title: Optimization-Based Solutions for Planning and Control

title: Optimization-based Solutions to Optimal Operation under Uncertainty and Disturbance Rejection

contributor:
Mahalec, Vladimir
Mhaskar, Prashant
Chemical Engineering

subject:
Production planning under uncertainty
system identification
artificial neural network
time series prediction
Hybrid model
Distillation column flooding control

abstract:
Industrial automation systems normally consist of four different hierarchy levels: planning, scheduling, real-time optimization, and control. At the planning level, the goal is to compute an optimal production plan that minimizes the production cost while meeting process constraints. The planning model is typically formulated as a mixed integer nonlinear programming (MINLP), which is hard to solve to global optimality due to nonconvexity and large dimensionality attributes. Uncertainty in component qualities in gasoline blending due to measurement errors and variation in upstream processes may lead to off-specification products which require re-blending. Uncertainty in product demands may lead to a suboptimal solution and fail in capturing some potential profit due to shortage in products supply. While incorporating process uncertainties is essential to reducing the production cost and increasing profitability, it comes with the disadvantage of increasing the complexity of the MINLP planning model. The key contribution in the planning level is to employ the inventory pinch decomposition method to consider uncertainty in components qualities and products demands to reduce the production cost and increase profitability of the gasoline blend application.
At the control level, the goal is to ensure desired operation conditions by meeting process setpoints, ensure process safety, and avoid process failures. Model predictive control (MPC) is an advanced control strategy that utilizes a dynamic model of the process to predict future process dynamic behavior over a time horizon. The effectiveness of the MPC relies heavily on the availability of a reasonably accurate process model. The key contributions in the control level are: (1) investigate the use of different system identification methods for the purpose of developing a dynamic model for high-purity distillation column, which is a highly nonlinear process. (2) Develop a novel hybrid based MPC to improve the control of the column and achieve flooding-free control.

abstract: Dissertation

abstract: Doctor of Philosophy (PhD)

abstract:
The operation of a chemical process involves many decisions which are normally distributed into levels referred to as process automation hierarchy. The process automation hierarchy levels are planning, scheduling, real-time optimization, and control. This thesis addresses two of the levels in the process automation hierarchy, which are planning and control. At the planning level, the objective is to ensure optimal utilization of raw materials and equipment to reduce production cost. At the control level, the objective is to meet and follow process setpoints determined by the real-time optimization level.
The main goals of the thesis are: (1) develop an efficient algorithm to solve a large-scale planning problem that incorporates uncertainties in components qualities and products demands to reduce the production cost and maximize profit for gasoline blending application. (2) Develop a novel hybrid-based model predictive control to improve the control strategy of an industrial distillation column that faces flooding issues.


title: Nanocomposite Materials for High-Performance Electrochemical Supercapacitors

contributor:
Puri, Ishwar K.
Zhitomirsky, Igor
Materials Science and Engineering

subject: Advanced colloidal techniques for nanocomposite materials

subject: Supercapacitors

subject: Nanomaterials

abstract:
Electrochemical supercapacitors (ESs) are one of the most modern energy storage systems that offer a balance between power and energy densities in which the energy storage mechanisms could be an electrostatic double layer (EDLCs) and pseudocapacitive.
In this thesis, hybrid asymmetric supercapacitors have been developed to optimize the advantages for different types of (ESs) such as high conductivity, stability, fast charge-discharge, and relatively high performance. These developments include high active mass loading electrodes based on multiwall carbon nanotubes (MWCNTs) and transition metal oxides with incubation of low binder percentage and a high mass loading of 40 mg cm-2 that guarantees high electrochemical performance at a wide potential range for different electrodes, especially the cathodic one. Novel synthesis techniques and different multi-dispersants have been demonstrated; a conception colloidal fabrication method has been developed to improve the morphology/dispersion for composites of Fe3O4/MWCNTs (M-CNTs) and NiFe2O4/MWCNTs.
Firstly, an advanced synthesis method called particle extraction through a liquid-liquid interface (PELLI) has been developed to enhance the dispersion of the nanoparticles M-CNTs. Furthermore, palmitic acid (PA) has been used as a surfactant in the bottom-up (PELLI) to reduce the agglomeration of M-CNTs with high Gamma (𝛾𝛾) ratio (nanoparticles/MWCNTs).             Moreover, different synthesis methods have been developed in the presence of celestine blue dye (CB) as a co-dispersant with advanced electrostatic interaction and coagulation mechanism that ensured well- dispersed of (Fe3O4, NiFe2O4) coated (MWCNTs) at high mass loading.
Subsequently, more optimizations have been done to analyze the effect of different adsorption mechanisms by using other co-dispersant agents such as pyrocatechol violet (PV), azure A chloride (AA), and m-cresol purple (CP).
Finally, cyclic voltammetry, galvanic charge-discharge (GCD), electrochemical impedance spectroscopy (EIS), and cyclic stability have been done for the fabricated electrodes and devices in neutral aqueous electrolytes that showed a relevant electrochemical performance in a large potential range.

abstract: Thesis

abstract: Doctor of Philosophy (PhD)

abstract:
The rapid increase in human population has caused many economic problems, one of them the enormous energy consumption rate as compared to the limitations of sources available for clean and renewable energy sources.
Energy storage systems can be classified into different types, e.g., chemical, electrochemical, thermal, and mechanical systems. Popular electrochemical energy storage systems, such as batteries and capacitors, are used for many important daily applications but have difficulties while optimizing power and energy densities. Here, electrochemical supercapacitors (ESs) are considered potential energy storage systems that could balance power and energy densities with fast charge-discharge and a long lifetime.
The purpose of this research is to advance nanocomposite materials for electrochemical supercapacitor applications, where we use new colloidal approaches to fabricate high-performance electrochemical supercapacitor electrodes and devices. Our results reveal that these devices can have exceptional performance that facilitates new routes for their development.


title: The Governance of AI-based Information Technologies within Corporate Environments

contributor:
Detlor, Brian
Business Administration

subject:
Governance
Artificial Intelligence
AI Governance
IT Governance
Grounded Theory
Constructivist Grounded Theory
Board of Directors
AI Ethics

abstract:
Artificial Intelligence (AI) is making significant progress in recent times and is gaining a strong foothold in business. Currently, there is no generally accepted scholarly framework for the governance of AI-based information technologies within corporate environments. Boards of directors who have the responsibility of overseeing corporate operations need to know how best to govern AI technologies within their companies. In response, this dissertation aims to understand the key elements that can assist boards in the governance of AI-based information technologies. Further, it attempts to understand how AI governance elements dynamically interact within a holistic system.
As AI governance is a novel phenomenon, an exploratory investigation was conducted via a qualitative approach. Specifically, the study adopted a grounded theory methodology, within the constructivist paradigm, with the intent of generating theory instead of validating existing theory. Data collection included in-depth interviews with key experts in AI research, development, management, and governance processes in corporate and academic settings. Data were further supplemented with data received from conference presentations given by AI experts.
Findings from this dissertation elicited a theoretical model of AI governance that shows various AI governance areas and constituting elements, their dynamic interaction, as well as the impact of these elements in enhancing the organizational performance of AI-based projects and reducing the risks associated with those projects. This dissertation provides a scholarly contribution by comparing governance elements within the IT governance domain and the new AI governance domain. In addition to theoretical contributions, this study provides practical contributions for the benefit of the boards of directors. These include a holistic AI governance framework that pictorially represents twenty-two AI governance elements that boards can use to build their own custom AI governance frameworks. In addition, recommendations are provided to assist boards in starting or enhancing their AI governance journeys.

abstract: Thesis

abstract: Doctor of Philosophy (PhD)

abstract:
Artificial Intelligence (AI) refers to a set of technologies that seek to perform cognitive functions associated with human minds, such as learning, planning, and problem-solving. AI brings abundant opportunities as well as substantial risks. Major companies are trying to figure out how best to benefit from AI technologies. Boards of directors, with the responsibility of overseeing company operations, need to know how best to govern such technologies.
In response, this study was conducted to uncover key AI governance elements that can assist boards in the governance of AI. Data were collected through in-depth interviews with AI experts and by attending AI conference presentations.
Findings yield a theoretical model of AI governance that can assist scholars in enhancing their understanding of this emerging governance area. Findings also provide a holistic framework of AI governance that boards can use as a practical tool to enhance their effectiveness of the AI governance process.


title: Corneal Epithelial Cell Fate and Stratification Abnormalities Observed Following Conditional Deletion of AP-2B in the Neural Crest Cells of the Mouse

title: The Regulatory Role of AP-2B in Corneal Development

contributor:
West-Mays, Judith
Medical Sciences

abstract: The cornea is an anterior eye structure that is specialized to be transparent. It is comprised of an endothelial monolayer, avascular stroma and stratified epithelium. Anterior ocular tissues, including the corneal endothelium and stroma, develop from the periocular mesenchyme (POM), which derives from neural crest cells (NCCs). Activating Protein-2B (AP-2B) is highly expressed in the POM. Our lab has used a conditional knock- out model in which AP-2B is deleted in the NCCs, known as the AP-2B NCC KO mouse, to investigate the role of this protein in anterior segment development. In these mutants we previously observed a closed iridocorneal angle, as well as corneal abnormalities including an absent endothelium, stromal neovascularization, and failed epithelial stratification. The present thesis sought to investigate corneal defects in the AP-2B NCC KO mouse, and particularly the corneal epithelium given that it arises from the surface ectoderm rather than POM. PAS and IHC staining showed changes to epithelial cell fate and stratification. We observed that Keratin-12, a marker of differentiated corneal epithelium, was absent, and Keratin-15, a limbal and conjunctival marker, was expanded across the epithelium. Changes to the basement membrane and integrin expression were also evident. Given the non-NCC origin of the epithelium we hypothesize that abnormalities in the corneal epithelium of the AP-2B NCC KO mouse result from changes to regulatory signaling from the POM-derived stroma. Our investigation of Wnt/B-Catenin signaling suggested an important role for this pathway through its interactions with growth factor Bmp4, which is supressed in the mutant. Ultimately these results indicate that AP-2B expression in the POM is crucial for normal corneal epithelial cell fate and stratification.

