A comparison of factors influencing perceived risk by French and Australian cyclists and drivers

Differences in the levels of risk perceived by cyclists and car drivers may contribute to the dangers in their interactions. Levels of perceived risk have been shown to vary according to personal and environmental factors and between countries. Cycling rates in France are higher than in Australia, particularly among women. This study investigated whether cultural differences between France and Australia are reflected in perceived risks for experienced adult cyclists and drivers in the two countries. In online surveys, regular cyclists (France 336, Australia 444) and drivers (France 92, Australia 151) were asked to rate the level of risk in six situations: failure to yield; going through a red light; not signalling when turning; swerving; tail-gating; and not checking traffic. The effects of type of interacting vehicle and participant type on perceived risk were similar in France and Australia. However, the influence of responsibility for the risky behaviour differed according to participant type, type of situation and nationality. When the bicycle rider committed the road rule violation, Australian cyclists and drivers gave higher risk ratings than French cyclists and drivers. In both countries, cyclists rated themselves significantly higher than drivers on the perceived control and overconfidence subscales of the perceived skill measure. The French cyclists rated themselves higher than Australian cyclists on these scales, which could be responsible for overall lower perceived risk levels when interacting with a bike. Australian cyclists rated themselves significantly lower than drivers on the incompetence subscale but French cyclists rated themselves higher than drivers. In both countries incompetence scores were positively related to levels of perceived risk. Weekly time was associated with perceived risk in Australia but not in France. Frequency of traffic violations was not associated with perceived risk in either country. In conclusion, levels of perceived risk differed between drivers and cyclists in both countries and were influenced by type of interacting vehicle, experience and perceived skill. However, some differences between the results from the two countries merit further investigation to shed light on potential improvements in safety and cycling participation.

Connecting theory, practice and place in today’s landscape : an education initiative

Since the establishment of Australia’s earliest formal studies in landscape architecture, landscape planning has been a traditional focus within post-graduate studies at QUT. Study in this area has evolved from an earlier emphasis on applied physical geography through to traditional techniques and processes in visual assessment and management. The emphasis on these techniques has shifted again to a more complex exploration of natural, economic, social and cultural landscapes. Recently, the School has explored more innovative and complex dimensions of human and natural landscapes. This has involved a focus on particular regions under pressure from local social and economic change. These have included the under-threat ‘picturesque’ landscapes of the Blackall Range and the Tweed Valley. Attempts to bridge the institution and the landscape have unearthed, through a studio focus, strong connections with notions of sustainable villages, roadside interpretation, way finding, local economic initiatives, special area creation, cultural heritage brokering and ecological enhancements. These initiatives have spanned both local practice interests and academic pursuits. Central to this exploration is the concept of problem solving through the investigation of the concept of ‘multiple scales’. An open, yet intensive program is being developed with a team of ‘futurist’ practitioners offering a range of experiences and perspectives to students. The program is being increasingly linked to design studios so that landscape planning and landscape design form a fabric of inquiry that works towards reclaiming complex landscapes.

Bayesian models for spatio-temporal assessment of disease

This thesis has contributed to the advancement of knowledge in disease modelling by addressing interesting and crucial issues relevant to modelling health data over space and time. The research has led to the increased understanding of spatial scales, temporal scales, and spatial smoothing for modelling diseases, in terms of their methodology and applications. This research is of particular significance to researchers seeking to employ statistical modelling techniques over space and time in various disciplines. A broad class of statistical models are employed to assess what impact of spatial and temporal scales have on simulated and real data.

An integrated modeling and risk analysis tool for mine water interactions

Poor mine water management can lead to corporate, environmental and social risks. These risks become more pronounced as mining operations move into areas of water scarcity and/or increase climatic variability while also managing increased demand, lower ore grades and increased strip ratios. Therefore, it is vital that mine sites better understand these risks in order to implement management practices to address them. Systems models provide an effective approach to understand complex networks, particularly across multiple scales. Previous work has represented mine water interactions using systems model on a mine site scale. Here, we expand on that work by present an integrated tool that uses a systems modeling approach to represent mine water interactions on a site and regional scale and then analyses the risks associated with events stemming from those interactions. A case study is presented to represent three indicative corporate, environmental and social risks associated with a mine site that exists in a water scarce region. The tool is generic and flexible, and can be used in many scenarios to provide significant potential utility to the mining industry.

