Digital Commons Network^™

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 …

Establishment And Histopathological Characterization Of A Kyse-30 Subcutaneous Xenograft Model Of Esophageal Squamous Cell Carcinoma, Pavel A. Solopov, Alayna Enos, Mantas Silkunas, Giedre Silkuniene, Eleni Zivla, Andrei G. Pakhomov, Olga N. Pakhomova

Bioelectrics Publications

Background/Objectives: Esophageal squamous cell carcinoma (ESCC) is an aggressive malignancy with poor prognosis and limited treatment options, highlighting the need for reliable preclinical models for translational research. Although xenograft models are widely used in cancer biology, systematic characterization of subcutaneous ESCC models under defined implantation conditions remains limited. The objective of this study was to systematically compare implantation conditions and define histopathological and growth-related parameters that enable reproducible tumor establishment while maintaining a practical experimental window for therapeutic studies. Methods: We established and characterized a subcutaneous ESCC xenograft model using human ESCC cell line KYSE-30 implanted into immunodeficient J:NU mice. …

Construction Industry Preparedness For Generation Z And Millennials: Aligning Industry Characteristics With Workforce Job Preferences, Ameenullah Amiri, Dhaval R. Gajjar, Jason D. Lucas

The Professional Constructor

The construction industry in the United States suffers from workforce shortages, partly due to younger generations being hired more slowly than baby boomers retire. Generation Z’s (Gen Z) lack of interest in joining the construction industry, coupled with the retirement of older workers, has amplified the problem. This paper investigates existing literature to identify the work and career preferences of Gen Z and Millennials and determine where the industry may focus efforts to attract these two generations. Through a systematic literature review, this study identified overlaps and gaps between the current construction industry workforce’s perceptions of the industry and the …

Anonymized Survey Dataset On Road Safety Assessment During Construction Of Bus Rapid Transit (Brt) Corridors In Dar Es Salaam, Tanzania, Lorain Salufu

Open Data

This dataset contains anonymized survey responses collected for a study on road safety assessment during construction of the Dar es Salaam Bus Rapid Transit (BRT) Phase 3 corridor. The dataset includes responses from 400 participants, together with the survey. The data were collected to assess perceived safety conditions, adequacy of construction-phase safety measures, effectiveness of traffic diversions, and the effects of construction activities on road users and nearby communities. No personally identifiable information is included in the shared files.

Gradient-Based, Post-Optimality Sensitivity Analysis With Respect To Parameters Of State Equations, Gene Hou, Jonathan Degroff

Mechanical & Aerospace Engineering Faculty Publications

Design optimization is a computational tool that can enable a designer to investigate the effectiveness of a design concept in an organized format. However, this design process requires the design variables, constraints, and objective function to be properly defined and expressed in mathematical forms. Post-optimality analysis thus becomes a necessary step to investigate different variations in the problem formulation and parameters to ensure that optimization produces a stable and trustworthy outcome. One efficient way to achieve this aim is to compute the local derivative of the optimized objective function with respect to the optimization problem parameters, such as bounds on …

Uncertainty-Aware Estimation, Planning, And Control For Tracking Multiple Drifting Patches In Flow Fields, Daniel O. Akanji, Krishnanand N. Kaipa, Cong Wei

Mechanical & Aerospace Engineering Faculty Publications

In this study, we present a replay-based framework for uncertainty-aware persistent tracking of multiple advected surface patches using an autonomous marine vehicle operating in spatiotemporal-varying currents. The method combines three components: local flow estimation, covariance-aware patch-boundary propagation with intermittent boundary fusion, and mission-level scheduling over multiple patches. Each patch is represented by a polygonal boundary, whose vertices are propagated through the estimated flow field while carrying per-vertex covariance, thereby quantifying uncertainty growth during advection. A flow-aware gain-scheduled linear quadratic regulator (LQR) was designed to shape the desired surge speed to take advantage of favorable currents. When the vehicle services a …

Influence Of Motion Artifacts On Instantaneous Frequency Based Heart Rate Variability Of Arterial Pulse Signals Measured By A Tactile Sensor: An Analytical Study, Mamun Hasan, Zhili Hao

