Physical Sciences and Mathematics Commons^™

Effects Of Short-Term Exposure To A Pesticide Mixture On Free-Swimming Behavior In Goldfish, Carassius Auratus, Esmirna Cantu, Michelle Rivera, Brittney Lacy, Md Saydur Rahman

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

Highlights

• We observed effects of pesticides exposure on free-swimming behaviors in goldfish.

• Pesticides profoundly impacting natural swimming patterns.

• Behavioral analysis showed a dose- and time-dependent, decrease in distance swam.

• Vertical/horizontal spatial behavioral use both affected under exposure conditions.

Abstract

The prevalence of pesticides in the aquatic environment continues to increase due to anthropogenic activities and poses a threat to aquatic organisms. Notably, the intensive use of pesticides can cause detrimental effects (i.e., chemical stressors) on animal behavior. The aim of this study was to determine the short-term exposure effects (5-day) of an environmentally relevant pesticide mixture (low- and high-dose: metolachlor …

Controllable Language Generation Using Deep Learning, Rohola Zandie

Electronic Theses and Dissertations

The advent of deep neural networks has sparked a revolution in Artificial Intelligence (AI), notably with the creation of Transformer models like GPT-X and ChatGPT. These models have surpassed previous methods in various Natural Language Processing (NLP) tasks. As the NLP field evolves, there is a need to further understand and question the capabilities of these models. Text generation, a crucial part of NLP, remains an area where our comprehension is limited while being critical in research.

This dissertation focuses on the challenging problem of controlling the general behaviors of language models such as sentiment, topical focus, and logical reasoning. …

Ocean Wave-Coherent Temperature And Humidity Near-Surface Vertical Distributions And Their Effect On Radar Performance Over The Ocean, Mathew James Stanek

Electronic Theses and Dissertations

Large knowledge gaps concerning the effect of ocean surface waves on near-surface vertical distributions of temperature and humidity in the marine atmospheric surface layer exist due to practical limitations and sensor fidelity challenges of direct measurements. Wave effects on these distributions between the wave trough and crest are least studied within the literature. These scalar distributions influence atmospheric refractivity, which can lead to anomalous propagation of electromagnetic energy. Measurements of temperature and humidity are classically made using rocket- or radiosondes and fixed weather stations, and can utilize tethered profiling systems. However, these measurement systems have limitations when obtaining measurements near …

Intercalation And High-Pressure Investigations Of Black Arsenic Phosphorus: Unraveling Material Transformations., Dinushika Vithanage

Electronic Theses and Dissertations

Black arsenic phosphorus (b-As_yP_1-y) alloys have emerged as intriguing materials within the realm of two-dimensional (2D) materials, following the discovery of black phosphorus (BP). These alloys possess capability to overcome major limitations of BP and exhibit potential for tunability and enhancement of properties making them promising materials for a wide range of applications, including lithium-ion batteries. Inspired by the intriguing findings obtained for BP, this research focuses on understanding the structural modifications that can be achieved in b-As_yP_1-y alloys through the application of intercalation and high pressure. The initial phase of our investigation …

Evaluating Chatgpt For Recommendation: How Does The Ability To Converse Impact Recommendation?, Kyle Spurlock

Electronic Theses and Dissertations

Recommendation algorithms have become an absolute necessity in the modern world to avoid information overload. However, the interaction between the human and the system is largely superficial and without any real contact. If you are given poor recommendations, you have no choice but to sift through mountains of content on your own until the model learns to accommodate your tastes more. This is bad for business as well as the consumer. Recently, large language models like ChatGPT have seen a significant rise in popularity due to their ease of use and wide range of knowledge. It has now become nearly …

Investigating The Effect Of Peephole Optimizations On Binary Code Differences, Xiaolei Ren

Computer Science and Engineering Dissertations

ABSTRACT: Binary diffing is a technique used to compare and identify differences or similarities in executable files without access to source code. The potential applications of binary diffing in various software security tasks, such as vulnerability search, code clone detection, and malware analysis, have generated a vast body of literature in recent years. One of the recurring themes in binary diffing research is the evaluation of its resilience against the impact of compiler optimization, which is the most common source of syntactic differences in binary code. Despite that most binary diffing tools claim that they are immune to compiler optimization, …

