cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.4903784
title: Data and code for the Validation of a Spanish Questionnaire Implementing the Stanford Educational Framework for Evaluation of Clinical Teachers: MEDUC30

description: <b>Introduction</b>. Although there are instruments in Spanish to evaluate teacher performance during the initial basic science training years or during medical specialization; there are few instruments for the clinical training years, in which the main role of the teacher is to facilitate experiential learning. The MEDUC30 questionnaire is a Spanish instrument developed by the xx University School of Medicine. It was built using the Stanford Faculty Development Program (SFDP) educational framework for evaluation of clinical teachers’ effectiveness by students. MEDUC30 has been used since 2004 at Xx University and was previously studied with exploratory methods. <b>Objective</b>. To provide satisfying evidence of validity and reliability to support MEDUC30’s usefulness in Spanish-speaking contexts, using confirmatory analytical methods. <b>Method</b>. This is an analytical, longitudinal and retrospective study, in which 24,681 MEDUC30 questionnaires evaluating 579 clinical teachers were analysed. They were completed by medical students from 3rd to 7th year of study, from 2004 throughout 2015. The questionnaire’s structure was studied by exploratory (EFA) and confirmatory factor analysis (CFA). Measurement invariance was evaluated with multi-group CFA. <b>Results</b>. Four different models were compared; a bi-factor model was the best alternative to explain the data’s structure. It was composed of one general and six domain-specific factors: [i] Patient-Based Teaching, [ii] Communication of Goals, [iii] Evaluation and Feedback, [iv] Promotion of Understanding, Retention and Self-directed Learning, [v] Control of the Session, and [vi] Learning Climate. The overall reliability of MEDUC30 scores was excellent (Cronbach’s α = .98, McDonald’s ω = .98) and that of the six specific factors was very good (Cronbach’s α =.88-.95, McDonald’s ω = .78-.94). Measurement invariance extended over teacher gender, date, semester, year of study, clinical teaching setting, and length of clinical rotation; all of these variables were sources of population heterogeneity. <b>Conclusions</b>. MEDUC30 is a valid and reliable Spanish instrument to evaluate clinical teachers. It can be used to provide formative feedback of general and domain-specific effectiveness to clinical teachers and to provide accurate information to department heads and program directors for resource allocation and promotion purposes, and ultimately to improve clinical teaching quality.
DOI: 10.17028/rd.lboro.4903841.v1
title: Rail complaints lodged by disabled travellers

description: This is a list of issues raised by travellers using the FixMyTransport platform developed by mySociety. The problems were submitted by travellers between mid 2011 and early 2015.The problem descriptions provide a good overview of the issues faced by rail travellers with disability.
DOI: 10.6084/m9.figshare.4903733
title: Fast Embedding for JOFC Using the Raw Stress Criterion

description: The joint optimization of fidelity and commensurability (JOFC) manifold matching methodology embeds an omnibus dissimilarity matrix consisting of multiple dissimilarities on the same set of objects. One approach to this embedding optimizes the preservation of fidelity to each individual dissimilarity matrix together with commensurability of each given observation across modalities via iterative majorization of a raw stress error criterion by successive Guttman transforms. In this article, we exploit the special structure inherent to JOFC to exactly and efficiently compute the successive Guttman transforms, and as a result we are able to greatly speed up the JOFC procedure for both in-sample and out-of-sample embedding. We demonstrate the scalability of our implementation on both real and simulated data examples.
DOI: 10.6084/m9.figshare.4903814.v1
title: Brugada Syndrome data for rare variant association analysis

description: The directory contains data described by Le Scouarnec et al. (2015) for the rare variant association analysis of Brugada syndrome (BrS). The quality control of this processed data is further detailed in the publication.<br>The directory contains:<br>-files named .txt. These files are genotype files with each row corresponding to a SNV and each column corresponding to an individual. SNV identifiers are indicated in the first column CHROM_POS_REF_ALT. Positions are according to the GRCh37/hg19 assembly. Other column names are the individual identifiers. Genotypes are coded 0, 1 or 2 according to the number of alternative alleles.<br>- a file named "phenotypes_BrS.txt". This file contains two columns: the individual identifier and the phenotype (affected: 1, unaffected: 0).<br>
DOI: 10.6084/m9.figshare.4903733.v1
title: Fast Embedding for JOFC Using the Raw Stress Criterion

