cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5517/ccdc.csd.cc2dx81n
title: CCDC 2231691: Experimental Crystal Structure Determination

description: Related Article: Eric C. Moinet, Benjamin M. Wolf, Olivier Tardif, Cäcilia Maichle-Mössmer, Reiner Anwander|2023|Angew.Chem.,Int.Ed.|62|e202219316|doi:10.1002/anie.202219316
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.cc2dx82p
title: CCDC 2231692: Experimental Crystal Structure Determination

description: Related Article: Eric C. Moinet, Benjamin M. Wolf, Olivier Tardif, Cäcilia Maichle-Mössmer, Reiner Anwander|2023|Angew.Chem.,Int.Ed.|62|e202219316|doi:10.1002/anie.202219316
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.cc2dx83q
title: CCDC 2231693: Experimental Crystal Structure Determination

description: Related Article: Eric C. Moinet, Benjamin M. Wolf, Olivier Tardif, Cäcilia Maichle-Mössmer, Reiner Anwander|2023|Angew.Chem.,Int.Ed.|62|e202219316|doi:10.1002/anie.202219316
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.cc2dx84r
title: CCDC 2231694: Experimental Crystal Structure Determination

description: Related Article: Eric C. Moinet, Benjamin M. Wolf, Olivier Tardif, Cäcilia Maichle-Mössmer, Reiner Anwander|2023|Angew.Chem.,Int.Ed.|62|e202219316|doi:10.1002/anie.202219316
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.cc2dx85s
title: CCDC 2231695: Experimental Crystal Structure Determination

description: Related Article: Eric C. Moinet, Benjamin M. Wolf, Olivier Tardif, Cäcilia Maichle-Mössmer, Reiner Anwander|2023|Angew.Chem.,Int.Ed.|62|e202219316|doi:10.1002/anie.202219316
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.cc2dx86t
title: CCDC 2231696: Experimental Crystal Structure Determination

description: Related Article: Eric C. Moinet, Benjamin M. Wolf, Olivier Tardif, Cäcilia Maichle-Mössmer, Reiner Anwander|2023|Angew.Chem.,Int.Ed.|62|e202219316|doi:10.1002/anie.202219316
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.cc2dx87v
title: CCDC 2231697: Experimental Crystal Structure Determination

description: Related Article: Eric C. Moinet, Benjamin M. Wolf, Olivier Tardif, Cäcilia Maichle-Mössmer, Reiner Anwander|2023|Angew.Chem.,Int.Ed.|62|e202219316|doi:10.1002/anie.202219316
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.cc2dx88w
title: CCDC 2231698: Experimental Crystal Structure Determination

description: Related Article: Eric C. Moinet, Benjamin M. Wolf, Olivier Tardif, Cäcilia Maichle-Mössmer, Reiner Anwander|2023|Angew.Chem.,Int.Ed.|62|e202219316|doi:10.1002/anie.202219316
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.cc2dxfmd
title: CCDC 2231864: Experimental Crystal Structure Determination

description: Related Article: Tiron H. L. Jahinge, Daniel K. Unruh, Tori Z. Forbes|2023|Eur.J.Inorg.Chem.|26|e202200791|doi:10.1002/ejic.202200791
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.cc2dxfnf
title: CCDC 2231865: Experimental Crystal Structure Determination

description: Related Article: Tiron H. L. Jahinge, Daniel K. Unruh, Tori Z. Forbes|2023|Eur.J.Inorg.Chem.|26|e202200791|doi:10.1002/ejic.202200791
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.cc2dxfpg
title: CCDC 2231866: Experimental Crystal Structure Determination

description: Related Article: Tiron H. L. Jahinge, Daniel K. Unruh, Tori Z. Forbes|2023|Eur.J.Inorg.Chem.|26|e202200791|doi:10.1002/ejic.202200791
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.cc2dz7c0
title: CCDC 2233592: Experimental Crystal Structure Determination

description: Related Article: Dong-Yang Li, Huai-Yuan Kang, Yu-Hang Liu, Jie Zhang, Cheng-Yang Yue, Dongpeng Yan, Xiao-Wu Lei|2024|Chemical Science|15|953|doi:10.1039/D3SC05245A
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.20453658.v3
title: Development of a multiplicative model to explore how biological nitrogen fixation responses to multiple edaphic factors in paddy soils.

