19 resultados para common method variance

em Universidad Politécnica de Madrid


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Common bean (Phaseolus vulgaris L.) is a leguminous in high demand for human nutrition and a very important agricultural product. Production of common bean is constrained by environmental stresses such as drought. Although conventional plant selection has been used to increase production yield and stress tolerance, drought tolerance selection based on phenotype is complicated by associated physiological, anatomical, cellular, biochemical, and molecular changes. These changes are modulated by differential gene expression. A common method to identify genes associated with phenotypes of interest is the characterization of Single Nucleotide Polymorphims (SNPs) to link them to specific functions. In this work, we selected two drought-tolerant parental lines from Mesoamerica, Pinto Villa, and Pinto Saltillo. The parental lines were used to generate a population of 282 families (F3:5) and characterized by 169 SNPs. We associated the segregation of the molecular markers in our population with phenotypes including flowering time, physiological maturity, reproductive period, plant, seed and total biomass, reuse index, seed yield, weight of 100 seeds, and harvest index in three cultivation cycles. We observed 83 SNPs with significant association (p < 0.0003 after Bonferroni correction) with our quantified phenotypes. Phenotypes most associated were days to flowering and seed biomass with 58 and 44 associated SNPs, respectively. Thirty-seven out of the 83 SNPs were annotated to a gene with a potential function related to drought tolerance or relevant molecular/biochemical functions. Some SNPs such as SNP28 and SNP128 are related to starch biosynthesis, a common osmotic protector; and SNP18 is related to proline biosynthesis, another well-known osmotic protector.

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Improved management of nitrogen (N) in agriculture is necessary to achieve a sustainable balance between the production of food and other biomass, and the unwanted effects of N on water pollution, greenhouse gas emissions, biodiversity deterioration and human health. To analyse farm N-losses and the complex interactions within farming systems, efficient methods for identifying emissions hotspots and evaluating mitigation measures are therefore needed. The present paper aims to fill this gap at the farm and landscape scales. Six agricultural landscapes in Poland (PL), the Netherlands (NL), France (FR), Italy (IT), Scotland (UK) and Denmark (DK) were studied, and a common method was developed for undertaking farm inventories and the derivation of farm N balances, N surpluses and for evaluating uncertainty for the 222 farms and 11 440 ha of farmland included in the study. In all landscapes, a large variation in the farm N surplus was found, and thereby a large potential for reductions. The highest average N surpluses were found in the most livestock-intensive landscapes of IT, FR, and NL; on average 202 ± 28, 179 ± 63 and 178 ± 20 kg N ha−1 yr−1, respectively. All landscapes showed hotspots, especially from livestock farms, including a special UK case with large-scale landless poultry farming. Overall, the average N surplus from the land-based UK farms dominated by extensive sheep and cattle grazing was only 31 ± 10 kg N ha−1 yr−1, but was similar to the N surplus of PL and DK (122 ± 20 and 146 ± 55 kg N ha−1 yr−1, respectively) when landless poultry farming was included. We found farm N balances to be a useful indicator for N losses and the potential for improving N management. Significant correlations to N surplus were found, both with ammonia air concentrations and nitrate concentrations in soils and groundwater, measured during the period of N management data collection in the landscapes from 2007–2009. This indicates that farm N surpluses may be used as an independent dataset for validation of measured and modelled N emissions in agricultural landscapes. No significant correlation was found with N measured in surface waters, probably because of spatial and temporal variations in groundwater buffering and biogeochemical reactions affecting N flows from farm to surface waters. A case study of the development in N surplus from the landscape in DK from 1998–2008 showed a 22% reduction related to measures targeted at N emissions from livestock farms. Based on the large differences in N surplus between average N management farms and the most modern and N-efficient farms, it was concluded that additional N-surplus reductions of 25–50%, as compared to the present level, were realistic in all landscapes. The implemented N-surplus method was thus effective for comparing and synthesizing results on farm N emissions and the potentials of mitigation options. It is recommended for use in combination with other methods for the assessment of landscape N emissions and farm N efficiency, including more detailed N source and N sink hotspot mapping, measurements and modelling.

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Measuring skin temperature (TSK) provides important information about the complex thermal control system and could be interesting when carrying out studies about thermoregulation. The most common method to record TSK involves thermocouples at specific locations; however, the use of infrared thermal imaging (IRT) has increased. The two methods use different physical processes to measure TSK, and each has advantages and disadvantages. Therefore, the objective of this study was to compare the mean skin temperature (MTSK) measurements using thermocouples and IRT in three different situations: pre-exercise, exercise and post-exercise. Analysis of the residual scores in Bland-Altman plots showed poor agreement between the MTSK obtained using thermocouples and those using IRT. The averaged error was -0.75 °C during pre-exercise, 1.22 °C during exercise and -1.16 °C during post-exercise, and the reliability between the methods was low in the pre- (ICC = 0.75 [0.12 to 0.93]), during (ICC = 0.49 [-0.80 to 0.85]) and post-exercise (ICC = 0.35 [-1.22 to 0.81] conditions. Thus, there is poor correlation between the values of MTSK measured by thermocouples and IRT pre-exercise, exercise and post-exercise, and low reliability between the two forms of measurement.