Mechanical & Aerospace Engineering Faculty Publications

Objective: Heart rate variability (HRV), quantified via the instantaneous frequency (IF) of arterial pulse signals, is a key indicator of cardiovascular (CV) regulation. This study presents a theoretical and experimental investigation of how motion artifacts (MA) influence IF-and thus HRVmeasured with a tactile sensor, emphasizing underlying mechanisms rather than population-level validation. Approach: Building on a previously developed single-degree-of-freedom (SDOF) model of the tissue-contact-sensor (TCS) stack between the sensor and the artery, MA is represented as low-frequency baseline drift and time-varying system parameters (TVSP) of the TCS stack. Analytical expressions quantify the effect of MA on the IF of each harmonic …

Mechanical-Medical Convergence In Heart Failure: Artificial Intelligence, Finite-Element Modeling, And 3d Printing For Diagnosis And Prognosis, Quazi Noor E. Sabrina, Quazi Md Zobaer Shah, Quazi Noor E. Sohela, Md Mahabub Hasan Mousum, Md. Moyeen Uddin Chisty, Quazi Md. Akbar Shah

Mechanical & Aerospace Engineering Faculty Publications

Heart failure remains a leading cause of global morbidity and mortality, yet routine clinical indices often miss the regional biomechanical disturbances that drive progression and shape treatment response. This State-of-the-Art review examines how finite-element (FE) modeling, additive manufacturing, and artificial intelligence (AI) are converging to improve the diagnosis, phenotyping, procedural planning, and prognostic assessment of heart failure (HF). Although these technologies have matured in structural heart disease and transcatheter intervention research, their greatest translational potential may lie in HF, where patient-specific ventricular remodeling, myocardial stress–strain heterogeneity, valve-ventricular coupling, and device-tissue interaction are incompletely captured by conventional clinical indices. We synthesize …

Code-Net++: An Attention-Guided Deep Learning Framework With Grad-Cam-Based Explainability For Covid-19 Detection Using Chest X-Ray Images, Fareesa Amina, Dr Krishnanaik Vankdoth

Mansoura Engineering Journal

Chest radiograph imaging has emerged as a practical and scalable diagnostic modality for respiratory diseases, including COVID-19. However, accurate discrimination of COVID-19 manifestations from other pulmonary abnormalities remains challenging because of low contrast, imaging noise, and overlapping radiographic patterns. This work presents CODE-NET++, an enhanced attention-guided deep learning framework with Grad-CAM-based explainability for reliable COVID-19 detection using chest X-ray images. The proposed framework integrates adaptive trilateral filtering for image enhancement, Reverse Edge Attention Network (RE-Net) for lesion-aware segmentation, and an Enhanced LinkNet architecture with dilated convolutions for multiscale feature extraction and classification. Grad-CAM-based explainable artificial intelligence visualization is incorporated to …

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 …

Radical-Based Oxidative Pretreatment Enhances Biofuel Production From Lignocellulosic Biomass Via Hydrothermal Liquefaction, João Vitor Dos Santos, Louis C. Bondurant, Patrick G. Hatcher

Chemistry & Biochemistry Faculty Publications

The sustainable production of biofuels from lignocellulosic biomass is a central goal in the transition to low-carbon energy systems. However, hydrothermal liquefaction (HTL), a promising thermochemical conversion pathway, is constrained by the high oxygen content and complex aromatic structure of lignin, which lowers bio-oil quality. Here, we used a model system of brown-rot-degraded white oak (Quercus alba) to test whether radical-based oxidative pretreatment could enhance HTL performance by converting lignin into more aliphatic intermediates. Oxidation was performed under simulated Fenton conditions using fixed Fe(II) (60 ppm) and two hydrogen peroxide concentrations (3 and 8 M), resulting in extensive lignin depolymerization …

Virtualized And Distributed Neighborhood Data Centers, Benjamin T. Niccum

Computer Science and Engineering Theses

This thesis evaluates whether PCIe-fabric-based resource pooling can support a decentralized neighborhood micro-data-center model under real implementation constraints. The work combines architecture design, prototype deployment, performance benchmarking, and security assessment. Results show strong prototype-scale feasibility with low-latency and high-throughput behavior, while also identifying deployment-blocking security gaps and operational maturity requirements. The thesis contributes an evidence-traceable path from concept validation to deployment-grade roadmap planning.

