Physical Sciences and Mathematics Commons^™

Improvements In Appropriate Placement Of Dental Sealants After Implementation Of A Clinical Decision Support System, Joanna Mullins, Ryan Brandon, Nicholas Skourtes, Elsbeth Kalenderian, Muhammad Walji

Faculty, Staff and Student Publications

BACKGROUND: Dental sealants are effective for the prevention of caries in children at elevated risk levels, and increasing the proportion of children and adolescents who have dental sealants on 1 or more molars is a Healthy People 2030 objective. Electronic health record (EHR)-based clinical decision support systems (CDSSs) have the ability to improve patient care. A dental quality measure related to dental sealant placement for children at elevated risk of caries was targeted for improvement using a CDSS.

METHODS: A validated dental quality measure was adapted to assess a patient's need for dental sealant placement. A CDSS was implemented to …

Development And Validation Of A Rule-Based Algorithm To Identify Periodontal Diagnosis Using Structured Electronic Health Record Data, Bunmi Tokede, Ryan Brandon, Chun-Teh Lee, Guo-Hao Lin, Joel White, Alfa Yansane, Xiaoqian Jiang, Elsbeth Kalenderian, Muhammad Walji

Faculty, Staff and Student Publications

AIM: To develop and validate an automated electronic health record (EHR)-based algorithm to suggest a periodontal diagnosis based on the 2017 World Workshop on the Classification of Periodontal Diseases and Conditions.

MATERIALS AND METHODS: Using material published from the 2017 World Workshop, a tool was iteratively developed to suggest a periodontal diagnosis based on clinical data within the EHR. Pertinent clinical data included clinical attachment level (CAL), gingival margin to cemento-enamel junction distance, probing depth, furcation involvement (if present) and mobility. Chart reviews were conducted to confirm the algorithm's ability to accurately extract clinical data from the EHR, and then …

Spin Disorder Control Of Topological Spin Texture, Hongrui Zhang, Yu-Tsun Shao, Xiang Chen, Binhua Zhang, Tianye Wang, Fanhao Meng, Kun Xu, Peter Meisenheimer, Xianzhe Chen, Xiaoxi Huang, Piush Behera, Sajid Husain, Tiancong Zhu, Hao Pan, Yanli Jia, Nick Settineri, Nathan Giles-Donovan, Zehao He, Andreas Scholl, Alpha N'Diaye, Padraic Shafer, Archana Raja, Changsong Xu, Lane W. Martin, Michael F. Crommie, Jie Yao, Ziqiang Qiu, Arun Majumdar, Laurent Bellaiche, David A. Muller, Robert J. Birgeneau, Ramamoorthy Ramesh

Physics Faculty Publications and Presentations

Stabilization of topological spin textures in layered magnets has the potential to drive the development of advanced low-dimensional spintronics devices. However, achieving reliable and flexible manipulation of the topological spin textures beyond skyrmion in a two-dimensional magnet system remains challenging. Here, we demonstrate the introduction of magnetic iron atoms between the van der Waals gap of a layered magnet, Fe₃GaTe₂, to modify local anisotropic magnetic interactions. Consequently, we present direct observations of the order-disorder skyrmion lattices transition. In addition, non-trivial topological solitons, such as skyrmioniums and skyrmion bags, are realized at room temperature. Our work highlights …

A Conceptual Understanding Of Concepts In Organic Chemistry, Timerra Chisham

Theses/Capstones/Creative Projects

As students continue to make the transfer into organic chemistry from general chemistry, they will have to adjust to the new type of thinking required so that they will not fall behind in understanding material and will have success in the course. For this research project, I explored which concepts taught in organic chemistry are the most difficult for students to grasp. I had two main goals for this project. The first one is the central idea that I focused on, which was to see which concepts that have been taught in Organic Chemistry 1 the students are most confident …

Selectivity Studies Of Cbds Against Cb1 And Cb2 Using Docking Approach, Brandon Villanueva Sanchez, Andy Zhong

Theses/Capstones/Creative Projects

Cannabis sativa is an herbal plant that is used for recreational and medicinal purposes. The two main components, ∆9-Tetrahydrocannabinol (THC) and Cannabidiol (CBD), are responsible for the two different uses. Both compounds have been heavily researched, with their mechanisms of action, docking site, and binding affinity and efficacy identified. Researchers have synthesized various analogs by altering the carbon side chains of THC/CBD’s molecular structures. These synthetic analogs have been created to study the structure-function relationship of different molecules to the endocannabinoid system receptors, CB1 and CB2. Here, we conduct a docking study of various THC/CBD analogs to both receptors using …

