Physical Sciences and Mathematics Commons^™

Exploring Latent Mediation Through Bayesian Regularization Methods Of Lasso, Ridge, Horseshoe, Spike-And-Slab, Ethan Harris

Graduate Theses and Dissertations

Regularization is a powerful tool to combat overfitting and drive sparsity in complex models. Regularization was initially applied in regression modeling but has been increasingly utilized in structural equation modeling where its utility in identifying the essential components has helped improve modeling. As structural equation models have increased in complexity both in the number of indicators but also the number of latent factors, researchers have begun to investigate how applying Bayesian regularization to these systems can further push the limits on modeling complex models with limited sample sizes. One area where research is limited is the application of Bayesian regularizations …

Contrastive Learning Techniques For Fraud Detection, Vinay Madanbhavi Shashidhar

Graduate Theses and Dissertations

Detecting fraud in computing platforms involves identifying malicious user sessions, often using deep learning models, but several challenges hinder effective deployment. Attackers can craft diverse malicious sessions that closely resemble normal ones, complicating the learning of robust decision boundaries. While supervised contrastive learning offers a promising solution through class-specific clustering, its potential remains underexplored. Real-world datasets typically contain few labeled malicious sessions and many normal ones, creating an open-set anomaly detection challenge. Costly expert annotation further limits labeled data, especially for smaller organizations, leading to Positive Unlabeled (PU) learning and noisy label learning issues. Organizations are increasingly turning to LLMs …

Conservation Agriculture Practice Effects On Greenhouse Gas Emissions From Fine-Textured Soils In Arkansas, Lauren Gwaltney

Graduate Theses and Dissertations

Biochar application and reduced tillage (RT) are both practices within the conservation agriculture framework, but specific impacts of these practices on direct greenhouse gas (GHG) emissions still require investigation in varied agricultural systems. This research aimed to evaluate the effects of biochar source (i.e., powder- and pellet-sized) and application rate (i.e., 0, 2.5, and 5 Mg ha^-1) on GHG production in simulated furrow-irrigated rice (Oryza sativa) in a greenhouse experiment, and to evaluate the effects of RT relative to conventional tillage (CT) on GHG production in soybean (Glycine max) in southeast Arkansas. Both studies …

Adversarial Machine Learning: Methods For Attacks And Defenses, Minh Hao Van

Graduate Theses and Dissertations

With the rapid development of machine learning in real-world applications, enhancing security plays an important role. Adversarial machine learning focuses on understanding malicious actions from attackers and developing defensive techniques against such threats when deploying machine learning systems. An attack can occur in different scenarios, such as poisoning attacks during the training stage and evasion attacks during the testing stage. Although extensive research has explored defense strategies to deal with these harmful attacks, there is a need for further research into areas such as how to counteract malicious attacks with healthy noise or how to train an adaptive defense against …

The Future Of Fashion: A Systematic Literature Review On Consumer Willingness To Pay For Green Apparel, Emma Clark

Graduate Theses and Dissertations

In recent years, consumers have become highly aware of the environmental impact of their purchases, specifically of apparel products. Accordingly, apparel brands have increasingly focused on enhancing the sustainability of their product offerings to attract environmentally conscious consumers and elevate their brand image (Dangelico et al., 2022). Furthermore, most sustainably produced products are priced higher for consumers compared to standard alternatives (Elmanadily & El-Deeb, 2022). Research has shown that consumers can accept higher prices for products that do less harm to the environment (Gomes et al., 2023), but it has yet to be determined in which cases this is consistently …

Koszul Cohomology Of Canonical Products, Alexander Scott Duncan

Graduate Theses and Dissertations

In this thesis, we give a complete classification of the Koszul cohomology groups K_p,₁(C, B, ω_C ⊗ B) on a smooth curve C of genus g ≥ 2 with B p-very ample. Such a classification in the case B = ω_C has been incomplete until [5]. The classification follows easily from our main result which precisely calculates K_p,1(C, B, B ω_C ⊗ B) in terms of h⁰(C, B). This result also handles the case B = ω_C. A straightforward …

