cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5517/ccdc.csd.cc2c9xm7
title: CCDC 2184279: Experimental Crystal Structure Determination

description: Related Article: Jin-Chang Huang, Hong-Hong Xu, Qing Shi, Chun Lei, Jing-Ya Li, Ai-Jun Hou|2023|Bioorg.Chem.|132|106381|doi:10.1016/j.bioorg.2023.106381
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.22065020
title: Full Supplementary Table S13&S14.xlsx

description: Full stepwise ANOVA analysis of stable isotopes from <em>Mycena</em> and surroundings in the study.
DOI: 10.6084/m9.figshare.22065020.v1
title: Full Supplementary Table S13&S14.xlsx

description: Full stepwise ANOVA analysis of stable isotopes from <em>Mycena</em> and surroundings in the study.
DOI: 10.25919/7g40-es07
title: Large-scale Inundation Simulation - Fitzroy Basin

description: This collection provides the water heights and associated metadata (e.g. DEM data, etc) obtained from a MIKE21 simulation applied to 3 flood event scenarios in the Fitzroy River basin (WA). The raw sparse triangular mesh water height and processed dense grid water height is provided. This data is suitable for training and verifying machine learning methods to predict water heights.
DOI: 10.7931/en0s-5j70
title: core_weathering_wsa
DOI: 10.26179/z1hz-7s71
title: Role of Antarctic marine protists in trophodynamics and global change and impact of UV-B on these organisms - Rotation 4 of the Astrolabe - 2004/2005 samples
DOI: 10.5281/zenodo.7625356
title: BridgeDb Complex Identifier Mapping Database

description: BridgeDb identifier mapping databases for complexes extracted from Wikidata. Code to generate the database (https://github.com/bridgedb/Wikidata2Bridgedb - ComplexIdentifiers.java).
DOI: 10.5281/zenodo.7625357
title: BridgeDb Complex Identifier Mapping Database

description: BridgeDb identifier mapping databases for complexes extracted from Wikidata. Code to generate the database (https://github.com/bridgedb/Wikidata2Bridgedb - ComplexIdentifiers.java).
DOI: 10.6084/m9.figshare.22065041
title: Descriptive stats.docx

description: This data describes the correlations between typing on a smartphone and wrist/hand pain among graduate students. Pain was measured pre/posttest using the Numeric Pain Rating Scale (NPRS).
DOI: 10.6084/m9.figshare.22065041.v1
title: Descriptive stats.docx

description: This data describes the correlations between typing on a smartphone and wrist/hand pain among graduate students. Pain was measured pre/posttest using the Numeric Pain Rating Scale (NPRS).
DOI: 10.5281/zenodo.7627206
title: Análisis multinivel bayesiano de experimento de parcelas divididas

description: Production of flour with improved nutritional and functional features from sprouted lentil (Lens culinaris) grains
DOI: 10.5281/zenodo.7627207
title: Análisis multinivel bayesiano de experimento de parcelas divididas

description: Production of flour with improved nutritional and functional features from sprouted lentil (Lens culinaris) grains
DOI: 10.5281/zenodo.7627257
title: Raw data for 'Signature of spin triplet exciton condensations in LaCoO3 at ultrahigh magnetic fields up to 600 T'

description: Raw data for the paper below Signature of spin triplet exciton condensations in LaCoO3 at ultrahigh magnetic fields up to 600 T<br> A. Ikeda, Y. H. Matsuda, K. Sato, Y. Ishii, H. Sawabe, D. Nakamura, S. Takeyama, J. Nasu<br> arXiv:2201.02704
DOI: 10.5281/zenodo.7627256
title: Raw data for 'Signature of spin triplet exciton condensations in LaCoO3 at ultrahigh magnetic fields up to 600 T'

description: Raw data for the paper below Signature of spin triplet exciton condensations in LaCoO3 at ultrahigh magnetic fields up to 600 T<br> A. Ikeda, Y. H. Matsuda, K. Sato, Y. Ishii, H. Sawabe, D. Nakamura, S. Takeyama, J. Nasu<br> arXiv:2201.02704
DOI: 10.5517/ccdc.csd.cc2cp0wz
title: CCDC 2194951: Experimental Crystal Structure Determination

