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Municipal Interpretations of Indigenous-Settler Reconciliation in Planning for Urban Redevelopment and Regeneration
No full textMunicipalities in settler-colonial countries such as Canada, Australia, and New Zealand are placing new emphasis on improving Indigenous-settler relations and addressing colonial injustices in the city, in discourse if not in practice. In Canada, municipalities increasingly identify comprehensive planning projects that define future change and (re)development in the city as a space through which to advance these ‘reconciliation’ objectives. However, such projects are also intertwined with gentrification outcomes, outcomes that include Indigenous displacement, dispossession, and erasure. While a growing body of scholarship underlines these settler-colonial dimensions, it is unclear if such connections are made in practice as municipal planners turn their attention to both advancing Indigenous-settler reconciliation and mitigating gentrification-induced displacement.
This dissertation deepens emerging dialogue between gentrification scholarship and literature on settler-colonial urbanism and Indigenous recognition as it examines tensions between gentrification, reconciliation, and displacement mitigation within municipal comprehensive planning. To identify the continuity and/or disruption of colonial-capitalist relations therein, I interrogate 1) how reconciliation discourses are translated into area redevelopment plans, 2) how municipal planners represent reconciliatory planning practice, and 3) how planning responses to gentrification concerns address the colonial dimensions of displacement. The research looks at comprehensive planning projects in cities across Canada, with a particular focus on Vancouver and Montréal. I draw on critical discourse analyses of both project documents and interviews with municipal planning staff and other relevant actors.
The findings reveal that municipal planners negotiate multiple colonial-capitalist ‘boundaries’ at the nexus of redevelopment and reconciliation: those of Indigenous recognition, existing planning structures, and status quo regeneration objectives. While these boundaries are often reproduced as planners look to advance reconciliation and mitigate displacement within their constraints, more transformative policies, approaches, and mentalities are also beginning to emerge. The research expands on the (im)possibilities of state-led reconciliation through a planning lens, nuances the dynamics of Indigenous recognition in planning within a new context, and provides insight into discursive and policy shifts regarding gentrification and displacement, including limitations therein. It also underlines the importance of building planners’ motivations and capacities to disrupt colonial-capitalist planning relations
Grounded or Guessing? An Empirical Evaluation of LLM Reasoning in Agentic Workflows for Root Cause Analysis in Cloud-based Systems
No full textRoot cause analysis (RCA) is essential for diagnosing failures within complex software systems to ensure system reliability. The highly distributed and interdependent nature of modern cloud-based systems often complicates RCA efforts, particularly for multi-hop fault propagation, where symptoms appear far from their true causes. Recent advancements in Large Language Models (LLMs) present new opportunities to enhance automated RCA. In particular, LLM-based agents offer autonomous execution and dynamic adaptability with minimal human intervention. However, their practical value for RCA depends on the fidelity of reasoning and decision-making. Existing work relies on historical incident corpora, operates directly on high-volume telemetry beyond current LLM capacity, or embeds reasoning inside complex multi-agent pipelines---conditions that obscure whether failures arise from reasoning itself or from peripheral design choices.
In this thesis, we present a focused empirical evaluation that isolates an LLM's reasoning behaviour. We design a controlled experimental framework that foregrounds the LLM by using a simplified experimental setting. We evaluate six LLMs under two agentic workflows (ReAct and Plan-and-Execute) and a non-agentic baseline on two real-world case studies (GAIA and OpenRCA). In total, we executed 48,000 simulated failure scenarios, totalling 228 days of execution time. We measure both root-cause accuracy and the quality of intermediate reasoning traces. We produce a labelled taxonomy of 16 common RCA reasoning failures and use an LLM-as-a-Judge for annotation. Our results clarify where current open-source LLMs succeed and fail in multi-hop RCA, quantify sensitivity to input data modalities, and identify reasoning failures that predict final correctness. Together, these contributions provide transparent and reproducible empirical results and a failure taxonomy to guide future work on reasoning-driven system diagnosis
Enhanced Performance and Stability of Planar Heterojunction Solar Cells via Hole Transport Layer Engineering and Low-Cost Fabrication
No full textGlobal energy demand has grown extensively in recent decades, and it has continued to rely on fossil fuels that are accompanied with environmental concerns. This has intensified the research for renewable energy alternatives with solar power standing out as a leading candidate due to its abundance, scalability and rapidly declining costs. As photovoltaic (PV) technologies have evolved significantly, their widespread adoption continues to face barriers in efficiency, stability and manufacturing costs.
