Physical Sciences and Mathematics Commons^™

Water Sufficiency For Organismal Function In Dryland Critical Zones, Lindsey Dacey

Open Access Theses & Dissertations

Water availability is crucial for organismal survival and growth in dryland environments, affecting both ecological interactions and carbon dynamics. The goal of this thesis is to develop soil water release curves (SWRCs) that link soil water potentials (Ψ) to soil water content (θ). Using the SWRCs, temporal soil water sufficiency curves are developed, which quantify the amount of time that dryland critical zones have enough water to sustain the physiology of organisms. These curves allow for effectively indicating water availability across different species, coverage types, and soil conditions, enhancing our understanding of water dynamics in drylands and contributing important parameters …

Produced Water: Characterization And Treatment, Ramon Antonio Sanchez Rosario

Open Access Theses & Dissertations

In recent years, environmental concerns have urged companies in the energy sector to modify their industrial activities to facilitate greater environmental stewardship. For example, the practice of unconventional oil and gas extraction has drawn the ire of regulators and various environmental groups due to its reliance on millions of barrels of fresh water for hydraulic fracturing well stimulation, which is generally withdrawn from natural sources and public water supplies. Additionally, this process generates two substantial waste streams, which are collectively characterized as flowback and produced water. Whereas flowback water is comprised of various chemical additives that are used during hydraulic …

Investigating Changes In Surface Water Chemistry Across The Llano Uplift And The Balcones Fault Zone In Central Texas Using Strontium And Uranium Isotopes, Hao Tuan Pham

Open Access Theses & Dissertations

The landscape of central Texas is shaped by over one billion years of Earth's history. An array of lithology lies within central Texas along with two large geological structures. The Llano Uplift, characterized by Proterozoic metamorphic and igneous rocks dating back to 1.37 billion years ago, is encircled by Paleozoic and Mesozoic sedimentary rocks. To the southeast of the Llano Uplift lies the Balcones Fault Zone (BFZ), an extensional structural system of mostly normal faults that delineates the transition between Paleozoic-Mesozoic sedimentary rocks and Cenozoic sedimentary cover, which are influential to the regional hydrogeology. This study investigates the hydrogeological dynamics …

Automated Composition Of Multivariable Scientific Workflows Considering Scientific Assumptions, Raul Alejandro Vargas Acosta

Open Access Theses & Dissertations

Many ground-breaking scientific experiments require the execution of multiple complex scientific computations. Thus, scientific workflows (i.e., a sequence of scientific computations) have received significant attention, more specifically, the automated composition of scientific workflows. Scientific workflows that repurpose data may have unique scientific assumptions that need to be considered when composing a workflow. Workflow composition tools have enabled a wider range of stakeholders (e.g., policymakers, the general public, and researchers) to create and execute workflows; however, domain expertise is still required for these tasks. The overarching goal of this work is to further improve the automatic composition of scientific workflows by …

Analyzing The Impact Of Oil And Gas-Contaminated Fluids On Soil In Eddy And Lea Counties Using Sequential Extraction, Mary Adu-Gyamfi

Open Access Theses & Dissertations

The study investigates the impacts of oil and gas-contaminated fluids on soil within the context of Eddy and Lea Counties in New Mexico, the United States. The increase in oil and gas operations has led to enormous wastewater production that is handled, stored, and transported, leading to thousands of spills yearly. The continuous and accidental release of this wastewater poses several risks to the environment due to its high levels of hazardous pollutants. Several studies were conducted on how to reduce the contaminants; however, the impact caused on the environment and the fate of the spilled fluids is unclear due …

Resource Scarcity Caused By Environmental Changes: Driving Factor In Terrorism Attacks In Afghanistan, Pakistan, Syria, Amaris Bustamante

Open Access Theses & Dissertations

Climate change, resource scarcity, and terrorist attacks are ever-growing crises that disproportionately impact different states. They are crises that can impact the stability and resilience of humanity in the following decades if they are not addressed and mitigated. This study addresses the impact of resource scarcity caused by climate change that can then serve as a driving force in terrorist attacks in climate-sensitive and conflict-prone states. The objective of this mixed-methods study is to identify the correlation between climate changes that lead to resource scarcity such as rainfall and surface temperatures with terrorist attacks when taking into consideration other demographic, …

Promoting Social Sustainability: Implementing A Dynamic Stem Driven Framework To Empower Underrepresented Communities In West Texas Schools, Raquel Haggerty

Open Access Theses & Dissertations

This dissertation explores how environmental engineering can utilize STEM education as a strategic tool, enhancing social sustainability and thereby empowering underserved Hispanic communities in West Texas. Responding to significant educational and resource disparities, this research introduces an innovative interdisciplinary framework that combines instruction-initiated resource activation (I2RA), culturally attuned parent engagement (CAPE), and community- centered STEM education (CCSE). This approach uniquely addresses the challenges faced by these communities, integrating environmental solutions with educational advancements to forge a path toward equitable STEM access and achievement.

