Physical Sciences and Mathematics Commons^™

Novel Pathways To Tailor Charge And Spin In Materials And Investigating The Impact On Sensing And Electrochemical Energy Applications, Aruna Narayanan Nair

Open Access Theses & Dissertations

Catalysis is integral to our daily lives, as it streamlines and accelerates numerous chemical reactions essential for producing various materials, fuels, and chemicals. With the rising demand for clean, sustainable energy sources, optimizing catalytic materials and processes becomes increasingly vital. In the realm of renewable energy production, catalysis is crucial for efficiently converting energy from sustainable resources, such as solar, wind, and biomass, into chemical energy stored in fuels or directly into electrical energy.The electronic charge distribution in materials significantly influences their physical and chemical properties, facilitating the development of advanced electronic, optoelectronic, sensing, and energy conversion devices. Since catalysis …

Differentiating Biotic Vs. Abiotic Co2 In The Formation Of Pedogenic Carbonate In Agriculture And Natural Dryland Soils, Valeria Isabel Molina

Open Access Theses & Dissertations

Drylands, characterized by low and sporadic precipitation, require irrigation for crop growth. However, irrigation practices can lead to salt accumulation in soil due to high evaporation rates and reduced leaching. In addition to loading salts to soil, irrigation promotes the accumulation of secondary calcite. In natural systems, the formation of pedogenic carbonate (secondary calcite, CaCO3) is critical, impacting the soil properties hydrologically and biogeochemically, and modifying the global carbon cycle over geological time, albeit at a lower rate. In agricultural sites, irrigation water supplies HCO3- and Ca2+, accelerating the rates of CaCO3 formation and releasing abiotic CO2. This study investigated …

Field Observations And Stable Isotope Analysis Of Alunite At The Sulphur Bank Mercury Mine, Clear Lake, California, David Edward Muller

Open Access Theses & Dissertations

The Sulphur Bank mercury mine is a historic mine located in Lake County, California, first exploited in the 1860s. Underground mining of mercury took place from 1873 to 1906 and open-pit mining of mercury was done from 1927 to 1957. The U.S. Environmental Protection Agency listed the Sulphur Bank mine and the adjacent Clear Lake as a Superfund site in 1990 due to mercury contamination at the mine site and in the sediment and food web of Clear Lake. Previous studies have described the vein material mineralogy and wall-rock alteration at Sulphur Bank as well as the composition of water …

Incorporating Community Science In Improving Environmental Data Quality Through Model Based Reasoning Techniques, John Gilbert Olgin

Open Access Theses & Dissertations

This dissertation will address the questions: In what ways can MBR theory be applied to designtraining that will improve the capacity of Citizen scientists to collect and analyze high quality scientific data? To what degree does this training impact their ability to formulate complex understandings of environmental problems in their Citizen? The project will be comprised of three research objectives focused in three sections, carried out with NASAâ??s GLOBE Observer Citizen Science Program:

Section 1: An analysis of existing GLOBE data will be conducted, identifying whereerrors in data collection originate. At least three principal errors will be selected from this …

Addressing The Challenged Of Dcop Based Decision-Making Algorithms In Modern Power Systems, Luis Daniel Ramirez Burgueno

Open Access Theses & Dissertations

Natural disasters have been determined as the leading cause of power outages, causing not only huge economic losses, but also the interruption of crucial welfare activities and the arise of security concerns. Because of the later, decision-making considering grid modernization, power system economics, and system resiliency has been a crucial theme in power systemsâ?? research. The need to better withstand catastrophic events and reducing the dependency of bulky generating units has propelled the development and better management of behind-the-meter generation or distributed energy resources (DERs). DERs can assist in the grid in different manners, not only by meeting energy demand …

Developing And Applying Computational Methods On Biomolecules, Shengjie Sun

Open Access Theses & Dissertations

Computational biophysics is an interdisciplinary subject that uses numerical algorithms to study the physical principles underlying biological phenomena and processes. Electrostatic interactions play an important role in computational molecular biophysics and their potential impact on disease mechanisms. At distances larger than several Angstroms, electrostatic interactions dominate all other forces, while the alteration of short-range electrostatic pairwise interactions can also have significant effects. The dual nature of electrostatic interactions, being dominant at long-range and specific at short-range, underscores their profound implications for wild-type structure and function. Any disruption of the complex electrostatic network of interactions may abolish wild-type functionality and could …

