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Recent Submissions

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    Solving Linear Programs with very Tall Constraint Matrices
    (University of Waterloo, 2026-09-16) Wang, ZiWen
    Given an LP with tall and skinny constraint matrix, we exploit this property and study an algorithm invented by Clarkson [8]. Although this algorithm has been around for over 30 years, there were no software or implementation that could be found online, nor there be any benchmarks for these special tall and skinny LP s. We describe some variants and changes to the algorithm aiming for practical performances to close this gap. We also study a first order algorithm (based on the Primal-Dual Hybrid Gradient al- gorithm) aimed for large scale LP s proposed by a group of researchers from Google [2], [3] called PDLP. And compare it with Clarkson’s algorithm.
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    Optimizing naloxone distribution in Canadian community pharmacies: Exploring barriers, intervention approaches and public funding considerations
    (University of Waterloo, 2026-09-16) Cid, Ashley
    Background: Community pharmacies are well positioned to expand access to take-home naloxone (THN) because of their accessibility and frequent interactions with individuals at risk of opioid-related harm. Despite national recommendations that pharmacists proactively offer naloxone to all patients receiving opioid prescriptions, pharmacy-based naloxone provision remains inconsistent and largely reactive. Important evidence gaps remain regarding the implementation of pharmacy-based naloxone programs, approaches to measuring and addressing opioid-related stigma, the effectiveness of interventions designed to support proactive naloxone offering, and the economic value of pharmacy-based naloxone distribution. Objectives: The overall objective of this thesis was to optimize pharmacy-based naloxone distribution in Canada by synthesizing the existing evidence, developing and evaluating a theory-informed educational intervention to support proactive naloxone offering, and assessing the cost-effectiveness of community pharmacy-based naloxone distribution. Methods: This thesis comprises five manuscripts describing four complementary studies. The first study was a scoping review of community pharmacy-based THN programs. The second adapted the Opening Minds Stigma Scale for Healthcare Providers (OMS-HC) to measure opioid-related stigma. The third developed and evaluated the Optimizing Naloxone Dispensing in Pharmacies (ONDP) continuing education program using a randomized controlled trial, process evaluation, and contribution analysis. The fourth study evaluated the cost-effectiveness of community pharmacy-based intramuscular (IM) and intranasal (IN) naloxone distribution in Canada. Results: The scoping review identified a wide range of community pharmacy-based take-home naloxone program interventions and demonstrated variability in naloxone availability and dispensing patterns. Key barriers included cost, stigma, and pharmacist education, while important pharmacist and patient knowledge gaps highlighted the need for standardized interventions evaluated through randomized controlled trials. Adaptation of the OMS-HC provided a standardized instrument to measure opioid-related stigma in pharmacy practice research and enabled evaluation of stigma within the ONDP intervention. The ONDP intervention significantly improved pharmacy professionals' naloxone knowledge and dispensing. Although changes in opioid-related stigma, confidence, and motivation were not statistically significant, the contribution analysis demonstrated that behaviour change occurred primarily by reducing uncertainty surrounding proactive naloxone offering, normalizing naloxone as routine care, and facilitating integration into existing pharmacy workflows. This evaluation further demonstrated that implementation and sustainability were influenced by organizational support, staffing, workflow, patient receptivity, and provincial funding policies. The economic evaluation demonstrated that community pharmacy distribution of both IM and IN naloxone was cost-effective across multiple patient populations in the Canadian context, supporting continued public investment in pharmacy-based naloxone programs and broader funding of IN naloxone. Conclusion: This thesis demonstrates that optimizing pharmacy-based naloxone distribution is fundamentally an implementation challenge rather than simply an access challenge. Sustainable implementation depends on addressing interacting individual, practice-environment, and system-level factors that influence proactive naloxone offering within routine community pharmacy practice. Collectively, these findings provide evidence to inform future pharmacy practice, educational interventions, implementation strategies, and policy development aimed at improving equitable access to naloxone and reducing opioid-related harms in Canada.
