Open Access Theses

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Access status: Open Access ,
The inward flow: an inhomogeneous flow asymptotic to the mean curvature flow
(2026) Mangalath, Vishnu
This thesis introduces and studies the inward flow: a contracting inhomogeneous curvature flow of closed immersed hypersurfaces in Euclidean space, with normal speed prescribed by a smooth positive increasing function of the mean curvature and asymptotic to mean curvature flow in the high-curvature regime. The inhomogeneity breaks the usual scaling structure of homogeneous flows and allows behaviours that do not occur for mean curvature flow, including loss of embeddedness without curvature blow-up and the appearance of higher multiplicity tangent flows. We prove a Huisken-Sinestrari-type convexity estimate for the inward flow, valid for arbitrary closed initial hypersurfaces without any constraint on the initial principal curvatures; it gives control over the negative part of the smallest principal curvature in terms of the speed and a constant depending only on the initial data and the dimension, and implies asymptotic weak convexity near singularities. A key complementary result is a pinching estimate comparing the size of the second fundamental form to the flow speed, ensuring that high-curvature regions evolve close to mean curvature flow. This result is also proven for a more general class of flows asymptotic to 1-homogeneous flows. Applying the convexity estimate, we obtain a compactness theorem for blow-up sequences at the first singular time analogous to a result of White: after passing to a subsequence, any blow-up sequence converges locally smoothly on compact subsets of spacetime to a convex ancient solution to mean curvature flow, and in the collapsing case the limit is a static plane of multiplicity two. As the inward flow admits collapsing singularities, we next study the formation of such singularities and obtain quantitative control over the graphical scale near collapsing points, including a decay rate for the graphical scale under a uniqueness hypothesis for tangent flows. In addition, we show that evolving graphs of revolution are noncollapsing via an analysis of the asymptotic height-to-width ratio. Finally, adapting the methods of Evans and Spruck, we construct weak level-set solutions by formulating the evolution as a degenerate elliptic Dirichlet problem inside the region bounded by the initial hypersurface; we prove existence and uniqueness of a Lipschitz continuous viscosity solution and show that the associated level-set evolution is nonfattening.
Access status: Open Access ,
Application of Conical Nanopores in SiO2 Membranes for Molecular Separation and Biosensing
(2026) Afrin, Nahid
Solid-state nanopore membranes have emerged as a powerful platform for controlling ionic transport and enabling molecular sensing at the nanoscale. Among the various fabrication techniques, ion-track etching offers a scalable and versatile approach to produce nanopores ranging from single pores to high-density arrays with well-defined geometry and narrow size distribution. In addition, silicon dioxide (SiO2) nanopore membranes provide a well-known and highly tunable surface chemistry, which is critical for regulating ionic transport, selectivity, and interfacial interactions. However, despite these advantages, the application of SiO2 nanopore membranes remains relatively underexplored, particularly in the context of exploiting surface functionality for practical applications. This thesis investigates the application of conical SiO2 nanopore membranes fabricated via ion-track etching for two distinct areas: charge-based molecular separation and ion current rectification (ICR)-based biosensing. The fabrication process enables precise control over pore geometry and density, while surface functionalization using silane chemistry allows systematic tuning of surface charge properties. In the first part of this work, charge-based molecular transport and separation are systematically investigated using model dye molecules with different charge states. The results clearly demonstrate that electrostatic interactions between the nanopore surface and the analyte molecules dominate the transport behavior, enabling highly selective separation of oppositely charged species. Native SiO2 membranes possess a negative surface charge at neutral pH and preferentially transport cationic molecules. Upon aminosilane functionalization, the surface charge is converted to positive, enabling selective transport of anionic species. This charge-dependent tunability results in strong separation performance, with separation factors reaching up to ∼36 and ∼20 for negatively and positively charged membranes, respectively. The influence of electrolyte concentration on transport is further examined, highlighting the crucial role of electric double layer effects in governing ion selectivity and transport rates. In the second part of this work, antibody-functionalized conical SiO2 nanopores are used as a label-free biosensing platform based on ion current rectification for protein detection. The platform is validated using model biomolecules, including bovine serum albumin (BSA) and heart-type fatty acid-binding protein (H-FABP). Ultrasensitive detection is demonstrated, achieving a limit of detection (LOD) as low as ∼0.4 aM for H-FABP with a dynamic detection range spanning from attomolar to nanomolar concentrations. Exceptional selectivity is observed, with clear discrimination of target proteins in the presence of non-target species at concentrations up to six orders of magnitude higher. The sensor further exhibits excellent reproducibility and reusability through effective surface regeneration, enabling repeated sensing cycles. Overall, this work establishes conical SiO2 nanopore membranes as a robust and versatile platform for selective molecular transport and ultrasensitive biomolecular detection. By systematically correlating pore geometry, surface chemistry, and electrostatic interactions with functional performance, this thesis provides fundamental insights and practical design principles for the development of next-generation nanopore-based separation technologies and diagnostic systems.
