Digital Commons Network^™

Exploring The Self-Assembly Of Functional Bis-Urea Macrocycles: M-Terphenyl Bis Urea Macrocycles And Triphenylamine Bis-Urea Macrocycles, Gamage Isuri Pramodya Wijesekera

Theses and Dissertations

Porous materials have gained significant attention due to their diverse applications in catalysis, separation, and molecular storage. Among them, self-assembled macrocycles represent a unique class of functional materials that leverage non-covalent interactions to form well-defined architectures with pores of controlled size. This thesis explores the design, synthesis, and self-assembly of bis-urea macrocycles in both solid-state and solution-phase environments, with a particular focus on supramolecular polymerization mechanisms and the emergence of kinetically trapped states.

The first chapter of this thesis presents a detailed overview of self-assembled porous materials, categorizing them based on pore dimensions and discussing their significance in catalysis, separation, …

Two Dimensional Van Der Waals Magnet, Cheongheon Lee

Theses and Dissertations

Conventional charge-based memory has reached its limits in improving energy efficiency while scaling down size. Consequently, memory utilizing 2D magnetic materials has emerged as an alternative. 2D Van der Waals (VdW) magnets are ultrathin magnets with unique properties that make them optimal for this purpose. Utilizing the weak interlayer coupling via VdW interaction has enhanced the possibility of integrating diverse materials to create heterostructures. The integration of spintronics requires not only stable magnetization but also an effective switching mechanism. Various external influences have been experimentally tested, such as the proximity effect, external magnetic field, gate voltage, and temperature dependence. This …

Physics Oriented Deep Learning For Material Prediction And Generation, Nihang Fu

Theses and Dissertations

The discovery of new materials is critical to advancing various industries, but traditional experimental methods for materials discovery remain slow and resource-intensive. Recent advances in machine learning (ML), particularly deep learning (DL), have greatly improved and accelerated two main aspects of modern computational material discovery: material design (e.g., material generation) and material screening (e.g., property prediction). However, a key challenge remains: standard ML models often struggle to perform domain-specific tasks effectively. Incorporating domain-specific knowledge, specifically the underlying physics of materials, into ML/DL models is key to improving the accuracy and reliability of material generation and prediction models.

This dissertation discusses …

On A Conjecture On Covering Systems And An Irreducibility Question On Sparse 0,1-Polynomials, Alexandros Kalogirou

Theses and Dissertations

In 1952, H. Davenport posed the problem of determining a condition on the minimum modulus $m_0$ in a finite distinct covering system that would imply that the sum of the reciprocals of the moduli in the covering system is bounded away from 1. In 1973, P.~Erd\H os and J.~Selfridge indicated that they believed that $m_0$ > 4 would suffice. We provide a proof that this is the case in Chapter 2. Chapters 3 and 4 are dedicated to showing that $0,1$-polynomials of high degree and few terms are irreducible with high probability. Formally, let $k\in\mathbb{N}$ and $F(x)=1+\sum_{i=1}^kx^{n_i}$, where $ 0

In Vivo Analysis Of Fe-S Cluster Assembly And Iron Homeostasis In Escherichia Coli, Dexter Mclaurin Reasons

Theses and Dissertations

Iron-sulfur (Fe-S) clusters are an essential cofactor for a wide range of cellular processes, and their assembly and storage require tight regulation.

In Escherichia coli (E. coli), there are two pathways of Fe-S cluster assembly, the Isc and the Suf pathways. The Isc pathway is used under good growth conditions, and the Suf pathway is used under iron starvation and oxidative stress conditions. Once the cluster has been assembled on the scaffold protein of either pathway, it is transferred to Fe-S cluster trafficking proteins. In E. coli, the monothiol glutaredoxin GrxD and the BolA-type proteins BolA and IbaG …

Some Likelihood-Based Methods For Clustering Functional Data, Tong Shan

Theses and Dissertations

The analysis of functional data is an increasingly relevant part of statistics. The exploratory data analytic method of cluster analysis plays a very important role in different fields. Over the years, researchers have developed many clustering approaches, striving to achieve more accurate and efficient clustering. In Chapter 1, we aim to improve the accuracy of our outcome when clustering functional data. To achieve this goal, we use a predictive likelihood function which serves as an objective function to optimize in order to determine the most appropriate clusters. To optimize the objective function over the space of clustering partitions, we produce …

