title: Ion exchange equilibrium: selectivity coefficient and ion exchange capacity, heavy metals removal, and mathematical modelling

contributor:
Kim, Younggy
Civil Engineering

subject:
Ion Exchange Resins
Selectivity Coefficient
Ion Exchange Capacity
Heavy Metals
Mathematical Modelling

abstract: This research conducted equilibrium experiments to determine ion exchange equilibria data for the inorganic cations Ca2+, Na+, and NH4+ for binary cation exchange involving sulfonic acid, polystyrene gel resins saturated with Na+ or NH4+. A linear least-square fitting was developed to find representative ion exchange capacity (IEC) and selectivity coefficient (K) values. Equilibrium experiments were utilized to test the developed new linearization method for binary systems: Ca-NH4; Ca-Na; and Na-NH4 using three commercial strong acid cation (SAC) exchange resins. It was determined that SAC exchange resins saturated with NH4+ were more selective towards Ca2+ than resins saturated with Na+. The valency and the size of the hydrated radius of the counterion influenced the selectivity of binary systems. A higher valence and a smaller hydrated radius resulted in an increased affinity of the resin for ions. Results can be used to estimate the technical and economic feasibility of a design process along with the estimation of the effect of a change in operating conditions. In addition, the removal of toxic heavy metals was also investigated with an initial metal concentration of 0.1 mg/L. Results showed that the maximum percent removal of toxic heavy metal ions, Cr3+, Pb2+, Ba2+, and Cd2+ ranged from ~ 95-99% when present in a solution containing a high molar concentration of Ca2+, Na+, and NH4+. It was observed that SAC exchange resins can effectively remove toxic heavy metals at very low concentrations. The high selectivity that SAC exchange resins possess towards heavy metals proves that they can be used as a pretreatment method for the removal of toxic heavy metals from municipal and industrial wastewaters. Moreover, the performance of SAC exchange resins for the removal of Ca2+ from waste solutions was investigated through computer modelling. Results showed that ion exchange is an efficient method for the removal of Ca2+. A sensitivity analysis showed that the variation in K and IEC greatly influenced the breakthrough time as an increase in both parameters resulted in greater Ca2+ uptake. Modelling results can be used to optimize the design of ion exchange systems for the pretreatment of inorganic cations which can reduce membrane scaling.

abstract: Thesis

abstract: Master of Applied Science (MASc)


title: Characterization of Prokaryotic Ku DNA Binding Properties

contributor:
Andres, Sara
Biochemistry

subject:
DNA repair
Non-Homologous End-Joining
Bacteria
Ku
Protein DNA interactions
NHEJ
DNA damage
AMR

abstract:
DNA damage occurs to all living things; its subsequent repair is a crucial component of life. The most dangerous, and potentially most useful form of DNA damage is the double strand break (DSB). A DSB is defined by breaks occurring to both sugar phosphate backbones in close enough proximity that they lead to the separation of the two pieces of the DNA. This type of damage will kill the cell if left unrepaired. It is the most lethal type of DNA damage.
Most living organisms have also developed ways to take advantage of DSBs through their repair systems, primarily as a means of introducing genetic variation. There are two primary DSB repair pathways across life: homologous recombination (HR) and non-homologous end-joining (NHEJ). The focus of this work is NHEJ. NHEJ is known as “error-prone” because it does not use a homologous template and can introduce small addition or deletion mutations during the repair process. This pathway has been extensively studied in eukaryotes and is known as the primary form of DSB repair in mammalian cells, however the prokaryotic NHEJ system was more recently identified and as a result, a void of information surrounds it.
NHEJ is comprised of 3 core steps: DSB recognition and binding, DNA end processing, and ligation. In the eukaryotic version of NHEJ these 3 steps involve a plethora of factors; conversely, in the prokaryotic version, the same functionality is accomplished by just 2 proteins, bacterial Ku and LigD. The focus of this research is Ku: the DNA end-binding protein responsible for identifying the DSB, binding and protecting the DNA end, as well as recruiting LigD to the break. Ku is composed of 2 domains, the first of which is predicted to be highly homologous to eukaryotic Ku’s equivalent domain; this is the core domain which forms a ring-like structure that DNA threads through. The second is completely unique to bacterial Ku, it is the C-terminal domain, which can further be split into 2 sub-domains, the minimal C-terminus, and the extended C-terminus. The sub-domains are defined by their level of conservation across bacterial species, with the minimal C-terminus being highly conserved, while the extended C-terminus is highly variable. Using DNA-binding assays and several mutant constructs which affect the C-terminal domain, I show that this C-terminus is unexpectedly responsible for destabilizing the Ku-DNA interaction. This observation leads me to hypothesize that maintaining a weak interaction with DNA is important for Ku because of the other proteins which need access to the DNA (e.g. replicative helicase). While Ku is bound, it could be capable of blocking regions of DNA, in turn blocking other vital cellular processes like replication. Ku maintaining a lower affinity for DNA should facilitate Ku displacement by other proteins. A tighter binding would restrict Ku’s freedom to move on DNA making it more likely to inhibit other critical pathways. To better understand Ku, I attempted to solve the Ku structure using X-ray crystallography, and was able to achieve crystals of Ku, however diffraction was too limited for a structure. Another way to investigate the validity of my proposed model is to use a biophysical approach with atomic force microscopy (AFM) to visualize protein-DNA complexes. The initial work has established key controls for future Ku-DNA AFM work by imaging and analyzing Ku on its own. Interest in bacterial NHEJ is two-fold from the antimicrobial perspective: NHEJ is a highly mutagenic pathway, so it serves as a proverbial well for differentiation and thus the development of antimicrobial resistance (AMR); NHEJ is very important in bacteria that enter a stationary phase due to their lack of a homologous piece of DNA for HR. Thus, NHEJ inhibition could be useful for slowing bacterial evolution and potentially as a treatment for infections such a Mycobacterium tuberculosis, which is known to lie dormant in host macrophages for long periods of time. To investigate the viability of NHEJ inhibition, I had begun the process of creating ∆ku strains of Pseudomonas aeruginosa to simulate Ku inhibition under various conditions. This Ku project is the focus of the first two chapters, however, during my Master’s degree I participated in 2 other major projects. The third chapter details a bacterial DNA damage tolerance pathway, which similarly is highly mutagenic and poorly characterized: the ImuABC translesion synthesis polymerase complex. The fourth and final chapter details the work for a Journal of Visualized Experiments article meant to highlight the benefits of AFM as a means of studying protein-DNA interactions.

abstract: Thesis

abstract: Master of Science (MSc)


title: Effect of Exposure to Sulphur-containing Heterocyclic Aromatic Compounds on Beta Cell Function

type: Report Thesis

contributor: Medical Sciences (Division of Physiology/Pharmacology)

subject:
Benzo[b]naphtho[2,3d]thiophene
Dibenzothiophene
Beta cell
Cellular stress
Type 2 diabetes

abstract:
Type 2 diabetes (T2D) is characterized by impaired beta cell function. The generation of various types of cellular stresses, including oxidative stress and ER stress, and the induction of cellular senescence can contribute to beta cell dysfunction. Recent studies have demonstrated associations between petrochemical exposure and beta cell dysfunction, particularly through induction of cellular stress. One class of compounds, commonly found in crude oil, are sulphur-containing heterocyclic aromatic compounds (S-HACs). S-HACs have been previously demonstrated to induce cellular stress in mammalian cells. This thesis aims to determine if S-HACs can induce cellular stress in beta cells and, consequently, impair beta cell function, particularly insulin production.
       Rat pancreatic beta cells, INS-1Es, were treated with two commonly occurring S-HACs, BNT(2,3D) and DBT, at doses which reflect non-occupational exposure levels. Upon treatment, various functional assays and qPCR experiments were performed for examining glucose uptake, ROS production, cellular senescence, ER stress and intracellular insulin production. It was observed that both BNT(2,3D) and DBT significantly increased glucose uptake and ROS production in the beta cells and upregulated the mRNA expression of various ER stress markers. In addition, BNT(2,3D) also induced cellular senescence, likely through a p53-independent pathway. This suggests that S-HACs may induce oxidative stress and ER stress in exposed beta cells, and some S-HACs may cause irreversible cell cycle arrest in response to these cellular stresses. However, intracellular insulin content in the INS-1Es was not altered by exposure to either S-HAC, suggesting that S-HACs may not impair insulin production.  Nevertheless, the significant accumulation of ROS in S-HAC-exposed beta cells and the subsequent induction of cellular senescence by some S-HACs may alter other important beta cell functions, including mitochondrial function and insulin secretion, which could lead to the development of T2D; suggesting the potential for S-HACs to be novel beta cell toxicants.

abstract: Thesis

abstract: Master of Science (MSc)


title: Characterization of ACLY Knockdown in Hepatocellular Carcinoma

contributor: Medical Sciences (Cell Biology and Metabolism)

abstract: Lipid is co-opted by cancer cells to meet the metabolic demands of uncontrolled cell proliferation. ATP citrate lyase (ACLY) plays an important role in lipid metabolism by catalyzing the synthesis of acetyl-CoA from mitochondrial citrate thus providing the essential cytosolic precursor for subsequent fatty acid/cholesterol synthesis. Previously, we demonstrated that inhibition of acetyl-CoA carboxylase (ACC) leads to impaired hepatic DNL and reduced incidence of hepatocellular carcinoma (HCC). Given that ACC acts downstream of ACLY, herein, we characterized the role of ACLY as a lipid metabolic regulator of HCC progression. Sourcing from publicly available patient transcriptome datasets, we found that ACLY expression positively correlates with HCC progression and mortality. Inducible knockdown of ACLY expression in Hep3B and SK-Hep1 cells reprograms lipid metabolism through reducing glucose mediated de novo lipogenesis (DNL), inducing fatty acid oxidation and upregulating acetate mediated DNL via the acyl-CoA synthetase 2 (ACSS2) pathway. This is accompanied by decreased cell proliferation, colony formation and invasion. In vivo, orthotopic modeling of human HCC in immune-compromised NOD-Rag1null IL2rgnull (NRG) mice using Hep3B cells results in reduced tumor weight upon ACLY knockdown.