Access status: Open Access ,
Effect of climate change on plant-microbe interactions in sub-alpine ecosystems
(2026) Sarker, Salma
Climate change is rapidly altering high-elevation ecosystems, where increases in temperature and shifts in rainfall patterns are expected to strongly influence both plant communities and the soil environments that support them. Microbial communities play a central role in these systems by regulating nutrient cycling, supporting plant growth, and maintaining ecosystem stability. However, how climate stressors especially multiple climate stressors interact to reshape these microbial communities and how such changes influence plant-microbe interactions remain poorly understood in this high-elevation ecosystem. My thesis investigates how warming and drought influence soil- and root-associated microbial communities in Australian sub-alpine grasslands, and how these changes affect plant performance and root colonisation. A set of field-based manipulations and controlled greenhouse experiments were used to examine microbial diversity, community structure, functional potential and plant-microbe interactions. Across the thesis, combined warming and drought consistently imposed the strongest impacts on both soil- and root-associated microbial communities and plant performance, indicating that interacting climatic stressors amplify ecological disruption in sub-alpine ecosystems. Among individual stressors, warming generally exerted broader and more consistent negative effects than drought alone, particularly for fungal and arbuscular mycorrhizal fungal (AMF) communities. In contrast, drought effects were often more variable and appeared especially important for bacterial community restructuring. Moreover, prolonged climatic stress generally reduced symbiotic fungal groups while favouring saprotrophic, opportunistic, and stress-associated taxa across both soil- and root-associated communities. These shifts suggest a potential weakening of beneficial plant-microbe associations under climatic stress, which may increase plant vulnerability to environmental stress and disease pressure under future climate change. Collectively, climate stress led to consistent but group-specific changes in soil microbial communities, with combined warming and drought producing the strongest effects. These changes extended beyond reductions in diversity to altered microbial interactions and functional potential, indicating that climate stress reshapes not only the composition of microbial communities but also their ecological roles. However, plant responses to warming and drought in control growth chambers were highly species-dependent and links between root fungal community changes and plant performance were often weak, suggesting that above and belowground responses do not always change in parallel. Finally, a field-based transplant experiment demonstrated that climate stress and host species reshapes root-associated fungal communities during plant establishment by altering which taxa successfully colonise plant roots. Overall, this thesis demonstrates that climate change reshapes soil- and root- microbiomes in group-specific ways, influencing not only microbial diversity and function but also the assembly of root-associated communities. These findings provide new insights into ecosystem responses to climate change and have important implications for predicting ecosystem resilience and informing restoration strategies in sub-alpine systems.
Access status: Open Access ,
Applied Epidemiology in Southeast Queensland
(2026) Miller, Maggie
For my master of Applied Epidemiology, I have been highly fortunate to be placed at the Metro North Public Health Unit (MNPHU) in Brisbane. During my placement, I have gained exposure to various areas of field epidemiology. In May of 2024, our unit handled the public health response to an outbreak of mpox that occurred in southeast QLD, which eventually required a coordinated response from various Queensland Health bodies. This presented itself as an excellent opportunity to meet my outbreak competency. Of note, a cohort study design was able to be carried out, and I presented the results at the Communicable Diseases and Immunisation Conference in June 2025. Additionally, a manuscript form was published in the Communicable Diseases Intelligence journal. My epidemiological and data analysis competencies have been met under one project, which involved a randomised control trial to determine the effects of a newly developed digital tool on the impact of respiratory outbreak management within residential aged care facilities in the Metro North Hospital and Health Services region. This project involved both qualitative and quantitative data analysis components and has high operational value within the Metro North Public Health Unit. To meet my final competency, I conducted an evaluation of the enhanced surveillance of cryptosporidiosis within the Metro North Hospital and Health Services region, a system established during the summer of 2023 to 2024 in response to an unusually high number of cases in the region. Findings from this evaluation have been able to inform future iterations of this surveillance system, in anticipation of its next use.
Access status: Open Access ,
Psi controls neural stem cell fate in the developing Drosophila brain
(2026) Kim, Nanhee
Oligodendroglioma (ODG) is a diffuse adult glioma molecularly defined by the IDH1/2 mutation and 1p/19q codeletion. Although slow growing, ODG recurs and remains incurable. Genetically, FUBP1 ranks in the top 23% of predicted ODG driver mutations with predicted loss-of-function, suggesting anti-proliferative functions in the brain. Counterintuitively, given the predicted tumour suppressor function in the brain, FUBP1, was initially discovered as a transcriptional activator of the MYC oncogene. Consistent with conserved pro-proliferative functions, the Drosophila FUBP1 ortholog (Psi) interacts with the transcriptional Mediator complex, to integrate developmental signals, and drive a network of genes (including Myc) to promote proliferative growth in the wing epithelium. This observation does not, however, provide a rationale for FUBP1's tumour suppressor function in the brain. Here we demonstrate Psi functions as a tumour suppressor in the Drosophila brain; Psi knockdown (KD) drives NSC lineage expansion, characterised by accumulation of specific progenitor populations. Psi's direct binding targets in the NSC lineage, identified using Targeted DamID (TaDa), were intersected with genes differentially expressed in Psi KD NSCs to reveal Psi directly regulates expression of factors governing NSC renewal and differentiation. Of note, the transcriptional regulator implicated in stem cell fate control, HmgZ (HMG) and Sox21a (SoxB) are normally repressed by Psi in the NSC lineage. HmgZ co-KD partially suppressed the progenitor expansion phenotype associated with Psi KD, whereas Sox21a co-KD did not significantly suppress this phenotype. Future studies investigating potential roles for the HmgZ orthologue(s) in FUBP1-mutant oligodendroglioma will be of much interest.
Access status: Open Access ,
Constructing the Artificial Intelligence research field: studies of infrastructures and practices
(2026) Berman, Glen
Artificial Intelligence (AI) has become a central figure in contemporary science and policy discourse, yet as a research endeavour it resists neat categorisation within disciplinary or institutional boundaries. Significant research funding and activity is now organised through the figure of AI. And, the computing techniques and technologies which this research activity is directed towards have rapidly moved from research settings into the wider world, often with deleterious effects on individuals and communities. In response, this thesis by compilation examines AI as a research field, and as a site for responsible intervention within the science system. First, the thesis explores how AI is constructed as a research field. Reflecting the contested and ill-defined boundaries of AI research, this exploration is undertaken through three complementary studies: of a computing platform used in AI research; of bibliometric and authorship patterns across AI publications and patents; and of AI-branded university-based research institutes. Together, these studies demonstrate the influence of underlying infrastructures of the science system on the development of the AI research field and help develop the concepts of generalisability (research outputs that can be applied across contexts, disciplines, or sectors), hybridity (research practices that enact the logics of multiple, usually distinct, sectors), and high-dimensionality (research fields that position themselves as mediators between many different sectors and social groupings) to characterise the AI research field. Second, the thesis considers how responsibility- and ethics-focused interventions (RAI interventions) can be designed within the AI research field. Researchers, policymakers, and practitioners have proposed a host of RAI interventions, from high-level ethical principles to granular checklists, to processes for ensuring AI impacts are considered before AI research is published or AI systems are deployed. The thesis explores these through a study of how RAI interventions evidence their effectiveness, highlighting the need to account for infrastructural dynamics in intervention design. A further case study, focused on AI evaluation in the cultural sector, develops an analytical framework for the design of RAI interventions that attend both to field-level dynamics and local contexts. The thesis contributes to sociological studies of science and the growing Responsible AI literature. Empirically, the thesis provides a transnational description of the AI research field. Theoretically, the thesis builds on existing discourse related to interstitial or hybrid fields to develop hybridity as an analytical tool for studying emerging research fields and high-dimensionality as a characteristic of some interstitial fields. From an applied perspective, the thesis also contributes to Responsible AI efforts by demonstrating the importance of attending to field-level dynamics when designing responsibility- or ethics- focused interventions.
