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Assessing The Role Of Ocean Literacy In Liberia's Blue Economy : Pathway To Sustainable Blue Ocean Development In Liberia, Precious Tete Nah

Ocean Sustainability, Governance & Management Dissertations

Ocean literacy involves understanding the fundamental concepts of the ocean's functioning, leading to informed and responsible decisions about the ocean. This understanding is vital for developing responsible ocean citizenship and implementing measures to sustain the ocean, as it highlights the ocean's influence on humans and the impact of human activities on it. Using a qualitative research method with a purposive sampling approach, the research asks focus group representatives from New Kru Town and Westpoint, both closed- and open-ended questions, on the importance of ocean literacy, challenges, prospects, and recommendations to promote sustainable blue ocean development.

The results of the research …

(Si15-142) Selection Of Single Sampling Plans Based On Zero Inflated Binomial Distribution Using Cost Optimization, Sangeetha S., Shalini K., Hemalatha R., Priyadharshini R.

Applications and Applied Mathematics: An International Journal (AAM)

Economic design of sampling plans involves creating sampling plans that minimize the total cost associated with the inspection process while ensuring quality. It aims to address the quality risk concerns of both producer and consumer, ensuring product quality while minimizing inspection costs. This article’s objective is to design single sampling plans by attributes based on Zero-inflated Binomial (ZIB) distribution, using cost optimization principles by developing an economic model aimed at achieving optimal total cost by considering the Average Total Inspection (ATI). Numerical illustration is provided to illustrate the selection of single sampling plans under ZIB distribution that minimizes producer’s total …

(Si15-093) Dynamics Of The Generalized Nonlinear Schrödinger Equation With A Source Using An Analytical Method, Manish Raghav, Manoj .

Applications and Applied Mathematics: An International Journal (AAM)

In the present article, an analytical method is used to obtain hyperbolic, trigonometric, and rational solutions of the generalized nonlinear Schrödinger (GNLS) equation with a source. The ability of solitons to preserve their shapes during propagation makes them suitable for optical fiber communication. Solutions to the generalized nonlinear Schrödinger equation with a source can also describe solitons, and understanding their dynamics helps to design communication systems based on solitons. The analytical method used is compelling and effective for finding exact solutions to various nonlinear evolution equations (NLEEs). To further understand the phenomena, we create 3−D, contour, and 2−D graphs of …

(Si15-107) Mathematical Modeling Of Cancer Dynamics Stability Analysis Of Post Therapy Protection, Rajendran Swetha, Tharmalingam Gunasekar, Kamalendra Kumar, Krishnasamy Sakthivel

Applications and Applied Mathematics: An International Journal (AAM)

The study of PSITPS mathematical model is developed to analyze cancer dynamics, focusing on post-therapy protection. The model’s solution is rigorously examined for boundedness and positivity of solutions. Equilibrium points are identified, and numerical methods are employed to study stability. Simulations using accurate cancer data demonstrate the effectiveness of post-treatment protection in controlling cancer spread and minimizing recurrence. Stability analysis confirms the model’s predictive capability, offering valuable insights into long-term patient outcomes. The results highlight the importance of continuous post-treatment care in improving survival rates and reducing disease prevalence. This study provides a framework for optimizing cancer treatment strategies by …

Numerical Simulations Of Highly Eccentric Systems Of Binary Neutron Stars With Spin, Victoria White

Harriet L Wilkes Honors College Theses

Binary Neutron Star (BNS) mergers are among the most energetic events in the universe, producing gravitational waves, electromagnetic radiation, and heavy elements. While previous research has utilized simulations for collisions, few studies have accounted for how the spin of the stars affects mergers. This thesis contains a general overview of the topic and a research component conducted in the field of numerical relativity. High-performance computing was used to simulate BNS collisions, examining how spin affects the inspiral, merger, and post-merger phases. Computations used the Einstein Toolkit, Cactus framework, and the numerical tool developed by the FAU Relativity Group, Sgrid. The …