The Rise In Height And Curb Weight Of The Top-Selling Vehicles In The United States From 1991 - 2025: Implications For Engineering Design And Vulnerable Road Users, Samuel L. Steinman-Friedman

Civil Engineering Theses

Road fatalities are higher in the United States than in other high-income regions. In 2024, 39,254 people died on roads in the United States compared to 19,940 in the European Union. These two regions have comparable exposure metrics, such as population size, roadway network length, and fatalities per mile traveled. Light trucks dominate the U.S. market, whereas hatchbacks are prevalent in Europe. The trendline of the average height and curb weight of the top-selling vehicles in the United States has increased by 0.24 inches and 23.52 pounds per year since 1991. The average 2025 top-selling U.S. passenger vehicle is 7.5 …

Integrated Thermal, Energy, And Structural Performance Assessment Of A Novel In-Service Shallow Geothermal Bridge Deicing System, Alireza Fakhrabadi

Civil Engineering Dissertations

Understanding the performance of bridge deck deicing systems under winter weather conditions is important for improving transportation safety and reducing long-term deterioration of bridge infrastructure. Bridge decks are more vulnerable to icing than ground-supported pavements because they are exposed to ambient air, wind, and radiation from multiple directions, while they do not receive thermal support from the underlying soil. Conventional deicing methods, especially chloride-based salts, can reduce ice formation in the short term, but repeated application may accelerate reinforcement corrosion, concrete damage, and environmental concerns. Therefore, shallow geothermal energy has been considered as a sustainable alternative for bridge deck deicing …

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 …

Autonomous Coupler Alignment Using Position-Based Visual Servoing In A Ros~2 Framework, Nickolas Giffen

Graduate Research Theses & Dissertations

As robotic arms are becoming increasingly common alongside humans as collaborative robots, their high precision in motion enables tasks to be performed at significantly higher speeds with reduced disruption in the environment. The Fermi National Accelerator Laboratory is exploring this application by incorporating a UR16e from Universal Robots in a cleanroom setting during assembly of couplers to superconducting radio frequency cavities as part of the PIP-II project. The goal of the robotic assembly process is to precisely position the UR16e robot so that the coupler flange, mounted on the robot’s end-effector, is accurately aligned with and pressed against the cavity …

Deterministic Black-Box Context-Free Grammar Inference: Scaling From Small To Big Languages, Mohammad Rifat Arefin

Computer Science and Engineering Dissertations

Context-free grammars are essential for a number of software engineering tasks like program understanding, debugging, and grammar-based testing. However, formal language descriptions (i.e. grammars) are often unavailable, outdated, or inaccessible because parsers are closed-source or cannot be instrumented. Black-box grammar inference addresses this gap using only valid sample programs and parser acceptance decisions. The problem is challenging because finite samples rarely exercise all language features or their combinations, while the inference process cannot inspect the parser’s internal representation of syntax. This dissertation develops deterministic techniques for black-box context-free grammar inference. The first tool, TreeVada introduces the structural assumption that balanced …

Effects Of Metals On Persulfate Activation For The Decomposition Of Pfas, Malu Deav Devadasan

Civil Engineering Dissertations

Per- and polyfluoroalkyl substances (PFAS) are persistent environmental contaminants widely used in industrial and consumer products due to their unique physicochemical properties. Their resistance to degradation, potential for bioaccumulation, and associated adverse health effects have prompted increasing regulatory attention, including the establishment of drinking water standards for six PFAS compounds by the U.S. Environmental Protection Agency in 2024.

Current PFAS treatment technologies are often energy-intensive and costly or generate secondary waste streams requiring further management. Meanwhile, this research investigated transition metal-catalyzed advanced oxidation processes for PFAS decomposition in water under ambient conditions. Previous studies demonstrated effective degradation of perfluorocarboxylic acids …

Gaussian Process Regression–Based Uncertainty Quantification For Unmanned Aircraft System Traffic Management And Advanced Air Mobility Applications, Aakarshan Khanal

Mechanical and Aerospace Engineering Dissertations

Uncertainty quantification has gained significant attention in recent years as a research area in dynamical systems. Mathematical representations of the physical system, combined with an understanding of model uncertainties, enable the propagation of uncertainty in temporal space, which allows us to make informed decisions. However, what if the true dynamics of the system is unknown or too complex to define explicitly? In such cases, the system’s behavior can instead be inferred or learned from observed input–output data rather than from an analytical or physics-based model. To this end, this dissertation focuses on developing a data-driven framework for nonparametric dynamics modeling, …