Access status: Open Access ,
Audio-Visual Scene Reconstruction of Geometry and Acoustic Fields
Gao, Huiyu
Reconstructing 3D scenes from sensor observations is an important problem in computer vision and embodied AI, with broad applications in augmented and virtual reality (AR/VR), robotics, telepresence, and immersive media. As real-world environments are spatially complex and rich in audio-visual information, faithful scene reconstruction requires modeling not only the geometric structure of the scene but also its visual and acoustic representations. In this thesis, we investigate audio-visual scene reconstruction, aiming to recover 3D scene geometry and acoustic fields from multi-view audio-visual recordings. While recent deep learning approaches have achieved promising results, critical challenges remain. At the scene scale, light propagates primarily along line-of-sight paths, leading to hard, near-binary visual occlusions across multiple views, whereas sound, with its longer wavelengths and more extensive reflective interactions, exhibits softer acoustic occlusions and pronounced multi-path propagation. We therefore focus on three key challenges in this area: (1) visual occlusions, (2) acoustic occlusions, (3) multi-path sound propagation, and present a series of methods that advance this line of research in audio-visual scene reconstruction. First, we propose a visibility-aware online reconstruction framework that reconstructs 3D scene geometry from monocular video. To address visual occlusions, we explicitly infer view-dependent voxel visibility and predict aggregation weights for multi-view feature fusion. We also develop a local sparsification strategy to preserve small structures and refine geometry in a coarse-to-fine manner with residual learning, yielding more complete surface reconstructions with finer details. Second, we introduce a scene occlusion-aware neural acoustic field that models the occlusion effects of scene geometry in sound propagation to enhance acoustic field learning. We derive a global acoustic prior via distance-aware parametric propagation and adapt it with room geometry recovered from visual frames to extract local acoustic features. With a direction-aware attention mechanism, our approach generates spatial audio with improved audio quality and binaural perception. Third, we present a physics-guided novel-view acoustic synthesis framework that further incorporates multi-path sound propagation modeling into the learning-based networks. By tracing geometry-dependent early reflections based on reconstructed scene layouts and estimating statistical late reverberation using predicted scene acoustic characteristics, our framework extracts physically meaningful acoustic features and synthesizes more accurate and realistic novel-view spatial audio. In summary, this thesis presents several novel ideas that advance the state of the art in audio-visual scene reconstruction, achieving superior performance in reconstructing 3D scene geometry and acoustic fields, thereby enabling more immersive AR/VR experiences and reliable perception for embodied systems.
Access status: Open Access ,
Harnessing Artificial Intelligence to Decode and Predict RNA-Mediated Gene Regulation
(2026) Ding, Ke
RNA-mediated gene regulation spans post-transcriptional mechanisms in which non-coding RNAs (e.g., microRNAs) silence targets, RNA-binding proteins control splicing, stability, localization, and translation, RNA secondary structures shape processing and interactions, and chemical modifications such as methylation and editing modulate RNA function and target recognition. Together, these factors determine translation efficiency and influence development, cancer, neurodegeneration, and emerging RNA-based therapeutics. The vast sequence space and combinatorial complexity outstrip experimental throughput, motivating deep learning approaches to model sequence-function relationships. This thesis advances RNA biology and deep learning through four major contributions that address long-range dependency modeling, multimodal integration, interpretability, and computational efficiency. First, DeepMirtron, a multimodal bidirectional LSTM model, integrates nucleotide sequence and secondary structure to identify non-canonical microRNAs, mirtrons, with 95.4% accuracy on canonical versus mirtron classification and 99% accuracy on an independent positive-only set of 286 mirtrons, outperforming prior CNN-based methods like CNN-concat and CNN-LSTM, and discovering 3,642 novel high-confidence candidates for experimental validation through genome-wide screening. Second, CRMnet, a transformer-encoded U-Net with squeeze-and-excitation and skip connections, predicts gene expression from yeast promoters with Pearson r = 0.971 on native and 0.987 on random sequences, surpassing existing models; mixed-precision distributed training shortens runtime by over 30-fold. Third, NucEL applies ELECTRA-style pretraining to genomic sequences, using single-nucleotide tokenization and hybrid local-global attention in a 93M-parameter model. It achieves state-of-the-art performance on regulatory benchmarks with 27 times fewer parameters than 2.5 B-parameter MLM models such as Nucleotide Transformer. We advance foundation models through efficient replaced token detection (RTD) rather than standard masked language modeling, replacing sparse 15% supervision with dense generator-discriminator feedback that provides roughly 7-fold greater supervisory signal, enabling compact yet powerful representations. Fourth, RegLLM continues pretraining from NucEL on transcriptomes, demonstrating efficient DNA-to-RNA transfer learning. It achieves state-of-the-art or competitive results across eight RNA-centric task domains, including non-coding RNA classification, RNA-RNA interaction prediction, m6A/m5C modification detection, mRNA stability, and translation efficiency using only raw sequences while reducing total training time from months to days. Interpretability analyses, saliency maps, attention visualization, and motif recovery confirm that learned representations align with biological priors such as regulatory motifs, thermodynamic stability, and position-specific signatures. Our findings establish key principles: hybrid architectures combining complementary components outperform single-paradigm approaches; multimodal integration yields more robust predictions; transfer learning offers substantial efficiency advantages; and interpretability mechanisms are essential for trust and actionable insights. By integrating biological knowledge with deep learning, this work advances our ability to decode genomic regulatory logic, establishing methodological foundations for continued progress in computational gene regulation understanding.
