VictorJuiz/thesis huggingface dataset:
Regionalism in the Operas of John Beckwith and James Reaney

Regionalism is the cultural trend in which the idiosyncrasies of a given region, and their influence on human lives, social structures, and cultural development, are explored and expressed through an artistic medium. This trend emerged in Canadian literature in the 1920’s and 30’s, and experienced a resurgence in prominence in the 1970’s. However, the significance of regionalism in Canadian art music remains virtually unexplored. The purpose of this study is to explore the concept of regionalism in the four Beckwith/Reaney operas: Night Blooming Cereus (1959), The Shivaree (1982), Crazy to Kill (1989), and Taptoo! (2003). The author extrapolates from a literary understanding of regionalism to create a framework of analysis for these four musical works. Beckwith and Reaney employed regionalism as a vehicle for innovation within the operatic form, and exploited the tension between European operatic norms and authentic portrayals of life in rural Ontario with these works. The concluding chapter situates these operas within the context of the twentieth-century Canadian opera marketplace through an examination of composition and performance history, and examines the influence of regionalism on their critical and popular reception.

Keywords: Canadian Music
James Reaney
John Beckwith
Music
Opera
Regionalism
Advisor: MacDonald, Lorna
Modelling of Multiphase Flows in Continuous Casting

Multiphase flow phenomena (MFP) during the continuous casting processes often become the root cause of defects in the final product. For high-end steel applications, understanding MFP-related defects is critical. At the caster, several phases interact during the course of casting. Gas-liquid interaction is observed when argon is injected into the mold which forms multi-size bubbles in liquid steel. Some bubbles are entrapped into the advancing solidifying shell and form blister defects in the slab. Gas-slag interaction occurs when bubbles interact with the slag layer. Bubbles shear the slag layer and create the slag open eye which becomes a source of reoxidation. Furthermore, slag/slag interaction can be observed when ladle slag enters the tundish due to vortex funneling or sink draining. Apart from emulsification, it can also affect the tundish covering slag layer. Physical modelling was performed using high-speed shadowgraphy imaging to capture the bubbles. Suitable image processing techniques (IPT) were identified and utilized to obtain bubble size distribution (BSD) and mean bubble size in a reduced scale mold. Dimensional analysis was performed to identify a correlation of mean bubble diameter at different gas and liquid flow rates, surface tension, viscosities, and densities of the liquids. To improve the correlation and reduce the prediction error, machine learning-based models were also developed with no overfitting. Moreover, for gas-slag interaction, the formation of open eyes in the mold top slag layer was studied through physical modelling. Different types of slag open eyes such as symmetrical, asymmetrical, liquid flow driven open eyes were observed at different gas fraction conditions. A mechanistic model was developed to predict the dimensionless open eye area of symmetrical open eyes. Lastly, for slag-slag interaction, a mechanistic model was developed and validated against physical modelling experiments to predict the affected area of tundish slag layer by ladle slag. A plumelike structure consisting of slag droplets is formed as ladle slag bounces back to the tundish slag layer. Ladle slag, upon reaching the tundish slag, pushes the tundish slag radially outward. A replacement of tundish cover was observed during physical modelling experiments. Total affected (replacement) area of tundish cover was modelled.

Keywords: Bubble size distribution
Continuous casting
Image Processing
Ladle slag entrainment
Mold Slag Open Eye
Multiphase flows
Advisor: Chattopadhyay, Kinnor Prof.
Quantifying Methane Emissions from the Greater Toronto Area