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Limit equilibrium is a common method used to analyze the stability of a slope, and minimization of the factor of safety or identification of critical slip surfaces is a classical geotechnical problem in the context of limit equilibrium methods for slope stability analyses. A mutative scale chaos optimization algorithm is employed in this study to locate the noncircular critical slip surface with Spencer’s method being employed to compute the factor of safety. Four examples from the literature—one homogeneous slope and three layered slopes—are employed to identify the efficiency and accuracy of this approach. Results indicate that the algorithm is flexible and that although it does not generally provide the minimum FS, it provides results that are close to the minimum, an improvement over other solutions proposed in the literature and with small relative errors with respect to other minimum factor of safety (FS) values reported in the literature.

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En las últimas dos décadas, se ha puesto de relieve la importancia de los procesos de adquisición y difusión del conocimiento dentro de las empresas, y por consiguiente el estudio de estos procesos y la implementación de tecnologías que los faciliten ha sido un tema que ha despertado un creciente interés en la comunidad científica. Con el fin de facilitar y optimizar la adquisición y la difusión del conocimiento, las organizaciones jerárquicas han evolucionado hacia una configuración más plana, con estructuras en red que resulten más ágiles, disminuyendo la dependencia de una autoridad centralizada, y constituyendo organizaciones orientadas a trabajar en equipo. Al mismo tiempo, se ha producido un rápido desarrollo de las herramientas de colaboración Web 2.0, tales como blogs y wikis. Estas herramientas de colaboración se caracterizan por una importante componente social, y pueden alcanzar todo su potencial cuando se despliegan en las estructuras organizacionales planas. La Web 2.0 aparece como un concepto enfrentado al conjunto de tecnologías que existían a finales de los 90s basadas en sitios web, y se basa en la participación de los propios usuarios. Empresas del Fortune 500 –HP, IBM, Xerox, Cisco– las adoptan de inmediato, aunque no hay unanimidad sobre su utilidad real ni sobre cómo medirla. Esto se debe en parte a que no se entienden bien los factores que llevan a los empleados a adoptarlas, lo que ha llevado a fracasos en la implantación debido a la existencia de algunas barreras. Dada esta situación, y ante las ventajas teóricas que tienen estas herramientas de colaboración Web 2.0 para las empresas, los directivos de éstas y la comunidad científica muestran un interés creciente en conocer la respuesta a la pregunta: ¿cuáles son los factores que contribuyen a que los empleados de las empresas adopten estas herramientas Web 2.0 para colaborar? La respuesta a esta pregunta es compleja ya que se trata de herramientas relativamente nuevas en el contexto empresarial mediante las cuales se puede llevar a cabo la gestión del conocimiento en lugar del manejo de la información. El planteamiento que se ha llevado a cabo en este trabajo para dar respuesta a esta pregunta es la aplicación de los modelos de adopción tecnológica, que se basan en las percepciones de los individuos sobre diferentes aspectos relacionados con el uso de la tecnología. Bajo este enfoque, este trabajo tiene como objetivo principal el estudio de los factores que influyen en la adopción de blogs y wikis en empresas, mediante un modelo predictivo, teórico y unificado, de adopción tecnológica, con un planteamiento holístico a partir de la literatura de los modelos de adopción tecnológica y de las particularidades que presentan las herramientas bajo estudio y en el contexto especifico. Este modelo teórico permitirá determinar aquellos factores que predicen la intención de uso de las herramientas y el uso real de las mismas. El trabajo de investigación científica se estructura en cinco partes: introducción al tema de investigación, desarrollo del marco teórico, diseño del trabajo de investigación, análisis empírico, y elaboración de conclusiones. Desde el punto de vista de la estructura de la memoria de la tesis, las cinco partes mencionadas se desarrollan de forma secuencial a lo largo de siete capítulos, correspondiendo la primera parte al capítulo 1, la segunda a los capítulos 2 y 3, la tercera parte a los capítulos 4 y 5, la cuarta parte al capítulo 6, y la quinta y última parte al capítulo 7. El contenido del capítulo 1 se centra en el planteamiento del problema de investigación así como en los objetivos, principal y secundarios, que se pretenden cumplir a lo largo del trabajo. Así mismo, se expondrá el concepto de colaboración y su encaje con las herramientas colaborativas Web 2.0 que se plantean en la investigación y una introducción a los modelos de adopción tecnológica. A continuación se expone la justificación de la investigación, los objetivos de la misma y el plan de trabajo para su elaboración. Una vez introducido el tema de investigación, en el capítulo 2 se lleva a cabo una revisión de la evolución de los principales modelos de adopción tecnológica existentes (IDT, TRA, SCT, TPB, DTPB, C-TAM-TPB, UTAUT, UTAUT2), dando cuenta de sus fundamentos y factores empleados. Sobre la base de los modelos de adopción tecnológica expuestos en el capítulo 2, en el capítulo 3 se estudian los factores que se han expuesto en el capítulo 2 pero adaptados al contexto de las herramientas colaborativas Web 2.0. Con el fin de facilitar la comprensión del modelo final, los factores se agrupan en cuatro tipos: tecnológicos, de control, socio-normativos y otros específicos de las herramientas colaborativas. En el capítulo 4 se lleva a cabo la relación de los factores que son más apropiados para estudiar la adopción de las herramientas colaborativas y se define un modelo que especifica las relaciones entre los diferentes factores. Estas relaciones finalmente se convertirán en hipótesis de trabajo, y que habrá que contrastar mediante el estudio empírico. A lo largo del capítulo 5 se especifican las características del trabajo empírico que se lleva a cabo para contrastar las hipótesis que se habían enunciado en el capítulo 4. La naturaleza de la investigación es de carácter social, de tipo exploratorio, y se basa en un estudio empírico cuantitativo cuyo análisis se llevará a cabo mediante técnicas de análisis multivariante. En este capítulo se describe la construcción de las escalas del instrumento de medida, la metodología de recogida de datos, y posteriormente se presenta un análisis detallado de la población muestral, así como la comprobación de la existencia o no del sesgo atribuible al método de medida, lo que se denomina sesgo de método común (en inglés, Common Method Bias). El contenido del capítulo 6 corresponde al análisis de resultados, aunque previamente se expone la técnica estadística empleada, PLS-SEM, como herramienta de análisis multivariante con capacidad de análisis predictivo, así como la metodología empleada para validar el modelo de medida y el modelo estructural, los requisitos que debe cumplir la muestra, y los umbrales de los parámetros considerados. En la segunda parte del capítulo 6 se lleva a cabo el análisis