Physical Sciences and Mathematics Commons^™

Spatial Patterns Of Salamander Density Across Human Disturbance Gradients In Warner Parks​, Siobhan M. Day

Science University Research Symposium (SURS)

Amphibians are sensitive to anthropogenic disturbance, making them valuable indicators of recreational impacts in urban parks. This study examines salamander occurrence across five research sites within Warner Parks, Nashville, Tennessee, which differ in trail density and foot traffic intensity. Salamander observations were compiled from two sources: field surveys conducted in Summer 2025 and iNaturalist records spanning the past 10 years. For spatial analysis, each site was defined by a 200 m radius buffer to include local habitat, and trail networks were further buffered at 10 m, 25 m, and 50 m to quantify salamander occurrence relative to trail proximity using …

Music's Effect On The Mental Health Of Differing Age Groups, Margaret Cleve, Kaniyah Newborn, Luke Magro

Science University Research Symposium (SURS)

Mental health disorders are a significant concern in today’s society. Music therapy has been shown to be an effective intervention for conditions such as anxiety, obsessive-compulsive disorder (OCD), depression, and insomnia. However, it is not clear if the benefits function the same across different ages. The present study examined the influence of music on mental health across age using a publicly available dataset from Kaggle.com. We hypothesized that music listening would be associated with improved mental health outcomes regardless of age and that increased listening time would correlate with lower anxiety and depression. Results indicated that daily hours of music …

Cv: Jake Cho (Computer Science), Jake Cho

ECaMS Department Faculty Curricula Vitae

No abstract provided.

The State Of Our Streams: A Land Trust's Approach To Monitoring The Health Of Three Headwater Streams, Lauren Mcgrath

Sustainability Research & Practice Seminar Presentations

Lauren McGrath, Director of Watershed Protection Program, Willistown Conservation Trust, presents "The State of Our Streams: a land trust's approach to monitoring the health of three headwater streams."

Postmortem Vitreous Humor As An Alternative Matrix To Peripheral Blood For Benzodiazepine Detection, Sara Bussey

Honors Theses

Benzodiazepines are commonly prescribed secondary drugs of abuse that cause Central Nervous System depression through the neurotransmitter gamma aminobutyric acid. While not commonly fatal on their own, benzodiazepines have a minor risk for physical dependence and abuse. They also can have cumulative effects with other medications that can lead to overdose situations; thus, they are considered secondary drugs of abuse. While peripheral blood is considered the standard for xenobiotic detection in postmortem forensic toxicology, it is important to consider the validity of alternative matrices that could be analyzed in the event that blood was not available due to circumstances like …

A Systematic Review Of Poisoning Attacks Against Large Language Models (Llm), Patrick Mcguffin

Cybersecurity Undergraduate Research Showcase

This paper provides a comprehensive review of poisoning attacks against large language models (LLMs), drawing primarily from Fendley et al. (2025) and complementary studies from 2022–2025. It categorizes poisoning research into two key dimensions, Metrics and Specifications, to evaluate how attack success is measured and how attacks are implemented. This paper synthesizes quantitative results, experimental findings, and defense strategies across data, model, and multi-modal poisoning contexts. Finally, it highlights emerging challenges posed by self-adaptive and synthetic-data-driven LLMs, and proposes future research directions to strengthen model security and reliability.

Data Supporting “High-Resolution Lidar Observations Of Sedimentation-Induced Size Sorting Of Droplets Near A Laboratory Cloud Top”, Fan Yang, Yong Meng Sua, Zipei Zheng, Jesse Anderson, Hamed F. Sadi, Jae Min Yeom, Suryadey P. Singh, Pei Hou, Will Cantrell, Ernie R. Lewis, Alexander Kostinski, Raymond Shaw

Michigan Tech Research Data

Cloud optical properties and precipitation, which are crucial to weather and climate, are strongly influenced by cloud microphysical properties that are still poorly understood. Here, we develop a high-resolution time-correlated single-photon-counting lidar and apply it to observe cloud microphysical properties at one-centimeter range resolution in a convection chamber under well-controlled conditions. Together with concurrent in-situ measurements and theoretical analysis, our lidar observations indicate that although turbulent mixing tends to homogenize the cloud in the bulk region, entrainment and sedimentation cause inhomogeneities in droplet concentrations near the cloud top. Specifically, the topmost region is directly affected by entrainment, and lidar profiles …