The government of Ontario has committed to reduce its greenhouse gas (GHG) emissions by 30% of2005 levels by 2030. The Greater Toronto Area (GTA, pop. 6.4 million) is the most populous city in Canada, thus accurately quantifying GHG emissions from the GTA is an important step towards meeting Ontario’s commitments. In order to quantify GHG emissions and emission trends in an urban area, it is important to monitor GHG concentration levels in the atmosphere regularly to verify the accuracy of the reported emissions. In this study, I develop a new methane (CH4) emission inventory, using individual facility reports and emission estimates from area sources gathered for each municipality in the GTA. This allows us to have an emission inventory with a high spatial resolution that can be evaluated by atmospheric measurements. I describe the development of a network of portable Fourier Transform Spectrometers (FTS) in the GTA that measure total columns of CO2, CH4 and CO in the atmosphere and use the tracer-tracer ratio method to estimate CH4 emissions in the GTA. In addition, I preform a detailed assessment of the FTS instrument accuracy, precision and their optical stability using data collected during a field campaign at 6 TCCON stations in North America. I also demonstrate that the low-resolution FTSs could be useful as a “travelling standard” to indirectly compare TCCON instruments to each other. Coincident measurements of the vertical profile of CO2, CH4, and CO from the AirCore balloon platform provided the data required to tie the FTS retrievals to the WMO trace gas standard scale so that they can be used as a satellite validation tool.

Keywords: Greater Toronto Area (GTA)
Greenhouse gas emission inventory
Greenhouse gas measurements
Methane (CH4)
Remote sensing of the atmosphere
Urban greenhouse gas emissions
Advisor: Wunch, Debra
Modulating the Neocortical Extracellular Potassium Concentration In Vivo: Roles for Astrocytes and Energy

A normally functioning nervous system, neuronal and glial activity are dependent on normal extracellular potassium ion concentration ([K]o). Raised [K]o is associated with several disorders including cortical spreading depression, migraine, stroke, neurotrauma and epilepsy. To avoid neuronal adverse conditions, several processes, including those of an astrocytic nature, and ATP-dependent pumps and channels are involved in regulating the [K]o. This dissertation explores the role of astrocytic gap junctional coupling, astrocytic membrane potential and intracellular ATP concentration ([ATP]i) in the neocortical [K]o regulation/distribution using in vivo electrophysiological techniques combined with optogenetics and pharmacological interventions. Application of gap junctional blockers, carbenoxolone and Gap27, partially modulated the amplitude and shape of the evoked potassium ion (K) response but most noticeably decreased the velocity of the spreading evoked K and spreading depolarization (SD)-like responses. Opening of gap junctions by trimethylamine, slightly decreased the amplitude of the evoked K response and markedly increased the velocity of the redistribution of the evoked K and SD-like events. Photostimulation of eNpHR expressing astrocytes, which hyperpolarizes these cells, resulted in a significantly decreased resting [K]o and evoked K responses, and the amplitude of concomitant SD-like events also decreased. Reducing the [ATP]i using 2,4-dinitrophenol, 2-deoxyglucose or endothelin-1 application led to raised [K]o and SD-like events. It is proposed that the increased [K]o is due to impairment of the Na/K ATPase pump and ATP-sensitive potassium channels in the absence of sufficient ATP because, Na/K ATPase inhibition by ouabain led to increased [K]o and ATP-sensitive potassium channel impairment by glibenclamide resulted in decreased [K]o. In brief, observations presented in this dissertation, suggest that [K]o regulation is only partially modulated by astrocytic gap junction coupling with the most critical impact on the velocity, and not the amplitude of the evoked K and SD-like responses. Also, astrocytic membrane hyperpolarization leads to decreased [K]o. Moreover, a decreased [ATP]i leads to increased [K]o. This dissertation has investigated some of the key mechanisms involved in [K]o dynamics and suggests that modulation of astrocytic membrane potential, astrocytic gap junction coupling, and [ATP]i could be potential tools for altering the cerebral cortical [K]o.

