Electronic Theses and Dissertations (ETD)

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All theses from 2011 to the present are in this collection, as well as some from 2010 and earlier years.

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Physical activity mHealth tailored to postpartum individuals with lumbopelvic pain
(2026) Hollman, Heather; Rhodes, Ryan E.
Background: Postpartum moderate-to-vigorous intensity physical activity (MVPA) is essential for the health of the birth parent, their future pregnancies, and their children. Unfortunately, over 55% of postpartum individuals are not meeting recommended MVPA guidelines and face significant barriers to MVPA participation such as lack of childcare, sleep, and time. Up to 67% of postpartum individuals suffer from lumbopelvic pain (LPP) which can affect their ability to be active. Mobile health applications (mHealth apps) have great potential for promoting MVPA amongst postpartum individuals; however, those currently available lack quality and evidence-based recommendations and have limited effectiveness and engagement. Objectives: To design and develop an evidence-based, acceptable, usable, feasible, scalable, and low-cost MVPA promotion mHealth app tailored to postpartum individuals with LPP. A series of three studies, following the IDEAS (Integrate, Design, Assess, and Share) framework, were conducted to meet this overarching objective. Methods: This proposal consists of six chapters. Chapter 1 provides an introduction with a brief overview of the background literature and dissertation objectives. Chapter 2 provides a more thorough background literature review. Chapter 3 is a systematic review of mediators of postpartum PA behaviour change interventions. Chapter 4 is a cross-sectional study to determine predictors of MVPA intention-PA translation among postpartum individuals. Chapter 5 is a co-design study, in partnership with key knowledge users (i.e., individuals with lived expertise of postpartum LPP and healthcare providers) to tailor a previously existing theory-informed and evidence-based MVPA promotion mHealth app to postpartum individuals with LPP. Chapter 6 is a general discussion to synthesize the findings of the aforementioned three studies and make suggestions for future directions. Significance: The findings of this research program illuminates the unique barriers, needs, and considerations for MVPA and mHealth when intervening with postpartum individuals with LPP. They also inform future large scale trials with the ultimate intents of optimizing health and reducing chronic disease for postpartum individuals themselves, their future pregnancies, and their children.
A factor analytic investigation of allostatic load and associations with cognitive performance
(2026) McDowell, Cynthia; MacDonald, Stuart Warren Swain
Introduction: Allostatic load (AL) reflects the cumulative physiological burden resulting from long-term chronic stress and has been linked to a range of adverse health outcomes, including cognitive impairment. However, operationalizing and measuring AL – requiring the integration of heterogeneous biomarkers across distinct physiological systems into a single unified construct – remains a significant methodological challenge. Research applying latent factor modeling to examine the underlying structure of AL is particularly limited, especially in older adults, despite AL being conceptualized as a cumulative, multisystem, and protracted process. Objectives: The present dissertation addressed two primary research questions: (1) Which latent factor structure best indexes AL in older adulthood? and (2) Is this AL latent factor model associated with individual differences in cognitive performance? Methods: Seventeen biomarkers spanning four physiological systems (cardiovascular, anthropometric, metabolic, and inflammatory) were analyzed in a large sample (N = 12,646) of community-dwelling adults aged 65 and older (Mage = 73.10 years; 50.13% Males). Four distinct AL measurement models were tested and compared using confirmatory factor analysis to identify the model of best fit for males and females separately. Structural equation modeling was then used to examine whether the final latent AL factor was associated with six cognitive tasks spanning executive functioning, memory, and psychomotor processing speed domains, while adjusting for age, education, and total medication use. Results: A bifactor model with relaxed orthogonality constraints emerged as the best-fitting structure for both sexes, whereby biomarkers loaded onto both a general AL factor and system-specific latent factors. In males, tumor necrosis factor alpha (TNF-α) and interleukin-6 (IL-6) were the strongest contributors to the general AL factor, highlighting the central role of inflammatory processes in males. In females, triglycerides and high-density lipoprotein (HDL) cholesterol were the strongest indicators of AL, suggesting that lipid dysregulation may be more salient in the expression of AL among aging females. Using this bifactor model structure, the general AL factor was significantly associated with individual differences in performance across all three cognitive domains in both sexes, even after adjusting for covariates. Conclusion: This dissertation provides an empirically rigorous and theory-informed modeling approach that advances both the conceptual and methodological foundations of AL research. The findings highlight the value of a latent AL factor for capturing individual differences in cognitive health and provide key insights for measuring multisystem dysregulation, understanding sex-specific biological differences, and enhancing early identification of cognitive vulnerabilities linked to chronic stress in older adults.
