Dynamic multi-partitioning for parallel finite element applications

The central product of the DRAMA (Dynamic Re-Allocation of Meshes for parallel Finite Element Applications) project is a library comprising a variety of tools for dynamic re-partitioning of unstructured Finite Element (FE) applications. The input to the DRAMA library is the computational mesh, and corresponding costs, partitioned into sub-domains. The core library functions then perform a parallel computation of a mesh re-allocation that will re-balance the costs based on the DRAMA cost model. We discuss the basic features of this cost model, which allows a general approach to load identification, modelling and imbalance minimisation. Results from crash simulations are presented which show the necessity for multi-phase/multi-constraint partitioning components

Case based adaptation using interpolation over nominal values

In this paper we propose a method for interpolation over a set of retrieved cases in the adaptation phase of the case-based reasoning cycle. The method has two advantages over traditional systems: the first is that it can predict “new” instances, not yet present in the case base; the second is that it can predict solutions not present in the retrieval set. The method is a generalisation of Shepard’s Interpolation method, formulated as the minimisation of an error function defined in terms of distance metrics in the solution and problem spaces. We term the retrieval algorithm the Generalised Shepard Nearest Neighbour (GSNN) method. A novel aspect of GSNN is that it provides a general method for interpolation over nominal solution domains. The method is illustrated in the paper with reference to the Irises classification problem. It is evaluated with reference to a simulated nominal value test problem, and to a benchmark case base from the travel domain. The algorithm is shown to out-perform conventional nearest neighbour methods on these problems. Finally, GSNN is shown to improve in efficiency when used in conjunction with a diverse retrieval algorithm.

Characteristics and trends of self-harming behaviours in young people

Deliberate self-harm is recognized as a serious public health issue in young people. There is evidence that young people who self-harm are more likely to repeat self-harm, and this in turn increases their risk of completed suicide. Prevalence studies have identified that the rate of self-harm among young people is on the increase, information largely based on data arising from review and analysis of hospital attendances. However, community-based studies indicate that the prevalence is much higher, with those seen in emergency departments representing the 'tip of the iceberg' (Hawton and Rodham, 2006). Young people's motives for self-harm are discussed, as are research findings which indicate that nurses can have negative attitudes towards patients who self-harm. The article considers the implications of this for young people and identifies areas for future research.

A conceptual framework for designing pharmaceutical reverse logistics networks in China

Over latest decade, Reverse Logistics (RL) has gained more and more attention from both industry and academia. In the past, most research on RL has been focused on automobile, electronic waste, computer, paper, package and package material. There is very little research and practice on drug recycling. Nevertheless, it is vital important to properly dispose expired drug because of hazardous contain which may harm to people and environment. In China, public awareness of the harmfulness of expired drugs is still very low and very few efforts have been made to recycle drugs. Therefore, this research aims to build up a conceptual framework to indentify factors of influencing drug recycling in China, from scratch borrowing from existing literature and industry practices in other recycling areas. This framework helps in designing reverse logistic (RL) network and also can provide a useful reference tool for policymakers at the local and national level. Furthermore, a primary research is planed to validate the framework and RL network.