Theses

Socio-Ecological Determinants of Young Men’s Help-Seeking: Barriers and Pathways to Engagement

2026-01-01T00:00:00Z

Socio-Ecological Determinants of Young Men’s Help-Seeking: Barriers and Pathways to Engagement Palmer, Robert Guided by the socio-ecological model, this thesis examines the determinants of young men’s help-seeking across multiple levels of influence and identifies practical strategies to support more effective and timely engagement with healthcare. Using a sequential, multi-phase, mixed methods approach, four interrelated studies were conducted. These included: a systematic review synthesising the existing evidence base on young men’s barriers and facilitators to help-seeking; secondary analyses of nationally representative survey data examining age differences in help-seeking barriers and the psychosocial determinants of these barriers for young men; and a qualitative study involving semi-structured interviews with a diverse sample of 29 young men. Together, these studies enabled a comprehensive examination of help-seeking determinants across individual, interpersonal, organisational, and societal domains. The findings clarify the unique considerations young men face when seeking help and highlight several key targets for intervention. Across studies, masculine attitudes, health literacy, service accessibility, and social contexts were consistently identified as central influences on young men’s readiness and ability to seek support. A cross-cutting insight was the important role of compassion, both self-directed and from others, in shaping young men’s engagement with healthcare and reducing perceived barriers. Taken together, this thesis provides a multi-level understanding of what holds young men back from seeking help and what can support their timely engagement with healthcare. The findings point to clear, actionable strategies, including strengthening health literacy, addressing loneliness and social disconnection, improving service accessibility, and embedding compassion within service design and public messaging. These insights offer practical pathways for improving early engagement and strengthening health outcomes for young men across the lifespan. Includes publication

Modernisation as Discourse, 1949 to the Great Leap Forward: Zhou Enlai, Chen Yun, and Mao Zedong

2026-01-01T00:00:00Z

Modernisation as Discourse, 1949 to the Great Leap Forward: Zhou Enlai, Chen Yun, and Mao Zedong Chen, Ximeng This thesis examines the discursive and intellectual architecture of modernisation (xiandaihua) in the People’s Republic of China from 1949 to the end of the Great Leap Forward by juxtaposing the ideological and philosophical underpinnings of the discourses of Zhou Enlai, Chen Yun and Mao Zedong. Methodologically, the study employs a discursive analysis that begins by de-sedimenting established scholarly and historiographical frameworks. It combines close textual analysis of both established and more recently released primary sources to foreground temporality, subjectivity, and conceptual differences that animated the discourse of modernisation. It demonstrates that modernisation emerged through three distinct visions: (1) Zhou Enlai’s linear, Soviet-inspired teleology that cast heavy-industry precedence as historical necessity; (2) Chen Yun’s recursive, balance-oriented pragmatism that privileged systemic viability and embodied socialism in the here-and-now; and (3) Mao Zedong’s ruptural ‘Great Leap’ dialectics that re-imagined modernity as a process of continuous, partial qualitative transformations. By recasting xiandaihua as a unifying keyword that masked these deep ideological divisions, the thesis unsettles mainstream narratives that reduce early PRC development to a binary of Stalinist mimicry versus Maoist voluntarism. It positions temporality and agency as central analytics for socialist modernity and demonstrates that divergent readings of dialectics were not academic quarrels but concrete drivers of historical changes.

Behavioral Dataset Compression for Efficient Reinforcement Learning

2026-01-01T00:00:00Z

Behavioral Dataset Compression for Efficient Reinforcement Learning Lei, Shiye Offline reinforcement learning (offline RL) provides a principled framework for learning decision-making policies from fixed datasets without environment interaction, enabling applications in safety-critical, privacy-sensitive, and resource-constrained settings. However, modern offline RL systems often rely on large-scale datasets collected from suboptimal policies, leading to substantial computational overhead and limited scalability. Improving data efficiency is therefore critical for making offline RL practically viable. In this thesis, we develop dataset compression algorithms for offline RL that explicitly account for these intrinsic data properties. From the action perspective, we establish a theoretical equivalence between the policy performance gap and an action-value-weighted decision discrepancy. This insight motivates an action-value-weighted objective for offline behavior distillation (OBD), which distills large offline RL datasets into compact synthetic training sets. From the state perspective, we identify state diversity as a key factor governing the effectiveness of offline behavior distillation. We show that insufficient state coverage in the original dataset limits policy performance after compression. To address this issue, we propose state-weighted OBD, which explicitly incorporates state diversity into the distillation objective and significantly improves robustness to dataset compression. Finally, by jointly considering action-value information, state density, and trajectory-level sequential structure, we propose stepwise dual ranking (SDR), a simple and scalable coreset selection algorithm that constructs compact yet informative subsets from large offline behavioral datasets without additional training overhead. Includes publication

Sonochemical Processing of Gallium-based Soft Composites

2026-01-01T00:00:00Z

Sonochemical Processing of Gallium-based Soft Composites Chiu, Shih-Hao Gallium-enabled soft materials have emerged as promising systems for flexible electronics and sustainable devices due to their metallic conductivity, low melting point, and deformability. This thesis investigates how sonochemical processing and interfacial engineering can address key limitations of gallium-based particles while enabling the design of soft, conductive, and biomass-integrated composites. Thiol-functionalized gallium nano- and microparticles are developed to suppress oxidation and achieve sintering-free conductivity via metal–molecule junctions, with conjugated ligands enabling tunable electrical performance. Liquid gallium nanoparticles are further integrated into PEDOT:PSS, significantly enhancing electrochromic switching kinetics through improved interfacial charge transport. The role of sonochemistry in intensifying mass transport is demonstrated through a coffee-brewing sonoreactor, where extraction efficiency is improved while preserving chemical integrity. Building on this, sustainable composites incorporating spent coffee grounds (SCGs) and gallium nanoparticles are fabricated, forming flexible films with integrated biomass functionality. Preliminary NO₂ sensing results further demonstrate the potential of these materials for functional applications. Overall, this thesis establishes sonochemical interface engineering, molecular functionalization, and biomass integration as complementary strategies for designing next-generation gallium-based soft materials, advancing both fundamental understanding and practical applications in flexible and sustainable systems. Includes publication

Mesoscale Modelling of Concrete Materials under Complex Loadings

2026-01-01T00:00:00Z

Mesoscale Modelling of Concrete Materials under Complex Loadings Liu, Qingchen Concrete is a widely used construction material. In marine environments, its durability and mechanical performance are critical, especially regarding chloride-induced corrosion and structural behaviour under complex stresses. As concrete is a complex composite exhibiting heterogeneity across length scales from the nano- to the macroscale, this work particularly focuses on the mesoscale, as this scale allows the assessment of macroscopic performance while supporting it with microscopic evidence. At the mesoscale, the concrete can be treated as a three-phase composite of cement paste, aggregates, and the interfacial transition zone (ITZ). Aggregates, as the strongest and most impermeable phase, significantly influence performance. However, many studies simplify aggregate shapes, and controlling shape irregularity experimentally is difficult, leaving the effects of realistic aggregate morphology on concrete diffusivity and fracture insufficiently understood. To bridge this gap, this research conducts mesoscale modelling of concrete with realistic aggregate shape to provide new macro- and microscopic insights into the influence of aggregate shape on various single-physical behaviours of concrete. These include ionic diffusion related to chloride-induced corrosion, as well as concrete fracture under triaxial and dynamic loading conditions that represent complex stress environments. The findings provide a new understanding of concrete transport and mechanical behaviours, highlighting the role of aggregate shape irregularity in the diffusivity and strength of concrete. Includes publication

Designing for Casual Human-Robot Collaboration in Urban Public Spaces

2026-01-01T00:00:00Z

Designing for Casual Human-Robot Collaboration in Urban Public Spaces Yu, Xinyan Robots are evolving beyond their traditional roles in controlled environments and are increasingly being deployed in dynamic public urban spaces (e.g., delivery robots). To ensure smooth deployment in these settings, robots must navigate around people and respond to unpredictable situations in which they may experience operational difficulties and require human assistance. Unlike robots in relatively static environments such as laboratories or domestic settings, urban robots encounter a diverse public, most of whom are bystanders without a pre-determined intention to interact. This shifts the dynamics of human–robot collaboration, giving rise to what I term casual human–robot collaboration: forms of collaboration that emerge spontaneously during encounters. These contextual and relational shifts necessitate tailored strategies to facilitate spontaneous interactions between urban robots and bystanders. This thesis aims to develop interaction strategies that facilitate casual collaboration between urban robots and bystanders. First, an online ethnography study was conducted to identify opportunities and gain preliminary insights into how casual collaboration may emerge. The thesis then adopts a research-through-design approach, beginning with bodystorming to generate design considerations. These considerations inform design concepts evaluated in three empirical case studies, including VR lab studies and an in-the-wild field study. The studies examine three scenarios: human–robot spatial conflicts, robot–environment misalignments, and robot technological limitations. This thesis contributes to HCI and HRI in four ways: it identifies design opportunities for casual human–robot collaboration; presents design artefacts and reflections through the RtD process; provides empirical insights into how people engage with these concepts; and offers a conceptual framing for understanding casual human–robot collaboration in public spaces.

