Physical Sciences and Mathematics Commons^™

Mathematical Modelling Of Prophage Dynamics, Tyler Pattenden

Electronic Thesis and Dissertation Repository

We use mathematical models to study prophages, viral genetic sequences carried by bacterial genomes. In this work, we first examine the role that plasmid prophage play in the survival of de novo beneficial mutations for the associated temperate bacteriophage. Through the use of a life-history model, we determine that mutations first occurring in a plasmid prophage are far more likely to survive drift than those first occurring in a free phage. We then analyse the equilibria and stability of a system of ordinary differential equations that describe temperate phage-host dynamics. We elucidate conditions on dimensionless parameters to determine a parameter …

Stable Carbon And Oxygen Isotope Investigation Of Pleistocene Growing-Season Paleoclimate Using Tree-Ring Cellulose From The Missinaibi Formation, Adam Creek, James Bay Lowland, Canada, Jumin Lee

Electronic Thesis and Dissertation Repository

The isotopic compositions of cellulose in tree rings provide a record of seasonal and annual climatic conditions such as precipitation and temperature. We analyzed stable isotopes of carbon (δ¹³C_cellulose) and oxygen (δ¹⁸O_cellulose) in early-wood and late-wood of five conifer sub-fossil wood samples from the Missinaibi Formation, which likely grew during the peak of Marine Isotope Substage (MIS) 5a (~82 kya) at Adam Creek, Ontario. There was no systematic difference between early-wood and late-wood for either δ¹³C_cellulose or δ¹⁸O_cellulose, suggesting similar climatic conditions throughout …

Simulation Approaches To X-Ray C-Arm-Based Interventions, Daniel R. Allen

Electronic Thesis and Dissertation Repository

Mobile C-Arm systems have enabled interventional spine procedures, such as facet joint injections, to be performed minimally-invasively under X-ray or fluoroscopy guidance. The downside to these procedures is the radiation exposure the patient and medical staff are subject to, which can vary greatly depending on the procedure as well as the skill and experience of the team. Standard training methods for these procedures involve the use of a physical C-Arm with real X-rays training on either cadavers or via an apprenticeship-based program. Many guidance systems have been proposed in the literature which aim to reduce the amount of radiation exposure …

Electronic And Local Structures Of Pt-Based Bimetallic Alloy And Core-Shell Systems, Jiatang Chen

Electronic Thesis and Dissertation Repository

This thesis investigates the electronic structure of Pt for catalysis applications. The importance of the Pt 5d band is discussed in terms of the bonding capability of Pt. The oxygen reduction reaction in proton exchange membrane fuel cells is chosen as the catalytic reaction model to illustrate the effect of Pt 5d states on Pt-O interaction. Pt-based bimetallic systems are introduced as a solution for the high price and limited resources of Pt. Despite lower usage of Pt, the tuning capability to optimize the Pt 5d band in bimetallic catalysts is supposed to provide superior catalytic activity. Advanced synchrotron X-ray …

Discrimination Of Leucine And Isoleucine In De Novo Peptide Sequencing Using Deep Neural Networks, Bingran Shen

Electronic Thesis and Dissertation Repository

De novo peptide sequencing from tandem MS data is a key technology in proteomics for understanding the structure of proteins, especially for first seen sequences. Although this technique has advanced rapidly in recent years and become more effective, one crucial problem remained unsolved. Due to the isomerism of leucine and isoleucine, they are practically indistinguishable in de novo sequencing using traditional tandem MS data. Some experimental attempts have been made to resolve this ambiguity such as EThCD fragmentation process. In this study, we took a data focused approach rather than only looking for characteristic satellite ions produced by the EThCD …

Ranking Comments: An Entropy-Based Method With Word Embedding Clustering, Yuyang Zhang

Electronic Thesis and Dissertation Repository

Automatically ranking comments by their relevance plays an important role in text mining and text summarization area. In this thesis, firstly, we introduce a new text digitalization method: the bag of word clusters model. Unlike the traditional bag of words model that treats each word as an independent item, we group semantic-related words as clusters using pre-trained word2vec word embeddings and represent each comment as a distribution of word clusters. This method can extract both semantic and statistical information from texts. Next, we propose an unsupervised ranking algorithm that identifies relevant comments by their distance to the “ideal” comment. The …

