VictorJuiz/thesis huggingface dataset:
Response of Retinal Ganglion Cells to Electrical Stimulation: From Prosthesis to "Seeing'"
Keywords: Artificial Vision
Electric Stimulation
Mathematical Model
Retinal Bipolar Cells

Electric stimulation is a promising method of restoring vision for those suffering from retinal degenerative diseases. To understand how retinal prostheses restore vision, computer models were developed to approximate the visual pathway. First, the electric potential generated by the subretinal implant within the retinal tissue was solved using Maxwell’s equation through finite-element method. Next, the primary neural response was calculated through the implementation of a recently proposed model of the retinal bipolar cell where the Hodgkin-Huxley equations and the cable model were solved for ten ionic currents. Finally, the entropy theory was introduced to calculate the ganglion response using the output of the bipolar response. For the first time, aspects of visual performance such as brightness and temporal response can be estimated for a subretinal implant. While these techniques have been developed to predict the biological response of any subretinal implant, much of the work presented here has been tailored towards a novel, passive implant developed by collaborators at Okayama University called the OUReP.
Using Assistive Technology To Facilitate Idea Generation in Writing For School Aged Children
Keywords: Assistive
Education
Psychology
Technology
Writing

The purpose of this study is to investigate the usefulness of idea generation software as an assistive technology for writing. Idea generation refers to the organization of thoughts into coherent words and sentences. A randomized controlled study was conducted which compared four conditions: no intervention, technology intervention, strategy intervention, and combination of technology and strategy intervention. Thirty-two grade four to seven typical learners completed the study. They were referred by their parents or teachers as they exhibited writing challenges. Each completed five minute paragraph writing exercises. Participants in the technology and strategy groups showed a significant improvement in written expression relative to students with no intervention. Students who used both interventions at the same time did not show the same positive effects relative to the students without support. Areas for future research and applied use in education are discussed.
Exploring Pediatric Volition among Children with Autism Spectrum Disorder in an adapted Robotics Program
Keywords: Autism Spectrum Disorder
Children
Youth
LEGO® Robotics
Pediatric Volition
Play

Children with autism spectrum disorder (ASD) often have fewer opportunities to participate in play than typically developing children because of their tendencies for repetitive play behaviour and independent play types. The Holland Bloorview (HB) FIRST® (For Inspiration Recognition of Science and Technology) robotics program embeds technology into a playful activity. This study included one main objective and three exploratory objectives. The main objective was: (1) to measure pediatric volition (i.e., score pediatric volition through a validated measure) among children with ASD participating in an adapted robotics program. The exploratory objectives were: (1) to assess off-task behaviours among children with ASD during an adapted robotics program (i.e., counting number of off-task behaviours during the program); (2) to describe volitional behaviour among children with ASD in an adapted robotics program; and (3) to describe off-task behaviour among children with ASD during an adapted robotics program. This study used a mixed-method design with a pediatric volitional questionnaire, video recordings, and structured observations of 6 consecutive workshops (2 hours each). Analysis of data from the Pediatric Volitional Questionnaire indicated that pediatric volition showed no statistically significant change in the total median score from the beginning to the end of the robotics program. However, observations of children highlighted patterns of showing interest and enjoyment while participating in the robotics program. In addition, the total number of off-task behaviours had a statistically significant decrease from the beginning to the end of the adapted robotics program. Although children demonstrated off-task behaviour, these behaviours were observed less frequently at the end of the program. The findings highlight that participating in a robotics program provides the potential to observe children’s volitional behaviours, and also may reduce their off-task behaviour.
Beyond Busfield: Primary Care, Youth Depression and Pharmaceuticalisation
Keywords: adolescent
antidepressant prescribing
medicalisation
pediatric
pharmaceuticalisation
primary care

