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Type d'Item : Item , Chilean Art Music During the Cold War (1970-1990): Political Commitment, Exile and Democratizing Practices in Musics(Université d'Ottawa | University of Ottawa, 2026-10-01) Rodriguez Mayen, Sebastian; Moore, Christopher LeeThis thesis examines the work of Chilean composers during the turbulent period between 1970 and 1990, spanning the presidency of Salvador Allende and the subsequent coup d’état and dictatorship of Augusto Pinochet. The works produced during these years by Luis Advis (1935–2004), Gustavo Becerra-Schmidt (1925–2010), Celso Garrido-Lecca (1926–2025), and Juan Orrego-Salas (1919–2019) bear witness to Chile’s rapidly shifting political and cultural landscape, which forced many artists into exile or silence under the dictatorship. Some of these composers later collaborated with folk music ensembles to express solidarity during their exile, whether imposed or voluntarily embraced. Through selected case studies, this thesis argues that the musical output of these composers constitutes a cultural response to broader geopolitical forces shaping both highbrow and popular culture, particularly the power dynamics of the Global Cold War. By analyzing their lives and works, the study demonstrates how political developments in the Global North influenced cultural production in the Global South, while also highlighting the varied forms of resistance — both overt and covert — and the resilience exhibited by composers and musicians in the Global South. These dynamics extended beyond exile to include the imposition and adaptation of dominant musical styles, practices of cultural diplomacy between host and home countries, and negotiations of indigeneity in artistic expression, all of which affected the composers examined in this study. Accordingly, this thesis considers not only the musical characteristics of these works but also the historical, political, and cultural conditions that shaped their creation. In doing so, it presents these composers and their compositions as historically situated witnesses to their time and place.Type d'Item : Item , Development of a Solid-State Nanopore Platform Toward High-Throughput, Ultra-Sensitive, and Robust Single-Molecule Analysis of Nucleic Acids and Proteins(Université d'Ottawa | University of Ottawa, 2026-10-01) Bouhamidi, Mohamed Yassine; Tabard-Cossa, VincentSolid-state nanopore sensors consist of a nanoscopic hole in a thin free-standing dielectric film (a membrane) bridging independent reservoirs of salt solution to interrogate the analytes present therein. Nanopores have demonstrated promising results in applications spanning DNA sequencing, biomarker detection, information storage and energy harvesting. Recently, researchers in the field have aimed to interrogate proteins with enough precision to extract their sequences. Despite their versatility, solid-state nanopores have advanced slowly experimentally due to obstacles and knowledge gaps that need to be explored. A few challenges are addressed in this thesis, attempting to provide insight for future steps in this direction, namely: 1) extracting surface charge density is key to studying the effect of membrane material properties on nanopore transport, fabrication conditions and subsequent chemical functionalization, 2) unwanted adsorption between the biomolecules and the sensor’s surface during the electrophoretic capture and translocation process hinders sensing performance and results in clog events, 3) small proteins or DNA nanostructures can be challenging to fully resolve, leading to missed or attenuated molecular event signatures, and 4) reducing membrane thickness to enhance the signal-to-noise ratio and the spatial resolution leads to faster sensor degradation over time for SiN. For the first objective, I present an experimental characterization platform capable of measuring the surface charge density of silicon nitride as a membrane material. The platform allows high-pressure streaming current measurements in the picoampere range, providing enough resolution to extract the zeta potential and surface charge density of new materials. Next, I explore an alternative anti-fouling protocol for the possibility of increasing sensing time while interrogating long and flexible single-stranded DNA (ssDNA). This analyte clogs the sensor in less than 15 seconds, while after surface modification, we collect relevant data for ⁓45–60 minutes before the first clog event. This improved protocol preserves noise performance comparable to pristine nanopores, even after surface modification. Furthermore, I evaluate the surface properties of these modified nanopores to confirm the successful binding of the polymer on the surface through zeta potential measurements. Moreover, I develop a trapping procedure that takes advantage of the surface characterization platform to reduce the translocation velocity of complex analytes, thus investigating pressure-voltage actuation for analytes of known velocity while determining the impact of this mode of translocation on dwell time. This actuation approach provides an up to 6× reduction in translocation velocity for DNA nanostructures and proteins respectively, facilitating the extraction of high-fidelity event signatures. Finally, I perform an exploration of nanopore membrane microfabrication processes and materials to improve signal amplitude while reducing noise limitations. Here, I present an alternative deposition approach for SiN thin films with a lower thermal budget, namely ion beam deposition (IBD) compared to the traditional Low-Pressure Chemical Vapor Deposition (LPCVD). Independently, I explore the properties of a sub-5 nm annealed Hafnium oxide (HfO2) membrane deposited by Atomic Layer Deposition (ALD), supported by an LPCVD SiN, in terms of film stability and sensing performance. Future work involves