abstract: Thesis

abstract: Master of Science (MSc)


title: Quality in primary care and use of the emergency department among home care patients

contributor:
Costa, Andrew
Health Research Methodology

subject:
Primary care
Home care
Older adults

abstract:
Background
Population aging has led to an increasing number of older adults living in the community with complex care needs such as functional limitations, cognitive impairment, and multimorbidity.  These individuals may need help to remain in their homes, which has created a growing demand for home care. Strategies to manage complex older adults such as home care patients safely in the community typically emphasize robust and integrated primary care. The objective of this thesis is to explore how specific measures of quality in primary care are associated with emergency department use among home care patients in Ontario.
Methods
I conducted four studies on varying subsets of the same population-based retrospective cohort of long-stay home care patients assessed in Ontario from 2014-2016. The first study was a descriptive examination of the entire cohort that characterized their primary care and other health system use.  The second was a case-crossover study among home nursing patients examining whether access to afterhours care modifies the association between home nursing visits and same-day emergency department visits. The third study looked at physician-level provision of primary care home visits and its association with emergency department visits among home care patients with extensive functional impairments. The final study examined and compared associations between continuity of primary and specialty physician care.
Results
Long-stay home care patients in Ontario are high users of both primary care and the emergency department.  Better access to afterhours care reduced the likelihood of an emergency department visit on the same day as a home nursing visit.  Patients with extensive functional impairments whose primary care physician who provided higher levels of home visits had lower rates of emergency department use. Finally, better continuity of both primary and specialty physician care were similarly associated with lower emergency department use.
Conclusion
Better quality primary care integrated with other sectors of the health system is crucial to enabling home care patients to age safety in the community.  Access to care is particularly important and can be improved though enhancing the availability of afterhours care and increasing the provision of home visits for those who have difficulty reaching primary care offices. Improving continuity of specialty physician care should be a health system objective alongside improving continuity of primary care.

abstract: Thesis

abstract: Doctor of Philosophy (PhD)

abstract: Older adults receiving home care are a growing population of individuals with complex care needs and high rates of emergency department use.  This thesis seeks to characterize the primary care use of home care patients in Ontario and examine to what degree better quality of primary care is associated with less use of the emergency department.  My findings indicate that increased access to afterhours primary care, higher levels of primary care home visits, and better continuity of both primary and specialty physician care were associated fewer emergency department visits.  In conjunction with other sectors, primary care plays a central role managing older adults with complex care needs in the community.  Better quality of primary care, particularly advanced access, can help keep older adults safely at home and out of hospitals as they age.


title: THE EXPLORATION OF FAMILY ENGAGEMENT IN SCHOOL-BASED OCCUPATIONAL THERAPY: CONCEPT DEVELOPMENT AND PRACTICE IMPLICATIONS

contributor:
Campbell, Wenonah
Rehabilitation Science

subject:
family engagement
school-based health services
occupational therapy
rehabilitation
qualitative research
family-therapist relationships
collaboration
service delivery models
parents

abstract: This thesis explores the concept of family engagement in education and school-based rehabilitation services and contributes to practice and policy implications.

abstract:
In pediatric occupational therapy, family-centered service is an essential part of practice. Working with families, occupational therapists facilitate capacity-building to enable parents to participate in their child’s occupational therapy services and make informed choices to best support their child. Family engagement can be particularly challenging in the school-based context, but without this engagement, services are at risk of being less meaningful and impactful for children. In this thesis, I explore the unique nature of the educational context, contribute to the conceptual development of ‘family engagement’, provide an in-depth analysis of family engagement in school-based occupational therapy, and generate stakeholder-informed solutions for occupational therapy practice.
The first manuscript depicts a concept analysis that critically analyzes the concept of family engagement as discussed in the education literature. I suggest implications for professionals working with families and children in educational settings, including a proposed definition to contribute to further concept development.
In the second manuscript, I present a qualitative description study exploring occupational therapists’ experiences on the development of family-therapist relationships using the Partnering for Change service delivery model. Through analysis of the data, I identify several factors influencing family-therapist relationships and recommend strategies to improve relationship-building.
In the last study, I present an interpretive description study exploring family engagement in school-based occupational therapy services from the perspectives of both occupational therapists and families. Based on the findings, I recommend service transformation to improve family engagement, and to increase the value of these services for children and their families.
Specific strategies for therapists, organizations, schools, regulatory colleges, and professional practice groups are outlined in this thesis to facilitate family engagement in school-based occupational therapy practice. Ensuring families are able to engage in services may lead to more individualized and impactful services in the school setting.

abstract: Thesis

abstract: Doctor of Philosophy (PhD)

abstract:
Pediatric occupational therapists aim to partner with the family in all aspects of a
child’s service. However, this is difficult for school-based occupational therapists.
Families are not typically present at the school when therapists provide services for
children, making it difficult to build relationships. This thesis explores factors that impact
on how families are able to engage in the school-setting, and on how to provide families
with better support. The first study examines how families engage in children’s education,
and what this means for school-based therapists. The second study explores therapists’
views of what influences family-therapist relationships in a school-based service delivery
model called Partnering for Change. The final study explores family engagement in
school-based occupational therapy from the perspective of both families and therapists.
Findings from all three studies contribute to a better understanding of what family
engagement means in the school-setting, and how to build stronger family-therapist
relationships in school-based occupational therapy services.


title: Selective Laser Melting of Porosity Graded Gyroids for Bone Implant Applications

contributor:
Elbestawi, Mohamed A.
Mechanical Engineering

subject:
Selective Laser Melting
Lattice structures
Biomedical implants
Gyroids
Finite Element Analysis
Mechanical Properties

abstract:
The main aim of this thesis is to investigate the manufacturability of different gyroid
designs using Selective laser melting (SLM) process . This study paves the way for a better
understanding of design aspects, process optimization, and characterization of titanium
alloy (Ti6Al4V) gyroid lattice structures for bone implant applications.
First, A MATLAB® code was developed to create various gyroid designs and understand
the relationship between the implicit equation parameters and the measurable outputs of
gyroid unit cells. A novel gyroid lattice structure is proposed, where the porosity is graded
in a radial direction. Second, gyroid designs were investigated by developing a permissible
design map to help choose the right gyroid parameters for bone implants.
Third, response surface methodology was used to study the process-structure-property
relationship and understand the effect of SLM process parameters on the manufacturability
of Ti6Al4V gyroid lattice structures. Laser power was found to be the most significant
factor affecting the errors in relative density and strut size of gyroid structures. A
volumetric energy density between 85 and 103 J/mm3 induces the least errors in the
gyroid’s relative density.
Fourth, the quasi-static properties of the novel designs were compared to uniform gyroids.
The proposed novel gyroids had the highest compressive strength reaching 160 MPa.
Numerical simulations were studied to give insight into how manufacturing irregularities
can affect the mechanical properties of gyroids. Last, an in-depth defect analysis was
conducted to understand how SLM defects may influence the fatigue properties of different
Ti6Al4V gyroids. Thin struts have less internal defects than thick ones; thus, they show less crack propagation rate and higher normalized fatigue life. These favorable findings
contributed to scientific knowledge of manufacturability of Ti6Al4V porosity graded
gyroids and determined the influence of SLM defects on the mechanical properties of
gyroid designs for bone implants.

abstract: Thesis

abstract: Doctor of Philosophy (PhD)

abstract:
This thesis studies the integration of design aspects, SLM manufacturability, and
mechanical characterization of Ti6Al4V gyroid lattice structures used for bone implants.
A MATLAB® code was developed to design novel porosity graded gyroids, and develop
permissible design map to aid the choice of different gyroid designs for bone implants..
Process maps were also developed to investigate the relationship among laser power, scan
speed, and the errors in the relative density of lattice structures. Moreover, the normalized
fatigue strength of thin struts gyoid was found to be higher than that of thicker
struts.Analytical models and finite element analysis (FEA) models were compared to
experimental results. The variation of the results gives a better understanding of the effect
of manufacturing defects. An improved insight of gyroids manufacturability has been
obtained by integrating the permissible design space with the process-structure-property
relationship, and the defect analysis of porosity graded gyroids.


title: Experimental Determination of the Four Principal Drag Coefficients of Magnetospirillum magneticum AMB-1 cells

contributor:
Fradin, Cécile
Biomedical Engineering

subject:
Magnetotactic bacteria
Principal drag coefficients

abstract:
Magnetotactic bacteria (MTB) possess organelles called magnetosomes which contain magnetite (Fe_3O_4) or greigite (Fe_3S_4) nanocrystals. These particles generate a magnetic moment allowing the use of external magnetic fields to control the cell orientation. MTB use this magnetic moment to reach environments with optimal oxygen concentration, a process called magnetotaxis. There are many possible technological applications for MTB, for example, they have been used as nanorobots to push beads and they can be used to remove heavy metals and radionuclides from waste water. In order to fully understand the motion of these micron-size organisms, which takes place at very low Reynolds number where friction dominates over inertia, we set out to measure their drag coefficients. As a starting point, we used a well-studied species of MTB with a corkscrew shape, Magnetospirillum magneticum AMB-1. Simulations were done to find the best external magnetic field strength at which to observe their diffusion. We then imaged non-motile cells placed in these preferred uniform magnetic fields and used automated image analysis to determine the position and orientation of the cells in each frame. This allowed calculating orientation correlation functions and mean-squared displacements, from which rotational and translational diffusion coefficients were obtained for each individual cell. We observed that the four principal drag coefficients of these cells greatly vary as a function of cell length as predicted for cylindrical or elliptical objects with comparable radius. However, we also detecting a coupling between the rotation around and translation along the long axis of the cell only observed for chiral objects. We were able for the first time to experimentally fully characterize the friction matrix for a micron-size elongated chiral object.