description:  Various sole edaphic factor has been screened as controlling factor for paddy biological nitrogen fixation (BNF), however, no single factor can interpret different results from different experiments. Paddy BNF might be influenced by several factors simultaneously at various degrees, but we still lack a model to predict BNF as a function of multiple edaphic factors. Developing this model will help us to estimate BNF based on soil properties and improve policy decisions to enhance paddy BNF. In this paper, 27 paddy soil samples with different soil properties were collected from the southwest to the northeast in China. These soils with rice plantations were incubated for 77 days in an airtight, transparent, and <sup>15</sup>N<sub>2</sub> enriched growth chamber to measure BNF. Results showed that BNF amounts ranged from 0.66 to 12.3 kg ha<sup>-1</sup> and had a lognormal distribution. A multiplicative model was developed, the R code and raw data were deposited in this project. This multiplicative model could explain 86% variance of the BNF in various soils. In each site, the controlling factors were screened and corresponding measures to enhance BNF were proposed. Our study provided a systematic framework on how BNF responded to a range of edaphic factors simultaneously in paddy soils, and this work might also give inspiration for the study of other ecological functions.
DOI: 10.5281/zenodo.10525919
title: The Influence of Characteristic Town Tourism Attractions on Tourists' Revisit Intentions
DOI: 10.5281/zenodo.10525920
title: The Influence of Characteristic Town Tourism Attractions on Tourists' Revisit Intentions
DOI: 10.18112/openneuro.ds004910.v1.0.1
title: An open relaxation-diffusion MRI dataset in neurosurgical studies
DOI: 10.21947/2228416
title: Gulf of Mexico Turbulence Intensity Model Data

description: The dataset is a subset of simulations carried out for the Gulf of Mexico region using the revised Weather Research and Forecasting (WRF) model version 4.2 that incorporates the implementation of online turbulence intensity (TI) calculations (Tai et al. 2023). The simulated atmospheric profiles near the Shell Exploration and Production Corporation's Tension Leg Platforms Ursa and Mars are archived. Physics parameterizations chosen for the simulations include the Thompson microphysics parameterization, Mellor-Yamada-Nakanishi Niino (MYNN) boundary layer parameterization, Mellor-Yamada-Janjic surface layer parameterization, Unified Noah land-surface parameterization, and the RRTMG longwave and shortwave radiation parameterization. Initial and boundary conditions are taken from NOAA’s High-Resolution Rapid Refresh (HRRR) product. The JPL 0.01-degree Level 4 Multiscale Ultrahigh Resolution (MUR) Global Foundation Sea Surface Temperature (SST) Analysis (V4.1) data are used as the model’s SST forcing. Simulations are performed from January through June in 2020 and output every 10 minutes, which permits comparison with corresponding lidar observations.
DOI: 10.6084/m9.figshare.24907428.v2
title: <b>Correlation of Prolonged Sitting Time and Sitting Posture on Low Back Pain: A Cross-Sectional Study among Medical Students at Universitas Sumatera Utara</b>

description: Background: Low Back Pain (LBP) is the most common musculoskeletal disorder in the world. Medical students, particularly those who use computers for study purposes, are more vulnerable to LBP due to prolonged sitting times and improper sitting posture during lectures. However, prior research showed that the prevalence of LBP among medical students appeared lower when they were enrolled during online pandemic learning. Hence, this research is performed to determine the correlation between the duration of sitting and sitting posture on the incidence of LBP among medical students in Universitas Sumatera Utara, Indonesia. Methods: A cross-sectional study with an analytical descriptive design was conducted in September 2023 among randomly selected 147 medical students at Universitas Sumatera Utara, Indonesia. The inclusion criteria of the research sample are students with BMI&lt; 23 kg/m2 while the exclusion criteria are students who have abnormalities and a history of trauma or spinal fractures. Data was obtained from filling out questionnaires of The Pain and Distress Scale (PAD) and Body Awareness of Postural Habit in Young People (BAPHY). A Chi-square test and logistic regression were used to analyze data with a p-value &lt; 0.05 was regarded as statistically significant. Results: The study's findings revealed that 40.1% of students reported having LBP problems, 72.1% reported sitting for more than seven hours each day, and 33.3% reported having a bad sitting posture. Chi-square analysis revealed a significant correlation between sitting duration and posture on complaints of lower back pain (RR = 1.69, p = 0.041 and RR = 1.69, p = 0.009). At a risk of 2,438 times, sitting posture is the main factor contributing to LBP among medical students at Universitas Sumatera Utara, Indonesia. Conclusions: This research showed a significant correlation between duration and sitting posture on the incidence of low back pain.
DOI: 10.21947/2279184
title: Gulf of Mexico Turbulence Intensity Model Data in Observational Space