THESE WALLS HAVE EYES AND EARS On architectural memory and conservation

2026-01-01T00:00:00Z

THESE WALLS HAVE EYES AND EARS On architectural memory and conservation Zammit, Sarah-Jane The desire to keep alive the memory of the past is deeply human and arguably universal. However, the set of claims the conservation movement has made about buildings as witnesses to time and repositories of memory are historically specific. In the nineteenth century, romantic writers used their artistic skills to anthropomorphise buildings as key to humanity’s memory, witnesses to the passage of time and human achievement, instigating what would become a long-standing cultural tradition. This idea persists today and characterises many contemporary claims for the protection of historic places. The question remains however, why do we expect buildings to remember and do memory work? This doctoral project investigates this long-standing cultural tradition. This thesis argues that the concept of architectural witnessing relies on human perception and the human mind’s complex abilities to remember, imagine and position oneself in different spatiotemporal contexts. The research seeks to understand the cultural mechanisms at work in the nineteenth and twentieth centuries which posited buildings as the memory and history of a city, region or nation. It identifies two key historical moments of crisis around memory which has shaped claims about the role of conservation in preserving and prolonging memory - the nineteenth century c.1810-1850 and the post-WWII period in the twentieth century. Using psychology and memory science as the conceptual apparatus the thesis interrogates these two key periods. The thesis establishes that building conservation, restoration and reconstruction is analogous for the psychological apparatus of memory. Ultimately arguing that this is why we expect buildings to remember, exploring the impact this expectation has on collective memory; how society deals with material evidence and authenticity in these periods; and the creative and recreative tendencies of post-war reconstructions as re-imagined through visual media like photography and painting. Includes publication

Determining changes in Eucalyptus litter during decomposition

2026-01-01T00:00:00Z

Determining changes in Eucalyptus litter during decomposition Hung, Tsz Ching Christy This study demonstrated that both natural and thermal decomposition alter litter carbon and nitrogen content, affecting decomposition rates. Climate was the dominant driver, with rapid initial mass loss under warm and wet conditions. At a regional scale, decomposition was governed by initial litter quality, particularly C/N ratio; for example, Eucalyptus litter with high C/N decomposed more slowly than N-rich understorey litter. Under natural environment, N-rich litter facilitated Eucalyptus decomposition through nutrient transfer. Prescribed burning, while effective for fuel reduction, also regulates litter decomposition and nutrient dynamics. Litter collected one year after fire decomposed faster than pre-fire litter, largely due to fire-induced changes in C/N ratios. In dry sclerophyll forests, post-fire understorey regeneration further enhanced decomposition, potentially supporting forest recovery through increased nutrient availability. However, carbon and nitrogen stored in surface litter are redistributed via volatilisation and mineralisation, with implications for ecosystem nutrient dynamics. These findings highlight the need to consider litter quality, understorey vegetation, and fire regimes in fire prone dry sclerophyll forests. Traditional methods for measuring litter quality are costly and labour-intensive. Spectroscopic techniques such as visible-near-infrared (vis-NIR) and attenuated total reflectance Fourier transform (ATR-FTIR) offer efficient alternatives. Across this thesis, performance ranked ATR-FTIR > NIR > vis-NIR. While vis-NIR and NIR were effective for predicting the quality of fresh litter, ATR-FTIR provided consistently accurate predictions of carbon and nitrogen across litterfall, decomposition stages, and combustion residues. Overall, spectroscopy is a powerful complement to laboratory analysis for understanding chemical transformations in forest litter.

Communal identities and legacies of hegemonic intervention: prospects for justpeace in Afghanistan

2026-01-01T00:00:00Z

Communal identities and legacies of hegemonic intervention: prospects for justpeace in Afghanistan Tippett, Diane This thesis seeks to address the following three research questions: 1. How have various communal identity groups and supra-communal understandings of belonging developed and been reproduced in Afghanistan? 2. How have successive hegemonic interventions affected patterns of state-making and civic organisation in Afghanistan? 3. What are the key relational considerations in respect of achieving a future justpeace in Afghanistan? This thesis examines how identity formation in Afghanistan is shaped by relational ontological insecurity—distinctively deepened and institutionalised during repeated hegemonic interventions— and argues that any future justpeace must therefore be grounded in relational, everyday, and structure–process dynamics that address the affective afterlives of the foregoing rather than interest based models. The above research questions situate this thesis not only within the existing case study scholarship on Afghanistan, but also within the following domains: - Politically applied psychology (specifically including discussions of self-making and identity group affiliation when faced with dynamic realities, the ‘prototype clarity’ of in-groups, and applied hegemony ); - Ontological security studies (specifically including discussions of anxiety, myth and narratives, habitus, rituals of state sovereignty and self/other relations which arise from the second wave of ontological security studies scholarship); and, - Justpeace (specifically including discussions of civic sovereignty, a structure-process orientation, and ordering power ). This broad contribution reflects the transdisciplinary nature of peace and conflict studies as a discipline but also the limitless movement and trajectory of belonging, violence, and peace— each of which are not only political processes, but phenomena continually re-grounded in the affective, relational, routinised practices of the everyday.

Chromosome-level, haplotype-phased genome assembly of an Australian isolate of the oat crown rust fungus Puccinia coronata f. sp. avenae provides insights into population structure and genomics

2026-01-01T00:00:00Z

Chromosome-level, haplotype-phased genome assembly of an Australian isolate of the oat crown rust fungus Puccinia coronata f. sp. avenae provides insights into population structure and genomics Guan, Haixia Puccinia coronata f. sp. avenae (Pca), the causal agent of oat crown rust, is one of the most damaging pathogens of oat worldwide. Rapid evolution and extensive virulence variation continually erode host resistance, posing major challenges for disease management and breeding. This thesis investigated the genomic architecture, population structure, and molecular basis of virulence evolution in Pca through integrated genomic analyses. A chromosome-scale, haplotype-phased reference genome was generated for OCR_502, a representative Australian isolate, using PacBio HiFi sequencing and Hi-C scaffolding. The resulting high-quality assembly provides a valuable genomic resource and a foundation for downstream analyses. Using this reference genome, whole-genome resequencing data from Australian isolates collected over multiple decades were analysed to examine population structure and evolutionary dynamics. The population exhibited high genetic diversity and consisted of several distinct lineages. Temporal shifts in lineage composition suggested that mutation, somatic recombination, and/or the introduction of exotic lineages contribute to diversification despite predominantly clonal reproduction. To investigate the genetic basis of virulence, genome-wide association studies (GWAS) and haplotype-resolved comparative genomics were conducted using 361 isolates phenotyped on five oat crown rust resistance genes (Pc38, Pc39, Pc50, Pc56, and Pc68). Comparative analyses indicated that virulence evolution is more likely driven by allelic variation than gene presence–absence variation. Four high-confidence candidate avirulence genes associated with AvrPc50 and AvrPc56 were identified. Overall, this study provides important genomic resources and advances understanding of the mechanisms underlying virulence evolution and population diversification in Pca. Includes publication

Enhancing Graph Representation Learning: Data-Aware Advances in Graph Neural Networks

2026-01-01T00:00:00Z

Enhancing Graph Representation Learning: Data-Aware Advances in Graph Neural Networks Xiao, Ye Graph-structured data is a fundamental data modality across diverse domains, in which the relations among entities can be as crucial as the entities themselves. However, the irregular nature of it renders traditional Euclidean-based deep learning methods inadequate for modeling its intricate interdependent structure. Graph Neural Networks (GNNs) have emerged as the de facto paradigm for learning effective representations that capture relational information, offering favorable performance through their message-passing mechanism. Despite their development, many recent advances address different tasks primarily in a model-centric view, revolving around more sophisticated designs to enhance representation learning. Considering that the evolving demand for classification further drives models toward more complex architectures, this thesis aims to contribute to the advancement of effective representation learning by placing data at the center of methodological design. To this end, the thesis delves into various data-aware schemes to efficiently and delicately exploit the potential of the graph, thereby enhancing the graph representation learning capabilities of GNNs.

Neural substrates underpinning co-occurring posttraumatic stress disorder and alcohol use disorder

2026-01-01T00:00:00Z

Neural substrates underpinning co-occurring posttraumatic stress disorder and alcohol use disorder Towers, Ellen Elizabeth Posttraumatic stress disorder (PTSD) and alcohol use disorder (AUD) are highly prevalent and debilitating. Despite this, the neurobiology of comorbid PTSD & AUD remains poorly understood. To address this gap, this thesis aimed to investigate neural and psychological mechanisms that may represent risk factors for, or consequences of, co-occurring PTSD and AUD (PTSD & AUD). Chapter 2 systematically reviewed the genetic, molecular, neural and cognitive mechanisms specific to PTSD & AUD. While evidence for greater hypothalamic-pituitary-adrenal axis dysregulation was limited, findings suggested potentially unique disruptions spanning genetic and neural domains, warranting further investigation. Building on these findings, Chapters 3-5 used pooled neuroimaging datasets to examine the structural and functional underpinnings of PTSD & AUD. Chapters 3 and 4 represents the first large-scale investigation to directly compare current PTSD & AUD with PTSD-only, AUD-only, and controls. Using complementary region-specific and graph-theoretical approaches, these chapters identified shared and comorbidity-specific structural alterations. Chapter 5 identified altered intrinsic functional connectivity patterns associated with depression and stress symptom severity in PTSD & AUD relative to AUD-only. Chapter 6 explored associations between negative affect, drinking motives, craving and use in a large Australian AUD sample with and without PTSD. Findings indicated that alcohol-related processes were more broadly linked to negative affect states (e.g., depression, stress, anxiety) in PTSD & AUD than AUD-only. This thesis provides a comprehensive and highly integrated body of work examining the neural substrates of co-occurring PTSD and AUD and explores how psychological features relate to both clinical and neurobiological phenotypes. Findings suggest that PTSD & AUD is characterised by distinct neural and psychological alterations that may represent risk and/or maintenance mechanisms. Includes publication

Melanoma risk assessment and risk-stratified melanoma screening and surveillance

2026-01-01T00:00:00Z

Melanoma risk assessment and risk-stratified melanoma screening and surveillance Reyes- Marcelino, Gillian Melanoma remains a major public health challenge in Australia, which has one of the highest melanoma incidence rates worldwide. Despite this burden, there is currently insufficient evidence to support the implementation of an organised population-wide melanoma screening program. Early detection largely relies on opportunistic skin checks undertaken in clinical practice. Current clinical guidance recommends identifying individuals at higher personal risk and offering them more regular skin examinations, yet the consistency of this risk-based approach remains uncertain. This thesis examined how melanoma early detection currently operates in Australia and how risk prediction tools might support more consistent risk-based approaches in clinical practice and future screening policy. The research programme combined studies examining clinical skin check behaviours, the acceptability of melanoma risk prediction tools, and the performance of existing melanoma risk prediction models. This thesis provides new evidence relevant to both current clinical practice and ongoing considerations regarding melanoma screening policy in Australia. Includes publication

