Monitoring mesenchymal stem cell cultures using image processing and pattern recognition techniques

Stem cells have attracted tremendous interest in recent times due to their promise in providing innovative new treatments for a great range of currently debilitating diseases. This is due to their potential ability to regenerate and repair damaged tissue, and hence restore lost body function, in a manner beyond the body's usual healing process. Bone marrow-derived mesenchymal stem cells or bone marrow stromal cells are one type of adult stem cells that are of particular interest. Since they are derived from a living human adult donor, they do not have the ethical issues associated with the use of human embryonic stem cells. They are also able to be taken from a patient or other donors with relative ease and then grown readily in the laboratory for clinical application. Despite the attractive properties of bone marrow stromal cells, there is presently no quick and easy way to determine the quality of a sample of such cells. Presently, a sample must be grown for weeks and subject to various time-consuming assays, under the direction of an expert cell biologist, to determine whether it will be useful. Hence there is a great need for innovative new ways to assess the quality of cell cultures for research and potential clinical application. The research presented in this thesis investigates the use of computerised image processing and pattern recognition techniques to provide a quicker and simpler method for the quality assessment of bone marrow stromal cell cultures. In particular, aim of this work is to find out whether it is possible, through the use of image processing and pattern recognition techniques, to predict the growth potential of a culture of human bone marrow stromal cells at early stages, before it is readily apparent to a human observer. With the above aim in mind, a computerised system was developed to classify the quality of bone marrow stromal cell cultures based on phase contrast microscopy images. Our system was trained and tested on mixed images of both healthy and unhealthy bone marrow stromal cell samples taken from three different patients. This system, when presented with 44 previously unseen bone marrow stromal cell culture images, outperformed human experts in the ability to correctly classify healthy and unhealthy cultures. The system correctly classified the health status of an image 88% of the time compared to an average of 72% of the time for human experts. Extensive training and testing of the system on a set of 139 normal sized images and 567 smaller image tiles showed an average performance of 86% and 85% correct classifications, respectively. The contributions of this thesis include demonstrating the applicability and potential of computerised image processing and pattern recognition techniques to the task of quality assessment of bone marrow stromal cell cultures. As part of this system, an image normalisation method has been suggested and a new segmentation algorithm has been developed for locating cell regions of irregularly shaped cells in phase contrast images. Importantly, we have validated the efficacy of both the normalisation and segmentation method, by demonstrating that both methods quantitatively improve the classification performance of subsequent pattern recognition algorithms, in discriminating between cell cultures of differing health status. We have shown that the quality of a cell culture of bone marrow stromal cells may be assessed without the need to either segment individual cells or to use time-lapse imaging. Finally, we have proposed a set of features, that when extracted from the cell regions of segmented input images, can be used to train current state of the art pattern recognition systems to predict the quality of bone marrow stromal cell cultures earlier and more consistently than human experts.

Fault diagnostics and supervised testing : How fault diagnostic tools can be proactive?

The topic of fault detection and diagnostics (FDD) is studied from the perspective of proactive testing. Unlike most research focus in the diagnosis area in which system outputs are analyzed for diagnosis purposes, in this paper the focus is on the other side of the problem: manipulating system inputs for better diagnosis reasoning. In other words, the question of how diagnostic mechanisms can direct system inputs for better diagnosis analysis is addressed here. It is shown how the problem can be formulated as decision making problem coupled with a Bayesian Network based diagnostic mechanism. The developed mechanism is applied to the problem of supervised testing in HVAC systems.

Aerial image analysis using spiking neural networks with application to power line corridor monitoring

Trees, shrubs and other vegetation are of continued importance to the environment and our daily life. They provide shade around our roads and houses, offer a habitat for birds and wildlife, and absorb air pollutants. However, vegetation touching power lines is a risk to public safety and the environment, and one of the main causes of power supply problems. Vegetation management, which includes tree trimming and vegetation control, is a significant cost component of the maintenance of electrical infrastructure. For example, Ergon Energy, the Australia’s largest geographic footprint energy distributor, currently spends over $80 million a year inspecting and managing vegetation that encroach on power line assets. Currently, most vegetation management programs for distribution systems are calendar-based ground patrol. However, calendar-based inspection by linesman is labour-intensive, time consuming and expensive. It also results in some zones being trimmed more frequently than needed and others not cut often enough. Moreover, it’s seldom practicable to measure all the plants around power line corridors by field methods. Remote sensing data captured from airborne sensors has great potential in assisting vegetation management in power line corridors. This thesis presented a comprehensive study on using spiking neural networks in a specific image analysis application: power line corridor monitoring. Theoretically, the thesis focuses on a biologically inspired spiking cortical model: pulse coupled neural network (PCNN). The original PCNN model was simplified in order to better analyze the pulse dynamics and control the performance. Some new and effective algorithms were developed based on the proposed spiking cortical model for object detection, image segmentation and invariant feature extraction. The developed algorithms were evaluated in a number of experiments using real image data collected from our flight trails. The experimental results demonstrated the effectiveness and advantages of spiking neural networks in image processing tasks. Operationally, the knowledge gained from this research project offers a good reference to our industry partner (i.e. Ergon Energy) and other energy utilities who wants to improve their vegetation management activities. The novel approaches described in this thesis showed the potential of using the cutting edge sensor technologies and intelligent computing techniques in improve power line corridor monitoring. The lessons learnt from this project are also expected to increase the confidence of energy companies to move from traditional vegetation management strategy to a more automated, accurate and cost-effective solution using aerial remote sensing techniques.

