Micrositing variability and mean flow scaling for marine turbulence in Ramsey Sound

We present turbulence results from two acoustic Doppler current profiler measurement campaigns carried out in Ramsey Sound at two locations within 50mof one another. The first measurements were taken in 2009 and the second in 2011; both include a complete spring–neap cycle. In this paper we characterise turbulence through turbulent kinetic energy (TKE) density and integral lengthscales and their relationships with one another and with mean flow parameters. We briefly describe the methods used to calculate these parameters. We find that a flood–ebb asymmetry is present in the data from both measurement campaigns, but although the flood tides are similar at both locations, the ebb tides are much more energetic in the 2011 data than the 2009 data. We suggest that this may be due to differences in seabed features between the two measurement locations. Dimensional analysis is employed to investigate how TKE scales with mean flow velocity; we find that the expected quadratic scaling is not well supported by the data at either measurement location. As a consequence, flows that have more energetic turbulence may instead appear to be less turbulent if judged by turbulence intensity. We investigate the correlation between lengthscales and TKE density and find that it is highly site-specific: it should not be assumed that for a given measurement location highly energetic turbulence is associated with larger flow structures or vice versa

The dependence of dijet production on photon virtuality in ep collisions at HERA

The dependence of dijet production on the virtuality of the exchanged photon, Q^2, has been studied by measuring dijet cross sections in the range 0 < Q^2 < 2000 GeV^2 with the ZEUS detector at HERA using an integrated luminosity of 38.6 pb^-1. Dijet cross sections were measured for jets with transverse energy E_T^jet > 7.5 and 6.5 GeV and pseudorapidities in the photon-proton centre-of-mass frame in the range -3 < eta^jet <0. The variable xg^obs, a measure of the photon momentum entering the hard process, was used to enhance the sensitivity of the measurement to the photon structure. The Q^2 dependence of the ratio of low- to high-xg^obs events was measured. Next-to-leading-order QCD predictions were found to generally underestimate the low-xg^obs contribution relative to that at high xg^obs. Monte Carlo models based on leading-logarithmic parton-showers, using a partonic structure for the photon which falls smoothly with increasing Q^2, provide a qualitative description of the data.Comment: 35 pages, 6 eps figures, submitted to Eur.Phys.J.

A Measurement of Rb using a Double Tagging Method

The fraction of Z to bbbar events in hadronic Z decays has been measured by the OPAL experiment using the data collected at LEP between 1992 and 1995. The Z to bbbar decays were tagged using displaced secondary vertices, and high momentum electrons and muons. Systematic uncertainties were reduced by measuring the b-tagging efficiency using a double tagging technique. Efficiency correlations between opposite hemispheres of an event are small, and are well understood through comparisons between real and simulated data samples. A value of Rb = 0.2178 +- 0.0011 +- 0.0013 was obtained, where the first error is statistical and the second systematic. The uncertainty on Rc, the fraction of Z to ccbar events in hadronic Z decays, is not included in the errors. The dependence on Rc is Delta(Rb)/Rb = -0.056*Delta(Rc)/Rc where Delta(Rc) is the deviation of Rc from the value 0.172 predicted by the Standard Model. The result for Rb agrees with the value of 0.2155 +- 0.0003 predicted by the Standard Model.Comment: 42 pages, LaTeX, 14 eps figures included, submitted to European Physical Journal

Assessing the reliability of retrospective reports of adverse childhood experiences among adolescents with documented childhood maltreatment

The literature suggests that childhood maltreatment is related to a higher probability of developing psychopathology and disease in adulthood. However, some authors have questioned the reliability of self-reports of maltreatment, suggesting that psychopathology at the time of evaluation affects self-reports. We evaluated the reliability of the self-reports of 79 young adults who were identified in childhood by Child Protective Services by comparing two moments of evaluation. Psychological and physical symptoms were tested to evaluate their interference with the reports. We found good to excellent agreement, with no significant correlation between the changes in self-reported experiences and the changes in physical and psychological symptoms, suggesting that the reliability of reports is not related to the health state at the time of the report