Three Essays in Corporate Finance and Informed Trading

2026-01-01T00:00:00Z

Three Essays in Corporate Finance and Informed Trading Sarkar, Md. Ahasan Habib This dissertation examines how uncertainty, organizational capabilities, and information networks shape corporate investment, international acquisitions, and institutional investor behavior. Using novel identification strategies and granular data across multiple institutional settings, it provides new evidence on how firms and financial intermediaries respond to uncertainty and exploit private information around major corporate events. The first essay examines how central bank governor transitions influence corporate investment. Exploiting predetermined leadership transitions that generate exogenous policy uncertainty, it shows that firms reduce investment in anticipation of governor turnover, particularly in interest- and exchange-rate-sensitive industries, with effects attenuated in countries with stronger central bank independence. The second essay studies the role of organization capital in international acquisitions. Firms with higher organization capital are more likely to undertake international acquisitions and create greater shareholder value following deal completion, highlighting the importance of intangible organizational capabilities in successful international expansion. The third essay provides transaction-level evidence on mutual fund trading around mergers and acquisitions. Mutual funds accumulate target shares before public announcements and earn substantial profits from these trades. Profitability is significantly higher when trades overlap with corporate insider activity, when affiliated investment banks advise transaction parties, and when funds are geographically closer to event firms. Overall, the dissertation contributes to the literatures on monetary policy uncertainty, organization capital, and informed trading by demonstrating how uncertainty, organizational capabilities, and information networks shape investment decisions, corporate strategy, institutional investor behavior, and ultimately asset prices. Includes publication

Translation of Digitally Enabled Health Initiatives for Human Development

2026-01-01T00:00:00Z

Translation of Digitally Enabled Health Initiatives for Human Development Pujitha Gunawardena, Dinushika Sathsarani Access to digital technologies alone is insufficient to achieve desired improvements in low- and middle-income countries (LMICs). Historically, efforts have focused on exporting solutions from Western settings to LMICs, with limited attention to local social, economic, political, and infrastructural contexts. Such approaches result in failure to achieve expected development outcomes, frustrating local users and posing a high risk for short-lived initiatives. Moreover, they remain inadequate for realising global aspirations for human development as envisioned by the United Nations. This thesis reimagines current approaches to digital development by proposing a translational approach that offers a promising path for the design and local embedding of digitally enabled health initiatives. Chapter 2 provides a conceptual review of human development, leading to a conceptual leap that emphasises translating Information System (IS) artifacts and associated knowledge to better support aspirations for human development. In Chapter 3, a four-phase research design is developed to guide the translation-focused design of digitally enabled health initiatives. Locally anticipated outcomes in Ecuador and Papua New Guinea inform the future design of a virtual care system for their contexts through translation. Chapter 4 investigates how translation facilitates the local embedding of a digitally enabled health initiative in Sub-Saharan Africa. How actors translate IS artifacts and associated knowledge to enhance their relevance within local practices, norms, and cultures is examined. This thesis makes five key contributions: it offers a reimagined approach for digital development research; broadens the understanding of what translation entails in digital development; contextualises and extends the lens of the IS artifact; makes a methodological contribution through a translation-focused research design; and identifies interrelated outcomes of virtual care in remote settings. Includes publication

Capturing Students' Conceptual Change When Exploring Decimals through Dynamic Digital Representations

2026-01-01T00:00:00Z

Capturing Students' Conceptual Change When Exploring Decimals through Dynamic Digital Representations Gorman, Amelia Kate Decimals are of great significance in the primary mathematics curriculum due to their application and use in everyday life. The purpose of this study was to investigate the effectiveness of certain dynamic digital representations in developing students’ knowledge of decimal fractions. Task-based interviews were used with six Year 4 (9-10 years old) students, that incorporated four different dynamic digital representations of decimals. Data collected via video-audio recordings were used to detect shifts in students’ attention while using the digital representations. Attention shifts were analysed using microgenetic methods to determine conceptual changes over time. Findings uncovered specific features of the digital representations that generated productive cognitive con-fusion which prompted changes in students’ understanding of decimal fractions. The unique affordances of each digital tool offered students opportunities to dynamically explore decimal concepts and could be used to enrich the teaching of decimals within the primary mathematics classroom. Includes publication

Confronting Plate Models with the Deep Mantle

2026-01-01T00:00:00Z

Confronting Plate Models with the Deep Mantle New, Thomas Christopher Mantle circulation models, numerical models of whole-mantle convection driven by tectonic reconstructions, are widely used to predict present-day mantle structure and, in turn, to evaluate the reconstructions themselves. Yet many studies compare modelled temperature fields directly with seismic tomography, overlooking nonlinearity in the temperature-velocity relationship, the strongly heterogeneous resolution of seismic imaging, and misfit metrics that saturate when anomalies do not overlap. This thesis develops a robust, physically consistent approach to evaluating competing tectonic reconstructions against tomography. I first develop a transferable comparison methodology, demonstrated with the G-ADOPT finite-element modelling library, comprising: (i) physically consistent conversion of predicted temperatures into seismic velocities; (ii) tomographic resolution operators to filter converted structures prior to comparison; and (iii) the Wasserstein metric to quantify misfit informatively even without anomaly overlap. After benchmarking G-ADOPT models across well-studied subduction regimes, I apply these tools to the collision of the Ontong-Java plateau with the Melanesian arc, where collision timing remains uncertain (~25 vs ~12 Ma). I show that physically consistent post-processing can flip qualitative inferences of slab morphology, shift inferred slab depths by tens of kilometres, change inferred sinking rates by up to 1.2 mm/yr, and laterally displace slab anomalies by up to 639 km. Benchmarking shows G-ADOPT reproduces mantle structure well where slab rollback dominates, but predicts incorrect dip polarity where trenches advance. The case study strongly supports the older collision scenario: only the ~25 Ma model reproduces slab material beneath the Melanesian arc, with 10-28% lower misfit, supporting a role for the collision in regional plate reorganisation. These results highlight the value of publishing tomography models alongside resolution operators. Includes publication

AI-driven Defect Detection and Multi-Agent Disaster Response for Civil Infrastructure

2026-01-01T00:00:00Z

AI-driven Defect Detection and Multi-Agent Disaster Response for Civil Infrastructure Chen, Zhaohui Rapid and reliable assessment of civil infrastructure is essential for effective disaster response. Traditional inspection relies on manual, expert-driven surveys, which are time-consuming, resource-intensive, and difficult to scale under limited accessibility and evolving hazards. Although computer vision enables automated damage detection, most approaches focus on isolated perception tasks and lack support for system-level reasoning. This thesis develops an AI-driven framework that integrates robust local-scale perception with structured global-scale reasoning. At the local scale, efficient vision models are designed for defect detection under realistic conditions. A Transformer-based crack segmentation model with average pooling improves robustness in noisy environments, while a Robust Feature Knowledge Distillation (RFKD) framework transfers noise-resilient representations from teacher to lightweight student models for deployment. Vision Mamba architectures are further explored to improve scalability for high-resolution inspection. At the global scale, a multi-agent framework transforms perceptual outputs into actionable insights through role-based task decomposition, information integration, and collaborative reasoning, enabling coherent situational awareness with human-in-the-loop support. Experiments demonstrate improved robustness and scalability over conventional methods. Challenges remain in handling uncertainty and ensuring reliable long-horizon reasoning. Future work will focus on uncertainty-aware models and tighter integration with sensing and decision-support systems. Includes publication

Investigating the Mechanisms and Applications of Liquid Metal-Biomolecule Interactions

2026-01-01T00:00:00Z

Investigating the Mechanisms and Applications of Liquid Metal-Biomolecule Interactions Liu, Li Gallium (Ga)-based liquid metals have attracted increasing attention due to their metallic conductivity, fluidity, and unique surface chemistry. However, their interactions with biological macromolecules remain insufficiently understood. This thesis investigates the interfacial interactions between liquid Ga droplets and biomolecules, focusing on protein self-assembly and nucleic acid reactivity. First, a self-standing soy protein isolate (SPI)-Ga composite film is developed to study interactions between Ga droplets and protein fibrils. Protein fibrils reduce Ga surface oxidation, promote droplet coalescence, and facilitate conductive pathway formation without disrupting the β-sheet-rich fibrillar network. The resulting composites exhibit combined electrical conductivity and mechanical robustness, enabling applications in gas sensing and electrically stimulated antibacterial activity. This thesis then investigates the interaction between Ga droplets and DNA. The results demonstrate that Ga droplets can cleave DNA phosphodiester bonds, with preference for adenine- and thymine-rich sequences. Mechanistic studies show that the activity originates from interfacial electron transfer associated with Ga surface oxidation, generating reactive species that cleave the DNA backbone while largely preserving nucleobase integrity. The nuclease-mimicking activity can also be tuned through droplet characteristics and external stimuli. Together, this thesis establishes a fundamental understanding of how liquid Ga interfaces interact with protein fibrils and nucleic acids, providing guidance for the design of liquid metal-based biohybrid materials and future biomedical applications. Includes publication

Optimizing Large Language Models: Algorithmic Advancements and Model Design Strategies

2026-01-01T00:00:00Z

Optimizing Large Language Models: Algorithmic Advancements and Model Design Strategies Bie, Fengxiang Large Language models have achieved remarkable performance across diverse tasks, but face two critical deployment challenges: (1) the key-value (KV) cache memory bottleneck that limits model deployment in resource-constrained environments, and (2) the sequential autoregressive generation latency that reduces inference throughput and user experience. This thesis presents two complementary contributions addressing these distinct challenges. First, CARE (Covariance-Aware and Rank-Enhanced) tackles the KV-cache memory bottleneck by converting pretrained Grouped Query Attention (GQA) models into memory-efficient Multi-Head Latent Attention (MLA) architectures. Unlike naive SVD approaches that ignore activation patterns, CARE introduces activation-preserving factorization using covariance-weighted SVD and adaptive rank allocation via water-filling algorithms. Second, Infinigram-based speculative decoding addresses inference latency by leveraging large-scale n-gram statistics to predict multiple tokens in parallel, achieving significant speedup through CPU-optimized data structures and confidence-based acceptance strategies. Experimental results on Llama-3.1-8B demonstrate that CARE achieves up to 331% relative improvement in zero-shot accuracy over baseline conversion methods while maintaining identical KV-cache footprint. Post-conversion healing fully recovers original model performance with minimal fine-tuning. Infinigram delivers significant inference speedups across various sequence lengths and batch sizes, with acceptance rates improving for longer context matches and higher-frequency patterns. This work contributes novel methodologies combining model design strategies and algorithmic advancements for efficient large generative model deployment, providing practical solutions to key memory and computational challenges without compromising model capabilities.

