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A novel two-step Isotopic Exchange (IE) technique has been developed to investigate the influence of oxygen containing components of ambient air (such as H₂O and CO₂) on the effective surface exchange coefficient (k*) of a common mixed ionic electronic conductor material. The two step ‘back-exchange’ technique was used to introduce a tracer diffusion profile, which was subsequently measured using Time-of-Flight Secondary Ion Mass Spectrometry (ToF-SIMS). The isotopic fraction of oxygen in a dense sample as a function of distance from the surface, before and after the second exchange step, could then be used to determine the surface exchange coefficient in each atmosphere. A new analytical solution was found to the diffusion equation in a semi-infinite domain with a variable surface exchange boundary, for the special case where D* and k* are constant for all exchange steps. This solution validated the results of a numerical, Crank-Nicolson type finite-difference simulation, which was used to extract the parameters from the experimental data. When modelling electrodes, D* and k* are important input parameters, which significantly impact performance. In this study La_(0.6)Sr_(0.4)Co_(0.2)Fe_(0.8)O_(3−δ) (LSCF6428) was investigated and it was found that the rate of exchange was increased by around 250% in ambient air compared to high purity oxygen at the same pO₂. The three experiments performed in this study were used to validate the back-exchange approach and show its utility.

Short chain fatty acids (SCFA), principally acetate, propionate, butyrate and valerate, are produced in pharmacologically relevant concentrations by the gut microbiome. Investigations indicate that they exert beneficial effects on colon epithelia. There is increasing interest in whether different SCFAs have distinct functions which may be exploited for prevention or treatment of colonic diseases including colorectal cancer (CRC), inflammatory bowel disease and obesity. Based on experimental evidence, we hypothesised that odd-chain SCFAs may possess anti-mitotic capabilities in colon cancer cells by disrupting microtubule (MT) structural integrity via dysregulation of β-tubulin isotypes. MT dynamic instability is an essential characteristic of MT cellular activity. We report a minimal deterministic model that takes a novel approach to explore the hypothesised pathway by triggering spontaneous oscillations to represent MT dynamic behaviour. The dynamicity parameters in silico were compared to those reported in vitro. Simulations of untreated and butyrate (even-chain length) treated cells reflected MT behaviour in interphase or untreated control cells. The propionate and valerate (odd-chain length) simulations displayed increased catastrophe frequencies and longer periods of MT-fibre shrinkage. Their enhanced dynamicity was dissimilar to that observed in mitotic cells, but parallel to that induced by MT-destabilisation treatments. Antimicrotubule drugs act through upward or downward modulation of MT dynamic instability. Our computational modelling suggests that metabolic engineering of the microbiome may facilitate managing CRC risk by predicting outcomes of SCFA treatments in combination with AMDs.

We have previously tried to explain perceptual inference and learning under a free-energy principle that pursues Helmholtz’s agenda to understand the brain in terms of energy minimization. It is fairly easy to show that making inferences about the causes of sensory data can be cast as the minimization of a free-energy bound on the likelihood of sensory inputs, given an internal model of how they were caused. In this article, we consider what would happen if the data themselves were sampled to minimize this bound. It transpires that the ensuing active sampling or inference is mandated by ergodic arguments based on the very existence of adaptive agents. Furthermore, it accounts for many aspects of motor behavior; from retinal stabilization to goal-seeking. In particular, it suggests that motor control can be understood as fulfilling prior expectations about proprioceptive sensations. This formulation can explain why adaptive behavior emerges in biological agents and suggests a simple alternative to optimal control theory. We illustrate these points using simulations of oculomotor control and then apply to same principles to cued and goal-directed movements. In short, the free-energy formulation may provide an alternative perspective on the motor control that places it in an intimate relationship with perception.

3D Reconstruction using multiple cameras is a technique often employed in the studio production environment. The outdoor sports broadcast environment is also a multicamera environment and this thesis attempts to apply and adapt studio techniques to the unique requirements of this environment, including increased errors in calibration and matting, variations in camera configuration and wide-baseline camera arrangements. This thesis examines 3D reconstruction and activity recognition as applied to the domain of field sports such as football and rugby. Video is captured from a number of cameras arranged around the pitch, and processed using computer vision techniques to generate a 3D scene representation for rendering or analysis. The applications considered in this thesis are free-viewpoint video and the synthetic representation of segments of a match. The thesis presents an analysis of the 3D reconstruction errors in the outdoor sports broadcast environment. Also presented are several Shape-Prom-Silhouette techniques which are shown to provide improved scene reconstruction in this environment. A dual-mode deformable model is presented that refines the reconstruction using stereo information from neighbouring cameras, and simultaneously optimises silhouette extraction in a manner that is more robust to the calibration and reconstruction errors typical of the outdoor sports broadcast scenario. This thesis also presents an action matching technique to extract temporally consistent, synchronised pose information for each player present in the scene. An analysis of matching scores shows that the symmetric Kullback Leibler divergence between shape histograms is a suitable score for measuring the difference between noisy visual hull reconstructions. Players are automatically segmented in 3D and a hidden Markov model is used to match extracted shape histograms against a library of exemplar poses. Various extensions to the scheme are presented and evaluated and it is shown that good results can be achieved using a combination of action matching and key-pose detection.