cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.28601801.v1
title: Disciplines, Divisions, and Groups for the ANZSRC fields of research classification

description: A classification of the ANZSRC Fields of Research. 5 disciplines: Biological Sciences and Biotechnology (BSB)Engineering, Information and Computing Sciences (EIC)Mathematics, Physics, Chemistry and Earth Sciences (MPCE)Social, Behavioural and Economic Sciences (SBE)Humanities and Creative Arts (HCA)
DOI: 10.6084/m9.figshare.16771945.v1
title: FeO_e135-e180.7z

description: Abundance and distribution of oxide abundances and Mg# values generated from KAGUYA multiband imager (MI) spectra<br>
DOI: 10.6084/m9.figshare.24719019.v3
title: An EEG Dataset of Neural Signatures in a Competitive Two-Player Game Encouraging Deceptive Behavior

description: The dataset features 12 pairs of participants in a two-player deception game, with role switching. EEG data were recorded using 30 electrodes per player, complemented by behavioral logs and EEG trigger timestamps. It includes both raw and preprocessed EEG data, as well as formated data for 1d-CNN classification, catering to various research needs. This comprehensive dataset, offering perspectives of both players and observers in a deceptive context, is a robust foundation for exploring cognitive processes during interactive deceptive tasks.
DOI: 10.6084/m9.figshare.28374224.v1
title: collective efficacy health and environment, US/China/Hong Kong

description: A survey on the relationship between perceived social norms and collective efficacy across two issues (infectious disease and climate change) and three regions (mainland China, Hong Kong, and the United States)
DOI: 10.6084/m9.figshare.28532357.v2
title: CFOSAT_SWIM_tracking

description: This is the dataset supporting the manuscript: Propagation and Dissipation of Southern Ocean Swells: A CFOSAT SWIM-Based Analysis. Results of swell track from NDBC to SWIM together with results of swell trajectories for dissipation calculation are uploaded. S00 to S04 corresponds to 4 steps in mythology. S_calcu is used for dissipation and attenuation calculation. It should be changed when extract the spectral width. S_fig7_8 is used for fig7 and fig8 after the calculation.
DOI: 10.3535/khn-kjt-4by
title: Pyromorphite

description: Digital Specimen for the physical specimen hosted at Tallinn University of Technology.
DOI: 10.3535/vxy-e9h-ffq
title: Barite

description: Digital Specimen for the physical specimen hosted at Tallinn University of Technology.
DOI: 10.48420/24156465.v1
title: Example patient information sheet for a study site for 'Patient views and experiences of preparatory information for CAR-T therapy in England: a qualitative study.'

description: This link contains the patient information sheet used at the one research site in the study, The Manchester Royal Infirmary (MRI), Manchester University NHS Foundation Trust, at the time of patients in the study being treated with CAR-T cell therapy. A further patent information sheet for the second site, The Christie NHS Foundation Trust, is provided in the text of the manuscript for review. The document Manchester Royal Infirmary CAR-T therapy PIS is shared with permission from the copyright owner under the specified licence.
DOI: 10.6084/m9.figshare.13135976.v1
title: Hundred nanosecond molecular dynamics simulation of the G domain of K-Ras4B

description: (This is a public copy of https://figshare.com/s/453b1b215cf2f9270769)<br>This is a one hundred nanosecond simulation of the G domain of K-Ras4B (UNIPROT:P01116-2, residues 1-166). The simulation was generated using GROMACS v.4.6.5 with the AMBER99SB-ILDN forcefield (altered following doi:10.1002/jcc.10262, see References), TIP3P water and 0.15 M salt. The leap-frog integrator with 2 fs timestep was used. A v-rescale thermostat was used at 310 K, with two energy groups (protein+GTP+MG and water+salt) and a time constant of 0.1 ps. PME was used with a tolerance of 1e-5 for the coulomb interactions and a cutoff was used for the VdW interactions, both with a cutoff of 1.1 nm. A Parrinello-rahman barostat was applied with a reference pressure of 1 bar and a time constant of 1 ps. For more information take a look at md.mdp. Coordinates were saved every 1 nanosecond and waters were stripped, resulting in a trajectory of 101 snapshots. <br>The initial model was made using the G-domain of GppNHp bound H-Ras (PDB ID: 4EFL). The protein was converted using MODELLER v9.16(doi:10.1002/cpbi.3 , see References) and GppNHp was converted to GTP by hand.
DOI: 10.3535/3hd-3eh-wth
title: Tourmaline

