title: Association of Arterial Stiffness and Changes in Brain Structure and Function in the UK Biobank

contributor:
Al-Khazraji, Baraa K.
Kinesiology

subject:
brain structure and function
grey matter
white matter
cognition
arterial stiffness
database
longitudinal
aging
healthy aging
vascular health
cerebrovascular disease

abstract: While evidence suggests there is indeed a relationship between arterial stiffness and changes in brain structure and function cross-sectionally, the longitudinal relationship between arterial stiffness and changes in brain structure and function is unclear. Also unclear is whether a regional effect of arterial stiffness on brain structure exists, or if the effect is homogenous across brain regions. Using a healthy cohort of the UK Biobank study (N = 1858, meanSD: 61  7 years), we investigated the longitudinal association between changes in arterial stiffness index (ASI) and brain structure (grey matter cortical thickness, whole brain grey matter volume, white matter hyperintensity volume) and function (cognitive performance in 6 tests) over 2.5  1 years. We also examined the association between baseline ASI and all structural and functional brain outcomes 8-11 years post-baseline (N = 630). Prior to post-hoc correction, we observed a significant effect of changes in ASI over 2.5  1 years on grey matter cortical thickness in 11 brain regions contributing to reductions between 0.0004-0.0024mm annually, but none of the 11 regions remained significant post-correction. Following correction there was also no effect of changes in ASI on whole brain grey matter volume (p = 0.76), white matter hyperintensity volume (p = 0.84), or cognitive performance in the domains of interest. Baseline ASI was not associated with regional grey matter cortical thickness, white matter hyperintensity volume, or cognitive function, but did have a significant negative association with whole brain grey matter volume 8.5  1.05 (p = 0.015) years later and 11  1.02 (p = 0.03) years later. Our findings suggest that taken with the effect of age, elevations in ASI may have an additive effect to accelerate changes in brain structure beyond the range that is to be expected as a part of normal aging. Our findings also suggest the relationship between ASI and reductions in whole brain grey matter volume may require long-term exposure to elevations in arterial stiffness in otherwise healthy older adults.

abstract: Thesis

abstract: Master of Science in Kinesiology

abstract: Arterial stiffening both accompanies the normal aging process and can progress due to acquired health conditions. As arteries begin to stiffen the ability to buffer high pressure blood flow is impaired and can put microvasculature at risk of damage. Microvascular damage in the brain can disrupt blood and subsequent oxygen delivery to the brain. When delivery to the brain does not meet the metabolic demand, changes in brain structure brain can occur. Changes in brain structure are associated with impaired brain function, as well as potentially accelerating the progression of neurological diseases. What remains unclear is whether arterial stiffness impacts brain structure differently across regions or all regions homogenously. The purpose of this thesis was to examine the relationship between arterial stiffness and structural and functional changes in the brain over time (objective 1: 2-5 years; objective 2: 8-11 years). Our observations suggest that the progression of arterial stiffness had an effect that was equivalent to approximately 30% of the rate of grey matter tissue loss associated with normal healthy aging (~0.25% reduction in grey matter per year). We found no effect of changes in arterial stiffness on the progression of total grey matter volume, white matter lesions or brain function. We did observe a significant negative relationship between arterial stiffness at baseline and total grey matter volume 8-11 years later. We found no relationship between baseline arterial stiffness and brain structure or function 8–11-years post-baseline. Taken with the effects of normal aging, the loss of tissue in select brain regions associated with changes in arterial stiffness may result in grey matter reductions beyond the range associated with what is considered healthy or normal aging. The association of arterial stiffness and total grey matter volume 8-11 years later suggests that changes in whole brain structure are the product of long-term exposure to arterial stiffness.


title: Developing Multivalent T Cell Engagers Towards Local Cancer Immunotherapies

contributor:
Wylie, Ryan
Chemistry

abstract: Immunotherapeutics that redirect the immune system toward cancerous cells have been extensively researched over the past decades. T cell engagers, such as BiTEs, are moving through clinical trials for many types of cancers. However, their small hydrodynamic radius and lack of Fc mediated recycling results in short plasma half-lives upon intravenous administration, which prevents the achievement of minimum effective concentrations in solid tumors. The local administration of T cell engagers provides a method to achieve therapeutic concentrations in tumor tissue. Herein, we developed a new T cell engager scaffold optimized for local delivery by increasing the size of the conjugate to extend tissue residence time and established a synthetic protocol to rapidly exchange the cancer targeting ligand towards addressing tumor heterogeneity. Redesigning T cell engagers for local administration utilized a full anti-CD3 antibody modified with short ethylene oxide ((EO)x) linkers for the grafting of cancer targeting peptides. Additionally, creating a scaffold using SPAAC-based conjugation allows for rapid fabrication of multivalent T cell engagers (MuTEs) for many cancers, utilizing an already existing library of cancer targeting peptides. Ideal grafting densities for short ethylene oxide ((EO)x) linkers were determined and tested in vitro in PSMA positive and HER2 positive cancer cell lines. In a local delivery in vitro model using embedded PSMA expressing spheroids, MuTEs resulted in greater cancer spheroid killing compared to traditional bispecific T cell engagers (BiTEs) over a 2-week period, with 2.5-fold greater cytotoxicity with MuTEs than BiTEs after 12 days. MuTEs have the potential to improve efficacy of T cell engagers for local delivery applications and offer a simplified synthetic pathway to develop a library to T cell engagers that target various cancer cell antigens.

abstract: Thesis

abstract: Master of Science (MSc)

abstract: Drugs that focus on engaging the patient’s immune system (immunotherapy) to target and kill cancerous cells offer a more effective and personalized path to cancer treatment. Many of these drugs have been designed for intravenous delivery and this has unfortunately created a short residence time in the body, lowering efficacy against solid tumors. High intravenous doses are needed to achieve efficacy, which often results in unwanted and potentially lethal toxicity. To improve this, re-designing the drugs for local delivery (i.e., intratumoral), would limit systemic toxicity while improving efficacy against solid tumors. Here, we develop a new scaffold for immunotherapeutics with improved retention at injection sites, in addition to being easy to fabricate, and tailor for different cancer targets.


title: Matching buying and selling of skills: An optimal skill selection problem in an online market

contributor:
Vaid, Sash
Zhou, Yun
Computational Engineering and Science

abstract:
The central function of the job market is to match the available job vacancies with job
candidates. For job candidates, it is critical for them to be equipped with the right skills for gaining competitive advantage. In this thesis, we obtain a dataset by scraping publicly available information from job postings for data science/analytics/engineering and similar positions on an online job marketplace. In the past few years, demand for those data-related jobs has been on the rise, and many job seekers change their career path to work in this area. For that purpose, it is important for them to understand the pattern of demand for skills in the labor market and to identify the best skills to acquire for maximizing the number of job vacancies they can apply for. We address these issues based on the real-life dataset. First, through exploratory data analyses,
we examine the correlation between the size of a company and the types of its required skills, as well as the correlation between the salary level offered by a company and the rating it receives on the online job marketplace. Then, we develop a linear integer programming model to formulate the skill selection problem to maximize the number of jobs covered by the selected skills. We show that the problem is NP-hard, and then solve it using both the commercial solver CPLEX and greedy heuristics.

abstract: Thesis

abstract: Master of Science (MSc)


title: Practical Solutions to Tracking Problems

subject:
tracking
bias estimation
information fusion

abstract:
Tracking systems are already encountered in everyday life in numerous applications, but
many algorithms from the existing literature rely on assumptions that do not always
hold in realistic scenarios, or can only be applied in niche circumstances. Therefor this
thesis is motivated to develop new approaches that relax assumptions and restrictions,
improve tracking performance, and are applicable in a broad range of scenarios. In
the area of terrain-aided tracking this an algorithm is proposed to track targets using
a Gaussian mixture measurement distribution to better represent multimodal distributions
that can arise due to terrain conditions. This allowed effective use in a wider
range of terrain conditions than existing approaches, which assume a unimodal Gaussian
measurement distribution. Next, the problem of estimating and compensating for
sensor biases is considered in the context of terrain-aided tracking. Existing approaches
to bias estimation cannot be easily reconciled with the nonlinear converted measurement
model applied in terrain-aided tracking. To address this, a novel efficient bias estimation
algorithm is proposed that can be applied to a wide range of measurement models
and operational scenarios, allowing for effective bias estimation and measurement compensation
to be performed in situations that cannot be handled by existing algorithms.
Finally, to address scenarios where converted measurement tracking is not possible or
desired, the problem of sensor motion compensation when tracking in pixel coordinates
is considered. Existing approaches compensate for sensor motion by transforming state
estimates between frames, but are only able to achieve partial transformation of the
state estimate and its covariance matrix. This thesis proposes a novel algorithm used to
transform the full state estimate and its covariance matrix, improving tracking performance
when tracking with a low frame rate and when tracking targets moving with a
nearly coordinated turn motion model. Each of the proposed algorithms are evaluated
in several simulated scenarios and compared against existing approaches and baselines
to demonstrate their efficacy.

abstract: Thesis

abstract: Doctor of Philosophy (PhD)


title: A Philosophy of Liberation

contributor:
Forbes, Allauren
Philosophy

subject: Philosophy Liberation Enrique Dussel

abstract: This thesis has two main goals. First, to examine Enrique Dussel’s philosophy of liberation and whether it can meaningfully contribute to intersectional analyses of race and gender. This is important due to problematic charges made against him in the past: that he only centers the voice of men in philosophies of liberation. As such, if his theories are to be taken seriously, they must be scrutinized to see if they are compatible with Black and queer liberation. Another, more pointed goal of the thesis, is to center the voices of marginalized philosophers in contemporary social and political philosophy. Essentially, I am responding to an ivory tower way of thinking about liberation. Ways of thinking about liberation are still lacking in an obvious sense: one way to explore liberation is through the works of prominent academics – however, this way of thinking about liberation is locked in the metaphorical ivory tower, away from the perspectives of folk on the ground. I intend to push social and political philosophy beyond this ivory tower gaze. This thesis is not an attempt to solve all problematics within philosophy of liberation, but it will provide a fruitful way for philosophers to think about liberation with intellectual tools from a marginalized philosopher and folk on the ground.

