cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.12480317
title: Supplementary Material for: HIF1α Deficiency in Dendritic Cells Attenuates Symptoms and Inflammatory Indicators of Allergic Rhinitis in a SIRT1-Dependent Manner

description: <b><i>Background:</i></b> Allergic rhinitis is the most prevalent atopic disorder worldwide. Inflammation is believed to participate in allergic rhinitis. Previous studies indicate that hypoxia-inducible factor (HIF) promotes the development of allergic rhinitis, and dendritic cells are also involved in allergic rhinitis. <b><i>Methods:</i></b>We explored the consequences of HIF1α deficiency in dendritic cells on allergic rhinitis. Allergic rhinitis in mice was induced by ovalbumin (OVA). The levels of IgE, leukotriene C4 (LTC4), eosinophil cationic protein (ECP), prostaglandin D2 (PGD2), IFN-γ, IL-2, IL-4, IL-5, IL-10, and IL-13 in serum or nasal lavage fluid (NLF) were detected by ELISA. Inflammatory cells in NLF were counted by hemocytometer. The protein levels of p-ERK1/2, p-p38, p-JNK2, SIRT1, p-IκBα, and p65 were determined by Western blot. <b><i>Results:</i></b>HIF1α deficiency in dendritic cells (HIF1α<sup>CD11c–/–</sup>) decreased sneezing and nasal rubbing, the production of OVA-specific IgE, LTC4, and ECP in serum and NLF, and the numbers of leukocytes, eosinophils, lymphocytes, and neutrophils in NLF. Th1 cytokines increased, while Th2 cytokines decreased in HIF1a<sup>CD11c–/–</sup> mice. SIRT1/NF-κB signaling was inhibited in HIF1α<sup>CD11c–/–</sup> mice, while SIRT1 inhibitor administration in HIF1α<sup>CD11c–/–</sup> mice attenuated the symptoms and inflammatory indicators of allergic rhinitis. <b><i>Conclusion:</i></b>HIF1α deficiency in dendritic cells attenuates symptoms and inflammatory indicators of allergic rhinitis in a SIRT1-dependent manner.
DOI: 10.6084/m9.figshare.12480314
title: ExperimentalData (Matsumoto et al., fNIRS study)

description: Searching_Cost(trial,condition[Tactile/Visual],participant)<br>OxyZ_Profile,DeoxyZ_Profile(frame,ch,session[1-2/7-8],participant)
DOI: 10.6084/m9.figshare.12480314.v1
title: ExperimentalData (Matsumoto et al., fNIRS study)

description: Searching_Cost(trial,condition[Tactile/Visual],participant)<br>OxyZ_Profile,DeoxyZ_Profile(frame,ch,session[1-2/7-8],participant)
DOI: 10.6084/m9.figshare.12480317.v1
title: Supplementary Material for: HIF1α Deficiency in Dendritic Cells Attenuates Symptoms and Inflammatory Indicators of Allergic Rhinitis in a SIRT1-Dependent Manner

