Physical Sciences and Mathematics Commons^™

Quantifying The Short-Term Hydrogeologic Responses Of Highway Construction In Hot Springs, Arkansas, Billy Jack Summerford

Graduate Theses and Dissertations

In late 2020, excavation for the Highway 5 Bypass in Hot Springs, Arkansas exposed seepage faces along roadcut walls. Groundwater levels at nearby wells decreased by up to 20.9 ft and have remained ~20 ft below pre-construction values on average. This study quantifies changes in storage in the unconfined aquifer within the Hot Springs thermal recharge zone associated with the seepage faces using a numerical groundwater model calibrated to pre-construction head at well ARb4. Model scenarios are used to evaluate whether construction-induced seepage or drought best explains the decrease from late 2020 to early 2021. The numerical groundwater simulation represented …

Impacts Of Climate-Smart Agriculture On Greenhouse Gas Emissions In Southeast Arkansas Cotton, Cassandra Seuferling

Graduate Theses and Dissertations

Increasing concerns of climate change have led to the evaluation of greenhouse gas (GHG) emissions [i.e., carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O)] from agroecosystems, particularly cotton (Gossypium hirsutum) production. Technology improvement and conservation agriculture methods [i.e., reduced-tillage (RT) instead of conventional tillage (CT) and the use of cover crops (CC)] require further evaluation regarding GHG emissions from Arkansas cotton production. The first objective of the study was to evaluate four gas-flux-determination methods [i.e., linear or exponential regression models, with negative fluxes (WNF) included in the dataset or replacing negative fluxes (RNF)] on CO2, CH4, and N2O fluxes …

Privacy Protection In Machine Learning: Methods For Structured And Unstructured Data, Karuna Bhaila

Graduate Theses and Dissertations

As machine learning models become increasingly integrated into data-driven decision-making, the protection of sensitive information throughout the model lifecycle is a paramount concern. As these models process and memorize sensitive, proprietary, or personal data, they risk leaking information through their outputs or internal states, especially in domains such as healthcare and finance. The protection of data in machine learning has thus been a crucial field of study. Within this paradigm, researchers have studied theoretical and application-oriented mechanisms for realizing privacy protections for various data formats. Nonetheless, privacy in machine learning still has many open problems, especially with the emergence of …

Toward Causal Generative Modeling: From Representation Learning To Controllable Generation, Aneesh Komanduri

Graduate Theses and Dissertations

The hallmark of human intelligence is causal reasoning, the ability to infer relationships between causes and effects through observation and intervention. While modern deep learning has excelled at identifying statistical patterns, current generative models often struggle to capture the underlying structural causal mechanisms of the data-generating process, leaving them vulnerable to shortcut learning and spurious associations. To achieve true generalizability and interpretability, artificial intelligence must transition from simple association to higher-level causal reasoning to be capable of scheduling and planning in the real world. This dissertation develops fundamental methodologies for causal generative modeling by integrating Pearl’s Structural Causal Model (SCM) …

The Impact Of Quantum Computing On Ransomware, Byron Denham

Graduate Theses and Dissertations

Ransomware is one of the most pervasive and dangerous threats to cybersecurity today. Attacks involving ransomware have been responsible for the disruption of critical services in many fields including healthcare, education, and government. In the current paradigm, crypto ransomware relies on asymmetric cryptography to perform its operations in a way that ensure the victim’s only chance for file recovery is by paying the attacker’s requested ransom payment. However, advancements in quantum computing threaten the asymmetric cryptography that ransomware relies on. It has been shown that, once developed, a sufficiently powerful quantum computer will have the ability to break asymmetric cryptography …

Efficient Deep Neural Networks For Autonomous Perception, Reeshad Khan

Graduate Theses and Dissertations

Autonomous perception systems must operate reliably under uncertainty arising from noisy observations, incomplete supervision, and hardware constraints. This dissertation investigates the design of efficient deep neural networks for autonomous perception through a unified perspective that treats uncertainty, efficiency, and sensing as interconnected challenges. The first contribution develops adaptive extensions of unbiased risk estimators, including eSURE and ePURE, enabling unsupervised training of deep neural networks for magnetic resonance image denoising under Gaussian and Poisson noise. However, these methods rely on known noise assumptions, which motivates the second contribution: a unified diffusion and Bayesian risk framework that estimates and adapts to unknown …

Developmental Mathematics As A Potential Barrier To Degree Completion In Community Colleges, Cynthia Bernice Fletcher