Use Of Modified Z-Domain Peptides To Specifically Label The Constant Region Of Immunoglobulin G And Vegf, Madeline Allen

Department of Chemistry: Dissertations, Theses, and Student Research

Antibodies are increasingly being used in medicinal therapies due to their ability to specifically bind to a target antigen. This fundamental behavior of antibodies has been used as a key component in drug development to address common problems with traditional drug molecules such as off-targeting, fast drug clearance, and low efficacy. This thesis provides some background into how antibodies can be used as potential treatments for a few diseases. Chapter 1 begins with an overview of the human immune system, and the role antibodies play within it. Then, the variety of ways in which antibodies can be used as medicinal …

(Si15-022) Five Efficient Cryptography Authentication Schemes With Functional Relation On General Spaces, L. Sreenivasulu Reddy, S. Lakshmisri

Applications and Applied Mathematics: An International Journal (AAM)

This work addresses the growing demand for diversification in cryptographic schemes to secure communication. This work proposes a novel suite of algorithms, including two block ciphers (TPBlock and TAP-Block), two stream ciphers (TP-Stream and TAP-Stream), and a zero-knowledge proof scheme (F-zero knowledge proof). All schemes leverage functional relations defined over the real number space with a dimension greater than one for encryption, decryption, and key generation, offering an alternative to the number-theoretical aspects and algebraic structures commonly used in existing schemes. The main goal of this work is to introduce and propose these five novel cryptographic schemes to provide authentication …

(Si15-010) On Perturbations Of Gabor Frames, Jamkhongam Touthang

Applications and Applied Mathematics: An International Journal (AAM)

Stability plays a crucial role in frame theory and its applications. The present paper studies the interaction between Gabor frames and perturbations, presenting perturbation results related to small changes of the frame parameters and the window functions both in regular and irregular settings. Examples are provided for illustration. Additionally, the paper briefly discusses algorithms pertinent to Gabor frames under perturbations and highlights challenging areas in the field.

(Si15-121) Analyzing Seitr Tuberculosis Transmission Model Using Caputo–Fabrizio Fractional Derivative With Diverse Contact Rates, S. S. Sumaiya Banu, T. Gunasekar, S. Manikandan, Kamalendra Kumar, M. Suba

Applications and Applied Mathematics: An International Journal (AAM)

In the modern age, tuberculosis remains a pressing global health concern. Our study introduces and evaluates the SEITR pandemic TB transmission model, dividing the population into five compartments to explore distinct characteristics relevant to our investigation. Additionally, we delve into the application of fractional calculus. Through the Laplace transform method, we derive series solutions for all compartments, ensuring their existence and uniqueness. We also investigate the reproduction number of the tuberculosis epidemic model, examining how varying contact rates impact disease spread. We apply the predictor-corrector method for the Caputo-Fabrizio fractional derivative to verify the accuracy of our approach. This accurately …

(Si15-120) Exploring Fractional Difference Equations And Their Applications With Mahgoub-Transform, Tharmalingam Gunasekar, Periyasamy Udhayasankar, Prabakaran Raghavendran, Kamalendra Kumar

Applications and Applied Mathematics: An International Journal (AAM)

We discuss the introduction and study of the nabla discrete Mahgoub transform along with its defining properties. The transform of fractional sums and fractional differences are derived, demonstrating the applicability of the transform from the computational viewpoint. Employing the transform, fractional difference equations with initial value problems are solved, thereby enhancing the knowledge of their closed forms. As a side-effect of the Mahgoub-transforms, an attractive connection is established, showing that the discrete Mittag-Leffler function acts as the eigenfunction for the Caputo-type fractional difference operator nabla. These results strengthen the core basis for fractional calculus and herald industrial applications in various …

Assessing Expected Cover Of Invasive Flora Species Near Corridor Features By Distance, Joshua G. Logan

