Digital Commons Network^™

An Analysis Of Coal Ash Pollution In The State Of Georgia, Mick W. Etchison

Theses and Dissertations

This social science paper will explore the factors contributing to the prevalence of coal ash in specific regions of Georgia and its impact on local ecosystems and human health. It provides an analysis of the current environmental and political issues surrounding the containment and spread of coal ash throughout the State. Coal ash is primarily found in the central, southwestern, and northeastern regions where coal-fired power plants and coal ash storage sites are located. The paper will then discuss the political, economic, and legal reasons behind the lack of effective regulation and mitigation of coal ash spread. Coal ash illustrates …

From Curiosity To Controversy: American Perception Of Japanese Immigrants, 1853-1924, Chloe Elizabeth Curbelo

Theses and Dissertations

In the mid-nineteenth century, as the United States reached the Pacific through westward expansion, Asia emerged as a new stage for commerce and power. Japan, long isolated under the Tokugawa shogunate, became an object of American fascination when forced into relations. While early depictions cast Japan as an exotic yet uncivilized nation in need of Western guidance, Japan’s rapid modernization and the growing number of Japanese immigrants on the West Coast transformed curiosity into anxiety. My paper traces this evolution of perception from 1850 to 1924, arguing that shifting views of Japan and its people reflected America’s ethnocentric notions of …

How Do School Counselors And School Social Workers Support High School Bullying Victims: A Qualitative Exploratory Case Study, Dalentina N. Robertson

Theses and Dissertations

Bullying and student aggression are increasing in public high schools. Bullying and cyberbullying are a safety concern, and victims of bullying have shown a decline academically and emotionally. Additionally, high schools need increased support with bullying behaviors. The purpose of this exploratory case study was to explore school counselors’ and school social workers’ insights and perspectives regarding the support they provided to bullying victims in two school districts in rural Georgia. Bronfenbrenner’s Ecological Systems Theory was the framework used to focus research on understanding how environmental systems influence an individual’s development. Semi-structured interviews were conducted from a purposeful sample of …

Nanotube Spectral Fingerprinting And Machine Learning For Optimized Bioimaging/Sensing And Disease Detection Applications In Als, Rodrigo Monroy Lopez

Open Access Master's Theses

Single-walled carbon nanotubes (SWCNTs) possess unique physicochemical and optical properties that make them ideal candidates for biomedical imaging, biosensing, and disease diagnostics. This thesis explores the potential of SWCNT-based spectral fingerprinting combined with ML (Machine Learning) algorithms to optimize bioimaging, disease detection and prediction, with a specific focus on differentiating between healthy and amyotrophic lateral sclerosis (ALS) lymphoblastic patient samples. By functionalizing SWCNTs with single-stranded DNA, we enhance their stability and target specificity, enabling their application in serum patient samples.

A comprehensive spectral analysis of DNA-SWCNTs was conducted using near-infrared fluorescence spectroscopy and other characterization techniques, including UV-Vis-absorption spectroscopy. The …

The P3 Event-Related Potential (Erp) In Visual And Auditory Tasks: Implications For Executive Functioning In Adhd Preadolescent Children, Alex Visal Seng

Open Access Master's Theses

Attention-Deficit/Hyperactivity Disorder (ADHD) is a widespread psychological disorder in children, poorly impacting executive functioning domains of inhibitory control and working memory. Event-related potentials (ERPs) provide neuroelectric insight into these cognitive processes. However, most ERP research focuses on one task type, limiting direct comparisons of cognitive demands across different task paradigms. This study examined P3 amplitude and latency in ADHD children using a visual NoGo task (response inhibition) and an auditory oddball task (working memory), and associations between the P3 ERP and behavioral measures of executive functions.

