VictorJuiz/thesis huggingface dataset:
Counterfactual Explanations for Discrete Optimization

This thesis develops the first application of counterfactual explanations to optimal solutions of discrete optimization problems. The techniques studied respond to a contrastive question: why did the optimal solution did not satisfy a previously unstated specification? The explanations take the form of alternative objective parameters which would have resulted in the optimal solution satisfying the additional specification, while minimally perturbing the initial objective parameters. Such explanations are formalized as the Nearest Counterfactual Explanation (NCE) problem, which is based on a variant of inverse optimization. A novel cutting plane algorithm is developed to solve NCEs which explain problems with linear objectives and constraints. Two special cases of NCEs are also studied, based on restrictive question and answer forms.

Keywords: Constraint Programming
Counterfactual Explanation
Discrete Optimization
Explainability
Mixed Integer Programming
Optimization
Advisor: Beck, Christopher J
Advancing Novel Methods for Interzonal Air Leakage Measurement in Multi-unit Residential Buildings

Effective airflow control is an important aspect of building performance that contributes to ventilation energy efficiency, occupant comfort and safety. However, the lack of accessible interzonal airtightness measurement methods inhibits the implementation of meaningful compartmentalization standards in multi-unit residential buildings. The feasibility of two novel approaches were investigated. Using sound transmission loss as an indicator of air leakage rate across suite partition walls, the estimate accuracy of 0.59 L/s/m2 remains inadequate for compliance verification at 1.53 L/s/m2, but it could be a feasible approach for screening air leakage rates between similar partitions. Correlation models specific to typical wall assemblies could be developed in the future to improve this accuracy. When MEMS absolute pressure sensors were used to monitor air pressure differentials, after applying calibration and noise removal techniques, sensors with ±3 Pa rating produced pressure differential estimates of ≤10 Pa accuracy, which appeared adequate for selective operational airflow monitoring applications.

Keywords: Air Pressure
Airflow
Compartmentalization
Multi-Unit Residential Building
Sensor
Sound Transmission
Advisor: Touchie, Marianne F
Closed-loop Control of Peripheral Nerve Stimulation using Resource-efficient Neural Networks

Closed-loop control of functional electrical stimulation (FES) can restore movement to paralyzed limbs by using recorded nerve signals to modulate stimulation in real-time. Previous work performed state-of-the-art classification of nerve signals using neural networks (NNs). This thesis explored reduced NNs for use in implanted systems and incorporated such NNs into closed-loop stimulation. NNs of varying complexities were evaluated for performance and resource usage when classifying individual naturally-evoked compound action potentials, previously collected from rat sciatic nerves using 7x8-channel cuff electrodes. Acute in vivo experiments used NNs to estimate nerve branch activity in real-time as feedback for neural stimulation, producing desired ankle movement trajectories. Reduced NNs achieved macro F1-scores of 0.70-0.71 while remaining within resource constraints defined by NN implementations in integrated circuit fabrication technologies. We demonstrated closed-loop stimulation in 6 rats. NNs that classify nerve signals can be reduced to fit implantable hardware platforms and used for closed-loop stimulation control.

Keywords: closed-loop
functional electrical stimulation
neuroprosthetic
peripheral
Advisor: Zariffa, José
Acetylation as a Modifier of H2A.Z Function in Memory