description: <b><i>Background:</i></b> Allergic rhinitis is the most prevalent atopic disorder worldwide. Inflammation is believed to participate in allergic rhinitis. Previous studies indicate that hypoxia-inducible factor (HIF) promotes the development of allergic rhinitis, and dendritic cells are also involved in allergic rhinitis. <b><i>Methods:</i></b>We explored the consequences of HIF1α deficiency in dendritic cells on allergic rhinitis. Allergic rhinitis in mice was induced by ovalbumin (OVA). The levels of IgE, leukotriene C4 (LTC4), eosinophil cationic protein (ECP), prostaglandin D2 (PGD2), IFN-γ, IL-2, IL-4, IL-5, IL-10, and IL-13 in serum or nasal lavage fluid (NLF) were detected by ELISA. Inflammatory cells in NLF were counted by hemocytometer. The protein levels of p-ERK1/2, p-p38, p-JNK2, SIRT1, p-IκBα, and p65 were determined by Western blot. <b><i>Results:</i></b>HIF1α deficiency in dendritic cells (HIF1α<sup>CD11c–/–</sup>) decreased sneezing and nasal rubbing, the production of OVA-specific IgE, LTC4, and ECP in serum and NLF, and the numbers of leukocytes, eosinophils, lymphocytes, and neutrophils in NLF. Th1 cytokines increased, while Th2 cytokines decreased in HIF1a<sup>CD11c–/–</sup> mice. SIRT1/NF-κB signaling was inhibited in HIF1α<sup>CD11c–/–</sup> mice, while SIRT1 inhibitor administration in HIF1α<sup>CD11c–/–</sup> mice attenuated the symptoms and inflammatory indicators of allergic rhinitis. <b><i>Conclusion:</i></b>HIF1α deficiency in dendritic cells attenuates symptoms and inflammatory indicators of allergic rhinitis in a SIRT1-dependent manner.
DOI: 10.6084/m9.figshare.12480344.v1
title: Chen F et al 2020 QSR-Holocene Tibetan Plateau review-Data

description: Data of a review of Holocene climate change, vegetation history, and landscape responses on the Tibetan Plateau. Stacks of climate change, glacier activity, eolian activity and vegetation change, and pollen-based temperature and precipitation reconstructions for some specific lakes are included. Original reference:
DOI: 10.6084/m9.figshare.12480149
title: Data availability

description: Litter traits and decomposition rate of 205 tree species in a subtropical forest
DOI: 10.6084/m9.figshare.12480344.v2
title: Chen F et al 2020 QSR-Holocene Tibetan Plateau review-Data

description: Data of a review of Holocene climate change, vegetation history, and landscape responses on the Tibetan Plateau. Stacks of climate change, glacier activity, eolian activity and vegetation change, and pollen-based temperature and precipitation reconstructions for some specific lakes are included. Original reference:
DOI: 10.6084/m9.figshare.12480104
title: gene set name for the embeddings

description: gene set name of msigdb, nci and reactome
DOI: 10.6084/m9.figshare.12480074
title: Deng_nutrients.xlsx

description: mineral cycling in plant and soil system
DOI: 10.6084/m9.figshare.12480077
title: Data for "Effects of grazing, wind erosion, and dust deposition on plant community composition and structure in a temperate steppe"

description: Data for "Effects of grazing, wind erosion, and dust deposition on plant community composition and structure in a temperate steppe", which was accepted for publication in Ecosystems.
DOI: 10.6084/m9.figshare.12480104.v1
title: gene set name for the embeddings

description: gene set name of msigdb, nci and reactome
DOI: 10.6084/m9.figshare.12480068
title: Data for: Johnson et al. 2020 Sci Rep

description: Increased insect herbivore performance under elevated CO<sub>2</sub> is associated with lower plant defence signalling and minimal declines in nutritional quality<br>
DOI: 10.6084/m9.figshare.12480074.v1
title: Deng_nutrients.xlsx

description: mineral cycling in plant and soil system
DOI: 10.6084/m9.figshare.12480053
title: Regional COW dataset.ods

description: Regional dataset on distributions of power.<br>
DOI: 10.6084/m9.figshare.12480068.v2
title: Data for: Johnson et al. 2020 Sci Rep

description: Increased insect herbivore performance under elevated CO<sub>2</sub> is associated with lower plant defence signalling and minimal declines in nutritional quality<br>
DOI: 10.6084/m9.figshare.12480032
title: ТЕХНОЛОГІЇ СТВОРЕННЯ ОСВІТНІХ КОМП’ЮТЕРНИХ ІГОР ТА ПРОЕКТУВАННЯ ДОПОВНЕНОЇ РЕАЛЬНОСТІ: Комп’ютерний практикум. Частина І [Електронний ресурс]: навч. посіб. для студ. спеціалізації «Електронні та інформаційні технології кінематографії та аудіовізуальних систем»

