VictorJuiz/thesis huggingface dataset:
Grounding the Design of a Supportive Post-Hospital Discharge Intervention in the Experiences and Perspectives of Sudden Cardiac Arrest Survivors and Family Members

While advancements in pre-hospital and critical care have contributed to greater sudden cardiac arrest (SCA) survival, advancements in survivorship support remain desperately needed. This research leveraged qualitative methods to conduct step two of an adapted experience-based co-design process. The aim was to gain an understanding of SCA survivor and family perspectives on their previous experiences, challenges, and needs along the first year of their (co-)survivorship journey. Two themes reflect experiences related to challenges and support needs including: 1) navigating new territory without a map and 2) the impact of time and evolution of needs. Within each (theme) are several sub-themes which inform on how to support survivors and families after hospital discharge. Based on the themes identified, a set of considerations for subsequent co-design activities have been produced. The findings inform on SCA survivor and family support needs in the first year after hospital discharge, and how these needs change over time. Moreover, this work highlights how qualitative methods can be used not only to identify and understand SCA survivorship needs, but to inform further action to address such needs as well.

Keywords: experience-based co-design
out-of-hospital cardiac arrest
qualitative research
sudden cardiac arrest
survivorship
Advisor: Dainty, Katie N
Usability and Feasibility Testing of Eating for Wellness (E4W) – An Image-Recognition Dietary Assessment Application for Adolescents with Obesity

Background: Use of image-recognition dietary assessment apps in adolescents with obesity is not well studied.Purpose: To evaluate the usability, feasibility, and preliminary effectiveness of Eating for Wellness (E4W), an mHealth app, in improving dietary intake in adolescents with obesity attending an obesity clinic. Methods: Usability was tested through iterative cycles of patient and healthcare provider interviews with standardized scenario-based tasks. A pilot RCT of 32 adolescents (each enrolled for 1 month) was completed to assess feasibility of implementation and preliminary effectiveness. Results: Usability testing demonstrated that E4W was effective, efficient, and well-liked. Feasibility testing was hindered by technical challenges, patient engagement and adherence to food records, and there was no statistically significant improvement in dietary intake. However, patient acceptance and satisfaction scores were high. Conclusions: E4W was well-received by patients and HCPs. Further research is warranted to determine if E4W can improve dietary intake in adolescents with obesity.

Keywords: adolescent
dietary assessment
mhealth
nutrition
obesity
weight management
Advisor: Hamilton, Jill K
Machine Learning-Assisted Computational Exploration of High Entropy Materials for Hydrogen Energy

Hydrogen fuel can be generated cleanly and used to store and transport energy. Challenges remain regarding the generation and storage of hydrogen, wherein low-cost materials with superior performance represent the final frontier towards ubiquitous adoption of this technology. Multi-principal element materials provide unlimited opportunity for tuning material properties to achieve desired performance goals. This thesis leverages density functional theory simulations and machine learning to both investigate previously synthesized materials and search for new, optimal compositions. Mechanisms of the hydrogen and oxygen evolution reactions were studied by analyzing the stability of intermediates on the active sites. Strategies for exploiting the varying local chemical environments within high-entropy surfaces are presented. Bayesian optimization was applied towards the accelerated discovery of high entropy alloys for hydrogen storage. Fundamental understanding of metal hydride stability was uncovered, and new alloy compositions were proposed.

Keywords: density functional theory
high entropy alloys
hydrogen
machine learning
Advisor: Singh, Chandra V
Approximate CVaR Optimal Control with a Maximum Cost

We consider a risk-aware optimal control problem, where the objective is the conditional value-at-risk of a maximum of stagewise and terminal costs along a finite time-horizon. Previous techniques for this problem rely on dynamic programming, and hence suffer from scalability issues when applied to multidimensional systems. To that end, we study an approximate technique that relies on empirical sampling and function approximation in a reproducing kernel Hilbert space to mitigate these scaling issues. Our contribution is the derivation of bounds on the ∞-norm error for this approximation that are pointwise functions of the sampling process, using techniques from functional analysis, probability theory, and a novel Lipschitz condition. To study the sampling processes, we develop a measure-theoretic framework that enables future analysis of probabilistic bounds. The performanceof our method is evaluated using a single-stage reservoir management problem, and we highlight theeffect different parameters have on the error.

