cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/3bsfy669xt.3
title: Employees’ personal relative deprivation negatively associated with job satisfaction and affective commitment: The mediating role of work-related basic need satisfaction

description: The current study aims to investigate the relationships between personal relative deprivation and employees’ attitudes towards job and organization and the underlying psychological mechanisms of the associations. Drawing on the self-determination theory, we propose the personal relative deprivation leads to the three work-related basic needs unsatisfied, which in turn lower the job satisfaction and affective commitment. We collected data from 390 participants recruited from a professional research participation system. The results indicated that higher level of personal relative deprivation significantly reduce individual’s job satisfaction and affective commitment. The indirect effects of personal relative deprivation on the job satisfaction or affective commitment through the satisfaction of the autonomy needs or the satisfaction of the relatedness needs are significant, while the mediating effects of the satisfaction of competence needs are nonsignificant.
DOI: 10.17632/7xvshh2s59.2
title: Data for Post-training corticosterone treatment differentially modulates recent and remote contextual fear specificity
DOI: 10.17632/bzxk2n78s9.4
title: GGG-BenchmarkSfM: Dataset for Benchmarking Close-range SfM Software Performance under Varying Capturing Conditions

description: The proposed dataset aims to benchmark the performance of SfM software under varying conditions - different environments, different lighting, image positions, camera setups, etc. Images of six objects are provided with varying shapes, sizes, surface textures and materials. The dataset is divided in two main parts, together with ReadMe files: - Objects and environments data - images from each of the objects both from indoor and outdoor environments are provided. - Capturing setups data - images from one of the objects are provided captured with different setups. Both with and without using a turntable, using one and multiple light sources and different amount of images All images are captured using Canon 6D DSLR camera. All images contain EXIF data with used camera parameters. A ground truth high resolution scanned of each of the objects is provided for verifying the accuracy of the SfM reconstructions.
DOI: 10.17632/fzcmhhjs76.1
title: Stimulation Artifact Source Separation

description: Transcranial alternating current stimulation (tACS) can affect perception, learning and cognition, but the underlying mechanisms are not well understood. A promising strategy to elucidate these mechanisms aims at applying tACS while electric or magnetic brain oscillations targeted by stimulation are recorded. However, reconstructing brain oscillations targeted by tACS remains a challenging problem due to stimulation artifacts. Besides lack of an established strategy to effectively supress such stimulation artifacts, there are also no resources available that allow for the development and testing of new and effective tACS artefact suppression algorithms, such as adaptive spatial filtering using beamforming or signal-space projection. Here, we provide a full dataset comprising encephalographic (EEG) recordings across six healthy human volunteers who underwent 10-Hz amplitude-modulated tACS (AM-tACS) during a 10-Hz steady-state visually evoked potential (SSVEP) paradigm. Moreover, data and scripts are provided related to the validation of a novel stimulation artefact suppression strategy, Stimulation Artifact Source Separation (SASS), removing EEG signal components that are maximally different in the presence versus absence of stimulation. Besides including EEG single-trial data and comparisons of 10-Hz brain oscillatory phase and amplitude recorded across three conditions (condition 1: no stimulation, condition 2: stimulation with SASS, condition 3: stimulation without SASS), also power spectra and topographies of SSVEP amplitudes across all three conditions are presented. Moreover, data is provided for assessing nonlinear modulations of the stimulation artifact in both time and frequency domains due to heartbeats. Finally, the dataset includes eigenvalue spectra and spatial patterns of signal components that were identified and removed by SASS for stimulation artefact suppression at the target frequency. Besides providing an valuable resource to assess properties of AM-tACS artifacts in the EEG, this dataset allows for testing different artifact rejection methods and offers in-depth insights into the workings of SASS.
DOI: 10.17632/fzcmhhjs76.2
title: Stimulation Artifact Source Separation

