Physical Sciences and Mathematics Commons^™

Functional Design Of Dissymmetric Ligands For Coordination Systems, Kaitlyn R. Brown

Theses and Dissertations (Comprehensive)

Herein, the functional design of dissymmetric ligands for coordination systems is explored with a focus on their synthesis and structural characterization. The design strategy of these ligands incorporates the ability to coordinate both metal cations and anions along with a ligand site for other functionalization. Their synthesis, structural and other characterization, Hirshfeld surface analysis, and some metal-coordinated complexes are discussed. Chapter 1 introduces supramolecular and coordination chemistry, along with relevant literature that supports this research and outlines the thesis objective. Chapter 2 investigates the hydrogen bonding of a dissymmetric pyrimidine thioether ligand in its neutral form, water solvate, protonated nitrate …

Construction Techniques For Linear Realizations Of Multisets With Small Support, M. A. Ollis

Emerson Authors, Researchers, & Creators

The Buratti-Horak Rosa Conjecture is a problem in graph theory asking when we can find a Hamiltonian path in the complete graph that has various properties to do with edge lengths. In this paper, we use constructive methods to show that the conjecture is true for various parameter sets where it was previously unknown.

The Gaps Programme At Tng: Lxv. Precise Density Measurement Of Toi-1430 B, A Young Planet With An Evaporating Atmosphere, D. Nardiello, J. M. Akana Murphy, R. Spinelli, M. Baratella, S. Desidera, V. Nascimbeni, L. Malavolta, K. Biazzo, A. Maggio, Ryan J. Oelkers

Physics & Astronomy Faculty Publications

Context. Small-sized (< 4 R_⊕) exoplanets in tight orbits around young stars (10–1000 Myr) give us the opportunity to investigate the mechanisms that led to their formation, the evolution of their physical and orbital properties, and, in particular, their atmospheres. Thanks to the all-sky survey carried out by the TESS spacecraft, many of these exoplanets have been discovered, and have subsequently been characterized with dedicated follow-up observations.

Aims. In the context of a collaboration among the Global Architecture of Planetary Systems (GAPS) team, the TESS-Keck Survey (TKS) team, and the California Planet Search (CPS) team, we measured …

A Hybrid Method For Source Direction Finding With Radio Frequency Interference And Gaussian White Noise, Yanming Zhang, Wenchao Xu, Antonios Argyriou, A. Long Jin, Tianquan Tang, Peifeng Ma, Lijun Jiang, Steven Gao

Electrical and Computer Engineering Faculty Research & Creative Works

This paper presents a hybrid data-driven method, termed moving average-Hankel-dynamic mode decomposition (MAHankDMD), for joint direction of arrival (DOA) and frequency estimation in environments affected by both radio frequency interference (RFI) and Gaussian white noise. The proposed approach integrates two key components: (1) a moving average-DMD filter that effectively mitigates Gaussian white noise and separates RFI from the source signal, and (2) a Hankel-DMD method that accurately estimates the DOA of the filtered signal and associates it with the corresponding frequency. The moving average-DMD stage first enhances the signal-to-noise ratio and improves the robustness of the estimation process through noise …

Applying Machine Learning And Optimization Algorithms To Perform Feature Selection, Shizhao Yu

Theses and Dissertations (Comprehensive)

The objective of feature selection in the realms of machine learning and data mining is integral, serving as an efficient mechanism to eradicate redundant or irrelevant features, and subsequently augmenting the performance of predictive models. In the contemporary landscape of big data, with the escalating dimensionality of datasets, the efficacy of traditional feature selection methodologies is compromised, due to their computational complexity and ineptitude in addressing the curse of dimensionality. This thesis posits a pioneering feature selection framework that amalgamates machine learning with advanced optimization algorithms. The methodology employs a Support Vector Machine (SVM), in conjunction with a cutting-edge metaheuristic …

Coupling Remote Sensing And Modelling To Monitor The Spatial Distribution And Trends Of Surface Temperature And Ice Thickness On Sub-Arctic Lakes, Gifty Attiah

Theses and Dissertations (Comprehensive)

