Physical Sciences and Mathematics Commons^™

What References Are Chatgpt, Gemini, Copilot, And Perplexity Providing For Consumer Health Questions?, Ivan Portillo, Scott Johnson, Catherine Johnson

Library Presentations, Posters, and Audiovisual Materials

No abstract provided.

Tailoring Evaluations Of Chronic Rhinosinusitis: Understanding Sleep And Its Effect On Memory Through Actigraphy, Donyea Moore, Rachel Nolte, Yitong Pepper Huang, Shreya Maharana, Pavan Nataraj, Bichun Ouyang, Mahboobeh Mahdavinia

Mathematics Sciences: Faculty Publications

Background/Objectives: Chronic rhinosinusitis (CRS) is a persistent inflammatory condition of the sinonasal mucosa lasting for at least three months. For patients, CRS-related sleep disturbances can significantly disrupt circadian rhythms, leading to further health complications such as cognitive impairment. Despite the well-documented sleep disturbances associated with CRS, there is limited research on objective assessment methods. Additionally, the severity of these issues can vary among patients. This study aims to assess sleep quality and timing in CRS patients and investigate their impact on cognition, providing guidance for personalized and tailored assessment and management of CRS. Methods: Our case–control study compares sleep patterns …

Classifying Detrital Zircon U-Pb Age Distributions Using Automated Machine Learning, Jack W. Fekete, Glenn R. Sharman, Xiao Huang

Geosciences Faculty Publications and Presentations

The prodigious use of detrital zircon U-Pb geochronology for provenance studies in recent decades has led many researchers to amass extensive datasets (>100,000 dates). When displayed as age distributions, individual samples are traditionally compared using visual inspection and statistical methods, which can become timeconsuming and challenging when using large datasets. We propose that machine learning (ML) can more efficiently classify a sample by its source using detrital zircon U-Pb age distributions. Specifically, we hypothesize that automated machine learning (AutoML), which optimizes algorithm selection and hyperparameters, will outperform an unoptimized Random Forest (RF) classifier and the cross-correlation coefficient (R-2), a …

Simulations Of Differential Reflectivity Columns In Quasi-Linear Convective Systems, Devon Jacob Healey

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

Much research over the past decade has revealed that dual-polarization radar is a powerful tool in furthering our understanding of severe storm dynamics and subsequently improving warning strategies for these hazardous events. However, there are currently very few studies examining a particularly prolific severe convective storm mode with dual-polarization radar: quasi-linear convective systems (QLCSs). These storms can occur in any season of the year throughout most of the contiguous United States and can have immense societal impacts. Warning for the hazards produced by QLCSs is currently a significant operational challenge, therefore, research is needed to see if applying dual-polarization radar …

The Weaving Of Machine Learning And Artificial Intelligence Into The Fabric Of Cybersecurity Curriculum: From Degree Plan To Capstone Projects, Mahmoud K. Quweider, Liyu Zhang, Jorge Castillo, Ala Qubbaj

Informatics and Engineering Systems Faculty Publications

As our newly designed degree in Cybersecurity enters its fourth year, students in the program are starting to take courses beyond the basic ones, including senior courses, technical electives, and capstone projects. While Cybersecurity is at the heart of our degree that addresses the national need for cybersecurity specialists, how we approach the education and pedagogy of cybersecurity in the era of Big Data and AI/ML (Artificial Intelligence/Machine Learning) is a question that we are addressing in real-time as techniques and measures and countermeasures of cybersecurity attacks keep evolving and taking advantages of the rapid advancements in computing, memory, storage, …

Status And Distribution Of Diseases Caused By Phytoplasmas In Africa, Shakiru Adewale Kazeem, Agnieszka Zwolińska, Joseph Mulema, Akindele Oluwole Ogunfunmilayo, Shina Salihu, Joy Oluchi Nwogwugwu, Inusa Jacob Ajene, Justina Folasayo Ogunsola, Adedapo Olutola Adediji, Olubusola Fehintola Oduwaye, Kouamé Daniel Kra, Mustafa Ojonuba Jibrin, Wei Wei

All Peer-Reviewed Publications

Phytoplasma (“Candidatus Phytoplasma” species) diseases have been reported globally to severely limit the productivity of a wide range of economically important crops and wild plants causing different yellows-type diseases. With new molecular detection techniques, several unknown and known diseases with uncertain etiologies or attributed to other pathogens have been identified as being caused by Phytoplasmas. In Africa, Phytoplasmas have been reported in association with diseases in a broad range of host plant species. However, the few reports of Phytoplasma occurrence in Africa have not been collated together to determine the status in different countries of the continent. Thus, this paper …

