Physical Sciences and Mathematics Commons^™

Patterns Of Interactions In Human-Machine Teams, Kazuhiko Momose

Theses and Dissertations

Increasingly capable machines, including Artificial Intelligence (AI) agents are playing a more important role in a wide range of applications, including human daily activities and safety-critical systems. They can benefit even more when humans and such machines agents work together as a team by leveraging each other's strengths and complementing each other to enhance overall performance. To design high-performing teams, it is critical to analyze the team dynamics and understand how humans and machines interact with each other. Collaboration, Coordination, and Cooperation (3Cs) are terms typically used to describe the behavior of teams. However, these terms tend to be used …

The Application Of High-Resolution Mass Spectrometry For The Analysis Of Biopolymers, Metabolites, And Biologically Relevant Small Molecules, Christ Duc Tran

Graduate Doctoral Dissertations

High-resolution mass spectrometry (HRMS), as its name suggests, possesses high resolving power that enables the separation of ions with very close mass values. This is particularly beneficial for analyzing complex samples where numerous compounds may have similar masses, as it helps prevent signal overlaps and ensures an accurate spectral analysis. The current work explores the diverse applications of high-resolution mass spectrometry in oligonucleotide research, organic synthesis and medicinal chemistry. Oligonucleotide research: Chapters 2-5 present the research results from studies that employed ultra-high-performance liquid chromatography coupled with high-resolution mass spectrometry (UHPLC-HRMS) to understand the pharmacokinetics of RNA interference (RNAi) therapeutics. The …

Machine Learning Optimized Depolymerization Of Pet (Polyethylene Terephthalate) Via Glycolysis, Mehwash Aamir

Theses and Dissertations

Over 90% of the approximately 1 million PET bottles sold every minute end up in landfills or oceans, where they can persist for centuries. Plastic pollution urgently needs sustainable management and recycling solutions to mitigate the environmental impact of PET waste. From all techniques to recycle plastic waste, catalytic glycolysis stands out for its rapid reaction time, high monomer yields, lower costs, and enhanced durability.

In this work glycolysis of PET was evaluated under microwave conditions using 1,5,7-Triazabicyclo [4.4.0] dec5-ene (TBD) and 1,8-Diazabicyclo [5.4.0] undec-7-ene (DBU) as catalysts, being DBU as the best catalyst for further analysis. The effect of …

Classifying Supersonic Frequencies For Active Acoustic Side-Channel Exploitation, Destin Hinkel

Graduate Theses and Dissertations (2019 - present)

Computing side-channel research explores the manner in which physical emanations from systems can be used to reconstruct data. Acoustic side-channels are those physical emanations that produce a sonic frequency that is subsonic, supersonic, or considered in the range of human hearing [1]. Acoustic side-channel attacks (SCAs) are typically performed passively: a listening device captures aural frequencies from a machine via a microphone that are transmitted to the attacker for analysis [1]–[3]. Machine learning models have been presented to classify individual keystrokes according to variations in acoustic frequency [4]. Furthermore, the SonarSnoop framework presents a novel active approach that involves both …

Hybrid Deep Learning-Based Model For Eclipse Attack Detection On Ethereum Network, Dhanasak Bhumichai

Graduate Theses and Dissertations (2019 - present)

An eclipse attack is a significant cyber threat targeting the network layer of blockchain platforms. Detecting eclipse attacks is challenging for several reasons. First, there are no available datasets for training and testing models. Second, comprehensive studies identifying features to detect eclipse attacks are lacking. Additionally, the amount of eclipse network traffic is much smaller than that of normal network traffic, which leads to imbalanced samples. Moreover, the characteristics of eclipse network traffic closely resemble those of normal traffic, causing overlapping samples, which makes it challenging for traditional classifiers to learn how to identify eclipse attacks. To address these challenges, …

Recovery Resiliency Of Interdependent Power Systems Infrastructure Subject To Extreme Events, Partha P. Sarker

