Thesis (Ph.D.). / Written for the Dept. of Mathematics and Statistics. Title from title page of PDF (viewed 2008/01/12). Includes bibliographical references.

We suppose that the price of a firm follows a nonlinear stochastic delay differential equation. We also assume that any claim whose value depends on firm value and time follows a nonlinear stochastic delay differential equation. Using self-financed strategy and replication we are able to derive a random partial differential equation (RPDE) satisfied by any corporate claim whose value is a function of firm value and time. Under specific final and boundary conditions, we solve the RPDE for the debt value and loan guarantees within a single period and homogeneous class of debt. We then analyze the risk structure of a levered firm. We also evaluate loan guarantees in the presence of more than one debt. Furthermore, we perform numerical simulations for specific companies and compare our results with existing models.

Orientador: Cláudia Pio Ferreira / Abstract: This thesis presents two manuscripts previously sent to publication in scientific journals. In the first manuscript, a delay differential equation model is developed to study the dynamics of two Aedes aegypti mosquito populations: infected by the intracellular bacteria Wolbachia and non-infected (wild) individuals. All the steady states of the system are determined, namely extinction of both populations, extinction of the infected population and persistence of the non-infected one, and coexistence. Their local stability is analyzed, including Hopf bifurcation, which promotes periodic solutions around the nontrivial equilibrium points. Finally, one investigates the global asymptotic stability of the trivial solution. In the second manuscript, after rearing soybean looper Chrysodeixis includens in laboratory conditions, thermal requirements for this insect-pest are estimated, from linear and nonlinear regression models, as well as the intrinsic growth rate. This parameter depends on the life-history traits and can provide a measure of population viability of the species. / Doutor

The thesis deals with numerical analysis of delay differential equations. Particularly, the -method is applied to the pantograph equation considering equidistant and quasi-geometric mesh. Qualitative properties of the numerical methods are demonstrated on several special cases of the pantograph equation.

In this thesis we construct a new model of the immune response to the growth of breast cancer cells and investigate the impact of certain drug therapies on the cancer. We use delay differential equations to model the interaction of breast cancer cells with the immune system. The new model is constructed by combining two previous models. The first model accounts for different cell cycles and includes terms to evaluate drug treatments, but ignores quiescent tumor cells. The second model includes quiescent cells, but ignores the immune response and drug treatments. The new model is obtained by combining and modifying these two models to account for quiescent cells, immune cells and includes drug intervention terms. This new model is used to evaluate the effects of pulsed applications of the drug Paclitaxel for models with and without quiescent cells. We use sensitivity equation methods to analyze the sensitivity of the model with respect to the initial number of immune cytotoxic T-cells. Numerical experiments are conducted to compare the model predictions to observed behavior. / Master of Science

This thesis is concerned with mathematical modelling of oncolytic virotherapy: the use of genetically modified viruses to selectively spread, replicate and destroy cancerous cells in solid tumours. Traditional spatially-dependent modelling approaches have previously assumed that virus spread is due to viral diffusion in solid tumours, and also neglect the time delay introduced by the lytic cycle for viral replication within host cells. A deterministic, age-structured reaction-diffusion model is developed for the spatially-dependent interactions of uninfected cells, infected cells and virus particles, with the spread of virus particles facilitated by infected cell motility and delay. Evidence of travelling wave behaviour is shown, and an asymptotic approximation for the wave speed is derived as a function of key parameters. Next, the same physical assumptions as in the continuum model are used to develop an equivalent discrete, probabilistic model for that is valid in the limit of low particle concentrations. This mesoscopic, compartment-based model is then validated against known test cases, and it is shown that the localised nature of infected cell bursts leads to inconsistencies between the discrete and continuum models. The qualitative behaviour of this stochastic model is then analysed for a range of key experimentally-controllable parameters. Two-dimensional simulations of in vivo and in vitro therapies are then analysed to determine the effects of virus burst size, length of lytic cycle, infected cell motility, and initial viral distribution on the wave speed, consistency of results and overall success of therapy. Finally, the experimental difficulty of measuring the effective motility of cells is addressed by considering effective medium approximations of diffusion through heterogeneous tumours. Considering an idealised tumour consisting of periodic obstacles in free space, a two-scale homogenisation technique is used to show the effects of obstacle shape on the effective diffusivity. A novel method for calculating the effective continuum behaviour of random walks on lattices is then developed for the limiting case where microscopic interactions are discrete.