A Novel Integrated Computational Approach For Agroecological Similarity, Franck B.N. Tonle, Henri E.Z. Tonnang, Milliam M.Z. Ndadji, Maurice T. Tchendji, Armand Nzeukou, Saliou Niassy

All Peer-Reviewed Publications

Assessing agroecological similarity is crucial for shaping sustainable agricultural practices and resource allocation, especially in regions undergoing rapid environmental changes. Current evaluation methods face challenges such as managing large datasets, adjusting for temporal variations across locations, and the need for accessible, comprehensive analytical tools. Addressing these challenges, this paper presents the Agroecology Fourier-based Similarity Assessment (AFSA), an innovative computational approach that applies principles of the Fourier transform to systematically evaluate similarities among agroecological sites. To enhance usability, AFSA is complemented by webafsa, a user-friendly web application designed for researchers and policymakers, emphasizing ease of use and broad applicability. The implementation …

Probing Shielding Tensor Components Of Amino Acids Using Nuclear Magnetic Resonance, Shiva Agarwal

Dissertations

Chirality is fundamental to terrestrial life. While most amino acids exist as nonsuperimposable mirror images, amino acids in terrestrial life are homochiral, with the L-enantiomer being ubiquitous. The detection of an excess of L-amino acids in carbonaceous meteorites suggests that extraterrestrial processes may have contributed to this enantiomeric excess (ee). One proposed mechanism, the magnetochiral model, provides a potential explanation for this phenomenon in stellar environments characterized by strong magnetic and electric fields and the presence of relativistic leptons. According to this model, subtle differences in the electronic environments of chiral amino acids under such conditions …

Equiangularity From Compatible Orthobiangularity, Tyler J. Myers

Theses and Dissertations

An equiangular tight frame (ETF) is an equal norm sequence of vectors in a Hilbert space whose coherence achieves equality in the Welch bound. Such sequences necessarily have minimal coherence and thus are, in some sense, as "spread out" in space as possible. ETFs have a variety of applications, such as compressed sensing and waveform design. The main problem in the study of ETFs is determining the pairs (D, N) for which an ETF with N vectors in a D-dimensional space exists. Real ETFs are moreover equivalent to a special subset of a well-studied class of graphs known as strongly …

Constraining Nuclear Data Uncertainty Requirements For The 19F(A, N)22Na Reaction For Non-Proliferation Applications, Tyler R. M. Smith

Theses and Dissertations

This thesis explores the requirements on nuclear data uncertainties needed for the use of the ¹⁹F(α, n)²²Na reaction for nuclear non-proliferation applications. An overview of how neutrons are produced from alpha decays in a UF₆ medium is discussed. Calculation demonstrate the role nuclear data uncertainties effect the neutron yield and energy spectra as a function of enrichment.

Rotating Scatter Mask System Optimization Study For Determining Optimal Image Recreation, Seth L. Grover

Theses and Dissertations

The Rotating Scatter Mask (RSM) system is a radiation imaging technology currently limited by the mask design and governing identification algorithm parameters. To optimize the RSM design, Dakota—an optimization software—was integrated with a ray tracing code that simulates particle interactions with the RSM detector, and with the Locally Competitive Algorithm (LCA), which reconstructs the source image based on the ray tracing code’s Detector Response Matrix (DRM). Since the original ray tracing code was developed in MATLAB, it was translated into Python to improve compatibility with both Dakota and LCA. The Python version of the ray tracing code was then integrated …

Contract Quality Feature Extraction Using Llm, Aaron C. Washington

Theses and Dissertations

This study explored the potential insights generated from linguistic complexity measurements and large language model (LLM) based assessments on the quality of contract documents. By combining structured True/False prompts with log-probability analysis and ambiguity scoring, the study introduced novel contract-quality assessment methods. Results support a feature-driven approach to contract evaluation, one that offers automated, scalable insights for triaging risk and improving drafting practices. These assessment methods contribute to the growing field of legal natural language processing by offering modular tools for effective contract analysis.

