cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.8183467
title: The evaluation of ActivityNet-EKG* knowledge graph

description: Evaluation of ActivityNet-EKG* knowledge graph for 286 multimodal documents.
DOI: 10.5281/zenodo.8183466
title: The evaluation of ActivityNet-EKG* knowledge graph

description: Evaluation of ActivityNet-EKG* knowledge graph for 286 multimodal documents.
DOI: 10.6084/m9.figshare.23549925
title: Data and R code for "Functional traits explain waterbirds’ host status, subtype richness, and community-level infection risk for avian influenza"

description: Species functional traits can influence several processes of pathogen transmission and, consequently, affect species’ host status, pathogen diversity, and community-level infection risk. In this study, we investigated, for 143 European waterbird species, the effects of functional traits on host status and pathogen diversity (subtype richness) for the avian influenza virus at the species level. We also explored the association between functional diversity and HPAI H5Nx occurrence at the community level for the 2016/17 and 2021/22 epidemics. This dataset contains datasets and R code files to replicate our analysis and results. Supplementary Dataset 1 is the data to replicate our analysis for host status and pathogen diversity (subtype richness) at the species level. Supplementary Dataset 2 is the data to replicate the analysis for the association between functional diversity and HPAI H5Nx occurrence at the community level. Supplementary Datasets 3 and 4 are the description data for Figure 1B and Figure 3 in the manuscript. Supplementary Codes 1 to 5 contain the R code to reproduce the analysis and figures. Supplementary phylogenetic birdtree contains the Hackett backbone phylogenetic tree of avian species.
DOI: 10.6084/m9.figshare.23549925.v1
title: Data and R code for "Functional traits explain waterbirds’ host status, subtype richness, and community-level infection risk for avian influenza"

description: Species functional traits can influence several processes of pathogen transmission and, consequently, affect species’ host status, pathogen diversity, and community-level infection risk. In this study, we investigated, for 143 European waterbird species, the effects of functional traits on host status and pathogen diversity (subtype richness) for the avian influenza virus at the species level. We also explored the association between functional diversity and HPAI H5Nx occurrence at the community level for the 2016/17 and 2021/22 epidemics. This dataset contains datasets and R code files to replicate our analysis and results. Supplementary Dataset 1 is the data to replicate our analysis for host status and pathogen diversity (subtype richness) at the species level. Supplementary Dataset 2 is the data to replicate the analysis for the association between functional diversity and HPAI H5Nx occurrence at the community level. Supplementary Datasets 3 and 4 are the description data for Figure 1B and Figure 3 in the manuscript. Supplementary Codes 1 to 5 contain the R code to reproduce the analysis and figures. Supplementary phylogenetic birdtree contains the Hackett backbone phylogenetic tree of avian species.
DOI: 10.17028/rd.lboro.23668782
title: Supplementary information files for An iron ore-based catalyst for producing hydrogen and metallurgical carbon via catalytic methane pyrolysis for decarbonisation of the steel industry

description: Supplementary files for article An iron ore-based catalyst for producing hydrogen and metallurgical carbon via catalytic methane pyrolysis for decarbonisation of the steel industry Experiments to investigate the catalytic pyrolysis of methane using an iron ore-based catalyst were carried out to optimize catalytic activity and examine the purity of the carbon produced from the process for the first time. Ball milling of the iron ore at 300 rpm for varying times – from 30 to 330 minutes – was studied to determine the effect of milling time on methane conversion. Optimal milling for 270 minutes led to a five-fold increase in methane conversion from ca. 1% to 5%. Further grinding resulted in a decline of methane conversion to 4% shown by SEM to correspond to an increase in particle size caused by agglomeration. Data from Raman and Mössbauer spectroscopy and H2 temperature programmed reduction indicated a change in phase from magnetite to maghemite and hematite (at the particle surface) as the grinding time increased. Analysis of the carbon produced as a byproduct of the reaction indicated a highly pure material with the potential to be used as an additive for steel production.
DOI: 10.17028/rd.lboro.23668782.v1
title: Supplementary information files for An iron ore-based catalyst for producing hydrogen and metallurgical carbon via catalytic methane pyrolysis for decarbonisation of the steel industry

