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No Cop, No Stop
No full textSet in a handful of locations across Southern Ontario, the following stories trace the development of the Meyers family from childhood until the death of the family matriarch, Beverley Meyers, who passes away after suffering from Alzheimer’s for over a decade. Spread from 1969 until 2023, these stories begin with the Meyerses in their hometown of Woodstock and end with Beverley’s burial in Mississauga. Although the collection’s overarching subjects—the growing decentralization of the Meyers family, the indignity of death and dying, and the cruelty of siblings—are unhappy ones, the collection is comic in tone. For example, while Mrs. Meyers’ cognitive decline is difficult for her and her family, her new-found obsession with traffic laws and unsuppressed temper allows readers to appreciate the ridiculousness of her situation.
Naturally, these stories are drawn from real-life experience, however I have also taken influence from Stuart McLean’s The Vinyl Cafe, and Diane Schoemperlen’s “Railroading: Or Twelve Stories with the Word Train in the Title.
Assessing the Environmental Impacts of Plastic Materials: A Step Towards Sustainable Materials and Eco-Friendly Products
No full textThe unprecedented surge in disposable face mask consumption during the COVID-19 pandemic has led to the accumulation of substantial plastic waste, posing significant environmental and ecological challenges, particularly due to the reliance on non-biodegradable polypropylene (PP) materials. However, the long-term environmental behavior and degradation pathways of these masks remain poorly understood, comparative evaluations of biodegradable alternatives such as polylactic acid (PLA) are still limited, and effective strategies for identifying and implementing sustainable material alternatives are still lacking. This dissertation presents a comprehensive, multi-phase investigation into the environmental impact, available material alternatives, and predictive evaluation frameworks for single-use face masks, facilitating the transition toward sustainable personal protective equipment (PPE) solutions.
The degradation behavior of PP-based masks in simulated landfill leachate environments was studied. The results revealed that PP masks experience rapid structural deterioration and release quantities of microplastics (MPs) and metal elements, raising concerns about long-term ecological toxicity. In addition, to address these issues, biodegradable polymer PLA was proposed as a sustainable alternative to be further investigated. A full life cycle assessment (LCA) comparing PP and PLA masks was systematically conducted, encompassing raw material extraction, production, packaging, transportation, and end-of-life management. Results indicate that PLA masks produce approximately 37% lower greenhouse gas emissions and generally outperform PP masks in several key environmental impact categories, particularly global warming potential and fossil resource depletion. To further validate the environmental suitability of PLA, laboratory-scale degradation experiments were carried out under diverse environmental conditions, including exposure to ultraviolet (UV) radiation, landfill leachate, seawater, and enzymatic environments. These results revealed that PLA degrades primarily through hydrolysis, with significant differences in degradation rates across environments and material layers. PLA masks released significantly fewer microparticles than PP masks, suggesting a significantly reduced risk of persistent pollution.
Building on these findings, the final phase of this study introduces a novel predictive screening framework that integrates multi-criteria decision analysis (MCDA) and machine learning (ML). The model uses material-level properties—such as molecular weight and functional group composition—to predict degradation performance and rank candidate materials in terms of environmental suitability. The framework enables rapid, early-stage screening of novel materials without requiring extensive laboratory experimentation, thus providing a scalable tool for sustainable material development and selection. In summary, this dissertation bridges environmental risk assessment, life cycle-based decision-making, and data-driven prediction to provide a holistic strategy for assessing and guiding the transition toward usage and development of sustainable raw materials for mask production
Hybrid Masculinities? A Thematic Analysis of Make-Up Advertisements for Men
No full textIn contemporary society, men are exposed to a variety of conflicting narratives pertaining to masculinity (Lafrance & Hoebanx, 2025). These narratives are prevalent in advertisements that are regularly accessible through popular and ever-expanding social media platforms (Leiss et al., 2018; Schwemmer & Ziewiecki, 2018). To better understand the nature of these narratives, this qualitative study seeks to analyze representations of masculinity and the norms that underlie them evident in contemporary men’s makeup advertisements. The study consists of five key parts. First, it includes a literature review that provides an overview of scholarship on men’s body modification practices, particularly as they relate to the skin and the face, highlighting the gaps in said scholarship and, by extension, the originality of my study. Second, the study presents a synthesis of the three most widely used theoretical frameworks in critical studies of men and masculinity, namely Connell’s (1987,1995, 2005) framework of ‘hegemonic masculinity’, Bridges and Pascoe’s (2014, 2018) framework of ‘hybrid masculinity’, and Anderson’s (2012) framework of ‘inclusive masculinity.’ Third, I outline my method of choice which is reflexive thematic analysis (Braun & Clarke, 2006, 2019, 2021), and how I apply it to the study of 15 sample advertisements collected from YouTube and published between 2013 and 2023. Fourth, I present an analysis and discussion of my sample of men’s makeup advertisements and how they both reinforce and redefine contemporary masculinity. And finally, I propose directions for future research on men’s makeup advertisements in the context of current scholarly debates
Development of an integrated Municipal Solid Waste conversion and CO2 utilization process for the environmentally friendly production of transportation fuels
No full textThe global rise in municipal solid waste (MSW) generation and the urgent need to decarbonize the transportation sector, particularly the aviation fuels and heavy trucks, have created a compelling
opportunity for circular carbon technologies. This thesis presents the development and analysis of a waste-to-jet fuel production pathway that integrates MSW gasification, syngas conditioning,
reverse water gas shift (RWGS) conversion, Fischer-Tropsch (FT) synthesis, and hydrocracking. The process design and simulation are performed using Aspen Plus, with a particular emphasis product selectivity and CO₂ utilization.