Bridging experiments, models and simulations : an integrative approach to validation in computational cardiac electrophysiology

Computational models in physiology often integrate functional and structural information from a large range of spatio-temporal scales from the ionic to the whole organ level. Their sophistication raises both expectations and scepticism concerning how computational methods can improve our understanding of living organisms and also how they can reduce, replace and refine animal experiments. A fundamental requirement to fulfil these expectations and achieve the full potential of computational physiology is a clear understanding of what models represent and how they can be validated. The present study aims at informing strategies for validation by elucidating the complex interrelations between experiments, models and simulations in cardiac electrophysiology. We describe the processes, data and knowledge involved in the construction of whole ventricular multiscale models of cardiac electrophysiology. Our analysis reveals that models, simulations, and experiments are intertwined, in an assemblage that is a system itself, namely the model-simulation-experiment (MSE) system. Validation must therefore take into account the complex interplay between models, simulations and experiments. Key points for developing strategies for validation are: 1) understanding sources of bio-variability is crucial to the comparison between simulation and experimental results; 2) robustness of techniques and tools is a pre-requisite to conducting physiological investigations using the MSE system; 3) definition and adoption of standards facilitates interoperability of experiments, models and simulations; 4) physiological validation must be understood as an iterative process that defines the specific aspects of electrophysiology the MSE system targets, and is driven by advancements in experimental and computational methods and the combination of both.

A multicenter study on chronic cough in children : burden and etiologies based on a standardized management pathway

Background While the burden of chronic cough in children has been documented, etiologic factors across multiple settings and age have not been described. In children with chronic cough, we aimed (1) to evaluate the burden and etiologies using a standard management pathway in various settings, and (2) to determine the influence of age and setting on disease burden and etiologies and etiology on disease burden. We hypothesized that the etiology, but not the burden, of chronic cough in children is dependent on the clinical setting and age. Methods From five major hospitals and three rural-remote clinics, 346 children (mean age 4.5 years) newly referred with chronic cough (> 4 weeks) were prospectively managed in accordance with an evidence-based cough algorithm. We used a priori definitions, timeframes, and validated outcome measures (parent-proxy cough-specific quality of life [PC-QOL], a generic QOL [pediatric quality of life (PedsQL)], and cough diary). Results The burden of chronic cough (PC-QOL, cough duration) significantly differed between settings (P = .014, 0.021, respectively), but was not influenced by age or etiology. PC-QOL and PedsQL did not correlate with age. The frequency of etiologies was significantly different in dissimilar settings (P = .0001); 17.6% of children had a serious underlying diagnosis (bronchiectasis, aspiration, cystic fibrosis). Except for protracted bacterial bronchitis, the frequency of other common diagnoses (asthma, bronchiectasis, resolved without specific-diagnosis) was similar across age categories. Conclusions The high burden of cough is independent of children’s age and etiology but dependent on clinical setting. Irrespective of setting and age, children with chronic cough should be carefully evaluated and child-specific evidence-based algorithms used.

