Global ETD Search

321	Mathematical Modelling of the Role of Haptotaxis in Tumour Growth and Invasion Mallet, Daniel Gordon January 2004 (has links) In this thesis, a number of mathematical models of haptotactic cell migration are developed. The modelling of haptotaxis is presented in two distinct parts - the ﬁrst comprises an investigation of haptotaxis in pre-necrotic avascular tumours, while the second consists of the modelling of adhesion-mediated haptotactic cell migration within tissue, with particular attention paid to the biological appropriateness of the description of cell-extracellular matrix adhesion. A model is developed that describes the eﬀects of passive and haptotactic migration on the cellular dynamics and growth of pre-necrotic avascular tumours. The model includes a description of the extracellular matrix and its eﬀect on cell migration. Questions are posed as to which cell types act as a source of the extracellular matrix, and the model is used to simulate the possible eﬀects of diﬀerent matrix sources. Simulations in one-dimensional and spherically symmetric geometry are presented, displaying familiar results such as three-phase tumour growth and tumours comprising a rim of proliferating cells surrounding a non-proliferating region. Novel eﬀects are also described such as cell population splitting and tumour shrinkage due to haptotaxis and appropriate extracellular matrix construction. The avascular tumour model is then extended to describe the internalisation of labelled cells and inert microspheres within multicell tumour spheroids. A novel model of adhesion-receptor mediated haptotactic cell migration is presented and speciﬁc applications of the model to tumour invasion processes are discussed. This model includes a more biologically realistic description of cell adhesion than has been considered in previous models of cell population haptotaxis. Through assumptions of fast kinetics, the model is simpliﬁed with the identiﬁcation of relationships between the simpliﬁed model and previous models of haptotaxis. Further simpli.cations to the model are made and travelling wave solutions of the original model are then investigated. It is noted that the generic numerical solution routine NAG D03PCF is not always appropriate for the solution of the model, and can produce oscillatory and inaccurate solutions. For this reason, a control volume numerical solver with .ux limiting is developed to provide a better method of solving the cell migration models. Adhesion Receptors Anoikis Cancer Cell Migration Chemotaxis Control Volume Method Extracellular Matrix ﬂux Limiting Haptotactic Boundary Layer Haptotaxis Integrin Blocking Integrins Internalisation Invasion Lamellipod Landau Transformation Ligand Metastasis Multicell Spheroid Newtons Method Phase Plane Protease Taxis Travelling Wave Tumor Tumour Wall Of Singularities
322	Non-convex Bayesian Learning via Stochastic Gradient Markov Chain Monte Carlo Wei Deng (11804435) 18 December 2021 (has links) <div>The rise of artificial intelligence (AI) hinges on the efficient training of modern deep neural networks (DNNs) for non-convex optimization and uncertainty quantification, which boils down to a non-convex Bayesian learning problem. A standard tool to handle the problem is Langevin Monte Carlo, which proposes to approximate the posterior distribution with theoretical guarantees. However, non-convex Bayesian learning in real big data applications can be arbitrarily slow and often fails to capture the uncertainty or informative modes given a limited time. As a result, advanced techniques are still required.</div><div><br></div><div>In this thesis, we start with the replica exchange Langevin Monte Carlo (also known as parallel tempering), which is a Markov jump process that proposes appropriate swaps between exploration and exploitation to achieve accelerations. However, the na\"ive extension of swaps to big data problems leads to a large bias, and the bias-corrected swaps are required. Such a mechanism leads to few effective swaps and insignificant accelerations. To alleviate this issue, we first propose a control variates method to reduce the variance of noisy energy estimators and show a potential to accelerate the exponential convergence. We also present the population-chain replica exchange and propose a generalized deterministic even-odd scheme to track the non-reversibility and obtain an optimal round trip rate. Further approximations are conducted based on stochastic gradient descents, which yield a user-friendly nature for large-scale uncertainty approximation tasks without much tuning costs. </div><div><br></div><div>In the second part of the thesis, we study scalable dynamic importance sampling algorithms based on stochastic approximation. Traditional dynamic importance sampling algorithms have achieved successes in bioinformatics