title: Measures of retention in HIV care: A study within a review

contributor:
Mbuagbaw, Lawrence
Health Research Methodology

subject: HIV; retention in care;definitions; heterogenous;components

abstract:
This is the first comprehensive systematic review of the definitions used for retention measures in HIV care.
This review provides a compilation of existing definitions of retention in HIV care in randomized controlled trials. In summary, we report very little consensus regarding definitions of retention in HIV care in the research literature. We report and compare definitions of retention so researchers can weigh their definitions with the body of definitions, with the ultimate aim of motivating the research community to establish a clear and unambiguous definition. This work will provide resources for researchers to recommend a definition of retention. Future research is needed to seek practitioners’ views on the most unambiguous, explicit definition of retention. This is only a first step in research toward a standard definition of retention.

abstract:
Introduction
Retention in HIV care is critical for PLHIV. However, retention in HIV care is not measured uniformly across studies. The aim of this study within a review (SWAR) is to describe the diversity in definitions used for retention in HIV care in randomized controlled trials.
Methods
We conducted a SWAR, drawing data from an overview of systematic reviews on interventions to improve the HIV care cascade. A comprehensive and exhaustive search was conducted of the following databases: PubMed, Excerpta Medica data BASE, Cumulative Index to Nursing and Allied Health Literature (CINAHL), PsycINFO, Web of Science, and the Cochrane Library. We identified randomized controlled trials (RCTs) of interventions to improve retention in care for people living with HIV (PLHIV). First, from the included studies in systematic reviews and second using targeted searches for RCTs. Only English language systematic reviews were included, but RCTs in any language were eligible. Data were screened and extracted in duplicate using pre-set criteria, with arbitration as needed. We identified distinct components from the definitions used to measure retention. The components were further categorized based on the similarities between them. We described the components narratively and presented the definitions in tables.
Results
We identified 8001 records, after a duplication check, 4147 unique titles and abstracts were examined for relevancy, leaving 744 articles. Full-text screening of the articles resulted in 50 articles that measured retention and provided 59 definitions for retention in care. Of the included studies, 11(22%) were conducted in low-income countries, 12(24%) were conducted in lower-middle-income and upper-middle-income countries, and 13(26%) were conducted in high-income countries. We identified ten different components used to define retention. These components are follow-up times (83%), administrative records (8%), clinical visits (61%), gap scores (8%), group-level measures (17%), lab records (15%), pharmacy-based measures (29%), scheduled visits (27%) and visit counts (17%). The most frequently used components are follow-up times (n=49), and the easiest to measure are retention data derived from administrative records (n=5). We put the components into categories based on the similarities between them.
Conclusion
We identified existing definitions of retention in HIV care and the commonly used components in the definitions. This compilation of the definitions and identification of the components may provide a framework for developing the standard globally agreed-upon definition of retention in HIV care.

abstract: Thesis

abstract: Master of Health Sciences (MSc)

abstract:
Globally, there are more than 37.7 million people living with HIV (PLHIV). Retention in human immunodeficiency virus (HIV) care is a common and modifiable determinant of increased adherence to antiretroviral therapy (ART), better health outcomes, and a better quality of life.
There is no consensus in the literature on measures of retention in HIV care. This makes it very difficult to compare different studies and jurisdictions. This thesis review summarizes the definitions of retention used in randomized controlled trials (RCTs) and identifies the various components used to measure retention, which can be used as a reference for researchers to identify the gaps in the current definitions for HIV retention measures and identify preferred measures with the goal of reaching a standard consensus definition of retention in HIV care.


title: Spare parts inventory management for substitute consumer durable products under uncertainties

contributor:
Huang, Kai
Business

abstract: In this thesis, we investigate the mathematical models based on adaptive robust optimization (ARO) and stochastic programming (SP) for the spare parts inventory management under various uncertainties in a multi-period planning horizon, especially for the substitute consumer durable products offered in an assortment. In the first part of the thesis, we present a comprehensive literature review of spare parts inventory management, and 142 papers are surveyed and classified. In the second part,  we consider a multi-period spare parts inventory system providing spare parts for the substitute products in an assortment and aim to develop the spare parts inventory policies when the assortment is given in advance and there are uncertainties in the failure rates of both products and spare parts. We formulate a multi-stage adaptive mixed-integer robust optimization model and improve the partition-and-bound method to solve it. In the third part, we consider a multi-period dynamic assortment planning problem for an original equipment manufacturer (OEM) who launches and sells substitute product variants through an online platform. To handle the uncertainties embedded in the customer preferences estimation, a multi-stage stochastic programming model is proposed, and a branch-and-price (B&P) algorithm is designed based on the block-angular structure of the model. In the last part of this thesis, we study an assortment planning problem from the product lifecycle perspective and intend to simultaneously determine the assortment decisions, spare parts inventory policies, and returned products remanufacturing decisions when there are uncertainties in the failure rates of products and spare parts, and the return rates of the used products. The aim of this part is to explore the impacts on product assortment decisions brought about by implementing the last time buy (LTB) and remanufacturing strategies to supply spare parts over the warranty periods.

abstract: Thesis

abstract: Doctor of Philosophy (PhD)


title: Analysis and Applications of Deep Learning Features on Visual Tasks

contributor:
Chen, Jun
Electrical and Computer Engineering

subject:
Deep Learning
Image Inpainting
Image Retrieval
Computer Vision

abstract:
Benefiting from hardware development, deep learning (DL) has become a popular research area in recent decades. Convolutional neural network (CNN) is a critical deep learning tool that has been utilized in many computer vision problems. Moreover, the data-driven  approach has unleashed CNN's potential in acquiring impressive learning ability with minimum human supervision. Therefore, many computer vision problems are brought into the spotlight again. In this thesis, we  investigate the application of deep-learning-based methods, particularly the role of deep learning features, in two representative visual tasks: image retrieval and image inpainting.

Image retrieval aims to find in a dataset images  similar to a query image.
 In the proposed image retrieval method, we use canonical correlation analysis to explore the relationship between matching and non-matching features from pre-trained CNN, and generate compact transformed features. The level of similarity between two images is determined by a hypothesis test regarding the joint distribution of transformed image feature pairs. The proposed approach is benchmarked against three popular statistical analysis methods, Linear Discriminant Analysis (LDA), Principal Component Analysis with whitening (PCAw), and Supervised Principal Component Analysis (SPCA). Our approach is shown to achieve competitive retrieval performances on Oxford5k, Paris6k, rOxford, and rParis datasets.

Moreover, an image inpainting framework is proposed to reconstruct the corrupted region in an image progressively. Specifically, we design a feature extraction network inspired by Gaussian and Laplacian pyramid, which is usually used to decompose the image into different frequency components. Furthermore, we use a two-branch iterative inpainting network to progressively recover the corrupted region on high and low-frequency features respectively and fuse both high and low-frequency features from each iteration. Moreover, an enhancement model is introduced to employ neighbouring iterations' features to further improve intermediate iterations' features. The proposed network is evaluated on popular image inpainting datasets such as Paris Streetview, Celeba, and Place2.
Extensive experiments prove the validity of the proposed method in this thesis, and demonstrate the competitive performance against the state-of-the-art.

abstract: Thesis

abstract: Doctor of Philosophy (PhD)


title: Biobehavioural Predictors of Treatment Outcome in Addiction

contributor:
MacKillop, James
Psychology

abstract: Substance and alcohol use disorders are highly prevalent and confer a considerable burden of morbidity and mortality including medical, psychosocial, and economic consequences. Although evidence-based treatments to treat substance and alcohol use disorders are present, treatment retention and efficacy within these treatment modalities remains low. Further, individuals with substance and alcohol use disorders are clinically complex and often present with concurrent psychiatric disorders, which makes treatment delivery and response more challenging. Developing novel treatments and improving clinical outcomes in patients with substance and alcohol use disorders is predicated upon basic scientific advances in understanding the biological and behavioural determinants of treatment response. The purpose of this dissertation is to examine the biobehavioural predictors of treatment outcome in substance and alcohol use disorders through three distinct studies that each used pre-treatment variables to predict addictions treatment response. The first study used latent profile analysis to elucidate clinical profiles and independent variables associated with premature treatment termination from clinically complex sample of individuals with concurrent disorders at a large residential addiction treatment centre. The second study systematically synthesized and critically appraised empirical findings of delayed reward discounting, a transdiagnostic behavioural economic indicator of impulsivity, as a predictor of smoking cessation treatment outcome. Finally, the third study used baseline resting state functional connectivity (rsFC) to predict response to a brief intervention to reduce alcohol consumption at three-month follow-up in individuals with alcohol use disorder. The results of this dissertation extend the current literature and highlight the utility of pre-treatment clinical, behavioural, and neuroimaging data in predicting treatment response and elucidating pre-treatment patterns of rsFC that are associated with poor prognosis. The pre-treatment variables identified in this dissertation can be used to identify high-risk patient populations that may benefit from additional care pathways, adjunctive treatment, or further resources to improve patient outcomes and prognosis.

abstract: Thesis

abstract: Candidate in Philosophy

abstract: Approximately 1 in 5 Canadians will use alcohol or substances problematically within their lifetime. While there are well-researched treatments for problematic alcohol or substance use, individuals either have considerable difficulty completing treatment, or relapse following treatment. Investigating factors that can help individuals remain in treatment and maintain progress can be challenging since individuals with substance and alcohol use challenges are clinically complex patients who often present with additional mental health disorders. Understanding the pre-treatment factors that contribute to treatment outcome is critical to improving patient outcomes during and following addictions treatment. This dissertation examined the role of pre-treatment clinical patient profiles, impulsivity, and brain functional connectivity in predicting addictions treatment outcome. Clinically, these results will help identify patients at high risk of poor prognosis, who may benefit from additional resources during treatment to improve progress through treatment and treatment outcome.


