Bayesian algorithms with applications

Advances in algorithms for approximate sampling from a multivariable target function have led to solutions to challenging statistical inference problems that would otherwise not be considered by the applied scientist. Such sampling algorithms are particularly relevant to Bayesian statistics, since the target function is the posterior distribution of the unobservables given the observables. In this thesis we develop, adapt and apply Bayesian algorithms, whilst addressing substantive applied problems in biology and medicine as well as other applications. For an increasing number of high-impact research problems, the primary models of interest are often sufficiently complex that the likelihood function is computationally intractable. Rather than discard these models in favour of inferior alternatives, a class of Bayesian "likelihoodfree" techniques (often termed approximate Bayesian computation (ABC)) has emerged in the last few years, which avoids direct likelihood computation through repeated sampling of data from the model and comparing observed and simulated summary statistics. In Part I of this thesis we utilise sequential Monte Carlo (SMC) methodology to develop new algorithms for ABC that are more efficient in terms of the number of model simulations required and are almost black-box since very little algorithmic tuning is required. In addition, we address the issue of deriving appropriate summary statistics to use within ABC via a goodness-of-fit statistic and indirect inference. Another important problem in statistics is the design of experiments. That is, how one should select the values of the controllable variables in order to achieve some design goal. The presences of parameter and/or model uncertainty are computational obstacles when designing experiments but can lead to inefficient designs if not accounted for correctly. The Bayesian framework accommodates such uncertainties in a coherent way. If the amount of uncertainty is substantial, it can be of interest to perform adaptive designs in order to accrue information to make better decisions about future design points. This is of particular interest if the data can be collected sequentially. In a sense, the current posterior distribution becomes the new prior distribution for the next design decision. Part II of this thesis creates new algorithms for Bayesian sequential design to accommodate parameter and model uncertainty using SMC. The algorithms are substantially faster than previous approaches allowing the simulation properties of various design utilities to be investigated in a more timely manner. Furthermore the approach offers convenient estimation of Bayesian utilities and other quantities that are particularly relevant in the presence of model uncertainty. Finally, Part III of this thesis tackles a substantive medical problem. A neurological disorder known as motor neuron disease (MND) progressively causes motor neurons to no longer have the ability to innervate the muscle fibres, causing the muscles to eventually waste away. When this occurs the motor unit effectively ‘dies’. There is no cure for MND, and fatality often results from a lack of muscle strength to breathe. The prognosis for many forms of MND (particularly amyotrophic lateral sclerosis (ALS)) is particularly poor, with patients usually only surviving a small number of years after the initial onset of disease. Measuring the progress of diseases of the motor units, such as ALS, is a challenge for clinical neurologists. Motor unit number estimation (MUNE) is an attempt to directly assess underlying motor unit loss rather than indirect techniques such as muscle strength assessment, which generally is unable to detect progressions due to the body’s natural attempts at compensation. Part III of this thesis builds upon a previous Bayesian technique, which develops a sophisticated statistical model that takes into account physiological information about motor unit activation and various sources of uncertainties. More specifically, we develop a more reliable MUNE method by applying marginalisation over latent variables in order to improve the performance of a previously developed reversible jump Markov chain Monte Carlo sampler. We make other subtle changes to the model and algorithm to improve the robustness of the approach.

Performance in the spotlight : exploring psychology in the performing arts

Sport and exercise psychologists are often sought after to apply their knowledge, skills and experience from a sporting context into other performance-related industries and endeavours. Over the past two decades, this has noticeably expanded out from a natural progression into the performing arts with other ‘typical’ performers (e.g., dancers, actors, musicians, singers) through to people who work in high pressure environments that consist of clear performance outputs and requirements that are usually linked to high impact consequences for non-achievement (e.g., lawyers, surgeons, executives, military personnel, safety professionals). Whilst these areas of application continue to increase in popularity and performance psychology is more readily recognised as an important factor in people performance across industries, the use of psychology within the performing arts continues to deepen and solidify its value as an essential and critical factor for success. This article focuses on the contribution of psychology to the performing arts that I have observed over more than 20 years – obtained through a variety of roles primarily within the dance sector including as performer, educator, health professional, researcher, commentator and senior leader.

