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Retrospective data from 147 selected patients that underwent strabismus surgery between 2013-2016. Includes information concerning the type and onset of the strabismus, relevant medical records, awake state eye deviation and the intraoperative strabismus inspection.

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Datos primarios asociados al artículo enviado a Journal of Personality Assessment, Since the publication of the Alternative Model on Personality Disders in Section III DSM-5, literature has widely focused on providing validity evidence for the 25 facets defined in Criterion B. More recently, scientific attention has shifted towards Criterion A, with a considerable set of mixed results both supporting and disagreeing the operational definition of the model. The present study aims to provide additional evidence on the structural and relational differentiation of self and interpersonal dimensions of personality functioning using a quick screener, the Level of Personality Functioning Scale – Brief Form 2.0 (LPFS-BF 2.0), in a community and clinical mixed sample. 1074 participants (717 community adults and 357 patients) completed the LPFS-BF 2.0, the Personality Inventory for DSM-5 Short Form and the Questionnaire for the World Health Organization Disability Assessment. The internal structure of LPFS 2.0 was assessed through a series of Confirmatory Factor Analyses and bifactor modeling was applied to assess the dimensionality. Exploratory Structural Equation Modelling was used to explore the joint structure of functioning and maladaptive traits. Multiple linear regressions, controlling for age and sex, were employed to evaluate the predictive validity of LPFS scales in explaining functional impairment. Our results clearly support a two-factor structure of criterion A (self and interpersonal functioning) when measured with LPFS-BF 2.0. Results also displayed clear differences between the personality functioning factors, with the self-functioning factor more closely linked to facets of the negative affect domains and the interpersonal-functioning factor linked to several antagonistic personality traits. Moreover, our results suggested a relevant role of self-functioning in the explanation of the functional impairment along and beyond personality facets. These results lead to consider the LPFS-BF 2.0 a useful tool for clinical routine monitoring self and interpersonal personality functioning., This work was supported by the grant “Network-Psyco: Modelización a través de redes empíricas de las conexiones entre facetas y rasgos psicológicos”, project UHU-1257470 on Programa Operativo FEDER Andalucía 2014-2020, provided by Fondo Europeo de Desarrollo Regional (EU) and by Ministry of Universities of the Government of Spain (PRX21/00319).

Datos primarios asociados al artículo enviado a Health and Quality of Life Outcomes, Trabajo financiado con el proyecto de Investigación PID2020-116187RB-I00: "CAMBIO FIABLE Y CLINICAMENTE RELEVANTE DEL INVENTORY OF DEPRESSION AND ANXIETY SYMPTOMS II (IDAS-II: UN ESTUDIO LONGITUDINAL SOBRE SU UTILIDAD CLINICA" de la Convocatoria Retos 2020 del Ministerio de Ciencia e Innovación.

Computational 3D models of human atria and torso with encoded anatomical and functional heterogeneity. The finite element model of the atria is a multi-layer mesh with a homogeneous wall thickness between 600 and 900 μm (754.893 nodes and 515.010 elements), built with linear hexahedral elements and with regular spatial resolution of 300 µm. The model consists of: 21 regions with 53 sub-divisions representing the detailed description of fibre orientation; electrophysiological heterogeneity represented by 8 cellular models with differences in the action potential properties; and conduction velocities and anisotropy ratios tuned to each atrial region. The torso was modelled using a dataset obtained from the online open repository at the Centre for Integrative Biomedical Computing (CBIC) from University of Utah. The torso model has 190.804 nodes and 1.149.531 tetrahedral elements with a spatial resolution of 0.6 mm. It has 6 different regions: lungs, bones, liver, ventricle, blood pools, and flesh.

