Wave energy in Europe: Views on experiences and progress to date

publisher: Elsevier articletitle: Wave energy in Europe: Views on experiences and progress to date journaltitle: International Journal of Marine Energy articlelink: http://dx.doi.org/10.1016/j.ijome.2015.09.001 content_type: article copyright: © 2015 Elsevier Ltd. All rights reserved

On quantifying expert opinion about multinomial models that contain covariates

This paper addresses the task of forming a prior distribution to represent expert opinion about a multinomial model that contains covariates. The task has not previously been addressed. We suppose the sampling model is a multinomial logistic regression and represent expert opinion about the regression coefficients by a multivariate normal distribution. This logistic-normal model gives a flexible prior distribution that can capture a broad variety of expert opinion. The challenge is to (i) find meaningful assessment tasks that an expert can perform and which should yield appropriate information to determine the values of parameters in the prior distribution, and (ii) develop theory for determining the parameter values from the assessments. A method is proposed that meets this challenge. The method is implemented in interactive user-friendly software that is freely available. It provides a graphical interface that the expert uses to assess quartiles of sets of proportions and the method determines a mean vector and a positive-definite covariance matrix to represent the expert's opinions. The chosen assessment tasks yield parameter values that satisfy the usual laws of probability without the expert being aware of the constraints this imposes. Special attention is given to feedback that encourages the expert to consider his/her opinions from a different perspective. The method is illustrated in an example that shows its viability and usefulness

Signatures of anthocyanin metabolites identified in humans inhibit biomarkers of vascular inflammation in human endothelial cells

Scope The physiological relevance of contemporary cell culture studies is often perplexing, given the use of unmetabolized phytochemicals at supraphysiological concentrations. We investigated the activity of physiologically relevant anthocyanin metabolite signatures, derived from a previous pharmacokinetics study of 500 mg 13C5-cyanidin-3-glucoside in 8 healthy participants, on soluble vascular adhesion molecule-1 (VCAM-1) and interleukin-6 (IL-6) in human endothelial cells. Methods and results Signatures of peak metabolites (previously identified at 1, 6 and 24 h post-bolus) were reproduced using pure standards and effects were investigated across concentrations ten-fold lower and higher than observed mean (<5 μM) serum levels. Tumor necrosis factor-α (TNF-α)-stimulated VCAM-1 was reduced in response to all treatments, with maximal effects observed for the 6 h and 24 h profiles. Profiles tested at ten-fold below mean serum concentrations (0.19-0.44 μM) remained active. IL-6 was reduced in response to 1, 6 and 24 h profiles, with maximal effects observed for 6 h and 24 h profiles at concentrations above 2 μM. Protein responses were reflected by reductions in VCAM-1 and IL-6 mRNA, however there was no effect on phosphorylated NFκB-p65 expression. Conclusion Signatures of anthocyanin metabolites following dietary consumption reduce VCAM-1 and IL-6 production, providing evidence of physiologically relevant biological activity

A tale of two tables

PostprintPeer reviewe

A novel approach to light-front perturbation theory

We suggest a possible algorithm to calculate one-loop n-point functions within a variant of light-front perturbation theory. The key ingredients are the covariant Passarino-Veltman scheme and a surprising integration formula that localises Feynman integrals at vanishing longitudinal momentum. The resulting expressions are generalisations of Weinberg's infinite-momentum results and are manifestly Lorentz invariant. For n = 2 and 3 we explicitly show how to relate those to light-front integrals with standard energy denominators. All expressions are rendered finite by means of transverse dimensional regularisation.Comment: 10 pages, 5 figure

Reference priors for high energy physics

Bayesian inferences in high energy physics often use uniform prior distributions for parameters about which little or no information is available before data are collected. The resulting posterior distributions are therefore sensitive to the choice of parametrization for the problem and may even be improper if this choice is not carefully considered. Here we describe an extensively tested methodology, known as reference analysis, which allows one to construct parametrization-invariant priors that embody the notion of minimal informativeness in a mathematically well-defined sense. We apply this methodology to general cross section measurements and show that it yields sensible results. A recent measurement of the single top quark cross section illustrates the relevant techniques in a realistic situation

Iterative graph cuts for image segmentation with a nonlinear statistical shape prior

Shape-based regularization has proven to be a useful method for delineating objects within noisy images where one has prior knowledge of the shape of the targeted object. When a collection of possible shapes is available, the specification of a shape prior using kernel density estimation is a natural technique. Unfortunately, energy functionals arising from kernel density estimation are of a form that makes them impossible to directly minimize using efficient optimization algorithms such as graph cuts. Our main contribution is to show how one may recast the energy functional into a form that is minimizable iteratively and efficiently using graph cuts.Comment: Revision submitted to JMIV (02/24/13

Statistical methods in cosmology

The advent of large data-set in cosmology has meant that in the past 10 or 20 years our knowledge and understanding of the Universe has changed not only quantitatively but also, and most importantly, qualitatively. Cosmologists rely on data where a host of useful information is enclosed, but is encoded in a non-trivial way. The challenges in extracting this information must be overcome to make the most of a large experimental effort. Even after having converged to a standard cosmological model (the LCDM model) we should keep in mind that this model is described by 10 or more physical parameters and if we want to study deviations from it, the number of parameters is even larger. Dealing with such a high dimensional parameter space and finding parameters constraints is a challenge on itself. Cosmologists want to be able to compare and combine different data sets both for testing for possible disagreements (which could indicate new physics) and for improving parameter determinations. Finally, cosmologists in many cases want to find out, before actually doing the experiment, how much one would be able to learn from it. For all these reasons, sophisiticated statistical techniques are being employed in cosmology, and it has become crucial to know some statistical background to understand recent literature in the field. I will introduce some statistical tools that any cosmologist should know about in order to be able to understand recently published results from the analysis of cosmological data sets. I will not present a complete and rigorous introduction to statistics as there are several good books which are reported in the references. The reader should refer to those.Comment: 31, pages, 6 figures, notes from 2nd Trans-Regio Winter school in Passo del Tonale. To appear in Lectures Notes in Physics, "Lectures on cosmology: Accelerated expansion of the universe" Feb 201

Uses of strength-based interventions for people with serious mental illness: a critical review

Background: For the past 3 decades, mental health practitioners have increasingly adopted aspects and tools of strength-based approaches. Providing strength-based intervention and amplifying strengths relies heavily on effective interpersonal processes. Aim: This article is a critical review of research regarding the use of strength-based approaches in mental health service settings. The aim is to discuss strength-based interventions within broader research on recovery, focussing on effectiveness and advances in practice where applicable. Method: A systematic search for peer-reviewed intervention studies published between 2001 and December 2014 yielded 55 articles of potential relevance to the review. Results: Seven studies met the inclusion criteria and were included in the analysis. The Quality Assessment Tool for Quantitative Studies was used to appraise the quality of the studies. Our review found emerging evidence that the utilisation of a strength-based approach improves outcomes including hospitalisation rates, employment/educational attainment, and intrapersonal outcomes such as self-efficacy and sense of hope. Conclusion: Recent studies confirm the feasibility of implementing a high-fidelity strength-based approach in clinical settings and its relevance for practitioners in health care. More high-quality studies are needed to further examine the effectiveness of strength-based approaches