Open Theses and Dissertations
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Item Open Access Stream Starting Soon: Exploring Theatrical Design Principles to Evoke Feelings of Safety for Livestreamers(2025-01-14) Colins, Mathilda; He, Helen Ai; Viczko, April; Aycock, John Daniel; Leblanc, Jean-ReneToxic behaviour is prevalent in livestreaming communities, particularly for minority groups such as LGBTQ+, POC, and women. To combat this, current solutions employ automatic or human content moderation. While necessary, moderation is a content-based intervention that is largely reactive, removing harmful content after it has already been posted. Drawing inspiration from physical theatre, I explore an alternative approach that seeks to create digital safe spaces by proactively fostering positive emotions for the livestreamer so that they engage in behaviours that encourage feelings of safety for others in their community. I leverage the field of theatre and the elements and principles of design to offer a Framework of Controllable Qualities, where “Controllable Qualities” refers to customizable audiovisual sensory cues used to create a particular mood or atmosphere in a space (such as the volume of a Sound, the colour of a Light, or the texture of a Costume). I illustrate the application of my framework with four manually-created design probes (background images informed by the framework) deployed by participating livestreamers in a small, exploratory qualitative study. The design probes aimed to foster a spectrum of feelings of safety from extremely safe, to extremely unsafe. Through a qualitative study, I examine the values and practices that livestreamers and moderators held surrounding the creation of digital safe spaces, and if the presence of the design probes influenced feelings of safety for the livestreamer. Drawing on their feedback, I created a computational program built in Processing to automatically generate design probes. I make four contributions: 1) a richer understanding of how to translate physical theatrical design elements to a digital livestream context through the creation of a Framework of Controllable Qualities, 2) the application of a subset of the Framework of Controllable Qualities to inform the design of manual and automatically generated design probes to foster feelings of safety, 3) a deeper understanding of livestreamer and moderator practices to foster safety and inclusivity within a livestream community, and 4) an understanding of livestreamer and moderator experiences with the manually-created design probes and its influence (if any) on feelings of safety for the livestreamer.Item Open Access Disease control practices used to prevent morbidity and mortality in preweaned beef calves(2025-01-15) Sanguinetti, Virginia Margarita; Windeyer, Claire; Checkley, Sylvia; Adams, Cindy; Campbell, John; Morley, Paul; Smith, DavidCalf morbidity and mortality negatively impact economic returns for cow-calf producers. Given this, preventing infectious diseases, including Neonatal Calf Diarrhea (NCD) and Bovine Respiratory Disease (BRD) is essential. However, recommended practices to attain this have not been recently summarized or updated. Therefore, the aim of this thesis was to study several aspects relevant to the implementation of disease control and update recommended practices. The objectives were to: i. summarize the scientific evidence on the effectiveness of practices in preventing health and mortality outcomes, ii. prioritize practices based on their usefulness in herds considering their effectiveness, ease of implementation, and economic feasibility, iii. assess the frequency of outbreaks, use of practices, the impact of practices on outbreaks across Canadian cow-calf herds, and the importance given to productivity parameters across regions, and iv. compile the evidence into a Calf Health Decision Tool to support discussions between producers and veterinarians and pilot it in Alberta, Canada. The work reported in Chapter 2 showed that the evidence of the impact of practices on mortality, regardless of the cause, was scarce. Only a few practices showed statistically significant associations. Herds that routinely intervened with colostrum or checked the fullness of the udder had a lower mortality risk than those not using these practices. Herds that calved early or during winter had a higher mortality risk than those calving later. Herds with longer calving seasons had a higher mortality risk than those with shorter seasons. Calves from herds that did not supplement with vitamin E and selenium at birth had higher odds of mortality than those from herds where this practice was used. Chapter 3 showed that most practices impacted both NCD and BRD. However, the evidence was of low and very low certainty. Chapter 4 found that veterinarians prioritized the effectiveness of a practice over its ease of implementation and economic feasibility. Vaccinating calves against clostridial disease and providing colostrum in case a calf had not nursed using an oesophageal tube or nipple bottle were practices considered always useful for all herds. Most practices were shown to have intermediate levels of usefulness in herds. Prophylactic and metaphylactic use of antibiotics were considered among the least useful. Yet, all practices that were considered at least very useful for some herds were deemed relevant enough to be included in a Calf Health Decision Tool. Chapter 5 found that over 40% of herds had at least one type of outbreak during the last three calving seasons. Also, it was demonstrated that eastern and western herds managed their cow-calf herds differently. Some frequently used practices were shown to increase the odds of having outbreaks. It was also found that western and eastern producers gave similar importance to several productivity parameters of their herds. In Chapter 5, it was revealed that the Tool was useful for facilitating discussions between producers and veterinarians regarding disease control. Responses showed that delaying the calving season for early