Physical Sciences and Mathematics Commons^™

Effects Of The Gravity Gradient On The Path Of 1i/‘Oumuamua, Hannah R. Richardson

Poster Presentations

In October 2017, the asteroid 1I/’Oumuamua first passed into viewing range [1]. The asteroid is notable for being the first interstellar object to enter the solar system. 1I/’Oumuamua was also unusual in its geometry; it is thought to have an aspect ratio of 6:1 and a length of approximately 400 m [2] [3]. The asteroid was observed to experience a non-Keplerian acceleration estimated to be on the order of 1×10−6 m s-2 Several theories have been proposed for the cause of this acceleration, all of which are non-gravitational in nature: volatile outgassing, photon pressure, and solar winds [1][4]. However, none …

How Do Simulated Phishing Attacks Impact Cybersecurity Awareness And The Enhancement Of Security Protocols Among Faculty Members In A University Environment?, Navnoor Sandhu

University Honors Program Senior Projects

Phishing attacks are cyber threats where attackers deceive users into performing actions that compromise the user’s security and benefit the attacker. In 2024 alone, phishing attacks have resulted in estimated damages of around 800 million dollars [1]. In response, many institutions have implemented internal simulated phishing attacks to enhance their employees' cybersecurity awareness. This training exercise has been proven beneficial in improving cybersecurity awareness on an enterprise scale[4]. This study aims to evaluate the potential effectiveness of a simulated phishing attack within a university setting, which is a relatively unseen practice thus far. Universities, like other secure organizations, store sensitive …

Assessing Perceived Safety Of Non Motorized Travel With Virtual Reality, Vahid Balali, Sahand Fathi

Mineta Transportation Institute

Cycling is increasingly advocated as a healthier and more sustainable mode of transportation, as reflected in both scholarly literature and policy initiatives. Nonetheless, the escalation in bicyclist crash fatalities underscores deficiencies in extant roadway designs that inadequately safeguard these vulnerable users. A persistent challenge in the examination of bicyclist safety, behavior, and comfort is the paucity of comprehensive cycling data. To enhance understanding of cyclists' behavioral and physiological responses safely and efficiently, this investigation utilizes a bicycle simulator within an immersive virtual environment (IVE). Off-the-shelf sensors are employed to evaluate cyclists' performance metrics (speed and lane position) and physiological responses …

Graph Codes, Jacquelyn Franqui

Theses, Dissertations and Culminating Projects

The concept of graph codes, introduced in recent work by Alon, applies coding theory to graphs by defining codewords as graphs and measuring distances between them through structural differences. In ordinary coding theory, the distance between two words is the number of positions in which the two words differ. In graph codes, each word is a graph and the distance between two graphs is measured by structural properties of their difference. For a fixed graph H, an H-code is a collection F of graphs on vertex set [n] = {1, 2, . . . , n} such that the symmetric …

Inversion Numbers Of Oriented Graphs, Sam Harris

Theses, Dissertations and Culminating Projects

This thesis investigates recent results and conjectures regarding inversion numbers of oriented graphs. We define the inversion number of an oriented graph G as the minimum size of a decycling family of subsets of vertices of G. We focus on three areas: the maximum inversion number of a graph on n vertices, the inversion numbers of dijoins of two oriented graphs, and computational algorithms for deciding the inversion number. The main contribution of this thesis is a proposed construction of a graph with higher inversion number than that of any other currently known construction. We also provide explicit, rather than …

Reevaluating The Role Of Ruppia Maritima: Recruitment Dynamics And Habitat Use By Blue Crabs (Callinectes Sapidus) And Associated Benthic Fauna In A Mid-Atlantic Seagrass Community, Delaney St. Pierre

Theses, Dissertations and Culminating Projects

The value of seagrasses as essential fish habitat is well recognized, but limited data exist on the value of one particular species, Ruppia maritima (widgeon grass), as habitat for fish and invertebrates. During the summer of 2024, I evaluated R. maritima, Zostera marina (eelgrass) and mixed beds to assess their relative value as habitat in Barnegat Bay, New Jersey. Results from throw traps indicated significant monthly differences for pipefish, gobies, blue crabs, grass shrimp, and sand shrimp, driven by active recruitment events. When evaluating habitat type, we found no taxa that were significantly more abundant in Z. marina habitat as …

