Physical Sciences and Mathematics Commons^™

Subduction Initiation Recorded In The Dadeville Complex Of Alabama And Georgia, Southeastern United States, Naomi A. Becker, Freya R. George, George L. Guice, James L. Crowley, Wendy R. Nelson, Joseph F. Browning-Hanson, Supratik Roy, Daniel R. Viete

Geosciences Faculty Publications and Presentations

The Dadeville Complex of Alabama and Georgia (southeastern United States) represents the largest suite of exposed mafic-ultramafic rocks in the southern Appalachians. Due to poor preservation, chemical alteration, and tectonic reworking, a specific tectonic origin for the Dadeville Complex has been difficult to deduce. We obtained new whole-rock and mineral geochemistry coupled with zircon U-Pb geochronology to investigate the magmatic and metamorphic processes recorded by the Dadeville Complex, as well as the timing of these processes. Our data reveal an up-stratigraphic evolution in the geochemistry of the volcanic rocks, from forearc basalts to boninites. Our new U-Pb zircon crystallization data—obtained …

Clueless: Revolutionizing Sustainable Fashion And Combating Overconsumption, Tanya Ravichandran

Graphic Communication

“Clueless” revolutionizes sustainable fashion by combating wardrobe overconsumption and the industry’s carbon footprint, using AI to suggest personalized outfits from existing wardrobes tailored to weather and wear history. It enhances user engagement through features like outfit ‘shuffle’ and provides insights into wardrobe utilization and carbon impact.

It’s more than an app; it’s a step towards a greener wardrobe and a healthier planet.

Weakly-Supervised Semantic Segmentation, Zhaozheng Chen

Dissertations and Theses Collection (Open Access)

Semantic segmentation is a fundamental task in computer vision that assigns a label to every pixel in an image based on the semantic meaning of the objects present. It demands a large amount of pixel-level labeled images for training deep models. Weakly-supervised semantic segmentation (WSSS) is a more feasible approach that uses only weak annotations to learn the segmentation task. Image-level label based WSSS is the most challenging and popular, where only the class label for the entire image is provided as supervision. To address this challenge, Class Activation Map (CAM) has emerged as a powerful technique in WSSS. CAM …

Effects Of Elevated Temperature On 8-Ohdg Expression In The American Oyster (Crassostrea Virginica): Induction Of Oxidative Stress Biomarkers, Cellular Apoptosis, Dna Damage And Γh2ax Signaling Pathways, Md Faizur Rahman, Mohammad Maruf Billah, Richard Kline, Md Saydur Rahman

School of Earth, Environmental, and Marine Sciences Faculty Publications and Presentations

Global temperature is increasing due to anthropogenic activities and the effects of elevated temperature on DNA lesions are not well documented in marine organisms. The American oyster (Crassostrea virginica, an edible and commercially important marine mollusk) is an ideal shellfish species to study oxidative DNA lesions during heat stress. In this study, we examined the effects of elevated temperatures (24, 28, and 32 °C for one-week exposure) on heat shock protein-70 (HSP70, a biomarker of heat stress), 8-hydroxy-2’-deoxyguanosine (8-OHdG, a biomarker of pro-mutagenic DNA lesion), double-stranded DNA (dsDNA), γ-histone family member X (γH2AX, a molecular biomarker of DNA damage), …

Why Sigmoid Transformation Helps Incorporate Logic Into Deep Learning: A Theoretical Explanation, Chitta Baral, Vladik Kreinovich

Departmental Technical Reports (CS)

Traditional neural networks start from the data, they cannot easily handle prior knowledge -- this is one of the reasons why they often take very long to train. It is desirable to incorporate prior knowledge into deep learning. For the case when this knowledge consists of propositional statements, a successful way to incorporate this knowledge was proposed in a recent paper by van Krieken et al. That paper uses the fact that a neural network does not directly return a truth value, it returns a real value -- in effect, the degree of confidence in the corresponding statement -- from …

Llm4vis: Explainable Visualization Recommendation Using Chatgpt, Lei Wang, Songheng Zhang, Yun Wang, Ee-Peng Lim, Yong Wang

Research Collection School Of Computing and Information Systems

Data visualization is a powerful tool for exploring and communicating insights in various domains. To automate visualization choice for datasets, a task known as visualization recommendation has been proposed. Various machine-learning-based approaches have been developed for this purpose, but they often require a large corpus of dataset-visualization pairs for training and lack natural explanations for their results. To address this research gap, we propose LLM4Vis, a novel ChatGPT-based prompting approach to perform visualization recommendation and return human-like explanations using very few demonstration examples. Our approach involves feature description, demonstration example selection, explanation generation, demonstration example construction, and inference steps. To …

