Public perceptions of tidal energy: Can you predict social acceptability across coastal communities in England?

Early consideration of potential societal issues faced by the nascent tidal industry is important to facilitate public engagement and potentially avoid levels of conflict that have arisen within other renewable energy sectors; general expressions of public support (as reported in national-scale attitude surveys) do not always translate into approval for local developments. It is a very appealing idea that the likely response of different types of communities to marine energy developments can be mapped and used to support planning. This study examined the attitudes of 963 people in South West England to hypothetical local tidal energy projects, analysing the results both by geographic location and according to the coastal community typology developed for England by the Marine Management Organisation. With the exception of age, demographic variables had little influence on the level of opposition to tidal energy, which instead was affected more by factors such as attitudes towards tidal energy in general (in particular its likely environmental impact), activities undertaken at the coast, and place attachment. These significant factors are typically not captured by the national census data used to determine community types. Any predictions about the acceptability of energy projects made as a result of community mapping based on demographic variables will not be a substitute for thorough public engagement and consultation, which should centre on the implications of tidal developments for the environment

Knowledge sharing in infection prevention in routine and outbreak situations: a survey of the Society for Healthcare Epidemiology of America Research Network

Abstract In this cross-sectional Society for Healthcare Epidemiology of America Research Network survey on knowledge sharing in infection prevention we identified a rudimentary understanding of how to communicate and share knowledge within healthcare institutions. Our data support the need of further research in this important field

A General Framework for Formal Tests of Interaction after Exhaustive Search Methods with Applications to MDR and MDR-PDT

The initial presentation of multifactor dimensionality reduction (MDR) featured cross-validation to mitigate over-fitting, computationally efficient searches of the epistatic model space, and variable construction with constructive induction to alleviate the curse of dimensionality. However, the method was unable to differentiate association signals arising from true interactions from those due to independent main effects at individual loci. This issue leads to problems in inference and interpretability for the results from MDR and the family-based compliment the MDR-pedigree disequilibrium test (PDT). A suggestion from previous work was to fit regression models post hoc to specifically evaluate the null hypothesis of no interaction for MDR or MDR-PDT models. We demonstrate with simulation that fitting a regression model on the same data as that analyzed by MDR or MDR-PDT is not a valid test of interaction. This is likely to be true for any other procedure that searches for models, and then performs an uncorrected test for interaction. We also show with simulation that when strong main effects are present and the null hypothesis of no interaction is true, that MDR and MDR-PDT reject at far greater than the nominal rate. We also provide a valid regression-based permutation test procedure that specifically tests the null hypothesis of no interaction, and does not reject the null when only main effects are present. The regression-based permutation test implemented here conducts a valid test of interaction after a search for multilocus models, and can be applied to any method that conducts a search to find a multilocus model representing an interaction

Use of domesticated pigs by Mesolithic hunter-gatherers in northwestern Europe

Acknowledgements We thank the Archaeological State Museum Schleswig-Holstein, the Archaeological State Offices of Brandenburg, Lower Saxony and Saxony and the following individuals who provided sample material: Betty Arndt, Jo¨rg Ewersen, Frederick Feulner, Susanne Hanik, Ru¨diger Krause, Jochen Reinhard, Uwe Reuter, Karl-Heinz Ro¨hrig, Maguerita Scha¨fer, Jo¨rg Schibler, Reinhold Schoon, Regina Smolnik, Thomas Terberger and Ingrid Ulbricht. We are grateful to Ulrich Schmo¨lcke, Michael Forster, Peter Forster and Aikaterini Glykou for their support and comments on the manuscript. We also thank many institutions and individuals that provided sample material and access to collections, especially the curators of the Museum fu¨r Naturkunde, Berlin; Muse´um National d0 Histoire Naturelle, Paris; Smithsonian Institution, National Museum of Natural History, Washington D.C.; Zoologische Staatssammlung, Mu¨nchen; Museum fu¨r Haustierkunde, Halle; the American Museum of Natural History, New-York. This work was funded by the Graduate School ‘Human Development in Landscapes’ at Kiel University (CAU) and supported by NERC project Grant NE/F003382/1. Radiocarbon dating was carried out at the Leibniz Laboratory, CAU. This work is licensed under a Creative Commons AttributionNonCommercial-NoDerivs 3.0 Unported License.Peer reviewedPublisher PD

Arduous implementation: Does the Normalisation Process Model explain why it's so difficult to embed decision support technologies for patients in routine clinical practice

Background: decision support technologies (DSTs, also known as decision aids) help patients and professionals take part in collaborative decision-making processes. Trials have shown favorable impacts on patient knowledge, satisfaction, decisional conflict and confidence. However, they have not become routinely embedded in health care settings. Few studies have approached this issue using a theoretical framework. We explained problems of implementing DSTs using the Normalization Process Model, a conceptual model that focuses attention on how complex interventions become routinely embedded in practice.Methods: the Normalization Process Model was used as the basis of conceptual analysis of the outcomes of previous primary research and reviews. Using a virtual working environment we applied the model and its main concepts to examine: the 'workability' of DSTs in professional-patient interactions; how DSTs affect knowledge relations between their users; how DSTs impact on users' skills and performance; and the impact of DSTs on the allocation of organizational resources.Results: conceptual analysis using the Normalization Process Model provided insight on implementation problems for DSTs in routine settings. Current research focuses mainly on the interactional workability of these technologies, but factors related to divisions of labor and health care, and the organizational contexts in which DSTs are used, are poorly described and understood.Conclusion: the model successfully provided a framework for helping to identify factors that promote and inhibit the implementation of DSTs in healthcare and gave us insights into factors influencing the introduction of new technologies into contexts where negotiations are characterized by asymmetries of power and knowledge. Future research and development on the deployment of DSTs needs to take a more holistic approach and give emphasis to the structural conditions and social norms in which these technologies are enacte