While inorganic semiconductors such as crystalline silicon remain dominant due to their favorable band gap and long-term stability, hybrid solar cells such as organic–inorganic heterojunction solar cells have gained increasing attention for their ability to combine the tunability and ease of processing of organics with the superior charge transport and stability of inorganics. In this work, we have investigated the stabilization of planar heterojunction solar cells through the incorporation of dimethyl sulfoxide (DMSO) into PEDOT:PSS-based hole transport layers (HTLs). The acidic and hygroscopic nature of PEDOT:PSS is a well-known source of device instability, leading to accelerated degradation under ambient conditions. By employing DMSO as a cosolvent alongside ethylene glycol and methanol, this work demonstrates that optimized modification enhances electrical conductivity, reduces recombination, and markedly improves stability. Devices incorporating DMSO-treated PEDOT:PSS films retain nearly 89.4% of their initial efficiency after 72 hours of ambient storage, in contrast to the sharp decline seen in control devices without DMSO. Atomic force microscopy (AFM) and X-ray photoelectron spectroscopy (XPS) confirm improved surface morphology and a favorable redistribution of conductive domains. The findings establish DMSO modification as a practical, cost-effective strategy for producing more inherently resilient heterojunction solar cells.
Following these insights, we introduce dimethyl sulfone (DMSO₂) as a solid-state additive for PEDOT:PSS films. Unlike liquid cosolvents, DMSO₂ crystallizes upon drying, inducing a unique reorganization of polymer microstructures that enhances phase separation and alignment of conductive PEDOT chains. The resulting films exhibit superior conductivity, improved charge transport, and greater stability against moisture induced degradation. Devices fabricated with DMSO₂-doped PEDOT:PSS achieve efficiencies up to 15.5% (EMD2) and an average T80 of ∼913 h of ambient storage (ED2), a substantial improvement over conventional treatment. Through a combination of external quantum efficiency (EQE), AFM, and conductivity analyses, this work highlights the ability of DMSO₂ to simultaneously enhance efficiency and extend ambient storage longevity, offering an environmentally benign and scalable pathway for advancing PEDOT:PSS-based solar technologies.
We also address the challenge of electrode optimization by introducing a rapid and low-cost method of shadow mask fabrication by desktop 3D printing. While electrode geometry is critical to current collection efficiency, series resistance reduction, and overall photovoltaic performance, traditional fabrication techniques are expensive, time-consuming, and inflexible. By employing polyethylene terephthalate glycol-modified (PETG) filaments for 3D printing, this study demonstrates a streamlined approach to fabricating custom shadow masks for top electrode manufacturing in hours rather than weeks. Comparative testing of three geometries (comb-like busbar, central busbar, and crossed busbar) shows that the central busbar design achieves superior efficiency enhancement by 21.62% and improves the fill factor by reducing resistive losses and balancing optical transparency. This work illustrates how low-cost additive manufacturing can democratize device prototyping, accelerate design iterations, and lower research and production costs without compromising performance.
In summary, this dissertation presents a cohesive exploration of strategies to improve efficiency, stability, and fabrication simplicity of planar heterojunction solar cells. Through targeted material modifications and innovative fabrication methods, the studies collectively highlight pathways to bridge laboratory innovation with commercial feasibility. Together, these contributions underscore the critical role of polymer modification and accessible fabrication in the evolution of next-generation solar cells, with the ultimate goal of advancing the prospects of clean, scalable, and sustainable energy technologies
Lower Bounds on Average-Case and Non-Local Quantum Computation
No full textThis thesis studies computational and information-theoretic limitations in both classical and quantum models of computation. It is organized into two parts, each addressing a different aspect of computational hardness. Despite their differences, both parts share a common goal: understanding how structural and physical constraints shape what classical and quantum algorithms can achieve.