Robust Test Selection For Deep Neural Networks, Weifeng Sun, Meng Yan, Zhongxin Liu, David Lo

Research Collection School Of Computing and Information Systems

Deep Neural Networks (DNNs) have been widely used in various domains, such as computer vision and software engineering. Although many DNNs have been deployed to assist various tasks in the real world, similar to traditional software, they also suffer from defects that may lead to severe outcomes. DNN testing is one of the most widely used methods to ensure the quality of DNNs. Such method needs rich test inputs with oracle information (expected output) to reveal the incorrect behaviors of a DNN model. However, manually labeling all the collected test inputs is a labor-intensive task, which delays the quality assurance …

A Comprehensive Evaluation Of Large Language Models On Legal Judgment Prediction, Ruihao Shui, Yixin Cao, Xiang Wang, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

Large language models (LLMs) have demonstrated great potential for domain-specific applications, such as the law domain. However, recent disputes over GPT-4’s law evaluation raise questions concerning their performance in real-world legal tasks. To systematically investigate their competency in the law, we design practical baseline solutions based on LLMs and test on the task of legal judgment prediction. In our solutions, LLMs can work alone to answer open questions or coordinate with an information retrieval (IR) system to learn from similar cases or solve simplified multi-choice questions. We show that similar cases and multi-choice options, namely label candidates, included in prompts …

Exgen: Ready-To-Use Exercise Generation In Introductory Programming Courses, Nguyen Binh Duong Ta, Hua Gia Phuc Nguyen, Gottipati Swapna

Research Collection School Of Computing and Information Systems

In introductory programming courses, students as novice programmers would benefit from doing frequent practices set at a difficulty level and concept suitable for their skills and knowledge. However, setting many good programming exercises for individual learners is very time-consuming for instructors. In this work, we propose an automated exercise generation system, named ExGen, which leverages recent advances in pre-trained large language models (LLMs) to automatically create customized and ready-to-use programming exercises for individual students ondemand. The system integrates seamlessly with Visual Studio Code, a popular development environment for computing students and software engineers. ExGen effectively does the following: 1) maintaining …

Energy Extraction, Or Lack Thereof, Nishanth Gudapati

Mathematics

The problem of stability of rotating black holes is the subject of a long standing research program since the 1960s and remains an unresolved problem in general relativity. A major obstacle in the black hole stability problem is that the energy of waves propagating through rotating black holes spacetimes is not necessarily positive-definite, due to the so called ergo-region. This is a serious complication that limits the efficacy of most mathematical techniques. In this expository article, we report that, despite the ergo-region, there exists a positive-definite total energy for axisymmetric Maxwell, gravitational and electrovacuum perturbations of Kerr and Kerr–Newman black …

Characterizing Silicate Materials Via Raman Spectroscopy And Machine Learning: Implications For Novel Approaches To Studying Melt Dynamics, Blake O. Ladouceur

Doctoral Dissertations

Silicate melt characteristics impose dramatic influence over igneous processes that operate, or have operated on, differentiated bodies: such as the Earth and Mars. Current understanding of these melt properties, such as composition, primarily comes from investigations on their volcanic byproducts. Therefore, it is imperative to innovate on modalities capable of constraining melt information in environments where a reliance on laboratory methods is severed. Recent investigations have turned to Raman Spectroscopy and amorphous volcanics as a suitable pairing for exploring these ideas. Silicate glasses are a proxy for igneous melts; and Raman spectroscopy is a robust analytical technique capable of operating …

Initial Limnology Of Laguna Pozo Verde, Costa Rica: Bathymetry, Water, Sediments, And Diatoms, Sally P Horn, Erik N. Johanson, Mauricio Murillo Herrera, Kurt A. Haberyan, Taber Friedel, Chad S. Lane

Geography Publications and Other Works

ABSTRACT. Introduction: Costa Rica has hundreds of lakes, many of which have never been scientifically studied. Objective: To carry out a first, basic limnological study of Laguna Pozo Verde in Juan Castro Blanco National Park, Costa Rica (~1935m elevation), to provide baseline data for studying future changes. Methods: We measured water depths and temperatures, and Secchi depth; analyzed surface sediments; and examined maps and satellite imagery. Results: Though described by some as formed by volcanic processes, Laguna Pozo Verde likely formed in a landslide, which occur frequently in this rainy area on the steep south slope of the inactive Porvenir …

