Physical Sciences and Mathematics Commons^™

Gravel Conveyance System: An Evaluation On E. Coli Removal Capabilities, Madison Grace

<strong> Theses and Dissertations </strong>

In many rural, low-income communities such as the Black Belt of Alabama, there is a lack of wastewater infrastructure and solutions leaving homeowners non-compliant to state and federal law and with potential health risks on their property. New regulations have allowed for onsite, surface discharge for single family homes that are not connected to a centralized sewer or large flow development. These new regulations also contain strict disinfection criteria for the treated wastewater that will be discharged. A low-cost and low-maintenance treatment system that provides adequate disinfection is necessary to allow homeowners to take advantage of the new opportunity for …

Rheological Bridge Zones: A New Perspective To Explore Strain Localization And Rock Rheological Weakening, He Feng

Electronic Theses and Dissertations

Strain localization, a ubiquitous geological phenomenon, emerges when rock undergoes extensive weakening and accommodates disproportionate deformation. This phenomenon spans from brittle faulting to viscous flow, known as shear zones. Despite its prevalence, discussions on weakening primarily center on highly strained samples, rather than the initial deformation state. This research delves into the evolution of localization and rheology in intact rocks.

Heterogeneous mechanical properties within the lithosphere vary based on mineralogy, microstructure, and environmental conditions. Chapter 2 characterizes microscale structures termed "bridge zones." These zones, observed through optical and electron microscopy, exhibit distinctive morphologies. Comprising fine-grained aggregates, bridge zones link weak …

Learning Heterogeneous Subgraph Representations For Team Discovery, Radin Hamidi Rad, Hoang Nguyen, Feras Al-Obeidat, Ebrahim Bagheri, Mehdi Kargar, Divesh Srivastava, Jaroslaw Szlichta, Fattane Zarrinkalam

All Works

The team discovery task is concerned with finding a group of experts from a collaboration network who would collectively cover a desirable set of skills. Most prior work for team discovery either adopt graph-based or neural mapping approaches. Graph-based approaches are computationally intractable often leading to sub-optimal team selection. Neural mapping approaches have better performance, however, are still limited as they learn individual representations for skills and experts and are often prone to overfitting given the sparsity of collaboration networks. Thus, we define the team discovery task as one of learning subgraph representations from a heterogeneous collaboration network where the …

On Hierarchical Clustering-Based Approach For Rddbs Design, Hassan I. Abdalla, Ali A. Amer, Sri Devi Ravana

All Works

Distributed database system (DDBS) design is still an open challenge even after decades of research, especially in a dynamic network setting. Hence, to meet the demands of high-speed data gathering and for the management and preservation of huge systems, it is important to construct a distributed database for real-time data storage. Incidentally, some fragmentation schemes, such as horizontal, vertical, and hybrid, are widely used for DDBS design. At the same time, data allocation could not be done without first physically fragmenting the data because the fragmentation process is the foundation of the DDBS design. Extensive research have been conducted to …

Software Jimenae Allows Efficient Dynamic Simulations Of Boolean Networks, Centrality And System State Analysis, Martin Kaltdorf, Tim Breitenbach, Stefan Karl, Maximilian Fuchs, David Komla Kessie, Eric Psota, Martina Prelog, Edita Sarukhanyan, Regina Ebert, Franz Jakob, Gudrun Dandekar, Muhammad Naseem, Chunguang Liang, Thomas Dandekar

All Works

The signal modelling framework JimenaE simulates dynamically Boolean networks. In contrast to SQUAD, there is systematic and not just heuristic calculation of all system states. These specific features are not present in CellNetAnalyzer and BoolNet. JimenaE is an expert extension of Jimena, with new optimized code, network conversion into different formats, rapid convergence both for system state calculation as well as for all three network centralities. It allows higher accuracy in determining network states and allows to dissect networks and identification of network control type and amount for each protein with high accuracy. Biological examples demonstrate this: (i) High plasticity …

Accelerated Evolution Of Sars-Cov-2 In Free-Ranging White-Tailed Deer, Dillon S. Mcbride, Sofya K. Garushyants, John Franks, Andrew F. Magee, Steven H. Overend, Devra Huey, Amanda M. Williams, Seth A. Faith, Ahmed Kandeil, Sanja Trifkovic, Lance Miller, Trushar Jeevan, Anami Patel, Jacqueline M. Nolting, Michael J. Tonkovich, J. Tyler Genders, Andrew J. Montoney, Kevin Kasnyik, Timothy J. Linder, Sarah N. Bevins, Julianna B. Lenoch, Jeffrey C. Chandler, Thomas J. Deliberto, Eugene V. Koonin, Marc A. Suchard, Philippe Lemey, Richard J. Webby, Martha I. Nelson, Andrew S. Bowman

