cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5445/ir/1000136285
title: Fuel Cells and Hydrogen Joint Undertaking (FCH JU)

description: Work package five of the PRESLHY project focusses on the combustion phenomena of liquid hydrogen (LH 2 ). The experimental programme was designed to provide insight into a number of credible and poorly understood LH 2 combustion scenarios. One such scenario is the effect of congestion or confinement on an ignited hydrogen cloud stemming from a release of LH 2 , potentially leading to deflagration to detonation transition (DDT). This report summarises the large-scale experiments carried out at the HSE Science and Research Centre in Buxton investigating the effect of differing levels of congestion and confinement on the combustion properties of a hydrogen cloud developing from a release of LH2. Various combustion parameters were measured, including; the overpressure, heat flux, and noise. Monitoring of ambient and release conditions were also made to allow for a thorough analysis of the results. A total of 23 ignited trials were completed and involved releasing LH2 using the same initial conditions as in the rainout experiments of work package 3, meaning that the dispersion patterns should remain similar. The congestion and confinement was created by a configurable steel structure placed directly in the path of the release. Two congestion levels, confinement and pool experiments were planned, however due to the safe noise level being reached, only the congestion experiments were completed. To compensate for this, multiple repeats and experiments with a wide variety of source conditions were conducted. From the results, it is clear that higher levels of volumetric congestion increases the measured overpressures in releases with the same initial conditions. The results also show that an increasing hydrogen inventory, either through an increased release pressure or larger nozzle, can result in a larger event upon ignition. However, the mixing of the jet also plays a part; some releases through the largest release orifice diameter showed lower overpressures potentially due to the hydrogen cloud being too rich. It was observed that the ambient conditions, in particular the wind speed and direction, were a significant factor in the outcome of each ignition. This was particularly prominent in trials 21 to 23.
DOI: 10.21227/6ckb-j053
title: Shallow depth of field image dataset for image sharpness and fitting results of BPBD and other algorithms

description: We provide two folders: (1)The shallow depth of field image data set folder consists of 27 folders from 1 to 27. In folder 1-27, each folder contains two test images and two word files. Img1 is the shallow depth of field image with the best focusing state taken with a 300 mm long focal lens, and img2 is the overall blurred image. The example to the weakness of the state-of-the-art methods word file shows the evaluation results and failure of various algorithms, and the subjective scoring results word file shows the results of the subjective evaluation of 30 volunteers.(The subjective test process, in which evaluation attribute is set to sharpness, strictly adheres to the Performance Methods in Stimulus-comparison Methods (SC) in ITU-R BT.500-14, and the observer’s task is to judge which one is the sharper from two pictures in each group. The sharper picture is marked as 1 and the less one is marked as 0.)(2)The fitting results of various algorithms(include our proposed metric BPBD) folder contains six folders showing the fitting results on TID2008, TID2013, LIVE, CID2013, FocusPath and CSIQ.
DOI: 10.6084/m9.figshare.14301282.v1
title: Community Participation of School-Age Children: Who is at Risk of Restricted Participation?

description: This study aimed to identify children with restricted community participation and examine the extent to which the child, family, and environmental factors were associated with restricted participation. A school-based sample of 92 children with disabilities and 391 children without disabilities aged 5–12 years was recruited in Hong Kong. Parents completed the Participation and Environment Measure for Children and Youth and a demographic questionnaire. Moreover, children completed the Children’s Depression Inventory. Rasch analysis was used to determine the criteria that differentiated between children with and without participation restriction, based on frequency of activities. Logistic regression was used to identify the factors associated with participation restriction. One hundred seventy-three children (35.8% of the sample), including 42 with disabilities, were identified as having restricted participation. Participation restriction was associated with higher depressive symptoms in children (odds ratio (OR) = 1.05, 95% confidence interval (CI) [1.01, 1.08]), lower environmental resources (OR = 0.97, 95% CI [0.96, 0.99]), and coming from families with three or more children (OR = 2.80, 95% CI [1.44, 5.46]). The results suggest that a sizable number of children are at risk for restricted participation in the community. Healthcare services and strategies that address the associated factors are needed to promote children’s community participation.
DOI: 10.6084/m9.figshare.14301282
title: Community Participation of School-Age Children: Who is at Risk of Restricted Participation?