Clinical utility of exhaled nitric oxide

Lower airway inflammation is generally classified as eosinophilic or neutrophilic. In conditions where eosinophilic inflammation predominates such as asthma in children, corticosteroids are usually beneficial. Traditionally, lower airway eosinophilia is measured using cellular count (through bronchoalveolar lavage or induced sputum). Both methods have limited applicability in children. When instruments to measure fractional exhaled nitric oxide (FeNO) became available, it presented an attractive option as it provided a non-invasive method of measuring eosinophilic inflammation suitable for children and adult. Not surprisingly, proposals have been made that FeNO measurement can be clinically used in many scenarios including monitoring the response to anti-inflammatory medications, to verify the adherence to treatment, and to predict upcoming asthma exacerbations. This thesis addresses the utility of FeNO levels in various scenarios, specifically in relation to asthma control and cough, a contentious aspect of the diagnosis of asthma. The thesis consists of a series of systematic reviews (related to the main question) and original studies in children. The over-arching aim of the thesis is to determine if FeNO is a clinically useful tool in the management of asthma and common asthma symptoms. The specific aims of the thesis were, to: 1. Determine if children with asthma have more severe acute respiratory symptoms at presentation with an asthma exacerbation and at days 7, 10 and 14 using validated scales. We also examined if children with asthma were more likely to have a persistent cough on day 14 than children with protracted bronchitis and/or controls. 2. Evaluate the efficacy of tailoring asthma interventions based on sputum analysis in comparison to clinical symptoms (with or without spirometry/peak flow) for asthma related outcomes in children and adults. 3. Evaluate the efficacy of tailoring asthma interventions based on exhaled nitric oxide in comparison to clinical symptoms (with or without spirometry/peak flow) for asthma related outcomes in children and adults. 4. Determine if adjustment of asthma medications based on FeNO levels (compared to management based on clinical symptoms) reduces severe exacerbations in children with asthma. 5. Examine the relationship between FeNO and exercise induced broncho-constriction and cough in children The aims above are addressed in respective chapters and all but one has been published/submitted. A synopsis of the findings are: In study-1 (Aim 1), we found that children with protracted bronchitis had the most severe acute respiratory infection symptoms and higher percentage of respiratory morbidity at day 14 in comparison to children with asthma and healthy controls. The systematic review of study-2 (Aim 2) included 246 randomised adult participants (no children) with 221 completing the trials. In the meta-analysis, a significant reduction in number of participants who had one or more asthma exacerbations occurred when treatment was based on sputum eosinophils in comparison to clinical symptoms. In the systematic review of study-3 (Aim 3), we found no significant difference between the intervention group (treatment adjusted based on FeNO) and control group (treatment adjusted based on clinical symptoms) for the primary outcome of asthma exacerbations or for the other outcomes (clinical symptoms, FeNO level and spirometry). In post-hoc analysis, a significant reduction in mean final daily dose ICS per adult was found in the group where treatment was based on FeNO in comparison to clinical symptoms. In contrast, in the paediatric studies, there was a significant increase in ICS dose in the FeNO strategy arm. Thus, controversy remains of the benefit or otherwise of utilising exhaled nitric oxide (FeNO) in routine clinical practice. FeNO levels are dependent on atopy and none of the 7 published trials have considered atopic status in FeNO levels when medications were adjusted. In study-4 (Aim 4), 64 children with asthma were recruited. Their asthma medications were adjusted according to either FeNO levels or usual clinical care utilising a management hierarchy taking into account atopy. It was concluded that tailoring of asthma medications in accordance to FeNO levels (compared to usual management), taking into account atopy status, reduced the number of children with severe exacerbations. However, a FeNO-based strategy resulted in higher daily ICS doses and had no benefit on asthma control. In study-5 (Aim 5), 33 children with cough and 17 controls were recruited. They were randomised to undertake an exercise challenge on day 1, or dry powder mannitol challenge on day 1 (with alternative challenge being done on day 2). In addition, a 24 hour cough meter, skin prick test, capsaicin cough sensitivity test and cough diary were undertaken. The change in cough frequency post exercise was significantly increased in the children with cough. FeNO decreases post exercise regardless of whether EIB is present or not. Limitations in the studies were addressed in the respective chapters. In summary, the studies from this thesis have provided new information on: • The severity of respiratory symptoms was increased in the early phase of the asthma exacerbation but not in the later recovery phase when compared with controls. • The utility of FeNO in the management of children with asthma. • The relationship of FeNO, cough and EIB in children. • Systematic reviews on the efficacy of tailoring asthma interventions based on eosinophilic inflammatory markers (sputum analysis and FeNO) in comparison to clinical symptoms.

Document clustering algorithms, representations and evaluation for information retrieval

This thesis presents new methods for classification and thematic grouping of billions of web pages, at scales previously not achievable. This process is also known as document clustering, where similar documents are automatically associated with clusters that represent various distinct topic. These automatically discovered topics are in turn used to improve search engine performance by only searching the topics that are deemed relevant to particular user queries.