On Berge Pancyclicity For Uniform Hypergraphs, Teegan Cole Bailey

Theses and Dissertations

An $n$-vertex graph $G$ is \textit{hamiltonian} if it contains a length $n$ cycle as a subgraph. A stronger notion of hamiltoncity is pancyclicity. A graph $G$ is \textit{pancyclic} if $G$ contains a cycle of length $k$ for every $3\leq k \leq n$. Dirac's classical result on hamiltonicity states that if an $n$-vertex graph $G$ has minimum degree $\delta(G)\geq \frac{n}{2}$, then $G$ is hamiltonian. Under the same minimum degree condition as Dirac, J. A. Bondy showed that $G$ must also be pancyclic or the exceptional graph $K_{\frac{n}{2}, \frac{n}{2}}$. In 1971, Bondy proposed a so called meta-conjecture claiming that \textit{``almost any nontrivial …

Effect Of Growth Conditions On The Performance Of Vertically Conducting Beta-Ga2o3 Diodes On 4h-Sic Substrate By Mocvd, Nifat Jahan Nipa

Theses and Dissertations

This thesis highlights the critical influence of doping strategies, specifically co-delta doping with silicon (Si) and indium (In), on improving the structural quality and device performance of β-Ga₂O₃-based Schottky barrier diodes (SBDs). To achieve better thermal management, β-Ga₂O₃ thin film was grown on bulk 4H-SiC substrates using the Metal-Organic Chemical Vapor Deposition (MOCVD) technique, renowned for its precise control over composition, thickness and doping profile. The ultra-wide bandgap (UWBG), high critical breakdown field and low turn-on resistance of β-Ga₂O₃ make it a strong candidate for next-generation power electronics and short-wavelength detection in extreme environments. However, the presence of structural defects …

Artificial Intelligence In Sport Management: A Systematic Review, Scale Development And Validation, And Implications, Kemardo Tyrell

Theses and Dissertations

The democratization of intelligent systems and their ubiquitous presence across the sport industry have created an urgent need to understand the current environment and how stakeholders perceive artificial intelligence (AI) as it reshapes decision-making, engagement, and organizational design. This three-manuscript dissertation conceptualizes artificial intelligence as a contested domain shaped by stakeholder meaning-making, consumer perception, and shifts in organizational practice. The first manuscript provides a systematic review of AI in sport management using the PRISMA framework, mapping how AI has been conceptualized as a methodological tool or contextual innovation across the sport industry segmentation (performance, production, and promotion). The second manuscript …

Causes And Effects Of Science Tutor Attrition At The Colleges Of Education In The Northern Zone Of Ghana: A Qualitative Study, Collins D. Amadu, Rose Dognia, Solomon Boachie, Taarique-Ahmad Yahaya

Journal of Global Education and Research

The study investigated the causes and effects of science tutor attrition in the colleges of education in the Northern Zone of Ghana. Three science and mathematics colleges were used for the study. The study adopted a qualitative approach with 9 participants who volunteered to take part. The interview guide was the sole instrument for data collection. The interviews were conducted through face-to-face and phone calls. The recorded conversations were transcribed and categorized into themes. The study found that the science tutor attrition rate was caused by several factors. These factors could be grouped into unmet expectations of the tutors and …

Effectiveness Of Digital Learning Materials On Students' Achievement In Science: A Meta-Analysis, Bingo L. Aligo, Maricar S. Prudente

Journal of Global Education and Research

Researchers have been examining educational resources and content to enhance and support the learning experience. As technology continues to transform the way we learn and access information, digital learning materials have become increasingly popular in modern education. This study looked at how different kinds of digital learning materials affected science students’ learning achievement. The moderator variables used were grade level (kindergarten, primary, intermediate, and secondary), subject (biological sciences, general science, and physical sciences), and length of exposure (1 to 3 weeks, 4 to 6 weeks, and 10 to 12 weeks). A total of 14 studies were considered, involving 789 students …

