cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5522/04/12383873.v1
title: Household Transmission of Seasonal Coronavirus Infections: Results from the Flu Watch cohort study

description: These datasets comprise the main analyses for the paper “Household Transmission of Seasonal Coronavirus Infections: Results from the Flu Watch cohort study”, published in Wellcome Open Research. Details of the statistical methods are reported in the article. Datasets are given in CSV format and, where relevant, in .dta format. Descriptions for each dataset are as follows:<br> Household_CoV_acquired.csv/dta – data required to compute the proportion of cases presumably acquired outside of the household versus and the proportion acquired from household transmission. Each row represents an anonymised PCR-confirmed seasonal coronavirus case. <br> Household_CoV_TransmissionRisk.csv/dta – data required to compute the risk of symptomatic onward household transmission following a seasonal coronavirus index case, and perform stratified descriptive analyses. <br> Household_CoV_SAR.csv/.dta – data required to compute the seasonal coronavirus secondary attack risk overall and by strain. Each row represents an anonymised exposed-index pair from a given outbreak.<br> HH Transmission Serial Interval.csv – presents available, anonymised data required to compute the median clinical-onset serial interval overall and by strain for each household outbreak
DOI: 10.6084/m9.figshare.12385421.v3
title: Adoção de políticas editoriais de dados científicos em revistas da Comunicação e Informação

description: O conjunto de dados trata de como as revistas da área de Comunicação e Informação, classificadas pelo estrato Qualis A1 do Quadriênio 2013-2016 estão adotando as políticas de dados científicos. A amostra cobriu 46 periódicos foi coletado informações a respeito: política editorial para dados, se o depósito de dados é obrigatório, se utiliza repositório interno ou externo, qual é indicado, também foi investigado nas diretrizes para autores o uso dos dados, se é recomendado algum padrão de citação de dados, que tipo de licença e vinculação institucional. Para o tratamento dos dados utilizou-se do Planilhas Google e para a visualização dos dados coletados foi utilizada a ferramenta Canva.<br>
DOI: 10.6084/m9.figshare.12383564
title: A Mode-Jumping Algorithm for Bayesian Factor Analysis

description: Exploratory factor analysis is a dimension-reduction technique commonly used in psychology, finance, genomics, neuroscience, and economics. Advances in computational power have opened the door for fully Bayesian treatments of factor analysis. One open problem is enforcing rotational identifability of the latent factor loadings, as the loadings are not identified from the likelihood without further restrictions. Nonidentifability of the loadings can cause posterior multimodality, which can produce misleading posterior summaries. The positive-diagonal, lower-triangular (PLT) constraint is the most commonly used restriction to guarantee identifiability, in which the upper <i>m</i> × <i>m</i> submatrix of the loadings is constrained to be a lower-triangular matrix with positive-diagonal elements. The PLT constraint can fail to guarantee identifiability if the constrained submatrix is singular. Furthermore, though the PLT constraint addresses identifiability-related multimodality, it introduces additional mixing issues. We introduce a new Bayesian sampling algorithm that efficiently explores the multimodal posterior surface and addresses issues with PLT-constrained approaches. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.12383549
title: Structure and Sensitivity in Differential Privacy: Comparing <i>K</i>-Norm Mechanisms

description: Differential privacy (DP) provides a framework for provable privacy protection against arbitrary adversaries, while allowing the release of summary statistics and synthetic data. We address the problem of releasing a noisy real-valued statistic vector <i>T</i>, a function of sensitive data under DP, via the class of <i>K</i>-norm mechanisms with the goal of minimizing the noise added to achieve privacy. First, we introduce the <i>sensitivity space of T</i>, which extends the concepts of sensitivity polytope and sensitivity hull to the setting of arbitrary statistics <i>T</i>. We then propose a framework consisting of three methods for comparing the <i>K</i>-norm mechanisms: (1) a multivariate extension of stochastic dominance, (2) the entropy of the mechanism, and (3) the conditional variance given a direction, to identify the optimal <i>K</i>-norm mechanism. In all of these criteria, the optimal <i>K</i>-norm mechanism is generated by the convex hull of the sensitivity space. Using our methodology, we extend the objective perturbation and functional mechanisms and apply these tools to logistic and linear regression, allowing for private releases of statistical results. Via simulations and an application to a housing price dataset, we demonstrate that our proposed methodology offers a substantial improvement in utility for the same level of risk.
DOI: 10.6084/m9.figshare.12383564.v2
title: A Mode-Jumping Algorithm for Bayesian Factor Analysis