Rewiring co-stimulatory receptors with targeted antibody agonists to improve cell therapy against cancer
(2026) Goodwin, Sydney; Nelson, Brad H.; Smazynski, Julian
Adoptive cell therapies (ACTs) have transformed cancer treatment, yet their efficacy is often limited by poor T cell persistence and sustained functionality. Effective anti-tumour immunity requires durable co-stimulatory signalling, particularly through pathways such as CD28, while inhibitory checkpoint pathways including PD-1 and CTLA-4 suppress T cell activity within the tumour microenvironment. Although immune checkpoint inhibitors (ICIs) can relieve inhibitory signalling, they remain dependent on pre-existing anti-tumour immunity. One potential approach involves the use of agonistic antibodies to stimulate co-stimulatory receptors on T cells; however, systemic administration of co-stimulatory agonists is associated with significant toxicity due to indiscriminate activation of endogenous immune populations. Another attractive approach is the use of switch receptors that combine the extracellular domain of a checkpoint protein with the intracellular domain of a co-stimulatory protein, such that endogenous ligand binding delivers a targeted stimulatory signal to adoptively transferred T cells. However, switch receptors are limited by endogenous ligand expression that varies between patients and cancer types, reducing their versatility and predicted efficacy. To address these limitations, we hypothesized that clinically approved ICIs could be repurposed as selective activators of chimeric co-stimulatory receptors (CCRs), enabling antibody-mediated enhancement of adoptively transferred T cells while avoiding broad systemic immune activation. To test this hypothesis, we engineered multiple CCR constructs fusing the extracellular domains of immune checkpoint proteins (PD-1, PD-L1, and CTLA-4) with the intracellular domain of CD28. Human T cells expressing these CCRs were evaluated for functional activation following stimulation by clinically relevant ICIs. In vitro, CCR-expressing T cells demonstrated robust activation in response to checkpoint antibodies, including enhanced IL-2 secretion, proliferation, and cytotoxicity that exceeded responses induced by conventional CD28 agonist antibodies. These findings established that ICIs can be functionally repurposed to deliver potent co-stimulatory signals through our engineered receptors. However, despite strong in vitro activity, in vivo adoptive transfer studies in NSG mouse models revealed a profound and unexpected loss of CCR-expressing T cells following systemic ICI administration. This depletion occurred across multiple CCR constructs and antibody subclasses, suggesting that antibody engagement may trigger deleterious immune-mediated mechanisms that override the intended co-stimulatory effects. Mechanistic studies investigating antibody Fc interactions demonstrated that Fc engineering strategies altered these effects in vitro but did not restore CCR+ T cell persistence in vivo. These findings implicate complex contributions from Fcγ receptor interactions, complement activation, and/or other immune processes. Collectively, this work establishes checkpoint-converting CCRs as a novel and conceptually compelling platform to improve cellular immunotherapies, while also identifying a major translational barrier to their implementation. More broadly, this thesis highlights the importance of Fc biology, host immune interactions, and preclinical model selection in the development of antibody and cell-based combination strategies. Although substantial mechanistic challenges remain, resolving the pathways responsible for CCR+ T cell depletion may enable the future development of next-generation ACT platforms that leverage existing clinically approved immunotherapies to enhance anti-tumour responses.
Evaluation of gold nanoparticles and docetaxel as radiosensitizing agents to improve current radiotherapy treatments
(2026) Jackson, Nolan; Chithrani, Devika
Radiotherapy (RT) remains an important form of cancer treatment in the regimens for many cancer patients. Despite substantial technological advancements in external beam radiotherapy (EBRT), tumor control and long-term survival outcomes can remain sub-optimal. A primary limitation arises from normal tissue toxicities, which constrain the maximum radiation dose that can be safely delivered. As a result, strategies that can enhance tumor response without increasing the administered dose are highly desirable. Radiosensitizers represent one such approach, offering the potential to improve the therapeutic ratio by increasing tumor sensitivity to radiation. In this context, gold nanoparticles (GNPs) and docetaxel (DTX) present a promising combination, leveraging complementary physical and biological mechanisms to enhance the effects of RT. The initial evaluation of this strategy was conducted using monolayer cell culture models to assess mechanistic insight. DTX treatment was shown to induce cell cycle synchronization in the G2/M phase, a stage known to exhibit increased radiosensitivity. In addition to these effects, DTX significantly enhanced the intracellular accumulation of GNPs, with PC-3 and MIA PaCa-2 cells demonstrating 34% and 49% increases in GNP concentration, respectively, compared to untreated controls 24 h after exposure to both agents. When combined with RT delivered using a clinically relevant 6 MV linear accelerator, this resulted in an enhanced radiation response, with the combined treatment increasing DNA damage foci by approximately 80% and 130% in PC-3 and MIA PaCa-2 cells, respectively. This was further associated with reduced cellular proliferation, where the addition of GNPs to DTX-treated cells combined with RT reduced cell growth by 15% and 10% three days after irradiation. These findings demonstrated that the combination of GNPs and DTX can effectively enhance radiosensitivity under controlled in vitro conditions. To further evaluate the translational potential of this approach, studies were extended to more physiologically relevant models, including 3D spheroids and in vivo xenograft tumors. Spheroid models incorporate key features of the tumor microenvironment (TME), such as extracellular matrix deposition, cell–cell interactions, and concentration gradients, which introduce barriers to nanoparticle (NP) penetration and influence treatment response. Despite these additional barriers, DTX retained its ability to induce cell cycle arrest and continued to enhance GNP accumulation. Importantly, the combined GNP/DTX strategy improved response to RT in spheroid models, where the addition of GNPs to DTX/RT resulted in a 20% reduction in spheroid size in both MIA PaCa-2 and PC-3 models compared to DTX/RT alone. These findings were further supported in xenograft tumors, where DTX increased tumor GNP accumulation by greater than 100% at 24 h post-injection. This translated into improved tumor response to RT, with the triple combination reducing tumor growth by 34% in MIA PaCa-2 tumors and 54% in PC-3 tumors compared to RT alone, reinforcing the potential applicability of this strategy in more complex biological systems. Recognizing the limitations of immunocompromised models, the final component of this work investigated GNP biodistribution in immunocompetent, syngeneic tumor models. The presence of an intact immune system was found to significantly alter GNP distribution, resulting in reduced tumor accumulation and increased sequestration in organs such as the liver and spleen. Specifically, less than 1% of the injected dose remained in the plasma 8 h post-injection, and GNP accumulation in KPCY tumors was reduced by 57% compared to MIA PaCa-2 tumors grown in NRG mice. However, DTX was still able to partially improve delivery in this setting, increasing GNP concentration in KPCY tumors by 67% and 75% at 24 h and 48 h post-injection, respectively. Additionally, surface functionalization strategies, including RGD targeting, were shown to influence immune recognition and GNP localization, where RGD-functionalized GNPs demonstrated a greater than 10-fold decrease in tumor accumulation and a 99% reduction in plasma concentration compared to GNP-PEG complexes. These findings highlight the critical role of immune-mediated processes in governing GNP delivery and underscore the importance of evaluating such strategies in immunocompetent models. Collectively, this work demonstrates the potential of combining GNPs and DTX as radiosensitizers while emphasizing the need to consider biological context to optimize their translational success.