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    Improving Robustness to Unknown Disturbances by Expanding the Region of Attraction Near the Current State
    (University of Waterloo, 2026-09-16) Liu, Elin
    Physical systems often experience unknown disturbances that can disrupt their safe operation. For example, consider a drone experiencing a wind gust, a power system experiencing a voltage spike, or an autonomous vehicle encountering a sudden obstacle. The normal or safe operating point of these systems can be represented by an equilibrium point. The RoA is the set of all states for which the system can return to the standard operating point. However, calculating a system's RoA is often very difficult and computationally intractable. Expanding the RoA is an effective method to increase a system's robustness against such disturbances. Expanding the RoA is also very challenging. Because of this, instead of expanding the true RoA, existing methods often expand estimates of the RoA, which can be overly conservative or computationally intractable for higher-dimensional systems. Additionally, these methods are limited to systems and/or controllers that adhere to specific specialized structures, and do not generalize to many nonlinear systems of practical importance. Furthermore, these methods work to expand the RoA in all directions as opposed to near the current state. Expanding the RoA near the current state maximizes the stability of the system given the current conditions, whereas expanding the RoA in all directions imposes unnecessary constraints and could lead to less stability given the current conditions in exchange for more robustness somewhere less relevant. In this thesis, we first use results from dynamical systems theory to re-express the challenging and abstract problem of expanding the RoA near the current state as a concrete max-min numerical optimization problem. This increases robustness against unknown disturbances under current conditions. To do so, we exploit properties of trajectory sensitivities, which measure how susceptible the system's behaviour is to changes in initial conditions and parameters. Trajectory sensitivities can be efficiently computed numerically. The inner optimization finds the closest point on the RoA boundary from the current state for given parameter values, and the outer optimization varies parameter values so as to maximize the distance to the RoA boundary. We then develop the ERA algorithm, which solves this problem efficiently using a particular choice of successive approximations that avoids the need for computationally intensive second derivatives, which are required for many common bi-level optimization solvers. Next, we provide a local convergence guarantee for the ERA algorithm for a large class of nonlinear dynamical systems, using a contraction argument to show convergence. Thus, the proposed ERA algorithm is applicable to a wide variety of practical engineered systems. Finally, we apply the ERA algorithm to two drone simulations in which the drone must take off, fly to a target destination, and then hover at its target despite unknown wind gusts which can disrupt its flight. The first drone uses an integral backstepping controller, and the second drone uses a cascaded PID controller modelled after the default Crazyflie controller as seen in the firmware. We show that, in simulation, with the nominal parameter values, the wind gust knocks the drone out of flight, whereas after the ERA algorithm is run to select new controller parameter values, the drone is able to fly safely to its destination despite experiencing the same wind gust. We then see this increased robustness against unknown disturbances after running the ERA algorithm, replicated in a physical experiment using a Crazyflie 2.1 and a hairdryer.
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    Form-Fitting Mass Timber Connections: Experimental Investigation of the Effect of Tenon Flange Angle on Structural Performance
    (University of Waterloo, 2026-09-16) Daviau, Maxime
    Mass timber construction has expanded rapidly as a lower-carbon alternative to conventional structural systems. However, connection design remains a critical factor affecting constructability, cost, and structural performance. Contemporary mass timber connections rely on steel hardware, proprietary connectors, and mechanical fasteners. While these systems are reliable and code-supported, advances in digital fabrication create opportunities to reconsider form-fitting connections. Despite their historical precedent in heavy timber structures, the structural behaviour of form-fitting glulam connections remains underexplored, particularly how geometry influences load transfer, deformation capacity, and failure mode. This thesis investigates form-fitting glulam connections for purlin-to-girder applications, with an emphasis on tenon flange angle in mortise-and-tenon geometries. The research program included a literature review, two stages of rapid prototyping, material characterization, full-scale experimental testing, and development of a preliminary mechanical model. The literature review established that wood anisotropy, especially its low tensile strength perpendicular-to-grain, and geometry govern load transfer and failure mode. It also identified inclined bearing surfaces as a potential means of redistributing load into compression and promoting embedment mechanisms. The rapid prototyping phase first evaluated traditional single-tenon, multiple flat-tenon, and multiple triangular-tenon configurations. The traditional tenon exhibited low capacity and brittle mortise splitting, while multiple tenons improved strength and deformation capacity through progressive engagement. The triangular-tenon configuration further improved performance, demonstrating that geometry can improve both capacity and failure response. A second prototyping phase then extended this concept to open-top wedge geometries compatible with vertical installation, supporting their selection for full-scale testing. Twelve full-scale glulam wedge-tenon specimens were tested under static loading. Three full-depth series varied the tenon flange angle, while one partial-depth series examined the influence of reduced tenon height. The results showed that flange angle significantly affected yield load, peak load, stiffness, post-yield behaviour, and failure mode. Larger angles produced higher yield and peak loads, whereas smaller angles reduced stiffness and capacity but increased the role of wedging, horizontal thrust, and progressive deformation. The partial-depth series behaved differently from the full-depth specimens, transitioning from side-face wedging to a hybrid wedge/notch mechanism once bottom bearing developed. A mechanical model was developed to estimate the yield load from inclined-face bearing, friction, and compression perpendicular-to-grain embedment. The model more closely reproduced the experimentally observed yield load trends than the CSA O86 fracture-shear provisions and a rounded dovetail-based prediction method. The proposed method applies to the onset of connection softening; ultimate failure mechanisms require separate consideration. Overall, this thesis showcases the promise of form-fitting connections
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    A Study of First-Order Primal-Dual Algorithms for Linear Optimization
    (University of Waterloo, 2026-09-16) Khan, Amaan
    interior point method large-scale linear programming quasi-Newton method first-order method low-rank update