Additionally, the "Elevate and Empower" case study exemplifies the practical application of this comprehensive framework, demonstrating its …

Assessing Urban Tree Coverage Along The U.S.-Mexico Border: A Gis Analysis Of Paso Del Norte, Melanie Escobar

Open Access Theses & Dissertations

In recent years, researchers have extensively studied the spatial distribution of social demographics and urban tree canopy (UTC) in urban cities, but very few, to this date, address U.S.-Mexico border cities. To date, there is no research that assesses the distribution of urban tree canopy (UTC) in the city of El Paso, Texas, and Ciudad Juarez, Chihuahua, along the U.S.- Mexico border. Leveraging advanced mapping techniques and GIS tools, the study performs comparisons between countries (Juárez vs. El Paso urbanized areas and intra-country (within each country). It compares land cover classifications, assesses variations in UTC distribution across census tracts and …

Dispersal And Population Structure Of Euchlanis Chihuahuaensis Via Anemochory In The Chihuahuan Desert, Tristan Chavez-Poeschel

Open Access Theses & Dissertations

Desert ecosystems present challenges for aquatic organisms as habitats are fragmented, both in space and time; however, diapausing stages of rotifers can travel hundreds of kilometers during wind events. I used the rotifer Euchlanis chihuahuaensis as a model species to investigate the influence of wind dispersal on gene flow and population genetics in Chihuahuan Desert populations. I hypothesized that anemochory facilitates gene flow from source populations in the Northern Chihuahuan Desert in Mexico and the western United States to habitats in the Trans-Pecos region via delineated wind corridors. To test this hypothesis, the genetic diversity of populations from both inside …

Local Map Of The Interstellar Fuv Field, David Lomeli

Open Access Theses & Dissertations

The strength of the far-ultraviolet field is an important parameter in determining the chemistry that takes place in star-forming regions. FUV radiation is produced by bright stars in the galaxy and absorbed by interstellar dust. By using newly available maps of the dust distribution, in conjunction with catalogs of stellar positions and spectra, we created a local map of the FUV field ranging from 6-13.6 eV. We find a value of 6.57*10^-14 erg/cm^3 at the location of the Sun. This value, alongside its spectra, follow previous measurements and estimates of the FUV field at the Sun. We further study the …

Computational Study Of Fluorescent Molecular Probes For The Early Detection Of Alzheimer's Disease, Gabriela Elizabeth Molina Aguirre

Open Access Theses & Dissertations

Alzheimer's disease is a debilitating brain disorder that affects memory, thinking, and behavior. It is the most prevalent form of dementia and the seventh leading cause of death in the United States. As, researchers have identified biomarkers that can indicate the presence of the disease many years before the first symptoms appear, so there is an opportunity for early detection and treatment follow-ups, which could significantly improve the quality of life for those affected by this disease.This dissertation investigates the relationship between molecular structure and optical properties of donor-bridge-acceptor (DBA) fluorescent molecular probes designed for detecting Amyloid-β and p-Tau protein …

Modeling The Spatiotemporal Variations Of The Magnetic Field In Active Regions On The Sun Using Deep Neural Networks, Godwill Asare Mensah Mensah

Open Access Theses & Dissertations

Solar active regions are areas on the Sun's surface that have especially strong magnetic fields. Active regions are usually linked to a number of phenomena that can have serious detrimental consequences on technology and, in turn, human life. Examples of these phenomena include solar flares and coronal mass ejections, or CMEs. The precise predictionof solar flares and coronal mass ejections is still an open problem since the fundamental processes underpinning the formation and development of active regions are still not well understood. One key area of research at the intersection of solar physics and artificial intelligence is deriving insights from …

Assessing Nordihydroguaiaretic Acid Properties And Its Potential Therapeutic Effect For Glioblastoma, Jose Arturo Guerrero