Renewable-Energy Resources, Economic Growth And Their Causal Link, Yiyang Chen

Electronic Thesis and Dissertation Repository

This thesis examines the presence and strength of predictive causal relationship between re-newable energy prices and economic growth. We look for evidence by investigating the cases of Norway, New Zealand, and Canada’s two provinces of Alberta and Ontario. The usual vectorautoregressive model (VAR) and its various improved versions still assume constant parametersover time. We devise a Markov-switching VAR (MS-VAR) model in order to accommodate the observed time-dependent causal relation changes. Our proposed modelling approach is induced by the hidden Markov model methodologies in terms of an online parameter estimationthrough recursive filtering. The parameters of the MS-VAR model are governed by …

Galvanic Corrosion Of Carbon Steel-Stainless Steel Welds, Mi Li

Electronic Thesis and Dissertation Repository

A water leak in one of the Canada Deuterium Uranium (CANDU) nuclear reactors could lead to galvanic corrosion between the materials of its supporting structures: carbon steel (CS) and stainless steel (SS). This project investigates the effects of physical and chemical solution parameters on the corrosion of galvanically coupled dissimilar CS-SS welds, with the aim of developing a corrosion dynamics model that can be used to assess the long-term integrity of the CANDU reactor structural materials with confidence. The studied parameters were solution pH, temperature, the presence or absence of γ-radiation and the cathode:anode surface area ratio. Multiple electrochemical techniques …

Gamma-Radiolysis Kinetics And Its Role In The Overall Dynamics Of Materials Degradation, Ryan P. Morco

Electronic Thesis and Dissertation Repository

The γ-radiation emitted during radioactive decay of the wastes in a nuclear fuel container can affect container corrosion. When a metal/water system is exposed to γ-radiation both the solid metal and the liquid water (or humid air) absorb energy. This energy dissipates mainly as heat in the metal but induces decomposition of water molecules to yield a range of chemically reactive species. The different chemical environments induced in the metal and liquid phases can change the driving forces for surface reactions and thereby influence the rate and pathway of metal corrosion.

This thesis presents the development of radiolysis kinetic models …

Nonlinear Dynamics Of Carbon Steel Corrosion Under Gamma Radiation, Youn Gyeong Shin

Electronic Thesis and Dissertation Repository

Corrosion of materials is still an unresolved problem affecting a multitude of industries. One of the grand challenges facing the corrosion community is the development of high-fidelity models for corrosion in actual service environments. The difficulties arise since corrosion involves transfer of metal atoms between the solid and solution phases thus making the system non-adiabatic. Interfacial transfer of atoms increases the chance of establishing systemic feedback between chemical reactions and transport processes, which results in chemical oscillation and periodic patterns on the corroding surfaces. These oscillating behavior in electrochemical measurements and pattern formation on corroding surfaces have been reported in …

Impact Melt-Bearing Deposits Around Martian Craters, William A. Yingling

Electronic Thesis and Dissertation Repository

In this work, we investigate impact melt emplacement around Martian craters. We compare our results to melt emplacement processes found on Venus, the Moon, and Mercury. We tentatively find Martian melt emplacement more closely resembles Venusian emplacement, rather than lunar emplacement. This suggests Martian melt emplacement likely takes place during the excavation stage where impactor momentum is imparted to the melt. Mercury and Mars have amongst the highest and lowest average impact velocities, respectively, of terrestrial bodies in the Solar System, but a significant difference in emplacement is not observed. This suggests impact velocity may not have as large an …

Spatial And Temporal Variation Of Nutrients In The Great Lakes-St. Lawrence Basin: Implications For Primary Production In Stream Ecosystems, Nolan Pearce

Electronic Thesis and Dissertation Repository

Growing human populations and associated land use activities has increased the amount of nutrients delivered to surface waters. Eutrophication from the over-enrichment of nitrogen and phosphorus has degraded ecosystem conditions in streams, lakes, and coastal areas worldwide. Thus, the management of anthropogenic nutrient loading is a global concern. This thesis employed a combination of field and experimental research to provide watershed managers with information on the spatial and temporal patterns in stream nutrient enrichment, and the associated ecological effects of anthropogenic nutrient loading in the Great Lakes-St. Lawrence basin. Four studies were completed to address this research goal. First, I …

