Master of Science / Department of Animal Sciences and Industry / Robert L. Weaber / The dynamic environments, varying production practices, and general biological uncertainty associated with bovine reproduction makes informed, strategic decision making regarding the implementation of bovine reproductive technology a great challenge for producers. One might also argue that traditionally, ET’s primary focus of genetic improvement has greatly overshadowed any consideration of short to mid-term financial gain. To accomplish the objective of creating an economic risk analysis tool for user-defined embryo transfer (ET) programs, a circumstantial, stochastic prediction model utilizing @Risk© software to generate comparable economic values as an aid in the ET decision making process has been created. More realistic than the use of means in deterministic models, distributions defining the biological uncertainty for a multitude of reproductive outcomes are estimated through extensive literature review and limited industry sources. Applying the Latin Hypercube variation of Monte Carlo simulation, a sample value from the descriptive distribution associated with each stochastic variable is included in an iteration of the simulation. Through large numbers of iterations with dynamic combinations of variables, the process culminates in a distribution of possible values for the net present value (NPV), annuity equivalent net present value (ANPV), and return on investment (ROI) associated with the model described scenario of in-vivo derived (IVD) or in-vitro produced (IVP). Finally, using the distributions of NPV, ANPV, and ROI a decision maker can assess the economic risk linked to a user-defined ET program. To further complicate matters, cattle producers are now presented with a choice between two primary methods of ET. IVD ET describes the traditional method of ET that involves follicular stimulation and insemination of a donor female followed by the collection of fertilized embryos from the uterus. IVP commonly refers to the method of generating transferable embryos by collecting oocytes by ovarian aspiration; in-vitro fertilization of the collected oocytes; and incubated maturation of the fertilized oocytes. Encompassed within the two methods of ET exist several different sub-techniques, principally regarding the exception or inclusion of follicular synchronization and/or stimulation before ovum pick-up (OPU) in IVP procedures. Ultimately, operators must decide whether ET programs, of any type, serve as an economically viable means to increase rate of genetic improvement or take advantage of marketing opportunities. Although several economic value predictors for ET programs already exist (Beltrame et al. 2010), the opportunity remains to create more applicable models for Bos taurus beef production and varying marketing avenues in the U.S. This circumstantial, stochastic simulation model can serve as an aid in the ET decision making process by generating output that allows for the financial risk and sensitivity analysis of a user-defined ET program.

Particle accelerators produce beams of high-energy particles, which are used for both fundamental and applied scientific research and are critical to the development of accelerator driven sub-critical reactor systems. An effective magnetic shield is very important to achieve higher quality factor (Qo) of the cryomodule of a particle accelerator. The allowed value of field inside the cavity due to all external fields (particularly the Earth’s magnetic field) is ~15 mG or less. The goal of this PhD dissertation is to comprehensively study the magnetic properties of commonly used magnetic shielding materials at both cryogenic and room temperatures. This knowledge can be used for the enhanced design of magnetic shields of cryomodes (CM) in particle accelerators. To this end, we first studied the temperature dependent magnetization behavior (M-H curves) of Amumetal and A4K under different annealing and deformation conditions. This characterized the effect of stress or deformation induced during the manufacturing processes and subsequent restoration of high permeability with appropriate heat treatment. Next, an energy based stochastic model for temperature dependent anhysteretic magnetization behavior of ferromagnetic materials was proposed and benchmarked against experimental data. We show that this model is able to simulate and explain the magnetic behavior of as rolled, deformed and annealed amumetal and A4K over a large range of temperatures. The experimental results for permeability are then used in a finite element model (FEM) in COMSOL to evaluate the shielding effectiveness of multiple shield designs at room temperature as well as cryogenic temperature. This work could serve as a guideline for future design, development and fabrication of magnetic shields of CMs.