Graduate Theses and Dissertations (2019 - present)

When Hurricane Maria struck the island of Puerto Rico on September 20, 2017, it devastated the island’s aging power systems infrastructure and inflicted an island-wide power outage that left Puerto Rico in total darkness for an entire week before the system slowly started to recover. This unprecedented failure of the critical power systems infrastructure exacerbated the failure of other critical infrastructures or lifeline systems of the island. This research explores and quantifies the relationships or interdependencies that exist between the power systems and other critical infrastructure systems by investigating the post-hurricane recovery data of these lifeline systems. Subsequently, the research …

D-Optimal Joint Best Linear Unbiased Predictors In Progressively Type-Ii Ordered Statistics, Tamim Alam

Open Access Theses & Dissertations

Reliability and life-testing experiments play a crucial role in understanding the longevity and performance of systems and components, particularly in high-stakes applications such as engineering, manufacturing, and quality control. In this thesis, we focus on the prediction of future unobserved failure times by employing joint predictors based on progressively Type-II censored data obtained from such life-testing experiments. Specifically, we derive explicit analytical expressions for the joint best linear unbiased predictors (BLUPs) of two future order statistics under the D-optimality criterion. The derivation involves minimizing the determinant of the variance-covariance matrix of the predictors within the context of progressively Type-II censored …

Thermal Inequity Along The Us-Mexico Border: An Analysis Of El Paso, Texas, Mia Alexandra Trevino

Open Access Theses & Dissertations

The Urban Heat Island effect (UHI) combined with rising average global temperatures invariably results in thermal inequality, the unequal distribution of temperature patterns by different socioeconomic and sociodemographic groups, resulting in an array of negative public health impacts. This thesis research focused on the historical factors that contribute to UHI and tree cover in historically underserved neighborhoods in El Paso, Texas. The impact of maps from 1933-1954 created by the Home Ownerâ??s Loan Corporation (HOLC), a federal selective lending program, resulted in decades of disinvestment and inequality especially in redlined areas. Geospatial analyses of environmental and socioeconomic indicators such as …

Optimization And Purification Of Magnesium Borides Fabricated By Combustion Synthesis And By High-Temperature Sintering, Miguel Joaquin Camarena

Open Access Theses & Dissertations

Hydrogen as a fuel provides several benefits over the use of fossil fuels; however, one challenge in utilizing hydrogen as an energy carrier revolves around its storage. Achieving sufficient volumetric hydrogen density in a storage solution will facilitate hydrogenâ??s adoption for use in both stationary and mobile applications. Solid-state hydrogen storage provides a promising pathway to solving this problem. However, the hydrogenation of these materials is characterized by slow kinetics and extreme thermodynamic conditions. Magnesium borohydride (Mg(BH4)2) is a promising material in hydrogen storage due to its reversible properties and a theoretical hydrogen capacity of 14.9 wt.%. To synthesize this …

Functionalized Carbon Quantum Dots: A Promising Nanomaterial For Investigating Their Potential In Neurodegenerative Disease Treatment, Sherin M. El Morsy

Open Access Theses & Dissertations

Neurodegenerative diseases such as Parkinson's Disease (PD), Alzheimer's Disease (AD), and Huntington's Disease (HD) remain incurable, despite extensive research into therapeutic development. In the United States of America, the annual cost of PD and AD in terms of patient care and lost productivity is approximately $200 billion. Consequently, there is a critical and unaddressed need for the development of innovative drugs and drug delivery systems that can decelerate, stop, or ideally reverse neurodegenerative diseases. The dissertation presented here focuses on devising strategies to target PD through multiple mechanisms, including the inhibition of protein aggregation and the reduction of oxidative stress. …

Redefining Approaches For Measuring Landscape Subsidence And Permafrost Degradation In Arctic Tundra Environments, Tabatha Lynn Fuson

