VictorJuiz/thesis huggingface dataset:
Visual Post-hoc Explanation of Convolutional Neural Networks Via Attribution-based Perturbation
Keywords: Artificial Intelligence
Computer Vision
Deep Learning
Explainable AI
Image Processing
Machine Learning

Visual explanation algorithms are a subset of post-hoc solutions in Explainable AI that aim to open the black-box of cumbersome models utilized for image recognition tasks. These algorithms aim to determine the features in each given input data that contribute the most to the model's prediction. Producing high-resolution and class-discriminative visual explanations that accurately represent the evidence leading the model to make its predictions is a common challenge in prior visual explanation solutions. This thesis proposes a novel CNN-specific visual explanation algorithm that circumvents these limitations by extracting and aggregating semantic and spatial information from various layers of CNN. The performance, complexity, and compatibility of our proposed algorithm are analyzed through thorough comparisons with state-of-the-art methods in large-scale experiments on natural scene object recognition and visual anomaly inspection applications. Furthermore, this thesis introduces a small-scale benchmark for validating the performance of visual explanation methods on a pattern classification task.
Using Ice and Sediment Cores to Quantify Climate-warming Induced Inputs of Legacy Mercury to Lake Hazen, Nunavut
Keywords: Arctic
Climate change
Contaminants
Ice core
Methylmercury
Total Mercury

Mercury (Hg) is a globally dispersed contaminant that can bioaccumulate and biomagnify in food-webs. This research uses a unique combination of measurements in an ice core and a sediment core collected within the same watershed (Lake Hazen, Nunavut) to determine how the relative importance of Hg inputs from atmospheric, glacier and terrestrial sources has changed over the last century. Hg accumulation in Lake Hazen sediment began increasing dramatically in the mid- 1990s, exhibiting a decoupling from atmospheric sources (as estimated from the ice core record), due to the increased importance of remobilized terrestrial Hg inputs to Lake Hazen. Increasing glacier melt and permafrost thaw slumping have increased the delivery of catchment Hg, via glacial rivers, into Lake Hazen. These results show that climate change is likely to slow the recovery of glacierized Arctic watersheds from Hg contamination, countering the anticipated benefit from recent international efforts to reduce anthropogenic Hg emissions.
Creating and Evaluating an Audio Detection Interface to Guide Families in Musical Play and Learning with Low-cost Musical Instruments at Home
Keywords: Acoustic signal processing
Audio classification
Classification algorithms
Education technology
Machine learning deployment
Music information retrieval

Musical play and learning are fundamental for child development, yet the opportunities are not the same for children with disabilities. Our overarching goal is to provide more opportunities for home-based musical play and learning for children who may not have access to teacher-led music programs. This thesis describes the design and evaluation of an audio detection interface which can classify low-cost, early childhood musical instruments such as a tambourine, shaker, and castanet. This interface achieves over 84% accuracy using an approximate 93 ms window length to in-lab variants across all 3 instrument families. This interface was deployed and tested with twelve families in a music application called Bootle Band. In this usability study, we observed an average accuracy of 73% [SD=6.8%] in family’s household. We found that children’s play time and responses on the Fun Toolkit Questionnaire were equivalent when the game was played with real-life instruments versus a typical touchscreen. This suggests that the performance of our audio detection interface was sufficient to support playability in real-world settings. This thesis lays the groundwork for a music education application that interacts with real-world musical instruments and is accessible to families and their children, with and without disabilities.
Probing the Neural Oscillatory Patterns Associated with Incidental Learning: A MEG Study
Keywords: cortical learning
incidental learning
MEG
prior knowledge

