Digital Commons Network^™

Two Essays On Out-Of-Town Home Buyers, Kamrul H. Talukdar

Graduate Studies Theses and Dissertations 2026

This dissertation analyzes the price premia paid by Out-of-Town (or non-local) home buyers. The first essay investigates the role of social connectedness in the price premia paid by non-local buyers in the residential housing market. Using over 74,000 residential transactions from Orange and Seminole counties, Florida between 2016 and 2019 and exploiting the Social Connectedness Index (SCI) constructed based on Facebook friendship links, I show that non-local buyers who come from regions which are more socially connected to the purchase location pay about 1.8% to 2.1% lower premia compared to those coming from less connected regions. This effect is attributed …

Exploring Barriers And Facilitators Of Mental Health Treatment For Law Enforcement Officers: The Impact Of Police Occupational Culture, April Reed

Graduate Studies Theses and Dissertations 2026

Prior research has explored the impact of police culture on mental health stigma among law enforcement, however, a deeper understanding about how different aspects of police culture may inhibit or facilitate mental health treatment utilization is needed to inform policy and practice. This dissertation explores the relationship between police culture and mental health using a qualitative research design. Twenty-five (n=25) law enforcement officers from a county sheriff’s office in Central Florida were interviewed and participant observations were conducted during a three-month period. The present study sought to address the following research questions: What are the experiences of the job and …

Online Risk And Harm For Marginalized Users: How Social Influence Amplifies Or Mitigates Vulnerability, Tangila Islam Tanni

Graduate Studies Theses and Dissertations 2026

Social media has reshaped how people connect, communicate, and influence one another, yet these environments also create harms that disproportionately affect marginalized users. Participation in online communities can expose users to identity-based harassment, emotional distress, and the normalization of harmful attitudes, shaping identity, well-being, and participation online and offline. Prior work has documented many forms of online harm, yet less is understood about how harmful norms and behaviors are reinforced across different forms of social media interaction, from private direct messages to online communities. Guided by the Social Ecological Model, this dissertation investigates how online harms toward marginalized users emerge …

“I Call For The Resurgence And Reclamation Of Our Indigenous Ways”: Institutional Landscapes, Resistance, And The Experiences Of Mmir Advocates, Sara Tehrani

Graduate Studies Theses and Dissertations 2026

Indigenous Peoples across Turtle Island experience disproportionately high rates of violence and homicide compared to other racial groups. Rooted in coloniality and sustained by Western institutions, this epidemic is recognized as the Missing and Murdered Indigenous Relatives (MMIR) crisis. In response, Indigenous women have mobilized the MMIR Movement to raise awareness and advocate for institutional change. Although scholarship on MMIR has expanded, limited research has explored the experiences of MMIR advocates. This study interrogates the institutional landscapes that shape MMIR advocacy and explores the resistance strategies advocates employ to address the crisis. Using reflexive thematic analysis, this study examines semi-structured …

Integrated Design And Trade Study Of A Sub-Ambient Ammonia Fuel Storage And Delivery System For Narrow-Body Commercial Aircraft, Ethan Taylor

Graduate Studies Theses and Dissertations 2026

This study develops an integrated design framework for a sub-ambient anhydrous-ammonia fuel storage and delivery system for narrow-body commercial aircraft, using the Boeing 737 MAX 8 as the baseline platform. Ammonia was selected because it contains no carbon in its molecular structure, benefits from an established global production and distribution infrastructure, and offers more practical storage conditions than several alternative carbon-free energy carriers. However, its relatively low energy density, toxicity, material-compatibility requirements, and combustion hazards require substantial modifications to power conventional commercial aircraft fuel storage and delivery systems.

The study proposes an integrated design and initial analysis of a sub-ambient …

Teachers’ Perceptions Of School Leaders’ Role In Implementing The Four Pillars Of Community Schools For Improving Student Achievement, Adrian Irwin Thomas

Graduate Studies Theses and Dissertations 2026

This study examined teachers’ perceptions of school leaders’ roles in implementing the Four Pillars of Community Schools to support Student achievement in under-resourced schools. The four pillars of Community Schools- Integrated Student Support, Expanded Learning Time and Opportunities, Family and Community Engagement, and Collaborative Leadership and Practices- served as the conceptual framework for the study. Distributed Leadership Theory and Epstein’s Framework of Parental Involvement provided the theoretical lens that guided the interpretation of the findings. The study explored teachers’ perceptions of leadership practices associated with the four pillars and identified leadership strategies perceived as most effective for sustaining the community …

Memory-Efficient Acceleration For Emerging Applications Via Hardware/Software Co-Design, Shilin Tian

