Digital Commons Network^™

Effects Of Climate Change On Fungal Diversity And Function In Streams, Syeda Tasfia Imam

Masters Theses

"This study investigated the impact of climate change, particularly drought, on leaf decomposition and associated fungal and macroinvertebrate communities in freshwater ecosystems. With climate change, streams may experience altered hydrology, leading to shifts in community composition and biogeochemical processes. Fungi decompose organic matter, facilitate nutrient cycling, and support food webs. However, drought can disrupt these processes by reducing water availability, causing declines in fungal diversity and activity. I examined leaf breakdown and associated biota in 13 stream sites across varying hydrologic conditions, from perennial to ephemeral flow patterns. Flow duration varied during the 8-week study. Leaf breakdown was significantly related …

Transfection Of Ionizable Lipid Nanoparticles On Raw 264.7 And Mda-Mb-231, Lavanya Bhargava

Masters Theses

"This thesis investigates the preparation, characterization, and transfection efficiency of various ionizable lipid nanoparticles (LNPs) formulated for the delivery of mRNA encoding enhanced green fluorescent protein (EGFP) in RAW 264.7 macrophages and MDA-MB-231 breast cancer cell lines. The ionizable cationic lipid studied are ALC-035, C12-200, C14-4, PPZ-A10, DLin-MC3-DMA. The study addresses the need for effective gene delivery systems to provide a safe and versatile platform that protects and transports nucleic acids into target cells. LNPs were synthesized using microfluidic mixing methods, incorporating lipid components such as the cationic lipids, DSPE, DOPE, cholesterol and PEG lipids to achieve controlled particle sizes, …

Fetal Acidosis Prediction Using Attention Enhanced Convolutional Neural Networks, Anusha Adhikari

Masters Theses

This study explores the integration of spectral mixtures of fetal heart rate (FHR) and uterine contraction (UC) signals to enhance the prediction of fetal acidosis, utilizing the CTU-CHB dataset. Several classification models were trained using two distinct oversampling techniques and inputs, demonstrating that models incorporating spectral mixtures significantly outperform those using raw signals. These models, particularly when combined with convolutional neural networks (CNNs) and attention mechanisms, achieved a notable F1-score of 0.98, with the highest model achieving an area under the Receiver Operating Characteristic (ROC) curve of 0.95. The research employs a variety of techniques including short-time Fourier transform and …

Characterization Of The Microstructural Changes Of Zrb2 Under Heavy Ion Irradiation For Molten Salt Reactor Applications, Narrie Loftus

Masters Theses

A primary challenge in finding suitable materials for Molten Salt Reactors (MSRs) lies in identifying those that concurrently exhibit high corrosion resistance, stability at elevated temperatures, resistance to radiation, and chemical compatibility with molten salts. 11B-enriched zirconium diboride (ZrB₂) is a potential candidate for applications in MSRs due to its unique combination of properties, including high melting point, high thermal conductivity, and resistance to corrosion in harsh environments. This ultra-high temperature ceramic (UHTC) has exhibited stability under extreme conditions, making it an attractive material for components within MSRs.

The microstructural response of ZrB₂ under heavy ion irradiation …

On Optimizing Sensor Data Collection, Processing, And Storage For Industrial Additive Manufacturing, Steven Thompson

Masters Theses

The widespread adoption of digital data management methods for transformative technologies, such as additive manufacturing (AM), within the aerospace industry is impeded by poor interoperability between AM component manufacturing processes. Moreover, data quality may be compromised due to sensor failures or other corruptions. Additionally, massive amounts of data are collected during these processes, often needing to remain accessible for decades. These storage costs can place a significant financial burden on smaller suppliers. This work aims to make digital data management methods more affordable and, therefore, approachable for smaller suppliers.

First, the design and initial implementation of an affordable and adaptable …

Augmentation Of Quality Of Service, Security, And Trust In Edge-Enhanced Iot Networks Leveraging Blockchain, Kyle Matthew Whitlatch

Masters Theses

The meteoric rise of the Internet of Things (IoT) has led to multiple architectural schemas to handle the data these devices create. Edge-enhancement is a technique where groups of IoT report to a median layer to aggregate the data before relaying to the endpoint. These edges also open opportunities to perform more operations to ensure devices are behaving properly before committing the data to long term storage. By interconnecting these edges with a technology like blockchain, it is possible to have an interconnected and responsive system to ensure the Quality of Service (QoS) of the IoT devices within the architecture …

Isolation And Characterization Of A Halophilic, Extremely Acidophilic, Iron-Oxidizing Bacterium, Connor Crites

Masters Theses

This thesis describes the isolation and characterization of a halophilic iron- oxidizing bacterium from sediments obtained from Lake Magic; an extremely acidic, saline lake located in Western Australia. The purpose for the isolation of novel, halotolerant/halophilic iron-oxidizing bacteria is to aid in metal-mining bioleaching operations. Currently used iron- and sulfur-oxidizing bacteria are extremely sensitive to chloride, which restricts their use in these industries.

