cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.3525232
title: Biophysical models of persistent connectivity and barriers on the northern Mid-Atlantic Ridge

description: This contains four data files that are all matlab binary files (.mat) <strong>all_vent_sites.mat</strong> This is a Matlab data file containing the <strong>longitude (column 1)</strong>, <strong>latitude (column 2)</strong>, of all vent sites used in the simulations. Column 3 specifies whether a vent-site is a <strong>known vent site (=1)</strong> or a <strong>ghost vent-site (=0)</strong> <strong>probeData_20W60W_04S45N.mat</strong> This is a Matlab data file containing data on Argo probe cycles used to estimate average ocean currents that drive the particle tracking simulations. The variables in the file are: <strong>fl</strong> Argo float ID <strong>depth </strong>parking depth of the Argo float (m) <strong>longlatStart </strong>longitude and latitude for the start of one dive cycle <strong>longlatEnd </strong>longitude and latitude for the end of one dive cycle <strong>month</strong> month of the dive cycle <strong>year</strong> year of the dive cycle <strong>timeStep</strong> number of days between the start and end of a dive cycle <strong>distStep</strong> distance between the start and end positions of a cycle (km) <strong>velocity</strong> average velocity of the Argo float over one dive cycle (km/day) <strong>pos</strong> the mid-point position of the Argos float for each cycle <strong>vent_connectivity_data.mat</strong> This is a Matlab data file containing the connectivity data from the particle tracking simulations. The variables in this file are: <strong>bbox_all</strong> The coordinates for the 64 target boxes <strong>particleCount</strong> The number of larval particles starting in each of the 64 target boxes. This should be 100000 for all target boxes <strong>connectTime</strong> A 64x64x500 array giving number of particles making a connection between two target boxes. connectTime(i,j,t) = number of particles from box i that have passed though box j in a time &lt;= t. The 500 times correspond to the vector tVec. <strong>leaveTime </strong>A 64x500 array giving the time taken for particles to leave their initial target box. leaveTime(i,t) = number of particles starting in box i that leave the box in a time &lt;=t. The 500 times correspond to the vector tVec. <strong>C_critical </strong> Critical connection probability <strong>tVec</strong> A vector of simulation times. This should be 500 time points starting at day 1 up to day 500 <strong>tMax</strong> The maximum simulation time (days) <strong>sim_larval_dispersal.mat</strong> This is a Matlab data file that contains the dispersal distances of all the simulated larval particles for six planktonic larval durations. The variables in this file are: <strong>bbox_all </strong>The coordinates for the 64 target boxes <strong>tMax</strong> The maximum simulation time (days). This is the planktonic larval duration. <strong>distAll </strong>The dispersal distance (km) within a given planktonic larval duration (tMax) <strong>startAll</strong> The target box where a simulated larval particle started. The position of this box is given by bbox_all
DOI: 10.5281/zenodo.6333909
title: Kraken2 Database (Human, SARS-CoV2)

description: Version 1.0.0: Kraken2 Database built on human GRCH38.p13 and NCBI RefSeq genomes of SARS-CoV2 downloaded on 25.05.2020. Update 2.0.0: Kraken2 Database built on human GRCH38.p13 all GISAID SARS-CoV-2 Sequences available on 08 Feb 2021 that passed QC by https://gitlab.com/RKIBioinformaticsPipelines/president fixed typo in the file name Update 3.0.0 please refer for notes regarding database generation to the bundled README.md Kraken2 Database built on human GCF_000001405.39_GRCh38.p13, 10% of GISAID SARS-CoV-2 sequences available on 2022-02-07 that passed QC by https://gitlab.com/RKIBioinformaticsPipelines/president
DOI: 10.5281/zenodo.3854855
title: Kraken2 Database (Human, SARS-CoV2)

description: Version 1.0.0: Kraken2 Database built on human GRCH38.p13 and NCBI RefSeq genomes of SARS-CoV2 downloaded on 25.05.2020. Update 2.0.0: Kraken2 Database built on human GRCH38.p13 all GISAID SARS-CoV-2 Sequences available on 08 Feb 2021 that passed QC by https://gitlab.com/RKIBioinformaticsPipelines/president fixed typo in the file name Update 3.0.0 please refer for notes regarding database generation to the bundled README.md Kraken2 Database built on human GCF_000001405.39_GRCh38.p13, 10% of GISAID SARS-CoV-2 sequences available on 2022-02-07 that passed QC by https://gitlab.com/RKIBioinformaticsPipelines/president
DOI: 10.5281/zenodo.5733562
title: Table of SwissADME Analysis of Flavonoid Compounds