empírico de los datos correspondientes a las dos muestras, una para blogs y otra para wikis, con el fin de validar las hipótesis de investigación planteadas en el capítulo 4. Finalmente, en el capítulo 7 se revisa el grado de cumplimiento de los objetivos planteados en el capítulo 1 y se presentan las contribuciones teóricas, metodológicas y prácticas derivadas del trabajo realizado. A continuación se exponen las conclusiones generales y detalladas por cada grupo de factores, así como las recomendaciones prácticas que se pueden extraer para orientar la implantación de estas herramientas en situaciones reales. Como parte final del capítulo se incluyen las limitaciones del estudio y se sugiere una serie de posibles líneas de trabajo futuras de interés, junto con los resultados de investigación parciales que se han obtenido durante el tiempo que ha durado la investigación. ABSTRACT In the last two decades, the relevance of knowledge acquisition and dissemination processes has been highlighted and consequently, the study of these processes and the implementation of the technologies that make them possible has generated growing interest in the scientific community. In order to ease and optimize knowledge acquisition and dissemination, hierarchical organizations have evolved to a more horizontal configuration with more agile net structures, decreasing the dependence of a centralized authority, and building team-working oriented organizations. At the same time, Web 2.0 collaboration tools such as blogs and wikis have quickly developed. These collaboration tools are characterized by a strong social component and can reach their full potential when they are deployed in horizontal organization structures. Web 2.0, based on user participation, arises as a concept to challenge the existing technologies of the 90’s which were based on websites. Fortune 500 companies – HP, IBM, Xerox, Cisco- adopted the concept immediately even though there was no unanimity about its real usefulness or how it could be measured. This is partly due to the fact that the factors that make the drivers for employees to adopt these tools are not properly understood, consequently leading to implementation failure due to the existence of certain barriers. Given this situation, and faced with theoretical advantages that these Web 2.0 collaboration tools seem to have for companies, managers and the scientific community are showing an increasing interest in answering the following question: Which factors contribute to the decision of the employees of a company to adopt the Web 2.0 tools for collaborative purposes? The answer is complex since these tools are relatively new in business environments. These tools allow us to move from an information Management approach to Knowledge Management. In order to answer this question, the chosen approach involves the application of technology adoption models, all of them based on the individual’s perception of the different aspects related to technology usage. From this perspective, this thesis’ main objective is to study the factors influencing the adoption of blogs and wikis in a company. This is done by using a unified and theoretical predictive model of technological adoption with a holistic approach that is based on literature of technological adoption models and the particularities that these tools presented under study and in a specific context. This theoretical model will allow us to determine the factors that predict the intended use of these tools and their real usage. The scientific research is structured in five parts: Introduction to the research subject, development of the theoretical framework, research work design, empirical analysis and drawing the final conclusions. This thesis develops the five aforementioned parts sequentially thorough seven chapters; part one (chapter one), part two (chapters two and three), part three (chapters four and five), parte four (chapters six) and finally part five (chapter seven). The first chapter is focused on the research problem statement and the objectives of the thesis, intended to be reached during the project. Likewise, the concept of collaboration and its link with the Web 2.0 collaborative tools is discussed as well as an introduction to the technology adoption models. Finally we explain the planning to carry out the research and get the proposed results. After introducing the research topic, the second chapter carries out a review of the evolution of the main existing technology adoption models (IDT, TRA, SCT, TPB, DTPB, C-TAM-TPB, UTAUT, UTAUT2), highlighting its foundations and factors used. Based on technology adoption models set out in chapter 2, the third chapter deals with the factors which have been discussed previously in chapter 2, but adapted to the context of Web 2.0 collaborative tools under study, blogs and wikis. In order to better understand the final model, the factors are grouped into four types: technological factors, control factors, social-normative factors and other specific factors related to the collaborative tools. The first part of chapter 4 covers the analysis of the factors which are more relevant to study the adoption of collaborative tools, and the second part proceeds with the theoretical model which specifies the relationship between the different factors taken into consideration. These relationships will become specific hypotheses that will be tested by the empirical study. Throughout chapter 5 we cover the characteristics of the empirical study used to test the research hypotheses which were set out in chapter 4. The nature of research is social, exploratory, and it is based on a quantitative empirical study whose analysis is carried out using multivariate analysis techniques. The second part of this chapter includes the description of the scales of the measuring instrument; the methodology for data gathering, the detailed analysis of the sample, and finally the existence of bias attributable to the measurement method, the "Bias Common Method" is checked. The first part of chapter 6 corresponds to the analysis of results. The statistical technique employed (PLS-SEM) is previously explained as a tool of multivariate analysis, capable of carrying out predictive analysis, and as the appropriate methodology used to validate the model in a two-stages analysis, the measurement model and the structural model. Futhermore, it is necessary to check the requirements to be met by the sample and the thresholds of the parameters taken into account. In the second part of chapter 6 an empirical analysis of the data is performed for the two samples, one for blogs and the other for wikis, in order to validate the research hypothesis proposed in chapter 4. Finally, in chapter 7 the fulfillment level of the objectives raised in chapter 1 is reviewed and the theoretical, methodological and practical conclusions derived from the results of the study are presented. Next, we cover the general conclusions, detailing for each group of factors including practical recommendations that can be drawn to guide implementation of these tools in real situations in companies. As a final part of the chapter the limitations of the study are included and a number of potential future researches suggested, along with research partial results which have been obtained thorough the research.