The use of antidepressants in the paediatric population has increased dramatically in recent years, but there are a number of concerns with prescribing antidepressants to the paediatric population. Joan Busfield’s theory of pharmaceuticalisation tries to explain why this is the case; suggesting physician’s roles as “gatekeepers” for pharmaceutical products is weakening. I conducted qualitative interviews with 11 primary care physicians and 2 paediatricians and used Thematic Analysis to analyze my data. The major finding of this study was that Busfield’s theory is inadequate to explain the rise of antidepressant prescribing in adolescent depression. I provide an alternative explanation that primary care physicians and paediatricians prescribed antidepressants when it was decided upon through shared decision-making with the patient. This finding challenges Busfield’s account of pharmaceuticalisation, and indicates that her theory may need to be refined for clinical situations where there is a lack of strong evidence for pharmacotherapy.
Exploitation of Stragglers in Hierarchical Coded Matrix Multiplication
Keywords: Coded computing
Distributed computing
Stragglers

In distributed computing systems slow-working nodes, known as stragglers, can greatly extend the finishing time. Coded computing is a technique that enables straggler-resistant computation. This thesis first develops a conceptual framework that unifies existing coded matrix multiplication techniques. In this framework the division of work amongst workers in different coding techniques is presented as a cuboid partitioning problem. Building on this framework, we then propose three methods of hierarchical coded computing: Bit-Interleaved Coded Computing (BICC), Multilevel Coded Computing (MLCC), and Hybrid Hierarchical Coded Computing (HHCC). In hierarchical coding the workers process a sequence (a hierarchy) of ordered subtasks and transmit per-subtask results to the master as they are completed. Such hierarchical design leads to exploit the work of stragglers and allows the fast workers to contribute even more to the overall computation. We prove both theoretically and experimentally that hierarchical coding improves the finishing time when compared with non-hierarchical coding.
Seasonal Variation in the Critical Thermal Maxima and Thermal Safety Margin of Redside Dace at its Northern Range
Keywords: Critical thermal maxima plasticity
Seasonal acclimation
Short-term acclimation
Thermal history
Thermal performance curve

Understanding seasonal changes in the thermal performance of fishes is necessary to identify optimal thermal habitat, which can provide insight into how species distributions may shift under climate change. Using an experimental thermal chamber in the field, I investigated the effect of short- and long-term acclimation, and body size on the critical thermal maximum (CTmax) and thermal safety margin (TSM) of wild-caught Redside Dace (n = 169) in Two Tree River, Ontario. Streamside CTmax trials were used to identify the maximum temperature at which Redside Dace maintain equilibrium, providing a powerful tool for understanding how thermal stress affects individual performance. CTmax and TSM of Redside Dace were sensitive to changes in temperature, regardless of season, suggesting that temperature pulses caused by climate change can impose negative fitness consequences year-round. The results provide insight into the thermal performance of Redside Dace that, to date, has been difficult to assess due to the species’ rarity and lack of suitable streamside protocols.
Combination of MRI, Histochemical, and Biochemical Analyses Reveal Specific Structural Changes in the Murine Cervix during Term and Preterm Labor
Keywords: cervix
MRI
pregnancy
preterm birth
structure
uterus

A better understanding of anatomical and structural changes in the murine cervix throughout gestation may improve detection of preterm birth, which is a leading cause of infant morbidities world-wide. I hypothesized that there are microstructural differences between the upper and lower parts of the cervix (endocervix and ectocervix, respectively) and that they undergo changes to facilitate labor. The hypothesis was tested by investigating the cervix from non-pregnant and pregnant CD-1 mice that delivered at term and preterm by histology, immunohistochemistry, MRI, and RT-qPCR. Our results showed that the endocervix had more muscle cells, smaller amount of hydration, and higher proportion of tense collagen fibers. Three zones of the endocervix were revealed, i.e. an inner longitudinal collagenous layer, a middle circular muscular layer, and an outer longitudinal muscular layer. During labor, structural integrity of the endocervix was lost making it an important marker for impending delivery at term and preterm.
The Role of Attachment Style in Resolution of Self-criticism Process
Keywords: attachment
depression
emotional focused therapy
outcome
process
resolution of self-criticism

