Developing the atlas of cancer in Queensland : methodological issues

Background: Achieving health equity has been identified as a major challenge, both internationally and within Australia. Inequalities in cancer outcomes are well documented, and must be quantified before they can be addressed. One method of portraying geographical variation in data uses maps. Recently we have produced thematic maps showing the geographical variation in cancer incidence and survival across Queensland, Australia. This article documents the decisions and rationale used in producing these maps, with the aim to assist others in producing chronic disease atlases. Methods: Bayesian hierarchical models were used to produce the estimates. Justification for the cancers chosen, geographical areas used, modelling method, outcome measures mapped, production of the adjacency matrix, assessment of convergence, sensitivity analyses performed and determination of significant geographical variation is provided. Conclusions: Although careful consideration of many issues is required, chronic disease atlases are a useful tool for assessing and quantifying geographical inequalities. In addition they help focus research efforts to investigate why the observed inequalities exist, which in turn inform advocacy, policy, support and education programs designed to reduce these inequalities.

Aspiration levels and educational choices: An experimental study

The explanation of social inequalities in education is still a debated issue in economics. Recent empirical studies tend to downplay the potential role of credit constraint. This article tests a different potential explanation of social inequalities in education, specifically that social differences in aspiration level result in different educational choices. Having existed for a long time in the sociology of education, this explanation can be justified if aspiration levels are seen as reference points in a prospect theory framework. In order to test this explanation, this article applies the method of experimental economics to the issue of education choice and behaviour. One hundred and twenty-nine individuals participated in an experiment in which they had to perform a task over 15 stages grouped in three blocks or levels. In order to continue through the experiment, a minimum level of success was required at the end of each level. Rewards were dependent on the final level successfully reached. At the end of each level, participants could either choose to stop and take their reward or to pay a cost to continue further in order to possibly receive higher rewards. To test the impact of aspiration levels, outcomes were either presented as gains or losses relative to an initial sum. In accordance with the theoretical predictions, participants in the loss framing group choose to go further in the experiment. There was also a significant and interesting gender effect in the loss framing treatment, such that males performed better and reached higher levels.

The impact of nonlinear exposure risk relationships on seasonal time series data: modelling danish neonatal birth anthropometric data

Background Birth weight and length have seasonal fluctuations. Previous analyses of birth weight by latitude effects identified seemingly contradictory results, showing both 6 and 12 monthly periodicities in weight. The aims of this paper are twofold: (a) to explore seasonal patterns in a large, Danish Medical Birth Register, and (b) to explore models based on seasonal exposures and a non-linear exposure-risk relationship. Methods Birth weight and birth lengths on over 1.5 million Danish singleton, live births were examined for seasonality. We modelled seasonal patterns based on linear, U- and J-shaped exposure-risk relationships. We then added an extra layer of complexity by modelling weighted population-based exposure patterns. Results The Danish data showed clear seasonal fluctuations for both birth weight and birth length. A bimodal model best fits the data, however the amplitude of the 6 and 12 month peaks changed over time. In the modelling exercises, U- and J-shaped exposure-risk relationships generate time series with both 6 and 12 month periodicities. Changing the weightings of the population exposure risks result in unexpected properties. A J-shaped exposure-risk relationship with a diminishing population exposure over time fitted the observed seasonal pattern in the Danish birth weight data. Conclusion In keeping with many other studies, Danish birth anthropometric data show complex and shifting seasonal patterns. We speculate that annual periodicities with non-linear exposure-risk models may underlie these findings. Understanding the nature of seasonal fluctuations can help generate candidate exposures.