Fast Algorithms for Fréchet-Based Similarity

2026-01-01T00:00:00Z

Fast Algorithms for Fréchet-Based Similarity Huang, Zijin Polygonal curves arise naturally when recording movement data from GPS traces, animal tracking, or eye-gaze measurements. A fundamental task is to compare such curves using a formal notion of similarity. The Fréchet distance is a widely used metric for this purpose, as it respects both the geometric proximity and the traversal order of two curves. This thesis develops faster algorithms for four Fréchet-based similarity problems, each using the freespace diagram as its central tool. In Chapter 2, we study the Fréchet distance under geometric transformations, which is essential when comparing shapes regardless of their position or orientation. We present the first improvement to the decision problem for a wide class of transformations, including translations, rotations, and scalings. In Chapter 3, we consider the Fréchet edit distance, which allows inserting or deleting vertices before measuring the continuous Fréchet distance. This variant is motivated by the need for robustness against outliers and noise in real-world trajectory data. We provide faster algorithms for several edit models, improving on prior bounds by up to a factor of k · n. In Chapter 4, we study subtrajectory clustering on c-packed trajectories, a realistic model of movement data with bounded self-overlap. We present a near-linear time approximation algorithm for the subtrajectory cluster problem, circumventing the conditional cubic lower bound for general curves. In Chapter 5, we connect the partial weak Fréchet similarity to shortest paths in weighted planar regions. We construct a near-linear size approximate spanner for the 0/1/∞ weighted region problem, and apply it to obtain an approximation algorithm for the partial weak Fréchet similarity.

BayeSpace - Applying Bayesian Statistics to Environmental and Ecological Phenomena

2026-01-01T00:00:00Z

BayeSpace - Applying Bayesian Statistics to Environmental and Ecological Phenomena Davis, Samuel Caradog Environmental and ecological phenomena are inherently complex, dynamic, and uncertain — requiring analytical tools that can generate accurate predictions while transparently quantifying uncertainty. This thesis introduces BayeSpace, a modular Python framework for applying Bayesian inference to spatiotemporal environmental and ecological modelling. It addresses key limitations in existing approaches, including fragmented workflows, steep learning curves, and model visualisation and comparison. BayeSpace integrates two core Bayesian methodologies: Bayesian Regression (BR) for problems with known functional forms, and Gaussian Process Regression (GPR) for flexible, non-parametric modelling. Built on libraries such as NumPyro and scikit-learn, it provides core classes for model definition, prior and likelihood specification, sampling, and visualisation. Key innovations include automated experiment tracking, domain generation, data simulation, kernel and transformation flexibility, and robust visualisation tools. The framework's capabilities are demonstrated through several applications. In marine cloud brightening research, BR was used to infer atmospheric dispersion parameters from real-world plume data over the Great Barrier Reef, suggesting oceanic dispersion may be more intense than terrestrial models predict. This case study illustrates BayeSpace's ability to explore complex phenomena, identify model limitations, and understand asymptotic behaviour. In species distribution modelling, GPR effectively handled spatiotemporal occurrence data, with model performance strongly correlating with total grid coverage. BayeSpace's iteration ability and flexibility were vital in designing a one-size-fits-all framework for species distribution modelling. Validation using simulated and real-world datasets confirmed BayeSpace's accuracy in linear cases while revealing challenges in highly non-linear regimes where complex posteriors affect sampler convergence.

Essays on Machine Learning in Economics

2026-01-01T00:00:00Z

Essays on Machine Learning in Economics Deng, Sinan This thesis presents three studies exploring how machine learning can be applied to understand and model complex phenomena in economics. Chapter 2 investigates how machine learning can be used to examine geographic diversity within global economics research. Chapter 3, published in Energy Economics (2024), develops a seasonal deep learning model for Great Britain’s electricity imbalance prices, showing that incorporating seasonality improves forecasting accuracy. Chapter 4 extends this framework by applying distributional deep learning methods to model full price distributions and distinguish between aleatoric and epistemic uncertainty. Includes publication

Engineering entanglement in trapped ion quantum harmonic oscillators using spin-dependent interactions

2026-01-01T00:00:00Z

Engineering entanglement in trapped ion quantum harmonic oscillators using spin-dependent interactions Millican, Maverick James Quantum harmonic oscillators are a central resource in quantum technologies. Coupling this resource to a two-level system gives rise to spin-oscillator dynamics that can be used for system calibrations, enhanced sensitivity to signals, and the preparation of oscillator entangled states. Chapter 4 introduces a motional-frequency calibration protocol based on a time-reversal, state-dependent force sequence that maps the effects of motional-frequency miscalibration onto a narrow spin-response feature. The chapter also discusses how thermally occupied motional states enhance sensitivity to particular Hamiltonian terms, making them effective probe states. A two-point feedback servo with processing performed on a field-programmable gate array, or FPGA, is used to track the interaction resonance in real time, enabling sub-second updates and continuous correction of frequency drift during data acquisition. Chapter 5 realizes phase-insensitive displacement sensing by embedding spin-dependent squeezing in a time-reversal interferometry sequence. The method prepares a spin-correlated superposition of orthogonally squeezed motional states, yielding a spin-observable response used to estimate displacement amplitudes while remaining agnostic to the signal phase. Experiments with vacuum and number-state probes demonstrate enhanced sensitivity with increasing motional energy. Chapter 6 extends the spin-oscillator toolkit to multi-oscillator control. Optimized phase modulations applied to Jaynes-Cummings and anti-Jaynes-Cummings couplings between a single spin and two motional modes synthesize an effective two-mode squeezing interaction, enabling preparation of two-mode squeezed vacuum states and a non-Gaussian superposition of those states. Joint phase-space tomography reveals multi-mode correlations, and continuous-variable entanglement is certified by the Einstein-Podolsky-Rosen criterion and a Clauser-Horne-Shimony-Holt-type continuous-variable Bell test. Includes publication

Mesenchymal stem cell senescence: Mechanisms and rejuvenation strategies

2025-01-01T00:00:00Z

Mesenchymal stem cell senescence: Mechanisms and rejuvenation strategies Zhang, Yiran Cellular senescence is a key contributor to organismal ageing and reduces the regenerative capacity of mesenchymal stem cells (MSCs), limiting their therapeutic potential in treating age-related diseases. This thesis aimed to investigate the mechanisms and functional consequences of MSC senescence and to develop strategies to rejuvenate senescent cells. Using adipose-derived mesenchymal stem cells (ASCs), this study first examined the effects of the chemotherapeutic drug doxorubicin (DOX) on senescence. Both short- and long-term DOX exposure induced senescence; however, while long-term exposure impaired osteogenic differentiation, short-term exposure enhanced osteogenesis. Transcriptomic analysis identified insulin-like growth factor 2 (IGF2) as a potential regulator of this dual effect, and IGF2 treatment restored osteogenic potential in senescent ASCs, suggesting a beneficial role of transient stress-induced senescence. To explore rejuvenation strategies, this thesis investigated both biomaterial and drug delivery approaches. Osteopontin (OPN), a major extracellular matrix protein, was shown to reverse senescence-associated phenotypes in replicative senescent ASCs, restoring proliferation, osteogenic differentiation, trophic support, and regulating cell morphology. In parallel, a liposome-based drug delivery system was developed to encapsulate nicotinamide mononucleotide (NMN), an anti-senescence drug. Optimised formulations achieved high encapsulation efficiency and reduced the expression of senescence markers in vitro. Together, these findings advance understanding of MSC senescence and identify OPN-based biomaterials and liposomal delivery systems as promising strategies for MSC rejuvenation and regenerative medicine.

Development of a sustainable acid resistant mortar for back-filling of impressed current cathodic protection (ICCP) anodes

2026-01-01T00:00:00Z

Development of a sustainable acid resistant mortar for back-filling of impressed current cathodic protection (ICCP) anodes Fatemi Nayeri, Sayed Hamid Reza Reinforced concrete (RC) structures in marine environments are highly susceptible to chloride-induced corrosion, for which impressed current cathodic protection (ICCP) is widely applied. The performance of ICCP systems is governed by the durability and electrochemical behaviour of the anode back-fill mortar. Field observations from New South Wales, Australia, show that conventional Portland cement-based mortars can degrade due to electrochemically induced acidification at the anode interface, highlighting the need for more stable and compatible materials. This thesis investigates ICCP-induced acidification through field sampling, laboratory characterisation, and electrochemical testing. Analyses of mortars retrieved from operational marine bridges show that anodic reactions generate acidic species that dissolve calcium-rich phases, promote gypsum formation, and degrade the binder, resulting in non-uniform deterioration. These mechanisms were reproduced under accelerated laboratory conditions. Based on this understanding, hybrid geopolymer mortars incorporating supplementary cementitious materials (SCMs) were developed as acid resistant alternatives. Laboratory results show improved resistance to acidic exposure, reduced mass loss, and enhanced microstructural stability. Field implementation confirmed material integrity and compatibility with electrochemical requirements under marine exposure. Transport properties were also assessed. While higher SCM content improved durability, it increased resistivity, highlighting a trade-off between durability and electrochemical performance. Ionic conductivity governed polarisation behaviour, and its optimisation improved performance in atmospheric zones, while conductive additives were unnecessary in submerged conditions. Overall, this research establishes an exposure-specific framework for designing ICCP back-fill mortars that balance durability and electrochemical functionality in marine environments.