abstract: Thesis

abstract: Master of Science (MSc)


title: The Effect of Direct Hot Press Forming on the Electrochemical Properties of Next Generation Zn-Coated Press Hardenable Steels

contributor:
McDermid, Joseph
Kish, Joseph
Materials Science and Engineering

subject:
Press Hardened Steels
Hot Stamping
Zinc Coatings
Galvanized Steel
Corrosion Resistance
Electrochemical Properties

abstract:
In recent years, the automotive industry has turned to press hardened steels (PHS) to improve passenger safety while enabling vehicle weight reduction. To form the complex shapes required for this purpose, they are often direct hot press formed. It is possible to provide corrosion resistance to these parts by galvanizing the PHS sheets prior to direct hot press forming (DHPF). However, the austenitization of the galvanized steel causes the Zn-based coating to transform into two intermetallic phases. These are iron-rich α-Fe(Zn) and zinc-rich Г-Fe3Zn10. The Г-Fe3Zn10 is liquid during traditional DHPF, and the applied stress can result in liquid metal embrittlement (LME). Recently, two new grades of PHS have been developed, which allow for DHPF at 600-700°C, below the Fe-Zn peritectic temperature at 782°C, thus avoiding LME. These prototype PHS grades are designated 2%Mn (0.2C-2Mn-0.25Si-0.005B (wt%)) and 2.5%Mn (0.2C-2.5Mn-0.25Si-0.005B (wt%)). The objective of this work is to determine the effect of DHPF on the ability of a Zn-based coating to provide robust cathodic protection to the two prototype PHS.
Galvanized panels of both the 2%Mn and 2.5%Mn steel were DHPF with a U-shape die at 700°C. The surface and cross-section of the coating were examined to determine the effects of DHPF on the coating surface. Die friction during DHPF resulted in die wiping on the wall of the part, leading to removal of surface Г-Fe3Zn10. In cross-section, coating cracks were present at the wall and corner of the U-shape part due to the deformation during DHPF. Potentiodynamic polarization scans were used to determine the corrosion potential of the coating, and this was used to calculate the driving force for cathodic protection using the difference in corrosion potential between the coating phases and the substrate. It was found that only Γ-Fe3Zn10 provided robust cathodic protection to both steel substrates, and the driving force for cathodic protection was lower for the coated DHPF 2.5%Mn steel. Galvanostatic scans were used to evaluate dissolution kinetics of coating phases. Robust cathodic protection was provided by the galvanized coating for austenitization times of 30 - 120 s for the 2%Mn substrate and 30 - 60 s for the 2.5%Mn substrate. The duration that robust cathodic protection was provided was shortest at the wall of the U-shape part.
This result was attributed to die wiping caused by DHPF, where the surface is smoothed by die friction. When there is less Г-Fe3Zn10 in the coating, such as at longer austenization times, surface Г-Fe3Zn10 was removed and an increased amount of α-Fe(Zn) is exposed, which does not provide robust cathodic protection. In addition, coating cracks form along α-Fe(Zn) grain boundaries after austenitization for 180 s on all examined regions of the U-shape part, allowing a greater surface area of the coating exposed to electrolyte, further increasing dissolution of the coating.

abstract: Thesis

abstract: Master of Applied Science (MASc)


title: Parallel Implementations of Parsimonious Gaussian Mixture Models and Extensions

contributor:
McNicholas, Paul
Mathematics and Statistics

abstract: Cluster analysis is the process of finding underlying group structures in a set of data. Model-based clustering has an array of swiftly growing literature surrounding this topic; however, a Gaussian mixture model has always been a prevalent model in model-based clustering literature. More specially, when dealing with high-dimensional data, the parsimonious Gaussian mixture model has shown great computational efficiency because the number of covariance parameters is linear with the number of variables for each model in the family. Parsimonious Gaussian mixture models generalize the mixture of factor analyzers model. For each group, the number of factors q has traditionally been held constant. An extension to the parsimonious Gaussian mixture model family is developed allowing q to be a vector of equal length to the number of components. Although the parsimonious Gaussian mixture model family has shown great computational potential, this new extension takes away from the aforementioned feat with rapidly growing parameter combinations to fit. Parallel computational techniques are explored throughout this thesis to improve computational runtime and allow the rapidly growing number of parameter combinations to be fit in a realistic time frame, especially in the case of high-dimensional data. The techniques are applied to real data to assess performance and computational efficiency.

abstract: Thesis

abstract: Doctor of Science  (PhD)


title: Hybrid Surrogate Model for Pressure and Temperature Prediction in a Data Center and Its Application

contributor:
Ishwar K. Puri, Rong Zheng
Mechanical Engineering

subject:
Data center
Data-driven models
Machine learning
Artificial neural network
Fault detection
Fault diagnosis

abstract:
One of the crucial challenges for Data Center (DC) operation is inefficient thermal management which leads to excessive energy waste. The information technology (IT) equipment and cooling systems of a DC are major contributors to power consumption. Additionally, failure of a DC cooling system leads to higher operating temperatures, causing critical electronic devices, such as servers, to fail which leads to significant economic loss. Improvements can be made in two ways, through (1) better design of a DC architecture and (2) optimization of the system for better heat transfer from hot servers.
Row-based cooling is a suitable DC configuration that reduces energy costs by improving airflow distribution. Here, the IT equipment is contained within an enclosure that includes a cooling unit which separates cold and back chambers to eliminate hot air recirculation and cold air bypass, both of which produce undesirable airflow distributions. Besides, due to scalability, ease of implementation, and operational cost, row-based systems have gained in popularity for DC computing applications. However, a general thermal model is required to predict spatiotemporal temperature changes inside the DC and properly apply appropriate strategies. As yet, only primitive tools have been developed that are time-consuming and provide unacceptable errors during extrapolative predictions. We address these deficiencies by developing a rapid, adaptive, and accurate hybrid model by combining a DDM and the thermofluid transport relations to predict temperatures in a DC. Our hybrid model has low interpolative prediction errors below 0.7 oC and extrapolative errors less than one half of black-box models. Additionally, by changing the studied DC configuration such as cooling unit fans and severs locations, there are a few zones with prediction error more than 2 oC.
Existing methods for cooling unit fault detection and diagnosis (FDD) are designed to successfully overcome individually occurring faults but have difficulty handling simultaneous faults. We apply a gray-box model involves a case study to detect and diagnose cooling unit fan and pump failure in a row-based DC cooling system. Fast detection of anomalous behavior saves energy and reduces operational costs by initiating remedial actions. Cooling unit fans and pumps are relatively low-reliability components, where the failure of one or more components can cause the entire system to overheat. Therefore, appropriate energy-saving strategies depend largely on the accuracy and timeliness of temperature prediction models. We used our gray-box model to produce thermal maps of the DC airspace for single as well as simultaneous failure conditions, which are fed as inputs for two different data-driven classifiers, CNN and RNN, to rapidly predict multiple simultaneous failures. Our FDD strategy can detect and diagnose multiple faults with accuracy as high as 100% while requiring relatively few simultaneous fault training data samples.

abstract: Thesis

abstract: Candidate in Philosophy


title: Exploiting Host Immunity for Anti-infective Discovery in Salmonella Typhimurium

title: ANTI-INFECTIVE DISCOVERY IN SALMONELLA TYPHIMURIUM

contributor:
Coombes, Brian K
Biochemistry and Biomedical Sciences

subject:
Salmonella
antibiotic discovery
innate immunity
bacterial pathogenesis

abstract: Salmonella enterica serovar Typhimurium (Salmonella) is a Gram-negative bacterial pathogen capable of causing both gastroenteritis and bacteraemia in human hosts. During infection, Salmonella invokes a complex network of virulence factors, regulatory systems, and metabolic pathways to promote immune evasion, sometimes demanding antibiotic treatment for resolution. Unfortunately, antibiotic resistance has reached critical levels in this and other pathogens, necessitating the discovery of new anti-infective targets and treatment options. Herein, we have sought to exploit the dynamic interactions between Salmonella and the host immune system to identify new, conditionally active anti-Salmonella therapies. In chapter 2, we aim to identify chemical compounds that are selectively antimicrobial against intracellular Salmonella, and discover that the anxiolytic drug metergoline inhibits Salmonella survival in cultured macrophages and systemically infected mice. In chapter 3, we screen for anti-virulence compounds that target regulatory signaling in Salmonella, and characterize the inhibitory activity of methyl-3,4-dephostatin, which perturbs SsrA/B and PmrB/A signaling and enhances sensitivity to colistin in vitro and in vivo. In chapter 4, we identify several host-directed compounds that modulate macrophage immunity and investigate their ability to attenuate a multidrug resistant Salmonella infection. Together, the work presented in this thesis demonstrates the potential for drug screening in infection-relevant conditions to identify new anti-infectives with non-traditional targets.