Open Access Theses & Dissertations

This study employs a combination of theoretical and experimental analysis to spectroscopically investigate the biomechanistic structure relationship and therapeutic effects of the Nordihydroguaiaretic Acid (NDGA) chemical derived from the Larrea Tridentata plant. These relationships are crucial for understanding NDGA's efficacy in disease prevention, treatment, and potential toxicological effects. While the medicinal and antiviral properties of the NDGA have been studied extensively, there remains a gap in optically identifying and reporting its structural changes. The current research successfully reveals evident trends in NDGA's vibrational signatures, particularly highlighting the absence of the Raman feature at 780 〖cm〗^(-1) as indicative of a fully …

Combining Green Analytical Methods And Machine Learning To Develop Urinary Fatty Acid Models For Cancer Detection, Elizabeth Noriega Landa

Open Access Theses & Dissertations

This study aimed to explore fatty acids (FAs) as non-invasive biomarkers for prostate cancer (PCa) detection and prognosis, and their potential applications in other cancers. The objectives of this study were: 1) Develop a non-invasive urinary FAs-based model for diagnosing PCa; 2) Develop a FAs-based liquid biopsy model for non-invasive monitoring of PCa progression; 3) Investigate FAs composition in periprostatic adipose tissue (PPAT) collected from PCa positive patients; 4) Investigate the potential of urinary FAs biomarkers for diagnosing clear cell renal cell carcinoma (ccRCC) and ovarian cancer (OC).For the PCa diagnostic model, urine samples from 334 biopsy-confirmed PCa-positive and 232 …

Earth Abundant Catalyst For Evironmental Sustainability Applications, Javier Hernandez

Open Access Theses & Dissertations

The development of experimental methodologies for synthesizing a diverse range of metallic and metal oxide nanoparticles tailored for sustainable water treatment applications was investigated. These nanoparticles are prepared using environmentally friendly and scalable synthesis methods, underscoring their potential for large-scale production. Synthesized nanoparticles are harnessed for various processes, including catalysis and electrocatalysis, with a primary objective of degrading and removing organic pollutants from water. Key to this research is the encapsulation of nanoparticles within solid supports. Multiple methodologies are explored to engineer supports that ensure nanoparticle stabilization, monodispersion, and prevent unintended release into the environment. Two alternative approaches were evaluated …

Vr Circuit Simulation With Advanced Visualization For Enhancing Comprehension In Electrical Engineering, Elliott Wolbach

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

As technology advances, the field of electrical and computer engineering continuously demands innovative tools and methodologies to facilitate effective learning and comprehension of fundamental concepts. Through a comprehensive literature review, it was discovered that there was a gap in the current research on using VR technology to effectively visualize and comprehend non-observable electrical characteristics of electronic circuits. This thesis explores the integration of Virtual Reality (VR) technology and real-time electronic circuit simulation with enhanced visualization of non-observable concepts such as voltage distribution and current flow within these circuits. The primary objective is to develop an immersive educational platform that makes …

Key Benefits Of Small Group Instruction For Diverse Learners, Lydia Mcevoy

Master's Theses

Utilizing a mixed method approach this research study investigated the effects of small group instruction on the learning of diverse learners. Informed by a preliminary literature review that supports the use of small-group instruction, the researcher conducted a small-scale action research project to focus on three diverse learners in a 1st-grade classroom over four weeks. One of the findings of this project shows that small group instruction helps promote social and emotional skills as students feel more comfortable interacting with peers in a small group rather than in a whole group. Another finding indicates that students feel more encouraged by …

Multigprompt For Multi-Task Pre-Training And Prompting On Graphs, Xingtong Yu, Chang Zhou, Yuan Fang, Xinming Zhan

Research Collection School Of Computing and Information Systems

Graph Neural Networks (GNNs) have emerged as a mainstream technique for graph representation learning. However, their efficacy within an end-to-end supervised framework is significantly tied to the availability of task-specific labels. To mitigate labeling costs and enhance robustness in few-shot settings, pre-training on self-supervised tasks has emerged as a promising method, while prompting has been proposed to further narrow the objective gap between pretext and downstream tasks. Although there has been some initial exploration of prompt-based learning on graphs, they primarily leverage a single pretext task, resulting in a limited subset of general knowledge that could be learned from the …

Plug-And-Play Policy Planner For Large Language Model Powered Dialogue Agents, Yang Deng, Wenxuan Zhang, Wai Lam, See-Kiong Ng, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