Advisor: Chapman, Margaret P
Quantized Analog Signaling on a Switch Capacitor DAC (SCDAC)-based Transmitter

The presence of multiple operative modes and standards in 5G/6G systems set two crucial requirements for the next generations of wireless transmitters (TX): flexibility and high spectral purity. Modern radio frequency (RF) TXs are evolving to become more digital signal processing (DSP) intensive. While the scaling of technology nodes benefits DSPs, certain analog front ends (AFE) of the TX are still limited to conventional architectures, which do not offer great flexibility nor dynamic range. The solution is to use quantized analog (QA) approach to create an AFE which offers a new design space typically not seen in an analog-only AFE This thesis focuses on the design and characterization of a Quantized Transmitter(QTX) using the QA approach. It is the first time that QA signalling has been applied to RF TX designs, where previously this novel architecture has only been applied to RX front-ends. Fundamentally, this QTX uses passive switch-capacitor (SC) networks, including a 6-bit SC-DAC which can achieve an equivalent number of bits (ENOB) of 11 bits using 32 QTX slices. Thanks to the slicing of the signal, multiple channel transmission is possible on this QTX, which serves similar functionality asan RF-DAC without using high sampling rates nor high physical bits. Designed and manufactured in GlobalFoundries’s 22nm FDSOI technology, this QTX achieves an adjacent channel leakage ratio (ACLR2) of -56dBc and an error vector magnitude(EVM) of -35dB for a 15MHz 64-QAM signal. The linearity (SFDR) is also improved by over 10dB after an algorithm is applied to the slice offsets for a single tone test.

Keywords: Quantized Analog
Switch Capacitor
Wireless Transmitter
Advisor: Liscidini, Antonio
A Robust Model Predictive Control Scheme for Slung-load UAS Operating in Confined Flight Space

Unmanned aerial systems (UAS) have been found across industries from construction to environmental monitoring. In particular, the payload transport function for autonomous water sampling has garnered notable research interest in recent years. This paper investigates an uncertainty disturbance estimator-based (UDE) nonlinear model predictive control (NMPC) framework to navigate a slung-load UAS around an obstacle in highly limited workspaces. Scenarios arise where the allowable flight space for the vehicle body is less than that of the payload. The use of NMPC allows for the manipulation of the payload motion to avoid incoming obstacles while respecting workspace boundaries for all components of the slung-load UAS. The addition of UDE enhances controller performance in the presence of parametric uncertainties. Three solutions facilitating collision-free flights for a pair of slung-load UAS in a similar workspace are then compared. The advantages of the proposed method are demonstrated through simulations. High-fidelity simulations with PX4 software-in-the-loop (SITL) and Gazebo are used to validate the proposed approaches.

Keywords: Aerial Robotics
Collision Avoidance
Model Predictive Control
Planning and Control
Uncertainty Disturbance Estimator
Unmanned Aerial Systems
Advisor: Liu, Hugh H.T.
Distance Correlation Market Graph

Financial markets, with their complex interconnections, demand refined tools for understanding. This thesis delves into market graph construction, transitioning from Pearson correlation to the nuanced distance correlation, focusing on the S\&P 500 index. Empirical findings reveal that distance correlation excels during market turbulence, offering superior insights compared to Pearson correlation. When constructing portfolios using distant stock pairs based on distance correlation, the study evidences enhanced risk management. Additionally, by integrating Quadratic Programming with K-Medoid clustering, traditional index tracking challenges are addressed. Evaluations across equity indices demonstrate the combined approach's marginal advantage in precisely capturing market intricacies. This research underscores the potential of distance correlation in advancing market graph construction and optimizing index tracking paradigms.