Lake surface temperature (LST), lake ice thickness (LIT), and lake ice phenology (LIP) play significant roles in the diverse regional processes of freshwater in cold regions. They offer direct indications of regional weather and climate conditions, and their interactions with the atmosphere impact climate processes. Furthermore, lake ice is valuable to northern communities, such as those in the Northwest Territories (NWT). Ice roads, including the longest ice road in the NWT, spanning over 80 lakes, are constructed during winter to haul goods to and from industrial establishments (e.g., mines) and for travel within and between communities. A significant challenge to …

Investigating The Thermal Stratification Patterns Of A Shallow Polymictic Boreal Shield Lake And The Effectiveness Of Models In Predicting Shallow Lake Thermal Profiles, Matthew Roberts

Theses and Dissertations (Comprehensive)

Thermal stratification is a core process of lakes which plays a critical role in shaping the ecological dynamics of lakes, influencing major processes like nutrient cycling and oxygen availability. For shallow polymictic lakes, thermal stratification patterns present some unique differences due to the complex and variable nature of these lakes. In this thesis, I examined thermal stratification in a shallow polymictic lake in northwestern Ontario during the ice-free season of 2019 to investigate the frequency, duration, and driving factors of thermal stratification. The lake underwent 146 separate stratification events, with a median duration of 2 hours per event, with a …

Co-Creation, Interpretations And Engagement With A Movement-Based Symbol For Climate Justice: A Qualitative Inquiry, Kai Reimer-Watts

Theses and Dissertations (Comprehensive)

The climate crisis demonstrates with complete clarity the need for massive systems-level changes towards far more sustainable societies. Global and local emissions need to decline rapidly to mitigate intensifying climate breakdown, accompanied by climate and sustainability solutions, to secure a far more stable, safe, and just future for all people and all life. Within these changes, engaging in our communities is essential to support and co-create broader solutions to help advance more sustainable societies, reduce negative impacts of a changing climate, and to move towards cultures and systems that recognize natural limits and centre care for people and planet.

‘Climate …

Capital Structure Models And Contingent Convertible Securities, Di Meng

Theses and Dissertations (Comprehensive)

The 2007-09 financial crisis showed financial institutions are vulnerable during distressed times. As an alternative resolution to a government bail-out, contingent convertible securities (contingent capital or CoCos) were proposed by various researchers. CoCo is a hybrid capital security that converts from a bond to common equity when a pre-determined event occurs. The loss absorption mechanism of CoCo is essential to the financial health of a bank during a crisis as it provides an instant capital infusion when public capital is difficult to access.

In this thesis, we first implement a methodology to calibrate capital structure models for large Canadian banks. …

Reinforcement Learning For Scheduling And Routing: Electric Vehicles Charging And Patrol Scheduling, Majid Ghasemi

Theses and Dissertations (Comprehensive)

This thesis offers a comprehensive exploration of Reinforcement Learning (RL), beginning with fundamental theoretical constructs, Markov Decision Processes, Dynamic Programming, Monte Carlo, and Temporal Difference methods, and extending into state-of-the-art deep RL approaches such as Deep Q-Networks (DQN) and policy-gradient algorithms. Through analytical experiments in controlled environments, the thesis demonstrates how distinct algorithmic choices (e.g., exploration techniques, eligibility traces, or network architectures) influence convergence and stability. These foundational insights pave the way for two in-depth case studies, which apply RL techniques to critical, real-world scheduling and routing challenges.

The first case study tackles the Electric Vehicle (EV) routing and charging …

Multi-Lingual And Cross-Domain Frontiers In Machine-Generated Content Detection, Gurunameh Singh Chhatwal

Theses and Dissertations (Comprehensive)

The rapid advancement of generative artificial intelligence, particularly Large Language Models (LLMs) such as GPT-4 and their multilingual capabilities, has significantly blurred the distinction between human-authored and machine-generated content. This technological evolution introduces critical challenges concerning the detection and attribution of textual authenticity and authorship, exacerbating societal issues like misinformation proliferation and compromising academic and professional integrity. Traditional detection methodologies, predominantly monolingual and heuristic-based, have demonstrated inadequate generalizability and efficacy against the sophisticated, multilingual capabilities of contemporary generative models.

