Physical Sciences and Mathematics Commons^™

Developing Educational Tools For Sustainable Stormwater Management, Lauren Houskeeper

All Graduate Reports and Creative Projects, Fall 2023 to Present

Rapid population growth and development in Western states are exerting strain on the region’s limited water resources. Urbanization exacerbates this issue by increasing impervious surfaces, limiting infiltration of precipitation during storm events and snowmelt, which results in changes to hydrologic conditions with higher runoff volumes and higher peak flows. Stormwater transports pollutants as it flows across impervious surfaces, discharging high volumes of runoff and elevated loads of urban contaminants into receiving waters. The amount of pollution entering waterways continually increases as urban areas expand. Utah is currently experiencing a rapid transition from undeveloped to developed landscapes, necessitating the implementation of …

Leveraging International Large-Scale Assessments: Insights From An Item-Writing Professional Development Program For High School Mathematics Teachers, Mark Lester B. Garcia, Catherine P. Vistro-Yu

Mathematics Faculty Publications

The Philippine Department of Education, despite seeing minimal improvements in the country’s score and rankings in the recent cycles of international large-scale assessments (ILSAs) such as TIMSS and PISA, maintained that it shall continue to participate in ILSAs to monitor the progress of educational effectiveness and benchmark with other countries by observing and adopting commendable practices. While legislators and other stakeholders push for increased financial resources in the education sector as part of the country’s preparations for upcoming ILSAs, one crucial aspect that is largely overlooked is teacher training. This paper presents a viable yet contentious way of upskilling teachers …

High Fat Diet & Social Isolation: Interactive Effects On Pain, Cognition, & Neuroinflammation, Ian M. Campuzano

Research Psychology Theses

Prior research has established a role for both social isolation and exposure to high fat Western diets in altering a range of behaviors from reduced memory performance to increased depression-like behaviors. The present study scrutinizes the interplay among these variables during the peri-adolescent developmental phase, utilizing Long-Evans rats as the experimental model. Our overarching hypothesis is that rats exposed to either social isolation, a high-fat diet, or both will result in heightened pain sensitivity, diminished cognitive flexibility, and increased neuroinflammatory responses within brain regions implicated in sociability, cognition, memory, and pain processing. Behavioral flexibility will be assessed using a maze-based …

Synthesis And Characterization Of Medicinally Privileged Aza Heterocycles, Nneoma James

Theses and Dissertations

Four-membered cyclic amides, commonly known as β-lactams, have played a crucial role in drug discovery research since its discovery by Alexander Fleming in 1928 from Penicillium notatum. The β-lactam antibiotics are broadly effective against several bacterial infections through acylating the transpeptidase involved in cross-linking peptides to form peptidoglycan or periplasmic murein, which is a fundamental constituent of the bacterial cell wall for both the gram-positive (ten or more layers) and gram-negative (one or two layers) bacteria. Although for more than eight decades, β-lactams have been recognized as antibiotics, later, other medicinal activities of β-lactam derivatives have been reported, including lowering …

Chemical Investigation Of The Ethanol Extract Of Tillandsia Usneoides (Spanish Moss), Jakir Hossain

Theses and Dissertations

Tillandsia usneoides in epiphytic bromeliads takes up water through absorptive trichomes on the shoot surface under extreme environmental conditions. Although previous studies revealed the way by which T. usneoides absorbs water and prevents water loss, its water transport remains unclear. Uses of T. usneoides L. have been documented going back to pre-Columbian and late archaic societies. Between the 1800s and 1900s. T. usneoides was utilized in fruit packing and polish, among other industrial goods. In terms of medicine, tillandsia is well-known for treating leucorrhea, rheumatism, ulcers, hemorrhoids, and as an anti-diabetic, emetic, analgesic, purgative, antispasmodic, and diuretic. The chemical composition …

White Light Specular Reflection Data Augmentation For Polyp Detection, Jose Angel Nunez

Theses and Dissertations

Colorectal cancer is among the deadliest cancers, but fortunately, this type of cancer can be prevented. The best current method of prevention is via detecting the bad polyps in the colon in time. Furthermore, the best method we have available to detect these bad polyps is through colonoscopies. Even though a lot of lives have been saved via these methods, it is still not perfect because of human error. Integrating artificial intelligence into colonoscopy procedures is our next evolution in increasing our prevention of colorectal cancer. Polyp detectors are one of the tools brought by advancements in technology that may …

Comparative Analysis Of Transfer Learning Strategies For Polyp Detection In Colonoscopy Images Using Yolov8, Fabian Vazquez Jr.