In Part I, we present lower bounds on the average-case complexity of certain tasks in classical and quantum settings. We develop a general framework for constructing efficient worst-case to average-case reductions. Applying this framework, we obtain such reductions for fundamental problems in a variety of computational models; namely, algorithms for matrix multiplication, streaming algorithms for the online matrix-vector multiplication problem, and static data structures for all linear problems, as well as the multivariate polynomial evaluation problem. We further extend this framework to the setting of quantum algorithms, along the way obtaining a tight bound on the average-case quantum query complexity of the matrix-vector multiplication problem. Our techniques rely crucially on tools from additive combinatorics. In particular, we show local correction lemmas that rely on new probabilistic and noise-robust versions of the quasi-polynomial Bogolyubov-Ruzsa lemma.
In Part II, we give quantum gate and entanglement lower bounds on certain non-local tasks. A non-local quantum computation (NLQC) replaces direct interaction between two quantum systems with a single simultaneous round of communication and shared entanglement. We study two classes of NLQC, f-routing and f-BB84, which are of relevance to classical information theoretic cryptography and quantum position-verification. We give the first non-trivial lower bounds on entanglement in both settings, under the assumption of perfect correctness. Within this setting, we give a lower bound on the Schmidt rank of any entangled state that completes these tasks for a given function f(x,y) in terms of the rank of a matrix G whose entries are zero when f(x,y)=0 and strictly positive otherwise. This also leads to a lower bound in terms of the non-deterministic quantum communication complexity of f. Due to a relationship between f-routing and the conditional disclosure of secrets (CDS) primitive studied in information theoretic cryptography, we obtain a new technique for lower bounding the randomness complexity of CDS. Finally, we show that the number of quantum gates plus single-qubit measurements required to implement a function f is at least linear in the entanglement-assisted simultaneous-message-passing communication complexity of f. As a consequence, we derive a linear lower bound for the inner-product function
Detection and Characterization of Viruses in the Environment Using Established and Novel Sequencing Approaches
No full textViruses play critical roles in both the environment and public health systems. This thesis integrates genomic sequencing methodologies to detect, characterize, and monitor viral diversity, advancing both fundamental ecological research and applied pathogen surveillance. Through three focused research projects, this work demonstrates how targeted and metagenomic sequencing strategies can address key knowledge gaps in environmental virology, plant pathology, and viral public health surveillance.
The first objective (Chapter 2) was to develop and apply novel tiled-amplicon sequencing assays for Influenza A virus (IAV) H3N2 and respiratory syncytial virus (RSV) A in wastewater-based surveillance. These assays successfully recovered near-complete viral genomes from wastewater samples collected during the peak of the 2023/2024 respiratory virus season. Genomic coverage trends mirrored clinical case data within the associated public health region, validating the approach as a complementary tool to traditional clinical surveillance. Variant deconvolution analyses revealed distinct spatiotemporal patterns in variant distribution, demonstrating the capacity of these assays and bioinformatic tools to resolve community-level transmission dynamics and emerging viral lineages.
The second objective (Chapter 3) extended this surveillance framework to the agriculturally significant Tomato brown rugose fruit virus (ToBRFV). A multiplexed tiled-amplicon assay was developed, achieving significant improvements in viral genome recovery compared to metagenomic RNA shotgun sequencing while reducing sequencing costs and resource requirements. ToBRFV clades circulating in Ontario wastewater were identified, including variants later recognized through global surveillance initiatives, underscoring the assay’s potential for early detection and the value of wastewater systems as environmental reservoirs for plant viruses.
The third objective (Chapter 4) involved the assembly and characterization of the complete genome of a novel freshwater algal virus, Chrysochromulina parva virus BQ1 (CpV-BQ1). Using a hybrid Nanopore and Illumina sequencing strategy, a high-quality 165,454 bp genome was assembled and annotated, revealing hallmark nucleocytoplasmic large DNA virus (NCLDV) genes and diverse functional categories associated with viral replication, host manipulation, and capsid formation. This work offers important insights into viral infection of the ecologically important freshwater algal species C. parva. Moreover, it establishes a methodological framework for the complete sequencing, assembly, and annotation of algal virus genomes.
