cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.12250379
title: S4: Association of the relative abundance of bacterial KEGG pathways to the VLBW infants and term infants

description: Each page of this file shows a separate<br>pathway which was significantly different between the two groups. The box plots<br>indicate the association of the metadata (here, the two groups preterm and term<br>infants) with the relative abundances. The strength of association is indicated by<br>the p-value and an FDR-corrected q-value. The partial residual plot shows the<br>relationship between the groups with abundances when all other variables are<br>included in the model.
DOI: 10.6084/m9.figshare.12250379.v1
title: S4: Association of the relative abundance of bacterial KEGG pathways to the VLBW infants and term infants

description: Each page of this file shows a separate<br>pathway which was significantly different between the two groups. The box plots<br>indicate the association of the metadata (here, the two groups preterm and term<br>infants) with the relative abundances. The strength of association is indicated by<br>the p-value and an FDR-corrected q-value. The partial residual plot shows the<br>relationship between the groups with abundances when all other variables are<br>included in the model.
DOI: 10.6084/m9.figshare.12250367
title: Original data of 2018 mental and behavioral survey among adolescents in Hunan, China

description: This study was a cross-sectional survey conducted from April toJuly 2018. The participants were recruited from Hunan Province, China, by using multi-stage cluster sampling.
DOI: 10.6084/m9.figshare.12250337
title: Trend between absolute difference in array and WGS-derived HRD score and array/WGS dLRS

description: This file relates the array and WGS dLRS to the absolute difference in array- and WGS-derived HRD score. It contains the following columns: Sample, which represents the sample identification, dlrs_array, representing the dLRS from the array tumour samples,dlrs_WGS, representing the dLRS from the WGS tumour samples, diff_HRD, representing the absolute difference between array- and WGS-derived HRD score and category, representing the categorized absolute difference in array and WGS-derived HRD score.
DOI: 10.6084/m9.figshare.12250319
title: LockDown3_Tweets.xlsx

description: Introduction: Coronavirus disease (COVID-19) is an infectious disease caused by a newly discovered coronavirus (2019). In order to avoid spreading of virus in India, On 24 March 2020, the Government of India ordered a nationwide lockdown for 21 days(#LockDown1). On 14 April, Government extended the nationwide lockdown until 3 May, with a conditional relaxation after 20 April for the regions where the spread had been contained(#LockDown2). On 1 May, the Government of India extended the nationwide lockdown further by two weeks until 17 May(#LockDown3). The Government divided the entire nation into three zones—green, red and orange—with relaxations applied accordingly. Data Details: The data was collected using the "searchTwitteR" in RapidMiner using the twitter API. Dataset is created by pulling tweets by hashtag(#Lockdown3) from twitter. There are 9999 rows(one for each tweet) and 10 columns. Rows: 9999 Columns: 1.Created-At 2.From-User 3.From-User-Id 4.To-User 5.To-User-Id 6.Language 7.Source 8.Text 9.Retweet-Count 10.Id Task Details: ü Apply exploratory data analysis ü Create Word cloud ü Apply data preprocessing ü What is the general sentiment of tweets? ü Conclusion regarding tweet sentiments. ü Generate topics (Most discussed topic in lockdown phase 3)
DOI: 10.6084/m9.figshare.12250349
title: IJGIS-code&data.rar

description: The code was developed based on JetBrains PyCharm Community Edition 2018.2.4 x64, and the code language is Python. Run according to the last number of the function file<br>
DOI: 10.6084/m9.figshare.12250319.v1
title: LockDown3_Tweets.xlsx

