cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.25919/0517-ns38
title: Parkes observations for project P1067 semester 2020APRS_11

description: The Parkes Ultra-wide-bandwidth receiver enables, for the first time with the Parkes telescope, a commensal high time and high frequency resolution survey. We will observe Baade's window in which we are guaranteed detections of pulsars and spectral lines. Our science drivers are diverse and range from understanding scattering, to detecting new pulsars, to searching for galaxies in the zone of avoidance, probing the globular cluster at the centre of the window and studying OH circumstellar masers and CO-dark molecular gas. The observing strategy and processing software developed for this survey will be applicable to all future Parkes surveys with the wide-band receiver or cyrogenically-cooled phased array feed.
DOI: 10.6084/m9.figshare.13263881.v1
title: How fast is Australia's broadband compared to our Top Ten Trading Partners (Speedtest Global Index)?

description: This data collates an excerpt from Speedtest Global Index, over time (2018 - 2020), for Australia's Top Ten Trading Partners by imports and exports. Download speeds are in Mbps. Figures are rounded to nearest 5Mbps, except for % growth, and smallest observations.<br>Australia's Top 10 Trading Partners are sourced from:- Observatory of Economic Complexity (https://oec.world).<br>A version of this data (2018 - 19) was published in the Journal of Telecommunications and the Digital Economy (JTDE link below), Figure 3 (Ferrers 2020) in 2020, and presented at a Telsoc NBN Future Forum on Learning from International Experiences. Data from paper is at Figshare (link below).<br>File is provided in formats:- numbers with paper graph, and formulae- csv (for browsing)<br>This dataset is intended to be updated annually. Speedtest provides monthly updates.
DOI: 10.6084/m9.figshare.13263881.v2
title: How fast is Australia's broadband compared to our Top Ten Trading Partners (Speedtest Global Index 2017-2020)?

description: This data collates an excerpt from Speedtest Global Index, over time (2018 - 2020), for Australia's Top Ten Trading Partners by imports and exports. Download speeds are in Mbps. Figures are rounded to nearest 5Mbps, except for % growth, and smallest observations.<br>Australia's Top 10 Trading Partners are sourced from:- Observatory of Economic Complexity (https://oec.world).<br>A version of this data (2018 - 19) was published in the Journal of Telecommunications and the Digital Economy (JTDE link below), Figure 3 (Ferrers 2020) in 2020, and presented at a Telsoc NBN Future Forum on Learning from International Experiences. Data from paper is at Figshare (link below).<br>File is provided in formats:- numbers with paper graph, and formulae- csv (for browsing)<br>This dataset is intended to be updated annually. Speedtest provides monthly updates.
DOI: 10.5281/zenodo.3899570
title: Ice speed and elevation change rate of the Patagonian icefields

description: These are the dataset of ice speed magnitude, error, number of valid velocity maps and elevation change rate of the Patagonian icefields (PIs) presented in the study. Please refer the main text for further technical information or directly ask the corresponding author. gererated April 2020, M. Minowa<br> updated Septempber 2020, M. Minowa =================================================================== 1. Annual velocity magnitude<br> File name: PIs_mag_utm18n_yyyy.tif<br> Format: geotiff<br> Coordinates: utm 18 North <br> No data value: -9999 <br> 2. Number of valid velocity maps<br> File name: PIs_cnt_utm18n_yyyy.tif<br> Format: geotiff<br> Coordinates: utm 18 North <br> 3. Annual velocity error<br> File name: PIs_er_utm18n_yyyy.tif<br> Format: geotiff<br> Coordinates: utm 18 North <br> No data value: -9999 4. Elevation change rate map between 2000 and 2019<br> File name: PIs_dhdt_utm18s_2000-2019.tif<br> Format: Geotiff<br> Coordinates: utm 18 South<br> No data value: -9999 5. Number of valid DEMs<br> File name: PIs_dhdt_cnt_utm18s_2000-2019.tif<br> Format: Geotiff<br> Coordinates: utm 18 South<br> No data value: -9999 6. Systematic error map in the elevation change rate<br> File name: PIs_dhdt_mu_utm18s_2000-2019.tif<br> Format: Geotiff<br> Coordinates: utm 18 South<br> No data value: -9999 7. Random error map in the elevation change rate<br> File name: PIs_dhdt_sigma_utm18s_2000-2019.tif<br> Format: Geotiff<br> Coordinates: utm 18 South<br> No data value: -9999<br>
DOI: 10.5281/zenodo.3899569
title: Ice speed and elevation change rate of the Patagonian icefields