Thermal Biology Of The Eastern Treehole Mosquito Aedes Triseriatus (Diptera: Culcidae) And Other Vertivorous Dipterans, Kelly I. Zimmerman

Theses, Dissertations and Culminating Projects

Temperature plays a critical role in mosquito life cycle, behavior, and other ecological interactions. My dissertation analyzed how temperature affects egg hatch rates of the eastern treehole mosquito (Aedes triseriatus) and how amino acid substitutions in TRPA1 correlated with host finding through thermotaxis and the convergent evolution of vertebrate feeding/utilizing in Dipterans. As ectotherms, embryonic development and egg hatch rates are directly influenced by the water temperature mosquito eggs are oviposited into. Ae. triseriatus eggs do not hatch all at once, to avoid potentially high larval mortality rates due to their non-static oviposition sites. They engage in staggered egg hatching, …

Advancing Drug-Drug Interaction Prediction Using Multi-Modal Feature Integration With Graph Neural Networks, Ernest C. Chianumba

Theses, Dissertations and Culminating Projects

Pharmaceutical treatments are essential for managing medical conditions, but drug-drug interactions (DDIs) pose significant risks to patient safety and healthcare outcomes. This research integrates Knowledge Graphs and Graph Neural Networks to predict DDIs by exploring complex drug relationships. We construct a comprehensive knowledge graph using DrugBank data (1,000 drugs, 155,774 interactions) enriched with molecular features from PubChem. Our methodology introduces a novel multi-modal approach by integrating transformer-based embeddings (ChemBERTa, SPECTER, and SBERT) to create 1152-dimensional feature vectors that capture structural, biomedical literature, and semantic properties of drugs. Formulating DDI prediction as a link prediction task, we compare three Graph Neural …

Life Cycle Analysis Of Cosmetic Products -- Assessing Environmental Sustainability And Potential Impacts, Karina Magro Machado

Theses, Dissertations and Culminating Projects

The cosmetic industry has a significant environmental footprint due to its reliance on water, energy, petrochemical-derived ingredients, and plastic-based packaging. This study performs a cradle-to-grave Life Cycle Analysis (LCA) to evaluate the environmental impacts of three cosmetic products: CeraVe Daily Moisturizing Lotion, bareMinerals Gen Nude Powder Blush, and Gillette Foamy Regular Shave Cream. The analysis was conducted using OpenLCA software and free databases, modeling each product across raw materials, packaging, manufacturing, transportation, use and end-of-life phases. The results showed that the shave cream had the highest environmental burden to three out of the four categories, especially in consumption and carbon …

Don't Let Lead Lead On Environmental Justice: A Simulative Approach To Lead Remediation In The Big Data Era, Charles C. Knoble Ii

Theses, Dissertations and Culminating Projects

Environmental justice, as both a movement and a theoretical construct, continues to evolve in response to shifting societal, environmental, and technological conditions. This dissertation investigates the integration of big data, such as social media, remote sensing imagery, and internet search frequencies, into the identification, analysis, and remediation of environmental injustices. Framing environmental justice through the lenses of distributive and data justice, the project explores both the promises and pitfalls of using emergent data sources to enhance the spatial and temporal precision of environmental equity investigations. Through a combination of systematic literature review, spatial analysis, system dynamics simulation, and policy evaluation, …

How The Ramapough Turtle Clan Tribe Sustained Their Culture Through Ford's Environmental Exploitation, Tori Sutera

Theses, Dissertations and Culminating Projects

The Ramapough Turtle Clan Tribe is an Indigenous community composed of individuals residing mainly in Ringwood, New Jersey and a few surrounding boroughs. This land holds irreplaceable significance among the community, who, after facing colonial diaspora, have ultimately resided in Ringwood. However, due to the vast effects of the Ringwood Superfund site, this community has dealt with the loss of their people and their culture. Beginning in 1967, Ford Motor Company – partial owners of the site at that time – initiated the dumping of heavily toxic materials into Cannon and Peters Mines. This dumping continued until 1971, and the …

Analysis And Mathematical Recomposition Of The Art Of The Fugue, Joshua Cellar

Theses, Dissertations and Culminating Projects

The Art of the Fugue is a collection of 18 fugues and cannons written by Johann Sebastian Bach in the 1700s. Each piece starts with a single theme which is transformed, developed and mixed in fascinating mathematical combinations resulting in a distinctive musical style. In this paper, we use the method introduced in [7] to analyze 14 pieces from The Art of the Fugue. We focus on the variation of motifs from one piece to another as well as the complexities of mathematical transformations present throughout the entire collection. We also demonstrate how using maps of transformations and the rules …

