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

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

Effect of Short Term Exercise and High Fat Diet on Skeletal Muscle miR133a

Micro RNAs (miR) are small non-coding RNA that regulate gene expression at the post-transcriptional level. miR133a is abundant in cardiac and skeletal muscle. In skeletal muscle, miR133a is best known for its regulatory role in myogenesis and differentiation. Nie (2016) found that muscle miR133a expression increased after acute exercise and with 12w of treadmill exercise training in mice. Knockdown of miR133a in transgenic mice resulted in blunted skeletal muscle mitochondrial biogenesis and function in response to exercise training (Nie, 2016) suggesting a role for miR133a in regulating the normal skeletal muscle metabolic adaptive response to exercise. Among other miR, skeletal muscle miR133a is reported as downregulated in insulin-resistant muscle. Insulin resistance in mice fed a high-fat diet is detectable after 3 days on diet (Lee, 2011). In this study, voluntary, rather than forced, exercise was employed to test whether miR133a expression is regulated early in the adoption of increased daily physical activity

What do we know about home education and autism? A thematic synthesis review

Background Mainstream education can be difficult for autistic children given the social communication difficulties, highly focused interests and sensory sensitives associated with autism. Educators can still find providing a safe, inclusive and supportive environment for autistic students challenging. Subsequently some parents decide to remove their children from school and home educate. The purpose of this thematic review is to synthesise reported findings on home educating autistic children who have previously attended formal education. Method PRISMA guidelines informed the review process. Articles included were published in the last 10 years and specific to autistic children being educated at home. Of the 22 articles meeting eligibility for full text review, 10 matched the final inclusion criteria. Results Findings related to four main themes emerging from the synthesis: the motivations and reasons that led parents to home educate their autistic children; parents’ experiences of home educating; practices and pedagogical approaches used by parents; and the impact of home education on the outcomes for autistic students. Findings revealed that home education can be a positive experience for families with good academic and social outcomes for autistic children and young people. Limitations of the evidence base are considered. Conclusion Although not all parents may be in a position to home educate their children, this review indicates that parents with appropriate educational, financial and social supports have found home educating their autistic child empowering. They report being able to provide flexible, balanced and individualised education leading to positive outcomes

An engineered E. coli strain for direct in vivo fluorination

This work was funded by the Industrial Biotechnology Innovation Centre (IBioIC) with support from GlaxoSmithKline, and also the EU Horizon 2020 (Sinfonia consortia).Selectively fluorinated compounds are found frequently in pharmaceutical and agrochemical products where currently 25–30 % of optimised compounds emerge from development containing at least one fluorine atom. There are many methods for the site‐specific introduction of fluorine, but all are chemical and they often use environmentally challenging reagents. Biochemical processes for C−F bond formation are attractive, but they are extremely rare. In this work, the fluorinase enzyme, originally identified from the actinomycete bacterium Streptomyces cattleya, is engineered into Escherichia coli in such a manner that the organism is able to produce 5′‐fluorodeoxyadenosine (5′‐FDA) from S‐adenosyl‐l‐methionine (SAM) and fluoride in live E. coli cells. Success required the introduction of a SAM transporter and deletion of the endogenous fluoride efflux capacity in order to generate an E. coli host that has the potential for future engineering of more elaborate fluorometabolites.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

Fast methods for training Gaussian processes on large data sets

Gaussian process regression (GPR) is a non-parametric Bayesian technique for interpolating or fitting data. The main barrier to further uptake of this powerful tool rests in the computational costs associated with the matrices which arise when dealing with large data sets. Here, we derive some simple results which we have found useful for speeding up the learning stage in the GPR algorithm, and especially for performing Bayesian model comparison between different covariance functions. We apply our techniques to both synthetic and real data and quantify the speed-up relative to using nested sampling to numerically evaluate model evidences.Comment: Fixed missing reference

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