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From Radical-Bridged to Polymetallic Lanthanide Metallocenes: Designing Single-Molecule Magnets Across Nuclearities
No full textSingle-molecule magnets (SMMs), particularly those based on lanthanide (Ln) ions, have emerged as promising candidates for next-generation molecular materials due to their potential applications in high-density data storage, quantum computing, and spintronic devices. The inherent large magnetic anisotropy and strong spin-orbit coupling of Ln ions have enabled mononuclear organometallic complexes to achieve record figure of merit for slow magnetic relaxation including high energy barriers and elevated blocking temperatures. However, extending this success to polynuclear systems has proven challenging, largely due to the weak magnetic exchange interactions between Ln centers. To overcome this limitation, radical ligands capable of mediating stronger coupling through their delocalized unpaired electrons have been employed as bridging units. This dissertation explores the design, synthesis, and magnetic properties of polynuclear Ln SMMs, with a focus on radical-bridging strategies to enhance magnetic exchange.
The investigation began with tetrazine-based radical bridges, focusing on the 3,6-bis(2-pyrimidyl)-1,2,4,5-tetrazine (bmtz) ligand. Two new dinuclear complexes of the formula [(Cp*₂Ln)₂(bmtz^•-)](BPh₄)·Solvent (Ln = Gd (2-Gd₂), Solvent = THF; Dy (2-Dy₂), Solvent = toluene) were synthesized and fully characterized. The bmtz ligand was selected for its rigid planar structure and ability to coordinate both in bridging and chelating modes, providing a strong platform for magnetic communication. Magnetic measurements combined with broken-symmetry density functional theory (DFT) calculations revealed a remarkably strong antiferromagnetic exchange coupling in 2-Gd₂ with J_Gd-rad = -12.6 cm⁻¹, among the highest reported for tetrazine-bridged systems. Moreover, 2-Dy₂ shows slow magnetic relaxation behavior under zero applied field, with an effective energy barrier (U_eff) of 125 cm⁻¹, which is one of the highest reported for tetrazine-based radical-bridged SMMs. These results establish bmtz^•- as a bridging ligand capable of enhancing the magnetic exchange coupling between lanthanide ions, thereby expanding the toolkit for designing high-performance lanthanide SMMs.
Building on these findings, the focus shifted to pyrazine (pyz) , specifically the use of pyrazinyl (pyz^•-) as a radical bridge, which offer several practical advantages, including synthetic accessibility, commercial availability, rigid and planar geometry that facilitates predictable coordination behavior. A series of dinuclear and tetranuclear pyz^•- -bridged complexes were synthesized: dinuclear [(Cp*₂Ln)₂(pyz^•-)(THF)₂][BPh₄]‧Et₂O (Ln = Gd (3-Gd₂), Dy (3-Dy₂) ; THF = tetrahydrofuran) and tetranuclear [(Cp*₂Ln)₄(pyz^•-)₄]‧10THF (Ln = Gd (3-Gd₄), Dy (3-Dy₄)) complexes. The dinuclear species can also serve as precursors to the tetranuclear complexes, acting as a building block. The magnetic coupling in the 3-Dy₂ complex was determined to be J_Gd-pyz = -22.2 cm⁻¹, setting a new benchmark for organic radical bridges in lanthanide SMMs and surpassing previous tetrazine and dinitrogen-bridged complexes. This strong exchange coupling translates into robust single-molecule magnet behavior under zero-field conditions, resulting in open magnetic hysteresis loops for the Dy complexes. Remarkably, 3-Dy₄ exhibited a giant coercive field of 65 kOe at 1.8 K, the largest coercivity reported to date for Dy radical-bridged SMMs.
The final stage of this dissertation involves extending the nuclearity to unprecedented levels via radical-radical cross-coupling reaction. A novel decanuclear dysprosium complex [(Cp*)₂₀Dy₁₀(L1)₁₀]·12(C₇H₈), where L1 is the anion of 2-prop-2-enylenyl-2-pyrazine, was synthesized. This complex forms a highly symmetric nanoscale wheel through in situ radical coupling, incorporating both S- and R-enantiomers of L1. Although L1 is not a radical species and thus does not mediate Dy-radical exchange, the large nuclearity and strong axial anisotropy of Dy ions lead to slow magnetic relaxation under an applied field. This synthetic advancement demonstrates the potential of using well-studied organic radical to form high-nuclearity species.