Carbon and Nutrient Interactions in Cereal-Legume Intercropping Systems: Impacts of Phosphorus Fertilization

2026-01-01T00:00:00Z

Carbon and Nutrient Interactions in Cereal-Legume Intercropping Systems: Impacts of Phosphorus Fertilization Rahman, Md Zillur Phosphorus (P) deficiency is a major constraint to agricultural productivity in low-input systems where nutrient availability limits crop growth and resource-use efficiency. Although cereal-legume intercropping is widely promoted to improve nutrient acquisition and productivity, the mechanisms by which P availability regulates nutrient uptake, biological nitrogen fixation (BNF), nitrogen competition, and belowground carbon (C) allocation remain poorly understood. This thesis investigated the effects of P fertilization on productivity, nutrient acquisition, and carbon-nitrogen interactions in cereal-legume systems through a global meta-analysis and isotope-based experiments in a P-limited soil. A meta-analysis showed that P fertilization significantly increased crop yield and N and P uptake in both monocropping and intercropping, while also improving land-use efficiency in intercrops. Experimental studies using wheat-chickpea intercrops demonstrated that P availability strongly regulated belowground C allocation and BNF. Phosphorus fertilization increased chickpea biomass, P uptake, and BNF, while reducing root C allocation, indicating a shift towards symbiotic N acquisition. In contrast, wheat maintained root C investment regardless of cropping system. A 15N-labelling experiment revealed that wheat was more competitive for nitrate uptake than chickpea, particularly under P fertilization, whereas ammonium acquisition was similar between species. Fine-root traits were important predictors of nutrient uptake under P limitation. A 13CO2 pulse-chase study showed contrasting P-acquisition strategies, with chickpea maintaining high P uptake with minimal changes in rhizodeposition, while wheat relied on increased root C allocation and rhizodeposition. These findings provide new insights into nutrient acquisition and belowground C dynamics in cereal-legume intercropping and highlight opportunities to improve P-use efficiency in sustainable low-input cropping systems. Includes publication

Causes, Mechanisms, and Mitigation of Socially-Induced Nocebo Effects

2026-01-01T00:00:00Z

Causes, Mechanisms, and Mitigation of Socially-Induced Nocebo Effects Saunders, Cosette Emilie The nocebo effect refers to adverse symptoms that arise in response to treatment but cannot be explained by its active properties. Despite their major clinical, social, and economic burden, nocebo effects remain understudied. Social learning, where people learn by observing or interacting with others, is a potent pathway for nocebo effects. In healthcare, where treatment experiences can be shared face-to-face and through mainstream and social media, understanding socially-acquired nocebo effects matters. This thesis examined the causes, mechanisms, spread, and reduction of socially-induced nocebo effects. Chapter 1 introduces nocebo effects, induction pathways, and key mechanisms. Chapter 2 presents a review and meta-analysis showing that observing adverse symptoms in another person produces medium-to-large nocebo effects compared with no treatment, with effects similar to classical conditioning and larger than explicit instruction. Prior studies, however, only tested cases where model and observer had identical experiences. Chapters 3 and 4 tested whether nocebo effects arise when the model’s experience differs from the observer’s. Using a virtual reality model of cybersickness and a simulated clinical paradigm, these studies showed that social nocebo effects generalise to similar treatments and contexts. This suggests social expectations are not limited to the modelled intervention, widening the scope of harm. Chapters 3 and 5 tested ways to reduce social nocebo effects. Choice was not found to reduce socially elicited cybersickness. In contrast, positive social modelling, where side effect warnings were paired with a peer reporting no side effects, reduced symptom severity. This gives initial evidence that social learning can also counter nocebo formation. Overall, this thesis advances understanding of socially-induced nocebo effects and shows that continued work is needed to develop and test ways to reduce their burden on individuals and the wider community.

Leveraging deep learning to enable real-time beam-view image-guided radiotherapy

2026-01-01T00:00:00Z

Leveraging deep learning to enable real-time beam-view image-guided radiotherapy Chrystall, Danielle Maria Real-time image-guided radiotherapy (IGRT) is essential for minimising the clinical impact of patient motion during radiotherapy. Existing IGRT systems often rely on additional imaging dose or specialised, expensive technology to enable continuous intrafraction monitoring. Beam-view imaging offers a promising alternative, enabling real-time tumour monitoring directly in the treatment beam without additional imaging dose and with broad compatibility on standard linear accelerators (linacs). However, its clinical use is limited by treatment-beam occlusions and poor megavoltage (MV) image quality. This thesis aims to develop, implement, and evaluate a deep learning-enabled beam-view IGRT framework that is safe, accurate, and compatible with standard linacs. Novel deep learning approaches were leveraged to overcome the aforementioned challenges facing beam-view imaging. Three research objectives are addressed: (i) develop deep learning-enabled beam-view target tracking approaches for abdominopelvic and thoracic treatment sites; (ii) experimentally evaluate real-time beam-view marker tracking using an anthropomorphic pelvic phantom, and develop associated workflows and patient-specific quality assurance procedures to facilitate safe clinical deployment for prostate cancer radiotherapy; and (iii) clinically implement and evaluate real-time beam-view marker tracking during prostate stereotactic body radiotherapy (SBRT). Real-time beam-view IGRT has been developed and investigated, with clinical feasibility demonstrated for prostate SBRT. Key implementation barriers are addressed, establishing a foundation for broader clinical adoption of real-time beam-view IGRT on standard linacs.

Multimodal Emotion Elicitation and Recognition in Virtual Reality

2026-01-01T00:00:00Z

Multimodal Emotion Elicitation and Recognition in Virtual Reality Kuang, Zheyuan Virtual Reality (VR) has been effectively used for eliciting emotions, yet most research focuses on the intensity of affective responses rather than on how interaction influences those experiences. To address this gap, this thesis advances a validated VR emotion-elicitation dataset through two extensions. First, we add a new high-arousal, high-valence scene and validate its effectiveness in a within-subject study (N=24). Second, we create interactive and non-interactive versions of each scene to examine the impact of interaction on emotional responses. We evaluate interaction using subjective ratings and physiological signals. Our evaluation study (N=84) shows that interaction not only amplifies emotions but also modulates them in context, supporting coping in negative scenes and enhancing enjoyment in positive scenes. Multimodal Emotion Recognition (MER) increasingly depends on fine-grained, evidence-grounded annotations, yet inspection and label construction are hard to scale when cues are dynamic and misaligned across modalities. This thesis presents an LLM-assisted toolkit that supports multimodal emotion data annotation through an inspectable, event-centered workflow. The toolkit aligns heterogeneous recordings, visualizes modalities on a shared timeline, and packages synchronized keyframes and time windows as traceable event packets. It then uses modality-specific tools and prompt templates to draft structured annotations for analyst verification and editing. Building on the dataset extensions and annotation, this thesis further investigates MER modeling approaches in VR that integrate behavioural and physiological signals from VR headsets and wearable sensors. We introduce an LLM-based Mixture-of-Experts (MoE) framework, where experts specialize in different modalities and a router assigns weights to experts for each event. The goal is to connect predictions to traceable multimodal evidence and support interpretation of affective cues in interactive VR.

Learning Theory for Transformers: An Operator-Learning Viewpoint

2026-01-01T00:00:00Z

Learning Theory for Transformers: An Operator-Learning Viewpoint Liu, Peilin Large language models (LLMs) have reshaped the foundations of artificial intelligence research and the modes of interaction between human cognition and machine intelligence. Their influence extends further still, transforming the scientific tools through which we interrogate and model the physical world. Underlying most of these achievements and breakthroughs is a dominant architecture: the Transformer. Although the Transformer was proposed nearly a decade ago, established mathematical frameworks remain insufficient to explain the complex phenomena observed in practice with Transformer-based networks, particularly large language models. This thesis offers a principled theoretical foundation for understanding the remarkable capabilities these models exhibit, grounded in a central argument that the Transformer performs operator learning during pretraining over vast text corpora. Our analysis reveals the nature of pretraining and in-context learning mechanisms of efficient Transformer structures in an operator learning framework. Transformers maps each context distribution to a response function for queries and with more samples from context distribution, they can recover information as much as possible to get a better response function with fixed and pretrained weights without any update.

If 'I am woman', what is man? British masculinity and the Women's Liberation Movement, 1970-1990

2026-01-01T00:00:00Z

If 'I am woman', what is man? British masculinity and the Women's Liberation Movement, 1970-1990 Wallhead, Emma Jane This thesis examines the theory and analysis by the Women’s Liberation Movement (WLM) about men - including their sons, husbands, fathers, friends and others - in the context of the project of liberation. The Women’s Liberation Movement (WLM) from the late 1960s has been widely recognised as naming men as oppressors in the systemic subordination of women. Beyond this, however, there has been little attention paid to the specific critique of men and masculinity that was made by this influential movement. Filling this gap, this thesis uncovers a consistent thread of thinking in the critique of men and masculinity that was sustained across campaigns and across the duration of the WLM. That thinking understood masculinity as a mechanism to assert power over others but, more explicitly, pointed to specific traits such as selfishness, hierarchical thinking, aggression and detachment as socially endorsed norms of masculinity. Rather than creating new forms of ‘masculinity’, feminists argued that, if systems of oppression were to be dismantled, gender categories such as masculinity would need to be abandoned in favour of a more egalitarian world in which women and men might coexist with a shared commitment to collective responsibility, regard for others, nonviolence and care.