Cross-sectional data of symptomatic ADHD children (N=13; F=5; aged 9.15 ± 1.86 years) were …

Big Cells, Big Impact: Unravelling Seasonal Patterns Of Net Primary Production In Narragansett Bay, Dominique Jae Lockwood

Open Access Master's Theses

Net primary production is a measurement of available energy, or the amount of biomass that phytoplankton produce during photosynthesis that fuels marine food webs and drives carbon cycling. Despite its ecological importance, net primary production is relatively understudied in comparison to chlorophyll-a, which is often used as a proxy for biomass rather than productivity. In this study, we measured size-fractionated net primary production and chlorophyll-a concentrations in Narragansett Bay over a 14-month period from January 2022 to February 2023. Weekly surface water samples were collected and filtered to distinguish between small (> 10 μm) and large ( …

The Anatomy Of Efficiency: Changes In British Military Medicine On The Western Front, 1914-1918, Ricky Mather

Open Access Master's Theses

The Western Front of the First World War was a theater of tragedy and unprecedented loss. As thousands of mangled British bodies were evacuated from the front lines, medical officers, surgeons, nurses, orderlies, stretcher-bearers, and other staff worked tirelessly in an efficient and technical manner to restore soldiers’ fitness so they might be redeployed into the chaos, and continue servicing the war machine. This thesis looks at changes in medicine driven by the war. First, it examines the evolution of medical theory and practice as reflected in three medical manuals. The first was published in 1911, before the war, and …

Through Their Eyes: Investigating The Broad Autism Phenotype In Parents An Exploration In Eye Tracking During A Phonemic Restoration Paradigm In Conjunction With Social Communication Measures, Elena Esposito

Open Access Master's Theses

The Broad Autism Phenotype (BAP) refers to traits that resemble those seen in autism spectrum disorder (ASD). The BAP traits are more common in first-degree relatives of individuals with ASD which suggests a potential genetic contribution to the disorder. Understanding how these traits manifest in communication remains limited. Previous research has shown differences in eye gaze patterns between children with ASD and neurotypical children. This study explored whether similar patterns exist in parents of children with autism (pASD) during a phonemic restoration task. The Social Responsiveness Scale (SRS-2) and Broad Autism Phenotype Questionnaire (BAPQ) were also used in this study …

Risk Factors For Autism Spectrum Disorder: A Statistical And Machine Learning Perspective, Supti Biswas

Open Access Master's Theses

his study explores factors associated with autism spectrum disorder (ASD) through analysis of a rich dataset comprising maternal and child characteristics. The data were carefully cleaned and preprocessed to address missing values and ensure analytical consistency. Statistical analyses and advanced visualization techniques were used to uncover patterns linking ASD status with variables such as maternal age, prenatal smoking, and education level. To further assess predictive capacity and feature importance, multiple supervised machine learning algorithms - logistic regression, decision trees, random forests, and support vector machines (SVM) - were applied. ASD appears to be influenced by a complex interplay of demographic …

Associations Between Dietary Sodium And Potassium Intakes, Urinary Sodium And Potassium Excretion And Blood Pressure Among Adult Females In Oromia Region, Ethiopia, Fred Baffour Addo

Open Access Master's Theses

Introduction: Accurate assessment of sodium (Na) and potassium (K) intake is essential for population level monitoring of salt intake as part of global strategies to reduce salt consumption to control the increasing prevalence of high blood pressure (BP). Thus, a simple, cost-effective, and low-burden method is particularly valuable in resource-limited settings for population level monitoring of Na and K intake. This study aimed to compare the reliability of various methods of Na and K intake assessment, and their associations with blood pressure measurements.

Methods: This secondary analysis was based on a cross-sectional study of 100 non-pregnant women of …

From Lawns To Life: Landscaping For Biodiversity On Mason’S Island, Margit Burgess

Open Access Master's Theses

The collapse of biodiversity is an existential threat to life on Earth. Residential landscapes, dominated by open lawns maintained in turfgrass, do not support biodiversity. In the United States, turfgrass has replaced native landscapes in over 40 million acres, with 500 square miles added each year (Tallamy, 2019). Of the 78% of the U.S. land that is privately owned, approximately 135 million acres - nearly twice the size of all national parks combined - are residential (Milesi et al., 2005). With a shift in private landscape management, this land could present a largely untapped opportunity for biodiversity restoration and social …

Micro- And Nano-Plastics Preparation And Their Impact On Cobetia Marina, Lauren Lamothe

