Thesis (M.S. - Hydrology and Water Resources)--University of Arizona. / Includes bibliographical references.

Thesis (M. Sc.)--Carleton University, 2008. / Includes bibliographical references (p. 92-97). Also available in electronic format on the Internet.

No description available.

Apresentamos um modelo estocástico para a evolução de uma espécie pelo processo de seleção natural. Compreender bem o processo evolutivo é de fundamental importância para a biologia, pois é através dele que as espécies e a vida se transformaram ao longo do tempo até chegarmos no mundo como conhecemos hoje. Detalhamos um resultado encontrado na literatura, e também introduzimos algumas variações e sugestões para aprimorar a modelagem original. O modelo proposto é interessante por conta de sua simplicidade e capacidade de capturar aspectos qualitativos esperados segundo as teorias biológicas. / We present a stochastic model for the evolution of a species by natural selection. A good understanding of the evolutionary process is fundamental for the biological sciences, since it describes how life and all species developed until we reached the world as we know today. We show in details a result available on the literature, and also introduce some variations and suggestions in order to improve the original modeling. The model presented here is interesting due to its simplicity and ability to reproduce some qualitative aspects expected from the biological theories.

Apresentamos um modelo estocástico para a evolução de uma espécie pelo processo de seleção natural. Compreender bem o processo evolutivo é de fundamental importância para a biologia, pois é através dele que as espécies e a vida se transformaram ao longo do tempo até chegarmos no mundo como conhecemos hoje. Detalhamos um resultado encontrado na literatura, e também introduzimos algumas variações e sugestões para aprimorar a modelagem original. O modelo proposto é interessante por conta de sua simplicidade e capacidade de capturar aspectos qualitativos esperados segundo as teorias biológicas. / We present a stochastic model for the evolution of a species by natural selection. A good understanding of the evolutionary process is fundamental for the biological sciences, since it describes how life and all species developed until we reached the world as we know today. We show in details a result available on the literature, and also introduce some variations and suggestions in order to improve the original modeling. The model presented here is interesting due to its simplicity and ability to reproduce some qualitative aspects expected from the biological theories.

No description available.

With big science projects like the human genome project, [2], and preliminary attempts to seriously study brain activity, e.g. [9], mathematical biology has come of age, employing formalisms and tools from most branches of mathematics. Recent results, [51] and [53], have extended the relational (or categorical) approach of Rosen [44], to demonstrate that (in a very general class of systems) cellular self-organization/self-replication is implicit in metabolism and repair/stability. This is a powerful philosophical statement and removes the need of teleological argument. However, the result carries a technical limitation to Cartesian closed categories, which excludes many mathematical languages. We review the relevant literature on metabolic-repair pathways, category theory and systems theory, before performing a critique of this work. We find that the restriction to Cartesian closed categories is purely for simplicity, and describe how equivalent arguments may be built for monoidal closed categories. Moreover, any symmetric monoidal category may be "embedded" in a closed one. We discuss how these constructions/techniques provide the formal structure to treat self-organization/self-replication in most contemporary mathematical (modelling) languages. These results signicantly soften the impact on current modelling paradigms while extending the philosophical implications. / Thesis (M.Sc.)-University of KwaZulu-Natal, Durban, 2012.

Thesis (Ph. D. in Mathematics)--Vanderbilt University, Dec. 2005. / Title from title screen. Includes bibliographical references.

Orientador: Rodney Carlos Bassanezi / Dissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Matematica, Estatistica e Computação Cientifica / Made available in DSpace on 2018-08-12T05:14:00Z (GMT). No. of bitstreams: 1 Santos_LuizRafaeldos_M.pdf: 1659435 bytes, checksum: 5f919360eaa92970fd9189ca97ecdb83 (MD5) Previous issue date: 2008 / Resumo: O objetivo deste trabalho é propor um modelo utilizando Sistemas Baseados em Regras Fuzzy (SBRF) que possa controlar, do ponto de vista teórico, uma determinada espécie, considerada como praga em uma lavoura ou plantação. Faz-se primeiro uma introdução à Teoria dos Conjuntos Fuzzy, bem como aos sistemas especialistas fuzzy que utilizam regras de inferência, através do método de inferência de Mamdani e que utilizem o método de defuzzificação por centro de massa. Logo após, são abordados os conceitos de Sistemas Dinâmicos P-Fuzzy uni e bidimensionais desenvolvidos por Silva [24] e Cecconelo [7]. É proposto um novo tipo de Sistema Dinâmico P-fuzzy para modelar a dinâmica populacional, de uma espécie ou de um sistema presa-predador, que leve em conta fatores extrínsecos da(s) espécie(s) envolvida(s). Estes fatores são representados por uma Condição Ambiental, que é definida e acoplada aos Sistemas P-fuzzy usuais. Ainda, usando um controlador fuzzy propomos um sistema de controle híbrido com controladores biológicos e químicos (biocidas) em que as espécies que interagem estão sujeitas também às condições ambientais. Simulações e experimentos computacionais feitos com o auxílio da Fuzzy Logic Toolbox do software Matlab são realizados e seus resultados são comentados. / Abstract: The aim of this work is to propose determined model, using Fuzzy Rule-based Systems (FRBS), wich can control, in a theoretical manner, a species considered a plage in a farming or plantation. An introduction to Fuzzy Sets is maded as well as maded to Fuzzy Systems wich uses inference mIes, through the Mamdani method of inference and that uses Centroid as defuzzification method. After this, the concepts of uni and bidimensional P-fuzzy Dynamic Systems are studied and approached, as developed by Silva [24] and Cecconelo [7]. We propose a new type of P-fuzzy Dynamic System, to model the population dynamics of one species system or of a prey-predator system, that takes into account extrinsic factors of the species involved. Such factores are represented by an Enviromental Condition wich is defined and connected to the usual P-fuzzy Systems. Finnaly, using a Fuzzy Controller, we propose a system for hybrid control with biological and chemical (biocides) controllers in wich the density of species are also influenced by enviromental conditions. Computational simulations and experiments are made with the aid of Matlab Fuzzy Logic Toolbox and its results are commented. / Mestrado / Biomatematica / Mestre em Matemática Aplicada

This study explores the possible role of mathematical system theory in integrating existing ecological knowledge within the existing concepts of the structure of the biosphere. The objective of this integration is a theory of ecosystems which must include interactions. The basic unit of the biosphere is the biogeocoenose; similar to the ecosystem, but homogeneous with respect to topographic, microclimatic, vegetation, animal, pedalogical, hydrological and geochemical conditions. The role of the biogeocoenose in a theory of ecosystems based on system theory is discussed. The biogeocoenose may serve as the building block for modeling watersheds as ecosystems. The fundamentals of system theory are reviewed. As an example, an analysis and synthesis of the arid zone water balance follows. The water balance is resolved into twenty components which represent the water balance of (1) the canopy, (2) the mulch, (3) the soil surface, (4) the soil, and (5) the plant, including interactions. The twenty components were modeled as separate systems which were later coupled into one overall, complex, well defined ecosystem water balance system. The example illustrates the role of system theory in integrating ecological knowledge. Further discussion indicates the need for explicitly including plant behavior in the water balance model.