abstract: Thesis

abstract: Candidate in Philosophy

abstract: This thesis attempts to explain Black and queer liberation utilizing Enrique Dussel’s framework for a philosophy of liberation. By utilizing a framework for liberation created by a marginalized philosopher, I seek to contribute to political philosophy from a perspective beyond the hegemonic ivory tower. In line with Dussel’s work, I propose that if theories of liberation are to be meaningful, they ought to center the marginalized.


title: Characterizing gluten immunopathology in DR3-DQ2 transgenic mice sensitized to gluten in early life

title: Characterizing an early life model of gluten sensitivity

contributor: Medical Sciences (Division of Physiology/Pharmacology)

subject:
Celiac disease
Early life
Mouse model

abstract:
The gastrointestinal tract specializes in digestion and nutrient absorption via its mucosal surface. Through this large mucosal surface, interactions between the host and its environment, including food antigens and microbes, occur. Therefore, it is imperative that the gut discriminates between innocuous food components, and potential threats such as infections. On some occasions, this fine-tuned discrimination fails, leading to chronic inflammation. Celiac disease (CeD) is an autoimmune enteropathy triggered by gluten, the name given to a family of storage proteins (prolamins) that are naturally found in wheat, barley, and rye. To develop CeD, an individual must carry the susceptibility genes, the HLA-DQ2 and/or HLA-DQ8 alleles and consume gluten. However, this is not sufficient to cause disease, indicating that environmental co-factors are at play. Individuals homozygous for the HLA-DQ2 allele are at high risk to developing CeD in infancy. Currently, there is no existing transgenic animal model that addresses early life exposure to gluten, co-factors, and their effects on CeD development. Therefore, the overall goal of my thesis is to characterize a mouse model transgenic for the HLA-DQ2 allele with exposure to gluten in early life.
	I first studied the physiological and immunological responses to gluten at the time of solid food introduction using DR3-DQ2 transgenic mice. I determined that after sensitization to gluten before weaning, mice developed moderate enteropathy and some developed both anti-tissue transglutaminase 2 and anti-gliadin antibodies. I then evaluated the recovery of gluten immunopathology after gluten was removed for an extended period. After 6 months on gluten-free food, enteropathy and intestinal anti-gliadin and anti-TG2 antibody levels improved. These findings show pre-weaning sensitization of DR3-DQ2 transgenic mice reproduces key features of CeD, which can be used in future studies to assess environmental triggers and mechanisms that are of importance during early life.

abstract: Thesis

abstract: Master of Science in Medical Sciences (MSMS)

abstract: Celiac disease is the destruction of the upper gut lining by an immune reaction caused by gluten in people with genetic risk. Celiac patients cannot absorb nutrients well and have many complications. While it can occur at any age, its onset in children is associated with the HLA-DQ2 gene. Because not every child with the HLA-DQ2 gene will develop celiac disease, additional factors are suspected. Understanding these factors could help prevent disease, as the only treatment – a life-long gluten-free diet – is not always effective. Thus, an animal model that mimics early life disease onset would be useful. Therefore, I characterized signs of celiac disease in young mice with the HLA-DQ2 gene. I determined that gluten and a microbial toxin given in early life induces inflammation and positive celiac blood tests. This model constitutes a useful tool to test the role of environmental factors in celiac disease in early life.


title: Optimizing Covalent Immune Recruiter Antibody Labelling Kinetics with Sulfur Fluoride Exchange Chemistry

contributor:
Rullo, Anthony
Chemical Biology

subject: sulfur fluoride

abstract:
Covalent antibody recruiting molecules (cARMs) are synthetic chemical tools that direct
antibodies naturally present in human serum to tumor receptors leading to immune recognition
and elimination. cARMs have three general features: an antibody binding domain (ABD), an
antibody labelling domain (ALD), and a tumor binding domain. Proximal to the ABD, the ALD
contains an electrophilic group which is attacked by a nucleophilic amino acid residue on the
target antibody upon cARM binding. Previous cARMs use an acyl-imidazole (AL) ALD to
successfully covalently recruit anti-dinitrophenyl IgG validated via fluorescence SDS-PAGE,and
form immune complexes with PSMA+ HEK cells in ADCP flow experiments.1 Through MS
analysis, AL cARMs were demonstrated to target lysine-59 of antiDNP.1 Problematically, there
are several properties associated with AL chemistry that limit the therapeutic potential of
associated cARMs. These limitations include limited stability in vivo, single amino acid (lysine)
selectivity, and modest intramolecular protein labelling rates (10-5 s-1)1. To target novel antibody
residues and possibly improve the rate of antibody labelling, a second generation of cARMs has
been developed using sulfur fluoride exchange (SuFEx) chemistry as the ALD. Sulfur fluorides
have been broadly used in academic and industrial applications due to intrinsically high stability
and broad amino acid reactivity.2 SuFEx cARMs are hypothesized to have enhanced hydrolytic
stability compared to AL cARMs. This thesis explores the synthesis, stability, binding, and
labeling kinetics of SuFEx cARMs to advance cARM design and development for in vivo
applications. This research contributes collectively to the design and development of novel
therapeutics in chemical biology and immune-oncology research.

abstract: Thesis

abstract: Master of Science (MSc)


title: DESIGNING CELL- AND PROTEIN-BASED IN VITRO ASSAYS AS MODELS FOR FIBROTIC RESPONSES TO IMPLANTED HYDROGEL CAPSULES

title: ASSAY DESIGN FOR IMMUNOLOGICAL RESPONSES ON POLYMER CAPSULES

contributor:
Holloway, Alison
Medical Sciences

subject:
Foreign Body Responses
Fibrosis
Hydrogel Capsules
Cell Encapsulation
Biocompatibility
Diabetes Mellitus
Cell Therapy
Polymer Coatings

abstract: For a lay summary of the thesis presented in a 1-minute video format, visit the following link: https://www.youtube.com/watch?v=VhLzt_tEz-s

abstract: It is projected that, by 2030, 8% of all adults in the world will have diabetes mellitus and treatment will account for 10% of the total healthcare budget in many countries. Polymeric biomaterial research has led to the design of robust polymer hydrogel capsules to develop curative cell-based therapies for chronic disorders such as diabetes mellitus. Encapsulation of insulin-producing beta cells within synthetic, semi-permeable polymer hydrogels can avoid host immune rejection including fibrotic responses, and thus holds the promise of a long-term curative treatment of this disease. There is a paucity of literature regarding methods available for standardized in vitro screening of synthetic polymer hydrogel capsules to predict host responses in vivo. Thus, the focus of this thesis was to design in vitro assays able to screen for subsequent in vivo fibrotic responses. Two dimensional (‘2D’) (cell attachment to thin film hydrogel coatings) and three dimensional (‘3D’) (cell attachment and protein adsorption to hydrogel capsules) in vitro experiments were designed and tested in an iterative process to assess fibrotic responses to a diverse group of polymer hydrogels. Cell attachment assays included fibroblast (NIH 3T3) and macrophage (RAW 264.7) cell lines, and protein adsorption assays included proteins used to model fibrosis including fibrinogen and lysozyme. For some formulations, in vitro assays were compared with in vivo data on pericapsular cellular overgrowth (PCO) after being implanted into mice. A binomial logistic regression model was designed and validated to assess whether the ‘3D’ in vitro assays correlated with in vivo PCO responses. It was found that the RAW 264.7 cell attachment assay was significantly correlated with PCO outcomes in vivo, demonstrating for the first time a simple, cost-effective, and rapid in vitro cell-based approach to screen and select capsules with lower fibrotic potential to be further tested in animals.

abstract: Thesis

abstract: Master of Health Sciences (MSc)

abstract: In North America, one in eleven adults, or about 415 million people, have diabetes. It is projected that by 2030, around 8% of the world population will be diagnosed with this disease. A common form of treatment is through the frequent injection of insulin, but this is costly, requires multiple daily interventions, and cannot prevent regular excursions from the ideal blood glucose range. Cell-based therapies have a lot of promise in treating several chronic diseases including diabetes. Donor and stem-cell derived islets can be implanted into patients with type 1 diabetes and have been shown to function for over a year, albeit at the price of systematic immune suppression. Alternatively, cells that produce insulin can be placed inside immune-evasive capsules and implanted, potentially providing continuous blood glucose regulation without the need for daily insulin injections. However, this novel form of treatment is limited by the encapsulated cells’ survival once implanted. Cell survival can be affected by the body’s response to a foreign body (the capsule), causing deposition of protein or cells on the capsule surface which can limit the oxygen supply to cells in the capsule and the ability of insulin to leave the capsule in a timely fashion. The goal of this project is to develop assays to screen new capsule formulations. This can advance research by using capsules more readily accepted by the body, leading to a more promising and long-term treatment of diabetes.