Apresentamos nesse trabalho uma proposta de dois modelos aleatórios para a evolução de espécies. O primeiro para a evolução via seleção natural por meio de competição entre espécies e o segundo por mutação. No primeiro caso consideramos uma versão do modelo proposto por Guiol, Machado e Schinazi no caso subcrítico. Para tal modelo derivamos a distribuição da aptidão de sobrevivência ao meio do indivíduo mais forte ao longo de uma excursão ao zero. Para o segundo modelo proposto, consideramos a mutação como uma estratégia para sobrevivência ao meio e provamos condições para sobrevivência e morte quando o modelo evolui sobre a árvore binária orientada com raiz, provando a existência de transição de fase no modelo. / Here we present a proposal for two random models for the evolution of species. To the first one we consider the evolution via natural selection through competition between species and to the second one by mutation. In the first case we consider a version of the model proposed by Guiol, Machado and Schinazi at the subcritical case. For this model we derive the distribution of fitness of the strongest individual along a excursion to zero. For the second one we consider mutation as a strategy for survival and we prove conditions for death and survival when the model evolves on the binary tree with root oriented and we prove the existence of phase transitions in the model.

Complex communities of microbes act collectively to regulate human health, provide sources of clean energy, and ripen aromatic cheese. The efficient functioning of these communities can be directly related to competitive and cooperative interactions between species. Physical constraints and local environment affect the stability of these interactions. Here we explore the role of spatial habitat and interaction networks in microbial ecology and human disease. In the first part of the dissertation, we model mutualism to understand how spatial microbial communities survive number fluctuations in physical habitats. We explicitly account for the production, consumption, and diffusion of public goods in a two-species microbial community. We show that increased sharing of nutrients breaks down coexistence, and that species may benefit from making slower-diffusing nutrients. In multi-species communities, indirect and higher order interactions may affect community function. We find that the requirement for spatial proximity severely restricts the network of possible microbial interactions. While cooperation between two species is stable, higher-order mutualism requiring three or more species succumbs easily to number fluctuations. Additional cyclic or reciprocal interactions between pairs can stabilize multi-species communities. Inter-species interactions also affect human health via the human microbiome: microbial communities in the gut, lungs and skin. In the second part of the dissertation, we use machine learning and statistics to establish links between microbiota abundance and composition, and the incidence of chronic diseases. We study the gut fungal profile to probe the effects of diet and fungal dysbiosis in a cohort of Saudi children with Crohn's disease. While statistical microbiome studies established that each disease phenotype is associated with a distinct state of intestinal dysbiosis, they often produced conflicting results and identified a very large number of microbes associated with disease. We show that a handful of taxa could drive the dynamics of ecosystem-level abundance changes due to strong inter-species interactions. Using maximum entropy methods, we propose a simple statistical approach (Direct Association Analysis or DAA) to account for interspecific interactions. When applied to the largest dataset on IBD, DAA detects a small subset of associations directly linked to the disease, avoids p-value inflation and identifies most predictive features of the microbiome.

The basis for many biological processes such as cell division and differentiation, immune responses, and tumor metastasis depends upon the cell's ability to migrate effectively. A mathematical model for simulating cell migration can be useful in identifying the underlying contributing factors to the crawling motions observed in different types of cells. We present a cell migration model that simulates the 2D motion of amoeba, fibroblasts, keratocytes, and neurons according to a set of input parameters. In the absence of external stimuli the pattern of cell migration follows a persistent random walk which necessitates for several stochastic components in the mathematical model. Consequently, the cell metrics which provide a quantitative description of the cell motion varies between simulations. First we examine different methods for computing the error observed between the output metrics generated by our model and a set of target cell metrics. We also investigate ways of minimizing the variability of the output by varying the number of iterations within a simulation. Finally we apply finite differences, Hooke and Jeeves, and Nelder-Mead minimization methods to our nonlinear stochastic function to search for optimal input values.

The eCommerce industry introduced new business principles, as well as new strategies for achieving these principles, and as a result some traditional measures of success are no longer valid. We classified and ranked the performance of twenty business-to-consumer eCommerce companies by developing critical benchmarks using the Balanced scorecard methodology. We applied a Latent class model, a statistical model along the Bayesian framework, to facilitate the determination of the best and worst performing companies. An eCommerce site's greatest asset is its customers, which is why some of the most valued and sophisticated metrics used today evolve around customer behavior. The results from our classification and ranking procedure showed that companies that ranked high overall also ranked comparatively well in the customer analysis ranking, For example, Amazon.com, one of the highest rated eCommerce companies with a large customer base ranked second in the critical benchmark developed towards measuring customer analysis. The results from our simulation also showed that the Latent class model is a good fit for the classification procedure, and it has a high classification rate for the worst and best performing companies. The resulting work offers a practical tool with the ability to identify profitable investment opportunities for financial managers and analysts.