description: Digital Specimen for the physical specimen hosted at Tallinn University of Technology.
DOI: 10.3535/m39-n7j-emc
title: Pyromorphite

description: Digital Specimen for the physical specimen hosted at Tallinn University of Technology.
DOI: 10.6084/m9.figshare.16892953.v1
title: March 2021 Covid-19 + Vaccines Twitter Streaming Dataset

description: The file contains Tweet IDs* for COVID-19 related tweets collected in <b>March, 2021</b> from <b>Twitter's COVID-19 Streaming Endpoint </b>via a custom script developed by the <b>Social Media Lab (https://socialmedialab.ca/)</b>.<br>Visit <b>our interactive dashboard at https://stream.covid19misinfo.org</b>/ for a preview and some general stats about this COVID-19 Twitter streaming dataset.<br>For more info about <b>Twitter's COVID-19 Streaming Endpoint</b>, visit <b>https://developer.twitter.com/en/docs/labs/covid19-stream/overview</b><br><b>Note</b>: In accordance with Twitter API Terms, the dataset only includes Tweet IDs (as opposed to the actual tweets and associated metadata). To recollect tweets contained in this dataset, you can use programs such as Hydrator (https://github.com/DocNow/hydrator/) or the Python library Twarc (https://github.com/DocNow/twarc/).
DOI: 10.6084/m9.figshare.28600563.v1
title: Additional file 5 of Metabolic profiling of adult and pediatric gliomas reveals enriched glucose availability in pediatric gliomas and increased fatty acid oxidation in adult gliomas

description: Supplementary Table 4. Supporting Data for Figure 4 Focusing on Analysis of Adult Glioblastomas Compared to Pediatric High-Grade Gliomas H3 Mutant.
DOI: 10.3535/530-dpl-t9x
title: Andradite

description: Digital Specimen for the physical specimen hosted at Tallinn University of Technology.
DOI: 10.3535/z5b-k9b-nzf
title: Dufrénite

description: Digital Specimen for the physical specimen hosted at Tallinn University of Technology.
DOI: 10.6084/m9.figshare.11925726.v1
title: Data and analyses for "The Impact of ROTO Track® in Helping Patients With Diabetes Rotate Their Insulin Injections Better (ROTOone)"

description: The data collected during the study "The Impact of ROTO Track® in Helping Patients With Diabetes Rotate Their Insulin Injections Better (ROTOone)".<br>The package additionally contains the data analysis output, figures and tables produced along with the code and instructions to reproduce the calculations.<br><br>
DOI: 10.6084/m9.figshare.12553778.v1
title: Taillardat et al. (2020) - Restoration cost database V5.xlsx from Climate change mitigation potential of wetlands and the cost-effectiveness of their restoration