ESSAYS ON Strategic Control and Consumer Response: Insights from Vertical Restraints and Promotional Tools

2026-01-01T00:00:00Z

ESSAYS ON Strategic Control and Consumer Response: Insights from Vertical Restraints and Promotional Tools Chen, Chia-Ying This thesis examines how location shapes market outcomes through its influence on both consumer behaviour and distribution channel design. The first essay investigates the effectiveness of electronic coupons using transaction, review, and mobile GPS data. The results show that consumers located farther from a focal restaurant are more likely to leave reviews after coupon redemption. E-coupons also generate positive spillover effects by increasing subsequent review activity at nearby restaurants. These effects vary across mobility segments, with transit-oriented consumers exhibiting stronger exploratory behaviour than consumers associated with workplaces or educational institutions. The second essay examines the interaction between exclusive dealing and exclusive territories in automobile distribution channels. Using multi-level data from the Chinese automobile industry, the study finds that the two contractual arrangements operate as complementary governance mechanisms in luxury markets. Dealer size negatively affects the likelihood of exclusive dealing, particularly for luxury brands. Overall, this thesis demonstrates how spatial considerations influence firm performance, market coordination, and competitive outcomes through both consumer mobility patterns and geographic distribution strategies.

Responsible Management of AI Use in Organizations: Case Studies of Strategic AI Capabilities, Risk Controls, and Knowledge Management

2026-01-01T00:00:00Z

Responsible Management of AI Use in Organizations: Case Studies of Strategic AI Capabilities, Risk Controls, and Knowledge Management Wang, Yichen Organizations are increasingly investing in artificial intelligence (AI), yet many still struggle to translate its technical potential into reliable, and strategically aligned organizational outcomes. These challenges have intensified as AI evolves from static predictive analytics to dynamic and opaque systems embedded in core organizational processes. Existing responsible AI approaches mainly provide high-level ethical principles. As such, an important research question remains: How can organizations achieve responsible management of AI use? To address this question, this thesis presents three qualitative case studies across different AI technologies and organizational contexts, contributing to explain how organizations can develop capabilities, governance mechanisms, and control approaches for responsible use. In particular, Study 1 examines how a social-media platform develops strategic AI capability when implementing predictive AI systems. The findings identify a cyclical capability development process that enables organizations to cultivate informed agility, controlled efficiency, and anticipatory resilience in response to evolving predictive AI outputs. Study 2 investigates dynamic learning recommendation systems across three leading social-media platforms and develops a cybernetic control approach for governing black-box AI systems through buffering, feedforward, and feedback controls. This study demonstrates how organizations maintain model performance and reliable control under conditions of continuous model evolution and learning instability. Study 3 examines a cybersecurity organization adopting generative AI for organizational knowledge management. Drawing on the SECI model of knowledge creation, this study proposes a phase-dependent AI alignment approach and identifies alignment mechanisms that support accountable, and domain aligned AI-generated knowledge outcomes.

Estimating Output Gaps in Open Economies

2026-01-01T00:00:00Z

Estimating Output Gaps in Open Economies De Gorostiza, Gilliane Angela Estimating the output gap remains a critical challenge for macroeconomic policy due to data limits, reporting lags, and global shocks. This dissertation extends the Beveridge-Nelson (BN) decomposition framework across three chapters to provide more reliable, informative, and timely indicators of economic slack for emerging Asian economies and Australia, demonstrating that multivariate and mixed-frequency BN frameworks improve real-time policy decision-making. The first chapter shows that the BN filter provides more reliable estimates for emerging Asian economies than Hodrick-Prescott, Christiano-Fitzgerald, or Hamilton filters. Cyclical consumption is more volatile than the output gap, and less than one-third of GDP growth fluctuations stem from trend shocks, countering the "cycle is the trend" view. Crucially, BN estimates suffer from smaller, less frequent revisions during major economic shifts. The second chapter reveals that while traditional domestic slack measures are uninformative for Southeast Asian economies due to structural issues and informal employment, financial and external variables are highly relevant. Financial factors dominated during the Asian and Global Financial Crises, with external variables often explaining a larger share of cyclical fluctuations than domestic output. The third chapter applies a mixed-frequency framework to Australia. It finds that the labor market's intensive margin (aggregate hours worked) offers a more significant informational contribution than headline unemployment. Furthermore, the Trade Weighted Index (TWI) provides informational value nearly equivalent to the entire financial or macroeconomic sectors combined. While domestic shocks drive most Australian fluctuations, the Global Financial Crisis was largely driven by foreign shocks. Finally, a weekly TWI indicator allows for more timely updates but does not improve nowcast accuracy relative to a monthly frequency.

Writing a Migrant Body: Identity Predicament and Resistance in Sinophone Fiction by Chinese Migrant Women in Australia 1996-2004

2026-01-01T00:00:00Z

Writing a Migrant Body: Identity Predicament and Resistance in Sinophone Fiction by Chinese Migrant Women in Australia 1996-2004 Ye, Su This thesis examines the migrant identities of mainland Chinese women in 1990s Australia through Sinophone fictional works by migrant women writers, centring the migrant body as a core site of gendered, racialized, and transnational power negotiation, exploitation, and resistance. Spanning five interwoven chapters, the study traces a thematic progression from male migrants’ socio-economic precarity and bodily marginalization to female migrants’ layered quests for belonging, sexual subjectivity, marital agency, and cross-cultural solidarity. Chapter One establishes an analytical baseline via metamorphosis and gaze subversion, highlighting the vulnerable male migrant body in women’s writing. Chapter Two explores “return” as a response to rootlessness, revealing the psychological un-recoverability of the homeland and an alternative return to Eastern Buddhist-Taoist philosophy. Chapter Three examines female sexual subjectivity as emerging not through linear Western emancipation but via imitation, sacrifice, rupture, and utilitarian coping. Chapter Four analyses migrant marriages as sites of power imbalance, where the female body becomes a locus of gendered labour displacement, exploitation, and resistance. Chapter Five explores “sisterhood” from internalized misogyny to cross-racial, cross-class solidarity. The thesis reveals that the conflicting roles of the literary “body” align with the complexity of Chinese women’s migrant identities, and that “writing a migrant body” is a unique tool to expose and resist multiple pressures. It argues that Sinophone fiction by 1990s migrant women reclaims the female body from Western Orientalist stereotypes and redefines migrant identity through nuanced portrayals of resistance and agency, revealing female solidarity as a vital form of empowerment. Migrant identity and feminist consciousness are iterative processes, forged through repeated engagement with marginalization across all spheres of migrant life.

Turning the gaze towards the monstrous: Alternative visions of humanity in the works of Virginie Despentes, Julia Ducournau and Paul B. Preciado

2026-01-01T00:00:00Z

Turning the gaze towards the monstrous: Alternative visions of humanity in the works of Virginie Despentes, Julia Ducournau and Paul B. Preciado Smith-Davies, Beaudicea This thesis examines the work of three contemporary Francophone artists: Virginie Despentes, Julia Ducournau, and Paul B. Preciado. It uses the monster of Mary Shelley’s Frankenstein as a model to analyse the monsters in the texts and films of these three artists. It argues for an all encompassing and universal monstrosity, which transcends binary oppositions and speaks to the whole of humanity.

The Unrealised Potential of AI Solutions for Pasture-based Dairy Systems

2026-01-01T00:00:00Z

The Unrealised Potential of AI Solutions for Pasture-based Dairy Systems Azubuike, Blessing Nnenna Efficient management of pasture-based dairy systems can benefit substantially from integrating individual cow supplementation, real-time pasture monitoring, and grazing event detection, but traditional herd-level approaches cannot address the biological variation and dynamic pasture growth inherent in commercial operations. This thesis developed and validated AI and machine learning methods across three interconnected domains, establishing empirical foundations for integrated precision management. Feeding optimisation was addressed through two studies. A Random Forest model combined with Differential Evolution reallocated concentrate to 81 cows across 91 days, achieving an 8% theoretical milk yield increase without additional feed cost (Chapter 3). Four evolutionary algorithms applied to 1,053 training cows and 165 optimised cows over 30 days achieved 6.63 to 8.64% theoretical yield improvements, with NSGA-II outperforming all others across 10 runs (Chapter 4). These gains are predictive estimates; controlled field validation remains necessary. Pasture biomass estimation was addressed through satellite and smartphone-based approaches, both validated against rising plate meter ground truth. An XGBoost model trained on Sentinel-2 imagery from 16 farms achieved R² = 0.70 and MAE = 216 kg DM/ha, outperforming the commercial Pasture.io platform (Chapter 5). These estimates supported automated grazing event detection across 12 farms, where Random Forest achieved within-year F1 = 0.878 and One-Class Support Vector Machine achieved cross-year F1 = 0.692, outperforming supervised models by 7.6% on Year 2 data despite average 24.2% supervised degradation (Chapter 6). Smartphone imagery achieved R² = 0.561 as a low-cost complement sensitive across high-biomass ranges where satellite indices saturate (Chapter 7). Each domain functions independently on commercial farms, though the integrated system linking all three in real time remains the frontier for future research.

