VictorJuiz/thesis huggingface dataset:
The Effect of an Anticipated Perturbation on Gait Variability and Stability during Treadmill Walking in Young, Healthy Adults

Increased movement variability in quiet standing correlates with improved standing stability following a balance perturbation. It is unknown if this translates to gait. This study aimed to determine if increasing gait variability is a strategy to improve stability. We hypothesized that 1) spatio-temporal gait features will be more variable prior to an expected perturbation than during unperturbed walking, and 2) increased spatio-temporal gait variability pre-perturbation will correlate with improved stability post-perturbation. Sixteen healthy young adults completed 15 treadmill-walking trials under two conditions (unperturbed and an expected perturbation). Short- and long-term variability of step length, width, and time were calculated. Stability was defined as the number of steps to restabilization post-perturbation. Long-term step width variability was significantly higher pre-perturbation compared to unperturbed walking. There was no significant relationship between pre-perturbation variability and post-perturbation restabilization. These findings suggest that participants increased movement variability as an exploratory strategy in anticipation of a perturbation.

Keywords: Gait
Perturbation
Stability
Treadmill
Variability
Advisor: Nestico, Jacqueline
Fast Eye-in-hand 3D Scanner-robot Calibration for Low Stitching Errors

This thesis proposes a new eye-in-hand 3D scanner-robot calibration approach to realize low data stitching/registration errors during long-term continuous measurement of industrial parts. Eye-in-hand systems are commonly used for complete measurement of an object under test (OUT) from multiple fields of view (FOVs). To align the multiple FOVs into a single coordinate system, marker-free stitching assisted by robot’s positioning is attractive since it bypasses the cumbersome traditional fiducial marker-based method. Based on capturing calibration images from a 2D calibration target, scanner’s and robot kinematic model’s parameters are optimized. The challenges overcome include, (1) compensating for the center-detection error in scanner calibration; (2) avoiding the dependency of hand-eye calibration on DH parameters; and (3) calculating an accurate world-to-robot transformation. In the experiments, the mean stitching error was effectively maintained to be

Keywords: Data stitching
Industrial metrology
Kinematic model
Manufacturing automation
Robot sensing systems
Structured light measurement
Advisor: Sun, Yu
Exploring Supervisors’ Decisions about Procedural Entrustment in Simulation-based and Workplace-based Settings

Entrustment decision-making is a fundamental goal of competency-based medical education (CBME). How supervisors engage their ‘rater cognition’ when judging for entrustment using workplace-based and simulation-based assessments is unclear. We carried out an interview-based, constructivist grounded theory-informed qualitative study that aimed to explore how supervisors make entrustment decisions in both settings using endoscopic polypectomy as a relevant entrustable professional activity (EPA). Gastroenterology supervisors completed EPAs for endoscopic polypectomy after both a single workplace-based and simulation-based assessment and were interviewed after each. Transcribed data were coded iteratively using constant comparison to generate themes. We found participants had difficulty making entrustment decisions and scored EPAs idiosyncratically due to variable personal meanings of entrustment. Each setting was found to have unique strengths in entrustment decision-making when combined in a program of assessment. These data support re-evaluation of the current usage of EPA assessments within CBME systems.

Advisor: Brydges, Ryan
Walsh, Catharine M
Badiou, Freire, and the Pedagogy of Concentration

The renowned pedagogical theorist Paulo Freire made political subjectivity one of his core concerns, and he opposed approaches to subjectivity which considered the latter in terms of classical transparency and approaches which understand subjectivity in a deterministic fashion. I argue that Freire’s approach is an example of “concentration”, a concept I borrow from Alain Badiou’s Theory of the Subject. I use Badiou’s dialectical concepts in order to argue that Freire’s famous Pedagogy of the Oppressed is a Marxist text, but one that engages in constructing an anti-deterministic approach to subjectivity. I make this argument via a consideration of the problems of subjectivity and objectivity in the classical Marxist canon in order to show how Freire and Badiou depart from this canon while building upon it. This analysis is intended to pose in new terms the relationship between Freire and Marxism, and between Badiou and education.