Proactive dialogues serve as a practical yet challenging dialogue problem in the era of large language models (LLMs), where the dialogue policy planning is the key to improving the proactivity of LLMs. Most existing studies enable the dialogue policy planning of LLMs using various prompting schemes or iteratively enhance this capability in handling the given case with verbal AI feedback. However, these approaches are either bounded by the policy planning capability of the frozen LLMs or hard to be transferred to new cases. In this work, we introduce a new dialogue policy planning paradigm to strategize LLMs for proactive dialogue …

Grasper: A Generalist Pursuer For Pursuit-Evasion Problems, Pengdeng Li, Shuxin Li, Xinrun Wang, Jakub Cerny, Youzhi Zhang, Stephen Mcaleer, Hau Chan, Bo An

Research Collection School Of Computing and Information Systems

Pursuit-evasion games (PEGs) model interactions between a team of pursuers and an evader in graph-based environments such as urban street networks. Recent advancements have demonstrated the effectiveness of the pre-training and fine-tuning paradigm in Policy-Space Response Oracles (PSRO) to improve scalability in solving large-scale PEGs. However, these methods primarily focus on specific PEGs with fixed initial conditions that may vary substantially in real-world scenarios, which significantly hinders the applicability of the traditional methods. To address this issue, we introduce Grasper, a GeneRAlist purSuer for Pursuit-Evasion pRoblems, capable of efficiently generating pursuer policies tailored to specific PEGs. Our contributions are threefold: …

Unraveling The ‘Anomaly’ In Time Series Anomaly Detection: A Self-Supervised Tri-Domain Solution, Yuting Sun, Guansong Pang, Guanhua Ye, Tong Chen, Xia Hu, Hongzhi Yin

Research Collection School Of Computing and Information Systems

The ongoing challenges in time series anomaly detection (TSAD), including the scarcity of anomaly labels and the variability in anomaly lengths and shapes, have led to the need for a more robust and efficient solution. As limited anomaly labels hinder traditional supervised models in anomaly detection, various state-of-the-art (SOTA) deep learning (DL) techniques (e.g., self-supervised learning) are introduced to tackle this issue. However, they encounter difficulties handling variations in anomaly lengths and shapes, limiting their adaptability to diverse anomalies. Additionally, many benchmark datasets suffer from the problem of having explicit anomalies that even random functions can detect. This problem is …

Statistical Modeling Of Right-Censored Spatial Data Using Gaussian Random Fields, Fathima Z. Sainul Abdeen, Akim Adekpedjou, Sophie Dabo Niang

Mathematics and Statistics Faculty Research & Creative Works

Consider a Fixed Number of Clustered Areas Identified by their Geographical Coordinates that Are Monitored for the Occurrences of an Event Such as a Pandemic, Epidemic, or Migration. Data Collected on Units at All Areas Include Covariates and Environmental Factors. We Apply a Probit Transformation to the Time to Event and Embed an Isotropic Spatial Correlation Function into Our Models for Better Modeling as Compared to Existing Methodologies that Use Frailty or Copula. Composite Likelihood Technique is Employed for the Construction of a Multivariate Gaussian Random Field that Preserves the Spatial Correlation Function. the Data Are Analyzed using Counting Process …

The Effect Of Vision On Lower Quarter Balance During Y-Balance Test Testing In College Students, Nathan Smith, Katelyn Mehr

Applied Health Sciences Student Works

Purpose: In order to maintain balance and stability, the body relies on the integration of information from the visual, vestibular, and proprioceptive systems. If an individual has an impairment or weakness in one or more systems, their ability to maintain balance may be impaired. Both postural stability and vision contribute to one’s ability to maintain balance in functions of everyday life. The Y-Balance Test (YBT) is a dynamic balance assessment. This study focuses on the visual system and its relation to postural balance, specifically if altered visual states affect one’s ability to maintain balance during a YBT via the use …

Efficient Fully Bayesian Approaches To Brain Activity Mapping With Complex-Valued Fmri Data: Analysis Of Real And Imaginary Components In A Cartesian Model And Extension To Magnitude And Phase In A Polar Model, Zhengxin Wang

All Dissertations

Functional magnetic resonance imaging (fMRI) plays a crucial role in neuroimaging, enabling the exploration of brain activity through complex-valued signals. Traditional fMRI analyses have largely focused on magnitude information, often overlooking the potential insights offered by phase data, and therefore, lead to underutilization of available data and flawed statistical assumptions. This dissertation proposes two efficient, fully Bayesian approaches for the analysis of complex-valued functional magnetic resonance imaging (cv-fMRI) time series.

