VictorJuiz/thesis huggingface dataset:
Implications of Reduced Inhibition in Schizophrenia on Human Prefrontal Microcircuit Activity and EEG

Reduced cortical inhibition by parvalbumin-expressing (PV) interneurons has been associated with impaired cortical processing in the prefrontal cortex (PFC) and altered EEG signals such as oddball mismatch negativity (MMN) in schizophrenia. However, establishing the link between reduced PV interneuron inhibition and reduced MMN experimentally in humans is currently not possible. To overcome these challenges, we used detailed computational models of human PFC microcircuits, and modeled schizophrenia microcircuits by integrating gene-expression data from schizophrenia patients indicating reduced PV interneuron inhibition output and NMDA input. We simulated spiking activity and EEG in microcircuits with different levels of reduced PV interneuron mechanisms and showed that a double effect of the reduction indicated by gene-expression led to a significantly reduced MMN amplitude as seen in Schizophrenia patients, whereas a single effect produced a smaller reduction in MMN that matched the magnitude seen in patients at high-risk of schizophrenia. In addition, we showed that simulated resting EEG of schizophrenia microcircuits exhibited a right shift from alpha to beta frequencies. Our study thus links the level of reduced PV interneuron inhibition to distinct EEG biomarkers that can serve to better stratify different severities of schizophrenia and improve the early detection using non-invasive brain signals.

Keywords: Computational modelling
Mismatch Negativity
Parvalbumin
Prefrontal cortex
Reduced Inhibition
Schizophrenia
Advisor: Hay, Etay
Pathfinder: Local Obstacle Avoidance for Long-Term Autonomous Path Following

Visual Teach and Repeat 3 (VT&R3), a generalization of stereo VT&R, achieves long-term autonomous path-following using topometric mapping and localization from a single rich sensor stream. In this thesis, we improve the capabilities of a LiDAR implementation of VT&R3 to reliably detect and avoid obstacles in changing environments. Our architecture simplifies the obstacle-perception problem to that of place-dependent change detection. We then extend the behaviour of generic sample-based motion planners to better suit the teach-and-repeat problem structure by introducing a new edge-cost metric paired with a curvilinear planning space. The resulting planner generates naturally smooth paths that avoid local obstacles while minimizing lateral path deviation to best exploit prior terrain knowledge. While we use the method with VT&R, it can be generalized to suit arbitrary path-following applications. Experimental results from online run-time analysis, unit testing, and qualitative experiments on a differential drive robot show the promise of the technique for reliable long-term autonomous operation in complex unstructured environments.

Keywords: Curvilinear Coordinates
Field Robotics
Model Predictive Control
Motion Planning
Obstacle Avoidance
Path Planning
Advisor: Barfoot, Timothy D
Law Reform through Deep Ecology: A Critical Review of the Canadian Environmental Protection Act, 1999

The single most important piece of legislation in Canadian environmental law, the Canadian Environmental Protection Act, 1999 (CEPA) proposed its set of amendments under Bill S-5, Strengthening Environmental Protection for a Healthier Canada Act. This project is a qualitative study, using Critical Discourse Analysis (CDA) to review the amendments in Bill S-5 against the philosophy of deep ecology which argues that nature has inherent worth. Overall, Bill S-5 does not display evidence of deep ecology principles. I argue that if the Act is amended to include stricter principles inspired by deep ecology, it can enhance sustainable development. By examining the Bill’s language and the law’s sociocultural contexts, CDA provides insights into the potential implications and effects if the Act indeed displayed a case for biocentric equality. Deep ecology at times underplays the capacity of the role of humans, therefore Canadian Indigenous knowledge systems will be discussed to address this gap.

Keywords: Climate change
Human health
Right to healthy environment
Sustainable development
Well-being
Advisor: Scharper, Stephen B.
Appolloni, Simon
Performance Analysis, Design, and Testing of Radio Frequency Earth Observation Microsatellite Missions

Modern terrestrial technologies are enabling small satellites to push the boundary of what radio frequency remote sensing payloads can achieve. Software defined radio and field programmable gate array technologies enable missions to increase the comprehensiveness of Earth observations through the flexibility inherent to these technologies. Significant engineering challenges must be overcome to fly them. This thesis presents work to enable two new missions by addressing challenges resulting from their payload systems. A new system-level performance analysis and electromagnetic compatibility testing system has been created to qualify multi-channel radio frequency payloads. Work has also been performed to facilitate spacecraft-level vibration and thermal vacuum testing, the latter of which required the design and construction of an antenna hat for safely dissipating emissions from a high power transceiver. Lastly, multiple data-handling payloads are connected using a field programmable gate array, where static timing analysis has been used to verify external interface timing requirements.

