Enhanced student learning in accounting utilising web-based technology, peer-review feedback and reflective practices: A learning community approach to assessment

Higher education is becoming a major driver of economic competitiveness in an increasingly knowledge-driven global economy. Maintaining the competitive edge has seen an increase in public accountability of higher education institutions through the mechanism of ranking universities based on the quality of their teaching and learning outcomes. As a result, assessment processes are under scrutiny, creating tensions between standardisation and measurability and the development of creative and reflective learners. These tensions are further highlighted in the context of large undergraduate subjects, learner diversity and time-poor academics and students. Research suggests that high level and complex learning is best developed when assessment, combined with effective feedback practices, involves students as partners in these processes. This article reports on a four-phase, cross-institution and cross-discipline project designed to embed peer-review processes as part of the assessment in two large, undergraduate accounting classes. Using a social constructivist view of learning, which emphasises the role of both teacher and learner in the development of complex cognitive understandings, we undertook an iterative process of peer review. Successive phases built upon students’ feedback and achievements and input from language/learning and curriculum experts to improve the teaching and learning outcomes.

Design of a tangible data visualization (extended)

In this paper we describe the design of DNA Jewelry, which is a wearable tangible data representation of personal DNA profile data. An iterative design process was followed to develop a 3D form-language that could be mapped to standard DNA profile data, with the aim of retaining readability of data while also producing an aesthetically pleasing and unique result in the area of personalised design. The work explores design issues with the production of data tangibles, contributes to a growing body of research exploring tangible representations of data and highlights the importance of approaches that move between technology, art and design.

Zombies on the road: A holistic design approach to balancing gamification and safe driving

This paper explores novel driving experiences that make use of gamification and augmented reality in the car. We discuss our design considerations, which are grounded in road safety psychology and video game design theory. We aim to address the tension between safe driving practices and player engagement. Specifically, we propose a holistic, iterative thinking process inspired by game design cognition and share our insights generated through the application of this process. We present preliminary game concepts that blend digital components with physical elements from the driving environment. We further highlight how this design process helped us to iteratively evolve these concepts towards being safer while maintaining fun. These insights and game design cognition itself will be useful to the AutomotiveUI community investigating similar novel driving experiences.

Understanding the relationship between interfragmentary movement and callus growth in fracture healing: A novel computational approach

Introduction & Aims Optimising fracture treatments requires a sound understanding of relationships between stability, callus development and healing outcomes. This has been the goal of computational modelling, but discrepancies remain between simulations and experimental results. We compared healing patterns vs fixation stiffness between a novel computational callus growth model and corresponding experimental data. Hypothesis We hypothesised that callus growth is stimulated by diffusible signals, whose production is in turn regulated by mechanical conditions at the fracture site. We proposed that introducing this scheme into computational models would better replicate the observed tissue patterns and the inverse relationship between callus size and fixation stiffness. Method Finite element models of bone healing under stiff and flexible fixation were constructed, based on the parameters of a parallel rat femoral osteotomy study. An iterative procedure was implemented, to simulate the development of callus and its mechanical regulation. Tissue changes were regulated according to published mechano-biological criteria. Predictions of healing patterns were compared between standard models, with a pre-defined domain for callus development, and a novel approach, in which periosteal callus growth is driven by a diffusible signal. Production of this signal was driven by local mechanical conditions. Finally, each model’s predictions were compared to the corresponding histological data. Results Models in which healing progressed within a prescribed callus domain predicted that greater interfragmentary movements would displace early periosteal bone formation further from the fracture. This results from artificially large distortional strains predicted near the fracture edge. While experiments showed increased hard callus size under flexible fixation, this was not reflected in the standard models. Allowing the callus to grow from a thin soft tissue layer, in response to a mechanically stimulated diffusible signal, results in a callus shape and tissue distribution closer to those observed histologically. Importantly, the callus volume increased with increasing interfragmentary movement. Conclusions A novel method to incorporate callus growth into computational models of fracture healing allowed us to successfully capture the relationship between callus size and fixation stability observed in our rat experiments. This approach expands our toolkit for understanding the influence of different fixation strategies on healing outcomes.