description: Related Article: Yi Zhang, Yuhang Liu, Pran Gopal Karmaker, Lilei Zhang, Kaijing Yang, Lianfang Chen, Xiupei Yang|2023|ACS Applied Materials and Interfaces|15|6177|doi:10.1021/acsami.2c19766
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.cc2cp99p
title: CCDC 2195212: Experimental Crystal Structure Determination

description: Related Article: Honglei Gao, Zhiyi Li, Zhi Pang, Yuanyuan Qin, Guanhao Liu, Teng Gao, Xiangyu Dong, Shaogang Shen, Xin Xie, Pengfei Wang, Chun-Sing Lee, Ying Wang|2023|ACS Applied Materials and Interfaces|15|5529|doi:10.1021/acsami.2c18851
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.cc2cp9ky
title: CCDC 2195220: Experimental Crystal Structure Determination

description: Related Article: Honglei Gao, Zhiyi Li, Zhi Pang, Yuanyuan Qin, Guanhao Liu, Teng Gao, Xiangyu Dong, Shaogang Shen, Xin Xie, Pengfei Wang, Chun-Sing Lee, Ying Wang|2023|ACS Applied Materials and Interfaces|15|5529|doi:10.1021/acsami.2c18851
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.cc2d6knv
title: CCDC 2210847: Experimental Crystal Structure Determination

description: Related Article: Hugo C. Hernández-Toledo, Marcos Flores-Alamo, Ivan Castillo|2023|J.Inorg.Biochem.|241|112128|doi:10.1016/j.jinorgbio.2023.112128
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.cc2d6kpw
title: CCDC 2210848: Experimental Crystal Structure Determination

description: Related Article: Hugo C. Hernández-Toledo, Marcos Flores-Alamo, Ivan Castillo|2023|J.Inorg.Biochem.|241|112128|doi:10.1016/j.jinorgbio.2023.112128
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.cc2d7mv4
title: CCDC 2211876: Experimental Crystal Structure Determination

description: Related Article: Fang-Yu Yuan, Zhuo-Ya Tang, Xue-Long Yan, Dong Huang, Han-Zhuang Weng, Jia-Luo Huang, Run-Zhu Fan, Ye Chen, Sheng Yin, Gui-Hua Tang|2023|Phytochemistry|208|113588|doi:10.1016/j.phytochem.2023.113588
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.cc2c9xl6
title: CCDC 2184278: Experimental Crystal Structure Determination

description: Related Article: Jin-Chang Huang, Hong-Hong Xu, Qing Shi, Chun Lei, Jing-Ya Li, Ai-Jun Hou|2023|Bioorg.Chem.|132|106381|doi:10.1016/j.bioorg.2023.106381
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: 10.34740/kaggle/dsv/4972823
title: OntoUML/UFO Catalog
DOI: 10.21227/fmqs-1416
title: (22,4,2^{21}-2^{10}-2^9) 函数的真值表

description: wu
DOI: 10.6084/m9.figshare.22065212
title: Strawberry cultivars

description: Strawberry cultivars
DOI: 10.25919/tdw1-zj86
title: IMOS Biological Ocean Observer - sysdata.rda

description: This is the sysdata.rda file that is used to populate the IMOS Biological Ocean Observer (BOO) Shiny App. The IMOS biological and supporting data is accessed directly from the AODN, processed and reformatted to the requirements of the Shiny App and stored in this location.
DOI: 10.6084/m9.figshare.20791240
title: An Empirical Study of Deep Learning Models for Vulnerability Detection

description: Deep learning (DL) models of code have recently reported great progress for vulnerability detection. In some cases, DL-based models have outperformed static analysis tools. Although many great models have been proposed, we do not yet have a good understanding of these models. This limits the further advancement of model robustness, debugging, and deployment for the vulnerability detection. In this paper, we surveyed and reproduced 9 state-of-the-art (SOTA) deep learning models on 2 widely used vulnerability detection datasets: Devign and MSR. We investigated 6 research questions in three areas, namely model capabilities, training data, and model interpretation. We experimentally demonstrated the variability between different runs of a model and the low agreement among different models’ outputs. We investigated models trained for specific types of vulnerabilities compared to a model that is trained on all the vulnerabilities at once. We explored the types of programs DL may consider ”hard” to handle. We investigated the relations of training data sizes and training data composition with model performance. Finally, we studied model interpretations and analyzed important features that the models used to make predictions. We believe that our findings can help better understand model results, provide guidance on preparing training data, and improve the robustness of the models.
DOI: 10.6084/m9.figshare.20791240.v2
title: An Empirical Study of Deep Learning Models for Vulnerability Detection

