cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.21561891.v1
title: Intestinal microbiota 16SrRNA sequencing data from hypothyroidism in the first half of pregnancy.rar

description: Intestinal flora 16SrRNA sequencing data of 57 pregnant women with hypothyroidism in the first half of pregnancy and 58 normal pregnant women during the same period, with C representing normal pregnant women and H representing hypothyroidism pregnant womenuencing data from hypothyroidism in the first half of pregnancy
DOI: 10.6084/m9.figshare.22012391
title: Raw data of the impact of multiple drivers on ambient ozone by machine learning coupled structure mining method

description: Raw data of the impact of multiple drivers on ambient ozone by machine learning coupled structure mining method
DOI: 10.6084/m9.figshare.22012391.v1
title: Raw data of the impact of multiple drivers on ambient ozone by machine learning coupled structure mining method

description: Raw data of the impact of multiple drivers on ambient ozone by machine learning coupled structure mining method
DOI: 10.6084/m9.figshare.21561891.v2
title: Intestinal microbiota 16SrRNA sequencing data from hypothyroidism in the first half of pregnancy.rar

description: Flow cytometry and 16S rRNA in hypothyroidism during the first half of pregnancy
DOI: 10.6084/m9.figshare.22004633
title: Supplementary Table

description: Supplementary Table 1 Comparison of alpha diversity between the hypothyroidism and control groups. <br> Supplementary Table 2 AUC values of intestinal microflora. <br> Supplementary Table 3. Correlations between the intestinal microflora with Th1/Th2 cells, cytokines, and clinical indicators. <br> Supplementary Table 4. Correlations between the TPOAb with the Th1/Th2 cells, cytokines, and clinical indicators.
DOI: 10.6084/m9.figshare.22004633.v3
title: Supplementary Table

description: Supplementary Table 1 Comparison of alpha diversity between the hypothyroidism and control groups. <br> Supplementary Table 2 AUC values of intestinal microflora. <br> Supplementary Table 3. Correlations between the intestinal microflora with Th1/Th2 cells, cytokines, and clinical indicators. <br> Supplementary Table 4. Correlations between the TPOAb with the Th1/Th2 cells, cytokines, and clinical indicators.
DOI: 10.6084/m9.figshare.22004633.v2
title: Supplementary Table

description: Supplementary Table 1 Comparison of alpha diversity between the hypothyroidism and control groups. <br> Supplementary Table 2 AUC values of intestinal microflora. <br> Supplementary Table 3. Correlations between the intestinal microflora with Th1/Th2 cells, cytokines, and clinical indicators. <br> Supplementary Table 4. Correlations between the TPOAb with the Th1/Th2 cells, cytokines, and clinical indicators.
DOI: 10.6084/m9.figshare.21561891.v3
title: Intestinal microbiota 16SrRNA sequencing data from hypothyroidism in the first half of pregnancy.rar

description: Flow cytometry and 16S rRNA in hypothyroidism during the first half of pregnancy
DOI: 10.6084/m9.figshare.22012421
title: Raw Data of the impact of multiple drivers on ambient ozone.xlsx

description: Raw data of the impact of multiple drivers on ambient ozone by machine learning coupled structure mining method.
DOI: 10.6084/m9.figshare.21561891.v4
title: Intestinal microflora and Th1/Th2 Balance in hypothyroidism during the first half of pregnancy

description: Flow cytometry and 16S rRNA in hypothyroidism during the first half of pregnancy
DOI: 10.5281/zenodo.7105136
title: Data for the manuscript titled "Solute front shear and coalescence control concentration gradient dynamics in porous micromodel"

