907 resultados para General Linear Methods


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Theoretical models predict lognormal species abundance distributions (SADs) in stable and productive environments, with log-series SADs in less stable, dispersal driven communities. We studied patterns of relative species abundances of perennial vascular plants in global dryland communities to: (i) assess the influence of climatic and soil characteristics on the observed SADs, (ii) infer how environmental variability influences relative abundances, and (iii) evaluate how colonisation dynamics and environmental filters shape abundance distributions. We fitted lognormal and log-series SADs to 91 sites containing at least 15 species of perennial vascular plants. The dependence of species relative abundances on soil and climate variables was assessed using general linear models. Irrespective of habitat type and latitude, the majority of the SADs (70.3%) were best described by a lognormal distribution. Lognormal SADs were associated with low annual precipitation, higher aridity, high soil carbon content, and higher variability of climate variables and soil nitrate. Our results do not corroborate models predicting the prevalence of log-series SADs in dryland communities. As lognormal SADs were particularly associated with sites with drier conditions and a higher environmental variability, we reject models linking lognormality to environmental stability and high productivity conditions. Instead our results point to the prevalence of lognormal SADs in heterogeneous environments, allowing for more evenly distributed plant communities, or in stressful ecosystems, which are generally shaped by strong habitat filters and limited colonisation. This suggests that drylands may be resilient to environmental changes because the many species with intermediate relative abundances could take over ecosystem functioning if the environment becomes suboptimal for dominant species.

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The purpose of this study was to assess the effect of maternal pre-pregnancy weight status on the relationship between prenatal smoking and infant birth weight (IBW). Prenatal cigarette smoking and maternal weight exert opposing effects on IBW; smoking decreases birth weight while maternal pre-pregnancy weight is positively correlated with birth weight. As such, mutual effect modification may be sufficiently significant to alter the independent effects of these two birth weight correlates. Finding of such an effect has implications of prenatal smoking cessation education. Perception of risk is an important determinant of smoking cessation, and reduced or low birth weight (LBW) as a smoking-associated risk predominates prenatal smoking counseling and education. In a population such as the US, where obesity is becoming epidemic, particularly among minority and low-income groups, perception of risk may be lowered should increased maternal size attenuate the effect of smoking. Previous studies have not found a significant interaction effect of prenatal smoking and maternal pre-pregnancy weight on IBW; however, use of self-reported smoking status may have biased findings. Reliability of self-reported smoking status reported in the literature is variable, with deception rates ranging from a low of 5% to as high as 16%. This study, using data from a prenatal smoking cessation project, in which smoking status was validated by saliva cotinine, was an opportunity to assess effect modification of smoking and maternal weight using biochemically determined smoking status in lieu of self report. Stratified by saliva cotinine, 151 women from a prenatal smoking cessation cohort, who were 18 years and older and had full-term, singleton births, were included in this study. The effect of smoking in terms of mean birth weight across three levels of maternal pre-pregnancy weight was assessed by general linear modeling procedures, adjusting for other known correlates of IBW. Effect modification was marginally significant, p = .104, but only with control for differential effects among racial/ethnic groups. A smaller than planned sample of nonsmokers, or women who quit smoking during the pregnancy, prohibited rejection of the null hypothesis of no difference in the effect of smoking across levels of pre-pregnancy weight. ^