Classification-Based Method For Estimating Dynamic Treatment Regimes, Junwei Shen

Electronic Thesis and Dissertation Repository

Dynamic treatment regimes are sequential decision rules dictating how to individualize treatments to patients based on evolving treatments and covariate history. In this thesis, we investigate two methods of estimating dynamic treatment regimes. The first method extends outcome weighted learning from two-treatments to multi-treatments and allows for negative treatment outcome. We show that under two different sets of assumptions, the Fisher consistency can be maintained. The second method estimates treatment rules by a neural classification tree. A weighted squared loss function is defined to approximate the indicator function to maintain the smoothness. A method of tree reconstruction and pruning is …

Hybrid Symbolic-Numeric Computing In Linear And Polynomial Algebra, Leili Rafiee Sevyeri

Electronic Thesis and Dissertation Repository

In this thesis, we introduce hybrid symbolic-numeric methods for solving problems in linear and polynomial algebra. We mainly address the approximate GCD problem for polynomials, and problems related to parametric and polynomial matrices. For symbolic methods, our main concern is their complexity and for the numerical methods we are more concerned about their stability. The thesis consists of 5 articles which are presented in the following order:

Chapter 1, deals with the fundamental notions of conditioning and backward error. Although our results are not novel, this chapter is a novel explication of conditioning and backward error that underpins the rest …

Optimized Machine Learning Models Towards Intelligent Systems, Mohammadnoor Ahmad Mohammad Injadat

Electronic Thesis and Dissertation Repository

The rapid growth of the Internet and related technologies has led to the collection of large amounts of data by individuals, organizations, and society in general [1]. However, this often leads to information overload which occurs when the amount of input (e.g. data) a human is trying to process exceeds their cognitive capacities [2]. Machine learning (ML) has been proposed as one potential methodology capable of extracting useful information from large sets of data [1]. This thesis focuses on two applications. The first is education, namely e-Learning environments. Within this field, this thesis proposes different optimized ML ensemble models to …

Automated Anomaly Detection And Localization System For A Microservices Based Cloud System, Priyanka Prakash Naikade

Electronic Thesis and Dissertation Repository

Context: With an increasing number of applications running on a microservices-based cloud system (such as AWS, GCP, IBM Cloud), it is challenging for the cloud providers to offer uninterrupted services with guaranteed Quality of Service (QoS) factors. Problem Statement: Existing monitoring frameworks often do not detect critical defects among a large volume of issues generated, thus affecting recovery response times and usage of maintenance human resource. Also, manually tracing the root causes of the issues requires a significant amount of time. Objective: The objective of this work is to: (i) detect performance anomalies, in real-time, through monitoring KPIs (Key Performance …

Locally Persistent Categories And Metric Properties Of Interleaving Distances, Luis N. Scoccola

Electronic Thesis and Dissertation Repository

This thesis presents a uniform treatment of different distances used in the applied topology literature. We introduce the notion of a locally persistent category, which is a category with a notion of approximate morphism that lets one define an interleaving distance on its collection of objects. The framework is based on a combination of enriched category theory and homotopy theory, and encompasses many well-known examples of interleaving distances, as well as weaker notions of distance, such as the homotopy interleaving distance and the Gromov–Hausdorff distance.

We show that the approach is not only an organizational tool, but a useful theoretical …

Visual Analytics Of Electronic Health Records With A Focus On Acute Kidney Injury, Sheikh S. Abdullah

Electronic Thesis and Dissertation Repository

The increasing use of electronic platforms in healthcare has resulted in the generation of unprecedented amounts of data in recent years. The amount of data available to clinical researchers, physicians, and healthcare administrators continues to grow, which creates an untapped resource with the ability to improve the healthcare system drastically. Despite the enthusiasm for adopting electronic health records (EHRs), some recent studies have shown that EHR-based systems hardly improve the ability of healthcare providers to make better decisions. One reason for this inefficacy is that these systems do not allow for human-data interaction in a manner that fits and supports …

Reinforcement Learning In Large, Structured Action Spaces: A Simulation Study Of Decision Support For Spinal Cord Injury Rehabilitation, Nathan Phelps

