Physical Sciences and Mathematics Commons^™

Insecticide Resistance Profile In Nashville Culex Spp. Mosquito Populations, Ellie Sebaugh, Zachary Bement, Abelardo Moncayo, Darlene Panvini

Science University Research Symposium (SURS)

Mosquitoes may develop resistance to insecticides used by control programs, potentially increasing population density and the risk of mosquito-borne diseases. Culex spp. mosquitos are the primary vector of West Nile Virus (WNV), the leading cause of mosquito-borne disease in the United States and a reportable disease in Tennessee. Resistance profiles were constructed for two insecticides, permethrin and malathion, in a Culex spp. population from Nashville, Tennessee. Adult female mosquitoes were live-captured using gravid traps and tested using the Centers of Disease Control and Prevention (CDC) bioassay protocol to assess resistance or susceptibility. Three inhibitors were also included to identify metabolic …

Fisheries Science Update - Western Australian Shark Resource: 2024 Stock Assessment Outcomes, Department Of Primary Industries And Regional Development, Western Australia

Fisheries Science Updates

The Western Australian (WA) shark resource includes more than 100 species of sharks and rays.

Key shark species are sustainably harvested in two commercial shark fisheries that provide fresh, local, affordable seafood to the WA community.

The WA shark resource has been in recovery since the 1990s–2000s when stocks were found to be at risk.

The Department of Primary Industries and Regional Development (DPIRD) tracks stock status by undertaking periodic weight of evidence stock assessments of indicator species.

Gummy, whiskery, dusky whaler, and sandbar sharks, are the indicator species for the WA shark resource, and make up ~80% of the …

Identifying Superior Finger Millet (Eleusine Coracana L.) Landraces Using The Multi-Trait Genotype-Ideotype Distance Index (Mgidi), Sujan Chapagaina, Bishnu Prasad Kandela, Sudikshya Shresthaa, Ankur Poudela, Shubh Pravat Singh Yadavb

Extension Publications

Genetic variability and selection are crucial for finger millet breeding programs to maximize genetic gain and productivity. This study evaluated 18 finger millet landraces cultivated in the mid-hills of Nepal, along with ‘Kavre Kodo 2’ as a check variety, assessing 14 agro-morphological traits. The objective was to identify superior finger millet landraces using a multivariate approach based on the multi-trait genotype– ideotype distance index (MGIDI). The experiment was conducted in a randomized complete block design (RCBD) with three replications. Principal component analysis revealed that the first five components collectively accounted for 80.8% of the total variation, reflecting the genetic relatedness …

Impact Of Height On Primrose Leaf Litter Decomposition, Lilianna Wrenne, Jacey Cardenas, Danner Brown, Wyatt Fooks, Darlene Panvini

Science University Research Symposium (SURS)

Decomposition is a crucial process in nutrient cycling, where dead organic matter turns into nutrients for the environment. Height is a significant abiotic factor that can influence these factors. Dried primrose was chosen for this experiment to test how much height affects decomposition; 8 mesh bags were filled with 4.0g of dried primrose leaves. Four bags were placed at ground level, and four were placed on top of a plant, 2ft above the ground. Using the fishing line, the bags at each site were tied together to prevent them from blowing away. By changing the height of the plants, the …

Comparative Decomposition Rates Of Prickly Pear And Sage Using Litterbags, Curtis Jang, Vy Ly, Ashlyn Reagan, Ellie Sebaugh, Darlene Panvini

Science University Research Symposium (SURS)

Litterbags are used to study nutrient cycling and track the rate of decomposition over time. Decomposition rates may vary between plant species due to various factors. One factor includes the abundance of lignin, or a structural component that provides support to a plant, which can slow the rate of decomposition. This study compared the decomposition rate of sage (Salvia officinalis), which has higher lignin levels, and prickly pear (Opuntia humifusa), which has higher water content and thus lower lignin levels. Four samples of each species, with two replicates each, were initially weighed and then placed in …

Presence Of Ophiognomonia Clavivignenti-Juglandacearum On Juglans Cinerea At Beaman Park In Nashville, Tennessee, Corinne Parker, Kidist Aklile, Darlene Panvini

Science University Research Symposium (SURS)