description: The cost-effective mitigation of climate change through nature-based carbon dioxide removal strategies has gained substantial policy attention. Inland and coastal wetlands (specifically boreal, temperate and tropical peatlands; tundra; floodplains; freshwater marshes; saltmarshes and mangroves) are among the most efficient natural long-term carbon sinks, yet they also release methane (CH<sub>4</sub>) that can offset the carbon they sequester. Here, we conducted a meta-analysis on wetland carbon dynamics to (i) determine the role they play on climate and discuss their suitability for inclusion in greenhouse gas emissions (GHG) mitigation policies; (ii) investigate the cost-effectiveness of wetland restoration for climate change mitigation strategies. Depending on metrics, a wetland can simultaneously be a net carbon sink (i.e. boreal and temperate peatlands net ecosystem carbon budget (NECB) = −28.1 ± 19.13 gC m<sup>−2</sup> y<sup>−1</sup>) but have a net warming effect on climate at the 100 years time-scale (i.e. boreal and temperate peatland sustained global warming potential (SGWP) = 298.2 ± 100.6 gCO<sub>2</sub> eq<sup>−1</sup> m<sup>−2</sup> y<sup>−1</sup>). This ambivalence shows that the choice of metric can lead to misinterpretation on the effect of wetlands on global temperature. Moreover, our review report high heterogeneity and a still limited number of studies that document wetland carbon budgets. In this study, we demonstrate that most coastal and inland wetlands have a net cooling effect as of today. This is explained by the limited CH<sub>4</sub> emissions that undisturbed coastal wetlands produce and the short lifetime of CH<sub>4</sub> in the atmosphere, compared with long-term carbon sequestration for older inland wetlands. Analysis of wetland restoration costs relative to the amount of carbon they can sequester revealed that restoration is more cost-effective in coastal wetlands such as mangroves (US$1800 ton C<sup>−1</sup>) compared with inland wetlands (US$ 4200–49 200 ton C<sup>−1</sup>). For inland wetlands, priority should be given to conservation rather than restoration, while for coastal wetlands, both conservation and restoration may be effective techniques for climate change mitigation.
DOI: 10.3535/vax-7hd-d2x
title: Vesuvianite

description: Digital Specimen for the physical specimen hosted at Tallinn University of Technology.
DOI: 10.6084/m9.figshare.19348058.v2
title: Pseudomized Twitter data- Home and Destination Attachment indexes and Profile information

description: Based on Twitter data.<br>
DOI: 10.6084/m9.figshare.c.3884047_d3.v1
title: Additional file 3: MovieÂ 3. of Microarchitecture of the tsetse fly proboscis

description: Hypopharynx infected with Trypanosoma congolense. (ZIP 149 kb)
DOI: 10.3535/11x-1js-014
title: Anglesite

description: Digital Specimen for the physical specimen hosted at Tallinn University of Technology.
DOI: 10.3535/7af-px4-zl2
title: Topaz

description: Digital Specimen for the physical specimen hosted at Tallinn University of Technology.
DOI: 10.6084/m9.figshare.19561618.v1
title: supplementary tables

description: the supplementary tables
DOI: 10.6084/m9.figshare.22814084.v1
title: Ex2: Network reliability estimation

description: Files whose names contain 'r1' concern reliability estimation for the network from Fig. 2 with component reliabilities given by the vector r1=[0.944, 0.964, 0.958, 0.946, 0.946, 0.948, 0.955, 0.954, 0.93, 0.955, 0.962, 0.952, 0.966]. These files whose names contain 'r2' concern reliability estimation for the network from Fig. 2 with component reliabilities given by the vector r2=[0.707, 0.699, 0.706, 0.693, 0.692, 0.704, 0.707, 0.693, 0.702, 0.708, 0.705, 0.679, 0.684]. Files whose names contain 'MC' concern reliability estimation based on d-MCs, otherwise the network reliability is based on d-MPs. If a file's name contains 'RX', then the file contains data concerning the performance of Chang's procedure for reliability estimation without steps 1 and 2 and Kozyra's procedure IFB (algorithm 1) for a given dataset of random vectors. Otherwise, the file contains data concerning the performance of Chang's procedure for reliability estimation using his first procedure generating random vectors and Kozyra's procedure IRE (algorithm 2). The meaning of columns in all datasets whose name does not contain 'RX' is as follows: 'd' - demand level, 'number' - the number of d-MPs or d-MCs; 'Chang R' and 'Chang T' - reliability estimation and running time, respectively, for Chang's reliability estimation procedure, 'Kozyra R' and 'Kozyra T' - reliability estimation and running time, respectively, for Kozyra's reliability estimation procedure (algorithm 2); 'Chang/Kozyra' - the ratio of the running time of Chang's procedure and the running time of Kozyra's algorithm. The meaning of columns in all datasets whose name contains 'RX' is as follows: 'd' - demand level, 'number' - the number of d-MPs or d-MCs; 'Simple R'/'Simple T' - reliability estimation/running time for Chang's estimation reliability procedure without steps 1-2 for X from a given dataset of random vectors, 'Intersection R'/'Intersection T' - reliability estimation/running time for Kozyra's estimation reliability procedure IFB (algorithm 1); 'Simple/Intersection' - the ration of the computational time of Chang's estimation reliability procedure without steps 1-2 and the running time of Kozyra's estimation reliability procedure IFB (algorithm 1).
DOI: 10.6084/m9.figshare.6369134.v1
title: Efficient Lock-Free Removing and Compaction for the Cache-Trie Data Structure

