Digital Commons Network^™

From Molecular Crystals To Catalytic Surfaces: Computational Approaches To Complex Systems, Thiago Henrique Da Silva

Boise State University Theses and Dissertations

Understanding and modeling complex systems is one of the core challenges in modern science. Whether it be the intricate interactions within molecular crystals, the evolving mechanisms of bacterial resistance, or the dynamics of catalytic surfaces, accurately representing these systems is essential for scientific progress. This dissertation addresses these challenges by focusing on advances in computational modeling, demonstrating how various methods such as Density Functional Theory (DFT), machine learning, and custom-developed methods can simplify and help predict complex behaviors across multiple domains. By applying and understanding the scope of these methods to each field, this work underscores how computational modeling bridges …

A Comprehensive Review Of Carbon Sequestration And Its Assessment Techniques Using Remote Sensing And Geospatial Methods, Imen Ben Salem

All Works

Global warming has elevated carbon sequestration as a critical strategy for mitigating climate change, while enhancing sustainability in productivity. Agricultural land use systems contribute substantially to CO2 emissions due to crop residues, shifting cultivation practices, low-biomass crops, land degradation, and deforestation. The significant rise in CO2 emissions over the past thirty years is associated with burning fossil fuels, leading to substantial environmental changes, including global warming. Remote sensing (RS) and Geographic Information Systems (GIS) are advanced geospatial technologies that facilitate the rapid evaluation of terrestrial carbon stock over extensive regions. An integrated RS-GIS approach for carbon stock estimation and precision …

Development And Characterization Of Aso-Based Ribonuclease Targeting Chimera For The Degradation Of Cug Rna Repeat Expansion In Myotonic Dystrophy Type, Audrey Coons

Chemistry

Myotonic Dystrophy Type 1 is a multisystemic genetic disorder that primarily affects the muscles in the body leading to such pathologies as myotonia, muscle atrophy, insulin resistance and even neurological deficits. This disorder is caused by a series of CUG repeats in the 3’ untranslated region of the DMPK gene; symptoms appear after around 34 repeats. These repeats form foci when MBNL1 protein that deals with alternative splicing of many events in the body, forms aggregations around these repeats. These foci render the MBNL 1 proteins useless. There is no FDA approved therapeutic, but many RNA targeting therapeutics have been …

Building Toward A Text-Based Intervention For Parents Of Suicidal Adolescents Seeking Emergency Department Care: A Pilot Randomized Controlled Trial., Ewa Czyz, Inbal Nahum-Shani, Cynthia Ewell Foster, Valerie Micol, Amanda Jiang, Nadia Al-Dajani, Alejandra Arango, Maureen Walton, Victor Hong, Sheikh Iqbal Ahamed, Cheryl King

Computer Science Faculty Research and Publications

Objective: The growing demand for emergency department (ED) care for suicidal ideation and attempts in adolescents calls for effective interventions preventing post-ED recurrence of suicidal crises. Parents are tasked with implementing postdischarge suicide prevention recommendations, often with little support. To address this need, this study examined a parent-facing texting intervention targeting parental engagement in suicide prevention activities to lower youth suicide risk after discharge. Method: A pilot randomized controlled trial was conducted with 120 parents (83.3% mothers) and their adolescents (ages 13–17, 65.8% female, 75.0% White) presenting to an ED with suicide risk concerns. Parents were randomized to a control …

Early Breast Cancer Detection With Ultrasound Data Using Nmf, Rutvi Khamar

Theses and Dissertations

Early detection of breast cancer significantly influences patient outcomes. Dynamic Contrast-Enhanced Ultrasound (DCE-US) has shown promise in early detection by visualizing tumor vascularity and perfusion dynamics in real-time. This study evaluates the efficacy of DCE-US in distinguishing four stages of cancer progression: normal, hyperplasia, ductal carcinoma in situ (DCIS), and invasive cancer, using a transgenic mouse model that mimics human breast cancer. Ultrasound burst pulses, while commonly used to remove unbound contrast agents, can potentially damage human tissues. Using the pre-pulse data helps mitigate this risk, ensuring safer and more reliable measurements. A VEGFR2-targeted microbubble contrast agent was injected, and …

Personality Trait Recognition Through Deep Neural Temporal Modeling Of Non-Verbal Behavior, Kushal Vangara