Butternut trees, (white walnut, Juglans cinerea), are infected by a fatal canker, Ophiognomonia clavigignenti-juglandacearum (O-cj), which impacts the survival and population density of the species. Once found throughout the eastern United States, the species has decreased considerably. Due to its uncommon occurrence in Middle Tennessee, the conditions of J. cinerea were investigated at Beaman Park in Nashville, TN. All butternut trees were hypothesized to be infected by O-cj. Each known tree in the park was examined to assess its bark health and determine the presence of the canker. Ecosystem analyses around each tree included surveys of soil characteristics, …

Symbolic Execution Engine For Dynamic Analysis Of System Software, Pansilu Madhura Bhashana Pitigala Arachchillage

Dissertations and Theses Collection (Open Access)

System software, like any regular software, is prone to errors. It plays a specific role in a computer system by managing the underlying hardware and providing a platform to execute the application software. Defective or vulnerable system software can be exploited by attackers to compromise the entire system. Therefore, the system software must be studied and thoroughly analyzed to evaluate its security. However, due to the inherent complexity and its close interactions with the hardware, analyzing system software is a challenging task. As a result, there is a lack of tools and techniques capable of effectively analyzing system software.

This …

Graph Perturbations For Robust Knowledge Discovery And Retrieval, Hanhua Xiao

Dissertations and Theses Collection (Open Access)

Graph perturbation, rooted in classical perturbation theory, studies how small topology edits, i.e., adding or deleting edges, affects graph properties (e.g., density, centrality). This fundamental problem underpins applications like bioinformatics, privacy preservation and system defense. While much prior work targets perturbations that influence global graph statistics or model outputs, comparatively little addresses robustness for knowledge discovery and information retrieval. In these settings, graphs are attributed: nodes carry real-world semantics (e.g., locations, people) and edges encode interactions or relationships. This thesis proposes new formulations and algorithms that generate and leverage graph perturbations to make knowledge discovery and retrieval more robust. Specifically, …

Energy-Harvesting Concurrent Lora Mesh With Timing Offsets For Underground Mine Emergency Communications, Hilary Kelechi Anabi, Samuel Frimpong, Sanjay Madria

Mining Engineering Faculty Research & Creative Works

Underground mine emergencies destroy communication infrastructure when situational awareness is most critical. Current systems rely on centralized network infrastructure, which fails during emergencies when miners are trapped and require rescue coordination. This paper proposes an energy-harvesting LoRa mesh network that addresses self-powered operation, interference management, and adaptive physical layer optimization under severe underground propagation conditions. A dual-antenna architecture separates RF energy harvesting (860 MHz) from LoRa communication (915 MHz), enabling continuous operation with supercapacitor storage. The core contribution is a decentralized scheduler that derives optimal timing offsets by modeling concurrent transmissions as a Poisson collision process, exploiting LoRa's capture effect …

Enhancing Multi-View, Multi-Modal Sensing, Perception And Actuation For Edge Intelligence, Dhanuja Tharith Wanniarachchige

Dissertations and Theses Collection (Open Access)

Artificial Intelligence of Things (AIoT) technologies have ushered in exciting new advances in intelligent sensing, perception, and actuation for many real-world cyberphysical systems (CPS) applications. These technologies have had a formidable impact in domains such as large-scale video surveillance, autonomous transportation and robotics, precision healthcare, and industrial automation. In these applications, sensors and actuators are often collocated with processing nodes, and such nodes are typically interconnected via wireless networks. Vision-based machine intelligence, exemplified by tasks such as object detection, object tracking, and activity analysis, is a very common enabler of such CPS applications. Efficient execution of Deep Neural Network (DNN) …

2025 November - Tennessee Monthly Climate Report, Tennessee Climate Office, East Tennessee State University

Tennessee Climate Office Monthly Reports

Hi All,

The month of November 2025 averaged warmer than normal by 2-4°F across most of the state. The northeastern corner of TN was closer to average, with a few areas even slightly cooler than normal. Additionally, November was drier than normal for most areas, with the exception of a few parts of the Cumberland Plateau and in East TN where heavier bands of precipitation set up while most of the state recorded only light rainfall.