Brain-Inspired Continual Learning: Rethinking The Role Of Features In The Stability-Plasticity Dilemma, Hikmat Khan

Theses and Dissertations

Continual learning (CL) enables deep learning models to learn new tasks sequentially while preserving performance on previously learned tasks, akin to the human's ability to accumulate knowledge over time. However, existing approaches to CL face the challenge of catastrophic forgetting, which occurs when a model's performance on previously learned tasks declines after learning the new task. In this dissertation, we focus on the crucial role of input data features in determining the robustness of CL models to mitigate catastrophic forgetting. We propose a framework to create CL-robustified versions of standard datasets using a pre-trained Oracle CL model. Our experiments show …

Examining The Relationship Between Manning's Roughness Coefficient And Stage, Henry Holtkamp

Biological and Agricultural Engineering Undergraduate Honors Theses

This paper uses LOESS regression to predict Manning's roughness coefficient to calculate flows in natural stream channels. Manning's roughness coefficient can introduce variability into Manning's equation, potentially destabilizing results. Utilizing LOESS to find n based on backcalculated n from collected discharge vs. stage information is the best way to acquire accurate Manning's roughness coefficient values at a variety of flows. Book values tend to drastically overestimate which can have wide-ranging implications for water allocation, flood management, maintaining environmental flows, and maintaining water quality.

Modeling Sex-Specific Changes In Myocardial Fibrosis, Grace Martin

Chemical Engineering Undergraduate Honors Theses

Heart disease the leading cause of death for both men and women in the United States. Cardiac fibrosis, or accumulation of extracellular matrix proteins in the heart, can occur after a heart attack and increase the risk for further complications. Current treatments for heart disease do not include extracellular matrix regulators, partly due to the complicated signaling network responsible for the production of these proteins. By using a computational model of the signaling network in cardia fibroblasts, the relationship between particular molecules and downstream extracellular matrix production can be examined.

Biological sex is an important factor for cardiac health and …

Predicting True Attributes Of Retailer Data, Abby Willard

Data Science Undergraduate Honors Theses

In the rapidly evolving landscape of consumer-packaged goods (CPG) retail, understanding the true values of various factors influencing sales performance is paramount for strategic decision-making and effective resource allocation. In ensuring accuracy of data points, the CatBoost model is utilized, a state-of-the-art gradient boosting technique, to predict the true attribution values of datasets sourced from CPG industry retailers.

By leveraging CatBoost’s inherent capabilities to handle categorical data and its robustness against overfitting, the models are optimized to accurately predict the true attribution values for various items. The performance of the CatBoost models is evaluated through rigorous cross-validation techniques and compared …

Concurrent Processing Of Retail Data In Python To Optimize Runtime, Bobby Slavin

Data Science Undergraduate Honors Theses

This thesis explores the application of multiprocessing and multithreading techniques in Python to optimize runtime efficiency on the analysis of retail data. As the retail data processed by a program increases, so does the runtime of the program. If you are performing this processing using only a single core, even a gigabyte of data can potentially take upwards to half an hour to finish processing, while larger datasets of 100 GB or more could take days, heavily limiting the amount of retail data that can be processed in a reasonable amount of time. By employing multithreading and multiprocessing architectures in …

The Importance Of Text Representation For Neural Networks Through Natural Language Processing Techniques, William Parsley

Data Science Undergraduate Honors Theses

Text representation is a fundamental aspect of natural language processing (NLP) when it comes to the performance of neural networks. Free-form text fields are being utilized in more and more industries. Anything from a description of an item on a web store to tracking service events to military-grade aircraft is being collected in free-form text. The goal of the thesis is to highlight best practices and discuss trends in data to prepare text for a neural network. It will demonstrate various techniques for representing free-form text in the context of neural networks, focusing on data preparation decisions, embedding techniques, and …

Examining The Impact Of Customer Rfp Characteristics On Award Compliance, Laasya Ravipati