Collectively, this thesis advances environmental virology and viral surveillance systems by developing scalable, sensitive, and cost-effective genomic workflows for virus detection and characterization in freshwater environments. By integrating virus ecology with applied public health and agricultural surveillance within a One Health framework, this work underscores the interconnectedness of environmental, human, and agricultural systems and provides practical guidance for future viral genomics research and pathogen monitoring programs
Mass Timber High-Rises: Integrating Form, Structure, and Dwelling Typologies
No full textThis thesis explores mass timber not only as a sustainable material, but as a spatial and conceptual framework for reimagining vertical urban housing. It treats mass timber as massing, a modular and volumetric system that organizes structure, form, and inhabitation through stacking, subtraction, and spatial play. Moving beyond material or structural efficiency, the project frames mass timber using a grid and modular based kit of parts as both constraints and opportunity as an architectural language for adaptable, community-oriented high-rise housing that responds to the environmental and social challenges of urban living.
Drawing inspiration from Adrian Wong’s explorations of modular systems and spatial adaptability, the research adopts a process of modular arrangement, like assembling and rearranging blocks, where modular volumes are assembled, layered, and reconfigured to generate diverse typologies and shared communal spaces. The project asks: How can the modular logic of mass timber inspire new forms of high-rise housing that balance environmental responsibility with social and spatial richness? The study focuses on how a repetitive volumetric modular unit can be transformed into lively, varied living environments through deliberate acts of aggregation and void-making through subtractive and additive massing.
In addressing Canada’s housing crisis and the global demand for low-carbon, rapidly deployable construction, this thesis positions mass timber’s prefabricated modularity as a key strategy for delivering affordable, efficient, and low-embodied-carbon housing construction that also inspires diverse spatial possibilities. Its lightweight nature reduces on-site labor, and the capacity for off-site fabrication enables faster assembly, minimal waste, and lower emissions compared to conventional concrete or steel systems. Through digital modeling and speculative design studies using Autodesk Revit, the research develops a catalogue of spatial strategies that demonstrate how mass timber’s modular volume can act as both structure and medium for spatial play, producing architecture that is sustainable, adaptable, and deeply human, uniting environmental performance with expressive form and social value
Navigating the Politics of Food System Futures: Post-Disaster Food Sovereignty in Puerto Rico
No full textPuerto Rico has been devastated by protracted economic collapse. Hurricanes Irma and Maria’s landfall in 2017 shattered the archipelago, followed by earthquakes in 2020, the COVID-19 pandemic, and Hurricane Fiona in 2022. There have been chronic issues with recovery post-disasters. In the context of economic, political, and ecological uncertainty, one of the most pressing concerns for Puerto Rico now and in the future will be its food supply. This research explores the effects of sequential disasters on the people of Puerto Rico and their food system. The study investigates food insecurity, government responses, and the will toward food sovereignty. The study is derived from individual in-depth interviews (n=84), archives (legal/court documents), media analysis (newspapers/photographs), and government data. The research adopts a critical and decolonial framework to the study of post-disaster Puerto Rico
Mine Tailings as Sources of Greenhouse Gas Emissions: A Multi-Site Investigation Incorporating Isotopic Signatures
No full textTailings are the slurry waste product from mining operations deposited in impoundments in large quantities and are associated with challenging environmental issues such as acid mine drainage. Sulfide-rich tailings can be oxidized due to O2 ingress and water infiltration, producing H+ that dissolves surrounding carbonate minerals, leading to CO2 production. To characterize the seasonal CO2 emissions from tailings impoundments with various cover systems and explore the geochemical and physical controls on the emissions, field studies were conducted at five mine tailings sites in Canada. The sites included tailings that are uncovered (Giant Mine, NT), sand/gravel-covered (South Bay Mine, Long Lake Mine, and Nickel Rim North Tailings, ON), and multi-layer-covered with O2-consuming-organic material and desulfurized tailings (Strathcona Tailings Management Area, ON).
Physical properties were measured and analyzed including tailings water content, soil temperature, particle density, and porosity. Tailings solid and pore water samples were collected via manual coring and squeezing extraction from core samples. Gas depth profile sampling and gas flux chambers were used to quantify subsurface gas concentrations and CO2 fluxes in the subsurface and to the atmosphere. To characterize the stable carbon isotope signatures across phases and source-trace CO2 transport, the δ13C values of solid, aqueous, and gaseous phases in the investigated tailings systems were determined.
