cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.13146614
title: R0169_20170505a_videos

description: Rat 0169, skilled reaching data collected in Leventhal laboratory by Alexandra Bova
DOI: 10.21227/gerh-vr88
title: COVID-19 Posteroanterior Chest X-Ray fused (CPCXR) dataset

description: The dataset is genrated by the fusion of three publicly available datasets: COVID-19 cxr image (https://github.com/ieee8023/covid-chestxray-dataset), Radiological Society of North America (RSNA) (https://www.kaggle.com/c/rsna-pneumonia-detection-challenge), and U.S. national library of medicine (USNLM) collected Montgomery country - NLM(MC) (https://lhncbc.nlm.nih.gov/publication/pub9931). These datasets were annotated by expert radiologists. The fused dataset consists of samples of diseases labeled as COVID-19, Tuberculosis, Other pneumonia (SARS, MERS, etc.), and Normal. The dataset can be utilized to train and evaulate deep learning and machine learning models as binary and multi-class classification problem.
DOI: 10.17632/sj8vtpvk5j.7
title: Data for: Antiulcerogenic effects of Celosia trigyna plant extracts on ethanol-induced gastric ulcer in adult Wistar rats

description: NMR data for isolated compounds.
DOI: 10.6084/m9.figshare.13148033
title: Kin recognition in Trogonophis

description: Tongue flick responses to scent of conspecifics<br>
DOI: 10.6084/m9.figshare.13148033.v1
title: Kin recognition in Trogonophis

description: Tongue flick responses to scent of conspecifics<br>
DOI: 10.6084/m9.figshare.13148021
title: Keras_object_detection_for_1k_data

description: Keras based object detection for 1k images from VTKEL dataset.
DOI: 10.21227/cff3-jc12
title: Model4.5

description: Mahalanobis distance on high dimensional features.
DOI: 10.21227/qr69-5e88
title: Ear-EEG Recording for Brain Computer Interface of Motor Task

description: Ear-EEG recording collects brain signals from electrodes placed in the ear canal. Compared with existing scalp-EEG, ear-EEG is more wearable and user-comfortable compared with existing scalp-EEG.In this dataset, we collected ear-EEG signals and the scalp-EEG signals when subjects were performing a left/right hand grasping motor task. We first validated the ear-EEG recordings by measuring the similarity of power ratio and channel correlation between ear-EEG and scalp-EEG signals. Then we applied EEG compact network (EEGNet) for classification of left/right-hand motor tasks using ear-EEG signals and scalp EEG signals separately. Our results showed motor task classification based on ear-EEG has a high potential for the practical BCI applications in motor task.
DOI: 10.26015/adwdocs-33
title: Die Bischöfe des Alten Reiches nach Erwin Gatz. Basisdaten und Normdaten
title: xml-Format, UTF 8
DOI: 10.26015/adwdocs-30
title: Die Bistümer des Alten Reiches nach Erwin Gatz. Basisdaten und Normdaten.
title: Tabellarische Übersicht (csv-Format, UTF 8)
DOI: 10.6084/m9.figshare.13140371.v1
title: Arctic COSMO-CLM Reanalysis all years

description: COSMO-CLM Russian Arctic climate dataset
DOI: 10.26015/adwdocs-34
title: Die Grenzen der Bistümer des Alten Reiches um 1500. Rekonstruktion der Germania Sacra anhand publizierter Karten und Quellenmaterialien
title: Geographische Daten (GIS-Format)
DOI: 10.5281/zenodo.3676385
title: Cinca River Field Survey: sediment sampling and tree measurement

description: A field survey was performed on 26-28 November 2018 by Melissa Latella, Matteo B. Bertagni, Paolo Vezza and Carlo Camporeale (Envirofluidgroup, Department of Environmental, Land and Infrastructure Engineering, Polytechnic of Turin, Italy). The survey was carried out over the riparian area of the Cinca River, in a river segment located between the towns of Ballobar and Zaidín (Spain). Sediment samples were collected through the Wolman Pebble Count method. Pictures of the samples constitute the input for the MATLAB-based image-processing tool BaseGrain. BaseGrain allows to extrapolate the intermediate diameter of a set of samples. The output diameters can be processed in order to obtain the grain size distribution, the d50 and d90, and the Manning coefficient. Also vegetation features were measured during the survey. Tree diameter and height were collected in order to regress allometric curves, whereas the number of trees in areas of known extension allows to determine the spatial tree density.
DOI: 10.5281/zenodo.3676384
title: Cinca River Field Survey: sediment sampling and tree measurement