description: The joint optimization of fidelity and commensurability (JOFC) manifold matching methodology embeds an omnibus dissimilarity matrix consisting of multiple dissimilarities on the same set of objects. One approach to this embedding optimizes the preservation of fidelity to each individual dissimilarity matrix together with commensurability of each given observation across modalities via iterative majorization of a raw stress error criterion by successive Guttman transforms. In this article, we exploit the special structure inherent to JOFC to exactly and efficiently compute the successive Guttman transforms, and as a result we are able to greatly speed up the JOFC procedure for both in-sample and out-of-sample embedding. We demonstrate the scalability of our implementation on both real and simulated data examples.
DOI: 10.6084/m9.figshare.4903736
title: Efficient Bayesian Inference for Multivariate Factor Stochastic Volatility Models

description: We discuss efficient Bayesian estimation of dynamic covariance matrices in multivariate time series through a factor stochastic volatility model. In particular, we propose two interweaving strategies to substantially accelerate convergence and mixing of standard MCMC approaches. Similar to marginal data augmentation techniques, the proposed acceleration procedures exploit nonidentifiability issues which frequently arise in factor models. Our new interweaving strategies are easy to implement and come at almost no extra computational cost; nevertheless, they can boost estimation efficiency by several orders of magnitude as is shown in extensive simulation studies. To conclude, the application of our algorithm to a 26-dimensional exchange rate dataset illustrates the superior performance of the new approach for real-world data. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.4903730
title: One-Step Generalized Estimating Equations With Large Cluster Sizes

description: Medical studies increasingly involve a large sample of independent clusters, where the cluster sizes are also large. Our motivating example from the 2010 Nationwide Inpatient Sample (NIS) has 8,001,068 patients and 1049 clusters, with average cluster size of 7627. Consistent parameter estimates can be obtained naively assuming independence, which are inefficient when the intra-cluster correlation (ICC) is high. Efficient generalized estimating equations (GEE) incorporate the ICC and sum all pairs of observations within a cluster when estimating the ICC. For the 2010 NIS, there are 92.6 billion pairs of observations, making summation of pairs computationally prohibitive. We propose a one-step GEE estimator that (1) matches the asymptotic efficiency of the fully iterated GEE; (2) uses a simpler formula to estimate the ICC that avoids summing over all pairs; and (3) completely avoids matrix multiplications and inversions. These three features make the proposed estimator much less computationally intensive, especially with large cluster sizes. A unique contribution of this article is that it expresses the GEE estimating equations incorporating the ICC as a simple sum of vectors and scalars.
DOI: 10.6084/m9.figshare.4903736.v1
title: Efficient Bayesian Inference for Multivariate Factor Stochastic Volatility Models

description: We discuss efficient Bayesian estimation of dynamic covariance matrices in multivariate time series through a factor stochastic volatility model. In particular, we propose two interweaving strategies to substantially accelerate convergence and mixing of standard MCMC approaches. Similar to marginal data augmentation techniques, the proposed acceleration procedures exploit nonidentifiability issues which frequently arise in factor models. Our new interweaving strategies are easy to implement and come at almost no extra computational cost; nevertheless, they can boost estimation efficiency by several orders of magnitude as is shown in extensive simulation studies. To conclude, the application of our algorithm to a 26-dimensional exchange rate dataset illustrates the superior performance of the new approach for real-world data. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.4903703
title: Supplementary Material for: Evacuation of a Tertiary Neonatal Centre: Lessons from the 2016 Kumamoto Earthquak

