A Bayesian model predicts the response of axons to molecular gradients

Axon guidance by molecular gradients plays a crucial role in wiring up the nervous system. However, the mechanisms axons use to detect gradients are largely unknown. We first develop a Bayesian “ideal observer” analysis of gradient detection by axons, based on the hypothesis that a principal constraint on gradient detection is intrinsic receptor binding noise. Second, from this model, we derive an equation predicting how the degree of response of an axon to a gradient should vary with gradient steepness and absolute concentration. Third, we confirm this prediction quantitatively by performing the first systematic experimental analysis of how axonal response varies with both these quantities. These experiments demonstrate a degree of sensitivity much higher than previously reported for any chemotacting system. Together, these results reveal both the quantitative constraints that must be satisfied for effective axonal guidance and the computational principles that may be used by the underlying signal transduction pathways, and allow predictions for the degree of response of axons to gradients in a wide variety of in vivo and in vitro settings.

The Bayesian conditional independence model for measurement error: applications in ecology

The measurement error model is a well established statistical method for regression problems in medical sciences, although rarely used in ecological studies. While the situations in which it is appropriate may be less common in ecology, there are instances in which there may be benefits in its use for prediction and estimation of parameters of interest. We have chosen to explore this topic using a conditional independence model in a Bayesian framework using a Gibbs sampler, as this gives a great deal of flexibility, allowing us to analyse a number of different models without losing generality. Using simulations and two examples, we show how the conditional independence model can be used in ecology, and when it is appropriate.

Young children as regenerative tissue donors : considering the need for legal reform in light of divergent ethical approaches

In Australia, young children who lack decision-making capacity can have regenerative tissue removed to treat another person suffering from a severe or life-threatening disease. While great good can potentially result from this as the recipient’s life may be saved, ethical unease remains over the ‘use’ of young children in this way. This paper examines the ethical approaches that have featured in the debate over the acceptability and limits of this practice, and how these are reflected in Australia’s legal regime governing removal of tissue from young children. This analysis demonstrates a troubling dichotomy within the Australia’s laws that requires decision-makers to adopt inconsistent ethical approaches depending on where a donor child is situated. It is argued that this inconsistency in approach warrants legal reform of this ethically sensitive issue.

Application of machine learning in fault diagnostics of mechanical systems

A diagnostic method based on Bayesian Networks (probabilistic graphical models) is presented. Unlike conventional diagnostic approaches, in this method instead of focusing on system residuals at one or a few operating points, diagnosis is done by analyzing system behavior patterns over a window of operation. It is shown how this approach can loosen the dependency of diagnostic methods on precise system modeling while maintaining the desired characteristics of fault detection and diagnosis (FDD) tools (fault isolation, robustness, adaptability, and scalability) at a satisfactory level. As an example, the method is applied to fault diagnosis in HVAC systems, an area with considerable modeling and sensor network constraints.

Computational approaches for modelling intrinsic noise and delays in genetic regulatory networks

This chapter focuses on the interactions and roles between delays and intrinsic noise effects within cellular pathways and regulatory networks. We address these aspects by focusing on genetic regulatory networks that share a common network motif, namely the negative feedback loop, leading to oscillatory gene expression and protein levels. In this context, we discuss computational simulation algorithms for addressing the interplay of delays and noise within the signaling pathways based on biological data. We address implementational issues associated with efficiency and robustness. In a molecular biology setting we present two case studies of temporal models for the Hes1 gene (Monk, 2003; Hirata et al., 2002), known to act as a molecular clock, and the Her1/Her7 regulatory system controlling the periodic somite segmentation in vertebrate embryos (Giudicelli and Lewis, 2004; Horikawa et al., 2006).

Choreographic approaches to music composition for a new musical interface : the eMic

Gesture in performance is widely acknowledged in the literature as an important element in making a performance expressive and meaningful. The body has been shown to play an important role in the production and perception of vocal performance in particular. This paper is interested in the role of gesture in creative works that seek to extend vocal performance via technology. A creative work for vocal performer, laptop computer and a Human Computer Interface called the eMic (Extended Microphone Stand Interface controller) is presented as a case study, to explore the relationships between movement, voice production, and musical expression. The eMic is an interface for live vocal performance that allows the singers’ gestures and interactions with a sensor based microphone stand to be captured and mapped to musical parameters. The creative work discussed in this paper presents a new compositional approach for the eMic by working with movement as a starting point for the composition and thus using choreographed gesture as the basis for musical structures. By foregrounding the body and movement in the creative process, the aim is to create a more visually engaging performance where the performer is able to more effectively use the body to express their musical objectives.

