors in language evolution provide evidence for the kinds of efficiency pressures involved"

description: CORRECTED Dataset for the paper "Universal attractors in language evolution provide evidence for the kinds of efficiency pressures involved"
DOI: 10.5066/p9i31mdq
title: Microanalysis of samples collected from sandstone-hosted uranium and vanadium deposits in the Colorado Plateau: Utah, New Mexico and Colorado, USA

description: These data are microanalyses of 91 polished thin sections that were examined using a scanning electron microscope (SEM) equipped with an energy dispersive spectrometer (EDS) to identify minerals and observe their relationships at high magnification. Samples are from the Triassic Chinle and Jurassic Morrison Formations and adjacent units, which are the main hosts for sandstone-hosted uranium-vanadium deposits in the Colorado Plateau region. The samples were collected in 2019, 2020, and 2021 from mine dumps and surface mineralized rock at deposits throughout the Colorado Plateau in Utah and Colorado. Samples from New Mexico were from archival drill core and outcropping mineralized rock collected by Alexandra Pearce as part of her dissertation research at the New Mexico Institute of Mining and Technology, Socorro, New Mexico (Pearce, 2020) and were provided to USGS by Dr. Pearce for this study. The spectra for each EDS measurement are provided in separate documents in Portable Data Format (pdf), with one document for each thin section (e.g., BC-20-01B) that was examined. Element spectra were collected at multiple sites within each thin section, and at multiple spots at each site. Sites are arranged in numeric order in the PDF file for each thin section. The separation between sites is marked by a new image of the site showing the numbered spots for each site. For each sample site in the thin sections, three images (BSE, SEI, and MAP) are provided as part of this data release. The images are titled (e.g., BC-20-01B_BSE _001, BC-20-01B_SEI_001 and BC-20-01B_MAP_001), with the sample name (e.g., BC-20-01B) followed by the image type (e.g., SEI or BSE), then site number (e.g., 001). The naming convention for image types is "SEI? for images taken using a secondary electron detector and ?BSE? for images taken using the backscattered electron detector. An image ?MAP? is also provided for each analyzed site showing the location of this site on a composite BSE image of the thin section. These thin sections and rock samples are stored in the hot rocks room, Building 810, Denver Federal Center, Lakewood, Colorado, USA. Raw EDS data are saved in the Vendor?s proprietary data formats. Visual displays of the EDS spectrum can be saved by the Laboratory Analyst or User in any image format or in a MS Word document. Report options exist that will output elemental compositions based on the Vendor?s standardless analysis routines. These data are for informational purposes and are not to be used in publication. Quantitative elemental composition by EDS in the DML is not routine and outside the scope of this SOP
DOI: 10.6084/m9.figshare.22094810
title: Decolourisation of Reactive Red 120 by a Novel Bacterial Consortium: Kinetics and Heavy Metal Inhibition Study

description: The Juru River is one of the most polluted rivers in Malaysia. A dye-degrading bacterial consortium has been isolated from the river’s sediment. The influence of various metal ions on the growth rate of this bacterial consortium on the Reactive Red 120 dye was investigated. This consortium JR3, consist of <em>Pseudomonas aeruginosa</em> MM01, <em>Enterobacter</em> sp. MM05 and <em>Serratia marcescens</em> MM06 were able to decolourise up to 700 ppm of RR120 under an optimal condition with limited substrate available. Substrate inhibition kinetics was investigated and based on the best model Aiba, the maximum growth rate was 0.795 h-1, while the saturation constant, and inhibitory constant, were 0.185 % and 0.14 %, respectively. Chromium showed the least effect on the decolourisation of 200 ppm RR120 with 73.5% removal with bacterial growth of 11.461 log CFU/mL. Zinc was the second least effect followed by silver and lead, with the percentage of RR120 decolourisation of 63.8%, 54.6% and 50.5%, respectively. Meanwhile, cadmium, arsenic, and copper reduced the decolourisation of RR120 in consortium JR3 by half. Mercury strongly inhibited decolourisation by 32.5%. Based on the least inhibited heavy metal on RR120 decolourisation activity of consortium JR3, the best inhibition kinetic model was Levenspiel with a maximum growth rate at 0.632 h-1, while the saturation constant and inhibitory constants were 15.08 % and 0.5783 %, respectively. The metal-tolerant azo-dye-degrading bacterial consortium will be very useful in dye remediation in metal-laden polluted environment.
DOI: 10.6084/m9.figshare.22094810.v1
title: Decolourisation of Reactive Red 120 by a Novel Bacterial Consortium: Kinetics and Heavy Metal Inhibition Study