title: Developmental Health Effects of Metformin and Guanylurea on Larval Zebrafish (Danio rerio)

title: Modest Developmental Effects in Larval Zebrafish (Danio rerio) Exposed to Metformin and Guanylurea

contributor:
Wilson, Joanna
Biology

subject:
Metformin
Guanylurea
Thigmotaxis
Development
Pharmaceutical
Aquatic Toxicology

abstract: Metformin is the most common first-line oral therapeutic agent used in the treatment of type-2 diabetes. Because of its widespread use, metformin has been increasingly detected in wastewater effluent. It is partially bio-transformed into guanylurea is subsequently released into aquatic environments. Since the literature concerning the effect of metformin and guanyl urea on early life stage of fish is scant, the aim of this research was to understand the potential influence of metformin and guanylurea on developmental, cardiometabolic and behavioral responses in zebrafish embryos, from the 4 cell stage (3 hours post fertilization, hpf) to first feed (120 hpf). To this end, embryos were exposed to environmentally relevant (0.4, 4, 40 μg·L−1) and supra-environmental (400 and 4000 μg·L−1) concentrations of the two chemicals. Metformin caused an increased mortality and spinal abnormalities in all concentrations compared to controls. and increased pericardial and yolk sac edema at the highest tested concentration. Metformin did not cause alterations in hatch or heart rate over the examined developmental stages. In addition, metformin did not cause alterations in general swimming, light-dark movement, startle response or thigmotaxis, irrespective of exposure concentration. Exposure to guanylurea over the same developmental stages caused a significant difference in mortality at 40 μg·L−1 only. Guanylurea did not cause alterations to any of the other tested endpoints. Our data suggests that metformin and guanylurea caused modest impacts to embryonic development of zebrafish at these concentrations.

abstract: Thesis

abstract: Master of Science (MSc)

abstract: Pharmaceuticals have been detected at the ng to µg L-1 range in aqueous environments for decades. These compounds are designed to be biologically active at low concentrations and can cause elicit adverse effects in non-target species.  Among the more recently detected compounds are the antihyperglycemic drug metformin and its biotransformation product (guanylurea), which have been the focus of few studies in fish. This thesis addresses multiple knowledge gaps by examining the potential impacts of metformin and guanylurea during the embryonic and early larval zebrafish period (3-120 hours post-fertilization). Exposure to metformin resulted in increased mortality and abnormalities. Guanylurea exposure increased mortality at one dose. We suggest that metformin and guanylurea cause modest effects in developing larval zebrafish.


title: THE AUTONOMY PARADOX IN PLATFORM WORK: A SOCIOMATERIAL PERSPECTIVE ON THE WORK OF INSTAGRAM CONTENT CREATORS

contributor:
Reid, Erin
Business

subject: Future of work, technology, identity, social media, personal branding, autonomy

abstract:
Organizational research about the autonomy paradox –the discrepancy between workers' increased level of autonomy in carrying out their work and their increased self-imposed constraints– is limited in two ways. First, our understanding of the role of technology in perpetuating the paradox of autonomy is limited to the influence of relatively simple features of technology (e.g., email devices' portability and ubiquity) in amplifying the expectations of near-constant availability. However, human-computer interaction research and practice increasingly show that design features of advanced technology, too, can play an important role in cultivating the culture of constant connectivity. Second, organizational research on the autonomy paradox has primarily focused on organizational shared expectations and has not examined social forces and cultural images that might contribute to the autonomy paradox in the individualized context of independent work. Thus, our understanding of socio-cultural processes that might contribute to the tension between autonomy and discipline in the context of platform work is incomplete. In this dissertation, I explore these issues through a review study and two empirical studies that draw on 50 semi-structured interviews with Instagram content creators, four years of participant observation, and a walkthrough analysis of the platform’s features.
The first study integrates the literature on sociomateriality, identity control, and autonomy paradox to explore the interconnected cultural, social, and material mechanisms that contribute to the autonomy paradox. I discuss how we can extend our understanding of autonomy in technology use by attending more explicitly to material features of digital technology and how mechanisms identified in organizational contexts can guide our understanding of platform workers’ autonomy. In so doing, this study maps out pathways for examining autonomy and discipline outside traditional organizational contexts.
The second paper examines how through a recurring process that I label identity baiting, evaluative metrics provided by digital platforms function as habit-forming identity affirming opportunities for desired identities which motivate work effort and sustain underpaid future oriented labor. By attending to workers’ desired identities rooted in cultural ideals of independent work, this study sheds light on entanglement of cultural ideals and technological features in shaping the tensions of autonomy and self-imposed constraints in platform work.
Finally, the third study explores how people navigate the tensions arising from the collocation of externally prescribed authenticity in the discourse of personal branding with the internal desire to be and feel authentic in contemporary work. I find that tensions arise from the consistency required to maintain a personal brand and the inconsistency of the authentic self over time. Further, practices induced by the rhetorical invocations of authenticity sometimes contradicted workers’ internal needs for a strategic balance between authentic and image management. This study shows that tensions of autonomy remain even if the external prescription demands individuality and authenticity rather conformity and collective assimilation.

abstract: Thesis

abstract: Candidate in Philosophy

abstract: How and why might workers (choose to) constrain their own autonomy in the context of platform work? Animated by this overarching research question, this thesis explores the tensions between autonomy and self-imposed constraints through three essays. The first essay integrates multiple streams of organizational research to portray the constellation of three structural forces (social norms, cultural discourses, and material features of technology) that interact with workers’ identity to shape the autonomy paradox. The second essay demonstrates how evaluative metrics provided by digital platforms function as habit-forming identity baits that control workers’ behavior and sustain underpaid labor. Finally, the third essay demonstrates how prescribed authenticity (e.g., the ethos of ‘just be yourself’) prevalent in the discourse of personal branding ironically constrain workers’ autonomy by turning the once protective fender of personal brand into a system of radical self-revelation. The second and third essays draw on an inductive qualitative inquiry of Instagram content creators.


title: Participation in Life Roles in People with Chronic Obstructive Pulmonary Disease

contributor:
Beauchamp, Marla K
Rehabilitation Science

subject:
social participation
psychometric properties
disability
lung disease
measurement
community engagement

abstract: For older adults and those with chronic disease, participation, or involvement in a life situation, is an important patient-centred aspect of health. Participation is commonly restricted in these individuals and is related to worse health outcomes and death. Despite its importance, in people with chronic obstructive pulmonary disease (COPD), participation is rarely assessed and targeted, perhaps due to the lack of validated outcome measures of participation in this population. The main objective of this thesis was to establish the psychometric properties of a measure of participation, the Late Life Disability Instrument (LLDI), in people with COPD and to explore participation restrictions in people with COPD. The first study showed that the LLDI demonstrated construct validity, internal consistency and test-retest reliability in people with COPD. In the second study, we found that people with COPD had worse scores on the LLDI than age-matched controls without respiratory disease, meaning that they participated less frequently and had greater limitations in participation. The third study established the validity and reliability of the LLDI’s computer adaptive test (LLDI-CAT) in people with COPD. And finally, the fourth study explored the responsiveness of the LLDI and LLDI-CAT in people with COPD who participated in pulmonary rehabilitation and provided estimates for the minimal important difference (MID) values on both measures. The findings from the four studies included in this thesis support the assessment of participation in people with COPD and the use of the LLDI and LLDI-CAT as tools for that purpose. The LLDI-limitation domain in particular appears responsive to changes that occur with pulmonary rehabilitation. Researchers and clinicians can use the MID values to interpret change scores on the LLDI and LLDI-CAT, increasing the clinical utility of these tools. These studies lay the groundwork for the development of interventions that target participation in people with COPD.

abstract: Thesis

abstract: Doctor of Philosophy (PhD)

abstract: Participation is involvement in a life situation or what people do in their homes and communities to fulfill their roles such as mother, brother, or friend. Many older adults develop difficulties in their participation due to health or environmental factors. These difficulties are linked with lower life satisfaction and even death. Older adults with lung disease have many participation difficulties. Although rehabilitation programs focus on improving physical function, for example walking, they do not specifically focus on participation. In order to do so, we need a valid and reliable measurement tool that can detect changes that happen with treatment. This thesis looked at the measurement properties of a participation tool, the Late Life Disability Instrument (LLDI), in people with chronic lung disease. The findings of this thesis show the importance of assessing participation in people with lung disease and can help healthcare providers use the LLDI with their patients.


title: N95 Respirators for a Diverse Population of Healthcare Workers: A Mixed-Methods, Pilot and Feasibility Study

contributor:
Fox-Robichaud, Alison
Health Research Methodology

abstract:
Introduction: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has had a global effect. While most of the transmission occurs through droplets produced by an infected individual, SARS-CoV-2 can be transmitted through virus-containing aerosols. The use of N95 respirators reduces the risk of infection; however, in the absence of standardized testing facilities, as well as supply chain and border challenges, Canadian healthcare workers (HCW) had to rely on United States (US) standards and respirators. In Canada, women represent 82% of HCWs, but most masks and respirators have been designed based on the anthropometrics of average men in the US and Europe. In the absence of a tight seal, female HCWs and any individual who does not fit the average male head and face, including individuals of different ethnicities, are at risk of contracting SARS-CoV-2 and other infectious diseases. Thus, there is a knowledge gap on the effects of gender and ethnicity on the fit of N95 respirators and the implications of poor fit on the physical and psychological well-being of HCWs.
Objectives: Primary: Feasibility of a multi-center mixed-method study, with a sample size of 100, 50% of participants self-identifying as non-white and having at least 1 characteristic of interest. Secondary: (1) Generate quantitative evidence on N95 fit using a PortaCount fit test, (2) describe participant-reported feelings on fit and breathability, and (3) evaluate the impacts of the pandemic and limited supply of N95’s on a HCWs overall physical and mental well-being.
Methods: This study was a mixed-method prospective pilot and feasibility study consisting of (1) a quantitative fit test and (2) a qualitative survey on N95 fit and comfort, as perceived by HCWs. The quantitative fit was assessed using a TSI PortaCount test and facial measurements of bizygomatic breadth and Menton-Sellion length. In parallel, a survey was administered to collect sociodemographic information, gauge the HCW's assessment of N95 fit and comfort, and assess the impact of PPE- related challenges on the physical and mental well-being of HCWs.
Analysis: Primary: The sample size, the proportion of various HCWs, and the number of participants who completed both aspects of the study were reported using descriptive statistics. Secondary: The results of the quantitative fit test, as well as the domains assessed in the survey using Likert scales, were summarized using descriptive statistics. Additional patient-reported assessments were collated and presented to provide a comprehensive reflection of HCW's feelings and attitudes on respirator fit and comfort.
Results: Following a study amendment to increase eligible sites, 37 of the 41 (90.2%) approached HCWs consented to participate, 36 of the 41 (97.3%) were successfully fitted, and all 36 HCWs completed the survey. Compared to the other included HCWs, female HCWs who identified as non-White had the lowest mean fit factor. Differences in Menton-sellion length and bizygomatic breadth were also observed between both male and female HCWs and between white and non-White HCWs. These results were corroborated by the survey data. On average, female HCWs reported lower scores in all measured domains, and the majority of HCWs reported physical discomfort, including headaches and itching, and negative impacts on their psychological well-being, as a result of fit, availability, and prolonged use of N95.
Conclusion: Despite the challenges of conducting research in the context of the COVID-19 pandemic, we have identified gender and ethnicity as key factors in the fit of N95 respirators and the negative implications of existing respirator designs on the physical and psychological well-being of HCWs. Future studies, including a larger mixed-method study, and respirator designs should consider the effects of gender and ethnicity to ensure that they reflect the diverse demographic of HCWs.