abstract: Thesis

abstract: Doctor of Philosophy (PhD)


title: Saving Flesh, Redeeming Body: Phenomenologies of Incarnation and Resurrection in the Thought of Michel Henry and Emmanuel Falque

contributor:
Kroeker, Travis
Religious Studies

subject: 'theological turn' in French Phenomenology

subject: Michel Henry

subject: Emmanuel Falque

subject: Flesh (Leib)/Body (Korper)

abstract: This thesis examines two French Catholic phenomenologists whose work engages in a serious manner with embodiment and theological phenomena. Michel Henry (1922-2002) and Emmanuel Falque (b. 1963) are both connected with the “theological turn” in French phenomenology. By using the tools of phenomenology, these thinkers take aim at the general phenomena of flesh and body and the religious phenomena of incarnation and resurrection. In this thesis I seek to uncover how their philosophical foundations inform their theological work, how they articulate a phenomenology of the body and the flesh in relation to incarnation and resurrection, and which thinker might provide a better account of these. I begin by providing a succinct overview of phenomenology—as articulated by Edmund Husserl and Martin Heidegger—paying attention to the phenomenological distinction between flesh (Leib) and body (Körper) that is vital to Henry’s and Falque’s analysis of incarnation and resurrection. I then lay out Dominique Janicaud’s critical labelling of the “theological turn” in French phenomenology in 1991, as well as responses by those who continue to knowingly operate under that label. I then critically examine the work of Henry and Falque, first by laying out their philosophical approach and method, and then by working through each of their theological trilogies, showing how the former influences the latter. My analysis reveals that both Henry and Falque have a similar understanding of a phenomenology of resurrection, in that it is a move from body to flesh. What my analysis also shows is that although Falque is critical of Henry’s position on the incarnation for neglecting materiality and completely understanding the human being as flesh, Falque’s critical response to it ironically mirrors it: by turning to material forces and drives to better describe the body in his recent work, Falque recapitulates Henry’s understanding of flesh.

abstract: Dissertation

abstract: Doctor of Philosophy (PhD)


title: Adoption of a Population Health Approach in Sexual Health Programs and Services within Public Health in Ontario: A Multi-phase Mixed Methods Study

contributor:
Valaitis, Ruta
Nursing

subject:
Public Health
Sexual Health
Population Health
Mixed-Methods

abstract: Since 2018, the Provincial Government of Ontario has begun transformation within the public health sector, which emphasizes the increased application of a population health approach. The goal of this transformation is to maximize the contribution of public health in improving the health of Ontarians by moving from a reactive to a proactive model that is focused on prevention. To support this transformation the standards that guide the programs and services provided through public health units underwent modernization in 2018. The emphasis of the modernized standards is about expanding the scope and reach of public health, by supporting the role of population health in the development and delivery of programs and services. This thesis used quantitative data to examine the extent that a population health approach was implemented in sexual health programs and services in public health units across Ontario. Qualitative data was gathered to explore public health managers’ and supervisors’ perceptions of barriers and facilitators that influenced the implementation of this approach. A mixed-methods study was used to determine if the qualitative findings helped our understanding of the quantitative results. This multi-phase mixed methods study involved four sequential phases. Phase 1 and 2 involved instrument development which included a literature review, input from experts, and testing; in phase 3 instrument administration was conducted; and phase 4 involved interviews with sexual health managers and supervisors. A qualitative descriptive approach was used as part of phases 1, 2, and in phase 4 for data collection and analysis using focus groups and semi-structured interviews with sexual health managers and supervisors delivering sexual health programs and services. The instrument was developed based on Health Canada’s Population Health Key Elements Template with multiple activities listed under each element and was administered in phase 3. Descriptive statistics were used to analyze this data. The Consolidated Framework for Implementation Research (CFIR) guided the development of the interviews for phase 4 and the qualitative analysis. Quantitative data showed that some population health elements were implemented more than others. For example, Address Determinants of Health and their Interactions was implemented by most health units while Employ Mechanisms for Public Involvement was implemented by a few. Qualitative data revealed that most factors influencing the implementation of a population health approach fit within CFIR’s domains of the inner and outer setting. For example Address Determinants of Health and Their Interactions and Focus on the Health of Populations were highly implemented by health units, due to factors such as organizational culture, and access to data. On the other hand, the elements Collaborate Across Sectors and Levels and Employ Mechanism for Public Involvement were less often implemented which were influenced by resources (e.g., human and financial) that were available to the health unit. This study fills an existing gap in the research and offers evidence of how to implement a population health approach within sexual health programs and services in public health.

abstract: Thesis

abstract: Candidate in Philosophy

abstract: Traditionally, sexual health programs and services provided by Ontario public health units have focused on providing services for individuals, such as clinic services. More recently, there has been a shift in public health to apply a population health approach, which focuses attention on addressing the broader social and economic influences on health. This is viewed as important to improving the health of communities and disadvantaged groups within those communities. It is not known to what extent this shift in the approach to sexual health services or programs is being implemented within Ontario public health units. Therefore, it is important to understand how public health units have moved towards a broader approach in sexual health and what challenges they have faced. This thesis examines how much sexual health programs and services have implemented a population health approach within sexual health programs and services in public health units. It also explores what helped or hindered this change. Some key population health activities (e.g., using evidence to plan programs, offering clinic services) have been implemented but not all (e.g., working with community partners, participating in primary research). An example of a barrier to implementation is having a lack of resources (human and financial). New knowledge from this study can support public health organizations to apply a broader population health approach in sexual health programs and services.


title: Type-Safe Modeling for Optimization

contributor:
Anand, Christopher
Kahl, Wolfram
Computing and Software

subject:
optimization
symbolic computing
haskell
mathematical optimization
type-safety
code generation
modeling
edsl
domain specific language
automatic differentiation

abstract: Mathematical optimization has many applications in operations research, image processing, and machine learning, demanding not only computational eﬀiciency but also convenience and correctness in constructing complex models. In this work, we introduce HashedExpression, an open-source algebraic modeling lan- guage (AML) that allows users to express unconstrained, box-constrained, and scalar-expressions-constrained optimization problems, aimed at embeddability, type-safety, and high-performance through symbolic transformation and code generation. Written in Haskell, a statically-typed, purely functional program- ming language, HashedExpression places a great emphasis on modeling correct- ness by providing users with a type-safe, correct-by-construction interface that uses Haskell type-level programming to express constraints on correctness which the compiler uses to flag many modelling errors as type errors (at compile time). We show how type-safety can be added in steps, first matching expressions’ shape and then associated physical units. The library implements symbolic ex- pressions with a hashed indexing scheme to implement common subexpression elimination (CSE). It abstracts away details of the underlying lookup table via monadic type class instances. We explain how using symbolic expressions with CSE enables performance-enhance transformations and automatic computation of derivatives without the issue of “expression swelling”. For high-performance purposes, we generate low-level C/C++ code for symbolic expressions and pro- vide bindings to open-source optimization solvers such as Ipopt or L-BFGS-B. We explain how this architecture lays the groundwork for future work on par- allelization including SIMDization and targetting multi-core CPUs and GPUs, and other hardware acceleration.

abstract: Thesis

abstract: Master of Science (MSc)


title: On the Sample Complexity of Privately Learning Gaussians and their Mixtures

contributor:
Ashtiani, Hassan
Computing and Software

subject: PAC learning, Learning Theory, Distribution Learning, Differential Privacy, Mixtures of Gaussians

abstract:
Multivariate Gaussians: We provide sample complexity upper bounds for semi-agnostically
learning multivariate Gaussians under the constraint of approximate differential
privacy. These are the first  finite sample upper bounds for general Gaussians
which do not impose restrictions on the parameters of the distribution. Our bounds
are near-optimal in the case when the covariance is known to be the identity, and
conjectured to be near-optimal in the general case. From a technical standpoint, we
provide analytic tools for arguing the existence of global "locally small" covers from
local covers of the space. These are exploited using modifications of recent techniques
for for differentially private hypothesis selection.
Mixtures of Gaussians: We consider the problem of learning mixtures of Gaussians
under the constraint of approximate differential privacy. We provide the first
sample complexity upper bounds for privately learning mixtures of unbounded axis-aligned
(or even unbounded univariate) Gaussians. To prove our results, we design
a new technique for privately learning mixture distributions. A class of distributions
F is said to be list-decodable if there is an algorithm that, given "heavily corrupted"
samples from a distribution f in F, outputs a list of distributions, H, such that one of the distributions in H approximates f. We show that if F is privately list-decodable then
we can privately learn mixtures of distributions in F. Finally, we show axis-aligned
Gaussian distributions are privately list-decodable, thereby proving mixtures of such
distributions are privately learnable.

abstract: Thesis

abstract: Master of Science (MSc)

abstract:
Is it possible to estimate an unknown probability distribution given random samples from it? This is a fundamental problem known as distribution learning (or density estimation) that has been studied by statisticians for decades, and in recent years has become a topic of interest for computer scientists. While distribution learning is a mature and well understood problem, in many cases the samples (or data) we observe may consist of sensitive information belonging to individuals and well-known solutions may inadvertently result in the leakage of private information.
In this thesis we study distribution learning under the assumption that the data is generated from high-dimensional Gaussians (or their mixtures) with the aim of understanding how many samples an algorithm needs before it can guarantee a good estimate. Furthermore, to protect against leakage of private information, we consider approaches that satisfy differential privacy — the gold standard for modern private data analysis.


title: Optimizing Body Mass Index Targets Using Genetics and Biomarkers

contributor:
Paré, Guillaume
Medical Sciences

subject:
Obesity
Body Mass Index
Mortality
Cancer
Cardiovascular Disease
Respiratory Disease
Type 2 Diabetes
Bioinformatics
Biostatistics
Genome-Wide Association Studies
Polygenic Risk Scores
Mendelian Randomization
Genetic Epidemiology
Population Health
Genetics
Genomics
Cox Proportional Hazards Regression

abstract: Introduction/Background: Guidelines from the World Health Organization currently recommend targeting a body mass index (BMI) between 18.5 and 24.9 kg/m2 based on the lowest risk of mortality observed in epidemiological studies. However, these recommendations are based on population observations and do not take into account potential inter-individual differences. We hypothesized that genetic and non-genetic differences in adiposity, anthropometric, and metabolic measures result in inter-individual variation in the optimal BMI. Methods: Genetic variants associated with BMI as well as related adiposity, anthropometric, and metabolic phenotypes (e.g. triglyceride (TG)) were combined into polygenic risk scores (PRS), cumulative risk scores derived from the weighted contributions of each variant. 387,692 participants in the UK Biobank were split by quantiles of PRS or clinical biomarkers such as C-reactive protein (CRP), and alanine aminotransferase (ALT). The BMI linked with the lowest risk of all-cause and cause-specific mortality outcomes (“nadir value”) was then compared across quantiles (“Cox meta-regression model”). Our results were replicated using the non-linear mendelian randomization (NLMR) model to assess causality. Results: The nadir value for the BMI–all-cause mortality relationship differed across percentiles of BMI PRS, suggesting inter-individual variation in optimal BMI based on genetics (p = 0.005). There was a difference of 1.90 kg/m2 in predicted optimal BMI between individuals in the top and bottom 5th BMI PRS percentile. Individuals having above and below median TG (p = 1.29×10-4), CRP (p = 7.92 × 10-5), and ALT (p = 2.70 × 10-8) levels differed in nadir for this relationship. There was no difference in the computed nadir between the Cox meta-regression or NLMR models (p = 0.102). Conclusions: The impact of BMI on mortality is heterogenous due to individual genetic and clinical biomarker level differences. Although we cannot confirm that are results are causal, genetics and clinical biomarkers have potential use for making more tailored BMI recommendations for patients.