calving herds was not feasible. Most herds could only follow only one of two recommended practices, either calving heifers before cows or calving seasons shorter than 80 days. Therefore, there might be an incompatibility between these recommendations. Most producers were willing to consider using some method to segregate calves by age. Given this, this could become a more widespread recommended practice. Only half of the herds vaccinated dams against NCD, and even one herd with a history of NCD outbreaks was not doing this. This may be because producers felt reluctant to manage pregnant dams in the chute. However, they were more willing to consider calf vaccination instead. The findings presented in this thesis reveal a general lack of consistent evidence proving the effectiveness, ease of implementation, and economic feasibility of practices. Overall, the work in this thesis showed that many commonly used practices make herds vulnerable to outbreaks, and thus, tailoring disease control practices to the operation is essential. Therefore, The Calf Health Decision Tool created may help support discussions between veterinarians and producers to implement this and prevent disease and mortality.Item Open Access Building Better from LEED to Living: An Approach to Net Zero Water Management(2024-12) Fatima, Kulsum; Assefa, Getachew; Tyler, Mary Ellen; Hilmi, TawabIn view of the increased concerns about the United Nations Sustainable Development Goals (UNSDGs), there is a need to minimize water-related challenges and maximize water security and availability through sustainable green building practices. As significant water consumers, university campuses play a crucial role in addressing water-related challenges. By focusing on water-efficient buildings to achieve net-zero water management and exploring the influence of green building practices, universities can contribute to the UNSDGs, particularly in promoting sustainable water management, climate action, and the development of resilient communities. This thesis explores the influence of green building practices on water management by comparing objectives, directives, and applications suggested by the LEED certification system and the Living Building Challenge (LBC) certification system. It aims to understand the advantages and challenges in transitioning UCalgary from LEED-guided water-efficient operations to LBC-compliant net-zero water operations. This research evaluates best practices from three design precedent sites: CIRS at the University of British Columbia, Bullitt Center with the University of Washington, and Kendeda Building at Georgia Institute of Technology. For this purpose, two evaluation frameworks are used: Performance Assessment Framework (PAF) and Water Literacy Assessment Framework (WLF). UCalgary and design precedent sites are evaluated using the PAF and WLF frameworks to identify challenges and barriers to water performance efficiency and improve water management practices. This research hopes to encourage decision-makers and practitioners at higher education institutions (HEIs) to achieve net-zero compliance as per LBC, minimize performance gaps and water-related challenges, motivate water managers to develop an operational net-zero water scenario, and incentivize water users to support this scenario by promoting good water use behaviours on HEI campuses. This research provides insights into the factors influencing the adoption of LEED and LBC at higher education institutions. It also highlights the challenges and barriers project teams involved in LEED and LBC applications face. Additionally, the research identifies problem situations related to selecting and determining water strategies for LBC compliance. The understanding gained from this research is valuable for addressing the complexities of water management and promoting the appreciation and value included in the joy and everyday understanding of water.Item Open Access Integrating Queue Dynamics into the Trip-Based Macroscopic Fundamental Diagram(2025-01-15) Hassanin, Omar; Kattan, Lina; Demissie, Merkebe Getachew; He, Jianxun (Jennifer)Macroscopic traffic models provide a simplified framework for analyzing and controlling traffic at the network level. Among these models, the trip-based macroscopic fundamental diagram (MFD), or generalized bathtub model, effectively captures inflow, accumulation, and outflow while considering trip lengths and travel times, particularly under rapidly changing traffic conditions. This study addresses a gap in the trip-based MFD, which lacks queuing dynamics under downstream restrictions, as its original outflow function assumes unrestricted flow. To resolve this, the research incorporates downstream queuing dynamics, accounting for waiting times and their changes over time. The study also examines the impact of connected and automated vehicles (CAVs) on traffic dynamics through numerical simulations. Assuming that CAVs improve the MFD shape and bottleneck capacity, a sensitivity analysis was conducted for various market penetration rates (MPRs). Key findings include: 1) Average upstream waiting time decreased from 130 seconds to 0 at 60% MPR; 2) Average reservoir travel time reduced by 60% (570 to 230 seconds) at 100% MPR; 3) Average downstream waiting time initially increased by 25% at 70% MPR but fell by 12.5% at 100% MPR; and 4) Average total trip time (TTT) dropped by 61%, from 780 to 300 seconds. The results show earlier commuter exits, shifting the peak time (𝑡𝑝) of TTT. However, as 𝑡𝑝 depends on external factors (e.g., work schedules), the inflow demand pattern was adjusted to maintain 𝑡𝑝 constant, revealing a 26-minute inflow peak shift at 100% MPR. Additionally, congestion duration reduced by 51%, from 96.6 to 46.6 minutes, while maximum travel time decreased by 66% (18.5 to 9.5 minutes). Lastly, previous enhancements in capacities maintained constant free-flow speed (𝑣𝑓) for safety reasons. However, when the MPR reaches 100% and there are no longer any human-driven vehicles, increasing 𝑣𝑓 no longer poses safety risks. Thus, 