Digital Commons Network^™

The Digital Neuron: Neural Cellular Automata For Neural–Symbolic Translation, Nicole Assenza

SMU Data Science Review

A neural cellular automata (NCA) architecture, referred to as Pluto’s NCA, was developed to characterize bilateral communication and semantic reciprocity between symbolic representations and a spatially distributed update field. The architecture employs an encoder–automata–decoder pipeline that maps symbolic inputs into a multichannel state field and reconstructs them through agreement-driven attractor convergence within a stable semantic attractor landscape. System behavior was evaluated under controlled perturbations, including rhythmic desynchronization, graded ablations, correlated and independent noise, and percolation-based structural degradation. Quantities such as Agreement(t), internal coherence Aᵢ(t), the recovery time constant τ, and the critical percolation threshold pc were measured to assess stability, …

Organic Synthesis Of A Hydrazine Functionalized Ammonium Compound For Improved Capture Of Aldehyde Metabolites From Exhaled Breath, Po'iu N. Burgo

Undergraduate Theses

Breath analysis has emerged as a non-invasive and inexpensive way to screen for respiratory diseases. This technique involves measuring concentrations of specific metabolites found in exhaled breath that serve as a biomarkers for disease. A subclass of volatile organic compounds called α,β-Unsaturated aldehydes, products of the lipid peroxidation mechanism, are underrepresented as biomarkers of lung cancer. These have been found to have relatively increased concentrations in the exhaled breath of lung cancer patients compared to a healthy patient. One of the reasons that these metabolites have been underreported is that the techniques used to measure and characterized exhaled metabolites do …

Phishing Restraint: University Simulated Phishing Campaigns, Alexander M. Abou Khir

Cybersecurity Undergraduate Research Showcase

Universities face heightened vulnerability to phishing attacks due to their open information-sharing culture and diverse user populations. This study examines how phishing exploits human factors within campus environments and evaluates three major training strategies: embedded phishing, microlearning, and role-based instruction to understand their individual and combined effectiveness. I explored studies that implement these strategies in pairs and use the strategies alone, identified trends in susceptibility reduction, behavioral reinforcement, and contextual relevance. I suggest that, while each method independently improves user awareness, multiple approaches offer stronger, more adaptable protection by addressing both psychological triggers and role-specific risks. The paper contributes a …

A Computer Vision Approach To Analyzing Taxane Effects On Prostate Cancer Cells, Diana Elizabeth Dancea

Electronic Theses and Dissertations

Actin is a family of proteins that help create the structure of the cytoskeleton, which gives shape to the cell. In many chemotherapy treatments, researchers target actin because it controls the cell division process. Therefore, if they are able to understand the actin fibers, that may help in formulating methods to stop or slow down cancer cells from reproducing. Another important protein is PAK6, which regulates actin. In our research, a collaborative effort with Prof. Michael Lu’s lab at Florida Atlantic University, we use machine learning techniques to analyze cells which had their PAK6 protein knocked out, and compare them …

Analyzing Label Structure And Regional Similarity In Watershed Data Via Spectral Clustering, Yifan Luo

25th Annual A. Paul and Carol C. Schaap Celebration of Undergraduate Research and Creative Activity (2026)

This project focuses on identifying patterns of seasonal transitions and nutrient salt fluctuations within the watershed environment. To capture the complex relationships between multiple sampling sites and environmental variables, we represent the watershed dataset as a weighted graph, where nodes correspond to water samples and edge weights reflect similarity in environmental conditions or nutrient concentrations. Using the Gaussian kernel function, we encode the connectivity structure of this network and quantify how similar different nodes are. We then perform spectral embedding by projecting the high-dimensional graph into a lower-dimensional space using the eigenvectors of the Laplacian matrix. This approach preserves the …

Plastic Purgatory: Investigating The Effects Of Plastic Litter On Water And Organic Content In Topsoil In Holland, Michigan, Kamryn Bice, Annis Cairns, Maddie Devries, Sebastian Lema

25th Annual A. Paul and Carol C. Schaap Celebration of Undergraduate Research and Creative Activity (2026)