Implicit graph theory: Scaling graph mining with vector arithmetic
(2026) Yu, Tengkai; Thomo, Alex; Srinivasan, Venkatesh
The rapid ascent of representation learning has transformed how we model complex systems, replacing discrete identifiers with continuous, high-dimensional vectors. In modern pipelines, relationships between entities, whether users in a recommender system or text chunks in a retrieval corpus, are defined not by explicit links but by geometric proximity in a dense vector space. Because every pair of embeddings yields a non-zero similarity, the induced graph is fully connected by construction, containing O(N^2) weighted edges that no standard adjacency representation can store at scale. Traditional graph mining algorithms, designed for sparse networks, remain tied to the "Explicit Paradigm" of materializing this adjacency matrix before performing computation. For the dense semantic graphs produced by modern embedding pipelines, this imposes a quadratic O(N^2) memory bottleneck that renders standard methods such as Label Propagation and Louvain intractable beyond a few thousand nodes. Common workarounds, such as k-nearest-neighbour pruning, discard precisely the long-range structure that semantic embeddings are meant to capture. This dissertation introduces Implicit Graph Theory, a unified framework that redefines the graph not as a static container of edges, but as a linear algebraic operator defined by the inner product of node embeddings (A = VV⊤). By exploiting the low-rank structure of semantic data, we derive exact matrix-vector formulations for fundamental graph primitives that operate in linear memory in N, without approximation error relative to the inner-product adjacency model. We validate this framework through three contributions. First, we introduce Vector-Based Label Propagation (VLP), which addresses the memory wall for semi-supervised learning on dense graphs. We prove that VLP is mathematically equivalent to explicit label propagation and show that it scales to 1.5 million nodes on a single GPU, in a setting where standard dense-graph libraries exhaust memory beyond roughly 15,000 nodes. Second, we present VLouvain, a structure-discovery algorithm that detects hierarchical communities directly from embedding vectors, without ever generating an edge list. The key result, the Vector Supernode Theorem, shows that modularity-driven graph coarsening reduces to vector addition, reproducing the modularity scores of standard Louvain exactly. VLouvain clusters 1.57 million product embeddings in minutes on a single GPU, a scale at which cuGraph and NetworKit exhaust memory entirely. Finally, we apply these principles to retrieval-augmented generation with GraphRAG-V, which uses VLouvain to organize text-chunk embeddings into semantic communities, replacing the expensive LLM-based entity extraction pipeline used by prior graph-RAG systems. On a multi-hop reasoning benchmark, GraphRAG-V reduces indexing time from 3.0 hours to 5.3 minutes (34x) while outperforming both a vector-store baseline and Microsoft's GraphRAG in answer recall. Together, these results argue for a different way of scaling graph mining to the era of dense representations: rather than storing the graph, we compute it on demand from the embeddings that already exist.
Enhancing self-regulation in emerging adults: Exploring the impact of a self-regulation multi-module intervention on emotion regulation, empathy, executive function and mood/anxiety symptoms
(2026) Hohn, Lillea; Smart, Colette
Self-regulation, the ongoing updating of cognitive, emotional, and behavioural states, is essential for well-being. It encompasses domains like emotion regulation and empathy. Executive function, a related construct, involves cognitive processes such as working memory, inhibition, and cognitive flexibility. Emerging adulthood (ages 18-25) is a critical period where prefrontal cortex maturation supports development of self-regulation skills. While research suggests that these skills are malleable during this period, mixed findings highlight the need to assess intervention efficacy among emerging adults. This study assessed the malleability of empathy, executive function, emotion regulation, and mood/anxiety symptoms following a six-week multi-module self-regulation intervention and further explored whether Adverse Childhood Experiences and Attention-Deficit/Hyperactivity Disorder moderated intervention outcomes. Data from 249 undergraduate students (aged 18-25 years; M =18.84, SD = 1.06) were analyzed. Students either completed surveys only as controls or, if training-interested were randomized to the intervention or waitlist (control n = 198, intervention n = 51). Participants completed baseline and follow-up self-report measures on empathy, executive function, emotion regulation, mood and anxiety, ACEs, and ADHD symptoms. Multi-level modelling revealed significant improvements in executive functioning and emotion regulation in the intervention group relative to the controls (ps < .05), with no significant effects observed for empathy or mood/anxiety models (ps > .05). ADHD and ACEs did not significantly moderate intervention-related changes for any outcomes. Findings suggest that a six-week self-regulation intervention strengthened facets of self-regulation; however, produced no improvement in empathy or mood/anxiety across time. These results support the implementation of a universal self-regulation intervention to improve executive functioning and emotion regulation in emerging adults.
