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Perceptual Experiences of Adult Dyslexia
No full textThis dissertation consists of four primary research studies collectively reporting on the perceptual experience of adults with dyslexia. Sequentially, these studies validate a screening tool for adult dyslexia, investigate the experience of adults with dyslexia and add to our knowledge of the role of visual attention in dyslexia. Data for study 1 was collected as part of a larger research collective within the Concordia Vision lab. Data for studies 2, 3 and 4 was collected as part of one large data collection effort lasting three years. Methods for data analysis span qualitative and quantitative efforts, parametric and non-parametric as well as both traditional null hypothesis testing and Bayesian statistics. Findings from these studies extend our knowledge of adults with dyslexia, deepening our understanding of dyslexia as a lifelong disorder. This thesis focuses on perception in dyslexia, enhancing our understanding of the role of perception as a possible causal deficit, with the overall aim of better understanding what it means to have dyslexia in adulthood
A Reduced-Order, Dynamic, Non-isothermal Model for an Open-Cathode, Air-Cooled Proton Exchange Membrane Fuel Cell System
No full textAn essential component in the renewable transformation of power grids in northern Canadian communities is the hydrogen energy storage system (HESS), which provides the necessary power stability for high renewable penetration microgrids. Open-cathode PEM fuel cell (OC-PEMFC) is an important component in a low-cost HESS to convert the stored hydrogen to electricity. However, this type of fuel cell demonstrates temperature-coupled, steady-state and dynamic electrical responses that are significantly different from closed-cathode ones, which creates challenges in the HESS power control and its safe operation.
In this thesis, a reduced-order, dynamic theoretical OC-PEMFC model was developed to predict the electrical and thermal characteristics under varying load conditions. The model was established on the basis of available reduced-order theoretical models with modifications for the open-cathode design. Experiment on an installed OC-PEMFC was performed to obtain its steady-state and dynamic electrical and thermal characteristics, which were further used to estimate the model parameters and to validate the accuracy of the developed model. The validation results demonstrated good accuracy in the estimation of thermal responses; however, the model was unable to accurately simulate the dynamic electrical responses, especially on the voltage undershoots and overshoots from load current fluctuations. An electrode “flooding” ratio was introduced to improve the estimation accuracy for dynamic electrical responses. The modification on the developed model had negligible influences on the accuracy of thermal responses or steady-state electrical response while improved the estimation accuracy for the voltage undershoots and overshoots
Detecting Prototype Pollution in NPM Packages with Proof of Concept Exploits
No full textPrototype pollution is a critical security vulnerability in JavaScript, particularly in Node.js packages and applications, where attackers can manipulate the global object prototype and inject malicious properties into all objects that inherit from it. State-of-the-art static and dynamic approaches face significant limitations in detecting this vulnerability–both in terms of accuracy and efficiency. Static approaches struggle to recognize unexploitable vulnerabilities (e.g., due to missing code context with preventive mechanism), causing high false positives, besides suffering from scalability issues. Dynamic approaches have low false positives as they can access runtime information by executing a package’s entry points with concrete inputs and validate the vulnerability by checking the runtime behavior. However, due to low code reachability (resulting from the use of e.g., improper argument types/values), their false negatives could be high.
In this thesis, we propose a novel dynamic analysis approach to detect prototype pollution vulnerability in Node.js packages, using tailored exploit input candidates to execute a package’s entry points. We use the developer-provided inputs from a package’s testsuites, and prototype pollution-related exploit inputs extracted from prior work. We then execute each entry point with its relevant exploit input candidates and observe the runtime for indications of prototype pollution. We implemented this approach in our tool called Bullseye.
We analyzed 44,513 highly popular Node.js packages (with 10,000+ weekly downloads), and 5,879 packages with lower weekly downloads in less than 8 hours. We detected previously unreported prototype pollution vulnerabilities in 290 packages, with no false positives. We responsibly disclosed all our findings with proof-of-concept exploit code to the respective package maintainers.We have been assigned a total of 149 CVEs (as of July 22, 2025); among them, 66 have been made public, with 25 rated as critical, and 34 as high
I, too, Belong Here: Legal Exclusion Regime and Foreign Labour in Kuwait
No full textIn recent years, Kuwait, like other Gulf states, has faced international scrutiny over its treatment of migrant workers, particularly within the framework of the Kafala sponsorship system. Reports of wage theft, restrictive mobility, and sudden deportations are often discussed as contemporary crises, yet their origins lie in much older patterns. The exponential growth of the oil industry in the Arabian Gulf during the mid-20th century transformed the region’s economies, societies, and labour systems. In Kuwait, as in other Gulf states, the rapid expansion of oil extraction and export created a labour demand far beyond what the local population could meet. This gap was filled largely by migrant workers from the South Asian subcontinent and neighbouring Arab countries.