Theses and Dissertations

Personality research seeks to explain the wide range of human behaviors through stable, measurable traits. Human interactions are inherently rich and multidimensional, and analyzing behavioral data offers a promising path to uncover personality insights. The increasing convergence of psychology, computer science, and machine learning has fueled interest in computational approaches to personality assessment. Advances in sensing technologies have made it possible to capture fine-grained information about individuals’ behaviors and interactions in naturalistic and controlled environments. Automated audio-visual analysis techniques extract relevant behavioral cues, which machine learning models then interpret to infer underlying personality traits. This work provides a comprehensive overview …

Environmental And Societal Impacts Of Agricultural Land Abandonment In Indonesia: A Bibliometric Review, Jane A. Landrum

Geosciences Undergraduate Honors Theses

In the past decades, Southeast Asia has faced one of the highest urbanization rates globally, with land conversion, agricultural land abandonment, and deforestation occurring simultaneously. High population growth rates and migration away from rural areas have also led to increased food insecurity, which has increased the need for agricultural production. In Indonesia, high rates of urbanization on the island of Java have historically prompted governmental policy solutions aimed at population redistribution and agricultural extensification (rather than intensification). The cost of this conversion of lands to agriculture often falls on the environment, with peatlands and forested lands being converted to large-scale …

More Concerns About Atmospheric Methane Removal Efforts, Joshua Luczak

Research Collection College of Integrative Studies

The National Oceanic and Atmospheric Administration reported record-high global atmospheric carbon dioxide levels (419.3 ppm) in 2023, alongside atmospheric methane levels (1922.6 ppb) now over 160% above pre-industrial levels. The World Meteorological Organization predicts 2024 could surpass 2023 as the warmest year on record, with more frequent and severe extreme weather events. Meeting the Paris Climate goal of limiting global warming to well below 2°C—or ideally 1.5°C—above pre-industrial levels is becoming increasingly difficult. To address these challenges, efforts are expanding beyond reducing greenhouse gas emissions. While carbon dioxide removal (CDR) technologies have been the focus, attention is now turning to …

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 …

Mathematics-Ai Based Phylogenetic Analysis Of Influenza Virus Mutation Data, Emilee Walden

Mathematical Sciences Undergraduate Honors Theses

The influenza virus is one of the most common viral infections each year and can mutate rapidly. Viral mutations pose significant threats to public health by increasing infectivity and strengthening vaccine resistance. To track these evolving patterns, agencies like the CDC annually evaluate thousands of virus strains to understand viral mutagenesis and evolution in depth. Therefore, a computational method for analyzing high-dimensional, noisy virus data could aid in the rapid identification of antigens essential for an effective influenza vaccine for the upcoming season. Through the integration of genomic analysis, clustering, and dimensionality reduction methods, this study specifically aims to develop …

Rotation-Adaptive Point Cloud Domain Generalization Via Intricate Orientation Learning, Bangzhen Liu, Chenxi Zheng, Xuemiao Xu, Cheng Xu, Huaidong Zhang, Shengfeng He

Research Collection School Of Computing and Information Systems

The vulnerability of 3D point cloud analysis to unpredictable rotations poses an open yet challenging problem: orientation-aware 3D domain generalization. Cross-domain robustness and adaptability of 3D representations are crucial but not easily achieved through rotation augmentation. Motivated by the inherent advantages of intricate orientations in enhancing generalizability, we propose an innovative rotation-adaptive domain generalization framework for 3D point cloud analysis. Our approach aims to alleviate orientational shifts by leveraging intricate samples in an iterative learning process. Specifically, we identify the most challenging rotation for each point cloud and construct an intricate orientation set by optimizing intricate orientations. Subsequently, we employ …

Functional Consequences Of Lysine Acetylation Of Phosphofructokinase Isozymes, Xinyu Lin, Nour Fatema, Qinglei Gan, Chenguang Fan

Chemistry & Biochemistry Faculty Publications and Presentations

Phosphofructokinase (Pfk) catalyzes the phosphorylation of fructose 6-phosphate and is a key regulatory point in the glycolysis pathway. Multiple lysine residues in both Pfk isozymes, PfkA and PfkB, have been identified to be acetylated in Escherichia coli by proteomic studies, but no studies have been implemented to further characterize these acetylation events. To investigate the role of Pfk acetylation, the genetic code expansion strategy was used to generate homogeneously acetylated Pfk variants at target lysine sites that have been reported to be acetylated in nature. We found that acetylation of K309 of PfkA and K27 of PfkB decreased PfK enzyme …