Collectively, this dissertation provides new insights into the role of redox-active organic ligands, coordination geometry, and nuclearity in governing the magnetic properties of lanthanide SMMs. The strong exchange interactions and slow magnetic relaxation observed in pyrazine- and tetrazine-bridged systems establish these ligands as valuable platforms for next-generation molecular magnets. Moreover, the successful isolation of high nuclearity complexes via controlled radical coupling highlights the potential for constructing multifunctional molecular architectures with tunable magnetic properties. This work lays a foundation for future exploration of radical-bridged lanthanide SMMs toward applications in information storage, quantum computing, and molecular spintronics
Development of Flexible 3D Printed Strain Sensors
No full textThis thesis investigates the development of fully 3D-printed capacitive strain sensors fabricated from flexible, multi-walled carbon nanotube (MWCNT) reinforced hot-melt adhesive composites. These copolyester- and copolyamide-based filaments (5 wt.% and 10 wt.% MWCNT) enable the creation of compliant, conductive architectures not achievable with conventional carbon-filled polylactide materials. The research first examines how key parameters of fused deposition modeling (FDM), including layer height, raster orientation, printing speed, and nozzle temperature, influence electrical resistivity by altering interlayer fusion, filler alignment, and the continuity of percolated CNT networks. Results show that thicker layers and higher extrusion temperatures promote more stable conductive pathways, while orientation strongly dictates anisotropy in both copolyester and copolyamide systems.
Building on these findings, the dielectric response of the composites is characterized under dynamic shear and temperature-dependent conditions using broadband dielectric spectroscopy. Across 10²-10⁵ Hz, both formulations exhibit conduction-dominated behaviour, with loss permittivity exceeding storage permittivity by two to three orders of magnitude. Mechanical deformation reduces permittivity by disrupting MWCNT-MWCNT contacts, and temperature elevation from 125 °C to 200 °C produces a pronounced increase in permittivity attributable to thermally activated charge transport. Classical dipolar relaxation models do not accurately reproduce the measured spectra, indicating that conduction and interfacial processes dominate relaxation behaviour.
Finally, a single step, multi-material capacitive strain sensor was designed and fabricated using co-printed MWCNT electrodes embedded within a flexible non-conductive sensor body. The hexagonal geometry provides stable deformation paths while simplifying electrode separation. A resonance-based readout system built around a commercially available evaluation module enables high-resolution capacitance tracking, supported by a Python acquisition framework for real-time filtering, drift correction, and visualization
La justice sociale en action ! Comprendre la justice sociale à travers les voix des militant.es : analyse critique du discours de trois luttes sociales francophones au Canada
No full textCette thèse doctorale explore la définition et la mobilisation du concept de justice sociale au sein de trois luttes sociales francophones au Canada : la lutte pour une université francophone en Ontario, la lutte pour le logement social à Montréal et la lutte pour les sites de consommation supervisée à Montréal et Québec. Bien que la justice sociale soit un concept central en travail social et en sciences sociales, elle reste souvent floue et contestée, tant dans le discours académique que sur le terrain. En partant de ce constat, cette recherche vise à clarifier ce concept à travers une approche empirique, en mettant en lumière les perspectives des militantes et militants engagés dans ces mouvements.
L'objectif principal est donc de comprendre comment le concept de justice sociale est compris et mobilisé au sein de luttes sociales militant pour le changement social au Canada. Les sous-objectifs sont : de documenter la place accordée à la justice sociale dans les discours des leaders des mouvements à l'étude ; d'identifier les différentes manières dont elle est comprise et mobilisée ; d'analyser les actions entreprises pour son avancement ; et de comparer les similarités et différences entre les luttes étudiées.
L'analyse critique du discours (Fairclough, 1995; van Leeuwen, 2015) sert à la fois de cadre théorique et méthodologique. Cette approche permet d'examiner les discours des leaders de mouvements sociaux ainsi que les documents produits par ces mouvements afin d'identifier la compréhension de la justice sociale et les stratégies utilisées. Sur le plan méthodologique, cette thèse comprend trois études de cas correspondant aux trois luttes sociales étudiées et s'appuie sur un corpus de recherche constitué à partir de deux méthodes de collecte de données : 29 entretiens menés avec des leaders militants et 51 documents recueillis, répartis entre les trois luttes.