description: Deep learning (DL) models of code have recently reported great progress for vulnerability detection. In some cases, DL-based models have outperformed static analysis tools. Although many great models have been proposed, we do not yet have a good understanding of these models. This limits the further advancement of model robustness, debugging, and deployment for the vulnerability detection. In this paper, we surveyed and reproduced 9 state-of-the-art (SOTA) deep learning models on 2 widely used vulnerability detection datasets: Devign and MSR. We investigated 6 research questions in three areas, namely model capabilities, training data, and model interpretation. We experimentally demonstrated the variability between different runs of a model and the low agreement among different models’ outputs. We investigated models trained for specific types of vulnerabilities compared to a model that is trained on all the vulnerabilities at once. We explored the types of programs DL may consider ”hard” to handle. We investigated the relations of training data sizes and training data composition with model performance. Finally, we studied model interpretations and analyzed important features that the models used to make predictions. We believe that our findings can help better understand model results, provide guidance on preparing training data, and improve the robustness of the models.
DOI: 10.34740/kaggle/dsv/4972997
title: 💥📰 Daily Breaking News Twitter Dataset
DOI: 10.6073/pasta/b30a934d431ea41a7d82b5e5dc99d592
title: MCR LTER: Coral Reef: Macroalgal CHN, ongoing since 2005

description: Samples of two common macroalgal species (Sargassum mangarevense, Turbinaria ornata) are collected yearly from fringing, backreef, and reef crest sites at each of the sites (LTER 1 through LTER 6) around Moorea. CHN analyses of dried, ground samples of each individual are made using standard methods. CHN data are used to track sustained variation in nutrient availability. Water column nutrients in coral reef systems usually are low to undetectable and their inputs tend to be episodic and ephemeral. Using CHN contents of macroalgae allows the integration of nitrogen availability over a longer time period, in this case, over approximately 3 months. This material is based upon work supported by the U.S. National Science Foundation under Grant No. OCE 16-37396 (and earlier awards) as well as a generous gift from the Gordon and Betty Moore Foundation. Research was completed under permits issued by the French Polynesian Government (Délégation à la Recherche) and the Haut-commissariat de la République en Polynésie Francaise (DTRT) (Protocole d'Accueil 2005-2023). This work represents a contribution of the Moorea Coral Reef (MCR) LTER Site.
DOI: 10.34740/kaggle/dsv/4973000
title: 🇺🇦 Ukraine Conflict Twitter Dataset
DOI: 10.6084/m9.figshare.22065284
title: Effect of urbanization on gust wind speed in summer over an urban area in Eastern China

description: The observation data includes 3 files: "DX_daily_obs.dat", "XL_daily_obs.dat", "LS_daily_obs.dat". Each file includes 24 hours of 9 variables data, including the wind speed at 10m (WS10), temperature at 2m (T2m), relative humidity at 2m (RH2m), sensible heat flux (HFX), latent heat flux (LH), net radiation (RN), friction velocity (Ustar), specific humidity (QV), and dew point temperature (Td). <br> The file " Urban_CTL_simulated_grid_data.nc" includes the URBAN and CTL case simulated daily mean, daytime, and nighttime grid (90*90) results of 7 variables, including WS10, gust wind speed at 10m (GWS10), wind speed at 950 hpa (WS950), wind speed at 850 hpa (WS850), friction velocity (Ustar), atmospheric stability, and wind shear (WS850-WS950). <br> The file "Urban_CTL_simulated_LIR_HIR_COI_mean_data.nc" includes the URBAN and CTL case simulated hourly-averaged 8 variables in LIR, HIR, COI and city-wide urban areas, including WS10, GWS10, WS950, WS850, Ustar, atmospheric stability, and the item 2 and item 3 in Equation (1). <br> The probability distribution results of the gust wind speed difference between before and after the urbanization in the urban area in the daytime, nighttime and whole time are in the files of "GWS_probability_distribution_difference_day.txt", " GWS_probability_distribution_difference_night.txt", and " GWS_probability_distribution_difference_diurnal.txt". <br> <br>
DOI: 10.34740/kaggle/dsv/4973027
title: Sneaker 899-Classification total-50,000-Images
DOI: 10.5517/ccdc.csd.cc29zlnk
title: CCDC 2144569: Experimental Crystal Structure Determination