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Purpose: To examine the effect of obesity and gestational weight gain on heart rate variability (HRV), oxygenation (HbO 2 and SpO2), hemoglobin A1c (HbA1c) and the frequency of pregnancy complications in obese (O) and non-obese (NO) women.^ Design: The study was an observational comparison study with a repeated measures design. ^ Setting: The setting was a low risk prenatal, university clinic located in a large southeastern metropolitan city. ^ Sample: The sample consisted of a volunteer group of 41 pregnant women who were observed at the three time points of 20, 28, and 36 weeks gestation. ^ Analysis: Analysis included general linear modeling with repeated measures to test for group differences with changes over time on vagal response, HbA1c, and oxygenation. Odds ratios were computed to compare the frequency of birth outcomes. ^ Findings: The interaction effect of time between O and NO women on HbO2 was significant. The mean HP, RSA, and HbO2 changed significantly over time within the NO women. The mean HbA 1c increased significantly over time within the O women. Women with excess gestational weight gain had significantly lower heart period than women with weight gain within the IOM recommendations. Obese women were more likely to have Group B streptococcal infections, gestational hypertension, give birth by cesarean or instrument assistance, and have at least one postnatal event. ^ Conclusions: Monitoring HRV, oxygenation, and HbA1c using minimally invasive measures may permit early identification of alterations in autonomic response. Implementation of interventions to promote vagal tone may help to reduce risks for adverse perinatal outcomes related to obesity. Future studies should examine the effect of obesity on the vagal response and perinatal outcomes. ^

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The infant mortality rate (IMR) is considered to be one of the most important indices of a country's well-being. Countries around the world and other health organizations like the World Health Organization are dedicating their resources, knowledge and energy to reduce the infant mortality rates. The well-known Millennium Development Goal 4 (MDG 4), whose aim is to archive a two thirds reduction of the under-five mortality rate between 1990 and 2015, is an example of the commitment. ^ In this study our goal is to model the trends of IMR between the 1950s to 2010s for selected countries. We would like to know how the IMR is changing overtime and how it differs across countries. ^ IMR data collected over time forms a time series. The repeated observations of IMR time series are not statistically independent. So in modeling the trend of IMR, it is necessary to account for these correlations. We proposed to use the generalized least squares method in general linear models setting to deal with the variance-covariance structure in our model. In order to estimate the variance-covariance matrix, we referred to the time-series models, especially the autoregressive and moving average models. Furthermore, we will compared results from general linear model with correlation structure to that from ordinary least squares method without taking into account the correlation structure to check how significantly the estimates change.^

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La mosca blanca del fresno, Siphoninus phillyreae (Haliday) , es una especie polífaga invasiva que causa graves daños en sus hospedadores, entre ellos el olivo (Olea europaea L.). El uso del hospedador por parte de S. phillyreae fue observado en tres cultivares de olivo (Arauco, Arbequina y Aloreña) en el norte de la provincia de La Rioja (Argentina) durante 2007 y 2008. De cada cultivar se muestrearon seis plantas infestadas y de cada planta se tomaron ocho hojas. De cada hoja se registró la abundancia de adultos y estados inmaduros de la mosca blanca que fueron comparadas entre los cultivares mediante modelos lineales generales y mixtos. Los resultados obtenidos mostraron diferencias significativas entre las densidades de adultos y ninfas de S. phillyreae en los distintos cultivares de olivo analizados. Dichos resultados indican que este insecto realiza un uso diferente de los cultivares de olivo, siendo Arauco y Arbequina las variedades hospedadoras más utilizadas en la zona de estudio.

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The analysis of the interdependence between time series has become an important field of research in the last years, mainly as a result of advances in the characterization of dynamical systems from the signals they produce, the introduction of concepts such as generalized and phase synchronization and the application of information theory to time series analysis. In neurophysiology, different analytical tools stemming from these concepts have added to the ‘traditional’ set of linear methods, which includes the cross-correlation and the coherency function in the time and frequency domain, respectively, or more elaborated tools such as Granger Causality. This increase in the number of approaches to tackle the existence of functional (FC) or effective connectivity (EC) between two (or among many) neural networks, along with the mathematical complexity of the corresponding time series analysis tools, makes it desirable to arrange them into a unified-easy-to-use software package. The goal is to allow neuroscientists, neurophysiologists and researchers from related fields to easily access and make use of these analysis methods from a single integrated toolbox. Here we present HERMES (http://hermes.ctb.upm.es), a toolbox for the Matlab® environment (The Mathworks, Inc), which is designed to study functional and effective brain connectivity from neurophysiological data such as multivariate EEG and/or MEG records. It includes also visualization tools and statistical methods to address the problem of multiple comparisons. We believe that this toolbox will be very helpful to all the researchers working in the emerging field of brain connectivity analysis.