Automated Object Detection And Change Quantification In Underground Mines Using Lidar Point Clouds And 360◦ Image Processing, Ana Fabiola Patricia Tejada Peralta, Roya Bakzadeh, Sina Siahidouzazar, Pedram Roghanchi

Mining Engineering Faculty Publications

Underground mining environments pose significant challenges for automated hazard detection due to low illumination, restricted visibility, and the absence of Global Navigation Satellite System (GNSS) coverage. These factors limit situational awareness and delay inspection efforts, particularly after disruptive events when rapid assessment is essential for safety. This study addresses this problem by developing a dual-pipeline framework for 2D–3D detection that uses 360° imaging and LiDAR-based machine learning to identify people, vehicles, and positional changes in underground settings without requiring personnel to re-enter hazardous areas. The objective was to create a system capable of recognizing objects and monitoring spatial changes under …

Heat-Related Injuries And Fatalities In Roofing: Osha Investigations From 2003-2024, Kenneth S. Sands Ii, Benjamin Marshall

The Professional Constructor

This study examines 52 heat-related roofing incidents recorded by the Occupational Safety and Health Administration (OSHA) between 2003-2024 to describe patterns in outcomes and identify trade-specific prevention opportunities. Researchers built a structured dataset from OSHA investigation summaries and analysed frequencies of the incidents and their associations with month, time of day, project type, end use, and age to complement a thematic review of narrative abstracts. Fifty-eight percent of cases were fatalities, with the remainder split between hospitalized and non-hospitalized injuries; these statistics underscore the consequences of heat events that trigger OSHA reporting. There was a clear relationship between number of …

Raw Data For The Manuscript "Silicon-Stabilized Three-Dimensional Covalent Networks In High Entropy Diborides", Michael Yeung, Reza Mohammadi

Chemistry Department Faculty Scholarship

Abstract for data:

Raw data for the journal publication, Silicon-stabilized three-dimensional covalent networks in high entropy diborides. ReadMe file provided.

Abstract for Journal publication: 

High entropy ceramics offer a pathway to stabilize unconventional chemistries beyond traditional alloying rules. We report the incorporation of silicon into an AlB₂-type high entropy diboride, Cr_0.2Nb_0.2Si_0.2Ta_0.2Ti_0.2B₂, despite silicon violating classical Hume-Rothery rules for alloying. Arc melting produced a phase-pure, chemically homogeneous structure, as confirmed by powder X-ray diffraction (pXRD) and scanning electron microscopy with energy dispersive X-ray spectroscopy (SEM–EDS). Silicon occupies …

Ev Charging And V2g Operation For Distribution System Vpp Including Model Predictive Control, Rosemary E. Alden, Simone Silvestri, Malcolm D. Mcculloch, Dan M. Ionel

Electrical and Computer Engineering Faculty Publications

Future smart grid virtual power plants (VPPs) are considered for development based on industry communication standards for electric vehicle (EV) chargers such as Open Charge Point Protocol (OCPP), IEC 15118, and IEC 61851. To support research and development of computationally intelligent controls for distributed EV batteries, a python-based API OpenDSS VPP framework is utilized with thousands of experimental smart meter profiles, the IEEE 123 node test feeder, and hundreds of national survey-based EV modules for conventional and optimal charging and vehicle-to-grid (V2G) control development to mitigate any voltage violations and reduce peak load. A methodology is proposed for model-predictive control …

Explainable Ai-Driven Predictive Maintenance Curriculum For Smart Manufacturing, Abdullah Al Mamun, Murat Kuzlu, Katherine Smith, Vukica Jovanovic, Dalya Ismael, Adel El-Shahat, Angela Sicaja, Md. Hedayetul Islam Chy

Engineering Technology Faculty Publications

Nowadays, Industry 4.0 has transformed manufacturing industries into a data-rich system driven by IoT, automation, and Artificial Intelligence (AI). Within this context, Predictive Maintenance (PdM) provides a proactive strategy that leverages heterogeneous sensor data such as vibration, acoustic, electrical, and visual signals along with historical performance and advanced analytics to forecast equipment failures before they occur. Usually, AI-driven PdM (AI-PdM) enhances this capability by integrating AI-based sensor analytics to automate fault prediction and optimize system reliability. However, traditional AI-PdM often functions as a “black box,” providing limited interpretability of its decision-making process and posing challenges for trust, validation, and human …