Theses and Dissertations

The early detection of polyps during colonoscopy procedures is crucial for preventing colorectal cancer, a leading cause of cancer-related deaths globally. Traditional methods for polyp detection are often time-consuming and prone to human error. This thesis investigates the effectiveness of transfer learning, the process of taking a pre-trained model that was trained on a large dataset and adapting it to a new, but related task, requiring less data and time for training. This research compares whether the YOLOv8 model trained from scratch on a specific polyp dataset is outperformed by transfer learning methods such as utilizing a pretrained model on …

Missing Data Imputation With Longitudinal Data, Joseph Omar Alanis

Theses and Dissertations

In the repeated measures longitudinal datasets where missing data is a relatively common issue, we explored different imputation methods, including machine learning (ML) methods in order to examine potential efficiencies for using traditional versus newer computational methods. In order to accomplish said comparison, we used a Monte Carlo simulation experiment of a population of size N=70000 to mimic a clinical trial, with different scenarios of missing at random (MAR) data in the response variable. To compare the behavior of each method resulting from the difference between population and sample dataset, a real dataset was used from the Boston College on …

Recognizing Triangles Using Weighted Ehrhart Polynomials, Rafael Sarabia

Theses and Dissertations

Ehrhart theory is a classical topic for polygons or polytopes with vertices with integer coordinates. One of the main results of the theory claims that for every convex polygon P with integer vertices, the number of integer points in its nth dilation is a polynomial in n, the Ehrhart polynomial of P. This property can be extended if for a polynomial weight w(x, y), we sum values of w(x, y) over all points with integer coordinates in the nth dilation of P. The resulted polynomial is called the weighted Ehrhart polynomial of P associated with the weight w. In this …

Rabi Oscillations And Entanglement Between Two Rydberg Atoms In An Optical Cavity Studied By The Jaynes-Cummings Model And Quantum Circuits On Qiskit, Francisco D. Santillan

Theses and Dissertations

Rydberg atoms are highly excited atoms in which one electron has a large principal quantum number. Due to their unusual atomic properties, Rydberg atoms are promising building blocks of two-qubit gates and light-atom quantum interfaces in quantum information processing. For two atoms at close distance (< 10 mm) the Rydberg blockade prevents the two atoms to be simultaneously in the excited state whereas this blockade is absent for atoms far apart. Recently, this effect was used to engineer a quantum processor based on two-dimensional arrays of neutral atoms which are trapped and transported by optical tweezers. Motivated by these experiments, we study the light-atom interaction and entanglement of two Rydberg atoms interacting by the Rydberg blockade in an optical cavity using the Jaynes-Cummings model. We find a rich variety of Rabi oscillations and entanglement as a function of initial conditions and interaction time, which may be used to generate two-qubit gates. Furthermore, we develop and simulate a quantum circuit of this system using Qiskit, an open-source software development kit designed to emulate the operation of a real Quantum Computer.

Density Functional Theory Calculations On Electronic And Optical Properties Of Mos2/Metal Heterojunction, Mos2/Graphene/Metal Vertical Heterostructure Interfaces And Sulfur Vacancies On Mos2/Au, Shishir Timilsena

Theses and Dissertations

In this study, we conducted a comprehensive investigation on computational simulations and analyses of heterostructures formed by two-dimensional (2D) molybdenum disulfide (MoS2) and graphene (Gr) on various metal coated substrates, including gold (Au), copper (Cu), nickel (Ni), and platinum (Pt). The frequency-dependent dielectric function (ɛ(ω)), refractive index (n), and reflectivity (R) are determined using light polarization parallel and perpendicular to the c axis of the 2D layers. Our findings reveal that MoS2/Au, MoS2/Cu, and MoS2/Pt heterostructures exhibit a direct bandgap at the K-point of the Brillouin zone, whereas their corresponding MoS2/MoS2/Metal structures present an indirect bandgap. The reduced interlayer spacing …

