cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.3761562.v1865
title: Online Labour Index: Measuring the Online Gig Economy for Policy and Research

description: Data repository for the data underlying the Online Labour Index. See http://ilabour.oii.ox.ac.uk online-labour-index/ for details.
DOI: 10.6084/m9.figshare.3761562.v1864
title: Online Labour Index: Measuring the Online Gig Economy for Policy and Research

description: Data repository for the data underlying the Online Labour Index. See http://ilabour.oii.ox.ac.uk online-labour-index/ for details.
DOI: 10.6084/m9.figshare.14390720.v1
title: MiCM workshop - polygenic risk scores

description: <b>Polygenic risk scores - Theory, Development and Evaluation</b><b><br></b>Please download all materials and store in one folder. Please also ensure plink and PRSice-2 are unzipped and executable.<br>Simulation of data example - simulation.RPart I - Part_I.codes.txtPart II - Part_II.codes.txt<br>Part III - Part_III.codes.txt<br><br>Additional methods - Part_II.LDPred.codes.txt, Part_II.SBayesR.codes,txt, and Part_II.lassosum.codes.txt
DOI: 10.6084/m9.figshare.9878843.v1
title: Number of subjects required in common study designs for functional GABA magnetic resonance spectroscopy in the human brain at 3 T

description: Data relating to:<br>Number of subjects required in common study designs for functional GABA magnetic resonance spectroscopy in the human brain at 3 T<b></b><br>
DOI: 10.6084/m9.figshare.14569251.v2
title: SupplementalTable1.xlsx

description: <b>Supplemental Table 1</b>: Metabolomic Results Abbreviation Table. The MS/MS spectral annotations were determined by using MS/MS-based spectral library matches for GNPS level 3 identification for all molecules, except for some of the bile acids, as noted - standards were run using the same method as samples for level 1 identification.
DOI: 10.6084/m9.figshare.14569251.v1
title: SupplementalTable1.xlsx

description: <b>Supplemental Table 1</b>: Metabolomic Results Abbreviation Table. The MS/MS spectral annotations were determined by using MS/MS-based spectral library matches for GNPS level 3 identification for all molecules, except for some of the bile acids, as noted - standards were run using the same method as samples for level 1 identification.
DOI: 10.48370/ofd/cjbpm0/hrt6pa
title: Golovinomyces cynoglossi (Wallr.) Heluta F-4549 (4).tif

description: :unav
DOI: 10.48370/ofd/cjbpm0/wcoi6a
title: Golovinomyces cynoglossi (Wallr.) Heluta F-4549 (5).tif

description: :unav
DOI: 10.48370/ofd/cjbpm0/5tcdnu
title: Golovinomyces cynoglossi (Wallr.) Heluta F-4549 (3).tif

description: :unav
DOI: 10.6084/m9.figshare.14573793.v1
title: Данные Эко-эффективность

description: Data set
DOI: 10.48370/ofd/cjbpm0/ma4ent
title: Golovinomyces cynoglossi (Wallr.) Heluta F-4549 (2).tif

description: :unav
DOI: 10.48370/ofd/jwpney/oepog2
title: Golovinomyces cynoglossi (Wallr.) Heluta F-4515.tif

description: :unav
DOI: 10.6084/m9.figshare.14575506.v1
title: fertilitytelecommuting.xlsx

description: Данные представляют собой набор индивидуальной информации о демографических и социально-экономических характеристик респондентов Российского мониторинга экономического положения и здоровья (RLMS-HSE). Включает 3 обследуемых года (2017, 2018, 2019). Все переменные, кроме переменной о рождении ребенка, представлены с лагом в 1 год. Поскольку даннные были отобраны, то они не представляют всю группу респондентов, принимавших участие в указанные годы.Первая колонка определяет количество вошедших в анализ людей. Переменная "birth" определяет случаи рождений, соответсвующие исследуемым годам. Переменная "work_home_woman" определяет лагированную информацию о том, работала ли женщина из дома. Далее идут лагированные переменные возраста и возраста в квадрате, количества имеющихся детей, наличия официально зарегистрированного или гражданского партнера, высшего образования, работы, проживания в областном центре или городе, логарифма площади жилья, логарифма дохода на члена домохозяйства, а также годы и федеральные округа, в которых проживают респонденты. В последних двух колонках представлены данные для замужних женщин: "employed_muzha" означает, работал ли муж женщины-респондента; "work_home_man" означает, работал ли муж женщины-респондента из дома.
DOI: 10.48370/ofd/cjbpm0/7uin8h
title: Golovinomyces cynoglossi (Wallr.) Heluta F-4549.tif

