cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.21227/rskf-0k77
title: Tweets Originating from India During COVID-19 Lockdowns

description: This India-specific COVID-19 tweets dataset has been developed using the large-scale Coronavirus (COVID-19) Tweets Dataset, which currently contains more than 700 million COVID-19 specific English language tweets. This dataset contains tweets originating from India during the first week of each four phases of nationwide lockdowns initiated by the Government of India. For more information on filtering keywords, please visit the primary dataset page.— 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-------------------------------------Related: (a) Coronavirus (COVID-19) Tweets Dataset(b) Coronavirus (COVID-19) Geo-tagged Tweets Dataset(c) Coronavirus (COVID-19) Tweets Sentiment Trend (Global)-------------------------------------What's inside the dataset? The files in the dataset contain IDs of the tweets present in the Coronavirus (COVID-19) Tweets Dataset. Note: Below, (all files) means that all the files mentioned and in-between have been considered to develop the ID file, while (only even-numbered files) suggests that only the even-numbered files have been considered.Lockdown period tweets: (all files)Lockdown1.zip: March 25, 2020 - April 02, 2020; corona_tweets_08.csv to corona_tweets_14.csvLockdown2.zip: April 14, 2020 - April 21, 2020; corona_tweets_27.csv to corona_tweets_33.csvLockdown3.zip: May 01, 2020 - May 07, 2020; corona_tweets_44.csv to corona_tweets_49.csvLockdown4.zip: May 18, 2020 - May 23, 2020; corona_tweets_61.csv to corona_tweets_66.csvExtras: (all files)extras_june1_june7.zip: corona_tweets_75.csv to corona_tweets_80.csvExtras: (only even-numbered files)extras_june24_july1.zip: corona_tweets_96.csv to corona_tweets_104.csvextras_july2_july15.zip: corona_tweets_106.csv to corona_tweets_118.csvextras_july16_august4.zip: corona_tweets_120.csv to corona_tweets_138.csvextras_august5_august18.zip: corona_tweets_140.csv to corona_tweets_152.csvextras_august19_september1.zip: corona_tweets_154.csv to corona_tweets_166.csvextras_september2_september15.zip: corona_tweets_168.csv to corona_tweets_180.csv
DOI: 10.21227/xqxy-dv85
title: Tweets Originating from India During COVID-19 Lockdowns

description: This India-specific COVID-19 tweets dataset has been developed using the large-scale Coronavirus (COVID-19) Tweets Dataset, which currently contains more than 700 million COVID-19 specific English language tweets. This dataset contains tweets originating from India during the first week of each four phases of nationwide lockdowns initiated by the Government of India. For more information on filtering keywords, please visit the primary dataset page.— 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-------------------------------------Related datasets: (a) Coronavirus (COVID-19) Tweets Dataset(b) Coronavirus (COVID-19) Geo-tagged Tweets Dataset(c) Coronavirus (COVID-19) Tweets Sentiment Trend (Global)-------------------------------------What's inside the dataset? The files in the dataset contain IDs of the tweets present in the Coronavirus (COVID-19) Tweets Dataset. Note: Below, (all files) means that all the files mentioned and in-between have been considered to develop the ID file, while (only even-numbered files) suggests that only the even-numbered files have been considered.Lockdown period tweets: (all files)Lockdown1.zip: March 25, 2020 - April 02, 2020; corona_tweets_08.csv to corona_tweets_14.csvLockdown2.zip: April 14, 2020 - April 21, 2020; corona_tweets_27.csv to corona_tweets_33.csvLockdown3.zip: May 01, 2020 - May 07, 2020; corona_tweets_44.csv to corona_tweets_49.csvLockdown4.zip: May 18, 2020 - May 23, 2020; corona_tweets_61.csv to corona_tweets_66.csvExtras: (all files)extras_june1_june7.zip: corona_tweets_75.csv to corona_tweets_80.csvExtras: (only even-numbered files)extras_june24_july1.zip: corona_tweets_96.csv to corona_tweets_104.csvextras_july2_july15.zip: corona_tweets_106.csv to corona_tweets_118.csvextras_july16_august4.zip: corona_tweets_120.csv to corona_tweets_138.csvextras_august5_august18.zip: corona_tweets_140.csv to corona_tweets_152.csvextras_august19_september1.zip: corona_tweets_154.csv to corona_tweets_166.csvextras_september2_september15.zip: corona_tweets_168.csv to corona_tweets_180.csv
DOI: 10.4225/08/5a8ff73e272b1
title: Visualization of the hydrogen atom wave functions