Open Access Theses & Dissertations

As climate change accelerates in the Arctic, the degradation of permafrost is leading to significant landscape transformation in tundra landscapes. This dissertation investigates the multifaceted responses of permafrost systems to warming, focusing on the dynamics of surface elevation changes and active layer thickness (ALT) across the North Slope of Alaska. In this study, I explore the capacity of repeat Terrestrial Laser Scanning (TLS) technology for modeling tundra features and detecting surface subsidence, specifically how different climate and landscape conditions during scanning impact TLS model precision. We also compare TLS model precision estimates to TLS model accuracy by comparing elevation values …

Assessing Sedimentation Impact Through Dem, Point Cloud, And Discharge Analysis, Shandell Thomas

Open Access Theses & Dissertations

This study focused on five arroyos flowing into the Rio Grande, in the stretch between Caballo Dam and Las Cruces, New Mexico. Drone imagery was acquired from study areas in each arroyo. Photogrammetry was used to create high-resolution digital elevation models (DEMs), point clouds, drone imagery and potential discharges were acquired for each arroyo. Investigation of seven different methods resulted in the selection of the Terrain Ruggedness Map (TRM) as a predictor of surface roughness, along with high-resolution DEMâ??s to illustrate small and low-relief channel features. The five arroyos with varying sediment sizes and characteristics were studied to understand how …

Rockets, Rovers, And Rocks, Oh My!, Tara Lynn Sweeney

Open Access Theses & Dissertations

This body of work undertakes three distinct projects, all with the ultimate goal of improving the future efforts of human space exploration.Chapter 2 is a seismic analysis of rocket launch and landing operations. Being able to identify and understand anthropogenically induced seismic signals in comparison to naturally occurring seismic signals is an important step in characterizing and monitoring both types of signals on the Moon. Relatively few terrestrial studies have been performed to explore this, but there is a growing opportunity to record, discern, and understand the differences between anthropogenic and naturally occurring seismic signals due to the increasing pace …

Enhancing Predictive Accuracy In Noisy Data: A Robust Gradient Boosting Approach, Gabriela Alexa Acuna

Open Access Theses & Dissertations

This thesis aims to enhance the gradient boosting technique, a well-known machine learning method, in a regression setup. Gradient boosting techniques implement sequential weak learners, in this case, shallow trees that contribute to the model with a small percentage. The traditional gradient boosting approach uses regression trees that choose thresholds based on minimizing variance and makes predictions based on the mean of the target variable for the observations contained within each node. The residual sum of squares (RSS) and mean metrics are sensitive to outliers, which makes the model's predictions less robust. Outliers influence the predictions, resulting in a model …

Towards Robust And Fair Vision Learning In Open-World Environments, Thanh-Dat Truong

Graduate Theses and Dissertations

The rapid increase of large-scale data and high-performance computational hardware has promoted the development of data-driven machine vision approaches. Advanced deep learning approaches have achieved remarkable performance in various vision problems and are closing the capability gap between artificial intelligence (AI) and humans. However, towards the ultimate goal of AI, which replicates human ability in visual perception tasks, the machine vision learning methods still need to address several ill-posed challenges. First, while the current vision learning methods often rely on large-scale annotated data, the data annotation process is a costly and time-consuming process. Second, the unfaired predictions produced by vision …

Neural Network Architecture Search Enabled Wide-Deep Learning (Nas-Wd) Integrated Hyperspectral Imaging Understanding For Woody Breast In Poultry Processing, Chaitanya Kumar Reddy Pallerla

Graduate Theses and Dissertations

The development and implementation of a Wide & Deep (WD) learning model tailored for classification and regression tasks utilizing spectral data provides a robust solution to evaluate woody breast (WB) conditions in poultry fillets. This process begins with thorough data preprocessing, which includes loading spectral and classification datasets, imputing missing values with medians, and splitting the data into training and testing sets to ensure rigorous model evaluation. The WD model architecture integrates wide linear models and deep neural networks to harness the strengths of both approaches. The wide component excels at memorizing sparse feature interactions, while the deep component captures …