description: The dataset archives model-simulated turbulence intensity and meteorological profiles and timeseries at the Shell Exploration and Production Corporation's Tension Leg Platforms Ursa and Mars. The simulated data are interpolated in time and/or space according to observed quantities. The simulations were carried out for the Gulf of Mexico region using the revised Weather Research and Forecasting (WRF) model version 4.2 that incorporates the implementation of online turbulence intensity (TI) calculations (Tai et al. 2023). The simulated atmospheric profiles near the Shell Exploration and Production Corporation's Tension Leg Platforms Ursa and Mars are archived. Physics parameterizations chosen for the simulations include the Thompson microphysics parameterization, Mellor-Yamada-Nakanishi Niino (MYNN) boundary layer parameterization, Mellor-Yamada-Janjic surface layer parameterization, Unified Noah land-surface parameterization, and the RRTMG longwave and shortwave radiation parameterization. Initial and boundary conditions are taken from NOAA’s High-Resolution Rapid Refresh (HRRR) product. The JPL 0.01-degree Level 4 Multiscale Ultrahigh Resolution (MUR) Global Foundation Sea Surface Temperature (SST) Analysis (V4.1) data are used as the model’s SST forcing.
DOI: 10.21947/2280860
title: Mid-Atlantic Turbulence Intensity Model Data

description: The dataset is a subset of simulations carried out for the mid-Atlantic region using the revised Weather Research and Forecasting (WRF) model version 4.2 that incorporates the implementation of online turbulence intensity (TI) calculations (Tai et al. 2023). The simulated atmospheric profiles near the Air-Sea Interaction Tower (ASIT) of Woods Hole Oceanographic Institution’s Martha's Vineyard Coastal Observatory are archived. Physics parameterizations chosen for the simulations include the Thompson microphysics parameterization, Mellor-Yamada-Nakanishi Niino (MYNN) boundary layer parameterization, Mellor-Yamada-Janjic surface layer parameterization, Unified Noah land-surface parameterization, and the RRTMG longwave and shortwave radiation parameterization. Initial and boundary conditions are taken from NOAA’s High-Resolution Rapid Refresh (HRRR) product. The JPL 0.01-degree Level 4 Multiscale Ultrahigh Resolution (MUR) Global Foundation Sea Surface Temperature (SST) Analysis (V4.1) data are used as the model’s SST forcing. Simulations are performed from February through June in 2020 and output every 10 minutes, which permits comparison with corresponding lidar observations.
DOI: 10.21947/2280861
title: Mid-Atlantic Turbulence Intensity Data in Observational Space

description: The dataset archives observed and model-simulated turbulence intensity and meteorological profiles and timeseries at the Air-Sea Interaction Tower (ASIT) of Woods Hole Oceanographic Institution’s Martha’s Vineyard Coastal Observatory (MVCO). The observational data were measured by lidar and buoy deployed at ASIT. The simulated profiles and timeseries data are interpolated in time and/or space according to observations. Simulations were carried out for the mid-Atlantic region using the revised Weather Research and Forecasting (WRF) model version 4.2 that incorporates the implementation of online turbulence intensity (TI) calculations (Tai et al. 2023). The simulated atmospheric profiles at the Shell Exploration and Production Corporation's Tension Leg Platforms Ursa and Mars are archived. Physics parameterizations chosen for the simulations include the Thompson microphysics parameterization, Mellor-Yamada-Nakanishi Niino (MYNN) boundary layer parameterization, Mellor-Yamada-Janjic surface layer parameterization, Unified Noah land-surface parameterization, and the RRTMG longwave and shortwave radiation parameterization. Initial and boundary conditions are taken from NOAA’s High-Resolution Rapid Refresh (HRRR) product. The JPL 0.01-degree Level 4 Multiscale Ultrahigh Resolution (MUR) Global Foundation Sea Surface Temperature (SST) Analysis (V4.1) data are used as the model’s SST forcing.
DOI: 10.21947/2280862
title: Northern Pacific Turbulence Intensity Model Data

description: The dataset is a subset of simulations carried out for the northern Pacific region using the revised Weather Research and Forecasting (WRF) model version 4.2 that incorporates the implementation of online turbulence intensity (TI) calculations (Tai et al. 2023). The simulated atmospheric profiles near the lidar buoys deployed off the coast of California (Humbolt and Morro Bay) are archived. Physics parameterizations chosen for the simulations include the Thompson microphysics parameterization, Mellor-Yamada-Nakanishi Niino (MYNN) boundary layer parameterization, Mellor-Yamada-Janjic surface layer parameterization, Unified Noah land-surface parameterization, and the RRTMG longwave and shortwave radiation parameterization. Initial and boundary conditions are taken from NOAA’s High-Resolution Rapid Refresh (HRRR) product. The JPL 0.01-degree Level 4 Multiscale Ultrahigh Resolution (MUR) Global Foundation Sea Surface Temperature (SST) Analysis (V4.1) data are used as the model’s SST forcing. Simulations are performed from November to December in 2020 and May through June in 2021. Model outputs every 10 minutes, permitting comparison with corresponding lidar observations.
DOI: 10.21947/2280863
title: Northern Pacific Turbulence Intensity Model Data in Observational Space