description: <i>Background:</i> Newborn infants hospitalised in the neonatal intensive care unit (NICU) are vulnerable to natural disasters. However, publications on evacuation from NICUs are sparse. The 2016 Kumamoto Earthquakes caused serious damage to Kumamoto City Hospital and its level III regional core NICU. Local/neighbour NICU teams and the disaster-communication team of a neonatal academic society cooperated to evacuate 38 newborn infants from the ward. <i>Objective:</i> The aim of this paper was to highlight potential key factors to improve emergency NICU evacuation and coordination of hospital transportation following natural disasters. <i>Methods:</i> Background variables including clinical risk scores and timing/destination of transportation were compared between infants, who subsequently were transferred to destinations outside of Kumamoto Prefecture, and their peers. <i>Results:</i> All but 1 of the infants were successfully evacuated from their NICU within 8 h. One very-low-birth-weight infant developed moderate hypothermia following transportation. Fourteen infants were transferred to NICUs outside of Kumamoto Prefecture, which was associated with the diagnosis of congenital heart disease, dependence on respiratory support, higher risk scores, and longer elapsed time from the decision to departure. There was difficulty in arranging helicopter transportation because the coordination office of the Disaster Medical Assistance Team had requisitioned most air/ground ambulances and only helped arrange ground transportations for 13 low-risk infants. Transportation for all 10 high-risk infants (risk scores greater than or equal to the upper quartile) was arranged by local/neighbour NICUs. <i>Conclusions:</i> Although the overall evacuation process was satisfactory, potential risks of relying on the adult-based emergency transportation system were highlighted. A better system needs to be developed urgently to put appropriate priority on vulnerable infants.
DOI: 10.6084/m9.figshare.4903706
title: FigShareNotes.txt

description: This is a "README" file for the archive.
DOI: 10.6084/m9.figshare.4903784.v1
title: Data and code for MEDUC30 validation

description: <b>Introduction</b>. Although there are instruments in Spanish to evaluate teacher performance during the initial basic science training years or during medical specialization; there are few instruments for the clinical training years, in which the main role of the teacher is to facilitate experiential learning. The MEDUC30 questionnaire is a Spanish instrument developed by the xx University School of Medicine. It was built using the Stanford Faculty Development Program (SFDP) educational framework for evaluation of clinical teachers’ effectiveness by students. MEDUC30 has been used since 2004 at Xx University and was previously studied with exploratory methods. <b>Objective</b>. To provide satisfying evidence of validity and reliability to support MEDUC30’s usefulness in Spanish-speaking contexts, using confirmatory analytical methods. <b>Method</b>. This is an analytical, longitudinal and retrospective study, in which 24,681 MEDUC30 questionnaires evaluating 579 clinical teachers were analysed. They were completed by medical students from 3rd to 7th year of study, from 2004 throughout 2015. The questionnaire’s structure was studied by exploratory (EFA) and confirmatory factor analysis (CFA). Measurement invariance was evaluated with multi-group CFA. <b>Results</b>. Four different models were compared; a bi-factor model was the best alternative to explain the data’s structure. It was composed of one general and six domain-specific factors: [i] Patient-Based Teaching, [ii] Communication of Goals, [iii] Evaluation and Feedback, [iv] Promotion of Understanding, Retention and Self-directed Learning, [v] Control of the Session, and [vi] Learning Climate. The overall reliability of MEDUC30 scores was excellent (Cronbach’s α = .98, McDonald’s ω = .98) and that of the six specific factors was very good (Cronbach’s α =.88-.95, McDonald’s ω = .78-.94). Measurement invariance extended over teacher gender, date, semester, year of study, clinical teaching setting, and length of clinical rotation; all of these variables were sources of population heterogeneity. <b>Conclusions</b>. MEDUC30 is a valid and reliable Spanish instrument to evaluate clinical teachers. It can be used to provide formative feedback of general and domain-specific effectiveness to clinical teachers and to provide accurate information to department heads and program directors for resource allocation and promotion purposes, and ultimately to improve clinical teaching quality.
DOI: 10.6084/m9.figshare.4903730.v2
title: One-Step Generalized Estimating Equations With Large Cluster Sizes

description: Medical studies increasingly involve a large sample of independent clusters, where the cluster sizes are also large. Our motivating example from the 2010 Nationwide Inpatient Sample (NIS) has 8,001,068 patients and 1049 clusters, with average cluster size of 7627. Consistent parameter estimates can be obtained naively assuming independence, which are inefficient when the intra-cluster correlation (ICC) is high. Efficient generalized estimating equations (GEE) incorporate the ICC and sum all pairs of observations within a cluster when estimating the ICC. For the 2010 NIS, there are 92.6 billion pairs of observations, making summation of pairs computationally prohibitive. We propose a one-step GEE estimator that (1) matches the asymptotic efficiency of the fully iterated GEE; (2) uses a simpler formula to estimate the ICC that avoids summing over all pairs; and (3) completely avoids matrix multiplications and inversions. These three features make the proposed estimator much less computationally intensive, especially with large cluster sizes. A unique contribution of this article is that it expresses the GEE estimating equations incorporating the ICC as a simple sum of vectors and scalars.
DOI: 10.6084/m9.figshare.4903682
title: Trace Fossils from the Brioverian (Ediacaran–Fortunian) in Brittany (NW France)