title: An Investigation of Haptic Object Discrimination and Cue Combination

title: An Investigation of Haptic Size Discrimination and Cue Combination

title: Haptic Size Discrimination

contributor:
Goldreich, Daniel
Psychology

subject: Tactile Psychophysics Bayesian Computation

abstract: Perception relies on the integration of numerous noisy inputs (cues). Cue combination has been relatively understudied in somatosensation, compared to vision and audition. Here, we investigated whether haptic cutaneous and hand configuration cues are combined optimally to discriminate between coin-sized discs of different sizes. When the hand is open such that the thumb and index fingers span the diameter of a disc to contact its perimeter, cutaneous cues occur from the indentation of the skin caused by the curvature of the disc (smaller discs cause greater indentation). Simultaneously, the hand configuration cue (relating to the perceived distance between fingers), provides an additional cue to size. These cues may vary in their reliability. In three experiments involving 34 participants, we measured these cues and considered three hypotheses for how humans may use them: humans rely solely on the least noisy cue (Winner-Take-All Model), humans combine cues based on a simple average (Average-Measurement Model), or humans combine cues via an optimal weighted average (Optimally-Weighted Model). Each experiment tested participants using a two-interval forced-choice (2IFC) paradigm with 3D printed disc stimuli. On each trial, under occluded vision, participants felt two discs sequentially and responded which felt larger. Participants were tested with each finger’s cutaneous cue alone, the hand configuration cue alone, and all cues together. In two experiments, the presented discs were both circular. In a third experiment, unknown to participants, some of the presented discs were oval-like cue conflict stimuli. Participant performance was compared to predictions of the cue combination models. We conclude that humans may combine haptic cutaneous and hand configuration cues optimally to judge the size of held objects.

abstract: Thesis

abstract: Doctor of Philosophy (PhD)

abstract: The sense of touch is understudied compared to the senses of sight and hearing. But simply reaching for a coin without looking involves complex calculations and decision-making. We studied how the brain may approach tasks like this. We were interested in how well the brain deals with multiple sources of information that do not always agree with each other. We investigated these questions in computer simulations and in experiments with undergraduate participants. Using carefully designed 3D-printed discs, we tested dozens of participants across 3 different experiments. Our results show that humans may use information in the best possible way and applications relevant to VR and robot-assisted surgery.


title: An Encoding of the Clock Cycle Semantics of Bluespec SystemVerilog in PVS

title: ENCODING THE CLOCK CYCLE SEMANTICS OF BSV IN PVS

contributor:
Lawford, Mark
Computing and Software

subject:
verification
formal verification
Bluespec SystemVerilog
PVS
Formal Logic
Translation Software
Programming Languages
Hardware Description Languages
BSV

abstract:
The invention of Hardware Description Languages has given hardware designers access to powerful methods of abstraction and organization, previously only available to software developers.

A high-powered means of examining properties such as reliability, correctness and safety is the creation of formal, mathematical proofs of correctness.  One approach to this is the modelling of the artifact in the logic of some deductive system, such as the higher order logic of the Prototype Verification System (PVS).  The ambition of this work is to demonstrate a mechanism by which a class of hardware descriptions may be used to generate such models automatically.  We further demonstrate the utility of said models, using them to demonstrate non-trivial correctness properties.  We also present a method of generating hardware descriptions, logical models, and proofs from a class of tabular specifications.

The language on which this method operates is Bluespec SystemVerilog (BSV), a high-level hardware description language notable for its elegant semantics.  The target platform of our translation is the Prototype Verification System (PVS), which features a highly automatic theorem-proving system.  The translation algorithm is discussed at length, including the reconciliation of BSV's action-oriented semantic and the Kripke semantics employed by our chosen model in PVS.

Five case studies demonstrate our methodology.  In studies one and two, function blocks of the IEC 61131-3 Annex F library are verified against tabular specifications, or generated from the same.  The remaining case studies are based on the Shakti RISC-V implementation of the RapidIO subsystem.  Our final case study demonstrates progress towards the verification of highly abstract and complex properties over the entire translatable subset of the RapidIO library.

abstract: Thesis

abstract: Doctor of Philosophy (PhD)


title: AUTONOMOUS UNMANNED AERIAL VEHICLES (UAVs): SYSTEM DESIGN & OPTIMIZATION

contributor:
Mohamed, Moataz
Civil Engineering

subject:
Drones
UAVs
Optimization
Autonomous Transportation
Sustainability

abstract: The introduction of electric autonomous Unmanned Arial Vehicles (UAVs) in cities is considered the ultimate disruptive sustainable technological solution due to the promised speed, affordability, and significant greenhouse gas (GHG) emission reductions. The integration of UAVs into the future smart city fabric offers a wide range of applications. In particular, UAVs are ideal for last-mile operation, which is expected to reduce delivery costs, GHG emissions, and delivery time compared to light trucks and other traditional delivery methods. As UAVs operate in the city airspace, and with the current generation of older cities, several technological challenges arise with the anticipated proliferation of heterogeneous UAV fleets in low-altitude airspace of dense urban areas. Being a fairly new disruptive technology with no real-world operation data, the literature only considers a few of the system design parameters and often disregards the impact of other essential parameters such as Kinematics and airspace policies. This leads to significant uncertainty in the estimated UAV energy consumption, ranges, and emissions yielding inaccurate conclusions regarding the full system design predilections. Therefore, an effective UAV system design should strive to understand the broad spectrum of parameters’ impacts to optimize the integration and operation. Towards that end, this research aims at investigating the different UAV system design parameters and their intertwined impacts on operation efficiency to obtain accurate system optimization results. The research utilized several datasets for the delivery demand and digital-twin city model data of Toronto, Ontario, Canada. The research employed a state-of-the-art flexible energy use model for UAVs calibrated to experimental measurements to generate a minimum-energy trajectory along with several proposed novel airspace discretization, trajectory optimization, and charging infrastructure allocation optimization models. In this respect, this dissertation quantified the impact of airspace policies, discretization, and trajectory generation on the energy consumption of UAVs. Furthermore, it unveiled the operation uncertainties and their implications on the cost, emissions, and allocated charging infrastructure demand. Unlike the UAV literature, our research included all system design parameters and their impact on the performance metrics. The dissertation also proposes a novel combined airspace discretization and trajectory generation algorithm for optimal UAV energy consumption, airspace capacity maximization, airspace traffic control, and off-grid solar charging station allocation. For instance, it is found that UAV deployment with carefully tailored airspace policies in delivery could reduce GHG emissions in the freight sector by up to 35% compared to EVs. Furthermore, the research highlighted how building integrated photovoltaic BIPV upgrades with associated buildings can eliminate GHG emissions and significantly reduce the decarbonization price through associated savings and excess generated electricity. Overall, this research presents a unique contribution to the knowledge of UAV research for practitioners, policymakers, and academia.

abstract: Thesis

abstract: Doctor of Philosophy (PhD)


title: Agency, Responsibility, and the Self

title: A Critical Analysis of the Ability to Choose Otherwise Through the Lens of Nietzsche, Heidegger and Sartre

contributor:
Steizinger, Johannes
Philosophy

subject: Nietzsche Heidegger Sartre Agency Responsibility Choice Autonomy Authenticity Causation Dependence

abstract: The aim of this thesis is to determine whether having an ability to choose otherwise aids our understanding of the kind of balanced autonomy that is required in order to claim that people should be held responsible for their actions. By looking to the theories of three historical philosophers (Friedrich Nietzsche, Martin Heidegger, Jean Paul Sartre), I find evidence that suggests having an ability to choose otherwise should not be the ground on which we base responsibility for an agent’s actions; actions involve ‘choosing one’s self’ and there is a relationship one has to one’s self which is often overlooked. My investigation reveals evidence that existential authenticity is an inherent quality of autonomy and that the ‘genuine self’ which grounds an agent’s actions ought to be viewed as a ‘dependence’ rather than a ‘cause’. My investigation also reveals a concept of a ‘genuine self’ as distinct from the concept of a narratively structured ‘ego’; the self and the ego appear to be distinct entities which are existentially interdependent. This thesis raises questions which should be addressed in future investigations. First, how is, and how should responsibility be related to the dependences from which actions arise and second, is the objective world best understood as causally structured, in accordance with the doctrine of determinism, or rather, should we seek an understanding of the objective world as dependently structured.

abstract: Thesis

abstract: Master of Philosophy (MA)

abstract: Is having an ability to choose otherwise the best ground on which to hold persons responsible for their actions? This thesis considers the works of Friedrich Nietzsche, Martin Heidegger and Jean-Paul Sartre, which reveal some evidence that persons should not be held responsible for their actions on the basis of being able to choose otherwise. I argue that authenticity is an inherent feature of autonomy which involves the relationship one has to one’s self and ‘choosing one’s self’; and that there is a distinction to be made between the ‘ego’ and the ‘self’. Further, I advance an argument that actions are dependent on a ‘self’, but that the ‘self’ is not a cause of action. This thesis raises questions to be addressed in future investigations regarding the connection between responsibility and dependence as well as whether the world is best understood as dependently structured rather than causally structured.