combining the lower thermal budget SiN deposition as a mechanical support for a sub-3 nm ALD HfO2 membrane. This approach will offer an ultra-thin solid-state nanopore architecture with reduced degradation, enhanced signal-to-noise ratio, and bypass the annealing step due to the temperature mismatch between depositions. Ultimately, my goal is to pave the way for more efficient and sensitive nanopore-based technologies, contributing to the fields of genomics, proteomics, and beyond.Type d'Item : Item , Behavioral Apathy and its Relationship with Physical Activity, Affective Attitudes, and Motor Cortex Excitability(Université d'Ottawa | University of Ottawa, 2026-10-01) Farajzadeh, Ataallah; Boisgontier, MatthieuApathy is a multidimensional syndrome characterized by diminished motivation and reduced goal-directed behavior. Although apathy is commonly studied in neurological and psychiatric populations, it is also observed in otherwise healthy adults and may represent an important barrier to engagement in physical activity. Because physical activity requires effort, action initiation, and persistence, individuals with higher levels of behavioral apathy may be less likely to initiate and maintain active behavior. Despite growing interest in the relationship between apathy and physical activity, the behavioral and neurophysiological mechanisms underlying this association remain poorly understood. This thesis examined the relationship between behavioral apathy, physical activity, affective attitudes toward physical activity, and motor cortex neurophysiology. Across four complementary studies, behavioral and neurophysiological pathways that may contribute to reduced physical activity in individuals with higher apathy were investigated. Study 1 is a systematic review and meta-analysis examining the association between apathy and physical activity across clinical and non-clinical populations. Study 2 examined whether intentions, explicit affective attitudes, and approach-avoidance tendencies toward physical activity mediated the relationship between behavioral apathy and physical activity in healthy adults. Study 3 is a systematic review and meta-analysis investigating the association between habitual physical activity and measures of motor cortex neurophysiology, including corticospinal excitability, intracortical inhibition, and intracortical facilitation. Study 4 used transcranial magnetic stimulation (TMS) to examine whether behavioral apathy was associated with these neurophysiological measures in healthy adults. Across the four studies, results demonstrated that apathy is associated with physical activity, but that this association is more strongly explained by motivational and affective processes than by resting-state motor cortex neurophysiology. The systematic review and meta-analysis showed a significant negative association between apathy and physical activity, with stronger associations in older adults and individuals with Parkinson’s disease. Behavioral analyses further demonstrated that higher behavioral apathy was associated with lower physical activity, partly through weaker intentions to be physically active and less positive affective attitudes toward physical activity. Individuals with lower apathy also showed stronger tendencies to approach physical activity stimuli and avoid sedentary stimuli, although these tendencies did not mediate physical activity behavior. In contrast, the neurophysiological studies showed no reliable associations between habitual physical activity and measures of corticospinal excitability, intracortical inhibition, or facilitation. Similarly, behavioral apathy showed negligible associations with these measures, with equivalence testing indicating that any potential effects were too small to be practically meaningful. These results suggest that the relationship between apathy and physical activity is primarily linked to motivational and affective mechanisms rather than stable differences in primary motor cortex neurophysiology. Specifically, higher behavioral apathy was associated with weaker intentions to be physically active and less positive affective attitudes toward physical activity, whereas neither habitual physical activity nor behavioral apathy showed meaningful associations with resting TMS-derived measures of corticospinal excitability or intracortical circuitry. Overall, this thesis refines the understanding of how apathy contributes to physical inactivity and highlights the importance of targeting motivational processes when designing interventions aimed at increasing physical activity engagement.Type d'Item : Item , Essays on Corporate Culture(Université d'Ottawa | University of Ottawa, 2026-10-01) Kumar, Ashok; Dutta, ShantanuIn this dissertation, I examine important questions in the measurement of organizational culture using computational textual analysis of corporate earnings conference calls. The research topics include contextual measurement of corporate integrity using a multi-agent LLM architecture in the first essay and measuring organizational culture through the Competing Values Framework using the same methodology in the second essay. Both of my essays are co-authored with Professor Shantanu Dutta with first essay currently under a revise-and-resubmit decision at Information Systems Frontier. The first essay addresses a fundamental measurement challenge in the corporate culture literature: dictionary-based approaches to measuring corporate integrity from corporate disclosures count every occurrence of culture-related keywords as evidence of the underlying construct, regardless of the context in which those words appear. We develop and validate a multi-agent large language model (LLM) pipeline, based on a blackboard architecture with eleven specialized agents, to measure four components of corporate integrity (i.e., Accountability, Compliance, Moral