Seismicity, Tectonics, And Site Response In The Nepalese Himalayas, Mohan Pant

Open Access Theses & Dissertations

The continental collision between the Indian plate and the Eurasian plate at ~55 Ma (Molnar and Tapponnier, 1975) has uplifted the northern part of Nepal forming the Himalayas. This convergence of India and Eurasia produced intra-upper crustal shear zones and thickened the crust to its present thickness of 70 km (Molnar, 1988; Zhao et al, 1993). The convergence rate across the Nepalese Himalayas is estimated between 17-21 mm/yr. (Ader et al., 2012). Because of this convergence, the region has experienced large, devastating earthquakes, including the 1934 Mw~8.2 Nepal-Bihar earthquake (Dunn et al., 1939) and two recent earthquakes on April 25, …

Flexible Models For The Estimation Of Treatment Effect, Habeeb Abolaji Bashir

Open Access Theses & Dissertations

Estimation of treatment effect is an important problem which is well studied in the literature. While the regression models are one of the most commonly used techniques for the estimation of treatment effect, they are prone to model misspecification. To minimize the model misspecification bias, flexible nonparametric models are introduced for the estimation. Continuing this line of research, we propose two flexible nonparametric models that allow the treatment effect to vary across different levels of covariates. We provide estimation algorithms for both these models. Using simulations and data analysis, we illustrate the usefulness of the proposed methods.

Multi-Objective Optimization Framework For Electrified Vehicle Penetration Based On Life Cycle Assessment And Life Cycle Cost., Eva Alondra Diaz Lozano

Open Access Theses & Dissertations

This research proposed a novel framework for creating optimal transportation scenarios that consider multiple objectives such as minimum greenhouse gas emissions, air pollutant levels, and cost of ownership. The thesis approach is a multi-objective evolutionary algorithm coupled with the AFEET tool, allowing us to efficiently explore the complex trade-offs between these objectives and identify a diverse set of optimal solutions. Through several case studies and a design of experiments, this demonstrates the effectiveness and practicality in different scenarios. This approach has significant implications for policymakers and industry professionals seeking to make sustainable and cost-effective decisions in the transportation sector.

Generalized Additive Model Using Marginal Integration Estimation Techniques With Interactions, Tahiru Mahama

Open Access Theses & Dissertations

Marginal Integration (MI) is a statistical method that is extensively employed to estimatecomponent functions of the nonparametric additive models. The shortcoming of the purely additive model is that interaction between predictor variables is often ignored, and it may produce poor performance in some real applications. As a result, this research considers the second-order interactions in the regression models. The primary objective is to use marginal integration techniques to estimate the nonparametric additive functions. We compare this model with other models/estimators such as the Generalized Additive Model (GAM), Generalized Additive Model with Selection (GAMSEL), Robust Marginal Integration (RMI), Ordinary Least Squares …

Linking Decomposition Reactions In Arctic Soils To Microbial Enzyme Production, Jane Karen Martinez

Open Access Theses & Dissertations

Microbial processes such as soil enzyme production are a major driver of decomposition and a current topic of interest in arctic soils due to the effects of climate warming. Despite the advances in understanding soil enzymes, there are still knowledge gaps regarding the role of enzymes in decomposition. In this dissertation, I addressed three of those gaps in the following chapters: (Ch.2) to explore the location of enzymes within the soil matrix, (Ch.3) to identify peptides matched to soil enzymes produced by microorganisms for organic matter decomposition, and (Ch.4) understand the longevity of enzymes in the soil after microbial production. …

Characterizing Spatial Variability In Soil Co2 Fluxes In The Chihuahuan Desert Using Geostatistical Techniques, Viridiana Orona

Open Access Theses & Dissertations

Spatial variability in soil CO2 efflux across landscapes is an important feature of the â??Critical Zoneâ?? within dryland ecosystems. In dryland critical zones, resources are often distributed in patches or resource islands. Although this is particularly true in natural settings, the significance of spatial variability in CO2 efflux and its patterns also extends to dryland agriculture. In both irrigated and unirrigated systems, human management practices can significantly impact both organic and inorganic carbon cycling processes, highlighting the importance of studying CO2 efflux in these systems. We examined the spatial patterns of soil CO2 efflux and quantified the magnitude and scale …

The Intersection Of Urban Heat Islands And The Cdc Social Vulnerability Index In Two Border Cities, Ileana Morales

Open Access Theses & Dissertations

No abstract provided.

