'Murder or Mercy?' an innovative module helping UK medical students to articulate their own ethical standpoints regarding end-of-life decisions

Objectives This student selected component (SSC) was designed to equip United Kingdom (UK) medical students to respond ethically and with sensitivity to requests they might receive as qualified doctors in regard to euthanasia and assisted dying. The aim was to expose students to relevant opinions and experiences and to provide opportunities to explore and justify their own views and rehearse ethical decision making in a safe learning environment. Method The module is delivered by specialists from a number of disciplines including law, theology, medicine and nursing, each providing students with a working knowledge allowing them to actively discuss cases, articulate their own views and practise ethical reasoning through group and individual study. Visits to local intensive care units, palliative care wards and hospices are integrated effectively with theory. Student assessment comprises a dissertation, student-led debate and reflective commentary. Module impact was evaluated by analysis of student coursework and a questionnaire. Results Students found the content stimulating and relevant to their future career and agreed that the module was well-structured and that learning outcomes were achieved. They greatly appreciated the clinical context provided by the visits and opportunities to apply ethical reasoning to real cases and to debate ethical issues with peers. Students reported an increased discernment of the ethical and legal position and practical considerations and a greater awareness of the range of professional and lay viewpoints held. Student perceptions were confirmed on analysis of their submitted coursework. Many participants were less strongly in favour of euthanasia and assisted dying on module completion than at the outset but all felt better equipped to justify their own viewpoint and to respond appropriately to patient requests. Conclusions The multi-disciplinary nature of this course is helpful in preparing students to deal effectively and sensitively with ethical dilemmas they will encounter in their medical career. Use of an integrated, learner-centred approach equips students to actively engage with their peers in discussion of such issues and to formulate and defend their own position.

Structural influence of gene networks on their inference: analysis of C3NET

Background: The availability of large-scale high-throughput data possesses considerable challenges toward their functional analysis. For this reason gene network inference methods gained considerable interest. However, our current knowledge, especially about the influence of the structure of a gene network on its inference, is limited.

Bagging statistical network inference from large-scale gene expression data.

Modern biology and medicine aim at hunting molecular and cellular causes of biological functions and diseases. Gene regulatory networks (GRN) inferred from gene expression data are considered an important aid for this research by providing a map of molecular interactions. Hence, GRNs have the potential enabling and enhancing basic as well as applied research in the life sciences. In this paper, we introduce a new method called BC3NET for inferring causal gene regulatory networks from large-scale gene expression data. BC3NET is an ensemble method that is based on bagging the C3NET algorithm, which means it corresponds to a Bayesian approach with noninformative priors. In this study we demonstrate for a variety of simulated and biological gene expression data from S. cerevisiae that BC3NET is an important enhancement over other inference methods that is capable of capturing biochemical interactions from transcription regulation and protein-protein interaction sensibly. An implementation of BC3NET is freely available as an R package from the CRAN repository. © 2012 de Matos Simoes, Emmert-Streib.

VLSI module for high-performance multiply, square root and divide

A high-performance VLSI architecture to perform multiply-accumulate, division and square root operations is proposed. The circuit is highly regular, requires only minimal control and can be pipelined right down to the bit level. The system can also be reconfigured on every cycle to perform any one of these operations. The gate count per row has been estimated at (27n+70) gate equivalents where n is the divisor wordlength. The throughput rate, which equals the clock speed, is the same for each operation and is independent of the wordlength. This is achieved through the combination of pipelining and redundant arithmetic. With a 1.0 µm CMOS technology and extensive pipelining, throughput rates in excess of 70 million operations per second are expected.

An Evaluation of the Effectiveness of an FE/HE Partnership in the Delivery of a Preparation for Practice Module within an Undergraduate Social Work Degree Programme

The Preparation for Practice module at the University of Ulster is delivered to 170 first year students via a collaborative arrangement between higher and further education institutions. In each of the five sites, students receive large group and small group teaching facilitated by social work training agency workers and academic tutor dyads. An evaluation of the module sought the perceptions of the agency and academic facilitators regarding the overall collaborative arrangement and the model of co-teaching involving social work academics and agency partners. Respondents were asked to complete a semi-structured questionnaire, which generated data from a Likert scale and also invited qualitative commentary. The Likert scale data were analysed via SPSS and the qualitative information was scrutinised using a manual thematic analysis technique. Findings indicated that continuous communication, consistency in programme content and the acknowledgement of the differences in organisation resources were key to a successful collaborative arrangement. It was also noted that a co-teaching model should be viewed as a positive vehicle for achieving module objectives in a safe learning environment.

Inference and Declaration of Independence in Task-Parallel Programs

The inherent difficulty of thread-based shared-memory programming has recently motivated research in high-level, task-parallel programming models. Recent advances of Task-Parallel models add implicit synchronization, where the system automatically detects and satisfies data dependencies among spawned tasks. However, dynamic dependence analysis incurs significant runtime overheads, because the runtime must track task resources and use this information to schedule tasks while avoiding conflicts and races.
We present SCOOP, a compiler that effectively integrates static and dynamic analysis in code generation. SCOOP combines context-sensitive points-to, control-flow, escape, and effect analyses to remove redundant dependence checks at runtime. Our static analysis can work in combination with existing dynamic analyses and task-parallel runtimes that use annotations to specify tasks and their memory footprints. We use our static dependence analysis to detect non-conflicting tasks and an existing dynamic analysis to handle the remaining dependencies. We evaluate the resulting hybrid dependence analysis on a set of task-parallel programs.