description: І частина комп'ютерного практикуму охоплює розділи дисципліни «Технології створення освітніх комп’ютерних ігор та проектування доповненої реальності», присвячені питанням проектування доповненої реальності і<b> </b>складається з опису 3 (2-годинних), 1 (4-годинного), 1(6-годинного) і 1(8-годинного) практикумів. При виконанні практикумів передбачається використання мережі Internet. Практикуми містять теоретичну частину, яка стосується теоретичних засад створення застосунків доповненної реальності, опис засобів для їх створення. В практикумах також наведено приклади реалізації типових завдань зі створення додатків віртуальної і доповненої реальності, вказівки до порядку виконання завданнь. <b></b>
DOI: 10.6084/m9.figshare.12480068.v1
title: Data for: Johnson et al. 2020 Sci Rep

description: Increased insect herbivore performance under elevated CO<sub>2</sub> is associated with lower plant defence signalling and minimal declines in nutritional quality<br>
DOI: 10.6084/m9.figshare.12480035
title: Supplementary Table 1

description: Supplementary Table 1: SNPs, INDELS, gaps, and ambiguous bases in genomes generated in EDGE COVID-19 compared to genomes in public repositories generated from the same datasets.
DOI: 10.6084/m9.figshare.12480035.v1
title: Supplementary Table 1

description: Supplementary Table 1: SNPs, INDELS, gaps, and ambiguous bases in genomes generated in EDGE COVID-19 compared to genomes in public repositories generated from the same datasets.
DOI: 10.6084/m9.figshare.12480032.v1
title: ТЕХНОЛОГІЇ СТВОРЕННЯ ОСВІТНІХ КОМП’ЮТЕРНИХ ІГОР ТА ПРОЕКТУВАННЯ ДОПОВНЕНОЇ РЕАЛЬНОСТІ: Комп’ютерний практикум. Частина І [Електронний ресурс]: навч. посіб. для студ. спеціалізації «Електронні та інформаційні технології кінематографії та аудіовізуальних систем»

description: І частина комп'ютерного практикуму охоплює розділи дисципліни «Технології створення освітніх комп’ютерних ігор та проектування доповненої реальності», присвячені питанням проектування доповненої реальності і<b> </b>складається з опису 3 (2-годинних), 1 (4-годинного), 1(6-годинного) і 1(8-годинного) практикумів. При виконанні практикумів передбачається використання мережі Internet. Практикуми містять теоретичну частину, яка стосується теоретичних засад створення застосунків доповненної реальності, опис засобів для їх створення. В практикумах також наведено приклади реалізації типових завдань зі створення додатків віртуальної і доповненої реальності, вказівки до порядку виконання завданнь. <b></b>
DOI: 10.6084/m9.figshare.12479966
title: Online Data for “Phylogenomics reveals convergent evolution of red-violet coloration in land plants and the origins of the anthocyanin biosynthetic pathway”

description: A folder containing the following items: <b> </b> <b>Orthogroup Assignments</b> A compressed tab-delimited spreadsheet containing orthogroup assignments from OrthoFinder. <b>Anthocyanin Biosynthetic Pathway (ABP) Orthogroup Reconciliations</b> A compressed folder containing the multiple sequence alignments, gene trees, and gene tree reconciliations for orthogroups containing reference genes in the anthocyanin biosynthetic pathway. Also included is the species tree generated using ASTRAL in Newick format. File endings: Multiple sequence alignment = ".fa" Cleaned multiple sequence alignment = ".fa.cln" Extended majority-rule consensus tree = ".contree" Rooted and reconciled gene tree = ".recon" IQ-TREE log file = ".log <b>Supplementary Material Results</b> A compressed folder containing information described in the Supplementary Material online. The following data are contained: (1) A tab-delimited spreadsheet containing the reciprocal best hits to reference genes in the anthocyanin biosynthetic pathway (2) All pairwise orthologs identified by SonicParanoid (3) The results from analysis of the OneKP dataset including multiple sequence alignments, gene trees, and gene tree reconciliations for orthogroups containing reference genes in the anthocyanin biosynthetic pathway. Also included is the main ASTRAL species tree from the OneKP capstone paper used to reconcile the gene trees. File endings: Multiple sequence alignment = ".fa" Cleaned multiple sequence alignment = ".fa.cln" Maximum likelihood tree = ".tree" Reconciled gene tree = ".recon"<br>
DOI: 10.6084/m9.figshare.12479912
title: All_Tetrad_Data_Final.csv