𝑣𝑓 can reach 21m/s instead of 15 m/s, leading to less congestion. The findings demonstrate that CAVs significantly reduce trip time and congestion but cannot alone eliminate the negative impacts of downstream bottlenecks.Item Open Access Assessing Multi-Coil Deep-learning-based MR Image Reconstruction(2025-01-11) Dubljevic, Natalia; Frayne, Richard; Souza, Roberto; Bayat, Sayeh; Levan, PierreMagnetic resonance (MR) imaging is a valuable non-invasive imaging technology essential for diagnostics and patient health management. However, scan times are often quite long, affecting both patient throughput and comfort. To help accelerate the process, parallel imaging uses an array of receiver coils to reduce the amount of data acquired. Recently deep learning (DL)-based MR image reconstruction has become popular as it allows for further scan acceleration. With its advent, new questions are raised regarding optimal coil design and processing strategies. This work investigates whether traditional geometric coil constraints imposed by parallel imaging can be relaxed when using DL-based reconstruction methods as compared to non-DL approaches. We also explore whether to first combine channels (coil-combined approach) to enhance model generalizability or to keep channel processing separate (all-coil approach) to fully utilize multi-channel information. Two sets of head coil profiles (8-channel and 32-channel geometries) were evaluated across three methods: a DL model, conjugate gradient SENSE (CG-SENSE), and L1-wavelet compressed sensing (CS). These methods were compared using both quantitative metrics and visual assessment as coil overlap increased. Results showed that as coil overlap increased, performance significantly decreased (p<0.001) across all methods, with the largest impact seen in CG-SENSE. DL-based reconstructions consistently outperformed their non-DL counterparts, with minimal changes in performance across coil overlap and signal-to-noise ratio (SNR). While CS demonstrated better robustness to coil overlap than CG-SENSE, it produced inferior reconstructions characterized by blurriness. Additionally, we assessed three popular DL architectures using both coil-combined and all-coil strategies on brain MR images in and out of distribution. All-coil styles slightly improved in-distribution performance, such as when reconstructing data from healthy individuals, while coil-combined designs better generalized to unseen pathological data. These findings suggest that DL-based reconstruction can produce high-quality images that are robust to coil overlap, offering the potential to relax geometric coil design constraints. Additionally, a coil-combined processing approach may be preferable when considering clinical use.Item Open Access An Attention-Based Deep Learning Approach for Forecasting Electricity Prices in Real-Time Electricity Markets(2025-01-15) do Carmo Junior, Jose Eustaquio; Zareipour, Hamidreza; de Souza, Roberto Medeiros; Papalexiou, Simon MichaelReal-time electricity markets are characterized by irregular and sudden price swings, leading to high price volatility and significant uncertainties for market participants. Accurate and informative electricity price forecasts are essential to reduce these uncertainties and enable more effective decision-making in energy generation, consumption, strategy planning, and risk management. This thesis presents a new forecasting framework for electricity prices in real-time markets, leveraging the capabilities of deep learning and advanced feature engineering. The proposed methodology integrates the Temporal Fusion Transformer (TFT), a deep learning model applied to time series forecasting, with dynamic clustering techniques to enhance forecasting accuracy. This is done by combining Hierarchical Density-Based Spatial Clustering of Applications with Noise and Dynamic Time Warping to cluster generators based on attributes such as geographical location, fuel type, installed capacity, and generation patterns. These clusters provide new covariates for forecasting models, enabling the method to adapt to the unique characteristics of any electricity market. The effectiveness of the proposed framework is demonstrated through a case study of the Ontario electricity market, where the methodology outperforms the forecasts of the system operator in terms of average error, accuracy, precision, and recall across a six-hour forecast horizon. This study underlines the framework's versatility and offers valuable insights into electricity price behavior, aiding market participants in mitigating risks and optimizing energy strategies.Item Open Access Whatls Left After Distillation? How Knowledge Transfer Impacts Fairness and Bias(2025-01-10) Mohammadshahi, Aida; Ioannou, Yani Andrew; Far, Behrouz H.; Bento, Mariana PinheiroKnowledge Distillation is a commonly used Deep Neural Network (DNN) compression method, which often maintains overall generalization performance. However, we show that even for balanced image classification datasets, such as CIFAR-100, Tiny ImageNet and ImageNet, as many as 41% of the classes are statistically significantly affected by distillation when comparing class-wise accuracy (i.e. class bias) between a teacher/distilled student or distilled student/non-distilled student model. Changes in class bias are not necessarily an undesirable outcome when considered outside of the context of a model’s usage. Using two common fairness metrics, Demographic Parity Difference (DPD) and Equalized Odds Difference (EOD) on models trained with the CelebA, Trifeature, and HateXplain datasets, our results suggest that increasing the distillation temperature improves the distilled student model’s fairness, and the distilled student fairness can even surpass the fairness of the teacher model at high temperatures. This study highlights the uneven effects of distillation on certain classes and its potentially significant role in fairness, emphasizing that caution is warranted when using distilled models for sensitive application domains.Item Open Access Ill-fated