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Existe un creciente interés internacional por el ahorro energético y la sostenibilidad en la edificación con importantes repercusiones en la Arquitectura. La inercia térmica es un parámetro fundamental para poder valorar energéticamente un edificio en condiciones reales. Para ello es necesario cambiar el enfoque tradicional de transmisión de calor en régimen estacionario por otro en régimen dinámico en el que se analizan las ondas térmicas y el flujo de calor oscilante que atraviesan los cerramientos. Los parámetros que definen la inercia térmica son: el espesor, la difusividad y el ciclo térmico. A su vez la difusividad está determinada por la conductividad térmica, la densidad y el calor específico del material. De estos parámetros la conductividad es el más complejo, variable y difícil de medir, especialmente en los cerramientos de tierra debido a su heterogeneidad y complejidad higrotérmica. En general, los métodos de medida de la conductividad o transmitancias en los paramentos presentan inconvenientes a la hora de medir un edificio construido con tierra: dificultades de implementación, el elevado coste o la fiabilidad de los resultados, principalmente. El Método de la Aguja Térmica (MAT) se basa en el principio de la evolución en el tiempo del calor emitido por una fuente lineal al insertarse en el seno de un material. Se ha escogido este método porque resulta práctico, de bajo coste y de fácil aplicación a gran escala pero tiene serios problemas de fiabilidad y exactitud. En esta tesis se desarrolla un método de medida de la conductividad térmica para Piezas de Albañilería de Tierra Cruda en laboratorio basado en el MAT, se mejora su fiabilidad, se analiza su incertidumbre, se compara con otros métodos de referencia y se aplica en adobes, Bloques de Tierra Comprimida y probetas de tierra estabilizada con distintas proporciones de paja. Este método servirá de base a una posterior aplicación in situ. Finalmente se proponen modelos matemáticos para mejorar la exactitud del dispositivo utilizado y para la estimación de la conductividad de cerramientos de tierra en función de su densidad. Con los resultados obtenidos se analizan las posibilidades de amortiguación y retardo de las ondas térmicas y capacidad de almacenaje de energía de los cerramientos en función de su densidad y humedad. There is growing international interest in energy saving and sustainability in buildings with significant impact on Architecture. Thermal inertia is a key parameter to assess energy in buildings in real conditions. This requires changing the traditional approach to heat transfer in steady state by another in dynamic regime which analyzes the thermal waves and oscillating heat flux passing through the external walls. The parameters defining the thermal inertia are: the thickness, the diffusivity and the thermal cycle. In turn, the diffusivity is determined by the thermal conductivity, density and specific heat of the material. Of these parameters, thermal conductivity is the most complex, variable and difficult to measure, especially in earth walls due to their heterogeneity and hygrothermal complexity. In general, the methods of measurement of conductivity and transmittance in walls have drawbacks when measuring a building with earth: implementation difficulties, high cost, or reliability of the results, mainly. The Thermal Needle Procedure (TNP) is based on the principle of evolution in time of heat from a line source when inserted within a material. This method was chosen because it is a practical, low cost and easy to implement on a large scale but has serious problems of reliability and accuracy. This thesis develops a laboratory method for measuring the thermal conductivity of Masonry Units Unfire Earth-based based on TNP, its uncertainty is analyzed, compared to other reference methods and applies in adobes, Compressed Earth Blocks and stabilized soil specimens with different proportions of straw. This method will form the basis of a subsequent application in situ. Finally, mathematical models are proposed to improve the accuracy of the device used, and to estimate the conductivity of earth enclosures depending on its density. With the results obtained earth enclosures are analyzed to estimate their possibilities of delay and buffer of termal waves and energy storage capacity according to their density and moisture.