description: The Juru River is one of the most polluted rivers in Malaysia. A dye-degrading bacterial consortium has been isolated from the river’s sediment. The influence of various metal ions on the growth rate of this bacterial consortium on the Reactive Red 120 dye was investigated. This consortium JR3, consist of <em>Pseudomonas aeruginosa</em> MM01, <em>Enterobacter</em> sp. MM05 and <em>Serratia marcescens</em> MM06 were able to decolourise up to 700 ppm of RR120 under an optimal condition with limited substrate available. Substrate inhibition kinetics was investigated and based on the best model Aiba, the maximum growth rate was 0.795 h-1, while the saturation constant, and inhibitory constant, were 0.185 % and 0.14 %, respectively. Chromium showed the least effect on the decolourisation of 200 ppm RR120 with 73.5% removal with bacterial growth of 11.461 log CFU/mL. Zinc was the second least effect followed by silver and lead, with the percentage of RR120 decolourisation of 63.8%, 54.6% and 50.5%, respectively. Meanwhile, cadmium, arsenic, and copper reduced the decolourisation of RR120 in consortium JR3 by half. Mercury strongly inhibited decolourisation by 32.5%. Based on the least inhibited heavy metal on RR120 decolourisation activity of consortium JR3, the best inhibition kinetic model was Levenspiel with a maximum growth rate at 0.632 h-1, while the saturation constant and inhibitory constants were 15.08 % and 0.5783 %, respectively. The metal-tolerant azo-dye-degrading bacterial consortium will be very useful in dye remediation in metal-laden polluted environment.
DOI: 10.6084/m9.figshare.22094816
title: miRNA analysis in skeletal myotube-derived EVs

description: miRNA data in skeletal myotube-derived extracellular vesicles. <br>
DOI: 10.6084/m9.figshare.22090697.v1
title: Daymet_forcings_CAMELS

description: Only for use with the macrosheds R package
DOI: 10.6084/m9.figshare.21329823
title: Compact and accurate models for the diatomic potential energy

description: Two compact analytical models for the diatomic potential energy are presented and tested. The first (6-parameter) model represents a significant improvement on the extended Lennard-Jones (ELJ) function proposed by Hajigeorgiou [<i>J. Mol. Spectrosc.</i> <b>263</b>, 101 (2010)], and the second (7-parameter) model is a modified Hulburt-Hirschfelder function. The adjustable parameters of the two functions can be determined either by an algebraic scheme that employs semiclassical expressions in terms of vibrational-rotational molecular constants, or by direct nonlinear least-squares fits to available numerical potential functions. Accuracy tests are carried out for a set of ground electronic states of 30 diatomic molecules. The two potential energy functions give accurate representations of the available numerical potential energy curves with average deviations over the 30 molecules of approximately 0.06% of <i>D</i><sub>e</sub>, or 1 meV (∼ 8 cm<sup>−1</sup>). The best cases give average absolute deviations of 0.0002% of <i>D</i><sub>e</sub>, or 0.007 meV (∼ 0.06 cm<sup>−1</sup>). Quantum-mechanical vibrational eigenvalues of the new potential representations are shown for selected molecules to agree very well with the experimental vibrational energies, with average absolute deviations of much less than 1 cm<sup>−1</sup>.
DOI: 10.6084/m9.figshare.21329823.v1
title: Compact and accurate models for the diatomic potential energy

description: Two compact analytical models for the diatomic potential energy are presented and tested. The first (6-parameter) model represents a significant improvement on the extended Lennard-Jones (ELJ) function proposed by Hajigeorgiou [<i>J. Mol. Spectrosc.</i> <b>263</b>, 101 (2010)], and the second (7-parameter) model is a modified Hulburt-Hirschfelder function. The adjustable parameters of the two functions can be determined either by an algebraic scheme that employs semiclassical expressions in terms of vibrational-rotational molecular constants, or by direct nonlinear least-squares fits to available numerical potential functions. Accuracy tests are carried out for a set of ground electronic states of 30 diatomic molecules. The two potential energy functions give accurate representations of the available numerical potential energy curves with average deviations over the 30 molecules of approximately 0.06% of <i>D</i><sub>e</sub>, or 1 meV (∼ 8 cm<sup>−1</sup>). The best cases give average absolute deviations of 0.0002% of <i>D</i><sub>e</sub>, or 0.007 meV (∼ 0.06 cm<sup>−1</sup>). Quantum-mechanical vibrational eigenvalues of the new potential representations are shown for selected molecules to agree very well with the experimental vibrational energies, with average absolute deviations of much less than 1 cm<sup>−1</sup>.
DOI: 10.6084/m9.figshare.22060238
title: Higher productivity in forests with mixed mycorrhizal strategies