Mission: Canada’s Franklin Expedition and its Role in Arctic Securitization(2025-02) Clifton, Robert; Huebert, Rob; Sayers, Anthony Michael; Rice, Roberta L.; Huebert, RobIn 1845, Sir John Franklin and his crew went missing while in search of a Northwest Passage in the Canadian Arctic. The shipwrecks were discovered in 2014 and 2016 (respectively) with the first, The HMS Erebus, discovered under the administration of Canadian Prime Minister Stephen Harper (2006-2015). Employing discourse analysis of qualitative research interviews and primary documents, and the process tracing method, this thesis investigates the role the Franklin Expedition searches and discoveries played in the Harper government’s Canadian Arctic securitizing move. This thesis tests the original Copenhagen, and Second Generation, Securitization theories for applicability to the Harper-era Franklin searches and communications in the context of Canada’s Arctic security policy. It finds mild support for the relevance of Second Generation theories over the original Copenhagen theory from which later theories of securitization evolved. Given analysis of theoretical underpinnings and after deep qualitative analysis, this study finds that the Franklin searches and discovery did not play a central role in Prime Minister Harper’s prior securitization of the Canadian arctic.Item Open Access Investigating Automatic Bug Repair Using Large Language Models for Digital Hardware Design(2025-01-13) Elnaggar, Abdelrahman; Tan, Benjamin; De Carli, Lorenzo; Ginde, GouriRegister-transfer level ( RTL) bugs present critical challenges, impacting the functional correctness, security, and performance of System-on-Chip (SoC) designs. Detecting and repairing RTL bugs is traditionally a time-consuming process requiring skilled engineers, which significantly prolongs SoC development cycles and reduces vendor competitiveness. Given this complexity, there is a strong need for automated repair solutions capable of efficiently addressing RTL bugs to accelerate development timelines. In this thesis, we propose an automated framework leveraging a large language model (LLM) to repair RTL functional bugs. We explore various prompting techniques, including zero-shot, few-shot, and feedback approaches. Zero-shot relies solely on the LLM ’s pretrained knowledge, few-shot provides specific examples of RTL bug repairs, and feedback iteratively refines the LLM’s responses using outputs from prior iterations. Additionally, we investigate six prompting strategies, each incorporating varying levels of context to guide the LLM in the repair process. Our proposed framework operates on benchmarks without requiring prior knowledge of the bug’s type, location, or specific repair steps, better reflecting real-world scenarios than previous approaches. Results demonstrate the potential of LLM -driven automation, with the feedback approach achieving the highest repair success rate by fixing 26 out of 32 benchmarks (81.25%), while the best zero-shot and few-shot strategies repaired 23 out of 32 benchmarks (71.88%). These findings highlight the ability of current LLMs to consistently address RTL functional bugs, offering significant promise for streamlining SoC development by reducing the time and effort required for RTL bug detection and repair.Item Open Access Unsupervised and Weakly Supervised Domain Adaptation of MRI Skull-Stripping Models Trained on Adult Data to Newborns(2025-01-13) Omidi, Abbas; Souza, Roberto; Abou-Zeid, Hatem; Ovens, KatieThe process of removing non-brain tissue signals from brain magnetic resonance imaging (MRI) is known as skull-stripping. It is a crucial preprocessing step in neuroimaging analysis, particularly for subsequent brain tissue segmentation and studying neurological disorders. Despite significant progress in deep learning-based methods for skull-stripping, data distribution shifts between adult and newborn MRI data present a major challenge, limiting the generalization of models trained on adult data when applied to newborns. This work proposes both unsupervised and weakly supervised domain adaptation techniques that leverage weakly annotated data, synthetic data, and the learning of domain-invariant features to address this challenge. First, I introduce an unsupervised method utilizing adversarial domain adaptation to align feature representations between adult and newborn MRI data, and a new contrast inversion data augmentation step to reduce the domain shift. Then, I extend this method by leveraging Gaussian Mixture Model (GMM)-generated synthetic data to enhance segmentation performance. Finally, I propose to incorporate weakly annotated newborn data during model training. This weakly supervised method achieves state-of-the-art performance for skull-stripping neonatal brain imaging, improving upon existing methods in terms of both the Dice coefficient and Hausdorff distance quantitative metrics. Together, these methods demonstrate the potential of leveraging domain adaptation techniques to bridge the gap between adult and newborn brain MRI data, enabling accurate skull-stripping across diverse populations. The source code and weights of the trained models are publicly available at https://github.com/abbasomidi77/DAUnet.Item Open Access Evaluating Eye-Tracking Multimodal Interactions in Virtual Reality(2025-01-10) Shishir, Naznin Sharmin; Zhao, Richard; Sharlin, Ehud; Maurer, FrankVirtual reality (VR) has gained significant traction as a tool for both education and gaming in recent years. This research explores the accuracy and effectiveness of eye tracking as an object interaction method in VR. Specifically, this thesis presents the development of an interactive virtual environment designed to compare the interaction time, accuracy, and task load associated with eye tracking, distance-based hand tracking, and close-up grabbing during interactions with 3D objects. A user study was conducted to compare the three interaction methods. The findings provide evidence that eye-tracking multimodal interactions outperforms both hand tracking