description: DCM plugin for generating hydrogen atom wave functions and electron probability densities for interactive visualization using a web browser.
DOI: 10.26180/13095281.v1
title: Collective transition and personal identity in autobiographical memory organization_memory level data.sav

description: Data set
DOI: 10.25919/zvfp-wn16
title: Parkes observations for project P574 semester 2020APRS_06

description: We request time to observe 260 pulsars on a regular basis in order to provide the accurate ephemerides necessary for the detection and characterisation of gamma-ray pulsars with the Fermi satellite. The main science goals are to increase the number of known gamma-ray pulsars (both radio-loud and radio-quiet), to determine accurate pulse profiles, and to characterise their high energy (phase-resolved) spectra. In the radio, the observations will also allow us to find glitches, characterise timing noise, investigate dispersion and rotation measure variability, and enhance our knowledge of single pulse phenomenology. To date, we are (co-)authors on over 80 papers arising from the collaboration and P574 data. The data have contributed to the PhD theses of students from Bordeaux, Oxford, Manchester, Stanford, and Swinburne.
DOI: 10.26180/13095281
title: Valence and the reminiscence bump for private and public memories_dataset

description: Data set
DOI: 10.26180/13095281.v3
title: Valence and the reminiscence bump for private and public memories_dataset

description: Data set
DOI: 10.26180/13095281.v2
title: Collective transition and personal identity in autobiographical memory organization_memory level data.sav

description: Data set
DOI: 10.5281/zenodo.4198689
title: EL, PGC, GB

description: Data set
DOI: 10.5281/zenodo.4198688
title: EL, PGC, GB

description: Data set
DOI: 10.6084/m9.figshare.13295507
title: Supplementary materials.docx

description: Supplementary materials and data for Microbial fuel cell
DOI: 10.6084/m9.figshare.13295507.v1
title: Supplementary materials.docx

description: Supplementary materials and data for Microbial fuel cell
DOI: 10.5281/zenodo.4034261
title: Phylogenomic analyses of 142 prokaryotic genera

description: This repository contains 142 tar archive files, each corresponding to a prokaryotic genus. Each archive contains the following files/directories: <code>accn.tax.tsv </code> a tab-delimited file containing the assembly accession (col 1) and an associated taxon name (col 2) for each selected genome (one per line) <code>gff/ </code> a directory containing a gzip-compressed GFF3 file (as returned by the annotation tool <em>Prokka</em>) for each genome specified in <code>accn.tax.tsv</code> <code>cds.fna.gz </code> a gzip-compressed FASTA file containing all the coding sequences (at the codon level) from the GFF3 files in the directory <code>gff/</code> <code>msa/ </code> a directory containing multiple amino acid and codon sequence alignments (compressed FASTA files with extensions .afa.gz and .afc.gz, respectively) for each cluster of at least four homologous sequences (as determined by the pipeline <em>Roary</em> from the GFF3 files in <code>gff/</code>) <code>supermatrix.fasta.gz </code> a gzip-compressed FASTA file obtained by concatenating all the multiple codon sequence alignments in the directory <code>msa/</code> <code>tree.nwk </code> a Newick-formatted file containing a maximum-likelihood (ML) phylogenetic tree inferred from the file <code>supermatrix.fasta.gz</code> using <em>IQ-TREE</em> <code>iqtree.txt </code> a txt file summarizing the ML estimates of the GTR+Γ evolutionary model parameters, as returned by <em>IQ-TREE</em> when inferring the phylogenetic tree <code>tree.nwk</code> A summary of the 142 phylogenomic analyses can be found in the tab-delimited file <code>GTR.params.tree.tsv</code>. Each line corresponds to one genus and contains the 12 following fields:<br> <code>[1] </code> genus name,<br> <code>[2-5] </code> frequencies of T, C, A, G, respectively,<br> <code>[6-10]</code> C-T, A-T, G-T, A-C, C-G rate parameters, respectively (normalized such that A-G rate = 1),<br> <code>[11] </code> Γ shape parameter alpha,<br> <code>[12] </code> Newick-formatted phylogenetic tree. _____ Criscuolo A (2020) <em>On the transformation of MinHash-based uncorrected distances into proper evolutionary distances for phylogenetic inference</em>. F1000Research, 9:1309. doi:10.12688/f1000research.26930.1
DOI: 10.5281/zenodo.4034244
title: Phylogenomic analyses of 142 prokaryotic genera

