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ARC Industry Laureate Fellowship project newsletter
No full textThe five-year Australian Research Council (ARC) Industry Laureate Fellowship project, led by Professor Jennifer Smith-Merry, continues to make strong progress toward improving outcomes for people with psychosocial disability within the National Disability Insurance Scheme (NDIS). See our December newsletter for latest updates
The Role of Risk Aversion in Morality
No full textMoral decision-making is increasingly salient amid global political and economic instability. Although past research has examined moral reasoning and situational influences, less is known about the psychological mechanisms and individual differences shaping moral choices. From an evolutionary perspective, morality promotes long-term cooperative benefits over short-term self-interest, yet some individuals still prioritise immediate personal gain. This thesis investigates how morality relates to self-regulation constructs (e.g., risk propensity, impulsivity, fear) and identifies distinct moral and amoral subgroups.
Three aims guided the research: (1) systematically evaluate moral decision-making measures for individual differences research; (2) examine associations between morality, risk propensity, and related traits; and (3) classify subgroups based on these variables. Across one systematic review and two empirical studies (Total N = 942 Australian adults), three key findings emerged. First, there is no unified theory of moral decision-making, and most measures were not designed to assess stable individual differences. Second, within a cooperative morality framework, two pro-cooperative moral factors (individual- and collective-focused) and one anti-cooperative amoral factor were identified, with the amoral factor strongly linked to risk propensity. Third, latent profile analyses consistently revealed two stable subgroups—moral risk-averse and amoral risk-seeking—plus a third group whose characteristics appear more situationally driven.
These findings clarify the interplay between morality and risk, highlight subgroup heterogeneity, and underscore the need to tailor interventions to specific moral profiles. The thesis advances theoretical understanding of moral decision-making and offers practical implications for predicting and influencing moral behaviour across contexts
Evaluating AI Models in Dental Education: Potential for Learning and Clinical Training
No full textArtificial intelligence enhances efficiency and accuracy in clinical dentistry, and deep learning (DL) has achieved significant advancements in the field. However, its application in dental education remains underdeveloped. Dental education involves demanding practical training and assessments. Traditional visual-tactile methods are time-consuming, subjective and prone to inconsistencies.
This thesis investigated the applicability of DL tools for assessing tooth cavity preparation and intraoral radiographic techniques.
Three studies were conducted: (1) intraoral images captured with a commercial intraoral camera were used to assess damage to adjacent teeth during cavity preparations using a DL pipeline with YOLOv5 for detection and DenseNet-169 for classification; (2) convolutional neural network architectures were applied to student-acquired bitewings (BWs) to detect common positioning errors; (3) large language models (LLMs), ChatGPT o1, o3-mini, Gemini 2.0 and Grok 3, were evaluated in providing feedback on radiographic positioning errors using baseline and engineered prompts.
The DL models assessing intraoral images achieved 0.81 accuracy, outperforming clinical educators with excellent performance in detecting damage requiring restoration. The CNN model for identifying positioning errors in BWs achieved high accuracy: 96.3% for cone cutting, 93.4% for interproximal overlap, and 73.2% for incorrect receptor placement. LLMs showed variable but promising performance. Gemini 2.0 and Grok 3 performed best for interproximal overlap with baseline prompts, while prompt-engineered ChatGPT o1 and Gemini 2.0 performed better for incorrect film placement.
