Single nucleotide polymorphism (SNP) selection for genotype-phenotype association studies

With hundreds of single nucleotide polymorphisms (SNPs) in a candidate gene and millions of SNPs across the genome, selecting an informative subset of SNPs to maximize the ability to detect genotype-phenotype association is of great interest and importance. In addition, with a large number of SNPs, analytic methods are needed that allow investigators to control the false positive rate resulting from large numbers of SNP genotype-phenotype analyses. This dissertation uses simulated data to explore methods for selecting SNPs for genotype-phenotype association studies. I examined the pattern of linkage disequilibrium (LD) across a candidate gene region and used this pattern to aid in localizing a disease-influencing mutation. The results indicate that the r2 measure of linkage disequilibrium is preferred over the common D′ measure for use in genotype-phenotype association studies. Using step-wise linear regression, the best predictor of the quantitative trait was not usually the single functional mutation. Rather it was a SNP that was in high linkage disequilibrium with the functional mutation. Next, I compared three strategies for selecting SNPs for application to phenotype association studies: based on measures of linkage disequilibrium, based on a measure of haplotype diversity, and random selection. The results demonstrate that SNPs selected based on maximum haplotype diversity are more informative and yield higher power than randomly selected SNPs or SNPs selected based on low pair-wise LD. The data also indicate that for genes with small contribution to the phenotype, it is more prudent for investigators to increase their sample size than to continuously increase the number of SNPs in order to improve statistical power. When typing large numbers of SNPs, researchers are faced with the challenge of utilizing an appropriate statistical method that controls the type I error rate while maintaining adequate power. We show that an empirical genotype based multi-locus global test that uses permutation testing to investigate the null distribution of the maximum test statistic maintains a desired overall type I error rate while not overly sacrificing statistical power. The results also show that when the penetrance model is simple the multi-locus global test does as well or better than the haplotype analysis. However, for more complex models, haplotype analyses offer advantages. The results of this dissertation will be of utility to human geneticists designing large-scale multi-locus genotype-phenotype association studies. ^

A novel method for evaluating an interaction effect of correlated continuous covariates in a linear model

Interaction effect is an important scientific interest for many areas of research. Common approach for investigating the interaction effect of two continuous covariates on a response variable is through a cross-product term in multiple linear regression. In epidemiological studies, the two-way analysis of variance (ANOVA) type of method has also been utilized to examine the interaction effect by replacing the continuous covariates with their discretized levels. However, the implications of model assumptions of either approach have not been examined and the statistical validation has only focused on the general method, not specifically for the interaction effect.^ In this dissertation, we investigated the validity of both approaches based on the mathematical assumptions for non-skewed data. We showed that linear regression may not be an appropriate model when the interaction effect exists because it implies a highly skewed distribution for the response variable. We also showed that the normality and constant variance assumptions required by ANOVA are not satisfied in the model where the continuous covariates are replaced with their discretized levels. Therefore, naïve application of ANOVA method may lead to an incorrect conclusion. ^ Given the problems identified above, we proposed a novel method modifying from the traditional ANOVA approach to rigorously evaluate the interaction effect. The analytical expression of the interaction effect was derived based on the conditional distribution of the response variable given the discretized continuous covariates. A testing procedure that combines the p-values from each level of the discretized covariates was developed to test the overall significance of the interaction effect. According to the simulation study, the proposed method is more powerful then the least squares regression and the ANOVA method in detecting the interaction effect when data comes from a trivariate normal distribution. The proposed method was applied to a dataset from the National Institute of Neurological Disorders and Stroke (NINDS) tissue plasminogen activator (t-PA) stroke trial, and baseline age-by-weight interaction effect was found significant in predicting the change from baseline in NIHSS at Month-3 among patients received t-PA therapy.^

Selection bias and the cross-validation of regression models for prediction

Strategies are compared for the development of a linear regression model with stochastic (multivariate normal) regressor variables and the subsequent assessment of its predictive ability. Bias and mean squared error of four estimators of predictive performance are evaluated in simulated samples of 32 population correlation matrices. Models including all of the available predictors are compared with those obtained using selected subsets. The subset selection procedures investigated include two stopping rules, C$\sb{\rm p}$ and S$\sb{\rm p}$, each combined with an 'all possible subsets' or 'forward selection' of variables. The estimators of performance utilized include parametric (MSEP$\sb{\rm m}$) and non-parametric (PRESS) assessments in the entire sample, and two data splitting estimates restricted to a random or balanced (Snee's DUPLEX) 'validation' half sample. The simulations were performed as a designed experiment, with population correlation matrices representing a broad range of data structures.^ The techniques examined for subset selection do not generally result in improved predictions relative to the full model. Approaches using 'forward selection' result in slightly smaller prediction errors and less biased estimators of predictive accuracy than 'all possible subsets' approaches but no differences are detected between the performances of C$\sb{\rm p}$ and S$\sb{\rm p}$. In every case, prediction errors of models obtained by subset selection in either of the half splits exceed those obtained using all predictors and the entire sample.^ Only the random split estimator is conditionally (on $\\beta$) unbiased, however MSEP$\sb{\rm m}$ is unbiased on average and PRESS is nearly so in unselected (fixed form) models. When subset selection techniques are used, MSEP$\sb{\rm m}$ and PRESS always underestimate prediction errors, by as much as 27 percent (on average) in small samples. Despite their bias, the mean squared errors (MSE) of these estimators are at least 30 percent less than that of the unbiased random split estimator. The DUPLEX split estimator suffers from large MSE as well as bias, and seems of little value within the context of stochastic regressor variables.^ To maximize predictive accuracy while retaining a reliable estimate of that accuracy, it is recommended that the entire sample be used for model development, and a leave-one-out statistic (e.g. PRESS) be used for assessment. ^