description: Tabulation of SwissADME Analysis for Journal Article: <em>In Silico Study</em> of Flavonoid Compound: Utilization of Molecular Simulation to Discover Drug Candidate for COVID-19
DOI: 10.5281/zenodo.5733561
title: Table of SwissADME Analysis of Flavonoid Compounds

description: Tabulation of SwissADME Analysis for Journal Article: <em>In Silico Study</em> of Flavonoid Compound: Utilization of Molecular Simulation to Discover Drug Candidate for COVID-19
DOI: 10.5281/zenodo.6333817
title: Chom18_AT

description: Data set for Chom18_AT
DOI: 10.5281/zenodo.6333816
title: Chom18_AT

description: Data set for Chom18_AT
DOI: 10.6084/m9.figshare.14102843
title: Supplemental Material | Human-level Ordinal Maintainability Prediction Based on Static Code Metrics

description: Supplemental Material for the paper <br>M<i>arkus Schnappinger, Arnaud Fietzke, and Alexander Pretschner. 2021. Human-level Ordinal Maintainability Prediction Based on Static Code Metrics. In Evaluation and Assessment in Software Engineering (EASE 2021). Association for Computing Machinery, New York, NY, USA, 160–169. DOI: https://doi.org/10.1145/3463274.3463315<br></i><br><br><b>Contents:</b><i>- </i>Complete list of all static metrics and used tools in <i>metrics.md</i><i>- C</i>omplete list of features ranked by their importance ranking (Table 2 in the paper) in <i>ranking.csv</i><br>- Exact configurations, i.e. hyper-parameters, preprocessing, selected features, used to achieve the reported results (Table 3 in the paper) in <i>configurations.csv</i><i><br></i><br>
DOI: 10.6084/m9.figshare.14102843.v2
title: Supplemental Material | Human-level Ordinal Maintainability Prediction Based on Static Code Metrics

description: Supplemental Material for the paper <br>M<i>arkus Schnappinger, Arnaud Fietzke, and Alexander Pretschner. 2021. Human-level Ordinal Maintainability Prediction Based on Static Code Metrics. In Evaluation and Assessment in Software Engineering (EASE 2021). Association for Computing Machinery, New York, NY, USA, 160–169. DOI: https://doi.org/10.1145/3463274.3463315<br></i><br><br><b>Contents:</b><i>- </i>Complete list of all static metrics and used tools in <i>metrics.md</i><i>- C</i>omplete list of features ranked by their importance ranking (Table 2 in the paper) in <i>ranking.csv</i><br>- Exact configurations, i.e. hyper-parameters, preprocessing, selected features, used to achieve the reported results (Table 3 in the paper) in <i>configurations.csv</i><i><br></i><br>
DOI: 10.6084/m9.figshare.14102843.v1
title: Supplemental Material | Human-level Ordinal Maintainability Prediction Based on Static Code Metrics

description: Supplemental Material for the paper "<i>Human-level Ordinal Maintainability Prediction Based on Static Code Metrics</i>" accepted at EASE'21, in press<br><br><b>Contents:</b><i>- </i>Complete list of all static metrics and used tools in <i>metrics.md</i><i>- C</i>omplete list of features ranked by their importance ranking (Table 2 in the paper) in <i>ranking.csv</i><br>- Exact configurations, i.e. hyper-parameters, preprocessing, selected features, used to achieve the reported results (Table 3 in the paper) in <i>configurations.csv</i><i><br></i><br>
DOI: 10.48370/ofd/o2a2ha/nxlvuk
title: m-1201.tif

description: :unav
DOI: 10.48370/ofd/o2a2ha/gho2u4
title: 1201.S3Dm

description: :unav
DOI: 10.48370/ofd/o2a2ha
title: Jamkówka rzędowa (Antrodia serialis (Fr.) Donk), 1201

description: Grzyby makromycetes
DOI: 10.6084/m9.figshare.19130645
title: EV charging model

description: Software and dataset used to synthesise residential EV charging schedules.
DOI: 10.13135/ela-323
title: Honours for Amyntor son of Demetrios
DOI: 10.48370/ofd/tx0lpc/xxht26
title: FMW_Daedalea_quercina_L_Pers_F_1210_3.JPG