Clients’ attachment styles have been shown to be a consistent predictor of therapeutic processes. However, how clients’ attachment styles impact the resolution of self-criticism, an important process in emotional-focused therapy (EFT), is not well understood. The main objective of this study was to examine whether the resolution of self-criticism mediates the relationship between clients’ pre and post therapy attachment style. To this end, data from a randomized control trial (RCT) conducted by Watson et al. (2003) was used. Results indicated that clients may engage and successfully complete in-session resolution of self-criticism irrespective of their pre-therapy attachment style. Moreover, although clients’ attachment styles change over the course of therapy, resolution of self-criticism did not contribute to changes in post-attachment style. However, resolution of self-criticism contributes to clients’ self-reported post-session changes and these changes predict improvement at the end of therapy. Theoretical and clinical implications are discussed.
Pipelined Training with Stale Weights of Deep Convolutional Neural Networks
Keywords: Deep Learning
Pipelined Training

Existing approaches that partition a convolutional neural network (CNN) onto multiple accelerators and pipeline the training computations avoid or limit the use of stale weights, and they either underutilize accelerators or increase memory footprint. We explore the impact of stale weights on the statistical efficiency and performance in a pipelined backpropagation scheme that maximizes accelerator utilization and keeps memory overhead modest. We use LeNet-5, AlexNet, VGG and ResNet, and show that when pipelining is limited to early layers in a network, training with stale weights converges and results in models with comparable inference accuracies to those resulting from non-pipelined training. However, when pipelining is deeper in the network, inference accuracies drop signicantly. We propose a hybrid training scheme to address this drop. We demonstrate the performance of our pipelined backpropagation on 2 GPUs achieving speedups of up to 1.8X over a 1-GPU baseline, with a small inference accuracy drop.
Towards Integrated 3D Printing as an Industrial Manufacturing Process
Keywords: 3D Printing
Flexible Electronics
Functional Material
Functionally Graded Material
Nanomaterial
Polymer Composite

3D printing is transitioning from a rapid prototyping tool to an industrial production technology. State-of-the-art 3D printing technologies manufacture objects with a wide range of materials. Currently, there is no integrated technology to print dissimilar materials within the same part. Bonding dissimilar parts creates interfaces with debilitating stress concentrations. Overall, part performance is compromised. Therefore, there is value in 3D printing multi-material and functionally graded objects. In this thesis, we propose a novel binder jetting approach using nanoparticle inks to build composites. The approach deposits nanoparticle inks containing physical/chemical bonding agents to bind polymer powders into an object; by switching between different nanoparticle inks (metal/graphene/conductive polymers), a functionally graded composite with non-distinct interfaces is built. To this end, a novel system for robustly ejecting nanoparticle ink is developed, and a graphene oxide (GO) ink was formulated and printed onto polyvinyl alcohol (PVOH) powder to build a 0.5vol% GO/PVOH composite.
Athletes' Perceptions of Pre-game Rituals in Open-skill Sports
Keywords: Performance Ritual
Pre-Game Ritual
Sport Ritual

Performance rituals have long been a topic of study in sport psychology. However, previous research has focused on closed-skill tasks and employed methodologies that make it difficult to capture athletes’ perspectives of these behaviours. The purpose of this study was to explore the perceptions of open-skill sport athletes regarding their performance rituals. Nineteen high-performance athletes participated in semi-structured interviews. Interview transcripts were thematically analyzed. Participants described their perceptions of the structures and functions of their performance rituals. These findings contribute to a more nuanced understanding of how athletes perceive their performance rituals. Exploring this phenomenon through a critical-realist lens allowed for the relevant components of pre-existing theoretical representations of rituals to be compared to the lived experiences of the athletes who engage in them.
An Examination and Analysis of the Ownership, Funding and Quality Assessment Structures of the Public and Private Laboratory Sector in Ontario
Keywords: health policy
healthcare
laboratory
Ontario
private
public

