cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.4704890
title: Results and further resources concerning our study concerning revealing biases in news articles

description: Media bias and its extreme form, fake news, can decisively affect public opinion. Especially when reporting on policy issues, slanted news coverage may strongly influence societal decisions, e.g., in democratic elections. Our paper makes three contributions to address this issue. First, we present a system for bias identification, which combines state-of-the-art methods from natural language understanding. Second, we devise bias-sensitive visualizations to communicate bias in news articles to non-expert news consumers. Third, our main contribution is a large-scale user study that measures bias-awareness in a setting that approximates daily news consumption, e.g., we present respondents with a news overview and individual articles. We not only measure the visualizations' effect on respondents' bias-awareness, but we can also pinpoint the effects to individual components of the visualizations by employing a conjoint design. Our bias-sensitive overviews strongly and significantly increase bias-awareness in respondents. Our study further suggests that our content-driven identification method detects groups of similarly slanted news articles due to substantial biases present in individual news articles. In contrast, the reviewed prior work rather only facilitates the visibility of biases, e.g., by distinguishing left- and right-wing outlets.
DOI: 10.5281/zenodo.4704164
title: Data related to the article "Evaluation of Oxford Nanopore MinION RNA-seq performance for human primary cells"

description: This record contains raw data related to the article “Evaluation of Oxford Nanopore MinION RNA-seq performance for human primary cells". <strong>Abstract: </strong>Transcript sequencing is a crucial tool for gaining a deep understanding of biological processes in diagnostic and clinical medicine. Given their potential to study novel complex eukaryotic transcriptomes, long-read sequencing technologies are able to overcome some limitations of short-read RNA-seq approaches. Oxford Nanopore Technologies (ONT) offers the ability to generate long-read sequencing data in real-time via portable protein nanopore USB devices at a reasonable cost. This work aimed to provide the user with the number of reads that should be sequenced, through ONT MinION platform, to reach the desired accuracy level for a human cell RNA study. We sequenced three cDNA libraries prepared from poly-adenosine RNA of human primary fibroblasts. Since the runs were comparable, they were combined in a total dataset of 48 million reads. Synthetic datasets with different sizes were generated starting from the total and analyzed in terms of the number of identified genes and their expression levels. As expected, an improved sensitivity was obtained increasing the sequencing depth, in particular for the non-coding genes. The reliability of expression levels was assayed by i) comparison with PCR quantifications of selected genes and ii) by the implementation of a user-friendly multiplexing method in a single run.
description: This work was supported by the Italian Ministry of Health funds (Ricerca Finalizzata: GR-2018-12366423; ERA-CVD: PICASSO-JTC-2018-042) and by Fondazione Gigi e Pupa Ferrari ONLUS (FPF-14).
DOI: 10.6084/m9.figshare.14176652
title: MEG_BIDS

description: The original MEG dataset was acquired from all 306 sensors (204 gradiometers and 102 magnetometers) during two different sessions for each participant and recorded as .fif files. As each session consists of two data files due to the session break, for better handling of the data, we have merged these files to create one single '.fif' file for each session. Thus, there are two raw '.fif' data files for each participant (i.e. one for each session). It is worth to be noted the data is available in two data formats i.e. MEG-BIDS format '.fif' and MATLAB compatible '.mat' file at the repository. The data directory for MEG-BIDS is defined, where only one subject data structure is illustrated to avoid repetition. The folder named 'MEG_BIDS' contains two files named 'dataset_description.json' and `participant.tsv'. Further, there are 17 sub-folders (one for each participant data), each having scan file `_scan.tsv' and a sub-folder named `meg'. Each `meg' folder contains five files i.e. `_coordsystem.json', `_channels.tsv',`_events.tsv',`_meg.fif', and `_meg.json'.
DOI: 10.6084/m9.figshare.14176673
title: MEG_mat

description: The original MEG dataset was acquired from all 306 sensors (204 gradiometers and 102 magnetometers) during two different sessions for each participant and recorded as .fif files. As each session consists of two data files due to the session break, for better handling of the data, we have merged these files to create one single '.fif' file for each session. Thus, there are two raw '.fif' data files for each participant (i.e. one for each session). It is worth to be noted the data is available in two data formats i.e. MEG-BIDS format '.fif' and MATLAB compatible '.mat' file at the repository. In .mat format, each participant data is stored in two folders (i.e. session 1 and session 2) under the root directory of 'MEG_mat'.
DOI: 10.6084/m9.figshare.14176652.v1
title: MEG_BIDS