DL models demonstrated high performance in detecting adjacent-tooth damage in intraoral images and positioning errors on BWs. Open-source LLMs showed variable performance in analysing BW positioning errors. AI-supported assessment is applicable in training dental procedures involving intraoral and radiographic images
Anatomical and histological comparisons of the epiglottis between brachycephalic, mesocephalic and doliocephalic dogs and puppies
No full textIn Brachycephalic Obstructive Airway Syndrome (BOAS), anatomical crowding of structures lead to interlinked pathophysiology involving increased negative airway pressure, turbulence and irritation. The syndrome presents with variable functional severity and increased risk of airway maintenance, thermoregulation and anaesthesia. The contribution of head morphology, nares, nasopharynx, tongue, soft palate, palatine tonsils, larynx, trachea and lungs in the pathophysiology of the syndrome has been well characterised. However, the epiglottal component of the larynx of brachycephalic dogs has scant anatomical and histological evaluation for its role in BOAS pathophysiology. In comparison to mesocephalic and doliocephalic dogs, it is hypothesised that the epiglottis of dogs affected by BOAS could have gross morphometric variation (dimension, distortion and relative volume), micromorphometric composition variation (epithelium, lamina propria-submucosa, cartilage core, chondral cell/matrix, fibrous and adipose tissue), and histological variation (inflammation, hyperplasia, reactive and degenerative changes). This study represents the first to demonstrate micromorphometric evaluation of six tissue components using camera-imaging software followed by area calculations from canine epiglottises using a manual approach. Results of this anatomical and histological study showed chondral cell/matrix area and chondral cell numbers were significantly greater in distal, middle or proximal sections of the epiglottis in adult brachycephalic dogs compared to mesocephalic dogs. While not statistically significant, adult brachycephalic dogs had relatively larger epiglottal dimensions compared to similar sized mesocephalic dogs, and brachycephalic individuals displayed subtle tissue proportion, reactive and degenerative differences. Findings suggest that the epiglottis has nuanced structural and histological differences in brachycephalic dogs interlinked with the pathophysiology of BOAS
Anchored in sustainability: Transitioning coal ports to circular economy precincts
No full textAs global efforts to decarbonise intensify, export-oriented coal ports increasingly face significant risks associated with declining throughput, asset stranding, and local economic disruption. This thesis addresses such challenges by reconceptualising coal ports as potential sites for circular economy precincts (CEPs) that harness existing infrastructure and industrial linkages to establish novel, low carbon value chains. The study presents an integrated empirical and modelling program focused on the Port of Newcastle (PON), Australia, the world’s largest coal port, as a critical case for evaluating transition pathways, policy options, and the appropriate sequencing of interventions. In doing so, it provides foundational practical guidance to a literature that has thus far offered few comprehensive analyses regarding the diversification of fossil fuel ports in a circular economy direction. The research is oriented around a central question: What are the mechanisms for the successful diversification of coal ports towards the circular economy? This is explored through three Sub-questions: (1) What are potential circular economy ecosystems for coal ports? (2) What key actions are required to transition coal ports towards the circular economy? and (3) What policy measures facilitate a successful transition to the circular economy for coal ports? The research design acknowledges considerable heterogeneity across ports in terms of geography, infrastructure, and regional demand. It structures the inquiry to move from the identification of viable futures to the delineation of transition pathways, and finally to the specification of enabling policy frameworks
STRATEGIC DEVELOPMENT OF BACTERIOPHAGE THERAPEUTICS: TREATMENT OPTIMIZATION AND PHARMACEUTICAL FORMULATION SCIENCE FOR PSEUDOMONAS AERUGINOSA PULMONARY INFECTION
No full textAntimicrobial resistance, causing over 1.27 million deaths annually, severely limits treatment of multidrug-resistant respiratory infections. Pseudomonas aeruginosa poses particular challenges due to biofilm formation, poor antibiotic penetration, and rapid resistance development. Bacteriophage therapy provides targeted antibacterial activity, self-amplification, and biofilm disruption, yet its clinical translation is constrained by resistance emergence, formulation instability, and delivery barriers.
This thesis integrates phage scheduling with solid-state formulation engineering to address these limitations. Sequential treatment, beginning with an LPS-targeting phage followed by a type IV pili–targeting phage, produced sustained suppression and reduced resistance compared with simultaneous dosing. Resistance profiling and AFM-IR analysis revealed receptor-specific adaptations and differential fitness costs that could be strategically exploited.