Service condition of railroad corridors around the insulated rail joints

Railroad corridors contain large number of Insulated Rail Joints (IRJs) that act as safety critical elements in the circuitries of the signaling and broken rail identification systems. IRJs are regarded as sources of excitation for the passage of loaded wheels leading to high impact forces; these forces in turn cause dips, cross levels and twists to the railroad geometry in close proximity to the sections containing the IRJs in addition to the local damages to the railhead of the IRJs. Therefore, a systematic monitoring of the IRJs in railroad is prudent to mitigate potential risk of their sudden failure (e.g., broken tie plates) under the traffic. This paper presents a simple method of periodic recording of images using time-lapse photography and total station surveying measurements to understand the ongoing deterioration of the IRJs and their surroundings. Over a 500 day period, data were collected to examine the trends in narrowing of the joint gap due to plastic deformation the railhead edges and the dips, cross levels and twists caused to the railroad geometry due to the settlement of ties (sleepers) around the IRJs. The results reflect that the average progressive settlement beneath the IRJs is larger than that under the continuously welded rail, which leads to excessive deviation of railroad profile, cross levels and twists.

Embedding environmental sustainability in the undergraduate chemistry curriculum : a case study

In spite of increasing attention devoted to the importance of embedding sustainability in university curricula, few Australian universities include specific green chemistry units, and there is no mention of green or sustainable chemistry concepts in the majority of units. In this paper, an argument is posited that all universities should embed sustainable chemistry within all Chemistry courses because it is the morally correct stance to minimise the harm of climate change. Attitudes of chemistry lecturers towards integrating sustainability into their teaching have been probed and it was found, using an established model, that personal environmental perspectives are critical to their attitude. Importantly, academic staff whose research has an environmental component were more likely to incorporate sustainability into their teaching while others struggled to find ways to do so even when they believed it to be important. This paper will recommend that resources are required to assist academic staff without a green chemistry research program to incorporate sustainability into their teaching and several suggestions are provided.

Investigative journalism in a socially networked world

This article explores how investigative journalists can join the network society by moving online, collaborating with other reporters and media outlets across regions and across national borders, yet publishing in newspapers which arguably remain the central stage of the public sphere (Carson, 2013). A better understanding of the potential of social media and web-based communications for undertaking journalistic investigations can lead to the adoption of a global perspective, enriching local, regional and national stories (Berglez, 2013). The research and collaboration for a transnational story published simultaneously in The Australian and collaboration in London in 2013 may provide insights into the potential for the use of social media platforms and web-based communications for finding stories, collaborating and following stories into the social media to find leads to follow-up stories. This article questions whether the synergies between mainstream media and social media platforms may yield potentially high impact stories for major masthead newspapers and thus contribute to their sustainability. Connectivity with news sources has always been an important resource for journalists. Online networks may have the potential to expand the range of voices that can be heard and the issues that can be covered.

Vertical dynamic interaction of trains and rail steel bridges

Rail steel bridges are vulnerable to high impact forces due to the passage of trains; unfortunately the determination of these transient impact forces is not straightforward as these are affected by a large number of parameters, including the wagon design, the wheel-rail contact and the design parameters of the bridge deck and track, as well as the operational parameters – wheel load and speed. To determine these impact forces, a detailed rail train-track/bridge dynamic interaction model has been developed, which includes a comprehensive train model using multi-body dynamics approach and a flexible track/bridge model using Euler– Bernoulli beam theory. Single and multi-span bridges have been modelled to examine their dynamic characteristics. From the single span bridge, the train critical speed is determined; the minimum distance of two peak loadings is found to affect the train critical speed. The impact factor and the dynamic characteristics are discussed.

Improving construction management : an investigation into the influences of effective stakeholder involvement on project quality outcomes

This research has developed a framework to improve the effectiveness and efficiency of stakeholder involvement during the early planning stages of residential construction projects, in order to improve many of the quality issues that occur during the construction phases of such projects. A mixed methods approach (survey, interviews and case studies) was employed to collect the required data. It is expected that with development, this framework can bring some significant benefits to future construction projects in terms of reducing rework and wastage, improving timely delivery and avoiding disputes. The research is also anticipated to produce three high impact journal articles.

