VictorJuiz/thesis huggingface dataset:
Developing a Complex Intervention to Improve Knee Osteoarthritis Care in Persons with Type 2 Diabetes

Knee osteoarthritis is a leading cause of disability, frequently co-occurs in people with type 2 diabetes, and the presence of knee osteoarthritis-related chronic joint pain and functional impairment can challenge optimal type 2 diabetes management. It is thus important to effectively identify and treat knee osteoarthritis in these individuals to improve type 2 diabetes outcomes and quality of life, in addition to osteoarthritis outcomes. Through four inter-related projects and guided by the Medical Research Council framework, this thesis describes the development of a complex intervention to improve the diagnosis and evidence-based treatment of knee osteoarthritis in people with type 2 diabetes. It involved a partnership with Arthritis Society Canada for intervention delivery. The first three projects used qualitative methods to understand determinants of behaviour in stakeholder groups using the Theoretical Domains Framework. The first project identified barriers and enablers to seeking and engaging in osteoarthritis care in people with type 2 diabetes. The second project identified barriers and enablers of diabetes health professionals’ assessment and treatment of knee osteoarthritis in their patients. The third project identified barriers and enablers of arthritis therapists from Arthritis Society Canada considering type 2 diabetes when formulating an osteoarthritis management plan. The fourth project comprehensively described the multi-step process of complex intervention development that combined theories of behaviour change, stakeholder involvement, and existing evidence. Relevant domains identified from stakeholder interviews were mapped to behavioural change techniques to identify potential intervention components. Stakeholder meetings ascertained acceptability and feasibility of proposed intervention components, and a program theory was constructed to inform the implementation of the intervention and its evaluation. The intervention components, incorporating a range of behavioural change techniques at the patient, health professional, and arthritis therapist level, intend to identify persons with knee osteoarthritis within type 2 diabetes care and refer them to Arthritis Society Canada for delivery of evidence-based longitudinal knee osteoarthritis management. Diverse stakeholder input throughout the development allowed co-design of an intervention that appears feasible and acceptable to target users. This thesis lays the foundation for subsequent feasibility testing and evaluation, and ultimately seeks to inform improved care and outcomes for individuals with type 2 diabetes and knee osteoarthritis.

Keywords: Implementation Science
Osteoarthritis
Type 2 Diabetes
Advisor: Hawker, Gillian A
Satisfying Model Validity for Robust Clinical Machine Learning for Time-Series

Many healthcare data are endogenously produced as a by-product of care. The chronologically recorded healthcare system interactions naturally become time-series data. Machine learning models built to infer meaningful information from these data have the ability to capture the complex dynamics of human health leading to an improvement in care without an escalation in cost. However, these models must be safe and effective in order to have an impact on healthcare. Safety and efficacy stem from models which are robust to perturbations. This thesis investigates machine learning robustness under three prominent dataset shift settings. First, this thesis identifies common design pitfalls that lead machine learning models to immediately violate internal validity. Such models will not be expected to generalise to deployment scenarios. The effects of these design decisions are highlighted and remedied. Next, internal validity violations due to dataset shift are explored. In an attempt to preserve privacy in de-identified datasets, models developed for electronic health record prediction tasks have been blinded to damaging covariate shift. In COVID-19 detection tasks using wearable data, failure to address prior probability shift leads to inflated expectations of performance. By addressing feature representation and study design, this thesis reports performance that could be reasonably expected during deployment. Finally, necessary external validity violations due to data scarcity are explored. With endogenously collected data, especially health data, it is not feasible to invest in collecting more supervised labels. Yet label-scarce datasets are abundant, whether it be for emergent disease detection, rare disease identification, or from data-scarce institutions. Pre-training using multi-task learning is discovered as a superior method to masked imputation for target-label scarce tasks. A large EHR domain transfer experiment reveals that pretraining on external datasets only confers benefits in the few-shot transfer setting. Preference is given to participate in data warehouses rather than sharing pre-trained models. This thesis illustrates how to design effective machine learning models for endogenously produced clinical time-series, how to ensure they are robust to inevitable distribution shifts, and how to share knowledge between domains. It is essential to overcome these bottlenecks to realise the potential of machine learning for clinical time-series data.