Electronic Thesis and Dissertation Repository

Reinforcement learning (RL) has helped improve decision-making in several applications. However, applying traditional RL is challenging in some applications, such as rehabilitation of people with a spinal cord injury (SCI). Among other factors, using RL in this domain is difficult because there are many possible treatments (i.e., large action space) and few patients (i.e., limited training data). Treatments for SCIs have natural groupings, so we propose two approaches to grouping treatments so that an RL agent can learn effectively from limited data. One relies on domain knowledge of SCI rehabilitation and the other learns similarities among treatments using an embedding …

Extensions Of Classification Method Based On Quantiles, Yuanhao Lai

Electronic Thesis and Dissertation Repository

This thesis deals with the problem of classification in general, with a particular focus on heavy-tailed or skewed data. The classification problem is first formalized by statistical learning theory and several important classification methods are reviewed, where the distance-based classifiers, including the median-based classifier and the quantile-based classifier (QC), are especially useful for the heavy-tailed or skewed inputs. However, QC is limited by its model capacity and the issue of high-dimensional accumulated errors. Our objective of this study is to investigate more general methods while retaining the merits of QC.

We present four extensions of QC, which appear in chronological …

Triaging Twitter Users: An Exploratory Visual Analytics System, Parinaz Nasr Esfahani

Electronic Thesis and Dissertation Repository

Twitter is one of the most popular microblogging and social networking services. Many people from a wide range of backgrounds use Twitter to contribute their thoughts on different topics through postings, known as ``tweets”. Analysts collect and analyze tweets to extract knowledge. To rely on tweets, it is crucial to assess Twitter users’ credibility. In recent years, researchers have proposed various techniques, especially data analytics models, for evaluating Twitter users and analyzing their behaviour; however, these techniques do not engage analysts in the process, leading to a lack of understanding and trust in results. In this thesis, an exploratory visual …

Determining Geological Controls On Nutrient Availability At Different Depths In The Soils Of The Pelee Island Winery, Lindsay M. Blythe

Electronic Thesis and Dissertation Repository

Terroir describes a sense of place that can give a unique flavour to wines grown in different environments. We explored the role of soil in the terroir at Canada’s most southern vineyard, Pelee Island Winery. This study examined the abundance of major nutrients, trace and rare earth elements of minerals and plant extractable nutrients from 19 soils across the vineyard to a depth of 2 m. We found that bedrock does not influence the element content of Pelee Island soils, the parent materials of the soils are tills and there are geochemical, mineralogical and grain size differences between the two …

Generalized 4/2 Factor Model, Yuyang Cheng

Electronic Thesis and Dissertation Repository

We investigate portfolio optimization, risk management, and derivative pricing for a factor stochastic model that considers the 4/2 stochastic volatility on the common/systematic factor as well as on the intrinsic factor. This setting allows us to capture stochastic volatility and stochastic covariation among assets. The model is also a generalization of existing models in the literature as it includes the mean reverting property and spillover effect to capture wider types of financial assets. At a theoretical level we identify conditions for well-defined changes of measure. A quasi-closed form solution within a 4/2 structured model is obtained for a portfolio optimization …

Iron(Ii) Metal-Ligand Cooperative Catalysts For Endo-Selective Intramolecular Hydrofunctionalization, Benjamin Bridge

Electronic Thesis and Dissertation Repository

Two new cationic Fe(II) P^R₂N^R'₂ complexes, [Fe(Cp*)(P^R₂N^Ph₂)(MeCN)]PF₆ (R = cyclohexyl, 3a) and [Fe(Cp*)(P^R₂N^Ph₂)(MeCN)]PF₆ (R = phenyl, 3b), were synthesized and characterized. The catalytic activity for intramolecular hydrofunctionalization was tested using the benchmark substrate 2-ethynylaniline (EA) and both catalysts effectively produced indole (Ind). The selectivity of catalysis was also tested using 2-ethynylbenzyl alcohol (EBA) and both catalysts formed only the endo product isochromene (IC). These complexes represent the first well-defined Fe(II) catalysts that …

Design Of Interactive Visualizations For Next-Generation Ultra-Large Communication Networks, Wenjun Chen

