cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.8397926
title: AMAR L2+Products_all_cruises

description: ADEON Cruises: AR025, EN615, EN626, and AR040 AMAR L2+ data product. This data contains the Level 2 results computed from the ADEON passive acoustic monitoring data. Level 2 results are sound pressure levels (SPL), sound exposure levels (SEL) computed over different snapshot durations, and SPL/SEL statistics computed over different temporal analysis windows, as described in the ADEON Soundscape and Modelling Metadata Standard. The data is accompanied by folder containing 6 different readme files.
DOI: 10.6084/m9.figshare.8397926.v12
title: AMAR L2+Products_all_cruises

description: ADEON Cruises: AR025, EN615, EN626, and AR040 AMAR L2+ data product. This data contains the Level 2 results computed from the ADEON passive acoustic monitoring data. Level 2 results are sound pressure levels (SPL), sound exposure levels (SEL) computed over different snapshot durations, and SPL/SEL statistics computed over different temporal analysis windows, as described in the ADEON Soundscape and Modelling Metadata Standard. The data is accompanied by folder containing 6 different readme files.
DOI: 10.5281/zenodo.5232000
title: CoVaxxy Tweet IDs data set

description: A collection of Tweet IDs related to Covid-19 Vaccines, gathered from Twitter since Jan 4, 2021. Please see https://arxiv.org/abs/2101.07694 for more information.
DOI: 10.6084/m9.figshare.15167406.v1
title: Registries performance CCAA NICSMORU 13-08-21

description: This is the census data for CCAA NICSMORU describing patients number of patients entering ICU and the number recorded in our registry
DOI: 10.6084/m9.figshare.14384832.v9
title: axivity-ax6-left-forearm-nondominant

description: 6-axis actigraphy (translation and rotation) using Axivity AX6 (similar to AX3 used in UK BioBank), configured with 100Hz sampling frequency, 16bit resolution and 2000dps gyro/rotation.<br>Attached with a velcro to the exterior of a cotton wrist band with arrow facing down towards the ground/back when arms are in a natural position along the body, on the left forearm (non-dominant arm).<br>Started acquisition in March 2021.<br>Each file represents one acquisition session of about 1 week. Multiple files can be concatenated to study a longer time period.
DOI: 10.6084/m9.figshare.14384819.v4
title: ibutton-left-nondominant-upper-arm-cotton-sports-wristband-5min

description: Skin temperature using a Maxim Thermocron iButton DS1925L set at a resolution of one sample every 5 min (max resolution) and temperature resolution of 0.0625°C (max resolution), placed on the radial artery on the forearm (between elbow and wrist, about in the middle with a slightly changing position regularly to avoid skin damage due to continuous skin obstruction and warmth), by being attached with a velcro to the interior of a cotton sports wrist band. See the works of Dr. Antonio Martinez Nicolas for more details on wrist skin temperature rhythm and WTIO.<br>The procedure is described in: https://pubmed.ncbi.nlm.nih.gov/18761026/<br>This dataset can be used alone or in combination with ibutton-left-nondominant-upper-arm-cotton-sports-wristband-dorsal-interior-5min and ibutton-left-nondominant-upper-arm-cotton-sports-wristband-ventral-exterior-5min to regress dorsal skin temperature and ambient temperature respectively.<br>Each file contains the whole history up to the timestamp in the filename. Hence, to study the longest period, use only the latest file, do not concatenate with previous ones.<br><br>There is unfortunately some missing data from 2021-07-06 to 2021-07-16 because the internal memory was unexpectedly already filled (it should have been able to store more than a year according to the manufacturer's documentation). The maximum number of samples seems to be 62720.
DOI: 10.6084/m9.figshare.14456312.v3
title: ibutton-left-nondominant-upper-arm-cotton-sports-wristband-ventral-exterior-5min

description: Skin temperature using a Maxim Thermocron iButton DS1925L set at a resolution of one sample every 5 min (max resolution) and temperature resolution of 0.0625°C (max resolution), placed on the ventral side of the forearm, by being attached with a velcro to the exterior of a cotton sports wrist band.<br>This dataset is meant to capture ambient temperature. It is placed just beside the main skin sensor but on the exterior of the cotton wristband instead of the interior, so that this sensor reflects the ambient temperature at the exact site where the main skin sensor is. This should be used in combination with the ibutton-left-nondominant-upper-arm-cotton-sports-wristband-5min dataset (main skin sensor, placed on the radial artery).<br>Each file contains the whole history up to the timestamp in the filename. Hence, to study the longest period, use only the latest file, do not concatenate with previous ones.
DOI: 10.6084/m9.figshare.14456314.v3
title: ibutton-left-nondominant-upper-arm-cotton-sports-wristband-dorsal-interior-5min

