Restricted Theses and Dissertations
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Item Embargo The Impact of Diagnostic Timing on Healthcare Use: Statistical Trends Among Early- and Late-diagnosed Autistic Youth(2025-07-09) Andreasen, Stephanie Marguerite; McMorris, Carly A.; McMorris, Carly A.; McCrimmon, Adam; Zwaigenbaum, LonnieBackground: Autism is a neurodevelopmental condition that now affects 1 in 50 Canadian children, with prevalence rising over the past 20 years. A disparity continues to exist in the ratio of males to females who have an autism diagnosis, with rates as high as four autistic males for every one autistic female. There is also an increasing trend of children and adolescents receiving their autism diagnosis much later in childhood and into adolescence, most often in youth without cognitive or developmental delays and mild autistic traits. A late autism diagnosis (i.e., after 6 years of age) is often associated with multiple co-occurring mental health challenges such as depression, anxiety, non-suicidal self-injury, and suicidal thoughts leading to a higher likelihood of accessing healthcare resources than non-autistic peers. Healthcare administration databases allow for researchers to determine trends in healthcare service usage, and while there is some literature on how much autistic children and adolescents are accessing healthcare services, there has been almost no exploration into the healthcare utilization of late diagnosed autistic people. This is the first study to determine and compare the number of encounters with the healthcare system between early and late diagnosed autistic children and adolescents (herein, youth), and characterize the referral reasons for these encounters. Objectives: The present study extended previous literature on healthcare service access in autistic children and adolescents and: (1) examined if late diagnosed autistic youth access more healthcare services than early diagnosed autistic youth; and (2) investigated if late diagnosed autistic youth have more distinct referral reasons compared to early diagnosed autistic youth. Methods: Participants were identified from a larger file review study; 147 children and adolescents diagnosed with autism spectrum disorder (herein autism) at the Alberta Health Services (AHS) Autism Diagnostic Clinic were included in the study (median age at assessment = 5.0 years, 24.49% female). Records from two administrative databases for participants were obtained: Practitioner Claims and the National Ambulatory Care Reporting System (NACRS), which include information on physician visits, emergency department visits, same-day surgery, visits to outpatient clinics, mental health services, urgent care, and public health clinics. A series of logistic regression analyses were conducted to determine if early versus late diagnosis predicted frequency of healthcare encounters, as well as the number of unique reasons for accessing services, while controlling for age. Sex was also added in the logistic regressions to determine if sex moderated either of these associations. Results: Sample sizes for diagnostic timing groups (early vs. late diagnosed) were comparable (53.74% early diagnosed), as well as a comparable sex distribution (25.0% female in late diagnosed group, 21.5% female in early diagnosed group). When controlling for age of first encounter, a late diagnosis predicted 59% more psychiatric visits than the early diagnosed group (β = 0.47, p = .0243). However, when sex was added as a moderator, this effect only approached significance (p = .066). Diagnostic timing and sex were not significant predictors in the number of visits to the emergency department, outpatient clinics, or overall physician claims. In looking at reasons for health care encounters, diagnostic timing and sex were not significant predictors of the number of distinct reasons for accessing healthcare services. Conclusions: This study is the first of its kind to examine the impact of timing of receiving an autism diagnosis and sex on the frequency of healthcare visits, as well as the unique reasons for accessing healthcare services. Findings highlight that late diagnosed autistic youth accessed a significantly higher number of psychiatric services; however, this effect diminished after adding sex as a moderator into the analysis. Findings from this study can inform post-diagnosis supports as well as training for medical professionals to better support late diagnosed autistic youth.Item Embargo Advances on Post-Compensation Techniques for OFDM Wireless Transmitters(2025-07-01) Orabi, Hammam; Helaoui, Mohamed; Ghannouchi, Fadhel; Leung, Henry; Westwick, David; Abou-Zeid, Hatem; Hammi, OualidThe increasing demand for high-speed wireless communication has driven the need for innovative solutions to address nonlinear distortions in transmitter systems, particularly in Orthogonal Frequency Division Multiplexing (OFDM) architectures. This thesis explores advanced post-compensation techniques designed to mitigate distortions introduced by power amplifiers (PAs) and clipping noise. A comprehensive review of existing methodologies is presented, followed by novel contributions that enhance the performance and efficiency of post-compensation under diverse scenarios. The proposed approaches leverage the Cumulative Distribution Function (CDF)-based and Compressed Sensing (CS)-based frameworks, integrating innovative modifications to improve distortion recovery and computational efficiency. Additionally, a hybrid Digital Pre-Distortion (DPD) and post-compensation technique is developed for Radio-over-Fiber (RoF) front-haul links, addressing unique challenges posed by complex wireless architectures. Extensive simulations and experimental validations demonstrate the efficacy of the proposed techniques in reducing Peak-to-Average Power Ratio (PAPR), minimizing Error Vector Magnitude (EVM), and improving Bit-Error Rate (BER) under practical channel conditions. These advancements contribute to the design of efficient and reliable next-generation communication systems, offering scalable solutions to the challenges of nonlinear distortions in modern wireless networks.Item Embargo A Novel Statistical and Experimental Framework for Real-Time Single Cell Classification using Cell Vibrations(2025-07-02) Al-Khaz'Aly, Ali; Amrein, Matthias Walter; Amrein, Matthias Walter; Farshidfar, Farshad; Belostotski, Leonid; Oblak, Daniel; Moo, Eng KuanCell vibrations are mechanical oscillations generated by living cells which have emerged as a promising