Atomic Level Characterization For The Transport Cycle Conformational Pathways Of Multidrug Resistance Protein 1 (Mrp1), Samuel Wamwere Mwatha

Graduate Theses and Dissertations

The multidrug resistance-associated protein 1 (MRP1/ABCC1) is an ATP-binding cassette (ABC) transporter that mediates the cellular efflux of endogenous and xenobiotic substrates, including therapeutic drugs. Its overexpression is a major contributor to multidrug resistance in cancer, which tends to result in negative clinical results. Even with considerable progress made in structural biology, the intricate details of how membrane lipid composition affects the conformational changes and functional switches of MRP1 still lack explanation.

This thesis employs long-timescale, all-atom molecular dynamics (MD) simulations to study the influence of various lipids on MRP1 lipid bilayer environments. Both inward-facing and outward-facing conformations of MRP1 …

Rotation Errors Due To Field Quantization For Simultaneously Driven Atoms, Hunter Lindemann

Graduate Theses and Dissertations

If we want to physically implement qubits by using two level atoms within a cavity, then certain single-qubit gates (such as the X-gate) can be performed by bathing the atoms in an electromagnetic field from a laser. If the average photon count n̄ of the field greatly exceeds the number of N qubits, then the slight fluctuations of the field's phase and amplitude are mostly negligible. However, such a strong field might require more energy than what is desirable for the setup. If a weaker field is used in which phase and amplitude fluctuations might be noticeable, then the …

Real-Time Anomaly Detection In Ot Networks Using Gru-Based Autoencoders, Grant Austin Wilkins

Graduate Theses and Dissertations

Operational Technology (OT) networks, particularly those used in critical infrastructure, face increasing cyber threats that target network-level protocols and behaviors. While most anomaly detection research for OT systems has traditionally relied on sensor data, this thesis explores the viability of detecting malicious activity directly from network telemetry. We propose a sequence-to-sequence autoencoder model based on Gated Recurrent Units (GRUs) with multilevel attention, trained to reconstruct normal patterns of packet-level communication extracted from raw PCAP data. The developed feature engineering pipeline integrates general networking attributes such as IP and MAC addresses, ports, and transport protocols with OT-specific protocol information from Modbus …

A Robust Rf Fingerprinting Approach Using Physics-Informed Neural Networks, Jozef Dusenka

Graduate Theses and Dissertations

Radio frequency (RF) fingerprints, caused by unique imperfections in communication hardware, offer a promising solution for zero-trust security. However, existing RF fingerprinting techniques, which aim to extract these signatures from transmitters to uniquely identify devices, often struggle with robustness in the face of temporal and spatial variations in real-world, time-varying wireless environments. For example, a neural network trained on RF signals collected on Day 1 can experience a significant performance drop when tested with data from Day 2.

To address this challenge, we propose a novel, robust RF fingerprinting method based on Physics-Informed Neural Networks (PINNs). Rather than training the …

The Formation Of Glacier Dirt Cones, Ryan M. Strickland, Matthew D. Covington

Geosciences Faculty Publications and Presentations

Glacier dirt cones are meter-scale cones of ice covered with sediment and rock. The cones develop through a process known as differential melt, whereby ice underlying thick debris melts more slowly than bare ice. We report observations of dirt cones on the Kuskulana Glacier, Alaska and develop a model that simulates the growth of dirt cones from debris-filled pits in the ice. With this model, we vary ice melt rates, hillslope debris diffusion rates and pit geometry. Cone heights scale with the square root of debris volume and growth occurs in three distinct stages: emergence, flux-controlled growth and melt-controlled growth. …

Transient Thermal Energy Harvesting At A Single Temperature Using Nonlinearity, Tamzeed B. Amin, James M. Mangum, Md R. Kabir, Syed M. Rahman, Pradeep Ashaduzzaman, Pradeep Kumar, Luis L. Bonilla, Paul M. Thibado

