Digital Commons Network^™

Implications Of Persistent Micro-Bioplastics On Biogeochemical Properties Across Soil Types, Casandra R. Leach

Master's Theses

Terrestrial microplastics are increasing in abundance and are an emerging contaminant of concern, particularly in agriculture ecosystems where plastic use and subsequent soil contamination are prevalent. Plastic film mulches make up a significant portion of the plasticulture industry and are directly linked to soil microplastic pollution where negative effects to soil biotic and abiotic functions have been observed. In response to this issue, biodegradable film mulches have been promoted as a sustainable alternative to conventional polyethylene-based mulches. These biodegradable mulches, composed of various bioplastics, are designed to be tilled back into the soil where they are expected to decompose. However, …

Drivers Of Microparticles Abundance In Freshwater Fish And Macroinvertibrates, Elizabeth Kazmierczak

Master's Theses

Anthropogenic microparticles (MP) (i.e., particles < 5 mm) are defined as materials of manufactured origin found in the environment. They are widespread and a rapidly emerging global contaminant. MP include microplastics (< 5 mm), as well as other microfibers or particles, which can be synthetic, semi-synthetic and non-synthetic. Rivers are a critical source of plastics to oceans, and MP within rivers are retained in part though biological processes, including ingestion. MP ingestion by freshwater biota varies by proximity to point sources (e.g., wastewater treatment plants; WWTP), overall environmental concentrations, and trophic level and functional feeding groups, but few studies have examined these factors together. In our first study we examined fish collected in the North Shore Channel of the Chicago River to determine MP abundance within organisms. We then compared trophic position (i.e., δ15N) and proximity to a WWTP. With all species combined, MP concentration were not significantly different across study sites, but stable isotopes increased downstream. Considered individually, MP abundance relative to WWTP proximity varied by species, which we attributed to habitat preference and mobility. In a second project, we collected macroinvertebrates from three different watersheds in North America and compared the abundance of MP in macroinvertebrates to concentration within the environment (i.e., water column, surface, and benthic). Functional feeding groups were a significant predictor in the amount of microparticles found in macroinvertebrates. Additionally, the concentration of water column microparticles showed a positive relationship with all macroinvertebrate’s microparticle abundance. Results will aid in understanding the ecological impacts of MPs on aquatic food webs and the pathways in which they can enter.

Assessment Of Dune Change Using Historical Aerial And Satellite Photos, Topographic Surveys, And Wave Data At Toro Creek Beach, Owen D. Emerson

Master's Theses

Coastal sand dunes play an important role in the littoral processes of California’s coastline. Functioning as both source and sink for sand, these dunes often protect coastal infrastructure and provide a buffer between anthropogenic development and coastal forces. At Toro Creek Beach, north of Morro Bay California, recent extreme winter storms have raised concerns about the erosion of the sand dunes that front California State Highway 1. This thesis attempts to characterize the historical growth and recession patterns of the Toro Creek dunes since 1977, the dune movement over the 2023-2024 winter seasons, the wave forcings behind recent high erosion …

Seal Counting On Our Plages (S.C.O.O.P.), Kaanan Kharwa

Master's Theses

The Vertebrate Integrative Physiology (VIP) lab monitors the population of northern elephant seals at the largest mainland breeding colony, located at Piedras Blancas (San Simeon, CA). As the population expands, more human-seal interactions and conflicts over land use occur. The VIP lab's work informs California State Parks and helps with the management of the rookery. Currently, members of the VIP lab fly a drone over the beaches, capture multiple images, and manually count the seals, which takes around 14 to 21 hours of analysis per survey. Machine learning methods such as Convolutional Neural Networks (CNN) and Region-based Convolutional Neural Networks …

Enabling Emg-Based Silent Speech Transcription Through Speech-To-Text Transfer Learning, Alexander T. Garcia

Master's Theses

In recent years, advances in deep learning have allowed various forms of electrographic signals, such as electroencephalography (EEG) and electromyography (EMG), to be used as a viable form of input in artificial intelligence applications, particularly for applications in the medical field. One such topic that EMG inputs have been used is in silent speech interfaces, or devices capable of processing speech without an audio-based input. The goal of this thesis is to explore a novel method of training a machine learning model to be used for silent speech interface development: using transfer learning to leverage a pre-trained speech recognition model …