description: Supplementary files for article An iron ore-based catalyst for producing hydrogen and metallurgical carbon via catalytic methane pyrolysis for decarbonisation of the steel industry Experiments to investigate the catalytic pyrolysis of methane using an iron ore-based catalyst were carried out to optimize catalytic activity and examine the purity of the carbon produced from the process for the first time. Ball milling of the iron ore at 300 rpm for varying times – from 30 to 330 minutes – was studied to determine the effect of milling time on methane conversion. Optimal milling for 270 minutes led to a five-fold increase in methane conversion from ca. 1% to 5%. Further grinding resulted in a decline of methane conversion to 4% shown by SEM to correspond to an increase in particle size caused by agglomeration. Data from Raman and Mössbauer spectroscopy and H2 temperature programmed reduction indicated a change in phase from magnetite to maghemite and hematite (at the particle surface) as the grinding time increased. Analysis of the carbon produced as a byproduct of the reaction indicated a highly pure material with the potential to be used as an additive for steel production.
DOI: 10.17631/rd-2023-0012-ddat
title: Making votes-at-16 work in Wales

description: The 2021 Welsh Parliament elections were the first in which 16- and 17-year-olds in Wales were allowed to vote. This presented a unique opportunity to extend the evidence base on experiences and outcomes of the lowering of the voting age from 18 to 16 years. The ‘Making Votes at 16 work in Wales’-project analysed how young people aged 16 and 17 experienced their inclusion in the franchise and the first election in which they were allowed to vote in Wales, with the aim of identifying which support young people aged 16 and 17 need to turn out to vote and what works to mobilise and enhance turnout levels among young people.<br>
A detailed overview of the data is attached. The data include 22 transcripts from focus group discussions with 86 young people from all over Wales, some of whom participated in two focus group discussions - one before and one after the election. The second subset of data are 3 files consisting of non-representative pre- and post-election survey data from focus group participants and further young people in Wales, 111 participants in total. Focus group participants joined 60- to 120-minute-long facilitated focus group discussions, conducted virtually, with young people participating via video call and online chat, between April and August 2021, in which they discussed their experience of the election and election campaign as well as their interest in and views of political issues, including of the lowering of the voting age, their attitudes to Welsh politics and governance. A few young people additionally kept election diaries, reacting to prompts from the research team in the leadup to the election and sharing an in-the-moment insight into their election experience; these data consist of 11 files.<br>
The research was funded by the UK Democracy Fund, a Joseph Rowntree Reform Trust Ltd initiative.
DOI: 10.5066/p9ch2zwd
title: Geochemistry of fine sediment from San Francisco Bay shoals (2012) and tributaries (2010, 2012, 2013)

description: Elemental chemistry and weight percent of the less than 0.063 mm fine sediment fraction are reported for surface sediments from shoals, the ebb tide delta, local tributaries, and inland rivers that carry sediment to San Francisco Bay, California.
DOI: 10.14473/csda/1hnh1i/hr3njk
title: TI_V1811en.pdf

description: Technical information
DOI: 10.14473/csda/1hnh1i/wccvr5
title: D_V1811en.pdf

description: Questionnaire
DOI: 10.14473/csda/1hnh1i/zp5sp5
title: NS_1811_DataFile-FINAL_ENG.tab

description: Data
DOI: 10.14473/csda/1hnh1i
title: Our Society 2018 - November

description: Research was conducted by the Public Opinion Research Center (CVVM) of the Institute of Sociology of the Czech Academy of Sciences as a part of the research "Our Society 2018 - November". Data collection was secured by the interviewer network of CVVM. Please note that this research is an English version / translation of materials from research "Naše společnost listopad 2018"
DOI: 10.14473/csda/1hnh1i/ybhlbi
title: K_V1811en.pdf

description: :unav
DOI: 10.5281/zenodo.7193997
title: Energies and descriptors of two-polaron configurations in Li4Ti5O12

description: This dataset contains structures, distance descriptors and relative energies of two-polaron configurations in a defected 2×2×1 supercell of Li<sub>4</sub>Ti<sub>5</sub>O<sub>12</sub>. Structures are given in ASE-readable xyz files in the archive lto_bulk_polaron_structures.tar.gz. Distance descriptors and energies are contained in a csv (tab separated) Training+Test-data.dat. Data is thereby separated into Training and test data. Energies in part computed from the given structures and in part extracted from J. Phys. Chem. Lett. 11, 2535 (2020).
description: Funded by: German Research Foundation (DFG): Grant Nos. OB 425/9-1, KI 2558/1-1
DOI: 10.5281/zenodo.7193998
title: Energies and descriptors of two-polaron configurations in Li4Ti5O12