description: This repository contains 142 tar archive files, each corresponding to a prokaryotic genus. Each archive contains the following files/directories: <code>accn.tax.tsv </code> a tab-delimited file containing the assembly accession (col 1) and an associated taxon name (col 2) for each selected genome (one per line) <code>gff/ </code> a directory containing a gzip-compressed GFF3 file (as returned by the annotation tool <em>Prokka</em>) for each genome specified in <code>accn.tax.tsv</code> <code>cds.fna.gz </code> a gzip-compressed FASTA file containing all the coding sequences (at the codon level) from the GFF3 files in the directory <code>gff/</code> <code>msa/ </code> a directory containing multiple amino acid and codon sequence alignments (compressed FASTA files with extensions .afa.gz and .afc.gz, respectively) for each cluster of at least four homologous sequences (as determined by the pipeline <em>Roary</em> from the GFF3 files in <code>gff/</code>) <code>supermatrix.fasta.gz </code> a gzip-compressed FASTA file obtained by concatenating all the multiple codon sequence alignments in the directory <code>msa/</code> <code>tree.nwk </code> a Newick-formatted file containing a maximum-likelihood (ML) phylogenetic tree inferred from the file <code>supermatrix.fasta.gz</code> using <em>IQ-TREE</em> <code>iqtree.txt </code> a txt file summarizing the ML estimates of the GTR+Γ evolutionary model parameters, as returned by <em>IQ-TREE</em> when inferring the phylogenetic tree <code>tree.nwk</code> A summary of the 142 phylogenomic analyses can be found in the tab-delimited file <code>GTR.params.tree.tsv</code>. Each line corresponds to one genus and contains the 12 following fields:<br> <code>[1] </code> genus name,<br> <code>[2-5] </code> frequencies of T, C, A, G, respectively,<br> <code>[6-10]</code> C-T, A-T, G-T, A-C, C-G rate parameters, respectively (normalized such that A-G rate = 1),<br> <code>[11] </code> Γ shape parameter alpha,<br> <code>[12] </code> Newick-formatted phylogenetic tree. _____ Criscuolo A (2020) <em>On the transformation of MinHash-based uncorrected distances into proper evolutionary distances for phylogenetic inference</em>. F1000Research, 9:1309. doi:10.12688/f1000research.26930.1
DOI: 10.6084/m9.figshare.13295540
title: A Powerlaw-Based-Approach to Mapping COVID-19 Cases in the United States Dataset

description: This dataset contains the data used in "A Power-Law-Based Approach to Mapping COVID-19 Cases in the United States". By Bin Jiang and Chris de Rijke.<br>The input data about the COVID-19 cases is obtained from https://github.com/CSSEGISandData/COVID-19/tree/master/csse_covid_19_data - which is maintained by Johns Hopkins University Center for Systems Science and Engineering (JHU CSSE).<br>The retrieved data used and obtained for this study are available in the "RawInputData" folder, where Daily and Weekly Cases are separated as well.<br>Shapefiles and administrative borders used for the figures and calculations are available in the "Figure2and4" folder. A combination of these shapefiles and the databaseis used to visualize the COVID-19 cases.<br>Processed powerlaw data can be found in the "Powerlawdata" folder in an excel file. All powerlaw results are available in a raw format.<br>Finally data used to create the time animation (http://lifegis.hig.se/COVID19/) is available in the folder "TimeAnimation" where a combination of an organized shapefiles and raw .csv data is used for the visualization.
DOI: 10.5281/zenodo.4034644
title: Model trees and associated simulated nucleotide sequences for testing phylogenetic inference methods