description: Transcranial alternating current stimulation (tACS) can affect perception, learning and cognition, but the underlying mechanisms are not well understood. A promising strategy to elucidate these mechanisms aims at applying tACS while electric or magnetic brain oscillations targeted by stimulation are recorded. However, reconstructing brain oscillations targeted by tACS remains a challenging problem due to stimulation artifacts. Besides lack of an established strategy to effectively supress such stimulation artifacts, there are also no resources available that allow for the development and testing of new and effective tACS artefact suppression algorithms, such as adaptive spatial filtering using beamforming or signal-space projection. Here, we provide a full dataset comprising encephalographic (EEG) recordings across six healthy human volunteers who underwent 10-Hz amplitude-modulated tACS (AM-tACS) during a 10-Hz steady-state visually evoked potential (SSVEP) paradigm. Moreover, data and scripts are provided related to the validation of a novel stimulation artefact suppression strategy, Stimulation Artifact Source Separation (SASS), removing EEG signal components that are maximally different in the presence versus absence of stimulation. Besides including EEG single-trial data and comparisons of 10-Hz brain oscillatory phase and amplitude recorded across three conditions (condition 1: no stimulation, condition 2: stimulation with SASS, condition 3: stimulation without SASS), also power spectra and topographies of SSVEP amplitudes across all three conditions are presented. Moreover, data is provided for assessing nonlinear modulations of the stimulation artifact in both time and frequency domains due to heartbeats. Finally, the dataset includes eigenvalue spectra and spatial patterns of signal components that were identified and removed by SASS for stimulation artefact suppression at the target frequency. Besides providing an valuable resource to assess properties of AM-tACS artifacts in the EEG, this dataset allows for testing different artifact rejection methods and offers in-depth insights into the workings of SASS.
DOI: 10.17632/ycnx37zj4b.1
title: Hidden long-distance movements by a migratory bird
DOI: 10.5281/zenodo.3981399
title: Data set of labeled scenes in a barn in front of automatic milking system

description: This data set includes supplementary files to our article \emph{"Deep learning image recognition of cow behavior near an automatic milking robot with an open data set"} (Leonardo Santiago Benitez Pereira, Olli Koskela, Ilpo Pölönen, Ilmo Aronen and Iivari Kunttu, in review, 2020). We acquired continuous video data over two-month period of cows in front of Automatic Milking Station (AMS). Each frame of the video is labeled as a single image belonging to one of classes described below. This data set includes 253 files of video data having in total \num{1526473} labeled frames. The data set used in the article consisted of 280 videos, but for privacy reasons, 27 video files including persons were removed from this data set, but their Java Script Object Notation (JSON) label files are left for, e.g., temporal analyses.
DOI: 10.15468/bz744e
title: Ascomycetes from the Qilian Mountains, China - Hypocreales

description: This dataset contains the digitized treatments in Plazi based on the original journal article Zeng, Zhao-Qing, Zheng, Huan-Di, Wang, Xin-Cun, Wei, Sheng-Long, Zhuang, Wen-Ying (2020): Ascomycetes from the Qilian Mountains, China - Hypocreales. MycoKeys 71: 119-137, DOI: http://dx.doi.org/10.3897/mycokeys.71.55009, URL: http://dx.doi.org/10.3897/mycokeys.71.55009
DOI: 10.17632/f67j6jh84h.1
title: Collaborative Reflection

description: This study investigated collaborative reflection within practical settings on a university-based coach education program. Data were collected through focus group interviews with undergraduate sports coaching students and individual interviews with module instructors. The sample consisted of 17 sports coaching students (14 males, 3 females, mean age=24.24, SD=3.01) enrolled on the first year of a sport and exercise undergraduate degree at a UK university. The university instructors were three males (mean age=38, SD=11) with an average of 8.33 (SD=4.73) years of experience teaching in higher education. Focus group and individual interviews were conducted using a semi-structured design which provided a general framework of questions whilst enabling the flexibility to probe into responses and gain detailed descriptions of thoughts and experiences (Hall & Getchell, 2014). The focus group interview guide was devised by drawing on relevant literature with open-ended questions that address the research topic in terms of experience, behaviour, and context (Smith & Sparkes, 2016). The individual interviews were based on analyses of focus group data in addition to key concepts arising from relevant literature. Interview data were transcribed and analysed thematically using Braun and Clark’s (2006) six-step process: (1) familiarisation with the data; (2) Generation of initial codes; (3) Searching for themes; (4) Reviewing themes; (5) Defining and naming themes; (6) Producing the report. By adopting a reflexive process of moving forwards and backwards through the data, the analysis was produced through the intersection of theoretical assumptions, disciplinary knowledge, research skills and experience, and the content of the data themselves (Braun & Clarke, 2016). Adopting an abductive approach to data analysis, we considered both the impact of data on theory, and also the impact of theory on data (Partington et al., 2015), as the thematic analysis enabled the flexibility to explore transcripts for surprising data, whilst the generation of themes was informed by extant research. Data analysis revealed three main themes and six sub-themes as follows: reflective processes (evaluating peers’ experiences, collaboration through shared knowledge); social support (effort and advice, emotional support); and engagement (task engagement, pressure of assessment).
DOI: 10.5281/zenodo.3928562
title: PULSE dataset