description: The dataset archives model-simulated turbulence intensity and meteorological profiles and timeseries at the lidar buoys sites off the coast of California (Humboldt and Morro Bay). The simulated data are interpolated in time and/or space according to observed quantities. The simulations were carried out for the north Pacific region using the revised Weather Research and Forecasting (WRF) model version 4.2 that incorporates the implementation of online turbulence intensity (TI) calculations (Tai et al. 2023). The simulated atmospheric profiles near the Shell Exploration and Production Corporation's Tension Leg Platforms Ursa and Mars are archived. Physics parameterizations chosen for the simulations include the Thompson microphysics parameterization, Mellor-Yamada-Nakanishi Niino (MYNN) boundary layer parameterization, Mellor-Yamada-Janjic surface layer parameterization, Unified Noah land-surface parameterization, and the RRTMG longwave and shortwave radiation parameterization. Initial and boundary conditions are taken from NOAA’s High-Resolution Rapid Refresh (HRRR) product. The JPL 0.01-degree Level 4 Multiscale Ultrahigh Resolution (MUR) Global Foundation Sea Surface Temperature (SST) Analysis (V4.1) data are used as the model’s SST forcing.
DOI: 10.6084/m9.figshare.25017077
title: Supplementary Material S3 from A framework for quantifying geodiversity at the local scale: a case study from the Rokua UNESCO Global Geopark

description: The study dataset
DOI: 10.6084/m9.figshare.25017077.v1
title: Supplementary Material S3 from A framework for quantifying geodiversity at the local scale: a case study from the Rokua UNESCO Global Geopark

description: The study dataset
DOI: 10.6084/m9.figshare.25017083
title: Supplementary Material S4 from A framework for quantifying geodiversity at the local scale: a case study from the Rokua UNESCO Global Geopark

description: The R code for conducting the analysis
DOI: 10.6084/m9.figshare.25017083.v1
title: Supplementary Material S4 from A framework for quantifying geodiversity at the local scale: a case study from the Rokua UNESCO Global Geopark

description: The R code for conducting the analysis
DOI: 10.17188/mpcontribs/2281590
title: The ab initio amorphous materials database: Empowering machine learning to decode diffusivity

description: Amorphous materials exhibit unique properties that make them suitable for
various applications in science and technology, ranging from optical and electronic
devices and solid-state batteries to protective coatings. However, data-driven ex-
ploration and design of amorphous materials is hampered by the absence of a com-
prehensive database covering a broad chemical space. In this work, we present
the largest computed amorphous materials database to date, generated from sys-
tematic and accurate ab initio molecular dynamics (AIMD) calculations. We also
show how the database can be used in simple machine-learning models to connect
properties to composition and structure, here specifically targeting ionic conductiv-
ity. These models predict the Li-ion diffusivity with speed and accuracy, offering a
cost-effective alternative to expensive density functional theory (DFT) calculations.
Furthermore, the process of computational quenching amorphous materials provides
a unique sampling of out-of-equilibrium structures, energies, and force landscape,
and we anticipate that the corresponding trajectories will inform future work in uni-
versal machine learning potentials, impacting design beyond that of non-crystalline
materials.
DOI: 10.5517/ccdc.csd.cc28ss62
title: CCDC 2109184: Experimental Crystal Structure Determination

description: Related Article: Fei-Fei Gao|2023|CSD Communication|||
description: Related Article: Fei-Fei Gao, Haipeng Song, Zhi-Gang Li, Yan Qin, Xiang Li, Zhao-Quan Yao, Jia-Hui Fan, Xiang Wu, Wei Li, Xian-He Bu|2023|Angew.Chem.,Int.Ed.|62|e202218675|doi:10.1002/anie.202218675
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.cc28ss51
title: CCDC 2109183: Experimental Crystal Structure Determination

description: Related Article: Fei-Fei Gao|2023|CSD Communication|||
description: Related Article: Fei-Fei Gao, Haipeng Song, Zhi-Gang Li, Yan Qin, Xiang Li, Zhao-Quan Yao, Jia-Hui Fan, Xiang Wu, Wei Li, Xian-He Bu|2023|Angew.Chem.,Int.Ed.|62|e202218675|doi:10.1002/anie.202218675
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.