Frequency response function based structural damage detection using artificial neural networks

Damage detection in structures has become increasingly important in recent years. While a number of damage detection and localization methods have been proposed, few attempts have been made to explore the structure damage with frequency response functions (FRFs). This paper illustrates the damage identification and condition assessment of a beam structure using a new frequency response functions (FRFs) based damage index and Artificial Neural Networks (ANNs). In practice, usage of all available FRF data as an input to artificial neural networks makes the training and convergence impossible. Therefore one of the data reduction techniques Principal Component Analysis (PCA) is introduced in the algorithm. In the proposed procedure, a large set of FRFs are divided into sub-sets in order to find the damage indices for different frequency points of different damage scenarios. The basic idea of this method is to establish features of damaged structure using FRFs from different measurement points of different sub-sets of intact structure. Then using these features, damage indices of different damage cases of the structure are identified after reconstructing of available FRF data using PCA. The obtained damage indices corresponding to different damage locations and severities are introduced as input variable to developed artificial neural networks. Finally, the effectiveness of the proposed method is illustrated and validated by using the finite element modal of a beam structure. The illustrated results show that the PCA based damage index is suitable and effective for structural damage detection and condition assessment of building structures.

Social influences on Chinese drivers : cultural context and traffic law enforcement

Reducing road crashes and associated trauma is a critical focus as the Decade of Action for Road Safety commences. China is one of many rapidly-motorizing nations to experience recent increases in private-vehicle ownership and an associated escalation in novice drivers. Unfortunately, however, China also experiences a high rate of death and injury from road crashes. Several key pieces of legislation have been introduced in recent decades in China to deal with these changes. While managing the legal aspects of road use is important, social influences on driver behaviour may offer additional avenues for promoting safe driving, particularly in a culture where such factors carry high importance. To date, there is limited research on the role of social influence factors on driver behaviour in China, yet we know that Chinese society is strongly based on social rules, customs, and relationships. There is reason to assume therefore, that road use and driving-related issues may also be strongly influenced by social relationships. One previous study that has investigated such issues highlighted the need to consider culturally-specific issues such as interpersonal networks and social hierarchy when examining driver behaviour in China (Xie & Parker, 2002). Those authors suggested that there are some concepts relating to Chinese driving culture that may not necessarily have been identified from research conducted in western contexts and that research conducted in China must be considered in light of such concepts. The current paper reports qualitative research conducted with Beijing drivers to investigate such social influence factors. Findings indicated that family members, friends, and driving instructors appear influential on driver behaviour and that some novice drivers seek additional assistance after obtaining their licence. The finding relating to the influence of driving instructors was not surprising, given the substantial number of new drivers in China. In Beijing, driving instruction is conducted off-road in purpose-specific driving facilities rather than on the road network. Once licensed, it is common for new drivers to have little or no experience driving in complex traffic situations. This learning situation is unlikely to provide all the skills necessary to successfully negotiate crowded city streets and assess the related risk associated with such driving. Therefore, it was not surprising to find that one reported strategy to assist new drivers was to employ the services of an ‘accompanying driver’ to provide ongoing driving instruction once licensed. In more highly motorised countries supervised practice is part of a graduated licensing system where it is compulsory for new drivers to be supervised by a more experienced driver for a requisite period of time before progressing to solo driving. However, as this system is not in place in China, it appears that some drivers seek out and pay for additional support once they commence on-road driving. Additionally, strategies to avoid detection and penalties for inappropriate road use were discussed, many of which involve the use of a third person. These findings indicate potential barriers to implementing effective traffic enforcement and highlight the importance of understanding culturally-specific social factors relating to driver behaviour.