title: A Diachronic Study of Clytemnestra's Characterization in the Agamemnon

contributor:
Mattison, Kathryn
Classics

subject:
Greek Tragedy
Gender
Clytemnestra
Aeschylus
Greek Literature
Reception Studies
Characterization
Women in Tragedy

abstract: My thesis examines the evolution of Clytemnestra’s characterization throughout the generations of receptions of Aeschylus’ Agamemnon. This diachronic study investigates how Clytemnestra’s complex use of gender, specifically her use of masculinity, allows her character to be understood in a different light by a modern audience in contrast to the original perception of her character in antiquity. In analysing the aspects that contribute to Clytemnestra’s ancient characterization, which display her to be dangerously masculine to a fifth-century male audience, the meaning behind her behaviour is also revealed, as it opens a discussion on masculinity in Athens through Clytemnestra’s emasculation of the men around her. The true depth of her character is revealed through a study of Clytemnestra’s modern characterization, as modern audiences are able to recognize the sympathetic aspects of her character in the text, which are reflected through the various feminist adaptations and performances today. The paradox of Clytemnestra’s characterization demonstrates the impact that she has not only on the plot of the play, but also on its survival, as her complexity is what continues to engage audiences in modernity. The findings of this thesis will demonstrate the importance of female characters in Greek tragedy through examining the various layers of Clytemnestra’s character that are uncovered by comparing her characterization in antiquity and modernity, thus proving that her figure, and tragedy overall, has the ability to evolve and influence audiences yet to come through the impact of these dynamic women.

abstract: Thesis

abstract: Master of Arts (MA)


title: A RECONSTRUCTION OF THE LOST TEMPLE OF JANUS: NERONIAN SESTERTII, 64/65 CE

contributor:
Beckmann, Martin
Classics

subject:
Nero
Temple of Janus
Coins

abstract: The Temple of Janus was an important and symbolic temple in Rome. The doors served as an index for peace and war and were either opened or closed accordingly. The only contemporary depiction of the temple is the Neronian coins that were struck in 64/5 CE in both Rome and Lugdunum in celebration of Nero’s defeat of the Parthians. This coin type is the only evidence that we have left of the Temple of Janus since the temple is lost and has no remains left. Therefore, it is necessary to analyze the depictions of the temple on these coins to discover the most reliable and accurate representation of the Temple of Janus since they are the only evidence left of its appearance. By discovering the exact order of striking and observing how the appearance of the temple changed over time in the earliest Neronian sestertii, I will attempt to uncover the most accurate depiction of the Temple of Janus. The architectural features present on the earliest dies, which will be discovered by means of a die study, will be further analyzed by un-manipulating its numismatic representation; this is because die engravers had certain working methods that they would use to manipulate the appearance in order to depict a large monument on such a small medium. I will then undo these changes made to the depiction of the temple in order to discover the true architectural features of the temple and therefore reconstruct the lost Temple of Janus and uncover its original appearance.

abstract: Thesis

abstract: Master of Arts (MA)


title: The effect of brief bodyweight exercise on acute glycemic control in healthy inactive adults.

contributor:
Gibala, Martin
Kinesiology

subject: glycemic control, bodyweight exercise, glucose, continuous glucose monitoring

abstract:
Introduction: Brief vigorous exercise can enhance glycemic control. Limited work has investigated the effect of simple, practical interventions that require no specialized equipment. We examined the effect of bodyweight exercise (BWE) on acute glycemic control using continuous glucose monitoring (Abbott Libre Sense) under controlled dietary conditions This study was registered as a clinical trial (NCT05144490).
Methods: Twenty-seven healthy adults (8 males, 19 females; age: 23±3 y) completed two virtually supervised trials in random order ~1 wk apart. The trials involved an 11-min BWE protocol that consisted of five, 1-min bouts performed at a self-selected pace interspersed with 1-min active recovery periods or a non-exercise sitting control period (CON). Food intake was standardized for each participant using pre-packaged meals supplied over 24 h.
Results: Mean rating of perceived exertion for BWE was 14±2 (6-20 scale). Mean HR over the 11-minute the BWE protocol was 147±14 bpm which corresponded to 75% of age-predicted maximal HR. Mean 24-h glucose after BWE and CON was not different (5.0±0.4 vs 5.0±0.5 mM respectively; p=0.39). Postprandial glucose responses were also not different between trials after ingestion of a 75 g glucose drink, lunch, dinner and breakfast meals after each intervention. Measures of glycemic variability were not different between conditions.
Conclusion: A single session of BWE did not alter acute glycemic control in healthy, young adults. This study demonstrates the feasibility of conducting a remotely supervised BWE intervention using CGM under free-living conditions. Future studies should investigate the effect of repeated sessions of BWE training as well as responses in people with impaired glycemic control.

abstract: Thesis

abstract: Master of Science (MSc)

abstract: We investigated the effect of brief bodyweight exercise (BWE) on glycemic control. This refers to the ability to maintain blood sugar within a healthy range. Glycemic control was assessed with a small device called a continuous glucose monitor (CGM) that is inserted just below the skin. Healthy adults completed a virtually supervised 11-minute BWE protocol or an equivalent period of sitting. There was no difference in glycemic control measured over 24 hours following the BWE compared to sitting under standardized dietary conditions. Future studies should investigate the effect of repeated sessions of BWE training as well as responses in people with impaired glycemic control.


title: Statistical Mechanics From Unitary Dynamics

contributor:
Sorensen, Erik
Physics and Astronomy

subject:
Statistical Mechanics
Quantum Mechanics
Many Body Physics
Thermodynamics

abstract: In this thesis I present a derivation of statistical mechanics starting from a closed, isolated quantum many body system. I first establish under what conditions we expect static equilibrium to emerge. It is found that the purity of the diagonal ensemble is a sufficient criteria for equilibration to occur and avoid short time recurrences. I next derive the usual ensembles of statistical mechanics using the principle of maximum entropy. These ensembles are then connected to the diagonal ensemble through the strong and the weak eigenstate thermalization hypothesis (ETH). Counter examples to ETH are discussed along with the process of scrambling. The thesis contains three contributed articles relevant to this introductory chapter studying early time relaxation, recurrences and scrambling.

abstract: Thesis

abstract: Doctor of Philosophy (PhD)


title: Integrated Energy Management and Autonomous Driving System: A Driving Simulation Study

contributor:
Emadi, Ali
Mechanical Engineering

subject:
energy management strategies
electrification
autonomous vehicles
vehicle dynamics
driving simulation
hybrid electric vehicles

abstract:
In searching for more efficient vehicles with lower carbon emissions, researchers have invested enormous time and resources in designing new materials, components, systems, and control methods. The result is not only an immense volume of publications and patents but also a true electrification revolution in the transportation sector. Although the advancements are remarkable, much is still to be developed. Energy management systems are often designed to fulfil drive cycles that represent just a fraction of the actual use of the vehicles, disregarding essential factors such as driving conditions that may vary in real life. Furthermore, control algorithms should not ignore one of the most relevant driving aspects, comfort. Driving should be a pleasant activity since we spend much time of our lives performing this task.
This research proposes a novel algorithm for managing energy consumption in electrified vehicles, the regen-based equivalent consumption minimization strategy (R-ECMS). Its suitability for solving the power-split problem is evaluated. Experiments emulating labelling schedules are conducted considering an example application. Robustness to different drive cycles and flexibility of the algorithm to various modes of operation are assessed. Furthermore, the method is integrated into an autonomous longitudinal control. The function leverages vehicle dynamics and journey mapping to assure energy efficiency and adequate drivability. Finally, the tests are conducted using human-driven cycles leveraging driving simulation technology. That allows for including driver subjective feelings in the design
and assessing the algorithm's performance in realistic driving conditions.

abstract: Thesis

abstract: Doctor of Philosophy (PhD)


title: The Formation Mechanisms of Galaxy Tails: A Statistical and Case Study

contributor:
Wadsley, James
Parker, Laura
Physics and Astronomy

subject:
Galaxy
Jellyfish
CGM
Tails
Ram Pressure
Simulation
SPH
Entrainment

abstract:
Using a hydrodynamical smoothed particle hydrodynamics (SPH) zoom-in simu lation of a galaxy group, we present a set of tail identification methods, and study
the statistical properties of galaxy tails and their correlations with their expected
formation mechanisms. We have a sample of 4548 M > 108 M⊙ galaxies across 58
snapshots from z = 0.67 to z = 0. For each galaxy, we apply a series of velocity and
density cuts to identify the tail. We observed no significant correlations between
galaxy tail mass and ram pressure, though we note some issues with our sampling.
Tracking four visually identified jellyfish galaxies over time showed some evidence
of increased ram pressure driving ISM mass loss, as well as spikes in tail mass pre ceding spikes in ram pressure with temporal offsets ranging from 500 Myr to 2 Gyr.
No correlation was found between ISM mass and tail mass. We track the tail gas
of a particularly well defined jellyfish galaxy 3.2 Gyrs back in time. We find that
a lower bound of 30% of the tail gas was never in the ISM. Distinguishing between
former ISM tail material and never ISM-accreted tail material, we see evidence of
temperature mixing with the IGM in the former. Velocity and radial trajectory
maps show a sharp impulse of ∆v ≈ 50 km s−1 over 4 snapshots, affecting both
the never ISM-accreted tail material and CGM material, with the former showing
evidence of momentum mixing onto the former ISM material. Combined with ob servations of CGM stripping, we propose that a significant portion of galaxy tails
consists of stripped CGM that got swept up into the stripped ISM

abstract: Thesis

abstract: Master of Science (MSc)


title: Investigating the Role of Virus-Mediated Tumour Modulation in T Cell Centric Cancer Immunotherapy

contributor:
Wan, Yonghong
Health Sciences

subject:
Cancer Immunotherapy
Oncolytic viruses
Oncolytic vaccines
Adoptive T cell Therapy
Vaccinia Virus
Vesicular Stomatitis Virus

