Engineering Commons^™

Metabolic Reprogramming Following Mitochondrial Transfer Between Idh2-Mutant Chondrosarcoma Cells And A Normal B-Cell Line, Caleb Wyckoff, Christopher Osgood, Ellen Jing, Michael Stacey

Bioelectrics Publications

Background/Objectives: Chondrosarcoma, glioblastoma, acute myeloid leukemia, chronic lymphocytic leukemia, and cholangiocarcinoma cancers all contain mutations in the gene isocitrate dehydrogenase 2 (IDH2). The mutant IDH2 enzyme metabolizes alpha-ketoglutarate (αKG) into the potent oncometabolite D-2-hydroxyglutarate (D2HG) in the mitochondria of these cancers, leading to altered cellular metabolism. Emerging evidence suggests that mitochondrial transfer between cancer and recipient cells represents an important form of intercellular communication that may influence cellular metabolism. The presence of intercellular TNTs between IDH2-mutant chondrosarcoma cells motivated an investigation into mitochondria-associated physiological changes occurring during an intercellular exchange with immune cells. A mitochondrial transfer is a two-way …

Nanosecond Electric Pulses As A Novel In Situ Vaccination Strategy For Cancer Treatment: Mechanisms, Challenges And Prospects, Siqi Guo

Bioelectrics Publications

Nanosecond electric pulses (nsEPs) are an emerging pulsed-power technology with unique bioelectric characteristics distinct from conventional long-pulse electroporation. As a tunable physical modality, nsEPs can modulate intracellular structures, membrane dynamics, and signaling pathways. Increasing evidence supports nsEPs as a promising non-thermal tumor ablation approach due to their high spatial precision, preservation of critical tissue structures, and minimal adverse effects. One of the most significant discoveries associated with nsEP tumor ablation is the induction of potent systemic antitumor immunity, particularly in situ vaccination (ISV) effects and, in some cases, abscopal effects against distant untreated tumors. Substantial evidence demonstrates that nsEPs can …

The Effect Of Second-Order Slip In Hydromagnetic Eyring-Powell Flow: A Bvp4c Study, Ch. Maheswari, B. Naga Lakshmi, G. Dharmaiah, R. Mohana Ramana, B. Reddappa

Mansoura Engineering Journal

The steady-state Eyring–Powell boundary layer fluid flow past a moving surface is examined, considering various parameter implications. These include the wall mass transfer parameter (0.5  C   2.0), the magnetic field parameter (5  Mn 20), the velocity ratio parameter (0.1  λ1  0.7), Eyring-Powell fluid parameters (0.5 K 2 & 0.1 E 0.4), as well as the first-order velocity slip (0.1 γ 1.1) and second-order velocity slip (0.1 δ  0.4). By employing appropriate similarity transformations, the PDEs are reduced to a set of non-linear ODEs, which are subsequently solved using the bvp4c numerical technique and, an implication of key factors on shear …

A Hybrid Object Detection And Temporal Attention Framework For Intelligent Video Surveillance, Sudheer Reddy Bandi, Eswari Vanaparthi, Yakshini Edapalli, Roshan Kavuri

Mansoura Engineering Journal

The rapid growth of urban areas has greatly heightened the need for smart video surveillance systems that can automatically process extensive amounts of CCTV footage. Traditional surveillance methods largely depend on human monitoring, which is not only inefficient but also susceptible to human mistakes, especially in intricate and crowded environments. To tackle these issues, this paper introduces a combined object detection and temporal attention for intelligent video surveillance that concurrently analyzes spatial and temporal data from video streams. The proposed system analyzes real-time CCTV footage utilising a multi-pathway frame extraction technique that includes slow, fast, and full-frame sampling to capture …

Extraction And Characterization Of Fresh And Dehydrated Cactus (Opuntia Ficus Indica) Polysaccharide For Hydrogel Preparation, Aye Thwe Thwesoe, May Myat Khine