Thermodynamic Feasibility Of Potential Nano-Energetic Systems Based On Metal Oxynitrides, Manoj Chhetri

Theses and Dissertations

A computational study was undertaken with the objective of identifying the nano-energetic systems containing aluminum as fuel and metal oxynitrides as oxidizer, aiming to achieve an exothermic reaction characterized by the maximum values of gas generation, adiabatic combustion temperature, and energy release. For the thermodynamic calculation, nine systems based on metal oxynitrides were taken using the THERMO software that works based on the Gibbs free energy minimization, together with HSC Chemistry 7 to calculate the thermodynamic equilibrium concentrations of reactants and products corresponding gas generation, temperature and energy release by varying the fuel to oxidizer ratio. Among all the chosen …

Enabling Iov Communication Through Secure Decentralized Clustering Using Federated Deep Reinforcement Learning, Chandler Scott

Electronic Theses and Dissertations

The Internet of Vehicles (IoV) holds immense potential for revolutionizing transporta- tion systems by facilitating seamless vehicle-to-vehicle and vehicle-to-infrastructure communication. However, challenges such as congestion, pollution, and security per- sist, particularly in rural areas with limited infrastructure. Existing centralized solu- tions are impractical in such environments due to latency and privacy concerns. To address these challenges, we propose a decentralized clustering algorithm enhanced with Federated Deep Reinforcement Learning (FDRL). Our approach enables low- latency communication, competitive packet delivery ratios, and cluster stability while preserving data privacy. Additionally, we introduce a trust-based security framework for IoV environments, integrating a central authority …

An Application Of An In-Depth Advanced Statistical Analysis In Exploring The Dynamics Of Depression, Sleep Deprivation, And Self-Esteem, Muslihat Gaffari

Electronic Theses and Dissertations

Depression, intertwined with sleep deprivation and self-esteem, presents a significant challenge to mental health worldwide. The research shown in this paper employs advanced statistical methodologies to unravel the complex interactions among these factors. Through log-linear homogeneous association, multinomial logistic regression, and generalized linear models, the study scrutinizes large datasets to uncover nuanced patterns and relationships. By elucidating how depression, sleep disturbances, and self-esteem intersect, the research aims to deepen understanding of mental health phenomena. The study clarifies the relationship between these variables and explores reasons for prioritizing depression research. It evaluates how statistical models, such as log-linear, multinomial logistic regression, …

Exploring The Diagnostic Potential Of Radiomics-Based Pet Image Analysis For T-Stage Tumor Diagnosis, Victor Aderanti

Electronic Theses and Dissertations

Cancer is a leading cause of death globally, and early detection is crucial for better

outcomes. This research aims to improve Region Of Interest (ROI) segmentation

and feature extraction in medical image analysis using Radiomics techniques

with 3D Slicer, Pyradiomics, and Python. Dimension reduction methods, including

PCA, K-means, t-SNE, ISOMAP, and Hierarchical Clustering, were applied to highdimensional features to enhance interpretability and efficiency. The study assessed the ability of the reduced feature set to predict T-staging, an essential component of the TNM system for cancer diagnosis. Multinomial logistic regression models were developed and evaluated using MSE, AIC, BIC, and Deviance …

Emotionality Stigma Scale: Measurement Development, Reliability, And Validity., Hayley D. Seely

Electronic Theses and Dissertations

Emotions are biological responses to stimuli that allow individuals to derive meaning, appraise experiences, and prepare to respond. However, individuals perceive emotions differently based on emotion socialization which not only dictates the way emotions are viewed and managed but also has been directly linked with mental health outcomes. Furthermore, research shows emotion socialization is informed by demographic variables such as gender such that the expectations of emotionality differ; where women are taught to express emotions, men are taught to conceal. Given the societal rules regarding emotionality, it is possible that emotionality stigma – the stigma around the experience and expression …