This thesis addresses two major problems arising from these advancements. Firstly, it introduces novel multilingual detection methodologies explicitly designed to differentiate …

Using Landscape Ecology And Spatial Statistics To Examine The Impacts Of Proposed Removals To Natural Heritage System And The Agricultural System Of Ontario’S Greenbelt, Brianna Downey

Theses and Dissertations (Comprehensive)

The 2022 proposed removals from the Greater Toronto Area (GTA), Southern Ontario’s Greenbelt would have resulted in negative impacts including, reductions to the size and functionality of the Agricultural System and Natural Heritage System, which are components of protected Greenbelt area. Several removal sites were located either on or in close proximity to corridor areas of the NHS, reducing connectivity and negatively impacting the surrounding ecological area. The removal of Agricultural land primarily consisted of corn and soybeans, as well as large removals of woodland, wetland, and shrubland class areas. The removal sites on local Agricultural composition and configuration were …

Controls Of Wetland Hydrology In The Zone Of Discontinuous Permafrost, Northwest Territories, Canada, Iain Thomson

Theses and Dissertations (Comprehensive)

Mean annual air temperatures are increasing rapidly in northwestern Canada, which is among the most rapidly warming regions on Earth (Box et al., 2019). Consequently, permafrost thaw within northwestern Canada is proceeding at a rate not found in the historical record (Pelletier et al., 2017), with areal thaw rates especially high in the peatland-dominated southern margin of discontinuous permafrost (Quinton et al., 2019). Permafrost thaw has caused vast land cover changes and transformed the permafrost underlain forest into permafrost free wetlands over much of Taiga Plains (Carpino et al., 2018; Jorgenson & Osterkamp, 2005). This land cover change has …

Alpha-Synuclein Interaction With Gedunin, Tony Matundura Nyabayo

Graduate Theses/Dissertations

Parkinson’s disease (PD) and other Proteinopathies develop when α-synuclein misfolds and aggregates into toxic amyloids. While existing treatments for PD are primarily focused on managing its symptoms, a viable solution for slowing down the progress of Parkinson’s disease involves targeting the toxic α-synuclein amyloids. Gedunin, a natural inhibitor of heat shock protein 90, has been extensively used to treat malaria. Also, recent research investigations have shed light on its potential beyond malaria therapy, indicating that Gedunin may offer a possible solution for treating a variety of neurodegenerative diseases. Using plate-based assays, we examined how Gedunin influences α-synuclein fibrillation and its …

Optical Properties Of Rare Earth Doped Molybdenum Trioxide Thin Films, Jessica Fink

Graduate Theses/Dissertations

This study aims to investigate the optical properties of Dy-doped MoO₃ thin films. MoO₃ is a transition metal oxide that is wide band gap semiconductor. As a transition-metal oxide, it has been widely studied for its tunable properties. However, there is little literature on the subject of Dysprosium doped MoO₃, and none found as of now on thin film Dy-MoO₃ . This indicates that this topic is at best under reported, and thin film Dy-MoO₃ possesses a certain novelty. Unlike most transition metal oxides, undoped MoO₃ has a negligible crystal field splitting. This is due to the electron vacancy of …

Predicting Real Estate Prices Using Deep Learning Regression Models On Socio Spatial Data, Gentle Engworo

Graduate Theses/Dissertations

ABSTRACT

Cities keep their own kind of ledger. Every block, bus stop, corner store, and year that slips by leaves a small entry about what homes are worth. That ledger is what we call socio-spatial data: simple facts about what a home is (its age), where it sits (latitude/longitude), how easy it is to get around (distance to the nearest MRT station), what’s nearby (number of convenience stores), and when it sold (transaction date). This thesis asks a practical question in that everyday language: given these common clues, can we predict home prices more accurately and explain why? Using 414 …

Topology-Guided Adaptive Social Navigation For A Robot In Environments With Dynamic Obstacles, S.M. Faiaz Mursalin

Graduate Theses/Dissertations

Robotic navigation in dynamic environments presents significant challenges, particularly in managing interactions with moving obstacles while ensuring efficient path planning. Incorporating social navigation principles is crucial as robots share the same workspaces with humans frequently in daily life. This becomes essential for safe, efficient, and socially acceptable movements. In this thesis, I introduce a novel integration of social navigation strategies with topological path planning that leverages Discrete Morse Theory, a homotopical framework to enhance adaptability. My method dynamically assesses path feasibility and optimizes trajectory selection through three key strategies: waiting, deflection, and diverse path selection. Based on how close the …

