HERMES: Towards an Integrated Toolbox to Characterize Functional and Effective Brain Connectivity

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

Selección de métodos estadísticos para la interpretación de intercomparaciones en ensayos de áridos para hormigón, mortero y balasto

El objeto del proyecto es determinar los métodos estadísticos adecuados para la evaluación de los resultados de un ejercicio de intercomparación entre laboratorios para ensayos de aptitud de áridos para hormigón, mortero y balasto. Los ensayos estudiados son los aludidos en la norma UNE-EN 12620:2002 de áridos para hormigón, UNE-EN 13139:2003 para mortero, y UNE-EN 13450:2003 para balasto, que pueden clasificarse según las propiedades a determinar: - Geométricas - Mecánicas y Físicas - Térmicas y de Alteración - Químicas Los criterios aplicables para el desarrollo de los trabajos son los exigidos por la Entidad Nacional de Acreditación (ENAC) para laboratorios acreditados conforme a la Norma UNE-EN ISO/IEC 17025 y para proveedores acreditados conforme a la Norma UNE-EN ISO/IEC 17043. ABSTRACT The purpose of the project is to determine the appropriate statistical methods to evaluate the results of an intercomparison exercise among laboratories for proficiency testing of aggregates for concrete, mortar and ballast. The studied assays are mentioned in the UNE-EN 12620:2002 standard of aggregates for concrete, UNE-EN 13139:2003 for mortar, and UNE-EN 13450:2003 for ballast, which can be classified according to the properties to determine: - Geometric - Mechanical and Physical - Thermal and Alteration - Chemical The criteria for the development of the work are those required by the National Accreditation Body (ENAC) for laboratories accredited according to the UNE-EN ISO / IEC 17025 and for suppliers according to the UNE-EN ISO / IEC 17043.

Detección de patrones y anomalías espectrales del terreno mediante espectrometría de imagen de alta resolución : reconocimiento, optimización y evaluación multiescenario