Data Science Undergraduate Honors Theses

In the context of intermodal transportation, understanding the dynamics of award compliance holds significant importance for operational efficiency and strategic decision-making. Award compliance refers to the percentage of awarded freight volume that is realized, indicating the extent to which contractual agreements are fulfilled. This analysis delves into the intricate relationship between customer characteristics and award compliance, aiming to provide valuable insights into the variability and predictability of compliance rates. By analyzing Request for Pricing (RFP) data and primary awarded freight volumes, the study seeks to address the need for more accurate volume estimations, crucial for sales planning, revenue projections, and …

Examining Award Compliance To Inform Resource Allocation, Jacob Haarala

Data Science Undergraduate Honors Theses

This project focuses on JB Hunt Transport Inc's intermodal business unit (JBI) by focusing on the challenges associated with Published Pricing and Contractual Pricing. The primary issue revolves around the variance between the awarded freight volumes in Requests for Pricing (RFPs) and the actual volumes realized when the freight is shipped. This discrepancy poses challenges for effective sales planning, revenue goals, and optimal freight network management within JBI. Reporting tools, such as PowerBI, are currently used by JBI to provide insights into award compliance on a weekly basis. However, our goal with this project was to provide a deeper understanding …

Tasks For Learning Trigonometry, Sydnee Andreasen

All Graduate Reports and Creative Projects, Fall 2023 to Present

Many studies have been done using task-based learning within different mathematics courses. Within the field of trigonometry, task-based learning is lacking. The following research aimed to create engaging, mathematically rich tasks that meet the standards for the current trigonometry course at Utah State University and align with the State of Utah Core Standards for 7th through 12th grades. Four lessons were selected and developed based on the alignment of standards, the relevance to the remainder of the trigonometry course, and the relevance to courses beyond trigonometry. The four lessons that were chosen and developed were related to trigonometric ratios, graphing …

Characterization Of Carbonaceous Fault Rocks, Pioneer Fault Zone, South-Central Idaho, Genna Baldassarre

All Graduate Reports and Creative Projects, Fall 2023 to Present

Differing crystallinities of carbonaceous material are common in fault rocks across a range of geologic settings and spatial scales and may provide constraints on strain rate, the nature of fault slip, fluid-rock interactions, and temperature variations over the earthquake cycle. The Pioneer fault at Little Fall Creek in south-central Idaho provides an excellent opportunity to study nanostructure changes of carbonaceous matter as a function of fault deformation. At this location, the Pioneer Fault exhibits a well-defined principal slip zone (PSZ) composed of multi-layered white siliceous mineralization and black carbon to graphite with a continuously exposed adjacent damage zone that includes …

Soil Reclamation Strategies In Construction Disturbed Soil, Alexis Koelling

All Graduate Reports and Creative Projects, Fall 2023 to Present

The rapid urbanization occurring in arid environments like the Intermountain West region of the U.S. significantly alters soil conditions. Construction of roads, buildings, and other infrastructure leads to the disturbance of soil structure, nutrient depletion, and reduced fertility. This research addresses the need for sustainable soil management practices that may restore soil health post-construction. In this study, the effectiveness of various soil amendments and application methods on specific soil parameters and turfgrass establishment in construction-disturbed soils was evaluated. The study highlights the critical role of soil amendments, particularly municipal solid waste (MSW) compost, in improving soil quality and plant growth. …

Side Channel Detection Of Pc Rootkits Using Nonlinear Phase Space, Rebecca Clark

Honors Theses

Cyberattacks are increasing in size and scope yearly, and the most effective and common means of attack is through malicious software executed on target devices of interest. Malware threats vary widely in terms of behavior and impact and, thus, effective methods of detection are constantly being sought from the academic research community to offset both volume and complexity. Rootkits are malware that represent a highly feared threat because they can change operating system integrity and alter otherwise normally functioning software. Although normal methods of detection that are based on signatures of known malware code are the standard line of defense, …

Cost-Risk Analysis Of The Ercot Region Using Modern Portfolio Theory, Megan Sickinger

Master's Theses

In this work, we study the use of modern portfolio theory in a cost-risk analysis of the Electric Reliability Council of Texas (ERCOT). Based upon the risk-return concepts of modern portfolio theory, we develop an n-asset minimization problem to create a risk-cost frontier of portfolios of technologies within the ERCOT electricity region. The levelized cost of electricity for each technology in the region is a step in evaluating the expected cost of the portfolio, and the historical data of cost factors estimate the variance of cost for each technology. In addition, there are several constraints in our minimization problem to …