From meaning-making to life sustaining: A narrative ethnography of students’ out-of-school daily practices
(2026) Misana, Leonard; Sanford, Kathy
Students’ out-of-school daily practices play a central role in shaping their lives, yet literacy-centred frameworks often marginalize them. This study examines how such practices relate to academic learning and personal development in a rural secondary school in Ukerewe District, Tanzania. Guided by an interpretivist paradigm, I conducted a narrative ethnography with 10 participants: four students, four parents, and two teachers. Data were generated through ethnographic conversations, focus group discussions, and participant observation, and analyzed using reflexive thematic analysis. I used the multiliteracies framework to examine students’ meaning-making and identity construction across modes and cultural contexts. Throughout the study, I worked within the Heshima framework, an ethical Afrocentric approach to engaging with Black people and people of African descent. Findings show that students participate in diverse everyday practices, including household and economic work, academic activities, and the arts. Schools privilege school-based academic practices, such as remedial classes and private tutoring, while often overlooking the educational significance of farming, animal care, and domestic work, despite the ways these practices sustain students’ participation in schooling. Although this hierarchy is partly shaped by pressures associated with high-stakes examinations, I argue that it also reflects limited theoretical attention to how student’ out-of-school daily practices sustain schooling. While the multiliteracies framework explains meaning-making across modes and contexts through design, representation, and identity, my analysis suggests that it offers less conceptual space for understanding how life-sustaining practices enable participation in schooling. I therefore propose Life-Sustaining Practices (LSP) as a framework for understanding how practices grounded in survival, care, and reciprocity sustain schooling while also giving rise to meaning-making and design
Psychedelic experience and the aesthetics of surrender
(2026) Lambert, Denelle; Young, James O.
This dissertation uses a phenomenological approach to investigate the aesthetic value of psychedelic experience. Using a critical Merleau-Pontian approach, I surface ‘surrender’ as the performative task of psychedelic experience. I argue that to appreciate a psychedelic experience aesthetically, one undergoes the process of surrender. In other words, I highlight a specific kind of surrender that a person is called on to enact during a psychedelic experience. To account for the uniqueness of the psychedelic context, I develop philosopher Patočka’s notion of surrender and argue that the process of psychedelic surrender is what makes psychedelic experiences aesthetically valuable. Ultimately, this project suggests that psychedelic experiences provide a unique opportunity to engage in an aesthetic experience, if aesthetic experience is understood broadly as experience that is valued for its own sake. By focusing on the aesthetic value of psychedelic experience, this dissertation departs from mainstream philosophical discourse on psychedelic experiences, which tends to emphasize the use of psychedelic drugs as therapeutic tools in medical contexts. The purpose of this dissertation is to show why psychedelic experiences are an especially powerful kind of aesthetic experience and are aesthetically valuable. This dissertation proceeds as follows. In chapter 1, I provide a general overview of psychedelic drugs and academic discourse relating to psychedelic experiences. I focus on psychedelic drugs in psychology and also some of the main conversations around psychedelic experiences in current philosophical discourse. In chapter 2, I talk about psychedelic experiences and aesthetic experience and aesthetic value. Here, I highlight why psychedelic experiences problematize current approaches to understanding aesthetic experience and aesthetic value. In chapter 3, I discuss embodied phenomenology. The purpose of chapter 3 is to provide the framework for tackling the question of whether psychedelic experiences are aesthetically valuable. In chapter 4, I use the embodied approach that I developed in chapter 3 to argue that psychedelic experiences are aesthetically valuable when a person surrenders. Here, I develop Patočka’s notion of surrender to account for the uniqueness of the psychedelic context. I argue that ‘psychedelic surrender’ is the performative task of psychedelic experience. Ultimately, this project suggests that psychedelic experiences provide a unique opportunity to engage in an aesthetic experience, if aesthetic experience is understood broadly to be an experience that is valued for its own sake.
An end-to-end radio interference monitoring system
(2026) Bruce, Nicholas; Driessen, Peter F.; Harrison, Stephen
This dissertation presents the design, implementation, and philosophy of an end-to-end radio frequency interference monitoring system designed primarily for radio astronomy observatories. Motivated by the growing density of anthropogenic emitters and the corresponding threat to ground-based radio astronomy, the work describes a modular monitoring pipeline that includes hardware, signal processing, and machine learning. This work introduces several novelties: a gain-stable wideband receiver providing calibrated long-term radio frequency environment comparisons, a direction-of-arrival estimation method allowing use of arbitrarily arranged antennas, a digital down-converter architecture enabling insight into individual signal detections, and an unsupervised learning framework to perform modulation recognition and novelty detection. The dissertation also emphasizes the importance of modular, software-defined architectures and outlines future work towards real-time algorithms for next-generation interference management.