Continuing our work on MTB, to study live cells for long periods of time, we looked to confine them in PDMS nanowells, but found that MTB were not growing well in this environment. We then turned to a device, which incorporated a PDMS microchannel to provide continuous nutrients and a gel membrane to enable cellular growth into a 2D monolayer. Hopefully, this experimental setup combined with time-lapse microscopy can in the future be used to observe cell growth and cell division, and further to determine whether the magnetosome of the mother is passed on equally between daughter cells.

abstract: Thesis

abstract: Master of Applied Science (MASc)


title: The BREAST-Q Utility Module: A New Preference-Based Measure For Breast Cancer

contributor:
Klassen, Anne F.
Rehabilitation Science

abstract: Preference-based measures (PBMs) of health-related quality of life (HRQOL) are used to generate health state utility values (HUVs). HUVs are then used to calculate quality-adjusted life-years (QALYs) for use in cost-effectiveness analyses (CEAs) of healthcare interventions. Although generic PBMs have been commonly used to estimate QALYs in cancer, they omit aspects of HRQOL that matter to women with breast cancer. This thesis begins by setting the stage for the development of a new PBM (Chapter 1). In Chapter 2, the results of a systematic literature review of published HUVs in breast cancer are presented. This review highlighted the heterogeneity in the study population and utility estimation methods in the literature and found that most studies use EQ-5D, a generic PBM, to assess HUVs in breast cancer. No breast cancer-specific PBM exists. Consequently, this thesis delineates the development of the descriptive system of a new breast cancer-specific PBM called the BREAST-Q Utility module. The development of the Utility module adhered to best practice guidelines for the development and validation of patient-reported outcome instruments; the protocol is included in Chapter 3. In Chapter 4, the results of the mixed methods, international study to develop the descriptive system of the Utility module are presented. Semi-structured interviews were conducted with 57 women diagnosed with breast cancer using an interpretive description approach. At the end of the interview, the women were asked to list their top five HRQOL concerns and rate the importance of each item on the BREAST-Q. The data were analyzed and used to develop the preliminary Utility module, which was refined with feedback from women with breast cancer (n=9) and a multidisciplinary group of experts (n=23). In the final chapter, the role of the BREAST-Q Utility module in CEAs of breast cancer interventions is described, and the strengths and limitations of the work are reviewed.

abstract: Thesis

abstract: Doctor of Philosophy (PhD)

abstract: The quality-adjusted life-year (QALY) incorporates the impact of treatments on quantity and quality of life and is the preferred measure of health outcome for economic evaluation. A review of breast cancer literature concluded that generic preference-based measures (PBMs) are commonly used to estimate the “quality” of life (QOL) in QALYs and no breast cancer-specific PBM currently exists. Hence, the objectives of this thesis were to develop and refine a breast cancer-specific PBM. To do this, 57 women with breast cancer from two countries participated in in-depth interviews and rating exercise. The data were analyzed to understand the aspects of QOL that mattered most to women and develop the new PBM, called the BREAST-Q Utility module. The Utility module was refined through feedback from women and experts. Future studies will examine the measurement properties of the module and assign weights to the health states assessed by the module.


title: Regulation of blood glucose by xenobiotic and microbial impactors of RIPK2 signalling

contributor:
Schertzer, Jonathan D.
Medical Sciences

subject: immunometabolism, Type 2 Diabetes, blood glucose, inflammation, NOD signalling

abstract: Obesity is characterized by hyperinsulinemia and chronic inflammation, contributing to insulin resistance and type 2 diabetes (T2D) risk. Pattern recognition receptors (PRRs) of the innate immune system, including Toll-like Receptors (TLRs) and Nod-like Receptors (NLRs), have been identified as propagators of metabolic inflammation. Circulating bacterial components exert distinct effects on inflammation and insulin sensitivity via TLRs and NLRs. Specific types of bacterial peptidoglycan engage NOD1 and NOD2. Activators of NOD1 increase inflammation and insulin resistance, while activators of NOD2 promote immune tolerance and insulin sensitivity. NOD1 and NOD2 use the common downstream adaptor RIPK2 to drive immune responses, but the role of RIPK2 in glucose homeostasis was unknown. RIPK2 is positioned to mediate effects of xenobiotics and microbial components on blood glucose. For example, tyrosine kinase inhibitors (TKIs) are being investigated for diabetes treatment. Improvements in blood glucose control have been observed in diabetic cancer patients receiving TKI therapy but the mechanism underlying these changes remains unclear. Several TKIs inhibit RIPK2. We sought to understand if TKIs that inhibit RIPK2 block inflammatory and metabolic consequences of NOD signalling.  We hypothesized inhibition of inflammation via NOD1-RIPK2 by certain TKIs contributes to lowered blood glucose/improved insulin sensitivity in pre-clinical models of obesity. We showed that RIPK2 was required for acute glycemic consequences of NOD1 and NOD2 activation, and RIPK2-specific TKIs attenuated these glycemic effects. We found TKI-mediated improvements in blood glucose are independent of NOD-RIPK2 signalling during diet-induced obesity. However, RIPK2 mediated the effects of certain TKIs on blood insulin. Finally, we tested if RIPK2 mediated the effects of bacterial components derived from commensal microbiota. We found injection of upper intestinal microbe components lowered blood glucose via NOD2-RIPK2 signalling. These findings demonstrate that modulation of RIPK2 signalling by xenobiotic or microbial factors is an important contributor to blood glucose and insulin homeostasis.

abstract: Thesis

abstract: Doctor of Philosophy (PhD)

abstract: Obesity increases the risk of chronic diseases, including Type 2 Diabetes (T2D). Obesity stops insulin from working properly, leading to the inability to lower blood glucose. Obesity and T2D are linked to chronic, low-grade activation of the immune system. The immune system normally defends the body against microbes by inducing a pro-inflammatory response. Inflammation can also be activated or inhibited by drugs (xenobiotics), and different aspects of inflammation can increase or decrease blood glucose and insulin. A major unanswered question was how certain cancer drugs and bacterial components interact with the immune system to change blood glucose or insulin. This work tested how an innate immune pathway that detects bacterial cell wall components is influenced by cancer drugs and alters blood glucose and insulin in pre-clinical models. This work is targeted at understanding how new prebiotics or existing drugs can be tasked as therapeutic strategies for prediabetes and T2D.


title: Ionoregulation in Daphnia Magna; Mechanisms of Major Ion Toxicity in Adults and Physiology of Ionoregulation in Juveniles

contributor:
O'Donnell, Michael J.
Biology

abstract: Elevations in major ions (sodium (Na+), potassium (K+), calcium (Ca2+) and magnesium (Mg2+) cations paired with chloride (Cl-), sulphate (SO42-) and (bi)carbonate (HCO3-/CO32- ) anions) in freshwater environments through anthropogenic activities cause physiological disturbances in freshwater animals. Because these animals are adapted for active ion uptake to combat passive ion loss to the external environment, increases in ambient major ion concentrations can alter ionoregulation. There has been a concerted research effort into toxicity of major ions and the development of predictive models, which require extensive physiological data, to support the development of comprehensive regulations surrounding pollution by major ions. The branchiopod crustacean, Daphnia magna has been the focus of many of these toxicological studies. The physiological effects of elevated ambient major ion concentrations in adults were investigated. Transepithelial potential (TEP) and hemolymph ion concentrations were altered in animals exposed to elevated ion concentrations approaching previously described LC50 values. These changes in TEP and hemolymph ion concentrations are indicative of physiological disturbance and may be indicators of toxicity. Diffusional gradients and active ion pumps were found to contribute to TEP in D. magna, unlike in freshwater fish. Notable differences between adult and juvenile D. magna in sensitivity to ionic composition of the water and ionoregulation have been described. These differences suggest that both juveniles and adults should be considered in studies focused on monitoring major ion pollution. Ion transport through the nuchal organ in embryo and neonate D. magna was directly measured. Influx of Na+ and efflux of NH4+, H+ and Cl- was observed. K+ flux is dependent on developmental stage. The results from the evaluation of the physiological effects of increased ambient major ions in adults and mechanisms of ion transport in juveniles will aid in establishing environmental regulations for major ions in aquatic ecosystems.

abstract: Thesis

abstract: Master of Science (MSc)


title: Novel Methods for Weather Distortions Mitigation in Images and Videos

contributor:
Shirani, Shahram
Kirubarajan, Thia
Electrical and Computer Engineering

abstract:
Images and videos captured under adverse weather condition usually suffer from bad visual quality. The reduced visual quality can diminish the the human operator comprehension of the image or video content or even it can make the higher-level computer vision applications such as object segmentation or detection, very challenging. This thesis focuses on recovering the images or videos affected by different adverse weather conditions.Airborne videos are extensively used for object detection and target tracking. However, under bad weather conditions, the presence of clouds and haze or even smoke coming from buildings can make the processing of these videos very challenging. Current cloud detection or classification methods only consider a single image. Moreover, the images they use are often captured by satellites or planes at high altitudes with very long ranges to clouds, which can help distinguish cloudy regions from non-cloudy ones. We propose a new approach for cloud and haze detection by exploiting both spatial and temporal information in airborne videos. In this method, several consecutive frames are divided into patches. Then, consecutive patches are collected as patch sets and fed into a deep convolutional neural network. The network is trained to learn the appearance of clouds as well as their motion characteristics. Therefore, instead of relying on single frame patches, the decision on a patch in the current frame is made based on patches from previous and subsequent consecutive frames. This approach, avoids discarding the temporal information about clouds in videos, which may contain important cues for discriminating between cloudy and non-cloudy regions. Experimental results show that using temporal information besides the spatial characteristics of haze and clouds can greatly increase detection accuracy.