abstract: Thesis

abstract: Master of Science (MSc)


title: Driven flow of droplets and bubbles

contributor:
Dalnoki-Veress, Kari
Physics and Astronomy

subject:
Droplets
Bubbles
Fluid dynamics
Capillarity

abstract:
The work contained in this thesis presents four research manuscripts concerning the flow and motion of drops and bubbles in different geometries.
The first project explores the geometry of a totally wetting droplet on a conical fiber. A droplet on a fiber undergoes spontaneous motion toward the base of the fiber due to capillary forces, and viscous dissipation opposes the motion. In the first paper (Chapter 3), it was found that balancing the viscous shear force with the driving capillary force describes the motion of the droplet along the fiber. However, in nature, if fibers are coated with a liquid, there is rarely one droplet present; the second paper (Chapter 4) studies a conical fiber coated with multiple droplets. A liquid film coating a fiber will break up into droplets and it is found that the spacing of droplets depends on the shape of the fiber. The merging of droplets was studied and the dynamics well matches numerical simulations. The third paper (Chapter 5) studies the fluid film that a droplet will leave behind as it moves along the fiber. Using asymptotic matching to film deposition theory, this study found that the film thickness is affected by the curvature of the droplet. These studies show that the conical geometry and droplet curvature play an important role in droplet motion and film deposition.
The last project (Chapter 6) in this thesis concerns a chain of uniform sticky bubbles that rise through an aqueous bath. It is found that the chain of bubbles will buckle regularly as it moves through a liquid bath, much like a solid rope will buckle when impacting a surface. As the bubble chain rises through the bath, a compressive force develops due to an imbalance between the buoyancy of the chain and the viscous drag of the liquid surrounding it. Unlike solid ropes, there is no bending to stabilize the bubble chain and the regular buckling pattern is unex- pected. Using scaling arguments, it is found that the viscous bath both stabilizes the chain and introduces the compressive force. The geometry of the buckling can be described from a force balance between the compressive and stabilizing forces.
Drops and bubbles prove to be useful experimental tools to probe driven flow in different geometries and provide valuable insight into fundamental and applied physics systems.

abstract: Thesis

abstract: Doctor of Science  (PhD)


title: Seismic Fragility Assessment of As-built and Retrofitted Bridges using Fiber Reinforced Elastomeric Isolator

contributor:
Tait, Michael
Civil Engineering

subject:
Fiber Reinforced Elastomeric Isolator
Fragility Analysis
Incremental Dynamic Analysis
Bridge
Soil-Structure Interaction
Cold Temperature

abstract:
Highway bridges are considered to be one of the most susceptible constituents of transportation networks when they are subjected to severe natural hazards such as earthquakes and environmental exposures like subfreezing temperatures. To facilitate and enhance pre-hazard event mitigation and post-hazard emergency response strategies, probabilistic risk assessment methodologies have attracted increased attention, recently. Seismic fragility assessment is one of the probabilistic techniques which predicts the damage risk of the structure for a given hazard level. While fragility curves can be developed using different methods, such as expert-based, empirical, experimental, analytical, and hybrid, analytical fragility curves are perceived to be the most reliable and least biased technique. Seismic isolation systems are prevalently used in bridge structures to mitigate the damage risk of bridge components against natural hazards. However, the effectiveness of implementing recently emerged isolators such as Stable Unbonded Fiber Reinforced Elastomeric Isolators (SU-FREI) should be examined by developing analytical fragility curves of retrofitted bridges and quantifying the mitigation in the damage probability of different bridge components. In this regard, incorporating the Soil-Structure Interaction (SSI) is critical since the lateral response of bridges relies on the relative stiffness of bridge components, such as columns and isolators and the supporting soil. In addition, all bridge components are exposed to environmental stressors like subfreezing temperature that can alter the seismic response of bridges.
In the first phase of this thesis, a seismic fragility assessment is carried out on an existing multi-span continuous reinforced concrete bridge. Two bridge representations are developed to simulate the as-built bridge along with its retrofitted counterpart utilizing SU-FREI. An Incremental Dynamic Analysis (IDA) is conducted using 45 synthetic ground motion records developed for eastern Canada and damage limit states are applied to generate fragility curves and determine the probability of damage to different bridge components. Bridges are analyzed in longitudinal and transverse directions, independently, and component- and system-level fragility curves are developed. In the second phase, the previously generated bridge models are expanded to incorporate the SSI effects by introducing the pile groups under piers and abutments. Several interactions including deck-abutment, abutment-embankment, pile-soil, and pile-soil-pile interactions are considered. A significant challenge in this phase is the accurate simulation of the lateral and vertical behavior of pile groups since all pile groups comprised of closely-spaced vertical and battered piles. A ground motion suite consisting of 45 ground motions has been selected, which reflects the seismicity of the bridge site. IDA is conducted to monitor the seismic performance of the bridge from the elastic linear region up to collapse. Fragility curves, which serve as an important decision-support tool have been developed to identify the potential seismic risk of the bridge. In the third phase, a multi-hazard assessment is carried out by conditioning the previously developed bridge models (i.e. monolithic fixed-base, isolated fixed-base, monolithic with SSI, and isolated with SSI) to a range of room and subfreezing temperatures and applying a seismic excitation, simultaneously. The cold temperature behavior of the constitutive materials of different bridge components, namely, concrete, reinforcing steel, rubber, and the supporting soil are studied and reflected in the bridge models. IDA is performed and damage potential of different bridge components are quantified.
In summary, it is demonstrated that SU-FREI is a competing alternative for seismic isolation of bridges by offering potentially less manufacturing time and cost, lower weight, and easier installation which is an attractive feature for accelerated bridge construction applications. In all three phases, it is shown that the bridges which are isolated using SU-FREI have improved seismic performance in comparison with monolithic bridges by exhibiting lower probability of damage to the primary bridge components like columns and pile caps and transferring the damage to less important components such as abutments at which damage does not cause bridge closure. In addition, it is shown that seismic isolation using SU-FREI can effectively mitigate the seismic demand and damage potential of the constitutive components of a bridge supported by weak soil. While occurrence of seismic events along with an environmental stressor such as cold temperature can drastically jeopardize the functionality of a bridge supported by weak soil, it is demonstrated that seismic isolation using SU-FREI can significantly alleviate the probability of damage to bridge components.

abstract: Dissertation

abstract: Doctor of Philosophy (PhD)


title: THE ROLE OF MYELOID GSK3α/β IN ATHEROSCLEROSIS AND ATHEROSCLEROTIC REGRESSION

title: GSK3α/β IN ATHEROSCLEROSIS

contributor:
WERSTUCK, GEOFF
Chemical Biology

subject:
Atherosclerosis
Glycogen Synthase Kinase (GSK)-3α/β
Inflammation
Macrophages
Mice Model
Regression
Macrophage polarization
Macrophage function
Bone marrow derived macrophages
M1 and M2 macrophages

abstract:
Atherosclerosis is a major underlying cause of cardiovascular disease; however, the molecular mechanisms by which cardiovascular risk factors promote the development of atherosclerosis are poorly understood. Recent evidence from our laboratory suggests that endoplasmic reticulum (ER) stress signaling through glycogen synthase kinase (GSK)-3α/β is involved in the activation of pro-atherosclerotic processes. Previous studies from our lab show that myeloid-specific deletion of GSK3α attenuates the progression of atherosclerosis. However, the precise role(s) of GSK3α/β in atherosclerotic regression is not known. The primary goal of this thesis is to investigate the role(s) of GSK3α/β in lesional macrophages and atherosclerotic regression.
Initially, we have targeted the ER stress- GSK3α/β pathway by supplementing the drinking water of low-density lipoprotein receptor (Ldlr)-/- mice with the small molecules 4-phenylbutyric acid or valproate. The results suggest that ER stress or GSK3α/β inhibition can attenuate the growth of existing atherosclerotic lesions and appear to increase lesion stability. From this study it remains unclear whether these interventions can promote atherosclerotic regression.
Next, to investigate the role(s) of GSK3α/β in pro-atherogenic processes, bone marrow derived macrophages were isolated from myeloid-specific GSK3α- and/or GSK3β-deficient mice. The effects of GSK3α/β-deficiency on signaling pathways regulating atherogenic functions in macrophage were analyzed. This study revealed that GSK3α and GSK3β play distinct, and often opposing roles in macrophage polarization, inflammatory response, lipid accumulation and migration. Furthermore, both GSK3α and GSK3β appear to play redundant roles macrophage viability, proliferation, and metabolism.
Lastly, we investigated the effect of macrophage-specific deletion of GSK3α and/or GSK3β on atherosclerotic regression in Ldlr−/− mice.  A novel inducible knock out mouse model has been created in which GSK3α and/or GSK3β expression can be ablated by treating the mice with tamoxifen. These mice were fed a high fat diet to promote the development of atherosclerosis, and then mice were treated with tamoxifen to induce GSK3α/β deletion and switched to a chow diet for 12 weeks. All mice were sacrificed at 33 weeks of age and atherosclerotic plaques were analysed. Female mice with induced macrophage-specific GSK3α deficiency, but not GSK3β deficiency, showed regression of existing atherosclerotic lesions.
Together, these studies begin to delineate the specific roles of GSK3α and GSK3β in atherosclerotic regression. Furthermore, these data suggest that GSK3α inhibition could be an effective strategy for the treatment of atherosclerotic cardiovascular disease.