Genome-wide interaction analysis reveals replicated epistatic effects on brain structure

The discovery of several genes that affect the risk for Alzheimer's disease ignited a worldwide search for single-nucleotide polymorphisms (SNPs), common genetic variants that affect the brain. Genome-wide search of all possible SNP-SNP interactions is challenging and rarely attempted because of the complexity of conducting approximately 1011 pairwise statistical tests. However, recent advances in machine learning, for example, iterative sure independence screening, make it possible to analyze data sets with vastly more predictors than observations. Using an implementation of the sure independence screening algorithm (called EPISIS), we performed a genome-wide interaction analysis testing all possible SNP-SNP interactions affecting regional brain volumes measured on magnetic resonance imaging and mapped using tensor-based morphometry. We identified a significant SNP-SNP interaction between rs1345203 and rs1213205 that explains 1.9% of the variance in temporal lobe volume. We mapped the whole brain, voxelwise effects of the interaction in the Alzheimer's Disease Neuroimaging Initiative data set and separately in an independent replication data set of healthy twins (Queensland Twin Imaging). Each additional loading in the interaction effect was associated with approximately 5% greater brain regional brain volume (a protective effect) in both Alzheimer's Disease Neuroimaging Initiative and Queensland Twin Imaging samples.

Exhaustive search of the SNP-sNP interactome identifies epistatic effects on brain volume in two cohorts

The SNP-SNP interactome has rarely been explored in the context of neuroimaging genetics mainly due to the complexity of conducting approximately 10(11) pairwise statistical tests. However, recent advances in machine learning, specifically the iterative sure independence screening (SIS) method, have enabled the analysis of datasets where the number of predictors is much larger than the number of observations. Using an implementation of the SIS algorithm (called EPISIS), we used exhaustive search of the genome-wide, SNP-SNP interactome to identify and prioritize SNPs for interaction analysis. We identified a significant SNP pair, rs1345203 and rs1213205, associated with temporal lobe volume. We further examined the full-brain, voxelwise effects of the interaction in the ADNI dataset and separately in an independent dataset of healthy twins (QTIM). We found that each additional loading in the epistatic effect was associated with approximately 5% greater brain regional brain volume (a protective effect) in both the ADNI and QTIM samples.

Warmwaters

This project originated from both investigation of the musicalisation of theatre and impact of gender upon contemporary physical comedy. Developed as a ‘music first’ proposition, the initial experiment was to blend music and theatre so they were indistinguishable. Musicalising theatre, and theatricalising music. This established a covert intermediality with the potential to work in theatre or music venues. An iterative cycle of writing, performance, and videography over two years in venues ranging from small cafes to Woodford Folk Festival resulted in a full-length performance premiering at Brisbane Powerhouse’s Queensland Cabaret Festival 2015. The soundtrack to the show was recorded as a full-length album at QUT’s Gasworks Studio and released in 2014. It’s become clear that male/female musical comedy acts are an extremely rare pairing. Certain preconceptions about gender and comedy complicate the field; indeed the comic tropes of the double act which the Warmwaters flow around and through. Brian Logan (2011) even poses that “the male-female dynamic militate[s] against comedy”. This performance-led research draws on Comedy Studies to examine three classic formulations of the comic duo as they are manifested at critical incidents in the Warmwaters’ show. These moments are examined in terms of comic functionality and gender, evaluating and potentially reformulating them, whilst working towards a better understanding of the relative scarcity of the male/female musical comedy duo. Prototypes have been performed in various venues, utilising performance as research: cycles in which discoveries made during unpredictable gigs in music venues are captured on video, transcribed, rewritten, then fed back into live performance.

A preconditioned numerical solver for stiff nonlinear reaction-diffusion equations with fractional Laplacians that avoids dense matrices

The numerical solution of fractional partial differential equations poses significant computational challenges in regard to efficiency as a result of the spatial nonlocality of the fractional differential operators. The dense coefficient matrices that arise from spatial discretisation of these operators mean that even one-dimensional problems can be difficult to solve using standard methods on grids comprising thousands of nodes or more. In this work we address this issue of efficiency for one-dimensional, nonlinear space-fractional reaction–diffusion equations with fractional Laplacian operators. We apply variable-order, variable-stepsize backward differentiation formulas in a Jacobian-free Newton–Krylov framework to advance the solution in time. A key advantage of this approach is the elimination of any requirement to form the dense matrix representation of the fractional Laplacian operator. We show how a banded approximation to this matrix, which can be formed and factorised efficiently, can be used as part of an effective preconditioner that accelerates convergence of the Krylov subspace iterative solver. Our approach also captures the full contribution from the nonlinear reaction term in the preconditioner, which is crucial for problems that exhibit stiff reactions. Numerical examples are presented to illustrate the overall effectiveness of the solver.