Keywords: Badiou
Dialectics
Freire
Marxism
Pedagogy
Advisor: Bialystok, Lauren
Big Data Insights into MRI Demand and Wait Time

The demand for Magnetic Resonance Imaging (MRI) in Ontario has been increasing annually, resulting in longer wait times for patients. This big data study links multiple administrative data sets to characterize and explore drivers of growth in MRI imaging in Ontario between 2008 and 2017. Our retrospective population-based big data study shows an increasing trend in the use of MRI scans, outpacing capacity. Demand increased the greatest amongst family physicians, and there were also wide variations in MRI referral rates among this group. Subgroup analysis demonstrates that family physicians practicing sports medicine ordered more extremities and spine MRIs. Multiple physician characteristics, including years of practice and physician demographics, also impacted the use of MRIs. Overall, 8% family physicians were consistent higher testers, who contributed to nearly 25% of extremities, spine, and brain MRI tests. These findings may help better target interventions to reduce variations in care and overuse.

Keywords: Big data
Healthcare
Magnetic resonance imaging
Population-based study
Retrospective study
Statistics
Advisor: Carter, Michael
Aleman, Dionne
Data-driven Parameter Learning without Groundtruth for Improving Robotic State Estimation

Probabilistic state estimation for robotics is a field that has greatly matured in recent years. Yet the performance of modern estimators is still heavily dependent on robot model parameters that can be difficult to determine from first principles. While it may be sufficient to hand tune these parameters, this is often time consuming or impossible due to the sheer number of unknown parameters. In this thesis, we investigate methods for learning parameters based on data, to come up with the parameter values most suitable for the particular robot and sensor. We first develop a novel continuous-time motion prior trained with data to improve an existing continuous-time estimation framework. We then provide a detailed investigation into parameter learning within a Gaussian variational inference setting using Expectation Maximization. We validate our work on various trajectory estimation problems using a 36 km long vehicle dataset collected as part of this work.

Keywords: Localization
Parameter Learning
Sensor Fusion
State Estimation
Advisor: Schoellig, Angela P
Barfoot, Timothy D
Generalizable Approaches for Tracking, Estimating, Optimizing, and Quantifying Uncertainty of Fuel Use in Earthworks Operations

Fuel use in earthworks processes are responsible for a considerable portion of global anthropogenic greenhouse gas (GHG) emissions and are directly tied to operation costs. Environmental and financial interests are therefore tied to the mitigation of fuel use. There is limited research devoted to understanding how to estimate, and ultimately minimize fuel use in earthwork processes, prompting a detailed analysis into how factors related to equipment, operations, and worksite influence the consumption of fuel. These factors were investigated in a comprehensive review of literature related to earthwork emissions and fuel use. In seeking to address these inconsistencies found in reviewed fuel use tracking efforts, a set of recommendations for tracking influencing factors during earthworks fuel use studies was developed and outlined in detail. Additionally, a modelling approach was developed to accurately estimate fuel use, GHG emissions, activity duration, and cost in a variety of earthwork contexts.

Keywords: Construction
Discrete Event Simulation
Earthworks
Fuel use tracking
Greenhouse Gas Emissions
Advisor: Posen, Ira D
McCabe, Brenda Y
Functional Consequences of Altered Invariant Natural Killer T Cell Development and Effector Differentiation in the Vα14 Transgenic Mouse Model

Invariant Natural Killer T (iNKT) cells constitute a conserved population of unconventional T cells in mammals that regulate inflammation and immunity, through rapid and abundant production of cytokines and chemokines. iNKT cells differentiate into discrete functional subsets, iNKT1, iNKT2, and iNKT17, akin to conventional CD4 T helper cells. Mice that express a transgene for the canonical Vα14-Jα18 iNKT TCRα chain (Vα14 Tg) and harbour increased iNKT cell numbers have been widely used to study iNKT cells. In this thesis, our goal was to compare the development and functional response of iNKT cells in wild-type and Vα14 Tg mice. In Vα14 Tg mice, iNKT cells develop precociously and exhibit a strong bias towards the iNKT2 subset. Consequently, this bias impacts the ability of iNKT cells to prevent the growth of B16F10 melanoma tumours in Vα14 Tg mice. Therefore, past and future work involving these mice should be analyzed with caution.