Purpose: The thesis questions aim to address how the Ontario laboratory sector is organized, with a focus on aspects of funding, ownership structure, access to care, health human resources and quality assurance. Methodology: A case study design used 15 semi-structured interviews and a document review. Results: Lab funding models did not incentivize unnecessary testing in hospital, for-profit or Public Health Ontario labs. Quality assessment of lab testing was generally well measured for the analytical phase. The mechanisms that are available to ensure that private for-profit labs adhere to societal goals include regulation of professionals, maintaining a rigorous quality assurance program, and updating the Schedule of Benefits-Laboratory Sector regularly. Conclusion: Legislation and funding models are changing for labs to reflect modernization due to technology and higher quality standards. All categories of labs need to work with government and regulatory bodies to ensure decisions prioritize the patient and the health care system.
Weakly-supervised Semantic Segmentation in the Multi-class Setting across Different Image Domains
Keywords: Computational Pathology
Self-Supervised Learning
Semantic Segmentation
Weakly-Supervised Semantic Segmentation

Weakly-supervised semantic segmentation from image-level annotations has been proposed for segmenting natural scene images and this performs well compared to full supervision with pixel-level annotations, which are harder and slower to obtain. However, this is a challenging problem because image labels lack location-specific information to learn object extents. Weakly-supervised semantic segmentation is unexplored in other image domains, such as histopathology and satellite imagery and it is unknown whether different methods are needed for these images. This thesis proposes a novel weakly-supervised semantic segmentation algorithm for histopathology images and explores its performance compared to state-of-the-art methods developed for natural scene images. The compatibility of each method for different image domains is analyzed and this thesis analyzes the effect of classification network choice, the self-supervised learning approach, and class co-occurrence on segmentation performance.
Memory-based Graph Networks
Keywords: Graph Neural Networks
Hierarchial Graph Representation Learning
Memory Networks

Graph Neural Networks (GNNs) are a class of deep models that operates on data with arbitrary topology and order-invariant structure represented as graphs. We introduce an efficient memory layer for GNNs that can learn to jointly perform graph representation learning and graph pooling. We also introduce two new networks based on our memory layer: Memory-Based Graph Neural Network (MemGNN) and Graph Memory Network (GMN) that can learn hierarchical graph representations by coarsening the graph throughout the layers of memory. The experimental results demonstrate that the proposed models achieve state-of-the-art results in six out of seven graph classification and regression benchmarks. We also show that the learned representations could correspond to chemical features in the molecule data.
“Don’t Rock the Boat”: A Qualitative Narrative Study Exploring Rheumatoid Arthritis Patients’ Experience of Illness and Biologics
Keywords: adherence
illness narratives
medication narratives
narrative inquiry
qualitative
Rheumatoid Arthritis (RA)

To date, we know little about the relationship between the experiences of rheumatoid arthritis (RA) and experiences of Biologic treatment, and what these medications mean to people. This study sought to examine this relationship. Through narrative analysis, using the boat as a metaphor to illustrate the storylines within which 8 participants accounts of illness and medication experiences were emplotted and embedded, two story typologies were defined. ‘Biologics as Life Preservers’ represented Biologics as something that can be donned when needed. ‘Biologics as Life Boats’ represented Biologics as rescuing participants from an identity-damaging illness. These stories illuminate what it is like to be on boat that has metaphorically capsized, to be saved from the rough waters of disease, to have that ‘rescue’ jeopardized by others, to be at the mercy of those who control access to care. The study findings hold implications for adherence research, clinician-patient interactions, and drug reimbursement policies.
Design and Implementation of a Micro-world Simulation Platform for Condition-based Maintenance using Machine Learning Algorithms
Keywords: Condition-Based Maintenance
Decision Support System
Machine Learning
Micro-world platform
Transparency
Web Human-Machine Interface

