'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.

The Paralax Infrastructure: Automatic Parallelization With a Helping Hand

Speeding up sequential programs on multicores is a challenging problem that is in urgent need of a solution. Automatic parallelization of irregular pointer-intensive codes, exempli?ed by the SPECint codes, is a very hard problem. This paper shows that, with a helping hand, such auto-parallelization is possible and fruitful. This paper makes the following contributions: (i) A compiler framework for extracting pipeline-like parallelism from outer program loops is presented. (ii) Using a light-weight programming model based on annotations, the programmer helps the compiler to ?nd thread-level parallelism. Each of the annotations speci?es only a small piece of semantic information that compiler analysis misses, e.g. stating that a variable is dead at a certain program point. The annotations are designed such that correctness is easily veri?ed. Furthermore, we present a tool for suggesting annotations to the programmer. (iii) The methodology is applied to autoparallelize several SPECint benchmarks. For the benchmark with most parallelism (hmmer), we obtain a scalable 7-fold speedup on an AMD quad-core dual processor. The annotations constitute a parallel programming model that relies extensively on a sequential program representation. Hereby, the complexity of debugging is not increased and it does not obscure the source code. These properties could prove valuable to increase the ef?ciency of parallel programming.

Behaviours in video

With a significant increment of the number of digital cameras used for various purposes, there is a demanding call for advanced video analysis techniques that can be used to systematically interpret and understand the semantics of video contents, which have been recorded in security surveillance, intelligent transportation, health care, video retrieving and summarization. Understanding and interpreting human behaviours based on video analysis have observed competitive challenges due to non-rigid human motion, self and mutual occlusions, and changes of lighting conditions. To solve these problems, advanced image and signal processing technologies such as neural network, fuzzy logic, probabilistic estimation theory and statistical learning have been overwhelmingly investigated.