Resilience of a corrupt police network : the first and second jokes in Queensland

Resilient organised crime groups survive and prosper despite law enforcement activity, criminal competition and market forces. Corrupt police networks, like any other crime network, must contain resiliency characteristics if they are to continue operation and avoid being closed down through detection and arrest of their members. This paper examines the resilience of a large corrupt police network, namely The Joke which operated in the Australian state of Queensland for a number of decades. The paper uses social network analysis tools to determine the resilient characteristics of the network. This paper also assumes that these characteristics will be different to those of mainstream organised crime groups because the police network operates within an established policing agency rather than as an independent entity hiding within the broader community.

Approximate clone detection in repositories of business process models

Evidence exists that repositories of business process models used in industrial practice contain significant amounts of duplication. This duplication may stem from the fact that the repository describes variants of the same pro- cesses and/or because of copy/pasting activity throughout the lifetime of the repository. Previous work has put forward techniques for identifying duplicate fragments (clones) that can be refactored into shared subprocesses. However, these techniques are limited to finding exact clones. This paper analyzes the prob- lem of approximate clone detection and puts forward two techniques for detecting clusters of approximate clones. Experiments show that the proposed techniques are able to accurately retrieve clusters of approximate clones that originate from copy/pasting followed by independent modifications to the copied fragments.

Flight trial of an electro-optical sense-and-avoid system

This paper presents the flight trials of an electro-optical (EO) sense-and-avoid system onboard a Cessna host aircraft (camera aircraft). We focus on the autonomous collision avoidance capability of the sense-and-avoid system; that is, closed-loop integration with the onboard aircraft autopilot. We also discuss the system’s approach to target detection and avoidance control, as well as the methodology of the flight trials. The results demonstrate the ability of the sense-and-avoid system to automatically detect potential conflicting aircraft and engage the host Cessna autopilot to perform an avoidance manoeuvre, all without any human intervention

Activity analysis in complicated scenes using DFT coefficients of particle trajectories

Modelling activities in crowded scenes is very challenging as object tracking is not robust in complicated scenes and optical flow does not capture long range motion. We propose a novel approach to analyse activities in crowded scenes using a “bag of particle trajectories”. Particle trajectories are extracted from foreground regions within short video clips using particle video, which estimates long range motion in contrast to optical flow which is only concerned with inter-frame motion. Our applications include temporal video segmentation and anomaly detection, and we perform our evaluation on several real-world datasets containing complicated scenes. We show that our approaches achieve state-of-the-art performance for both tasks.

The roles of the preproghrelin-derived peptides - ghrelin, desacyl ghrelin and obestatin - in prostate cancer