The main weather and climate story of November 2025 was the early taste of winter that impacted the state November 9-12, which also coincided …

Impact Of Lignin Content On Decomposition Rates, Lindsey Powell, Olivia Fawkes, Moses Elijah Cadawas, Isaac Paul Dent, Darlene Panvini

Science University Research Symposium (SURS)

This study aimed to analyze decomposition rates of plants containing different amounts of lignin. Lignin can be found within cell wall structures in plants and aids in natural rigidity. Opuntia humifusa was chosen to represent plants with high levels of lignin, and Allium schoenoprasum was chosen in contrast because of its significantly lower levels of lignin. Due to these characteristics, A. schoenoprasum is hypothesized to decompose at a quicker rate than O. humifusa. To test this hypothesis, eight samples of O. humifusa and eight samples of A. schoenoprasum were placed in litter bags to prevent macroorganisms from aiding in …

Assessment Of Nature Based Solutions Through Soil Microbial Community Diversity Using Biolog Ecoplates™, Roma C. Brassell, Lili M. Wrenne, Darlene Panvini

Science University Research Symposium (SURS)

Nature-based solutions (NBS) mimic the functions of natural environments to promote ecosystem services beneficial to society and biodiversity, which is especially crucial to urban environments. On a college campus in an urban landscape, how do NBSs affect soil microbial diversity? Three soil samples were collected from seven locations across Belmont University’s campus in Nashville, TN: a community garden, rose garden, indigenous-people’s garden, manufactured creek, two green roofs, and an alley-berm as the control. To characterize each site, the pH, nitrogen and phosphorus level, percent moisture, and soil type were determined. Plant diversity and percent coverage were assessed using a 1 …

An Update & Exploration Of The Herbarium At Belmont University, Corinne Parker, Darlene Panvini

Science University Research Symposium (SURS)

The Belmont University Herbarium is a collection of plant samples used to catalogue species for research and teaching. These specimens have been collected by Belmont students since 1973, helping to document the flora of Middle Tennessee. This semester the specimens have been organized, and identifications have been confirmed. An Excel spreadsheet was developed to record the specimens. This allowed for analyses of the 1,790 specimens by phylum and family. The updated organization of the herbarium and spreadsheet allows for faster specimen retrieval and identification of target species for future collection.

“The Role Of Machine Learning In Social Media Content Moderation”, Bethaney A. Mallory-Smothers

Science University Research Symposium (SURS)

The majority of the world's over one billion active users depend on large-scale machine learning based social media platforms to personalize content through various methods of curation. Recommendation systems use many types of machine learning model including collaborative filtering, content-based filtering and deep learning to find what a specific user is likely to be interested in, and therefore increase user engagement. As beneficial as this is to the user experience, it has also generated a significant amount of concern about both bias in recommendations and the dissemination of false information on the web, as well as issues related to the …

Bioaccumulation Pattern Of Per- And Polyfluoroalkyl Substances (Pfas) In Fish Tissues From Two Freshwater Systems, Margaret D. Taiwo, Husam Kafeenah, David D. Duvernell, Michael O. Eze

Biological Sciences Faculty Research & Creative Works

Per- and polyfluoroalkyl substances (PFAS) are known for their persistence, ubiquity, bioaccumulation in different matrices of the environment and their detrimental effect on human health. In this study, we used EPA 1633 to examine the prevalence of ten PFAS compounds in two freshwater systems and investigated their bioaccumulation pattern across different tissues of grass carp fish (Ctenopharyngodon idella), common carp (Cyprinus carpio), and flathead catfish (Pylodictis olivaris). Among the PFAS compounds analyzed, PFBS exhibited the highest concentration in the freshwater sample, exceeding the U.S. EPA regulatory limit of 4 ng/L for drinking water. The total PFAS concentrations in the muscle, …

Resource Assessment Report No.6: Western Rock Lobster Resource - 2025 Update Assessment, Simon De Lestang, Emma-Jade Tuffley

Resource Assessment Reports

Executive Summary

The western rock lobster (WRL) fishery is considered sustainable with catches being slightly below those associated with the maximum economic yield (MEY) proxy (39% harvest rate), which ensures the large lobster biomass and economical catch rates are maintained. The marine environment continues to be the biggest driver in stock dynamics with post larval recruitment (puerulus) and adult behaviour, including catchability, strongly influenced by oceanic conditions. Recent seasons have seen strong Leeuwin Currents and warm ocean conditions. Over the past few seasons, puerulus settlement levels have been below average at numerous locations and it has been almost 10 years …

Scaling Up Cooperative Multi-Agent Reinforcement Learning, Minghong Geng

Dissertations and Theses Collection (Open Access)