Margin-adaptive model selection in statistical learning

A classical condition for fast learning rates is the margin condition, first introduced by Mammen and Tsybakov. We tackle in this paper the problem of adaptivity to this condition in the context of model selection, in a general learning framework. Actually, we consider a weaker version of this condition that allows one to take into account that learning within a small model can be much easier than within a large one. Requiring this “strong margin adaptivity” makes the model selection problem more challenging. We first prove, in a general framework, that some penalization procedures (including local Rademacher complexities) exhibit this adaptivity when the models are nested. Contrary to previous results, this holds with penalties that only depend on the data. Our second main result is that strong margin adaptivity is not always possible when the models are not nested: for every model selection procedure (even a randomized one), there is a problem for which it does not demonstrate strong margin adaptivity.

Sensitivity of building zones to potential global warming

As global warming entails new conditions for the built environment, the thermal and energy performance of existing buildings, which are designed based on current weather data, may become unclear and remain a great concern. Through building computer simulation and qualitative analysis of the weighted factor for the outdoor temperature impact on building energy and thermal performance, this paper investigates the sensitivity of different office building zoning to the potential global warming. A standard office building type is examined for all eight capital cities in Australia. Results show that comparing the middle and top floors, except for cool climate (i.e. Hobart), the ground floor appears to be the most sensitive to the effect of global warming and has the highest tendency for a overheating problem. From the analysis of the responses of different zone orientations to the outdoor air temperature increase, it is also found that there are widely varied responses between zone orientations, with South zone (in the southern hemisphere) being the most sensitive. With an increased external air temperature, the variation between different floors or zone orientations will become more significant, up to 53 percent increase of overheating hours in Darwin and 47 percent increase of cooling load in Hobart.

Proactive detection of high collision concentration locations on highways

In previous research (Chung et al., 2009), the potential of the continuous risk profile (CRP) to proactively detect the systematic deterioration of freeway safety levels was presented. In this paper, this potential is investigated further, and an algorithm is proposed for proactively detecting sites where the collision rate is not sufficiently high to be classified as a high collision concentration location but where a systematic deterioration of safety level is observed. The approach proposed compares the weighted CRP across different years and uses the cumulative sum (CUSUM) algorithm to detect the sites where changes in collision rate are observed. The CRPs of the detected sites are then compared for reproducibility. When high reproducibility is observed, a growth factor is used for sequential hypothesis testing to determine if the collision profiles are increasing over time. Findings from applying the proposed method using empirical data are documented in the paper together with a detailed description of the method.

Having a yarn about smoking : using action research to develop a 'no smoking' policy within an Aboriginal health organisation

Objectives: This article reports on a culturally appropriate process of development of a smoke-free workplace policy within the peak Aboriginal Controlled Community Health Organisation in Victoria, Australia. Smoking is acknowledged as being responsible for at least 20% of all deaths in Aboriginal communities in Australia, and many Aboriginal health workers smoke. Methods: The smoke-free workplace policy was developed using the iterative, discursive and experience-based methodology of Participatory Action Research, combined with the culturally embedded concept of ‘having a yarn’. Results: Staff members initially identified smoking as a topic to be avoided within workplace discussions. This was due, in part, to grief (everyone had suffered a smoking related bereavement). Further, there was anxiety that discussing smoking would result in culturally difficult conflict. The use of yarning opened up a safe space for discussion and debate,enabling development of a policy that was accepted across the organisation. Conclusions: Within Aboriginal organisations, it is not sufficient to focus on the outcomes of policy development. Rather, due attention must be paid to the process employed in development of policy, particularly when that policy is directly related to an emotionally and communally weighted topic such as smoking.