Cortical learning is a hippocampal-independent neocortex-dependent memory consolidation process. Cortical learning could be promoted by prior knowledge. Research found hippocampal-amnesia patients, including HM, are able to acquire new semantic knowledge if it relates to prior knowledge. This study examined the underlying neural processes that are associated with cortical learning of semantic knowledge with an incidental learning paradigm and MEG. We found cortical regions in visual association areas, multi-modal areas and paralimbic areas associated with incidental learning. We also found increased alpha and gamma power in cortical regions at the end of learning, and last but not least, we found cortical regions activation power at the end of learning positively correlated with learning accuracy. This study indexed the cortical regions and neural oscillatory processes that are associated with cortical learning and provide ground for future studies to probe deeper into the neural mechanisms that support cortical learning. At the same time, our study provides new perspectives on the theories of semantic representation.
Interrogating the Small-cell Lung Cancer Methylome using Liquid Biopsies
Keywords: cfMeDIP-seq
DNA methylation
epigenetics
liquid biopsy
small cell lung cancer

Small cell lung cancer (SCLC) is one of the most aggressive types of cancers. Despite being initially responsive to treatment, most patients relapse. Currently it is not clear how such mechanisms of resistance develop, though recent evidence suggests epigenetic mechanisms may be involved. In this study the cell-free methylated DNA immunoprecipitation (cfMeDIP-seq) assay was performed on blood from SCLC patients, healthy donors, and novel circulating-tumour cell derived xenograft (CDX) models. SCLC patients appear to have a distinct methylation profile compared to healthy donors. CDX models derived from SCLC patients also appear to be highly similar, highlighting their future use for biomarker development and discovery. Finally, consensus clustering on SCLC patient methylation profiles shows three distinct methylation-defined subtypes. These subtypes appear to have differential methylation of Wnt-signalling genes, a pathway known to be dysregulated in relapsed SCLC.
Analysis of Adenosine A2A Receptor Conformational States by Stationary Phase EPR Spectroscopy
Keywords: A2AR
DEER
EPR
GPCR

The adenosine A2A G protein-coupled receptor (A2AR) plays an essential role in many biological functions linking extracellular signals to intracellular events. A2AR adopts various conformational states that are stabilized depending on ligand and G protein. To study A2AR’s conformational equilibria, a stationary phase pulsed electron paramagnetic resonance (EPR) spectroscopy platform was developed for characterizing the immobilized receptor on cobalt resin. This platform provides a high local A2AR concentration and comparable results to the traditional in-solution measurements. With this method, A2AR transmembrane helix (TM) 6 was found to adopt four states with a distinct outward displacement of TM6, while TM7 adopts at least three states. The partial agonist preferentially stabilizes an active intermediate state of TM6 and an inactive state of TM7. These results may stimulate further studies on more intricate aspects of A2AR’s structural dynamics, while this platform may be integrated with other advanced technologies for similar protein research topics.
Territory Acknowledgment, Unacknowledgement, and Misacknowledgement: A Haunting
Keywords: Haunting
Indigenous education
Place-based education
Reconciliation
Territory Acknowledgement
Visiting

This thesis analyzes conversations on the practice of territory acknowledgements, particularly as they are practiced in academic spaces, arts spaces and by organizations and institutions. Themes that are drawn from these conversations and attended to include: territory acknowledgements as distinctly not “traditional protocol”, territory acknowledgements and the politics of recognition (what is their purpose?), the labour of territory acknowledgements (who is doing them, and who are they for?) and the exhausting repetition of territory acknowledgements (how often?). Territory acknowledgement (as well as unacknowledgement and misacknowledgement) is then removed from the framework of reconciliation and theorized instead as haunting. The author posits, if reconciliation is dead, is territory acknowledgement a haunting? Finally, visiting practices are introduced as alternative ways to make relationships to place not based on possession or ownership. This final chapter considers the positionality of being a visitor, an ethics of care for visiting, and offers examples of visiting practices.
Evaluating the Role Of Hippocampal Inputs to the Mammillary Nuclei In Spatial Memory
Keywords: Allocentric Navigation
Egocentric Navigation
Hippocampus
Mammillary Bodies
Spatial Memory
Spatial Navigation