Dans l'ensemble cette recherche démontre que la justice sociale est un concept polysémique qui prend des formes distinctes selon les contextes, influencée par les objectifs, les besoins et les revendications spécifiques de chaque lutte sociale. Les résultats démontrent également que la justice sociale peut être définie au travers de plusieurs thèmes, notamment l'équité et l'égalité, la défense et la reconnaissance des droits, et la redistribution de la richesse. La justice sociale agit aussi comme un moteur d'action grâce aux stratégies et actions spécifiques de chaque lutte. Enfin, cette recherche montre que la justice sociale est un concept qui va au-delà des objectifs de la lutte, participant ainsi à la création de solidarités entre différentes luttes sociales
Automated Log Analysis: Failure Prediction and Anomaly Detection Using Machine Learning and Large Language Models
No full textThe dependability of modern software systems is becoming increasingly crucial as their complexity and scope continue to grow. Log data recorded during system execution can be leveraged to predict failures and detect anomalies automatically. However, designing accurate and efficient log-based analysis methods remains challenging due to the diversity of system environments, the instability of logs over time, and the scarcity of labeled data for training. This thesis addresses these challenges by systematically evaluating deep learning models for log-based failure prediction and by proposing a hybrid data-efficient approach that combines machine learning and a Large Language Model (LLM) for anomaly detection in unstable logs.
The first part of the thesis focuses on failure prediction using log data. While several Machine Learning (ML) and Deep Learning (DL) methods have been proposed, existing empirical studies are limited in scope, often examining only a subset of DL architectures or narrow dataset conditions. This thesis systematically investigates the combination of different log embedding strategies with major types of DL architectures, including Recurrent Neural Networks (RNNs), Convolutional Neural Networks (CNNs), and transformers. To enable a comprehensive evaluation, we design a modular architecture to accommodate various embedding strategies with different DL encoder configurations and synthesize 360 datasets with controlled characteristics, such as dataset size and failure rate, across three distinct system behavioral models. Experimental results demonstrate that CNN-based models with the Logkey2vec embedding strategy achieve the best overall performance, particularly when the dataset size exceeds 350 instances or when the failure rate exceeds 7.5%. These findings provide actionable insights into selecting effective models depending on dataset characteristics.
The second part of the thesis addresses Anomaly Detection in Unstable Logs (ULAD), a more realistic but underexplored situation where logs evolve due to software or environmental changes. Existing approaches based on machine learning typically require substantial labeled data, whereas LLMs can generalize with little data but struggle to capture structured log patterns. To address these complementary limitations, this thesis introduces FlexLog, a novel hybrid approach that integrates simple ML models (Decision Trees (DT), K-Nearest Neighbors (KNN), and Single-layer Feedforward Network (SLFN)) with a LLM (Mistral) through ensemble learning. FlexLog further incorporates a cache and a retrieval-augmented generation (RAG) components to improve time efficiency and accuracy, respectively. We evaluate FlexLog on four datasets specifically configured for unstable log anomaly detection. Results show that FlexLog consistently outperforms baseline methods by at least 1.2 percentage points (pp) in F1 score, while reducing labeled data requirements by 62.87 pp. When trained on the same amount of data as the baselines, FlexLog achieves up to a 13 pp increase in F1 score on the ADFA-U dataset, while maintaining an inference time of less than one second per log sequence, making it suitable for most practical applications.
By systematically evaluating deep learning architectures for log-based failure prediction and introducing a hybrid ML-LLM framework for detecting unstable log anomalies, this thesis provides a unified and empirical foundation for advancing log-based dependability analysis. To ensure reproducibility and enable future research, all datasets, tools, and experimental results are made publicly available
Factors associated with adverse haemodynamic events during the STARRT-AKI trial: a post-hoc secondary analysis
No full textAbstract Introduction Haemodynamic adverse events related to renal replacement therapy are a complication of all RRT modalities used in the ICU, including intermittent haemodialysis (IHD), sustained low efficiency dialysis (SLED) and continuous renal replacement therapy (CRRT). At present it is unclear which risk factors predispose to HAE and whether these contribute to adverse patient outcomes. Methods We performed a secondary analysis of the multinational STARRT-AKI trial to assess factors associated with the occurrence of haemodynamic adverse events (HAE) in patients receiving RRT and whether these HAE were associated with less favourable clinical outcomes. The primary analysis was a multivariable Cox proportional hazards model based on the least absolute shrinkage and selection operator (LASSO), which included time to HAE as the dependent variable. Results Factors significantly associated with an increased hazard ratio (HR) for HAE during RRT were a higher SOFA score at RRT initiation (HR 1.05; 95% 1.00-1.10), use of IHD as the initial RRT