El objeto de esta Tesis doctoral es el desarrollo de una metodologia para la deteccion automatica de anomalias a partir de datos hiperespectrales o espectrometria de imagen, y su cartografiado bajo diferentes condiciones tipologicas de superficie y terreno. La tecnologia hiperespectral o espectrometria de imagen ofrece la posibilidad potencial de caracterizar con precision el estado de los materiales que conforman las diversas superficies en base a su respuesta espectral. Este estado suele ser variable, mientras que las observaciones se producen en un numero limitado y para determinadas condiciones de iluminacion. Al aumentar el numero de bandas espectrales aumenta tambien el numero de muestras necesarias para definir espectralmente las clases en lo que se conoce como Maldicion de la Dimensionalidad o Efecto Hughes (Bellman, 1957), muestras habitualmente no disponibles y costosas de obtener, no hay mas que pensar en lo que ello implica en la Exploracion Planetaria. Bajo la definicion de anomalia en su sentido espectral como la respuesta significativamente diferente de un pixel de imagen respecto de su entorno, el objeto central abordado en la Tesis estriba primero en como reducir la dimensionalidad de la informacion en los datos hiperespectrales, discriminando la mas significativa para la deteccion de respuestas anomalas, y segundo, en establecer la relacion entre anomalias espectrales detectadas y lo que hemos denominado anomalias informacionales, es decir, anomalias que aportan algun tipo de informacion real de las superficies o materiales que las producen. En la deteccion de respuestas anomalas se asume un no conocimiento previo de los objetivos, de tal manera que los pixeles se separan automaticamente en funcion de su informacion espectral significativamente diferenciada respecto de un fondo que se estima, bien de manera global para toda la escena, bien localmente por segmentacion de la imagen. La metodologia desarrollada se ha centrado en la implicacion de la definicion estadistica del fondo espectral, proponiendo un nuevo enfoque que permite discriminar anomalias respecto fondos segmentados en diferentes grupos de longitudes de onda del espectro, explotando la potencialidad de separacion entre el espectro electromagnetico reflectivo y emisivo. Se ha estudiado la eficiencia de los principales algoritmos de deteccion de anomalias, contrastando los resultados del algoritmo RX (Reed and Xiaoli, 1990) adoptado como estandar por la comunidad cientifica, con el metodo UTD (Uniform Targets Detector), su variante RXD-UTD, metodos basados en subespacios SSRX (Subspace RX) y metodo basados en proyecciones de subespacios de imagen, como OSPRX (Orthogonal Subspace Projection RX) y PP (Projection Pursuit). Se ha desarrollado un nuevo metodo, evaluado y contrastado por los anteriores, que supone una variacion de PP y describe el fondo espectral mediante el analisis discriminante de bandas del espectro electromagnetico, separando las anomalias con el algortimo denominado Detector de Anomalias de Fondo Termico o DAFT aplicable a sensores que registran datos en el espectro emisivo. Se han evaluado los diferentes metodos de deteccion de anomalias en rangos del espectro electromagnetico del visible e infrarrojo cercano (Visible and Near Infrared-VNIR), infrarrojo de onda corta (Short Wavelenght Infrared-SWIR), infrarrojo medio (Meadle Infrared-MIR) e infrarrojo termico (Thermal Infrared-TIR). La respuesta de las superficies en las distintas longitudes de onda del espectro electromagnetico junto con su entorno, influyen en el tipo y frecuencia de las anomalias espectrales que puedan provocar. Es por ello que se han utilizado en la investigacion cubos de datos hiperepectrales procedentes de los sensores aeroportados cuya estrategia y diseno en la construccion espectrometrica de la imagen difiere. Se han evaluado conjuntos de datos de test de los sensores AHS (Airborne Hyperspectral System), HyMAP Imaging Spectrometer, CASI (Compact Airborne Spectrographic Imager), AVIRIS (Airborne Visible Infrared Imaging Spectrometer), HYDICE (Hyperspectral Digital Imagery Collection Experiment) y MASTER (MODIS/ASTER Simulator). Se han disenado experimentos sobre ambitos naturales, urbanos y semiurbanos de diferente complejidad. Se ha evaluado el comportamiento de los diferentes detectores de anomalias a traves de 23 tests correspondientes a 15 areas de estudio agrupados en 6 espacios o escenarios: Urbano - E1, Semiurbano/Industrial/Periferia Urbana - E2, Forestal - E3, Agricola - E4, Geologico/Volcanico - E5 y Otros Espacios Agua, Nubes y Sombras - E6. El tipo de sensores evaluados se caracteriza por registrar imagenes en un amplio rango de bandas, estrechas y contiguas, del espectro electromagnetico. La Tesis se ha centrado en el desarrollo de tecnicas que permiten separar y extraer automaticamente pixeles o grupos de pixeles cuya firma espectral difiere de manera discriminante de las que tiene alrededor, adoptando para ello como espacio muestral parte o el conjunto de las bandas espectrales en las que ha registrado radiancia el sensor hiperespectral. Un factor a tener en cuenta en la investigacion ha sido el propio instrumento de medida, es decir, la caracterizacion de los distintos subsistemas, sensores imagen y auxiliares, que intervienen en el proceso. Para poder emplear cuantitativamente los datos medidos ha sido necesario definir las relaciones espaciales y espectrales del sensor con la superficie observada y las potenciales anomalias y patrones objetivos de deteccion. Se ha analizado la repercusion que en la deteccion de anomalias tiene el tipo de sensor, tanto en su configuracion espectral como en las estrategias de diseno a la hora de registrar la radiacion prodecente de las superficies, siendo los dos tipos principales de sensores estudiados los barredores o escaneres de espejo giratorio (whiskbroom) y los barredores o escaneres de empuje (pushbroom). Se han definido distintos escenarios en la investigacion, lo que ha permitido abarcar una amplia variabilidad de entornos geomorfologicos y de tipos de coberturas, en ambientes mediterraneos, de latitudes medias y tropicales. En resumen, esta Tesis presenta una tecnica de deteccion de anomalias para datos hiperespectrales denominada DAFT en su variante de PP, basada en una reduccion de la dimensionalidad proyectando el fondo en un rango de longitudes de onda del espectro termico distinto de la proyeccion de las anomalias u objetivos sin firma espectral conocida. La metodologia propuesta ha sido probada con imagenes hiperespectrales reales de diferentes sensores y en diferentes escenarios o espacios, por lo tanto de diferente fondo espectral tambien, donde los resultados muestran los beneficios de la aproximacion en la deteccion de una gran variedad de objetos cuyas firmas espectrales tienen suficiente desviacion respecto del fondo. La tecnica resulta ser automatica en el sentido de que no hay necesidad de ajuste de parametros, dando resultados significativos en todos los casos. Incluso los objetos de tamano subpixel, que no pueden distinguirse a simple vista por el ojo humano en la imagen original, pueden ser detectados como anomalias. Ademas, se realiza una comparacion entre el enfoque propuesto, la popular tecnica RX y otros detectores tanto en su modalidad global como local. El metodo propuesto supera a los demas en determinados escenarios, demostrando su capacidad para reducir la proporcion de falsas alarmas. Los resultados del algoritmo automatico DAFT desarrollado, han demostrado la mejora en la definicion cualitativa de las anomalias espectrales que identifican a entidades diferentes en o bajo superficie, reemplazando para ello el modelo clasico de distribucion normal con un metodo robusto que contempla distintas alternativas desde el momento mismo de la adquisicion del dato hiperespectral. Para su consecucion ha sido necesario analizar la relacion entre parametros