abstract: Cancer immunotherapy continues to be at the forefront of cancer treatment modalities delivering unprecedented outcomes. In this thesis we have investigated the combination of Oncolytic Viral Vaccines (OVVs) and Adoptive T Cell Therapy (ACT) for treating solid tumours. We used animal models, flow cytometry and high throughput transcriptomic analyses to characterize the therapeutic outcomes of such combination and understand the mechanisms behind its success on cellular and molecular levels. We focused on comparing the behaviour of different viruses, Vesicular Stomatitis Virus (VSV), and Vaccinia Virus (VacV), and showed that the choice of viral backbone indeed shapes the therapy outcome. While both viruses can achieve complete tumour regression when combined with ACT, VSV-treated tumours relapse shortly after remission. Additionally, we studied the effect of the virus route of administration and observed that intratumoural (IT) delivery leads to better overall survival of mice compared to intravenous (IV) delivery regardless of the viral backbone. Furthermore, we evaluated the necessity of virus replication in different tumour models. Our results show that virus replication, despite being dispensable for immunogenic tumour models, is necessary for durable outcomes in immunosuppressive models. Importantly, the reprogramming of the tumour microenvironment (TME) by OVVs was shown to be crucial for therapy success. Specifically, we show that unlike VSV, VacV is able to induce more inflammatory pathways, block metabolic pathways, cell cycle pathways and DNA repair pathways. We highlighted the role of inhibiting DNA repair pathways in preventing antigen loss and immune escape. Lastly, we examined the effect of the transcriptomic signature induced by VacV on the prognosis and survival of Skin Cutaneous Melanoma (SKCM) patients using a public dataset derived from the Cancer Genome Atlas (TCGA). Our analysis demonstrates that VacV transcriptomic signature correlates with favorable disease prognosis and better overall patient survival. In conclusion, the research described in this thesis reveals important insights pertaining to the choice of viral backbone, route of administration and unveils additional mechanisms by which OVVs complement the CD8+ T cell mediated elimination of tumour cells.

abstract: Dissertation

abstract: Doctor of Philosophy (Medical Science)


title: Computational inference and prediction in public health

contributor:
Jonathan, Dushoff
Computational Engineering and Science

subject:
Machine learning
Public health
Cancer
Survival data

abstract: Using computational approaches utilizing large datasets to investigate public health information is an important mechanism for institutions seeking to identify strategies for improving public health. The art in computational approaches, for example in health research, is managing the trade-offs between the two perspectives: first, inference and second, prediction. Many techniques from statistical methods (SM) and machine learning (ML) may, in principle, be used for both perspectives. However, SM has a well established focus on inference by building probabilistic models which allows us to determine a quantitative measure of confidence about the magnitude of the effect. Simulation-based validation approaches can be used in conjunction with SM to explicitly verify assumptions and redefine the specified model, if necessary. On the other hand, ML uses general-purpose algorithms to find patterns that best predict the outcome and makes minimal assumptions about the data-generating process; and may be more effective in a number of situations. My work employs both SM- and ML- based  computational approaches to investigate particular public health problems. Chapter One provides philosophical background and compares the application of the two approaches in public health. Chapter Two describes and implements penalized Cox proportional hazard models for time-varying covariates time-to-event data. Chapter Three applies traditional survival models and machine learning algorithms to predict survival times of cancer patients, while incorporating the information about the time-varying covariates. Chapter Four discusses and implements various approaches for computing predictions and effects for generalized linear (mixed) models. Finally, Chapter Five implements and compares various statistical models for handling univariate and multivariate binary outcomes for water, sanitation and hygiene (WaSH) data.

abstract: Thesis

abstract: Doctor of Philosophy (PhD)


title: Comparing Quality Indicator Rates for Home Care Clients Receiving Palliative and End-of-Life Care Before and During the COVID-19 Pandemic

contributor:
Kaasalainen, Sharon
Fisher, Kathryn
Northwood, Melissa
Guthrie, Dawn
Nursing

subject:
Quality indicators
Palliative and end-of-life care
Home care
Quality

abstract:
Background. The consensus among Canadians with regards to end-of-life preferences is that with adequate support the majority prefer to live and die at home.
Purpose. To compare quality indicator (QI) rates for home care clients receiving palliative and end-of-life care prior to and after the onset of the COVID-19 pandemic.
Methods. A retrospective population-based cohort design was used. Sixteen QIs informed by existing literature and a preliminary set of QIs recently evaluated by a modified Delphi panel were compared. Data were obtained from the over 280-item interRAI PC instrument for Ontario home care clients for two separate cohorts: the pre-COVID (January 14th, 2019 to March 16th, 2020) and COVID cohort (March 17th, 2020 to May 18th, 2021). A propensity score analysis was used to match on 21 covariates, resulting in a sample size of 2479 unique interRAI PC assessments per cohort. Alternative propensity score methods were explored as part of a sensitivity analysis.
Results. After matching the pre-COVID and COVID cohorts (using nearest neighbour matching), five of the 16 QIs had statistically-significant differences in the QI rates. The two alternative propensity score methods produced slightly different results with fewer statistically-significant differences between the cohorts. However, in examining the effect sizes, the results of all propensity score methods were found to be not clinically meaningful. High rates of the prevalence of shortness of breath with activity, no advance directives, and fatigue were observed in both cohorts and across all three propensity score methods.
Discussion. This study is the first to examine differences in QI rates for home care clients receiving palliative and end-of-life care before and during COVID in Ontario. Key limitations in interpreting the results include a limited understanding of the typical variation in QI rates over time and reliance on the comparison of a single proportion (the QI) in judging potential differences in quality. Importantly, a strength of this study was that these QIs focused on outcomes of care and were mainly symptom-focused as aspects of high-quality care valued by home care clients and families and in contrast to previous studies focusing on structure and processes of care. These QIs also indicated how frequently quality concerns may be occurring for those receiving palliative and end-of-life home care.
Conclusion. It appears that QI rates did not change over the course of the pandemic in this population. Future work should be directed to understanding the temporal variation in these QI rates, risk-adjusting the QI rates for further comparison among jurisdictions, provinces, and countries and in creating benchmarks to project acceptable rates of different QIs.

abstract: Thesis

abstract: Master of Science in Nursing (MSN)


title: ANTIBIOTICS USE FOR TREATING HOSPITALIZED COVID-19 PATIENTS: A SYSTEMATIC REVIEW & META-ANALYSIS

contributor:
de Souza, Russell
Global Health

subject:
COVID-19
SARS-COV-2
Corona
COVID
Pandemic
Antimicrobial resistance
Antibiotic resistance
AMR
Systematic review
Meta-analysis

abstract:
ACKNOWLEDGEMENTS

I would like to take this moment to extend my utmost appreciation for all the support provided by my supervisor, Dr. Russell de Souza. He assisted me along the way and ensured that I was always on the right path to achieve all my goals and checkpoints in every circumstance. I would also like to thank my committee for providing me with fantastic support: Ms. Laura Banfield for always being there to help solve any problem in this process, and Dr. Zain Chagla for providing a plethora of knowledge from the technical perspective of infectious disease and being so patient. Special thanks to Dr. Alexandra Mayhew for her support in our prevalence meta-analysis. Finally, I would like to thank my family, my wife, Dr. Sanjida Rowshan Anannya, for whom I am here today, and my parents, siblings, and in-laws; you are always there for me in every walk of life. You are why I have gotten to where I am today and are my daily inspiration.

abstract:
Background: Bacteria is a major cause of many infectious diseases, and the treatment for these diseases is antibiotics designed to kill or subdue the growth of the bacteria. However, bacteria evolve, and if an antibiotic prescription is not the right antibiotic for the right patient at the right time with the correct dose and the right route, Antimicrobial Resistance (AMR) may result. During this pandemic, the use of antibiotics to treat hospitalized COVID-19 patients without any bacterial coinfection threatens the effectiveness of antibiotic treatment for current and future bacterial infections.
Methods: A systematic search was conducted of the Embase, Medline, Web of Science, and Cochrane Library databases by generating search terms using the concepts of “COVID-19,” “Bacterial Coinfection,” “Secondary bacterial infection,” and “Antimicrobial resistance” to identify studies that reported the prevalence of antibiotic prescription for the treatment of COVID-19 in hospitalized patients with and without bacterial coinfection. The pooled estimate of the percentage of the total and confirmed appropriate antibiotic prescriptions provided to hospitalized COVID-19 patients was generated using a random effect meta-analysis with inverse variance weighting.
Result: Of 157,623 participants from 29 studies included in our review, 67% (CI 64% to 71%, P<0.00001) were prescribed antibiotics, among which 80% (CI 76% to 83%, P<0.00001) prescriptions were given for the COVID-19 patients without any bacterial coinfections. The use of antibiotics varied during the pre-immunosuppressive period (before 16 June 2020) and post-immunosuppressive period of the pandemic and between the High-Income Countries and Upper and Lower Middle-Income Countries.
Conclusion: This Systematic Review and Meta-analysis finds greater than expected use of antibiotics to treat hospitalized COVID-19 patients without bacterial coinfections, which can worsen AMR globally. Clear and concrete guidelines for the use of antibiotic prescriptions to treat COVID-19 patients, strict monitoring, and compliance with Antimicrobial Stewardship are needed to prevent over-prescription.

abstract: Thesis

abstract: Master in Advanced Studies (MAS)

abstract: Bacteria is a major cause of many infectious diseases. Before the discovery of Antibiotics in 1928, hundreds of thousands of people used to die due to infectious diseases caused by bacteria. While Antibiotics are essential to treat bacterial infectious diseases, overuse or misuse can accelerate Antibiotic Resistance, a phenomenon when bacteria change and/or develop the ability to escape the drugs designed to kill them. Self-medication, availability of antibiotics without a prescription, and inappropriate dosing of antibiotics can worsen the situation. During the COVID-19 pandemic, antibiotics were commonly prescribed as part of the treatment regime for COVID-19, even when a clear bacterial infection was not identified. In our Systematic Review and Meta-analysis, we aimed to see the frequency of antibiotic prescriptions to treat hospitalized COVID-19 patients without any bacterial coinfections.


