Demonstrating the merits of the peer research process: A Northern Ireland case study

This article discusses the benefits and challenges of involving peer researchers in social research projects. A research project on pupil participation in policy making on school bullying in Northern Ireland’s schools was commissioned by the Office of the Northern Ireland Commissioner for Children and Young People and undertaken by the National Children’s Bureau in conjunction with researchers from Queen’s University Belfast in fourteen schools across Northern Ireland, utilizing a mixed methods approach. We trained and employed nine 15–18-year-old peer researchers to support them in this project. After the project’s completion, we conducted interviews with six of the peer researchers to investigate how they experienced their involvement in the research. We discuss the findings from these interviews and contextualize in a review
of literature on research involving children and young people.

A Diagnostic System Using Broad Categories With Clinicaly Relevant Specifiers: Lessons for ICD-10

A diagnostic system for ICD-11 is proposed which commences with broad reorganization and simplification of the current categories and the use of clinically relevant specifiers. Such changes have implications for the positioning of diagnostic groups and lead to a range of possibilities for improving terminology and the juxtaposition of individual conditions. The development of ICD-11 provides the first opportunity in almost two decades to improve the validity and reliability of the international classification system. Widespread change in broad categories and criteria cannot be justified by research that has emerged since the last revision. It would also be disruptive to clinical practice and might devalue past research work. However, the case for reorganization of the categories is stronger and has recently been made by an eminent international group of researchers (Andrews et al., 2009). A simpler, interlinked diagnostic system is proposed here which is likely to have fewer categories than its predecessor. There are major advantages of such a system for clinical practice and research and it could also produce much needed simplification for primary care (Gask et al., 2008) and the developing world (Wig, 1990; Kohn et al., 2004).

Neural Network Modeling of Rheological Parameters of Grouts Containing Viscosity-Modifying Agent

The development of artificial neural network (ANN) models to predict the rheological behavior of grouts is described is this paper and the sensitivity of such parameters to the variation in mixture ingredients is also evaluated. The input parameters of the neural network were the mixture ingredients influencing the rheological behavior of grouts, namely the cement content, fly ash, ground-granulated blast-furnace slag, limestone powder, silica fume, water-binder ratio (w/b), high-range water-reducing admixture, and viscosity-modifying agent (welan gum). The six outputs of the ANN models were the mini-slump, the apparent viscosity at low shear, and the yield stress and plastic viscosity values of the Bingham and modified Bingham models, respectively. The model is based on a multi-layer feed-forward neural network. The details of the proposed ANN with its architecture, training, and validation are presented in this paper. A database of 186 mixtures from eight different studies was developed to train and test the ANN model. The effectiveness of the trained ANN model is evaluated by comparing its responses with the experimental data that were used in the training process. The results show that the ANN model can accurately predict the mini-slump, the apparent viscosity at low shear, the yield stress, and the plastic viscosity values of the Bingham and modified Bingham models of the pseudo-plastic grouts used in the training process. The results can also predict these properties of new mixtures within the practical range of the input variables used in the training with an absolute error of 2%, 0.5%, 8%, 4%, 2%, and 1.6%, respectively. The sensitivity of the ANN model showed that the trend data obtained by the models were in good agreement with the actual experimental results, demonstrating the effect of mixture ingredients on fluidity and the rheological parameters with both the Bingham and modified Bingham models.

WASP-22 b: A Transiting "Hot Jupiter" Planet in a Hierarchical Triple System

We report the discovery of a transiting planet orbiting the star TYC 6446-326-1. The star, WASP-22, is a moderately bright (V = 12.0) solar-type star (Teff = 6000 ± 100 K, [Fe/H] = -0.05 ± 0.08). The light curve of the star obtained with the WASP-South instrument shows periodic transit-like features with a depth of about 1% and a duration of 0.14 days. The presence of a transit-like feature in the light curve is confirmed using z-band photometry obtained with Faulkes Telescope South. High-resolution spectroscopy obtained with the CORALIE and HARPS spectrographs confirms the presence of a planetary mass companion with an orbital period of 3.533 days in a near-circular orbit. From a combined analysis of the spectroscopic and photometric data assuming that the star is a typical main-sequence star we estimate that the planet has a mass M p = 0.56 ± 0.02M Jup and a radius R p = 1.12 ± 0.04R Jup. In addition, there is a linear trend of 40 m s-1 yr-1 in the radial velocities measured over 16 months, from which we infer the presence of a third body with a long-period orbit in this system. The companion may be a low mass M-dwarf, a white dwarf, or a second planet.