description: Introduction: Coronavirus disease (COVID-19) is an infectious disease caused by a newly discovered coronavirus (2019). In order to avoid spreading of virus in India, On 24 March 2020, the Government of India ordered a nationwide lockdown for 21 days(#LockDown1). On 14 April, Government extended the nationwide lockdown until 3 May, with a conditional relaxation after 20 April for the regions where the spread had been contained(#LockDown2). On 1 May, the Government of India extended the nationwide lockdown further by two weeks until 17 May(#LockDown3). The Government divided the entire nation into three zones—green, red and orange—with relaxations applied accordingly. Data Details: The data was collected using the "searchTwitteR" in RapidMiner using the twitter API. Dataset is created by pulling tweets by hashtag(#Lockdown3) from twitter. There are 9999 rows(one for each tweet) and 10 columns. Rows: 9999 Columns: 1.Created-At 2.From-User 3.From-User-Id 4.To-User 5.To-User-Id 6.Language 7.Source 8.Text 9.Retweet-Count 10.Id Task Details: ü Apply exploratory data analysis ü Create Word cloud ü Apply data preprocessing ü What is the general sentiment of tweets? ü Conclusion regarding tweet sentiments. ü Generate topics (Most discussed topic in lockdown phase 3)
DOI: 10.6084/m9.figshare.12250337.v1
title: Trend between absolute difference in array and WGS-derived HRD score and array/WGS dLRS

description: This file relates the array and WGS dLRS to the absolute difference in array- and WGS-derived HRD score. It contains the following columns: Sample, which represents the sample identification, dlrs_array, representing the dLRS from the array tumour samples,dlrs_WGS, representing the dLRS from the WGS tumour samples, diff_HRD, representing the absolute difference between array- and WGS-derived HRD score and category, representing the categorized absolute difference in array and WGS-derived HRD score.
DOI: 10.6084/m9.figshare.12250349.v1
title: IJGIS-code&data.rar

description: The code was developed based on JetBrains PyCharm Community Edition 2018.2.4 x64, and the code language is Python. Run according to the last number of the function file<br>
DOI: 10.6084/m9.figshare.12250271
title: Modelling the Array HRD score

description: The columns contain the following information: Donor represents the sample for which the data is reported, log_HRD_score_Array is the log of the array-derived HRD score, log_HRD_score_WGS represents the log of the WGS-derived HRD score, Seg.LRR.dev is the deviation in segmented LRR data, dLRS_array is the dLRS for the array data, dLRS_WGS represents the dLRS for the WGS data, LRR.cor is the correlation between array and WGS LRR data, ACF is the cellularity of the sample, as derived from ascatNGS, Tumour_coverage is the coverage of the tumour sample, Normal_coverage is the coverage of the normal sample, fit represents the fitted array-derived HRD score, based on our model, lwr represents the lower 95% pointwise CI for the fitted array-derived HRD score, upr is the upper 95% pointwise CI for the fitted array-derived HRD score and Germline status reports the germline status of the sample.
DOI: 10.6084/m9.figshare.12250250
title: Drosophila melanogaster wing images genetic manipulation (UAS/GAL4) of growth regulators, and sex determination genes

description: This will be the repository for the raw images of <i>Drosophila melanogaster</i> used for the analysis of wing size, wing shape and cell (trichome) density counts from a very large study manipulating key genes in both the sex determination pathway (in particular <i>transformer</i>, <i>doublesex</i> and <i>fruitless</i>) and genes involved with tissue growth (in particular <i>Insulin Receptor</i>, <i>Target Of Rapamycin/</i>TOR and <i>dFoxo</i>) among others, using the UAS/GAL4 system in Drosophila melanogaster. While the full description will be included in the readme file. Essentially all strains were (when possible) backcrossed into a common wild type strain (Samarkand, marked with<i> white</i>). Experiments were performed at 3 temperatures (where the flies of each genotype were reared at each temperature), 18C, 24C and 28C. Control crosses (many different control crosses were done, see details) at each temperature. This experiment was done largely using the NP6333-GAL4 (also called Pen-GAL4) but a large chunk was replicated using the nubbin-GAL4 which had stronger expression in the wing and no expression (based on GFP reporter) in the legs like NP6333-GAL4 (which made it difficult to morphological determine the sex of individuals from some crosses). <br>The wings were imaged using an Olympus BX-41 microscope under brightfield conditions with the UPlanSApo 4x objective (Numerical aperature of 0.16) for a total magnification of 40X. Images were captured on an Olympus DP80 Digital camera in 8bit RGB (24 bit total) with adobe colour space. Image size (in pixels) is 4080 x 3072, with 587.5 nano-meters/pixel. Olympus cellSens Standard software (version 1.14) was used to capture images. Exposure time and white balance was performed automatically. Sensitivity was set to iso200. Each raw image is 36.75 MB in size.<br>Please note. Given how slow Figshare is for uploading and there is more than 10000 images (and I think close to a TB of total images), it will take me a while to get these up along with the assorted README files to explain everything.<br><br>
DOI: 10.6084/m9.figshare.12250250.v1
title: Drosophila melanogaster wing images genetic manipulation (UAS/GAL4) of growth regulators, and sex determination genes