description: Related Article: Badri Z. Momeni, S. Farzad Hosseini, Jan Janczak|2023|J.Mol.Struct.|1279|135038|doi:10.1016/j.molstruc.2023.135038
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: 10.48505/nims.3844
title: Raw data files for Fig. 6 Auger depth profiles in "Auger Depth Profiling Analysis of HfO2/Si Specimen Using an Ultra Low Angle Incidence Ion Beam"

description: We have investigated the Auger depth profiling analysis of HfO2/Si by the glancing-angle ion beam sputtering method at an incident angle of 7 degree from the sample surface with argon ion beam. The depth resolutions of the O KLL interface profiles were 0.9 nm and 1.5 nm, at the ion-beam acceleration voltage of 2.0 kV and 3.0 kV re-spectively, which were better than the depth resolutions at a commonly-used incident angle of 51 degree. However, the ion-beam-induced reduction of HfO2 was not suppressed by the glancing-angle ion beam sputtering at the ion acceleration voltage of 0.5 kV, which is expected to be the lowest damage sputtering condition in this study. The reduction of HfO2 due to preferential sputtering of oxygen was observed by the intensity ratio of O KLL and Hf NVV depth profiles. It was found that the ratio of preferential sputtering depends on the ion incidence angle and the ion acceleration voltage. Under the glancing-angle condition, the ratio of preferential sputtering greatly de-pended on the ion accelerating voltage, and it was found that the lower the ion acceleration voltage is, the easier it is for O to be sputtered than Hf. On the other hand, under the commonly-used incident angle conditions, the ratio of preferential sputtering did not depend much on the ion acceleration voltage. The dependency of the ratio of preferential sputtering on the ion incidence angle can be explained by the difference in sputtering models depend-ing on the ion incidence angle. It was found that the O KLL depth profiles showed partial recovery of the oxygen intensity near the interface of HfO2/Si, which can be related to oxygen generated by the ion-beam-induced decom-position of the diffusion layer at the interface. In addition, the glancing-angle ion beam enables the reduction of the effect of recoil implantation of Hf atoms into the Si substrate.
DOI: 10.5439/1893611
title: camspmfsrsmovie (a1)

description: camspmfsrsmovie
DOI: 10.6084/m9.figshare.22065409.v1
title: Supplementary Information from Ancient DNA of narrow-headed vole reveal common features of the Late Pleistocene population dynamics in cold-adapted small mammals

description: The narrow-headed vole, collared lemming and common vole were the most abundant small mammal species across the Eurasian Late Pleistocene steppe-tundra environment. Previous ancient DNA studies of the collared lemming and common vole have revealed dynamic population histories shaped by climatic fluctuations. To investigate the extent to which species with similar adaptations share common evolutionary histories, we generated a dataset comprised the mitochondrial genomes of 139 ancient and 6 modern narrow-headed voles from several sites across Europe and northwestern Asia covering approximately the last 100 thousand years (kyr). We inferred Bayesian time-aware phylogenies using 11 radiocarbon-dated samples to calibrate the molecular clock. Divergence of the main mtDNA lineages across the three species occurred during marine isotope stages (MIS) 7 and MIS 5, suggesting a common response of species adapted to open habitat during interglacials. We identified several time-structured mtDNA lineages in European narrow-headed vole, suggesting lineage turnover. The timing of some of these turnovers was synchronous across the three species, allowing us to identify the main drivers of the Late Pleistocene dynamics of steppe- and cold-adapted species.
DOI: 10.6084/m9.figshare.22065409
title: Supplementary Information from Ancient DNA of narrow-headed vole reveal common features of the Late Pleistocene population dynamics in cold-adapted small mammals