The second problem that we address is the removal of haze problem in aerial images or airborne videos. Existing single-image dehazing methods that work on ground-to-ground images, do not perform well on aerial images. Moreover, current dehazing methods are not capable for real-time processing. We propose a new end-to-end aerial image dehazing method using a deep convolutional autoencoder. Using the convolutional autoencoder, the dehazing problem is divided into two parts, namely, encoder, which aims extract important features to dehaze hazy regions and decoder, which aims to reconstruct the dehazed image using the down-sampled image received from the encoder. In this proposed method, we also exploit the superpixels in two different scales to generate synthetic thin cloud data to train our network. Since this network is trained in an end-to-end manner, in the test phase, for each input hazy aerial image, the proposed algorithm outputs a dehazed version without requiring any other information such as transmission map or atmospheric light value. The idea used for generating the synthetic hazy images is further extended for generation of the synthetic hazy frame sequences for airborne video dehazing. The thin clouds in these videos can be distinguished from the other objects on the ground by their two main characteristics: color and motion. Here, we propose a new method for airborne video dehazing by incorporating both the color and motion features of the thin clouds. Using the generated synthetic data, a new end-to-end convolutional autoencoder is trained for dehazing the hazy frames of airborne videos. This network is trained in a way to extract both the temporal and spatial information for the dehazing task. With the proposed dehazing methods, hazy regions are dehazed and objects within hazy regions become more visible while the contrast of non-hazy regions is increased.

The third challenging weather condition that we address is the atmospheric turbulence problem caused by heat. Atmospheric turbulence is one of the causes of quality degradation in long-range imaging and the removal of its bad effects from degraded frame sequences is considered an ill-posed problem. Although there have been numerous attempts to address this problem, the quality of the restored scenes is not promising. In contrast to the previous approaches to address this problem, in this thesis, we propose a data-driven approach. First, an end-to-end deep convolutional autoencoder is trained using natural images and its encoder part is exploited to extract high-level features from all the frames in a sequence that are distorted by atmospheric turbulence. Then, the Binary search algorithm and the unsupervised \textit{k}-means clustering method are jointly exploited to analyze these high-level features to find the best set of frames that can help accurately reconstruct the original high-quality image. After removing the geometric distortion from the selected frames, the saliency map of the average set of the selected frames is calculated and used with the original selected frames to train an end-to-end multi-scale saliency-guided deep convolutional autoencoder network to fuse the registered frames. This networks uses different scales of the input frames and their saliency map for better fusion performance. Specifically, the fusion network learns how to fuse these sets of frames and also exploit information from their saliency map to generate an image with more details of the scene. Finally, this fused image is post-processed to boost the visual quality of the output fused image. The experimental results are conducted on both synthetically and naturally distorted sequences to show the performance of the proposed method compared to the other state-of-the-art methods.

The fourth and the last problem that is addressed in this thesis is the removal of rain streaks and snow particles from single images. Rainy or snowy weather conditions can severely impair the visual quality of single images. Moreover, due to lack of temporal information in single images, removal of these artifacts becomes more challenging. We address both the deraining and desnowing problem in a single framework using a data-driven approach. In this method, the spatial characteristics of rain streaks and snow particles are well investigated and two maps, namely, direction map and intensity map are generated and exploited in the removal process. Using these two maps the type of the distortion is classified using a convolutional neural network (CNN) and this information is forwarded to the removal step. In the removal step, The input image with the two extracted maps and the information about the distortion type are used to train a deep fully convolutional rain/snow removal network (RSRNet). This network is trained in a way that separates the important background scene edges from the rain streaks or snow particles and use the extracted edge map to augment the quality of the output clear image. Moreover, single images usually suffer from atmospheric haze made in the case of heavy rain/snow. Therefore, a simple dehazing method based on the dark channel prior (DCP) algorithm is proposed which uses the edge map extracted in the RSRNet to build a transmission map for the haze removal task. The experimental results on both the real and synthetic single rainy/snowy images demonstrate the superiority of our method compared to the other rain/snow removal methods.

abstract: Dissertation

abstract: Doctor of Philosophy (PhD)


title: EXTENDED TARGET TRACKING METHODS IN MODERN SENSOR APPLICATIONS

contributor:
Kirubarajan, Thiagalingam
Electrical and Computer Engineering

subject:
Sensor
Multi-target tracking
Extended target

abstract:
With the recent advances in sensor technology and resulting sensor resolution, conven- tional point-based target tracking algorithms are becoming insufficient, particularly in application domains such as autonomous vehicles, visual tracking and surveillance using high resolution sensors. This has renewed the interest in extended target (ET) tracking, which aims to track not only the centroid of a target, but also its shape and size over time.
This thesis addresses three of the most challenging problems in the domain of ET tracking applications. The first investigated challenge is the need for an accu- rate shape and centre estimate for the ET object with an arbitrary unknown star- convex shape in presence of non-Gaussian noise. The proposed method is based on a Student’s-t process regression algorithm which is defined in a recursive framework to be applicable for on-line tracking problems.
The second problem tries to relax any constraints, including the star-convex con- straint, that is imposed on the shape of the ET object during the course of estimation by defining a novel Random Polytopes shape descriptor. Also, the proposed solution introduces a method to mitigate the troubles caused as a result of self-occlusion in ET tracking applications which its ignorance may cause catastrophic divergence in the ET state estimate.Finally, a framework for tracking multiple ET objects in the presence of clutter and occlusion is studied and a solution is proposed. The proposed method can estimate the centre and shape of the ET objects in a realistically scenario with the self- and mutual-occlusion challenges being considered. The proposed approach defines a time varying state-dependent probability of detection for each ET that enables the track to prolong even under adverse conditions caused due to mutual-occlusion. Plus, the proposed algorithm uses set-membership uncertainty models to bound the association and target shape uncertainties of occluded ET, to obtain more accurate state and shape estimates of an ET object.
The performance of the proposed methods are quantified on realistically simulated scenarios with self- and mutual-occlusions and their results are compared against existing state-of-the-art methods for ET tracking applications.

abstract: Thesis

abstract: Doctor of Philosophy (PhD)


title: Data Association Algorithms for Multisensor-Multitarget Tracking

contributor:
Kirubarajan, Thia
Electrical and Computer Engineering

abstract:
In this thesis, the data association problem in multisensor-multitarget tracking is explored. Algorithms that improve data association performance by eliminating sensor biases or utilizing available domain knowledge are proposed.

Sensor calibration and data association are two essential steps in multisensor-multitarget tracking systems to correct local measurements using estimated sensor biases and to associate measurements from different sensors. The problem of multitarget localization using time difference of arrival (TDOA) measurements at multiple unsynchronized sensors under measurement origin uncertainty is considered. A novel joint multidimensional association algorithm for multisensor synchronization is proposed. This algorithm is extended to a multiframe case to ensure the observability of unknown parameters consisting of target positions and sensor clock offsets. To improve the proposed algorithm's efficiency, a gating method and a multidimensional plus sequential two-dimensional association approach are developed. The Cram\'er-Rao lower bound for this problem is derived as a performance benchmark. Numerical results show that the proposed algorithm outperforms the algorithms that address sensor calibration and data association separately in terms of correct association rate and target position and sensor clock bias estimation accuracies.

Exploring and exploiting domain knowledge can improve tracking performance, especially in the context of on-road target tracking. Due to traffic rules and limited lane capacity, on-road targets tend to move in an orderly manner along the centerline of each lane of the roads except for occasional lane changes. A novel sequence-aided 2D assignment (SA-2DA) algorithm, which integrates the target position sequence information into data association by utilizing this information in evaluating the probability of association hypothesis, is proposed. The sequence information is further exploited within the joint probabilistic data association (JPDA) framework, making it suitable for high false alarm rate or high association ambiguity scenarios, and within the tracking framework consisting of the interacting multiple model (IMM) estimator and the JPDA algorithm, making it suitable for tracking maneuvering targets. The uncertainty in target position sequence due to target lane-changing behavior is addressed by two strategies: a) The multiple-hypothesis method combined with the modeling of target lane-changing behavior as a homogeneous Markov chain; b) The track segment association algorithm. The posterior Cram\'er-Rao lower bound is derived for tracking multitarget along a multi-lane road. Numerical results show that the proposed algorithms (i.e., SA-2DA, SA-JPDA and SA-IMMJPDA) achieve better track accuracy and consistency than the existing multitarget tracking algorithms (i.e., standard 2DA, JPDA and IMMJPDA)) that do not make use of target position sequence information.

abstract: Thesis

abstract: Doctor of Philosophy (PhD)


title: Pre-Transformation Phenomena in the Intermetallic Compound TiNi

contributor:
Purdy, G. R.
Metallurgical Engineering

subject:
pre-transformation
phenomena
intermetallic compound

abstract: Prior work in this system has indicated that, under favourable conditions, the formation of a martensitic transformation product on cooling may be preceded by a second-order cubic-rhombohedral transformation. In the present investigation, thin film electron microscopy and diffraction have been employed to study the pre-transformation phenomena in the temperature range 20-300°C. The results are interpreted in terms of localized thermal diffuse scattering, resulting from incipient mechanical instability. A model for the cubic-rhombohedral transformation of the rhombohedral phase suggest a moderate degree of co-operation between adjacent domains. Additional data is provided in the form of volumetric and x-ray intensity measurements.

abstract: Thesis

abstract: Master of Engineering (ME)


title: Phase Transformations in the Intermetallic Compound TiNi

contributor:
Purdy, G. R.
Metallurgy

subject:
phase transformation
intermetallic compound
TiNi

abstract:
Survey work has resolved certain reported anomalies in this system.
In particular, TiNi was found to undergo two displacive phase transformations at temperatures near room temperature. Below 50°C the pseudo body-centered cubic compound undergoes a gradual distortion in an unusual second order phase transformation producing the "transition phase”, the existence of which is terminated by a typical martensitic burst transformation at 20°C which produces the "martensitic phase". The crystal structures of the parent phase and transformation products, and the transformation characteristics have been studied with X-ray and electron diffraction, electron microscopy, electrical resistance and density measurements.