Prostate cancer is the second most common cause of cancer related deaths in Western men. Despite the significant improvements in current treatment techniques, there is no cure for advanced metastatic, castrate-resistant disease. Early detection and prevention of progression to a castrate-resistant state may provide new strategies to improve survival. A number of growth factors have been shown to act in an autocrine/paracrine manner to modulate prostate cancer tumour growth. Our laboratory has previously shown that ghrelin and its receptors (the functional GHS-R1a and the non-functional GHS-R1b) are expressed in prostate cancer specimens and cell lines. We have shown that ghrelin increases cell proliferation in the PC3 and LNCaP prostate cancer cell lines through activation of ERK1/2, suggesting that ghrelin could regulate prostate cancer cell growth and play a role in the progression of the disease. Ghrelin is a 28 amino-acid peptide hormone, identified to be the natural ligand of the growth hormone secretagogue receptor (GHS-R1a). It is well characterised as a growth hormone releasing and as an orexigenic peptide that stimulates appetite and feeding and regulates energy expenditure and bodyweight. In addition to its orexigenic properties, ghrelin has been shown to play a regulatory role in a number of systems, including the reproductive, immune and cardiovascular systems and may play a role in a number of pathological conditions such as chronic heart failure, anorexia, cachexia, obesity, diabetes and cancer. In cancer, ghrelin and its receptor are expressed in a range of tumours and cancer cell lines and ghrelin has been demonstrated to modulate cell proliferation, apoptosis, migration and invasion in some cell types. The ghrelin gene (GHRL) encodes preproghrelin peptide, which is processed to produce three currently known functional peptides - ghrelin, desacyl ghrelin and obestatin. Prohormone convertases (PCs) have been shown to cleave the preproghrelin peptide into two primary products - the 28 amino acid peptide, ghrelin, and the remaining 117 amino acid C-terminal peptide, C-ghrelin. C-ghrelin can then be further processed to produce the 23 amino acid peptide, obestatin. Ghrelin circulates in two different forms - an octanoylated form (known as ghrelin) and a non-octanoylated form, desacyl ghrelin. The unique post-translational addition of octanoic acid to the serine 3 residue of the propeptide chain to form acylated ghrelin is catalysed by ghrelin O-acyltransferase (GOAT). This modification is necessary for binding of ghrelin to its only known functional receptor, the GHS-R1a. As desacyl ghrelin cannot bind and activate the GHS-R1a, it was initially thought to be an inactive peptide, despite the fact that it circulates at much higher levels than ghrelin. Further research has demonstrated that desacyl ghrelin is biologically active and shares some of the actions of ghrelin, as well as having some opposing and distinct roles. Interestingly, both ghrelin and desacyl ghrelin have been shown to modulate apoptosis, cell differentiation and proliferation in some cell types, and to stimulate cell proliferation through activation of ERK1/2 and PI3K/Akt pathways. The third known peptide product of the ghrelin preprohormone, obestatin, was initially thought to oppose the actions of ghrelin in appetite regulation and food intake and to mediate its effects through the G protein-coupled receptor 39 (GPR39). Subsequent research failed to reproduce the initial findings, however, and the possible anorexigenic effects of obestatin, as well as the identity of its receptor, remain unclear. Obestatin plays some important physiological roles, including roles in improving memory, the inhibition of thirst and anxiety, increased secretion of pancreatic juice, and regulation of cell proliferation, survival, apoptosis and differentiation. Preliminary studies have also shown that obestatin stimulates cell proliferation in some cell types through activation of ERK1/2, Akt and PKC pathways. Overall, however, at the commencement of this PhD project, relatively little was known regarding the functions and mechanisms of action of the preproghrelin-derived functional peptides in modulating prostate cancer cell proliferation. The roles of obestatin, and desacyl ghrelin as potential growth factors had not previously been investigated, and the potential expression and regulation of the preproghrelin processing enzymes, GOAT and prohormone convertases was unknown in prostate cancer cell lines. Therefore, the overall objectives of this study were to: 1. investigate the effects of obestatin on cell proliferation and signaling in prostate cancer cell lines 2. compare the effects of desacyl ghrelin and ghrelin on cell proliferation and signaling in prostate cancer cell lines 3. investigate whether prostate cancer cell lines possess the necessary enzymatic machinery to produce ghrelin and desacyl ghrelin and if these peptides can regulate GOAT expression Our laboratory has previously shown that ghrelin stimulates cell proliferation in the PC3 and LNCaP prostate cancer cell line through activation of the ERK1/2 pathway. In this study it has been demonstrated that treatments with either ghrelin, desacyl ghrelin or obestatin over 72 hours significantly increased cell proliferation in the PC3 prostate cancer cell line but had no significant effect in the RWPE-1 transformed normal prostate cell line. Ghrelin (1000nM) stimulated cell proliferation in the PC3 prostate cancer cell line by 31.66 6.68% (p<0.01) with the WST-1 method, and 13.55 5.68% (p<0.05) with the CyQUANT assay. Desacyl ghrelin (1000nM) increased cell proliferation in PC3 cells by 21.73 2.62% (p<0.01) (WST-1), and 15.46 7.05% (p<0.05) (CyQUANT) above untreated control. Obestatin (1000nM) induced a 28.37 7.47% (p<0.01) (WST-1) and 12.14 7.47% (p<0.05) (CyQUANT) significant increase in cell proliferation in the PC3 prostate cancer cell line. Ghrelin and desacyl ghrelin treatments stimulated Akt and ERK phosphorylation across a range of concentrations (p<0.01). Obestatin treatment significantly stimulated Akt, ERK and PKC phosphorylation (p<0.05). Through the use of specific inhibitors, the MAPK inhibitor U0126 and the Akt1/2 kinase inhibitor, it was demonstrated that ghrelin- and obestatin-induced cell proliferation in the PC3 prostate cancer cell line is mediated through activation of ERK1/2 and Akt pathways. Although desacyl ghrelin significantly stimulated Akt and ERK phosphorylation, U0126 failed to prevent desacyl ghrelin-induced cell proliferation suggesting ghrelin and desacyl ghrelin might act through different mechanisms to increase cell proliferation. Ghrelin and desacyl ghrelin have shown a proliferative effect in osteoblasts, pancreatic -cells and cardiomyocytes through activation of ERK1/2 and PI3K/Akt pathways. Here it has been shown that ghrelin and its non-acylated form exert the same function and stimulate cell proliferation in the PC3 prostate cancer cell line through activation of the Akt pathway. Ghrelin-induced proliferation was also mediated through activation of the ERK1/2 pathway, however, desacyl ghrelin seems to stimulate cell proliferation in an ERK1/2-independent manner. As desacyl ghrelin does not bind and activate GHSR1a, the only known functional ghrelin receptor, the finding that both ghrelin and desacyl ghrelin stimulate cell proliferation in the PC3 cell line suggests that these peptides could be acting through the yet unidentified alternative ghrelin receptor in this cell type. Obestatin treatment also stimulated PKC phosphorylation, however, a direct role for this pathway in stimulating cell proliferation could not be proven using available PKC pathway inhibitors, as they caused significant cell death over the extended timeframe of the cell proliferation assays. Obestatin has been shown to stimulate cell proliferation through activation of PKC isoforms in human retinal epithelial cells and in the human gastric cancer cell line KATO-III. We have demonstrated that all of the prostate-derived cell lines examined (PC3, LNCaP, DU145, 22Rv1, RWPE-1 and RWPE-2) expressed GOAT and at least one of the prohormone convertases, which are known to cleave the proghrelin peptide, PC1/3, PC2 and furin, at the mRNA level. These cells, therefore, are likely to possess the necessary machinery to cleave the preproghrelin protein and to produce the mature ghrelin and desacyl ghrelin peptides. In addition to prohormone convertases, the presence of octanoic acid is essential for acylated ghrelin production. In this study octanoic acid supplementation significantly increased cell proliferation in the PC3 prostate cancer cell line by over 20% compared to untreated controls (p<0.01), but surprisingly, not in the DU145, LNCaP or 22Rv1 prostate cancer cell lines or in the RWPE-1 and RWPE-2 prostate-derived cell lines. In addition, we demonstrated that exogenous ghrelin induced a statistically significant two-fold decrease in GOAT mRNA expression in the PC3 cell line (p<0.05), suggesting that ghrelin could pontentially downregulate its own acylation and, therefore, regulate the balance between ghrelin and desacyl ghrelin. This was not observed, however, in the DU145 and LNCaP prostate cancer cell lines. The GOAT-ghrelin system represents a direct link between ingested nutrients and regulation of ghrelin production and the ghrelin/desacyl ghrelin ratio. Regulation of ghrelin acylation is a potentially attractive and desirable tool for the development of better therapies for a number of pathological conditions where ghrelin has been shown to play a key role. The finding that desacyl ghrelin stimulates cell proliferation in the PC3 prostate cancer cell line, and responds to ghrelin in the same way, suggests that this cell line expresses an alternative ghrelin receptor. Although all the cell lines examined expressed both GHS-R1a and GHS-R1b mRNA, it remains uncertain whether these cell lines express the unidentified alternative ghrelin receptor. It is possible that the varied responses seen could be due to the expression of different ghrelin receptors in different cell lines. In addition to GOAT, prohormone convertases and octanoic acid availability may regulate the production of different peptides from the ghrelin preprohormone. The studies presented in this thesis provide significant new information regarding the roles and mechanisms of action of the preproghrelin-derived peptides, ghrelin, desacyl ghrelin and obestatin, in modulating prostate cancer cell line proliferation. A number of key questions remain to be resolved, however, including the identification of the alternative ghrelin/desacyl ghrelin receptor, the identification of the obestatin receptor, a clarification of the signaling mechanisms which mediate cell proliferation in response to obestatin treatment and a better understanding of the regulation at both the gene and post-translational levels of functional peptide generation. Further studies investigating the role of the ghrelin axis using in vivo prostate cancer models may be warranted. Until these issues are determined, the potential for the ghrelin axis, to be recognised as a novel useful target for therapy for cancer or other pathologies will be uncertain.