description: This artifact contains the source code required to run and reproduce the results from the corresponding paper on Cache-trie compaction and remove operations: "Efficient Lock-Free Removing and Compaction for the Cache-Trie Data Structure".<br>Cache-tries improve the running time of conventional lock-free hash tries through the addition of a cache. The addition of this cache has been shown to improve the run time of lookup and insert operations from <i>O</i>(log <i>n</i>) to <i>O</i>(1) time.<br>Here, as described in the accompanying paper, a lock-free remove operation for cache-tries is implemented, both with and without compaction. In addition, a further optimization to the remove operation is presented, along with a performance evaluation comparing the novel implementations against three similar data structures.<br>The implementations presented here are written in Scala using the concurrent reactive programming framework Reactors.IO. Full details on installation as well as running the presented benchmarks are provided in the file <b>artifact-doc.pdf</b>, located at the root level of the artifact.<br>This artifact is provided as a tarball that can be decompressed using standard utilities.
DOI: 10.15468/dl.fj63xs
title: Occurrence Download

description: A dataset containing 38 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "TaxonKey is Rana kukunoris Nikolskii, 1918"
 ]
}

 The dataset includes 38 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009894-250325103851331/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.3535/l0y-lqr-ee5
title: Mollusca

description: Digital Specimen for the physical specimen hosted at Tallinn University of Technology.
DOI: 10.3535/yxw-72k-qsv
title: Monazite

description: Digital Specimen for the physical specimen hosted at Tallinn University of Technology.
DOI: 10.6084/m9.figshare.11629314.v1
title: De novo transcriptome_filter-out

description: This folder contains the transcripts obtained after filter out the transcripts from non-plant species(e.g. endophytic fungi). The plant transcripts were characterized using EggNOG, TransDECODER and BLAST-x tools.The "transcriptome_filter out.xlsx" archive contains the 27,429 transcripts used in abundance quantification and differential expression analysis. Within this archive the "Gene annotation" sheet includes the transcripts ID, EggNOG description, taxonomy, best BLAST-x hit, translation characteristics and, in transcripts codifying transcription factors, the gene family to which they belong.The "transcriptome_filter out.fasta" archive includes the nucleotide sequence of 27,429 transcripts mentioned.<br>
DOI: 10.6084/m9.figshare.2009469.v1
title: Ones et al. 2016

description: The data for the analyses is organized by folder for each figure. Each zip file contains (1) perievent histrograms for each cell used in the analyses (TTx folders), (2) Video Tracking files (VT folder), (3) raw data and parameter files for each tetrode (Neuralynx type), (4) TTL times for each event during a trial during the course of a session, and (5) cluster cut files using the raw data (e.g., TT2_Sorted).
DOI: 10.6084/m9.figshare.23605557.v1
title: gRNA-target-sites for CCSAS paper (Zhong et al., 2021 Microbiome)