description: The narrow-headed vole, collared lemming and common vole were the most abundant small mammal species across the Eurasian Late Pleistocene steppe-tundra environment. Previous ancient DNA studies of the collared lemming and common vole have revealed dynamic population histories shaped by climatic fluctuations. To investigate the extent to which species with similar adaptations share common evolutionary histories, we generated a dataset comprised the mitochondrial genomes of 139 ancient and 6 modern narrow-headed voles from several sites across Europe and northwestern Asia covering approximately the last 100 thousand years (kyr). We inferred Bayesian time-aware phylogenies using 11 radiocarbon-dated samples to calibrate the molecular clock. Divergence of the main mtDNA lineages across the three species occurred during marine isotope stages (MIS) 7 and MIS 5, suggesting a common response of species adapted to open habitat during interglacials. We identified several time-structured mtDNA lineages in European narrow-headed vole, suggesting lineage turnover. The timing of some of these turnovers was synchronous across the three species, allowing us to identify the main drivers of the Late Pleistocene dynamics of steppe- and cold-adapted species.
DOI: 10.15473/1922358
title: Modeled Hourly Tidal Current Velocities, Directions, and Heights from May 1 - September 1, 2005 at Two Points Near East Forelands and Tyonek in Cook Inlet, Alaska

description: This dataset includes modeled tidal current velocities, direction and depth at two locations in East and North Forelands (60.716, -151.434 and 61.024, -151.157) near Nikiski and Tyonek, respectively, in Cook Inlet, Alaska. Data from two grid cells were provided by the Pacific Northwest National Laboratory based on a tidal hydrodynamic model that characterized the tidal stream resources in Cook Inlet for a period from May 1 to September 1, 2005 (Wang and Yang 2020). The model grid size had a horizontal spatial resolution of 100 m at East Forelands and 200 m at Tyonek; mean sea level (MSL) depth was 47.9 m and 23.7 m at each respective site, and there were 10 depth bins that ranged in size with the tide from 4.3-5.2 m and 1.9-2.8 m, respectively (Wang and Yang 2020).
DOI: 10.6084/m9.figshare.22041674
title: Old data

description: Old data
DOI: 10.6084/m9.figshare.22041674.v2
title: Old data

description: Old data
DOI: 10.6084/m9.figshare.22041674.v1
title: LZD IV to PO Excel sheet.xlsx

description: This data is the monthly spending and DOT/1000 DP for IV and PO Linezolid at Methodist University Hospital, and the Methodist LeBonheur Healthcare System between Feb 2021 and March 2022.
DOI: 10.6084/m9.figshare.21674960.v1
title: All-summary.zip

description: Simplification algorithms comparison dataset
DOI: 10.6084/m9.figshare.22061261
title: test

description: 7 datasets used in simplification
DOI: 10.6084/m9.figshare.22061261.v2
title: test

description: 7 datasets used in simplification
DOI: 10.6084/m9.figshare.22061261.v1
title: OSM Datasets

description: 7 datasets used in simplification
DOI: 10.5281/zenodo.7627372
title: Open Science and Open Innovation database

description: Open Science and Open Innovation database
DOI: 10.5281/zenodo.7627373
title: Open Science and Open Innovation database

description: Open Science and Open Innovation database
DOI: 10.5281/zenodo.7627405
title: Open Science and Open Innovation database

description: Open Science and Open Innovation database
DOI: 10.15783/c7kw2n
title: CRAWDAD dataset cu/lte (v. 2012-05-04)

description: This data was collected at the University of Colorado Boulder. It contains
careful point measurements, taken on a 100m equilateral triangular lattice, of
the Verizon LTE network.
description: Changelog: the initial version
DOI: 10.6084/m9.figshare.21965829
title: Raw fly data RSOS from A biphasic model of lifespan in nematode <i>Caenorhabditis elegans</i> worm

description: The file contains all raw data pertaining to the fly experiments.
DOI: 10.6084/m9.figshare.21965829.v1
title: Raw fly data RSOS from A biphasic model of lifespan in nematode <i>Caenorhabditis elegans</i> worm

description: The file contains all raw data pertaining to the fly experiments.