Access status: Open Access ,
Learning User and Item Representations from Heterogeneous Feedback for Accurate and Explainable Recommendation
(2026) Liu, Lei
Representation learning is central to recommender systems because the information encoded in user and item representations directly affects how effectively user preferences and item characteristics can be modelled. Recommender systems increasingly learn from heterogeneous feedback, including behavioural interactions, numerical ratings, and textual reviews. These feedback sources provide complementary information, but they also raise an important representation learning problem: the same user or item may need to be represented differently depending on the type of feedback being modelled or the particular interaction for which a prediction is made. This thesis investigated this problem from the perspective of accurate and aspect-level explainable recommendation. The thesis examined two related research questions. The first concerned how implicit and explicit feedback could be integrated while preserving their different meanings and allowing information to be exchanged between their respective user and item representations. The second concerned how user and item representations could depend on their current interaction counterpart in aspect-level recommendation. To investigate these questions, the thesis adopted a polymorphic representation learning perspective, under which the same entity can have different representations across feedback types or interaction counterparts. For the first research question, we developed Interdependent Embedding Learning (IEL), a GCN-based framework that maintained separate user and item representations for implicit and explicit feedback. IEL used intra-graph and selected inter-graph message passing to allow these feedback-specific representations to exchange collaborative information and was evaluated for both item ranking and rating prediction. For the second research question, we developed Dynamic Representation Learning (DRL), which combined general collaborative representations learned from ratings with aspect-sentiment information extracted from textual reviews for the current interaction. DRL constructed an item-dependent user representation and a user-dependent item representation for rating and positive-aspect prediction. A prompt-based large language model (LLM) procedure was used to transform reviews into structured aspect-sentiment information for this study. Offline experiments on public Amazon product-review datasets provided empirical support for both approaches. IEL improved recommendation performance relative to the compared unified recommendation baselines, with the strongest and most consistent improvements observed for item ranking. DRL achieved lower rating-prediction MSE than the compared baselines across all three evaluated datasets, with an average reduction of 5.1\% relative to the strongest compared baseline. It also improved Hit@1 for positive-aspect prediction by an average of 4.8\%. The latter evaluation measured the model's ability to predict aspects subsequently appearing in held-out reviews and therefore served as an operational measure of aspect-level explanation. The main contribution of this thesis is a unified representation-learning perspective that connects feedback-dependent and interaction-dependent representations. The IEL and DRL studies demonstrate how heterogeneous feedback can be preserved and integrated without requiring a single invariant representation of each user or item. In addition, the thesis constructed three derived Amazon review datasets containing LLM-extracted aspect-sentiment information for aspect-level recommendation research. Overall, the findings suggest that allowing user and item representations to vary according to the feedback type and the interaction being modelled provides a useful direction for learning from heterogeneous feedback in accurate and explainable recommender systems.
Access status: Open Access ,
Political Parties and Election Campaign: Strategic Dimensions of Political Communication in India
(2026) Sarma, Pratyush
This thesis examines how Indian political parties adapt electoral campaign strategies across the world's largest and most diverse democracy. While there is extensive literature on Indian politics focused on voter behaviour, what often goes unnoticed is that political campaigns are contingent on parties. What happens inside a party, how it is organised, how it listens, and how it adapts to different regional contexts are some of the important questions which shape election outcomes. To address this research gap, my thesis shifts focus to the 'supply side' of campaigns, examining how organisational structures shape the extent to which parties can adapt their campaigns across national, state and constituency levels. Adaptation is observed through three dominant strategies found in electoral campaigns around the world which are personalisation (projecting leaders as the face of the party), programmatic appeals (policy and development promises linked to party ideology), and performance-based strategy (emphasising governmental achievements). The theoretical framework draws on debates about party organisation and shows how cadre, mass, catch-all and cartel models apply to the Indian context. The theoretical claim is that party organisation conditions how parties respond to regional and local variation in voter attitudes, and it does so by determining whether constituency-level knowledge informs the campaign narrative or follows it. The study examines the 2024 general election campaigns in India, focusing on the two major parties, Bharatiya Janata Party (BJP) and Indian National Congress (INC). To capture how these parties' campaign at different levels, the study analyses both national and regional social media (specifically Facebook accounts), with a particular focus on the northeastern state of Assam. Assam was selected for its political diversity, and three distinctive constituencies, Dhubri, Nagaon, and Guwahati were studied to provide a nuanced perspective on how national parties adapt their strategies locally. The study uses a mixed-method approach combining speech analysis, interviews with party professionals and volunteers, and social media data. Findings reveal that national parties use their organisational structures to reach grassroots political support, though they do so in different ways. The BJP employs a highly centralised system that extends down to the voter list, consistently projecting PM Modi's leadership while drawing on local successes and leadership at regional and constituency levels to reinforce that narrative. It further combines organisational discipline with a logic of coalition and co-optation, supporting regional allies as required even across deep ideological divides. In contrast, the INC adopts a quasi-decentralised structure, granting autonomy to state and local units to prioritise community-specific issues, while focusing on criticising BJP national policies at the broader level. The analysis also considers regional parties like All-India United Democratic Front (AIUDF) and Asom Gana Parishad (AGP), which further illustrate organisational diversity. AIUDF relies on cadre-based mobilisation, while the AGP's strategy centres on alliances, showing cartel-like features. The thesis demonstrates that Indian parties are not monolithic as their success depends on their ability to synthesise inherited traditions, local expertise, and emergent communication platforms to manage the complexity of modern Indian campaigns. Organisational structure determines where local knowledge enters the campaign, and therefore how far a national strategy can be reshaped by local conditions, whether responding to demographic change, forging alliances, or leveraging social media for targeted outreach. Through this lens, the thesis provides fresh insight into the crucial but often overlooked role of party organisation in contemporary Indian electoral politics.