description: :unav
DOI: 10.48370/ofd/jwpney
title: Golovinomyces cynoglossi (Wallr.) Heluta, 4515

description: Fungarium Mikromycetes
DOI: 10.6084/m9.figshare.14572260.v1
title: Ginsenoside CK suppresses colitis-associated colorectal cancer referring to gut microbiota

description: gut microbiota
DOI: 10.48370/ofd/cjbpm0
title: Golovinomyces cynoglossi (Wallr.) Heluta, 4549

description: Fungarium Mikromycetes
DOI: 10.6084/m9.figshare.3761562.v1870
title: Online Labour Index: Measuring the Online Gig Economy for Policy and Research

description: Data repository for the data underlying the Online Labour Index. See http://ilabour.oii.ox.ac.uk online-labour-index/ for details.
DOI: 10.6084/m9.figshare.3761562.v1869
title: Online Labour Index: Measuring the Online Gig Economy for Policy and Research

description: Data repository for the data underlying the Online Labour Index. See http://ilabour.oii.ox.ac.uk online-labour-index/ for details.
DOI: 10.6084/m9.figshare.3761562.v1872
title: Online Labour Index: Measuring the Online Gig Economy for Policy and Research

description: Data repository for the data underlying the Online Labour Index. See http://ilabour.oii.ox.ac.uk online-labour-index/ for details.
DOI: 10.6084/m9.figshare.3761562.v1871
title: Online Labour Index: Measuring the Online Gig Economy for Policy and Research

description: Data repository for the data underlying the Online Labour Index. See http://ilabour.oii.ox.ac.uk online-labour-index/ for details.
DOI: 10.6084/m9.figshare.14330795.v5
title: An Immune Cell Atlas Reveals Dynamic COVID-19 Specific Neutrophil Programming Amendable to Therapy

description: SARS-CoV-2 is a novel coronavirus that causes acute respiratory distress syndrome (ARDS) and death. Innate immune cells are critical for host defense but are also the primary drivers of acute respiratory distress syndrome. The relationships between innate cellular responses in ARDS resulting from COVID-19 compared to other causes of ARDS, such as bacterial sepsis is unclear. Moreover, the beneficial cellular effects of dexamethasone therapy during severe COVID-19 remains speculative but understanding their mechanistic effects could improve rationally targeted drug design. We discovered that compared to bacterial septic ARDS, COVID-19 induced distinct neutrophil polarization characterized by either interferon (IFN) or prostaglandin (PG) active states. IFN polarization required the transcriptional regulators PRDM1, STAT1 and IRF1 while prostaglandin polarization was induced by E2F4. Bacterial ARDS neutrophils upregulated antibacterial molecules such as PLAC8 via STAT5b and demonstrated conventional transcription factors CEBPA and CEBPB. Steroid therapy rapidly altered IFN polarization, downregulated interferon responsive genes, and induced immunoretrained neutrophils withelevations of the decoy IL-1R2 regulatory receptor. Steroids induced the emergence of immature neutrophils expressing immunosuppressive molecules ARG1 and ANXA1. Moreover, steroids remodeled global cellular communication hierarchies by changing neutrophils from information receivers into information providers. Importantly, male patients had higher proportions of IFN-active neutrophils and a greater degree of steroid induced attenuation of cellular polarization. Indeed, the highest proportion of IFN-active neutrophils was associated with mortality. These results define neutrophil states unique to COVID-19 when contextualized to other life-threatening infections, thereby enhancing the relevance of our findings at the bedside. Furthermore, the clinical benefits of dexamethasone therapy are molecularly defined, and this information highlights essential molecular pathways to which improved therapeutic targeting can now be conceived.<br>
DOI: 10.6084/m9.figshare.14330795.v4
title: An Immune Cell Atlas Reveals Dynamic COVID-19 Specific Neutrophil Programming Amendable to Therapy

