Digital Commons Network^™

Multiscale Integration Of Receptor-Ligand Dynamics Into Discrete And Continuous Tumor Growth Models With Application To Tyrosine Kinase Inhibitor Treatment, Romasa Qasim

Open Access Theses & Dissertations

The epidermal growth factor (EGF) receptor cascade plays a crucial role in the survival and proliferation of tumor cells. Tyrosine kinase inhibitors (TKIs) are a class of drugs that inhibit epidermal growth factor receptors (EGFRs), thereby preventing the downstream signal transduction. Despite their importance, models that link spatial receptor dynamics to tumor growth remain scarce. Further, TKIs act through selective mechanisms, inhibiting active, inactive, or all receptor states, which poses a challenge to traditional modeling approaches.

We propose to numerically study two mathematical models incorporating receptor-dynamics into cancer models to describe the impact of EGFR overexpression and TKIs. The first …

A Numerical Study Of Self-Assembling Amphiphilic Systems, Joshua Albert Sackey

Open Access Theses & Dissertations

Mixing processes in ternary mixtures involve immiscible fluids such as oil and water, and a surface-active molecule called surfactant. These physical processes find applications in various fields, including enhanced oil recovery, drug delivery design systems, and the formulation of cleaning products. Even though this process has several applications, the mathematical models describing it and the numerical methods solving it are not well understood. The underlying mathematical model is a nonlinear initial-boundary value problem involving sixth-order derivatives and belongs to the class of sixth-order Cahn-Hilliard equations. Authors Sharma and Tierra recently proposed a numerical method to approximate its solutions in two …

Machine Learning And Protein Engineering Approaches To Understanding Kinesin-5 Activity, Jason Eden Sanchez

Open Access Theses & Dissertations

Cancer is a term describing a collection of diseases that result in uncontrolled cell growth. Cancer has manifold etiologies and underlying cancers are rouge biochemical pathways involving many different proteins. In the current work, two approaches are used to enhance knowledge of kinesin-5, a potential cancer target involved in cell division. Kinesin-5 promotes cell division by cross-linking and separating microtubules in dividing cells. The first approach uses machine learning (ML) to identify small molecule inhibitors for kinesin-5. Though decades of research have uncovered classes of small-molecules which inhibit kinesin-5 in vitro and in vivo, no candidates have reached phase III …

Engineering Of Metallic Interpenetrating Phase Composites For The Control Of Deformation And Failure Modes During Dynamic Events, David Kiyoshi Santacruz

Open Access Theses & Dissertations

Aerospace components, automotive structures, and ballistics armor are all engineered to withstand high strain rate service events through a combination of material selection and design choices. However, structural components may be less effective when their implementation is constrained by other factors such as weight or design limitations. To meet these challenges, the development of next-generation materials will need to increasingly rely on composite material systems rather than monolithic materials. This thesis presents the fabrication, dynamic characterization testing, and post-mortem analysis of 316L/A356 interpenetrating phase composites (IPCs) made from the PrintCasting methodology. These composites consist of additively manufactured 316L stainless steel …

Machine Learning And Time Series Forecasting For Hydropower Predictions, Jose Reynaldo Vega

Open Access Theses & Dissertations

Recent advancements in machine learning have led to the design of many neural network architectures aimed at solving real-world problems. Each network works to make predictions by finding patterns in the provided data. One common application is time series forecasting, where a model predicts future events based on historical time series data. Time series forecasting is used in a variety of fields, one example being in predicting water releases of Hybrid Floating Photovoltaic-Hydropower (HFPVH) systems. As global population growth drives an increase in energy demand, the need for resilient and sustainable energy generation has become urgent. HFPVH systems have emerged …

De Novo Design Of Ablative Polymers For Aerospace Thermal Protection Systems Through An Integrated Ai-Theory-Experiment Approach, Rene Damaso Boisseau