Hpc-Enabled Fast And Configurable Dynamic Simulation, Analysis, And Learning For Complex Power System Adaptation And Control, Cong Wang

All Dissertations

This dissertation presents an HPC-enabled fast and configurable dynamic simulation, analysis, and learning framework for complex power system adaptation and control. Dynamic simulation for a large transmission system comprising thousands of buses and branches implies the latency of complicated numerical computations. However, faster-than-real-time execution is often required to provide timely support for power system planning and operation. The traditional approaches for speeding up the simulation demand extensive computing facilities such as CPU-based multi-core supercomputers, resulting in heavily resource-dependent solutions. In this work, by coupling the Message Passing Interface (MPI) protocol with an advanced heterogeneous programming environment, further acceleration can be …

Developing Detection And Mapping Of Roads Within Various Forms Of Media Using Opencv, Jordan C. Lyle

Computer Science and Computer Engineering Undergraduate Honors Theses

OpenCV, and Computer Vision in general, has been a Computer Science topic that has interested me for a long time while completing my Bachelor’s degree at the University of Arkansas. As a result of this, I ended up choosing to utilize OpenCV in order to complete the task of detecting road-lines and mapping roads when given a wide variety of images. The purpose of my Honors research and this thesis is to detail the process of creating an algorithm to detect the road-lines such that the results are effective and instantaneous, as well as detail how Computer Vision can be …

Insight Into The Binding Of Argon To Cyclic Water Clusters From Symmetry-Adapted Perturbation Theory, Carly A. Rock, Gregory S. Tschumper

Chemistry Faculty Research & Creative Works

This work systematically examines the interactions between a single argon atom and the edges and faces of cyclic H (Formula presented.) O clusters containing three–five water molecules (Ar(H (Formula presented.) O) (Formula presented.)). Full geometry optimizations and subsequent harmonic vibrational frequency computations were performed using MP2 with a triple- (Formula presented.) correlation consistent basis set augmented with diffuse functions on the heavy atoms (cc-pVTZ for H and aug-cc-pVTZ for O and Ar; denoted as haTZ). Optimized structures and harmonic vibrational frequencies were also obtained with the two-body–many-body (2b:Mb) and three-body–many-body (3b:Mb) techniques; here, high-level CCSD(T) computations capture up through the …

Computationally-Driven Insights Into The Ligand Environments Of Materials For Catalysis And Separations, Stephen Vicchio

All Dissertations

Designing new catalytic and sorption materials is necessary to limit global temperature rise below 1.5 ◦C by 2050, while also meeting global energy demands. Climate change and energy production are not mutually exclusive; global population growth has direct impacts on global energy demands and climate. In both catalysis and adsorption applications, new technologies are needed to address these challenges. Catalysis can provide alternate, low-energy routes for converting low-value gases into higher-value chemical commodities, thus altering our current energy production. Likewise, new sorption materials can capture previously emitted CO₂ from decades of energy production from fossil fuels, thus helping to …

Controlled Manipulation And Transport By Microswimmers In Stokes Flows, Jake Buzhardt

All Dissertations

Remotely actuated microscale swimming robots have the potential to revolutionize many aspects of biomedicine. However, for the longterm goals of this field of research to be achievable, it is necessary to develop modelling, simulation, and control strategies which effectively and efficiently account for not only the motion of individual swimmers, but also the complex interactions of such swimmers with their environment including other nearby swimmers, boundaries, other cargo and passive particles, and the fluid medium itself. The aim of this thesis is to study these problems in simulation from the perspective of controls and dynamical systems, with a particular focus …

Understanding The Interaction Of Environmental Contaminants With Polystyrene Nanoparticles And Dna Using Nuclear Magnetic Resonance Spectroscopy And Density Functional Theory, Saduni Arachchi

All Dissertations

The objective of the thesis is to study the effect of environmental pollutants on polystyrene nanoparticles and biomolecules. This is done in two different techniques, particularly NMR and density functional theory. In this thesis, we use a combination of 1H NMR, Saturation-Transfer Difference (STD) NMR and relaxation experiments to study the interactions, kinetics and dynamics of antibiotics with polystyrene nanoparticles. (PS NPs) Density functional theory (DFT) is used to study the binding of commonly used non-oxidative hair dyes to biomolecules (DNA and amino acids) and PS particles.