Performance control of distributed generation using digital estimation of signal parameters

The Queensland University of Technology (QUT) allows the presentation of a thesis for the Degree of Doctor of Philosophy in the format of published or submitted papers, where such papers have been published, accepted or submitted during the period of candidature. This thesis is composed of seven published/submitted papers, of which one has been published, three accepted for publication and the other three are under review. This project is financially supported by an Australian Research Council (ARC) Discovery Grant with the aim of proposing strategies for the performance control of Distributed Generation (DG) system with digital estimation of power system signal parameters. Distributed Generation (DG) has been recently introduced as a new concept for the generation of power and the enhancement of conventionally produced electricity. Global warming issue calls for renewable energy resources in electricity production. Distributed generation based on solar energy (photovoltaic and solar thermal), wind, biomass, mini-hydro along with use of fuel cell and micro turbine will gain substantial momentum in the near future. Technically, DG can be a viable solution for the issue of the integration of renewable or non-conventional energy resources. Basically, DG sources can be connected to local power system through power electronic devices, i.e. inverters or ac-ac converters. The interconnection of DG systems to power system as a compensator or a power source with high quality performance is the main aim of this study. Source and load unbalance, load non-linearity, interharmonic distortion, supply voltage distortion, distortion at the point of common coupling in weak source cases, source current power factor, and synchronism of generated currents or voltages are the issues of concern. The interconnection of DG sources shall be carried out by using power electronics switching devices that inject high frequency components rather than the desired current. Also, noise and harmonic distortions can impact the performance of the control strategies. To be able to mitigate the negative effect of high frequency and harmonic as well as noise distortion to achieve satisfactory performance of DG systems, new methods of signal parameter estimation have been proposed in this thesis. These methods are based on processing the digital samples of power system signals. Thus, proposing advanced techniques for the digital estimation of signal parameters and methods for the generation of DG reference currents using the estimates provided is the targeted scope of this thesis. An introduction to this research – including a description of the research problem, the literature review and an account of the research progress linking the research papers – is presented in Chapter 1. One of the main parameters of a power system signal is its frequency. Phasor Measurement (PM) technique is one of the renowned and advanced techniques used for the estimation of power system frequency. Chapter 2 focuses on an in-depth analysis conducted on the PM technique to reveal its strengths and drawbacks. The analysis will be followed by a new technique proposed to enhance the speed of the PM technique while the input signal is free of even-order harmonics. The other techniques proposed in this thesis as the novel ones will be compared with the PM technique comprehensively studied in Chapter 2. An algorithm based on the concept of Kalman filtering is proposed in Chapter 3. The algorithm is intended to estimate signal parameters like amplitude, frequency and phase angle in the online mode. The Kalman filter is modified to operate on the output signal of a Finite Impulse Response (FIR) filter designed by a plain summation. The frequency estimation unit is independent from the Kalman filter and uses the samples refined by the FIR filter. The frequency estimated is given to the Kalman filter to be used in building the transition matrices. The initial settings for the modified Kalman filter are obtained through a trial and error exercise. Another algorithm again based on the concept of Kalman filtering is proposed in Chapter 4 for the estimation of signal parameters. The Kalman filter is also modified to operate on the output signal of the same FIR filter explained above. Nevertheless, the frequency estimation unit, unlike the one proposed in Chapter 3, is not segregated and it interacts with the Kalman filter. The frequency estimated is given to the Kalman filter and other parameters such as the amplitudes and phase angles estimated by the Kalman filter is taken to the frequency estimation unit. Chapter 5 proposes another algorithm based on the concept of Kalman filtering. This time, the state parameters are obtained through matrix arrangements where the noise level is reduced on the sample vector. The purified state vector is used to obtain a new measurement vector for a basic Kalman filter applied. The Kalman filter used has similar structure to a basic Kalman filter except the initial settings are computed through an extensive math-work with regards to the matrix arrangement utilized. Chapter 6 proposes another algorithm based on the concept of Kalman filtering similar to that of Chapter 3. However, this time the initial settings required for the better performance of the modified Kalman filter are calculated instead of being guessed by trial and error exercises. The simulations results for the parameters of signal estimated are enhanced due to the correct settings applied. Moreover, an enhanced Least Error Square (LES) technique is proposed to take on the estimation when a critical transient is detected in the input signal. In fact, some large, sudden changes in the parameters of the signal at these critical transients are not very well tracked by Kalman filtering. However, the proposed LES technique is found to be much faster in tracking these changes. Therefore, an appropriate combination of the LES and modified Kalman filtering is proposed in Chapter 6. Also, this time the ability of the proposed algorithm is verified on the real data obtained from a prototype test object. Chapter 7 proposes the other algorithm based on the concept of Kalman filtering similar to those of Chapter 3 and 6. However, this time an optimal digital filter is designed instead of the simple summation FIR filter. New initial settings for the modified Kalman filter are calculated based on the coefficients of the digital filter applied. Also, the ability of the proposed algorithm is verified on the real data obtained from a prototype test object. Chapter 8 uses the estimation algorithm proposed in Chapter 7 for the interconnection scheme of a DG to power network. Robust estimates of the signal amplitudes and phase angles obtained by the estimation approach are used in the reference generation of the compensation scheme. Several simulation tests provided in this chapter show that the proposed scheme can very well handle the source and load unbalance, load non-linearity, interharmonic distortion, supply voltage distortion, and synchronism of generated currents or voltages. The purposed compensation scheme also prevents distortion in voltage at the point of common coupling in weak source cases, balances the source currents, and makes the supply side power factor a desired value.