description: This repository contains 142 tar.gz archive files, each containing nucleotide sequence data that have been simulated using <em>INDELible</em> for testing alignment-free phylogenetic inference methods. These datasets were generated by using the results (trees and model parameters) of 142 phylogenomic analyses of real-case data as model (available here). Initial sequence length was 5 Mbs, and an indel rate of 0.01 was set with indel length drawn from [1, 50000] according to a Zipf distribution with parameter 1.5 (see <em>INDELible</em> manual). Each archive contains the following files/directories: <code>GTR.params.trees.tsv </code> a tab-delimited file summarizing the real-case GTR+Γ model parameters and the phylogenetic tree used to simulate the sequence dataset (gathered from https://zenodo.org/record/4034261) <code>tax.tsv </code> a tab-delimited file containing the initial (col 1) and simplified (col 2) taxon names <code>model.nwk </code> a Newick-formatted file containing the initial model tree (gathered from <code>GTR.params.trees.tsv</code>) with simplified leaf names (following <code>tax.tsv</code>) <code>control.txt </code> the <em>INDELible</em> input file used to simulate the evolution of a sequence along the tree in <code>model.nwk</code> <code>seq/ </code> a directory containing the simulated sequences (one FASTA file per leaf in the tree in <code>model.nwk</code>) ___ Criscuolo A (2020) <em>On the transformation of MinHash-based uncorrected distances into proper evolutionary distances for phylogenetic inference</em>. F1000Research, 9:1309. doi:10.12688/f1000research.26930.1
DOI: 10.5281/zenodo.4034643
title: Model trees and associated simulated nucleotide sequences for testing phylogenetic inference methods

description: This repository contains 142 tar.gz archive files, each containing nucleotide sequence data that have been simulated using <em>INDELible</em> for testing alignment-free phylogenetic inference methods. These datasets were generated by using the results (trees and model parameters) of 142 phylogenomic analyses of real-case data as model (available here). Initial sequence length was 5 Mbs, and an indel rate of 0.01 was set with indel length drawn from [1, 50000] according to a Zipf distribution with parameter 1.5 (see <em>INDELible</em> manual). Each archive contains the following files/directories: <code>GTR.params.trees.tsv </code> a tab-delimited file summarizing the real-case GTR+Γ model parameters and the phylogenetic tree used to simulate the sequence dataset (gathered from https://zenodo.org/record/4034261) <code>tax.tsv </code> a tab-delimited file containing the initial (col 1) and simplified (col 2) taxon names <code>model.nwk </code> a Newick-formatted file containing the initial model tree (gathered from <code>GTR.params.trees.tsv</code>) with simplified leaf names (following <code>tax.tsv</code>) <code>control.txt </code> the <em>INDELible</em> input file used to simulate the evolution of a sequence along the tree in <code>model.nwk</code> <code>seq/ </code> a directory containing the simulated sequences (one FASTA file per leaf in the tree in <code>model.nwk</code>) ___ Criscuolo A (2020) <em>On the transformation of MinHash-based uncorrected distances into proper evolutionary distances for phylogenetic inference</em>. F1000Research, 9:1309. doi:10.12688/f1000research.26930.1
DOI: 10.25919/p4k0-7609
title: Parkes observations for project P1050 semester 2020APRS_37

description: This is a request for observing time for the initial follow-up of pulsar discoveries from the re-processing of the low-latitude Galactic plane section of the HTRU survey (P630). We have now completed a first pass re-processing of the 60 % of the survey with GPU based coherent acceleration search and template bank search pipelines, and have discovered potential 54 previously unknown pulsars. Interesting science can usually only be derived from a new pulsar after confirmation and a follow-up timing campaign is carried out. One year of initial timing is the minimum timespan required to fully characterise any newly-discovered pulsars, essential for deriving pulsar parameters such as the characteristic age, magnetic field strength, spin-down rate, as well as to detect any unexpected behaviour of the pulsar which might result from emission instabilities. This follow-up and timing project is necessary for following up on any interesting pulsar systems discovered from the HTRU Galactic plane survey. Since all of the pulsars on the observing list here are being followed-up for the first time, they will produce completely new and exciting results. In addition, this timing project will enable a large-scale examination of the Galactic plane pulsar population, exploring the true boundaries of pulsar parameter space.
DOI: 10.34740/kaggle/dsv/1688152
title: Petals to metals model
DOI: 10.6084/m9.figshare.13295597
title: Phylogenetic matrix from The postcranial skeleton of the erythrosuchid archosauriform <i>Garjainia prima</i> from the Early Triassic of European Russia

