Desarrollo de un programa piloto a nivel nacional de mejora genética en dorada (Sparus aurata L.) : estimación de parámetros genéticos de caracteres de crecimiento y calidad e interacción genotipo ambiente

[ES] En este estudio, se ha protocolizado la metodología que permite la integración de la selección genética bajo los condicionantes propios del sistema de producción de dorada (Sparus aurata L.) poniéndola en práctica a nivel nacional en colaboración con seis empresas españolas. Se criaron peces descendientes de tres lotes industriales (ICCM: Canarias, CULMASUR S.A.: Andalucía, PISCIMAR S.L.: Valencia), marcados con Passive Integrated Transponder (PIT) y mezclados, en las instalaciones de cuatro centros de investigación y cuatro empresas (ICCM y CANEXMAR S.L.: Canarias; IFAPA y PIM S.A.: Andalucía; IRTA y CULTIMAR S.A.: Cataluña; IMIDA y SERVICIOS ATUNEROS DEL MEDITERRÁNEO: Murcia). Se realizaron muestreos de crecimiento de manera simultánea en las cuatro comunidades autónomas (179, 269, 389 y 539 días), además de un muestreo final de sacrificio (689 días) a talla ración donde se valoraron nuevas e importantes variables fenotípicas, tras unificar criterios. Para la determinación de las relaciones parentales-filiales se pusieron a punto nuevas PCRs múltiplex con marcadores microsatélites del mapa de dorada.

Estimación de parámetros genéticos en corvina, Argysomus regius, para caracteres de rendimiento y calidad de la carne y del pez.

Programa de doctorado: Acuicultura: producción controlada de animales acuáticos

Factores genéticos y ambientales relacionados con la génesis de cáncer vesical

[ES] Antecedentes: La exposición a sustancias químicas es uno de los factores de riesgo más conocidos y relevantes del cáncer vesical (CaV). Asimismo los factores reguladores de la proliferación celular (como los Insulin-like growth factors- IGF) y la expresión de genes involucrados en la transformación de xenobióticos y en la angiogénesis y proliferación celular, parecen ser factores relevantes en la etiología del CaV. Objetivo: Evaluar la relevancia de los hábitos de vida, la exposición a contaminantes ambientales (y factores de crecimiento celular relacionados) y las características genéticas de la población canaria como factores de riesgo de cáncer vesical en un estudio de casos y controles hospitalarios desarrollado en el Complejo Hospitalario Insular Materno Infantil de Gran Canaria.

La biología de la conservación de vegetales. El enfoque genético. ¿Qué puede aportar a la conservación de la biodiversidad?

[ES] Dentro del contexto de la Biología de la Conservación de especies, los principios y la base de la conservación de la diversidad genética o sencillamente de la conservación genética está alcanzando de forma general, una importancia muy relevante en los últimos años. La genética de poblaciones y sus técnicas y algoritmos, están proporcionando a la ciencia de la conservación una precisión de análisis sin precedente, que se basa fundamentalmente en el mantenimiento del potencial adaptativo de las especies, especialmente en el contexto actual de cambio climático. También proporciona una base teórica que contribuye a entender los mecanismos que dan lugar a los cambios evolutivos y afectan el patrón genético observado en las poblaciones naturales y restituidas contribuyendo a proporcionar guías de manejo para aplicarse en los taxones amenazados. Pero además, la genética participa en un concepto integrado de conservación de la biodiversidad necesario para definir los métodos, concretar los objetivos e identificar las prioridades requeridas en cada programa de conservación y recuperación. No obstante, la importancia de los factores genéticos en la conservación de una especie, especialmente a gran escala, permanece hoy día como una cuestión abierta, existiendo un importante debate respecto a su importancia relativa y su auténtica contribución en la Biología de la Conservación y en la elaboración y ejecución de planes de conservación y recuperación de especies amenazadas.