biophysical marker reflecting cellular state, function, and identity. Previous studies have identified the presence of cell-specific vibrations; however, their clinical translation has been hindered by methodological inconsistencies and a lack of available analytical frameworks. This thesis presents a novel methodology for non-invasive cellular classification utilizing these vibrations through a technique called Cell Vibrational Profiling (CVP), wherein we acquire data on these nanoscale mechanical oscillations measured via Optical Tweezers (OT). Here we address limitations through three major contributions: first, we advance the real-time vibration acquisition technique through the integration of microinjectors supporting fluidic treatments during vibration experiments, next we perform a comprehensive analysis of experimental factors influencing cell vibrational data, and finally we develop a robust statistical framework called the Vibration Scanner Analysis Suite (VSAS). Using U251 glioblastoma cells as a primary model, significant vibrations were identified at 402.6, 1254.6, 1909.0, 2169.4, and 3462.8 Hz, which were statistically different from polystyrene bead controls (p<0.0001). Using a fixative (Paraformaldehyde) we observed a three-fold decrease in the Coefficient of Variance (COV) produced by U251 cells, confirming the metabolic origin of these signals. Next, we validate this technique by reanalyzing existing datasets and compare experimental conditions to find those that produce maximum differentiation. This was done using Partial Least-Squares Discriminant Analysis (PLS-DA). We found that differentiation was maximized for A549 alveolar epithelium cells when data was collected in conventional petri-dishes (F1=0.89) and while their cell-cycle was synchronized in G0/G1 using serum-deprivation (F1 = 0.82). All findings were generated through the VSAS, which is an automated statistical analysis program purposefully designed to address heterogeneity and noise across CVP datasets and present objective, data-driven results. Together, this research combines both experimental and analytical advancements and establishes a comprehensive pipeline for cell vibration studies with potential applications in cancer detection, pharmaceutical testing, and realtime diagnostics in surgical settings.Item Embargo Electrochemical Exfoliation of Graphene for Vanadium Redox Flow Battery Membrane Modification(2025-06-30) Yang, Lixin; Roberts, Edward; Sabharwal, Mayank; Siegler, Hector De la HozGraphene’s unique combination of high electrical conductivity, large surface area, and mechanical robustness positions it as an ideal material for advanced electrochemical technologies. Among the various synthesis methods developed, electrochemical exfoliation offers a promising route due to its scalability, simplicity, and environmental friendliness. However, there remains a limited understanding of how exfoliation parameters, specifically temperature, pH, and electrolyte composition, influence the structural and functional properties of electrochemically exfoliated graphene. These factors often go unreported or inconsistently reported, despite their substantial impact on graphene quality and properties. This thesis explores the influence of key exfoliation conditions on graphene properties using a two-step electrochemical exfoliation approach. Graphite was first intercalated in 16 M KOH, followed by exfoliation in a 0.1 M aqueous solution of 70% (NH4)2SO4 and 30% (NH4)2HPO4 at pH 7. By systematically adjusting exfoliation temperature, pH, and salt composition, graphene with tunable properties was obtained. The highest electrical conductivity of 512 S cm-1 was achieved at 30 °C, whereas the greatest specific surface area of 1375 m2 g-1 was recorded at room temperature. Characterization using Raman spectroscopy and X-ray photoelectron spectroscopy validated that exfoliation conditions significantly affected oxidation levels, defect density, and heteroatom doping. To demonstrate the material’s applicability, the optimized graphene was deposited as a single layer onto commercial Nafion 115 and 117 membranes using a modified Langmuir Blodgett technique. These graphene-coated membranes showed significant reductions in vanadium ion crossover and improvements in voltage efficiency and capacity retention in vanadium redox flow battery tests. Overall, this work highlights the importance of precise control over exfoliation conditions to produce high-quality graphene. It was found that synthesis parameters directly impact material properties and functional performance. By building these connections, the study provides a clearer understanding of how exfoliation conditions shape graphene quality. Although this study applied electrochemically exfoliated graphene only in a vanadium redox flow battery, the findings suggest strong potential for its use in a wider range of electrochemical energy storage systems.Item Embargo Investigating the Retinal Age Gap as an Innovative Disease Biomarker(2025-06-30) Nielsen, Christopher Stephen; Forkert, Nils Daniel; Fear, Elise; Costello, FionaRecently, the retinal age gap (RAG), the difference between chronological age and retinal biological age predicted from imaging data, has emerged as a promising biomarker for disease screening. RAG estimation is non-invasive, cost-effective, and widely accessible, making it suitable for global health applications. Elevated RAG values have been shown to correlate with increased risk for various ocular and systemic diseases, highlighting its potential as a health indicator. This study addresses key challenges in clinical translation by developing an efficient, multimodal, distributed learning framework for retinal age prediction and RAG estimation, specifically designed for decentralized, privacy-sensitive real-world settings. Therefore, an EfficientNet convolutional neural network was trained on color fundus photography (CFP) from 86,522 UK Biobank participants achieving a mean absolute error (MAE) of 3.11 years, surpassing previous CNN-based models, and demonstrating strong generalizability (MAE of 4.03 years) on the external BRSET dataset. Using this model, the largest RAG analysis to date was conducted, covering 159 disease/injury groups from the 2019 Global Burden of Disease study. Significant RAG differences from healthy controls were found in 56 groups, reinforcing its clinical relevance. To further enhance accuracy and disease sensitivity, the first multimodal retinal age prediction model combining CFP and optical coherence