Open Access Master's Theses

Plastic pollution has become an increasing threat to marine and coastal environments. Macroplastics derived from consumer waste are broken down by chemical and physical degradation processes, resulting in micro- and nano-plastics (MPs and NPs). This thesis presents an investigation into the MP and NP pollution in the sea surface microlayer (SSML). The SSML contains surface active compounds and natural and anthropogenic matter. This study provides insight into the deeper impacts on the transport and fate of MPs and NPs and on marine bacteria. The first chapter works through the breakdown of plastic particles with the use of a top-down approach …

Investigating The Effectiveness Of Best Management Practices In Reducing Fecal Bacteria In Narrow River, Rhode Island, Katherine Thompson

Open Access Master's Theses

Fecal bacterial contamination shapes how communities manage and use estuarine waters, with consequences for ecosystem health and public access. In Rhode Island's Narrow River, elevated concentrations of fecal coliforms and enterococci have restricted shellfishing for decades despite ongoing management efforts. From 2004 to 2018, local organizations implemented Best Management Practices (BMPs) to address water quality challenges, yet their effectiveness remains incompletely understood. This study analyzes three decades of monitoring data using linear regression, generalized additive models, and Before After Control Impact methods to evaluate BMP effectiveness and identify key drivers of contamination. Linear regression revealed spatially variable trends, with bacterial …

The Coral Carousel: A Device And Method For In-Situ Propagation Of Deep-Sea Corals, Gregory Bales

Open Access Master's Theses

The research described herein covers the development of a tool station for performing in-situ propagation of corals using a work class ROV. This includes a system for manipulating coral fragments and affixing them to a cement base plug. To validate this tool station, testing was performed both in the lab as well as at depth in the Gulf of Mexico. As restoration of shallow-water corals has grown in popularity, many techniques have been developed for propagation. However, it is difficult or inappropriate to directly apply these techniques to deep-sea corals. While some forms of diving are capable of approaching the …

Plastics And Their Interactions With Bacterial Biofilms Of Synechococcus Sp. Pcc 7002 And Escherichia Coli Nissle 1917, Jackson Zmich

Open Access Master's Theses

Plastic waste is a leading global pollutant with increasing concerns, as recent studies have shown that these wastes are not only concentrated on a macro scale but on a micro and nano scale. These micro- and nano- sized plastic particles, denoted as MPs and NPs, have been measured in marine and freshwater sources, air, food products, and within biosolids expelled from organisms, including humans. Due to their small size, MNPs are entering organisms through inhalation, ingestion, or dermal absorption. [1] Humans are ingesting MNPs daily, with median rates of approximately 200 ng/capita/day for children and 600 ng/capita/day for adults. [2] …

Estrogen Receptor-Mediated Effects Of Resveratrol On Muscle Function, David Ayi-Bonte

Open Access Master's Theses

Artemis missions are set to send the next man and the first woman back to the moon and enable long-term missions on the lunar surface. However, exposure to lunar gravity has significant physiological effects characterized by loss of muscle mass, weakness and decreased bone density. Nutraceutical countermeasures such as Resveratrol (RSV), a naturally occurring polyphenol, have been identified as promising strategies to preserve musculoskeletal health; however, its pleiotropic effect hinders our ability to identify the primary cellular pathways through which it delivers its benefits. Furthermore, its efficacy in simulated lunar gravity is unknown. Based on the benefits observed with RSV …

Evaluating Uas & Als Lidar’S Ability To Detect Understory Shrubs In Rhode Island Forests, Noah Henkenius

Open Access Master's Theses

Understory shrubs provide important habitat for wildlife and assist with nutrient cycling in forests. The use of remote sensing to map shrubs in forest understories is challenging due to the obscuring effect of the forest overstory. We tested the effectiveness of leaf-off aerial LiDAR and uncrewed aerial system (UAS) (point densities of 8+ pts/m² and 250+ pts/m², respectively) to map shrub cover in a mixed deciduous forest in Rhode Island (USA). We used a terrestrial laser scanner (TLS) and field vegetation surveys to provide validation data. We found that UAS and aerial LiDAR had average omission errors …

Alterations Of Serotonin Receptor 7 Expression In The Spinal Cord In A Model Of Cerebral Palsy, Tracy Santos

Open Access Master's Theses

Cerebral palsy often results from perinatal hypoxia-ischemia and is characterized by motor and sensory dysfunction associated with altered serotonergic signaling in the spinal cord. The 5-HT₇ receptor, a G-protein-coupled receptor implicated in both motor control and nociceptive modulation, may thus play a critical role in these post-injury changes. However, the regional and developmental patterns of expression of 5-HT₇ following HI injury are not well understood.

