cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.4276957
title: "Pressure-to-depth conversion models for metamorphic rocks: derivation and applications" (Supplementary material and Figures)

description: Supporting Information and Figures associated to the paper entitled: "Pressure-to-depth conversion models for metamorphic rocks: derivation and applications" by A. Bauville and P. Yamato. (Geochemistry, Geophysics, Geosystems). These links allow to download: - The figures of the paper in .pdf format - The scripts used to generate the figures - The supporting information file. Please, contact A. Bauville for additional information.
DOI: 10.5281/zenodo.4194309
title: A heterometallic [LnLn'Ln] lanthanide complex as a qubit with embedded quantum error correction. Open data set

description: Includes data relevant for publication with DOI 10.1039/d0sc03107k plus a table with information on how the data were obtained and processed.
DOI: 10.5281/zenodo.4194308
title: A heterometallic [LnLn'Ln] lanthanide complex as a qubit with embedded quantum error correction. Open data set

description: Includes data relevant for publication with DOI 10.1039/d0sc03107k plus a table with information on how the data were obtained and processed.
DOI: 10.5281/zenodo.4274177
title: The last interglacial sea-level record of the Israeli coastline - WALIS database of sea-level indicators

description: This file is a record of relative sea level proxies of the last Interglacial sea-level along the Israeli coastline. It has been exported from the World Atlas of Last Interglacial Shorelines - WALIS
DOI: 10.6084/m9.figshare.12813176.v2
title: A dataset on occurrence of ten potential host animals of SARS-CoV-2

description: This dataset provides 5429 geo-referenced occurrence records in 2158 unique locations of 10 potential animal hosts, mainly concerning the wild mammals in the geographic scope of China and adjacent countries.
DOI: 10.6084/m9.figshare.12813176
title: A dataset on occurrence of ten potential host animals

description: This dataset provides 5429 geo-referenced occurrence records in 2158 unique locations of 10 potential animal hosts, mainly concerning the wild mammals in the geographic scope of China and adjacent countries.
DOI: 10.6084/m9.figshare.12813176.v3
title: A dataset on occurrence of ten potential host animals of SARS-CoV-2

description: This dataset provides 5429 geo-referenced occurrence records in 2158 unique locations of 10 potential animal hosts, mainly concerning the wild mammals in the geographic scope of China and adjacent countries.
DOI: 10.6084/m9.figshare.13246304
title: Supplementary Material for: Serum Concentration and Skin Expression of S100A7 (Psoriasin) in Patients Suffering from Hidradenitis Suppurativa

description: <b><i>Background:</i></b> Hidradenitis suppurativa (HS) is a chronic inflammatory skin disease. An important role of innate immune dysregulation in the pathogenesis of HS has been highlighted. S100A7 (psoriasin) is an innate, antimicrobial protein that exerts proinflammatory and chemotactic action. <b><i>Objectives:</i></b> The objective of the study was to investigate serum concentrations of S100A7 in individuals with HS as compared to healthy controls. Further, we evaluated the expression of S100A7 in lesional HS skin as compared to perilesional (clinically uninvolved) HS skin and normal skin. <b><i>Methods:</i></b> Serum concentrations of S100A7 were evaluated with a commercially available ELISA kit. The expression of S100A7 in the skin was assessed using qRT-PCR and immunofluorescence staining. <b><i>Results:</i></b> We found increased expression of S100A7 in lesional HS skin as compared to perilesional HS skin (<i>p</i> = 0.0017). The expression of S100A7 in lesional HS skin was positively associated with serum C-reactive protein concentration and the severity of disease according to Hurley staging. The serum concentration of S100A7 in individuals with HS was decreased as compared to healthy controls and patients with psoriasis. <b><i>Conclusions:</i></b> Upregulated in lesional HS skin, S100A7 may enhance the inflammatory process and contribute to the HS pathogenesis.
DOI: 10.6084/m9.figshare.13246304.v1
title: Supplementary Material for: Serum Concentration and Skin Expression of S100A7 (Psoriasin) in Patients Suffering from Hidradenitis Suppurativa