Access status: Open Access ,
From States to Measurements: Information-Theoretic Measures for Quantum Characterisation
(2026) Das, Aritra
Quantum states and measurements are two central physical objects in the theory of quantum mechanics. The preparation, control and measurement of quantum states lies at the heart of modern quantum information processing protocols ranging from secure communication to quantum computation and precision sensing. And yet, the reliable operation of these advanced protocols ultimately rests on a far more essential prerequisite - our ability to calibrate, certify and benchmark the quantum states we prepare and the quantum measurements we perform. Quantum information theory provides a natural framework for these tasks, meaningfully connecting the resources we expend for characterisation with the accuracy and precision we can expect in return. While decades of advances in quantum information have refined our understanding of quantum characterisation and sharpened our practical ability to calibrate with enhanced precision, important questions about the fundamental limits of quantum characterisation remain unanswered. Although incorporating entanglement at the measurement stage is known to enhance the estimation of unknown quantum states, the extent of this improvement remains poorly understood. This leaves open a fundamental question on the utility of complex entangling measurement strategies, impeding progress towards bridging the significant gap between practically achievable precision and the ultimate theoretical quantum limit. Complementary to quantum state estimation, which is relatively well-established in theory and practice, the characterisation of quantum measurements lacks a rigorous information-theoretic foundation, leading to a dearth of principled benchmarks and provably optimal strategies despite growing experimental interest. This thesis develops and applies information-theoretic tools to answer questions in quantum characterisation, with an eye to enabling practical improvements beyond current techniques in the field. First, we introduce a computable measure of entanglement enhancement for quantum state estimation and study its variation across general multi-parameter estimation problems for higher-dimensional quantum states. We show that the entanglement enhancement is maximised for full qudit state tomography but grows only linearly with system dimension even when allowing an asymptotically large number of entangling operations. Our proposed tight upper bound to entanglement enhancement therefore constitutes a strong limitation on the utility of such entangling measurements. Next, we formulate the dual problem of quantum detector estimation, developing a comprehensive framework for maximally precise calibration centred around a newly introduced quantity - the detector quantum Fisher information. This information-theoretic measure stipulates the ultimate precision attainable for measurement calibration and identifies the optimal input states that achieve this precision. Further, our framework enables the first provably optimal detector estimation experiment and reveals the scope for entanglement-based enhancements, thereby placing measurement characterisation on equal footing with state characterisation. Considered together, these results suggest two contrasting conclusions about quantum characterisation. On the one hand, they show that for quantum state estimation, increasingly powerful entangling measurements offer only diminishing returns at the ultimate precision limit. On the other hand, they highlight practical quantum advantages available for detector estimation by providing a framework that can improve calibration performance and guide future experimental design. More broadly, these results complete and advance the triad of state, process, and detector characterisation, positioning quantum information measures as not merely abstract bounds, but practical guides for deciding when complex quantum resources are genuinely worth deploying and where near-term quantum advantages are most likely to be realised.
Access status: Open Access ,
Medical Volumetric Reconstruction with Neural Fields
(2026) Zha, Ruyi
Reconstructing volumetric models from multi-view images is a fundamental task in computer vision and graphics, supporting a wide range of applications in medical imaging, robotics, and extended reality. Historically, volumetric reconstruction has progressed from tomographic reconstruction, which aims to recover physically meaningful volumes for non-intrusive inspection, to inverse rendering, which seeks to reproduce volumetric scenes for photorealistic novel-view synthesis. Traditional voxel-based approaches often yield poor reconstruction quality in challenging settings such as sparse views and dynamic scenes. Recent neural field-based methods have revolutionized inverse rendering through expressive field models and differentiable rendering techniques. However, their potential for tomographic reconstruction remains largely unexplored, and substantial challenges persist when deploying inverse rendering in real-world settings. This thesis explores neural field-based volumetric reconstruction, with a particular emphasis on tomographic reconstruction and demanding medical applications. The primary contributions of this thesis are organised into three main directions. First, we establish neural field-based tomographic reconstruction as a novel paradigm. In particular, we introduce two foundational frameworks: an implicit field approach, NAF, and an explicit primitive-based approach, R$^2$-Gaussian. While the two methods pursue different design objectives in terms of reconstruction fidelity and computational efficiency, both achieve superior reconstruction quality and demonstrate greater extensibility compared with traditional techniques. Second, we extend neural field methods beyond controlled experimental settings to real-world medical applications. On the one hand, we adapt R$^2$-Gaussian to digital subtraction angiography, addressing dynamic tomography for blood vessel reconstruction. On the other hand, we explore surgical robotics through inverse rendering by proposing a novel method for reconstructing deformable tissues from highly occluded and motion-constrained endoscopic videos. Finally, we enhance neural field reconstruction by leveraging large-scale external datasets. This includes a large feedforward model that produces high-fidelity neural fields under extremely sparse-view conditions, as well as a diffusion model-based generative prior that regularizes neural field optimization. In summary, this thesis advances medical volumetric reconstruction, particularly tomographic reconstruction, by establishing neural fields as a powerful alternative to traditional voxel-based methods. We not only build the theoretical and mathematical foundations of neural field-based reconstruction, but also develop practical solutions that enhance these methods and extend them to real-world applications. Looking ahead, we hope that the ideas and techniques introduced in this thesis will inspire future research in volumetric reconstruction and ultimately contribute to making medical imaging more reliable, efficient, and accessible for improving human healthcare.