Social and emotional determinants of health

- describe what is meant by socioeconomic differences in health, and the social and emotional determinants of health - understand how health inequalities are affected by the social and economic circumstances that people experience throughout their lives - discuss how factors such as living and working conditions, income, place and education can impact on health - identify actions for public health policy-makers that have the potential to make a difference in improving health outcomes within populations - appreciate the concept of social cohesion and social capital, and their role as potential protective factors in health - understand conceptual models that can assist in analysing these issues.

Socio-economic differences in takeaway food consumption among adults

To examine socioeconomic differences in the frequency and types of takeaway foods consumed. Cross-sectional postal survey. Participants were asked about their usual consumption of overall takeaway food (< four times a month, or ≥ four times a month) and 22 specific takeaway food items (< once a month, or ≥ once a month): these latter foods were grouped into “healthy” and “less healthy” choices. Socioeconomic position was measured using education and equivalised household income and differences in takeaway food consumption were assessed by calculating prevalence ratios using log binomial regression. Adults aged 25–64 years from Brisbane, Australia were randomly selected from the electoral roll (N = 903, 63.7% response rate). Compared with their more educated counterparts, the least educated were more regular consumers of overall takeaway food, fruit/vegetable juice, and less regular consumers of sushi. For the “less healthy” items, the least educated more regularly consumed potato chips, savoury pies, fried chicken, and non-diet soft drinks; however, the least educated were less likely to consume curry. Household income was not associated with overall takeaway consumption. The lowest income group were more regular consumers of fruit/vegetable juice compared with the highest income group. Among the “less healthy” items, the lowest income group were more regular consumers of fried fish, ice-cream, and milk shakes, while curry was consumed less regularly. The frequency and types of takeaway foods consumed by socioeconomically disadvantaged groups may contribute to inequalities in overweight/obesity and chronic disease.