Integrity, and Honesty) from the Q&A sections of earnings conference call transcripts. Our contextual approach reveals that fewer than 30% of the segments containing integrity-related dictionary terms are meaningfully related to the integrity construct, demonstrating that traditional dictionary methods substantially overcount meaningful cultural discourse. The multi-agent classification system achieves 95.67% accuracy and a Cohen’s kappa of 0.913 against human annotations, with five independent stability runs producing an inter-run mean kappa of 0.945. To validate the resulting measure empirically, we examine its association with established indicators of corporate governance quality and reporting integrity. We find that firms with greater board independence and higher female board representation engage in more integrity-related discourse, consistent with prior research linking these governance characteristics to stronger ethical oversight. We also find that firms with higher contextual integrity scores are more likely to disclose non-fraudulent restatements, consistent with the view that integrity-oriented cultures promote transparent correction of reporting problems rather than increasing the incidence of misreporting. Furthermore, higher integrity scores are associated with lower discretionary accruals, higher dividend payouts, and greater access to trade credit, in line with theoretical predictions that integrity culture constrains opportunistic reporting, enhances credibility with capital providers, and reduces counterparty risk. Across these analyses, the dictionary-based measure exhibits systematically weaker and, in several cases, statistically insignificant associations, underscoring that contextual interpretation is not merely methodological refinement but a necessary step for recovering economically meaningful integrity signals from corporate discourse. The second essay implements the methodological innovations of the first essay to the Competing Values Framework (CVF), the most widely adopted theoretical model of organizational culture. Despite its theoretical maturity, empirical measurement of the CVF has relied predominantly on dictionary-based word counts from 10-K filings, an approach that is both context-insensitive and confined to heavily curated corporate documents. We adapt the multi-agent blackboard architecture to classify earnings call Q&A discourse into the four CVF cultural orientations (i.e., Clan, Adhocracy, Hierarchy, and Market) using over 183,000 transcripts spanning 2008 to 2024. Our classification identifies approximately 20% of total segments as containing genuine cultural content, with Market discourse predominating, followed by Hierarchy, Adhocracy, and Clan, a distribution that reflects the externally oriented communicative demands of the earnings call setting. We conduct the first systematic construct-validation exercise that pairs each CVF dimension with the specific firm outcomes its own theoretical logic predicts, and we benchmark our contextual scores against the widely used dictionary-based measures on the same validation outcomes. Our contextual CVF scores produce theoretically consistent and statistically significant associations across all four dimensions (i.e., Clan with labor intensity, Adhocracy with innovation, Market with profitability, and Hierarchy with regulatory discipline) whereas the dictionary-based scores yield inconsistent and often economically negligible results. These findings demonstrate that all four dimensions of the CVF carry distinct economic content when measured with sufficient contextual precision, and that the apparent irrelevance of certain CVF dimensions in prior work likely reflects measurement noise rather than a genuine absence of cultural influence on firm behavior.Type d'Item : Item , Data Efficient Deep Learning for Rolling Element Bearing Fault Diagnosis(Université d'Ottawa / University of Ottawa, 2026-09-30) Sehri, Mert; Dumond, PatrickRoller element bearings are responsible for 50 to 60 percent of rotating machinery failures, making reliable fault diagnosis critical for industrial machinery health monitoring. This thesis demonstrates that state of the art performance in bearing fault diagnosis does not require massive datasets, but rather well-designed data collection, preprocessing, and loading methods. Focusing on the entire data lifecycle from acquisition to model input, this work challenges the notion that extensive data is required to train machine learning (ML) models for condition monitoring by showing that carefully structured and efficiently loaded data can deliver superior cross domain generalization even with limited samples. Benchmark publicly available bearing datasets are analyzed, revealing weak cross domain coverage that restrict the transferability of ML models to industrial scenarios. To address this gap, a new bearing dataset design is proposed under controlled conditions with naturally developed faults, and a novel selective embedding data loading method is introduced, which alternates sensor inputs in a structured and alternating fashion to maximize training diversity and prevent overfitting without increasing data volume. Theoretical foundations connecting selective embedding to gradient variance reduction, effective sample size, and generalization bounds are established to explain why the method works. Cross domain experiments are conducted across heavy machinery, manufacturing, and railway datasets to confirm that selective embedding can achieve over 90% classification accuracy under challenging domain splits, outperforming both single-channel and parallel loading methods that require significantly more data or computational effort. These findings establish that data efficiency, not data size, is the key to scalable, transferable, and computationally affordable deep learning for industrial bearing fault diagnosis.