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Articles 2101 - 2130 of 291657

Full-Text Articles in Physical Sciences and Mathematics

A Bifurcation Theorem And Its Application To Discrete-Time Models In Ecology And Epidemiology, Jenita Jahangir Jun 2026

A Bifurcation Theorem And Its Application To Discrete-Time Models In Ecology And Epidemiology, Jenita Jahangir

Doctoral Dissertations

Matrix models are useful for modeling populations or diseases that involve discrete developmental stages, multiple stages of infection, and interactions among species. To study the coexistence dynamics in matrix models, we extend a bifurcation theorem for resident-invader host-parasitoid type populations by allowing every block of the projection matrix, depending on the bifurcation parameter and the off-diagonal blocks, to be nonzero. As an application, in the first part of the dissertation, we propose a discrete-time host-parasitoid model with stage structure in both species. For this model, we establish conditions for the existence and global stability of the extinction and parasitoid-free equilibria. …

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Fairness-Aware And Efficient Federated Learning Frameworks For Heterogeneous Systems, Simin Javaherian Jun 2026

Fairness-Aware And Efficient Federated Learning Frameworks For Heterogeneous Systems, Simin Javaherian

Doctoral Dissertations

Federated Learning (FL) enables decentralized clients to collaboratively train machine learning models without sharing raw data, making it a promising paradigm for privacy-preserving intelligence across large-scale, heterogeneous systems. However, practical FL environments face significant challenges arising from variations in client resources, participation patterns, client behavior, and data distributions. These challenges often lead to inefficiency, unbalanced contributions, and unfairness, ultimately degrading model performance and discouraging long-term client participation. This dissertation advances the state of FL by developing a unified suite of fairness-aware and efficiency-driven frameworks tailored for heterogeneous environments. We investigate fairness from multiple perspectives, including client selection, contribution weighting, and …

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Strang-Type Exponential Integrators For Stiff Reaction-Diffusion Systems, Saburi Tolulope Rasheed Jun 2026

Strang-Type Exponential Integrators For Stiff Reaction-Diffusion Systems, Saburi Tolulope Rasheed

Doctoral Dissertations

Reaction-diffusion systems, as examples of semilinear parabolic partial differential equations, have played significant roles in the mathematical modeling of physical, chemical, and biological processes. Several reaction-diffusion systems typically do not have exact solutions in closed form, and numerically solving them also comes with challenges due to the presence of the nonlinear local interaction/chemical reaction dynamics representing the reaction term, coupling between components, multidimensionality of the diffusion operator, and stiffness of the diffusion and/or reaction terms. Wederive and analyze several second-order accurate exponential integrators of the Strang type for the time discretization of stiff reaction-diffusion systems. We utilize the finite difference …

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The Interplay Of Seasonality, Evolution, And Density-Dependence In Discrete-Time Predator-Prey Dynamics, Narendra Pant Jun 2026

The Interplay Of Seasonality, Evolution, And Density-Dependence In Discrete-Time Predator-Prey Dynamics, Narendra Pant

Doctoral Dissertations

We extend the discrete-time mathematical models developed in (Ackleh et al., 2019) and (Ackleh et al., 2024) to account for seasonal prey reproduction and build a class of discrete-time predator-prey seasonal models. Each model distinguishes between breeding and non-breeding seasons, representing prey reproduction as a periodic function of period 2. Altogether, three different models are analyzed. In the first part, we extend the predator-prey model from (Ackleh et al., 2019) to incorporate seasonality. We study the resulting dynamics and show that when the inherent reproduction number of the prey and the invasion reproduction number of the predator are larger than …

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Building And Restoring Trust In Deep Learning: From Multimodal Sensing To Generative Synthesis And Model Integrity, Liqun Shan Jun 2026

Building And Restoring Trust In Deep Learning: From Multimodal Sensing To Generative Synthesis And Model Integrity, Liqun Shan