abstract: Thesis

abstract: Master of Science (MS)


title: SUBJECTIVE AND OBJECTIVE COGNITIVE IMPAIRMENT IN BIPOLAR DISORDER

title: Subjective and Objective Cognitive Impairment in Bipolar Disorder Relative to Similar Neuropsychological Disorders

contributor:
Kapczinski, Flavio
Neuroscience

subject:
Bipolar Disorder
Cognitive Impairment
MCI
Dementia
MDD
Subjective Complaints

abstract: This thesis presents research investigating objectively and subjectively examined cognitive impairment in Bipolar Disorder (BD) in comparison to disorders with similar cognitive symptomatologies. First, a systematic review and meta-analyses compared the cognitive performance between BD and Mild Cognitive Impairment (MCI) or dementia. Studies included in this review and meta-analyses assessed cognitive performances using multiple objective cognitive assessments. Results from these meta-analyses found greater impairment in BD relative to MCI on motor initiative abilities. Additionally, there were similarities in cognitive deficits on delayed memory recall and visuoconstructional abilities between BD and MCI. For the comparison between BD and dementia, we analyzed the findings of studies comparing BD across different mood states with different types of dementia, where BD in acute mood episode demonstrated greater deficits in attention, working memory, verbal memory, and executive function than behavioral variant frontotemporal dementia (bvFTD). In contrast, overall cognitive functioning and verbal fluency was more impaired in Alzheimer’s disease (AD) in comparison to BD during euthymia. Next, we shifted the focus on examining subjective cognitive complaints in BD relative to Major Depressive Disorder (MDD). Our study is unique from previous literature with the same aim considering that it only involved patients recently diagnosed with BD, and subjective complaints were assessed with the Cognitive Complaints in Bipolar Disorder Rating Assessment (COBRA), an instrument specific to cognitive complaints detected in BD. The findings demonstrate higher subjective cognitive complaints in euthymic BD in comparison to euthymic MDD, suggesting greater self-perceived difficulties in BD, even in the beginning of the illness. Taken together, findings from the studies presented in this thesis highlight the importance of early detection and intervention of cognitive impairments in BD, with the aim of enhancing cognitive abilities, and prevention of further cognitive degradation with the progression of the disorder

abstract: Thesis

abstract: Master of Science (MSc)


title: Galaxy Clusters and Their Role in Galaxy Evolution

contributor:
Parker, Laura
Physics and Astronomy

abstract: Galaxy clusters are the most-massive, collapsed, galaxy environments in the Universe, and they exist along a spectrum of dynamical state and virialization.  Such extreme environments extend the range of physical processes that we can study relevant to galaxy evolution.  Therefore, galaxy clusters are important laboratories to advance our understanding of galaxy evolution.  With optical and X-ray observations, along with dark matter only simulations, we test methods for classifying galaxy cluster dynamical state.  We show that the shape of the member-galaxy redshift distribution, for a given cluster, is a useful proxy for cluster dynamical state which correlates with cluster X-ray morphology.  Applying these classifications to simulated clusters, we show that unrelaxed clusters have experienced recent major mergers as well as active accretion of new galaxies.  We also present evidence for enhanced star formation in galaxies within unrelaxed clusters, compared to counterparts in relaxed systems.  This trend is likely connected to the shorter times-since-infall for galaxies in unrelaxed clusters.  Interactions between galaxies and the intracluster medium (ICM) play an important role in quenching galaxy star formation.  With a sample of SDSS clusters, and archival X-ray observations from the Chandra observatory, we investigate galaxy star formation as a function of ICM density.  For all masses, the quenched fraction of galaxies increases with ICM density.  For low-mass galaxies, there is evidence for enhanced quenching in the densest cluster regions, consistent with ram pressure stripping.  To further probe ram pressure in clusters, we use high-resolution imaging to search for galaxies undergoing stripping in the Coma cluster.  We present ~40 ram pressure stripping candidates, which are consistent with being stripped on their first infall toward the Coma centre.  These galaxies show enhanced star formation rates, suggesting that gas compression from ram pressure may be catalyzing star formation.  Environmentally-driven quenching in galaxy clusters is a function of both, both how long a galaxy has been part of a cluster, and how efficiently cluster processes quench galaxies.  The former is informed by accurate characterization of cluster dynamical state, and the latter by detailed studies of quenching mechanisms as a function of galaxy mass, both of which are focal points of this work.

abstract: Thesis

abstract: Doctor of Philosophy (PhD)


title: SURGICAL CLOSURE OF PELVIC PRESSURE INJURIES IN SCI ADULTS

title: SURGICAL CLOSURE OF PELVIC PRESSURE INJURIES IN SPINAL CORD INJURED ADULTS: CASE IDENTIFICATION, COSTS, HEALTH CARE UTILIZATION AND RISK FACTORS FOR SURGICAL COMPLICATIONS

contributor:
Thabane, Lehana
Browne, Gina
Campbell, Karen E.
Birch, Stephen
Nursing

subject: spinal cord injury, pressure injury, surgical reconstruction, cost, outcomes

abstract:
Impaired wound healing in SCI patients contributes to the progression in severity of PIs. Best practice guidelines suggest that surgical flap reconstruction is an option for chronic stage 4 PIs that have failed to heal with more conservative measures, but little is known about the epidemiology of surgically reconstructed PIs in SCI patients. Rates of surgical wound complications are high, and cost of management is extensive. Accordingly, this study aims to establish a systematic approach for identifying SCI patients with surgically reconstructed PIs, to facilitate study of predictors of sustained wound closure, quantify costs of surgical reconstruction, and evaluate efficiency of treatment and recovery options.
To address gaps in the literature, this study’s objectives were: (1) estimate surgical reconstruction hospital costs for stage 4 PIs in SCI patients and characterize the relationship of demographic, socioeconomic and lifestyle factors to cost at discharge, (2) explore a standardized method of identifying these cases in large databases, (3) identify and validate risk factors for complications at discharge from wound care follow-up, and (4) identify long-term cost and health care utilization of persons with SCI who have undergone surgical flap closure.
	It proved difficult to identify our own cohort of patients using administrative codes applied, making population-based study using administrative data less than ideal.  Factors associated with open incision at three-to-six weeks post-index surgery included number of nursing visits in the previous year, and revision surgery within the six-week follow-up period. The cost of persons with SCI and PI was high one year prior to surgery (look-back) and almost double in the first year look-back. However, significant cost and health care utilization was demonstrated in Year 2 and 3 post-index surgery.
	Further prospective studies exploring models of health care delivery and addressing some of modifiable risk factors may improve cost-effectiveness and outcomes.

abstract: Thesis

abstract: Doctor of Philosophy (PhD)

abstract: Pressure ulcers, also known as pressure injuries (PI) or bedsores, are a common secondary complication in persons with spinal cord injury (SCI). While surgical closure is an option offered to patients, little is known about the long-term outcomes, including cost and use of health care services following the surgery. Risk factors for complications following surgery are known from a physical/co-morbidity/technique perspective, but environmental and behavioural factors have not been included these studies, and the use of health care administrative databases to accurately identify these patients for research has not been studied. A historical cohort study was conducted at one tertiary care centre in Toronto, Canada to identify known cases of SCI and PI reconstruction. Hospital codes were recorded in an algorithm used to evaluate the accuracy in identifying the known cases in the database. Health care usage and costs were also recorded, and risk factors for complications were also evaluated.


title: NUMERICAL STUDY OF ANISOTROPY AND DUCTILITY ENHANCEMENT IN SHEET METALS

contributor:
Wu, Peidong
Mechanical Engineering

abstract:
GTN is analyzed and extended to be suitable for anisotropic matrix materials on the basis of Hill’s quadratic anisotropic yield theory. An effective coefficient is defined in the extension, and it replaces Hill’s constants to provide the elastic–plastic behavior of metals. In this model, three dimensional (3D) and plane stress elements are considered, containing ellipsoidal and spherical microvoids in matrix materials. The effect of each case is studied and compared with the stress–strain curve of a typical Al alloy.
Superimposed hydrostatic pressure delays the growth and coalescence of microvoids. Thus, bendability is significantly enhanced by superimposing hydrostatic pressure. The effect of hydrostatic pressure on tensile test simulation is determined and compared with that obtained under bending. This test is simulated under the plane strain state. Sheet metals have higher deformation under bending than under tension. The sensitivity of ductile fracture parameters in the GTN model to bendability is analyzed and used as the basis for exploring the bending response of sheet metals given by this model.
Cladding sheet metals slows down the development of stress triaxiality, which has a significant effect on the fracture of sheet metals. Consequently, the growth and coalescence of microvoids are delayed, and this condition leads to high bendability and increases fracture strain. A transition zone in the location of failure initiation is observed. This transition zone changes with increasing cladding thickness ratio (Γ). Fracture initiation changes from the core material close to the clad–core interface to the clad material on the outer surface of the specimen at increased Γ. The effect of mandrel span length as well as stress–strain curves for clad materials on bendability is investigated and used as the basis for understanding changes in transition zones.

abstract: Thesis

abstract: Doctor of Philosophy (PhD)