Keywords: Astrocytes
Electrophysiology
In vivo
Intracellular ATP concentarion
Neocortical extracellular Potassium concentration
Optogenetics
Advisor: Carlen, Peter
From Palladium to Nickel: The Carboiodination Reaction Forward and Back

For the past half-century, transition-metal catalysis has been an essential part of developing economical, sustainable and efficient strategies to generate pharmaceutically relevant small molecules. Despite the tremendous progress made towards these goals, new synthetic approaches are needed to keep up with the demand for innovation in drug production and discovery. Our group has had a mission to discover atom-economical processes that enable rapid access to a wide array of halogenated heterocycles. We have popularized a strategy known as the carbohalogenation reaction, wherein an aryl/acyl group and a halogen are transferred across a tethered π-bond, generating a cyclic product. Early success was achieved using palladium catalysis, however many limitations remained. First, can we access previously unattainable stereoisomers, whether it be enantioenriched products or different diastereomers? How can we reach a more structurally broad class of halogenated molecules? Lastly, what is the reaction mechanism using different catalysts? Motivated by a shift in the field to convert from precious metals to earth abundant base metals, in 2017 we began our exploration with nickel to answer these questions. Chapter 1 contains necessary background information on transition-metal catalyzed halogenation methods, domino Mizoroki-Heck reactions and landmark reports of carboiodination reactions. Chapter 2 describes the development of the first nickel-catalyzed carboiodination reaction. The following four chapters outline unique reports of nickel-carboiodination reactions, each focusing on fundamental limitations in the field, culminating with the first enantioselective nickel-catalyzed carboiodination reaction in chapter 6. Chapters 7 and 8 focus on the use of palladium in domino reactions. Chapter 7 contains the synthesis of medicinally relevant bis-heterocyclic spirocycles, via a palladium catalyzed domino Mizoroki-Heck/C–H activation reaction. Employing the knowledge of the previous work, chapter 8 combines nickel carboiodination chemistry and palladium C–H activation reactions. Fundamentally, all reactions are microscopically reversible, though studying the reversibility of Mizoroki-Heck reactions is challenging. Enabled by compounds obtained via our carboiodination methodologies, this chapter outlines our comprehensive study of the reversible C–C bond formation using palladium catalysis. Herein, we focus on mechanistic elucidation, development of a diastereoconvergent methodology, as well as study electronic and steric parameters effecting the reaction.

Keywords: Catalysis
Heterocycles
Nickel
Palladium
Advisor: Lautens, Mark
Properties and Stability of Gould Belt Star Forming Regions: Observational and Theoretical Analyses

Star formation occurs when the self-gravity of a clump in a molecular cloud overcomes the support by kinetic motions and collapses. Understanding the morphology and dynamics of these clouds has been crucial in understanding this balance of energy. With a wide range of observations, we are able to estimate various key properties of these regions, which are then used to assess the stability of these clumps. It is imperative that we calculate these properties accurately because any systematic uncertainty will propagate into succeeding analysis. We generated Herschel Optimized Tau and Temperature (HOTT) maps of Gould Belt regions using submillimeter images of the intensity of thermal emission by dust from Herschel Space Observatory. Our robust pipeline fitting the spectral energy distribution to a modified blackbody model using chi-squared minimization required accurate uncertainties for weighting. We investigated and quantified multiple sources of uncertainty in the observed intensity maps, which gave us a chi-squared distribution as expected from theory. Furthermore, we also confirmed the validity of using a modified blackbody to model dust emission in molecular clouds. Generating these products consistently for multiple fields created standardized parameter maps to be used in further analysis. Recent studies on the virial stability of massive clumps reported an unexpected amount of gravitational energy, making these clumps sub-virial. This cannot be explained without a high amount of magnetization, which is contradictory to what is observed. Our explorations suggested that this arises due to the methods used to implement the virial analysis. Therefore, we proposed a new technique that calculates direct estimates of gravitational and kinetic energy using resolved parameter maps. Additionally, we introduced a new clump extraction method using the Abel reconstruction. This allowed us to get better estimates of the column density and mass of the clumps. Applying these techniques to the clumps in multiple Gould Belt regions using the dust parameters from HOTT and molecular line kinematics from GAS, we found that these massive clumps are, in fact, not sub-virial and so are consistent with our current understanding of these regions.