Graduate Theses and Dissertations

Developmental mathematics is often seen as a barrier to student progression in community colleges, especially for students pursuing Associate of Science degrees requiring math coursework. This quantitative, ex post facto, non-experimental study examined how developmental mathematics factors predicted Associate of Science degree completion at a two-year community college in the West South-Central United States. Specifically, it assessed how academic performance in developmental mathematics, placement method, math pathway, and number of developmental math courses related to Associate of Science degree completion, as well as differences across student subgroups. Archival institutional data were used for first-time-in-college students across four cohorts: 2018, 2019, …

Genre Prediction Using Rnns And Llm-Enhanced Video Game Review Data, Gabriel Young

Graduate Theses and Dissertations

LLMs (Large Language Models) are powerful tools for engaging with textual data, carrying many advantages over classical NLP (Natural Language Processing) and ML (Machine Learning) approaches. However, a classical ML model can still be faster, more efficient to run, and accessible than an LLM. We seek to gain the benefits of LLM text comprehension and preserve them in a classical ML model, a hybrid approach. The LLM operates on text to surface relevant information and associations in our problem space, then the ML model trains on the LLM output. The model may learn from the LLM and provide a more …

Structural Relaxation In Glass-Forming Liquids At Extreme Pressure: Photon-Correlation Spectroscopy And Constrained Thermodynamic Surface Modeling, Kevin Wayne Lyon

Graduate Theses and Dissertations

Structural relaxation in glass-forming liquids is strongly dependent on both temperature and pressure, yet direct measurement of structural α-relaxation under multi-gigapascal compression has remained experimentally challenging. This work extends depolarized photon correlation spectroscopy (DPCS) to pressures approaching 5 GPa in a diamond anvil cell, representing the highest-pressure implementation of this technique and enabling direct measurement of the structural α-relaxation in a pure liquid at extreme compression. This capability provides access to dynamical regimes previously unexplored by photon correlation spectroscopy and establishes a platform for probing glassy dynamics at high pressure. To describe these measurements, a constrained relaxation-time surface framework is …

From Phenology To Yield Zones: Functional Clustering Of Satellite Time Series For Crop Growth Monitoring, Ikram Morso

Graduate Theses and Dissertations

Remote sensing and land surface phenology provide a strong basis for characterizing crop development, but their usefulness for within-field yield-zone delineation depends on whether crop development is analyzed as a phenological trajectory and whether the resulting zones are evaluated with spatially defensible statistics. These questions are especially relevant in soybean production because soybean is one of the most important row crops in the United States and the country’s dominant oilseed crop. This relevance is strong in Arkansas, where soybean is a major component of agricultural production. In soybean production, within-field yield variability reflects the combined influence of soil properties, stand …

Sel & Hil Integrations For Real-Time Cyber Threat Modeling, Risk Assessment, And Result Validation, Zachary Coel Harris

Graduate Theses and Dissertations

The electrical power grid is one of the most critical infrastructure systems, with virtually every other critical system relying on its electricity to operate effectively [1]. One failure in the electrical grid can have cascading effects, reducing, or outright stopping the operation of services vital to people’s lives. Ensuring continuous availability of the electrical grid is vital. This constant need for availability poses a challenge to identify potential cyber-attacks and their impacts. The grid is constantly growing with the addition of DERs (Distributed Energy Resources). Common DERs, such as photovoltaic systems or wind farms, can provide primary or secondary generation …

Solid Embedded Telemetry, Pranav Balasubramanian Natarajan

Graduate Theses and Dissertations

This thesis explores the integration of the Solid decentralized data framework within embedded and legacy energy control systems to enable secure, access-controlled, and interoperable data exchange. Two implementations were developed to evaluate Solid’s practical applicability: an ESP32 client implementing Solid-OIDC authentication and telemetry publication to a Solid Pod, and a Modbus-to-Solid bridge translating Modbus RTU communications into RDF-based data for bidirectional control. Experimental evaluation highlighted the effects of task scheduling and blocking operations on the ESP32, and polling-based communication latency within the Modbus bridge. These findings reveal the architectural and computational trade-offs involved in extending Solid to constrained or protocol-bound …

Effects Of Wetting And Drying On Nutrient Mobilization In Aquatic Systems, Karessa Grace De La Paz