Digital Stress Scale (Dsc): Development And Psychometric Validation Of A Measure Of Stress In The Digital Age, Agathi Argyriadi, Dimitra Katsarou, Athina Patelarou, Kalliopi Megari, Evridiki Patelarou, Stiliani Kotrotsiou, Konstantinos Giakoumidakis, Shabnam Abdoola, Evangelos Mantsos, Efthymia Efthymiou, Alexandros Argyriadis

All Works

(1) Background: The integration of digital technologies such as electronic health records (EHRs), telepsychiatry, and communication platforms has transformed the mental health sector a lot compared to in previous years. While these tools enhance service delivery, they also introduce unique stressors. Despite growing concerns, there is no validated instrument specifically designed to measure the digital stress experienced by mental health professionals. (2) Methods: This study involved the development and psychometric validation of the Digital Stress Scale (DSC). The process included item generation through a literature review and qualitative interviews, expert panel validation, and a two-phase statistical evaluation. Exploratory Factor Analysis …

The Impact Of The Flipped Learning Approach On Student Engagement In A High School Chemistry Classroom, Alana Lyn Hicks

Theses and Dissertations

This mixed-methods action research study investigated the impact of the flipped classroom approach on student engagement and attitudes within a science classroom. Data was collected using student-reported responses on the Classroom Engagement Inventory, Motivated Strategies for Learning Questionnaire, student journal entries, teacher reflective journals, and an observation tracking chart kept by the classroom teacher. Findings revealed that the flipped classroom model significantly increased affective and cognitive engagement among students in a larger class size, as well as for medium-achieving students and girls. These results suggest that while the flipped classroom has the potential to enhance engagement, its effectiveness is influenced …

Explainable Process Recommendation Through Multi-Contextual Grounding Of Dynamic Multimodal Process Knowledge Graphs, Revathy Venkataramanan

Theses and Dissertations

Can I eat this food or not? Is this food suitable for diabetes and why? Which AI pipeline is best suited for a given task and dataset? How should an end-to-end pipeline be constructed? These questions differ from factual question-answering tasks. Recipes and AI pipelines are processes consisting of several entities interacting with each other. A recipe consists of ingredients, cooking methods, and their interactions, while an AI pipeline includes datasets, preprocessing techniques, models, hyperparameters, tasks, and results. Each entity must be analyzed individually, and collective inferencing is performed to derive the final decision. This decision-making process, known as compositional …

The Tur Nout Effect: Challenging The Median Voter Theorem, George Thomas Rogers

Theses and Dissertations

The classical Median Voter Theorem (MVT) predicts that, in a two-party system with majority rule, candidates will converge toward the ideological center to capture the median voter. This logic, grounded in spatial models of political competition, assumes full voter participation and fails to account for the growing ideological polarization in modern democracies. This thesis reevaluates the MVT by incorporating probabilistic turnout into a utility-based model of voter behavior. It theorizes that turnout is shaped not only by ideological proximity but also by expressive motivations, including both strong affinity and strong aversion to candidates. A novel measure of turnout utility is …

A Spatial Scan Statistic For Group Testing Data, Vincent Onyame

Theses and Dissertations

Group testing involves pooling specimens from multiple individuals and offers an efficient means to surveil low-prevalence pathogens, but poses challenges for spatial cluster detection when only pooled results are observed. In this thesis, we develop a spatial scan statistic tailored to group-testing data with variable pool sizes. The statistic compares a null hypothesis of a homogeneous infection rate across all clusters to an alternative hypothesis that infection probabilities differ inside and outside a candidate cluster, with both models fitted by maximum likelihood estimation. We approximate the null distribution of the maximum likelihood ratio test via Monte Carlo simulation.

Through a …

Bayesian Inference Of Fitness Landscapes Via Tree-Structured Branching Processes, Xiang Ge Luo, Jack Kuipers, Kevin Rupp, Koichi Takahashi, Niko Beerenwinkel

Faculty, Staff and Student Publications

Motivation: The complex dynamics of cancer evolution, driven by mutation and selection, underlies the molecular heterogeneity observed in tumors. The evolutionary histories of tumors of different patients can be encoded as mutation trees and reconstructed in high resolution from single-cell sequencing data, offering crucial insights for studying fitness effects of and epistasis among mutations. Existing models, however, either fail to separate mutation and selection or neglect the evolutionary histories encoded by the tumor phylogenetic trees.

