title: Enforcement and Refinement of Data Currency and Data Consistency

contributor:
Fei, Chiang
Computing and Software

abstract: This thesis focuses on tackling three problems in two data quality dimensions: data currency and data consistency.  We first address the problem of estimating data currency in a relational database, and we argue that data currency is a relative notion that is dependent on an individual’s update pattern.  This pattern can have spatial and temporal variance among individuals. By learning the patterns from an update history, we present a probabilistic system for identifying and cleaning stale values. Secondly, we explore the problem of estimating data currency in distributed database settings. Replicas of the same data item often exhibit varying consistency levels when executing read and write requests due to system availability and network limitations.  When one or more replicas respond to a query, estimating the currency of the returned data item is essential for applications requiring timely data.  Depending on how confident the estimation is, the query may dynamically decide to return the retrieved replicas, or wait for the remaining replicas to respond.  We present a system that accurately estimates whether the retrieved replicas are current or stale, and guarantees that the estimation satisfies a user-given confidence threshold.  Using this confidence-bounded replica currency estimation, we implement a novel DYNAMIC consistency level in the open-source, NoSQL database, Cassandra. Finally, we tackle the problem of resolving inconsistencies in a database.  Data consistency is often measured by whether the data adheres to a set of data quality rules.  Recent work has proposed a new class of data quality rules that considers the data semantics with respect to (w.r.t.) an ontology.  As the data evolves w.r.t. these rules and ontology, we propose a system to re-align and repair the data and the ontology w.r.t these ontological rules.

abstract: Thesis

abstract: Candidate in Philosophy


title: Adapting and Evaluating the Namaste Care Program Delivered by Caregivers of Community-Dwelling Older Adults with Moderate to Advanced Dementia: A Mixed Methods Study

title: Adapting and Evaluating Namaste Care for Home Use

contributor:
Ploeg, Jenny
Nursing

subject:
Caregivers
Family
Community-dwelling older adults
Dementia
Psychosocial intervention
Namaste care
Qualitative
Quantitative
Mixed methods

abstract:
Introduction: More than half a million Canadians are living with dementia and 260,000 of these individuals live at home. As dementia progresses, persons with dementia require more assistance from caregivers to meet their daily needs including stimulation and emotional support. However, caregivers receive little training in this role. Namaste Care is a program originally developed for use in long-term care homes promoting a structured routine, a slow pace of care, and multisensorial activities for persons with advanced dementia. The program has not yet been adapted or evaluated for use by caregivers of community-dwelling older adults with moderate to advanced dementia. The objective of this study is to explore the feasibility, acceptability and preliminary effectiveness of a version of Namaste Care adapted by caregivers.
Methods: A multiphase mixed methods design was used. In the adaptation phase, six caregivers participated in workshop sessions to adapt Namaste Care for home use. In the evaluation phase, 12 caregivers received training to use the adapted program. Surveys were used to collect data on caregiver quality of life, perceptions of caregiving, self-efficacy, and burden at baseline and 3-month follow-up. Qualitative interviews at 3-month follow-up were also completed to assess the acceptability of the program and implementation facilitators and barriers.
Findings: All caregivers used the program for a minimum of twice a week as planned and used a variety of program activities. The retention rate was 83%. Caregivers perceived that the program improved their relationships with persons with dementia. Implementation facilitators were receiving a Namaste Care Toolbox and written resources about Namaste Care. No statistically significant effects were found with regards to the outcome measures listed above.
Conclusions: The adapted Namaste Care program was feasible and acceptable for use by caregivers. There is a need to conduct a larger trial to determine the extent of its effects.

abstract: Thesis

abstract: Doctor of Philosophy (PhD)

abstract: With the growing numbers of family and friend caregivers across Canada supporting people living with dementia at home, there is a need to better prepare caregivers for their role. The aim of this study is to adapt, implement and evaluate a sense-based, skill-building program called Namaste Care delivered by caregivers of older adults living with moderate to advanced dementia. First, workshops for caregivers were held to adapt the Namaste Care program for home use. Afterwards, 12 caregivers received training in using the adapted program and delivered the program for three months. Caregivers used the program at least twice a week as intended and delivered a variety of activities. The program improved relationships with persons with dementia. No significant changes for caregiver quality of life, positive beliefs of caregiving, burden, and confidence were found. Next steps are to further test the effects of the program in a larger trial.


title: Computational Approaches to State Estimation of Periodic Signals and Control of Switched Systems

contributor:
Von Mohrenschildt, Martin
Computing and Software

subject:
State Estimation
Control Theory
Hybrid Systems
Periodic Signals

abstract: In this thesis, two separate problems are examines. First, sinusoidal signals are quite prevalent in practical applications. For example, any machine driven by a rotary shaft will exhibit periodic behaviour. For this reason, the estimation of sinusoidal parameters is studied extensively in the literature. Often in practical applications, there are unmodeled disturbances to the system, and the incoming measurements are noisy. Thus, estimation of the parameters of a sinusoidal signal in real-time for these conditions is of interest, calling for the use of a filter-based approach such as the Extended Kalman Filter. Considering the sinusoidal signal in its complex form, a novel approach is proposed resulting in a complex-valued filter. The resulting complex Extended Kalman Filter’s performance is evaluated in various test environments and is compared to standard approaches to the estimation problem using a Discrete Fourier Transform and standard Extended Kalman Filter. Results show that the complex Extended Kalman Filter outperforms the standard approaches in some cases in both accuracy and convergence rate. Second, research on hybrid systems has seen a large growth in interest in recent years. This is largely due to the increase of natural systems where discrete mode dynamics interact with continuous state dynamics. Switched systems are a subclass of hybrid systems that restrict their definition to continuous dynamic systems that interact with dis- crete switching events. Controller synthesis for such systems is no trivial task. Given the current trend in Artificial Intelligence and Machine Learning approaches, Dynamic Programming is explored as a means to approximate optimal control policies for switched systems. Discussions of discretization of the system’s state space are presented, followed by a high-level overview of an algorithm that leverages Dynamic Programming to find the approximated optimal control policies. Finally, the algorithm is applied to several examples to demonstrate its effectiveness.

abstract: Thesis

abstract: Master of Applied Science (MASc)


title: Data-Driven Modeling and Control of Batch and Continuous Processes using Subspace Methods

contributor:
Prashant, Mhaskar
Chemical Engineering

subject:
Data-Driven Modeling
Subspace Identification

abstract:
This thesis focuses on subspace based data-driven modeling and control techniques for batch and continuous processes. Motivated by the increasing amount of process data, data-driven modeling approaches have become more popular. These approaches are better in comparison to first-principles models due to their ability to capture true process dynamics. However, data-driven models rely solely on mathematical correlations and are subject to overfitting. As such, applying first-principles based constraints to the subspace model can lead to better predictions and subsequently better control. This thesis demonstrates that the addition of process gain constraints leads to a more accurate constrained model. In addition, this thesis also shows that using the constrained model in a model predictive control (MPC) algorithm allows the system to reach desired setpoints faster. The novel MPC algorithm described in this thesis is specially designed as a quadratic program to include a feedthrough matrix. This is traditionally ignored in industry however this thesis portrays that its inclusion leads to more accurate process control.
Given the importance of accurate process data during model identification, the missing data problem is another area that needs improvement. There are two main scenarios with missing data: infrequent sampling/ sensor errors and quality variables. In the infrequent sampling case, data points are missing in set intervals and so correlating between different batches is not possible as the data is missing in the same place everywhere. The quality variable case is different in that quality measurements require additional expensive test making them unavailable for over 90\% of the observations at the regular sampling frequency. This thesis presents a novel subspace approach using partial least squares and principal component analysis to identify a subspace model. This algorithm is used to solve each case of missing data in both simulation (polymethyl methacrylate) and industrial (bioreactor) processes with improved performance.

abstract: Dissertation

abstract: Doctor of Philosophy (PhD)

abstract: An important consideration of chemical processes is the maximization of production and product quality. To that end developing an accurate controller is necessary to avoid wasting resources and off-spec products.  All advance process control approaches rely on the accuracy of the process model, therefore, it is important to identify the best model. This thesis presents two novel subspace based modeling approaches the first using first principles based constraints and the second handling missing data approaches. These models are then applied to a modified state space model with a predictive control strategy to show that the improved models lead to improved control. The approaches in this work are tested on both simulation (polymethyl methacrylate) and industrial (bioreactor) processes.


title: Resting state functional connectivity in pediatric concussion

contributor:
Bock, Nicholas
Hall, Geoffrey
Psychology

subject:
pediatric
fMRI
concussion
resting state
brain networks
childhood
adolescence
functional connectivity
mTBI
traumatic brain injury

abstract:
Children and adolescents with concussion display aberrant functional connectivity in some of the major neurocognitive networks. This includes the Default Mode Network, Central Executive Network and Salience Network. Using resting state fMRI, the purpose of this thesis was to explore the functional connectivity of cognition-related networks in youth experiencing concussion. With a prospective cohort study, the functional connectivity (defined as the temporal coherence between spatially separated brain regions) of children and adolescents ages 10-18 years old was evaluated in relation to a number of demographic and injury-specific factors including recovery length, age at the time of injury, symptom severity, and neurocognitive performance.
The results showed two general trends: (1) a reduction in connectivity (i.e., hypoconnectivity) between the regions of the Default Mode Network, and (2) an increase in connectivity (i.e., hyperconnectivity) between additional sensory-related regions like the cerebellum and hippocampus. The Default Mode Network, which processes self-referential information, has a long-protracted development across childhood through adulthood. Given that the participants in this cohort exhibited reduced functional connectivity within the Default Mode Network and between the Default Mode Network and other neurocognitive networks suggests that this is an area of vulnerability in youth in the event of concussion. Increased connectivity between the Central Executive Network and Salience Network, and between cognitive- and sensory-related regions such as the hippocampus and cerebellum might be interpreted as a compensatory mechanism to supplement deficits of the Default Mode Network.
This thesis sheds light on important concussion-related regions for future research to investigate further and delves into the possible neural mechanisms contributing to the cognitive, sensory, mood, and sleep disturbances in children and adolescents with concussion.