Deep Learning For Molecular Property Prediction, Hehuan Ma

Computer Science and Engineering Dissertations

Drug discovery has always been a crucial task for society, and molecular property prediction is one of the fundamental problem. It is responsible for identifying the target properties or severe side-effects, so that certain molecules can be selected as the candidates of drugs. Traditional methods usually conduct a series of biochemical experiments to test the molecular properties, which may take up to decades. Nowadays, this process can be facilitated due to the rapid growth of deep learning methods. I present my work toward solving this critical problem by utilizing deep learning techniques. My research study can be summarized in three …

Generative And Implicit Methods For 3d Point Cloud Processing, Mohammad Samiul Arshad

Computer Science and Engineering Dissertations

3D point clouds are a popular form of data representation with many applications in computer vision, computer graphics, and robotics. As the output of range sensing devices, point clouds have gained popularity with the current interest in self-driving vehicles. More formally, point clouds are an unordered set of irregular points collected from the surface of an object. Each point consists of a Cartesian coordinate, along with additional information such as an RGB color value and surface normal estimate. However, deep learning methods fall short in the processing of 3D point clouds due to the irregular and permutation-invariant nature of the …

Compact Representatives Of Databases And Responsible Data Management, Suraj Shetiya

Computer Science and Engineering Dissertations

With the advent of advanced computational models, we are being constantly judged by AI systems, complex algorithmic systems based on data that has been collected about us. These analysis are critical as they span many wide spread areas of our lives. For instance, these systems have been shown to find effective ways to fight back and make informed decisions during the COVID-19 pandemic. The wide spread use of these models naturally give rise to a few questions regarding explaining decisions that these systems have made, fairness questions in various parts of these systems. In this dissertation, we present three important …

Resource Provisioning For Data-Intensive User-Facing Applications, Huiyang Li

Computer Science and Engineering Dissertations

Data-intensive, User-facing Services (DUSes) such as web searching, digital marketing, online social networking, and online retailing are critical workloads in clouds and datacenters. Meeting stringent query tail-latency Service Level Objectives (SLO) for DUS queries is essential for optimal user experience and business success. However, achieving these objectives is challenging due to the scale-out nature of DUese workloads and the varying resource demands of queries with different fanouts. Additionally, the design and configuration options for clusters significantly impact query performance. In this dissertation, we present solutions of DUSes performance online and offline optimization. We highlight the importance of reducing query tail …

On-Line Environment Adaptation For User Performance Optimization, Subharag Sarkar

Computer Science and Engineering Dissertations

In today’s fast-paced and globally connected world, businesses are creating products with more significance to user personalization and customization. This has amplified the importance of capturing and learning user preferences as more information from users can lead to the designing and development of products that will improve user engagement and performance. Numerous algorithms based on collaborative filtering and recommender systems have been used to learn user preferences, but almost all of them require big datasets to train on. This creates a dependency on collecting more and more user information which might lead to ethical considerations and privacy concerns. To solve …

Acceleration Methods For Nonlinear Solvers And Application To Fluid Flow Simulations, Duygu Vargun

All Dissertations

This thesis studies nonlinear iterative solvers for the simulation of Newtonian and non- Newtonian fluid models with two different approaches: Anderson acceleration (AA), an extrapolation technique that accelerates the convergence rate and improves the robustness of fixed-point iterations schemes, and continuous data assimilation (CDA) which drives the approximate solution towards coarse data measurements or observables by adding a penalty term.