Investigation Of Temperature, Solution Strength, And Applied Stress Effects On Cation Exchange Processes In Different Geosynthetic Clay Liner Products, Kendra Fuller

Master's Theses

An extensive laboratory test program was conducted to analyze and compare the cation exchange processes in three different varieties of sodium bentonite (Na-B) geosynthetic clay liners (GCLs) over increased conditioning durations up to 32 days and investigate the effects of temperature, solution strength, and applied stress. The goal of this test program was to establish whether the variables of temperature, solution strength, and applied stress improved or degraded the engineering properties of GCLs in laboratory testing and municipal solid waste (MSW) landfill applications. The GCLs were conditioned in liquids of increasing ionic strength, using deionized water and 2, 50, and …

Dual Base Sige Is-Hbt For Use In Biosensing Applications, Liam Stephen Hayes

Master's Theses

The proposed research is for a novel SiGe-based Ion-Sensitive Dual Hetero-junction Bipolar Transistor (IS-HBT) to be used in both trans-dermal biological sensing as well as Lab-on-Chip (LOC) applications. The end goals for the device designed are two: For one, the research done for this work will be used to substantiate the claims made by Zafar et al. [1] that an HBT-style structure is better suited for biosensing application rather than a conventional Field Effect Transistor (FET) based geometries. Secondly, it provides the final element to be integrated along with a selectivity membrane, as well as with a reverse-iontophoresis system to …

Design And Implementation Of An Inverted Short Baseline Acoustic Positioning System, Jakob Frabosilio

Master's Theses

This document details the design, implementation, testing, and analysis of an inverted short baseline acoustic positioning system. The system presented here is an above-water, air-based prototype for an underwater acoustic positioning system; it is designed to determine the position of remotely-operated underwater vehicles (ROVs) and autonomous underwater vehicles (AUVs) in the global frame using a method that does not drift over time.

A ground-truth positioning system is constructed using a stacked hexapod platform actuator, which mimics the motion of an AUV and provides the true position of an ultrasonic microphone array. An ultrasonic transmitter sends a pulse of sound towards …

Validation Of Mobile Devices In Arbitrary Locations Against Force Plate Standard For Balance Assessment, German J. Ellsworth

Master's Theses

With balance assessment being essential to the prediction of fall risk and detection and assessment of motor disorders, increasing clinical accessibility to objective balance metrics is essential. Work has been done validating center of mass (COM) acceleration metrics against well regarded force plate center of pressure (COP) position standards for mobile device data acquisition systems, but most research is restricted to devices being close to the COM or strapped in a harness configuration. Through the use of rigid body kinematics and the inverted pendulum model, this study develops novel methodology for calculating COM acceleration using mobile devices in arbitrary positions, …

Dynamic Maze Puzzle Navigation Using Deep Reinforcement Learning, Luisa Shu Yi Chiu

Master's Theses

The implementation of deep reinforcement learning in mobile robotics offers a great solution for the development of autonomous mobile robots to efficiently complete tasks and transport objects. Reinforcement learning continues to show impressive potential in robotics applications through self-learning and biological plausibility. Despite its advancements, challenges remain in applying these machine learning techniques in dynamic environments. This thesis explores the performance of Deep Q-Networks (DQN), using images as an input, for mobile robot navigation in dynamic maze puzzles and aims to contribute to advancements in deep reinforcement learning applications for simulated and real-life robotic systems. This project is a step …

A Data-Driven Framework For Analyzing And Predicting Social Media Engagement During Rumor Propagation, Joseph E. Faza

Master's Theses

The spread of rumors on social media has become a significant concern, as platforms like X (formerly known as Twitter) enable rapid dissemination of unverified information. These rumors can shape public perception and behavior, making it crucial to understand the dynamics of their spread. The main objective of this study is to explore how users interact with rumor-related tweets and identify key factors that predict tweet engagement. By analyzing tweets from seven different rumor events, this research aims to uncover patterns in user engagement and provide insights into the spread of misinformation. The study utilized a dataset of tweets from …

Of Geese And Grass: Investigating Impacts Of Brant Grazing On Eeelgrass, Dakota L. Osborne