In recent years, there has been increasing interest in studying time-delayed coupled networks of oscillators since these occur in many real life applications. In many cases symmetry, patterns can emerge in these networks; as a consequence, a part of the system might repeat itself, and properties of this symmetric subsystem represent the whole dynamics. In this thesis, an analysis of a second order N-node time-delay fully connected network is made. This study is carried out using symmetry groups. The existence of multiple eigenvalues forced by symmetry is shown, as well as the possibility of uncoupling the linearization at equilibria, into irreducible representations due to the symmetry. The existence of steady-state and Hopf bifurcations in each irreducible representation is also proved. Three different models are used to analyze the network dynamics, namely, the full-phase, the phase, and the phase-difference model. A finite set of frequencies ω is also determined, which might correspond to Hopf bifurcations in each case for critical values of the delay. Although we restrict our attention to second order nodes, the results could be extended to higher order networks provided the time-delay in the connections between nodes remains equal. / Nos últimos anos, tem havido um crescente interesse em estudar redes de osciladores acopladas com retardo de tempo uma vez que estes ocorrem em muitas aplicações da vida real. Em muitos casos, simetria e padrões podem surgir nessas redes; em consequência, uma parte do sistema pode repetir-se, e as propriedades deste subsistema simétrico representam a dinâmica da rede toda. Nesta tese é feita uma análise de uma rede de N nós de segunda ordem totalmente conectada com atraso de tempo. Este estudo é realizado utilizando grupos de simetria. É mostrada a existência de múltiplos valores próprios forçados por simetria, bem como a possibilidade de desacoplamento da linearização no equilíbrio, em representações irredutíveis. É também provada a existência de bifurcações de estado estacionário e Hopf em cada representação irredutível. São usados três modelos diferentes para analisar a dinâmica da rede: o modelo de fase completa, o modelo de fase, e o modelo de diferença de fase. É também determinado um conjunto finito de frequências ω, que pode corresponder a bifurcações de Hopf em cada caso, para valores críticos do atraso. Apesar de restringir a nossa atenção para nós de segunda ordem, os resultados podem ser estendido para redes de ordem superior, desde que o tempo de atraso nas conexões entre nós permanece igual.

Réguler la prise alimentaire et la dépense énergétique permet en général de limiter d'importants changements de poids corporel. Hormones (leptine, ghréline, insuline) et nutriments sont impliqués dans ces régulations. La résistance à la leptine, souvent associée à l'obésité, limite la régulation de la prise alimentaire. La modélisation mathématique de la dynamique du poids contribue en particulier à une meilleure compréhension des mécanismes de régulation (notamment chez l’humain). Or les régulations hormonales sont largement ignorées dans les modèles existants.Dans cette thèse, nous considérons un modèle de régulation hormonale du poids appliqué aux rats, composé d'équations différentielles non-linéaires. Il décrit la dynamique de la prise alimentaire, du poids et de la dépense énergétique, régulés par la leptine, la ghréline et le glucose. Il reproduit et prédit l'évolution du poids et de la prise alimentaire chez des rats soumis à différents régimes hypocaloriques, et met en évidence l'adaptation de la dépense énergétique. Nous introduisons ensuite le premier modèle décrivant le développement de la résistance à la leptine, prenant en compte la régulation de la prise alimentaire par la leptine et ses récepteurs. Nous montrons que des perturbations de la prise alimentaire, ou de la concentration en leptine, peuvent rendre un individu sain résistant à la leptine et obèse. Enfin, nous présentons une simplification réaliste de la dynamique du poids dans ces modèles, permettant de construire un nouveau modèle combinant les deux modèles précédents / The regulation of food intake and energy expenditure usually limits important loss or gain of body weight. Hormones (leptin, ghrelin, insulin) and nutrients (glucose, triglycerides) are among the main regulators of food intake. Leptin is also involved in leptin resistance, often associated with obesity and characterized by a reduced efficacy to regulate food intake. Mathematical models describing the dynamics of body weight have been used to assist clinical weight loss interventions or to study an experimentally inaccessible phenomenon, such as starvation experiments in humans. Modeling of the effect of hormones on body weight has however been largely ignored.In this thesis, we first consider a model of body weight regulation by hormones in rats, made of nonlinear differential equations. It describes the dynamics of food intake, body weight and energy expenditure, regulated by leptin, ghrelin and glucose. It is able to reproduce and predict the evolution of body weight and food intake in rats submitted to different patterns of caloric restriction, showing the importance of the adaptation of energy expenditure. Second, we introduce the first model of leptin resistance development, based on the regulation of food intake by leptin and leptin receptors. We show that healthy individuals may become leptin resistant and obese due to perturbations in food intake or leptin concentration. Finally, modifications of these models are presented, characterized by simplified yet realistic body weight dynamics. The models prove able to fit the previous, as well as new sets of experimental data and allow to build a complete model combining both previous models regulatory mechanisms