biofisicos, como la reflectancia y la emisividad de los materiales, y la distribucion espacial de entidades detectadas respecto de su entorno. Por ultimo, el algoritmo DAFT ha sido elegido como el mas adecuado para sensores que adquieren datos en el TIR, ya que presenta el mejor acuerdo con los datos de referencia, demostrando una gran eficacia computacional que facilita su implementacion en un sistema de cartografia que proyecte de forma automatica en un marco geografico de referencia las anomalias detectadas, lo que confirma un significativo avance hacia un sistema en lo que se denomina cartografia en tiempo real. The aim of this Thesis is to develop a specific methodology in order to be applied in automatic detection anomalies processes using hyperspectral data also called hyperspectral scenes, and to improve the classification processes. Several scenarios, areas and their relationship with surfaces and objects have been tested. The spectral characteristics of reflectance parameter and emissivity in the pattern recognition of urban materials in several hyperspectral scenes have also been tested. Spectral ranges of the visible-near infrared (VNIR), shortwave infrared (SWIR) and thermal infrared (TIR) from hyperspectral data cubes of AHS (Airborne Hyperspectral System), HyMAP Imaging Spectrometer, CASI (Compact Airborne Spectrographic Imager), AVIRIS (Airborne Visible Infrared Imaging Spectrometer), HYDICE (Hyperspectral Digital Imagery Collection Experiment) and MASTER (MODIS/ASTER Simulator) have been used in this research. It is assumed that there is not prior knowledge of the targets in anomaly detection. Thus, the pixels are automatically separated according to their spectral information, significantly differentiated with respect to a background, either globally for the full scene, or locally by the image segmentation. Several experiments on different scenarios have been designed, analyzing the behavior of the standard RX anomaly detector and different methods based on subspace, image projection and segmentation-based anomaly detection methods. Results and their consequences in unsupervised classification processes are discussed. Detection of spectral anomalies aims at extracting automatically pixels that show significant responses in relation of their surroundings. This Thesis deals with the unsupervised technique of target detection, also called anomaly detection. Since this technique assumes no prior knowledge about the target or the statistical characteristics of the data, the only available option is to look for objects that are differentiated from the background. Several methods have been developed in the last decades, allowing a better understanding of the relationships between the image dimensionality and the optimization of search procedures as well as the subpixel differentiation of the spectral mixture and its implications in anomalous responses. In other sense, image spectrometry has proven to be efficient in the characterization of materials, based on statistical methods using a specific reflection and absorption bands. Spectral configurations in the VNIR, SWIR and TIR have been successfully used for mapping materials in different urban scenarios. There has been an increasing interest in the use of high resolution data (both spatial and spectral) to detect small objects and to discriminate surfaces in areas with urban complexity. This has come to be known as target detection which can be either supervised or unsupervised. In supervised target detection, algorithms lean on prior knowledge, such as the spectral signature. The detection process for matching signatures is not straightforward due to the complications of converting data airborne sensor with material spectra in the ground. This could be further complicated by the large number of possible objects of interest, as well as uncertainty as to the reflectance or emissivity of these objects and surfaces. An important objective in this research is to establish relationships that allow linking spectral anomalies with what can be called informational anomalies and, therefore, identify information related to anomalous responses in some places rather than simply spotting differences from the background. The development in recent years of new hyperspectral sensors and techniques, widen the possibilities for applications in remote sensing of the Earth. Remote sensing systems measure and record electromagnetic disturbances that the surveyed objects induce in their surroundings, by means of different sensors mounted on airborne or space platforms. Map updating is important for management and decisions making people, because of the fast changes that usually happen in natural, urban and semi urban areas. It is necessary to optimize the methodology for obtaining the best from remote sensing techniques from hyperspectral data. The first problem with hyperspectral data is to reduce the dimensionality, keeping the maximum amount of information. Hyperspectral sensors augment considerably the amount of information, this allows us to obtain a better precision on the separation of material but at the same time it is necessary to calculate a bigger number of parameters, and the precision lowers with the increase in the number of bands. This is known as the Hughes effects (Bellman, 1957) . Hyperspectral imagery allows us to discriminate between a huge number of different materials however some land and urban covers are made up with similar material and respond similarly which produces confusion in the classification. The training and the algorithm used for mapping are also important for the final result and some properties of thermal spectrum for detecting land cover will be studied. In summary, this Thesis presents a new technique for anomaly detection in hyperspectral data called DAFT, as a PP's variant, based on dimensionality reduction by projecting anomalies or targets with unknown spectral signature to the background, in a range thermal spectrum wavelengths. The proposed methodology has been tested with hyperspectral images from different imaging spectrometers corresponding to several places or scenarios, therefore with different spectral background. The results show the benefits of the approach to the detection of a variety of targets whose spectral signatures have sufficient deviation in relation to the background. DAFT is an automated technique in the sense that there is not necessary to adjust parameters, providing significant results in all cases. Subpixel anomalies which cannot be distinguished by the human eye, on the original image, however can be detected as outliers due to the projection of the VNIR end members with a very strong thermal contrast. Furthermore, a comparison between the proposed approach and the well-known RX detector is performed at both modes, global and local. The proposed method outperforms the existents in particular scenarios, demonstrating its performance to reduce the probability of false alarms. The results of the automatic algorithm DAFT have demonstrated improvement in the qualitative definition of the spectral anomalies by replacing the classical model by the normal distribution with a robust method. For their achievement has been necessary to analyze the relationship between biophysical parameters such as reflectance and emissivity, and the spatial distribution of detected entities with respect to their environment, as for example some buried or semi-buried materials, or building covers of asbestos, cellular polycarbonate-PVC or metal composites. Finally, the DAFT method has been chosen as the most suitable for anomaly detection using imaging spectrometers that acquire them in the thermal infrared spectrum, since it presents the best results in comparison with the reference data, demonstrating great computational efficiency that facilitates its implementation in a mapping system towards, what is called, Real-Time Mapping.