Physics Faculty Publications and Presentations

The authors present an in-depth theoretical study of two nonlinear circuits capable of transient thermal energy harvesting at one temperature. The first circuit has a storage capacitor and diode connected in series. The second circuit has three storage capacitors, and two diodes arranged for full wave rectification. The authors solve both Ito-Langevin and Fokker-Planck equations for both circuits using a large parameter space including capacitance values and diode quality. Surprisingly, using diodes one can harvest thermal energy at a single temperature by charging capacitors. However, this is a transient phenomenon. In equilibrium, the capacitor charge is zero, and this solution …

The Mechanistic Target Of Rapamycin Mediates Clostridium Perfringens-Induced Chicken Necrotic Enteritis Attenuated By Secondary Bile Acid Deoxycholic Acid, Mohit Bansal, Tahrir Alenezi, Ying Fu, Janashrit Shrestha, Ayidh Almansour, Hong Wang, Anamika Gupta, Rohana Liyanage, Xiaolun Sun

Poultry Science Faculty Publications and Presentations

Clostridium perfringens is a prevalent gut bacterial pathogen in humans and animals. This study investigated the role of the mechanistic targets of rapamycin (mTOR) and deoxycholic acid (DCA) on C. perfringens intestinal infection. Chickens were sequentially infected with Eimeria maxima and received the mTOR inhibitor rapamycin and DCA. C. perfringens-induced necrotic enteritis (NE) was evaluated using body weight gain (BWG), histopathology, bile acids, pathogen colonization, cell infiltration and death, and gene expression. The significant difference of p < 0.05 was analyzed by one-way ANOVA and multiple comparisons. Notably, rapamycin strongly reduced the subclinical and clinical NE histopathologies. DCA and DCA combined with rapamycin alleviated clinical NE and BWG loss. Rapamycin, DCA, and DCA + rapamycin attenuated bile acid reduction in NE birds, and they also reduced immune cell infiltration into the intestinal lamina propria as well as immune cell migration in vitro. At molecular levels, DCA and DCA + rapamycin reduced proinflammatory IFN gamma, MMP9, IL23, and IL17 gene expression. Rapamycin, DCA, and DCA + rapamycin reduced NE-induced intestinal cell apoptosis. Together, these results suggest that mTOR signaling mediates C. perfringens-induced ileitis, and combining mTOR inhibition and DCA improves the intervention efficacy against NE ileitis and BWG loss.

A Tutorial For Scanning Electrochemical Cell Microscopy (Seccm) Measurements: Step-By-Step Instructions, Visual Resources, And Guidance For First Experiments, Kamsy Lerae Anderson, Martin Andrew Edwards

Chemistry & Biochemistry Faculty Publications and Presentations

Scanning electrochemical cell microscopy (SECCM) produces nanoscale-resolution electrochemical maps of electrode surfaces using the meniscus at the tip of an electrolyte-filled nanopipette as a mobile electrochemical cell. While the use and range of applications of SECCM have grown rapidly since its introduction, the pathway to performing SECCM measurements can be daunting to those without direct access to expert users. This work fills this expertise gap by providing a step-by-step guide to performing one's first SECCM experiments, including troubleshooting strategies, videos/images, suggested parameters and experimental systems, and representative data (of both successful experiments and common problems). No background in SECCM is …

Enhancing Tree Species Mapping In Arkansas’ Forests Through Machine Learning And Satellite Data Fusion: A Google Earth Engine–Based Approach, Abdullah Al Saim, Mohamed Aly

Geosciences Faculty Publications and Presentations

Arkansas' subtropical climate nurtures extensive forested regions, particularly within the Ozark-St. Francis and Ouachita National Forests. Despite this, the state lacks an up-to-date high-resolution map detailing the distribution of tree species within its forests. This study harnesses the power of machine learning, specifically the Random Forest (RF), Gradient Tree Boosting (GTB), Support Vector Machine (SVM), and K-Nearest Neighbors (K-NN) classifiers, within the Google Earth Engine (GEE) framework. These classifiers are applied to classify tree species distribution in Arkansas' forests by integrating data from various sources, including Sentinel-1/-2, Landsat-8, and the National Agriculture Imagery Program (NAIP). The study evaluates the classification …