Open Access Theses & Dissertations

Novolac phenolic resin (NPR) is a widely used polymeric ablative material (PAM) for thermal protection systems (TPS) due to its high thermal decomposition temperature (TD, 500â?¯Â°C) and char yield (YC, 55â?¯wt%). However, its drawbacks (including high thermal conductivity, low mechanical properties and water uptake) prompt the need for improved PAMs. This study explores the pyrolysis behavior and char-forming capabilities of NPR and a potential alternative PAM, poly(1,6-dimethyl phenol) (PPO), through both theoretical and experimental approaches. A graph neural network (GNN) was developed to predict structure-property relationships, revealing that benzyl group positioning and oxygen atom placement significantly influence YC. PPO's para-positioned …

Yield Prediction Of Pv Solar Energy Systems And Its Application In The Energy Grid For Operational Efficiency, Pablo Bustamante

Open Access Theses & Dissertations

The generation of power from photovoltaic (PV) solar panels is influenced by a multitude of factors. These include the tilt and orientation of the solar panels, the latitude of their location, and the prevailing climate and weather conditions. Additionally, shading at specific locations, particularly if the panels are not part of a solar facility, can significantly impact their efficiency. The quality and efficiency of the panels themselves, along with the preventive maintenance of both the solar panels and associated components such as inverters and trackers, are also critical. Finally, the overall system design and installation play a vital role in …

Cyber Resiliency Framework And Mechanisms For Software Defined Tactical Networks, Anthony Castanares

Open Access Theses & Dissertations

Traditional tactical networks fail to achieve cyber resiliency for many reasons, but the most prevalent causes include flat designs, the absence of cyber detection capabilities at the lowest level, and immutable resource allocations after instantiation. These design choices allow network threats direct visibility to each device on the network, and the lack of detection allows infections to proliferate. Furthermore, tactical battlefield networks are difficult to secure because of the lack of persistent oversight by an intelligent agent that can exercise control over the network's topology or resources in real-time. However, advances in software-defined networking (SDN) provide an opportunity to address …

Generative Ai For 3d Printed Antenna Design, Jennifer Ann Chavez

Open Access Theses & Dissertations

This research explores the integration of generative artificial intelligence (AI) with a physics-informed particle swarm optimizer (PSO) to develop 3D printable microstrip patch antennas. A neural network was trained on a dataset of microstrip patch antenna geometries and their corresponding performance metrics: return loss and gain. The PSO used a fitness function prioritizing low return loss in potential antennas, eventually yielding novel antenna geometries with parasitic components. 3D printing constraints were also hard coded into the framework, thus preventing any geometries being generated that cannot be fabricated. When simulated using Ansys HFSS, the AI generated microstrip patch antennas exceeded the …

2023 Annual Operations And Maintenance Report 2023 Bres Annual Summary Report For Work Completed In Quadrant 3, Butte-Silver Bow Department Of Reclamation And Environmental Services

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Characterization Of Residual Mineral Content Of Bauxite Stockpiles In Saline County, Arkansas: An Xrd Analysis Approach, Andrew Kaze Sezibera

Electronic Theses and Dissertations

The Saline Mining District of central Arkansas once led U.S. alumina production and hosts extensive bauxite and nepheline syenite deposits. With the depletion of highgrade ore, renewed interest in bauxite stockpiles has focused on critical mineral potential. Previous X-ray Fluorescence studies have identified critical elements in significant concentrations, including uranium (U), thorium (Th), gallium (Ga), molybdenum (Mo), and lanthanides (Ln). This study examines five stockpiles (SP1, Clay, SP2, SP3, and SP4) in Section 20 of the Aluminum Company of America (ALCOA) Saline County bauxite mine, using Xray Diffraction (XRD) on 25 samples to characterize mineral phases and compare them with …

Lidar-Based Delineation Of Karst Features In The Gypsum Plain, Eddy County, New Mexico And Culberson County, Texas, Kaitlyn Rae Levassar

Electronic Theses and Dissertations

The Gypsum Plain of the Delaware Basin encompasses approximately 1,800 km² of massive to laminated gypsum (anhydrite in the subsurface) outcrop of early Ochoan Castile and Salado strata. These extensive Permian-age evaporites host significant karst phenomena as a result of the region's complex hydrogeologic system which has continuously evolved since the early Paleogene. Karst features that manifest surficially as sinkholes when breached range from extensive hypogene cave systems to epigene features and suffosion caves. In contrast, paleo-collapse structures forming breccia pipes attesting to more ancient karst within these strata often manifest as topographic highs across the Gypsum Plain.

