Digital Commons Network^™

Aqueous Geochemistry Drives Microbial Cu, Fe, And Zn Uptake Rates In Yellowstone, A Continental Hydrothermal System, Eva Carolina Andrade-Barahona

Graduate Theses & Non-Theses

Microbial uptake of trace metal cofactors such as copper (Cu), iron (Fe), and zinc (Zn) is governed by biogeochemical processes in hydrothermal systems where metal bioavailability varies widely. In situ microbial metal uptake rates were quantified by applying metal stable isotope probing (MSIP) in the Yellowstone hydrothermal system across diverse geochemical conditions in hydrothermal springs. The findings in these studies revealed that pH exerts a dominant influence on microbial copper uptake rate, also enhanced by increased Cu²⁺ ion availability and dissolved oxygen. Microbial iron uptake, in contrast, displayed a broad tolerance to environmental variability, occurring across a pH range of …

Considerations For Cottonseed Oil As A Feedstock For Renewable Fuels, John Elmore

Theses and Dissertations

As the world population grows and the standard of living improves in developing countries, global energy demand will continue to rise, with energy use in the developing world expected to increase dramatically more than the per capita reductions in developed countries from efficiency improvements. Nearly a third of the total global energy demand is used for transportation, resulting in a substantial contribution to greenhouse gas (GHG) emissions. While the demand for energy rises, initiatives and regulations are underway to mitigate the amount of GHG emissions to Earth’s atmosphere. As efforts progress in industry, governments, and society to reduce the total …

Study On Vehicle-Pedestrian Interaction Autonomy By Risk Potential Theory, Riku Kikuta

Theses and Dissertations

Vehicle–pedestrian interaction is a critical aspect of autonomous vehicle (AV) development, as socially acceptable AVs must account for pedestrian intention and behavior. Risk Potential (RP) theory provides a framework to build human-like AVs by modeling expert driver risk perception, but conventional RP models treat pedestrians as static obstacles and neglect their dynamics. This dissertation extends RP theory by incorporating pedestrian velocity and orientation into three new models: the RP velocity model, the RP related-velocity model, and the RP Pedestrian Potential Position (PPP) model. These models were implemented in the Navigating All Terrains Using Robotic Exploration (NATURE) autonomy stack and tested …

Electrochemical Detection Of No And Ca2+ During Cold Atmospheric Plasma Treatment Of Acute Wounds: Sensor Selectivity And Stability In The Plasma-Bio-System, Jonathan E. Thomas, Kristina Pattison, Suneel Kumar, Gagana Karkada, Duncan Trosan, Aunic Goodin, Jason Rainone, Dnyaneshwari Rananavare, Vandana Miller, Francois Berthiaume, Katharina Stapelmann

Kimmel Cancer Center Faculty Papers

Cold atmospheric plasmas (CAP) are a versatile tool in medical applications like wound healing. Its therapeutic benefits are partially attributed to the generation of biologically active reactive oxygen and nitrogen species (RONS). Characterization of RONS, however, typically only occurs after treatment. Here we report the first real-time in situ detection of CAP-generated nitric oxide (NO), and the simultaneous detection of cellular calcium ions (Ca²⁺) release using electrochemical sensors during CAP treatment of murine wounds. In vivo, NO rose rapidly within the first minute of CAP treatment but accumulated less overall than in PBS, reflecting reactions with wound-bed targets. In situ …

Technological Disruption And Regulatory Response: The Case Of Decentralised Finance, Jakub Wisła, Jolanta Bartoszewska

Journal of Banking and Financial Economics

This article examines responses to the regulatory challenges posed by decentralised finance (DeFi), a fast-evolving domain of blockchain-based financial innovation. It investigates the factors shaping divergent regulatory strategies, with a focus on the European Union’s comprehensive cryptoasset framework and selected comparative insights. Adopting a qualitative legal methodology – combining doctrinal-functional analysis, multivocal literature review, and two case studies – the authors explore how regulatory responses are influenced by three key variables: legal tradition, the financial function performed by blockchain-based solutions, and the level of technological and institutional autonomy. The case studies – Bitcoin as a payment instrument and cryptoassets as …