Linguistic Landscapes, Assemblages, and Affective Regimes in Chongqing’s Public Transport Hubs: From Transit Spaces to Meaningful Places

2026-01-01T00:00:00Z

Linguistic Landscapes, Assemblages, and Affective Regimes in Chongqing’s Public Transport Hubs: From Transit Spaces to Meaningful Places Liao, Ke This thesis examines how the linguistic landscape (LL) shapes the social functions of public transport hubs and generates patterned affective experiences in Chongqing, a megacity in Southwestern China. Responding to the largely quantitative focus of prior LL research in China, this thesis advances an interpretive and theoretical informed analysis of how signage mediates relations among people, space, affect, and mobility. Drawing on three rounds of large-scale data collection, this thesis first maps the categories, spatial distribution, and linguistic composition of signage across six major transport modes. This quantitative overview identifies key semiotic features and notes changes in the institutional and social functions of these transport hubs. Building on this foundation, an in-depth qualitative analysis of Chongqing North High-Speed Railway Station employs Pennycook’s (2017) assemblage and Scollon and Scollon’s (2003) geosemiotics framework to examine the dynamic interactions among linguistic and semiotic resources, passengers, and differentiated spatial zones. The analysis is further extended to Jiangbei International Airport, where Wee and Goh’s (2019) concept of affective regimes is integrated with Bourdieusian notions of affect and capital to elucidate how passengers’ emotions are structured, circulated, and rendered socially productive across interconnected online and offline contexts. Overall, this thesis demonstrates how LL transforms transport hubs from sites of transit into multifunctional and meaningful places through co-constitutive sign–people–space relations. It also shows how affect is institutionally organised and implicated in the production of social functions within regimes of mobility. Empirically, this thesis contributes a rich and systematic corpus to LL research on China and transport infrastructures; theoretically, it advances the integration of assemblage and affect in LL scholarship.

Towards a Framework for Community Stakeholder Engagement with Infrastructure Projects Through Social Media

2025-01-01T00:00:00Z

Towards a Framework for Community Stakeholder Engagement with Infrastructure Projects Through Social Media Zhang, Jingbo In infrastructure projects, systematic engagement with the perspectives and positions of community stakeholders is usually challenging. In this study, social media is introduced as a platform for observing and gathering the voices and attitudes of community stakeholders. Based on traditional stakeholder engagement theory, this research employs naturalistic inquiry to collect data on the organic interactions between stakeholders and projects on social media. It analyses and summarises stakeholder engagement patterns on social media, introducing a novel framework of stakeholder sentiment and emotion analysis. This theoretical framework includes a new social media dialogue model. It employs two main analytical tools: categorical grouping of online community stakeholders and a stakeholder emotion matrix based on social media data. The model also categorises the online response strategies for projects based on the output of these tools. This study supplements current stakeholder engagement theory by providing a framework to guide online stakeholder engagement. The theoretical framework outlines the general environment for online stakeholder engagement, offers essential elements and steps for project stakeholder dialogues, and provides appropriate theories and methods for different dialogue stages and steps. It offers new perspectives and theories for future research on online stakeholder engagement. The novel social media stakeholder framework proposed in this study can be applied to project stakeholder engagement practices, providing new analytical tools and response strategies for studying community stakeholder engagement via social media, which will enable practitioners to use social media to carry out community stakeholder engagement for projects more efficiently.

Young active galaxies across the radio spectrum

2026-01-01T00:00:00Z

Young active galaxies across the radio spectrum Kerrison, Emily Florence The lifecycle of active galaxies is an open question in modern astronomy. In particular, not all active galaxies are active radio galaxies, in possession of synchrotron-emitting jets, and it is not obvious why. This thesis focuses on these active radio galaxies, and was completed as part of the First Large Absorption Survey in HI conducted with the Australian SKA Pathfinder (ASKAP-FLASH). Early on, we realised many HI detections in ASKAP-FLASH were made towards so-called 'Peaked Spectrum' sources, active galaxies in which the synchrotron jets are still embedded in the dense, nuclear gas of their host galaxy. The thesis presents a new Bayesian framework for identifying peaked spectrum sources using pre-existing radio survey data, RadioSED. Applying RadioSED to a test field, we increase the number of known peaked spectrum sources by more than an order of magnitude in that area through careful treatment of pre-existing datasets. We investigate the multiwavelength properties of this sample, and identify that many of them are distant, making them interesting probes of the physical conditions at cosmic noon and beyond. We then take early results from the ASKAP-FLASH Pilot Surveys and use a new pipeline for mock observations, SANGRiA, to determine whether we can recover the high observed HI detection rate towards compact jets in simulations, under the assumption that it is a purely geometrical effect. Finally, this thesis presents a multiwavelength study of a different type of radio AGN detected in HI with ASKAP-FLASH, demonstrating the gains to be made by multi-wavelength follow up of HI detections, and revealing at least three intervening galaxies along that line of sight, one of which is the likely host of the HI. Overall, this thesis reinforces the key role of peaked spectrum sources in studies of active galaxy evolution, jet-gas interactions, and the changing distribution of gas across the different ages of our Universe. Includes publication

Critical point network-based organizational principle of cortical spatiotemporal dynamics

2026-01-01T00:00:00Z

Critical point network-based organizational principle of cortical spatiotemporal dynamics Xu, Yiben Inspired by the field of turbulence and vector field topology in neural activities, this thesis introduces a novel and generalizable organizational principle of cortical spatiotemporal dynamics based on a global network of interacting critical points. Starting from the analysis of human fMRI signals, this thesis highlights the discovery of travelling cortical spiral waves (termed ‘brain spirals’) during both the resting and task states, emphasizing the mechanistic and functional relevance of a novel spiralbased organizational principle of large-scale brain activities. Next, based on human high-density electroencephalography (HdEEG) recordings, this thesis extends the spiral-based organizational principle from wakefulness to non-rapid-eye-movement (NREM) sleep, revealing that this spiralbased organizational principle is also a defining feature of human N2 sleep, which is associated with sleep-dependent-memory-consolidation and aging-related memory decline. Finally, this thesis further expands the spiral-based organizational principle to include other types of critical points (i.e., sinks, sources and saddles), two new recording modalities (Magnetoencephalography/MEG and Electrocorticography/ECoG), and intracranial recordings of non-human primates (marmoset). In two distinct datasets, a global network of interacting critical points can be consistently observed regardless of species, recording modalities and cognitive states. Acting like an organizational skeleton, this network of critical points collectively enables the task-dependent organizations of largescale brain activities, supporting the universal presence of a critical point network-based organizational principle of large-scale brain activities across species.

Greenwashing: Regulatory Enforcement, Prevention and Detection

2026-01-01T00:00:00Z

Greenwashing: Regulatory Enforcement, Prevention and Detection Peng, Shiyao The prevalence of sustainability disclosures is rapidly increasing, with many such disclosures becoming mandatory across major jurisdictions. At the same time, greenwashing – defined as misleading sustainability claims exaggerating or misrepresenting environmental or other sustainability performance – has proliferated. This has attracted intensified global regulatory scrutiny. Despite academic interest, there is limited knowledge about how regulators identify, assess, and sanction greenwashing claims in practice. The thesis addresses this gap, examining greenwashing through a regulatory lens. In so doing, unique greenwashing datasets are systematically constructed, including a dataset of global greenwashing regulatory enforcement cases between 2015-2024, as well as a greenwashing taxonomy consolidated from eight regulatory guidelines. These datasets provide the thesis’ conceptual and empirical foundation, clarifying how greenwashing is characterised in academic research and regulatory action. Building on this foundation, the thesis comprises three interconnected studies investigating: (1) how regulators define, interpret, and act against greenwashing; (2) whether sustainability assurance potentially reduces greenwashing by addressing regulator-relevant subject matters; and (3) how generative large language models (LLMs) can support large-scale automated detection of greenwashing based on regulatory indicators. Includes publication

Carbonate sequestration in the Pacific, Indian and Atlantic oceans over the Cenozoic

2026-01-01T00:00:00Z

Carbonate sequestration in the Pacific, Indian and Atlantic oceans over the Cenozoic Dalvand, Faranak This thesis reconstructs the regional evolution of the carbonate compensation depth (CCD) across the Pacific and Indian oceans during the Cenozoic. Using lithological, carbonate, and paleo-depth data from DSDP, ODP, and IODP drill sites, regional CCD variability was modelled through time. The results reveal strong spatial differences linked to ocean circulation, tectonic gateway changes, Antarctic glaciation, atmospheric CO₂ fluctuations, and climate transitions. The Pacific Ocean records major Neogene CCD fluctuations associated with gateway reorganisations and the late Miocene biogenic bloom, while the Indian Ocean shows significant variability related to Indo-Pacific circulation and monsoon intensification. This thesis also presents the first basin-specific synthesis of carbonate accumulation rates across the Atlantic, Pacific, and Indian oceans since the Cretaceous, highlighting major inter-basin differences in pelagic carbonate burial. The findings demonstrate that long-term carbonate preservation and oceanic carbon storage were strongly controlled by tectonic evolution, deep-water circulation, and global climate change, providing new insights into the evolution of Earth’s carbon cycle and climate system through geological time. Includes publication

Rebuilding Public Trust in Social Media Platforms? A Case Study of Meta’s Oversight Board

2026-01-01T00:00:00Z

Rebuilding Public Trust in Social Media Platforms? A Case Study of Meta’s Oversight Board Cao, Rumeng Social media platforms have become an integral part of everyday life. Power within the digital environment has become concentrated in a few dominant platforms because of user behaviour and platform design. This concentration allows these platforms to exert a strong influence on civic discourse and the public sphere. However, the growing prevalence of misinformation has transformed how public discussions unfold online. Companies, such as Meta, have faced ongoing criticism for permitting harmful content to spread and for their misuse of user data. These companies’ ineffective responses to these issues have further undermined public trust. Trust plays a crucial role in the digital era. It determines whether users remain active and engaged on social media platforms. To restore public trust, Meta established the Oversight Board as an independent body to review user appeals for removing their content and to enhance transparency and accountability in content moderation. This thesis investigates the effectiveness of Meta’s Oversight Board and examines its decision-making processes. Following the platform regulation triangle theory, this study employs the methodology of document analysis and semi-structured interviews. This study analyses Facebook’s regulatory history from 2010 to 2020 and evaluates Meta’s current strategies for addressing misinformation. This study’s findings contribute to broader debates on platform regulation and offer practical insights for other social media platforms seeking to improve content governance.

