Physical Sciences and Mathematics Commons^™

Constructing An Attractive Targeted Sugar Bait For Reducing Mosquito Populations, Xi Xian Ng

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

Mosquito-borne pathogen transmission continues to pose a significant burden to global public health, well-being, and economic productivity. In the absence of universally available vaccines and amidst rising insecticide resistance that leads to product failures, there is an urgent need to develop new tools to mitigate mosquito-borne disease risk. Two general strategies exist to reduce transmission risk: personal protective measures and area-wide chemical interventions. Attractive Targeted Sugar Bait (ATSB) systems leverage the sugar-feeding behavior of mosquitoes—critical for sustaining their flight, metabolism, development, and fecundity—by delivering oral toxicants through attractively formulated sugar baits. This study aimed to develop an optimized ATSB formulation …

Physics Embedded Neural Network: A Novel Data-Free Numerical Method For Solving Computational Physics Problems, Pawan Gaire

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

A novel approach for solving partial differential equations (PDEs) using neural networks for scientific computing is introduced. The proposed approach, referred to as physics-embedded neural network (PENN), features a unique architecture that incorporates the PDE and boundary conditions information directly within the final fully-connected layer of the feed-forward neural network (NN). The key aspect of PENN is the parallel numerical embedding of a differential equation associated with physical problems within the activation function of the network’s final layer. This integration leads to a new class of computational solvers competitive with classical methods like the Finite Element Method (FEM) and capable …

A Study Of Ultrafast, Intense-Field Photodynamics In Carbon Dioxide, Carbon Disulfide, And Select Substituted Benzenes, Joshua Edwin Beck

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

The study of the photodynamics of molecules in ultrashort pulses of intense radiation continues to be of interest. Electric field strengths in such pulses can approach or exceed the typical electric field strengths binding the electrons to the nuclear framework (ke/a²₀ ≈ 5 × 10⁹ V/cm). The resulting excitation, ionization, and dissociation of molecular targets is of interest in many areas including attosecond science, femtochemistry, atmospheric science, high harmonic generation, and many other fields.

This dissertation investigates the photoionization and photofragmentation behavior of carbon dioxide, carbon disulfide, and the substituted benzenes nitrobenzene, aniline, as …

A Machine Learning Framework For Packet Anomaly Detection In Smartgrid Substation Networks, Sowmya Bandari

School of Computing: Dissertations, Theses, and Student Research

The increasing reliance on Smart Grid Substation Networks for efficient electricity distribution has amplified cybersecurity vulnerabilities, particularly within Supervisory Control and Data Acquisition (SCADA) systems. The IEC 60870-5-104 (IEC-104) protocol, widely adopted for communication between Remote Terminal Units (RTUs) and Human-Machine Interfaces (HMIs), lacks inherent encryption and authentication mechanisms, rendering it susceptible to sophisticated cyberattacks. Threats such as False Data Injection Attacks (FDIAs), command injection, covert attacks and replay attacks pose significant risks by manipulating grid control signals, potentially leading to undetected operational disruptions, cascading failures, or system-wide instability. Conventional signature-based Intrusion Detection Systems (IDS) often fail to identify zero-day …

Predicting Cardiac Resynchronization Therapy Response: Development And Validation Of A Single Photon Emission Computed Tomography-Based Nomogram, Zhongwei Jiang, Zhongqiang Zhao, Zhuo He, Qiushi Chen, Ju Bu, Chunxiang Li, Dianfu Li, Chang Cui, Weihua Zhou, Huiyuan Qin, Cheng Wang