Overexpression And Biophysical And Functional Characterization Of A Recombinant Fgf21, Phuc Phan, Jason Hoang, Thallapuranam Krishnaswamy Suresh Kumar

Chemistry & Biochemistry Faculty Publications and Presentations

Fibroblast growth factor 21 (FGF21) is an endocrine FGF that plays a vital role in regulating essential metabolic pathways. FGF21 increases glucose uptake by cells, promotes fatty acid oxidation, reduces blood glucose levels, and alleviates metabolic diseases. However, detailed studies on its stability and biophysical characteristics have not been reported. Herein, we present the overexpression, biophysical characterization, and metabolic activity of a soluble recombinant FGF21 (rFGF21). The far-UV circular dichroism spectra of rFGF21 show a negative trough at 215 nm, indicating that the protein's backbone predominantly adopts a 13 sheet conformation. rFGF21 shows intrinsic tyrosine fluorescence at 305 nm. Thermal …

Conformational Free Energy Landscape Of A Glutamate Transporter And Microscopic Details Of Its Transport Mechanism, Sundar Thangapandian, Ashkan Fakharzadeh, Mahmoud Moradi, Emad Tajkhorshid

Chemistry & Biochemistry Faculty Publications and Presentations

Removing glutamate from the synaptic cleft is vital for proper function of the brain. Excitatory amino acid transporters mediate this process by uptaking the neurotransmitter from the synaptic cleft back to the cell after its release. The archaeal homolog, GltPh, an aspartate transporter from Pyrococcus horikoshii, presents the best structurally characterized model for this family of transporters. In order to transport, GltPh undergoes elevator-like conformational changes between inward-facing (IF) and outward-facing (OF) states. Here, we characterize, at an atomic level, the OF=+/- IF transition of GltPh in different apo/bound states using a combination of ensemble-based enhanced sampling techniques, employing more …

Wayne E. Sabbe Arkansas Soil Fertility Studies 2024, 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.

Sobolev Regularity For The Bergman Projection On Relatively Compact Domains In Hermitian Manifolds, Philip Harrington

Mathematical Sciences Faculty Publications and Presentations

Generalizing a result of Berndtsson and Charpentier, we provide sufficient conditions for L2\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$L< ^>2$$\end{document} Sobolev regularity of the Bergman projection acting on L2\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$L< ^>2$$\end{document} sections of a holomorphic line bundle restricted to a relatively compact domain with Lipschitz boundary in a Hermitian manifold. We provide examples to show that our methods work for domains in Hopf manifolds endowed with a suitable Hermitian metric.

Low-Level Kinetic-Energy-Powered Temperature Sensing System, James M. Mangum, Syed M. Rahman, Tamzeed B. Amin, Md R. Kabir, Hung Do, Gordon Carichner, David Blaauw, Paul M. Thibado

Physics Faculty Publications and Presentations

Powering modern nanowatt sensors from omnipresent low-level kinetic energy: This study investigates the power levels produced by a varying-capacitance kinetic energy harvesting system. A model system consisting of a uniformly driven rotating capacitor was built to develop an accurate output power performance model. We found a quantitative linear relationship between the rectified output current and the input applied bias voltage, driving frequency, and capacitance variation. We also demonstrate that our variable capacitor system is equivalent to a fixed capacitor driven with an alternating current power source. Both the fixed-capacitance and varying-capacitance energy harvesting systems recharge a three-volt battery, which in …

Characterizing The Stability Of Ultra-Thin Metal Oxide Catalyst Films In Non-Thermal Plasma Co2 Reduction Reactions, Samuel Keith Conlin, Joseph Joel Muhanga, David Parette, Robert H. Coridan

