University of Lethbridge Theses
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- ItemGenetic population structure of the least flycatcher (Empidonax minimus): implications for evaluating migratory connectivity(Lethbridge, Alta. : University of Lethbridge, Dept. of Biological Sciences, 2025) Castro García, Sara; University of Lethbridge. Faculty of Arts and Science; Burg, Theresa M.Over the last six decades, avian aerial insectivores in North America have experienced an overall decline of ~60% in their population across their breeding ranges. Understanding their population genetic structure and spatial connections across the annual cycle is critical to determining potential factors driving these trends; however, this information is limited for many species. This study uses RADseq data to examine population structure and connectivity in least flycatchers (Empidonax minimus) across North America. Supported by field and museum sampling, blood, feather, and/or tissue samples were collected from 14 sites throughout the breeding range as well as during migration in Canada and the USA, and on the non-breeding grounds in Mexico. The results from principal components analysis (PCA), pairwise FST, STRUCTURE, and least-cost corridor analyses indicate high levels of gene flow among breeding populations, with weak genetic structure observed between two groups that exhibit an east-west split, which is enhanced using outlier loci. A genetic stock identification analysis was conducted to determine the breeding origin of the non-breeding samples, utilizing outlier loci. Twelve out of 29 non-breeding samples were successfully assigned to a breeding population. In two of the three non-breeding locations, individuals of mixed origin were observed, indicating weak migratory connectivity. The results indicate that the weak migratory connectivity and young age of the species might contribute to the low levels of population structure observed. This study allowed to increase the comprehension of the genetic structure and migratory connectivity of the least flycatcher.
- ItemTowards new zwitterioinic difluoroglycine analogues: preparation methods and reactivity studies(Lethbridge, Alta. : University of Lethbridge, Dept. of Chemistry and Biochemistry, 2025) Lilienthal, Elaura O.; University of Lethbridge. Faculty of Arts and Science; Hamel, Jean-DenysResearch into new methods of fluorination is imperative as the addition of fluorine onto organic molecules has a great influence on a compound’s properties. Difluorocarbene can be used in such fluorination methods, and it is currently being explored for its unique properties. The purpose of this thesis was to see if it was possible to create new zwitterionic difluoroglycine-derived difluorocarbene precursors, and to test their ability against the previously reported phosphine-based analogue. The formation of the phosphine-based difluorocarbene source is achieved through nucleophilic substitution, and then release of the difluorocarbene through heating. It was believed that this procedure can be ameliorated, by improving the atom economy of the reaction, as well lowering the temperature of release allowing for better use on small scale and in industry. First, the precursors would have the phosphine group swapped for new nitrogen and sulfur-based groups, hopefully allowing for difluorocarbene release at a lower temperature. This was tested by using different types of amines, pyridines and two sulfides. A subset of potential difluorocarbene precursors was thus synthesized. The new difluorocarbene sources were tested in (2+1) cycloaddition reactions and difluoromethylation reactions to test their ability to release the difluorocarbene. The nitrogen-based precursors were tested against the phosphine analogue and showed comparable results. However, all data collected proved that the concept of forming these new difluoroglycine analogues and their reactivity bears potential, but is not fully understood yet. The work presented in this thesis gives key insights into the possibility of synthesizing zwitterionic difluoroglycine analogues and their subsequent reactivity.
- ItemForm-preserving transformations of the Schrödinger equation(Lethbridge, Alta. : University of Lethbridge, Dept. of Physics and Astronomy, 2025) Daub, Mason J.; University of Lethbridge. Faculty of Arts and Science; Walton, Mark A.Coordinate transformations of differential equations have long been studied in the context of mathematics and physics. They allow us to change a differential equation into one that is easier to solve. In nonrelativistic quantum mechanics, the time evolution of a wave function is determined by the time-dependent Schrodinger equation (TDSE). Since quantum mechanics must work in every nonrelativistic frame, there must be a TDSE for every set of coordinates one chooses to measure in. Coordinate transformations between two reference frames must then transform one Schrodinger equation into another. Called form-preserving transformations (FPTs), these transformations allow for many puzzling solutions to the TDSE and can be used for the efficient determination of symmetry groups. In this work, we will determine the most general allowed FPT for the Schrodinger-Pauli equation of a spinless charged particle in N-dimensions. Furthermore, we show that the FPTs form a continuous Lie group, whose algebra is discussed in detail. Well-known symmetry groups such as the Galilean and Schrodinger groups are shown to be subgroups of the form-preserving group. We conclude with an analysis of FPTs in the phase-space formulation of quantum mechanics.
- ItemRbm-od: a restricted Boltzmann machine framework for outlier detection(Lethbridge, Alta. : University of Lethbridge, Dept. of Mathematics and Computer Science, 2025) Hoeksema, Brady F.; University of Lethbridge. Faculty of Arts and Science; Zhang, John Z.This thesis explores the use of Restricted Boltzmann Machines (RBMs), a class of unsupervised generative neural networks, for detecting outliers through data generation and representation-based comparison. Outlier detection (OD) is a critical task in domains where rare or anomalous patterns may indicate errors, fraud, or unexpected behaviour in data. The primary contribution of this work is a unified framework for RBM-based outlier detection that emphasizes data generation as a detection strategy. We explore multiple model variants, including single RBMs, ensembles of RBMs, stacked RBMs, and ensembles of stacked RBMs, each offering distinct advantages in representing complex data patterns. By generating synthetic samples from trained RBMs and comparing them to input data, the approach enables unsupervised detection of unusual or unexpected instances. This gener ative perspective distinguishes RBM-OD from traditional methods and provides a flexible foundation for future extensions.
- ItemAdvanced boundary-enhanced instance segmentation and spatial-temporal transformer models for automated schizophrenic investigation(Lethbridge, Alta. : University of Lethbridge, Dept. of Mathematics and Computer Science, 2025) Imarhiagbe, Osasumwen Raphael; University of Lethbridge. Faculty of Arts and Science; Zhang, John Z.Accurate segmentation and detection in neuroimaging is essential for advancing clinical understanding and the diagnosis of schizophrenia. This thesis introduces Boundary-Refined Attention Network (BoRefAttnNet), a novel boundary-refined 3D U-Net variant specifically designed for precise segmentation of subcortical brain structures from structural magnetic resonance imaging (sMRI). BoRefAttnNet incorporates multi-scale boundary attention modules that explicitly highlight anatomically critical edges while suppressing background noise, significantly improving segmentation accuracy for small or complex anatomical structures. Evaluations using FastSurfer-processed sMRI data from the publicly available Centre for Biomedical Research Excellence (COBRE) dataset demonstrate that BoRefAttnNet significantly outperforms conventional 3D U-Net baselines in accurately delineating key subcortical structures, including the hippocampus, amygdala, and basal ganglia. Building upon this enhanced segmentation capability, we further experiment with a Dynamic Spatial-Temporal Transformer Model (DySTTM) to detect schizophrenia by integrating structural and functional MRI (fMRI) modalities. The DySTTM leverages spatial attention to capture anatomical interdependencies from segmented sMRI data and temporal attention to model dynamic brain connectivity patterns from resting-state fMRI. Experimental results indicate that the integration of these multimodal imaging features using DySTTM provides superior diagnostic accuracy and interpretability compared to established models such as 3D ResNet and XGBoost classifiers.