DNA is packaged into the nucleus by wrapping around an octamer of histone proteins that form nucleosomes, which regulate DNA accessibility to transcriptional activators and repressors. Post-translational modifications (PTMs) of histone proteins are key regulators of transcription, with different PTMs producing unique effects on gene activity. Histone variants are a category of functionally unique histones that replace canonical histones in chromatin, yet PTMs are rarely considered in studies of histone variants. Our laboratory showed that the histone variant H2A.Z suppresses memory, but that its acetylation (H2A.Zac) is lastingly increased by learning, suggesting that H2A.Z may have a positive role in memory when it is acetylated. Indeed, acetylation of other histone types is positively linked with memory, which contrasts the suppressive effect of H2A.Z on memory when PTMs are not considered. Thus, the goal of my thesis was to investigate how acetylation alters the role of H2A.Z in memory. Rather than targeting acetylation writers and erasers using drugs, which influence modifications across different histone types, we selectively manipulated the acetylation profile of H2A.Z by overexpressing mutant constructs that either mimic or block H2A.Z acetylation. We found that H2A.Z acetylation has sex- and task-specific effects on memory; specifically, blocking H2A.Z acetylation in males significantly inhibits fear-memory without affecting object location memory. In females, mimicking H2A.Z acetylation enhances object location memory whereas blocking acetylation impairs this type of spatial memory, but neither manipulation impacted fear memory in female mice. This targeted gene-editing approach is a major leap in studies of histone PTMs in the brain as it provides the first direct investigation of acetylation’s function in H2A.Z-regulated memory and demonstrates H2A.Z’s unique sex-specific effects on aversive and non-aversive memories.

Keywords: Acetylation
H2A.Z
Memory
Advisor: Zovkic, Iva
SilverFace: Automated Authentication of Older Adults using Face Recognition

Recent interest in exergaming, and ambient activity technologies in long term care, is creating a need for better methods of authenticating older people that do not require things to be remembered (passwords) or objects to be carried around (e.g., badges and RFID tags). Face recognition is a promising form of automated authentication that doesn’t require any effort or input on the part of the users. Using existing deep learning algorithms, with data trained on older faces, two face recognition authentication prototypes were developed on inexpensive single board computers running a customized Ubuntu version of Linux. The second prototype ("SilverFace") used a more powerful computer that avoided overheating problems found with the first prototype. SilverFace was integrated with the 2RaceWithMe exergaming system installed at the York Care Centre long term care home in Fredericton. Results from the York Care Centre trial, and from an evaluation by Ambient Activity Technology (AAT) are reported.

Keywords: Automated Authentication
Face detection
Face identification
Face Recognition
Older Adults
Advisor: Chignell, Mark
Homomorphically Trained Neural Networks

This thesis has two main contributions. Firstly, we present Cryptograd: an autograd-compatible homomorphically encrypted training and inference library built in Python. Using this library, we successfully train a fully encrypted model using fully encrypted training data on the QSAR Andogen receptor dataset. We obtain an accuracy value of 90% and a total training time of 670s on an Intel Core i7-11700K @ 3.60GHz using 12 cores. Secondly, we introduce a modified privacy-preserving federated learning scheme. At the core of this scheme is DRMSprop: a decentralized optimizer that utilizes a global gradient vector to improve convergence, stability, and performance. This modified scheme yielded an accuracy increase of 1.7% relative to other optimizers on the census income prediction dataset. Furthermore, it lags behind the optimal insecure model by only 2.3%.

Keywords: Autograd
Automatic differentiation
Homomorphic encryption
Machine learning
Optimization
Advisor: Gulak, Glenn
Long-term Stiffness and Shrinkage Strain Monitoring of Reinforced Concrete Elements

It is important to accurately evaluate the initial uncracked stiffness in critical buildings such as nuclear power plants to determine their serviceability, natural periods, and dynamic response. Based on a literature review, the initial stiffnesses of RC elements are less than the stiffnesses estimated from plain concrete properties. This one-year experimental program showed that the initial compressive stiffnesses of plain and reinforced normal strength concrete decreases over time in an indoor environment. Based on the reduction rate correlation with reinforcement ratio and drying age, it is necessary to further investigate the stiffness trends regarding the shrinkage to draw a general conclusion. In addition to the topic, a new strain gauge and shrinkage monitoring system are proposed and tested for future large-scale and long-term deployments. The results from thermal characteristics, gauge factors, and the average measurement across concrete cracks proved the potential of the system and the validity of testing methodologies.