Graduate Studies Theses and Dissertations 2026

Emerging artificial-intelligence and data-intensive scientific workloads increasingly face a memory wall: irregular access patterns and large intermediate data volumes make data movement, rather than arithmetic, the primary constraint on performance and energy efficiency. This dissertation develops a memory-centric hardware/software co-design methodology that jointly reshapes algorithms, architectures, and dataflows to retain frequently reused data on chip. The methodology is demonstrated through three accelerators and an RTL design tool. VITA replaces multi-head attention in vision-transformer-based 3D human mesh recovery with hardware-friendly average pooling and maps the resulting operators to a reconfigurable datapath, achieving 5.05-fold and 69.12-fold speedups over a state-of-the-art GPU and …

Puff, Puff, Pass? Examining Cannabis Use Among Black American Adults, Christopher B. Walker

Graduate Studies Theses and Dissertations 2026

In the United States, cannabis has become one of the most widely used controlled substances due to its increase in social acceptance, the growing number of states legalizing it for medical and non-medical purposes, and the expansion of consumption methods.  However, little is known about the modes of cannabis use chosen by Black American adults.  This population is of importance due to existing research suggesting their increased risk of developing cannabis use disorder compared to their White counterparts and their underrepresentation in existing literature.  The goal of this study is to examine cannabis use among Black adults in the U.S., …

Investigation On Selective Catalytic Reduction For Retrofit Of Commercial Aviation Aircraft Engines, Connor M. Wall

Graduate Studies Theses and Dissertations 2026

As the aviation industry continues to grow, the ever-increase of emissions from the sector becomes a growing concern. While the International Civil Aviation Organization (ICAO) set a goal of net-zero carbon emissions by 2050, there are other emissions like contrails and NOx that must still be addressed. Selective Catalytic Reduction (SCR) has been used in the transportation and power generation industry for over two decades and has been an effective solution for NOx reduction. Even with the success SCR has had in other industries, its capabilities in the aviation industry have been trivially investigated. Aircraft engines pose an unique challenge …

Volumetric Fluorescence Microscopy For High-Throughput And High-Sensitivity Imaging: From Single Molecules To Tissues, Le-Mei Wang

Graduate Studies Theses and Dissertations 2026

Fluorescence microscopy is an indispensable tool in the biological sciences, enabling researchers to investigate intricate subcellular structures, particularly for volumetric studies. However, conventional optical microscopy for volumetric imaging remains fundamentally constrained by imaging speed and throughput. To bypass traditional serial z-scanning, we introduce an axially scan-free method using a phase layer cake to modulate the system's point spread function. This approach projects volumetric information onto a 2D plane in a single shot, offering high flexibility in tuning axial depth alongside simultaneous multicolor imaging with high spatial resolution and sensitivity. This dissertation divides these technical advancements into cellular and tissue imaging …

Two Papers Exploring Cognitive Fit Theory And Data Visualization In Accounting, Kelly Wellman

Graduate Studies Theses and Dissertations 2026

This dissertation examines how data visualization design influences judgment and decision making in accounting using cognitive fit theory as a unifying framework. As visualization tools such as dashboards, Excel, Tableau, and Power BI become increasingly prevalent, understanding which design choices improve performance has become critical. The first paper provides a structured literature review of cognitive fit theory from 1991 through 2025, synthesizing research across accounting and related disciplines and tracing its evolution from early graph vs tables comparisons to mor recent work incorporating task complexity, individual differences, and design-specific features. The review identifies key gaps, including limited attention to difference …

Advanced Ysz/Si(B)Cn And Bnnt/Si(B)Cn Ceramics Matrix Composites For Extreme Environments In Hydrogen Combustion, Yiting Wang

Graduate Studies Theses and Dissertations 2026

The growing demand for carbon-neutral energy conversion has accelerated the development of hydrogen-fueled gas turbine systems, which operate at significantly higher temperatures and more chemically aggressive environments than conventional natural gas turbines. To meet these stringent requirements, ceramic matrix composite (CMC) materials consisting of yttria-stabilized zirconia (YSZ) fiber reinforced Si(B)CN ceramic matrix were developed. To further enhance in-plane heat dissipation, thermal stability, thermal shock resistance, and thermal cycling performance, a Si(B)CN/Boron Nitride Nanotubes (BNNT) nanocomposite coating was incorporated onto the YSZ/Si(B)CN composites. Microstructural characterization confirmed the formation of a continuous Si(B)CN ceramic matrix reinforced with uniformly distributed BNNTs. The resulting …

Switching Things Up: Investigating The Costs Of Switching Between Tasks Of Varying Interdependence And Factors That Influence These Transitions, Taylor A. Wilhelmy