description: Skin temperature using a Maxim Thermocron iButton DS1925L set at a resolution of one sample every 5 min (max resolution) and temperature resolution of 0.0625°C (max resolution), placed on the dorsal side of the forearm, at the opposite of the radial artery, by being attached with a velcro to the interior of a cotton sports wrist band.<br>This dataset is meant to capture skin temperature at another site than the radial artery, so that the dataset may be useful for spurious temperature changes regression. This should be used in combination with the ibutton-left-nondominant-upper-arm-cotton-sports-wristband-5min dataset.<br>Each file contains the whole history up to the timestamp in the filename. Hence, to study the longest period, use only the latest file, do not concatenate with previous ones.
DOI: 10.6084/m9.figshare.14650542.v2
title: non24-body-weight

description: Body weight evolution from 2018 up to 2021, using a RENPHO bluetooth connected bathroom scale through the FeelFit Android app.<br>Each CSV file contains the whole dataset up to the exported date as indicated in the filename, hence prefer using only the latest file only, the others can be discarded.
DOI: 10.6084/m9.figshare.16305324
title: PTCNs.xlsx

description: The data is for the numerical test in "Collaborative Pricing in a Power-transportation coupled network: A Variational Inequality Approach".
DOI: 10.6084/m9.figshare.16305324.v1
title: PTCNs.xlsx

description: The data is for the numerical test in "Collaborative Pricing in a Power-transportation coupled network: A Variational Inequality Approach".
DOI: 10.5281/zenodo.5229277
title: Distinct Roles of Land Cover in Regulating Spatial Variabilities of Temperature Responses to Radiative Effects of Aerosols and Clouds

description: Dataset of drawing figures in work 'Distinct Roles of Land Cover in Regulating Spatial Variabilities of Temperature Responses to Radiative Effects of Aerosols and Clouds'. Dataset File List 1. Present_Day_Variables.nc : global spatial distributions of radiative forcing, climate sensitivity and temperature response 2. Regional_Variables.xlsx : regional data of radiative forcing, climate sensitivity and temperature response 3. Aerosol_Burdens.nc : monthly aerosol burdens (atmospheric column concentration) of ten simulation cases 4. Aerosol_Burdens_README.txt : dimensional descriptions of Aerosol_Burdens.nc 5. Monthly_Radiation.nc : monthly radiation variables of PD simulation for testing model performance 6. Monthly_Radiation_README.txt : dimensional descriptions of Monthly_Radiation.nc
DOI: 10.5281/zenodo.5229276
title: Distinct Roles of Land Cover in Regulating Spatial Variabilities of Temperature Responses to Radiative Effects of Aerosols and Clouds

description: Dataset of drawing figures in work 'Distinct Roles of Land Cover in Regulating Spatial Variabilities of Temperature Responses to Radiative Effects of Aerosols and Clouds'. Dataset File List 1. Present_Day_Variables.nc : global spatial distributions of radiative forcing, climate sensitivity and temperature response 2. Regional_Variables.xlsx : regional data of radiative forcing, climate sensitivity and temperature response 3. Aerosol_Burdens.nc : monthly aerosol burdens (atmospheric column concentration) of ten simulation cases 4. Aerosol_Burdens_README.txt : dimensional descriptions of Aerosol_Burdens.nc 5. Monthly_Radiation.nc : monthly radiation variables of PD simulation for testing model performance 6. Monthly_Radiation_README.txt : dimensional descriptions of Monthly_Radiation.nc
DOI: 10.18112/openneuro.ds003673.v1.0.1
title: Yale Resting State fMRI/Pupillometry: Arousal Study
DOI: 10.6084/m9.figshare.16305345
title: Different conformations of RNA-dependent RNA polymerase of SARS-CoV-2 under different experimental conditions

description: Proteins do not exist in isolation in the cellular milieu. Often, they are bound to other proteins, cofactors, or are influenced by the prevailing physicochemical conditions to be under different conformations. This work collates four different experimental structures of RNA-dependent RNA polymerase of SARS-CoV-2 deposited at the Protein Data Bank. Obtained under different experimental conditions such as with and without reducing conditions, or pre- or post-translocation, the presented structures should be useful for further analysis of the functional role of RNA-dependent RNA polymerase in the pathogenesis of SARS-CoV-2.
DOI: 10.6084/m9.figshare.16305345.v1
title: Different conformations of RNA-dependent RNA polymerase of SARS-CoV-2 under different experimental conditions