This thesis argues that the legal, economic, and social frameworks governing these migrant labour forces were not created in a vacuum but were rooted in colonial-era labour regimes. While much existing scholarship centres the Kafala system as the principal mechanism of exploitation, this study moves beyond Kafala as a singular explanatory frame to examine the broader historical, political, and economic structures that made such systems possible and enduring. These regimes, inherited and adapted by newly independent Gulf states, perpetuated exclusionary practices that tied the migrant worker’s value to their productivity in the oil economy while denying them pathways to permanent residency, political rights, or social integration
Flowable One-Part Alkali Activated Materials: Challenges and Techniques
No full textCanada has committed to achieving net zero greenhouse gas emissions by 2050, and the construction sector plays a critical role in meeting this target. Cement production alone contributes nearly 8% of global CO2 emissions, making it essential to explore alternatives to Ordinary Portland Cement (OPC). One promising solution is the use of alkali-activated materials (AAMs), which are produced from industrial by-products and can substantially reduce both carbon emissions and energy consumption in concrete production. Among these, one-part alkali-activated slag (AAS), often referred to as “just add water AAM,” is particularly attractive because of its ease of application and ability to achieve high early strength without heat curing. Despite these advantages, one-part AAS still faces significant challenges, including low workability, rapid slump loss, and short setting times, which limit its practical use in ready-mix and on-site applications. While some studies have examined chemical admixtures to enhance AAM performance, there remains limited research on the specific behavior of one-part AAS systems. In particular, little attention has been given to the effects of mixing protocols, retarders, and viscosity-modifying admixtures on both fresh and hardened properties. To address these gaps, this research is divided into four phases. The first phase evaluates the effect of changing ingredient addition sequences on reaction kinetics. Based on these findings, the optimized sequence is carried into the following phases. The second phase investigates the influence of mixing times, speeds, and styles (continuous versus discrete) on the fresh and rheological behavior of one-part AAS. The third phase examines the use of chemical retarders to improve workability and extend slump life without compromising strength. Finally, the fourth phase explores the role of viscosity-modifying admixtures (VMAs) in stabilizing the mix and enhancing flowability and setting behavior. By systematically studying these variables, this research advances understanding of one-part AAS and highlights pathways to improve its fresh properties. The outcomes are expected to support broader adoption of sustainable binders in construction and contribute to Canada’s net-zero emission goals
Modeling, Analysis, and Control of Opinion Dynamics in Social Media Networks
No full textThis dissertation presents five main contributions to the field of opinion dynamics.
The first contribution introduces a discrete opinion-dynamics model for social-influence networks that incorporates both synchronous and asynchronous updating mechanisms. Each agent holds two distinct states — a synchronously updated private opinion and an asynchronously updated expressed opinion. Private opinions evolve through interactions with neighbors’ expressed opinions, while expressed opinions are shaped by neighboring views and pressure to conform to public discourse. The model is analyzed under several network topologies, and simulation results confirm its ability to capture realistic patterns of online opinion formation.
The second contribution is the collection, preprocessing, and public release of a large-scale Twitter/X dataset spanning four months of discussion on a focused topic. The dataset includes opinions, timestamps, geo-tags, stance labels, and follower–friend graphs. Thorough cleaning, bot removal, and language filtering ensure a research-ready corpus that supports longitudinal studies of network structure and opinion evolution.
The third contribution analyzes competitive influence in social-media networks by combining the evolved DeGroot-based model with reinforcement learning. Agents employ Q-learning to decide when to voice their views, aiming to maximize their impact on connected individuals. By varying topologies and examining convergence behaviors, the study reveals how strategic timing affects polarization and consensus formation, underscoring the role of competition in shaping discourse.
The fourth contribution extends the reinforcement-learning framework by formalizing the opinion-dynamics environment as a partially observable Markov decision process and introducing adaptive control agents whose policies update at every time step. Robustness tests across networks of different sizes, densities, and topologies demonstrate that learned policies can steer collective opinion toward arbitrary targets with minimal intervention. Open-source code and cross-network experiments validate the scalability and generalizability of this approach.
The fifth contribution develops a Double Deep Q-Learning controller that strategically amplifies polarization and disagreement in online networks. Integrating the controller with the Expressed-and-Private Opinion model, the study shows that manipulating only a small subset of accounts can markedly increase ideological division once a topology-specific threshold is crossed. These findings shed light on how algorithmic interventions can engineer polarization in digital spaces.