description: Dataset of cannabinoid tetrad assays in young and old, male and female mice treated with varying doses of synthetic cannabinoid CP55940 with and without CB1 and CB2 antagonists. <br>
DOI: 10.6084/m9.figshare.12479876
title: Dataset for 'A genealogical approach to academic success'

description: Our genealogical data is drawn from the Mathematics Genealogy Project (MGP), an online database developed as a historicalrecord of scientists with a Ph.D. in mathematics to keep track of mentor-mentee relationships. Each scientist is registered by a unique ID. The project also records the instituteand country where the Ph.D. degree was obtained, the year in which the degree was obtained, and, often, the title and subject classification of the thesis.We use this dataset to study whether ancestry size and ancestry diversity affects future academic success of scientists.
DOI: 10.6084/m9.figshare.12479846
title: ---

description: ----
DOI: 10.6084/m9.figshare.12479852.v1
title: Data Set - Drag coefficient of emergent flexible vegetation in steady nonuniform flow.xlsx

description: The dataset describes the experimental data about water surface in the nonuniform flow through a flexible vegetated patch. Measurements were conducted with five vegetation densities. This data set is suitable for fitting the water surface in the vegetated patch. It accompanies the journal article submission entitled "Drag coefficient of emergent flexible vegetation in steady nonuniform flow".
DOI: 10.6084/m9.figshare.12479720
title: raw_100samples_seq_split.zip

description: Sequencing data of gut microbiota
DOI: 10.6084/m9.figshare.12479720.v1
title: raw_100samples_seq_split.zip

description: Sequencing data of gut microbiota
DOI: 10.6084/m9.figshare.12479675
title: Lemmatizer Evaluation Sheets (Lys 7, Hom. Il. 1.1-279)

description: Evaluation of accuracy of lemmatizers for 2 samples (Lys 7, Hom. Il. 1.1-279)
DOI: 10.6084/m9.figshare.12479846.v1
title: Dataset for paper 'A typology of Scientific Breakthroughs'

description: Dataset of scientific breakthroughs as identified by Science Magazine's Breakthrough of the Year 1999 - 2012. We used the DOI of each article to collect data from Web of Science: (1) publication date; (2) publication source; (3) citation report consisting of the number of citations per year for ten years, or as many years as possible for articles published after 2008; (4) number of authors. The variables <i>question, new, anomalies, applied </i>and<i> basic</i> are coded by means of the article's full text, as described in the paper. This data was collected in April-May 2018. WoS queries ran on April 24 and 25 2018.
DOI: 10.6084/m9.figshare.12479582
title: Metadata record for: Centuries of monthly and 3-hourly global ocean wave data for past, present, and future climate research

description: This dataset contains key characteristics about the data described in the Data Descriptor Centuries of monthly and 3-hourly global ocean wave data for past, present, and future climate research. <br> Contents: <br> 1. human readable metadata summary table in CSV format 2. machine readable metadata file in JSON format <br> <br> <br>
DOI: 10.6084/m9.figshare.12479570
title: Artificial Intelligence and the Fight Against COVID-19