Using spatial linear models with SAR and CAR structure to examine Texas lung cancer incidence rates

Scholars have found that socioeconomic status was one of the key factors that influenced early-stage lung cancer incidence rates in a variety of regions. This thesis examined the association between median household income and lung cancer incidence rates in Texas counties. A total of 254 individual counties in Texas with corresponding lung cancer incidence rates from 2004 to 2008 and median household incomes in 2006 were collected from the National Cancer Institute Surveillance System. A simple linear model and spatial linear models with two structures, Simultaneous Autoregressive Structure (SAR) and Conditional Autoregressive Structure (CAR), were used to link median household income and lung cancer incidence rates in Texas. The residuals of the spatial linear models were analyzed with Moran's I and Geary's C statistics, and the statistical results were used to detect similar lung cancer incidence rate clusters and disease patterns in Texas.^

A comparison of adherence with minocycline treatment in Parkinson's disease and rheumatoid arthritis clinical trials

Background: Little is known about the effects on patient adherence when the same study drug is administered in the same dose in two populations with two different diseases in two different clinical trials. The Minocycline in Rheumatoid Arthritis (MIRA) trial and the NIH Exploratory Trials in Parkinson's disease (NET-PD) Futility Study I provide a unique opportunity to do the above and to compare methods measuring adherence. This study may increase understanding of the influence of disease and adverse events on patient adherence and will provide insights to investigators selecting adherence assessment methods in clinical trials of minocycline and other drugs in future.^ Methods: Minocycline adherence by pill count and the effect of adverse events was compared in the MIRA and NET-PD FS1 trials using multivariable linear regression. Within the MIRA trial, agreement between assay and pill count was compared. The association of adverse events with assay adherence was examined using multivariable logistic regression.^ Results: Adherence derived from pill count in the MIRA and NET-PD FS1 trials did not differ significantly. Adverse events potentially related to minocycline did not appear useful to predict minocycline adherence. In the MIRA trial, adherence measured by pill count appears higher than adherence measured by assay. Agreement between pill count and assay was poor (kappa statistic = 0.25).^ Limitations: Trial and disease are completely confounded and hence the independent effect of disease on adherence to minocycline treatment cannot be studied.^ Conclusion: Simple pill count may be preferred over assay in the minocycline clinical trials to measure adherence. Assays may be less sensitive in a clinical setting where appointments are not scheduled in relation to medication administration time, given assays depend on many pharmacokinetic and instrument-related factors. However, pill count can be manipulated by the patient. Another study suggested that self-report method is more sensitive than pill count method in differentiating adherence from non-adherence. An effect of medication-related adverse events on adherence could not be detected.^

Modelos de demanda potencial de viajeros en redes de transporte público : aplicaciones en el Metro de Madrid

Este trabajo propone una metodología basada en Sistemas de Información Geográfica para estimar la demanda de viajes en estaciones de redes de transporte público, tomando como ejemplo la red de metro de Madrid. Primero se emplea una serie de datos descriptivos para caracterizar la red, clasificar las estaciones y obtener una tipología de las mismas. Luego, con el objetivo de explicar y predecir los viajes (entradas a la red) se generan dos modelos: uno sencillo a partir de las tasas de penetración de uso del metro en función de la distancia (distance decay), y otro más complejo basado en un modelo de regresión lineal múltiple (MRLM) que incorpora variables relativas a la estación y su entorno (densidad, mezcla de usos, diseño urbano, presencia de modos competidores). Su aplicación muestra resultados alentadores, y se plantea como una alternativa a los clásicos modelos de cuatro etapas, más complejos y con un mayor coste económico.

Optimización del Abonado Nitrogenado en el Melón (Cucumis Melo L.) Tipo Piel de Sapo