Keywords: complex networks
Distance correlation
Index Tracking
Investment science
market graphs
stock network
Advisor: Lawryshyn, Yuri
Methotrexate-loaded Microbubbles for Ultrasound-triggered Treatment of Inflammatory Bowel Disease

Methotrexate (MTX) is a systemically injected immunomodulatory drug used to treat inflammatory bowel disease (IBD). The goal of this thesis was to develop ultrasound-responsive MTX-loaded, phospholipid microbubbles (MBs) with comparable in vitro stability as existing clinical MBs and with sufficient drug-loading for future ultrasound-guided, targeted, MTX treatment of IBD. To quantify drug-loading and stability with different lipid formulations, four different MTX-phospholipid complexes were formed via co-solvent evaporation, and used to stabilize oil droplets in water. Subsequent lyophilization formed empty MTX-lipid shells, which were fluorocarbon gas-filled and reconstituted with saline to form MTX-MBs. MTX-MB stability was greater when MTX-18-carbon lipid (DSPC) complexes were used in comparison to MTX-16-carbon lipid (DPPC) complexes (60 minutes and 160 minutes at 37 ̊C, respectively). MTX-loading varied substantially between formulations, with highest drug-loading being 7.2 ± 3.01 μg per 109 DSPC MBs. Based on results, these MTX-loaded MBs are a promising approach for future, targeted, IBD treatment.

Advisor: Matsuura, Naomi
Experimental Analysis of Partially Premixed Combustion in a Direct Injected Spark Ignited Natural Gas Engine

Partially premixed combustion using early direct injection of natural gas was explored in a spark ignited single cylinder research engine. An overall equivalence ratio of 0.70 was used, with intake pressures of 5 and 10psig. Varied injection timings were employed to investigate different degrees of premixing, from full premixing with injection near BDC, to stratified combustion with injection near TDC. The effects on engine performance and combustion behaviour were assessed, along with NO, CO, unburnt hydrocarbon, and particulate matter emissions levels. Two injector nozzle designs were employed to evaluate the effects of confining the fuel to the piston bowl. Substantial increases in efficiency were seen in partially premixed operation, along with decreases in unburnt hydrocarbon emissions, resulting in significantly lowered greenhouse gas emissions. This came with the consequence of increased CO and particulate matter emissions at later injection timings.

Keywords: combustion
engine
natural gas
partially premixed
stratified
Advisor: Wallace, James S
Repetitive Peripheral Magnetic Stimulation for Phasic Heat Pain Modulation

Existing pain management tools have limited efficacy and can be associated with significant side effects. Repetitive peripheral magnetic stimulation (rPMS) is a novel non-pharmacological technique that could induce non-invasive analgesia. The aim of this thesis was to determine whether rPMS reduces experimental phasic heat pain (PHP), compared to TENS. Seventy-seven healthy participants (41 males, 36 females) attended two sessions counterbalanced across participants: control and stimulation. Participants were randomly allocated to three stimulations groups: TENS or one of two rPMS paradigms (intermittent or continuous theta burst stimulation). PHP stimuli were applied in each session, and differences in three outcome measures across the two sessions were collected: (1) pain intensity, (2) pain unpleasantness, and (3) secondary hyperalgesia. There were significant reductions in secondary hyperalgesia (p=.002) between stimulation groups, but not pain intensity or pain unpleasantness (p=.100, p=.355, respectively). These results show that rPMS may be a suitable modality for non-invasive pain management.

Keywords: acute pain
hyperalgesia
pain management
peripheral magnetic stimulation
phasic heat
TENS
Advisor: Moayedi, Massieh
Open and Closed-Book Assessments in Secondary School Mathematics

This qualitative research study investigates teachers’ perspectives on open and closed-book assessments in secondary math classrooms. The covid-19 pandemic forced many teachers in Ontario to change their assessment style from closed-book to open-book. After teaching a full year with open-book assessments (2021/2022), three secondary math teachers were interviewed based on their experiences. The following year (2022/2023), the same teachers transitioned their classrooms back to closed-book and participated in another interview. Based on their interviews, this study had twelve major findings pertaining to open and closed-book assessments within the themes; student learning, grades, assessment practices, learning skills, higher order thinking, anxiety and equity. Some of the findings include; (1) teachers stated that some students struggled with time management on open-book assessments, (2) the teachers stated that students assumed open-book assessments would be easier and two teachers stated that some students spend less time preparing for their assessments as a result, and (3) the teachers stated that students engage in last-minute preparation for their closed-book assessments.