Temporal Trends In Dryland Soil Carbon Fluxes In Response To Artificial And Natural Pulsed Moisture Events, Briana Alyce Salcido

Open Access Theses & Dissertations

Critical zone processes in drylands play a crucial role in the global carbon cycle, and one of the most important processes is soil CO2 efflux at the interface between soils and the atmosphere, which represents a main pathway for loss of carbon. Predicting the carbon dynamics at this interface is challenging due to the complexity of belowground processes, which include both biotic (soil respiration) and abiotic (calcite precipitation) production of CO2, as well as transport processes that include both diffusive and advective components. In this study, we aimed to investigate the contribution of soil air displacement to soil CO2 efflux …

A Framework To Build Secure Microservice Architecture, Wai Yan Elsa Tai Ramirez

Open Access Theses & Dissertations

Microservice architecture has become a popular architecture style in recent years. According to a series of surveys conducted by IBM Market Development & amp; Insights in 2021, microservices are heavily used in many industries worldwide. With an increase in the adoption of microservice architecture in the development of applications, such as Netflix, Amazon, Uber, Ebay, Twitter, DoorDash, Capital One, and Monzo, and the increase in security breaches in microservice based systems (e.g., the DoorDash data breaches in 2019 and 2022, Twitter data breach in 2022, and compromises to Netflixâ??s infrastructure), there is a need to examine and understand security issues …

Modeling And Predicting Emerging Threats Using Disparate Data, Ismael Villanueva Miranda

Open Access Theses & Dissertations

Early detection is crucial to mitigate the impact of emerging threats. This work proposes four innovative frameworks that build machine learning and deterministic epidemiological models using multiple domain-specific datasets to detect the onset of emerging threats in two domains: infectious diseases and cybersecurity. Our models are designed to detect infectious disease outbreaks, model their spread, detect malware activity, and analyze the relationship between software/hardware weaknesses and attack techniques.

First, we present a novel framework to detect multiple infectious disease outbreaks by integrating standardized disease-specific domain knowledge and public search trend data. Our framework showed high performance in identifying infectious disease …

Spatially Adaptive Estimation Of Spectrum, Yi Xie

Open Access Theses & Dissertations

A time series may be analyzed either in the time or in the frequency domain. When working in the frequency domain, the main objective is to estimate the underlying spectrum. Various approaches have been proposed to this end, but most are based on smoothing the periodogram using a single smoothing parameter across all Fourier frequencies. Such a global smoothing parameter may result in a biased estimate. To improve the estimation, in this paper, we smooth the log periodogram by placing a dynamic shrinkage prior, such that varying degrees of smoothing may be applied to different regions of the Fourier frequencies, …

Detecting Complex Cyber Attacks Using Decoys With Online Reinforcement Learning, Marcus Gutierrez

Open Access Theses & Dissertations

Most vulnerabilities discovered in cybersecurity can be associated with their own singular piece of software. I investigate complex vulnerabilities, which may require multiple software to be present. These complex vulnerabilities represent 16.6% of all documented vulnerabilities and are more dangerous on average than their simple vulnerability counterparts. In addition to this, because they often require multiple pieces of software to be present, they are harder to identify overall as specific combinations are needed for the vulnerability to appear.