Theses

Fragmentation of landscapes has been a growing topic of interest within scientific literature over the past several decades, as the way we as humans affect our planet becomes more apparent as the years go on. As humans, we have shaped the land and what it contains in immeasurable ways, erasing or forever altering entire natural ecosystems. Chief among the drivers altering these ecosystems is the fragmentation of landscapes, which can have all kinds of effects on natural ecosystems, from limiting nutrient transport to providing easier access for invasives to permeate throughout a landscape. Corridors are significant areas of interest regarding …

Investigating The Redox Properties Of Photoredox Catalysts And Organic Compounds Through Quantum Chemistry, Peter Girnt

Open Access Theses & Dissertations

This dissertation explores the redox behavior of organic and organometallic systems using density functional theory (DFT), focusing on electron transfer mechanisms and structur –property relationships. The first study investigates the two-electron reduction of bianthrone isomers, revealing a potential-inverted ECE mechanism driven by isomerization and electronic destabilization. The second study examines ruthenium photoredox catalysts, showing that ligand fusion positions significantly affect redox potentials due to backbone dearomatization, while p extension has minimal impact. Together, these findings provide insight into redox tuning strategies and support the rational design of advanced catalysts and electroactive materials.

Enhancing Llm Code Generation: A Systematic Evaluation Of Multi-Agent Collaboration And Runtime Debugging For Improving Accuracy, Reliability, And Latency, Nazmus Ashrafi

Theses

The use of large language models (LLMs) for automated code generation has emerged as a significant focus within AI research. As these pretrained models continue to evolve, their ability to understand and generate complex code structures has opened up new possibilities for automating intricate programming tasks with greater accuracy. Although contemporary foundational models demonstrate promising results, researchers continue to explore optimal post-training strategies to enhance code quality. These include supervised fine-tuning, retrieval-augmented generation (RAG), debugging, and many others. In this thesis, I combine two such widely used post training approaches—namely (1) multi agent collaboration and (2) runtime execution of information-based …

Improved Extraction And Detection Of Disinfection Byproducts, Impacts Of Wildland-Urban Interface Wildfires On Drinking Water, And Change In Disinfection Byproducts Over Time In Chlorinated Vs. Chloraminated Distribution Systems, Patrick Thomas Justen

Theses and Dissertations

Drinking water disinfection is critical to prevent the occurrence of waterborne pathogens in drinking water. However, disinfection causes the unintended formation of disinfection byproducts (DBPs) through the reaction of disinfectants (e.g., chlorine, chloramine) with natural organic matter (NOM), algal matter, or anthropogenic pollutants present in source waters. Exposure to DBPs is associated with increased bladder cancer, colorectal cancer, miscarriage, and birth defects. The U.S. EPA currently regulates eleven DBPs in drinking water—four trihalomethanes, five haloacetic acids, bromate, and chlorite. However, research shows that DBP related toxicity in drinking water is driven mainly by other, non-regulated DBPs, particularly iodinated DBPs and …

The Science Of Sound: Studying The Cognitive, Emotional, And Physiological Effects Of Frequency, Genre, And Music, Jett Yarborough

Senior Honors Theses

Music influences emotion, physiology, and cognition, yet little is known about how the frequency it is tuned to affects these influences. Prior research has shown that music tuned to 432 Hz can reduce stress, lower blood pressure, and improve sleep. My colleagues and I conducted two studies to investigate this. Our research found that music tuned to 432 Hz promotes a significant increase in memory retention and induces a state of focus and relaxation. These results suggest that shifting from the standard tuning frequency of 440 Hz to 432 Hz could have a profoundly positive impact on our daily lives. …

47th Biennial Convention Of Sigma Gamma Epsilon, Western Illinois University, April 11–13, 2025, Richard L. Ford, Lee S. Potter