Investigating the use of steroids in children with Infantile Epileptic Spasms Syndrome: A multi-omics evaluation of gene and epigenetic regulation

2026-01-01T00:00:00Z

Investigating the use of steroids in children with Infantile Epileptic Spasms Syndrome: A multi-omics evaluation of gene and epigenetic regulation Innes, Emily Amy Objectives: Infantile epileptic spasms syndrome (IESS) is a severe developmental and epileptic encephalopathy of infancy. High-dose oral prednisolone may induce epileptic spasm remission yet long-term outcomes remain poor and it remains unclear whether steroids are targeting disease mechanisms. We investigated the biological pathways underlying IESS and how prednisolone treatment exerts an effect in IESS. Methods: A multi-omics analyses compared blood samples from infants with IESS at baseline (n=11) to controls (n=11) and IESS pre-post prednisolone treatment (n=11). Analyses included bulk RNA sequencing, proteomics, phosphoproteomics and neuroinflammation panel testing. Pathway enrichment analysis using GSEA and ORA identified significantly enriched pathways based on FDR-adjusted p-values. Results: Infants with unknown aetiology had better developmental outcomes than infants with structural aetiologies. Prednisolone induced significant leukophilia, neutrophilia and lymphopenia (all adjusted p-value <0.05). BDNF was significantly elevated at baseline, and prednisolone caused significant increase in nerve growth factor, and significant decrease in the chemokine CCL2. Using RNA seq, prednisolone reversed baseline upregulated ribosomal and mitochondrial pathways, and reversed baseline downregulated immune and membrane transport pathways. Using concordance of quantitative RNA and protein to explore the effects of prednisolone, the most upregulated pathway was 'secretory granule membrane' and the most downregulated pathway was 'ribonucleoprotein complex biogenesis'. Phosphoproteomics revealed the most dysregulated pathway at baseline and after prednisolone was 'chromatin binding'. Significance: Altered gene and epigenetic regulation may be an aetiological mechanism underlying IESS. Prednisolone treatment may control epileptic spasms by altering gene expression through immune-mediated, ribosomal and chromatin pathways.

Compassion Satisfaction and Compassion Fatigue in Australian Rural and Remote Rehabilitation Healthcare Workers

2026-01-01T00:00:00Z

Compassion Satisfaction and Compassion Fatigue in Australian Rural and Remote Rehabilitation Healthcare Workers McGrath, Kelly Lucinda Background. Australian rural and remote rehabilitation healthcare workers operate within insurance-based frameworks with standardised KPIs that do not consider the complexities of rural and remote practice. They face isolation, travel, limited resources, and hazardous conditions that affect professional quality of life, including compassion satisfaction (CS) and compassion fatigue (CF), which comprises burnout and secondary traumatic stress (STS). Aim. To examine, for the first time, levels, experiences, risk and protective factors of CS and CF in this work cohort. Methods. The Professional Quality of life (ProQOL) model guided three studies: a scoping review (n=12 studies), semi‑structured interviews (n=16), and a national mixed‑methods survey that included the ProQoL5 scale (n=29). Each informed the next study. Volunteer participants were rural and remote rehabilitation healthcare workers and registered members of their professional body. Results. No studies specific to rural and remote rehabilitation healthcare workers were found by the scoping review; research focused on medicine and nursing, where CS, CF, and burnout were linked to negative work and environmental factors. Interviews revealed that poor support and safety cultures normalised WHS risks. Survey findings showed lower CS, higher burnout and worse STS than mostly urban Australian healthcare workers Organisational impacts included poor work-life balance and work culture. Conclusions. Rural and remote rehabilitation healthcare workers may experience lower CS and higher CF than urban colleagues. Reported organisational factors align with psychosocial hazards identified in Safe Work Australia legislative updates. The ProQOL5 scale may not fully capture these hazards and therefore needs to be validated in this cohort. Addressing organisational conditions through supervision and workload management is important for workforce sustainability. Includes publication

Memory, Perception & the Art of Seeing Double

2007-01-01T00:00:00Z

Memory, Perception & the Art of Seeing Double Brollo, Deidre This project seeks to examine the role of memory in the viewing of art, in a thesis, ‘Memory, Perception & the Art of Seeing Double’, and an exhibition, ‘the return room’. Drawing on the writings of Henri Bergson and Marcel Proust, the discussion argues for the interrelationship of perception and memory. In contending that perception is inherently bound up with memory, it argues that all artworks have the potential to elicit acts of recollection in the viewer. These acts of recollection should not be understood as an individual reverie detached from the world, but rather as a sort of introspective engagement, an act of viewing that encompasses both the present moment and a past one, in which individual recollection is brought to bear upon the artwork. It is therefore a process of seeing double. Subsequent chapters investigate the use of forms of memory technology in art, looking firstly at the privileged though problematic forms of the photograph and the public memorial. This is followed by an examination of text, maps, and books. The exhibition ‘the return room’ consists of an installation of artists’ books in a specially constructed room reminiscent of both a domestic and a gallery space. It draws on the idea of the palimpsest as a site in which other traces are visible, while also having the potential to be read as a form of memory theatre. The exhibition employs the forms of memory technology discussed in the thesis, with text, maps, and photographs, used within the books. This project, then, claims to be original in the following ways. It claims that Proust and Bergson’s demonstration of the interrelation of memory and perception has important implications for the role of memory in the viewing of all artworks. Secondly, this project draws attention to the possibilities of other forms of memory technology (text and maps) which have not been previously discussed in an art context with regard to their mnemonic potential in relation to the viewer. Thirdly, emphasising that memory is about the juxtaposition of past and present moments, the discussion here offers the models of the palimpsest and the stereoscope as useful conceptual models to describe the ‘art of seeing double.’ Finally, in taking a broad approach to the concept of the artist’s book, the project suggests that the idea of the book may move beyond its boundaries, and that the idea of the palimpsest can be applied in an extended sense to installation space. Includes publication

Mathematical Models for Immune Checkpoint Blockade and Delayed Responses

2026-01-01T00:00:00Z

Mathematical Models for Immune Checkpoint Blockade and Delayed Responses Zheng, Collin Yarmeng Immune checkpoint blockades have transformed oncology, yet a persistent clinical puzzle remains: Why do some patients exhibit delayed responses, with tumours that initially grow or plateau before abruptly regressing? This thesis tackles that question with a multi-scale mathematical study that couples analytically tractable ordinary differential equation (ODE) models with a spatial, stochastic agent-based model (ABM). In ODE form, we show that delayed responses can arise intrinsically, without imposed time lags, via costimulation bottlenecks and slow passages near tipping points associated with special saddle-node bifurcations. We map delayed responses to a statistically-thin part of the model parameter space, suggesting their rarity. Our ODE results enable us to propose an immune profile framework that maps patient prognosis to the natural strength of their immune system---an idea that has become increasingly popular in clinical research since COVID-19. To move beyond mean-field assumptions, we develop an ABM tracking cancer cells, dendritic cells (DCs), CD8+ T cells, and Tregs at single-cell resolution, with molecular attributes and cell-level rules. Mechanistically, our ABM explains why combination therapy outperforms monotherapy: anti-CTLA-4 'reopens the gate' while anti-PD-1 'lifts the brake', yielding a larger and fitter effector CD8+ T cell pool. Our results supports two hypothesised mechanisms of action underlying CTLA-4 blockades---Treg depletion in humans and Treg-driven stripping of B7 ligands---highlighting how depleting suppressors and protecting strategically-important ligands reopen the costimulatory pathway. We characterise delayed responses as an alignment of a multitude of immune events, followed by a fast cascade of killing. This suggests that DC therapies prioritising net DC recruitment and T cell therapies that prioritise tumour-infiltrating lymphocyte (TIL) survivability synergise well with immune checkpoint blockades.

Animating the “Outside”: a Tripartite Model of Analysing 1960s Jazz

2026-01-01T00:00:00Z

Animating the “Outside”: a Tripartite Model of Analysing 1960s Jazz Clarkson, Timothy Nicholas Garrett The revolutionary change in jazz improvisation of the 1960s featured a sudden increase in the degree and duration of departure from pre-composed forms. This practice, commonly known as “outside” playing, has generally been interpreted in musicology and music theory through the lens of “dissonance.” Black radical scholars claim a different, Afrological ontology of dissonance, distinct from the Eurological ontology and philosophy that underpins most mainstream music theory. In this thesis, I argue that a music-theoretical focus on outside playing’s technical dimension has produced a Eurological attunement in discussions of 1960s jazz, neglecting its interactive dimension and cultural practice. Benjamin Givan’s alternative conception of “apart” playing foregrounds interactivity through layers of relationships between musicians working in a group dialogue with composed materials (the “referent”). Black radical discourse more strongly foregrounds the cooperative togetherness that “apart” playing requires, and resists the necessity for resolution and unity. I adopt Fred Moten’s use of “appositional” playing to reflect both these dimensions of improvisational practice and its cultural resonances. I develop new animated music-theoretical tools that innovatively redeploy the Neo-Riemannian Tonnetz to illuminate the dynamic nature of “appositional” playing outlined above. My rationale is anchored in Eric Isaacson’s argument for advantages of animation over still images in engaging temporal relationships. Two case studies investigate strategies within John Coltrane and Ornette Coleman’s ensembles for problematising the referent, developing evidence supporting the sonic phenomena listeners have regularly identified as “transcendence” and “freedom” in their music. These case studies demonstrate the unique advantage of animated tools for investigating the technical and interactive layers of “appositional” playing, and for tying this evidence to the music’s socio-cultural moment.