Spain is the fifth-largest producer of melon (Cucumis melo L.) and the second exporter in the world. To a national level, Castilla-La Mancha emphasize and, specifically, Ciudad Real, where is cultivated 27% of national area dedicated to this crop and 30% of melon national production. Melon crop is cultivating majority in Ciudad Real and it is mainly located in the Alto Guadiana, where the major aquifers of the region are located, the aquifer 23 or Mancha Occidental and the aquifer 24 or Campo de Montiel, both declared overexploited and vulnerable zones to nitrate pollution from agricultural sources. The problem is exacerbated because in this area, groundwater is the basic resource of supply to populations, and even often the only one. Given the importance of melon in the area, recent research has focused on the irrigation of melon crop. Unfortunately, scant information has been forthcoming on the effect of N fertilizer on melon piel de sapo crop, so it is very important to tackle in a serious study that lead to know the N requirements on the melon crop melon by reducing the risks of contamination by nitrate leaching without affecting productivity and crop quality. In fact, the recommended dose is often subjective and practice is a N overdose. In this situation, the taking of urgent measures to optimize the use of N fertilization is required. To do it, the effect of N in a melon crop, fertirrigated and on plastic mulch, was studied. The treatments consisted in different rates of N supply, considering N fertilizer and N content in irrigation water, so the treatment applied were: 30 (N30), 85 (N85), 112 (N112) and 139 (N139) Kg N ha-1 in 2005; 93 (N93), 243 (N243) and 393 (N393) kg ha-1 in 2006; and 11 (N11), 61 (N61), 95 (N95) and 148 (N148) kg ha-1 in 2007. A randomized complete-block design was used and each treatment was replicated four times. The results showed a significant effect of N on dry biomass and two patterns of growth were observed. On the one hand, a gradual increase in vegetative biomass of the plant, leaves and stem, with increasing N, and on the other hand, an increase of fruit biomass also with increasing N up to a maximum of biomass corresponding to the optimal dose determined in 90 kg ha-1 of N applied, corresponding to 160 kg ha-1 of N available for melon crop, since this optimum dose, the fruit biomass suffers a decline. A significant effect was observed in concentration and N uptake in leaf, steam, fruit and whole plant, increasing in all of them with increasing of N doses. Fast N uptake occurred from 30-35 to 70-80 days after transplanting, coinciding with the fruit development. The N had a clear influence on the melon yield, its components, skin thickness and flesh ratio. The melon yield increased, as the mean fruit weight and number of fruits per m2 with increasing N until achieve an above 95% of the maximum yield when the N applied is 90 kg ha-1 or 160 kg ha-1 of N available. When N exceeds the optimal amount, there is a decline in yield, reducing the mean fruit weight and number of fruits per square meter, and was also observed a decrease in fruit quality by increasing the skin thickness and decrease the flesh ratio, which means an increase in fruit hollowed with excessive N doses. There was a trend for all indexes of N use efficiency (NUE) to decline with increasing N rate. We observed two different behaviours in the calculation result of the NUE; on the one hand, all the efficiency indexes calculated with N applied and N available had an exponential trend, and on the other hand, all the efficiency indexes calculated with N uptake has a linear trend. The linear regression cuts the exponential curve, delimiting a range within which lies the optimum quantity of N. The N leaching as nitrates increased exponentially with the amount of N. The increase of N doses was affected on the N mineralization. There was a negative exponential effect of N available on the mineralization of this element that occurs in the soil during the growing season, calculated from the balances of this element. The study of N leaching for each N rate used, allowed to us to establish several environmental indices related to environmental risk that causes the use of such doses, a simple way for them to be included in the code of Best Management Practices.

Lazy Lasso for local regression

Locally weighted regression is a technique that predicts the response for new data items from their neighbors in the training data set, where closer data items are assigned higher weights in the prediction. However, the original method may suffer from overfitting and fail to select the relevant variables. In this paper we propose combining a regularization approach with locally weighted regression to achieve sparse models. Specifically, the lasso is a shrinkage and selection method for linear regression. We present an algorithm that embeds lasso in an iterative procedure that alternatively computes weights and performs lasso-wise regression. The algorithm is tested on three synthetic scenarios and two real data sets. Results show that the proposed method outperforms linear and local models for several kinds of scenarios

Estimación y evolución temporal de variables forestales con tecnología LiDAR en el Valle de la Fuenfría (Cercedilla, Madrid)

Este estudio profundiza en la estimación de variables forestales a partir de información LiDAR en el Valle de la Fuenfría (Cercedilla, Madrid). Para ello se dispone de dos vuelos realizados con sensor LiDAR en los años 2002 y 2011 y en el invierno de 2013 se ha realizado un inventario de 60 parcelas de campo. En primer lugar se han estimado seis variables dasométricas (volumen, área basimétrica, biomasa total, altura dominante, densidad y diámetro medio cuadrático) para 2013, tanto a nivel de píxel como a nivel de rodal y monte. Se construyeron modelos de regresión lineal múltiple que permitieron estimar con precisión dichas variables. En segundo lugar, se probaron diferentes métodos para la estimación de la distribución diamétrica. Por un lado, el método de predicción de percentiles y, por otro lado, el método de predicción de parámetros. Este segundo método se probó para una función Weibull simple, una función Weibull doble y una combinación de ambas según la distribución que mejor se ajustaba a cada parcela. Sin embargo, ninguno de los métodos ha resultado suficientemente válido para predecir la distribución diamétrica. Por último se estimaron el crecimiento en volumen y área basimétrica a partir de la comparación de los vuelos del 2002 y 2011. A pesar de que la tecnología LiDAR era diferente y solo se disponía de un inventario completo, realizado en 2013, los modelos construidos presentan buenas bondades de ajuste. Asimismo, el crecimiento a nivel de pixel se ha mostrado estar relacionado de forma estadísticamente significativa con la pendiente, orientación y altitud media del píxel. ABSTRACT This project goes in depth on the estimation of forest attributes by means of LiDAR data in Fuenfria’s Valley (Cercedilla, Madrid). The available information was two LiDAR flights (2002 and 2011) and a forest inventory consisting of 60 plots (2013). First, six different dasometric attributes (volume, basal area, total aboveground biomass, top height, density and quadratic mean diameter) were estimated in 2013 both at a pixel, stand and forest level. The models were developed using multiple linear regression and were good enough to predict these attributes with great accuracy. Second, the measured diameter distribution at each plot was fitted to a simple and a double Weibull distribution and different methods for its estimation were tested. Neither parameter prediction method nor percentile prediction method were able to account for the diameter distribution. Finally, volume and top height growths were estimated comparing 2011 LiDAR flight with 2002 LiDAR flight. Even though the LiDAR technology was not the same and there was just one forest inventory with sample plots, the models properly explain the growth. Besides, growth at each pixel is significantly related to its average slope, orientation and altitude.