abstract: Thesis

abstract: Master of Science (MSc)

abstract: The World Health Organization (WHO) recommends targeting a body mass index (BMI) between 18.5 - 24.9 kg/m2 for optimal health. However, this recommendation does not take into account individual differences in genetics or biology. Our project aimed to determine whether the optimal BMI, or the BMI associated with the lowest risk of mortality, varies due to genetic or biological variation. Analyses were conducted across 387,692 individuals. We divided participants into groups according to genetic risk for obesity or clinical biomarker profile. Our results show that the optimal BMI varies according to genetic or biomarker profile. WHO recommendations do not account for this variation, as the optimal BMI can fall under the normal 18.5 - 24.9 kg/m2 or overweight 25.0 – 29.0 kg/m2 WHO BMI categories depending on individual genetic or biomarker profile. Thus, there is potential for using genetic and/or biomarker profiles to make more precise BMI recommendations for patients.


title: On the KP-II Limit of Two-Dimensional FPU Lattices

contributor:
Pelinovsky, Dmitry
Mathematics and Statistics

subject:
Partial Differential Equations
Dynamical Systems
Analysis of PDE

abstract: We study a two-dimensional Fermi-Pasta-Ulam lattice in the long-amplitude, small-wavelength limit. The one-dimensional lattice has been thoroughly studied in this limit, where it has been established that the dynamics of the lattice is well-approximated by the Korteweg–De Vries (KdV) equation for timescales of the order ε^−3. Further it has been shown that solitary wave solutions of the FPU lattice in the one dimensional case are well approximated by solitary wave solutions of the KdV equation. A two-dimensional analogue of the KdV equation, the Kadomtsev–Petviashvili (KP-II) equation, is known to be a good approximation of certain two-dimensional FPU lattices for similar timescales, although no proof exists. In this thesis we present a rigorous justification that the KP-II equation is the long-amplitude, small-wavelength limit of a two-dimensional FPU model we introduce, analogous to the one-dimensional FPU system with quadratic nonlinearity. We also prove that the cubic KP-II equation is the limit of a model analogous to a one-dimensional FPU system with cubic nonlinearity. Further we study whether stability of line solitons in the KP-II equation extends to stability of one-dimensional FPU solitary waves in the two-dimensional lattices.

abstract: Thesis

abstract: Doctor of Philosophy (PhD)


title: Sulfur Biogeochemistry of Circumneutral Mining Wastewaters

title: IDENTIFICATION OF BIOGEOCHEMICAL INDICATORS TOWARDS ACID GENERATION IN MICROBIAL SULFUR CYCLING OF CIRCUMNEUTRAL MINING WASTEWATERS

title: New insights into Acidithiobacillus thiooxidans Sulfur Metabolism through Coupled Gene Expression, Solution Chemistry, Microscopy and Spectroscopy Analyses

title: Microbial Succession Signals the Initiation of Acidification in Mining Wastewaters

title: Microbial Sulfur Reaction Pathways from Circumneutral to Acidic pH on Thiosulfate and Tetrathionate in Mine Wastewater Enrichment Communities

contributor:
Warren, Lesley
Geography and Earth Sciences

subject: Sulfur Microbial Mining Biogeochemistry Water Wastewater

abstract:
Acid mine drainage (AMD) is a major issue for the mining industry and a global environmental concern. It is facilitated heavily by microbially catalyzed sulfur oxidation/ disproportionation reactions involving reduced sulfide components in mine wastes that result in the release of harmful acidity and metals. The microbial processes catalyzing sulfide mineral leaching of mine waste rock resulting in AMD have been previously studied. However, the initiation of AMD processes in mining wastewaters has not been well studied.  Post extraction, highly contaminated, mining wastewater is stored in retention (tailings) impoundments on site and treated to prevent impacts such as toxicity, contamination, and acidity prior to discharge to the receiving environment. Tailings, the waste stream generated through extraction of sulfide ores contains a variety of aqueous sulfur oxidation intermediate compounds (SOIs), such as polysulfides, elemental sulfur, and sulfur oxyanions, of the form SxOy2- termed “thiosalts” by the industry, which can also generate AMD. These wastewaters typically initially start off with circumneutral pH, but if thiosalts are present in high enough concentrations, microbial processes can cause net-acid generation leading to AMD. The microbial ecology and functionality of endemic tailings impoundment microbial assemblages in the “pre-net acid generating phase” (PNAG) of circumneutral mine wastewaters, as well as the associated sulfur species and reactions are not well understood. Thus, early-stage indicators that would offer mines proactive monitoring tools for improved tailings impoundment management are currently lacking.
In collaboration with our mining industry partners, who provided tailings impoundment water samples, this dissertation tackles these limitations. This dissertation aimed to identify important microbes and the SOI important to the initiation of AMD in PNAG tailings impoundment wastewaters and to determine potential markers (microbial and/or geochemical) associated with these initiating AMD processes that would inform the development of monitoring tools in mine water management. The objectives of this doctoral research were to constrain the S biogeochemistry of the PNAG phase by characterizing both expression levels of sulfur oxidation genes and sulfur speciation under experimental conditions designed to assess the roles of microbial community, SOI geochemistry and pH. Specifically three well constrained laboratory experiments determined: (1) gene expression by a pure culture of Acidithiobacillus thiooxidans and sulfur speciation with either thiosulfate or elemental sulfur added as the starting SOI substrate (Chapter 3);  (2) parent mining wastewater communities and associated sulfur oxidizing bacteria (SoxB) enrichments collected seasonally at two mines and grown at either pH 7-5 or pH 5-3 genetically (16S amplicon) (Chapter 4); and (3) geochemical sulfur pathways of three unique mine wastewater SoxB enrichment communities for six distinct simulated mine wastewater thiosulfate and/or tetrathionate treatments (Chapter 5).
Results presented in Chapter 3 expand the understanding of the reactions and enzymes involved in S0 and S2O32- metabolism by a pure strain sulfur oxidizing bacteria A. thiooxidans ATCC 19377 by developing the first models integrating gene expression, solution sulfur speciation, electron microscopy and spectroscopy. These novel results reveal that A. thiooxidans S2O32- metabolism involves the conversion of S2O32- to SO42-, S0 and S4O62-, mediated by the sulfur oxidase complex (Sox), tetrathionate hydrolase (TetH), sulfide quinone reductase (Sqr) and heterodisulfate reductase (Hdr) proteins. These same proteins, with the addition of rhodanese (Rhd), were identified to convert S0 to SO32-, S2O32- and polythionates in the A. thiooxidans S0 metabolism model. The results of this chapter advance understanding by revealing (1) the important role specifically of TetH in S2O32- metabolism; (2) Hdr proteins, rather than Sdo proteins, are likely associated with S0 oxidation; (3) that formation of intracellular S2O32- is a critical step in S0 metabolism, and (4) that recycling of internally generated SO32- occurs, through comproportionating reactions that result in S2O32-.
Results summarized in Chapter 4, identify that pH is the most important factor influencing which sulfur oxidizing bacteria (SoxB) occur irrespective of total S concentration of SOI substrate provided in enrichment experiments for two mines of different parent wastewater geochemistry. Mine 1 exhibited a lower total S and reactive soluble sulfur compounds (oxidation state < +VI) concentrations, and greater parent wastewater microbial community diversity with more unique sequences relative to Mine 2. All experimental SoxB enrichment experiment microbial communities evidenced a shift in dominance from primarily Alphaproteobacteria (28% - 77%) at circumneutral pH to Gammaproteobacteria (>80%) under moderately acidic pH values. A further pH dependent shift was observed at the genus level, from Halothiobacillus spp. dominating the circumneutral pH SoxB enrichments to Thiomonas spp. dominating the mildly acidic SoxB enrichments. These results provide some of the first putative biological indicators to improve prediction and management of sulfur processes and AMD onset within mining wastewaters.
Chapter 5 results importantly assess the influences of SOI chemistry and SoxB consortia identity on SOI cycling. Results identify that SOI substrate, whether S2O32- , S4O62-, or S2O32- + S4O62-,  was a more important determinant of microbial sulfur outcomes than the relative abundances of Halothiobacillus spp. and Thiomonas spp.. Further, three pH dependent phases of microbial sulfur processing were identified: Phase 1, pH > 5, dis/comproportionation reactions and acid consuming reactions were prevalent alongside oxidation, with S2O32- identified as an important indicator; Phase 2, pH 5 – 3, further dis/comproportionation occurred, with S0 emerging as an important indicator signalling the progression of the system towards net acid generation with S4O62- or S2O32- as the major S species present and; Phase 3, pH < 3, i.e. full AMD conditions, with dominant oxidation reactions resulting in SO42- and acid generation. Collectively, these results identify specific SOI species important at different pH stages in AMD initiation and development across different microbial SoxB, providing new indicators that may serve as signals associated with predictive tool development.
The integration of the novel results of this thesis revealed some of the first biologically informed possible indicators (bacterial and geochemical) that will enable improved management through proactive monitoring tools for AMD initiation in mining wastewaters.