HERMES: towards an integrated toolbox to characterize functional and effective brain connectivity

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

Desarrollo de un Laboratorio Virtual para la realización de e-comparisons en los ensayos de aislamiento acústico de fachadas según UNE-EN ISO 140-5

Actualmente son una práctica común los procesos de normalización de métodos de ensayo y acreditación de laboratorios, ya que permiten una evaluación de los procedimientos llevados a cabo por profesionales de un sector tecnológico y además permiten asegurar unos mínimos de calidad en los resultados finales. En el caso de los laboratorios de acústica, para conseguir y mantener la acreditación de un laboratorio es necesario participar activamente en ejercicios de intercomparación, utilizados para asegurar la calidad de los métodos empleados. El inconveniente de estos ensayos es el gran coste que suponen para los laboratorios, siendo en ocasiones inasumible por estos teniendo que renunciar a la acreditación. Este Proyecto Fin de Grado se centrará en el desarrollo de un Laboratorio Virtual implementado mediante una herramienta software que servirá para realizar ejercicios de intercomparación no presenciales, ampliando de ese modo el concepto e-comparison y abriendo las bases a que en un futuro este tipo de ejercicios no presenciales puedan llegar a sustituir a los llevados a cabo actualmente. En el informe primero se hará una pequeña introducción, donde se expondrá la evolución y la importancia de los procedimientos de calidad acústica en la sociedad actual. A continuación se comentará las normativas internacionales en las que se soportará el proyecto, la norma ISO 145-5, así como los métodos matemáticos utilizados en su implementación, los métodos estadísticos de propagación de incertidumbres especificados por la JCGM (Joint Committee for Guides in Metrology). Después, se hablará sobre la estructura del proyecto, tanto del tipo de programación utilizada en su desarrollo como la metodología de cálculo utilizada para conseguir que todas las funcionalidades requeridas en este tipo de ensayo estén correctamente implementadas. Posteriormente se llevará a cabo una validación estadística basada en la comparación de unos datos generados por el programa, procesados utilizando la simulación de Montecarlo, y unos cálculos analíticos, que permita comprobar que el programa funciona tal y como se ha previsto en la fase de estudio teórico. También se realizará una prueba del programa, similar a la que efectuaría un técnico de laboratorio, en la que se evaluará la incertidumbre de la medida calculándola mediante el método tradicional, pudiendo comparar los datos obtenidos con los que deberían obtenerse. Por último, se comentarán las conclusiones obtenidas con el desarrollo y pruebas del Laboratorio Virtual, y se propondrán nuevas líneas de investigación futuras relacionadas con el concepto e-comparison y la implementación de mejoras al Laboratorio Virtual. ABSTRACT. Nowadays it is common practise to make procedures to normalise trials methods standards and laboratory accreditations, as they allow for the evaluation of the procedures made by professionals from a particular technological sector in addition to ensuring a minimum quality in the results. In order for an acoustics laboratory to achieve and maintain the accreditation it is necessary to actively participate in the intercomparison exercises, since these are used to assure the quality of the methods used by the technicians. Unfortunately, the high cost of these trials is unaffordable for many laboratories, which then have to renounce to having the accreditation. This Final Project is focused on the development of a Virtual Laboratory implemented by a software tool that it will be used for making non-attendance intercomparison trials, widening the concept of e-comparison and opening the possibility for using this type of non-attendance trials instead of the current ones. First, as a short introduction, I show the evolution and the importance today of acoustic quality procedures. Second, I will discuss the international standards, such as ISO 145-5, as well the mathematic and statistical methods of uncertainty propagation specified by the Joint Committee for Guides in Metrology, that are used in the Project. Third, I speak about the structure of the Project, as well as the programming language structure and the methodology used to get the different features needed in this acoustic trial. Later, a statistical validation will be carried out, based on comparison of data generated by the program, processed using a Montecarlo simulation, and analytical calculations to verify that the program works as planned in the theoretical study. There will also be a test of the program, similar to one that a laboratory technician would carry out, by which the uncertainty in the measurement will be compared to a traditional calculation method so as to compare the results. Finally, the conclusions obtained with the development and testing of the Virtual Laboratory will be discussed, new research paths related to e-comparison definition and the improvements for the Laboratory will be proposed.