Michigan Tech Publications

Background: Cardiac resynchronization therapy (CRT) is an effective treatment for patients with drug-refractory heart failure. However, more than thirty percent of patients do not benefit from CRT. This study aimed to develop and validate a novel model based on single photon emission computed tomography (SPECT) phase analysis features to predict CRT response. Methods: We identified 163 CRT patients who received gated resting SPECT myocardial perfusion imaging (MPI) between 2010 and 2020 at The First Affiliated Hospital of Nanjing Medical University. All variables were first processed by univariate logistic regression, and those with a P value < 0.05 were retained. The selected variables were subsequently used in the least absolute shrinkage and selection operator (LASSO) regression to construct a predictive model, which was then represented as a nomogram. Nomogram performance was assessed via receiver operating characteristic (ROC) curves, calibration curves, and decision curve analyses (DCAs). Internal validation was performed by bootstrapping with 1,000 replicates. Results: Of the 163 patients, 93 (57.1%) responded to CRT during follow-up. Responders had a wider QRS complex duration (QRSd) (164.80 vs. 154.51 ms, P=0.003), fewer premature ventricular contractions (PVCs) (1,392.98 vs. 2,283.60, P=0.003), lower prevalence of non-sustained ventricular tachycardia (NS-VT) (45.2% vs. 77.1%, P< 0.001), and better cardiac function [based on N-terminal pro-B-type natriuretic peptide (NT-proBNP), New York Heart Association (NYHA), and left ventricle (LV) parameters] compared to non-responders. Univariate logistic regression revealed 14 variables significantly associated with CRT response (all P< 0.05). The area under the ROC curve (AUC) value for the nomogram was 0.845 [95% confidence interval (CI): 0.785–0.906; sensitivity: 0.771; specificity: 0.849]. Internal validation yielded a mean AUC of 0.814 (95% CI: 0.777–0.836). The calibration curve demonstrated strong consistency between the predicted and observed outcomes. DCA revealed that the nomogram consistently provides a net benefit over the baseline, demonstrating its high practical value in clinical decision-making. A web-based dynamic nomogram (https:// jzw20000624.shinyapps.io/CRTpredictionmodel/) was developed for clinical application. Conclusions: We developed and validated a SPECT-based prediction model for predicting CRT response, which can assist clinicians in optimizing CRT candidacy preoperatively. Pacing at the latest contraction and relaxation segments, while avoiding scarred regions and optimizing preoperative status, is anticipated to improve CRT response.

Analyzing Meteor Shower Radiants, Elise Springman

Celebrating Scholarship and Creativity Day (2018-)

Meteor shower origin points, or radiants, are a widely studied topic in astrophysics as they give a lot of context to the meteor shower itself as well as provide a way study broader space. Specifically, when it comes to annual showers, these radiant points are compared with previous years to create a broader database about the shower and check accuracy of instruments. This project is ongoing with several places tracking these annual showers and comparing data to give a more detailed history of each shower. Here at CSBSJU, meteor showers were analyzed using an AllSky camera, and a few additional …

Nonlinear Power Function Model Changepoint Detection., Jacob Steven Townson

Electronic Theses and Dissertations

Most work surrounding changepoint analysis focuses on linear models. This dissertation explores changepoint detection in nonlinear power function models, specifically focusing on models where the constant multiplier and power are the parameters to be estimated in addition to the changepoint parameter. The study assumes an asymptotic framework as the number of observations approaches infinity. The study explores various model fitting algorithms, and decides to employ the Newton-Raphson method for parameter estimation, with a custom implementation developed to optimize the process. The research first establishes the strong consistency of estimators for the model without a changepoint. Building on this result, consistency …

Thin-Film Optical Filters For Selective Transmission And Black-Body Reflection In Pyroelectric Energy Systems., Cedric Cruz Silva

Electronic Theses and Dissertations

Essential to pyroelectric energy systems is the ability for a pyroelectric material to achieve high temperatures rapidly. In pursuit of augmenting this process, several thin-film optical filters were designed for transmitting laser excitation in the near-infrared region, while simultaneously reflecting black-body radiation for pyroelectric materials. Designs include a classical Fabry-Perot structure with gold and tantalum pentoxide, an induced transmittance filter with silica, hafnia, and gold, and an indium-tin-oxide filter with silica, alumina, and ITO. Performance varies depending on the design. The Fabry-Perot filter experimentally showed a maximum transmittance of 42% at 1.04 μm and an infrared reflectance of 98%. The …