Keywords: Interstellar Medium
Star Formation
Advisor: Martin, Peter G
Matzner, Christopher D
Warning Systems for Undesirable Events during Cancer Treatment: Applying Machine Learning to Administrative Data

Patients frequently experience undesirable events during cancer treatment. Identifying those at risk of undesirable events could facilitate research on prevention and mitigation. We linked multiple population-level administrative databases in Ontario to identify patients who received systemic therapy for cancer between July 1, 2014, and June 30, 2020. We developed longitudinal machine learning systems to predict undesirable events during cancer treatments from demographic, cancer, treatment, symptom, and laboratory features. We focused on three categories of undesirableevents: 1) acute care use, specifically emergency department visits and hospitalizations; 2) cytopenias, including anemia, thrombocytopenia, and neutropenia; and 3) nephrotoxicity from cisplatin, both acute kidney injury and chronic kidney disease. Machine learning generally outperformed simpler regression-based models and provided risk estimates beyond the initial period after treatment initiation. Sensitivity analyses revealed performance deterioration within some subgroups, most concerningly in some underserved populations. Together, these studies demonstrate the potential of warning systems based on longitudinal machine learning models applied to administrative data to predict undesirable events in cancer care. They also highlight potential challenges to address when the systems are deployed in clinical practice.

Advisor: Gallinger, Steven
Investigation of the Involvement of NLRP3 Inflammasome Activation in the Proinflammatory Response to Clozapine

Idiosyncratic drug reactions (IDRs) represent a major concern in the development of new drugs as they are rarely identified in clinical trials and can be severe and life-threatening in nature, putting a given drug’s success at risk. Improved tools for estimating the IDR potential of a drug are of paramount importance in identifying these reactions before products make it to market. The overarching goal of this research was to investigate the role of the inflammasome in the proinflammatory immune response to clozapine, using in vitro and in vivo models of clozapine exposure. Clozapine induces a well-documented proinflammatory response in patients characterized by a delayed increase in neutrophils and proinflammatory cytokines. Clozapine was found to activate NLRP3 inflammasomes, inducing a release of interleukin-1β, and the structural-functional analogue olanzapine, not associated with IDRs, did not activate inflammasomes in the in vitro assay characterized in Chapter 2. An animal model of clozapine-induced neutrophilia in rats was developed and used to characterize the clozapine-proinflammatory response. The role of inflammasome activation in the response to clozapine was evaluated using a new inhibitor of inflammasome signalling, the endogenous ketone β-hydroxybutyrate. Findings from these studies support the role of NLRP3 in the in vivo response to clozapine, as β-hydroxybutyrate was found to attenuate clozapine-induced neutrophilia and increases in CXCL-1 and α-1-acid glycoprotein (Chapter 3). Based on previous findings, myeloperoxidase (MPO) was identified as a neutrophil-derived, oxidative, metabolizing enzyme involved in the covalent binding of proteins. The data from the work described were not sufficient to define a bioactivation mechanism, but further support involving the myeloperoxidase was identified (Chapter 4). The role of inflammasome activation in the initiation and/or development of IDRs was investigated following the in vitro findings reported in Chapter 2 and expanded to the in vivo clozapine work in Chapter 3. The attenuation of the clozapine-induced proinflammatory response by inhibition of NLRP3 inflammasome activation observed in these studies supports the hypothesis that the inflammasome is involved in the development of clozapine-induced agranulocytosis and possesses significant potential for its involvement in other immune-mediated IDRs.