Graduate Studies Theses and Dissertations 2026

Though researchers have indicated that there is a high probability teams will transition between tasks of varying interdependence (Benishek & Lazzara, 2019; Mesmer-Magnus et al., 2016), there is a need to further examine this idea (Smith-Jentsch, 2015; Mesmer-Magnus et al., 2016) as few have actually studied it. Expanding upon Moon et al. (2004), this study examines the costs associated with transitioning between two tasks of varying levels of interdependence (i.e., pooled and team interdependence; Saavedra et al., 1993), how these costs vary depending on the order the tasks are engaged while examining how team cognition (i.e., transactive memory systems) and/or …

Human And Ai Support In Business Simulations: A Quasi-Experimental Mixed Methods Study Of Performance At Scale, Sara Willox

Graduate Studies Theses and Dissertations 2026

Large classes change what instruction looks like. In hybrid business courses with high enrollment, it becomes harder to respond to individual students, and performance can suffer as a result. This study looked at what happens when that gap is addressed in different ways during an eight-week business simulation at the University of Central Florida. Six course sections were divided into three study groups. One group worked without support, one received instructor guidance, and one used AI tools that included a course search system and generative responses. Student outcomes were based on weekly profit and loss recorded in Sim Companies. The …

Careless Responding: Testing The Theory Of Vigilance, Rusty Wilson

Graduate Studies Theses and Dissertations 2026

Careless responding (CR) has been identified as a threat to the psychometric integrity of cognitive and non-cognitive tests, with much of the current research focusing on the identification and removal of carelessness from dataset. While this research has proved fruitful in improving data quality, there has been a recent push to move towards preventing carelessness as opposed to post-hoc removal, which harms statistical power. However, the most common prevention strategy to prevent carelessness (pre-survey warnings) has shown equivocal effects. Additionally, the literature lacks an agreed upon theory to explain why carelessness occurs. To address these gaps I introduce theory from …

How Did Covid-19 Affect Volunteer And Donor Management For Human Services Agencies? What Are The Lessons For Future Response?, Nina Yon

Graduate Studies Theses and Dissertations 2026

The COVID-19 pandemic created unprecedented challenges for human services agencies, disrupting the interdependent systems of volunteer engagement and donor support essential to nonprofit sustainability. This study integrates insights from literature, theory, and empirical analysis to examine how nonprofit organizations adapted their volunteer and donor management strategies during this prolonged crisis. Drawing on Contingency Theory and Resource Dependence Theory (RDT), the research explores how organizational structures and strategies evolved in response to shifting environmental conditions, health mandates, and resource constraints. Using a multiple-case qualitative design, data was collected from semi-structured interviews with 20 leaders representing five Central Florida human services agencies, …

Michigan Academician Volume 50, Issue 2

Michigan Academician

Volume 50, Issue 2 - Abstract Issue

Upconversion Photoluminescence In Wsse Alloy Monolayer Under Uniaxial Tensile Strain, Shrawan Roy, Jie Gao, Xiaodong Yang

Mechanical and Aerospace Engineering Faculty Research & Creative Works

The optical responses of monolayer transition metal dichalcogenides (1L-TMDs) can be tuned effectively by using mechanical strain. In this work, the tuning of upconversion photoluminescence (UPL) emission in 1L-WSSe alloy by applying uniaxial tensile strain is investigated. When the uniaxial tensile strain is changed from 0 % to 1.02 %, the peak position of UPL emission has a redshift of around 25.6 nm, and the UPL intensity goes up with an exponential function of the applied strain as the upconversion energy difference is varied from −197 meV to −131 meV. The sublinear power dependence for UPL emission in 1L-WSSe alloy …

Physics-Constrained Generative Adversarial Networks For Dimensionality Reduction In Optimization, Samuel Sisk, Xiaosong Du

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Electric vertical takeoff and landing (eVTOL) aircraft make a unique form of urban air mobility due to their low noise, zero emission, and precision control. To maximize efficiency, high-fidelity simulation-based multidisciplinary design optimization discovers the optimal balance among subsystems within an eVTOL. However, conventional multidisciplinary design optimization is computationally intensive due to excessive high-fidelity model evaluations. Moreover, complex nonlinear constraints deteriorate optimization efficiency and convergence. While surrogate models enable efficient design optimization, surrogate modeling suffers in large-scale applications and surrogate-based optimization still has to deal with nonlinear constraints. To address these challenges, the authors' previous work proposed physics-constrained generative adversarial …

Tomo-Piv Study Of Baseline Flow Structures Behind A Strut Injector, Josiah Mcdermott, Connor Bell, Davide Viganò