A singular bacterial morphology was isolated from Lake Magic sediments that was roundly-rod shaped, 1-2 um in length, and stained Gram-negative. This organism was able to grow in a modified medium (DSM14174) using ferrous sulfate as an …

Power Flow Control Of The Triple Active Bridge Converter, Lauryn Reece Morris

Masters Theses

With the rise of renewable energies, electric vehicles, and microgrids, the development of power electronic topologies that can seamlessly integrate these systems into the grid is crucial. The triple active bridge is an extension of the dual active bridge topology and is capable of energy storage or renewable energy integration into a power electronic converter and thus the power grid. Consisting of three H-Bridge converters, the triple active bridge topology is an expanding area of research to meet these growing demands. With the addition of the third bridge, the system has additional nonlinear characteristics which introduce complexity in solving for …

Overall Tropospheric Noise Over The St. Louis Using Isce And Fringe Processing, Maryann Lee

Masters Theses

Interferometric Synthetic Aperture Radar (InSAR) is a satellite-based technique that is used to measure various aspects such as ground deformation, earthquakes, volcanic activity, and motions of glaciers. Although the technique has proved very useful, measurements errors such as ionospheric and tropospheric noise, and deformation often cause problems with making precise measurements. InSAR is a tool used in geodesy that is used to measure the change of surface deformation over time through a series of repeated SAR acquisitions. These errors in the acquisitions occur from factors of signal decorrelation, atmospheric delays, and phase unwrapping errors that affect the accuracy and precision …

Long Short-Term Memory (Lstm) -Based Neural Network Model For Optimizing Composite Manufacturing Process Using Autoclave, Sourav P. Bolar

Masters Theses

The combination of high pressure and controlled heat plays a critical role in ensuring the uniform curing of composite materials, leading to parts with superior mechanical properties. In this study, three composite samples of IM7/CYCOM 5320-1, each cut into 12x12-inch squares, were placed in an autoclave at three different locations, spaced 6 inches apart. Sixteen thermocouples were randomly distributed across the setup to monitor the curing process as the autoclave temperature was systematically ramped up and down while maintaining constant pressure, creating a fully controlled curing environment. The primary objective was to optimize the curing locations to reduce machine runtime …

Frequency-Tracker And Power Supply For Piezoelectric Lunar Dust Removal Actuator, Praneeth Uddarraju

Masters Theses

"This work presents a reconfigurable phase-locked loop (PLL)-based control system for the resonant excitation of piezoelectric actuators aimed at automated removal of particulate contaminants from photovoltaic (PV) surfaces—particularly in extraterrestrial environments such as the lunar surface. Regolith or lunar dust buildup on solar panels is a serious hazard to the effectiveness of energy harvesting on extended missions. By using high-frequency structural excitation and inertial forces the suggested system removes surface impurities. Tunable Sallen-Key low-pass filters for reliable feedback conditioning are used in conjunction with a digitally implemented PLL on an FPGA (XLR8 platform) to precisely lock the drive frequency to …

Enabling Drone-Integrated Active Microwave Thermography Via A Slot Antenna Design, Alec P. Fitzmaurice

Masters Theses

Civil infrastructure inspection quality and inspector safety may be enhanced from the advancement in the capabilities of nondestructive testing and evaluation of remote or otherwise hard-to-reach areas such as nuclear power plants, wind turbines, bridges, or other civil infrastructure using drone-based Active Microwave Thermography (AMT). AMT is a nondestructive testing technique that utilizes high frequency energy (often radiated from an antenna) to induce heating in a specimen. Following this thermal excitation, an infrared camera is used to measure the resulting surface thermal profile. From this, defect indications may be detected. To enable drone-based deployment of AMT, where the antenna size …

Investigation Of Arm Stiffness Modulation During Overground Physical Human-Human Interaction, Henry Tien