tomography (OCT) was developed, achieving a state-of-the-art MAE of 2.75 years, outperforming CFP-only (3.21 years), OCT-only (3.98 years), and baseline convolutional neural network (3.27 years) models. Multimodal RAG estimates improved disease classification for type 1 diabetes, multiple sclerosis, and chronic kidney disease. Additionally, algorithmic bias analyses showed that while single-modality models exhibited significant sex- and ethnicity-based biases, the multimodal model did not, highlighting how multimodal models may provide benefits from a fairness perspective. For scalable deployment, a distributed learning framework using 8-bit quantized RETFound feature representations was developed, achieving performance comparable to centralized learning and enabling training on mobile and low-resource devices. Additionally, a novel gradient inversion attack method was developed to quantify privacy vulnerabilities, which were subsequently addressed through developing differential privacy methods and an innovative homomorphic encryption approach. Overall, this work provides a robust, generalizable, and privacy-preserving multimodal framework for RAG estimation, advancing its potential for clinical health applications.Item Embargo Graphene-Coated Membranes for Reduced Crossover in Vanadium Redox Flow Batteries(2025-07-04) Vetriselvam, Yogapriya; Roberts, Edward P.L.; Karan, Kunal; Natale, Giovanniantonioanadium redox flow batteries (VRFBs) have become a promising electrochemical energy storage system with strong potential for grid-scale applications when integrated with renewable energy sources. Despite their advantages, the limited selectivity of membranes remains a significant issue, which allows the vanadium ion to crossover, gradually leading to capacity loss during long-term cycling. Although periodic mixing of the electrolytes can help reduce this issue, minimizing crossover is essential for improving system efficiency and reducing operational costs. This study addresses the challenges by applying graphene coatings to commercial cation and anion exchange membranes (Nafion 212 and Fumasep FAP-450). Graphene has a two-dimensional structure that serves as an effective physical barrier, limiting vanadium ion diffusion across the membrane. The impact of coating graphene on one side or both sides of the vanadium flow battery membrane was evaluated, and the battery performance was studied at a range of current densities. While a reduction in ionic conductivity was observed, the coated membranes demonstrated comparable energy efficiency with significantly improved coulombic efficiency: 98% vs 96% for Nafion 212 and 99.8% vs 98% for FAP-450. Permeability results confirmed that the graphene coatings reduced vanadium crossover by 73% and 56% for the coated Nafion and FAP membranes, respectively. Additionally, the capacity decay rate was lower, and self-discharge rates improved by approximately 3-4 times compared to uncoated membranes.Item Embargo Effects of C-type Natriuretic Peptide on Sinoatrial Node Function and Atrial Arrhythmogenesis in Mice with Hypertensive Heart Disease(2025-07-05) Rougier, Elise; Rose, Robert; Deniset, Justin; Chen, S.R. WayneEach heartbeat is initiated by the sinoatrial node (SAN). Normal SAN function is important for proper electrical activation of the atria (upper chambers of the heart) and maintenance of a regular heart rhythm. High blood pressure (hypertension) can cause remodeling in the SAN and atria that can lead to arrhythmias such as SAN disease (SND) and atrial fibrillation (AF). Currently, arrhythmia treatment options are limited. Previous work in our lab demonstrates that Natriuretic Peptide Receptor Type B (NPR-B) and Natriuretic Peptide Receptor Type C (NPR-C) are protective against SAN/atrial arrhythmias. C-type Natriuretic Peptide (CNP) signals through both these receptors; however, the effects of CNP on SAN/atrial remodeling and arrhythmogenesis in hypertensive heart disease are unknown. Accordingly, the effects of CNP on SAN and atrial electrophysiology and arrhythmogenesis were measured in mice infused chronically with Angiotensin II (Ang II), an established model of hypertension which leads to atrial remodeling and arrhythmogenesis. SAN and atrial structure and function were assessed using intracardiac electrophysiology in anesthetized mice, optical mapping in isolated atrial preparations, and histology in atrial tissues. Male and female mice were used to assess for sex differences. Results suggest CNP prevents SAN/atrial remodeling and arrhythmogenesis in AngII-infused mice. AngII+CNP co-infused mice exhibit reduced AF inducibility in association with attenuations in P wave duration (PWD), improved atrial conduction and shorter optical action potential durations (APDs) compared to mice infused with AngII alone. These improvements were found to occur independent of improvements in fibrosis. Further, AngII mice infused with CNP exhibited improved SAN function in association with increased heart rate and improved SAN conduction. These experiments provide new insight into the effects of CNP on SAN/atrial remodeling in hypertensive heart disease. This work could contribute to the development and use of CNP for the treatment of SND and AF in patients affected by hypertensive heart disease.Item Embargo An Optimization Framework for Next-Generation Video Streaming Systems(2025-06-30) Hedayati Majdabadi, Reza; Wang, Mea; Rakai, Logan; Zhao, Richard; Krishnamurthy, DiwakarThe rapid expansion of internet connectivity and digital media consumption has firmly established video streaming as the dominant contributor to global internet traffic. With the advent of immersive formats such as 360-degree and volumetric video, user experiences are shifting from passive viewing to interactive, spatially-aware engagement. However, these advanced formats introduce significant challenges, including extremely high bandwidth demands, real-time processing constraints, viewport prediction inaccuracies, and unpredictable user behavior in three and six degrees of freedom (3DoF and 6DoF) environments. The growing adoption of such technologies has placed considerable strain on existing network infrastructures and streaming platforms, exposing critical limitations in scalability, responsiveness, and quality assurance. Despite temporary mitigations—such as lowering streaming resolution—users often attribute service degradation to Internet Service Providers (ISPs), underscoring the urgent need to better balance Quality of Service (QoS) and Quality of Experience (QoE) in bandwidth-constrained and dynamic environments. This thesis presents a dual-layer optimization framework to address these challenges at both the application and network layers. At the application layer, two frameworks—Opt360 and OptVV—introduce real-time optimization models tailored to immersive media. Opt360 enforces stall-free playback as a strict constraint, accounting for dynamic viewport changes and prediction inaccuracies. It also introduces a staged streaming enhancement to the DASH protocol to improve the quality of field-of-view (FoV) content. Experimental results show that Opt360 ensures seamless playback, remains resilient to head movement variations, and maintains high video quality across fluctuating bandwidth conditions. OptVV extends this approach to volumetric video streaming, offering a comprehensive optimization model built around three components: (1) adaptive QoE optimization to balance video quality and resource efficiency in real time; (2) a DASH-based scheduling strategy tailored to the unique demands of volumetric content; and (3) resource-aware decoding optimization for managing computational complexity. Evaluations reveal that OptVV achieves up to 80% bandwidth savings, 177% improvement in viewport quality, 51\% fewer playback stalls, and 72% faster decoding performance compared to existing solutions. At the network layer, this thesis introduces SOFT-Stream, a scalable, SDN-enabled optimization framework for managing DASH sessions in large-scale ISP environments. SOFT-Stream jointly optimizes the quantity and quality of concurrent streaming sessions, while addressing practical concerns such as dynamic session behavior and real-time optimization overhead. Experimental validation shows that SOFT-Stream outperforms conventional network resource management schemes, delivering a 52% increase in session acceptance, a 200% improvement in bandwidth allocation, a 70% reduction in bandwidth wastage, and a 77% speed-up in computation time. The framework also delivers consistently smoother playback and enhanced end-user experiences across varying network conditions. Together, the contributions of this thesis offer a robust, end-to-end solution for next-generation immersive video delivery.Item Embargo Linearization of Wireless Transmitters Using Blind Digital Post-Distortion Techniques(2025-07-08) Dalbah, Ahmad Ibrahim R; Ghannouchi, Fadhel; Helaoui, Mohamed; Belostotski, Leonid; Wu, HuaqingNonlinearity in power amplifiers (PAs) severely degrades wireless communication signals through distortion and spectral regrowth, posing significant challenges. Currently, the only robust solution to PA nonlinearity is digital pre-distortion (DPD). While digital post-distortion (DPoD) may offer an alternative, conventional DPoD methods often rely on prior PA knowledge or extensive training data, hindering their practical applications. This thesis introduces a novel, blind frequency-domain algorithm to reconstruct distorted orthogonal frequency division multiplexing (OFDM) signals without requiring prior PA information or training sequences, proving effective across diverse transmission scenarios. For single-input-single-output (SISO) systems, the reserved-subcarrier blind DPoD method is proposed, and it employs a polynomial model to estimate nonlinear distortion by analyzing reserved out-of-band (OOB) components generated by the PA. The proposed approach has been shown to reconstruct heavily distorted signals, even with wide bandwidth and significant memory effects, demonstrating superior performance—for instance, improving EVM from over 4.5% to nearly 2% under the challenging nonlinearity of a 20-watt Doherty PA. The algorithm maintains efficacy using only a subset of reserved subcarriers, offering flexibility for real-world constraints. The approach extends to multi-layer multiple-input-multiple-output (MIMO) systems. Tested via simulation in configurations up to 16x16 antennas and 4 data streams (layers), the method effectively addresses both linear crosstalk in frequency-selective channels and nonlinear crosstalk via a proposed DPoD scheme. Measurements further validate its efficacy in a 2-layer 2x2 Doherty PA system. Finally, the proposed DPoD framework is extended to mitigate cross-modulation distortion in concurrent multi-band scenarios arising from PA nonlinearity and concurrent multi-band interactions. This proposed model is evaluated using wideband PA measurements under various conditions, including arbitrary and harmonically related concurrent multi-band signals. The technique’s power scalability is assessed, and a partitioned linearization scheme is presented using low-complexity DPD at the transmitter and the proposed DPoD framework at the receiver. Overall, the proposed blind frequency-domain, adaptable DPoD technique might of- fer a cost-effective alternative for mobile and fixed broadband linearization applications. The results presented in this thesis demonstrated scalability and versatility across SISO, MIMO, and carrier aggregation scenarios, positioning the proposed DPoD method as a com-pelling alternative to conventional linearization for future wireless communication schemes or standards.Item Embargo Experiences of Continuity of Care in Relation to Emergency Department Encounters for People with Kidney Failure: A Qualitative Study(2025-06-26) Kotani, Hana; Elliott, Meghan; Harrison, Tyrone; Thompson, StephanieBackground: People with kidney failure have complex care needs and use the emergency department (ED) at high rates. Little is known about how continuity of care (CoC) relates to ED care seeking for patients with kidney failure. Objectives: To understand the experiences of CoC (i.e., relational, informational, and management) among adults with kidney failure in relation to their recent ED encounter. Methods: Using a qualitative descriptive methodology, we purposively sampled adults with kidney failure (defined as eGFR < 15 mL/min/1.73m2 or receipt of maintenance dialysis) from Alberta who accessed the ED for a non-life-threatening indication within the preceding six weeks from May 2024 until January 2025. We conducted individual semi-structured interviews and analyzed transcripts using a framework analysis approach. Findings: 29 participants were included (12 in-centre hemodialysis, 1 in-centre hemodialysis nocturnal, 7 peritoneal dialysis, 5 home hemodialysis, and 4 without kidney replacement therapy). Themes were identified within CoC types and across before-acute care, during acute care, and after-acute care settings. Under