Using the simulation results, a comprehensive techno-economic analysis (TEA) is carried out to estimate capital and operating expenditures, minimum selling prices, and project viability under
Quebec’s low-carbon electricity conditions. Additionally, a detailed life cycle assessment (LCA) is conducted in OpenLCA to evaluate the environmental footprint of the proposed system compared to conventional pathway of jet fuel production and waste incineration. The LCA results, based on ReCiPe methodology, indicate that the MSW-to-jet fuel pathway can achieve net negative greenhouse gas emissions under low-carbon electricity scenarios.
The findings highlight the dual benefit of MSW valorization: reducing landfill dependency and enabling the production of sustainable aviation fuel (SAF) with a significantly lower carbon
intensity. This research demonstrates that MSW can serve as a viable feedstock for decarbonized fuel production, offering a scalable and economically competitive solution aligned with global
climate and waste management goals
New paradigms for radiological segmentation with AI foundation models: automatic prompting and interactive VR agent design
No full textThis thesis investigates data-efficient and interactive methods for medical image segmentation, addressing two major related hurdles: the scarcity of high-quality annotations for fully-supervised lesion segmentation and the labor/expertise-intensive nature of manual segmentation workflows. Our first contribution, YOLO-URSAM, is a weakly supervised intracranial hemorrhage (ICH) segmentation model that leverages the Segment-Anything Model (SAM), where we fine-tune YOLOv8 on bounding-box annotated CT scans, introduce automatic point prompting for SAM, and apply perturbation-based majority-voting for uncertainty rectification. YOLO-URSAM achieves 0.933 detection accuracy, 0.796 AUC, and a mean Dice score of 0.629, surpassing existing weakly supervised methods and popular supervised models (U-Net and Swin-UNETR) on available public data. Our second contribution, SAMIRA, is a virtual reality system with a conversational AI agent for semi-automated 3D radiological segmentation. Users issue simple voice commands to initialize masks, correct them using a human-in-the-loop approach, then view the 3D segmentations as a true-to-scale 3D mesh. In a user study, SAMIRA achieved a System Usability Scale score of 90.0±9.0, demonstrated a low cognitive load, and was praised for its intuitive guidance, educational benefits, and immersive visualization. Together, these methods combine AI foundation models, prompting, and limited human interaction to deliver accurate and efficient segmentation for clinical imaging
Etale Cohomology and the Galois Representation attached to a Modular Form
No full textIn this thesis, we introduce the theory of ´etale cohomology, assuming basics in algebraic
geometry and sheaf theory on topological spaces. In particular, we define ´etale morphisms
and develop the theory of sheaves on the ´etale site alongside some of the most important
examples.
In the last two chapters, we collect, mostly without proofs, some of the most important
results on ´etale cohomology and apply them to outline Deligne’s construction of the Galois
representation attached to a modular form, illustrating the usefulness of that cohomology
theory in number theory
Design and Demonstration of Optical Logic Gates with Electronic Interface for Optical Switching Applications
No full textThe scalability of high‑capacity networks increasingly depends on advances in switching technology. Optical switching, particularly using microring‑based logic, offers a path to higher bandwidth and lower signal degradation while enabling compact, cascadable architectures.
This thesis presents a microring modulator (MRM)‑based 2×2 optical switch built from cascadable optical logic gates (OLGs) with electronic control circuits. An OLG is a fundamental building block of optical computing systems, performing logic operations by manipulating optical signals rather than electrical ones, thereby leveraging the inherently higher speed and lower propagation loss of light. The OLG’s functionality is validated through experimental measurements of power transfer characteristics (PTC), optical noise margins (ONMs), and fan‑out performance. The 2×2 switch, implemented with seven interconnected OLGs, demonstrates the scalability of this approach for more complex optical logic networks.