United States Department of Agriculture Wildlife Services: Staff Publications

The zoonotic origin of the COVID-19 pandemic virus highlights the need to fill the vast gaps in our knowledge of SARS-CoV-2 ecology and evolution in non-human hosts. Here, we detected that SARS-CoV-2 was introduced from humans into white-tailed deer more than 30 times in Ohio, USA during November 2021-March 2022. Subsequently, deer-to-deer transmission persisted for 2–8 months, disseminating across hundreds of kilometers. Newly developed Bayesian phylogenetic methods quantified how SARS-CoV-2 evolution is not only three-times faster in white-tailed deer compared to the rate observed in humans but also driven by different mutational biases and selection pressures. The long-term effect of …

Rapid Evolution Of A(H5n1) Influenza Viruses After Intercontinental Spread To North America, Ahmed Kandeil, Christopher Patton, Jeremy C. Jones, Trushar Jeevan, Walter N. Harrington, Sanja Trifkovic, Jon P. Seiler, Thomas Fabrizio, Karlie Woodard, Jasmine C. Turner, Jeri Carol Crumpton, Lance Miller, Adam Rubrum, Jennifer Debeauchamp, Charles J. Russell, Elena A. Govorkova, Peter Vogel, Mia Kim-Torchetti, Yohannes Berhane, David Stallknecht, Rebecca Poulson, Lisa Kercher, Richard J. Webby

United States Department of Agriculture Wildlife Services: Staff Publications

Highly pathogenic avian influenza A(H5N1) viruses of clade 2.3.4.4b underwent an explosive geographic expansion in 2021 among wild birds and domestic poultry across Asia, Europe, and Africa. By the end of 2021, 2.3.4.4b viruses were detected in North America, signifying further intercontinental spread. Here we show that the western movement of clade 2.3.4.4b was quickly followed by reassortment with viruses circulating in wild birds in North America, resulting in the acquisition of different combinations of ribonucleoprotein genes. These reassortant A(H5N1) viruses are genotypically and phenotypically diverse, with many causing severe disease with dramatic neurologic involvement in mammals. The proclivity of …

Enhancing Urban Water Quality Through Biological-Chemical Treatment: Aquatic Macroinvertebrate Community And Temporal Chlorophyll-A Response, Matthew Chaffee

Department of Biological Systems Engineering: Dissertations and Theses

With a growing human population, urbanization is impeding a plethora of natural waterways. Of these, urban ponds play a vital role in nutrient sequestration, flood prevention, and habitat sanctuaries. However, nutrient loading can reduce habitat effectiveness and promote harmful algae blooms. To reduce internal nutrient loads, a biological-chemical treatment strategy consisting of floating treatment wetlands (FTWs) and lanthanum were applied to two urban retention ponds, Densmore and Wilderness Ridge Ponds. To measure effectiveness, chlorophyll-a samples were collected and correlated with Sentinel-2. A novel band algorithm termed 3BR1 produced a strong correlation (R² = 0.72) to physical chlorophyll-a …

Upcyclying Of Polyethylene Terephtalate By Addition Of Thermoplastic Elastomer, Diego Francisco Bermudez

Open Access Theses & Dissertations

Continual overconsumption of single-use plastics has generated challenges of solid waste management across the United States. Common plastic waste management solutions, such as landfill, have caused the migration of contaminants into the environment consequently affecting not only the health of wildlife, but also that of human beings. Alternative strategies for the handling of single-use plastic such as polyethylene terephthalate (PET), used in the food packaging industry, can ultimately help mitigate the noxious consequences of single-use plastics affecting entire ecosystems. This study demonstrates a potential avenue of materials upcycling by studying the effects of coupling PET with the thermoplastic elastomer styrene-ethylene-butylene-styrene …

Synthesis And Characterization Of Acetaminophen-Derived Nanoparticles: A Novel Approach To Inhibit Fibril Formation, Hannia Elena Mendoza-Dickey

Open Access Theses & Dissertations

In the realm of nanotechnology, nanoparticles (NPs), have garnered significant notoriety in recent scientific research due to their unique physical and chemical properties, such as fluorescence emissions, nanoscale dimensions (typically <1000 nm), ease of surface modification, and biocompatibility. Nanoparticles have shown their potential across a variety of areas, including advanced industrial applications and cutting-edge biomedical research. Considering their cost-effective synthesis, they have shown promise as therapeutic agents for a variety of bioimaging and biomedical applications. This thesis describes the synthesis and detailed analysis of acetaminophen-derived nanoparticles. Techniques such as Dynamic Light Scattering (DLS), Thioflavin T (THT) assay, Attenuated Total Reflectance Infrared Spectroscopy (ATR-IR), 1H NMR spectroscopy, and Ultraviolet-Visible Spectroscopy (UV-VIS) were utilized for structural and functional assessments. Acetaminophen derived nanoparticles (ANPs) exhibit potential to hinder the amyloidogenic conversion of soluble amyloid-forming proteins into their toxic form. The novelty of this research focuses on the utilization of chemical structures capable of traversing the Blood Brain Barrier (BBB) to mitigate xenotoxicant-induced neuronal damage, a notable contributor to neurodegenerative disorders. This thesis describes the synthesis and characterization of acetaminophen derived-nanoparticles (ANPs). Our nanoparticles possess anti-amyloidogenic properties as evidenced by their ability to disrupt in the soluble-to-toxic trajectory of HEWL. The prevalence and evolution of amyloid fibrils are consistent features in the pathology of neurodegenerative diseases such as Parkinson's disease (PD), Alzheimerâ??s Disease (AD), and Huntingtonâ??s Disease (HD), as well as metabolic disorders like Type 2 diabetes (T2D). The relationship between amyloidogenic pathways and these disorders highlights the imperative for enhanced understanding and the formulation of specific therapeutic interventions.