Keywords: Concrete
Elastic
Monitoring
Shrinkage
Stiffness
Strain
Advisor: Kwon, Oh-Sung
Bentz, Evan C
Multilayer C3N/Blue Phosphorene Heterostructures as Effective Anode Materials for Potassium-ion Batteries

Two-dimensional van der Waals heterostructures outperform conventional anode materials for post-lithium ion batteries in terms of mechanical, thermal, electrical, and electrochemical properties. This study systematically investigates the performance of multilayer C3N/Blue Phosphorene (C3N/BP) heterostructures as anode materials for potassium-ion batteries (KIBs) using first-principles density functional theory (DFT) simulations. We demonstrate that the electronic, mechanical, and electrochemical properties of multilayer C3N/BP heterostructures are markedly superior to those of their monolayer counterparts. Most prominently, a two-layer heterostructure (C3N/BP) effectively reduces the bandgap of the BP monolayer (1.98 eV) to 0.02 eV, whereas three-layer heterostructures (bilayer-C3N/BP and C3N/bilayer-BP) exhibit metallic behavior with no bandgap. Additionally, the theoretical capacity of the proposed heterostructures ranges from 636.7 mAh.g-1 to 755.5 mAh.g-1, considerably higher than the theoretical capacity of other 2D heterostructures for KIBs, ranging from 209.8 mAh.g-1 to 727.6 mAh.g-1. Overall, our findings indicate that C3N/BP heterostructures can function as high-performance anode materials for KIBs.

Keywords: electric vehicles
multilayer heterostructures
potassium-ion batteries
theoretical capacity
Advisor: Amon, Cristina
Identifying the Hematopoietic Cells Immortalized by HOXB4

Self-renewal is the ability of a cell to produce identical daughter cells upon division. Multipotent hematopoietic stem cells (HSCs) permanently self-renew whereas more differentiated cells have only transient self-renewal capacities or none at all. Despite the importance of self- renewal in sustaining blood cell populations, the molecular mechanisms that regulate it is unclear. Hoxb4, a member of the Homeobox family of transcription factors, has been implicated in self-renewal regulation due to evidence suggesting that exogenous HOXB4 seems to sustain the self-renewal capacity of oligopotent progenitors (OPPs). However, the specific cells susceptible to this immortalization remains unknown. The purpose of my thesis is to identify these cells so that they can be purified and analyzed which will uncover the regulatory underpinnings of self- renewal. I have identified a potential cell population that exhibits permanent self-renewal given HOXB4. These cells are not as primitive as multipotent HSCs nor as differentiated as certain OPP subsets.

Keywords: Cytometry
Hematopoiesis
HOXB4
Mice
Self-renewal
Stem cell
Advisor: Iscove, Norman N
Supervised and Unsupervised Deep Learning Seizure Prediction using EEG

Epilepsy affects more than 50 million people worldwide, making it one of the world’s most prevalent neurological diseases. The main symptom of epilepsy is seizures, which occur abruptly and can cause serious injury or death. The ability to predict the occurrence of an epileptic seizure could alleviate many risks and stresses people with epilepsy face. We have taken several approaches to predict the occurrence of a seizure using deep learning. Firstly, we developed a supervised model to identify pre-seizure EEG from normal EEG. Then, we developed an unsupervised approach where the model is trained on just the normal EEG, and pre-seizure EEG is identified as an anomalous event indicating the onset of a seizure. These models were trained and evaluated on two public EEG databases. We have found that both supervised and unsupervised approaches are feasible; however, their performance varies depending on the patient and the approach and architecture.

Keywords: Anomaly detection
Autoencoder
EEG
Epilepsy
Seizure prediction
Unsupervised learning
Advisor: Popovic, Milos R
Khan, Shehroz S
Design and Evaluation of a Hand Hygiene Prompting System for Private Residences

Hand hygiene can prevent the spread of infection, but it is often overlooked in the community. The objective of this project was to develop and evaluate a hand hygiene prompting system for use at the entrance of private residences. The system included passive infrared sensors, a buzzer, and a light emitting diode connected to a microcontroller that was programed to prompt individuals to wash their hands using an attached alcohol gel dispenser as they entered their residences. The system was evaluated over 4 weeks in 20 households (10 control and 10 intervention). There was an increase in hand hygiene adherence (41.7% to 92.5%, p < 0.0001) for the intervention group in Week 2 when prompting was activated, followed by a decrease in Week 3 after prompting was deactivated (92.5% to 44.8%, p < 0.0001) while no change was seen for the control group (p = 0.789). Key words: Hand hygiene, prompting, infection control, smart home, biometrics