Doctoral Dissertations

Deep learning has become a foundational technology for modern intelligent systems used in sensing, authentication, media generation, and automated decision-making. As these systems are increasingly deployed in security- and privacy-sensitive settings, ensuring their trustworthiness has become a critical challenge. Yet deep learning models remain vulnerable to spoofed sensory inputs, synthetic media, and malicious behaviors hidden within trained networks. These vulnerabilities undermine reliability and raise serious concerns about whether such systems can be trusted under adversarial and deceptive scenarios. This dissertation investigates how to build and restore trust in deep learning across three tightly connected dimensions: multimodal sensing, generative authenticity, and …

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Learning And Predicting The Performance Of Gradual Type System, Mohammad Wahiduzzaman Khan Jun 2026

Learning And Predicting The Performance Of Gradual Type System, Mohammad Wahiduzzaman Khan

Doctoral Dissertations

Gradual typing reconciles the complementary strengths of static and dynamic typing by allowing programmers to incrementally introduce type annotations while preserving the flexibility of dynamically typed code. This approach improves reliability, documentation, and tooling support without sacrificing rapid prototyping. To ensure soundness, gradual type systems enforce annotations through runtime checks, typically implemented via cast insertion. Although these checks guarantee correctness, they can introduce substantial and highly variable runtime overhead, making performance prediction and optimization a central challenge for practical adoption. Prior work has largely focused on coarse-grained (macro-level) configurations, where entire modules are either fully typed or untyped. While such …

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Investigating The Distribution And Origin Of Pitted Mounds On Mars Using Machine Learning-Based Mapping And Integrated Geological Analysis: Application To Isidis Planitia, Precious Batubo Jun 2026

Investigating The Distribution And Origin Of Pitted Mounds On Mars Using Machine Learning-Based Mapping And Integrated Geological Analysis: Application To Isidis Planitia, Precious Batubo

Doctoral Dissertations

Pitted mounds are widespread landforms across the northern plains of Mars, yet their origin remains uncertain. These features have been interpreted as possible expressions of subsurface fluid activity, including sedimentary volcanism, magmatic processes, or other fluid-assisted mechanisms. Determining their distribution, morphology, and geology is therefore important for understanding the evolution of subsurface hydrological processes and the planet’s potential for habitability. However, the large spatial extent of mound-bearing terrains makes comprehensive manual mapping impractical. This dissertation presents an automated approach to mound detection using Faster Region-Based Convolutional Neural Network (Faster R-CNN) from high-resolution Context Camera (CTX) images including morphometric and mineralogical …

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Mgrre_Thinsections_Mgrre-147_7, Mgrre Jun 2026

Mgrre_Thinsections_Mgrre-147_7, Mgrre

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No abstract provided.

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Mgrre_Thinsections_Mgrre-147_2, Mgrre Jun 2026

Mgrre_Thinsections_Mgrre-147_2, Mgrre

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Mgrre_Thinsections_Mgrre-147_8, Mgrre Jun 2026

Mgrre_Thinsections_Mgrre-147_8, Mgrre

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Mgrre_Thinsections_Mgrre-147_3, Mgrre Jun 2026

Mgrre_Thinsections_Mgrre-147_3, Mgrre

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Mgrre_Thinsections_Mgrre-147_1, Mgrre Jun 2026

Mgrre_Thinsections_Mgrre-147_1, Mgrre

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Mgrre_Thinsections_Mgrre-147_9, Mgrre Jun 2026

Mgrre_Thinsections_Mgrre-147_9, Mgrre

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Mgrre_Thinsections_Mgrre-147_10, Mgrre Jun 2026

Mgrre_Thinsections_Mgrre-147_10, Mgrre

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Emerging Catalysts And System Designs For High-Current-Density Co2 Electroreduction To Multicarbon Fuels And Chemicals Toward Industrial-Scale Applications, Godwin Uche Edor Jun 2026

Emerging Catalysts And System Designs For High-Current-Density Co2 Electroreduction To Multicarbon Fuels And Chemicals Toward Industrial-Scale Applications, Godwin Uche Edor