We analyze the properties of nonlinear solvers to apply the AA technique. We consider the Picard iteration for the Bingham equation which models the motion of viscoplastic materials, and the classical iterated penalty Picard and Arrow-Hurwicz iterations for the incompressible …

Cannabidiol Tweet Miner: A Framework For Identifying Misinformation In Cbd Tweets., Jason Turner

Electronic Theses and Dissertations

As regulations surrounding cannabis continue to develop, the demand for cannabis-based products is on the rise. Despite not producing the psychoactive effects commonly associated with THC, products containing cannabidiol (CBD) have gained immense popularity in recent years as a potential treatment option for a range of conditions, particularly those associated with pain or sleep disorders. However, due to current federal policies, these products have yet to undergo comprehensive safety and efficacy testing. Fortunately, utilizing advanced natural language processing (NLP) techniques, data harvested from social networks have been employed to investigate various social trends within healthcare, such as disease tracking and …

A Machine Learning Approach To Constructing Ramsey Graphs Leads To The Trahtenbrot-Zykov Problem., Emily Hawboldt

Electronic Theses and Dissertations

Attempts at approaching the well-known and difficult problem of constructing Ramsey graphs via machine learning lead to another difficult problem posed by Zykov in 1963 (now commonly referred to as the Trahtenbrot-Zykov problem): For which graphs F does there exist some graph G such that the neighborhood of every vertex in G induces a subgraph isomorphic to F? Chapter 1 provides a brief introduction to graph theory. Chapter 2 introduces Ramsey theory for graphs. Chapter 3 details a reinforcement learning implementation for Ramsey graph construction. The implementation is based on board game software, specifically the AlphaZero program and its …

Stability Of Cauchy's Equation On Δ+., Holden Wells

Electronic Theses and Dissertations

The most famous functional equation f(x+y)=f(x)+f(y) known as Cauchy's equation due to its appearance in the seminal analysis text Cours d'Analyse (Cauchy 1821), was used to understand fundamental aspects of the real numbers and the importance of regularity assumptions in mathematical analysis. Since then, the equation has been abstracted and examined in many contexts. One such examination, introduced by Stanislaw Ulam and furthered by Donald Hyers, was that of stability. Hyers demonstrated that Cauchy's equation exhibited stability over Banach Spaces in the following sense: functions that approximately satisfy Cauchy's equation are approximated with the same level of error by functions …

Development And Applications Of Novel And Practical Fluorination Reagents., Yuhao Yang

Electronic Theses and Dissertations

The fluorine (F) atom has distinctive properties such as the highest electronegativity, small size, low polarizability, and strong C–F bond strength. Not surprisingly, fluorinated organic compounds have garnered significant attention in the pharmaceutical, agrochemical, and material fields. Since organofluorides are very rare in nature, we need fluorination reagents to help us transfer fluorine into the organic molecules. In past decades, a vast number of fluorination reagents have been developed and many of them are commercially available now. However, there is still much room for the improvement of these reagents. Our target is to develop novel and practical fluorination reagents to …

New Methodologies For Sustainable Organic Synthesis In Water., Sudripet Sharma

Electronic Theses and Dissertations

Water is stable, benign, and green solvent. Its usage as a solvent in organic synthesis is significantly enhanced by micellar catalysis. However, replacing water as a reaction medium in organic synthesis is not sufficient to meet the sustainability challenges—excessive organic solvents are still required for product isolation and purification. Notably, solvents used in syntheses contribute to more than 80% of waste generation. In addition to solvents, the use of palladium in large amounts is also a problem for the future as it is a precious, low-abundance metal, and its supply is dwindling. Therefore, this dissertation highlights the various sustainable protocols …

Insights Into The Structural And Electronic Properties Of 2d Polar Sic/Gec Heterostructures And Asxp1−X Alloys., Kazi Jannatul Tasnim

Electronic Theses and Dissertations

Due to the unique structural and electronic properties along with the practical applications in current and near future, investigations about the group-IV graphene-like two-dimensional (2D) sheets have been accelerated. Among them, 2D SiC and GeC sheets are polar materials with in-plane charge transfer from Si (Ge) to C atoms. An interesting question is how the electrostatic force, triggered by such in-plane charge transfer, plays a role in stabilizing the vertical heterostructures formed by 2D SiC and GeC sheets beyond vdW interaction. To answer this question, we have systematically investigated, in my PhD research projects, the effects of the electrostatic interaction …

Towards Deposition Of Iron & Nickel Onto Cadmium Selenide/Cadmium Sulfide Nanorods, Rajib Nath

