cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.6588626
title: Efficient Probabilistic Prediction and Uncertainty Quantification of Tropical Cyclone-driven Storm Tides and Inundation: Model Data and Analysis Code

description: This repository contains model data and analysis codes related to the manuscript entitled "Efficient Probabilistic Prediction and Uncertainty Quantification of Tropical Cyclone-driven Storm Tides and Inundation", as follows: Model data are maximum water surface elevations of ensemble 48-hr forecast ADCIRC model simulations for three historical US landfalling hurricanes: 2017 Irma, 2018 Florence, and 2020 Laura. These are located in the "NameYYYY_Results.tar" archive files as "maxele.63.nc" files. Also included in the tar files are the hurricane forecast track files in Automated Tropical Cyclone Forecasting (ATCF) system format (*.22) and the error variable parameters (*.json) for each forecast. Model data of best-track runs for the 2017 Irma, 2018 Florence, and 2020 Laura hurricanes, and astronomical tide-only runs for the corresponding time periods are located in the "NameYYYY_besttrack+tides.tar" archive files. Both the maximum water surface elevations "maxele.63.nc" and the time series of water surface elevations "fort.63.nc" are included. ADCIRC input mesh (*.14) and mesh property files (*.13) are included in "ADCIRC_mesh_files.zip". Joint Karhunen-Loeve Polynomial Chaos (KL-PC) analysis python scripts with and without considering inundation are located in "klpc_analysis_scripts.zip". Requires EnsemblePerturbation python toolbox. Python scripts for analyzing and plotting the KL-PC results (Figures 6-14 and Table 1 in the manuscript) are located in "results_plotting_scripts.zip". Requires EnsemblePerturbation python toolbox.
description: {"references": ["Pringle, W. J., Burnett, Z., Sargsyan, K., Moghimi, S., & Myers, E. (2023). Efficient Probabilistic Prediction and Uncertainty Quantification of Tropical Cyclone-driven Storm Tides and Inundation. Artificial Intelligence for the Earth Systems, 2. https://doi.org/10.1175/AIES-D-22-0040.1"]}
DOI: 10.17043/oden-ryder-2019-bathymetry-1
title: High-resolution bathymetry from the Ryder 2019 expedition to Northwest Greenland
DOI: 10.17043/oden-ryder-2019-ctd-1
title: Oceanographic CTD data from the Ryder 2019 expedition
DOI: 10.17043/oden-ryder-2019-ladcp-1
title: Oceanographic LADCP data from the Ryder 2019 expedition
DOI: 10.5066/p95ce4oj
title: Geochemical data for waters, rocks, sediments and biofilms from Rio Tinto, Spain

description: Rio Tinto, Spain, is an example of a fluvial system strongly influenced by acid rock and acid mine drainage. During the spring of 2018 and 2019, samples of stream waters and mine waters, biofilms, sediments and rocks, were collected in the field by Aubrey Zerkle. These samples were analyzed for comprehensive geochemistry, including Cr isotope geochemistry, anions and cations. Mineralogical analysis was conducted on powdered sediments and rocks.
DOI: 10.5281/zenodo.3956587
title: S71 | CECSCREEN | HBM4EU CECscreen: Screening List for Chemicals of Emerging Concern Plus Metadata and Predicted Phase 1 Metabolites

description: This is the collection associated with list S71 CECSCREEN HBM4EU CECscreen: Screening List for Chemicals of Emerging Concern Plus Metadata and Predicted Phase 1 Metabolites<strong> </strong>on the NORMAN Suspect List Exchange. https://www.norman-network.com/nds/SLE/ CECScreen is part of the HBM4EU project (coord. UBA) &gt; WP16 "emerging chemicals" (lead INRA, JP Antignac/L Debrauwer) &gt; Task 16.1 (lead IRAS, J Vlanderen / R Vermeulen) &gt; Main contributor (J Meijer) &gt; Involved Partners (M Lamoree, T Hamers, S Hutinet, A, Covaci, C Huber, M Krauss, DI Walker, EL Schymanski). Further details in Meijer et al (submitted). Dataset DOI: 10.5281/zenodo.3956586.
DOI: 10.5281/zenodo.7865503
title: Temperature and salinity data from KH-15-4, KS-18-1, and KS-19-19 cruises

