Sydney eScholarship
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Quantifying and Improving Bus Delay Prediction Accuracy in Sydney
No full textThe reliability of transit operations is a crucial factor in a user’s mode choice, as it affects their ability to make an accurate travel plan and arrive at their destination on time. Transit reliability, however, is not just about schedule adherence. Users can anticipate and adjust to regular deviations from a schedule and thus, for a user, transit reliability is often about schedule variance rather than absolute delay. With the advent of real-time data being made available to the public, users can make last-minute changes to their schedule based off the real-time delay reported in the transit network. These last-minute changes are dependent on the accuracy of the delay predictions, however, and so this thesis seeks to understand the accuracy of these predictions by quantifying the difference between them and the true delay. After quantifying this, the thesis proposes a series of post-processing additions to our current delay prediction models in order to improve the prediction accuracy. It was found that substantial improvements in delay prediction performance could be achieved, particularly when the buses were over 20 minutes away from a stop. Additionally, it was noted that this improvement varied depending on the error quantification method that was used, with the MAPE (Mean absolute percentage error) showing the greatest improvement. The thesis recommends the adoption of some of the improved prediction models and also discusses the implications of more transparently conveying the uncertainty in the prediction to users
Competency in general surgical training
No full textSurgical training has challenges, including the need to equip surgeons for future growth, which is underpinned by their training. This thesis systematically examines the application and implications of a competency-based training framework to the traditional master apprentice-based model for surgical education and training in Australia and elsewhere.
With significant technological advances and the implementation of advanced minimally invasive techniques such as robotic surgery, the validation of competency-based training as a foundation is tested. The objectives of this thesis, which are based on the implications of this training programme on the future growth capacity and evolution of the profession, are of the utmost importance.
This thesis aims to review surgical education and training and the need to adopt a new competency-based model, assess the impact of these core competencies, and apply the concepts of deliberative practice, feedback and reflections to surgical education and training.
The recognition that surgical proficiency develops along a continuum has led to the widespread adoption of lifelong learning principles in surgery, where surgeons are encouraged to assess and update their skills throughout their careers regularly. This model of ongoing education, combined with a structured approach to initial training, ensures that surgeons can perform complex procedures safely and effectively, even as new technologies and techniques emerge. The shift from a time-based model of surgical training to a competency-based one represents a significant advancement in the quality and consistency of surgical education, helping to ensure that all surgeons meet high standards of patient care
Supramolecular approaches for chloride transport
No full textThis thesis reports three different species of novel anion receptors designed to address current
challenges in the field of transmembrane anion transport. The chloride (Cl−) binding affinities of the
receptors were assessed, and their transport activities were investigated in model synthetic vesicle
systems.
In Chapter 2, carbazole was used as the scaffold for a series of 1,8-bis-(thio)urea compounds
appended with a variety of electron-withdrawing groups. The compounds exhibited a structural
change in the presence of excess Cl−, and high levels of anion transport activity were exhibited by
the most efficient compounds in the series, with a preference for non-selective anion transport.
Chapter 3 explored the transport activity of a series of isoquinoline-appended Pt(II) complexes in
synthetic model vesicles for the first time. Anionophoric activity was observed to be heavily
dependent on lipophilicity, with a preference for non-selective anion transport. The most active
complexes were also tested in vitro, and apoptosis was induced in cancerous cell lines, which
highlighted the therapeutic potential for these complexes.
In Chapter 4, a series of calix[4]pyrroles were appended with squaramides, and their anion transport
activities were investigated for the first time. The compounds exhibited improved transport properties
compared to the unsubstituted meso-octamethylcalix[4]pyrrole, with a preference for non-selective
anion transport. The results highlighted the significant impact of a single substituent on the transport
activity of the calix[4]pyrrole scaffold
Enhancing Dental Radiographic Interpretation by Collaborating with AI Systems to Minimise Interpretive Errors
No full textInterpretive errors in dental radiology pose risks to patient care, often resulting from limitations in human capabilities, including visual detection, pattern recognition and clinical reasoning. Despite the critical role of radiographic assessments, there is a lack of evidence on the prevalence and cause of dental radiographic interpretation, their consequences and the solutions to mitigate them. This PhD thesis addressed this gap by investigating the factors contributing to interpretive errors and evaluating the effectiveness of machine learning (ML) algorithms as cognitive aids in improving diagnostic accuracy.
The research involved a systematic review, surveys of Australian dental practitioners and students, and a comparative study assessing cognitive aids (ML algorithms and checklists) for diagnosing caries on bitewing radiographs. Errors of omission were most frequent, leading to undertreatment (72%), increased costs (62%), legal issues (82%) and reputational damage (75.6%).