Quantifying Benefits Of Biochar With Variable Absorption Capacity As A Partial Cement Replacement In Concrete, Benjamin Shannon

Theses and Dissertations

Extensive research has been conducted on biochar-incorporated concrete. However, no concrete mixture design guideline is currently available for implementing biochar incorporation in practice. The objective of this study was to correlate biochar absorption capacity with the compressive strength of biochar-incorporated concrete, to quantify the benefits of biochar and develop mix design guidelines. Biochar with varying absorption capacities was incorporated into concrete at 10%, 20%, and 40%. Strength and moisture loss were recorded over the 90-day curing period of the biochar-incorporated concrete. Results revealed three main findings: (1) in 10%, 20%, and 40% biochar mixes, the normalized strengths ranged from 0.65–0.85, …

Physics-Informed Neural Network For Maximum Detectable Distance Estimation In Mobile Gamma Spectrometry, Nancy A. Ibrahim

Theses and Dissertations

Accurate estimation of the Maximum Detectable Distance (MDD) is critical for environmental remediation, nuclear incident response, and public safety. Conventional approaches assume stationary detectors and rely on computationally intensive simulations, limiting their applicability for mobile, real-time surveys. Mobile gamma spectrometry introduces additional complexities due to detector motion, variable acquisition times, and heterogeneous backgrounds. This study addresses the central question of how effectively a Physics-Informed Neural Network (PINN) can estimate MDD for mobile gamma spectrometry, while maintaining both accuracy and computational efficiency under dynamically changing environmental conditions. A multi-phase approach was employed, combining field data collection, computational modeling, and operational tool …

A Case Study On Redesigning Classroom Activities And Assessments For Generation Z Students, Sushma Shrinivasan

Theses and Dissertations

This dissertation investigates the dynamic interplay between pedagogical strategies, learner diversity, and emerging educational technologies through three interconnected studies. Study 1 compares Traditional instruction, Problem-Based Learning (PBL), and Simulation-Based Learning (SBL), revealing that while PBL and SBL enhance student performance—particularly PBL—their impact on perceived learning varies. Notably, SBL reduced perceived learning despite strong outcomes, underscoring the affective and metacognitive complexities of active learning. Study 2 examines the role of demographic factors such as gender, ethnicity, employment, and first-generation status, finding no significant main effects but identifying a key two-way and three-way interactions, suggesting that instructional effectiveness is influenced by the …

Dem Simulations For Tractive Performance Of Rigid Wheel In Granular Media, Aidan Noah Dickerson

Theses and Dissertations

Accurately predicting vehicle mobility in granular media is essential for evaluating off-road mobility in agriculture, defense, and planetary exploration. Traditional empirical models often fail in capturing complex micromechanics of soil deformation, especially under dynamic conditions such as high slips and maneuvering. This study demonstrates the value of the discrete element method (DEM) in modeling wheel-soil interactions with higher fidelity. Using Altair EDEM and pre-calibrated GEMM materials, simulations were conducted for a range of forward (-5.9% to 54.8%) and side slip angles (3°, 6°, 12°) in dry sand. DEM enabled detailed analysis of sinkage, traction forces, and lateral loads, revealing trends …

Exploring The Impact Of Incorporating Artificial Intelligence Integrated Systems In The Workplace, Catherine Cruz Agosto Noda

Theses and Dissertations

This study focuses on assessing the impact of incorporating systems integrated with in the workplace by assessing the constructs of usability, cognitive load, and trust. The constructs are assessed by generation and experience level to determine which factors are relevant in a workplace setting. A workplace scenario was simulated by asking participants to complete tasks where they assumed the role of a warehouse manager assigned with assessing two scheduling systems – one with artificial intelligence and one without artificial intelligence. The participants were presented with three tasks of increasing difficulty for each prototype. Both quantitative and qualitative measures were used …