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The analysis of the interdependence between time series has become an important field of research in the last years, mainly as a result of advances in the characterization of dynamical systems from the signals they produce, the introduction of concepts such as generalized and phase synchronization and the application of information theory to time series analysis. In neurophysiology, different analytical tools stemming from these concepts have added to the ?traditional? set of linear methods, which includes the cross-correlation and the coherency function in the time and frequency domain, respectively, or more elaborated tools such as Granger Causality. This increase in the number of approaches to tackle the existence of functional (FC) or effective connectivity (EC) between two (or among many) neural networks, along with the mathematical complexity of the corresponding time series analysis tools, makes it desirable to arrange them into a unified, easy-to-use software package. The goal is to allow neuroscientists, neurophysiologists and researchers from related fields to easily access and make use of these analysis methods from a single integrated toolbox. Here we present HERMES (http://hermes.ctb.upm.es), a toolbox for the Matlab® environment (The Mathworks, Inc), which is designed to study functional and effective brain connectivity from neurophysiological data such as multivariate EEG and/or MEG records. It includes also visualization tools and statistical methods to address the problem of multiple comparisons. We believe that this toolbox will be very helpful to all the researchers working in the emerging field of brain connectivity analysis.

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La Ingeniería del Software Empírico (ISE) utiliza como herramientas los estudios empíricos para conseguir evidencias que ayuden a conocer bajo qué circunstancias es mejor usar una tecnología software en lugar de otra. La investigación en la que se enmarca este TFM explora si las intuiciones y/o preferencias de las personas que realizan las pruebas de software, son capaces de predecir la efectividad de tres técnicas de evaluación de código: lectura por abstracciones sucesivas, cobertura de decisión y partición en clases de equivalencia. Para conseguir dicho objetivo, se analizan los datos recogidos en un estudio empírico, realizado por las tutoras de este TFM. En el estudio empírico distintos sujetos aplican las tres técnicas de evaluación de código a tres programas distintos, a los que se les habían introducido una serie de faltas artificialmente. Los sujetos deben reportar los fallos encontrados en los programas, así como, contestar a una serie de preguntas sobre sus intuiciones y preferencias. A la hora de analizar los datos del estudio, se ha comprobado: 1) cuáles son sus intuiciones y preferencias (mediante el test estadístico X2 de Pearson); 2) si los sujetos cambian de opinión después de aplicar las técnicas (para ello se ha utilizado índice de Kappa, el Test de McNemar-Bowker y el Test de Stuart-Maxwell); 3) la consistencia de las distintas preguntas (mediante el índice de Kappa), comparando: intuiciones con intuiciones, preferencias con preferencias e intuiciones con preferencias; 4) Por último, si hay coincidencia entre las intuiciones y preferencias con la efectividad real obtenida (para ello se ha utilizado, el Modelo Lineal General con medidas repetidas). Los resultados muestran que, no hay una intuición clara ni tampoco una preferencia concreta, con respecto a los programas. Además aunque existen cambios de opinión después de aplicar las técnicas, no se encuentran evidencias claras para afirmar que la intuición y preferencias influyen en su efectividad. Finalmente, existen relaciones entre las intuiciones con intuiciones, preferencias con preferencias e intuiciones con preferencias, además esta relación es más notoria después de aplicar las técnicas. ----ABSTRACT----Empirical Software Engineering (ESE) uses empirical studies as a mean to generate evidences to help determine under what circumstances it is convenient to use a given software technology. This Master Thesis is part of a research that explores whether intuitions and/or preferences of testers, can be used to predict the effectiveness of three code evaluation techniques: reading by stepwise abstractions, decision coverage and equivalence partitioning. To achieve this goal, this Master Thesis analyzes the data collected in an empirical study run by the tutors. In the empirical study, different subjects apply three code evaluation techniques to three different programs. A series of faults were artificially introduced to the programs. Subjects are required to report the defects found in the programs, as well as answer a series of questions about their intuitions and preferences. The data analyses test: 1) what are the intuitions and preferences of the subjects (using the Pearson X2 test); 2) whether subjects change their minds after applying the techniques (using the Kappa coefficient, McNemar-Bowker test, and Stuart-Maxwell test); 3) the consistency of the different questions, comparing: intuitions versus intuitions, preferences versus preferences and preferences versus intuitions (using the Kappa coefficient); 4) finally, if intuitions and/or preferences predict the actual effectiveness obtained (using the General Linear Model, repeated measures). The results show that there is not clear intuition or particular preference with respect to the programs. Moreover, although there are changes of mind after applying the techniques, there are not clear evidences to claim that intuition and preferences influence their effectiveness. Finally, there is a relationship between the intuitions versus intuitions, preferences versus preferences and intuitions versus preferences; this relationship is more noticeable after applying the techniques.