Graduate Theses and Dissertations

Wetting and drying cycles are a fundamental, but underexplored, control on nutrient mobilization and transport in aquatic ecosystems. Such intermittency impacts approximately 60% of the world's streams and rivers, and the extent is expected to increase with future climate change. Additionally, aging reservoir infrastructure is driving restoration efforts, like large-scale drawdowns, that can expose benthic sediments to extended dry periods before refilling. Despite the prevalence of wet-dry cycles, how they influence nutrient transport and mobilization across different aquatic ecosystems remains poorly understood. To address this gap, this thesis presents two complementary studies exploring nutrient dynamics in Arkansas aquatic ecosystems that …

Fast Hyperspectral And Super-Resolved Mapping Of Lipid Membrane Polarity With Single-Molecule Sensitivity, Elric Dion Pott, Meek Yang, James Ethan Batey, Jole Embree, Bin Dong

Chemistry & Biochemistry Faculty Publications and Presentations

Cell membranes display nanoscale heterogeneity in lipid composition and organization that regulates vital biological processes yet remain challenging to resolve with conventional imaging. We introduce spectral phasor single-molecule localization microscopy (SP-SMLM), a hyperspectral and super-resolution method that combines wavefront-like optical filtering with single-molecule imaging for simultaneous spatial and spectral analysis. A lab-built three-channel imager with sine/cosine filters encodes emission spectra of single molecules into the phasor space, enabling high-throughput, high-SNR mapping of membrane polarity at sub-50 nm spatial and 15 s temporal resolutions. Through simulation, we validate that the phasor angle correlates with the spectral mean for single dye molecules. …

Machine Learning And Multisensor Data Fusion For Forest Above Ground Biomass Estimation In Arkansas, Abdullah Al Saim, Mohamed Aly

Geosciences Faculty Publications and Presentations

Forests are essential for biodiversity conservation, climate change, natural education, scientific research, and carbon sequestration. This study uses machine learning-based Random Forest (RF) regression to estimate the Above Ground Biomass (AGB) of the Ozark and Ouachita forests at a 10-meter resolution by combining data from Sentinel-2, Sentinel-1, and GEDI (Global Ecosystem Dynamics Investigation) on Google Earth Engine. The RF model included 34 out of 154 variables representing topographical, spectral, and textural factors demonstrating strong correlations with measured biomass. The RF model showed strong performance with R-squared and RMSE values of 0.95 and 18.46 for the training dataset and 0.75 and …

The Modern Sisyphus Blows Leaves: Attitudes And Impacts Regarding Leaf Litter Removal On A Suburban Campus, A. C. Nony, M. R. Mcclung, M. L. Reid

Journal of the Arkansas Academy of Science

Leaf litter habitat disruption in suburban spaces stems from the prevalence of “lawn culture,” that is, the accepted societal norm that land immediately surrounding humans or meant for human recreational use should be clean, tidy, controlled, and aesthetically pleasing, above other considerations. When leaf litter on residential and recreational lawns is cleared, it removes vital habitat for organisms of several taxa, especially species that rely on litter as a moisture and temperature-controlled substrate for overwintering. We administered an opinion survey to students, staff, and faculty at Hendrix College, a highly residential and suburban campus in Conway, Arkansas, to assess views …

Wayne E. Sabbe Arkansas Soil Fertility Studies 2025, Nathan A. Slaton

Arkansas Agricultural Experiment Station Research Series

Rapid technological changes in crop management and production require that the research efforts be presented in an expeditious manner. The contributions of soil fertility and fertilizers are major production factors in all Arkansas crops. The studies described within will allow producers to compare their practices with the university’s research efforts. Additionally, soil-test data and fertilizer sales are presented to allow comparisons among years, crops, and other areas within Arkansas.

Effects Of Varying Ph, Temperature, And Sucrose Concentration On The Activity Of Invertase Enzyme, B. Rainwater, S. Pratihar

Journal of the Arkansas Academy of Science

The purpose of this research is to study the factors that affect the enzymatic activity of invertase, extracted from baker’s yeast, on hydrolysis of sucrose in aqueous medium. Invertase, a glycoprotein, is an enzyme in the glycoside hydrolase family. It catalyzes the hydrolysis of sucrose producing equimolar mixture of a-D-glucose and b-D-fructose. Invertase shows high affinity for the substrate, and is capable of both cleaving the glycosidic linkage in sucrose and transferring ab-D-O-fructofuranoside residue to an acceptor substrate. (Toledo et al. 2019). A detailed mechanism of the action of invertase was postulated by Shall et al. (Shall et al. 1971). …

Whose Water Is It, Anyway? Federalism And Texas V. New Mexico, Bryon Louk

Arkansas Law Review

When a problem erupts between two states, interstate compacts provide a solution without the need for a nationwide decision. Rather than waiting for federal consensus, the states can, with Congressional approval, compact to solve their problems. However, the Supreme Court’s decision in Texas v. New Mexico (Texas II) has threatened interstate compacts, ignored principles of federalism, and overextended its original jurisdiction. It has allowed the United States to force Texas and New Mexico to keep fighting over a compact, even when the states have resolved their issues on their own.