description: These are the dataset of ice speed magnitude, error, number of valid velocity maps and elevation change rate of the Patagonian icefields (PIs) presented in the study. Please refer the main text for further technical information or directly ask the corresponding author. gererated April 2020, M. Minowa<br> updated Septempber 2020, M. Minowa =================================================================== 1. Annual velocity magnitude<br> File name: PIs_mag_utm18n_yyyy.tif<br> Format: geotiff<br> Coordinates: utm 18 North <br> No data value: -9999 <br> 2. Number of valid velocity maps<br> File name: PIs_cnt_utm18n_yyyy.tif<br> Format: geotiff<br> Coordinates: utm 18 North <br> 3. Annual velocity error<br> File name: PIs_er_utm18n_yyyy.tif<br> Format: geotiff<br> Coordinates: utm 18 North <br> No data value: -9999 4. Elevation change rate map between 2000 and 2019<br> File name: PIs_dhdt_utm18s_2000-2019.tif<br> Format: Geotiff<br> Coordinates: utm 18 South<br> No data value: -9999 5. Number of valid DEMs<br> File name: PIs_dhdt_cnt_utm18s_2000-2019.tif<br> Format: Geotiff<br> Coordinates: utm 18 South<br> No data value: -9999 6. Systematic error map in the elevation change rate<br> File name: PIs_dhdt_mu_utm18s_2000-2019.tif<br> Format: Geotiff<br> Coordinates: utm 18 South<br> No data value: -9999 7. Random error map in the elevation change rate<br> File name: PIs_dhdt_sigma_utm18s_2000-2019.tif<br> Format: Geotiff<br> Coordinates: utm 18 South<br> No data value: -9999<br>
DOI: 10.5281/zenodo.4281727
title: Dataset for Early pandemic molecular diversity of SARS-CoV-2 in children

description: 169 SARS-CoV-2 genomes used in Early pandemic molecular diversity of SARS-CoV-2 in children
DOI: 10.6084/m9.figshare.13264301
title: Summary Survey Data 16.12.19.pdf

description: Summary data 16.12.19
DOI: 10.21227/g9m2-y139
title: Coronavirus (COVID-19) Geo-tagged Tweets Dataset

description: This dataset contains IDs and sentiment scores of the geo-tagged tweets related to the COVID-19 pandemic. The tweets are captured by an on-going project deployed at https://live.rlamsal.com.np. The model monitors the real-time Twitter feed for coronavirus-related tweets using 90+ different keywords and hashtags that are commonly used while referencing the pandemic. Complying with Twitter's content redistribution policy, only the tweet IDs are shared. You can re-construct the dataset by hydrating these IDs. The tweet IDs in this dataset belong to the tweets tweeted providing an exact location.The paper associated with this dataset is available here: Design and analysis of a large-scale COVID-19 tweets dataset-------------------------------------Related: Coronavirus (COVID-19) Tweets Sentiment Trend (Global), Coronavirus (COVID-19) Tweets Dataset and Tweets Originating from India During COVID-19 Lockdowns 1, 2, 3, 4-------------------------------------Below is the quick overview of this dataset.— Dataset name: GeoCOV19Tweets Dataset— Number of tweets : 265,319 tweets— Coverage : Global— Language : English (EN)— Dataset usage terms : By using this dataset, you agree to (i) use the content of this dataset and the data generated from the content of this dataset for non-commercial research only, (ii) remain in compliance with Twitter's Developer Policy and (iii) cite the following paper:Lamsal, R. Design and analysis of a large-scale COVID-19 tweets dataset. Applied Intelligence (2020). https://doi.org/10.1007/s10489-020-02029-z— Primary dataset : Coronavirus (COVID-19) Tweets Dataset (COV19Tweets Dataset)— Dataset updates : Everyday— Active keywords and hashtags: keywords.tsvPlease visit this page (primary dataset) for details regarding the collection date and time (and other notes) of each CSV file present in this dataset.
DOI: 10.6084/m9.figshare.13264661
title: Chemical data for "Heterogeneous Martian Mantle: Evidence from Petrology, Mineral Chemistry, and in situ U-Pb Chronology of the Basaltic Shergottite Northwest Africa 8653"