description: Datasets analysed in a paper mapping AI research activity against COVID-19. Includes:<br><b>-rxiv metadata:</b> A dataset with metadata about 1.8m papers from arXiv, biorXiv and medrXiv as of end May 2020 enriched with dummies about whether the papers are related to AI and/or COVID-19 research (<i>updated 22/06/2020 to fix some ids)</i><br><br><b>-rxi_geo:</b> A dataset with geographical metadata for papers based on the institutional affiliations of their authors after matching with the GRID database.<br><b>-covid_semantic:</b> A dataset with topic information about COVID-19 papers based on a semantic analysis of their abstracts, including the clusters where papers have been classified and their topic mixes (<i>updated 22/06/2020 to fix some ids).</i><br><b>-citation_metadata:</b> Two JSON objects. One contains a lookup between COVID-19 related papers in the rXiv corpus and the papers they cite. Another contains metadata about the cited papers including their fields of study.<br><b>-mag_fos: </b>A dataset with the Microsoft Academic Graph field of study hierarchy we use in our analysis (added 22 June 2020)<br>Each zipped folder includes a data dictionary.<br>For information about data processing and analysis in: https://github.com/nestauk/ai_covid_19
DOI: 10.6084/m9.figshare.12479582.v1
title: Metadata record for: Centuries of monthly and 3-hourly global ocean wave data for past, present, and future climate research

description: This dataset contains key characteristics about the data described in the Data Descriptor Centuries of monthly and 3-hourly global ocean wave data for past, present, and future climate research. <br> Contents: <br> 1. human readable metadata summary table in CSV format 2. machine readable metadata file in JSON format <br> <br> <br>
DOI: 10.6084/m9.figshare.12479846.v2
title: Dataset for paper 'A typology of Scientific Breakthroughs'

description: Dataset of scientific breakthroughs as identified by Science Magazine's Breakthrough of the Year 1999 - 2012. Number of authors is retrieved from Web of Science, using the DOI of each article. The variables <i>question, new, anomalies, applied </i>and<i> basic</i> are coded by means of the article's full text, as described in the paper. This data was collected in April-May 2018. WoS queries ran on April 24 and 25 2018.
DOI: 10.6084/m9.figshare.12479846.v4
title: ---

description: ----
DOI: 10.6084/m9.figshare.12479846.v3
title: Dataset for paper 'A typology of Scientific Breakthroughs'

description: Dataset of scientific breakthroughs as identified by Science Magazine's Breakthrough of the Year 1999 - 2012. Number of authors is retrieved from Web of Science, using the DOI of each article. The variables <i>question, new, anomalies, applied </i>and<i> basic</i> are coded by means of the article's full text, as described in the paper. This data was collected in April-May 2018. WoS queries ran on April 24 and 25 2018.
DOI: 10.6084/m9.figshare.12479570.v1
title: Artificial Intelligence and the Fight Against COVID-19

description: Datasets analysed in a paper mapping AI research activity against COVID-19. Includes:<br>-A dataset with metadata about 1.8m papers from arXiv, biorXiv and medrXiv as of end May 2020 enriched with dummies about whether the papers are related to AI and/or COVID-19 research<br><br>-rxiv_metadata: A dataset with geographical metadata for papers based on the institutional affiliations of their authors<br>-A dataset with topical information about COVID-19 papers based on a semantic analysis of their abstracts<br>Each zipped folder includes a data dictionary.<br>For information about data processing and analysis in: https://github.com/nestauk/ai_covid_19
DOI: 10.6084/m9.figshare.12479570.v2
title: Artificial Intelligence and the Fight Against COVID-19

description: Datasets analysed in a paper mapping AI research activity against COVID-19. Includes:<br><b>-rxiv metadata:</b> A dataset with metadata about 1.8m papers from arXiv, biorXiv and medrXiv as of end May 2020 enriched with dummies about whether the papers are related to AI and/or COVID-19 research<br><br><b>-rxi_geo:</b> A dataset with geographical metadata for papers based on the institutional affiliations of their authors after matching with the GRID database.<br><b>-covid_semantic:</b> A dataset with topic information about COVID-19 papers based on a semantic analysis of their abstracts, including the clusters where papers have been classified and their topic mixes.<br><b>-citation_metadata:</b> Two JSON objects. One contains a lookup between COVID-19 related papers in the rXiv corpus and the papers they cite. Another contains metadata about the cited papers including their fields of study.<br>Each zipped folder includes a data dictionary.<br>For information about data processing and analysis in: https://github.com/nestauk/ai_covid_19
DOI: 10.6084/m9.figshare.12479570.v3
title: Artificial Intelligence and the Fight Against COVID-19