abstract: Dissertation

abstract: Doctor of Philosophy (PhD)

abstract:
Your brain at rest is not resting. In fact, your many brain regions are continuously communicating even during rest to maintain important communication between them. This communication between brain regions is termed functional connectivity. When you receive a blow to the head, face, neck, or another part of your body that senses a biomechanical force to your brain, the functional connectivity (i.e., communication lines) between your brain regions may be altered. A blow of this nature is considered a concussion, also known as a mild traumatic brain injury. With disruptions to the typical functional connectivity between your brain regions following a concussion, you may experience difficulty in managing cognitive tasks, emotions, and body coordination. Among those most vulnerable to the effects of concussion are children and adolescents whose brains have yet to develop fully.
The goal of this thesis was to evaluate the functional connectivity between brain regions of children and adolescents to determine how brain communication might be disrupted following concussion. These evaluations were done using functional magnetic resonance imaging (fMRI) of the brains of children and adolescents ages 10-18 years old. It was discovered that the functional connectivity of the frontal lobe is related severity of post-concussion symptoms such that individuals with worse symptoms had reduced functional connectivity in the frontal lobe compared to individuals who reported less severe symptoms. Further, children and adolescents with longer recovery periods have a different level of functional connectivity in the temporal lobe compared to youth with relatively shorter recovery periods. This might suggest that both of these regions could provide prognostic value in determining who might have worse symptoms or a longer recovery time following injury.
In comparison to children and adolescents who have not had a concussion, children and adolescents experiencing a concussion are more likely to have abnormal functional connectivity between the hippocampus and cerebellum, which are particularly involved in processing sensory information and navigation. This was interpreted to mean that the brain responded to the concussion by increasing the communication between regions that might help a child with a concussion coordinate their bodies so that they can move from place to place. This was additionally supported by a further investigation which showed that children and adolescents have reduced communication between areas of the brain that might allow them to process information about the self (e.g., memories, sensations, relationships with others, etc.).
Overall, the results demonstrated that following a concussion, children and adolescents may have a deficit in the functioning of the frontal lobe in a specific region that allows them to process cognitive and sensory information. This might explain why concussion leads to poor memory, body coordination, sensitivity to light and sounds, and even difficulty sleeping. Their brains might then compensate for the disruption by increasing alternate pathways of communication. Together these findings open gateways for future researchers to look more deeply at the specific regions affected by concussion in youth. It draws attention to the many neurocognitive, emotional, and somatic symptoms a child with a concussion exhibits and their symptoms’ underlying neurological processes.


title: String-Order in Multileg Kitaev-Heisenberg Ladders

contributor:
Sorensen, Erik
Physics and Astronomy

subject:
Quantum spin liquid
Kitaev
DMRG
String order parameter

abstract: The Kitaev model has become a source of much excitement in the field of condensed matter. It is a two dimensional model of spins ½ on a honeycomb lattice with bond-dependent interactions. Its interesting properties include a quantum spin liquid ground state and anyonic excitations. These properties could lead to exciting applications in quantum computing if materials were found to behave similarly to the Kitaev model. Such materials have been found, however the Kitaev model is too simple to describe these materials and additional interactions must be considered. The Heisenberg interaction is one such additional interaction. As such, we can define the Kitaev-Heisenberg model by combining the Kitaev and Heisenberg interactions. We can now ask ourselves if the quantum spin liquid ground state and anyonic excitations still exist in the Kitaev-Heisenberg model. To answer this question, a non-local string order parameter has been defined which is non-zero inside the quantum spin liquid phase and zero outside of it. This string order parameter was shown to exist and survive the Heisenberg interaction on the 2-leg ladder. In this thesis, we look to expand this result to multileg ladders such as the 3-leg, 4-leg, and 5-leg ladders to see if the string order parameter survives in the Kitaev-Heisenberg model in 2 dimensions. Our results show that the string order parameter does exist in multileg ladders, however the phase space window in which it survives the Heisenberg interaction is narrower than in the 2-leg ladder.

abstract: Thesis

abstract: Master of Science (MSc)


title: Structural neuroimaging biomarkers of major depressive disorder and antidepressant response

contributor:
Frey, Benicio N.
Neuroscience

abstract:
Introduction: There is an ongoing interdisciplinary effort to identify objective biomarkers that could improve clinical treatment outcomes in major depressive disorder (MDD). MDD encompasses symptoms ranging from the affective and vegetative to the cognitive and executive domains, mainly marked by depressed mood and loss of interest/pleasure. With MDD prevalence rates on the rise, there is an increasing need to investigate the biological correlates of symptoms and response to antidepressants, which can vary widely between patients. In this thesis, we investigated the structural neuroimaging correlates of MDD and antidepressant response in living human participants using non-invasive magnetic resonance imaging (MRI). We endeavoured to describe structural brain features related to depressive symptoms and treatment response using both cross-sectional and longitudinal designs. We additionally investigated neuroimaging findings within the greater biological context of MDD by incorporating stress variables and molecular data pertaining to gene expression and epigenetics.
Results: Analyses of baseline differences in brain structure between MDD and healthy control (HC) participants revealed that the cerebral cortex tends to be thinner in frontal and temporoparietal regions in MDD, including the middle rostral frontal cortex, orbitofrontal cortex, pars opercularis and lingual gyrus with a general emphasis on the left hemisphere. Although hypothalamus volume was not shown to be significantly different between MDD and HC groups, we observed a greater extent of epigenetic functional relevance and a stronger relationship between hypothalamus volume and DNA methylation of key genes controlling the physiological stress response (CRHBP, FKBP5 and NR3C1). Generally, with the exception of a weak correlation between left hypothalamus volume and current episode duration, we did not observe any reliable associations between structural neuroimaging features and symptom severity, antidepressant response or childhood maltreatment. Short courses of antidepressant treatment ranging from weeks to a few months did not seem to affect brain structure to an extent detectable with 3T MRI.
Conclusion: The results suggest that there are certain structural features associated with major depressive disorder in the unmedicated state, most reliably thinner cerebral cortex in anterior frontal regions. Hypothalamus volume may additionally be linked to epigenetic characteristics to a greater extent in the disease state. We did not observe any structural features at 3T at baseline related to short-term antidepressant response.

abstract: Thesis

abstract: Doctor of Philosophy (PhD)


title: Bio-Inspired Artificial Intelligence Approach for Reinforced Concrete Block Shear Wall System Response Predictions

contributor:
El-Dakhakhni, Wael
Civil Engineering

subject:
backbone model
fully grouted reinforced masonry walls
seismic performance
variables selection
multigene genetic programming

abstract: Reinforced concrete block shear walls (RCBSWs) are used as seismic force resisting systems in low- and medium-rise buildings. However, attributed to their nonlinear behavior and composite material nature, accurate prediction of their seismic performance relying only on mechanics is challenging. This study introduces multi-gene genetic programming (MGGP)— a class of bio-inspired artificial intelligence, to uncover the complexity of RCBSW behaviors and develop simplified procedures for predicting the full backbone curve of flexure-dominated fully grouted RCBSWs under cyclic loading. A piecewise linear backbone curve was developed using five secant stiffness expressions associated with cracking, yielding, 80% ultimate, ultimate, and 20% strength degradation (i.e., post-peak stage) derived through controlled MGGP. Based on the experimental results of large-scale cyclically loaded RCBSWs, compiled from previously reported studies, a variable selection procedure was performed to identify the most influential variable subset governing wall behaviors. Utilizing individual wall results, the MGGP stiffness expressions were first trained and tested, and their accuracy was subsequently compared to that of existing models employing various statistical measures. In addition, the predictability of the developed backbone model was assessed at the system-level against experimental results of two two-story buildings available in the literature. The outcomes obtained from this study demonstrate the power of MGGP approach in addressing the complexity of the cyclic behavior of RCBSWs at both component- and system-level—offering an efficient prediction tool that can be adopted by relevant seismic design standards pertaining to RCBSW buildings.

abstract: Thesis

abstract: Master of Applied Science (MASc)


title: The Heart of a Mother, The Waves of Mothering: A Narrative Inquiry into Mothering Experiences of Child Weight Management

contributor:
Dumbrill, Gary
Social Work

subject:
Mothering experiences
Child weight management
Narrative Inquiry

abstract:
Many stories exist within the professional landscape of child weight management programming and health services. Grand narratives within these spaces story fat bodies as “unhealthy”, “risky” and in need of transformation, and often position the family and mothers in particular given gendered caregiving norms, as responsible for their children’s weight and poor health. Mothering stories and experiences are rarely told by the mothers themselves within this professional landscape. This study is a narrative inquiry that explores the in-depth experiences of two mothers who previously participated with their children in an Ontario paediatric weight management program. Given my work as a social worker within child weight management clinics I also explore my experiences alongside the participants.
	Clandinin and Connelly’s conceptualization of narrative inquiry and the three dimensional framework of temporality (past, present, future), sociality and place, inquiring inward, outward, backward and forward, were used in order to find meaning in mothering experiences of child weight management. Narrative beginnings share my own experiences of mothering and child weight management. Relational ethics were central as the inquiry unfolded, allowing for simultaneous exploration of experiences, continuous negotiation, awareness and re-evaluation with each mother, from recruitment, field work, to field text, interim text and the writing of the final text. Given the current social distancing restrictions related to the COVID-19 pandemic, conversations took place over zoom and telephone and were audio-recorded and transcribed verbatim. Detailed narrative accounts were written for each mother capturing individual experiences of child weight management as they intersected with many other experiences in their everyday lives. Narrative threads weaved together the mother’s experiences throughout the inquiry and focused on disrupting the grand narrative and resisting fragmentation. The inquiry contributes to the scholarship within fields of social work, social justice, mothering and health care by providing new ways of knowing about and engaging in conversations about mothering, weight, fatness and health.