title: Resting State Functional Connectivity and Alcohol Misuse in Heavy Drinking Adults

contributor:
MacKillop, James
Moulden, Heather
Neuroscience

subject: alcohol fMRI neuroimaging resting-state

abstract:
Purpose: The triple network model posits that the salience network (SN), default
mode network (DMN), and central executive network (CEN), are essential in
understanding higher cognitive function and dysfunction. These networks are affected
variably across many psychiatric conditions. Previous functional magnetic resonance
imaging (fMRI) research in alcohol use disorder (AUD) has found altered functional
connectivity in the SN, DMN, and CEN, suggesting all three networks may be involved.
The current study utilizes fMRI to investigate the association between resting-state
functional connectivity in the SN, DMN, and CEN and alcohol misuse.
Methods: Fifty-two heavy drinking adults completed measures of alcohol use severity
and quantity, as well as a 7-minute resting state scan.
Results: Linear regression was used to test if connectivity was associated with past
12-month AUD symptoms and number of heavy drinking days. Results revealed that
CEN connectivity (right lateral prefrontal cortex seed co-activating with 19 clusters)
was significantly associated with AUD symptoms (b = .425, p = .003), but not heavy
drinking days. Post-hoc tests revealed six clusters co-activating with the CEN were
associated with AUD symptoms – right middle frontal gyrus, right inferior parietal
gyrus, left middle temporal gyrus, left cerebellum 7b, right cerebellum 7b, and left
cerebellum 9. DMN and SN connectivity was not associated with drinking outcomes.
Conclusion: These findings illustrate that connectivity within the CEN, but not the
DMN or SN, is associated with alcohol use severity. Regarding the triple network
model, these results suggest that altered functional connectivity in heavy drinkers is
located primarily in the CEN.

abstract: Thesis

abstract: Master of Science (MSc)

abstract:
Alcohol use disorder is a complex condition that is not yet fully understood,
especially when it comes to the underlying changes in the brain. One theory suggests
that individuals with mental health conditions show changes in one or more of three
key networks in the brain. These networks are essential in understanding higher
cognitive function and dysfunction (e.g., emotional regulation and problem solving).
This theory suggests that the range of damage in these networks leads to the
differences in symptoms and symptom severity that individuals experience. Prior
research among alcohol users has found changes in connectivity in all three networks,
suggesting they may all be involved. This study used neuroimaging to examine
whether connectivity was associated with alcohol misuse. We found that connectivity
in the network involved in decision-making and problem solving was associated with
alcohol use severity, suggesting this network may be a useful target for new treatment
strategies.


title: Combining reversible interactions and controlled degradation for hydrogel-only pulsatile protein release

contributor:
Wylie, Ryan
Chemistry and Chemical Biology

abstract: Due to transport barriers and biological responses, repeated local injections are often required to achieve efficacy for protein-based therapeutics and vaccines. Strategies to achieve timed burst releases of proteins with a single injection are being developed to avoid the need for multiple injections, especially for high-risk injections or the treatment of remote populations. Herein, we report the first hydrogel platform that tunes two burst releases of a therapeutic antibody, bevacizumab, by combining an iminoboronate affinity release system with controlled hydrogel hydrolysis. The first burst release is controlled by the protein-iminoboronate reversible covalent interaction, where iminoboronate is immobilized to the polymer network, and can be tuned by (1) using a protein modified with oxyamine moieties to enhance complex formation, and (2) the inclusion of fructose, which decreases the strength of the protein-iminoboronate interaction. Protein release from hydrogels with affinity-controlled release mechanisms, which is similar to the reversible protein-iminoboronate interaction, often plateaus, which reserves protein for the second burst release. The timing of the second burst release, which comprises of terminating protein after the initial burst, is then controlled by the hydrolytic crosslink, which occurred ~3-4 weeks after initial hydrogel formation. Hydrogel degradation rates can be further tuned by altering hydrolysis kinetics. Therefore, affinity release in combination with controlled degradation allows for the construction of hydrogel platforms to achieve two burst releases from a single injection.

abstract: Thesis

abstract: Master of Science (MSc)


title: Maximizing Driving Range for Fuel Cell Range Extender Vehicles with Fixed Energy Storage Costs

contributor:
Bauman, Jennifer
Electrical and Computer Engineering

subject:
fuel cells
modeling
optimization methods
vehicles

abstract:
Industry and researchers are investigating both battery electric vehicles (BEVs) and
fuel cell hybrid vehicles (FCHV) for the future of sustainable passenger vehicle technology.
While BEVs have clear efficiency advantages, FCHVs have key benefits in terms of
refueling time and energy density.
This thesis first proposes the concept of a fuel cell range extended vehicle (FCREV)
that uses Whole-Day Driving Prediction (WDDP) control, which uses driver destination
inputs to determine whether the planned driving trips that day will exceed the useable
battery energy capacity. If so, the fuel cell is turned on at the start of the day. The benefit
of WDDP control is that a smaller, lower cost fuel cell can be used to greatly extend the
driving range, since the fuel cell can charge the battery during both driving and parked
periods of the day. Furthermore, this research proposes a fast analytical optimization
algorithm for designing a WDDP-FCREV to maximize range on a given drive cycle for a
set cost. The results show an optimized WDDP-FCREV can greatly exceed the range of a
same-cost BEV, by 105% to 150% for no H2 refueling and by 150% to 250% when H2
refueling is allowed every 4 hours.

abstract: Thesis

abstract: Master of Applied Science (MASc)


title: Development of Hard PVD Coating Systems for Machining Austenitic Stainless Steels

contributor:
Veldhuis, Stephen
Mechanical Engineering

subject:
PVD coatings
Machining
Stainless steels

abstract: PhD thesis on developing PVD coating systems for high speed machining of austenitic stainless steels

abstract: Application of hard coatings was found to be a promising method in response to industry’s growing demand for improved productivity and avoiding high temperature in cutting zone. Cutting speed as a one of the major factors of productivity, significantly increase the heat generation and temperature in cutting zone. Therefore, using protective coatings with higher thermal stability is required to maintain the productivity at high level. This research investigated the effect of Al concentration in Ti1-xAlxN lattice with various x amount during high-speed machining of austenitic stainless steels. The results showed that higher up to a certain point, thermal stability, mechanical properties, machining performance of the coating improved. Above this point, a drop in properties was observed associated with a change in crystal structure. further development in coating properties was obtained by incorporating Ta into TiAlN coating. As a results, a significant improvement in mechanical properties, 25% prolonged tool life at higher cutting speed (650 m/min), better thermal stability and excellent oxidation resistance was obtained. Out of different coating architecture, the results showed that monolayer TiAlTaN coating showed best properties.

abstract: Dissertation

abstract: Doctor of Philosophy (PhD)

abstract: Recent developments in materials selections and machining processes have introduced hard-to-cut materials to the modern manufacturing industry. The ever-increasing demands for high-speed machining of hard-to-cut materials highlight the importance of efficient cutting tools protection with high-performance coatings. Physical vapor deposition is an effective method to alter superficial tool properties by applying a thin layer of hard coating and, thus, protecting the tool during the machining process. In recent research, Ti1-xAlxN coatings with various x content and Ti-Al-Ta-N-based coating has been developed for machining of austenitic stainless steel. Thermal stability, mechanical properties, oxidation resistance and machining performance have been evaluated. Results showed more than 25% improvement in tool life during high speed machining, significant increase in mechanical properties and higher oxidation resistance and thermal stability associated with incorporation of Ta into Ti-Al-N coating.


title: The efficacy of aspergillomarasmine A to overcome β-lactam antibiotic resistance

title: The efficacy of aspergillomarasmine A

contributor:
Wright, Gerard
Biochemistry and Biomedical Sciences

subject:
Antibiotic Resistance
β-Lactams
β-Lactamases

abstract: While antibiotics have saved the lives of millions of people since the discovery of the first β-lactam, penicillin, their continued effectiveness is being increasingly threatened by resistant bacteria. Bacterial resistance to β-lactams is mainly achieved through the production of serine-β-lactamases (SBLs) and metallo-β-lactamases (MBLs). Although both types of β-lactamases are commonly isolated in clinical settings, MBLs represent the greatest threat to public health since they are resistant to SBL inhibitors and most β-lactams. However, aspergillomarasmine A (AMA), a fungal natural product synthesized by Aspergillus versicolor, was shown to be a rapid and potent inhibitor against two clinically relevant MBLs: NDM-1 and VIM-2. In bacteria possessing these enzymes, AMA could rescue the activity of meropenem, a broad-spectrum β-lactam that is usually reserved for the treatment of the most severe bacterial infections. However, many questions remain revolving around AMA's inhibitory potency and spectrum. Therefore, the activity of AMA in combination with six β-lactams from three subclasses (carbapenem, penam, cephem) was explored against 19 MBLs from three subclasses (B1, B2, B3). After determining that AMA activity was linked to MBL zinc affinity and that AMA was more potent when paired with a carbapenem, the efficacy of an AMA/meropenem combination was evaluated with and without avibactam, a potent SBL inhibitor. This study used ten Escherichia coli and ten Klebsiella pneumoniae laboratory strains as well as 30 clinical strains producing at least one MBL and one SBL. Once establishing that the AMA/avibactam/meropenem combination was effective against carbapenemase-producing Enterobacterales, new Acinetobacter and Pseudomonas shuttle vectors were created. With these shuttle vectors, it was determined that the AMA/avibactam/meropenem combination was effective against some of the bacteria topping the World Health Organization’s priority pathogen list.