Keywords: Dataset Shift
Healthcare
Machine Learning
Neural Networks
Robustness
Time-series
Advisor: Goldenberg, Anna
Ghassemi, Marzyeh
Analysis of Learning Algorithms via Diffusion Limits

Modern machine learning algorithms are often very difficult to analyze, as discrete units of scaling and time typically do not lead to very clean closed form representations. For example, updates can be in discrete time, and neural networks have finitely many distinct neurons per layer. In this thesis, we study the computational properties of two such algorithms through their continuous scaling limits. In both cases, the limiting object has a rich mathematical structure, is significantly more tractable to analyze, yet remains a good approximation of the finite discrete algorithms. In particular, we will see that both algorithms converges to a diffusion limit described by stochastic differential equations. In the first project of this thesis, we study a discretization of the Langevin diffusion on a product of spheres manifold. We provide a convergence guarantee in terms of KL-divergence under the assumption of a logarithmic Sobolev inequality. Furthermore, we also establish a Poincar\'e and logarithmic Sobolev inequality in the presence of saddle points, where we introduce a new escape time based approach. In the second project, we consider ResNets --- neural networks with skip connections --- at initialization. We show that the infinite-depth-and-width limit for a single input marginal is a log-normal distribution with adjusted parameters. In particular, we provide a new approach of analyzing of this limiting result by identifying the norm of each layer as a key structure, and hence avoiding previous combinatorial arguments. In the final project of this thesis, we consider the joint distribution of neural networks over many input data points. We show that upon a modification of the activation functions, the infinite-depth-and-width limit is described by a stochastic differential equation for the covariance matrix. In particular, the limit remains a great approximation for finite size networks, and we already gain significant tractability over a simple example for finite explosions.

Keywords: Deep Learning Theory
Infinite-Depth-and-Width Limit
Langevin Algorithm
Advisor: Roy, Daniel M
Erdogdu, Murat A
Harmonic Measures for Random Walks on Cocompact Fuchsian Groups

The singularity conjecture states that for an admissible finite-range random walk on a cofinite Fuchsian group $\Gamma$, the hitting measure is singular with respect to the Lebesgue measure on $S^1$. It has been known to hold for finite-range random walks on cofinite non-cocompact Fuchsian groups; however, none of the existing methods immediately generalize to the cocompact case. In this thesis we present a method which allows us to prove the singularity conjecture for a wide variety of finite-range random walks on cocompact Fuchsian groups, using the Blach\`ere-Ha\"{i}ssinsky-Mathieu criterion. In particular, we are able to prove the conjecture for a class of random walks on cocompact Fuchsian groups generated by the side-pairing translations identifying opposite sides of a centrally symmetric polygon. This includes a family of non-nearest-neighbour random walks supported on powers of side-pairing translations. Finally, we generalize our results to a similarly defined class of random walks on Coxeter groups, showing that the hitting measures for the Coxeter groups generated by reflections with respect to the sides of centrally symmetric polygons are singular in the nearest-neighbor case.

Keywords: Fuchsian groups
harmonic measures
random walks
singularity conjecture
Advisor: Tiozzo, Giulio
Unconventional Superconductivity in Spin-Orbit Coupled Systems