description: The Ediacaran–Fortunian ichnofauna from Central Brittany (NW France) is revised for the first time since the pioneering work by Lebesconte at the end of the 19th century. The study is based on fossils from the type-localities of the historical Brioverian taxa <i>Montfortia</i> (traces from Montfort-sur-Meu) and <i>Neantia</i> (wrinkle surfaces from Néant-sur-Yvel), and on two new outcrops from Saint-Gonlay. The ichnofossil assemblage includes <i>Helminthoidichnites tenuis, Helminthopsis tenuis, Gordia marina, Palaeophycus tubularis, ?Neonereites uniserialis</i>, and <i>?Spirodesmos archimedeus</i>. Locally, the grazing traces are associated with wrinkle surfaces considered as microbially induced sedimentary structures (MISS). The sedimentological characteristics of these deposits correspond to a shelf marine environment. Both U-Pb datings on detrital zircon and ichnostratigraphic criteria tend toward an Ediacaran age of the fossiliferous deposits, but we cannot exclude the possibility of a Fortunian age at the present state of knowledge.
DOI: 10.6084/m9.figshare.4903682.v1
title: Trace Fossils from the Brioverian (Ediacaran–Fortunian) in Brittany (NW France)

description: The Ediacaran–Fortunian ichnofauna from Central Brittany (NW France) is revised for the first time since the pioneering work by Lebesconte at the end of the 19th century. The study is based on fossils from the type-localities of the historical Brioverian taxa <i>Montfortia</i> (traces from Montfort-sur-Meu) and <i>Neantia</i> (wrinkle surfaces from Néant-sur-Yvel), and on two new outcrops from Saint-Gonlay. The ichnofossil assemblage includes <i>Helminthoidichnites tenuis, Helminthopsis tenuis, Gordia marina, Palaeophycus tubularis, ?Neonereites uniserialis</i>, and <i>?Spirodesmos archimedeus</i>. Locally, the grazing traces are associated with wrinkle surfaces considered as microbially induced sedimentary structures (MISS). The sedimentological characteristics of these deposits correspond to a shelf marine environment. Both U-Pb datings on detrital zircon and ichnostratigraphic criteria tend toward an Ediacaran age of the fossiliferous deposits, but we cannot exclude the possibility of a Fortunian age at the present state of knowledge.
DOI: 10.6084/m9.figshare.4903703.v1
title: Supplementary Material for: Evacuation of a Tertiary Neonatal Centre: Lessons from the 2016 Kumamoto Earthquak

description: <i>Background:</i> Newborn infants hospitalised in the neonatal intensive care unit (NICU) are vulnerable to natural disasters. However, publications on evacuation from NICUs are sparse. The 2016 Kumamoto Earthquakes caused serious damage to Kumamoto City Hospital and its level III regional core NICU. Local/neighbour NICU teams and the disaster-communication team of a neonatal academic society cooperated to evacuate 38 newborn infants from the ward. <i>Objective:</i> The aim of this paper was to highlight potential key factors to improve emergency NICU evacuation and coordination of hospital transportation following natural disasters. <i>Methods:</i> Background variables including clinical risk scores and timing/destination of transportation were compared between infants, who subsequently were transferred to destinations outside of Kumamoto Prefecture, and their peers. <i>Results:</i> All but 1 of the infants were successfully evacuated from their NICU within 8 h. One very-low-birth-weight infant developed moderate hypothermia following transportation. Fourteen infants were transferred to NICUs outside of Kumamoto Prefecture, which was associated with the diagnosis of congenital heart disease, dependence on respiratory support, higher risk scores, and longer elapsed time from the decision to departure. There was difficulty in arranging helicopter transportation because the coordination office of the Disaster Medical Assistance Team had requisitioned most air/ground ambulances and only helped arrange ground transportations for 13 low-risk infants. Transportation for all 10 high-risk infants (risk scores greater than or equal to the upper quartile) was arranged by local/neighbour NICUs. <i>Conclusions:</i> Although the overall evacuation process was satisfactory, potential risks of relying on the adult-based emergency transportation system were highlighted. A better system needs to be developed urgently to put appropriate priority on vulnerable infants.
DOI: 10.6084/m9.figshare.4903706.v1
title: FigShareNotes.txt

