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Depression is a complex psychiatric illness that affects a large proportion of the population. Many researchers make use of preclinical animal models to study the behavioural and neurobiological characteristics of this disease. However, although a bias towards maladaptive thinking patterns and emotional responses is a cardinal symptom of depression, these symptoms have been rarely considered in preclinical models. One way to investigate maladaptive thinking is through the use of fear conditioning paradigms. Fear conditioning evaluates emotional memory by assessing a rodent’s ability to associate neutral cues with an aversive experience. It requires the activation of brain structures critically involved in emotion-related learning and memory processes, most notably the hippocampus and amygdala, to successfully learn the task. The primary goal of this dissertation was to gain a better understanding of the consequences of repeated corticosterone injections—a validated preclinical model of depression-- on emotionally driven behaviour, the involvement of the hippocampus and amygdala in mediating these behaviours, and whether the antidepressant, fluoxetine, can prevent the effects of corticosterone on these behaviours. To begin, in Chapter 2 I confirmed that the depressogenic effects of corticosterone in the forced swim test, which is a traditional behavioural assay for depression in rodents, are not due to procedural differences or non-specific motor effects. I then investigated the impact of repeated corticosterone injections on the learning and memory of delay and contextual fear conditioning. I examined whether altering the order in which rats recall context versus tone cued fear associations determines the magnitude of corticosterone’s effect on conditioned fear. I found that corticosterone dose-dependently increased freezing to contextual cues whereas freezing to tone cues was increased regardless of dose. Furthermore, the order of the presentation of context versus tone cues during recall determined whether corticosterone produced significant enhancements in freezing. In Chapter 4, I investigated whether neuronal activity in the hippocampus and amygdala after recall of contextual or tone cued fear was associated with the effects of corticosterone found in Chapter 3. Recall of contextual cues was associated with neuronal activity in specific sub regions of the amygdala without any observed changes in the hippocampus. In Chapter 5, I investigated whether repeated corticosterone injections would also enhance the learning and memory of trace fear conditioning, a task that is heavily reliant on the hippocampus. I found that corticosterone increased freezing during recall of trace cues and enhanced the acquisition of trace cues. The results from this chapter, taken together with the results from chapters 3 and 4, suggest that repeated corticosterone exposure readily enhances learning and memory processes that evoke emotional arousal. In Chapter 6, I asked whether repeated treatment with the antidepressant, fluoxetine, could prevent increased fear learning produced by repeated corticosterone injections. I found that fluoxetine decreased freezing behaviour in corticosterone rats during recall of tone cues. Overall, the results of this dissertation further our understanding of the effects of corticosterone on learning and memory tasks that evoke emotional arousal, support the use of fear conditioning as a measure of depression-like behaviour, and demonstrate that repeated corticosterone injections reliably produce a depressive phenotype in rats.

The shortage of natural resources calls for energy conservation and the changing structure of modern science and technology makes possible the efficient dynamic energy modelling. This thesis presents a general review of existing techniques in the field of building and plant system energy modelling and concentrates on the establishment of a generalised modelling tool - the control volume conservation state space approach - to cope with the developing modern technology. The theoretical basis of this approach is discussed and verified in detail and applications demonstrated to the modelling of HVAC systems and equipment. Using this approach, any component of an HVAC system can be modelled at different levels and the qualities of the model are fully supported by the theoretical background of this approach. A computer programme for heating system simulation has been developed for the purpose of model validation and the validation efforts have been involved in the international cooperated programme of IEA Annex 10 exercises. As a part of group research, the work presented in this thesis has been involved in the development of advanced energy modelling techniques and methodology which has taken place at the ABACUS unit.

Magnesium alloys, as the lightest of all structural metallic materials, and aluminium-based particulate metal matrix composites (PMMCs), offering unified combination of metallic and ceramic properties, have attracted increased interest from the automotive, aerospace, electronic and recreation industries. Current processing technologies for PMMCs do not achieve a uniform distribution of fine-sized reinforcements and produce agglomerated particles in the ductile matrix, which are detrimental to the ductility. At the same time, molten magnesium alloys contain impurities and oxides and when cast conventionally, the final components usually exhibit a coarse and non-uniform microstructure with various casting defects. The key idea in this thesis has been to adopt a novel intensive melt conditioning process, allowing the application of sufficient shear stress that would disperse solid particles present in the melt and offer unique solidification behaviour, improved fluidity and die-filling during casting. The Melt Conditioned High Pressure Die Casting (MC-HPDC) process, where intensive shearing is directly imposed on the alloy melt, which is then cast by the conventional HPDC process, has been used to produce PMMC and magnesium alloy castings. The MC-HPDC process for PMMCs leads to a uniform dispersion of the reinforcement in the matrix, confirmed by quantitative statistical analysis, and increased mechanical performance as indicated by an increase in the hardness and the tensile properties of the composites. We describe a solidification path for aluminium containing magnesium alloys, where intensive shearing prior to casting leads to effective dispersion of solid oxide particles, which then effectively act as nucleation sites for magnesium grains, resulting in significant grain refinement. The MC-HPDC processed magnesium castings have a significantly refined microstructure, with reduced porosity levels and casting defects. Evaluation of the mechanical properties of the castings reveals the beneficial effect of intensive shearing. After careful optimization, the MC-HPDC process shows promising potential for the direct recycling of high purity magnesium die casting scrap, producing casting with mechanical properties comparable to those of primary magnesium alloys.

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