Regioselective Catalytic Synthesis Of Potentially Bioactive 1,3,4-Selenadiazole, Mohamed Ali Mahmoud

Theses

Isoselenocyanates have a crucial role as reactants in chemical processes, facilitating the efficient synthesis of significant chemical intermediates and physiologically active chemicals. The utilization of (Z)-2-oxo-N-phenylpropanehydrazonoyl chlorides in a one-step procedure for the synthesis of the core structure of various heterocyclic compounds has been widely explored. This study focuses on the synthesis of 5-arylimino-1,3,4-selenadiazole derivatives through the reaction of isoselenocyanates with various substituted (Z)-2-oxo-N-phenylpropanehydrazonoyl chlorides. The objective is to achieve selective and accurate formation of these derivatives. The derivatives exhibit a diverse range of functional groups on both aryl rings. The synthetic procedure is conducted under ambient conditions, promoting environmental …

On The Synthesis Of Heavy Rare Earth Solid Solutions And Their Hydrides, Joshua R. Van Cleave

UNLV Theses, Dissertations, Professional Papers, and Capstones

The theoretical predictions and results from the (La,Y)Hx ternary hydride solution provided evidence toward phase stability at comparatively lower pressures, as consequence the (Yb,Lu)H_x and (Tm,Lu)H_x ternary hydrides are studied here with pressures up to 25 GPa in the diamond anvil cell. The onset of an unknown feature in the XRD pattern coincides with crystallographic plane distortions in the tetragonal lattice of ytterbium hydride at their laser-heated interface, possibly driven by a solid solution of Lu-Yb. Findings in collected Raman spectra and X-ray diffraction patterns in an Ar environment suggest potential stability of the FCC and high-temperature HCP …

Mgmt Promoter Methylation Status Prediction Using Mri Scans? An Extensive Experimental Evaluation Of Deep Learning Models, Numan Saeed, Muhammad Ridzuan, Hussain Alasmawi, Ikboljon Sobirov, Mohammad Yaqub

Computer Vision Faculty Publications

The number of studies on deep learning for medical diagnosis is expanding, and these systems are often claimed to outperform clinicians. However, only a few systems have shown medical efficacy. From this perspective, we examine a wide range of deep learning algorithms for the assessment of glioblastoma - a common brain tumor in older adults that is lethal. Surgery, chemotherapy, and radiation are the standard treatments for glioblastoma patients. The methylation status of the MGMT promoter, a specific genetic sequence found in the tumor, affects chemotherapy's effectiveness. MGMT promoter methylation improves chemotherapy response and survival in several cancers. MGMT promoter …

Vertical Free-Swinging Photovoltaic Racking Energy Modeling: A Novel Approach To Agrivoltaics, Koami Soulemane Hayibo, Joshua M. Pearce

Electrical and Computer Engineering Publications

To enable lower-cost building materials, a free-swinging bifacial vertical solar photovoltaic (PV) rack has been proposed, which complies with Canadian building codes and is the lowest capital-cost agrivoltaics rack. The wind force applied to the free-swinging PV, however, causes it to have varying tilt angles depending on the wind speed and direction. No energy performance model accurately describes such a system. To provide a simulation model for the free-swinging PV, where wind speed and direction govern the array tilt angle, this study builds upon the open-source System Advisor Model (SAM) using Python. After the SAM python model is validated, a …

Ru(Ii) Polypyridyl Photosensitizers For Phototherapy, Houston Cole

Chemistry & Biochemistry Dissertations

This dissertation describes the design, synthesis, and photobiological characterization of key target molecules that modify the 1) length of the IP-nT “PDT” ligand, 2) electronic nature of the bipyridine or phenanthroline type ancillary ligands, and 3) chirality of the coordination complex. The targets and subsequent studies will test the hypothesis that molecules with low-lying and long-lived 3ILCT states are responsible for this unusually high photocytotoxic potency and seeks to further understand what structural features (aside from the IP-nT ligand) lead to more favorable photobiological properties.