description: This will be the repository for the raw images of <i>Drosophila melanogaster</i> used for the analysis of wing size, wing shape and cell (trichome) density counts from a very large study manipulating key genes in both the sex determination pathway (in particular <i>transformer</i>, <i>doublesex</i> and <i>fruitless</i>) and genes involved with tissue growth (in particular <i>Insulin Receptor</i>, <i>Target Of Rapamycin/</i>TOR and <i>dFoxo</i>) among others, using the UAS/GAL4 system in Drosophila melanogaster. While the full description will be included in the readme file. Essentially all strains were (when possible) backcrossed into a common wild type strain (Samarkand, marked with<i> white</i>). Experiments were performed at 3 temperatures (where the flies of each genotype were reared at each temperature), 18C, 24C and 28C. Control crosses (many different control crosses were done, see details) at each temperature. This experiment was done largely using the NP6333-GAL4 (also called Pen-GAL4) but a large chunk was replicated using the nubbin-GAL4 which had stronger expression in the wing and no expression (based on GFP reporter) in the legs like NP6333-GAL4 (which made it difficult to morphological determine the sex of individuals from some crosses). <br>The wings were imaged using an Olympus BX-41 microscope under brightfield conditions with the UPlanSApo 4x objective (Numerical aperature of 0.16) for a total magnification of 40X. Images were captured on an Olympus DP80 Digital camera in 8bit RGB (24 bit total) with adobe colour space. Image size (in pixels) is 4080 x 3072, with 587.5 nano-meters/pixel. Olympus cellSens Standard software (version 1.14) was used to capture images. Exposure time and white balance was performed automatically. Sensitivity was set to iso200. Each raw image is 36.75 MB in size.<br>Please note. Given how slow Figshare is for uploading and there is more than 10000 images (and I think close to a TB of total images), it will take me a while to get these up along with the assorted README files to explain everything.<br><br>
DOI: 10.6084/m9.figshare.12250271.v1
title: Modelling the Array HRD score

description: The columns contain the following information: Donor represents the sample for which the data is reported, log_HRD_score_Array is the log of the array-derived HRD score, log_HRD_score_WGS represents the log of the WGS-derived HRD score, Seg.LRR.dev is the deviation in segmented LRR data, dLRS_array is the dLRS for the array data, dLRS_WGS represents the dLRS for the WGS data, LRR.cor is the correlation between array and WGS LRR data, ACF is the cellularity of the sample, as derived from ascatNGS, Tumour_coverage is the coverage of the tumour sample, Normal_coverage is the coverage of the normal sample, fit represents the fitted array-derived HRD score, based on our model, lwr represents the lower 95% pointwise CI for the fitted array-derived HRD score, upr is the upper 95% pointwise CI for the fitted array-derived HRD score and Germline status reports the germline status of the sample.
DOI: 10.6084/m9.figshare.12250205
title: Metrics and KPIs identified in the study

