cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.19396011
title: Additional file 9 of Proteomic profiling of hydatid fluid from pulmonary cystic echinococcosis

description: Additional file 9: Table S6. Comparative analysis of the proteins detected in at least two biological replicates in one of the species.
DOI: 10.6084/m9.figshare.19396011.v1
title: Additional file 9 of Proteomic profiling of hydatid fluid from pulmonary cystic echinococcosis

description: Additional file 9: Table S6. Comparative analysis of the proteins detected in at least two biological replicates in one of the species.
DOI: 10.6084/m9.figshare.19396012
title: Additional file 10 of Phylogenomic analysis of the diversity of graspetides and proteins involved in their biosynthesis

description: Additional file 10. Table S3. Detailed information for graspetides identified in this work
DOI: 10.6084/m9.figshare.19396012.v1
title: Additional file 10 of Phylogenomic analysis of the diversity of graspetides and proteins involved in their biosynthesis

description: Additional file 10. Table S3. Detailed information for graspetides identified in this work
DOI: 10.6084/m9.figshare.19396015
title: Additional file 11 of Phylogenomic analysis of the diversity of graspetides and proteins involved in their biosynthesis

description: Additional file 11. ATP-grasp sequences (fasta format)
DOI: 10.6084/m9.figshare.19396015.v1
title: Additional file 11 of Phylogenomic analysis of the diversity of graspetides and proteins involved in their biosynthesis

description: Additional file 11. ATP-grasp sequences (fasta format)
DOI: 10.6084/m9.figshare.19396018
title: Additional file 12 of Phylogenomic analysis of the diversity of graspetides and proteins involved in their biosynthesis

description: Additional file 12. ATP-grasp tree (newick format)
DOI: 10.6084/m9.figshare.19396021
title: Additional file 13 of Phylogenomic analysis of the diversity of graspetides and proteins involved in their biosynthesis

description: Additional file 13. Final set of precursor sequences; Alignments of 174 distinct clusters of precursors (zip file).
DOI: 10.6084/m9.figshare.19396024.v1
title: Additional file 14 of Phylogenomic analysis of the diversity of graspetides and proteins involved in their biosynthesis

description: Additional file 14. 16s rRNA tree (newick format)
DOI: 10.6084/m9.figshare.19396021.v1
title: Additional file 13 of Phylogenomic analysis of the diversity of graspetides and proteins involved in their biosynthesis

description: Additional file 13. Final set of precursor sequences; Alignments of 174 distinct clusters of precursors (zip file).
DOI: 10.6084/m9.figshare.19396018.v1
title: Additional file 12 of Phylogenomic analysis of the diversity of graspetides and proteins involved in their biosynthesis

description: Additional file 12. ATP-grasp tree (newick format)
DOI: 10.6084/m9.figshare.19396024
title: Additional file 14 of Phylogenomic analysis of the diversity of graspetides and proteins involved in their biosynthesis

description: Additional file 14. 16s rRNA tree (newick format)
DOI: 10.6084/m9.figshare.19396048
title: Additional file 8 of Phylogenomic analysis of the diversity of graspetides and proteins involved in their biosynthesis

description: Additional file 8. Table S1. ATP-grasp sequences in this study and features of respective loci.
DOI: 10.6084/m9.figshare.19396048.v1
title: Additional file 8 of Phylogenomic analysis of the diversity of graspetides and proteins involved in their biosynthesis

description: Additional file 8. Table S1. ATP-grasp sequences in this study and features of respective loci.
DOI: 10.6084/m9.figshare.19396051
title: Additional file 9 of Phylogenomic analysis of the diversity of graspetides and proteins involved in their biosynthesis

description: Additional file 9. Table S2. Detailed information for ATP-grasp loci
DOI: 10.6084/m9.figshare.19396051.v1
title: Additional file 9 of Phylogenomic analysis of the diversity of graspetides and proteins involved in their biosynthesis

description: Additional file 9. Table S2. Detailed information for ATP-grasp loci
DOI: 10.6084/m9.figshare.19396132
title: Additional file 2 of Development and psychometric evaluation of the Physical Resilience Instrument for Older Adults (PRIFOR)