description: Eksykat_makrofotografia
DOI: 10.48370/ofd/tx0lpc/60ysli
title: FMW_Daedalea_quercina_L_Pers_F_1210_2.JPG

description: Eksykat_makrofotografia
DOI: 10.48370/ofd/tx0lpc/kuz4tv
title: M-1210.jpg

description: :unav
DOI: 10.48370/ofd/tx0lpc/eaejws
title: FMW_Daedalea_quercina_L_Pers_F_1210_1.JPG

description: Eksykat_makrofotografia
DOI: 10.48370/ofd/tx0lpc/wvmiar
title: 1210_1.S3Dm

description: :unav
DOI: 10.48370/ofd/tx0lpc/ivg9kv
title: 1210_2.S3Dm

description: :unav
DOI: 10.48370/ofd/tx0lpc
title: Gmatwek dębowy (Daedalea quercina (L.) Pers.), 1210

description: Fungarium Makromycetes
DOI: 10.48370/ofd/imebol/1lubwz
title: m-1284.tif

description: :unav
DOI: 10.48370/ofd/imebol/o2rlkb
title: 1284.S3Dm

description: :unav
DOI: 10.48370/ofd/imebol
title: Wrośniaczek żelatynowaty (Cinereomyces lindbladii (Berk.) Jülich), 1284

description: Grzyby makromycetes
DOI: 10.5281/zenodo.6334123
title: Trialstreamer data

description: Trialstreamer annotated collection of RCTs. This respository contains baseline files (large), and subsequent updates (daily for PubMed, weekly for ICTRP).
DOI: 10.6084/m9.figshare.19316525
title: mol traj 2-propanol

description: MD trajectory
DOI: 10.6084/m9.figshare.19316525.v1
title: mol traj 2-propanol

description: MD trajectory
DOI: 10.5281/zenodo.6319952
title: CH4 isotopic signatures of emissions from oil and gas extraction sites in Romania

description: Dataset linked to the manuscript "CH4 isotopic signatures of emissions from oil and gas extraction sites in Romania", submitted to Elementa: Science of the Anthropocene. Abstract: Methane (CH4) emissions to the atmosphere from the oil and gas sector in Romania remain highly uncertain, despite their relevance for the European Union’s goals to reduce greenhouse gas emissions. Measurements of the isotopic composition of CH4 can be used for source attribution, which is important in top-down studies of emissions from extended areas. We performed isotope measurements of CH4 in atmospheric air samples collected from an aircraft (24 locations) and ground vehicles (83 locations), around oil and gas production sites in Romania, with focus on the Romanian Plain. Ethane to methane ratios (C2:C1) were derived at 412 locations of the same fossil fuel activity clusters. The resulting isotopic signals (δ13C and δ2H in CH4) covered a wide range of values, indicating mainly thermogenic gas sources (associated with oil production) in the Romanian Plain, mostly in Prahova county (δ13C from -67.8 to -22.4 per mille V-PDB; δ2H from -255 to -138 per mille V-SMOW) but also the presence of some natural gas reservoirs of microbial origin in Dolj, Ialomia, Prahova and likely Teleorman counties. The classification based on C2:C1 ratios was generally in agreement with the one based on CH4 isotopic composition, and confirmed the characterisation of the gas origin. In several cases, the CH4 enhancements sampled from the aircraft could directly be linked to the underlying production clusters using wind data. The combination of δ13C and δ2H signals determined on these samples confirm that the oil and gas production sector is the main source of CH4 emissions in the target areas.
DOI: 10.5281/zenodo.6319951
title: CH4 isotopic signatures of emissions from oil and gas extraction sites in Romania