abstract: Thesis

abstract: Doctor of Philosophy (PhD)

abstract: Atherosclerosis is a disease involving the build-up of fatty plaques in the arteries, making them hard and narrow, which leads to damage in the heart, coronary or peripheral blood vessels. This can cause acute cardiovascular complications (heart attacks or stroke) and potentially death. We suspect that protein named glycogen synthase kinase (GSK)-3α/β is involved in the development of atherosclerosis. The purpose of this research is to see if we can treat atherosclerosis by blocking GSK3α/β’s functions. The findings of this study demonstrate that blocking GSK3α reduces inflammation, which is a primary cause of atherosclerosis. Furthermore, blocking GSK3α promotes the regression of atherosclerotic plaques and may lower the risk of cardiovascular disease. This knowledge could aid in the development of medications to treat atherosclerosis and reduce the number of individuals who die from heart attacks or strokes.


title: An Investigation of Graph Signal Processing Applications to Muscle BOLD and EMG

contributor:
Noseworthy, Michael
Biomedical Engineering

subject:
MRI
EMG
Graph Signal Processing
Muscle
Signal Processing
BioSignal

abstract:
Graph Signal Processing (GSP) has been used in the analysis of functional Magnetic Resonance Imaging(fMRI). As a holistic view of brain function and the connections between and within brain regions, by structuring data as node points
within the brain and modelling the edge connections between nodes. Many studies have used GSP with Blood Oxygenation Level Dependent (BOLD) imaging of
the brain and brain activation. Meanwhile, the methodology has seen little use in
muscle imaging. Similar to brain BOLD, muscle BOLD (mBOLD) also aims to
demonstrate muscle activation. Muscle BOLD depends on oxygenation, vascularization, fibre type, blood flow, and haemoglobin count. Nevertheless the mBOLD
signal still follows muscle activation closely. Electromyography (EMG) is another
modality for measuring muscle activation. Both mBOLD and EMG can be represented and analyzed with GSP. In order to better understand muscle activation
during contraction the proposed method focused on using GSP to model mBOLD
data both alone and jointly with EMG. Simultaneous mBOLD imaging and EMG
recording of the calf muscles was performed, creating a multimodal dataset. A
generalized filtering methodology was developed for the removal of the MRI gradient artifact in EMG sensors within the MR bore. The filtered data was then used
to generate a GSP model of the muscle, focusing on gastrocnemius, soleus, and
tibialis anterior muscles. The graph signals were constructed along two edge connection dimensions; coherence and fractility. For the standalone mBOLD graph signal models, the models’ goodness of fits were 1.3245 × 10-05 and 0.06466 for
coherence and fractility respectively. The multimodal models showed values of
2.3109 × -06 and 0.0014799. These results demonstrate the promise of modelling
muscle activation with GSP and its ability to incorporate multimodal data into
a singular model. These results set the stage for future investigations into using
GSP to represent muscle with mBOLD, EMG, and other biosignal modalities.

abstract: Thesis

abstract: Master of Applied Science (MASc)

abstract:
Magnetic Resonance Imaging(MRI) and electromyography (EMG) are techniques
used in the analysis of muscle, for detecting injury or deepening the understanding
of muscle function. Graph Signal Processing (GSP) is a methodology used to
represent data and the information flow between positions. While GSP has been
used in modelling the brain, applications to muscle are scarce. This work aimed
to model muscle activation using GSP methods, using both MRI and EMG data.
To do so, a method for being able to simultaneously record MRI and EMG data
was developed through hardware construction and the software implementation
of EMG signal filtering. The collected data were then used to construct multiple
GSP models based on the coherence and complexity of the signals, the goodness
of fit for each of the constructed models were then compared. In conclusion, it
is feasible to use GSP to model muscle activity with multimodal MRI and EMG
data. This shows promise for future investigations into the applications of GSP to
muscle research.


title: You Need to Calm Down – Emotional Epistemic Injustice

subject:
emotional epistemic injustice
epistemic injustice
emotions
epistemic violence

abstract:
Our emotions tell us that something is happening. When we experience or express an emotion, it is a reaction to a situation that is happening to or around us. This thesis project seeks to address the social and political inequalities that obstruct certain individuals and groups from being able to access and express the unique form of information that emotions provide. Emotional epistemic injustice concerns the ways in which our emotions can be used against us as an epistemic agent along gendered, racial, and ableist lines. Our capacity as a knower is influenced by social rules – and these same social rules dictate which kind of people can feel what, and in which situations. The first two chapters of this project are focused on identifying and analyzing two existing kinds of emotional epistemic injustice – misogynistic emotion reframing and emotional epistemic exploitation. By explicitly acknowledging these phenomena, I provide two new actionable hermeneutical resources, demonstrate the significance of our emotional experiences, and establish the need for a recategorization of emotions as a significant and unique source of information. The third and final chapter focuses on how this recategorization can be done. By specifically identifying socio-epistemically significant emotions, I argue for the recategorization
of emotions as an invitation to further investigation of our experiences within the context of existing social and political inequalities. Our emotions, both felt and expressed, have the potential to be powerful tools for real social and political change – and in order for them to have this impact, they must be embraced as their own unique and significant source of information.

abstract: Thesis

abstract: Master of Philosophy (MA)

abstract: The primary goal of this thesis project is to formally acknowledge the role of emotions in how we are able to acquire and contribute to knowledge construction, and successfully communicate said knowledge to others. Our gender, race, sexuality, socio-economic status, and ability all influence how we are allowed to express our emotions, and to what extent they will receive uptake from a given audience. These social feeling rules allow others to “justifiably” dismiss the information our emotions are signaling based on our social position, and results in the expression of emotion being used to undermine our reason-based testimony or communication as well. By identifying two specific ways in which this is already happening via misogynistic emotion reframing and emotional epistemic exploitation, as well as presenting a new way of categorizing our emotions as unique forms of information, I will demonstrate that the information our emotions provide can be a powerful tool for real social and political change.


title: Association between family contextual factors and child mental health during the third wave of the pandemic in Ontario: A cross-sectional analysis

contributor:
Gonzalez, Andrea
Health Research Methodology

subject:
child mental health
pandemic

abstract:
BACKGROUND: In Ontario, school closures due to the pandemic lasted 20 weeks at various times throughout March 2020 to June 2021; longer than any Canadian province or territory. School closures may have had a detrimental impact on school-aged children’s academic and psychological functioning.

OBJECTIVES: The objective was to examine the variability in child mental/emotional mental health in association with family factors (caregiver depression, caregiver anxiety, overreactive parenting, partner conflict, work-family conflict) and COVID-19 experiences (health-related stressors, resource-related stressors, positive experiences) among children from two-caregiver working households in Ontario

METHODS: Data came from the second iteration of the Ontario Parent Survey. The cross-sectional analysis (n=5787) was restricted to working adults, part of a two-caregiver household, with a child aged 4 to 17 years. Sample selection reflected the focus on work-family conflict and partner-conflict as important predictors of interest. Parent-reported, child negative affect and the negative impact on child functioning since the pandemic started, were the main outcomes of interest. Hierarchal linear regression models were constructed, and each group of predictors (covariates, family factors and COVID-19 experiences) were added in a step-wise fashion.  Findings were also stratified by child age and child gender. Missing data were handled via multiple imputations.

RESULTS: The final model accounted for 38.7% of the variability in negative affect scores, and 24.1% of the variability in COVID-19 negative impact scores. Negative affect was significantly associated with all family factors, resource-related COVID-19 stressors and positive COVID-19 experiences. The negative impact of COVID-19 on child functioning was significantly associated with all COVID-19 experiences and all family factors except overreactive parenting. Caregiver depression was the strongest predictor of worsening child mental/emotional health in all models.
Upon stratifying the analyses by child gender and age, partner-conflict was only a predictor of child mental/emotional health for females and child adolescents. Additionally, health-related COVID-19 stress was a significant predictor for males/other only and caregiver anxiety, overreactive parenting and health-related COVID-19 stressors were significant predictors for children, but not for adolescents.