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El MC en baloncesto es aquel fenómeno relacionado con el juego que presenta unas características particulares determinadas por la idiosincrasia de un equipo y puede afectar a los protagonistas y por ende al devenir del juego. En la presente Tesis se ha estudiado la incidencia del MC en Liga A.C.B. de baloncesto y para su desarrollo en profundidad se ha planteado dos investigaciones una cuantitativa y otra cualitativa cuya metodología se detalla a continuación: La investigación cuantitativa se ha basado en la técnica de estudio del “Performance analysis”, para ello se han estudiado cuatro temporadas de la Liga A.C.B. (del 2007/08 al 2010/11), tal y como refleja en la bibliografía consultada se han tomado como momentos críticos del juego a los últimos cinco minutos de partidos donde la diferencia de puntos fue de seis puntos y todos los Tiempos Extras disputados, de tal manera que se han estudiado 197 momentos críticos. La contextualización del estudio se ha hecho en función de la variables situacionales “game location” (local o visitante), “team quality” (mejores o peores clasificados) y “competition” (fases de LR y Playoff). Para la interpretación de los resultados se han realizado los siguientes análisis descriptivos: 1) Análisis Discriminante, 2) Regresión Lineal Múltiple; y 3) Análisis del Modelo Lineal General Multivariante. La investigación cualitativa se ha basado en la técnica de investigación de la entrevista semiestructurada. Se entrevistaron a 12 entrenadores que militaban en la Liga A.C.B. durante la temporada 2011/12, cuyo objetivo ha sido conocer el punto de vista que tiene el entrenador sobre el concepto del MC y que de esta forma pudiera dar un enfoque más práctico basado en su conocimiento y experiencia acerca de cómo actuar ante el MC en el baloncesto. Los resultados de ambas investigaciones coinciden en señalar la importancia del MC sobre el resultado final del juego. De igual forma, el concepto en sí entraña una gran complejidad por lo que se considera fundamental la visión científica de la observación del juego y la percepción subjetiva que presenta el entrenador ante el fenómeno, para la cual los aspectos psicológicos de sus protagonistas (jugadores y entrenadores) son determinantes. ABSTRACT The Critical Moment (CM) in basketball is a related phenomenon with the game that has particular features determined by the idiosyncrasies of a team and can affect the players and therefore the future of the game. In this Thesis we have studied the impact of CM in the A.C.B. League and from a profound development two investigations have been raised, quantitative and qualitative whose methodology is as follows: The quantitative research is based on the technique of study "Performance analysis", for this we have studied four seasons in the A.C.B. League (2007/08 to 2010/11), and as reflected in the literature the Critical Moments of the games were taken from the last five minutes of games where the point spread was six points and all overtimes disputed, such that 197 critical moments have been studied. The contextualization of the study has been based on the situational variables "game location" (home or away), "team quality" (better or lower classified) and "competition" (LR and Playoff phases). For the interpretation of the results the following descriptive analyzes were performed: 1) Discriminant Analysis, 2) Multiple Linear Regression Analysis; and 3) Analysis of Multivariate General Linear Model. Qualitative research is based on the technique of investigation of a semi-structured interview. 12 coaches who belonged to the A.C.B. League were interviewed in seasons 2011/12, which aimed to determine the point of view that the coach has on the CM concept and thus could give a more practical approach based on their knowledge and experience about how to deal with the CM in basketball. The results of both studies agree on the importance of the CM on the final outcome of the game. Similarly, the concept itself is highly complex so the scientific view of the observation of the game is considered essential as well as the subjective perception the coach presents before the phenomenon, for which the psychological aspects of their characters (players and coaches) are crucial.