Sustainability outcomes of infrastructure sustainability rating schemes for road projects

The construction and operation of infrastructure assets can have significant impact on society and the region. Using a sustainability assessment framework can be an effective means to build sustainability aspects into the design, construction and operation of infrastructure assets. The conventional evaluation processes and procedures for infrastructure projects do not necessarily measure the qualitative/quantitative effectiveness of all aspects of sustainability: environment, social wellbeing and economy. As a result, a few infrastructure sustainability rating schemes have been developed with a view to assess the level of sustainability attained in the infrastructure projects. These include: Infrastructure Sustainability (Australia); CEEQUAL (UK); and Envision (USA). In addition, road sector specific sustainability rating schemes such as Greenroads (USA) and Invest (Australia) have also been developed. These schemes address several aspects of sustainability with varying emphasis (weightings) on areas such as: use of resources; emission, pollution and waste; ecology; people and place; management and governance; and innovation. The attainment of sustainability of an infrastructure project depends largely on addressing the whole-of-life environmental issues. This study has analysed the rating schemes’ coverage of different environmental components for the road infrastructure under the five phases of a project: material, construction, use, maintenance and end-of-life. This is based on a comprehensive life cycle assessment (LCA) system boundary. The findings indicate that there is a need for the schemes to consider key (high impact) life cycle environmental components such as traffic congestion during construction, rolling resistance due to surface roughness and structural stiffness of the pavement, albedo, lighting, and end-of-life management (recycling) to deliver sustainable road projects.

Optimal Irrigation and N-fertilizer Management for Sustainable Winter Wheat Production in Khorezm, Uzbekistan

The efficiency of the nitrogen (N) application rates 0, 120, 180 and 240 kg N ha−1 in combination with low or medium water levels in the cultivation of winter wheat (Triticum aestivum L.) cv. Kupava was studied for the 2005–2006 and 2006–2007 growing seasons in the Khorezm region of Uzbekistan. The results show an impact of the initial soil Nmin (NO3-N + NH4-N) levels measured at wheat seeding on the N fertilizer rates applied. When the Nmin content in the 0–50 cm soil layer was lower than 10 mg kg−1 during wheat seeding in 2005, the N rate of 180 kg ha−1 was found to be the most effective for achieving high grain yields of high quality. With a higher Nmin content of about 30 mg kg−1 as was the case in the 2006 season, 120 kg N ha−1 was determined as being the technical and economical optimum. The temporal course of N2O emissions of winter wheat cultivation for the two water-level studies shows that emissions were strongly influenced by irrigation and N-fertilization. Extremely high emissions were measured immediately after fertilizer application events that were combined with irrigation events. Given the high impact of N-fertilizer and irrigation-water management on N2O emissions, it can be concluded that present N-management practices should be modified to mitigate emissions of N2O and to achieve higher fertilizer use efficiency.

Four generations of sequencing: Is it ready for the clinic yet?

Next-generation sequencing techniques have revolutionized over the last decade providing researchers with low cost, high-throughput alternatives compared to the traditional Sanger sequencing methods. These sequencing techniques have rapidly evolved from first-generation to fourth-generation with very broad applications such as unravelling the complexity of the genome, in terms of genetic variations, and having a high impact on the biological field. In this review, we discuss the transition of sequencing from the second-generation to the third- and fourth-generations, and describe some of their novel biological applications. With the advancement in technology, the earlier challenges of minimal size of the instrument, flexibility of throughput, ease of data analysis and short run times are being addressed. However, the need for prospective analysis and effectiveness to test whether the knowledge of any given new variants identified has an effect on clinical outcome may need improvement.

Priority threat management of non-native plants to maintain ecosystem integrity across heterogeneous landscapes

Invasive non-native plants have negatively impacted on biodiversity and ecosystem functions world-wide. Because of the large number of species, their wide distributions and varying degrees of impact, we need a more effective method for prioritizing control strategies for cost-effective investment across heterogeneous landscapes. Here, we develop a prioritization framework that synthesizes scientific data, elicits knowledge from experts and stakeholders to identify control strategies, and appraises the cost-effectiveness of strategies. Our objective was to identify the most cost-effective strategies for reducing the total area dominated by high-impact non-native plants in the Lake Eyre Basin (LEB). We use a case study of the ˜120 million ha Lake Eyre Basin that comprises some of the most distinctive Australian landscapes, including Uluru-Kata Tjuta National Park. More than 240 non-native plant species are recorded in the Lake Eyre Basin, with many predicted to spread, but there are insufficient resources to control all species. Lake Eyre Basin experts identified 12 strategies to control, contain or eradicate non-native species over the next 50 years. The total cost of the proposed Lake Eyre Basin strategies was estimated at AU$1·7 billion, an average of AU$34 million annually. Implementation of these strategies is estimated to reduce non-native plant dominance by 17 million ha – there would be a 32% reduction in the likely area dominated by non-native plants within 50 years if these strategies were implemented. The three most cost-effective strategies were controlling Parkinsonia aculeata, Ziziphus mauritiana and Prosopis spp. These three strategies combined were estimated to cost only 0·01% of total cost of all the strategies, but would provide 20% of the total benefits. Over 50 years, cost-effective spending of AU$2·3 million could eradicate all non-native plant species from the only threatened ecological community within the Lake Eyre Basin, the Great Artesian Basin discharge springs. Synthesis and applications. Our framework, based on a case study of the ˜120 million ha Lake Eyre Basin in Australia, provides a rationale for financially efficient investment in non-native plant management and reveals combinations of strategies that are optimal for different budgets. It also highlights knowledge gaps and incidental findings that could improve effective management of non-native plants, for example addressing the reliability of species distribution data and prevalence of information sharing across states and regions.