description: This study aimed to identify children with restricted community participation and examine the extent to which the child, family, and environmental factors were associated with restricted participation. A school-based sample of 92 children with disabilities and 391 children without disabilities aged 5–12 years was recruited in Hong Kong. Parents completed the Participation and Environment Measure for Children and Youth and a demographic questionnaire. Moreover, children completed the Children’s Depression Inventory. Rasch analysis was used to determine the criteria that differentiated between children with and without participation restriction, based on frequency of activities. Logistic regression was used to identify the factors associated with participation restriction. One hundred seventy-three children (35.8% of the sample), including 42 with disabilities, were identified as having restricted participation. Participation restriction was associated with higher depressive symptoms in children (odds ratio (OR) = 1.05, 95% confidence interval (CI) [1.01, 1.08]), lower environmental resources (OR = 0.97, 95% CI [0.96, 0.99]), and coming from families with three or more children (OR = 2.80, 95% CI [1.44, 5.46]). The results suggest that a sizable number of children are at risk for restricted participation in the community. Healthcare services and strategies that address the associated factors are needed to promote children’s community participation.
DOI: 10.5281/zenodo.4739393
title: Dataset: Comparative analysis of the coordinated motion of Hsp70s from different organelles observed by single molecule three-color FRET

description: Dataset: Comparative analysis of the coordinated motion of Hsp70s from different organelles observed by single molecule three-color FRET
DOI: 10.5281/zenodo.4739392
title: Dataset: Comparative analysis of the coordinated motion of Hsp70s from different organelles observed by single molecule three-color FRET

description: Dataset: Comparative analysis of the coordinated motion of Hsp70s from different organelles observed by single molecule three-color FRET
DOI: 10.6084/m9.figshare.15172407.v1
title: data

description: data of article"Effects of γ-ray irradiation on expression levels and activities of cytochrome P450 2E1, oxidative stress and apoptosis in rat liver"<br>
DOI: 10.6084/m9.figshare.15172407
title: data

description: data of article"Effects of γ-ray irradiation on expression levels and activities of cytochrome P450 2E1, oxidative stress and apoptosis in rat liver"<br>
DOI: 10.6084/m9.figshare.11303372.v1
title: Intracranial aneurysm genome-wide association study summary statistics 2020

description: <b>Summary statistics of a genome-wide association study of intracranial aneurysms in 10,754 cases and 306,882 controls.</b><b><br></b><b>Dataset described in: </b>Genome-wide association study of intracranial aneurysms identifies 17 risk loci and genetic overlap with clinical risk factors<b><br></b>Bakker, M.K. et alNature Genetics, 16 November 2020doi: 10.1038/s41588-020-00725-7https://www.nature.com/articles/s41588-020-00725-7<br><b><br></b>The study consisted of 2 stages. Stage 1: European ancestry only. Stage 2: European and East Asian ancestry.Extra files:-Association statistics of the East Asian subset only.-Association statistics of only aneurysmal subarachnoid hemorrhage versus controls-Association statistics of only unruptured intracranial aneurysms versus controls<br>Please check the <b>Data Access Policy</b> for further information regarding data use, access and options for additional analyses.
DOI: 10.6084/m9.figshare.15169914.v2
title: Source Data for Histone Modification Imaging Using Plasmonic Nanoparticles

description: Data hat support the findings of the paper named "High-Spatial and Colourimetric Imaging of Histone Modifications in Single Senescent Cells Using Plasmonic Nanoprobes".
DOI: 10.6084/m9.figshare.15169914.v3
title: Source Data for Histone Modification Imaging Using Plasmonic Nanoparticles

description: Data hat support the findings of the paper named "High-Spatial and Colourimetric Imaging of Histone Modifications in Single Senescent Cells Using Plasmonic Nanoprobes".
DOI: 10.5281/zenodo.5204502
title: MigrationsKB: A Knowledge Base of Public Attitudes towards Migrations and their Driving Factors

description: <strong>MigrationsKB(MGKB)</strong> is a public Knowledge Base of anonymized <strong>Migration</strong> related <strong>annotated</strong> tweets. The MGKB currently contains over <strong>200 thousand</strong> tweets, spanning over 9 years (January 2013 to July 2021), filtered with 11 European countries of <em>the United Kingdom, Germany, Spain, Poland, France, Sweden, Austria, Hungary, Switzerland, Netherlands and Italy</em>. <strong>Metadata</strong> information about the tweets, such as Geo information (<strong>place name</strong>, <strong>coordinates</strong>, <strong>country code</strong>). <strong>MGKB</strong> contains <strong>entities</strong>, <strong>sentiments</strong>, <strong>hate speeches</strong>, <strong>topics</strong>, <strong>hashtags</strong>, <em>encrypted user mentions</em> in RDF format. The schema of <strong>MGKB</strong> is an extension of TweetsKB for migrations related information. Moreover, to associate and represent the potential economic and social factors driving the migration flows such as <strong>eurostat</strong>, <strong>statista</strong>, etc. FIBO ontology was used. The extracted <strong>economic indicators</strong>, such as GDP Growth Rate, are connected with each Tweet in RDF using geographical and temporal dimensions. The user IDs and the tweet texts are encrypted for privacy purposes, while the tweet IDs are preserved.
DOI: 10.6084/m9.figshare.15172389
title: Raw data and statistical analysis pertaining to use of alteplase in COVID 19