ML algorithms significantly enhanced diagnostic performance, achieving a higher sensitivity (79%) and diagnostic odds ratio (20.3) than the other methods. Participants in the ML group also reported greater confidence in diagnosis. However, concerns regarding accuracy, trust and job displacement remain barriers to AI adoption in dentistry. Beyond caries detection, the potential applications of AI span dentomaxillofacial radiology, implantology and prosthodontics. Additionally, this thesis developed a novel explainability method, enabling clinicians and computer scientists to interpret ML-generated outputs better.
In conclusion, ML algorithms serve as valuable assistive cognitive aids, reducing interpretive errors and enhancing clinician confidence in dental radiology. The findings support AI integration as a means to improve diagnostic accuracy and clinical decision making in dentistry
Ten Provocations on AI, Trust, and the Future of Communication
No full textAs we enter a global artificial intelligence (AI) boom, it is important to bring together the disparate array of conversations, provocations, and prophecies regarding AI and its societal impacts. This article addresses such questions from the standpoint of trust as a concept and communications as a disciplinary field. It notes both historical continuities and areas of discontinuity in these debates and the importance of popular culture as a means of framing AI debates. This article also questions the pessimistic scenario on AI’s likely impact on education, noting that it could be potentially positive for the humanities
Event-based 3D Reconstruction: Innovative Event Representation Methods
No full textThe event camera is a bio-inspired asynchronous brightness-change sensor capable of performing various computer vision tasks such as object tracking, object recognition, depth estimation, etc. The sparse event stream generated by the event camera contains pixel coordinates, timestamps, and polarity information corresponding to changes in brightness. Event representation refers to the specialised data preprocessing and arrangement on the event stream, which facilitates feature information extraction. Many types of event representations have been developed, but each has characteristics that vary in their applicability to different tasks. Meanwhile, many studies have attempted to use event cameras for 3D reconstruction tasks. Stereo event cameras have been more widely used in 3D reconstruction, mainly for real-time semi-dense reconstruction by calculating disparity information. On the other hand, methods based on monocular event cameras are fewer and can be divided into geometry-based real-time semi-dense reconstruction methods and deep learning-based dense reconstruction methods. Most of these methods require physical prior information, such as trajectories, and rely on a pipeline for arranging the procedures. Recently, the E2V method innovatively proposed a direct deep learning-based approach for dense voxel 3D reconstruction without requiring physical priors or a pipeline, which is a complete simplification of the event processing structure. We use the E2V method as the experimental baseline and aim to improve it through event representation. In this study, we propose five new event representation methods: Differencing Event Frame, Sobel Event Frame, Differencing Sobel Event Frame, High-Pass Event Frame, and Differencing High-Pass Event Frame. These methods enhance edge information in event frames to improve the reconstruction accuracy of the E2V method. Experiments show that our proposed best event representation method can improve the mIoU by 54% and F-Score by 38% compared to the E2V method under the same experimental conditions, which is a significant improvement. Additionally, we are the first to propose that the binarisation threshold in deep learning-based event-driven 3D reconstruction tasks should be dynamically selected for optimal performance
Flogging a dead maxim? The future viability of the ex turpi rule in Australian law
No full textIn 1775 Lord Mansfield penned the classic formulation of the common law maxim ex turpi causa non oritur actio. ‘No court’, his Honour said, ‘will lend its aid to a man who founds his cause of action upon an immoral or an illegal act’. 250 years later, the scope of the ex turpi maxim is unclear. It has long been accepted that illegality may operate as a defence to civil claims by depriving a claimant of their otherwise legal rights on the ground of public policy. Yet the issue of when a party to a contract impacted in some way by illegality will be barred from enforcing their bargain, or recovering property transferred under it, remains uncertain. Case law regarding the maxim has been heavily criticised, not necessarily for producing incorrect outcomes, but for being notoriously difficult, inexplicable and inflexible. Parties to contracts, from everyday consumers to billion dollar businesses and innocent third parties, are left in doubt as to whether rights acquired or lost under contracts will be protected by the courts if their bargain is affected by statutory or common law illegality. This undermines the rule of law, which requires that the law be knowable and internally consistent, and exacerbates demands upon courts. The UK, Canada, Singapore and South Australia have toyed with creating a statutory judicial discretion to resolve questions of illegality but declined to implement legislative reform, except New Zealand. This research critically analyses the scope and character of the ex turpi maxim in Australia and synthesises from the common law a binding legal rule with clear exceptions to determine the effect of illegality in contract. That Synthesised Rule should be codified to better protect the maxim, promote greater clarity and consumer confidence. While the maxim is not the unruly horse of public policy it was once feared to be, statutory reform would guard against judicial error and jurisdictional creep which threaten to lure it away from orderly pastures
Extending the Ex Vivo Viability of Transplant Organs Using Normothermic Conditions
No full textLiver-related disease is a significant health issue globally, accounting for approximately 2 million deaths per year. In the most extreme cases such as end-stage liver disease, the only treatment is liver transplantation. Public health trends, such as an ageing population and rising obesity, are limiting the use of this treatment, increasing demand for transplants and reducing the supply of donated viable organs. This has led to the increasing use of extended criteria donor livers. However, these are known to result in generally worse transplant outcomes.