Keywords: Earth Observation
Electromagnetic Compatibility
Microspace
Performance Analysis
Radio Frequency
Satellite
Advisor: Zee, Robert E
Power Grid Safety under Electromigration

Electromigration is a reliability concern that affects chip power grids carrying high current over the course of several years. Power grid safety is an important issue that can be addressed in several ways. In this work, we present two different ways of guaranteeing grid safety from electromigration. First, for safety of the chip from void nucleations due to electromigration, a set of current constraints can be generated as guidelines or constraints for chip design. The proposed procedure efficiently generates approximate constraints by projecting the system onto a smaller subspace, based on an Arnoldi scheme for model-order reduction. It then leverages several properties of the matrices at hand to efficiently perform the required computations in the reduced subspace, before projecting the results back to the original space. Second, for safety of the chip from electromigration-related voltage failures, we developed a procedure which widens some metal lines in order to prolong the lifetime of the chip. This work improves on a previous iterative method for grid fixing by the use of a faster and more accurate electromigration simulator.

Keywords: Computer Simulation
Electromigration
Power Grid Safety
Advisor: Najm, Farid N
Deep Learning for Long-Term Metric Visual Localization

Visual localization is the task of estimating camera pose in a known scene, which is an essential problem in robotics and computer vision. However, long-term visual localization is still a challenge due to the environmental appearance changes caused by lighting and seasons. While experience-based localization methods bridge the appearance gap by relying on intermediate experiences, they require collecting ex- periences continuously to capture the incremental appearance changes, and cannot directly generalize to a new path. In this thesis, we tackle long-term localization using deep learning methods with- out relying on intermediate experiences. We first show that we can learn appearance- invariant sparse visual features using self-supervised learning that can be used in closed-loop path following across a full range of lighting change while preserving generalizability. We further explore deep image-to-image translation as a mean of improving long-term metric localization. We show that by transforming input images captured from different lighting conditions into a common target domain prior to feature matching substantially improves upon localization accuracy.

Keywords: Autonomous Navigation
Computer Vision
Deep Learning
Long-term localization
Robotics
Advisor: Barfoot, Timothy
Biopsychosocial Characterization of Cognitive Decline and Late-Life Depression Trajectories Using Bayesian Consensus Clustering and Machine Learning

Cognitive decline and late-life depression (LLD) often co-occur and impact elderly’s wellbeing. However, their intersection and antecedents are understudied. We analyzed 2,992 participants from the Religious Orders Study and Memory and Aging Project, integrating symptoms and diagnostic records with Bayesian consensus clustering to define latent sub-trajectories of cognitive decline and LLD. Logistic regression, elastic-net regression and XGBoost were used to build models of these trajectories including n=57 biopsychosocial predictors. Associations of subgroups with postmortem neuropathologies were assessed for 1,721 deceased participants. Three subgroups were identified for cognitive decline and two for LLD, which overlapped significantly (chi-square p=8.1x10-26). Elastic-net regression performed best overall, while XGBoost excelled at predicting moderate subgroups. High neuroticism and low physical health at baseline predicted unhealthy subgroups for both cognition and LLD. There were no neuropathologies associated with LLD trajectories. Our results suggest potential values of targeting neuroticism and physical health for healthy aging and patient screening.