Chemistry & Biochemistry Faculty Publications and Presentations

The use of metal oxide catalysts to enhance plasma CO2 reduction has seen significant recent development towards processes to reduce greenhouse gas emissions and produce renewable chemical feedstocks. While plasma reactors are effective at producing the intended chemical transformations, the conditions can result in catalyst degradation. Atomic layer deposition (ALD) can be used to synthesize complex, hierarchically structured metal oxide plasma catalysts that, while active for plasma CO2 reduction, are potentially vulnerable to degradation due to their high surface area and nanoscopic thickness. In this work, we characterized the effects of extended non-thermal, glow discharge plasma exposure on ALD synthesized, …

Active Learning-Based Automated Construction Of Hamiltonian For Structural Phase Transitions: A Case Study On Batio3, Mian Dai, Yixuan Zhang, Nuno Fortunato, Peng Chen, Hongbin Zhang

Physics Faculty Publications and Presentations

The effective Hamiltonians have been widely applied to simulate the phase transitions inpolarizable materials, with coefficients obtained by fitting to accurate first-principlescalculations. However, it is tedious to generate distorted structures with symmetry constraints,in particular when high-ordered terms are considered. In this work, we implement and apply aBayesian optimization-based approach to sample potential energy surfaces, automating theeffective Hamiltonian construction by selecting distorted structures via active learning. Taking BaTiO3(BTO) as an example, we demonstrate that the effective Hamiltonian can be obtainedusing fewer than 30 distorted structures. Follow-up Monte Carlo simulations can reproduce thestructural phase transition temperatures of BTO, comparable to experimental values …

The Effects Of Functional Moves In Teacher Questioning On Students’ Contextualization Of Mathematical Word Problem Solving, Yi-Jung Lee

Curriculum and Instruction Faculty Publications and Presentations

Posing purposeful questions is one of the most effective teaching practices (NCTM in Principles to actions: Ensuring mathematics success for all. National Council of Teachers of Mathematics, 2014). Although the types and functions of teacher questioning have been abundantly studied, research on the role of teacher questioning in students’ contextualization process as they solve word problems is rather scarce. This study was conducted to investigate the function of six elementary preservice teachers’ questioning, its impact on students’ contextualization, as well as the successes and difficulties of enacting questioning. The collected data were analyzed using thematic analysis. The findings indicated that …

Photogalvanic Shift Currents In Bifeo3-Lafeo3 Superlattices, Francesco Delodovici, Charles Paillard

Physics Faculty Publications and Presentations

Designing materials with a controlled photovoltaic response may lead to improved solar cells or photosensors. In this regard, ferroelectric superlattices have emerged as a rich platform to engineer functional properties. In addition, ferroelectrics are naturally endowed with a bulk photovoltaic response stemming from nonthermalized photoexcited carriers, which can overcome the fundamental limits of current solar cells. Yet, their photovoltaic output has been limited by poor optical absorption and poor charge collection or photoexcited carrier mean free path. We use Density Functional Theory and Wannierization to compute the so-called Bulk Photovoltaic shift current and the optical properties of BiFeO3/LaFeO3 superlattices. We …

Large Negative Magnetoresistance In The Off-Stoichiometric Topological Semimetal Prsbxte2-X, Gokul Acharya, Krishna Pandey, M. M. Sharma, Jian Wang, Santosh Karki Chhetri, Md Rafique Un Nabi, Dinesh Upreti, Rabindra Basnet, Joshua Sakon, Jin Hu

Physics Faculty Publications and Presentations

Magnetic topological materials LnSbTe (Ln = lanthanide) have attracted intensive attention because of the presence of interplay between magnetism, topological, and electron correlations depending on the choices of magnetic Ln elements. Varying Sb and Te composition is an efficient approach to control structural, magnetic, and electronic properties. Here, we report on the composition-dependent properties in PrSbxTe2-x. We identified the tetragonal-to-orthorhombic structure transitions in this material system and very large negative magnetoresistance in the x = 0.3 composition, which might be ascribed to the coupling between magnetism and transport. Such unusual magnetotransport enables PrSbxTe2-x topological materials as a promising platform for …

Facial Chick Sexing: An Automated Chick Sexing System From Chick Facial Image, Marta Veganzones Rodriguez, Thinh Phan, Arthur F.A. Fernandes, Vivian Breen, Jesus Arango, Michael T. Kidd, Ngan Le