Teachers’ detecting and reporting child abuse and neglect : research into the determinants of complex professional behavior

Child abuse and neglect is prevalent and entails significant costs to children, families and society. Teachers are responsible for significant proportions of official notifications to statutory child protection agencies. Hence, their accurate and appropriate reporting is crucial for well-functioning child protection systems. Approximately one-quarter of Australian teachers indicate never detecting a case of child maltreatment across their careers, while a further 13-15% admit to not reporting suspected cases in some circumstances. The detection and reporting of child abuse and neglect are complex decision-making behaviors, influenced by: the nature of the maltreatment itself; the characteristics of the teacher; the school environment; and the broader legislative and policy environment. In this chapter, the authors provide a background to teachers’ involvement in detecting and reporting child abuse and neglect, and an overview of the role of teachers is provided. Results are presented from three Australian studies that examine the unique contributions of: case; teacher; and contextual characteristics to detection and reporting behaviors. The authors conclude by highlighting the key implications for enhancing teacher training in child abuse and neglect, and outline future research directions.

Impact of physical, psychological, and sexual violence on social adjustment of school children in India

and sexual violence on the social adjustment of Grade 8 and 9 school children in the state of Tripura, India. The study participants, 160 boys and 160 girls, were randomly selected from classes in eight English and Bengali medium schools in Agartala city, Tripura. Data were collected using a self-administered Semi-structured Questionnaire for Children/Students and a Social Adjustment Inventory which were custom-made for the study based on measures in the extant research adapted for the Indian context. Findings revealed that students experienced physical (21.9%), psychological (20.9%), and sexual (18.1%) violence at home, and 29.7% of the children had witnessed family violence. Boys were more often victims of physical and psychological violence while girls were more often victims of sexual violence. The social adjustment scores of school children who experienced violence, regardless of the nature of the violence, was significantly lower when compared with scores of those who had not experienced violence (p<0.001). Social adjustment was poorer for girls than boys (p<0.001). The study speaks in favour of early detection and intervention for all child maltreatment subtypes and for children exposed to interparental violence, and highlights the crucial role of schools and school psychology in addressing the problem.

The relationship between drivers’ perceptions toward police speed enforcement and self-reported speeding behaviour

Exceeding the speed limit and driving too fast for the conditions are regularly cited as significant contributing factors in traffic crashes, particularly fatal and serious injury crashes. Despite an extensive body of research highlighting the relationship between increased vehicle speeds and crash risk and severity, speeding remains a pervasive behaviour on Australian roads. The development of effective countermeasures designed to reduce the prevalence of speeding behaviour requires that this behaviour is well understood. The primary aim of this program of research was to develop a better understanding of the influence of drivers’ perceptions and attitudes toward police speed enforcement on speeding behaviour. Study 1 employed focus group discussions with 39 licensed drivers to explore the influence of perceptions relating to specific characteristics of speed enforcement policies and practices on drivers’ attitudes towards speed enforcement. Three primary factors were identified as being most influential: site selection; visibility; and automaticity (i.e., whether the enforcement approach is automated/camera-based or manually operated). Perceptions regarding these enforcement characteristics were found to influence attitudes regarding the perceived legitimacy and transparency of speed enforcement. Moreover, misperceptions regarding speed enforcement policies and practices appeared to also have a substantial impact on attitudes toward speed enforcement, typically in a negative direction. These findings have important implications for road safety given that prior research has suggested that the effectiveness of speed enforcement approaches may be reduced if efforts are perceived by drivers as being illegitimate, such that they do little to encourage voluntary compliance. Study 1 also examined the impact of speed enforcement approaches varying in the degree of visibility and automaticity on self-reported willingness to comply with speed limits. These discussions suggested that all of the examined speed enforcement approaches (see Section 1.5 for more details) generally showed potential to reduce vehicle speeds and encourage compliance with posted speed limits. Nonetheless, participant responses suggested a greater willingness to comply with approaches operated in a highly visible manner, irrespective of the corresponding level of automaticity of the approach. While less visible approaches were typically associated with poorer rates of driver acceptance (e.g., perceived as “sneaky” and “unfair”), participants reported that such approaches would likely encourage long-term and network-wide impacts on their own speeding behaviour, as a function of the increased unpredictability of operations and increased direct (specific deterrence) and vicarious (general deterrence) experiences with punishment. Participants in Study 1 suggested that automated approaches, particularly when operated in a highly visible manner, do little to encourage compliance with speed limits except in the immediate vicinity of the enforcement location. While speed cameras have been criticised on such grounds in the past, such approaches can still have substantial road safety benefits if implemented in high-risk settings. Moreover, site-learning effects associated with automated approaches can also be argued to be a beneficial by-product of enforcement, such that behavioural modifications are achieved even in the absence of actual enforcement. Conversely, manually operated approaches were reported to be associated with more network-wide impacts on behaviour. In addition, the