description: Geochemical data used for "Heterogeneous Martian Mantle: Evidence from Petrology, Mineral Chemistry, and in situ U-Pb Chronology of the Basaltic Shergottite Northwest Africa 8653".
DOI: 10.6084/m9.figshare.13264661.v1
title: Chemical data for "Heterogeneous Martian Mantle: Evidence from Petrology, Mineral Chemistry, and in situ U-Pb Chronology of the Basaltic Shergottite Northwest Africa 8653"

description: Geochemical data used for "Heterogeneous Martian Mantle: Evidence from Petrology, Mineral Chemistry, and in situ U-Pb Chronology of the Basaltic Shergottite Northwest Africa 8653".
DOI: 10.6084/m9.figshare.13206320
title: Turbulence Study

description: This data is collected using hot-wire anemometry.<br>A NACA 2412 aerofoil was used in this turbulence study. The standard baseline aerofoil has files beginning with 'aerofoil_nonns', and the aerofoil with negative stiffness inclusions has files beginning with 'aerofoil_ns167' since the elements have a Q ratio of 1.67.<br>All aerofoils were tested at 4 angles of attack (0, 4, 8, 12) and 5 freestream velocities (10, 15, 20, 25, 30). This is in the relevant file name.<br>Calibration data for the hot-wire is included. Use these values to convert from voltage to velocity. Use the morning calibration for the nonns aerofoil and afternoon calibration for the ns167 aerofoil.<br>v1 and v1_m is voltage. <br>For acquiring data, Step_2_acquisition.m was usedFor acquiring data, Step_1_calibration.m was used
DOI: 10.6084/m9.figshare.13206320.v1
title: Turbulence Study

description: This data is collected using hot-wire anemometry.<br>A NACA 2412 aerofoil was used in this turbulence study. The standard baseline aerofoil has files beginning with 'aerofoil_nonns', and the aerofoil with negative stiffness inclusions has files beginning with 'aerofoil_ns167' since the elements have a Q ratio of 1.67.<br>All aerofoils were tested at 4 angles of attack (0, 4, 8, 12) and 5 freestream velocities (10, 15, 20, 25, 30). This is in the relevant file name.<br>Calibration data for the hot-wire is included. Use these values to convert from voltage to velocity. Use the morning calibration for the nonns aerofoil and afternoon calibration for the ns167 aerofoil.<br>v1 and v1_m is voltage. <br>For acquiring data, Step_2_acquisition.m was usedFor acquiring data, Step_1_calibration.m was used
DOI: 10.6084/m9.figshare.13175885
title: Vibration Transmissibility Experiment

description: This experiment involved exciting each negative stiffness honeycomb structure with a sinusoidal chirp signal from 5-600 Hz. The transmitted vibration was measured with a laser vibrometre. All measurements in the .mat files are in volts.<br>Some test files were failures with the equipment moving off axis. It is easy to tell which ones these are. Best tests to use for each structure are:Q = 1.67 - use T2Q = 2.00 - use T1Q = 2.31 - use T5Q = 2.71 - use T2<br>The velspec files show the voltage trace. The unnamed figure shows the prelim frequency spectrum - this spectrum needs adjusting.
DOI: 10.25958/4sj2-sw67
title: Predictors of marine genetic structure in the Indo-Australian Archipelago