Three-dimensional spatial distribution of synapses in the neocortex: A dual-beam electron microscopy study

In the cerebral cortex, most synapses are found in the neuropil, but relatively little is known about their 3-dimensional organization. Using an automated dual-beam electron microscope that combines focused ion beam milling and scanning electron microscopy, we have been able to obtain 10 three-dimensional samples with an average volume of 180 µm(3) from the neuropil of layer III of the young rat somatosensory cortex (hindlimb representation). We have used specific software tools to fully reconstruct 1695 synaptic junctions present in these samples and to accurately quantify the number of synapses per unit volume. These tools also allowed us to determine synapse position and to analyze their spatial distribution using spatial statistical methods. Our results indicate that the distribution of synaptic junctions in the neuropil is nearly random, only constrained by the fact that synapses cannot overlap in space. A theoretical model based on random sequential absorption, which closely reproduces the actual distribution of synapses, is also presented.

Comparison of Airborne Laser Scanning Methods for Estimating Forest Structure Indicators Based on Lorenz Curves

The purpose of this study was to compare a number of state-of-the-art methods in airborne laser scan- ning (ALS) remote sensing with regards to their capacity to describe tree size inequality and other indi- cators related to forest structure. The indicators chosen were based on the analysis of the Lorenz curve: Gini coefficient ( GC ), Lorenz asymmetry ( LA ), the proportions of basal area ( BALM ) and stem density ( NSLM ) stocked above the mean quadratic diameter. Each method belonged to one of these estimation strategies: (A) estimating indicators directly; (B) estimating the whole Lorenz curve; or (C) estimating a complete tree list. Across these strategies, the most popular statistical methods for area-based approach (ABA) were used: regression, random forest (RF), and nearest neighbour imputation. The latter included distance metrics based on either RF (NN–RF) or most similar neighbour (MSN). In the case of tree list esti- mation, methods based on individual tree detection (ITD) and semi-ITD, both combined with MSN impu- tation, were also studied. The most accurate method was direct estimation by best subset regression, which obtained the lowest cross-validated coefficients of variation of their root mean squared error CV(RMSE) for most indicators: GC (16.80%), LA (8.76%), BALM (8.80%) and NSLM (14.60%). Similar figures [CV(RMSE) 16.09%, 10.49%, 10.93% and 14.07%, respectively] were obtained by MSN imputation of tree lists by ABA, a method that also showed a number of additional advantages, such as better distributing the residual variance along the predictive range. In light of our results, ITD approaches may be clearly inferior to ABA with regards to describing the structural properties related to tree size inequality in for- ested areas.

Análisis fundamental aplicado a la industria minera : un estudio multivariante

Este trabajo tiene por objeto aplicar los principios del Value Investing a veinticuatro empresas del sector minero y definir las claves para extrapolar, en base a un análisis fundamental, una calificación para cada una de las empresas. Con este fin, se ha realizado un estudio estadístico multivariante para comparar las correlaciones existentes entre cada ratio fundamental y su evolución en bolsa a uno, tres y cinco años vista. Para procesar los datos se han utilizado los programas MATLAB y EXCEL. Sobre ellos se ha planteado una Matriz de Correlaciones de Pearson y un estudio de dispersión por cruce de pares. El análisis demostró que es posible aplicar la metodología del Value Investing a empresas del sector minero con resultados positivos aunque, el ajuste de las correlaciones, sugiere utilizar series temporales más largas y un mayor número de empresas para ganar fiabilidad en el contraste de estas hipótesis. De los estudios realizados, se deduce que unos buenos fundamentales influyen, de manera notable, a la revalorización bursátil a 3 y 5 años destacando, además, que el ajuste es mejor cuanto mayor sea este tiempo. Abstract This study aims to apply the principles of Value Investing to twenty four mining companies and, based on this fundamental study, develop a rating to classify those companies. For this purpose, we have performed a multivariate statistical study to compare the correlations between each fundamental ratio and its stock revalorization for one, three and five years. MATLAB and EXCEL have been used to process data. The statistical methods used are Pearson Matrix of Correlations and a Cross Pairs Scattering Study. The analysis showed that it is possible to apply the methodology of Value Investing to mining companies, although, the adjustment of correlations suggests using longer time series and a larger amount of companies to test these hypothesis. From the studies performed, it follows that good fundamentals significantly influence the stock market value at 3 and 5 years, noting that, the larger the period under study, the better the fit.