I consider the motivating scenario where an attacker is repeatedly deploying exploits that use complex vulnerabilities into an Airport Wi-Fi. The network …

Enhancing Basic Geology Skills With Artificial Intelligence: An Exploration Of Automated Reasoning In Field Geology, Perry Ivan Quinto Houser

Open Access Theses & Dissertations

This thesis explores the use of Artificial Intelligence, specifically semantics, ontologies, and reasoner techniques, to improve field geology mapping. The thesis focuses on two use cases: 1) identifying a geologic formation based on observed characteristics; and 2) predicting the geologic formation that might be expected next based upon known stratigraphic sequence. The results show that the ontology was able to correctly identify the geologic formation for the majority of rock descriptions, with higher search results for descriptions that provided more detail. Similarly, the units expected next were correctly given and if incorrect, would provide a flag to the field geologist …

Theoretical And Computational Aspects Of Robust Cluster Analysis For Multivariate And High-Dimensional Datasets, Andrews Tawiah Anum

Open Access Theses & Dissertations

Multivariate and high-dimensional datasets typically contain subgroups that may not be immediately apparent. To reveal these groups, cluster analysis is performed. Cluster analysis is an unsupervised machine learning technique commonly employed to partition a dataset into distinct categories referred to as clusters. The k-means algorithm is a prominent distance-based clustering method. Despite overwhelming popularity, the algorithm is not invariant under non-singular affine transformations and is not robust, i.e., can be unduly influenced by outliers. To address these deficiencies, we propose an alternative model-based clustering procedure by minimizing a “trimmed” variant of the negative log-likelihood function. We develop a “concentration step”, …

Performance Classification Of Ornstein-Uhlenbeck-Type Models Using Fractal Analysis Of Time Series Data., Peter Kwadwo Asante

Open Access Theses & Dissertations

This dissertation aims to assess the performance of Ornstein-Uhlenbeck-type models by examining the fractal characteristics of time series data from various sources, including finance, volcanic and earthquake events, US COVID-19 reported cases and deaths, and two simulated time series with differing properties. The time series data is categorized as either a Gaussian or a Lévy process (Lévy walk or Lévy flight) by using three scaling methods: Rescaled range analysis, Detrended fluctuation analysis, and Diffusion entropy analysis. The outcomes of this analysis indicate that the financial indices are classified as Lévy walks, while the volcanic, earthquake, and COVID-19 data are classified …

Development Of Multi-Configuration Methods On Density Functional Theory Orbitals And Application On The Study Of Dimers, Jose Gustavo Bravo Flores

Open Access Theses & Dissertations

The configuration interaction (CI) methods is an exact method to solve the non relativistic Schrodinger equation, describing the wave function as a linear combination of Slater determinants. Because the computation time grows factorially as the number of electrons, CI is mostly used for relatively small systems. Density functional theory (DFT) rose as one of the most used methods for computational quantum chemistry in the last 30 years. DFT can describe a system's properties with the electron density, which only depends of of three coordinates. Due to its low computational costs it allows one to study bigger systems than CI, however …

Comparison Of Different Robust Methods In Linear Regression And Applications In Cardiovascular Data, Jagannath Das

Open Access Theses & Dissertations

Due to advanced technology and wide source of data collection, high-dimensional data is available in several fields, including healthcare, bioinformatics, medicine, epidemiology, economics, finance, sociology, and climatology. In those datasets, outliers are generally encountered due to technical errors, heterogeneous sources, or the effect of some confounding variables. As outliers are often difficult to detect in high-dimensional data, the standard approaches may fail to model such data and produce misleading information. In this thesis, we studied Huber and Tukey's M-estimators for linear regression that automatically down-weight outliers and provide a good fit. We also investigated two variable selection methods -- LASSO …

Analysis Of The Electrostatic Characteristics Of The Zika Virus Capsid Using Computational Methods, Cassandra Guadalupe Del Rio De Avila

Open Access Theses & Dissertations

Zika virus (ZIKV) is a flavivirus that is usually transmitted through the bite of infected mosquitoes. This virus can cause a variety of neurological disorders, the most common being Guillain-Barré syndrome in adults. Moreover, it is of great concern in pregnant women, since can cause deformities in the brain and other organs of newborns.Studying the structural characteristics of the virus during its mature and infectious phase can provide crucial information on the mechanisms by which it enters and replicates within host cells, as well as its evolution, transmission, and interaction with other living organisms. The symmetric pattern present in the …

Evaluating The Impact Of Climate Variability And Landcover Changes On Hydrologic Responses, Marisol Dominguez