Keywords: Bayesian clustering
Biostatistics
Cognitive decline
Dementia
Depression
Machine Learning
Advisor: Felsky, Daniel
Characterizing the NLRP1B Inflammasome in the Intestinal Epithelium

The intestine is a non-sterile organ that must maintain its epithelial barrier to prevent microbial invasion into deeper tissue. Intestinal epithelial cells (IECs) are equipped with innate immune receptors, such as NOD-like receptors (NLRs), that facilitate destruction of infected cells and initiate an inflammatory response through inflammasome formation. NLRP1B, the major mouse homolog of human NLRP1, has been primarily studied in macrophages; and therefore, very little is known about this NLR in the intestinal epithelium. Here, we determine that NLRP1B is expressed higher in murine ileal organoids than in bone marrow-derived macrophages (BMDMs), however, only BMDMs are responsive to the NLRP1B activator, Val-boro-Pro. Additionally, IL-13, which is important in enteric parasite defense, induces Nlrp1b expression and this was confirmed in vivo using Tritrichomonas muris infection. Overall, our data suggests that the NLRP1B inflammasome is differentially regulated in IECs and BMDMs and could have a novel role in enteric parasite infection.

Keywords: Innate Immunity
Advisor: Girardin, Stephen
Mogridge, Jeremy
Exploring the Effect of Social Support from Sport Medicine Staff on Injured Female Athletes’ Well-Being During Rehabilitation

This study explored female athlete experiences with sport medicine staff while they navigated injury rehabilitation, specifically exploring the ways in which social support from sport medicine staff influenced well-being during this process. Eleven injured athletes completed two semi-structured interviews and six audio diary entries. Thematic analysis of the collected data suggested that athletes perceived sport medicine staff as supportive if they made athletes feel that they mattered. Further analysis demonstrated that sport medicine staff showed athletes they mattered by providing clear information about rehabilitation, demonstrating competency in delivering treatment, and developing a personal connection with athletes. These findings provide valuable insight into how female athletes experience social support from sport medicine staff during injury rehabilitation. Additionally, it provides applied suggestions for sport medicine staff who work with injured female athletes.

Keywords: Athlete well-being
Injury rehabilitation
Mattering
Social support
Sport medicine staff
Advisor: Tamminen, Katherine
Material Efficiency Strategies for Building More Housing with Less Embodied Greenhouse Gas Emissions

Embodied emissions from construction are accounting for a large and growing share of global emissions due to increasing demand for housing and related infrastructure. Strategies are urgently needed to find ways of building the infrastructure required for social and economic good while staying committed to emission reductions. This thesis uses detailed data to look at the role of form, design, and materials in reducing embodied emissions of residential buildings and related infrastructure. The 2nd chapter presents an analysis of 102 bottom-up building material quantifications. The analysis highlights the most materially efficient forms of housing and identifies strategies for reducing embodied emissions within all forms. The 3rd chapter introduces a new model for forecasting embodied emissions in houses, roads, and water infrastructure. Through a Canadian case study, the model reveals drivers of embodied emissions at a neighbourhood level and the time-dependent effectiveness of different reduction strategies.

Keywords: Construction
Housing
Industrial Ecology
Infrastructure
Modelling
Sustainability
Advisor: Saxe, Shoshanna
Measuring the Risk for Pedestrian Falls on Outdoor Walkways: A Pilot Evaluation Using the Minimum Foot Clearance Estimation System

Falls are the leading cause of injury for older adults, and nearly half of these the result of tripping. Measuring an individual’s minimum foot clearance (MFC), is related to their risk of tripping.The objective of this project was to estimate MFC values from four groups of pedestrians (healthy young, healthy older, unusual gait, mobile device users) on outdoor walkways using a pair of calibrated video cameras positioned near four sites featuring different sizes of abrupt level changes (0 mm, 5 mm, 10 mm and 15 mm). Data was analyzed from 160 pedestrians and MFC values ranged from 7.1 mm to 49.2 mm. MFC values for healthy older adults were significantly lower than for healthy young pedestrians and mobile device users. MFC values from 0 mm obstacles were significantly lower than for 5 mm obstacles and MFC for 5 mm obstacles was higher than for 10 mm obstacles.