description: <strong><em>This Zenodo page is not currently hosting any data. The full PULSE dataset is expected to be online within the next month.</em></strong> <strong>Motivation</strong> The data in this dataset is derived and cleaned from the full PULSE project dataset to gives others data about the users during the project. <strong>Disclaimer</strong> Any third party need to respect ethics rules and GDPR and must mention “PULSE DATA H2020 - 727816” in any dissemination activities related to data being exploited. Also, you should provide a link to the project associated website: http://www.project-pulse.eu/ The data provided in the files is provided as is. Despite our best efforts at filtering out potential issues, some information could be erroneous. <strong>Description of the dataset</strong> The only difference with the original dataset comes from anonymised user information. The dataset content is described in a dedicated JSON file: <em>PULSE_shared_data_definition.json</em>
DOI: 10.17632/x64srrc39p.3
title: Dataset on cadaveric human abdominal aorta aneurysm biomechanics (uniaxial) and histology

description: The present dataset is a collection of information about the biomechanical behavior and histological characterization of abdominal aortic aneurysms (AAA) harvested during the autopsy procedure. The primary hypothesis of the present research is: Do cadaveric AAA walls, when previously stressed by inflation, conserve significant resistance against tearing comparable to no previously stressed aortas described in the literature? Eight AAAs (6 fusiform and two saccular) were carefully dissected and had their branches ligated with cotton or prolene sutures. Each specimen was submitted to intraluminal pressurization, up to the rupture of their wall. This pressurization was made through the inflation of an air balloon inside the specimens up to their rupture. From the border of the rupture sites, and from the proximal (control sample 1) and distal (control sample 2) no dilated portions of each vessel, samples were harvested for uniaxial tensile tests, and histological analysis. The uniaxial tensile test utilized the INSTRON SPEC 2200 device and was coordinated by INSPEC software and SERIES IX software. The essential variables collected through this test are failure stress, failure tension, and failure strain. Each sample test generated a chart representing the relationship between stress and strain. The histological analysis included hematoxylin-eosin, Picrocirius, and Voerhoeff stains. Unfortunately, some samples were lost, especially during histological processing. A quantitative analysis (collagen and elastic fibers) was made using the software Pannoramic Viewer and Case Viewer.1 Notable findings: Even after being stretched/stressed up to their rupture, the specimens conserved uniaxial biomechanical properties comparable to AAA and normal aorta samples previously described in the literature by Monteiro e Nynomiya respectively.2,3 DATA DESCRIPTION: a) Biomechanical Data: As explained above, four samples were collected for each specimen, two from each side of the rupture border and two control samples, one from a proximal and a second from a distal region of the vessel. It is important to highlight here that some samples did not produce valid biomechanical tests, so they do not have their results included here. For each valid sample test, three documents are generated: 1. Stress X strain chart 2. Table (excel file containing all the values related to the stress X strain chart 3. A report from the Biomechanical test software containing details of the test All charts contain a notification in their left upper corner about the failure stress, strain and tension of each sample. b) Histological Data: The percentage of coverage of collagen fibers and elastin fibers is expressed in table I in decimal numbers (for example, 0.36 = 36%). Similarly to the sampling for biomechanical tests, four samples were harvested from each aorta, when it was feasible. Ps.: All Case C samples were lost during processing
DOI: 10.17632/85d73fv3y2.1
title: Data for Fully 3D Modeling of Single-Phase Fluid Flow