reported acceptance of such methods was high, due to the increased swiftness of punishment, ability for additional illegal driving behaviours to be policed and the salutary influence associated with increased face-to-face contact with authority. Study 2 involved a quantitative survey conducted with 718 licensed Queensland drivers from metropolitan and regional areas. The survey sought to further examine the influence of the visibility and automaticity of operations on self-reported likelihood and duration of compliance. Overall, the results from Study 2 corroborated those of Study 1. All examined approaches were again found to encourage compliance with speed limits, such that all approaches could be considered to be “effective”. Nonetheless, significantly greater self-reported likelihood and duration of compliance was associated with visibly operated approaches, irrespective of the corresponding automaticity of the approach. In addition, the impact of automaticity was influenced by visibility; such that significantly greater self-reported likelihood of compliance was associated with manually operated approaches, but only when they are operated in a less visible fashion. Conversely, manually operated approaches were associated with significantly greater durations of self-reported compliance, but only when they are operated in a highly visible manner. Taken together, the findings from Studies 1 and 2 suggest that enforcement efforts, irrespective of their visibility or automaticity, generally encourage compliance with speed limits. However, the duration of these effects on behaviour upon removal of the enforcement efforts remains questionable and represents an area where current speed enforcement practices could possibly be improved. Overall, it appears that identifying the optimal mix of enforcement operations, implementing them at a sufficient intensity and increasing the unpredictability of enforcement efforts (e.g., greater use of less visible approaches, random scheduling) are critical elements of success. Hierarchical multiple regression analyses were also performed in Study 2 to investigate the punishment-related and attitudinal constructs that influence self-reported frequency of speeding behaviour. The research was based on the theoretical framework of expanded deterrence theory, augmented with three particular attitudinal constructs. Specifically, previous research examining the influence of attitudes on speeding behaviour has typically focussed on attitudes toward speeding behaviour in general only. This research sought to more comprehensively explore the influence of attitudes by also individually measuring and analysing attitudes toward speed enforcement and attitudes toward the appropriateness of speed limits on speeding behaviour. Consistent with previous research, a number of classical and expanded deterrence theory variables were found to significantly predict self-reported frequency of speeding behaviour. Significantly greater speeding behaviour was typically reported by those participants who perceived punishment associated with speeding to be less certain, who reported more frequent use of punishment avoidance strategies and who reported greater direct experiences with punishment. A number of interesting differences in the significant predictors among males and females, as well as younger and older drivers, were reported. Specifically, classical deterrence theory variables appeared most influential on the speeding behaviour of males and younger drivers, while expanded deterrence theory constructs appeared more influential for females. These findings have important implications for the development and implementation of speeding countermeasures. Of the attitudinal factors, significantly greater self-reported frequency of speeding behaviour was reported among participants who held more favourable attitudes toward speeding and who perceived speed limits to be set inappropriately low. Disappointingly, attitudes toward speed enforcement were found to have little influence on reported speeding behaviour, over and above the other deterrence theory and attitudinal constructs. Indeed, the relationship between attitudes toward speed enforcement and self-reported speeding behaviour was completely accounted for by attitudes toward speeding. Nonetheless, the complexity of attitudes toward speed enforcement are not yet fully understood and future research should more comprehensively explore the measurement of this construct. Finally, given the wealth of evidence (both in general and emerging from this program of research) highlighting the association between punishment avoidance and speeding behaviour, Study 2 also sought to investigate the factors that influence the self-reported propensity to use punishment avoidance strategies. A standard multiple regression analysis was conducted for exploratory purposes only. The results revealed that punishment-related and attitudinal factors significantly predicted approximately one fifth of the variance in the dependent variable. The perceived ability to avoid punishment, vicarious punishment experience, vicarious punishment avoidance and attitudes toward speeding were all significant predictors. Future research should examine these relationships more thoroughly and identify additional influential factors. In summary, the current program of research has a number of implications for road safety and speed enforcement policy and practice decision-making. The research highlights a number of potential avenues for the improvement of public education regarding enforcement efforts and provides a number of insights into punishment avoidance behaviours. In addition, the research adds strength to the argument that enforcement approaches should not only demonstrate effectiveness in achieving key road safety objectives, such as reduced vehicle speeds and associated crashes, but also strive to be transparent and legitimate, such that voluntary compliance is encouraged. A number of potential strategies are discussed (e.g., point-to-point speed cameras, intelligent speed adaptation. The correct mix and intensity of enforcement approaches appears critical for achieving optimum effectiveness from enforcement efforts, as well as enhancements in the unpredictability of operations and swiftness of punishment. Achievement of these goals should increase both the general and specific deterrent effects associated with enforcement through an increased perceived risk of detection and a more balanced exposure to punishment and punishment avoidance experiences.