Until …

Identifying Salt Suture Zones And Lithological Changes Of The Louann Salt In The Gulf Of Mexico Basin, La. U.S.A., Jamie Dale Singer

Electronic Theses and Dissertations

The Louann Salt, a key evaporite unit in the Gulf of Mexico Basin, influences salt tectonics, hydrocarbon migration, and basin evolution. This study examines Louann Salt deposition and deformation within the Puma Diapir, focusing on mineralogical, geochemical, and structural features of suture zones in three offshore wells (Puma 2(w), Puma 3, and Panther). Using drill cuttings, X-ray fluorescence (XRF), inductively coupled plasma mass spectrometry (ICP-MS), X-ray diffraction (XRD), well-log data, and 3D seismic interpretation, the study analyzed salt composition and suture formation. Results show the salt primarily consists of halite, with minor anhydrite, gypsum, and sylvite, indicating continuous precipitation. Geochemical …

Towards Multimodal Scene Graph Generation Approaches To Video Understanding, Trong-Thuan Nguyen

Graduate Theses and Dissertations

This thesis advances video understanding by enhancing Video Scene Graph Generation (VidSGG) through improved temporal modeling, the integration of long-range temporal dependencies via continuous updates to interaction histories, and the utilization of Large Language Models (LLMs) for scene graph reasoning. To this end, three novel datasets and corresponding approaches are introduced. First, the ASPIRe dataset incorporates interactivity annotations and leverages the Hierarchical Interlacement Graph (HIG) for hierarchical temporal modeling, providing deep insights into scene changes and effectively capturing intricate interactions. Next, the AeroEye dataset, focusing on drone videos, is paired with the Cyclic Graph Transformer (CYCLO), which establishes circular connectivity …

Administering Grant-Subsidized Workforce Training: A Critical Case Study, Kaleb Preston Futch

Graduate Theses and Dissertations

Grant monies are distributed for the purpose of funding workforce training programs aimed at affecting the skills gap in the United States. While research has shown that these grants are being awarded, there is not a well-established standard for designing and implementing the programs they fund. This study focuses on recording and classifying the lived experiences of grant staff working on a state funded workforce training program in the United States. This study will employ a qualitative case study approach designed to capture and codify, in the words of those most familiar with it, the aspects of the grant program …

Quantifying The Effects Of Urbanization On Stream Nutrient Loads And Decomposition, Caroline Anscombe

Graduate Theses and Dissertations

Urban stream syndrome (USS) refers to the common symptoms of degradation in urban streams globally. Two symptoms of USS are increased nutrient and salt concentrations in streams, affecting ecosystem structure and function. Excess nutrients negatively impact freshwater ecosystems, placing downstream habitats at risk of eutrophication and harmful algal blooms. Excess salt runoff, derived from road salt application, is toxic to freshwater organisms and affects leaf litter decomposition, the base of aquatic food webs. Here, I aimed to quantify the effects of nutrient pollution and salinization on urban water quality and ecosystem function. Despite the widespread consequences of nutrient pollution, most …

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 …

Achieving Flexible Fairness And Privacy In Federated Learning, Alycia N. Carey

Graduate Theses and Dissertations

Having access to large, high-quality datasets is crucial for training machine learning models that achieve satisfactory performance. Unfortunately, it is common that a single entity (e.g., mobile device or organization) does not have access to such datasets due to monetary or resource constraints. Traditional machine learning requires that all training data reside in a centralized location during the entire duration of model training, however, in many circumstances it is difficult or even impossible (e.g., due to governmental regulations) for multiple parties to combine their data to meet this constraint. Federated learning is a machine learning paradigm that facilitates the joint …

Geospatial Modeling Of Winter-Related Property Damage In Arkansas, Braedyn Mcbroom