description: Data for a Fully 3D Modeling of Single-Phase Fluid Flow in Fractured-Vuggy Carbonate Formations Using the Transient Brinkman Equation Coupled with the Second-order Gradient Rock Mechanics Equation Including Porosity Evolution study
DOI: 10.17632/mc49zmg7n7.2
title: Time series from PBO and UNR used in Bartlow (2019)

description: MATLAB .mat files containing input data (processed daily position time series from PBO and UNR) for Bartlow (2019), along with the inversion results from that study (shown in Figure 3A). Codes used to produce the results can be found at https://github.com/noelbartlow/Long-Term-Cascadia-ETS-velocities. results_for_paper.mat includes the long-term ETS slip rate (variable slip_rate) on a mesh with nodes given by variables nd (local coordinates) or nd_ll (lat/long coordinates) and elements in variable el. To plot the results use &gt;&gt; figure; trisurf(el, nd_ll(:, 1), nd_ll(:, 2), nd_ll(:, 3), slip_rate). Also included in this file are the long-term ETS velocities are each station (Nv_SSE, Ev_SSE, Uv_SSE) and their uncertainties (variables beginning with sig). Strike and rake refer to each subfault; slip directions were fixed in the inversion. Pole gives the Euler pole used to define slip directions.
DOI: 10.17632/yfj4wfszbw.2
title: Dataset on human NORMAL DIAMETER abdominal aorta biomechanics (uniaxial) and histology (specimens harvested during autopsy)

description: The present dataset is a collection of information about the biomechanical behavior and histological characterization of normal diameter abdominal aortas harvested during the autopsy procedure. The primary hypothesis of the present research is: Do cadaveric abdominal aortic walls, when previously stressed by inflation, conserve significant resistance against tearing comparable to no previously stressed aortas described in the literature? Thirty normal diameter abdominal aortas were carefully dissected and had their branches ligated with cotton or prolene sutures. Each specimen was submitted to intraluminal pressurization, up to the rupture of their wall. This pressurization was made through the inflation of an air balloon inside the specimens up to their rupture. From the border of the rupture sites, and from the proximal (control sample 1) and distal (control sample 2) portions of each vessel, samples were harvested for uniaxial tensile tests, and histological analysis. The uniaxial tensile test utilized the INSTRON SPEC 2200 device and was coordinated by INSPEC software and SERIES IX software. The essential variables collected through this test are failure stress, failure tension, and failure strain. Each sample test generated a graph representing the relationship between stress and strain. The histological analysis included hematoxylin-eosin, Picrosirius, and Voerhoeff stains1. Unfortunately, some samples were lost, especially during histological processing. A quantitative analysis (collagen fibers and elastic fibers percentage of coverage) was made using the software Pannoramic Viewer and Case Viewer. Notable findings: Even after being stretched/stressed up to their rupture, the specimens conserved some uniaxial biomechanical properties comparable to normal diameter aorta samples previously described in the literature by Monteiro e Nynomiya respectively.2,3 DATA DESCRIPTION: a) Biomechanical Data: As explained above, whenever possible, four samples were collected from each specimen destinated to the biomechanical test. It is important to highlight that some samples did not produce valid biomechanical tests, so they do not have their results included here. For each valid sample test, three documents were generated: 1. Stress X strain graph (all graphs contain a notification in their left upper corner about the failure stress, strain and tension of each sample). 2. Table (excel file containing all the values related to the stress X strain graph 3. A report from the Biomechanical test software containing details of the test All available files related to the biomechanical tests of these 30 normal aortas were included in the present dataset. b) Histological Data: The percentage of coverage of collagen fibers and elastin fibers is expressed in the table "HISTOLOGY - NORMAL AORTAS.xls in decimal numbers (for example, 0.36 = 36%). Four samples were harvested from each aorta, when it was feasible.
DOI: 10.17632/d89gphmnsk.1
title: IR-QUMA

description: IR-QUMA The IR-QUMA study (Iranian Survey on Quality in Messenger Apps) is defined to evaluate the quality of some messenger apps. A questionnaire was designed to evaluate some quality-related measures, metrics and features from users’ experience point of view. The questionnaire was published in popular channels of Iranian mobile social networks, in 10 different messengers (including Telegram, Whatsapp, Instagram, Eita, Soroush, Bale, Gap, IGap, Shaad and Rubika). More than 40 communities of users in these 10 messengers have contributed to this research questionnaire. Total of data is exceeds the level of 7k filled online forms. We hash the name of these messengers randomly by assigning ID-codes from M1 to M10.
DOI: 10.17632/d89gphmnsk.2
title: IR-QUMA