Multi-agent systems (MAS) involve multiple autonomous agents that coordinate their actions to achieve shared or competing objectives in dynamic environments. Over the past decade, multi-agent reinforcement learning (MARL) has emerged as a powerful paradigm for enabling collaborative behaviors among autonomous agents within MAS to solve complex tasks. This dissertation discusses a critical scalability gap that exists between current MARL capabilities and real-world deployment requirements. Most existing MARL research focuses on small-scale laboratory problems, often struggling to coordinate large agent populations and facing challenges with extended decision-making horizons. In contrast, many real-world applications demand coordination among hundreds or thousands of agents …

Composition Pedagogy As Ai‑Native Coding: From Design Kit To Scholarly Framework, Daniel Plate, James Hutson

Faculty Scholarship

This article advances a field-ready framework that reconceives first-year composition as AI-native coding, translating a complete “design kit” into scholarly method, evaluative protocol, and curriculum architecture. Background: Contemporary composition pedagogy emphasizes process, genre awareness, and collaborative revision; meanwhile, modern software practice operationalizes iteration through version control, test-driven development, and continuous integration. The uploaded kit demonstrates that these cultures are isomorphic: writing stages align with SDLC phases, and automated pipelines can lint prose, execute argument “tests,” and publish artifacts with auditable histories. Approach: The study systematizes that kit into (1) a conceptual map that recasts authorship as orchestration and verification, (2) …

Perspectives On Firearm Storage Conversations: Summary Of Health Care Provider Interviews And Parent Focus Group, Rachel M. Gallo Mph

Publications

This report summarizes perspectives from Maine parents who own firearms and health care providers on safe firearm storage and related conversations in health care settings. Through interviews and a parent focus group, the project explored how firearms are stored, what influences storage decisions, and how families and providers feel about discussing firearm safety. Parents emphasized the importance of responsible ownership, education, and individualized storage solutions, while identifying cost as a key barrier to safer storage options. Many health care providers expressed interest in addressing firearm safety but cited limited time, lack of training, and concerns about patient trust as challenges. …

Advancing Security Safeguards In Large Language Models Through Multi-Agent Systems, Mohammed Rashed Alnuaimi

Theses

This thesis focused on enhancing the safe use of Large Language Model (LLM) through the innovative use of a Multi-Agent System (MAS). As LLMs like ChatGPT became essential to our everyday interactions, the need to maintain the safe use of these systems increased. This research thoroughly assessed the current security measures in place for LLM, pointed out their limitations and developed new and more effective security strategies. The core of the proposed solution was a MAS designed to ensure that all data processed by LLM met guidelines including Privacy, Confidentiality, and Ethical standards before reaching the user. The system involved …

Detecting Data Poisoning Attacks In Medical Imaging: A Study On Chest X-Ray Classification Tasks, Akhila Abdulla Asgar

Theses

This thesis examines the vulnerability of AI medical imaging models to adversarial threats, with a specific focus on data poisoning attacks in chest X-ray classification. The study begins with a Systematic Literature Review (SLR) to assess the existing adversarial attacks and defenses in medical imaging, revealing a significant research gap in studies exploring data poisoning attacks in the medical domain. Based on our literature search, an efficient and lightweight defense, namely friendly noise defense, against data poisoning has not been investigated in medical imaging classification tasks. Hence, in this work, we investigated its effectiveness on the chest X-ray dataset, and …

Startup Success Forecasting Through Machine Learning: A Comprehensive Analysis Of It Startups, Khaled Abdulla Alhassani

Theses

Lately, startups attracted significant attention from investors throughout the previous years. This raised several questions concerning startups and what they possibly define as them. It could refer to collective individuals who focus on innovative ideas with a reproducible and scalable business model; others refer to it as a newly established business. Nevertheless, all these definitions lead to a predictive question. Will these startups face success?

This study explores startup success prediction methods, focusing on forecasting information technology startup (SIT) insights using Machine Learning (ML) models such as Random Forest (RF), Decision Tree (DT), Support Vector Machine (SVM), K-Nearest Neighbor (k-NN), …

Evaluating Large Language Models For Automated Cv Ranking: A Hybrid Embedding Approach For Enhanced Recruitment, Sarah Mohamed Alhindaassi

Theses

Increasing numbers of applications have revealed limitations in legacy keyword-filtering-based Applicant Tracking Systems (ATS), which commonly overlook candidate potential and ignore contextual or transferable skills. Advances in Natural Language Processing (NLP) and Large Language Models (LLMs) offer an exhilarating alternative, supporting context-sensitive and human-crafted reasoning in candidate evaluation. This thesis systematically evaluates four classes of approaches, lexical models, embedding-based methods, Large Language Models (LLMs), and hybrid ensembles, for automation of Curriculum Vitae (CV) to Job Description (JD) matching without exploiting prior annotations or annotations at match time. Using a combination of publicly available datasets and real-world sample data covering three …