3d Analysis Of Fe-Ti Oxides And How They Affect Crystal-Plastic Deformation In Atlantis Bank, Southwest Indian Ridge, Sarah Hill

Master's Theses

This project focuses on the importance of the relationship between Fe-Ti oxide abundance and interconnectivity, and crystal-plastic deformation in Atlantis Bank, Southwest Indian Ridge by utilizing Micro-CT scanning. This was done through comparing the Micro-CT scans of 15 samples from three different Ocean Drilling Program and International Ocean Discovery Program drill holes using the Nikon NIS Advanced Research 3-D visualization program and producing plots and statistics from MATLAB. Results indicate a wide range of textures across a range of crystal-plastic fabric intensity and Fe-Ti oxide abundance. Ultimately, there was a generally positive relationship between depth, CPF intensity, and Fe-Ti oxide …

Analysis And Construction Of Artificial Neural Networks For The Heat Equations, And Their Associated Parameters, Depths, And Accuracies., Shakil Ahmed Rafi

Graduate Theses and Dissertations

This dissertation seeks to explore a certain calculus for artificial neural networks. Specifically we will be looking at versions of the heat equation, and exploring strategies on how to approximate them.

Our strategy towards the beginning will be to take a technique called Multi-Level Picard (MLP), and present a simplified version of it showing that it converges to a solution of the equation (^∂/_∂t u_d ) (t, x) = (∇² _x u_d)(t, x).

We will then take a small detour exploring the viscosity super-solution properties of solutions to such …

Fabrication And Characterization Of Black Phosphorus Terahertz Photoconductive Antennae, Katie Michelle Welch

Graduate Theses and Dissertations

Advancements in terahertz (THz) imaging systems, particularly for applications like post-surgical analysis of breast cancer, have led to the exploration of novel materials such as black phosphorus as the active material for a THz photoconductive antenna (PCA). This thesis, motivated by innovative techniques developed at the University of Arkansas, investigates the potential of black phosphorus as a material to enhance the performance of THz PCAs, focusing on generation efficiency and bandwidth. Previous implementations of BP as THz emitters have shown limitations, highlighting the need for thorough material characterization and optimized fabrication processes. Therefore, we adopted a dual-phase approach to this …

Ethical Imperatives And Challenges: Review Of The Use Of Machine Learning For Predictive Analytics In Higher Education, Emily Barnes, James Hutson, Karriem Perry

Faculty Scholarship

The escalating integration of machine learning (ML) in higher education necessitates a critical examination of its ethical implications. This article conducts a comprehensive review of the application of ML for predictive analytics within higher education institutions (HEIs), emphasizing the technology's potential to enhance student outcomes and operational efficiency. The study identifies significant ethical concerns, such as data privacy, informed consent, transparency, and accountability, that arise from the use of ML. Through a detailed analysis of current practices, this review underscores the need for HEIs to develop robust ethical frameworks and technological infrastructures to navigate these challenges effectively. The findings reveal …

Design, Synthesis, And Optimization Of Allosteric Inhibitors Of Hiv-1 Integrase, Krunal H. Patel

Dissertations

The human immunodeficiency virus type 1 (HIV-1) infection remains a global health crisis, necessitating the development of innovative antiviral strategies. During the integration step, HIV-1 integrase (IN) interacts with viral DNA and the cellular cofactor LEDGF/p75 to effectively integrate the reverse transcript into the host chromatin. Recently, a novel class of antiretroviral agents called Allosteric Inhibitors of HIV-1 Integrase (ALLINI) compounds has emerged as a promising avenue in the fight against HIV-1. While originally designed to inhibit IN-LEDGF/p75 interactions, these compounds have been shown to also impact late-stage viral maturation severely through IN multimerization. Induction of IN multimerization interferes with …

Consultation Summary For Proposed Declared Pest Rates 2024/2025, Department Of Primary Industries And Regional Development, Western Australia

Biosecurity published reports

Before determining a rate, the Minister for Agriculture and Food is required to consult with owners of the land to be rated, as described in the Biosecurity and Agriculture Management (Declared Pest Account) Regulations 2014 (the Regulations).

The annual process for consultation enables the Department of Primary Industries and Regional Development (DPIRD) to gauge landholder perception on the proposed Declared Pest Rate (DPR) in accordance with the Regulations.