relational continuity, key themes included: stability and trust in care teams, disrupted therapeutic relationships, and re-establishing engagement in circles of care. For management continuity, themes included: safeguarding kidney supports and kidney care fragmentation in the ED. Within information continuity, themes included: patients as continuity self-advocates, bridging care through information sharing and extending continuity beyond the ED. Conclusion: Participants expressed varied experiences of CoC and identified important gaps surrounding emergency care. Strategies addressing perceived gaps in management and informational continuity across both outpatient and acute care settings may help mitigate the burden of ED and acute care use for people with kidney failure.Item Embargo Global Incidence of Appendectomy: A Population-Based Study of the Organisation for Economic Co-operation and Development(2025-06-23) Buie, Elizabeth; Kaplan, Gilaad; Quan, May Lynn; Gimon, TamaraAppendicitis is one of the most common causes of abdominal pain presenting to emergency departments; the highest rates are found between the ages of 10−20 years old and males have a higher lifetime risk than females. Studies have shown early industrialized regions are experiencing a decreasing or plateauing trend in appendicitis incidence, while newly industrialized regions are experiencing a sharp increase. Additionally, the incidence of complicated appendicitis rose after the onset of the COVID-19 pandemic. Temporal trends of appendicitis and appendectomy have shown high heterogeneity across the globe, especially within the Organisation for Economic Co-operation and Development (OECD). The primary outcomes of this thesis are appendectomy temporal incidence trends and the comparison of appendectomy incidence rates pre-pandemic and during the pandemic. We conducted an observational, population-based cohort study using data from 33 of the 38 member regions of the OECD and seven non-member regions from 2000–2023. The OECD provides health outcomes data based on national health surveillance datasets of each region. We used Poisson regression to calculate Average Annual Percentage Change (AAPC) in appendectomy rates with associated 95% confidence intervals (CI) using Davies’ tests for inflection points. AAPCs were pooled across all regions using meta-analysis. Incidence Rate Ratios (IRR) were calculated using Poisson regression to compare rates immediately before (2018−2019) and during (2020−2021) the pandemic and pooled across all regions using meta-analysis. Poisson models were assessed for overdispersion and, if present, negative binomial regression was used. In the 21st century, time trends of appendectomy rates across the OECD dataset displayed variation, with the majority decreasing. There was a decrease in the incidence rate of appendectomy during the pandemic compared to prior. Potential factors for geographic heterogeneity influencing the rates and trends of appendectomy include differential methodological, clinical, environmental, industrial, or behavioural realities. Understanding the influence of COVID-19 on appendicitis may help inform more research into potential viral triggers and ultimately help health systems’ management of the disease. Due to the geographic variation, understanding trends throughout the world may also help inform health policy through a better understanding of the burden of the disease globally.Item Embargo Tailoring Perovskite-Type Oxides for Intermediate-Temperature Solid Oxide Fuel Cells (IT-SOFCs)(2025-06-27) Ndubuisi, Amanda Onyinye; Thangadurai, Venkataraman; Shimizu, George; Marriott, Robert; Roesler, Roland; Dolgos, Michelle; Ye, Zuo-GuangSolid oxide fuel cells (SOFCs) are high-temperature electrochemical devices that convert chemical fuels directly into electricity, offering an efficient and environmentally sustainable approach to power generation. The primary objective of this thesis is to develop and characterize perovskite-type oxide materials for intermediate-temperature (600–800 °C) solid oxide fuel cells (IT-SOFCs), with a focus on enhancing cathodic performance and investigating potential electrolyte candidates. The effect of Fe substitution on the electrochemical performance of PrSrCo2-xFexO5+δ (PSCF, x = 0, 1, 2) was investigated. Electrochemical impedance spectroscopy revealed that partial substitution of Co with Fe in PSCF improved the electrochemical performance of the cathode. A composite of PSCF (x = 1) – Sm0.2Ce0.8O2-δ exhibited the lowest area-specific resistance of 0.07 Ω cm² at 750 °C in air. Additionally, the effect of Pr substitution on the performance of Gd1-xPrxSrCo2O5+ (GPSC, 0 ≤ x ≤ 1) was studied using advanced structural and spectroscopic techniques. It was observed that the partial substitution of Gd with Pr increased the concentration of oxygen vacancies in the structure, thereby enhancing oxygen surface exchange and oxygen ion diffusion. Gd0.1Pr0.9SrCo2O5+ exhibited the lowest ASR value of 0.12 Ω cm² at 750 °C, along with an activation energy of 1.18 eV. The final part of this research examined bismuth-doped barium zinc niobates (BaZn0.33Nb0.67-xBixO3-δ, x = 0, 0.017, 0.03, 0.05) as potential electrolytes. A solubility limit for Bi was identified at x ≈ 0.017, beyond which phase segregation occurred. Although classical proton conduction behaviour was not observed, the substitution of Bi improved bulk density, electrical conductivity, and dielectric properties.Item Embargo We Can Persist – Exploring the Phenomenon of Shame and How Coping Strategies Impact Resilience for People with Lived Experience of Homelessness and Diabetes(2025-06-26) Larsen, Matt; Campbell, David John Thomas; Bouchal, Donna Shelley Raffin; Mushquash, Aislin; Walsh, Christine Ann; Milaney, Katrina J.; Harrison, AlexandraBackground People with lived experience of homelessness and diabetes (PWLEHD) often encounter significant challenges in their day to day lives. While many of these challenges are physical in nature, these individuals also experience considerable psychological stress, and feelings of shame are especially common. Even though shame can cause numerous and significant adverse effects, no study has been done that specifically examines the shame felt by PWLEHD. Objectives The aim of our study was to explore the experiences of PWLEHD with a focus on understanding the phenomenon of shame. In addition, we also explored which coping methods appeared to lead to greater shame resilience for PWLEHD. Methods Hermeneutic phenomenology, the study of interpreting the essence of lived experience, was the philosophical and methodological foundation of this research project. 