Measurement of the B+ and B-0 lifetimes and search for CP(T) violation using reconstructed secondary vertices

The lifetimes of the B+ and B-0 mesons, and their ratio, have been measured in the OPAL experiment using 2.4 million hadronic Z(0) decays recorded at LEP. Z(0) --> b (b) over bar decays were tagged using displaced secondary vertices and high momentum electrons and muons. The lifetimes were then measured using well-reconstructed charged and neutral secondary vertices selected in this tagged data sample. The results aretau(B+) = 1.643 +/- 0.037 +/- 0.025 pstau(Bo) = 1.523 +/- 0.057 +/- 0.053 pstau(B+)/tau(Bo) = 1.079 +/- 0.064 +/- 0.041,where in each case the first error is statistical and the second systematic.A larger data sample of 3.1 million hadronic Z(o) decays has been used to search for CP and CPT violating effects by comparison of inclusive b and (b) over bar hadron decays, No evidence fur such effects is seen. The CP violation parameter Re(epsilon(B)) is measured to be Re(epsilon(B)) = 0.001 +/- 0.014 +/- 0.003and the fractional difference between b and (b) over bar hadron lifetimes is measured to(Delta tau/tau)(b) = tau(b hadron) - tau((b) over bar hadron)/tau(average) = -0.001 +/- 0.012 +/- 0.008

Having a lot of a good thing: multiple important group memberships as a source of self-esteem.

Copyright: © 2015 Jetten et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are creditedMembership in important social groups can promote a positive identity. We propose and test an identity resource model in which personal self-esteem is boosted by membership in additional important social groups. Belonging to multiple important group memberships predicts personal self-esteem in children (Study 1a), older adults (Study 1b), and former residents of a homeless shelter (Study 1c). Study 2 shows that the effects of multiple important group memberships on personal self-esteem are not reducible to number of interpersonal ties. Studies 3a and 3b provide longitudinal evidence that multiple important group memberships predict personal self-esteem over time. Studies 4 and 5 show that collective self-esteem mediates this effect, suggesting that membership in multiple important groups boosts personal self-esteem because people take pride in, and derive meaning from, important group memberships. Discussion focuses on when and why important group memberships act as a social resource that fuels personal self-esteem.This study was supported by 1. Australian Research Council Future Fellowship (FT110100238) awarded to Jolanda Jetten (see http://www.arc.gov.au) 2. Australian Research Council Linkage Grant (LP110200437) to Jolanda Jetten and Genevieve Dingle (see http://www.arc.gov.au) 3. support from the Canadian Institute for Advanced Research Social Interactions, Identity and Well-Being Program to Nyla Branscombe, S. Alexander Haslam, and Catherine Haslam (see http://www.cifar.ca)

Mapping structural diversity in networks sharing a given degree distribution and global clustering: Adaptive resolution grid search evolution with Diophantine equation-based mutations

Methods that generate networks sharing a given degree distribution and global clustering can induce changes in structural properties other than that controlled for. Diversity in structural properties, in turn, can affect the outcomes of dynamical processes operating on those networks. Since exhaustive sampling is not possible, we propose a novel evolutionary framework for mapping this structural diversity. The three main features of this framework are: (a) subgraph-based encoding of networks, (b) exact mutations based on solving systems of Diophantine equations, and (c) heuristic diversity-driven mechanism to drive resolution changes in the MapElite algorithm.We show that our framework can elicit networks with diversity in their higher-order structure and that this diversity affects the behaviour of the complex contagion model. Through a comparison with state of the art clustered network generation methods, we demonstrate that our approach can uncover a comparably diverse range of networks without needing computationally unfeasible mixing times. Further, we suggest that the subgraph-based encoding provides greater confidence in the diversity of higher-order network structure for low numbers of samples and is the basis for explaining our results with complex contagion model. We believe that this framework could be applied to other complex landscapes that cannot be practically mapped via exhaustive sampling