Modelo del sistema de gestión de la calidad y el desempeño organizacional en la producción de petróleo

El proceso de cambio de una sociedad industrial a una sociedad del conocimiento, que experimenta el mundo globalizado en el siglo XXI, induce a las empresas y organizaciones a desarrollar ventajas competitivas y sostenibles basadas en sus activos intangibles, entre los cuales destacan los sistemas de gestión en general y los sistemas de gestión de la calidad (SGC) en particular. Las organizaciones dedicadas a la producción de petróleo están influenciadas por dicha tendencia. El petróleo es un recurso natural con reservas limitadas, cuya producción y consumo ha crecido progresivamente, aportando la mayor cuota (35 %) del total de la energía que se consume en el mundo contemporáneo, aporte que se mantendrá hasta el año 2035, según las previsiones más conservadoras. Por tanto, se hace necesario desarrollar modelos de producción innovadores, que contribuyan a la mejora del factor de recobro de los yacimientos y de la vida útil de los mismos, al tiempo que satisfagan los requerimientos de producción y consumo diarios de los exigentes mercados globales. El objeto de esta investigación es el desarrollo de un modelo de gestión de la calidad y su efecto en el desempeño organizacional, a través del efecto mediador de los constructos satisfacción del cliente interno y gestión del conocimiento en la producción de petróleo. Esta investigación de carácter explicativo, no experimental, transeccional y ex-postfacto, se realizó en la región petrolífera del lago de Maracaibo, al occidente de Venezuela, la cual tiene más de 70 años en producción y cuenta con yacimientos maduros. La población objeto de estudio fue de 369 trabajadores petroleros, quienes participaron en las mesas técnicas de la calidad, durante los meses de mayo y julio del año 2012, los cuales en su mayoría están en proceso de formación como analistas, asesores y auditores de los SGC. La técnica de muestreo aplicada fue de tipo aleatorio simple, con una muestra de 252 individuos. A la misma se le aplicó un cuestionario diseñado ad hoc, el cual fue validado por las técnicas de juicio de expertos y prueba piloto. El procedimiento de investigación se realizó a través de una secuencia, que incluyó la elaboración de un modelo teórico, basado en la revisión del estado del arte; un modelo factorial, sobre la base del análisis factorial de los datos de la encuesta; un modelo de regresión lineal, elaborado a través del método de regresión lineal simple y múltiple; un modelo de análisis de sendero, realizado con el software Amos 20 SPSS y finalmente, un modelo informático, realizado con el simulador Vensim PLE v.6.2. Los resultados obtenidos indican que el modelo teórico se transformó en un modelo empírico, en el cual, la variable independiente fue el SGC, la variable mediadora fue la integración de las dimensiones eliminación de la no conformidad, satisfacción del cliente interno y aprendizaje organizacional (ENCSCIAO) y la variable respuesta la integración de las dimensiones desempeño organizacional y aprendizaje organizacional (DOOA). Se verificó el efecto mediador del ENSCIAO sobre la relación SGC-DOOA con una bondad del ajuste, del 42,65%. En el modelo de regresión múltiple se encontró que las variables determinantes son eliminación de la no conformidad (ENC), conocimiento adquirido (CA) y conocimiento espontáneo (CE), lo cual fue corroborado con el modelo de análisis de sendero. El modelo informático se desarrolló empleando datos aproximados de una unidad de producción tipo, generándose cuatro escenarios; siendo el más favorable, aquel en el cual se aplicaba el SGC y variables relacionadas, reduciendo la desviación de la producción, incrementando el factor de recobro y ampliando la vida útil del yacimiento. Se concluye que la aplicación del SGC y constructos relacionados favorece el desempeño y la producción de las unidades de explotación de yacimientos petrolíferos maduros. Los principales aportes de la tesis son la obtención de un modelo de gestión de la producción de petróleo en yacimientos maduros, basado en los SGC. Asimismo, el desarrollo de un concepto de gestión de la calidad asociado a la reducción de la desviación de la producción petrolífera anual, al incremento del factor de recobro y al aumento de la vida útil del yacimiento. Las futuras líneas de investigación están orientadas a la aplicación del modelo en contextos reales y específicos, para medir su impacto y realizar los ajustes pertinentes. ABSTRACT The process of change from an industrial society to a knowledge-based society, which undergoes the globalized world in the twenty-first century, induces companies and organizations to develop a sustainable and competitive advantages based on its intangible assets, among which are noteworthy the management systems in general and particularly the quality management systems (QMS). Organizations engaged in oil production are influenced by said trend. Oil is a natural resource with limited reserves, where production and consumption has grown progressively, providing the largest share (35%) of the total energy consumed in the contemporary world, a contribution that will remain until the year 2035 according to the more conservative trust estimations. Therefore, it becomes necessary to develop innovative production models which contribute with the improvement of reservoirs´ recovery factor and the lifetime thereof, while meeting the production requirements and daily consumption of demanding global markets. The aim of this research is to develop a model of quality management and its effect on organizational performance through the mediator effect of the constructs, internal customer satisfaction and knowledge management in oil production. This research of explanatory nature, not experimental, transactional and expos-facto was carried out in the oil-region of Maracaibo Lake located to the west of Venezuela, which has more than 70 years in continuous production and has mature reservoirs. The population under study was 369 oil workers who participated in the technical quality workshops, during the months of May and July of 2012, the majority of which were in the process of training as analysts, consultants and auditors of the QMS. The sampling technique applied was simple random type. To a sample of 252 individuals of the population it was applied an ad hoc designed questionnaire, which was validated by the techniques of expert judgment and pilot test. The research procedure was performed through a sequence, which included the elaboration of a theoretical model, based on the review of the state of the art; a factorial model with based on factorial analysis of the survey data; a linear regression model, developed through the method of simple and multiple linear regression; a structural equation model, made with software °Amos 20 SPSS° and finally, a computer model, performed with the simulator Vensim PLE v.6.2. The results indicate that the theoretical model was transformed into an empirical model, in which the independent variable was the QMS, the mediator variable was the integration of the dimensions: elimination of non-conformity, internal customer satisfaction and organizational learning (ENCSCIAO) and the response variable the integration of the dimensions, organizational performance and learning organizational (DOOA). ENSCIAO´s mediator effect on the relation QMS-DOOA was verified with a goodness of fit of 42,65%. In the multiple regression model was found to be the determining variables are elimination of nonconformity (ENC), knowledge acquired (CA) and spontaneous knowledge (EC), which was verified with the structural equation model. The computer model was developed based on approximate data of an oil production unit type, creating four (04) scenarios; being the most favorable, that one which it was applied the QMS and related variables, reducing the production deviation, increasing the recovery factor and extending the lifetime of the reservoir. It is concluded that QMS implementation powered with the related constructs, favors performance and production of mature oilfield of exploitation reservoirs units. The main contributions of this thesis are obtaining a management model for oil production in mature oilfields, based on QMS. In addition, development of a concept of quality associated to reduce the annual oil production deviation, increase the recovery factor and increase oilfield lifetime. Future lines of research are oriented to the implementation of this model in real and specific contexts to measure its impact and make the necessary adjustments that might take place.