Fused-Silica Microelectromechanical Systems For Relative Gravimetry, Ethan Doerstling

Theses and Dissertations

Gravimeters are devices that measure gravitational acceleration which can be used by the United States Air Force (USAF) in the areas of navigation and remote sensing. Fused-silica microelectromechanical systems (MEMS) devices offer capabilities to make inexpensive relative gravimeters with higher thermal stability than common silicon devices while maintaining good gravitational sensitivity. The fused-silica devices in this research were designed, simulated, fabricated, and tested to observe their performance as gravimeters. The devices exhibit properties of highly sensitive accelerometers but the current designs do not qualify as gravimeters. This study provides information to improve the sensitivity and stability of these fused-silica MEMS …

The Influence Of Black Soldier Fly Residue On Watermelon Growth And The Properties Of A Coarse-Textured Ultisol, Benedict Onyebuchi Unagwu, Chidiebere Fransica Odu, Chinedu Felix Amuji, Michael Onyedika Eze, Nancy Ekene Ebido, Chidike Ude Abara, Chioma Rosita Igboka, Uchechukwu Paschal Chukwudi

Chemistry Faculty Research & Creative Works

Improving the fertility status of nutrient-depleted soils is critical to achieving food security. The negative effects of chemical fertilizers on soils necessitate the global quest for eco-friendly, effective, and sustainable alternatives. This work assessed the effect of black soldier fly (BSF) residue application on soil properties and watermelon growth. The study was set up in a completely randomized design with six replications. The treatments were BSF1 (BSF applied at 10 t ha⁻¹), BSF2 (20 t ha⁻¹), BSF3 (30 t ha⁻¹), and control. The plant data collected in this study were vine length, leaf width, …

Potential And Pitfalls Of Romantic Artificial Intelligence (Ai) Companions: A Systematic Review, Qi Hui Jerlyn Ho, Meilan Hu, Tracy Xi Chen, Andree Hartanto

Research Collection School of Social Sciences

As Artificial Intelligence (AI) becomes more integrated into daily life, individuals have increasingly turned to AIdriven systems for emotional support, companionship, and even romantic relationships. These relationships can be both beneficial and detrimental. Given the need for a comprehensive understanding of this phenomenon, this systematic review uses Sternberg’s Triangular Theory of Love to provide a holistic summary of its key potentials and pitfalls. A total of 23 articles were identified from the following databases: EBSCOhost ERIC, EBSCOhost PsycInfo, PubMed, Scopus, and Web of Science. Results highlighted the key potentials of being in a romantic relationship with AI companions as: the …

Unveiling The Vital Role Of Blue Carbon In Mangroves: Understanding Environmental Influences, Jahnelle Howe

Dissertations, Theses, and Capstone Projects

Mangrove ecosystems provide essential ecological services, including carbon sequestration, coastal protection, and heavy metal retention. However, their resilience and functionality are increasingly influenced by hurricanes, climate variability, and anthropogenic contamination. This dissertation integrates three research efforts examining mangrove canopy dynamics, carbon storage, and heavy metal contamination in two Puerto Rican mangrove systems: La Parguera and Laguna Grande.

Using remote sensing techniques (LiDAR and NDVI analysis), we assessed the impact of Hurricane Maria (Category 4, 2017) on mangrove canopy structure and vegetation health. Results revealed significant canopy height loss, with greater damage at Laguna Grande, where pre-storm canopy height and human …

Computability Theoretic Aspects Of Profinite Groups And Models Of Presburger Arithmetic, Jason Block

Dissertations, Theses, and Capstone Projects

Profinite groups, which are exactly the Galois groups, are all either finite or uncountable. However, all second countable profinite groups can be presented as the set of paths through a countable tree. We use these tree presentations to find upper bounds on the complexity of the existential theories of profinite groups, as well as to prove sharpness for these bounds. These complexity results enable us to distinguish the class of profinite groups that are isomorphic to a direct product of finite groups, for which we find an upper bound on the complexity of the entire first order theory. Additionally, given …

Streaming Instabilities In Class 0/I Disks, Shirin Gul Zaidi

Dissertations, Theses, and Capstone Projects

While it is clear that planets form in protoplanetary disks, fragmentation and the radial drift of pebbles inhibit the growth of grains to planetesimals. To overcome these barriers, effective localized dust clumping on a short enough time scale is required. One promising solution to this problem is the streaming instability. Streaming instability is only triggered with a large enough dust-to-gas ratio and grain size. Though it is unknown when and where those conditions are met in protoplanetary disks, recent studies have indicated that planetary cores likely require early formation to match detected exoplanet system masses, so that we need to …

