Spatial clusters of suicide in Australia

Background: Understanding the spatial distribution of suicide can inform the planning, implementation and evaluation of suicide prevention activity. This study explored spatial clusters of suicide in Australia, and investigated likely socio-demographic determinants of these clusters. Methods: National suicide and population data at a statistical local area (SLA) level were obtained from the Australian Bureau of Statistics for the period of 1999 to 2003. Standardised mortality ratios (SMR) were calculated at the SLA level, and Geographic Information System (GIS) techniques were applied to investigate the geographical distribution of suicides and detect clusters of high risk in Australia. Results: Male suicide incidence was relatively high in the northeast of Australia, and parts of the east coast, central and southeast inland, compared with the national average. Among the total male population and males aged 15 to 34, Mornington Shire had the whole or a part of primary high risk cluster for suicide, followed by the Bathurst-Melville area, one of the secondary clusters in the north coastal area of the Northern Territory. Other secondary clusters changed with the selection of cluster radius and age group. For males aged 35 to 54 years, only one cluster in the east of the country was identified. There was only one significant female suicide cluster near Melbourne while other SLAs had very few female suicide cases and were not identified as clusters. Male suicide clusters had a higher proportion of Indigenous population and lower median socio-economic index for area (SEIFA) than the national average, but their shapes changed with selection of maximum cluster radii setting. Conclusion: This study found high suicide risk clusters at the SLA level in Australia, which appeared to be associated with lower median socio-economic status and higher proportion of Indigenous population. Future suicide prevention programs should focus on these high risk areas.

Guerrilla research tactics: alternative research methods

This case-study explores alternative and experimental methods of research data acquisition, through an emerging research methodology, ‘Guerrilla Research Tactics’ [GRT]. The premise is that the researcher develops covert tactics for attracting and engaging with research participants. These methods range between simple analogue interventions to physical bespoke artefacts which contain an embedded digital link to a live, interactive data collecting resource, such as an online poll, survey or similar. These artefacts are purposefully placed in environments where the researcher anticipates an encounter and response from the potential research participant. The choice of design and placement of artefacts is specific and intentional. DESCRIPTION: Additional information may include: the outcomes; key factors or principles that contribute to its effectiveness; anticipated impact/evidence of impact. This case-study assesses the application of ‘Guerrilla Research Tactics’ [GRT] Methodology as an alternative, engaging and interactive method of data acquisition for higher degree research. Extending Gauntlett’s definition of ‘new creative methods… an alternative to language driven qualitative research methods' (2007), this case-study contributes to the existing body of literature addressing creative and interactive approaches to HDR data collection. The case-study was undertaken with Masters of Architecture and Urban Design research students at QUT, in 2012. Typically students within these creative disciplines view research as a taxing and boring process, distracting them from their studio design focus. An obstacle that many students face, is acquiring data from their intended participant groups. In response to these challenges the authors worked with students to develop creative, fun, and engaging research methods for both the students and their research participants. GRT are influenced by and developed from a combination of participatory action research (Kindon, 2008) and unobtrusive research methods (Kellehear, 1993), to enhance social research. GRT takes un-obtrusive research in a new direction, beyond the typical social research methods. The Masters research students developed alternative methods for acquiring data, which relied on a combination of analogue design interventions and online platforms commonly distributed through social networks. They identified critical issues that required action by the community, and the processes they developed focused on engaging with communities, to propose solutions. Key characteristics shared between both GRT and Guerrilla Activism, are notions of political issues, the unexpected, the unconventional, and being interactive, unique and thought provoking. The trend of Guerrilla Activism has been adapted to: marketing, communication, gardening, craftivism, theatre, poetry, and art. Focusing on the action element and examining elements of current trends within Guerrilla marketing, we believe that GRT can be applied to a range of research areas within various academic disciplines.

Using photography in ‘The Restaurant of the Future’. A useful way to assess portion selection and plate cleaning?