Physical Activity And Memory Retention, Hannah Blackman, Marisa Ronner, Lindsay Biggs, Izzy Melendez

Science University Research Symposium (SURS)

Attached

Developmental Effects On Zebrafish Embryos Exposed To Alcohol, Tamya Mchaney

Science University Research Symposium (SURS)

Zebrafish are a good organism model due to their similarities with human biology. The transparency of their embryos allows for an easier view to see the developmental stages of the embryos, and easily and accurately note any mutations or defects in any of the embryos. In addition, they make excellent candidates to track potential effects that mirror human embryos with ethanol and alcohol will have on their developmental stages. The aim of this study was to measure the genetic size developmental differences of the embryo’s lens, eyes, and heart that are given 1% alcohol and 2% alcohol. This study’s experimental …

The Effect Of Leaf Composition And Structure On Decomposition Rates In Primula Sp. And Allium Schoenoparsum, Tatum P. Fortney, Kidist Aklile, Matty Mackay, Solomon Kap

Science University Research Symposium (SURS)

Decomposition is the process by which dead organic matter is broken down by bacteria and fungi. Leaves are a prominent form of organic matter that decomposes and enriches soil by returning nutrients. In this experiment, chive and primrose leaves were investigated. Chive leaves are thinner and softer, while primrose leaves are thicker and more dense, supporting our hypothesis that Chive leaf litter will decompose faster than primrose leaf litter because chives have a lower lignin content and are structurally narrower, making them easier to decompose. For this experiment, we placed around 4 grams of both species into a series of …

Proactllm: Proactive Conversational Information Seeking With Large Language Models, Shubham Chatterjee, Xi Wang, Shuo Zhang, Sajad Ebrahimi, Zhaochun Ren, Debasis Ganguly, Gareth Jones, Emine Arrousse, Hamed Zamani

Computer Science Faculty Research & Creative Works

Large Language Models (LLMs) have transformed information access by enabling human-like text understanding and generation. This workshop explores the next step for conversational AI: building proactive information-seeking assistants that go beyond reactive question answering. We aim to investigate how LLMs can anticipate user needs, model complex context, support mixed-initiative interactions, integrate retrieval and external tools, personalize responses, adapt through feedback, and ensure fairness, transparency, and cognitive grounding. Bringing together experts from NLP, IR, HCI, and cognitive science, the workshop will serve as a timely forum for advancing intelligent, proactive dialogue systems. It will also foster interdisciplinary collaboration.

The Effect Of Leaf Composition And Structure On Decomposition Rates In Primula Sp. And Allium Schoenoparsum, Tatum P. Fortney, Darlene Panvini, Kidist Aklile, Matty Mackay, Solomon Kap

Science University Research Symposium (SURS)

Decomposition is the process by which dead organic matter is broken down by bacteria and fungi. Leaves are a prominent form of organic matter that decomposes and enriches soil by returning nutrients. In this experiment, chive and primrose leaves were investigated. Chive leaves are thinner and softer, while primrose leaves are thicker and more dense, supporting our hypothesis that Chive leaf litter will decompose faster than primrose leaf litter because chives have a lower lignin content and are structurally narrower, making them easier to decompose. For this experiment, we placed around 4 grams of both species into a series of …

Metadata Analysis On The Relationship Between Sleep, Depression, And Cognition In Older Adults, Sara Miller, Kristie Stephens, Grayson Harris, Vincent Flegeance

Science University Research Symposium (SURS)

Metadata Analysis on the relationship between sleep, depression, and cognition in older adults

Abstract

Previous research has revealed that both sleep and depression play significant roles in influencing memory. Adequate sleep facilitates memory consolidation during rest, ultimately enhancing cognitive performance. In contrast, elevated levels of depression are associated not only with physical symptoms, but also with declines in cognitive functioning. The present study aims to determine whether the cognitive benefits of sufficient sleep duration outweigh the detrimental effects of depression on memory. We hypothesize that sleep duration will have a stronger influence on memory consolidation in older adults than depression. …