Results: We introduce FiTree, a tree-structured multi-type branching process model with epistatic fitness parameterization and a Bayesian inference scheme to learn fitness landscapes from single-cell …

Βiv Spectrin Abundancy, Cellular Distribution And Sensitivity To Akt/Gsk3 Regulation In Schizophrenia, Jessica Di Re, Michela Marini, Syed Ibrar Hussain, Aditya K Singh, Akshaya Venkatesh, Musaad A Alshammari, Tahani K Alshammari, Abdul-Rizaq Ali Hamoud, Ali Sajid Imami, Zahra Haghighijoo, Nickolas Fularcyzk, Laura Stertz, Derek Hawes, Angela Mosebarger, Jordan Jernigan, Claire Chaljub, Ralda Nehme, Consuelo Walss-Bass, Anton Schulmann, Marquis P Vawter, Robert Mccullumsmith, Robert D Damoiseaux, Agenor Limon, Demetrio Labate, Michael F Wells, Fernanda Laezza

Faculty, Staff and Student Publications

Schizophrenia (SCZ) is a complex psychiatric disorder with unclear biological mechanisms. Spectrins, cytoskeletal proteins linked to neurodevelopmental disorders, are regulated by the AKT/GSK3 pathway, which is implicated in SCZ. However, the impact of SCZ-related dysregulation of this pathway on spectrin expression and distribution remains unexplored. Here, we show that βIV spectrin protein levels were reduced in neurons of the dorsolateral prefrontal cortex in SCZ postmortem samples compared to healthy control (HC) from the Human Brain Collection Core (HBCC). To investigate potential links between βIV spectrin and the AKT/GSK3 pathway, we analyzed the PsychEncode dataset, revealing elevated SPTBN4 and AKT2 mRNA …

Adtnorm: Robust Integration Of Single-Cell Protein Measurement Across Cite-Seq Datasets, Ye Zheng, Daniel P Caron, Ju Yeong Kim, Seong-Hwan Jun, Yuan Tian, Florian Mair, Kenneth D Stuart, Peter A Sims, Raphael Gottardo

Faculty, Staff and Student Publications

Cellular Indexing of Transcriptomes and Epitopes by Sequencing (CITE-seq) enables paired measurement of surface protein and mRNA expression in single cells using antibodies conjugated to oligonucleotide tags. Due to the high copy number of surface protein molecules, sequencing antibody-derived tags (ADTs) allows for robust protein detection, improving cell-type identification. However, variability in antibody staining leads to batch effects in the ADT expression, obscuring biological variation, reducing interpretability, and obstructing cross-study analyses. Here, we present ADTnorm, a normalization and integration method designed explicitly for ADT abundance. Benchmarking against 14 existing scaling and normalization methods, we show that ADTnorm accurately aligns populations …

Powerest: Statistical Power Estimation For Spatial Transcriptomics Experiments To Detect Differentially Expressed Genes Between Two Conditions, Lan Shui, Anirban Maitra, Ying Yuan, Ken Lau, Harsimran Kaur, Liang Li, Ziyi Li

Faculty, Staff and Student Publications

Recent advancements in spatial transcriptomics (ST) have significantly enhanced biological research in various domains. However, the high cost for current ST data generation techniques restricts the large-scale application of ST. Consequently, maximization of the use of available resources to achieve robust statistical power for ST data is a pressing need. One fundamental question in ST analysis is detection of differentially expressed genes (DEGs) under different conditions using ST data. Such DEG analyses are performed frequently, but their power calculations are rarely discussed in the literature. To address this gap, we developed PoweREST, a power estimation tool designed to support the …

1d Thermoembolization Model Using Ct Imaging Data For Porcine Liver, Rohan Amare, Danielle Stolley, Steve Parrish, Megan Jacobsen, Rick R Layman, Chimamanda Santos, Beatrice Riviere, Natalie Fowlkes, David Fuentes, Erik Cressman