Fishing Vessel Detection In Exclusive Economic Zones From Low Earth Orbit Satellites With Power And Computational Constraints, Kyler E. Nelson

All Graduate Theses and Dissertations, Fall 2023 to Present

Illegal fishing activities pose a significant threat to the sustainability of marine ecosystems and the economies and societies which rely on them. Detection of fishing vessels engaging in illegal activity is difficult, as many ships engaging in such activity actively avoid detection through radio systems used for maritime traffic monitoring. Satellite imagery provides a promising means for detecting fishing vessels, though designing an effective system is difficult due to limited availability of labeled image datasets of fishing vessels. This research proposes a system to detect illegal fishing activity through the use of a low-power ship detection satellite and proposes a …

Md Simulations Of Collision Effects For A Strongly Coupled Plasma, Jawon Jo

All Graduate Theses and Dissertations, Fall 2023 to Present

Studying strongly coupled plasmas can be effectively accomplished using molecular dynamics (MD) simulations. We have developed an advanced MD simulation code that can analyze plasmas with various coupling parameters. This code employs a spherically symmetric cut-off Coulomb force verified through convergence tests by modulating the cut-off and minimum force ranges. Additionally, it incorporates a new algorithm for optimizing the initial positions of particles at a given temperature. This method maintains the temperature constant and the velocity distribution unchanged. As a result, we eliminate the unphysical initial rises and oscillations in temperature that a random distribution of positions causes. The code …

Informed Intervention Design, Deployment, And Analysis For The Computer Science Classroom, Jaxton J. Winder

All Graduate Theses and Dissertations, Fall 2023 to Present

Improving the teaching of computer science is a challenging task. Educators and computing education researchers devote large amounts of time, energy, and resources towards doing so effectively. One of the ways this is done is through research-informed design, deployment, and analysis of targeted interventions to the classroom. This thesis will detail research conducted at Utah State University targeting classroom interventions: centered around their design, deployment, and analysis.

One of these interventions aims to tackle student procrastination through the offering of “grace points”–forgiving a small amount of mistakes on a student’s assignment–for analyzing a homework assignment early. Through studying this intervention, …

Current Trends In Bee Conservation And Habitat Restoration In Different Types Of Anthropogenic Habitats, Olivia Kline, Neelendra K. Joshi

Entomology and Plant Pathology Faculty Publications and Presentations

Recent declines in bee populations and ranges have been cause for concern due to the valuable pollination service that they provide. Several factors have been proposed to contribute to these declines, including habitat loss, pathogen spread, and pesticide usage, so many pollinator conservation schemes have involved the addition of pollinator-friendly habitat through wildflower plantings and artificial nesting sites. Because of this, many efforts have been made to enhance bee populations across different landscape types, including natural, agricultural, urban, and industrial areas. Many of these schemes have focused on providing habitat for bees and other animal pollinators in agricultural landscapes, but …

Creating A Virtual Hierarchy From A Relational Database, Yucong Mo

All Graduate Theses and Dissertations, Fall 2023 to Present

In data management and modeling, the value of the hierarchical model is that it does not require expensive JOIN operations at runtime; once the hierarchy is built, the relationships among data are embedded in the tree-like hierarchical structure, and thus querying data could be much faster than using a relational database. Today most data is stored in relational databases, but if the data were stored in hierarchies, what would these hierarchies look like? And more importantly, would this transition lead to a more efficient database? This thesis explores these questions by introducing a set of algorithms to convert a relational …

Metal Assisted O2-Dependent Carbon-Carbon Bond Cleavage Of Β-Diketones And Flavonols, Stephen N. Anderson

All Graduate Theses and Dissertations, Fall 2023 to Present

Almost everything we interact with on a daily basis has been synthesized by chemists ranging from plastics, food preservatives, and medications. The diversity of synthetic molecules are achieved by the formation of new bonds between existing molecules and/or through the cleaving of bonds found in a molecule. There are uncountable amount of conditions reported to facilitate chemical reactions which all depend on the nature of molecules being used and the environment it is used in.