description: Exploratory factor analysis is a dimension-reduction technique commonly used in psychology, finance, genomics, neuroscience, and economics. Advances in computational power have opened the door for fully Bayesian treatments of factor analysis. One open problem is enforcing rotational identifability of the latent factor loadings, as the loadings are not identified from the likelihood without further restrictions. Nonidentifability of the loadings can cause posterior multimodality, which can produce misleading posterior summaries. The positive-diagonal, lower-triangular (PLT) constraint is the most commonly used restriction to guarantee identifiability, in which the upper <i>m</i> × <i>m</i> submatrix of the loadings is constrained to be a lower-triangular matrix with positive-diagonal elements. The PLT constraint can fail to guarantee identifiability if the constrained submatrix is singular. Furthermore, though the PLT constraint addresses identifiability-related multimodality, it introduces additional mixing issues. We introduce a new Bayesian sampling algorithm that efficiently explores the multimodal posterior surface and addresses issues with PLT-constrained approaches. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.12383549.v2
title: Structure and Sensitivity in Differential Privacy: Comparing <i>K</i>-Norm Mechanisms

description: Differential privacy (DP) provides a framework for provable privacy protection against arbitrary adversaries, while allowing the release of summary statistics and synthetic data. We address the problem of releasing a noisy real-valued statistic vector <i>T</i>, a function of sensitive data under DP, via the class of <i>K</i>-norm mechanisms with the goal of minimizing the noise added to achieve privacy. First, we introduce the <i>sensitivity space of T</i>, which extends the concepts of sensitivity polytope and sensitivity hull to the setting of arbitrary statistics <i>T</i>. We then propose a framework consisting of three methods for comparing the <i>K</i>-norm mechanisms: (1) a multivariate extension of stochastic dominance, (2) the entropy of the mechanism, and (3) the conditional variance given a direction, to identify the optimal <i>K</i>-norm mechanism. In all of these criteria, the optimal <i>K</i>-norm mechanism is generated by the convex hull of the sensitivity space. Using our methodology, we extend the objective perturbation and functional mechanisms and apply these tools to logistic and linear regression, allowing for private releases of statistical results. Via simulations and an application to a housing price dataset, we demonstrate that our proposed methodology offers a substantial improvement in utility for the same level of risk.
DOI: 10.6084/m9.figshare.12383525
title: Bayesian Regression With Undirected Network Predictors With an Application to Brain Connectome Data

description: This article focuses on the relationship between a measure of creativity and the human brain network for subjects in a brain connectome dataset obtained using a diffusion weighted magnetic resonance imaging procedure. We identify brain regions and interconnections that have a significant effect on creativity. Brain networks are often expressed in terms of symmetric adjacency matrices, with row and column indices of the matrix representing the regions of interest (ROI), and a cell entry signifying the estimated number of fiber bundles connecting the corresponding row and column ROIs. Current statistical practices for regression analysis with the brain network as the predictor and the measure of creativity as the response typically vectorize the network predictor matrices prior to any analysis, thus failing to account for the important structural information in the network. This results in poor inferential and predictive performance in presence of small sample sizes. To answer the scientific questions discussed above, we develop a flexible Bayesian framework that avoids reshaping the network predictor matrix, draws inference on brain ROIs and interconnections significantly related to creativity, and enables accurate prediction of creativity from a brain network. A novel class of <i>network shrinkage priors</i> for the coefficient corresponding to the network predictor is proposed to achieve these goals simultaneously. The Bayesian framework allows characterization of uncertainty in the findings. Empirical results in simulation studies illustrate substantial inferential and predictive gains of the proposed framework in comparison with the ordinary high-dimensional Bayesian shrinkage priors and penalized optimization schemes. Our framework yields new insights into the relationship of brain regions with creativity, also providing the uncertainty associated with the scientific findings. Supplementary materials for this article, including a standardized description of the materials available for reproducing the work, are available as an online supplement.
DOI: 10.6084/m9.figshare.12383525.v2
title: Bayesian Regression With Undirected Network Predictors With an Application to Brain Connectome Data