description: This is a "README" file for the archive.
DOI: 10.6084/m9.figshare.4903730.v1
title: One-Step Generalized Estimating Equations with Large Cluster Sizes

description: Medical studies increasingly involve a large sample of independent clusters, where the cluster sizes are also large. Our motivating example from the 2010 Nationwide Inpatient Sample (NIS) has 8,001,068 patients and 1049 clusters, with average cluster size of 7627. Consistent parameter estimates can be obtained naively assuming independence, which are inefficient when the intra-cluster correlation (ICC) is high. Efficient generalized estimating equations (GEE) incorporate the ICC and sum all pairs of observations within a cluster when estimating the ICC. For the 2010 NIS, there are 92.6 billion pairs of observations, making summation of pairs computationally prohibitive. We propose a one-step GEE estimator that 1) matches the asymptotic efficiency of the fully-iterated GEE; 2) uses a simpler formula to estimate the ICC that avoids summing over all pairs; and 3) completely avoids matrix multiplications and inversions. These three features make the proposed estimator much less computationally intensive, especially with large cluster sizes. A unique contribution of this paper is that it expresses the GEE estimating equations incorporating the ICC as a simple sum of vectors and scalars.
DOI: 10.6084/m9.figshare.4903601
title: kerr_results_nocontrol_withpixel.csv

description: Breaking continuous flash suppression dataset with semantic word primes and word targets. Includes target word pixel data, but semantic priming control trials are excluded.<br>
DOI: 10.6084/m9.figshare.4903607
title: kerr_results_withcontrol_nopixel.csv

description: Breaking continuous flash suppression dataset with semantic word primes and word targets. Includes visible semantic priming control trials, but no target word pixel info.<br>
DOI: 10.6084/m9.figshare.4903601.v1
title: kerr_results_nocontrol_withpixel.csv

description: Breaking continuous flash suppression dataset with semantic word primes and word targets. Includes target word pixel data, but semantic priming control trials are excluded.<br>
DOI: 10.6084/m9.figshare.4903607.v1
title: kerr_results_withcontrol_nopixel.csv

description: Breaking continuous flash suppression dataset with semantic word primes and word targets. Includes visible semantic priming control trials, but no target word pixel info.<br>
DOI: 10.6084/m9.figshare.4903550
title: Data from Tolerance to herbivory and the resource availability hypothesis

description: Study data to be available
DOI: 10.6084/m9.figshare.4903541
title: SnoRNA locus and expression. from The circadian dynamics of small nucleolar RNA in the mouse liver

description: A comma separated file listing all snoRNA Ensembl ids in GRCm38, locus, id and locus of host (if any), RFAM family, and whether expressed or not.
DOI: 10.6084/m9.figshare.4903541.v1
title: SnoRNA locus and expression. from The circadian dynamics of small nucleolar RNA in the mouse liver

description: A comma separated file listing all snoRNA Ensembl ids in GRCm38, locus, id and locus of host (if any), RFAM family, and whether expressed or not.
DOI: 10.6084/m9.figshare.4903526
title: R code for nested sampling. from The circadian dynamics of small nucleolar RNA in the mouse liver

description: A tar archive of the R code for nested sampling with examples of usage.
DOI: 10.6084/m9.figshare.4903526.v1
title: R code for nested sampling. from The circadian dynamics of small nucleolar RNA in the mouse liver

description: A tar archive of the R code for nested sampling with examples of usage.
DOI: 10.6084/m9.figshare.4903511
title: SnoRNA and host gene expression. from The circadian dynamics of small nucleolar RNA in the mouse liver

description: A comma separated file listing snoRNA Ensembl ids for genes identified in Fig 2c and d, log10 ratio to host expression, mean expression, fold change (b value), p and q values from sleuth.
DOI: 10.6084/m9.figshare.4903511.v1
title: SnoRNA and host gene expression. from The circadian dynamics of small nucleolar RNA in the mouse liver

description: A comma separated file listing snoRNA Ensembl ids for genes identified in Fig 2c and d, log10 ratio to host expression, mean expression, fold change (b value), p and q values from sleuth.