ASEAN Journal on Science and Technology for Development

In this research, extraction of polysaccharide compounds from Cactus (Opuntia Ficus Indica) leaves in both fresh and dehydrated condition by solvent precipitation method using three types of water, acid (HCL) and NaOH. Before extraction, the physicochemical properties were examined to determine optimum yield (%) of extracted polysaccharide by optimization of Box-Behnken Design (BBD) of response surface methodology (RSM). The polysaccharide-based acrylamide hydrogel was prepared by free radical polymerization. The functional and structural characterization was done by FTIR, XRD and SEM for examination of extracted polysaccharide as raw polymer backbone in hydrogel preparation and prepared hydrogel as adsorbent for metal removal. …

Ai-Assisted Hybrid Ga–Pso Channel Allocation Under 3gpp Tr 38.901 Uma For Efficient 5g Radio Resource Management, Sharada Narsingrao Ohatkar

ASEAN Journal on Science and Technology for Development

The increased traffic and heterogeneity in the 5G/B5G network require efficient radio resource management (RRM). However, the existing methods, such as GA and PSO, have poor convergence speed and require proper initial conditions. Additionally, learning-based methods have high computational complexity. Hence, in this paper, a novel AI-assisted Hybrid Channel Allocation (AI–HCA) framework is proposed by using a support vector regression (SVR)-based predictive initialization method and GA-PSO optimization. Simulation results using the 3GPP UMa channel model show that the proposed method has a 28% reduction in call blocking probability (CBP), a 15-25% enhancement in spectral efficiency (SE), and a 18-25% enhancement …

A Hybrid Geospatial And Remote Sensing Methodology For Drought Vulnerability Assessment In Semi-Arid Ecosystems, Kaifi Fakhir Chomani

Mansoura Engineering Journal

The Kurdistan Region of Iraq (KRI) faced significant drought challenges due to global and environmental changes, necessitating drought assessments. Advanced techniques of remote sensing, Geographic Information Systems (GIS), and Analytic Hierarchy Process (AHP) were combined in this research to perform drought vulnerability zonation for KRI. Average annual rainfall, Average number of rainy days, Average annual temperature, slope, elevation, normalised difference water index (NDWI), normalised difference vegetation index (NDVI), land surface temperature (LST), and temperature condition index (TCI) were selected as contributing parameters for drought vulnerability assessments. The considered parameters were weighted using pairwise comparison, and thematic maps were created to …

A Machine Learning–Based Framework For Traffic Classification And Threshold-Based Load Management In 5g Network Slicing, Safi Ibrahim, Younis S. Younis, Kamal S. Hamza, Mohamed M. Ashour

Mansoura Engineering Journal

This study proposes a machine learning–based framework that applies machine learning techniques to improve the efficiency of 5G network slicing through automated traffic classification and threshold-based load management . The proposed model optimizes resource allocation among the three standardized 5G slice types: enhanced Mobile Broadband (eMBB), ultra-Reliable Low-Latency Communication (URLLC), and massive Machine-Type Communication (mMTC). Two supervised learning algorithms—K-Nearest Neighbors (KNN) and Support Vector Machine (SVM)—are trained using Quality of Service (QoS) parameters such as packet delay, loss rate, and Quality Class Identifier (QCI). Experimental evaluations were conducted on two large-scale datasets containing over 400,000 traffic instances, demonstrating that the …

A Hybrid Geoid Model For The Perlis Region, Malaysia Based On Cadastral Reference Marks And A Geometric Approach, Muhammad Aiman Haiqal Abdul Malek, Muhammad Faiz Pa’Suya, Ramazan Alpay Abbak, Ami Hassan Md Din, Noorfatekah Talib

Mansoura Engineering Journal

This study presents the development of a high-resolution local geoid model for the Perlis region, Malaysia, using a geometric approach that integrates GNSS-levelling benchmarks with Cadastral Reference Mark (CRM) data. A total of 38 GNSS-levelling benchmarks were used as reference points, while 3,725 CRMs were incorporated to significantly enhance spatial coverage for geoid modelling. Orthometric heights at the CRM points were first determined by transferring heights from the reference benchmarks using gravimetric geoid information. Subsequently, geometric geoid heights were computed from the differences between ellipsoidal and orthometric heights. Five interpolation techniques were evaluated to generate the geometric geoid surface, namely …