title: Brain Inspired Intelligence for Engineering and Healthcare Applications

contributor:
Kumar, Shiva
Deen, Jamal
Electrical and Computer Engineering

abstract:
The cyber processing layer of smart systems based on a cognitive dynamic system (CDS) can be a good solution for better decision making and situation understanding in non-Gaussian and nonlinear environments (NGNLEs). The NGNLE situation understanding means deciding between certain known situations in NGNLE to understand the current state condition. Here, we report on a cognitive decision-making (CDM) system inspired by the human brain decision-making using prediction outcome of actions using a virtual NGNLE. The simple low-complexity algorithmic design of the proposed CDM system can make it suitable for real-time applications. The proposed system can be extended as a general software-based platform for brain-inspired decision making in smart systems in the presence of nonlinearity and non-Gaussian characteristics. Therefore, it can easily upgrade conventional systems to a smart one for autonomic CDM applications. Towards these objectives, CDS is applied to long-haul fiber optic link and a smart e-Health system as two examples of NGNLE.
In first case study, brain-inspired intelligence using the CDS concept is proposed to control the quality-of-service (QoS) over a long-haul fiber-optic link that is nonlinear and with non-Gaussian channel noise. Digital techniques such as digital-back-propagation (DBP) assume that the fiber optic link parameters such as loss, dispersion, and nonlinear coefficients, are known at the receiver. However, the proposed CDSs does not need to know about the fiber optic link physical parameters, and it can improve the bit error rate (BER) or enhance the data rate based on information extracted from the fiber optic link. The information extraction (Bayesian statistical modeling) using intelligent perception processing on the received data, or using the previously extracted models in the model library, is carried out to estimate the transmitted data in the receiver. Then, the BER is sent to the executive through the main feedback channel and the executive produces actions on the physical system/signal or internal commands for adaptive modeling configurations to ensure that the BER is continuously under the pre-defined forward-error-correction (FEC) threshold. Therefore, the proposed CDS is an intelligent and adaptive system that can mitigate disturbance in the fiber optic link (especially in an optical network) using prediction in the perceptor and/or doing proper actions in the executive based on BER and the internal reward. Also, the earlier versions of CDS can achieve pre-defined goal faster using prediction outcome of actions in the executive. CDS was implemented for nonlinear fiber optic systems based on orthogonal frequency division multiplexing (OFDM) to show how the proposed CDS can bring noticeable improvement in the system’s performance.
In second case study, CDS is applied for the autonomic computing layer of smart e-Health system for automatic diagnostic test and automatic screening process. In recent years, there has been a growing interest in smart e-Health systems to improve people’s quality of life by enhancing healthcare accessibility and reducing healthcare costs. Continuous monitoring of health through a smart e-Health system may enable automatic diagnosis of diseases like Arrhythmia at its early onset that otherwise may become fatal if not detected on time. Towards this objective, we start from understanding the health situation by diagnosing healthy and unhealthy persons for automatic diagnostic test. For this, a decision-making system is developed that is inspired by medical doctors (MDs) decision-making processes. Our system is based on a CDS for CDM and it can create a decision tree automatically. Then, a CDS-based framework is developed for the smart e-Health system to realize an automatic screening process in the presence of a defective dataset. A defective dataset may have poor labeling and/or lack enough training patterns. To mitigate the adverse effect of such a defective dataset, we developed a decision-making system that is inspired by the decision-making processes in humans in case of conflict-of-opinions (CoO). The proposed CDS algorithm can thereby be incorporated in the autonomic computing layer of a smart-e-Health-home platform to achieve a pre-defined degree of screening accuracy in the presence of a defective dataset. The proposed platforms for automatic diagnostic test and automatic screening process can be extended for more healthcare applications such as disease class diagnosis, prevention, treatment or monitoring healing. As a result, the proposed CDS algorithms can be an example of the initial steps for designing the autonomic computing layer of a smart e-Health home platform.

abstract: Thesis

abstract: Doctor of Philosophy (PhD)


title: Study of Sum of Complex Exponential Signals

contributor:
Zhang, Jiankang
Electrical and Computer Engineering

abstract: This thesis focuses mainly on a finite sum of complex exponential signals. This kind of signal model usually captures a variety of applications involving damped signals such as magnetic resonance spectroscopy, gravitational wave bursts, synchronized neuronal hyppocampal rhythms, financial modelling and the acoustic localization of underground oil field. Each coefficient and complex exponential function in the sum signal can be uniquely characterized by the z-transform of the sampling signal of the continuous-time sum signal as its poles and residues. We study the estimation of all these parameters using Pade approximation theory. The Pade approximation theory deals primarily with the optimally asymptotic approximation of a rational fraction with each of the denominator and numerator having an allowable degree to the z- transform of a given discrete-time signal. The poles and the residues of the rational fraction normally provide relatively precise information on the poles and the residues of the original z-transform. Particularly for the sum of complex exponential signals, its poles and the residues can be completely characterized by its Pade approximation rational fraction with a proper degree constraint. Hence, the Pade approximation theory becomes a very strong mathematical tool for studying such sum of complex exponential signals. We make two kinds of contributions: (a) When the residues are all equal to each other, we derive a closed-form formula for determining the Pade approximation rational fraction as well as for predicting the future data points. (b) A co-prime sampling scheme is proposed, with a closed-form algorithm being provided for efficiently determining the original poles and residues using elementary diophantine theory.

abstract: Thesis

abstract: Master of Applied Science (MASc)


title: Development of a Versatile Platform for Combination Targeted Radionuclide and Immune Cell Recruitment Therapies using Bio-orthogonal Chemistry

contributor:
Valliant, John
Chemistry

subject: Cancer Immunotherapy Radiotherapy

abstract:
This thesis describes a general platform for the synthesis of radiolabelled antibody recruiting small molecules (R-ARMs) for combination radio and immune recruitment therapies. The novel trifunctional ARM was synthesized and radiolabelled with beta (lutetium-177) and alpha (actinium-225) emitting radionuclides in high yield. Biodistribution of the lutetium-ARM revealed rapid renal clearance and minimal uptake in non-target tissues with all organs and tissues containing less than 0.3 %ID/g by 24 hours post-injection. Having determined the pharmacokinetic properties of the ligand, a biodistribution study was performed to determine the targeting potential of the platform. Through the use of a validated bone targeted bisphosphonate, uptake in the arm and leg bones was achieved. Flow cytometry studies successfully demonstrated ARM and antibody dependent immune cell recruitment. Based on the promising results of the ARM in vitro and in vivo, the next step was to perform therapy studies.
In order to validate the novel R-ARM, an intratumoral (i.t.) strategy was developed through the preparation of a TCO-bovine serum albumin (BSA) derivative. This new chemical entity was used in both an aggregated and non-aggregated form to retain the R-ARM in the tumour after i.t. administration. Biodistribution showed high retention of the aggregated and non-aggregated BSA out to 120 hours with 167 ± 94 and 81 ± 32 %ID/g respectively remaining in the tumour. An autoradiography study revealed the after i.t. administration the aggregated material was localized in specific regions within the tumour compared to the non-aggregated material which diffused throughout. The aggregated material was used in a single and multi-dosing radiotherapy study in which the latter induced a statistically significant survival advantage compared to the control. One additional multi-dosing study was performed with the non-
aggregated material which resulted in the largest survival advantage to date. Intratumoral administration of TCO-BSA linked to the trifunctional tetrazine showed promising radiotherapy results and future work on dose optimization with lutetium and actinium is required prior to the combination R-ARM therapy.
In parallel, the efficacy of the unlabelled ARM linked to TCO-BSA was interrogated in preclinical models. The compound was administered i.t. three times per week in a breast cancer tumour model, and response to therapy monitored. The immunized group showed no survival advantage compared to the control group comprised of naïve animals. Biodistribution studies were performed to determine if TCO-BSA was accessible to the bloodstream following i.t. administration in both the aggregated and non-aggregated forms. Saline, aggregated or non-aggregated TCO-BSA were administered i.t. followed by the R-ARM. The results showed very low uptake in the tumour for all three groups, with minimal change in distribution from that of the native R-ARM. This suggests that after i.t. administration, the TCO-BSA was not available to molecules in the bloodstream or the concentration was insufficient to promote in vivo coupling. Further work on this component of the platform is needed before further ARM studies are performed.

abstract: Thesis

abstract: Doctor of Science  (PhD)


title: Optical Waveguide Interconnects in Optoelectronic Matrix Switches

contributor:
Jessop, Paul
Engineering Physics

subject:
optical waveguide
optoelectronic matric switch

abstract: The speed and simplicity of the metal-semiconductor-metal (MSM) detector has made it a prime candidate for use in integrated optoelectronic circuits. While in most applications the optical input is coupled in through the top surface of the device, it is also possible to distribute the optical signal by means of transparent waveguides that are located below the absorbing detector layer. By controlling the degree of coupling between the waveguide and detector layers the detectors can be made to act as optical taps. The optical signal can thus be shared among a series of detectors as required in optoelectronic switching applications. We have made a series of simple ridge waveguides, each with a number of MSM structures designed for the characterization of absorption, responsivity and frequency response. A 4x4 optoelectronic switch was also fabricated and analyzed. We show that balancing the switch is accomplished by tailoring the absorption coefficient in the detector region so that all detectors absorb equal amounts of optical power.

abstract: Thesis

abstract: Master of Engineering (ME)


title: Investigating the microbial and immune mechanisms of depressive-like behaviour in a humanized mouse model of MDD

contributor:
Bercik, Premysl
Medical Sciences

subject:
intestinal microbiota
depression
gut-brain axis
inflammation
microglia
fecal microbiota transplant
anxiety

abstract: Major depressive disorder (MDD) is a highly heterogeneous disorder, with some patients displaying immune activation and altered intestinal microbiota composition when compared to healthy controls. In recent years, the transfer of fecal microbiota pooled from several MDD patients has been used to model depression in recipient rodents. However, we have previously observed the induction of donor-specific phenotypes in mice receiving microbiota from individual irritable bowel syndrome and generalized anxiety disorder patients. Therefore, we assessed the efficacy of fecal microbiota transplant (FMT) using individual versus pooled MDD patient microbiota to induce depressive-like behaviour in recipient rodents. We observed that pooling microbiota from several patients abrogated microbial features unique to individual donors. Mice that received pooled microbiota displayed different behavioural and immune phenotypes when compared to mice that received individual patient microbiota. Two individual MDD microbiota donors, patients MDD1 and MDD5, altered the behaviour of recipient mice when compared to controls. We identified several microbial species that may underlie the anxiety- and depressive-like behaviours observed in MDD1 and MDD5 mice. Additionally, altered expression of neural and immune genes was observed along the gut-brain axis of mice colonized with MDD1 microbiota. As microglia activation may play a role in our model, we developed a protocol for the isolation and phenotyping of adult mouse microglia that will facilitate future research efforts. Overall, our results demonstrate the heterogeneity of the microbial underpinnings of MDD and support the use of individual patient microbiota in future FMT experiments.

abstract: Thesis

abstract: Master of Science (MSc)


title: Exploring Associations Between a Maternal Nutrition+Exercise Intervention in Pregnancy and Infant Growth and Body Composition

contributor:
Atkinson, Stephanie
Medical Sciences

subject:
nutrition
exercise
pregnancy
body composition
pediatrics
diet
intervention

abstract:
Background: Pregnancy lifestyle interventions may effectively mediate gestational weight gain and adverse pregnancy outcomes. Whether maternal diet and exercise in pregnancy also benefits offspring body size and composition in infancy is not widely investigated. Further, adherence to interventions in longitudinal studies is often overlooked.