Keywords: biometrics
Hand hygiene
infection control
prompting
smart home
Advisor: Dutta, Tilak
Exploring the Emotional Climate and Emotion Norms in Female Competitive Sport

This study explored the development of emotion norms within a competitive female volleyball team, specifically examining how athlete leaders and coaches influence the development of emotion norms and the emotional climate of the team. Twelve athletes and three coaches from one competitive female varsity team participated in two semi-structured interviews. Thematic analysis of interview data suggested coaches and leaders play key roles in generating and reinforcing appropriate emotional experiences and behaviours through their own emotional expressions, and their attempts to regulate athletes’ emotions. Further analyses suggest leaders’ and coaches’ emotional expressions could uniquely influence the team’s emotional climate and performance, depending on athletes’ perceived appropriateness of the coach and leader emotions in the given context. These results provide valuable insight into the emotional experiences of athletes and demonstrates how coaches and leaders can improve the emotional climate of a team to maximize team performance.

Advisor: Tamminen, Katherine
Examination of Mitochondrial Genetic Variation in Reported Autism Spectrum Disorder

The knowledge surrounding the neurobiology of Autism Spectrum Disorder (ASD) remains limited. Mitochondrial dysfunction appears to be involved in the etiology of ASD, given evidence indicating disrupted oxidative phosphorylation and increased oxidative stress in ASD. Therefore, variation within mitochondrial genes may contribute to ASD. The objective of this study is to examine whether mitochondrial genetic variation is associated with ASD risk. N = 172 reported autism cases and 9854 controls ages 9-10 from the Adolescent Brain Cognitive Development (ABCD) study were selected for analysis. Tractor software was used to conduct an ancestry-aware logistic regression for reported autism diagnosis and nuclear-encoded mitochondrial SNPs. Next, a meta-analysis using the ABCD European sub-sample, and the Psychiatric Genetics Consortium ASD sample was conducted using METAL. Finally, mtDNA haplogroups were analyzed for association with reported ASD diagnosis using the Chi-squared test. No nuclear-encoded mitochondrial SNPs or mtDNA haplogroups were significantly associated with reported ASD diagnosis.

Keywords: Admixture
Autism Spectrum Disorder
Genetics
Mitochondria
Mitochondrial DNA
Advisor: Gonçalves, Vanessa
Kennedy, James L
Labour Supply Outcomes of Informal Home-based Palliative Caregivers

Introduction: Informal palliative caregivers provide ongoing care and support to patients and are at increased risk to reduce their labour supply and to modify their labour market behaviours. Objective: The purpose of this thesis was to assess the relationship between the supply of informal palliative caregiving and labour supply outcomes over the care trajectory. Methods: This study used prospective longitudinal cohort data of palliative care caregivers in Ontario from 2014-2017 obtained through interviews with informal caregivers. Regression models were used to estimate the effects of informal caregiving on labour supply outcomes. Results: There is a negative association between informal palliative caregiving and labour supply intensity and propensity. Caregivers providing more than 58 hours of care bi-weekly experienced the steepest decline in labour force participation. Conclusion: Support and workplace legislation that encourages flexibility for caregiving-labour arrangements may improve economic outcomes for families and employers.

Keywords: Health Economics
Informal labour
Palliative care
Advisor: Coyte, Peter C
Gecko: Hardware Support for Deep Learning Training Acceleration by Dynamic Adaption of Floating Point Value Encoding

We introduce an improved hardware approach to reduce memory traffic and footprint during training with floating-point. This paper proposes a new exponent encoding method which reduces the bits needed to represent the number. The total exponent bitlength can be reduced up to 63.1\% compared with the 32-bit floating point baseline. We implemented hardware encoders/decoders that transparently perform the compression and decompression process when transferring to/from off-chip memory. The hardware module helped increase energy efficiency and reduce training time while preventing the modification of existing training code.