Análisis paramétrico determinista y aleatorio de problemas dinámicos en estructuras aeroespaciales

Los fenómenos dinámicos pueden poner en peligro la integridad de estructuras aeroespaciales y los ingenieros han desarrollado diferentes estrategias para analizarlos. Uno de los grandes problemas que se plantean en la ingeniería es cómo atacar un problema dinámico estructural. En la presente tesis se plantean distintos fenómenos dinámicos y se proponen métodos para estimar o simular sus comportamientos mediante un análisis paramétrico determinista y aleatorio del problema. Se han propuesto desde problemas sencillos con pocos grados de libertad que sirven para analizar las diferentes estrategias y herramientas a utilizar, hasta fenómenos muy dinámicos que contienen comportamientos no lineales, daños y fallos. Los primeros ejemplos de investigación planteados cubren una amplia gama de los fenómenos dinámicos, como el análisis de vibraciones de elementos másicos, incluyendo impactos y contactos, y el análisis de una viga con carga armónica aplicada a la que también se le añaden parámetros aleatorios que pueden responder a un desconocimiento o incertidumbre de los mismos. Durante el desarrollo de la tesis se introducen conceptos y se aplican distintos métodos, como el método de elementos finitos (FEM) en el que se analiza su resolución tanto por esquemas implícitos como explícitos, y métodos de análisis paramétricos y estadísticos mediante la técnica de Monte Carlo. Más adelante, una vez ya planteadas las herramientas y estrategias de análisis, se estudian fenómenos más complejos, como el impacto a baja velocidad en materiales compuestos, en el que se busca evaluar la resistencia residual y, por lo tanto, la tolerancia al daño de la estructura. Se trata de un suceso que puede producirse por la caída de herramienta, granizo o restos en la pista de aterrizaje. Otro de los fenómenos analizados también se da en un aeropuerto y se trata de la colisión con un dispositivo frangible, el cual tiene que romperse bajo ciertas cargas y, sin embargo, soportar otras. Finalmente, se aplica toda la metodología planteada en simular y analizar un posible incidente en vuelo, el fenómeno de la pérdida de pala de un turbohélice. Se trata de un suceso muy particular en el que la estructura tiene que soportar unas cargas complejas y excepcionales con las que la aeronave debe ser capaz de completar con éxito el vuelo. El análisis incluye comportamientos no lineales, daños, y varios tipos de fallos, y en el que se trata de identificar los parámetros clave en la secuencia del fallo. El suceso se analiza mediante análisis estructurales deterministas más habituales y también mediante otras técnicas como el método de Monte Carlo con el que se logran estudiar distintas incertidumbres en los parámetros con variables aleatorias. Se estudian, entre otros, el tamaño de pala perdida, la velocidad y el momento en el que se produce la rotura, y la rigidez y resistencia de los apoyos del motor. Se tiene en cuenta incluso el amortiguamiento estructural del sistema. Las distintas estrategias de análisis permiten obtener unos resultados valiosos e interesantes que han sido objeto de distintas publicaciones. ABSTRACT Dynamic phenomena can endanger the integrity of aerospace structures and, consequently, engineers have developed different strategies to analyze them. One of the major engineering problems is how to deal with the structural dynamics. In this thesis, different dynamic phenomena are introduced and several methods are proposed to estimate or simulate their behaviors. The analysis is considered through parametric, deterministic and statistical methods. The suggested issues are from simple problems with few degrees of freedom, in order to develop different strategies and tools to solve them, to very dynamic phenomena containing nonlinear behaviors failures, damages. The first examples cover a wide variety of dynamic phenomena such as vibration analysis of mass elements, including impacts and contacts, and beam analysis with harmonic load applied, in which random parameters are included. These parameters can represent the unawareness or uncertainty of certain variables. During the development of the thesis several concepts are introduced and different methods are applied, such as the finite element method (FEM), which is solved through implicit and explicit schemes, and parametrical and statistical methods using the Monte Carlo analysis technique. Next, once the tools and strategies of analysis are set out more complex phenomena are studied. This is the case of a low-speed impact in composite materials, the residual strength of the structure is evaluated, and therefore, its damage tolerance. This incident may occur from a tool dropped, hail or debris throw on the runway. At an airport may also occur, and it is also analyzed, a collision between an airplane and a frangible device. The devise must brake under these loads, however, it must withstand others. Finally, all the considered methodology is applied to simulate and analyze a flight incident, the blade loss phenomenon of a turboprop. In this particular event the structure must support complex and exceptional loads and the aircraft must be able to successfully complete the flight. Nonlinear behavior, damage, and different types of failures are included in the analysis, in which the key parameters in the failure sequence are identified. The incident is analyzed by deterministic structural analysis and also by other techniques such as Monte Carlo method, in which it is possible to include different parametric uncertainties through random variables. Some of the evaluated parameters are, among others, the blade loss size, propeller rotational frequency, speed and angular position where the blade is lost, and the stiffness and strength of the engine mounts. The study does also research on the structural damping of the system. The different strategies of analysis obtain valuable and interesting results that have been already published.

