cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.22011086.v1
title: Minimal dataset for PONE-D-23-00790

description: This is the source data for the manuscript entitled"Characterization of Hemodialysis Fistulas Experienced Abrupt Thrombosis and Determination of a Proper Follow-up Protocol: A Retrospective Cohort Study and an IR’s Prospective'.
DOI: 10.6084/m9.figshare.21996920
title: PONE-D-23-00790 minimal dataset.xlsx

description: The dataset is the source data for the findings presented in the article named "Characterization of Hemodialysis Fistulas Experienced Abrupt Thrombosis and Determination of a Proper Follow-up Protocol: A Retrospective Cohort Study and an IR’s Prospective".
DOI: 10.6084/m9.figshare.21996920.v2
title: PONE-D-23-00790 minimal dataset.xlsx

description: The dataset is the source data for the findings presented in the article named "Characterization of Hemodialysis Fistulas Experienced Abrupt Thrombosis and Determination of a Proper Follow-up Protocol: A Retrospective Cohort Study and an IR’s Prospective".
DOI: 10.6084/m9.figshare.21996920.v1
title: PONE-D-23-00790.xlsx

description: The dataset is the source data for the findings presented in the article named "Characterization of Hemodialysis Fistulas Experienced Abrupt Thrombosis and Determination of a Proper Follow-up Protocol: A Retrospective Cohort Study and an IR’s Prospective".
DOI: 10.34740/kaggle/dsv/4948007
title: arXiv Dataset
DOI: 10.5281/zenodo.7606547
title: Dyall double-zeta, triple-zeta, and quadruple-zeta basis set archive files

description: This archive contains the archive files of the Dyall basis sets for each basis set level (dz, tz, qz) for all blocks of the periodic table from 1s to 7p. Each file is a plain text file that contains a description of the basis set development and recommended use, the atomic orbitals for the reference configuration with the exponents, and lists of correlating, polarization, and diffuse functions. The exponents, in the Dirac program format, are given in a separate location, https://doi.org/10.5281/zenodo.7574628; the reference list is also given at this location.
DOI: 10.5281/zenodo.7606546
title: Dyall double-zeta, triple-zeta, and quadruple-zeta basis set archive files

description: This archive contains the archive files of the Dyall basis sets for each basis set level (dz, tz, qz) for all blocks of the periodic table from 1s to 7p. Each file is a plain text file that contains a description of the basis set development and recommended use, the atomic orbitals for the reference configuration with the exponents, and lists of correlating, polarization, and diffuse functions. The exponents, in the Dirac program format, are given in a separate location, https://doi.org/10.5281/zenodo.7574628; the reference list is also given at this location.
DOI: 10.5281/zenodo.7604173
title: MUSES Leaf Area Index (LAI) 8-Day Global 500m SIN Grid in 2005

