The text and the tale: differences between scientific reports and scientists’ reportings on the eruption of Mount Chance, Montserrat

This article looks at the difference between scientists’ written reports and their oral accounts, explanations and stories. The subject of these discourses is the eruption of Mount Chance on Montserrat, a British Overseas Territory in the Eastern Caribbean, and its continued monitoring and reporting. Scientific notions of risk and uncertainty which feature in these texts and tales will subsequently be examined and critiqued. Further to this, this article will end by pointing out that, ironically, the latter - the tale – can in some cases be a more effective and approximate mode of communication with the public than the former – the text.

A survey of formalisms for representing and reasoning with scientific knowledge

With the rapid growth in the quantity and complexity of scientific knowledge available for scientists, and allied professionals, the problems associated with harnessing this knowledge are well recognized. Some of these problems are a result of the uncertainties and inconsistencies that arise in this knowledge. Other problems arise from heterogeneous and informal formats for this knowledge. To address these problems, developments in the application of knowledge representation and reasoning technologies can allow scientific knowledge to be captured in logic-based formalisms. Using such formalisms, we can undertake reasoning with the uncertainty and inconsistency to allow automated techniques to be used for querying and combining of scientific knowledge. Furthermore, by harnessing background knowledge, the querying and combining tasks can be carried out more intelligently. In this paper, we review some of the significant proposals for formalisms for representing and reasoning with scientific knowledge.

British Society of Haematology, Slide Session presented at the Annual Scientific Meeting, Brighton 2009

P>Seven cases were discussed by an expert panel at the 2009 Annual Scientific Meeting of the British Society of Haematology. These cases are presented in a similar format to that adopted for the meeting. There was an initial discussion of the presenting morphology, generation of differential diagnoses and then, following display of further presenting and diagnostic information, each case was concluded with provision of a final diagnosis.

Scientific revolutions, progess and accounting research

Thomas Kuhn’s concept of a normal science paradigm has been utilised and criticised across a range of social science fields. However, Kuhn’s aim was to argue that science progresses not in an incremental manner but through a series of paradigms that need a revolution in thought to shift from one to the next. This paper addresses Kuhn’s work focusing on the totality of his model, but recognising the ambiguities concerning paradigm shifts that have led to charges of relativism. To address this weakness an argument is advanced for a political economy analysis of the publication process and the development of critical accounting research centred on human emancipation. The paper concludes with some suggested research agendas particularly relevant to the Irish context.

Prediction-Based Power-Performance Adaptation of Multithreaded Scientific Codes

Computing has recently reached an inflection point with the introduction of multicore processors. On-chip thread-level parallelism is doubling approximately every other year. Concurrency lends itself naturally to allowing a program to trade performance for power savings by regulating the number of active cores; however, in several domains, users are unwilling to sacrifice performance to save power. We present a prediction model for identifying energy-efficient operating points of concurrency in well-tuned multithreaded scientific applications and a runtime system that uses live program analysis to optimize applications dynamically. We describe a dynamic phase-aware performance prediction model that combines multivariate regression techniques with runtime analysis of data collected from hardware event counters to locate optimal operating points of concurrency. Using our model, we develop a prediction-driven phase-aware runtime optimization scheme that throttles concurrency so that power consumption can be reduced and performance can be set at the knee of the scalability curve of each program phase. The use of prediction reduces the overhead of searching the optimization space while achieving near-optimal performance and power savings. A thorough evaluation of our approach shows a reduction in power consumption of 10.8 percent, simultaneous with an improvement in performance of 17.9 percent, resulting in energy savings of 26.7 percent.