description: Additional file 2.
DOI: 10.6084/m9.figshare.19396132.v1
title: Additional file 2 of Development and psychometric evaluation of the Physical Resilience Instrument for Older Adults (PRIFOR)

description: Additional file 2.
DOI: 10.6084/m9.figshare.19396164
title: Additional file 3 of Shortening of the Burnout Assessment Tool (BAT)—from 23 to 12 items using content and Rasch analysis

description: Additional file 3.
DOI: 10.6084/m9.figshare.19396164.v1
title: Additional file 3 of Shortening of the Burnout Assessment Tool (BAT)—from 23 to 12 items using content and Rasch analysis

description: Additional file 3.
DOI: 10.6084/m9.figshare.19396173
title: Additional file 5 of Shortening of the Burnout Assessment Tool (BAT)—from 23 to 12 items using content and Rasch analysis

description: Additional file 5.
DOI: 10.6084/m9.figshare.19396173.v1
title: Additional file 5 of Shortening of the Burnout Assessment Tool (BAT)—from 23 to 12 items using content and Rasch analysis

description: Additional file 5.
DOI: 10.6084/m9.figshare.19396176
title: Additional file 6 of Shortening of the Burnout Assessment Tool (BAT)—from 23 to 12 items using content and Rasch analysis

description: Additional file 6.
DOI: 10.6084/m9.figshare.19396176.v1
title: Additional file 6 of Shortening of the Burnout Assessment Tool (BAT)—from 23 to 12 items using content and Rasch analysis

description: Additional file 6.
DOI: 10.6084/m9.figshare.19396179.v1
title: Additional file 7 of Shortening of the Burnout Assessment Tool (BAT)—from 23 to 12 items using content and Rasch analysis

description: Additional file 7.
DOI: 10.6084/m9.figshare.19396182.v1
title: Additional file 8 of Shortening of the Burnout Assessment Tool (BAT)—from 23 to 12 items using content and Rasch analysis

description: Additional file 8.
DOI: 10.6084/m9.figshare.19396179
title: Additional file 7 of Shortening of the Burnout Assessment Tool (BAT)—from 23 to 12 items using content and Rasch analysis

description: Additional file 7.
DOI: 10.6084/m9.figshare.19396182
title: Additional file 8 of Shortening of the Burnout Assessment Tool (BAT)—from 23 to 12 items using content and Rasch analysis

description: Additional file 8.
DOI: 10.6084/m9.figshare.13378946
title: Warming causes differential seedling mortalities in tropical tree species

description: Amplicon sequencing data of soil fungi for the warming effect on plant-soil feedback in a tropical montane rain forest.
DOI: 10.6084/m9.figshare.19349870
title: The change of AGB density due to LUCC under five SSPs scenarios

description: The change of above-ground biomass carbon density due to LUCC from 2010 to 2100 under five SSPs scenarios
DOI: 10.6084/m9.figshare.19395637
title: Additional file 5 of Opportunities to improve the impact of two national clinical audit programmes: a theory-guided analysis

description: Additional file 5. Example of an interview summary (TARN).
DOI: 10.5281/zenodo.6374865
title: MIROC4-ACTM CH4 inversion fluxes (2000-2016)

description: This version of inversion is prepared by Dmitry Belikov, Chiba University. Results updated from Chandra et al. (Chandra et al., 2021) Methods detailed in Emissions from the Oil and Gas Sectors, Coal Mining and Ruminant Farming Drive Methane Growth over the Past Three Decades Naveen CHANDRA, Prabir K. PATRA, Jagat S. H. BISHT, Akihiko ITO, Taku UMEZAWA, Nobuko SAIGUSA, Shinji MORIMOTO, Shuji AOKI, Greet JANSSENS-MAENHOUT, Ryo FUJITA, Masayuki TAKIGAWA, Shingo WATANABE, Naoko SAITOH, Josep G. CANADELL DOI https://doi.org/10.2151/jmsj.2021-015
DOI: 10.5281/zenodo.6374864
title: MIROC4-ACTM CH4 inversion fluxes (2000-2016)