description: Concentration images and data for plots for the manuscript "Solute front shear and coalescence control concentration gradient dynamics in porous micromodel" submitted for publication in Geophysical Research Letters. See the README file for explanations on the data file. <strong>Movie captions:</strong> <strong>Movie S1:</strong> Concentration field for the Péclet Pe = 33 experiment. Solid pillars are represented by the gray discs, and the colormap corresponds to the rescaled concentration \(c/c_\mathrm{max}\). The black line represents the solute front, which is the boundary of the continuous \(c/c_\mathrm{max} &lt; 0.5\) region within the porous medium. The x- and y-coordinates of the porous medium length and width (respectively) are rescaled by the average pore diameter \(\lambda\). <strong>Movie S2:</strong> Concentration gradient field for the Pe = 33 experiment. Solid pillars are represented by the gray discs, and the colormap corresponds to the rescaled gradient \( a \nabla c / c_\mathrm{max}\). The x- and y-coordinates of the porous medium length and width (respectively) are rescaled by the average pore diameter \(\lambda\). <strong>Movie S3:</strong> Concentration field for the Pe = 1104 experiment. Solid pillars are represented by the gray discs, and the colormap corresponds to the rescaled concentration \(c/c_\mathrm{max}\). The black line represents the solute front, which is the boundary of the continuous \(c/c_\mathrm{max} &lt; 0.5\) region within the porous medium. The x- and y-coordinates of the porous medium length and width (respectively) are rescaled by the average pore diameter \(\lambda\). <strong>Movie S4:</strong> Concentration gradients field for the Pe = 1104 experiment. Solid pillars are represented by the gray discs, and the colormap corresponds to the rescaled gradient \( a \nabla c / c_\mathrm{max}\). The x- and y-coordinates of the porous medium length and width (respectively) are rescaled by the average pore diameter \(\lambda\).
DOI: 10.6084/m9.figshare.21561891.v5
title: Intestinal microflora and Th1/Th2 Balance in hypothyroidism during the first half of pregnancy

description: Flow cytometry and 16S rRNA in hypothyroidism during the first half of pregnancy
DOI: 10.34740/kaggle/dsv/4949940
title: YouTube Daily
DOI: 10.6084/m9.figshare.22012445
title: Main data

description: Data used to create the figures
DOI: 10.6084/m9.figshare.22012445.v1
title: Main data

description: Data used to create the figures
DOI: 10.6084/m9.figshare.22010699
title: Wallstreetbets Reddit Data (10/2020 - 04/2022)

description: Data used in the article "The Echo Chamber Effect Resounds on Financial Markets: A Social Media Alert System for Meme Stocks" by Ilaria Gianstefani, Luigi Longo, Massimo Riccaboni. <br> https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4053771 <br> To cite the paper: <br> @article{gianstefani2022echo,<br> title={The echo chamber effect resounds on financial markets: A social media alert system for meme stocks},<br> author={Gianstefani, Ilaria and Longo, Luigi and Riccaboni, Massimo},<br> journal={arXiv preprint arXiv:2203.13790},<br> year={2022}<br> }<br> <br> The folder common_stats contains raw data for submissions and comments related to keywords. <br> The folder reddit_raw contains statistics computed with the methodology used in the paper.
DOI: 10.6084/m9.figshare.21991844.v1
title: supplementary file 3 (data set).xlsx

description: this is a raw data for a project titled ''Knowledge and information sources of Helicobacter pylori among Jordanian population: a cross-sectional study.''
DOI: 10.6084/m9.figshare.22012460
title: Spatial and spatiotemporal approaches

description: Raw data associated with: Ángel Gálvez, Pedro R. Peres-Neto, Andreu Castillo-Escrivà, Fabián Bonilla, Antonio Camacho, Eduardo M. García-Roger, Sanda Iepure, Javier Miralles-Lorenzo, Juan S. Monrós, Carla Olmo, Antonio Picazo, Carmen Rojo, Juan Rueda, Mahmood Sasa, Mati Segura, Xavier Armengol and Francesc Mesquita-Joanes. Comparing spatial and spatiotemporal metacommunity approaches across Mediterranean and tropical temporary ponds: a multi-taxon analysis <br> Data containing: Environmental, XY and temporal variables of tropical and mediterranean ponds Species matrices of phytoplankton, microinvertebrates, macroinvertebrates and amphibians from tropical and mediterranean ponds ZOTUs matrices of bacteria and archaea of the water column from tropical and mediterranean ponds.
DOI: 10.6084/m9.figshare.22012460.v1
title: Spatial and spatiotemporal approaches