This study sets the stage for an investigation into the role of subiculum efferents to the mammillary bodies (MB) in spatial navigation. We characterized baseline behaviour of male and female C57BL/6 mice (n = 11) in an egocentric and allocentric spatial escape assay using a Barnes maze. Egocentric testing revealed escape to a previously memorized shelter location can be encoded after a brief exploration under red light condition and that an animal’s position relative to the shelter is constantly updated for goal-directed flight. Allocentric testing revealed mice can encode a shelter location to effectively utilize distal cues for goal-directed escape. Finally, anatomical tracing experiments reveal MB-projecting subicular neurons are organized topographically such that axons originating from the dorsal or ventral subiculum terminate in the dorsal or ventral regions of the medial MB respectively. Parallel pathways may represent a functional differentiation of subicular inputs to the MB.
The Impacts of the Great Recession on Systolic Blood Pressure in the United States: A Population Health Perspective
Keywords: Decomposition methods
Economic recession
Great Recession
Social determinants of health
Systolic Blood Pressure

Despite the importance of socioeconomic status for health, there are inconsistent conclusions over the health impacts of the Great Recession. One potential reason is that smaller, more pervasive, individual-level changes in health could have occurred and pushed populations towards poorer distributions of health overall, but no studies have used a distributional approach. Thus, this dissertation asks: Can distributional perspectives provide additional insights into the health impacts of the Great Recession? In conducting three studies, I find: i) heterogeneity among the methods used in the literature, but none appropriate for distributional outcomes; ii) a decomposition analysis of distributional outcomes provides more insights than that of mean outcomes; and iii) that while mean systolic blood pressure (SBP) improved for most American adults, a distributional approach reveals that SBP may have worsened overall for some. This work applies a distributional perspective to provide more comprehensive insights into the health impacts of recessions.
Oscillatory Basis of Working Memory Function and Dysfunction in Children with Epilepsy
Keywords: Epilepsy
High-frequency oscillations
Hippocampi
Interictal epileptiform discharges
Neural oscillations
Working memory

Working memory (WM) deficits are prevalent in children with epilepsy. The causes of these impairments remain elusive. In the current work, we leveraged intracranial recordings from the hippocampi and epileptogenic zones of children with epilepsy performing a WM task to probe the oscillatory basis of WM function and dysfunction in children with epilepsy. First, we demonstrated that low-frequency phase resetting of hippocampal oscillations occurred in response to stimulus presentation, and the precision of the phase angle was associated with optimal WM processing, as indexed by faster reaction times. Second, enhancement of coordinated interactions between the hippocampi and WM-related networks occurred concurrent to phase resetting. Finally, the occurrence of transient epileptic activity was associated with prolonged reaction times, attenuated low-frequency hippocampal phase resetting, and alterations in interregional low-frequency connectivity. This dissertation presents evidence that may guide the development of future treatments aimed at improving memory function in children with epilepsy.
Use of High-concentration Chlorhexidine (Prevora®) for Reduction in ‘Need for Surgery’ in Patients with Periodontitis
Keywords: Chlorhexidine
Periodontitis
Periodontology
Prevora
Treatment
Varnish

AbstractIn this clinical study, we studied the effects of treating patients with Prevora® following initial scaling and root planing (SRP) as an adjunct in order to assess whether this treatment would improve clinical disease parameters beyond SRP alone. Our results showed that there was a statistically significant reduction in BOP from 32.8% to 22.9%, reduction in mean probing depths (PD) of 0.25 ± 0.01mm and a gain in mean clinical attachment level (CAL) of 0.27 ± 0.02mm. However, for sites with PDs of 4-6mm, an average reduction of 0.73 ± 0.07mm was observed; for sites with ≥ 7mm PD, an average reduction of 1.11 ± 0.48mm. More importantly, we found a significant decrease in the number of teeth that would have required surgical treatment from 111 teeth to 58 teeth; a 48% decrease in the total number of teeth that would have required surgical treatment.
Effects of Maternal High Fat Diet and Milk-derived Exosome Supplementation on DNA Methyltransferase 1
Keywords: DNA methyltransferases
Epigenetic programming
Maternal obesity
Microglia cell culture
Milk-derived exosomes
Neurodevelopment