New Bayesian Methods For Longitudinal Data Analysis With Complex Dependence Structures., Anish Mukherjee

Electronic Theses and Dissertations

Longitudinal data in real-world settings are frequently found to be heterogeneous and exhibit intricate spatio-temporal dependence structures. Analyzing such complex data to obtain reliable estimation while quantifying uncertainty necessitates using sophisticated Bayesian methodology. In this work, we present novel Bayesian methods developed to address these challenges. We often observe heterogeneity in longitudinal data, where the mean and variance for certain profiles meaningfully differs from the rest. Some profiles may also exhibit outliers at a limited number of measurements. Using a standard mixed effects model, which assumes homogeneity, can lead to overestimating the residual variance and inefficient estimation. In this work, …

A Hierarchical Soft Computational Model For Optimizing Agricultural Uavs: Recruiting Neutrosophic Theory And Tree Soft Sets, Mona Mohamed, Nurhan Alaa, Bilal Arain, Karam M. Sallam

Neutrosophic Systems with Applications

Precision agriculture is being transformed by Unmanned Aerial Vehicles (UAVs), which make it possible for yield optimization, targeted spraying, and sophisticated crop monitoring. With an emphasis on their operational capabilities, economic feasibility, and environmental implications, this research explores the revolutionary potential of UAV technology in contemporary farming systems. Practically speaking, the procedure of opting UAVs for agricultural applications is complicated by several competing aspects, inherent uncertainties, and differing stakeholder agendas. This paper suggests a new hybrid decision framework that combines Tree Soft Sets (TrSS), Neutrosophic theory, and Multi-Criteria Decision-Making (MCDM) to methodically handle these issues. Hence, the robust hybrid model …

Triple-Valued Neutrosophic Set, Quadruple-Valued Neutrosophic Set, Quintuple-Valued Neutrosophic Set, And Double-Valued Indetermsoft Set, Takaaki Fujita

Neutrosophic Systems with Applications

Concepts such as Fuzzy Sets, Neutrosophic Sets, Rough Sets, and Plithogenic Sets have been extensively studied to address uncertainty, finding diverse applications across various fields. A Double-Valued Neutrosophic Set (DVNS) extends traditional neutrosophic sets by introducing two distinct indeterminacy components: one leaning towards truth and the other towards falsity. In this paper, we explore Triple-Valued Neutrosophic Sets, Quadruple-Valued Neutrosophic Sets, and Quintuple-Valued Neutrosophic Sets, as well as an extension of the Indetermsoft Set, termed the Double-Valued Indetermsoft Set. Note that related concepts such as the Multi-Valued Neutrosophic Set and the n-Valued Refined Neutrosophic Set have already been established.

More Concerns About Atmospheric Methane Removal Efforts, Joshua Luczak

Research Collection College of Integrative Studies

The National Oceanic and Atmospheric Administration reported record-high global atmospheric carbon dioxide levels (419.3 ppm) in 2023, alongside atmospheric methane levels (1922.6 ppb) now over 160% above pre-industrial levels. The World Meteorological Organization predicts 2024 could surpass 2023 as the warmest year on record, with more frequent and severe extreme weather events. Meeting the Paris Climate goal of limiting global warming to well below 2°C—or ideally 1.5°C—above pre-industrial levels is becoming increasingly difficult. To address these challenges, efforts are expanding beyond reducing greenhouse gas emissions. While carbon dioxide removal (CDR) technologies have been the focus, attention is now turning to …

Park Cool Island Modifications To Assess Radiative Cooling Of A Tropical Urban Park, Graces N. Y. Ching, Sin Kang Yik, Su Li Heng, Beatrice H. Ho, Peter J. Crank, Moshe Eliezer Mandelmilch, Xiang Tian Ho, Winston T. L. Chow