description: SARS-CoV-2 is a novel coronavirus that causes acute respiratory distress syndrome (ARDS) and death. Innate immune cells are critical for host defense but are also the primary drivers of acute respiratory distress syndrome. The relationships between innate cellular responses in ARDS resulting from COVID-19 compared to other causes of ARDS, such as bacterial sepsis is unclear. Moreover, the beneficial cellular effects of dexamethasone therapy during severe COVID-19 remains speculative but understanding their mechanistic effects could improve rationally targeted drug design. We discovered that compared to bacterial septic ARDS, COVID-19 induced distinct neutrophil polarization characterized by either interferon (IFN) or prostaglandin (PG) active states. IFN polarization required the transcriptional regulators PRDM1, STAT1 and IRF1 while prostaglandin polarization was induced by E2F4. Bacterial ARDS neutrophils upregulated antibacterial molecules such as PLAC8 via STAT5b and demonstrated conventional transcription factors CEBPA and CEBPB. Steroid therapy rapidly altered IFN polarization, downregulated interferon responsive genes, and induced immunoretrained neutrophils withelevations of the decoy IL-1R2 regulatory receptor. Steroids induced the emergence of immature neutrophils expressing immunosuppressive molecules ARG1 and ANXA1. Moreover, steroids remodeled global cellular communication hierarchies by changing neutrophils from information receivers into information providers. Importantly, male patients had higher proportions of IFN-active neutrophils and a greater degree of steroid induced attenuation of cellular polarization. Indeed, the highest proportion of IFN-active neutrophils was associated with mortality. These results define neutrophil states unique to COVID-19 when contextualized to other life-threatening infections, thereby enhancing the relevance of our findings at the bedside. Furthermore, the clinical benefits of dexamethasone therapy are molecularly defined, and this information highlights essential molecular pathways to which improved therapeutic targeting can now be conceived.<br>
DOI: 10.48370/ofd/tryysc/ufeirv
title: Golovinomyces cynoglossi (Wallr.) Heluta F-4407 (4).tif

description: :unav
DOI: 10.48370/ofd/tryysc/zvlntz
title: Golovinomyces cynoglossi (Wallr.) Heluta F-4407 (5).tif

description: :unav
DOI: 10.6084/m9.figshare.12798296.v15
title: Data and code from Rizzuto et al. “Forage stoichiometry predicts home range size in a small terrestrial herbivore"

description: Data and code used in Rizzuto et al. "Forage stoichiometry predicts home range size in a small terrestrial herbivore”.<br>The “SupportingCode.html” file provides an in-depth description and discussion of our R workflow to estimate home range size of snowshoe hare and investigate its relationship with the ecological stoichiometry of preferred plant forage species. <br><br>If you would like to reproduce our analyses, you can recompile the R notebook “SupportingCode.Rmd”. This is a modular document that collects the output of 8 other R notebooks. For correct compilation of the SupportingCode.Rmd file, please organize the files in this repository on your machine as follows:<br>- all .Rmd and .R files in a "../Code/“ folder- all .csv files in a "../Data/" folder- all .tiff files in a “../Data/StDMs_Rasters/Ratios/" folder- unzip the SamplePoints.zip file in a "../Data/GridPoints/" folder- all .rds files in a "../Results/" folder<br>Where the Code, Data, and Results folder all share the same root.<br>Please note that access to some shapefiles used to produce the maps in the manuscript, SI, or Supporting Code document was regulated by agreements with the Government of Newfoundland and Labrador and the Federal Government of Canada. As such, they could not be publicly shared. This does not impact the analyses, only the production of some visual supporting material (e.g., study area maps). Please contact the corresponding author (M. Rizzuto) for any question. <br> See README.md for details on the repository’s contents.
DOI: 10.48370/ofd/tryysc/ccnmpr
title: Golovinomyces cynoglossi (Wallr.) Heluta F-4407 (2).tif

description: :unav
DOI: 10.6084/m9.figshare.3761562.v1876
title: Online Labour Index: Measuring the Online Gig Economy for Policy and Research

description: Data repository for the data underlying the Online Labour Index. See http://ilabour.oii.ox.ac.uk online-labour-index/ for details.
DOI: 10.48370/ofd/tryysc/udcobp
title: Golovinomyces cynoglossi (Wallr.) Heluta F-4407 (3).tif

description: :unav
DOI: 10.6084/m9.figshare.3761562.v1875
title: Online Labour Index: Measuring the Online Gig Economy for Policy and Research

description: Data repository for the data underlying the Online Labour Index. See http://ilabour.oii.ox.ac.uk online-labour-index/ for details.
DOI: 10.48370/ofd/tryysc/kh7kp4
title: Golovinomyces cynoglossi (Wallr.) Heluta F-4407.tif

description: :unav
DOI: 10.6084/m9.figshare.14343152.v2
title: Bacteria associated with vascular wilt of poplar