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Researchers in ecology commonly use multivariate analyses (e.g. redundancy analysis, canonical correspondence analysis, Mantel correlation, multivariate analysis of variance) to interpret patterns in biological data and relate these patterns to environmental predictors. There has been, however, little recognition of the errors associated with biological data and the influence that these may have on predictions derived from ecological hypotheses. We present a permutational method that assesses the effects of taxonomic uncertainty on the multivariate analyses typically used in the analysis of ecological data. The procedure is based on iterative randomizations that randomly re-assign non identified species in each site to any of the other species found in the remaining sites. After each re-assignment of species identities, the multivariate method at stake is run and a parameter of interest is calculated. Consequently, one can estimate a range of plausible values for the parameter of interest under different scenarios of re-assigned species identities. We demonstrate the use of our approach in the calculation of two parameters with an example involving tropical tree species from western Amazonia: 1) the Mantel correlation between compositional similarity and environmental distances between pairs of sites, and; 2) the variance explained by environmental predictors in redundancy analysis (RDA). We also investigated the effects of increasing taxonomic uncertainty (i.e. number of unidentified species), and the taxonomic resolution at which morphospecies are determined (genus-resolution, family-resolution, or fully undetermined species) on the uncertainty range of these parameters. To achieve this, we performed simulations on a tree dataset from southern Mexico by randomly selecting a portion of the species contained in the dataset and classifying them as unidentified at each level of decreasing taxonomic resolution. An analysis of covariance showed that both taxonomic uncertainty and resolution significantly influence the uncertainty range of the resulting parameters. Increasing taxonomic uncertainty expands our uncertainty of the parameters estimated both in the Mantel test and RDA. The effects of increasing taxonomic resolution, however, are not as evident. The method presented in this study improves the traditional approaches to study compositional change in ecological communities by accounting for some of the uncertainty inherent to biological data. We hope that this approach can be routinely used to estimate any parameter of interest obtained from compositional data tables when faced with taxonomic uncertainty.

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In this paper, a new linear method for optimizing compact low noise oscillators for RF/MW applications will be presented. The first part of this paper makes an overview of Leeson's model. It is pointed out, and it is demonstrates that the phase noise is always the same inside the oscillator loop. It is presented a general phase noise optimization method for reference plane oscillators. The new method uses Transpose Return Relations (RRT) as true loop gain functions for obtaining the optimum values of the elements of the oscillator, whatever scheme it has. With this method, oscillator topologies that have been designed and optimized using negative resistance, negative conductance or reflection coefficient methods, until now, can be studied like a loop gain method. Subsequently, the main disadvantage of Leeson's model is overcome, and now it is not only valid for loop gain methods, but it is valid for any oscillator topology. The last section of this paper lists the steps to be performed to use this method for proper phase noise optimization during the linear design process and before the final non-linear optimization. The power of the proposed RRT method is shown with its use for optimizing a common oscillator, which is later simulated using Harmonic Balance (HB) and manufactured. Then, the comparison of the linear, HB and measurements of the phase noise are compared.

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The paper presents a method to analyze robust stability and transient performance of a distributed power system consisting of commercial converter modules interconnected through a common input filter. The method is based on the use of four transfer functions, which are measurable from the converter input and output terminals. It is shown that these parameters provide important information on the power module sensitivity to the interactions caused by the external impedances. Practical characterization for the described system structure is performed introducing special transfer functions utilized for the interactions assessment. Experimental results are provided to support the presented analysis procedure.

