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Academy Presidents And Institutional Members, Academy Editors

Journal of the Arkansas Academy of Science

No abstract provided.

Table Of Contents, Academy Editors

Journal of the Arkansas Academy of Science

No abstract provided.

Journal Of The Arkansas Academy Of Science Volume 79, Academy Editors

Journal of the Arkansas Academy of Science

No abstract provided.

Analysis On Thermo-Viscous Steady Fluid Motion Over An Impermeable Infinitely Stretched Horizontal Moving Rectangular Surface, P. Krishna, N. Pothanna, K. Spandana

Mansoura Engineering Journal

This study presents analysis on thermo-viscous steady fluid motion over an impermeable infinitely stretched horizontal moving rectangular surface. The numerical results have been found employing R-K method of order 6 shooting techniques developed in Mathematica software ND solve for the flow adaptable equations comprising temperature and velocity. The flow behavior and the impacts of material constraints on the flow region have been analyzed and deliberated taking the help from the generated graphs. The variations of these flow fields have been studied for wide spectrum of physical characteristics which influences the nature of thermo-viscous fluid. The impact of viscosity, constant pressure …

Adaptative And Structured Optimization Stockwell Transform For Robust Power-Quality Disturbances Detection, Moudjibatou Afoda, Séna Apeke, Filippo Gatti, Alessio Iovine, Léonce W. Tokam, Guy M. Toche Tchio, Ouro-Djobo S. Sanoussi

Mansoura Engineering Journal

The monitoring of electrical power quality requires advanced analysis techniques capable of accurately detecting and localizing non-stationary disturbances. This work proposes a structured and adaptive optimization of the Stockwell Transform (ST), referred to as Two-Power Optimization (TPO). A multiparametric Gaussian window governed by four parameters (m, p, k, r), is introduced, and a genetic algorithm is applied independently to each signal to optimize these parameters. The optimization process adapts the analysis scale to the local characteristics of the signal while preserving the physical consistency of the window function. Simulation results on synthetic power quality signals demonstrate that the proposed method …

Finite Element Modelling On A Non-Linear Radiative Hybrid Nanofluid Flowing Through A Rotating Disk, N. Janaki Phani Madhuri, Md. Shamshuddin

Mansoura Engineering Journal

This study develops a finite element model to investigate the MHD flow and heat transfer phenomena of Cu–H₂O and Cu–Fe₃O₄–H₂O hybrid nanofluids flow across a spinning disk modelling by the Tiwari–Das model. The governing non-dimensional momentum and energy equations account for the effects of buoyancy, nonlinear radiation, and ohmic heating. The nonlinear coupled system is solved with the element method (FEM) to find the velocity and temperature fields. Parametric studies will investigate the effects of the magnetic field, buoyancy, volume fraction of nanoparticles, and radiation. Skin friction and Nusselt number are also reported. The results show that with the hybrid …

Real-Time Iot-Enabled Dissolved Oxygen Monitoring And Automated Wastewater Recirculation In Constructed Wetlands, Sivasankar Pandiarajan, Vanitha Sankararajan, Devarinti Chandu

Mansoura Engineering Journal

Wastewater treatment is necessary for environmental conservation and combating water pollution. This study demonstrates real-time dissolved oxygen (DO) monitoring in constructed wetland treatment. The system would ensure an adequate supply of oxygen through automated water circulation whenever the level is below 4 mg/L, and shut down when it reaches the normal level. From experiments conducted, it was observed that within three automated circulation processes, it is possible to increase DO concentrations from 0.5 mg/L to 5.0 mg/L. Additionally, Total Dissolved Solids reduced from 1,380 ppm to 920 ppm. pH also stabilized from 8.38 to 7.9. In this system, data is …

Bridging Machine Learning And Climate Futures: A Framework For Explainable, Self-Directed (Agentic) Ai Models In Monitoring, Mitigation, And Governance Of Anthropogenic Climate Impacts, Vijayanandh Rajamanickam, Ketaki Kulkarni, Vishwanadham Mandala, Ozgur Kisi

Mansoura Engineering Journal

Environmental and societal damage due to anthropogenic climate change demands detection and mitigation strategies that are both effective and accountable. Machine Learning (ML) appears to offer a powerful set of tools but remains unexploited in these areas. A key barrier remains its poor ability to draw causal inferences about external systems, an essential requirement for meaningful continued monitoring, acting on, and shaping of the climate. Explainable, self-directed learned models operate by attributing environmental changes and deciding how best to model the resulting dynamics—they offer a natural solution. Recent developments in computational ecology, meteorology, and ML are combined to propose a …