Optimizing Military Fighter Jet Selection: A Decision Analysis Approach For Nuclear-Capable Aircraft, Eni Kelechi Ofong

Theses and Dissertations

This research investigates the strategic decision-making process involved in selecting a nuclear-capable fighter aircraft for NATO (North Atlantic Treaty Organization) nations in Europe. In adaptation to the continuously changing technology landscape and the necessity for enhanced deterrence capabilities, this study evaluates three potential aircraft: the legacy Panavia Tornado (PA-200), the widely deployed F-16 Fighting Falcon (F-16), and the advanced F-35 Lightning II (F-35). Each platform presents distinct advantages and limitations regarding operational performance, mission adaptability, cost-effectiveness, and long-term sustainability. To systematically assess these alternatives, the study employs various decision analysis frameworks, including Multi-Criteria Decision Analysis (MCDA), single dimensional value function …

Concerted Rattling-Induced Strong Anharmonicity And Phonon Coherence Lead To Ultralow Glasslike Thermal Conductivity In Tlagte, Shantanu Semwal, Yi Xia, Chris Wolverton, Koushik Pal

Mechanical and Materials Engineering Faculty Publications and Presentations

Ordered crystalline compounds exhibiting ultralow and glass-like thermal conductivity are both fundamentally and technologically important, where phonon quasi-particles dominate their heat transport. Understanding the microscopic mechanisms that govern such unusual transport behavior is necessary to unravel the complex interplay of crystal structure, phonons, and collective excitations of these quasi-particles. Here, we use state-of-the-art first-principles calculations based on quantum density functional theory to investigate the origin of experimentally measured unusually low and glassy thermal conductivity in semiconducting TlAgTe that possesses disconnected chains of Tl atoms within its three-dimensional crystalline framework made up of distorted AgTe4 tetrahedra. Utilizing a unifying framework of …

Power Resilience In Utah's Water Sector: A Survey Of Stakeholder Practices, Preferences And Potential, Tyler Christopher Peterson

Theses and Dissertations

Drinking water and wastewater services are vulnerable to disruptions because they rely heavily on the electric grid. As a result, power outages can lead to water outages, creating cascading failures that compromise sanitation, firefighting, healthcare, and daily routines. Although an important topic, there are little to no studies of water and wastewater power resilience at a geographic or state level. In this study we investigate the extent of existing backup power and renewable energy integration as well as the motivations and barriers around their power resilience. We collect our data through semi-structured interviews with staff at 19 urban and rural …

Mechanical Quality Of Hemp Fiber As Influenced By Tillage, Cover Crop, And Nitrogen Management In Regenerative Organic Systems, Parinaz Heydar, Alyssa Pierce, Gabriella Fioravanti, Ronald Kander

School of Design and Engineering Papers

Industrial hemp (Cannabis sativa L.) is an emerging crop for renewable fiber materials. For farmers, finding a balance between agronomic performance and economic return is crucial, especially when targeting specific markets like the textile industry, which values not just fiber quantity, but overall quality. This field study, conducted at the Rodale Institute in Kutztown, Pennsylvania, assessed the effects of tillage (till vs. no till), cover crop (with cover vs. no cover), and nitrogen (N) rate (0, 50, 100, 150 kg ha⁻¹) on hemp fiber yield, N concentrations in leaf and stalk, and mechanical performance under regenerative organic conditions. Fiber mechanical …

Parameter Informed Reinforcement Learning For Vehicle System Identification, Nathan Schaff

Doctoral Dissertations and Master's Theses

Accurate system identification is essential for modeling and controlling vehicle dynamics. This dissertation explores the application of Parameter Informed Reinforcement Learning (PIRL) as a novel approach to system identification (SYSID). PIRL integrates prior system knowledge, such as physical parameters, into reinforcement learning (RL) frameworks to improve estimation accuracy. The study begins with an overview of traditional SYSID methods and then introduces PIRL as a modification of standard RL. The research applies PIRL to short-period aircraft dynamics, demonstrating its effectiveness in both offline and online learning frameworks. The dissertation then further explores PIRL’s utility in an indirect model reference adaptive control …