description: A field survey was performed on 26-28 November 2018 by Melissa Latella, Matteo B. Bertagni, Paolo Vezza and Carlo Camporeale (Envirofluidgroup, Department of Environmental, Land and Infrastructure Engineering, Polytechnic of Turin, Italy). The survey was carried out over the riparian area of the Cinca River, in a river segment located between the towns of Ballobar and Zaidín (Spain). Sediment samples were collected through the Wolman Pebble Count method. Pictures of the samples constitute the input for the MATLAB-based image-processing tool BaseGrain. BaseGrain allows to extrapolate the intermediate diameter of a set of samples. The output diameters can be processed in order to obtain the grain size distribution, the d50 and d90, and the Manning coefficient. Also vegetation features were measured during the survey. Tree diameter and height were collected in order to regress allometric curves, whereas the number of trees in areas of known extension allows to determine the spatial tree density.
DOI: 10.21227/e1n2-jx32
title: Emotional Status Determination using Physiological Parameters Data Set

description: This dataset is created with the usage of Galvanic Skin Response Sensor and Electrocardiogram sensor of MySignals Healthcare Toolkit. MySignals toolkit consists of the Arduino Uno board and different sensor ports. The sensors were connected to the different ports of the hardware kit which was controlled by Arduino SDK.MySignals is a development platform for medical devices and e-Health applications. It is a multichannel physiological signal recorder which measures more than 15 different biometric parameters such as pulse, breath rate, oxygen in blood, electrocardiogram signals, blood pressure, muscle electromyography signals, glucose levels, galvanic skin response, lung capacity, snore waves, patient position, airflow and body scale parameters (weight, bone mass, body fat, muscle mass, body water, visceral fat, Basal Metabolic Rate and Body Mass Index).This novel dataset can be applied for training and evaluating deep learning, machine learning and big data analytic models to deal with binary and multi-class stress and emotion classification problem.
DOI: 10.21227/8xem-zg33
title: Emotional Status Determination using Physiological Parameters Data Set

description: This dataset is created with the usage of Galvanic Skin Response Sensor and Electrocardiogram sensor of MySignals Healthcare Toolkit. MySignals toolkit consists of the Arduino Uno board and different sensor ports. The sensors were connected to the different ports of the hardware kit which was controlled by Arduino SDK.MySignals is a development platform for medical devices and e-Health applications. It is a multichannel physiological signal recorder which measures more than 15 different biometric parameters such as pulse, breath rate, oxygen in blood, electrocardiogram signals, blood pressure, muscle electromyography signals, glucose levels, galvanic skin response, lung capacity, snore waves, patient position, airflow and body scale parameters (weight, bone mass, body fat, muscle mass, body water, visceral fat, Basal Metabolic Rate and Body Mass Index).This novel dataset can be applied for training and evaluating deep learning, machine learning and big data analytic models to deal with binary and multi-class stress and emotion classification problem.
DOI: 10.21227/z1xa-8r51
title: Emotional Status Determination using Physiological Parameters Data Set

description: This dataset is created with the usage of Galvanic Skin Response Sensor and Electrocardiogram sensor of MySignals Healthcare Toolkit. MySignals toolkit consists of the Arduino Uno board and different sensor ports. The sensors were connected to the different ports of the hardware kit which was controlled by Arduino SDK.MySignals is a development platform for medical devices and e-Health applications. It is a multichannel physiological signal recorder which measures more than 15 different biometric parameters such as pulse, breath rate, oxygen in blood, electrocardiogram signals, blood pressure, muscle electromyography signals, glucose levels, galvanic skin response, lung capacity, snore waves, patient position, airflow and body scale parameters (weight, bone mass, body fat, muscle mass, body water, visceral fat, Basal Metabolic Rate and Body Mass Index).This novel dataset can be applied for training and evaluating deep learning, machine learning and big data analytic models to deal with binary and multi-class stress and emotion classification problem.
DOI: 10.15129/a1856801-2146-40ee-a24c-9790ef2b65ae
title: Data for: "Electrochemilumescent Sensors: A Move in the Light Direction for New Drug Detection"

description: Poster presentation for RSC Twitter Poster Conference #RSCAnalytical #RSCPhys
DOI: 10.21227/xxx1-ft24
title: Emotional Status Determination using Physiological Parameters Data Set