description: Data used in ``Salt-fingering under the thermal-wind and lateral shears in the Kuroshio fronts" published in Journal of Geophysical Research Oceans
DOI: 10.14459/2021mp1620140
title: How atmospheric conditions affect degradation mechanisms of high-efficiency perovskite solar cells

description: Supporting data from the above publication, including numerical source data files as the xlsx format, and image source data as jpg or tif format. Data underlying each Figure in the paper and the supplementary file are included and named as they are. The individual data behind the average values and raw data generated at the Deutsches Elektronen-Synchrotron radiation facility is included in the Image source data Fig. 2 file.
DOI: 10.5281/zenodo.7620956
title: Data related to carbon flux footprints

description: Data related to carbon flux footprints Researchers should preferably obtain access by making a data request at the Semi‐Arid Climate and Environment Observatory of Lanzhou University (SACOL; http://climate.lzu.edu.cn/English/Data_Sharing/LACMS_data.htm)
DOI: 10.34740/kaggle/dsv/6051244
title: AutoXGB
DOI: 10.57745/tp5mef
title: 31P-NMR_OL_Flax_2020-01.tif

description: This file contains the 31P NMR spectrum of OL_Flax_2020-01.
DOI: 10.57745/gbw48l
title: 31P-NMR_OL_Pine_2017.tif

description: This file contains the 31P NMR spectrum of OL_Pine_2017.
DOI: 10.57745/mhy76a
title: 31P-NMR_OL_Flax_2020-02.tif

description: This file contains the 31P NMR spectrum of OL_Flax_2020-02.
DOI: 10.57745/izqc9h
title: 31P-NMR_OL_Switchgrass_2018.tif

description: This file contains the 31P NMR spectrum of OL_Switchgrass_2018.
DOI: 10.57745/dxnnwa
title: 31P-NMR_OL_Pine_2015.tif

description: This file contains the 31P NMR spectrum of OL_Pine_2015.
DOI: 10.57745/k0galu
title: 31P-NMR_OL_Method.pdf

description: This file describes the method used to quantify the hydroxyl groups in lab-extracted organosolv lignins.
DOI: 10.57745/rkfovf
title: 31P-NMR_OL_Poplar_2016.tif

description: :unav
DOI: 10.57745/hcjmzf
title: 31P-NMR_OL_Wheat_2016.tif

description: This file contains the 31P NMR spectrum of OL_Wheat_2016.
DOI: 10.6084/m9.figshare.23599305
title: 01 Neonatal Hypernatremic Dehydration in Breastfed Neonates: A Prospective Study Unmasking the Influences of Breastfeeding Practices and Early Weight Monitoring

description: descriptive data for a prospective study
DOI: 10.57745/cglrey
title: 31P-NMR_OL_Pine_2018.tif

description: This file contains the 31P NMR spectrum of OL_Pine_2018.
DOI: 10.26050/wdcc/cliccs-a2-m
title: CLICCS-MODES - Modal wave filtering of ERA5 reanalyses with MODES (Version 2.0)