abstract: Dissertation

abstract: Doctor of Philosophy (PhD)

abstract: This narrative inquiry explores the in-depth experiences of two mothers who previously participated in a child weight management program. As part of this research, I also explore my experiences in relation to the mothers, as a social worker who historically worked in the clinic. Mothers were often positioned as responsible for their children’s body weight and poor health and stories and experiences were rarely told by the mothers themselves across research and policy in the field. Clandinin and Connelly’s three-dimensional framework was used to find meaning in mothering experiences of child weight management. Conversations took place over zoom and telephone over a year. Detailed narrative accounts capture the individual mothering experiences of child weight management and come together in narrative threads that focus on disrupting the grand narrative and resisting fragmentation. The inquiry contributes to the scholarship within fields of social work and health care, providing new ways of knowing about and engaging in conversations about mothering, weight, fatness and health.


title: Effects of Carbon Metabolism on the growth of bacteria and antibiotic efficacy

contributor:
Brown, Eric
Biochemistry and Biomedical Sciences

subject: carbon source, antibiotic resistance, bacterial metabolism

abstract: With the rise of antibiotic resistance, there is ongoing need to find new antibiotics. As bacteria develop resistance to the current classes of antibiotics available, it is imperative to discover new ways to target bacteria. In this thesis, I focused on one of the basic components that all bacteria need to survive: a source of carbon. Here, I explore whether we can exploit this aspect for drug discovery. For bacteria to colonize a host and cause an infection, it must first be able to meet its nutritional needs for growth. Different host infection sites will have different carbon sources available. Some sites, like the gut, will have commensal bacteria which will compete with invading pathogens for carbon sources. While we still lack understanding of the specific growth environment bacteria experience during infection, it is important to understand how bacteria grow when given different nutrients. For the first part of my work, I systematically probed the gene essentiality patterns of E. coli grown in different carbon sources. I generated a large dataset of growth phenotypes that I compiled into a user-friendly web-application, Carbon Phenotype Explorer (CarPE). I identified many poorly annotated genes, and further characterized the gene ydhC as an adenosine transporter. After characterizing how the growth of E. coli and the genes essential for survival change depending on each carbon source, I looked at whether antibiotic efficacy changed depending on the carbon source used. I found that growth in oxaloacetate alters the proton motive force and potentiates macrolide antibiotics. I also found that linezolid, a compound that does not work on gram-negative bacteria due to efflux, is more effective when adenosine is the carbon source. Together, this work forms a foundation for future research into studying how carbon sources can be exploited in the field of antibiotic discovery.

abstract: Thesis

abstract: Candidate in Philosophy

abstract: There is an urgent need for new antibiotics. Previous antibiotic discovery has primarily been conducted on bacteria growing in nutrient rich laboratory conditions. This led to antibiotics that targeted the same few bacterial processes. However, since bacteria need to survive in a host to cause an infection, there are targets that may be viable during an infection that we miss by using standard laboratory media. Bacteria need a source of carbon to survive, and each infection site contains different chemicals that bacteria can use as a source of carbon. My work studies how bacteria grow in the presence of different carbon sources. First, I systematically tested which bacterial genes are required for E. coli to grow in 30 different carbon sources. I then examined the effectiveness of antibiotics on bacteria grown using these different carbon sources. Together, this work helps us understand how changing carbon sources in the growth media we use to cultivate bacteria can change which genes are required and how it may change how bacteria survive antibiotic stress. When we discover the specific compositions of host infection environments, we can leverage this knowledge to find antibiotics that target these carbon acquisition pathways in bacteria.


title: SECTUALLY TRANSMITTED DEMONS: CATEGORIZING THE APOTROPAIC DEAD SEA SCROLLS

contributor:
Machiela, Daniel
Schuller, Eileen
Thiessen, Matthew
Religious Studies

subject: Apotropaism, Exorcism, Dead Sea Scrolls

abstract: Apotropaism is a word used to describe a number of texts from the Dead Sea Scrolls that are meant to deal with the problem of evil, especially the demonic. Yet, scholars of Early Judaism have labeled some texts as apotropaic while others have described them as exorcistic. Drawing on the criteria of proximity and time suggested by Philip S. Alexander, this dissertation argues the following points: 1) That the difference between an apotropaic ritual and an exorcistic ritual is the proximity of evil to the human being and the expected temporal efficacy of the ritual. By closely examining the language of each individual text, evidence suggests that such delineations can be based on these two criteria; 2) That some texts that have otherwise been neglected in the study of apotropaism at Qumran may be part of this group of protective rituals; 3) That there is a difference between works concerned primarily with protection from evil spirits (anti-demonic) and those concerned with Sin (anti-peccable); 4) That a number of shared elements within the apotropaic texts at Qumran emphasize themes such as covenant faithfulness, obedience, predestination, among others.

abstract: Dissertation

abstract: Doctor of Philosophy (PhD)


title: Theory of Disperse Diblock Copolymers

contributor:
Shi, An-Chang
Physics and Astronomy

subject:
block copolymers
self-assembly
dispersity

abstract: The equilibrium phase behavior of disperse diblock copolymers is studied using the self-consistent field theory. We first examine how dispersity affects the formation of complex spherical phases in conformationally asymmetric diblock copolymers. For disperse diblock copolymers with Poisson and Schulz-Zimm distributions, the Frank-Kasper σ phase appears at a lower degree of conformational asymmetry than what is predicted in monodisperse systems. We next present a general method of treating molecular weight distributions (MWDs) specified by a set of molecular weight fractions in numerical self-consistent field theory. The procedure is applied to MWDs with similar dispersity indices and different skewness obtained from experimental measurements. We find that consistent with experiments, the domain spacing and equilibrium morphology could vary with the skewness. Lastly, we investigate how the MWD shape characterized by the dispersity index and skewness affects the relative stability of complex spherical phases. The predicted set of complex phases could differ between MWDs with identical dispersity indices and different skewness. In particular, it is found that the formation of the C14 and C15 phases is favored for more positively-skewed distributions. Overall, the work underlines the importance of the MWD shape on the phase behavior of disperse diblock copolymers and the need of considering other statistical measures alongside the dispersity index, such as the skewness.

abstract: Dissertation

abstract: Doctor of Philosophy (PhD)


title: Optimization Models in Retail Reverse Supply Chains

contributor:
Hassini, Elkafi
Computational Engineering and Science

subject:
Reverse Supply Chain
Reverse Logistics
Retail
Vendor-Retailer Return Contracts
Profit-loss Budget
Inventory Optmization

abstract:
Unlike most of the existing literature on reverse supply chains, that focuses on product recovery or waste management, in this thesis we consider reverse supply chain operations for an independent retailer. The latter have forward and reverse supply chains that are independent of the manufacturers.  We study three major problems related to Retail Reverse Supply Chains (RRSC) for independent retailers. In RRSCs, each retail store holds some products that are not selling (and/or under-selling) and wishes to salvage them optimally. We refer to these  products as Ineffective Inventory. Salvage can be in many forms and take place by relocating a product within the reverse supply chain (RSC), such as sending the product from a franchise store back to a Distribution/Return Center (RC) and then forward to another franchise store, or returning it to a vendor, liquidation, etc. The RRSC network may includes system members such as stores (retailer owned and/or franchise), RCs, warehouses, vendors and liquidators.  Each of the stores carries some inventory that is underselling, and it is important to reduce the inventory of such products in order to refill the space with inventory that is more likely to sell.

In the first problem, we consider a basic RRSC with retail stores, vendors and a warehouse. The retail company allocates a budget for its RRSC activities. We refer to this budget as a Profit-Loss budget, due to lost income from the items that will be removed from the stores that was a part of the gains resulting from the previous year tax calculations. The objective is to use this Profit-Loss budgetary limitation as effectively as possible with the most suitable products to relocate products within the supply chain and/or return them back to their vendor. A heuristic algorithm is developed to solve this problem, by making use of the problem structure, and results are compared with the solutions of an exact state-of-the-art commercial solver.

In the second problem, we consider a network optimization model with inventory decisions.  The goal is to optimize  ineffective inventory levels in stores and the disposition of their returns. We model a comprehensive RRSC network with multiple stores that could be Company-Owned or Franchise Stores, multiple warehouses, multiple RCs, multiple vendors, and liquidators. The objective of the retailer is to minimize costs for relocating  some of this ineffective inventory within the network or scrapping. However, individual franchise stores have their own goals of how their excessive inventory should be handled. The franchisee goals may be conflicting with those of the franchisor in terms of how much inventory should be chosen from each store to be relocated. In return, this conflict may lead to a conflict among franchise stores. This issue is addressed and resolved through inventory transparency among all the supply chain members. The tactical decision making process of which RC should be used for handling returns is incorporated into the model. In order to overcome the complexities of the large size problem, a multi-stage heuristic is developed to solve this problem within reasonable times. The results are then compared with the solutions of  state-of-the-art commercial solver.