Maternal high fat diet (mHFD) exposure during perinatal life shapes offspring’s neurodevelopment trajectories. mHFD also influences the bioactive composition of maternal milk, including milk-derived exosomes (MDEs), nanovesicles that transport functional microRNAs (miRNA). miRNA-148/152 regulate DNA methyltransferase-1 (DNMT1), enzyme that catalyzes DNA methylation modifications, which in turn downregulates fat-mass and obesity-associated (Fto) gene via promoter hypermethylation. The main objectives of this thesis were: 1) examine the effects of mHFD exposure on DNMTs and Fto expressions in postnatal day 7 rats and 2) investigate MDE-supplementation effects on DNMTs and Fto expressions using a human microglia cell line. DNMT1 and Fto transcript abundances remained unchanged in the PVN and ventral hippocampus but decreased in the retroperitoneal fat of mHFD offspring. In microglia, MDE-supplementation resulted in increased DNMT1 expression only. These findings indicate that DNMT1 and Fto exhibit tissue-specific sensitivity to mHFD exposure in neonates, and that DNMT1 is altered by MDE-supplementation in microglia.
Self-supervised Semantic Learning of LiDAR Point Clouds for Large-scale Scene Understanding
Keywords: Deep Learning
Point Cloud
Robotics
Semantic Learning

Semantic segmentation is a challenging task in the robotic vision community to classify various objects in a scene. While recent works employ supervised learning approaches using hand-annotated examples, these training samples are often costly to obtain. In this thesis, we present a self-supervised semantic learning method for large-scale scene understanding. Our offline method retrieves point cloud annotations by combining a mapping and localization solution with ray-tracing algorithms. Through multi-session navigation experiences in the same environment, our method labels points into four semantic classes: ground, non-movable, long-term movable, and short-term movable. These semantic labels allow us to train a semantic segmentation network without any hand annotations, which can then be used online. For qualitative and quantitative analysis, we demonstrate our method on a simulation dataset. We also provide a qualitative evaluation of a real-world dataset. Furthermore, by semantically filtering out movable points, results show that our method improves existing localization performance.
Less Than the Sum of its Parts: Viewing Parts of Faces Increases Subsequent Attractiveness Ratings of the Original Wholes
Keywords: attractiveness
face perception
holistic processing

People’s general expertise with faces leads them to quickly process them as wholes rather than as collected sums of their parts. Here, I tested whether judgments of facial attractiveness (one of the most socially consequential attributes of a face) change when such holistic processing is disrupted. Participants in three studies rated faces as more attractive after perceiving their constituent features separately. Repeated exposure to the features and local-processing dominance did not explain this benefit, which improved ratings of attractive faces more than unattractive faces. Disruptions of holistic processing thus positively affect how perceivers view facial attractiveness.
The Role of Geospatial Factors and Distance on Timely Physician Follow-up after a First Hospitalization Discharge with a Diagnosis of a Schizophrenia Spectrum Disorder: A Retrospective Population-based Cohort Study
Keywords: Distance
Geospatial
Hospitalization
Quality of care
Schizophrenia
Schizophrenia spectrum disorders

Timely follow-up after a hospitalization for a schizophrenia spectrum disorder (SSD) is an important quality indicator. We examined the proportion of physician follow-up within 7 and 30 days of a first hospitalization discharge for a SSD by health administrative region in Ontario. The effect of distance between a person’s residence and discharging hospital on follow-up was estimated using multilevel models. We identified 6,382 incident hospitalizations for a SSD between January 1, 2012 and March 30, 2019. Only 14.2% received follow-up care with a psychiatrist within 7 days and 49.2% received follow-up care with a psychiatrist within 30 days. These proportions varied between regions. Although distance was not associated with psychiatrist follow-up within 7 days of discharge, increasing distance was associated with reduced odds of follow-up within 30 days of discharge. Geospatial factors may impact post-discharge care and should be considered in further evaluation of quality of care in this population.
Machine Learning Models for Traffic Flow Prediction
Keywords: Machine Learning
Traffic Prediction