In this study, we investigated the expression of spinal 5-HTR₇ in a neonatal rabbit model of HI injury at P1, P5, and P8 using Western blot analyses normalized to total protein. Tissue was …

Uncertainty-Aware Meta-Learning For Learning From Limited Data, Deep Shankar Pandey

Theses

Deep Learning (DL) models have achieved great success in large data fields ranging from computer vision and natural language processing to digital arts and robotics. However, the effectiveness of the DL models is challenged by many real-world limited data problems (e.g., medicine, healthcare, and security intelligence) where data for model training is scarce. Unlike DL models, humans can use the prior knowledge stored in their brains to quickly learn new tasks with limited data. Inspired by such human learning, various meta-learning models have been developed that aim to address the challenge of learning from limited data. However, existing models are …

Predictive Policing - Leveraging Cctv Data And Ai For Crime Hotspots, Maitha Ahmad

Theses

This thesis explores fine-grained sentiment analysis in the context of police social media posts, leveraging hybrid approaches to manage the rapid flow of big data and mitigate its negative impact on youth. As social media becomes a primary medium for public interaction, understanding sentiment within police-related posts is crucial for law enforcement agencies to gauge public opinion and address community concerns effectively. The rapid dissemination of information and the potential for negative sentiments to spread swiftly pose significant challenges, particularly for young audiences. The research begins with a comprehensive review of existing sentiment analysis techniques and their applicability to large-scale …

Multimodal Feature Fusion And Machine Learning For Adhd Detection Using Neuroimaging Data, Isabel Pham

Master's Projects

Attention Deficit Hyperactivity Disorder (ADHD) is a common neurodevelopment disorder that can significantly affect a person’s attention, impulse control, and executive function. Currently, the traditional diagnosis method often relies on clinical assessments and observations. However, these methods can be subjective and lead to inconsistencies in diagnosis between individuals. To address this challenge, neuroimaging and machine learning (ML) are promising tools for providing a more objective diagnosis of ADHD. The goal of this project is to apply a multimodal approach in which structural and functional features of specific regions of the brain are used to develop a more accurate and objective …

Effects Of Data Augmentation On Sponge Identification Using Computer Vision Models, George Ku

Master's Projects

Coral reefs can be primarily found in tropical and sub-tropical regions of our oceans, providing a thriving habitat for millions of species. Marine sponges, which can be frequently found in coral reefs, play a critical role that contributes to the maintenance of these ecosystems, including the recycling of nutrients through water filtration. However, rising ocean temperatures and acidification due to climate change have resulted in the bleaching and death of coral reefs worldwide. In order to preserve these reefs and the sponges that depend on them, scientists have been performing studies on their biodiversity. This includes collecting numerous images of …

Combining Esm Models With Experimentally Derived Structural Stability To Identify Functional Missense Mutations, Rucha Deo

Master's Projects

Missense mutations can impact protein function and structure, yet their effects on protein function are difficult to predict. In this study, I compared two deep learning models, ESM1v and ESM1b, by evaluating their mutation predictions against experimental structural stability data. ESM1v showed a stronger correlation with experimental structural stability scores compared to ESM1b. A sigmoid curve was fitted to explore this relationship further. Over 100,000 mutations were identified where experimental stability differed significantly from model predictions. Many mutations that remained structurally stable experimentally but were predicted as harmful by the ESM models were frequently found at known functional sites. Structural …

Ribomoe: An Application Of Mixture Of Experts On Artificial Riboswitch Classification, Hainian Audrey Long

Master's Projects

Urban water sewage is a potential health concern due to its possibility to spread contagious RNA viruses such as Coxsackievirus B3. However, detection of viral particles remains challenging because of low viral concentrations in wastewater and high mutation rates of the RNA virus. To address this, this study proposes a novel viral detection method using synthetic riboswitches that bind to the target virus and trigger a reporter gene, amplifying the detection signals. To support the design of effective riboswitches, we present a machine learning model for classifying riboswitch performance, integrating RNA sequence data with secondary structural features. This model used …