Tracking Fall Migration With The Motus Wildlife Tracking System: The Fate Of Window-Struck And Captive-Raised Passerines, Cailin O'Connor

Theses, Dissertations and Culminating Projects

Many species of North American passerines migrate along the Atlantic flyway in the fall to reach winter habitats in the southeastern United States, the Caribbean, and Central and South America. Birds face many perils along their journeys including window strikes, which kill over one billion birds per year in the United States alone. Some birds survive the impact and may continue their migration. These birds may suffer delayed mortality or show aberrant migration due to injuries. This research seeks to understand if window-struck birds that initially survive bird-building collisions survive into the future and, if so, if they migrate effectively. …

The Influence Of Complex Terrain On The Turin, New York Tornado Of 2023, Alex D. Kramer

Atmospheric and Environmental Sciences Honors Program

Although uncommon as compared to other regions of the United States, the Northeast does experience significant tornados; those rated F/EF3 and above, of which some have had profound impacts on the region. Due to the diverse topography of the region, including its many northsouth oriented river valleys, most of these significant tornados traversed considerable changes in elevation throughout their lifetime. This study seeks to better understand the impacts of local topography on the intensity and overall progression of a significant tornadic event through using the most recent Northeast EF3: the Turin, NY tornado. With the consideration of previous studies involving …

Gaussian Process Regression And Nested Sampling For Planetary Parameter Prediction, Alexandro Balarezo

Physics

In this project, we implemented a Gaussian Process (GP) regression framework using MATLAB to model two planetary (Earth) parameters, the surface temperature and albedo, as functions of planetary rotation rate and insolation (the amount of sunlight impinging on the planet). We used simulation data from the NASA ROCKE-3D general circulation model developed by the NASA Goddard Institute for Space Studies (GISS). The GP model generates a joint multivariate Gaussian distribution that is entirely captured by a covariance matrix and the output of a training data set. The covariance matrix is determined by the input data and the three hyperparameters a …

Behind The Screen: Understanding The Human Firewall In Cybersecurity, Arun Venkitanarayanan

Emergency Preparedness, Homeland Security, and Cybersecurity

No abstract provided.

How Will Artificial Intelligence Impact The Roles, Skills, And Design Processes Of Ux Professionals In The Next 5 Years?, Olivia Behan

Informatics

Artificial intelligence (AI) is changing the way we think about user experience (UX) design. This thesis explores how AI could impact the roles, skills, and design processes of UX professionals over the next five years. The research conducted consists of a mixed-methods approach, combining an online survey administered through Qualtrics to 50 survey respondents and a case study, which included individually interviewing 3 UX professionals over Zoom, to gather data and personal insights. The results show that while AI has the power and potential to make some parts of UX work faster, like research analysis, prototyping, and automating redundant tasks, …

Development And Characterization Of Aso-Based Ribonuclease Targeting Chimera For The Degradation Of Cug Rna Repeat Expansion In Myotonic Dystrophy Type, Audrey Coons

Chemistry

Myotonic Dystrophy Type 1 is a multisystemic genetic disorder that primarily affects the muscles in the body leading to such pathologies as myotonia, muscle atrophy, insulin resistance and even neurological deficits. This disorder is caused by a series of CUG repeats in the 3’ untranslated region of the DMPK gene; symptoms appear after around 34 repeats. These repeats form foci when MBNL1 protein that deals with alternative splicing of many events in the body, forms aggregations around these repeats. These foci render the MBNL 1 proteins useless. There is no FDA approved therapeutic, but many RNA targeting therapeutics have been …

Compartmental Disaggregation: Bridging Simulation And Sampling Methods For Synthetic Population Data Generation, Dylan Mack

McKelvey School of Engineering Graduate Student Theses & Dissertations

As agent-based models (ABMs) grow increasingly widespread in public health, their associated challenges have become all the more significant. Lauded for their ability to capture population heterogeneity, nonlinear dynamics, and emergent behaviors, disease ABMs are also computationally expensive and often require detailed inputs that describe each agent at the individual-level, known as synthetic population data. Current approaches for synthetic population data generation generally fall into one of two categories: sampling or simulation. These methods are both feasible only under restricted conditions and suffer from challenges surrounding data availability and computing power. This thesis proposes compartmental disaggregation, an intermediate method for …

Laboratory Earthquakes In Heterogeneous, Meter-Scale Faults: Collaborative Research With Utah State University, And University Of Texas At Austin, Srisharan Shreedharan

Funded Research Records

No abstract provided.