description: This dataset contains structures, distance descriptors and relative energies of two-polaron configurations in a defected 2×2×1 supercell of Li<sub>4</sub>Ti<sub>5</sub>O<sub>12</sub>. Structures are given in ASE-readable xyz files in the archive lto_bulk_polaron_structures.tar.gz. Distance descriptors and energies are contained in a csv (tab separated) Training+Test-data.dat. Data is thereby separated into Training and test data. Energies in part computed from the given structures and in part extracted from J. Phys. Chem. Lett. 11, 2535 (2020).
description: Funded by: German Research Foundation (DFG): Grant Nos. OB 425/9-1, KI 2558/1-1
DOI: 10.6084/m9.figshare.10027952.v1
title: MOESM5 of A genomic analysis and transcriptomic atlas of gene expression in Psoroptes ovis reveals feeding- and stage-specific patterns of allergen expression

description: Additional file 5. Annotated lists of differentially expressed genes identified from each of the pairwise life-cycle stage comparisons.
DOI: 10.6084/m9.figshare.10027937
title: MOESM2 of A genomic analysis and transcriptomic atlas of gene expression in Psoroptes ovis reveals feeding- and stage-specific patterns of allergen expression

description: Additional file 2. Gene lists for each life cycle expression cluster.
DOI: 10.5281/zenodo.4001759
title: seb369/hemp_microbiome: First release of hemp microbiome project data

description: This is the first public release of the hemp microbiome project data for archiving on Zenodo.
DOI: 10.6084/m9.figshare.10027937.v1
title: MOESM2 of A genomic analysis and transcriptomic atlas of gene expression in Psoroptes ovis reveals feeding- and stage-specific patterns of allergen expression

description: Additional file 2. Gene lists for each life cycle expression cluster.
DOI: 10.6084/m9.figshare.10027898
title: MOESM1 of Physiological phenotyping of mammalian cell lines by enzymatic activity fingerprinting of key carbohydrate metabolic enzymes: a pilot and feasibility study

description: Additional file 1. Enzyme activity assay excel template: excel file for enzyme activity assay setup support. The file contains a blank layout sheet for test sample and control sample distribution on a 96-well plate. Additional sheets contain master mix volume calculations for activity assays for Aldolase, Glucose-6-phosphate Dehydrogenase, Hexokinase, Phosphofructokinase, Phosphoglucose isomerase, and Phosphoglucosemutase. Adjustment of the desired number of control and test samples (grey fields) results in recalculation of required volumes. All sheets are printable on A4 paper and can be filled out digitally or manually. https://doi.org/10.6084/m9.figshare.7859801 .
DOI: 10.6084/m9.figshare.10027898.v1
title: MOESM1 of Physiological phenotyping of mammalian cell lines by enzymatic activity fingerprinting of key carbohydrate metabolic enzymes: a pilot and feasibility study

description: Additional file 1. Enzyme activity assay excel template: excel file for enzyme activity assay setup support. The file contains a blank layout sheet for test sample and control sample distribution on a 96-well plate. Additional sheets contain master mix volume calculations for activity assays for Aldolase, Glucose-6-phosphate Dehydrogenase, Hexokinase, Phosphofructokinase, Phosphoglucose isomerase, and Phosphoglucosemutase. Adjustment of the desired number of control and test samples (grey fields) results in recalculation of required volumes. All sheets are printable on A4 paper and can be filled out digitally or manually. https://doi.org/10.6084/m9.figshare.7859801 .
DOI: 10.6084/m9.figshare.10027865
title: MOESM8 of A yeast phenomic model for the influence of Warburg metabolism on genetic buffering of doxorubicin

description: Additional file 8. Quantitative summaries of REMc clusters. File A depicts REMc results, in terms of cluster distributions of L and K interaction (â shiftâ is not used for REMc and thus is not displayed), as a way to visualize cluster differences quantitatively. File B is organized by first round clusters and plots the change in p-value for significant terms with respect to round of clustering. Clusters derived from one another and sharing enrichment of the same GO term are connected by a line. Only GO terms with a background size of 500 or smaller are included. Scroll over a symbol to see embedded detail about each GO term. The square root of the p-value is used on the y-axis to evenly distribute data.
DOI: 10.6084/m9.figshare.10027871
title: MOESM9 of A yeast phenomic model for the influence of Warburg metabolism on genetic buffering of doxorubicin