description: Raw data and statistical analysis pertaining to use of alteplase in COVID 19
DOI: 10.6084/m9.figshare.15172389.v2
title: Raw data and statistical analysis pertaining to use of alteplase in COVID 19

description: Raw data and statistical analysis pertaining to use of alteplase in COVID 19
DOI: 10.6084/m9.figshare.15172389.v1
title: Raw data and statistical analysis pertaining to use of alteplase in COVID 19

description: Raw data and statistical analysis pertaining to use of alteplase in COVID 19
DOI: 10.5281/zenodo.5205426
title: Sediment routing and anthropogenic impact in the Huanghe River catchment, China: an investigation using Nd isotopes of river sediments

description: Table A1. Sampling locations, Sr-Nd isotopes, geochemical compositions and grain size parameters of Huanghe and loess sediments investigated. Table A2. Annual sediment load (Mt/yr) at major gauging stations along the Huanghe mainstream. Table A3. Nd isotopic compositions of major tectonic terranes and sources in the Huanghe basin (literature data). Table A4. Nd isotopes and geochemical compositions of rocks in the North China Craton. Table A5. Nd model ages of rocks from North China Craton (NCC), only rocks with Th/Sc, Th/Cr, Th/Co and Sm/Nd ratios within the range of references for NCC-UC have been selected. Table A6. Nd isotopes mixing of sediments from the lower Huanghe.
DOI: 10.5281/zenodo.5205425
title: Sediment routing and anthropogenic impact in the Huanghe River catchment, China: an investigation using Nd isotopes of river sediments

description: Table A1. Sampling locations, Sr-Nd isotopes, geochemical compositions and grain size parameters of Huanghe and loess sediments investigated. Table A2. Annual sediment load (Mt/yr) at major gauging stations along the Huanghe mainstream. Table A3. Nd isotopic compositions of major tectonic terranes and sources in the Huanghe basin (literature data). Table A4. Nd isotopes and geochemical compositions of rocks in the North China Craton. Table A5. Nd model ages of rocks from North China Craton (NCC), only rocks with Th/Sc, Th/Cr, Th/Co and Sm/Nd ratios within the range of references for NCC-UC have been selected. Table A6. Nd isotopes mixing of sediments from the lower Huanghe.
DOI: 10.6084/m9.figshare.12966971.v1
title: Orthogroup functional annotations and effector candidates

description: Functional annotations of all predicted proteins in a <i>Parastagonospora nodorum</i> pangenome.<br>Orthogroups were predicted using OrthoFinder, each gene is annotated with the P. nodorum isolate that it is predicted in and the orthogroup that it belongs to.<br>Predicted whole protein functions were found by searching the Swiss-Prot database version 2020_02 (Bairoch & Apweiler, 2000) using MMSeqs2 version 11-e1a1c (--start-sens 3 -s 7.5 --sens-steps 3 -a) (Steinegger & Söding, 2017). Matches were considered reliable for functional annotation if they covered &gt;= 70% of both sequences, with &gt;=60% sequence identity, and an e-value &lt; 1e-10. Functional domains were predicted using InterProScan (P. Jones et al., 2014; Mitchell et al., 2019). Additionally, GO-terms and predicted product names were predicted using the web-servers of PANNZER (Koskinen et al., 2015) and eggNOG-Mapper (Huerta-Cepas et al., 2017). GO-term predictions from InterProScan, PANNZER, and eggNOG-Mapper were combined and filtered to exclude terms in the GO do_not_annotate “anti-slim” set (available at: http://geneontology.org/docs/download-ontology, downloaded: 2020-05-15) to remove uninformative terms, forming the final GO-term set for the predicted proteomes.<br>Effector-like sequences were predicted using the Predector pipeline (https://github.com/ccdmb/predector, version: 0.1.0-alpha) (Submitted), which incorporates several software analyses including SignalP versions 3.0, 4.1g, 5.0b (José Juan Almagro Armenteros et al., 2019; Dyrløv Bendtsen et al., 2004; Petersen et al., 2011), DeepSig (Savojardo et al., 2018), TargetP version 2.0 (Jose Juan Almagro Armenteros et al., 2019), DeepLoc version 1.0 (Almagro Armenteros et al., 2017), TMHMM version 2.0c (Krogh et al., 2001), Phobius version 1.01 (Käll et al., 2004), EffectorP versions 1 and 2 (Sperschneider et al., 2016; Sperschneider, Dodds, Gardiner, et al., 2018), ApoplastP version 1 (Sperschneider, Dodds, Singh, et al., 2018), LOCALIZER (Sperschneider et al., 2017), homology searches against dbCAN version 8 using HMMER version 3.3 (Mistry et al., 2013), and sequence matches against PHI-base version 4.9 (Urban et al., 2020) using MMSeqs2 version 11.e1a1c (Steinegger & Söding, 2017).Information from Predector, InterProScan, Pannzer, eggNOG-mapper, positive selection and orthogroup analyses were combined into a single table.
DOI: 10.21227/h2mz-0g54
title: Convergence analysis of the Decomposition-Iteration algorithm