Adaptive and efficient resource allocation for cognitive radio networks
(2026) Shaghluf, Nagwa; Gulliver, Aaron
The increasing demand for wireless connectivity, massive device access, and data-intensive applications has intensified the need for efficient and intelligent spectrum utilization in modern wireless networks. Although radio spectrum is a limited resource, many licensed bands remain underutilized due to static allocation policies. Cognitive Radio Networks (CRNs) address this challenge by enabling Secondary Users (SUs) to dynamically access underutilized spectrum while protecting Primary Users (PUs) from harmful interference. However, efficient resource allocation in CRNs remains challenging due to sensing uncertainty, dynamic channel conditions, interference coupling, limited Channel State Information (CSI), and the high computational complexity of conventional optimization methods. This dissertation develops an intelligent and adaptive resource allocation framework for CRNs by improving spectrum awareness through predictive spectrum sensing and progressively integrating Multi-Agent Deep Reinforcement Learning (MADRL) and Non-Orthogonal Multiple Access (NOMA). The first contribution is a Predictive-Cooperative Spectrum Sensing (PCSS) framework that combines spectrum prediction with Cooperative Spectrum Sensing (CSS). Unlike conventional sensing schemes that rely only on instantaneous sensing decisions, the proposed PCSS approach uses historical cooperative sensing decisions to predict future PU channel availability before sensing is performed. This reduces unnecessary sensing of busy channels and improves spectrum awareness. The sensing time and fusion decision threshold are jointly optimized to characterize the trade-off between Spectrum Efficiency (SE) and Energy Efficiency (EE). Simulation results show that PCSS improves SE and achieves a better SE–EE trade-off compared with conventional sensing, local prediction, and cooperative spectrum prediction schemes. The second contribution is a MADRL-based resource allocation framework for Cognitive Device-to-Device (C-D2D) communication underlaying cellular networks. The joint Resource Block (RB) assignment and power control problem is formulated as a Mixed-Integer Nonlinear Programming (MINLP) problem due to binary RB allocation, nonlinear SINR expressions, and interference-coupled constraints. To address this complexity, a Proximal Policy Optimization (PPO)-based MADRL approach is developed, where each C-D2D pair acts as an autonomous agent. Both Centralized Training with Decentralized Execution (CTDE) and Decentralized Training with Decentralized Execution (DTDE) architectures are investigated under perfect and imperfect CSI. Simulation results demonstrate that the proposed PPO-based MADRL framework improves C-D2D sum-rate, scalability, and robustness compared with random allocation, random search, and other DRL baselines. The third contribution extends the framework to NOMA-enabled C-D2D networks. In this model, each C-D2D transmitter serves two receivers using power-domain NOMA while reusing cellular uplink RBs under CR protection constraints. This introduces additional challenges due to inter-group interference, intra-group NOMA interference, SIC decoding requirements, and fairness among C-D2D groups. A PPO-based MADRL framework is proposed for joint RB reuse and power allocation under constrained sum-rate and fairness-aware objectives. Different observation models, including local, partial, and full CSI, are systematically evaluated to study the impact of information availability on learning, coordination, and performance. The results show that structured partial CSI can approach full-CSI performance while reducing signaling overhead. Fairness-aware reward shaping further improves rate distribution, coordination stability, and EE when the fairness coefficient is properly selected. Overall, this dissertation demonstrates that intelligent CRNs can be developed through a progressive framework that begins with spectrum awareness and extends toward decentralized learning-based resource allocation. The proposed approaches improve SE, EE, throughput, fairness, and constraint satisfaction compared with conventional optimization and learning-based baselines. The work provides a scalable foundation for future 5G, beyond-5G, and 6G networks requiring adaptive, distributed, and autonomous spectrum management under practical constraints.
People are still calling it menopause—I’m not menopausal: Women in New Brunswick’s experiences and understandings of reproductive ageing
(2026) de Molitor, Rachel; Albert, Katelin
Perimenopause represents a significant yet understudied stage of reproductive ageing that is often framed primarily through biomedical understandings of hormonal change and symptom management. This research explores how women make sense of, experience, and respond to perimenopause within their everyday lives. Drawing on 11 in-depth interviews with self-identified perimenopausal women living in New Brunswick, Canada, the research examines how individuals understand themselves as perimenopausal, how they engage with or resist dominant Western narratives surrounding women’s reproductive ageing, and how perimenopause is framed as both a biological and socially constituted experience. The findings demonstrate that perimenopause is not experienced solely as a biological transition but rather as a biopsychosocial life-course transition shaped by cultural narratives of ageing, prior reproductive experiences, and anticipated reproductive futures. Participants often described becoming aware of perimenopause as prompting reflection on identity, bodily change, and future ageing trajectories. Experiences of perimenopause were also strongly shaped by social and structural contexts, including workplace expectations, caregiving responsibilities, access to healthcare services, and varying levels of knowledge about reproductive ageing. Many participants reported delayed recognition of perimenopause due to limited prior knowledge and described the broader information landscape as fragmented and overwhelming. Although health-care providers were frequently consulted, participants commonly expressed frustration with limited clinical knowledge and support. Discussions surrounding hormone replacement therapy emerged prominently and were frequently framed through health maintenance or risk assessments. Overall, this research highlights how individuals actively negotiate biomedical authority, societal expectations of productivity and resilience, and narratives about ageing when interpreting and responding to perimenopausal changes. By centring lived experiences, the study contributes to broader understandings of reproductive ageing. The findings underscore the importance—both in research and in care delivery—of advancing more expansive understandings of the menopause transition that recognizes its connection to ageing and highlight the need for improved health-care provider education and clinical guidelines, more responsive and person-centred services, and workplace policies that acknowledge and support diverse experiences of reproductive ageing.