Navigating The Challenges Of Coccidioides Surveillance: Insights From The Environment Of El Paso County, Texas, Tanzir Hossain

Open Access Theses & Dissertations

Coccidioidomycosis, or Valley fever, is a fungal infection resulting from the inhalation of spores from the Coccidioides species (C. immitis and C. posadasii), native to arid areas of the Western Hemisphere. Coccidioidomycosis presents considerable health hazards and can be fatal. It affects between 206,000 and 360,000 individuals annually, leading to 700 to 1,100 fatalities in the United States alone. In response to these issues, extensive research has concentrated on therapeutic goals for this infectious disease. Nonetheless, more limited research has focused on the environmental detection of its causative fungi, which is crucial for forecasting treatment needs and formulating preventive strategies. …

Investigation Of High-Frequency Electron Spin Dynamics In The Kagome-Lattice Ymn6sn6 Crystal, Lovia Ofori

Open Access Theses & Dissertations

Kagome magnetic crystals received a great deal of research attention in the recent past for their intriguing magnetic properties. Recently, YMn6Sn6 (Y166) has shown to exhibit several nontrivial magnetic phases (such as the Distorted Spiral (DS) phase, Transverse Conical Spiral (TCS) phase, Fan-like (FL) phase and the Forced-Ferromagnetic (FF) phase) and complex magnetic interactions. In this work, we employed very high-frequency electron paramagnetic resonance (VHF-EPR) spectroscopy to investigate the local microscopic magnetic interactions of Mn ions in the Kagome Crystal Y166 to better understand the new observed magnetic phases. Particularly, we studied the temperature-dependent EPR behavior at variable very-high microwave …

From Land To Lagoon: The Spatiotemporal Biogeochemical Dynamics Of Arctic Coastal Erosion In Elson Lagoon, Alaska, Sasha Victoria Peterson

Open Access Theses & Dissertations

TThe Arctic is warming rapidly, driving widespread environmental change across coastal landscapes, including permafrost thaw, shoreline erosion, and shifts in sediment and carbon dynamics, pose growing challenges for predicting carbon cycling and climate feedbacks. This dissertation investigates the spatiotemporal variability of erosion, decomposition, and nearshore turbidity in Elson Lagoon, Alaska (1955–2023), to better understand how carbon, nitrogen, and sediment are mobilized, transformed, and potentially emitted as greenhouse gases in Arctic coastal systems. Chapter 2 presents a high-resolution analysis of shoreline change and erosion-driven material fluxes spanning nearly seven decades. Drawing on 795 soil data points, airborne LiDAR, and five shoreline …

Kernel Density Estimation And Convolution, Nicholas Tenkorang

Open Access Theses & Dissertations

Kernel Density Estimation (KDE) is a widely used technique for estimating the probability density function of a random variable. In this study, we revisit KDE through the lens of convolution and extend this perspective to special cases such as positive, bounded and heavy tailed random variables. Building on this foundation, we propose a novel simulation-based density estimation method that generates new data by adding noise to observed values and then smoothing the resulting histogram using splines. A minor adjustment to natural cubic splines is required to ensure nonnegative estimates. The noise is drawn from a class of bounded polynomial kernel …

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 …

Structure Disorder And Magnetic Behavior Of An Olivine-Type Cathode Material, Hamida Hassan, Madalynn Marshall

Symposium of Student Scholars

Our research investigates the structure disorder and magnetic behavior of Li(Mn,Fe)PO₄, an olivine-type material relevant for lithium-ion battery applications. Using single-crystal neutron diffraction at Oak Ridge National Laboratory, we precisely determined Mn and Fe occupancy, revealing a 56% Fe and 44% Mn distribution at the atomic 4c site within the Pnma space group. Additionally, we observed significant lithium site vacancies (78% occupied), influencing the material's electrochemical and magnetic properties. The varying Mn/Fe ratio affected spin reorientation transitions, shifting from antiferromagnetic alignment along the a-axis to the b-axis. Our findings provide crucial insights for optimizing olivine-based cathodes, enhancing energy …

Computational Study Of The Proton Transfer In The H7o3+ Cluster, Anna James, Martina Kaledin