Health monitoring of a new hysteretic damper subjected to earthquakes on a shaking table

This paper presents the experimental results obtained by applying frequency-domain structural health monitoring techniques to assess the damage suffered on a special type of damper called Web Plastifying Damper (WPD). The WPD is a hysteretic type energy dissipator recently developed for the passive control of structures subjected to earthquakes. It consists of several I-section steel segments connected in parallel. The energy is dissipated through plastic deformations of the web of the I-sections, which constitute the dissipative parts of the damper. WPDs were subjected to successive histories of dynamically-imposed cyclic deformations of increasing magnitude with the shaking table of the University of Granada. To assess the damage to the web of the I-section steel segments after each history of loading, a new damage index called Area Index of Damage (AID) was obtained from simple vibration tests. The vibration signals were acquired by means of piezoelectric sensors attached on the I-sections, and non-parametric statistical methods were applied to calculate AID in terms of changes in frequency response functions. The damage index AID was correlated with another energy-based damage index-ID- which past research has proven to accurately characterize the level of mechanical damage. The ID is rooted in the decomposition of the load-displacement curve experienced by the damper into the so-called skeleton and Bauschinger parts. ID predicts the level of damage and the proximity to failure of the damper accurately, but it requires costly instrumentation. The experiments reported in this paper demonstrate a good correlation between AID and ID in a realistic seismic loading scenario consisting of dynamically applied arbitrary cyclic loads. Based on this correlation, it is possible to estimate ID indirectly from the AID, which calls for much simpler and less expensive instrumentation.

Aggregation and disaggregation of senile plaques in Alzheimer disease

We quantitatively analyzed, using laser scanning confocal microscopy, the three-dimensional structure of individual senile plaques in Alzheimer disease. We carried out the quantitative analysis using statistical methods to gain insights about the processes that govern Aβ peptide deposition. Our results show that plaques are complex porous structures with characteristic pore sizes. We interpret plaque morphology in the context of a new dynamical model based on competing aggregation and disaggregation processes in kinetic steady-state equilibrium with an additional diffusion process allowing Aβ deposits to diffuse over the surface of plaques.

A first trial of retrospective collaboration for positional cloning in complex inheritance: Assay of the cytokine region on chromosome 5 by the Consortium on Asthma Genetics (COAG)

The central problem of complex inheritance is to map oligogenes for disease susceptibility, integrating linkage and association over samples that differ in several ways. Combination of evidence over multiple samples with 1,037 families supports loci contributing to asthma susceptibility in the cytokine region on 5q [maximum logarithm of odds (lod) = 2.61 near IL-4], but no evidence for atopy. The principal problems with retrospective collaboration on linkage appear to have been solved, providing far more information than a single study. A multipoint lod table evaluated at commonly agreed reference loci is required for both collaboration and metaanalysis, but variations in ascertainment, pedigree structure, phenotype definition, and marker selection are tolerated. These methods are invariant with statistical methods that increase the power of lods and are applicable to all diseases, motivating collaboration rather than competition. In contrast to linkage, positional cloning by allelic association has yet to be extended to multiple samples, a prerequisite for efficient combination with linkage and the greatest current challenge to genetic epidemiology.

Analysis and interpretation of cost data in randomised controlled trials: review of published studies

Objective To review critically the statistical methods used for health economic evaluations in randomised controlled trials where an estimate of cost is available for each patient in the study.