description: Raw data associated with: Ángel Gálvez, Pedro R. Peres-Neto, Andreu Castillo-Escrivà, Fabián Bonilla, Antonio Camacho, Eduardo M. García-Roger, Sanda Iepure, Javier Miralles-Lorenzo, Juan S. Monrós, Carla Olmo, Antonio Picazo, Carmen Rojo, Juan Rueda, Mahmood Sasa, Mati Segura, Xavier Armengol and Francesc Mesquita-Joanes. Comparing spatial and spatiotemporal metacommunity approaches across Mediterranean and tropical temporary ponds: a multi-taxon analysis <br> Data containing: Environmental, XY and temporal variables of tropical and mediterranean ponds Species matrices of phytoplankton, microinvertebrates, macroinvertebrates and amphibians from tropical and mediterranean ponds ZOTUs matrices of bacteria and archaea of the water column from tropical and mediterranean ponds.
DOI: 10.34740/kaggle/dsv/4950033
title: Global Genomic Neurofibromatosis Neoplasia
DOI: 10.34740/kaggle/dsv/4950116
title: 2021 World Population (updated daily)
DOI: 10.5281/zenodo.7607157
title: co-injection_images

description: Images of simultaneous air-liquid injection
DOI: 10.21227/261x-mr59
title: Dataset for Channel Estimation in RIS-assisted Satellite IoT Communications

description: The proposed GAT-based channel estimation method examines the performance of the DtS IoT networks for different RIS configurations to solve the challenging channel estimation problem. It is shown that the proposed GAT both demonstrates a higher performance with increased robustness under changing conditions and has lower computational complexity compared to conventional deep learning methods.
DOI: 10.6084/m9.figshare.22012394
title: Water Metagenome Databases.zip

description: Unpublished metagenome database
DOI: 10.6084/m9.figshare.22012394.v1
title: Water Metagenome Databases.zip

description: Unpublished metagenome database
DOI: 10.34740/kaggle/dsv/4950184
title: YouTube Trending Video Dataset (updated daily)
DOI: 10.5281/zenodo.7607268
title: Anwendung des Oxford Stringency Index auf die Spanische Grippe in den Städten Winterthur und St. Gallen

description: This is data, used in the bachelor thesis "Anwendung des Oxford Stringency Index auf die Spanische Grippe in den Städten Winterthur und St. Gallen". The excel is written mainly in German. On the second tab relevant historical sources are listed. The file contains tabs with the following data: Tab Name Content INT_WT All for the thesis used primary sources (excl. secondary sources) INT_SG Interventions in St. Gallen INT_LONGLIST Longlist of all interventions on all levels (federal, cantonal, municipality level) MM_OVERVIEW Morbidity & mortality of St. Gallen, Winterthur and other Swiss regions per week SI_WT Stringency Index Winterthur SI_SG Stringency Index St. Gallen
DOI: 10.5281/zenodo.7515011
title: Anwendung des Oxford Stringency Index auf die Spanische Grippe in den Städten Winterthur und St. Gallen

description: This is data, used in the bachelor thesis "Anwendung des Oxford Stringency Index auf die Spanische Grippe in den Städten Winterthur und St. Gallen". The excel is written mainly in German. On the second tab relevant historical sources are listed. The file contains tabs with the following data: Tab Name Content INT_WT All for the thesis used primary sources (excl. secondary sources) INT_SG Interventions in St. Gallen INT_LONGLIST Longlist of all interventions on all levels (federal, cantonal, municipality level) MM_OVERVIEW Morbidity & mortality of St. Gallen, Winterthur and other Swiss regions per week SI_WT Stringency Index Winterthur SI_SG Stringency Index St. Gallen
DOI: 10.5281/zenodo.7605252
title: MUSES Leaf Area Index (LAI) 8-Day Global 500m SIN Grid in 2006