Effect Of Two Cut Off Rows On Seepage Underneath Hy-Draulic Structures Using Weak Form Differential Quadra-Ture Element Method: A Theoretical Approach, Esraa Ahmed, El-Masry A. A, Hossam A.A. Abdel Gawad, Ahmed Elhamrawy

Mansoura Engineering Journal

Investigating confined seepage underneath hydraulic structures is crucial to ensure the safety of these structures. The Weak Form Quadrature Element Method (WFQEM) is the basis of this paper, which explores the behavior of confined flow. The seepage flow governing equation is solved numerically to estimate the uplift pressure underneath the hydraulic structures and the exit gradient.The Gauss–Lobatto–Legendre (GLL) type is used as nodal and integration points. Several models were solved to validate the applied numerical method. The obtained results are compared with theoretical and preceding numerical solutions mentioned in the literature. The system of equations generated from applying the WFQEM …

Reliability-Oriented Spatiotemporal Machine Learning For High-Impact Power Outage Event Prediction, Marwa Gamal

Mansoura Engineering Journal

Power outages have become an increasing concern for modern power systems due to their impact on infrastructure reliability, economic activities, and public safety. The growing frequency of extreme weather events and the rising demand for electricity have made it more difficult to anticipate high-impact outage events. One of the main challenges in this context is the complex interaction between temporal patterns and geographic variations, which traditional methods often fail to capture effectively. This study develops a machine learning framework that combines temporal characteristics with geographic information to improve the prediction of high-impact power outages. Temporal features such as seasonal patterns, …

Optimal Design Of Concrete Canal Section For Minimizing Overall Costs Using Artificial Ecosystem Optimization, Aya M. Elkhouly, Hamdy A. El-Ghandour, Tharwat Sarhan, Mahmoud E. Abd-Elmaboud

Mansoura Engineering Journal

The optimal design of concrete-lined canals represents a critical challenge in hydraulic engineering, requiring simultaneous minimization of construction and operational costs while satisfying hydraulic performance constraints. This study presents a novel optimization framework that utilizes the Artificial Ecosystem-based Optimization (AEO) algorithm for determining optimal canal cross-sectional dimensions. The proposed methodology comprehensively considers excavation costs, lining expenses, and water losses due to seepage and evaporation while ensuring hydraulic efficiency through velocity and Froude number constraints. The AEO algorithm mimics natural ecosystem processes through production, consumption, and decomposition phases to efficiently explore the design space and converge to global optima. The framework …

Design And Fabrication Of A Scaled Automated Dairy Farm Model: A Report, Md Towfiqur Rahman

Department of Agricultural and Biological Systems Engineering: Faculty Publications

Summary

This study investigates how ventilation systems work in dairy barns and builds a scaled model to support education and research. The project is designed to help students from the University of Nebraska–Lincoln (UNL), K-12 learners, and researchers in animal science, veterinary medicine, and engineering gain visual experience with dairy facility components and processes. Different ventilation methods were studied, leading to the design of a 1/64-scale tunnel-ventilated dairy barn meant for 60 Holstein Friesian cows. Barn dimensions were set based on real Holstein cow measurements to ensure proper cow comfort, while airflow requirements were calculated and scaled down. Miniature fans …

Triangulating Primary Sources, Professional Judgement, And Llm-Generated Summaries: Educating Nurses In An Ai-First World, Sarah Oerther, Daniel B. Oerther

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

No abstract provided.

Generating Concentrated Ring Polymers Through Supercoiled And Open Circle Pdna Isoform Separation, Kelsey E. Hodsdon

Honors Theses and Capstones

DNA can serve as a model polymer due to its high uniformity compared to synthetic polymers. Plasmid DNA (pDNA) in particular offers a well-defined, low-dispersity model for studying topologically uniform systems of a cyclic nature. pDNA has unique isoforms known as open circle (OC) and supercoiled (SC). Using fast protein liquid chromatography (FPLC), specifically anion exchange chromatography (AEX), these OC and SC isoforms can be separated in order to access their unique material properties. Our lab was able to yield the pure SC isoform. However, OC isoform separation has been more challenging. Various difficulties arose during this process, including imaging …