description: This dataset contains CRISPR-Cas9 compatible and taxon-specific gRNA-target-site sequences, specifically designed to target host 18S rRNA genes, without affecting microeukaryotes. This enables the profiling of eukaryotic microbiomes associated with metazoans and plants using the CRISPR-Cas Selective Amplicon Sequencing (CCSAS) method (Zhong et al., 2021). The gRNA-target-site oligonucleotide sequences compiled in this database correspond to the V4 region of the 18S rRNA gene in SILVA SSU database v119 (Quast et al., 2003), which can be amplified by the universal 18S primer set, TAReuk454FWD1 and TAReukREV3 (Stoeck et al., 2010). Further details can be found in Zhong et al. (2021) and GitHub page (https://github.com/kevinzhongxu/CasOligo). <br> <strong>References</strong> 1. Zhong KX, Cho A, Deeg CM, Chan AM & Suttle CA. (2021) The use of CRISPR-Cas Selective Amplicon Sequencing (CCSAS) to reveal the eukaryotic microbiome of metazoans. Microbiome 9, 230. https://doi.org/10.1186/s40168-021-01180-0. 2. Quast, C. et al. The SILVA ribosomal RNA gene database project: improved data processing and web-based tools. Nucleic Acids Res. 41, D590–D596 (2013). 3. Stoeck, T. et al. Multiple marker parallel tag environmental DNA sequencing reveals a highly complex eukaryotic community in marine anoxic water. Mol. Ecol. 19, 21–31 (2010). <br> <br>
DOI: 10.6084/m9.figshare.28409531.v1
title: <b>Quorum sensing regulatory protein LsrR affects Avian Pathogenic </b><b><i>Escherichia coli </i></b><b>pathogenicity by regulating </b><b><i>cysN</i></b>

description: The study determined that the <i>cysN</i> gene influences<i> </i>biofilm formation, motility, adhesion, invasion, bacterial persistence, antibiotic susceptibility, and minimum inhibition concentration. Further, the results revealed that LsrR binds to a region -289 to -319 of the <i>cysN</i> promoter. The most intriguing discovery of this study is that <i>cysN</i> contributes to APEC survival efficiency and pathogenicity. Future research studies should explore additional quorum sensing pathways, mechanistic studies on binding affinities, <i>cysN</i> role in multi-drug resistance, and immune modulation mechanisms
DOI: 10.3535/1kg-ett-5n8
title: Cinnabar

description: Digital Specimen for the physical specimen hosted at Tallinn University of Technology.
DOI: 10.3535/w2h-1a7-zv6
title: Apatite

description: Digital Specimen for the physical specimen hosted at Tallinn University of Technology.
DOI: 10.6084/m9.figshare.19122887.v1
title: RNA seq of macrophages from old and young mice

description: Normalized counts from bulk RNA sequencing analysis of macrophages from old and young mice in co-culture with osteoblasts during mineralization<br>
DOI: 10.6084/m9.figshare.25358053.v3
title: data

description: 123456789
DOI: 10.3535/lsd-c6s-8gl
title: sedimentary rocks

description: Digital Specimen for the physical specimen hosted at Tallinn University of Technology.
DOI: 10.3535/p6f-lsj-6pt
title: Tourmaline

description: Digital Specimen for the physical specimen hosted at Tallinn University of Technology.
DOI: 10.6084/m9.figshare.1340582.v1
title: DAS HS 578T

description: The effect of DAS on HS 578T
DOI: 10.3535/2e5-v70-0l4
title: Holonema J.E. Areschoug, 1855

description: Digital Specimen for the physical specimen hosted at Tallinn University of Technology.
DOI: 10.3535/7tx-n6f-6bk
title: Holonema J.E. Areschoug, 1855

description: Digital Specimen for the physical specimen hosted at Tallinn University of Technology.
DOI: 10.6084/m9.figshare.17701202.v1
title: EEG Dataset for RSVP and P300 Speller Brain-Computer Interfaces

description: EEG dataset for subject 45
DOI: 10.6084/m9.figshare.26999575.v1
title: <b>Data set for article "Divergent Subregional Information Processing in Mouse Prefrontal Cortex during Working Memory"</b>