Plastic accumulation in soils can offer important insights into how human activity affects terrestrial ecosystems. In this study, we examined the relationship between plastic litter and soil quality at several sites across Holland, Michigan to determine whether plastic abundance was associated with changes in soil properties. Soil samples from five different site types – construction, residential, commercial, nature, and a control – were collected over a threeweek period, then analyzed for pH, water contents, total organic carbon (TOC), and plastic abundance through field testing and laboratory methods. The number of plastic pieces ranged from 0 to 27 with the largest …

Recent Wetland Elevation Dynamics In Coastal Louisiana, Usa, Elizabeth Harris

LSU Master's Theses

Coastal marshes globally are increasingly vulnerable to accelerating relative sea-level rise (RSLR), which threatens their capacity to maintain elevation through feedbacks among sediment supply, vegetation productivity, hydrology, and soil processes. Although many marshes can persist under moderate rates of sea-level rise through vertical accretion and belowground biomass production, this resilience is strongly constrained by sediment availability and subsurface processes such as autocompaction and organic matter decomposition. High accretion is often assumed to confer marsh resilience; however, subsurface processes, particularly autocompaction driven by surface loading, can substantially offset elevation gains. Coastal Louisiana experiences among the highest rates of RSLR worldwide due …

Characterizing The Unique Chemical Imprint Of On-Axis, Lower-Temperature Hydrothermal Flow To The Deep Ocean (Southern East Pacific Rise, 16.5°–18.0°S), Laura E. Moore, Randelle M. Bundy, Joseph A. Resing, Scott M. White, Tamara Baumberger, Peter N. Sedwick, Nathaniel J. Buck, Anson M. Antriasian, Isaac Keohane

Faculty Publications

In addition to high-temperature vents, lower-temperature flow (LTF) (< 300°C) is abundant along mid-ocean ridges and contributes globally-important fluxes of heat and water along with largely-unconstrained geochemical influences on the ocean. We examined the impact of on-axis LTF on the chemical composition of the overlying water column (< 40 m above seafloor) along the 16.5°–18.0°S sector of the ultrafast-spreading southern East Pacific Rise using autonomous underwater vehicle Sentry surveys and conductivity-temperature-depth rosette casts. LTF sites were typically spatially isolated from high-temperature systems and imparted unique chemical signatures to the overlying ocean. Water column samples impacted by LTF exhibited low particulate iron:sulfur ratios and high methane: total-dissolvable manganese ratios, whereas samples influenced by high-temperature venting exhibited opposite trends. We confirmed that LTF imparts a distinct and measurable chemical signature to the water column, independent from high-temperature vents. Isolated, on-axis LTF will be important to consider when assessing hydrothermal circulation impacts upon ocean biogeochemistry.

Characterizing The Macroinvertebrate Community In Crissy Lake, An Impounded Reach Of The Pomme De Terre River, Prior To Channel Modification, Max Lundgren

Undergraduate Research Symposium (2026- )

The aging Crissy Lake Dam, on the Pomme de Terre River in Morris, has altered natural stream flow and impeded upstream passage of several fish species since 1939. In late 2026 the Minnesota Department of Natural Resources will replace the dam with stone arch rapids and facilitate river channel formation upstream of the dam. In order to evaluate the river modification project, we characterized the macroinvertebrate community in Crissy Lake, the impoundment upstream of the dam before implementation of channel modification. In September 2025 we collected benthic macroinvertebrates from two sets of Ekman grab samples. We found 12 taxa (average …

Brown Pelican (Pelecanus Occidentalis) Groundings On A Four-Lane Divided Highway In South Texas: A Comparative Study Using Citizen Science, Bradley Evan Beer, Kevin W. Ryer, Md. Saydur Rahman, John H. Young Jr., Richard J. Kline

School of Integrative Biological & Chemical Sciences Faculty Publications

The population of the once-endangered brown pelican (Pelecanus occidentalis) has increased over the past several decades and is now considered fully recovered. However, in south Texas, the combined effects of weather patterns, transportation infrastructure, and brown pelican biology have led to road mortalities on State Highway 48 (SH 48) at the Carl “Joe” Gayman Bridge. To mitigate these mortalities, the Texas Department of Transportation modified traffic barriers on SH 48. We aimed to examine the effect of the barrier change and determine which weather variables influence brown pelican groundings on SH 48. Citizen scientists monitored sections of SH …