Enhancing The Acceptability Of Decision-Making System Using Xai Case: Crime Profiling System, Mohamed Saeed Al Shamsi

Theses

In the current world, we need to place more emphasis on how easily interpretable, accurate, and acceptable data analysis results are, given that essential operations in law enforcement, among other sectors, are backed up by the use of complex computing systems. Crime profiling systems that use crime data for profiling encounter major problems because they depend on algorithm-based methods. These methods can be ambiguous and inaccurate, leading to low public acceptability. The study investigates major problems with Complex Crime profiling systems (CPS) because their unexplained algorithms result in system performance issues and public scepticism. XAI provides a solution to handle …

Cobalt Layered Double Hydroxide As Advanced Electrode Materials For Supercapacitors And Electrocatalysis, Wafa Sultan Alaryani

Theses

Due to the high demand for sustainable energy storage options and efficient energy conversion devices, extensive research has been conducted on various electrode materials. This thesis is concerned with the fabrication of electrode material mainly using cobalt-based material, particularly cobalt layered double hydroxides (Co-LDH) with the combination of nitrogen-doped carbon nanotubes (N-CNTs) to be used in supercapacitors and oxygen evolution reactions (OERs) applications. The main objective is to enhance the electrochemical performance of supercapacitors and to develop a novel electrode material for a more stable and efficient OER in alkaline medium.

The methodology involved a one-step hydrothermal procedure to synthesize …

Enhanced Privacy Preserving Healthcare Data Management With Federated Learning Using Homomorphic Encryption, Omar Abdulla Ali

Theses

Federated Learning (FL) is a decentralized approach of machine learning on multiple clients jointly training models without sharing their raw data, which drastically improves privacy and enhance protection against security breach. This is particularly critical in the healthcare sector, where hospitals and medical institutions are often unable to exchange patient records due to strict privacy regulations and data-management policies. However, there is still a risk of privacy breach when clients send their model updates to the central server, because if a model update is intercepted or analyzed by a malicious entity, it could be used to recover sensitive data using …

Determination Of Variations In Orbital Parameters Of Sample Of Satellites Through Spacecraft Tracking, Asma Ali Alasmari

Theses

The continues increasing density of Resident Space Objects (RSOs) in Earth’s orbit highlights the crucial need for Space Situational Awareness (SSA). This thesis studies the orbital changes in two regions, active low Earth orbit (LEO) satellites and inactive geostationary Earth orbit (GEO) satellites. For LEO satellites we used publicly available data (two line element TLE from Space-Track) and ASTRIAGraph. We verified the orbital elements series and time ordered them, applied a Hampel (median+MAD) mask to semi-major axis, eccentricity vector and inclination to find outliers and exclude them from event detection. The events are then detected using time normalized slopes and …

The Simulation Of Hyperspectral Observations By The Upcoming Spacecraft "Arab Satellite 813", With The Radiative Transfer Model Sciatran, Sara Maher Alhasan

Theses

The Arab Satellite 813, which is scheduled to be launched in 2025/2026 by the UAE Space Agency, is set to increase earth observation and monitor the climate across the middle East and North Africa (MENA) region. This study uses the SCIATRAN radiative transfer model which was originally developed for the Envisat mission to simulate the hyperspectral observation specifically tailored for the satellite's payload. Using calibrations that were used by the previous research in their SCIATRAN V4.6 study and adjusting parameters like the Leaf Area Index (LAI), a simulation which agreed robustly with the benchmarks set by the previous research was …

Enhancing It Security Management With An Advanced Intrusion Detection System Based On Machine Learning And Explainable Ai, Hanan Aslam Al Zubaidi

Theses

The fast changing landscape of cyber threats continues to challenge the development of strong and reliable security frameworks for IT management systems. Traditional defense tools, such as Intrusion Detection Systems (IDS), often struggle to keep up with today's advanced and constantly evolving attack methods. This thesis explores these ongoing challenges and looks into how machine learning (ML) and explainable artificial intelligence (XAI) can be used to boost IDS performance.

The research outlines a smart, adaptive system that combines supervised learning for real-time threat detection, unsupervised models for anomaly analysis, and proactive defense strategies. The goal is to improve detection accuracy, …