Computer Science and Computer Engineering Faculty Publications and Presentations

Chick sexing, the process of determining the gender of day-old chicks, is a critical task in the poultry industry due to the distinct roles that each gender plays in production. While effective traditional methods achieve high accuracy, color, and wing feather sexing is exclusive to specific breeds, and vent sexing is invasive and requires trained experts. To address these challenges, we propose a novel approach inspired by facial gender classification techniques in humans: facial chick sexing. This new method does not require expert knowledge and aims to reduce training time while enhancing animal welfare by minimizing chick manipulation. We develop …

Human Serum Albumin Interaction With Organochlorine Pesticides, D. S. Sanford, R. Yadav, A. Mishra

Journal of the Arkansas Academy of Science

Human serum albumin (HSA) is the most abundant blood plasma protein and plays a crucial role in drug transport and physiological homeostasis. HSA has a highly flexible structure consisting of three domains, each with multiple binding sites lined with hydrophobic and hydrophilic residues. The structural properties of HSA make it a robust reservoir and receptor for various endogenous and exogenous compounds, including therapeutic drugs. Organochlorine pesticides (OCPs) are a subclass of pesticides characterized by their chlorine content. Once widely used, these compounds remain persistent in the environment and biological systems despite regulatory restrictions in many developed countries. The strong ligand-binding …

Sogar: Self-Supervised Spatiotemporal Attention-Based Social Group Activity Recognition, Naga Venkata Sai Raviteja Chappa, Pha Nguyen, Alexander H. Nelson, Han-Seok Seo, Xin Li, Page Daniels Dobbs, Khoa Luu

Electrical Engineering and Computer Science Faculty Publications and Presentations

Social group activity recognition is crucial for various applications including surveillance, human-robot interaction, and behavioral analysis. Current approaches often require extensive manual annotations and rely heavily on pre-trained detectors, limiting their practical applications. Additionally, existing methods struggle to effectively model long-term spatiotemporal relationships in group activities. This paper introduces a novel approach to Social Group Activity Recognition (SoGAR) using Self-supervised Transformers network that can effectively utilize unlabeled video data. To extract spatio-temporal information, we create local and global views with varying frame rates. Our self-supervised objective ensures that features extracted from contrasting views of the same video are consistent across …

Eeg-Based Multi-Scale Perturbed Brain Cognitive Pattern Recognition Network For Gamer Level Classification, Lijun Jiang, Yanping Chen, Kexuan Liu, Xingyuan Chen, Li Dong, Weiya Ma, Diankun Gong, Dezhong Yao

General Human Environmental Sciences Faculty Publications and Presentations

Electroencephalogram (EEG)-based classification of video game experts versus amateurs reveals cognitive brain patterns underlying complex abilities, with applications in attention modulation, medical rehabilitation, and health monitoring. While deep learning has advanced EEG-based cognitive state detection, challenges remain in extracting meaningful patterns from noisy data and preventing reverse inference attacks on user privacy. Here, we propose a novel multi-scale perturbed brain cognitive pattern recognition network (MsPE). Its key contributions are: (1) a multi-scale weak encryption method with attention mechanisms that protects privacy by perturbing EEG signals in temporal and frequency domains; (2) ConvFormer modules with adaptive channel sizes (3, 5, 15) …

Orchestrating Digital Technologies With Incumbent Enterprise Systems For Attaining Innovation, Sachithra Lokuge, Darshana D. Sedera, Varun Grover, Suprateek Sarker

Information Systems Faculty Publications and Presentations

In the late 1990s, most organizations adopted enterprise systems (ES) to automate their core business processes. The very same organizations are presented with a new wave of opportunities to innovate with digital technologies—technologies that purport to have diametrically opposed characteristics to ES. This study explores how organizations integrate digital technologies with their incumbent ES for attaining innovation. The study followed a qualitative approach and gathered data from four organizations consisting of six such projects. By applying a unique theoretical foundation, this study derives interesting insights into the orchestration process of ES and digital technologies for attaining innovation.