High Germinability Can Facilitate Recovery Of Adelia Vaseyi (Euphorbiaceae), An Imperiled Tamaulipan Thornscrub Shrub, Saroj Dhakal, Bashira Chowdhury, Alejandro Fierro-Cabo

School of Earth, Environmental, & Marine Sciences Faculty Publications

While critical to maintaining dryland biodiversity and drought resilience, reforestation has been limited in subtropical dry forests because of knowledge gaps in seed biology that must be filled to upscale seedling production and ensure recovery of imperiled endemic plants. We characterized seed germination, dormancy, and storage needs for Adelia vaseyi, a threatened endemic shrub commonly included in planting mixes to restore Tamaulipan thornscrub, an imperiled subtropical forest spanning South Texas and Northeastern Mexico. We found A. vaseyi seeds have high germinability (82.0%) and a short mean germination time (3.04 ± 0.08 days). A delia vaseyi seed does not appear …

Electroenzymatic Cascades For Nitrogen Upgrading: Beyond Ammonia Towards Value-Added Nitrogen Chemicals, Rohit G. Jadhav, Vamshi Krishna Kamaja, Wassim El Housseini, Monica Brachi, Shelley D. Minteer

Chemistry Faculty Research & Creative Works

The global transition toward sustainable chemical manufacturing demands technologies that leverage natural carbon and nitrogen cycles while minimizing reliance on sacrificial reagents and fossil resources. These biogeochemical cycles are fundamental to life, and enzymes catalyze many of their key transformations. Bio electrochemical, specifically electroenzymatic, systems offer a promising route to sustainable synthesis by enabling selective redox transformations powered by electricity. However, whereas carbon-cycle enzymes are now well established in bio electrochemical synthesis, enzymes from the nitrogen cycle remain comparatively underexplored. Moreover, the nitrogen cycle alone does not access many value-added nitrogen-containing products, which require additional C-N bond formation and organic …

Drainage Proximity And Sinkhole Occurrence In Sivrihisar (Central Turkey): A Comparative Analysis Of Linear, Poisson, And Negative Binomial Regression Models, Bilge Bingül, Emrah Pekkan, Resul Çömert

International Journal of Speleology

This study investigates the relationship between sinkhole occurrence and distance to drainage in the Sivrihisar region (Central Turkey) and evaluates the suitability of different regression approaches for modeling clustered count data in karst terrains. A comprehensive inventory of 104 sinkholes developed within the Neogene lacustrine limestones of the Akpınar Formation was compiled using official records, remote sensing analyses, and detailed field surveys. Sinkhole occurrences were analyzed relative to a drainage network derived from a high-resolution Digital Surface Model and grouped by proximity to drainage lines. Linear Regression (LM), Poisson Regression (PR), and Negative Binomial Regression (NBR) models were comparatively applied …

The Efficacy Of Manganese Sulfate As A Negative Contrast Agent For Magnetic Resonance Cholangiopancreatography, Zainab Abdulla Mankhi

Karbala International Journal of Modern Science

The current study aims to find an alternate oral contrast media for use in magnetic resonance cholangiopancreatography (MRCP) that satisfies the following criteria, the greatest imaging quality safety, no or few side effects, and low cost. The present study created an oral contrast agent sample (solution) by dissolving a one tablet of manganese sulfate supplement (taken daily dose) in 200 ml of distilled water. Thirty-three volunteers assessed the sample using MRCP examine pre and post contrast. By evaluating the signal intensity to compute contrast (C), signal to noise ratios (SNR), and contrast to noise ratio (CNR), the resulting MR images …

Stylemys Nebrascensis Predation Hypothesis, Noah Lohrmeyer, Amanda Peng

SACAD: Scholarly Activities

In 2008 a fossilized tortoise shell was brought into the Sternberg Museum of Natural History. As we prepared the fossil, we observed markings that resembled predation. We are trying to find what species from the White River Formation could preyed on the tortoise. There are few publications on predation for this species. With few publications, we want to find what predator would hunt these species. We cross referenced the site of the tortoise and observed several carnivorous species. We used straight carapace length (Hermanson et al., 2024) and a regression formula (Wilson et al., 2016) to analyze the species we …