In recent years, more attention has been paid to identify chemical reactions that can use more environmentally favorable conditions and reduce the use of limited …

Dynamics Of Climate And Tectonics On Surface Processes And Their Sedimentary Archives In The Colorado Plateau And Basin And Range, Usa And The Calabrian Forearc, Sicily, Natalie M. Tanski

All Graduate Theses and Dissertations, Fall 2023 to Present

Landscapes change over time in response to movements of the Earth’s crust and the effects of climate. This dissertation examines how these factors shape different landscapes, focusing on erosion of river canyons in elevated plateaus, how the transport history in quartz sand may be encoded in its properties, and how a paleo-delta has formed in response to sea-level change and fault displacement. I use dating techniques, field methods, and topographic analyses to offer insight into erosional patterns and rates in different landscapes.

Rivers can take a long time to adjust to changes in boundary conditions, even after those changes have …

Settingsorder Article Reprints Open Accessarticle A Model To Account For The Effects Of Load Ratio And Hydrogen Pressure On The Fatigue Crack Growth Behavior Of Pressure Vessel Steels, Ashok Saxena, Kip O. Findley

Mechanical Engineering Faculty Publications and Presentations

A phenomenological model for estimating the effects of load ratio R and hydrogen pressure P_H2 on the hydrogen-assisted fatigue crack growth rate (HA-FCGR) behavior in the transient and steady-state regimes of pressure vessel steels is described. The "transient regime" is identified with crack growth within a severely embrittled zone of intense plasticity at the crack tip. The "steady-state" behavior is associated with the crack growing into a region of comparatively lower hydrogen concentration located further away from the crack tip. The model treats the effects of R and P_H2 as being functionally separable. In the transient …

Electrocatalytic Reduction Of Hydrogen Peroxide At Paraffin-Sealed Nitrogen-Doped Carbon Fiber Ultramicroelectrodes, Yakubu Gausu Mohammed

Electronic Theses and Dissertations

Compared to unmodified carbons and even some metal materials, nitrogen-doped carbons have been found to exhibit better performance for reducing oxygen-oxygen bonds, a key step in electroreduction of both O₂ (an important reaction in energy applications) and H₂O₂ (an important reaction in sensing and biosensing). Previous studies from our lab revealed that thermal decomposition of urea in the presence of carbon fiber (CF) results in N-doped that exhibited good electrocatalytic properties for H₂O₂ reduction. However, previous methods of sealing ultramicroelectrodes (UMEs) made from N-doped CF using laser heating of borosilicate capillaries and epoxy …

High Prevalence Of Artifacts In Optical Coherence Tomography With Adequate Signal Strength, Wei-Chun Lin, Aaron Coyner, Charles Amankwa, Abigail Lucero, Gadi Wollstein, Joel Schuman, Hiroshi Ishikawa

Wills Eye Hospital Papers

PURPOSE: This study aims to investigate the prevalence of artifacts in optical coherence tomography (OCT) images with acceptable signal strength and evaluate the performance of supervised deep learning models in improving OCT image quality assessment.

METHODS: We conducted a retrospective study on 4555 OCT images from 546 patients, with each image having an acceptable signal strength (≥6). A comprehensive analysis of prevalent OCT artifacts was performed, and five pretrained convolutional neural network models were trained and tested to infer images based on quality.

RESULTS: Our results showed a high prevalence of artifacts in OCT images with acceptable signal strength. Approximately …

Checklist For Reproducibility Of Deep Learning In Medical Imaging, Mana Moassefi, Yashbir Singh, Gian Marco Conte, Bardia Khosravi, Pouria Rouzrokh, Sanaz Vahdati, Nabile Safdar, Linda Moy, Felipe Kitamura, Amilcare Gentili, Paras Lakhani, Nina Kottler, Safwan Halabi, Joseph Yacoub, Yuankai Hou, Khaled Younis, Bradley Erickson, Elizabeth Krupinski, Shahriar Faghani