modality in comparison to CRRT (HR 1.74; 95% CI 1.28–2.37) and use of SLED as the initial RRT modality in comparison to CRRT (HR 2.73; 95% CI 1.65–4.51). In a multivariable analysis, adjusted for baseline patient characteristics and RRT initiation covariates, there was no significant association between the occurrence of a HAE during RRT and mortality, dialysis dependence, length of stay, RRT-free days, ventilator-free days or vasoactive-free days, respectively. There was, however, a significant association between multiple haemodynamic adverse events and all-cause mortality at 90 days. Conclusions In this secondary analysis of the STARRT-AKI trial, the use of intermittent RRT modalities and higher severity of illness were associated with HAE during RRT. These events were not significantly associated with adverse clinical outcomes, apart from a significant association between multiple HAE and all-cause mortality at 90 days
Cadre de référence pour l’apprentissage expérientiel: Guide synthèse
No full textLe Cadre d'apprentissage expérientiel (AE) de l'Université d'Ottawa est un outil à la fois pratique et stratégique conçu pour appuyer le développement de programmes, la conception de cours et la reconnaissance d'activités d'AE de haute qualité. Développé à l'origine dans le cadre de la création du Régime d'apprentissage expérientiel approfondi (RAEA), un parcours de 30 crédits de premier cycle de cours labellisés AE, ce cadre a depuis évolué pour devenir un guide institutionnel global visant à favoriser la cohérence, la qualité et la visibilité de l'offre en AE. Alors que de nouvelles formes d'AE sont développées sur le campus, le Cadre demeure un outil adaptatif qui continuera d'évoluer selon les besoins et les nouvelles opportunités.Préparé par Affaires Étudiantes, Développement de carrière et apprentissage expérientiel (DCAE), Université d'Ottaw
Multi-level barriers and facilitators to buprenorphine use in Ontario, Canada: a qualitative study using the theoretical domains framework
No full textAbstract Background Few studies have systematically examined the barriers and facilitators to buprenorphine uptake, despite increasing opioid-related harms and guideline recommendations for use. The aim of the study was to use behaviour change frameworks to investigate barriers and facilitators to buprenorphine access and use from diverse perspectives in Ontario, Canada. Methods We conducted semi-structured face-to-face or telephone interviews with Ontarians including: people with living/lived expertise of opioid use (including family members), healthcare professionals, and organizational and system-level representatives. We used purposive sampling via existing professional networks to recruit participants with diverse experiences. The Theoretical Domains Framework (TDF) guided the data collection tool and analysis. Interviews were recorded, transcribed, coded, and underwent thematic analysis involving three study team members. Results We interviewed 28 participants between September 2019 and January 2020. Three predominant TDF domains were identified across all 4 levels: (1) environmental context/resources; (2) beliefs about consequences; (3) social influences. Key cross-cutting themes included access to comprehensive care, medication and treatment characteristics, confidence and experiences with buprenorphine, as well as supportive relationships and stigma/discrimination. Conclusions Multi-level barriers to optimal buprenorphine implementation continue in the face of the drug toxicity crisis. To counter the identified barriers and enhance facilitators, there is need for mentorship models of support for prescribing, flexibility in buprenorphine treatment requirements, better recognition of mental health and the social determinants of health in buprenorphine treatment, and comprehensive and integrated systems of care
Identifying behaviour change techniques within precision health interventions that use continuous glucose monitoring: a secondary analysis of a scoping review
No full textAbstract Background Continuous glucose monitoring (CGM) is increasingly being used within precision health interventions to motivate behaviour change. However, there is considerable variability and complexity in the design of behaviour change interventions that incorporate CGM-based biofeedback, making it challenging to disentangle the intervention components that are driving intervention effects. The objective of this review is to identify the behaviour change techniques and mechanisms of action commonly implemented alongside CGM-based biofeedback. Methods We conducted secondary analyses of a scoping review to identify health behaviour interventions (RCTs) that provided CGM-based biofeedback to promote behaviour change in adults. Two researchers applied the 93-item Behaviour Change Techniques (BCT) Taxonomy (v1) to independently code intervention content in all trial arms (i.e., intervention and comparison arms) dependent upon their targeted behaviour of CGM use, glucometer use, diet, physical activity, or medication adherence. BCTs were analysed individually and according to their corresponding category. We performed univariate linear regression analyses to examine whether the presence of individual BCTs and target behaviours influenced pre-post changes in HbA1c within CGM-based intervention arms. Results Thirty-one RCTs comprising 35 intervention arms and 29 comparison arms were included. Theory was reported in 4 studies (13%), most commonly Self-Efficacy Theory. Mechanisms of action (MoAs) were specified in 5 studies (16%), typically targeting beliefs about capabilities. We identified 40 (of 93 possible) unique BCTs, with intervention