David Berkowitz, Enzyme-Assisted Organic Synthesis & Nsf Officer, Mark A. Griep, David B. Berkowitz

Department of Chemistry: Faculty Interviews

Dr. Dave Berkowitz was born in Urbana, Illinois. He earned his bachelor's degree in chemistry from the University of Chicago, where he did undergraduate research. Next, he earned his doctorate from Harvard University. However, his advisor, Steve Benner, moved from Harvard to ETH Zurich, also called the Swiss Federal Institute of Technology. Dave accompanied him to Zurich, where he completed his dissertation work. When Dave returned to the U.S., he did a postdoc with the legendary Samuel Danishefsky at Yale University. In 1991, he joined UNL as an assistant professor of chemistry and quickly rose through the ranks. Dave is …

Heavy Metal In Water Resources, Zuming Bi, Jeanne Sumrall

SACAD: Scholarly Activities

Heavy metal pollution in surface water has posed a serious threat to human health. The goals of this research are to analyze the concentration and distribution of key heavy metals and compare the measured values with global standards. This study analyzed major heavy metals like Fe, Mn, Cu, Pb, and Ag across several test points in Kansas and converted them to standard units mg/L. Based on the statistical graph, heavy metal iron and manganese levels are exceeded USEPA and WHO limits several times,  while other heavy metals stay in the safe range. The results indicate that the pollution in Kansas …

Desialylation And Sialidase Secretion From Monocytes And Macrophages Upon Lps Activation, Yu Zhao, Majdi Aljohani, Morgan Pychowycz, Xue-Long Sun

Chemistry Faculty Publications

Introduction The cell surface expresses a dense layer of glycans often terminated with sialic acids (Sias), known as sialylation, which represents different cellular statuses. Meanwhile, the removal of Sias from the glycans catalyzed by sialidase (desialylation) is also involved in many biological processes, such as inflammatory responses. Previous studies demonstrated that desialylation is involved in LPS/TLR4 signaling pathway and pro-inflammatory cytokine production. In this report, we systematically profiled desialylation and sialidase activity, expression and secretion from monocytes and macrophages upon LPS activation.Methods THP-1 monocytes and THP-1 macrophages were activated by LPS (100 ng/mL) for 24 hours. The cellular Sia changes …

Negotiating Digital Identities With Ai Companions: Motivations, Strategies, And Emotional Outcomes, Renkai Ma, Shuo Niu, Lingyao Li, Alexander Hirth, Ava Brehm, Rowajana Behterin Barbie

Computer Science

AI companions enable deep emotional relationships by engaging a user's sense of identity, but they also pose risks like unhealthy emotional dependence. Mitigating these risks requires first understanding the underlying process of identity construction and negotiation with AI companions. Focusing on Character.AI (C.AI), a popular AI companion, we conducted an LLM-assisted thematic analysis of 22,374 online discussions on its subreddit. Using Identity Negotiation Theory as an analytical lens, we identified a three-stage process: 1) five user motivations; 2) an identity negotiation process involving three communication expectations and four identity co-construction strategies; and 3) three emotional outcomes. Our findings surface the …

Coral Reef Hydrodynamics: A Critical Review Of Roughness Indices And Their Characteristic Complexity, Faisal Karim, N. A. K. Nandasena, Lujain Kuruvachalil, Mohamed M. Mohamed, James P. Terry

All Works

This study provides a systematic review of hydrodynamic roughness in coral reef systems, focusing on drag coefficient (Cd), Manning's roughness coefficient (n), friction factor, and rugosity metrics. A structured bibliometric analysis was conducted using Scopus and Web of Science databases, including field measurements, laboratory flume experiments, and numerical studies validated with physical data. Results show substantial variability in roughness parameters across scales and environments. Reported drag coefficients range from 0.002 for smooth sandy beds to values exceeding 7.0 in complex mangrove-reef systems, with typical reef crest values between 0.05 and 0.30. Manning's n varies from 0.01 in smooth channels to …