CONCLUSIONS: The pandemic recovery period in Ontario should consist of significant efforts to provide preventative family-based programming and interventions to address the growing mental health crisis in children. Future research efforts should aim to explore the mechanisms by which family factors and COVID-19 specific experiences interact to produce various family dynamics and psychological presentations in children. Further research should also replicate the present study in marginalized and culturally diverse populations.

abstract: Thesis

abstract: Master of Public Health (MPH)

abstract: School closures in Ontario due to the COVID-19 pandemic may have impacted child development and wellbeing. The objective of this study was to examine the variability in child mental/emotional mental health scores, in association with family factors (caregiver depression, caregiver anxiety, overreactive parenting, partner conflict, work-family conflict) and COVID-19 experiences (health-related stressors, resource-related stressors, positive experiences). A cross-sectional study was conducted using the second iteration of the Ontario Parent Survey (n=5787). Parent-reported child negative affect and negative impact of COVID-19 on child functioning, as indicators of their mental health, were the outcomes of interest. The final model accounted for about 40% of the variability in negative affect scores, and about one-quarter of the variability in child functioning scores. Poor child mental/emotional health were associated with all family factors and COVID-19 experiences. Caregiver depression was the strongest predictor of worsening child mental/emotional health in all models. Consistent with other findings, this research can be used to support the provision of family-centered community mental health services.


title: A COMPARISON STUDY OF ACTUATORS AND PATH PLANNERS FOR INCREASING ROBOT SAFETY

contributor:
Bone, Gary
Mechanical Engineering

abstract:
Since robotic arms operating close to people are increasingly common, there is a need to better understand how they can be made safe, while still providing the required performance. The objective of this thesis is to study and compare various actuators and methods for improving robot safety.
It begins with a study of the safety and performance of a one degree of freedom (DOF) robotic arm whose parameters are mostly derived from the first joint of a 6-DOF industrial robot. The use of electric actuator (EA), series elastic actuator (SEA), pneumatic actuator (PA) and hybrid pneumatic electric actuator (HPEA) with model-based controllers to drive the robotic arm, and the collision between the arm and a human head, are simulated. The simulation employs dynamic models of the robot, actuators, and collision. The addition of a compliant covering to the arm, and the use of collision detection and reaction strategies are also studied. The performance and safety of the robot are quantified using root mean square error (RMSE) between the desired and actual joint angles in the trajectory, and maximum impact force (MIF), respectively. When compliant covering and the collision reaction strategy “withdrawing the arm (WTA)” are both applied, and the detection delay is 25 ms, the MIF reduced by 65% or more. Furthermore, when the desired closed-loop bandwidth is chosen individually, EA has the best performance, and SEA and PA are the safest. The HPEA is the best choice when considering both safety and performance.
Next, the relationship between the joint angles and the reflected mass of a 3-DOF planar robot is studied. A novel optimal path planner for reducing the reflected mass is then proposed. Simulation results show the planner can reduce the MIF by 75%, while still being able to bring the robot’s end-effector to the target position precisely.

abstract: Thesis

abstract: Master of Applied Science (MASc)

abstract: A robotic arm’s performance and safety are important factors in both industrial and non-industrial applications. In this thesis, performance is measured by how precisely the robot moves along a desired trajectory, and safety is measured by the maximum contact force that occurs in a simulated collision between the robot and a human head. The use of four different actuators to drive the joint of a robotic arm is simulated and the actuators’ performance and safety are discussed and compared. In addition, several methods to improve robot safety are proposed and simulated, and their advantages and disadvantages are discussed in detail. Finally, we propose and simulate a new path planner for a robotic arm with three motorized joints. The path planner is shown to be effective at improving safety and can be applied to more robots than existing methods.


title: The Application of Machine Learning to Event Classification in Radiation Detectors

contributor: Radiation Sciences (Medical Physics/Radiation Biology)

abstract:
Radiation physics is typically troubled by the accompanying of an interesting radiation field with an uninteresting one, presented as the
 signal and the background respectively. In some instances this background is a consequence of the signal of interest and its interaction with the world around it. These issues can be alleviated by clever experimental design that take advantage of the highly predictable way in which radiation interacts with the world. This predictability can lead to structured data which lends itself to data driven techniques which enable the identification of signal and background. One such technique that can exploit the structure of
radiation detection data is machine learning, which is the focus of this thesis. The first application was event selection onboard a satellite, called Advanced Energetic Pair Telescope (AdEPT), being developed for photon polarimetry. This application utilizes an adaptation of Google’s GoogLeNet which was trained off of simulated data produced in a simulation developed in Geant4. The performance of this adaptation, named GammaNet, was investigated and found to achieve the desired 99.99 % background rejection while maintaining signal sensitivity ranging from 0.1±0.1 % to 69±2 %. The signal sensitivity range depends on the down sampling rate implemented and the energy of the incident photon. The other application explored was neutron and photon separation in EJ-301
and EJ-309 neutron sensitive scintillators. This application, being experimental and not simulation based, required the implementation of an already existing classification routine to generate the labelled data necessary for machine learning. This was accomplished by utilizing Tail-To-Total (TTT) Pulse Shape Discrimination (PSD) and algorithmically fitting the resultant photon and neutron populations.
With this technique it was possible to correctly identify 75.3±0.5 % of the neutrons while removing 99.9999 % of the photons. The neutron identification rate was found to depend on the neutron source used, but was mostly accounted for when considering the differences in neutron energies for those sources. Both machine learning applications had the feature extraction technique, Gradient weighted Class Activation Mapping (Grad-CAM), applied to them. This technique produces a spatially correlated activation mapping for each class inside the neural network, identifying regions of the input that produced the greatest confidence to an output classification. The features observed from both applications aligned with the intuition of what comprises the dominant features of each signal and
background.

abstract: Thesis

abstract: Doctor of Philosophy (PhD)


title: Data-driven Supply Chain Monitoring and Optimization

contributor:
Swartz, Christopher L.E.
Huang, Kai
Computational Engineering and Science

subject:
Supply chain
Supply chain monitoring
Supply chain optimization
Data-driven methods
Machine learning
Reinforcement learning
Deep learning
Model predictive control

abstract:
In the era of Industry 4.0, conventional supply chains are undergoing a transformation into digital supply chains with the wide application of digital technologies such as big data, cloud computing, and Internet of Things. A digital supply chain is an intelligent and value-driven process that has superior features such as speed, flexibility, transparency, and real-time inventory monitoring and management. This concept is further included in the framework of Supply Chain 4.0, which emphasizes the connection between supply chain and Industry 4.0. In this context, data analytics for supply chain management presents a promising research opportunity. This thesis aims to investigate the use of data analytics in supply chain decision-making, including modelling, monitoring, and optimization.

First, this thesis investigates supply chain monitoring (SCMo) using data analytics. The goal of SCMo is to raise an alarm when abnormal supply chain events occur and identify the potential reason. We propose a framework of SCMo based on a data-driven method, principal component analysis (PCA). Within this framework, supply chain data such as inventory levels and customer demand are collected, and the normal operating conditions of a supply chain are characterized using PCA. Fault detection and diagnosis are implemented by examining the monitoring statistics and variable contributions. A supply chain simulation model is developed to carry out the case studies. The results show that dynamic PCA (DPCA) successfully detected abnormal behaviour of the supply chain, such as transportation delay, low production rate, and supply shortage. Moreover, the contribution plot is shown to be effective in interpreting the abnormality and identify the fault-related variables. The method of using data-driven methods for SCMo is named data-driven SCMo in this work.

Then, a further investigation of data-driven SCMo based on another statistical process monitoring method, canonical variate analysis (CVA), is conducted. CVA utilizes the state-space model of a system and determines the canonical states by maximizing the correlation between the combination of past system outputs and inputs and the combination of future outputs. A state-space model of supply chain is developed, which forms the basis of applying CVA to detect supply chain faults. The performance of CVA and PCA are assessed and compared in terms of dimensionality reduction, false alarm rate, missed detection rate, and detection delay. Case studies show that CVA identifies a smaller system order than PCA and achieves comparable performance to PCA in a lower-dimensional latent space.

Next, we investigate data-driven supply chain control under uncertainty with risk taken into account. The method under investigation is reinforcement learning (RL). Within the RL framework, an agent learns an optimal policy that maps the state to action during the process of interacting with the non-deterministic environment, such that a numerical reward is maximized. The current literature regarding supply chain control focuses on conventional RL that maximizes the expected return. However, this may be not the best option for risk-averse decision makers. In this work, we explore the use of safe RL, which takes into account the concept of risk in the learning process. Two safe RL algorithms, Q-hat-learning and Beta-pessimistic Q-learning, are investigated. Case studies are carried out based on the supply chain simulator developed using agent-based modelling. Results show that Q-learning has the best performance under normal scenarios, while safe RL algorithms perform better under abnormal scenarios and are more robust to changes in the environment. Moreover, we find that the benefits of safe RL are more pronounced in a closed-loop supply chain.

Finally, we investigate real-time supply chain optimization. The operational optimization problems for supply chains of realistic size are often large and complex, and solving them in real time can be challenging. This work aims to address the problem by using a deep learning-based model predictive control (MPC) technique. The MPC problem for supply chain operation is formulated based on the state space model of a supply chain, and the optimal state-input pairs are precomputed in the offline phase. Then, a deep neural network is built to map the state to input, which is then used in the online phase to reduce solution time. We propose an approach to implement the deep learning-based MPC method when there are delayed terms in the system, and a heuristic approach to feasibility recovery for mixed-integer MPC, with binary decision variables taken into account. Case studies show that compared with solving the nominal MPC problem online, deep learning-based MPC can provide near-optimal solution at a lower computational cost.