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Two experiments were conducted to estimate the standardized ileal digestible (SID) Trp:Lys ratio requirement for growth performance of nursery pigs. Experimental diets were formulated to ensure that lysine was the second limiting AA throughout the experiments. In Exp. 1 (6 to 10 kg BW), 255 nursery pigs (PIC 327 × 1050, initially 6.3 ± 0.15 kg, mean ± SD) arranged in pens of 6 or 7 pigs were blocked by pen weight and assigned to experimental diets (7 pens/diet) consisting of SID Trp:Lys ratios of 14.7%, 16.5%, 18.4%, 20.3%, 22.1%, and 24.0% for 14 d with 1.30% SID Lys. In Exp. 2 (11 to 20 kg BW), 1,088 pigs (PIC 337 × 1050, initially 11.2 kg ± 1.35 BW, mean ± SD) arranged in pens of 24 to 27 pigs were blocked by average pig weight and assigned to experimental diets (6 pens/diet) consisting of SID Trp:Lys ratios of 14.5%, 16.5%, 18.0%, 19.5%, 21.0%, 22.5%, and 24.5% for 21 d with 30% dried distillers grains with solubles and 0.97% SID Lys. Each experiment was analyzed using general linear mixed models with heterogeneous residual variances. Competing heteroskedastic models included broken-line linear (BLL), broken-line quadratic (BLQ), and quadratic polynomial (QP). For each response, the best-fitting model was selected using Bayesian information criterion. In Exp. 1 (6 to 10 kg BW), increasing SID Trp:Lys ratio linearly increased (P < 0.05) ADG and G:F. For ADG, the best-fitting model was a QP in which the maximum ADG was estimated at 23.9% (95% confidence interval [CI]: [<14.7%, >24.0%]) SID Trp:Lys ratio. For G:F, the best-fitting model was a BLL in which the maximum G:F was estimated at 20.4% (95% CI: [14.3%, 26.5%]) SID Trp:Lys. In Exp. 2 (11 to 20 kg BW), increasing SID Trp:Lys ratio increased (P < 0.05) ADG and G:F in a quadratic manner. For ADG, the best-fitting model was a QP in which the maximum ADG was estimated at 21.2% (95% CI: [20.5%, 21.9%]) SID Trp:Lys. For G:F, BLL and BLQ models had comparable fit and estimated SID Trp:Lys requirements at 16.6% (95% CI: [16.0%, 17.3%]) and 17.1% (95% CI: [16.6%, 17.7%]), respectively. In conclusion, the estimated SID Trp:Lys requirement in Exp. 1 ranged from 20.4% for maximum G:F to 23.9% for maximum ADG, whereas in Exp. 2 it ranged from 16.6% for maximum G:F to 21.2% for maximum ADG. These results suggest that standard NRC (2012) recommendations may underestimate the SID Trp:Lys requirement for nursery pigs from 11 to 20 kg BW.