Evaluation Of Internal Field In Ppln And Studies On Qpm Shg Efficiency Factor, Prasath Rk Mr

Theses and Dissertations

Periodically Poled Lithium Niobate (PPLN) crystals have attracted interest in optoelectronics and nonlinear optics. The response to the applied electric field is determined by their larger electro-optic and nonlinear optical coefficients. An internal electric field exists in congruent PPLN crystals due to its defects. Its evaluation is important in controlling the electro-optical behavior. A simple nondestructive diffraction method is proposed to estimate the internal electric field present in the congruent lithium niobate crystal.

Due to the presence of an unrelaxed internal field, the as-poled sample acts as an index grating. When a light is incident on such a sample, it …

In-Situ Investigations Of Calcium-Magnesium-Aluminosilicates (Cmas) Infiltration Effects On Thermal Barrier Coatings Under Extreme Environments Replicating Jet Engines, Zachary Stein

Doctoral Dissertations and Master's Theses

Calcium-magnesium-aluminosilicate (CMAS) particulates, such as sand or volcanic ash, are ingested by gas turbine jet engines during operation. When operating within high abundance regions, these particulates negatively interact and degrade the high temperature thermal barrier coatings (TBC) protecting underlying superalloy turbine blades vital to engine operation. These CMAS particulates melt within the engine and infiltrate into the ceramic coatings. In electron-beam physical vapor deposited (EB-PVD) TBCs, the CMAS within the intercolumnar gaps stiffens the coatings and causes thermomechanical induced high stress concentrations, risking crack formation. While molten, the CMAS thermochemically alters and destabilizes the coating, also risking coating failure. Premature, …

Pria: Process Risk Identification And Analysis, Raymond Fasano

Nuclear Engineering ETDs

This dissertation proposes and evaluates two approaches, with-in a Process Risk and Analysis (PRIA) framework, that advance data-driven hazard discovery in complex cyber-physical systems. First, a transferability-based clustering method groups subspace-identified segments into operational modes, prioritizing cross-predictive performance over raw feature proximity. Second, a Neural Switching Linear Dynamical System (NeuralSLDS) model anchors learning in identified state-space models with Bayesian residuals, calibrated predictive uncertainty, and context-aware operating mode transitions. Together, these methods generate physics-informed, probabilistic world models that can support model-in-the-loop analysis of hazardous trajectories. The approach is validated on a simulated point-kinetics reactor and a centrifugal chiller dataset, demonstrating coherent …

Dynamic Urban Air Mobility Systems Modeling And Simulation, Amer M. Ibrahim

Tennessee State University Alumni Theses and Dissertations

The use of electrical vertical takeoff and landing (eVTOL) aircraft to provide efficient, high-speed, on-demand air transportation within a metropolitan area is an increasingly popular topic, which is expected to bring fundamental changes to cities. The concept of Urban Air Mobility (UAM) has the potential to make meaningful door-to-door trip time savings compared with other transportation. The capability to manage many of these eVTOL aircraft safely in a congested urban area presents an unprecedented challenge in air traffic management. In order to enable safe and efficient autonomous on-demand free flight operations in UAM, a computational guidance algorithm with collision avoidance …

Bilstm-Based Zero-Aware Traffic Forecasting Using Lidar Data For Intersection Safety, Md Atiqur Rahman Mallick