Capacidad de obtener beneficio de reglas técnicas de contratación basadas en algoritmos de minería de datos

Trabajo Fin de Grado de la doble titulación de Grado en Ingeniería Informática y Grado en Administración y Dirección de Empresas.

Parameterschätzung in zeitdiskreten ergodischen Markov-Prozessen am Beispiel des Cox-Ingersoll-Ross-Modells

In dieser Arbeit geht es um die Schätzung von Parametern in zeitdiskreten ergodischen Markov-Prozessen im allgemeinen und im CIR-Modell im besonderen. Beim CIR-Modell handelt es sich um eine stochastische Differentialgleichung, die von Cox, Ingersoll und Ross (1985) zur Beschreibung der Dynamik von Zinsraten vorgeschlagen wurde. Problemstellung ist die Schätzung der Parameter des Drift- und des Diffusionskoeffizienten aufgrund von äquidistanten diskreten Beobachtungen des CIR-Prozesses. Nach einer kurzen Einführung in das CIR-Modell verwenden wir die insbesondere von Bibby und Sørensen untersuchte Methode der Martingal-Schätzfunktionen und -Schätzgleichungen, um das Problem der Parameterschätzung in ergodischen Markov-Prozessen zunächst ganz allgemein zu untersuchen. Im Anschluss an Untersuchungen von Sørensen (1999) werden hinreichende Bedingungen (im Sinne von Regularitätsvoraussetzungen an die Schätzfunktion) für die Existenz, starke Konsistenz und asymptotische Normalität von Lösungen einer Martingal-Schätzgleichung angegeben. Angewandt auf den Spezialfall der Likelihood-Schätzung stellen diese Bedingungen zugleich lokal-asymptotische Normalität des Modells sicher. Ferner wird ein einfaches Kriterium für Godambe-Heyde-Optimalität von Schätzfunktionen angegeben und skizziert, wie dies in wichtigen Spezialfällen zur expliziten Konstruktion optimaler Schätzfunktionen verwendet werden kann. Die allgemeinen Resultate werden anschließend auf das diskretisierte CIR-Modell angewendet. Wir analysieren einige von Overbeck und Rydén (1997) vorgeschlagene Schätzer für den Drift- und den Diffusionskoeffizienten, welche als Lösungen quadratischer Martingal-Schätzfunktionen definiert sind, und berechnen das optimale Element in dieser Klasse. Abschließend verallgemeinern wir Ergebnisse von Overbeck und Rydén (1997), indem wir die Existenz einer stark konsistenten und asymptotisch normalen Lösung der Likelihood-Gleichung zeigen und lokal-asymptotische Normalität für das CIR-Modell ohne Einschränkungen an den Parameterraum beweisen.

Il gruppo delle trecce ed il teorema di Markov

Il lavoro concerne il gruppo delle trecce, il suo legame con i link e si concentra sui teoremi di Markov e Alexander.

Markov Constraints for Generating Texts with Style

This thesis addresses the issue of generating texts in the style of an existing author, that also satisfy structural constraints imposed by the genre of the text. Although Markov processes are known to be suitable for representing style, they are difficult to control in order to satisfy non-local properties, such as structural constraints, that require long distance modeling. The framework of Constrained Markov Processes allows to precisely generate texts that are consistent with a corpus, while being controllable in terms of rhymes and meter. Controlled Markov processes consist in reformulating Markov processes in the context of constraint satisfaction. The thesis describes how to represent stylistic and structural properties in terms of constraints in this framework and how this approach can be used for the generation of lyrics in the style of 60 differents authors An evaluation of the desctibed method is provided by comparing it to both pure Markov and pure constraint-based approaches. Finally the thesis describes the implementation of an augmented text editor, called Perec. Perec is intended to improve creativity, by helping the user to write lyrics and poetry, exploiting the techniques presented so far.