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 2006. <em>Please <strong>click here</strong> to download the MUSES LAI product <strong>in 2005</strong></em><strong>, </strong>and <em><strong>click here</strong> to download the MUSES LAI product <strong>in 2007</strong></em>. <strong>Dataset Characteristics:</strong> Spatial Coverage: Global Temporal Coverage: 2006 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.7605251
title: MUSES Leaf Area Index (LAI) 8-Day Global 500m SIN Grid in 2006

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 2006. <em>Please <strong>click here</strong> to download the MUSES LAI product <strong>in 2005</strong></em><strong>, </strong>and <em><strong>click here</strong> to download the MUSES LAI product <strong>in 2007</strong></em>. <strong>Dataset Characteristics:</strong> Spatial Coverage: Global Temporal Coverage: 2006 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: 10.5517/ccdc.csd.cc2c5cwt
title: CCDC 2179916: Experimental Crystal Structure Determination

description: Related Article: Nabil Mroweh, Thomas Cauchy, Nicolas Vanthuyne, Narcis Avarvari|2022|CrystEngComm|24|6187|doi:10.1039/D2CE00857B
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.7607275
title: co-injection_images

description: Images of simultaneous air-liquid injection
DOI: 10.5281/zenodo.7607156
title: co-injection_images

description: Images of simultaneous air-liquid injection
DOI: 10.34740/kaggle/dsv/4950343
title: COVID Vaccination in World (updated daily)
DOI: 10.5281/zenodo.7607303
title: balanus_glandula_spades_01.fasta.gz

description: .
DOI: 10.5281/zenodo.7607302
title: balanus_glandula_spades_01.fasta.gz

description: .
DOI: 10.5281/zenodo.7607321
title: pyrrhura_rhodocephala_spades_01.fasta.gz

description: .
DOI: 10.5281/zenodo.7607320
title: pyrrhura_rhodocephala_spades_01.fasta.gz

description: .
DOI: 10.6084/m9.figshare.21532920
title: cifar10&cifar100

description: This is Cifar10 & Cifar100 datasets.
DOI: 10.6084/m9.figshare.21532920.v2
title: cifar10&cifar100

description: This is Cifar10 & Cifar100 datasets.
DOI: 10.6084/m9.figshare.21532920.v1
title: datasets.rar

description: This is Cifar10 & Cifar100 datasets.
DOI: 10.5281/zenodo.7599932
title: Data and code for "Realization of a minimal Kitaev chain in coupled quantum dots"

description: This folder contains the raw data and code used to generate the plots for the paper <em>Realization of a minimal Kitaev chain in coupled quantum dots</em> (arXiv: 2206.08045). To run the Jupyter notebook, install Anaconda and execute: <pre><code class="language-bash">conda env create -f env.yml</code></pre> followed by: <pre><code class="language-bash">conda activate pmm-paper</code></pre> Finally, <pre><code class="language-bash">jupyter notebook</code></pre> to launch the notebook. Raw data are stored in netCDF (.nc) format. The files are exported by the data acquisition package QCoDeS and can be read as an xarray Dataset.
DOI: 10.5281/zenodo.6594169
title: Data and code for "Realization of a minimal Kitaev chain in coupled quantum dots"