Keywords: assessments
closed-book
education
mathematics
open-book
secondary school
Advisor: McDougall, Douglas
Evaluation of a RANS-based Computational Framework for Predicting Sooting Turbulent Jet Flames

A Reynolds-averaged Navier-Stokes (RANS)-based computational framework for predicting soot formation in turbulent flames using the commercial computational fluid dynamics (CFD) software, Ansys Fluent, is evaluated for two experimental turbulent, non-premixed, sooting jet flames. The computational framework includes modelling for turbulent combustion through the Steady Laminar Flamelet Model (SLFM) and Flame-Prolongation of Intrinsic Low-Dimensional Manifold (FPI) tabulated chemistry approaches coupled to a presumed conditional moment (PCM) method. Modelling of soot is treated via a semi-empirical two-equation model for the transport of soot mass fraction and number density with reaction mechanisms governing soot inception, surface growth, coagulation, and oxidation. Radiative heat transfer is modelled via three strategies: (i) the optically thin approximation (OTA), the P1 spherical harmonics closure, and (iii) the discrete ordinates method (DOM). Non-gray radiation is treated via the Statistical Narrow Band Correlated-κ (SNBCK) method for evaluation of the gas phase absorption coefficients and soot absorption is estimated using Rayleigh scattering theory. Turbulence-radiation interaction (TRI) is evaluated from tabulated thermochemical quantities for the emission TRI, whereas absorption TRI is treated via the optically thin fluctuation approximation (OTFA). Results for the proposed framework were evaluated for three commonly-used two-equation turbulence models: the 1998 and Shear Stress Transport (SST) k-ω models, and the standard k- model with some tuning of model constants applied. The capabilities of the proposed framework to predict temperature, soot volume fraction, axial velocity, fuel mass fraction, and normalized OH concentration is assessed via comparisons to experimental data. A discussion of the relative capabilities to other modelling options is also provided.

Keywords: Radiative Heat Transfer
RANS
Soot
Turbulent Combustion
Advisor: Groth, Clinton P.T.
The Professional Ballet School ‘Bubble’: Former Students’ Experiences in (Potentially) Harmful Environments

Research on professional ballet schools typically focuses on the ballet training context, and little research addresses student experiences beyond the ballet studio. Many students reside at their ballet schools, and recent cases of child maltreatment at international ballet schools raise concerns for student welfare across the entire school context. The purpose of this exploratory study was to understand the nature of former students’ experiences across dance, academics, socializing, and living, and any perceived contributing contextual factors to those experiences. Fifteen former students from six countries completed semi-structured interviews, which were analyzed using reflexive thematic analysis and a social constructionist approach. Interpretations included themes about complex positive and negative experiences and maltreatment; perceived effects of experiences; and perceptions of contributing contextual factors. Developed themes and accompanying participant recommendations for safer, healthier, and more inclusive ballet schools suggest that many environments and student experiences were misaligned with children’s rights, welfare, and development.

Keywords: child maltreatment
children's rights
classical ballet education
professional ballet schools
safe sport
vocational ballet schools
Advisor: Kerr, Gretchen
Investigating the Relationship Between Insulin-like Growth Factor-1 and Cognition in Normoglycemia, Prediabetes, and Type 2 Diabetes Mellitus

The relationship between insulin-like growth factor-1 (IGF-1) and cognition has not been studied extensively with regards to type 2 diabetes mellitus (T2DM). We examined the association between IGF-1 and cognition across different diabetes status using the Midlife in the United States (MIDUS) study. Normoglycemia, prediabetes, and T2DM was defined using a self-report of diabetes diagnosis, glycated hemoglobin (HbA1c), and antidiabetic medication use. Among 583 normoglycemic (48.4% female, 51.0±12.2 years old), 512 prediabetes (58.4% female, 57.3±11.8 years old), and 305 T2DM participants (53.8% female, 57.6±11.5 years old), IGF-1 concentrations were associated with better executive performance in individuals with prediabetes (β=0.115 [0.028, 0.202], p=0.010), particularly in males (β=0.251 [0.123, 0.380], p<0.001), but not in normoglycemia or T2DM. No associations were seen between IGF-1 and memory. The results suggest that peripheral IGF-1 concentrations may be related to executive function, and that the relationship may be sex-specific and dependent on diabetes status.