methods across multiple metrics.Item Open Access Natural Gas to Hydrogen and Other Products at Low to Zero Emissions(2025-01-09) Ferrer, Francisco Daniel Alana; Mehta, Sudarshan; Clarke, Matthew Alexander; Pereira-Almao, Pedro R.In light of pressing environmental challenges, such as global warming driven by greenhouse gas emissions, hydrogen has emerged as a vital component in maximizing renewable energy use and facilitating the transition to a sustainable future. Currently, the majority of hydrogen production relies heavily on fossil fuels, particularly natural gas. While significant advancements have been made in alternative hydrogen generation technologies, steam methane reforming (SMR) remains the most established and widely implemented method. However, its high energy demands and CO2 emissions have prompted research into low-temperature hydrogen production technologies. This study focuses on low-temperature steam reforming (LTSR) and dry reforming (DRM) processes, operating between 500 and 600 °C, utilizing innovative Ni-Ce formulation catalysts (CAT-1 and CAT-2). Catalyst CAT-1 demonstrated exceptional performance in the LTSR of a natural gas model, achieving complete conversion of ethane and propane while maintaining near-equilibrium levels of methane under various operational conditions. This approach eliminated the need for water-gas shift and pre-reforming stages, simplifying system complexity and reducing construction costs. While the catalyst showed remarkable efficacy in hydrogen production, challenges related to sulfur compound deactivation were noted, leading to the recommendation of a guard reactor. Furthermore, catalyst CAT-2 exhibited outstanding stability during DRM, achieving near-equilibrium conversion rates and effectively suppressing carbon deposition through elevated CO2/CH4 ratios. Long-term tests confirmed no signs of catalyst degradation, enabling direct feeding of natural gas into the dry reforming reactor and thereby minimizing pre-treatment requirements and capital expenditures. Ultimately, the integration of LTSR and DRM processes represents a promising solution for significantly reducing carbon emissions while producing hydrogen and syngas more efficiently than conventional methods, with estimated CAPEX savings of approximately 36% for standalone LTSR units compared to traditional steam methane reforming units.Item Open Access Empowering Indigenous Youth: A Strengths-Based Approach to Positive Development, Relationship Safety, and Community Building(2025-01-08) Van Bavel, Marisa; Schwartz, Kelly Dean; Exner-Cortens, Deinera; Lacerda-Vandenborn, ElisaThis dissertation presents three interconnected manuscripts on various aspects of Indigenous youth wellness and the researcher’s journey in community-based research. The first paper (Chapter Two) provides a review of wellness factors that help Indigenous youth thrive. These factors are explored through the lens of the First Nations Mental Wellness Continuum framework. When cultural, social, and historical factors are prioritized, Indigenous youth may find hope, belonging, purpose, and meaning. Further, this review emphasises that culturally rooted initiatives empower Indigenous youth to build on their strengths. In paper two (Chapter Three), I utilized data from the nationally representative General Social Survey: Canadian’s Safety to explore Indigenous youths’ experiences of dating violence. Dating violence represents a manifestation of unhealthy relationship patterns that have emerged from colonial violence. Dating violence was significantly associated with age and gender, along with several social and psychological factors including religion, sense of belonging, and awareness of services. Findings illuminate the need for cultural and community supports as experiences of dating violence were significantly associated with poorer well-being among Indigenous youth. This secondary data analysis presents emerging insights into Indigenous youths’ experience of dating violence and offers some suggestions that can inform programming to support survivors. Finally, in paper three (Chapter Four), I share an autoethnography of my reflections observing Tsuut’ina Nation Police as they built a prevention and intervention program for youth who may be justice-system involved. This personal account sheds light on challenges and learning opportunities for Western researchers. I discuss the need to be flexible, respect local knowledge, and illustrate the practical application of principles discussed in previous chapters. This paper showcases the strengths of Tsuut’ina Nation, and the inherent capacity Indigenous communities have to develop community-driven, culturally-relevant programming that supports their youth. Together, these chapters present a deeper understanding of Indigenous youth wellness and the significance of culturally responsive, community-driven approaches. Indigenous knowledge must be integrated into practice and research to foster positive outcomes for Indigenous youth.Item Open Access Examining the Effects of an Outdoor Nature-Based Park Visit Program on the Behaviors, Mood, Quality of Life and Cognitive Symptoms of Individuals with Dementia and the Burden, Well-Being, and Support of Caregivers(2025-01-13) Abolarin, Margaret Oluwabukola; Seitz, Dallas Peter; Pouli, Marc; Jakubec, Sonya Lee; Longman, Stewart RichardBackground: As Canada's population ages, dementia prevalence is projected to rise significantly, highlighting the need for effective interventions to maintain cognitive function and enhance quality of life (QoL). Activities involving nature, particularly outdoor activities, may help slow cognitive decline and improve mood in people living with dementia (PLWD). However, the benefits of outdoor nature-based activities for PLWD in community settings and their impact on caregivers are poorly understood. Objective: This thesis examines the effects of an 8-week park visiting program on PLWD and caregivers. It investigates how this nature-based intervention is associated with changes in behaviour, mood, cognitive