description: Datasets analysed in a paper mapping AI research activity against COVID-19. Includes:<br><b>-rxiv metadata:</b> A dataset with metadata about 1.8m papers from arXiv, biorXiv and medrXiv as of end May 2020 enriched with dummies about whether the papers are related to AI and/or COVID-19 research<br><br><b>-rxi_geo:</b> A dataset with geographical metadata for papers based on the institutional affiliations of their authors after matching with the GRID database.<br><b>-covid_semantic:</b> A dataset with topic information about COVID-19 papers based on a semantic analysis of their abstracts, including the clusters where papers have been classified and their topic mixes.<br><b>-citation_metadata:</b> Two JSON objects. One contains a lookup between COVID-19 related papers in the rXiv corpus and the papers they cite. Another contains metadata about the cited papers including their fields of study.<br>Each zipped folder includes a data dictionary.<br>For information about data processing and analysis in: https://github.com/nestauk/ai_covid_19
DOI: 10.6084/m9.figshare.12479570.v5
title: Artificial Intelligence and the Fight Against COVID-19

description: Datasets analysed in a paper mapping AI research activity against COVID-19. Includes:<br><b>-rxiv metadata:</b> A dataset with metadata about 1.8m papers from arXiv, biorXiv and medrXiv as of end May 2020 enriched with dummies about whether the papers are related to AI and/or COVID-19 research (<i>updated 22/06/2020 to fix some ids)</i><br><br><b>-rxi_geo:</b> A dataset with geographical metadata for papers based on the institutional affiliations of their authors after matching with the GRID database.<br><b>-covid_semantic:</b> A dataset with topic information about COVID-19 papers based on a semantic analysis of their abstracts, including the clusters where papers have been classified and their topic mixes (<i>updated 22/06/2020 to fix some ids).</i><br><b>-citation_metadata:</b> Two JSON objects. One contains a lookup between COVID-19 related papers in the rXiv corpus and the papers they cite. Another contains metadata about the cited papers including their fields of study.<br><b>-mag_fos: </b>A dataset with the Microsoft Academic Graph field of study hierarchy we use in our analysis (added 22 June 2020)<br>Each zipped folder includes a data dictionary.<br>For information about data processing and analysis in: https://github.com/nestauk/ai_covid_19
DOI: 10.6084/m9.figshare.12479570.v4
title: Artificial Intelligence and the Fight Against COVID-19

description: Datasets analysed in a paper mapping AI research activity against COVID-19. Includes:<br><b>-rxiv metadata:</b> A dataset with metadata about 1.8m papers from arXiv, biorXiv and medrXiv as of end May 2020 enriched with dummies about whether the papers are related to AI and/or COVID-19 research (<i>updated 22/06/2020 to fix some ids)</i><br><br><b>-rxi_geo:</b> A dataset with geographical metadata for papers based on the institutional affiliations of their authors after matching with the GRID database.<br><b>-covid_semantic:</b> A dataset with topic information about COVID-19 papers based on a semantic analysis of their abstracts, including the clusters where papers have been classified and their topic mixes (<i>updated 22/06/2020 to fix some ids).</i><br><b>-citation_metadata:</b> Two JSON objects. One contains a lookup between COVID-19 related papers in the rXiv corpus and the papers they cite. Another contains metadata about the cited papers including their fields of study.<br><b>-mag_fos: </b>A dataset with the Microsoft Academic Graph field of study hierarchy we use in our analysis (added 22 June 2020)<br>Each zipped folder includes a data dictionary.<br>For information about data processing and analysis in: https://github.com/nestauk/ai_covid_19