Evaluation of fast atmospheric dispersion models in a regular street network

The need to balance computational speed and simulation accuracy is a key challenge in designing atmospheric dispersion models that can be used in scenarios where near real-time hazard predictions are needed. This challenge is aggravated in cities, where models need to have some degree of building-awareness, alongside the ability to capture effects of dominant urban flow processes. We use a combination of high-resolution large-eddy simulation (LES) and wind-tunnel data of flow and dispersion in an idealised, equal-height urban canopy to highlight important dispersion processes and evaluate how these are reproduced by representatives of the most prevalent modelling approaches: (i) a Gaussian plume model, (ii) a Lagrangian stochastic model and (iii) street-network dispersion models. Concentration data from the LES, validated against the wind-tunnel data, were averaged over the volumes of streets in order to provide a high-fidelity reference suitable for evaluating the different models on the same footing. For the particular combination of forcing wind direction and source location studied here, the strongest deviations from the LES reference were associated with mean over-predictions of concentrations by approximately a factor of 2 and with a relative scatter larger than a factor of 4 of the mean, corresponding to cases where the mean plume centreline also deviated significantly from the LES. This was linked to low accuracy of the underlying flow models/parameters that resulted in a misrepresentation of pollutant channelling along streets and of the uneven plume branching observed in intersections. The agreement of model predictions with the LES (which explicitly resolves the turbulent flow and dispersion processes) greatly improved by increasing the accuracy of building-induced modifications of the driving flow field. When provided with a limited set of representative velocity parameters, the comparatively simple street-network models performed equally well or better compared to the Lagrangian model run on full 3D wind fields. The study showed that street-network models capture the dominant building-induced dispersion processes in the canopy layer through parametrisations of horizontal advection and vertical exchange processes at scales of practical interest. At the same time, computational costs and computing times associated with the network approach are ideally suited for emergency-response applications

Cellular Radiosensitivity: How much better do we understand it?

Purpose: Ionizing radiation exposure gives rise to a variety of lesions in DNA that result in genetic instability and potentially tumorigenesis or cell death. Radiation extends its effects on DNA by direct interaction or by radiolysis of H2O that generates free radicals or aqueous electrons capable of interacting with and causing indirect damage to DNA. While the various lesions arising in DNA after radiation exposure can contribute to the mutagenising effects of this agent, the potentially most damaging lesion is the DNA double strand break (DSB) that contributes to genome instability and/or cell death. Thus in many cases failure to recognise and/or repair this lesion determines the radiosensitivity status of the cell. DNA repair mechanisms including homologous recombination (HR) and non-homologous end-joining (NHEJ) have evolved to protect cells against DNA DSB. Mutations in proteins that constitute these repair pathways are characterised by radiosensitivity and genome instability. Defects in a number of these proteins also give rise to genetic disorders that feature not only genetic instability but also immunodeficiency, cancer predisposition, neurodegeneration and other pathologies. Conclusions: In the past fifty years our understanding of the cellular response to radiation damage has advanced enormously with insight being gained from a wide range of approaches extending from more basic early studies to the sophisticated approaches used today. In this review we discuss our current understanding of the impact of radiation on the cell and the organism gained from the array of past and present studies and attempt to provide an explanation for what it is that determines the response to radiation

Automated operant assessments of Huntington's Disease mouse models

Huntington’s disease (HD) presents clinically with a triad of motor, cognitive, and psychiatric symptoms. Cognitive symptoms often occur early within the disease progression, prior to the onset of motor symptoms, and they are significantly burdensome to people who are affected by HD. In order to determine the suitability of mouse models of HD in recapitulating the human condition, these models must be behaviorally tested and characterized. Operant behavioral testing offers an automated and objective method of behaviorally profiling motor, cognitive, and psychiatric dysfunction in HD mice. Furthermore, operant testing can also be employed to determine any behavioral changes observed after any associated interventions or experimental therapeutics. We here present an overview of the most commonly used operant behavioral tests to dissociate motor, cognitive, and psychiatric aspects of mouse models of HD