cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.9337469.v1
title: Untitled Item

description: Every replicates(individual or together) in the 3 datasets H3K4me3, H3K27me3 and H3K36me3 and dataset H3K27ac have a fixed number of cell-types in it. H3K4me3 has two replicates: 1 and 2 . H3K27 holds replicate 1 and replicates 1 and 2 together. Dataset H3K36 has only replicate 1. For combined analysis of H3K4me3 and H3K27me3 we have a folder named H3K4me3-H3K27me3(combined). In each dataset folder there are 4 subfolders named IQA, MLQA ,ML and Overlap representation. Here in the three folders named ML, MLQA and IQA we have included the results from these three cell-type tree generation methods. All the three folders contain cell-type tree in newick format. Estimated quartet files which we generated for MLQA and IQA methods, are given in both MLQA and IQA folders. Finally the overlap representation data for the cell-types are in the folder Overlap representation. In this folder we have a text file named Overlap_datarepresentaion in which the the two numbers in the first row contains the number of cell-types and data length. After that each row identified by t1,t2 etc carries the overlap data. The mapping from t1, t2 etc to original cell-types are provided in file_sequence text file.<br>
DOI: 10.6084/m9.figshare.9337448.v1
title: Cell differentiation tree

description: peak files, generated quartets, merged trees from these quartets, besttrees from RAxML for H3K4me3, H3K27me3, H3K36me3, H3K27ac.
DOI: 10.6084/m9.figshare.9340712.v5
title: Eurasian perch age information and gravel pit characteristics dataset

description: These are supplementary files for te article "Evironmental determinants of perch (<i>Perca fluviatilis</i>) and the performance of simple vs. complex ecological predictors" by Leander Höhne et al. <br>"Fish.csv" = Raw data files of operculum-radii-at-age measurements of Eurasian perch from 13 gravel pit lakes in Lower Saxony, Germany, sampled by gillnetting and electrofishing."Lakes.csv" = Values for 16 biotic and abiotic variables of the same 13 gravel pit lakes, describing their morphometry, nutrient status, habitat availability, fish community, etc."Hoehne_fish" and Hoehne_lakes" contain the same data, but with more descriptive headers to facilitate interpretation, saved as Excel-files
DOI: 10.6084/m9.figshare.9337439
title: Flat periwinkles SNPs before filtering (reference Lfab4ind)

description: Raw vcf file (zipped) containing SNPs for flat periwinkles after mapping the reads against the transcriptome reference assembled with data from four L. fabalis individuals (Lfab4ind)<br>
DOI: 10.6084/m9.figshare.9337469.v2
title: cell differentiation tree

description: Every replicates(individual or together) in the 3 datasets H3K4me3, H3K27me3 and H3K36me3 and dataset H3K27ac have a fixed number of cell-types in it. H3K4me3 has two replicates: 1 and 2 . H3K27 holds replicate 1 and replicates 1 and 2 together. Dataset H3K36 has only replicate 1. For combined analysis of H3K4me3 and H3K27me3 we have a folder named H3K4me3-H3K27me3(combined). In each dataset folder there are 4 subfolders named IQA, MLQA ,ML and Overlap representation. Here in the three folders named ML, MLQA and IQA we have included the results from these three cell-type tree generation methods. All the three folders contain cell-type tree in newick format. Estimated quartet files which we generated for MLQA and IQA methods, are given in both MLQA and IQA folders. Finally the overlap representation data for the cell-types are in the folder Overlap representation. In this folder we have a text file named Overlap_datarepresentaion in which the the two numbers in the first row contains the number of cell-types and data length. After that each row identified by t1,t2 etc carries the overlap data. The mapping from t1, t2 etc to original cell-types are provided in file_sequence text file.<br>
DOI: 10.6084/m9.figshare.9340712.v6
title: Eurasian perch growth information and gravel pit characteristics dataset