Electronic Thesis and Dissertation Repository

With the increasing size and complexity of next-generation communication networks, it is critical to utilize interactive information visualization to support the network monitoring, planning, and management. Effectively visualizing large-scale networks has been considered difficult with traditional methods because of the high link density and complicated node relationship. Given the limited screen space, it is essential to explore how to present ultra-large-scale network data efficiently that can assist Internet Service Provider’s (ISP) network planning and management activities. This work proposes a design of the real-time interactive visualization system that combines the idea of progressive disclosure and multiple panels to elegantly visualize …

Airborne Observations Of Thermal Anisotropy From Urban Residential Neighbourhoods In Salt Lake City, Utah, Samantha J. Claessens

Electronic Thesis and Dissertation Repository

Urban surface temperatures are important variables in urban climatological processes. This thesis examines the directional variability of remotely sensed urban surface temperatures (thermal anisotropy or Λ) for three vegetated residential neighbourhoods in Salt Lake City, Utah, USA. Airborne thermal remote sensing using a thermal imager sampled the directional brightness temperature (DBT) at three times within a day for each site. Results indicate that temporal variability over a 20 – 30-minute flight was not negligible. Average DBT were then extracted from atmospherically corrected images and plotted on polar plots. For low density residential neighbourhoods Λ is increased with increasing tree-canopy coverage …

Plasmon-Enabled Physical And Chemical Transformations Of Nanomaterials, Danielle Mcrae

Electronic Thesis and Dissertation Repository

When the electromagnetic field of light is incident on metallic nanostructures of dimensions smaller than the incident wavelength of the light, there is a strong interaction, resulting in an enhanced, highly confined electromagnetic field in the vicinity of the nanostructure. This effect is referred to as a localized surface plasmon resonance, most commonly exploited for plasmon-enhanced spectroscopies, such as surface-enhanced Raman spectroscopy (SERS) and tip-enhanced Raman spectroscopy (TERS). The location, number and intensity of these regions of enhancement, or “hotspots”, can be tuned by changing the nature of the metal, the size, shape and arrangement of the nanoparticles, its surroundings, …

The Relationship Between Visible Gold And Arsenopyrite At The Orenada Zone 4 Deposit, Val D'Or, Quebec, Cassandra Powell

Electronic Thesis and Dissertation Repository

The Orenada Zone 4 deposit is an Archean orogenic gold deposit situated southeast of Val d’Or, Québec in the southeastern Abitibi Greenstone Belt. It is located directly within the Cadillac-Larder-Lake Deformation Zone. Mineralization is hosted within a volcanoclastic horizon of the Cadillac Group where two distinct facies were defined. Both facies underwent a pervasive sericite-chlorite-carbonate±albite alteration assemblage that predates gold mineralization. Gold is associated with two generation of auriferous quartz-carbonate-tourmaline veins and within fractures of corroded arsenopyrite grains, located proximal to the vein walls. A LA-ICP-MS study determined that neither textural type of arsenopyrite displayed refractory gold. Therefore, gold was …

Issues Related To Framing And Interpretation Of Studies In The Orthopaedic Literature, Shgufta Docter

Electronic Thesis and Dissertation Repository

In research, appropriate statistical interpretation and methodology are essential to conduct quality work. To interpret results, p-values are frequently used in isolation, but this is insufficient as treatment effects, confidence intervals (CIs), and clinically important thresholds should also be reported. Further, the equality, superiority, non-inferiority, and equivalence frameworks have critical differences not well delineated in current literature. We conducted a systematic review of studies published in high-impact orthopaedic journals and examined a) how well studies interpreted the results of patient-reported outcome measures, and b) whether a consistent framework was used throughout studies. We found that the majority of studies do …

A Hybrid Approach To Procedural Dungeon Generation, Mathias Paul Babin

Electronic Thesis and Dissertation Repository

This thesis presents a novel approach to the Procedural Content Generation (PCG) of both maze and dungeon environments. The solution we propose in this thesis borrows techniques from both Procedural Content Generation via Machine Learning as well as Constructive PCG methods. The approach we take involves decomposing the problem of level generation into a series of stages which begins with the production of macro-level functional structures and ends with micro-level aesthetic details; specifically, we train a Deep Convolutional Neural Network to produce high-quality mazes, which in turn, are transformed into the rooms of larger dungeon levels using a constructive algorithm. …