Bayesian models for the determination of resonant frequencies in a DI diesel engine

A time series method for the determination of combustion chamber resonant frequencies is outlined. This technique employs the use of Markov-chain Monte Carlo (MCMC) to infer parameters in a chosen model of the data. The development of the model is included and the resonant frequency is characterised as a function of time. Potential applications for cycle-by-cycle analysis are discussed and the bulk temperature of the gas and the trapped mass in the combustion chamber are evaluated as a function of time from resonant frequency information.

Approaches to acquiring ‘doctorateness’ in the creative industries : an Australian perspective

Over the last two decades, particularly in Australia and the UK, the doctoral landscape has changed considerably with increasingly hybridised approaches to methodologies and research strategies as well as greater choice of examinable outputs. This paper provides an overview of doctoral practices that are emerging in the context of the creative industries, with a focus on practice-led approaches within the Doctor of Philosophy and recent developments in professional doctorates, from a predominantly Australian perspective. In interrogating what constitutes ‘doctorateness’ in this context, the paper examines some of the diverse theoretical principles which foreground the practitioner/researcher, methodological approaches that incorporate tacit knowledge and reflective practice together with qualitative strategies, blended learning delivery modes, and flexible doctoral outputs; and how these are shaping this shifting environment. The paper concludes with a study of the Doctor of Creative Industries at Queensland University of Technology as one model of an interdisciplinary professional research doctorate.

Year 7 students’ approaches to understanding and solving NAPLAN numeracy problems

This study investigated how the interpretation of mathematical problems by Year 7 students impacted on their ability to demonstrate what they can do in NAPLAN numeracy testing. In the study, mathematics is viewed as a culturally and socially determined system of signs and signifiers that establish the meaning, origins and importance of mathematics. The study hypothesises that students are unable to succeed in NAPLAN numeracy tests because they cannot interpret the questions, even though they may be able to perform the necessary calculations. To investigate this, the study applied contemporary theories of literacy to the context of mathematical problem solving. A case study design with multiple methods was used. The study used a correlation design to explore the connections between NAPLAN literacy and numeracy outcomes of 198 Year 7 students in a Queensland school. Additionally, qualitative methods provided a rich description of the effect of the various forms of NAPLAN numeracy questions on the success of ten Year 7 students in the same school. The study argues that there is a quantitative link between reading and numeracy. It illustrates that interpretation (literacy) errors are the most common error type in the selected NAPLAN questions, made by students of all abilities. In contrast, conceptual (mathematical) errors are less frequent amongst more capable students. This has important implications in preparing students for NAPLAN numeracy tests. The study concluded by recommending that increased focus on the literacies of mathematics would be effective in improving NAPLAN results.

Reshaping Doctoral Education : International Approaches and Pedagogies

The number of doctorates being awarded around the world has almost doubled over the last ten years, propelling it from a small elite enterprise into a large and ever growing international market. Within the context of increasing numbers of doctoral students this book examines the new doctorate environment and the challenges it is starting to face. Drawing on research from around the world the individual authors contribute to a previously under-represented focus of theorising the emerging practices of doctoral education and the shape of change in this arena. Key aspects, expertly discussed by contributors from the UK, USA, Australia, New Zealand, China, South Africa, Sweden and Denmark include: -the changing nature of doctoral education -the need for systematic and principled accounts of doctoral pedagogies -the importance of disciplinary specificity -the relationship between pedagogy and knowledge generation -issues of transdisciplinarity. Reshaping Doctoral Education provides rich accounts of traditional and more innovative pedagogical practices within a range of doctoral systems in different disciplines, professional fields and geographical locations, providing the reader with a trustworthy and scholarly platform from which to design the doctoral experience. It will prove an essential resource for anyone involved in doctorate studies, whether as students, supervisors, researchers, administrators, teachers or mentors.