Investigating the population structure of Queensland invasive Streptococcus pneumoniae isolates in children: Using a modified multi-locus variable number of tandem repeat analysis and a novel minimum SNPs capsular typing method

This research investigated the use of DNA fingerprinting to characterise the bacteria Streptococcus pneumoniae or pneumococcus, and hence gain insight into the development of new vaccines or antibiotics. Different bacterial DNA fingerprinting methods were studied, and a novel method was developed and validated, which characterises different cell coatings that pneumococci produce. This method was used to study the epidemiology of pneumococci in Queensland before and after the introduction of the current pneumococcal vaccine. This study demonstrated that pneumococcal disease is highly prevalent in children under four years, that the bacteria can `switch' its cell coating to evade the vaccine, and that some DNA fingerprinting methods are more discriminatory than others. This has an impact on understanding which strains are more prone to cause invasive disease. Evidence of the excellent research findings have been published in high impact internationally refereed journals.

Effect of simulated rock dumping on geotextile

The use of geotextiles in coastal structures such as revetments and bund walls has become a common practice. The performance of these structures during their lifetime depends on the durability of geotextile used. During construction of these coastal structures, geotextiles are subjected to a drop load with high impact stress and that can damage the geotextile. In the current design practice, index tests are insufficient in predicting the performance of the geotextile. This puts the stability and performance of the coastal structures at risk. The current geotextile design guidelines are based on index tests and there is no standard procedure to account for the potential loss in the geotextile’s mechanical properties during installation (construction).This study aims to develop a standard procedure to estimate the properties of geotextile after its installation and using these properties for designing the performance of these structures. This paper describes the laboratory method of simulating large scale rock dumping on non-woven geotextiles and how to quantify the retained strength of damaged geotextiles. Results show that the reduction in retained strength of geotextile could extent up to 26% during installation.

Predicting weediness - what has the CRC achieved?

Dane Panetta and colleagues recently published their paper 'Predicting weediness - what has the CRC achieved?' in Proceedings of the 16th Australian Weeds Conference. They reviewed the research outcomes from the CRC for Australian Weeds Management for predicting weediness of plant species and concluded that advances have been made in identifying traits that distinguish high impact species for a range of environments. However these were not consistent between studies. They considered that Australia's border Weed Risk Assessment System has performed well under considerable local and international scientific scrutiny though minor improvements could still be made.

WHIPPET: a novel tool for prioritizing invasive plant populations for regional eradication

Large geographic areas can have numerous incipient invasive plant populations that necessitate eradication. However, resources are often deficient to address every infestation. Within the United States, weed lists (either state-level or smaller unit) generally guide the prioritization of eradication of each listed species uniformly across the focus region. This strategy has several limitations that can compromise overall effectiveness, which include spending limited resources on 1) low impact populations, 2) difficult to access populations, or 3) missing high impact populations of low priority species. Therefore, we developed a novel science-based, transparent, analytical ranking tool to prioritize weed populations, instead of species, for eradication and tested it on a group of noxious weeds in California. For outreach purposes, we named the tool WHIPPET (Weed Heuristics: Invasive Population Prioritization for Eradication Tool). Using the Analytic Hierarchy Process that included expert opinion, we developed three major criteria, four sub-criteria, and four sub-sub-criteria, taking into account both species and population characteristics. Subject matter experts weighted and scored these criteria to assess the relative impact, potential spread, and feasibility of eradication (major criteria) for 100 total populations of 19 species. Species-wide population scores indicated that conspecific populations do not necessarily group together in the final ranked output. Thus, priority lists based solely on species-level characteristics are less effective compared to a blended prioritization based on both species attributes and individual population and site parameters. WHIPPET should facilitate a more efficacious decision-making process allocating limited resources to target invasive plant infestations with the greatest predicted impacts to the region under consideration.