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Sin duda, el rostro humano ofrece mucha más información de la que pensamos. La cara transmite sin nuestro consentimiento señales no verbales, a partir de las interacciones faciales, que dejan al descubierto nuestro estado afectivo, actividad cognitiva, personalidad y enfermedades. Estudios recientes [OFT14, TODMS15] demuestran que muchas de nuestras decisiones sociales e interpersonales derivan de un previo análisis facial de la cara que nos permite establecer si esa persona es confiable, trabajadora, inteligente, etc. Esta interpretación, propensa a errores, deriva de la capacidad innata de los seres humanas de encontrar estas señales e interpretarlas. Esta capacidad es motivo de estudio, con un especial interés en desarrollar métodos que tengan la habilidad de calcular de manera automática estas señales o atributos asociados a la cara. Así, el interés por la estimación de atributos faciales ha crecido rápidamente en los últimos años por las diversas aplicaciones en que estos métodos pueden ser utilizados: marketing dirigido, sistemas de seguridad, interacción hombre-máquina, etc. Sin embargo, éstos están lejos de ser perfectos y robustos en cualquier dominio de problemas. La principal dificultad encontrada es causada por la alta variabilidad intra-clase debida a los cambios en la condición de la imagen: cambios de iluminación, oclusiones, expresiones faciales, edad, género, etnia, etc.; encontradas frecuentemente en imágenes adquiridas en entornos no controlados. Este de trabajo de investigación estudia técnicas de análisis de imágenes para estimar atributos faciales como el género, la edad y la postura, empleando métodos lineales y explotando las dependencias estadísticas entre estos atributos. Adicionalmente, nuestra propuesta se centrará en la construcción de estimadores que tengan una fuerte relación entre rendimiento y coste computacional. Con respecto a éste último punto, estudiamos un conjunto de estrategias para la clasificación de género y las comparamos con una propuesta basada en un clasificador Bayesiano y una adecuada extracción de características. Analizamos en profundidad el motivo de porqué las técnicas lineales no han logrado resultados competitivos hasta la fecha y mostramos cómo obtener rendimientos similares a las mejores técnicas no-lineales. Se propone un segundo algoritmo para la estimación de edad, basado en un regresor K-NN y una adecuada selección de características tal como se propuso para la clasificación de género. A partir de los experimentos desarrollados, observamos que el rendimiento de los clasificadores se reduce significativamente si los ´estos han sido entrenados y probados sobre diferentes bases de datos. Hemos encontrado que una de las causas es la existencia de dependencias entre atributos faciales que no han sido consideradas en la construcción de los clasificadores. Nuestro resultados demuestran que la variabilidad intra-clase puede ser reducida cuando se consideran las dependencias estadísticas entre los atributos faciales de el género, la edad y la pose; mejorando el rendimiento de nuestros clasificadores de atributos faciales con un coste computacional pequeño. Abstract Surely the human face provides much more information than we think. The face provides without our consent nonverbal cues from facial interactions that reveal our emotional state, cognitive activity, personality and disease. Recent studies [OFT14, TODMS15] show that many of our social and interpersonal decisions derive from a previous facial analysis that allows us to establish whether that person is trustworthy, hardworking, intelligent, etc. This error-prone interpretation derives from the innate ability of human beings to find and interpret these signals. This capability is being studied, with a special interest in developing methods that have the ability to automatically calculate these signs or attributes associated with the face. Thus, the interest in the estimation of facial attributes has grown rapidly in recent years by the various applications in which these methods can be used: targeted marketing, security systems, human-computer interaction, etc. However, these are far from being perfect and robust in any domain of problems. The main difficulty encountered is caused by the high intra-class variability due to changes in the condition of the image: lighting changes, occlusions, facial expressions, age, gender, ethnicity, etc.; often found in images acquired in uncontrolled environments. This research work studies image analysis techniques to estimate facial attributes such as gender, age and pose, using linear methods, and exploiting the statistical dependencies between these attributes. In addition, our proposal will focus on the construction of classifiers that have a good balance between performance and computational cost. We studied a set of strategies for gender classification and we compare them with a proposal based on a Bayesian classifier and a suitable feature extraction based on Linear Discriminant Analysis. We study in depth why linear techniques have failed to provide competitive results to date and show how to obtain similar performances to the best non-linear techniques. A second algorithm is proposed for estimating age, which is based on a K-NN regressor and proper selection of features such as those proposed for the classification of gender. From our experiments we note that performance estimates are significantly reduced if they have been trained and tested on different databases. We have found that one of the causes is the existence of dependencies between facial features that have not been considered in the construction of classifiers. Our results demonstrate that intra-class variability can be reduced when considering the statistical dependencies between facial attributes gender, age and pose, thus improving the performance of our classifiers with a reduced computational cost.