abstract: Thesis

abstract: Doctor of Philosophy (PhD)


title: Clinical, Cognitive, and Functional Effects of Ambulatory Electroconvulsive Therapy for Mixed Mood Disorders in a Naturalistic Setting

contributor:
McNeely, Heather
McKinnon, Margaret
Psychology

subject:
Mood Disorders
Electroconvulsive Therapy

abstract: Mood disorders (major depressive and bipolar spectrum disorders) have devastating effects on quality of life, with individuals who do not respond to pharmacological interventions showing a greater risk of impaired functioning, suicidality, and symptom relapse. Electroconvulsive therapy (ECT) has demonstrated consistent efficacy for treating mood disorders. However, there is a relative paucity of research examining the effectiveness of ECT in ambulatory settings and for patients who present with psychiatric comorbidities. This thesis sought to characterize the clinical, functional, and neuropsychological profile and outcomes (i.e., effectiveness and side effects) of a mixed mood disorders population undergoing ambulatory ECT with minimal research-related restrictions. In study one, we demonstrated that ambulatory ECT patients were clinically severe and complex, with frequent psychiatric multimorbidity, high symptom severity, and elevated functional impairment. ECT was effective at significantly reducing depressive symptoms in the short- and long-term; yet the rates of remission and response were lower than expected. In study two, we found that objective cognitive functioning remained largely unchanged following ECT, a finding that should be interpreted with caution given the use of a brief cognitive screening battery.  Interestingly, whereas patients who responded to ECT reported a lessening of subjective memory complaints, those who did not respond showed an increase in memory complaints post-ECT. In study 3, we sought to identify clinical and cognitive predictors of ECT outcomes using machine learning methods; we were unable to predict remission status, response status, or percent change in depressive symptoms in our sample. Overall, this thesis advances our understanding of the clinical, cognitive, and functional characteristics and outcomes of ambulatory ECT delivered under naturalistic conditions. This work highlights the importance of considering clinical comorbidities and cognitive functioning in ECT research and delivery and encourages a collaborative approach to clinical care aimed at enhancing treatment of patients with severe mental illness.

abstract: Dissertation

abstract: Doctor of Philosophy (PhD)

abstract: Severe mood disorders, such as depression and bipolar disorder, are associated with significant difficulties in social, occupational, and personal functioning. Electroconvulsive therapy (ECT) has shown consistent efficacy in reducing depressive symptoms, even in patients who did not respond to pharmacotherapy. This thesis advances our understanding of the therapeutic and adverse side effects of ECT in two understudied areas, ECT delivered in an outpatient setting and under naturalistic conditions with minimal research-related restrictions. We found that patients undergoing ECT were clinically complex and severe. ECT was effective at reducing depressive symptoms, but remission and response rates were lower than expected. Although, cognitive functioning, following ECT, remained largely unchanged on a brief screening assessment that may have underestimated cognitive changes, patients continued to report memory concerns. This thesis highlights the importance of considering patients’ full clinical and cognitive presentation in ECT research and delivery and encourages a collaborative approach to clinical care to better treat patients with severe mental illness.


title: Assessing the Feasibility of an Intervention for Adolescents and Parents Transitioning out of Pediatric Eating Disorder Services: A Mixed Methods Study

contributor:
Couturier, Jennifer
Health Research Methodology

subject:
eating disorders
mixed methods
feasibility
adolescent medicine
transition

abstract:
Background. The continuation of eating disorders from adolescence into adulthood often requires youth to undergo a healthcare transition from pediatric to adult eating disorder services. This transition is difficult, uncoordinated, and puts affected adolescents at an increased risk of relapse. Although transition barriers and recommendations have been identified, no known interventions exist to support youth and families transitioning to adult eating disorder services.
Methods. Over a three-month period, ten 17-year-old adolescents and their parents (n=9) completed up to five intervention components designed to prepare them for the transition out of pediatric eating disorder treatment in Hamilton, Ontario. A convergent parallel mixed methods design was used to assess intervention feasibility, the nature of transition, and other outcomes, with equal emphasis on the quantitative data, where measures were collected using a single arm pre-post design, and qualitative data, which comprised of written reflection entries and interview data, was informed by Qualitative Description, and analyzed using qualitative content analysis.
Results. Quantitative data pertaining to chosen feasibility indicators showed that adolescents and parents completed an average of 73% and 78% of expected components respectively, all within the three-month intervention period. Findings generated from the qualitative data indicated that participants found the intervention helpful, convenient, and easy to navigate. Of the seven adolescents interviewed, most were planning to transition to their family doctor, a private therapist, or both, while awaiting entry to specialized adult mental health care.
Conclusions. This intervention is acceptable, feasible, and highlights likely care pathways among transition-age youth with eating disorders. These findings support the continuation of this research using more rigorous study designs to examine the effectiveness of this intervention in larger and more diverse samples.

abstract: Thesis

abstract: Master of Science (MSc)

abstract: Most programs that specialize in treating children with eating disorders discharge patients when they turn 18. This sudden change often leaves youth without a solid plan to continue this care as an adult. Currently, no known interventions exist to help with this problem. In our study, ten adolescents and their parents completed five activities designed to improve their transition into adult mental health care. Interviews, reflections, and questionnaires were used to explore multiple outcomes, such as how many or the duration to complete these activities and where they plan to go for adult mental health treatment. Adolescents and parents completed most of the supports, described them as easy and helpful, and set up a plan for their future care. The activities in this study have the potential to improve this difficult transition for youth and families affected by eating disorders and should be further studied.


title: EVALUATING THE DWELLING SATISFACTION OF HOUSEHOLDS WITH DISABLED MEMBERS IN ONTARIO, CANADA

title: DWELLING SATISFACTION OF DISABLED HOUSEHOLDS IN ONTARIO

contributor:
Wilton, Robert
Newbold, Bruce
Geography

subject:
Housing Adaptations
Disability
Statistics Canada

abstract:
Housing stock remains overwhelmingly inaccessible to disabled people in Ontario. The primary method by which accessibility in the home is improved is through the installation of dwelling adaptations, which modify the layout or structure of parts of the home. Measuring the impact these adaptations have on various measures of a household’s dwelling satisfaction will help inform disability and housing legislation, two policy arenas that have seen renewed interest by both provincial and federal governments in recent years after decades of cutbacks to social supports for disabled people.

Using the 2018 Canadian Housing Survey dataset collected by Statistics Canada, Ontario households were split up into three groups; households that need no adaptations, households that need and have adaptations, and households that need but do not have adaptations. Demographic profiles of each group were built and compared. Various measures of dwelling satisfaction were also compared. This was done using descriptive statistics, t-tests, and logistic regression. All households that require a dwelling adaptation had much higher rates of Core Housing Need, rent subsidy, and lived in non-market rental housing compared to non-disabled households. Only half of households requiring adaptations had them. Households that had the adaptations they required had statistically comparable rates of dwelling satisfaction measures to non-disabled households. Households without the adaptations they required were more likely to be women-led, more likely to be led by a young adult, and were more likely to feel unsafe in their home. Adaptations were found to significantly alleviate dissatisfaction with the condition, safety, and accessibility of the home, but adapted households remain in more precarious and substandard housing compared to non-disabled households.

abstract: Thesis

abstract: Master of Arts (MA)

abstract:
For disabled households in Ontario, the most common method of making their home more accessible is through the installation of a dwelling adaptation. Measuring the positive impacts these adaptations have on dwelling satisfaction is important for informing federal and provincial housing and disability policy.

Using the 2018 Canadian Housing Survey dataset collected by Statistics Canada, various dwelling satisfaction measures of Ontario households were compared based on whether they needed an adaptation and whether they had one. This was done using descriptive statistics and logistic regression. Households that had the adaptations they needed were found to have comparable satisfaction rates to non-disabled households, but they were much more likely to be living in Core Housing Need. Households without the necessary adaptations were much more dissatisfied with their housing, felt unsafe in their home, and were more likely to be led by women and/or a younger adult compared to adapted households.


title: EXPLOITING BACTERIAL NUTRIENT STRESS IN THE TREATMENT OF ANTIBIOTIC-RESISTANT PATHOGENS

title: TARGETING NUTRIENT STRESS AS AN ANTIBIOTIC APPROACH

contributor:
Brown, Eric D
Biochemistry and Biomedical Sciences

subject:
antibiotic discovery
nutrient stress
biotin biosynthesis
bacterial pathogenesis

abstract: To revitalize the antibiotic pipeline, it is critical to identify and validate new antimicrobial targets. An uncharted area of antibiotic discovery can be explored by inhibiting nutrient biosynthesis. Herein, we investigate the potential of inhibiting biotin biosynthesis in monotherapy and combination therapy approaches to treat multidrug-resistant Gram-negative pathogens. In chapter 2, we validate biotin biosynthesis as a viable target for Gram-negative pathogens. Historically, biotin biosynthesis was overlooked as a target in Gram-negative pathogens as there was no observed fitness cost associated with its inhibition in standard mouse infection models. We discovered traditional mouse models do not accurately represent the biotin levels in humans. We developed an innovative mouse model to account for this discrepancy, validating biotin biosynthesis as an antimicrobial target in the presence of human-mimicking levels of biotin. Exploiting this sensitivity, we show that an inhibitor of biotin biosynthesis, MAC13772, is efficacious against Acinetobacter baumannii in a systemic murine infection model. In chapter 3, we continue to investigate the potential of targeting biotin biosynthesis in a combination therapy approach. In this work, we identify the ability of MAC13772 to synergize with colistin exclusively against colistin-resistant pathogens. The first committed step of fatty acid biosynthesis requires biotin as a cofactor; therefore, it is indirectly inhibited through the action of MAC13772. We propose that the inhibition of fatty acid biosynthesis leads to changes in membrane fluidity and phospholipid composition, restoring colistin sensitivity. The combination of a fatty acid biosynthesis inhibitor and colistin proved superior to either treatment alone against mcr-1 expressing Klebsiella pneumoniae and colistin-resistant Escherichia coli murine infection models. Together, these data suggest that biotin biosynthesis is a robust antibiotic target for further development in monotherapy and combination therapy approaches.

abstract: Thesis

abstract: Doctor of Philosophy (PhD)


title: Divergent Immunity Proteins Protect Against a Type VI Secretion System Effector Family Found in the Human Gut Microbiome

contributor:
Whitney, John C
Biochemistry and Biomedical Sciences

subject:
Type Six Secretion System (T6SS)
Human Gut Microbiota
Orphan Immunity
Bacterial Antagonism

abstract:
Antagonistic interactions between competing species of bacteria are an important driver of bacterial community composition in the human gut microbiota. Of particular significance is the role of the type six secretion system (T6SS), which many species of Gram-negative bacteria use to kill competitor bacteria in a contact-dependent manner. T6SSs are syringe-like nanomachines that function to deliver antibacterial toxins into susceptible competitors. Many bacteria present in the human gut microbiota possess an extremely potent T6SS that is capable of rapidly eradicating nearby bacteria. Remarkably, however, species of beneficial bacteria that coexist in the gut are often resistant to T6SS attack by their neighbours. This resistance is mediated by bacterial immunity proteins that block the activity of the antibacterial toxins delivered by the T6SS. Intriguingly, past studies have shown that the widespread T6SS-mediated competition in the gut has led to the acquisition of repertoires of immunity genes across different bacterial strains.

