Stability of the factorial structure of metabolic syndrome from childhood to adolescence : a 6-year follow-up study

Background: Metabolic syndrome (MS) is a clustering of cardiometabolic risk factors that is considered a predictor of cardiovascular disease, type 2 diabetes and mortality. There is no consistent evidence on whether the MS construct works in the same way in different populations and at different stages in life. Methods: We used confirmatory factor analysis to examine if a single-factor-model including waist circumference, triglycerides/HDL-c, insulin and mean arterial pressure underlies metabolic syndrome from the childhood to adolescence in a 6-years follow-up study in 174 Swedish and 460 Estonian children aged 9 years at baseline. Indeed, we analyze the tracking of a previously validated MS index over this 6-years period. Results: The estimates of goodness-of-fit for the single-factor-model underlying MS were acceptable both in children and adolescents. The construct stability of a new model including the differences from baseline to the end of the follow-up in the components of the proposed model displayed good fit indexes for the change, supporting the hypothesis of a single factor underlying MS component trends. Conclusions: A single-factor-model underlying MS is stable across the puberty in both Estonian and Swedish young people. The MS index tracks acceptably from childhood to adolescence.

Empirical Doppler Characterization of Signals Scattered by Wind Turbines in the UHF Band under Near Field Condition

Time variability of the scattering signals from wind turbines may lead to degradation problems on the communication systems provided in the UHF band, especially under near field condition. In order to analyze the variability due to the rotation of the blades, this paper characterizes empirical Doppler spectra obtained from real samples of signals scattered by wind turbines with rotating blades under near field condition. A new Doppler spectrum model is proposed to fit the spectral characteristics of these signals, providing notable goodness of fit. Finally, the effect of this kind of time variability on the degradation of OFDM signals is studied.

Estimacion de sexo y edad a nivel esqueletico: aplicacion forense y antropologica

[ES] La estimación del sexo y la edad son esenciales para la identificación individual de restos humanos y para el conocimiento e interpretación de la variabilidad biológica del pasado. El objetivo de este trabajo es la elaboración de un protocolo metodológico de análisis morfológico y morfométrico, para la estimación del sexo en adultos y de la edad en subadultos y adultos. Las principales metodologías incluidas en este trabajo pueden emplearse en restos esqueléticos de procedencia europea. Se realizó una revisión bibliográfica en revistas de ámbito forense y antropológico a fin de reunir un conjunto de metodologías aplicables tanto a esqueletos completos como parciales. Finalmente, en la elección de los métodos incluidos en este protocolo se tuvieron en cuenta dos criterios: la bondad de ajuste y el grado de complejidad del método.

Innovación, financiación pública y tamaño empresarial

[ES] A partir de los microdatos de la "encuesta sobre innovación tecnológica 1998-2000" se construye una base de datos con las empresas manufactureras españolas que realizan actividades de innovación. Posteriormente, mediante las pruebas Chi-cuadrado de Pearson y Mann-Whitney, contrastamos si el tamaño condiciona la participación de las empresas manufactureras innovadoras en los sistemas de ayuda pública a la innovación; asimismo, a través de los índices de Kendall y Spearman evaluamos la dirección de dicho condicionamiento. Al respecto, los contrastes realizados nos indican que la variable tamaño se encuentra relacionada con la variable financiación pública, y que son las empresas de mayor tamaño las que más se benefician de las ayudas públicas a la innovación.

Clinical factors associated with a Candida albicans Germ Tube Antibody positive test in Intensive Care Unit patients

Background: Poor outcomes of invasive candidiasis (IC) are associated with the difficulty in establishing the microbiological diagnosis at an early stage. New scores and laboratory tests have been developed in order to make an early therapeutic intervention in an attempt to reduce the high mortality associated with invasive fungal infections. Candida albicans IFA IgG has been recently commercialized for germ tube antibody detection (CAGTA). This test provides a rapid and simple diagnosis of IC (84.4% sensitivity and 94.7% specificity). The aim of this study is to identify the patients who could be benefited by the use of CAGTA test in critical care setting. Methods: A prospective, cohort, observational multicentre study was carried out in six medical/surgical Intensive care units (ICU) of tertiary-care Spanish hospitals. Candida albicans Germ Tube Antibody test was performed twice a week if predetermined risk factors were present, and serologically demonstrated candidiasis was considered if the testing serum dilution was >= 1: 160 in at least one sample and no other microbiological evidence of invasive candidiasis was found. Results: Fifty-three critically ill non-neutropenic patients (37.7% post surgery) were included. Twenty-two patients (41.5%) had CAGTA-positive results, none of them with positive blood culture for Candida. Neither corrected colonization index nor antifungal treatment had influence on CAGTA results. This finding could corroborate that the CAGTA may be an important biomarker to distinguish between colonization and infection in these patients. The presence of acute renal failure at the beginning of the study was more frequent in CAGTA-negative patients. Previous surgery was statistically more frequent in CAGTA-positive patients. Conclusions: This study identified previous surgery as the principal clinical factor associated with CAGTA-positive results and emphasises the utility of this promising technique, which was not influenced by high Candida colonization or antifungal treatment. Our results suggest that detection of CAGTA may be important for the diagnosis of invasive candidiasis in surgical patients admitted in ICU.

Judgmental-analytical procedures for adapting tests: Adaptation to Spanish of the Reasoning Tests Battery

Adapting a test between cultures or languages requires taking into account legal, linguistic, metric, and use-related considerations. Significantly more attention has been paid to the methodological aspects involved in the study of metric equivalence than to judgmental-analytical procedures prior to the empirical confirmation stage. However, considering the latter is crucial in the adaptation process. Along these lines, this paper seeks to describe and focus on the relevance of the previous stages, thereby offering a systematization process that comprises ten sections. This approach contributes to ensuring the construction of a test adapted and equivalent in as much as possible to the original. This process is exemplified by means of a Spanish language adaptation of a cognitive test originally designed in Portuguese for the Portuguese population, the Reasoning Test Battery. Copyright (C) 2013, Konrad Lorenz University Foundation. Published by Elsevier Espana, S.L.U.

Feature Selection for Speech Emotion Recognition in Spanish and Basque: On the Use of Machine Learning to Improve Human-Computer Interaction

Study of emotions in human-computer interaction is a growing research area. This paper shows an attempt to select the most significant features for emotion recognition in spoken Basque and Spanish Languages using different methods for feature selection. RekEmozio database was used as the experimental data set. Several Machine Learning paradigms were used for the emotion classification task. Experiments were executed in three phases, using different sets of features as classification variables in each phase. Moreover, feature subset selection was applied at each phase in order to seek for the most relevant feature subset. The three phases approach was selected to check the validity of the proposed approach. Achieved results show that an instance-based learning algorithm using feature subset selection techniques based on evolutionary algorithms is the best Machine Learning paradigm in automatic emotion recognition, with all different feature sets, obtaining a mean of 80,05% emotion recognition rate in Basque and a 74,82% in Spanish. In order to check the goodness of the proposed process, a greedy searching approach (FSS-Forward) has been applied and a comparison between them is provided. Based on achieved results, a set of most relevant non-speaker dependent features is proposed for both languages and new perspectives are suggested.