description: These are supplementary files for the article "Environmental determinants of perch (<i>Perca fluviatilis</i>) growth and the performance of simple vs. complex ecological predictors" by Leander Höhne et al. <br>"Supporting_Information_S4_Complex_Model_#20" = R script to generate results of the "best-performing complex model" to predict perch growth in gravel pits, referenced as S4 in Supporting Information of Höhne et al."Supporting_Information_S5_Simple_Model_#20" = R script to generate results of the "best-performing simple model" to predict perch growth in gravel pits, referenced as S5 in Supporting Information of Höhne et al."Fish.csv" = Raw data files of operculum-radii-at-age measurements of Eurasian perch from 13 gravel pit lakes in Lower Saxony, Germany, sampled by gillnetting and electrofishing."Lakes.csv" = Values for 16 biotic and abiotic variables of the same 13 gravel pit lakes, describing their morphometry, nutrient status, habitat availability, fish community, etc."Hoehne_fish" and Hoehne_lakes" contain the same data, but with more descriptive headers to facilitate interpretation, saved as Excel-files <br>
DOI: 10.6084/m9.figshare.12782519
title: SUpp2A.tif

description: Confocal movie of a Life-Act-eGFP expressing Tribolium embryos
DOI: 10.6084/m9.figshare.9337439.v1
title: Flat periwinkles SNPs before filtering (reference Lfab4ind)

description: Raw vcf file (zipped) containing SNPs for flat periwinkles after mapping the reads against the transcriptome reference assembled with data from four L. fabalis individuals (Lfab4ind)<br>
DOI: 10.6084/m9.figshare.12782519.v1
title: SUpp2A.tif

description: Confocal movie of a Life-Act-eGFP expressing Tribolium embryos
DOI: 10.6084/m9.figshare.9337439.v3
title: Flat periwinkles SNPs before filtering (reference Lfab4ind)

description: Raw vcf file (zipped) containing SNPs for flat periwinkles after mapping the reads against the transcriptome reference assembled with data from four L. fabalis individuals (Lfab4ind)<br>
DOI: 10.6084/m9.figshare.9337418
title: Flat periwinkles SNPs before filtering (reference oMIN)

description: Raw vcf file (zipped) containing SNPs for flat periwinkles after mapping the reads against the transcriptome reference for Littorina obtusata (oMIN)
DOI: 10.6084/m9.figshare.9337418.v1
title: Flat periwinkles SNPs before filtering (reference oMIN)

description: Raw vcf file (zipped) containing SNPs for flat periwinkles after mapping the reads against the transcriptome reference for Littorina obtusata (oMIN)
DOI: 10.6084/m9.figshare.9337439.v2
title: Flat periwinkles SNPs before filtering (reference Lfab4ind)

description: Raw vcf file (zipped) containing SNPs for flat periwinkles after mapping the reads against the transcriptome reference assembled with data from four L. fabalis individuals (Lfab4ind)<br>
DOI: 10.6084/m9.figshare.9337169
title: Flat periwinkles SNPs before filtering (reference fSAM)

description: Raw vcf file (zipped) containing SNPs for flat periwinkles after mapping the reads against the transcriptome reference for Littorina fabalis (fSAM)<br>
DOI: 10.6084/m9.figshare.9336662
title: Data Extraction Template for AYFHS

description: Data Abstraction Template used for AYFHS analysis at 2 Primary Healthcare Centers
DOI: 10.6084/m9.figshare.9336842
title: Annotation of all flat periwinkles' reference transcriptomes

description: Files (zipped) containing the annotation of all flat periwinkles' transcriptome references based on the Swiss-prot database and the L. saxatilis transcriptome, separately.
DOI: 10.6084/m9.figshare.9336359
title: Annotation of flat periwinkles pseudoreference transcriptome

description: Fasta file containing the annotation of the flat periwinkles pseudoreference transcriptome based on the Swiss-prot database and L. saxatilis transcriptome
DOI: 10.6084/m9.figshare.9336662.v1
title: Data Extraction Template for AYFHS

description: Data Abstraction Template used for AYFHS analysis at 2 Primary Healthcare Centers
DOI: 10.6084/m9.figshare.9336842.v1
title: Annotation of all flat periwinkles' reference transcriptomes

description: Files (zipped) containing the annotation of all flat periwinkles' transcriptome references based on the Swiss-prot database and the L. saxatilis transcriptome, separately.
DOI: 10.6084/m9.figshare.9336356
title: Filtered SNPs alternatively fixed between flat periwinkles' species (20)

description: Filtered SNPs (minimum coverage of 20) alternatively fixed between Littorina fabalis and L. obtusata (after mapping the reads against the pseudoreference).
DOI: 10.6084/m9.figshare.9337169.v1
title: Flat periwinkles SNPs before filtering (reference fSAM)