The Compass: Earth Science Journal of Sigma Gamma Epsilon

The Society of Sigma Gamma Epsilon (SGE), the national honorary society for the Earth sciences, held its 47th biennial convention (April 11–13, 2025) at the Quad Cities campus, located in Moline, Illinois, of Western Illinois University (WIU). The convention was hosted by SGE’s Delta Psi Chapter and the Department of Earth, Atmospheric, and Geographic Information Sciences at WIU. Ten (10) of SGE’s approximately 57 active collegiate chapters sent delegates to the convention. The traditional convention field trip, an exploration of the Paleozoic stratigraphy and economic geology of the Quad Cities area of Illinois and Iowa, made stops at the Fryxell …

Assessing The Effectiveness Of Bridge Grate And Pipe Cattle Guard Designed To Mitigate Ocelot Road Mortality On Texas State Highway, Rupesh Maharjan, John H. Young Jr., Kevin W. Ryer, Md. Saydur Rahman, Richard J. Kline

School of Earth, Environmental, & Marine Sciences Faculty Publications

The mitigated and fenced section of State Highway 100, extending from Laguna Vista to Los Fresnos, includes five wildlife crossing structures and 16 modified cattle guards (also called wildlife guards) installed to mitigate ocelot road mortality. Bridge grate and pipe wildlife guards were deployed at vehicle entries, and we evaluated their effectiveness in preventing meso-carnivores and ungulates from entering the roadway through the fence gaps from April 2020 to 2024. Wildlife guards collectively were >82% effective in repelling ungulate attempts to enter the roadway, while only 16.64% of meso-carnivore attempts were repelled. The pipe wildlife guard (PWG) design repelled 86.79% …

Chemistry And Biochemistry Affiliated Publications: Snapshot Of The Research Publications 2019-2024., Jeremy J. Smith, Lutishoor Salisbury

University Libraries Faculty Publications and Presentations

This report highlights the chemistry and biochemistry faculty publications for the period 2019-2024. It includes tables identifying the types of publications, the characteristics of the authors, inter-departmental and external cooperation, summary of the citations of the publications, and the JCR ranking of the journals in which they published.

Morphology-Aware Hrv Estimation From Wrist Ppg In Sedentary Scenarios, Changshuo Hu, Hung Manh Pham, Dong Ma

Research Collection School Of Computing and Information Systems

Photoplethysmography (PPG) is widely used in wearable devices for non-invasive heart rate variability (HRV) monitoring. While most prior work focuses on mitigating motion artifacts, recent studies highlight that even subtle contact pressure variations can distort waveform morphology and lead to inaccurate HRV estimates. In this work, we propose a morphology-aware deep learning framework that conditions HRV estimation on beat-level waveform types. Our model jointly encodes the raw PPG waveform and a sequence of pressure-induced morphology labels using parallel encoders, integrates them via cross-attention, and predicts normal-to-normal (NN) intervals and beat count to support downstream HRV computation. Evaluated on the public …

Cross-Subject Mind Decoding From Inaccurate Representations, Yangyang Xu, Bangzhen Liu, Wenqi Shao, Yong Du, Shengfeng He, Tingting Zhu

Research Collection School Of Computing and Information Systems

Decoding stimulus images from fMRI signals has advanced with pre-trained generative models. However, existing methods struggle with cross-subject mappings due to cognitive variability and subject-specific differences. This challenge arises from sequential errors, where unidirectional mappings generate partially inaccurate representations that, when fed into diffusion models, accumulate errors and degrade reconstruction fidelity. To address this, we propose the Bidirectional Autoencoder Intertwining framework for accurate decoded representation prediction. Our approach unifies multiple subjects through a Subject Bias Modulation Module while leveraging bidirectional mapping to better capture data distributions for precise representation prediction. To further enhance fidelity when decoding representations into stimulus images, …

Data-Driven Optimization And Parameter Estimation For A Metric Graph Epidemic Model With Applications To Covid-19 Spread In Poland: A Real-World Example Of Optimization For A Challenging Rosenbrock-Type Objective Function, Hannah Kravitz, Christina Duron, Brittani Nieves, Moysey Brio