Formulation studies established stable, inhalable phage powders. High-molecular-weight PVP matrices maintained long-term viability under low humidity by preserving thermal stability, while lactose–leucine systems supported multi-phage stability for up to four years, though aerosol performance declined at elevated temperature. A novel HSA–lactose formulation achieved superior fine particle fractions and delayed recrystallisation while maintaining phage viability.
Together, these findings demonstrate that combining evolutionary dosing strategies with advanced powder engineering provides a robust platform for inhalable bacteriophage therapy. This multidisciplinary approach addresses resistance management, stability, and targeted pulmonary delivery, offering a viable pathway toward clinical application in multidrug-resistant respiratory infections
Software pipelines for processing soil water data and predicting plant available water using approaches from the SoilWaterNow project
No full textThe SoilWaterNow project utilised both Python and R to create software pipelines that process soil moisture data and can be used for predicting plant available water. There is 4 different parts, processing CosmOz surveys, SMAP data assimilation, a water balance model, and a data driven model for predicting agriculture systems. Within each section, there is a working script with an example dataset. This allows users to repeat the analysis with the example data in order to understand the data inputs and formats required to run the analysis on their own study area.
CosmOz survey - Data processing: This pipeline transforms raw neutron count data from cosmic ray probe survey data into soil moisture measurements. The pipeline was used with the associated CosmOz survey data and soil data. The R code is available along with an example dataset.
SMAP Data Assimilation: This pipeline assimilates Soil Moisture Active Passive (SMAP) satellite estimates of soil moisture into an API model for soil moisture reanalysis. Sample data is provided for CosmOz sites and their locations of these points are in "cosmoz_site_info.csv". The Python code for the API model is available. The forcing data used was GPM rainfall and air temperature anomalies. These parameters were calibrated and are listed in "API_parameters.csv".
Water balance model: There are two models available, one that is point-based and used for running on small datasets, e.g. soil moisture probes, and one that is raster-based, which is faster and can be used for obtaining maps of soil moisture. Both models rely on daily evapotranspiration (ET), bucket size, and rainfall as the 3 inputs. These data for these 3 inputs can be accessed publicly: 8-day MODIS evapotranspiration data can be downloaded from the USGS website or directly from google earth engine, rainfall data can be accessed from SILO through the Long Paddock website, and soil data can be accessed from the eSoil website. 5 bucket sizes were used for both models, 0-5 cm, 5-15 cm, 15-30 cm, 30-60 cm, and 60-100 cm. The "ET&rain4WBmodel.r" file contains code that organises daily data for model execution. Alternatively, provided example datasets can be used to run the model. R code is available for both models.
Data-driven approach: This pipeline uses a Gaussian Process regression model/workflow that can be used to predict soil moisture in space and time. This model uses a complex base function that can capture underlying trends in soil data. Each workflow consists of 4 steps: 1. data-preprocessing 2. feature analysis and selection 2. model training, optimisation, evaluation, and selection 4. generating prediction and uncertainty maps. Python code is available for this model and an example dataset is available that is already pre-processed. The "Methods.pdf" file discusses feature selection and model details and the "README.md" file contains in depth information about how this model works and gives example outputs.
The software pipelines are stored in a public GitHub repository (https://github.com/thomasfabishop/soilwaternow) and are also stored on the USYD-RDS at \\shared.sydney.edu.au\research-data\PRJ-soilwaternowarchive. The pipelines are open access under a creative commons license (CC-BY 4.0). Please contact Dr Patrick Filippi ([email protected]) for further information
Defining the complexity of liver transplant: the development of a scoring system to assess recipient risk
No full textIntroduction: Patients undergoing liver transplantation (LT) are routinely assessed for surgical difficulty, but the predictability of these assessments is unreliable and are unquantified. We aimed to identify and quantify risk factors for surgical complexity in LT to inform decision making and assist in peri-operative planning. Methodology: We retrospectively examined all adult liver transplants performed at a single centre between 2012 and 2023. Surgical difficulty was defined by three surrogate measures; operating time, estimated blood loss, and intraoperative complications. Patients were allocated points based on their percentiles for each surrogate and stratified into low (LD), intermediate (ID) and high (HD) difficulty cohorts. Cohorts were compared based on demographic, biochemical, surgical and radiological data.