description: Project: Cluster of Excellence “Climate, Climatic Change, and Society” - CLICCS will explore climate change with broad expertise. CLICCS will investigate how the climate changes and how society changes with it, thereby feeding back on climate. Understanding these changes, including how societies adapt, will enable us to assess with far greater confidence than before the range of imaginable climate futures. In taking on this challenge, CLICCS is guided by the overarching question: "Which climate futures are possible and which are plausible?" Find more information about CLICCS at https://www.cliccs.uni-hamburg.de/ Funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany's Excellence Strategy - EXC 2037 'CLICCS - Climate, Climatic Change, and Society' - Project Number: 390683824. Contribution to the Center for Earth System Research and Sustainability (CEN) of Universität Hamburg. Summary: MODES applies three-dimensional linear wave theory for the decomposition of global circulation in terms of normal-mode functions (NMFs). NMFs used by MODES are eigensolutions of the linearized primitive equations in the terrain-following sigma coordinates and were derived by Kasahara and Puri (1981, Mon. Wea. Rev). The available data are three data sets (40 years), calculated from ERA5 reanalyses by modal filtering of certain wave components, here Kelvin waves (KW), Mixed Rossby-gravity waves (MRG) and Rossby wave n=1 (Rosn1). Near-realtime modal decompositions of ECMWF deterministic forecasts, using the same tool (MODES) as has been used for the generation of the dataset are under this URL: https://modes.cen.uni-hamburg.de/
DOI: 10.57745/tluide
title: 31P-NMR_OL_Miscanthus_2016.tif

description: This file contains the 31P NMR spectrum of OL_Miscanthus_2016.
DOI: 10.57745/tsrjas
title: 31P-NMR_OL_Results.csv

description: This file contains the results of the quantification of hydroxyl groups by phosphorus nuclear magnetic resonance analysis for all lab-extracted organosolv lignins.
DOI: 10.18419/darus-1696
title: Data for: Tuning the Latent Behavior of Molybdenum Imido Alkylidene N-Heterocyclic Carbene Complexes in Dicyclopentadiene Polymerization

description: We report the synthesis of O- and N-chelated hexacoordinated molybdenum imido alkylidene N-heterocyclic carbene (NHC) bistriflate and pentacoordinated molybdenum imido alkylidene NHC monotriflate monoalkoxide complexes and their use as thermally latent and in some cases air-stable precatalysts in the ring-opening metathesis polymerization (ROMP) of dicyclopentadiene (DCPD). Introduction of electron- withdrawing and electron-donating groups at the O-chelated alkylidene ligand allowed for the tuning of both the onset temperature of polymerization (Tonset) and the temperature of the exotherm maximum (Texo,max). In addition, N-chelated complexes were synthesized using easily available 2-vinylpyridine or 2-vinyl- N,N-dimethylaniline to yield five-membered and, for the first time, four-membered molybdenum imido alkylidene NHC chelates. With these precatalysts, Tonset and Texo,max could be varied between 52 and 142 °C and between 99 and 174 °C, respectively. All primary data files and processed data of the journal article from the Buchmeiser group. Tuning the Latent Behavior of Molybdenum Imido Alkylidene N-Heterocyclic Carbene Complexes in Dicyclopentadiene Polymerization. Nuclear magnetic resonance (NMR) spectra are uploaded. Also differential scanning calorimetry (DSC) data are available.
DOI: 10.5281/zenodo.8093932
title: Characterisation of electro- and thermophysical properties of materials used in 3D printing

description: A complex of materials’ properties was measured: electrical conductivity, thermal expansion, thermal conductivity, the density of the materials, and the technical density of construction with porosity.
description: This research was supported by ERDF Project No. 1.1.1.1/19/A/031 "OPTITOOL, Decision Tool for Optimal Design of Smart Polymer Nanocomposite Structures Produced by 3D Printing".
DOI: 10.5281/zenodo.8093931
title: Characterisation of electro- and thermophysical properties of materials used in 3D printing

description: A complex of materials’ properties was measured: electrical conductivity, thermal expansion, thermal conductivity, the density of the materials, and the technical density of construction with porosity.
description: This research was supported by ERDF Project No. 1.1.1.1/19/A/031 "OPTITOOL, Decision Tool for Optimal Design of Smart Polymer Nanocomposite Structures Produced by 3D Printing".
DOI: 10.5281/zenodo.3660800
title: Rigorose Fehlerschranken für das Elektronenstrukturproblem