Exploring how professional development can advance trauma- and violence-informed child care in Canada: A jurisdictional scan
(2026) Macasaquit, Mariel; Gerlach, Alison
To address young children’s experiences of trauma and adversity, there is increasing interest in integrating trauma-informed care (TIC) approaches in early learning and child care (ELCC) settings in Canada. However, evidence suggests that early childhood educators (ECEs) are unprepared to provide TIC due to considerable gaps in trauma-related knowledge and how to implement TIC in routine practice. Building on previous research that calls for a shift towards trauma- and violence-informed care (TVIC) in ELCC in Canada, this text-based research was guided by two research questions: how are ELCC professional development (PD) programs in Canada currently conceptualizing TIC, and how can the findings of this research inform PD programs in advancing the implementation of TVIC in ELCC settings in Canada? This research involved a jurisdictional scan of public facing information on 35 ELCC PD programs in 12 provincial jurisdictions across Canada. Data was analyzed using a decolonial lens, a scoping review method, and reflexive thematic analysis. Analysis identified two main themes: 1) reproducing biomedical discourses of trauma, with subthemes (a) reinforcing neurodevelopmental perspectives of trauma and (b) sustaining a decontextualized understanding of trauma, and theme (2) maintaining limited understandings of trauma in TIC, with subthemes (a) privileging individualistic approaches to care and (b) employing self-care as a panacea to secondary trauma. Given the pervasiveness of interpersonal and structural forms of violence in Canada, particularly for structurally marginalized communities, these findings can inform PD programs with ECEs that promote a broader framing of trauma- and violence-informed child care. This research has relevance for ECEs, ECE associations, and postsecondary institutions seeking to foster a workforce that can respond to families’ and young children’s experiences of trauma and violence in their routine practice.
Crafting closeness: Building connection through collaborative creativity in Minecraft
(2026) Berger, Phaedra; Mandryk, Regan; Somanath, Sowmya
We investigate how designing to support collaborative creativity can foster social connection in interactive systems. Although creativity and social connection are conceptually linked, engaging in digital creative activity has not been examined as a mechanism for explicitly fostering social connection. We conducted a mixed-methods survey study of people who play Minecraft with others, combining measures of creativity, social connection, and features of digital collaboration with open-ended responses. Quantitative analysis revealed that both creative self-perception and the creativity support of the tool influenced the building of social capital through creative collaboration. Furthermore, creativity support was more influential in informing bonding ties than bridging ties. Qualitative thematic analysis identified three phases of the creative process (problem-finding, brainstorming, and implementation) and four experiential factors (unity, agency, playfulness, and achievement) that shaped experiences of social connection and disconnection. We contribute a set of general design implications for leveraging collaborative creativity to support social connection in digital systems.
Associations between home literacy environment, executive function, and emergent literacy among four-year-old children from low-income families
(2026) Opao, Josellie; Harrison, Gina Louise
Emergent literacy skills are a set of knowledge, skills and behaviors that serve as precursors to conventional reading and writing. Despite a wealth of research investigating the influence of the home literacy environment (HLE) on the emerging literacy skills of preschool children, findings across studies remain inconsistent. More recently, researchers have been interested in the role of executive function (EF) in school readiness skills, including emergent literacy, as well as its potential mediating role between the HLE and early literacy skills. However, their associations remain insufficiently understood, particularly among low-income preschool populations. Therefore, the present study sought to examine the direct effects of the different types of HLE activities (reading books, telling stories, and learning activities) on children’s emergent literacy skills, as well as their indirect effects operating through EF among 4-year-olds from low-income families. The three HLE activities were examined separately to determine whether each would show a differential pattern of association with emergent literacy. Using secondary data from the Baby’s First Years study, the path analysis revealed a significant direct association between EF and emergent literacy. In contrast, no significant direct and indirect effects were found between any of the three HLE activities and emergent literacy via EF. These findings underscore the important role of early EF in supporting the acquisition of early literacy skills prior to school entry.
“Only if the mother is healthy, the baby can be”: Understanding maternal health through Indian low-caste and tribal women’s perspectives
(2026) Ottsen, Patricha Jeppe; Benoit, Cecilia; Mellor, Andrea
Background: India has made substantial progress in reducing maternal mortality in recent decades. However, these collective gains obscure persistent inequities, as low-caste and tribal women continue to experience disproportionate barriers to maternal health and wellbeing. While community-based initiatives are increasingly promoted, a gap remains between low-caste and tribal women’s own priorities for maternal health and those reflected in widely implemented programs based on the World Health Organisation’s (WHO) definition of maternal health. This study seeks to address this gap by examining low-caste and tribal women’s understanding of maternal health, ultimately nuancing and contextualising WHO’s framework. Methods: Guided by an intersectionality-informed life course approach, a framework synthesis review of scholarly literature was conducted, informed by a community consultation in Kherwara, Rajasthan, India. Results were validated with the same community to refine and contextualise findings. Results: Maternal health is understood by low-caste and tribal women in India as encompassing the health of the mother and baby, and to an extent, other family members. Women in this context understand maternal health as holistic, relational, and collectively governed. According to this study, maternal health is a continuum that begins with marriage and extends through pregnancy, childbirth, breastfeeding, and beyond, as women often have multiple children and later transition into caregiving roles as sisters, friends, and grandmothers. These women also identified food security along with respectful, inclusive, and accessible health services as central to achieving maternal well-being. Discussion/Conclusion: There is a disconnect between low-caste and tribal women’s conceptualisation of maternal health and existing healthcare and supports available to them. Centring low-caste and tribal women’s articulated priorities is essential to designing equitable maternal health systems that support maternal well-being.