In the third problem, we focus on the strategic decision of developing optimal vendor contract parameters for the retailer, using optimization models. Specifically, we identify optimal return penalties and associated return thresholds, between an independent retailer and its vendors. This model will support the retailer in their contract re-negotiation for its RSC activities. Vendors use a multi-layered penalty structure that assigns higher penalties to higher returns. The objective is to find the optimal penalties and/or optimal return thresholds that should be negotiated with the vendors in order to pay a lower penalty in the upcoming return cycles compared to existing penalty structures. We first design a Mixed Integer Non-Linear Program (MINLP) where the model makes the decision of vendor penalty fees and return thresholds simultaneously for each vendor. We generate small size to large size problems and solve them via MINLP solvers such as DICOPT and ANTIGONE. In order to gain insights to the inner workings of the MINLP, the decision variables, vendor penalty fees and return thresholds, are considered as parameters and hence, two models are designed to find the optimal penalty structure and optimal return thresholds, respectively. Useful insights from both of the models’ solutions are derived in order to generate rule-of-thumb methodologies to find approximate solutions close to optimal penalty percentages and return thresholds via identifying all possible scenarios that can exist in the problem structure.

abstract: Thesis

abstract: Doctor of Philosophy (PhD)

abstract: This thesis deals with Retail Reverse Supply Chain (RRSC) management. We consider an independent retail company's and its franchise stores' ineffective inventory which may be constituted of unsold,  under-selling, slow-moving, customer-returned, end-of-life, end-of-use, damaged, and faulty products within their inventory. We take into account the retailer's reverse supply chain structure and investigate the following problems: 1) How to manage a store's product returns under a given budgetary limitation for financial planning and taxation reasons, due to lost income from returned items, 2) Inventory optimization by taking into account the reverse supply chain structure of the retailer, and 3) Providing insight to the retailer on how it can best re-negotiate its vendor (buy-back) contracts for its product returns. The thesis covers decision making in all three levels: day-to-day operational decisions such as which products to be returned and where to allocate them within its reverse supply chain options, mid-term tactical decisions such as which Return Centers (RC) to be activated for the Reverse Logistics (RL) activities, and long-term strategic decisions such as what should be the optimal contract terms to re-negotiate with the vendors in order to cut future return costs.


title: CO2 Soil Flux in Temperate Forests Located in Southern Ontario

abstract: Forests sequester large amounts of CO2 from the atmosphere, playing a significant role in the global carbon cycle and contributing significantly to building carbon sinks. Some of the sequestered carbon is released back into the atmosphere through autotrophic and heterotrophic respiration. The release of carbon, known as soil respiration (Rs), is regulated by environmental factors, primarily soil temperature (Ts) and soil moisture (SM). This study examines the difference in Rs at two forests sites in Southern Ontario for the 2021 growing season using automated CO2 flux measurement systems. The first site is a mature coniferous forest (TP74), and the second is a mature deciduous forest (TPD). There was no clear relationship between Rs and Ts or SM at both sites, primarily due to limited observed data available in 2021. However, it was found that an increase in SM could cause a different Rs response between the sites. When both sites experienced an increase in SM, on the same day, Rs increased at TPD, but Rs decreased at TP74. The difference in the response may be due to differences in organic material between sites, with TPD having a higher amount of organic material. A Rs Ts SM model was fitted to the data, but the correlation was poor at both sites. Model parameters from a past study at TPD were used to simulate Rs at TPD for whole year. These findings contribute to the understanding of Rs in different forest types and how environmental factors may alter rates of Rs.


title: Design of Liquid Cold Plates for Thermal Management of DC-DC Converters in Aerospace Applications

contributor:
Emadi, Ali
Mechanical Engineering

subject:
pin fins
heat transfer
cold plate
cold plate design
cold plate manufacturing
cold plate cooling

abstract:
Due to increasing power demands and decreasing component size, thermal management has become the bottleneck for many power electronic applications. The aerospace industry has focused on reducing weight, operating temperature, and pumping power of power converters since these will limit an aircrafts' range and load carrying capacity. This paper outlines a tool created in MATLAB to automate the cold plate design process for DC-DC converters (or similar applications). The tool incorporates a genetic algorithm to fi nd the optimal aligned or staggered pin fi n confi guration that maintains the devices below their critical junction temperature while reducing the system's overall weight and pressure drop. Utilizing this MATLAB design tool, a cold plate was designed, manufactured, and tested. The convection coefficient calculated within MATLAB (via empirical correlations) was veri fed using simplifi ed CFD simulations within 5% of each other. The same CFD setup, boundary condition types, and methodology are then applied for the full-sized prototype cold plate simulations. These simulations were then validated using the experimental results. For all cases, the percentage error between the simulated convection coefficient values (CFD) and the experimental results was less than 12%. The experiments' measured surface temperature and pressure drop errors were less than 8% of the predicted CFD results. Therefore, the MATLAB tool and its correlations/calculations could be veri fied (via CFD) and validated (experimentally) based on good agreement between the CFD and the experimental results. This three-pronged approach (analytical calculations, CFD simulations, and experimental validation) is an effective and robust method to solve heat transfer problems.
Overall, with the framework outlined in this thesis, a complete cold plate design can now be completed in weeks instead of months. This streamlined approach will save companies signifi cant time and money in the design and simulation phases, making this tool a valuable addition to the current literature available.

abstract: Thesis

abstract: Master of Applied Science (MASc)


title: THE CONTRIBUTIONS OF ACTIVIN B SIGNALING TO DIABETIC KIDNEY DISEASE

title: ACTIVIN B IN DIABETIC KIDNEY DISEASE

contributor:
Krepinsky, Joan
Medical Sciences

subject:
diabetic kidney disease
activin B

abstract: DKD is the leading cause of kidney failure in Canada and its patients suffer the highest morbidity and mortality rates of any kidney failure patient group. Current interventions including strict glycemic control only delay DKD. Thus, there is a major need to identify new therapeutic targets. High glucose (HG) is identified as a major pathogenic factor, inducing the release of growth factors leading to kidney fibrosis. Although treatments have been developed to target these factors, their effectiveness is accompanied by adverse effects due to the lack of specificity. Recently, activins have been suggested to have a prominent role in promoting renal fibrosis and developing a specific anti-activin therapy can avoid potential side effects. Although there is evidence supporting an important role for activin A (ActA) in the induction of fibrosis in DKD, whether ActB also contributes is unknown. In this study, we aim to determine the potential contribution of ActB to promoting fibrosis. Our results show that ActA and ActB are upregulated in rodent and human DKD. We show that hyperglycemia leads to the secretion of ActA and ActB by mesangial cells (MC), whereas only ActB is secreted by renal fibroblasts (RF). Similar to HG, treatment with ActA or ActB leads to Smad2/3 activation and upregulation of extracellular matrix proteins, whereas specific inhibition of either ActA or ActB attenuates these effects. We show that ActA and ActB regulate HG-induced activation of MRTF-A/SRF in MC, leading to an activated phenotype characterized by increased α-SMA expression and ECM production. Lastly, we confirm the specificity and functionality of the activin propeptides in vitro, providing evidence for their effectiveness in vivo. This study will help further our knowledge of the role activins in DKD, potentially providing an alternative therapy.

abstract: Thesis

abstract: Master of Science (MSc)

abstract: As the leading cause of end stage renal disease, diabetic kidney disease (DKD) is described as the reduction in renal function due to chronic exposure to diabetes. This thesis is aimed to understand the pathways and mechanisms that contribute to the development and progression of DKD to help identify novel therapeutic options. This project identified activin B (ActB) as a contributor to the disease and gives evidence that blocking the actions of ActB can prevent profibrotic effects in cells, similar to the profibrotic effects seen in DKD. Furthermore, this thesis demonstrates preliminary evidence for the beneficial effects of anti-ActB therapy, providing a potential alternative therapeutic option for DKD patients.