description: This dataset is created with the usage of Galvanic Skin Response Sensor and Electrocardiogram sensor of MySignals Healthcare Toolkit. MySignals toolkit consists of the Arduino Uno board and different sensor ports. The sensors were connected to the different ports of the hardware kit which was controlled by Arduino SDK.MySignals is a development platform for medical devices and e-Health applications. It is a multichannel physiological signal recorder which measures more than 15 different biometric parameters such as pulse, breath rate, oxygen in blood, electrocardiogram signals, blood pressure, muscle electromyography signals, glucose levels, galvanic skin response, lung capacity, snore waves, patient position, airflow and body scale parameters (weight, bone mass, body fat, muscle mass, body water, visceral fat, Basal Metabolic Rate and Body Mass Index).This novel dataset can be applied for training and evaluating deep learning, machine learning and data analytics models to deal with binary and multi-class stress and emotion classification problem.
DOI: 10.5281/zenodo.4139236
title: A comparative study of the effect of Electroconvulsive therapy and Transcranial direct current stimulation in the treatment of persons suffering from treatment-resistant depression

description: This study sought to compare the effectiveness of electroconvulsive therapy and transcranial direct current stimulation in the treament of Treatment-resistant depression.
DOI: 10.5281/zenodo.4139235
title: A comparative study of the effect of Electroconvulsive therapy and Transcranial direct current stimulation in the treatment of persons suffering from treatment-resistant depression

description: This study sought to compare the effectiveness of electroconvulsive therapy and transcranial direct current stimulation in the treament of Treatment-resistant depression.
DOI: 10.21227/f9vc-k044
title: A solution based on two FNNs (version 2)

description: This solution bases on a feedforward neural network. The network for prediction of the usage has got five inputs: average temperature for the month (estimated from the data from last year), usage in last december, dwelling type, number of rooms, and the month. Each value is normalized to the range [-1, 1]. If the number of rooms or dwelling type is not available in the input data, this value is estimated by a second feedforward neural network. It's very simmilar to previous solunion, the only difference is the preparation of the training data.
DOI: 10.21227/f26c-zq46
title: SEM of fission bubbles with submicropores

description: See our next articles.
DOI: 10.21227/cebp-0w65
title: SEM of fission bubbles with submicropores

description: See our next articles.
DOI: 10.6084/m9.figshare.13146614.v1
title: R0169_20170505a_videos

description: Rat 0169, skilled reaching data collected in Leventhal laboratory by Alexandra Bova
DOI: 10.6084/m9.figshare.13146617.v1
title: R0312_20191119a_videos

description: Rat 0312, skilled reaching data collected in Leventhal laboratory by Alexandra Bova
DOI: 10.6084/m9.figshare.12494609
title: Data for stream wise velocity in Y shaped confluence

description: open channel hydraulics
DOI: 10.6084/m9.figshare.12494609.v2
title: Data for stream wise velocity in Y shaped confluence

description: open channel hydraulics
DOI: 10.6084/m9.figshare.12494609.v1
title: Data for stream wise velocity in Y shaped confluence

description: Open-channel confluence is an important phenomenon in rivers, and the confluence of the vegetation within it has a significant impact on its hydrodynamics and the transport of pollutants in it. This study experimentally investigated the effects of submerged vegetation on the flow structure (in terms of flow velocity, secondary currents, and turbulent kinetic energy) and the mixing of contaminants in a Y-shaped confluence channel. The results showed that the velocity profile could be divided into three layers vertically and characterized as S-shaped within the vegetated system, where this was different from the J-shaped profile in the non-vegetated 35 system. The presence of vegetation thus reduced the scale of secondary currents, which hindered the mixing of contaminants and stratified the distribution of pollutants. The different discharge modes and locations of the contaminants led to different paths of transport in the vegetated confluence channel, and it became easier for the discharge in the inner bank of the tributaries to diffuse and mix. Finally, the turbulent kinetic energy within the vegetated system was higher than that in the non-vegetated system, and peaked at the top of the canopy. The interaction between flow and vegetation increased the intensity of turbulence.
DOI: 10.6084/m9.figshare.12515189
title: Genome-wide association study and pathway analysis identify NTRK2 as a novel candidate gene for litter size in sheep

description: 50k SNP data for 91 Iranian Baluchi ewes. Plink tfam and tped files.
DOI: 10.6084/m9.figshare.13148075
title: support file.zip

description: The data in the file correspond to different figures in the paper, and the data corresponding to each figure is stored in a separate folder for easy viewing.
DOI: 10.6084/m9.figshare.13148075.v1
title: support file.zip

description: The data in the file correspond to different figures in the paper, and the data corresponding to each figure is stored in a separate folder for easy viewing.
DOI: 10.21227/4754-3a76
title: A solution based on two FNNs 2