Estudio de la adherencia de armaduras corroídas y su influencia en la capacidad resistente de elementos de hormigón armado

La verificación de la seguridad estructural, tanto de estructuras que permitan un cierto grado de deterioro en su dimensionado como de estructuras existentes deterioradas, necesita disponer de modelos de resistencia que tengan en cuenta los efectos del deterioro. En el caso de la corrosión de las armaduras en las estructuras de hormigón armado, la resistencia depende de múltiples factores tales como la sección del acero corroído, el diagrama tensión-deformación del acero corroído, la adherencia hormigón-acero corroído, la fisuración o desprendimiento del hormigón debido a la expansión de los productos de corrosión. En este sentido, la transferencia de las fuerzas a través de la superficie de contacto entre el hormigón y el acero, la adherencia, es uno de los aspectos más importantes a considerar y es la base del comportamiento del hormigón armado como elemento estructural. La adherencia debe asegurar el anclaje de las armaduras y transmitir la tensión tangencial que aparece en las mismas como consecuencia de la variación de las solicitaciones a lo largo de un elemento estructural. Como consecuencia de la corrosión de las armaduras, el desarrollo de la adherencia se altera y, por tanto, la transferencia de la tensión longitudinal. Esta Tesis Doctoral aborda el comportamiento en estado límite último de la adherencia en el hormigón estructural con armaduras corroídas. El objetivo principal es la obtención de un modelo suficientemente realista y fiable para la evaluación de la adherencia con armaduras corroídas en el marco de la verificación de la seguridad estructural de elementos de hormigón armado con armaduras corroídas. Para ello se ha llevado a cabo un programa experimental de ensayos tipo pull-out excéntricos, con diferentes probetas, unas sin corrosión y otras sometidas tanto a procesos de corrosión natural como a procesos de corrosión acelerada, con diferentes grados de deterioro. Este tipo de ensayo de adherencia representa de forma realista y fiable realista los esfuerzos de adherencia en la zona de anclaje. Por otra parte, para la realización de estos ensayos se ha puesto a punto, además del procedimiento de ensayo, un sistema de adquisición de datos entre los que se incluye el empleo de sensores de tipo fibra óptica con redes de Bragg embebidos en la armadura para determinar los parámetros representativos de la adherencia en el hormigón estructural con armaduras corroídas. Por otra parte, la recopilación de los datos de los estudios de adherencia con armaduras corroídas procedentes de la literatura científica, además de los resultados de la presente investigación, junto con la identificación de las variables relevantes en el comportamiento de la adherencia con armaduras sanas y corroídas ha servido para la obtención de una formulación realista y fiable para la evaluación conjunta de la adherencia con armaduras sanas y corroídas a partir de modelos de regresión múltiple. La formulación propuesta ha sido validada mediante criterios estadísticos y comparada con otras formulaciones propuestas en la literatura científica. Además se ha realizado un análisis de las variables influyentes de la formulación propuesta. También se ha obtenido un modelo numérico simple y eficiente, validado con alguno de los ensayos realizados en esta tesis, para simular la adherencia con armaduras sanas y corroídas. Finalmente, se presenta un procedimiento para realizar la evaluación de vigas deterioradas por corrosión mediante el método de los campos de tensiones que incluye la evaluación de la adherencia mediante la formulación sugerida en esta Tesis Doctoral. Las conclusiones alcanzadas en este trabajo han permitido evaluar la adherencia con armaduras corroídas de forma realista y fiable. Asimismo, se ha podido incluir la evaluación de la adherencia en el marco de la verificación de la seguridad estructural en elementos de hormigón armado deteriorados por corrosión. ABSTRACT Structural safety verification of both structures allowing a certain degree of deterioration in design and deteriorated existing structures needs strength models that factor in the effects of deterioration. In case of corrosion of steel bars in reinforced concrete structures, the resistance depends on many things such as the remaining cross-section of the corroded reinforcement bars, the stress-strain diagrams of steel, the concrete-reinforcement bond and corrosion-induced concrete cracking or spalling. Accordingly, the force transfer through the contact surface between concrete and reinforcement, bond, is one of the most important aspects to consider and it is the basis of the structural performance of reinforced concrete. Bond must assure anchorage of reinforcement and transmit shear stresses as a consequence of the different stresses along a structural element As a consequence of corrosion, the bond development may be affected and hence the transfer of longitudinal stresses. This PhD Thesis deals with ultimate limit state bond behaviour in structural concrete with corrode steel bars. The main objective is to obtain a realistic and reliable model for the assessment of bond within the context of structural safety verifications of reinforced concrete members with corroded steel bars. In that context, an experimental programme of eccentric pull-out tests were conducted, with different specimens, ones without corrosion and others subjected to accelerated or natural corrosion with different corrosion degrees. This type of bond test reproduces in a realistic and reliable way bond stresses in the anchorage zone. Moreover, for conducting these tests it was necessary to develop both a test procedure and also a data acquisition system including the use of an embedded fibre-optic sensing system with fibre Bragg grating sensors to obtain the representative parameters of bond strength in structural concrete with corroded steel bars. Furthermore, the compilation of data from bond studies with corroded steel bars from scientific literature, including tests conducted in the present study, along with the identification of the relevant variables influencing bond behaviour for both corroded and non-corroded steel bars was used to obtain a realistic and reliable formulation for bond assessment in corroded and non-corroded steel bars by multiple linear regression analysis. The proposed formulation was validated with a number of statistical criteria and compared to other models from scientific literature. Moreover, an analysis of the influencing variables of the proposed formulation has been performed. Also, a simplified and efficient numerical model has been obtained and validated with several tests performed in this PhD Thesis for simulating the bond in corroded and non-corroded steel bars. Finally, a proposal for the assessment of corrosion-damaged beams with stress field models including bond assessment with the proposed formulation is presented. The conclusions raised in this work have allowed a realistic and reliable bond assessment in corroded steel bars. Furthermore, bond assessment has been included within the context of structural safety verifications in corrosion-damaged reinforced concrete elements.