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Due to the sensitive international situation caused by still-recent terrorist attacks, there is a common need to protect the safety of large spaces such as government buildings, airports and power stations. To address this problem, developments in several research fields, such as video and cognitive audio, decision support systems, human interface, computer architecture, communications networks and communications security, should be integrated with the goal of achieving advanced security systems capable of checking all of the specified requirements and spanning the gap that presently exists in the current market. This paper describes the implementation of a decision system for crisis management in infrastructural building security. Specifically, it describes the implementation of a decision system in the management of building intrusions. The positions of the unidentified persons are reported with the help of a Wireless Sensor Network (WSN). The goal is to achieve an intelligent system capable of making the best decision in real time in order to quickly neutralise one or more intruders who threaten strategic installations. It is assumed that the intruders’ behaviour is inferred through sequences of sensors’ activations and their fusion. This article presents a general approach to selecting the optimum operation from the available neutralisation strategies based on a Minimax algorithm. The distances among different scenario elements will be used to measure the risk of the scene, so a path planning technique will be integrated in order to attain a good performance. Different actions to be executed over the elements of the scene such as moving a guard, blocking a door or turning on an alarm will be used to neutralise the crisis. This set of actions executed to stop the crisis is known as the neutralisation strategy. Finally, the system has been tested in simulations of real situations, and the results have been evaluated according to the final state of the intruders. In 86.5% of the cases, the system achieved the capture of the intruders, and in 59.25% of the cases, they were intercepted before they reached their objective.

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Stochastic model updating must be considered for quantifying uncertainties inherently existing in real-world engineering structures. By this means the statistical properties,instead of deterministic values, of structural parameters can be sought indicating the parameter variability. However, the implementation of stochastic model updating is much more complicated than that of deterministic methods particularly in the aspects of theoretical complexity and low computational efficiency. This study attempts to propose a simple and cost-efficient method by decomposing a stochastic updating process into a series of deterministic ones with the aid of response surface models and Monte Carlo simulation. The response surface models are used as surrogates for original FE models in the interest of programming simplification, fast response computation and easy inverse optimization. Monte Carlo simulation is adopted for generating samples from the assumed or measured probability distributions of responses. Each sample corresponds to an individual deterministic inverse process predicting the deterministic values of parameters. Then the parameter means and variances can be statistically estimated based on all the parameter predictions by running all the samples. Meanwhile, the analysis of variance approach is employed for the evaluation of parameter variability significance. The proposed method has been demonstrated firstly on a numerical beam and then a set of nominally identical steel plates tested in the laboratory. It is found that compared with the existing stochastic model updating methods, the proposed method presents similar accuracy while its primary merits consist in its simple implementation and cost efficiency in response computation and inverse optimization.

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The relationship between pairs of individuals is an important topic in many areas of population and quantitative genetics. It is usually measured as the proportion of thegenome identical by descent shared by the pair and it can be inferred from pedigree information. But there is a variance in actual relationships as a consequence of Mendelian sampling, whose general formula has not been developed. The goal of this work is to develop this general formula for the one-locus situation,. We provide simple expressions for the variances and covariances of all actual relationships in an arbitrary complex pedigree. The proposed method relies on the use of the nine identity coefficients and the generalized relationship coefficients; formulas have been checked by computer simulation. Finally two examples for a short pedigree of dogs and a long pedigree of sheep are given.

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The bankability of CPV projects is an important issue to pave the way toward a swift and sustained growth in this technology. The bankability of a PV plant is generally addressed through the modeling of its energy yield under a b aseline loss scenario, followed by an on-site measurement campaign aimed at verifying its energetic behavior. The main difference between PV and CPV resides in the proper CPV modules, in particular in the inclusion of optical lements and III-V multijunction cells that are much more sensitive to spectral variations than xSi cells, while the rest of the system behaves in a way that possesses many common points with xSi technology. The modeling of the DC power output of a CPV system thus requires several impo rtant second order parameters to be considered, mainly related to optics, spectral direct solar radiation, wind speed, tracker accuracy and heat dissipation of cells.

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In the last decade, Object Based Image Analysis (OBIA) has been accepted as an effective method for processing high spatial resolution multiband images. This image analysis method is an approach that starts with the segmentation of the image. Image segmentation in general is a procedure to partition an image into homogenous groups (segments). In practice, visual interpretation is often used to assess the quality of segmentation and the analysis relies on the experience of an analyst. In an effort to address the issue, in this study, we evaluate several seed selection strategies for an automatic image segmentation methodology based on a seeded region growing-merging approach. In order to evaluate the segmentation quality, segments were subjected to spatial autocorrelation analysis using Moran's I index and intra-segment variance analysis. We apply the algorithm to image segmentation using an aerial multiband image.