This thesis explores the development of the simulation platform ARDAS (Automated Reliability Decision Aid System) following the micro-world framework. ARDAS simulates a decision support system for the maintenance management of a hydraulic process applying the Condition-Based Maintenance method. This platform intends to support decision-making to solve maintenance problems that might affect the performance of the hydraulic process. ARDAS uses an open-source data set collected from a hydraulic process to train a Machine Learning algorithm that estimates the health condition of four components within the hydraulic process. This platform also includes the implementation of a web user interface that presents information about the inner workings of the automated system, process diagram, trend of variables, and contextual information. This platform can be used to aid those who wish to study the effects of an ML-based decision aid system on human performance.
Investigating the Intrinsically Disordered Regions of USF1 and Other bHLHZ Transcription Factors
Keywords: bHLHZ
Intrinsically disordered regions

Part I of this thesis describes structural studies of the disordered loop of the basic helix-loop-helix/zipper (bHLHZ) transcription factor USF1. The objective was to understand how USF1 recognizes a single nucleotide polymorphism in a 4G tract found in the regulatory region of the plasminogen activator inhibitor 1 (PAI-1) gene, by mutating selected residues in its disordered loop. T234 is the key residue implicated in differentiating the PAI-1 polymorphism, and the USF1 bHLHZ preferentially binds the 5G variant of the polymorphism and not the 4G variant. Part II explores the design of minimalist transcription factors where domains from various transcription factors with desired properties were combined to generate novel proteins. By using crystal structures of the parent proteins, we appended domains of interest onto the MEF bHLHZ to create MEF variants with altered DNA binding properties. Additionally, phage-assisted continuous evolution (PACE), is being utilized to further improve these MEF variants.
Targeting the Hypoxic Fraction of Head and Neck Squamous Cell Carcinoma through the Inhibition of Lactate Transporters MCT1 and MCT4 in Synergy with Metformin
Keywords: Head Neck Cancer
Hypoxia
Lactate
Monocarboxylate Transporters
Tumour Metabolism

Head and neck cancer is a common form of cancer, and a major factor affecting treatment outcome is tumour hypoxia. A defining characteristic of hypoxia are the changes in cellular metabolism such as producing large amounts of lactate. Monocarboxylate transporters (MCTs) play a crucial role in regulating lactate metabolism, and thus constitute a target against hypoxic cells. In this study, we explored the possibility of inhibiting MCT1 and MCT4 in conjunction with the antidiabetic drug metformin to selectively kill hypoxic cells. We generated a double MCT1/4 knockout cell line and have shown this strategy is effective in halting HNSCC cell proliferation under hypoxia, in addition to further sensitizing these cells to metformin. Moreover, we have shown that full MCT1/4 inhibition slows tumour growth and extends survival in animal models. Our results indicate MCT inhibition constitutes an effective way of targeting the hypoxic niche and generates a potential therapeutic opportunity.
Epigenetic Mechanisms Governing the Differentiation of Glioblastoma Stem Cells
Keywords: ASCL1
Cancer
Differentiation
Epigenetics
Glioblastoma
Histones

Glioblastoma (GBM) is the most aggressive primary brain tumour of adults. Targeting the self-renewal property of glioblastoma stem cells (GSCs) is critical for tumour eradication. Our lab found that patient-derived GSCs with high expression of ASCL1 (ASCL1hi) were competent to undergo neuronal differentiation in response to differentiation cues and this was associated with reduced tumorigenicity. Overexpressing ASCL1 in the initially unresponsive subset, ASCL1lo GSCs, was able to enforce a neuronal cell fate. The epigenetic mechanisms underlying differentiation of GSCs have not been fully elucidated. In this thesis, I uncover distinct accessible chromatin landscapes, where ASCL1hi GSCs are primed for neuronal differentiation, while ASCL1lo GSCs are enriched for immune pathways. I further provide functional evidence for a potential upstream transcriptional regulator of ASCL1. Finally, I reveal changes in histone post-translational modifications that may contribute to ASCL1-mediated differentiation of GSCs. These results provide early insights into the epigenetic requirements of differentiation therapy for GBM.