Evaluating The Effects Of Water Quality And Anthropogenic Disturbance On Salamander Species Diversity, Abundance And Health In Warner Parks, Tatum P. Fortney, Chase Kinsey

Science University Research Symposium (SURS)

Salamanders utilize cutaneous respiration, making them vulnerable to pollution, shifts in water chemistry, and habitat degradation. Increased anthropogenic habitat use may be a detriment to local salamander populations and pollution increases with land use. Understanding how water quality influences salamander abundance, diversity and physiological condition is crucial for amphibian conservation and for assessing freshwater ecosystem health, as they serve as a key bioindicator species. The objective of this study was to examine how variation in water quality parameters influences salamander species abundance, diversity and locomotor performance across stream sites within Warner Parks in Nashville, Tennessee. Field sampling was conducted weekly …

Synthesis And Characterization Of Eco-Engineered Hollow Fe2o3/Carbon Nanocomposite Spheres: Evaluating Structural, Optical, Antibacterial, And Lead Adsorption Properties, Islam Gomaa, Nikita Yushin, Mekki Bayachou, Vojislav Stani´, Inga Zinicovscaia

Chemistry Faculty Publications

This work presents a facile mechano-thermal route for the synthesis of carbon-decorated, hollow, mesoporous alpha-Fe2O3 microspheres. Comprehensive characterization (XRD, XPS, FT-IR, SEM/EDX, TGA, zeta-potential) confirmed the formation of phase-pure hematite with nanoscale crystallites (similar to 19 nm), substantial residual surface carbon (similar to 40 wt%) consistent with Fe-O-C linkages, and a positive surface charge (+15.9 mV). The hierarchical hollow/mesoporous architecture enables fast ion transport and provides extensive interior binding sites, resulting in rapid Pb(II) uptake that reaches 92% removal in approximate to 15 min at pH 5.0. The adsorption follows a Langmuir isotherm (q(max) approximate to 70.6 mg/g) and pseudo-second-order …

Detecting Generative-Ai-Enabled Polymorphic Malware: A Semantic-Behavior Approach, Allyson M. Morris

Cybersecurity Undergraduate Research Showcase

AI drastically reduces the effort required to produce malware that mutates both its code and behavior, thereby creating polymorphic and nondeterministic variants in which traditional signatures and many heuristic defenses fail. In this paper, I survey recent developments in AI-assisted malware generation, explain why conventional defenses are insufficient, and propose a layered detection architecture emphasizing semantic behavior, streaming anomaly detection, and defensive generative augmentation. I also outline why this approach generalizes to previously unseen AI-mutated samples, provide an evaluation plan with meaningful metrics, and describe a feasible MVP roadmap for practical deployment. Recent disclosures and threat intelligence further highlight the …

A Comprehensive Evaluation Of Next-Generation Firewall Effectiveness Against Encrypted And Evasive Threats In Enterprise Networks, John Costanzo, Favour Anene

Cybersecurity Undergraduate Research Showcase

Encrypted traffic is becoming a pillar of security and privacy in enterprise networks. According to Google Transparency Report, over 95 percent of internet traffic is encrypted with the use of Hypertext Transfer Protocol secure (HTTPS), Transport Layer Security (TLS) 1.3 and Quick UDP Internet Connections (QUIC). Although encryption safeguards confidentiality and integrity, it has also introduced new blind spots to the conventional security solutions. Encrypted channels are used to hide command-and-control (C2) traffic, issue malware and extract sensitive data without their notice.

To make the issue even harder, the opponents have sophisticated avoidance methods including traffic fragmentation, tunneling, and polymorphic …

Investigating The Security Vulnerabilities Of Ip Cameras: Classifications And Trends From Public Cve Data, Sam Oliver

Cybersecurity Undergraduate Research Showcase

Internet of Things (IoT) devices are increasingly targeted by cyber attacks due to weak authentication, insecure communication protocols, outdated firmware, and many other vulnerabilities. Internet Protocol (IP) cameras, a subset of these IoT devices, are particularly vulnerable and often transmit sensitive information. This paper analyzes vulnerability data from the National Vulnerability Database (NVD) to classify security vulnerabilities affecting IP cameras. Using this dataset, the paper examines the types and frequencies of these vulnerabilities, including authentication bypass, web interface exploits, and default and weak credentials. We additionally examine trends over time and across categories. This research aims to identify the primary …