Research Collection College of Integrative Studies

Many cities experience urban overheating from climate change and the urban heat island phenomenon. Previous studies demonstrate that parks are a potential nature-based solution to mitigate urban overheating through the ‘Park Cool Island’ (PCI) effect. PCI intensity can be measured through field measurements (FM) or remote sensing. This FM study used a network of meteorological sensors within a park and in its surrounding urban area to ascertain its PCI intensity in Singapore from January to December 2022. Consistently cooler air temperatures were found throughout a 24-h period in the park area, with mean daytime (nighttime) PCI intensity measured ~ 2.21 …

Sensors And Sensibilities: Exploring Interactions For Habitat Comfort With An Environmental-Physiological Sensing Eyewear In The Wild, Sailin Zhong, Patrick Chwalek, Nathan Perry, David Ramsay, Clayton Miller, Denis Lalanne, S. Hamed Alavi, A. Joseph Paradiso

Research Collection College of Integrative Studies

Buildings increasingly incorporate sensing and actuation techniques to automate the regulation of temperature, lighting, ventilation, and more. This trend seeks to minimize human intervention, justified by the promise of enhancing energy optimization. However, it has been widely acknowledged that loss of control over environmental conditions can lead to a diminished perception of comfort and compromised long-term user awareness and satisfaction. How can we envision building systems that can interact with building inhabitants and engage them at the “right” time and place? In this work, we address this challenge through three key contributions: 1) AirSpecs, a novel smart glasses-based system that …

Full-Stack Web Applications: Industry Standard Frameworks, Libraries & Technologies, Yassine Chahid, Patrick Slattery

Publications and Research

This research explores emerging full-stack web development technologies across front-end, back-end, and DevSecOps domains. It evaluates modern tools including Django, React, and TypeScript—focusing on their key features such as compile-time error checking—through to the development of a web application. By examining documentation for the frameworks Node.js, Next.js, Tailwind CSS, and others, along with the deployment tools Docker and Git for version/release control, the study analyzes how these innovations speed up development, improve existing practices, and have often replaced older technologies. Cloud solutions for tasks such as authentication and deployment will also be evaluated, along with various web-application technology stacks and …

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 …

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, …

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. …

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 …

Elucidating The Mechanisms Of Collagenase H From Hathewaya (Clostridium) Histolytica In Collagen Degradation And Developing A Cross-Linked Platform For Efficient Capture And Release Of Adeno-Associated Virus Serotype 2 (Aav2), Adjoa Otubea Bonsu

Graduate Theses and Dissertations

In biological systems, Hathewaya (Clostridium) histolytica secretes collagenases that degrade structural collagen in host tissues and cause tissue necrosis. Despite their detrimental effects, these enzymes have significant therapeutic potential by effectively digesting various collagen subtypes to treat connective tissue disorders. The bacterium produces two homologous collagenases, ColG and ColH, with a catalytic module crucial for hydrolyzing collagen and binding domains, including collagen-binding domains (CBDs) and polycystic kidney disease-like domains (PKDs), for substrate interaction.

Although the crystal structure of the catalytic module of collagenase G (ColG) has been determined, shedding light on its chew-and-digest mechanism, the structure of collagenase H (ColH) …

Exploring Latent Mediation Through Bayesian Regularization Methods Of Lasso, Ridge, Horseshoe, Spike-And-Slab, Ethan Harris

Graduate Theses and Dissertations

Regularization is a powerful tool to combat overfitting and drive sparsity in complex models. Regularization was initially applied in regression modeling but has been increasingly utilized in structural equation modeling where its utility in identifying the essential components has helped improve modeling. As structural equation models have increased in complexity both in the number of indicators but also the number of latent factors, researchers have begun to investigate how applying Bayesian regularization to these systems can further push the limits on modeling complex models with limited sample sizes. One area where research is limited is the application of Bayesian regularizations …