Chapter 2 introduces the model, referred to as CV-sSGLMM, using the real and imaginary components of cv-fMRI data and sparse spatial generalized linear mixed model prior. This model extends the …

Deterministic Global 3d Fractal Cloud Model For Synthetic Scene Generation, Aaron M. Schinder, Shannon R. Young, Bryan J. Steward, Michael L. Dexter, Andrew Kondrath, Stephen Hinton, Ricardo Davila

Faculty Publications

This paper describes the creation of a fast, deterministic, 3D fractal cloud renderer for the AFIT Sensor and Scene Emulation Tool (ASSET). The renderer generates 3D clouds by ray marching through a volume and sampling the level-set of a fractal function. The fractal function is distorted by a displacement map, which is generated using horizontal wind data from a Global Forecast System (GFS) weather file. The vertical windspeed and relative humidity are used to mask the creation of clouds to match realistic large-scale weather patterns over the Earth. Small-scale detail is provided by the fractal functions which are tuned to …

Investigation Of Magnetic, Spectroscopic, And Structural Properties Of Molecular Metal Compounds, Alexandria Bone

Doctoral Dissertations

Compounds exhibiting single-molecule magnetism (SMM) are of current interest for potential use in molecular data storage and quantum computing applications. However, rapid magnetic relaxation at desired operating temperatures currently limits the use of these materials, and a more thorough understanding of the magnetic and vibrational transitions that affect magnetic memory is required to inform SMM design. The primary focus of this dissertation is the study of magnetic and vibrational modes in molecular magnetic compounds via advanced spectroscopic techniques such as inelastic neutron scattering (INS), far-IR magneto-spectroscopy (FIRMS), and high-field, high-frequency electron paramagnetic resonance (HFEPR) to directly observe transitions among zero-field …

Classifying Facial Expressions Of Students Being Tutored In A Gateway College Math Course, Kriss Gabourel

Doctoral Dissertations

When it comes to tutoring, computers have not quite been able to achieve the success that humans have in helping students improve learning outcomes. This research sought to address one aspect of what makes human tutors more effective, the ability to identify and to interpret facial expressions. When a student is feeling anxious, confused, distracted or frustrated, or when a student has an ‘aha’ moment, human tutors can identify the student’s facial expressions and adjust their tutoring approach as necessary. This study sought to determine if, in the context of a gateway college math course, these particular learning-centered affects could …

Multi-Objective Radiological Analysis In Real Environments, David Raji

Doctoral Dissertations

Designing systems to solve problems arising in real-world radiological scenarios is a highly challenging task due to the contextual complexities that arise. Among these are emergency response, environmental exploration, and radiological threat detection. An approach to handling problems for these applications with explicitly multi-objective formulations is advanced. This is brought into focus with investigation of a number of case studies in both natural and urban environments. These include node placement in and path planning through radioactivity-contaminated areas, radiation detection sensor network measurement update sensitivity, control schemes for multi-robot radioactive exploration in unknown environments, and adversarial analysis for an urban nuclear …

Jet Production And Rppb In Pp Collisions At Sqrt(S) = 8 Tev And P--Pb Collisions At Sqrt(Snn) = 8.16 Tev Using The Alice Detector, Austin Schmier

Doctoral Dissertations

At the CERN Large Hadron Collider, protons and heavy ions are collided at relativistic
speeds in order to study the behavior and processes of Quantum Chromodynamics (QCD). One such process is the production of collimated sprays of particles called jets resulting from the hard scattering of two partons. Jets are an important probe that provide a window into the early stages of the collision.

Measurements in small systems such as proton-proton (pp) and proton-lead (p–Pb)
collisions are important in order to provide constraints on nuclear parton distribution
functions and the strong coupling constant αS [55]. Measurements at different center of …

Graph-Based And Anomaly Detection Learning Models For Just-In-Time Defect Prediction, Aradhana Soni

Doctoral Dissertations

Efficiently identifying and resolving software defects is essential for producing high quality software. Early and accurate prediction of these defects plays a pivotal role in maintaining software quality. This dissertation focuses on advancing software defect prediction methodologies and practical applications by incorporating graph-based learning techniques and generative adversarial-based anomaly detection techniques. First, we present a novel approach to software defect prediction by introducing a graph-based defect ratio (GDR). This innovative metric leverages the intricate graph structure that captures the interdependencies among developers, commits, and repositories, offering a promising alternative to standard traditional features. This study highlights the potential for graph-based …