The thesis concludes with a discussion of the limitations and directions for future research
The Relation Between Callous-Unemotional Traits and Treatment-Related Variables in a Sample of Adolescents with ADHD
No full textBackground: Callous-unemotional (CU) traits are associated with lower treatment engagement, more severe symptoms, and worse treatment outcome for youths with disruptive behaviours (Hawes et al., 2014; Perlstein et al., 2023). Another condition that is often comorbid with disruptive behaviour is attention-deficit/hyperactivity disorder (ADHD) (Graziano et al., 2017). Preliminary research suggests that nearly half of youths with ADHD have CU traits. CU traits may similarly predict lower treatment engagement and response for youths with ADHD, but research is lacking. This study examines associations between CU traits and post-treatment ADHD symptoms, reliable improvement, and treatment engagement for youths. Method: Data were drawn from a previous study examining the effectiveness of summer treatments for youths with ADHD. Seventy-two youths (Mage = 13.04) were assessed at baseline, end of summer treatment, and end of academic year. Multiple and binary logistic regression analyses assessed if CU traits predicted 1) post-treatment ADHD symptoms, 2) reliable clinical improvement in ADHD symptoms, and 3) treatment engagement. Results: CU traits did not significantly predict parent- (b = -0.003, p =.509) or teacher-rated (b = 0.020, p =.712) post-treatment ADHD symptoms. Additionally, only parent-rated CU traits positively predicted reliable improvement from baseline to end of summer (b = 0.051, OR = 1.053, p =.048). Finally, CU traits were not a significant predictor of treatment engagement (b = -0.002, p =.663). Implications: Overall, the research contributes to understanding of adolescents with ADHD and CU traits and their responsiveness in summer treatment programs
Multimodal Investigations of Human Cortico-Ponto-Cerebellar Connectivity
No full textLong regarded as being uniquely involved with motor control, the cerebellum is now recognized to contribute to nearly every aspect of human cognition. The cerebellum forms reciprocal connections with much of the cerebral cortex, receiving input via the pons and sending output back through the deep cerebellar nuclei and thalamus. These topographically organized, closed loop circuits, are thought to underly the cerebellum’s capacity to influence such a breadth of different processes. These connections have a rich history of study in non-human animals, but their organization in humans is largely understudied. In this dissertation we present a series of three studies that investigated the connectivity of the downstream, cortico-ponto-cerebellar, pathway in humans. In our first study (Chapter 2) we reconstructed connections between the pons and lobules of the cerebellar cortex using diffusion MRI tractography. We demonstrated topographic organizational principles broadly reflecting the segregation of motor and non-motor inputs to the cerebellum. Our second diffusion MRI tractography study (Chapter 3) mapped the corticopontine segment using methods to reconstruct gradients that reflect the continuous mappings of the cerebral cortex onto pons. In our final study (Chapter 3), we shifted to a functional connectivity approach, reconstructing gradients in the pons based on its connectivity with the cerebral and cerebellar cortices. While the first two studies serve as bridges to prior work conducted in non-human animals, the final study supports a novel perspective of the pons as a functionally dynamic integrative hub. Taken together, this work advances our understanding of cerebellar connectivity in humans and, by extension, its diverse contributions to behaviour and cognition
An Agentic Benchmarking of Large Language Models for Security Incident Analysis
No full textSecurity incident analysis poses a difficult challenge for security operation centers, because they must respond to an overwhelming number of alerts, requiring analysis of large volumes of data, a myriad of tools, while facing shortages of experienced analysts. The job of an analyst is further complicated as incidents are dynamic and require multifaceted, multi-step analysis. While companies are keen to apply Large Language Models (LLM) to augment analysts’ efforts in security incident analysis (SIA), the lack of benchmarking of LLMs for SIA renders huge risks on their overall effectiveness and design choices. Moreover, such benchmarking becomes non-trivial as: (i) no dataset currently exists in a digestible format for LLMs that covers a wide range of SIA tasks; (ii) considering the vast diversity in analysts’ job, there is a continuous need to add new tasks; and (iii) frequent model releases must be included in evaluation. In this thesis, we aim to address these challenges while building an agentic evaluation framework, SIABENCH. Specifically, first, we build a first-of-its-kind dataset that includes two major SIA tasks: (i) deep analysis of security incidents (25 scenarios) and (ii) alert triaging (35 scenarios). Second, we build an agent to automatically conduct a wide range of SIA tasks (covering network/memory forensics, malware analysis in binary/code/PDF, phishing email/kit analysis, and log analysis) along with false alert detection. Third, we evaluate the performance of nine major LLMs (covering both open- and closed-weight) in SIA with the capability to support newer models and tasks
Labyrinths of Despair: Crime, Emotion, and the Racialized Courtroom in Nineteenth-Century Yucatán
No full textThis dissertation delves into a neglected area of Latin American historiography: the emotional dynamics of violent crime in Yucatán, Mexico. It examines the effects of legal codification on homicide trials across the 19th century, revealing intersections between law, crime, race, and emotions. This transition is significant for two reasons. First, the modern Mexican penal code included something absent from earlier laws: emotions appeared for the first time in the law as potentially mitigating or aggravating factors. Second, in the colonial period, Indigenous people had special courts and procedural advantages. With independence, this explicit racial distinction was removed from republican legislation. By analyzing over 400 trials, this research seeks to clarify the implications of the inclusion of emotions in law and the removal of 'Indians' as a legal category. This dissertation explores how the law changed its approach to emotions and the everyday relationship between Indigenous people and legal institutions, advancing two main arguments. First, the incorporation of emotions into the law had an unintended consequence: a decline in emotional expression during trials—especially in cases of gender-based violence. Second, the erasure of the legal category of “Indio” did not end the widespread assumption that Indigenous people were intellectually and morally inferior. Liberals did not set out to reduce gender-based violence yet inadvertently contributed to its decline. In contrast, although they sought to eliminate racial distinctions from the law, their reforms ultimately deepened the legal exclusion of Indigenous peoples