Physical Sciences and Mathematics Commons^™

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, …

Robust Hydropower Planning Balances Energy Generation, Carbon Emissions And Sediment Connectivity In The Mekong River Basin, M. Tangi, Rafael Schmitt, Rafael M. Almeida, S. Bossi, Alexander S. Flecker, F. Sala, A. Castelletti

School of Earth, Environmental, & Marine Sciences Faculty Publications

We present a framework for strategic dam planning under uncertainty, which includes GHG emissions mitigation as a novel objective. We focus on the Mekong River Basin, a fast‐developing region heavily relying on river‐derived ecosystem services. We employ a multi‐objective evolutionary algorithm to identify strategic dam portfolios for different hydropower expansion targets, using process‐related and statistical models to derive indicators of sediment supply disruption and GHG emissions. We introduce a robust optimization approach that explores variations in optimal portfolio compositions for more than 5,000 state‐of‐ the‐world configurations, regarding sediment origins and trapping and GHG emissions. Thus, we can rank dam projects' …

Consistency Of Advanced Radiation Therapy Qa Methods And Global Auditing Systems, Fre'etta Brooks

Dissertations and Theses (Open Access)

Consistency of Advanced Radiation Therapy QA Methods and Global Auditing Systems

Fre’Etta M.D. Brooks, B.S.

Advisory Professor: Stephen F. Kry, Ph.D.

Abstract

Auditing systems provide a means to verify the implementation and operation of all equipment and radiation parameters used by an institution providing radiation therapy treatments. The systems are important tools that are used to determine if an institution can accurately deliver radiation therapy that requires complex planning in the form of IMRT or VMAT and credential radiotherapy treatment institutions for specific clinical trial protocols; to assure the quality of treatment to all patients. Auditing techniques vary by region …

Influential Factors And Predicting Dose Delivery Accuracy For Imaging And Radiation Oncology Core’S Phantom Program Using Machine Learning, Hunter Mehrens

Dissertations and Theses (Open Access)

IROC’s mission is to help ensure consistent and comparable, high-quality radiotherapy across clinics that participate in national clinical trials. To obtain this mission, IROC’s phantom program provides a third-party end-to-end check of the clinical workflow of a patient receiving radiotherapy. The goal of the phantom audit is to compare the dose delivered to the dose planned by the treatment system ensuring dose delivery accuracy. While IROC’s phantoms are better equipped to catch dose delivery errors compared to a clinic’s QA process, the end-to-end process and reporting of results is time-consuming creating a bottleneck for clinical trial participation. Furthermore, IROC’s passing …

Probabilistic Frames And Concepts From Optimal Transport, Dongwei Chen

All Dissertations

As the generalization of frames in the Euclidean space $\mathbb{R}^n$, a probabilistic frame is a probability measure on $\mathbb{R}^n$ that has a finite second moment and whose support spans $\mathbb{R}^n$. The p-Wasserstein distance with $p \geq 1$ from optimal transport is often used to compare probabilistic frames. It is particularly useful to compare frames of various cardinalities in the context of probabilistic frames. We show that the 2-Wasserstein distance appears naturally in the fundamental objects of frame theory and draws consequences leading to a geometric viewpoint of probabilistic frames.

We convert the classic lower bound estimates of 2-Wasserstein distance \cite{Gelbrich90, …

Electrochemical Characteristics Of Bio-Derived And Silicon-Based Materials For Lithium Ion And Lithium Sulfur Batteries, Nawraj Sapkota

All Dissertations

The increasing demand for advanced batteries, driven by automotive and energy storage needs, emphasizes the need for improved energy density, longevity, and cost-effectiveness. While lithium-ion batteries (LIBs) offer high energy density, their traditional anode and cathode materials are reaching their limits. Innovations in battery chemistry, particularly using sulfur cathodes and silicon-based anodes, are crucial. Sulfur and silicon are attractive due to their abundance, environmental friendliness, and higher theoretical capacities. This research aims to enhance the electrochemical performance of lithium-sulfur batteries using three-dimensional architectures and solid-state electrolytes, and to improve silicon-based materials by modifying their surface architectures.