description: The provided dataset contains rigorous error bounds for many linear conic programming problems, provided by the benchmark libraries DIMACS, ESC, RDM, SDPLIB, and SPARSE_SDP from the well-known website by Hans D. Mittelmann http://plato.asu.edu/sub/testcases.html. Those rigorous error bounds were computed by VSDP 2018, a MATLAB/GNU Octave software package for the computation of verified results in conic programming. This computation is done by careful post-processing of approximate solutions given by the conic solver programs CSDP, SDPA, SDPT3, SeDuMi, and MOSEK. The data is published in the PhD thesis "Rigorose Fehlerschranken für das Elektronenstrukturproblem" by Kai T. Ohlhus (2019 in German). Detailed information are given in the README.md file.
DOI: 10.5281/zenodo.8093640
title: Managing Human Factors in Automated Vehicle Development: Towards Challenges and Practices

description: This data set complements our manuscript with the title: "Managing Human Factors in Automated Vehicle Development: Towards Challenges and Practices" To support our research, we are providing two files: a) Interview Guide<br> b) Overview of Themes Please note that the themes mentioned in the theme file are not directly relevant to this specific paper. They relate to another study conducted using the same dataset. We have included these themes to demonstrate that the dataset was used for two separate papers, each examining different aspects.
DOI: 10.25403/upresearchdata.23596254.v1
title: Exploring network typologies, network development, network functions and network benefits

description: This is dataset for a study that was conducted to have a nuance understanding of the networking behaviours of immigrant entrepreneurs in the South African entrepreneurial ecosystem. The data presents answers to four major research questions. Specifically, the dataset answer questions related to network typologies used by immigrant entrepreneurs, how such networks are developed and what the functions and benefits of networks are in the entrepreneurial ecosystem context. The researcher employed an interpretivist research paradigm using a qualitative method to collect data from 25 immigrant entrepreneurs via the purposive sampling method. The research was carried out in three municipalities in the Gauteng province i.e. Ekurhuleni, Johannesburg, and Tshwane.
DOI: 10.25403/upresearchdata.23596254
title: Exploring network typologies, network development, network functions and network benefits

description: This is dataset for a study that was conducted to have a nuance understanding of the networking behaviours of immigrant entrepreneurs in the South African entrepreneurial ecosystem. The data presents answers to four major research questions. Specifically, the dataset answer questions related to network typologies used by immigrant entrepreneurs, how such networks are developed and what the functions and benefits of networks are in the entrepreneurial ecosystem context. The researcher employed an interpretivist research paradigm using a qualitative method to collect data from 25 immigrant entrepreneurs via the purposive sampling method. The research was carried out in three municipalities in the Gauteng province i.e. Ekurhuleni, Johannesburg, and Tshwane.
DOI: 10.34740/kaggle/dsv/6051412
title: Natural Questions Answering
DOI: 10.34740/kaggle/dsv/6051380
title: Natural Questions Answering
DOI: 10.26180/23597031
title: PICO for synthesis data file: Cumpston_et_al_2023_PICO.xlsx

description: This file includes the data extracted and coded from systematic reviews included in the paper: "Cumpston MS, Brennan SE, Ryan R, Thomas J, McKenzie JE. 2023. Synthesis questions are incompletely reported: survey of systematic reviews" <strong>Data dictionary:</strong> PICO for synthesis data dictionary (https://doi.org/10.26180/23598933) <strong>Analysis code: </strong>PICO for synthesis Stata code: Cumpston_et_al_2023_PICO.do (https://doi.org/10.26180/23597073) <strong>Study protocol: </strong>Cumpston MS, McKenzie JE, Thomas J and Brennan SE. The use of ‘PICO for synthesis’ and methods for synthesis without meta-analysis: protocol for a survey of current practice in systematic reviews of health interventions. <em>F1000Research</em> 2021, <strong>9</strong>:678. (https://doi.org/10.12688/f1000research.24469.2) <strong>Note: </strong>Naming convention of the variables. The naming convention for the variables links to the data dictionary. The character prefix identifies the section of the data_directory (e.g. variables names with the prefix 'Chars' are from the 'CHARACTERISTICS' section). The number of the variable reflects the item number in the data dictionary, except that the first digit is removed because this is captured by the character prefix. For example, Chars_2 is item number 1.2 under the 'CHARACTERISTICS' section of the data dictionary.
DOI: 10.26180/23597031.v1
title: PICO for synthesis data file: Cumpston_et_al_2023_PICO.xlsx