A thorough investigation of the interdependent behavior of prestressed system

Due to the existing of many prestressed members in the structural system, the interdependent behavior of all prestressed members is the main concern in the analysis of the pretension process. A thorough investigation of this mutual effect is essential for an effective, reliable, and optimal analysis. Focus on this aspect, this paper presents an investigation of the interdependent behavior of all prestressed members in the whole structural system based on influence matrix (IFM). Four different types of IFM are introduced. Two different solving methods are brought forth to analyze the pretension process. The direct solving method solves for the accurate solution, whereas the iterative solving method repeatedly amends to achieve an approximate solution. A numerical example is then conducted. The result shows that various kinds of complicated batched and repeated tensioning schemes can be analyzed reliably, effectively, and completely based on IFM.

Rheumatoid arthritis sera react with a phage-displayed peptide selected by a monoclonal antibody to type II collagen that has homology to EBNA-1

Antibodies to type II collagen, and to Epstein Barr virus nuclear antigen-1 (EBNA-1) have been associated with rheumatoid arthritis (RA). In studies involving probing of phage-displayed random peptide libraries with an antibody to type II collagen, CII-C1, we observed that among 17 phagotopes selected 5 expressed peptides with homology with the sequence of EBNA-1. The residues in common were RLPFG. Hence we tested sera from 50 patients with RA, of whom 26 had antibodies to native type II collagen, and 43 healthy controls, for reactivity by ELISA with a phagotope selected 4 times, which expressed the peptide RRLPFGSQM. Eight RA sera (16%) but no normal sera reacted with the phagotope (p = 0.025). This reactivity could not be correlated with reactivity of RA sera with EBNA-1 by semi-quantitative western blot, with which reactivity occurred in 78% of RA patients and 81% of controls. Evidence for molecular mimicry was not found insofar as the phagotope did not inhibit reactivity of RA sera with EBNA-1 and CII-C1 was not reactive with EBNA-1. We conclude that the reactivity of the RA sera with the phagotope is most likely due to the phagotope being a mimic of an epitope of type II collagen for a proportion of RA sera.

A principled experimental design approach to Big Data analysis

Big Datasets are endemic, but they are often notoriously difficult to analyse because of their size, heterogeneity, history and quality. The purpose of this paper is to open a discourse on the use of modern experimental design methods to analyse Big Data in order to answer particular questions of interest. By appealing to a range of examples, it is suggested that this perspective on Big Data modelling and analysis has wide generality and advantageous inferential and computational properties. In particular, the principled experimental design approach is shown to provide a flexible framework for analysis that, for certain classes of objectives and utility functions, delivers near equivalent answers compared with analyses of the full dataset under a controlled error rate. It can also provide a formalised method for iterative parameter estimation, model checking, identification of data gaps and evaluation of data quality. Finally, it has the potential to add value to other Big Data sampling algorithms, in particular divide-and-conquer strategies, by determining efficient sub-samples.

Whole exome sequencing is an efficient and sensitive method for detection of germline mutations in patients with phaeochromcytomas and paragangliomas