Masters Theses

Electrochemical CO2 reduction (eCO2RR) offers a sustainable route to convert CO2 into value-added fuels and chemicals, particularly multicarbon (C2+) products due to their higher energy density and economic value compared to C1 counterparts. Industrial adoption of eCO2RR technology is hindered by the difficulty in stably reaching superior Faradaic efficiency (FE) for C2+ products at ≥ 200 mA cm-2 at low applied overpotential due to sluggish C–C coupling kinetics, competing reactions, and catalyst instability. Hence, we examine the recent advances in eCO2RR catalyst engineering strategies, such as nanostructural and electronic modifications of Cu-based catalysts (e.g., interfacial, surface, facet, and defect engineering, …

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Micro-Hyperspectral Imaging Of Phytoplankton Enables Deconvolution Of Mixed Communities For Spaceborne Hyperspectral Remote Sensing, Chisom Okwuchi Emeghiebo Jun 2026

Micro-Hyperspectral Imaging Of Phytoplankton Enables Deconvolution Of Mixed Communities For Spaceborne Hyperspectral Remote Sensing, Chisom Okwuchi Emeghiebo

Masters Theses

Characterizing phytoplankton diversity is critical for large-scale biodiversity monitoring and harmful algal bloom (HAB) detection. Here, we present a micro hyperspectral imaging method to characterize reflectance signatures, for the first time across major phytoplankton groups. Spectral variability among taxa in laboratory cultures is interpreted using algal pigment and absorption analyses, demonstrating that pigment composition and absorption govern reflectance features. Chlorophytes and cryptophytes exhibit distinct spectral signatures and are readily distinguishable, whereas diatoms and dinoflagellates show greater spectral similarity, with differentiation relying on subtle reflectance features associated with chlorophyll c₁c₂ near ~463 nm and within 620–650 nm. We further applied this …

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Linking Greenhouse Gas Fluxes And Plant Responses To Saltwater Intrusion Events Using Remote Sensing, Madeline Jean Moore Jun 2026

Linking Greenhouse Gas Fluxes And Plant Responses To Saltwater Intrusion Events Using Remote Sensing, Madeline Jean Moore

Masters Theses

As sea level rise and coastal subsidence increase coastal Louisiana's vulnerability to saltwater intrusion (SWI) events, accurate and rapid monitoring of vegetation responses to these events is becoming increasingly important. In this study, we utilized unmanned aerial vehicle (UAV) multispectral imagery to assess short-term vegetation responses to simulated SWI events in the Visser’s Experimental Wetland Complex in Saint Martinville, Louisiana. Vegetation patches of two common freshwater wetland species, Panicum hemitomon (Maidencane) and Typha domingensis (Southern Cattail), were exposed to 5 ppt salinity for 6-, 10-, and 17-day durations. Multispectral imagery of both species was collected before and after each SWI …

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Classifying Storm Surges Along Louisiana Coast Using Machine Learning, Faith Ewere Okunbor Jun 2026

Classifying Storm Surges Along Louisiana Coast Using Machine Learning, Faith Ewere Okunbor

Masters Theses

Storm surges are among the most significant threats to coastal wetlands, causing flooding and saltwater intrusion that alter hydrology, vegetation structure, and long-term ecosystem resilience. Along the Louisiana coast, storm surge effects vary depending on storm behavior, shoreline geometry, and marsh hydrologic connectivity, yet are commonly characterized using broad storm metrics rather than site-specific environmental responses. This study develops a data-driven framework to classify storm surges across coastal Louisiana wetlands using observations from the Coastwide Reference Monitoring System (CRMS). Hourly water-level and salinity time series from twelve hurricanes (2007-2024) were analyzed using a 40-day storm-centered window. Hydrologic and salinity metrics …

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Regioselective Tellurination Reactions And Their Utilities, Itunu Comfort Olanrewaju Jun 2026

Regioselective Tellurination Reactions And Their Utilities, Itunu Comfort Olanrewaju