Advancing Cyclic Ion Mobility Mass Spectrometry For Structural Characterization, Isomer Discrimination And Gas-Phase Ion Chemistry, Sudam Shivaji Mane

Theses and Dissertations

This dissertation focuses on the development and application of high-resolution ion mobility-mass spectrometry (IMS-MS) methodologies for gas-phase separation and structural characterization of small molecules, with particular emphasis on epimers, positional isomers, and protomers. In addition to structural separations, this work investigates fundamental aspects of gas-phase ion chemistry using IMS-MS in combination with collision-induced ion activation and dissociation techniques. Advanced separations were performed using cyclic traveling-wave ion mobility spectrometry (cyclic TWIMS), implemented in a commercial cyclic ion mobility-mass spectrometry (cIMS) platform, to systematically evaluate both the capabilities and limitations of high-resolution IMS in resolving subtle structural differences. Initial studies demonstrated that, …

The Promises And Perils Of Using Llms For Effective Public Services, Erina Seh-Young Moon, Matthew Tamura, Angelina Zhai, Nuzaira Habib, Behnaz Shirazi, Altaf Kassam, Devansh Saxena, Shion Guha

Health Services and Informatics Research

Governments are the primary providers of essential public services and are responsible for delivering them effectively. In high-stakes decision-making domains such as child welfare (CW), agencies must protect children without unnecessarily prolonging a family’s engagement with the system. With growing optimism around AI, governments are pushing for its integration but concerns regarding feasibility and harms remain. Through collaborations with a large Canadian CW agency, we examined how LocalLLM and BERTopic models can track CW case progress. We demonstrate how the tools can potentially assist workers in opportunistically addressing gaps in their work by signaling case progress/deviations. And yet, we also …

How To Effectively Trap Invasive Crayfish: A Discrete Life Stage Mathematical Model, Rini Pattison

Seaver College Research And Scholarly Achievement Symposium

The red swamp crayfish is an invasive species introduced into several streams within the Santa Monica Mountains (SMM). Crayfish predation decimates native aquatic species. The Mountains Restoration Trust (MRT) has worked to remove crayfish through regular trapping in Malibu Creek.

A prior student created a crayfish life cycle model with trapping, which we expand to better predict the efficacy of crayfish removal efforts in the SMM. We separate crayfish based upon life stages and sizes. We construct and parameterize this discrete crayfish population model with and without trapping. We use literature and crayfish removal data from MRT to fit the …

Tipping Points In Crayfish Management: Exploring Population Dynamics With The Bifurcations Activity In Slopes, Evan Inrig, Benjamin Lucas

Seaver College Research And Scholarly Achievement Symposium

Slopes is an interactive environment for exploring numerical methods and graphical solutions to ordinary differential equations. The app launched with five activities for exploration: slopefields, phase planes, oscillations, solutions to systems, and numerical methods for approximation. Bifurcations is a new sixth activity that we designed to investigate changes in the long term behavior of solutions to autonomous differential equations. This activity displays a slopefield and implements the ability to add solutions, but also introduces two new views that show how varying a single parameter impacts the values and stability of equilibrium solutions. We demonstrate the value of the new bifurcations …

Bio-Cybersecurity: Securing The Healthcare Industry, Amanda D. Coleman

Cybersecurity Undergraduate Research Showcase

Bio-cybersecurity refers to the aspect of cybersecurity that applies to the biological sciences and the protection of digital biomedical information. Today’s healthcare industry has evolved with the enhancement of internet and biomedical technology. While hospitals and private medical providers remain compliant with the Health Information Portability and Accountability Act (HIPAA) through traditional means of securing documented patient information, the emergence of beneficial internet-based healthcare services like virtual appointments and digital patient records requires new policies and healthcare cybersecurity frameworks to protect sensitive information from unauthorized access. This paper examines the role of cybersecurity in healthcare, the vulnerabilities that exist and …

Practical, Scalable, And Cost-Effective Nanolc-Ms Workflow For Single-Cell Proteomics, Siqi Huang