Symposium of Student Scholars

Proton transfer (PT) from one molecule to another is among the most studied phenomena in chemistry. PT requires the bond cleavage and the formation of a new one, AH⁺ + B -> A+ BH⁺. In protonated water clusters, such a process consists of the interconversion of hydrogen bonds. Experimentally, such a process can be observed as a significant increase of a dipole moment. However, other vibrational transitions often occur with small changes in the dipole moment while large changes in polarizability. In this work, we study the PT process in a protonated water cluster, H₇O …

Properties Of Eigenvalues Of The Fractal Laplacian, Eric Stachura, Andrew Chincea

Symposium of Student Scholars

We investigate the properties of the eigenvalues of the fractal Laplacian. We begin by defining the fractal Laplacian operator in one dimension and formulate the corresponding Dirichlet eigenvalue problem. Analytical solutions are obtained for specific fractal parameters, and computational results illustrate the structure of eigenvalues and their associated eigenfunctions. We extend our analysis to two dimensions using separation of variables. Our findings contribute to a deeper understanding of how fractal geometry affects the spectral characteristics of differential operators.

Predicting Healthcare Service Quality Based On A Kalman-Optimized Bi-Lstm-Inspired Deep Learning Model, Mohammed K. Al-Khafaji, Eman S. Al-Shamery

Karbala International Journal of Modern Science

Health is one of the most important aspects of human well-being, and access to high-quality healthcare is essential for a good quality of life. Providing top-level health services at all times is crucial. However, the research in healthcare poses significant challenges due to the diversity and variations of medical practices across different hospitals. This paper aims to tackle the challenge of data missing and scattering during data collection. Then, the quality of services (QoS) offered by healthcare facilities will be analyzed and predicted from the patient's perspective. The model begins preprocessing data by data cleaning, handling missing values, and scattering …

Artificial Intelligence In Orthopedic Medical Education: A Comprehensive Review Of Emerging Technologies And Their Applications, Kyle Sporn, Rahul Kumar, Phani Paladugu, Tejas Sekhar, Swapna Vaja, Tamer Hage, Ethan Waisberg, Chirag Gowda, Ram Jagadeesan, Nasif Zaman, Alireza Tavakkoli

SKMC Student Presentations and Publications

Integrating artificial intelligence (AI) and mixed reality (MR) into orthopedic education has transformed learning. This review examines AI-powered platforms like Microsoft HoloLens, Apple Vision Pro, and HTC Vive Pro, which enhance anatomical visualization, surgical simulation, and clinical decision-making. These technologies improve the spatial understanding of musculoskeletal structures, refine procedural skills with haptic feedback, and personalize learning through AI-driven adaptive algorithms. Generative AI tools like ChatGPT further support knowledge retention and provide evidence-based insights on orthopedic topics. AI-enabled platforms and generative AI tools help address challenges in standardizing orthopedic education. However, we still face many barriers that relate to standardizing data, …

Analysis And Derivation Of The Compressible Euler System With Nonlinear Velocity Alignment: An Investigation Into Collective Behavior, Mckenzie Meredith Black

Theses and Dissertations

Collective behavior refers to the observable patterns, actions, or movements that emerge within a group of entities, such as individuals, animals, or particles, when they interact with each other. In this study, we concentrate on the pressureless compressible Euler system, expanding it to incorporate a family of nonlinear velocity alignment. This extension represents a nonlinear iteration of the Euler-alignment system within collective dynamics, revealing intriguing asymptotic emergent phenomena such as alignment and flocking. Our investigation explores different types of nonlinearity and nonlocal communication protocols, unveiling a diverse spectrum of asymptotic behaviors within the system.

In focusing on the derivation, we …

Understanding The Through-Space Intermolecular Interactions Of Isothiourea Catalysts In Acylation/Silylation Reactions Of Secondary Alcohols, Ziyuan Gong

Theses and Dissertations

Through space interactions, including cation-π interaction, lone pair-πinteraction, steric hinderance etc. play a central role in organocatalytic reaction. They can control the reactivity or the selectivity of an organic reaction. Previous work in our group has already shown that the chiral isothiourea compounds can catalyze the acylation as well as silylation reaction of secondary alcohol with the possible cation-πinteraction between the catalyst and substrate. However, there is lack of study to understand how the delocalization of the positive charge would affect the reaction rate and whether some unexpected inter- or intramolecular interaction could help stabilize …