description: Proteins do not exist in isolation in the cellular milieu. Often, they are bound to other proteins, cofactors, or are influenced by the prevailing physicochemical conditions to be under different conformations. This work collates four different experimental structures of RNA-dependent RNA polymerase of SARS-CoV-2 deposited at the Protein Data Bank. Obtained under different experimental conditions such as with and without reducing conditions, or pre- or post-translocation, the presented structures should be useful for further analysis of the functional role of RNA-dependent RNA polymerase in the pathogenesis of SARS-CoV-2.
DOI: 10.6084/m9.figshare.16305388
title: Additional file 10 of Pathogen and drought stress affect cell wall and phytohormone signaling to shape host responses in a sorghum COMT bmr12 mutant

description: Additional file 10 Shell script for using Kallisto to pseudoalign reads to the S. bicolor genome.
DOI: 10.6084/m9.figshare.16305388.v1
title: Additional file 10 of Pathogen and drought stress affect cell wall and phytohormone signaling to shape host responses in a sorghum COMT bmr12 mutant

description: Additional file 10 Shell script for using Kallisto to pseudoalign reads to the S. bicolor genome.
DOI: 10.6084/m9.figshare.16305391
title: Additional file 11 of Pathogen and drought stress affect cell wall and phytohormone signaling to shape host responses in a sorghum COMT bmr12 mutant

description: Additional file 11. R markdown notebook containing WGCNA and downstream analysis.
DOI: 10.6084/m9.figshare.16305391.v1
title: Additional file 11 of Pathogen and drought stress affect cell wall and phytohormone signaling to shape host responses in a sorghum COMT bmr12 mutant

description: Additional file 11. R markdown notebook containing WGCNA and downstream analysis.
DOI: 10.6084/m9.figshare.16305397
title: Additional file 13 of Pathogen and drought stress affect cell wall and phytohormone signaling to shape host responses in a sorghum COMT bmr12 mutant

description: Additional file 13. R markdown notebook containing time to bloom and metabolite analysis.
DOI: 10.6084/m9.figshare.16305397.v1
title: Additional file 13 of Pathogen and drought stress affect cell wall and phytohormone signaling to shape host responses in a sorghum COMT bmr12 mutant

description: Additional file 13. R markdown notebook containing time to bloom and metabolite analysis.
DOI: 10.6084/m9.figshare.16305400
title: Additional file 14 of Pathogen and drought stress affect cell wall and phytohormone signaling to shape host responses in a sorghum COMT bmr12 mutant

description: Additional file 14. Pseudoalignment statistics from Kallisto v0.44.
DOI: 10.6084/m9.figshare.16305400.v1
title: Additional file 14 of Pathogen and drought stress affect cell wall and phytohormone signaling to shape host responses in a sorghum COMT bmr12 mutant

description: Additional file 14. Pseudoalignment statistics from Kallisto v0.44.
DOI: 10.6084/m9.figshare.16305406
title: Additional file 16 of Pathogen and drought stress affect cell wall and phytohormone signaling to shape host responses in a sorghum COMT bmr12 mutant

description: Additional file 16. Complete Cq values for qPCR validation.
DOI: 10.6084/m9.figshare.16305406.v1
title: Additional file 16 of Pathogen and drought stress affect cell wall and phytohormone signaling to shape host responses in a sorghum COMT bmr12 mutant

description: Additional file 16. Complete Cq values for qPCR validation.
DOI: 10.6084/m9.figshare.16305409
title: Additional file 1 of Pathogen and drought stress affect cell wall and phytohormone signaling to shape host responses in a sorghum COMT bmr12 mutant

description: Additional file 1. Data table containing all plants sampled for this study, including metabolite samples, where applicable.
DOI: 10.6084/m9.figshare.16305412
title: Additional file 2 of Pathogen and drought stress affect cell wall and phytohormone signaling to shape host responses in a sorghum COMT bmr12 mutant

description: Additional file 2. Filterable table of module-trait correlations for lesion-related genes, as defined in the text.
DOI: 10.6084/m9.figshare.16305409.v1
title: Additional file 1 of Pathogen and drought stress affect cell wall and phytohormone signaling to shape host responses in a sorghum COMT bmr12 mutant

description: Additional file 1. Data table containing all plants sampled for this study, including metabolite samples, where applicable.
DOI: 10.6084/m9.figshare.16305412.v1
title: Additional file 2 of Pathogen and drought stress affect cell wall and phytohormone signaling to shape host responses in a sorghum COMT bmr12 mutant