description: Dataset, readme, and r script used for "High productivity in forest with mixed mycorrhizal strategies" (Luo et al. Nature Communications) <br> This dataset includes 74,563 forest inventory plots, spanning 35 ecoregions in the contiguous USA. Total aboveground biomass, tree species richness, stand age, elevation, slope, and physiographic class were extracted from the FIA database. Climatic information and soil pH were added to each plot. <br>
DOI: 10.6084/m9.figshare.22060238.v2
title: Higher productivity in forests with mixed mycorrhizal strategies

description: Dataset, readme, and r script used for "High productivity in forest with mixed mycorrhizal strategies" (Luo et al. Nature Communications) <br> This dataset includes 74,563 forest inventory plots, spanning 35 ecoregions in the contiguous USA. Total aboveground biomass, tree species richness, stand age, elevation, slope, and physiographic class were extracted from the FIA database. Climatic information and soil pH were added to each plot. <br>
DOI: 10.5281/zenodo.7442218
title: Datasets supplementing journal article "Probing dynamic covalent chemistry in a 2D boroxine framework by in-situ near-ambient pressure X-ray photoelectron spectroscopy" in Nanoscale 2022

description: Datasets supporting the Nanoscale journal article "Probing dynamic covalent chemistry in a 2D boroxine framework by in-situ near-ambient pressure X-ray photoelectron spectroscopy". VT220321_A2_0009.zip: Scanning tunneling microscopy image, Figure 5a, inset. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 101007417, having benefited from the access provided by by ALBA in Barcelona (Spain) and CNR-IOM in Trieste (Italy) within the framework of the NFFA-Europe Pilot Transnational Access Activity, proposal ID075.
DOI: 10.5281/zenodo.7574174
title: Datasets supplementing journal article "Probing dynamic covalent chemistry in a 2D boroxine framework by in-situ near-ambient pressure X-ray photoelectron spectroscopy" in Nanoscale 2022

description: Datasets supporting the Nanoscale journal article "Probing dynamic covalent chemistry in a 2D boroxine framework by in-situ near-ambient pressure X-ray photoelectron spectroscopy". NAP-XPS.zip: Near-ambient pressure X-ray photoelectron spectroscopy, Figures 2, 3. (NEP 101007417) STM.zip: Scanning tunneling microscopy, Figure 5a, inset. (NEP 101007417) TPD.zip: Temperature programmed desorption, Figure 1a. UHV-XPS.zip: X-ray photoelectron spectroscopy, Figure 1b,c. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 101007417, having benefited from the access provided by by ALBA in Barcelona (Spain) and CNR-IOM in Trieste (Italy) within the framework of the NFFA-Europe Pilot Transnational Access Activity, proposal ID075.
DOI: 10.5281/zenodo.7641169
title: Datasets supplementing journal article "Probing dynamic covalent chemistry in a 2D boroxine framework by in-situ near-ambient pressure X-ray photoelectron spectroscopy" in Nanoscale 2022

description: Datasets supporting the Nanoscale journal article "Probing dynamic covalent chemistry in a 2D boroxine framework by in-situ near-ambient pressure X-ray photoelectron spectroscopy". NAP-XPS.zip: Near-ambient pressure X-ray photoelectron spectroscopy, Figures 2, 3. (NEP 101007417) STM.zip: Scanning tunneling microscopy, Figure 5a, inset. (NEP 101007417) TPD.zip: Temperature programmed desorption, Figure 1a. UHV-XPS.zip: X-ray photoelectron spectroscopy, Figure 1b,c. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 101007417, having benefited from the access provided by by ALBA in Barcelona (Spain) and CNR-IOM in Trieste (Italy) within the framework of the NFFA-Europe Pilot Transnational Access Activity, proposal ID075.
DOI: 10.6084/m9.figshare.20407857.v1
title: CScat

description: The first global long-term satellite radar backscatter data set with a C-band signal dynamic
DOI: 10.5281/zenodo.7641200
title: Data S1