description: This solution bases on a feedforward neural network. The network for prediction of the usage has got five inputs: average temperature for the month (estimated from the data from last year), usage in last december, dwelling type, number of rooms, and the month. Each value is normalized to the range [-1, 1]. If the number of rooms or dwelling type is not available in the input data, this value is estimated by a second feedforward neural network. It's very simmilar to previous solunion, the only difference is the preparation of the training data.
DOI: 10.25345/c5qn3q
title: MassIVE MSV000086374 - Extensive and accurate benchmarking of DIA acquisition methods and softwares using a complex proteomic standard
title: In order to compare workflows for acquisition and treatment of proteomic data analyzed in Data Independent Acquisition (DIA) mode, a proteomic standard has been generated by spike-in the 48 human proteins of UPS1 (Sigma) in a whole cell extract of E.coli at 8 different concentrations ranging from 0.1 to 50 fmol of UPS1/ug of E.coli. Each sample has been trypsin-digested analyzed in triplicate on an Orbitrap Fusion instrument (Thermo) operating in DIA mode with four different sizes of precursor windows (narrow, wide, variable or overlapped). These 4 x 24 raw files have then been analyzed with 6 different DIA softwares (Spectronaut, Scaffold-DIA, Skyline, DIA-Umpire, OpenSwath and DIA-NN) with the use or not of a fractionated E.coli library. Here we deposit the 96 Thermo raw files of the analysis, the outputs of the softwares (5 with the use of a peptide library and 4 with a search against Human+E.coli fasta files) for the 4 acquisition modes and the peptide library (.blib file) generated by the DDA analysis of 48 fractions of E.coli whole cell extract + 200fmol/ug of UPS1 proteins.
DOI: 10.5281/zenodo.4139353
title: Dataset for the manuscript of the "Experimental investigation into simultaneous adsorption of water vapor and methane onto shales"

description: Dataset for the manuscript of the "Experimental investigation into simultaneous adsorption of water vapor and methane onto shales"<br>
DOI: 10.5281/zenodo.4139352
title: Dataset for the manuscript of the "Experimental investigation into simultaneous adsorption of water vapor and methane onto shales"

description: Dataset for the manuscript of the "Experimental investigation into simultaneous adsorption of water vapor and methane onto shales"<br>
DOI: 10.21227/kmcp-hs79
title: Filopodial rheology modeling using synthetic elastomers. Case of the form made from the monomer (CH2=C(CH3)2) via cationic addition polymerization

description: See our next articles.
DOI: 10.21227/h0hd-xw24
title: Filopodial rheology modeling using synthetic elastomers. Case of the form made from the monomer (CH2=C(CH3)2) via cationic addition polymerization

description: See our next articles.
DOI: 10.15129/78e8712e-fa1e-40fc-9727-2d105ae719e3
title: Data for: "Electrochemical Monitoring of Alcohol in Sweat"

description: All electrochemical data including cyclic voltammograms and differential pulse voltammograms pertaining to the publication "Electrochemical Monitoring of Alcohol in Sweat" including supplementary material Initial data embargo applied until 01/11/2022
DOI: 10.17632/9brc7fkddx.1
title: Data for: Input-based assessment on integrated pest management for transplanted rice (Oryza sativa) in India

description: Details of data
DOI: 10.25934/00005772.0
title: Available IPD datapackage for study 'A Randomized, Double-blind, Parallel Group Study of Safety and the Effect on Clinical Outcome of Tocilizumab Subcutaneous (sc) Versus Placebo sc in Combination With Traditional Disease Modifying Anti-rheumatic Drugs (DMARDs) in Patients With Moderate to Severe Active Rheumatoid Arthritis'

description: Vivli is an independent, non-profit organization that has developed a global data-sharing and analytics platform to serve all elements of the international research community. Our mission is to promote, coordinate, and facilitate scientific sharing and reuse of clinical research data through the creation and implementation of a sustainable global data-sharing enterprise. The Vivli platform includes an independent data repository, in-depth search engine and a cloud-based, secure analytics platform.
DOI: 10.5281/zenodo.4139537
title: Supplemental material for "The influence of temperature on the seasonality of historical plague outbreaks"

description: This repository provides the code and raw data for the project.
DOI: 10.5281/zenodo.4139455
title: dictionaria/wersing: Wersing dictionary

description: Schapper, Antoinette. 2020. Wersing dictionary. Dictionaria 11. 1-1430 (Available online at https://dictionaria.clld.org/contributions/wersing)
DOI: 10.5281/zenodo.4139528
title: Pigments and environmental properties dataset of the austral spring/summer of 2015/2016