description: This version of inversion is prepared by Dmitry Belikov, Chiba University. Results updated from Chandra et al. (Chandra et al., 2021) Methods detailed in Emissions from the Oil and Gas Sectors, Coal Mining and Ruminant Farming Drive Methane Growth over the Past Three Decades Naveen CHANDRA, Prabir K. PATRA, Jagat S. H. BISHT, Akihiko ITO, Taku UMEZAWA, Nobuko SAIGUSA, Shinji MORIMOTO, Shuji AOKI, Greet JANSSENS-MAENHOUT, Ryo FUJITA, Masayuki TAKIGAWA, Shingo WATANABE, Naoko SAITOH, Josep G. CANADELL DOI https://doi.org/10.2151/jmsj.2021-015
DOI: 10.6084/m9.figshare.8868218
title: vHIT VS Longitude Study Data

description: Supplementary data and figures for the publication "The human vestibulo-ocular reflex and compensatory saccades in schwannoma patients before and after vestibular nerve section", by Pogson, et al. 2022. <i>Clinical Neurophysiology</i>. DOI: https://doi.org/10.1016/j.clinph.2022.02.014<br>The LongitudeData file follows 'tidy data' principles, with one column per variable and one row per observation, reading from left to right. Data is described in the DatasheetLegend file.<br>supp_gain_models and supp_sac_models are tables of model outputs that show generalized estimating equations (GEE) values for joint tests of contrasts among each term i.e., “Type-III ANOVA”. See supp_model_key for description of models. <br><br>Table 1 shows mean(lower–upper confidence interval) of the VOR gain, and the first (1) and second (2) saccade metrics across for each semicircular canal and age. See manuscript methods for description of cutoff values for e.g., age-groups. Left and right ear directions are combined. <br>Table 2 shows normal subject ranges per Pogson, et al. (2019) <i>J Neurophysiology</i> DOI: https://doi.org/a10.1152/jn.00847.2018, as well as values calculated from the 40 UVD subjects in this manuscript i.e., respectively for two normal ears and one normal ear for each semicircular canal for three age groups. See manuscript methods for description of cutoff values for e.g., age-groups. Left and right ear directions are combine and can be separated on request.
DOI: 10.6084/m9.figshare.8868218.v1
title: vHIT VS Longitude Study Data

description: Supplementary data and figures for the publication "The human vestibulo-ocular reflex and compensatory saccades in schwannoma patients before and after vestibular nerve section", by Pogson, et al. 2022. <i>Clinical Neurophysiology</i>. DOI: https://doi.org/10.1016/j.clinph.2022.02.014<br>The LongitudeData file follows 'tidy data' principles, with one column per variable and one row per observation, reading from left to right. Data is described in the DatasheetLegend file.<br>supp_gain_models and supp_sac_models are tables of model outputs that show generalized estimating equations (GEE) values for joint tests of contrasts among each term i.e., “Type-III ANOVA”. See supp_model_key for description of models. <br><br>Table 1 shows mean(lower–upper confidence interval) of the VOR gain, and the first (1) and second (2) saccade metrics across for each semicircular canal and age. See manuscript methods for description of cutoff values for e.g., age-groups. Left and right ear directions are combined. <br>Table 2 shows normal subject ranges per Pogson, et al. (2019) <i>J Neurophysiology</i> DOI: https://doi.org/a10.1152/jn.00847.2018, as well as values calculated from the 40 UVD subjects in this manuscript i.e., respectively for two normal ears and one normal ear for each semicircular canal for three age groups. See manuscript methods for description of cutoff values for e.g., age-groups. Left and right ear directions are combine and can be separated on request.
DOI: 10.34820/fk2/pz08ap/skwslg
title: DATA KOPERASI (DATAVERSE).tab

description: Data Koperasi
DOI: 10.34820/fk2/pz08ap
title: Menumbuhkan Daya Saing Koperasi

description: Data mentah penelitian mengenai Koperasi dan digitalisasi
DOI: 10.5281/zenodo.6370715
title: Network Pharmacology-based Approach combined with Bioinformatic Analytics to Elucidate the Potential of Curcumol Against Hepatocellular Carcinoma