7 individuals with lived experience of homelessness and diabetes were interviewed for this study. Over 3 interviews, participants were questioned about their shame in regard to homelessness, shame in regard to diabetes, and the ways they cope with shame. 5 co-researchers from the Calgary Diabetes Advocacy Committee (CDAC) participated in many aspects of the project, from providing feedback and suggesting questions for the interview guides to the gathering and analysis of interview data. Results We found 4 main themes related to the shame experienced by PWLEHD: shame in being vulnerable, shame in having to rely on inadequate support systems, shame in being isolated and lonely, and shame in experiencing profound and/or unexpected loss. Constrained agency, the perception that one’s available actions are unduly limited and that control over one’s life is fundamentally reduced, permeated all 4 primary themes. Additionally, we found that problem-focused coping strategies tend to mitigate feelings of shame and facilitate lasting resilience towards it, while avoidant emotional coping strategies provide a momentary reprieve but often result in more shame and decreased shame resilience. Conclusion At a system level, any measures implemented that increase the agency of PWLEHD are likely to reduce their shame. Additionally, the establishment of groups with a focus on fostering empathetic understanding can provide critical support to those dealing with this painful and debilitating emotion.Item Embargo Norepinephrine recruits astrocytes of the paraventricular nucleus of the hypothalamus to regulate corticotropin-releasing hormone neuron activity during fear learning(2025-06-26) Peringod, Govind; Gordon, Grant Robert; Bains, Jaideep Singh; Kurrasch, Deborah Marie; McGirr, Alexander; Lohman, Alexander; Papouin, ThomasAstrocytes, long underappreciated as passive support cells, are now recognized as active regulators of circuit function and behavior. Nowhere is this more consequential for survival than in the hypothalamic paraventricular nucleus, a core integrator of stress and neuroendocrine responses. This thesis investigates how norepinephrine recruits PVN astrocytes during aversive experiences and how this glial activation modulates the excitability of corticotropin-releasing hormone neurons, shaping the strength and persistence of fear memory. Using a combination of single-photon miniscope imaging, fiber photometry, two-photon imaging of acute brain slices, and in vivo pharmacology, I show that PVN astrocytes exhibit rapid and stimulus-specific calcium responses to a range of aversive stimuli. These calcium dynamics evolve across fear learning and recall, increasing in complexity after conditioning and reflecting oscillatory anticipation of threat. Pharmacological blockade of α1-adrenoceptors abolishes this learning-dependent recruitment, implicating norepinephrine as a critical upstream modulator. Using a genetic loss-of-function approach to chronically suppress astrocyte calcium signaling, I demonstrate that PVN astrocytes are required to constrain CRHPVN neuron activity during stress, and support perfusion and normoxia during stress. Together, these findings reveal that astrocytes of the hypothalamic PVN are not merely reactive, but serve as dynamic, neuromodulator-sensitive integrators that are poised to shape both the encoding and expression of fear. By exploring a norepinephrine-driven, purinergic signaling mechanism in a major stress effector node, this work advances a new framework for understanding glial contributions to threat processing.Item Embargo Artificial Intelligence Powered Platform for Capillary Microfluidic Design Automation (AI-CMDA)(2025-06-27) Khalghollah, Mahmood; Far, Behrouz; Sanati-Nezhad, Amir; Hejazi, Hossein; Souza, Roberto; Mohammed, Emad; Rezai, PouyaPoint-of-care (POC) testing has become an essential tool across modern healthcare, environmental monitoring, food safety, and veterinary applications, enabling rapid and cost-effective diagnostics in situations ranging from centralized laboratories to remote and resource-limited locations. Capillary microfluidic chips (CMCs) show tremendous promise in this arena, as they utilize capillary forces to autonomously drive fluid motion and perform a sequence of operations without relying on external power sources or active control. However, designing or redesigning these chips remains a time-consuming and largely manual iterative process, often requiring several weeks to over a year, depending on assay complexity, material compatibility, and fabrication variability. This slow and empirical development restricts the scalability, responsiveness, and broader adoption of CMC-based solutions, especially during urgent health crises or in resource-limited environments, highlighting the critical need for an integrated framework that systematically improves the design process. To bridge this gap, this thesis develops the Artificial Intelligence-Powered Capillary Microfluidic Design Automation Platform (AI-CMDA) that systematically address experimental analysis, predictive modelling, and optimization to form a unified design automation platform for CMCs. Its first module, Capillary Microfluidic Chip Analysis (CMCA), focuses on automating the extraction of fluidic behaviour from experimental videos by applying deep learning-based segmentation techniques to identify the fluid interface position over time. The second module, Capillary Microfluidic Chip fluid path Prediction (CMCP), develops a hybrid predictive framework that couples reduced-order hydraulic–electric circuit models with neural network models trained on experimental and computational data, enabling fast and accurate prediction of fluid motion through complex microfluidic networks, while significantly reducing computational cost compared to full CFD simulations. The third module, Capillary Microfluidic Design Automation (CMDA), integrates these capabilities into an optimization engine that autonomously refines chip geometries to meet user-defined performance targets, using surrogate-assisted gradient-based optimization. Combined, these modules enable fully automated design, prediction, and optimization of CMCs, accelerating the development of next-generation microfluidic devices. The capabilities of the AI-CMDA platform are demonstrated through the design, fabrication, and experimental validation of a Tree-Shaped Concentration Gradient Generator (TCG-CMDA) optimized for minimum inhibitory concentration (MIC) assays. Leveraging AI-CMDA, the entire design–build–test cycle was reduced from several weeks to less than 24 hours. The platform successfully identified optimized chip geometries that achieved targeted dilution profiles with over 95% agreement between predicted and experimentally measured concentration distributions, verified through fluorescent dye assays. Additionally, fluid path predictions achieved an R² of 0.97 relative to experimental time-course data, validating the platform predictive accuracy. Experimental prototypes fabricated from AI-optimized designs consistently outperformed manually designed counterparts in achieving linear and reproducible concentration gradients across multiple independent runs. This case study highlights the ability of AI-CMDA to dramatically compress prototyping timelines, enhance design reproducibility, reduce reliance on trial-and-error and expert intuition, and establish a scalable, automated pathway for capillary microfluidic chip development. By integrating data-driven design, predictive modelling, and optimization into a single streamlined framework, AI-CMDA paves the way for democratizing and accelerating the deployment of next-generation microfluidic systems. These results demonstrate that AI-CMDA can substantially accelerate CMC development while enhancing precision and scalability for high-performance microfluidic applications.Item Embargo Ready Assessment of Prognostic Indicators and Diagnostics (RAPID) for Concussion(2025-06-12) McIntosh, Samantha Joan; Debert, Chantel; Crowder, Kathryn; Hill, Michael; Ganesh, AravindMild traumatic brain injury (mTBI) more commonly known as concussion impacts millions of individuals every year. Annually in Canada alone, approximately 400,000 individuals sustain a concussion. Fortunately, most individuals recover from this type of brain injury and have resolution of concussion symptoms within 2-4 weeks of injury. However, a substantial proportion, up to 30% of individuals, have prolonged recovery, known as persisting symptoms after concussion (PSaC). Prolonged recovery can have negative impacts on individuals’ quality of life and ability to participate in activities of daily living. Providing accurate prognosis for these individuals acutely post-concussion may aid in their ability to access acute concussion care and ultimately could reduce symptom burden. This thesis begins by characterizing our current knowledge on concussion prognosis by evaluating the literature using a systematic review and meta-analysis to identify clinical risk factors associated with PSaC in adults with concussion. The next chapter describes the protocol for a prospective observational case-controlled study, the Ready Assessment of Prognostic Indicators and Diagnostics (RAPID) for Concussion Study. In the following chapter, the 1 month outcomes of the RAPID Concussion Study are presented and risk factors of PSaC at 1 month as well as predictors of time to recovery are examined. The thesis then goes on to discuss clinical outcomes at 3 and 6 months post-concussion, and the potential utility of fluid biomarkers for concussion prognosis. This work aims to characterize our current knowledge on acute concussion prognosis for adults and build on the literature by evaluating risk factors of PSaC in an adult cohort that is representative of a diverse population of adults who sustain a concussion. The risk factors identified during the systematic review and meta-analysis were formative in guiding a priori risk factors that may be relevant for the RAPID Concussion Study. In this study, we identified age, sex, loss of consciousness (LOC), post-traumatic amnesia (PTA), and acute physical and emotional symptoms as important clinical factors associated with PSaC at 1 month and time to recovery in adults with concussion. Chapter 5 will present preliminary results evaluating risk factors of PSaC at 3 and 6 months post-concussion. Chapter 6 will present preliminary results examining the utility of fluid biomarkers as a potential objective marker of concussion recovery in adults. Together, this thesis provides data to suggest that there are acute variables including age, sex, clinical signs (LOC and PTA) and acute symptoms that are associated with PSaC. We also show that clinical predictors vary with time post-concussion and highlight the need for more objective risk factors of PSaC, potentially blood biomarkers, that may increase prognostic accuracy. Finally, larger prospective multicentre trials are necessary to validate the results presented here and develop a multivariable prognostic tool for clinical utility.Item Embargo Carbon Credits: Holy Grail or Hot Air? Do Carbon Credits Enhance Firm Value? An Analysis of Financial and Legitimacy Moderators.(2025-06-26) Versfeld, Niels Gerardus; Koskinen, Yrjo Juhani; Osiyevskyy, Oleksiy; Herrremans, Irene; Pandes, Ari J.; Schulz, Robert A.; El Ghoul, SadokThis study examines from both financial and legitimacy perspectives the nuanced relationship between carbon credit use and firm value for North American firms. While carbon credits are increasingly embedded in corporate sustainability strategies, their impact on firm value remains contested. Resource-based theory views credits as sources of competitive and financial advantage, whereas legitimacy theory emphasizes stakeholder perceptions as critical to the acceptance and valuation of corporate climate actions. Using a panel dataset of more than 5,000 firm-year observations from publicly-listed North American companies, this research applies fixed effects and dynamic panel regression models to assess whether carbon credit use enhances firm value, as measured by Tobin’s Q. The results indicate no significant relationship between carbon credit use and firm value overall, challenging expectations that market-based emissions strategies consistently drive financial returns. However, in jurisdictions with stringent climate regulation, such as Canada, and for firms whose products enable customer emissions reductions, carbon credit use is positively linked to firm value. Conversely, high-emission firms using credits face negative impacts, particularly in Canada, reinforcing the importance of firm context. The study also found no financial advantage for originating or being allocated credits compared to purchasing them, implying that legitimacy signals and cost efficiency may outweigh innovation-related benefits. These findings underscore that stakeholder legitimacy, not only