description: This is the dataset extracted from 101 publications on 99 marine species from eight taxonomic groups in the Indo Australian Archipelago. Data extracted includes measures of genetic structure and the potential predictors.
DOI: 10.21227/a6sa-9f35
title: Latency measurements API gateway

description: This dataset contains requests execution times for comparison of direct requests and requests via API gateway to test API.
DOI: 10.17632/sr3fggftx9.1
title: Data for: Natural mineralized fractures from the Montney-Doig Formations (Western Canada Sedimentary Basin): controlling factors and implications for unconventional exploration

description: Table S1a. Details on investigated samples from well core 16-17, including sample name, depth, sequence of provenance, depositional environment, number of fractures, their orientation and kinematic aperture, texture of the sealing calcites and their O-C-Sr isotope composition. In some samples, O-C isotope analysis were performed for different veins or for different calcite textures occurring in the same vein. Table S1b. Same as in Table S1a for the samples from well core 12-36. Table S2a. Details on samples from well core 16-17, including sample name, depth, sequence of provenance, depositional environment and the parameters obtained from Rock-Eval analysis accomplished with the Shale Play Method® developed at IFP Energies nouvelles (Pillot et al., 2014; Romero-Sarmiento et al., 2016a, 2016b): Sh0, Sh1, Sh2, Tmax, TOC, HI, OI, HCcont, MinC. TOC= total organic carbon, HI= hydrogen index, OI= oxygen index, HCcont= content in hydrocarbons, MinC= mineral carbon. Column names with –B and –E refer to analyses performed on bulk-rock and extracted organic matter, respectively. Table S2b. Same as in Table S2a for the samples from well core 12-36. Table S3a. Spreadsheet for well core 16-17 with the evolution of different properties with depth used for frequency distribution analysis with EasytraceTM software. The properties considered are: presence/absence of fractures (i.e. FRACTURE), the stratigraphic sequence (i.e. SEQUENCE), the depositional environment (i.e. ENVIRONMENT), the TOC values (i.e. TOC). Each line of the table represents a point virtually sampled along the log of well 16-17 to which information on the different properties were attributed via numerical codes (see Table 1). As requested by the software, the value “777” was attributed to the cells where information for a given property was not available. Table S3b. Same as in Table S3a for well core 12-36.
DOI: 10.17632/jdxf2pj489.1
title: Data for: Phosphotungstate-sandwiched between cerium oxide and gold nanoparticles exhibit enhanced catalytic reduction of 4-nitrophenol and peroxidase enzyme-like activities

description: In this research work, we have synthesized and characterized gold decorated cerium oxide nanoparticles. Phosphotungstic acid (PTA) was utilized for the reduction of gold nanoparticles on the lattice surface of cerium oxide nanoparticles. The synthesized nanocomposite showed enhanced peroxidase like activity as compared to independent controls. Additionally, the composite showed faster degradation of 4-nitrophenol than either nanoceria or PTA-AuNPs. electron transfer ability of PTA molecules leads to the excellent improvement in the catalytic performance of nanoceria-PTA-AuNPs composite. The obtained improved catalytic activity might be due to the rapid electron transfer from nanoceria to AuNPs, where metal nanoparticles act as electron sink, mediated by PTA. Thus, the developed nanoceria-PTA-AuNPs nanocomposites are expected to have wide range of uses in mimicking other enzyme-like activities, photocatalysis, organic pollutant degradation, and other biomedical applications.
DOI: 10.21335/nmdc-752613514
title: Havforskningsinstituttet Smoltbur 2019 Hardangerfjorden

description: The dataset includes Institute of Marine Research data of salmon lice counts on smolts in sentinel cages in Hardangerfjord, Norway in 2019.
DOI: 10.21335/nmdc-1301982876
title: Havforskningsinstituttet Smoltbur 2019 Boknafjorden

description: The dataset includes Institute of Marine Research data of salmon lice counts on smolts in sentinel cages in Boknafjord, Norway in 2019.
DOI: 10.21335/nmdc-1443483525
title: Havforskningsinstituttet Smoltbur 2019 Namsen