abstract: Thesis

abstract: Doctor of Philosophy (PhD)

abstract: Bacteria are all around us. While some bacteria can promote human health, others can cause serious infections. These infections are typically treated with antibiotics. β-Lactam antibiotics, such as penicillins and cephalosporins, are especially important to medicine. Unfortunately, an increasing number of bacteria employ enzymes, known as β-lactamases, which negate the effects of β-lactam antibiotics. Previous studies demonstrated that a natural product, known as aspergillomarasmine A (AMA), could inhibit some β-lactamase enzymes. Consequently, the inhibitory power of AMA was further explored against a larger number of β-lactamase enzymes and in combination with different β-lactam antibiotics. After discovering that AMA had more inhibitory power when combined with a β-lactam antibiotic known as meropenem, the efficacy of the AMA/meropenem pairing was evaluated against resistant bacteria in the presence and absence of avibactam, another β-lactamase inhibitor. The AMA/avibactam/meropenem combination was shown to be effective against some of the world’s most antibiotic-resistant bacteria.


title: DEGRADATION OF SOFC AND SOEC AND ITS IMPACT ON SYSTEM OPERATION

contributor:
Adams II, Thomas A.
Chemical Engineering

abstract:
The key to a cleaner future is to alleviate reliance of energy sectors on non-renewable fossil fuel sources and reduce their environmental burdens. This can be achieved by using power generation units such as Solid Oxide Fuel Cell (SOFC) that use natural gas more efficiently compared to the existing fossil fuel-based technologies as well as energy storage units such as Solid Oxide Electrolysis Cell (SOEC) that enable increase in the amount of intermittent renewable power supply.
This thesis describes the models constructed for conventional SOFC and SOEC degradation to show how performance of these cells degrade over long periods of time under their operating conditions. The goal of this thesis is to evaluate the economic and environmental performance of SOFC and SOEC under degradation and compare them to the existing technologies.
In this thesis project, the economically optimal sizing, and trajectories of natural gas-SOFC and SOEC are found considering their degradation. Impacts of SOFC capital cost, price of natural gas, and CO2 tax on economic performance of SOFC and impacts of SOEC capital cost and price of electricity on economic performance of SOEC are quantified to help decision makers evaluate economic feasibility of these cells in different locations. Economical operation of an SOFC plant requires lowering its current density slowly over time which results in power output reduction. This can limit the application of SOFC for communities that need constant load of power all the time. To combat this issue, this thesis also focuses on scheduling start-up of optimally operated SOFC modules such that SOFC system as a whole has a constant power output.
This thesis assesses environmental performances of SOFC and SOEC and compares them with the existing technologies. A detailed life cycle analysis of optimally operated natural gas-fueled SOFC plant under degradation is performed using ReCiPe 2016 and TRACI 2.1 US-Canada 2008 methods. Then, it compares the major environmental impact categories of this plant with those of two mature technologies that use natural gas for power generation. Moreover, life cycle greenhouse gases (GHG) emitted from manufacturing SOEC and its power source are quantified to assess environmental performance of SOEC. This is performed for SOECs with various power sources from low GHG emission sources to high GHG emission ones. The levelized cost of hydrogen and life cycle GHG emissions of SOECs with different power sources are then compared to those of other hydrogen generation units.
SOFC can serve as an efficient, cost-effective, environmentally friendly option for power only or heat and power generation in many places even at high natural gas prices and carbon taxes. While SOEC, despite its high efficiency, might not be a very economical or environmentally responsible option for hydrogen production when the price of electricity is high and power supply has high GHG emissions.

abstract: Thesis

abstract: Doctor of Engineering (DEng)


title: FEASIBILITY & COST-IMPLICATION ANALYSIS OF THE CARER-INCLUSIVE ORGANIZATIONAL STANDARD AS AN INTERVENTION

contributor:
Williams, Allison
Geography

abstract:
Canada’s aging demographics has produced a crisis in which the working age population is increasingly required to provide unpaid care for aging friends, family or relatives while maintaining employment responsibilities. Currently, there are 8.1 million carers in Canada, with 6.1 million of these carers simultaneously managing their own careers/paid employment alongside these care duties. This dual role of carer and employee places physical and mental burden on a growing number of carer-employees, and is associated with adverse effects on both health and work performance. The literature suggests that adverse effects such as stress, depression, anxiety are associated with caregiving burden, and can manifest in physical symptoms affecting health such as sleep deprivation or fatigue. Additionally, care-work conflict may impede work responsibilities by increasing absenteeism/presentism, reducing productivity, delaying career development and early retirement from the workforce. As a result of these adverse consequences, an understanding of the role the employer plays in supporting carer-employees needs is critical, as these arrangements are mutually beneficial for both employer and carer-employee.

However, evidence of the effectiveness of workplace interventions for carers is nascent; additional investigation is needed in order to bridge this gap and encourage widespread uptake of carer initiatives in the private sector. In this dissertation study, an intervention is implemented within a large-sized workplace. We evaluate the following questions: 1) How has COVID-19 impacted the workplace and the nature of caregiving?; 2) What are the gaps within the workplace pertaining to baseline carer-supportive workplace culture?; 3) Does our designed intervention improve work and health outcomes of employees?; 4) Is the intervention cost-saving from the employer’s perspective? These research questions contribute to the paucity of knowledge on this topic as well as providing actionable evidence and tools for employers and policymakers to stimulate change.

We found that with the transition to remote working during COVID, carers were struggling with the work-life balance due to the undefined boundaries between work, care and personal life, this effect was exacerbated by the closure of community carer supports, thereby increasing feelings of isolation. However, flexibility and privacy was gained as a result of this arrangement. In designing a tailored intervention, we highlighted that within our partnered workplace, carers had significantly less coworker support, and employee-rated family supportive supervisor behaviour was dispersed across all potential score ranges. As a result, our designed intervention focused on generating a supportive and approachable work culture for carers, centered around education and consciousness-raising. With the implementation of the intervention however, we found mixed results. We did not observe significant changes in employee health and work outcome variables post-intervention compared to pre-intervention, nor did we find the intervention to be cost-saving. However, carers and managers/HR communicated their positive informative experiences with the intervention and highlighted its capacity of practicality in the future. These findings in conjunction suggests that the intervention may be a starting point for culture change, however, further research is needed across a variety of contexts.

abstract: Thesis

abstract: Doctor of Philosophy (PhD)


title: GASTROINTESTINAL DYSMOTILITY ASSOCIATED WITH SPINAL PATHOLOGY: DIAGNOSIS AND TREATMENT USING NON-INVASIVE NEUROMODULATION

contributor:
Chen, Jihong
Medical Sciences

subject: Gastroenterology

subject: neuromodulation

subject: functional motility disorders

subject: autonomic nervous system

subject: autonomic dysfunction

abstract:
Chronic refractory gastrointestinal (GI) motility disorders are a significant burden on the healthcare system, acting as a large public health issue with significant impact on the quality of life in both the pediatric and adult population. Control systems of gastrointestinal motility are complex and involve coordination of smooth muscle contraction and relaxation, which the autonomic nervous system is largely responsible for. Gaps in the diagnosis process, such as overlooking autonomic function, has left patients with diminished quality of life and limited treatment options.
Many patients in the clinic have experienced injury within the spinal cord and we hypothesized that GI symptoms might be related to spinal injury causing disruption of sensory and/or motor nerves of the autonomic nervous system. Our objective became to better understand the specific location and nature of spinal injuries and GI symptoms, as completed through the development of a self-report questionnaire. Main findings suggest symptoms indicative of T3-T9 and T10-L2 spinal pathology.
COVID-19 did not allow for in-clinic neuromodulation with autonomic assessments, resulting in experiments remotely assessing at-home neuromodulation treatment for GI symptoms with suspected spinal autonomic dysfunction. At-home neuromodulation was not suitable for many patients, but those who were able to manage it showed highly promising results. After years of suffering, transcutaneous electrical nerve stimulation alleviated symptoms, particularly postprandial abdominal pain, constipation, vomiting and nausea. I discuss what we learned to set us up for successful at-home treatment, and we will use all information to design randomized controlled trials to prove the benefit of TENS.
The present work offers significant information on the relationship of thoracolumbar spinal pathology and complex GI symptoms, which is now used in the clinic in the diagnosis process of GI dysmotility. In addition, we have learned how to conduct at-home treatment using TENS, which allows us to execute future studies.

abstract: Thesis

abstract: Master of Science (MSc)

abstract: There are gaps in the diagnosis process of complex gastrointestinal (GI) dysmotility disorders, including lack of testing of autonomic function, leaving patients suffering with diminished quality of life with unsuccessful treatment attempts. As many patients also experience injury or conditions of the spine, I have hypothesized that GI symptoms may be related to spinal injury-induced dysfunction of the autonomic nervous system. Experimental models aim to understand the location and nature of spinal pathology with GI symptoms for future diagnoses, as well as potential treatment options such as neuromodulation. Findings of this thesis suggest symptoms indicative of particular thoracolumbar spinal pathology and promising results of transcutaneous electrical nerve stimulation (TENS) to alleviate GI symptoms, including T3-T9 and T10-L2 spinal pathology-related postprandial abdominal pain, constipation, nausea, and vomiting. This work offers information for the diagnostic process of GI dysmotility and the future design of clinical trials of neuromodulation therapies.