Multifractal characterisation and analysis of complex networks

Complex networks have been studied extensively due to their relevance to many real-world systems such as the world-wide web, the internet, biological and social systems. During the past two decades, studies of such networks in different fields have produced many significant results concerning their structures, topological properties, and dynamics. Three well-known properties of complex networks are scale-free degree distribution, small-world effect and self-similarity. The search for additional meaningful properties and the relationships among these properties is an active area of current research. This thesis investigates a newer aspect of complex networks, namely their multifractality, which is an extension of the concept of selfsimilarity. The first part of the thesis aims to confirm that the study of properties of complex networks can be expanded to a wider field including more complex weighted networks. Those real networks that have been shown to possess the self-similarity property in the existing literature are all unweighted networks. We use the proteinprotein interaction (PPI) networks as a key example to show that their weighted networks inherit the self-similarity from the original unweighted networks. Firstly, we confirm that the random sequential box-covering algorithm is an effective tool to compute the fractal dimension of complex networks. This is demonstrated on the Homo sapiens and E. coli PPI networks as well as their skeletons. Our results verify that the fractal dimension of the skeleton is smaller than that of the original network due to the shortest distance between nodes is larger in the skeleton, hence for a fixed box-size more boxes will be needed to cover the skeleton. Then we adopt the iterative scoring method to generate weighted PPI networks of five species, namely Homo sapiens, E. coli, yeast, C. elegans and Arabidopsis Thaliana. By using the random sequential box-covering algorithm, we calculate the fractal dimensions for both the original unweighted PPI networks and the generated weighted networks. The results show that self-similarity is still present in generated weighted PPI networks. This implication will be useful for our treatment of the networks in the third part of the thesis. The second part of the thesis aims to explore the multifractal behavior of different complex networks. Fractals such as the Cantor set, the Koch curve and the Sierspinski gasket are homogeneous since these fractals consist of a geometrical figure which repeats on an ever-reduced scale. Fractal analysis is a useful method for their study. However, real-world fractals are not homogeneous; there is rarely an identical motif repeated on all scales. Their singularity may vary on different subsets; implying that these objects are multifractal. Multifractal analysis is a useful way to systematically characterize the spatial heterogeneity of both theoretical and experimental fractal patterns. However, the tools for multifractal analysis of objects in Euclidean space are not suitable for complex networks. In this thesis, we propose a new box covering algorithm for multifractal analysis of complex networks. This algorithm is demonstrated in the computation of the generalized fractal dimensions of some theoretical networks, namely scale-free networks, small-world networks, random networks, and a kind of real networks, namely PPI networks of different species. Our main finding is the existence of multifractality in scale-free networks and PPI networks, while the multifractal behaviour is not confirmed for small-world networks and random networks. As another application, we generate gene interactions networks for patients and healthy people using the correlation coefficients between microarrays of different genes. Our results confirm the existence of multifractality in gene interactions networks. This multifractal analysis then provides a potentially useful tool for gene clustering and identification. The third part of the thesis aims to investigate the topological properties of networks constructed from time series. Characterizing complicated dynamics from time series is a fundamental problem of continuing interest in a wide variety of fields. Recent works indicate that complex network theory can be a powerful tool to analyse time series. Many existing methods for transforming time series into complex networks share a common feature: they define the connectivity of a complex network by the mutual proximity of different parts (e.g., individual states, state vectors, or cycles) of a single trajectory. In this thesis, we propose a new method to construct networks of time series: we define nodes by vectors of a certain length in the time series, and weight of edges between any two nodes by the Euclidean distance between the corresponding two vectors. We apply this method to build networks for fractional Brownian motions, whose long-range dependence is characterised by their Hurst exponent. We verify the validity of this method by showing that time series with stronger correlation, hence larger Hurst exponent, tend to have smaller fractal dimension, hence smoother sample paths. We then construct networks via the technique of horizontal visibility graph (HVG), which has been widely used recently. We confirm a known linear relationship between the Hurst exponent of fractional Brownian motion and the fractal dimension of the corresponding HVG network. In the first application, we apply our newly developed box-covering algorithm to calculate the generalized fractal dimensions of the HVG networks of fractional Brownian motions as well as those for binomial cascades and five bacterial genomes. The results confirm the monoscaling of fractional Brownian motion and the multifractality of the rest. As an additional application, we discuss the resilience of networks constructed from time series via two different approaches: visibility graph and horizontal visibility graph. Our finding is that the degree distribution of VG networks of fractional Brownian motions is scale-free (i.e., having a power law) meaning that one needs to destroy a large percentage of nodes before the network collapses into isolated parts; while for HVG networks of fractional Brownian motions, the degree distribution has exponential tails, implying that HVG networks would not survive the same kind of attack.