description: Raw vcf file (zipped) containing SNPs for flat periwinkles after mapping the reads against the transcriptome reference for Littorina fabalis (fSAM)<br>
DOI: 10.6084/m9.figshare.9336347
title: Flat periwinkles filtered biallelic SNPs (20)

description: Filtered flat periwinkles SNPs with minimum coverage of 20.
DOI: 10.6084/m9.figshare.9336350
title: Filtered SNPs alternatively fixed between flat periwinkles' species (5)

description: Filtered SNPs (minimum coverage of 5) alternatively fixed between Littorina fabalis and L. obtusata (after mapping the reads against the pseudoreference)<br><br>
DOI: 10.6084/m9.figshare.9336350.v1
title: Filtered SNPs alternatively fixed between flat periwinkles' species (5)

description: Filtered SNPs (minimum coverage of 5) alternatively fixed between Littorina fabalis and L. obtusata (after mapping the reads against the pseudoreference)<br><br>
DOI: 10.6084/m9.figshare.9336359.v2
title: Annotation of flat periwinkles pseudoreference transcriptome

description: Fasta file containing the annotation of the flat periwinkles pseudoreference transcriptome based on the Swiss-prot database and L. saxatilis transcriptome
DOI: 10.6084/m9.figshare.9336311
title: Union River Sonde Data 2017-2018

description: Data for Indivero et al 2019<br>
DOI: 10.6084/m9.figshare.9336311.v1
title: Union River Sonde Data 2017-2018

description: Data for Indivero et al 2019<br>
DOI: 10.6084/m9.figshare.9334793
title: Datasets for the Role of Financial Investors in Commodity Futures Risk Premium

description: The datasets for the Role of Financial Investors on Commodity Futures Risk Premium are weekly datasets for the period from 1995 to 2015 for three commodities in the energy market: crude oil (WTI), heating oil, and natural gas. These datasets contain futures prices for different maturities, open interest positions for each commodity (long and short open interest positions), and S&P 500 composite index. The selected commodities are traded on the New York Mercantile Exchange (NYMEX). The data comes from the Thomson Reuters Datastream and from the Commodity Futures Trading Commission (CFTC).<br>
DOI: 10.6084/m9.figshare.9335081
title: Data set for the paper "Effects of latent toxoplasmosis on mental health"

description: Data are described in the paper "<b>Effects of latent toxoplasmosis on mental health"</b><b>Abstract</b>Infection by the parasite <i>Toxoplasma</i>, which affects about 33% of world population, is associated with increased risk of several mental health disorders, especially with schizophrenia. It is unknown whether schizophrenia is associated with this infection the most strongly, or whether this association has just been the most intensively studied for historical reasons. We used the data from 6,367 subjects tested for toxoplasmosis, who took part in an internet survey, for searching in the associations of these infections with 24 mental health disorders and other indices of impaired mental health. The typical symptom associated with toxoplasmosis was anxiety, and the typical toxoplasmosis-associated disorders were autism (OR=4.78), schizophrenia (OR=3.34), attention deficit hyperactivity disorder (OR=2.50), obsessive compulsive disorder (OR=1.86), antisocial personality disorder (OR=1.63), learning disabilities (OR=1.59), and anxiety disorder (OR=1.48). Based on our data we can conclude that Toxoplasmosis probably plays a substantial role in the etiopathogenesis of mental health disorders and its association with schizophrenia is the second strongest association, after autism.<b></b>
DOI: 10.6084/m9.figshare.9335069
title: Diversity and distributional patterns of aroids (Alismatales: Araceae) along an elevational gradient in Darién, Panama

description: The family Araceae (aroids) represents an ecologically important and diverse group of plants in Panama, represented by 25 genera, 615 species, of which 277 (45%) are considered endemic. The aim of this study is to analyse the diversity and distributional patterns of aroids along an elevation gradient in the species-rich forests of Darién, Panama. We confined our study to three study sites, selected across gradients of elevation (ranges): 100–300 , 500–700 and 1100–1300 m. We recorded 3187 specimens, of which 397 were terrestrials, 637 epiphytes and 2153 nomadic vines, distributed in 10 genera and 61 species. Our study shows that the most diverse areas were those between 500 and 700 m and the highest abundance were measured at 1100–1300 m. The epiphytic aroids displayed greater species richness and abundance at 1100–1300 m; the nomadic vines had greater richness between 500 and 700 m and greater abundance from 100 to 300 m. Similarly, terrestrial aroids showed greater richness at 500–700 m, and exhibited abundance values similar to that of the epiphytes. We measured a high degree of aroid species turnover along the elevation gradient and some genera and species (many being endemic) appeared strongly associated with sites at specific elevations.
DOI: 10.6084/m9.figshare.9334241
title: PHENOTYPIC INTEGRATION OF TURNERA VELUTINA LEAVES

