Physical Sciences and Mathematics Commons^™

Meta-Analysis Of Mesenchymal Stem Cell Gene Expression Data From Obese And Non-Obese Patients, Dakota William Shields

Masters Theses

"The prevalence of gene expression microarray datasets in public repositories gives opportunity to analyze biologically interesting datasets without running the laboratory aspect in house. Such experimentation is expensive in terms of finances, time, and expertise, which often results in low numbers of replicates. Meta-analysis techniques attempt to overcome issues due to few biological or technical replicates by combining separate experiments together to increase statistical power. Proper statistical considerations help to offset issues like simultaneous testing of thousands of genes, unintended hybridization, and other noises.

Microarrays contain light intensities from tens of thousands of hybridized probes giving a measure of gene …

Dynamic Discounted Satisficing Based Driver Decision Prediction In Sequential Taxi Requests, Sree Pooja Akula

Masters Theses

"Ridesharing platforms rely on connecting available taxi drivers to potential passengers to maximize their revenue. However, predicting the stopping decision made by every driver, i.e., the final task performed during a given day, is crucial to achieving this goal. Unfortunately, little research has been done on predicting drivers’ stopping decisions, especially when they deviate from expected utility maximization behavior. This research proposes a Dynamic Discounted Satisficing (DDS) heuristic to model and learn the task at which human agents will stop working for that day, assuming that the human agents are taking sequential decisions based on their preference order. We apply …

Electrodeposition Of Epitaxial Wide Bandgap P-Type Semiconductors And Copper Metal For Energy Conversion And Flexible Electronics, Bin Luo

Doctoral Dissertations

"Epitaxial electrodeposition is a simple, low-cost technology to produce highly ordered materials on single-crystal surfaces. This research focuses on the epitaxial electrodeposition of wide bandgap p-type semiconductors and epitaxial Cu thin films via a self-assembled monolayer for energy conversion and flexible electronics. Paper I introduces the epitaxial electrodeposition of hole conducting CuSCN nanorods onto Au (111) surface, and lift-off to produce flexible and transparent foils. Highly ordered CuSCN could serve as an inorganic transport layer in various opto-electronic devices such as perovskite solar cells, LEDs, and transistors. An ordered and transparent CuSCN foil was also produced by epitaxial lift-off following …

Novel Quantum Materials For Spintronic And Opto-Electronic Applications, Ali Sarikhani

Doctoral Dissertations

"Multi-functional quantum materials play a crucial role in the development of spintronics and opto-electronics, as their properties can greatly influence device performance. For instance, in spintronics, materials such as ferromagnetic half-metals, Giant Magnetoresistants (GMR), and magnetic semiconductors have been extensively studied due to their ability to manipulate the spin of electrons for applications in magnetic storage. In opto-electronics, materials such as Diluted Magnetic Semiconductors (DMS) and non-oxide Transparent Conductors (TC) offer advantages such as tunable bandgap and high absorption coefficients, which enable improved device performance.

For this purpose, we have experimentally investigated the compounds that have shown theoretically interesting physical …

Efficient High Order Ensemble For Fluid Flow, John Carter

Doctoral Dissertations

"This thesis proposes efficient ensemble-based algorithms for solving the full and reduced Magnetohydrodynamics (MHD) equations. The proposed ensemble methods require solving only one linear system with multiple right-hand sides for different realizations, reducing computational cost and simulation time. Four algorithms utilize a Generalized Positive Auxiliary Variable (GPAV) approach and are demonstrated to be second-order accurate and unconditionally stable with respect to the system energy through comprehensive stability analyses and error tests. Two algorithms make use of Artificial Compressibility (AC) to update pressure and a solenoidal constraint for the magnetic field. Numerical simulations are provided to illustrate theoretical results and demonstrate …

Advances In Differentially Methylated Region Detection And Cure Survival Models, Daniel Ahmed Alhassan

Doctoral Dissertations

"This dissertation focuses on two areas of statistics: DNA methylation and survival analysis. The first part of the dissertation pertains to the detection of differentially methylated regions in the human genome. The varying distribution of gaps between succeeding genomic locations, which are represented on the microarray used to quantify methylation, makes it challenging to identify regions that have differential methylation. This emphasizes the need to properly account for the correlation in methylation shared by nearby locations within a specific genomic distance. In this work, a normalized kernel-weighted statistic is proposed to obtain an optimal amount of "information" from neighboring locations …

Essays On Conditional Heteroscedastic Time Series Models With Asymmetry, Long Memory, And Structural Changes, K C M R Anjana Bandara Yatawara

Doctoral Dissertations

"The volatility of asset returns is usually time-varying, necessitating the introduction of models with a conditional heteroskedastic variance structure. In this dissertation, several existing formulations, motivated by the Generalized Autoregressive Conditional Heteroskedastic (GARCH) type models, are further generalized to accommodate more dynamic features of asset returns such as asymmetry, long memory, and structural breaks. First, we introduce a hybrid structure that combines short-memory asymmetric Glosten, Jagannathan, and Runkle (GJR) formulation and the long-memory fractionally integrated GARCH (FIGARCH) process for modeling financial volatility. This formulation not only can model volatility clusters and capture asymmetry but also considers the characteristic of long …

Near-Ir Spectroscopic Analysis Of The Primary Volatile Composition Of Long And Short-Period Comets, Younas Khan