title: Investigating the Interaction Mechanism and Effect of ATP on Alpha-Synuclein Aggregation by NMR Spectroscopy

contributor:
Melacini, Giuseppe
Chemical Biology

subject: Alpha-Synuclein ATP

abstract: Recent studies suggest that Adenosine Triphosphate (ATP) can either enhance or inhibit the aggregation of amyloid proteins, depending on the interaction mechanism as well as specific protein properties. The connection between ATP and protein solubility is particularly important in Parkinson’s Disease (PD), where the aggregation of alpha-synuclein (αS) is closely linked to pathology. Since the greatest risk factor for PD is aging, and ATP levels decline dramatically with age and are greatly reduced in the brains of patients with early PD, it is possible that the modulating effect of ATP on protein solubility is a factor in PD onset. However, the driving mechanism behind the interaction of ATP and αS is currently unclear, as is the effect of physiologically-relevant ATP concentrations on early- and late-stage αS aggregation. Here, we determine using NMR spectroscopy that the triphosphate moeity of ATP drives its electrostatic interaction primarily with the N-terminal pseudo-apolipoprotein repeats of αS monomers. These interactions are modulated by magnesium and disrupt long-range N- to C-terminal contacts in αS monomers, causing a concentration-dependent enhancement of initial αS aggregation. We also show by Thioflavin T fluorescence as well as electron microscopy that ATP inhibits late-stage αS β-sheet fibril formation in a phosphate-dependent manner. Our NMR data reveals that ATP inhibits αS monomer-fibril interactions, suggesting that ATP attenuates αS secondary nucleation. Lastly, we show that the effects of ATP are different in the presence of PD-related αS mutations E46K and A53T. Overall, our study contributes a thorough characterization of the biologically- and pathologically-relevant interactions between ATP and αS, while also proposing a role for ATP in the age-related development of PD pathology.

abstract: Thesis

abstract: Master of Science (MSc)

abstract: Alpha-synuclein (αS) is a protein whose abnormal aggregation is characteristic of Parkinson’s Disease (PD). Adenosine Triphosphate (ATP) is a molecule that has recently been shown to reduce the aggregation of select disease-causing proteins. Therefore, the aim of this study is to characterize the interaction mechanism between ATP and αS, to explore how this interaction influences αS structural dynamics and to determine the effect of ATP on early- and late-stage αS aggregation. Another overall aim of this study is to characterize how the ATP-αS interaction is influenced by PD-related mutations in αS. To accomplish these aims, we will rely primarily on NMR spectroscopy as well as fluorescence and microscopy techniques. Our goal is to determine the role of ATP in αS aggregation as well as potentially connect the age-related decrease in ATP levels with PD, an age-related disease.


title: Robust Approaches for Learning with Noisy Labels

contributor:
He, Wenbo
Computing and Software

subject:
Machine Learning
Weakly Supervised Learning
Classification

abstract: Deep neural networks (DNNs) have achieved remarkable success in data-intense applications, while such success relies heavily on massive and carefully labeled data. In practice, obtaining large-scale datasets with correct labels is often expensive, time-consuming, and sometimes even impossible. Common approaches of constructing datasets involve some degree of error-prone processes, such as automatic labeling or crowdsourcing, which inherently introduce noisy labels. It has been observed that noisy labels severely degrade the generalization performance of classifiers, especially the overparameterized (deep) neural networks. Therefore, studying noisy labels and developing techniques for training accurate classifiers in the presence of noisy labels is of great practical significance. In this thesis, we conduct a thorough study to fully understand LNL and provide a comprehensive error decomposition to reveal the core issue of LNL. We then point out that the core issue in LNL is that the empirical risk minimizer is unreliable, i.e., the DNNs are prone to overfitting noisy labels during training. To reduce the learning errors, we propose five different methods, 1) Co-matching: a framework consists of two networks to prevent the model from memorizing noisy labels; 2) SELC: a simple method to progressively correct noisy labels and refine the model; 3) NAL: a regularization method that automatically distinguishes the mislabeled samples and prevents the model from memorizing them; 4) EM-enhanced loss: a family of robust loss functions that not only mitigates the influence of noisy labels, but also avoids underfitting problem; 5) MixNN:  a framework that trains the model with new synthetic samples to mitigate the impact of noisy labels. Our experimental results demonstrate that the proposed approaches achieve comparable or better performance than the state-of-the-art approaches on benchmark datasets with simulated label noise and large-scale datasets with real-world label noise.

abstract: Dissertation

abstract: Doctor of Philosophy (PhD)

abstract: Machine Learning has been highly successful in data-intensive applications but is often hampered when datasets contain noisy labels. Recently, Learning with Noisy Labels (LNL) is proposed to tackle this problem. By using techniques from LNL, the models can still generalize well even when trained on the data containing noisy supervised information. In this thesis, we study this crucial problem and provide a comprehensive analysis to reveal the core issue of LNL. We then propose five different methods to effectively reduce the learning errors in LNL. We show that our approaches achieve comparable or better performance compared to the state-of-the-art approaches on benchmark datasets with simulated label noise and real-world noisy datasets.


title: Remote vs in-person cognitive behavior therapy for psychiatric and somatic disorders: a systematic review and meta-analysis of randomized controlled trials

title: COMPARISON OF REMOTE CBT  VS  IN-PERSON  CBT

contributor: Clinical Health Sciences (Health Research Methodology)

subject:
Cognitive Behavior Therapy
Meta-analysis
remote CBT
Systematic review

abstract: It has been demonstrated that remote cognitive behavior therapy (CBT) is more effective than usual care; however, the comparative effectiveness of remote versus in-person CBT is uncertain. The objective of this thesis is to conduct a systematic review and meta-analysis to address this issue. MEDLINE, EMBASE, PsycINFO, CINAHL, and Web of Science were searched from inception to May 11, 2022, for randomized control trials that: (1) enrolled adults (≥18 years) presenting with any psychiatric or somatic disorder, and (2) randomized them to guided remote CBT or in-person CBT. We used a random effects model for pooling the effects on primary outcomes across trials, the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) framework to assess the certainty of the evidence, and the Instrument to Assess the Credibility of Effect Modification Analyses (ICEMAN) to rate the credibility of subgroup effects. We identified a total of 32 randomized control trials with 2,962 patients that were eligible for review. There were ten studies focused on the treatment of anxiety and related disorders, six on depressive symptoms, three on chronic pain, four on body image/eating disorder, four on insomnia, three on chronic tinnitus, one on alcohol use disorder, and one on insomnia comorbid with depression. High certainty evidence from 32 studies revealed no difference in the overall pooled estimate between remote CBT and in-person CBT (standardized mean difference = -0.07, 95% CI: -0.19 to 0.06).

abstract: Thesis

abstract: Master of Science (MSc)


title: Thermoregulatory Trade-Offs Underlie the Effects of Warming Summer Temperatures on Deer Mice

title: The Effect of Climate Warming on the Metabolic Physiology and Activity of Deer Mice (Peromyscus Maniculatus)

contributor:
Scott, Graham
Biology

subject:
Climate change
Hyperthermia
Thermal plasticity
Thermoregulation
Metabolism

abstract: As global temperatures continue to rise due to the effects of climate change, the ability of endotherms to property thermoregulate and maintain normal body temperature (Tb) may be challenged. The effects of warming summer temperatures on activity and thermoregulatory physiology in small mammals remain poorly understood. Using deer mice (Peromyscus maniculatus), a nocturnal species that maintains high activity in the wild allows us to investigate whether ecologically realistic summer ambient temperatures (Ta) will impact the physiology and activity of these animals. With exposure to warming temperatures up to 38°C, animals had a strong Tb dysregulation that culminated in a complete reversal of the diel pattern of Tb variation during the late weeks of the summer warming acclimation. During this, Tb surged to extreme highs (~40°C) during daytime heat but extreme lows (~34°C) at cooler nighttime temperatures. The decrease in nighttime Tb was associated with a decrease in thermogenic capacity and decreased mass and uncoupling protein (UCP1) content of brown adipose tissue. Activity, body mass and food consumption were also reduced, and water consumption was increased in later stages of summer warming. However, there was an increased capacity for heat dissipation through evaporative water loss (EWL) and a lower baseline metabolic rate typically of heat acclimation. Therefore, we propose that thermoregulatory trade-offs associated with heat acclimatization may limit nighttime activity, impacting the ability of nocturnal mammals to perform behaviours important for fitness in the wild.

abstract: Thesis

abstract: Master of Science (MSc)

abstract: Global climate warming is a predominant issue in today’s world and is causing dramatic changes in animals’ ecology, overall health, and physiology. However, relatively few studies have investigated the impacts of increasingly high temperatures on endothermic species. My thesis focuses on the physiological and activity changes that occur with heat exposure and acclimation when endotherms transition into summer environmental temperatures. To address this question, I exposed North American deer mice to environmentally realistic summer temperatures and examined several physiological changes. My thesis contributes to understanding how climate warming impacts and will continue to impact endothermic animals.


title: A trial of Japanese versus English translations of orthopaedic evidence reports

contributor:
Bhandari, Mohit
Health Research Methodology

subject: Evidence-Based Medicine

abstract:
Background:
The gap between evidence and practice is an important problem that may, in part, be exacerbated by language barriers.
Methods:
We surveyed members of the Japanese Society for Fracture Repair regarding their self-perceived familiarity with evidence-based medicine, and barriers to keeping up with evidence relevant to their practice. We subsequently enrolled these same orthopedic surgeons in a randomized trial to explore the impact of providing 20 electronic links to English or Japanese OrthoEvidence summaries on whether surgeons accessed the link.
Results:
A total of 106 participants were enrolled in the study, and 105 completed the pre-trial survey. Fifty-seven participants acknowledged barriers to adopting EBM; the three most prominent reasons were lack of time (77%), lack of training in critical appraisal (100%), and language barriers (95%). The mean EBM familiarity score on a 4-point scale, higher scores indicating greater familiarity, was 2.59 (standard deviation [SD] 0.38, 95% confidence interval [CI] 2.52 to 2.66). Our randomized trial found no significant difference in the number of evidence summaries that were accessed whether they were provided in Japanese (median 9, interquartile range[IQR] 5 to 15; n = 52) or English (median 3, IQR 2 to 15; n = 53) (p=0.06).
Conclusion:
Although most Japanese orthopaedic surgeons acknowledge barriers in adopting EBM into clinical practice, and highlighted language as a key barrier, providing evidence summaries in Japanese did not significantly increase the number that were accessed.