Synthesis Of Thermoresponsive Poly(N-Isopropyl Acrylamide) Based Core-Shell And Hollow Shell Nanogel With Tunable Core And Shell Thickness, Mohamad Hijazi, Molla R. Islam

Student Scholar Symposium Abstracts and Posters

Nanogels have emerged as a notably safer and more effective means for drug delivery, primarily due to their adjustable drug-loading capabilities. Hollow-core nanoparticles offer some unique properties that are desirable for drug delivery applications. Initially, silica core nanoparticles were synthesized using the Stöber process at different temperatures where Tetraethoxysilane (TEOS) undergoes hydrolysis in the presence of ethanol and then a condensation reaction to form silica nanoparticles. Scanning Electron Microscopy (SEM) and Optical Microscopy (OM) analysis revealed that the size of silica core particles varied with the synthesis temperature (300 nm at 30°C to 150 at 60°C). The core silica particles …

Life On The Edge: The Cambrian Marine Realm And Oxygenation, Sara Pruss, Benjamin C. Gill

Geosciences: Faculty Publications

The beginning of the Phanerozoic saw two biological events that set the stage for all life that was to come: (a) the Cambrian Explosion (the appearance of most marine invertebrate phyla) and (b) the Great Ordovician Biodiversification Event (GOBE), the subsequent substantial accumulation of marine biodiversity. Here, we examine the current state of understanding of marine environments and ecosystems from the late Ediacaran through the Early Ordovician, which spans this biologically important interval. Through a compilation and review of the existing geochemical, mineralogical, sedimentological, and fossil records, we argue that this interval was one of sustained low and variable marine …

Reviving The Past: Enhancing Language Models With Historical Text Optimization, Heather D. Broome

Honors Theses

Recent advancements in Natural Language Processing (NLP) have brought attention to the significant potential that exists for widespread applications of Large Language Models (LLMs). As demands and expectations for LLMs rise, ensuring efficiency and accuracy becomes paramount. Addressing these challenges requires more than just optimizing current techniques; it urges novel approaches to NLP as a whole. This study investigates novel data preprocessing methods designed to enhance LLM performance by mitigating inefficiencies rooted in natural language, particularly by simplifying the complexities presented by historical texts. Utilizing the classical text The Odyssey by Homer, two preprocessing techniques are introduced: tokenization of names …

Disconnectivity Graphs Of Spin Glasses On The Kagome Lattice, Richard Richardson

Honors Theses

The topology of the potential energy landscape for a spin-glass arranged on the Kagome lattice is studied by the use of enhanced disconnectivity graphs. Enhanced disconnectivity graphs display location and type of minima structures and the barrier heights between them. Three different models which differ in the range of allowed values for the bond strength are analyzed. The allowed values for bond strength for the three different models are {±1}, {±1, ±2}, and {±1, ±2, ±3}. 100 systems were randomly generated for each model, and enhanced disconnectivity graphs were drawn for each system by using the Hamiltonian of the Ising …

How To Explain Allen-Manandhar’S Method To Beginner Mathematicians : A Convergence Analysis Of A Hybrid Method For Variable-Coefficient Boundary Value Problems, Rebecca Scariano

Honors Theses

In this project, analogies are employed to make complex math concepts approachable to beginners who may only have a basic understanding of calculus and linear algebra. Serving as the focal point of this project, Allen-Manandhar’s method solves an equation, known as an ordinary differential equation (ODE). The mentioned equation with its coefficients is comparable to a pie recipe with ingredients. With the outcome to a recipe seen as its solution, the solution to our pie recipe is a perfectly baked pie, as in without error. The chosen method for baking a pie then classifies as its baking approach that when …

Learning Scene Semantics For 3d Scene Retrieval, Natalie Gleason

Honors Theses

This project presents a comprehensive exploration into semantics-driven 3D scene retrieval, aiming to bridge the gap between 2D sketches/images and 3D models. Through four distinct research objectives, this project endeavors to construct a foundational infrastructure, develop methodologies for quantifying semantic similarity, and advance a semantics-based retrieval framework for 2D scene sketch-based and image-based 3D scene retrieval. Leveraging WordNet as a foundational semantic ontology library, the research proposes the construction of an extensive hierarchical scene semantic tree, enriching 2D/3D scenes with encoded semantic information. The methodologies for semantic similarity computation utilize this semantic tree to bridge the semantic disparity between 2D …