cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.3613688
title: Atlas for RecobundlesX

description: <strong>Multi-atlas bundle segmentation</strong> This data is made to be used with the following script: scil_recognize_multi_bundles.py This script is in fact a multi-atlas, multi-parameters version of <em>Garyfallidis et al. (2018)</em> with labels fusions. We name this algorithm RecobundlesX. If you have any questions, email <em>francois.rheault@gmail.com.</em> <em>Garyfallidis, Eleftherios, et al. "Recognition of white matter bundles using local and global streamline-basedregistration and clustering." NeuroImage 170 (2018): 283-295.</em>
DOI: 10.5281/zenodo.2547025
title: Tractostorm: Rater reproducibility assessment in tractography dissection of the pyramidal tract

description: Segmentation of the 13 experts and 11 non-experts for the Tractostorm project. Contains the original dataset each participants received to perform their tasks. The tractography file format is *.trk and the image file format is *.nii.gz
DOI: 10.5281/zenodo.2547024
title: Tractostorm: Rater reproducibility assessment in tractography dissection of the pyramidal tract

description: Segmentation of the 13 experts and 11 non-experts for the Tractostorm project. Contains the original dataset each participants received to perform their tasks. The tractography file format is *.trk and the image file format is *.nii.gz
DOI: 10.5258/soton/d1422
title: Dataset for the paper: Reliable UHF Long-Range Textile-Integrated RFID Tag based on a Compact Flexible Antenna Filament

description: Data supports the paper: Wagih, M.; Wei, Y.; Komolafe, A.; Torah, R.; Beeby, S. Reliable UHF Long-Range Textile-Integrated RFID Tag Based on a Compact Flexible Antenna Filament. Sensors 2020, 20, 3435.
DOI: 10.5258/soton/d1184
title: Dataset for: A mechanical approach to understanding the impact of the nematode Anguillicoloides crassus on the European eel swimbladder

description: Dataset supports: Currie, H.A.L., Flores Martin, N., Espindola Garcia, G., Davis, F.M., & Kemp, P.S. (2020). A mechanical approach to understanding the impact of the nematode Anguillicoloides crassus on the European eel swimbladder. J. Exp. Biol.
DOI: 10.5281/zenodo.3928402
title: WP6 dataset.csv

description: EmERGE Validation study dataset (csv)
DOI: 10.5281/zenodo.3928401
title: WP6 dataset.csv

description: EmERGE Validation study dataset (csv)
DOI: 10.5281/zenodo.3928444
title: WP6 Dataset.dta

description: EmERGE Validation study dataset
DOI: 10.5281/zenodo.3928443
title: WP6 Dataset.dta

description: EmERGE Validation study dataset
DOI: 10.5281/zenodo.3928299
title: First report of electron measurements during a Europa footprint tail crossing

description: This is the repository for the data files for Figures 1, 2, and 3 of the manuscript "First report of electron measurements during a Europa footprint tail crossing" by F. Allegrini et al. Abstract: We report the first in situ observations of electron measurements at a Europa footprint tail (FPT) crossing in the auroral region. During its 12<sup>th</sup> science perijove pass, Juno crossed magnetic field lines connected to Europa’s footprint tail. We find that electrons in the range ~0.4 to ~25 keV, with a characteristic energy of 3.3 ± 0.4 keV, precipitate into Jupiter’s atmosphere to create the footprint aurora. The energy flux peaks at ~30 mW/m<sup>2</sup>, while the peak ultraviolet (UV) brightness is estimated at 37 kR. We estimate the peak electron density and temperature to be 17.3 cm<sup>−3</sup> and 1.6 ± 0.1 keV, respectively. Using magnetic flux shell mapping, we estimate that the radial width of the interaction at Europa’s orbit spans roughly 3.6 ± 1.0 Europa radii. In contrast to typical Io FPT crossings, the instrument background caused by penetrating energetic radiation (&gt;~5-10 MeV electrons) increased during the Europa FPT crossing.
DOI: 10.5281/zenodo.3925679
title: Smartphone Gyroscope and Accelerometer Dataset for Human Activity Recognition

description: This dataset is from a study in which we collected smartphone accelerometer and gyroscope data of four subjects while they performed various activities. Two iPhone smartphones were used, with one in the front pants pocket and the other in the back pants pocket. The datasets have been annotated with ground truth activity labels based on video footage. The study procedure is described in our paper: Huang, E.J. and Onnela, J.P. Augmented Movelet Method for Activity Classification Using Smartphone Gyroscope and Accelerometer Data. Sensors 2020, 20, 3706.
description: {"references": ["Huang, E.J. and Onnela, J.P. Augmented Movelet Method for Activity Classification Using Smartphone Gyroscope and Accelerometer Data. Sensors 2020, 20, 3706."]}
DOI: 10.5281/zenodo.3925678
title: Smartphone Gyroscope and Accelerometer Dataset for Human Activity Recognition