abstract: Dissertation

abstract: Doctor of Science  (PhD)


title: The Characterization and Therapeutic Targeting of CD133 in Human Glioblastoma

contributor:
Singh, Sheila
Biochemistry and Biomedical Sciences

subject:
Cancer
Glioblastoma
BioID
Proteins
CAR-T
Immunotherapy
Allogeneic
T-cell
CD133
Brain tumor initiating cells
Cancer stem cells

abstract:
CD133, a pentaspan glycoprotein, has long been known to represent aggressive, stem-like populations across various human malignancies. While its expression correlates with numerous clinical outcomes including disease progression, metastasis, recurrence, and poor overall survival in numerous cancers, little is currently known about its function. In the brain cancer glioblastoma (GBM), CD133-expressing cells have previously been shown to initiate tumours, evade therapy and interestingly, self-renew, a key property of cancer stem cells. With an implied signalling role in driving self-renewal, we aim to elucidate the role of CD133 in glioblastoma. To understand the role of CD133, we aim to study its protein-protein interactions using the proximity-dependent labelling technique known as miniTurboID. By tagging proteins of interest with a promiscuous biotin ligase at both      protein termini, potential interactors can be biotinylated and identified by subsequent mass spectrometry. While miniTurboID has traditionally been performed by synthetic transgenes expressing the tagged proteins of interest in commercial cell lines, overexpression may not recapitulate its native function. Thus, using CRISPR technology, we aim to insert the miniTurboID ligase at both the N- and C-terminus of CD133 in patient-derived human GBM lines.
Although little is currently known about CD133 function, development of targeted therapies has presented a promising strategy in pre-clinical studies. In the Singh Lab, we previously developed a chimeric antigen receptor T-cell, or CAR-T, comprised of a T-cell expressing a synthetic receptor capable of recognizing a tumor-associated antigen and activating cytolytic-killing directed towards the target cell. Currently, CAR-T therapies are autologous, or patient-derived, in nature which may host a myriad of concerns including patient-specific qualitative and quantitative T-cell dysfunction, inconsistent generation of CAR products, and availability to rapidly progressing patients. To circumvent this concern, “off-the-shelf”, donor-derived or allogeneic CAR-T products may be generated for use in GBM patients. However, in addition to CAR integration, allogeneic products must be additionally modified to eradicate expression of the endogenous TCR, as this would induce a phenomenon known as graft versus host disease, in which healthy tissues are targeted.
Thus, in this thesis, we show gene editing potential in human GBMs to perform an endogenous genomic knock-in of miniTurboID. With the identification of interacting proteins, defining the subsequent functionality of CD133 may elucidate oncogenic cellular programs, and highlight common nodes of interaction within divergent cell signaling pathways.  To develop an allogeneic CAR-T product, we designed a two-step approach in which the CAR sequence was integrated into the TCR gene for simultaneous knock-out. We later show early pre-clinical efficacy in comparison to traditional autologous CAR-T in our patient-derived models of human GBM. Thus, by using CD133 as a centralizing concept in this thesis, we ultimately hope to develop our biological understanding of CD133, while testing the therapeutic development of a donor-derived CAR-T therapy.

abstract: Thesis

abstract: Master of Science (MSc)

abstract:
Glioblastoma (GBM) is one of the most common malignant brain tumors in adults. Despite an aggressive therapy regimen, almost all patients relapse 7-9 months post-diagnosis. Therapy failure and poor patient outcome may be attributed to a small population of cells known as glioblastoma stem cells, or GSCs, that are able to escape therapy and seed disease recurrence. GSCs are most notably identified by the cell surface protein CD133, which has previously been shown to associate with pro-tumor properties including treatment resistance, tumor growth, maintenance, progression and metastasis. While expression of CD133 in cancer has been heavily characterized, little is currently known about its function. One such avenue to understand its mechanism of action in cancer, and more particularly GBM, is to define its interactions with other proteins. Protein-protein interactions play a pivotal part as the backbone of signalling pathways that drive tumor development and growth. Therefore, defining and mapping the CD133 interaction network may help us understand how this protein governs regulation of GSCs, and ultimately, GBM progression.
While the biology of CD133 has yet to be elucidated, targeting CD133 on GSCs has presented a promising therapeutic strategy for patients with GBM. Previously in the Singh Lab, we developed an engineered T-cell therapy, known as a CAR-T, that can recognize CD133 to induce tumor cell death. While this showed success in our animal models of human GBM, other considerations must be addressed on its path to clinical development. As of current, CAR-T therapies are generated from T-cells taken from cancer patients. This hosts a myriad of concerns including the quality of patient T-cells, the time and cost to manufacture, and its availability for patients with rapidly progressing disease. To circumvent this issue, donor-derived CAR-T cells can be genetically engineered for safe usage in GBM patients as a readily available, “off-the-shelf” therapy.
To define the function of CD133, we have attempted to use a technique known as BioID, which tags the protein of interest with a smaller biotin ligase. This biotin ligase can subsequently tag proteins that come within the vicinity of CD133, that may later be identified by sequencing as potential interactors. As current use of BioID may not reliably mimic the interaction of CD133, we sought to genetically engineer human GBM lines with the BioID protein to more closely resemble tumor-relevant behaviours of CD133. To develop a donor-derived CAR-T therapy, we similarly used genetic engineering of T-cells to ensure specific targeting of tumor cells with CD133, while sparing healthy tissues. By using CD133 as a centralizing concept in this thesis, we ultimately hope to develop our biological understanding of CD133, while testing the therapeutic development of a donor-derived CAR-T therapy.


title: Cognitive influences on the crossed-hands deficit: An investigation of the dynamic nature of tactile processing

contributor:
Monteiro, Sandra
Psychology

subject: multisensory perception

abstract: Theories of tactile localization ability are based largely on the study of crossing effects, in which crossing the hands leads to a significant impairment in performance. This work has resulted in a rich literature that establishes tactile localization as inherently multisensory in nature. However, new work suggests that the studies used to date have made incorrect assumptions about the processes underlying performance (Maij et al., 2020) and the perceptual information that is considered (Badde et al., 2019). This thesis proposes the addition of a new parameter to existing theory that allows for these new results to be incorporated into the existing literature—specifically, the influence of cognitive factors on performance. The Introduction provides an overview of the current state of the literature, as well as the novel findings that seem to contradict it. I then propose a framework that highlights the malleability of tactile localization. The empirical work focuses on previously unexplored cognitive influences on tactile localization performance. In Chapter 2 I demonstrate that visual imagery influences performance, and importantly, that individual differences in visual imagery ability influence imagery’s effect on performance. In Chapter 3 I demonstrate that an individual’s attentional set influences performance, and that results previously thought to be due to changes in perceptual signal are likely due to changes in attentional focus. In Chapter 4 I highlight the biases in theory and measurement practice that have limited our understanding of tactile localization more broadly. The General Discussion then provides a detailed discussion about how to incorporate the findings of this thesis with existing literature, which requires a paradigm shift to how we view tactile localization.

abstract: Dissertation

abstract: Doctor of Philosophy (PhD)

abstract: Our ability to localize tactile stimuli is critical to successfully interact with our environment: if we feel something crawling on us, we need to eliminate this unwanted visitor as quickly and accurately as possible. A large body of evidence suggests that tactile localization requires perceptual signals beyond the somatotopic information about where on your skin you feel the tactile stimulus. Just think about how much easier it is to swat at a bug on your arm when you can see it as well as feel it. In this thesis I provide novel empirical evidence that cognitive factors also influence our ability to engage in tactile localization, including visual imagery and attention. I then propose an update to existing theory that can account for the influence of these cognitive factors, alongside the traditional approach to the integration of perceptual signals such as vision.


title: AGE AND SEX-RELATED NORMATIVE JOINT KINEMATIC AND KINETIC WALKING STRATEGIES IN A HEALTHY ADULT POPULATION

contributor:
Astephen Wilson, Janie
Biomedical Engineering

subject: Gait Healthy Kinematics Kinetics PCA

abstract: A comprehensive understanding of sex-specific gait patterns throughout the lifespan is important considering differences between males and females that can manifest biomechanically, and epidemiological evidence of female sex being a risk factor for some age-related pathologies such as osteoarthritis. This thesis aimed to, 1) characterize the differences in lower extremity joint kinematics and kinetics during gait between healthy women and men in different age groups, and 2) define salient inter-joint kinematic coordination strategies in healthy adult gait. Gait data from 154 asymptomatic adult participants was analyzed. Waveform principal component analysis (PCA) was applied to hip, knee and ankle joint angles and net external moments to extract major patterns of variability. Using a two-factor ANOVA, PC scores were examined for significant sex, age and interaction effects. A second series of PCA models were also developed with the PC scores of the kinematic features of each joint to model the inter-joint kinematic coordination. Demographics, anthropometrics and root mean square (RMS) of EMG waveforms for the high and low groups (85th and 15th percentile) of the retained kinematic strategies were statistically compared using a one-way ANOVA analysis. 13 PC features differed between healthy male and female gait patterns and were independent of age category. No PC features significantly differed between the age groups, and there was no significant sex by age interactions. Four different kinematic gait coordination strategies were identified, one with a significant sex-effect. Therefore, both analyses supported sex-differences in gait biomechanics and the importance of using sex-specific normative data in clinical gait studies. Additionally, the results suggest underlying kinematic differences within asymptomatic adults are concentrated in the patterns of their gait mechanics. Understanding how these strategies may link to susceptibility of injury and disease has important implications for patient-centered care and may provide important insight into age-related pathology and disease.