Faculty, Staff and Student Publications

Innovative therapies such as thermoembolization are expected to play an important role in improving care for patients with diseases such as hepatocellular carcinoma. Thermoembolization is a minimally invasive strategy that combines thermal ablation and embolization in a single procedure. This approach exploits an exothermic chemical reaction that occurs when an acid chloride is delivered via an endovascular route. However, comprehension of the complexities of the biophysics of thermoembolization is challenging. Mathematical models can aid in understanding such complex processes and assisting clinicians in making informed decisions. In this study, we used a Hagen-Poiseuille 1D blood flow model to predict the …

The Sports-Betting Market: A Road To Sports Betting As Viable Investing, Tyler Gottlieb

Vanderbilt Journal of Entertainment & Technology Law

Since its legalization, sports betting has experienced rapid growth, both in terms of economic output and expansion into more states. The current system of sports betting in the United States requires individuals to place bets using a sportsbook. The sportsbook sets the lines on every bet. If an individual wins their bet, the sportsbook pays them money according to the listed odds. If an individual loses their bet, the sportsbook keeps the amount staked. Sportsbooks set lines in a way to ensure that on average, they make money on every bet. This system has been widely accepted, often based on …

Stability Analysis Of The Eulerian-Lagrangian Finite Volume Methods For Nonlinear Hyperbolic Equations In One Space Dimension, Yang Yang, Jiajie Chen, Jing Mei Qiu

Michigan Tech Publications

In this paper, we construct a novel Eulerian-Lagrangian finite volume (ELFV) method for nonlinear scalar hyperbolic equations in one space dimension. It is well known that the exact solutions to such problems may contain shocks though the initial conditions are smooth, and direct numerical methods may suffer from restricted time step sizes. To relieve the restriction, we propose an ELFV method, where the space-time domain was separated by the partition lines originated from the cell interfaces whose slopes are obtained following the Rakine-Hugoniot junmp condition. Unfortunately, to avoid the intersection of the partition lines, the time step sizes are still …

A Discrete-Time Adaptive Sliding Mode Controller For A Multicopter With A Suspended Payload, John Helzer

Department of Mechanical and Materials Engineering: Dissertations, Theses, and Student Research

This thesis presents a Discrete-time Adaptive Sliding Mode Controller (DASMC) for control of a multicopter with a suspended payload. DASMC is designed to stabilize the multicopter at a desired position while minimizing the load oscillations induced by a significant hanging payload. The proposed DASMC minimizes the need for system-specific parameters like tunable gains and improves robustness to both external disturbances and model uncertainties compared with existing controllers. The controller is designed for direct digital implementation on a variety of multicopter platforms with considerations like discrete-time design, adaptive gain shrinking, and saturation handling. When deployed on a real multicopter in an …

Extubation Decisions With Predictive Information For Mechanically Ventilated Patients In Icu, Guang Cheng, Jingui Xie, Zhichao Zheng, Haidong Luo, Oon Cheong Ooi

Research Collection Lee Kong Chian School Of Business

Weaning patients from mechanical ventilators is a crucial decision in intensive care units (ICUs), significantly affecting patient outcomes and the throughput of ICUs. This study aims to improve the current extubation protocols by incorporating predictive information on patient health conditions. We develop a discrete-time, finite-horizon Markov decision process with predictions of future state to support extubation decisions. We characterize the structure of the optimal policy and provide important insights into how predictive information can lead to different decision protocols. We demonstrate that adding predictive information is always beneficial, even if physicians place excessive trust in the predictions, as long as …

Multi-Period Portfolio Allocation: A One-Shot Stochastic Optimization Approach, Peng Liu, Chyng Wen Tee, Xiaofei Xu

Research Collection Lee Kong Chian School Of Business

Multi-period portfolio optimization is a central problem in finance, yet it is computationally intractable for traditional dynamic programming methods due to the curse of dimensionality. This paper develops a tractable and theoretically grounded 'one-shot' stochastic optimization framework that recasts the sequential decision problem into a single, high-dimensional optimization task. Our approach models the predictive distribution of factor returns using Gaussian Processes (GPs), allowing it to capture complex, non-linear market dynamics. We make three primary contributions. First, for the special case of a linear GP kernel, we derive an analytical solution for the optimal portfolio path, providing a clear economic interpretation …