description: This dataset is from a study in which we collected smartphone accelerometer and gyroscope data of four subjects while they performed various activities. Two iPhone smartphones were used, with one in the front pants pocket and the other in the back pants pocket. The datasets have been annotated with ground truth activity labels based on video footage. The study procedure is described in our paper: Huang, E.J. and Onnela, J.P. Augmented Movelet Method for Activity Classification Using Smartphone Gyroscope and Accelerometer Data. Sensors 2020, 20, 3706.
description: {"references": ["Huang, E.J. and Onnela, J.P. Augmented Movelet Method for Activity Classification Using Smartphone Gyroscope and Accelerometer Data. Sensors 2020, 20, 3706."]}
DOI: 10.5281/zenodo.3926933
title: CCLid: A toolkit to authenticate the genotype and stability of cancer cell lines

description: CCLid (Cancer Cell Line identification) is designed as a toolkit to address the lack of a publicly available resource for genotype-based cell line authentication. We developed this resource to allow for genotype-matching of any given cancer cell line to the 1,204 unique cell lines found in the CCLE dataset, with support to include additional SNP array datasets. Using the B-allele frequencies (BAFs) for all SNPs found in common between the input data and reference datasets, this tool will allow for a genotype matching operation that trains and uses a logistic model to calculate the probability of the best cell line matches. This is followed by a measure of genetic drift between isogenic lines by look for segments of the genome that have significantly different BAF values. This zenodo dataset contains the (sample x probeset) BAF matrix for the CCLE dataset, as well as supporting datasets to allow mapping of SNP probesets and genotype correction between SNP array technologies (i.e. Affymetrix SNP 6.0 and Illumina HumanOmni 2.5M). This also contains all the metadata for cell line identities in CCLE, GDSC, and gCSI as well their corresponding cellosaurus unique identifies.
DOI: 10.5281/zenodo.3891804
title: CCLid: A toolkit to authenticate the genotype and stability of cancer cell lines

description: CCLid (Cancer Cell Line identification) is designed as a toolkit to address the lack of a publicly available resource for genotype-based cell line authentication. We developed this resource to allow for genotype-matching of any given cancer cell line to the 1,204 unique cell lines found in the CCLE dataset, with support to include additional SNP array datasets. Using the B-allele frequencies (BAFs) for all SNPs found in common between the input data and reference datasets, this tool will allow for a genotype matching operation that trains and uses a logistic model to calculate the probability of the best cell line matches. This is followed by a measure of genetic drift between isogenic lines by look for segments of the genome that have significantly different BAF values. This zenodo dataset contains the (sample x probeset) BAF matrix for the CCLE dataset, as well as supporting datasets to allow mapping of SNP probesets and genotype correction between SNP array technologies (i.e. Affymetrix SNP 6.0 and Illumina HumanOmni 2.5M). This also contains all the metadata for cell line identities in CCLE, GDSC, and gCSI as well their corresponding cellosaurus unique identifies.
DOI: 10.5281/zenodo.3928449
title: WP6 Dataset.sav

description: EmERGE Validation Study
DOI: 10.5281/zenodo.3928448
title: WP6 Dataset.sav

description: EmERGE Validation Study
DOI: 10.5281/zenodo.3928455
title: WP6 Dataset.v8xpt

description: EmERGE Validation Study Dataset
DOI: 10.5281/zenodo.3928454
title: WP6 Dataset.v8xpt

description: EmERGE Validation Study Dataset
DOI: 10.5281/zenodo.3928150
title: RealVAD: A Real-world Dataset for Voice Activity Detection