description: The dataset includes Institute of Marine Research data of salmon lice counts on smolts in sentinel cages in Namsen, Norway in 2019.
DOI: 10.21227/5nek-tn10
title: diabetic foot

description: This is a dataset of diabetic foot. We are preparing to publish this dataset.
DOI: 10.21335/nmdc-877249338
title: Havforskningsinstituttet Smoltbur 2019 Sognefjorden

description: The dataset includes Institute of Marine Research data of salmon lice counts on smolts in sentinel cages in Sognefjord, Norway in 2019.
DOI: 10.25345/c5zj5m
title: MassIVE MSV000086492 - GNPS Theriac Andromachalis and Opiium extract NEW
title: Analysis of theriac adromachalis and aged opium medicine
DOI: 10.21335/nmdc-1877740266
title: Havforskningsinstituttet Smoltbur 2020 Hardangerfjorden

description: The dataset includes Institute of Marine Research data of salmon lice counts on smolts in sentinel cages in Hardangerfjord, Norway in 2020.
DOI: 10.5281/zenodo.4282048
title: Dataset for Early pandemic molecular diversity of SARS-CoV-2 in children

description: 169 SARS-CoV-2 genomes used in Early pandemic molecular diversity of SARS-CoV-2 in children
DOI: 10.5281/zenodo.4281726
title: Dataset for Early pandemic molecular diversity of SARS-CoV-2 in children

description: 169 SARS-CoV-2 genomes used in Early pandemic molecular diversity of SARS-CoV-2 in children
DOI: 10.5281/zenodo.4104116
title: Re-evaluating phoneme frequencies: Supplementary materials S6–S7

description: Supplementary materials (Sections S6–S7) for the paper <em>Re-evaluating phoneme frequencies</em><em> </em>(Macklin-Cordes & Round, 2020) These materials include: S6: Data viewer app S7: Code, data and results Usage instructions for the code and app can be found in S1 of the paper's Supplementary Materials and in the readme file contained here.
DOI: 10.5281/zenodo.3886211
title: Re-evaluating phoneme frequencies: Supplementary materials S6–S7

description: Supplementary materials (Sections S6–S7) for the paper <em>Re-evaluating phoneme frequencies</em><em> </em>(Macklin-Cordes & Round, 2020) These materials include: S6: Data viewer app S7: Code, data and results Usage instructions for the code and app can be found in S1 of the paper's Supplementary Materials and in the readme file contained here.
DOI: 10.5281/zenodo.4282089
title: Good practice in evaluating measurement uncertainty

description: This document illustrates good practice in the evaluation of measurement uncertainty. It contains examples from a variety of areas in calibration and testing, and illustrates the use of the methods from the “Guide to the expression of Uncertainty in Measurement” and its supplements, as well as Bayesian approaches. Dcoument attached: Compendium_M18.pdf: document
DOI: 10.18112/openneuro.ds003097.v2.0.0
title: AOMIC-ID1000
DOI: 10.15129/d4ca75d2-a462-4940-9614-b1b3fe5a8e2e
title: Data for "Controlled beat-wave Brillouin scattering in the ionosphere"

description: The dataset contains experimental data as well as simulation data used to analyse an ionospheric beat wave Brillouin scattering experiment experiment carried out at the EISCAT facility in Tromso, Northern Norway, 29 November 2014. More details on the data are given in the README file as well as in separate README files contained in each data file.
DOI: 10.6084/m9.figshare.12770114
title: Demography.csv

description: An overview of the demography as well as the head circumferences, head widths, pinna lengths and pinna widths of all participants
DOI: 10.6084/m9.figshare.12770114.v1
title: Demography.csv

description: An overview of the demography as well as the head circumferences, head widths, pinna lengths and pinna widths of all participants
DOI: 10.6084/m9.figshare.12770117
title: Microphone_Positions.zip