Unpacking The Orders, Leonard J. Santos

Dissertations, Theses, and Capstone Projects

At the end of the first week of his presidency this year in 2025, Donald Trump signed a total of thirty-six executive orders. After only one month, that number had gone up to seventy-six. He is currently on track to sign the highest number of executive orders in his first year in office of any president in the last 50 years, and potentially even the last 100 years if he keeps moving at this rate. In the first 90 days of his term, Donald Trump has signed 159 executive orders, more than any other president in the history of the …

Investigation Of Retention And Dehydration Of Preformed Particle Gel For Conformance Control In Fractured Carbonates, Abdulaziz A. Almakimi, Abdullah O. Almansour, Junchen Liu, Baojun Bai, Ibnelwaleed A. Hussein

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

Preformed particle gel (PPG) treatment has proved to be among the most effective methods to reduce excessive water production in fractured reservoirs. The blocking ability of PPGs to fractures or fracture-like features is highly dependent on injected gel properties and volume. Gel dehydration during extrusion through fracture is common and has a considerable effect on gel properties, transport, and plugging efficiency. As the gel particles propagate through the fracture, continuous dehydration is often associated and causes the gel to concentrate and require high-pressure gradients to move. Dehydration might be desirable to a certain limit because it can help to form …

Proton Exchange Membrane Fuel Cells In Electric Vehicles: Innovations, Challenges, And Pathways To Sustainability, Tarek Abedin, Jagadeesh Pasupuleti, Johnny Koh Siaw Paw, Yaw Chong Tak, Monowar Mahmud, Md Pauzi Abdullah, Mohammad Nur-E-Alam

Research outputs 2022 to 2026

Proton exchange membrane fuel cells are leading the shift to sustainable energy, especially in fuel-cell electric vehicles. In PEMFCs, hydrogen is converted into electricity which contributes to reduced greenhouse gas emissions and decreased dependence on fossil fuels. Many works have been conducted to improve the power density and longevity of the whole system to be adopted in vehicles. The power density was considerably increased by a stack design incorporating lightweight material such as graphene-coated Ni form and weak carbon nanofiber films. Hydrogen refueling failures such as overfilling with hydrogen, hydrogen flow overfill, and hydrogen leakage need mitigation by developing advanced …

Multi-Point And Multi-Station Orbit Propagation For Non-Functional Drifting Geo Satellites, Hritik Mitra

Theses

Currently, there are thousands of man-made space objects that are orbiting the Earth. These satellites serve a host of essential purposes (scientific research, technical applications, services) and they are all required to remain within their mission parameters. Most critical for them is to maintain the orbital parameters that are specified to achieve a particular mission’s objectives. If a satellite deviates beyond a certain limit, there is not only a risk of mission failure but there is a major hazard for possible collisions with other objects such as active satellites, space debris and even natural objects in some cases. There is …

Measurement And Improvement Of Photon Identification Efficiencies Using Machine Learning Techniques In The Atlas Detector At The Lhc, Abdulla Esam Mahboub

Theses

Photons play a crucial role in numerous analyses at the Large Hadron Collider (LHC), particularly in studies like the Higgs boson decay to two photons. Precise photon identification is essential for enhancing the sensitivity and accuracy of such measurements. This thesis focuses on the development of a machine learning (ML)-based photon identification algorithm to improve the photon identification efficiency within the ATLAS detector, using a Deep Neural Network (DNN) approach. The primary goal is to boost photon identification efficiency by using advanced neural network techniques. Traditional photon identification relies on cuts applied to shower shape variables, which can limit the …

Design Of A Deployable Rolled Antenna System For Satellite Applications, Ashwaq Abdulla Alkaabi

Theses

This project presents the development of a deployable Synthetic Aperture Radar (SAR) antenna designed for a 16U CubeSat platform. The primary challenge in SAR satellite design lies in the need for large antennas to achieve high-resolution imaging, which traditionally results in increased satellite size and cost. To address this, the proposed solution employs a scalable 4 × 21 patch antenna array operating at 1.275 GHz, fabricated on a flexible Polyimide-based Printed Circuit Board (PCB). This flexible PCB allows the antenna to safely roll during deployment, avoiding damage and facilitating compact storage. However, Polyimide poses challenges due to higher losses and …

Numerical Methods For Approximating Line Integrals Over Implicitly Defined Curves, Raghd Alsaadawi

Theses

In this thesis, we develop and investigate a predictor-corrector method for the numerical tracing of implicitly defined curves. The study begins with the introduction of modified numerical integration techniques — specifically, the modified trapezoidal and modified midpoint rules — for evaluating the line integral of a vector field along an implicitly defined curve. Furthermore, we explore higher-order methods aimed at improving the accuracy of such integrals. Theoretical and numerical results, including asymptotic error expansions, are presented to support the analysis. In addition, several numerical experiments are carried out to illustrate the effectiveness and robustness of the proposed approaches.