Processing Mechanism And Efficacy Maintenance Strategy Of Ginseng Active Ingredients Based On Spectroscopy Technology, Yang Hantong, Kong Linghui, Jiang Mengmeng, Wang Yingxiu, Li Xiangguo

Food and Machinery

Ginseng, as a medicinal and edible plant, has ginsenosides as its core active components, which are widely applied due to their physiological functions such as antioxidant and anti-inflammatory activities; however, their structures and activities are easily affected by food processing. During processing steps such as cleaning, steaming/boiling, and fermentation, temperature, pH, and microbial enzyme systems alter the types, contents, and stability of active components through reactions such as hydrolysis and oxidation. The intrinsic linkage mechanism of "component transformation-activity-bioavailability" constitutes a core focus and challenge in current research. This study, based on spectroscopic techniques including high-performance liquid chromatography (HPLC), nuclear magnetic …

Ontology-Based Decision Support System For Improving Aquaculture Management, Thuy Thi Thu Pham, Phuong Thi Can, Nga Thi Thanh Ha

Journal of Marine Science and Technology–Taiwan

Early detection of shrimp diseases is vital for reducing losses and ensuring sustainable aquaculture. In this study, a novel ontology-driven framework for shrimp disease diagnosis that integrates environmental knowledge with machine learning-based image analysis is proposed. An ontology was constructed from a structured dataset of environmental parameters and farm conditions related to shrimp diseases, which formally represents concepts such as farm characteristics, environmental factors, symptoms, and disease types. Two public shrimp image datasets were subsequently used to train convolutional neural networks (ResNet50 and MobileNetV2) for automated disease classification. The predicted disease labels and confidence scores were mapped onto the ontology. …

Case Study On Operational Performance Improvement By Turbocharger Nozzle-Ring Modification In Shipboard Generators, Jong-Hun Im, Mukyeong Kang, Sang-Deuk Lee

Journal of Marine Science and Technology–Taiwan

Owing to increasingly stringent emission regulations imposed by the International Maritime Organization and rising fuel prices, the demand for enhanced energy efficiency and emission control in marine power systems is increasing. This study presents a case study in which the performance of an aging auxiliary generator is restored by modifying the turbocharger nozzle ring. The vessel, a 12-year-old crude-oil tanker, experienced repeated operational issues with its No. 3 generator. This included elevated exhaust gas temperatures, reduced intake air pressure, and frequent turbocharger surges. To address these challenges, the nozzle-ring blade angle was reduced by approximately 2° using spare components, while …

Towards Sustainable Marine Education: Assessing High School Students’ Understanding Of Conservation Concepts, Cheng-Chieh Chang, Tsuyoshi Sasaki, Ya-Yin Liao, Ling-Ya Hung, Liang-Ting Tsai

Journal of Marine Science and Technology–Taiwan

This study assesses the concepts of marine resource conservation and sustainability among Taiwanese high school students by developing a Chinese version of the Marine Resources Conservation and Sustainability Scale. Grounded in the cognitive, socio-emotional, and behavioral learning objectives outlined in UNESCO’s Education for Sustainable Development Goals (ESDGs), the scale targets students aged 16 to 18 to examine gender differences in marine knowledge and conservation concepts. The scale comprises 31 items across four dimensions: the first section evaluates marine knowledge, while the remaining dimensions utilize a four-point Likert scale to assess cognitive, socio-emotional, and behavioral learning objectives, respectively. The results indicate …

Dynamic Governance Of Transboundary Fisheries Through Deep Learning And High-Frequency Vessel Tracking Data For Climate-Resilient Management: An Application To The East China Sea, Qin Lin, Yaqing Shu, Manel Grifoll, Hongxiang Feng

Journal of Marine Science and Technology–Taiwan

Transboundary fisheries governance is increasingly challenged by jurisdictional conflicts, regulatory asymmetries, and climate-induced stock shifts in fish stocks, especially in contested regions like the East China Sea (ECS). This study capitalizes on China’s high-frequency BeiDou Navigation Satellite System (BDS) data (June 2021–May 2022) to pioneer a CNN-BiLSTM deep learning model to dynamically identify fishing hotspots and evaluate policy effectiveness. By integrating vessel trajectories, environmental variables, and regulatory events, we examine spatiotemporal patterns of fishing effort relative to seasonal bans, extreme weather, and quota systems. Key findings reveal: (1) post-moratorium (September–December) concentration of fishing intensity, peaking in November; (2) significant weather-driven …