Theses and Dissertations

Single-cell proteomics provides a novel research strategy for decoding cellular heterogeneity, revealing the molecular mechanisms of rare cell subpopulations, and studying the dynamic responses of cells to external stimuli. However, compared to transcriptomics, single-cell proteomics faces even more challenging technical challenges: extremely low protein amount in single cells, wide dynamic range, significant adsorptive losses during sample preparation, and the complex matrix and trace sample injection demanding extremely high stability and sensitivity from the separation and detection systems. Mass spectrometry-based bottom-up proteomics has become an important tool for analyzing complex biological systems, and nano-flow liquid chromatography-mass spectrometry (nanoLC-MS) exhibits unique advantages …

Machine Learning Based Models For Simulation And Analysis Of Bulk Earth Melt System, Abin Shakya

LSU Doctoral Dissertations

Understanding the segregation of bulk Earth melt systems into metallic (core) and silicate (mantle) phases under high-pressure and high-temperature conditions is central to modeling Earth’s interior, yet relevant experimental and computational studies remain limited. This work develops a machine learning–based simulation pipeline that iteratively couples first-principles (quantum mechanical) calculations with neural network training to generate high-fidelity force fields. Using major-element Fe–Mg–Si–O melt systems, with and without H and N, as testbeds, we demonstrate that this framework enables large-scale molecular dynamics simulations at near first-principles accuracy. We further introduce a sequence of phase identification methods, progressing from statistical binning of elemental …

Differentials As Models: Constructing A Differentials-Within-Limits Framework For First-Year Calculus And Examining Students' Understanding Of Limits, Differentials, And Derivatives Within It, Alexander A. Swindler

Theses and Dissertations

Work in first-year calculus has clearly shown the power that treating differentials (such as dx) as tiny quantities affords for first-year calculus learning, yet a traditional limits-based approach leaves no room for them. While some researchers have loosely described informal differentials and limits within the same paradigm, their actual conceptual definitions and relationships have not been explicitly constructed. Continued progress in this area could benefit from theoretical consideration of (a) providing clearer intuitive definitions for differentials inside a limits-based approach to calculus, and (b) defining more exactly the relationships between differentials and limits. In this study, I propose a theoretical …

Applications Of Machine Learning In Enhancing Evaporation Estimation For Small Reservoirs: A Case Study In Semi-Arid South Texas, Syed Muhammad F Abdullah, Chu-Lin Cheng, Jude A. Benavides, Jungseok Ho, Rafael M. Almeida

School of Earth, Environmental, & Marine Sciences Faculty Publications

Small reservoirs in semi-arid regions experience substantial evaporative losses but are rarely monitored at daily scales. A multi-reservoir machine learning (ML) framework was developed to estimate daily open-water evaporation. Empirical models (Penman, Penman-Monteith, Priestley-Taylor, Bowen Ratio Energy Budget) andabenchmark combination method (Daily Lake Evaporation Model-DLEM) were compared against ML models. Predictors combined gridded meteorology (gridMET) with reservoir attributes (surface area, average depth, maximum depth, and fetch). ML models (Random Forest-RF, Decision Tree-DT, K-Nearest Neighbor-KNN, and Support Vector Regression-SVR) were trained on four reservoirs using data from 2018 to 2025. Results from ML models were further validated using both DLEM and …

Investigating The Effect Of Kcl Stress In Raphanus Sativus, Mason P. Oelke

ATU Scholars Symposium

Presented by Stephanie Nelms at the Arkansas INBRE Conference on November 7-8, 2025.

Presented by Mason Oelke at Arkansas Tech Scholar's Symposium on April 9th, 2026.

Potassium is an essential macronutrient for plant growth and development, yet excessive potassium fertilization can induce salt stress with detrimental consequences for crop productivity and nutritional quality. Despite its agricultural relevance, potassium chloride induced stress remains significantly understudied compared to classical sodium-based salinity. This thesis investigates the physiological, biochemical, and molecular responses of Raphanus sativus to KCl stress using an integrated approach that combines germination assays, mineral profiling, and gene expression analysis.

Radish seeds …