Apresentamos nesse trabalho uma proposta de dois modelos aleatórios para a evolução de espécies. O primeiro para a evolução via seleção natural por meio de competição entre espécies e o segundo por mutação. No primeiro caso consideramos uma versão do modelo proposto por Guiol, Machado e Schinazi no caso subcrítico. Para tal modelo derivamos a distribuição da aptidão de sobrevivência ao meio do indivíduo mais forte ao longo de uma excursão ao zero. Para o segundo modelo proposto, consideramos a mutação como uma estratégia para sobrevivência ao meio e provamos condições para sobrevivência e morte quando o modelo evolui sobre a árvore binária orientada com raiz, provando a existência de transição de fase no modelo. / Here we present a proposal for two random models for the evolution of species. To the first one we consider the evolution via natural selection through competition between species and to the second one by mutation. In the first case we consider a version of the model proposed by Guiol, Machado and Schinazi at the subcritical case. For this model we derive the distribution of fitness of the strongest individual along a excursion to zero. For the second one we consider mutation as a strategy for survival and we prove conditions for death and survival when the model evolves on the binary tree with root oriented and we prove the existence of phase transitions in the model.

There are a huge number of pathogens with multi-component transmission cycles, involving ampli_er hosts, vectors, complex pathogen life cycles and particular environmental conditions. These complex systems present challenges in terms of modeling and policy development. The deadliest tick-borne infectious disease in the world, the Brazilian Spotted Fever (BSF), is a relevant example of that. The current increase of human cases of BSF has been associated with the presence and expansion of capybaras Hydrochoerus hydrochaeris, amplifer host for the agent Rickettsia rickettsii and primary host for the tick vector Amblyomma sculptum. The objective of this thesis was to analyze the dynamics of the FMB with the purpose of providing bases for the planning of strategies focused on the prevention of human cases. We proposed diferent approaches to evaluating: i) the contribution of hosts and vectors in the transmission of BSF, ii) potential risk areas and anthropogenic parameters associated with the occurrence of human cases, iii) the pattern and the spatial propagation velocity of BSF, and iv) climatic and landscape factors that could be related to the distribution of the vector. The proposed approaches elucidated how BSF control and prevention strategies can be focused on the management of amplifier hosts populations. We found that geographical barriers generated, for example, by areas of riparian reforestation, could prevent the spatial spread of BSF, since a positive association between the occurrence of human cases and the increment of sugarcane crop was determined, as well as a higher propagation velocity of BSF in places with higher carrying capacity. This thesis was interdisciplinary and required, on one hand, expertise in biology, computational epidemiology, mathematics and statistics and on the other hand, a datarich environment such as the Laboratory of Parasitology of the VPS/FMVZ/USP. The results of this thesis can be usefulness in the planning of public health policies related to the prevention of BSF. Furthermore, this work will open the path to further mathematical and computational studies focused on the dynamics and prevention of other vector-borne infectious diseases. / Existe um grande número de agentes patogênicos com ciclos de transmissão complexos, envolvendo hospedeiros amplificadores, vetores e condições ambientais particulares. Esses sistemas complexos apresentam desafios quanto a modelagem e desenvolvimento de políticas públicas. A Febre Maculosa Brasileira (FMB) é a doença transmitida por carrapatos mais letal do mundo e é um claro exemplo de um sistema complexo. O aumento atual de casos humanos de BSF tem sido associado à presença e expansão de capivaras Hydrochoerus hydrochaeris, hospedeiros amplificadores do agente Rickettsia rickettsii e hospedeiros primários do carrapato vetor Amblyomma sculptum. O objetivo desta tese foi analisar a dinâmica da FMB com o propósito de fornecer bases para o delineamento de estratégias de prevenção de casos em humanos. Diferentes abordagens foram propostas para avaliar: i) a contribuição específica de hospedeiros e vetores na transmissão da FMB, ii) os parâmetros antropogênicos associados com a ocorrência dos casos e potenciais áreas de risco, iii) o padrão e a velocidade de propagação espacial e da doença, e iv) os fatores climáticos e paisagísticos que poderiam estar relacionados à distribuição do vetor. Os modelos propostos elucidaram que as estratégias de controle e prevenção da FMB podem estar focadas em práticas de manejo das populações de hospedeiros amplificadores. Uma vez que uma associação positiva entre ocorrência de casos humanos e o incremento de cultura de cana-de-açúcar foi determinada, assim como uma maior velocidade de propagação da FMB em locais com alta quantidade desta cultura, barreiras geográficas geradas, por exemplo, por zonas de reflorestamento ciliar, poderiam impedir a disseminação da FMB. Esta tese foi interdisciplinar e exigiu, por um lado, conhecimentos em biologia, epidemiologia computacional, matemática e estatística e, em contrapartida, um ambiente rico em dados biológicos como o Laboratório de Parasitologia do VPS/USP. Os resultados desta tese poderão ser utilizados na planificação de políticas de saúde pública enfocadas à prevenção da FMB. Complementarmente, este trabalho abrirá o caminho para futuros estudos matemáticos e computacionais orientados no estudo da dinâmica e prevenção de outras doenças infecciosas transmitidas por vetores.