Objectives: 1) Determine the effects of a nutrition+exercise intervention compared with standard prenatal care throughout pregnancy on infant anthropometry and body composition 2) Compare the dietary practices between intervention and control groups 3) Create an algorithm to assess intervention adherence

Study Design: Maternal diet and physical activity were collected from a subset of women at 12-17, 26-28, 36-38 weeks gestation while enrolled in the Be Healthy in Pregnancy randomized controlled trial. Infant birth size was obtained from hospital records, and anthropometry and body composition outcomes were measured at six months postpartum. Percentile values for anthropometric measures were obtained using population reference growth standards. Diet quality was assessed through food frequency questionnaire, and a novel adherence algorithm was created using step counts from an accelerometer and three-day diet record.

Results: For 183 participants of mean age 31 ± 4 years and BMI 25.3 ± 4.7 kg/m2 , infant anthropometry and body composition at birth and six months were similar between intervention and control groups with the exception that intervention infants had significantly higher birth length and a higher proportion categorized above the 97th percentile for reference length measures. In the analysis of healthy dietary practices (N=111) intervention and control participants had similar scores at baseline but only intervention participants improved and maintained their dietary practice scores in mid and late pregnancy. Application of the adherence score incorporating diet and step counts demonstrated increased adherence to the intervention in mid-pregnancy in intervention participants, but this level of adherence was not maintained through the end of pregnancy.

Conclusion: In a healthy pregnant cohort, a lifestyle intervention did not significantly impact infant anthropometry or body composition and most measures were within appropriate reference ranges for age and sex. The novel algorithm to measure intervention adherence demonstrated inconsistent compliance across pregnancy in intervention participants, potentially contributing to null findings.

abstract: Thesis

abstract: Master of Science (MSc)

abstract: Excessive weight gain in pregnancy can impact fetal and child growth and health. Diet and exercise modifications during pregnancy may improve weight gain but influence on infant outcomes is unknown. It is important to determine if women actually follow such guidance. Our study showed that infants of women randomized to a diet and exercise program compared to usual prenatal care had similar body size and body composition at birth (except length) and age six months. Women in both treatment groups had similar healthy dietary practices in early pregnancy, but with dietary counselling intervention women improved their diet. However, a unique scoring system developed to measure adherence to diet and exercise revealed that it was difficult for women to follow the guidance provided. Our study provides insights into the association of diet in pregnancy and infant growth in a Canadian population, and a novel approach to measuring ability to follow guidance.


title: Machine Learning Based Failure Detection in Data Centers

contributor:
Narimani, Mehdi
Electrical and Computer Engineering

subject: predictive maintenance, artificial intelligence, machine learning, supervised learning, unsupervised learning, micro data center, anomaly detection, data acquisition, support vector machine (SVM), One-Class SVM

abstract: This work proposes a new approach to fast detection of abnormal behaviour of cooling, IT, and power distribution systems in micro data centers based on machine learning techniques. Conventional protection of micro data centers focuses on monitoring individual parameters such as temperature at different locations and when these parameters reach certain high values, then an alarm will be triggered. This research employs machine learning techniques to extract normal and abnormal behaviour of the cooling and IT systems. Developed data acquisition system together with unsupervised learning methods quickly learns the physical dynamics of normal operation and can detect deviations from such behaviours. This provides an efficient way for not only producing health index for the micro data center, but also a rich label logging system that will be used for the supervised learning methods. The effectiveness of the proposed detection technique is evaluated on an micro data center placed at Computing Infrastructure Research Center (CIRC) in McMaster Innovation Park (MIP), McMaster University.

abstract: Thesis

abstract: Master of Science (MSc)


title: 18/12 Switched Reluctance Motor Design For A Mild-Hybrid Electric Powertrain Application

contributor:
Emadi, Ali
Bilgin, Berker
Electrical Engineering

subject:
Motor Design
Switched Reluctance Machine
Mild-Hybrid Electric Vehicle
Electromagnetic Design

abstract: A novel belt alternator starter (BAS) is proposed to replace the starter and alternator in a hybrid electric vehicle. The BAS designed utilizes an 18 rotor, 12 stator pole switched reluctance machine (SRM) configuration, with concentrated bar windings wound in parallel. Through iteration of various machine geometry parameters, the SRM can meet the torque and speeds demands over standardized drive cycles described by the US Environmental Protection Agency.

abstract:
With the depletion of oil wells and changing global climate, a large emphasis is placed on the research, development and adoption of electric vehicles (EVs) to replace vehicles driven by internal combustion engines (ICEs). However the global supply chain is still not ready for such a large demand in EVs; therefore hybrid electric vehicles (HEVs) aim to ease the transition between ICEs and EVs.

The research outlined in this thesis investigates the design of a 18 stator, 12 rotor pole (18/12) configuration switched reluctance machine (SRM) utilizing novel technologies for use as a belt alternator starter (BAS) motor in an HEV. Background research on current trends and technologies for electric motors and vehicles is performed before evaluating initial geometry for the motor core to be designed. Initial geometry is brought into JMAG to develop an electromagnetic model and begin the geometry optimization. The 18/12 design process highlights how changes to motor parameters from a geometry and winding standpoint will affect motor performance. After the motor core geometry yields suitable performance, a mechanical design is proposed encompassing the rotary assembly, cooling as well as solutions for mounting.

abstract: Thesis

abstract: Master of Applied Science (MASc)

abstract: Hybrid electric vehicles are becoming more prevalent as stricter restrictions are placed on fuel economy and emissions targets. Full electric vehicles on the other hand have not yet become the standard form of transportation due to the limits on range and infrastructure. Because of this, automotive manufacturers are researching and developing new methods in which they can meet these restrictions and limitations. Switched reluctance motors aim to be a solution to meet these demands while forging a new path by alleviating the demand on rare earth metals for the motor core. In this thesis, a design is proposed to fill an existing role in vehicle electrification best suited for a belted alternator starter.


title: The Effect of Cosmic Web Filaments on Quenching in Galaxy Clusters

contributor:
Wadsley, James
Welker, Charlotte
Physics and Astronomy

subject:
galaxy
quenching
astrophysics
cosmology
cosmic web
filament

abstract:
Environment plays an important role in the evolution of galaxies. In particular, denser
environments, such as galaxy clusters and large-scale field filaments of the cosmic web
have been found to reduce star formation in galaxies. The intersection of these environments
provides an interesting regime of study. We investigate how cosmic filaments
impact the quenching of galaxies within one virial radius of 324 simulated clusters. We
use hydrodynamic runs from The Three Hundred Project along with the cosmic web
extractor DisPerSE to track filaments and the structure finder VELOCIraptor to identify
halos hosting galaxies. Limited by the resolution of the simulation, we examine star
formation indirectly by way of galaxy colour and cold gas fraction. We find that cluster
galaxies residing closer to filaments tend to be star-forming, bluer, and contain more
cold gas than their counterparts further away from filaments. This is in stark contrast
with galaxies residing outside of clusters, where galaxies close to filaments show clear
signs of density related pre-processing. Careful examination of flows around and into
cluster galaxies strongly suggests that the colder, dynamically coherent hydrodynamic
streams along intra-cluster filaments partially shield galaxies close to them from strangulation
by the hot, dense intra-cluster medium. These streams, in addition to the reduced
density contrast of intra-cluster filaments with the intra-cluster medium, also limit the
ram pressure stripping experienced by cluster galaxies. We further examine stripping in
the context of gas disturbances in phase space to create a classification for wet and dry
galaxies.

abstract: Thesis

abstract: Master of Science (MSc)


title: THE EFFECTS OF WASTEWATER TREATMENT PLANT EFFLUENT ON THE GUT MICROBIOME OF AQUATIC AND RIPARIAN INVERTEBRATES IN THE GRAND RIVER, ON

contributor:
Kidd, Karen
Biology

subject:
microbiome
macroinvertebrates
wastewater treatment
spider
gut microbiome
mussel
aquatic insects
Grand River
effluent
wastewater treatment plant
bacteria

abstract: The composition of gut microbes affects host weight, immune function, and disease status, and is sensitive to diet, environment, and pharmaceutical exposure. The gut microbiome modulates the toxicity and bioavailability of chemical stressors, however the effects of chemicals on the gut microbiome of aquatic biota are largely unknown. The Waterloo and Kitchener wastewater treatment plants (WWTPs) release effluents containing antibiotics, pharmaceuticals, and other contaminants into the Grand River (ON) that may negatively affect the gut microbiome of downstream organisms. In this study done in Fall 2018, I collected freshwater mussels (Lasmigona costata), several species of insect larvae, and riparian spiders (Tetragnathidae) from sites upstream and downstream of these WWTPs. The gut microbiome was analyzed following the extraction, PCR amplification, and sequencing of bacterial DNA using the V3-V4 hypervariable regions of the 16S rRNA genetic barcode. Changes in the relative abundance of major gut microbiome phyla were observed in all targeted aquatic organisms downstream of WWTPs except Hydropsychidae. Shannon alpha diversity, a measure of bacterial abundance and evenness, differed significantly among sites for mussels (one-way ANOVA:  F=7.894, p=0.001), spiders (F=4.788, p=0.01), Perlidae (F=3.1, p=0.0056), Hydropsychidae (F=3.674, p=0.0014), and Heptageniidae (F=2.715, p=0.0143), but not for Baetidae and Ephemerellidae. In sites downstream of the Waterloo WWTP, alpha diversity decreased in spiders, while in sites downstream of the Kitchener WWTP diversity decreased in mussels and Perlidae, while increasing for spiders. Bray-Curtis beta diversity, a measure of dissimilarity between bacterial communities, was significantly dissimilar among sites in all invertebrate taxa (Permanova: p<0.02). Upstream sites differed from downstream Waterloo sites in spiders, Perlidae, and Hydropsychidae (Adonis pairwise: p<0.05), while upstream mussels, spiders, Perlidae, and Hydropsychidae differed from downstream Kitchener sites (p<0.05). Additionally, effluent-derived bacteria were found in the microbiomes of aquatic invertebrates downstream of the WWTPs and not upstream. Taxa was also a significant driver of bacterial composition and diversity in invertebrates. These results indicate that the gut microbiome of downstream organisms differed from the bacterial composition observed in the same invertebrate taxa upstream of the WWTPs, potentially leading to altered host health. This adds to our understanding of how chemical stressors impact the gut microbiome of aquatic and riparian biota; however, future studies are needed to investigate linkages between the gut microbiome and health of these species.