description: This file includes the data extracted and coded from systematic reviews included in the paper: "Cumpston MS, Brennan SE, Ryan R, Thomas J, McKenzie JE. 2023. Synthesis questions are incompletely reported: survey of systematic reviews" <strong>Data dictionary:</strong> PICO for synthesis data dictionary (https://doi.org/10.26180/23598933) <strong>Analysis code: </strong>PICO for synthesis Stata code: Cumpston_et_al_2023_PICO.do (https://doi.org/10.26180/23597073) <strong>Study protocol: </strong>Cumpston MS, McKenzie JE, Thomas J and Brennan SE. The use of ‘PICO for synthesis’ and methods for synthesis without meta-analysis: protocol for a survey of current practice in systematic reviews of health interventions. <em>F1000Research</em> 2021, <strong>9</strong>:678. (https://doi.org/10.12688/f1000research.24469.2) <strong>Note: </strong>Naming convention of the variables. The naming convention for the variables links to the data dictionary. The character prefix identifies the section of the data_directory (e.g. variables names with the prefix 'Chars' are from the 'CHARACTERISTICS' section). The number of the variable reflects the item number in the data dictionary, except that the first digit is removed because this is captured by the character prefix. For example, Chars_2 is item number 1.2 under the 'CHARACTERISTICS' section of the data dictionary.
DOI: 10.34740/kaggle/dsv/6051373
title: Bigbasket Customer Analytics
DOI: 10.5281/zenodo.8094484
title: Results from the preliminary co-creation activities

description: Annex of Master Thesis. Results from the preliminary co-creation activities.
DOI: 10.5281/zenodo.8094483
title: Results from the preliminary co-creation activities

description: Annex of Master Thesis. Results from the preliminary co-creation activities.
DOI: 10.48668/x1uofw
title: First record of the alien invasive mussel Mytella strigata (Hanley, 1843) in Hong Kong

description: Data of survey locations, sites, lat and long; Mytella presence/absence; number, and shell lengths
DOI: 10.48668/x1uofw/o9amfj
title: First record of the alien invasive mussel Mytella strigata Hanley 1843 in Hong Kong - data.tab

description: Data of survey locations, sites, lat and long; Mytella presence/absence; number, and shell lengths
DOI: 10.15480/336.3174
title: Laser-Excited Elastic Guided Waves Reveal the Complex Mechanics of Nanoporous Silicon

description: Nanoporosity in silicon leads to completely new functionalities of this mainstream semiconductor. A difficult to assess mechanics has however significantly limited its application in fields ranging from nanofluidics and biosensorics to drug delivery and energy storage. Here, we present a study on laser-excited elastic guided waves detected contactless and non-destructively in dry and liquid-infused single-crystalline porous silicon.These experiments reveal that the selforganised formation of 100 billions of parallel nanopores per squarecentimetre crosssection results in a nearly isotropic elasticity perpendicular to the pore axes and an 80% stiffnessreduction in the material, despite a bulk-like and anisotropic porewall elasticity. Our thorough assessment of the wafer-scale mechanics of nanoporous silicon provides the base for predictive applications in robust on-chip devices and evidences that recent breakthroughs in laser ultrasonics open up entirely new frontiers for in-situ, non-destructive mechanical characterisation of dry and liquid-functionalised porous materials. Here saved are raw and processed data of laser ultrasonics measurements of porous and bulk silicon.
DOI: 10.5281/zenodo.8093519
title: Dataset for 'Favorable trade-off between heat transfer and pressure drop in 3D printed baffled logpile catalyst structures'