description: This article focuses on the relationship between a measure of creativity and the human brain network for subjects in a brain connectome dataset obtained using a diffusion weighted magnetic resonance imaging procedure. We identify brain regions and interconnections that have a significant effect on creativity. Brain networks are often expressed in terms of symmetric adjacency matrices, with row and column indices of the matrix representing the regions of interest (ROI), and a cell entry signifying the estimated number of fiber bundles connecting the corresponding row and column ROIs. Current statistical practices for regression analysis with the brain network as the predictor and the measure of creativity as the response typically vectorize the network predictor matrices prior to any analysis, thus failing to account for the important structural information in the network. This results in poor inferential and predictive performance in presence of small sample sizes. To answer the scientific questions discussed above, we develop a flexible Bayesian framework that avoids reshaping the network predictor matrix, draws inference on brain ROIs and interconnections significantly related to creativity, and enables accurate prediction of creativity from a brain network. A novel class of <i>network shrinkage priors</i> for the coefficient corresponding to the network predictor is proposed to achieve these goals simultaneously. The Bayesian framework allows characterization of uncertainty in the findings. Empirical results in simulation studies illustrate substantial inferential and predictive gains of the proposed framework in comparison with the ordinary high-dimensional Bayesian shrinkage priors and penalized optimization schemes. Our framework yields new insights into the relationship of brain regions with creativity, also providing the uncertainty associated with the scientific findings. Supplementary materials for this article, including a standardized description of the materials available for reproducing the work, are available as an online supplement.
DOI: 10.6084/m9.figshare.12383291
title: Metadata record for: Transcriptome data of temporal and cingulate cortex in the Rett syndrome brain

description: This dataset contains key characteristics about the data described in the Data Descriptor Transcriptome data of temporal and cingulate cortex in the Rett syndrome brain. <br> Contents: <br> 1. human readable metadata summary table in CSV format 2. machine readable metadata file in JSON format <br> <br> <br>
DOI: 10.6084/m9.figshare.12383291.v1
title: Metadata record for: Transcriptome data of temporal and cingulate cortex in the Rett syndrome brain

description: This dataset contains key characteristics about the data described in the Data Descriptor Transcriptome data of temporal and cingulate cortex in the Rett syndrome brain. <br> Contents: <br> 1. human readable metadata summary table in CSV format 2. machine readable metadata file in JSON format <br> <br> <br>
DOI: 10.6084/m9.figshare.12383015
title: COVID-19 in India: an epidemic in congested cities

description: COVID-19 in India
DOI: 10.6084/m9.figshare.12383015.v1
title: COVID-19 in India: an epidemic in congested cities

description: COVID-19 in India
DOI: 10.6084/m9.figshare.12382916
title: Data_Perceived and Actual Growth Following HSCT

description: This dataset presents the scores from various psychometric scales in order to establish different relationships between several dimensions involved in mental health, quality of life and post-traumatic-growth of patients undergoing bone marrow transplantation. Mean, difference scores, reliable change index have been also computed. <br>
DOI: 10.6084/m9.figshare.12382892
title: Illustrative Example 1 for TabbyXL, a Software Platform for Rule-Based Spreadsheet Data Extraction and Transformation

description: This illustrative example demonstrates the applicability of TabbyXL toolset (https://github.com/tabbydoc/tabbyxl) for extracting data items and their relationships from spreadsheet tables.
DOI: 10.6084/m9.figshare.12382892.v1
title: Illustrative Example 1 for TabbyXL, a Software Platform for Rule-Based Spreadsheet Data Extraction and Transformation

description: This illustrative example demonstrates the applicability of TabbyXL toolset (https://github.com/tabbydoc/tabbyxl) for extracting data items and their relationships from spreadsheet tables.
DOI: 10.6084/m9.figshare.12382916.v2
title: Data_Perceived and Actual Growth Following HSCT

description: This dataset presents the scores from various psychometric scales in order to establish different relationships between several dimensions involved in mental health, quality of life and post-traumatic-growth of patients undergoing bone marrow transplantation. Mean, difference scores, reliable change index have been also computed. <br>
DOI: 10.6084/m9.figshare.12382865
title: Supplementary Tables from Internet ‘shellebrity' reflects on origin of rare mirror-image snails