Keywords: Abrupt level changes
Falls
Gait characteristics
Minimum foot clearance (MFC)
Public walkways
Tripping
Advisor: Dutta, Tilak
Adverse Childhood Experiences in a Paediatric Systemic Lupus Erythematosus Cohort

Childhood-onset systemic lupus erythematosus (cSLE) is a chronic autoimmune disease. Neuropsychiatric manifestations are common in cSLE, yet poorly understood. Adverse childhood experiences (ACEs) are traumatic experiences occurring in childhood. While adults with SLE and ACEs report more depressive symptoms, ACEs are less studied in cSLE. This retrospective study aimed to determine the prevalence of ACEs in a cSLE cohort, and examine the association between ACEs and cognitive performance, mood symptoms, and inflammation (high sensitivity C-reactive protein; hs-CRP). ACEs and hs-CRP data were collected via medical chart review. Neuropsychiatric data were leveraged from prospective studies. Associations were examined with regression models. Of 224 patients with cSLE, 41% had ≥1 documented ACE. Exposure to ACEs was significantly associated with worse executive function and clinically elevated depressive symptoms. ACEs exposure was not associated with anxiety symptoms or hs-CRP levels. Further prospective studies should investigate the relationship between ACEs and neuropsychiatric manifestations in cSLE.

Advisor: Knight, Andrea
Does Ontario's Ministry of Education Promote Critical Theory in K-12 Education

Critical Theory (CT) has evolved from European neo-Marxism into American Identitarianism. Its pedagogy seeks societal revolution by re-focusing children’s education on identity power conflicts. CT has been criticized in the literature as pedagogically misguided, harmful to low SES students, dependent on stereotyping, hostile to evidence, and self-serving; therefore, any adoption by educational policy-makers begs for an explanation. This thesis examines whether Ontario’s Ministry of Education has indeed promoted CT in K-12 education. I employ mixed methods to define key terminology, and track its usage in 673 Ministry policy documents spanning 1982-2022. I find that the Ministry – even under the Conservatives – has increasingly adopted CT terms while poorly and inconsistently defining them. I attribute this to opportunistic framing, institutional isomorphism, and elite agenda-setting, arguing that the Ministry is generating disregard for empirically-tested teaching methods necessary for literacy, numeracy and critical thinking proficiency. Additionally, CT’s pessimistic divisiveness threatens social and civic cohesion.

Keywords: Critical Gender Theory
Critical Race Theory
Critical Theory
Culturally Relevant Pedagogy
Educational policy
K-12
Advisor: Davies, Scott
Measuring and Comparing the Concentration of PM2.5 in the GTA using Low-cost Sensors

This thesis developed exposure models which can predict the concentration of particulate matter (PM2.5) in the city of Toronto by using low-cost sensors manufactured by PurpleAir. Compared with other devices, these low-cost sensors can achieve higher spatial resolution with high sensor density in an area. They can work only with a connection to Wi-Fi, and a power supply. This study used twenty existing sensors in Toronto to collect PM concentration, temperature, humidity, and air pressure. Based on the PM2.5 concentrations collected from January 23, 2022, to January 20, 2023, multi-linear regression models and generalized additive models were used to predict the spatial distributions of PM2.5 concentration throughout the city. An exposure map was made based on the generalized additive model.

Advisor: Wunch, Debra
Franklin, Meredith
Directional Data Integration for Multi-omics Pathway Enrichment Analysis and Biomarker Discovery

Different omics techniques allow us to characterize the genetic, transcriptomic, epigenomic, and proteomic landscapes of cells and tissues and better understand their perturbations in disease. However, joint analyses of different omics datasets for a holistic understanding of cell function present a computational challenge. Our lab recently created the ActivePathways software tool, an integrative pathway enrichment analysis method that uses data fusion to merge signals from multiple omics datasets. Here I develop Directional P-value Merging (DPM), a method that extends this computation framework by accounting for directional activities of genes across the input omics datasets. DPM penalizes genes and pathways that violate user-defined constraints, enabling more effective data integration experiments. I demonstrate the use of the DPM method on three biological case studies, identifying pan-cancer biomarkers with consistent survival associations and the mechanisms driving tumor biology that have been previously overlooked in the analysis of individual omics datasets.