Assessing uncertainty in pollutant wash-off modelling via model validation

Stormwater pollution is linked to stream ecosystem degradation. In predicting stormwater pollution, various types of modelling techniques are adopted. The accuracy of predictions provided by these models depends on the data quality, appropriate estimation of model parameters, and the validation undertaken. It is well understood that available water quality datasets in urban areas span only relatively short time scales unlike water quantity data, which limits the applicability of the developed models in engineering and ecological assessment of urban waterways. This paper presents the application of leave-one-out (LOO) and Monte Carlo cross validation (MCCV) procedures in a Monte Carlo framework for the validation and estimation of uncertainty associated with pollutant wash-off when models are developed using a limited dataset. It was found that the application of MCCV is likely to result in a more realistic measure of model coefficients than LOO. Most importantly, MCCV and LOO were found to be effective in model validation when dealing with a small sample size which hinders detailed model validation and can undermine the effectiveness of stormwater quality management strategies.

Physical activity, walking and quality of life in women with depressive symptoms

Background Physical activity (PA) has a positive association with health-related quality of life (HRQL) in the general population. The association between PA and HRQL in those with poor mental health is less clear. Purpose To examine the concurrent and prospective dose-response relationships between total physical activity (TPA) and walking only with HRQL in women aged 50-55 with depressive symptoms in 2001. Methods Participants were 1904 women born in 1946-1951 who completed mailed surveys for the Australian Longitudinal Study on Women's Health in 2001, 2004, 2007 and 2010 and who, in 2001, reported depressive symptoms. At each time point, they reported their weekly minutes of walking, moderate PA, and vigorous PA. A summary TPA score was created that accounted for differences in energy expenditure among the three PA types. Mixed models were used to examine associations between TPA and HRQL (SF-36 component and subscale scores) and between walking and HRQL, for women who reported walking as their only PA. Analyses were conducted in 2013-2014. Results Concurrently, higher levels of TPA and walking were associated with better HRQL (p<0.05). The strongest associations were found for physical functioning, vitality, and social functioning subscales. In prospective models, associations were attenuated, yet compared with women doing no TPA or walking, women doing “sufficient” TPA or walking had significantly better HRQL over time for most SF-36 scales. Conclusions This study extends previous work by demonstrating trends between both TPA and walking and HRQL in women reporting depressive symptoms.

Real or imagined? A study exploring the existence of common method variance effects in road safety research

Common method variance (CMV) has received little attention within the field of road safety research despite a heavy reliance on self-report data. Two surveys were completed by 214 motorists over a two-month period, allowing associations between social desirability and key road safety variables and relationships between scales across the two survey waves to be examined. Social desirability was found to have a strong negative correlation with the Driver Behaviour Questionnaire (DBQ) sub-scales as well as age, but not with crashes and offences. Drivers who scored higher on the social desirability scale were also less likely to report aberrant driving behaviours as measured by the DBQ. Controlling for social desirability did not substantially alter the predictive relationship between the DBQ and the crash and offences variables. The strength of the correlations within and between the two waves were also compared with the results strongly suggesting that effects associated with CMV were present. Identification of CMV would be enhanced by the replication of this study with a larger sample size and comparing self-report data with official sources.

Modelling the water, energy and economic nexus

The mining industry faces three long term strategic risks in relation to its water and energy use: 1) securing enough water and energy to meet increased production; 2) reducing water use, energy consumption and emissions due to social, environmental and economic pressures; and 3) understanding the links between water and energy, so that an improvement in one area does not create an adverse effect in another. This project helps the industry analyse these risks by creating a hierarchical systems model (HSM) that represents the water and energy interactions on a sub-site, site and regional scales; which is coupled with a flexible risk framework. The HSM consists of: components that represent sources of water and energy; activities that use water and energy and off-site destinations of water and produced emissions. It can also represent more complex components on a site, with inbuilt examples including tailings dams and water treatment plants. The HSM also allows multiple sites and other infrastructure to be connected together to explore regional water and energy interactions. By representing water and energy as a single interconnected system the HSM can explore tradeoffs and synergies. For example, on a synthetic case study, which represents a typical site, simulations suggested that while a synergy in terms of water use and energy use could be made when chemical additives were used to enhance dust suppression, there were trade-offs when either thickened tailings or dry processing were used. On a regional scale, the HSM was used to simulate various scenarios, including: mines only withdrawing water when needed; achieving economics-of-scale through use of a single centralised treatment plant rather than smaller decentralised treatment plants; and capturing of fugitive emissions for energy generation. The HSM also includes an integrated risk framework for interpreting model output, so that onsite and off-site impacts of various water and energy management strategies can be compared in a managerial context. The case studies in this report explored company, social and environmental risks for scenarios of regional water scarcity, unregulated saline discharge, and the use of plantation forestry to offset carbon emissions. The HSM was able to represent the non-linear causal relationship at the regional scale, such as the forestry scheme offsetting a small percentage of carbon emissions but causing severe regional water shortages. The HSM software developed in this project will be released as an open source tool to allow industry personnel to easily and inexpensively quantify and explore the links between water use, energy use, and carbon emissions. The tool can be easily adapted to represent specific sites or regions. Case studies conducted in this project highlighted the potential complexity of these links between water, energy, and carbon emissions, as well as the significance of the cumulative effects of these links over time. A deeper understanding of these links is vital for the mining industry in order to progress to more sustainable operations, and the HSM provides an accessible, robust framework for investigating these links.