description: Dataset of foliar traits used to estimate phenotypic integration of 13 maternal families in reproductive Turnera velutina plants under a natural setting in the coastal dune of Centro de Investigaciones Costeras La Mancha CICOLMA, Veracruz, Mexico. The data includes fitness estimators for growth, flower and seed production at individual and family level.
DOI: 10.6084/m9.figshare.9333317
title: Tables S1 - S8 from A multifactor coupling prediction model for the failure depth of floor rocks in fully mechanized caving mining: a numerical and <i>in situ</i> study

description: To study the mining-induced failure depth of floor rocks in a fully mechanized mining caving field affected by different coal seam pitches, mining face lengths, burial depths and aquifer water pressures, multifactor-coupled orthogonal numerical tests on the failure depth of floor rocks were conducted. The numerical results show that the failure depth of floor rocks increases with increasing mining face length, coal seam pitch and burial depth. According to the relationship between failure depth and these impact factors, a multifactor-coupled prediction model for the failure depth of floor rocks was established. In addition, the <i>in situ</i> measurement of the failure depth of floor rocks in the Yitang Coal Mine in Huoxi coal field in Shanxi Province, China, was performed, and the <i>in situ</i> failure depths of floor rocks in the 100 502 (80 m) and 100 502 (180 m) mining faces were approximately 12.50–14.65 m and 17.50–19.20 m, in good agreement with the results of the multifactor prediction model. Furthermore, the sensitivity of each impact factor in the prediction model of the floor failure depth was further analysed by <i>F</i>-test and range analysis, and the impact order of studied factors on the floor failure depth is coal seam pitch &gt; mining face length &gt; burial depth &gt; aquifer water pressure.
DOI: 10.6084/m9.figshare.9333317.v1
title: Tables S1 - S8 from A multifactor coupling prediction model for the failure depth of floor rocks in fully mechanized caving mining: a numerical and <i>in situ</i> study

description: To study the mining-induced failure depth of floor rocks in a fully mechanized mining caving field affected by different coal seam pitches, mining face lengths, burial depths and aquifer water pressures, multifactor-coupled orthogonal numerical tests on the failure depth of floor rocks were conducted. The numerical results show that the failure depth of floor rocks increases with increasing mining face length, coal seam pitch and burial depth. According to the relationship between failure depth and these impact factors, a multifactor-coupled prediction model for the failure depth of floor rocks was established. In addition, the <i>in situ</i> measurement of the failure depth of floor rocks in the Yitang Coal Mine in Huoxi coal field in Shanxi Province, China, was performed, and the <i>in situ</i> failure depths of floor rocks in the 100 502 (80 m) and 100 502 (180 m) mining faces were approximately 12.50–14.65 m and 17.50–19.20 m, in good agreement with the results of the multifactor prediction model. Furthermore, the sensitivity of each impact factor in the prediction model of the floor failure depth was further analysed by <i>F</i>-test and range analysis, and the impact order of studied factors on the floor failure depth is coal seam pitch &gt; mining face length &gt; burial depth &gt; aquifer water pressure.
DOI: 10.6084/m9.figshare.9333314
title: Figures S1 - S4 from A multifactor coupling prediction model for the failure depth of floor rocks in fully mechanized caving mining: a numerical and <i>in situ</i> study