Advisor: Reimand, Juri JR
Characterizing proNGF and NGF Expression in a Mouse Model of Alzheimer’s Disease

Alzheimer’s disease is underscored by the degeneration of basal forebrain cholinergic neurons (BFCNs). The survival and function of BFCNs depends on nerve growth factor (NGF) and its precursor (proNGF). The levels of NGF, proNGF, and their receptors, TrkA and p75NTR, dictate the engagement of pro-survival or degenerative pathways in BFCNs. Deficits in TrkA and NGF were described in the TgCRND8 mouse model of amyloidosis (Xhima et al, 2020); however, the methodology used to measure NGF did not discriminate between NGF and proNGF. The primary goal of this thesis was to elucidate the levels of proNGF in TgCRND8 mice. The data show that proNGF levels are higher in TgCRND8 compared to non-transgenic mice in the septohippocampal pathway, but not in the basalocortical pathway. These findings highlight the effects of amyloidosis on proNGF levels in TgCRND8 mice, thereby establishing it as a model to explore therapeutic candidates targeting the proNGF signaling axis.

Keywords: Alzheimer's
Basal Forebrain
Cholinergic system
NGF
proNGF
Advisor: Aubert, Isabelle
Investigations on an Alternative Approach to Fmoc Deprotection and Diversification of the Alumino-Mannich Reaction

The Fmoc group is widely used for amine protection, but the classical deprotection approach, piperidine in DMF, has drawbacks due to toxicity and cost. Previous research explored alternative conditions using diethylamine and Lewis acids. This thesis outlines the synthesis of Fmoc-protected dipeptides and alternative deprotection conditions: classical, diethylamine alone, and diethylamine with Lewis acids (Ca(TFA)2, CaCl2, BF3•Et2O). NMR analysis reveals that CaCl2 and BF3•Et2O only slightly accelerate deprotection, making this an impractical alternative in peptide chemistry and amine protection.Chapter 2 broadens the substrate and product range of an asymmetric “alumino-Mannich” reaction using a range of sulfinyl imine and alkenylaluminum reagents for homochiral allylamine synthesis. Factors including temperature, steric bulk, and electronic effects are studied. Steric bulk of alkenylaluminum reagents dominates selectivity; electronic effects within sulfinyl aldimines dominates the yield, and electron deficiency is crucial at cryogenic temperatures. Surprisingly, high yields and selectivities were achieved at room temperature.

Keywords: alumino-Mannich
chiral allylic amines
Fmoc Deprotection
Sulfinyl aldimines
Advisor: Batey, Robert A
Development of a Millimeter-Wave Radar Based Touch Screen

This thesis presents the design of a wide-band mm-wave radar antenna that can recognize touch locations on a smartphone keyboard. An L-shaped antenna assembly with one transmitting antenna and three receiving antennas was used to determine the target's location in 3 dimensions. The antenna has a 28 GHz bandwidth, allowing for a 5 mm range resolution, ideal for distinguishing between two fingers while typing. This study also assessed the implications of the mobile phone’s structure on the antennas’ performance. A smartphone with a plastic frame performs better than a structure with an aluminum frame. A TI IWR1443 evaluation board was used to investigate the radar potential to find a target location within mm accuracy. To improve the accuracy and overcome the FFT’s limitation, a Chirp Z-Transform (CZT) was used to get a finer estimate of the IF frequency, resulting in an average error of 0.5%, corresponding to 0.8 mm accuracy.

Advisor: Ben Mrad, Ridha
Etiological Classification of Out-of-Hospital Cardiac Arrest (OHCA) and Relationship of Causality and Survival Outcomes; A Scoping Review

Introduction: The Utstein reporting template was published to standardize reporting OHCA-related data, including etiology. This thesis defines the current state of initial etiological classification based on abstracted data compared with other sources, the impact of this classification on reported survival outcome, and the role of circumstance-related factors in refining the classification through three scoping reviews.Method: Three electronic databases were searched to identify studies. After screening titles and abstracts, full texts were reviewed against inclusion criteria. Result: 108 studies met inclusion criteria. A significant discrepancy was observed between initial etiological classification using the Utstein template against other sources. The survival of non-cardiac etiologies was inconsistent compared with presumed cardiac etiologies. Circumstance-related factors are associated with refinement of etiology. Conclusion: Etiological classifications of cardiac arrest are heterogeneous which may affect outcomes and patient selection for research. Adjusting the Utstein template to report etiology more carefully may refine future research in cardiac arrest and improve the quality of data registries.

Keywords: Contributing factors
Data registry
Emergency medical services
Etiology
Out-Of-Hospital cardiac arrest
Survival outcome
Advisor: Morrison, Laurie LJM