Who Am I As A Learner? The Effects Of A Self-Regulated Learning Intervention On Ninth Graders’ Academic Self-Concepts And Intrinsic Motivation, Kaitlyn Elizabeth Bailey

Theses and Dissertations

The transition from middle school to high school is a notoriously difficult one, and a student’s success in ninth grade is typically a predictor of future success in high school. Unfortunately, many ninth graders struggle to engage in school. Despite their capability to complete the work, these students appear unmotivated and simply disengaged from school. In this action research case study, three students had the opportunity to share their education stories and the experiences that have shaped their academic self-concepts. These students also participated in a self-regulated learning intervention to determine if students’ feelings of autonomy, competence, and relatedness could …

Developing Predictive Mathematical Model For Optimizing Coating Weight Variation In Galvalume Production: A Case Study Of A Metal Industry, Victoria Mahabi

Tanzania Journal of Engineering and Technology (TJET)

Variations in coating weight for galvanized steel sheets can result in notable differences between batches. Such variations may cause various issues, such as diminished corrosion resistance, lower mechanical strength, and visual defects, which can ultimately drive-up costs, lead to customer dissatisfaction, and pose safety risks. Even with attempts to manage elements like air knife pressure and line speed, coating weight inconsistencies remain challenging. The research focuses on developing a predictive mathematical model designed to optimize variations in coating weight during Galvalume production. The critical parameters influencing coating weight variation were identified and analysed using a systematic literature review, primary data …

Assessing Relationships Between Water Quality, Precipitation, Land Cover And Stormwater Conveyance Type Across A Range Of Sub-Watersheds In The Southeastern Coastal Zone, Kevencia Sabine Gabriel Faton

Theses and Dissertations

The expansion of urban land use/cover along the coast may degrade water quality by introducing a plethora of pollutants and pathogens that negatively impact human and ecological health. It is hypothesized that anthropogenic contaminants associated with stormwater runoff increase with increasing urban density and vary with the timing and magnitude of rainfall. In this study, we examined land use/cover change and relationships between Escherichia coli (E. coli), turbidity, nutrients, and the timing and magnitude of rainfall in two different types of stormwater conveyances (ditches and ponds) within Murrells Inlet, SC during the summer of 2023. Our results indicate …

The Design And Optimization Of Optical Systems For The Detection And Characterization Of Phytoplankton, Caitlyn M. English

Theses and Dissertations

Phytoplankton are among the smallest organisms found in marine and freshwater ecosystems. Despite their small size, phytoplankton play a vital role in sustaining life on Earth as primary producers. Through oxygenic photosynthesis phytoplankton are also responsible for large scale carbon fixation and oxygen production. The distribution of phytoplankton in a given water resource can exhibit a high degree of variability across time and space, and this is in large part due to their varying sensitivities to environmental conditions such as resource availability and grazing by predator organisms. As such, phytoplankton community structure is widely used as an investigative tool for …

Building A Framework For Analyzing Non-Linear And Multidimensional Kinetics, Mainak Dhar

Theses and Dissertations

Many materials exhibit multiple rates of molecular relaxation due to structural complexities. Standard linear and one-dimensional kinetic cannot extract all the necessary dynamic information about these systems. This dissertation contributes to an overarching scheme to develop new non-linear and multidimensional kinetic experiments to obtain this information. The studies span computation and experiments, picosecond to second timescales, and both single-molecule and pulsed-laser kinetics

Single-molecule kinetics experiments yield time series that contain information about unique structural and dynamic properties of materials. However, these time series are noisy, and data analysis is challenging. Parametric methods are computationally intensive and require strong, unverifiable assumptions …

Dual Colorimetric And Fluorometric Detection Of Hydrogen Peroxide In Aqueous Samples, Nathan F. Surles, Kaitlin A. Edwards

ATU Scholars Symposium

In this project, a simple, inexpensive colorimetric and fluorometric method for determining hydrogen peroxide in aqueous samples is described. In this method, aryl boronic acid is de-protected to produce a red dye that absorbs and emits in the red/near infrared region of the electromagnetic spectrum. Upon deprotection by the hydrogen peroxide, an intramolecular charge transfer occurs between a strong phenolate donor and a TCF acceptor to produce the strong absorption and bright fluorescence. This allows naked eye detection of hydrogen peroxide within seconds in water under physiological conditions. The detection limit is impressive and falls in the sub-micromolar (µM) range. …