description: <strong>RealVAD: A Real-world Dataset for Voice Activity Detection</strong> The task of automatically detecting “Who is Speaking and When” is broadly named as Voice Activity Detection (VAD). Automatic VAD is a very important task and also the foundation of several domains, e.g., human-human, human-computer/ robot/ virtual-agent interaction analyses, and industrial applications. RealVAD dataset is constructed from a YouTube video composed of a panel discussion lasting approx. 83 minutes. The audio is available from a single channel. There is one static camera capturing all panelists, the moderator and audiences. Particular aspects of RealVAD dataset are: It is composed of panelists with different nationalities (British, Dutch, French, German, Italian, American, Mexican, Columbian, Thai). This aspect allows studying the effect of ethnic origin variety to the automatic VAD. There is a gender balance such that there are four female and five male panelists. The panelists are sitting in two rows and they can be gazing audience, other panelists, their laptop, the moderator or anywhere in the room while speaking or not-speaking. Therefore, they were captured not only from frontal-view but also from side-view varying based on their instant posture and head orientation. The panelists are moving freely and are doing various spontaneous actions (e.g., drinking water, checking their cell phone, using their laptop, etc.), resulting in different postures. The panelists’ body parts are sometimes partially occluded by their/other's body part or belongings (e.g., laptop). There are also natural changes of illumination and shadow rising on the wall behind the panelists in the back row. Especially, for the panelists sitting in the front row, there is sometimes background motion occurring when the person(s) behind them moves. The annotations includes: The upper body detection of nine panelists in bounding box form. Associated VAD ground-truth (speaking, not-speaking) for nine panelists. Acoustic features extracted from the video: MFCC and raw filterbank energies. <em>All info regarding the annotations are given in the ReadMe.txt and Acoustic Features README.txt files.</em> <strong>When using this dataset for your research, please cite the following paper in your publication:</strong> C. Beyan, M. Shahid and V. Murino, "RealVAD: A Real-world Dataset and A Method for Voice Activity Detection by Body Motion Analysis", in IEEE Transactions on Multimedia, 2020.
DOI: 10.24396/ordar-38
title: Data - H in enstatite chondrites

description: Hydrogen content and isotopic composition in enstatite chondrites _ SIMS and EA-IRMS data
DOI: 10.5281/zenodo.3928500
title: Probe requests of 24 devices in a semianechoic chamber

description: This dataset was created collecting probe requests generated by 24 devices inside a semianechoic chamber. The scanning duration is around 22 minutes and for each probe request acquired, several details are reported: - MAC ADDRESS: for privacy reasons the id annotated in mac column is the result of hashing with SHA256 algorithm on the original mac address - SEQ: the sequence number of the probe request - TIME: is the unixtime of istant when the probe request where collected - ID_X: for each column, the X value indicates the information element ID and its value represents the length for that field - OUI: indicates the Organizationally Unique Identifier directly from the original mac address - VENDOR: contains the vendor extracted from the original OUI.
DOI: 10.5281/zenodo.3928499
title: Probe requests of 24 devices in a semianechoic chamber

description: This dataset was created collecting probe requests generated by 24 devices inside a semianechoic chamber. The scanning duration is around 22 minutes and for each probe request acquired, several details are reported: - MAC ADDRESS: for privacy reasons the id annotated in mac column is the result of hashing with SHA256 algorithm on the original mac address - SEQ: the sequence number of the probe request - TIME: is the unixtime of istant when the probe request where collected - ID_X: for each column, the X value indicates the information element ID and its value represents the length for that field - OUI: indicates the Organizationally Unique Identifier directly from the original mac address - VENDOR: contains the vendor extracted from the original OUI.
DOI: 10.5519/qd.fd575ew6
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (1 records)
DOI: 10.5281/zenodo.3928503
title: Atlas for RecobundlesX

description: <strong>Multi-atlas bundle segmentation</strong> This data is made to be used with the following script: scil_recognize_multi_bundles.py This script is in fact a multi-atlas, multi-parameters version of <em>Garyfallidis et al. (2018)</em> with labels fusions. We name this algorithm RecobundlesX. If you have any questions, email <em>francois.rheault@gmail.com.</em> <em>Garyfallidis, Eleftherios, et al. "Recognition of white matter bundles using local and global streamline-basedregistration and clustering." NeuroImage 170 (2018): 283-295.</em>
DOI: 10.34622/datarepositorium/zxjgnt/grhkvq
title: LibQualQuestionario_PT2018.pdf

description: Questionário (PT)
DOI: 10.34622/datarepositorium/zxjgnt/4bm18q
title: LibQualQuestionario_Ing2018.pdf

description: Survey (EN)
DOI: 10.34622/datarepositorium/zxjgnt/pc3peg
title: LibQualDados2018.tab

description: Dados em bruto
DOI: 10.34622/datarepositorium/qlxewj/ur2tuh
title: LibQualQuestionario_Ing2019.pdf

description: Survey (EN)
DOI: 10.34622/datarepositorium/qlxewj/o9gcjz
title: LibQualQuestionario_PT2019.pdf

description: Questionário (PT)
DOI: 10.34622/datarepositorium/qlxewj/6im1ho
title: LibQualDados2019.tab