description: List of metrics identified and KPIs collected during the study "Digital Supply Chain Performance Measures- A Literature Review"
DOI: 10.6084/m9.figshare.12250145
title: Data for Parks et al 2017 - Current Zoology

description: The excel file contains all of the behavioral and body size measurements for each spider, including their experimental grouping. The ab1 files contain the DNA electropherograms and the raw sequence data for each bacteria.<br>
DOI: 10.6084/m9.figshare.12250145.v1
title: Data for Parks et al 2017 - Current Zoology

description: The excel file contains all of the behavioral and body size measurements for each spider, including their experimental grouping. The ab1 files contain the DNA electropherograms and the raw sequence data for each bacteria.<br>
DOI: 10.6084/m9.figshare.12250106
title: Figure 5 - Biofilm-detached cells Viability (CFU and Cytometry).xlsx

description: RAW Data from the paper "<b>Cell death and biomass reduction in biofilms of multidrug resistant extended spectrum β-lactamase-producing uropathogenic <i>Escherichia coli</i> isolates by 1,8-cineole</b>" from Plos One.
DOI: 10.6084/m9.figshare.12250112
title: Figure 5 - Cytometry Data.zip

description: RAW Data from the paper "<b>Cell death and biomass reduction in biofilms of multidrug resistant extended spectrum β-lactamase-producing uropathogenic <i>Escherichia coli</i> isolates by 1,8-cineole</b>" from Plos One.
DOI: 10.6084/m9.figshare.12250205.v2
title: Metrics and KPIs identified in the study

description: List of metrics identified and KPIs collected during the study "Digital Supply Chain Performance Measures- A Literature Review"
DOI: 10.6084/m9.figshare.12250100
title: Figure 2 - Concentration Response and Time Course.xlsx

description: RAW Data from the paper "<b>Cell death and biomass reduction in biofilms of multidrug resistant extended spectrum β-lactamase-producing uropathogenic <i>Escherichia coli</i> isolates by 1,8-cineole</b>" from Plos One.
DOI: 10.6084/m9.figshare.12250112.v1
title: Figure 5 - Cytometry Data.zip

description: RAW Data from the paper "<b>Cell death and biomass reduction in biofilms of multidrug resistant extended spectrum β-lactamase-producing uropathogenic <i>Escherichia coli</i> isolates by 1,8-cineole</b>" from Plos One.
DOI: 10.6084/m9.figshare.12250076
title: Figure 4 - Biofilm Viability (Confocal).xlsx

description: RAW Data from the paper "<b>Cell death and biomass reduction in biofilms of multidrug resistant extended spectrum β-lactamase-producing uropathogenic <i>Escherichia coli</i> isolates by 1,8-cineole</b>" from Plos One.
DOI: 10.6084/m9.figshare.12250082
title: Table 3 - Biofilm Disruption.xlsx

description: RAW Data from the paper "<b>Cell death and biomass reduction in biofilms of multidrug resistant extended spectrum β-lactamase-producing uropathogenic <i>Escherichia coli</i> isolates by 1,8-cineole</b>" from Plos One.
DOI: 10.6084/m9.figshare.12250073
title: Figure 3 - Biofilm Viability (CFU).xlsx

description: RAW Data from the paper "<b>Cell death and biomass reduction in biofilms of multidrug resistant extended spectrum β-lactamase-producing uropathogenic <i>Escherichia coli</i> isolates by 1,8-cineole</b>" from Plos One.
DOI: 10.6084/m9.figshare.12250100.v1
title: Figure 2 - Concentration Response and Time Course.xlsx

description: RAW Data from the paper "<b>Cell death and biomass reduction in biofilms of multidrug resistant extended spectrum β-lactamase-producing uropathogenic <i>Escherichia coli</i> isolates by 1,8-cineole</b>" from Plos One.
DOI: 10.6084/m9.figshare.12250082.v1
title: Table 3 - Biofilm Disruption.xlsx

