On Hamilton cycles in locally connected graphs with vertex degree constraints

It is shown that every connected, locally connected graph with the maximum vertex degree Δ(G)=5 and the minimum vertex degree δ(G)3 is fully cycle extendable. For Δ(G)4, all connected, locally connected graphs, including infinite ones, are explicitly described. The Hamilton Cycle problem for locally connected graphs with Δ(G)7 is shown to be NP-complete

Dynamic mesh partitioning and load-balancing for parallel computational mechanics codes

In this Chapter we discuss the load-balancing issues arising in parallel mesh based computational mechanics codes for which the processor loading changes during the run. We briefly touch on geometric repartitioning ideas and then focus on different ways of using a graph both to solve the load-balancing problem and the optimisation problem, both locally and globally. We also briefly discuss whether repartitioning is always valid. Sample illustrative results are presented and we conclude that repartitioning is an attractive option if the load changes are not too dramatic and that there is a certain trade-off between partition quality and volume of data that the underlying application needs to migrate.

Support vector machines for regression and applications to software quality prediction

Software metrics are the key tool in software quality management. In this paper, we propose to use support vector machines for regression applied to software metrics to predict software quality. In experiments we compare this method with other regression techniques such as Multivariate Linear Regression, Conjunctive Rule and Locally Weighted Regression. Results on benchmark dataset MIS, using mean absolute error, and correlation coefficient as regression performance measures, indicate that support vector machines regression is a promising technique for software quality prediction. In addition, our investigation of PCA based metrics extraction shows that using the first few Principal Components (PC) we can still get relatively good performance.

The food multimix concept: new innovative approach to meeting nutritional challenges in Sub-Saharan Africa

Food insecurity, chronic hunger, starvation and malnutrition continue to affect millions of individuals throughout the developing world, especially Sub-Saharan Africa. Various initiatives by African governments and International Agencies such as the UN, the industrial nations, the International Monetary Fund, the World Bank and the World Trade Organisation to boost economic development, have failed to provide the much-needed solution to these challenges. The impact of these economic shifts and the failures of structural adjustment programmes on the nutritional well-being and health of the most vulnerable members of poor communities cannot be over-emphasised. The use of ad hoc measures as an adjunct to community-based rural integrated projects have provided little success and will be unsustainable unless they are linked to harnessing available local resources. The present paper therefore focuses on exploring alternative ways of harnessing the scant agricultural resources by employing a scientific approach to food-related problem-solving. The food multimix (FMM) concept offers a scientific contribution alongside other attempts currently in use by the World Food Programme, WHO and FAO to meet the food insecurity challenges that confront most of the developing world in the twenty-first century. It is an innovative approach that makes better use of traditional food sources as a tool for meeting community nutritional needs. The FMM concept employs a food-based approach using traditional methods of food preparation and locally-available, cheap and affordable staples (fruits, pulses, vegetables and legumes) in the formulation of nutrient-enriched multimixes. Developed recipes can provide >= 40% of the daily nutritional requirements of vulnerable groups, including patients with HIV/AIDS and children undergoing nutrition rehabilitation. The FMM approach can also be used as a medium- to long-term adjunct to community-based rural integration projects aimed at health improvement and economic empowerment in Sub-Saharan Africa.

Increasing research evidence in practice: a possible role for the consultant nurse

Aims: To determine the extent to which clinical nursing practice has adopted research evidence. To identify barriers to the application of research findings in practice and to propose ways of overcoming these barriers. Background: Way back in 1976, nursing and midwifery practice started adopting research evidence. By 1990s, there was some transparency of research evidence in practice, but more could have been done to widen its adoption. Many barriers were identified which could hinder implementation of the evidence in practice, and the effort to remove these remains weak. Evaluation: 25 research articles from across Europe and America were selected, and scrutinized, and recommendations analysed. Findings: Many clinical practitioners report a lack of time, ability and motivation to appraise research reports and adopt findings in practice. The clinical environment was not seen as research friendly as there were a general lack of research activities and facilities locally. There was a clear lack of research leadership in practice. Implication for nursing management: This paper reviewed the research evidence from several published research papers and provides consultant nurses with practical suggestions on how to enhance research evidence application in their practice. It recommends how consultant nurses can make their practice more research transparent by providing the required leadership, creating a research-friendly organization, developing a clear research agenda and facilitating staff develop a local research framework for reading research and implementing research evidence in their practice.