Psycho-educational assessment of specific learning disabilities: Views and practices of Australian psychologists and guidance counsellors

This paper reports an investigation of the views and practices of 203 Australian psychologists and guidance counsellors with respect to psycho-educational assessment of students with Specific Learning Disabilities (SLDs). Results from an online survey indicated that practitioners draw upon a wide-range of theoretical perspectives when conceptualising and identifying SLDs, including both response to intervention and IQ – achievement discrepancy models. Intelligence tests (particularly the Wechsler scales) are commonly employed, with the main stated reasons for their use being ‘traditional’ perspectives (including IQ-achievement discrepancy-based definitions of SLDs), to exclude a diagnosis of intellectual disability, and to guide further assessment and intervention. In contrast participants reported using measures of academic achievement and tests of specific cognitive deficits known to predict SLDs (e.g., phonological awareness) relatively infrequently.

A national satellite-based land-use regression model for air pollution exposure assessment in Australia

Land-use regression (LUR) is a technique that can improve the accuracy of air pollution exposure assessment in epidemiological studies. Most LUR models are developed for single cities, which places limitations on their applicability to other locations. We sought to develop a model to predict nitrogen dioxide (NO2) concentrations with national coverage of Australia by using satellite observations of tropospheric NO2 columns combined with other predictor variables. We used a generalised estimating equation (GEE) model to predict annual and monthly average ambient NO2 concentrations measured by a national monitoring network from 2006 through 2011. The best annual model explained 81% of spatial variation in NO2 (absolute RMS error=1.4 ppb), while the best monthly model explained 76% (absolute RMS error=1.9 ppb). We applied our models to predict NO2 concentrations at the ~350,000 census mesh blocks across the country (a mesh block is the smallest spatial unit in the Australian census). National population-weighted average concentrations ranged from 7.3 ppb (2006) to 6.3 ppb (2011). We found that a simple approach using tropospheric NO2 column data yielded models with slightly better predictive ability than those produced using a more involved approach that required simulation of surface-to-column ratios. The models were capable of capturing within-urban variability in NO2, and offer the ability to estimate ambient NO2 concentrations at monthly and annual time scales across Australia from 2006–2011. We are making our model predictions freely available for research.

Multiscale features and information extraction of online strain for long-span bridges

The strain data acquired from structural health monitoring (SHM) systems play an important role in the state monitoring and damage identification of bridges. Due to the environmental complexity of civil structures, a better understanding of the actual strain data will help filling the gap between theoretical/laboratorial results and practical application. In the study, the multi-scale features of strain response are first revealed after abundant investigations on the actual data from two typical long-span bridges. Results show that, strain types at the three typical temporal scales of 10^5, 10^2 and 10^0 sec are caused by temperature change, trains and heavy trucks, and have their respective cut-off frequency in the order of 10^-2, 10^-1 and 10^0 Hz. Multi-resolution analysis and wavelet shrinkage are applied for separating and extracting these strain types. During the above process, two methods for determining thresholds are introduced. The excellent ability of wavelet transform on simultaneously time-frequency analysis leads to an effective information extraction. After extraction, the strain data will be compressed at an attractive ratio. This research may contribute to a further understanding of actual strain data of long-span bridges; also, the proposed extracting methodology is applicable on actual SHM systems.