description: RAW Data from the paper "<b>Cell death and biomass reduction in biofilms of multidrug resistant extended spectrum β-lactamase-producing uropathogenic <i>Escherichia coli</i> isolates by 1,8-cineole</b>" from Plos One.
DOI: 10.6084/m9.figshare.12250082.v2
title: Table 3 - Biofilm Disruption.xlsx

description: RAW Data from the paper "<b>Cell death and biomass reduction in biofilms of multidrug resistant extended spectrum β-lactamase-producing uropathogenic <i>Escherichia coli</i> isolates by 1,8-cineole</b>" from Plos One.
DOI: 10.6084/m9.figshare.12250106.v1
title: Figure 5 - Biofilm-detached cells Viability (CFU and Cytometry).xlsx

description: RAW Data from the paper "<b>Cell death and biomass reduction in biofilms of multidrug resistant extended spectrum β-lactamase-producing uropathogenic <i>Escherichia coli</i> isolates by 1,8-cineole</b>" from Plos One.
DOI: 10.6084/m9.figshare.12250067
title: Figure 1 - Biofilm Production.xlsx

description: RAW Data from the paper "<b>Cell death and biomass reduction in biofilms of multidrug resistant extended spectrum β-lactamase-producing uropathogenic <i>Escherichia coli</i> isolates by 1,8-cineole</b>" from Plos One.
DOI: 10.6084/m9.figshare.12250034
title: US COVID-19 2020-03

description: Survey of US population in March 2020 about COVID-19.
DOI: 10.6084/m9.figshare.12250067.v1
title: Figure 1 - Biofilm Production.xlsx

description: RAW Data from the paper "<b>Cell death and biomass reduction in biofilms of multidrug resistant extended spectrum β-lactamase-producing uropathogenic <i>Escherichia coli</i> isolates by 1,8-cineole</b>" from Plos One.
DOI: 10.6084/m9.figshare.12250100.v2
title: Figure 2 - Concentration Response and Time Course.xlsx

description: RAW Data from the paper "<b>Cell death and biomass reduction in biofilms of multidrug resistant extended spectrum β-lactamase-producing uropathogenic <i>Escherichia coli</i> isolates by 1,8-cineole</b>" from Plos One.
DOI: 10.6084/m9.figshare.12250034.v1
title: US COVID-19 2020-03

description: Survey of US population in March 2020 about COVID-19.
DOI: 10.6084/m9.figshare.12249989
title: FiM Submission Datasets

description: These datasets were generated for the 2020 publication "Community Consolidation Dictates Hydroponic Root Microbiome".<br>Raw sequence data includes both Fastq files and text files of the OTU classifications for each sample.
DOI: 10.6084/m9.figshare.12249995
title: README_FIRST.txt

description: The purpose of this script is to illustrate the method developed in the article entitled <em>Minimum-area ellipse bounding an isovist: towards a 2D GIS-based efficient implementation</em> to be published in the International Journal of Geographical Information Science.
DOI: 10.6084/m9.figshare.12249989.v1
title: FiM Submission Datasets

description: These datasets were generated for the 2020 publication "Community Consolidation Dictates Hydroponic Root Microbiome".<br>Raw sequence data includes both Fastq files and text files of the OTU classifications for each sample.
DOI: 10.6084/m9.figshare.12249974
title: Raw Data

description: Raw ER data before processing has been divided by acquisition year: 2014 (Marine ER data, A1), 2015 (B transects) and 2019 (C transects and A2).
DOI: 10.6084/m9.figshare.12249965
title: Data For Paper 2

description: This is the Data that was used in the Paper
DOI: 10.6084/m9.figshare.12249974.v1
title: Raw Data

description: Raw ER data before processing has been divided by acquisition year: 2014 (Marine ER data, A1), 2015 (B transects) and 2019 (C transects and A2).
DOI: 10.6084/m9.figshare.12249995.v1
title: README_FIRST.txt