description: The spatial coordinates of the microphone positions are provided in a .csv file. Furthermore, the Euclidean distances between the microphones were calculated for each participant and averaged over all participants; they are also available as .csv files. All position and distance data of the microphone coordinates are given in millimeters. In addition to the microphone distance matrices and absolute coordinates, the tilt of the microphone headband in relation to the "Frankfurt Plane" was calculated for all participants and added as a .csv file.
DOI: 10.6084/m9.figshare.12770117.v1
title: Microphone_Positions.zip

description: The spatial coordinates of the microphone positions are provided in a .csv file. Furthermore, the Euclidean distances between the microphones were calculated for each participant and averaged over all participants; they are also available as .csv files. All position and distance data of the microphone coordinates are given in millimeters. In addition to the microphone distance matrices and absolute coordinates, the tilt of the microphone headband in relation to the "Frankfurt Plane" was calculated for all participants and added as a .csv file.
DOI: 10.5519/qd.z0nit7se
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (0 records)
DOI: 10.5281/zenodo.4273840
title: Parametric Study of the Radiative Load Distribution on the EU-DEMO First Wall Due to SPI-Mitigated Disruptions and in Steady-State (dataset)

description: Database for reproducing the calculations presented in the publication "Parametric Study of the Radiative Load Distribution on the EU-DEMO First Wall Due to SPI-Mitigated Disruptions", submitted to <em>Fusion Engineering and Design</em>. Work carried out within the framework of the EUROfusion Consortium.
description: The dataset is called CHERAB_SPIMD_SS since it contains both data related to Shattered-Pellet Injection Mitigated Disruptions (SPIMD) radiative load and Steady-State (SS) load conditions The README.txt file describes the dataset content and its organization, contains licence and copyright information, lists the contributors. Instructions and software requirements for reproducing the calculations are also indicated. As indicated in that main README.txt file, instructions for running the simulations are contained in the read_me.txt file in the Simulations/ folder. Due to the significant computational time associated to the simulations, the full set of results have been included in the dataset. README.txt has been written in compliance with the Dublin Core Standard for metadata, https://dublincore.org/.
DOI: 10.5281/zenodo.3707938
title: X-ray diffraction images of the beta4 tetramer of the C-terminal peptide of the split chain transketolase

description: X-ray images for PDB entry 6YAJ DOI for the pdb is https://doi.org/10.2210/pdb6YAJ/pdb Title: A 'Split-Gene' Transketolase From the Hyper-Thermophilic Bacterium Carboxydothermus hydrogenoformans : Structure and Biochemical Characterization.<br> Journal: Front Microbiol<br> Volume: 11<br> Pages: 592353 - 592353<br> Year: 2020<br> PubMed ID: 33193259<br> DOI: 10.33 89/fmicb .2020.592353
DOI: 10.5281/zenodo.3707937
title: X-ray diffraction images of the beta4 tetramer of the C-terminal peptide of the split chain transketolase

description: X-ray images for PDB entry 6YAJ DOI for the pdb is https://doi.org/10.2210/pdb6YAJ/pdb Title: A 'Split-Gene' Transketolase From the Hyper-Thermophilic Bacterium Carboxydothermus hydrogenoformans : Structure and Biochemical Characterization.<br> Journal: Front Microbiol<br> Volume: 11<br> Pages: 592353 - 592353<br> Year: 2020<br> PubMed ID: 33193259<br> DOI: 10.33 89/fmicb .2020.592353
DOI: 10.5281/zenodo.3708998
title: X-ray diffraction images of the alpah2beta2 heterotetramer of the split chain transketolase

description: Data were collected on Diamond I04-1 14 Dec 2013. James, P.,Isupov, M.N.,De Rose, S.A.,Sayer, C.,Cole, I.S.,Littlechild, J.A.<br> <br> A 'Split-Gene' Transketolase From the Hyper-Thermophilic Bacterium Carboxydothermus hydrogenoformans : Structure and Biochemical Characterization.<br> <br> Journal: Front Microbiol<br> Volume: 11<br> Pages: 592353 - 592353<br> Year: 2020<br> PubMed ID : 3319 3259<br> DOI: 10.3389/fmicb.2020.592353<br> <br> PDB DOI: https://doi.org/10.2210/pdb6YAK/pdb