By examining available human gut metagenomes, I identified a putative immunity locus, named I2, in a species of gut bacteria. This locus is located downstream of its cognate T6SS toxin-encoding locus, E2, and I show when co-expressed with E2 in E. coli, it protects against E2 mediated-toxicity. Additionally, I show that four gut-derived I2 homologues bearing sequence identity levels to I2 ranging from 38% to 75% are equally capable of abrogating E2 toxicity. Using quantitative biophysical measurements, I also show that these I2 homologues physically bind E2 equally tightly pointing to the potential molecular mechanism of toxin neutralization. Lastly, through mutagenesis experiments, I found that the E2-I2 interaction is likely mediated by electrostatic forces between a small number of residues found in the interaction interface of the two proteins. Overall, these findings demonstrate that a human gut microbiome encoded type VI secretion system effector can be neutralized by divergent immunity proteins.

abstract: Thesis

abstract: Master of Science (MSc)


title: A Non Invasive Complex Representation of Muscle: A Description through BOLD Fractal Dimension, Phase Space, and Concurrent EMG Metrics

title: Understanding and Describing Muscle Complexity

subject: Skeletal Muscle, Muscle BOLD, EMG, Fractal Dimension, Phase Space

abstract: An investigation into the complex function of muscle using non-invasive imaging and novel analytical approaches.

abstract: The human body is inherently complex as seen through the structural organization of muscle in terms of its contractile subunit organization and scaling, innervation patterns, and vascular organization. However, the functional complexity of muscle such as its state of oxygenation, metabolism or blood-flow has been less well explored. Thus in an effort to improve our understanding of muscle, blood oxygenation level dependent (BOLD) magnetic resonance imaging of the lower leg, at rest and during a variety of weighted plantar-flexion paradigms, at 40% maximal voluntary contraction, was employed. Prior to experimentation, on 11 healthy subjects, an ergometer and electromyogram (EMG), suitable for use within the MRI, were constructed to allow for concurrent exercise and image acquisition. After collecting muscle BOLD data, four novel techniques were using to describe muscle function. The first technique used the fractal dimension, a measure of complexity, conveying the rate of variation of muscle blood flow at rest. This technique was able to determine differences between the muscles of lower leg, which have varying distributions of muscle fibre types based on function. The second exploratory technique was the use of the phase space, which provides insight into state/state-transitions of a system over time. The phase space representation of the BOLD signal provided novel insight into the muscle activation state. It demonstrated that muscle has more than the two blood flow states of reduced levels at rest and increased levels when exercising. The third technique involved using a signal saturation (SAT) region, proximal to the imaging region, to mitigate the arterial in-flow effects to more accurately represent muscle activation. By observing the correlation between the ideal reference and recorded signal, the acquisition with the arterial suppression improved the assessment of what regions in the muscle were active in the range borderline activation, which has the highest uncertainty. The final outlook on muscle behaviour involved using measures of fatigue from the collected EMG data to develop novel metrics of fatigue based on the BOLD signal. Concurrent BOLD and EMG of the anterior compartment of the lower leg during a plantar-flexion block design, demonstrated that the change in blood-flow between rest and contracted states is an excellent indicator of muscle fatigue. The primary outlook of this thesis is to provide a unique data collection and analytic framework to describe muscle behaviour, which was achieved using non-invasive measures with a complex outlook.

abstract: Thesis

abstract: Master of Applied Science (MASc)

abstract: The human body is complex, and an incredible amount of research has been done to better understand it. Specifically, muscle is built and works in a complex way to allow us to move and perform everyday tasks. There are many diseases that affect how a muscle works, which is why there is a need to describe muscle performance when it is healthy and unhealthy. In this research, muscle behaviour is explored by taking pictures of the leg. From these pictures the blood flow in the calf and shin was measured both when staying still and when performing exercise. Four new techniques were created to describe the blood flow in the leg. The first technique measured how complex the muscle activity is, while staying still. If blood-flow  changes a lot in a short amount of time, it is complex. This showed that the different components of muscle, either used for stamina or power, receive blood differently. The second technique used a different way of looking at the muscle to show that there are many different rates and amounts of blood-flow in the muscle. It revealed that muscle has more than the two blood flow options of 1) the normal level when resting and 2) the increased level when exercising. The third technique involved using an image filter to get a clean image of the muscle without the blood vessels affecting or misrepresenting the image. It was able to show what muscle regions were involved in exercise more accurately than before. The final technique involved measuring muscle electricity and blood flow at the same time, to find out when the muscle was exhausted. It demonstrated that muscle, when exhausted, showed larger changes in blood flow when going from resting to exercising. Overall, this research described how muscle performs in healthy individuals using new techniques. These techniques can now be used to compare healthy muscle to damaged/diseased muscle to determine how the muscle is recovering or to diagnose muscular disease.


title: EFFECTS OF PAUSING AND TASK RELEVANCE ON ONLINE LEARNING, A MEDIA MULTITASKING STUDY

contributor:
Kim, Joe
Psychology

abstract: The shift to online learning amidst the COVID-19 pandemic created a host of new challenges. One of which involves students’ rising media multitasking (MMT) habits while engaging online academic content. Few studies have investigated the learning implications of newer forms asynchronous video lecture consumption in context of concurrent and sequential MMT behaviours, such as social media scrolling. The current study investigates the impact of media-based secondary tasks under conditions of pausing (pause and no-pause) and task-relevance (relevant and non-relevant) on academic performance during a pre-recorded psychology lecture video. In addition, two separate Media Multitasking Indexes (MMI) assessing students’ general MMT and online lecture MMT habits were compared to each other, and to academic performance. To our surprise no-pause conditions did not demonstrate an academic performance cost when compared to both the control and pause conditions, and the relevant pause condition demonstrated an academic enhancement effect. However, academic performance costs were found for no-pause groups when academic performance was narrowed to content that overlapped with the six MMT distractors. Moderate positive correlations were revealed between both MMI’s. Both indexes demonstrated similar correlations to academic performance across all conditions. However, further speculation reveals the control scores may be deflated as a result of “non-compliant” participants paradoxically engaging in a higher volume of non-study-related MMT behaviours during the uninterrupted lecture than participants in the experimental conditions. Future online MMT studies need to enforce novel methods to prevent or control for non-study-related MMT during the study.

abstract: Thesis

abstract: Master of Science (MSc)

abstract: In context of students engaging in media multitasking behaviours during an online video lecture environment, it is unclear the extent to which pausing behaviours and task-relevance influences learning. To our surprise, findings demonstrate that engaging in distractive secondary media tasks simultaneously with the video lecture did not impair learning. On the other hand, a learning boost was found when the secondary media task is relevant to the lecture and tended to while the video lecture is paused. This suggests that multitasking, regardless of whether its unrelated to the lecture or done simultaneously to online lectures, does not impair learning. However, analysis reveals that these results may be skewed by participants engaging in non-study-related media multitasking.


title: Battery Pack Design of Cylindrical Lithium-Ion Cells and Modelling of Prismatic Lithium-Ion Battery Based on Characterization Tests

contributor:
Habibi, Saeid
Mechanical Engineering

subject:
Battery Pack Design
Battery Testing and Modelling

abstract:
With increasing research on lithium batteries, the technology of electric vehicles equipped with lithium battery packs as the main energy storage system has become more and more mature, and the design and testing of lithium ion battery packs are becoming extremely important. As the battery system becomes more complex, it is necessary to optimize its structural design and to monitor its dynamic performance accurately. This research considers two related topics. The first is the design of a battery submodule made up of cylindrical lithium cells. The objective of this design is to improve its energy density and optimize the heat dissipation performance according to the installation position and space constraints in Ford Focus EV 2013, and, produce a submodule prototype based on this design; The second objective is to derive and verify an equivalent circuit model for a prismatic lithium battery cell of high energy capacity based on experimental results.
In terms of mechanical structure, the basic structure of a battery pack is determined by the desired performance as well as cell characteristics. In this research, the Samsung 35E 18650 cylindrical cells are chosen. 20 battery cells are connected in parallel to form a battery submodule, and 13 battery submodules are connected in series to form a battery pack. The battery pack design process mainly includes positioning and connection of battery cells, heat dissipation mechanism, cabling and inside the pack. The above considerations were applied to prototype battery submodule with an energy density of 216.87 Wh/kg. Some key considerations in the design of the battery pack include checking the conductivity and the welding connection.
 Chemistry of lithium-ion batteries are constantly evolving with industrial demands which call for higher energy storage capacity. Therefore, this research selected a new high-capacity prismatic cell to establish an equivalent circuit model using characterization and experiments, followed by verification. A 280 Ah Lithium Iron Phosphate (LFP) prismatic battery cell was selected and characterized by testing under various operating conditions for validation, the Urban Dynamometer Driving Schedule (UDDS) was used.

abstract: Thesis

abstract: Master of Applied Science (MASc)

abstract: This thesis introduces how to design a battery pack using cylindrical battery cells, also shows how to conduct characterization tests and build a equivalent circuit battery model.