description: The purpose of this script is to illustrate the method developed in the article entitled <em>Minimum-area ellipse bounding an isovist: towards a 2D GIS-based efficient implementation</em> to be published in the International Journal of Geographical Information Science.
DOI: 10.6084/m9.figshare.12249995.v3
title: README_FIRST.txt

description: The purpose of this script is to illustrate the method developed in the article entitled <em>Minimum-area ellipse bounding an isovist: towards a 2D GIS-based efficient implementation</em> to be published in the International Journal of Geographical Information Science.
DOI: 10.6084/m9.figshare.12249950
title: GRF matlab code

description: Machine learning methods (e.g., random forest (RF)) have recently been applied in data-driven predictive modeling of mineral prospectivity.
DOI: 10.6084/m9.figshare.12249962
title: Boletín del Bibliotecario. Abril de 2020

description: Se trata de un boletín bibliotecario, emitido por la Biblioteca Universitaria de la Universidad de Ciencias Médicas de Cienfuegos. Cuba.<br>
DOI: 10.6084/m9.figshare.12249950.v1
title: GRF matlab code

description: Machine learning methods (e.g., random forest (RF)) have recently been applied in data-driven predictive modeling of mineral prospectivity.
DOI: 10.6084/m9.figshare.12249962.v1
title: Boletín del Bibliotecario. Abril de 2020

description: Se trata de un boletín bibliotecario, emitido por la Biblioteca Universitaria de la Universidad de Ciencias Médicas de Cienfuegos. Cuba.<br>
DOI: 10.6084/m9.figshare.12249995.v2
title: README_FIRST.txt

description: The purpose of this script is to illustrate the method developed in the article entitled <em>Minimum-area ellipse bounding an isovist: towards a 2D GIS-based efficient implementation</em> to be published in the International Journal of Geographical Information Science.
DOI: 10.6084/m9.figshare.12249917
title: Hemodynamical values

description: Database
DOI: 10.6084/m9.figshare.12249917.v1
title: Hemodynamical values

description: Database
DOI: 10.6084/m9.figshare.12249902
title: Foster rather than biological parental telomere length predicts offspring survival and telomere length in king penguins

description: Data set corresponding to the publication by Viblanc, Schull, Stier, Durand, Lefol, Robin, Zahn, Bize, Criscuolo (2020). Foster rather than biological parental telomere length predicts offspring survival and telomere length in king penguins
DOI: 10.6084/m9.figshare.12249902.v1
title: Foster rather than biological parental telomere length predicts offspring survival and telomere length in king penguins

description: Data set corresponding to the publication by Viblanc, Schull, Stier, Durand, Lefol, Robin, Zahn, Bize, Criscuolo (2020). Foster rather than biological parental telomere length predicts offspring survival and telomere length in king penguins
DOI: 10.6084/m9.figshare.12249887
title: Processed Data

description: The data is divided between: marine, land, and underwater ER surveys. Each dataset has a corresponding x, depth, and resistivity values. <br>The land and underwater ER datasets include conductivity, resolution index and topography values. The topography data was used to constrain the land and UW ER surveys where it was available. The underwater and land ER surveys used the resolution index as an alpha values for the plotting to take into account how well each survey can resolve the subsurface.
DOI: 10.6084/m9.figshare.12249896.v1
title: JCEM SUPPLEMENTAL DATA 06.05.2020.docx

description: High prevalence and a long delay in the diagnosis of primary aldosteronism among patients with young-onset hypertension <b></b>
DOI: 10.6084/m9.figshare.12249887.v1
title: Processed Data

description: The data is divided between: marine, land, and underwater ER surveys. Each dataset has a corresponding x, depth, and resistivity values. <br>The land and underwater ER datasets include conductivity, resolution index and topography values. The topography data was used to constrain the land and UW ER surveys where it was available. The underwater and land ER surveys used the resolution index as an alpha values for the plotting to take into account how well each survey can resolve the subsurface.