Estimation of divergence times from multiprotein sequences for a few mammalian species and several distantly related organisms

When many protein sequences are available for estimating the time of divergence between two species, it is customary to estimate the time for each protein separately and then use the average for all proteins as the final estimate. However, it can be shown that this estimate generally has an upward bias, and that an unbiased estimate is obtained by using distances based on concatenated sequences. We have shown that two concatenation-based distances, i.e., average gamma distance weighted with sequence length (d2) and multiprotein gamma distance (d3), generally give more satisfactory results than other concatenation-based distances. Using these two distance measures for 104 protein sequences, we estimated the time of divergence between mice and rats to be approximately 33 million years ago. Similarly, the time of divergence between humans and rodents was estimated to be approximately 96 million years ago. We also investigated the dependency of time estimates on statistical methods and various assumptions made by using sequence data from eubacteria, protists, plants, fungi, and animals. Our best estimates of the times of divergence between eubacteria and eukaryotes, between protists and other eukaryotes, and between plants, fungi, and animals were 3, 1.7, and 1.3 billion years ago, respectively. However, estimates of ancient divergence times are subject to a substantial amount of error caused by uncertainty of the molecular clock, horizontal gene transfer, errors in sequence alignments, etc.

Geoquímica multielementar de sedimentos de corrente no Estado de São Paulo: abordagem através da análise estatística multivariada

Este trabalho apresenta resultados geoquímicos multielementares de sedimentos de corrente no estado de São Paulo, obtidos através do projeto institucional do Serviço Geológico do Brasil denominado \"Levantamento Geoquímico de Baixa Densidade no Brasil\". Dados analíticos de 1422 amostras de sedimento de corrente obtidos por ICP-MS (Inductively Coupled Plasma Mass Spectrometry), para 32 elementos químicos (Al, Ba, Be, Ca, Ce, Co, Cr, Cs, Cu, Fe, Ga, Hf, K, La, Mg, Mn, Mo, Nb, Ni, P, Pb, Rb, Sc, Sn, Sr, Th, Ti, U, V, Y, Zn e Zr), foram processadas e abordadas através da análise estatística uni e multivariada. Os resultados do tratamento dos dados através de técnicas estatísticas univariadas forneceram os valores de background geoquímico (teor de fundo) dos 32 elementos para todo estado de São Paulo. A análise georreferenciada das distribuições geoquímicas unielementares evidenciaram a compartimentação geológica da área. As duas principais províncias geológicas do estado de São Paulo, Bacia do Paraná e Complexo Cristalino, se destacam claramente na maioria das distribuições geoquímicas. Unidades geológicas de maior expressão, como a Formação Serra Geral e o Grupo Bauru também foram claramente destacadas. Outras feições geoquímicas indicaram possíveis áreas contaminadas e unidades geológicas não cartografadas. Os resultados da aplicação de métodos estatísticos multivariados aos dados geoquímicos com 24 variáveis (Al, Ba, Ce, Co, Cr, Cs, Cu, Fe, Ga, La, Mn, Nb, Ni, Pb, Rb, Sc, Sr, Th, Ti, U, V, Y, Zn e Zr) permitiram definir as principais assinaturas e associações geoquímicas existentes em todo estado de São Paulo e correlacioná-las aos principais domínios litológicos. A análise de agrupamentos em modo Q forneceu oito grupos de amostras geoquimicamente correlacionáveis, que georreferenciadas reproduziram os principais compartimentos geológicos do estado: Complexo Cristalino, Grupos Itararé e Passa Dois, Formação Serra Geral e Grupos Bauru e Caiuá. A análise discriminante multigrupos comprovou, estatisticamente, a classificação dos grupos formados pela análise de agrupamentos e forneceu as principais variáveis discriminantes: Fe, Co, Sc, V e Cu. A análise de componentes principais, abordada em conjunto com a análise fatorial pelo método de rotação varimax, forneceram os principais fatores multivariados e suas respectivas associações elementares. O georreferenciamento dos valores de escores fatoriais multivariados delimitaram as áreas onde as associações elementares ocorrem e forneceram mapas multivariados para todo o estado. Por fim, conclui-se que os métodos estatísticos aplicados são indispensáveis no tratamento, apresentação e interpretação de dados geoquímicos. Ademais, com base em uma visão integrada dos resultados obtidos, este trabalho recomenda: (1) a execução dos levantamentos geoquímicos de baixa densidade em todo país em caráter de prioridade, pois são altamente eficazes na definição de backgrounds regionais e delimitação de províncias geoquímicas com interesse metalogenético e ambiental; (2) a execução do mapeamento geológico contínuo em escala adequada (maiores que 1:100.000) em áreas que apontam para possíveis existências de unidades não cartografadas nos mapas geológicos atuais.