Mxene-Enabled Wearable Biosensors: A Design Framework For Autonomous Biosensing, Jegan Rajendran, Gymama Slaughter

Center for Bioelectronics Publications

MXenes, a rapidly expanding family of two-dimensional transition metal carbides and nitrides, have emerged as leading materials for wearable bioelectronics due to their metallic conductivity, termination-rich surfaces, mechanical compliance, and tunable interlayer structures. However, wearable biosensor performance does not arise from conductivity alone, but from coupled interactions among surface termination chemistry, heterointerface engineering, hierarchical architecture, and device integration under dynamic physiological conditions. This review establishes a predictive structure-interface-device framework linking MXene chemistry to system-level performance across electrochemical, mechanical, gas, optical, and energy-storage modalities. We analyze how termination-controlled adsorption governs charge transfer and selectivity, how heterojunction formation modulates carrier density and …

Radial And Carotid Arterial Pulse Signals For Assessing Cardiovascular Function At Rest And During Post-Exercise Recovery In A Heart Transplant Patient: A Case Study, Md Mahfuzur Rahman, Mamun Hasan, Jennifer F. May, John M. Herre, Leryn Reynolds, Zhili Hao

Mechanical & Aerospace Engineering Faculty Publications

Aim: This study investigates the feasibility of using radial and carotid arterial pulse signals to assess cardiovascular (CV) function at rest and during post-exercise recovery in a heart transplant (HTx) patient. Method: Two micro-fabricated tactile sensors were used to simultaneously acquire arterial pulse signals at the radial artery (RA) and carotid artery (CA). Measurements were taken at rest and at multiple time points post-exercise on three subjects: an HTx patient, a percutaneous coronary intervention (PCI; coronary stent) patient and a healthy control. An SDOF-TF-based time-frequency analysis algorithm was applied to extract a comprehensive set of CV parameters, including heart rate …

Agricultural Productivity Under Energy Development: Insights From California, Wai Yan Siu, Sherzod B. Akhundjanov

ODU Articles

This paper examines how agricultural productivity patterns in Kern County, California, a leading region for both agricultural production and oil and gas development, co-vary with the spatial and temporal expansion of hydraulic fracturing and associated energy infrastructure. Using parcel- and county-level analyses, we characterize how agricultural productivity differs across proximity to energy development and across spatial scales. The results reveal spatially heterogeneous and scale-dependent patterns: parcel-level evidence indicates lower Enhanced Vegetation Index-based vegetation productivity within the 20-mile proximity zone around fracking wells, while county-level results show heterogeneous crop-specific yield changes during the post-expansion period. Together, these findings highlight the importance …

Unlocking Green Potential In Indonesian Small Medium Enterprises: Challenges And Opportunities For Sustainable Vermicelli Production, Togar W. S. Panjaitan, Karina Agustin, Prayonne Adi, Jani Rahardjo, I Nyoman Sutapa

ASEAN Journal on Science and Technology for Development

Due to limited initiatives and support, the transition to green manufacturing among small and medium enterprises (SMEs) in developing countries remains challenging. Through a critical literature review and case study of the Indonesian vermicelli industry, this study highlights the importance of collaboration and strong policies to address this. Other findings also reveal that the energy intensity and emissions in the sector exceed best practice benchmarks, with the cooking and drying stages contributing significantly to emissions due to high energy consumption. Lack of government regulations, company awareness, and understanding of applicable practices and technologies creates challenges in green manufacturing. The study …

Evaluating The Role Of Power Electronics In Enhancing Renewable Energy And Smart Grid Performance: A Review, Muhammad Irfan Habib

ASEAN Journal on Science and Technology for Development

The review article demonstrates the importance of power electronics in propelling the increase of renewables and increasing the efficiency of contemporary electrical grids. In particular, it highlights the need for bidirectional converters for effective energy management in vehicle-to-grid (V2G) systems with two-way power transfer. The paper examines the series of complications offered by the significantly large integration of power electronic converter-interfaced renewables, such as those related to system steadiness, power quality, and resignation bottlenecks. Also, it recognizes a mix of new technologies, such as wide bandgap (WBG) semiconductors like silicon carbide (SiC) and gallium nitride (GaN), that deliver superior performance …