Masters Theses

The vision of advancing robots capable of direct physical engagement with humans begins with an understanding of how humans interact with each other. Even rudimentary interactive tasks, such as shaking hands, provides tremendous challenges for modern robotics and current research into the biomechanics of such interactions is limited. Thus, further analysis of physical Human-Human Interaction (pHHI) will bolster efforts to enhance collaborative robot capabilities. To this end, a custom Force Perturbation Handle (FPH) was developed, including the requisite mechanical, electrical, and software systems, to investigate the unique role of arm stiffness modulation in haptic communication between humans. The novel device …

Extraction And Separation Of Metal Cations From Synthetic Acidic Solutions Using Emulsion Liquid Membrane, Nouhaila Filali

Masters Theses

The work is organized into two main papers supported by experimental and comparative studies using Emulsion Liquid Membrane (ELM) systems. The first paper explores the individual extraction of heavy metals (Cd, Cr, As, Ni) from synthetic phosphoric acid using Alamine 336 and D2EHPA as carriers. Alamine 336 achieved the highest extraction efficiency (>90%) and stability, offering a promising route to reduce toxic impurities in fertilizer-grade acid. The second paper examines the selective separation of Ni2+ and Co2+ from various acidic solutions using the ELM configuration. Systematic variation of carriers, stripping agent and feed acidity, clarified transport mechanisms and stability, …

Testing The Life-History Dependence Of Dietary Restriction Effects On Oxidative Molecular Damage In Hornworms, Fahime Taheri

Masters Theses

DR and ambient temperature are two environmental factors widely implicated in shaping organismal maintenance and longevity through effects on metabolic rate and oxidative damage. This study tests whether DR and reduced body temperature independently or interactively reduce oxidative protein damage in the gut of tobacco hornworm larvae, a short-lived ectotherm whose life history may constrain typical DR responses. Larvae hatched from eggs were allocated to two feeding regimes (AL and DR) and to 20 °C and 30 °C. At a defined endpoint, guts dissected and homogenized, and analyzed for protein carbonyl content and total protein. Protein damage was expressed as …

Design Of Real-Time And Energy-Efficient Driver Assist Systems Using Electroencephalogram And Neuromorphic Computing, Nathan Alan Lutes

Doctoral Dissertations

Despite the technological breakthroughs in advanced driver assist systems, distracted driving persists as a major challenge to roadway safety. This investigation advances the body of knowledge towards a solution by developing an individualized driver-state detection method using electroencephalogram (EEG) and neuromorphic computing to provide a less invasive and more energy efficient ADAS solution. It furthermore explores the changes in brain functional connectivity under distracted conditions to better understand brain state information that could be used for neuro-feedback intervention systems. The first contribution introduces the concept of using Convolutional Spiking Neural Networks (CSNNs) for recognition of patterns with movement-intention predictive power …

Higher-Order Statistics And Normalized Decay Analysis For Detector Deadtime Characterization, Abdallah Wazzan

Doctoral Dissertations

Detector deadtime limits radiation measurement accuracy at high count rates, yet current methods rely on idealized paralyzable or non-paralyzable models. Real detectors exhibit hybrid behavior requiring advanced characterization approaches. This study explores deadtime characterization using two Monte Carlo simulation approaches: higher-order statistical analysis of inter-arrival times and simplified deadtime correction with hybrid models.

Using MATLAB (PULSE-WIZ), we analyzed full decay curves spanning ~4.5 half-lives of Cobalt-60 and Vanadium-52, examining coefficient of variation (CV), skewness, and kurtosis of inter-arrival times, plus normalized decay curves with Full Width at Half Maximum (FWHM) analysis. Hybrid models incorporated paralyzable and non-paralyzable components with dead …

Characterization And Deportment Of Anode Impurities In Copper Electrorefining, Charles Michael Campbell

Doctoral Dissertations

The objective of this research was to study the deportment of the group 15 elements, arsenic, antimony and bismuth during copper electrorefining. Samples were collected from six industrial copper anodes with different compositions. Specimens were physically characterized and electro refined to understand the differences in the behavior of selected impurities. Inclusions in the cast metal structures were characterized using automated scanning electron microscopy and energy dispersive spectroscopy to measure and correlate their size, shape and composition. Arsenic and lead were found to have a positive correlation between concentration and size of inclusions. Using wavelength dispersive spectroscopy, multiphase inclusions were examined, …