Mathematics and Statistics Faculty Publications and Presentations

In this paper, we apply data-driven optimization to estimate key parameters in a metric graph-based epidemiological model, with the aim of analyzing the effect of road networks on the geographic spread of epidemics. As a case study, we fit our model to data from the COVID-19 pandemic in Poland during 2021. Our dataset integrates county-level daily case reports, national census information, and traffic flow studies. This framework allows us to examine the relative contribution of specific travel routes over time and infer unobserved transmission patterns in the presence of incomplete or unreliable case reporting. The optimization problem that arises from …

Memad: Structured Memory Of Debates For Enhanced Multi-Agent Reasoning, Shuai Ling, Lizi Liao, Dongmei Jiang, Weili Guan

Research Collection School Of Computing and Information Systems

Large Language Models (LLMs) demonstrate remarkable in-context learning capabilities but often struggle with complex, multi-step reasoning. Multi-Agent Debate (MAD) frameworks partially address these limitations by enabling iterative agent interactions. However, they neglect valuable historical insights by treating each new debate independently. In this paper, we propose Memory-Augmented MAD (MeMAD), a parameter-free memory-augmented MAD framework that systematically organizes and reuses past debate transcripts. MeMAD stores structured representations of successful and unsuccessful reasoning attempts enriched with self-reflections and peer feedback. It systematically retrieves them via semantic similarity at inference time to inform new reasoning tasks. Our experiments on challenging mathematical reasoning, scientific …

Advances In Iot, Ai, And Sensor‑Based Technologies For Disease Treatment, Health Promotion, Successful Ageing, And Ageing Well, Yuzhou Qian, Keng Siau

Research Collection School Of Computing and Information Systems

Recent advancements in the Internet of Things (IoT) and artificial intelligence (AI) are unlocking transformative opportunities across society. One of the most critical challenges addressed by these technologies is the ageing population, which presents mounting concerns for healthcare systems and quality of life worldwide. By supporting continuous monitoring, personal care, and data-driven decision-making, IoT and AI are shifting healthcare delivery from a reactive approach to a proactive one. This paper presents a comprehensive overview of IoT-based systems with a particular focus on the Internet of Healthcare Things (IoHT) and their integration with AI, referred to as the Artificial Intelligence of …

Economic Viability And Environmental Sustainability: A Cost-Benefit Analysis Of Green Technologies In Mineral Extraction, Tshinkobo Bukasa Orphea, Agyingi Babaca Agyingib, Xiangrui Meng

Journal of Sustainable Mining

This research offers a novel approach to comparing green technologies’ economic profitability and environmental sustainability of their mineral extraction based upon econometric and life cycle assessment methodologies. Quantitative results show attractive results with an NPV of $2,014,001 and an IRR of 17%. In the third year, the project nets at $300,000, or 63%, at a 7% discount rate. However, soil protection remains challenging, but pollution coefficients are improved, as evidenced by environmental impact assessments (EIAs). The findings in the study further underscore how regulatory frameworks and market drivers dictate the use of green technology. The economic, environmental and regulatory costs …

Effect Of Coniferous Trees And Water Availability On Soil Acidification, Jessica A. Cheever

Journal of the Symposium of University Research and Creative Expression

Project Mentor(s): Mary Poulson, PhD

Water availability and coniferous tree species can cause acidification and a change in soil fertility. Previous research in European forests found that rainfall, soil acidity, and conifer prevalence influenced soil quality and biodiversity. However, not much is known about these effects in the Pacific Northwest’s forests. Three forests were chosen based on a gradient of annual precipitation. The Hoh Rain Forest, the Tiger Mountain State Forest, and the Okanogan-Wenatchee National Forest were used for wet, mesic, and dry conditions, respectively. Each location had a three-by-six grid spaced 50 meters between each plot. The location was …

Synthesis Of Nitrogen-Enriched 3d Graphene Foam For Electrochemical Sensing Of Hydrogen Peroxide (H₂O₂), Bhargavi Dronavalli, Madhava Rao Vallabhaneni, Jatla Murali Prakash, Deepti Kolli, Dandamudi Srilaxmi