New technology is required to expand the donor pool, aimed at repairing and regenerating livers before transplantation. This will “retrieve” a large number of the donated livers that are currently discarded, returning them to viability. The core challenge, however, is that the biological processes involved in repairing and regenerating human livers are known to take place over a period of days and weeks.
While short-term normothermic machine perfusion of livers is well-established clinically, defined here as perfusion for a period of less than 24 hours, its primary benefit is improved assessment of livers prior to transplantation. Currently, no long-term normothermic machine perfusion systems are available commercially, meaning the critical solution of organ repair and regeneration has not yet been translated clinically.
This study builds on previous work undertaken by the research team at Royal Prince Alfred Transplant Institute, who developed a long-term normothermic perfusion model for livers that had successfully kept split livers alive for up to 13 days. The current work contributes automated management of critical system parameters, improving system stability and lowering human labour costs. Data from the successful perfusion of five human livers are presented, including a liver maintained ex vivo in a viable state for transplant for three weeks, longer than any organ recorded in the research literature
Developing 3D Models of Paediatric Solid Tumours
No full textHigh-grade gliomas (HGG) are aggressive brain tumours with no curative therapies, and survival rates have remained unchanged for decades. Although treatments often appear promising in preclinical studies using conventional 2D assays and animal models, they frequently fail at clinical trials due to a lack of efficacy or unacceptable toxicity. More representative 3D in vitro models of the tumour and healthy brain microenvironment are urgently required to address these discrepancies and to improve patient outcomes. Initially, we developed a functional assay for assessing neurotoxicity using dorsal cortical organoids mimicking the structure and cellular populations of the developing human neocortex. Spontaneous electrical activity in organoids, measured by micro-electrode array (MEA), was significantly altered upon chronic exposure to kinase inhibitors lorlatinib and gefitinib. Next, we evaluated the potency of a novel EphA2-targeted CAR-T cell therapy against HGG models. Treatment sensitivity decreased from 2D to 3D spheroid models, necessitating increased dosage and duration. When treatment was administered to assembloid co-culture models comprising both tumour and organoid components, CAR-T cells targeted EphA2-expressing tumour cells with diminished sensitivity, more closely reflecting in vivo responses. Lastly, patient-derived organoids (PDOs) were established from paediatric glioblastoma multiforme (pGBM) patient tumour samples, and circulating tumour DNA (ctDNA) was isolated from culture medium. ctDNA exhibited hotspot mutations consistent with clinical reports from the primary tumour, offering an alternative resource for diagnosis, preclinical therapeutic screening, and personalised treatment selection. Collectively, this research underscores the importance of 3D in vitro models in drug development and clinical workflows, demonstrating their utility in predicting neurotoxicity, assessing treatment efficacy, and enhancing diagnostic characterisation
Holocaust Education in Sydney and Regional New South Wales Classrooms
No full textThis thesis has examined the challenges faced by educators when teaching about the Holocaust to Stage 5 classes (Years 9 and 10) in schools across Sydney and in some regional areas in New South Wales. It is based on completed online questionnaires from 75 teachers, qualitative research with over 20 respondents, pre- and post-teaching questionnaires completed by 170 students, media reports and annual surveys of antisemitism by the ECAJ. It presents a thoroughly detailed picture of the state of Holocaust education in Sydney and regional classrooms. While many respondents teach about the Holocaust in great detail, spending well above the required hours and covering the essential aspects of Holocaust education, others spend far less time and some do not teach this topic at all. This is despite the Holocaust being a compulsory topic in New South Wales schools. While teachers noted a range of challenges in teaching about this topic, including available time and the confronting nature of the Holocaust, this research has demonstrated that racism and antisemitism present some of the greatest challenges for educators working across a range of sectors and schools. Almost 25% of teachers reported that racism and antisemitism were significant classroom challenges in their schools. Three key strands of antisemitism in Sydney schools have been identified, each of which has different historical antecedents and manifests itself in quite distinct ways. These differences in the nature of antisemitism across Sydney schools can be ascribed to demographic variations, especially with regard to socio-economic position, education, ethnicity and religion. This research has also shown the importance of gender, with very few respondents noting female students as perpetrators of racist or antisemitic incidents, and has highlighted the role that teacher professional development can play in preventing and responding to antisemitism in the classroom