Aportación al análisis de espectros de radiación: estructuras y algoritmos

A lo largo del presente trabajo se investiga la viabilidad de la descomposición automática de espectros de radiación gamma por medio de algoritmos de resolución de sistemas de ecuaciones algebraicas lineales basados en técnicas de pseudoinversión. La determinación de dichos algoritmos ha sido realizada teniendo en cuenta su posible implementación sobre procesadores de propósito específico de baja complejidad. En el primer capítulo se resumen las técnicas para la detección y medida de la radiación gamma que han servido de base para la confección de los espectros tratados en el trabajo. Se reexaminan los conceptos asociados con la naturaleza de la radiación electromagnética, así como los procesos físicos y el tratamiento electrónico que se hallan involucrados en su detección, poniendo de relieve la naturaleza intrínsecamente estadística del proceso de formación del espectro asociado como una clasificación del número de detecciones realizadas en función de la energía supuestamente continua asociada a las mismas. Para ello se aporta una breve descripción de los principales fenómenos de interacción de la radiación con la materia, que condicionan el proceso de detección y formación del espectro. El detector de radiación es considerado el elemento crítico del sistema de medida, puesto que condiciona fuertemente el proceso de detección. Por ello se examinan los principales tipos de detectores, con especial hincapié en los detectores de tipo semiconductor, ya que son los más utilizados en la actualidad. Finalmente, se describen los subsistemas electrónicos fundamentales para el acondicionamiento y pretratamiento de la señal procedente del detector, a la que se le denomina con el término tradicionalmente utilizado de Electrónica Nuclear. En lo que concierne a la espectroscopia, el principal subsistema de interés para el presente trabajo es el analizador multicanal, el cual lleva a cabo el tratamiento cualitativo de la señal, y construye un histograma de intensidad de radiación en el margen de energías al que el detector es sensible. Este vector N-dimensional es lo que generalmente se conoce con el nombre de espectro de radiación. Los distintos radionúclidos que participan en una fuente de radiación no pura dejan su impronta en dicho espectro. En el capítulo segundo se realiza una revisión exhaustiva de los métodos matemáticos en uso hasta el momento ideados para la identificación de los radionúclidos presentes en un espectro compuesto, así como para determinar sus actividades relativas. Uno de ellos es el denominado de regresión lineal múltiple, que se propone como la aproximación más apropiada a los condicionamientos y restricciones del problema: capacidad para tratar con espectros de baja resolución, ausencia del concurso de un operador humano (no supervisión), y posibilidad de ser soportado por algoritmos de baja complejidad capaces de ser instrumentados sobre procesadores dedicados de alta escala de integración. El problema del análisis se plantea formalmente en el tercer capítulo siguiendo las pautas arriba mencionadas y se demuestra que el citado problema admite una solución en la teoría de memorias asociativas lineales. Un operador basado en este tipo de estructuras puede proporcionar la solución al problema de la descomposición espectral deseada. En el mismo contexto, se proponen un par de algoritmos adaptativos complementarios para la construcción del operador, que gozan de unas características aritméticas especialmente apropiadas para su instrumentación sobre procesadores de alta escala de integración. La característica de adaptatividad dota a la memoria asociativa de una gran flexibilidad en lo que se refiere a la incorporación de nueva información en forma progresiva.En el capítulo cuarto se trata con un nuevo problema añadido, de índole altamente compleja. Es el del tratamiento de las deformaciones que introducen en el espectro las derivas instrumentales presentes en el dispositivo detector y en la electrónica de preacondicionamiento. Estas deformaciones invalidan el modelo de regresión lineal utilizado para describir el espectro problema. Se deriva entonces un modelo que incluya las citadas deformaciones como una ampliación de contribuciones en el espectro compuesto, el cual conlleva una ampliación sencilla de la memoria asociativa capaz de tolerar las derivas en la mezcla problema y de llevar a cabo un análisis robusto de contribuciones. El método de ampliación utilizado se basa en la suposición de pequeñas perturbaciones. La práctica en el laboratorio demuestra que, en ocasiones, las derivas instrumentales pueden provocar distorsiones severas en el espectro que no pueden ser tratadas por el modelo anterior. Por ello, en el capítulo quinto se plantea el problema de medidas afectadas por fuertes derivas desde el punto de vista de la teoría de optimización no lineal. Esta reformulación lleva a la introducción de un algoritmo de tipo recursivo inspirado en el de Gauss-Newton que permite introducir el concepto de memoria lineal realimentada. Este operador ofrece una capacidad sensiblemente mejorada para la descomposición de mezclas con fuerte deriva sin la excesiva carga computacional que presentan los algoritmos clásicos de optimización no lineal. El trabajo finaliza con una discusión de los resultados obtenidos en los tres principales niveles de estudio abordados, que se ofrecen en los capítulos tercero, cuarto y quinto, así como con la elevación a definitivas de las principales conclusiones derivadas del estudio y con el desglose de las posibles líneas de continuación del presente trabajo.