Lock Scheduling Decisions And Strategy Optimization Under Operation Interruption Scenarios, Junhe Li, Qiang Zhang, Junpeng Jiang, Jiangchao Bao

Journal of Marine Science and Technology–Taiwan

Locks are critical nodes in inland waterway transportation systems that concentrate vessel traffic between upstream and downstream reaches, making their operations highly sensitive to hydrological conditions. Therefore, disruptions caused by droughts, floods, or routine maintenance can easily trigger congestion. To address this issue, this study systematically examines the interrelationships among the number of ships awaiting passage, scheduling strategies, the trade-off between lock chamber utilization and ship waiting time, the influence of ship entry sequences on user satisfaction, and the combined effects of these factors on overall lock scheduling performance. Based on these analyses, an integrated decision-making model for two-stage ship …

Corrosion Protection Assessment Of Offshore Wind Turbine Substructures Using Beasy Cp Simulation Analysis, Chuan-Yang Wan, Hung-Hua Sheu, Sheng-Yu Wang, Yao-Ming Wang, Wei-De Chen, Ming-Yuan Lin, Hung-Bin Lee

Journal of Marine Science and Technology–Taiwan

This study investigates the corrosion protection assessment of offshore wind turbine substructures established in the waters off Keelung, Taiwan. First, a cathodic protection system for the monopile foundation is designed and established. The Boundary Element Method (BEM) is applied using the BEASY simulation software to develop a 3D geometric model for cathodic protection. In the steel monopile simulation analysis, the exposed marine environment is set based on the sea conditions of the Keelung small boat marina, including parameters such as salinity, resistance, and polarization curves, to establish an effective cathodic protection system for underwater structures. By simulating these parameters, a …

Face-To-Face Versus Distance Education In Competence-Based Maritime Education And Training, Clara Borén, Marcella Castells-Sanabra, Manel Grifoll

Journal of Marine Science and Technology–Taiwan

The COVID-19 pandemic created significant challenges for higher education, with universities being shut down and face-to-face teaching and assessment shifting to an online format. This presented an opportunity to focus on the continuity of learning through distance education, especially in the maritime context, due to the on-board training requirements, and even though five years have passed, this shift has reshaped the education landscape, proving that remote learning has come to stay.

At the Barcelona School of Nautical Studies, we have developed a weather routing software in the framework of distance education and teaching innovation. We conducted a teaching trial alternatively …

A Bibliometric And Visualization Analysis Of Global Giant Clam Research, Chia-Hsiang Chen, Chih-Hsien Chang

Journal of Marine Science and Technology–Taiwan

In this study, bibliometric analysis and visualization tools were used to investigate the academic network and knowledge structure surrounding global giant clam research. A total of 551 relevant publications from the Web of Science database, published from 1900 to 2024, were analyzed. The findings indicate that research on giant clams has experienced considerable growth since 2012, peaking in publication output in 2021. Sixty-six countries were represented in the study sample, with the United States, Australia, China, Singapore, and Japan being the most represented ones. Notably, the rate of international collaboration was only 29%, highlighting a need for additional integrated cross-border …

Evaluating The Impact Of Early Contractor Involvement On Enhancing The Performance Of Construction Projects In Egypt, Samah Saleh Abdelraof, Ayman Ahmed Ezzat Othman, Lamees Mostafa Ahmed

Mansoura Engineering Journal

The construction industry constitutes a critical pillar of Egypt’s national economic growth and sustainable development. Despite its strategic importance, the sector continues to face persistent challenges, including chronic cost overruns, schedule delays, and inadequate coordination among stakeholders. These inefficiencies are largely attributed to the dominance of the traditional Design–Bid–Build (DBB) system, which enforces a rigid separation between design and construction, fostering adversarial relationships and project disputes, which highlights the need for alternative procurement approaches. This research investigates the impact of Early Contractor Involvement (ECI) as a collaborative procurement alternative to enhance project performance. Case studies show that ECI improves early-stage …

A Computational Micropatterning Approach To Study Caveolae And Protein Localization In Vascular Biology, Andrew B. Grespin

Electronic Theses and Dissertations

Caveolae are specialized, flask-shaped membrane invaginations highly expressed in endothelium and dysregulated in atherosclerosis. Caveolae play a central role in buffering membrane tension, yet the principles governing their spatial organization remain elusive. Thus, we sought to generate the most comprehensive and systematic analysis of blood vessel caveolar spatial organization. However, cell culturing, the backbone of human-focused biological research, does not standardly do well to model physiologically relevant cell behaviors such as migration or polarity-based tissue formation, particularly for punctate proteins and structures like caveolae. Micropatterns are cell-adhesive shapes that biophysically confine cell(s) to a user defined geometry which stereotype organelle …