Hygrothermal resiliency of wood-frame wall assemblies and climate change
(2026) Croyle, Benjamin; Mukhopadhyaya, Phalguni
Moisture-related deterioration in wood-frame building envelopes is a major concern in cold and wet climates and is expected to intensify under increasingly extreme conditions driven by climate change. Existing hygrothermal performance metrics do not adequately capture the resilience of building envelopes to prolonged and extreme moisture loading. This thesis presents a comprehensive hygrothermal analysis of the resilience of wood-frame building envelopes under extreme climates. Hygrothermal simulations were conducted in WUFI Pro V6.7 to evaluate brick, stucco, composite wood, and engineered wood clad wall assemblies in six Canadian climates. Across two chapters, the wall assemblies were analyzed under increasing wind-driven rain leakage and projected future climates. Two indices were developed to assess performance: a Robustness Index, based on peak moisture content to represent maximum loss of functionality, and a Resilience Index, which evaluates the capacity for moisture dissipation and recovery over time relative to a critical threshold. These metrics were validated against the mould growth index, a widely used indicator of biodeterioration risk. The new indices were shown to be sensitive to both cladding properties and climate characteristics. In particular, the Resilience Index responded negatively in assemblies with high capillary uptake claddings in low drying potential climates. The Robustness Index was more sensitive to large amounts of concentrated wind-driven rain. The impact of climate change on the two new indices was found to be dependent on both location and cladding type. Under the tested conditions, the robustness and resilience indices demonstrated greater sensitivity to performance changes under low biodeterioration risk than the mould growth index. This work provides a functionality-based framework for evaluating and comparing building envelope designs, supporting the development of more climate-adaptive wall assemblies under both current and future environmental conditions.
Fluorescence excitation emission matrix spectral imaging microscopy
(2026) Abbey, Emma X.; Loock, Hans-Peter
With this dissertation the capabilities of fluorescence microscopic imaging are greatly extended to allow for fast chemical fingerprinting in each pixel of an image. Spatial fluorescence imaging microscopy using multispectral and hyperspectral cameras with multiplexed excitation sources has been thus far not described in the literature. Three systems to acquire fluorescence excitation-emission matrix (F-EEM) spectra are demonstrated in this work, using Hadamard-multiplexed programmable excitation light sources. Computational approaches to bypass the limitations of multi- and hyperspectral camera hardware are implemented to increase the time resolution and emission spectral resolution. The first chapter contains background and instrumentation used in F-EEM spectroscopy and multispectral imaging. Microscopy illumination methods are described as they relate to the methods used in this work, and a brief overview of parameters used for creating spatially distinct dye samples under a microscope are described. Raman spectroscopy and how it relates to multiplexed fluorescence spectroscopy is described and is followed by an overview of multivariate analysis methods used in F-EEM analysis. F-EEM imaging requires a fully programmable excitation light source and an imaging detector. The work shown here develops and uses Hadamard-multiplexed excitation sources based on instruments built by our group in the past. The basis for multiplexed spectroscopy and the theory of the Hadamard transform are described in Chapter 2. The optical design and software integration of two programmable light sources—one white-light source based on a digital micromirror array and one using an array of discrete-wavelength laser diodes—are described in Chapter 3. Acquisition of F-EEM images is done through one of two cameras—a snapshot multispectral camera using an eight-channel colour filter array, or an interferogram-based hyperspectral camera providing up to 141 spectral channels over a wide wavelength range. These commercial cameras and their integration into our systems are described in Chapter 4. The processing and analysis for F EEM images acquired using Hadamard-modulated light sources and some unique challenges to these datasets are detailed in Chapter 5. Four fluorescent components are spatially and spectrally separated in a macroscopic application of the multispectral camera and Hadamard-modulated white-light excitation source, described in Chapter 6. Here, an image of capillaries containing fluorophores and mixtures thereof is analyzed using multivariate analysis to demonstrate the spatial and spectral separation of four fluorescent components in an F EEM image. The excitation light source is then modified for use in numerous microscopy illumination methods. F-EEM microscopic imaging using three distinct combinations of excitation source and imaging detectors is demonstrated in Chapter 7 using combinations of dye emulsions. Multivariate analysis of F EEM images taken with an 8-channel multispectral camera and using seven laser diodes can find ten fluorophores in a microscopy image when those spectral signatures are known. Without prior knowledge of the fluorophores, at least four fluorescent dyes in a microscope image are separated using multivariate analysis of an F EEM photomicrograph taken using the same multispectral camera and a white-light programmable light source. The emission spectra of F EEM images acquired with the eight-channel multispectral camera are spectrally upscaled in Chapter 8 to increase the spectral resolution without hardware modifications. The upscaled spectra are demonstrated to provide a superior method of fluorophore identification and separation in an F EEM image—more fluorophores can be identified in F EEM images using upscaled spectra than raw spectra. A new computational method for increasing the time resolution of F EEM images acquired using a Hadamard-modulated excitation light source is also demonstrated. These two computational techniques allow us to obtain chemical identifiers and intensities for each of the 65,536 pixels per frame, when these frames are obtained at a rate between 3-10 per second. Numerous avenues for experiments using the programmable light sources with the multispectral and hyperspectral cameras are described in Chapter 9, along with future work on a multi-wavelength multiplexed Raman and fluorescence spectroscopy experiment.