Many methods of traffic prediction have been proposed over the years, from the time series models over 40 years ago to the latest deep learning models today, which prompts the need for an in-depth comparison and the critical question of whether deep learning offers significant improvements over the traditional methods. This thesis addresses this situation by systematically evaluating the different methods. We first procure a diverse set of traffic data from simulation software and real-world sensors. We then compare the different methods and perform further analysis on the latest deep learning models. Finally, we also consider the task of predicting long-term traffic up to a week in advance. Overall, we demonstrate that deep learning models are effective in short-term prediction. However, the classical random forest regression provides the best performance in both short-term and long-term prediction, which suggests that there is still room for improvement for deep learning methods.
The Cognitive Processes and Neural Regions Supporting Unitization
Keywords: aging
amnesia
frontal lobe
memory
relational memory
unitization

Hippocampal damage or dysfunction can result in impairments in relational memory (RM), which is the ability to bind distinct elements into a lasting memory representation. The cognitive strategy, unitization, can mitigate RM impairments by fusing objects into a single unit through a physical interaction. The transverse patterning task was used to determine whether the unitization strategy supported memory above-and-beyond effects of extended practice (EP), and whether strategy transfer occurred. Healthy older adults benefitted from extended practice, and unitization use surpassed EP benefits. Five older adult cases with varying damage to the ventromedial prefrontal cortex, and medial temporal lobe and extended regions, did not benefit from strategy training or EP; suggesting potential roles for these regions in RM and unitization. Neither population showed transfer. Relational memory impairments may be remediated through strategy interventions by aligning with one’s cognitive and neural profiles, and in conjunction with extended practice.
Driver Scanning Behavior at Urban and Suburban Intersections: An On-road Approach
Keywords: Eye tracking
Glance allocation
Human factors
Instrumented vehicle
Intersections
Vulnerable road users

The safety of Vulnerable Road Users (VRUs), such as pedestrians and cyclists, is highly jeopardized at intersections, with driver inattention being a leading cause. It is not well known (1) where drivers distribute their visual attention at real intersections or how this impacts VRU safety, and (2) how driver attention interacts with different intersection elements from an on-road perspective. This thesis utilizes rich instrumented vehicle data from 26 experienced drivers (13 cyclists and 13 non-cyclists) to quantify drivers gaze distributions at signalized right turns. Key findings include that drivers spent the most time glancing at relevant pedestrians, irrespective of signal status, and that driver attention was heavily skewed toward leftward traffic during red lights. Additionally, this thesis outlines an instrumented study which will examine the effects of Guelph’s suburban road infrastructure on driver scanning behaviour. Reported findings can benefit broad road safety perspectives from urban planning, collision forensics, and more.
Numerical Modelling and Testing of Recovery Boiler Deposits to Investigate Fracture by Sootblower Jet Impingement
Keywords: Deposits
Finite Element Analysis
Fracture toughness
Recovery Boiler
Sintering
Sootblowing

Steam is used to remove deposits that build up on the heat exchanger tubes in a boiler. Fouling causes a reduction in boiler efficiency, and costly sootblower steam is used to remove deposits. A fundamental study of deposit break-up and crack propagation at boiler temperatures was carried out to improve sootblower efficiency. To analyze fracture of deposits, the material properties of a deposit, mainly the fracture toughness KC, needs to be measured. Moreover, the work of fracture, WF, is used to compare the energy required to fracture brittle deposits versus ductile deposits. Finally, the deposits were modelled in FEA to investigate the effects of surface pits on amplifying the maximum principal stresses created by a jet. A small notch was introduced in the model to investigate crack growth through the deposit under jet impingement using the failure criterion K > KC.The fracture toughness of a deposit declined as the temperature of the testing furnace increased due to the decrease in peak load. The deposit samples tested experienced a brittle to ductile transition at 450°C. Ductile deposits (740 J/m2) required four times more energy to fracture compared to a brittle deposit (185 J/m2). The increased WF resulted from the ductile deposits deforming under force, requiring more energy to fracture. The numerical model indicates that a pit significantly amplifies the maximum stresses leading to small microcracks forming upon jet impingement. The fracture model of a microcrack shows that brittle deposits will fail when the stress intensity factor at the crack tip, K is greater than the critical stress intensity factor KC.