Doctoral Dissertations

"Comets are among the most well-preserved objects that formed in the protosolar nebula ∼4.5 Gyr ago. Hence, they are important for understanding various aspects of the formation, evolution, and habitability of the solar system. Multiple primary volatiles (molecules directly sublimating into the coma from the nucleus) emit via rovibrational transitions in the near-IR, providing opportunities to calculate their abundances. To date, only ∼50 comets have been characterized for their primary volatiles, with the short-period Jupiter-family comets (JFCs) being significantly underrepresented. In contrast, hundreds of comets have been sampled at optical/UV wavelengths, primarily for the composition of daughter species, leading to …

Fluorination Of Rubisco-Mimetic Co2 Capture Systems. Theoretical And Experimental Studies Of Ammonium Ion Acidity Depression And Carbamylation, Brian Michael Jameson

Doctoral Dissertations

"RuBisCO-inspired CO₂ capture and release (CCR) systems featuring amines have been developed for the purpose of reversable CO₂ capture from air. The enzyme active site consists of the tetrapeptide sequence Lys-Asp-Asp-Glu. The Lys sidechain amine undergoes carbamylation and an Mg²⁺ cation stabilizes the resulting carbamate. The N^a-acyl-lysinyl-aspratyl-aspartyl-glutamide (Lys-Asp-Asp-Glu, KDDE) peptide featured maximum capture at pH ≈ 10; a pH region too high for Mg²⁺ ions to remain in solution. This work aims to achieve pKa depression by introducing fluorine in the proximity of the lysine’s sidechain amine. A comparative analysis was made of butylamine, …

Recurrent Event Data Analysis With Mismeasured Covariates, Ravinath Alahakoon Mudiyanselage

Doctoral Dissertations

"Consider a study with n units wherein every unit is monitored for the occurrence of an event that can recur with random end of monitoring. At each recurrence, p concomitant variables associated to the event recurrence are recorded with q (q ≤ p) collected with errors. Of interest in this dissertation is the estimation of the regression parameters of event time regression models accounting for the covariates. To circumvent the problem of bias and consistency associated with model's parameter estimation in the presence of measurement errors, we propose inference for corrected estimating functions with well-behaved roots under additive measurement errors …

Applied Geochemistry, Geochronology And Biostratigraphy: Case Studies From The 38th Parallel Structures In Missouri And Orange Basin, Offshore Western South Africa, Marissa Kay Spencer

Doctoral Dissertations

"The unique alignment of the Decaturville, Crooked Creek, and Weaubleau geological structures in central Missouri, three of nine known such structures along the 38th parallel in Illinois, Missouri, and Kansas, has puzzled geoscientists for decades. Research using palynology (palynomorphs and particulate organic matter) and radiometric dating of impact spherules were used to constrain age and a relationship between these enigmatic structures and infer their paleoenvironmental conditions. Novel melting damages, unique to impact, were documented in the palynomorphs in all the three structures. Early Ordovician acritarchs with melted processes correlate with ⁴⁰Ar-³⁹Ar stepwise heating age of impact spherules …

The Application Of Statistical Modeling To Identify Genetic Associations With Mild Traumatic Brain Injury Outcomes, Caroline Schott

Masters Theses

"Traumatic brain injury (TBI) is a growing health concern, with millions of TBI diagnoses in the United States each year. The vast majority of TBI diagnoses are mild traumatic brain injuries (mTBI), which can be challenging to manage due to variation in symptoms and outcomes. Most individuals with mTBI successfully recover quickly, but a small subset has a delayed recovery. Although the factors that contribute to this variation in recovery are not clearly understood, it is possible that genetic differences may play a role. Very few studies have investigated the association between single nucleotide polymorphisms (SNPs) with mTBI outcomes and …

Computer Vision In Adverse Conditions: Small Objects, Low-Resoltuion Images, And Edge Deployment, Raja Sunkara

Masters Theses

"Computer vision based on deep learning is an essential field that plays a significant role in object detection, image classification, semantic segmentation, instance segmentation, and other applications. However, these models face significant challenges in adverse conditions, such as small objects, low-resolution images, and edge deployment. These challenges limit the accuracy and efficiency of computer vision algorithms, making it difficult to obtain reliable results.

The primary objective of this thesis is to assess the performance of deep learning- based computer vision models in challenging conditions and provide viable solutions to overcome the obstacles. The study will specifically address three key challenges, …

Mat: Genetic Algorithms Based Multi-Objective Adversarial Attack On Multi-Task Deep Neural Networks, Nikola Andric

Masters Theses

"Vulnerability to adversarial attacks is a recognized deficiency of not only deep neural networks (DNNs) but also multi-task deep neural networks (MT-DNNs) that attracted much attention in the past few years. To the best of our knowledge, all multi-task deep neural network adversarial attacks currently present in the literature are non-targeted attacks that use gradient descent to optimize a single loss function generated by aggregating all loss functions into one. On the contrary, targeted attacks are sometimes preferred since they give more control over the attack. Hence, this paper proposes a novel targeted multi-objective adversarial ATtack (MAT) based on genetic …

Investigation Of Defect Production And Displacement Energies In Wurtzite Aluminum Nitride, Sean Anderson

Masters Theses

"Aluminum Nitride is an active element of sensors that monitor the performance and well-being of the nuclear reactors due to its piezoelectric properties. Yet, the variations of its properties under irradiation are largely unexplored. We report the results of the molecular dynamics simulations of the structural changes in AlN under irradiation via the knock-on atom technique. By creating and evolving the irradiation cascades due to energetic particle interaction with the atom of the crystalline lattice we determine the rate of the defect production as a function of the deposited energy. Further, we determine a displacement energy, a key characteristic that …