Masters Theses & Specialist Projects

Metal-semiconductor hybrids have been studied extensively as photocatalysts for the watersplitting reaction to generate hydrogen gas and oxygen gas to use as a renewable energy source. The semiconductor component converts light into electrochemical energy, while the metal component provides a site for chemical reactions with water. Here, the choice of metal can have a significant impact on the efficiency of the catalyst. Platinum efficiently catalyzes the watersplitting reaction and is therefore commonly used in metal-semiconductor hybrids to generate hydrogen. Platinum is very expensive, which motivates research into improving less costly metals like iron or nickel that do not have nearly …

On Phishing: Proposing A Host-Based Multi-Layer Passive/Active Anti-Phishing Approach Combating Counterfeit Websites, Wesam Harbi Fadheel

Dissertations

Phishing is the starting point of most cyberattacks, mainly categorized as Email, Websites, Social Networks, Phone calls (Vishing), and SMS messaging (Smishing). Phishing refers to an attempt to collect sensitive data, typically in the form of usernames, passwords, credit card numbers, bank account information, etc., or other crucial facts, intending to use or sell the information obtained. Similar to how a fisherman uses bait to catch a fish, an attacker will pose as a trustworthy source to attract and deceive the victim.

This study explores the efficacy of host-side APT (Anti-Phishing Techniques) based onWebsite features like Lexical, Host-Based, or Content-Based …

Simulating Strongly Coupled Many-Body Systems With Quantum Algorithms, Manqoba Qedindaba Hlatshwayo

Dissertations

The complexity of the nuclear many-body problem is a severe obstacle to finding a general and accurate numerical approach needed to simulate medium-mass and heavy nuclei. Even with the advent of exascale classical computing, the impediment of exponential growth of the Hilbert space renders the problem intractable for most classical calculations. In the last few years, quantum algorithms have become an attractive alternative for practitioners because quantum computers are more efficient in simulating quantum physics than classical computers. While a fully fault-tolerant universal quantum computer will not be realized soon, this dissertation explores quantum algorithms for simulating nuclear physics suitable …

Topology Optimization For Artificial Neural Networks, Justin Mills

Masters Theses & Specialist Projects

This thesis examines the feasibility of implementing two simple optimization methods, namely the Weights Power method (Hagiwara, 1994) and the Tabu Search method (Gupta & Raza, 2020), within an existing framework. The study centers around the generation of artificial neural networks using these methods, assessing their performance in terms of both accuracy and the capacity to reduce components within the Artificial Neural Network’s (ANN) topology.

The evaluation is conducted on three classification datasets: Air Quality (Shahane, 2021), Diabetes (Soni, 2021), and MNIST (Deng, 2012). The main performance metric used is accuracy, which measures the network's predictive capability for the classification …

Clickable Lipid Precursors As Chemical Tools For Imaging And Tracking Lipids, Christelle Anne Fernandez Ancajas

Doctoral Dissertations

The regulation of lipid metabolism is crucial for maintaining the human body, as disruptions in lipid homeostasis have drastic implications. While lipids are known for their roles as energy stores as well as for cellular compartmentalization, certain lipid classes can serve as signaling agents that govern cellular behavior and physiology or as biomarkers whose concentration and spatial organization impacts cell fate. Thus, dysregulation in these processes coincide with a variety of diseases and cancers. However, the ability to track lipids has been a long-standing challenge in the area of chemical biology since lipids are chemically diverse and undergo continuous interconversion …

Reduced Order Modeling And Analysis Of Cardiac Chaos, Tuhin Subhra Das

Doctoral Dissertations

Numerous physiological processes are functioning at the level of cells, tissues and organs in the human body, out of which some are oscillatory and some are non-oscillatory. Networks of coupled oscillators are widely studied in the modeling of oscillatory or rhythmical physiological processes. Phase-isostable reduction is an emerging model reduction strategy that can be used to accurately replicate nonlinear behaviors in dynamical systems for which standard phase reduction techniques fail. We apply strategies of phase reduction, or isostable reductions in biologically motivated problems like eliminating cardiac alternans to alleviate arrhythmia by applying energy-optimal, non-feedback type control solutions.