Wir betrachten die stochastische Differentialgleichung mit Gedächtnis (SDDE) mit Gedächtnislänge r dX(t) = b(X(u);u in [t-r,t])dt + sigma(X(u);u in [t-r,t])dB(t) mit eindeutiger schwacher Lösung. Dabei ist B eine Brownsche Bewegung, b and sigma sind stetige, lokal beschränkte Funktionen mit Definitionsbereich C[-r,0], und X(u);u in [t-r,t] bezeichnet das Segment der Werte von X(u) für Zeitpunkte u im Intervall [t,t-r]. Unser Ziel ist eine Folge von diskreten Zeitreihen Xh höherer Ordung zu konstruieren, so dass mit h gegen 0 die Zeitreihen Xh schwach gegen die Lösung X der stochastischen Differentialgleichung mit Gedächtnis konvergieren. Desweiteren werden wir Bedingungen angeben, unter denen eine gegeben Folge von Zeitreihen Xh höherer Ordung schwach gegen die Lösung X einer stochastischen Differentialgleichung mit Gedächtnis konvergiert. Als ein Beispiel werden wir den schwachen Grenzwert einer Folge von diskreten GARCH-Prozessen höherer Ordnung ermitteln. Dieser Grenzwert wird sich als schwache Lösung einer stochastischen Differentialgleichung mit Gedächtnis herausstellen. / Consider the stochastic delay differential equation (SDDE) with length of memory r dX(t) = b(X(u);u in [t-r,t])dt + sigma(X(u);u in [t-r,t])dB(t), which has a unique weak solution. Here B is a Brownian motion, b and sigma are continuous, locally bounded functions defined on the space C[-r,0], and X(u);u in [t-r,t] denotes the segment of the values of X(u) for time points u in the interval [t,t-r]. Our aim is to construct a sequence of discrete time series Xh of higher order, such that Xh converges weakly to the solution X of the stochastic differential delay equation as h tends to zero. On the other hand we shall establish under which conditions time series Xh of higher order converge weakly to a weak solution X of a stochastic differential delay equation. As an illustration we shall derive a weak limit of a sequence of GARCH processes of higher order. This limit tends out to be the weak solution of a stochastic differential delay equation.

Dynamik auf Netzwerken ist ein mathematisches Feld, das in den letzten Jahrzehnten schnell gewachsen ist und Anwendungen in zahlreichen Disziplinen wie z.B. Physik, Biologie und Soziologie findet. Die Funktion vieler Netzwerke hängt von der Fähigkeit ab, die Elemente des Netzwerkes zu synchronisieren. Mit anderen Worten, die Existenz und die transversale Stabilität der synchronen Mannigfaltigkeit sind zentrale Eigenschaften. Erst seit einigen Jahren wird versucht, den verwickelten Zusammenhang zwischen der Kopplungsstruktur und den Stabilitätseigenschaften synchroner Zustände zu verstehen. Genau das ist das zentrale Thema dieser Arbeit. Zunächst präsentiere ich erste Ergebnisse zur Klassifizierung der Kanten eines gerichteten Netzwerks bezüglich ihrer Bedeutung für die Stabilität des synchronen Zustands. Folgend untersuche ich ein komplexes Verzweigungsszenario in einem gerichteten Ring von Stuart-Landau Oszillatoren und zeige, dass das Szenario persistent ist, wenn dem Netzwerk eine schwach gewichtete Kante hinzugefügt wird. Daraufhin untersuche ich synchrone Zustände in Ringen von Phasenoszillatoren die mit Zeitverzögerung gekoppelt sind. Ich bespreche die Koexistenz synchroner Lösungen und analysiere deren Stabilität und Verzweigungen. Weiter zeige ich, dass eine Zeitverschiebung genutzt werden kann, um Muster im Ring zu speichern und wiederzuerkennen. Diese Zeitverschiebung untersuche ich daraufhin für beliebige Kopplungsstrukturen. Ich zeige, dass invariante Mannigfaltigkeiten des Flusses sowie ihre Stabilität unter der Zeitverschiebung erhalten bleiben. Darüber hinaus bestimme ich die minimale Anzahl von Zeitverzögerungen, die gebraucht werden, um das System äquivalent zu beschreiben. Schließlich untersuche ich das auffällige Phänomen eines nichtstetigen Übergangs zu Synchronizität in Klassen großer Zufallsnetzwerke indem ich einen kürzlich eingeführten Zugang zur Beschreibung großer Zufallsnetzwerke auf den Fall zeitverzögerter Kopplungen verallgemeinere. / Since a couple of decades, dynamics on networks is a rapidly growing branch of mathematics with applications in various disciplines such as physics, biology or sociology. The functioning of many networks heavily relies on the ability to synchronize the network’s nodes. More precisely, the existence and the transverse stability of the synchronous manifold are essential properties. It was only in the last few years that people tried to understand the entangled relation between the coupling structure of a network, given by a (di-)graph, and the stability properties of synchronous states. This is the central theme of this dissertation. I first present results towards a classification of the links in a directed, diffusive network according to their impact on the stability of synchronization. Then I investigate a complex bifurcation scenario observed in a directed ring of Stuart-Landau oscillators. I show that under the addition of a single weak link, this scenario is persistent. Subsequently, I investigate synchronous patterns in a directed ring of phase oscillators coupled with time delay. I discuss the coexistence of multiple of synchronous solutions and investigate their stability and bifurcations. I apply these results by showing that a certain time-shift transformation can be used in order to employ the ring as a pattern recognition device. Next, I investigate the same time-shift transformation for arbitrary coupling structures in a very general setting. I show that invariant manifolds of the flow together with their stability properties are conserved under the time-shift transformation. Furthermore, I determine the minimal number of delays needed to equivalently describe the system’s dynamics. Finally, I investigate a peculiar phenomenon of non-continuous transition to synchrony observed in certain classes of large random networks, generalizing a recently introduced approach for the description of large random networks to the case of delayed couplings.