abstract: Thesis

abstract: Master of Science (MSc)

abstract:
Evidence-based medicine (EBM) incorporates current best evidence into clinical decision-making. The volume of new publications presents a challenge to staying on top of research findings in practice. Further, as most research is published in English, language barriers may hinder adoption into practice by non-English clinicians.
We administered a survey to Japanese orthopedic surgeons to assess their familiarity with EBM, and perceived barriers to incorporating EBM into clinical practice. We subsequently conducted a randomized trial to explore the effect of providing electronic links to Japanese or English research summaries to Japanese orthopedic surgeons on whether or not they accessed summaries. Participants endorsed several barriers to incorporating EBM into practice, including lack of time, lack of training in critical appraisal, and language barriers; however, there was no difference in the number of evidence summaries accessed in our trial whether research reports were provided in English or Japanese.


title: Control of the ICE-Harvest System using an Advanced Multi-Agent Framework

contributor:
Narimani, Mehdi
Cotton, James
Electrical and Computer Engineering

abstract: This thesis presents the development of an advanced control structure for the novel Integrated Community Energy and Harvesting (ICE-Harvest) system. The ICE-Harvest system is similar to a District Energy (DE) system in many ways and is different in others. It consists of a set of energy producing and storage units coupled to a thermal network which connects residential and commercial buildings of various types. Its operation is geared towards addressing challenges associated with the current energy landscape in Ontario, with potential to be applicable elsewhere in Canada. The control of this system is based on the implementation of a Multi-Agent System (MAS) combined with Sequential Logic Controllers (SLCs). Results demonstrate the capability of the developed control framework to operate the ICE-Harvest system while ensuring the thermal and electrical energy supply to the different consumers. Based on the results presented, the operation of the ICE-Harvest system by the developed control framework is compared with that of a Business-As-Usual (BAU) scenario. This comparison demonstrates the capability of the developed control framework to operate the ICE-Harvest system in a way that also increases the energy utilization and reduces emissions.

abstract: Thesis

abstract: Master of Applied Science (MASc)


title: Contextualizing antimicrobial resistance determinants using deep-learning language models

contributor:
McArthur, Andrew G.
Biochemistry and Biomedical Sciences

subject:
antimicrobial resistance
natural language processing
epidemiology

abstract: Bacterial outbreak publications outline the key factors involved in uncontrolled spread of infection. Such factors include the environments, pathogens, hosts, and antimicrobial resistance (AMR) genes involved. Individually, each paper published in this area gives a glimpse into the devastating impact drug resistant infections have on healthcare, agriculture, and livestock. When examined together, these papers reveal a story across time, from the discovery of new resistance genes to their dissemination to different pathogens, hosts, and environments. My work aims to extract this information from publications by using the biomedical deep-learning language model, BioBERT. BioBERT is pre-trained on all abstracts found in PubMed and has state-of-the-art performance with language tasks using biomedical literature. I trained BioBERT on two tasks: entity recognition to identify AMR-relevant terms (i.e., AMR genes, taxonomy, environments, geographical locations, etc.) and relation extraction to determine which terms identified through entity recognition contextualize AMR genes. Datasets were generated semi-automatically to train BioBERT for these tasks. My work currently collates results from 204,094 antimicrobial resistance publications worldwide and generates interpretable results about the sources where genes are commonly found. Overall, my work takes a large-scale approach to collect antimicrobial resistance data from a commonly overlooked resource, i.e., the systematic examination of the large body of AMR literature.

abstract: Thesis

abstract: Master of Science (MSc)


title: DEVELOPING A HISTOLOGY-BASED COMPOSITE INDEX TO ASSESS THE  DEGREE OF LUNG FIBROSIS USING QUANTITATIVE HALO® MODULES

title: USING QUANTITATIVE HISTOLOGICAL READOUTS OF PULMONARY  FIBROSIS TO PRODUCE A SCORE OF FIBROTIC LUNG DISEASE SEVERITY

contributor:
Ask, Kjetil
Medical Sciences

subject: Fibrosis, Lung, Histology, Digital Pathology, HALO®, Composite Index, Model, Machine Learning

abstract:
Histological and visual assessment of pulmonary fibrosis are used as a
gold standard to determine severity of fibrotic lung disease. The Ashcroft scoring
technique and histological stains like Masson’s trichrome and picrosirius red
(PSR) have been used for decades as primary readouts, often alongside a
biochemical assay estimating the amount of hydroxyproline in the tissue. As
pulmonary fibrosis is a heterogeneous disease and collagen content rarely shows
more than a two-fold increase between a non-diseased and a diseased lung,
therapeutic assessment is challenging due to the variability animal models.
 To improve the assessment of the severity of fibrotic lung disease, we
have developed models using multivariate linear regression and XGBoost
machine learning that consider digital quantifications of histological features from
73 clinically diagnosed cases of IPF and 11 control tissues, obtained using the
HALO® platform, that correlate with the Ashcroft score and combine them into a
composite index that we believe represents a better, more objective way of
scoring fibrotic lung tissues.
The tissues were stained with H&E for structural assessment, Trichrome
(TRI), and Picrosirius Red (PSR) for collagen content, alpha-smooth muscle actin
(αSMA) to assess the amount of ECM-producing myofibroblasts (MFBs), and
CD68, CD163, and CD206 for macrophage content and activation as they have
been correlated with lung fibrosis and are considered a therapeutic target.

abstract: Thesis

abstract: Master of Science (MSc)

abstract:
Lung diseases involving excess scar tissue formation resulting in lung
failure are difficult to study, especially when the most used method for assessing
the progression of the disease, the Ashcroft score, is imprecise and subject to
bias. The goal with this project is to update this current gold standard for rating
disease severity in a portion of lung from the purely visual Ashcroft score to one
that uses robust computational methods.
This novel method uses digital pathology software, HALO®, to quantify
components of the lung tissue, such as population densities of specific cell types,
the proportion of alveolar airspace to alveolar interstitium, and the extent of
scarring in the lung according to collagen content. Then, machine learning is
used to generate a severity score that resembles the standard method, and
should feel familiar to lung researchers, but that we believe is more reliable and
would be consistent between research groups.


title: The Electrophysiological Correlates of Multisensory Self-Motion Perception

contributor:
Shedden, Judith
Psychology

subject:
self-motion perception
beta oscillations
theta oscillations
direction processing
visual-vestibular weighting
multisensory integration

abstract: The perception of self-motion draws on inputs from the visual, vestibular and proprioceptive systems. Decades of behavioural research has shed light on constructs such as multisensory weighting, heading perception, and sensory thresholds, that are involved in self-motion perception. Despite the abundance of knowledge generated by behavioural studies, there is a clear lack of research exploring the neural processes associated with full-body, multisensory self-motion perception in humans. Much of what is known about the neural correlates of self-motion perception comes from either the animal literature, or from human neuroimaging studies only administering visual self-motion stimuli. The goal of this thesis was to bridge the gap between understanding the behavioural correlates of full-body self-motion perception, and the underlying neural processes of the human brain. We used a high-fidelity motion simulator to manipulate the interaction of the visual and vestibular systems to gain insights into cognitive processes related to self-motion perception. The present line of research demonstrated that theta, alpha and beta oscillations are the underlying electrophysiological oscillations associated with self-motion perception. Specifically, the three empirical chapters combine to contribute two main findings to our understanding of self-motion perception. First, the beta band is an index of visual-vestibular weighting. We demonstrated that beta event-related synchronization power is associated with visual weighting bias, and beta event-related desynchronization power is associated with vestibular weighting bias. Second, the theta band is associated with direction processing, regardless of whether direction information is provided through the visual or vestibular system. This research is the first of its kind and has opened the door for future research to further develop our understanding of biomarkers related to self-motion perception.

abstract: Dissertation

abstract: Doctor of Philosophy (PhD)

abstract: As we move through the environment, either by walking, or operating a vehicle, our senses collect many different kinds of information that allow us to perceive factors such as, how fast we are moving, which direction we are headed in, or how other objects are moving around us. Many of our senses take in very different information, for example, the vestibular system processes information about our head movements, while our visual system processes information about incoming light waves. Despite how different all of this self-motion information can be, we still manage to have one smooth perception of our bodies moving through the environment. This smooth perception of self-motion is due to our senses sharing information with one another, which is called multisensory integration. Two of the most important senses for collecting information about self-motion are the visual and vestibular systems. To this point, very little is known about the biological processes in the brain while the visual and vestibular systems integrate information about self-motion. Understanding this process is limited because until recently, we have not had the technology or the methodology to adequately record the brain while physically moving people in a virtual environment. Our team developed a ground-breaking set of methodologies to solve this issue, and discovered key insights into brainwave patterns that take place in order for us to perceive ourselves in motion. There were two critical insights from our line of research. First, we identified a specific brainwave frequency (beta oscillations) that indexes integration between the visual and vestibular systems. Second, we demonstrated another brainwave frequency (theta oscillation) that is associated with perceiving which direction we are headed in, regardless of which sense this direction information is coming from. Our research lays the foundation for our understanding of biological processes of self-motion perception and can be applied to diagnosing vestibular disorders or improving pilot simulator training.