description: To study the mining-induced failure depth of floor rocks in a fully mechanized mining caving field affected by different coal seam pitches, mining face lengths, burial depths and aquifer water pressures, multifactor-coupled orthogonal numerical tests on the failure depth of floor rocks were conducted. The numerical results show that the failure depth of floor rocks increases with increasing mining face length, coal seam pitch and burial depth. According to the relationship between failure depth and these impact factors, a multifactor-coupled prediction model for the failure depth of floor rocks was established. In addition, the <i>in situ</i> measurement of the failure depth of floor rocks in the Yitang Coal Mine in Huoxi coal field in Shanxi Province, China, was performed, and the <i>in situ</i> failure depths of floor rocks in the 100 502 (80 m) and 100 502 (180 m) mining faces were approximately 12.50–14.65 m and 17.50–19.20 m, in good agreement with the results of the multifactor prediction model. Furthermore, the sensitivity of each impact factor in the prediction model of the floor failure depth was further analysed by <i>F</i>-test and range analysis, and the impact order of studied factors on the floor failure depth is coal seam pitch &gt; mining face length &gt; burial depth &gt; aquifer water pressure.
DOI: 10.17028/rd.lboro.9333158
title: Pathways of antibiotic use in humans and animals in Bangladesh: Interview Guides

description: These guides are those used by interviewers who conducted interviews around antibiotic use in humans and animals in Bangladesh. Interviews examined antibiotic use and behaviours contributing to antibiotic resistance from the perspective of household members and healthcare providers in one urban and one rural site in Bangladesh. Household interviews were carried out with the household decision-maker or main care-giver (total 48 interviews). Healthcare provider interviews were carried out with a range of qualified and unqualified providers from human and veterinary medicine (total 46 interviews). The interviews gathered information on where people sought treatment for illnesses due to infection, what determined their choice of healthcare provider; factors contributing to antibiotic use in humans and animals; knowledge and understanding of antibiotic resistance. Similar questions about antibiotic prescribing and selling practices were asked of healthcare providers.<br>The associated transcripts are available upon request to the PI at https://doi.org/10.17028/rd.lboro.8953118.v1<br>Further information on the study as well as details on methods and analysis are available under a CC-BY licence at https://doi.org/10.1136/bmjopen-2018-028215 or https://dspace.lboro.ac.uk/2134/36467<br>
DOI: 10.17028/rd.lboro.9333158.v1
title: Pathways of antibiotic use in humans and animals in Bangladesh: Interview Guides

description: These guides are those used by interviewers who conducted interviews around antibiotic use in humans and animals in Bangladesh. Interviews examined antibiotic use and behaviours contributing to antibiotic resistance from the perspective of household members and healthcare providers in one urban and one rural site in Bangladesh. Household interviews were carried out with the household decision-maker or main care-giver (total 48 interviews). Healthcare provider interviews were carried out with a range of qualified and unqualified providers from human and veterinary medicine (total 46 interviews). The interviews gathered information on where people sought treatment for illnesses due to infection, what determined their choice of healthcare provider; factors contributing to antibiotic use in humans and animals; knowledge and understanding of antibiotic resistance. Similar questions about antibiotic prescribing and selling practices were asked of healthcare providers.<br>The associated transcripts are available upon request to the PI at https://doi.org/10.17028/rd.lboro.8953118.v1<br>Further information on the study as well as details on methods and analysis are available under a CC-BY licence at https://doi.org/10.1136/bmjopen-2018-028215 or https://dspace.lboro.ac.uk/2134/36467<br>
DOI: 10.6084/m9.figshare.9333314.v1
title: Figures S1 - S4 from A multifactor coupling prediction model for the failure depth of floor rocks in fully mechanized caving mining: a numerical and <i>in situ</i> study

description: To study the mining-induced failure depth of floor rocks in a fully mechanized mining caving field affected by different coal seam pitches, mining face lengths, burial depths and aquifer water pressures, multifactor-coupled orthogonal numerical tests on the failure depth of floor rocks were conducted. The numerical results show that the failure depth of floor rocks increases with increasing mining face length, coal seam pitch and burial depth. According to the relationship between failure depth and these impact factors, a multifactor-coupled prediction model for the failure depth of floor rocks was established. In addition, the <i>in situ</i> measurement of the failure depth of floor rocks in the Yitang Coal Mine in Huoxi coal field in Shanxi Province, China, was performed, and the <i>in situ</i> failure depths of floor rocks in the 100 502 (80 m) and 100 502 (180 m) mining faces were approximately 12.50–14.65 m and 17.50–19.20 m, in good agreement with the results of the multifactor prediction model. Furthermore, the sensitivity of each impact factor in the prediction model of the floor failure depth was further analysed by <i>F</i>-test and range analysis, and the impact order of studied factors on the floor failure depth is coal seam pitch &gt; mining face length &gt; burial depth &gt; aquifer water pressure.