description: This data set was used to generate the results in the paper 'Favorable trade-off between heat transfer and pressure drop in 3D printed baffled logpile catalyst structures', published in Chemical Engineering Research and Design by Leon R.S. Rosseau, Jord T.A. Jansen, Ivo Roghair and Martin van Sint Annaland (https://doi.org/10.1016/j.cherd.2023.06.046).<br> The data is ordered first by configuration, then by gap spacing and finally by relative baffle length (if applicable). The heatrun case folders contain the temperature, wall-heat flux and velocity distributions at steady state with heated walls. The rtdrun case folders contain the pressure and velocity distributions at steady state without heated walls. The E-curve sampling is available as numpy array, as the storage requirements for all of the individual time steps are too high. This data set and the corresponding paper are based on research undertaken in relation to a project (ZEOCAT-3D) which has received funding from the European Union’s Horizon 2020 research and innovation program, under Grant Agreement No. 814548. The authors would like to thank the EU Horizon 2020 program for this opportunity. This publication only reflects the author’s views and neither the funding Agency nor the European Commission are responsible for any use that may be made of the information contained therein.<br> This work made use of the Dutch national e-infrastructure with the support of the SURF Cooperative using grant no. EINF-1478 and grant no. EINF-3116.
DOI: 10.5281/zenodo.8093518
title: Dataset for 'Favorable trade-off between heat transfer and pressure drop in 3D printed baffled logpile catalyst structures'

description: This data set was used to generate the results in the paper 'Favorable trade-off between heat transfer and pressure drop in 3D printed baffled logpile catalyst structures', published in Chemical Engineering Research and Design by Leon R.S. Rosseau, Jord T.A. Jansen, Ivo Roghair and Martin van Sint Annaland (https://doi.org/10.1016/j.cherd.2023.06.046).<br> The data is ordered first by configuration, then by gap spacing and finally by relative baffle length (if applicable). The heatrun case folders contain the temperature, wall-heat flux and velocity distributions at steady state with heated walls. The rtdrun case folders contain the pressure and velocity distributions at steady state without heated walls. The E-curve sampling is available as numpy array, as the storage requirements for all of the individual time steps are too high. This data set and the corresponding paper are based on research undertaken in relation to a project (ZEOCAT-3D) which has received funding from the European Union’s Horizon 2020 research and innovation program, under Grant Agreement No. 814548. The authors would like to thank the EU Horizon 2020 program for this opportunity. This publication only reflects the author’s views and neither the funding Agency nor the European Commission are responsible for any use that may be made of the information contained therein.<br> This work made use of the Dutch national e-infrastructure with the support of the SURF Cooperative using grant no. EINF-1478 and grant no. EINF-3116.
DOI: 10.6084/m9.figshare.23599374
title: Ankylosaur 3D models

description: Supplementary Data for "Divergent strategies in cranial biomechanics and feeding ecology of the ankylosaurian dinosaurs", Antonio Ballell, Bohao Mai and Michael J. Benton. <br> This folder contains the 3D surface models of the skulls of Euoplocephalus tutus and Panoplosaurus mirus used in the biomechanical analyses. <br> I. Euoplocephalus tutus <br> Euoplocephalus_cranium.ply : surface model of the retrodeformed and restored cranium in PLY format. Euoplocephalus_mandible.ply : surface model of the restored mandible in PLY format. <br> Euoplocephalus_cranium_secpalate.ply : surface model of the cranium with digitally removed secondary palate in PLY format. <br> II. Panoplosaurus mirus <br> Panoplosaurus_cranium.ply : surface model of the retrodeformed and restored cranium in PLY format. Panoplosaurus_mandible.ply : surface model of the restored mandible in PLY format. <br> Panoplosaurus_cranium_secpalate.ply : surface model of the cranium with digitally removed secondary palate in PLY format.