description: Additional file 9. GO term-specific heatmaps for REMc/GTF-enriched clusters. GO term-specific heatmaps for significant GO process terms were generated as described in methods and Figs. 3 and 4. Any related child terms are presented in subsequent pages of the parent file name. GO terms with more than 100 children, with 2 or fewer genes annotated to the term, or a file size over 300KB are not shown. All heatmaps are generated with the same layout (see Figs. 3 and 4).
DOI: 10.6084/m9.figshare.10027871.v1
title: MOESM9 of A yeast phenomic model for the influence of Warburg metabolism on genetic buffering of doxorubicin

description: Additional file 9. GO term-specific heatmaps for REMc/GTF-enriched clusters. GO term-specific heatmaps for significant GO process terms were generated as described in methods and Figs. 3 and 4. Any related child terms are presented in subsequent pages of the parent file name. GO terms with more than 100 children, with 2 or fewer genes annotated to the term, or a file size over 300KB are not shown. All heatmaps are generated with the same layout (see Figs. 3 and 4).
DOI: 10.6084/m9.figshare.10027865.v1
title: MOESM8 of A yeast phenomic model for the influence of Warburg metabolism on genetic buffering of doxorubicin

description: Additional file 8. Quantitative summaries of REMc clusters. File A depicts REMc results, in terms of cluster distributions of L and K interaction (â shiftâ is not used for REMc and thus is not displayed), as a way to visualize cluster differences quantitatively. File B is organized by first round clusters and plots the change in p-value for significant terms with respect to round of clustering. Clusters derived from one another and sharing enrichment of the same GO term are connected by a line. Only GO terms with a background size of 500 or smaller are included. Scroll over a symbol to see embedded detail about each GO term. The square root of the p-value is used on the y-axis to evenly distribute data.
DOI: 10.6084/m9.figshare.10027850
title: MOESM6 of A yeast phenomic model for the influence of Warburg metabolism on genetic buffering of doxorubicin

description: Additional file 6. Gene Ontology Term Averaging (GTA) results and interactive plots. File A contains all GTA values, cross-referenced with REMc-enriched terms. File B displays GTA values associated with above-threshold GTA scores (see note below) plotted for HLD vs. HLEG. GTA values for REMc-enriched terms are also included (regardless of whether |GTA score| &gt;2). File C displays a subset of File B, containing only GO Terms with above-threshold GTA scores and that were enriched by REMc/GTF. File D reports GTA value using the K parameter. Files B-D should be opened in an Internet web browser so that embedded information from File A can be viewed by scrolling over points on the graphs. Subsets in each of the plots can be toggled off and on by clicking on the respective legend label. In the embedded information, X1 represents HLEG and X2 represents HLD information. Note: The GTA score threshold (for L) indicates that GTA-gtaSD &gt; 2 for enhancers or GTA+gtaSD &lt; -2 for suppressors, in at least one media.
DOI: 10.6084/m9.figshare.10027859
title: MOESM7 of A yeast phenomic model for the influence of Warburg metabolism on genetic buffering of doxorubicin

description: Additional file 7. Systematic comparisons involving genome-wide studies of doxorubicin-gene interaction. Table S9. Genes with deletion-enhancing doxorubicin-gene interaction from Xia et al. 2007 and Westmoreland et al. 2009. Table S10. Summary of experimental details associated with Table S9. Table S11. Test of enrichment for doxorubicin-gene interaction among genes encoding proteins predicted as substrates of the NatC complex. Table S12. Test of enrichment for doxorubicin-gene interaction among genes predicted to be regulated by conserved uORFs (Cvijovic et al. 2007).
DOI: 10.6084/m9.figshare.10027850.v1
title: MOESM6 of A yeast phenomic model for the influence of Warburg metabolism on genetic buffering of doxorubicin

description: Additional file 6. Gene Ontology Term Averaging (GTA) results and interactive plots. File A contains all GTA values, cross-referenced with REMc-enriched terms. File B displays GTA values associated with above-threshold GTA scores (see note below) plotted for HLD vs. HLEG. GTA values for REMc-enriched terms are also included (regardless of whether |GTA score| &gt;2). File C displays a subset of File B, containing only GO Terms with above-threshold GTA scores and that were enriched by REMc/GTF. File D reports GTA value using the K parameter. Files B-D should be opened in an Internet web browser so that embedded information from File A can be viewed by scrolling over points on the graphs. Subsets in each of the plots can be toggled off and on by clicking on the respective legend label. In the embedded information, X1 represents HLEG and X2 represents HLD information. Note: The GTA score threshold (for L) indicates that GTA-gtaSD &gt; 2 for enhancers or GTA+gtaSD &lt; -2 for suppressors, in at least one media.
DOI: 10.6084/m9.figshare.10027859.v1
title: MOESM7 of A yeast phenomic model for the influence of Warburg metabolism on genetic buffering of doxorubicin