description: This folder contains the raw data and code used to generate the plots for the paper <em>Realization of a minimal Kitaev chain in coupled quantum dots</em> (arXiv: 2206.08045). To run the Jupyter notebook, install Anaconda and execute: <pre><code class="language-bash">conda env create -f env.yml</code></pre> followed by: <pre><code class="language-bash">conda activate pmm-paper</code></pre> Finally, <pre><code class="language-bash">jupyter notebook</code></pre> to launch the notebook. Raw data are stored in netCDF (.nc) format. The files are exported by the data acquisition package QCoDeS and can be read as an xarray Dataset.
DOI: 10.5281/zenodo.7607347
title: mopalia_vespertina_spades_01.fasta.gz

description: .
DOI: 10.5281/zenodo.7607346
title: mopalia_vespertina_spades_01.fasta.gz

description: .
DOI: 10.6084/m9.figshare.22012529
title: Tiny_Imagenet

description: iny Imagenet has 200 Classes, each class has 500 traininig images, 50 Validation Images and 50 test images. Label Classes and Bounding Boxes are provided. More details can be found at https://tiny-imagenet.herokuapp.com/", <br> This challenge is part of Stanford Class CS 231N
DOI: 10.5281/zenodo.7607372
title: pyrrhura_leucotis_spades_01.fasta.gz

description: .
DOI: 10.5281/zenodo.7607371
title: pyrrhura_leucotis_spades_01.fasta.gz

description: .
DOI: 10.5281/zenodo.7607350
title: Underlying data for The impact of COVID-19 severity on pregnancy outcomes among Iraqi women: a retrospective observational study

description: Underlying data for The impact of COVID-19 severity on pregnancy outcomes among Iraqi women: a retrospective observational study
DOI: 10.6084/m9.figshare.21977324
title: Tables S1 to S3

description: An Excel file including three tables. Table 1: Characteristics of the videos and tracing challenges. Table 2: Parameters used for the tracking with AnimalTA Table 3: Performance of the tracking and comparison with two other programs.
DOI: 10.6084/m9.figshare.21977324.v3
title: Tables S1 to S3

description: An Excel file including three tables. Table 1: Characteristics of the videos and tracing challenges. Table 2: Parameters used for the tracking with AnimalTA Table 3: Performance of the tracking and comparison with two other programs.
DOI: 10.6084/m9.figshare.21977324.v2
title: Tables S1 to S3

description: An Excel file including three tables. Table 1: Characteristics of the videos and tracing challenges. Table 2: Parameters used for the tracking with AnimalTA Table 3: Performance of the tracking and comparison with two other programs.
DOI: 10.5281/zenodo.7607381
title: STROBE checklist for: The impact of COVID-19 severity on pregnancy outcomes among Iraqi women: a retrospective observational study

description: STROBE checklist for: The impact of COVID-19 severity on pregnancy outcomes among Iraqi women: a retrospective observational study
DOI: 10.6084/m9.figshare.19114213
title: Interprofessional communication in the hospital setting : a systematic review of the qualitative literature

description: Communication plays a key role in the provision of safe patient care, and miscommunication in healthcare can lead to avoidable patient harm or mortality. Interprofessional communication (IPCom) can be challenging due to differences in training, education and roles between healthcare professions. The aim of this systematic review was to synthesize the qualitative evidence regarding healthcare providers’ perceptions of interprofessional communication in the hospital setting. Four databases (PubMed, CINAHL, Web of Science, and Embase) were searched for studies that met the inclusion criteria. Eighteen studies were identified as suitable for inclusion in the review and were examined using thematic synthesis. Thematic synthesis led to the development of five descriptive themes: 1) <i>‘Hierarchy”</i>, 2) “<i>Interprofessional Ethos,”</i> 3) <i>“Healthcare Environment,”</i> 4) “<i>Personal Factors”</i> and 5) “<i>Methods of Communication,”</i> and two overarching analytical themes: “<i>Barriers to Communication</i>” and <i>“Facilitators to Communication</i>.” Personal factors, such as strong interprofessional relationships, were found to be important facilitators to IPCom, while organizational factors, such as challenging and hierarchical working environments, were found to pose barriers to IPCom.