abstract: Thesis

abstract: Master of Applied Science (MASc)

abstract: Since variability in healthy walking gait strategies may provide evidence for early mobility decline, this thesis aimed to identify the primary walking gait strategies in a healthy adult population. This work is distinct from previous work in that it comprehensively investigates the influence of sex and age on walking gait features and simultaneously defines primary walking gait strategies in healthy adults. The results indicate an overall difference in walking strategy between healthy male and female adults but no significant differences with age, indicating that age-matching for gait studies using adult controls is not as critical as sex considerations. Additionally, the results suggest that gait differences within healthy adults are concentrated in the patterns of their gait mechanics. Understanding how these strategies may link to susceptibility of injury and disease may provide important insight into age-related mobility limitations and help improve mobility longevity in the aging population.


title: Proportion Manipulation of the Emotional Stroop

contributor:
Shedden, Judith M.
Psychology

subject: Emotional Stroop, Emotion, Cognition, Attention, Proportion Congruent

abstract: The Stroop effect is commonly demonstrated by measuring the time required to identify the colour of the ink (e.g. blue) in which a colour word (e.g. RED) is printed and illustrates a strong interference effect when the prepotent response of processing the word must be inhibited to respond correctly to the colour of the ink. Longer response latencies in colour-identification tasks involving emotional words versus neutral words, an effect dubbed the Emotional Stroop (ES), is often likened to the type of interference found in the Stroop task.  However, research has suggested that the effect of attentional modulation in Stroop tasks may be very different from the kind of emotional interference found when comparing reaction times to emotional versus neutral words (McKenna & Sharma, 2004).  Proportional congruency experiments using the Stroop task manipulate the amount of incongruity present in a block of trials (Logan & Zbrodoff, 1979), and demonstrate attentional modulation as a change in the size of the Stroop effect such that a greater amount of Stroop interference in a block is associated with a smaller Stroop effect.  Manipulating the proportion of interference trials may inform understanding of the differences between Stroop colour-word interference and emotional-word interference. In three experiments, we manipulated the proportion of emotional words in a mixed-list design to study the effect of proportion manipulation on the ES.  An enlarged ES was found in blocks of trials that contained more emotional interference; a finding contrary to attentional modulation seen for proportion manipulations of congruency in the Stroop task.  The differences between the ES effect and the Stroop effect are discussed, including the role of response incongruity as one possible reason for the discrepancy.

abstract: Thesis

abstract: Master of Science (MSc)

abstract: In three experiments, we investigated the role of proportionally more or less emotional interference on a colour naming task.  Emotional interference in the form of emotional words was compared to response interference where participants see mismatched and matched colour words (e.g.  the word ‘NIGHTMARE’ in green versus the word ‘BLUE’ in green).  We expected participants to be able to learn which blocks contained more emotional word content and to adapt in order to reduce this slow-down effect.  Instead, participants were especially slow on emotional words when they were in blocks that contained more emotional word interference.  The possible importance of emotional stimuli to participants over the task demands of naming the colour of a word, as compared to other kinds of interference, is discussed.


title: A community-engaged study to understand the HIV/STI risk of young South Asian sexual minority women in the Greater Toronto Area

contributor:
Greene, Saara
Health Research Methodology

subject:
Sexual health
Sexually transmitted infections (STI)
Human immunodeficiency virus (HIV)
South Asian
LGBTQ+
Sexual minority

abstract:
The human immunodeficiency virus/acquired immunodeficiency syndrome (HIV/AIDS) epidemic has surpassed forty years with many medical advancements in prevention and treatment. Often believed to be at negligible or low risk by society at large, sexual minority women have remained understudied regarding their risk of HIV and other sexually transmitted infections (STIs), leaving their sexual health inadequately understood and supported in healthcare and social services. The sexual health of young South Asian sexual minority women, who are multiply minoritized due to their intersecting identities, has been entirely overlooked. This qualitative study aimed to understand the knowledge, attitudes, and practices of young South Asian sexual minority women as it pertains to their HIV/STI risk. Barriers and facilitators to accessing community-based sexual health supports and services were also investigated.
A community-engaged approach was taken to develop this study in partnership with the Alliance for South Asian AIDS Prevention to investigate the HIV/STI risk context and sexual health needs of this group residing in the Greater Toronto Area. A maximum variation sampling strategy was used to recruit six young South Asian sexual minority women and semi-structured in-depth interviews were conducted to collect narrative data. Narrative analysis of the data found socio-cultural and structural influences which guide the HIV/STI risk context for this group. The participants illuminated an inadequate understanding of sexual health when engaging in sex with women, an overall low HIV/STI risk perception, barriers to adequate sexual healthcare and health promotion resources, and multiple minority stressors which impacted their access to safe sex. These findings have major implications for school-based sexual health education, medical training for healthcare practitioners, and sexual health support and services provided by community-based sexual health organizations in the Greater Toronto Area.

abstract: Thesis

abstract: Master of Public Health (MPH)


title: Investigating the Impact of Cigarette Smoke on Myeloid Cell Function and Kinetics During the Pathogenesis of Atherosclerosis and Aortic Aneurysm

title: MYELOID CELL FUNCTION AND KINETICS IN ARTERIAL DISEASE

contributor: Medical Sciences (Molecular Virology and Immunology Program)

subject:
Atherosclerosis
Aneurysm
Macrophage
Monocyte
Cigarette smoke
Immunology

abstract:
Rationale. Cigarette smoking is a well-known risk factor for cardiovascular disease, including arterial diseases such as atherosclerosis and abdominal aortic aneurysm. However, our understanding of how exposure to cigarette smoke impacts arterial disease pathogenesis is not well known. Consequently, this doctoral thesis focuses on understanding the development of atherosclerosis and aortic aneurysm in the context of exposure to cigarette smoke. In particular, since monocytes and macrophage are key immune cells implicated in arterial pathology, this work concentrates on understanding the impact of cigarette smoke exposure on the function and kinetics of monocytes and arterial macrophages.
Main Findings. Using a mouse model that combines two clinically relevant risk factors, hyperlipidemia and cigarette smoke, we showed that smoke exposure increases atherosclerosis and induces the spontaneous formation, progression, and rupture of abdominal aneurysms. We also provide experimental evidence that atherosclerosis strongly associates with regions of elastin damage and arterial dilation, suggesting atherogenesis may directly contribute to abdominal aneurysm formation.
Given the importance of macrophages in arterial disease, we investigated arterial macrophage heterogeneity and function following exposure to cigarette smoke. We report that cigarette smoke exposure increased the abundance of arterial monocytes and macrophages, whereas heterogeneity was primarily driven by hypercholesterolemia in aneurysmal tissue. Specifically, hypercholesterolemia is associated with an increase in macrophage populations with putative functions in inflammation and tissue remodelling including Trem2 foamy macrophages, inflammatory macrophages, and interferon-inducible macrophages. Moreover, we demonstrated that arterial macrophages play a critical role in elastin fragmentation within the arterial wall of smoke exposed mice.
Finally, we investigated the impact of cigarette smoke on kinetic factors that can contribute to arterial macrophage accumulation. We found that, despite increased development of arterial disease, exposure to cigarette smoke is associated with an overall suppression of circulating monocytes and pro-inflammatory cytokines. Using a parabiosis model, we show monocyte recruitment is significantly increased and is likely a key factor contributing to accumulation of arterial macrophages following exposure to cigarette smoke. We also present evidence suggesting that endothelial dysfunction, related to a loss of endothelial nitric oxide synthase, contributes to increased arterial monocyte recruitment following exposure to cigarette smoke.
Conclusions and Significance. Overall, we provide evidence that atherosclerosis likely contributes to abdominal aneurysm pathology in a model of cigarette smoke-induced aneurysm formation. We further provide insight into how tobacco smoke promotes arterial disease development through increased local accumulation of arterial macrophages despite suppressed monopoiesis and systemic inflammation. We identify monocyte recruitment and endothelial dysfunction as key factors contributing to the increased accumulation of arterial macrophages, with no overall differences in macrophage heterogeneity, following smoke exposure. In addition to providing insight into the increased risk of arterial disease following exposure to cigarette smoke, this study also provides experimental evidence that atherogenesis can contribute to abdominal aneurysm pathology. Overall, this thesis furthers our understanding of arterial disease pathogenesis and can provide a foundation for further mechanistic or therapeutic focused research aimed at reducing the burden of cardiovascular disease.

abstract: Thesis

abstract: Doctor of Philosophy (PhD)

abstract: Diseases that affect the heart and major blood vessels are one of the leading causes of illness and death worldwide. Atherosclerosis is one such disease caused by the buildup of fatty deposits in the walls of major blood vessels called arteries. This buildup can eventually block the artery and lead to a heart attack or stroke. Abdominal aortic aneurysms are another type of disease that affects arteries. In this case, the walls of the artery grow weak and begin to balloon out until the artery eventually breaks causing severe internal bleeding and death. One of the most important cells involved in the development of atherosclerosis and aneurysms is the macrophage, a type of white blood cell that is an important part of the immune system and found in diseased arteries. Although we know that cigarette smoking is one of the most significant risk factors for developing atherosclerosis and abdominal aneurysms, we do not fully understand why. Therefore, the goal of this thesis project was to investigate how cigarette smoke affects the development of arterial disease with a focus on understanding how it impacts the movement and function of macrophages. Using a mouse model, we found that the development of atherosclerosis and aneurysm are likely related, and also identified ways that exposure to cigarette smoke increases the numbers of macrophages in arteries. This work advances our understanding of how arterial diseases may be related and provides insight into how smoking can increase the risk of developing arterial disease.