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Context. The Gaia-ESO Public Spectroscopic Survey is obtaining high-quality spectroscopy of some 100 000 Milky Way stars using the FLAMES spectrograph at the VLT, down to V = 19 mag, systematically covering all the main components of the Milky Way and providing the first homogeneous overview of the distributions of kinematics and chemical element abundances in the Galaxy. Observations of young open clusters, in particular, are giving new insights into their initial structure, kinematics, and their subsequent evolution. Aims. This paper describes the analysis of UVES and GIRAFFE spectra acquired in the fields of young clusters whose population includes pre-main sequence (PMS) stars. The analysis is applied to all stars in such fields, regardless of any prior information on membership, and provides fundamental stellar atmospheric parameters, elemental abundances, and PMS-specific parameters such as veiling, accretion, and chromospheric activity. Methods. When feasible, different methods were used to derive raw parameters (e.g. line equivalent widths) fundamental atmospheric parameters and derived parameters (e.g. abundances). To derive some of these parameters, we used methods that have been extensively used in the past and new ones developed in the context of the Gaia-ESO survey enterprise. The internal precision of these quantities was estimated by inter-comparing the results obtained by these different methods, while the accuracy was estimated by comparison with independent external data, such as effective temperature and surface gravity derived from angular diameter measurements, on a sample of benchmarks stars. A validation procedure based on these comparisons was applied to discard spurious or doubtful results and produce recommended parameters. Specific strategies were implemented to resolve problems of fast rotation, accretion signatures, chromospheric activity, and veiling. Results. The analysis carried out on spectra acquired in young cluster fields during the first 18 months of observations, up to June 2013, is presented in preparation of the first release of advanced data products. These include targets in the fields of the ρ Oph, Cha I, NGC 2264, γ Vel, and NGC 2547 clusters. Stellar parameters obtained with the higher resolution and larger wavelength coverage from UVES are reproduced with comparable accuracy and precision using the smaller wavelength range and lower resolution of the GIRAFFE setup adopted for young stars, which allows us to provide stellar parameters with confidence for the much larger GIRAFFE sample. Precisions are estimated to be ≈120 K rms in Teff, ≈0.3 dex rms in log g, and ≈0.15 dex rms in [Fe/H] for the UVES and GIRAFFE setups.

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Results from the humid tropics of Australia demonstrate that diverse plantations can achieve greater productivity than monocultures. We found that increases in both the observed species number and the effective species richness were significantly related to increased levels of productivity as measured by stand basal area or mean individual tree basal area. Four of five plantation species were more productive in mixtures with other species than in monocultures, offering on average, a 55% increase in mean tree basal area. A general linear model suggests that species richness had a significant effect on mean individual tree basal area when environmental variables were included in the model. As monoculture plantations are currently the preferred reforestation method throughout the tropics these results suggest that significant productivity and ecological gains could be made if multi-species plantations are more broadly pursued. (c) 2006 Elsevier B.V. All rights reserved.

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The Perk-Schultz model may be expressed in terms of the solution of the Yang-Baxter equation associated with the fundamental representation of the untwisted affine extension of the general linear quantum superalgebra U-q (gl(m/n)], with a multiparametric coproduct action as given by Reshetikhin. Here, we present analogous explicit expressions for solutions of the Yang-Baxter equation associated with the fundamental representations of the twisted and untwisted affine extensions of the orthosymplectic quantum superalgebras U-q[osp(m/n)]. In this manner, we obtain generalizations of the Perk-Schultz model.