description: In 2017, the 560-ha area of hybrid poplar plantation in northern Poland showed symptoms of tree decline. Leaves appeared smaller, turned yellow-brown, and were shed prematurely. Twigs and smaller branches died. Bark was sunken and discolored, often loosened and split. Trunks decayed from the base. Phloem and xylem showed brown necrosis. Ten per cent of trees died in 1-2 months. None of these symptoms was typical for known poplar diseases.<b> </b>Bacteria in soil and the necrotic base of poplar trunk were analysed with Illumina sequencing. The 16S rDNA was amplified with bacteria-specific primers: 16S-F 5' CAGCCTACGGGNGGCWGCAG, 16S-R 5' ACAGGACTACHVGGGTATCTAATCC (Klindworth et al. 2013).
DOI: 10.48370/ofd/tryysc
title: Golovinomyces cynoglossi (Wallr.) Heluta, 4407

description: Fungarium Mikromycetes
DOI: 10.6084/m9.figshare.14343152.v1
title: Bacteria associated with vascular wilt of poplar

description: In 2017, the 560-ha area of hybrid poplar plantation in northern Poland showed symptoms of tree decline. Leaves appeared smaller, turned yellow-brown, and were shed prematurely. Twigs and smaller branches died. Bark was sunken and discolored, often loosened and split. Trunks decayed from the base. Phloem and xylem showed brown necrosis. Ten per cent of trees died in 1-2 months. None of these symptoms was typical for known poplar diseases.<b> </b>Bacteria in soil and the necrotic base of poplar trunk were analysed with Illumina sequencing. The 16S rDNA was amplified with bacteria-specific primers: 16S-F 5' CAGCCTACGGGNGGCWGCAG, 16S-R 5' ACAGGACTACHVGGGTATCTAATCC (Klindworth et al. 2013).
DOI: 10.6084/m9.figshare.14623758.v1
title: 食品中750种污染物免疫定量快速检测技术和产品

description: 附件材料
DOI: 10.6084/m9.figshare.14625537.v1
title: Genomic adaptations of Escherichia coli strains from patients with inflammatory bowel diseases

description: Comparative genomic study of E. coli from fecal metagenomes of patients with IBD, revealing lineages with different metabolic capabilites and disease-specific adaptations.
DOI: 10.48370/ofd/kdx8v2/ty4s9t
title: Golovinomyces cynoglossi (Wallr.) Heluta F-0476.tif

description: :unav
DOI: 10.6084/m9.figshare.14626425.v1
title: Supplementary Table 2.docx

description: Co-administration of clomiphene citrate and letrozole in mild ovarian stimulation for POSEIDON Group 4 patients<br>
DOI: 10.48370/ofd/kdx8v2
title: Golovinomyces cynoglossi (Wallr.) Heluta, 476

description: Fungarium Mikromycetes
DOI: 10.6084/m9.figshare.13079489.v3
title: MargazoglouEtAl_2020.zip

description: We present here the majority of the dataset used for the figures of the paper "Multistability of the Earth's Climate as a Problem of Stochastic Dynamics and of Data Science". Some datafiles are sufficient to reproduce directly the figures, while others are the raw data one needs to reproduce the figures using the methodologies described in the paper.<br><br>For more information, please contact Georgios Margazoglou at g.margazoglou@reading.ac.uk or Valerio Lucarini at v.lucarini@reading.ac.uk. Thank you!<br><br>
DOI: 10.48370/ofd/sitlmh/xsxrv7
title: Golovinomyces cynoglossi (Wallr.) Heluta F-2661.tif

description: :unav
DOI: 10.6084/m9.figshare.13607279.v1
title: Data from: Temporal variation of daily activity on pollinator and frugivorous birds simultaneously interacting with a specialized mistletoe

description: Original data from: Fernández, V.P. & F.E. Fontúrbel (2021) Temporal variation of daily activity on pollinator and frugivorous birds simultaneously interacting with a specialized mistletoe. Community Ecology.<br>This dataset contains three files:<br>(1) flowers_fruits.txt with the original data on flower and ripe fruit abundance per month and mistletoe(2) data_humm.txt original activity data for Sephanoides sephaniodes(3) data_mock.txt original activity data for Mimus thenca
DOI: 10.48370/ofd/sitlmh
title: Golovinomyces cynoglossi (Wallr.) Heluta, 2661

description: Fungarium Mikromycetes
DOI: 10.6084/m9.figshare.13079489.v4
title: Data and Supplementary Material for the paper: Dynamical landscape and multistability of a climate model