function, and QoL among PLWD, along with caregiver burden, well-being, and support. Design: This pilot study included community-dwelling PLWD and caregivers. Participants completed weekly 120-minute park visits guided by evidence-based recommendations. Outcome measures were collected at baseline, week 4, and week 8. The primary outcome measure was the Neuropsychiatric Inventory (NPI) to assess behavioural changes. Secondary outcomes included the Cornell Scale for Depression in Dementia (CSDD), Repeatable Battery for the Assessment of Neuropsychological Status (RBANS), Dementia Quality of Life (DEMQOL), Zarit Burden Interview (ZBI) and the Carer Well-being and Support questionnaire (CWS). Results: Eight PLWD-caregiver pairs participated. The mean age of PLWD was 73.4 ± 5.8 years (mean ± standard deviation) and 62.5% males. Caregivers ranged in age from 45 to 71 years, with 87.5% being female. The NPI scores showed non-significant numerical improvement at Week 8 (mean difference (MD) -3.63, p = 0.10). Secondary outcomes revealed significant reductions in depressive symptoms on the CSDD (MD -1.50, p = 0.04) at Week 8, significant improvement in overall cognitive function on the RBANS (MD 6.25, p = 0.02) at Week 8, and a significant increase in QoL at Week 8 (DEMQOL: MD 3.25, p = 0.003; DEMQOL-proxy: MD 6.38, p = 0.04). Caregiver burden and well-being did not show significant changes Conclusion: Nature-based outdoor interventions, such as visits to local parks, may improve behaviours, mood, cognition, and QoL for PLWD, offering a promising lifestyle approach in dementia care. Future research could establish these activities as essential components of psychosocial dementia interventions.Item Open Access Pre-stabilization strategies for systems-wide in situ crosslinking mass spectrometry(2025-01-09) Michael, Andrew Roy; Schriemer, David C.; Lees-Miller, Susan P.; Williams, Gareth J.Understanding the associations proteins form within a network of protein-protein interactions (PPIs) provides insight into the functions that drive cellular processes. These networks have largely been sampled and studied using various high-throughput screening techniques providing network maps. However, these investigative approaches only generate indirect interaction data that are prone to false positives. Crosslinking mass spectrometry (XL-MS) has the potential to map the interactome with high resolution and coverage. Current in situ XL-MS methods are limited by the low permeability of crosslinking reagents necessitating long incubation times to accrue appreciable signal. Consequently, sampling of the interactome is sparse and the long incubation times can distort the structural proteome resulting in questionable validity of the identified PPIs. This thesis aims to address these concerns through development of novel in situ XL-MS procedures that incorporate pre-stabilization into the workflow to facilitate cellular ultrastructure preservation and improve sampling of the spatiotemporal proteome. Pre-stabilization of cells was explored through chemical and temperature-based fixation strategies using either formaldehyde or freeze-substitution, respectively. Both methods facilitated PPI sampling at or above conventional in situ XL-MS workflows and provided opportunities to further maximize crosslinking yields while maintaining a preserved cellular ultrastructure. Pre-stabilizing cells with formaldehyde further created an opportunity to explore a novel crosslinking approach where the crosslinking reaction was split into two sequential and orthogonal coupling events. This approach followed a stepwise process of installing crosslink precursors across the proteome at saturated levels with crosslink formation done through click-chemistry, resulting in over 5X higher yield of PPIs over conventional in situ XL-MS.Item Open Access Asset Tokenization: An Exploration Through the Lens of Extant Theory(2025-01-09) Sumar, Aly-khaan; Verbeke, Alain CM; Kano, Elena (Liena) Lvovna; Li, Pengfei; Schulz, Robert AdolphBlockchain and its related uses as a foundation for a new internet—and, by extension, a new financial system—have garnered much attention in current media and extant literature. This dissertation will explore tokenization, an application of blockchain technology, which aims to create a digital version of an asset on a blockchain, one that can be owned digitally on a digital asset network. The extolled benefits of tokenization are examined through the lens of transaction cost theory (TCT), comprised of transaction cost economics (TCE), transaction cost internalization (TCI) and bounded reliability (BRel) Initial implementations of tokenized asset offerings reflect a technology in a nascent form, but on a trajectory of growth. The evolution of the internet exemplifies how this might unfold, from a medium where users passively consumed written or visual content (web 1.0) to a platform that users participate in and interact with (web 2.0), to an anticipated next stage (web 3.0) that incorporates digital asset networks and becomes a source of data for both people and machines. Ideally, this will democratize the internet, including decentralized, democratized ownership of blockchain native applications. The tokenization of both current real-world assets and digitally native assets is intended to increase access, reduce transactional friction, and enable improved price discovery for assets to ultimately foster a more inclusive financial system. The current immaturity of blockchain technology limits the capacity of tokenization to reduce asset specificity, bounded rationality, and bounded reliability, resulting in little improvement in the efficiency of transactions versus existing alternatives. The findings of this doctoral research bring to the forefront two key expectations related to adopting blockchain-based tokenization. First, the current digital asset ecosystem is an innovation incubator for the traditional financial system (TradFi). As the ecosystem matures, it will be strategically adopted in a piecemeal