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El texto completo de este trabajo no se encuentra disponible por no haber sido facilitado aún por su autor, por restricciones de copyright, o por no existir una versión digital, This paper tackles a problem of surface wind speed reconstruction based on synoptic-scale meteorological fields. Specifically, two different approaches are discussed and compared: a pure Machine Learning method, formed by a Support Vector Regression and a genetic algorithm that only considers synoptic pressure as input variable, and a Weather Regimes Classification Technique, based on a k-means clustering of the main three principal components of the geopotential height field and a simple, but efficient, linear regression between the surface pressure gradient and the observed surface wind. Both algorithms are shown to be accurate enough for wind speed reconstruction at medium latitude regions, even when there are only a few years of observations. These methodologies can also be used for filling gaps in wind speed series and, with some modifications and further research, they could be used for wind speed forecasting. The algorithms proposed are fully described and compared in this paper, and their performance has been comparatively evaluated in several real problems of wind speed reconstruction at three sites (Cabauw (The Netherlands), Capel (Wales, UK) and Kaegnes (Denmark)), obtaining excellent results in terms of wind speed reconstruction with moderate complexity in data processing and algorithms. Copyright (c) 2014 John Wiley & Sons, Ltd., Ministerio de Ciencia e Innovación (España), Solute Ingenieros, through the Project "Desarrollo de nuevos sistemas de caracterizacon del recurso colico, evaluacion de emplazamientos especificos y prediccion de viento: ETSWIND", Depto. de Física de la Tierra y Astrofísica, Fac. de Ciencias Físicas, TRUE, pub

Sarcopenia, the age-related decline in muscle mass and strength, poses diagnostic challenges due to limited, costly, and specialized evaluation methods. This study suggests using surface electromyography (sEMG) as a diagnostic tool. This research aims to evaluate the performance of the core shape modelling, a novel biomarker obtained from the sEMG signal for sarcopenia assessment. The study involved nine sarcopenic and eleven healthy individuals performing consecutive thirty-second sit-to-stand movements while a bipolar sEMG signal was recorded from the rectus femoris and biceps femoris muscles. Traditional sEMG parameters (root mean square and mean frequency) and core shape modelling features were analyzed. The statistical comparison revealed no significant differences in conventional parameters between groups for either muscle. However, the core shape modelling approach displayed significant distinctions, particularly in left shape distance (rectus femoris) and right shape distance (biceps femoris) between sarcopenic and control subjects. These findings suggest that the proposed biomarker holds promise in improving sarcopenia diagnosis.

La terapia farmacológica tiene un gran potencial para el tratamiento de la fibrilación auricular paroxística (pAF); aunque su eficacia es dependiente de las características de cada paciente. Este estudio busca analizar qué perfiles iónicos y mecanismos electrofisiológicos modulan la efectividad de dos fármacos antiarrítmicos (flecainida y vernakalant) contra los episodios fibrilatorios. En los modelos auriculares paroxísticos de aurícula izquierda 2D, los bloqueos GK1, GNaK, Gto y GK,ACh son importantes para reducir la iniciación y el mantenimiento de la AF a través del aumento de la duración del potencial y la refractariedad junto con la reducción de la frecuencia dominante del rotor (DF). Cuando se parte de pAFs con DFs bajos, los medicamentos flecainida y vernakalant tienen una mayor eficacia. Las características de las corrientes iónicas influyen en la iniciación, el mantenimiento y la respuesta de la AF al tratamiento farmacológico.

West Nile virus (WNV) is a neurotropic flavivirus transmitted by the bites of infected mosquitoes. Severe forms of West Nile disease (WND) can curse with meningitis, encephalitis, or acute flaccid paralysis. A better understanding of the physiopathology associated with disease progression is mandatory to find biomarkers and effective therapies. In this scenario, blood derivatives (plasma and serum) constitute the more commonly used biofluids due to their ease of collection and high value for diagnostic purposes. Therefore, the potential impact of this virus in the circulating lipidome was addressed by combining the analysis of samples from experimentally infected mice and naturally WND patients. Our results unveil dynamic alterations in the lipidome that define specific metabolic fingerprints of different infection stages. Concomitant with neuroinvasion in mice, the lipid landscape was dominated by a metabolic reprogramming that resulted in significant elevations of circulating sphingolipids (ceramides, dihydroceramides and dihydrosphingomyelins), along with some phosphatidylethanolamines and triacylglycerols. Remarkably, patients suffering from WND also displayed an elevation of ceramides, dihydroceramides, and lactosylceramides in their sera. The dysregulation of sphingolipid metabolism by WNV may provide new therapeutic opportunities and supports the potential of certain lipids as novel peripheral biomarkers of WND progression.

Atrial fibrillation (AF) is the most frequently encountered arrhythmia in clinical practise. One of the major problems in the management of AF is the difficulty in identifying the arrhythmia sources from clinical recordings. That difficulty occurs because it is currently impossible to verify algorithms which determine these sources in clinical data, as high resolution true excitation patterns cannot be recorded in patients. Therefore, alternative approaches, like computer modelling are of great interest. In a recent published study such an approach was applied for the verification of one of the most commonly used algorithms, phase mapping (PM). A meandering rotor was simulated in the right atrium and a basket catheter was placed at 3 different locations: at the Superior Vena Cava (SVC), the Crista Terminalis (CT) and at the Coronary Sinus (CS). It was shown that although PM can identify the true source, it also finds several false sources due to the far-field effects and interpolation errors in all three positions. In addition, the detection efficiency strongly depended on the basket location. Recently, a novel tool was developed to analyse any arrhythmia called Directed Graph Mapping (DGM). DGM is based on network theory and creates a directed graph of the excitation pattern, from which the location and the source of the arrhythmia can be detected. Therefore, the objective of the current study was to compare the efficiency of DGM with PM on the basket dataset of this meandering rotor. The DGM-tool was applied for a wide variety of conduction velocities (minimal and maximal), which are input parameters of DGM. Overall we found that DGM was able to distinguish between the true rotor and false rotors for both the SVC and CT basket positions. For example, for the SVC position with a [Formula presented], DGM detected the true core with a prevalence of 82% versus 94% for PM. Three false rotors where detected for 39.16% (DGM) versus 100% (PM); 22.64% (DGM) versus 100% (PM