The effects of linkage disequilibrium in large scale SNP datasets for MDR

<p>Abstract</p> <p>Background</p> <p>In the analysis of large-scale genomic datasets, an important consideration is the power of analytical methods to identify accurate predictive models of disease. When trying to assess sensitivity from such analytical methods, a confounding factor up to this point has been the presence of linkage disequilibrium (LD). In this study, we examined the effect of LD on the sensitivity of the Multifactor Dimensionality Reduction (MDR) software package.</p> <p>Results</p> <p>Four relative amounts of LD were simulated in multiple one- and two-locus scenarios for which the position of the functional SNP(s) within LD blocks varied. Simulated data was analyzed with MDR to determine the sensitivity of the method in different contexts, where the sensitivity of the method was gauged as the number of times out of 100 that the method identifies the correct one- or two-locus model as the best overall model. As the amount of LD increases, the sensitivity of MDR to detect the correct functional SNP drops but the sensitivity to detect the disease signal and find an indirect association increases.</p> <p>Conclusions</p> <p>Higher levels of LD begin to confound the MDR algorithm and lead to a drop in sensitivity with respect to the identification of a direct association; it does not, however, affect the ability to detect indirect association. Careful examination of the solution models generated by MDR reveals that MDR can identify loci in the correct LD block; though it is not always the functional SNP. As such, the results of MDR analysis in datasets with LD should be carefully examined to consider the underlying LD structure of the dataset.</p

Use of a Semi-field System to Evaluate the Efficacy of Topical Repellents under user Conditions Provides a Disease Exposure free Technique Comparable with Field Data.

Before topical repellents can be employed as interventions against arthropod bites, their efficacy must be established. Currently, laboratory or field tests, using human volunteers, are the main methods used for assessing the efficacy of topical repellents. However, laboratory tests are not representative of real life conditions under which repellents are used and field-testing potentially exposes human volunteers to disease. There is, therefore, a need to develop methods to test efficacy of repellents under real life conditions while minimizing volunteer exposure to disease. A lotion-based, 15% N, N-Diethyl-3-methylbenzamide (DEET) repellent and 15% DEET in ethanol were compared to a placebo lotion in a 200 sq m (10 m x 20 m) semi-field system (SFS) against laboratory-reared Anopheles arabiensis mosquitoes and in full field settings against wild malaria vectors and nuisance-biting mosquitoes. The average percentage protection against biting mosquitoes over four hours in the SFS and field setting was determined. A Poisson regression model was then used to determine relative risk of being bitten when wearing either of these repellents compared to the placebo. Average percentage protection of the lotion-based 15% DEET repellent after four hours of mosquito collection was 82.13% (95% CI 75.94-88.82) in the semi-field experiments and 85.10% (95% CI 78.97-91.70) in the field experiments. Average percentage protection of 15% DEET in ethanol after four hours was 71.29% (CI 61.77-82.28) in the semi-field system and 88.24% (84.45-92.20) in the field. Semi-field evaluation results were comparable to full-field evaluations, indicating that such systems could be satisfactorily used in measuring efficacy of topically applied mosquito repellents, thereby avoiding risks of exposure to mosquito-borne pathogens, associated with field testing

Rare coding SNP in DZIP1 gene associated with late-onset sporadic Parkinson's disease

We present the first application of the hypothesis-rich mathematical theory to genome-wide association data. The Hamza et al. late-onset sporadic Parkinson's disease genome-wide association study dataset was analyzed. We found a rare, coding, non-synonymous SNP variant in the gene DZIP1 that confers increased susceptibility to Parkinson's disease. The association of DZIP1 with Parkinson's disease is consistent with a Parkinson's disease stem-cell ageing theory.Comment: 14 page

Factors affecting Removal of Bacterial Pathogens from Healthcare Surfaces during Dynamic Wiping

Wiping of surfaces contaminated with pathogenic bacteria is a key strategy for combatting transmission of healthcare associated infections. It is essential to understand the extent to which removal of bacteria is modulated by fibre properties, biocidal liquid impregnation and applied hand pressure. The influence of intrinsic and extrinsic factors on the removal efficiencies of pathogenic bacteria was studied. Nonwoven wipes made of either hydrophobic (polypropylene) or hygroscopic (lyocell) fibres were manufactured and dynamic removal efficiency of bacteria studied. The single most important parameter affecting bacterial removal efficiency was impregnation with biocidal liquid (p <0.05). For inherently hygroscopic 100% regenerated cellulose (lyocell) wipes impregnated with biocidal liquid, removal of E. coli, S. aureus and E. faecalis improved by increasing the fabric surface density and wiping pressure to their maximal values - 150 g.m-2 and 13.80 kN.m-2 respectively. For inherently hydrophobic 100% polypropylene nonwoven wipes, the same conditions maximised the removal efficiency of S. aureus, but for E. coli and E. faecalis a reduction in the wiping pressure to 4.68 kN.m-2 was required. Best practice involves the use of higher surface density wipes (150 g m-2) containing regenerated cellulose fibres loaded with liquid biocide, and applied with the greatest possible wiping pressure