Locations Of Outfalls In The Indian River Lagoon And Lake Worth Lagoon, Florida, Kelly M. Kibler, Melinda J. Donnelly, Vincent Encomio, Madison Giuntoli, Manisha Thenuwara, Brice Bennett, Laura Andrade Barron, Mariam Sonbol, Wynter Raine Seppala, Namritha Ramakrishnan, Jennifer Jordan Báez, Beth Orlando, Irene Arpayoglou, Melissa Meisenburg

Indian River Lagoon Shorelines

The spatial dataset: UCF_Outfalls_IRL_LWL.shp was created under grants from the Indian River Lagoon National Estuaries Program and Florida Sea Grant. These projects cumulatively led to creation of a living shoreline restoration prioritization model and hydrodynamic habitat suitability models for 1,550 km (963 miles) of estuarine shorelines in Indian River Lagoon (IRL) and Lake Worth Lagoon (LWL).

The dataset presented here includes the location of outfalls identified throughout the study region and general characteristics of the shoreline where they were identified.

Seagrass Persistence In The Indian River Lagoon And Lake Worth Lagoon, Florida, Kelly Kibler, Melinda Donnelly, Vincent Encomio, Madison Giuntoli, Manisha Thenuwara, Brice Bennett, Laura Andrade Barron, Mariam Sonbol, Wynter Raine Seppala, Namritha Ramakrishnan, Jennifer Jordan Báez, Beth Orlando, Irene Arpayoglou, Melissa Meisenburg

Indian River Lagoon Shorelines

The spatial dataset: UCF_seagrasspersistence_IRL_LWL.shp was created with support from the Indian River Lagoon National Estuaries Program and Florida Sea Grant. These projects cumulatively led to creation of a living shoreline restoration prioritization model and hydrodynamic habitat suitability models for 1,550 km (963 miles) of estuarine shorelines in Indian River Lagoon (IRL) and Lake Worth Lagoon (LWL). The dataset presented herein represents persistence of seagrass throughout waters of the IRL and LWL.

Soccer In-Game Event Classification Using Spatio-Temporal Data, Million Haileyesus

Theses and Dissertations

Classifying soccer ball events, such as pass, shot, ball loss, and ball out, are crucial for advancing game analytics and tactical insights. This thesis investigates the application of machine learning to classify these ball events using player and ball spatio-temporal data, as well as additional features. We implement and compare traditional machine learning algorithms (AdaBoost, Logistic Regression, and Random Forest) with several deep learning approaches, including Feed-Forward Neural Network (FFNN), sequence-to-sequence (seq2seq) recurrent models (Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU)), and Transformer. Our experiments, evaluated on a dataset comprising of three professional soccer matches using accuracy, precision, …

Efficient Multimodal Streaming Recommendation Via Expandable Side Mixture-Of-Experts, Yunke Qu, Liang Qu, Tong Chen, Quoc Viet Hung Nguyen, Hongzhi Yin

Research outputs 2022 to 2026

Streaming recommender systems (SRSs) are widely deployed in real-world applications, where user interests shift and new items arrive over time. As a result, effectively capturing users' latest preferences is challenging, as interactions reflecting recent interests are limited and new items often lack sufficient feedback. A common solution is to enrich item representations using multimodal encoders (e.g., BERT or ViT) to extract visual and textual features. However, these encoders are pretrained on general-purpose tasks: they are not tailored to user preference modeling, and they overlook the fact that user tastes toward modality-specific features such as visual styles and textual tones can …

11.10.2025 Ored Connect, Liz Williamson

ORED Newsletter

• Sherilyn Hulugalla winds Biosafety and Biosecurity Month Challenge

Contrasting Effects Of Impervious Cover On Riparian Plant And Soil Bacterial Communities In A Rapidly Urbanising Himalayan City, Karma Jamtsho, Mark A. Lund, David Blake, Eddie Van Etten

