Crossing Thresholds and Expanding Conceptual Spaces: Using Arts-Based Methods to Extend Teachers’ Perceptions of Literacy

The context for this paper is a teacher education program for adult literacy practitioners at Queen’s University Belfast in Northern Ireland. This paper describes and reflects on the use of arts-based approaches to enhance these practitioners’ conceptualizations of literacy, presenting their arts-based responses and their evaluations of the methods and their contrasting definitions of literacy at the start and the end of the course. The discussion raises questions about the inclusion of visual literacy in adult literacy teacher education programmes.

Lagrangian description of nonlinear dust-ion acoustic waves in dusty plasmas

An analytical model is presented for the description of nonlinear dust-ion-acoustic waves propagating in an unmagnetized, collisionless, three component plasma composed of electrons, ions and inertial dust grains. The formulation relies on a Lagrangian approach of the plasma fluid model. The modulational stability of the wave amplitude is investigated. Different types of localized envelope electrostatic excitations are shown to exist.

A Description of the Stationary Wave Pattern of a Marine Craft in Shallow and Intermediate Water Depths

A stationary phase model is used to study supercritical waves generated by high speed ferries. Some general relationships in terms of wave angle, propagation direction, dispersion relationship and depth wavelength relationship are explored and discussed. In particular, it is shown that the wave pattern generated by high speed craft at supercritical speeds depends mainly on the relationship of water depth and ship speed and that the wave patterns are similar in terms of location of crests and troughs for a given depth Froude number. In addition it is found that the far field wave pattern can be described adequately using a single moving point source. The theoretical model compares well with towing tank measurements and full scale data over a range of parameters and hull shapes. The paper also demonstrates that the far field wave pattern at supercritical speeds should be non-dimensionalised by water depth and not hull length unlike it is usually done for subcritical speeds.

Cohort description: The Northern Ireland Longitudinal Study (NILS)

no abstract available

Conceptual and Perceptual Priming and Dissociation in Chronic Posttraumatic Stress Disorder.

Cognitive models of posttraumatic stress disorder (PTSD) assert that memory processes play a significant role in PTSD (see e.g., Ehlers & Clark, 2000). Intrusive reexperiencing in PTSD has been linked to perceptual processing of trauma-related material with a corresponding hypothesized lack of conceptual processing. In an experimental study that included clinical participants with and without PTSD (N = 50), perceptual priming and conceptual priming for trauma-related, general threat, and neutral words were investigated in a population with chronic trauma-induced complaints as a result of the Troubles in Northern Ireland. The study used a new version of the word-stem completion task (Michael, Ehlers, & Halligan, 2005) and a word-cue association task. It also assessed the role of dissociation in threat processing. Further evidence of enhanced perceptual priming in PTSD for trauma stimuli was found, along with evidence of lack of conceptual priming for such stimuli. Furthermore, this pattern of priming for trauma-related words was associated with PTSD severity, and state dissociation and PTSD group made significant contributions to predicting perceptual priming for trauma words. The findings shed light on the importance of state dissociation in trauma-related information processing and posttraumatic symptoms.

Improved Nonlinear PCA for Process Monitoring Using Support Vector Data Description

Nonlinear principal component analysis (PCA) based on neural networks has drawn significant attention as a monitoring tool for complex nonlinear processes, but there remains a difficulty with determining the optimal network topology. This paper exploits the advantages of the Fast Recursive Algorithm, where the number of nodes, the location of centres, and the weights between the hidden layer and the output layer can be identified simultaneously for the radial basis function (RBF) networks. The topology problem for the nonlinear PCA based on neural networks can thus be solved. Another problem with nonlinear PCA is that the derived nonlinear scores may not be statistically independent or follow a simple parametric distribution. This hinders its applications in process monitoring since the simplicity of applying predetermined probability distribution functions is lost. This paper proposes the use of a support vector data description and shows that transforming the nonlinear principal components into a feature space allows a simple statistical inference. Results from both simulated and industrial data confirm the efficacy of the proposed method for solving nonlinear principal component problems, compared with linear PCA and kernel PCA.

Networks for systems biology: conceptual connection of data and function

The purpose of this study is to survey the use of networks and network-based methods in systems biology. This study starts with an introduction to graph theory and basic measures allowing to quantify structural properties of networks. Then, the authors present important network classes and gene networks as well as methods for their analysis. In the last part of this study, the authors review approaches that aim at analysing the functional organisation of gene networks and the use of networks in medicine. In addition to this, the authors advocate networks as a systematic approach to general problems in systems biology, because networks are capable of assuming multiple roles that are very beneficial connecting experimental data with a functional interpretation in biological terms.

Network biology: a direct approach to study biological function

In this paper we discuss the dualism of gene networks and their role in systems biology. We argue that gene networks ( 1) can serve as a conceptual framework, forming a fundamental level of a phenomenological description, and ( 2) are a means to represent and analyze data. The latter point does not only allow a systems analysis but is even amenable for a direct approach to study biological function. Here we focus on the clarity of our main arguments and conceptual meaning of gene networks, rather than the causal inference of gene networks from data. (C) 2010 John Wiley & Sons, Inc. WIREs Syst Biol Med 2011 3 379-391 DOI: 10.1002/wsbm.134