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Los análisis de fiabilidad representan una herramienta adecuada para contemplar las incertidumbres inherentes que existen en los parámetros geotécnicos. En esta Tesis Doctoral se desarrolla una metodología basada en una linealización sencilla, que emplea aproximaciones de primer o segundo orden, para evaluar eficientemente la fiabilidad del sistema en los problemas geotécnicos. En primer lugar, se emplean diferentes métodos para analizar la fiabilidad de dos aspectos propios del diseño de los túneles: la estabilidad del frente y el comportamiento del sostenimiento. Se aplican varias metodologías de fiabilidad — el Método de Fiabilidad de Primer Orden (FORM), el Método de Fiabilidad de Segundo Orden (SORM) y el Muestreo por Importancia (IS). Los resultados muestran que los tipos de distribución y las estructuras de correlación consideradas para todas las variables aleatorias tienen una influencia significativa en los resultados de fiabilidad, lo cual remarca la importancia de una adecuada caracterización de las incertidumbres geotécnicas en las aplicaciones prácticas. Los resultados también muestran que tanto el FORM como el SORM pueden emplearse para estimar la fiabilidad del sostenimiento de un túnel y que el SORM puede mejorar el FORM con un esfuerzo computacional adicional aceptable. Posteriormente, se desarrolla una metodología de linealización para evaluar la fiabilidad del sistema en los problemas geotécnicos. Esta metodología solamente necesita la información proporcionada por el FORM: el vector de índices de fiabilidad de las funciones de estado límite (LSFs) que componen el sistema y su matriz de correlación. Se analizan dos problemas geotécnicos comunes —la estabilidad de un talud en un suelo estratificado y un túnel circular excavado en roca— para demostrar la sencillez, precisión y eficiencia del procedimiento propuesto. Asimismo, se reflejan las ventajas de la metodología de linealización con respecto a las herramientas computacionales alternativas. Igualmente se muestra que, en el caso de que resulte necesario, se puede emplear el SORM —que aproxima la verdadera LSF mejor que el FORM— para calcular estimaciones más precisas de la fiabilidad del sistema. Finalmente, se presenta una nueva metodología que emplea Algoritmos Genéticos para identificar, de manera precisa, las superficies de deslizamiento representativas (RSSs) de taludes en suelos estratificados, las cuales se emplean posteriormente para estimar la fiabilidad del sistema, empleando la metodología de linealización propuesta. Se adoptan tres taludes en suelos estratificados característicos para demostrar la eficiencia, precisión y robustez del procedimiento propuesto y se discuten las ventajas del mismo con respecto a otros métodos alternativos. Los resultados muestran que la metodología propuesta da estimaciones de fiabilidad que mejoran los resultados previamente publicados, enfatizando la importancia de hallar buenas RSSs —y, especialmente, adecuadas (desde un punto de vista probabilístico) superficies de deslizamiento críticas que podrían ser no-circulares— para obtener estimaciones acertadas de la fiabilidad de taludes en suelos. Reliability analyses provide an adequate tool to consider the inherent uncertainties that exist in geotechnical parameters. This dissertation develops a simple linearization-based approach, that uses first or second order approximations, to efficiently evaluate the system reliability of geotechnical problems. First, reliability methods are employed to analyze the reliability of two tunnel design aspects: face stability and performance of support systems. Several reliability approaches —the first order reliability method (FORM), the second order reliability method (SORM), the response surface method (RSM) and importance sampling (IS)— are employed, with results showing that the assumed distribution types and correlation structures for all random variables have a significant effect on the reliability results. This emphasizes the importance of an adequate characterization of geotechnical uncertainties for practical applications. Results also show that both FORM and SORM can be used to estimate the reliability of tunnel-support systems; and that SORM can outperform FORM with an acceptable additional computational effort. A linearization approach is then developed to evaluate the system reliability of series geotechnical problems. The approach only needs information provided by FORM: the vector of reliability indices of the limit state functions (LSFs) composing the system, and their correlation matrix. Two common geotechnical problems —the stability of a slope in layered soil and a circular tunnel in rock— are employed to demonstrate the simplicity, accuracy and efficiency of the suggested procedure. Advantages of the linearization approach with respect to alternative computational tools are discussed. It is also found that, if necessary, SORM —that approximates the true LSF better than FORM— can be employed to compute better estimations of the system’s reliability. Finally, a new approach using Genetic Algorithms (GAs) is presented to identify the fully specified representative slip surfaces (RSSs) of layered soil slopes, and such RSSs are then employed to estimate the system reliability of slopes, using our proposed linearization approach. Three typical benchmark-slopes with layered soils are adopted to demonstrate the efficiency, accuracy and robustness of the suggested procedure, and advantages of the proposed method with respect to alternative methods are discussed. Results show that the proposed approach provides reliability estimates that improve previously published results, emphasizing the importance of finding good RSSs —and, especially, good (probabilistic) critical slip surfaces that might be non-circular— to obtain good estimations of the reliability of soil slope systems.