description: We provide here the Supplementary Material and majority of the dataset used for the figures of the paper:<br><br>"Dynamical landscape and multistability of a climate model" by Margazoglou G, Grafke T, Laio A, Lucarini V., (2021), Proc. R. Soc. A, 20210019. https://doi.org/10.1098/rspa.2021.0019<br><br>Some datafiles are sufficient to reproduce directly the figures, while others are the raw data one needs to reproduce the figures using the methodologies described in the paper.<br><br>For more information or any question, please contact:<br>Georgios Margazoglou at g.margazoglou@reading.ac.uk or<br>Valerio Lucarini at v.lucarini@reading.ac.uk<br><br>Thank you!<br><br>
DOI: 10.48370/ofd/gp6f7w/xt2url
title: Golovinomyces cynoglossi (Wallr.) Heluta F-0474.tif

description: :unav
DOI: 10.6084/m9.figshare.14555268.v2
title: Chinese herbal medicine for the treatment of children and adolescents with Refractory Mycoplasma Pneumoniae Pneumonia: a systematic review and a meta-analysis

description: Table S1 Search strategy 2Table S2 Characteristics of adverse events for included studies 5Table S3 Supplement Details respecting to the information of Self-made formulas 8Table S4 Supplement Details respecting to the information of Chinese patent medicines 11File 1 PRISMA checklist. 14File 2 A list of excluded studies by reading full text 17FigureS1 Sensitivity analysis 20
DOI: 10.48370/ofd/gp6f7w
title: Golovinomyces cynoglossi (Wallr.) Heluta, 474

description: Fungarium Mikromycetes
DOI: 10.6084/m9.figshare.14555268.v1
title: Chinese herbal medicine for the treatment of children and adolescents with Refractory Mycoplasma Pneumoniae Pneumonia: a systematic review and a meta-analysis

description: Table S1 Search strategy 2Table S2 Characteristics of adverse events for included studies 5Table S3 Supplement Details respecting to the information of Self-made formulas 8Table S4 Supplement Details respecting to the information of Chinese patent medicines 11File 1 PRISMA checklist. 14File 2 A list of excluded studies by reading full text 17FigureS1 Sensitivity analysis 20
DOI: 10.6084/m9.figshare.14634492.v1
title: FoRham1 sequence data

description: This data shows the results screen of a mascot search.
DOI: 10.6084/m9.figshare.12130980.v95
title: MOOD Maps of Google community mobility change during the COVID-19 outbreak

description: The MOOD project (MOnitoring Outbreak events for Disease surveillance in a data science context. H2020) has geo-referenced the data Google has published as a series of PDF files presenting reports on national and subnational human mobility levels relative to a baseline data of late January 2020. The details and the PDF files can be found at https://www.google.com/covid19/mobility/.<br>More detail on these files can be found at https://www.moodspatialdata.com/humanmobilityforcovid19 <br>The first set of data were released on April 2 2020 and have been revised weekly since then. The maps now utilise the CSV data released by Google. Please note that the maps figures use a mean of the previous three days, while the Google PDFs use a single days data so there will be differences between values in our maps when compare to the Google PDFs.<br>The authors have extracted the majority of these data into a series of excel spreadsheets. Each worksheet provides the data for % change in numbers of records at various types of location categories illustrated by: retail and recreation, grocery and pharmacy, parks and beaches, transit stations, workplaces and residential (columns f to K). A second set of columns calculates the difference of each value from the mean values for each category (columns L to P) Columns A to E contain geographical details. Column Q contains the names used to link to a mapping file.There are separate worksheets for the date of the data from each dated release (e.g. 2903, 0504 etc.) and separate worksheets calculating the changes between specific dates.<br>A second spreadsheet has been added calculating the 3 day moving mean of each day from the 15th of February. Each day is referenced by the Gregorian calendar day count. So day 48 = Feb 17th.<br>The maps (for EU & Global) display these data. We provide 600 dpi jpegs of the Global (“WD”) and European (“EU”) mapped values at the latest date available, for each of the mobility categories: retail and recreation (“retrec”) , grocery and pharmacy (“grocphar”) , parks (“parks”) , transit stations (“transit”), residential (“resid”) and workplaces (“work”). We also provide maps of the changes from the previous week (“ch”).<br>All data extracting and subsequent processing have been carried out by ERGO (Environmental Research Group Oxford, c/o Dept Zoology, University of Oxford) on behalf of the MOOD H2020 project. Data will be periodically updated. Additional maps can be obtained on request to the authors.