description: Dataset linked to the manuscript "CH4 isotopic signatures of emissions from oil and gas extraction sites in Romania", submitted to Elementa: Science of the Anthropocene. Abstract: Methane (CH4) emissions to the atmosphere from the oil and gas sector in Romania remain highly uncertain, despite their relevance for the European Union’s goals to reduce greenhouse gas emissions. Measurements of the isotopic composition of CH4 can be used for source attribution, which is important in top-down studies of emissions from extended areas. We performed isotope measurements of CH4 in atmospheric air samples collected from an aircraft (24 locations) and ground vehicles (83 locations), around oil and gas production sites in Romania, with focus on the Romanian Plain. Ethane to methane ratios (C2:C1) were derived at 412 locations of the same fossil fuel activity clusters. The resulting isotopic signals (δ13C and δ2H in CH4) covered a wide range of values, indicating mainly thermogenic gas sources (associated with oil production) in the Romanian Plain, mostly in Prahova county (δ13C from -67.8 to -22.4 per mille V-PDB; δ2H from -255 to -138 per mille V-SMOW) but also the presence of some natural gas reservoirs of microbial origin in Dolj, Ialomia, Prahova and likely Teleorman counties. The classification based on C2:C1 ratios was generally in agreement with the one based on CH4 isotopic composition, and confirmed the characterisation of the gas origin. In several cases, the CH4 enhancements sampled from the aircraft could directly be linked to the underlying production clusters using wind data. The combination of δ13C and δ2H signals determined on these samples confirm that the oil and gas production sector is the main source of CH4 emissions in the target areas.
DOI: 10.5281/zenodo.6334068
title: Data related to the manuscript "Sequence-specific aggregation of magnetic nanoparticles and single-stranded DNA amplification products for detection of antibiotic resistance gene sul1."

description: Absorbance and AC susceptometry raw and processed excel files used.
description: Work funded by the Uppsala Antibiotic Center
DOI: 10.5281/zenodo.6334067
title: Data related to the manuscript "Sequence-specific aggregation of magnetic nanoparticles and single-stranded DNA amplification products for detection of antibiotic resistance gene sul1."

description: Absorbance and AC susceptometry raw and processed excel files used.
description: Work funded by the Uppsala Antibiotic Center
DOI: 10.6084/m9.figshare.19316528.v1
title: just molecule 2-propanol

description: just a molecule
DOI: 10.6084/m9.figshare.19316528
title: just molecule 2-propanol

description: just a molecule
DOI: 10.5281/zenodo.5025801
title: Datasets for "A unified framework to estimate the origins of atmospheric moisture and heat using Lagrangian models"

description: This repository contains the post-processed model outputs from HAMSTER v1.2.0 as used in the following paper: Keune, J., Schumacher, D. L., and Miralles, D. G.: A unified framework to estimate the origins of atmospheric moisture and heat using Lagrangian models, Geosci. Model Dev., 15, 1875–1898, https://doi.org/10.5194/gmd-15-1875-2022, 2022.<br> <br> The data set contains (1) global validation statistics for the three fluxes (evaporation, precipitation, sensible heat), and (2) the climatological source regions of precipitation and heat for Denver, Beijing and Windhoek. The former are found in the directory 'validation/global', and the latter are found in the directories '1001' (Denver), '3001' (Beijing) and '5002' (Windhoek). Multiple experiments were performed to assess the uncertainty of the source regions. Thus, multiple files exist, that show the same variables but for multiple experiments (indicated by the names "ALLPBL", "RH-10-20", "SOD08-SCH19", "SCH20", "FAS19" in the file name). For the moisture source regions, the uncertainty of the attribution methodology was assessed; these are indicated by the different folders, i.e. 'linear_upscaled' and 'random2_upscaled'. For each city and each experiment, the climatologically averaged source regions ('_mean.nc') and the climatologically averaged individual backward day contributions ('_bwmean.nc') are provided. Data sets are in the netCDF format and contain metadata following the CF convention.
description: If you use this data, please cite this paper: Keune, J., Schumacher, D. L., and Miralles, D. G.: A unified framework to estimate the origins of atmospheric moisture and heat using Lagrangian models, Geosci. Model Dev., 15, 1875–1898, https://doi.org/10.5194/gmd-15-1875-2022, 2022.
description: {"references": ["Keune, J., Schumacher, D. L., and Miralles, D. G.: A unified framework to estimate the origins of atmospheric moisture and heat using Lagrangian models, Geosci. Model Dev., 15, 1875\u20131898, https://doi.org/10.5194/gmd-15-1875-2022, 2022."]}
DOI: 10.5281/zenodo.6334145
title: testData

description: This is just a dummy dataset to test the access-right functionality since the information in the FAQ is not clear if it is possible to change the access. Also, the Zenodo Sandbox is not available.
DOI: 10.5281/zenodo.6334144
title: testData

description: This is just a dummy dataset to test the access-right functionality since the information in the FAQ is not clear if it is possible to change the access. Also, the Zenodo Sandbox is not available.
DOI: 10.5281/zenodo.6327062
title: WIld boar demographic parameters extracted from the literature