description: <b><i>Background:</i></b> Hidradenitis suppurativa (HS) is a chronic inflammatory skin disease. An important role of innate immune dysregulation in the pathogenesis of HS has been highlighted. S100A7 (psoriasin) is an innate, antimicrobial protein that exerts proinflammatory and chemotactic action. <b><i>Objectives:</i></b> The objective of the study was to investigate serum concentrations of S100A7 in individuals with HS as compared to healthy controls. Further, we evaluated the expression of S100A7 in lesional HS skin as compared to perilesional (clinically uninvolved) HS skin and normal skin. <b><i>Methods:</i></b> Serum concentrations of S100A7 were evaluated with a commercially available ELISA kit. The expression of S100A7 in the skin was assessed using qRT-PCR and immunofluorescence staining. <b><i>Results:</i></b> We found increased expression of S100A7 in lesional HS skin as compared to perilesional HS skin (<i>p</i> = 0.0017). The expression of S100A7 in lesional HS skin was positively associated with serum C-reactive protein concentration and the severity of disease according to Hurley staging. The serum concentration of S100A7 in individuals with HS was decreased as compared to healthy controls and patients with psoriasis. <b><i>Conclusions:</i></b> Upregulated in lesional HS skin, S100A7 may enhance the inflammatory process and contribute to the HS pathogenesis.
DOI: 10.5517/ccdc.csd.cc25qm0k
title: CCDC 2017728: Experimental Crystal Structure Determination

description: Related Article: Mikhail N. Zharkov, Ilya V. Kuchurova, Sergei G. Zlotin|2020|CrystEngComm|22|7549|doi:10.1039/d0ce01167c
DOI: 10.34740/kaggle/dsv/1645386
title: 126 RNA_Seq datasets of COVID-19
DOI: 10.25899/div-12346-1
title: Tabelle der physikalisch-chemischen Eigenschaften und Zusammensetzung von Thermalwässern

description: In the project 'Setup of a geothermal information system for Germany' (2006-2009), data on physico-chemical fluid properties and composition were compiled and validated. Exclusively boreholes with hydraulic tests were used, whereby the fluid properties were mostly sampled during those tests. In North-Eastern Germany 217 samples were evaluated, in the Upper Rhine Graben 194 and in the Southern German Molasse Basin 55.
description: Cations, Anions, pH, Redox-Potential, electrical conductivity, gas content
DOI: 10.14768/29fbfe70-a8e8-41db-914c-b14be9a6f90b
title: The High-Tune Explorer : first tests and publications

description: High-Tune Explorer is a suite of programs developed in the frame of the High-Tune project, supported by the ANR french research agency. The data available on the DOI is linked to a 2-part publications in Journal of Advances in Modeling Earth Systems Process-based climate model development harnessing machine learning: I. a calibration tool for parameterization improvement A major task in the development of atmospheric models is the development of parameterizations to account for processes not resolved by the dynamical core. The improvement of models is slow partly due to the difficulty of encompassing key processes into parameterizations and because parameterizations contain `free' parameters that must be calibrated or `tuned'. Considering the number of parameters in a model, their calibration is a complicated task, generally done manually. Recently, machine learning has been proposed as a replacement for these parameterizations. However, when models are to be used for long-term projections, exploring states far from the training data, sole use of machine learning might be dangerous. It also seems counter-intuitive to replace our strong physical understanding with unconstrained systems. Our proposition consists in retaining parameterizations but adjoining new tools relying on machine learning to accelerate model development. In particular we use Gaussian process-based methods from uncertainty quantification to calibrate the free parameters at a process level. To achieve this, we focus on the comparison of single-column simulations and reference large-eddy simulations over multiple boundary-layer cases. This paper describes the tools and the philosophy of tuning in single-column mode. Part 2 emphasizes how this framework can help accelerate model development. II. model calibration from single column to global. In view of the importance of global numerical models for the anticipation of future climate changes, their improvement is often considered too slow. We present a new approach that we believe could boost model improvement significantly. This approach promotes the use of machine learning techniques developed by the "uncertainty quantification" community for the adjustment of model free parameters, or tuning. These techniques are applied to physics improvement at process scale, represented through parameterizations. In this approach, the tuning of the global atmospheric model is preconditioned by calibration of the model free parameters on a series of well documented cloud scenes for which explicit very high resolution simulations are available (see Part I). We demonstrate on a real example how the reduction of the parameter space with this approach allows us to save a large amount of computer resources and detract from the long and tedious by-hand phase of model tuning. By automating part of the tuning process, the approach enables climate modeler expertise to focus on understanding and improving the model physics through parameterization.
DOI: 10.6084/m9.figshare.13244744.v4
title: Fuel Moisture Content (FMC)

description: Fuel moisture content (FMC) is defined as the ratio of canopy water content to dry weight, which is a key index for evaluating wildfire risk and fire spread rate.<br>
DOI: 10.5281/zenodo.3369247
title: Child mortality dataset (from the UN Inter-agency Group for Child Mortality Estimation database). June 2019

description: This dataset compromises all country data included in the UN Inter-agency Group for Child Mortality Estimation (IGME) database (https://childmortality.org/data, downloaded June 2019). It includes: <strong>Reference area: </strong>name of the country <strong>Indicator:</strong> child mortality indicator (neonatal mortality, infant mortality, under-5 mortality and mortality rate age 5 to 14) <strong>Sex: </strong>sex of the child (male, female and total) <strong>Series name:</strong> name of survey/census/VR [note: UN IGME estimates, i.e. not source data, are identified as "UN IGME estimate" in this field] <strong>Series year: </strong>year of survey/census/VR series <strong>Observation value: </strong>value of indicator from survey/census/VR <strong>Observation status:</strong> indicates whether the data point is included or excluded for estimation [status of "normal" indicates UN IGME estimate, i.e. not source data] <strong>Series Category:</strong> category of survey/census/VR, and can be: DHS [Demographic and Health Survey] MIS [Malaria Indicator Survey] AIS [AIDS Indicator Survey] Interim DHS Special DHS NDHS [National DHS] WFS [World Fertility Survey] MICS [Multiple Indicator Cluster Survey] NMICS [National MICS] RHS [Reproductive Health Survey] PAP [Pan Arab Project for Child or Pan Arab Project for Family Health or Gulf Famly Health Survey] LSMS [Living Standard Measurement Survey] Panel [Dual record, multiround/follow-up survey and longitudinal/panel survey] Census VR [Vital Registration] SVR [Sample Vital Registration] Others [e.g. Life Tables] <strong>Series type: </strong>the type of calculation method used to derive the indicator value (direct, indirect, household deaths, life table and vital records) <strong>Standard error: </strong>sampling standard error of the observation value <strong>Series method: </strong>data collection method, and can be: Survey/census with Full Birth Histories Survey/census with Summary Birth Histories Survey/census with Household death Vital Registration Other <strong>Lower and upper bound:</strong> the lower and upper bounds of 90% uncertainty interval of UN IGME estimates (for estimates only, i.e., not source data). The dataset is used in the following paper: <em>Ezbakhe, F. and Pérez-Foguet, A. (2019) Levels and trends in child mortality: a compositional approach. Demographic Research (Under Review)</em>
DOI: 10.5281/zenodo.3369246
title: Child mortality dataset (from the UN Inter-agency Group for Child Mortality Estimation database). June 2019

description: This dataset compromises all country data included in the UN Inter-agency Group for Child Mortality Estimation (IGME) database (https://childmortality.org/data, downloaded June 2019). It includes: <strong>Reference area: </strong>name of the country <strong>Indicator:</strong> child mortality indicator (neonatal mortality, infant mortality, under-5 mortality and mortality rate age 5 to 14) <strong>Sex: </strong>sex of the child (male, female and total) <strong>Series name:</strong> name of survey/census/VR [note: UN IGME estimates, i.e. not source data, are identified as "UN IGME estimate" in this field] <strong>Series year: </strong>year of survey/census/VR series <strong>Observation value: </strong>value of indicator from survey/census/VR <strong>Observation status:</strong> indicates whether the data point is included or excluded for estimation [status of "normal" indicates UN IGME estimate, i.e. not source data] <strong>Series Category:</strong> category of survey/census/VR, and can be: DHS [Demographic and Health Survey] MIS [Malaria Indicator Survey] AIS [AIDS Indicator Survey] Interim DHS Special DHS NDHS [National DHS] WFS [World Fertility Survey] MICS [Multiple Indicator Cluster Survey] NMICS [National MICS] RHS [Reproductive Health Survey] PAP [Pan Arab Project for Child or Pan Arab Project for Family Health or Gulf Famly Health Survey] LSMS [Living Standard Measurement Survey] Panel [Dual record, multiround/follow-up survey and longitudinal/panel survey] Census VR [Vital Registration] SVR [Sample Vital Registration] Others [e.g. Life Tables] <strong>Series type: </strong>the type of calculation method used to derive the indicator value (direct, indirect, household deaths, life table and vital records) <strong>Standard error: </strong>sampling standard error of the observation value <strong>Series method: </strong>data collection method, and can be: Survey/census with Full Birth Histories Survey/census with Summary Birth Histories Survey/census with Household death Vital Registration Other <strong>Lower and upper bound:</strong> the lower and upper bounds of 90% uncertainty interval of UN IGME estimates (for estimates only, i.e., not source data). The dataset is used in the following paper: <em>Ezbakhe, F. and Pérez-Foguet, A. (2019) Levels and trends in child mortality: a compositional approach. Demographic Research (Under Review)</em>
DOI: 10.5281/zenodo.3989751
title: Supplementary material for "Compounds with antiviral, anti-inflammatory and anticancer activity identified in wine via high resolution mass spectrometry and bioinformatics analyses"

description: Wine contains a variety of molecules with potential beneficial effects on human health. Our aim was to examine the wine components with high-resolution mass spectrometry including high-resolution tandem mass spectrometry in two wine types made from grapes with or without the fungus <em>Botrytis cinerea</em>, or “noble rot.” For LC-MS/MS analysis, 12 wine samples (7 without and 5 with noble rotting) from 4 different wineries were used and wine components were identified and quantified. 288 molecules were identified in the wines and the amount of 169 molecules was statistically significantly different between the two wine types. A database search was carried out to find the molecules, which were examined in functional studies so far, with high emphasis on molecules with antiviral, anti-inflammatory and anticancer activities. A comprehensive functional dataset related to identified wine components is also provided highlighting the importance of components with potential health benefits.
DOI: 10.5286/isis.e.rb2010169
title: Investigation of crystal field excitations in Li ion battery cathode materials

description: Mixed lithium ion transition metal oxides LiNixMnyCozO2 (x+y+z=1) (commonly abbreviated as Li NMC oxides) are next-generation lithium ion battery cathode materials for electric vehicles and grid storage. These materials consist of multivalent transition metal ions in octahedral coordination. We propose that inelastic neutron scattering (INS) experiments can be used to measure the single-ion spectrum of each magnetic ion and hence model each valence state separately. In this experiment we aim to determine whether INS measurements of these single-ion levels are feasible by measuring each ionic species present in the Li NMC oxides separately. The materials we propose to measure containing a single ionic species are LiCoO2 (Co3+), LiMn2O4 (Mn3+/4+), NaNiO2 (Ni3+), MnO2 (Mn4+) and NiO (Ni2+).
DOI: 10.5286/isis.e.rb2010169-1
title: Investigation of crystal field excitations in Li ion battery cathode materials

description: Mixed lithium ion transition metal oxides LiNixMnyCozO2 (x+y+z=1) (commonly abbreviated as Li NMC oxides) are next-generation lithium ion battery cathode materials for electric vehicles and grid storage. These materials consist of multivalent transition metal ions in octahedral coordination. We propose that inelastic neutron scattering (INS) experiments can be used to measure the single-ion spectrum of each magnetic ion and hence model each valence state separately. In this experiment we aim to determine whether INS measurements of these single-ion levels are feasible by measuring each ionic species present in the Li NMC oxides separately. The materials we propose to measure containing a single ionic species are LiCoO2 (Co3+), LiMn2O4 (Mn3+/4+), NaNiO2 (Ni3+), MnO2 (Mn4+) and NiO (Ni2+).
DOI: 10.15161/oar.it/73263
title: CovidStat project data

description: This record contains the daily updated data of the CovidStat project. CovidStat is a project carried out by the CovidStat Working Group at INFN, whose creation was promoted within the Italian National Institute of Nuclear Physics with the aim of making a statistical analysis of the data provided daily by the Civil Protection on the spread of the pandemic in Italy. CovidStat data can interactively be browsed at https://covid19.infn.it.
description: The software to process this Root TTree is in the related identifier. Be sure to use the right corresponding version, based on the data in which Root TTree was generated.
DOI: 10.25405/data.ncl.13242248
title: PosidoniaData.zip