Masters Theses

This thesis provides a comprehensive study of regioselective tellurination and its applications by integrating experimental and computational techniques, with an aim of synthesizing libraries of organotellurium heterocycles. This study addresses existing challenges in regioselective tellurination, such as unpredictable regioselectivity and avoidance of toxic reagents by harnessing intramolecular Te…O coordination and electrophilic aromatic tellurination. This strategy enables the development of previously poorly accessible compounds including benzotellurazinones, 2-acylaminobenzotellurazoles, and previously unknown 2,3-dihydrobenzo [b] oxatelluranes, which were prepared by antiMarkovnikov anti-addition of TeCl4 to C-C triple bonds. Experimental studies were complemented by computational DFT analyses to provide mechanistic and energetic insight into the …

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Stratigraphic Distribution Of Pleistocene Aves At Fossil Lake In Lake County, Oregon, Cole Bradley Phillips Jun 2026

Stratigraphic Distribution Of Pleistocene Aves At Fossil Lake In Lake County, Oregon, Cole Bradley Phillips

Masters Theses

The Fossil Lake locality in south-central Oregon is rich in many species of fossil remains and is also home to packages of sandstone that grade upward into finer siltstone or claystone. These packages have been interpreted to represent rising and falling lake levels as a result of glacial transgressive and regressive sequences. The fossil vertebrates and invertebrates have also fluctuated because of the different climates at Fossil Lake. Although the stratigraphic distribution of most classes of animals have been determined, fossil birds have not. Here, the distribution of 329 avian fossils is presented in the stratigraphic framework. The species were …

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Disparities In The Identification Of Vulnerable Communities Due To Design Storm Methods: A Case Study In The Vermilion River Watershed, South Louisiana, Usa, Claire Orgeron Jun 2026

Disparities In The Identification Of Vulnerable Communities Due To Design Storm Methods: A Case Study In The Vermilion River Watershed, South Louisiana, Usa, Claire Orgeron

Masters Theses

Accurately identifying socially vulnerable populations at-risk of flooding is critical for equitable disaster mitigation and planning. This study investigates how the selection of design storm method, which is fundamental to developing flood risk maps used for this identification, influences which socially vulnerable populations are recognized as being at elevated flood risk. The most widely used design storm approach relies on National Oceanic and Atmospheric Administration (NOAA) Atlas 14 point-based rainfall frequency estimates. These estimates are typically applied spatially using areal reduction factors, thereby disregarding rainfall spatial variability in real storms. Stochastic Storm Transposition (SST), an alternative design storm approach that …

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Mgrre_Thinsections_Mgrre-147_24, Mgrre Jun 2026

Mgrre_Thinsections_Mgrre-147_24, Mgrre

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Mgrre_Thinsections_Mgrre-147_23, Mgrre Jun 2026

Mgrre_Thinsections_Mgrre-147_23, Mgrre

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Mgrre_Thinsections_Mgrre-147_25, Mgrre Jun 2026

Mgrre_Thinsections_Mgrre-147_25, Mgrre

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Scientific Crosstalk: Natural Language Processing, Praveshika Bhandari Jun 2026

Scientific Crosstalk: Natural Language Processing, Praveshika Bhandari

Theses and Dissertations

While sentiment analysis has made significant strides in domains such as social media and personal correspondence, its application to formal scientific writings remains under-explored. The crosstalk between emotional expressions in personal and professional communications has also received limited attention despite its potential to reveal insights into the emotional drivers of scientific creativity. Our research introduces a computational framework designed to detect and quantify emotional expressions across various documents over time. Leveraging state-of-the-art transformer models fine-tuned on domain-specific corpora, the framework models emotional tone distribution. Integrating emotion analysis with knowledge graph modeling enables the exploration of emotional trends alongside key scientific …

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Generating Live Heatmaps Of Edr Data Through A Spatiotemporal Weighting, Joel T. Williams, C. Sean Bohun, Alberto Fornaci, Michael R. Lindstrom Jun 2026

Generating Live Heatmaps Of Edr Data Through A Spatiotemporal Weighting, Joel T. Williams, C. Sean Bohun, Alberto Fornaci, Michael R. Lindstrom