description: Convergence analysis of the Decomposition-Iteration algorithm.
DOI: 10.5281/zenodo.5205444
title: Data and scripts for the preprint gmd-2021-95 (a revised verison)

description: The datasets and Matlab scripts we upload at Zenodo on 2021-07-02 are for the reproduction of our manuscript (a revised version of the preprint gmd-2021-95) submitted to Geoscientific Model Development for possible publication. This is a model evaluation paper. We downloaded the original data kindly provided by the The UK Meteorological Office (EN4.2.1) and JAMSTEC (OFES1 and OFES2). These original data are monthly values and we calculated the annual mean fields (the archived data). The uploaded data included the zonal, meridional and vertical velocities (not for the EN4); and also the potential temperature and salinity data. We also included some grid files for the calculation of OHC or other variables in our manuscript. These data are suggested to be used only to reproduce the results in our submitted revision of the preprint gmd-2021-95. The readers can also access the original data as follows. Limited by the local network connection, we have to separate all the datasets into a couple of folders to successfully upload. Note: the original monthly EN4.2.1 data is downloaded from: https://www.metoffice.gov.uk/hadobs/en4/download-en4-2-1.html the original monthly OFES1 data is downloaded from: http://apdrc.soest.hawaii.edu/dods/public_ofes/OfES/ncep_0.1_global_mmean; the original monthly OFES2 data is downloaded from (temporarily suspended): http://www.jamstec.go.jp/esc/fes/dods/OFES2/Monthly/
DOI: 10.5281/zenodo.5055696
title: Data and scripts for the preprint gmd-2021-95 (a revised verison)

description: The datasets and Matlab scripts we upload at Zenodo on 2021-07-02 are for the reproduction of our manuscript (a revised version of the preprint gmd-2021-95) submitted to Geoscientific Model Development for possible publication. This is a model evaluation paper. We downloaded the original data kindly provided by the The UK Meteorological Office (EN4.2.1) and JAMSTEC (OFES1 and OFES2). These original data are monthly values and we calculated the annual mean fields (the archived data). The uploaded data included the zonal, meridional and vertical velocities (not for the EN4); and also the potential temperature and salinity data. We also included some grid files for the calculation of OHC or other variables in our manuscript. These data are suggested to be used only to reproduce the results in our submitted revision of the preprint gmd-2021-95. The readers can also access the original data as follows. Limited by the local network connection, we have to separate all the datasets into a couple of folders to successfully upload. Note: the original monthly EN4.2.1 data is downloaded from: https://www.metoffice.gov.uk/hadobs/en4/download-en4-2-1.html the original monthly OFES1 data is downloaded from: http://apdrc.soest.hawaii.edu/dods/public_ofes/OfES/ncep_0.1_global_mmean; the original monthly OFES2 data is downloaded from (temporarily suspended): http://www.jamstec.go.jp/esc/fes/dods/OFES2/Monthly/
DOI: 10.5281/zenodo.5148302
title: Database 'Documents of Ancient Greek Music' (dDAGM)