description: Data contains a complete set of micromechanical results on Posidonia shale for a paper submitted to Journal of Geophysical Research: Solid Earth entitled "Effect of diagenesis on geomechanical properties of organic-rich shale: a multiscale investigation" <br>
DOI: 10.25405/data.ncl.13242248.v1
title: PosidoniaData.zip

description: Data contains a complete set of micromechanical results on Posidonia shale for a paper submitted to Journal of Geophysical Research: Solid Earth entitled "Effect of diagenesis on geomechanical properties of organic-rich shale: a multiscale investigation" <br>
DOI: 10.6084/m9.figshare.13246561.v1
title: Supplementary Table 1. U–Pb zircon analytical data. U–Pb Detrital Zircon Constraints on Active Margin Magmatism and Sedimentation after the Grampian Orogeny in Western Ireland

description: Supplementary Table 1. U–Pb zircon analytical data.
DOI: 10.6084/m9.figshare.13246561
title: Supplementary Table 1. U–Pb zircon analytical data. U–Pb Detrital Zircon Constraints on Active Margin Magmatism and Sedimentation after the Grampian Orogeny in Western Ireland

description: Supplementary Table 1. U–Pb zircon analytical data.
DOI: 10.6084/m9.figshare.13246541
title: Table 1.txt

description: Sticking coefficients at increasing H2O and CO2 exposures, and mean value S
DOI: 10.6084/m9.figshare.13246541.v1
title: Table 1.txt

description: Sticking coefficients at increasing H2O and CO2 exposures, and mean value S
DOI: 10.5519/qd.skefmz98
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (1229 records)
DOI: 10.5281/zenodo.4106578
title: Systematic reanalysis of co-fractionation mass spectrometry data: processed chromatograms

description: A total of 206 co-fractionation mass spectrometry (CF-MS) experiments were downloaded from public proteomics repositories such as PRIDE and MASSIVE, then re-analyzed with MaxQuant. This upload contains processed chromatogram matrices for all 206 experiments. Database search and protein quantitation was performed with MaxQuant (version 1.6.5.0), and potential contaminants, reverse hits, and proteins identiifed only by modified peptides were filtered out. Multiple chromatograms are provided for each experiment, corresponding to different protein quantitation strategies. These include iBAQ, MaxLFQ, MS1 intensity, and spectral counts, for label-free datasets, and the isotopologue ratio for SILAC or dimethyl labelling datasets. Each directory also contains a metadata file, which contains further information about each row in the corresponding chromatogram matrices output by MaxQuant. Complete MaxQuant outputs for each experiment are available from the PRIDE repository under the accession PXD022048.
DOI: 10.5281/zenodo.4245282
title: Systematic reanalysis of co-fractionation mass spectrometry data: predicted interactomes

description: This upload contains predicted interactomes for 27 species or clades: 17 individual organisms with at least three published CF-MS experiments, and 9 phylogenetic groupings of those organisms. The following individual organisms are represented: Arabidopsis thaliana Brassica oleracea Caenorhabditis elegans Chaetomium thermophilum Chlamydomonas reinhardtii Dictyostelium discoideum Drosophila melanogaster Nematostella vectensis Homo sapiens Mus musculus Oryza sativa Plasmodium berghei Plasmodium falciparum Plasmodium knowlesi Strongylocentrotus purpuratus Triticum aestivum Trypanosoma brucei Xenopus laevis The following clades are also represented: BOP clade Deuterostomia Eucharontoglires Eukaryota Mesangiospermae Opiskothonta Plasmodium Tetrapoda Viridaplantae The interactomes are provided in two forms. Files in the 'All interactions' directory include the complete classifier scores for every possible protein pair (sorted in descending order). Files in the '50% precision' directory include only those interactions identified above 50% precision, for convenience. Proteins were mapped to orthogroups using eggNOG. Maps from eggNOG orthogroups to UniProt accessions are available from https://github.com/skinnider/CF-MS-analysis/tree/master/data/resources/eggNOG. The phylogenetic tree used to group species into clades is also available from https://github.com/skinnider/CF-MS-analysis/tree/master/data/resources/TimeTree/species.nwk. The third and final directory, 'Human', contains the consensus CF-MS human interactome, in which proteins were merged across 46 human experiments by their gene names, rather than based on eggNOG orthogroups. The directory contains both complete classifier scores (file 'classifier-scores.tsv.gz') and the consensus CF-MS interactome, at 50% precision (file 'CF-MS-interactome.tsv').