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Stabilizing combustion in scramjet engines is a formidable challenge due to the small-time scales afforded for air-fuel mixing. Numerous studies in this area have demonstrated the potential of strut-style platforms for fuel injection and mixing enhancement, which remains an active area of research. In the Aerodynamics Research Laboratory at Missouri S&T, a strut-style injector system has recently been installed. In this study, we characterize the baseline flow structures behind this platform absent fuel injection. The wake generated by a strut itself has an appreciable impact on the resulting air-fuel mixing, which motivates its characterization. In future studies, this characterization will …

Optimal Takeoff Trajectory Prediction Of Electric Drones Based On A Fully Automated Optimal Experimental Design Method, Jiachen Wang, Dheeraj Paramkusham, Xiaosong Du

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Electric vertical takeoff and landing (eVTOL) aircraft is attracting great interest as a viable solution to promote urban aerial mobility with promising flexibility as well as emission reductions. However, the low specific energy of the current battery is still a strong constraint on the range and endurance of eVTOL flights, especially considering the significant power demands during the takeoff process. Engineering design optimization permits promising solutions for the minimum takeoff energy consumption but can be computationally intensive due to iteratively evaluating simulation models. Surrogate-based design optimization is efficient but still relies on optimization iterations which prohibit real-time decision-making. To fill …

Impact Of Dispersed Crystalline Domains On Lithium-Ion Conductivity In Amorphous Li2.99ba0.005ocl Electrolytes, Emmanuel Olugbade, Junquan Ou, Leon Shaw, Jonghyun Park

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Solid-state electrolytes promise safer, high-energy batteries, yet ionic transport is limited by structural heterogeneity and interfacial resistance. We combine hydrothermal synthesis and molecular dynamics (MD) to determine how dispersed crystallinity and interfacial orientation govern lithium-ion conduction in barium-doped anti-perovskite Li_2.99Ba_0.005OCl. Structural and thermal analyses identify a largely amorphous matrix with embedded nano crystallites, and MD captures the same short-range order and dispersion seen experimentally. Electrochemical impedance spectroscopy separates high amorphous-phase conductivity from a pellet-scale response dominated by interfacial limitations, consistent with direct-current polarization. Cyclic voltammetry indicates a broad electrochemical stability window. We quantify transport in crystalline …

Design, Construction, And Initial Testing Of A Oxy-Acetylene Testing Facility, Blake Bowman, Davide Viganò

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Thermal Protection Systems (TPS) are critical for atmospheric re-entry and hypersonic flight vehicles, yet ground-based evaluation of TPS materials remains challenging due to the cost, complexity, and limited availability of large arc-jet and inductively coupled plasma (ICP) facilities. Oxy-acetylene testing provides a low-cost and accessible alternative for preliminary material screening, sensor development, and fundamental studies of material response under high heat-flux conditions. This paper presents the design, construction, and initial validation of the High-Enthalpy Acetylene Testing (HEAT) facility at Missouri University of Science and Technology. The facility incorporates a modular experimental architecture, independently controlled oxygen and acetylene mass-flow systems, and …

Supersonic Wind Tunnel Free Stream Turbulence Characterization Using 2-Point Focused Laser Differential Interferometry, Joseph Villarreal, Joshua Gary, Davide Vigano

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Non-intrusive laser-based diagnostics, such as Two-Point Focused Laser Differential Interfer-ometry (2-FLDI), play a crucial role in modern aerodynamic research by enabling simultaneous measurements of density and velocity in compressible flows. A 2-FLDI system has been developed and implemented for the Missouri S&T Supersonic Wind Tunnel to characterize free stream turbulence fluctuations and free stream convective velocity. Design choices that enabled the 2-FLDI to overcome low turbulence to measure free stream velocity are detailed. The free stream velocity measurements are validated against previous particle image velocimetry data, showing good agreement. Analysis of normalized velocities and density-based turbulence intensities found that the …

Temperature Compensation In Loop And Patch Fss Strain Sensors: Analysis And Experimental Validation, Swathi Muthyala Ramesh, Kristen M. Donnell

Electrical and Computer Engineering Faculty Research & Creative Works

Frequency selective surfaces (FSSs) are arrays of conductive elements or apertures that exhibit frequency-dependent reflection and transmission properties. Their electromagnetic response is influenced by geometry and environmental conditions, making them attractive for wireless strain-sensing applications. However, temperature variations can produce frequency shifts similar to those caused by strain, reducing measurement accuracy. This work investigates the effects of intrinsic temperature compensation on two common FSS unit cell geometries—loop and patch—through comprehensive simulation analysis. The results show that loop-based cells offer superior thermal stability, while patch-based cells provide greater strain sensitivity, illustrating the trade-off between thermal robustness and mechanical responsiveness. A patch-type …