Chapter 1 reviews the …

Assessment Of Tce And Chiral Pcb Dechlorination Rate, Congener Diversity, And Enantioselectivity In Town Creek, Sc, Usa Sediment Microcosms, Catherine P. Sumner

All Dissertations

Polychlorinated biphenyls (PCBs) and trichloroethene (TCE) are ubiquitous contaminants and are recognized as persistent organic pollutants due to their extreme chemical stability. PCBs were manufactured by chlorinating biphenyls that created 209 congeners with various structures, of which 19 are chiral and can exist as a pair of stable atropisomers. PCBs have been known to cause developmental and neurological toxicity in humans and wildlife; they can act as endocrine disrupters, carcinogens, and teratogens. Sangamo Weston Inc. was an industrial plant located near Town Creek in Pickens Country, South Carolina, that manufactured capacitors and used Aroclors 1016 and 1254 as dialectic fluids …

Ensuring The Privacy Compliance Of Voice Personal Assistant Applications, Song Liao

All Dissertations

Voice Personal Assistants (VPA) such as Amazon Alexa and Google Assistant are quickly and seamlessly integrating into people’s daily lives. Meanwhile, the increased reliance on VPA services raises privacy concerns, such as the leakage of private conversations and sensitive information. Privacy policies play an important role in addressing users’ privacy concerns and developers are required to provide privacy policies to disclose their apps’ data practices. In addition, voice apps targeting users in European countries are required to comply with the GDPR (General Data Protection Regulation). However, little is known about whether these privacy policies are informative and trustworthy on emerging …

Genomic Data Science Approaches For Understanding Human Diseases, Snehal Shah

All Dissertations

The intricate interplay of genetic predisposition, environmental influences, and lifestyle acts as the multifactorial landscape of diseases. Understanding this complexity presents a significant challenge. Molecular insights into disease mechanisms, particularly the interactions of DNA, RNA, and proteins with environmental and lifestyle factors, have revolutionized disease diagnosis, prognosis, and treatment. High-throughput technologies, such as next-generation sequencing, generate large amounts of molecular data, holding a wealth of knowledge. These datasets unveil the roles of genes and their interactions with various factors through analysis, shedding light on previously unknown molecular mechanisms underlying disease pathogenesis. Furthermore, they facilitate the discovery of biomarkers crucial for …

Relating Elasticity And Other Multiplicative Properties Among Orders In Number Fields And Related Rings, Grant Moles

All Dissertations

This dissertation will explore factorization within orders in a number ring. By far the most well-understood of these orders are rings of algebraic integers. We will begin by examining how certain types of subrings may relate to the larger rings in which they are contained. We will then apply this knowledge, along with additional techniques, to determine how the elasticity in an order relates to the elasticity of the full ring of algebraic integers. Using many of the same strategies, we will develop a corresponding result in the rings of formal power series. Finally, we will explore a number of …

Gan With Skip Patch Discriminator For Biological Electron Microscopy Image Generation, Nishith Ranjon Roy

Graduate Theses and Dissertations

GAN models have been successfully used for image generation in various sections such as real-life objects like human faces, cars, animal faces, landscapes, etc. This work focuses on biological electron microscopy (EM) image generation. Unlike other real-life objects, biological EM images are obtained through electron microscopy techniques to study biological specimens. Electron microscopy offers high resolution and magnification capabilities, making it a powerful tool for visualizing biological structures at the nanoscale. However, using GAN models for biological EM image generation poses challenges due to the complex and unique arrangements of biological structures and the sparse and asymmetrical patterns in EM …

Cubic Soft Ideals On B-Algebra For Solving Complex Problems: Trend Analysis, Proofs, Improvements, And Applications, Muhammad Saeed, Hafiz Inam Ul Haq, Mubashir Ali

Neutrosophic Systems with Applications

In this paper, we introduce the concepts of cubic soft (CS) algebra, CS o-subalgebra, and CS ideals within the framework of B-algebra. We provide comprehensive characterizations of these new structures, elucidating their unique properties and interrelationships. Specifically, we present detailed conditions under which a CS subalgebra can be classified as a closed CS ideal. Our analysis explores the intricate relationships among closed cubic soft ideals, cubic soft subalgebras, and cubic soft o-subalgebras. By doing so, we aim to provide a deeper understanding of how these structures interact and coexist within the broader context of B-algebra The findings offer significant insights …

Divergence Measures And Aggregation Operators For Single-Valued Neutrosophic Sets With Applications In Decision-Making Problems, Surender Singh, Sonam Sharma

Neutrosophic Systems with Applications

Single-valued neutrosophic sets (SVNSs) facilitate the representation of uncertain information more extensively than conventional methods. The study of divergence measures of SVNSs is important due to their applications in different areas like multi-criteria decision-making (MCDM), pattern recognition, cluster analysis, machine learning, etc., In this paper, we introduce a divergence measure for SVNSs. The suggested divergence measure is applied to cluster analysis for the classification of imprecise data. For establishing the reasonability and advantage of the suggested divergence measure in a clustering problem over the existing measures, a comparative assessment is also presented. Furthermore, we introduce, an inferior ratio method for …

Rotational State-To-State Transition Rate Coefficients For H2O + H2O Collisions At Nonequilibrium Conditions, Bikramaditya Mandal, Michal Zoltowski, Martin Cordiner, François Lique, Dmitri Babikov

Chemistry Faculty Research and Publications

Aims. The goal is to develop a database of rate coefficients for rotational state-to-state transitions in H₂O + H₂O collisions that is suitable for the modeling of energy transfer in nonequilibrium conditions, in which the distribution of rotational states of H₂O deviates from local thermodynamic equilibrium.