This repository contains four Excel 2017 files named “APD.xlsx”, “QT.xlsx”, “Tx_APD.xlsx” and “Tx_QT.xlsx”. APD.xlsx and Tx_APD.xlsx files contain three sheets (called “Epi”, “Mid” and “Endo”), whereas the rest contain only one sheet (called “QT”). These files contain the results of simulations performed in the O’Hara-Rudy model (ORd) [1] of human ventricular cells (206.766 simulations) and tissue (7072 simulations), which consist of APD90 and QT intervals as well as a new index called Tx extracted from both APD and QT values. References: [1]. O’Hara, T.; Virág, L.; Varró, A.; Rudy, Y. Simulation of the Undiseased Human Cardiac Ventricular Action Potential: Model Formulation and Experimental Validation. PLoS Comput. Biol. 2011, 7 (5), e1002061. [2]. Romero L., Cano J., Gomis-Tena J., Trenor B., Sanz F., Pastor M., Saiz J. In silico QT and APD Prolongation Assay for Early Screening of Drug-Induced Proarrhythmic Risk. Journal of Chemical Information and Modeling. 2017 (Currently in revision).

Twitter dataset for a research on the 2015 Spanish General Election. The tweets were obtained through the Twitter API's Search function since November 2 to December 21, 2015. Three criteria for filtering tweets were established: two general terms linked to the elections ("#20D", "20-D"); the name and usernames of the four main parties (PP, PSOE, Podemos and Ciudadanos), and the name and usernames of the four candidates from those parties. The research assessed the tweet's issue according to Patterson (1980)'s typology for evaluating political mediatisation. The dataset contains three files: the unlabelled collection of the 15.8 million tweet ids obtained through the API, the annotated sample of the 3,117 tweet ids for assessing the issue via machine learning, and the readme.txt file. It is recommended to open the file from a text editor or through a script. The id_str must be handled as a string. If the file is open from Excel, the id_str will be interpreted as a number, and then converted into a float, losing information in this transformation

This repository contains the Matlab functions used in [1] and six Excel files named “Tx matrix KrKsCaL.xlsx”, “Tx matix KrNaLCaL.xlsx”, “TqNet matrix KrKsCaL.xlsx”, “TqNet matrix KrNaLCaL.xlsx”, "Ttirang matrix KrKsCaL.xlsx" and “Ttirang matrix KrNaLCaL.xlsx”. These files contain the value of three arrhythmogenic indices proposed in [1] (Tx, TqNet and Ttriang) resulting from simulations of drug effects on the action potential. The simulations were performed in a modified version of the O’Hara-Rudy model (ORd) [2] of human endocardial ventricular cells (492.536 simulations). References: [1]. Llopis J., Gomis-Tena J., Cano J., Romero L., Saiz J., Trenor B. In-Silico Classifiers for Assessment of Drug Proarrhythmicity. 2020 (Currently under revision) [2]. O’Hara, T.; Virág, L.; Varró, A.; Rudy, Y. Simulation of the Undiseased Human Cardiac Ventricular Action Potential: Model Formulation and Experimental Validation. PLoS Comput. Biol. 2011, 7 (5), e1002061., The authors would like to strongly thank Dr. Manuel Pastor from Research Programme on Biomedical Informatics (GRIB), at Universitat Pompeu Fabra (Barcelona, Spain) for its review of the manuscript and expert opinions and suggestions. This work was partially supported by the Dirección general de Política Científica de la Generalitat Valencia (PROMETEU2016/088), Primeros Proyectos de Investigación (PAID-06-18), Vicerrectorado de Investigación, Innovación y Transferencia de la Universitat Politècnica de València (UPV), València, Spain as well as Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016 from the Ministerio de Economía, Industria y Competitividad of Spain (DPI2016-75799-R) and AEI/FEDER, UE. JL is being funded by the Ministerio de Ciencia, Innovación y Universidades for the Formación de Profesorado Universitario (grant reference: FPU18/01659).

Material complementario con datos brutos utilizados en artículo aceptado para su publicación en la Revista Española de Documentación Científica. Se incluye la taxonomía de consultas realizada, las combinaciones de palabras clave y consultas efectuadas, los resultados de posicionamiento de universidades públicas valencianas en Google (top 20) así como la clasificación temática del primer sitio web posicionado de cada universidad para cada consulta.

[EN] The data were used to analyse the correlation between some aspects of the library of the Universitat Politècnica de València (UPV) and the research outputs of the UPV. There are two kinds of data: on the one hand, data of the library of the UPV that was mainly obtained from the statistical data published annually by REBIUN. On the other hand, data of research outputs of the UPV that were obtained by consulting different bibliographic databases such as SCOPUS. Several variables of each kind of data were selected and a correlation analysis was made between different variables of each group.