Evaluation Of High Temperature Borehole Heat Exchangers For Thermal Energy Storage, Robert J. Mcdaniel

All Theses

The development of renewable power sources like solar panels and wind turbines is crucial to lowering greenhouse gas emissions and slowing the increase in global temperature. These sources are limited by the intermittency of power output depending on factors such as weather or time of day. Storing energy during periods of peak productivity improves the efficiency of renewable sources and makes them more competitive with fossil fuels. The excess energy can be stored underground as heat. At high enough temperatures (>150ºC) and discharge rates (>70 kW) the stored energy can be converted back into electricity. This turns the …

Reducing Stigma Around Neurodiversity Through The Use Of Celebratory Technology Ice Breakers In First-Year Undergraduate Classrooms, Briana Craig

Electrical Engineering and Computer Science (MS) Theses

Celebratory technology for Neurodiversity is a new paradigm in the field of human computer interaction; it focuses on reducing stigma surrounding neurodivergent labels and behaviors. Celebratory technology aims to highlight the strengths of neurodiversity rather than fixing socially undesired traits, shifting the responsibility for change from neurodivergent individuals to society's attitudes. Stigma reduction can be accomplished through providing high quality interactions, where anyone can meet and learn about positive traits in others as well as learn of interests' others have in common, thus reframing neurodivergence as inclusion in human diversity rather than a condition to be stigmatized or objectified. This …

From Seasonality To Causality: Understanding Urban Water Usage Using Statistical And Machine Learning Models, Kelsey Hawkins

Electrical Engineering and Computer Science (MS) Theses

This study examines the relationship between climate conditions and residential water usage, focusing on how seasonal and environmental changes influence water consumption. Utilizing data from over 100,000 households across three micro-climate zones for over a five-year period, we apply statistical analysis and machine learning techniques to assess the impact of temperature, precipitation, evapotranspiration, and location on water usage. By integrating climate and billing data, this research provides a data-driven approach on water usage behaviors in Irvine, CA, in collaboration with Irvine Ranch Water District (IRWD).

Our analysis utilizes time series modeling, including a Seasonal Autoregressive Integrated Moving Average (SARIMA) and …

Implementation Of Residual Tandem Neural Networks For Photonic Inverse Design, Ponthea A. Zahraii

Electrical Engineering and Computer Science (MS) Theses

Deep-learning approaches can greatly benefit the modeling and design of nanophotonic and optical structures. Traditional full-wave simulations are time and resource-intensive, which can act as a bottleneck in photonic design. On the other hand, deep-learning approaches for designing the response of nanophotonic geometries can be computationally inexpensive and produce accurate and efficient results. In this project, we specifically investigate the case of optical forces near meta-structures. We propose using an inverse design approach with residual blocks to account for the deep nature of this architecture and inherently address the non-uniqueness problem. A tandem approach, which consists of two interconnected models, …

An Analysis Of Bias Towards Women In Large Language Models Using Likert Scale Evaluations, Sarah T. Fieck

Electrical Engineering and Computer Science (MS) Theses

Closed-source large language models (LLMs) developed by large technology companies continue to grow in popularity. However, ethical conversations surrounding the safety of model outputs have been a prominent topic of discussion. This project aims to assess three leading closed-source LLMs: OpenAI’s ChatGPT, Google’s Gemini, and Anthropic’s Claude, to analyze how their outputs perform when treated as a subject of several psychological evaluation scales measuring biased behaviors against women. The Ambivalent Sexism Index, Modern Sexism Scale, and Belief in Sexism Shift evaluations were used to get descriptions of how the LLMs respond to traditional and modern prompts involving sexism and gender …

A Narrative-Focused Machine Learning Approach To Predicting Feature Film Success, Arisa T. Trombley

Electrical Engineering and Computer Science (MS) Theses

For decades, the field of film production has been driven by marketability, and it has relied on gut feelings and subjectivity to produce feature films. The analysis of the relationship between a screenplay’s narrative and a film’s success has been widely overlooked due to the challenges involved in data acquisition and complexity. This study investigates the predictive power of narrative structure on film success and aims to build evidence for hypothesized narrative principles. The results suggest that narrative structural elements exhibit moderate predictive power, with strong support for the alignment of the 2nd act crucial moments and the 2nd act …