and statistical physics, however, the lack of scalability has greatly limited their extensions to big data applications. To handle this scalability issue, we resolve the vanishing gradient problem and propose two dynamic importance sampling algorithms based on stochastic gradient Langevin dynamics. Theoretically, we establish the stability condition for the underlying ordinary differential equation (ODE) system and guarantee the asymptotic convergence of the latent variable to the desired fixed point. Interestingly, such a result still holds given non-convex energy landscapes. In addition, we also propose a pleasingly parallel version of such algorithms with interacting latent variables. We show that the interacting algorithm can be theoretically more efficient than the single-chain alternative with an equivalent computational budget.</div> Statistics Stochastic Analysis and Modelling Monte Carlo Algorithm Artificial intelligence Importance sampling Computer vision Langevin Dynamics Variance reduction techniques Wang-Landau algorithm Interacting particles Hamiltonian Monte Carlo Log-Sobolev inequality Metropolis Hasting Deep neural network Stochastic variance-reduced gradient Wasserstein distance Convolutional neural network Deterministic even odd scheme Non-reversibility Stochastic approximation Monte Carlo Stochastic differential equation Stochastic gradient descent Parallel tempering Stochastic approximation Replica exchange Stochastic gradient Langevin dynamics Markov Chain Monte Carlo
323	Embryo Adoption: Implications of Personhood, Marriage, and Parenthood McMillen, Brooke Marie 14 April 2008 (has links) Indiana University-Purdue University Indianapolis (IUPUI) / One’s personal claims regarding personhood will influence his moral belief regarding embryo adoption. In Chapter One, I consider the personhood of the human embryo. If the human embryo is a person, we are morally obligated to permit the practice of embryo adoption as an ethical means to save human persons. However, for those who do not claim that an embryo is a person at conception, embryo adoption is not a necessary practice because we have no moral obligation to protect them. There are still others who claim that personhood is gained at some point during gestation when certain mental capacities develop. I offer my own claim that consciousness and sentience as well as the potential to be self-conscious mark the beginning of personhood. Embryo adoption raises several questions surrounding the institution of marriage. Due to its untraditional method of procreation, embryo adoption calls into question the role of procreation within marriage. In Chapter Two, I explore the nature of the marriage relationship by offering Lisa Cahill’s definition of marriage which involves both a spiritual and physical dimension, and then I describe the concept of marriage from different perspectives including a social, religious, and a personal perspective. From a personal perspective, I explore the relationship between marriage and friendship. Finally, I describe how the concept of marriage is understood today and explore the advantages to being married as opposed to the advantages of being single. Embryo adoption changes the way we customarily think about procreation within a family because in embryo adoption, couples are seeking an embryo from another union to be implanted into the woman. This prompts some philosophers to argue that embryo adoption violates the marriage relationship. In Chapter Three, I further consider the impact of embryo adoption on the family as an extension of the marital relationship as well as the impact of embryo adoption on the traditional roles of motherhood and fatherhood. I examine motherhood by looking at how some philosophers define motherhood and when these philosophers claim a woman becomes a mother. After considering these issues regarding motherhood, I examine the same issues surrounding fatherhood. Peg Brand, PhD., Chair Embryo adoption Embryo rescue Embryo Adoption Rescue Motherhood Fatherhood Marriage Personhood Gestation Conception Reproductive technology Reproduction Surrogacy Conscious Consciousness Sentience Person Self-conscious Self-consciousness Procreation Conjugal union Marriage relationship Procreate Pregnancy Genetic motherhood Gestational motherhood Social motherhood Genetic father Social father Mother Motherhood Father Fatherhood IVF In vitro In vitro fertilization Pregnancy Postnatal adoption Althaus Aquinas Conee Crosby DeGrazia Finnis Ford Locke Lovering McMahan Parfit Quinn Singer Sumner Thomson Tooley Warren Cahill Moller Landau Mill Catholic Lutheran Calvinist Calvinism Aristotle Catholicism Kant Parsons Primoratz Feldman Firestone Tonti-Filippini Watt Geach Human embryo -- Transplantation Adoption -- Religious aspects Motherhood Fatherhood Marriage

Page generated in 0.0504 seconds