Metal Oxide Nanoparticle‑Integrated Phema Hydrogels: Morphology, Chemical Properties, And Biological Interaction, Venkateswar Rao, Collin Cox, Brandon Clark, Arushi Rai, Erick S. Vasquez-Guardado, Madhuri Kango-Singh, Soubantika Palchoudhury

Chemical and Materials Engineering Faculty Publications

Hydrogels offer attractive matrices for incorporating inorganic metal oxide nanoparticles (NPs) to generate multifunctional hybrid materials, but challenges remain in scalable synthesis and correlating their properties to bio-interaction. Therefore, we report the synthesis and characterization of poly(2-hydroxyethyl methacrylate) (pHEMA) hydrogels, and pHEMA hydrogels encapsulating iron oxide or zinc oxide NPs, using a modified free-radical polymerization. Dose-dependent survivorship studies on Drosophila melanogaster revealed that both NP-embedded hydrogels are tolerated over a wide dose range (e.g., 50–200 mg), although ZnO NP-gels exhibit lower survivorship at some concentrations due to their inherent composition and a wider size distribution of iron oxide NPs.

Corrigendum To " Computational Investigation Of Cavitation Inception In Centrifugal Pumps"

Mansoura Engineering Journal

Abstract is not required.

Rape Pregnancies And Consequent Ptsd Resulting From The Overturn Of Roe V. Wade, Emma Lindenfelser, Yulia Garaeva, Nenette Nti-Agyemang, Ellen Davis, Anna Kabwa, Alexandra M Calaman

Binghamton University Undergraduate Journal

Prior to the 1973 Roe v. Wade ruling, access to safe legal abortions was limited and often restricted along racial, economic, and geographic lines. Nearly fifty years later, women’s health policy evolved again following the 2022 Dobbs v. Jackson Women’s Health Organization decision overturning Roe v. Wade. This court ruling decimated federal protections of abortion. This paper presents the research that the 2022 Dobbs judicial decision may contribute to and exacerbate rape-related PTSD on 1 out of 20 American who are unable to access a safe abortion after a rape-related pregnancy. Pregnant women living in conservative states that have outlawed …

Declination Of Groundwater Potential Zones Of Nashik, Maharashtra Using Geographic Information System With Analytic Hierarchy Process-Fuzzy Techniques, Madhusudhan M. Reddy, Bhogayya G. Naidu, Bharat N. Mulay, Ramanjaneyulu B, Ravi K. Kumar, Mirzi L. Betasolo, Praveen U. Goud, Snehal N. Chaudhari

Mansoura Engineering Journal

Groundwater is a critical resource for agriculture and domestic use in the semi-arid region of Nashik District, Maharashtra, where overexploitation and erratic climatic conditions have led to declining groundwater availability. This study integrates Geographic Information System (GIS) with Analytic Hierarchy Process (AHP) and Fuzzy-AHP techniques to delineate groundwater potential zones (GWPZs) and identify suitable sites for artificial recharge. A total of ten thematic layers drainage density, rainfall, geomorphology, elevation, distance from river, geology, slope, land use/land cover, topographic wetness index (TWI), and curvature were derived from SRTM DEM, Landsat-8, and IMD datasets, representing key controls on groundwater recharge, infiltration, and …

Leveraging Ict Adoption And Electricity Access For Sustainable Agricultural Productivity Among Nigerian Households, Menghan Huang, Qin Chen, Oluwayemisi Kadijat Adeleke, Mamdouh Abdulaziz Saleh Al-Faryan

The Philippine Agricultural Scientist

This study investigated ICT adoption (mobile phone and internet usage), access to electricity, and their impact on household agricultural productivity in Nigeria, Africa’s largest economy. Utilizing Wave 4 (2018 to 2019) Living Standards Measurement Study–Integrated Survey on Agriculture (LSMS–ISA) data covering 4,980 household heads, this study applied logit regression and Propensity Score Matching (PSM) for estimation, alongside a Cobb-Douglas production function to analyze input contributions to agricultural output. The findings revealed that the age, residential location, educational level, and access to electricity of household heads significantly determine technology adoption among farming households. Furthermore, ICT adoption exhibits a significant, positive relationship …

Can Generative Ai Make Farming Decisions? Current Status And Future Pathways: A Case Study In Row Crop Production With Chatgpt, Nipuna Chamara, Yufeng Ge, Joe Luck, Yu Pan, Saleh Taghvaeian, Cory Walters, Christopher Proctor, Daran Rudnick, Daren Redfearn