Ergodicity and regularity of invariant measure for branching Markov processes with immigration

In this thesis we consider systems of finitely many particles moving on paths given by a strong Markov process and undergoing branching and reproduction at random times. The branching rate of a particle, its number of offspring and their spatial distribution are allowed to depend on the particle's position and possibly on the configuration of coexisting particles. In addition there is immigration of new particles, with the rate of immigration and the distribution of immigrants possibly depending on the configuration of pre-existing particles as well. In the first two chapters of this work, we concentrate on the case that the joint motion of particles is governed by a diffusion with interacting components. The resulting process of particle configurations was studied by E. Löcherbach (2002, 2004) and is known as a branching diffusion with immigration (BDI). Chapter 1 contains a detailed introduction of the basic model assumptions, in particular an assumption of ergodicity which guarantees that the BDI process is positive Harris recurrent with finite invariant measure on the configuration space. This object and a closely related quantity, namely the invariant occupation measure on the single-particle space, are investigated in Chapter 2 where we study the problem of the existence of Lebesgue-densities with nice regularity properties. For example, it turns out that the existence of a continuous density for the invariant measure depends on the mechanism by which newborn particles are distributed in space, namely whether branching particles reproduce at their death position or their offspring are distributed according to an absolutely continuous transition kernel. In Chapter 3, we assume that the quantities defining the model depend only on the spatial position but not on the configuration of coexisting particles. In this framework (which was considered by Höpfner and Löcherbach (2005) in the special case that branching particles reproduce at their death position), the particle motions are independent, and we can allow for more general Markov processes instead of diffusions. The resulting configuration process is a branching Markov process in the sense introduced by Ikeda, Nagasawa and Watanabe (1968), complemented by an immigration mechanism. Generalizing results obtained by Höpfner and Löcherbach (2005), we give sufficient conditions for ergodicity in the sense of positive recurrence of the configuration process and finiteness of the invariant occupation measure in the case of general particle motions and offspring distributions.

Algoritmi e ricorsività: macchine di Turing e algoritmi di Markov

In questa questa tesi vengono presentate alcune delle più importanti definizioni di funzione computabile mediante un algoritmo: una prima descrizione è quella data tramite le funzioni ricorsive, un secondo approccio è dato in termini di macchine di Turing, infine, vengono considerati gli algoritmi di Markov. Si dimostra che tutte queste definizioni sono equivalenti. Completa la tesi un breve cenno al lambda-K-calcolo.

New markov chain based methods for single and cross-domain sentiment classification

Nowadays communication is switching from a centralized scenario, where communication media like newspapers, radio, TV programs produce information and people are just consumers, to a completely different decentralized scenario, where everyone is potentially an information producer through the use of social networks, blogs, forums that allow a real-time worldwide information exchange. These new instruments, as a result of their widespread diffusion, have started playing an important socio-economic role. They are the most used communication media and, as a consequence, they constitute the main source of information enterprises, political parties and other organizations can rely on. Analyzing data stored in servers all over the world is feasible by means of Text Mining techniques like Sentiment Analysis, which aims to extract opinions from huge amount of unstructured texts. This could lead to determine, for instance, the user satisfaction degree about products, services, politicians and so on. In this context, this dissertation presents new Document Sentiment Classification methods based on the mathematical theory of Markov Chains. All these approaches bank on a Markov Chain based model, which is language independent and whose killing features are simplicity and generality, which make it interesting with respect to previous sophisticated techniques. Every discussed technique has been tested in both Single-Domain and Cross-Domain Sentiment Classification areas, comparing performance with those of other two previous works. The performed analysis shows that some of the examined algorithms produce results comparable with the best methods in literature, with reference to both single-domain and cross-domain tasks, in $2$-classes (i.e. positive and negative) Document Sentiment Classification. However, there is still room for improvement, because this work also shows the way to walk in order to enhance performance, that is, a good novel feature selection process would be enough to outperform the state of the art. Furthermore, since some of the proposed approaches show promising results in $2$-classes Single-Domain Sentiment Classification, another future work will regard validating these results also in tasks with more than $2$ classes.