description: S1-S3_GO terms enrichment analyses for common targets S4_KEGG pathways enrichment analysis for common targets S5-S7_GO terms enrichment analyses for functional clusters S8_ KEGG pathways enrichment analysis for functional clusters S9.1-S9.4_Rare data of survival analyses (OS, PFS, DFS, DSS, respectively) S10_Rare data of prognostic model for OS
DOI: 10.34740/kaggle/dsv/3336501
title: ECB speeches etc. 1997 to 2022-03-21
DOI: 10.6084/m9.figshare.19396979.v1
title: SUPPLEMENTAL MATERIAL 2: Training-set Paintings and Evaluation-set Paintings

description: This is a supplemental material for the paper <i>Exploratory Research on Influences of Style-Based Categorization on Affective Evaluations of Paintings.</i>
DOI: 10.6084/m9.figshare.19396979
title: SUPPLEMENTAL MATERIAL 2: Training-set Paintings and Evaluation-set Paintings

description: This is a supplemental material for the paper <i>Exploratory Research on Influences of Style-Based Categorization on Affective Evaluations of Paintings.</i>
DOI: 10.48370/ofd/1eazs0
title: Isorhipis melasoides (Laporte, 1835), C-606

description: Coleoptera collection
DOI: 10.5281/zenodo.6374926
title: Codes and results for self-learning entropic population annealing for interpretable materials design

description: Codes that can reproduce the results in the paper entitled "self-learning entropic population annealing for interpretable materials design". Results, when the number of particles is 50, are included.
DOI: 10.5281/zenodo.6374925
title: Codes and results for self-learning entropic population annealing for interpretable materials design

description: Codes that can reproduce the results in the paper entitled "self-learning entropic population annealing for interpretable materials design". Results, when the number of particles is 50, are included.
DOI: 10.48370/ofd/ffycpp
title: Isorhipis melasoides (Laporte, 1835), C-607

description: Coleoptera collection
DOI: 10.48370/ofd/zuzudp
title: Melasis buprestoides (Linnaeus, 1761), C-608

description: Coleoptera collection
DOI: 10.48370/ofd/3rnyzy/xhgbms
title: Xylophilus corticalis.jpg

description: :unav
DOI: 10.48370/ofd/3rnyzy
title: Xylophilus corticalis (Paykull, 1800), C-609

description: Coleoptera collection
DOI: 10.48370/ofd/egoizk/6bp5pe
title: Xylophilus testaceus.jpg

description: :unav
DOI: 10.48370/ofd/egoizk
title: Xylophilus testaceus (Herbst, 1806), C-610

description: Coleoptera collection
DOI: 10.5281/zenodo.6374104
title: CellTypeGraph Benchmark

description: This repository contains the benchmark dataset proposed in: CellTypeGraph: A New Geometric Computer Vision Benchmark, Cerrone et al., CVPR2022 <strong>Paper Abstract:</strong> Classifying all cells in an organ is a relevant and difficult problem from plant developmental biology. We here abstract the problem into a new benchmark for node classification in a geo-referenced graph. Solving it requires learning the spatial layout of the organ including symmetries. <br> To allow the convenient testing of new geometrical learning methods, the benchmark of <em>Arabidopsis thaliana</em> ovules is made available as a PyTorch data loader, along with a large number of precomputed features. <strong>Raw Data Source:</strong> The benchmark raw data is derived from "A digital 3D reference atlas reveals cellular growth patterns shaping the <em>Arabidopsis</em> ovule, A. Vijayan et al., eLife 2021". <strong>Source code:</strong> Repository for using the benchmark: https://github.com/hci-unihd/celltype-graph-benchmark Repository for reproducing the experiments in the manuscript: https://github.com/hci-unihd/plant-celltype <strong>Index:</strong> Repository for using the benchmark (data-loaders, transforms, metrics): https://github.com/hci-unihd/celltype-graph-benchmark Repository for reproducing the experiments in the manuscript (experiments, training, GNN models, features extraction, visualization, inference): https://github.com/hci-unihd/plant-celltype <strong>Download integrity check (md5sum):</strong> raw_data.zip: fd0ecccdea684d156fd8ac182a22251b label_grs_surface.zip: 51e21dc509a9205b9ec47f38a307b156
DOI: 10.5281/zenodo.6352390
title: CellTypeGraph Benchmark

description: This repository contains the benchmark dataset proposed in: CellTypeGraph: A New Geometric Computer Vision Benchmark, Cerrone et al., CVPR2022 <strong>Paper Abstract:</strong> Classifying all cells in an organ is a relevant and difficult problem from plant developmental biology. We here abstract the problem into a new benchmark for node classification in a geo-referenced graph. Solving it requires learning the spatial layout of the organ including symmetries. <br> To allow the convenient testing of new geometrical learning methods, the benchmark of <em>Arabidopsis thaliana</em> ovules is made available as a PyTorch data loader, along with a large number of precomputed features. <strong>Raw Data Source:</strong> The benchmark raw data is derived from "A digital 3D reference atlas reveals cellular growth patterns shaping the <em>Arabidopsis</em> ovule, A. Vijayan et al., eLife 2021". <strong>Source code:</strong> Repository for using the benchmark: https://github.com/hci-unihd/celltype-graph-benchmark Repository for reproducing the experiments in the manuscript: https://github.com/hci-unihd/plant-celltype <strong>Index:</strong> Repository for using the benchmark (data-loaders, transforms, metrics): https://github.com/hci-unihd/celltype-graph-benchmark Repository for reproducing the experiments in the manuscript (experiments, training, GNN models, features extraction, visualization, inference): https://github.com/hci-unihd/plant-celltype <strong>Download integrity check (md5sum):</strong> raw_data.zip: fd0ecccdea684d156fd8ac182a22251b label_grs_surface.zip: 51e21dc509a9205b9ec47f38a307b156
DOI: 10.48370/ofd/iyjgt5/amucds
title: Pityophagus ferrugineus.jpg

description: :unav
DOI: 10.48370/ofd/iyjgt5
title: Pityophagus ferrugineus (Linnaeus, 1761), C-611

description: Coleoptera collection
DOI: 10.48370/ofd/j8agxt/1sqsss
title: Pityophagus ferrugineus.jpg

description: :unav
DOI: 10.48370/ofd/j8agxt
title: Pityophagus ferrugineus (Linnaeus, 1761), C-612

description: Coleoptera collection
DOI: 10.13016/m2yt-mfxk
title: Experimental data from Francis et al. (2022) "Sequential Transmission of Task-Relevant Information in Cortical Neuronal Networks", bioRxiv (https://doi.org/10.1101/2021.08.31.458395)
DOI: 10.34808/a2v2-c880
title: The impact of QDgreen, QDgreen−β−CD−FA, β−CD, C−2028, β−CD(C−2028), QDgreen−C−2028, and QDgreen−β−CD(C−2028)−FA nanoconjugates on lysosomal content in the cancer (H460, Du-145, LNCaP) and normal (MRC-5, PNT1A) cells

description: The impact of QDgreen, QDgreen−β−CD−FA, β−CD, C−2028, β−CD(C−2028), QDgreen−C−2028, and QDgreen−β−CD(C−2028)−FA nanoconjugates on lysosomal content in the cancer (H460, Du-145, LNCaP) and normal (MRC-5, PNT1A) cells was performed by Confocal Laser Scanning Microscopy (63× magnification; ZEISS LSM T-PMT, Magdeburg, Germany). To explore the influence of compounds on lysosomal content in the cells LysoTracker Red DND-99 (Invitrogen, USA) was added to a final concentration of 100 nM for 15 min at 37 °C. The imaging conditions were: QDgreen (λex = 300 nm, λem = 543 nm), C−2028 (λex = 528 nm, λem = 553 nm), and LysoTracker Red DND-99 (λex = 578 nm, λem = 700 nm). The Mean Fluorescence Intensity (MFI) of LysoTracker Red DND-99 from the images was performed with ImageJ software (version 1.8.0., Wisconsin, Madison, USA). The scale bar is 20 µm.
DOI: 10.26165/juelich-data/bropel
title: Measurement-Ionic Liquid Water Mixtures in Confinement 01

description: Dataset exported from iffSamples.
DOI: 10.34820/fk2/a1vcsu/hm6qgz
title: phone_ont.2.6.5.owl

description: Smartphone Ontology
DOI: 10.34820/fk2/a1vcsu
title: Smartphone Ontology

description: This dataset is a smartphone ontology that used for developing conversational recommender system in smartphone domain
DOI: 10.5281/zenodo.6374951
title: Bathymetry data from detonation scars in the Fehmarnbelt, German Baltic Sea.

description: The bathymetric data were collected on the 27<sup>th</sup> of June 2020 as underway research data on a 1.5 km track during the cruise EMB239 with the German research vessel Elisabeth Mann Borgese. The objective of the data acquisition was to survey seafloor scars resulting from the controlled detonation of ground mines. For data acquisition, the ship’s hull-mounted Sonic 2024 (R2Sonic Inc.) multibeam echosounder was used. The raw sonar data were loaded in Qimera v2.4.3 (Quality Positioning Services B.V.) and automatically processed to compute sounding footprint location under consideration of sound velocity, position, motion, and heading information. To make the data usable without any specific software, the georeferenced soundings were exported without any bathymetric data cleaning as comma-separated ASCII file in the coordinate reference system EPSG: 32632 - WGS84 / UTM zone 32N. For more details please refer to Papenmeier, S., Darr, A., Feldens, P. (in prep): Geomorphological data from detonation craters in the Fehmarnbelt, German Baltic Sea.
DOI: 10.5281/zenodo.6374950
title: Bathymetry data from detonation scars in the Fehmarnbelt, German Baltic Sea.

description: The bathymetric data were collected on the 27<sup>th</sup> of June 2020 as underway research data on a 1.5 km track during the cruise EMB239 with the German research vessel Elisabeth Mann Borgese. The objective of the data acquisition was to survey seafloor scars resulting from the controlled detonation of ground mines. For data acquisition, the ship’s hull-mounted Sonic 2024 (R2Sonic Inc.) multibeam echosounder was used. The raw sonar data were loaded in Qimera v2.4.3 (Quality Positioning Services B.V.) and automatically processed to compute sounding footprint location under consideration of sound velocity, position, motion, and heading information. To make the data usable without any specific software, the georeferenced soundings were exported without any bathymetric data cleaning as comma-separated ASCII file in the coordinate reference system EPSG: 32632 - WGS84 / UTM zone 32N. For more details please refer to Papenmeier, S., Darr, A., Feldens, P. (in prep): Geomorphological data from detonation craters in the Fehmarnbelt, German Baltic Sea.
DOI: 10.6084/m9.figshare.19397099
title: YarlungZangbo Dataset

description: This dataset includes simulated rainfall field from WRF simulations and gridded raifnall product CN05.1. The list of POT flood records are also included.
DOI: 10.48370/ofd/psr2s9
title: Pityophagus laevior (Abeille de Perrin, 1872), C-613

description: Coleoptera collection
DOI: 10.5281/zenodo.6371237
title: Dataset for small pelagic stocks assessment in Moroccan Atlantic coast

description: Datasets for stock assessment of small pelagic stocks in Moroccan Atlantic coast, Including available data on catches (all small pelagic stocks), fishing effort (sardine and chub mackerel stocks), age and length composition of landings (sardine and chub mackerel stocks), biological parameters (sardine, chub mackerel and anchovy), surveys data (sardine, chub mackerel and anchovy.
DOI: 10.6084/m9.figshare.19397132
title: Entire Arthropod Dataset (Input data for R script).xlsx

description: Input data for R script.<br>
DOI: 10.5281/zenodo.6371236
title: Dataset for small pelagic stocks assessment in Moroccan Atlantic coast

description: Datasets for stock assessment of small pelagic stocks in Moroccan Atlantic coast, Including available data on catches (all small pelagic stocks), fishing effort (sardine and chub mackerel stocks), age and length composition of landings (sardine and chub mackerel stocks), biological parameters (sardine, chub mackerel and anchovy), surveys data (sardine, chub mackerel and anchovy.
DOI: 10.34820/fk2/0pql9o/yo0cgp
title: penjualan.csv

description: :unav
DOI: 10.34820/fk2/0pql9o
title: Sales Dataset

description: Sales Dataset from Puri Utami