Methods. A two-temperature model was employed that assumed that although there is no equilibrium between all possible degrees of freedom in the system, the translational and rotational degrees of freedom can be expected to achieve their own equilibria independently, and that they can be approximately characterized by Boltzmann …

La1-Xsrxcoo3 Perovskite: Antimicrobial Properties And Pvdf Based Piezoelectric Nanogenerator For Energy Storage Through Self-Induced Polling, S M. Anyet Ullah Shohag

Theses and Dissertations

Piezoelectric Nanogenerators (PENGs), which can produce electrical energy from mechanical energy via ferroelectric effect, are one of the ambient sources of green energy. PENGs have gathered a huge attention due to cost-effectiveness, mechanical stability, and easy installation process. In this experiment, different weight percent of Sr2+ doped Lanthanum Cobaltite (La1- XSrXCoO3) perovskite, a ferroelectric material, was synthesizes by using a simple combination of sol-gel and molten-salt process and then characterization by X-ray diffraction, and scanning electron microscopy ensures the uniform morphology of nano cubes. Poly (vinylidene difluoride) (PVDF), N,N-dimethylformamide and acetone solution were used to make a flexible film using …

Exploratory Analysis In Rio Grande Valley Real Estate Development, Mathew C. Sosa

Theses and Dissertations

The aim of this thesis is to apply exploratory data analysis and machine learning (ML) to answer critical questions in real estate development within the Rio Grande Valley (RGV). The real estate development sector is highly dynamic and relies on multiple integrated systems and planning to bring new homes to the market. Customer Relationship Management (CRM) software and real estate listing services, such as Redfin, are utilized to manage the customer lifecycle and analyze the local market, respectively. Two of the most crucial aspects of the customer lifecycle are the first home tour and deal closing. This paper explores the …

Tales In The Teeth: Using Isotopic Analysis To Understand The Paleoecology And Social Behavior Of Brontotheres Of The Intermountain Basins During The Middle Eocene, John Michael Michalski

All Graduate Reports and Creative Projects, Fall 2023 to Present

Isotopic analysis has been a common practice used in paleontology to study ancient ecosystems, and the lives of animals therein. Oxygen isotopic analysis is of particular importance not only because of its use in studying paleoecology, diet, and migration, but also its use in studying mountain elevation, and its impact on ancient ecosystems. I use stable oxygen isotopic analysis to study the habits and ecology of brontotheres from intermountain basins surrounding the Uinta Mountains of Utah and Wyoming, USA. I studied the oxygen isotopes from 16 fossil specimens of teeth, most of which belonged to brontotheres, including the genera Palaeosyops …

Staying Fresh: Unconventional Approaches Towards Advancing Energy Sustainability, Water Resources, And Community Resiliency In The Southwestern United States, Judith Hoyt

Open Access Theses & Dissertations

This dissertation addresses critical challenges in urban heat management, sustainable energy resource utilization, and water quality communication through three studies. Study 1 investigates the impact of roof color on urban heat islands in Tucson, Arizona where approximately 70% of roofs display high albedo (i.e., light) colors. Energy consumption simulations conducted indicate that converting dark- to light-colored roofs could save Tucson approximately $1,400,000 annually in energy costs, highlighting the potential of cool roofs for energy savings and improved thermal comfort. Study 2 assesses the sources of lithium in subsurface waters in West Texas and South Central New Mexico. Water chemistry data …

Neural Networks For Decisions Under Uncertainty, Edwin Tomy George

Open Access Theses & Dissertations

Neural networks are used in many real-world applications, ranging from classification tasks to medical diagnostics. For each task, a neural network is typically able to make predictions due to its ability to extract meaningful patterns from processing large amounts of data. Thus, given the increases in available data in recent decades, the performance of neural networks in making accurate predictions has greatly increased. However, this data often comes with ingrained uncertainties due to measurement errors or the inherent variability of individual data points. Neural networks can learn despite the errors in the overall data, but what if we want them …

Experimental And Theoretical Investigation Of The Coordination Of 8-Hydroxquinoline Inhibitors To Biomimetic Zinc Complexes And Histone Deacetylase 8 (Hdac8), Anthony M. Baudino, Harris F. Ciaccio, Michael J. Turski, Xavier A. Akins, Phoebus Sun Cao, Elisa Morales, Roger D. Sommer, Adam R. Johnson, Donald J. Wink, Kyle A. Grice, Kari Stone