Following the exciting discovery of the high-temperature superconducting cuprates, resulting in a rapid rise in the highest known transition temperatures, the condensed matter community broadened its search for superconductivity tonon-cuprate compounds with similar structures. Much interest and intrigue surrounded the discovery of superconductivity in Sr2RuO4, thought to be a leading candidate for chiral p-wave superconductivity, a possible building block of fault tolerant quantum computers. However, 20-year-old Knight shift results, once taken as evidence of this p-wave state, were recently overturned, reinvigorating the debate on the superconducting symmetry. Despite receiving a vast amount of attention, the pairing state remains shrouded in mystery with various seemingly contradictory experimental results. Throughout this thesis we attempt to reconcile some of these experimental results within one coherent picture. Using an interorbital even-parity spin-triplet pairing state, we show that the pseudospin-singlet nature of this state, arising due to spin-orbit coupling, results in a drop of the Knight shift in the superconducting state, consistent with experiments. We also consider how the microscopic details of the spin-orbit coupling allow for a multi-component, nodal, time-reversal symmetry breaking superconducting state as required by various experiments. Further, we use the underlying interorbital nature of this pairing state to explain phase-sensitive Josephson junction experiments, thought to be indicative of an odd-parity pairing state, despite the even-parity pairing presenthere.Using the same model which results in superconductivity in Sr2RuO4, we consider the closely related material, Sr3Ru2O7, and show that this same model captures both the lack of superconductivity, as well as the observed spin-density wave order, helping to justify our model. Finally, as the presence of p-wave superconductivity in Sr2RuO4 appears less and less likely, we consider how a p-wave superconductor may instead be engineered via distortions. In the related material, Sr2IrO4, rotations and tilting of the oxygen octahedra alter the Fermi surface as well as effective interaction terms, which work in combination to supress d-wave pairing and reveal p-wave pairing as the leading instability.

Keywords: interorbital pairing
spin-orbit coupling
spin-triplet
strontium ruthenate
superconductivity
Advisor: Kee, Hae-Young
Volatility, Atmosphere and Relation: A Multi-Modal Ethnography of Petrochemical VOCs in Toronto, Canada

This dissertation draws from feminist science and technology studies (STS) and sociocultural anthropological theory and methods to explore multiple sources of knowledge production about petrochemical derived gases known as volatile organic compounds (VOCs) in Toronto, Canada. A multi-modal dissertation, it brings 18 months of ethnographic fieldwork at two fieldsites, a publicly-funded environmental health clinic, and the neighbourhood of South Parkdale together with original archival research, filmic media art, photography produced during collaborative workshops with chronically ill and disabled women, and autobiographical prose. Framed throughout by the key concept of “volatility,” an understanding that petrochemical volatile organic compounds have socially, affective, and economically volatile effects beyond the material, I articulate the uneven intergenerational consequences that everyday, long-term atmospheric exposures to petrochemicals in everyday consumer products have, underscoring intersectional forms of identity and difference. Medical chart review (N=82) and interviews (N=70) reveal how chemical sensitivities in particular are not adequately addressed by the existing highly gendered and classed medical system and disability insurance providers. Drawing on my experiences in housing organizing contexts and navigating rental housing accessibility, I point to how uneven distributions of atmospheric exposures especially impact low-income tenants and are instrumentalized in processes of renoviction (eviction via renovation). Given these stakes, I highlight the crip-led possibilities of collective atmospheric access production. I conclude by suggesting that collective relations to volatility must center how VOCs are signatures of chemical violence in settler colonial Toronto, and thus be foregrounded in relation to the historical and material preconditions of their existence. This is supported by an immanent relationship to material ethics, and building alliances across crip, anticolonial, and antiracist movements.

Keywords: atmosphere
chemical sensitivity
feminist science and technology studies
multi-modal ethnography
petrochemicals
volatile organic compounds
Advisor: Song, Jesook
Kilroy-Marac, Katie
Searches for Lepton Flavour Violating Higgs Boson Decays with the ATLAS Detector

Measurements of the lepton flavour violating Higgs boson decays to the final states $e\tau$ and $\mu\tau$ are presented in this thesis. These measurements use data from proton-proton collisions measured by the ATLAS detector at a centre-of-mass energy of $\sqrt{s} = 13$ TeV, corresponding to an integrated luminosity of 138 fb$^{-1}$. No signicant excess above the Standard Model predictions is observed and upper limits on the lepton flavour violating branching ratios are set.