description: IR-QUMA The IR-QUMA study (Iranian Survey on Quality in Messenger Apps) is defined to evaluate the quality of some messenger apps. A questionnaire was designed to evaluate some quality-related measures, metrics and features from users’ experience point of view. The questionnaire was published in popular channels of Iranian mobile social networks, in 10 different messengers (including Telegram, Whatsapp, Instagram, Eita, Soroush, Bale, Gap, IGap, Shaad and Rubika). More than 40 communities of users in these 10 messengers have contributed to this research questionnaire. Total of data is exceeds the level of 7k filled online forms. We hash the name of these messengers randomly by assigning ID-codes from M1 to M10.
DOI: 10.17632/694773zt2m.1
title: Bowshock-ANN_Test-Set
DOI: 10.17632/64r4jr8c88.2
title: Binary-Classification Performance Metric-Spaces Data

description: Metric-Space is a proposed concept by Gürol Canbek et al (2019). A metric-space indicates all possible permutations of contingency table (or confusion matrix) elements yielding the same sample size (Sn). It holds all possible results of a hypothetical classification conducted in a dataset with a given sample size in terms of one or more performance metrics (e.g. Accuracy, F1, or TPR). Metric-space provides a pseudo-universal space to analyze and compare metrics in complete coverage. The formal definition and the details are given in the article. Each data file has the following performance 13 measures and 13 metrics: * True Positive (TP), False Positive (FP), False Negative (FN), True Negative (TN), Positive (P), Negative (N), Outcome Positive (OP), Outcome Negative (ON), True Classification (TC), False Classification (FC), Sample Size (Sn), Prevalence (PREV), Bias (BIAS) * True Positive Rate (TPR), True Negative Rate (TNR), Positive Predictive Value (PPV), Negative Predictive Value (NPV), Accuracy (ACC), Informedness (INFORM), Markedness (MARK), Balanced Accuracy (BACC), G, Normalized Mutual Information (nMI), F1, Cohen’s Kappa (CK), and Mathews Correlation Coefficient (MCC) Each data file belongs to metric-spaces for different Sn values (10, 25, 50, 75, 100, 125, 150, 175, 200, 225). The file format is RData (compatible with The R Project for Statistical Computing) instead of CSV (comma separated values) because of large CSV file sizes. Therefore, MATLAB users should convert the files into CSV and save them in R: &gt; load('MetricSpaces_Sn_10.RData') &gt; metric_spaces_Sn_10 write.csv(metric_spaces_Sn_10, file='MetricSpaces_Sn_10.csv') Note that metric-space sizes (permutations) increase exponentially: Sn=25 (3,276); Sn=50 (23,426); Sn=75 (76,076); Sn=100 (176,851); Sn=125 (341,376); Sn=150 (585,276); Sn=175 (924,176); Sn=200 (1,373,701); Sn=250 (2,667,126).
DOI: 10.17632/2g36672s5f.3
title: Binary-Classification Performance-Metrics Benchmarking Data

description: This data provides the detailed test results of the benchmarking for the binary-classification performance metrics. The benchmark comprising three stages was applied on 13 metrics namely True Positive Rate, True Negative Rate, Positive Predictive Value, Negative Predictive Value, Accuracy, Informedness, Markedness, Balanced Accuracy, G, Normalized Mutual Information, F1, Cohen’s Kappa, and Mathew’s Correlation Coefficient (MCC). The new benchmarking method is described in Gürol Canbek, Tugba Taskaya Temizel, and Seref Sagiroglu, "BenchMetrics: A Systematic Benchmarking Method for Binary-Classification Performance Metrics", Information Processing & Management, 2020 (Submitted).
DOI: 10.5517/ccdc.csd.cc1nv48x
title: CCDC 1544459: Experimental Crystal Structure Determination

description: Related Article: Ikram Dhouib, Ali Ouasri, Zakaria Elaoud|2020|J.Saudi Chem.Soc.|24|567|doi:10.1016/j.jscs.2020.06.001