description: The MUltiscale Satellite remotE Sensing (MUSES) product suite includes products with different spatial and temporal resolutions for parameters such as Normalized Difference Vegetation Index (NDVI), Near-Infrared Reflectance of Vegetation (NIRv), Leaf Area Index (LAI), Fraction of Absorbed Photosynthetically Active Radiation (FAPAR), Fractional Vegetation Coverage (FVC), Gross Primary Production (GPP), Net Primary Production (NPP). For more information about the MUSES products, please refer to this website (https://muses.bnu.edu.cn/). This dataset is the MUSES global LAI product at 500m spatial resolution and 8-day temporal resolution. The MUSES LAI product is provided on a Sinusoidal grid and spans from 2000 to 2019 (continuously updated). It was generated from time-series Moderate Resolution Imaging Spectroradiometer (MODIS) surface reflectance product using general regression neural networks (GRNNs) (Xiao <em>et al</em>., 2014; Xiao <em>et al.</em>, 2016). The MUSES LAI product is spatially complete and temporally continuous. This dataset is the MUSES LAI product in 2005. <em>Please <strong>click here</strong> to download the MUSES LAI product <strong>in 2004</strong></em><strong>, </strong>and <em><strong>click here</strong> to download the MUSES LAI product <strong>in 2006</strong></em>. <strong>Dataset Characteristics:</strong> Spatial Coverage: Global Temporal Coverage: 2005 Spatial Resolution: 500m Temporal Resolution: 8 days Projection: Sinusoidal Data Format: HDF Scale: 0.01 Valid Range: 0 – 1000 <strong>Citation </strong>(Please cite this paper whenever these data are used)<strong>:</strong> Xiao Zhiqiang, <em>et al</em>. (2014). Use of General Regression Neural Networks for Generating the GLASS Leaf Area Index Product From Time-Series MODIS Surface Reflectance. <em>IEEE Transactions on Geoscience and Remote Sensing</em>, 52, 209-223. Xiao Zhiqiang, <em>et al</em>. (2016). Long-time-series global land surface satellite leaf area index product derived from MODIS and AVHRR surface reflectance. <em>IEEE Transactions on Geoscience and Remote Sensing</em>, 54, 5301-5318. Xiao Zhiqiang, Jinling Song, Hua Yang, Rui Sun and Juan Li. (2022). A 250 m resolution global leaf area index product derived from MODIS surface reflectance data. <em>International Journal of Remote Sensing</em>, 43(4), 1199-1225. Xiao Zhiqiang, <em>et al</em>. (2017). Evaluation of four long time-series global leaf area index products. <em>Agricultural and Forest Meteorology</em>, 246, 218-230. If you have any questions, please contact Prof. Zhiqiang Xiao (zhqxiao@bnu.edu.cn).
DOI: 10.5281/zenodo.7604172
title: MUSES Leaf Area Index (LAI) 8-Day Global 500m SIN Grid in 2005

description: The MUltiscale Satellite remotE Sensing (MUSES) product suite includes products with different spatial and temporal resolutions for parameters such as Normalized Difference Vegetation Index (NDVI), Near-Infrared Reflectance of Vegetation (NIRv), Leaf Area Index (LAI), Fraction of Absorbed Photosynthetically Active Radiation (FAPAR), Fractional Vegetation Coverage (FVC), Gross Primary Production (GPP), Net Primary Production (NPP). For more information about the MUSES products, please refer to this website (https://muses.bnu.edu.cn/). This dataset is the MUSES global LAI product at 500m spatial resolution and 8-day temporal resolution. The MUSES LAI product is provided on a Sinusoidal grid and spans from 2000 to 2019 (continuously updated). It was generated from time-series Moderate Resolution Imaging Spectroradiometer (MODIS) surface reflectance product using general regression neural networks (GRNNs) (Xiao <em>et al</em>., 2014; Xiao <em>et al.</em>, 2016). The MUSES LAI product is spatially complete and temporally continuous. This dataset is the MUSES LAI product in 2005. <em>Please <strong>click here</strong> to download the MUSES LAI product <strong>in 2004</strong></em><strong>, </strong>and <em><strong>click here</strong> to download the MUSES LAI product <strong>in 2006</strong></em>. <strong>Dataset Characteristics:</strong> Spatial Coverage: Global Temporal Coverage: 2005 Spatial Resolution: 500m Temporal Resolution: 8 days Projection: Sinusoidal Data Format: HDF Scale: 0.01 Valid Range: 0 – 1000 <strong>Citation </strong>(Please cite this paper whenever these data are used)<strong>:</strong> Xiao Zhiqiang, <em>et al</em>. (2014). Use of General Regression Neural Networks for Generating the GLASS Leaf Area Index Product From Time-Series MODIS Surface Reflectance. <em>IEEE Transactions on Geoscience and Remote Sensing</em>, 52, 209-223. Xiao Zhiqiang, <em>et al</em>. (2016). Long-time-series global land surface satellite leaf area index product derived from MODIS and AVHRR surface reflectance. <em>IEEE Transactions on Geoscience and Remote Sensing</em>, 54, 5301-5318. Xiao Zhiqiang, Jinling Song, Hua Yang, Rui Sun and Juan Li. (2022). A 250 m resolution global leaf area index product derived from MODIS surface reflectance data. <em>International Journal of Remote Sensing</em>, 43(4), 1199-1225. Xiao Zhiqiang, <em>et al</em>. (2017). Evaluation of four long time-series global leaf area index products. <em>Agricultural and Forest Meteorology</em>, 246, 218-230. If you have any questions, please contact Prof. Zhiqiang Xiao (zhqxiao@bnu.edu.cn).
DOI: 10.34740/kaggle/dsv/4948130
title: OntoUML/UFO Catalog
DOI: 10.21227/bfr8-sz20
title: Data of Influential Factors of College Students' Learning Intention on the Online Teaching Video During the COVID-19 Pandemic in China