Tennessee State University Alumni Theses and Dissertations

LSTM retains information from long-term data and is highly effective in generating time-based forecasts. Recently, BiLSTM has enhanced the precision of traffic predictions by assimilating information from both antecedent and subsequent directions via bidirectional data flow. BiLSTM demonstrates exceptional efficacy in the analysis of long-term traffic data. Our study presents a custom forecasting model that leverages advanced LiDAR sensor technology in combination with state-of-the-art deep learning techniques to improve road conditions. Eight LiDAR sensors were strategically deployed along the 26th Clarksville Pike corridor to collect high-resolution traffic data—including vehicle speed and count/flow—over the period from September 1, 2024 to November …

Experimental And Theoretical Characterization Of Molten Salt Thermal Conductivity, Jacob C. Numbers

Theses and Dissertations

Molten salts form an ideal heat transfer fluid for advanced energy generation systems, including molten salt reactors (MSR). Accurate characterization of molten salt thermal conductivity is needed to confidently predict transient thermal behavior and optimize salt properties. Measurements are hindered by salts' challenging material properties, which---in the case of the needle probe device---induced unaccounted physical changes that limited its accuracy and repeatability. Sparse thermal conductivity data in general is exacerbated by a limited fundamental understanding of molecular energy transfer in liquids. This work extends the experimental capacity for compositional studies using the needle probe and proposes a theoretical model for …

Development And Validation Of 2nn-Meam Interatomic Potential For Sc And Al-Sc Alloys Thermodynamics Solidification And Intermetallic Ordering, Avik Mahata

Mechanical Engineering Faculty Publications

We present a second-nearest-neighbor Modified Embedded Atom Method (2NN–MEAM) potential for Scandium (Sc) and Aluminum-Scandium (Al–Sc) alloys that unifies cohesive, thermodynamic, and solidification behavior within a single transferable framework. The Sc component accurately reproduces cohesive energy, lattice constants, defect energetics, and the experimental melting point obtained from two-phase coexistence, demonstrating reliable description of both hcp and liquid phases. The Al–Sc binary interaction parameters were fitted using the L1₂–Al₃Sc reference and benchmarked against first-principles and calorimetric data. The potential reproduces the strong negative formation enthalpy of Al₃Sc (–0.45 eV atom⁻¹), correct relative stability …

Time Series Modeling Of Land Use And Land Cover Classification Using Remote Sensing, Ahmed A. F. Abd El Hamed, Fawzi H. Zarzoura, Mahmoud El-Mewafi

Mansoura Engineering Journal

Understanding land use / land cover changes is essential for planning sustainable development. It represents the transformation of the land due to human activities, which is related to sustainable development that aims to achieve the needs of the present generations without affecting the future. Land use / Land cover is studied in Al Alamein region, northern Egypt, with supervised classification methods using satellite images from Landsat 8 and Sentinel - 2A in 2023 and analyzes the accuracy assessment, which shows Maximum likelihood is better in both sensors achieving overall accuracy (91.80% and 91.02%) and kappa coefficient (0.814 and 0.8799). Then …

Nonlinear Excitation Control Of Multimachine Systems Via The Invariant-Set Design, Ehab Bayoumi

Mechanical Engineering

Power grids are inherently vulnerable to many uncertainties. All power networks are prone to instability because of the uncertainties inherent in the operation of power systems. Rotor-angle instability is a challenging issue, and if not properly managed, could give rise to cascading failures and even blackouts. This paper addresses the generator excitation system’s state feedback sliding mode control (SMC). The global system is divided into multiple subsystems to achieve decentralized control. A disturbance is defined as the influence of the system as a whole on a specific subsystem. The state-feedback controller is to be designed taking into account the disturbance …

Patent Searching With Uspto, Derwent Innovation And Lens.Org, Ibis Anette Moreno-Lozano

Day Family Research Lab Workshop Series

No abstract provided.