Wavelet-Based Multi-Step Methods For Systems Of Differential Equations, Rashad Assad Hijji

Theses

Wavelets have been widely used in many areas of engineering and mathematics, including the development of multistep algorithms to solve initial value problems (IVPs) in the context of the Galerkin method using Daubechies' wavelets. The main scope of our work is to build a comprehensive framework for solving Systems of Differential equations using the compactly supported wavelets proposed by I. Daubechies. Wavelets are mathematical functions that decompose data into distinct frequency components, and each element is analyzed with a resolution that matches its scale. Compact support of Daubechies wavelets is key in allowing them to be computationally efficient for high-dimensional …

On-Demand Heterogeneous Drone Delivery Problem, Xupeng Wen, Zhiguang Cao, Shu Xu, Dapeng Ren, Guohua Wu, Yaoxin Wu

Research Collection School Of Computing and Information Systems

In the on-demand problem domain, actual demand frequently deviates from the expected demand. This paper intricately delves into the exploration of on-demand heterogeneous multi-drone routing problem (ODHDRP), in which a transport drone carries multiple terminal drones to subregions in the first echelon, and the terminal drones deliver parcels during a flight trip to customers with demands in subregions to maintain economies of scale in the second echelon. We formulate the customer demands using a normal distribution, and exploit a reliability model of customer demands with chance constraints. To solve the ODHDRP efficiently, we propose a hybrid iterative optimisation heuristic (HIOH) …

Demystifying Memorization In Llm-Based Program Repair Via A General Hypothesis Testing Framework, Jiaolong Kong, Xiaofei Xie, Shangqing Liu

Research Collection School Of Computing and Information Systems

Large Language Models (LLMs) have achieved remarkable success in various applications, particularly in code-related tasks such as code generation and program repair, setting new performance benchmarks. However, the extensive use of large training corpora raises concerns about whether these achievements stem from genuine understanding or mere memorization of training data—a question often overlooked in current research. This paper aims to study the memorization issue within LLM-based program repair by investigating whether the correct patches generated by LLMs are the result of memorization. The key challenge lies in the absence of ground truth for confirming memorization, leading to various ad-hoc methods …

Modfinity: Unsupervised Domain Adaptation With Multimodal Information Flow Intertwining, Shanglin Liu, Jianming Lv, Jingdan Kang, Huaidong Zhang, Zequan Liang, Shengfeng He

Research Collection School Of Computing and Information Systems

Multimodal unsupervised domain adaptation leverages unlabeled data in the target domain to enhance multimodal systems continuously. While current state-of-the-art methods encourage interaction between sub-models of different modalities through pseudo-labeling and feature-level exchange, varying sample quality across modalities can lead to the propagation of inaccurate information, resulting in error accumulation. To address this, we propose Modal-Affinity Multimodal Domain Adaptation (MODfinity), a method that dynamically manages multimodal information flow through fine-grained control over teacher model selection, guiding information intertwining at both feature and label levels. By treating labels as an independent modality, MODfinity enables balanced performance assessment across modalities, employing a novel …

Rich Models And Methods For On-Demand Same Day Deliveries, Zhiqin Zhang

Dissertations and Theses Collection (Open Access)

Same-day delivery has brought numerous conveniences to people’s lives, but it has also presented challenges in terms of service management. To effectively optimize on-demand same-day delivery operations within urban logistics, intelligent decision-making strategies capable of adapting to rapidly changing circumstances are essential. Employing effective decisionmaking strategies that account for order allocation, route planning, courier scheduling, and other relevant factors, is pivotal in advancing logistics operations, enhancing efficiency, customer satisfaction, and resource utilization in the context of dynamic same-day delivery problems.

The focus of this thesis revolves around different emerging challenges presented by on-demand same-day delivery problems, with a particular emphasis …