description: Character-taxon matrix used in the phylogenetic analysis
DOI: 10.6084/m9.figshare.13295597.v1
title: Phylogenetic matrix from The postcranial skeleton of the erythrosuchid archosauriform <i>Garjainia prima</i> from the Early Triassic of European Russia

description: Character-taxon matrix used in the phylogenetic analysis
DOI: 10.6084/m9.figshare.13271039
title: The Supplementary of "The Effect of Optimized Carbon Source on Synthesis and Composition of Exopolysaccharides Produced by Lactobacillus paracasei".

description: The UGPG and GMPPB reaction systems.Putative genes related to phosphotransferase system (PTS) in <i>L. paracasei </i>TD 062.
DOI: 10.6084/m9.figshare.13271039.v1
title: The Supplementary of "The Effect of Optimized Carbon Source on Synthesis and Composition of Exopolysaccharides Produced by Lactobacillus paracasei".

description: The UGPG and GMPPB reaction systems.Putative genes related to phosphotransferase system (PTS) in <i>L. paracasei </i>TD 062.
DOI: 10.25919/dztz-1h24
title: Ashmore Reef Marine Park Environmental Assessment 2019

description: This is an overall (parent) record for the data collected from surveys of selected marine and terrestrial environmental values at Ashmore Reef Marine Park that were carried out in 2019. In early 2019 Parks Australia commissioned CSIRO to undertake a survey of selected marine and terrestrial environmental values at Ashmore Reef Marine Park. For the terrestrial component, the required elements were to quantify the diversity and abundance of native and non-native plant species, determine the population status and diversity of birds on the islands and to determine the abundance of non-native invasive tropical fire ants. The remit included any evidence of interactions between the fire ants and native fauna, especially birds and turtles. Specific foci for the marine component of the survey were to assess the abundance of key invertebrates which have historically been the subject of illegal fishing and over-exploitation (trochus, beche-de-mer and giant clams), and to assess status (cover and health) of key habitat forming benthic assemblages (corals, macroalgae and seagrass).
DOI: 10.21227/9xp3-e734
title: the Sintel 4D Light Field Videos dataset

description: The generated dataset consists of 23 synthetic 4D LFVs with 1,204x436 pixels, 9x9 views, and 20--50 frames, and has ground-truth depth values in the central view, so that can be used for training deep learning-based methods. Each scene was rendered with a ``clean'' pass after modifying the production file of ``Sintel'' with reference to the MPI Sintel dataset ~\cite{butler2012naturalistic}. A ``clean'' pass includes complex illumination and reflectance properties including specular reflections, such as smooth shading and specular reflections, while bokeh, motion blur, and semi-transparent objects are excluded.
DOI: 10.34740/kaggle/dsv/1688182
title: Petals to metals model
DOI: 10.18112/openneuro.ds002606.v1.1.0
title: bids_dataset
DOI: 10.5281/zenodo.4293266
title: A complete dietary review of Japanese birds with special focus on molluscs

description: We present a new database reviewing dietary information for all Japanese bird species. The information within this database was collected through intense literary review to provide a complete look at bird species historically present around the country.
DOI: 10.23729/202c0143-31a8-47a5-8f92-2235125fd40a
title: XBA_Ind_XCT preview

description: Various 3D-printed samples imaged to test the capabilities of the device. Materials consist of different metals and shapes. 3D model for PipeJoint is available publicly at https://info.vttresearch.com/3dmetalprint-sharing-platform Preview of PAS dataset https://doi.org/10.23729/7a8f761b-3be0-4038-8199-73b5427978fa
DOI: 10.5281/zenodo.4293278
title: Surface Area Analysis of carbonized-bagasse

description: The Data Set about the result of surface area analysis of the carbonized-bagasse
DOI: 10.5281/zenodo.4293277
title: Surface Area Analysis of carbonized-bagasse

description: The Data Set about the result of surface area analysis of the carbonized-bagasse