title: EXTRACORPOREAL MEMBRANE OXYGENATION FOR EARLY GRAFT DYSFUNCTION FOLLOWING HEART TRANSPLANTATION: A SYSTEMATIC REVIEW AND INDIVIDUAL PATIENT DATA META-ANALYSIS

contributor:
Gordon, Guyatt
Health Research Methodology

abstract:
Background: Early graft dysfunction (EGD) is a major cause of early morbidity and mortality following heart transplantation (HT). The management of severe EGD often includes the use of veno-arterial extracorporeal membrane oxygenation (VA-ECMO). Studies evaluating the effectiveness of VA-ECMO are primarily retrospective single centre studies with variable results.
Objectives: The objectives of this systematic review and individual patient data (IPD) meta-analysis are to appraise the available evidence to: 1) evaluate overall prognosis (30-day mortality, in-hospital mortality, 1-year mortality), 2) characterize rates of other major VA-ECMO complications, 3) identify factors associated with prognosis (in-hospital mortality, 1-year mortality) and 4) compare  the effect of different ways of delivering VA-ECMO (e.g., peripheral vs. central cannulation, early intraoperative vs. delayed postoperative cannulation) on outcomes in adult HT recipients who developed severe EGD and received VA-ECMO
Search methods: We searched Ovid MEDLINE, Ovid Embase, Cochrane Database of Systematic Reviews, and Cochrane Central Register of Controlled Clinical Trials from January 1, 2009 to May 15, 2020. We included randomized and non-randomized studies published in any language, as abstracts or full texts that included adults (≥18 years) who received VA-ECMO during their index hospitalization after HT and reported on mortality at any timepoint.
Data collection and analysis: We assessed risk of bias using QUIPS for objectives 1-3 and ROBINS-I for objective 4.  One reviewer completed data extraction and a second reviewer verified. Authors of each identified study from the systematic review received invitations to participate in the IPD meta-analysis. We pooled study level data for 30-day mortality, in-hospital mortality, 1-year mortality and VA-ECMO complications using random-effects models with the metaprop command on STATA (StataCorp. 2019. Stata Statistical Software: Release 16. College Station, TX: StataCorp LLC.). To identify prognostic factors, we analysed IPD using a mixed effects logistic regression with a random effects term for each IPD study. We calculated summary risk ratios using random effect models for the effect of the following interventions on survival to hospital discharge: central vs. peripheral cannulation, intraoperative (early) vs. postoperative (delayed) cannulation, LV unloading vs. no LV unloading, nitric oxide vs. no nitric oxide while on VA-ECMO support. We assessed the certainty in the evidence using the GRADE framework.
Results: We included 49 observational studies of 1,477 patients of which 15 studies of 448 patients provided IPD. In addressing prognosis using QUIPS, most studies (79%) proved at low or acceptable overall risk of bias. There were no important differences in short-term or 1-year mortality estimates between IPD and non-IPD studies. We are moderately certain in the short-term mortality estimate of 33% (95%CI: 27%, 39%) and 1-year mortality estimate of 50% (95%CI: 43%, 57%). With moderate certainty, estimates of bleeding and sepsis/infection while on VA-ECMO support were 38% (95%CI: 28%, 48%) and 21% (95%CI: 14%, 28%) respectively. Three factors were associated with increased short-term mortality with high certainty: recipient age (OR 1.02, 95% CI: 1.01-1.04), donor age (OR 1.01, 95% CI 1.00-1.03) and prior sternotomy (OR 1.57, 95%CI 0.99-2.49). Lastly, there is very low certainty evidence that VA-ECMO strategies of early intraoperative cannulation and peripheral cannulation reduce the risk of in-hospital mortality.
Conclusions: One third of patients who receive VA-ECMO for EGD do not survive to hospital discharge, and nearly half do not survive to 1 year after HT. Improving outcomes in this patient population will require careful consideration of recipient factors such as age and prior sternotomy and further research on optimal VA-ECMO strategies.

abstract: Thesis

abstract: Master of Health Sciences (MSc)

abstract: Early graft dysfunction (EGD) refers to the failure of a donor heart soon after it is transplanted into a recipient. EGD is a major cause of early complications and death in heart transplant recipients. The management of severe EGD may include the use of a temporary heart-lung machine called veno-arterial extracorporeal membrane oxygenation (VA-ECMO), which supports the circulation while the transplanted heart recovers. In our review of studies reporting rates of death in recipients who required VA-ECMO for EGD, we found that approximately one-third die in the short-term and just under half die by one-year after transplant. The most common complications while supported on VA-ECMO were bleeding, infection and need for dialysis. Older recipient, donor age, and having a prior sternotomy were factors associated with lower survival to hospital discharge. Connecting to peripheral blood vessels rather than central ones and earlier use of VA-ECMO support may be associated with lower risk of death. Our findings are important because we demonstrate that prognosis in the first year after HT for these patients is not as favorable as is commonly believed. Strategies at the time of VA-ECMO use may improve survival but require further study.


title: Supporting the Implementation of Integrated Primary Care and Social Care Services: A Qualitative Descriptive Study

contributor:
Wilson, Michael
Health Research Methodology

subject:
Public Health
Integrated Care
Social Determinants of Health
Social Services

abstract:
Background:
Within the Ontario context, a recent shift towards integrated care has led to primary care reforms that have aimed to achieve the quadruple aim benchmarks. Particular focus has been placed on population health management, a key pillar of the quadruple aim metrics, which recognizes and aims to address the broader social, structural and institutional determinants that impact upon population health outcomes. As a result, this study aims to identify and describe the key characteristics of integrated primary care and social care models, programs, and initiatives in Ontario that aim to address the social determinants of health. It also aims to identify barriers and facilitators in the implementation of these integrated care initiatives to support future implementation efforts.

Methods:
A qualitative descriptive study design was utilized and was conducted in two phases: 1) document analysis; and 2) 13 in-depth semi-structured interviews with policymakers, managers/ administrators, clinicians and service providers involved in leading integrated primary and social care initiatives in Ontario.

Results:
Developing and implementing these initiatives had primarily required the introduction of new governance and delivery arrangements. This included the adoption of shared governance structures where equal decision-making authority was often established between health and social partners, and the introduction of a system navigator role who was commonly co-located within primary care. There were minimal insights in relation to the development of new financial arrangements aside from a few joint funding agreements, as almost all initiatives did not share financial resources and few modified staff or provider remuneration. Initiatives experienced barriers including a lack of permanent or long-term funding and technological infrastructure to support patient tracking, follow-up, and information sharing between health and social partners. However, the system navigator position was found to be an essential role in bridging communication gaps between sectors and delivering integrated care for clients. In addition, factors such as pre-existing informal and formal partnerships between primary care and social care organizations, communication and trust between health and social partners, and organizational leadership support for integration were viewed as enablers.

Discussion and Conclusions:
The lessons learned from participants’ experiences in planning and implementing integrated primary care and social care models are timely and can inform future implementation and scale up as the province continues to move towards integrated care arrangements in efforts to achieve the quadruple aim benchmarks. Specific recommendations for policy and future research are proposed.

abstract: Thesis

abstract: Master of Public Health (MPH)

abstract: Health systems in Canada are positioned to treat symptoms of health issues instead of addressing the root causes of illness and disease, such as lack of housing, access to healthy and nutritious food, and stable employment opportunities. Recently, health system reforms in Ontario have shifted to population health-based approaches to care which recognize and aim to address these non-medical determinants of health outcomes. Primary care, which is often an individual's first point of contact with the health system, may be uniquely positioned to fulfill this mandate due to the capabilities of primary care providers to develop and sustain relationships with patients along the life course. Primary care practitioners may be more aware of patients' underlying social needs that result in adverse health outcomes. This study aimed to identify models of care in Ontario that coordinate care for patients between health and social services such as housing and employment support. It was conducted in two phases. Phase one included a targeted document search which used government policy documents, stakeholder websites, and journal databases to identify these integrated models of care in Ontario. In phase two, 13 stakeholders identified from existing models were interviewed to explore their experiences with models that integrate primary care and social care services and the barriers and facilitators to implementing such models. The study found that most initiatives had made modifications to governance and delivery arrangements to support implementation, including the adoption of shared governance approaches and a system navigator position responsible for coordinating care for clients. The initiatives primarily experienced barriers with funding insecurity, communication and information sharing between health and social partners, and technology. However, communication and trust between health and social partners and organizational leadership support were factors that supported the implementation of initiatives. The findings from this research may support future implementation and scale-up of these coordinated models of care in Ontario.


title: Advanced State Estimation For Electric Vehicle Batteries

contributor:
Habibi, Saeid
Goward, Gillian

subject:
Lithium-ion Batteries
Battery Packs
State of Charge
State of Health
State of Power
Parameter Identification
Smooth Variable Structure Filter
Adaptive Filtering

abstract:
Lithium-ion (Li-ion) batteries are amongst the most commonly used types in Electric (EVs) and Hybrid Electric (HEVs) Vehicles due to their high energy and power densities, as well as long lifetime. A battery is one of the most important components of an EV and hence it needs to be monitored and controlled accurately. The safety, and reliability of battery packs must then, be ensured by accurate management, control, and monitoring functions by using a Battery Management System (BMS).
A BMS is also responsible for accurate real-time estimation of the State of Charge (SoC), State of Health (SoH) and State of Power (SoP) of the battery. The battery SoC provides information on the amount of energy left in the battery. The SoH determines the remaining capacity and health of a pack, and the SoP represents the maximum available power. These critical battery states cannot be directly measured. Therefore, they have to be inferred from measurable parameters such as the current delivered by the battery as well as its terminal voltage. Consequently, in order to offer
accurate monitoring of SoC, SoH and SoP, advanced numerical estimation methods need to be deployed.
In the estimation process, the states and parameters of a system are extracted from measurements. The objective is to reduce the estimation errors in the presence of uncertainties and noise under different operating conditions. This thesis uses and provides different enhancements to a robust estimation strategy referred to as the Smooth Variable Structure Filter (SVSF) for condition monitoring of batteries. The SVSF is a predictor-corrector method based on sliding mode control that enhances the robustness in the presence of noise and uncertainties. The methods are proposed to
provide accurate estimates of the battery states of operation and can be implemented in real-time in BMS.
To improve the performance of battery condition monitoring, a measurement-based SoC estimation method called coulomb counting is paired with model-based state estimation strategy. Important considerations in parameter and state estimation are model formulation and observability. In this research, a new model formulation that treats coulomb counting as an added measurement is proposed. It is shown that this formulation enhanced information extraction, leading to a more accurate state estimation, as well as an increase in the number of parameters and variables that
can be estimated while maintaining observability. This model formulation is used for characterizing the battery in a range of operating conditions. In turn, the models are integral to a proposed adaptive filter that is a combination of the Interacting Multiple Model (IMM) concept and the SVSF. It is shown that this combined strategy is an efficient estimation approach that can effectively deal with battery aging. The proposed method provides accurate estimation for various SoH of a battery.
Further to battery aging adaptation, measurement errors such as sensor noise, drift, and bias that affect estimation performance, are considered. To improve the accuracy of battery state estimation, a noise covariance adaptation scheme is developed for the SVSF method. This strategy further improves the robustness of the SVSF in the presence of unknown physical disturbances, noise, and initial conditions. The proposed estimation strategies are also considered for their implementation on battery packs. An important consideration in pack level battery management is
cell-to-cell variations that impact battery safety. This study considers online battery parametrization to update the pack’s model over time and to detect cell-to-cell variability in parallel-connected battery cells configurations. Experimental data are used to validate and test the efficacy of the proposed methods in this thesis.