Jwst Reveals The Diversity Of Nuclear Obscuring Dust In Nearby Agn: Nuclear Isolation Of Miri/Mrs Data Cubes And Continuum Spectral Fitting, Omaira González-Martín, Daniel J. Díaz-González, Mariela Martínez-Paredes, Almudena Alonso-Herrero, Enrique López-Rodríguez, Begoña García-Lorenzo, Cristina Ramos Almeida, Ismael García-Bernete, Donaji Esparza-Arredondo, Sebastian F. Hoenig, Santiago García-Burillo, Chris Packham, Nancy A. Levenson, Alvaro Labiano, Miguel Pereira-Santaella, Francoise Combes, Anelise Audibert, Erin K.S. Hicks, Lulu Zhang, Enrica Bellocchi, Richard I. Davies, Laura Hermosa Muñoz, Masatoshi Imanishi, Claudio Ricci, Marko Stalevski

Faculty Publications

We investigate the capabilities of the mid-infrared instrument (MIRI) of JWST to advance our knowledge of active galactic nucleus (AGN) dust using the spectral fitting technique on an AGN collection of 21 nearby (z < 0.05) AGN (7 type-1 and 14 type-2) observations obtained with the medium resolution spectroscopy (MRS) mode. This collection includes publicly available AGN and data from the collaboration of Galactic Activity, Torus, and Outflow Survey (GATOS). We developed a tool named MRSPSFisol that decomposes MRS cubes into point-like and extended contributions. We found statistically good fits for 12 targets with current AGN dust models. The model that provides good fits (χ²/dof< 2) for these 12 targets assumes a combination of clumpy and smooth distribution of dust in a flare-disc geometry where the dust grain size is a free parameter. Still, two and one AGN statistically prefer the disc + wind and the classical clumpy torus model, respectively. However, the currently available models fail to reproduce 40 per cent of the targets, likely due to the extreme silicate features not well reproduced by the models and signatures of water-ice and aliphatic hydrocarbon absorption features in most targets. New models exploring, for instance, new chemistry, are needed to explain the complexity of AGN dust continuum emission observed by JWST.

2-Segal Sets And Pseudomonoids In The Bicategory Of Spans, Sophia E. Marx, Rajan Amit Mehta

Mathematics Sciences: Faculty Publications

In this survey article, we give an introduction to the notion of a 2-Segal set and prove that 2-Segal sets are equivalent to pseudomonoids in the bicategory of spans. The proof utilizes graphical techniques for 2-Segal sets and spans that should be useful in more general settings.
There are procedures for obtaining an associative algebra from a 2-Segal set (satisfying finiteness conditions). We describe these procedures and give several examples of algebras arising from 2-Segal sets.
Wherever possible, we avoid higher category theory so as to make the paper accessible to a wide audience.

Survey On Application Of Large Language Models In Network Attack And Defense, Prisha Purohit

Honors Theses

The emergence of Large Language Models (LLMs) has significantly transformed the technological and cybersecurity landscape, introducing both unprecedented opportunities and formidable challenges. With the public release of ChatGPT in 2022, LLMs have gained global prominence, redefining natural language processing capabilities and enabling advancements across various fields. In cybersecurity, these models represent a dual-use technology: while they offer powerful tools for threat detection, automated analysis, and security training, they also pose risks when leveraged by malicious actors for phishing, social engineering, and the creation of evasive malware. This thesis presents a comprehensive literature review exploring the dual roles of LLMs in …

Synthesis Of Single Chain Polymer Nanoparticle Networks By Reinitiating Raft Polymerization, Dallas Donovan

Honors Theses

Hydrogel materials, which are polymer networks comprised mostly of water, hold significant promise for biomedical applications due to their compatibility with biological systems. Conventional hydrogel materials are often brittle and weak, but most applications in biomedical systems require materials to be strong and tough. The topology of a polymer network dictates its mechanical properties. An important strategy for designing tougher hydrogels is the release of stored length, such as from the unfolding of polyprotein cross-linkers. Inspired by the success of the strategy, we report progress towards a fully synthetic design using single chain nanoparticles (SCNPs) into a hydrogel. SCNPs, which …