Master's Theses

Grazing pressure is important in structuring plant communities, particularly in aquatic environments. Eelgrass (Zostera marina), a keystone species in estuaries across North America, is experiencing widespread population declines. As a keystone species, eelgrass provides numerous important functions, including: 1) water filtration, 2) sediment stabilization, 3) providing refuge and nursery habitat for numerous species, and 4) carbon sequestration. Benefits which could be lost if eelgrass beds continue to diminish. California has experienced some of the greatest eelgrass declines, and Morro Bay, CA experienced a 96% decrease in eelgrass from 2007 to 2017. Most studies to date have examined bottom-up …

The Post-Closet Home: Queer Domesticity, Enclosure, And Queer Southern Gothicism In Lee Mandelo's "Summer Sons", Andrew Dylan Dampier

Master's Theses

In current discussions of queer theory, terms such as “post-gay” leave room for misrepresentation. The premise behind this term serves a primarily cisgenderheterosexual agenda by promising the assimilation of queer individuals into the dominant society. For this reason, I prefer to align the term “post-closet” with the queer person’s journey towards, and past, such societal barriers while maintaining the significance of foundational queer theories. In his novel Summer Sons, Lee Mandelo depicts Andrew Blur’s journey through the grief-ridden confines of the closet as he seeks a new identity following the death of his best friend. Mandelo accomplishes this by juxtaposing …

Assessment Of Mediterranean Diet Adherence Using The Kidmed Diet 2.0 Tool: College Student Questionnaire, Nakia Cyrice Hilton

Master's Theses

The Mediterranean Diet has garnered increasing popularity due to its multifaceted health benefits. The MedDiet enhances well-being across all age groups, emphasizing high consumption of fruits, vegetables, legumes, nuts, olive oil, and whole grains and moderate fish, poultry, and dairy intake. Recent research underscores the significant impact of Mediterranean diet adherence on college students' physical and mental health. The diet's emphasis on nutrient-dense foods rich in vitamins, minerals, and antioxidants supports cognitive function, which is pivotal for academic performance. Moreover, the abundant presence of healthy fats, particularly from olive oil and fatty fish, may contribute to improved mood regulation, potentially …

Supervised Classification Modeling On Louisiana Medicaid Data: A Comparative Study, Yead Rahman

Master's Theses

This thesis systematically optimizes and compares state-of-the-art supervised classification models for Louisiana Medicaid data targeting clinical services, COVID-19 infection, and tobacco use. These target variables are critically important as they represent key health outcomes and behaviors among Medicaid enrollees in Louisiana, a population often characterized by poverty and limited access to education. This study applies advanced machine learning techniques to identify the best model for multinomial and binary classification tasks. These include models such as Logistic Regression, XGBoost, AdaBoost, Random Forest, Decision Tree, Artificial Neural Networks, and Naïve Bayes. Extensive tuning of the hyperparameters and optimization of each classifier were …

Adherence To Mediterranean Diet Principles In Minority College Students, Bridgette Lorraine Barbre

Master's Theses

Every year, millions of young adults attend college. The Centers for Disease Control and Prevention (CDC) lists heart disease and diabetes as the top health concerns for minority Americans. African American and Hispanic/Latino communities could see a reduction in illness risk by promoting physical activity and healthy eating habits such as the Mediterranean Diet. Research indicates that young adults may benefit significantly from taking charge of their eating habits at the crucial point in their transition from high school to college. By determining the dietary patterns of minority college students, as related to the Mediterranean diet principles, this study intends …

Division I Collegiate Baseball Pitching Performance In Relation To Forearm Kinematics And Kinetics, Christopher W. Watson

Master's Theses

This thesis investigates physical and anthropometric factors influenced by forearm rotation biases associated with supination and pronation on pitch characteristics among Division I college baseball pitchers. The study involved twenty-two participants who underwent comprehensive physical assessments, including measures of forearm strength, range of motion, and grip strength, as well as finger and hand length measurements. Ball flight metrics were collected during intrasquad scrimmages using advanced radar tracking technology. Results revealed significant relationships between distinct physical biases of strength in pronation and supination, pinch strength, anthropometrics such as middle finger length, and specific pitch characteristics. This study lays the groundwork for …

Robotic Odor Source Localization Using Vision And Olfaction Sensing, Sunzid Hassan