Managing innovative change within organisations and project team environments

In an attempt to enhance the efficiency, productivity and competitiveness of today’s Architectural, Engineering, and Contractor (AEC) industry, this paper summarises the current status of an ongoing PhD research investigation in developing a sustainable AEC industry specific best-practice ‘Innovation-driven Change Framework’—more specifically a summation of the ‘fourth interrelated dynamic’ (culture). Leveraging off the outcomes of a two year industry and government supported Cooperative Research Centre for Construction Innovation (CRCCI) research project, as well as referring to recent internationally renowned case studies and related literature investigations, this research investigation includes further identifying, processing, analysing and categorizing various culture change methods, models, frameworks and processes utilized within the AEC and other industry sectors, and incorporating these findings in developing an AEC industry-specific ‘Innovation-driven Change Framework’

Developing a fuzzy multi-criteria decision-making model for selecting design-build operational variations

Many academic researchers have conducted studies on the selection of design-build (DB) delivery method; however, there are few studies on the selection of DB operational variations, which poses challenges to many clients. The selection of DB operational variation is a multi-criteria decision making process that requires clients to objectively evaluate the performance of each DB operational variation with reference to the selection criteria. This evaluation process is often characterized by subjectivity and uncertainty. In order to resolve this deficiency, the current investigation aimed to establish a fuzzy multicriteria decision-making (FMCDM) model for selecting the most suitable DB operational variation. A three-round Delphi questionnaire survey was conducted to identify the selection criteria and their relative importance. A fuzzy set theory approach, namely the modified horizontal approach with the bisector error method, was applied to establish the fuzzy membership functions, which enables clients to perform quantitative calculations on the performance of each DB operational variation. The FMCDM was developed using the weighted mean method to aggregate the overall performance of DB operational variations with regard to the selection criteria. The proposed FMCDM model enables clients to perform quantitative calculations in a fuzzy decision-making environment and provides a useful tool to cope with different project attributes.

Effectiveness of powered hospital bed movers for reducing physiological strain and back muscle activation

Battery powered bed movers are becoming increasingly common within the hospital setting. The use of powered bed movers is believed to result in reduced physical efforts required by health care workers, which may be associated with a decreased risk of occupation related injuries. However, little work has been conducted assessing how powered bed movers impact on levels of physiological strain and muscle activation for the user. The muscular efforts associated with moving hospital beds using three different methods; manual pushing, StaminaLift Bed Mover (SBM) and Gzunda Bed Mover (GBM)were measured on six male subjects. Fourteen muscles were assessed moving a weighted hospital bed along a standardized route in an Australian hospital environment. Trunk inclination and upper spine acceleration were also quantified. Powered bed movers exhibited significantly lower muscle activation levels than manual pushing for the majority of muscles. When using the SBM, users adopted a more upright posture which was maintained while performing different tasks (e.g. turning a corner, entering a lift), while trunk inclination varied considerably for manual pushing and the GBM. The reduction in lower back muscular activation levels and the load reducing effect of a more upright posture may result in lower incidence of lower back injury.

Organizational rhetoric in the prospectuses of elite private schools: unpacking strategies of persuasion

The way in which private schools use rhetoric in their communications offers important insights into how these organizational sites persuade audiences and leverage marketplace advantage in the context of contemporary educational platforms. Through systemic analysis of rhetorical strategies employed in 65 ‘elite’ school prospectuses in Australia, this paper contributes to understandings of the ways schools’ communications draw on broader cultural politics in order to shape meanings and interactions among organizational actors. We identify six strategies consistently used by schools to this end: identification, juxtapositioning, bolstering or self-promotion, partial reporting, self-expansion, and reframing or reversal. We argue that, in the context of marketization and privatization discourses in twenty-first-century western education, these strategies attempt to subvert potentially threatening discourses, in the process actively reproducing broader economic and social privilege and inequalities.