Machine Learning Models For Location Prediction, Message Routing And Path Planning For Rescue Of Underground Miners, Abhay Goyal

Doctoral Dissertations

Self-rescue during underground mine disasters is vital for miner safety. Evolving hazards and post-disaster conditions demand solutions that enable navigation under severe communication and computational constraints. Centralized systems often fail in such rugged settings, while decentralized methods—particularly Delay Tolerant Networks (DTNs), proven in battlefields and space missions—offer distinct advantages for underground applications. This research addresses five core challenges: (i) predicting miners’ next locations on low-power devices using points of interest and movement sequences; (ii) delivering timely updates on safe routes, evacuation zones, and hazardous areas; (iii) evaluating energy efficiency and comparing graph-based approaches to existing methods; (iv) enabling edge-ready frameworks, …

Applying Human System Integration Principles To The Investigation, Design And Validation Of Interventions For Self-Escape In Underground Mines, Eugene Adubofour Gyawu

Doctoral Dissertations

This dissertation investigates the use of human systems integration (HSI) to develop technologies for miners’ self-escape during a mine emergency, addressing barriers that compromise miner safety during emergencies.

Recognizing the inherently hazardous nature of underground mining, this study has three core objectives: (1) assessing miners' perceptions of proposed self-escape interventions, (2) designing interventions based on these insights, and (3) validating their effectiveness using experimental testing. This work evaluates self-escape interventions for both coal and metal/non-metal miners using scenario-based surveys, information design reviews, label designs and experimental testing methods varying across three distinct studies.

Results reveal that miners identified improvements to …

Quantum And Classical Phase Transitions In Disordered Systems, Gaurav Ramesh Khairnar

Doctoral Dissertations

This work examines the effects of quenched disorder on classical and quantum phase transitions. There are countless examples of phase transitions in nature. Here, we study phase transitions in condensed matter with the help of simple models that focus on the essential unifying features of the problems. We are particularly interested in investigating how the presence of disorder changes the behavior of the system in the vicinity of a phase transition.

Here, we discuss three closely related problems regarding phase transitions. First we consider the behavior of highly diluted magnets with varying dilution levels in order to explain the unusual …

Development Of Dual-Scan Nuclear Magnetic Resonance (Nmr) Pulse Programs For Spin-Lattice Relaxation Measurements, Zachary Mayes

Doctoral Dissertations

This research develops and refines the Split Inversion Pulse and Recovery (SIP R) methodology for spin-lattice relaxation (T₁) measurements in NMR spectroscopy. SIP R introduces a two-scan difference technique using a split inversion pulse sequence, where the 180° pulse is split into two 90° pulses phase-shifted with respect to each other. This approach simplifies data fitting, requiring only two parameters to extract T₁ values, compared to the traditional inversion-recovery method, which needs three. The SIP-R-DS and SIP-R-S adaptations extend this framework by incorporating selective NMR resonance excitations, enhancing its applicability to cross-polarization experiments and enabling unobstructed NOE measurements. These adaptations …

Metal-Organic Thin Film Coated On Optical Fiber, Nahideh Salehifar

Doctoral Dissertations

This dissertation explores the development of metal-organic framework (MOF)-based optical fiber sensors for detecting volatile organic compounds (VOCs) at low concentrations (parts-per-billion to parts-per-million). In the first part of the study, theoretical calculations were performed using effective medium approximation (EMA) models, including Lorentz–Lorentz, Maxwell–Garnett, and Bruggeman equations, to predict the refractive index changes of MOFs upon gas adsorption. These models were applied to MOFs such as ZIF-7, ZIF-8, ZIF-90, MIL-101(Cr), and HKUST-1 to evaluate their potential for gas sensing.

In the second part of the dissertation, experimental work was conducted to validate the theoretical predictions. MOF-coated optical fibers were fabricated …

Deep Learning And Adaptive Clustering Approaches For Flood Prediction And Efficient Sensor Placement In Missouri, Fahimeh Sharafkhani

Doctoral Dissertations

Floods represent formidable natural calamities, posing a significant threat to communities and infrastructure due to their unpredictable and often devastating consequences. The occurrence of floods is influenced by a convergence of meteorological, hydrological, and geographical factors, resulting in changes to the patterns of rising water levels. Machine learning models have emerged as favored tools in recent times for modeling water levels and enhancing the precision of flood predictions. This research employs both supervised and unsupervised machine learning models, with the main objective of improving the accuracy of flood predictions and sensor placement. Four distinct deep learning models are used to …