Master's Theses

Robotic Odor Source Localization (ROSL) technology allows autonomous agents like robots to find an odor source in unknown environments. A successful odor source location depends crucially on an effective navigation algorithm that directs the robot towards the odor source. This thesis is a combination of three projects. First, we detail development of a versatile multi-modal robotic platform for ROSL real-world ROSL experimentation and discussed real-world validation of a traditional olfactionbased ROSL algorithm. Secondly, we introduced vision in ROSL by proposing a fusion navigation algorithm that integrates deep-learning enabled vision and olfaction-based navigation. This hybrid approach tackles challenges such as turbulent …

Evolutionary Patterns Of Anolis Lizard Skulls: An Investigation In Geometric Morphometrics And An Educational Exploration Of Structure And Function, Katherine Beyer Starr

Master's Theses

This study explores the evolutionary patterns of Anolis lizard skulls and integrates findings into a curriculum focused on elucidating the structure and function of a lizard's head. The first objective was to develop an understanding of how the evolutionary patterns, of an extraordinary group of lizards (Anolis) compares to their relatives. Most of the prior research on Anolis morphology has focused on the post-cranium because of its significance towards subdivision of the arboreal habitat. But the group’s remarkable diversity in head shape has been seriously under-investigated. By performing geometric morphometric analysis of skull shape across a large sample of anoles …

Absolute Quantification Of Human Myosin And Titin Isoforms In Disease By A Mass Spectrometry Approach, Nitha Aima Muntu

Master's Theses

Heart failure (HF) is the leading cause of death worldwide and produces an immense economic burden. Dilated cardiomyopathy (DCM), characterized by contractile weakness and chamber dilation, is a significant cause of HF. The sarcomeric proteins play a crucial role in regulating the contractile properties of the heart. As the primary motor protein, the expression of cardiac myosin isoforms (α-MHC and β-MHC) dictates the performance and cardiac energy utilization of the sarcomere. Titin is the giant spring protein in the sarcomere, and titin isoform expression impacts the passive stiffness of the myocardium. Small changes in the α-MHC/β-MHC and titin isoform ratios …

A Qualitative Evaluation Of Speech Sound Disorder Treatment Apps For Children, Rachel G. Barnett

Master's Theses

This research examined 20 speech sound disorder (SSD) treatment apps’ features and costs as related to the feature matching process within speech-language therapy. Methods included the development of a 67-item SSD checklist and sorted into 9 categories, including linguistic levels, speech models, software customization, cost, game types, image types, technical elements, feedback types, and engagement and manipulation. Two independent reviewers applied the checklist to randomly selected contemporary apps available on both iPhones and iPads. App cost was capped at $25. Results indicated that app cost was not a good predictor of feature quantity and contemporary apps had some relevant feature …

Remote Sensing With Airborne Infrared Thermography For Assessment Of Landscape Scale Wildfire Spread And Intensity, Christopher C. Giesige

Master's Theses

Wildland fire is one of the most complex environmental physical processes to quantify. The way in which we observe and measure wildland fire is critical in understanding how these processes drive fire dynamics. Fire behavior can be observed in several ways including the use of ground sensors and remote sensing packages aboard aircraft and satellites. Airborne sensors provide high spatial resolution and can provide high temporal resolution. Infrared thermography takes advantage of radiant heat transfer allowing for the study of fire characteristics such as fire spread and intensity. Aircraft observations utilizing infrared cameras have been a well-established method of fire …

Flora And Fauna Lexical Indicators Of Prehistoric Movement Of Yuman Peoples, Adam Ingwerson

Master's Theses

Amyloid fibrils are locally ordered protein aggregates characterized by a filamentous morphology held together by a hydrogen bonding motif known as cross-β structure whereby hydrogen bonds form between backbone amide bond moieties across separate protein segments. The most notable medical significance of amyloid fibrils is their central role in the etiology of Alzheimer’s disease, type 2 diabetes, and other human diseases. Although amyloid fibrils have been studied extensively, the mechanism of their formation is still not fully understood. X-ray crystallography is a leading experimental technique for resolving amyloid fibril structures from crystallized proteins; however, inherent limitations leave open the possibility …

Deep-Learning Approaches To Predict Remaining Useful Life Of Hard Disks, Rohan Mohapatra

Master's Theses

On a daily basis, data centers process huge volumes of data using inexpensive hard disks. Data stored in these disks serve a range of critical functional needs from financial, and healthcare to aerospace. As such, premature disk failure and consequent loss of data can be catastrophic. To mitigate the risk of failures, cloud storage providers perform condition-based monitoring and replace hard disks before they fail. By estimating the remaining useful life (RUL) of hard disk drives, one can predict the time-to-failure of a particular device and replace it at the right time, ensuring maximum utilization whilst reducing operational costs. We …