Advisor: Mallevaey, Thierry
Research Perspectives on the Marginalization of Core French Teachers: A Qualitative Meta-analysis and Research Agenda for Elementary-level Ontario Core French Education

French as a Second Language (FSL) education is mandatory in Ontario. Research on elementary Core French education in Ontario has shown that its teachers are marginalized in practice. How this marginalization is positioned by researchers and what researchers recommend to end it are key foci of this thesis. Using a hybrid framework of complexity theory, critical theory, and language as right, the research perspective on the marginalization of Core French teachers is examined in order to form an agenda for future research. Dichotomy and variability in researchers’ positioning of the issue as well as in their recommendations are uncovered. A move toward grassroots-level activist research is highlighted, with a salient theme of agency and empowerment. A major implication of this research is the need to address the place of Core French within national bilingualism. Suggestions for future research include larger sample sizes, quantitative investigations, and interventionist research. L'enseignement du français langue seconde (FLS) est obligatoire en Ontario. La recherche sur l'enseignement du français de base au niveau primaire en Ontario ont montré que les enseignant.es sont marginalisé.es. Comment cette marginalisation est positionnée par les chercheurs et ce que les chercheurs recommandent pour y mettre fin sont les axes clés de cette thèse. En utilisant un cadre hybride de théorie de la complexité, de théorie critique, et de langage comme juste (Language-as-Right), les perspectives de la recherche sur la marginalisation des enseignants de français de base est examinée afin de former un agenda pour les recherches futures. La dichotomie et la variabilité du positionnement des chercheurs sur la question et aditionellement dans leurs recommandations sont découvertes. Un mouvement vers la recherche militante au niveau local est souligné, avec un thème saillant de l'agence et de l'autonomisation. Une implication majeure de cette recherche est la nécessité d'envisager la place du français de base dans le bilinguisme officiel du Canada. Les suggestions de recherche future comprennent des échantillons plus grands, des enquêtes quantitatives, et de recherche interventionniste.

Keywords: Core French
Education
Elementary Education
FSL
Ontario
Second Language
Advisor: Piccardo, Enrica
Telemedicine use Amongst Homeopaths and Naturopaths in Ontario, Canada

Telemedicine, in the form of online video consultations, holds great potential for the delivery of medical care. This research aims to investigate the extent of, rationale for, and the motivations for telemedicine use by homeopaths and naturopaths. State-regulated homeopaths and naturopaths in Ontario were surveyed. Survey questions captured telemedicine use, demographic and socio-economic data, and opinions regarding respondents’ motivations behind telemedicine use. The survey, conducted between October 2018-January 2019, had 183 homeopath and 366 naturopath respondents. Telemedicine consultations were performed by 65.6% of homeopaths and 32.5% of naturopaths in the previous 6 months. There were no significant differences between telemedicine users and non-users for gender, geographical location, and age. The best fit regression model of motivational factors comprised of attitude towards telemedicine and perceived ability to use telemedicine (Nagelkerke R-squared=.281). Telemedicine is used substantially by Ontario homeopaths. Attitude and perceived ability to use telemedicine were associated with telemedicine use.

Keywords: Complementary and Alternative Medicine
Health Services
Telemedicine
Advisor: Boon, Heather
A Computational Wind Engineering Framework for Studying Climate Change on High-rise Buildings in Dense Urban Areas

Structures in the built environment that are safe and serviceable under current wind loading conditions may experience problems in the coming decades as wind load characteristics get affected by rapidly changing climate. Given the high uncertainty in predicting future wind environment conditions, there is a need to formulate flexible adaptation strategies that mitigate climate change effects in urban regions. The present work proposes a multi-disciplinary framework to investigate and address the impact of climate change and the associated wind load effects on the built environment. As an example application of this framework, computational fluid dynamics (CFD) simulations are performed on a building located in downtown Toronto, under current and projected wind conditions to evaluate its response. The framework seeks to translate the range of predicted effects of climate change into actionable knowledge useful in the area of urban building design.

