Language and utilisation of emergency care in Queensland

Objective: To compare access and utilisation of EDs in Queensland public hospitals between people who speak only English at home and those who speak another language at home. Methods: A retrospective analysis of a Queensland statewide hospital ED dataset (ED Information System) from 1 January 2008 to 31 December 2010 was conducted. Access to ED care was measured by the proportion of the state’s population attending EDs. Logistic regression analyses were performed to determine the relationships between ambulance use and language, and between hospital admission and language, both after adjusting for age, sex and triage category. Results: The ED utilisation rate was highest in English only speakers (290 per 1000 population), followed by Arabic speakers (105), and lowest among German speakers (30). Compared with English speakers, there were lower rates of ambulance use in Chinese (odds ratio 0.50, 95% confidence interval, 0.47–0.54), Vietnamese (0.87, 0.79–0.95), Arabic (0.87, 0.78–0.97), Spanish (0.56, 0.50–0.62), Italian (0.88, 0.80–0.96), Hindi (0.61, 0.53–0.70) and German (0.87, 0.79–0.90) speakers. Compared with English speakers, German speakers had higher admission rates (odds ratio 1.17, 95% confidence interval, 1.02–1.34), whereas there were lower admission rates in Chinese (0.90, 0.86–0.99), Arabic (0.76, 0.67–0.85) and Spanish (0.83, 0.75–0.93) speakers. Conclusion: This study showed that there was a significant association between lower utilisation of emergency care and speaking languages other than English at home. Further researches are needed using in-depth methodology to investigate if there are language barriers in accessing emergency care in Queensland.

The smart skies project : enabling technologies for future airspace environments

This paper summarises the achievements of the Smart Skies Project, a three-year, multi-award winning international project that researched, developed and extensively flight tested four enabling aviation technologies: an electrooptical mid-air collision avoidance system, a static obstacle avoidance system, a mobile ground-based air traffic surveillance system, and a global automated airspace separation management system. The project included the development of manned and unmanned flight test aircraft, which were used to characterise the performance of the prototype systems for a range of realistic scenarios under a variety of environmental conditions. In addition to the collection of invaluable flight data, the project achieved world-firsts in the demonstration of future automated collision avoidance and separation management concepts. This paper summarises these outcomes, the overall objectives of the project, the research and the development of the prototype systems, the engineering of the flight test systems, and the results obtained from flight-testing.

Electoral behaviour in the 2010 Australian federal election

All elections are unique, but the Australian federal election of 2010 was unusual for many reasons. It came in the wake of the unprecedented ousting of the Prime Minister who had led the Australian Labor Party to a landslide victory, after eleven years in opposition, at the previous election in 2007. In a move that to many would have been unthinkable, Kevin Rudd’s increasing unpopularity within his own parliamentary party finally took its toll and in late June he was replaced by his deputy, Julia Gillard. Thus the second unusual feature of the election was that it was contested by Australia’s first female prime minister. The third unusual feature was that the election almost saw a first-term government, with a comfortable majority, defeated. Instead it resulted in a hung parliament, for the first time since 1940, and Labor scraped back into power as a minority government, supported by three independents and the first member of the Australian Greens ever to be elected to the House of Representatives. The Coalition Liberal and National opposition parties themselves had a leader of only eight months standing, Tony Abbott, whose ascension to the position had surprised more than a few. This was the context for an investigation of voting behaviour in the 2010 election....

Leadership change, policy issues and voter defection in the 2010 Australian election

Leadership change formed the backdrop to the 2010 Australian federal election, with the replacement of Kevin Rudd as prime minister by Julia Gillard, the country’s first female prime minister. This article uses the 2010 Australian Election Study, a post-election survey of voters, to examine patterns of voter defection between the 2007 and 2010 elections. The results show that the predominant influence on defection was how voters rated the leaders. Julia Gillard was particularly popular among female voters and her overall impact on the vote was slightly greater than that of Tony Abbott. Policy issues were second in importance after leadership, particularly for those moving from the Coalition to Labor, who were concerned about health and unemployment. Labor defectors to the Greens particularly disliked Labor’s education policies. Overall, the results point to the enduring importance of leaders as the predominant influence on how voters cast their ballot.

Heavy Weather

Heavy Weather was a monumental sculptural work produced for the prestigious McClelland National Sculpture Survey in 2012. The work was a large cold-cast aluminium figure depicting the artist in athletic costume arching backwards across the top of massive boulder. The pose of the figure was derived from the ‘Fosbury flop’, the awkward backwards manoeuvre associated with high-jump event. The boulder was a portrait of a different kind - a remake of the Ian Fairweather memorial on Bribie Island but elongated to tower upwards. The work thus emphasised two contrasting impressions of movement – immense inertia and writhing agility. Heavy Weather sought to bring these two opposing forces together as a way of representing the tensions that shape our relationship with objects. In so doing, the work contributed to the artist’s ongoing exploration of sculpture, self-portraiture and the civic monument. The work was promoted nationally including the Art Guide and the Melbourne Review. It was also the subject of a article in the Australian Art Collector.