arms employing an average of 7.1 BCTs (SD: 4.8) compared to 5.3 BCTs (SD: 4.3) in comparison arms. The most frequently implemented BCT categories in CGM-based biofeedback interventions were ‘Feedback and monitoring’ (n = 35/35, 100%), ‘Shaping knowledge’ (n = 28/35, 80%), and ‘Social support’ (n = 22/35, 63%). Commonly used BCTs supporting CGM use and promoting dietary and physical activity changes included ‘Biofeedback’ (n = 35/35; 100%), ‘Instruction on how to perform the behaviour’ (n = 19/35; 54%), and ‘Credible source’ (n = 14/35; 40%). Univariate linear regressions did not identify any individual BCTs or targeted behaviours that significantly moderated HbA1c outcomes. Conclusions RCTs using CGM to change behaviour in adult populations include a range of BCTs, focusing predominantly on BCTs that support the implementation of CGM itself. Future research should examine whether BCTs operate through distinct MoAs when supporting CGM uptake and use versus when promoting broader health behaviour change in conjunction with CGM-based biofeedback
Development of the Canadian food intake screener for adolescents based on Canada’s Food Guide 2019 healthy eating recommendations
No full textAbstract Background Assessing adolescents’ dietary intakes in relation to Canada’s Food Guide 2019 (CFG-2019) recommendations on healthy food choices is a critical component to public health surveillance efforts. The study aimed to develop a brief self-administered screener to assess food intake based on CFG-2019 food choices recommendations among English- and French-speaking adolescents aged 10–17 years living in Canada. Methods The development and assessment of the content validity of the tool was undertaken in collaboration with Health Canada advisors and informed by external content experts, including nutrition researchers and practitioners. Following a rapid review of screeners used among children aged 6–17 years, an initial draft was developed, and content validity was assessed by an expert panel with expertise in public health nutrition and questionnaire validation (English n = 13, French n = 7). Two rounds of cognitive interviews were then conducted with adolescents (English n = 15, French n = 14) to assess comprehension and further refine the screener items. Cognitive testing using a direct probing approach was conducted iteratively in two phases to assess understanding of questions and incorporate feedback from adolescents to improve the clarity and wording of the items at each phase. Results Following the expert panel and iterative discussions with Health Canada advisors, four items were removed from the initial 14-item screener as these items were deemed not sufficiently reflective of the CFG recommendations and one item asking about water intake was tested. Cognitive testing revealed that the items were well understood overall, and feedback at each interview round enabled additional refinements to improve comprehension. The resulting screener includes 10 items designed to rapidly assess food intake based on CFG-2019 recommendations on healthy food choices for adolescents aged 10 to 17 years. Conclusions The Canadian Food Intake Screener for Adolescents/Questionnaire court canadien sur les apports alimentaires des adolescents is designed to rapidly assess dietary intake over the past week among children aged 10 to 17 years. Before it can be used for research and population-level nutrition surveillance, further research is needed to develop a scoring system and evaluate the screener’s construct validity and reliability
Association between physical activity, sleep, and screen time and cardiometabolic risk factors among Brazilian adolescents: a cross-sectional analysis of a nationally representative sample
No full textAbstract Background A prominent gap in the literature is the lack of evidence from low-middle-income countries on the association between adherence to 24-Hour Movement Guidelines (physical activity, sleep, and screen time) and cardiometabolic risk factors among adolescents. This study examined the association between adherence to the 24-Hour Movement Guidelines and cardiometabolic risk factors among Brazilian adolescents. Methods The probabilistic sample consisted of 29,226 adolescents (60.5% females) aged 12 to 17 years. This school-based cross-sectional study was conducted across all geographical regions of Brazil. Body mass and height were measured to estimate body mass index. Waist circumference, blood pressure, and venous blood samples were collected to estimate fasting glucose, triglycerides, and HDL cholesterol. Cardiometabolic risk factors were classified according to International Diabetes Federation criteria. Data on 24-hour movement behaviors (moderate- to vigorous-intensity physical activity, sleep duration, and recreational screen time) were collected using a self-administered questionnaire and classified according to the Canadian 24-Hour Movement Guidelines. Binary logistic regression models were used to estimate odds ratios (OR) and 95% confidence intervals (95%CI). Results For males, lower ORs for high blood pressure [OR: 0.34 (95%CI: 0.20–0.58)], high triglycerides [OR: 0.47 (0.28–0.78)], metabolic syndrome [OR: 0.36 (0.17–0.78)], and the presence of two [OR: 0.49 (0.32–0.58)] and ≥ 3 cardiometabolic risk factors [OR: 0.35 (0.15–0.80)] were observed in adolescents who met the 24-Hour Movement Guidelines compared to peers who did not meet the guidelines. For females, no association was found between adherence to 24-Hour Movement Guidelines and cardiometabolic risks. Conclusion Meeting 24-Hour Movement Guidelines was beneficial for reducing the odds of cardiometabolic risk factors in males