Access status: Open Access ,
'A continent that Australians must be proud to advertise' Nature, Tourism and the National Image, 1905-1988
(2026) Woodward, Josh
Since Federation, national tourism advertising campaigns have carried messages about Australia, its scenery and its people around the world. Tourism advertising has also served an important function as a bellwether for how the world perceives the nation from the outside. A unifying condition of twentieth-century Australian tourism advertising programs is their dependence on environmental imagery. Australia's crystal-clear waters, abundant sunshine, temperate climates, and unique and exotic flora and fauna are all recurrent and familiar tropes in the country's marketable image. Nevertheless, historians have paid scant attention to how advertising freighted Australia's natural and environmental symbols with the anxieties, values and attitudes of the wider settler nation. The question of how tourist advertising enrolled Australia's environmental and natural imagery in twentieth-century nation building, and how advertising images shaped and responded to contemporary discourses about the nation and identity of its people, remains unanswered. In undertaking a close analysis of the archives and sales materials of the nation's top national tourism promoters, this thesis fills a heretofore unexamined gap in Australian environmental and tourism history. I argue throughout that an environmental dimension lays at the heart of the Australian tourist experience. Environmental imagery persisted across the century, even as values, tastes and opinions changed. Each chapter offers a case study of the nation's overall image, as well as of Sydney, Canberra, and the Great Barrier Reef. In each campaign, organisations and their administrators, particularly the Australian National Travel Association and the Australian Tourist Commission, recruited nature, whether of a specific destination or the continent as a whole, to enliven the wider image of the nation. Each organisation has left historians a vast record of sales ephemera (posters, brochures and television campaigns) as well as the internal correspondence, reports and memoranda that explain the decision-making driving advertising creation. But these organisations' commodification of nature went beyond the obvious commercial imperative to grow tourism as a profitable industry. Instead, the story of how promoters positioned Australian symbols of nature, scenic landscapes, and environmental attributes, like the conduciveness of the temperate climate for good health and mortality, belies a deeper twentieth-century narrative about how the nation imagined itself, and how it sought to be understood from the outside. A careful analysis of these sources reveals a higher quality to tourism advertising than just driving up the bottom line of dollars and migrants for a productive economy. It is in drawing out what precisely this higher quality was that the original contribution of this work lies. The circulation of national advertising materials, in massive numbers at home and overseas, contains real insights into an intergenerational conversation between promoters and their likely audience about the nation and what its people aspired for it. Partly an effort to foster civic pride through the celebration of modernity and progress, and partly an effort to remediate colonial and racial anxieties and project a distinctive Australian identity, tourism advertising sought to legitimise the nation in the eyes of the world, but more importantly, in the eyes of its own people. Current affairs and shifting cultural appetites and opinions affected the psychology of national tourist advertising. But as this thesis systematically demonstrates, the proclivity of advertisers to appeal to a human desire to spend time in nature remained ever constant.
Access status: Open Access ,
Exploring the epidemiology of commercial tobacco, e-cigarettes and nicotine in Australia
(2026) Pousini-Hilton, Dean
This thesis presents three major research projects and one study proposal to satisfy all competencies of the Master of Philosophy in Applied Epidemiology public health program. My placement was within Yardhura Walani, The National Centre for Aboriginal and Torres Strait Islander Wellbeing Research at the Australian National University. I conducted all projects within the Tobacco Free Program in Yardhura Walani with a primary focus on commercial tobacco and nicotine access in Australia. Each of the projects that form this thesis were grounded in a relational approach to understanding and improving commercial tobacco and nicotine-related health outcomes for Aboriginal and Torres Strait Islander peoples and all peoples. Further, this thesis aims to shift the public health lens from decades of deficit-based narratives to instead focus on the commercial tobacco and nicotine industry itself as a vector of death and disease. The major epidemiological project utilised naturalistic observational methods to document smoking product retail outlet features including product availability, display, pricing strategy, and promotion in Queensland Australia. The next project continued this with a second wave of data collection to determine the impact or change in retail features after the introduction of a statewide smoking product licensing scheme. The third project outlined a study proposal to develop a commercial tobacco and nicotine eradication framework with and for the Torres Strait Islands. This was developed as a protocol to model co-design and self-determination principles in partnership with key stakeholders of the Torres Strait Islander community. The fourth project investigated an acute outbreak of gastroenteritis in Canberra, Australian Capital Territory. In my journey through the MAE program, I have learned, developed and applied epidemiological methodologies and critical thinking to complete a public health investigation from end-to-end. I have conducted independent data collection in the field, several forms of statistical analyses, and had the opportunity to disseminate findings to stakeholders. Collectively, this thesis demonstrates how applied epidemiology can be mobilised to address commercial tobacco and nicotine harms through integrated surveillance, evaluation, and policy-relevant analysis. Across retail monitoring, policy evaluation, outbreak investigation, and the co-design of an eradication framework, the thesis shows how epidemiological methods operate as connected tools for tobacco and nicotine industry accountability, health protection, and health equity, rather than as isolated technical exercises.
Access status: Open Access ,
Culture in Australian Mental Health Podcasts
(2025) Cupit, Jessica
In recent years, mental health and mental health services have become a topic of increasing interest not only for governments and policymakers, but also for researchers. In the wake of COVID-19, online discourses of mental health in particular have garnered interest as a topic of research. According to the Australian Bureau of Statistics, over a fifth of Australians experienced a mental health disorder in 2020-2022, but less than half of those individuals saw a mental health professional (Australian Bureau of Statistics, 2020). Research on online mental health discourses is therefore critical to our understanding of how people are experiencing mental health and seeking non-professional support for mental health issues. Much of the current research which has been performed has been carried out on written discussion fora (such as r/Depression, (Low et al., 2020 & Sik et al., 2023) or organisationally-sponsored blogs (Jamet & Coupe , 2023)). Spoken data, such as podcasts, have generally not been studied. Although it is accepted in linguistics that culture is a critical component of how meaning and ideas about emotion are constructed through language (Wierzbicka, 1999; Ye, 2022a), very little of the current research has considered the question of how culture, through language, might shape the discourses being studied. The few studies which have considered culture have lacked an appropriate framework through which to examine these culturally specific influences. This study begins to address that lack, examining how embedded cultural meanings are produced and used in podcast mental health discourses in Anglo-Australian linguaculture and, in turn, how culture informs our conceptualisation of mental health. It does so through an appropriately culturally-focussed framework, Semantically-enhanced Discourse Studies (Bromhead, 2024; Ye, 2022a). This approach offers a uniquely ethnopragmatic lens, combining a focus on culture in communication with the deep analytical power and emphasis on rendering embedded concepts transparent of the Natural Semantic Metalanguage approach (Goddard, 2018). A corpus of c. 23 hours of spoken data has been collected from popular podcasts representative of contemporary, non-expert Australian discourses and analysed in order to answer the aim of the study. From this corpus, three cultural keywords have been identified for analysis: struggle with, stressed, and validation. Each of these keywords has been carefully explicated, and the proposed explications tested against each instance of the keyword in the corpus. Through these explications, not only the cultural attunement of each keyword, but also how culture shapes conceptualisations in the broader discourse space are revealed through the culturally-attuned, embedded meanings within each keyword. It is found that culture shapes how mental health is conceptualised in lay discourses. Several key cultural scripts in the discourse are identified, and it is found that these scripts combine to form a model for ‘what to do’, accessible to participants in online, lay discourses of mental health. This suggests that in order to understand experiences of mental health, it must first be understood how culture constructs ideas about mental health in discourse.