To enable higher‑speed operation, a CMOS implementation of the electronic control circuit, for driving and processing optical‑logic signals, was designed and fabricated in TSMC's 65 nm technology, occupying an active area of 1 mm × 1.25 mm. The design incorporates a peak/low detector‑based offset compensation technique that ensures stable performance under unbalanced input data patterns.
Post-layout simulations verify correct logic functionality, showing a simulated propagation delay of approximately 107 ps. Despite this delay, the standalone gate can process narrow pulses, corresponding to a data throughput of up to 8 Gbps.
The combined demonstration of discrete and integrated implementations highlights the potential of microring‑based optical switching as a scalable solution for future high‑performance networking and computing systems
Mathematical models and solution algorithms for resilient network design
No full textThis thesis presents novel models and optimization strategies for dynamic resilient network flow problems under consecutive disruptions. The study addresses the need for resilient network design by focusing on the integration of stochastic elements, partial information, and flexible recovery
strategies within supply chains and other critical infrastructure networks. Three mathematical frameworks are developed, each targeting specific aspects of network resilience, including dynamic flow optimization, collaborative network design, and flexible recovery under uncertain conditions.
The first part of the thesis introduces a generalized structure for interconnected networks, enabling collaboration among different entities to enhance resilience. This model leverages both proactive and reactive strategies, using shared resources and interdependencies to mitigate the impact of disruptions more effectively. Computational experiments demonstrate that the proposed intertwined network structure significantly improves network stability and reduces disruption costs.
The second part focuses on dynamic network flow models that optimize rerouting strategies under consecutive disruptions with partial information. By employing two-stage stochastic programming and rolling-horizon optimization, the models dynamically adjust decisions based on real-time updates about disruption severity and timing. Results show that the dynamic models maintain network functionality more effectively than traditional static approaches, particularly in scenarios with evolving disruptions.
The final part extends the dynamic flow models to include overlapping disruptions and flexible recovery strategies. Different recovery options, characterized by varying costs and timeframes, are integrated
into the optimization framework, allowing decision-makers to select recovery actions based on disruption conditions. Simulation results reveal that flexible recovery strategies substantially reduce total disruption costs and recovery times, proving critical in managing complex cascading disruptions.
Overall, this thesis advances the field of network resilience by providing comprehensive models that address dynamic disruptions, optimize recovery decisions, and offer practical solutions for real-world applications in supply chains, logistics, and transportation networks
Joy Across Distance: Remediative Explorations of Iraqi Jewish Musicking
No full textWhat can be achieved through the present-day remediation of the remaining media traces of early twentieth century Iraqi Jewish musicking? As a result of Iraqi Jewry’s emigration-deportation from Iraq in 1951, much of its material culture was lost; this also resulted in a sudden truncation of the various threads of the transmission of intangible culture. The emergence of sound recording technologies in the early twentieth century suddenly enabled the creation of sonic cultural objectivations of Iraqi Jewry’s musical life in the Islamic world, a musical life that lost its cultural context, and, with later generations, intelligibility, without Iraq. Two artists of Iraqi Jewish descent, Regine Basha and Dudu Tassa, remediated these sound recordings in projects of cultural discovery that are readily accessible online in the English-speaking world. The results—the album Dudu Tassa and the Al-Kuwaitys (2011) and the project Tuning Baghdad—are personal creative explorations that are accessible to audiences without existing familiarity with Arab or Iraqi musicking, but they have no pretense of establishing a monolithic sense of what Iraqi Jewish musicking has been or will be. Further, both centre the joy of musicking in their explorations, which resists a “lachrymose historiography” of Iraqi Jewish history and experience
Scaling Up Upcycling: A Comparative Analysis of Furniture, Lighting and Bags Made Through Repurposing (Author Accepted Manuscript, Preprint)
No full textUpcycling offers a transitional approach to the circular economy, using current material recovery systems in ways which increase the value of waste materials, namely through reuse, repair, refurbishment, remanufacturing, and repurposing. Research tackling the challenges of scaling up upcycling has largely focused on meso and macro level factors and lacks details in terms of the day-to-day practices of upcycling designers. This chapter offers a comparative analysis of 20 upcycled products to contribute to an understanding of scaling up upcycling through the lenses of operational scalability and business viability. Cross-disciplinary literature review identifies the craft nature of production in the repurposing approach of many upcycling enterprises as the key challenge for scaling-up. Comparative analysis of the cases confirms this challenge and identify material sourcing, design, production, marketing and distribution practices as helpful factors. The findings contribute to supporting designer-makers and other practitioners in creating and scaling up upcycling enterprises