description: In order to explore the influencing factors of college students' learning intention on online teaching video during the pandemic, this article uses empirical research on college students from four aspects including performance expectancy, effort expectancy, social influence and facilitating conditions.
DOI: 10.5281/zenodo.7606596
title: Insights into substrate transport and water permeation in the mycobacterial transporter MmpL3

description: These are all input and final structures for a set of simulations investigating the protein MmpL3. All topology, parameter, and NAMD configuration files for running the molecular dynamics simulations are also included. Recommended software to use is Visual Molecular Dynamics (VMD).
DOI: 10.5281/zenodo.7606594
title: Insights into substrate transport and water permeation in the mycobacterial transporter MmpL3

description: These are all input and final structures for a set of simulations investigating the protein MmpL3. All topology, parameter, and NAMD configuration files for running the molecular dynamics simulations are also included. Recommended software to use is Visual Molecular Dynamics (VMD).
DOI: 10.6084/m9.figshare.22004633.v1
title: Supplementary Table

description: Supplementary Table 1. Comparison of alpha diversity between the hypothyroidism and the control group. <br> Supplementary Table 2. The AUC value of intestinal microflora. <br> Supplementary Table 3. Correlation of intestinal microflora with Th1/Th2 cells, cytokines, and clinical indicators. <br> Supplementary Table 4. Correlation of TPOAb with Th1/Th2 cells, cytokines, and clinical indicators.
DOI: 10.34740/kaggle/dsv/4948564
title: 🇺🇦 Ukraine Conflict Twitter Dataset
DOI: 10.6084/m9.figshare.21867813
title: Encoding of Dynamic Facial Information in the Middle Dorsal Face Area

description: PSTH of each cell to the dyanmic face experiment (faceMotionData) and to the gaze experiment (gazeData). <br> <br>
DOI: 10.5281/zenodo.7606644
title: Meridional wave power distribution data for article "Latitudinal Dependence of Ground VLF Transmitter Wave Power in the Inner Magnetosphere"

description: The data are the meridional wave power distribution for the four VLF transmitters: NWC, NAA, NML, and NLK in the inner magnetosphere. Each transmitter has a .mat file, and in each data file, we provide the meridional wave power distribution for both ray tracing simulation (parameter "rt") and ERG observation (parameter "erg"). In each distribution data, the variables "x2d" and "z2d" are the cartesian coordinates in the meridional plane in the unit of Re (the Eearth's radius). x2d=r*cos(theta) and z2d=r*sin*(theta), where r is the radius from the Earth's center, and theta is the magnetic latitude. The variable "power" is the corresponding transmitter wave power in the unit of V^2/m^2.
DOI: 10.5281/zenodo.7606643
title: Meridional wave power distribution data for article "Latitudinal Dependence of Ground VLF Transmitter Wave Power in the Inner Magnetosphere"

description: The data are the meridional wave power distribution for the four VLF transmitters: NWC, NAA, NML, and NLK in the inner magnetosphere. Each transmitter has a .mat file, and in each data file, we provide the meridional wave power distribution for both ray tracing simulation (parameter "rt") and ERG observation (parameter "erg"). In each distribution data, the variables "x2d" and "z2d" are the cartesian coordinates in the meridional plane in the unit of Re (the Eearth's radius). x2d=r*cos(theta) and z2d=r*sin*(theta), where r is the radius from the Earth's center, and theta is the magnetic latitude. The variable "power" is the corresponding transmitter wave power in the unit of V^2/m^2.
DOI: 10.17909/trtf-5s84
title: NGC 247 ULX-1
DOI: 10.34740/kaggle/dsv/4948659
title: NSE-Scripts-Data
DOI: 10.6084/m9.figshare.22011368
title: Ana-1-KO vs WT-20230205 submit.xlsx