Advisor: Swardfager, Walter
Investigating the Isoform-specific Functions of the Liver X Receptor during Fasting and Refeeding

The liver x receptors (LXRα and LXRβ) are key transcription factors known to be important for cholesterol and triglyceride homeostasis under the fed state but their importance in fasting has not been examined. Using whole-body LXR knockout mice, we demonstrate that mice with one LXR isoform can compensate using the other isoform to maintain liver transcriptome and cholesterol homeostasis when fed a chow-diet. Liver transcriptomic and metabolite data did not find LXR isoform-specific functions after 24 hr fasting. With 24 hr refeeding, we show LXRα is the dominant isoform mediating the induction of lipogenic genes (from plasma and liver triglyceride data) consistent with prior literature. We observed sex-specific and LXR-dependent effects in liver triglyceride, plasma free fatty acid, and plasma cholesterol levels within LXR-/- mice, however the molecular mechanisms governing these effects is as yet unclear and could be due to LXR expression in other metabolic tissues apart from liver.

Keywords: cholesterol
fasting
glucose metabolism
lipid metabolism
liver x receptor
sex differences
Advisor: Cummins, Carolyn L
Leveraging Cancer Mutation Data to Predict the Pathogenicity of Germline Missense Variants

This thesis explores the potential of leveraging cancer mutation data as an additional line of evidence to enhance the interpretation of germline missense variants. The challenges in interpreting these variants often result in their classification as variants of uncertain significance (VUS). This study identified overlapping missense cancer mutations from the Cancer Hotspots database and germline variants from ClinVar. The analysis demonstrates a significantly higher likelihood of pathogenicity among the overlapping variants. By incorporating comprehensive data from the Cancer Hotspots database, the study employs supervised learning models to predict the pathogenicity of germline missense variants, showcasing robust and reliable predictive abilities on a separate test dataset. Incorporating cancer mutation data was identified as moderate-level evidence for pathogenicity, highlighting the potential upgrade of a substantial proportion of VUS to “likely pathogenic”. Overall, this research underscores the significant value of cancer mutation data in improving the interpretation of germline missense variants.

Keywords: Bioinformatics
Cancer mutations
Databases
Statistics
Supervised learning models
Variant interpretation
Advisor: Costain, Gregory
Implementing a GPU-Assisted LDPC Decoder for 5G New Radio

This thesis presents a study on implementing a low-density parity-check (LDPC) decoder on a graphics processing unit (GPU) for 5G New Radio (NR). The proposed modifications include distributed execution configuration, compressed parity-check matrices (PCM) and message passing matrices to save memory space and applying the optimal iteration limit to the decoder. The performance of the LDPC decoder is evaluated using various testing cases with different algorithms, code rates and transport block sizes. The results show that the proposed decoder has more than 5× decoding speedup improvement on the short codes and more than 20× decoding speedup improvement on the long codes, while maintaining the error-correction performance. The optimal iteration limit is found to depend on the specific code rate and transport block size. The layered scheduling is a viable option on short codes over noisy channels.

Keywords: 5G New Radio
GPU Computing
LDPC
Advisor: Sousa, Elvino S
Therapeutic Alliance: A Predictor of Emotional Intelligence in Addiction Therapy for Youths with Attention-Deficit Hyperactive Disorder?

These studies aimed to investigate the impact of therapeutic alliance (TA) dimensions (Bond, Task, Goal) on emotional intelligence (EI) within the context of therapeutic addiction treatment and the differences in this relationship for adolescents with and without ADHD. TA was measured mid- and late-treatment using the WAI-YR, and EI was measured mid-, late- and post-treatment using the TEIque-SF. Study 1 (n = 70) regressions between TA and EI during treatment were stronger for the ADHD group. However, MANOVA found no significant group differences in mid- or late-treatment EI or TA scores, or in score changes between treatment points. When observing the total sample, Bond was the most significant predictor of EI, promoting its importance in building emotional intelligence in youths with addiction in general. Study 2 (n = 41) found that late-treatment Bond predicted post-treatment EI, but this may only apply to adolescent patients with stronger Bond-EI relationships during treatment.

Keywords: adolescents
attention-deficit hyperactive disorder
emotional intelligence
substance use disorder
therapeutic alliance
Advisor: Cunningham, Todd