Improving Medical Diagnostics With Vision-Language Models: Convex Hull-Based Uncertainty Analysis, Ferhat Ozgur Catak, Murat Kuzlu, Taylor Patrick, Michel Audette

Engineering Technology Faculty Publications

In recent years, vision-language models (VLMs) have been applied to various fields, including healthcare, education, finance, and manufacturing, with remarkable performance. However, concerns remain regarding VLMs' consistency and uncertainty, particularly in critical applications such as healthcare, which demand a high level of trust and reliability. This paper proposes a novel approach to evaluate uncertainty in VLMs' responses using a convex hull approach on a healthcare application for visual question answering (VQA). For any VLM, temperature refers to a sampling parameter used in probabilistic generation, which controls the randomness of the model's output. The LLM-CXR model is selected as the medical …

A Mold Mating Surface Temperature Monitoring System For Injection Molding Using Infrared Thermography And Mahalanobis Distance, Yoshio Fukushima, Makoto Fukushima, Sho Shibuya, Keigo Kudo, Yuta Abe

ASEAN Journal on Science and Technology for Development

In plastic injection molding, minimizing defects is crucial for sustainable and stable manufacturing because resin behavior and molding conditions fluctuate due to variations in material lots, seasonal shifts, and factory environmental factors such as temperature and humidity. Among various process parameters, mold temperature　- specifically the mold mating surface temperature immediately after part ejection-　 plays a critical role in mitigating these variations and maintaining consistent product quality. However, embedding conventional sensors into the mating surface is structurally difficult. While non-contact infrared thermography is an effective alternative, shiny metallic mold surfaces suffer from low emissivity, leading to inaccurate readings. Furthermore, high-end …

Perception Of Transportation Challenges And Their Influence On Mode Choice In A Small Us City: A Generalized Structural Equation Modeling Approach, Anindya Kishore Debnath, Suman Kumar Mitra

Civil Engineering Faculty Publications and Presentations

This study profiles individuals encountering transportation challenges by analyzing factors influencing their perceptions and how they affect mode choice decisions in Fort Smith, Arkansas. Using primary travel survey data, we estimated a multinomial logit (MNL) within a Generalized Structural Equation Model (GSEM) that controls for residential self-selection and car ownership endogeneity. We find that individuals from low-income households are more likely to perceive transportation challenges, particularly due to a lack of a car and inadequate public transport. Higher household car ownership generally diminishes perceived challenges, except regarding limited bike lanes. Weekend or late-shift workers are more likely to own cars …

A Comparative Review Of Roller Compacted And Conventional Concrete: Performance, Economics, And Environmental Sustainability, Masood Abu-Bakr, Hersh F Mahmood, Soran Abdrahman Ahmad

Mansoura Engineering Journal

Roller Compacted Concrete (RCC), distinguished by its zero-slump consistency and high density achieved through heavy roller compaction, has gained recognition as an effective alternative to conventional concrete in applications such as pavements, industrial flooring, and dam construction. This paper reviews the evolution, material composition, and common uses of RCC in comparison with Conventional Concrete (CC), emphasizing the advantages and limitations of each. Key performance aspects, including mechanical strength, durability, workability, construction efficiency, and maintenance demands, are examined. The findings indicate that RCC can reduce construction time by up to 25% and lower maintenance costs by approximately 30–40%. Additionally, life-cycle cost …

Pillpetz: A Smarter Way To Encourage Medication Adherence In Children, John H. Begley

CMC Senior Theses

Medication adherence is usually framed as a problem of patient behavior, but this thesis argues that it is equally a problem of design. Children who take daily medication face barriers that adults often do not: developing executive function, dependence on caregivers, shifting school and home routines, privacy concerns, and stigma around being perceived as different. The standard prescription bottle, by contrast, was designed primarily for dispensing efficiency, safety, and accidental ingestion prevention—not for sustained daily use by a developing child.

This thesis proposes PillPetz, a smart pill case and digital companion that uses routine, play, dose confirmation, and caregiver-connected support …

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 …