description: Additional file 7. Systematic comparisons involving genome-wide studies of doxorubicin-gene interaction. Table S9. Genes with deletion-enhancing doxorubicin-gene interaction from Xia et al. 2007 and Westmoreland et al. 2009. Table S10. Summary of experimental details associated with Table S9. Table S11. Test of enrichment for doxorubicin-gene interaction among genes encoding proteins predicted as substrates of the NatC complex. Table S12. Test of enrichment for doxorubicin-gene interaction among genes predicted to be regulated by conserved uORFs (Cvijovic et al. 2007).
DOI: 10.6084/m9.figshare.10027832
title: MOESM3 of A yeast phenomic model for the influence of Warburg metabolism on genetic buffering of doxorubicin

description: Additional file 3. Interaction plots for HLEG. (A, B) Genome-wide and (C, D) validation analyses for (A, C) YKO/KD and (B, D) reference strains in HLEG. See also methods and Additional file 2.
DOI: 10.6084/m9.figshare.10027844
title: MOESM5 of A yeast phenomic model for the influence of Warburg metabolism on genetic buffering of doxorubicin

description: Additional file 5. REMc results with doxorubicin-gene interaction profile heatmaps and Gene Ontology enrichment (GO Term Finder; GTF) results. File A contains REMc results and associated gene interaction and shift data. File B is the heatmap representation of each REMc cluster after incorporating shift values and hierarchical clustering. File C contains the GTF results obtained for REMc clusters for the three ontologies â process, function, and component.
DOI: 10.6084/m9.figshare.10027838
title: MOESM4 of A yeast phenomic model for the influence of Warburg metabolism on genetic buffering of doxorubicin

description: Additional file 4. Interaction plots for HLD. (A, B) Genome-wide and (C, D) validation analyses. (A, C) YKO/KD and (B, D) reference strains in HLD media. See also methods and Additional file 2.
DOI: 10.6084/m9.figshare.10027832.v1
title: MOESM3 of A yeast phenomic model for the influence of Warburg metabolism on genetic buffering of doxorubicin

description: Additional file 3. Interaction plots for HLEG. (A, B) Genome-wide and (C, D) validation analyses for (A, C) YKO/KD and (B, D) reference strains in HLEG. See also methods and Additional file 2.
DOI: 10.6084/m9.figshare.10027844.v1
title: MOESM5 of A yeast phenomic model for the influence of Warburg metabolism on genetic buffering of doxorubicin

description: Additional file 5. REMc results with doxorubicin-gene interaction profile heatmaps and Gene Ontology enrichment (GO Term Finder; GTF) results. File A contains REMc results and associated gene interaction and shift data. File B is the heatmap representation of each REMc cluster after incorporating shift values and hierarchical clustering. File C contains the GTF results obtained for REMc clusters for the three ontologies â process, function, and component.
DOI: 10.6084/m9.figshare.10027829
title: MOESM2 of A yeast phenomic model for the influence of Warburg metabolism on genetic buffering of doxorubicin

description: Additional file 2. Doxorubicin-gene interaction data; Tables S1-S8. Tables S1-S4 are the genome-wide experiment: Table S1. YKO/KD strains in HLEG. Table S2. Reference cultures in HLEG. Table S3. YKO/KD strains in HLD. Table S4. Reference cultures in HLD. Tables S5-S8 are the validation study: Table S5. YKO/KD strains in HLEG. Table S6. Reference cultures in HLEG. Table S7. YKO/KD strains in HLD. Table S8. Reference cultures in HLD.
DOI: 10.6084/m9.figshare.10027838.v1
title: MOESM4 of A yeast phenomic model for the influence of Warburg metabolism on genetic buffering of doxorubicin

description: Additional file 4. Interaction plots for HLD. (A, B) Genome-wide and (C, D) validation analyses. (A, C) YKO/KD and (B, D) reference strains in HLD media. See also methods and Additional file 2.
DOI: 10.6084/m9.figshare.10027820
title: MOESM12 of A yeast phenomic model for the influence of Warburg metabolism on genetic buffering of doxorubicin

description: Additional file 12. Comparisons between yeast studies of doxorubicin in the context of integrating cancer pharmacogenomics data. Overlapping and unique sets of genes reported from the different studies of doxorubicin, using the YKO/KD libraries, are assessed with regard to correlation with cancer pharmacogenomics data.