description: Supplementary Tables 1 and 2 and 3
DOI: 10.6084/m9.figshare.12382916.v1
title: Data_Perceived and Actual Growth Following HSTC

description: This dataset presents the scores from various psychometric scales in order to establish different relationships between several dimensions involved in mental health, quality of life and post-traumatic-growth of patients undergoing bone marrow transplantation. Mean, difference scores, reliable change index have been also computed. <br>
DOI: 10.6084/m9.figshare.12382865.v1
title: Supplementary Tables from Internet ‘shellebrity' reflects on origin of rare mirror-image snails

description: Supplementary Tables 1 and 2 and 3
DOI: 10.25386/genetics.12855311.v1
title: Supplemental Material for Kuhl et al., 2020

description: Supplemental Data, including yeast strains, and figure legends.
DOI: 10.25386/genetics.12855311
title: Supplemental Material for Kuhl et al., 2020

description: Supplemental Data, including yeast strains, and figure legends.
DOI: 10.6084/m9.figshare.12382748
title: Illustrative Example 2 for TabbyXL, a Software Platform for Rule-Based Spreadsheet Data Extraction and Transformation

description: This illustrative example demonstrates the applicability of TabbyXL toolset (https://github.com/tabbydoc/tabbyxl) for extracting data items and their relationships from spreadsheet tables.
DOI: 10.6084/m9.figshare.12382748.v1
title: Illustrative Example 2 for TabbyXL, a Software Platform for Rule-Based Spreadsheet Data Extraction and Transformation

description: This illustrative example demonstrates the applicability of TabbyXL toolset (https://github.com/tabbydoc/tabbyxl) for extracting data items and their relationships from spreadsheet tables.
DOI: 10.6084/m9.figshare.12382694
title: Provenance of the Miocene Nanchital Conglomerate, western Chiapas Foldbelt, Mexico: implications for reservoir sands in the Sureste Basin, greater Campeche Province

description: Supplementary table 1: Detailed zircon Uâ€“Pb analytical data
DOI: 10.6084/m9.figshare.12382694.v1
title: Provenance of the Miocene Nanchital Conglomerate, western Chiapas Foldbelt, Mexico: implications for reservoir sands in the Sureste Basin, greater Campeche Province

description: Supplementary table 1: Detailed zircon Uâ€“Pb analytical data
DOI: 10.25375/uct.12382706.v1
title: MOSAIC: A model to assess the cost-effectiveness of ICU strategies for the South African Covid-19 response

description: As the COVID-19 pandemic progresses, the demands on the health care system will intensify and will result in critical shortages of resources (hospital beds, intensive care unit (ICU) beds, ventilators, medical workforce), particularly in the public sector. Given the expected downturn in an already weak economy coupled with the increased demand for government resources for economic relief and other measures, the ability of government to commit additional funding to an already under-funded public health sector is limited. Within this context, it is imperative that available public resources are used fairly, optimally and efficiently - we simply cannot afford to waste any resources. <br>This rapid economic evaluation intends to inform Covid-19 health system decision-making. In this report, we respond to the question: What is the cost-effectiveness of ICU care versus treatment in general ward in supporting severe Covid-19 cases? Given the emergent nature of Covid-19 and the huge uncertainty in key parameters, a simple excel-based model is provided. This simplicity is designed to facilitate understanding. In addition, the framework allows for parameters to be varied and ultimately updated as sufficient local data become available.<br>
DOI: 10.25375/uct.12382706.v2
title: MOSAIC: A model to assess the cost-effectiveness of ICU strategies for the South African COVID-19 response

description: As the COVID-19 pandemic progresses, the demands on the health care system will intensify and will result in critical shortages of resources (hospital beds, intensive care unit (ICU) beds, ventilators, medical workforce), particularly in the public sector. In such a context, it becomes imperative that resources are used in the most humane ways possible; and that decisions about resource allocation are made carefully and with compassion. While there are a number of key resource allocation decisions that need to be made in the response to COVID-19, this rapid economic evaluation responds to the question: What is the cost-effectiveness of ICU care versus treatment in general ward in supporting severe COVID-19 cases? Given the emergent nature of COVID-19 and the huge uncertainty in key parameters, a simple excel-based model is provided. This simplicity is designed to facilitate understanding. In addition, the framework allows for parameters to be varied and ultimately updated as sufficient local data become available.
DOI: 10.25375/uct.12382706.v3
title: MOSAIC: A model to assess the cost-effectiveness of ICU strategies for the South African COVID-19 response

