Initial losses, corporate governance and earnings management

This thesis examines the relationship between initial loss events and the corporate governance and earnings management behaviour of these firms. This is done using four years of corporate governance information spanning the report of an initial loss for companies listed on the UK Stock Exchange. An industry- and sizematched control sample is used in a difference-in-difference analysis to isolate the impact of the initial loss event during the period. It is reported that, in general, an initial loss motivates an improvement in corporate governance in those loss firms where a relative weakness existed prior to the loss and that these changes mainly occur before the initial loss is announced. Firms with stronger (i.e. better quality) corporate governance have less need to alter it in response to the loss. It is also reported that initial loss firms use positive abnormal accruals in the year before the loss in an attempt to defer/avoid the loss — the weaker corporate governance the more likely is it that loss firms manage earnings in this manner. Abnormal accruals are also found to be predictive of an initial loss and when used as a conditioning variable, the quality of corporate governance is an important mitigating factor in this regard. Once the loss is reported, loss firms unwind these abnormal accruals although no evidence of big-bath behaviour is found. The extent to which these abnormal accruals are subsequently unwound are also found to be a function of both the quality of corporate governance as well as the severity of the initial loss.

Azione destabilizzante e impegno politico. Le figure femminili tra il giallo e il nero Italiani dal 1980 a oggi

My thesis analyses female figures in Italian crime fiction since 1980, from narratological, sociological and gender-studies perspectives. It considers the narrative structure of the giallo and the noir, taking into account the difficulties, particularly in Italy, of establishing what noir fiction is and if/how it is possible to frame it in a specific narrative scheme. This discourse connects to the extraordinary success of Italian giallo and noir fiction over the past fifteen-twenty years. In this scenario, I examine the place of female writers in relation to this phenomenon, especially since the 1980s: in terms of the level of visibility/acceptance of their work, in a narrative space traditionally considered as a male territory, and with regard to their writings, which introduce different narrative perspectives. Specifically, I consider selected texts by leading female Italian writers, in which female elements (writers/characters) become destabilizing factor both on the narrative level, by undermining the schemes of ‘formulaic’ fiction, and on the political one, through their implicit potential (as women) for disrupting the rigid models inherited from processes of social conditioning and from political structures. In terms of gender identities, such texts offer scope to question conventional social constructions of the subject: by empowering the female narrative voice and by embodying it in characters (investigators/killers) traditionally personified by male figures. These texts offer themselves as a critical space where, potentially, readers can rethink static gendered relationships and stereotypical symbolical categories.

The use of fault detection and diagnostics to reduce air handling unit energy consumption

The contribution of buildings towards total worldwide energy consumption in developed countries is between 20% and 40%. Heating Ventilation and Air Conditioning (HVAC), and more specifically Air Handling Units (AHUs) energy consumption accounts on average for 40% of a typical medical device manufacturing or pharmaceutical facility’s energy consumption. Studies have indicated that 20 – 30% energy savings are achievable by recommissioning HVAC systems, and more specifically AHU operations, to rectify faulty operation. Automated Fault Detection and Diagnosis (AFDD) is a process concerned with potentially partially or fully automating the commissioning process through the detection of faults. An expert system is a knowledge-based system, which employs Artificial Intelligence (AI) methods to replicate the knowledge of a human subject matter expert, in a particular field, such as engineering, medicine, finance and marketing, to name a few. This thesis details the research and development work undertaken in the development and testing of a new AFDD expert system for AHUs which can be installed in minimal set up time on a large cross section of AHU types in a building management system vendor neutral manner. Both simulated and extensive field testing was undertaken against a widely available and industry known expert set of rules known as the Air Handling Unit Performance Assessment Rules (APAR) (and a later more developed version known as APAR_extended) in order to prove its effectiveness. Specifically, in tests against a dataset of 52 simulated faults, this new AFDD expert system identified all 52 derived issues whereas the APAR ruleset identified just 10. In tests using actual field data from 5 operating AHUs in 4 manufacturing facilities, the newly developed AFDD expert system for AHUs was shown to identify four individual fault case categories that the APAR method did not, as well as showing improvements made in the area of fault diagnosis.