Measurement Method And Applications Of Transfer Function In Rf Desensitization Problem, Xiangrui Su

Doctoral Dissertations

Radio frequency (RF) desensitization issues comprise two components: noise radiation sources and the transfer function from noise sources to the victim antenna. RFI is a critical challenge in modern electronic systems, particularly in densely packed environments. This work presents a comprehensive study of RFI, addressing key aspects through three novel contributions. First, a transfer function measurement method is developed for compact metallic enclosures. This method provides a precise characterization of the electromagnetic (EM) environment within confined spaces, enabling accurate identification of interference pathways. Second, an EM emission management analysis framework is proposed, leveraging transfer functions to quantify and mitigate interference …

Topics On Ai Fairness Preferences In Kidney Transplantation, Mukund Telukunta

Doctoral Dissertations

Modern kidney transplantation incorporates artificial intelligence (AI) decision-support systems which exhibit social discrimination due to biases inherited from training data. Although researchers have proposed various group-based fairness notions to assess biases in AI, it remains uncertain which criterion is most suitable for evaluating biases in such complex healthcare systems. This dissertation explores human perception of fairness to identify the most appropriate fairness criterion for assessing AI tools in kidney transplantation, focusing on the preferences of non-expert (e.g. public, patients) stakeholders. The study examines two distinct AI systems employed in kidney transplantation: a classification model and a regression model. Human subject …

New Topologies For High Voltage Gain Dc-Dc Power Electronic Converters – Theoretical Analysis And Experimental Validation, Saeed Habibi

Doctoral Dissertations

"This dissertation is focused on developing and analyzing new high voltage gain DC-DC power electronic converters. The proposed converters in this dissertation are suitable candidates for connecting low voltage sources such as photovoltaic (PV) panels or fuel cell (FC) stacks to a DC microgrid or DC link of an inverter. The proposed converters provide desired characteristics such as high voltage gain at a low or medium duty cycle values, low voltage stress on power semiconductors, and continuous input current. Initially, the research introduces three novel converter topologies: First, two quadratic converters based on the combination of a three-winding coupled inductor …

Characterizations Of Eco-Friendly Class C Fly Ash-Based Alkali-Activated Mixtures For Various 3d-Printing Techniques, Fareh Abudawaba

Doctoral Dissertations

This study explored the potential of using high-calcium class C fly ash (FA) as the main precursor for synthesizing alkali-activated mortar (AAM) suitable for 3D-printed concrete (3DPC) applications. The objective was to broaden the selection of AAMs, designed to suit various printing techniques, including continuous mixing and pumping, large batch mixing, and set-on-demand processes. The study began by assessing the fresh properties of various mixtures, utilizing tests such as open time (OT), initial setting time (IST), immediate axial deformation, and penetration test (PT), to determine the mixtures' extrudability and buildability. The study optimized mixtures with a broad spectrum of cycle …

Sensor Embedding And Thermal Monitoring Strategies For Laser-Foil-Printing Additive Manufacturing, Tunay Turk

Doctoral Dissertations

"This work investigates Laser Foil Printing (LFP), a novel metal additive manufacturing (AM) process that fabricates parts layer-by-layer using metal foils. To enhance LFP productivity, the process steps were optimized, and an 88.1% reduction in processing duration was achieved. A unique aspect of this study was the introduction of laser polishing as an edge polishing technique within the LFP process. This innovative approach, employing an overlapping spiral pattern, leverages selective laser remelting and erosion to effectively suppress elevated edges. To stabilize the molten melt pool, a discrete spot scanning strategy was implemented. The fabricated parts were subjected to detailed analysis, …

Processing And Densification Of Multi-Phase High-Entropy Ceramics, Steven Smith

Doctoral Dissertations

"This work focuses on the processing and densification of multiphase, high-entropy ceramics to promote their use in friction stir welding technologies. Several high-entropy systems including high-entropy borides, carbides, and their composites were produced. Boro/carbothermal and carbothermal synthesis were used to produce high-entropy powders from oxide powder mixtures. Composites of high-entropy borides and high-entropy carbides were produced using a sequential approach to produce both phases. The carbide was first produced using carbothermal reduction, then ZrH2 and B4C were added to the carbide powder to produce the high-entropy boride phase. The resulting powder was densified by spark plasma sintering and pressureless sintering, …