---ABSTRACT---Through the present research, the feasibility of Automatic Gamma-Radiation Spectral Decomposition by Linear Algebraic Equation-Solving Algorithms using Pseudo-Inverse Techniques is explored. The design of the before mentioned algorithms has been done having into account their possible implementation on Specific-Purpose Processors of Low Complexity. In the first chapter, the techniques for the detection and measurement of gamma radiation employed to construct the spectra being used throughout the research are reviewed. Similarly, the basic concepts related with the nature and properties of the hard electromagnetic radiation are also re-examined, together with the physic and electronic processes involved in the detection of such kind of radiation, with special emphasis in the intrinsic statistical nature of the spectrum build-up process, which is considered as a classification of the number of individual photon-detections as a function of the energy associated to each individual photon. Fbr such, a brief description of the most important matter-energy interaction phenomena conditioning the detection and spectrum formation processes is given. The radiation detector is considered as the most critical element in the measurement system, as this device strongly conditions the detection process. Fbr this reason, the characteristics of the most frequent detectors are re-examined, with special emphasis on those of semiconductor nature, as these are the most frequently employed ones nowadays. Finally, the fundamental electronic subsystems for preaconditioning and treating of the signal delivered by the detector, classically addresed as Nuclear Electronics, is described. As far as Spectroscopy is concerned, the subsystem most interesting for the scope covered by the present research is the so-called Multichannel Analyzer, which is devoted to the cualitative treatment of the signal, building-up a hystogram of radiation intensity in the range of energies in which the detector is sensitive. The resulting N-dimensional vector is generally known with the ñame of Radiation Spectrum. The different radio-nuclides contributing to the spectrum of a composite source will leave their fingerprint in the resulting spectrum. Through the second chapter, an exhaustive review of the mathematical methods devised to the present moment to identify the radio-nuclides present in the composite spectrum and to quantify their relative contributions, is reviewed. One of the more popular ones is the so-known Múltiple Linear Regression, which is proposed as the best suited approach according to the constraints and restrictions present in the formulation of the problem, i.e., the need to treat low-resolution spectra, the absence of control by a human operator (un-supervision), and the possibility of being implemented as low-complexity algorithms amenable of being supported by VLSI Specific Processors. The analysis problem is formally stated through the third chapter, following the hints established in this context, and it is shown that the addressed problem may be satisfactorily solved under the point of view of Linear Associative Memories. An operator based on this kind of structures may provide the solution to the spectral decomposition problem posed. In the same context, a pair of complementary adaptive algorithms useful for the construction of the solving operator are proposed, which share certain special arithmetic characteristics that render them specially suitable for their implementation on VLSI Processors. The adaptive nature of the associative memory provides a high flexibility to this operator, in what refers to the progressive inclusión of new information to the knowledge base. Through the fourth chapter, this fact is treated together with a new problem to be considered, of a high interest but quite complex nature, as is the treatment of the deformations appearing in the spectrum when instrumental drifts in both the detecting device and the pre-acconditioning electronics are to be taken into account. These deformations render the Linear Regression Model proposed almost unuseful to describe the resulting spectrum. A new model including the drifts is derived as an extensión of the individual contributions to the composite spectrum, which implies a simple extensión of the Associative Memory, which renders this suitable to accept the drifts in the composite spectrum, thus producing a robust analysis of contributions. The extensión method is based on the Low-Amplitude Perturbation Hypothesis. Experimental practice shows that in certain cases the instrumental drifts may provoke severe distortions in the resulting spectrum, which can not be treated with the before-mentioned hypothesis. To cover also these less-frequent cases, through the fifth chapter, the problem involving strong drifts is treated under the point of view of Non-Linear Optimization Techniques. This reformulation carries the study to the consideration of recursive algorithms based on the Gauss-Newton methods, which allow the introduction of Feed-Back Memories, computing elements with a sensibly improved capability to decompose spectra affected by strong drifts. The research concludes with a discussion of the results obtained in the three main levéis of study considerad, which are presented in chapters third, fourth and fifth, toghether with the review of the main conclusions derived from the study and the outline of the main research lines opened by the present work.