description: Pigments and environmental properties dataset of the austral spring/summer of 2015/2016 along the Northern Antarctic Peninsula, performed during three (November, January and February) oceanographic cruises conducted on board the<em> RV Almirante Maximiano</em> of the Brazilian Navy.
DOI: 10.5281/zenodo.4139527
title: Pigments and environmental properties dataset of the austral spring/summer of 2015/2016

description: Pigments and environmental properties dataset of the austral spring/summer of 2015/2016 along the Northern Antarctic Peninsula, performed during three (November, January and February) oceanographic cruises conducted on board the<em> RV Almirante Maximiano</em> of the Brazilian Navy.
DOI: 10.5281/zenodo.4139511
title: Suppelementary Table S1. List of heat-affected proteins in buds, open flowers, wilted flowers, and donor leaves of common buckwheat accessions 'Panda' and PA15. Comparison of protein abundance between heat-treated plants and those growing in optimal conditions.

description: Suppelementary Table S1. List of heat-affected proteins in buds, open flowers, wilted flowers, and donor leaves of common buckwheat accessions ‘Panda’ and PA15. Comparison of protein abundance between heat-treated plants and those growing in optimal conditions.
DOI: 10.5281/zenodo.4139510
title: Suppelementary Table S1. List of heat-affected proteins in buds, open flowers, wilted flowers, and donor leaves of common buckwheat accessions 'Panda' and PA15. Comparison of protein abundance between heat-treated plants and those growing in optimal conditions.

description: Suppelementary Table S1. List of heat-affected proteins in buds, open flowers, wilted flowers, and donor leaves of common buckwheat accessions ‘Panda’ and PA15. Comparison of protein abundance between heat-treated plants and those growing in optimal conditions.
DOI: 10.6084/m9.figshare.13140371.v2
title: Arctic COSMO-CLM Reanalysis 2004

description: COSMO-CLM Russian Arctic climate dataset
DOI: 10.6084/m9.figshare.13148069.v1
title: Arctic COSMO-CLM Reanalysis 2005

description: COSMO-CLM Russian Arctic climate dataset
DOI: 10.6084/m9.figshare.13147928.v1
title: China-LCFMCD-CCI (China-Land Cover Fraction): China's land cover faction during 2001-2015 based on data fusion between MCD12 and CCI-LC

description: This dataset provides 1km resolution land cover fraction for eight land cover types (i.e., forest, grassland and shrub, cropland, wetland, water, construction, bare land, permanent snow and ice) of China from 2000 to 2015. MCD12 and CCI-LC were fused by weighted consistency analysis and produced the China-LCF<sub>MCD-CCI</sub>.<br> *** The format of provided data is GeoTIFF. Each file was projected to the Albers projection and Geographic coordinate system is D_WGS_1984, with a spatial resolution of 1km. *** The pixel value is the land cover fraction. *** Filename convention: Land cover types_Year.tif *** Land Cover Types: Forest, Grassland and Shrub (GS), Cropland, Wetland, Water, Construction, Bare land, Permanent Snow and Ice (PSI).
DOI: 10.6084/m9.figshare.13084621
title: Data S4 from Krüppel-like factor/specificity protein evolution in the Spiralia and the implications for cephalopod visual system novelties

description: Alignment file for RAxML and MrBayes tree of SP6-9 full length sequences across Spiralia
DOI: 10.6084/m9.figshare.13084624
title: Table S4 from Krüppel-like factor/specificity protein evolution in the Spiralia and the implications for cephalopod visual system novelties

description: Spiralian transcriptomes used with no <i>SP6-9</i> transcript identified
DOI: 10.6084/m9.figshare.13084633
title: Data S7 from Krüppel-like factor/specificity protein evolution in the Spiralia and the implications for cephalopod visual system novelties

description: Alignment file for MrBayes tree of SP6-9 full length sequences across Cephalopoda
DOI: 10.6084/m9.figshare.13084639
title: Data S11 from Krüppel-like factor/specificity protein transcription factor evolution in the spiralia and the implications for cephalopod visual system novelties

description: Alignment file for MrBayes tree of SP6-9 full length sequences across Mollusca
DOI: 10.6084/m9.figshare.13084636
title: Data S2 from Krüppel-like factor/specificity protein evolution in the Spiralia and the implications for cephalopod visual system novelties

description: Nexus tree file for RAxML tree of KLF/SP conserved domains across Metazoa