Laboratory-based studies of human dietary behaviour benefit from highly controlled conditions; however, this approach can lack ecological validity. Identifying a reliable method to capture and quantify natural dietary behaviours represents an important challenge for researchers. In this study, we scrutinised cafeteria-style meals in the ‘Restaurant of the Future.’ Self-selected meals were weighed and photographed, both before and after consumption. Using standard portions of the same foods, these images were independently coded to produce accurate and reliable estimates of (i) initial self-served portions, and (ii) food remaining at the end of the meal. Plate cleaning was extremely common; in 86% of meals at least 90% of self-selected calories were consumed. Males ate a greater proportion of their self-selected meals than did females. Finally, when participants visited the restaurant more than once, the correspondence between selected portions was better predicted by the weight of the meal than by its energy content. These findings illustrate the potential benefits of meal photography in this context. However, they also highlight significant limitations, in particular, the need to exclude large amounts of data when one food obscures another.

Hybrid light-emitting diodes based on ZnO nanowires

ZnO is a wide band-gap semiconductor that has several desirable properties for optoelectronic devices. With its large exciton binding energy of ~60 meV, ZnO is a promising candidate for high stability, room-temperature luminescent and lasing devices [1]. Ultraviolet light-emitting diodes (LEDs) based on ZnO homojunctions had been reported [2,3], while preparing stable p-type ZnO is still a challenge. An alternative way is to use other p-type semiconductors, ether inorganic or organic, to form heterojunctions with the naturally n-type ZnO. The crystal structure of wurtzite ZnO can be described as Zn and O atomic layers alternately stacked along the [0001] direction. Because of the fastest growth rate over the polar (0001) facet, ZnO crystals tend to grow into one-dimensional structures, such as nanowires and nanobelts. Since the first report of ZnO nanobelts in 2001 [4], ZnO nanostructures have been particularly studied for their potential applications in nano-sized devices. Various growth methods have been developed for growing ZnO nanostructures, such as chemical vapor deposition (CVD), Metal-organic CVD (MOCVD), aqueous growth and electrodeposition [5]. Based on the successful synthesis of ZnO nanowires/nanorods, various types of hybrid light-emitting diodes (LEDs) were made. Inorganic p-type semiconductors, such as GaN, Si and SiC, have been used as substrates to grown ZnO nanorods/nanowires for making LEDs. GaN is an ideal material that matches ZnO not only in the crystal structure but also in the energy band levels. However, to prepare Mg-doped p-GaN films via epitaxial growth is still costly. In comparison, the organic semiconductors are inexpensive and have many options to select, for a large variety of p-type polymer or small-molecule semiconductors are now commercially available. The organic semiconductor has the limitation of durability and environmental stability. Many polymer semiconductors are susceptible to damage by humidity or mere exposure to oxygen in the air. Also the carrier mobilities of polymer semiconductors are generally lower than the inorganic semiconductors. However, the combination of polymer semiconductors and ZnO nanostructures opens the way for making flexible LEDs. There are few reports on the hybrid LEDs based on ZnO/polymer heterojunctions, some of them showed the characteristic UV electroluminescence (EL) of ZnO. This chapter reports recent progress of the hybrid LEDs based on ZnO nanowires and other inorganic/organic semiconductors. We provide an overview of the ZnO-nanowire-based hybrid LEDs from the perspectives of the device configuration, growth methods of ZnO nanowires and the selection of p-type semiconductors. Also the device performances and remaining issues are presented.

A spectroscopic comparison of YBCO superconductors synthesised by solid-state and co-precipitation methods

Raman spectroscopy, X-ray diffraction (XRD), and scanning electron microscopy (SEM) have been used to compare samples of YBa2Cu3O7 (YBCO) synthesised by the solid-state method and a novel co-precipitation technique. XRD results indicate that YBCO prepared by these two methods are phase pure, however the Raman and SEM results show marked differences between these samples.

A safe system-based approach to selection of clear zones, safety barriers and other roadside treatments

On average, 560 fatal run-off-road crashes occur annually in Australia and 135 in New Zealand. In addition, there are more than 14,000 run-off-road crashes causing injuries each year across both countries. In rural areas, run-off-road casualty crashes constitute 50-60% of all casualty crashes. Their severity is particularly high with more than half of those involved sustaining fatal or serious injuries. This paper reviews the existing approach to roadside hazard risk assessment, selection of clear zones and hazard treatments. It proposes a modified approach to roadside safety evaluation and management. It is a methodology based on statistical modelling of run-off-road casualty crashes, and application of locally developed crash modification factors and severity indices. Clear zones, safety barriers and other roadside design/treatment options are evaluated with a view to minimise fatal and serious injuries – the key Safe System objective. The paper concludes with a practical demonstration of the proposed approach. The paper is based on findings from a four-year Austroads research project into improving roadside safety in the Safe System context.