First, this Comment will describe the legal background of compact …

A Runtime-Adaptive Transformer Neural Network Accelerator On Fpgas, Ehsan Kabir, Jason D. Bakos, David Andrews, Miaoqing Huang

Electrical Engineering and Computer Science Faculty Publications and Presentations

Transformer neural networks (TNN) excel in natural language processing (NLP), machine translation, and computer vision (CV) without relying on recurrent or convolutional layers. However, they have high computational and memory demands, particularly on resource constrained devices like FPGAs. Moreover, transformer models vary in processing time across applications, requiring custom models with specific parameters. Designing custom accelerators for each model is complex and time-intensive. Some custom accelerators exist with no runtime adaptability, and they often rely on sparse matrices to reduce latency. However, hardware designs become more challenging due to the need for application-specific sparsity patterns. This paper introduces ADAPTOR, a …

One-Step Purification Of A Bioactive Pak1-Derived Peptide, Djamali Muhoza, Emily P. Esquivel, Stacy R. Hunter, Pateince S. Okoto, Thallapuranam K.S. Kumar, Paul D. Adams

Chemistry & Biochemistry Faculty Publications and Presentations

The serine/threonine kinase PAK1 serves as a mediator of cytoskeletal reorganization and cancer-related signaling downstream of the small GTPases. Due to the challenges in purifying PAK1 complexes, a 46-residue peptide from PAK1, is widely used to study PAK1-Cdc42 signaling. Traditionally, this purification involved multi-step chromatography of recombinant GST-PBD46 complexes, yielding approximately 1 mg per 1.5 L culture. In this study, a 30 min heat treatment step after thrombin cleavage was used to precipitate GST while leaving pure PBD46 in solution. This step eliminated the need for further affinity and size-exclusion chromatography steps. This improved protocol produces proteins with a 6.5-fold …

Evaluating Groundwater-Surface Water Interactions At Selected Streams In The Mississippi River Valley Alluvial Aquifer, Usa, And Comparison To Regional Potentiometric Surfaces, Joshua Michael Blackstock, Oladipo S. Obembe, Aaron Shew, Phillip Hays, Phillip R. Owens, Christopher D. Delhom

Geosciences Faculty Publications and Presentations

Field measurements of groundwater-surface water interactions (GWSW) are critical for quantifying stream leakage, but are often limited in availability. In the Mississippi River Valley alluvial aquifer (MRVAA), USA, GWSW interactions are often inferred through interpolated potentiometric surfaces, which can provide information on GWSW changes through time, but are often limited in spatial resolution. Field measurements of GWSW interactions were conducted at several locations and compared with potentiometric surfaces using objectively calculated cell sizes. The potentiometric surfaces showed similar regional-scale groundwater-flow patterns irrespective of grid cell size. Field measurements of GWSW interactions exhibited a broader range of gaining and losing conditions …

First Arkansas Records Of The True Bugs Lasiochilus Hirtellus (Hemiptera: Heteroptera: Lasiochilidae) And Physopleurella Mundula (Anthocoridae)., S. W. Chordas Iii, R. Tumlison

Journal of the Arkansas Academy of Science

We report 2 uncommon species of true bugs (Hemiptera: Heteroptera), Lasiochilus hirtellus (Lasiochilidae) and Physopleurella mundula (Anthocoridae), for the first time from Arkansas. This includes the first report of the family Lasiochilidae for Arkansas. Both species were captured in UV light traps set in Clark County. We discuss identification, provide digital images of the voucher specimens and include updated distribution maps (north of Mexico) for both species. With the addition of these 2 species, there are now a total of 7 anthocorid species, among the 3 bug families Lasiochilidae, Anthocoridae and Lytocoridae, known for Arkansas.