Keywords: ATLAS
Experiment
Flavour
Higgs
Lepton
Search
Advisor: Orr, Robert S
Structural Insights into Modification and Export of the Pseudomonas aeruginosa Alginate Exopolysaccharide

Pseudomonas aeruginosa is an opportunistic human pathogen that is notorious for causing chronic lung infections in individuals with cystic fibrosis and tolerating antimicrobial treatments by forming a biofilm. Biofilms contain a variety of different components, including exopolysaccharides. During chronic lung infections, P. aeruginosa converts to a mucoid phenotype by constitutive expression of the AlgU/T regulon. As a result, P. aeruginosa overproduces the alginate exopolysaccharide, leading to worse patient outcomes.In the cytoplasm, the process of alginate biosynthesis begins with nucleotide-sugar precursor formation by AlgA, AlgC, and AlgD. These precursors are polymerized by Alg8 in the inner membrane upon cyclic diguanylate binding to Alg44. Following polymerization and translocation into the periplasm, the polymer can be modified by epimerization by AlgG, or acetylation by the concerted action of AlgI, AlgJ, AlgF, and AlgX. We proposed that AlgF is involved in protein-protein interactions mediating formation of an AlgJFX periplasmic acetylation complex. We demonstrated that AlgF can bind to AlgJ and AlgX in vitro and provide evidence for formation of an AlgIJFX complex. Once the polymer is modified, it gets exported via the outer membrane porin AlgE and the tetratricopeptide repeat-containing protein AlgK. We elucidated the crystal structure of the AlgKX complex and showed that AlgK, AlgX, and the AlgKX complex are capable of binding alginate polymer. In P. aeruginosa, disruption of the AlgKX complex resulted in abrogated alginate secretion and biofilm attachment, demonstrating a role for AlgX in alginate export. Predictive modelling of the AlgEKX outer membrane modification and secretion complex provided insight into how the process of alginate acetylation and export are coordinated in P. aeruginosa. If polymer is accumulated within the periplasm, AlgL functions as a periplasmic homeostasis enzyme to degrade aberrantly exported alginate. We identified key catalytic site residues in AlgL that result in loss of enzymatic activity, reduced cell viability, and abnormal cellular morphology when mutated. We showed that an algL deletion mutant results in accumulation of alginate within the periplasm. This was mitigated by constitutive expression of the AlgU/T regulon, suggesting that there are proteins within the regulon that can compensate for loss of AlgL.

Advisor: Howell, Patricia L
Identification and Systemic Investigation of Novel Chemical Seed Priming Agents and their Persistent Effect on Plant Phenotype and Metabolism

Priming is a general term for a phenomenon in which exposure to an early environmental stimulus results in a more rapid or vigorous response when the plant is exposed to subsequent challenges. Various types of priming have been described: ‘systemic acquired resistance’ against biotic stimuli, ‘epigenetic stress memory’ induced by repeated abiotic stimuli, and ‘seed priming’ treatments which apply water and additional adjuncts to seeds to improve crop performance. Using a high-throughput chemical genomic approach, thousands of small molecules were screened to identify compounds capable of ‘chemical priming’, asking if these could serve as artificial environments to persistently induce altered response to later abiotic challenges when applied as seed treatments. Several novel structural categories of molecules were identified that had the ability to reduce total anthocyanin accumulation in 7-18-day old seedlings induced by later low temperature challenge, persisting days after the removal of the compounds. Application variables were explored with thought to future use of the priming compounds as functional treatments: a dose-dependent relationship was established, the necessary temporal window of treatment was explored and reduced, and duration of additional effects on growth and development were documented to ensure minimal detrimental side effects on the treated plants. Cross-testing of the priming treatments identified by low temperature screening for ability to reduce anthocyanin induction by alternative exogenous and endogenous conditions showed consistent attenuative effect and revealed that the effect of priming on this metabolic phenotype was not specific to low temperature response. Targeted transcriptional profiling of genes encoding flavonoid and anthocyanin biosynthetic enzymes and untargeted metabolomic profiling of total plant extracts were undertaken to characterize the detailed effect of these chemical seed priming treatments on this pathway. These revealed significant continued perturbations in the secondary metabolism of chemically-primed plants including but not limited to the expected changes in anthocyanins, and suggested a potential target site in upstream phenylpropanoid regulation for further analysis. The presented research represents a proof-of-concept for the functional potential of seed priming with novel compounds, and underscores the complexity of secondary metabolism as a component of plant stress response.