Access status: Open Access ,
Algebraic Envelopes of Commutative Rings over Fields of Characteristic Zero
(2026) Allen, Lucas
In the 1996 monograph Cogroups and Corings in Categories of Associative Rings by George Bergman and Adam Hausknecht, a complete descrpition of the initial affine ring scheme, equipped with a map from the ring scheme version of the integers, is given. This thesis builds upon this work. In particular, for the category of affine schemes over a field of characteristic zero, we give a description of the initial object, equipped with a ring scheme map from the ring scheme version of an arbitrary commutative ring. Such an initial object is called an algebraic envelope. This thesis also elucidates the background theory given in Bergman and Hausknecht's monograph and expands on it to affine schemes over Dedekind domains. It concludes with several examples of algebraic envelopes.
Access status: Open Access ,
Reimagining How We Work: An Investigation of Flexible Work from Concept to Career
(2026) Brett, Kathryn
Flexible work evolved from a simple scheduling accommodation designed to support workforce participation into a complex systems phenomenon. Tensions across the individual and organisational levels complicate the implementation of flexible work, resulting in cross-level effects that lead to inconsistent outcomes. Flexible work has the potential to mutually benefit individuals and organisations, but the diversity of personal preferences and circumstances creates difficulties for both designing work practices and managing them. This thesis examines the flexible work phenomenon from three vantage points. Combined, the conceptual, organisational and individual-level studies answer the research question: what is the nature and significance of flexible work in contemporary employment and how do organisations and individuals leverage flexibility? Study 1 explores what flexible work is, what drives it, and how it influences the future of work through a systematic literature review of 212 articles from 2007-18. The research reveals two paradigmatic shifts: (1) a pivot from viewing flexible work through organisational power dynamics toward a mutually beneficial perspective; and (2) the emergence of a neo-ideal worker characterised by outcome-based performance rather than bound by traditional office constraints. While initially driven by employees, particularly women, wanting to juggle competing priorities, flexible work has evolved into a practice with significant potential to benefit both employees and organisations. Study 2 investigates how organisations signal flexible work information via their corporate websites, using 2018-19 website data from 50 companies (encompassing 219 entities) across Australia, Canada, UK, US, Denmark, Finland, Norway, and Sweden. The study introduces flexible work branding and identifies three distinct signalling approaches (strategic, routinised and absent). The findings demonstrate that organisations engaged in strategic flexible work branding position flexibility as mutually beneficial, citing a range of organisational benefits such as retention and increased diversity. Regional variations were evident between Anglo and Nordic countries, the former framing flexible work as a competitive differentiator with the latter framing it as a normative work practice necessary for sustainable careers. Study 3 investigates how employees navigate flexible work on their journey to leadership - how it influences career progression, how employees benefit from it and how organisational support affects outcomes. Drawing on interviews with 56 senior leaders, conducted in 2023-24, the study addresses the complexity between flexible work and career progression, explaining why flexible work can both hinder progression due to flexibility stigma and the ideal worker norm, yet support sustainable career progression over time. Through iterative analysis the study reveals that temporal management (how employees allocate and redistribute their time) affects the implementation of flexible work, and that supportive managers and organisational cultures are a key factor in successfully recalibrating work time. This thesis reframes flexible work as a mutually beneficial, strategic practice rather than an accommodation. Managed well, it supports sustainable careers instead of eroding them. It is not just whether employees work flexibly but how they allocate their time that shapes both the trajectory of individual careers and life beyond the workplace. This temporal, dynamic view of flexible work is a central contribution that future research can build on to investigate how organisations can pursue their goals while enhancing rather than monopolising employees' lives.
Access status: Open Access ,
The association between Work-Family Conflict (WFC) and mental health in Australian context
(2026) Wang, Tianying
Background In light of significant changes in employment structures and family dynamics in Australia, work-family conflict (WFC) has become recognised as a major psychosocial stressor. In recent decades, the Australian labour market has seen growing work demands, an increasing number of dual-income families, and extensive underemployment and instability in employment. While previous studies have consistently linked WFC to general psychological distress, much of this work has been concentrated within the occupational health or parenting literature, often relying on self-reported distress measures. There remains limited epidemiological research examining the associations between WFC and clinically diagnosed mental disorders such as Major Depressive Disorder (MDD) and Generalized Anxiety Disorder (GAD), as well as suicidal ideation. Purpose This thesis investigates the associations between WFC and a range of mental health indicators among Australian adults, with a focus on the most commonly experienced clinically diagnosable disorders. Moving beyond prior research that has largely focused solely on parent populations (mostly mothers) and specific workplaces/occupations, this thesis adopts a broader epidemiological perspective to examine how varying levels of WFC contribute to the development of serious and commonly experienced mental health conditions, specifically MDD, GAD, and suicidal ideation. Methods The study draws on data from the Personality and Total Health (PATH) Through Life project, an ongoing, community-based longitudinal study aimed at evaluating life-course patterns. Specifically, Wave 5 data from the '20s' cohort were utilized in this thesis. Measures of WFC and CIDI disorder diagnosis were introduced in Wave 5 and this cohort is particularly relevant given their exposure to midlife stressors involving career progression, parenting responsibilities, and caregiving for ageing relatives. The final analytical sample utilised throughout all studies in this thesis included 1,312 employed individuals. Results This thesis found that higher levels of WFC are linked to poorer mental health outcomes for mid-life working individuals, including greater symptom severity of depression and anxiety. WFC emerged as an important and independent risk factor for common mental health disorders and suicidal ideation. Specifically, individuals experiencing higher WFC reported significantly greater depressive symptom severity and greater anxiety symptoms (Study 1). Further, participants with high levels of WFC had significantly increased odds of meeting criteria for MDD when evaluated using the PHQ-9 with a clinically validated cut-off point of 10 (Study 2). For GAD, high WFC was associated with increased odds of both PHQ-defined clinical anxiety and DSM-IV-defined GAD (Study 3). In addition, individuals with high WFC had significantly greater odds of reporting active suicidal ideation (Study 4). Conclusion This thesis, and the published studies included, incorporates knowledge from the work-family literature with an epidemiological framework to provide detailed evidence about the association between WFC and commonly experienced serious mental health problems in Australian workers - ranging from psychological symptoms to clinical conditions such as GAD and MDD, and suicidal ideation. The thesis findings suggest that WFC is harmful for mental health - it is not only associated with psychological distress, but also more serious diagnosable mental health conditions. The findings highlight the specific mental health risks associated with high WFC exposure for midlife Australian adults separate to other socio-demographics and/or psychosocial stressors experienced at work and home. They underscore the importance of including work-family conflict/balance in mental health screening, preventive interventions, and occupational health management - not only for women or parents, but all employees.