School of Mathematical & Statistical Sciences Faculty Publications

This paper introduces a novel method for generating live heatmaps of eddy dissipation rate (EDR) data through a spatiotemporal weighting designed to enhance turbulence visualization in aviation. As more flight data become available, approaches relying solely on in-flight EDR measurements have the potential to accurately nowcast and visualize turbulence with low computational cost. The proposed method significantly improves the turbulence visualization capabilities of common commercial aircraft. This is particularly valuable for pilot decision-making and trip planning, enhancing flight safety and operational efficiency. This approach also incorporates an innovative uncertainty threshold, which refrains from predicting when there are insufficient data, thereby …

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30 Db On-Chip Ultra-High Inverse Weak Value Amplification, Yuhan Mei, Meiting Song, Andrew N. Jordan, Jaime Cardenas Jun 2026

30 Db On-Chip Ultra-High Inverse Weak Value Amplification, Yuhan Mei, Meiting Song, Andrew N. Jordan, Jaime Cardenas

Mathematics, Physics, and Computer Science Faculty Articles and Research

Weak value amplification (WVA) has emerged as a powerful technique that enhances measurement precision. However, traditional table-top WVA setups and on-chip demonstrations have not achieved an amplification over 20 dB. The practical limit of the amplification is the fidelity of photon post-selection. To address this limit, we design a weak value device with an over 30 dB interferometer extinction ratio, where the stray light in the dark port is minimized with thermally tunable phase shifters. As a result, the device successfully shows 30 dB WVA, termed ultra-high WVA. This WVA optimization strategy by improving interferometer extinction is extensible to a …

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A Large Language Model-Based Analysis Of Vulnerability Discovery In Windows Software, Puya Pakshad, Samson Quaye, Jamal Al-Karaki, Marwan Omar, Maurice E. Dawson Jun 2026

A Large Language Model-Based Analysis Of Vulnerability Discovery In Windows Software, Puya Pakshad, Samson Quaye, Jamal Al-Karaki, Marwan Omar, Maurice E. Dawson

All Works

Source code security auditing is essential before software release in order to identify programming faults that may lead to vulnerabilities and functional failures. In this paper, we present a structured security assessment of the Windows App SDK by integrating multiple static analysis tools with a context-aware and disagreement-aware Large Language Model (LLM) interpretation layer. Although static analyzers are effective in reporting potential weaknesses, their raw outputs often contain redundant alerts, limited contextual explanation, and inconsistent severity assignments. To address these limitations, the proposed LLM-based interpretation layer normalizes and de-duplicates alerts, filters context-limited or nonactionable warnings, and refines severity prioritization under …

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Breadquest: Enhancing Roguelike Accessibility Through Procedural Generation And Thematic Design, Hahns Pena Jun 2026

Breadquest: Enhancing Roguelike Accessibility Through Procedural Generation And Thematic Design, Hahns Pena

Computer Science and Software Engineering

BreadQuest is a top-down roguelike dungeon crawler with a whimsical dessert theme that aims to make the genre more accessible while preserving strategic depth and replayability. Players explore procedurally generated dungeons, fight pastry-themed enemies, and collect bakery-inspired items that support a flavor-elemental combat system, with each run offering unique layouts, encounters, and rewards. Built in Unity with a modular, data-driven architecture, the game uses procedural generation techniques like Binary Space Partitioning, Voronoi diagrams, and Perlin noise to create varied and replayable levels. The project emphasizes approachable gameplay, cultural dessert inspiration, and replayability, with success evaluated through playtesting and player feedback.

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Active Galaxies In A New Light: The Broad Line Region In The Near-Infrared, Sky O'Donnell Jun 2026

Active Galaxies In A New Light: The Broad Line Region In The Near-Infrared, Sky O'Donnell

Physics

At the center of most massive galaxies, there is a supermassive black hole with a mass millions to billions of times that of the Sun. In some of these galaxies, so-called Active Galactic Nuclei (AGNs), the supermassive black hole is converting the gas that falls toward it into radiation energy, creating large amounts of luminosity. AGNs are composed of the central supermassive black hole, its accretion disk, and a region just outside, composed of fast-moving ionized gas clouds called the Broad Line Region (BLR). Using spectra obtained with NASA’s Infrared Telescope Facility, we use a technique known as reverberation mapping …

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