abstract: Thesis

abstract: Doctor of Philosophy (PhD)

abstract: To address the critical issue of climate change, it is necessary to replace fossil-fuel vehicles with battery-powered electric vehicles. Despite the benefits of electric vehicles, their popularity is still limited by the range anxiety and the cost determined by the battery pack. The range of an electric vehicle is determined by the amount of charge in its battery pack. This is comparable to the amount of gasoline in a gasoline vehicle’s tank. In consideration of the need for methods to address range anxiety, it is necessary to develop advanced algorithms for continuous monitoring and control of a battery pack to maximize its performance. However, the amount of charge and health of a battery pack cannot be measured directly and must be inferred from measurable variables including current, voltage and temperature. This research presents several algorithms for detecting the range and health of a battery pack under a variety of operating conditions. With a more accurate algorithm, a battery pack can be monitored closely, resulting in lower long-term costs. Adaptive methods for determining a battery’s state of charge and health in uncertain and noisy conditions have been developed to provide an accurate measure of available charge and capacity. Methods are then extended to improve the determination of state of charge and health for a battery module.


title: Comparison of vernal pool characteristics in an old-growth forest and a disturbed urban forest in Southern Ontario

subject:
vernal pool
Southern Ontario
Jefferson salamander
forest disturbance
urbanization
conservation

abstract: There is a large incentive to understand vernal pool ecosystems in Southern Ontario, as they serve essential ecological functions within forests – including providing critical habitat for at-risk amphibians like Jefferson salamanders. Additionally, while deforestation has drastically reduced the quantity of vernal pools in this region, it is unclear how these landscape alterations have affected the quality and characteristics of vernal pools in remaining woodlots. This study addresses this gap in knowledge, by evaluating whether or not vernal pool characteristics vary between an old-growth forest (Backus Woods) and a more disturbed forest (Hamilton) in Southern Ontario. Using fall field surveys, I recorded characteristics of 10 vernal pools in the Hamilton region and 13 vernal pools in the old-growth forests of Backus Woods, and used GIS to evaluate their landscape context. Vernal pools in the Hamilton region had less shaded canopies, shallower depths, and higher water conductivities and total nitrate nitrogen concentrations than those in Backus Woods. Hamilton vernal pools occurred nearer to forest edges and adjacent urban lands, whereas those in Backus Woods were located within larger regions of forest and were surrounded by agricultural land. Land use was not a significant predictor of vernal pool characteristics; instead, forest structure (e.g., disturbed vs old-growth, coniferous vs deciduous) likely played a key role in determining how vernal pool characteristics responded to the surrounding landscape. My results support that human disturbances such as land use alteration can influence vernal pool characteristics, which may influence habitat suitability of at-risk amphibians.


title: Improving Thermal Stability and Intratracheal Delivery of Viral-Vectored Dry Powder Vaccines

contributor:
Thompson, Michael
Cranston, Emily
Chemical Engineering

subject:
Dry Powder Vaccines
Thermal Stabilty
Inhalation
Spray Drying

abstract: This work focuses on the development of a spray dried adenoviral vector for its application as a thermally stable and inhalable vaccine against tuberculosis.

abstract:
As the global public health community continues to strive for more equitable vaccine access, thermal instability of liquid vaccines continues to be a significant challenge due to strict cold-chain temperature requirements. Dry powder vaccines offer a favourable alternative, with the ability to retain vaccine efficacy at ambient temperature conditions. In the form of dry powder, vaccines against respiratory diseases can also be administered via inhalation for targeted delivery to the lung tissue. A processing technique known as spray drying is particularly promising for the development of thermally stable and inhalable dry powder vaccines, offering a method of continuous and scalable production. Spray drying is widely used in the pharmaceutical industry and can effectively encapsulate and immobilize labile biologics, like adenoviral vectors, within a glassy carbohydrate matrix to help retain biologic function. However, pulmonary delivery of a thermally stable, viral vectored dry powder vaccine has yet to be demonstrated.
This thesis focuses on improving the formulation of a carbohydrate excipient blend of mannitol and dextran encapsulating a human serotype 5 adenovirus (AdHu5), with the goal of producing an inhalable vaccine with sufficient viral potency for in vivo murine testing. First, the impact of cryoprotective agents used for frozen storage of the stock adenovirus was investigated with respect to viral activity retention, thermal stability and inhalation properties of the dry powder after spray drying. Trehalose was considered a preferred cryoprotective agent, compared to glycerol traditionally used for adenoviral cryo-storage, allowing for the preparation of a high potency viral dry powder with 1.5 log loss of viral titre after processing and thermal aging. Further investigation of the dextran mass ratio and dextran molecular weight used within the excipient blend revealed that incorporating mannitol in a 1:3 ratio with 500 kDa dextran can further improve viral activity to achieve 0.8 log loss of viral titre after aging. Through controlled drying dynamics, this formulation led to improved activity retention and thermal stability, in addition to desirable aerosolization properties for pulmonary delivery. Using this optimized formulation, custom-made intratracheal dosator devices were evaluated for pulmonary powder delivery in mice. The method of powder loading in the device was found to be a significant factor of device performance in vivo when determining if the critical powder mass dosage could be delivered.  Successful intratracheal delivery of the AdHu5-vectored dry powder was achieved with a pipette-tip loading dosator and led to a strong bioactive response. Overall, this work indicates the feasibility of murine pulmonary delivery and immunological testing of a thermally stable, adenoviral-vectored vaccine in dry powder form.

abstract: Thesis

abstract: Master of Applied Science (MASc)

abstract: Most vaccines currently available on the market must be stored and transported at temperatures ranging from 2-8 ⁰C to properly maintain their function, with some vaccine requiring temperatures as low as -80 ⁰C. The equipment required to maintain such temperatures is costly and is a significant limitation for developing nations trying to secure vaccine access. As an alternative to traditional liquid vaccine formulations, dry powder vaccines offer stability at room temperature without the need for expensive equipment and can also be administered through inhalation. Using a processing method called spray drying, an active vaccine component can be encapsulated in a carefully selected sugar formulation which forms a protective coating as the particles dry to provide stabilization. Since the efficacy of such dry powder vaccines must be first evaluated with mouse models, the focus of this work was to improve an existing blend of sugars to produce a dry vaccine powder that contains high enough dosage for mouse testing. Processing losses from spray drying were minimized through careful selection of vaccine cryoprotective agents, in addition to optimizing the blend ratio and molecular weight of sugars used for encapsulation. Successful delivery of the optimized powder to the lungs of mice was also accomplished after analyzing the suitability of a variety of custom-made handheld devices. This work shows that inhalable dry powder vaccine delivery is a promising solution to help improve temperature stability and achieve more equitable access to vaccines globally.


title: Characterization of UVA biophoton emission and survival of α-irradiated HCT116+/+ cells via radium exposure

subject:
Radiation
Radiation Biology
Radium
Ra-226
Cell Culture
Biophoton
UVA
Alpa-radiation

abstract:
Background: It’s been hypothesized that biophoton production is a result of the generation of excited species followed by relaxation of these excited species to a stable state. This can occur as a result of many stressors including irradiation from radioactive materials. Cell exposure to radium (Ra-226) has not been thoroughly explored for biophoton production. Furthermore, biophoton production is often associated with oxidative stress and cell death which is concurrently also an area of exploration.
Objectives: The objective of this study was to characterize biophoton emission and additionally observe cell survival from α-irradiated HCT116+/+ cells via radium exposure. We aim to expand evidence that supports increased biophoton production and decreased cell survival as a result of oxidative stress and exposure to radioactive material.
Methods: HCT116+/+ cells were standardly cultured in this study. For characterization of biophotons, cell groups were irradiated with 10, 100, 1000 and 10,000mBq/ml of Ra-226 for 24 hours. A photon counter was used to quantify counts. For characterization of cell survival, standard clonogenic assay techniques were used. Cell groups were irradiated with the same concentrations for Ra-226 and colonies were counted 7-9 days later.
Results: No significant results were seen when observing biophoton counts from Ra-226 irradiated groups compared to a background count. Furthermore, there was a significant difference between Ra-226 irradiated groups when compared to a positive control known to produce biophotons. Some significant differences were seen in the surviving fraction of directly irradiated cells when looking at the different concentrations of Ra-226. However, overall there was a correlation that could be seen where an increase in concentration of Ra-226 resulted in a decreased surviving fraction of cells.
Conclusions: The hypothesis of this study was partially supported where increased exposure and sensitivity to Ra-226 showed decreased cell survival, and assumed to have implications on biophoton production at higher concentrations although was not observed here at environmentally relevant concentrations. It was also concluded that biophoton production and oxidative stress are independent events. The significance of biophoton production as a radiation-induced bystander effect was explored as an implication of this study.