Microwave-Assisted Green Synthesis Of Spiroindolinopyranopyrazoles, Esther Owusu

Theses and Dissertations

Green Chemistry, usually known as sustainable chemistry, is widely implemented worldwide to safeguard human health and the environment. Recent investigations in organic synthesis and chemical transformation have demonstrated that green chemistry techniques are significantly reducing both chemical waste and reaction time. In order to fulfill this ecological requirement, it is crucial to lessen the utilization of perilous solvents and noxious chemicals, while also creating innovative reaction methods that decrease the production of trash. The implementation of such methodologies can greatly enhance the field of green chemistry. A more environmentally friendly synthetic method was utilized to generate spiro chemicals and their …

Policies And Price Controls On The Research And Development Of Orphan Drugs In The United States And The European Union, Bena Pearl Filipczak Smith

Master's Theses

There is substantive literature surrounding the impact of price controls on the research and development (R&D) of new pharmaceutical products. The European Union (EU) and United States (US) are often studied in contrast to examine the influence of price controls as the US has fewer pharmaceutical price controls than the EU.

We find moderate evidence that the US spent more on annual domestic pharmaceutical R&D than the EU between 2004 and 2021, on average, before and after adjusting for GDP growth per capita and year. We find strong evidence that the US increased annual domestic R&D spending at a faster …

Fitting Quality Of Nmr Relaxation Data To Differentiate Asphalt Binders, Rebecca M. Herndon, Kevin Lai, Magdy Abdelrahman, Klaus Woelk

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Asphalt binder performance grades (PGs) are important metrics in designing pavements for effective transportation infrastructure. the PG system relies on the binder's stiffness and is determined through energy- and time-intensive physical testing. Physical properties, like stiffness, can also be determined by spin–lattice NMR relaxometry, a non-destructive chemical method. NMR relaxometry can quantify the molecular mobility of materials by determining relaxation times from exponential decays of excited nuclear magnetization. While relaxation times have been used to determine physical properties of materials, a quantitative relation to the PG grades of asphalt binder is yet to be established. in this study, T1 NMR …

This Year In Space: The Astounding Astronomical Events Of 2024, Celeste Wicks

The Synapse: Intercollegiate science magazine

No abstract provided.

Issue 41

The Synapse: Intercollegiate science magazine

No abstract provided.

The Care Crisis: The Neurology Of Dementia And International Solutions, Sophie Paton

The Synapse: Intercollegiate science magazine

No abstract provided.

Will My Celsius Addiction Kill Me?: The Thermogenic Drink And Its Impact On Nutrition And Metabolism, Katie Johnstone

The Synapse: Intercollegiate science magazine

No abstract provided.

Genes And Zzz's: The Genetic Variations Of Sleep Disorders, Ananya Sivasubramaniam

The Synapse: Intercollegiate science magazine

No abstract provided.

Call For Contributors

The Synapse: Intercollegiate science magazine

No abstract provided.

Puzzle Corner

The Synapse: Intercollegiate science magazine

No abstract provided.

Invisible Intruders: The Growing Presence Of Microplastics And Its Effects On The Brain, Megan Carlson

The Synapse: Intercollegiate science magazine

No abstract provided.

Digging Up A New Era In Fertilizer: Investigating The Potential Of Electron Bifurcation In Ammonia Synthesiss, Ella Wurtzbacher

The Synapse: Intercollegiate science magazine

No abstract provided.

Peeling Back Allergies: Punica Granatum And Its Various Bene.Its, Mina Stalhamer, Haimanot Assefa

The Synapse: Intercollegiate science magazine

No abstract provided.

On A Color Wheel: Adhd Under The Social Model's Scope, Ben Tran

The Synapse: Intercollegiate science magazine

No abstract provided.