Synthetic Data Generation For Accurate, Fair, And Private Recommender Systems, Derek B. Lilienthal

Master's Theses

A notorious challenge for recommender systems on online platforms is to accurately and fairly recommend items that align with users’ preferences while retaining user privacy. These systems often rely on historical data that is partially labeled and includes incomplete user information, leading to the over-representation of majority groups and disproportionately favoring popular items. Substituting user data with synthetic data can address these concerns, but accurately replicating real-world datasets has been a challenging problem. Recent advancements in generative AI have demonstrated the impressive capabilities of diffusion models in generating realistic data across several domains. In this work, we introduce two variations …

Reinforcement Learning Based Planning And Control For Robotic Source Seeking Inspired By Fruit Flies, Gauravkumar Koradiya

Master's Theses

In the exploration of mobile sensing agents such as robots equipped with sensors, these agents have the potential to measure unknown scalar fields, ranging from chemical concentrations to temperature fluctuations. One of the primary interests is the robots’ ability to gravitate towards the peaks or troughs of these fields, a phenomenon termed as “source seeking”. This behavior is invaluable in practical scenarios, like detecting chemical leaks or locating survivors after catastrophes. However, the challenge becomes significantly more pronounced when operating in turbulent flow fields, where the erratic nature of odorant plumes makes predictions and simulations highly unreliable. Interestingly, fruit flies …

Controllable Physics-Informed Latent Space For Acoustic Wave Manipulation, Tristan Shah

Master's Theses

Partial Differential Equations (PDEs) are foundational descriptive tools in scientific and engineering disciplines, enabling the exploration of phenomena from material design to climate dynamics and the propagation of pandemics and wildfires. Establishing control of PDEs, especially when the underlying phenomena are only partially observable, holds great potential for fostering technological innovations. This ambition faces considerable obstacles, as a robust sample-based solution remains elusive. Addressing this challenge, this thesis introduces a framework leveraging physics-informed machine learning (ML) to enable control of PDEs. Central to this framework is an agent, equipped with sensors to perceive its environment, that generates a low-dimensional physics-informed …

Extraction, Preparation, And Characterization Of Alginate Biopolymer Films From Natural Seaweed, David Ly

Master's Theses

This study evaluates the use of naturally harvested seaweed from the Monterey Bay to produce a biodegradable film for food packaging applications. Two different film-forming methods were evaluated: solution casting and compression molding. The solution casting method using an alginate biopolymer produced the most consistent results. The seaweed biopolymer was extracted from the seaweed biomass using a modified method, resulting in a yield of 11-25 %. The highest yield was observed when using the lowest biomass concentration of 10 wt. %. The extracted alginate was then cast into films at different levels of glycerol plasticization (15-35 wt.%). The addition of …

A Simulation Framework To Understand The Error Generation And Propagation Of Quantum Algorithms, Anika Zaman

Master's Theses

In this work, we present a Python framework designed to demonstrate various error types within quantum circuits through the utilization of probabilistic data obtained from quantum computers. The framework serves as a valuable tool for monitoring and mitigating errors across all stages of quantum circuits involving multiple qubits and gates. Leveraging the Harrow-Hassidim-Lloyd (HHL) quantum circuit, we conduct an analysis of errors on an IBM quantum computer and subsequently optimize the circuit. The paper introduces an automated methodology for computing single bit-flip errors and propagation errors, and gate errors offering insights into opportunities for mitigating errors in the context of …

An Exploration Of Dimensionality Reduction Of Dynamics On Lie Groups Via Structure-Aware Canonical Correlation Analysis, Wooyoung Chung

Master's Theses

Incorporating prior knowledge into a data-driven modeling problem can drastically improve performance, reliability, and generalization outside of the training sample. The stronger the structural properties, the more effective these improvements become. Manifolds are a powerful nonlinear generalization of Euclidean space for modeling finite dimensions. When additionally assuming that the manifold carries (Lie) group structure, this imposes a drastically stricter global constraint. The range of their applications is very wide and includes the important case of robotic tasks. We apply this idea to Canonical Correlation Analysis (CCA). In traditional CCA one constructs a hierarchical sequence of maximal correlations of up to …