Studies Toward A Total Synthesis Of The Pyrrole-Imidazole Alkaloid Palau'amine And Computationally Assisted Stereochemical Elucidation, Brandon Fulton

Chemistry & Biochemistry Dissertations

This thesis documents progress toward a total synthesis of the marine natural product palau'amine, a stereochemically dense hexacyclic pyrrole-imidazole alkaloid with pharmaceutically relevant anticancer, antifungal, and antibacterial activity. Also described herein are several miscellaneous synthesis projects and the application of computational NMR as an aid for solving structure elucidation problems. Chapter 1 is a continuation of our lab’s prior work utilizing vinylimidazoles in cycloaddition reactions to gain rapid access to scaffolds resembling dimeric pyrrole-imidazole alkaloids such as ageliferin or palau’amine. Mechanistic aspects of these cycloadditions for both inter- and intramolecular cases were probed via time-course NMR experiments and computational studies, …

Effect Of Self-Interaction Correction On Molecular Polarizabilities And Core Ionization Energies, Sharmin Akter

Open Access Theses & Dissertations

Density Functional Theory (DFT) is one of the most successful and popular computational Quantum Mechanical approaches to understanding materials. DFT allows the prediction of material properties from the electron density. Although in principle, density functional theory is exact, it, however, relies on approximate functional for exchange-correlation energy. Due to the approximate nature of the exchange-correlation functional, the self-Coulomb energy of the electrons is not exactly canceled out by the self-exchange, leading to the spurious self-interaction error (SIE). Due to this error, the potential shows incorrect behavior which leads to errors in calculated properties such as ionization energies, electron affinities, polarizabilities, …

Addressing Binational Issues For Water Quality Along The United States-Mexico Border And The Use Of The 1944 Water Treaty As A Means For Developing Transboundary Aquifer Agreements, Gilbert Anaya

Open Access Theses & Dissertations

The water resources of the United States (U.S.) and Mexico are under tremendous pressure due to declining reservoir levels, changes in climate, and prolonged drought. The U.S.-Mexico border region relies on the Rio Grande and Colorado River, and shared groundwater resources that are transboundary in nature. These resources are vital to the U.S.-Mexico border and are susceptible to drought that leads to reduced flow and allocation to the users. In addition, there are impacts to water quality caused by return flows and from failing sanitation infrastructure. In this study, we focus on 1) the contribution of springs in an area …

Context-Aware Temporal Embeddings For Text And Video Data, Ahnaf Farhan

Open Access Theses & Dissertations

Recent years have seen an exponential increase in unstructured data, primarily in the form of text, images, and videos. Extracting useful features and trends from large-scale unstructured datasets -- such as news outlets, scientific papers, and videos like security cameras or body cam recordings -- is faced with substantial challenges of volume, scalability, complexity, and semantic understanding. In analyzing trends, comprehending the temporal context is vital for uncovering patterns and narratives that are not apparent from a single video frame or text document. Despite its importance, many existing data mining and machine learning approaches overlook extracting evolutionary contextual features in …

Integrating Machine Learning Methods For Medical Diagnosis, Jazmin Quezada

Open Access Theses & Dissertations

Abstract:The rapid advancement of machine learning techniques has revolutionized the field of medical diagnosis by offering powerful tools to analyze complex data sets and make accurate predictions. In this proposed method, we present a novel approach that integrates machine learning and optimization models to enhance the accuracy of medical diagnoses. Our method focuses on fine-tuning and optimizing the parameters of machine learning algorithms commonly used in medical diagnosis, such as logistic regression, support vector machines, and neural networks. By employing optimization techniques, we systematically explore the parameter space of these algorithms to discover the most optimal configurations. Moreover, by representing …

Customer Churn Prediction Using Composite Deep Learning Technique, Asad Khattak, Zartashia Mehak, Hussain Ahmad, Muhammad Usama Asghar, Muhammad Zubair Asghar, Aurangzeb Khan

All Works

Customer churn, a phenomenon that causes large financial losses when customers leave a business, makes it difficult for modern organizations to retain customers. When dissatisfied customers find their present company's services inadequate, they frequently migrate to another service provider. Machine learning and deep learning (ML/DL) approaches have already been used to successfully identify customer churn. In some circumstances, however, ML/DL-based algorithms lacks in delivering promising results for detecting client churn. Previous research on estimating customer churn revealed unexpected forecasts when utilizing machine learning classifiers and traditional feature encoding methodologies. Deep neural networks were also used in these efforts to extract …

Depth-Resolved Defect Characterization Of Multi-Layer Thin-Film Semiconductor Materials Via Positron Annihilation Spectroscopy, Jack Driscoll

Physics Theses

Positron annihilation spectroscopy has frequently been used to perform depth-resolved defect characterization. In this thesis, the application of UTA's advanced positron beam to conduct depth-resolved defect studies on multi-layer semiconductor thin-film materials is demonstrated.