Univariate and multivariate logistic regression was performed to calculated odds ratios (OR) with p1, OR 1.94, p<0.05), prior open hepatobiliary surgery (OR 3.86, p<0.05), re-transplantation (OR 5.89, p<0.05) and prior spontaneous bacterial peritonitis (OR 3.04, p<0.05) Conclusions: We identified four key variables associated with significant risk for surgical complexity in LT. These risk factors have been incorporated into a score in a pre-operative setting to adequately inform patient of risks and plan perioperative resources accordingly
Supporting Behaviour in Early Childhood Education for Enhanced Teacher and Child Wellbeing through Behaviour Support Strategies
No full textChallenging behaviour among children in Australian Early Childhood Education and Care (ECEC) settings is increasing, contributing to worsening social and emotional outcomes for children, and workforce challenges for educators. This thesis used Bronfenbrenner's Ecological Systems Theory to examine the systems that influence children's behaviour, emphasising the role of educators in the ECEC context (microsystem) and early childhood education frameworks (macrosystem) that underpin ECEC quality in Australia. An analysis of educator preparation found clear mismatches between qualification requirements and the practical skills required to support children's behaviour. This gap leaves many educators feeling unprepared for the behavioural challenges they face routinely. Further, quality assessment processes guided by the National Quality Standard do not provide educators with meaningful feedback or actionable recommendations to enhance their ECEC practices. Behavioural support interventions enhance educator’s understanding of children’s behaviour and provide them with practical strategies to best support behaviour in ECEC settings. A scoping review identified six studies examining behavioural support interventions in Australian ECEC. The interventions universally promoted prosocial behaviours rather than correcting challenging behaviours, showing multiple mechanisms to effectively support behaviour change amongst young children, all, ultimately resulting in improvements in social and emotional functioning. However, these interventions are likely to have immediate but short-term effects. To effect sustainable behaviour change, comprehensive systems-level reform is required. The thesis proposes a three-pronged approach: 1) integrating evidence-based behaviour support content throughout ECEC training, 2) providing hands-on practice opportunities in real settings, 3) transforming quality assessment to provide ongoing professional development and targeted support
Cultural representation in Evolve 1: A Critical Multimodal Study.
No full textThis research investigates the cultural representation in Evolve 1, an English as a Foreign Language (EFL) textbook designed for learners in the Middle East and North Africa (MENA) region. While a plethora of studies have explored culture in EFL textbooks, few have adopted both multimodal semiotic and mixed-method approaches. This study analyzes cultural representation both linguistically and visually, combining quantitative measures with qualitative semiotic analysis to provide a more comprehensive understanding of how culture is represented in Evolve 1. The analysis draws on corpus-based methods for linguistic data and applies van Leeuwen’s (2008) social actor representation frameworks (for both visual and linguistic representation) alongside Martin and Rose’s (2007, 2008) tools for analyzing tenor, field, and genre. The study seeks to answer two central questions: (1) Who is represented in the Evolve 1 textbook? and (2) How are they represented? Findings show that although visual representation appears balanced quantitatively, closer analysis reveals the dominance of certain subgroups within cultural categories. Key disparities emerge in gender roles, family structures, and visual strategies across cultures. Notably, representations of MENA cultures tend to be dynamic and internally diverse, challenging simplistic or monolithic portrayals. This study contributes to ongoing efforts to ensure equitable and culturally sensitive representations in global EFL materials.
References:
van Leeuwen, T. (2008). Discourse and Practice: New Tools for Critical Analysis (1st ed.). Oxford University Press. https://doi.org/10.1093/acprof:oso/9780195323306.001.0001
Martin, J. R., & Rose, D. (2008). Genre relations : mapping culture. Equinox Pub.
Martin, J. R., & Rose, D. (2007). Working with discourse : meaning beyond the clause (2nd ed.). Continuum