description: Additional file 2. Filterable table of module-trait correlations for lesion-related genes, as defined in the text.
DOI: 10.6084/m9.figshare.16305421
title: Additional file 4 of Pathogen and drought stress affect cell wall and phytohormone signaling to shape host responses in a sorghum COMT bmr12 mutant

description: Additional file 4. KEGG enrichment results for all modules, calculated by the KOBAS tool.
DOI: 10.6084/m9.figshare.16305421.v1
title: Additional file 4 of Pathogen and drought stress affect cell wall and phytohormone signaling to shape host responses in a sorghum COMT bmr12 mutant

description: Additional file 4. KEGG enrichment results for all modules, calculated by the KOBAS tool.
DOI: 10.6084/m9.figshare.16305427
title: Additional file 5 of Pathogen and drought stress affect cell wall and phytohormone signaling to shape host responses in a sorghum COMT bmr12 mutant

description: Additional file 5. Relative expression of module eigengenes, calculated by WGCNA.
DOI: 10.6084/m9.figshare.16305427.v1
title: Additional file 5 of Pathogen and drought stress affect cell wall and phytohormone signaling to shape host responses in a sorghum COMT bmr12 mutant

description: Additional file 5. Relative expression of module eigengenes, calculated by WGCNA.
DOI: 10.6084/m9.figshare.16305433
title: Additional file 7 of Pathogen and drought stress affect cell wall and phytohormone signaling to shape host responses in a sorghum COMT bmr12 mutant

description: Additional file 7. SAS script to calculate a linear model to compare lesion lengths.
DOI: 10.6084/m9.figshare.16305433.v1
title: Additional file 7 of Pathogen and drought stress affect cell wall and phytohormone signaling to shape host responses in a sorghum COMT bmr12 mutant

description: Additional file 7. SAS script to calculate a linear model to compare lesion lengths.
DOI: 10.6084/m9.figshare.16305442
title: Additional file 9 of Pathogen and drought stress affect cell wall and phytohormone signaling to shape host responses in a sorghum COMT bmr12 mutant

description: Additional file 9. Lexogen-recommended script for trimming raw RNA-Seq reads.
DOI: 10.6084/m9.figshare.16305685.v1
title: Additional file 1 of Modeling analysis reveals the transmission trend of COVID-19 and control efficiency of human intervention

description: Additional file 1: Data S1. Data on the number of cumulative cases of COVID-19 in seven countries.
DOI: 10.6084/m9.figshare.16305822
title: Additional file 1 of Use of research electronic data capture (REDCap) in a COVID-19 randomized controlled trial: a practical example

description: Additional file 1.
DOI: 10.6084/m9.figshare.16305822.v1
title: Additional file 1 of Use of research electronic data capture (REDCap) in a COVID-19 randomized controlled trial: a practical example

description: Additional file 1.
DOI: 10.6084/m9.figshare.16305826
title: Additional file 2 of GWAS provides biological insights into mechanisms of the parasitic plant (Striga) resistance in sorghum

description: Additional file 2.
DOI: 10.6084/m9.figshare.16305826.v1
title: Additional file 2 of GWAS provides biological insights into mechanisms of the parasitic plant (Striga) resistance in sorghum

description: Additional file 2.
DOI: 10.6084/m9.figshare.16305829
title: Additional file 3 of GWAS provides biological insights into mechanisms of the parasitic plant (Striga) resistance in sorghum

description: Additional file 3.
DOI: 10.6084/m9.figshare.16305829.v1
title: Additional file 3 of GWAS provides biological insights into mechanisms of the parasitic plant (Striga) resistance in sorghum

description: Additional file 3.
DOI: 10.6084/m9.figshare.16305832
title: Additional file 4 of GWAS provides biological insights into mechanisms of the parasitic plant (Striga) resistance in sorghum

description: Additional file 4.
DOI: 10.6084/m9.figshare.16305832.v1
title: Additional file 4 of GWAS provides biological insights into mechanisms of the parasitic plant (Striga) resistance in sorghum

description: Additional file 4.
DOI: 10.6084/m9.figshare.16305852
title: Additional file 2 of Mesenchymal stem cell-based therapy and exosomes in COVID-19: current trends and prospects

description: Additional file 2. Detailed Excel sheet of the ongoing clinical trials with MSCs interventions in COVID-19 patients.
DOI: 10.6084/m9.figshare.16305852.v1
title: Additional file 2 of Mesenchymal stem cell-based therapy and exosomes in COVID-19: current trends and prospects