Graduate Theses and Dissertations

Storm Data, a monthly publication by the National Weather Service with records of weather events, reports on property damage caused by natural hazards. Since 1996, the database has included winter-related events. While the property damage data is considered incomplete, no other unique, public datasets report winter-related property damage at the county level. From 1996 to 2024, Arkansas ranked #1 in winter-related property damage. To understand the factors that are driving property damage and potentially reduce Arkansas’ vulnerability to it, three groups separated by temporal periods, i.e., “2000” (01/1996 - 06/2005), “2010” (07/2005 - 06/2015), and “2020” (07/2015 - 06/2024) …

Geochemical Analysis For Potential Critical Mineral Resources In Carbon Fly Ash, Korei D. Patterson Teer

Graduate Theses and Dissertations

The growing demand for critical minerals, coupled with the increasing supply chain vulnerabilities, has intensified the need for alternative domestic resources of critical minerals beyond traditional mining. Many of these critical minerals are essential for advanced technologies, energy storage, and national security, yet the United States remains heavily dependent on foreign imports, particularly from China. This study evaluates the economic potential of critical mineral recovery from Carbon Fly Ash (CFA), a byproduct of coal combustion, to determine its viability as a secondary source of critical minerals. A geochemical and mineralogical assessment was conducted on CFA samples from various storage sites …

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 …

An Instructional Remodel: How Adopting A Unifying Model-Of-Instruction Impacted Teacher Self-Efficacy And Teacher Development And Evaluation Efforts In A Midwestern High School, Charles D. Patterson Carpenter

Graduate Theses and Dissertations

This mixed methods study sought to determine the effect of adopting a unifying model-of-instruction on teacher self-efficacy and the development and evaluation processes of administrators. By assessing the level of teacher self-efficacy (Tschannen-Moran & Hoy, 2001) in the nascent stages of the instructional model’s implementation, then reassessing it after a multiple-month sequence of professional learning, the researcher provides a judgment on statistical significance concerning the two measurements and conjectures the extent to which the instructional model impacted any differences in self-efficacy levels. Using two separate “before and after” interviews with purposefully selected administrators, the researcher explored how the unification of …

Space And Subjectivity In The Emerging American West, Scott Hendry

Graduate Theses and Dissertations

The American West resists theoretical definition. As myth, ideal, region, contact zone, place, space, symbol, territory, home, assemblage, dream, and home, the West is continually changing. As a region, the West is not a closed space; it is an open, ongoing constellation of processes, an unfolding simultaneity of storied events or happenings. This dissertation, “Space and Subjectivity in the Emerging American West,” explores literature and cinema of the modern West. My project seeks to answer the question “What is the American West?” by examining the work of novelists, poets, filmmakers, cultural geographers, philosophers, and photographers who reimagine identity, locality, and …

A New Method Using Lidar And Well Logs To Identify And Correlate The Pennsylvanian Atoka Formation Subdivisions In The Surface Outcrops Of The Boston Mountains, Arkansas, Robert Brent Boyd

Graduate Theses and Dissertations

The surface outcrops of the Boston Mountains in northwest Arkansas primarily consist of the Pennsylvanian Atoka formation. Where fully preserved in the Arkoma Basin to the south, the Atoka formation exceeds 18,000 ft of sand and shale. However, it remains undifferentiated on the surface geological map of Arkansas. This study investigates the possibility of identifying and correlating the subsurface subdivisions of the Atoka Formation to the surface outcrops of the Boston Mountains using a new method. Recognizing the Atoka subdivisions in surface outcrops using standard lithology and biostratigraphy correlation techniques has been challenging. The subdivision of the Atoka has instead …

Real Time Adaptive Control Of A Pid Via Genetic Algorithm Machine Learning Systems, Cemre Tas

Graduate Theses and Dissertations

The most common control method that is utilized by all industries across the world is the proportional-integrative-derivative controller (PID) due the relatively low cost and complexity of the system. However, there are draw-backs with PIDs, it is not adaptative to a changing system, so it works on nominal systems, and it starts breaking down when a system begins to have a non-linear response. The method chosen to overcome both is the utilization of machine learning with the use of genetic algorithms.