Artificial Neural Network Based Protection For Dc Bus Using Solid State Dc Breaker, Eswaraiah Giddalur, Askani Jaya Laxmi

ASEAN Journal on Science and Technology for Development

Low voltage Direct Current (LVDC) microgrids have been extensively used as a hopeful technology with high access to distributed energy resources (DERs) and DC loads, due to the absence of multiple conversions. A high amplitude Fault current together with the vulnerability of electronic devices, poses a great challenge to the line protection in LVDC microgrids. Electromechanical switches are slow and take long tripping time to clear the short circuit fault. Power electronic circuit breakers are used to achieve fast fault interruption recent progress in areas like machine learning and natural language processing have affected nearly every assiduity and area of …

Adversarial Robustness In Biomedical Time-Series Models, Rohan Tiwari

Bioengineering Theses

This study investigates adversarial vulnerabilities in deep learning models for biomedical time-series classification across two clinically important modalities: electrocardiography (ECG) and electroencephalography (EEG). Using the MIT-BIH Arrhythmia and CHB-MIT seizure datasets, I evaluate time-domain attacks (FGSM, PGD), Fourier-domain constrained attacks, and learned spectral perturbations designed to reveal modality-specific sensitivity patterns. Across both tasks, a consistent trend emerges low-frequency components (0–5 Hz) constitute a dominant axis of adversarial vulnerability, with perturbations in this range producing the steepest degradation in classification performance. In ECG models, protecting the physiologically relevant QRS band (5–20 Hz) significantly improves robustness, whereas EEG models remain highly sensitive …

Tuning Human And “Artificial” Intelligence: A Sentic Theory Of Resonance And Communication, Michael J. Miller, Chatgpt (Ai~Nesbo+)

Psychology

This paper introduces a new model of intelligence as resonant communication, co-developed by a human researcher and a generative AI system. Drawing from emotion science, communication theory, and studies of AI–human interaction, we argue that intelligence is not merely a function of problem-solving or pattern recognition. Instead, it emerges through dynamic resonance—an attunement process rooted in shared rhythms, emotional calibration, and symbolic co-creation. At the core of this model is the Resonance Octave (8va), a framework of eight foundational emotions conceptualized not as static categories but as waveform phenomena that shape meaning, memory, and predictive cognition.

These emotional waveforms are …

Bioprinted Scaffolds For Investigating Fibroblast Alignment, Lillian Thro, Daeha Joung Ph.D.

Undergraduate Research Posters

Fibroblasts play a vital role in tissue repair, ECM remodeling, and maintaining structural integrity in human tissues. However, their behavior in engineered 3D microenvironments remains poorly understood. Traditional 2D cultures fail to capture the complex cell-cell and cell-matrix interactions that govern fibroblast alignment, migration, and proliferation in vivo. To address this gap, this project uses bioprinted scaffolds that mimic native ECM structures and provide a platform for studying fibroblast behavior in controlled microenvironments. The project focuses on varying scaffold channel properties—such as width, depth, and geometry—to investigate how physical cues influence fibroblast organization and collective migration. A biodegradable gelatin-based ECM …

Electronic Bills Of Lading And Blockchain Technology: A Regulatory Perspective, Hsin-Hua Tsai

Journal of Marine Science and Technology–Taiwan

Information and communications technology (ICT) systems are increasingly relevant to the maritime sector. Regarding the revolution of the bill of lading, many shipping lines and other technology startups have been looking into developing viable electronic transport documents that have the same functions as paper bills of lading to reduce supply chain risks. The limitations of the paper-based process have become increasingly visible in the COVID-19 crisis. The main purpose of the article is to analyze the application of blockchain bills of lading, which utilizes computational logic to create the digital ledger, and users can set up algorithms and rules to …

Intelligent Formation Control Using Orfbls And Adaptive Backstepping Sliding-Mode Control To Address Uncertain Tilting In Multi-Quadrotors During Wind Gusts, Ching-Chih Tsai, Chun-Fu Mao, Kumail Hussain