description: <strong><em>Escherichia coli </em>genomic and phenotypic data</strong>
DOI: 10.5281/zenodo.7641199
title: Data S1

description: <strong><em>Escherichia coli </em>genomic and phenotypic data</strong>
DOI: 10.6084/m9.figshare.22090694.v2
title: watershed_summaries_CAMELS

description: Only for use with the macrosheds R package
DOI: 10.5281/zenodo.6777951
title: Numerical simulation of non-abelian anyons

description: We introduce an algorithm that allows to simulate anyonic tight-binding Hamiltonians on two-dimensional lattices. This dataset contains implementations of the basics algorithms as well as raw data used for the plots.
DOI: 10.5281/zenodo.7638790
title: Numerical simulation of non-abelian anyons

description: We introduce an algorithm that allows to simulate anyonic tight-binding Hamiltonians on two-dimensional lattices. This dataset contains implementations of the basics algorithms as well as raw data used for the plots.
DOI: 10.5281/zenodo.6777950
title: Numerical simulation of non-abelian anyons

description: We introduce an algorithm that allows to simulate anyonic tight-binding Hamiltonians on two-dimensional lattices. This dataset contains implementations of the basics algorithms as well as raw data used for the plots.
DOI: 10.5281/zenodo.7641207
title: Numerical simulation of non-abelian anyons

description: We introduce an algorithm that allows to simulate anyonic tight-binding Hamiltonians on two-dimensional lattices. This dataset contains implementations of the basics algorithms as well as raw data used for the plots.
DOI: 10.48324/dandi.000363/0.230214.1833
title: Mesoscale Activity Map Dataset

description: Mesoscale Activity Map Project. Map behavior-related activity in a multi-regional network supporting memory-guided movement in mice. Anatomy-guided recordings from multiple connected brain regions, from anterior lateral motor cortex to the medulla.

Supported by Simons Collaboration on the Global Brain, Janelia Visitor Project, NIH U19NS123714-01, R01NS112312, R01EB028171, McKnight foundation
DOI: 10.5517/ccdc.csd.cc2bq9lz
title: CCDC 2166391: Experimental Crystal Structure Determination

description: Related Article: Swah Mohd. Nashre-ul-Islam, Kamala Kanta Borah, Muhammad Asam Raza, Füreya Elif Öztürkkan|2023|Polyhedron|233|116304|doi:10.1016/j.poly.2023.116304
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.cc2btgyl
title: CCDC 2169440: Experimental Crystal Structure Determination

description: Related Article: Suinan Deng, Wenjun Luo, Lianjie Zhang, Guojing Xie, Shuyi Lei, Mei Luo, Zuhao Wu, Dong Yuan, Jiahao Liang, Zengqi Xie, Junwu Chen|2023|J.Mater.Chem.A|11|3437|doi:10.1039/D2TA09159C
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.cc2bwx5b
title: CCDC 2171772: Experimental Crystal Structure Determination

description: Related Article: Li Wang, Zhi Zhou, Jian-Ping Huang, Liang Zhang, Xiaotao Tuo, Zhiyin Yu, Sheng-Xiong Huang, Yang Liu, Jing Yang|2023|Org.Chem.Front.|10|880|doi:10.1039/D2QO01767A
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.cc2bwx6c
title: CCDC 2171773: Experimental Crystal Structure Determination

description: Related Article: Li Wang, Zhi Zhou, Jian-Ping Huang, Liang Zhang, Xiaotao Tuo, Zhiyin Yu, Sheng-Xiong Huang, Yang Liu, Jing Yang|2023|Org.Chem.Front.|10|880|doi:10.1039/D2QO01767A
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.cc2bydg5
title: CCDC 2173207: Experimental Crystal Structure Determination

description: Related Article: Yinran Wang, Lin Huang, Zhaomin Hou, Fang Guo|2023|Polym.Chem.|14|828|doi:10.1039/D2PY01526A
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.cc2bydyn
title: CCDC 2173222: Experimental Crystal Structure Determination

description: Related Article: Yinran Wang, Lin Huang, Zhaomin Hou, Fang Guo|2023|Polym.Chem.|14|828|doi:10.1039/D2PY01526A
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.cc2byf4w
title: CCDC 2173228: Experimental Crystal Structure Determination

description: Related Article: Yinran Wang, Lin Huang, Zhaomin Hou, Fang Guo|2023|Polym.Chem.|14|828|doi:10.1039/D2PY01526A
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.