In wireless communications systems, it is well known that the instantaneous received signal is a random variable that follows a given distribution. The randomness mainly stems from e ects such as multipath fading, shadowing, and interference. The received signal is a relevant metric, such that several distributions have been used in the literature to characterize it. However, as new radio technologies emerge, the known distributions are deemed insu cient to t simulated and measure data. Subsequently, as the wireless industry moves onto the fth generation (5G), newer distributions are proposed to well represent the received signal for new wireless technologies, including those operating in the millimeter-wave (mmWave) band. These are mainly application speci c and may not be adequate to model complex 5G devices performance. Therefore, there is a need to unify and generalize the received signal distributions used for performance analysis of wireless systems. Secondly, an explosion of new radio technologies and devices operating in the same limited radio spectrum to collect and share data at alarming rates is expected. Such an explosion coupled with the 5G promise of ubiquitous connectivity and network densi cation, will thrust interference modeling in dense networks to the fore-front. Thus, interference characterization is essential when analyzing such wireless networks. Thirdly, the classical distributions used to model the received signal do not account for the inherent mobility feature for emerging radio technologies, such as avionics systems (e.g. drones), which may make the distributions inadequate as mobility e ects can no longer be ignored. Consequently, in this dissertation, we propose the use of a unifying distribution, the Fox's H-function distribution, with subsume ability to represent several traditional and future distributions, as a statistical tool to evaluate the performance of wireless communications systems. Additionally, two interference models, one with a xed number and the other with a random number of interferers, are considered to derive interference statistics, and further utilize the results to analyze system performance under the e ect of interference. Finally, we extend the classical distributions to include the mobility regime for several wireless network topologies, and perform network analysis. The analytical results are validated using computer Monte Carlo simulations. / Includes bibliography. / Dissertation (Ph.D.)--Florida Atlantic University, 2017. / FAU Electronic Theses and Dissertations Collection

<p>Historically, evolution has been studied either by looking at morphological traits in living organisms and the fossil record, or by using bioinformatics and comparative genomics. While highly useful for deducing evolutionary history, these approaches are not particularly well suited for studying the mechanisms of evolution. In order to address such issues, other methods are needed. Mathematical modelling is one of the most powerful options available, and it is the approach used in this thesis. By constructing models of biological systems, the work aims to resolve some of the many unresolved questions regarding evolutionary processes, such as how new genes evolve and how selection acts in fragmented populations. Some answers have been reached, and thus the thesis makes a small contribution to our overall understanding of evolution.</p><p>The creation of novel genes was studied both directly and by extension of an analogous system, which revolved around reversion of a frameshift mutant. The results pointed to gene amplification as a likely mechanism for both reversion of the frameshift mutant and creation of new genes.</p><p>Selection in fragmented populations is shown to be effective even when sub-populations, rather than individuals, are competing against each other. Modeling of a system of bacterial symbionts living in aphids indicates that, although the bacterial population within a single host is small and subject to rampant genetic drift, the bacterial population as a whole is regulated by selection on the host level. Thus, deleterious mutations do no accumulate and the population maintains its fitness over time.</p>