description: The original MEG dataset was acquired from all 306 sensors (204 gradiometers and 102 magnetometers) during two different sessions for each participant and recorded as .fif files. As each session consists of two data files due to the session break, for better handling of the data, we have merged these files to create one single '.fif' file for each session. Thus, there are two raw '.fif' data files for each participant (i.e. one for each session). It is worth to be noted the data is available in two data formats i.e. MEG-BIDS format '.fif' and MATLAB compatible '.mat' file at the repository. The data directory for MEG-BIDS is defined, where only one subject data structure is illustrated to avoid repetition. The folder named 'MEG_BIDS' contains two files named 'dataset_description.json' and `participant.tsv'. Further, there are 17 sub-folders (one for each participant data), each having scan file `_scan.tsv' and a sub-folder named `meg'. Each `meg' folder contains five files i.e. `_coordsystem.json', `_channels.tsv',`_events.tsv',`_meg.fif', and `_meg.json'.
DOI: 10.6084/m9.figshare.14176673.v1
title: MEG_mat

description: The original MEG dataset was acquired from all 306 sensors (204 gradiometers and 102 magnetometers) during two different sessions for each participant and recorded as .fif files. As each session consists of two data files due to the session break, for better handling of the data, we have merged these files to create one single '.fif' file for each session. Thus, there are two raw '.fif' data files for each participant (i.e. one for each session). It is worth to be noted the data is available in two data formats i.e. MEG-BIDS format '.fif' and MATLAB compatible '.mat' file at the repository. In .mat format, each participant data is stored in two folders (i.e. session 1 and session 2) under the root directory of 'MEG_mat'.
DOI: 10.5525/gla.researchdata.1110
title: A peer-led intervention to promote sexual health in secondary schools: the STASH feasibility study
DOI: 10.6084/m9.figshare.14453526
title: 2009-2017panel dataset for Examining the spatial mode in the early market for electric vehicles adoption.xlsx

description: In this study, the number of new energy passenger cars to be popularized and implemented is selected as the measurement index for the dependent variable (EV adoption).The independent variables included socio-economic characteristics (including population intensity, university degree, per capita income, public employment, self-employment, and unemployment) and the characteristics of the transportation system (including the number of charging piles, residents’ enjoyment of bus service, and residents’ enjoyment of taxi service). The EVs in this study refer to pure EVs and plug-in hybrid EVs as obtained from the Statistical Yearbook of Energy-saving and New Energy Vehicles (2010-2018) and by consolidating the number of popularization and implementation of pure EVs and plug-in hybrid vehicles. The measurement index of independent variables is obtained by considering representativeness and measurability, as presented in Table 1. Apart from the number of charging piles sourced from the Statistical Yearbook of Energy Saving and New Energy Vehicles (2010–2018), the other independent variables were obtained from the Statistical Yearbook of Chinese Cities (2010–2017), the Annual Statistical Bulletins of Cities and the Qianzhan network(www.qianzhan.com).
DOI: 10.7795/710.20210414
title: Measurement and simulation data for "Optical form measurement employing a tiltable line scanning low coherence interferometer for annular subaperture stitching interferometry"

description: The provided data set and simulation software enables the immediate replication of the results presented in "Optical form measurement employing a tiltable line scanning low coherence interferometer for annular subaperture stitching interferometry." The research data is structured with respect to the figures presented in the contribution. Each subfolder contains all necessary measurement or simulation data to receive the figure from the contribution by running a MATLAB file. Therefore, it is possible to compare the results with full context to those presented in the contribution. The simulations demonstrate the transition of radial displacement uncertainties in an annular subaperture stitching interferometer through surface stitching algorithms to the topography result. The comparison of the simulation and measurement results indicates, that the radial displacement errors are the dominant source of topography deviations. By modelling of the radial displacement errors an estimate of the expanded uncertainty of the surface form measurement may be received.
description: description of the individual files: Each folder refers to a figure or a table in the related article: Figs. 2-5 contain simulation results Figs. 6-7 contain measurement results Figs. 8-11 contain comparisons of measurement and simulation results Each folder contains a "HOWTO.txt" file with instructions how to generate the graphical output of the measurement or simulation data. Additional instructions in the "HOWTO.txt" files explain how to repeat the virtual experiments. recommended software to open the data: MATLAB R2016b, Python (https://docs.scipy.org/doc/scipy/reference/generated/scipy.io.loadmat.html) -The simulation and data evaluation files are *.m files and require MATLAB to be executed. However, they may be opened in a text editor to view the code. -The measurement and simulation data are stored as compressed multidimensional structures in *.mat files. These may be opened with MATLAB, but may also be converted with the named Python script into ASCII-based data formats like *.h5.
DOI: 10.6084/m9.figshare.12991592
title: COVID-CT-MD: COVID-19 Computed Tomography Scan Dataset Applicable in Machine Learning and Deep Learning