Cardiac fibrillation caused …

Simulating The Eccentricity Evolution Of Accreting Equal-Mass Binaries: Numerical Sensitivity To The Computational Domain Size And Grid Resolution, Zhongtian Hu

All Theses

With high resolution hydrodynamics simulations, we show that the optimal values of domain radius and grid resolution for the software Sailfish when simulating time-based eccentricity evolution of equal mass, non-circular accreting binaries in a circumbinary disk to be $r_{\rm out} \leq 15a$ and $\delta x / a \le 0.01 $. These values provide a useful guideline for optimizing the performance of simulation runs while maintaining scientific accuracy. Each artificial parameter is probed with 15 runs of 2000 orbits each.

Measurement Of Microplastics In A Freshwater Micro-Watershed, Cole Bowman

All Theses

The role of microplastics as an emerging contaminant can be complex to study because of the lack of standardization in the collection and analysis of microplastic particles. The purpose of this manuscript is to detail an iterative process of different collection methods in trying to understand microplastic deposition and transport in a freshwater micro-watershed through lab-based and field-based studies. A flume experiment was conducted to test the trapping efficiency of a sediment trap design at two different velocities (1.12 m/s and 2.24 m/s). Eight types of microplastics varying in morphology and density were introduced to the flume in order to …

Generalizable Deep-Learning-Based Wireless Indoor Localization, Ali Owfi

All Theses

The growing interest in indoor localization has been driven by its wide range of applications in areas such as smart homes, industrial automation, and healthcare. With the increasing reliance on wireless devices for location-based services, accurate estimation of device positions within indoor environments has become crucial. Deep learning approaches have shown promise in leveraging wireless parameters like Channel State Information (CSI) and Received Signal Strength Indicator (RSSI) to achieve precise localization. However, despite their success in achieving high accuracy, these deep learning models suffer from limited generalizability, making them unsuitable for deployment in new or dynamic environments without retraining. To …

Dinitroxides In Rapid Scan Electron Paramagnetic Resonance Imaging, Lukas B. Woodcock

Electronic Theses and Dissertations

Local tissue physiology is an important parameter in understanding disease behavior. Rapid Scan (RS) electron paramagnetic resonance (EPR) offers a unique, non-invasive tool for investigation of these so-called microenvironments through EPR Imaging (EPRI). Research into advancement of EPRI falls into many categories. Not least among those are advances in instrumentation and methodology. Presented here are updates to a benchtop EPRI instrument operating at 1 GHz targeted at pre-clinical EPRI applications. Newly developed methods for reducing RS-EPR background through inversion of the magnetic field are also demonstrated. EPR applications are limited in native biological systems due to the miniscule concentration of …

Do-It-Together: Informal Transformative Sustainability Education, Derek Brannon

Electronic Theses and Dissertations

The Climate Crisis is an urgent and inescapable reality students are thrust into. Learners must be prepared adequately for their futures, not only for their sakes but also because collective and transformative change is required. Transformative sustainability education provides one pathway to this transformation and focuses on radically altering students’ perceptions about the world and their agency in effecting change on ecological issues. The field of transformative sustainability education is emergent and thus is still fragmented, leaving gaps in the literature. Little research has been conducted on how informal and nonformal university spaces can be used to create transformative experiences …

Statistical Methods For Assessing Treatment Effects On Ordinal Outcomes And Selecting Optimal Treatment On Survival Outcomes Using Observational Data., Huirong Hu

Electronic Theses and Dissertations

This dissertation consists of two projects investigating statistical methods in causal inference and personalized medication using observational data. In the first project, we propose a parametric marginal structural ordinal logistic regression model (MS-OLRM) to assess treatment effects on ordinal outcomes. Average treatment effect (ATE) is used to measure the difference of the mean outcomes if all patients would have been treated compared with the outcomes if they would not have been treated. Many statistical methods have been developed to estimate ATE when the outcome is continuous or binary. The methodology on assessing treatment effect for an ordinal outcome is less …