description: Dados em bruto
DOI: 10.5519/qd.47bcjjet
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (1 records)
DOI: 10.4119/unibi/2943918
title: Dataset Exploring Fixation-related Potentials in Naturalistic Search Tasks
DOI: 10.17632/pyfwcwks5w.1
title: Data for: TARGETING HIGHER LEVELS OF LACTATE IN THE POST-INJURY PERIOD FOLLOWING TRAUMATIC BRAIN INJURY
DOI: 10.25405/data.ncl.12047292
title: Biodegradable bone cement loaded with doxorubicin-based nanoparticles: In Vitro behaviour of co-cultured osteosarcoma and mesenchymal stem cells

description: Data set with raw data for mechanical properties in compression, ATR-FTIR, curing time and injectability, X-Rays (radiopaque properties), IC50, drug release of both nanoparticles (NPs) and bone cements, DLS , cellular work (metabolic activity, LDH, live & dead, confocal, SEM), pores size
DOI: 10.25405/data.ncl.12047292.v1
title: Biodegradable bone cement loaded with doxorubicin-based nanoparticles: In Vitro behaviour of co-cultured osteosarcoma and mesenchymal stem cells

description: Data set with raw data for mechanical properties in compression, ATR-FTIR, curing time and injectability, X-Rays (radiopaque properties), IC50, drug release of both nanoparticles (NPs) and bone cements, DLS , cellular work (metabolic activity, LDH, live & dead, confocal, SEM), pores size
DOI: 10.5281/zenodo.3928240
title: WHO tweets data

description: Dataset in .csv and with tweets from WHO. Datasets contain additional data about tweets languages.
DOI: 10.5281/zenodo.3798211
title: WHO tweets data

description: Dataset in .csv and with tweets from WHO. Datasets contain additional data about tweets languages.
DOI: 10.17632/5zf83p3tv6.1
title: Data for: The influence of energy recovery on the Overall Efficiency of acoustic sources at low frequencies

description: Simulation in LTspice IV and in combination with MATLAB R2015b, related to Fig.13a in the manuscript.
DOI: 10.15129/02db89e9-64d1-4ded-9324-6d952ce35099
title: Data and Code for the EEM2020 Wind Power Forecasting Competition

description: The competition data and code used by Team 12 to come second in the 2020 European Energy Market Conference Wind Power Forecasting Competition. The competition was organized and hosted by the EEM20 organizing team at KTH. The organizers thank Greenlytics for archiving the data for the competition. The weather data used for the competition has been acquired from met.no and the organizers acknowledge MET Norway for making it available. EEMwind2020_1.tar.gz is an R package containing the source code and data generated by Team 12. It may be installed from source using this file. EEM2020data.zip and EEM2020data2.zip contain the competition data. Weather forecasts are in netCDF format. Power and wind farm data are in csv files. EEM2020data should be placed in the same folder as the EEMwind2020 R package and the subfolders in *data2 should be moved to *data in order to run the scripts.
DOI: 10.21227/g924-sq30
title: EEG of Genetic Absence Epilepsy Rats (GAERS)

description: This Dataset contains EEG recordings from epileptic rats. The genetic absence epilepsy rats (GAERS) are one of the best-established rodent models for generalized epilepsy. The rats show seizures with characteristic "spike and wave discharge" EEG patterns. Experiments were performed in accordance with the German law on animal protection and were approved by the Animal Care and Ethics Committee of the University of Kiel.
DOI: 10.17632/wvyydpdwhp.2
title: JAAD-D-19-02780R2 Appendix

description: Supplemental appendix to describe methods for our systematic review and case series.
DOI: 10.17632/wvyydpdwhp.1
title: JAAD-D-19-02780R2 Appendix

description: Supplemental appendix to describe methods for our systematic review and case series.
DOI: 10.5519/qd.5i0cz7fl
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (9 records)
DOI: 10.5519/qd.sz19i1vq
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (21 records)
DOI: 10.5281/zenodo.3928585
title: Likely weakening of the Florida Current during the past century revealed by sea-level observations

description: This file accompanies the paper 'Likely weakening of the Florida Current during the past century revealed by sea-level observations' by Christopher G. Piecuch published in Nature Communications. It contains the probabilistic reanalysis of annual Florida Current transport during 1909-2018 (e.g., Figure 2 in the paper). Please cite the accompanying paper if you use the data and/or find the data useful.
description: {"references": ["Piecuch, C. G. (2020). Likely weakening of the Florida Current during the past century revealed by sea-level observations."]}
DOI: 10.5281/zenodo.3928584
title: Likely weakening of the Florida Current during the past century revealed by sea-level observations