Access status: Open Access ,
Plasmonic and dielectric metaplatform for chiroptical sensing
(2026) Jiang, Min
Detection of enantiomers is essential because chiral molecules with opposing structural handedness exhibit different biochemical properties. Although circular dichroism (CD) spectroscopy identifies chiral enantiomers by measuring their absorption difference under oppositely handed circularly polarized light (CPL) excitation, the CD signal is intrinsically weak. Near-field optical chirality enhancement (OCE) using nanostructures offers a promising route to amplify CD signals. Ideally, nanostructures should exhibit spatially extended OCE distribution of the same handedness, and unobstructed molecular access to regions exhibiting this OCE. This thesis develops plasmonic and dielectric metasystems to meet these requirements. First, a two-arm 3D Au Archimedean spiral with interwire links as structural support producing broadband, spatially extended, single-handed OCE under both CPL and linearly polarized light (LPL) excitation in the visible–near-infrared spectral range is demonstrated. A deterministic fabrication strategy is developed, and experimental results confirm numerically predicted behavior. The cone like geometry works as a sieve, demonstrating the potential to trap nanoparticles coated with chiral analytes within the OCE zone for broadband chiroptical sensing. Second, a low loss, monocrystalline SiO₂–InGaP bilayer metasurface is introduced, consisting of an InGaP cylinder array integrated with a diagonal glass grating. The bilayer metasurface achieves strong single-handed OCE under LPL illumination, with handedness controlled by rotating the polarization angle. Optical characterization of fabricated metasurface agrees with numerical prediction. The exposed OCE regions provide accessible sites for enhanced chiral sensing. Overall, this thesis demonstrates practical plasmonic and dielectric metasystems capable of converting far-field light into strongly enhanced chiral near fields, providing platforms for highly sensitive, low-concentration chiral sensing.
Access status: Open Access ,
Resources to Support Consumer Engagement in Health Research About Chronic Conditions: A Mixed Methods Study
(2026) Zhou, Mingming
In health research, consumers are people with lived experience of health issues, as well as carers and family members. Engaging consumers is increasingly recognised as essential for making research relevant, impactful, and grounded in lived experience, especially in chronic conditions research, where experiences are long-term, complex, and shaped by ongoing interactions with health services. However, engagement remains uneven. Support resources are fragmented and rarely synthesised, and recognition practices vary widely across Australian research settings, with limited consistency in financial remuneration, non-financial recognition, or payment rates. This inconsistency can undervalue consumers' time, expertise, and labour, undermining meaningful engagement. This thesis aimed to (1) identify and synthesise evidence-based resources to support consumer engagement in chronic conditions research; (2) examine how consumers' contributions are currently recognised across Australian research organisations; and (3) develop an evidence-informed framework to strengthen recognition of consumers' contribution to research for their engagement in the Australian context. A mixed-methods study was conducted in three phases. Phase 1 was a systematic scoping review (2013-2023) using Arksey and O'Malley's framework and subsequent enhancements, searching seven databases and synthesising findings through thematic analysis. Phase 2 was a national survey of Research Australia member organisations, co-designed with a multi-stakeholder working group; quantitative data were analysed descriptively and qualitative responses via content analysis, generating preliminary recognition models for stakeholder review. Phase 3 involved deliberative co-design workshops with 21 stakeholders (including nine consumers with chronic conditions) to refine the models and develop a recognition framework informed by guidance, survey results, and workshop evidence. Findings were then integrated using joint displays and interpreted through Axel Honneth's recognition theory to produce an integrated, recognition theory-based framework for consumer engagement in chronic conditions research. Four primary contributions emerged. First, the scoping review produced an overarching framework for consumer engagement in chronic conditions research comprising six interrelated themes: promoting reciprocal learning; fostering supportive environments; providing capacity-building training; acknowledging contributions; using facilitative resources; and evaluating engagement impact. Second, the national survey mapped organisational recognition practices across Australia, demonstrating strong support for recognising consumer contributions alongside substantial variation in remuneration and non-financial recognition approaches, and a clear appetite for national guidance. Third, deliberative workshops refined stakeholder priorities and led to the co-development of Australia's first nationally oriented framework for recognising consumers' contributions to health research, including guidance on decision-making considerations, remuneration structures (project-based, meeting-based and hourly), payment methods, and non-financial recognition options. Fourth, synthesis of findings across phases positioned consumer engagement as an ethical relationship grounded in dignity, equity, and social justice, and specified how relational, structural, and symbolic recognition interact to shape what meaningful engagement requires and how it can be operationalised across research contexts. This thesis provides a coherent evidence base and practical tools to strengthen consumer engagement in chronic conditions research. By integrating empirical findings with recognition theory, it offers a theoretically grounded and implementation-oriented account of how recognition can be enacted across relational, organisational, and symbolic domains to support more equitable, consistent, and meaningful consumer engagement.

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