Research outputs 2022 to 2026

Rapid urbanisation—particularly the expansion of impervious surfaces—is reshaping riparian landscapes worldwide. These areas are frequently targeted for development due to their favourable topography, abundant water resources, and aesthetic appeal. However, the impact of increasing impervious cover on soil bacterial communities in biodiverse urban riparian zones remains poorly understood, especially in developing countries, raising concerns about potential declines in essential ecosystem functions. In this study, we investigated the effects of impervious cover, quantified as the Percentage of Total Impervious Area (PTIA), on the taxonomic and functional diversity of riparian soil bacteria in Thimphu City, Bhutan. Using plot-based taxonomic profiling and metagenomic …

Correcting Class Imbalance Through Synthetic Training Data And 3d Modeling For Carabid Pitfall Trap Sampling, Blair Mirka

Geography ETDs

Crowdsourced biodiversity data provide an accessible foundation for large-scale ecological monitoring, but class imbalance limits automated species identification, particularly for rare taxa. This research explores the use of synthetic training data generated from 3D models of carabid beetle museum specimens to improve detection and classification performance for underrepresented species in crowdsourced datasets. High-resolution 3D models were created to simulate variation in lighting, orientation, and background. These synthetic images were incorporated into convolutional neural network training datasets at varying synthetic-to-real ratios to assess their impact on classification accuracy. Models were evaluated using controlled pitfall-trap imagery to examine the influence of scene …

Air Emissions From Combustion And Incineration Processes: Insights Into Air Quality And Us Epa Regulations, Madjid Delkash

All Faculty Scholarship (Archived)

The escalating global generation of waste necessitates robust and environmentally sound management strategies. Among these, combustion and incineration processes play a crucial role in waste volume reduction and energy recovery. Nevertheless, these thermal treatment methods are significant sources of atmospheric pollutants, impacting air quality and public health. This review systematically examines air emissions from four major incineration types regulated under the U.S. Environmental Protection Agency’s (EPA) Clean Air Act (CAA) Sects. 111 (New Source Performance Standards [NSPS]) and 129 (National Emission Standards for Hazardous Air Pollutants [NESHAP]). These categories include Large Municipal Waste Combustors (LMWC), Hospital/Medical/Infectious Waste Incinerators (HMIWI), Commercial …

An Integrated Ca–Markov Modeling Framework For Forecasting Land Use And Land Cover Dynamics In Arkansas, Usa, Rasool Vahid, Mohamed H. Aly

Environmental Dynamics Faculty Publications and Presentations

Land use and land cover (LULC) changes significantly shape urban environments and directly impact ecological and socioeconomic systems. This study aims to explore these interconnections by employing the Cellular Automata–Markov (CA–Markov) model to assess and predict LULC dynamics in Arkansas. Historical LULC datasets from 2001 to 2021, obtained from the National Land Cover Database, were simplified from 11 into 5 classes to facilitate analysis and effectively map transitions. The model was validated by predicting LULC for 2016 and 2021 and comparing the predictions with the real maps, achieving an overall accuracy of approximately 91.9%, using model validation metrics, including precision, …

Re: Butte Priority Soils Operable Unit (Bpsou) 2025 Monthly Progress Report. Consent Decree For The Butte Priority Soils Operable Unit. Civil Action No. Cv 89-039-Bu-Seh, Josh Bryson

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Software-Defined Networking Powered By Ai-Driven Anomaly Detection, Dina Moloja, Vusumuzi Malele Prof

Journal of Cybersecurity Education, Research and Practice

Software Defined Networking (SDN) revolutionizes network control by separating the control plane from the data plane. Although the latter improves SDN agility and scalability, it creates a security hole, particularly in a central control plane, leading to SDN environments becoming high-profile targets for advanced cybersecurity threats. Due to static and signature-based point-in-time behavior, traditional security methods are unable to keep up with modern attacks that are an anomaly to SDNs. Artificial Intelligence (AI) with its different applications and techniques, has the capability of detecting SDN cyber threats’ anomalies. This paper presents the results of a literature scoping exercise that used …

Using Compartmental Systems Of Ordinary Differential Equations And Optimal Control Theory To Compute Ideal Quantities Of Mentors For Student Populations, Timofey B. Gafurov

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.