description: COVID-19, CAP and Normal subjects are placed in separate folders, within which patients are arranged in folders, followed by CT scan slices in DICOM format. Index.csv is related to the patients having slice-level and lobe-level labels. The indices given to patients in Index.csv file are then used in Slice-level-labels.npy and Lobe-level-labels.npy to indicate the slice and lobe labels. Slice-level-labels.npy is a 2D binary Numpy array in which the existence of infection in a specific slice is indicated by 1 and the lack of infection is shown by 0. In Slice-level-labels.npy, the first dimension represents the case index and the second one represents the slice numbers. Lobe-level-labels.npy is a 3D binary Numpy array in which the existence of infection in a specific lobe and slice is determined by 1 in the corresponding element of the array. Like the slice-level array, in Lobe-level-labels.npy, the two first dimensions represent the case index and slice numbers respectively. The third dimension shows the lobe indices which are specified as follows: 0 : Left Lower Lobe (LLL) 1 : Left Upper Lobe (LUL) 2 : Right Lower Lobe (RLL) 3 : Right Middle Lobe (RML) 4 : Right Upper Lobe (RUL) It is worth noting that CT slices are sorted based on the "Slice Location" value stored in the corresponding DICOM tag "(0020,1041) - DS - Slice Location". The slice-level and lobe-level labels are provided according to described slice order. The researchers, however, can re-arrange the slices using other CT attributes based on their preference, as long as they re-arrange the labels accordingly. The COVID-CT-MD dataset is also accompanied with the clinical data, stored in "Clinical-data.csv". Finally, to facilitate the inter-observer reliability studies, labels assigned by the three radiologists are separately provided in "Radiogists-seperated-labels.csv".
DOI: 10.15468/uh62kg
title: New and poorly known giant scale insects (Homoptera: Coccinea: Margarodidae s. lat.) from the Oriental region with taxonomic and nomenclatural notes on the subfamily Monophlebinae

description: This dataset contains the digitized treatments in Plazi based on the original journal article Gavrilov-Zimin, Ilya A. (2021): New and poorly known giant scale insects (Homoptera: Coccinea: Margarodidae s. lat.) from the Oriental region with taxonomic and nomenclatural notes on the subfamily Monophlebinae. European Journal of Taxonomy 746 (1): 50-61, DOI: https://doi.org/10.5852/ejt.2021.746.1317, URL: http://zoobank.org/c8b84fd5-c191-4228-9cc9-9cbb4f8a0c68
DOI: 10.17028/rd.lboro.14453553
title: Supplemental Information files for: YOT Talk: Examining the communicative influences on children’s engagement with youth justice assessment processes

description: Supplemental Information files for: YOT Talk: Examining the communicative influences on children’s engagement with youth justice assessment processes<br>This article presents an evidence-based analysis of the communicative influences on children’s engagement in the Youth Justice System of England and Wales. The multidisciplinary criminologist–linguist ‘YOT Talk’ project utilized Svalberg’s (2009) dimensions of engagement (cognitive, affective, social; augmented by behavioural) to explore the enablers of, and barriers to, children’s engagement with youth justice assessment processes. A tripartite mixed methodology of observation of assessment interviews, questionnaires with children in the Youth Justice System and youth justice practitioners, and focus groups with practitioners was implemented across three Youth Offending Teams in England and Wales. Analyses synergized methods from conversation analysis and corpus linguistics. Findings inform recommendations for refocusing youth justice assessment and staff training on facilitating children’s communicative engagement (that is, enhancing enablers and removing/minimizing barriers). These findings and recommendations challenge asymmetrical (adult-centric) power dynamics during assessment interviews and challenge perceptions of children’s communicative deficits as irreconcilable barriers to effective assessment.<br>
DOI: 10.17028/rd.lboro.14453553.v1
title: Supplemental Information files for: YOT Talk: Examining the communicative influences on children’s engagement with youth justice assessment processes