fashion, bolstering the efficiencies in the current financial system rather than disrupting the current financial system intermediaries. Second, it will be necessary to reduce asset specificity, bounded rationality challenges from intermediaries, and bounded reliability challenges from implementing the blockchain-based technology for successful adoption.Item Open Access Women’s Experiences of Seeking Healthcare at the Intersection of Pregnancy and Housing Instability(2024-12-17) Locey, Claire; Milaney, Katrina; Kelly, Martina Ann; Ducey, Ariel; Nixon, LaraBackground. Women have historically and contemporarily been at the margins of health research due to a lack of qualitative and biomedical research emphasis on sex and gender. This thesis centred patient voice through interviewing 4 women (ages 19-37) about their experiences seeking healthcare in Alberta while unstably housed and pregnant. Guided by an intersectional feminist orientation to critical phenomenology and building upon relevant literature, this thesis sought to understand and uncover: 1. What are the health-seeking experiences of unstably housed women while pregnant in Alberta? 2. How are the experiences and perspectives of these women significant and meaningful to medical education? Methods. I spent five months conducting 7 interviews with 4 participants about their lived experiences of pregnancy and housing instability in Alberta. This entailed following participants at various stages of their pregnancy, with the exclusion of one participant who reflected on two previous pregnancies. Participants were selected through purposive and snowball sampling with Trellis Society and Alcove Recovery Centre for Women. In keeping with the critical phenomenological framework of this study, a smaller sample size was best suited for this project to prioritize depth of interviews and foster relationships with participants. Findings. While participants described that finding healthcare was relatively manageable, accessing and trusting the care they received and building relationships with their prenatal care providers was more complicated and ultimately impacted their healthcare experiences. Participants highlighted that healthcare experiences could be improved through an empathetic educational approach to patient care – with regards to both healthcare education and subsequently patient education. Additionally, participants found that trust, relationship-building, and allocating more time for appointments were important factors in their prenatal care. Conclusion. Participants’ relationships and rapport with their healthcare providers played a vital role in shaping their experience of pregnancy at the intersection of housing instability. This study found that the healthcare system acts as a social determinant of health (SDoH) in and of itself based on experiences of stigma, accessibility, and trust. Despite significant obstacles in their prenatal care journeys, participants expressed positive outlooks for change in healthcare systems and found pregnancy and motherhood to have an overall positive impact in their lives. Medical education would benefit from reflecting on its role, responsibilities, and obligations in shaping the future of care, particularly in addressing the needs and concerns of individuals facing health inequities. The importance of this work lies in illuminating the embodied epistemologies and interpreting the meaning of these women’s health-seeking experiences while at the intersection of pregnancy and housing instability.Item Open Access First Measurement of Antihydrogen Free Fall Using a Radial Time Projection Chamber(2025-01-08) Woosaree, Pooja Devi; Friesen, Timothy; Gomes da Rocha, Claudia; Wieser, Michael EUsing antihydrogen, an apparatus known as ALPHA-g was designed to test Einstein's Weak Equivalence Principle (WEP), where the acceleration due to gravity that a body experiences is independent of its structure or composition. A measurement of the gravitational mass of antimatter has never been done before, as previous experiments used charged particles, which meant the experiments were dominated by electromagnetic forces. The ALPHA-g apparatus uses electrically neutral antihydrogen atoms produced in a vertical Penning-Malmberg trap and trapped in a magnetic minimum trap. By measuring the antihydrogen annihilation positions after a controlled magnetic release of the atoms, the gravitational mass of antihydrogen can be determined. Annihilation positions are reconstructed using a radial time projection chamber (rTPC) surrounding the trapping volume. ALPHA-g was used to complete a successful run in 2022 in the pursuit of measuring the gravitational mass of antihydrogen. The results of this experiment are discussed in this thesis To accurately determine vertical annihilation positions used in the gravity measurement, precise detector calibrations are needed. A laser calibration system was developed and used to gather drift time data in the rTPC, which resulted in drift time measurements and the Lorentz displacement, both of which were used in vertex reconstruction analyses to accurately determine the antihydrogen annihilation positions. Simulations were used to determine the expected electron drift time and Lorentz displacement. Using a Garfield++ toolkit, these observables were simulated from electrons drifting through the gas portion of the ALPHA-g rTPC. Further improvements were made to the reconstruction software to optimise the detector resolution and the number of reconstructed vertices. These methods ultimately led to a free fall direction experiment that concluded antihydrogen fell down on Earth. The experiment was also used to make a preliminary measurement on the gravitational acceleration of a_g = (0:75+/-0:13(statistical + systematic)+/-0:16(simulation))g, where g = 9:81 m/s^2 [1]. Further precision measurements are underway using ALPHA-g to precisely determine the gravitational mass of antihydrogen. Measuring the free-fall direction and gravitational mass of antihydrogen leads the way to a better understanding of