description: As the COVID-19 pandemic progresses, the demands on the health care system will intensify and will result in critical shortages of resources (hospital beds, intensive care unit (ICU) beds, ventilators, medical workforce), particularly in the public sector. In such a context, it becomes imperative that resources are used in the most humane ways possible; and that decisions about resource allocation are made carefully and with compassion. While there are a number of key resource allocation decisions that need to be made in the response to COVID-19, this rapid economic evaluation responds to the question: What is the cost-effectiveness of ICU care versus treatment in general ward in supporting severe COVID-19 cases? Given the emergent nature of COVID-19 and the huge uncertainty in key parameters, a simple excel-based model is provided. This simplicity is designed to facilitate understanding. In addition, the framework allows for parameters to be varied and ultimately updated as sufficient local data become available.
DOI: 10.6084/m9.figshare.12382667.v1
title: LUCAS 2018 Copernicus

description: LUCAS 2018 Copernicus data<br>The data published are distributed along with the paper entitled "<b>LUCAS Copernicus 2018: Earth Observation relevant in-situ data on land cover throughout the European Union</b>" by <i>Raphaël d’Andrimont, Astrid Verhegghen, Michele Meroni, Guido Lemoine, Peter Strobl, Beatrice Eiselt, Momchil Yordanov, Laura Martinez-Sanchez and Marijn van der Velde</i>.<br><br><br>Shapefile of polygons to join with the CSV using POINT_ID<br>97 original variables of LUCAS survey9 label explicit variables3 variables<br>Data generated with 'CreateCopernicusPolygonsAll.R'
DOI: 10.6084/m9.figshare.12382667.v2
title: LUCAS 2018 Copernicus

description: LUCAS 2018 Copernicus data<br>The data published are distributed along with the paper entitled "<b>LUCAS Copernicus 2018: Earth Observation relevant in-situ data on land cover throughout the European Union</b>" by <i>Raphaël d’Andrimont, Astrid Verhegghen, Michele Meroni, Guido Lemoine, Peter Strobl, Beatrice Eiselt, Momchil Yordanov, Laura Martinez-Sanchez and Marijn van der Velde</i>.<br><br><br>The repository contains the following files:<br>- "<b>LUCAS_2018_Copernicus_polygons.shp</b>" : Shapefile of polygons with the "POINT_ID" attribute- "<b>LUCAS_2018_Copernicus_attributes.csv</b>" : CSV containing the 109 variables including the "POINT_ID" - "<b>CreateCopernicusPolygonsAll.R</b>" : R script used to generate the data- "<b>LUCAS_2018_Copernicus_ReadMe.txt</b>" : short description of the data repository<br>
DOI: 10.6084/m9.figshare.12382619
title: Adult emergence patterns and body size of two mayfly species of <i>Isonychia</i> Eaton, 1871 from Hokkaido, Japan

description: We conducted an emergence survey of <i>Isonychia</i> (<i>Isonychia</i>) <i>japonica</i> Ulmer, 1919 and <i>Isonychia</i> (<i>Prionoides</i>) <i>shima</i> Matsumura, 1931 at four sites in the Izari-gawa River system, Hokkaido, Japan in 2015 and 2016 to investigate differences in emergence seasons between the species. The present study showed that <i>I.</i> (<i>I.</i>) <i>japonica</i> was widely distributed from up- to down-stream with abundant numbers in middle-stream, while <i>I.</i> (<i>P.</i>) <i>shima</i> was mostly distributed up-stream. The emergence season of <i>I.</i> (<i>I.</i>) <i>japonica</i> was longer than that of <i>I.</i> (<i>P.</i>) <i>shima</i>, but their emergence periods overlapped in August and early September, suggesting that their adults are not separated temporally. Body size comparison showed that, at the same sites, the emerged in August specimens of <i>I.</i> (<i>I.</i>) <i>japonica</i> were larger than those of <i>I.</i> (<i>P.</i>) <i>shima</i>.