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A computational investigation was undertaken to examine techniques for predicting supersonic dynamic flows, involving unsteadiness over fixed and moving surfaces. The fixed geometries examined were cylinder-flares and compression ramps, and the moving body geometries a pitching aerofoil and a rapidly deployed flap. Investigation into the characteristics of incipient separation of a supersonic cylinder-flare flow revealed that the separated length varied with a power of the flare angle and that the variation in height of the separated region varies in a bi-modal manner with flare angle. For small-scale separations (flare angles less than those which would traditionally have been expected to induce separation) the height of the separated region was seen to vary slowly with flare angle. For larger flare angles, the separation bubble was found to grow rapidly in height and length with increasing flare angle and produce significant deflection of the external flow. Computations of a Mach 5, compression ramp induced unsteady shock boundary layer interaction exhibited self-sustained oscillations at frequencies and amplitudes consistent with experimental data. Large dynamic structures (up to 1.7 boundary layer thicknesses in extent) were observed, and their production, propagation and deformation illustrated. By modifying the turbulent viscosities produced by a non-dimensional implementation of the Baldwin-Lomax turbulence model (using under- relaxation) a turbulence model was produced which accurately predicted separation lengths for a series of Mach 6.85 compression ramp flows encompassing laminar, transitional and turbulent flow regimes (dependent on ramp angle). A technique was developed to enable efficient computation of dynamically moving and/or deforming body flows. This technique was based on hierarchical, adaptive mesh refinement coupled with automatic generation of body surfaces, in which mesh adaption was used to capture the body geometry to within a specified accuracy. This, in conjunction with automatic cell creation and destruction, enabled the derivation of steady and unsteady, time accurate, conservative boundary conditions. This algorithm was used to compute a quasi-steady laminar supersonic pitching aerofoil flow, and an unsteady turbulent supersonic flap deployment. In both cases agreement with experiment was found to be good.

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Computer-aided tools appropriate to architecture, engineering and construction have been Summarised, including digital terrain modelling (DTM), computer-aided design and draughting (CADD) and database management systems (DBMS). DTM and CADD techniques have been applied to simulating the hydraulic filling of tailings, or mine waste dams. A relational DBMS was used to structure and manage filling and terrain data relevant to hydraulic tailings disposal at the Wheal Jane mine in Cornwall.

In this thesis, the problem of probability density function estimation using finite mixture models is considered. Gaussian mixture modelling is used to provide a semi-parametric density estimate for a given data set. The fundamental problem with this approach is that the number of mixtures required to adequately describe the data is not known in advance. In this work, a predictive validation technique [91] is studied and developed as a useful, operational tool that automatically selects the number of components for Gaussian mixture models. The predictive validation test approves a candidate model if, for the set of events they try to predict, the predicted frequencies derived from the model match the empirical ones derived from the data set. A model selection algorithm, based on the validation test, is developed which prevents both problems of over-fitting and under-fitting. We investigate the influence of the various parameters in the model selection method in order to develop it into a robust operational tool. The capability of the proposed method in real world applications is examined on the problem of face image segmentation for automatic initialisation of lip tracking systems. A segmentation approach is proposed which is based on Gaussian mixture modelling of the pixels RGB values using the predictive validation technique. The lip region segmentation is based on the estimated model. First a grouping of the model components is performed using a novel approach. The resulting groups are then the basis of a Bayesian decision making system which labels the pixels in the mouth area as lip or non-lip. The experimental results demonstrate the superiority of the method over the conventional clustering approaches. In order to improve the method computationally an image sampling technique is applied which is based on Sobol sequences. Also, the image modelling process is strengthened by incorporating spatial contextual information using two different methods, a Neigh-bourhood Expectation Maximisation technique and a spatial clustering method based on a Gibbs/Markov random field modelling approach. Both methods are developed within the proposed modelling framework. The results obtained on the lip segmentation application suggest that spatial context is beneficial.

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The basic objective of this paper is to compare two entropy formulae used as objective functions in spatial intreraction modelling. This is carried out by comparing some attributes of the interaction models derived from both of them. The comparison results in the design of the third formula, which, however, represents a slight modification of one of them. (author's abstract) / Series: Discussion Papers of the Institute for Economic Geography and GIScience

Reactivating quiescent cells to proliferate is critical to tissue repair and homoeostasis. Quiescence exit is highly noisy even for genetically identical cells under the same environmental conditions. Deregulation of quiescence exit is associated with many diseases, but cellular mechanisms underlying the noisy process of exiting quiescence are poorly understood. Here we show that the heterogeneity of quiescence exit reflects a memory of preceding cell growth at quiescence induction and immediate division history before quiescence entry, and that such a memory is reflected in cell size at a coarse scale. The deterministic memory effects of preceding cell cycle, coupled with the stochastic dynamics of an Rb-E2F bistable switch, jointly and quantitatively explain quiescence-exit heterogeneity. As such, quiescence can be defined as a distinct state outside of the cell cycle while displaying a sequential cell order reflecting preceding cell growth and division variations.

While premature birth is still one of the major clinical problems worldwide, the exact physiological mechanisms underlying myometrium activity during pregnancy remain unclear. In this thesis, a novel biophysically detailed model was constructed using available experimental data to simulate chemical, electrical and mechanical activity in a late pregnant rat uterine myocycte. The developed model has been used to elucidate the ionic mechanism underlying myometrium functionality, providing better insights in the function of the uterus during pregnancy. The model consisted of 15 membrane currents, intracellular calcium handling process coupled with a sliding actin-myosin filament mechanical model to describe uterine behaviour and contractile activity at the single myocyte level. Each of the ionic currents were modelled using Hodgkin-Huxley-type equations. The simulated current traces and current-voltage curves were validated with experimental recordings and the model was further validated by the ability to produce a bursting action potential (AP) during an external stimulus. The model replicated the effects of estradiol during pregnancy, modulating the amplitude and activation properties of individual Ca2+ and K+ currents, therefore altering the AP configuration to a tonic-like plateau. The model also reproduced the actions of drugs to inhibit certain channels to investigate their roles in myometrium. Sensitivity analysis was performed to examine the model's behaviour to changing parameters. A simple 1-D study was conducted to investigate how electrical signals propagate along strand of cells. Although the model successfully replicated results similar to recordings seen in the experiments, limitations have to be addressed and more studies have to be carried out to further improve the model.