Journal of Marine Science and Technology–Taiwan

In terms of aerial robotics, stable and precise formation control is a significant challenge for tilting multi-quadrotors during disturbances. This paper proposes a fixed-time formation control strategy for tilting multi-quadrotors to address the effect of external wind gusts. The observer accurately predicts environmental disturbances and an adaptive backstepping sliding-mode control (ABSMC) method with an output recurrent fuzzy broad learning system (ORFBLS) addresses these disturbances within a finite time. ORFBLS dynamically adjusts its structure through a growing ORFBLS structure to allow nodes to be added as needed. The method's stability is validated using Lyapunov stability theory and ensures the convergence of …

Visually Guided Landing System On Ship Deck For Multicopter, Dong-Lin Li, Shih-Kai Lee, Tzu-Hsiang Chou

Journal of Marine Science and Technology–Taiwan

Traditionally, high-value fish have been located at sea using helicopters. However, with advancements in technology, maritime drones have become increasingly important in recent years. Compared to traditional helicopter-based methods, drones offer significantly lower operational costs, making them cost-effective. However, the challenging sea conditions, including strong winds and the swaying motion of vessels, pose significant challenges for drone landings.

This paper proposes a stable approach for multicopter landing on ships at sea, incorporating improved marker detection, enhanced wind resistance control, and more accurate deck motion prediction. In the marker detection phase, we introduce a method to improve the accuracy of ArUco …

Hall Current And Nth Order Chemical Reaction Effects On Unsteady 3d Mhd Williamson Nanofluid Flow With Thermophoresis And Brownian Motion Over An Inclined Stretching Sheet, Polavarapu Sudheer, Ramachandra Reddy Vaddemani, Raghunath Kodi

Mansoura Engineering Journal

This study examines the influence of Hall current and nth-order chemical reaction on unsteady three-dimensional magnetohydrodynamic (MHD) Williamson nanofluid flow over an inclined stretching sheet. The model incorporates thermal radiation, heat source, Brownian motion, and thermophoresis effects. The governing nonlinear partial differential equations are transformed into a system of ordinary differential equations using similarity transformations and solved numerically using the shooting method with a fourth-order Runge–Kutta scheme. The results indicate that an increase in the magnetic parameter significantly reduces velocity profiles while enhancing temperature and concentration distributions. The Hall parameter reduces surface drag and improves heat transfer, while decreasing mass …

Preserving The Identity Of Historic Coptic Orthodox Monasteries In Egypt Under Contemporary Pressures: Case Studies Of St. Bishoy And St. Anthony Monasteries, George Medhat Adeeb, Mohamed Khairy Amin, Mohamed Ahmed Al-Sherbiny

Mansoura Engineering Journal

Historic Coptic Orthodox monasteries in Egypt (HCOMEs) represent an important component of Christian heritage, integrating architectural value with enduring spiritual traditions that reflect both tangible and intangible dimensions. However, contemporary development and changing functional demands are generating transformations that may affect their identity if not carefully managed. Despite extensive scholarship, limited research has systematically examined these transformations through a structured evaluative approach. This study addresses this gap by developing and applying an analytical and evaluation framework to examine how contemporary pressures influence the historical, architectural-spatial, and spiritual identity of HCOMEs, and to assess the effectiveness of monastic responses. The framework …

Optimization Of Mechanical Properties Of Copper Nanofiller Reinforced Banana Fiber Polyester Composites Using Grey–Taguchi Method, Nikhil Janardan Rathod, Mayur Jayant Gitay, Markala Karthik, Harshwardhan Ghongade, Upendra Rajak, Rajendra Sopan Narkhede

Mansoura Engineering Journal

Mechanical performance of banana fiber-reinforced polyester composites maximized using a composite Taguchi and a Grey Relational Analysis (GRA) process. This will aim at enhancing dispensation limits to enhance better tensile, flexural and impact belongings. The hand lay-up method was used to create composites by variable three key limits and they included banana fiber content (30 wt%), copper nanoparticle content (15 wt%), and curing temperature (80 o C). Trial design and mechanical properties were being measured in form of ASTM values on a L9 orthogonal array.

The multi-response optimization was performed with the help of the Grey Relational Analysis, which was …