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Phaseolus vulgaris L. (frijol común o judía) es una leguminosa de gran demanda para la nutrición humana y un producto agrícola muy importante. Sin embargo, la producción de frijol se ve limitada por presiones ambientales como la sequía. En México, el 85% de la cosecha de frijol se produce en la temporada de primavera-verano, principalmente en las regiones del altiplano semiárido con una precipitación anual entre 250 y 400 mm. A pesar del implemento de tecnología en el campo, los factores naturales impiden al agricultor llegar a los rendimientos deseados. El Instituto Nacional de Investigaciones Forestales, Agrícolas y Pecuarias (INIFAP), como instituto de investigación gubernamental en México, tiene como objetivo la mejora de cultivos estratégicos, uno de ellos, P. vulgaris. Los estudios en relación a la sequía se enfocan especialmente en la selección de genotipos tolerantes, los cuales son sometidos en condiciones de estrés y monitoreando parámetros como el rendimiento y peso de semilla, además de algunos indicadores tales como índice de cosecha. El resultado de estos trabajos ha sido la obtención de variedades con mayor tolerancia a la sequía, tales como Pinto Villa y Pinto Saltillo. En los últimos años se ha avanzado notablemente en el conocimiento de las bases moleculares en las respuestas de las plantas al estrés. De acuerdo a diversos estudios se ha demostrado que las plantas bajo estrés por sequía experimentan cambios en la expresión de genes involucrados en la señalización, regulación de la transcripción y la traducción, transporte de agua y la función directa en la protección celular. También se ha observado que el déficit de agua es causado por las temperaturas extremas y la alta concentración de sales, por lo que al nivel molecular, las respuestas al estrés tienen puntos de especificidad y puntos de entrecruzamiento. La sequía puede generar estreses secundarios, tales como el nutricional, oxidativo y osmótico. Sin embargo, es necesario identificar y caracterizar muchos de los componentes involucrados en las respuestas al déficit hídrico, la caracterización de estos genes permitirá tener una mejor comprensión de los mecanismos bioquímicos y fisiológicos involucrados en la tolerancia al estrés. Actualmente, con el apoyo de la biología molecular se han identificado algunos genes que otorgan ventajas para la adaptación a ambientes desfavorables. Por lo que el objetivo del presente trabajo es identificar marcadores genéticos asociados a rasgos fenotípicos con énfasis a la tolerancia a estrés hídrico en P. vulgaris. Una vez establecidos los marcadores asociados al estrés hídrico, es factible considerar su uso para la selección asistida por marcadores en líneas o variedades de frijol de interés para los mejoradores. Se evaluaron 282 familias F3:5 derivadas de la cruza entre los cultivares Pinto Villa y Pinto Saltillo. Las familias se sembraron bajo un diseño simple de látice 17x17, el experimento se llevo acabo en el ciclo primavera-verano del 2010 y 2011, y otoñoinvierno de 2010 en el Campo Experimental Bajío del INIFAP con dos repeticiones para cada tratamiento de humedad (riego completo y sequía terminal). En todos los genotipos se realizó el fenotipado (variables fenotípicas) y el genotipado a través de marcadores moleculares. Los análisis estadísticos se basaron en el análisis de componentes principales (Eigen Analysis Selection Index Method, ESIM), la asociación entre marcadores SNP y el fenotipado (paquete SNPassoc para R) y el análisis de varianza (ANOVA). Los valores ESIM mostraron que las variables de Rendimiento, Días a floración, Días a madurez fisiológica e Índice de cosecha fueron sobresalientes en sequía terminal, por lo que se sugieren tomarse en consideración para los estudios de sequía en P. vulgaris como monitores de evaluación a la resistencia. Se identificaron nueve familias sobresalieron por sus valores ESIM (PV/PS6, 22, 131, 137, 149, 154, 201, 236 y 273), además de presentar valores superiores para el rendimiento en comparación con los parentales. Estos genotipos son candidatos interesantes para realizar estudios de identificación de loci asociados con la respuesta al estrés, y como potenciales parentales en el desarrollo de nuevas variedades de frijol. En los análisis de asociación SNPassoc se identificaron 83 SNPs significativos (p<0,0003) asociados a los rasgos fenotípicos, obteniendo un total de 222 asociaciones, de las cuales predomina el modelo genético de codominancia para las variables Días a floración, Periodo reproductivo y Biomasa total. Treinta y siete SNPs se identificaron a diferentes funciones biológicas a través del análisis de anotación funcional, de los cuales 12 SNPs (9, 18, 28, 39, 61, 69, 80, 106, 115, 128, 136 y 142) sobresalen por su asociación al fenotipado, y cuya anotación funcional indica que se encuentran en genes relacionados a la tolerancia a la sequía, tales como la actividad kinasa, actividad metabólica del almidón, carbohidratos y prolina, respuesta al estrés oxidativo, así como en los genes LEA y posibles factores de transcripción. En el caso de los análisis ANOVA, se identificaron 72 asociaciones entre los SNPs y las variables fenotípicas (F< 3,94E-04). Las 72 asociaciones corresponden a 30 SNPs y 7 variables fenotípicas, de las que predomina Peso de 100 semillas y Periodo reproductivo. Para los rasgos de Rendimiento, Índice de cosecha y Días a madurez fisiológica se presentaron asociaciones con seis SNPs (17, 34, 37, 50, 93 y 107), de los cuales, a los SNP37 y SNP107 fueron identificados a la anotación biológica de protein binding. Por otro lado, los SNP106 y SNP128 asociados al Periodo reproductivo, son genes con actividad kinasa y actividad metabólica del almidón, respectivamente. Para los marcadores tipo AFLP, se identificaron 271 asociaciones (F<2,34E-04). Las asociaciones corresponden a 86 AFLPs con todas las variables fenotípicas evaluadas, de las que predomina peso de 100 semillas, Días a floración y Periodo reproductivo. Debido a que los en los AFLPs no es posible determinar su anotación biológica, se proponen como marcadores potenciales relacionados a la resistencia a la sequía en frijol. Los AFLPs candidatos requieren más estudios tales como la secuenciación de los alelos respectivos, así como la identificación de éstas secuencias en el genoma de referencia y su anotación