Department of Radiology Faculty Papers

The application of deep learning (DL) in medicine introduces transformative tools with the potential to enhance prognosis, diagnosis, and treatment planning. However, ensuring transparent documentation is essential for researchers to enhance reproducibility and refine techniques. Our study addresses the unique challenges presented by DL in medical imaging by developing a comprehensive checklist using the Delphi method to enhance reproducibility and reliability in this dynamic field. We compiled a preliminary checklist based on a comprehensive review of existing checklists and relevant literature. A panel of 11 experts in medical imaging and DL assessed these items using Likert scales, with two survey …

Advancing Telehealth Through Artificial Intelligence: Incorporating Emotional Intelligence And Addressing Cybersecurity Challenges, Mahima Rajendra Pulgaonkar

Electronic Theses, Projects, and Dissertations

This culminating experience project explores the integration of Emotional Artificial Intelligence (Emotional AI) into telehealth systems, addressing the dual challenges of enhancing patient care and mitigating cybersecurity risks. The research questions are: (Q1) How can Emotionally Intelligent AI improve telehealth systems' ability to recognize and respond to mental health symptoms? and (Q2) What are the specific cybersecurity challenges associated with AI in telehealth and how can they be mitigated? The findings for each question are: Q1: Emotionally Intelligent AI can significantly enhance telehealth by providing personalized, empathetic interactions that improve patient engagement, adherence to treatment plans, and early detection of …

Interpregnancy Interval And Adverse Perinatal Outcomes: A Within-Individual Comparative Method, Maria Sevoyan, Marco Geraci, Edward A. Frongillo, Jihong Liu, Nansi S. Boghossian

Faculty Publications

Background and Aim: Previously observed associations between interpregnancy interval (IPI) and perinatal outcomes using a between-individual method may be confounded by unmeasured maternal factors. This study aims to examine the association between IPI and adverse perinatal outcomes using within-individual comparative analyses. Methods: We studied 10,647 individuals from the National Institute of Child Health and Human Development Consecutive Pregnancies Study in Utah with ≥3 liveborn singleton pregnancies. We matched two IPIs per individual and used conditional logistic regression to examine the association between IPI and adverse perinatal outcomes, including preterm birth (PTB, < 37 weeks’ gestation), small-for-gestational-age (SGA, < 10th percentile of sex-specific birthweight for gestational age), low birthweight (LBW, < 2,500 g), and neonatal intensive care unit (NICU) admission. Point and 95% confidence interval (CI) estimates were adjusted for factors that vary across pregnancies within individuals. Results: CIs did not unequivocally support either an increase or a decrease in the odds of PTB (adjusted odds ratio [aOR]: 1.31, 95% CI: 0.87, 1.96), SGA (aOR: 0.81, 95% CI: 0.51, 1.28), LBW (aOR: 1.59, 95% CI: 0.90, 2.80), or NICU admission (aOR: 0.96, 95% CI: 0.66, 1.40) for an IPI < 6 months compared to 18–23-months IPI (reference), and neither did the CIs for the aOR of IPIs of 6–11 and 12–18 months compared to the reference. In contrast, an IPI ≥24 months was associated with increased odds of LBW (aOR: 1.66, 95% CI: 1.03, 2.66 for 24–29 months; aOR: 2.27, 95% CI: 1.21, 4.29 for 30–35 months; and aOR: 2.09, 95% CI: 1.17, 3.72 for ≥36 months). Conclusions: Using a within-individual comparative method, we did not find evidence that a short IPI compared to the recommended IPI of 18–23 months was associated with increased odds of PTB, SGA, LBW, and NICU admission. IPI ≥ 24 months was associated with increased odds of delivering an LBW infant.

A Survey On Homomorphic Encryption Based On The Learning With Rounding Problem, Jose Manuel Montoya

Boise State University Theses and Dissertations

Much of modern day cryptography deals with the notion of security and efficiency. The main concern with any cryptosystem deals with the practicality of being able to implement any encryption algorithm over large data sets. In this paper, we will look at the various properties of the Learning With Rounding problem (LWR) which comes from the Learning With Errors problem (LWE) first introduced by Oded Regev. We will also present the topic of Homomorphic Encryption (HE) as well as its three variants: Partially Homomorphic Encryption (PHE), Somewhat Homomorphic Encryption (SHE), and Fully Homomorphic Encryption (FHE). This paper also highlights SABER, …