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.

Adams-Type Methods for the Numerical Solution of Stochastic Ordinary Differential Equations

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. (C) 2000 Elsevier Science B.V. All rights reserved.

High strong order methods for non-commutative stochastic ordinary differential equation systems and the Magnus formula

In recent years considerable attention has been paid to the numerical solution of stochastic ordinary differential equations (SODEs), as SODEs are often more appropriate than their deterministic counterparts in many modelling situations. However, unlike the deterministic case numerical methods for SODEs are considerably less sophisticated due to the difficulty in representing the (possibly large number of) random variable approximations to the stochastic integrals. Although Burrage and Burrage [High strong order explicit Runge-Kutta methods for stochastic ordinary differential equations, Applied Numerical Mathematics 22 (1996) 81-101] were able to construct strong local order 1.5 stochastic Runge-Kutta methods for certain cases, it is known that all extant stochastic Runge-Kutta methods suffer an order reduction down to strong order 0.5 if there is non-commutativity between the functions associated with the multiple Wiener processes. This order reduction down to that of the Euler-Maruyama method imposes severe difficulties in obtaining meaningful solutions in a reasonable time frame and this paper attempts to circumvent these difficulties by some new techniques. An additional difficulty in solving SODEs arises even in the Linear case since it is not possible to write the solution analytically in terms of matrix exponentials unless there is a commutativity property between the functions associated with the multiple Wiener processes. Thus in this present paper first the work of Magnus [On the exponential solution of differential equations for a linear operator, Communications on Pure and Applied Mathematics 7 (1954) 649-673] (applied to deterministic non-commutative Linear problems) will be applied to non-commutative linear SODEs and methods of strong order 1.5 for arbitrary, linear, non-commutative SODE systems will be constructed - hence giving an accurate approximation to the general linear problem. Secondly, for general nonlinear non-commutative systems with an arbitrary number (d) of Wiener processes it is shown that strong local order I Runge-Kutta methods with d + 1 stages can be constructed by evaluated a set of Lie brackets as well as the standard function evaluations. A method is then constructed which can be efficiently implemented in a parallel environment for this arbitrary number of Wiener processes. Finally some numerical results are presented which illustrate the efficacy of these approaches. (C) 1999 Elsevier Science B.V. All rights reserved.

General order conditions for stochastic Runge-Kutta methods for both commuting and non-commuting stochastic ordinary differential equation systems

In many modeling situations in which parameter values can only be estimated or are subject to noise, the appropriate mathematical representation is a stochastic ordinary differential equation (SODE). However, unlike the deterministic case in which there are suites of sophisticated numerical methods, numerical methods for SODEs are much less sophisticated. Until a recent paper by K. Burrage and P.M. Burrage (1996), the highest strong order of a stochastic Runge-Kutta method was one. But K. Burrage and P.M. Burrage (1996) showed that by including additional random variable terms representing approximations to the higher order Stratonovich (or Ito) integrals, higher order methods could be constructed. However, this analysis applied only to the one Wiener process case. In this paper, it will be shown that in the multiple Wiener process case all known stochastic Runge-Kutta methods can suffer a severe order reduction if there is non-commutativity between the functions associated with the Wiener processes. Importantly, however, it is also suggested how this order can be repaired if certain commutator operators are included in the Runge-Kutta formulation. (C) 1998 Elsevier Science B.V. and IMACS. All rights reserved.

A bound on the maximum strong order of stochastic Runge-Kutta methods for stochastic ordinary differential equations

In Burrage and Burrage [1] it was shown that by introducing a very general formulation for stochastic Runge-Kutta methods, the previous strong order barrier of order one could be broken without having to use higher derivative terms. In particular, methods of strong order 1.5 were developed in which a Stratonovich integral of order one and one of order two were present in the formulation. In this present paper, general order results are proven about the maximum attainable strong order of these stochastic Runge-Kutta methods (SRKs) in terms of the order of the Stratonovich integrals appearing in the Runge-Kutta formulation. In particular, it will be shown that if an s-stage SRK contains Stratonovich integrals up to order p then the strong order of the SRK cannot exceed min{(p + 1)/2, (s - 1)/2), p greater than or equal to 2, s greater than or equal to 3 or 1 if p = 1.