Enhancing Phenotyping Accuracy For Selection Of Urochloa Spp. Tolerant Genotypes To Red Spider Mite (Oligonychus Trichardti), Paula Espitia-Buitrago, José Miguel Cotes Torres, Luis Miguel Hernández, Juan Andres Cardoso, Frank Chidawanyika, Rosa N. Jauregui

All Peer-Reviewed Publications

The red spider mites are a major biotic limitation to productivity for Brachiaria (Urochloa spp.) grasses in tropical Eastern Africa, causing severe economic losses mainly in the dry seasons. However, due to the lack of reports of integrated pest management strategies, genetic resistance can play a crucial role in Brachiaria-based livestock systems, minimising the impact of this pest. The objective of this study was to develop and validate a methodology for accurately categorising resistance responses in Urochloa genotypes to identify potential sources of resistance to the Western Kenya red spider mite Oligonychus trichardti (Meyer 1974). Accordingly, 25 genotypes of Urochloa …

Meeting Report On An Integrated Research Agenda For Mosquito-Borne Arboviruses, Angela K. Ulrich, Nicolina M. Moua, Alison Mack, Natsuko Imai-Eaton, J. Erin Staples, Angela J. Mehr, Julia T. Ostrowsky, Tabitha Leighton, Ana Cehovin, Petra C. Fay, Josephine P. Golding, Emma Maynard, Luke Alphey, Diana P. Rojas Alvarez, Lark L. Coffey, Nuno R. Faria, Rafael Maciel-De-Freitas, Kevin Maringer, Kris A. Murray, Henrik Salje, Rosemary Sang, Pedro F.C. Vasconcelos, Yee Sin Leo, Steven P. Sinkins, Jocelyne Neto De Vasconcelos, Samuel K. Dadzie, Eva Harris, Thais H. Dos Santos, Raman Velayudhan

All Peer-Reviewed Publications

The emergence and re-emergence of mosquito-borne arbovirus (MBV) diseases pose a rapidly expanding global health threat fueled by the convergence of multiple ecologic, economic, and social factors, including climate change, land use, poverty, deficiencies of water storage and sanitation, and limitations of vector control programs. On December 6, 2023, the Wellcome Trust and the University of Minnesota's Center for Infectious Disease Research and Policy held a meeting titled "An integrated approach to mosquito-borne arboviruses: a priority research agenda."The meeting comprised presentations, panels, and facilitated discussions aimed at describing the state of the field, highlighting recent accomplishments, identifying novel strategies, and …

Mixed Quantum/Classical Theory Approach To Rotationally Inelastic Molecular Collisions Implemented On A Quantum Computer, Jonathan Andrade-Plascencia, Tamila Kuanysheva, Dulat Bostan, Brian K. Kendrick, Dmitri Babikov

Chemistry Faculty Research and Publications

All elements of a quantum algorithm for calculations of rotationally inelastic molecule + atom scattering within the framework of a mixed quantum/classical theory are outlined. In this approach, the rotational motion of the molecule is described quantum mechanically using the time-dependent Schrödinger equation, while the scattering process of two collision partners is treated classically. The matrix of potential coupling is precomputed on a classical processor, whereas the quantum hardware is used to propagate the system of coupled equations for the rotational state-to-state transitions. All quantum circuits needed for practical implementation of the algorithm are presented. First, the quantum codes written …

Self-Efficacy And Mathematical Identities In A Rural Georgia Middle School Classroom, Gavin Wilson

Theses and Dissertations

Even into adulthood, some people have a strong resentment of math. Their beliefs toward their mathematical abilities have created a fear of the subject, resulting in an avoidance of anything math-related. These thoughts and beliefs regarding math and mathematical abilities begin somewhere along an individual’s academic journey in a math classroom. This action research study, using a mixed-methods approach, attempted to uncover the origins and development of self-efficacy and mathematical identities in rural eighth-grade students. Furthermore, this study explored ways that a teacher can influence these sets of beliefs and examined the impact on academic performance. The framework used to …