abstract: Thesis

abstract: Master of Science (MSc)


title: Risk Prediction in Forensic Psychiatry: A Path Forward

subject:
Artificial Intelligence
Crime Prediction
Machine Learning
Precision Psychiatry
Forensics

abstract:
Background: Actuarial risk estimates are considered the gold-standard way to assess whether forensic psychiatry patients are likely to commit prospective criminal offences. However, these risk estimates cannot individually predict the type of criminal offence a patient will subsequently commit, and often simply assess the general likelihood of crime occurring in a group sample. In order to advance the predictive utility of risk assessments, better statistical strategies are required.
Aim: To develop a machine learning model to predict the type of criminal offense committed in forensic psychiatry patients, at an individual level.
Method: Machine learning algorithms (Random Forest, Elastic Net, SVM), were applied to a representative and diverse sample of 1240 patients in the forensic mental health system. Clinical, historical, and sociodemographic variables were considered as potential predictors and assessed in a data-driven way. Separate models were created for each type of criminal offence, and feature selection methods were used to improve the interpretability and generalizability of our findings.
Results: Sexual and violent crimes can be predicted at an individual level with 83.26% sensitivity and 77.42% specificity using only 20 clinical variables. Likewise, nonviolent, and sexual crimes can be individually predicted with 74.60% sensitivity and 80.65% specificity using 30 clinical variables.
Conclusion: The current results suggest that machine learning models have accuracy comparable to existing risk assessment tools (AUCs .70-.80). However, unlike existing risk tools, this approach allows for the prediction of cases at an individual level, which is more clinically useful. The accuracy of prospective models is expected to only improve with further refinement.

abstract: Thesis

abstract: Master of Science (MSc)

abstract:
Individuals end up in the forensic mental health system when they commit crimes and are found to be not criminality responsible because of a mental disorder. They are released back into the community when deemed to be low risk. However, it is important to consider the accuracy of the method we use to determine risk at the level of an individual person. Currently, we use group average to assess individual risk, which does not work very well. The range of our predictions become so large, that they are virtually meaningless. In other words, the average of a group is meaningless with respect to you.
Instead, statistical models can be developed that can make predictions accurately, and at an individual level. Therefore, the current work sought to predict the types of criminal offences committed, among 1240 forensic patients. Making accurate predictions of the crimes people may commit in the future is urgently needed to identify better strategies to prevent these crimes from occurring in the first place.
Here, we show that it is possible to predict the type of criminal offense an individual will later commit, using data that is readily available by clinicians. These models perform similarly to the best risk assessment tools available, but unlike these risk assessment tools, can make predictions at an individual level. It is suggested that similar approaches to the ones outlined in this paper could be used to improve risk prediction models, and aid crime prevention strategies.


title: EXPLORING THE OPERATIONALIZATION OF SEDENTARY BEHAVIOUR AND IDENTIFYING IMPORTANT HEALTH OUTCOMES OF PHYSICAL ACTIVITY IN INDIVIDUALS WITH CEREBRAL PALSY

contributor:
Gorter, Jan Willem
Rehabilitation Science

subject:
Children
Adults
Cerebral Palsy
Sedentary Behaviour
Physical Activity
Operationalization
Health Outcome

abstract: Children and adults with cerebral palsy (CP) perform reduced physical activity (PA) levels and increased sedentary behaviour (SB), which predisposes them to negative health outcomes. SB is characterized in the typically developing population by an energy expenditure component of ≤1.5 metabolic equivalents of task (METs) while sitting, reclining or lying. There is no consensus on an operationalized definition of SB for the CP population. Furthermore, there are no established outcomes to inform guidelines promoting PA in this population. I will address these two research gaps by investigating the operationalization of SB and by identifying important health outcomes of PA, through expert opinions, in individuals with CP. The first chapter is a scoping review of the operationalization of SB in individuals with CP. I found that, in individuals with CP, i) the definition for SB in the typically developing population of ≤1.5 METs generally applies to sitting and lying, and ii) sitting and lying are reported as operationalizations of SB. The second chapter was a conference-based survey to identify critical and important health outcomes for PA in individuals with CP. Clinicians and researchers (n=55) who attended a workshop on PA in CP rated nine pre-determined health outcomes on a 9-point Likert-type scale from the Grading of Recommendations Assessment, Development and Evaluation Approach. The experts identified both the psychological aspects of health (i.e. anxiety and depression) as being critical. The physical health outcomes rated as critical were sleep, nutrition, and cardiorespiratory endurance, and those rated as important were body size, body composition, blood lipids and glucose, and blood pressure. Together, this research suggests that the operationalization of SB in individuals with CP is similar to that of the typically developing population, and that both the physical and mental aspects of health must be considered in future PA management.

abstract: Thesis

abstract: Master of Science Rehabilitation Science (MSc)


title: Deep Convolutional Neural Networks for Multiclassification of Imbalanced Liver MRI Sequence Dataset

contributor:
Doyle, Thomas
eHealth

subject:
Imbalanced
Medical Imaging
Deep Learning
Convolutional Neural Networks
Clinical Decision Support
Radiology

abstract: Application of deep learning in radiology has the potential to automate workflows, support radiologists with decision support, and provide patients a logic-based algorithmic assessment. Unfortunately, medical datasets are often not uniformly distributed due to a naturally occurring imbalance. For this research, a multi-classification of liver MRI sequences for imaging of hepatocellular carcinoma (HCC) was conducted on a highly imbalanced clinical dataset using deep convolutional neural network. We have compared four multi classification classifiers which were Model A and Model B (both trained using imbalanced training data), Model C (trained using augmented training images) and Model D (trained using under sampled training images). Data augmentation such as 45-degree rotation, horizontal and vertical flip and random under sampling were performed to tackle class imbalance. HCC, the third most common cause of cancer-related mortality [1], can be diagnosed with high specificity using Magnetic Resonance Imaging (MRI) with the Liver Imaging Reporting and Data System (LI-RADS). Each individual MRI sequence reveals different characteristics that are useful to determine likelihood of HCC. We developed a deep convolutional neural network for the multi-classification of imbalanced MRI sequences that will aid when building a model to apply LI-RADS to diagnose HCC. Radiologists use these MRI sequences to help them identify specific LI-RADS features, it helps automate some of the LIRADS process, and further applications of machine learning to LI-RADS will likely depend on automatic sequence classification as a first step. Our study included an imbalanced dataset of 193,868 images containing 10 MRI sequences: in- phase (IP) chemical shift imaging, out-phase (OOP) chemical shift imaging, T1-weighted post contrast imaging (C+, C-, C-C+), fat suppressed T2 weighted imaging (T2FS), T2 weighted imaging, Diffusion Weighted Imaging (DWI), Apparent Diffusion Coefficient map (ADC) and In phase/Out of phase (IPOOP) imaging. Model performance for Models A, B, C and D provided a macro average F1 score of 0.97, 0.96, 0.95 and 0.93 respectively. Model A showed higher classification scores than models trained using data augmentation and under sampling.

abstract: Thesis

abstract: Master of Science (MSc)


title: Constitution as Promise

contributor:
Waluchow, Wilfrid
Philosophy

subject:
constitutionalism
promising
interpretation
constitutional law
vagueness
judicial review

abstract:
Constitution as Promise contends that constitutions are sets of promises.  As such, it argues that they must be interpreted in a living constitutionalist manner.
	Chapter One argues that constitutions meet the analytic criteria to be considered promises.  It is argued that constitutions are expressions of the intention of a government to bind itself to a set of principles.  Absent this expression, citizens lack assurance of the protection of their rights and legal recourse when their rights are violated.
	Chapter Two considers the use of promise in contract theory and investigates its viability in constitutional theory.  Some theories of contract are skeptical of promise as a basis for contract.  The chapter argues that while promise may be an inadequate moral underpinning for the law of contract, it is apt for the law of constitutions.
	Chapter Three notes that constitutions are sets of vague promises.  Vague promises ought not be interpreted solely in accordance with the intentions of promisors or promisees.  Traditional forms of originalism contend that constitutions should be interpreted according to the intentions of their framers.   So, constitution as promise rules out traditional forms of originalism.
	Chapter Four considers the positive consequences of constitution as promise.  It argues that vague promises ought to be interpreted through a negotiation process between promisor and promisee.  This negotiation should consider what moral reasoning reveals about the promise’s terms, the context in which the promise was uttered, the capacities and competing obligations of the promisor, and the expectations of the promisee.  To properly consider these factors, the chapter maintains that the negotiation must occur on a case-by-case basis, incrementally specifying the promise’s terms.  The chapter then notes the similarities between this negotiation process and the interpretive suggestions of living constitutionalism.  It concludes that living constitutionalism is entailed by the promissory nature of constitutions.

abstract: Thesis

abstract: Master of Philosophy (MA)

abstract: Constitution as Promise investigates the interpretive consequences of conceptualizing constitutions as promises from governments to citizens.  It first argues that constitutions satisfy the criteria to be considered promises.  It then maintains that the morality of promising is apt for application to constitutional law.  In the third and fourth chapters, it considers how one ought to interpret vague promises.  Vague promises, it argues, should be interpreted incrementally, on a case-by-case basis.  The promisor and the promisee must come to an agreement about what their vague promise requires, as new cases arise.  When they cannot agree, promisor and promisee need an adjudicator.  Since constitutions are sets of vague promises, they must also be interpreted incrementally, on a case-by-case basis and require adjudication where agreement is impossible.  Constitution as Promise concludes that the only available interpretive theory that is sensitive to constitution’s nature as vague promise is living constitutionalism.  As such, constitutions ought to be interpreted in a living constitutionalist manner.