description: This is the data extraction and description of parameters of WB population dynamics, including general drivers, population demography, mortality, reproduction, and spatial behaviour. The definition of the most relevant parameters that describe the wild boar (WB) population dynamics is essential to guide African swine fever (ASF) control policies. These parameters should be framed considering different contexts, such as geographic, ecological and management contexts, and gaps of data useful for the parameter definition should be identified. This information would allow better harmonized monitoring of WB populations and higher impact of ASF management actions, as well as better parametrizing population dynamics and epidemiological models, which is key to develop more efficient cost-benefit strategies. ENETwild is a project funded by EFSA, www.enetwild.com.
description: EU; xlsx; biohaw@efsa.europa.eu
DOI: 10.5281/zenodo.6327060
title: WIld boar demographic parameters extracted from the literature

description: This is the data extraction and description of parameters of WB population dynamics, including general drivers, population demography, mortality, reproduction, and spatial behaviour. The definition of the most relevant parameters that describe the wild boar (WB) population dynamics is essential to guide African swine fever (ASF) control policies. These parameters should be framed considering different contexts, such as geographic, ecological and management contexts, and gaps of data useful for the parameter definition should be identified. This information would allow better harmonized monitoring of WB populations and higher impact of ASF management actions, as well as better parametrizing population dynamics and epidemiological models, which is key to develop more efficient cost-benefit strategies. ENETwild is a project funded by EFSA, www.enetwild.com.
description: EU; xlsx; biohaw@efsa.europa.eu
DOI: 10.5517/ccdc.csd.cc277m04
title: CCDC 2062895: Experimental Crystal Structure Determination

description: Related Article: Marvin Sindlinger, Markus Ströbele, Cäcilia Maichle-Mössmer, Holger F. Bettinger|2022|Chem.Commun.|58|2818|doi:10.1039/D1CC06588B
DOI: 10.6084/m9.figshare.19316557.v1
title: Matlab bundle from Physics-inspired analysis of the two-class income distribution in the USA in 1983–2018

description: This zip file contains the data and the Matlab scripts for data analysis and generation of figures.
DOI: 10.6084/m9.figshare.19316557
title: Matlab bundle from Physics-inspired analysis of the two-class income distribution in the USA in 1983–2018

description: This zip file contains the data and the Matlab scripts for data analysis and generation of figures.
DOI: 10.22008/fk2/x9u5bf/xlokdd
title: G500_Sheet3_Søndre_Strømfjord_Nuussuaq_2nd_400dpi.tif

description: :unav
DOI: 10.3886/e164121
title: Audit Evidence

description: This data set has responses from 400 auditors
DOI: 10.3886/e164121v1
title: Audit Evidence

description: This data set has responses from 400 auditors
DOI: 10.5519/qd.s5ufrqhp
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (1703 records)
DOI: 10.5281/zenodo.5865069
title: Primary Studies

description: List of primary studies analysed in an IRR study on ML testing
DOI: 10.5281/zenodo.6334231
title: Video Games Bad Smells: What they are and how Developers Perceive Them - Online dataset

description: This artifact contains the online replication package of the manuscript "Video Games Bad Smells: What they are and how Developers Perceive Them"
DOI: 10.21227/0d10-nm73
title: Quantification of Well Clear for autonomous small UAS

description: There are three data sets, corresponding to analysis found on this manuscript "Quantification of Well Clear for autonomous small UAS". 1. final_results.dat - it contains sUAS flight encounters, with different well clear thresholds, but with the same alerting time thresholds. 2. al_resluts.dat - it contains sUAS flight encounters, with same well clear thresholds, but with different alerting time thresholds
DOI: 10.5281/zenodo.6334235
title: DevOps: is there a gap between Education and Industry?

description: This is the dataset obtained from a survey with 99 respondents about the teaching or use of DevOps technological practices in Higher-Educatoin or Industry, respectively. Questions are tabbled in the first line, and results of this study are published in the following Reference:
DOI: 10.5281/zenodo.6334234
title: DevOps: is there a gap between Education and Industry?

description: This is the dataset obtained from a survey with 99 respondents about the teaching or use of DevOps technological practices in Higher-Educatoin or Industry, respectively. Questions are tabbled in the first line, and results of this study are published in the following Reference: