VictorJuiz/thesis huggingface dataset:
Development of a System to Measure Adherence to Lower Back Pain Rehabilitation with Wearable Sensors and Artificial Intelligence
Keywords: Adherence
Home-Monitoring
IMU
Lower Back Pain
Physiotherapy
Rehabilitation

Lower back pain (LBP) is a prevalent health problem that is often effectively treated with physiotherapy/rehabilitation. Adherence to a prescribed rehabilitation program is positively correlated with its overall effectiveness. However, currently there are no simple and deployable quantitative methods to assess home-based LBP rehabilitation participation, where the majority of exercises should be performed. It is hypothesized that inertial data collected from a set of multi-IMU-based wearables analyzed with machine learning will successfully identify the performance of LBP exercises and good sitting posture. With an optimized system utilizing an XGBoost classifier and three IMU sensors placed at the lower back, thigh, and ankle, accuracies of 94% ± 3% and 90% ± 11% were achieved for classification of LBP exercises and good sitting posture, respectively. The technology generated within this project has the potential to improve the effectiveness of LBP rehabilitation by facilitating remote monitoring, early problem diagnosis, and quantitative clinical feedback.
A Pattern-driven Stochastic Process for Degradation Forecasting with Applications to Rechargeable Batteries
Keywords: Degradation Pattern
End-of-life Prediction
State-space Model
Stochastic Process

In recent decades, there has been significant growth in the development of rechargeable battery-powered devices such as electric vehicles, leading to an urgent demand for batteries with high reliability and quality. The end-of-life (EoL), a critical indicator of battery health, can be estimated by adaptive stochastic processes or advanced machine learning techniques. However, unless such approaches assume that the degradation path has a specific form, they operate as black boxes and are unable to provide stochastic interpretation. To address these challenges, a pattern-driven degradation process (PdDP) was executed that can model battery degradation, controlling degradation fluctuation by a GRU-driven degradation pattern. Further, a joint-learning sampling-based expectation maximization (JSEM) algorithm was developed to handle non-Markovian state transitions in estimating model parameters. Finally, a case study showed that the proposed methods outperform traditional methods with respect to both one-step and multistep-ahead prediction accuracies.
Understanding Material Stocks in Roads at the City and Multinational Scale
Keywords: industrial ecology
material efficiency
material flow analysis (MFA)
pavement
roads
transportation

Improving resource efficiency is critical to reduce the environmental impacts of constructing and maintaining the built environment. Construction materials represent a growing share of global greenhouse gas emissions, but limited knowledge concerning the quantity and distribution of materials making up infrastructure is an obstacle to designing robust policies and tracking progress towards greater resource efficiency. This thesis investigates material stocks in roads at the city and multinational scale through case studies of the road networks of Toronto and six high-income countries. Modelling material stocks at the city scale using simplified archetypes is shown to introduce significant uncertainty that is not well addressed in existing studies. Multinational road stocks are estimated using a method that better captures the inherent variability in pavement design. Considerable differences in the material intensities of different countries’ road networks are observed, suggestive of opportunities to build roads with lower environmental impact.
The Role of Teacher Mental Health Literacy in Identifying Emerging Mental Health Disorders in Students
Keywords: Education
Mental Health
Psychology
Psychopathology
Teachers

The present study explored the relationship between teaching experience, mental health literacy and the ability of teachers to accurately rate the severity of behaviors presented through a vignette measure. Canadian certified primary grade teachers (N = 101) completed a survey with a novel vignette measure and a mental health literacy scale. Participants rated the severity of the behaviors depicted in the vignettes and their accuracy was calculated based on how closely their ratings matched the intended severity of symptoms depicted. A hierarchical regression model established that teaching experience alone was not significantly predictive of behavioral rating accuracy, but the inclusion of mental health literacy yielded a significant model. A binomial logistics regression indicated that neither the gender nor pathology depicted in the vignettes significantly influenced rating accuracy. These results substantiate the importance of teacher mental health literacy training in supporting the identification of emerging mental health disorders in students.
Operations Research Applications in Ontario's Healthcare System during the COVID-19 Pandemic
Keywords: Healthcare
Optimization
Queueing
Stochastic Models

The COVID-19 pandemic challenged former norms in hospital operations and motivated innovative strategies for allocating healthcare resources. We present three strategies for mitigating stress on Ontario’s healthcare system. First, we consider inter-hospital patient transfers to address capacity concerns and uneven distribution of COVID-19 caseloads among hospitals. We formulate a queueing control problem and propose an approximate solution approach. With a case study of 21 hospitals we show that patient transfers significantly reduce the number of patient-days above occupancy thresholds, while distributing the COVID caseload. Second, we formulate an integer program to facilitate staff redeployment, and summarize some major challenges in redeployment efforts. Finally, we propose a virtual assessment centre for LTC residents. With data from seven hospitals we estimate staffing and diagnostic imaging resource requirements, and find that 1) aggregating call volume across multiple hospitals greatly reduces staffing requirements; 2) existing outpatient facilities could likely meet the diagnostic imaging requirements.
Managing Type 2 Diabetes During a Pandemic: An Investigation of Reddit Data
Keywords: COVID-19
Natural Language Processing
Reddit
Sentiment Analysis
Topic Modelling
Type 2 Diabetes

Type 2 Diabetes (T2D) is a chronic disease that can be managed through lifestyle. However, the COVID-19 pandemic impacted management of T2D. Our objective is to examine the impact of the pandemic on the health behaviours and attitudes of people living with T2D by examining Reddit forums. Support Vector Machines classifed a post as COVID-related and Latent Dirichlet Allocation topic modelling gathered topics of discussion. VADER Sentiment Analysis gauged attitudes. Amongst COVID-specific posts, topics of discussion were Coping with Poor Mental Health, Accessing Doctor Medications and Controlling Blood Sugar, Changing Food Habits during Pandemic, Impact of Stress of Blood Glucose Levels, Changing Status of Employment Insurance, and Risk of COVID Complications. Posts classified as COVID-related were associated with lower sentiment. Discussions pertaining to receiving support, stress and glycemic control, and mental health were associated with lower sentiment. Discussions pertaining to food habits were associated with higher sentiment.
Influence of Psychosocial Factors on The Experience of Pain Synaesthesia
Keywords: Empathy
Pain
Perception
Psychosocial
Synaesthesia

Pain synaesthesia is a phenomenon in which one can personally feel the pain of another on their own body. This phenomenon has commonly been observed in populations who have experienced prior traumatic injury. However, the influence of psychosocial factors which commonly influence the experience of subjective pain have not been considered. The purpose of this study was to examine the influence of psychosocial factors on the experience of pain synaesthesia. Regression analyses revealed several aspects of empathy (e.g., emotional empathy) were predicative of pain perception ratings in response to painful images. In addition, factors know to increase hypervigilance towards pain cues contributed to the experience of pain synaesthesia in participants with a previous injury. The overall findings suggest empathy may play a central role in the experience of pain synaesthesia while psychosocial factors such as state anxiety and perceived social support might also contribute to the overall experience.
Equitable Green Infrastructure for Climate Change Adaptation: Distributional and Procedural Justice in the City of Toronto
Keywords: Adaptation
Climate Change Adaptation
Environmental Justice
Green Equity
Green Infrastructure
Toronto

Green Infrastructure (GI) presents as a potential tool for climate change adaptation. This study seeks to answer the questions: where should GI be implemented to improve both distributional justice and climate change adaptation in the City of Toronto and how can GI plans be implemented to improve procedural justice. This study takes a mixed-methods approach, developing and applying a GI Equity Index, modelled after Heckert Rosan’s (2016) methodology, to answer question one and semi-structured interviews to answer question two. The results of this study highlight the inequitable distribution of GI in the City of Toronto and proposes prioritizing GI implementation in six neighbourhoods to improve distributional justice. Interviews with residents of the priority neighbourhoods revealed key considerations for future engagement such as distributional injustice and lack of access, desire for more GI and co- production of space, accounting for quality and maintenance in distributional justice, and an inequitable burden of adaptation.
The Effect of Bilingual Exposure on Language and Cognitive Recovery in Children following Stroke
Keywords: bilingual
children
cognition
language
pediatric stroke
recovery

Pediatric stroke often affects higher-level cognition and linguistic processes. Certain linguistic and cognitive advantages have been confirmed in behavioural studies of typically developing bilingual children. This research evaluates the effects of bilingual exposure on linguistic/cognitive recovery in children post-stroke. In Study 1, an interaction effect between language group and stroke-onset group revealed that bilinguals 1-12 months at stroke onset had better expressive language compared to monolinguals, based on the Pediatric Stroke Outcome Measure administered at several points post-stroke. In Study 2, a monolingual-bilingual pair of children aged 78 at stroke onset were compared using language/cognitive assessments in a case study. Results taking relative change over time in account showed similarities to Study 1, with the bilingual case having a more consistent recovery of expressive language. Overall, no negative effect of bilingualism on development after stroke was found; rather there may be an expressive linguistic advantage post-stroke outcome for bilingual patients.
Integrated Modelling of Statistical Process Control and Maintenance
Keywords: Condition Based Maintenance
Semi-Markov Decision Process
Statistical Process Control

Quality of products has been a major concern in various industries due to increasing competition. Maintenance of machines and production processes is a key factor in ensuring high quality of the products. In addition, control charts have long been utilized to monitor variation in the production process. In this thesis, we propose a Semi-Markov Decision Process (SMDP) model to integrate Statistical Process Control (SPC) and maintenance operations. The objective is to determine jointly optimal maintenance and process control policies that minimize the total long-run average costs comprised of maintenance and monitoring costs. We propose a policy iteration algorithm to find the optimal parameters. Finally, we illustrate the results and benefits of integrated SPC and maintenance using a numerical case study.
Generating Constraints for Electromigration Safety for Chip Power Grids
Keywords: Chip
Constraints
Electromigration
Power Grid
Safety

This project is focused on generating constraints that the supply currents drawn by the underlying circuit blocks must satisfy in order to guarantee electromigration (EM) safety in the on-chip power grid. This safety is based on an accurate physical model of EM that comprehends atomic flux and material flow among connected metal lines. Normally, one takes user-provided currents as inputs and produces the stress in metal lines as output, and this forms the basis for EM checking and verification. In contrast, we are here solving what may be called the inverse problem: given a grid and a safety threshold for stress in the metal lines, we want to produce constraints on the circuit supply currents that guarantee EM safety. These constraints, taken altogether, provide a description of the space of safe currents, which we call the safety set.
Qualitative Study Examining the Role of Stigma in the Help-seeking Behaviours of South Asian Youth Accessing Psychotherapy in Ontario
Keywords: Help-Seeking
Psychotherapy
South Asian
Stigma
Youth

South Asian (SA) youth face many mental health challenges yet access psychotherapy less often than other ethnic groups and this may be, in part, due to stigma. The aim of this qualitative descriptive study (N=10) was to understand SA youth’s experiences with stigma when accessing psychotherapy using semi-structured interviews. This level of understanding is sought to learn how the barrier of stigma was overcome. The Cultural Help-seeking Model served as a theoretical framework informing the author’s understanding of the role of stigma within the help-seeking process of SA youth. Six major themes were identified in the data: 1) influence of SA culture; 2) others as barriers to accessing psychotherapy; 3) others as facilitators to accessing psychotherapy; 4) personal attitudes; 5) context of mental health care; and 6) strategies for reducing stigma. The results of this study are used to propose recommendations for social work researchers, educators, practitioners, and policymakers.
First-order Fast Algorithms for Structurally Optimal Large-scale Multi-Group Multicast Beamforming
Keywords: Alternating direction method of multipliers
Computational complexity
Extragradient algorithm
Multicast beamforming
Optimal structure
Successive convex approximation

This thesis considers multi-group multicast beamforming design in large-scale systems, where two typical problems, the quality-of-service (QoS) problem and the max-min fair (MMF) problem, are studied. Based on the optimal multicast beamforming structure obtained recently, we propose two fast first-order algorithms to obtain the beamforming solutionsfor the QoS problem. The two algorithms both utilize the successive convex approximation (SCA) method, and they solve each SCA subproblem by the extragradient method and the alternating direction method of multipliers (ADMM), respectively. Initialization methods for SCA are also developed, including an extragradient-based approach, an ADMM-based approach, and semi-definite relaxation. Next, we propose solving the MMF problem via a simple closed-form scaling scheme, whose feasibility and bounded performance are guaranteed from the theoretical analysis. Our extensive experimental results show clear evidence of the effectiveness of our proposed methods.
Biodistribution and Fate of Intravenously-delivered First Trimester Human Umbilical Cord Perivascular Cells in a Murine Model of Systemic Inflammation
Keywords: Inflammation
Mesenchymal stem cells

Immunomodulation is a major property underlying the therapeutic benefit of mesenchymal stem cells (MSC). A lack of detailed biodistribution and fate investigations is limiting our understanding of the relative roles of paracrine secretion and passive phagocytosis in MSC immunomodulation. I investigated the biodistribution and fate of IV-delivered first trimester human umbilical cord perivascular cells (FTM HUCPVC) in a murine model of inflammation. I hypothesized that IV administered FTM HUCPVC MSC will attenuate lung inflammation in a murine model of systemic inflammation, in a time-dependent manner. Immunohistochemistry and cytokine arrays were used to assess FTM HUCPVC biodistribution, apoptosis, impact on immune cells and cytokine levels. FTM HUCPVC localized to the lungs, associated with immune cells, and, despite limited persistence, mediated a reduction in proinflammatory mediators. Results demonstrate a significant role for the innate immune system in MSC immunomodulation and provide insight for potential bolstering of MSC therapy through the immune system.
Assessing the Role of Sleep in Shaping Hippocampal Engram Connectivity in CA3-CA1
Keywords: Engram
Hippocampus
Learning
Memory
Sleep
Synapses

Memories are stored in engrams. Crucial to the formation of engrams is the enhancement of synaptic strength between the neurons co-active during learning. Sleep has been hypothesized as a state which drives the ‘offline’ synaptic modification. Recent studies now corroborate this account, uncovering sleep-dependent changes at the synaptic scale. However, the interaction between sleep and the strengthening of engram synapses had not been experimentally reported. We hypothesized that sleep supports the enhancement of engram-engram (E-E) connectivity that occurs during learning. We leveraged dual-eGRASP, a viral labeling strategy which tags converging inputs from engram and non-engram presynaptic populations onto postsynaptic engram and non-engram dendrites, to assess the synaptic connectivity patterns of mice that were sleep deprived after contextual fear conditioning. Our results showed no effect of learning or sleep deprivation on the E-E connectivity in CA3-CA1. Additional experiments are needed to validate this result.
Exploring the Role of Heavy Metal Pollutants on the Physiology of Commercially Relevant Fish from Atlantic Canada
Keywords: Atlantic fish
Ecotoxicology
Heavy metals
Spine curvatures

The Gulf of Maine/Bay of Fundy have documented increases in heavy metal pollutants. Whether species from distinctive water column zones (epipelagic, mesopelagic, demersal) are differently accumulating heavy metals and experiencing negative impacts on their physiology was the focus of this work. Benthic and anadromous species were also examined for additional effects of residing in areas of higher pollution such as near sediment and rivers. Morphometrics were recorded and muscle, liver and kidney biopsies for heavy metal profiles were assessed. The highest heavy metal levels were in epipelagic and demersal species, accompanied by the greatest reductions in growth (weight for length) compared to historical values. Anadromous and benthic species overall had the highest levels of heavy metals, reductions in growth and presence of spine curvatures. Thus, fish are accumulating heavy metals at levels dependent on their location in the water column, associated with negative impacts on their growth and physiology.
Solar Transformative Processes in Hatshepsut´s Coronation Scenes in the Red Chapel
Keywords: Coronation
Crowns
Hatshepsut
Iconography
Red Chapel
Solar rebirth

Queen Hatshepsut stands out among the minority of women who have held the role of king of Egypt thanks to the unique methods that Hatshepsut used in order to obtain this position. Among these procedures, her complex iconographic programs should be highlighted. As such, the Red Chapel in the Temple of Karnak proves to be an invaluable source as its complex iconographic program presents key moments of her rule – the most intriguing being her coronation ceremony. However, there is reason to believe that these scenes also contain an underlying symbolic and cosmological meaning. In the following study, I aim to bring these themes to light by analyzing the iconographic elements of these scenes and the diverse texts that accompany them, focusing on the order and various iconographic details of Hatshepsut´s crowns, and the visual effect they would have had on the ancient viewer.
Class, Gender, and Nationalism in ‘Aziza Amir and Fatma Rushdie’s Films
Keywords: Arab Cinema
Class
Cultural Production
Egyptian Feminism
Egyptian Nationalism
Women's History

This thesis examines the works of lower-class Egyptian women filmmakers during the first half of the 20th century, focusing on the films of ‘Aziza Amir and Fatma Rushdie in particular. After contextualizing their films in the political and intellectual atmosphere of the time, I analyze two of ‘Aziza Amir’s works as a screenwriter and four of Fatma Rushdie’s works as an actress. I demonstrate that both women strategically used their films to interrogate, challenge, and/or reproduce the Egyptian nationalist and feminist discourse of the time, particularly as it related to gender, class, nationalism, and national identity. I argue that both women made significant contributions to popularizing and disseminating the language and ideals that would then become the trademark of the Gamal Abdel-Nasser era starting in 1952.
Simulation-assisted Colloidal Quantum Dot Solar Cell Band Alignment using Two-step Ionic Doping
Keywords: band alignment
colloidal quantum dot
fluoride doping
scaps
solar cell

Colloidal quantum dot (CQD) solar cells have tunable optoelectronic properties, enabling CQD solar cells to absorb solar radiation inaccessible to many existing liquid-processed semiconductors. I explore herein routes to increasing stability and performance in CQD solar cells through modifications of the active layer, aided by simulation and implemented experimentally. I find that the results of these simulations provide an avenue to improving device performance experimentally. Based on these results, I implement a fluoride ionic doping procedure which allows for greater control of doping characteristic of solar cells by inducing greater p-type characteristic. Based on this procedure, the improvements in VOC, FF, and PCE that I predicted via simulation are observed experimentally, with fluoride-doped devices showing a maximum performance of 12.7% AM1.5 PCE. This work showcases the potential of device simulations to assist in further device performance improvements and provides recommendations for a path to commercialization of CQD solar cells.
Vibration and Attitude Control of Square Solar Sails using Tip Vane Null Motion
Keywords: attitude control
control allocation
control systems
solar sails
structural dynamics
vibration control

This thesis covers the development and simulation based implementation of a control law used to concurrently control the vibration and attitude of a square solar sail using dual gimballed corner-attached reflective vane actuators. An introduction to the topic is presented along with the prerequisite mathematical foundation needed to follow the thesis. Following that, a flexible structural dynamics model of the solar sail is developed using a Rayleigh-Ritz expansion to model the coupled rotational and elastic dynamics of the system. Next, a control law is developed using Lyapunov control design to concurrently damp structural vibrations as well as reorient the sail to a desired attitude. Subsequently, a control allocation process is presented to tackle the underconstrained nature of the tip vane actuators such that desired control forces can be realized as closely as possible. Finally, simulation results using the control law with the structural dynamics model are presented to demonstrate the improvement in vibration damping using the augmented PD control law developed as opposed to a simple PD control law.