Keywords: Anthocyanin
Arabidopsis
Chemical genetics
Plant stress
Seed priming
Advisor: Campbell, Malcolm M
Instability of Gravitational and Electromagnetic Perturbations of Extremal Reissner--Nordstr\"om Spacetime

We study the linear stability problem to gravitational and electromagnetic perturbations of the \textit{extremal}, $ |Q |=M, $ Reissner--Nordstr\"om spacetime, as a solution to the Einstein-Maxwell equations. Our work uses and extends the framework \cite{giorgi2019boundedness,giorgie2020boundedness} of Giorgi, and contrary to the subextremal case we prove that instability results hold, similar to those of Aretakis, for a set of gauge invariant quantities along the event horizon $ \mathcal{H}^+ $. In particular, for associated quantities shown to satisfy generalized Regge--Wheeler equations we prove decay, non-decay, and polynomial blow-up estimates asymptotically along $ \mathcal{H}^+ $, the exact behavior depending on the number of translation invariant derivatives that we take. As a consequence, we show that for generic initial data, solutions to the generalized Teukolsky system of positive and negative spin satisfy both stability and instability results. It is worth mentioning that the negative spin solutions are significantly more unstable, with the extreme curvature component $ \underline{\alpha} $ not decaying asymptotically along the event horizon $ \mathcal{H}^+, $ a result previously unknown in the literature.

Keywords: Extremal Reissner--Nordstr\"om
Instability
Linear Stability
Teukolsky system
Advisor: Aretakis, Stefanos
The Dynamic Network Connectivity of Music Listening

Music listening is a sophisticated behaviour that employs numerous networks of brain regions. Because music remains enjoyable later in life, it is often used in clinical settings with those with neurodegeneration. However, much is still unknown about how music listening adapts to reconfigurations in brain network dynamics related to healthy aging. This dissertation examines dynamic brain network activity during music listening in healthy adults. Network measures were analyzed with behavioural and stimulus data across three studies using a combination of hidden Markov modelling and partial least squares. The first study presents age- and preference-related differences in music listening in healthy younger and older adults using fMRI. Both age groups showed higher occupancy (the proportion of time a network was active) in a temporal-mesolimbic network while listening to self-selected music. Activity in this network was strongly positively correlated with liking and familiarity ratings in younger adults, but was more ambiguously correlated in older adults. Additionally, older adults showed a higher degree of correlation between liking and familiarity ratings consistent with past behavioural work on age-related dedifferentiation. The second study presents effects in a subset of the older adult group from the first study following an 8-week music listening intervention. Results showed higher occupancy in the temporal-mesolimbic network following the intervention suggesting that network activity can change in response to music-based interventions. The third study presents task differences in a music listening task in healthy young adults using EEG. In this study, participants listened to music while continuously rating either perceptual features in the musical signal, or emotional states induced by the music. Network activity in medial frontoparietal, pericentral, anterior frontal, and bilateral temporal networks was most strongly positively correlated with rudimentary features in the musical signal during the perceptual listening task. In the emotional task, transitions between networks were more positively correlated with low-arousal low-valence emotional states in anterior cingulate, frontal, and occipital networks. I discuss the implications of modelling music at different spatiotemporal scales with a particular focus on these findings’ applicability for clinical research.

Keywords: Aging
Computational neuroscience
Music
Network dynamics
Advisor: McIntosh, Anthony R