financial logic, plays a critical role in shaping investor’s views on firm value. Implications include the need for strengthened verification standards, transparent reporting, and strategic alignment of credit use with stakeholder expectations. The study provides guidance to firms and policymakers navigating the dual demands of environmental performance and legitimacy.Item Embargo Isolation and Characterization of Human Adipose Derived Mesenchymal Stromal Cells and the Small Extracellular Vesicles They Produce(2025-06-26) Booth, Heather Carole; Sen, Arindom; Badv, Maryam; Hart, David ArthurMesenchymal stromal cells (MSCs) are unspecialized cells that can be isolated in small quantities from adult tissues (e.g. fat, bone marrow). They can be cultured to increase their numbers to clinically relevant numbers and then implanted into damaged or diseased tissue to upregulate repair. Evidence now suggests that the therapeutic qualities of MSCs may be due, at least in part, to the small extracellular vesicles (sEVs) they release during culture. sEVs are non-living, membrane-bound nanoparticles that, upon release, migrate to target cells where they deliver bioactive cargo to elicit specific biological responses, such as tissue repair. Given their non-living nature, sEV-based therapies have fewer translational roadblocks compared to MSC implantation. However, the production of functionally tailored sEV populations for clinical purposes will first require the development of standardized protocols for MSC isolation and culture. During this project, a comprehensive protocol was developed to isolate cells from fat tissue and was conducted using both serum-containing and serum-free culture medium. Serum is a commonly used animal-derived component of culture medium, despite evidence that it alters cell behaviour and contains contaminating sEVs. A combination of techniques based on the literature was used to characterize cell and nanoparticle populations, which demonstrated that the populations possessed MSC- and sEV-associated characteristics, respectively, in both serum-containing and serum-free media. However, the extent to which they exhibited these characteristics in each type of medium differed. The protocols developed during this project will allow researchers to reproducibly generate MSC-derived sEVs, thereby bringing the field closer to the widespread implementation of sEV-based therapies.Item Embargo Towards Practical and Resource-Efficient Volumetric Video Streaming(2025-06-25) Heidarirad, Hadi; Wang, Mea; Boyd, Jeffrey; Runions, AdamVolumetric video offers immersive, six-degrees-of-freedom (6DoF) experiences but presents significant challenges in streaming due to its massive data size, high bitrate demands, and computational complexity. This thesis proposes two systems to address these challenges. First, we present VV-DASH, an end-to-end framework for adaptive volumetric video streaming over DASH. VV-DASH introduces a codec-agnostic segment format (DVV) that consolidates compressed volumetric content into DASH-ready segments, improving streaming throughput by 13.2% and reducing bandwidth demands. It also features a parallel accelerator that enables real-time decoding—achieving up to 183 fps for Draco and 30 fps for V-PCC—while supporting flexible integration with diverse codec pipelines. Next, we introduce TARS, a temporal-spatial adaptive streaming solution for dynamic point cloud videos that reduces temporal redundancy by exploiting inter-frame correlations. TARS employs a Field-of-View (FoV)-aware approach to intelligently avoid the retransmission of redundant regions across consecutive frames, leveraging a specialized Point Cloud Structural Similarity metric for precise similarity assessment. Experiments show that TARS reduces bandwidth usage by up to 66% while maintaining high visual quality (MSE as low as 0.145), and boosts decoding speed by up to 2.42x compared to decoding all I-frames. These results demonstrate the effectiveness of VV-DASH and TARS for enabling practical, real-time, and resource-efficient volumetric video streaming.Item Embargo Temporal Trends of Depression Hospitalization and Suicide in those with Inflammatory Bowel Disease(2025-06-26) Markovinović, Ante; Kaplan, Gilaad G.; Ma, Christopher; Shaheen, Abdel-AzizInflammatory bowel disease (IBD) is a chronic inflammatory condition currently affecting more than 320,000 Canadians. Individuals with IBD are more susceptible to mental health disorders, such as depression. Research has found that those with IBD have increased risk of both depression and suicide death compared to non-IBD individuals. However, literature examining severe outcomes of depression in IBD, including depression hospitalization and suicide death, is limited. This population-based study used administrative data to identify the prevalent IBD population and 10:1 age- and sex-matched controls in Alberta from fiscal year 2005/06 to 2021/22. The primary outcomes were hospitalization for depression and suicide death. Using an IBD inception cohort of IBD cases, the 1-, 3-, and 5-year risks of depression hospitalization with 95% confidence intervals (CI) were calculated. Using the prevalent IBD cohort and controls, average annual percent change (AAPC) with 95% CI were calculated. AAPCs for depression hospitalization were stratified by age (<18, 18–40, 41–64, and ≥65), sex (male or female), and geography (urban vs. rural) for both cases and controls, with cases further stratified by IBD type (Crohn’s disease or ulcerative colitis). AAPCs (with 95% CI) were also calculated for suicide deaths in cases and controls. The 1-, 3-, and 5-year risk of depression hospitalization in those with IBD was 0.11% (95% CI: 0.07%, 0.18%), 0.29% (95% CI: 0.20%, 0.40%), and 0.56% (95% CI: 0.42%, 0.72%), respectively. Hospitalization rates for depression in those with IBD significantly decreased with an AAPC of −3.38% (95% CI: −4.72, −2.03) from 2.55 (95% CI: 1.73, 3.37) per 1,000 in 2005/06 to 2.08 (95% CI: 1.61, 2.55) per 1,000 in 2021/22, and significantly decreased in controls with an APPC of −2.04% (95% CI: −2.61, −1.48). Hospitalization rates for depression in those with IBD significantly decreased for all age stratifications except pediatric cases (AAPC: 0.74%; 95% CI: −8.43, 10.85). Suicide deaths in those with IBD were 0.26% (n=95) and decreased over time (AAPC: −1.35%; 95% CI: −5.58, 3.06). Depression hospitalizations in individuals with IBD have decreased overall. Suicide deaths have accounted for 0.26% of the prevalent IBD population and remain stable.