description: This file accompanies the paper 'Likely weakening of the Florida Current during the past century revealed by sea-level observations' by Christopher G. Piecuch published in Nature Communications. It contains the probabilistic reanalysis of annual Florida Current transport during 1909-2018 (e.g., Figure 2 in the paper). Please cite the accompanying paper if you use the data and/or find the data useful.
description: {"references": ["Piecuch, C. G. (2020). Likely weakening of the Florida Current during the past century revealed by sea-level observations."]}
DOI: 10.5519/qd.2d04ud2y
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (8 records)
DOI: 10.5281/zenodo.3928592
title: Some Similarities and Differences between the Observed Alfvénic Fluctuations in the Fast Solar Wind and Navier-Stokes Turbulence

description: Three text data sets are uploaded: wind tunnel data (modane1.txt), solar-wind magnetic-field data (Flat1maginterp.txt) and solar-wind velocity data (Flat15interp3DP.txt)
DOI: 10.5281/zenodo.3928591
title: Some Similarities and Differences between the Observed Alfvénic Fluctuations in the Fast Solar Wind and Navier-Stokes Turbulence

description: Three text data sets are uploaded: wind tunnel data (modane1.txt), solar-wind magnetic-field data (Flat1maginterp.txt) and solar-wind velocity data (Flat15interp3DP.txt)
DOI: 10.7910/dvn/66qcg6/4as4t4
title: LewerSaenz Estimates TBML within European Union-1.tab

description: :unav
DOI: 10.17632/7bf75ymb3w.1
title: Data for: The nature of subduction system in the Neoarchean: magmatic records from the northern Yangtze Craton, South China
DOI: 10.5281/zenodo.3928481
title: Gibbs 7002G Nafplio Prosymna globe sundial

description: Textured 3D model of the entire surface except region near bottom (uninscribed). Compressed (ZIP) WaveFront OBJ generated by photogrammetry (Agisoft Photoscan Standard 1.4.5) from photographs taken with a Nikon D7100 and an iPhone 4S. Each compressed file contains .obj, .mtl, .obj.mtl, and/pr .jpg files. Radius of globe: 26.2 cm. Archaeological Museum of Nafplio s.n.<br> Gibbs 7002G<br> Berlin Ancient Sundials ObjID269 Dialface ID 284, 719, 723<br> Bonnin fiche 556<br> Winter Prosymna 1
DOI: 10.5281/zenodo.3928480
title: Gibbs 7002G Nafplio Prosymna globe sundial

description: Textured 3D model of the entire surface except region near bottom (uninscribed). Compressed (ZIP) WaveFront OBJ generated by photogrammetry (Agisoft Photoscan Standard 1.4.5) from photographs taken with a Nikon D7100 and an iPhone 4S. Each compressed file contains .obj, .mtl, .obj.mtl, and/pr .jpg files. Radius of globe: 26.2 cm. Archaeological Museum of Nafplio s.n.<br> Gibbs 7002G<br> Berlin Ancient Sundials ObjID269 Dialface ID 284, 719, 723<br> Bonnin fiche 556<br> Winter Prosymna 1
DOI: 10.17909/t9-1a6b-jk76
title: A PSF-Based Approach To Kepler/K2 Data ("PSFK2")

description: The Kepler/K2 mission offered to the science community the opportunity of obtaining high-precision light curves for a large variety of stellar fields, including stellar clusters. However, most Kepler/K2 data analyses reported in the literature are based on aperture photometry. Aperture photometry is perfectly suitable to investigating stars in sparse fields but it suffers from severe limitations in crowded environments like the central regions of stellar clusters. Thus, the wealth of information included in stellar clusters analyzed with the Kepler/K2 mission is often unexplored. The team has made use of their experience with undersampled Hubble Space Telescope images and developed a new method to analyze crowded regions with the Kepler/K2 data. The combination of a high-angular-resolution catalog and accurate point-spread-function (PSF) models allows them to pinpoint a star in a Kepler/K2 exposure and measure its flux after all detectable nearby stars are PSF subtracted from the image. This PSF-based technique: (i) increases the number of analyzable objects in the field, (ii) provides an unbiased flux measurement for each source, (iii) extracts stellar light curves in a crowded environment and (iv) improves the reachable photometric precision for faint stars. This technique is designed to exploit the huge potential offered by the "super-stamps", but it is also perfectly suitable to analyze single, isolated stamps. The team releases the light curves for stars in the open clusters M35 and NGC2158 observed during Campaign 0, and M44 and M67 in Campaign 5. They also provide the high-angular-resolution input catalogs used in their works, the lists of the variable stars identified (only for M 44 and M67 clusters) and the Kepler/K2 stacked images for each cluster.