the fundamental symmetries in nature, such as the matter-antimatter asymmetry.Item Open Access Monitoring Sand Mining in Nepalese Rivers Using Deep Learning and Earth Observation(2025-01-08) Kshetri, Tek Bahadur; Shugar, Daniel H; Bendixen, MetteSand mining has become one of the major environmental issues impacting river systems worldwide, including in Nepal. This thesis focuses on monitoring sand mining activities in Nepalese rivers using deep learning techniques for detecting sand processing plants (SPPs) and assessing the geomorphological consequences of mining over several decades. The study examines five major rivers: East Rapti, Indrawati, Kamala, Tinau, and West Rapti, using multi-temporal satellite imagery from Landsat, Sentinel-2, PlanetScope, and other remote sensing sources to track the changes in river morphology (between 1973 and 2023) and sand mining operations (between 1990 and 2023). The deep learning model was specifically trained to detect SPPs, providing a comprehensive timeline of sand mining trends. Findings showed that sand mining began to escalate significantly after the year 2000, coinciding with increased infrastructure development in Nepal. The number of detected SPPs peaked between 2015 and 2020, particularly along the Kamal, Ratu (102 locations in 2020) and West Rapti (37 in 2019) rivers, with a notable growth in mining intensity during this period. However, from 2020 onwards, a declining trend was observed, potentially influenced by stricter regulations. This temporal analysis offers key insights into the trajectory of sand mining activities, underscoring the need for continuous monitoring to assess the effectiveness of policy interventions. In parallel, the geomorphological impacts of human intervention were quantified by calculating two key indices—the Braiding Index (BI) and Sinuosity Index (SI)—to evaluate changes in river morphology. Significant geomorphological changes were detected across all studied rivers mainly due to human intervention (sand and gravel mining, river training, and urban encroachment), with both BI and SI showing sharper declines in mining-affected areas than either up- or downstream. In the Tinau River, the BI dropped by over 70% near Butwal mainly due to urban encroachment, indicating a loss of channel complexity. Similarly, the SI in the East Rapti River decreased by more than half, reflecting a transition toward more straightened channels primarily due to urban expansion and mining. Other rivers, such as the Kamala and West Rapti, also exhibited clear trends of reduced channel braiding and sinuosity, with human intervention (mainly due to sand and gravel mining) seriously altering natural river dynamics. This thesis highlights the dual approach of employing deep learning for automated detection of sand processing plants and remote sensing techniques for detailed geomorphological analysis. The integration of these methodologies provides a powerful tool for monitoring and managing sand mining activities across Nepal’s diverse river systems. By offering both a temporal and spatial understanding of the scope and consequences of sand mining, the research underscores the urgent need for sustainable resource management practices. The findings suggest that without stronger regulation and continuous monitoring, sand mining will continue to pose severe risks to river health, biodiversity, and local communities.Item Open Access Dynamic Properties of Chondrocytes(2025-01-07) Otoo, Baaba Sekyiwaa; Herzog, Walter; Hart, David Arthur; Duncan, Neil AlexanderArticular cartilage plays a crucial role in joint function by providing a smooth, load-bearing surface that facilitates movement and absorbs mechanical impact. Chondrocytes, the cells within cartilage, experience continuous mechanical loading in vivo and adapt their volume and shape accordingly, a process that is essential for maintaining cartilage health and function. Volume and shape changes in chondrocytes are key to cellular mechanotransduction, the mechanism by which cells detect and respond to external forces, influencing responses that are vital in both physiological and pathological conditions. This thesis focuses on developing methods to study the effects of dynamic cyclic compression loading on chondrocyte volume and shape changes, not only at the beginning and end of the loading cycle but, crucially, throughout the loading process. These dynamic responses are then compared with those observed under static conditions. A novel experimental approach was developed, incorporating the simultaneous loading and imaging of cartilage tissue, to overcome common technical challenges, such as motion artifacts, which have previously limited studies on chondrocyte deformations to static conditions. Using this setup, cartilage tissues were subjected to cycles of mechanical loading, with cell volume and shape measurements taken at specific time points, both at maximum and minimum stress. The study revealed that chondrocytes exhibit an initial transient decrease in volume within the first few cycles, followed by a gradual return to the baseline (pre-loading) volume despite the surrounding cartilage tissue not fully recovering. This dynamic behavior suggests that chondrocytes engage in active volume regulation as an adaptive response to sustained mechanical loading. Moreover, we also found that cell volume and shape responses under dynamic loading differ substantially from static loading conditions, highlighting the unique behavior of chondrocytes embedded in their native extracellular matrix in response to dynamic mechanical loads. The outcomes of this research underscore the importance of studying cellular adaptation mechanisms in a dynamic, physiologically relevant contexts, rather than under static conditions. This work offers insights into how chondrocytes modulate their volume and shape under cyclic mechanical stress, contributing to our understanding of cellular adaptations within articular cartilage and potentially informing future studies on cartilage health, degeneration, and mechanobiology.