title: Thermodynamic and Workload Optimization of Data Center Cooling Infrastructures

contributor:
Puri, Ishwar K.
Mechanical Engineering

subject:
Data center
Thermal management
Workload management
Waste heat recovery
Thermodynamic analysis
Multi-objective optimization

abstract: The ever-growing demand for cyber-physical infrastructures has significantly affected worldwide energy consumption and environmental sustainability over the past two decades. Although the average heat load of the computing infrastructures has increased, the supportive capacity of cooling infrastructures requires further improvement. Consequently, energy-efficient cooling architectures, real-time load management, and waste heat utilization strategies have gained attention in the data center (DC) industry. In this dissertation, essential aspects of cooling system modularization, workload management, and waste-heat utilization were addressed. At first, benefits of several legacy and modular DCs were assessed from the viewpoint of the first and second laws of thermodynamics. A computational fluid dynamics simulation-informed thermodynamic energy-exergy formulation captured equipment-level inefficiencies for various cooling architectures and scenarios. Furthermore, underlying reasons and possible strategies to reduce dominant exergy loss components were suggested. Subsequently, strategies to manage cooling parameters and IT workload were developed for the DCs with rack-based and row-based cooling systems. The goal of these management schemes was to fulfill either single or multiple objectives such as energy, exergy, and computing efficiencies. Thermal models coupled to optimization problems revealed the non-trivial tradeoffs across various objective functions and operation parameters. Furthermore, the scalability of the proposed approach for a larger DC was demonstrated. Finally, a waste heat management strategy was developed for new-age infrastructures containing both air- and liquid-cooled servers, one of the critical issues in the DC industry. Exhaust hot water from liquid-cooled servers was used to drive an adsorption chiller, which in turn produced chilled water required for the air-handler units of the air-cooled system. This strategy significantly reduced the energy consumption of existing compression chillers. Furthermore, economic and environmental assessments were performed to discuss the feasibility of this solution for the DC community. The work also investigated the potential tradeoffs between waste heat recovery and computing efficiencies.

abstract: Thesis

abstract: Doctor of Philosophy (PhD)


title: Applications of Deep Learning to Visual Content Processing and Analysis

contributor:
Chen, Jun
Electrical and Computer Engineering

subject: Video Super-Resolution

subject: Image Manipulation Detection and Localization

abstract:
The advancement of computer architecture and chip design has set the stage for the deep learning revolution by supplying enormous computational power. In general, deep learning is built upon neural networks that can be regarded as a universal approximator of any mathematical function. In contrast to model-based machine learning where the representative features are designed by human engineers, deep learning enables the automatic discovery of desirable feature representations based on a data-driven manner. In this thesis, the applications of deep learning to visual content processing and analysis are discussed.

For visual content processing, two novel approaches, named LCVSR and RawVSR, are proposed to address the common issues in the filed of Video Super-Resolution (VSR). In LCVSR, a new mechanism based on local dynamic filters via Locally Connected (LC) layers is proposed to implicitly estimate and compensate motions. It avoids the errors caused by the inaccurate explicit estimation of flow maps. Moreover, a global refinement network is proposed to exploit non-local correlations and enhance the spatial consistency of super-resolved frames. In RawVSR, the superiority of camera raw data (where the primitive radiance information is recorded) is harnessed to benefit the reconstruction of High-Resolution (HR) frames. The developed network is in line with the real imaging pipeline, where the super-resolution process serves as a pre-processing unit of ISP. Moreover, a Successive Deep Inference (SDI) module is designed in accordance with the architectural principle suggested by a canonical decomposition result for Hidden Markov Model (HMM) inference, and a reconstruction module is built with elaborately designed Attention based Residual Dense Blocks (ARDBs).

For visual content analysis, a new approach, named PSCC-Net, is proposed to detect and localize image manipulations. It consists of two paths: a top-down path that extracts the local and global features from an input image, and a bottom-up path that first distinguishes manipulated images from pristine ones via a detection head, and then localizes forged regions via a progressive mechanism, where manipulation masks are estimated from small scales to large ones, each serving as a prior of the next-scale estimation. Moreover, a Spatio-Channel Correlation Module (SCCM) is proposed to capture both spatial and channel-wise correlations among extracted features, enabling the network to cope with a wide range of manipulation attacks.

Extensive experiments validate that the proposed methods in this thesis have achieved the SOTA results and partially addressed the existing issues in previous works.

abstract: Dissertation

abstract: Doctor of Philosophy (PhD)


title: Electrically Conductive Membranes for Water and Wastewater Treatment: Their Surface Properties, Antifouling Mechanisms, and Applications

contributor:
de Lannoy, Charles-François
Chemical Engineering

subject:
Membrane
Water Treatment
Separation
Purification
Fouling
Responsive membrane
Membrane Stability
Electrochemistry
Bacterial Inactivation
Electrically Conductive

abstract:
Climate change, water stress, and rapid population growth have increased the need
to manage water resources through innovative sustainable technologies. Decentralized
systems such as membrane treatment trains have become increasingly important to provide
high volumes of potable water to millions of people. Pressure-driven membrane systems
have dominated separation processes due to their low cost, small footprint, ease of
operation, and high permeate quality. Conventionally, pressure-driven membranes are
classified into microfiltration (MF), ultrafiltration (UF), nanofiltration (NF), and reverse
osmosis (RO). MF and UF membranes operate under low pressure (< 7 bar, <~100 psi).
They can separate a variety of large particles such as bacteria, natural organic matter,
suspended solids, and colloids. In contrast, NF and RO membranes are more energy-intense
due to operating at high pressures (7 – 80 bar, ~100 – 1200 psi) and can remove small
molecules such as ions, pharmaceuticals, and heavy metals. Fouling is a primary challenge
with membranes that compromises the membrane performance, increases energy
consumption, and reduces the membrane lifetime. Many strategies are used to address
fouling, such as pre-treatment (pH adjustment, screening, coagulation), membrane
modification (chemical and morphological properties), and membrane cleaning (physical,
chemical). However, such strategies increase operational expenditures, produce waste
products that can impact the environment, and negatively impact membrane lifetimes.
Recently, electrically conductive membranes (ECMs) have been introduced to
address the challenges with traditional membranes. They contain conductive surfaces that
offer self-cleaning and antifouling properties across the surface in response to electrical potential externally applied to them. ECMs are advantageous as compared to traditional
membranes because (a) they are more effective in treating foulants as they target foulants
at the membrane/solvent interface, (b) they are more economical and environmentally
friendly as they reduce the need for chemical consumption, and (c) they can be responsive
to fouling conditions as their antifouling mechanisms can be easily manipulated by
changing the applied current type (positive, negative, direct current, alternating current) to
match the foulant.
ECMs have been formed from all categories of membranes (MF, UF, NF, MD, FO,
and RO) with a range of applications. Despite the remarkable progress in demonstrating
their excellent antifouling performance, there are many hurdles to overcome before they
can be commercialized. Two of these are (a) a fundamental understanding of their
underlying mechanisms, (b) surface materials that can withstand extreme chemical and
electrical conditions. In this work, we have comprehensively discussed antifouling
mechanisms with respect to surface polarization and elaborated on the impact of
electrically-induced mechanisms on four major fouling categories. i.e., biofouling, organic
fouling, mineral scaling, and oil wetting. In addition, we characterized surface properties
of a common electrically conductive composite membrane composed of carbon nanotubes
(CNTs) and polyvinyl alcohol (PVA). We then investigated the impact of cross-linkers in
CNT/PVA network on transmembrane flux, electrical conductivity, hydrophilicity, and
surface roughness. In addition, we proposed standard, practical, and straightforward
methodologies to detect and quantify the electrochemical, physical, and mechanical
stability of ECMs, using chronoamperometry and cyclic voltammetry, an evaluation of polymer leaching from membranes, and micro mechanical scratch testing, respectively. Our
methods can readily be extended to all membrane-based separation processes and different
membrane materials (carbonaceous materials, ceramics, metal-based, and polymers).
To demonstrate the antifouling properties of ECMs, we challenged ECMs with
mixed-bacterial cultures in a flow-through system. Although ECMs showed high rejection,
comparable flux, and excellent self-cleaning performance under application of electrical
potential, understanding the relationship between applied electrical currents and antifouling
mechanisms demands a well-controlled investigation. To this end, we quantified the impact
of electrochemically-induced acidic conditions, alkaline conditions, and H2O2
concentration on model bacteria, Escherichia Coli. We first quantified the electrochemical
potential of CNT-based ECMs in generating stressors such as protons, hydroxyl ions, and
H2O2, under a range of applied electrical currents (± 0-150 mA). Next, these individual
stressors with identical magnitude were imposed on E. Coli cells and biofilms in batch and
flow-through systems, respectively. This thesis guides researchers to understand the
underlying antifouling mechanisms associated with ECMs, how to match the mechanisms
to the application of ECMs, and offers benchmarks for making practical ECMs.

abstract: Thesis

abstract: Doctor of Philosophy (PhD)


title: On the stator design of an axial flux permanent magnet synchronous traction machine for aerospace applications

title: Stator Design of an AFPMSM for Aerospace Applications

contributor:
Emadi, Ali
Electrical and Computer Engineering

subject:
AFPMSM
Electrification
Aerospace
Electric Motor
Permanent Magnet Machine

abstract:
Aviation is one of the fastest growing methods of transportation, with passenger
volumes expected to triple in the next twenty-five years. It is also contributing
an ever increasing share of global emissions. One of the highly effective ways to
reduce emissions in aerospace is through electrification. This is already underway
with the development and adoption of More Electric Aircraft. A next step is the
development of hybrid propulsion, or all electric aircraft, with electric propulsion
systems. In order to achieve this goal, the power density of the electric drive is
of critical importance. Axial flux permanent magnet synchronous machines have
been identified as one the highest power density machine types suitable for these
electric drives.
In this thesis, an axial flux permanent magnet machine is developed for an
electric aircraft propulsion system. A review of electric machines in aerospace applications
is conducted, followed by an overview of the design and simulation of
axial flux machines, and a presentation of the machine under study. The primary
objective of this thesis is to improve the stator design of the axial flux machine by
reducing loss, weight, and volume. Magnetic materials are studied, and using grain
oriented silicone steel for the stator teeth is shown to improve torque production
of the machine. The wire, coil, and stator geometry are modified to reduce copper
loss. A tightly spaced coil, axially centered on the tooth, with high aspect ratio
wire and chamfered pole shoe is shown to reduce loss. Finally, a compact stator
winding is proposed with coil terminations on the inner diameter of the stator.
The proposed winding reduces the volume of the machine, as well as further reducing
copper loss due to less wire utilized. These actions significantly improve
the efficiency of the machine, while reducing weight and volume.