Large Language Models For Neurology: A Mini Review, Donald C. Wunsch, Daniel B. Hier

Electrical and Computer Engineering Faculty Research & Creative Works

Large language models have the potential to transform neurology by augmenting diagnostic reasoning, streamlining documentation, and improving workflow efficiency. This Mini Review surveys emerging applications of large language models in Alzheimer's disease, Parkinson's disease, multiple sclerosis, and epilepsy, with emphasis on ambient documentation, multimodal data integration, and clinical decision support. Key barriers to adoption include bias, privacy, reliability, and regulatory alignment. Looking ahead, neurology-focused language models may develop greater fluency in biomedical ontologies and FHIR standards, improving data interoperability and supporting more seamless collaboration between clinicians and AI systems. Two future developments have the potential to be particularly impactful: (1) …

Evaluation Of Multiple Generative Large Language Models On Neurology Board-Style Questions, Mohammad Almomani, Vijaya Valaparla, James Weatherhead, Xiang Fang, Alok Dabi, Chih Ying Li, Peter Mccaffrey, Dan Hier, Jorge Mario Rodríguez-Fernández

Electrical and Computer Engineering Faculty Research & Creative Works

Objective: To compare the performance of eight large language models (LLMs) with neurology residents on board-style multiple-choice questions across seven subspecialties and two cognitive levels. Methods: In a cross-sectional benchmarking study, we evaluated Bard, Claude, Gemini v1, Gemini 2.5, ChatGPT-3.5, ChatGPT-4, ChatGPT-4o, and ChatGPT-5 using 107 text-only items spanning movement disorders, vascular neurology, neuroanatomy, neuroimmunology, epilepsy, neuromuscular disease, and neuro-infectious disease. Items were labeled as lower- or higher-order per Bloom's taxonomy by two neurologists. Models answered each item in a fresh session and reported confidence and Bloom classification. Residents completed the same set under exam-like conditions. Outcomes included overall and …

Safety Aware Continual Reinforcement Learning-Based Output Tracking Control Of Nonlinear Continuous-Time Systems, Irfan Ganie, Sarangapani Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

An output feedback (OF)-based control scheme utilizing both a scalable multilayer neural network (MNN) observer and actor–critic MNN via integral reinforcement learning (IRL)/adaptive dynamics programming (ADP) approach for a class of nonlinear systems with output constraints is introduced. The proposed observer, critic, and actor MNN weight updates are derived using a singular value decomposition (SVD) of MNN activation function gradient along with output error, Bellman and control input errors, respectively. Next, the approach incorporates continual learning (CL), utilizing a penalty function in the weight update laws for both actor–critic MNNs to consolidate knowledge from previous tasks and enhance learning in …

Multi-Parameter Optimization And Adaptive Temperature Compensation For Fbg Strain Sensors In Wide-Temperature-Range Aerospace Applications, Ruling Zhou, Jiacheng Yu, Yutang Dai, Jianguan Tang, Minghong Yang, Farhan Mumtaz

Electrical and Computer Engineering Faculty Research & Creative Works

Accurate strain measurement in cryogenic fuel pipelines is crucial for ensuring the structural integrity and reliability of rocket engine systems operating under extreme thermal conditions. Fiber Bragg grating (FBG) sensors show significant potential for such applications; however, their inherent temperature-strain cross-sensitivity limits performance over wide temperature ranges. This research presents an enhanced compensation strategy combining multi-parameter optimization with temperature-zone-specific adaptation to improve the accuracy and stability of FBG-based strain sensing in harsh aerospace environments. Four special steel substrate materials including S03, S06, S07, and 1Cr18Ni9Ti, were evaluated using strain transfer theory and thermo-mechanical coupling simulations. Genetic algorithms optimized key design …

Safe Optimal Control Framework For Cooperative Manipulation Of Objects In Human–Robot Teams, Irfan Ganie, Sarangapani Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

This article introduces a distributed deep neural network (NN)-based adaptive control framework for cooperative object manipulation in human–robot teams with unknown agent dynamics by using three distinct multilayer NN observers (MNNOs). The first observer, termed the reference point estimator, enables each robotic agent to estimate the object's reference center using consensus-based learning, even without direct access to global reference trajectories. The second observer, referred to as the human force-to-trajectory estimator, uses human-applied forces to infer the intended position, velocity, and acceleration of the object, enabling real-time estimation of human intent. Together, these two observers allow distributed estimation of human-intended motion. …