Keywords: climate change
Computational Fluid Dynamics (CFD)
k-ω turbulence model
Wind load
Advisor: Mercan, Oya
Investigating Mitochondrial Dysfunction in Bipolar Disorder: From Peripheral Biomarkers to Patient-Derived Induced Pluripotent Stem Cells

Bipolar disorder (BD) is a neuropsychiatric illness characterized by cycles of high and low mood states. The pathophysiology of BD is not fully understood but studies show mitochondrial dysfunction may play a role. Our objective is to interrogate the link between mitochondrial dysfunction and BD using patient blood samples. We observe an increase in serum lactate and a positive correlation between lactate and circulating cell-free mitochondrial DNA (ccf-mtDNA) in BD. Our meta-analysis found elevated ccf-mtDNA in patients with psychiatric conditions, suggesting evidence of mitochondrial stress. We reprogram patient blood cells into induced pluripotent stem cells (iPSC) that are capable in differentiating into neural progenitor cells and we show exploratory work differentiating these into cortical neurons that will be used to investigate the role of mitochondrial dysfunction in BD. We highlight our findings in support of mitochondrial dysfunction in BD and a future direction in understanding BD using these iPSCs.

Keywords: Bipolar Disorder
Induced Pluripotent Stem Cells
Lactate
Mitochondria
Advisor: Andreazza, Ana C
Quantification of Event-related Desynchronization under anAction-observation Prompting Paradigm

Brain-computer interface (BCI)-based rehabilitation techniques have recently shown promisefor restoring motor function in stroke survivors. BCIs detect the intent to move in brain signalsby identifying a pattern of neural activity called event-related desynchronization (ERD), andthen triggering the intended movement by some external modality, such as robotics. BCI-basedtherapy may be improved by enhancing the ability to detect ERD. This study examined theeffect of prompting various motor tasks with action observation (AO) as a paradigm for en-hancement of ERD. The magnitude, duration, and latency of ERD as well as the ability of aBCI to detect ERD were compared across several tasks with and without AO-prompting. Itwas found that AO-prompting reliably produced ERD in motor regions of the brain, but AO-prompted tasks were shorter in duration and smaller in magnitude than alternatively-promptedtasks used for comparison.

Keywords: Action Observation
Brain-Computer Interface
Electroencephalography
Event-Related Desynchronization
Rehabilitation
Advisor: Popovic, Milos R
Marquez-Chin, Cesar
Characterizing a Novel Mutation in MECP2 using an hiPSC Model of Rett Syndrome

Rett Syndrome (RTT) is a neurodevelopmental disorder in girls with mutations in the X-linked gene that encodes methyl-CpG-binding protein 2 (MECP2). Using neurons differentiated from patient-derived induced pluripotent stem cells (iPSC), I analyzed the MECP2 RNA levels, MECP2 protein levels, morphology, and extracellular electrophysiology of a novel L124W MECP2 mutation. My results show that L124W exhibits no change in RNA, protein, dendrite length, soma size, or electrophysiology but does show a subtle significant change in dendrite order and dendrite complexity. This is the first in vitro iPSC characterization of a mild RTT case. While developing a CRISPR/Cas9 protocol that will eventually genetically rescue the L124W mutation, I also generated the first iPSC knock-out lines for NEDD4L, a downstream target of MECP2. Overall, this work can be used to further elucidate MECP2 pathways and eventually identify treatments for RTT.

Keywords: dendrite complexity
iPSC
MEPC2
neurodevelopmental
rett syndrome
stem cell
Advisor: Ellis, James
Clinical Outcomes and Capacity to Consent to Electroconvulsive Therapy in Patients with Schizophrenia and Patient Experience with Legally Mandated Treatment

Background: Schizophrenia is one of the most debilitating psychiatric illnesses and affects 1% of people globally. Objectives: To evaluate the experiences of patients with schizophrenia who were legally mandated to treatment. To evaluate the clinical outcomes for incapable and capable patients with schizophrenia who were treated with electroconvulsive therapy (ECT). Methods: For the first objective, we searched 4 electronic bibliographic databases and completed a systematic review of qualitative studies. For the second objective, we completed a chart review of all inpatients with schizophrenia who were treated with at least one acute course of ECT. Results: Patients who were legally mandated to receive treatment reported both positive and negative experiences. Incapable and capable patients experienced treatment response with limited cognitive impairment. Conclusions: Addressing patients’ concerns could lead to better attitudes towards legally mandated treatment. ECT appears to be a safe and effective procedure regardless of capacity status.