The Presence Of Outer Giant Planets And Their Role In Inner Planet Formation With And Without Their Influence, Mateo E. Guerra Toro

Graduate Theses/Dissertations

We performed dynamical simulations of the giant impact phase of planet formation to investigate the formation of inner terrestrial planets under the influence of 4 solar system-like outer giant planets. We developed a new code using the N-body simulation suite REBOUND and REBOUNDx (Rein et al. (2019) and Tamayo et al. (2019)) to simulate 2 stages of planetary formation: a residual gaseous protoplanetary disk phase and subsequent dynamical evolution after the disk photoevaporates. The initial conditions for the inner planetary embryos were taken by Morrison et al. (2020) based on a range of solid surface densities that produced Super-Earth terrestrial …

A Retrieval Augmented Approach To Improving Accuracy Of Biomedical Term Normalization By Large Language Models, Thanh Son Do

Graduate Theses/Dissertations

Ontology normalization is crucial in biomedical text processing, as it enables the mapping of medical expressions to standardized ontology terms and their corresponding identifiers. This thesis explores the feasibility of using large language models (LLMs) for ontology normalization, with a specific focus on the Human Phenotype Ontology and Gene Ontology. Prior research studies indicated that LLMs employing zero-shot learning tend to exhibit low accuracy and are prone to frequent hallucinations. We propose a retrieval augmented generation (RAG) approach to address these limitations and enhance normalization accuracy. We generated synthetic test sets of ontology-derived synonyms to evaluate normalization performance and developed …

The Effect Of Polyethylene Glycol Surface Density Of Dense Brush Gold Nanoparticles On Insulin Fibrillation, Ethan Patrick Grier

Graduate Theses/Dissertations

The development of various neurodegenerative diseases such as Parkinson’s disease and Alzheimer’s disease has been linked to the fibrillation of various proteins within the brain. Parkinson’s disease is specifically linked to the fibrillation of α-Synuclein. During the fibrillation process, the proteins take the form of oligomers, and exposure to these oligomers has been linked to various cytotoxic and neurotoxic effects. Once the fibrillation process is complete, the fibrils made have been shown to be much less toxic than the oligomer stage. This fibrillation process is thermodynamically favorable and is largely irreversible, so one course of action for treatment of these …

Development Of Cyan And Blue Thermostable Fluorescent Proteins: Characterization And Structural Analysis, Acacia J. Jurkowski

Graduate Theses/Dissertations

Fluorescent proteins are commonly used as cell markers in living organisms. Modifications by mutation can be used to improve the qualities of these proteins including fluorescence, thermostability, pH stability, and chemical stability. The goal of this project is to use mutagenesis to improve the fluorescence of thermostable cyan and blue proteins derived from the thermal green protein (TGP). The first cyan protein developed by the DeVore lab (CTP 0.0) shifted the fluorescence to cyan but decreased the quantum yield (Φ_F) to 0.056. Further mutations were incorporated to increase the quantum yield through incorporating hydrogen bonding interactions to the …

Effect Of Reduction Annealing On The Structural And Electrical Properties Of Α-Moo3 Thin Films, Sandipani Ghosh

Graduate Theses/Dissertations

2D layered molybdenum oxide has attracted significant research interest due to its tuneable bandgap and diverse structural, chemical, electrical, and optical properties influenced by growth parameters and synthesis techniques. In this study, the effects of reduction annealing on the structural and electrical properties of few-layer MoO₃ thin films, deposited on Si/SiO₂ substrates via pulsed laser deposition, were investigated. X-ray diffraction revealed nanocrystalline structures with a preferred (020) orientation, reduction annealing produced highly crystalline orthorhombic α-MoO₃ with reduced unit cell volume. FESEM/EDS provided detailed analyses of microstructures and elemental compositions. Raman spectroscopy confirmed the orthorhombic structure, with characteristic peaks at 667, …

Cyber Warfare And The Future Of Conflict, Victor A. Mercado

Graduate Theses/Dissertations

This thesis examines whether cyber warfare now poses a more immediate threat to U.S. national security than weapons of mass destruction (WMD). Cyber operations have become a dominant instrument of contemporary conflict, with malicious actors operating in a persistent “grey zone” that blurs traditional boundaries between war and peace. These operations target military and civilian entities, both directly and often as collateral damage due to the uncontrollable nature of cyber threats. WMDs, despite their catastrophic destructive potential, remain largely constrained by established deterrence frameworks.