Contrastive Learning Techniques For Fraud Detection, Vinay Madanbhavi Shashidhar

Graduate Theses and Dissertations

Detecting fraud in computing platforms involves identifying malicious user sessions, often using deep learning models, but several challenges hinder effective deployment. Attackers can craft diverse malicious sessions that closely resemble normal ones, complicating the learning of robust decision boundaries. While supervised contrastive learning offers a promising solution through class-specific clustering, its potential remains underexplored. Real-world datasets typically contain few labeled malicious sessions and many normal ones, creating an open-set anomaly detection challenge. Costly expert annotation further limits labeled data, especially for smaller organizations, leading to Positive Unlabeled (PU) learning and noisy label learning issues. Organizations are increasingly turning to LLMs …

Conservation Agriculture Practice Effects On Greenhouse Gas Emissions From Fine-Textured Soils In Arkansas, Lauren Gwaltney

Graduate Theses and Dissertations

Biochar application and reduced tillage (RT) are both practices within the conservation agriculture framework, but specific impacts of these practices on direct greenhouse gas (GHG) emissions still require investigation in varied agricultural systems. This research aimed to evaluate the effects of biochar source (i.e., powder- and pellet-sized) and application rate (i.e., 0, 2.5, and 5 Mg ha^-1) on GHG production in simulated furrow-irrigated rice (Oryza sativa) in a greenhouse experiment, and to evaluate the effects of RT relative to conventional tillage (CT) on GHG production in soybean (Glycine max) in southeast Arkansas. Both studies …

Adversarial Machine Learning: Methods For Attacks And Defenses, Minh Hao Van

Graduate Theses and Dissertations

With the rapid development of machine learning in real-world applications, enhancing security plays an important role. Adversarial machine learning focuses on understanding malicious actions from attackers and developing defensive techniques against such threats when deploying machine learning systems. An attack can occur in different scenarios, such as poisoning attacks during the training stage and evasion attacks during the testing stage. Although extensive research has explored defense strategies to deal with these harmful attacks, there is a need for further research into areas such as how to counteract malicious attacks with healthy noise or how to train an adaptive defense against …

The Future Of Fashion: A Systematic Literature Review On Consumer Willingness To Pay For Green Apparel, Emma Clark

Graduate Theses and Dissertations

In recent years, consumers have become highly aware of the environmental impact of their purchases, specifically of apparel products. Accordingly, apparel brands have increasingly focused on enhancing the sustainability of their product offerings to attract environmentally conscious consumers and elevate their brand image (Dangelico et al., 2022). Furthermore, most sustainably produced products are priced higher for consumers compared to standard alternatives (Elmanadily & El-Deeb, 2022). Research has shown that consumers can accept higher prices for products that do less harm to the environment (Gomes et al., 2023), but it has yet to be determined in which cases this is consistently …

Koszul Cohomology Of Canonical Products, Alexander Scott Duncan

Graduate Theses and Dissertations

In this thesis, we give a complete classification of the Koszul cohomology groups K_p,₁(C, B, ω_C ⊗ B) on a smooth curve C of genus g ≥ 2 with B p-very ample. Such a classification in the case B = ω_C has been incomplete until [5]. The classification follows easily from our main result which precisely calculates K_p,1(C, B, B ω_C ⊗ B) in terms of h⁰(C, B). This result also handles the case B = ω_C. A straightforward …

Atomic Level Characterization For The Transport Cycle Conformational Pathways Of Multidrug Resistance Protein 1 (Mrp1), Samuel Wamwere Mwatha

Graduate Theses and Dissertations

The multidrug resistance-associated protein 1 (MRP1/ABCC1) is an ATP-binding cassette (ABC) transporter that mediates the cellular efflux of endogenous and xenobiotic substrates, including therapeutic drugs. Its overexpression is a major contributor to multidrug resistance in cancer, which tends to result in negative clinical results. Even with considerable progress made in structural biology, the intricate details of how membrane lipid composition affects the conformational changes and functional switches of MRP1 still lack explanation.

This thesis employs long-timescale, all-atom molecular dynamics (MD) simulations to study the influence of various lipids on MRP1 lipid bilayer environments. Both inward-facing and outward-facing conformations of MRP1 …