Open Access Theses & Dissertations

Projected climate and land cover changes in the 21st century profoundly impact the functioning of the earth’s water cycle. Identifying the components that contribute to the persistence and resilience of watersheds in light of climate change constitutes a research priority of global relevance, and will enable detect the areas most sensitive to climate variability and landcover changes. Global vulnerability of ecosystem services, particularly water service provision, needs to be urgently and continually assessed, given the unceasing human and climate-induced changes in land cover conditions worldwide. Given the increasing rate of extreme weather events, we present three interrelated research studies evaluating …

Development Of A Cost-Constrained Intelligent Prosthetic Knee With Real-Time Machine Learning, Predictive Stumble Control, Lucas Jonathan Galey

Open Access Theses & Dissertations

The field of biomechatronics is evolving quickly with advances in computer science, biology, and electrical and mechanical engineering. Coupled with increased interests in machine learning (ML) across all industry sectors, there are opportunities to leverage advanced analytics in uniquely complex problems. This study aimed to deploy real-time ML predictions in a novel microprocessor-controlled prosthetic knee (MPK) device capable of identifying and responding to stumble-events to reduce amputee fall prevalence. Innately, stumbling is a chaotic event. Current MPKs operate by detecting gait characteristics and reacting to preprogrammed states. While these systems are beneficial in significant ways, such as energy expenditure and …

Thermal Behavior Of Plain And Fiber-Reinforced Rigid Concrete Airfield Runways, Arash Karimi Pour

Open Access Theses & Dissertations

The environmental condition and temperature gradient are important factors resulting in concrete airfield runways cracking during the time. Rigid concrete airfield runways experience different thermal gradients during the day and night due to changes in air temperature. Curling and thermal expansion stresses are the main consequences resulting in various types of cracking over the surface and thickness of concrete airfield runways and increasing maintenance costs. The curvature of concrete slabs increases with an increase in the temperature gradient which is amplified when runways open to traffic. Additionally, the combination of the curling and shrinkage stresses, in rare circumstances, can be …

Geological Mapping Of Ferric And Ferrous Irons In The Apache Hills, New Mexico: Applying Landsat 8 (Oli), Spectrometry, And Geographic Information System (Gis) Methods, Sergio Gerardo Macias

Open Access Theses & Dissertations

Mineral discoveries are typically tangible on surface studies. Previous research describes mineral deposits of ferric and ferrous irons in the lithology, structures, and alluvial fans in the Apache Hills in southwest New Mexico. The research for this thesis combines and models four methods for validating and mapping the presence of Ferric and Ferrous Irons developed in weathered zones above mineral deposits. A beneficial steppingstone before exploration and discovery begins with extensive research. This study began with data acquisition and reviewing previous research and was essential for the project methods. The study combines four techniques: spectral geology (e.g., remote sensing and …

Isotopic Insights Into Water Of Condensation, Cross-Formation Water Flow, And Natural Hydrocarbon Migration In Sedimentary Basins, Lisa J. Molofsky

Open Access Theses & Dissertations

This dissertation applies geochemical tools to track the movement, transformation, and behavior of water and gases in hydrocarbon-bearing sedimentary basins. During petroleum exploration and production, hydrocarbons are generated at the surface along with other fluids naturally present in the formation, such as formation water. In addition, where hydraulic fracturing is used to stimulate shale gas and oil production, a percentage of the injected fracturing fluid also returns to the surface. Understanding the origin and movement of these water sources, as well as targeted and non-targeted hydrocarbon gases is critical to evaluating reservoir performance and properly managing fluids at the surface. …

Catalytic Water Photolysis For Generating Renewable Hydrogen Fuel, Dr. Niveditha Nanda

Open Access Theses & Dissertations

Modern advances have enabled rapid industrialization and urbanization. However, the consequences of global modernization have included significant pollution to the air and water resources. Consequently, many changes to energy use must come to address and mitigate damages to our future. Solar energy derived hydrogen gas is a clean, renewable fuel that does not produce carbon dioxide or other pollutants. My research investigates the use of heterogeneous photocatalysis, by focusing on solar photochemical energy conversion, which is the making of hydrogen from water using sunlight. The production of clean, renewable hydrogen fuel will enable the utilization of low-cost, pollution-free energy resources …