Tax evasion, inequality, and progressive taxes : a political economy perspective

The standard approach to tax compliance applies the economics-of-crime methodology pioneered by Becker (1968): in its first application, due to Allingham and Sandmo (1972) it models the behaviour of agents as a decision involving a choice of the extent of their income to report to tax authorities, given a certain institutional environment, represented by parameters such as the probability of detection and penalties in the event the agent is caught. While this basic framework yields important insights on tax compliance behavior, it has some critical limitations. Specifically, it indicates a level of compliance that is significantly below what is observed in the data. This thesis revisits the original framework with a view towards addressing this issue, and examining the political economy implications of tax evasion for progressivity in the tax structure. The approach followed involves building a macroeconomic, dynamic equilibrium model for the purpose of examining these issues, by using a step-wise model building procedure starting with some very simple variations of the basic Allingham and Sandmo construct, which are eventually integrated to a dynamic general equilibrium overlapping generations framework with heterogeneous agents. One of the variations involves incorporating the Allingham and Sandmo construct into a two-period model of a small open economy of the type originally attributed to Fisher (1930). A further variation of this simple construct involves allowing agents to initially decide whether to evade taxes or not. In the event they decide to evade, the agents then have to decide the extent of income or wealth they wish to under-report. We find that the ‘evade or not’ assumption has strikingly different and more realistic implications for the extent of evasion, and demonstrate that it is a more appropriate modeling strategy in the context of macroeconomic models, which are essentially dynamic in nature, and involve consumption smoothing across time and across various states of nature. Specifically, since deciding to undertake tax evasion impacts on the consumption smoothing ability of the agent by creating two states of nature in which the agent is ‘caught’ or ‘not caught’, there is a possibility that their utility under certainty, when they choose not to evade, is higher than the expected utility obtained when they choose to evade. Furthermore, the simple two-period model incorporating an ‘evade or not’ choice can be used to demonstrate some strikingly different political economy implications relative to its Allingham and Sandmo counterpart. In variations of the two models that allow for voting on the tax parameter, we find that agents typically choose to vote for a high degree of progressivity by choosing the highest available tax rate from the menu of choices available to them. There is, however, a small range of inequality levels for which agents in the ‘evade or not’ model vote for a relatively low value of the tax rate. The final steps in the model building procedure involve grafting the two-period models with a political economy choice into a dynamic overlapping generations setting with more general, non-linear tax schedules and a ‘cost-of evasion’ function that is increasing in the extent of evasion. Results based on numerical simulations of these models show further improvement in the model’s ability to match empirically plausible levels of tax evasion. In addition, the differences between the political economy implications of the ‘evade or not’ version of the model and its Allingham and Sandmo counterpart are now very striking; there is now a large range of values of the inequality parameter for which agents in the ‘evade or not’ model vote for a low degree of progressivity. This is because, in the ‘evade or not’ version of the model, low values of the tax rate encourages a large number of agents to choose the ‘not-evade’ option, so that the redistributive mechanism is more ‘efficient’ relative to the situations in which tax rates are high. Some further implications of the models of this thesis relate to whether variations in the level of inequality, and parameters such as the probability of detection and penalties for tax evasion matter for the political economy results. We find that (i) the political economy outcomes for the tax rate are quite insensitive to changes in inequality, and (ii) the voting outcomes change in non-monotonic ways in response to changes in the probability of detection and penalty rates. Specifically, the model suggests that changes in inequality should not matter, although the political outcome for the tax rate for a given level of inequality is conditional on whether there is a large or small or large extent of evasion in the economy. We conclude that further theoretical research into macroeconomic models of tax evasion is required to identify the structural relationships underpinning the link between inequality and redistribution in the presence of tax evasion. The models of this thesis provide a necessary first step in that direction.

Prostate cancer biomarkers and the emerging proteomic techniques used in biomarker research

Prostate cancer (CaP) is the second leading cause of cancer-related deaths in North American males and the most common newly diagnosed cancer in men world wide. Biomarkers are widely used for both early detection and prognostic tests for cancer. The current, commonly used biomarker for CaP is serum prostate specific antigen (PSA). However, the specificity of this biomarker is low as its serum level is not only increased in CaP but also in various other diseases, with age and even body mass index. Human body fluids provide an excellent resource for the discovery of biomarkers, with the advantage over tissue/biopsy samples of their ease of access, due to the less invasive nature of collection. However, their analysis presents challenges in terms of variability and validation. Blood and urine are two human body fluids commonly used for CaP research, but their proteomic analyses are limited both by the large dynamic range of protein abundance making detection of low abundance proteins difficult and in the case of urine, by the high salt concentration. To overcome these challenges, different techniques for removal of high abundance proteins and enrichment of low abundance proteins are used. Their applications and limitations are discussed in this review. A number of innovative proteomic techniques have improved detection of biomarkers. They include two dimensional differential gel electrophoresis (2D-DIGE), quantitative mass spectrometry (MS) and functional proteomic studies, i.e., investigating the association of post translational modifications (PTMs) such as phosphorylation, glycosylation and protein degradation. The recent development of quantitative MS techniques such as stable isotope labeling with amino acids in cell culture (SILAC), isobaric tags for relative and absolute quantitation (iTRAQ) and multiple reaction monitoring (MRM) have allowed proteomic researchers to quantitatively compare data from different samples. 2D-DIGE has greatly improved the statistical power of classical 2D gel analysis by introducing an internal control. This chapter aims to review novel CaP biomarkers as well as to discuss current trends in biomarker research from two angles: the source of biomarkers (particularly human body fluids such as blood and urine), and emerging proteomic approaches for biomarker research.