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The American economy is dominated by finance. Institutional investors and asset managers control ever-greater amounts of capital. Non-financial firms almost uniformly abide by the corporate governance principle of shareholder value maximisation. In short, following a process of financialisation that started around 1980, the United States has entered an era of financial capitalism. Focusing on this jurisdiction, the thesis considers the implications of financialisation for competition law. Centrally, the thesis advances the concept of finance-led consolidation, a term that describes how financial institutions and finance-led corporate managers drive the anticompetitive accumulation of economic power in markets for goods and services. The thesis traces the origins of finance-led consolidation to the turn of the twentieth century, when investment banks spurred a merger wave that led to almost every industry in the United States coming under the control of a monopolist. An antagonism existed between competition law and financial institutions at this time, with the former attempting to disperse concentrations of capital brought about by the latter. Yet, as this early iteration of finance-led consolidation fell away, the connection between competition law and finance was lost. Modern competition law sees no meaningful relationship between the nature of the financial economy and competition in the non-financial economy. The thesis stresses that finance-led consolidation has returned alongside financialisation and highlights two specific examples of this phenomenon: common ownership and start-up acquisitions. Both are among the most pressing issues in competition law, and each is innately tied to the dynamics of financial capitalism. Given the reappearance of finance-led consolidation, which diminishes competition in the service of corporate and financial interests, the thesis argues that competition law should regain its hostility towards this phenomenon. In this vein, the thesis offers various proposals for how to combat finance-led consolidation in the context of common ownership and start-up acquisitions.

This thesis focuses on modelling complex economic concepts in the Roman Adriatic. A quantitative focus is taken, and an effort is made to consider evidence from across the region, both terrestrial and maritime, from the offset. Section A considers the geographic and ecological evidence, taking a consciously non-archaeological approach in order to identify micro-regions within the wider region. This also introduces Circuit Theory (CT), which is central to modelling potential connectivity and ultimately economic cohesion in this thesis. Section B is focused on the archaeological evidence, considering the urban population, wine and oil production and the transport infrastructure of the Adriatic. For each of these, the archaeological evidence is compared to the geographic and ecological evidence established in Section A. The CT data is used to identify areas and sites of particular significance, and through this, a complex economic system, operating on multiple scales begins to emerge; potential connectivity is at the centre of all of this. In Section C, the distribution of amphorae and shipwrecks is considered. This expands on the production and connectivity outlined in Section B, and begins to more directly model the economic system in which the Roman Adriatic functioned through quantitative analysis. This thesis demonstrates the importance of geography and potential mobility to ancient economies. A combined maritime and terrestrial approach is vital for any full understanding. Ultimately, this thesis demonstrates that the Roman Adriatic existed as a distinct economic system but one which was reliant on the wider Roman economy. Inter-regional trade was important and prevalent, extra-regional trade was organised in a more hierarchical system, with access to the wider economy likely conducted primarily through relatively few large sites in the north.

According to Wells' metacognitive model of Generalised Anxiety Disorder, GAD, patients attempt to suppress intrusions that trigger worry. Wells postulates that these attempts are rarely effective and may, in fact, increase the frequency of worry triggers. These apparent failures are interpreted as evidence for loss of mental control, thereby exacerbating beliefs about the uncontrollability of worry. The current study tested these predictions. Sixty-two high worriers completed a naturalistic experiment comprising two sessions separated by an experimental week. In Session 1, participants recorded their beliefs about worry in general, including its uncontrollability. They then selected a current worry and recorded how often it came to mind over the following week. The Suppression group (N=32) suppressed their chosen worry during the week. The Mention group (N=30) simply monitored its occurrence. In Session 2, measures completed at Session 1 were repeated. Contrary to prediction, the Suppression group reported a significant improvement in the controllability of their worrying in general. No shift was demonstrated by the Mention group. In addition, relative to the Mention group, the Suppression group reported more success at suppressing their chosen worries, spent less time thinking about them, and found them to be more controllable and less distressing. Findings are discussed within the context of Wells' model.

The work described here involved the application of the well established technique of maximum entropy data analysis to a number of experimental problems where it was not thought to have previously been used. Three real experimental problems were considered: the determination of magnetic hyperfine field distributions from overlapped Mössbauer spectra, the determination of particle size distributions from light scattering from particles of unknown shape and the merging of panchromatic and multispectral data in geographical remote sensing. In addition the more general theoretical problem of estimating distributions from samples is considered, which, though it is treated theoretically, was motivated by an enquiry from a spectroscopist. The common factor shared by the three applications of maximum entropy to real problems is the presence of additional, so called, nuisance parameters which it was not feasible to marginalize out of the problem. The approach taken was to fix these parameters such that the entropy of the distribution we wish to determine was maximised. This procedure was applied successfully to all three cases. It should be noted that this procedure produces the 'most conservative' possible solution, as any other solution consistent with the data would have a lower entropy, and thus contain more information. The individual problems also produced their own conclusions. The light scattering problem demonstrated that there was information in the scattering pattern about the size distribution of particles, even when the data analysis allowed for the possibility that the particles were not of a uniform shape. The investigation of the problem of merging panchromatic and multispectral images produced successful maximum entropy based reconstructions which were better than the conventional techniques with which they were compared. Though, this was achieved only at the cost of orders of magnitude more computing power. In addition, the physics based approach to the problem resulted in a better understanding of the current techniques. In particular a generalization of the intensity-hue-saturation technique, called generalized IHS, or GIHS, has been developed.