At uncovered and sand/gravel covered sites with high sulfide content, acidic conditions (pH 20 vol.%), and substantial surface fluxes (up to 140 kg ha-1 day-1) to the atmosphere were measured. Effective covers (composite desulfurized tailings/organic materials) suppressed acid generation but still sustained considerable CO₂ fluxes to the atmosphere (~100-120 kg ha⁻¹ day⁻¹). Sites rehabilitated with different cover systems showed CO2 fluxes in June and July that were twice as high compared to September and October. δ13C values (-4‰ to +3‰) of pore-gas CO2 samples suggest that CO2 originated from geogenic carbonate mineral dissolution at the sand/gravel-covered site. At the multi-layer-covered site, the δ13C-CO2 values of <-20‰ in the organic material cover and -10‰ to -5‰ in the deeper desulfurized tailings, suggest mixed sources of CO2 production. This study demonstrates that tailings emit CO2 at rates exceeding or comparable to wetlands, forests, and farmland sites. A large portion of the CO2 is derived from primary carbonate minerals contained within the mine wastes. Integrating CO2 emissions into global C budgets is critical, and future cover designs must balance remediation control with C management to mitigate climate impacts
Real-Time Speed of Sound Estimation for Point-of-Care Tissue Health Assessment.
No full textSpeed-of-Sound (SoS) is a fundamental acoustic property that emerging Ultrasound (US) modalities aim to leverage for tissue health assessment and image quality improvement. Tissue SoS has been tied to tumor malignancy classification, muscle health assessment, steatotic liver classification and bone porosity measurement among other. Consequently, leveraging the tissue SoS for more accurate beamforming, not only enables higher resolution imaging, leading to more accurate cyst classification, but also correct for heavy skull aberration and defocusing during High Intensity Focused Ultrasound. Directly measuring the tissue SoS requires multi-site access, thus limiting such methods to the breast and some limbs. Current Pulse-echo SoS estimation algorithms demand high computation time or provide a single global SoS value, either constraining real-time assessment or decreasing accuracy.
In this dissertation, I developed: 1) A single-shot SoS estimation algorithm that estimates the global SoS of the media by leveraging the signal consistency across channels from a single transmitting event. 2) Multiple localized SoS estimators that leverage image dissimilarity from multiple transmission events to provide the user with the SoS of the segmented regions in the image, either in stratified media, or arbitrary configurations. By developing custom image formation, segmentation, raytracing and wavefront tracking frameworks, optimal transmission schemes, and GPU acceleration on a portable, research scanner, I’m able to provide robust, accurate, SoS estimation platforms that have been thoroughly validated in vitro, ex vivo and in vivo.
This dissertation research aims to bridge the gap between SoS research and other US modalities that can benefit from the SoS information, as well as the gap between the low-level-research side that develops methods for robust US tissue assessment, and the clinical research side that tracks and relates such features to conditions of clinical relevance. With the single-shot algorithm, I provide non-SoS researchers with valuable information to increase the accuracy of their algorithms without the need of long transmitting times or high computational demands, crucial for flow or real time imaging. With the other algorithms, I provide robust avenues for non-invasive tissue health assessment, as well as arming clinicians with access to intrinsic tissue features, that can be used for real time monitoring or for subsequent research that arise from the insights clinicians gain with this novel tool
Spectra of Translation-Invariant Function Algebras of Compact Groups
No full textLet G be a compact group and let Trig(G) denote the algebra of trigonometric polynomials of G. For a translation-invariant subalgebra A of Trig(G), one can consider the completions of A under the uniform norm and the Fourier norm. We show in Chapter 2 using techniques developed by Gichev that both completions have the same Gelfand spectrum, answering a question posed in a paper of Spronk and Stokke. In the same paper, a theorem describing of the Gelfand spectrum of the Fourier completion of finitely-generated such algebras A was given. In Chapter 3, we extend this theorem to the case of countably-generated, translation-invariant subalgebras, A. In Chapter 4, we give a brief overview of the Beurling--Fourier algebra, a weighted variant of the classical Fourier algebra studied by Ludwig, Spronk, and Turowska. The addition of a weight for these particular algebras invites new spectral data in contrast to its classical counterpart. In Chapter 5, we show for Beurling--Fourier algebras of compact abelian groups G that its weight can be used to construct a seminorm on tensor product of the real numbers with the Pontryagin dual of G that remembers the spectral data of the algebra