description: Supplemental Information files for: YOT Talk: Examining the communicative influences on children’s engagement with youth justice assessment processes<br>This article presents an evidence-based analysis of the communicative influences on children’s engagement in the Youth Justice System of England and Wales. The multidisciplinary criminologist–linguist ‘YOT Talk’ project utilized Svalberg’s (2009) dimensions of engagement (cognitive, affective, social; augmented by behavioural) to explore the enablers of, and barriers to, children’s engagement with youth justice assessment processes. A tripartite mixed methodology of observation of assessment interviews, questionnaires with children in the Youth Justice System and youth justice practitioners, and focus groups with practitioners was implemented across three Youth Offending Teams in England and Wales. Analyses synergized methods from conversation analysis and corpus linguistics. Findings inform recommendations for refocusing youth justice assessment and staff training on facilitating children’s communicative engagement (that is, enhancing enablers and removing/minimizing barriers). These findings and recommendations challenge asymmetrical (adult-centric) power dynamics during assessment interviews and challenge perceptions of children’s communicative deficits as irreconcilable barriers to effective assessment.<br>
DOI: 10.5281/zenodo.4704887
title: Output data for the BG publication bg-2020-97

description: Description
DOI: 10.5281/zenodo.4704886
title: Output data for the BG publication bg-2020-97

description: Description
DOI: 10.34740/kaggle/dsv/2137721
title: UK Pickup Brands Dataset
DOI: 10.34740/kaggle/dsv/2137713
title: UK Van Brands Dataset
DOI: 10.6084/m9.figshare.12948713.v4
title: A dataset on affiliation of venture capitalists in China between 2000 and 2016

description: This dataset identifies the affiliation of each VC that have invested in China between 2000 and 2006. Specifically, a VC in a given year can be labelled as the following types: GVC (public agency-affiliated and state-owned enterprise-affiliated), CVC (corporate VC), IVC (independent VC), BVC (bank-affiliated VC), FVC (financial & non-bank-affiliated VC), UVC (university endowment/spin-out unit), and PenVC (pension-affiliated VC). The dataset also denotes whether a VC has foreign background. For more information, please contact Dr Jin Chen, University of Nottingham Ningbo China (Email: jin.chen@nottingham.edu.cn).
DOI: 10.5517/ccdc.csd.cc23vhzg
title: CCDC 1961896: Experimental Crystal Structure Determination

description: Related Article: Lin Xiao, Yanxia Zhao, Sijie Qiao, Ziyue Sun, Orlando Santoro, Carl Redshaw|2020|Dalton Trans.|49|1456|doi:10.1039/C9DT04332B
DOI: 10.5517/ccdc.csd.cc25vbn1
title: CCDC 2021313: Experimental Crystal Structure Determination

description: Related Article: Toshiya Ikeuchi, Keiichi Hirano, Masanobu Uchiyama|2021|J.Am.Chem.Soc.|143|4879|doi:10.1021/jacs.0c12619
DOI: 10.5517/ccdc.csd.cc26p2gg
title: CCDC 2046045: Experimental Crystal Structure Determination

description: Related Article: Toshiya Ikeuchi, Keiichi Hirano, Masanobu Uchiyama|2021|J.Am.Chem.Soc.|143|4879|doi:10.1021/jacs.0c12619
DOI: 10.6084/m9.figshare.3761562.v1843
title: Online Labour Index: Measuring the Online Gig Economy for Policy and Research

description: Data repository for the data underlying the Online Labour Index. See http://ilabour.oii.ox.ac.uk online-labour-index/ for details.
DOI: 10.6084/m9.figshare.14453700
title: Engineering Protein Dynamics of Ancestral Luciferase (Microfluidic temperature profiles)