The evolving nature of cyber warfare warrants comparison to WMD effects and impact, as cyber capabilities …

Critical Mineral Exploration In The Superior Province Of Northwestern Minnesota - A Geophysical Data Analysis, Michell L. Waterman

Graduate Theses/Dissertations

The Archean basement geology of northwest Minnesota, a region covered by glacial deposits and historically underexplored for minerals, was analyzed using gravity, magnetic, radiometric, and geochemical data. These datasets were integrated to aid in identifying subsurface structures and evaluating the area's potential for economic mineralization within the Wabigoon, Quetico, and Wawa Subprovinces of the Superior Province. Gravity and magnetic datasets, analyzed through upward continuation, derivative maps, and two-dimensional modeling, revealed distinct northeast-to-southwest-trending maxima corresponding to fault-bounded, high-density, and magnetically susceptible bodies. These features were interpreted as mafic to ultramafic intrusions and dikes, several of which align with known Proterozoic fault …

Modeling The Impact Of Climate Change On Plant Hardiness Zones Across The Contiguous United States Using Empirical Bayesian Kriging Regression Prediction, Daniel Donkor

Graduate Theses/Dissertations

Mapping plant hardiness zones is crucial to understanding and predicting the spatial distribution of plants in response to climatic conditions. The United States Department of Agriculture (USDA) developed the plant hardiness zones based on the average of annual extreme minimum temperatures using the Parameter elevation Regression on Independent Slope Model (PRISM). While the USDA’s 2012 and 2023 Plant Hardiness Zone maps remain standard references, they offer limited geostatistical transparency that causes more complications in replicating. This study applies Empirical Bayesian Kriging Regression Prediction (EBKRP) method to generate Plant Hardiness Zone maps, analyze spatial and temporal shifts in the plant hardiness …

Constructing Hamiltonians Using A Wannier Basis Set To Study Localized Electronic Interactions Using A Variational Quantum Eigensolver, Matthew D. Bruenning

Graduate Theses/Dissertations

In this study, I demonstrate how Wannier basis sets can be used to construct a tight binding Hamiltonian that is localized in real space. This Hamiltonian can then be studied using the Variational Quantum Eigensolver (VQE), which is able to extract the minimized energy of the system. Unlike Bloch functions, Wannier functions are localized in real space, allowing each Hamiltonian element to represent orbital overlaps between neighboring atomic orbitals. This locality enables a substantial reduction in the Hamiltonian’s size by including only the orbital projections that contribute meaningfully to localized interaction energies, such as those involved in adsorption. As a …

Generational Exposures To Cerium Oxide Nanoparticles And Perfluorooctanesulfonic Acid Affect The Performance Of Daughter Plants, Preston Clubb

Graduate Theses/Dissertations

The effects of parental stress on the performance of next generation exposed to another contaminant were investigated. Wheat was exposed to cerium oxide nanoparticles (CeO2-NPs) in first and second generations and exposed to perfluorooctanesulfonic acid (PFOS) in the third generation. Phenotypic or metabolic responses were assessed at 21-day (short-term exposure) or 90-day (long-term exposure) exposure periods. Biomass production, chlorophyll content, enzyme activity, and membrane damage were measured at short-term exposure, while elemental and PFOS concentrations, and grain metabolites were analyzed in long-term exposure. Results showed that continued exposures to CeO2-NPs and PFOS enhanced chlorophyll content but reduced concentrations of important …

Sparse Transformer For Anomaly Detection In Mobile Crowdsensing, Sanjeev Shrestha

Graduate Theses/Dissertations

Mobile Crowdsensing (MCS) is a sensing paradigm that leverages mobile devices to conduct a large-scale data collection. However, due to its openness and mobility nature, it is highly vulnerable to security issues such as injection attacks of malicious workers and fake tasks that can severely affect the platform’s normal functioning. To address this problem, the arrival of workers and task submission process is represented as a multivariate time series, and a two-stage framework is proposed. In the first step, we propose a novel transformer-based model, DozerAnomaly, that can efficiently detect anomalies in multivariate time series. We integrated a sparse attention …