abstract: This work was supported by the Canadian Research Chairs Program [grant number 950- 221284]; National Chronic Fatigue and Immune Dysfunction Syndrome Foundation Inc.; Natural Sciences and Engineering Research Council Collaborative Research and Development Grant [grant number RGPIN293153-12]; CANDU Owners Group [grant number CRDPJ484381-15]; Bruce Power; and the Natural Sciences and Engineering Research Council of Canada Undergraduate Student Research Award program. Funding sources had no role in in study design; in the collection, analysis and interpretation of data; and in the writing of the report.


title: MAPPING PATTERNS AND IDENTIFYING CONCEPTUAL FRAMEWORKS IN GLOBAL HEALTH RESEARCH: A SYSTEMATIC REVIEW

contributor:
Shannon, Harry
Doubleday, Nancy
Global Health

subject: global health

subject: multiple correspondence analysis

subject: decolonization

subject: systematic review

abstract: Background: Global health is a complex, interdisciplinary, and contested field. It is rapidly growing and undergoing ideological and methodological changes. Despite many theoretical claims over what global health research ought to be, there are few empirical reports on what global health is, as a present field of research. The aim of this study is to: 1) determine patterns in global health research, based on key research characteristics; and 2) determine relationships between these characteristics to identify and define conceptual frameworks in global health research. Methodology: A systematic review of research in global health journals was conducted for papers published in the years 2010, 2015, and 2020. Categorical data on 17 research characteristics was extracted from all studies included in the analysis. The relationships between these characteristics was analyzed and visualized using multiple correspondence analysis, as implemented in the R’s ca package. Significance tests of independence determined relationships between pairs of variables. Results: The final analysis was done on 1033 included studies from 14 journals. 56% of the studies used a quantitative observational methodology. While 82% of research had at least one author affiliated with a high-income country, 96% of research funded (at least partially) by the Bill & Melinda Gates Foundation had at least one author affiliated with a high-income country. There was a significant relationship between the use of social and structural determinants of health and the authors’ affiliations (X2=59.06, p < 0.001), with the use of social and structural determinants of health lower among lower-income authors than high-income authors. The first and second dimensions of multiple correspondence analysis explained 38% of the variables’ deviation from independence. Conclusion: Multiple correspondence analysis offers a novel way of understanding global health research, contributing empirical data to the discourse on what lies ahead for the field of global health. The relationship between the use of social and structural determinants of health, authorship, and research methodologies point to the need for important conversations on the direction of global health research, starting from where we are at now.

abstract: Thesis

abstract: Master of Science (MSc)

abstract: While the importance of the field of global health is more prominent than ever, it is a field of uncertainty, controversy, contested merit, and often disreputable history. Conversations abound on the strengths and weaknesses of the field and what needs to change; yet, there is a lack of empirical grounding for these discussions. In this study, I reviewed global health research literature, identifying 17 key characteristics that surface in theoretical conversations on global health, and scored 1033 global health research studies according to these characteristics. Using multiple correspondence analysis, the 17 characteristics were analyzed together and visualized to elucidate the relationships between the characteristics. I found that: over half of the studies were quantitative observational; most research in global health had at least one author from a high-income country; and middle-income authors were less likely to study social and structural determinants of health than high-income authors. These findings lend important empirical evidence to conversations on the direction of the field, starting from where we are at now.


title: Geophysical investigations and interactive visualizations of the Charlie-Gibbs Fracture Zone.

publisher: School of Earth, Environment and Society

subject: geophysics, North Atlantic, fracture zone, micro-gravity, geomagnetism

abstract:
Oceanic transform faults and their associated fracture zones are key constituents of tectonic processes and regions of high seismic activity. While they are of scientific interest, the remote nature and extreme ocean depths at these sites limits manual exploration and sample collection. This challenge has promoted the use of other methods of data collection and analysis such as satellite altimetry, ship depth-soundings, and computational modelling. Despite decades of study and large quantities of data, these features remain poorly understood. A common difficulty in analyzing these structures lies in the fact that many geophysical datasets are largely disjointed and often have incompatible resolutions and file formats. Additionally, some datasets must be derived from others or require processing in order to discern features of interest.
This thesis aims to broaden our understanding of the Charlie-Gibbs Fracture Zone, an extensive structure found in the North-Atlantic Ocean. As the largest interruption of the Mid-Atlantic Ridge between Iceland and the Azores, this unique system of two parallel FZs is of particular interest to many geoscientists. Through the processing and compilation of several geophysical datasets, this study sought to find computational methods that could highlight key structural features, enhance small-scall anomalies, and allow hidden patterns to be seen.
Freely available datasets for bathymetry, free-air gravity anomaly, and magnetic anomaly were downloaded and read into GMT (the general mapping tools), where they were converted to grid files and clipped to the study region. A bathymetric illumination grid was calculated using the directional derivative of the bathymetry grid, and the Bouguer anomaly was derived from the bathymetry and free-air gravity anomaly grids. Upward continuation and wavelength filtering were applied to both the free-air gravity anomaly and magnetic anomaly datasets, to compare the effects of the different processes and enhance small-scale anomalies and linear features. Transects across final datasets were sampled and intermediate values were interpolated to create profiles in Microsoft Excel. All resulting datasets were converted to netCDF files, from which raster layers were produced in ArcGIS Pro. This allowed the findings to be presented in a new and educational way: through the creation of an online interactive story map.


title: CHARACTERIZING THE ROLE OF THE TRANSCRIPTION FACTOR PLAG1 IN HUMAN HEMATOPOIETIC STEM AND PROGENITOR CELLS

title: CHARACTERIZING PLAG1 IN HUMAN HEMATOPOIETIC STEM CELLS

contributor:
Hope, Kristin
Biochemistry and Biomedical Sciences

abstract: Hematopoietic stem cell (HSC) dormancy is understood as supportive of HSC function and their long-term integrity. While regulation of stress responses incurred as a result of HSC activation is recognized as important in maintaining stem cell function, little is understood of the preventative machinery present in human HSCs that may serve to resist their activation and promote HSC self-renewal. We demonstrate that the transcription factor PLAG1 is essential for long-term HSC function and when overexpressed endows a 15.6-fold enhancement in the frequency of functional HSCs in stimulatory conditions. Genome-wide measures of chromatin occupancy and PLAG1-directed gene expression changes combined with functional measures reveal that PLAG1 dampens protein synthesis, restrains cell growth and division, and enhances survival, with the primitive cell advantages it imparts being attenuated by addition of the potent translation activator, c-MYC. We find PLAG1 capitalizes on multiple regulatory factors to ensure protective diminished protein synthesis including 4EBP1 and translation-targeting miR-127, and does so independently of stress response signaling. Overall, our study identifies PLAG1 as an enforcer of human HSC dormancy and self-renewal through its highly context-specific regulation of protein biosynthesis, and classifies PLAG1 among a rare set of bona fide regulators of mRNA translation in these cells. Our findings showcase the importance of regulated translation control underlying human HSC physiology, its dysregulation under activating demands, and the potential if its targeting for therapeutic benefit.

abstract: Thesis

abstract: Doctor of Science  (PhD)

abstract: Blood production (hematopoiesis) is a stem cell-driven regenerative system that can repair damaged blood systems and therefore offer lifesaving treatments for devastating malignancies and immune disorders. Realizing the full potential of hematopoietic stem cells (HSCs) is encumbered by our inability to maintain HSCs with long-term functionality in clinical settings. Enhanced fundamental insights into the properties that define human HSC identity and fates can thus inform the rational design and advancement of HSC-based therapies. We discovered a regulator, PLAG1, that is essential for the long-term blood production function of human HSCs. When elevated PLAG1 amplified the absolute number of human HSCs 15-fold and improved their maintenance and function in clinically-relevant culture and transplantation settings. Using genome-wide technologies paired with functional assays we elucidated that PLAG1 employs a multi-pronged strategy to rewire protein production rates as a means to enhance HSC preservation and function. Our findings highlight regulation of protein production as an untapped strategy that could be incorporated into clinical settings to improve patient outcomes.


title: ASSESSING THE IMPACT OF VEGETATION ON EROSION PROCESSES ON THE NIAGARA ESCARPMENT IN THE HAMILTON REGION, CANADA

contributor:
Eyles, Carolyn
Earth and Environmental Sciences

subject:
Niagara Escarpment
Erosion
Vegetation
Triaxial Accelerometer

abstract:
The stability of the Niagara Escarpment is of critical importance to residents of Hamilton, Ontario as it bisects and divides the lower downtown core from upper residential and commercial areas. The frequency of large rockfalls and debris slides from the exposed escarpment face has resulted in reoccurring road closures that connect these two areas and has prompted the city to seek information on the processes affecting escarpment erosion and slope stability. The research reported here examines the relationship between tree and plant growth on bedrock stability by investigating relationships between species abundance and slope profile, and the potential movement of tree roots growing in rock fractures.
The contributing factors of tree growth to physical weathering processes on highly fractured bedrock remain largely unknown; however, plants are suggested to play a key role in weathering processes in the critical zone. Bedrock structure and lithology influence the establishment of vegetation, and vegetation in turn exploits bedrock joints, fractures, and bedding planes, exacerbating physical and biomechanical weathering processes. In this study, vegetation characteristics observed on different parts of the escarpment face were documented and categorized into three distinct biophysical zones: upper and intermediary plateau, bedrock face, and sloping talus. Tree growth, with the potential to enhance bedrock disaggregation through the transfer of tree bole movement to roots exploiting bedrock fractures, was particularly prevalent on areas of sloping talus. To document the potential for bedrock disaggregation through tree bole movement, triaxial accelerometers were mounted on the boles of three different tree species growing along the escarpment in Hamilton. Sampled trees varied in geographic location to allow identification of the relationship between tree bole movement, wind speed, and dominant wind direction. Both deciduous and coniferous species were monitored to determine the impacts of canopy architecture on tree sway in response to wind. Monitoring took place over several days in the months of March, May, September, and November. Recorded tree bole movement (tilt) varied between deciduous and coniferous tree species; wind speed was strongly correlated to tilt of the coniferous tree, and wind direction was strongly correlated to tilt of the deciduous trees. Overall tree bole movement was strongly influenced by diurnal cycles of air movement and was greatest in the hours around mid-day.
The outcomes of this research will form an integral component of an erosion-risk assessment study conducted, in part, for the City of Hamilton and will facilitate the design and development of vegetation management strategies for the Niagara Escarpment that may reduce erosion processes and potential damages to impacted citizens and businesses.