description: The change of gene expression in murine macrophage cell lines after siglec15 knockout
DOI: 10.5519/qd.m62laglm
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (5390332 records)
DOI: 10.11570/23.0006
title: PHANGS-MUSE: detection and Bayesian classification of ~40000 ionised nebulae in nearby spiral galaxies
DOI: 10.15151/esrf-es-1018259414
title: Austrian Crystallographic Diffraction Consortium

description: This proposed Austrian Crystallographic.... TO BE FILLED IN
DOI: 10.15151/esrf-es-1018419365
title: The Netherlands BAG

description: The Netherlands BAG includes groups situated at five Dutch universities (Utrecht, Groningen, Amsterdam, Wageningen and Eindhoven) and at the Netherlands Cancer Institute in Amsterdam, with a total of twelve PIs. The structural biology research carried out in these groups is highly diverse, including prokaryotic and eukaryotic proteins with a strong focus on targets and processes of biomedical relevance. Central to many projects are protein receptors and their interactions with other proteins and with small molecule modulators. An additional major research area concerns structure-based protein engineering and design aiming at the characterization and engineering of new enzymes for green chemistry and new-to-nature reactions. Projects deal with membrane and soluble proteins, cell surface receptors, and protein-protein, protein-ribonucleotide, protein-drug and enzyme-ligand complexes.
DOI: 10.15151/esrf-es-1021966178
title: Heidelberg BAG (HeidelBAG)

description: The HeidelBAG unifies structural efforts of EMBL Heidelberg and the Heidelberg University Biochemistry Center (BZH). Central to all projects are large assemblies involved in chromosome organization and transcription control, in nuclear and cytoplasmic RNA regulation, in translational control by ribosome associated factors or further on in protein targeting, membrane protein insertion or post-translational modification. While Eric Stebbins from DKFZ has left the BAG, Jirka Peschek from BZH will join and adds projects on tRNA ligases and interactors. Nearly all projects make use of integrated structural biology techniques combined with complementary biophysical, biochemical and cell biological approaches, a strategy that warranties the continuous success of the BAG. More and more pathological implications of the studied central cellular processes come into focus. In the 1st year of the proposal the BAG reports on 17 publications and 43 PDB entries and many unpublished results.
DOI: 10.15151/esrf-es-1026511637
title: Understanding intra- and intermolecular interactions of Sugar Beet Phytoglobin BvPgb 1.2.

description: This project aims to study the structure-dynamic relationship of one plant hemoglobin (phytoglobin) (BvPgb1.2) and one mutated version of the same denoted Cys86Ala. The goal is to expand the knowledge of important interactions for dimer formation in the wild-type (WT) protein, and compare it with the mutant, to obtain valuable information on the impact of this selected mutation. This will be studied by using different protein concentrations and buffer solution conditions, and the interactions between the subunits will be examined in detail. The results obtained in this project will be used to develop detailed models regarding the effect of this amino acid substitution on the dynamic properties within the protein to be solved by molecular dynamics (MD) simulations.
DOI: 10.15151/esrf-es-1025993103
title: H2-induced structural ductility in Pt/Al2O3 catalysts: gas-phase vs. liquid phase conditions

description: The goal of this proposal is to study the H2-induced reconstruction of Pt nanoparticles (NPs) in Pt/Al2O3 catalysts by time-resolved XRD/PDF experiments under gas- and liquid-phase conditions. Previous multi-technique gas-phase experiments pointed to morphology changes of the Pt NPs as a function of H-coverage. The behavior in liquid-phase conditions is less explored, although preliminary ATR-IR measurements indicate that the solvent plays a relevant role. Here, we want to extend the comparison between gas-phase and liquid-phase conditions to cover the structural dynamics of Pt NPs a) during Pt-hydride formation; b) as a function of the H-coverage, and c) during the hydrogenation of toluene as a model reaction. The results will highlight the behavior of supported Pt NPs in the presence of H2 in conditions widely applicable to the catalytic production of chemicals and energy.
DOI: 10.5281/zenodo.7593172
title: Anti-Riok2 virtual screening output results