Ovipositional Behavior Of The Twig Girdler (Cerambycidae: Oncideres Cingulata) On Stems Of Mockernut Hickory (Carya Tomentosa) In Arkansas, R. Tumlison, L. Serviss

Journal of the Arkansas Academy of Science

The Twig Girdler (Cerambycidae: Oncideres cingulata) is a long-horned beetle that girdles stems of certain species of trees to prepare a habitat for its offspring. The stems eventually die, break, and fall from the tree, but the beetle usually had already laid its eggs within the stems. Eggs are laid singly, almost always at growth rings or leaf bases. Because the space for the young to develop is finite, laying too many eggs could cause reproductive failure and too few eggs would be suboptimal. We hypothesized that the female laying eggs should be able to evaluate the stem and …

Monitoring Long-Term Water Quality Benefits Of Urban Stream Restoration, Kira Burnett

2026 Research Poster Competition

Urbanization without conscious environmental planning can result in the degradation of stream ecosystems. This tends to result in urban stream syndrome, which is often characterized by increased sediment and nutrient concentrations, decreased biodiversity, more frequent flash flooding, and overall water quality degradation. As such, stream restoration practices are often implemented to address urban stream syndrome. Commonly used restoration practices include applying natural channel design to stabilize eroding stream banks and establishing diverse streamside vegetation to filter pollutant inputs. However, the benefits of restoration are not often quantified due to a lack of post-restoration monitoring, making it challenging to determine what …

Developing Bioassays For Detection Of Residual Herbicides In Compost, Esther Moore

2026 Research Poster Competition

Developing Bioassays for Detection of Residual Herbicides in Compost, the use of synthetic herbicides has dominated the field of agricultural production for over a century. While synthetic herbicide use has resulted in an undeniable boost in agricultural productivity, risks such as environmental degradation and reduced yield of non-target plant species must be considered. Key among these risks is compost contamination, especially from persistent herbicides. After these herbicides are applied, they are absorbed by growing vegetation, consumed by herbivores, passed through the digestive tract, and reintroduced into soil manure based compost. Even after this process, chemicals in such herbicides can remain …

Modeling The Development Of Keyhole Passage Morphology, Charlotte Boehme

2026 Research Poster Competition

Cave passage morphology is an important indicator of the hydrological conditions under which a cave passage was formed. Keyhole passages are a commonly occurring type of passage morphology that consists of a round, wide top with a smaller canyon incised in the bottom of the passage. These passages typically indicate a shift from fully water-filled to partially water-filled conditions. There are multiple mechanisms by which such a transition can occur, and little is understood about which of these mechanisms is most common, or whether aspects of keyhole passage morphology may indicate the primary formation mechanism. CaveCHAMP is a physically based …

Optimizing Microscale Tesla Valve Design For Enhanced Efficiency For Filtering And Sorting Bacteria, Brian Ewalt

2026 Research Poster Competition

Invented by Nikola Tesla in 1920, a Tesla valve is a passive check valve with no moving parts but showing diodicity for fluids (i.e., allowing fluids to flow easily in one direction but not in the other). Tesla valves have demonstrated remarkable versatility across a range of scientific fields. Recently, a study conducted at the University of Arkansas showed that these conduits exhibited diodicity for bacteria in the absence of fluid flows (Rogers et al. 2023), serving as proof of concept for applying microscale Tesla valves for filtering and sorting bacteria and microorganisms in biomedical settings. However, the design of …

Chronostratigraphy Using Stable Carbon Isotopes Of The Elliot Formation, South Africa, Aidan Del Pino

2026 Research Poster Competition

The Elliot Formation in South Africa preserves a fossil-bearing record spanning the Late Triassic–Early Jurassic, a time marked by significant environmental changes related to the Central Atlantic Magmatic Province (CAMP) and the end-Triassic extinction event. Despite its importance, the Elliot Formation remains poorly constrained due to limited chronostratigraphic markers. Chronostratigraphy is the branch of geology that correlates and dates rock units in time, allowing researchers to arrange these rock units into a chronological sequence. Globally, the Triassic–Jurassic boundary is characterized by a pronounced negative carbon isotope excursion linked to CAMP volcanism and the end Triassic extinction event. This C-isotope excursion …

Temporal Variational Graph Autoencoder For Influenza Evolution, Soumya Chauhan

2026 Research Poster Competition

Frequent mutations in influenza virus surface proteins can increase infectivity while evading human and vaccine immunity, causing seasonal epidemics. The CDC annually evaluates thousands of virus strains to predict mutated sequences likely to be dominant in the next season, which creates a need for methods that better capture how viral mutations evolve over time. In this study, we represent influenza protein sequences as a network-like graph, creating connections if sequences are collected a week apart and only differ by one mutation. This method explicitly considers time information as part of the evolution, while other existing methods analyze mutated sequences without …