Background Genetic testing is recommended when the probability of a disease-associated germline mutation exceeds 10%. Germline mutations are found in approximately 25% of individuals with phaeochromcytoma (PCC) or paraganglioma (PGL); however, genetic heterogeneity for PCC/PGL means many genes may require sequencing. A phenotype-directed iterative approach may limit costs but may also delay diagnosis, and will not detect mutations in genes not previously associated with PCC/PGL. Objective To assess whether whole exome sequencing (WES) was efficient and sensitive for mutation detection in PCC/PGL. Methods Whole exome sequencing was performed on blinded samples from eleven individuals with PCC/PGL and known mutations. Illumina TruSeq™ (Illumina Inc, San Diego, CA, USA) was used for exome capture of seven samples, and NimbleGen SeqCap EZ v3.0 (Roche NimbleGen Inc, Basel, Switzerland) for five samples (one sample was repeated). Massive parallel sequencing was performed on multiplexed samples. Sequencing data were called using Genome Analysis Toolkit and annotated using annovar. Data were assessed for coding variants in RET, NF1, VHL, SDHD, SDHB, SDHC, SDHA, SDHAF2, KIF1B, TMEM127, EGLN1 and MAX. Target capture of five exome capture platforms was compared. Results Six of seven mutations were detected using Illumina TruSeq™ exome capture. All five mutations were detected using NimbleGen SeqCap EZ v3.0 platform, including the mutation missed using Illumina TruSeq™ capture. Target capture for exons in known PCC/PGL genes differs substantially between platforms. Exome sequencing was inexpensive (<$A800 per sample for reagents) and rapid (results <5 weeks from sample reception). Conclusion Whole exome sequencing is sensitive, rapid and efficient for detection of PCC/PGL germline mutations. However, capture platform selection is critical to maximize sensitivity.

Emotional food design: From designing food products to designing food systems

Contemporary food systems promote the consumption of highly processed foods of limited nutrition, contributing to overweight and obesity, diet-related disease and significant financial burden on healthcare systems. In part, this has resulted from highly successful design, development and marketing strategies for processed foods. The successful application of such strategies to healthy food options, and the services and business plans that accompany them, could assist in enhancing health and alleviating burden on health care systems. Product designers have long been aware of the importance of intertwining emotional experiences with new products. However, a lack of theoretical precision exists for applying emotional design beyond food products, to the food systems, services and business models that drive them. This article explores emotional design within the context of food and food systems and proposes a new concept – Emotional Food Design (EFD), through which emotional design is integrated across levels of a food system. EFD complements the dominating deductive view of food systems research with an abductive iterative design approach contextualized within the creation of new food products, services and business models and their associated emotional attachments. This paper concludes by outlining what EFD can offer to reorient food systems to successfully promote healthy eating.

Single-cell-precision microplasma-induced cancer cell apoptosis

The issue of single-cell control has recently attracted enormous interest. However, in spite of the presently achievable intracellular-level physiological probing through bio-photonics, nano-probe-based, and some other techniques, the issue of inducing selective, single-cell-precision apoptosis, without affecting neighbouring cells remains essentially open. Here we resolve this issue and report on the effective single-cell-precision cancer cell treatment using the reactive chemistry of the localized corona-type plasma discharge around a needle-like electrode with the spot size ∼1 µm. When the electrode is positioned with the micrometer precision against a selected cell, a focused and highly-localized micro-plasma discharge induces apoptosis in the selected individual HepG2 and HeLa cancer cells only, without affecting any surrounding cells, even in small cell clusters. This is confirmed by the real-time monitoring of the morphological and structural changes at the cellular and cell nucleus levels after the plasma exposure.

The effect of thermal radiation on the natural convection boundary layer flow over a wavy horizontal surface

In this article, natural convection boundary layer flow is investigated over a semi-infinite horizontal wavy surface. Such an irregular (wavy) surface is used to exchange heat with an external radiating fluid which obeys Rosseland diffusion approximation. The boundary layer equations are cast into dimensionless form by introducing appropriate scaling. Primitive variable formulations (PVF) and stream function formulations (SFF) are independently used to transform the boundary layer equations into convenient form. The equations obtained from the former formulations are integrated numerically via implicit finite difference iterative scheme whereas equations obtained from lateral formulations are simulated through Keller-box scheme. To validate the results, solutions produced by above two methods are compared graphically. The main parameters: thermal radiation parameter and amplitude of the wavy surface are discussed categorically in terms of shear stress and rate of heat transfer. It is found that wavy surface increases heat transfer rate compared to the smooth wall. Thus optimum heat transfer is accomplished when irregular surface is considered. It is also established that high amplitude of the wavy surface in the boundary layer leads to separation of fluid from the plate.