Utilización de modelos hidráulicos bidimensionales en la determinación del tiempo de concentración

El tiempo de concentración de una cuenca sigue siendo relativamente desconocido para los ingenieros. El procedimiento habitual en un estudio hidrológico es calcularlo según varias fórmulas escogidas entre las existentes para después emplear el valor medio obtenido. De esta media se derivan los demás resultados hidrológicos, resultados que influirán en el futuro dimensionamiento de las infraestructuras. Este trabajo de investigación comenzó con el deseo de conseguir un método más fiable y objetivo que permitiera obtener el tiempo de concentración. Dada la imposibilidad de poner en práctica ensayos hidrológicos en una cuenca física real, ya que no resulta viable monitorizar perfectamente la precipitación ni los caudales de salida, se planteó llevar a cabo los ensayos de forma simulada, con el empleo de modelos hidráulicos bidimensionales de lluvia directa sobre malla 2D de volúmenes finitos. De entre todos los disponibles, se escogió InfoWorks ICM, por su rapidez y facilidad de uso. En una primera fase se efectuó la validación del modelo hidráulico elegido, contrastando los resultados de varias simulaciones con la formulación analítica existente. Posteriormente, se comprobaron los valores de los tiempos de concentración obtenidos con las expresiones referenciadas en la bibliografía, consiguiéndose resultados muy satisfactorios. Una vez verificado, se ejecutaron 690 simulaciones de cuencas tanto naturales como sintéticas, incorporando variaciones de área, pendiente, rugosidad, intensidad y duración de las precipitaciones, a fin de obtener sus tiempos de concentración y retardo. Esta labor se realizó con ayuda de la aceleración del cálculo vectorial que ofrece la tecnología CUDA (Arquitectura Unificada de Dispositivos de Cálculo). Basándose en el análisis dimensional, se agruparon los resultados del tiempo de concentración en monomios adimensionales. Utilizando regresión lineal múltiple, se obtuvo una nueva formulación para el tiempo de concentración. La nueva expresión se contrastó con las formulaciones clásicas, habiéndose obtenido resultados equivalentes. Con la exposición de esta nueva metodología se pretende ayudar al ingeniero en la realización de estudios hidrológicos. Primero porque proporciona datos de manera sencilla y objetiva que se pueden emplear en modelos globales como HEC-HMS. Y segundo porque en sí misma se ha comprobado como una alternativa realmente válida a la metodología hidrológica habitual. Time of concentration remains still fairly imprecise to engineers. A normal hydrological study goes through several formulae, obtaining concentration time as the median value. Most of the remaining hydrologic results will be derived from this value. Those results will determine how future infrastructures will be designed. This research began with the aim to acquire a more reliable and objective method to estimate concentration times. Given the impossibility of carrying out hydrological tests in a real watershed, due to the difficulties related to accurate monitoring of rainfall and derived outflows, a model-based approach was proposed using bidimensional hydraulic simulations of direct rainfall over a 2D finite-volume mesh. Amongst all of the available software packages, InfoWorks ICM was chosen for its speed and ease of use. As a preliminary phase, the selected hydraulic model was validated, checking the outcomes of several simulations over existing analytical formulae. Next, concentration time values were compared to those resulting from expressions referenced in the technical literature. They proved highly satisfactory. Once the model was properly verified, 690 simulations of both natural and synthetic basins were performed, incorporating variations of area, slope, roughness, intensity and duration of rainfall, in order to obtain their concentration and lag times. This job was carried out in a reasonable time lapse with the aid of the parallel computing platform technology CUDA (Compute Unified Device Architecture). Performing dimensional analysis, concentration time results were isolated in dimensionless monomials. Afterwards, a new formulation for the time of concentration was obtained using multiple linear regression. This new expression was checked against classical formulations, obtaining equivalent results. The publication of this new methodology intends to further assist the engineer while carrying out hydrological studies. It is effective to provide global parameters that will feed global models as HEC-HMS on a simple and objective way. It has also been proven as a solid alternative to usual hydrology methodology.