description: This database, created by Dr Tosca A.C. Lynch (https://oxford.academia.edu/ToscaLynch), includes all the notes attested in the ancient Greek musical documents collected in the standard edition <em>DAGM</em> (Pöhlmann, E. and West, M.L., 2001, <em>Documents of Ancient Greek Music</em>, Oxford: OUP). Dr Lynch will present historically informed interpretations of these data in a series of articles devoted, respectively, to: –the Classical/Hellenistic harmonic system and the relative documents (marked as BC in this database); –the Imperial harmonic system and the relative documents (marked as AD in this database)Dubious readings follow Pöhlmann and West; DAGM 17-18 are grouped with Imperial documents, as discussed in the articles. <br> This Database Documents of Ancient Greek Music is licensed by Tosca A.C. Lynch under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License for academic research purposes (https://creativecommons.org/licenses/by-nc-nd/4.0/). <br> <br> The Greek musical notation fonts used in <em>dDAGM</em> have been designed by Stefan Hagel (Austrian Academy of Sciences, Vienna).<br> <br> Please contact Dr Lynch if you have further questions on this database, its use or related matters, or if you find any typos.
DOI: 10.6084/m9.figshare.14192090
title: Sequence Assembly and Base composition

description: The complete mitochondrial genome of Conaspida wangi (Wei, 2015)<br>Base composition table<br><br>
DOI: 10.6084/m9.figshare.14192090.v1
title: Sequence Assembly and Base composition

description: The complete mitochondrial genome of Conaspida wangi (Wei, 2015)<br>Base composition table<br><br>
DOI: 10.6084/m9.figshare.14192063
title: Bankit

description: Sqn<br>Biosample tableSRA table
DOI: 10.6084/m9.figshare.14192063.v1
title: Bankit

description: Sqn<br>Biosample tableSRA table
DOI: 10.6084/m9.figshare.14192057.v1
title: Tree_IQtree

description: IQTREE_13PCG
DOI: 10.6084/m9.figshare.11303372.v2
title: Intracranial aneurysm genome-wide association study summary statistics 2020

description: <b>Summary statistics of a genome-wide association study of intracranial aneurysms in 10,754 cases and 306,882 controls.</b><b><br></b><b>Dataset described in: </b>Genome-wide association study of intracranial aneurysms identifies 17 risk loci and genetic overlap with clinical risk factors<b><br></b>Bakker, M.K. et alNature Genetics, 16 November 2020doi: 10.1038/s41588-020-00725-7https://www.nature.com/articles/s41588-020-00725-7<br><b><br></b>The study consisted of 2 stages. Stage 1: European ancestry only. Stage 2: European and East Asian ancestry.Extra files:-Association statistics of the East Asian subset only.-Association statistics of only aneurysmal subarachnoid hemorrhage versus controls-Association statistics of only unruptured intracranial aneurysms versus controls-Association statistics excluding the UK Biobank (4 files): Stage 1 excluding UK Biobank, Stage 2 excluding UK Biobank, European-only aSAH-only excluding UK Biobank, and cross-ancestry aSAH-only excluding UK Biobank.<br>Please check the <b>Data Access Policy</b> for further information regarding data use, access and options for additional analyses.
DOI: 10.6084/m9.figshare.14192057
title: Tree_IQtree

description: IQTREE_13PCG
DOI: 10.6084/m9.figshare.14191937
title: Data Matix_34_13NN

description: 34taxa13NNaligned with transXConcatenate with Phylosuite
DOI: 10.6084/m9.figshare.14191937.v1
title: Data Matix_34_13NN

description: 34taxa13NNaligned with transXConcatenate with Phylosuite
DOI: 10.5281/zenodo.5090497
title: Global variation in the fraction of leaf nitrogen allocated to photosynthesis

description: ReadMe 1. The datasets were produced based on the method described in Luo X. et al. Global variation in the fraction of leaf nitrogen allocated to photosynthesis. Nature Communications. doi: 10.1038/s41467-021-25163-9. 2. Vcmax25_RF and fLNR_RF are the key output. Vcmax25_RF was estimated using random forest trained by ground observations, remote sensing leaf chlorophyll content and some ancillary environment variables. fLNR_RF was further calculated from Vcmax25_RF. 3. Vcmax25_un and fLNR_un are the uncertainties of Vcmax25_RF and fLNR_RF. 4. Note there are several gridded leaf nitrogen content maps (LNC; area-based) available for our derivation of fLNR from Vcmax25. In our study, we mainly use EB17, but also provide the results based on AMM18 and CB20 (see reference). 5. Other Vcmax25 and fLNR datasets are provided for comparison. They are all driven by CRU TS4.01 climate data, soil grids soil data and EB17 leaf nitrogen/phosphorus datasets. If you have any questions about the dataset, please contact Xiangzhong (Remi) Luo at xzluo.remi@nus.edu.sg