Efficient Task Scheduling In Cloud Infrastructures Using Dynamic Score-Based Allocation And Deep Q-Learning, Shadman Sakib

Graduate Theses/Dissertations

Cloud computing has grown rapidly in recent years, mainly due to the sharp increase in data transferred over the internet. This growth makes task scheduling a key and challenging part of cloud systems, as it helps distribute user requests across servers to minimize response time, prevent overloading, and ensure smooth user experience. This thesis proposes two novel approaches for dynamic task scheduling in cloud environments. First, a novel Score-Based Dynamic Load Balancing (SBDLB) strategy is developed, which leverages system parameters to allocate tasks efficiently across virtual machines (VMs) in data centers. SBDLB ensures balanced workload distribution by continuously evaluating VM …

การศึกษาแบบแผนการเต้นของหัวใจระหว่างการวิ่ง โดยใช้การเรียนรู้ของเครื่องแบบไม่มีผู้สอนเพื่อการตรวจจับความผิดปกติ, ชวิน หังสสูต

Chulalongkorn University Theses and Dissertations (Chula ETD)

การศึกษานี้มีวัตถุประสงค์เพื่อวิเคราะห์รูปแบบการเต้นของหัวใจระหว่างการวิ่ง โดยใช้เทคนิคการตรวจจับความผิดปกติแบบไม่มีผู้สอน (Unsupervised Anomaly Detection - UAD) เพื่อการตรวจจับความผิดปกติ ปัญหาหลักในงานวิจัยนี้คือข้อจำกัดทางจริยธรรมในการรวบรวมข้อมูลภาวะวิกฤตเพื่อใช้สอนแบบจำลอง และความแปรปรวนของข้อมูลสรีรวิทยาที่สูงมากระหว่างบุคคลเพื่อแก้ไขปัญหานี้ งานวิจัยนี้ได้พัฒนาระบบเว็บแอปพลิเคชันสำหรับการรวบรวมและกำกับข้อมูล โดยผู้เชี่ยวชาญ และได้สร้างชุดข้อมูลอ้างอิงจากกลุ่มตัวอย่างนักวิ่ง 5 ท่าน จากนั้น ได้ดำเนินการศึกษาเชิงเปรียบเทียบแบบจำลอง UAD จำนวน 7 แบบจำลอง โดยใช้กลยุทธ์การเรียนรู้แบบจำเพาะบุคคล ภายใต้เงื่อนไข การกำหนดค่าไฮเปอร์พารามิเตอร์แบบคงที่ เพื่อจำลองสถานการณ์การใช้งานจริงแบบเริ่มต้น โดยปราศจากการปรับแต่งค่าล่วงหน้า และประเมินผลด้วยค่า F0.5-Score เพื่อเน้นความแม่นยำและลดการแจ้งเตือนที่ผิดพลาดผลการทดลองพบว่า เมื่อไม่มีการปรับจูนพารามิเตอร์ ประสิทธิภาพโดยรวมของทุกแบบจำลองลดลงอย่างมีนัยสำคัญ ซึ่งสะท้อนถึงความท้าทายในการสร้างแบบจำลองสากล อย่างไรก็ตาม แบบจำลอง Matrix Profile (MP) ในกลุ่มคลาสสิก พิสูจน์ให้เห็นถึงความทนทานสูงที่สุด โดยมีประสิทธิภาพเฉลี่ยสูงสุด (F0.5-Score 2.71%) และสามารถตรวจจับความผิดปกติได้ดีในรายบุคคล ในขณะที่แบบจำลองพื้นฐานล้มเหลวโดยสิ้นเชิง (0.00%) สำหรับกลุ่มการเรียนรู้เชิงลึก (USAD, LSTM-AE) พบว่ามีข้อจำกัดในการใช้งานแบบเริ่มต้น (Cold-start) โดยไม่สามารถตรวจจับความผิดปกติได้แม้จะมีปริมาณข้อมูลมาก หากปราศจากการปรับแต่งค่าพารามิเตอร์ ผลลัพธ์นี้ยืนยันว่าระบบเฝ้าระวังสุขภาพในอนาคตจำเป็นต้องมีกลไกการเรียนรู้แบบปรับตัว ร่วมด้วยเพื่อให้สามารถนำไปใช้งานจริงได้อย่างมีประสิทธิภาพ