A multi-scaled approach for simulating chemical reaction systems

In this paper we give an overview of some very recent work, as well as presenting a new approach, on the stochastic simulation of multi-scaled systems involving chemical reactions. In many biological systems (such as genetic regulation and cellular dynamics) there is a mix between small numbers of key regulatory proteins, and medium and large numbers of molecules. In addition, it is important to be able to follow the trajectories of individual molecules by taking proper account of the randomness inherent in such a system. We describe different types of simulation techniques (including the stochastic simulation algorithm, Poisson Runge-Kutta methods and the balanced Euler method) for treating simulations in the three different reaction regimes: slow, medium and fast. We then review some recent techniques on the treatment of coupled slow and fast reactions for stochastic chemical kinetics and present a new approach which couples the three regimes mentioned above. We then apply this approach to a biologically inspired problem involving the expression and activity of LacZ and LacY proteins in E coli, and conclude with a discussion on the significance of this work. (C) 2004 Elsevier Ltd. All rights reserved.

Numerical simulation of stochastic ordinary differential equations in biomathematical modelling

In this work we discuss the effects of white and coloured noise perturbations on the parameters of a mathematical model of bacteriophage infection introduced by Beretta and Kuang in [Math. Biosc. 149 (1998) 57]. We numerically simulate the strong solutions of the resulting systems of stochastic ordinary differential equations (SDEs), with respect to the global error, by means of numerical methods of both Euler-Taylor expansion and stochastic Runge-Kutta type.

Numerical methods for strong solutions of stochastic differential equations : an overview

This paper gives a review of recent progress in the design of numerical methods for computing the trajectories (sample paths) of solutions to stochastic differential equations. We give a brief survey of the area focusing on a number of application areas where approximations to strong solutions are important, with a particular focus on computational biology applications, and give the necessary analytical tools for understanding some of the important concepts associated with stochastic processes. We present the stochastic Taylor series expansion as the fundamental mechanism for constructing effective numerical methods, give general results that relate local and global order of convergence and mention the Magnus expansion as a mechanism for designing methods that preserve the underlying structure of the problem. We also present various classes of explicit and implicit methods for strong solutions, based on the underlying structure of the problem. Finally, we discuss implementation issues relating to maintaining the Brownian path, efficient simulation of stochastic integrals and variable-step-size implementations based on various types of control.

High strong order explicit Runge-Kutta methods for stochastic ordinary differential equations

The pioneering work of Runge and Kutta a hundred years ago has ultimately led to suites of sophisticated numerical methods suitable for solving complex systems of deterministic ordinary differential equations. However, in many modelling situations, the appropriate representation is a stochastic differential equation and here numerical methods are much less sophisticated. In this paper a very general class of stochastic Runge-Kutta methods is presented and much more efficient classes of explicit methods than previous extant methods are constructed. In particular, a method of strong order 2 with a deterministic component based on the classical Runge-Kutta method is constructed and some numerical results are presented to demonstrate the efficacy of this approach.

Order conditions of stochastic Runge-Kutta methods by B-series

In this paper, general order conditions and a global convergence proof are given for stochastic Runge Kutta methods applied to stochastic ordinary differential equations ( SODEs) of Stratonovich type. This work generalizes the ideas of B-series as applied to deterministic ordinary differential equations (ODEs) to the stochastic case and allows a completely general formalism for constructing high order stochastic methods, either explicit or implicit. Some numerical results will be given to illustrate this theory.

The influence of online reviews on consumers’ attributions of service quality and control for service standards in hotels

Online travel reviews are emerging as a powerful source of information affecting tourists' pre-purchase evaluation of a hotel organization. This trend has highlighted the need for a greater understanding of the impact of online reviews on consumer attitudes and behaviors. In view of this need, we investigate the influence of online hotel reviews on consumers' attributions of service quality and firms' ability to control service delivery. An experimental design was used to examine the effects of four independent variables: framing; valence; ratings; and target. The results suggest that in reviews evaluating a hotel, remarks related to core services are more likely to induce positive service quality attributions. Recent reviews affect customers' attributions of controllability for service delivery, with negative reviews exerting an unfavorable influence on consumers' perceptions. The findings highlight the importance of managing the core service and the need for managers to act promptly in addressing customer service problems.

Numerical solutions of stochastic differential equations – implementation and stability issues

Stochastic differential equations (SDEs) arise fi om physical systems where the parameters describing the system can only be estimated or are subject to noise. There has been much work done recently on developing numerical methods for solving SDEs. This paper will focus on stability issues and variable stepsize implementation techniques for numerically solving SDEs effectively.