abstract: Thesis

abstract: Master of Science (MSc)

abstract: This research examines the impact of vegetation growth on erosion processes on the Niagara Escarpment in Hamilton, Ontario. The slope of the escarpment face exerts an important control on vegetation growth which in turn affects slope stability. Documentation of the dominant vegetation species at two research sites allows the identification of three distinct vegetation zones on the upper plateau, bedrock face, and sloping talus. The movement of tree trunks in response to air movement was also measured for several days in the months of March, May, October and November. Results show that the movement of two monitored deciduous trees was most strongly correlated to wind direction, while the movement of a coniferous tree was strongly correlated to changes in wind speed. All monitored trees were strongly influenced by daily cycles of air movement which were greatest around noon. This research identifies factors that influence both vegetation growth and slope stability on the Niagara Escarpment and may be used to develop effective erosion protection and mitigation strategies.


title: Impact of Completing Face-Q Craniofacial Module Scales on Children and Young Adults with Facial Differences: An International Study

contributor:
Klassen, Anne
Thoma, Achilles
Voineskos, Sophocles
Health Research Methodology

abstract:
BACKGROUND: The FACE-Q Craniofacial module measures outcomes that matter to patients with diverse craniofacial conditions. However, it is not known whether completing a patient reported outcome measure (PROM) has a negative impact on patients, particularly children. This study aims to investigate the impact of completing the FACE-Q Craniofacial module and identify factors associated with a negative impact.
METHODS: Participants were aged 8-29 years, with a facial difference, who completed at least one module of the FACE-Q Craniofacial module as part of the international field-test study between December 2016-2019. Participants were asked three questions: ‘Did you like or dislike answering this questionnaire?’; ‘Did answering these questions change how you feel about how you look?’; and ‘Did answering this questionnaire make you feel unhappy or happy?’ Univariate and multivariable logistic regression analyses were used to evaluate variables associated with a negative response.
RESULTS: The sample included 927 participants. Most patients responded neutrally to all impact questions: 42.7% neither disliked nor liked the questionnaire; 76.6% felt the same about how they looked; and 72.7% felt neither unhappy/happy after completion. Negative responses represented a small proportion of patients across all three impact questions (<13.2%). Increased craniofacial severity, more scales completed, and lower scores on all FACE-Q scales were associated with negative responses for all three impact questions (p<0.01).
CONCLUSION: This study provides evidence that the FACE-Q Craniofacial module is acceptable for most participants. Clinicians and study investigators should follow up with patients after completing this PROM to address areas of concern in scale scores.

abstract: Thesis

abstract: Master of Science (MSc)

abstract: The FACE-Q Craniofacial module measures outcomes that matter to children and young adults with diverse facial conditions. To date, it remains unclear whether asking detailed questions about facial appearance and function can negatively impact patients, particularly children. The purpose of this study was to investigate the impact of completing the FACE-Q Craniofacial module and to identify factors associated with a negative impact in children and young adults. Participants aged 8-29, who completed at least one scale of the FACE-Q Craniofacial module as part of the international field-test study between December 2016-2019, were asked three impact questions following scale completion. Most patients responded neutrally to all questions with negative responses representing only a small proportion of patients (<13%). Increased severity of the facial condition, more scales completed, and lower FACE-Q scale scores were associated with a negative impact. Ultimately, this study demonstrates the FACE-Q Craniofacial module is acceptable for most participants.


title: Deep Learning Approaches to  Low-level Vision Problems

contributor:
Chen, Jun
Electrical and Computer Engineering

subject:
Low-level Vision
Computer Vision
Image Restoration
Image Dehazing
Image Denoising
Image Super-resolution
Test-time Adaptation
Meta-Learning
Stereo Matching
Depth Estimation
Optimal Transport

abstract:
Recent years have witnessed tremendous success in using deep learning approaches to handle low-level vision problems. Most of the deep learning based methods address the low-level vision problem by training a neural network to approximate the mapping from the inputs to the desired ground truths. However, directly learning this mapping is usually difficult and cannot achieve ideal performance. Besides, under the setting of unsupervised learning, the general deep learning approach cannot be used. In this thesis, we investigate and address several problems in low-level vision using the proposed approaches.
To learn a better mapping using the existing data, an indirect domain shift mechanism is proposed to add explicit constraints inside the neural network for single image dehazing. This allows the neural network to be optimized across several identified neighbours, resulting in a better performance.
Despite the success of the proposed approaches in learning an improved mapping from the inputs to the targets, three problems of unsupervised  learning is also investigated. For unsupervised monocular depth estimation, a teacher-student network is introduced to strategically integrate both supervised and unsupervised learning benefits. The teacher network is formed by learning under the binocular depth estimation setting, and the student network is constructed as the primary network for monocular depth estimation. In observing that the performance of the teacher network is far better than that of the student network, a knowledge distillation approach is proposed to help improve the mapping learned by the student.
For single image dehazing, the current network cannot handle different types of haze patterns as it is trained on a particular dataset. The problem is formulated as a multi-domain dehazing problem. To address this issue, a test-time training approach is proposed to leverage a helper network in assisting the dehazing network adapting to a particular domain using self-supervision.
In lossy compression system, the target distribution can be different from that of the source and ground truths are not available for reference.
Thus, the objective is to transform the source to target under a rate constraint, which generalizes the optimal transport. To address this problem, theoretical analyses on the trade-off between compression rate and minimal achievable distortion are studied under the cases with and without common randomness. A deep learning approach is also developed using our theoretical results for addressing super-resolution and denoising tasks.
Extensive experiments and analyses have been conducted to prove the effectiveness of the proposed deep learning based methods in handling the problems in low-level vision.

abstract: Thesis

abstract: Doctor of Philosophy (PhD)


title: Developing and validating a novel in vitro smoke exposure model and investigating the innate immunological impact of cannabis smoke exposure on primary human bronchial epithelial cells

contributor:
Jeremy, Hirota
Medical Sciences

subject:
Cannabis Smoke
in vitro model
Human Bronchial Epithelial Cells

abstract:
Accessible in vitro models recapitulating the human airway that are amenable to study whole cannabis smoke exposure are needed for immunological and toxicological studies that inform public health policy as well as medicinal and recreational cannabis use. In the present study, we developed and validated a novel three-dimensional (3D)-printed in vitro exposure system (IVES) that can be directly applied to study the effect of cannabis smoke exposure on primary human bronchial epithelial cells (HBECs).
Using commercially available design software and a 3D printer, we designed a four-chamber Transwell insert holder for exposures to whole smoke. COMSOL Multiphysics software was used to model gas distribution, concentration gradients, velocity profile, and shear stress within IVES. Following simulations, primary HBECs cultured at the air–liquid interface on Transwell inserts were exposed to whole cannabis smoke using a modified version of the Foltin puff procedure. Following 24 h, outcome measurements included cell morphology, epithelial barrier function, lactate dehydrogenase (LDH) levels, cytokine expression and gene expression.
HBECs exposed to cannabis smoke using IVES showed changes in cell morphology and disruption of barrier function without significant cytotoxicity. Cannabis smoke elevated interleukin-1 (IL-1) family cytokines and elevated CYP1A1 and CYP1B1 expression relative to control. These findings validate IVES to have an effect in HBECs at a molecular level following cannabis smoke exposure. In addition, HBECs stimulated with a viral mimetic, Poly I:C, challenge following cannabis smoke exposure showed a suppression of key antiviral cytokines.
The growing legalization of cannabis on a global scale must be paired with research related to potential health impacts on lung exposures. IVES represents an accessible, open-source, exposure system that can be used to model varying types of cannabis smoke exposures with HBECs grown under air–liquid interface culture conditions.

abstract: Thesis

abstract: Master of Science (MSc)

abstract: Despite its recent legalization in Canada, cannabis smoke has been understudied and a lack of evidence exists to inform legislative policies, medicinal and recreational usage. Due to a lack of relevant ways to study cannabis smoke in a lab setting, it is difficult to accumulate literature around its impacts in the lungs. Here, we addressed this gap by engineering and validating a novel model to expose lung cultures to cannabis smoke. In addition, we investigated its impact on the immune response. Our findings suggest exposure to cannabis smoke alters the immune functions of these cells. We also found that in response to a viral mimetic stimulus, cell cultures pre-exposed to cannabis smoke exhibited impaired immune responses. Our novel model to expose cell cultures to cannabis smoke creates a foundation for future researchers to investigate environmental insults, such as cannabis smoke, in the context of respiratory health and infectious disease.