http://hdl.handle.net/10453/19979 2026-10-22T22:54:12Z http://hdl.handle.net/10453/197244 Title: “Do It Fuh d’Gram” The Influence of Gender Dynamics on the Content of Social Media Influencers and Consumers in Trinidad & Tobago Authors: Le Blanc, Ave Abstract: This PhD thesis examines how gender dynamics shape the practices and experiences of Social Media Influencers (SMIs) and the responses of their consumer followers within the SMI domain in Trinidad and Tobago (T&T). It analyses discourse in SMI produced content and draws on narrative interviews with both SMIs and consumers. Research shows that SMIs with marginalised identities, such as women, those outside the Global North, and those racialised or disabled, often face harmful gendered feedback online. This backlash shapes how they present themselves and influence within the SMI domain. Some self censor, while others resist through self expression. Scholars have called for deeper exploration of how consumers, brands, and social media platforms shape these dynamics, particularly at the intersections of multiple identities. Guided by Crenshaw’s intersectionality framework and Caribbean feminist scholarship, this study uses two data stages: (1) a Feminist Critical Discourse Analysis of content from 40 SMIs, and (2) narrative interviews with 21 SMIs and 20 consumers, all drawn from this original sample. Findings, presented across three articles, show how SMIs negotiate identity, challenge gendered expectations, and shape influence within the SMI domain. The thesis offers theoretical, practical, and methodological contributions to SMI gender marketing, social marketing, and Global South scholarship. Description: University of Technology Sydney. Faculty of Business. 2026-01-01T00:00:00Z http://hdl.handle.net/10453/197243 Title: Advanced Recommendation Systems for Overcoming Cold Start and Data Sparsity Challenges Authors: Huang, Yuanming Abstract: Recommender systems alleviate information overload by delivering personalised content, yet their effectiveness in real platforms is frequently constrained by imperfect signals, including sparse user–item interactions, item cold-start, and non-stationary user behaviour. Moreover, as modern recommender systems increasingly rely on item-side content, missing or degraded modalities further distort representation learning and fusion. This thesis studies robust recommendations under these practical imperfections through three interconnected contributions that progress from temporal modelling to structural representation enhancement, and finally to missing-modality robustness. Non-stationary user behaviour is examined through the lens of sequential recommendation with long interaction histories. It introduces a state-space-based sequential architecture augmented with a wavelet frequency rescaling mechanism, enabling frequency-aware adaptation to dynamic user behaviours while maintaining efficient modelling of long-range dependencies. Interaction sparsity is investigated from an item representation perspective in graph-based recommendation. It proposes a graph learning framework that injects global relational priors via fuzzy clustering and strengthens item representations beyond local neighbourhood aggregation, improving robustness when collaborative signals are limited or unevenly distributed. Item cold-start is further studied in multimodal recommendation, where item content modalities may be incomplete, inducing a completeness shift between complete and incomplete items and entangling modality-invariant and modality-specific information. It proposes a modality-adversarial generative enhancement framework that reconstructs missing modalities from observed ones, aligns complete–incomplete distributions through domain-adversarial learning, and disentangles invariant versus specific signals via mutual-information regularisation to support more reliable multimodal fusion. Taken together, these three studies demonstrate that robust recommendations in realistic settings benefit from jointly addressing non-stationary temporal dynamics in user behaviour, globally informed structural modelling under interaction sparsity, and distribution-aware generation and fusion under missing modalities. By connecting frequency-aware sequential modelling, fuzzy-structured graph representation learning, and completeness-shift-aware multimodal enhancement, this thesis provides a coherent framework for building recommender systems that remain dependable when data are sparse, behaviours evolve, and content is incomplete. Description: University of Technology Sydney. Faculty of Engineering and Information Technology. 2026-01-01T00:00:00Z http://hdl.handle.net/10453/197236 Title: Optimising Liquid Biopsy Technologies for Improved Cancer Monitoring Authors: Salomon, Robert Abstract: Liquid biopsy offers a minimally invasive alternative to traditional tissue biopsies. This research focuses on optimising technologies for the analysis of circulating tumour cells (CTCs) and circulating tumour DNA (ctDNA) with a focus on implementation in paediatric oncology. The scope of this work encompasses the use of microfluidics for blood fractionation and CTC enrichment, the clinical requirements for ctDNA-based testing, and the practical application of next-generation ctDNA assays in neuroblastoma. Regarding CTCs, this thesis establishes a comprehensive framework for categorising microfluidic tools based on their mechanisms of action and is designed to enables labs to choose the right tool for the biological question being asked. A novel quantitative method using flow cytometry was developed to evaluate the performance of Microfluidic CTC enrichment devices. This method proved superior to traditional imaging-based approaches by providing reproducible, quantitative data on purity and separation efficiency within complex mixtures. Evaluations of the Bio-Rad Genesis system and a bespoke 3D-printed inertial focusing device revealed that both were unsuitable for broad clinical use in paediatric oncology due to clogging, low purity, and manufacturing inconsistencies. This work identifies the limitations of these approaches and defines key areas for improvement in clinical implementation. Regarding ctDNA, the research explores current and future clinical applications through a survey of healthcare professionals, revealing a strong belief in its clinical value despite low current utilization. Finally, the thesis demonstrates the utility of a neuroblastoma-specific ctDNA panel in informing clinical management for high-risk patients. These findings underscore the potential of ctDNA based liquid biopsy to enable personalised medicine and thus improve outcomes for children with cancer. Description: University of Technology Sydney. Faculty of Science. 2025-01-01T00:00:00Z http://hdl.handle.net/10453/197235 Title: Military Veterans’ Career Transition to Entrepreneurship: The Interplay of Identity Work, Support Networks, and Institutional Factors Authors: Atkins, Rachel Abstract: NO FULL TEXT AVAILABLE. Access is restricted indefinitely. Description: University of Technology Sydney. Faculty of Business. 2025-01-01T00:00:00Z