biológica, entre otros análisis, de esta manera podríamos establecer aquellos marcadores candidatos a la validación para la selección asistida. El presente trabajo propone tanto genotipos como marcadores genéticos, que deben ser validados para ser utilizados en el programa de mejoramiento de P. vulgaris, con el objetivo de desarrollar nuevas líneas o variedades tolerantes a la sequía. ABSTRACT Phaseolus vulgaris L. (common bean or judia) is a legume of great demand for human consumption and an important agricultural product. However, the common bean production is limited by environmental stresses, such as drought. In Mexico, 85% of the common bean crop is produced in the spring-summer season mainly in semiarid highland regions with a rainfall between 250 and 400 mm per year. In spite of the improvement of crop technology, the natural factors hamper getting an optimal yield. The National Institute for Forestry, Agriculture and Livestock (INIFAP) is a government research institute from Mexico, whose main objective is the genetic breeding of strategic crops, like P. vulgaris L. The drought tolerance studies particularly focus on the selection of bean tolerant genotypes, which are subjected to stress conditions, by means of monitoring parameters such as yield and seed weight, plus some agronomic indicators such as harvest index. The results of these works have led to obtain cultivars with higher drought tolerance such as Pinto Villa and Pinto Saltillo. Significant achievements have been recently made in understanding the molecular basis of stress plant responses. Several studies have shown that plants under drought stress present changes in gene expression related to cell signalling, transcriptional and translational regulation, water transport and cell protection. In addition, it has been observed that the extreme temperatures and high salt concentrations can cause a water deficiency so, at the molecular level, stress responses have specific and crossover points. The drought can cause secondary stresses, such as nutritional, oxidative and osmotic stress. It is required the identification of more components involved in the response to water deficit, the characterization of these genes will allow a better understanding of the biochemical and physiological mechanisms involved in stress tolerance. Currently, with the support of molecular biology techniques, some genes that confer an advantage for the crop adaptation to unfavourable environments have been identified. The objective of this study is to identify genetic markers associated with phenotypic traits with emphasis on water stress tolerance in P. vulgaris. The establishment of molecular markers linked to drought tolerance would make possible their use for marker-assisted selection in bean breeding programs. Two hundred and eighty two F3:5 families derived from a cross between the drought resistant cultivars Pinto Villa and Pinto Saltillo were evaluated. The families were sowed under a 17x17 simple lattice design. The experiment was conducted between spring-summer seasons in 2010 and 2011, and autumn-winter seasons in 2010 at the Bajio Experimental Station of INIFAP with two treatments (full irrigation and terminal drought). All families were phenotyped and genotyped using molecular markers. Statistical analysis was based on principal component analysis (Eigen Analysis Selection Index Method, ESIM), association analysis between SNP markers and phenotype (SNPassoc package R) and analysis of variance (ANOVA). The ESIM values showed that seed yield, days to flowering, days to physiological maturity and harvest index were outstanding traits in terminal drought treatment, so they could be considered as suitable parameters for drought-tolerance evaluation in P. vulgaris. Nine outstanding families for the ESIM values were identified (PV/PS6, 22, 131, 137, 149, 154, 201, 236 and 273), in addition, these families showed higher values for seed yield compared to the parental cultivars. These families are promising candidates for studies focused on the identification of loci associated to the stress response, and as potential parental cultivars for the development of new varieties of common bean. In the SNPassoc analysis, 83 SNPs were found significantly associated (p<0.0003) with phenotypic traits, obtaining a total of 222 associations, most of which involved the traits days to flowering, reproductive period and total biomass under a codominant genetic model. The functional annotation analysis showed 37 SNPs with different biological functions, 12 of them (9, 18, 28, 39, 61, 69, 80, 106, 115, 128, 136 and 142) stand out by their association to phenotype. The functional annotation suggested a connection with genes related to drought tolerance, such as kinase activity, starch, carbohydrates and proline metabolic processes, responses to oxidative stress, as well as LEA genes and putative transcription factors. In the ANOVA analysis, 72 associations between SNPs and phenotypic traits (F<3.94E- 04) were identified. All of these associations corresponded to 30 SNPs markers and seven phenotypic traits. Weight of 100 seeds and reproductive period were the traits with more associations. Seed yield, harvest index and days to physiological maturity were associated to six SNPs (17, 34, 37, 50, 93 and 107), the SNP37 and SNP107 were identified as located in protein binding genes. The SNP106 and SNP128 were associated with the reproductive period and belonged to genes with kinase activity and genes related to starch metabolic process, respectively. In the case of AFLP markers, 271 associations (F<2.34E-04) were identified. The associations involved 86 AFLPs and all phenotypic traits, being the most frequently associated weight of 100 seeds, days to flowering and reproductive period. Even though it is not possible to perform a functional annotation for AFLP markers, they are proposed as potential markers related to drought resistance in common bean. AFLPs candidates require additional studies such as the sequencing of the respective alleles, identification of these sequences in the reference genome and gene annotation, before their use in marker assisted selection. This work, although requires further validation, proposes both genotypes and genetic markers that could be used in breeding programs of P. vulgaris in order to develop new lines or cultivars with enhanced drought-tolerance.