description: Additional file 2. Detailed Excel sheet of the ongoing clinical trials with MSCs interventions in COVID-19 patients.
DOI: 10.6084/m9.figshare.16305900
title: Additional file 1 of Identification of key genes affecting porcine fat deposition based on co-expression network analysis of weighted genes

description: Additional file 1: Supplementary Table 1. Body weight and backfat thickness between different groups. Supplementary Table 2. KEGG analysis of genes in the four modules related to traits. Supplementary Fig. 1. Analysis of network topology for various soft-thresholding powers. According to the definition of soft threshold, try to choose a large R2 value. According to the suggestion of WGCNA package, choose an R2 value greater than 0.8, that is, the value above the red line in the left figure. The figure on the right shows the average connectivity of the constructed network. The larger the network is, the closer the gene is, and the more conducive it is to screen out hub genes. Supplementary Fig. 2. Venn map of differentially expressed genes (DEGs) of Panel a, b and c respectively shows the situation of the differentially expressed genes in adipose tissue, muscle and liver of Songliao black pigs. Panel e, f and g respectively shows the situation of the differentially expressed genes in adipose tissue, muscle and liver of Landrace. The x-axis represents the multiple of difference, which is denoted by log2FoldChange. The larger the absolute value is, the larger the multiple of difference is. The y-axis represents the significance of the difference, which is denoted by -log10(P-value). The larger the value is, the more significant the difference is. Each panel shows the names of the top 20 genes with the most significant differences. Supplementary Fig. 3. Volcanogram of differentially expressed genes in different tissues of two breeds. Panel a and b respectively shows the overlap of the differentially expressed genes in adipose tissue, muscle and liver of Songliao black pigs and Landrace. Panel b shows the overlap of all the differentially expressed genes of Songliao black pigs and Landrace. Supplementary Fig. 4. GO enrichment analysis and KEGG pathway analysis in different tissues of two breeds. Panel a, b and c respectively shows the enrichment entries of the differentially expressed genes in adipose tissue, liver and muscle of Landrace. Panel d, e and f shows the enrichment entries of the differentially expressed genes in adipose tissue, liver and muscle of Songliao black pigs. The x-axis represents the significance of the difference, which is denoted by -log2(P-value). Each bubble represents an enriched function, and the size of the bubble is set with six gradients according to the p-value, from small to large, representing the different significance levels: ns (P-value&gt; = 0.05), * (0.01
DOI: 10.6084/m9.figshare.16305900.v1
title: Additional file 1 of Identification of key genes affecting porcine fat deposition based on co-expression network analysis of weighted genes

description: Additional file 1: Supplementary Table 1. Body weight and backfat thickness between different groups. Supplementary Table 2. KEGG analysis of genes in the four modules related to traits. Supplementary Fig. 1. Analysis of network topology for various soft-thresholding powers. According to the definition of soft threshold, try to choose a large R2 value. According to the suggestion of WGCNA package, choose an R2 value greater than 0.8, that is, the value above the red line in the left figure. The figure on the right shows the average connectivity of the constructed network. The larger the network is, the closer the gene is, and the more conducive it is to screen out hub genes. Supplementary Fig. 2. Venn map of differentially expressed genes (DEGs) of Panel a, b and c respectively shows the situation of the differentially expressed genes in adipose tissue, muscle and liver of Songliao black pigs. Panel e, f and g respectively shows the situation of the differentially expressed genes in adipose tissue, muscle and liver of Landrace. The x-axis represents the multiple of difference, which is denoted by log2FoldChange. The larger the absolute value is, the larger the multiple of difference is. The y-axis represents the significance of the difference, which is denoted by -log10(P-value). The larger the value is, the more significant the difference is. Each panel shows the names of the top 20 genes with the most significant differences. Supplementary Fig. 3. Volcanogram of differentially expressed genes in different tissues of two breeds. Panel a and b respectively shows the overlap of the differentially expressed genes in adipose tissue, muscle and liver of Songliao black pigs and Landrace. Panel b shows the overlap of all the differentially expressed genes of Songliao black pigs and Landrace. Supplementary Fig. 4. GO enrichment analysis and KEGG pathway analysis in different tissues of two breeds. Panel a, b and c respectively shows the enrichment entries of the differentially expressed genes in adipose tissue, liver and muscle of Landrace. Panel d, e and f shows the enrichment entries of the differentially expressed genes in adipose tissue, liver and muscle of Songliao black pigs. The x-axis represents the significance of the difference, which is denoted by -log2(P-value). Each bubble represents an enriched function, and the size of the bubble is set with six gradients according to the p-value, from small to large, representing the different significance levels: ns (P-value&gt; = 0.05), * (0.01