description: Various investigations have revealed the role of RIOK2 in the carcinogenesis and potential of RIOK2 inhibitors as anticancer medicine. In this study, an in-silico approach have been utilized to find potential RIOK2 inhibitors and the uplouded file is the output of docking based virtual screening.
DOI: 10.5281/zenodo.7593171
title: Anti-Riok2 virtual screening output results

description: Various investigations have revealed the role of RIOK2 in the carcinogenesis and potential of RIOK2 inhibitors as anticancer medicine. In this study, an in-silico approach have been utilized to find potential RIOK2 inhibitors and the uplouded file is the output of docking based virtual screening.
DOI: 10.21227/bcds-a684
title: The matlab script for the Hook-Jeeves search algorithm

description: The Hook-Jeeves algorithm is a direct search algorithm that is widely used for multi-parameter optimisation problems in engineering computation. The file code provided contains Hook-Jeeves algorithm functions and simple test cases that can be used by copying the code into Matlab.
DOI: 10.6084/m9.figshare.22011371
title: The Chromosome-scale genome of Diospyros kaki

description: The Chromosome-scale genome of Diospyros kaki
DOI: 10.6084/m9.figshare.22011371.v1
title: The Chromosome-scale genome of Diospyros kaki

description: The Chromosome-scale genome of Diospyros kaki
DOI: 10.34740/kaggle/dsv/4949295
title: Elon Musk Tweets
DOI: 10.6084/m9.figshare.22012322
title: Data of the manuscript.docx

description: The dataset is the original data of the artical " <strong>Fucoidan</strong> <strong>alleviates bile duct ligation-induced hepatorenal syndrome in mice".</strong>
DOI: 10.6084/m9.figshare.22012322.v1
title: Data of the manuscript.docx

description: The dataset is the original data of the artical " <strong>Fucoidan</strong> <strong>alleviates bile duct ligation-induced hepatorenal syndrome in mice".</strong>
DOI: 10.5281/zenodo.7580078
title: Himawari-8/AHI hourly clear-sky land surface temperature and emissivity dataset (2016.5-2016.8)

description: This is the clear-sky LST and LSE dataset (0.02°, hourly) derived by the iTES algorithm (Zhou and Cheng, 2020) from the Himawari-8 AHI thermal infrared data. A broadband emissivity (BBE, 8-13.5μm) dataset was also produced using the derived AHI narrowband LSEs (Cheng et al. 2013). The in-situ validation results show that the bias and RMSE of the retrieved AHI LST are 0.19 and 2.93 K in the daytime, and −0.43 and 1.95 K in the nighttime, respectively. The bias and RMSE of the retrieved LSE are less than 0.005 and 0.014, respectively, compared with the latest MYD21 LSE. The time period of this dataset is 2016-2021, covering the AHI 0.02° nominal fixed grid (60°N∼60°S, 80°E∼160°W). This is the LST&E dataset in 2016.05-2016.08 <strong>Dataset Characteristics:</strong> Spatial Coverage: East Asia and Western Pacific regions (60°N∼60°S, 80°E-140°E) Temporal Coverage: 2016.05-2016.08 Spatial Resolution: 0.02 ° Temporal Resolution: one hour Projection: GCS_WGS_1984 Data Format: NetCDF <strong>Citation </strong>(Please cite these papers when using the data)<strong>:</strong> Zhou, S., & Cheng, J. (2020). An Improved Temperature and Emissivity Separation Algorithm for the Advanced Himawari Imager. <em>IEEE Transactions on Geoscience and Remote Sensing, 58</em>, 7105-7124 Cheng, J., et al. (2013). Estimating the Optimal Broadband Emissivity Spectral Range for Calculating Surface Longwave Net Radiation. <em>IEEE Geoscience and Remote Sensing Letters, 10</em>, 401-40 If you have any questions, please contact Prof. Jie Cheng (Jie_Cheng@bnu.edu.cn).
DOI: 10.5281/zenodo.7580077
title: Himawari-8/AHI hourly clear-sky land surface temperature and emissivity dataset (2016.5-2016.8)