description: The dataset contains primary data for the microfluidic characterization of InDel hits (within publication https://doi.org/10.26434/chemrxiv.12808295.v1) using the microfluidic platform (published in https://doi.org/10.1021/acs.analchem.9b01839). There are 6 batches in the dataset, in which different enzyme variants (InDel hits) were characterized for HLD activity in different temperatures (to obtain temperature profiles). The TXT file describes, which InDels were measured in which batch. For each batch, there is also an excel sheet with the processed data using MatLab script (accesible in Supplementary information of above mentioned paper in Analytical Chemistry - https://pubs.acs.org/doi/suppl/10.1021/acs.analchem.9b01839/suppl_file/ac9b01839_si_001.pdf.)<br>
DOI: 10.25345/c5nf99
title: MassIVE MSV000087244 - queryraw.mzid test test test test test test test test test test
title: test test test test test test test test test test test test test test test test test test test test test test test test test test test test test test test test test test test test test test test test test test test test test test test test test test test test test test test test test test test test
DOI: 10.5281/zenodo.4705050
title: QC'd European 1000G data

description: QC'd European 1000G data from LDAK vignette
DOI: 10.5281/zenodo.4705096
title: Deliverable 3.1 - Demonstration of an Organic hot-electron double transistor

description: The objective of the deliverable is to explore hybrid organic spintronic devices in which to perform spin transport and manipulation beyond simple spin valves. With the aim of exploring the spin transport mechanisms in organic materials with small spin-orbit coupling, we need to demonstrate the fabrication of <strong>double organic hot-electron transistors</strong> in which the spin current can eventually be manipulated by an external out-of-plane magnetic field.
DOI: 10.5281/zenodo.4697254
title: Deliverable 3.1 - Demonstration of an Organic hot-electron double transistor

description: The objective of the deliverable is to explore hybrid organic spintronic devices in which to perform spin transport and manipulation beyond simple spin valves. With the aim of exploring the spin transport mechanisms in organic materials with small spin-orbit coupling, we need to demonstrate the fabrication of <strong>double organic hot-electron transistors</strong> in which the spin current can eventually be manipulated by an external out-of-plane magnetic field.
DOI: 10.6084/m9.figshare.14453772.v1
title: Row data.csv

description: row data
DOI: 10.5281/zenodo.4701316
title: Synbols: Probing Learning Algorithms with Synthetic Datasets

description: <strong>Synbols: Probing Learning Algorithms with Synthetic Datasets</strong> Benchmark datasets generated using the Synbols dataset generator. [ Paper ] [ Code ]
DOI: 10.5281/zenodo.4701315
title: Synbols: Probing Learning Algorithms with Synthetic Datasets

description: <strong>Synbols: Probing Learning Algorithms with Synthetic Datasets</strong> Benchmark datasets generated using the Synbols dataset generator. [ Paper ] [ Code ]
DOI: 10.6084/m9.figshare.14453814
title: Code names.xlsx

description: Code names
DOI: 10.6084/m9.figshare.14453814.v2
title: Code names.xlsx

description: Code names
DOI: 10.6084/m9.figshare.14453814.v1
title: Code names.xlsx

description: Code names
DOI: 10.6084/m9.figshare.14453811
title: Stata code.xlsx

description: Stata code
DOI: 10.6084/m9.figshare.14453811.v2
title: Stata code.xlsx

description: Stata code
DOI: 10.5281/zenodo.4680442
title: Raindrops on Windshield Dataset

description: Autonomous vehicles use cameras as one of the primary sources of information about the environment. Adverse weather conditions such as raindrops, snow, mud, and others, can lead to various image artifacts. Such artifacts significantly degrade the quality and reliability of the obtained visual data and can lead to accidents if they are not detected in time. We present an ongoing work on a new dataset for training and assessing vision algorithms' performance for different tasks of image raindrops detection on either camera lens or windshield. At the moment, it contains 8190 images, of which 3390 contain raindrops. Images were labeled by outlining artifacts with polygons. Labeling results are stored in JSON format. Besides, binary masks were generated from this markup, which are also presented in the dataset for convenience. White color denotes an artifact area. For a fast download please use zenodo-get. To install it use the following commands: <pre><code>pip install zenodo-get zenodo_get https://zenodo.org/record/4680442 --output-dir=RaindropsOnWindshield</code></pre>
description: {"references": ["Vera Soboleva and Oleg Shipitko. \"Raindrops on Windshield: Dataset and Lightweight Gradient-Based Detection Algorithm\". arXiv preprint https://arxiv.org/abs/2104.05078 (2021)"]}