Karbala International Journal of Modern Science

In this work, A simple hydrothermal process was utilized to create 3D-foam-type Nitrogen-doped graphene (NDG). The synthesized material was characterized using a range of physicochemical characterization techniques. These techniques confirm that nitrogen is successfully incorporated into the carbon network, resulting in NDG. Cyclic voltammetry (CV) investigation demonstrated that NDG-modified glassy carbon electrode (NDG/GCE) displayed finite charge transfer properties against typical redox systems. NDG/GCE is identified as a simple, facile, and efficient electrocatalyst material for the estimation of hydrogen peroxide (H₂O₂). From CV analysis, it is revealed that NDG/GCE can produce a signal for electrochemical quantification of …

Investigating The Market Dynamics Of Aeroponically Cultivated Products With Delay, Pulak Kundu, Uzzwal Kumar Mallick

Mathematical Modelling and Numerical Simulation with Applications

Aeroponically grown potatoes offer higher yields and year-round production but often face delayed market entry due to high setup costs, technical barriers, and logistical challenges. A delay-based mathematical model has been newly proposed in this study to analyze the dynamics of demand, supply, and pricing for aeroponically grown products. The model’s existence, stability, and sensitivity have been investigated analytically, and numerical simulations have been carried out using the Runge-Kutta 4th order method with the dde23 solver. Findings reveal that market stability is maintained when delays are below seven years, but delays beyond this threshold lead to persistent fluctuations in price, …

Drawing On Uncertainty Methodologies Of Neutrosophic Hypersoft Sets In Cognitive Computing-Driven Healthcare Systems, Mona Mohamed, Nurhan Alaa

Neutrosophic Systems with Applications

A new paradigm called cognitive computing simulates human reasoning and decision-making through integrating advanced techniques such as artificial intelligence (AI) and natural language processing (NLP). Cognitive computing systems, in contrast to traditional systems, can handle both structured and unstructured data, adjust to new information, and offer context-sensitive insights. This study examines how cognitive computing improves decision-making, personalization, and human-machine collaboration in various fields. Cognitive computing in the healthcare sector processes clinical notes, imaging data, and electronic health records to help physicians with diagnosis, treatment planning, and patient engagement. This study examines key applications, including their role in diagnostic support, where …

A Feature Engineering Technique For Enhancing The Generalization Of Machine Learning Models In Estimating Crop Evapotranspiration, Gaku Yokoyama, Sohta Harigai, Shigehiro Kubota, Koichi Nomura, Gregory R. Goldsmith, Daisuke Yasutake, Tomoyoshi Hirota, Masaharu Kitano

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Accurate and precise estimation of evapotranspiration (ET) is crucial for understanding the terrestrial carbon, water, and energy cycles. While process-based models of ET, such as the Penman–Monteith model offer robust generalization capabilities, they are limited by the need for detailed parameters (e.g., stomatal conductance,) that are challenging to measure continuously. On the other hand, machine learning models can estimate ET by capturing relationships between ET and environmental variables without experimentally measuring model parameters. However, machine learning models face the challenge of limited generalizability. This issue is particularly significant given the uncertainty introduced by changing climatic …

High-Order Adaptive Solutions For Coupled Fractional Riccati Equations Via Daubechies Redundant Frames, Mutaz Mohammad, Alexander Trounev

Mathematical Modelling and Numerical Simulation with Applications

Coupled fractional Riccati equations play a fundamental role in modeling complex systems with memory effects and anomalous diffusion, frequently arising in engineering, control theory, finance, and quantum mechanics. Their analytical and numerical treatment remains highly challenging due to the nonlocal nature of fractional-order derivatives and the presence of nonlinear coupling terms. This study introduces an adaptive numerical framework that combines the Caputo fractional derivative with redundant Daubechies wavelet frames. The method leverages multi-resolution analysis, compact support, and controlled redundancy to achieve accurate approximation of both localized and global solution features, particularly in scenarios characterized by singular behavior and long-range memory …