Multi-scale remote sensing of coral reef community dynamics
(2026) Harrison, Dominica Elaine; Baum, Julia Kathleen
Ecological patterns and processes are inherently scale-dependent, yet our ability to observe and quantify how community structures vary across space and time remains a central challenge in ecology. This dissertation develops a multi-scale framework to understand how coral reef benthic communities and compositions assemble across spatial gradients and reorganize through time. Focusing on reef-building corals as marine foundation species, I integrate imaging spectroscopy, spatial modeling, and three-dimensional (3D) structural mapping to bridge organismal scales; embayment (1–3 km) and regional spatial scales (~32 km); and multiyear temporal scales spanning an acute disturbance event (a 10-month El Niño–induced marine heatwave) and a prolonged disturbance gradient (a chronic anthropogenic gradient). By linking ecological theory with remote-sensing technologies, this work addresses long-standing technological limitations in coral reef mapping, in which classifications have historically been limited to coarse benthic categories or geomorphic proxies. Using coral reefs across southwest Hawaiʻi Island, USA, as a case study, my second chapter demonstrates that fine-scale biological and morphological variation in corals can be detected and scaled using high-resolution imaging spectroscopy. Through a sensitivity analysis that combines in-situ spectral libraries, endmember modeling, simulated ocean optical properties, and Global Airborne Observatory (GAO) data, I quantify how organismal and benthic signals propagate through the water column to produce detectable airborne spectral signals. In my third chapter, I demonstrate that spectral decomposition isolates higher-order principal components that retain benthic signal, enabling their delineation, classification, and ecological attribution to benthic compositional assemblages, which I term “spectral communities.” Scaling from individual embayments to a 32-km regional coastline in chapter four, I demonstrate that spectrally derived classes, identified through spatial clustering and k-means classification of higher-order principal components, are organized along continuous benthic compositional gradients shaped by interacting, scale-dependent processes. Broad-scale patterns reflect the combined influence of environmental filtering and dispersal limitation; mesoscale structure emerges from dispersal and neighborhood effects; and fine-scale heterogeneity is driven primarily by local environmental filtering. In chapter 5, focusing on temporal coral reef dynamics in Kiritimati, Republic of Kiribati, I integrate structure-from-motion (SfM) photogrammetry and a convolutional neural network to automate benthic classification and quantify reef structural complexity, seven years after the 2015–2016 marine heatwave and across a persistent human disturbance gradient. In my final chapter, I show that acute thermal stress and chronic human disturbance interact, leading to the reassembly of coral cover, taxonomic morphology, and structural complexity. Although reefs exhibited partial recovery seven years post-disturbance, chronic human pressure constrained recovery trajectories and altered morphological composition, revealing scale-dependent resilience and functional reassembly. Overall, this dissertation develops a scalable and repeatable approach for detecting, modeling, and interpreting coral reef dynamics across space and time, providing critical tools for monitoring and conservation in a rapidly changing climate. This dissertation also demonstrates how integrating imaging spectroscopy, spatial modeling, and 3D structural mapping can address fundamental ecological questions about scale dependence, community assembly, and the processes that structure benthic composition in coral reef ecosystems.
Applying automatic speech recognition to Indigenous language documentation: A case study with Hul’q’umi’num’
(2026) Jiang, Xin He; Bird, Sonya; Urbanczyk, Suzanne Claire
The process of documenting Indigenous languages can create a large amount of audio recordings that are difficult to convert into a written form. Speeding up the transcription process using automatic speech recognition could help the Hul’q’umi’num’ Language & Culture Society to create pedagogical materials and make their recordings more accessible. In this project, I trained a language model known as XLS-R on Hul’q’umi’num’ audio recordings to determine how accurately it can transcribe Hul’q’umi’num’, whether particular linguistic and orthographic features are more difficult for XLS-R to transcribe, and what amount of time and computational resources the training takes. The model reached a CER of 11.1% and WER of 50% using 26 minutes of continuous speech. Most phonemes could be transcribed with high accuracy but the model showed difficulties with segmenting words, differentiating glottalized consonants from plain consonants, determining vowel length, and predicting the placement of glottal stops.
Investigating the function of thymic eosinophils
(2026) Gatti, Dominique; Reynolds, Lisa A.
Eosinophils reside in the thymus of humans, mice and other vertebrates, yet their function during steady-state development remains poorly defined. However, two, non-mutually exclusive, functional roles have been proposed: that eosinophils contribute to T cell development and/or support thymic tissue maintenance and repair. In this thesis we examined both proposed functions of thymic eosinophils using mouse models. We began with a broad characterization of thymic eosinophils at different time points throughout life and investigated the factors that affect their accumulation within the thymus. We then sought to understand their population dynamics and interrogated how eosinophils maintain residency in the thymus. Finally, using eosinophil-deficient mice, we investigated two possible roles that eosinophils might contribute to in the thymus. In young mice, we quantified thymocyte subsets to understand the influence of eosinophils on T cell development. In adult mice, we exploited pregnancy-induced thymic involution—a physiological model of acute thymic atrophy—to determine whether eosinophils facilitated thymic repair postpartum. Collectively, this thesis provides insight into the complexities of thymic T cell development as the cell types and signals governing thymocyte maturation are still not fully understood. Identifying the mechanisms that shape T cell ontogeny has important implications for advancing fundamental principles of developmental immunology and for improving our understanding of immune-mediated disease. Moreover, defining the functional role of eosinophils in the thymus will help clarify the potential immunological consequences of eosinophil-targeted therapies. For example, infants born to birth parents that receive eosinophil-depleting treatments may experience transient eosinophil deficiency during early life—when immune development is highly sensitive to environmental and cellular cues. By investigating both the role of eosinophils in postpartum thymic regeneration in dams and their contribution to T cell ontogeny in pups, this thesis provides a more comprehensive understanding of how eosinophils may influence thymic biology and immune development.

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