description: This is the clear-sky LST and LSE dataset (0.02°, hourly) derived by the iTES algorithm (Zhou and Cheng, 2020) from the Himawari-8 AHI thermal infrared data. A broadband emissivity (BBE, 8-13.5μm) dataset was also produced using the derived AHI narrowband LSEs (Cheng et al. 2013). The in-situ validation results show that the bias and RMSE of the retrieved AHI LST are 0.19 and 2.93 K in the daytime, and −0.43 and 1.95 K in the nighttime, respectively. The bias and RMSE of the retrieved LSE are less than 0.005 and 0.014, respectively, compared with the latest MYD21 LSE. The time period of this dataset is 2016-2021, covering the AHI 0.02° nominal fixed grid (60°N∼60°S, 80°E∼160°W). This is the LST&E dataset in 2016.05-2016.08 <strong>Dataset Characteristics:</strong> Spatial Coverage: East Asia and Western Pacific regions (60°N∼60°S, 80°E-140°E) Temporal Coverage: 2016.05-2016.08 Spatial Resolution: 0.02 ° Temporal Resolution: one hour Projection: GCS_WGS_1984 Data Format: NetCDF <strong>Citation </strong>(Please cite these papers when using the data)<strong>:</strong> Zhou, S., & Cheng, J. (2020). An Improved Temperature and Emissivity Separation Algorithm for the Advanced Himawari Imager. <em>IEEE Transactions on Geoscience and Remote Sensing, 58</em>, 7105-7124 Cheng, J., et al. (2013). Estimating the Optimal Broadband Emissivity Spectral Range for Calculating Surface Longwave Net Radiation. <em>IEEE Geoscience and Remote Sensing Letters, 10</em>, 401-40 If you have any questions, please contact Prof. Jie Cheng (Jie_Cheng@bnu.edu.cn).
DOI: 10.5281/zenodo.7580853
title: Himawari-8/AHI hourly clear-sky land surface temperature and emissivity dataset (2016.9-2016.12)

description: This is the clear-sky LST and LSE dataset (0.02°, hourly) derived by the iTES algorithm (Zhou and Cheng, 2020) from the Himawari-8 AHI thermal infrared data. A broadband emissivity (BBE, 8-13.5μm) dataset was also produced using the derived AHI narrowband LSEs (Cheng et al. 2013). The in-situ validation results show that the bias and RMSE of the retrieved AHI LST are 0.19 and 2.93 K in the daytime, and −0.43 and 1.95 K in the nighttime, respectively. The bias and RMSE of the retrieved LSE are less than 0.005 and 0.014, respectively, compared with the latest MYD21 LSE. The time period of this dataset is 2016-2021, covering the AHI 0.02° nominal fixed grid (60°N∼60°S, 80°E∼160°W). This is the LST&E dataset in 2016.09-2016.12 <strong>Dataset Characteristics:</strong> Spatial Coverage: East Asia and Western Pacific regions (60°N∼60°S, 80°E-140°E) Temporal Coverage: 2016.09-2016.12 Spatial Resolution: 0.02 ° Temporal Resolution: one hour Projection: GCS_WGS_1984 Data Format: NetCDF <strong>Citation </strong>(Please cite these papers when using the data)<strong>:</strong> Zhou, S., & Cheng, J. (2020). An Improved Temperature and Emissivity Separation Algorithm for the Advanced Himawari Imager. <em>IEEE Transactions on Geoscience and Remote Sensing, 58</em>, 7105-7124 Cheng, J., et al. (2013). Estimating the Optimal Broadband Emissivity Spectral Range for Calculating Surface Longwave Net Radiation. <em>IEEE Geoscience and Remote Sensing Letters, 10</em>, 401-40 If you have any questions, please contact Prof. Jie Cheng (Jie_Cheng@bnu.edu.cn).