Intercomparison Of Planetary Boundary Layer Over El Paso-Juarez Region Using Vaisala Ceilometers, Vianey Arvilla

Open Access Theses & Dissertations

Vaisala ceilometers (models CL 31 and Cl 51) were used to monitor and study the planetary boundary layer (PBL). There were four ceilometer stations that we connected to create the Paso del Norte ceilometer network. These stations are located at: UTEP, Socorro, Ivanhoe, and Juarez. This network has been automatized and its hourly averaged mean boundary layer height data is being downloaded into a computer accessible to TCEQ (Texas Commission on Environmental Quality) and to the public. In this study, data from each ceilometer was used to produce scatter plots. These scatter plots were analyzed to obtain the PBL heights …

Evaluation Of Evapotranspiration Estimates Using An Existing Hybrid Machine Learning Model In A Natural And A Managed Dryland Site, Katya Esquivel Herrera

Open Access Theses & Dissertations

Evapotranspiration (ET) is a critical component of the hydrologic cycle, encompassing both evaporative water loss from surfaces and transpiration through plant stomata. The environmental factors influencing ET include water and energy availability, atmospheric capacity for water uptake, and various meteorological variables. ET serves as a unique climate variable linking water, energy, and carbon cycles. In agroecosystems, accurate ET quantification is vital for optimizing water use efficiency, irrigation management, and crop yield. Traditional methods for ET estimation involve direct measurements and indirect models, with both presenting limitations.

Recent years have witnessed the integration of remote sensing and machine learning (ML) algorithms …

A Noninvasive Urine-Based Method For Kidney Cancer Early Detection, Kiana Holbrook

Open Access Theses & Dissertations

Based on the traditional serological uses to obtain diagnoses of cancer and biopsy techniques, common cancer detection could be not only invasive but expensive and some tests are also unreliable. Currently, urine is one of the most frequently used and collected specimens in the clinical diagnoses. While the areas of urinalysis and metabolomic profiling has received interest in the top clinical research, there are limited components to the validity, specificity, as well as sensitivity of endogenous urine substrates to detect early stages of cancers. Although there is research showcasing that urine is impacted by age, cancer type, geographical location, and …

Bitcoin's Technical Foundation And Its Potential For A Decentralized And Environmentally Friendly Future, Iqtiar Md Siddique

Open Access Theses & Dissertations

This research examines a systematic analysis of Bitcoin, employing a Coefficient of Variation (CV) approach to gauge its degree of decentralization. Bitcoin, an innovative decentralized digital currency, has received much attention for its potential to revolutionize traditional financial systems. This study employs the Coefficient of Variation (CV) to acquire insights into the wealth distribution and concentration among Bitcoin users. This research demonstrates how decentralized the network of Bitcoin is. The methodology uses real data on Bitcoin addresses and their holdings to compute the Coefficient of Variation (CV). This approach provides valuable insights into the ongoing discourse surrounding Bitcoin's decentralization, offering …

Preliminary Assessment For Critical Minerals In The Terlingua Quicksilver District, Texas And Tres Marias Mine, Chihuahua, Mexico, Eduardo Lee Zuniga

Open Access Theses & Dissertations

The Terlingua Quicksilver district was discovered around the 1880s and was a mercury producing district from 1900 through 1946. The most productive years were during World War one and two. From 1900-1946 the Terlingua Quicksilver District (TQD) produced 150,000 flasks; 80% came from three mines: the Rainbow-Chisos, Mariposa, and Study Butte mines. The structural controls of the Mercury mineralization within these mines are breccia pipes and fractures, often located near igneous intrusions. This study will assess the potential for Critical Minerals and Rare Earth Elements in the Terlingua Quicksilver District. Fifty-five samples have been collected and analyzed for forty-four different …

Towards Expressive And Versatile Visualization-As-A-Service (Vaas), Tanner C. Hobson

Doctoral Dissertations

The rapid growth of data in scientific visualization has posed significant challenges to the scalability and availability of interactive visualization tools. These challenges can be largely attributed to the limitations of traditional monolithic applications in handling large datasets and accommodating multiple users or devices. To address these issues, the Visualization-as-a-Service (VaaS) architecture has emerged as a promising solution. VaaS leverages cloud-based visualization capabilities to provide on-demand and cost-effective interactive visualization. Existing VaaS has been simplistic by design with focuses on task-parallelism with single-user-per-device tasks for predetermined visualizations. This dissertation aims to extend the capabilities of VaaS by exploring data-parallel visualization …

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 …