Department of Agricultural and Biological Systems Engineering: Faculty Publications

The agricultural decision-making process is experience-based, knowledge-dependent, time-sensitive, complex, and driven by historical data. Planting, fertilization, irrigation, and chemigation are key categories in farm decision-making, and currently there is no one-shot decision-support tool that covers all these activities. Generative Artificial Intelligence (AI) models are more advanced than traditional machine learning and deep learning models. These models have been trained on vast amounts of data from the internet, allowing them to accept unstructured data in various forms and generate human-like text, solutions to problems, and scenario predictions. Given this capability, we became interested in exploring the potential of generative AI in …

Large Scale Kmer-Based Proteomic Analysis: An Application Towards Evolutionary Constraint Discovery, Matthew Chak

Master's Theses

Large protein databases now make it possible to study short peptides across natural protein sequence space at unprecedented scale, but exhaustively counting k-mers across billions of protein sequences remains computationally difficult. This thesis develops an exact amino-acid k-mer counting method based on direct addressing, in which fixed-length amino-acid strings are encoded as base-20 integers and updated with a sliding-window recurrence. By avoiding key storage and collision resolution, this approach removes overhead inherent to hash-map-based methods when the k-mer space is sufficiently dense. A memory analysis shows when direct addressing is preferable to open-addressing hash tables, and expected-saturation calculations motivate its …

Computational Insights Into Nucleosome Dynamics In Epigenetics Using Molecular Dynamics Simulations, Rutika Patel

Dissertations, Theses, and Capstone Projects

Nucleosome core particles (NCP) are the building blocks that form a highly organized and compact chromatin structure. Nucleosomes package DNA in the nucleus of eukaryotic cells. The NCP consists of about 147 base pairs of DNA wrapped around the histone octamer, with 1.65 superhelical turns in a left-handed manner. The histone octamer is composed of two copies of H3, H4, H2A, and H2B. Together with histone H1 and linker DNA, they further assemble into a higher-order chromatin structure. The nucleosome complex is stabilized by electrostatic interactions between positively charged histone residues and the negatively charged DNA backbone. To effectively access …

A Review On Credit Card Electronic Fraud Detection Methodologies, Titilayo Mary Sayikanmi, Ibrahim Adepoju Adeyanju, Bolaji Abigail Omodunbi

Mansoura Engineering Journal

Credit card fraud remains a critical and escalating challenge within the global financial ecosystem, driving substantial annual losses and necessitating the continuous evolution of detection methodologies. This paper presents a systematic literature review, conducted via the Preferred Reporting Items for Systematic Reviews and Meta-Analyses framework, which comprehensively analyzes the state-of-the-art in electronic credit card fraud detection. Through a rigorous examination of 49 high-quality studies, this review maps the methodological evolution from traditional rulebased systems and statistical models to advanced artificial intelligence techniques, including machine learning, deep learning, and graph-based approaches. The analysis reveals that while individual methods possess distinct advantages …

Vergence Task-Based Neural Pathways With Binocularly Normal Vision And Comorbid Persistent Post-Concussive Symptoms -Convergence Insufficiency, Ayushi Sangoi

Dissertations

Binocular dysfunctions are more prevalent in the persistent post-concussive symptoms (PPCS) population than in the general population. The most prevalent binocular disorder is convergence insufficiency (CI), affecting 3-17% of the general population and up to 10 times as many people with PPCS. CI makes it difficult to fuse or maintain fusion on targets at near, and its symptoms include double or blurry vision and headaches when performing close-range tasks such as reading, which can exacerbate PPCS symptoms. Given controversy over the subjectivity and effectiveness of diagnostic tools and symptom surveys for both PPCS and CI, understanding why CI has high …

Transcranial Ac Modulation Of Cerebellar Nuclear Activity In Awake Animals, Nuran Kavakli

Dissertations

Entrainment of cerebellar nuclear (CN) cells via cerebellar transcranial alternating current stimulation (ctACS) has been reported in animals under ketamine/xylazine anesthesia. Our main objective was to demonstrate modulation of CN activity in unanesthetized, freely moving animals using ctACS. Multi-channel carbon-fiber electrodes were implanted into the interpositus nucleus for recording multi-unit (MU) activity, and thin-film electrodes were implanted subcutaneously over the posterior cerebellum for stimulation. A frequency-domain-based metric was developed to quantify modulation from MU signals. The results demonstrated modulation in a wide range of frequencies (4 Hz-300 Hz) as in anesthetized animals. In contrast, the amplitude of the peak in …