This method allows any PID system to be capable of adapting in real-time, while not adding significant additional cost …

Solving Real-World Optimization Problems Using Near-Term Quantum Computing With Applications In Vehicle Routing And Drone Delivery, James Bradley Holliday

Graduate Theses and Dissertations

Quantum computing (QC) stands at the cusp of revolutionizing computation, yet its near-term potential, constrained by Noisy Intermediate-Scale Quantum (NISQ) devices, remains underexplored. This dissertation investigates how hybrid quantum-classical algorithms can address combinatorial optimization challenges in logistics, focusing on vehicle routing and drone delivery—NP-hard problems with exponential solution spaces that defy classical exhaustive methods. Amidst NISQ limitations like limited qubits and high noise, we confront key challenges: encoding complex constraints, e.g., time windows, battery capacity, into quantum models, balancing quantum and classical components for scalability, and accessing scarce quantum resources. By integrating quantum annealing (QA) and the Quantum Approximate Optimization …

Simulations Of Richtmyer-Meshkov Instability Using High Order Weno Methods, Ryan Holley

Graduate Theses and Dissertations

Turbulent mixing due to hydrodynamic instabilities occurs in a broad spectrum of engineering, astrophysical and geophysical applications. Theory, experiment, and numerical simulation help us to understand the dynamics of interface instabilities between two fluids. This thesis presents an increasingly accurate and robust front tracking method for the numerical simulations of shock-induced turbulent mixing known as Richtmyer-Meshkov Instability (RMI). Front tracking is an adaptive computational method, where the interface instability is explicitly represented as lower dimensional manifolds moving through a rectangular grid. All the cell-center states (density, velocity and pressure) are updated using higher order weighted essentially non-oscillatory (WENO) scheme. Performance …

Exploring The Relationship Between Novice Teacher Autonomy And Workplace Engagement, Burnout, And Intentions To Remain In The Teaching Profession, Bryce Bennett

Graduate Theses and Dissertations

Administrators and experienced faculty frequently disagree on the degree of autonomy that should exist for classroom teachers. Administrators seeking to make adjustments to the levels of autonomy experienced by their teachers may struggle to account for differences between novice teachers and their more seasoned counterparts. This study applies researched-based models for exploring the relationship between various job resources and demands and their ultimate impact on workers. A mixed method designed employing a survey across three large school districts in Arkansas asked participants questions intended to uncover the degree of autonomy novice teachers typically experience, levels of burnout & workplace engagement, …

Evaluating The Impact Of Work-Based Learning On Postsecondary Completion And Job Placement Of Electronics Technology Students, Amanda J. Seidenzahl

Graduate Theses and Dissertations

The manufacturing industry today is facing a critical shortage in the availability of talent and skills needed in an ever-changing technological workforce. With an estimated 2.1 million jobs in the manufacturing industry predicted to be unfilled by 2030, organizations are struggling to find a workforce with the skills needed for this evolving industry (NAM, 2020; Ahmad, 2019). Employers have often suggested there is a lack of alignment between classroom experience in higher education, and work-based learning (WBL) is one option to bridge this gap (Krishnamoorthy & Keating, 2021). WBL provides real world experiences that connect learning in the classroom (Krishnamoorthy …

Exploring Hybrid Cohort-Based Doctoral Program Features That Support Nontraditional Doctoral Students’ Persistence: A Preregistered Case Study., Glenda Winborn

Graduate Theses and Dissertations

With the rise of hybrid learning models, non-traditional learners have greater access to doctoral education. However, attrition rates from doctoral programs remain high, ranging from 40% to 50% across all doctoral programs and exceeding these levels in online non-traditional programs. Numerous causes of attrition or persistence in doctoral studies have been researched and can affect the student, the academic institution, and the broader academic society. This qualitative case study will explore adult and lifelong learning doctoral students' perceptions of the programmatic and instructional support resources that have helped improve persistence in their program. Two of the important programmatic features of …