Improving Road Safety Through Multimodal Deep Learning For Driver Drowsiness Detection, Hadel A. Hussain, Mohammed A. Subhi, Ahmed S. Al Tmeme, Ahmed D. Radhi, Marwan Ali Albahar

Iraqi Journal for Computer Science and Mathematics

One of the most common causes of road accidents globally is driver drowsiness and it needs solutions that are reliable and can be applicable in numerous real-life situations. We present this paper with the aim of developing a deep-learning system that is capable of reliably detecting drowsiness in diverse and varied conditions across different drivers, environments, and sensor types. Our system is known as Multimodal Attention Network (MMAN), which combines information of eye and head movement, heart-rate and breathing pattern, and vehicle-dynamics signal. MMAN has a gradient-reversal layer that enables the layer to be domain-adaptive such that it does not …

Deep Learning-Based Fog-Cloud Approach Intrusion Detection System In Iomt, Yahya Rbah, Mohammed Mahfoudi, Mohammed Fattah, Younes Balboul, Said Mazer, Moulhime Elbekkali

Iraqi Journal for Computer Science and Mathematics

The Internet of Medical Things (IoMT) creates an interconnected environment linking humans, devices, sensors, and systems, enhancing healthcare services through advanced technologies. Nonetheless, these IoMT devices are susceptible to cyberattacks, which can endanger patient safety and healthcare services. To identify and mitigate cyberattacks in IoMT, techniques such as threat intelligence, log monitoring, and intrusion detection systems are employed. As attackers evolve their strategies, there is a growing trend towards leveraging artificial intelligence to achieve more predictive and accurate attack detection. Since IoMT devices are inherently low-power, they require minimal computing resources. Existing intrusion detection systems are generally trained in the …

Multitaskvenationnet: A Multi-Task Deep Neural Network With Strip Pooling And Hybrid Upsampling For Leaf Vein Segmentation, Ishak Ariawan, Ahmad Ashari, Moh. Edi Wibowo

Iraqi Journal for Computer Science and Mathematics

Leaf vein segmentation is a critical task in plant phenotyping and species classification, yet it remains challenging due to the hierarchical, curvilinear nature of veins and interference from complex backgrounds. Existing methods face three key limitations. First, they lack directional context modeling, leading to blurred vein boundaries and the omission of fine venation. Second, they fail to effectively capture global dependencies, limiting semantic coherence across spatial regions. Third, they do not incorporate explicit mechanisms for detecting vein discontinuities, which is essential for complete topological understanding. To address these challenges, we propose MultiTaskVenationNet (MTV-Net), a multi-task deep segmentation framework that integrates …

Analytical Assessment Of Pedestrian Crashes On Low-Speed Corridors, Therezia Matongo, Deo Chimba

Civil and Architectural Engineering Faculty Research

This study presents a comprehensive statewide analysis of pedestrian-involved crashes recorded in Tennessee between 2002 and 2025. We evaluated the influence of roadway, traffic, environmental, and socioeconomic factors on pedestrian crash frequency and severity with substantial components focused on lighting impacts including dark and nighttime. A multi-method analytical framework was implemented, combining descriptive statistics, non-parametric tests, regression analysis, and advanced machine learning techniques including the Adaptive Neuro-Fuzzy Inference System (ANFIS) and the gradient boosting model (XGBoost). Results indicated that dark and nighttime conditions accounted for a disproportionate share of severe crashes—fatal and serious injuries under dark conditions reached over 40%, …

Portable Skin Imaging Light-Box For Clinical Grade Skin Scans, Kayandra Lewis, Cayden Skidmore, Komi Atitsogbe Golo

Senior Design Project For Engineers

This project focuses on designing and developing a modular, portable skin-imaging light box to improve the consistency and accuracy of smartphone-based dermatological imaging. As AI-driven skin assessment tools grow in capability, a major limitation remains the variability in lighting, angle, and color fidelity in user-captured photos. To address this challenge, the team created a fold-flat, low-cost light box that attaches securely to a wide range of smartphones and provides uniform, high-CRI illumination suitable for clinical-grade analysis. Research into lighting technologies, human factors, smartphone specifications, and AI diagnostic tools guided the engineering decisions, ensuring the design aligned with real-world telemedicine and …