FUELGEN: effective evolutionary design of refuellings for pressurized water reactors

The paper describes the design of an efficient and robust genetic algorithm for the nuclear fuel loading problem (i.e., refuellings: the in-core fuel management problem) - a complex combinatorial, multimodal optimisation., Evolutionary computation as performed by FUELGEN replaces heuristic search of the kind performed by the FUELCON expert system (CAI 12/4), to solve the same problem. In contrast to the traditional genetic algorithm which makes strong requirements on the representation used and its parameter setting in order to be efficient, the results of recent research results on new, robust genetic algorithms show that representations unsuitable for the traditional genetic algorithm can still be used to good effect with little parameter adjustment. The representation presented here is a simple symbolic one with no linkage attributes, making the genetic algorithm particularly easy to apply to fuel loading problems with differing core structures and assembly inventories. A nonlinear fitness function has been constructed to direct the search efficiently in the presence of the many local optima that result from the constraint on solutions.

Automatic and effective multi-dimensional parallelisation of structured mesh based codes

The most common parallelisation strategy for many Computational Mechanics (CM) (typified by Computational Fluid Dynamics (CFD) applications) which use structured meshes, involves a 1D partition based upon slabs of cells. However, many CFD codes employ pipeline operations in their solution procedure. For parallelised versions of such codes to scale well they must employ two (or more) dimensional partitions. This paper describes an algorithmic approach to the multi-dimensional mesh partitioning in code parallelisation, its implementation in a toolkit for almost automatically transforming scalar codes to parallel form, and its testing on a range of ‘real-world’ FORTRAN codes. The concept of multi-dimensional partitioning is straightforward, but non-trivial to represent as a sufficiently generic algorithm so that it can be embedded in a code transformation tool. The results of the tests on fine real-world codes demonstrate clear improvements in parallel performance and scalability (over a 1D partition). This is matched by a huge reduction in the time required to develop the parallel versions when hand coded – from weeks/months down to hours/days.

Effective e-moderation in e-courses

E-learning promises people the ability to learn at a time and place to suit their needs. However, we frequently assume they can automatically adapt to an online environment. This is not the case. They need focussed support on their journey of development from e-user to e-learner. However, many fail to complete this journey. It is essential we identify how best to support them if we are to fully realise the potential of e-learning. This paper builds on previous research and presents an e-moderation activity model for tutor-led courses.

Barriers to effective pain management in sickle cell disease

Sickle cell disease (SCD) is a long-term condition that would benefit from a long-term conditions approach to its care and management. SCD is growing in prevalence, affecting 10,000-12,000 people in the UK, with SCD sufferers having an increased life expectancy from in the past. The most problematic aspect of managing SCD is management of the pain from vaso-occlusive crises. Vaso-occlusive pain is the most common reason for hospital admissions in people with SCD and accounts for large numbers of accident and emergency (A&E) attendances. A literature review was carried out to examine the management of vaso-occlusive pain in SCD. The review identified three main barriers to effective pain management in SCD: the manifestation of vaso-occlusive pain, the sociocultural factors affecting pain assessment, and the concerns regarding addiction and pseudo-addiction. Addressing these barriers will allow people with SCD to have their pain managed more effectively, improve their quality of life and potentially reduce A&E attendances and admissions to hospital.

Can effective teaching and learning strategies help student nurses to retain drug calculation skills?

Student nurses need to develop and retain drug calculation skills in order accurately to calculate drug dosages in clinical practice. If student nurses are to qualify and be fit to practise accurate drug calculation skills, then educational strategies need to not only show that the skills of student nurses have improved but that these skills have been retained over a period of time. A quasi-experimental approach was used to test the effectiveness of a range of strategies in improving retention of drug calculation skills. The results from an IV additive drug calculation test were used to compare the drug calculation skills of student nurses between two groups of students who had received different approaches to teaching drug calculation skills. The sample group received specific teaching and learning strategies in relation to drug calculation skills and the second group received only lectures on drug calculation skills. All test results for students were anonymous. The results from the test for both groups were statistically analysed using the Mann Whitney test to ascertain whether the range of strategies improved the results for the IV additive test. The results were further analysed and compared to ascertain the types and numbers of errors made in each of the sample groups. The results showed that there is a highly significant difference between the two samples using a two-tailed test (U=39.5, p<0.001). The strategies implemented therefore did make a difference to the retention of drug calculation skills in the students in the intervention group. Further research is required into the retention of drug calculation skills by students and nurses, but there does appears to be evidence to suggest that sound teaching and learning strategies do result in better retention of drug calculation skills.