abstract: Thesis

abstract: Master of Applied Science (MASc)


title: Where not what: the role of spatial-motor processing in decision-making

contributor:
Bennett, Patrick
Sekuler, Allison
Psychology

subject:
eeg
psychology
neuroscience
electroencephalography
decision
reinforcement learning
choice
q-learning
motor
vision
basal ganglia
striatum
putamen
nucleus accumbens
cannabis
sex

abstract: Decision-making is comprised of an incredibly varied set of behaviours. However, all vertebrates tend to repeat previously rewarding actions and avoid those that have led to loss, behaviours known collectively as the win-stay, lose-shift strategy. This response strategy is supported by the sensorimotor striatum and nucleus accumbens, structures also implicated in spatial processing and the integration of sensory information in order to guide motor action. Therefore, choices may be represented as spatial-motor actions whose value is determined by the rewards and punishments associated with that action. In this dissertation I demonstrate that the location of choices relative to previous rewards and punishments, rather than their identities, determines their value. Chapters 2 and 4 demonstrate that the location of rewards and punishments drives future decisions to win-stay or lose-shift towards that location. Even when choices differ in colour or shape, choice value is determined by location, not visual identity. Chapter 3 compares decision-making when two, six, twelve, or eighteen choices are present, finding that the value of a win or loss is not tied to a single location, but is distributed throughout the choice environment. Finally, Chapter 5 provides anatomical support for the spatial-motor basis of choice. Specifically, win-stay responses are associated with greater oscillatory activity than win-shift responses in the motor cortex corresponding to the hand used to make a choice, whereas lose-shift responses are accompanied by greater activation of frontal systems compared to lose-stay responses. The win-stay and lose-shift behaviours activate structures known to project to different regions of the striatum. Overall, this dissertation provides behavioural evidence that choice location, not visual identity, determines choice value.

abstract: Thesis

abstract: Doctor of Philosophy (PhD)


title: Combating Climate Change with Green Central Banking: A Continuous-Time, Stock-Flow Consistent Approach

contributor:
Grasselli, Matheus
Bolker, Ben
Mathematics and Statistics

abstract: Climate change is one of the biggest threats humanity has ever confronted as it threatens both environmental and financial stability. Therefore, this thesis aims to add to the current literature surrounding stock-flow consistent continuous-time climate-economy models by exploring the role of innovative green debt instruments, such as green bonds and green loans, in aiding the private sectors' transition towards net-zero emissions. Moreover,  the increased financialization of the macroeconomic system opens up the opportunity to explore unique climate-related monetary policies such as green quantitative easing (QE) and a green interest rate and whether they alleviate short-term debt burdens without neglecting the long-term destabilizing effects of climate change.  Our key findings include: (i) providing the productive sector with a more efficient alternative to financing mitigation costs via green fixed-income resulted in increased debt levels that the central bank is ill-equipped to reduce; (ii) introducing green loans as a financial avenue towards renewable energies increased the effectiveness of monetary intervention as the green interest rate served its dual purpose of reducing short-term debt burdens, promoting a faster reduction of carbon emissions and minimizing the long-term destabilizing effects of climate change.

abstract: Thesis

abstract: Master of Science (MSc)


title: Design of a Time-to-Digital Converter and Multi-Time-Gated SPAD Arrays Towards Biomedical Imaging Applications

contributor:
Deen, M. Jamal
Electrical and Computer Engineering

subject: Time-to-Digital Converter, Single-Photon Avalanche Diode

abstract:
Digital silicon photomultipliers (dSiPMs) and single-photon avalanche diode (SPAD) imagers are optical sensing systems formed from the integration of time-to-digital converters (TDCs) with arrays of highly sensitive photodetectors known as SPADs. TDCs are high-performance mixed-signal circuits capable of timestamping events with picosecond level resolution. The digital operation mechanisms of SPADs allow for their outputs to be sent to TDCs, where the timestamps of individual photon detections are recorded. In recent years, time-resolved SPAD-based sensors have been a heavily studied topic due to their exceptional performance potential in biomedical imaging applications, including time-of-flight (ToF) positron emission tomography (PET), fluorescence lifetime imaging microscopy (FLIM), and diffuse optical tomography (DOT). This work targets the optimization of these sensors in low-cost standard complementary metal-oxide-semiconductor (CMOS) processes.
Firstly, this thesis provides a detailed review of the work accomplished in CMOS TDCs and their integration in SPAD-based sensors. Next, a feedback time amplification TDC was designed and tested in the TSMC 65 nm process that can achieve < 5 ps timing resolution in a very compact area of 0.016 mm2. The design is then described for a multi-time-gated array of p+/n-well SPADs that aims to mitigate SPAD dark noise while providing high-speed imaging by applying shifted gate windows simultaneously to an array of SPADs. The p+/n-well SPAD is first characterized in a passive quench configuration where it demonstrated a maximum dark count rate of 44.9 kHz, 18.1% peak PDP at 420 nm, and 0.82 ns timing jitter at a 0.7 V excess bias. While the current multi-time-gated prototype is not fully functional, the measurement results for individual pixels of the multi-time-gated array showed a 3.25 ns median gate window with a 2.2x 10-4 dark count probability for a 0.7 V excess bias, with 440 ps timing resolution and ~1 LSBrms timing jitter. Based on the results, limitations of the current design and sources for future improvement are then discussed in detail.

abstract: Thesis

abstract: Master of Applied Science (MASc)

abstract:
Medical imaging plays a key role in the diagnosis of diseases like cancer, and as such, the optimized performance of medical imaging systems is a large area of research. Recently, highly sensitive photodetectors known as single-photon avalanche diodes (SPADs) were integrated with high-performance timing circuits known as time-to-digital converters (TDCs) to form digital silicon photomultipliers (dSiPMs) and SPAD imagers. DSiPMs and SPAD imagers are capable of timestamping the detection of individual photons with a very high level of accuracy in order to generate biomedical images.
 This thesis focuses on the design and measurement of these sensors using standard fabrication processes with the aim of working towards high-performance medical imaging sensors at a low cost. Firstly, we review the results achieved in TDCs and SPAD-based sensors within the recent literature. Following that, we present the design and performance results of a custom-designed TDC that aims to achieve state-of-the-art performance within a small area in order to maintain low-cost and optimal integration with SPADs. Next, the design is described for an array of custom time-gated SPADs with integrated TDCs. Finally, the SPAD is characterized in two different configurations to identify sources of improvement for future design iterations.


title: Sensitivity and Stability: An Investigation of Stock-Flow Consistent Climate-Economic Models

contributor:
Grasselli, Matheus R.
Bolker, Benjamin M.
Mathematics and Statistics

subject: Economics, Stock-flow Consistent, Stability, Sensitivity, Climate Economics, Ecological Economics, Mathematical Economics, Jacobian Analysis, Differential Equations

abstract:
We aim to investigate the stability of various stock-flow consistent economic models,
and the potential causes for economic collapse therein. Through parameter sensitivity
analysis, we study models that feature a public sector, an active central bank, and
a household sector with independent consumption. Our final, most comprehensive
economic system combines all of the intricacies of each model, prominently featuring
a demand-driven economy that is stabilized by an expansionary monetary policy. In
addition, we incorporate a climate module for each economic system, and analyze
public sector intervention through carbon taxes and abatement subsidies. We find
that the most common feature of economic instability is a lack of demand, driven by
decreases in capital investment from firms, as well as a decline in household consumption. In order to maintain a stable growth path and prevent a permanent economic
contraction, we propose the implementations of an expansionary monetary policy,
increased public sector subsidies of abatement costs, and stricter carbon taxes.

abstract: Thesis

abstract: Master of Science (MSc)


title: Types in Algebraically Closed Valued Fields: A Defining Schema for Definable 1-Types

contributor:
Haskell, Deirdre
Mathematics

subject:
Model Theory
Valuation
Algebraically closed valued fields
Types
ACVF
Definable Schema

abstract: In this thesis we study the types of algebraically closed valued fields (ACVF). We prove the definable types of ACVF are residual and valuational and provide a defining schema for the definable types. We then conclude that all the types are invariant.

abstract: Thesis

abstract: Master of Science (MSc)


title: Existence and Stability of Periodic Waves in the Fractional Korteweg-de Vries Type Equations

contributor:
Pelinovsky, Dmitry
Mathematics

subject: Fractional Korteweg-de Vries equation, fractional modified Korteweg-de Vries equation, Petviashvili method, Green's function of fractional Laplacian operator, periodic travelling waves, existence, spectral stability, bifurcation, energy minimization

abstract:
This thesis is concerned with the existence and spectral stability of periodic
waves in the fractional Korteweg-de Vries (KdV) equation and the fractional
modified Korteweg-de Vries (mKdV) equation. We study the existence of
periodic travelling waves using various tools such as Green's function for fractional
Laplacian operator, Petviashvili fixed point method, and a new variational
characterization in which the periodic waves in fractional KdV and
fractional mKdV are realized as the constrained minimizers of the quadratic
part of the energy functional subject to fixed L3 and L4 norm respectively.
This new variational framework allows us to identify the existence region of
periodic travelling waves and to derive the criterion for spectral stability of
the periodic waves with respect to perturbations of the same period.

abstract: Thesis

abstract: Doctor of Philosophy (PhD)