Advisor: Moshovos, Andreas AM
Development of Strategies to Map out Metabolic Pathways using Copper-catalyzed Azide/alkyne Cycloaddition Reaction

LC-MS-based metabolomics has emerged as a powerful tool to study biochemical fluxes indicative of biological and environmental perturbations, which can provide novel insights into previously unknown biological processes. However, challenges in LC-MS-based metabolomics, such as the matrix effect and inability to detect low-abundance metabolites, serves as an obstacle to comprehensively profile all metabolites involved in a specific pathway of interest. Click chemistry has emerged as a powerful tool to overcome some of the challenges associated with LC-MS-based metabolomics. More specifically, click chemistry allows tagging and enrichment of metabolites from specific pathway of interest, which reduces matrix effect and simplifies data analysis. Through a series of experiments testing different reaction conditions, we optimized two click chemistry protocols to maximize the click reaction between biotin azide with alkyne-functionalized metabolites of varying physiochemical properties. Additionally, we demonstrated unexpected side reactions in both protocols. These side reactions are caused partly by production of hydrogen peroxide and hydroxy radicals, which leads to oxidation of metabolites

Advisor: Montenegro-Burke, Rafael
Role of 9-PHEnanthrol on Ventricular Fibrillation Substrate Characteristics of Spontaneously Hypertensive Rat: An Optical Mapping-based Study

Background: Higher expression of the Transient receptor potential melastatin 4 (TRPM4) channels in the ventricle is associated with poor repolarization reserve in the spontaneous hypertensive rat (SHR). The role of TRPM4 inhibition by 9-phenanthrol (PHE) on ventricular electrophysiology in SHR is unknown. Methods: Explanted hearts from SHRs (n=10) and WKY rats (n=10) of 10-14 months of age were subjected to LV epicardial optical mapping for voltage and calcium transient following treatment with 9-PHE (20µM) or vehicle in Langendorff-setup. Hearts were then subjected to rapid electrical pacing to induce ventricular fibrillation (VF). LV tissues from SHR hearts were collected for protein analysis. Results: APD alternans was higher in WKY rats with 9-PHE treatment (p <0.0001). In SHR (p=0.001) and WKY (p<0.0001) rats, epicardial conduction velocity was reduced by 9-PHE treatment. 9-PHE treatment was associated with a reduction in VF dominant frequency in SHR hearts (p = 0.01).

Advisor: Nanthakumar, Kumaraswamy Dr
Riazi, Sheila Dr
Distribution, Course, and Spatial Relationships of the Saphenous Nerve: A 3D Neuroanatomical Map for Nerve Stimulation

Saphenous nerve (SN) stimulation is a novel therapeutic approach that offers a non-pharmacologic alternative to treating overactive bladder (OAB) syndrome. Although precise anatomical knowledge of SN is required to optimize electrode placement protocols, there are no 3D studies of the subcutaneous distribution of SN nerve branches in the leg. The purpose of this thesis is to document and model in 3D the course of the branches of SN relative to bony and soft tissue landmarks using serial dissection, digitization, laser scanning, and 3D modelling. The course of the main branches, number of collateral branches, and relationship of SN to the great saphenous vein (GSV) were defined in 3D. Further, bony landmarks were identified and measurements were taken to quantify their spatial relationships to SN. The results enable us to identify potential electrode placement sites and implement highly realistic computational models that can be used to simulate various forms of SN stimulation.

Advisor: Agur, Anne MR
Intermediate to Secondary School Transition: Teachers' Perceptions on Factors Affecting Student Transition to Grade 9 Mathematics

This study investigates how current Grade 9 mathematics teachers perceive the transition from Grade 8 to Grade 9 mathematics following the release of the new de-streamed curriculum. Based on the evidence found in this study, the transition to Grade 9 does influence students academically and socially. There were three major findings: (1) a student’s previous experiences in mathematics classrooms has the ability to influence their current progress as a Grade 9 math student; (2) how the teacher integrates lessons and engages their students with the new curriculum is a predictive factor of successful transition and student achievement; and (3) the way in which the teacher gets to know their students and responds to their needs impacts a student’s success in transition to Grade 9 mathematics. Suggestions for future teacher practices in the Grade 9 math classroom are discussed in order to continue supporting students during this critical period of transition.

Advisor: McDougall, Douglas