Chemistry Department Faculty Articles

Zinc is integral to diverse biological functions, acting catalytically, structurally, and supportively in essential enzyme cycles, despite its limited amounts in the body. Targeting zinc enzymes with potent drugs, such as Vorinostat, demonstrates the therapeutic efficacy of zinc-binding ligands, notably in cutaneous T-cell lymphoma treatments. Our study merges experimental and theoretical approaches to analyze the coordination of 8-hydroxylquinoline (8HQ) inhibitors with biomimetic zinc complexes and human histone deacetylase 8 (HDAC8), a monozinc hydrolase enzyme. Assessing 10 8HQ derivatives for structural and electronic characteristics against these models, we observe minimal inhibition efficacy, corroborated through protein–ligand docking analyses, highlighting the complexities of …

Semantic Linguistic User Profiles For Automatic Computational Narrative Creation For Scientific Models, Angel Uriel Ortega Castillo

Open Access Theses & Dissertations

The outcomes of scientific models can be hard to understand given the need for context, domain knowledge, and many variables and data being used. This research aims to provide users of scientific models with understandable information that can be automatically generated. For the context of this research, understandable is defined as being correctly interpreted (i.e., with respect to the original intent of the data). Scientific information can be conveyed to users in the form of a narrative or visualizations, and these are not necessarily separate from each other, but rather complimentary. One of the objectives of this research is to …

Random Forest For High-Dimensional Data, George Ekow Quaye

Open Access Theses & Dissertations

The exponential growth of data has led to a rapid increase in high-dimensional datasets across various domains, presenting significant challenges in data analysis, particularly in predictive modeling tasks. Traditional Random Forest (RF), while robust, often struggles with datasets filled with numerous noisy or non-informative features, compromising both performance and accuracy. This study introduces an advanced algorithm, High-Dimensional Random Forests (HDRF), designed to address these challenges by integrating robust multivariate feature selection techniques directly into the decision tree construction process. Unlike standard RF, HDRF incorporates ridge regression-based variable screening at each decision split, enhancing its ability to identify and utilize the …

Quantum Circuit Optimization Leveraging Multi-Qubit Exchange Interactions In Spin Qubits, Miguel Gonzalo Rodriguez

Open Access Theses & Dissertations

This thesis looks into how multi-qubit exchange interactions can be used to improve quantumcircuits in semiconductor quantum devices. Pairwise interactions between qubits are a common tenet of traditional quantum computing paradigms, although they can impose complexity and depth constraints on circuits. In order to improve the efficiency and scalability of quantum circuits, this research explores the theoretical underpinnings and practical uses of multi-qubit interactions. A thorough theoretical framework is formulated, outlining the mathematical equivalence of a unitary matrix representing interactions between multiple qubits. We obtain the timeevolution operator by analyzing the Hamiltonian of three spin-1/2 particles. A number of quantum …

Seismic Imaging Of Mcmurdo Ice Shelf Near Williams Airfield, Yeshey Seldon

Open Access Theses & Dissertations

Seismic exploration has played a crucial role in understanding the Earth's interior and has been successfully employed in various regions, including Antarctica. This research focuses on analyzing a 1000-m seismic line on McMurdo Ice Shelf near Williams Airfield, as part of the Thwaites Interdisciplinary Margin Evolution (TIME) project. The McMurdo Ice Shelf, covering an expansive area within the Ross Ice Shelf, has undergone significant changes due to evolving oceanic and atmospheric conditions. The presence of Circumpolar Deep Water (CDW) has recently impacted the ice shelf, with warmer ocean waters causing basal melting and changes in wind patterns affecting ice flow …

Investigating Styles Of Contraction And Overprinting By Rio Grande Rift Extension In The Southern Indio Mountains, Western Texas, David W. West

Open Access Theses & Dissertations

Laramide-style intracontinental deformation occurred throughout a large area in the western United States from the late Cretaceous through the Eocene. This event is largely investigated and viewed from classic exposures in Colorado and Wyoming, extending south to southern New Mexico. In this region the Laramide orogen merges with the Mexican fold and thrust belt (MFTB) and the northern limits of the Mexican orogen along a blurry boundary. In the Indio Mountain range in western Texas, Cretaceous sediments were deposited in the Jurassic-Cretaceous Chihuahua trough. They were inverted due to contraction and emplaced adjacent to the Diablo Plateau. This region lies …

A Uniformly Most Powerful Test For The Mean Of A Beta Distribution, Richard Ntiamoah Kyei

Electronic Theses and Dissertations

The beta distribution is used in numerous real-world applications, including areas such as manufacturing (quality control) and analyzing patient outcomes in health care. It also plays a key role in statistical theory, including multivariate analysis of variance (MANOVA) and Bayesian statistics. It is a flexible distribution that can account for many different characteristics of real data. To our surprise, there has been very little work or discussion on performing statistical hypothesis testing for the mean when it is reasonable to assume that the population is beta distributed. Many analysts conduct traditional analyses using a t-test or nonparametric approach, try transformations, …