Identifying Red Sponges On Arms Plates By Preprocessing Images Using Histogram Equalization, Barry Ng

Master's Projects

Sponges play a vital role in marine ecosystems, being the only organisms capable of converting dissolved organic matter (DOM) into particulate organic matter (POM). They provide nutrients for coral reefs to thrive in oligotrophic waters. Autonomous reef monitoring structures (ARMS) are used to measure the biodiversity of coral reefs by simulating the complex cavities inside reef structures. Organisms settle on them and scientists can retrieve them after a period of time for analysis. Images are taken of ARMS plates after they are retrieved. Human analysis is unsuitable for the analysis of ARMS plates due to the huge number of images. …

An Evidence-Based Approach To Predicting Pancreatic Ductal Adenocarcinoma, Surya Teja Nalluri

Master's Projects

Pancreatic ductal adenocarcinoma (PDAC) is a complex disease with hidden clinical indicators, so a reliable diagnosis of PDAC requires high precision and sophisticated analysis. Traditional probabilistic methods often rely on making unwarranted assumptions or undesirable approximations about probabilistic estimates, limiting their ability to provide the precision needed for correct diagnosis and treatment planning. In contrast, Dempster–Shafer Theory offers a formal framework for integrating uncertain and potentially conflicting evidence. This makes it well-suited for analyzing incomplete and ambiguous data typically associated with PDAC. By employing an evidential reasoning (ER) model based on Dempster-Shafer Theory, this approach systematically combines and evaluates imperfect …

Image-To-Text Transcription: Analyzing And Describing Visual Content, Zixiao Fan

Master's Projects

Image captioning, which provides a textual understanding of visual content, is the fundamental support for the advancement of Human-A.I. Interaction technology. In the hope of exploring the application of such technology, this project focuses on two specific goals. One is to directly explore the application of the image informationretrieving abilities, and the other is to dive into the specifics of the pipeline and components of image captioning models. As a result, this project presents a working app that exploits the text retrieval functionalities to enable image storage with functions like tagging and transcription. It also supports search functionality with a …

Galora: A Lightweight Graph-Aware Llm Framework For Node Classification On Text-Attributed Graphs, Mayur Choudhary

Master's Projects

With the exponential rise of language models (LMs) and their potential to understand semantic relationships, large LMs are being used across a wide range of applications. Text-attributed graphs (TAGs) are one notable example where LLMs can be combined with Graph Neural Networks (GNNs) to enhance node classification results. TAGs associate textual content with each node and are commonly seen in various domains such as social networks, citation graphs, recommendation systems, etc. Effectively modeling TAGs would enable deeper insights into different aspects of the graph and improve decision-making in relevant domains. We present GaLoRA, a parameter-efficient framework to integrate structural information …

Extraction Of A Knowledge Graph Of Biomedical Relationships, Brian Tran

Master's Projects

Rapid release in biomedical literature poses a challenge in linking information. This thesis aims to extract data from expanding datasets to identify and form meaningful relationships between biomedical entities. Large language models (LLMs) enable us to learn at a rapid pace. Creation of LLms from scratch are impractical. This thesis aims to collect a small dataset, containing biomedical papers, and use it to train large language models (LLMs) to extract entities from the text and learn the relationships between these entities. The experiment will be divided into two stages and utilize EU-ADR and ChemProt dataset. Starting with named entity recognition …

Performance Comparison Of Machine Learning Across Metal, Cuda, And Neuromorphic Frameworks, Ryan Saini

Master's Projects

Machine learning’s computational demands necessitate optimal performance and utilization. This research compares Apple Silicon M3 Pro with MPS, NVIDIA RTX 3070 GPU with CUDA, and neuromorphic computing for machine learning methods. We provide a cross-platform and cross-architecture performance analysis of machine learning methods to identify optimal configurations for training and inference scenarios. On traditional neural networks, Apple Silicon with MPS delivers superior energy efficiency at the cost of longer processing times for training and inference. NVIDIA with CUDA offers faster computation in training and inference at higher energy costs. Convolutional spiking neural networks perform competitively on event-based data, particularly on …