Coventry University

About: Coventry University is a education organization based out in Coventry, United Kingdom. It is known for research contribution in the topics: Context (language use) & Population. The organization has 4964 authors who have published 12700 publications receiving 255898 citations. The organization is also known as: Lanchester Polytechnic & Coventry Polytechnic.

The Dragon's Gift. The Real Story of China in Africa

Abstract: The Dragon's Gift. The Real Story of China in Africa, Deborah Brautigam, Oxford University Press, Oxford (2009). xiii + 397 pp. US$29.95 (hbk). ISBN 978-0-19-955022-7. Deborah Brautigam, a well-inf...

Effects of communicating DNA‐based disease risk estimates on risk‐reducing behaviours

Abstract: BACKGROUND: There are high expectations regarding the potential for the communication of DNA-based disease risk estimates to motivate behaviour change. OBJECTIVES: To assess the effects of communicating DNA-based disease risk estimates on risk-reducing behaviours and motivation to undertake such behaviours. SEARCH STRATEGY: We searched the following databases using keywords and medical subject headings: Cochrane Central Register of Controlled Trials (CENTRAL, The Cochrane Library, Issue 4 2010), MEDLINE (1950 to April 2010), EMBASE (1980 to April 2010), PsycINFO (1985 to April 2010) using OVID SP, and CINAHL (EBSCO) (1982 to April 2010). We also searched reference lists, conducted forward citation searches of potentially eligible articles and contacted authors of relevant studies for suggestions. There were no language restrictions. Unpublished or in press articles were eligible for inclusion. SELECTION CRITERIA: Randomised or quasi-randomised controlled trials involving adults (aged 18 years and over) in which one group received actual (clinical studies) or imagined (analogue studies) personalised DNA-based disease risk estimates for diseases for which the risk could plausibly be reduced by behavioural change. Eligible studies had to include a primary outcome measure of risk-reducing behaviour or motivation (e.g. intention) to alter such behaviour. DATA COLLECTION AND ANALYSIS: Two review authors searched for studies and independently extracted data. We assessed risk of bias according to the Cochrane Handbook for Systematic Reviews of Interventions. For continuous outcome measures, we report effect sizes as standardised mean differences (SMDs). For dichotomous outcome measures, we report effect sizes as odds ratios (ORs). We obtained pooled effect sizes with 95% confidence intervals (CIs) using the random effects model applied on the scale of standardised differences and log odds ratios. MAIN RESULTS: We examined 5384 abstracts and identified 21 studies as potentially eligible. Following a full text analysis, we included 14 papers reporting results of 7 clinical studies (2 papers report on the same trial) and 6 analogue studies.Of the seven clinical studies, five assessed smoking cessation. Meta-analyses revealed no statistically significant effects on either short-term (less than 6 months) smoking cessation (OR 1.35, 95% CI 0.76 to 2.39, P = 0.31, n = 3 studies) or cessation after six months (OR 1.07, 95% CI 0.64 to 1.78, P = 0.80, n = 4 studies). Two clinical studies assessed diet and found effects that significantly favoured DNA-based risk estimates (OR 2.24, 95% CI 1.17 to 4.27, P = 0.01). No statistically significant effects were found in the two studies assessing physical activity (OR 1.03, 95% CI 0.59 to 1.80, P = 0.92) or the one study assessing medication or vitamin use aimed at reducing disease risks (OR 1.26, 95% CI 0.58 to 2.72, P = 0.56).�For the six non-clinical analogue studies, meta-analysis revealed a statistically significant effect of DNA-based risk on intention to change behaviour (SMD 0.16, 95% CI 0.04 to 0.29, P = 0.01).There was no evidence that communicating DNA-based disease risk estimates had any unintended adverse effects. Two studies that assessed fear arousal immediately after the presentation of risk information did, however, report greater fear arousal in the DNA-based disease risk estimate groups compared to comparison groups.The quality of included studies was generally poor. None of the clinical or analogue studies were considered to have a low risk of bias, due to either a lack of clarity in reporting, or where details were reported, evidence of a failure to sufficiently safeguard against the risk of bias. AUTHORS' CONCLUSIONS: Mindful of the weak evidence based on a small number of studies of limited quality, the results of this review suggest that communicating DNA-based disease risk estimates has little or no effect on smoking and physical activity. It may have a small effect on self-reported diet and on intentions to change behaviour. Claims that receiving DNA-based test results motivates people to change their behaviour are not supported by evidence. Larger and better-quality RCTs are needed.

Public transport networks: empirical analysis and modeling

Abstract: Public transport networks of fourteen cities of so far unexplored network size are analyzed in standardized graph representations: the simple graph of the network map, the bipartite graph of routes and stations, and both one mode projections of the latter. Special attention is paid to the inter-relations and spatial embedding of transport routes. This systematic approach reveals rich behavior beyond that of the ubiquitous scale-free complex network. We find strong evidence for structures in PTNs that are counter-intuitive and need to be explained, among these a pronounced diversity in the expression of typical network characteristics within the present sample of cities, a surprising geometrical behavior with respect to the two-dimensional geographical embedding and an unexpected attraction between transport routes. A simple model based on these observations reproduces many of the identified PTN properties by growing networks of attractive self-avoiding walks.

Genetic algorithms, path relinking, and the flowshop sequencing problem

Abstract: In a previous paper, a simple genetic algorithm (GA) was developed for finding (approximately) the minimum makespan of the n-job, m-machine permutation flowshop sequencing problem (PFSP). The performance of the algorithm was comparable to that of a naive neighborhood search technique and a proven simulated annealing algorithm. However, recent results have demonstrated the superiority of a tabu search method in solving the PFSP. In this paper, we reconsider the implementation of a GA for this problem and show that by taking into account the features of the landscape generated by the operators used, we are able to improve its performance significantly.