description: This data repository contains six structures storing the data from the Sonneborn et al. Communications Biology publication "Divergent Subregional Information Processing in Mouse Prefrontal Cortex during Working Memory". The six structures contain the raw data used tomake all figures in the paper. Each of the three brain regions in the paper has two corresponding structures, one for raw spike data, and one for sorted behavioral data, including sorted by ports visited. It also containes 2 custom MATLAB functions. <br>The SPIKE STRUCTURES have the raw spiking data for all recorded neurons aligned to important poke events. Each row of these structures corresponds to an individualneuron. The columns are listed below:<br>Column 1 - Session_Name: Shows the mouse number and (session) during which that neuron was recorded. Example: the label NMTP_1(5) has neurons from mouse #1, session #5.<br>Column 2 - Spike_Times: A vector of raw spike timestamps from the output of Kilosort3. Sampled at 30kHz. <br>Remaining Columns: Logical arrays organized in trials x time (30 kHz) matrices. The rows of each matrix are sorted by either the sample ports on individual trials (sample sorted) or the choice ports on individual drials (choice sorted). For example, the column 'SampleSortedChoice' contains logical spike data (1s for spikes, 0s for no spike), sorted by sample port location (Left or Right), during the delay phase of the DNMTP task). <br>The PORT STRUCTURES contain info about how data in the spike arrays was organized by trial type, and also include behavioral data used in several figures. For example, the columnSortedSamplePorts includes the sorting key for individual sessions which shows exactlywhich trials were left and right sample trials for the corresponding neurons in the spikestruct. There is also a similar column for choice struct. For sample ports, Left = 1 and Right = 5. For choice ports, Left = 1, Right = 5, and Center = 3.<br>The functions take the structures as input (one subregion at at time). One function plotsthe cross-temporal support vector machines used in several figures, and the other providesthe GLM analysis used in Figures 6 and 7. Each function contains detailed instructions onhow to input the structures into the functions and read the output.
DOI: 10.3535/88v-g8h-9l5
title: Holonema J.E. Areschoug, 1855

description: Digital Specimen for the physical specimen hosted at Tallinn University of Technology.
DOI: 10.3535/rmc-cza-dvz
title: Holonema J.E. Areschoug, 1855

description: Digital Specimen for the physical specimen hosted at Tallinn University of Technology.
DOI: 10.6084/m9.figshare.25625283.v1
title: <i>Microcroissants</i>

description: Sequence alignments
DOI: 10.3535/0z5-fky-ltz
title: Holonema J.E. Areschoug, 1855

description: Digital Specimen for the physical specimen hosted at Tallinn University of Technology.
DOI: 10.6084/m9.figshare.1326666.v1
title: Wearable Devices (capabilities and pricing)

description: This dataset provides information on several wearables devices, including the Fitbit Flex, Fitbit Charge HR, Basis Peak, GeneActiv Watch and others.
DOI: 10.3535/mt4-xe8-982
title: Holonema J.E. Areschoug, 1855

description: Digital Specimen for the physical specimen hosted at Tallinn University of Technology.
DOI: 10.3535/y88-2ya-3b7
title: Holonema J.E. Areschoug, 1855

description: Digital Specimen for the physical specimen hosted at Tallinn University of Technology.
DOI: 10.3535/5dy-v77-5kp
title: Specimen from Tallinn University of Technology

description: Digital Specimen for the physical specimen hosted at Tallinn University of Technology.
DOI: 10.3535/6qd-lks-6sp
title: Holonema J.E. Areschoug, 1855

description: Digital Specimen for the physical specimen hosted at Tallinn University of Technology.
DOI: 10.3535/0jv-4kp-v19
title: Holonema J.E. Areschoug, 1855

description: Digital Specimen for the physical specimen hosted at Tallinn University of Technology.
DOI: 10.3535/3v7-pwv-50b
title: Brachiopoda Duméril, 1805

description: Digital Specimen for the physical specimen hosted at Tallinn University of Technology.
DOI: 10.3535/d31-31z-erx
title: Brachiopoda Duméril, 1805

description: Digital Specimen for the physical specimen hosted at Tallinn University of Technology.