Keywords: Agranulocytosis
Clozapine
Idiosyncratic Drug Reaction
Inflammasomes
NLRP3 Inflammasome
Advisor: Piquette-Miller, Micheline
The Effects of Antimicrobials and Microbial Consortia on Human Gut Microbiota and Antibiotic Resistance Genes

The human gut microbiome is a significant contributor to health and disease. Numerous host and environmental factors are associated with perturbation of gut microbiome composition. Antibiotics significantly alter the composition and function of the gut microbiome, but dose, class and duration-specific antimicrobial effects are not well studied. As it becomes increasingly clear that perturbation of the microbiome is associated with adverse health outcomes, we must understand what factors influence microbiome composition, how to measure relevant aspects of microbiome composition and function, and identify therapeutic targets to remediate or protect the microbiome from iatrogenic perturbation. The first aim of this thesis was to understand the differential effects of antibiotic type and duration on the composition of the microbiota to inform antibiotic therapy that limits its disruption. In a retrospective cohort of 72 term and preterm infants in the neonatal intensive care unit we compared the composition of the microbiota within one week post antimicrobial exposure between infants who received ampicillin plus tobramycin, ampicillin plus cefotaxime, or ampicillin plus tobramycin plus metronidazole. No differences in the composition of the microbiota were observed between treatment groups, but we observed that each additional day of antibiotics was associated with decreased health-associated anaerobes. Our next aim was to validate sequencing and bioinformatic methods to enable accurate detection of antimicrobial resistance genes in a metagenome to inform sequencing requirements for clinical studies. We found that 30 million sequencing reads would be required to detect antimicrobial resistance genes in organisms comprising 1% of a microbial community. Finally, in a post-hoc analysis of a clinical trial of a microbial consortium for treatment of recurrent Clostridioides difficile infection, we found that treatment was associated with multiple-log decreases in Proteobacteria abundance and antimicrobial resistance genes, and sustained increases in health-associated anaerobes. Together these data demonstrate the daily harms of antibiotics on the composition of the gut microbiota where microbial consortia may be an effective strategy for remediating the gut microbiome post-antimicrobial exposure.

Keywords: antibiotic resistance genes
antibiotics
microbial consortia
microbiome
sequencing
Advisor: Coburn, Bryan A
The New Normal? The Practice of Doctoral Education in a Global Pandemic

There has been an increasing interest in doctoral education in recent years, and an increase in the number of doctoral graduates as institutions and nations strive to be competitive in the global knowledge economy, making doctoral education a prescient issue. There is very little existing literature on doctoral education in Canada. In the broader, existing literature, a socialization framework is frequently employed to explore the student’s journey from novice to scholar. A significant factor in this socialization has been the global COVID-19 pandemic, with the Canadian response first being felt in March 2020. In some provinces, some of the COVID-19 social distancing measures remained until early 2022. To address the broad aim of this research — to attempt to understand doctoral students’ perceptions, experiences, and socialization during the COVID-19 pandemic, contextualizing these aspects using Bourdieu’s conceptual tools — the following two-part research question was addressed: Firstly, how were students’ perceptions and experiences of their doctoral programs affected in the immediate response to the COVID-19 pandemic? And secondly, how can Bourdieu’s conceptual tools help us conceptualize students’ experiences? Semi-structured interviews were conducted with 18 doctoral students across various disciplines and departments at three research-intensive universities in one Canadian province. A fundamental aspect of this thesis was the application of Pierre Bourdieu’s conceptual tools of habitus, capital, and field, both in the design of interview questions and examination of the participant responses, to explore doctoral student experience both generally and with specific reference to experiences between March 2020 and the date of their interview, with the final interview occurring July 2021. The results suggested that previously described factors affecting socialization were exacerbated during this time. The expectations placed on students and the valued activities for socialization remained unchanged, but how students perceived those expectations and experienced those activities changed significantly. The research revealed that long-standing assumptions of doctoral study as leading to an academic faculty position are not only outdated but may be actively hindering socialization. This research advances that a new field of doctoral education has emerged due to pandemic adaptations, which has implications for the design of future doctoral programs.

Keywords: Bourdieu
Doctoral education
Inequity
Pandemic experience
Socialization
Advisor: Jones, Glen A