Keywords: Electroconvulsive Therapy
Legally Mandated Treatment
Schizophrenia
Advisor: Blumberger, Daniel M
Effect of Cognitively Engaging Physical Activity on Executive Functions in Children

The purpose of this study was to investigate whether cognitively engaging physical activity (PA) impacts executive functions (EFs), and whether affect and fitness mediate or moderate this relationship. A randomized controlled trial was utilized to assess changes in EFs following a 20-minute Dual Task, PA Task, or Cognitive Task. EFs were assessed using the Stroop Task, Trail Making Task, and Forward Working Memory Task. 38 children (Mage=11.95 years, SD=0.49) participated. Repeated measures ANOVA showed significant main effects for time on inhibition scores (p

Keywords: children
cognition
executive functions
physical activity
Advisor: Cairney, John
Latent Modelling of Urban Data: Enriching Computational Analysis in Urban Studies by Applying Novel Methods

Within Urban Studies, increasing appetite for computational analysis has produced research reliant on a limited set of methods. This has resulted in a lack of exploration of newer methods which may be applicable. These methods restrict the scope of research by failing to consider nuance which can be modeled in contemporary methods. Here we look to demonstrate how latent variable models empower the field to draw nuanced conclusions from big data. First, we show that New York City income can be better predicted with a supervised latent variable model than with existing techniques. Second, we show that information about neighbourhood change can be extracted from social media data using latent embeddings. Finally, we present a method for learning disentangled embeddings for big data. The success of latent variable models in all of these applications demonstrates how the study of urban change can expand in scope by employing more nuanced approaches.

Keywords: Computational Sociology
Latent Methods
Machine Learning
Mixed Integer Linear Programming
Representation Learning
Urban Studies
Advisor: Sanner, Scott
FDTD-based Modeling of Diffuse Scattering in 5G Millimeter-wave Frequencies and Integration with Ray Tracing Models

With 5G communication systems along with several radar and imaging technologies employing millimeter-waves (mm-waves), accurately modeling wave propagation at these frequencies is as important as ever. At mm-wave frequencies, mm-size anomalies on the surfaces of indoor and outdoor environments can cause the power to spread in many directions. That can significantly affect link budget analysis in wireless channels. In this thesis, a two-stage solution to this problem is proposed. First, reflection and transmission through rough slabs, such as doors, walls, and windows, are modeled with the FDTD method. The results indicate the influence of roughness; either reducing the magnitude of the reflected and transmitted waves, or (most importantly) generating diffuse components. In the latter case, the surface effectively acts as a secondary source, whose pattern is computed by full-wave analysis. Then, this pattern is embedded in a ray-tracer, enabling the computation and tracing of diffuse field components.

Advisor: Sarris, Costas D
Brain Protection for Aortic Arch Surgery: A Randomized Trial of Axillary Versus Innominate Artery Cannulation – The ACE CardioLink-3 Trial

Neuroprotection remains the cornerstone of successful aortic surgery however there is no consensus as to the optimal strategy. We compared the safety and efficacy of innominate to axillary artery cannulation for delivering antegrade cerebral protection (ACP) during proximal aortic arch surgery. This randomized study allocated 111 individuals to either innominate or axillary cannulation. The primary safety outcome was the appearance of new severe ischemic lesions on the postoperative compared with the preoperative diffusion-weighted (DW)- MRI. The primary efficacy outcome was the between-groups difference in total operative time. 102 individuals were included in the primary safety analysis. New severe ischemic lesions occurred in 19 participants (38.8%) in the axillary vs. 18 (34%) in the innominate group (p for non-inferiority = 0.0009). Total operative times were comparable (p for superiority = 0.47). Our DW-MRI assessments indicate that ACP with innominate cannulation is safe and affords similar neuroprotection to axillary cannulation during aortic surgery.

Keywords: aortic surgery
axillary artery
cognitive dysfunction
diffusion weighted MRI
innominate artery
neuronal biomarkers
Advisor: Verma, Subodh